code stringlengths 114 1.05M | path stringlengths 3 312 | quality_prob float64 0.5 0.99 | learning_prob float64 0.2 1 | filename stringlengths 3 168 | kind stringclasses 1
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"""Image conversion between ROS and OpenCV formats."""
from __future__ import annotations
import re
import sys
from contextlib import suppress
from enum import IntEnum
from itertools import product
from typing import TYPE_CHECKING
import cv2 # type: ignore
import numpy
from rosbags.typesys.types import sensor_msgs__msg__CompressedImage as CompressedImage
if TYPE_CHECKING:
from typing import Any, Optional, Union
if sys.version_info < (3, 9):
Imagebytes = numpy.ndarray[Any, Any]
else:
from numpy.typing import NDArray
Imagebytes = NDArray[Any]
from rosbags.typesys.types import sensor_msgs__msg__Image as Image
ENC_RE = re.compile('(8U|8S|16U|16S|32S|32F|64F)(?:C([0-9]+))?')
DIGITS_RE = re.compile(r'^\d+')
class ImageError(Exception):
"""Unsupported Image Format."""
class ImageFormatError(ImageError):
"""Unsupported Image Format."""
class ImageConversionError(ImageError):
"""Unsupported Image Conversion."""
class Format(IntEnum):
"""Supported Image Formats."""
GENERIC = -1
GRAY = 0
RGB = 1
BGR = 2
RGBA = 3
BGRA = 4
YUV = 5
BAYER_RG = 6
BAYER_BG = 7
BAYER_GB = 8
BAYER_GR = 9
CONVERSIONS = {
key: getattr(cv2, f'COLOR_{n1}2{n2}{({"YUV": "_Y422"}).get(n1, "")}', None)
for key in product(*(2 * (list(Format)[1:],)))
if (n1 := key[0].name) == (n2 := key[1].name) or hasattr(cv2, f'COLOR_{n1}2{n2}')
}
DEPTHMAP = {
'8U': 'uint8',
'8S': 'int8',
'16U': 'uint16',
'16S': 'int16',
'32S': 'int32',
'32F': 'float32',
'64F': 'float64',
}
ENCODINGMAP = {
'mono8': (8, Format.GRAY, 'uint8', 1),
'bayer_rggb8': (8, Format.BAYER_BG, 'uint8', 1),
'bayer_bggr8': (8, Format.BAYER_RG, 'uint8', 1),
'bayer_gbrg8': (8, Format.BAYER_GR, 'uint8', 1),
'bayer_grbg8': (8, Format.BAYER_GB, 'uint8', 1),
'yuv422': (8, Format.YUV, 'uint8', 2),
'bgr8': (8, Format.BGR, 'uint8', 3),
'rgb8': (8, Format.RGB, 'uint8', 3),
'bgra8': (8, Format.BGRA, 'uint8', 4),
'rgba8': (8, Format.RGBA, 'uint8', 4),
'mono16': (16, Format.GRAY, 'uint16', 1),
'bayer_rggb16': (16, Format.BAYER_BG, 'uint16', 1),
'bayer_bggr16': (16, Format.BAYER_RG, 'uint16', 1),
'bayer_gbrg16': (16, Format.BAYER_GR, 'uint16', 1),
'bayer_grbg16': (16, Format.BAYER_GB, 'uint16', 1),
'bgr16': (16, Format.BGR, 'uint16', 3),
'rgb16': (16, Format.RGB, 'uint16', 3),
'bgra16': (16, Format.BGRA, 'uint16', 4),
'rgba16': (16, Format.RGBA, 'uint16', 4),
}
def to_cvtype(encoding: str) -> tuple[int, Format, str, int]:
"""Get typeinfo for encoding.
Args:
encoding: String representation of image encoding.
Returns:
Tuple describing OpenCV type.
Raises:
ImageFormatError: If encoding cannot be parsed.
"""
with suppress(KeyError):
return ENCODINGMAP[encoding]
if mat := ENC_RE.fullmatch(encoding):
depth, nchan = mat.groups()
mat = DIGITS_RE.search(depth)
assert mat
return (int(mat.group()), Format.GENERIC, DEPTHMAP[depth], int(nchan or 1))
raise ImageFormatError(f'Format {encoding!r} is not supported')
def convert_color(src: Imagebytes, src_color_space: str, dst_color_space: str) -> Imagebytes:
"""Convert color space.
Args:
src: Source image.
src_color_space: Source color space.
dst_color_space: Destination color space.
Returns:
Image in destination color space, or source image if conversion is
a noop.
Raises:
ImageConversionError: If conversion is not supported.
"""
if src_color_space == dst_color_space:
return src
src_depth, src_fmt, src_typestr, src_nchan = to_cvtype(src_color_space)
dst_depth, dst_fmt, dst_typestr, dst_nchan = to_cvtype(dst_color_space)
try:
conversion = CONVERSIONS[(src_fmt, dst_fmt)]
except KeyError:
if Format.GENERIC not in (src_fmt, dst_fmt) or src_nchan != dst_nchan:
raise ImageConversionError(
f'Conversion {src_color_space!r} -> {dst_color_space!r} is not supported',
) from None
conversion = None
if conversion:
src = cv2.cvtColor(src, conversion) # pyright: ignore # pylint: disable=no-member
if src_typestr != dst_typestr:
if src_depth == 8 and dst_depth == 16:
return numpy.multiply( # type: ignore
src.astype(dst_typestr, copy=False),
65535. / 255.,
)
if src_depth == 16 and dst_depth == 8:
return numpy.multiply( # type: ignore
src,
255. / 65535.,
).astype(dst_typestr, copy=False)
return src.astype(dst_typestr, copy=False)
return src
def image_to_cvimage(msg: Image, color_space: Optional[str] = None) -> Imagebytes:
"""Convert sensor_msg/msg/Image to OpenCV image.
Args:
msg: Image message.
color_space: Color space of output image.
Returns:
OpenCV image.
"""
_, _, typestr, nchan = to_cvtype(msg.encoding)
shape = (msg.height, msg.width) if nchan == 1 else (msg.height, msg.width, nchan)
dtype = numpy.dtype(typestr) # .newbyteorder('>' if msg.is_bigendian else '<')
img: Imagebytes = numpy.ndarray(shape=shape, dtype=dtype, buffer=msg.data)
if msg.is_bigendian != (sys.byteorder != 'little'):
img.byteswap(inplace=True)
if color_space:
return convert_color(img, msg.encoding, color_space)
return img
def compressed_image_to_cvimage(
msg: CompressedImage,
color_space: Optional[str] = None,
) -> Imagebytes:
"""Convert sensor_msg/msg/CompressedImage to OpenCV image.
Args:
msg: CompressedImage message.
color_space: Color space of output image.
Returns:
OpenCV image.
"""
img: Imagebytes = cv2.imdecode( # pyright: ignore # pylint: disable=no-member
numpy.frombuffer(msg.data, numpy.uint8),
cv2.IMREAD_ANYCOLOR, # pyright: ignore # pylint: disable=no-member
)
if color_space:
return convert_color(img, 'bgr8', color_space)
return img
def message_to_cvimage(
msg: Union[CompressedImage, Image],
color_space: Optional[str] = None,
) -> Imagebytes:
"""Convert ROS message to OpenCV image.
Args:
msg: CompressedImage or Image message.
color_space: Color space of output image.
Returns:
OpenCV image.
"""
if isinstance(msg, CompressedImage):
return compressed_image_to_cvimage(msg, color_space)
return image_to_cvimage(msg, color_space) | /rosbags-image-0.9.1.tar.gz/rosbags-image-0.9.1/src/rosbags/image/image.py | 0.816223 | 0.302076 | image.py | pypi |
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy of the
# License at http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed
# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
# CONDITIONS OF ANY KIND, either express or implied. See the License for the
# speROSCO_cific language governing permissions and limitations under the License.
import numpy as np
from ROSCO_toolbox import turbine as ROSCO_turbine
import matplotlib.pyplot as plt
import sys
# Some useful constants
deg2rad = np.deg2rad(1)
rad2deg = np.rad2deg(1)
rpm2RadSec = 2.0*(np.pi)/60.0
class Sim():
"""
Simple controller simulation interface for a wind turbine.
- Currently runs a 1DOF simple rotor model based on an OpenFAST model
Note: Due to the complex nature of the wind speed estimators implemented in ROSCO,
using them for simulations is known to cause problems for the simple simulator.
We suggesting using WE_Mode = 0 for the simulator
Methods:
--------
sim_ws_series
Parameters:
-----------
turbine: class
Turbine class containing wind turbine information from OpenFAST model
controller_int: class
Controller interface class to run compiled controller binary
"""
def __init__(self, turbine, controller_int):
"""
Setup the simulator
"""
self.turbine = turbine
self.controller_int = controller_int
def sim_ws_series(self,t_array,ws_array,rotor_rpm_init=10,init_pitch=0.0, make_plots=True):
'''
Simulate simplified turbine model using a complied controller (.dll or similar).
- currently a 1DOF rotor model
Parameters:
-----------
t_array: float
Array of time steps, (s)
ws_array: float
Array of wind speeds, (s)
rotor_rpm_init: float, optional
initial rotor speed, (rpm)
init_pitch: float, optional
initial blade pitch angle, (deg)
make_plots: bool, optional
True: generate plots, False: don't.
'''
print('Running simulation for %s wind turbine.' % self.turbine.TurbineName)
# Store turbine data for conveniente
dt = t_array[1] - t_array[0]
R = self.turbine.rotor_radius
GBRatio = self.turbine.Ng
# Declare output arrays
bld_pitch = np.ones_like(t_array) * init_pitch
rot_speed = np.ones_like(t_array) * rotor_rpm_init * rpm2RadSec # represent rot speed in rad / s
gen_speed = np.ones_like(t_array) * rotor_rpm_init * GBRatio * rpm2RadSec # represent gen speed in rad/s
aero_torque = np.ones_like(t_array) * 1000.0
gen_torque = np.ones_like(t_array) # * trq_cont(turbine_dict, gen_speed[0])
gen_power = np.ones_like(t_array) * 0.0
# Loop through time
for i, t in enumerate(t_array):
if i == 0:
continue # Skip the first run
ws = ws_array[i]
# Load current Cq data
tsr = rot_speed[i-1] * self.turbine.rotor_radius / ws
cq = self.turbine.Cq.interp_surface([bld_pitch[i-1]],tsr)
# Update the turbine state
# -- 1DOF model: rotor speed and generator speed (scaled by Ng)
aero_torque[i] = 0.5 * self.turbine.rho * (np.pi * R**2) * cq * R * ws**2
rot_speed[i] = rot_speed[i-1] + (dt/self.turbine.J)*(aero_torque[i] * self.turbine.GenEff/100 - self.turbine.Ng * gen_torque[i-1])
gen_speed[i] = rot_speed[i] * self.turbine.Ng
# Call the controller
gen_torque[i], bld_pitch[i] = self.controller_int.call_controller(t,dt,bld_pitch[i-1],gen_torque[i-1],gen_speed[i],self.turbine.GenEff/100,rot_speed[i],ws)
# Calculate the power
gen_power[i] = gen_speed[i] * gen_torque[i]
# Save these values
self.bld_pitch = bld_pitch
self.rot_speed = rot_speed
self.gen_speed = gen_speed
self.aero_torque = aero_torque
self.gen_torque = gen_torque
self.gen_power = gen_power
self.t_array = t_array
self.ws_array = ws_array
if make_plots:
fig, axarr = plt.subplots(4,1,sharex=True,figsize=(6,10))
ax = axarr[0]
ax.plot(self.t_array,self.ws_array)
ax.set_ylabel('Wind Speed (m/s)')
ax.grid()
ax = axarr[1]
ax.plot(self.t_array,self.rot_speed)
ax.set_ylabel('Rot Speed (rad/s)')
ax.grid()
ax = axarr[2]
ax.plot(self.t_array,self.gen_torque)
ax.set_ylabel('Gen Torque (N)')
ax.grid()
ax = axarr[3]
ax.plot(self.t_array,self.bld_pitch*rad2deg)
ax.set_ylabel('Bld Pitch (deg)')
ax.set_xlabel('Time (s)')
ax.grid() | /rosco-toolbox-2.3.0.tar.gz/rosco-toolbox-2.3.0/ROSCO_toolbox/sim.py | 0.832611 | 0.669974 | sim.py | pypi |
# Licensed under the Apache License, Version 2.0 (the "License"); you may not use
# this file except in compliance with the License. You may obtain a copy of the
# License at http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software distributed
# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
# CONDITIONS OF ANY KIND, either express or implied. See the License for the
# specific language governing permissions and limitations under the License.
import os
import numpy as np
import datetime
from scipy import interpolate
from numpy import gradient
import pickle
import matplotlib.pyplot as plt
import pandas as pd
from ROSCO_toolbox.utilities import load_from_txt
# Load OpenFAST readers
try:
import weis.aeroelasticse
use_weis = True
print('Using weis.aeroelasticse in ROSCO_toolbox...')
except:
use_weis = False
print('ofTools in ROSCO_toolbox...')
# Some useful constants
now = datetime.datetime.now()
pi = np.pi
deg2rad = np.deg2rad(1)
rad2deg = np.rad2deg(1)
rpm2RadSec = 2.0*(np.pi)/60.0
RadSec2rpm = 60/(2.0 * np.pi)
class Turbine():
"""
Class Turbine defines a turbine in terms of what is needed to
design the controller and to run the 'tiny' simulation.
Primary functions (at a high level):
- Reads an OpenFAST input deck
- Runs cc-blade rotor performance analysis
- Writes a text file containing Cp, Ct, and Cq tables
Methods:
-------
__str__
load
save
load_from_fast
load_from_ccblade
load_from_txt
generate_rotperf_fast
write_rotor_performance
Parameters:
-----------
turbine_params : dict
Dictionary containing known turbine paramaters that are not directly available from OpenFAST input files
"""
def __init__(self, turbine_params):
"""
Load turbine parameters from input dictionary
"""
print('-----------------------------------------------------------------------------')
print('Loading wind turbine data for NREL\'s ROSCO tuning and simulation processeses')
print('-----------------------------------------------------------------------------')
# ------ Turbine Parameters------
self.rotor_inertia = turbine_params['rotor_inertia']
self.rated_rotor_speed = turbine_params['rated_rotor_speed']
self.v_min = turbine_params['v_min']
self.v_rated = turbine_params['v_rated']
self.v_max = turbine_params['v_max']
self.max_pitch_rate = turbine_params['max_pitch_rate']
self.min_pitch_rate = -1 * self.max_pitch_rate
self.max_torque_rate = turbine_params['max_torque_rate']
self.rated_power = turbine_params['rated_power']
self.bld_edgewise_freq = turbine_params['bld_edgewise_freq']
if turbine_params['twr_freq']:
self.twr_freq = turbine_params['twr_freq']
else:
self.twr_freq = 0.0
if turbine_params['ptfm_freq']:
self.ptfm_freq = turbine_params['ptfm_freq']
else:
self.ptfm_freq = 0.0
if turbine_params['TSR_operational']:
self.TSR_operational = turbine_params['TSR_operational']
else:
self.TSR_operational = None
if turbine_params['bld_flapwise_freq']:
self.bld_flapwise_freq = turbine_params['bld_flapwise_freq']
else:
self.bld_flapwise_freq = 0.0
# Allow print out of class
def __str__(self):
'''
Print some data about the turbine.
'''
print('-------------- Turbine Info --------------')
print('Turbine Name: {}'.format(self.TurbineName))
print('Rated Power: {} [W]'.format(self.rated_power))
print('Total Inertia: {:.1f} [kg m^2]'.format(self.J))
print('Rotor Radius: {:.1f} [m]'.format(self.rotor_radius))
print('Rated Rotor Speed: {:.1f} [rad/s]'.format(self.rated_rotor_speed))
print('Max Cp: {:.2f}'.format(self.Cp.max))
print('------------------------------------------')
return ' '
# Save function
def save(self,filename):
'''
Save turbine to pickle
Parameters:
----------
filename : str
Name of file to save pickle
# '''
pickle.dump(self, open( filename, "wb" ) )
# Load function
@staticmethod
def load(filename):
'''
Load turbine from pickle - outdated, but might be okay!!
Parameters:
----------
filename : str
Name of pickle file
'''
turbine = pickle.load(open(filename,'rb'))
return turbine
# Load data from fast input deck
def load_from_fast(self, FAST_InputFile,FAST_directory, FAST_ver='OpenFAST',dev_branch=True,rot_source=None, txt_filename=None):
"""
Load the parameter files directly from a FAST input deck
Parameters:
-----------
Fast_InputFile: str
Primary fast model input file (*.fst)
FAST_directory: str
Directory for primary fast model input file
FAST_ver: string, optional
fast version, usually OpenFAST
dev_branch: bool, optional
dev_branch input to InputReader_OpenFAST, probably True
rot_source: str, optional
desired source for rotor to get Cp, Ct, Cq tables. Default is to run cc-blade.
options: cc-blade - run cc-blade
txt - from *.txt file
txt_filename: str, optional
filename for *.txt, only used if rot_source='txt'
"""
if use_weis:
from weis.aeroelasticse.FAST_reader import InputReader_OpenFAST
else:
from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST
print('Loading FAST model: %s ' % FAST_InputFile)
self.TurbineName = FAST_InputFile.strip('.fst')
fast = self.fast = InputReader_OpenFAST(FAST_ver=FAST_ver,dev_branch=dev_branch)
fast.FAST_InputFile = FAST_InputFile
fast.FAST_directory = FAST_directory
fast.execute()
if txt_filename:
self.rotor_performance_filename = txt_filename
else:
self.rotor_performance_filename = 'Cp_Ct_Cq.txt'
# Grab general turbine parameters
self.TipRad = fast.fst_vt['ElastoDyn']['TipRad']
self.Rhub = fast.fst_vt['ElastoDyn']['HubRad']
self.hubHt = fast.fst_vt['ElastoDyn']['TowerHt'] + fast.fst_vt['ElastoDyn']['Twr2Shft']
self.NumBl = fast.fst_vt['ElastoDyn']['NumBl']
self.TowerHt = fast.fst_vt['ElastoDyn']['TowerHt']
self.shearExp = 0.2 #HARD CODED FOR NOW
self.rho = fast.fst_vt['AeroDyn15']['AirDens']
self.mu = fast.fst_vt['AeroDyn15']['KinVisc']
self.Ng = fast.fst_vt['ElastoDyn']['GBRatio']
self.GenEff = fast.fst_vt['ServoDyn']['GenEff']
self.GBoxEff = fast.fst_vt['ElastoDyn']['GBoxEff']
self.DTTorSpr = fast.fst_vt['ElastoDyn']['DTTorSpr']
self.generator_inertia = fast.fst_vt['ElastoDyn']['GenIner']
self.tilt = fast.fst_vt['ElastoDyn']['ShftTilt']
try:
self.precone = fast.fst_vt['ElastoDyn']['PreCone1'] # May need to change to PreCone(1) depending on OpenFAST files
except:
self.precone = fast.fst_vt['ElastoDyn']['PreCone(1)']
self.yaw = 0.0
self.J = self.rotor_inertia + self.generator_inertia * self.Ng**2
self.rated_torque = self.rated_power/(self.GenEff/100*self.rated_rotor_speed*self.Ng)
self.max_torque = self.rated_torque * 1.1
self.rotor_radius = self.TipRad
# self.omega_dt = np.sqrt(self.DTTorSpr/self.J)
# Load blade information
self.load_blade_info()
# Load Cp, Ct, Cq tables
if rot_source == 'cc-blade': # Use cc-blade
self.load_from_ccblade()
elif rot_source == 'txt': # Use specified text file
self.pitch_initial_rad, self.TSR_initial, self.Cp_table, self.Ct_table, self.Cq_table = load_from_txt(
txt_filename)
else: # Use text file from DISCON.in
if os.path.exists(os.path.join(FAST_directory, fast.fst_vt['ServoDyn']['DLL_InFile'])):
try:
self.pitch_initial_rad = fast.fst_vt['DISCON_in']['Cp_pitch_initial_rad']
self.TSR_initial = fast.fst_vt['DISCON_in']['Cp_TSR_initial']
self.Cp_table = fast.fst_vt['DISCON_in']['Cp_table']
self.Ct_table = fast.fst_vt['DISCON_in']['Ct_table']
self.Cq_table = fast.fst_vt['DISCON_in']['Cq_table']
except: # Load from cc-blade
print('No rotor performance data source available, running CC-Blade.')
self.load_from_ccblade()
# Parse rotor performance data
self.Cp = RotorPerformance(self.Cp_table,self.pitch_initial_rad,self.TSR_initial)
self.Ct = RotorPerformance(self.Ct_table,self.pitch_initial_rad,self.TSR_initial)
self.Cq = RotorPerformance(self.Cq_table,self.pitch_initial_rad,self.TSR_initial)
# Define operational TSR
if not self.TSR_operational:
self.TSR_operational = self.Cp.TSR_opt
# Pull out some floating-related data
wave_tp = fast.fst_vt['HydroDyn']['WaveTp']
try:
self.wave_peak_period = 1/wave_tp # Will work if HydroDyn exists and a peak period is defined...
except:
self.wave_peak_period = 0.0 # Set as 0.0 when HydroDyn doesn't exist (fixed bottom)
# Load rotor performance data from CCBlade
def load_from_ccblade(self):
'''
Loads rotor performance information by running cc-blade aerodynamic analysis. Designed to work with Aerodyn15 blade input files.
Parameters:
-----------
fast: dict
Dictionary containing fast model details - defined using from InputReader_OpenFAST (distributed as a part of AeroelasticSE)
'''
from wisdem.ccblade.ccblade import CCAirfoil, CCBlade
print('Loading rotor performance data from CC-Blade.')
# Load blade information if it isn't already
try:
isinstance(self.cc_rotor,object)
except(AttributeError):
self.load_blade_info()
# Generate the look-up tables, mesh the grid and flatten the arrays for cc_rotor aerodynamic analysis
TSR_initial = np.arange(3, 15,0.5)
pitch_initial = np.arange(-1,25,0.5)
pitch_initial_rad = pitch_initial * deg2rad
ws_array = np.ones_like(TSR_initial) * self.v_rated # evaluate at rated wind speed
omega_array = (TSR_initial * ws_array / self.rotor_radius) * RadSec2rpm
ws_mesh, pitch_mesh = np.meshgrid(ws_array, pitch_initial)
ws_flat = ws_mesh.flatten()
pitch_flat = pitch_mesh.flatten()
omega_mesh, _ = np.meshgrid(omega_array, pitch_initial)
omega_flat = omega_mesh.flatten()
# tsr_flat = (omega_flat * rpm2RadSec * self.rotor_radius) / ws_flat
# Get values from cc-blade
print('Running CCBlade aerodynamic analysis, this may take a minute...')
try: # wisde/master as of Nov 9, 2020
_, _, _, _, CP, CT, CQ, CM = self.cc_rotor.evaluate(ws_flat, omega_flat, pitch_flat, coefficients=True)
except(ValueError): # wisdem/dev as of Nov 9, 2020
outputs, derivs = self.cc_rotor.evaluate(ws_flat, omega_flat, pitch_flat, coefficients=True)
CP = outputs['CP']
CT = outputs['CT']
CQ = outputs['CQ']
print('CCBlade aerodynamic analysis run successfully.')
# Reshape Cp, Ct and Cq
Cp = np.transpose(np.reshape(CP, (len(pitch_initial), len(TSR_initial))))
Ct = np.transpose(np.reshape(CT, (len(pitch_initial), len(TSR_initial))))
Cq = np.transpose(np.reshape(CQ, (len(pitch_initial), len(TSR_initial))))
# Store necessary metrics for analysis
self.pitch_initial_rad = pitch_initial_rad
self.TSR_initial = TSR_initial
self.Cp_table = Cp
self.Ct_table = Ct
self.Cq_table = Cq
def generate_rotperf_fast(self, openfast_path, FAST_runDirectory=None, run_BeamDyn=False,
debug_level=1, run_type='multi'):
'''
Use openfast to generate Cp surface data. Will be slow, especially if using BeamDyn,
but may be necessary if cc-blade is not sufficient.
Parameters:
-----------
openfast_path: str
path to openfast
FAST_runDirectory: str
directory to run openfast simulations in
run_BeamDyn: bool
Flag to run beamdyn - does not exist yet
debug_level: float
0 - no outputs, 1 - simple outputs, 2 - all outputs
run_type: str
'serial' - run in serial, 'multi' - run using python multiprocessing tools,
'mpi' - run using mpi tools
'''
if use_weis:
from weis.aeroelasticse import runFAST_pywrapper, CaseGen_General
from weis.aeroelasticse.Util import FileTools
else:
from ROSCO_toolbox.ofTools.case_gen import runFAST_pywrapper, CaseGen_General
from ROSCO_toolbox.ofTools.util import FileTools
# Load pCrunch tools
from pCrunch import pdTools, Processing
# setup values for surface
v0 = self.v_rated + 2
TSR_initial = np.arange(3, 15,1)
pitch_initial = np.arange(-1,25,1)
rotspeed_initial = TSR_initial*v0/self.rotor_radius * RadSec2rpm # rpms
# Specify Case Inputs
case_inputs = {}
# ------- Setup OpenFAST inputs --------
case_inputs[('Fst','TMax')] = {'vals': [330], 'group': 0}
case_inputs[('Fst','Compinflow')] = {'vals': [1], 'group': 0}
case_inputs[('Fst','CompAero')] = {'vals': [2], 'group': 0}
case_inputs[('Fst','CompServo')] = {'vals': [1], 'group': 0}
case_inputs[('Fst','CompHydro')] = {'vals': [0], 'group': 0}
if run_BeamDyn:
case_inputs[('Fst','CompElast')] = {'vals': [2], 'group': 0}
else:
case_inputs[('Fst','CompElast')] = {'vals': [1], 'group': 0}
case_inputs[('Fst', 'OutFileFmt')] = {'vals': [2], 'group': 0}
# AeroDyn15
case_inputs[('AeroDyn15', 'WakeMod')] = {'vals': [1], 'group': 0}
case_inputs[('AeroDyn15', 'AfAeroMod')] = {'vals': [1], 'group': 0}
case_inputs[('AeroDyn15', 'TwrPotent')] = {'vals': [0], 'group': 0}
# ElastoDyn
case_inputs[('ElastoDyn', 'FlapDOF1')] = {'vals': ['True'], 'group': 0}
case_inputs[('ElastoDyn', 'FlapDOF2')] = {'vals': ['True'], 'group': 0}
case_inputs[('ElastoDyn', 'EdgeDOF')] = {'vals': ['True'], 'group': 0}
case_inputs[('ElastoDyn', 'TeetDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'DrTrDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'GenDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'YawDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'TwFADOF1')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'TwFADOF2')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'TwSSDOF1')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'TwSSDOF2')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmSgDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmSwDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmHvDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmRDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmPDOF')] = {'vals': ['False'], 'group': 0}
case_inputs[('ElastoDyn', 'PtfmYDOF')] = {'vals': ['False'], 'group': 0}
# BeamDyn
# NEEDED
# InflowWind
case_inputs[('InflowWind', 'WindType')] = {'vals': [1], 'group': 0}
case_inputs[('InflowWind', 'HWindSpeed')] = {'vals': [v0], 'group': 0}
case_inputs[('InflowWind', 'PLexp')] = {'vals': [0], 'group': 0}
# ServoDyn
case_inputs[('ServoDyn', 'PCMode')] = {'vals': [0], 'group': 0}
case_inputs[('ServoDyn', 'VSContrl')] = {'vals': [0], 'group': 0}
case_inputs[('ServoDyn', 'HSSBrMode')] = {'vals': [0], 'group': 0}
case_inputs[('ServoDyn', 'YCMode')] = {'vals': [0], 'group': 0}
# ------- Setup sweep values inputs --------
case_inputs[('ElastoDyn', 'BlPitch1')] = {'vals': list(pitch_initial), 'group': 1}
case_inputs[('ElastoDyn', 'BlPitch2')] = {'vals': list(pitch_initial), 'group': 1}
case_inputs[('ElastoDyn', 'BlPitch3')] = {'vals': list(pitch_initial), 'group': 1}
case_inputs[('ElastoDyn', 'RotSpeed')] = {'vals': list(rotspeed_initial), 'group': 2}
# FAST details
fastBatch = runFAST_pywrapper.runFAST_pywrapper_batch(FAST_ver='OpenFAST', dev_branch=True)
fastBatch.FAST_exe = openfast_path # Path to executable
fastBatch.FAST_InputFile = self.fast.FAST_InputFile
fastBatch.FAST_directory = self.fast.FAST_directory
if not FAST_runDirectory:
FAST_runDirectory = os.path.join(os.getcwd(), 'RotPerf_OpenFAST')
fastBatch.FAST_runDirectory = FAST_runDirectory
fastBatch.debug_level = debug_level
# Generate cases
case_name_base = self.TurbineName + '_rotperf'
case_list, case_name_list = CaseGen_General.CaseGen_General(
case_inputs, dir_matrix=fastBatch.FAST_runDirectory, namebase=case_name_base)
fastBatch.case_list = case_list
fastBatch.case_name_list = case_name_list
# Make sure proper outputs exist
var_out = [
# ElastoDyn (this is probably overkill on the outputs)
"BldPitch1", "BldPitch2", "BldPitch3", "Azimuth", "RotSpeed", "GenSpeed", "NacYaw",
"OoPDefl1", "IPDefl1", "TwstDefl1", "OoPDefl2", "IPDefl2", "TwstDefl2", "OoPDefl3",
"IPDefl3", "TwstDefl3", "RootFxc1",
"RootFyc1", "RootFzc1", "RootMxc1", "RootMyc1", "RootMzc1", "RootFxc2", "RootFyc2",
"RootFzc2", "RootMxc2", "RootMyc2", "RootMzc2", "RootFxc3", "RootFyc3", "RootFzc3",
"RootMxc3", "RootMyc3", "RootMzc3", "Spn1MLxb1", "Spn1MLyb1", "Spn1MLzb1", "Spn1MLxb2",
"Spn1MLyb2", "Spn1MLzb2", "Spn1MLxb3", "Spn1MLyb3", "Spn1MLzb3", "RotThrust", "LSSGagFya",
"LSSGagFza", "RotTorq", "LSSGagMya", "LSSGagMza",
# ServoDyn
"GenPwr", "GenTq",
# AeroDyn15
"RtArea", "RtVAvgxh", "B1N3Clrnc", "B2N3Clrnc", "B3N3Clrnc",
"RtAeroCp", 'RtAeroCq', 'RtAeroCt', 'RtTSR', # NECESSARY
# InflowWind
"Wind1VelX",
]
channels = {}
for var in var_out:
channels[var] = True
fastBatch.channels = channels
# Run OpenFAST
if run_type.lower() == 'multi':
fastBatch.run_multi()
elif run_type.lower()=='mpi':
fastBatch.run_mpi()
elif run_type.lower()=='serial':
fastBatch.run_serial()
# ========== Post Processing ==========
# Save statistics
fp = Processing.FAST_Processing()
# Find all outfiles
fname_case_matrix = os.path.join(FAST_runDirectory, 'case_matrix.yaml')
case_matrix = FileTools.load_yaml(fname_case_matrix, package=1)
cm = pd.DataFrame(case_matrix)
# Parse case matrix and find outfiles names
outfiles = []
case_names = cm['Case_Name']
outfiles = []
for name in case_names:
outfiles.append(os.path.join(FAST_runDirectory, name + '.outb'))
# Set some processing parameters
fp.OpenFAST_outfile_list = outfiles
fp.namebase = case_name_base
fp.t0 = 270
fp.parallel_analysis = True
fp.results_dir = os.path.join(FAST_runDirectory,'stats')
fp.verbose = True
# Save for debug!
fp.save_LoadRanking = False
fp.save_SummaryStats = False
print('Processing openfast data on {} cores.'.format(fp.parallel_cores))
# Load and save statistics and load rankings
stats, load_rankings = fp.batch_processing()
# Get means of last 30 seconds of 300 second simulation
CP = stats[0]['RtAeroCp']['mean']
CT = stats[0]['RtAeroCt']['mean']
CQ = stats[0]['RtAeroCq']['mean']
# Reshape Cp, Ct and Cq
Cp = np.transpose(np.reshape(CP, (len(pitch_initial), len(TSR_initial))))
Ct = np.transpose(np.reshape(CT, (len(pitch_initial), len(TSR_initial))))
Cq = np.transpose(np.reshape(CQ, (len(pitch_initial), len(TSR_initial))))
# Store necessary metrics for analysis
self.pitch_initial_rad = pitch_initial * deg2rad
self.TSR_initial = TSR_initial
self.Cp_table = Cp
self.Ct_table = Ct
self.Cq_table = Cq
def load_blade_info(self):
'''
Loads wind turbine blade data from an OpenFAST model.
Should be used if blade information is needed (i.e. for flap controller tuning),
but a rotor performance file is defined and and cc-blade does not need to be run.
Parameters:
-----------
self - note: needs to contain fast input file info provided by load_from_fast.
'''
if use_weis:
from weis.aeroelasticse.FAST_reader import InputReader_OpenFAST
else:
from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST
from wisdem.ccblade.ccblade import CCAirfoil, CCBlade
# Create CC-Blade Rotor
r0 = np.array(self.fast.fst_vt['AeroDynBlade']['BlSpn'])
chord0 = np.array(self.fast.fst_vt['AeroDynBlade']['BlChord'])
theta0 = np.array(self.fast.fst_vt['AeroDynBlade']['BlTwist'])
# -- Adjust for Aerodyn15
r = r0 + self.Rhub
chord_intfun = interpolate.interp1d(r0,chord0, bounds_error=None, fill_value='extrapolate', kind='zero')
chord = chord_intfun(r)
theta_intfun = interpolate.interp1d(r0,theta0, bounds_error=None, fill_value='extrapolate', kind='zero')
theta = theta_intfun(r)
af_idx = np.array(self.fast.fst_vt['AeroDynBlade']['BlAFID']).astype(int) - 1 #Reset to 0 index
AFNames = self.fast.fst_vt['AeroDyn15']['AFNames']
# Read OpenFAST Airfoil data, assumes AeroDyn > v15.03 and associated polars > v1.01
af_dict = {}
for i, section in enumerate(self.fast.fst_vt['AeroDyn15']['af_data']):
Alpha = section[0]['Alpha']
if section[0]['NumTabs'] > 1: # sections with multiple airfoil tables
ref_tab = int(np.floor(section[0]['NumTabs']/2)) # get information from "center" table
Re = np.array([section[ref_tab]['Re']])*1e6
Cl = section[ref_tab]['Cl']
Cd = section[ref_tab]['Cd']
Cm = section[ref_tab]['Cm']
af_dict[i] = CCAirfoil(Alpha, Re, Cl, Cd, Cm)
else: # sections without multiple airfoil tables
Re = np.array([section[0]['Re']])*1e6
Cl = section[0]['Cl']
Cd = section[0]['Cd']
Cm = section[0]['Cm']
af_dict[i] = CCAirfoil(Alpha, Re, Cl, Cd, Cm)
# define airfoils for CCBlade
af = [0]*len(r)
for i in range(len(r)):
af[i] = af_dict[af_idx[i]]
# Now save the CC-Blade rotor
nSector = 8 # azimuthal discretizations
self.cc_rotor = CCBlade(r, chord, theta, af, self.Rhub, self.rotor_radius, self.NumBl, rho=self.rho, mu=self.mu,
precone=-self.precone, tilt=-self.tilt, yaw=self.yaw, shearExp=self.shearExp, hubHt=self.hubHt, nSector=nSector)
# Save some additional blade data
self.af_data = self.fast.fst_vt['AeroDyn15']['af_data']
self.span = r
self.chord = chord
self.twist = theta
self.bld_flapwise_damp = self.fast.fst_vt['ElastoDynBlade']['BldFlDmp1']/100
class RotorPerformance():
'''
Class RotorPerformance used to find details from rotor performance
tables generated by CC-blade or similer BEM-solvers.
Methods:
--------
interp_surface
interp_gradient
plot_performance
Parameters:
-----------
performance_table : array_like (-)
An [n x m] array containing a table of rotor performance data (Cp, Ct, Cq).
pitch_initial_rad : array_like (rad)
An [m x 1] or [1 x m] array containing blade pitch angles corresponding to performance_table.
TSR_initial : array_like (rad)
An [n x 1] or [1 x n] array containing tip-speed ratios corresponding to performance_table
'''
def __init__(self,performance_table, pitch_initial_rad, TSR_initial):
# Store performance data tables
self.performance_table = performance_table # Table containing rotor performance data, i.e. Cp, Ct, Cq
self.pitch_initial_rad = pitch_initial_rad # Pitch angles corresponding to x-axis of performance_table (rad)
self.TSR_initial = TSR_initial # Tip-Speed-Ratios corresponding to y-axis of performance_table (rad)
# Calculate Gradients
self.gradient_TSR, self.gradient_pitch = gradient(performance_table) # gradient_TSR along y-axis, gradient_pitch along x-axis (rows, columns)
# "Optimal" below rated TSR and blade pitch (for Cp) - note this may be limited by resolution of Cp-surface
self.max = np.amax(performance_table)
self.max_ind = np.where(performance_table == np.amax(performance_table))
self.pitch_opt = pitch_initial_rad[self.max_ind[1]]
# --- Find TSR ---
# Make finer mesh for Tip speed ratios at "optimal" blade pitch angle, do a simple lookup.
# -- nja: this seems to work a little better than interpolating
# Find the 1D performance table when pitch is at the maximum part of the Cx surface:
performance_beta_max = np.ndarray.flatten(performance_table[:,self.max_ind[1][-1]]) # performance metric at the last maximizing pitch angle
# If there is more than one max pitch angle:
if len(self.max_ind[1]) > 1:
print('ROSCO_toolbox Warning: repeated maximum values in a performance table and the last one @ pitch = {} rad. was taken...'.format(self.pitch_opt[-1]))
TSR_ind = np.arange(0,len(TSR_initial))
TSR_fine_ind = np.linspace(TSR_initial[0],TSR_initial[-1],int(TSR_initial[-1] - TSR_initial[0])*100)
f_TSR = interpolate.interp1d(TSR_initial,TSR_initial,bounds_error='False',kind='quadratic') # interpolate function for Cp(tsr) values
TSR_fine = f_TSR(TSR_fine_ind)
f_performance = interpolate.interp1d(TSR_initial,performance_beta_max,bounds_error='False',kind='quadratic') # interpolate function for Cp(tsr) values
performance_fine = f_performance(TSR_fine_ind)
performance_max_ind = np.where(performance_fine == np.max(performance_fine))
self.TSR_opt = float(TSR_fine[performance_max_ind[0]])
def interp_surface(self,pitch,TSR):
'''
2d interpolation to find point on rotor performance surface
Parameters:
-----------
pitch : float (rad)
Pitch angle to look up
TSR : float (rad)
Tip-speed ratio to look up
'''
# Form the interpolant functions which can look up any arbitrary location on rotor performance surface
interp_fun = interpolate.interp2d(
self.pitch_initial_rad, self.TSR_initial, self.performance_table, kind='cubic')
return interp_fun(pitch,TSR)
def interp_gradient(self,pitch,TSR):
'''
2d interpolation to find gradient at a specified point on rotor performance surface
Parameters:
-----------
pitch : float (rad)
Pitch angle to look up
TSR : float (rad)
Tip-speed ratio to look up
Returns:
--------
interp_gradient : array_like
[1 x 2] array coresponding to gradient in pitch and TSR directions, respectively
'''
# Form the interpolant functions to find gradient at any arbitrary location on rotor performance surface
dCP_beta_interp = interpolate.interp2d(self.pitch_initial_rad, self.TSR_initial, self.gradient_pitch, kind='linear')
dCP_TSR_interp = interpolate.interp2d(self.pitch_initial_rad, self.TSR_initial, self.gradient_TSR, kind='linear')
# grad.shape output as (2,) numpy array, equivalent to (pitch-direction,TSR-direction)
grad = np.array([dCP_beta_interp(pitch,TSR), dCP_TSR_interp(pitch,TSR)])
return np.ndarray.flatten(grad)
def plot_performance(self):
'''
Plot rotor performance data surface.
Parameters:
-----------
self
'''
# Find maximum point
max_ind = np.unravel_index(np.argmax(self.performance_table, axis=None), self.performance_table.shape)
max_beta_id = self.pitch_initial_rad[max_ind[1]]
max_tsr_id = self.TSR_initial[max_ind[0]]
P = plt.contourf(self.pitch_initial_rad * rad2deg, self.TSR_initial, self.performance_table,
levels=np.linspace(0,np.max(self.performance_table),20))
plt.colorbar(format='%1.3f')
plt.title('Power Coefficient', fontsize=14, fontweight='bold')
plt.xlabel('Pitch Angle [deg]', fontsize=14, fontweight='bold')
plt.ylabel('TSR [-]', fontsize=14, fontweight='bold')
plt.scatter(max_beta_id * rad2deg, max_tsr_id, color='red')
plt.annotate('max = {:<1.3f}'.format(np.max(self.performance_table)),
(max_beta_id+0.2, max_tsr_id+0.2), color='red')
plt.xticks(fontsize=12)
plt.yticks(fontsize=12) | /rosco-toolbox-2.3.0.tar.gz/rosco-toolbox-2.3.0/ROSCO_toolbox/turbine.py | 0.789356 | 0.305697 | turbine.py | pypi |
ElastoDyn = {}
# Blade 1 Tip Motions
ElastoDyn['TipDxc1'] = False # (m); Blade 1 out-of-plane tip deflection (relative to the undeflected position); Directed along the xc1-axis
ElastoDyn['OoPDefl1'] = False # (m); Blade 1 out-of-plane tip deflection (relative to the undeflected position); Directed along the xc1-axis
ElastoDyn['TipDyc1'] = False # (m); Blade 1 in-plane tip deflection (relative to the undeflected position); Directed along the yc1-axis
ElastoDyn['IPDefl1'] = False # (m); Blade 1 in-plane tip deflection (relative to the undeflected position); Directed along the yc1-axis
ElastoDyn['TipDzc1'] = False # (m); Blade 1 axial tip deflection (relative to the undeflected position); Directed along the zc1- and zb1-axes
ElastoDyn['TipDzb1'] = False # (m); Blade 1 axial tip deflection (relative to the undeflected position); Directed along the zc1- and zb1-axes
ElastoDyn['TipDxb1'] = False # (m); Blade 1 flapwise tip deflection (relative to the undeflected position); Directed along the xb1-axis
ElastoDyn['TipDyb1'] = False # (m); Blade 1 edgewise tip deflection (relative to the undeflected position); Directed along the yb1-axis
ElastoDyn['TipALxb1'] = False # (m/s^2); Blade 1 local flapwise tip acceleration (absolute); Directed along the local xb1-axis
ElastoDyn['TipALyb1'] = False # (m/s^2); Blade 1 local edgewise tip acceleration (absolute); Directed along the local yb1-axis
ElastoDyn['TipALzb1'] = False # (m/s^2); Blade 1 local axial tip acceleration (absolute); Directed along the local zb1-axis
ElastoDyn['TipRDxb1'] = False # (deg); Blade 1 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb1-axis
ElastoDyn['RollDefl1'] = False # (deg); Blade 1 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb1-axis
ElastoDyn['TipRDyb1'] = False # (deg); Blade 1 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb1-axis
ElastoDyn['PtchDefl1'] = False # (deg); Blade 1 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb1-axis
ElastoDyn['TipRDzc1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
ElastoDyn['TipRDzb1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
ElastoDyn['TwstDefl1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
ElastoDyn['TipClrnc1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['TwrClrnc1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['Tip2Twr1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 2 Tip Motions
ElastoDyn['TipDxc2'] = False # (m); Blade 2 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc2-axis
ElastoDyn['OoPDefl2'] = False # (m); Blade 2 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc2-axis
ElastoDyn['TipDyc2'] = False # (m); Blade 2 in-plane tip deflection (relative to the pitch axis); Directed along the yc2-axis
ElastoDyn['IPDefl2'] = False # (m); Blade 2 in-plane tip deflection (relative to the pitch axis); Directed along the yc2-axis
ElastoDyn['TipDzc2'] = False # (m); Blade 2 axial tip deflection (relative to the pitch axis); Directed along the zc2- and zb2-axes
ElastoDyn['TipDzb2'] = False # (m); Blade 2 axial tip deflection (relative to the pitch axis); Directed along the zc2- and zb2-axes
ElastoDyn['TipDxb2'] = False # (m); Blade 2 flapwise tip deflection (relative to the pitch axis); Directed along the xb2-axis
ElastoDyn['TipDyb2'] = False # (m); Blade 2 edgewise tip deflection (relative to the pitch axis); Directed along the yb2-axis
ElastoDyn['TipALxb2'] = False # (m/s^2); Blade 2 local flapwise tip acceleration (absolute); Directed along the local xb2-axis
ElastoDyn['TipALyb2'] = False # (m/s^2); Blade 2 local edgewise tip acceleration (absolute); Directed along the local yb2-axis
ElastoDyn['TipALzb2'] = False # (m/s^2); Blade 2 local axial tip acceleration (absolute); Directed along the local zb2-axis
ElastoDyn['TipRDxb2'] = False # (deg); Blade 2 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb2-axis
ElastoDyn['RollDefl2'] = False # (deg); Blade 2 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb2-axis
ElastoDyn['TipRDyb2'] = False # (deg); Blade 2 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb2-axis
ElastoDyn['PtchDefl2'] = False # (deg); Blade 2 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb2-axis
ElastoDyn['TipRDzc2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
ElastoDyn['TipRDzb2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
ElastoDyn['TwstDefl2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
ElastoDyn['TipClrnc2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['TwrClrnc2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['Tip2Twr2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 3 Tip Motions
ElastoDyn['TipDxc3'] = False # (m); Blade 3 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc3-axis
ElastoDyn['OoPDefl3'] = False # (m); Blade 3 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc3-axis
ElastoDyn['TipDyc3'] = False # (m); Blade 3 in-plane tip deflection (relative to the pitch axis); Directed along the yc3-axis
ElastoDyn['IPDefl3'] = False # (m); Blade 3 in-plane tip deflection (relative to the pitch axis); Directed along the yc3-axis
ElastoDyn['TipDzc3'] = False # (m); Blade 3 axial tip deflection (relative to the pitch axis); Directed along the zc3- and zb3-axes
ElastoDyn['TipDzb3'] = False # (m); Blade 3 axial tip deflection (relative to the pitch axis); Directed along the zc3- and zb3-axes
ElastoDyn['TipDxb3'] = False # (m); Blade 3 flapwise tip deflection (relative to the pitch axis); Directed along the xb3-axis
ElastoDyn['TipDyb3'] = False # (m); Blade 3 edgewise tip deflection (relative to the pitch axis); Directed along the yb3-axis
ElastoDyn['TipALxb3'] = False # (m/s^2); Blade 3 local flapwise tip acceleration (absolute); Directed along the local xb3-axis
ElastoDyn['TipALyb3'] = False # (m/s^2); Blade 3 local edgewise tip acceleration (absolute); Directed along the local yb3-axis
ElastoDyn['TipALzb3'] = False # (m/s^2); Blade 3 local axial tip acceleration (absolute); Directed along the local zb3-axis
ElastoDyn['TipRDxb3'] = False # (deg); Blade 3 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb3-axis
ElastoDyn['RollDefl3'] = False # (deg); Blade 3 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb3-axis
ElastoDyn['TipRDyb3'] = False # (deg); Blade 3 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb3-axis
ElastoDyn['PtchDefl3'] = False # (deg); Blade 3 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb3-axis
ElastoDyn['TipRDzc3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
ElastoDyn['TipRDzb3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
ElastoDyn['TwstDefl3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
ElastoDyn['TipClrnc3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['TwrClrnc3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
ElastoDyn['Tip2Twr3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 1 Local Span Motions
ElastoDyn['Spn1ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 1; Directed along the local xb1-axis
ElastoDyn['Spn1ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 1; Directed along the local yb1-axis
ElastoDyn['Spn1ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 1; Directed along the local zb1-axis
ElastoDyn['Spn2ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 2; Directed along the local xb1-axis
ElastoDyn['Spn2ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 2; Directed along the local yb1-axis
ElastoDyn['Spn2ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 2; Directed along the local zb1-axis
ElastoDyn['Spn3ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 3; Directed along the local xb1-axis
ElastoDyn['Spn3ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 3; Directed along the local yb1-axis
ElastoDyn['Spn3ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 3; Directed along the local zb1-axis
ElastoDyn['Spn4ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 4; Directed along the local xb1-axis
ElastoDyn['Spn4ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 4; Directed along the local yb1-axis
ElastoDyn['Spn4ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 4; Directed along the local zb1-axis
ElastoDyn['Spn5ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 5; Directed along the local xb1-axis
ElastoDyn['Spn5ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 5; Directed along the local yb1-axis
ElastoDyn['Spn5ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 5; Directed along the local zb1-axis
ElastoDyn['Spn6ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 6; Directed along the local xb1-axis
ElastoDyn['Spn6ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 6; Directed along the local yb1-axis
ElastoDyn['Spn6ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 6; Directed along the local zb1-axis
ElastoDyn['Spn7ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 7; Directed along the local xb1-axis
ElastoDyn['Spn7ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 7; Directed along the local yb1-axis
ElastoDyn['Spn7ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 7; Directed along the local zb1-axis
ElastoDyn['Spn8ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 8; Directed along the local xb1-axis
ElastoDyn['Spn8ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 8; Directed along the local yb1-axis
ElastoDyn['Spn8ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 8; Directed along the local zb1-axis
ElastoDyn['Spn9ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 9; Directed along the local xb1-axis
ElastoDyn['Spn9ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 9; Directed along the local yb1-axis
ElastoDyn['Spn9ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 9; Directed along the local zb1-axis
ElastoDyn['Spn1TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb1-axis
ElastoDyn['Spn1TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb1-axis
ElastoDyn['Spn1TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb1-axis
ElastoDyn['Spn2TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb1-axis
ElastoDyn['Spn2TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb1-axis
ElastoDyn['Spn2TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb1-axis
ElastoDyn['Spn3TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb1-axis
ElastoDyn['Spn3TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb1-axis
ElastoDyn['Spn3TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb1-axis
ElastoDyn['Spn4TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb1-axis
ElastoDyn['Spn4TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb1-axis
ElastoDyn['Spn4TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb1-axis
ElastoDyn['Spn5TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb1-axis
ElastoDyn['Spn5TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb1-axis
ElastoDyn['Spn5TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb1-axis
ElastoDyn['Spn6TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb1-axis
ElastoDyn['Spn6TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb1-axis
ElastoDyn['Spn6TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb1-axis
ElastoDyn['Spn7TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb1-axis
ElastoDyn['Spn7TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb1-axis
ElastoDyn['Spn7TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb1-axis
ElastoDyn['Spn8TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb1-axis
ElastoDyn['Spn8TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb1-axis
ElastoDyn['Spn8TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb1-axis
ElastoDyn['Spn9TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb1-axis
ElastoDyn['Spn9TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb1-axis
ElastoDyn['Spn9TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb1-axis
ElastoDyn['Spn1RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn1RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn1RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn2RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn2RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn2RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn3RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn3RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn3RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn4RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn4RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn4RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn5RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn5RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn5RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn6RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn6RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn6RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn7RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn7RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn7RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn8RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn8RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn8RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
ElastoDyn['Spn9RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
ElastoDyn['Spn9RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
ElastoDyn['Spn9RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
# Blade 2 Local Span Motions
ElastoDyn['Spn1ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 1; Directed along the local xb2-axis
ElastoDyn['Spn1ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 1; Directed along the local yb2-axis
ElastoDyn['Spn1ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 1; Directed along the local zb2-axis
ElastoDyn['Spn2ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 2; Directed along the local xb2-axis
ElastoDyn['Spn2ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 2; Directed along the local yb2-axis
ElastoDyn['Spn2ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 2; Directed along the local zb2-axis
ElastoDyn['Spn3ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 3; Directed along the local xb2-axis
ElastoDyn['Spn3ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 3; Directed along the local yb2-axis
ElastoDyn['Spn3ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 3; Directed along the local zb2-axis
ElastoDyn['Spn4ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 4; Directed along the local xb2-axis
ElastoDyn['Spn4ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 4; Directed along the local yb2-axis
ElastoDyn['Spn4ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 4; Directed along the local zb2-axis
ElastoDyn['Spn5ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 5; Directed along the local xb2-axis
ElastoDyn['Spn5ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 5; Directed along the local yb2-axis
ElastoDyn['Spn5ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 5; Directed along the local zb2-axis
ElastoDyn['Spn6ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 6; Directed along the local xb2-axis
ElastoDyn['Spn6ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 6; Directed along the local yb2-axis
ElastoDyn['Spn6ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 6; Directed along the local zb2-axis
ElastoDyn['Spn7ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 7; Directed along the local xb2-axis
ElastoDyn['Spn7ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 7; Directed along the local yb2-axis
ElastoDyn['Spn7ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 7; Directed along the local zb2-axis
ElastoDyn['Spn8ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 8; Directed along the local xb2-axis
ElastoDyn['Spn8ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 8; Directed along the local yb2-axis
ElastoDyn['Spn8ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 8; Directed along the local zb2-axis
ElastoDyn['Spn9ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 9; Directed along the local xb2-axis
ElastoDyn['Spn9ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 9; Directed along the local yb2-axis
ElastoDyn['Spn9ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 9; Directed along the local zb2-axis
ElastoDyn['Spn1TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb2-axis
ElastoDyn['Spn1TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb2-axis
ElastoDyn['Spn1TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb2-axis
ElastoDyn['Spn2TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb2-axis
ElastoDyn['Spn2TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb2-axis
ElastoDyn['Spn2TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb2-axis
ElastoDyn['Spn3TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb2-axis
ElastoDyn['Spn3TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb2-axis
ElastoDyn['Spn3TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb2-axis
ElastoDyn['Spn4TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb2-axis
ElastoDyn['Spn4TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb2-axis
ElastoDyn['Spn4TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb2-axis
ElastoDyn['Spn5TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb2-axis
ElastoDyn['Spn5TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb2-axis
ElastoDyn['Spn5TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb2-axis
ElastoDyn['Spn6TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb2-axis
ElastoDyn['Spn6TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb2-axis
ElastoDyn['Spn6TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb2-axis
ElastoDyn['Spn7TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb2-axis
ElastoDyn['Spn7TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb2-axis
ElastoDyn['Spn7TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb2-axis
ElastoDyn['Spn8TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb2-axis
ElastoDyn['Spn8TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb2-axis
ElastoDyn['Spn8TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb2-axis
ElastoDyn['Spn9TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb2-axis
ElastoDyn['Spn9TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb2-axis
ElastoDyn['Spn9TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb2-axis
ElastoDyn['Spn1RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn1RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn1RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn2RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn2RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn2RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn3RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn3RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn3RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn4RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn4RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn4RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn5RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn5RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn5RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn6RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn6RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn6RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn7RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn7RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn7RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn8RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn8RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn8RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
ElastoDyn['Spn9RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
ElastoDyn['Spn9RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
ElastoDyn['Spn9RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
# Blade 3 Local Span Motions
ElastoDyn['Spn1ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 1; Directed along the local xb3-axis
ElastoDyn['Spn1ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 1; Directed along the local yb3-axis
ElastoDyn['Spn1ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 1; Directed along the local zb3-axis
ElastoDyn['Spn2ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 2; Directed along the local xb3-axis
ElastoDyn['Spn2ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 2; Directed along the local yb3-axis
ElastoDyn['Spn2ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 2; Directed along the local zb3-axis
ElastoDyn['Spn3ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 3; Directed along the local xb3-axis
ElastoDyn['Spn3ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 3; Directed along the local yb3-axis
ElastoDyn['Spn3ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 3; Directed along the local zb3-axis
ElastoDyn['Spn4ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 4; Directed along the local xb3-axis
ElastoDyn['Spn4ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 4; Directed along the local yb3-axis
ElastoDyn['Spn4ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 4; Directed along the local zb3-axis
ElastoDyn['Spn5ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 5; Directed along the local xb3-axis
ElastoDyn['Spn5ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 5; Directed along the local yb3-axis
ElastoDyn['Spn5ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 5; Directed along the local zb3-axis
ElastoDyn['Spn6ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 6; Directed along the local xb3-axis
ElastoDyn['Spn6ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 6; Directed along the local yb3-axis
ElastoDyn['Spn6ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 6; Directed along the local zb3-axis
ElastoDyn['Spn7ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 7; Directed along the local xb3-axis
ElastoDyn['Spn7ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 7; Directed along the local yb3-axis
ElastoDyn['Spn7ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 7; Directed along the local zb3-axis
ElastoDyn['Spn8ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 8; Directed along the local xb3-axis
ElastoDyn['Spn8ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 8; Directed along the local yb3-axis
ElastoDyn['Spn8ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 8; Directed along the local zb3-axis
ElastoDyn['Spn9ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 9; Directed along the local xb3-axis
ElastoDyn['Spn9ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 9; Directed along the local yb3-axis
ElastoDyn['Spn9ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 9; Directed along the local zb3-axis
ElastoDyn['Spn1TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb3-axis
ElastoDyn['Spn1TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb3-axis
ElastoDyn['Spn1TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb3-axis
ElastoDyn['Spn2TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb3-axis
ElastoDyn['Spn2TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb3-axis
ElastoDyn['Spn2TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb3-axis
ElastoDyn['Spn3TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb3-axis
ElastoDyn['Spn3TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb3-axis
ElastoDyn['Spn3TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb3-axis
ElastoDyn['Spn4TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb3-axis
ElastoDyn['Spn4TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb3-axis
ElastoDyn['Spn4TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb3-axis
ElastoDyn['Spn5TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb3-axis
ElastoDyn['Spn5TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb3-axis
ElastoDyn['Spn5TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb3-axis
ElastoDyn['Spn6TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb3-axis
ElastoDyn['Spn6TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb3-axis
ElastoDyn['Spn6TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb3-axis
ElastoDyn['Spn7TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb3-axis
ElastoDyn['Spn7TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb3-axis
ElastoDyn['Spn7TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb3-axis
ElastoDyn['Spn8TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb3-axis
ElastoDyn['Spn8TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb3-axis
ElastoDyn['Spn8TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb3-axis
ElastoDyn['Spn9TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb3-axis
ElastoDyn['Spn9TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb3-axis
ElastoDyn['Spn9TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb3-axis
ElastoDyn['Spn1RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn1RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn1RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn2RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn2RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn2RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn3RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn3RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn3RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn4RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn4RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn4RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn5RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn5RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn5RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn6RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn6RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn6RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn7RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn7RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn7RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn8RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn8RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn8RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
ElastoDyn['Spn9RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
ElastoDyn['Spn9RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
ElastoDyn['Spn9RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
# Blade Pitch Motions
ElastoDyn['PtchPMzc1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
ElastoDyn['PtchPMzb1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
ElastoDyn['BldPitch1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
ElastoDyn['BlPitch1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
ElastoDyn['PtchPMzc2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
ElastoDyn['PtchPMzb2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
ElastoDyn['BldPitch2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
ElastoDyn['BlPitch2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
ElastoDyn['PtchPMzc3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
ElastoDyn['PtchPMzb3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
ElastoDyn['BldPitch3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
ElastoDyn['BlPitch3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
# Teeter Motions
ElastoDyn['TeetPya'] = False # (deg); Rotor teeter angle (position); About the ya-axis
ElastoDyn['RotTeetP'] = False # (deg); Rotor teeter angle (position); About the ya-axis
ElastoDyn['TeetDefl'] = False # (deg); Rotor teeter angle (position); About the ya-axis
ElastoDyn['TeetVya'] = False # (deg/s); Rotor teeter angular velocity; About the ya-axis
ElastoDyn['RotTeetV'] = False # (deg/s); Rotor teeter angular velocity; About the ya-axis
ElastoDyn['TeetAya'] = False # (deg/s^2); Rotor teeter angular acceleration; About the ya-axis
ElastoDyn['RotTeetA'] = False # (deg/s^2); Rotor teeter angular acceleration; About the ya-axis
# Shaft Motions
ElastoDyn['LSSTipPxa'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
ElastoDyn['LSSTipPxs'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
ElastoDyn['LSSTipP'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
ElastoDyn['Azimuth'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
ElastoDyn['LSSTipVxa'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
ElastoDyn['LSSTipVxs'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
ElastoDyn['LSSTipV'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
ElastoDyn['RotSpeed'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
ElastoDyn['LSSTipAxa'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
ElastoDyn['LSSTipAxs'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
ElastoDyn['LSSTipA'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
ElastoDyn['RotAccel'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
ElastoDyn['LSSGagPxa'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagPxs'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagP'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagVxa'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagVxs'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagV'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagAxa'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagAxs'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['LSSGagA'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
ElastoDyn['HSShftV'] = False # (rpm); Angular speed of the high-speed shaft and generator; Same sign as LSSGagVxa / LSSGagVxs / LSSGagV
ElastoDyn['GenSpeed'] = False # (rpm); Angular speed of the high-speed shaft and generator; Same sign as LSSGagVxa / LSSGagVxs / LSSGagV
ElastoDyn['HSShftA'] = False # (deg/s^2); Angular acceleration of the high-speed shaft and generator; Same sign as LSSGagAxa / LSSGagAxs / LSSGagA
ElastoDyn['GenAccel'] = False # (deg/s^2); Angular acceleration of the high-speed shaft and generator; Same sign as LSSGagAxa / LSSGagAxs / LSSGagA
# Nacelle IMU Motions
ElastoDyn['NcIMUTVxs'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the xs-axis
ElastoDyn['NcIMUTVys'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the ys-axis
ElastoDyn['NcIMUTVzs'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the zs-axis
ElastoDyn['NcIMUTAxs'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the xs-axis
ElastoDyn['NcIMUTAys'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the ys-axis
ElastoDyn['NcIMUTAzs'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the zs-axis
ElastoDyn['NcIMURVxs'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the xs-axis
ElastoDyn['NcIMURVys'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the ys-axis
ElastoDyn['NcIMURVzs'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the zs-axis
ElastoDyn['NcIMURAxs'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the xs-axis
ElastoDyn['NcIMURAys'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the ys-axis
ElastoDyn['NcIMURAzs'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the zs-axis
# Rotor-Furl Motions
ElastoDyn['RotFurlP'] = False # (deg); Rotor-furl angle (position); About the rotor-furl axis
ElastoDyn['RotFurl'] = False # (deg); Rotor-furl angle (position); About the rotor-furl axis
ElastoDyn['RotFurlV'] = False # (deg/s); Rotor-furl angular velocity; About the rotor-furl axis
ElastoDyn['RotFurlA'] = False # (deg/s^2); Rotor-furl angular acceleration; About the rotor-furl axis
# Tail-Furl Motions
ElastoDyn['TailFurlP'] = False # (deg); Tail-furl angle (position); About the tail-furl axis
ElastoDyn['TailFurl'] = False # (deg); Tail-furl angle (position); About the tail-furl axis
ElastoDyn['TailFurlV'] = False # (deg/s); Tail-furl angular velocity; About the tail-furl axis
ElastoDyn['TailFurlA'] = False # (deg/s^2); Tail-furl angular acceleration; About the tail-furl axis
# Nacelle Yaw Motions
ElastoDyn['YawPzn'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
ElastoDyn['YawPzp'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
ElastoDyn['NacYawP'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
ElastoDyn['NacYaw'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
ElastoDyn['YawPos'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
ElastoDyn['YawVzn'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
ElastoDyn['YawVzp'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
ElastoDyn['NacYawV'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
ElastoDyn['YawRate'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
ElastoDyn['YawAzn'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
ElastoDyn['YawAzp'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
ElastoDyn['NacYawA'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
ElastoDyn['YawAccel'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
# Tower-Top / Yaw Bearing Motions
ElastoDyn['YawBrTDxp'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xp-axis
ElastoDyn['YawBrTDyp'] = False # (m); Tower-top / yaw bearing side-to-side (translational) deflection (relative to the undeflected position); Directed along the yp-axis
ElastoDyn['YawBrTDzp'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zp-axis
ElastoDyn['YawBrTDxt'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xt-axis
ElastoDyn['TTDspFA'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xt-axis
ElastoDyn['YawBrTDyt'] = False # (m); Tower-top / yaw bearing side-to-side (translation) deflection (relative to the undeflected position); Directed along the yt-axis
ElastoDyn['TTDspSS'] = False # (m); Tower-top / yaw bearing side-to-side (translation) deflection (relative to the undeflected position); Directed along the yt-axis
ElastoDyn['YawBrTDzt'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis
ElastoDyn['TTDspAx'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis
ElastoDyn['YawBrTAxp'] = False # (m/s^2); Tower-top / yaw bearing fore-aft (translational) acceleration (absolute); Directed along the xp-axis
ElastoDyn['YawBrTAyp'] = False # (m/s^2); Tower-top / yaw bearing side-to-side (translational) acceleration (absolute); Directed along the yp-axis
ElastoDyn['YawBrTAzp'] = False # (m/s^2); Tower-top / yaw bearing axial (translational) acceleration (absolute); Directed along the zp-axis
ElastoDyn['YawBrRDxt'] = False # (deg); Tower-top / yaw bearing angular (rotational) roll deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the xt-axis
ElastoDyn['TTDspRoll'] = False # (deg); Tower-top / yaw bearing angular (rotational) roll deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the xt-axis
ElastoDyn['YawBrRDyt'] = False # (deg); Tower-top / yaw bearing angular (rotational) pitch deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the yt-axis
ElastoDyn['TTDspPtch'] = False # (deg); Tower-top / yaw bearing angular (rotational) pitch deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the yt-axis
ElastoDyn['YawBrRDzt'] = False # (deg); Tower-top / yaw bearing angular (rotational) torsion deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the zt-axis
ElastoDyn['TTDspTwst'] = False # (deg); Tower-top / yaw bearing angular (rotational) torsion deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the zt-axis
ElastoDyn['YawBrRVxp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) roll velocity (absolute); About the xp-axis
ElastoDyn['YawBrRVyp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) pitch velocity (absolute); About the yp-axis
ElastoDyn['YawBrRVzp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) torsion velocity. This output will always be very close to zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. (absolute); About the zp-axis
ElastoDyn['YawBrRAxp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) roll acceleration (absolute); About the xp-axis
ElastoDyn['YawBrRAyp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) pitch acceleration (absolute); About the yp-axis
ElastoDyn['YawBrRAzp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) torsion acceleration. This output will always be very close to zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. (absolute); About the zp-axis
# Local Tower Motions
ElastoDyn['TwHt1ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 1 ; Directed along the local xt-axis
ElastoDyn['TwHt1ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 1 ; Directed along the local yt-axis
ElastoDyn['TwHt1ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 1 ; Directed along the local zt-axis
ElastoDyn['TwHt2ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 2; Directed along the local xt-axis
ElastoDyn['TwHt2ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 2; Directed along the local yt-axis
ElastoDyn['TwHt2ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 2; Directed along the local zt-axis
ElastoDyn['TwHt3ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 3; Directed along the local xt-axis
ElastoDyn['TwHt3ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 3; Directed along the local yt-axis
ElastoDyn['TwHt3ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 3; Directed along the local zt-axis
ElastoDyn['TwHt4ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 4; Directed along the local xt-axis
ElastoDyn['TwHt4ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 4; Directed along the local yt-axis
ElastoDyn['TwHt4ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 4; Directed along the local zt-axis
ElastoDyn['TwHt5ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 5; Directed along the local xt-axis
ElastoDyn['TwHt5ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 5; Directed along the local yt-axis
ElastoDyn['TwHt5ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 5; Directed along the local zt-axis
ElastoDyn['TwHt6ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 6; Directed along the local xt-axis
ElastoDyn['TwHt6ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 6; Directed along the local yt-axis
ElastoDyn['TwHt6ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 6; Directed along the local zt-axis
ElastoDyn['TwHt7ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 7; Directed along the local xt-axis
ElastoDyn['TwHt7ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 7; Directed along the local yt-axis
ElastoDyn['TwHt7ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 7; Directed along the local zt-axis
ElastoDyn['TwHt8ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 8; Directed along the local xt-axis
ElastoDyn['TwHt8ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 8; Directed along the local yt-axis
ElastoDyn['TwHt8ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 8; Directed along the local zt-axis
ElastoDyn['TwHt9ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 9; Directed along the local xt-axis
ElastoDyn['TwHt9ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 9; Directed along the local yt-axis
ElastoDyn['TwHt9ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 9; Directed along the local zt-axis
ElastoDyn['TwHt1TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local xt-axis
ElastoDyn['TwHt1TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local yt-axis
ElastoDyn['TwHt1TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local zt-axis
ElastoDyn['TwHt2TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local xt-axis
ElastoDyn['TwHt2TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local yt-axis
ElastoDyn['TwHt2TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local zt-axis
ElastoDyn['TwHt3TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local xt-axis
ElastoDyn['TwHt3TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local yt-axis
ElastoDyn['TwHt3TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local zt-axis
ElastoDyn['TwHt4TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local xt-axis
ElastoDyn['TwHt4TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local yt-axis
ElastoDyn['TwHt4TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local zt-axis
ElastoDyn['TwHt5TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local xt-axis
ElastoDyn['TwHt5TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local yt-axis
ElastoDyn['TwHt5TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local zt-axis
ElastoDyn['TwHt6TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local xt-axis
ElastoDyn['TwHt6TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local yt-axis
ElastoDyn['TwHt6TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local zt-axis
ElastoDyn['TwHt7TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local xt-axis
ElastoDyn['TwHt7TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local yt-axis
ElastoDyn['TwHt7TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local zt-axis
ElastoDyn['TwHt8TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local xt-axis
ElastoDyn['TwHt8TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local yt-axis
ElastoDyn['TwHt8TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local zt-axis
ElastoDyn['TwHt9TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local xt-axis
ElastoDyn['TwHt9TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local yt-axis
ElastoDyn['TwHt9TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local zt-axis
ElastoDyn['TwHt1RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt1RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt1RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 1. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt2RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt2RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt2RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 2. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt3RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt3RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt3RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 3. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt4RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt4RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt4RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 4. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt5RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt5RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt5RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 5. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt6RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt6RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt6RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 6. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt7RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt7RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt7RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 7. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt8RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt8RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt8RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 8. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt9RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
ElastoDyn['TwHt9RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
ElastoDyn['TwHt9RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 9. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
ElastoDyn['TwHt1TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 1; Directed along the local xi-axis
ElastoDyn['TwHt1TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 1; Directed along the local yi-axis
ElastoDyn['TwHt1TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 1; Directed along the local zi-axis
ElastoDyn['TwHt2TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 2; Directed along the local xi-axis
ElastoDyn['TwHt2TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 2; Directed along the local yi-axis
ElastoDyn['TwHt2TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 2; Directed along the local zi-axis
ElastoDyn['TwHt3TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 3; Directed along the local xi-axis
ElastoDyn['TwHt3TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 3; Directed along the local yi-axis
ElastoDyn['TwHt3TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 3; Directed along the local zi-axis
ElastoDyn['TwHt4TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 4; Directed along the local xi-axis
ElastoDyn['TwHt4TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 4; Directed along the local yi-axis
ElastoDyn['TwHt4TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 4; Directed along the local zi-axis
ElastoDyn['TwHt5TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 5; Directed along the local xi-axis
ElastoDyn['TwHt5TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 5; Directed along the local yi-axis
ElastoDyn['TwHt5TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 5; Directed along the local zi-axis
ElastoDyn['TwHt6TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 6; Directed along the local xi-axis
ElastoDyn['TwHt6TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 6; Directed along the local yi-axis
ElastoDyn['TwHt6TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 6; Directed along the local zi-axis
ElastoDyn['TwHt7TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 7; Directed along the local xi-axis
ElastoDyn['TwHt7TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 7; Directed along the local yi-axis
ElastoDyn['TwHt7TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 7; Directed along the local zi-axis
ElastoDyn['TwHt8TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 8; Directed along the local xi-axis
ElastoDyn['TwHt8TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 8; Directed along the local yi-axis
ElastoDyn['TwHt8TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 8; Directed along the local zi-axis
ElastoDyn['TwHt9TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 9; Directed along the local xi-axis
ElastoDyn['TwHt9TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 9; Directed along the local yi-axis
ElastoDyn['TwHt9TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 9; Directed along the local zi-axis
ElastoDyn['TwHt1RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt1RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt1RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt2RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt2RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt2RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt3RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt3RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt3RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt4RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt4RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt4RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt5RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt5RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt5RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt6RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt6RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt6RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt7RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt7RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt7RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt8RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt8RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt8RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
ElastoDyn['TwHt9RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
ElastoDyn['TwHt9RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
ElastoDyn['TwHt9RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
# Platform Motions
ElastoDyn['PtfmTDxt'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xt-axis
ElastoDyn['PtfmTDyt'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yt-axis
ElastoDyn['PtfmTDzt'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zt-axis
ElastoDyn['PtfmTDxi'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xi-axis
ElastoDyn['PtfmSurge'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xi-axis
ElastoDyn['PtfmTDyi'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yi-axis
ElastoDyn['PtfmSway'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yi-axis
ElastoDyn['PtfmTDzi'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zi-axis
ElastoDyn['PtfmHeave'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zi-axis
ElastoDyn['PtfmTVxt'] = False # (m/s); Platform horizontal surge (translational) velocity; Directed along the xt-axis
ElastoDyn['PtfmTVyt'] = False # (m/s); Platform horizontal sway (translational) velocity; Directed along the yt-axis
ElastoDyn['PtfmTVzt'] = False # (m/s); Platform vertical heave (translational) velocity; Directed along the zt-axis
ElastoDyn['PtfmTVxi'] = False # (m/s); Platform horizontal surge (translational) velocity; Directed along the xi-axis
ElastoDyn['PtfmTVyi'] = False # (m/s); Platform horizontal sway (translational) velocity; Directed along the yi-axis
ElastoDyn['PtfmTVzi'] = False # (m/s); Platform vertical heave (translational) velocity; Directed along the zi-axis
ElastoDyn['PtfmTAxt'] = False # (m/s^2); Platform horizontal surge (translational) acceleration; Directed along the xt-axis
ElastoDyn['PtfmTAyt'] = False # (m/s^2); Platform horizontal sway (translational) acceleration; Directed along the yt-axis
ElastoDyn['PtfmTAzt'] = False # (m/s^2); Platform vertical heave (translational) acceleration; Directed along the zt-axis
ElastoDyn['PtfmTAxi'] = False # (m/s^2); Platform horizontal surge (translational) acceleration; Directed along the xi-axis
ElastoDyn['PtfmTAyi'] = False # (m/s^2); Platform horizontal sway (translational) acceleration; Directed along the yi-axis
ElastoDyn['PtfmTAzi'] = False # (m/s^2); Platform vertical heave (translational) acceleration; Directed along the zi-axis
ElastoDyn['PtfmRDxi'] = False # (deg); Platform roll tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the xi-axis
ElastoDyn['PtfmRoll'] = False # (deg); Platform roll tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the xi-axis
ElastoDyn['PtfmRDyi'] = False # (deg); Platform pitch tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the yi-axis
ElastoDyn['PtfmPitch'] = False # (deg); Platform pitch tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the yi-axis
ElastoDyn['PtfmRDzi'] = False # (deg); Platform yaw angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the zi-axis
ElastoDyn['PtfmYaw'] = False # (deg); Platform yaw angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the zi-axis
ElastoDyn['PtfmRVxt'] = False # (deg/s); Platform roll tilt angular (rotational) velocity; About the xt-axis
ElastoDyn['PtfmRVyt'] = False # (deg/s); Platform pitch tilt angular (rotational) velocity; About the yt-axis
ElastoDyn['PtfmRVzt'] = False # (deg/s); Platform yaw angular (rotational) velocity; About the zt-axis
ElastoDyn['PtfmRVxi'] = False # (deg/s); Platform roll tilt angular (rotational) velocity; About the xi-axis
ElastoDyn['PtfmRVyi'] = False # (deg/s); Platform pitch tilt angular (rotational) velocity; About the yi-axis
ElastoDyn['PtfmRVzi'] = False # (deg/s); Platform yaw angular (rotational) velocity; About the zi-axis
ElastoDyn['PtfmRAxt'] = False # (deg/s^2); Platform roll tilt angular (rotational) acceleration; About the xt-axis
ElastoDyn['PtfmRAyt'] = False # (deg/s^2); Platform pitch tilt angular (rotational) acceleration; About the yt-axis
ElastoDyn['PtfmRAzt'] = False # (deg/s^2); Platform yaw angular (rotational) acceleration; About the zt-axis
ElastoDyn['PtfmRAxi'] = False # (deg/s^2); Platform roll tilt angular (rotational) acceleration; About the xi-axis
ElastoDyn['PtfmRAyi'] = False # (deg/s^2); Platform pitch tilt angular (rotational) acceleration; About the yi-axis
ElastoDyn['PtfmRAzi'] = False # (deg/s^2); Platform yaw angular (rotational) acceleration; About the zi-axis
# Blade 1 Root Loads
ElastoDyn['RootFxc1'] = False # (kN); Blade 1 out-of-plane shear force at the blade root; Directed along the xc1-axis
ElastoDyn['RootFyc1'] = False # (kN); Blade 1 in-plane shear force at the blade root; Directed along the yc1-axis
ElastoDyn['RootFzc1'] = False # (kN); Blade 1 axial force at the blade root; Directed along the zc1- and zb1-axes
ElastoDyn['RootFzb1'] = False # (kN); Blade 1 axial force at the blade root; Directed along the zc1- and zb1-axes
ElastoDyn['RootFxb1'] = False # (kN); Blade 1 flapwise shear force at the blade root; Directed along the xb1-axis
ElastoDyn['RootFyb1'] = False # (kN); Blade 1 edgewise shear force at the blade root; Directed along the yb1-axis
ElastoDyn['RootMxc1'] = False # (kN m); Blade 1 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc1-axis
ElastoDyn['RootMIP1'] = False # (kN m); Blade 1 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc1-axis
ElastoDyn['RootMyc1'] = False # (kN m); Blade 1 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc1-axis
ElastoDyn['RootMOoP1'] = False # (kN m); Blade 1 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc1-axis
ElastoDyn['RootMzc1'] = False # (kN m); Blade 1 pitching moment at the blade root; About the zc1- and zb1-axes
ElastoDyn['RootMzb1'] = False # (kN m); Blade 1 pitching moment at the blade root; About the zc1- and zb1-axes
ElastoDyn['RootMxb1'] = False # (kN m); Blade 1 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb1-axis
ElastoDyn['RootMEdg1'] = False # (kN m); Blade 1 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb1-axis
ElastoDyn['RootMyb1'] = False # (kN m); Blade 1 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb1-axis
ElastoDyn['RootMFlp1'] = False # (kN m); Blade 1 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb1-axis
# Blade 2 Root Loads
ElastoDyn['RootFxc2'] = False # (kN); Blade 2 out-of-plane shear force at the blade root; Directed along the xc2-axis
ElastoDyn['RootFyc2'] = False # (kN); Blade 2 in-plane shear force at the blade root; Directed along the yc2-axis
ElastoDyn['RootFzc2'] = False # (kN); Blade 2 axial force at the blade root; Directed along the zc2- and zb2-axes
ElastoDyn['RootFzb2'] = False # (kN); Blade 2 axial force at the blade root; Directed along the zc2- and zb2-axes
ElastoDyn['RootFxb2'] = False # (kN); Blade 2 flapwise shear force at the blade root; Directed along the xb2-axis
ElastoDyn['RootFyb2'] = False # (kN); Blade 2 edgewise shear force at the blade root; Directed along the yb2-axis
ElastoDyn['RootMxc2'] = False # (kN m); Blade 2 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc2-axis
ElastoDyn['RootMIP2'] = False # (kN m); Blade 2 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc2-axis
ElastoDyn['RootMyc2'] = False # (kN m); Blade 2 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc2-axis
ElastoDyn['RootMOoP2'] = False # (kN m); Blade 2 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc2-axis
ElastoDyn['RootMzc2'] = False # (kN m); Blade 2 pitching moment at the blade root; About the zc2- and zb2-axes
ElastoDyn['RootMzb2'] = False # (kN m); Blade 2 pitching moment at the blade root; About the zc2- and zb2-axes
ElastoDyn['RootMxb2'] = False # (kN m); Blade 2 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb2-axis
ElastoDyn['RootMEdg2'] = False # (kN m); Blade 2 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb2-axis
ElastoDyn['RootMyb2'] = False # (kN m); Blade 2 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb2-axis
ElastoDyn['RootMFlp2'] = False # (kN m); Blade 2 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb2-axis
# Blade 3 Root Loads
ElastoDyn['RootFxc3'] = False # (kN); Blade 3 out-of-plane shear force at the blade root; Directed along the xc3-axis
ElastoDyn['RootFyc3'] = False # (kN); Blade 3 in-plane shear force at the blade root; Directed along the yc3-axis
ElastoDyn['RootFzc3'] = False # (kN); Blade 3 axial force at the blade root; Directed along the zc3- and zb3-axes
ElastoDyn['RootFzb3'] = False # (kN); Blade 3 axial force at the blade root; Directed along the zc3- and zb3-axes
ElastoDyn['RootFxb3'] = False # (kN); Blade 3 flapwise shear force at the blade root; Directed along the xb3-axis
ElastoDyn['RootFyb3'] = False # (kN); Blade 3 edgewise shear force at the blade root; Directed along the yb3-axis
ElastoDyn['RootMxc3'] = False # (kN m); Blade 3 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc3-axis
ElastoDyn['RootMIP3'] = False # (kN m); Blade 3 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc3-axis
ElastoDyn['RootMyc3'] = False # (kN m); Blade 3 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc3-axis
ElastoDyn['RootMOoP3'] = False # (kN m); Blade 3 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc3-axis
ElastoDyn['RootMzc3'] = False # (kN m); Blade 3 pitching moment at the blade root; About the zc3- and zb3-axes
ElastoDyn['RootMzb3'] = False # (kN m); Blade 3 pitching moment at the blade root; About the zc3- and zb3-axes
ElastoDyn['RootMxb3'] = False # (kN m); Blade 3 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb3-axis
ElastoDyn['RootMEdg3'] = False # (kN m); Blade 3 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb3-axis
ElastoDyn['RootMyb3'] = False # (kN m); Blade 3 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb3-axis
ElastoDyn['RootMFlp3'] = False # (kN m); Blade 3 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb3-axis
# Blade 1 Local Span Loads
ElastoDyn['Spn1MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 1; About the local xb1-axis
ElastoDyn['Spn1MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 1; About the local yb1-axis
ElastoDyn['Spn1MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 1; About the local zb1-axis
ElastoDyn['Spn2MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 2; About the local xb1-axis
ElastoDyn['Spn2MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 2; About the local yb1-axis
ElastoDyn['Spn2MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 2; About the local zb1-axis
ElastoDyn['Spn3MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 3; About the local xb1-axis
ElastoDyn['Spn3MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 3; About the local yb1-axis
ElastoDyn['Spn3MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 3; About the local zb1-axis
ElastoDyn['Spn4MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 4; About the local xb1-axis
ElastoDyn['Spn4MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 4; About the local yb1-axis
ElastoDyn['Spn4MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 4; About the local zb1-axis
ElastoDyn['Spn5MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 5; About the local xb1-axis
ElastoDyn['Spn5MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 5; About the local yb1-axis
ElastoDyn['Spn5MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 5; About the local zb1-axis
ElastoDyn['Spn6MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 6; About the local xb1-axis
ElastoDyn['Spn6MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 6; About the local yb1-axis
ElastoDyn['Spn6MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 6; About the local zb1-axis
ElastoDyn['Spn7MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 7; About the local xb1-axis
ElastoDyn['Spn7MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 7; About the local yb1-axis
ElastoDyn['Spn7MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 7; About the local zb1-axis
ElastoDyn['Spn8MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 8; About the local xb1-axis
ElastoDyn['Spn8MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 8; About the local yb1-axis
ElastoDyn['Spn8MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 8; About the local zb1-axis
ElastoDyn['Spn9MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 9; About the local xb1-axis
ElastoDyn['Spn9MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 9; About the local yb1-axis
ElastoDyn['Spn9MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 9; About the local zb1-axis
ElastoDyn['Spn1FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 1; Directed along the local xb1-axis
ElastoDyn['Spn1FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 1; Directed along the local yb1-axis
ElastoDyn['Spn1FLzb1'] = False # (kN); Blade 1 local axial force at span station 1; Directed along the local zb1-axis
ElastoDyn['Spn2FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 2; Directed along the local xb1-axis
ElastoDyn['Spn2FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 2; Directed along the local yb1-axis
ElastoDyn['Spn2FLzb1'] = False # (kN); Blade 1 local axial force at span station 2; Directed along the local zb1-axis
ElastoDyn['Spn3FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 3; Directed along the local xb1-axis
ElastoDyn['Spn3FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 3; Directed along the local yb1-axis
ElastoDyn['Spn3FLzb1'] = False # (kN); Blade 1 local axial force at span station 3; Directed along the local zb1-axis
ElastoDyn['Spn4FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 4; Directed along the local xb1-axis
ElastoDyn['Spn4FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 4; Directed along the local yb1-axis
ElastoDyn['Spn4FLzb1'] = False # (kN); Blade 1 local axial force at span station 4; Directed along the local zb1-axis
ElastoDyn['Spn5FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 5; Directed along the local xb1-axis
ElastoDyn['Spn5FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 5; Directed along the local yb1-axis
ElastoDyn['Spn5FLzb1'] = False # (kN); Blade 1 local axial force at span station 5; Directed along the local zb1-axis
ElastoDyn['Spn6FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 6; Directed along the local xb1-axis
ElastoDyn['Spn6FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 6; Directed along the local yb1-axis
ElastoDyn['Spn6FLzb1'] = False # (kN); Blade 1 local axial force at span station 6; Directed along the local zb1-axis
ElastoDyn['Spn7FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 7; Directed along the local xb1-axis
ElastoDyn['Spn7FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 7; Directed along the local yb1-axis
ElastoDyn['Spn7FLzb1'] = False # (kN); Blade 1 local axial force at span station 7; Directed along the local zb1-axis
ElastoDyn['Spn8FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 8; Directed along the local xb1-axis
ElastoDyn['Spn8FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 8; Directed along the local yb1-axis
ElastoDyn['Spn8FLzb1'] = False # (kN); Blade 1 local axial force at span station 8; Directed along the local zb1-axis
ElastoDyn['Spn9FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 9; Directed along the local xb1-axis
ElastoDyn['Spn9FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 9; Directed along the local yb1-axis
ElastoDyn['Spn9FLzb1'] = False # (kN); Blade 1 local axial force at span station 9; Directed along the local zb1-axis
# Blade 2 Local Span Loads
ElastoDyn['Spn1MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 1; About the local xb2-axis
ElastoDyn['Spn1MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 1; About the local yb2-axis
ElastoDyn['Spn1MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 1; About the local zb2-axis
ElastoDyn['Spn2MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 2; About the local xb2-axis
ElastoDyn['Spn2MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 2; About the local yb2-axis
ElastoDyn['Spn2MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 2; About the local zb2-axis
ElastoDyn['Spn3MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 3; About the local xb2-axis
ElastoDyn['Spn3MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 3; About the local yb2-axis
ElastoDyn['Spn3MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 3; About the local zb2-axis
ElastoDyn['Spn4MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 4; About the local xb2-axis
ElastoDyn['Spn4MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 4; About the local yb2-axis
ElastoDyn['Spn4MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 4; About the local zb2-axis
ElastoDyn['Spn5MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 5; About the local xb2-axis
ElastoDyn['Spn5MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 5; About the local yb2-axis
ElastoDyn['Spn5MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 5; About the local zb2-axis
ElastoDyn['Spn6MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 6; About the local xb2-axis
ElastoDyn['Spn6MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 6; About the local yb2-axis
ElastoDyn['Spn6MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 6; About the local zb2-axis
ElastoDyn['Spn7MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 7; About the local xb2-axis
ElastoDyn['Spn7MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 7; About the local yb2-axis
ElastoDyn['Spn7MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 7; About the local zb2-axis
ElastoDyn['Spn8MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 8; About the local xb2-axis
ElastoDyn['Spn8MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 8; About the local yb2-axis
ElastoDyn['Spn8MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 8; About the local zb2-axis
ElastoDyn['Spn9MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 9; About the local xb2-axis
ElastoDyn['Spn9MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 9; About the local yb2-axis
ElastoDyn['Spn9MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 9; About the local zb2-axis
ElastoDyn['Spn1FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 1; Directed along the local xb2-axis
ElastoDyn['Spn1FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 1; Directed along the local yb2-axis
ElastoDyn['Spn1FLzb2'] = False # (kN); Blade 2 local axial force at span station 1; Directed along the local zb2-axis
ElastoDyn['Spn2FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 2; Directed along the local xb2-axis
ElastoDyn['Spn2FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 2; Directed along the local yb2-axis
ElastoDyn['Spn2FLzb2'] = False # (kN); Blade 2 local axial force at span station 2; Directed along the local zb2-axis
ElastoDyn['Spn3FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 3; Directed along the local xb2-axis
ElastoDyn['Spn3FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 3; Directed along the local yb2-axis
ElastoDyn['Spn3FLzb2'] = False # (kN); Blade 2 local axial force at span station 3; Directed along the local zb2-axis
ElastoDyn['Spn4FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 4; Directed along the local xb2-axis
ElastoDyn['Spn4FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 4; Directed along the local yb2-axis
ElastoDyn['Spn4FLzb2'] = False # (kN); Blade 2 local axial force at span station 4; Directed along the local zb2-axis
ElastoDyn['Spn5FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 5; Directed along the local xb2-axis
ElastoDyn['Spn5FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 5; Directed along the local yb2-axis
ElastoDyn['Spn5FLzb2'] = False # (kN); Blade 2 local axial force at span station 5; Directed along the local zb2-axis
ElastoDyn['Spn6FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 6; Directed along the local xb2-axis
ElastoDyn['Spn6FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 6; Directed along the local yb2-axis
ElastoDyn['Spn6FLzb2'] = False # (kN); Blade 2 local axial force at span station 6; Directed along the local zb2-axis
ElastoDyn['Spn7FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 7; Directed along the local xb2-axis
ElastoDyn['Spn7FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 7; Directed along the local yb2-axis
ElastoDyn['Spn7FLzb2'] = False # (kN); Blade 2 local axial force at span station 7; Directed along the local zb2-axis
ElastoDyn['Spn8FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 8; Directed along the local xb2-axis
ElastoDyn['Spn8FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 8; Directed along the local yb2-axis
ElastoDyn['Spn8FLzb2'] = False # (kN); Blade 2 local axial force at span station 8; Directed along the local zb2-axis
ElastoDyn['Spn9FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 9; Directed along the local xb2-axis
ElastoDyn['Spn9FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 9; Directed along the local yb2-axis
ElastoDyn['Spn9FLzb2'] = False # (kN); Blade 2 local axial force at span station 9; Directed along the local zb2-axis
# Blade 3 Local Span Loads
ElastoDyn['Spn1MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 1; About the local xb3-axis
ElastoDyn['Spn1MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 1; About the local yb3-axis
ElastoDyn['Spn1MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 1; About the local zb3-axis
ElastoDyn['Spn2MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 2; About the local xb3-axis
ElastoDyn['Spn2MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 2; About the local yb3-axis
ElastoDyn['Spn2MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 2; About the local zb3-axis
ElastoDyn['Spn3MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 3; About the local xb3-axis
ElastoDyn['Spn3MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 3; About the local yb3-axis
ElastoDyn['Spn3MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 3; About the local zb3-axis
ElastoDyn['Spn4MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 4; About the local xb3-axis
ElastoDyn['Spn4MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 4; About the local yb3-axis
ElastoDyn['Spn4MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 4; About the local zb3-axis
ElastoDyn['Spn5MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 5; About the local xb3-axis
ElastoDyn['Spn5MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 5; About the local yb3-axis
ElastoDyn['Spn5MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 5; About the local zb3-axis
ElastoDyn['Spn6MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 6; About the local xb3-axis
ElastoDyn['Spn6MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 6; About the local yb3-axis
ElastoDyn['Spn6MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 6; About the local zb3-axis
ElastoDyn['Spn7MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 7; About the local xb3-axis
ElastoDyn['Spn7MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 7; About the local yb3-axis
ElastoDyn['Spn7MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 7; About the local zb3-axis
ElastoDyn['Spn8MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 8; About the local xb3-axis
ElastoDyn['Spn8MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 8; About the local yb3-axis
ElastoDyn['Spn8MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 8; About the local zb3-axis
ElastoDyn['Spn9MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 9; About the local xb3-axis
ElastoDyn['Spn9MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 9; About the local yb3-axis
ElastoDyn['Spn9MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 9; About the local zb3-axis
ElastoDyn['Spn1FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 1; Directed along the local xb3-axis
ElastoDyn['Spn1FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 1; Directed along the local yb3-axis
ElastoDyn['Spn1FLzb3'] = False # (kN); Blade 3 local axial force at span station 1; Directed along the local zb3-axis
ElastoDyn['Spn2FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 2; Directed along the local xb3-axis
ElastoDyn['Spn2FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 2; Directed along the local yb3-axis
ElastoDyn['Spn2FLzb3'] = False # (kN); Blade 3 local axial force at span station 2; Directed along the local zb3-axis
ElastoDyn['Spn3FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 3; Directed along the local xb3-axis
ElastoDyn['Spn3FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 3; Directed along the local yb3-axis
ElastoDyn['Spn3FLzb3'] = False # (kN); Blade 3 local axial force at span station 3; Directed along the local zb3-axis
ElastoDyn['Spn4FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 4; Directed along the local xb3-axis
ElastoDyn['Spn4FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 4; Directed along the local yb3-axis
ElastoDyn['Spn4FLzb3'] = False # (kN); Blade 3 local axial force at span station 4; Directed along the local zb3-axis
ElastoDyn['Spn5FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 5; Directed along the local xb3-axis
ElastoDyn['Spn5FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 5; Directed along the local yb3-axis
ElastoDyn['Spn5FLzb3'] = False # (kN); Blade 3 local axial force at span station 5; Directed along the local zb3-axis
ElastoDyn['Spn6FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 6; Directed along the local xb3-axis
ElastoDyn['Spn6FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 6; Directed along the local yb3-axis
ElastoDyn['Spn6FLzb3'] = False # (kN); Blade 3 local axial force at span station 6; Directed along the local zb3-axis
ElastoDyn['Spn7FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 7; Directed along the local xb3-axis
ElastoDyn['Spn7FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 7; Directed along the local yb3-axis
ElastoDyn['Spn7FLzb3'] = False # (kN); Blade 3 local axial force at span station 7; Directed along the local zb3-axis
ElastoDyn['Spn8FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 8; Directed along the local xb3-axis
ElastoDyn['Spn8FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 8; Directed along the local yb3-axis
ElastoDyn['Spn8FLzb3'] = False # (kN); Blade 3 local axial force at span station 8; Directed along the local zb3-axis
ElastoDyn['Spn9FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 9; Directed along the local xb3-axis
ElastoDyn['Spn9FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 9; Directed along the local yb3-axis
ElastoDyn['Spn9FLzb3'] = False # (kN); Blade 3 local axial force at span station 9; Directed along the local zb3-axis
# Hub and Rotor Loads
ElastoDyn['LSShftFxa'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
ElastoDyn['LSShftFxs'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
ElastoDyn['LSSGagFxa'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
ElastoDyn['LSSGagFxs'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
ElastoDyn['RotThrust'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
ElastoDyn['LSShftFya'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the ya-axis
ElastoDyn['LSSGagFya'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the ya-axis
ElastoDyn['LSShftFza'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the za-axis
ElastoDyn['LSSGagFza'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the za-axis
ElastoDyn['LSShftFys'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the ys-axis
ElastoDyn['LSSGagFys'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the ys-axis
ElastoDyn['LSShftFzs'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the zs-axis
ElastoDyn['LSSGagFzs'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the zs-axis
ElastoDyn['LSShftMxa'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['LSShftMxs'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['LSSGagMxa'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['LSSGagMxs'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['RotTorq'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['LSShftTq'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
ElastoDyn['LSSTipMya'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the ya-axis
ElastoDyn['LSSTipMza'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the za-axis
ElastoDyn['LSSTipMys'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the ys-axis
ElastoDyn['LSSTipMzs'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the zs-axis
ElastoDyn['RotPwr'] = False # (kW); Rotor power (this is equivalent to the low-speed shaft power); N/A
ElastoDyn['LSShftPwr'] = False # (kW); Rotor power (this is equivalent to the low-speed shaft power); N/A
# Shaft Strain Gage Loads
ElastoDyn['LSSGagMya'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the ya-axis
ElastoDyn['LSSGagMza'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the za-axis
ElastoDyn['LSSGagMys'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the ys-axis
ElastoDyn['LSSGagMzs'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the zs-axis
# High-Speed Shaft Loads
ElastoDyn['HSShftTq'] = False # (kN m); High-speed shaft torque (this is constant along the shaft); Same sign as LSShftTq / RotTorq / LSShftMxa / LSShftMxs / LSSGagMxa / LSSGagMxs
ElastoDyn['HSSBrTq'] = False # (kN m); High-speed shaft brake torque (i.e., the actual moment applied to the high-speed shaft by the brake); Always positive (indicating dissipation of power)
ElastoDyn['HSShftPwr'] = False # (kW); High-speed shaft power; Same sign as HSShftTq
# Rotor-Furl Bearing Loads
ElastoDyn['RFrlBrM'] = False # (kN m); Rotor-furl bearing moment; About the rotor-furl axis
# Tail-Furl Bearing Loads
ElastoDyn['TFrlBrM'] = False # (kN m); Tail-furl bearing moment; About the tail-furl axis
# Tower-Top / Yaw Bearing Loads
ElastoDyn['YawBrFxn'] = False # (kN); Rotating (with nacelle) tower-top / yaw bearing shear force; Directed along the xn-axis
ElastoDyn['YawBrFyn'] = False # (kN); Rotating (with nacelle) tower-top / yaw bearing shear force; Directed along the yn-axis
ElastoDyn['YawBrFzn'] = False # (kN); Tower-top / yaw bearing axial force; Directed along the zn- and zp-axes
ElastoDyn['YawBrFzp'] = False # (kN); Tower-top / yaw bearing axial force; Directed along the zn- and zp-axes
ElastoDyn['YawBrFxp'] = False # (kN); Tower-top / yaw bearing fore-aft (nonrotating) shear force; Directed along the xp-axis
ElastoDyn['YawBrFyp'] = False # (kN); Tower-top / yaw bearing side-to-side (nonrotating) shear force; Directed along the yp-axis
ElastoDyn['YawBrMxn'] = False # (kN m); Rotating (with nacelle) tower-top / yaw bearing roll moment; About the xn-axis
ElastoDyn['YawBrMyn'] = False # (kN m); Rotating (with nacelle) tower-top / yaw bearing pitch moment; About the yn-axis
ElastoDyn['YawBrMzn'] = False # (kN m); Tower-top / yaw bearing yaw moment; About the zn- and zp-axes
ElastoDyn['YawBrMzp'] = False # (kN m); Tower-top / yaw bearing yaw moment; About the zn- and zp-axes
ElastoDyn['YawBrMxp'] = False # (kN m); Nonrotating tower-top / yaw bearing roll moment; About the xp-axis
ElastoDyn['YawBrMyp'] = False # (kN m); Nonrotating tower-top / yaw bearing pitch moment; About the yp-axis
# Tower Base Loads
ElastoDyn['TwrBsFxt'] = False # (kN); Tower base fore-aft shear force; Directed along the xt-axis
ElastoDyn['TwrBsFyt'] = False # (kN); Tower base side-to-side shear force; Directed along the yt-axis
ElastoDyn['TwrBsFzt'] = False # (kN); Tower base axial force; Directed along the zt-axis
ElastoDyn['TwrBsMxt'] = False # (kN m); Tower base roll (or side-to-side) moment (i.e., the moment caused by side-to-side forces); About the xt-axis
ElastoDyn['TwrBsMyt'] = False # (kN m); Tower base pitching (or fore-aft) moment (i.e., the moment caused by fore-aft forces); About the yt-axis
ElastoDyn['TwrBsMzt'] = False # (kN m); Tower base yaw (or torsional) moment; About the zt-axis
# Local Tower Loads
ElastoDyn['TwHt1MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 1; About the local xt-axis
ElastoDyn['TwHt1MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 1; About the local yt-axis
ElastoDyn['TwHt1MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 1; About the local zt-axis
ElastoDyn['TwHt2MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 2; About the local xt-axis
ElastoDyn['TwHt2MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 2; About the local yt-axis
ElastoDyn['TwHt2MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 2; About the local zt-axis
ElastoDyn['TwHt3MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 3; About the local xt-axis
ElastoDyn['TwHt3MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 3; About the local yt-axis
ElastoDyn['TwHt3MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 3; About the local zt-axis
ElastoDyn['TwHt4MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 4; About the local xt-axis
ElastoDyn['TwHt4MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 4; About the local yt-axis
ElastoDyn['TwHt4MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 4; About the local zt-axis
ElastoDyn['TwHt5MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 5; About the local xt-axis
ElastoDyn['TwHt5MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 5; About the local yt-axis
ElastoDyn['TwHt5MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 5; About the local zt-axis
ElastoDyn['TwHt6MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 6; About the local xt-axis
ElastoDyn['TwHt6MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 6; About the local yt-axis
ElastoDyn['TwHt6MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 6; About the local zt-axis
ElastoDyn['TwHt7MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 7; About the local xt-axis
ElastoDyn['TwHt7MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 7; About the local yt-axis
ElastoDyn['TwHt7MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 7; About the local zt-axis
ElastoDyn['TwHt8MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 8; About the local xt-axis
ElastoDyn['TwHt8MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 8; About the local yt-axis
ElastoDyn['TwHt8MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 8; About the local zt-axis
ElastoDyn['TwHt9MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 9; About the local xt-axis
ElastoDyn['TwHt9MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 9; About the local yt-axis
ElastoDyn['TwHt9MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 9; About the local zt-axis
ElastoDyn['TwHt1FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 1; About the local xt-axis
ElastoDyn['TwHt1FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 1; About the local yt-axis
ElastoDyn['TwHt1FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 1; About the local zt-axis
ElastoDyn['TwHt2FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 2; About the local xt-axis
ElastoDyn['TwHt2FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 2; About the local yt-axis
ElastoDyn['TwHt2FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 2; About the local zt-axis
ElastoDyn['TwHt3FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 3; About the local xt-axis
ElastoDyn['TwHt3FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 3; About the local yt-axis
ElastoDyn['TwHt3FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 3; About the local zt-axis
ElastoDyn['TwHt4FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 4; About the local xt-axis
ElastoDyn['TwHt4FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 4; About the local yt-axis
ElastoDyn['TwHt4FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 4; About the local zt-axis
ElastoDyn['TwHt5FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 5; About the local xt-axis
ElastoDyn['TwHt5FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 5; About the local yt-axis
ElastoDyn['TwHt5FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 5; About the local zt-axis
ElastoDyn['TwHt6FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 6; About the local xt-axis
ElastoDyn['TwHt6FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 6; About the local yt-axis
ElastoDyn['TwHt6FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 6; About the local zt-axis
ElastoDyn['TwHt7FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 7; About the local xt-axis
ElastoDyn['TwHt7FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 7; About the local yt-axis
ElastoDyn['TwHt7FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 7; About the local zt-axis
ElastoDyn['TwHt8FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 8; About the local xt-axis
ElastoDyn['TwHt8FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 8; About the local yt-axis
ElastoDyn['TwHt8FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 8; About the local zt-axis
ElastoDyn['TwHt9FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 9; About the local xt-axis
ElastoDyn['TwHt9FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 9; About the local yt-axis
ElastoDyn['TwHt9FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 9; About the local zt-axis
# Internal Degrees of Freedom
ElastoDyn['Q_B1E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 1;
ElastoDyn['Q_B2E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 2;
ElastoDyn['Q_B3E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 3;
ElastoDyn['Q_B1F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 1;
ElastoDyn['Q_B2F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 2;
ElastoDyn['Q_B3F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 3;
ElastoDyn['Q_B1F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 1;
ElastoDyn['Q_B2F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 2;
ElastoDyn['Q_B3F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 3;
ElastoDyn['Q_Teet'] = False # (rad); Displacement of hub teetering DOF;
ElastoDyn['Q_DrTr'] = False # (rad); Displacement of drivetrain rotational-flexibility DOF;
ElastoDyn['Q_GeAz'] = False # (rad); Displacement of variable speed generator DOF;
ElastoDyn['Q_RFrl'] = False # (rad); Displacement of rotor-furl DOF;
ElastoDyn['Q_TFrl'] = False # (rad); Displacement of tail-furl DOF;
ElastoDyn['Q_Yaw'] = False # (rad); Displacement of nacelle yaw DOF;
ElastoDyn['Q_TFA1'] = False # (m); Displacement of 1st tower fore-aft bending mode DOF;
ElastoDyn['Q_TSS1'] = False # (m); Displacement of 1st tower side-to-side bending mode DOF;
ElastoDyn['Q_TFA2'] = False # (m); Displacement of 2nd tower fore-aft bending mode DOF;
ElastoDyn['Q_TSS2'] = False # (m); Displacement of 2nd tower side-to-side bending mode DOF;
ElastoDyn['Q_Sg'] = False # (m); Displacement of platform horizontal surge translation DOF;
ElastoDyn['Q_Sw'] = False # (m); Displacement of platform horizontal sway translation DOF;
ElastoDyn['Q_Hv'] = False # (m); Displacement of platform vertical heave translation DOF;
ElastoDyn['Q_R'] = False # (rad); Displacement of platform roll tilt rotation DOF;
ElastoDyn['Q_P'] = False # (rad); Displacement of platform pitch tilt rotation DOF;
ElastoDyn['Q_Y'] = False # (rad); Displacement of platform yaw rotation DOF;
ElastoDyn['QD_B1E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 1;
ElastoDyn['QD_B2E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 2;
ElastoDyn['QD_B3E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 3;
ElastoDyn['QD_B1F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 1;
ElastoDyn['QD_B2F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 2;
ElastoDyn['QD_B3F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 3;
ElastoDyn['QD_B1F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 1;
ElastoDyn['QD_B2F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 2;
ElastoDyn['QD_B3F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 3;
ElastoDyn['QD_Teet'] = False # (rad/s); Velocity of hub teetering DOF;
ElastoDyn['QD_DrTr'] = False # (rad/s); Velocity of drivetrain rotational-flexibility DOF;
ElastoDyn['QD_GeAz'] = False # (rad/s); Velocity of variable speed generator DOF;
ElastoDyn['QD_RFrl'] = False # (rad/s); Velocity of rotor-furl DOF;
ElastoDyn['QD_TFrl'] = False # (rad/s); Velocity of tail-furl DOF;
ElastoDyn['QD_Yaw'] = False # (rad/s); Velocity of nacelle yaw DOF;
ElastoDyn['QD_TFA1'] = False # (m/s); Velocity of 1st tower fore-aft bending mode DOF;
ElastoDyn['QD_TSS1'] = False # (m/s); Velocity of 1st tower side-to-side bending mode DOF;
ElastoDyn['QD_TFA2'] = False # (m/s); Velocity of 2nd tower fore-aft bending mode DOF;
ElastoDyn['QD_TSS2'] = False # (m/s); Velocity of 2nd tower side-to-side bending mode DOF;
ElastoDyn['QD_Sg'] = False # (m/s); Velocity of platform horizontal surge translation DOF;
ElastoDyn['QD_Sw'] = False # (m/s); Velocity of platform horizontal sway translation DOF;
ElastoDyn['QD_Hv'] = False # (m/s); Velocity of platform vertical heave translation DOF;
ElastoDyn['QD_R'] = False # (rad/s); Velocity of platform roll tilt rotation DOF;
ElastoDyn['QD_P'] = False # (rad/s); Velocity of platform pitch tilt rotation DOF;
ElastoDyn['QD_Y'] = False # (rad/s); Velocity of platform yaw rotation DOF;
ElastoDyn['QD2_B1E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 1;
ElastoDyn['QD2_B2E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 2;
ElastoDyn['QD2_B3E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 3;
ElastoDyn['QD2_B1F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 1;
ElastoDyn['QD2_B2F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 2;
ElastoDyn['QD2_B3F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 3;
ElastoDyn['QD2_B1F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 1;
ElastoDyn['QD2_B2F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 2;
ElastoDyn['QD2_B3F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 3;
ElastoDyn['QD2_Teet'] = False # (rad/s^2); Acceleration of hub teetering DOF;
ElastoDyn['QD2_DrTr'] = False # (rad/s^2); Acceleration of drivetrain rotational-flexibility DOF;
ElastoDyn['QD2_GeAz'] = False # (rad/s^2); Acceleration of variable speed generator DOF;
ElastoDyn['QD2_RFrl'] = False # (rad/s^2); Acceleration of rotor-furl DOF;
ElastoDyn['QD2_TFrl'] = False # (rad/s^2); Acceleration of tail-furl DOF;
ElastoDyn['QD2_Yaw'] = False # (rad/s^2); Acceleration of nacelle yaw DOF;
ElastoDyn['QD2_TFA1'] = False # (m/s^2); Acceleration of 1st tower fore-aft bending mode DOF;
ElastoDyn['QD2_TSS1'] = False # (m/s^2); Acceleration of 1st tower side-to-side bending mode DOF;
ElastoDyn['QD2_TFA2'] = False # (m/s^2); Acceleration of 2nd tower fore-aft bending mode DOF;
ElastoDyn['QD2_TSS2'] = False # (m/s^2); Acceleration of 2nd tower side-to-side bending mode DOF;
ElastoDyn['QD2_Sg'] = False # (m/s^2); Acceleration of platform horizontal surge translation DOF;
ElastoDyn['QD2_Sw'] = False # (m/s^2); Acceleration of platform horizontal sway translation DOF;
ElastoDyn['QD2_Hv'] = False # (m/s^2); Acceleration of platform vertical heave translation DOF;
ElastoDyn['QD2_R'] = False # (rad/s^2); Acceleration of platform roll tilt rotation DOF;
ElastoDyn['QD2_P'] = False # (rad/s^2); Acceleration of platform pitch tilt rotation DOF;
ElastoDyn['QD2_Y'] = False # (rad/s^2); Acceleration of platform yaw rotation DOF;
""" BeamDyn """
BeamDyn = {}
# Reaction Loads
BeamDyn['RootFxr'] = False # (N); x-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootFyr'] = False # (N); y-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootFzr'] = False # (N); z-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMxr'] = False # (N-m); x-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMyr'] = False # (N-m); y-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMzr'] = False # (N-m); z-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
# Tip Motions
BeamDyn['TipTDxr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTDyr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTDzr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDxr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDyr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDzr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTVXg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTVYg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTVZg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVXg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVYg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVZg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTAXl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipTAYl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipTAZl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAXl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAYl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAZl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
# Sectional Loads
BeamDyn['N1Fxl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Fyl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Fzl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fxl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fyl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fzl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fxl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fyl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fzl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fxl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fyl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fzl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fxl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fyl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fzl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fxl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fyl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fzl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fxl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fyl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fzl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fxl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fyl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fzl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fxl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fyl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fzl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Mxl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Myl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Mzl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Mxl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Myl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Mzl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Mxl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Myl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Mzl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Mxl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Myl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Mzl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Mxl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Myl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Mzl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Mxl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Myl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Mzl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Mxl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Myl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Mzl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Mxl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Myl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Mzl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Mxl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Myl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Mzl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Sectional Motions
BeamDyn['N1TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Applied Loads
BeamDyn['N1PFxl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PFyl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PFzl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFxl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFyl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFzl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFxl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFyl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFzl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFxl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFyl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFzl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFxl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFyl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFzl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFxl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFyl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFzl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFxl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFyl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFzl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFxl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFyl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFzl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFxl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFyl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFzl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMxl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMyl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMzl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMxl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMyl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMzl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMxl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMyl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMzl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMxl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMyl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMzl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMxl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMyl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMzl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMxl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMyl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMzl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMxl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMyl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMzl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMxl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMyl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMzl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMxl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMyl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMzl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFxl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFyl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFzl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFxl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFyl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFzl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFxl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFyl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFzl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFxl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFyl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFzl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFxl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFyl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFzl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFxl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFyl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFzl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFxl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFyl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFzl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFxl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFyl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFzl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFxl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFyl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFzl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMxl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMyl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMzl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMxl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMyl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMzl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMxl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMyl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMzl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMxl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMyl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMzl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMxl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMyl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMzl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMxl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMyl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMzl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMxl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMyl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMzl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMxl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMyl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMzl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMxl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMyl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMzl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Pitch Actuator
BeamDyn['PAngInp'] = False # (deg); Pitch angle input;
BeamDyn['PAngAct'] = False # (deg); Actual pitch angle ;
BeamDyn['PRatAct'] = False # (deg/s); Actual pitch rate;
BeamDyn['PAccAct'] = False # (deg/s^2); Actual pitch acceleration;
""" ServoDyn """
ServoDyn = {}
# Pitch Control
ServoDyn['BlPitchC1'] = False # (deg); Blade 1 pitch angle command; Positive towards feather about the minus zc1- and minus zb1-axes
ServoDyn['BlPitchC2'] = False # (deg); Blade 2 pitch angle command; Positive towards feather about the minus zc2- and minus zb2-axes
ServoDyn['BlPitchC3'] = False # (deg); Blade 3 pitch angle command; Positive towards feather about the minus zc3- and minus zb3-axes
# Generator and Torque Control
ServoDyn['GenTq'] = False # (kN m); Electrical generator torque; Positive reflects power extracted and negative represents a motoring-up situation (power input)
ServoDyn['GenPwr'] = False # (kW); Electrical generator power; Same sign as GenTq
# High Speed Shaft Brake
ServoDyn['HSSBrTqC'] = False # (kN m); High-speed shaft brake torque command (i.e., the commanded moment applied to the high-speed shaft by the brake); Always positive (indicating dissipation of power)
# Nacelle Yaw Control
ServoDyn['YawMomCom'] = False # (kN m); Nacelle yaw moment command; About the zn- and zp-axes
ServoDyn['YawMom'] = False # (kN m); Nacelle yaw moment command; About the zn- and zp-axes
# Nacelle Tuned Mass Damper (TMD)
ServoDyn['NTMD_XQ'] = False # (m); Nacelle X TMD position (displacement); Relative to rest position
ServoDyn['NTMD_XQD'] = False # (m/s); Nacelle X TMD velocity; Relative to nacelle
ServoDyn['NTMD_YQ'] = False # (m); Nacelle Y TMD position (displacement); Relative to rest position
ServoDyn['NTMD_YQD'] = False # (m/s); Nacelle Y TMD velocity; Relative to nacelle
# Tower Tuned Mass Damper (TMD)
ServoDyn['TTMD_XQ'] = False # (m); Tower X TMD position (displacement); Relative to rest position
ServoDyn['TTMD_XQD'] = False # (m/s); Tower X TMD velocity; Relative to tower
ServoDyn['TTMD_YQ'] = False # (m); Tower Y TMD position (displacement); Relative to rest position
ServoDyn['TTMD_YQD'] = False # (m/s); Tower Y TMD velocity; Relative to tower
# Flap outputs
ServoDyn['BLFLAP1'] = False # (m/s); Tower Y TMD velocity; Relative to tower
ServoDyn['BLFLAP2'] = False # (m/s); Tower Y TMD velocity; Relative to tower
ServoDyn['BLFLAP3'] = False # (m/s); Tower Y TMD velocity; Relative to tower
""" AeroDyn """
AeroDyn = {}
# Tower
AeroDyn['TwN1VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 1; local tower coordinate system
AeroDyn['TwN1VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 1; local tower coordinate system
AeroDyn['TwN1VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 1; local tower coordinate system
AeroDyn['TwN2VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 2; local tower coordinate system
AeroDyn['TwN2VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 2; local tower coordinate system
AeroDyn['TwN2VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 2; local tower coordinate system
AeroDyn['TwN3VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 3; local tower coordinate system
AeroDyn['TwN3VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 3; local tower coordinate system
AeroDyn['TwN3VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 3; local tower coordinate system
AeroDyn['TwN4VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 4; local tower coordinate system
AeroDyn['TwN4VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 4; local tower coordinate system
AeroDyn['TwN4VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 4; local tower coordinate system
AeroDyn['TwN5VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 5; local tower coordinate system
AeroDyn['TwN5VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 5; local tower coordinate system
AeroDyn['TwN5VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 5; local tower coordinate system
AeroDyn['TwN6VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 6; local tower coordinate system
AeroDyn['TwN6VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 6; local tower coordinate system
AeroDyn['TwN6VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 6; local tower coordinate system
AeroDyn['TwN7VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 7; local tower coordinate system
AeroDyn['TwN7VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 7; local tower coordinate system
AeroDyn['TwN7VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 7; local tower coordinate system
AeroDyn['TwN8VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 8; local tower coordinate system
AeroDyn['TwN8VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 8; local tower coordinate system
AeroDyn['TwN8VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 8; local tower coordinate system
AeroDyn['TwN9VUndx'] = False # (m/s); Undisturbed x-component wind velocity at Tw node 9; local tower coordinate system
AeroDyn['TwN9VUndy'] = False # (m/s); Undisturbed y-component wind velocity at Tw node 9; local tower coordinate system
AeroDyn['TwN9VUndz'] = False # (m/s); Undisturbed z-component wind velocity at Tw node 9; local tower coordinate system
AeroDyn['TwN1STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 1; local tower coordinate system
AeroDyn['TwN1STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 1; local tower coordinate system
AeroDyn['TwN1STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 1; local tower coordinate system
AeroDyn['TwN2STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 2; local tower coordinate system
AeroDyn['TwN2STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 2; local tower coordinate system
AeroDyn['TwN2STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 2; local tower coordinate system
AeroDyn['TwN3STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 3; local tower coordinate system
AeroDyn['TwN3STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 3; local tower coordinate system
AeroDyn['TwN3STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 3; local tower coordinate system
AeroDyn['TwN4STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 4; local tower coordinate system
AeroDyn['TwN4STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 4; local tower coordinate system
AeroDyn['TwN4STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 4; local tower coordinate system
AeroDyn['TwN5STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 5; local tower coordinate system
AeroDyn['TwN5STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 5; local tower coordinate system
AeroDyn['TwN5STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 5; local tower coordinate system
AeroDyn['TwN6STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 6; local tower coordinate system
AeroDyn['TwN6STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 6; local tower coordinate system
AeroDyn['TwN6STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 6; local tower coordinate system
AeroDyn['TwN7STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 7; local tower coordinate system
AeroDyn['TwN7STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 7; local tower coordinate system
AeroDyn['TwN7STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 7; local tower coordinate system
AeroDyn['TwN8STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 8; local tower coordinate system
AeroDyn['TwN8STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 8; local tower coordinate system
AeroDyn['TwN8STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 8; local tower coordinate system
AeroDyn['TwN9STVx'] = False # (m/s); Structural translational velocity x-component at Tw node 9; local tower coordinate system
AeroDyn['TwN9STVy'] = False # (m/s); Structural translational velocity y-component at Tw node 9; local tower coordinate system
AeroDyn['TwN9STVz'] = False # (m/s); Structural translational velocity z-component at Tw node 9; local tower coordinate system
AeroDyn['TwN1Vrel'] = False # (m/s); Relative wind speed at Tw node 1;
AeroDyn['TwN2Vrel'] = False # (m/s); Relative wind speed at Tw node 2;
AeroDyn['TwN3Vrel'] = False # (m/s); Relative wind speed at Tw node 3;
AeroDyn['TwN4Vrel'] = False # (m/s); Relative wind speed at Tw node 4;
AeroDyn['TwN5Vrel'] = False # (m/s); Relative wind speed at Tw node 5;
AeroDyn['TwN6Vrel'] = False # (m/s); Relative wind speed at Tw node 6;
AeroDyn['TwN7Vrel'] = False # (m/s); Relative wind speed at Tw node 7;
AeroDyn['TwN8Vrel'] = False # (m/s); Relative wind speed at Tw node 8;
AeroDyn['TwN9Vrel'] = False # (m/s); Relative wind speed at Tw node 9;
AeroDyn['TwN1DynP'] = False # (Pa); Dynamic Pressure at Tw node 1;
AeroDyn['TwN2DynP'] = False # (Pa); Dynamic Pressure at Tw node 2;
AeroDyn['TwN3DynP'] = False # (Pa); Dynamic Pressure at Tw node 3;
AeroDyn['TwN4DynP'] = False # (Pa); Dynamic Pressure at Tw node 4;
AeroDyn['TwN5DynP'] = False # (Pa); Dynamic Pressure at Tw node 5;
AeroDyn['TwN6DynP'] = False # (Pa); Dynamic Pressure at Tw node 6;
AeroDyn['TwN7DynP'] = False # (Pa); Dynamic Pressure at Tw node 7;
AeroDyn['TwN8DynP'] = False # (Pa); Dynamic Pressure at Tw node 8;
AeroDyn['TwN9DynP'] = False # (Pa); Dynamic Pressure at Tw node 9;
AeroDyn['TwN1Re'] = False # (-); Reynolds number (in millions) at Tw node 1;
AeroDyn['TwN2Re'] = False # (-); Reynolds number (in millions) at Tw node 2;
AeroDyn['TwN3Re'] = False # (-); Reynolds number (in millions) at Tw node 3;
AeroDyn['TwN4Re'] = False # (-); Reynolds number (in millions) at Tw node 4;
AeroDyn['TwN5Re'] = False # (-); Reynolds number (in millions) at Tw node 5;
AeroDyn['TwN6Re'] = False # (-); Reynolds number (in millions) at Tw node 6;
AeroDyn['TwN7Re'] = False # (-); Reynolds number (in millions) at Tw node 7;
AeroDyn['TwN8Re'] = False # (-); Reynolds number (in millions) at Tw node 8;
AeroDyn['TwN9Re'] = False # (-); Reynolds number (in millions) at Tw node 9;
AeroDyn['TwN1M'] = False # (-); Mach number at Tw node 1;
AeroDyn['TwN2M'] = False # (-); Mach number at Tw node 2;
AeroDyn['TwN3M'] = False # (-); Mach number at Tw node 3;
AeroDyn['TwN4M'] = False # (-); Mach number at Tw node 4;
AeroDyn['TwN5M'] = False # (-); Mach number at Tw node 5;
AeroDyn['TwN6M'] = False # (-); Mach number at Tw node 6;
AeroDyn['TwN7M'] = False # (-); Mach number at Tw node 7;
AeroDyn['TwN8M'] = False # (-); Mach number at Tw node 8;
AeroDyn['TwN9M'] = False # (-); Mach number at Tw node 9;
AeroDyn['TwN1Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 1; local tower coordinate system
AeroDyn['TwN2Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 2; local tower coordinate system
AeroDyn['TwN3Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 3; local tower coordinate system
AeroDyn['TwN4Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 4; local tower coordinate system
AeroDyn['TwN5Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 5; local tower coordinate system
AeroDyn['TwN6Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 6; local tower coordinate system
AeroDyn['TwN7Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 7; local tower coordinate system
AeroDyn['TwN8Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 8; local tower coordinate system
AeroDyn['TwN9Fdx'] = False # (N/m); x-component of drag force per unit length at Tw node 9; local tower coordinate system
AeroDyn['TwN1Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 1; local tower coordinate system
AeroDyn['TwN2Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 2; local tower coordinate system
AeroDyn['TwN3Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 3; local tower coordinate system
AeroDyn['TwN4Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 4; local tower coordinate system
AeroDyn['TwN5Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 5; local tower coordinate system
AeroDyn['TwN6Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 6; local tower coordinate system
AeroDyn['TwN7Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 7; local tower coordinate system
AeroDyn['TwN8Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 8; local tower coordinate system
AeroDyn['TwN9Fdy'] = False # (N/m); y-component of drag force per unit length at Tw node 9; local tower coordinate system
# Blade
AeroDyn['B1Azimuth'] = False # (deg); Azimuth angle of blade 1;
AeroDyn['B2Azimuth'] = False # (deg); Azimuth angle of blade 2;
AeroDyn['B3Azimuth'] = False # (deg); Azimuth angle of blade 3;
AeroDyn['B1Pitch'] = False # (deg); Pitch angle of blade 1;
AeroDyn['B2Pitch'] = False # (deg); Pitch angle of blade 2;
AeroDyn['B3Pitch'] = False # (deg); Pitch angle of blade 3;
AeroDyn['B1N1VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B2N1VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B3N1VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VUndy'] = False # (m/s); y-component of undisturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VUndz'] = False # (m/s); z-component of undisturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B1N1VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B2N1VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B3N1VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VDisx'] = False # (m/s); x-component of disturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VDisy'] = False # (m/s); y-component of disturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9VDisz'] = False # (m/s); z-component of disturbed wind velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B1N1STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9STVx'] = False # (m/s); x-component of structural translational velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9STVy'] = False # (m/s); y-component of structural translational velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B1N1STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 1; local blade coordinate system
AeroDyn['B1N2STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 2; local blade coordinate system
AeroDyn['B1N3STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 3; local blade coordinate system
AeroDyn['B1N4STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 4; local blade coordinate system
AeroDyn['B1N5STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 5; local blade coordinate system
AeroDyn['B1N6STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 6; local blade coordinate system
AeroDyn['B1N7STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 7; local blade coordinate system
AeroDyn['B1N8STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 8; local blade coordinate system
AeroDyn['B1N9STVz'] = False # (m/s); z-component of structural translational velocity at Blade 1, Node 9; local blade coordinate system
AeroDyn['B2N1STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9STVx'] = False # (m/s); x-component of structural translational velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9STVy'] = False # (m/s); y-component of structural translational velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B2N1STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 1; local blade coordinate system
AeroDyn['B2N2STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 2; local blade coordinate system
AeroDyn['B2N3STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 3; local blade coordinate system
AeroDyn['B2N4STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 4; local blade coordinate system
AeroDyn['B2N5STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 5; local blade coordinate system
AeroDyn['B2N6STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 6; local blade coordinate system
AeroDyn['B2N7STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 7; local blade coordinate system
AeroDyn['B2N8STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 8; local blade coordinate system
AeroDyn['B2N9STVz'] = False # (m/s); z-component of structural translational velocity at Blade 2, Node 9; local blade coordinate system
AeroDyn['B3N1STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9STVx'] = False # (m/s); x-component of structural translational velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9STVy'] = False # (m/s); y-component of structural translational velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B3N1STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 1; local blade coordinate system
AeroDyn['B3N2STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 2; local blade coordinate system
AeroDyn['B3N3STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 3; local blade coordinate system
AeroDyn['B3N4STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 4; local blade coordinate system
AeroDyn['B3N5STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 5; local blade coordinate system
AeroDyn['B3N6STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 6; local blade coordinate system
AeroDyn['B3N7STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 7; local blade coordinate system
AeroDyn['B3N8STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 8; local blade coordinate system
AeroDyn['B3N9STVz'] = False # (m/s); z-component of structural translational velocity at Blade 3, Node 9; local blade coordinate system
AeroDyn['B1N1VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 1;
AeroDyn['B1N2VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 2;
AeroDyn['B1N3VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 3;
AeroDyn['B1N4VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 4;
AeroDyn['B1N5VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 5;
AeroDyn['B1N6VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 6;
AeroDyn['B1N7VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 7;
AeroDyn['B1N8VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 8;
AeroDyn['B1N9VRel'] = False # (m/s); Relvative wind speed at Blade 1, Node 9;
AeroDyn['B2N1VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 1;
AeroDyn['B2N2VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 2;
AeroDyn['B2N3VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 3;
AeroDyn['B2N4VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 4;
AeroDyn['B2N5VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 5;
AeroDyn['B2N6VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 6;
AeroDyn['B2N7VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 7;
AeroDyn['B2N8VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 8;
AeroDyn['B2N9VRel'] = False # (m/s); Relvative wind speed at Blade 2, Node 9;
AeroDyn['B3N1VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 1;
AeroDyn['B3N2VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 2;
AeroDyn['B3N3VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 3;
AeroDyn['B3N4VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 4;
AeroDyn['B3N5VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 5;
AeroDyn['B3N6VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 6;
AeroDyn['B3N7VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 7;
AeroDyn['B3N8VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 8;
AeroDyn['B3N9VRel'] = False # (m/s); Relvative wind speed at Blade 3, Node 9;
AeroDyn['B1N1DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 1;
AeroDyn['B1N2DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 2;
AeroDyn['B1N3DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 3;
AeroDyn['B1N4DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 4;
AeroDyn['B1N5DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 5;
AeroDyn['B1N6DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 6;
AeroDyn['B1N7DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 7;
AeroDyn['B1N8DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 8;
AeroDyn['B1N9DynP'] = False # (Pa); Dynamic pressure at Blade 1, Node 9;
AeroDyn['B2N1DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 1;
AeroDyn['B2N2DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 2;
AeroDyn['B2N3DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 3;
AeroDyn['B2N4DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 4;
AeroDyn['B2N5DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 5;
AeroDyn['B2N6DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 6;
AeroDyn['B2N7DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 7;
AeroDyn['B2N8DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 8;
AeroDyn['B2N9DynP'] = False # (Pa); Dynamic pressure at Blade 2, Node 9;
AeroDyn['B3N1DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 1;
AeroDyn['B3N2DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 2;
AeroDyn['B3N3DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 3;
AeroDyn['B3N4DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 4;
AeroDyn['B3N5DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 5;
AeroDyn['B3N6DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 6;
AeroDyn['B3N7DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 7;
AeroDyn['B3N8DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 8;
AeroDyn['B3N9DynP'] = False # (Pa); Dynamic pressure at Blade 3, Node 9;
AeroDyn['B1N1Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 1;
AeroDyn['B1N2Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 2;
AeroDyn['B1N3Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 3;
AeroDyn['B1N4Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 4;
AeroDyn['B1N5Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 5;
AeroDyn['B1N6Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 6;
AeroDyn['B1N7Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 7;
AeroDyn['B1N8Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 8;
AeroDyn['B1N9Re'] = False # (-); Reynolds number (in millions) at Blade 1, Node 9;
AeroDyn['B2N1Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 1;
AeroDyn['B2N2Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 2;
AeroDyn['B2N3Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 3;
AeroDyn['B2N4Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 4;
AeroDyn['B2N5Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 5;
AeroDyn['B2N6Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 6;
AeroDyn['B2N7Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 7;
AeroDyn['B2N8Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 8;
AeroDyn['B2N9Re'] = False # (-); Reynolds number (in millions) at Blade 2, Node 9;
AeroDyn['B3N1Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 1;
AeroDyn['B3N2Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 2;
AeroDyn['B3N3Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 3;
AeroDyn['B3N4Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 4;
AeroDyn['B3N5Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 5;
AeroDyn['B3N6Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 6;
AeroDyn['B3N7Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 7;
AeroDyn['B3N8Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 8;
AeroDyn['B3N9Re'] = False # (-); Reynolds number (in millions) at Blade 3, Node 9;
AeroDyn['B1N1M'] = False # (-); Mach number at Blade 1, Node 1;
AeroDyn['B1N2M'] = False # (-); Mach number at Blade 1, Node 2;
AeroDyn['B1N3M'] = False # (-); Mach number at Blade 1, Node 3;
AeroDyn['B1N4M'] = False # (-); Mach number at Blade 1, Node 4;
AeroDyn['B1N5M'] = False # (-); Mach number at Blade 1, Node 5;
AeroDyn['B1N6M'] = False # (-); Mach number at Blade 1, Node 6;
AeroDyn['B1N7M'] = False # (-); Mach number at Blade 1, Node 7;
AeroDyn['B1N8M'] = False # (-); Mach number at Blade 1, Node 8;
AeroDyn['B1N9M'] = False # (-); Mach number at Blade 1, Node 9;
AeroDyn['B2N1M'] = False # (-); Mach number at Blade 2, Node 1;
AeroDyn['B2N2M'] = False # (-); Mach number at Blade 2, Node 2;
AeroDyn['B2N3M'] = False # (-); Mach number at Blade 2, Node 3;
AeroDyn['B2N4M'] = False # (-); Mach number at Blade 2, Node 4;
AeroDyn['B2N5M'] = False # (-); Mach number at Blade 2, Node 5;
AeroDyn['B2N6M'] = False # (-); Mach number at Blade 2, Node 6;
AeroDyn['B2N7M'] = False # (-); Mach number at Blade 2, Node 7;
AeroDyn['B2N8M'] = False # (-); Mach number at Blade 2, Node 8;
AeroDyn['B2N9M'] = False # (-); Mach number at Blade 2, Node 9;
AeroDyn['B3N1M'] = False # (-); Mach number at Blade 3, Node 1;
AeroDyn['B3N2M'] = False # (-); Mach number at Blade 3, Node 2;
AeroDyn['B3N3M'] = False # (-); Mach number at Blade 3, Node 3;
AeroDyn['B3N4M'] = False # (-); Mach number at Blade 3, Node 4;
AeroDyn['B3N5M'] = False # (-); Mach number at Blade 3, Node 5;
AeroDyn['B3N6M'] = False # (-); Mach number at Blade 3, Node 6;
AeroDyn['B3N7M'] = False # (-); Mach number at Blade 3, Node 7;
AeroDyn['B3N8M'] = False # (-); Mach number at Blade 3, Node 8;
AeroDyn['B3N9M'] = False # (-); Mach number at Blade 3, Node 9;
AeroDyn['B1N1Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 1;
AeroDyn['B1N2Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 2;
AeroDyn['B1N3Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 3;
AeroDyn['B1N4Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 4;
AeroDyn['B1N5Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 5;
AeroDyn['B1N6Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 6;
AeroDyn['B1N7Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 7;
AeroDyn['B1N8Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 8;
AeroDyn['B1N9Vindx'] = False # (m/s); Axial induced wind velocity at Blade 1, Node 9;
AeroDyn['B2N1Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 1;
AeroDyn['B2N2Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 2;
AeroDyn['B2N3Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 3;
AeroDyn['B2N4Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 4;
AeroDyn['B2N5Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 5;
AeroDyn['B2N6Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 6;
AeroDyn['B2N7Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 7;
AeroDyn['B2N8Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 8;
AeroDyn['B2N9Vindx'] = False # (m/s); Axial induced wind velocity at Blade 2, Node 9;
AeroDyn['B3N1Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 1;
AeroDyn['B3N2Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 2;
AeroDyn['B3N3Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 3;
AeroDyn['B3N4Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 4;
AeroDyn['B3N5Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 5;
AeroDyn['B3N6Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 6;
AeroDyn['B3N7Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 7;
AeroDyn['B3N8Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 8;
AeroDyn['B3N9Vindx'] = False # (m/s); Axial induced wind velocity at Blade 3, Node 9;
AeroDyn['B1N1Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 1;
AeroDyn['B1N2Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 2;
AeroDyn['B1N3Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 3;
AeroDyn['B1N4Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 4;
AeroDyn['B1N5Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 5;
AeroDyn['B1N6Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 6;
AeroDyn['B1N7Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 7;
AeroDyn['B1N8Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 8;
AeroDyn['B1N9Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 1, Node 9;
AeroDyn['B2N1Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 1;
AeroDyn['B2N2Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 2;
AeroDyn['B2N3Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 3;
AeroDyn['B2N4Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 4;
AeroDyn['B2N5Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 5;
AeroDyn['B2N6Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 6;
AeroDyn['B2N7Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 7;
AeroDyn['B2N8Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 8;
AeroDyn['B2N9Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 2, Node 9;
AeroDyn['B3N1Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 1;
AeroDyn['B3N2Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 2;
AeroDyn['B3N3Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 3;
AeroDyn['B3N4Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 4;
AeroDyn['B3N5Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 5;
AeroDyn['B3N6Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 6;
AeroDyn['B3N7Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 7;
AeroDyn['B3N8Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 8;
AeroDyn['B3N9Vindy'] = False # (m/s); Tangential induced wind velocity at Blade 3, Node 9;
AeroDyn['B1N1AxInd'] = False # (-); Axial induction factor at Blade 1, Node 1;
AeroDyn['B1N2AxInd'] = False # (-); Axial induction factor at Blade 1, Node 2;
AeroDyn['B1N3AxInd'] = False # (-); Axial induction factor at Blade 1, Node 3;
AeroDyn['B1N4AxInd'] = False # (-); Axial induction factor at Blade 1, Node 4;
AeroDyn['B1N5AxInd'] = False # (-); Axial induction factor at Blade 1, Node 5;
AeroDyn['B1N6AxInd'] = False # (-); Axial induction factor at Blade 1, Node 6;
AeroDyn['B1N7AxInd'] = False # (-); Axial induction factor at Blade 1, Node 7;
AeroDyn['B1N8AxInd'] = False # (-); Axial induction factor at Blade 1, Node 8;
AeroDyn['B1N9AxInd'] = False # (-); Axial induction factor at Blade 1, Node 9;
AeroDyn['B2N1AxInd'] = False # (-); Axial induction factor at Blade 2, Node 1;
AeroDyn['B2N2AxInd'] = False # (-); Axial induction factor at Blade 2, Node 2;
AeroDyn['B2N3AxInd'] = False # (-); Axial induction factor at Blade 2, Node 3;
AeroDyn['B2N4AxInd'] = False # (-); Axial induction factor at Blade 2, Node 4;
AeroDyn['B2N5AxInd'] = False # (-); Axial induction factor at Blade 2, Node 5;
AeroDyn['B2N6AxInd'] = False # (-); Axial induction factor at Blade 2, Node 6;
AeroDyn['B2N7AxInd'] = False # (-); Axial induction factor at Blade 2, Node 7;
AeroDyn['B2N8AxInd'] = False # (-); Axial induction factor at Blade 2, Node 8;
AeroDyn['B2N9AxInd'] = False # (-); Axial induction factor at Blade 2, Node 9;
AeroDyn['B3N1AxInd'] = False # (-); Axial induction factor at Blade 3, Node 1;
AeroDyn['B3N2AxInd'] = False # (-); Axial induction factor at Blade 3, Node 2;
AeroDyn['B3N3AxInd'] = False # (-); Axial induction factor at Blade 3, Node 3;
AeroDyn['B3N4AxInd'] = False # (-); Axial induction factor at Blade 3, Node 4;
AeroDyn['B3N5AxInd'] = False # (-); Axial induction factor at Blade 3, Node 5;
AeroDyn['B3N6AxInd'] = False # (-); Axial induction factor at Blade 3, Node 6;
AeroDyn['B3N7AxInd'] = False # (-); Axial induction factor at Blade 3, Node 7;
AeroDyn['B3N8AxInd'] = False # (-); Axial induction factor at Blade 3, Node 8;
AeroDyn['B3N9AxInd'] = False # (-); Axial induction factor at Blade 3, Node 9;
AeroDyn['B1N1TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 1;
AeroDyn['B1N2TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 2;
AeroDyn['B1N3TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 3;
AeroDyn['B1N4TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 4;
AeroDyn['B1N5TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 5;
AeroDyn['B1N6TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 6;
AeroDyn['B1N7TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 7;
AeroDyn['B1N8TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 8;
AeroDyn['B1N9TnInd'] = False # (-); Tangential induction factor at Blade 1, Node 9;
AeroDyn['B2N1TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 1;
AeroDyn['B2N2TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 2;
AeroDyn['B2N3TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 3;
AeroDyn['B2N4TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 4;
AeroDyn['B2N5TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 5;
AeroDyn['B2N6TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 6;
AeroDyn['B2N7TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 7;
AeroDyn['B2N8TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 8;
AeroDyn['B2N9TnInd'] = False # (-); Tangential induction factor at Blade 2, Node 9;
AeroDyn['B3N1TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 1;
AeroDyn['B3N2TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 2;
AeroDyn['B3N3TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 3;
AeroDyn['B3N4TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 4;
AeroDyn['B3N5TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 5;
AeroDyn['B3N6TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 6;
AeroDyn['B3N7TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 7;
AeroDyn['B3N8TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 8;
AeroDyn['B3N9TnInd'] = False # (-); Tangential induction factor at Blade 3, Node 9;
AeroDyn['B1N1Alpha'] = False # (deg); Angle of attack at Blade 1, Node 1;
AeroDyn['B1N2Alpha'] = False # (deg); Angle of attack at Blade 1, Node 2;
AeroDyn['B1N3Alpha'] = False # (deg); Angle of attack at Blade 1, Node 3;
AeroDyn['B1N4Alpha'] = False # (deg); Angle of attack at Blade 1, Node 4;
AeroDyn['B1N5Alpha'] = False # (deg); Angle of attack at Blade 1, Node 5;
AeroDyn['B1N6Alpha'] = False # (deg); Angle of attack at Blade 1, Node 6;
AeroDyn['B1N7Alpha'] = False # (deg); Angle of attack at Blade 1, Node 7;
AeroDyn['B1N8Alpha'] = False # (deg); Angle of attack at Blade 1, Node 8;
AeroDyn['B1N9Alpha'] = False # (deg); Angle of attack at Blade 1, Node 9;
AeroDyn['B2N1Alpha'] = False # (deg); Angle of attack at Blade 2, Node 1;
AeroDyn['B2N2Alpha'] = False # (deg); Angle of attack at Blade 2, Node 2;
AeroDyn['B2N3Alpha'] = False # (deg); Angle of attack at Blade 2, Node 3;
AeroDyn['B2N4Alpha'] = False # (deg); Angle of attack at Blade 2, Node 4;
AeroDyn['B2N5Alpha'] = False # (deg); Angle of attack at Blade 2, Node 5;
AeroDyn['B2N6Alpha'] = False # (deg); Angle of attack at Blade 2, Node 6;
AeroDyn['B2N7Alpha'] = False # (deg); Angle of attack at Blade 2, Node 7;
AeroDyn['B2N8Alpha'] = False # (deg); Angle of attack at Blade 2, Node 8;
AeroDyn['B2N9Alpha'] = False # (deg); Angle of attack at Blade 2, Node 9;
AeroDyn['B3N1Alpha'] = False # (deg); Angle of attack at Blade 3, Node 1;
AeroDyn['B3N2Alpha'] = False # (deg); Angle of attack at Blade 3, Node 2;
AeroDyn['B3N3Alpha'] = False # (deg); Angle of attack at Blade 3, Node 3;
AeroDyn['B3N4Alpha'] = False # (deg); Angle of attack at Blade 3, Node 4;
AeroDyn['B3N5Alpha'] = False # (deg); Angle of attack at Blade 3, Node 5;
AeroDyn['B3N6Alpha'] = False # (deg); Angle of attack at Blade 3, Node 6;
AeroDyn['B3N7Alpha'] = False # (deg); Angle of attack at Blade 3, Node 7;
AeroDyn['B3N8Alpha'] = False # (deg); Angle of attack at Blade 3, Node 8;
AeroDyn['B3N9Alpha'] = False # (deg); Angle of attack at Blade 3, Node 9;
AeroDyn['B1N1Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 1;
AeroDyn['B1N2Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 2;
AeroDyn['B1N3Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 3;
AeroDyn['B1N4Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 4;
AeroDyn['B1N5Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 5;
AeroDyn['B1N6Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 6;
AeroDyn['B1N7Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 7;
AeroDyn['B1N8Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 8;
AeroDyn['B1N9Theta'] = False # (deg); Pitch+Twist angle at Blade 1, Node 9;
AeroDyn['B2N1Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 1;
AeroDyn['B2N2Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 2;
AeroDyn['B2N3Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 3;
AeroDyn['B2N4Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 4;
AeroDyn['B2N5Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 5;
AeroDyn['B2N6Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 6;
AeroDyn['B2N7Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 7;
AeroDyn['B2N8Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 8;
AeroDyn['B2N9Theta'] = False # (deg); Pitch+Twist angle at Blade 2, Node 9;
AeroDyn['B3N1Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 1;
AeroDyn['B3N2Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 2;
AeroDyn['B3N3Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 3;
AeroDyn['B3N4Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 4;
AeroDyn['B3N5Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 5;
AeroDyn['B3N6Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 6;
AeroDyn['B3N7Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 7;
AeroDyn['B3N8Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 8;
AeroDyn['B3N9Theta'] = False # (deg); Pitch+Twist angle at Blade 3, Node 9;
AeroDyn['B1N1Phi'] = False # (deg); Inflow angle at Blade 1, Node 1;
AeroDyn['B1N2Phi'] = False # (deg); Inflow angle at Blade 1, Node 2;
AeroDyn['B1N3Phi'] = False # (deg); Inflow angle at Blade 1, Node 3;
AeroDyn['B1N4Phi'] = False # (deg); Inflow angle at Blade 1, Node 4;
AeroDyn['B1N5Phi'] = False # (deg); Inflow angle at Blade 1, Node 5;
AeroDyn['B1N6Phi'] = False # (deg); Inflow angle at Blade 1, Node 6;
AeroDyn['B1N7Phi'] = False # (deg); Inflow angle at Blade 1, Node 7;
AeroDyn['B1N8Phi'] = False # (deg); Inflow angle at Blade 1, Node 8;
AeroDyn['B1N9Phi'] = False # (deg); Inflow angle at Blade 1, Node 9;
AeroDyn['B2N1Phi'] = False # (deg); Inflow angle at Blade 2, Node 1;
AeroDyn['B2N2Phi'] = False # (deg); Inflow angle at Blade 2, Node 2;
AeroDyn['B2N3Phi'] = False # (deg); Inflow angle at Blade 2, Node 3;
AeroDyn['B2N4Phi'] = False # (deg); Inflow angle at Blade 2, Node 4;
AeroDyn['B2N5Phi'] = False # (deg); Inflow angle at Blade 2, Node 5;
AeroDyn['B2N6Phi'] = False # (deg); Inflow angle at Blade 2, Node 6;
AeroDyn['B2N7Phi'] = False # (deg); Inflow angle at Blade 2, Node 7;
AeroDyn['B2N8Phi'] = False # (deg); Inflow angle at Blade 2, Node 8;
AeroDyn['B2N9Phi'] = False # (deg); Inflow angle at Blade 2, Node 9;
AeroDyn['B3N1Phi'] = False # (deg); Inflow angle at Blade 3, Node 1;
AeroDyn['B3N2Phi'] = False # (deg); Inflow angle at Blade 3, Node 2;
AeroDyn['B3N3Phi'] = False # (deg); Inflow angle at Blade 3, Node 3;
AeroDyn['B3N4Phi'] = False # (deg); Inflow angle at Blade 3, Node 4;
AeroDyn['B3N5Phi'] = False # (deg); Inflow angle at Blade 3, Node 5;
AeroDyn['B3N6Phi'] = False # (deg); Inflow angle at Blade 3, Node 6;
AeroDyn['B3N7Phi'] = False # (deg); Inflow angle at Blade 3, Node 7;
AeroDyn['B3N8Phi'] = False # (deg); Inflow angle at Blade 3, Node 8;
AeroDyn['B3N9Phi'] = False # (deg); Inflow angle at Blade 3, Node 9;
AeroDyn['B1N1Curve'] = False # (deg); Curvature angle at Blade 1, Node 1;
AeroDyn['B1N2Curve'] = False # (deg); Curvature angle at Blade 1, Node 2;
AeroDyn['B1N3Curve'] = False # (deg); Curvature angle at Blade 1, Node 3;
AeroDyn['B1N4Curve'] = False # (deg); Curvature angle at Blade 1, Node 4;
AeroDyn['B1N5Curve'] = False # (deg); Curvature angle at Blade 1, Node 5;
AeroDyn['B1N6Curve'] = False # (deg); Curvature angle at Blade 1, Node 6;
AeroDyn['B1N7Curve'] = False # (deg); Curvature angle at Blade 1, Node 7;
AeroDyn['B1N8Curve'] = False # (deg); Curvature angle at Blade 1, Node 8;
AeroDyn['B1N9Curve'] = False # (deg); Curvature angle at Blade 1, Node 9;
AeroDyn['B2N1Curve'] = False # (deg); Curvature angle at Blade 2, Node 1;
AeroDyn['B2N2Curve'] = False # (deg); Curvature angle at Blade 2, Node 2;
AeroDyn['B2N3Curve'] = False # (deg); Curvature angle at Blade 2, Node 3;
AeroDyn['B2N4Curve'] = False # (deg); Curvature angle at Blade 2, Node 4;
AeroDyn['B2N5Curve'] = False # (deg); Curvature angle at Blade 2, Node 5;
AeroDyn['B2N6Curve'] = False # (deg); Curvature angle at Blade 2, Node 6;
AeroDyn['B2N7Curve'] = False # (deg); Curvature angle at Blade 2, Node 7;
AeroDyn['B2N8Curve'] = False # (deg); Curvature angle at Blade 2, Node 8;
AeroDyn['B2N9Curve'] = False # (deg); Curvature angle at Blade 2, Node 9;
AeroDyn['B3N1Curve'] = False # (deg); Curvature angle at Blade 3, Node 1;
AeroDyn['B3N2Curve'] = False # (deg); Curvature angle at Blade 3, Node 2;
AeroDyn['B3N3Curve'] = False # (deg); Curvature angle at Blade 3, Node 3;
AeroDyn['B3N4Curve'] = False # (deg); Curvature angle at Blade 3, Node 4;
AeroDyn['B3N5Curve'] = False # (deg); Curvature angle at Blade 3, Node 5;
AeroDyn['B3N6Curve'] = False # (deg); Curvature angle at Blade 3, Node 6;
AeroDyn['B3N7Curve'] = False # (deg); Curvature angle at Blade 3, Node 7;
AeroDyn['B3N8Curve'] = False # (deg); Curvature angle at Blade 3, Node 8;
AeroDyn['B3N9Curve'] = False # (deg); Curvature angle at Blade 3, Node 9;
AeroDyn['B1N1Cl'] = False # (-); Lift force coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cl'] = False # (-); Lift force coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cl'] = False # (-); Lift force coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cl'] = False # (-); Lift force coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cl'] = False # (-); Lift force coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cl'] = False # (-); Lift force coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cl'] = False # (-); Lift force coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cl'] = False # (-); Lift force coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cl'] = False # (-); Lift force coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cl'] = False # (-); Lift force coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cl'] = False # (-); Lift force coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cl'] = False # (-); Lift force coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cl'] = False # (-); Lift force coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cl'] = False # (-); Lift force coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cl'] = False # (-); Lift force coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cl'] = False # (-); Lift force coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cl'] = False # (-); Lift force coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cl'] = False # (-); Lift force coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cl'] = False # (-); Lift force coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cl'] = False # (-); Lift force coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cl'] = False # (-); Lift force coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cl'] = False # (-); Lift force coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cl'] = False # (-); Lift force coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cl'] = False # (-); Lift force coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cl'] = False # (-); Lift force coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cl'] = False # (-); Lift force coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cl'] = False # (-); Lift force coefficient at Blade 3, Node 9;
AeroDyn['B1N1Cd'] = False # (-); Drag force coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cd'] = False # (-); Drag force coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cd'] = False # (-); Drag force coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cd'] = False # (-); Drag force coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cd'] = False # (-); Drag force coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cd'] = False # (-); Drag force coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cd'] = False # (-); Drag force coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cd'] = False # (-); Drag force coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cd'] = False # (-); Drag force coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cd'] = False # (-); Drag force coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cd'] = False # (-); Drag force coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cd'] = False # (-); Drag force coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cd'] = False # (-); Drag force coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cd'] = False # (-); Drag force coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cd'] = False # (-); Drag force coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cd'] = False # (-); Drag force coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cd'] = False # (-); Drag force coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cd'] = False # (-); Drag force coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cd'] = False # (-); Drag force coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cd'] = False # (-); Drag force coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cd'] = False # (-); Drag force coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cd'] = False # (-); Drag force coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cd'] = False # (-); Drag force coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cd'] = False # (-); Drag force coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cd'] = False # (-); Drag force coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cd'] = False # (-); Drag force coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cd'] = False # (-); Drag force coefficient at Blade 3, Node 9;
AeroDyn['B1N1Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cm'] = False # (-); Pitching moment coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cm'] = False # (-); Pitching moment coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cm'] = False # (-); Pitching moment coefficient at Blade 3, Node 9;
AeroDyn['B1N1Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cx'] = False # (-); Normal force (to plane) coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cx'] = False # (-); Normal force (to plane) coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cx'] = False # (-); Normal force (to plane) coefficient at Blade 3, Node 9;
AeroDyn['B1N1Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cy'] = False # (-); Tangential force (to plane) coefficient at Blade 3, Node 9;
AeroDyn['B1N1Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 1;
AeroDyn['B1N2Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 2;
AeroDyn['B1N3Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 3;
AeroDyn['B1N4Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 4;
AeroDyn['B1N5Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 5;
AeroDyn['B1N6Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 6;
AeroDyn['B1N7Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 7;
AeroDyn['B1N8Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 8;
AeroDyn['B1N9Cn'] = False # (-); Normal force (to chord) coefficient at Blade 1, Node 9;
AeroDyn['B2N1Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 1;
AeroDyn['B2N2Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 2;
AeroDyn['B2N3Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 3;
AeroDyn['B2N4Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 4;
AeroDyn['B2N5Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 5;
AeroDyn['B2N6Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 6;
AeroDyn['B2N7Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 7;
AeroDyn['B2N8Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 8;
AeroDyn['B2N9Cn'] = False # (-); Normal force (to chord) coefficient at Blade 2, Node 9;
AeroDyn['B3N1Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 1;
AeroDyn['B3N2Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 2;
AeroDyn['B3N3Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 3;
AeroDyn['B3N4Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 4;
AeroDyn['B3N5Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 5;
AeroDyn['B3N6Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 6;
AeroDyn['B3N7Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 7;
AeroDyn['B3N8Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 8;
AeroDyn['B3N9Cn'] = False # (-); Normal force (to chord) coefficient at Blade 3, Node 9;
AeroDyn['B1N1Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 1;
AeroDyn['B1N2Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 2;
AeroDyn['B1N3Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 3;
AeroDyn['B1N4Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 4;
AeroDyn['B1N5Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 5;
AeroDyn['B1N6Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 6;
AeroDyn['B1N7Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 7;
AeroDyn['B1N8Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 8;
AeroDyn['B1N9Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 1, Node 9;
AeroDyn['B2N1Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 1;
AeroDyn['B2N2Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 2;
AeroDyn['B2N3Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 3;
AeroDyn['B2N4Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 4;
AeroDyn['B2N5Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 5;
AeroDyn['B2N6Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 6;
AeroDyn['B2N7Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 7;
AeroDyn['B2N8Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 8;
AeroDyn['B2N9Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 2, Node 9;
AeroDyn['B3N1Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 1;
AeroDyn['B3N2Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 2;
AeroDyn['B3N3Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 3;
AeroDyn['B3N4Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 4;
AeroDyn['B3N5Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 5;
AeroDyn['B3N6Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 6;
AeroDyn['B3N7Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 7;
AeroDyn['B3N8Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 8;
AeroDyn['B3N9Ct'] = False # (-); Tangential force (to chord) coefficient at Blade 3, Node 9;
AeroDyn['B1N1Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 1;
AeroDyn['B1N2Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 2;
AeroDyn['B1N3Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 3;
AeroDyn['B1N4Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 4;
AeroDyn['B1N5Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 5;
AeroDyn['B1N6Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 6;
AeroDyn['B1N7Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 7;
AeroDyn['B1N8Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 8;
AeroDyn['B1N9Fl'] = False # (N/m); Lift force per unit length at Blade 1, Node 9;
AeroDyn['B2N1Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 1;
AeroDyn['B2N2Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 2;
AeroDyn['B2N3Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 3;
AeroDyn['B2N4Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 4;
AeroDyn['B2N5Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 5;
AeroDyn['B2N6Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 6;
AeroDyn['B2N7Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 7;
AeroDyn['B2N8Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 8;
AeroDyn['B2N9Fl'] = False # (N/m); Lift force per unit length at Blade 2, Node 9;
AeroDyn['B3N1Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 1;
AeroDyn['B3N2Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 2;
AeroDyn['B3N3Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 3;
AeroDyn['B3N4Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 4;
AeroDyn['B3N5Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 5;
AeroDyn['B3N6Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 6;
AeroDyn['B3N7Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 7;
AeroDyn['B3N8Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 8;
AeroDyn['B3N9Fl'] = False # (N/m); Lift force per unit length at Blade 3, Node 9;
AeroDyn['B1N1Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 1;
AeroDyn['B1N2Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 2;
AeroDyn['B1N3Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 3;
AeroDyn['B1N4Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 4;
AeroDyn['B1N5Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 5;
AeroDyn['B1N6Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 6;
AeroDyn['B1N7Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 7;
AeroDyn['B1N8Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 8;
AeroDyn['B1N9Fd'] = False # (N/m); Drag force per unit length at Blade 1, Node 9;
AeroDyn['B2N1Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 1;
AeroDyn['B2N2Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 2;
AeroDyn['B2N3Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 3;
AeroDyn['B2N4Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 4;
AeroDyn['B2N5Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 5;
AeroDyn['B2N6Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 6;
AeroDyn['B2N7Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 7;
AeroDyn['B2N8Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 8;
AeroDyn['B2N9Fd'] = False # (N/m); Drag force per unit length at Blade 2, Node 9;
AeroDyn['B3N1Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 1;
AeroDyn['B3N2Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 2;
AeroDyn['B3N3Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 3;
AeroDyn['B3N4Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 4;
AeroDyn['B3N5Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 5;
AeroDyn['B3N6Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 6;
AeroDyn['B3N7Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 7;
AeroDyn['B3N8Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 8;
AeroDyn['B3N9Fd'] = False # (N/m); Drag force per unit length at Blade 3, Node 9;
AeroDyn['B1N1Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 1;
AeroDyn['B1N2Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 2;
AeroDyn['B1N3Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 3;
AeroDyn['B1N4Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 4;
AeroDyn['B1N5Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 5;
AeroDyn['B1N6Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 6;
AeroDyn['B1N7Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 7;
AeroDyn['B1N8Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 8;
AeroDyn['B1N9Mm'] = False # (N m/m); Pitching moment per unit length at Blade 1, Node 9;
AeroDyn['B2N1Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 1;
AeroDyn['B2N2Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 2;
AeroDyn['B2N3Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 3;
AeroDyn['B2N4Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 4;
AeroDyn['B2N5Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 5;
AeroDyn['B2N6Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 6;
AeroDyn['B2N7Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 7;
AeroDyn['B2N8Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 8;
AeroDyn['B2N9Mm'] = False # (N m/m); Pitching moment per unit length at Blade 2, Node 9;
AeroDyn['B3N1Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 1;
AeroDyn['B3N2Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 2;
AeroDyn['B3N3Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 3;
AeroDyn['B3N4Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 4;
AeroDyn['B3N5Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 5;
AeroDyn['B3N6Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 6;
AeroDyn['B3N7Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 7;
AeroDyn['B3N8Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 8;
AeroDyn['B3N9Mm'] = False # (N m/m); Pitching moment per unit length at Blade 3, Node 9;
AeroDyn['B1N1Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 1;
AeroDyn['B1N2Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 2;
AeroDyn['B1N3Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 3;
AeroDyn['B1N4Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 4;
AeroDyn['B1N5Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 5;
AeroDyn['B1N6Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 6;
AeroDyn['B1N7Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 7;
AeroDyn['B1N8Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 8;
AeroDyn['B1N9Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 1, Node 9;
AeroDyn['B2N1Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 1;
AeroDyn['B2N2Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 2;
AeroDyn['B2N3Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 3;
AeroDyn['B2N4Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 4;
AeroDyn['B2N5Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 5;
AeroDyn['B2N6Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 6;
AeroDyn['B2N7Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 7;
AeroDyn['B2N8Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 8;
AeroDyn['B2N9Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 2, Node 9;
AeroDyn['B3N1Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 1;
AeroDyn['B3N2Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 2;
AeroDyn['B3N3Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 3;
AeroDyn['B3N4Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 4;
AeroDyn['B3N5Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 5;
AeroDyn['B3N6Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 6;
AeroDyn['B3N7Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 7;
AeroDyn['B3N8Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 8;
AeroDyn['B3N9Fx'] = False # (N/m); Normal force (to plane) per unit length at Blade 3, Node 9;
AeroDyn['B1N1Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 1;
AeroDyn['B1N2Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 2;
AeroDyn['B1N3Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 3;
AeroDyn['B1N4Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 4;
AeroDyn['B1N5Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 5;
AeroDyn['B1N6Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 6;
AeroDyn['B1N7Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 7;
AeroDyn['B1N8Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 8;
AeroDyn['B1N9Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 1, Node 9;
AeroDyn['B2N1Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 1;
AeroDyn['B2N2Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 2;
AeroDyn['B2N3Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 3;
AeroDyn['B2N4Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 4;
AeroDyn['B2N5Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 5;
AeroDyn['B2N6Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 6;
AeroDyn['B2N7Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 7;
AeroDyn['B2N8Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 8;
AeroDyn['B2N9Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 2, Node 9;
AeroDyn['B3N1Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 1;
AeroDyn['B3N2Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 2;
AeroDyn['B3N3Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 3;
AeroDyn['B3N4Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 4;
AeroDyn['B3N5Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 5;
AeroDyn['B3N6Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 6;
AeroDyn['B3N7Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 7;
AeroDyn['B3N8Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 8;
AeroDyn['B3N9Fy'] = False # (N/m); Tangential force (to plane) per unit length at Blade 3, Node 9;
AeroDyn['B1N1Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 1;
AeroDyn['B1N2Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 2;
AeroDyn['B1N3Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 3;
AeroDyn['B1N4Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 4;
AeroDyn['B1N5Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 5;
AeroDyn['B1N6Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 6;
AeroDyn['B1N7Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 7;
AeroDyn['B1N8Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 8;
AeroDyn['B1N9Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 1, Node 9;
AeroDyn['B2N1Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 1;
AeroDyn['B2N2Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 2;
AeroDyn['B2N3Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 3;
AeroDyn['B2N4Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 4;
AeroDyn['B2N5Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 5;
AeroDyn['B2N6Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 6;
AeroDyn['B2N7Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 7;
AeroDyn['B2N8Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 8;
AeroDyn['B2N9Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 2, Node 9;
AeroDyn['B3N1Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 1;
AeroDyn['B3N2Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 2;
AeroDyn['B3N3Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 3;
AeroDyn['B3N4Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 4;
AeroDyn['B3N5Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 5;
AeroDyn['B3N6Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 6;
AeroDyn['B3N7Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 7;
AeroDyn['B3N8Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 8;
AeroDyn['B3N9Fn'] = False # (N/m); Normal force (to chord) per unit length at Blade 3, Node 9;
AeroDyn['B1N1Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 1;
AeroDyn['B1N2Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 2;
AeroDyn['B1N3Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 3;
AeroDyn['B1N4Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 4;
AeroDyn['B1N5Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 5;
AeroDyn['B1N6Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 6;
AeroDyn['B1N7Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 7;
AeroDyn['B1N8Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 8;
AeroDyn['B1N9Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 1, Node 9;
AeroDyn['B2N1Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 1;
AeroDyn['B2N2Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 2;
AeroDyn['B2N3Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 3;
AeroDyn['B2N4Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 4;
AeroDyn['B2N5Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 5;
AeroDyn['B2N6Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 6;
AeroDyn['B2N7Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 7;
AeroDyn['B2N8Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 8;
AeroDyn['B2N9Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 2, Node 9;
AeroDyn['B3N1Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 1;
AeroDyn['B3N2Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 2;
AeroDyn['B3N3Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 3;
AeroDyn['B3N4Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 4;
AeroDyn['B3N5Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 5;
AeroDyn['B3N6Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 6;
AeroDyn['B3N7Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 7;
AeroDyn['B3N8Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 8;
AeroDyn['B3N9Ft'] = False # (N/m); Tangential force (to chord) per unit length at Blade 3, Node 9;
AeroDyn['B1N1Clrnc'] = False # (m); Tower clearance at Blade 1, Node 1 (based on the absolute distance to the nearest point in the tower from B1N1 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N1 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N2Clrnc'] = False # (m); Tower clearance at Blade 1, Node 2 (based on the absolute distance to the nearest point in the tower from B1N2 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N2 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N3Clrnc'] = False # (m); Tower clearance at Blade 1, Node 3 (based on the absolute distance to the nearest point in the tower from B1N3 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N3 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N4Clrnc'] = False # (m); Tower clearance at Blade 1, Node 4 (based on the absolute distance to the nearest point in the tower from B1N4 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N4 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N5Clrnc'] = False # (m); Tower clearance at Blade 1, Node 5 (based on the absolute distance to the nearest point in the tower from B1N5 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N5 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N6Clrnc'] = False # (m); Tower clearance at Blade 1, Node 6 (based on the absolute distance to the nearest point in the tower from B1N6 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N6 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N7Clrnc'] = False # (m); Tower clearance at Blade 1, Node 7 (based on the absolute distance to the nearest point in the tower from B1N7 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N7 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N8Clrnc'] = False # (m); Tower clearance at Blade 1, Node 8 (based on the absolute distance to the nearest point in the tower from B1N8 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N8 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B1N9Clrnc'] = False # (m); Tower clearance at Blade 1, Node 9 (based on the absolute distance to the nearest point in the tower from B1N9 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B1N9 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N1Clrnc'] = False # (m); Tower clearance at Blade 2, Node 1 (based on the absolute distance to the nearest point in the tower from B2N1 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N1 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N2Clrnc'] = False # (m); Tower clearance at Blade 2, Node 2 (based on the absolute distance to the nearest point in the tower from B2N2 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N2 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N3Clrnc'] = False # (m); Tower clearance at Blade 2, Node 3 (based on the absolute distance to the nearest point in the tower from B2N3 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N3 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N4Clrnc'] = False # (m); Tower clearance at Blade 2, Node 4 (based on the absolute distance to the nearest point in the tower from B2N4 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N4 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N5Clrnc'] = False # (m); Tower clearance at Blade 2, Node 5 (based on the absolute distance to the nearest point in the tower from B2N5 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N5 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N6Clrnc'] = False # (m); Tower clearance at Blade 2, Node 6 (based on the absolute distance to the nearest point in the tower from B2N6 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N6 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N7Clrnc'] = False # (m); Tower clearance at Blade 2, Node 7 (based on the absolute distance to the nearest point in the tower from B2N7 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N7 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N8Clrnc'] = False # (m); Tower clearance at Blade 2, Node 8 (based on the absolute distance to the nearest point in the tower from B2N8 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N8 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B2N9Clrnc'] = False # (m); Tower clearance at Blade 2, Node 9 (based on the absolute distance to the nearest point in the tower from B2N9 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B2N9 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N1Clrnc'] = False # (m); Tower clearance at Blade 3, Node 1 (based on the absolute distance to the nearest point in the tower from B3N1 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N1 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N2Clrnc'] = False # (m); Tower clearance at Blade 3, Node 2 (based on the absolute distance to the nearest point in the tower from B3N2 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N2 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N3Clrnc'] = False # (m); Tower clearance at Blade 3, Node 3 (based on the absolute distance to the nearest point in the tower from B3N3 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N3 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N4Clrnc'] = False # (m); Tower clearance at Blade 3, Node 4 (based on the absolute distance to the nearest point in the tower from B3N4 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N4 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N5Clrnc'] = False # (m); Tower clearance at Blade 3, Node 5 (based on the absolute distance to the nearest point in the tower from B3N5 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N5 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N6Clrnc'] = False # (m); Tower clearance at Blade 3, Node 6 (based on the absolute distance to the nearest point in the tower from B3N6 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N6 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N7Clrnc'] = False # (m); Tower clearance at Blade 3, Node 7 (based on the absolute distance to the nearest point in the tower from B3N7 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N7 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N8Clrnc'] = False # (m); Tower clearance at Blade 3, Node 8 (based on the absolute distance to the nearest point in the tower from B3N8 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N8 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
AeroDyn['B3N9Clrnc'] = False # (m); Tower clearance at Blade 3, Node 9 (based on the absolute distance to the nearest point in the tower from B3N9 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N9 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output;
# Rotor
AeroDyn['RtSpeed'] = False # (rpm); Rotor speed;
AeroDyn['RtTSR'] = False # (-); Rotor tip-speed ratio;
AeroDyn['RtVAvgxh'] = False # (m/s); Rotor-disk-averaged relative wind velocity (x-component); the hub coordinate system
AeroDyn['RtVAvgyh'] = False # (m/s); Rotor-disk-averaged relative wind velocity (y-component); the hub coordinate system
AeroDyn['RtVAvgzh'] = False # (m/s); Rotor-disk-averaged relative wind velocity (z-component); the hub coordinate system
AeroDyn['RtSkew'] = False # (deg); Rotor inflow-skew angle;
AeroDyn['RtAeroFxh'] = False # (N); Total rotor aerodynamic load (force in x direction); the hub coordinate system
AeroDyn['RtAeroFyh'] = False # (N); Total rotor aerodynamic load (force in y direction); the hub coordinate system
AeroDyn['RtAeroFzh'] = False # (N); Total rotor aerodynamic load (force in z direction); the hub coordinate system
AeroDyn['RtAeroMxh'] = False # (N m); Total rotor aerodynamic load (moment in x direction); the hub coordinate system
AeroDyn['RtAeroMyh'] = False # (N m); Total rotor aerodynamic load (moment in y direction); the hub coordinate system
AeroDyn['RtAeroMzh'] = False # (N m); Total rotor aerodynamic load (moment in z direction); the hub coordinate system
AeroDyn['RtAeroPwr'] = False # (W); Rotor aerodynamic power;
AeroDyn['RtArea'] = False # (m^2); Rotor swept area;
AeroDyn['RtAeroCp'] = False # (-); Rotor aerodynamic power coefficient;
AeroDyn['RtAeroCq'] = False # (-); Rotor aerodynamic torque coefficient;
AeroDyn['RtAeroCt'] = False # (-); Rotor aerodynamic thrust coefficient;
""" InflowWind """
InflowWind = {}
# Wind Motions
InflowWind['Wind1VelX'] = False # (m/s); X component of wind at user selected wind point 1; Directed along the xi-axis
InflowWind['Wind1VelY'] = False # (m/s); Y component of wind at user selected wind point 1; Directed along the yi-axis
InflowWind['Wind1VelZ'] = False # (m/s); Z component of wind at user selected wind point 1; Directed along the zi-axis
InflowWind['Wind2VelX'] = False # (m/s); X component of wind at user selected wind point 2; Directed along the xi-axis
InflowWind['Wind2VelY'] = False # (m/s); Y component of wind at user selected wind point 2; Directed along the yi-axis
InflowWind['Wind2VelZ'] = False # (m/s); Z component of wind at user selected wind point 2; Directed along the zi-axis
InflowWind['Wind3VelX'] = False # (m/s); X component of wind at user selected wind point 3; Directed along the xi-axis
InflowWind['Wind3VelY'] = False # (m/s); Y component of wind at user selected wind point 3; Directed along the yi-axis
InflowWind['Wind3VelZ'] = False # (m/s); Z component of wind at user selected wind point 3; Directed along the zi-axis
InflowWind['Wind4VelX'] = False # (m/s); X component of wind at user selected wind point 4; Directed along the xi-axis
InflowWind['Wind4VelY'] = False # (m/s); Y component of wind at user selected wind point 4; Directed along the yi-axis
InflowWind['Wind4VelZ'] = False # (m/s); Z component of wind at user selected wind point 4; Directed along the zi-axis
InflowWind['Wind5VelX'] = False # (m/s); X component of wind at user selected wind point 5; Directed along the xi-axis
InflowWind['Wind5VelY'] = False # (m/s); Y component of wind at user selected wind point 5; Directed along the yi-axis
InflowWind['Wind5VelZ'] = False # (m/s); Z component of wind at user selected wind point 5; Directed along the zi-axis
InflowWind['Wind6VelX'] = False # (m/s); X component of wind at user selected wind point 6; Directed along the xi-axis
InflowWind['Wind6VelY'] = False # (m/s); Y component of wind at user selected wind point 6; Directed along the yi-axis
InflowWind['Wind6VelZ'] = False # (m/s); Z component of wind at user selected wind point 6; Directed along the zi-axis
InflowWind['Wind7VelX'] = False # (m/s); X component of wind at user selected wind point 7; Directed along the xi-axis
InflowWind['Wind7VelY'] = False # (m/s); Y component of wind at user selected wind point 7; Directed along the yi-axis
InflowWind['Wind7VelZ'] = False # (m/s); Z component of wind at user selected wind point 7; Directed along the zi-axis
InflowWind['Wind8VelX'] = False # (m/s); X component of wind at user selected wind point 8; Directed along the xi-axis
InflowWind['Wind8VelY'] = False # (m/s); Y component of wind at user selected wind point 8; Directed along the yi-axis
InflowWind['Wind8VelZ'] = False # (m/s); Z component of wind at user selected wind point 8; Directed along the zi-axis
InflowWind['Wind9VelX'] = False # (m/s); X component of wind at user selected wind point 9; Directed along the xi-axis
InflowWind['Wind9VelY'] = False # (m/s); Y component of wind at user selected wind point 9; Directed along the yi-axis
InflowWind['Wind9VelZ'] = False # (m/s); Z component of wind at user selected wind point 9; Directed along the zi-axis
# Wind Sensor Measurements
InflowWind['WindMeas1'] = False # (m/s); Wind measurement at sensor 1; Defined by sensor
InflowWind['WindMeas2'] = False # (m/s); Wind measurement at sensor 2; Defined by sensor
InflowWind['WindMeas3'] = False # (m/s); Wind measurement at sensor 3; Defined by sensor
InflowWind['WindMeas4'] = False # (m/s); Wind measurement at sensor 4; Defined by sensor
InflowWind['WindMeas5'] = False # (m/s); Wind measurement at sensor 5; Defined by sensor
""" WAMIT """
WAMIT = {}
# WAMIT Body Forces
WAMIT['Wave1El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave2El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave3El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave4El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave5El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave6El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave7El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave8El2'] = False # (m); 2nd order wave elevation correction;
WAMIT['Wave9El2'] = False # (m); 2nd order wave elevation correction;
# WAMIT second order Body Forces
WAMIT['WavesF2xi'] = False # (N); ;
WAMIT['WavesF2yi'] = False # (N); ;
WAMIT['WavesF2zi'] = False # (N); ;
WAMIT['WavesM2xi'] = False # (N m); ;
WAMIT['WavesM2yi'] = False # (N m); ;
WAMIT['WavesM2zi'] = False # (N m); ;
# WAMIT Body Forces
WAMIT['WavesFxi'] = False # (N); ;
WAMIT['WavesFyi'] = False # (N); ;
WAMIT['WavesFzi'] = False # (N); ;
WAMIT['WavesMxi'] = False # (N m); ;
WAMIT['WavesMyi'] = False # (N m); ;
WAMIT['WavesMzi'] = False # (N m); ;
WAMIT['HdrStcFxi'] = False # (N); ;
WAMIT['HdrStcFyi'] = False # (N); ;
WAMIT['HdrStcFzi'] = False # (N); ;
WAMIT['HdrStcMxi'] = False # (N m); ;
WAMIT['HdrStcMyi'] = False # (N m); ;
WAMIT['HdrStcMzi'] = False # (N m); ;
WAMIT['RdtnFxi'] = False # (N); ;
WAMIT['RdtnFyi'] = False # (N); ;
WAMIT['RdtnFzi'] = False # (N); ;
WAMIT['RdtnMxi'] = False # (N m); ;
WAMIT['RdtnMyi'] = False # (N m); ;
WAMIT['RdtnMzi'] = False # (N m); ;
""" HydroDyn """
HydroDyn = {}
# Forces due to additional preload, stiffness, and damping
HydroDyn['AddFxi'] = False # (N); ;
HydroDyn['AddFyi'] = False # (N); ;
HydroDyn['AddFzi'] = False # (N); ;
HydroDyn['AddMxi'] = False # (N m); ;
HydroDyn['AddMyi'] = False # (N m); ;
HydroDyn['AddMzi'] = False # (N m); ;
# Integrated hydrodynamic loads at the WAMIT reference point
HydroDyn['HydroFxi'] = False # (N); ;
HydroDyn['HydroFyi'] = False # (N); ;
HydroDyn['HydroFzi'] = False # (N); ;
HydroDyn['HydroMxi'] = False # (N m); ;
HydroDyn['HydroMyi'] = False # (N m); ;
HydroDyn['HydroMzi'] = False # (N m); ;
# Wave Motions
HydroDyn['Wave1Elev'] = False # (m); ;
HydroDyn['Wave2Elev'] = False # (m); ;
HydroDyn['Wave3Elev'] = False # (m); ;
HydroDyn['Wave4Elev'] = False # (m); ;
HydroDyn['Wave5Elev'] = False # (m); ;
HydroDyn['Wave6Elev'] = False # (m); ;
HydroDyn['Wave7Elev'] = False # (m); ;
HydroDyn['Wave8Elev'] = False # (m); ;
HydroDyn['Wave9Elev'] = False # (m); ;
# WRP Motions
HydroDyn['WRPSurge'] = False # (m); ;
HydroDyn['WRPSway'] = False # (m); ;
HydroDyn['WRPHeave'] = False # (m); ;
HydroDyn['WRPRoll'] = False # (rad); ;
HydroDyn['WRPPitch'] = False # (rad); ;
HydroDyn['WRPYaw'] = False # (rad); ;
HydroDyn['WRPTVxi'] = False # (m/s); ;
HydroDyn['WRPTVyi'] = False # (m/s); ;
HydroDyn['WRPTVzi'] = False # (m/s); ;
HydroDyn['WRPRVxi'] = False # (rad/s); ;
HydroDyn['WRPRVyi'] = False # (rad/s); ;
HydroDyn['WRPRVzi'] = False # (rad/s); ;
HydroDyn['WRPTAxi'] = False # (m/s^2); ;
HydroDyn['WRPTAyi'] = False # (m/s^2); ;
HydroDyn['WRPTAzi'] = False # (m/s^2); ;
HydroDyn['WRPRAxi'] = False # (rad/s^2); ;
HydroDyn['WRPRAyi'] = False # (rad/s^2); ;
HydroDyn['WRPRAzi'] = False # (rad/s^2); ;
""" Morison """
Morison = {}
# Member-level Wave Kinematics
Morison['M1N1Axi'] = False # (m/s^2); fluid acceleration;
Morison['M1N2Axi'] = False # (m/s^2); ;
Morison['M1N3Axi'] = False # (m/s^2); ;
Morison['M1N4Axi'] = False # (m/s^2); ;
Morison['M1N5Axi'] = False # (m/s^2); ;
Morison['M1N6Axi'] = False # (m/s^2); ;
Morison['M1N7Axi'] = False # (m/s^2); ;
Morison['M1N8Axi'] = False # (m/s^2); ;
Morison['M1N9Axi'] = False # (m/s^2); ;
Morison['M2N1Axi'] = False # (m/s^2); ;
Morison['M2N2Axi'] = False # (m/s^2); ;
Morison['M2N3Axi'] = False # (m/s^2); ;
Morison['M2N4Axi'] = False # (m/s^2); ;
Morison['M2N5Axi'] = False # (m/s^2); ;
Morison['M2N6Axi'] = False # (m/s^2); ;
Morison['M2N7Axi'] = False # (m/s^2); ;
Morison['M2N8Axi'] = False # (m/s^2); ;
Morison['M2N9Axi'] = False # (m/s^2); ;
Morison['M3N1Axi'] = False # (m/s^2); ;
Morison['M3N2Axi'] = False # (m/s^2); ;
Morison['M3N3Axi'] = False # (m/s^2); ;
Morison['M3N4Axi'] = False # (m/s^2); ;
Morison['M3N5Axi'] = False # (m/s^2); ;
Morison['M3N6Axi'] = False # (m/s^2); ;
Morison['M3N7Axi'] = False # (m/s^2); ;
Morison['M3N8Axi'] = False # (m/s^2); ;
Morison['M3N9Axi'] = False # (m/s^2); ;
Morison['M4N1Axi'] = False # (m/s^2); ;
Morison['M4N2Axi'] = False # (m/s^2); ;
Morison['M4N3Axi'] = False # (m/s^2); ;
Morison['M4N4Axi'] = False # (m/s^2); ;
Morison['M4N5Axi'] = False # (m/s^2); ;
Morison['M4N6Axi'] = False # (m/s^2); ;
Morison['M4N7Axi'] = False # (m/s^2); ;
Morison['M4N8Axi'] = False # (m/s^2); ;
Morison['M4N9Axi'] = False # (m/s^2); ;
Morison['M5N1Axi'] = False # (m/s^2); ;
Morison['M5N2Axi'] = False # (m/s^2); ;
Morison['M5N3Axi'] = False # (m/s^2); ;
Morison['M5N4Axi'] = False # (m/s^2); ;
Morison['M5N5Axi'] = False # (m/s^2); ;
Morison['M5N6Axi'] = False # (m/s^2); ;
Morison['M5N7Axi'] = False # (m/s^2); ;
Morison['M5N8Axi'] = False # (m/s^2); ;
Morison['M5N9Axi'] = False # (m/s^2); ;
Morison['M6N1Axi'] = False # (m/s^2); ;
Morison['M6N2Axi'] = False # (m/s^2); ;
Morison['M6N3Axi'] = False # (m/s^2); ;
Morison['M6N4Axi'] = False # (m/s^2); ;
Morison['M6N5Axi'] = False # (m/s^2); ;
Morison['M6N6Axi'] = False # (m/s^2); ;
Morison['M6N7Axi'] = False # (m/s^2); ;
Morison['M6N8Axi'] = False # (m/s^2); ;
Morison['M6N9Axi'] = False # (m/s^2); ;
Morison['M7N1Axi'] = False # (m/s^2); ;
Morison['M7N2Axi'] = False # (m/s^2); ;
Morison['M7N3Axi'] = False # (m/s^2); ;
Morison['M7N4Axi'] = False # (m/s^2); ;
Morison['M7N5Axi'] = False # (m/s^2); ;
Morison['M7N6Axi'] = False # (m/s^2); ;
Morison['M7N7Axi'] = False # (m/s^2); ;
Morison['M7N8Axi'] = False # (m/s^2); ;
Morison['M7N9Axi'] = False # (m/s^2); ;
Morison['M8N1Axi'] = False # (m/s^2); ;
Morison['M8N2Axi'] = False # (m/s^2); ;
Morison['M8N3Axi'] = False # (m/s^2); ;
Morison['M8N4Axi'] = False # (m/s^2); ;
Morison['M8N5Axi'] = False # (m/s^2); ;
Morison['M8N6Axi'] = False # (m/s^2); ;
Morison['M8N7Axi'] = False # (m/s^2); ;
Morison['M8N8Axi'] = False # (m/s^2); ;
Morison['M8N9Axi'] = False # (m/s^2); ;
Morison['M9N1Axi'] = False # (m/s^2); ;
Morison['M9N2Axi'] = False # (m/s^2); ;
Morison['M9N3Axi'] = False # (m/s^2); ;
Morison['M9N4Axi'] = False # (m/s^2); ;
Morison['M9N5Axi'] = False # (m/s^2); ;
Morison['M9N6Axi'] = False # (m/s^2); ;
Morison['M9N7Axi'] = False # (m/s^2); ;
Morison['M9N8Axi'] = False # (m/s^2); ;
Morison['M9N9Axi'] = False # (m/s^2); ;
Morison['M1N1Ayi'] = False # (m/s^2); ;
Morison['M1N2Ayi'] = False # (m/s^2); ;
Morison['M1N3Ayi'] = False # (m/s^2); ;
Morison['M1N4Ayi'] = False # (m/s^2); ;
Morison['M1N5Ayi'] = False # (m/s^2); ;
Morison['M1N6Ayi'] = False # (m/s^2); ;
Morison['M1N7Ayi'] = False # (m/s^2); ;
Morison['M1N8Ayi'] = False # (m/s^2); ;
Morison['M1N9Ayi'] = False # (m/s^2); ;
Morison['M2N1Ayi'] = False # (m/s^2); ;
Morison['M2N2Ayi'] = False # (m/s^2); ;
Morison['M2N3Ayi'] = False # (m/s^2); ;
Morison['M2N4Ayi'] = False # (m/s^2); ;
Morison['M2N5Ayi'] = False # (m/s^2); ;
Morison['M2N6Ayi'] = False # (m/s^2); ;
Morison['M2N7Ayi'] = False # (m/s^2); ;
Morison['M2N8Ayi'] = False # (m/s^2); ;
Morison['M2N9Ayi'] = False # (m/s^2); ;
Morison['M3N1Ayi'] = False # (m/s^2); ;
Morison['M3N2Ayi'] = False # (m/s^2); ;
Morison['M3N3Ayi'] = False # (m/s^2); ;
Morison['M3N4Ayi'] = False # (m/s^2); ;
Morison['M3N5Ayi'] = False # (m/s^2); ;
Morison['M3N6Ayi'] = False # (m/s^2); ;
Morison['M3N7Ayi'] = False # (m/s^2); ;
Morison['M3N8Ayi'] = False # (m/s^2); ;
Morison['M3N9Ayi'] = False # (m/s^2); ;
Morison['M4N1Ayi'] = False # (m/s^2); ;
Morison['M4N2Ayi'] = False # (m/s^2); ;
Morison['M4N3Ayi'] = False # (m/s^2); ;
Morison['M4N4Ayi'] = False # (m/s^2); ;
Morison['M4N5Ayi'] = False # (m/s^2); ;
Morison['M4N6Ayi'] = False # (m/s^2); ;
Morison['M4N7Ayi'] = False # (m/s^2); ;
Morison['M4N8Ayi'] = False # (m/s^2); ;
Morison['M4N9Ayi'] = False # (m/s^2); ;
Morison['M5N1Ayi'] = False # (m/s^2); ;
Morison['M5N2Ayi'] = False # (m/s^2); ;
Morison['M5N3Ayi'] = False # (m/s^2); ;
Morison['M5N4Ayi'] = False # (m/s^2); ;
Morison['M5N5Ayi'] = False # (m/s^2); ;
Morison['M5N6Ayi'] = False # (m/s^2); ;
Morison['M5N7Ayi'] = False # (m/s^2); ;
Morison['M5N8Ayi'] = False # (m/s^2); ;
Morison['M5N9Ayi'] = False # (m/s^2); ;
Morison['M6N1Ayi'] = False # (m/s^2); ;
Morison['M6N2Ayi'] = False # (m/s^2); ;
Morison['M6N3Ayi'] = False # (m/s^2); ;
Morison['M6N4Ayi'] = False # (m/s^2); ;
Morison['M6N5Ayi'] = False # (m/s^2); ;
Morison['M6N6Ayi'] = False # (m/s^2); ;
Morison['M6N7Ayi'] = False # (m/s^2); ;
Morison['M6N8Ayi'] = False # (m/s^2); ;
Morison['M6N9Ayi'] = False # (m/s^2); ;
Morison['M7N1Ayi'] = False # (m/s^2); ;
Morison['M7N2Ayi'] = False # (m/s^2); ;
Morison['M7N3Ayi'] = False # (m/s^2); ;
Morison['M7N4Ayi'] = False # (m/s^2); ;
Morison['M7N5Ayi'] = False # (m/s^2); ;
Morison['M7N6Ayi'] = False # (m/s^2); ;
Morison['M7N7Ayi'] = False # (m/s^2); ;
Morison['M7N8Ayi'] = False # (m/s^2); ;
Morison['M7N9Ayi'] = False # (m/s^2); ;
Morison['M8N1Ayi'] = False # (m/s^2); ;
Morison['M8N2Ayi'] = False # (m/s^2); ;
Morison['M8N3Ayi'] = False # (m/s^2); ;
Morison['M8N4Ayi'] = False # (m/s^2); ;
Morison['M8N5Ayi'] = False # (m/s^2); ;
Morison['M8N6Ayi'] = False # (m/s^2); ;
Morison['M8N7Ayi'] = False # (m/s^2); ;
Morison['M8N8Ayi'] = False # (m/s^2); ;
Morison['M8N9Ayi'] = False # (m/s^2); ;
Morison['M9N1Ayi'] = False # (m/s^2); ;
Morison['M9N2Ayi'] = False # (m/s^2); ;
Morison['M9N3Ayi'] = False # (m/s^2); ;
Morison['M9N4Ayi'] = False # (m/s^2); ;
Morison['M9N5Ayi'] = False # (m/s^2); ;
Morison['M9N6Ayi'] = False # (m/s^2); ;
Morison['M9N7Ayi'] = False # (m/s^2); ;
Morison['M9N8Ayi'] = False # (m/s^2); ;
Morison['M9N9Ayi'] = False # (m/s^2); ;
Morison['M1N1Azi'] = False # (m/s^2); ;
Morison['M1N2Azi'] = False # (m/s^2); ;
Morison['M1N3Azi'] = False # (m/s^2); ;
Morison['M1N4Azi'] = False # (m/s^2); ;
Morison['M1N5Azi'] = False # (m/s^2); ;
Morison['M1N6Azi'] = False # (m/s^2); ;
Morison['M1N7Azi'] = False # (m/s^2); ;
Morison['M1N8Azi'] = False # (m/s^2); ;
Morison['M1N9Azi'] = False # (m/s^2); ;
Morison['M2N1Azi'] = False # (m/s^2); ;
Morison['M2N2Azi'] = False # (m/s^2); ;
Morison['M2N3Azi'] = False # (m/s^2); ;
Morison['M2N4Azi'] = False # (m/s^2); ;
Morison['M2N5Azi'] = False # (m/s^2); ;
Morison['M2N6Azi'] = False # (m/s^2); ;
Morison['M2N7Azi'] = False # (m/s^2); ;
Morison['M2N8Azi'] = False # (m/s^2); ;
Morison['M2N9Azi'] = False # (m/s^2); ;
Morison['M3N1Azi'] = False # (m/s^2); ;
Morison['M3N2Azi'] = False # (m/s^2); ;
Morison['M3N3Azi'] = False # (m/s^2); ;
Morison['M3N4Azi'] = False # (m/s^2); ;
Morison['M3N5Azi'] = False # (m/s^2); ;
Morison['M3N6Azi'] = False # (m/s^2); ;
Morison['M3N7Azi'] = False # (m/s^2); ;
Morison['M3N8Azi'] = False # (m/s^2); ;
Morison['M3N9Azi'] = False # (m/s^2); ;
Morison['M4N1Azi'] = False # (m/s^2); ;
Morison['M4N2Azi'] = False # (m/s^2); ;
Morison['M4N3Azi'] = False # (m/s^2); ;
Morison['M4N4Azi'] = False # (m/s^2); ;
Morison['M4N5Azi'] = False # (m/s^2); ;
Morison['M4N6Azi'] = False # (m/s^2); ;
Morison['M4N7Azi'] = False # (m/s^2); ;
Morison['M4N8Azi'] = False # (m/s^2); ;
Morison['M4N9Azi'] = False # (m/s^2); ;
Morison['M5N1Azi'] = False # (m/s^2); ;
Morison['M5N2Azi'] = False # (m/s^2); ;
Morison['M5N3Azi'] = False # (m/s^2); ;
Morison['M5N4Azi'] = False # (m/s^2); ;
Morison['M5N5Azi'] = False # (m/s^2); ;
Morison['M5N6Azi'] = False # (m/s^2); ;
Morison['M5N7Azi'] = False # (m/s^2); ;
Morison['M5N8Azi'] = False # (m/s^2); ;
Morison['M5N9Azi'] = False # (m/s^2); ;
Morison['M6N1Azi'] = False # (m/s^2); ;
Morison['M6N2Azi'] = False # (m/s^2); ;
Morison['M6N3Azi'] = False # (m/s^2); ;
Morison['M6N4Azi'] = False # (m/s^2); ;
Morison['M6N5Azi'] = False # (m/s^2); ;
Morison['M6N6Azi'] = False # (m/s^2); ;
Morison['M6N7Azi'] = False # (m/s^2); ;
Morison['M6N8Azi'] = False # (m/s^2); ;
Morison['M6N9Azi'] = False # (m/s^2); ;
Morison['M7N1Azi'] = False # (m/s^2); ;
Morison['M7N2Azi'] = False # (m/s^2); ;
Morison['M7N3Azi'] = False # (m/s^2); ;
Morison['M7N4Azi'] = False # (m/s^2); ;
Morison['M7N5Azi'] = False # (m/s^2); ;
Morison['M7N6Azi'] = False # (m/s^2); ;
Morison['M7N7Azi'] = False # (m/s^2); ;
Morison['M7N8Azi'] = False # (m/s^2); ;
Morison['M7N9Azi'] = False # (m/s^2); ;
Morison['M8N1Azi'] = False # (m/s^2); ;
Morison['M8N2Azi'] = False # (m/s^2); ;
Morison['M8N3Azi'] = False # (m/s^2); ;
Morison['M8N4Azi'] = False # (m/s^2); ;
Morison['M8N5Azi'] = False # (m/s^2); ;
Morison['M8N6Azi'] = False # (m/s^2); ;
Morison['M8N7Azi'] = False # (m/s^2); ;
Morison['M8N8Azi'] = False # (m/s^2); ;
Morison['M8N9Azi'] = False # (m/s^2); ;
Morison['M9N1Azi'] = False # (m/s^2); ;
Morison['M9N2Azi'] = False # (m/s^2); ;
Morison['M9N3Azi'] = False # (m/s^2); ;
Morison['M9N4Azi'] = False # (m/s^2); ;
Morison['M9N5Azi'] = False # (m/s^2); ;
Morison['M9N6Azi'] = False # (m/s^2); ;
Morison['M9N7Azi'] = False # (m/s^2); ;
Morison['M9N8Azi'] = False # (m/s^2); ;
Morison['M9N9Azi'] = False # (m/s^2); ;
Morison['M1N1Vxi'] = False # (m/s); fluid velocity;
Morison['M1N2Vxi'] = False # (m/s); ;
Morison['M1N3Vxi'] = False # (m/s); ;
Morison['M1N4Vxi'] = False # (m/s); ;
Morison['M1N5Vxi'] = False # (m/s); ;
Morison['M1N6Vxi'] = False # (m/s); ;
Morison['M1N7Vxi'] = False # (m/s); ;
Morison['M1N8Vxi'] = False # (m/s); ;
Morison['M1N9Vxi'] = False # (m/s); ;
Morison['M2N1Vxi'] = False # (m/s); ;
Morison['M2N2Vxi'] = False # (m/s); ;
Morison['M2N3Vxi'] = False # (m/s); ;
Morison['M2N4Vxi'] = False # (m/s); ;
Morison['M2N5Vxi'] = False # (m/s); ;
Morison['M2N6Vxi'] = False # (m/s); ;
Morison['M2N7Vxi'] = False # (m/s); ;
Morison['M2N8Vxi'] = False # (m/s); ;
Morison['M2N9Vxi'] = False # (m/s); ;
Morison['M3N1Vxi'] = False # (m/s); ;
Morison['M3N2Vxi'] = False # (m/s); ;
Morison['M3N3Vxi'] = False # (m/s); ;
Morison['M3N4Vxi'] = False # (m/s); ;
Morison['M3N5Vxi'] = False # (m/s); ;
Morison['M3N6Vxi'] = False # (m/s); ;
Morison['M3N7Vxi'] = False # (m/s); ;
Morison['M3N8Vxi'] = False # (m/s); ;
Morison['M3N9Vxi'] = False # (m/s); ;
Morison['M4N1Vxi'] = False # (m/s); ;
Morison['M4N2Vxi'] = False # (m/s); ;
Morison['M4N3Vxi'] = False # (m/s); ;
Morison['M4N4Vxi'] = False # (m/s); ;
Morison['M4N5Vxi'] = False # (m/s); ;
Morison['M4N6Vxi'] = False # (m/s); ;
Morison['M4N7Vxi'] = False # (m/s); ;
Morison['M4N8Vxi'] = False # (m/s); ;
Morison['M4N9Vxi'] = False # (m/s); ;
Morison['M5N1Vxi'] = False # (m/s); ;
Morison['M5N2Vxi'] = False # (m/s); ;
Morison['M5N3Vxi'] = False # (m/s); ;
Morison['M5N4Vxi'] = False # (m/s); ;
Morison['M5N5Vxi'] = False # (m/s); ;
Morison['M5N6Vxi'] = False # (m/s); ;
Morison['M5N7Vxi'] = False # (m/s); ;
Morison['M5N8Vxi'] = False # (m/s); ;
Morison['M5N9Vxi'] = False # (m/s); ;
Morison['M6N1Vxi'] = False # (m/s); ;
Morison['M6N2Vxi'] = False # (m/s); ;
Morison['M6N3Vxi'] = False # (m/s); ;
Morison['M6N4Vxi'] = False # (m/s); ;
Morison['M6N5Vxi'] = False # (m/s); ;
Morison['M6N6Vxi'] = False # (m/s); ;
Morison['M6N7Vxi'] = False # (m/s); ;
Morison['M6N8Vxi'] = False # (m/s); ;
Morison['M6N9Vxi'] = False # (m/s); ;
Morison['M7N1Vxi'] = False # (m/s); ;
Morison['M7N2Vxi'] = False # (m/s); ;
Morison['M7N3Vxi'] = False # (m/s); ;
Morison['M7N4Vxi'] = False # (m/s); ;
Morison['M7N5Vxi'] = False # (m/s); ;
Morison['M7N6Vxi'] = False # (m/s); ;
Morison['M7N7Vxi'] = False # (m/s); ;
Morison['M7N8Vxi'] = False # (m/s); ;
Morison['M7N9Vxi'] = False # (m/s); ;
Morison['M8N1Vxi'] = False # (m/s); ;
Morison['M8N2Vxi'] = False # (m/s); ;
Morison['M8N3Vxi'] = False # (m/s); ;
Morison['M8N4Vxi'] = False # (m/s); ;
Morison['M8N5Vxi'] = False # (m/s); ;
Morison['M8N6Vxi'] = False # (m/s); ;
Morison['M8N7Vxi'] = False # (m/s); ;
Morison['M8N8Vxi'] = False # (m/s); ;
Morison['M8N9Vxi'] = False # (m/s); ;
Morison['M9N1Vxi'] = False # (m/s); ;
Morison['M9N2Vxi'] = False # (m/s); ;
Morison['M9N3Vxi'] = False # (m/s); ;
Morison['M9N4Vxi'] = False # (m/s); ;
Morison['M9N5Vxi'] = False # (m/s); ;
Morison['M9N6Vxi'] = False # (m/s); ;
Morison['M9N7Vxi'] = False # (m/s); ;
Morison['M9N8Vxi'] = False # (m/s); ;
Morison['M9N9Vxi'] = False # (m/s); ;
Morison['M1N1Vyi'] = False # (m/s); ;
Morison['M1N2Vyi'] = False # (m/s); ;
Morison['M1N3Vyi'] = False # (m/s); ;
Morison['M1N4Vyi'] = False # (m/s); ;
Morison['M1N5Vyi'] = False # (m/s); ;
Morison['M1N6Vyi'] = False # (m/s); ;
Morison['M1N7Vyi'] = False # (m/s); ;
Morison['M1N8Vyi'] = False # (m/s); ;
Morison['M1N9Vyi'] = False # (m/s); ;
Morison['M2N1Vyi'] = False # (m/s); ;
Morison['M2N2Vyi'] = False # (m/s); ;
Morison['M2N3Vyi'] = False # (m/s); ;
Morison['M2N4Vyi'] = False # (m/s); ;
Morison['M2N5Vyi'] = False # (m/s); ;
Morison['M2N6Vyi'] = False # (m/s); ;
Morison['M2N7Vyi'] = False # (m/s); ;
Morison['M2N8Vyi'] = False # (m/s); ;
Morison['M2N9Vyi'] = False # (m/s); ;
Morison['M3N1Vyi'] = False # (m/s); ;
Morison['M3N2Vyi'] = False # (m/s); ;
Morison['M3N3Vyi'] = False # (m/s); ;
Morison['M3N4Vyi'] = False # (m/s); ;
Morison['M3N5Vyi'] = False # (m/s); ;
Morison['M3N6Vyi'] = False # (m/s); ;
Morison['M3N7Vyi'] = False # (m/s); ;
Morison['M3N8Vyi'] = False # (m/s); ;
Morison['M3N9Vyi'] = False # (m/s); ;
Morison['M4N1Vyi'] = False # (m/s); ;
Morison['M4N2Vyi'] = False # (m/s); ;
Morison['M4N3Vyi'] = False # (m/s); ;
Morison['M4N4Vyi'] = False # (m/s); ;
Morison['M4N5Vyi'] = False # (m/s); ;
Morison['M4N6Vyi'] = False # (m/s); ;
Morison['M4N7Vyi'] = False # (m/s); ;
Morison['M4N8Vyi'] = False # (m/s); ;
Morison['M4N9Vyi'] = False # (m/s); ;
Morison['M5N1Vyi'] = False # (m/s); ;
Morison['M5N2Vyi'] = False # (m/s); ;
Morison['M5N3Vyi'] = False # (m/s); ;
Morison['M5N4Vyi'] = False # (m/s); ;
Morison['M5N5Vyi'] = False # (m/s); ;
Morison['M5N6Vyi'] = False # (m/s); ;
Morison['M5N7Vyi'] = False # (m/s); ;
Morison['M5N8Vyi'] = False # (m/s); ;
Morison['M5N9Vyi'] = False # (m/s); ;
Morison['M6N1Vyi'] = False # (m/s); ;
Morison['M6N2Vyi'] = False # (m/s); ;
Morison['M6N3Vyi'] = False # (m/s); ;
Morison['M6N4Vyi'] = False # (m/s); ;
Morison['M6N5Vyi'] = False # (m/s); ;
Morison['M6N6Vyi'] = False # (m/s); ;
Morison['M6N7Vyi'] = False # (m/s); ;
Morison['M6N8Vyi'] = False # (m/s); ;
Morison['M6N9Vyi'] = False # (m/s); ;
Morison['M7N1Vyi'] = False # (m/s); ;
Morison['M7N2Vyi'] = False # (m/s); ;
Morison['M7N3Vyi'] = False # (m/s); ;
Morison['M7N4Vyi'] = False # (m/s); ;
Morison['M7N5Vyi'] = False # (m/s); ;
Morison['M7N6Vyi'] = False # (m/s); ;
Morison['M7N7Vyi'] = False # (m/s); ;
Morison['M7N8Vyi'] = False # (m/s); ;
Morison['M7N9Vyi'] = False # (m/s); ;
Morison['M8N1Vyi'] = False # (m/s); ;
Morison['M8N2Vyi'] = False # (m/s); ;
Morison['M8N3Vyi'] = False # (m/s); ;
Morison['M8N4Vyi'] = False # (m/s); ;
Morison['M8N5Vyi'] = False # (m/s); ;
Morison['M8N6Vyi'] = False # (m/s); ;
Morison['M8N7Vyi'] = False # (m/s); ;
Morison['M8N8Vyi'] = False # (m/s); ;
Morison['M8N9Vyi'] = False # (m/s); ;
Morison['M9N1Vyi'] = False # (m/s); ;
Morison['M9N2Vyi'] = False # (m/s); ;
Morison['M9N3Vyi'] = False # (m/s); ;
Morison['M9N4Vyi'] = False # (m/s); ;
Morison['M9N5Vyi'] = False # (m/s); ;
Morison['M9N6Vyi'] = False # (m/s); ;
Morison['M9N7Vyi'] = False # (m/s); ;
Morison['M9N8Vyi'] = False # (m/s); ;
Morison['M9N9Vyi'] = False # (m/s); ;
Morison['M1N1Vzi'] = False # (m/s); ;
Morison['M1N2Vzi'] = False # (m/s); ;
Morison['M1N3Vzi'] = False # (m/s); ;
Morison['M1N4Vzi'] = False # (m/s); ;
Morison['M1N5Vzi'] = False # (m/s); ;
Morison['M1N6Vzi'] = False # (m/s); ;
Morison['M1N7Vzi'] = False # (m/s); ;
Morison['M1N8Vzi'] = False # (m/s); ;
Morison['M1N9Vzi'] = False # (m/s); ;
Morison['M2N1Vzi'] = False # (m/s); ;
Morison['M2N2Vzi'] = False # (m/s); ;
Morison['M2N3Vzi'] = False # (m/s); ;
Morison['M2N4Vzi'] = False # (m/s); ;
Morison['M2N5Vzi'] = False # (m/s); ;
Morison['M2N6Vzi'] = False # (m/s); ;
Morison['M2N7Vzi'] = False # (m/s); ;
Morison['M2N8Vzi'] = False # (m/s); ;
Morison['M2N9Vzi'] = False # (m/s); ;
Morison['M3N1Vzi'] = False # (m/s); ;
Morison['M3N2Vzi'] = False # (m/s); ;
Morison['M3N3Vzi'] = False # (m/s); ;
Morison['M3N4Vzi'] = False # (m/s); ;
Morison['M3N5Vzi'] = False # (m/s); ;
Morison['M3N6Vzi'] = False # (m/s); ;
Morison['M3N7Vzi'] = False # (m/s); ;
Morison['M3N8Vzi'] = False # (m/s); ;
Morison['M3N9Vzi'] = False # (m/s); ;
Morison['M4N1Vzi'] = False # (m/s); ;
Morison['M4N2Vzi'] = False # (m/s); ;
Morison['M4N3Vzi'] = False # (m/s); ;
Morison['M4N4Vzi'] = False # (m/s); ;
Morison['M4N5Vzi'] = False # (m/s); ;
Morison['M4N6Vzi'] = False # (m/s); ;
Morison['M4N7Vzi'] = False # (m/s); ;
Morison['M4N8Vzi'] = False # (m/s); ;
Morison['M4N9Vzi'] = False # (m/s); ;
Morison['M5N1Vzi'] = False # (m/s); ;
Morison['M5N2Vzi'] = False # (m/s); ;
Morison['M5N3Vzi'] = False # (m/s); ;
Morison['M5N4Vzi'] = False # (m/s); ;
Morison['M5N5Vzi'] = False # (m/s); ;
Morison['M5N6Vzi'] = False # (m/s); ;
Morison['M5N7Vzi'] = False # (m/s); ;
Morison['M5N8Vzi'] = False # (m/s); ;
Morison['M5N9Vzi'] = False # (m/s); ;
Morison['M6N1Vzi'] = False # (m/s); ;
Morison['M6N2Vzi'] = False # (m/s); ;
Morison['M6N3Vzi'] = False # (m/s); ;
Morison['M6N4Vzi'] = False # (m/s); ;
Morison['M6N5Vzi'] = False # (m/s); ;
Morison['M6N6Vzi'] = False # (m/s); ;
Morison['M6N7Vzi'] = False # (m/s); ;
Morison['M6N8Vzi'] = False # (m/s); ;
Morison['M6N9Vzi'] = False # (m/s); ;
Morison['M7N1Vzi'] = False # (m/s); ;
Morison['M7N2Vzi'] = False # (m/s); ;
Morison['M7N3Vzi'] = False # (m/s); ;
Morison['M7N4Vzi'] = False # (m/s); ;
Morison['M7N5Vzi'] = False # (m/s); ;
Morison['M7N6Vzi'] = False # (m/s); ;
Morison['M7N7Vzi'] = False # (m/s); ;
Morison['M7N8Vzi'] = False # (m/s); ;
Morison['M7N9Vzi'] = False # (m/s); ;
Morison['M8N1Vzi'] = False # (m/s); ;
Morison['M8N2Vzi'] = False # (m/s); ;
Morison['M8N3Vzi'] = False # (m/s); ;
Morison['M8N4Vzi'] = False # (m/s); ;
Morison['M8N5Vzi'] = False # (m/s); ;
Morison['M8N6Vzi'] = False # (m/s); ;
Morison['M8N7Vzi'] = False # (m/s); ;
Morison['M8N8Vzi'] = False # (m/s); ;
Morison['M8N9Vzi'] = False # (m/s); ;
Morison['M9N1Vzi'] = False # (m/s); ;
Morison['M9N2Vzi'] = False # (m/s); ;
Morison['M9N3Vzi'] = False # (m/s); ;
Morison['M9N4Vzi'] = False # (m/s); ;
Morison['M9N5Vzi'] = False # (m/s); ;
Morison['M9N6Vzi'] = False # (m/s); ;
Morison['M9N7Vzi'] = False # (m/s); ;
Morison['M9N8Vzi'] = False # (m/s); ;
Morison['M9N9Vzi'] = False # (m/s); ;
Morison['M1N1DynP'] = False # (Pa); fluid dynamic pressure;
Morison['M1N2DynP'] = False # (Pa); ;
Morison['M1N3DynP'] = False # (Pa); ;
Morison['M1N4DynP'] = False # (Pa); ;
Morison['M1N5DynP'] = False # (Pa); ;
Morison['M1N6DynP'] = False # (Pa); ;
Morison['M1N7DynP'] = False # (Pa); ;
Morison['M1N8DynP'] = False # (Pa); ;
Morison['M1N9DynP'] = False # (Pa); ;
Morison['M2N1DynP'] = False # (Pa); ;
Morison['M2N2DynP'] = False # (Pa); ;
Morison['M2N3DynP'] = False # (Pa); ;
Morison['M2N4DynP'] = False # (Pa); ;
Morison['M2N5DynP'] = False # (Pa); ;
Morison['M2N6DynP'] = False # (Pa); ;
Morison['M2N7DynP'] = False # (Pa); ;
Morison['M2N8DynP'] = False # (Pa); ;
Morison['M2N9DynP'] = False # (Pa); ;
Morison['M3N1DynP'] = False # (Pa); ;
Morison['M3N2DynP'] = False # (Pa); ;
Morison['M3N3DynP'] = False # (Pa); ;
Morison['M3N4DynP'] = False # (Pa); ;
Morison['M3N5DynP'] = False # (Pa); ;
Morison['M3N6DynP'] = False # (Pa); ;
Morison['M3N7DynP'] = False # (Pa); ;
Morison['M3N8DynP'] = False # (Pa); ;
Morison['M3N9DynP'] = False # (Pa); ;
Morison['M4N1DynP'] = False # (Pa); ;
Morison['M4N2DynP'] = False # (Pa); ;
Morison['M4N3DynP'] = False # (Pa); ;
Morison['M4N4DynP'] = False # (Pa); ;
Morison['M4N5DynP'] = False # (Pa); ;
Morison['M4N6DynP'] = False # (Pa); ;
Morison['M4N7DynP'] = False # (Pa); ;
Morison['M4N8DynP'] = False # (Pa); ;
Morison['M4N9DynP'] = False # (Pa); ;
Morison['M5N1DynP'] = False # (Pa); ;
Morison['M5N2DynP'] = False # (Pa); ;
Morison['M5N3DynP'] = False # (Pa); ;
Morison['M5N4DynP'] = False # (Pa); ;
Morison['M5N5DynP'] = False # (Pa); ;
Morison['M5N6DynP'] = False # (Pa); ;
Morison['M5N7DynP'] = False # (Pa); ;
Morison['M5N8DynP'] = False # (Pa); ;
Morison['M5N9DynP'] = False # (Pa); ;
Morison['M6N1DynP'] = False # (Pa); ;
Morison['M6N2DynP'] = False # (Pa); ;
Morison['M6N3DynP'] = False # (Pa); ;
Morison['M6N4DynP'] = False # (Pa); ;
Morison['M6N5DynP'] = False # (Pa); ;
Morison['M6N6DynP'] = False # (Pa); ;
Morison['M6N7DynP'] = False # (Pa); ;
Morison['M6N8DynP'] = False # (Pa); ;
Morison['M6N9DynP'] = False # (Pa); ;
Morison['M7N1DynP'] = False # (Pa); ;
Morison['M7N2DynP'] = False # (Pa); ;
Morison['M7N3DynP'] = False # (Pa); ;
Morison['M7N4DynP'] = False # (Pa); ;
Morison['M7N5DynP'] = False # (Pa); ;
Morison['M7N6DynP'] = False # (Pa); ;
Morison['M7N7DynP'] = False # (Pa); ;
Morison['M7N8DynP'] = False # (Pa); ;
Morison['M7N9DynP'] = False # (Pa); ;
Morison['M8N1DynP'] = False # (Pa); ;
Morison['M8N2DynP'] = False # (Pa); ;
Morison['M8N3DynP'] = False # (Pa); ;
Morison['M8N4DynP'] = False # (Pa); ;
Morison['M8N5DynP'] = False # (Pa); ;
Morison['M8N6DynP'] = False # (Pa); ;
Morison['M8N7DynP'] = False # (Pa); ;
Morison['M8N8DynP'] = False # (Pa); ;
Morison['M8N9DynP'] = False # (Pa); ;
Morison['M9N1DynP'] = False # (Pa); ;
Morison['M9N2DynP'] = False # (Pa); ;
Morison['M9N3DynP'] = False # (Pa); ;
Morison['M9N4DynP'] = False # (Pa); ;
Morison['M9N5DynP'] = False # (Pa); ;
Morison['M9N6DynP'] = False # (Pa); ;
Morison['M9N7DynP'] = False # (Pa); ;
Morison['M9N8DynP'] = False # (Pa); ;
Morison['M9N9DynP'] = False # (Pa); ;
Morison['M1N1STVxi'] = False # (m/s); structure translational velocity;
Morison['M1N2STVxi'] = False # (m/s); ;
Morison['M1N3STVxi'] = False # (m/s); ;
Morison['M1N4STVxi'] = False # (m/s); ;
Morison['M1N5STVxi'] = False # (m/s); ;
Morison['M1N6STVxi'] = False # (m/s); ;
Morison['M1N7STVxi'] = False # (m/s); ;
Morison['M1N8STVxi'] = False # (m/s); ;
Morison['M1N9STVxi'] = False # (m/s); ;
Morison['M2N1STVxi'] = False # (m/s); ;
Morison['M2N2STVxi'] = False # (m/s); ;
Morison['M2N3STVxi'] = False # (m/s); ;
Morison['M2N4STVxi'] = False # (m/s); ;
Morison['M2N5STVxi'] = False # (m/s); ;
Morison['M2N6STVxi'] = False # (m/s); ;
Morison['M2N7STVxi'] = False # (m/s); ;
Morison['M2N8STVxi'] = False # (m/s); ;
Morison['M2N9STVxi'] = False # (m/s); ;
Morison['M3N1STVxi'] = False # (m/s); ;
Morison['M3N2STVxi'] = False # (m/s); ;
Morison['M3N3STVxi'] = False # (m/s); ;
Morison['M3N4STVxi'] = False # (m/s); ;
Morison['M3N5STVxi'] = False # (m/s); ;
Morison['M3N6STVxi'] = False # (m/s); ;
Morison['M3N7STVxi'] = False # (m/s); ;
Morison['M3N8STVxi'] = False # (m/s); ;
Morison['M3N9STVxi'] = False # (m/s); ;
Morison['M4N1STVxi'] = False # (m/s); ;
Morison['M4N2STVxi'] = False # (m/s); ;
Morison['M4N3STVxi'] = False # (m/s); ;
Morison['M4N4STVxi'] = False # (m/s); ;
Morison['M4N5STVxi'] = False # (m/s); ;
Morison['M4N6STVxi'] = False # (m/s); ;
Morison['M4N7STVxi'] = False # (m/s); ;
Morison['M4N8STVxi'] = False # (m/s); ;
Morison['M4N9STVxi'] = False # (m/s); ;
Morison['M5N1STVxi'] = False # (m/s); ;
Morison['M5N2STVxi'] = False # (m/s); ;
Morison['M5N3STVxi'] = False # (m/s); ;
Morison['M5N4STVxi'] = False # (m/s); ;
Morison['M5N5STVxi'] = False # (m/s); ;
Morison['M5N6STVxi'] = False # (m/s); ;
Morison['M5N7STVxi'] = False # (m/s); ;
Morison['M5N8STVxi'] = False # (m/s); ;
Morison['M5N9STVxi'] = False # (m/s); ;
Morison['M6N1STVxi'] = False # (m/s); ;
Morison['M6N2STVxi'] = False # (m/s); ;
Morison['M6N3STVxi'] = False # (m/s); ;
Morison['M6N4STVxi'] = False # (m/s); ;
Morison['M6N5STVxi'] = False # (m/s); ;
Morison['M6N6STVxi'] = False # (m/s); ;
Morison['M6N7STVxi'] = False # (m/s); ;
Morison['M6N8STVxi'] = False # (m/s); ;
Morison['M6N9STVxi'] = False # (m/s); ;
Morison['M7N1STVxi'] = False # (m/s); ;
Morison['M7N2STVxi'] = False # (m/s); ;
Morison['M7N3STVxi'] = False # (m/s); ;
Morison['M7N4STVxi'] = False # (m/s); ;
Morison['M7N5STVxi'] = False # (m/s); ;
Morison['M7N6STVxi'] = False # (m/s); ;
Morison['M7N7STVxi'] = False # (m/s); ;
Morison['M7N8STVxi'] = False # (m/s); ;
Morison['M7N9STVxi'] = False # (m/s); ;
Morison['M8N1STVxi'] = False # (m/s); ;
Morison['M8N2STVxi'] = False # (m/s); ;
Morison['M8N3STVxi'] = False # (m/s); ;
Morison['M8N4STVxi'] = False # (m/s); ;
Morison['M8N5STVxi'] = False # (m/s); ;
Morison['M8N6STVxi'] = False # (m/s); ;
Morison['M8N7STVxi'] = False # (m/s); ;
Morison['M8N8STVxi'] = False # (m/s); ;
Morison['M8N9STVxi'] = False # (m/s); ;
Morison['M9N1STVxi'] = False # (m/s); ;
Morison['M9N2STVxi'] = False # (m/s); ;
Morison['M9N3STVxi'] = False # (m/s); ;
Morison['M9N4STVxi'] = False # (m/s); ;
Morison['M9N5STVxi'] = False # (m/s); ;
Morison['M9N6STVxi'] = False # (m/s); ;
Morison['M9N7STVxi'] = False # (m/s); ;
Morison['M9N8STVxi'] = False # (m/s); ;
Morison['M9N9STVxi'] = False # (m/s); ;
Morison['M1N1STVyi'] = False # (m/s); ;
Morison['M1N2STVyi'] = False # (m/s); ;
Morison['M1N3STVyi'] = False # (m/s); ;
Morison['M1N4STVyi'] = False # (m/s); ;
Morison['M1N5STVyi'] = False # (m/s); ;
Morison['M1N6STVyi'] = False # (m/s); ;
Morison['M1N7STVyi'] = False # (m/s); ;
Morison['M1N8STVyi'] = False # (m/s); ;
Morison['M1N9STVyi'] = False # (m/s); ;
Morison['M2N1STVyi'] = False # (m/s); ;
Morison['M2N2STVyi'] = False # (m/s); ;
Morison['M2N3STVyi'] = False # (m/s); ;
Morison['M2N4STVyi'] = False # (m/s); ;
Morison['M2N5STVyi'] = False # (m/s); ;
Morison['M2N6STVyi'] = False # (m/s); ;
Morison['M2N7STVyi'] = False # (m/s); ;
Morison['M2N8STVyi'] = False # (m/s); ;
Morison['M2N9STVyi'] = False # (m/s); ;
Morison['M3N1STVyi'] = False # (m/s); ;
Morison['M3N2STVyi'] = False # (m/s); ;
Morison['M3N3STVyi'] = False # (m/s); ;
Morison['M3N4STVyi'] = False # (m/s); ;
Morison['M3N5STVyi'] = False # (m/s); ;
Morison['M3N6STVyi'] = False # (m/s); ;
Morison['M3N7STVyi'] = False # (m/s); ;
Morison['M3N8STVyi'] = False # (m/s); ;
Morison['M3N9STVyi'] = False # (m/s); ;
Morison['M4N1STVyi'] = False # (m/s); ;
Morison['M4N2STVyi'] = False # (m/s); ;
Morison['M4N3STVyi'] = False # (m/s); ;
Morison['M4N4STVyi'] = False # (m/s); ;
Morison['M4N5STVyi'] = False # (m/s); ;
Morison['M4N6STVyi'] = False # (m/s); ;
Morison['M4N7STVyi'] = False # (m/s); ;
Morison['M4N8STVyi'] = False # (m/s); ;
Morison['M4N9STVyi'] = False # (m/s); ;
Morison['M5N1STVyi'] = False # (m/s); ;
Morison['M5N2STVyi'] = False # (m/s); ;
Morison['M5N3STVyi'] = False # (m/s); ;
Morison['M5N4STVyi'] = False # (m/s); ;
Morison['M5N5STVyi'] = False # (m/s); ;
Morison['M5N6STVyi'] = False # (m/s); ;
Morison['M5N7STVyi'] = False # (m/s); ;
Morison['M5N8STVyi'] = False # (m/s); ;
Morison['M5N9STVyi'] = False # (m/s); ;
Morison['M6N1STVyi'] = False # (m/s); ;
Morison['M6N2STVyi'] = False # (m/s); ;
Morison['M6N3STVyi'] = False # (m/s); ;
Morison['M6N4STVyi'] = False # (m/s); ;
Morison['M6N5STVyi'] = False # (m/s); ;
Morison['M6N6STVyi'] = False # (m/s); ;
Morison['M6N7STVyi'] = False # (m/s); ;
Morison['M6N8STVyi'] = False # (m/s); ;
Morison['M6N9STVyi'] = False # (m/s); ;
Morison['M7N1STVyi'] = False # (m/s); ;
Morison['M7N2STVyi'] = False # (m/s); ;
Morison['M7N3STVyi'] = False # (m/s); ;
Morison['M7N4STVyi'] = False # (m/s); ;
Morison['M7N5STVyi'] = False # (m/s); ;
Morison['M7N6STVyi'] = False # (m/s); ;
Morison['M7N7STVyi'] = False # (m/s); ;
Morison['M7N8STVyi'] = False # (m/s); ;
Morison['M7N9STVyi'] = False # (m/s); ;
Morison['M8N1STVyi'] = False # (m/s); ;
Morison['M8N2STVyi'] = False # (m/s); ;
Morison['M8N3STVyi'] = False # (m/s); ;
Morison['M8N4STVyi'] = False # (m/s); ;
Morison['M8N5STVyi'] = False # (m/s); ;
Morison['M8N6STVyi'] = False # (m/s); ;
Morison['M8N7STVyi'] = False # (m/s); ;
Morison['M8N8STVyi'] = False # (m/s); ;
Morison['M8N9STVyi'] = False # (m/s); ;
Morison['M9N1STVyi'] = False # (m/s); ;
Morison['M9N2STVyi'] = False # (m/s); ;
Morison['M9N3STVyi'] = False # (m/s); ;
Morison['M9N4STVyi'] = False # (m/s); ;
Morison['M9N5STVyi'] = False # (m/s); ;
Morison['M9N6STVyi'] = False # (m/s); ;
Morison['M9N7STVyi'] = False # (m/s); ;
Morison['M9N8STVyi'] = False # (m/s); ;
Morison['M9N9STVyi'] = False # (m/s); ;
Morison['M1N1STVzi'] = False # (m/s); ;
Morison['M1N2STVzi'] = False # (m/s); ;
Morison['M1N3STVzi'] = False # (m/s); ;
Morison['M1N4STVzi'] = False # (m/s); ;
Morison['M1N5STVzi'] = False # (m/s); ;
Morison['M1N6STVzi'] = False # (m/s); ;
Morison['M1N7STVzi'] = False # (m/s); ;
Morison['M1N8STVzi'] = False # (m/s); ;
Morison['M1N9STVzi'] = False # (m/s); ;
Morison['M2N1STVzi'] = False # (m/s); ;
Morison['M2N2STVzi'] = False # (m/s); ;
Morison['M2N3STVzi'] = False # (m/s); ;
Morison['M2N4STVzi'] = False # (m/s); ;
Morison['M2N5STVzi'] = False # (m/s); ;
Morison['M2N6STVzi'] = False # (m/s); ;
Morison['M2N7STVzi'] = False # (m/s); ;
Morison['M2N8STVzi'] = False # (m/s); ;
Morison['M2N9STVzi'] = False # (m/s); ;
Morison['M3N1STVzi'] = False # (m/s); ;
Morison['M3N2STVzi'] = False # (m/s); ;
Morison['M3N3STVzi'] = False # (m/s); ;
Morison['M3N4STVzi'] = False # (m/s); ;
Morison['M3N5STVzi'] = False # (m/s); ;
Morison['M3N6STVzi'] = False # (m/s); ;
Morison['M3N7STVzi'] = False # (m/s); ;
Morison['M3N8STVzi'] = False # (m/s); ;
Morison['M3N9STVzi'] = False # (m/s); ;
Morison['M4N1STVzi'] = False # (m/s); ;
Morison['M4N2STVzi'] = False # (m/s); ;
Morison['M4N3STVzi'] = False # (m/s); ;
Morison['M4N4STVzi'] = False # (m/s); ;
Morison['M4N5STVzi'] = False # (m/s); ;
Morison['M4N6STVzi'] = False # (m/s); ;
Morison['M4N7STVzi'] = False # (m/s); ;
Morison['M4N8STVzi'] = False # (m/s); ;
Morison['M4N9STVzi'] = False # (m/s); ;
Morison['M5N1STVzi'] = False # (m/s); ;
Morison['M5N2STVzi'] = False # (m/s); ;
Morison['M5N3STVzi'] = False # (m/s); ;
Morison['M5N4STVzi'] = False # (m/s); ;
Morison['M5N5STVzi'] = False # (m/s); ;
Morison['M5N6STVzi'] = False # (m/s); ;
Morison['M5N7STVzi'] = False # (m/s); ;
Morison['M5N8STVzi'] = False # (m/s); ;
Morison['M5N9STVzi'] = False # (m/s); ;
Morison['M6N1STVzi'] = False # (m/s); ;
Morison['M6N2STVzi'] = False # (m/s); ;
Morison['M6N3STVzi'] = False # (m/s); ;
Morison['M6N4STVzi'] = False # (m/s); ;
Morison['M6N5STVzi'] = False # (m/s); ;
Morison['M6N6STVzi'] = False # (m/s); ;
Morison['M6N7STVzi'] = False # (m/s); ;
Morison['M6N8STVzi'] = False # (m/s); ;
Morison['M6N9STVzi'] = False # (m/s); ;
Morison['M7N1STVzi'] = False # (m/s); ;
Morison['M7N2STVzi'] = False # (m/s); ;
Morison['M7N3STVzi'] = False # (m/s); ;
Morison['M7N4STVzi'] = False # (m/s); ;
Morison['M7N5STVzi'] = False # (m/s); ;
Morison['M7N6STVzi'] = False # (m/s); ;
Morison['M7N7STVzi'] = False # (m/s); ;
Morison['M7N8STVzi'] = False # (m/s); ;
Morison['M7N9STVzi'] = False # (m/s); ;
Morison['M8N1STVzi'] = False # (m/s); ;
Morison['M8N2STVzi'] = False # (m/s); ;
Morison['M8N3STVzi'] = False # (m/s); ;
Morison['M8N4STVzi'] = False # (m/s); ;
Morison['M8N5STVzi'] = False # (m/s); ;
Morison['M8N6STVzi'] = False # (m/s); ;
Morison['M8N7STVzi'] = False # (m/s); ;
Morison['M8N8STVzi'] = False # (m/s); ;
Morison['M8N9STVzi'] = False # (m/s); ;
Morison['M9N1STVzi'] = False # (m/s); ;
Morison['M9N2STVzi'] = False # (m/s); ;
Morison['M9N3STVzi'] = False # (m/s); ;
Morison['M9N4STVzi'] = False # (m/s); ;
Morison['M9N5STVzi'] = False # (m/s); ;
Morison['M9N6STVzi'] = False # (m/s); ;
Morison['M9N7STVzi'] = False # (m/s); ;
Morison['M9N8STVzi'] = False # (m/s); ;
Morison['M9N9STVzi'] = False # (m/s); ;
Morison['M1N1STAxi'] = False # (m/s); structure translational Acceleration;
Morison['M1N2STAxi'] = False # (m/s); ;
Morison['M1N3STAxi'] = False # (m/s); ;
Morison['M1N4STAxi'] = False # (m/s); ;
Morison['M1N5STAxi'] = False # (m/s); ;
Morison['M1N6STAxi'] = False # (m/s); ;
Morison['M1N7STAxi'] = False # (m/s); ;
Morison['M1N8STAxi'] = False # (m/s); ;
Morison['M1N9STAxi'] = False # (m/s); ;
Morison['M2N1STAxi'] = False # (m/s); ;
Morison['M2N2STAxi'] = False # (m/s); ;
Morison['M2N3STAxi'] = False # (m/s); ;
Morison['M2N4STAxi'] = False # (m/s); ;
Morison['M2N5STAxi'] = False # (m/s); ;
Morison['M2N6STAxi'] = False # (m/s); ;
Morison['M2N7STAxi'] = False # (m/s); ;
Morison['M2N8STAxi'] = False # (m/s); ;
Morison['M2N9STAxi'] = False # (m/s); ;
Morison['M3N1STAxi'] = False # (m/s); ;
Morison['M3N2STAxi'] = False # (m/s); ;
Morison['M3N3STAxi'] = False # (m/s); ;
Morison['M3N4STAxi'] = False # (m/s); ;
Morison['M3N5STAxi'] = False # (m/s); ;
Morison['M3N6STAxi'] = False # (m/s); ;
Morison['M3N7STAxi'] = False # (m/s); ;
Morison['M3N8STAxi'] = False # (m/s); ;
Morison['M3N9STAxi'] = False # (m/s); ;
Morison['M4N1STAxi'] = False # (m/s); ;
Morison['M4N2STAxi'] = False # (m/s); ;
Morison['M4N3STAxi'] = False # (m/s); ;
Morison['M4N4STAxi'] = False # (m/s); ;
Morison['M4N5STAxi'] = False # (m/s); ;
Morison['M4N6STAxi'] = False # (m/s); ;
Morison['M4N7STAxi'] = False # (m/s); ;
Morison['M4N8STAxi'] = False # (m/s); ;
Morison['M4N9STAxi'] = False # (m/s); ;
Morison['M5N1STAxi'] = False # (m/s); ;
Morison['M5N2STAxi'] = False # (m/s); ;
Morison['M5N3STAxi'] = False # (m/s); ;
Morison['M5N4STAxi'] = False # (m/s); ;
Morison['M5N5STAxi'] = False # (m/s); ;
Morison['M5N6STAxi'] = False # (m/s); ;
Morison['M5N7STAxi'] = False # (m/s); ;
Morison['M5N8STAxi'] = False # (m/s); ;
Morison['M5N9STAxi'] = False # (m/s); ;
Morison['M6N1STAxi'] = False # (m/s); ;
Morison['M6N2STAxi'] = False # (m/s); ;
Morison['M6N3STAxi'] = False # (m/s); ;
Morison['M6N4STAxi'] = False # (m/s); ;
Morison['M6N5STAxi'] = False # (m/s); ;
Morison['M6N6STAxi'] = False # (m/s); ;
Morison['M6N7STAxi'] = False # (m/s); ;
Morison['M6N8STAxi'] = False # (m/s); ;
Morison['M6N9STAxi'] = False # (m/s); ;
Morison['M7N1STAxi'] = False # (m/s); ;
Morison['M7N2STAxi'] = False # (m/s); ;
Morison['M7N3STAxi'] = False # (m/s); ;
Morison['M7N4STAxi'] = False # (m/s); ;
Morison['M7N5STAxi'] = False # (m/s); ;
Morison['M7N6STAxi'] = False # (m/s); ;
Morison['M7N7STAxi'] = False # (m/s); ;
Morison['M7N8STAxi'] = False # (m/s); ;
Morison['M7N9STAxi'] = False # (m/s); ;
Morison['M8N1STAxi'] = False # (m/s); ;
Morison['M8N2STAxi'] = False # (m/s); ;
Morison['M8N3STAxi'] = False # (m/s); ;
Morison['M8N4STAxi'] = False # (m/s); ;
Morison['M8N5STAxi'] = False # (m/s); ;
Morison['M8N6STAxi'] = False # (m/s); ;
Morison['M8N7STAxi'] = False # (m/s); ;
Morison['M8N8STAxi'] = False # (m/s); ;
Morison['M8N9STAxi'] = False # (m/s); ;
Morison['M9N1STAxi'] = False # (m/s); ;
Morison['M9N2STAxi'] = False # (m/s); ;
Morison['M9N3STAxi'] = False # (m/s); ;
Morison['M9N4STAxi'] = False # (m/s); ;
Morison['M9N5STAxi'] = False # (m/s); ;
Morison['M9N6STAxi'] = False # (m/s); ;
Morison['M9N7STAxi'] = False # (m/s); ;
Morison['M9N8STAxi'] = False # (m/s); ;
Morison['M9N9STAxi'] = False # (m/s); ;
Morison['M1N1STAyi'] = False # (m/s); ;
Morison['M1N2STAyi'] = False # (m/s); ;
Morison['M1N3STAyi'] = False # (m/s); ;
Morison['M1N4STAyi'] = False # (m/s); ;
Morison['M1N5STAyi'] = False # (m/s); ;
Morison['M1N6STAyi'] = False # (m/s); ;
Morison['M1N7STAyi'] = False # (m/s); ;
Morison['M1N8STAyi'] = False # (m/s); ;
Morison['M1N9STAyi'] = False # (m/s); ;
Morison['M2N1STAyi'] = False # (m/s); ;
Morison['M2N2STAyi'] = False # (m/s); ;
Morison['M2N3STAyi'] = False # (m/s); ;
Morison['M2N4STAyi'] = False # (m/s); ;
Morison['M2N5STAyi'] = False # (m/s); ;
Morison['M2N6STAyi'] = False # (m/s); ;
Morison['M2N7STAyi'] = False # (m/s); ;
Morison['M2N8STAyi'] = False # (m/s); ;
Morison['M2N9STAyi'] = False # (m/s); ;
Morison['M3N1STAyi'] = False # (m/s); ;
Morison['M3N2STAyi'] = False # (m/s); ;
Morison['M3N3STAyi'] = False # (m/s); ;
Morison['M3N4STAyi'] = False # (m/s); ;
Morison['M3N5STAyi'] = False # (m/s); ;
Morison['M3N6STAyi'] = False # (m/s); ;
Morison['M3N7STAyi'] = False # (m/s); ;
Morison['M3N8STAyi'] = False # (m/s); ;
Morison['M3N9STAyi'] = False # (m/s); ;
Morison['M4N1STAyi'] = False # (m/s); ;
Morison['M4N2STAyi'] = False # (m/s); ;
Morison['M4N3STAyi'] = False # (m/s); ;
Morison['M4N4STAyi'] = False # (m/s); ;
Morison['M4N5STAyi'] = False # (m/s); ;
Morison['M4N6STAyi'] = False # (m/s); ;
Morison['M4N7STAyi'] = False # (m/s); ;
Morison['M4N8STAyi'] = False # (m/s); ;
Morison['M4N9STAyi'] = False # (m/s); ;
Morison['M5N1STAyi'] = False # (m/s); ;
Morison['M5N2STAyi'] = False # (m/s); ;
Morison['M5N3STAyi'] = False # (m/s); ;
Morison['M5N4STAyi'] = False # (m/s); ;
Morison['M5N5STAyi'] = False # (m/s); ;
Morison['M5N6STAyi'] = False # (m/s); ;
Morison['M5N7STAyi'] = False # (m/s); ;
Morison['M5N8STAyi'] = False # (m/s); ;
Morison['M5N9STAyi'] = False # (m/s); ;
Morison['M6N1STAyi'] = False # (m/s); ;
Morison['M6N2STAyi'] = False # (m/s); ;
Morison['M6N3STAyi'] = False # (m/s); ;
Morison['M6N4STAyi'] = False # (m/s); ;
Morison['M6N5STAyi'] = False # (m/s); ;
Morison['M6N6STAyi'] = False # (m/s); ;
Morison['M6N7STAyi'] = False # (m/s); ;
Morison['M6N8STAyi'] = False # (m/s); ;
Morison['M6N9STAyi'] = False # (m/s); ;
Morison['M7N1STAyi'] = False # (m/s); ;
Morison['M7N2STAyi'] = False # (m/s); ;
Morison['M7N3STAyi'] = False # (m/s); ;
Morison['M7N4STAyi'] = False # (m/s); ;
Morison['M7N5STAyi'] = False # (m/s); ;
Morison['M7N6STAyi'] = False # (m/s); ;
Morison['M7N7STAyi'] = False # (m/s); ;
Morison['M7N8STAyi'] = False # (m/s); ;
Morison['M7N9STAyi'] = False # (m/s); ;
Morison['M8N1STAyi'] = False # (m/s); ;
Morison['M8N2STAyi'] = False # (m/s); ;
Morison['M8N3STAyi'] = False # (m/s); ;
Morison['M8N4STAyi'] = False # (m/s); ;
Morison['M8N5STAyi'] = False # (m/s); ;
Morison['M8N6STAyi'] = False # (m/s); ;
Morison['M8N7STAyi'] = False # (m/s); ;
Morison['M8N8STAyi'] = False # (m/s); ;
Morison['M8N9STAyi'] = False # (m/s); ;
Morison['M9N1STAyi'] = False # (m/s); ;
Morison['M9N2STAyi'] = False # (m/s); ;
Morison['M9N3STAyi'] = False # (m/s); ;
Morison['M9N4STAyi'] = False # (m/s); ;
Morison['M9N5STAyi'] = False # (m/s); ;
Morison['M9N6STAyi'] = False # (m/s); ;
Morison['M9N7STAyi'] = False # (m/s); ;
Morison['M9N8STAyi'] = False # (m/s); ;
Morison['M9N9STAyi'] = False # (m/s); ;
Morison['M1N1STAzi'] = False # (m/s); ;
Morison['M1N2STAzi'] = False # (m/s); ;
Morison['M1N3STAzi'] = False # (m/s); ;
Morison['M1N4STAzi'] = False # (m/s); ;
Morison['M1N5STAzi'] = False # (m/s); ;
Morison['M1N6STAzi'] = False # (m/s); ;
Morison['M1N7STAzi'] = False # (m/s); ;
Morison['M1N8STAzi'] = False # (m/s); ;
Morison['M1N9STAzi'] = False # (m/s); ;
Morison['M2N1STAzi'] = False # (m/s); ;
Morison['M2N2STAzi'] = False # (m/s); ;
Morison['M2N3STAzi'] = False # (m/s); ;
Morison['M2N4STAzi'] = False # (m/s); ;
Morison['M2N5STAzi'] = False # (m/s); ;
Morison['M2N6STAzi'] = False # (m/s); ;
Morison['M2N7STAzi'] = False # (m/s); ;
Morison['M2N8STAzi'] = False # (m/s); ;
Morison['M2N9STAzi'] = False # (m/s); ;
Morison['M3N1STAzi'] = False # (m/s); ;
Morison['M3N2STAzi'] = False # (m/s); ;
Morison['M3N3STAzi'] = False # (m/s); ;
Morison['M3N4STAzi'] = False # (m/s); ;
Morison['M3N5STAzi'] = False # (m/s); ;
Morison['M3N6STAzi'] = False # (m/s); ;
Morison['M3N7STAzi'] = False # (m/s); ;
Morison['M3N8STAzi'] = False # (m/s); ;
Morison['M3N9STAzi'] = False # (m/s); ;
Morison['M4N1STAzi'] = False # (m/s); ;
Morison['M4N2STAzi'] = False # (m/s); ;
Morison['M4N3STAzi'] = False # (m/s); ;
Morison['M4N4STAzi'] = False # (m/s); ;
Morison['M4N5STAzi'] = False # (m/s); ;
Morison['M4N6STAzi'] = False # (m/s); ;
Morison['M4N7STAzi'] = False # (m/s); ;
Morison['M4N8STAzi'] = False # (m/s); ;
Morison['M4N9STAzi'] = False # (m/s); ;
Morison['M5N1STAzi'] = False # (m/s); ;
Morison['M5N2STAzi'] = False # (m/s); ;
Morison['M5N3STAzi'] = False # (m/s); ;
Morison['M5N4STAzi'] = False # (m/s); ;
Morison['M5N5STAzi'] = False # (m/s); ;
Morison['M5N6STAzi'] = False # (m/s); ;
Morison['M5N7STAzi'] = False # (m/s); ;
Morison['M5N8STAzi'] = False # (m/s); ;
Morison['M5N9STAzi'] = False # (m/s); ;
Morison['M6N1STAzi'] = False # (m/s); ;
Morison['M6N2STAzi'] = False # (m/s); ;
Morison['M6N3STAzi'] = False # (m/s); ;
Morison['M6N4STAzi'] = False # (m/s); ;
Morison['M6N5STAzi'] = False # (m/s); ;
Morison['M6N6STAzi'] = False # (m/s); ;
Morison['M6N7STAzi'] = False # (m/s); ;
Morison['M6N8STAzi'] = False # (m/s); ;
Morison['M6N9STAzi'] = False # (m/s); ;
Morison['M7N1STAzi'] = False # (m/s); ;
Morison['M7N2STAzi'] = False # (m/s); ;
Morison['M7N3STAzi'] = False # (m/s); ;
Morison['M7N4STAzi'] = False # (m/s); ;
Morison['M7N5STAzi'] = False # (m/s); ;
Morison['M7N6STAzi'] = False # (m/s); ;
Morison['M7N7STAzi'] = False # (m/s); ;
Morison['M7N8STAzi'] = False # (m/s); ;
Morison['M7N9STAzi'] = False # (m/s); ;
Morison['M8N1STAzi'] = False # (m/s); ;
Morison['M8N2STAzi'] = False # (m/s); ;
Morison['M8N3STAzi'] = False # (m/s); ;
Morison['M8N4STAzi'] = False # (m/s); ;
Morison['M8N5STAzi'] = False # (m/s); ;
Morison['M8N6STAzi'] = False # (m/s); ;
Morison['M8N7STAzi'] = False # (m/s); ;
Morison['M8N8STAzi'] = False # (m/s); ;
Morison['M8N9STAzi'] = False # (m/s); ;
Morison['M9N1STAzi'] = False # (m/s); ;
Morison['M9N2STAzi'] = False # (m/s); ;
Morison['M9N3STAzi'] = False # (m/s); ;
Morison['M9N4STAzi'] = False # (m/s); ;
Morison['M9N5STAzi'] = False # (m/s); ;
Morison['M9N6STAzi'] = False # (m/s); ;
Morison['M9N7STAzi'] = False # (m/s); ;
Morison['M9N8STAzi'] = False # (m/s); ;
Morison['M9N9STAzi'] = False # (m/s); ;
# Morison Element Loads
Morison['M1N1FDxi'] = False # (N/m); x-component of the distributed drag force expressed in the inertial coordinate system;
Morison['M1N2FDxi'] = False # (N/m); ;
Morison['M1N3FDxi'] = False # (N/m); ;
Morison['M1N4FDxi'] = False # (N/m); ;
Morison['M1N5FDxi'] = False # (N/m); ;
Morison['M1N6FDxi'] = False # (N/m); ;
Morison['M1N7FDxi'] = False # (N/m); ;
Morison['M1N8FDxi'] = False # (N/m); ;
Morison['M1N9FDxi'] = False # (N/m); ;
Morison['M2N1FDxi'] = False # (N/m); ;
Morison['M2N2FDxi'] = False # (N/m); ;
Morison['M2N3FDxi'] = False # (N/m); ;
Morison['M2N4FDxi'] = False # (N/m); ;
Morison['M2N5FDxi'] = False # (N/m); ;
Morison['M2N6FDxi'] = False # (N/m); ;
Morison['M2N7FDxi'] = False # (N/m); ;
Morison['M2N8FDxi'] = False # (N/m); ;
Morison['M2N9FDxi'] = False # (N/m); ;
Morison['M3N1FDxi'] = False # (N/m); ;
Morison['M3N2FDxi'] = False # (N/m); ;
Morison['M3N3FDxi'] = False # (N/m); ;
Morison['M3N4FDxi'] = False # (N/m); ;
Morison['M3N5FDxi'] = False # (N/m); ;
Morison['M3N6FDxi'] = False # (N/m); ;
Morison['M3N7FDxi'] = False # (N/m); ;
Morison['M3N8FDxi'] = False # (N/m); ;
Morison['M3N9FDxi'] = False # (N/m); ;
Morison['M4N1FDxi'] = False # (N/m); ;
Morison['M4N2FDxi'] = False # (N/m); ;
Morison['M4N3FDxi'] = False # (N/m); ;
Morison['M4N4FDxi'] = False # (N/m); ;
Morison['M4N5FDxi'] = False # (N/m); ;
Morison['M4N6FDxi'] = False # (N/m); ;
Morison['M4N7FDxi'] = False # (N/m); ;
Morison['M4N8FDxi'] = False # (N/m); ;
Morison['M4N9FDxi'] = False # (N/m); ;
Morison['M5N1FDxi'] = False # (N/m); ;
Morison['M5N2FDxi'] = False # (N/m); ;
Morison['M5N3FDxi'] = False # (N/m); ;
Morison['M5N4FDxi'] = False # (N/m); ;
Morison['M5N5FDxi'] = False # (N/m); ;
Morison['M5N6FDxi'] = False # (N/m); ;
Morison['M5N7FDxi'] = False # (N/m); ;
Morison['M5N8FDxi'] = False # (N/m); ;
Morison['M5N9FDxi'] = False # (N/m); ;
Morison['M6N1FDxi'] = False # (N/m); ;
Morison['M6N2FDxi'] = False # (N/m); ;
Morison['M6N3FDxi'] = False # (N/m); ;
Morison['M6N4FDxi'] = False # (N/m); ;
Morison['M6N5FDxi'] = False # (N/m); ;
Morison['M6N6FDxi'] = False # (N/m); ;
Morison['M6N7FDxi'] = False # (N/m); ;
Morison['M6N8FDxi'] = False # (N/m); ;
Morison['M6N9FDxi'] = False # (N/m); ;
Morison['M7N1FDxi'] = False # (N/m); ;
Morison['M7N2FDxi'] = False # (N/m); ;
Morison['M7N3FDxi'] = False # (N/m); ;
Morison['M7N4FDxi'] = False # (N/m); ;
Morison['M7N5FDxi'] = False # (N/m); ;
Morison['M7N6FDxi'] = False # (N/m); ;
Morison['M7N7FDxi'] = False # (N/m); ;
Morison['M7N8FDxi'] = False # (N/m); ;
Morison['M7N9FDxi'] = False # (N/m); ;
Morison['M8N1FDxi'] = False # (N/m); ;
Morison['M8N2FDxi'] = False # (N/m); ;
Morison['M8N3FDxi'] = False # (N/m); ;
Morison['M8N4FDxi'] = False # (N/m); ;
Morison['M8N5FDxi'] = False # (N/m); ;
Morison['M8N6FDxi'] = False # (N/m); ;
Morison['M8N7FDxi'] = False # (N/m); ;
Morison['M8N8FDxi'] = False # (N/m); ;
Morison['M8N9FDxi'] = False # (N/m); ;
Morison['M9N1FDxi'] = False # (N/m); ;
Morison['M9N2FDxi'] = False # (N/m); ;
Morison['M9N3FDxi'] = False # (N/m); ;
Morison['M9N4FDxi'] = False # (N/m); ;
Morison['M9N5FDxi'] = False # (N/m); ;
Morison['M9N6FDxi'] = False # (N/m); ;
Morison['M9N7FDxi'] = False # (N/m); ;
Morison['M9N8FDxi'] = False # (N/m); ;
Morison['M9N9FDxi'] = False # (N/m); ;
Morison['M1N1FDyi'] = False # (N/m); y-component of the distributed drag force expressed in the inertial coordinate system;
Morison['M1N2FDyi'] = False # (N/m); ;
Morison['M1N3FDyi'] = False # (N/m); ;
Morison['M1N4FDyi'] = False # (N/m); ;
Morison['M1N5FDyi'] = False # (N/m); ;
Morison['M1N6FDyi'] = False # (N/m); ;
Morison['M1N7FDyi'] = False # (N/m); ;
Morison['M1N8FDyi'] = False # (N/m); ;
Morison['M1N9FDyi'] = False # (N/m); ;
Morison['M2N1FDyi'] = False # (N/m); ;
Morison['M2N2FDyi'] = False # (N/m); ;
Morison['M2N3FDyi'] = False # (N/m); ;
Morison['M2N4FDyi'] = False # (N/m); ;
Morison['M2N5FDyi'] = False # (N/m); ;
Morison['M2N6FDyi'] = False # (N/m); ;
Morison['M2N7FDyi'] = False # (N/m); ;
Morison['M2N8FDyi'] = False # (N/m); ;
Morison['M2N9FDyi'] = False # (N/m); ;
Morison['M3N1FDyi'] = False # (N/m); ;
Morison['M3N2FDyi'] = False # (N/m); ;
Morison['M3N3FDyi'] = False # (N/m); ;
Morison['M3N4FDyi'] = False # (N/m); ;
Morison['M3N5FDyi'] = False # (N/m); ;
Morison['M3N6FDyi'] = False # (N/m); ;
Morison['M3N7FDyi'] = False # (N/m); ;
Morison['M3N8FDyi'] = False # (N/m); ;
Morison['M3N9FDyi'] = False # (N/m); ;
Morison['M4N1FDyi'] = False # (N/m); ;
Morison['M4N2FDyi'] = False # (N/m); ;
Morison['M4N3FDyi'] = False # (N/m); ;
Morison['M4N4FDyi'] = False # (N/m); ;
Morison['M4N5FDyi'] = False # (N/m); ;
Morison['M4N6FDyi'] = False # (N/m); ;
Morison['M4N7FDyi'] = False # (N/m); ;
Morison['M4N8FDyi'] = False # (N/m); ;
Morison['M4N9FDyi'] = False # (N/m); ;
Morison['M5N1FDyi'] = False # (N/m); ;
Morison['M5N2FDyi'] = False # (N/m); ;
Morison['M5N3FDyi'] = False # (N/m); ;
Morison['M5N4FDyi'] = False # (N/m); ;
Morison['M5N5FDyi'] = False # (N/m); ;
Morison['M5N6FDyi'] = False # (N/m); ;
Morison['M5N7FDyi'] = False # (N/m); ;
Morison['M5N8FDyi'] = False # (N/m); ;
Morison['M5N9FDyi'] = False # (N/m); ;
Morison['M6N1FDyi'] = False # (N/m); ;
Morison['M6N2FDyi'] = False # (N/m); ;
Morison['M6N3FDyi'] = False # (N/m); ;
Morison['M6N4FDyi'] = False # (N/m); ;
Morison['M6N5FDyi'] = False # (N/m); ;
Morison['M6N6FDyi'] = False # (N/m); ;
Morison['M6N7FDyi'] = False # (N/m); ;
Morison['M6N8FDyi'] = False # (N/m); ;
Morison['M6N9FDyi'] = False # (N/m); ;
Morison['M7N1FDyi'] = False # (N/m); ;
Morison['M7N2FDyi'] = False # (N/m); ;
Morison['M7N3FDyi'] = False # (N/m); ;
Morison['M7N4FDyi'] = False # (N/m); ;
Morison['M7N5FDyi'] = False # (N/m); ;
Morison['M7N6FDyi'] = False # (N/m); ;
Morison['M7N7FDyi'] = False # (N/m); ;
Morison['M7N8FDyi'] = False # (N/m); ;
Morison['M7N9FDyi'] = False # (N/m); ;
Morison['M8N1FDyi'] = False # (N/m); ;
Morison['M8N2FDyi'] = False # (N/m); ;
Morison['M8N3FDyi'] = False # (N/m); ;
Morison['M8N4FDyi'] = False # (N/m); ;
Morison['M8N5FDyi'] = False # (N/m); ;
Morison['M8N6FDyi'] = False # (N/m); ;
Morison['M8N7FDyi'] = False # (N/m); ;
Morison['M8N8FDyi'] = False # (N/m); ;
Morison['M8N9FDyi'] = False # (N/m); ;
Morison['M9N1FDyi'] = False # (N/m); ;
Morison['M9N2FDyi'] = False # (N/m); ;
Morison['M9N3FDyi'] = False # (N/m); ;
Morison['M9N4FDyi'] = False # (N/m); ;
Morison['M9N5FDyi'] = False # (N/m); ;
Morison['M9N6FDyi'] = False # (N/m); ;
Morison['M9N7FDyi'] = False # (N/m); ;
Morison['M9N8FDyi'] = False # (N/m); ;
Morison['M9N9FDyi'] = False # (N/m); ;
Morison['M1N1FDzi'] = False # (N/m); z-component of the distributed drag force expressed in the inertial coordinate system;
Morison['M1N2FDzi'] = False # (N/m); ;
Morison['M1N3FDzi'] = False # (N/m); ;
Morison['M1N4FDzi'] = False # (N/m); ;
Morison['M1N5FDzi'] = False # (N/m); ;
Morison['M1N6FDzi'] = False # (N/m); ;
Morison['M1N7FDzi'] = False # (N/m); ;
Morison['M1N8FDzi'] = False # (N/m); ;
Morison['M1N9FDzi'] = False # (N/m); ;
Morison['M2N1FDzi'] = False # (N/m); ;
Morison['M2N2FDzi'] = False # (N/m); ;
Morison['M2N3FDzi'] = False # (N/m); ;
Morison['M2N4FDzi'] = False # (N/m); ;
Morison['M2N5FDzi'] = False # (N/m); ;
Morison['M2N6FDzi'] = False # (N/m); ;
Morison['M2N7FDzi'] = False # (N/m); ;
Morison['M2N8FDzi'] = False # (N/m); ;
Morison['M2N9FDzi'] = False # (N/m); ;
Morison['M3N1FDzi'] = False # (N/m); ;
Morison['M3N2FDzi'] = False # (N/m); ;
Morison['M3N3FDzi'] = False # (N/m); ;
Morison['M3N4FDzi'] = False # (N/m); ;
Morison['M3N5FDzi'] = False # (N/m); ;
Morison['M3N6FDzi'] = False # (N/m); ;
Morison['M3N7FDzi'] = False # (N/m); ;
Morison['M3N8FDzi'] = False # (N/m); ;
Morison['M3N9FDzi'] = False # (N/m); ;
Morison['M4N1FDzi'] = False # (N/m); ;
Morison['M4N2FDzi'] = False # (N/m); ;
Morison['M4N3FDzi'] = False # (N/m); ;
Morison['M4N4FDzi'] = False # (N/m); ;
Morison['M4N5FDzi'] = False # (N/m); ;
Morison['M4N6FDzi'] = False # (N/m); ;
Morison['M4N7FDzi'] = False # (N/m); ;
Morison['M4N8FDzi'] = False # (N/m); ;
Morison['M4N9FDzi'] = False # (N/m); ;
Morison['M5N1FDzi'] = False # (N/m); ;
Morison['M5N2FDzi'] = False # (N/m); ;
Morison['M5N3FDzi'] = False # (N/m); ;
Morison['M5N4FDzi'] = False # (N/m); ;
Morison['M5N5FDzi'] = False # (N/m); ;
Morison['M5N6FDzi'] = False # (N/m); ;
Morison['M5N7FDzi'] = False # (N/m); ;
Morison['M5N8FDzi'] = False # (N/m); ;
Morison['M5N9FDzi'] = False # (N/m); ;
Morison['M6N1FDzi'] = False # (N/m); ;
Morison['M6N2FDzi'] = False # (N/m); ;
Morison['M6N3FDzi'] = False # (N/m); ;
Morison['M6N4FDzi'] = False # (N/m); ;
Morison['M6N5FDzi'] = False # (N/m); ;
Morison['M6N6FDzi'] = False # (N/m); ;
Morison['M6N7FDzi'] = False # (N/m); ;
Morison['M6N8FDzi'] = False # (N/m); ;
Morison['M6N9FDzi'] = False # (N/m); ;
Morison['M7N1FDzi'] = False # (N/m); ;
Morison['M7N2FDzi'] = False # (N/m); ;
Morison['M7N3FDzi'] = False # (N/m); ;
Morison['M7N4FDzi'] = False # (N/m); ;
Morison['M7N5FDzi'] = False # (N/m); ;
Morison['M7N6FDzi'] = False # (N/m); ;
Morison['M7N7FDzi'] = False # (N/m); ;
Morison['M7N8FDzi'] = False # (N/m); ;
Morison['M7N9FDzi'] = False # (N/m); ;
Morison['M8N1FDzi'] = False # (N/m); ;
Morison['M8N2FDzi'] = False # (N/m); ;
Morison['M8N3FDzi'] = False # (N/m); ;
Morison['M8N4FDzi'] = False # (N/m); ;
Morison['M8N5FDzi'] = False # (N/m); ;
Morison['M8N6FDzi'] = False # (N/m); ;
Morison['M8N7FDzi'] = False # (N/m); ;
Morison['M8N8FDzi'] = False # (N/m); ;
Morison['M8N9FDzi'] = False # (N/m); ;
Morison['M9N1FDzi'] = False # (N/m); ;
Morison['M9N2FDzi'] = False # (N/m); ;
Morison['M9N3FDzi'] = False # (N/m); ;
Morison['M9N4FDzi'] = False # (N/m); ;
Morison['M9N5FDzi'] = False # (N/m); ;
Morison['M9N6FDzi'] = False # (N/m); ;
Morison['M9N7FDzi'] = False # (N/m); ;
Morison['M9N8FDzi'] = False # (N/m); ;
Morison['M9N9FDzi'] = False # (N/m); ;
Morison['M1N1FIxi'] = False # (N/m); x-component of the distributed inertial force expressed in the inertial coordinate system;
Morison['M1N2FIxi'] = False # (N/m); ;
Morison['M1N3FIxi'] = False # (N/m); ;
Morison['M1N4FIxi'] = False # (N/m); ;
Morison['M1N5FIxi'] = False # (N/m); ;
Morison['M1N6FIxi'] = False # (N/m); ;
Morison['M1N7FIxi'] = False # (N/m); ;
Morison['M1N8FIxi'] = False # (N/m); ;
Morison['M1N9FIxi'] = False # (N/m); ;
Morison['M2N1FIxi'] = False # (N/m); ;
Morison['M2N2FIxi'] = False # (N/m); ;
Morison['M2N3FIxi'] = False # (N/m); ;
Morison['M2N4FIxi'] = False # (N/m); ;
Morison['M2N5FIxi'] = False # (N/m); ;
Morison['M2N6FIxi'] = False # (N/m); ;
Morison['M2N7FIxi'] = False # (N/m); ;
Morison['M2N8FIxi'] = False # (N/m); ;
Morison['M2N9FIxi'] = False # (N/m); ;
Morison['M3N1FIxi'] = False # (N/m); ;
Morison['M3N2FIxi'] = False # (N/m); ;
Morison['M3N3FIxi'] = False # (N/m); ;
Morison['M3N4FIxi'] = False # (N/m); ;
Morison['M3N5FIxi'] = False # (N/m); ;
Morison['M3N6FIxi'] = False # (N/m); ;
Morison['M3N7FIxi'] = False # (N/m); ;
Morison['M3N8FIxi'] = False # (N/m); ;
Morison['M3N9FIxi'] = False # (N/m); ;
Morison['M4N1FIxi'] = False # (N/m); ;
Morison['M4N2FIxi'] = False # (N/m); ;
Morison['M4N3FIxi'] = False # (N/m); ;
Morison['M4N4FIxi'] = False # (N/m); ;
Morison['M4N5FIxi'] = False # (N/m); ;
Morison['M4N6FIxi'] = False # (N/m); ;
Morison['M4N7FIxi'] = False # (N/m); ;
Morison['M4N8FIxi'] = False # (N/m); ;
Morison['M4N9FIxi'] = False # (N/m); ;
Morison['M5N1FIxi'] = False # (N/m); ;
Morison['M5N2FIxi'] = False # (N/m); ;
Morison['M5N3FIxi'] = False # (N/m); ;
Morison['M5N4FIxi'] = False # (N/m); ;
Morison['M5N5FIxi'] = False # (N/m); ;
Morison['M5N6FIxi'] = False # (N/m); ;
Morison['M5N7FIxi'] = False # (N/m); ;
Morison['M5N8FIxi'] = False # (N/m); ;
Morison['M5N9FIxi'] = False # (N/m); ;
Morison['M6N1FIxi'] = False # (N/m); ;
Morison['M6N2FIxi'] = False # (N/m); ;
Morison['M6N3FIxi'] = False # (N/m); ;
Morison['M6N4FIxi'] = False # (N/m); ;
Morison['M6N5FIxi'] = False # (N/m); ;
Morison['M6N6FIxi'] = False # (N/m); ;
Morison['M6N7FIxi'] = False # (N/m); ;
Morison['M6N8FIxi'] = False # (N/m); ;
Morison['M6N9FIxi'] = False # (N/m); ;
Morison['M7N1FIxi'] = False # (N/m); ;
Morison['M7N2FIxi'] = False # (N/m); ;
Morison['M7N3FIxi'] = False # (N/m); ;
Morison['M7N4FIxi'] = False # (N/m); ;
Morison['M7N5FIxi'] = False # (N/m); ;
Morison['M7N6FIxi'] = False # (N/m); ;
Morison['M7N7FIxi'] = False # (N/m); ;
Morison['M7N8FIxi'] = False # (N/m); ;
Morison['M7N9FIxi'] = False # (N/m); ;
Morison['M8N1FIxi'] = False # (N/m); ;
Morison['M8N2FIxi'] = False # (N/m); ;
Morison['M8N3FIxi'] = False # (N/m); ;
Morison['M8N4FIxi'] = False # (N/m); ;
Morison['M8N5FIxi'] = False # (N/m); ;
Morison['M8N6FIxi'] = False # (N/m); ;
Morison['M8N7FIxi'] = False # (N/m); ;
Morison['M8N8FIxi'] = False # (N/m); ;
Morison['M8N9FIxi'] = False # (N/m); ;
Morison['M9N1FIxi'] = False # (N/m); ;
Morison['M9N2FIxi'] = False # (N/m); ;
Morison['M9N3FIxi'] = False # (N/m); ;
Morison['M9N4FIxi'] = False # (N/m); ;
Morison['M9N5FIxi'] = False # (N/m); ;
Morison['M9N6FIxi'] = False # (N/m); ;
Morison['M9N7FIxi'] = False # (N/m); ;
Morison['M9N8FIxi'] = False # (N/m); ;
Morison['M9N9FIxi'] = False # (N/m); ;
Morison['M1N1FIyi'] = False # (N/m); y-component of the distributed inertial force expressed in the inertial coordinate system;
Morison['M1N2FIyi'] = False # (N/m); ;
Morison['M1N3FIyi'] = False # (N/m); ;
Morison['M1N4FIyi'] = False # (N/m); ;
Morison['M1N5FIyi'] = False # (N/m); ;
Morison['M1N6FIyi'] = False # (N/m); ;
Morison['M1N7FIyi'] = False # (N/m); ;
Morison['M1N8FIyi'] = False # (N/m); ;
Morison['M1N9FIyi'] = False # (N/m); ;
Morison['M2N1FIyi'] = False # (N/m); ;
Morison['M2N2FIyi'] = False # (N/m); ;
Morison['M2N3FIyi'] = False # (N/m); ;
Morison['M2N4FIyi'] = False # (N/m); ;
Morison['M2N5FIyi'] = False # (N/m); ;
Morison['M2N6FIyi'] = False # (N/m); ;
Morison['M2N7FIyi'] = False # (N/m); ;
Morison['M2N8FIyi'] = False # (N/m); ;
Morison['M2N9FIyi'] = False # (N/m); ;
Morison['M3N1FIyi'] = False # (N/m); ;
Morison['M3N2FIyi'] = False # (N/m); ;
Morison['M3N3FIyi'] = False # (N/m); ;
Morison['M3N4FIyi'] = False # (N/m); ;
Morison['M3N5FIyi'] = False # (N/m); ;
Morison['M3N6FIyi'] = False # (N/m); ;
Morison['M3N7FIyi'] = False # (N/m); ;
Morison['M3N8FIyi'] = False # (N/m); ;
Morison['M3N9FIyi'] = False # (N/m); ;
Morison['M4N1FIyi'] = False # (N/m); ;
Morison['M4N2FIyi'] = False # (N/m); ;
Morison['M4N3FIyi'] = False # (N/m); ;
Morison['M4N4FIyi'] = False # (N/m); ;
Morison['M4N5FIyi'] = False # (N/m); ;
Morison['M4N6FIyi'] = False # (N/m); ;
Morison['M4N7FIyi'] = False # (N/m); ;
Morison['M4N8FIyi'] = False # (N/m); ;
Morison['M4N9FIyi'] = False # (N/m); ;
Morison['M5N1FIyi'] = False # (N/m); ;
Morison['M5N2FIyi'] = False # (N/m); ;
Morison['M5N3FIyi'] = False # (N/m); ;
Morison['M5N4FIyi'] = False # (N/m); ;
Morison['M5N5FIyi'] = False # (N/m); ;
Morison['M5N6FIyi'] = False # (N/m); ;
Morison['M5N7FIyi'] = False # (N/m); ;
Morison['M5N8FIyi'] = False # (N/m); ;
Morison['M5N9FIyi'] = False # (N/m); ;
Morison['M6N1FIyi'] = False # (N/m); ;
Morison['M6N2FIyi'] = False # (N/m); ;
Morison['M6N3FIyi'] = False # (N/m); ;
Morison['M6N4FIyi'] = False # (N/m); ;
Morison['M6N5FIyi'] = False # (N/m); ;
Morison['M6N6FIyi'] = False # (N/m); ;
Morison['M6N7FIyi'] = False # (N/m); ;
Morison['M6N8FIyi'] = False # (N/m); ;
Morison['M6N9FIyi'] = False # (N/m); ;
Morison['M7N1FIyi'] = False # (N/m); ;
Morison['M7N2FIyi'] = False # (N/m); ;
Morison['M7N3FIyi'] = False # (N/m); ;
Morison['M7N4FIyi'] = False # (N/m); ;
Morison['M7N5FIyi'] = False # (N/m); ;
Morison['M7N6FIyi'] = False # (N/m); ;
Morison['M7N7FIyi'] = False # (N/m); ;
Morison['M7N8FIyi'] = False # (N/m); ;
Morison['M7N9FIyi'] = False # (N/m); ;
Morison['M8N1FIyi'] = False # (N/m); ;
Morison['M8N2FIyi'] = False # (N/m); ;
Morison['M8N3FIyi'] = False # (N/m); ;
Morison['M8N4FIyi'] = False # (N/m); ;
Morison['M8N5FIyi'] = False # (N/m); ;
Morison['M8N6FIyi'] = False # (N/m); ;
Morison['M8N7FIyi'] = False # (N/m); ;
Morison['M8N8FIyi'] = False # (N/m); ;
Morison['M8N9FIyi'] = False # (N/m); ;
Morison['M9N1FIyi'] = False # (N/m); ;
Morison['M9N2FIyi'] = False # (N/m); ;
Morison['M9N3FIyi'] = False # (N/m); ;
Morison['M9N4FIyi'] = False # (N/m); ;
Morison['M9N5FIyi'] = False # (N/m); ;
Morison['M9N6FIyi'] = False # (N/m); ;
Morison['M9N7FIyi'] = False # (N/m); ;
Morison['M9N8FIyi'] = False # (N/m); ;
Morison['M9N9FIyi'] = False # (N/m); ;
Morison['M1N1FIzi'] = False # (N/m); z-component of the distributed inertial force expressed in the inertial coordinate system;
Morison['M1N2FIzi'] = False # (N/m); ;
Morison['M1N3FIzi'] = False # (N/m); ;
Morison['M1N4FIzi'] = False # (N/m); ;
Morison['M1N5FIzi'] = False # (N/m); ;
Morison['M1N6FIzi'] = False # (N/m); ;
Morison['M1N7FIzi'] = False # (N/m); ;
Morison['M1N8FIzi'] = False # (N/m); ;
Morison['M1N9FIzi'] = False # (N/m); ;
Morison['M2N1FIzi'] = False # (N/m); ;
Morison['M2N2FIzi'] = False # (N/m); ;
Morison['M2N3FIzi'] = False # (N/m); ;
Morison['M2N4FIzi'] = False # (N/m); ;
Morison['M2N5FIzi'] = False # (N/m); ;
Morison['M2N6FIzi'] = False # (N/m); ;
Morison['M2N7FIzi'] = False # (N/m); ;
Morison['M2N8FIzi'] = False # (N/m); ;
Morison['M2N9FIzi'] = False # (N/m); ;
Morison['M3N1FIzi'] = False # (N/m); ;
Morison['M3N2FIzi'] = False # (N/m); ;
Morison['M3N3FIzi'] = False # (N/m); ;
Morison['M3N4FIzi'] = False # (N/m); ;
Morison['M3N5FIzi'] = False # (N/m); ;
Morison['M3N6FIzi'] = False # (N/m); ;
Morison['M3N7FIzi'] = False # (N/m); ;
Morison['M3N8FIzi'] = False # (N/m); ;
Morison['M3N9FIzi'] = False # (N/m); ;
Morison['M4N1FIzi'] = False # (N/m); ;
Morison['M4N2FIzi'] = False # (N/m); ;
Morison['M4N3FIzi'] = False # (N/m); ;
Morison['M4N4FIzi'] = False # (N/m); ;
Morison['M4N5FIzi'] = False # (N/m); ;
Morison['M4N6FIzi'] = False # (N/m); ;
Morison['M4N7FIzi'] = False # (N/m); ;
Morison['M4N8FIzi'] = False # (N/m); ;
Morison['M4N9FIzi'] = False # (N/m); ;
Morison['M5N1FIzi'] = False # (N/m); ;
Morison['M5N2FIzi'] = False # (N/m); ;
Morison['M5N3FIzi'] = False # (N/m); ;
Morison['M5N4FIzi'] = False # (N/m); ;
Morison['M5N5FIzi'] = False # (N/m); ;
Morison['M5N6FIzi'] = False # (N/m); ;
Morison['M5N7FIzi'] = False # (N/m); ;
Morison['M5N8FIzi'] = False # (N/m); ;
Morison['M5N9FIzi'] = False # (N/m); ;
Morison['M6N1FIzi'] = False # (N/m); ;
Morison['M6N2FIzi'] = False # (N/m); ;
Morison['M6N3FIzi'] = False # (N/m); ;
Morison['M6N4FIzi'] = False # (N/m); ;
Morison['M6N5FIzi'] = False # (N/m); ;
Morison['M6N6FIzi'] = False # (N/m); ;
Morison['M6N7FIzi'] = False # (N/m); ;
Morison['M6N8FIzi'] = False # (N/m); ;
Morison['M6N9FIzi'] = False # (N/m); ;
Morison['M7N1FIzi'] = False # (N/m); ;
Morison['M7N2FIzi'] = False # (N/m); ;
Morison['M7N3FIzi'] = False # (N/m); ;
Morison['M7N4FIzi'] = False # (N/m); ;
Morison['M7N5FIzi'] = False # (N/m); ;
Morison['M7N6FIzi'] = False # (N/m); ;
Morison['M7N7FIzi'] = False # (N/m); ;
Morison['M7N8FIzi'] = False # (N/m); ;
Morison['M7N9FIzi'] = False # (N/m); ;
Morison['M8N1FIzi'] = False # (N/m); ;
Morison['M8N2FIzi'] = False # (N/m); ;
Morison['M8N3FIzi'] = False # (N/m); ;
Morison['M8N4FIzi'] = False # (N/m); ;
Morison['M8N5FIzi'] = False # (N/m); ;
Morison['M8N6FIzi'] = False # (N/m); ;
Morison['M8N7FIzi'] = False # (N/m); ;
Morison['M8N8FIzi'] = False # (N/m); ;
Morison['M8N9FIzi'] = False # (N/m); ;
Morison['M9N1FIzi'] = False # (N/m); ;
Morison['M9N2FIzi'] = False # (N/m); ;
Morison['M9N3FIzi'] = False # (N/m); ;
Morison['M9N4FIzi'] = False # (N/m); ;
Morison['M9N5FIzi'] = False # (N/m); ;
Morison['M9N6FIzi'] = False # (N/m); ;
Morison['M9N7FIzi'] = False # (N/m); ;
Morison['M9N8FIzi'] = False # (N/m); ;
Morison['M9N9FIzi'] = False # (N/m); ;
Morison['M1N1FBxi'] = False # (N/m); x-component of the distributed bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FBxi'] = False # (N/m); ;
Morison['M1N3FBxi'] = False # (N/m); ;
Morison['M1N4FBxi'] = False # (N/m); ;
Morison['M1N5FBxi'] = False # (N/m); ;
Morison['M1N6FBxi'] = False # (N/m); ;
Morison['M1N7FBxi'] = False # (N/m); ;
Morison['M1N8FBxi'] = False # (N/m); ;
Morison['M1N9FBxi'] = False # (N/m); ;
Morison['M2N1FBxi'] = False # (N/m); ;
Morison['M2N2FBxi'] = False # (N/m); ;
Morison['M2N3FBxi'] = False # (N/m); ;
Morison['M2N4FBxi'] = False # (N/m); ;
Morison['M2N5FBxi'] = False # (N/m); ;
Morison['M2N6FBxi'] = False # (N/m); ;
Morison['M2N7FBxi'] = False # (N/m); ;
Morison['M2N8FBxi'] = False # (N/m); ;
Morison['M2N9FBxi'] = False # (N/m); ;
Morison['M3N1FBxi'] = False # (N/m); ;
Morison['M3N2FBxi'] = False # (N/m); ;
Morison['M3N3FBxi'] = False # (N/m); ;
Morison['M3N4FBxi'] = False # (N/m); ;
Morison['M3N5FBxi'] = False # (N/m); ;
Morison['M3N6FBxi'] = False # (N/m); ;
Morison['M3N7FBxi'] = False # (N/m); ;
Morison['M3N8FBxi'] = False # (N/m); ;
Morison['M3N9FBxi'] = False # (N/m); ;
Morison['M4N1FBxi'] = False # (N/m); ;
Morison['M4N2FBxi'] = False # (N/m); ;
Morison['M4N3FBxi'] = False # (N/m); ;
Morison['M4N4FBxi'] = False # (N/m); ;
Morison['M4N5FBxi'] = False # (N/m); ;
Morison['M4N6FBxi'] = False # (N/m); ;
Morison['M4N7FBxi'] = False # (N/m); ;
Morison['M4N8FBxi'] = False # (N/m); ;
Morison['M4N9FBxi'] = False # (N/m); ;
Morison['M5N1FBxi'] = False # (N/m); ;
Morison['M5N2FBxi'] = False # (N/m); ;
Morison['M5N3FBxi'] = False # (N/m); ;
Morison['M5N4FBxi'] = False # (N/m); ;
Morison['M5N5FBxi'] = False # (N/m); ;
Morison['M5N6FBxi'] = False # (N/m); ;
Morison['M5N7FBxi'] = False # (N/m); ;
Morison['M5N8FBxi'] = False # (N/m); ;
Morison['M5N9FBxi'] = False # (N/m); ;
Morison['M6N1FBxi'] = False # (N/m); ;
Morison['M6N2FBxi'] = False # (N/m); ;
Morison['M6N3FBxi'] = False # (N/m); ;
Morison['M6N4FBxi'] = False # (N/m); ;
Morison['M6N5FBxi'] = False # (N/m); ;
Morison['M6N6FBxi'] = False # (N/m); ;
Morison['M6N7FBxi'] = False # (N/m); ;
Morison['M6N8FBxi'] = False # (N/m); ;
Morison['M6N9FBxi'] = False # (N/m); ;
Morison['M7N1FBxi'] = False # (N/m); ;
Morison['M7N2FBxi'] = False # (N/m); ;
Morison['M7N3FBxi'] = False # (N/m); ;
Morison['M7N4FBxi'] = False # (N/m); ;
Morison['M7N5FBxi'] = False # (N/m); ;
Morison['M7N6FBxi'] = False # (N/m); ;
Morison['M7N7FBxi'] = False # (N/m); ;
Morison['M7N8FBxi'] = False # (N/m); ;
Morison['M7N9FBxi'] = False # (N/m); ;
Morison['M8N1FBxi'] = False # (N/m); ;
Morison['M8N2FBxi'] = False # (N/m); ;
Morison['M8N3FBxi'] = False # (N/m); ;
Morison['M8N4FBxi'] = False # (N/m); ;
Morison['M8N5FBxi'] = False # (N/m); ;
Morison['M8N6FBxi'] = False # (N/m); ;
Morison['M8N7FBxi'] = False # (N/m); ;
Morison['M8N8FBxi'] = False # (N/m); ;
Morison['M8N9FBxi'] = False # (N/m); ;
Morison['M9N1FBxi'] = False # (N/m); ;
Morison['M9N2FBxi'] = False # (N/m); ;
Morison['M9N3FBxi'] = False # (N/m); ;
Morison['M9N4FBxi'] = False # (N/m); ;
Morison['M9N5FBxi'] = False # (N/m); ;
Morison['M9N6FBxi'] = False # (N/m); ;
Morison['M9N7FBxi'] = False # (N/m); ;
Morison['M9N8FBxi'] = False # (N/m); ;
Morison['M9N9FBxi'] = False # (N/m); ;
Morison['M1N1FByi'] = False # (N/m); y-component of the distributed bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FByi'] = False # (N/m); ;
Morison['M1N3FByi'] = False # (N/m); ;
Morison['M1N4FByi'] = False # (N/m); ;
Morison['M1N5FByi'] = False # (N/m); ;
Morison['M1N6FByi'] = False # (N/m); ;
Morison['M1N7FByi'] = False # (N/m); ;
Morison['M1N8FByi'] = False # (N/m); ;
Morison['M1N9FByi'] = False # (N/m); ;
Morison['M2N1FByi'] = False # (N/m); ;
Morison['M2N2FByi'] = False # (N/m); ;
Morison['M2N3FByi'] = False # (N/m); ;
Morison['M2N4FByi'] = False # (N/m); ;
Morison['M2N5FByi'] = False # (N/m); ;
Morison['M2N6FByi'] = False # (N/m); ;
Morison['M2N7FByi'] = False # (N/m); ;
Morison['M2N8FByi'] = False # (N/m); ;
Morison['M2N9FByi'] = False # (N/m); ;
Morison['M3N1FByi'] = False # (N/m); ;
Morison['M3N2FByi'] = False # (N/m); ;
Morison['M3N3FByi'] = False # (N/m); ;
Morison['M3N4FByi'] = False # (N/m); ;
Morison['M3N5FByi'] = False # (N/m); ;
Morison['M3N6FByi'] = False # (N/m); ;
Morison['M3N7FByi'] = False # (N/m); ;
Morison['M3N8FByi'] = False # (N/m); ;
Morison['M3N9FByi'] = False # (N/m); ;
Morison['M4N1FByi'] = False # (N/m); ;
Morison['M4N2FByi'] = False # (N/m); ;
Morison['M4N3FByi'] = False # (N/m); ;
Morison['M4N4FByi'] = False # (N/m); ;
Morison['M4N5FByi'] = False # (N/m); ;
Morison['M4N6FByi'] = False # (N/m); ;
Morison['M4N7FByi'] = False # (N/m); ;
Morison['M4N8FByi'] = False # (N/m); ;
Morison['M4N9FByi'] = False # (N/m); ;
Morison['M5N1FByi'] = False # (N/m); ;
Morison['M5N2FByi'] = False # (N/m); ;
Morison['M5N3FByi'] = False # (N/m); ;
Morison['M5N4FByi'] = False # (N/m); ;
Morison['M5N5FByi'] = False # (N/m); ;
Morison['M5N6FByi'] = False # (N/m); ;
Morison['M5N7FByi'] = False # (N/m); ;
Morison['M5N8FByi'] = False # (N/m); ;
Morison['M5N9FByi'] = False # (N/m); ;
Morison['M6N1FByi'] = False # (N/m); ;
Morison['M6N2FByi'] = False # (N/m); ;
Morison['M6N3FByi'] = False # (N/m); ;
Morison['M6N4FByi'] = False # (N/m); ;
Morison['M6N5FByi'] = False # (N/m); ;
Morison['M6N6FByi'] = False # (N/m); ;
Morison['M6N7FByi'] = False # (N/m); ;
Morison['M6N8FByi'] = False # (N/m); ;
Morison['M6N9FByi'] = False # (N/m); ;
Morison['M7N1FByi'] = False # (N/m); ;
Morison['M7N2FByi'] = False # (N/m); ;
Morison['M7N3FByi'] = False # (N/m); ;
Morison['M7N4FByi'] = False # (N/m); ;
Morison['M7N5FByi'] = False # (N/m); ;
Morison['M7N6FByi'] = False # (N/m); ;
Morison['M7N7FByi'] = False # (N/m); ;
Morison['M7N8FByi'] = False # (N/m); ;
Morison['M7N9FByi'] = False # (N/m); ;
Morison['M8N1FByi'] = False # (N/m); ;
Morison['M8N2FByi'] = False # (N/m); ;
Morison['M8N3FByi'] = False # (N/m); ;
Morison['M8N4FByi'] = False # (N/m); ;
Morison['M8N5FByi'] = False # (N/m); ;
Morison['M8N6FByi'] = False # (N/m); ;
Morison['M8N7FByi'] = False # (N/m); ;
Morison['M8N8FByi'] = False # (N/m); ;
Morison['M8N9FByi'] = False # (N/m); ;
Morison['M9N1FByi'] = False # (N/m); ;
Morison['M9N2FByi'] = False # (N/m); ;
Morison['M9N3FByi'] = False # (N/m); ;
Morison['M9N4FByi'] = False # (N/m); ;
Morison['M9N5FByi'] = False # (N/m); ;
Morison['M9N6FByi'] = False # (N/m); ;
Morison['M9N7FByi'] = False # (N/m); ;
Morison['M9N8FByi'] = False # (N/m); ;
Morison['M9N9FByi'] = False # (N/m); ;
Morison['M1N1FBzi'] = False # (N/m); z-component of the distributed bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FBzi'] = False # (N/m); ;
Morison['M1N3FBzi'] = False # (N/m); ;
Morison['M1N4FBzi'] = False # (N/m); ;
Morison['M1N5FBzi'] = False # (N/m); ;
Morison['M1N6FBzi'] = False # (N/m); ;
Morison['M1N7FBzi'] = False # (N/m); ;
Morison['M1N8FBzi'] = False # (N/m); ;
Morison['M1N9FBzi'] = False # (N/m); ;
Morison['M2N1FBzi'] = False # (N/m); ;
Morison['M2N2FBzi'] = False # (N/m); ;
Morison['M2N3FBzi'] = False # (N/m); ;
Morison['M2N4FBzi'] = False # (N/m); ;
Morison['M2N5FBzi'] = False # (N/m); ;
Morison['M2N6FBzi'] = False # (N/m); ;
Morison['M2N7FBzi'] = False # (N/m); ;
Morison['M2N8FBzi'] = False # (N/m); ;
Morison['M2N9FBzi'] = False # (N/m); ;
Morison['M3N1FBzi'] = False # (N/m); ;
Morison['M3N2FBzi'] = False # (N/m); ;
Morison['M3N3FBzi'] = False # (N/m); ;
Morison['M3N4FBzi'] = False # (N/m); ;
Morison['M3N5FBzi'] = False # (N/m); ;
Morison['M3N6FBzi'] = False # (N/m); ;
Morison['M3N7FBzi'] = False # (N/m); ;
Morison['M3N8FBzi'] = False # (N/m); ;
Morison['M3N9FBzi'] = False # (N/m); ;
Morison['M4N1FBzi'] = False # (N/m); ;
Morison['M4N2FBzi'] = False # (N/m); ;
Morison['M4N3FBzi'] = False # (N/m); ;
Morison['M4N4FBzi'] = False # (N/m); ;
Morison['M4N5FBzi'] = False # (N/m); ;
Morison['M4N6FBzi'] = False # (N/m); ;
Morison['M4N7FBzi'] = False # (N/m); ;
Morison['M4N8FBzi'] = False # (N/m); ;
Morison['M4N9FBzi'] = False # (N/m); ;
Morison['M5N1FBzi'] = False # (N/m); ;
Morison['M5N2FBzi'] = False # (N/m); ;
Morison['M5N3FBzi'] = False # (N/m); ;
Morison['M5N4FBzi'] = False # (N/m); ;
Morison['M5N5FBzi'] = False # (N/m); ;
Morison['M5N6FBzi'] = False # (N/m); ;
Morison['M5N7FBzi'] = False # (N/m); ;
Morison['M5N8FBzi'] = False # (N/m); ;
Morison['M5N9FBzi'] = False # (N/m); ;
Morison['M6N1FBzi'] = False # (N/m); ;
Morison['M6N2FBzi'] = False # (N/m); ;
Morison['M6N3FBzi'] = False # (N/m); ;
Morison['M6N4FBzi'] = False # (N/m); ;
Morison['M6N5FBzi'] = False # (N/m); ;
Morison['M6N6FBzi'] = False # (N/m); ;
Morison['M6N7FBzi'] = False # (N/m); ;
Morison['M6N8FBzi'] = False # (N/m); ;
Morison['M6N9FBzi'] = False # (N/m); ;
Morison['M7N1FBzi'] = False # (N/m); ;
Morison['M7N2FBzi'] = False # (N/m); ;
Morison['M7N3FBzi'] = False # (N/m); ;
Morison['M7N4FBzi'] = False # (N/m); ;
Morison['M7N5FBzi'] = False # (N/m); ;
Morison['M7N6FBzi'] = False # (N/m); ;
Morison['M7N7FBzi'] = False # (N/m); ;
Morison['M7N8FBzi'] = False # (N/m); ;
Morison['M7N9FBzi'] = False # (N/m); ;
Morison['M8N1FBzi'] = False # (N/m); ;
Morison['M8N2FBzi'] = False # (N/m); ;
Morison['M8N3FBzi'] = False # (N/m); ;
Morison['M8N4FBzi'] = False # (N/m); ;
Morison['M8N5FBzi'] = False # (N/m); ;
Morison['M8N6FBzi'] = False # (N/m); ;
Morison['M8N7FBzi'] = False # (N/m); ;
Morison['M8N8FBzi'] = False # (N/m); ;
Morison['M8N9FBzi'] = False # (N/m); ;
Morison['M9N1FBzi'] = False # (N/m); ;
Morison['M9N2FBzi'] = False # (N/m); ;
Morison['M9N3FBzi'] = False # (N/m); ;
Morison['M9N4FBzi'] = False # (N/m); ;
Morison['M9N5FBzi'] = False # (N/m); ;
Morison['M9N6FBzi'] = False # (N/m); ;
Morison['M9N7FBzi'] = False # (N/m); ;
Morison['M9N8FBzi'] = False # (N/m); ;
Morison['M9N9FBzi'] = False # (N/m); ;
Morison['M1N1MBxi'] = False # (N); x-component of the distributed bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MBxi'] = False # (N); ;
Morison['M1N3MBxi'] = False # (N); ;
Morison['M1N4MBxi'] = False # (N); ;
Morison['M1N5MBxi'] = False # (N); ;
Morison['M1N6MBxi'] = False # (N); ;
Morison['M1N7MBxi'] = False # (N); ;
Morison['M1N8MBxi'] = False # (N); ;
Morison['M1N9MBxi'] = False # (N); ;
Morison['M2N1MBxi'] = False # (N); ;
Morison['M2N2MBxi'] = False # (N); ;
Morison['M2N3MBxi'] = False # (N); ;
Morison['M2N4MBxi'] = False # (N); ;
Morison['M2N5MBxi'] = False # (N); ;
Morison['M2N6MBxi'] = False # (N); ;
Morison['M2N7MBxi'] = False # (N); ;
Morison['M2N8MBxi'] = False # (N); ;
Morison['M2N9MBxi'] = False # (N); ;
Morison['M3N1MBxi'] = False # (N); ;
Morison['M3N2MBxi'] = False # (N); ;
Morison['M3N3MBxi'] = False # (N); ;
Morison['M3N4MBxi'] = False # (N); ;
Morison['M3N5MBxi'] = False # (N); ;
Morison['M3N6MBxi'] = False # (N); ;
Morison['M3N7MBxi'] = False # (N); ;
Morison['M3N8MBxi'] = False # (N); ;
Morison['M3N9MBxi'] = False # (N); ;
Morison['M4N1MBxi'] = False # (N); ;
Morison['M4N2MBxi'] = False # (N); ;
Morison['M4N3MBxi'] = False # (N); ;
Morison['M4N4MBxi'] = False # (N); ;
Morison['M4N5MBxi'] = False # (N); ;
Morison['M4N6MBxi'] = False # (N); ;
Morison['M4N7MBxi'] = False # (N); ;
Morison['M4N8MBxi'] = False # (N); ;
Morison['M4N9MBxi'] = False # (N); ;
Morison['M5N1MBxi'] = False # (N); ;
Morison['M5N2MBxi'] = False # (N); ;
Morison['M5N3MBxi'] = False # (N); ;
Morison['M5N4MBxi'] = False # (N); ;
Morison['M5N5MBxi'] = False # (N); ;
Morison['M5N6MBxi'] = False # (N); ;
Morison['M5N7MBxi'] = False # (N); ;
Morison['M5N8MBxi'] = False # (N); ;
Morison['M5N9MBxi'] = False # (N); ;
Morison['M6N1MBxi'] = False # (N); ;
Morison['M6N2MBxi'] = False # (N); ;
Morison['M6N3MBxi'] = False # (N); ;
Morison['M6N4MBxi'] = False # (N); ;
Morison['M6N5MBxi'] = False # (N); ;
Morison['M6N6MBxi'] = False # (N); ;
Morison['M6N7MBxi'] = False # (N); ;
Morison['M6N8MBxi'] = False # (N); ;
Morison['M6N9MBxi'] = False # (N); ;
Morison['M7N1MBxi'] = False # (N); ;
Morison['M7N2MBxi'] = False # (N); ;
Morison['M7N3MBxi'] = False # (N); ;
Morison['M7N4MBxi'] = False # (N); ;
Morison['M7N5MBxi'] = False # (N); ;
Morison['M7N6MBxi'] = False # (N); ;
Morison['M7N7MBxi'] = False # (N); ;
Morison['M7N8MBxi'] = False # (N); ;
Morison['M7N9MBxi'] = False # (N); ;
Morison['M8N1MBxi'] = False # (N); ;
Morison['M8N2MBxi'] = False # (N); ;
Morison['M8N3MBxi'] = False # (N); ;
Morison['M8N4MBxi'] = False # (N); ;
Morison['M8N5MBxi'] = False # (N); ;
Morison['M8N6MBxi'] = False # (N); ;
Morison['M8N7MBxi'] = False # (N); ;
Morison['M8N8MBxi'] = False # (N); ;
Morison['M8N9MBxi'] = False # (N); ;
Morison['M9N1MBxi'] = False # (N); ;
Morison['M9N2MBxi'] = False # (N); ;
Morison['M9N3MBxi'] = False # (N); ;
Morison['M9N4MBxi'] = False # (N); ;
Morison['M9N5MBxi'] = False # (N); ;
Morison['M9N6MBxi'] = False # (N); ;
Morison['M9N7MBxi'] = False # (N); ;
Morison['M9N8MBxi'] = False # (N); ;
Morison['M9N9MBxi'] = False # (N); ;
Morison['M1N1MByi'] = False # (N); y-component of the distributed bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MByi'] = False # (N); ;
Morison['M1N3MByi'] = False # (N); ;
Morison['M1N4MByi'] = False # (N); ;
Morison['M1N5MByi'] = False # (N); ;
Morison['M1N6MByi'] = False # (N); ;
Morison['M1N7MByi'] = False # (N); ;
Morison['M1N8MByi'] = False # (N); ;
Morison['M1N9MByi'] = False # (N); ;
Morison['M2N1MByi'] = False # (N); ;
Morison['M2N2MByi'] = False # (N); ;
Morison['M2N3MByi'] = False # (N); ;
Morison['M2N4MByi'] = False # (N); ;
Morison['M2N5MByi'] = False # (N); ;
Morison['M2N6MByi'] = False # (N); ;
Morison['M2N7MByi'] = False # (N); ;
Morison['M2N8MByi'] = False # (N); ;
Morison['M2N9MByi'] = False # (N); ;
Morison['M3N1MByi'] = False # (N); ;
Morison['M3N2MByi'] = False # (N); ;
Morison['M3N3MByi'] = False # (N); ;
Morison['M3N4MByi'] = False # (N); ;
Morison['M3N5MByi'] = False # (N); ;
Morison['M3N6MByi'] = False # (N); ;
Morison['M3N7MByi'] = False # (N); ;
Morison['M3N8MByi'] = False # (N); ;
Morison['M3N9MByi'] = False # (N); ;
Morison['M4N1MByi'] = False # (N); ;
Morison['M4N2MByi'] = False # (N); ;
Morison['M4N3MByi'] = False # (N); ;
Morison['M4N4MByi'] = False # (N); ;
Morison['M4N5MByi'] = False # (N); ;
Morison['M4N6MByi'] = False # (N); ;
Morison['M4N7MByi'] = False # (N); ;
Morison['M4N8MByi'] = False # (N); ;
Morison['M4N9MByi'] = False # (N); ;
Morison['M5N1MByi'] = False # (N); ;
Morison['M5N2MByi'] = False # (N); ;
Morison['M5N3MByi'] = False # (N); ;
Morison['M5N4MByi'] = False # (N); ;
Morison['M5N5MByi'] = False # (N); ;
Morison['M5N6MByi'] = False # (N); ;
Morison['M5N7MByi'] = False # (N); ;
Morison['M5N8MByi'] = False # (N); ;
Morison['M5N9MByi'] = False # (N); ;
Morison['M6N1MByi'] = False # (N); ;
Morison['M6N2MByi'] = False # (N); ;
Morison['M6N3MByi'] = False # (N); ;
Morison['M6N4MByi'] = False # (N); ;
Morison['M6N5MByi'] = False # (N); ;
Morison['M6N6MByi'] = False # (N); ;
Morison['M6N7MByi'] = False # (N); ;
Morison['M6N8MByi'] = False # (N); ;
Morison['M6N9MByi'] = False # (N); ;
Morison['M7N1MByi'] = False # (N); ;
Morison['M7N2MByi'] = False # (N); ;
Morison['M7N3MByi'] = False # (N); ;
Morison['M7N4MByi'] = False # (N); ;
Morison['M7N5MByi'] = False # (N); ;
Morison['M7N6MByi'] = False # (N); ;
Morison['M7N7MByi'] = False # (N); ;
Morison['M7N8MByi'] = False # (N); ;
Morison['M7N9MByi'] = False # (N); ;
Morison['M8N1MByi'] = False # (N); ;
Morison['M8N2MByi'] = False # (N); ;
Morison['M8N3MByi'] = False # (N); ;
Morison['M8N4MByi'] = False # (N); ;
Morison['M8N5MByi'] = False # (N); ;
Morison['M8N6MByi'] = False # (N); ;
Morison['M8N7MByi'] = False # (N); ;
Morison['M8N8MByi'] = False # (N); ;
Morison['M8N9MByi'] = False # (N); ;
Morison['M9N1MByi'] = False # (N); ;
Morison['M9N2MByi'] = False # (N); ;
Morison['M9N3MByi'] = False # (N); ;
Morison['M9N4MByi'] = False # (N); ;
Morison['M9N5MByi'] = False # (N); ;
Morison['M9N6MByi'] = False # (N); ;
Morison['M9N7MByi'] = False # (N); ;
Morison['M9N8MByi'] = False # (N); ;
Morison['M9N9MByi'] = False # (N); ;
Morison['M1N1MBzi'] = False # (N); z-component of the distributed bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MBzi'] = False # (N); ;
Morison['M1N3MBzi'] = False # (N); ;
Morison['M1N4MBzi'] = False # (N); ;
Morison['M1N5MBzi'] = False # (N); ;
Morison['M1N6MBzi'] = False # (N); ;
Morison['M1N7MBzi'] = False # (N); ;
Morison['M1N8MBzi'] = False # (N); ;
Morison['M1N9MBzi'] = False # (N); ;
Morison['M2N1MBzi'] = False # (N); ;
Morison['M2N2MBzi'] = False # (N); ;
Morison['M2N3MBzi'] = False # (N); ;
Morison['M2N4MBzi'] = False # (N); ;
Morison['M2N5MBzi'] = False # (N); ;
Morison['M2N6MBzi'] = False # (N); ;
Morison['M2N7MBzi'] = False # (N); ;
Morison['M2N8MBzi'] = False # (N); ;
Morison['M2N9MBzi'] = False # (N); ;
Morison['M3N1MBzi'] = False # (N); ;
Morison['M3N2MBzi'] = False # (N); ;
Morison['M3N3MBzi'] = False # (N); ;
Morison['M3N4MBzi'] = False # (N); ;
Morison['M3N5MBzi'] = False # (N); ;
Morison['M3N6MBzi'] = False # (N); ;
Morison['M3N7MBzi'] = False # (N); ;
Morison['M3N8MBzi'] = False # (N); ;
Morison['M3N9MBzi'] = False # (N); ;
Morison['M4N1MBzi'] = False # (N); ;
Morison['M4N2MBzi'] = False # (N); ;
Morison['M4N3MBzi'] = False # (N); ;
Morison['M4N4MBzi'] = False # (N); ;
Morison['M4N5MBzi'] = False # (N); ;
Morison['M4N6MBzi'] = False # (N); ;
Morison['M4N7MBzi'] = False # (N); ;
Morison['M4N8MBzi'] = False # (N); ;
Morison['M4N9MBzi'] = False # (N); ;
Morison['M5N1MBzi'] = False # (N); ;
Morison['M5N2MBzi'] = False # (N); ;
Morison['M5N3MBzi'] = False # (N); ;
Morison['M5N4MBzi'] = False # (N); ;
Morison['M5N5MBzi'] = False # (N); ;
Morison['M5N6MBzi'] = False # (N); ;
Morison['M5N7MBzi'] = False # (N); ;
Morison['M5N8MBzi'] = False # (N); ;
Morison['M5N9MBzi'] = False # (N); ;
Morison['M6N1MBzi'] = False # (N); ;
Morison['M6N2MBzi'] = False # (N); ;
Morison['M6N3MBzi'] = False # (N); ;
Morison['M6N4MBzi'] = False # (N); ;
Morison['M6N5MBzi'] = False # (N); ;
Morison['M6N6MBzi'] = False # (N); ;
Morison['M6N7MBzi'] = False # (N); ;
Morison['M6N8MBzi'] = False # (N); ;
Morison['M6N9MBzi'] = False # (N); ;
Morison['M7N1MBzi'] = False # (N); ;
Morison['M7N2MBzi'] = False # (N); ;
Morison['M7N3MBzi'] = False # (N); ;
Morison['M7N4MBzi'] = False # (N); ;
Morison['M7N5MBzi'] = False # (N); ;
Morison['M7N6MBzi'] = False # (N); ;
Morison['M7N7MBzi'] = False # (N); ;
Morison['M7N8MBzi'] = False # (N); ;
Morison['M7N9MBzi'] = False # (N); ;
Morison['M8N1MBzi'] = False # (N); ;
Morison['M8N2MBzi'] = False # (N); ;
Morison['M8N3MBzi'] = False # (N); ;
Morison['M8N4MBzi'] = False # (N); ;
Morison['M8N5MBzi'] = False # (N); ;
Morison['M8N6MBzi'] = False # (N); ;
Morison['M8N7MBzi'] = False # (N); ;
Morison['M8N8MBzi'] = False # (N); ;
Morison['M8N9MBzi'] = False # (N); ;
Morison['M9N1MBzi'] = False # (N); ;
Morison['M9N2MBzi'] = False # (N); ;
Morison['M9N3MBzi'] = False # (N); ;
Morison['M9N4MBzi'] = False # (N); ;
Morison['M9N5MBzi'] = False # (N); ;
Morison['M9N6MBzi'] = False # (N); ;
Morison['M9N7MBzi'] = False # (N); ;
Morison['M9N8MBzi'] = False # (N); ;
Morison['M9N9MBzi'] = False # (N); ;
Morison['M1N1FBFxi'] = False # (N/m); x-component of the distributed filled fluid bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FBFxi'] = False # (N/m); ;
Morison['M1N3FBFxi'] = False # (N/m); ;
Morison['M1N4FBFxi'] = False # (N/m); ;
Morison['M1N5FBFxi'] = False # (N/m); ;
Morison['M1N6FBFxi'] = False # (N/m); ;
Morison['M1N7FBFxi'] = False # (N/m); ;
Morison['M1N8FBFxi'] = False # (N/m); ;
Morison['M1N9FBFxi'] = False # (N/m); ;
Morison['M2N1FBFxi'] = False # (N/m); ;
Morison['M2N2FBFxi'] = False # (N/m); ;
Morison['M2N3FBFxi'] = False # (N/m); ;
Morison['M2N4FBFxi'] = False # (N/m); ;
Morison['M2N5FBFxi'] = False # (N/m); ;
Morison['M2N6FBFxi'] = False # (N/m); ;
Morison['M2N7FBFxi'] = False # (N/m); ;
Morison['M2N8FBFxi'] = False # (N/m); ;
Morison['M2N9FBFxi'] = False # (N/m); ;
Morison['M3N1FBFxi'] = False # (N/m); ;
Morison['M3N2FBFxi'] = False # (N/m); ;
Morison['M3N3FBFxi'] = False # (N/m); ;
Morison['M3N4FBFxi'] = False # (N/m); ;
Morison['M3N5FBFxi'] = False # (N/m); ;
Morison['M3N6FBFxi'] = False # (N/m); ;
Morison['M3N7FBFxi'] = False # (N/m); ;
Morison['M3N8FBFxi'] = False # (N/m); ;
Morison['M3N9FBFxi'] = False # (N/m); ;
Morison['M4N1FBFxi'] = False # (N/m); ;
Morison['M4N2FBFxi'] = False # (N/m); ;
Morison['M4N3FBFxi'] = False # (N/m); ;
Morison['M4N4FBFxi'] = False # (N/m); ;
Morison['M4N5FBFxi'] = False # (N/m); ;
Morison['M4N6FBFxi'] = False # (N/m); ;
Morison['M4N7FBFxi'] = False # (N/m); ;
Morison['M4N8FBFxi'] = False # (N/m); ;
Morison['M4N9FBFxi'] = False # (N/m); ;
Morison['M5N1FBFxi'] = False # (N/m); ;
Morison['M5N2FBFxi'] = False # (N/m); ;
Morison['M5N3FBFxi'] = False # (N/m); ;
Morison['M5N4FBFxi'] = False # (N/m); ;
Morison['M5N5FBFxi'] = False # (N/m); ;
Morison['M5N6FBFxi'] = False # (N/m); ;
Morison['M5N7FBFxi'] = False # (N/m); ;
Morison['M5N8FBFxi'] = False # (N/m); ;
Morison['M5N9FBFxi'] = False # (N/m); ;
Morison['M6N1FBFxi'] = False # (N/m); ;
Morison['M6N2FBFxi'] = False # (N/m); ;
Morison['M6N3FBFxi'] = False # (N/m); ;
Morison['M6N4FBFxi'] = False # (N/m); ;
Morison['M6N5FBFxi'] = False # (N/m); ;
Morison['M6N6FBFxi'] = False # (N/m); ;
Morison['M6N7FBFxi'] = False # (N/m); ;
Morison['M6N8FBFxi'] = False # (N/m); ;
Morison['M6N9FBFxi'] = False # (N/m); ;
Morison['M7N1FBFxi'] = False # (N/m); ;
Morison['M7N2FBFxi'] = False # (N/m); ;
Morison['M7N3FBFxi'] = False # (N/m); ;
Morison['M7N4FBFxi'] = False # (N/m); ;
Morison['M7N5FBFxi'] = False # (N/m); ;
Morison['M7N6FBFxi'] = False # (N/m); ;
Morison['M7N7FBFxi'] = False # (N/m); ;
Morison['M7N8FBFxi'] = False # (N/m); ;
Morison['M7N9FBFxi'] = False # (N/m); ;
Morison['M8N1FBFxi'] = False # (N/m); ;
Morison['M8N2FBFxi'] = False # (N/m); ;
Morison['M8N3FBFxi'] = False # (N/m); ;
Morison['M8N4FBFxi'] = False # (N/m); ;
Morison['M8N5FBFxi'] = False # (N/m); ;
Morison['M8N6FBFxi'] = False # (N/m); ;
Morison['M8N7FBFxi'] = False # (N/m); ;
Morison['M8N8FBFxi'] = False # (N/m); ;
Morison['M8N9FBFxi'] = False # (N/m); ;
Morison['M9N1FBFxi'] = False # (N/m); ;
Morison['M9N2FBFxi'] = False # (N/m); ;
Morison['M9N3FBFxi'] = False # (N/m); ;
Morison['M9N4FBFxi'] = False # (N/m); ;
Morison['M9N5FBFxi'] = False # (N/m); ;
Morison['M9N6FBFxi'] = False # (N/m); ;
Morison['M9N7FBFxi'] = False # (N/m); ;
Morison['M9N8FBFxi'] = False # (N/m); ;
Morison['M9N9FBFxi'] = False # (N/m); ;
Morison['M1N1FBFyi'] = False # (N/m); y-component of the distributed filled fluid bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FBFyi'] = False # (N/m); ;
Morison['M1N3FBFyi'] = False # (N/m); ;
Morison['M1N4FBFyi'] = False # (N/m); ;
Morison['M1N5FBFyi'] = False # (N/m); ;
Morison['M1N6FBFyi'] = False # (N/m); ;
Morison['M1N7FBFyi'] = False # (N/m); ;
Morison['M1N8FBFyi'] = False # (N/m); ;
Morison['M1N9FBFyi'] = False # (N/m); ;
Morison['M2N1FBFyi'] = False # (N/m); ;
Morison['M2N2FBFyi'] = False # (N/m); ;
Morison['M2N3FBFyi'] = False # (N/m); ;
Morison['M2N4FBFyi'] = False # (N/m); ;
Morison['M2N5FBFyi'] = False # (N/m); ;
Morison['M2N6FBFyi'] = False # (N/m); ;
Morison['M2N7FBFyi'] = False # (N/m); ;
Morison['M2N8FBFyi'] = False # (N/m); ;
Morison['M2N9FBFyi'] = False # (N/m); ;
Morison['M3N1FBFyi'] = False # (N/m); ;
Morison['M3N2FBFyi'] = False # (N/m); ;
Morison['M3N3FBFyi'] = False # (N/m); ;
Morison['M3N4FBFyi'] = False # (N/m); ;
Morison['M3N5FBFyi'] = False # (N/m); ;
Morison['M3N6FBFyi'] = False # (N/m); ;
Morison['M3N7FBFyi'] = False # (N/m); ;
Morison['M3N8FBFyi'] = False # (N/m); ;
Morison['M3N9FBFyi'] = False # (N/m); ;
Morison['M4N1FBFyi'] = False # (N/m); ;
Morison['M4N2FBFyi'] = False # (N/m); ;
Morison['M4N3FBFyi'] = False # (N/m); ;
Morison['M4N4FBFyi'] = False # (N/m); ;
Morison['M4N5FBFyi'] = False # (N/m); ;
Morison['M4N6FBFyi'] = False # (N/m); ;
Morison['M4N7FBFyi'] = False # (N/m); ;
Morison['M4N8FBFyi'] = False # (N/m); ;
Morison['M4N9FBFyi'] = False # (N/m); ;
Morison['M5N1FBFyi'] = False # (N/m); ;
Morison['M5N2FBFyi'] = False # (N/m); ;
Morison['M5N3FBFyi'] = False # (N/m); ;
Morison['M5N4FBFyi'] = False # (N/m); ;
Morison['M5N5FBFyi'] = False # (N/m); ;
Morison['M5N6FBFyi'] = False # (N/m); ;
Morison['M5N7FBFyi'] = False # (N/m); ;
Morison['M5N8FBFyi'] = False # (N/m); ;
Morison['M5N9FBFyi'] = False # (N/m); ;
Morison['M6N1FBFyi'] = False # (N/m); ;
Morison['M6N2FBFyi'] = False # (N/m); ;
Morison['M6N3FBFyi'] = False # (N/m); ;
Morison['M6N4FBFyi'] = False # (N/m); ;
Morison['M6N5FBFyi'] = False # (N/m); ;
Morison['M6N6FBFyi'] = False # (N/m); ;
Morison['M6N7FBFyi'] = False # (N/m); ;
Morison['M6N8FBFyi'] = False # (N/m); ;
Morison['M6N9FBFyi'] = False # (N/m); ;
Morison['M7N1FBFyi'] = False # (N/m); ;
Morison['M7N2FBFyi'] = False # (N/m); ;
Morison['M7N3FBFyi'] = False # (N/m); ;
Morison['M7N4FBFyi'] = False # (N/m); ;
Morison['M7N5FBFyi'] = False # (N/m); ;
Morison['M7N6FBFyi'] = False # (N/m); ;
Morison['M7N7FBFyi'] = False # (N/m); ;
Morison['M7N8FBFyi'] = False # (N/m); ;
Morison['M7N9FBFyi'] = False # (N/m); ;
Morison['M8N1FBFyi'] = False # (N/m); ;
Morison['M8N2FBFyi'] = False # (N/m); ;
Morison['M8N3FBFyi'] = False # (N/m); ;
Morison['M8N4FBFyi'] = False # (N/m); ;
Morison['M8N5FBFyi'] = False # (N/m); ;
Morison['M8N6FBFyi'] = False # (N/m); ;
Morison['M8N7FBFyi'] = False # (N/m); ;
Morison['M8N8FBFyi'] = False # (N/m); ;
Morison['M8N9FBFyi'] = False # (N/m); ;
Morison['M9N1FBFyi'] = False # (N/m); ;
Morison['M9N2FBFyi'] = False # (N/m); ;
Morison['M9N3FBFyi'] = False # (N/m); ;
Morison['M9N4FBFyi'] = False # (N/m); ;
Morison['M9N5FBFyi'] = False # (N/m); ;
Morison['M9N6FBFyi'] = False # (N/m); ;
Morison['M9N7FBFyi'] = False # (N/m); ;
Morison['M9N8FBFyi'] = False # (N/m); ;
Morison['M9N9FBFyi'] = False # (N/m); ;
Morison['M1N1FBFzi'] = False # (N/m); z-component of the distributed filled fluid bouyancy force expressed in the inertial coordinate system;
Morison['M1N2FBFzi'] = False # (N/m); ;
Morison['M1N3FBFzi'] = False # (N/m); ;
Morison['M1N4FBFzi'] = False # (N/m); ;
Morison['M1N5FBFzi'] = False # (N/m); ;
Morison['M1N6FBFzi'] = False # (N/m); ;
Morison['M1N7FBFzi'] = False # (N/m); ;
Morison['M1N8FBFzi'] = False # (N/m); ;
Morison['M1N9FBFzi'] = False # (N/m); ;
Morison['M2N1FBFzi'] = False # (N/m); ;
Morison['M2N2FBFzi'] = False # (N/m); ;
Morison['M2N3FBFzi'] = False # (N/m); ;
Morison['M2N4FBFzi'] = False # (N/m); ;
Morison['M2N5FBFzi'] = False # (N/m); ;
Morison['M2N6FBFzi'] = False # (N/m); ;
Morison['M2N7FBFzi'] = False # (N/m); ;
Morison['M2N8FBFzi'] = False # (N/m); ;
Morison['M2N9FBFzi'] = False # (N/m); ;
Morison['M3N1FBFzi'] = False # (N/m); ;
Morison['M3N2FBFzi'] = False # (N/m); ;
Morison['M3N3FBFzi'] = False # (N/m); ;
Morison['M3N4FBFzi'] = False # (N/m); ;
Morison['M3N5FBFzi'] = False # (N/m); ;
Morison['M3N6FBFzi'] = False # (N/m); ;
Morison['M3N7FBFzi'] = False # (N/m); ;
Morison['M3N8FBFzi'] = False # (N/m); ;
Morison['M3N9FBFzi'] = False # (N/m); ;
Morison['M4N1FBFzi'] = False # (N/m); ;
Morison['M4N2FBFzi'] = False # (N/m); ;
Morison['M4N3FBFzi'] = False # (N/m); ;
Morison['M4N4FBFzi'] = False # (N/m); ;
Morison['M4N5FBFzi'] = False # (N/m); ;
Morison['M4N6FBFzi'] = False # (N/m); ;
Morison['M4N7FBFzi'] = False # (N/m); ;
Morison['M4N8FBFzi'] = False # (N/m); ;
Morison['M4N9FBFzi'] = False # (N/m); ;
Morison['M5N1FBFzi'] = False # (N/m); ;
Morison['M5N2FBFzi'] = False # (N/m); ;
Morison['M5N3FBFzi'] = False # (N/m); ;
Morison['M5N4FBFzi'] = False # (N/m); ;
Morison['M5N5FBFzi'] = False # (N/m); ;
Morison['M5N6FBFzi'] = False # (N/m); ;
Morison['M5N7FBFzi'] = False # (N/m); ;
Morison['M5N8FBFzi'] = False # (N/m); ;
Morison['M5N9FBFzi'] = False # (N/m); ;
Morison['M6N1FBFzi'] = False # (N/m); ;
Morison['M6N2FBFzi'] = False # (N/m); ;
Morison['M6N3FBFzi'] = False # (N/m); ;
Morison['M6N4FBFzi'] = False # (N/m); ;
Morison['M6N5FBFzi'] = False # (N/m); ;
Morison['M6N6FBFzi'] = False # (N/m); ;
Morison['M6N7FBFzi'] = False # (N/m); ;
Morison['M6N8FBFzi'] = False # (N/m); ;
Morison['M6N9FBFzi'] = False # (N/m); ;
Morison['M7N1FBFzi'] = False # (N/m); ;
Morison['M7N2FBFzi'] = False # (N/m); ;
Morison['M7N3FBFzi'] = False # (N/m); ;
Morison['M7N4FBFzi'] = False # (N/m); ;
Morison['M7N5FBFzi'] = False # (N/m); ;
Morison['M7N6FBFzi'] = False # (N/m); ;
Morison['M7N7FBFzi'] = False # (N/m); ;
Morison['M7N8FBFzi'] = False # (N/m); ;
Morison['M7N9FBFzi'] = False # (N/m); ;
Morison['M8N1FBFzi'] = False # (N/m); ;
Morison['M8N2FBFzi'] = False # (N/m); ;
Morison['M8N3FBFzi'] = False # (N/m); ;
Morison['M8N4FBFzi'] = False # (N/m); ;
Morison['M8N5FBFzi'] = False # (N/m); ;
Morison['M8N6FBFzi'] = False # (N/m); ;
Morison['M8N7FBFzi'] = False # (N/m); ;
Morison['M8N8FBFzi'] = False # (N/m); ;
Morison['M8N9FBFzi'] = False # (N/m); ;
Morison['M9N1FBFzi'] = False # (N/m); ;
Morison['M9N2FBFzi'] = False # (N/m); ;
Morison['M9N3FBFzi'] = False # (N/m); ;
Morison['M9N4FBFzi'] = False # (N/m); ;
Morison['M9N5FBFzi'] = False # (N/m); ;
Morison['M9N6FBFzi'] = False # (N/m); ;
Morison['M9N7FBFzi'] = False # (N/m); ;
Morison['M9N8FBFzi'] = False # (N/m); ;
Morison['M9N9FBFzi'] = False # (N/m); ;
Morison['M1N1MBFxi'] = False # (N); x-component of the distributed filled fluid bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MBFxi'] = False # (N); ;
Morison['M1N3MBFxi'] = False # (N); ;
Morison['M1N4MBFxi'] = False # (N); ;
Morison['M1N5MBFxi'] = False # (N); ;
Morison['M1N6MBFxi'] = False # (N); ;
Morison['M1N7MBFxi'] = False # (N); ;
Morison['M1N8MBFxi'] = False # (N); ;
Morison['M1N9MBFxi'] = False # (N); ;
Morison['M2N1MBFxi'] = False # (N); ;
Morison['M2N2MBFxi'] = False # (N); ;
Morison['M2N3MBFxi'] = False # (N); ;
Morison['M2N4MBFxi'] = False # (N); ;
Morison['M2N5MBFxi'] = False # (N); ;
Morison['M2N6MBFxi'] = False # (N); ;
Morison['M2N7MBFxi'] = False # (N); ;
Morison['M2N8MBFxi'] = False # (N); ;
Morison['M2N9MBFxi'] = False # (N); ;
Morison['M3N1MBFxi'] = False # (N); ;
Morison['M3N2MBFxi'] = False # (N); ;
Morison['M3N3MBFxi'] = False # (N); ;
Morison['M3N4MBFxi'] = False # (N); ;
Morison['M3N5MBFxi'] = False # (N); ;
Morison['M3N6MBFxi'] = False # (N); ;
Morison['M3N7MBFxi'] = False # (N); ;
Morison['M3N8MBFxi'] = False # (N); ;
Morison['M3N9MBFxi'] = False # (N); ;
Morison['M4N1MBFxi'] = False # (N); ;
Morison['M4N2MBFxi'] = False # (N); ;
Morison['M4N3MBFxi'] = False # (N); ;
Morison['M4N4MBFxi'] = False # (N); ;
Morison['M4N5MBFxi'] = False # (N); ;
Morison['M4N6MBFxi'] = False # (N); ;
Morison['M4N7MBFxi'] = False # (N); ;
Morison['M4N8MBFxi'] = False # (N); ;
Morison['M4N9MBFxi'] = False # (N); ;
Morison['M5N1MBFxi'] = False # (N); ;
Morison['M5N2MBFxi'] = False # (N); ;
Morison['M5N3MBFxi'] = False # (N); ;
Morison['M5N4MBFxi'] = False # (N); ;
Morison['M5N5MBFxi'] = False # (N); ;
Morison['M5N6MBFxi'] = False # (N); ;
Morison['M5N7MBFxi'] = False # (N); ;
Morison['M5N8MBFxi'] = False # (N); ;
Morison['M5N9MBFxi'] = False # (N); ;
Morison['M6N1MBFxi'] = False # (N); ;
Morison['M6N2MBFxi'] = False # (N); ;
Morison['M6N3MBFxi'] = False # (N); ;
Morison['M6N4MBFxi'] = False # (N); ;
Morison['M6N5MBFxi'] = False # (N); ;
Morison['M6N6MBFxi'] = False # (N); ;
Morison['M6N7MBFxi'] = False # (N); ;
Morison['M6N8MBFxi'] = False # (N); ;
Morison['M6N9MBFxi'] = False # (N); ;
Morison['M7N1MBFxi'] = False # (N); ;
Morison['M7N2MBFxi'] = False # (N); ;
Morison['M7N3MBFxi'] = False # (N); ;
Morison['M7N4MBFxi'] = False # (N); ;
Morison['M7N5MBFxi'] = False # (N); ;
Morison['M7N6MBFxi'] = False # (N); ;
Morison['M7N7MBFxi'] = False # (N); ;
Morison['M7N8MBFxi'] = False # (N); ;
Morison['M7N9MBFxi'] = False # (N); ;
Morison['M8N1MBFxi'] = False # (N); ;
Morison['M8N2MBFxi'] = False # (N); ;
Morison['M8N3MBFxi'] = False # (N); ;
Morison['M8N4MBFxi'] = False # (N); ;
Morison['M8N5MBFxi'] = False # (N); ;
Morison['M8N6MBFxi'] = False # (N); ;
Morison['M8N7MBFxi'] = False # (N); ;
Morison['M8N8MBFxi'] = False # (N); ;
Morison['M8N9MBFxi'] = False # (N); ;
Morison['M9N1MBFxi'] = False # (N); ;
Morison['M9N2MBFxi'] = False # (N); ;
Morison['M9N3MBFxi'] = False # (N); ;
Morison['M9N4MBFxi'] = False # (N); ;
Morison['M9N5MBFxi'] = False # (N); ;
Morison['M9N6MBFxi'] = False # (N); ;
Morison['M9N7MBFxi'] = False # (N); ;
Morison['M9N8MBFxi'] = False # (N); ;
Morison['M9N9MBFxi'] = False # (N); ;
Morison['M1N1MBFyi'] = False # (N); y-component of the distributed filled fluid bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MBFyi'] = False # (N); ;
Morison['M1N3MBFyi'] = False # (N); ;
Morison['M1N4MBFyi'] = False # (N); ;
Morison['M1N5MBFyi'] = False # (N); ;
Morison['M1N6MBFyi'] = False # (N); ;
Morison['M1N7MBFyi'] = False # (N); ;
Morison['M1N8MBFyi'] = False # (N); ;
Morison['M1N9MBFyi'] = False # (N); ;
Morison['M2N1MBFyi'] = False # (N); ;
Morison['M2N2MBFyi'] = False # (N); ;
Morison['M2N3MBFyi'] = False # (N); ;
Morison['M2N4MBFyi'] = False # (N); ;
Morison['M2N5MBFyi'] = False # (N); ;
Morison['M2N6MBFyi'] = False # (N); ;
Morison['M2N7MBFyi'] = False # (N); ;
Morison['M2N8MBFyi'] = False # (N); ;
Morison['M2N9MBFyi'] = False # (N); ;
Morison['M3N1MBFyi'] = False # (N); ;
Morison['M3N2MBFyi'] = False # (N); ;
Morison['M3N3MBFyi'] = False # (N); ;
Morison['M3N4MBFyi'] = False # (N); ;
Morison['M3N5MBFyi'] = False # (N); ;
Morison['M3N6MBFyi'] = False # (N); ;
Morison['M3N7MBFyi'] = False # (N); ;
Morison['M3N8MBFyi'] = False # (N); ;
Morison['M3N9MBFyi'] = False # (N); ;
Morison['M4N1MBFyi'] = False # (N); ;
Morison['M4N2MBFyi'] = False # (N); ;
Morison['M4N3MBFyi'] = False # (N); ;
Morison['M4N4MBFyi'] = False # (N); ;
Morison['M4N5MBFyi'] = False # (N); ;
Morison['M4N6MBFyi'] = False # (N); ;
Morison['M4N7MBFyi'] = False # (N); ;
Morison['M4N8MBFyi'] = False # (N); ;
Morison['M4N9MBFyi'] = False # (N); ;
Morison['M5N1MBFyi'] = False # (N); ;
Morison['M5N2MBFyi'] = False # (N); ;
Morison['M5N3MBFyi'] = False # (N); ;
Morison['M5N4MBFyi'] = False # (N); ;
Morison['M5N5MBFyi'] = False # (N); ;
Morison['M5N6MBFyi'] = False # (N); ;
Morison['M5N7MBFyi'] = False # (N); ;
Morison['M5N8MBFyi'] = False # (N); ;
Morison['M5N9MBFyi'] = False # (N); ;
Morison['M6N1MBFyi'] = False # (N); ;
Morison['M6N2MBFyi'] = False # (N); ;
Morison['M6N3MBFyi'] = False # (N); ;
Morison['M6N4MBFyi'] = False # (N); ;
Morison['M6N5MBFyi'] = False # (N); ;
Morison['M6N6MBFyi'] = False # (N); ;
Morison['M6N7MBFyi'] = False # (N); ;
Morison['M6N8MBFyi'] = False # (N); ;
Morison['M6N9MBFyi'] = False # (N); ;
Morison['M7N1MBFyi'] = False # (N); ;
Morison['M7N2MBFyi'] = False # (N); ;
Morison['M7N3MBFyi'] = False # (N); ;
Morison['M7N4MBFyi'] = False # (N); ;
Morison['M7N5MBFyi'] = False # (N); ;
Morison['M7N6MBFyi'] = False # (N); ;
Morison['M7N7MBFyi'] = False # (N); ;
Morison['M7N8MBFyi'] = False # (N); ;
Morison['M7N9MBFyi'] = False # (N); ;
Morison['M8N1MBFyi'] = False # (N); ;
Morison['M8N2MBFyi'] = False # (N); ;
Morison['M8N3MBFyi'] = False # (N); ;
Morison['M8N4MBFyi'] = False # (N); ;
Morison['M8N5MBFyi'] = False # (N); ;
Morison['M8N6MBFyi'] = False # (N); ;
Morison['M8N7MBFyi'] = False # (N); ;
Morison['M8N8MBFyi'] = False # (N); ;
Morison['M8N9MBFyi'] = False # (N); ;
Morison['M9N1MBFyi'] = False # (N); ;
Morison['M9N2MBFyi'] = False # (N); ;
Morison['M9N3MBFyi'] = False # (N); ;
Morison['M9N4MBFyi'] = False # (N); ;
Morison['M9N5MBFyi'] = False # (N); ;
Morison['M9N6MBFyi'] = False # (N); ;
Morison['M9N7MBFyi'] = False # (N); ;
Morison['M9N8MBFyi'] = False # (N); ;
Morison['M9N9MBFyi'] = False # (N); ;
Morison['M1N1MBFzi'] = False # (N); z-component of the distributed filled fluid bouyancy moment expressed in the inertial coordinate system;
Morison['M1N2MBFzi'] = False # (N); ;
Morison['M1N3MBFzi'] = False # (N); ;
Morison['M1N4MBFzi'] = False # (N); ;
Morison['M1N5MBFzi'] = False # (N); ;
Morison['M1N6MBFzi'] = False # (N); ;
Morison['M1N7MBFzi'] = False # (N); ;
Morison['M1N8MBFzi'] = False # (N); ;
Morison['M1N9MBFzi'] = False # (N); ;
Morison['M2N1MBFzi'] = False # (N); ;
Morison['M2N2MBFzi'] = False # (N); ;
Morison['M2N3MBFzi'] = False # (N); ;
Morison['M2N4MBFzi'] = False # (N); ;
Morison['M2N5MBFzi'] = False # (N); ;
Morison['M2N6MBFzi'] = False # (N); ;
Morison['M2N7MBFzi'] = False # (N); ;
Morison['M2N8MBFzi'] = False # (N); ;
Morison['M2N9MBFzi'] = False # (N); ;
Morison['M3N1MBFzi'] = False # (N); ;
Morison['M3N2MBFzi'] = False # (N); ;
Morison['M3N3MBFzi'] = False # (N); ;
Morison['M3N4MBFzi'] = False # (N); ;
Morison['M3N5MBFzi'] = False # (N); ;
Morison['M3N6MBFzi'] = False # (N); ;
Morison['M3N7MBFzi'] = False # (N); ;
Morison['M3N8MBFzi'] = False # (N); ;
Morison['M3N9MBFzi'] = False # (N); ;
Morison['M4N1MBFzi'] = False # (N); ;
Morison['M4N2MBFzi'] = False # (N); ;
Morison['M4N3MBFzi'] = False # (N); ;
Morison['M4N4MBFzi'] = False # (N); ;
Morison['M4N5MBFzi'] = False # (N); ;
Morison['M4N6MBFzi'] = False # (N); ;
Morison['M4N7MBFzi'] = False # (N); ;
Morison['M4N8MBFzi'] = False # (N); ;
Morison['M4N9MBFzi'] = False # (N); ;
Morison['M5N1MBFzi'] = False # (N); ;
Morison['M5N2MBFzi'] = False # (N); ;
Morison['M5N3MBFzi'] = False # (N); ;
Morison['M5N4MBFzi'] = False # (N); ;
Morison['M5N5MBFzi'] = False # (N); ;
Morison['M5N6MBFzi'] = False # (N); ;
Morison['M5N7MBFzi'] = False # (N); ;
Morison['M5N8MBFzi'] = False # (N); ;
Morison['M5N9MBFzi'] = False # (N); ;
Morison['M6N1MBFzi'] = False # (N); ;
Morison['M6N2MBFzi'] = False # (N); ;
Morison['M6N3MBFzi'] = False # (N); ;
Morison['M6N4MBFzi'] = False # (N); ;
Morison['M6N5MBFzi'] = False # (N); ;
Morison['M6N6MBFzi'] = False # (N); ;
Morison['M6N7MBFzi'] = False # (N); ;
Morison['M6N8MBFzi'] = False # (N); ;
Morison['M6N9MBFzi'] = False # (N); ;
Morison['M7N1MBFzi'] = False # (N); ;
Morison['M7N2MBFzi'] = False # (N); ;
Morison['M7N3MBFzi'] = False # (N); ;
Morison['M7N4MBFzi'] = False # (N); ;
Morison['M7N5MBFzi'] = False # (N); ;
Morison['M7N6MBFzi'] = False # (N); ;
Morison['M7N7MBFzi'] = False # (N); ;
Morison['M7N8MBFzi'] = False # (N); ;
Morison['M7N9MBFzi'] = False # (N); ;
Morison['M8N1MBFzi'] = False # (N); ;
Morison['M8N2MBFzi'] = False # (N); ;
Morison['M8N3MBFzi'] = False # (N); ;
Morison['M8N4MBFzi'] = False # (N); ;
Morison['M8N5MBFzi'] = False # (N); ;
Morison['M8N6MBFzi'] = False # (N); ;
Morison['M8N7MBFzi'] = False # (N); ;
Morison['M8N8MBFzi'] = False # (N); ;
Morison['M8N9MBFzi'] = False # (N); ;
Morison['M9N1MBFzi'] = False # (N); ;
Morison['M9N2MBFzi'] = False # (N); ;
Morison['M9N3MBFzi'] = False # (N); ;
Morison['M9N4MBFzi'] = False # (N); ;
Morison['M9N5MBFzi'] = False # (N); ;
Morison['M9N6MBFzi'] = False # (N); ;
Morison['M9N7MBFzi'] = False # (N); ;
Morison['M9N8MBFzi'] = False # (N); ;
Morison['M9N9MBFzi'] = False # (N); ;
Morison['M1N1FMGxi'] = False # (N/m); x-component of the distributed marine growth weight expressed in the inertial coordinate system;
Morison['M1N2FMGxi'] = False # (N/m); ;
Morison['M1N3FMGxi'] = False # (N/m); ;
Morison['M1N4FMGxi'] = False # (N/m); ;
Morison['M1N5FMGxi'] = False # (N/m); ;
Morison['M1N6FMGxi'] = False # (N/m); ;
Morison['M1N7FMGxi'] = False # (N/m); ;
Morison['M1N8FMGxi'] = False # (N/m); ;
Morison['M1N9FMGxi'] = False # (N/m); ;
Morison['M2N1FMGxi'] = False # (N/m); ;
Morison['M2N2FMGxi'] = False # (N/m); ;
Morison['M2N3FMGxi'] = False # (N/m); ;
Morison['M2N4FMGxi'] = False # (N/m); ;
Morison['M2N5FMGxi'] = False # (N/m); ;
Morison['M2N6FMGxi'] = False # (N/m); ;
Morison['M2N7FMGxi'] = False # (N/m); ;
Morison['M2N8FMGxi'] = False # (N/m); ;
Morison['M2N9FMGxi'] = False # (N/m); ;
Morison['M3N1FMGxi'] = False # (N/m); ;
Morison['M3N2FMGxi'] = False # (N/m); ;
Morison['M3N3FMGxi'] = False # (N/m); ;
Morison['M3N4FMGxi'] = False # (N/m); ;
Morison['M3N5FMGxi'] = False # (N/m); ;
Morison['M3N6FMGxi'] = False # (N/m); ;
Morison['M3N7FMGxi'] = False # (N/m); ;
Morison['M3N8FMGxi'] = False # (N/m); ;
Morison['M3N9FMGxi'] = False # (N/m); ;
Morison['M4N1FMGxi'] = False # (N/m); ;
Morison['M4N2FMGxi'] = False # (N/m); ;
Morison['M4N3FMGxi'] = False # (N/m); ;
Morison['M4N4FMGxi'] = False # (N/m); ;
Morison['M4N5FMGxi'] = False # (N/m); ;
Morison['M4N6FMGxi'] = False # (N/m); ;
Morison['M4N7FMGxi'] = False # (N/m); ;
Morison['M4N8FMGxi'] = False # (N/m); ;
Morison['M4N9FMGxi'] = False # (N/m); ;
Morison['M5N1FMGxi'] = False # (N/m); ;
Morison['M5N2FMGxi'] = False # (N/m); ;
Morison['M5N3FMGxi'] = False # (N/m); ;
Morison['M5N4FMGxi'] = False # (N/m); ;
Morison['M5N5FMGxi'] = False # (N/m); ;
Morison['M5N6FMGxi'] = False # (N/m); ;
Morison['M5N7FMGxi'] = False # (N/m); ;
Morison['M5N8FMGxi'] = False # (N/m); ;
Morison['M5N9FMGxi'] = False # (N/m); ;
Morison['M6N1FMGxi'] = False # (N/m); ;
Morison['M6N2FMGxi'] = False # (N/m); ;
Morison['M6N3FMGxi'] = False # (N/m); ;
Morison['M6N4FMGxi'] = False # (N/m); ;
Morison['M6N5FMGxi'] = False # (N/m); ;
Morison['M6N6FMGxi'] = False # (N/m); ;
Morison['M6N7FMGxi'] = False # (N/m); ;
Morison['M6N8FMGxi'] = False # (N/m); ;
Morison['M6N9FMGxi'] = False # (N/m); ;
Morison['M7N1FMGxi'] = False # (N/m); ;
Morison['M7N2FMGxi'] = False # (N/m); ;
Morison['M7N3FMGxi'] = False # (N/m); ;
Morison['M7N4FMGxi'] = False # (N/m); ;
Morison['M7N5FMGxi'] = False # (N/m); ;
Morison['M7N6FMGxi'] = False # (N/m); ;
Morison['M7N7FMGxi'] = False # (N/m); ;
Morison['M7N8FMGxi'] = False # (N/m); ;
Morison['M7N9FMGxi'] = False # (N/m); ;
Morison['M8N1FMGxi'] = False # (N/m); ;
Morison['M8N2FMGxi'] = False # (N/m); ;
Morison['M8N3FMGxi'] = False # (N/m); ;
Morison['M8N4FMGxi'] = False # (N/m); ;
Morison['M8N5FMGxi'] = False # (N/m); ;
Morison['M8N6FMGxi'] = False # (N/m); ;
Morison['M8N7FMGxi'] = False # (N/m); ;
Morison['M8N8FMGxi'] = False # (N/m); ;
Morison['M8N9FMGxi'] = False # (N/m); ;
Morison['M9N1FMGxi'] = False # (N/m); ;
Morison['M9N2FMGxi'] = False # (N/m); ;
Morison['M9N3FMGxi'] = False # (N/m); ;
Morison['M9N4FMGxi'] = False # (N/m); ;
Morison['M9N5FMGxi'] = False # (N/m); ;
Morison['M9N6FMGxi'] = False # (N/m); ;
Morison['M9N7FMGxi'] = False # (N/m); ;
Morison['M9N8FMGxi'] = False # (N/m); ;
Morison['M9N9FMGxi'] = False # (N/m); ;
Morison['M1N1FMGyi'] = False # (N/m); y-component of the distributed marine growth weight expressed in the inertial coordinate system;
Morison['M1N2FMGyi'] = False # (N/m); ;
Morison['M1N3FMGyi'] = False # (N/m); ;
Morison['M1N4FMGyi'] = False # (N/m); ;
Morison['M1N5FMGyi'] = False # (N/m); ;
Morison['M1N6FMGyi'] = False # (N/m); ;
Morison['M1N7FMGyi'] = False # (N/m); ;
Morison['M1N8FMGyi'] = False # (N/m); ;
Morison['M1N9FMGyi'] = False # (N/m); ;
Morison['M2N1FMGyi'] = False # (N/m); ;
Morison['M2N2FMGyi'] = False # (N/m); ;
Morison['M2N3FMGyi'] = False # (N/m); ;
Morison['M2N4FMGyi'] = False # (N/m); ;
Morison['M2N5FMGyi'] = False # (N/m); ;
Morison['M2N6FMGyi'] = False # (N/m); ;
Morison['M2N7FMGyi'] = False # (N/m); ;
Morison['M2N8FMGyi'] = False # (N/m); ;
Morison['M2N9FMGyi'] = False # (N/m); ;
Morison['M3N1FMGyi'] = False # (N/m); ;
Morison['M3N2FMGyi'] = False # (N/m); ;
Morison['M3N3FMGyi'] = False # (N/m); ;
Morison['M3N4FMGyi'] = False # (N/m); ;
Morison['M3N5FMGyi'] = False # (N/m); ;
Morison['M3N6FMGyi'] = False # (N/m); ;
Morison['M3N7FMGyi'] = False # (N/m); ;
Morison['M3N8FMGyi'] = False # (N/m); ;
Morison['M3N9FMGyi'] = False # (N/m); ;
Morison['M4N1FMGyi'] = False # (N/m); ;
Morison['M4N2FMGyi'] = False # (N/m); ;
Morison['M4N3FMGyi'] = False # (N/m); ;
Morison['M4N4FMGyi'] = False # (N/m); ;
Morison['M4N5FMGyi'] = False # (N/m); ;
Morison['M4N6FMGyi'] = False # (N/m); ;
Morison['M4N7FMGyi'] = False # (N/m); ;
Morison['M4N8FMGyi'] = False # (N/m); ;
Morison['M4N9FMGyi'] = False # (N/m); ;
Morison['M5N1FMGyi'] = False # (N/m); ;
Morison['M5N2FMGyi'] = False # (N/m); ;
Morison['M5N3FMGyi'] = False # (N/m); ;
Morison['M5N4FMGyi'] = False # (N/m); ;
Morison['M5N5FMGyi'] = False # (N/m); ;
Morison['M5N6FMGyi'] = False # (N/m); ;
Morison['M5N7FMGyi'] = False # (N/m); ;
Morison['M5N8FMGyi'] = False # (N/m); ;
Morison['M5N9FMGyi'] = False # (N/m); ;
Morison['M6N1FMGyi'] = False # (N/m); ;
Morison['M6N2FMGyi'] = False # (N/m); ;
Morison['M6N3FMGyi'] = False # (N/m); ;
Morison['M6N4FMGyi'] = False # (N/m); ;
Morison['M6N5FMGyi'] = False # (N/m); ;
Morison['M6N6FMGyi'] = False # (N/m); ;
Morison['M6N7FMGyi'] = False # (N/m); ;
Morison['M6N8FMGyi'] = False # (N/m); ;
Morison['M6N9FMGyi'] = False # (N/m); ;
Morison['M7N1FMGyi'] = False # (N/m); ;
Morison['M7N2FMGyi'] = False # (N/m); ;
Morison['M7N3FMGyi'] = False # (N/m); ;
Morison['M7N4FMGyi'] = False # (N/m); ;
Morison['M7N5FMGyi'] = False # (N/m); ;
Morison['M7N6FMGyi'] = False # (N/m); ;
Morison['M7N7FMGyi'] = False # (N/m); ;
Morison['M7N8FMGyi'] = False # (N/m); ;
Morison['M7N9FMGyi'] = False # (N/m); ;
Morison['M8N1FMGyi'] = False # (N/m); ;
Morison['M8N2FMGyi'] = False # (N/m); ;
Morison['M8N3FMGyi'] = False # (N/m); ;
Morison['M8N4FMGyi'] = False # (N/m); ;
Morison['M8N5FMGyi'] = False # (N/m); ;
Morison['M8N6FMGyi'] = False # (N/m); ;
Morison['M8N7FMGyi'] = False # (N/m); ;
Morison['M8N8FMGyi'] = False # (N/m); ;
Morison['M8N9FMGyi'] = False # (N/m); ;
Morison['M9N1FMGyi'] = False # (N/m); ;
Morison['M9N2FMGyi'] = False # (N/m); ;
Morison['M9N3FMGyi'] = False # (N/m); ;
Morison['M9N4FMGyi'] = False # (N/m); ;
Morison['M9N5FMGyi'] = False # (N/m); ;
Morison['M9N6FMGyi'] = False # (N/m); ;
Morison['M9N7FMGyi'] = False # (N/m); ;
Morison['M9N8FMGyi'] = False # (N/m); ;
Morison['M9N9FMGyi'] = False # (N/m); ;
Morison['M1N1FMGzi'] = False # (N/m); z-component of the distributed marine growth weight expressed in the inertial coordinate system;
Morison['M1N2FMGzi'] = False # (N/m); ;
Morison['M1N3FMGzi'] = False # (N/m); ;
Morison['M1N4FMGzi'] = False # (N/m); ;
Morison['M1N5FMGzi'] = False # (N/m); ;
Morison['M1N6FMGzi'] = False # (N/m); ;
Morison['M1N7FMGzi'] = False # (N/m); ;
Morison['M1N8FMGzi'] = False # (N/m); ;
Morison['M1N9FMGzi'] = False # (N/m); ;
Morison['M2N1FMGzi'] = False # (N/m); ;
Morison['M2N2FMGzi'] = False # (N/m); ;
Morison['M2N3FMGzi'] = False # (N/m); ;
Morison['M2N4FMGzi'] = False # (N/m); ;
Morison['M2N5FMGzi'] = False # (N/m); ;
Morison['M2N6FMGzi'] = False # (N/m); ;
Morison['M2N7FMGzi'] = False # (N/m); ;
Morison['M2N8FMGzi'] = False # (N/m); ;
Morison['M2N9FMGzi'] = False # (N/m); ;
Morison['M3N1FMGzi'] = False # (N/m); ;
Morison['M3N2FMGzi'] = False # (N/m); ;
Morison['M3N3FMGzi'] = False # (N/m); ;
Morison['M3N4FMGzi'] = False # (N/m); ;
Morison['M3N5FMGzi'] = False # (N/m); ;
Morison['M3N6FMGzi'] = False # (N/m); ;
Morison['M3N7FMGzi'] = False # (N/m); ;
Morison['M3N8FMGzi'] = False # (N/m); ;
Morison['M3N9FMGzi'] = False # (N/m); ;
Morison['M4N1FMGzi'] = False # (N/m); ;
Morison['M4N2FMGzi'] = False # (N/m); ;
Morison['M4N3FMGzi'] = False # (N/m); ;
Morison['M4N4FMGzi'] = False # (N/m); ;
Morison['M4N5FMGzi'] = False # (N/m); ;
Morison['M4N6FMGzi'] = False # (N/m); ;
Morison['M4N7FMGzi'] = False # (N/m); ;
Morison['M4N8FMGzi'] = False # (N/m); ;
Morison['M4N9FMGzi'] = False # (N/m); ;
Morison['M5N1FMGzi'] = False # (N/m); ;
Morison['M5N2FMGzi'] = False # (N/m); ;
Morison['M5N3FMGzi'] = False # (N/m); ;
Morison['M5N4FMGzi'] = False # (N/m); ;
Morison['M5N5FMGzi'] = False # (N/m); ;
Morison['M5N6FMGzi'] = False # (N/m); ;
Morison['M5N7FMGzi'] = False # (N/m); ;
Morison['M5N8FMGzi'] = False # (N/m); ;
Morison['M5N9FMGzi'] = False # (N/m); ;
Morison['M6N1FMGzi'] = False # (N/m); ;
Morison['M6N2FMGzi'] = False # (N/m); ;
Morison['M6N3FMGzi'] = False # (N/m); ;
Morison['M6N4FMGzi'] = False # (N/m); ;
Morison['M6N5FMGzi'] = False # (N/m); ;
Morison['M6N6FMGzi'] = False # (N/m); ;
Morison['M6N7FMGzi'] = False # (N/m); ;
Morison['M6N8FMGzi'] = False # (N/m); ;
Morison['M6N9FMGzi'] = False # (N/m); ;
Morison['M7N1FMGzi'] = False # (N/m); ;
Morison['M7N2FMGzi'] = False # (N/m); ;
Morison['M7N3FMGzi'] = False # (N/m); ;
Morison['M7N4FMGzi'] = False # (N/m); ;
Morison['M7N5FMGzi'] = False # (N/m); ;
Morison['M7N6FMGzi'] = False # (N/m); ;
Morison['M7N7FMGzi'] = False # (N/m); ;
Morison['M7N8FMGzi'] = False # (N/m); ;
Morison['M7N9FMGzi'] = False # (N/m); ;
Morison['M8N1FMGzi'] = False # (N/m); ;
Morison['M8N2FMGzi'] = False # (N/m); ;
Morison['M8N3FMGzi'] = False # (N/m); ;
Morison['M8N4FMGzi'] = False # (N/m); ;
Morison['M8N5FMGzi'] = False # (N/m); ;
Morison['M8N6FMGzi'] = False # (N/m); ;
Morison['M8N7FMGzi'] = False # (N/m); ;
Morison['M8N8FMGzi'] = False # (N/m); ;
Morison['M8N9FMGzi'] = False # (N/m); ;
Morison['M9N1FMGzi'] = False # (N/m); ;
Morison['M9N2FMGzi'] = False # (N/m); ;
Morison['M9N3FMGzi'] = False # (N/m); ;
Morison['M9N4FMGzi'] = False # (N/m); ;
Morison['M9N5FMGzi'] = False # (N/m); ;
Morison['M9N6FMGzi'] = False # (N/m); ;
Morison['M9N7FMGzi'] = False # (N/m); ;
Morison['M9N8FMGzi'] = False # (N/m); ;
Morison['M9N9FMGzi'] = False # (N/m); ;
Morison['M1N1FAMxi'] = False # (N/m); x-component of the distributed added mass force due to the member's displacement of the external fluid, expressed in the inertial coordinate system;
Morison['M1N2FAMxi'] = False # (N/m); ;
Morison['M1N3FAMxi'] = False # (N/m); ;
Morison['M1N4FAMxi'] = False # (N/m); ;
Morison['M1N5FAMxi'] = False # (N/m); ;
Morison['M1N6FAMxi'] = False # (N/m); ;
Morison['M1N7FAMxi'] = False # (N/m); ;
Morison['M1N8FAMxi'] = False # (N/m); ;
Morison['M1N9FAMxi'] = False # (N/m); ;
Morison['M2N1FAMxi'] = False # (N/m); ;
Morison['M2N2FAMxi'] = False # (N/m); ;
Morison['M2N3FAMxi'] = False # (N/m); ;
Morison['M2N4FAMxi'] = False # (N/m); ;
Morison['M2N5FAMxi'] = False # (N/m); ;
Morison['M2N6FAMxi'] = False # (N/m); ;
Morison['M2N7FAMxi'] = False # (N/m); ;
Morison['M2N8FAMxi'] = False # (N/m); ;
Morison['M2N9FAMxi'] = False # (N/m); ;
Morison['M3N1FAMxi'] = False # (N/m); ;
Morison['M3N2FAMxi'] = False # (N/m); ;
Morison['M3N3FAMxi'] = False # (N/m); ;
Morison['M3N4FAMxi'] = False # (N/m); ;
Morison['M3N5FAMxi'] = False # (N/m); ;
Morison['M3N6FAMxi'] = False # (N/m); ;
Morison['M3N7FAMxi'] = False # (N/m); ;
Morison['M3N8FAMxi'] = False # (N/m); ;
Morison['M3N9FAMxi'] = False # (N/m); ;
Morison['M4N1FAMxi'] = False # (N/m); ;
Morison['M4N2FAMxi'] = False # (N/m); ;
Morison['M4N3FAMxi'] = False # (N/m); ;
Morison['M4N4FAMxi'] = False # (N/m); ;
Morison['M4N5FAMxi'] = False # (N/m); ;
Morison['M4N6FAMxi'] = False # (N/m); ;
Morison['M4N7FAMxi'] = False # (N/m); ;
Morison['M4N8FAMxi'] = False # (N/m); ;
Morison['M4N9FAMxi'] = False # (N/m); ;
Morison['M5N1FAMxi'] = False # (N/m); ;
Morison['M5N2FAMxi'] = False # (N/m); ;
Morison['M5N3FAMxi'] = False # (N/m); ;
Morison['M5N4FAMxi'] = False # (N/m); ;
Morison['M5N5FAMxi'] = False # (N/m); ;
Morison['M5N6FAMxi'] = False # (N/m); ;
Morison['M5N7FAMxi'] = False # (N/m); ;
Morison['M5N8FAMxi'] = False # (N/m); ;
Morison['M5N9FAMxi'] = False # (N/m); ;
Morison['M6N1FAMxi'] = False # (N/m); ;
Morison['M6N2FAMxi'] = False # (N/m); ;
Morison['M6N3FAMxi'] = False # (N/m); ;
Morison['M6N4FAMxi'] = False # (N/m); ;
Morison['M6N5FAMxi'] = False # (N/m); ;
Morison['M6N6FAMxi'] = False # (N/m); ;
Morison['M6N7FAMxi'] = False # (N/m); ;
Morison['M6N8FAMxi'] = False # (N/m); ;
Morison['M6N9FAMxi'] = False # (N/m); ;
Morison['M7N1FAMxi'] = False # (N/m); ;
Morison['M7N2FAMxi'] = False # (N/m); ;
Morison['M7N3FAMxi'] = False # (N/m); ;
Morison['M7N4FAMxi'] = False # (N/m); ;
Morison['M7N5FAMxi'] = False # (N/m); ;
Morison['M7N6FAMxi'] = False # (N/m); ;
Morison['M7N7FAMxi'] = False # (N/m); ;
Morison['M7N8FAMxi'] = False # (N/m); ;
Morison['M7N9FAMxi'] = False # (N/m); ;
Morison['M8N1FAMxi'] = False # (N/m); ;
Morison['M8N2FAMxi'] = False # (N/m); ;
Morison['M8N3FAMxi'] = False # (N/m); ;
Morison['M8N4FAMxi'] = False # (N/m); ;
Morison['M8N5FAMxi'] = False # (N/m); ;
Morison['M8N6FAMxi'] = False # (N/m); ;
Morison['M8N7FAMxi'] = False # (N/m); ;
Morison['M8N8FAMxi'] = False # (N/m); ;
Morison['M8N9FAMxi'] = False # (N/m); ;
Morison['M9N1FAMxi'] = False # (N/m); ;
Morison['M9N2FAMxi'] = False # (N/m); ;
Morison['M9N3FAMxi'] = False # (N/m); ;
Morison['M9N4FAMxi'] = False # (N/m); ;
Morison['M9N5FAMxi'] = False # (N/m); ;
Morison['M9N6FAMxi'] = False # (N/m); ;
Morison['M9N7FAMxi'] = False # (N/m); ;
Morison['M9N8FAMxi'] = False # (N/m); ;
Morison['M9N9FAMxi'] = False # (N/m); ;
Morison['M1N1FAMyi'] = False # (N/m); y-component of the distributed added mass force due to the member's displacement of the external fluid, expressed in the inertial coordinate system;
Morison['M1N2FAMyi'] = False # (N/m); ;
Morison['M1N3FAMyi'] = False # (N/m); ;
Morison['M1N4FAMyi'] = False # (N/m); ;
Morison['M1N5FAMyi'] = False # (N/m); ;
Morison['M1N6FAMyi'] = False # (N/m); ;
Morison['M1N7FAMyi'] = False # (N/m); ;
Morison['M1N8FAMyi'] = False # (N/m); ;
Morison['M1N9FAMyi'] = False # (N/m); ;
Morison['M2N1FAMyi'] = False # (N/m); ;
Morison['M2N2FAMyi'] = False # (N/m); ;
Morison['M2N3FAMyi'] = False # (N/m); ;
Morison['M2N4FAMyi'] = False # (N/m); ;
Morison['M2N5FAMyi'] = False # (N/m); ;
Morison['M2N6FAMyi'] = False # (N/m); ;
Morison['M2N7FAMyi'] = False # (N/m); ;
Morison['M2N8FAMyi'] = False # (N/m); ;
Morison['M2N9FAMyi'] = False # (N/m); ;
Morison['M3N1FAMyi'] = False # (N/m); ;
Morison['M3N2FAMyi'] = False # (N/m); ;
Morison['M3N3FAMyi'] = False # (N/m); ;
Morison['M3N4FAMyi'] = False # (N/m); ;
Morison['M3N5FAMyi'] = False # (N/m); ;
Morison['M3N6FAMyi'] = False # (N/m); ;
Morison['M3N7FAMyi'] = False # (N/m); ;
Morison['M3N8FAMyi'] = False # (N/m); ;
Morison['M3N9FAMyi'] = False # (N/m); ;
Morison['M4N1FAMyi'] = False # (N/m); ;
Morison['M4N2FAMyi'] = False # (N/m); ;
Morison['M4N3FAMyi'] = False # (N/m); ;
Morison['M4N4FAMyi'] = False # (N/m); ;
Morison['M4N5FAMyi'] = False # (N/m); ;
Morison['M4N6FAMyi'] = False # (N/m); ;
Morison['M4N7FAMyi'] = False # (N/m); ;
Morison['M4N8FAMyi'] = False # (N/m); ;
Morison['M4N9FAMyi'] = False # (N/m); ;
Morison['M5N1FAMyi'] = False # (N/m); ;
Morison['M5N2FAMyi'] = False # (N/m); ;
Morison['M5N3FAMyi'] = False # (N/m); ;
Morison['M5N4FAMyi'] = False # (N/m); ;
Morison['M5N5FAMyi'] = False # (N/m); ;
Morison['M5N6FAMyi'] = False # (N/m); ;
Morison['M5N7FAMyi'] = False # (N/m); ;
Morison['M5N8FAMyi'] = False # (N/m); ;
Morison['M5N9FAMyi'] = False # (N/m); ;
Morison['M6N1FAMyi'] = False # (N/m); ;
Morison['M6N2FAMyi'] = False # (N/m); ;
Morison['M6N3FAMyi'] = False # (N/m); ;
Morison['M6N4FAMyi'] = False # (N/m); ;
Morison['M6N5FAMyi'] = False # (N/m); ;
Morison['M6N6FAMyi'] = False # (N/m); ;
Morison['M6N7FAMyi'] = False # (N/m); ;
Morison['M6N8FAMyi'] = False # (N/m); ;
Morison['M6N9FAMyi'] = False # (N/m); ;
Morison['M7N1FAMyi'] = False # (N/m); ;
Morison['M7N2FAMyi'] = False # (N/m); ;
Morison['M7N3FAMyi'] = False # (N/m); ;
Morison['M7N4FAMyi'] = False # (N/m); ;
Morison['M7N5FAMyi'] = False # (N/m); ;
Morison['M7N6FAMyi'] = False # (N/m); ;
Morison['M7N7FAMyi'] = False # (N/m); ;
Morison['M7N8FAMyi'] = False # (N/m); ;
Morison['M7N9FAMyi'] = False # (N/m); ;
Morison['M8N1FAMyi'] = False # (N/m); ;
Morison['M8N2FAMyi'] = False # (N/m); ;
Morison['M8N3FAMyi'] = False # (N/m); ;
Morison['M8N4FAMyi'] = False # (N/m); ;
Morison['M8N5FAMyi'] = False # (N/m); ;
Morison['M8N6FAMyi'] = False # (N/m); ;
Morison['M8N7FAMyi'] = False # (N/m); ;
Morison['M8N8FAMyi'] = False # (N/m); ;
Morison['M8N9FAMyi'] = False # (N/m); ;
Morison['M9N1FAMyi'] = False # (N/m); ;
Morison['M9N2FAMyi'] = False # (N/m); ;
Morison['M9N3FAMyi'] = False # (N/m); ;
Morison['M9N4FAMyi'] = False # (N/m); ;
Morison['M9N5FAMyi'] = False # (N/m); ;
Morison['M9N6FAMyi'] = False # (N/m); ;
Morison['M9N7FAMyi'] = False # (N/m); ;
Morison['M9N8FAMyi'] = False # (N/m); ;
Morison['M9N9FAMyi'] = False # (N/m); ;
Morison['M1N1FAMzi'] = False # (N/m); z-component of the distributed added mass force due to the member's displacement of the external fluid, expressed in the inertial coordinate system;
Morison['M1N2FAMzi'] = False # (N/m); ;
Morison['M1N3FAMzi'] = False # (N/m); ;
Morison['M1N4FAMzi'] = False # (N/m); ;
Morison['M1N5FAMzi'] = False # (N/m); ;
Morison['M1N6FAMzi'] = False # (N/m); ;
Morison['M1N7FAMzi'] = False # (N/m); ;
Morison['M1N8FAMzi'] = False # (N/m); ;
Morison['M1N9FAMzi'] = False # (N/m); ;
Morison['M2N1FAMzi'] = False # (N/m); ;
Morison['M2N2FAMzi'] = False # (N/m); ;
Morison['M2N3FAMzi'] = False # (N/m); ;
Morison['M2N4FAMzi'] = False # (N/m); ;
Morison['M2N5FAMzi'] = False # (N/m); ;
Morison['M2N6FAMzi'] = False # (N/m); ;
Morison['M2N7FAMzi'] = False # (N/m); ;
Morison['M2N8FAMzi'] = False # (N/m); ;
Morison['M2N9FAMzi'] = False # (N/m); ;
Morison['M3N1FAMzi'] = False # (N/m); ;
Morison['M3N2FAMzi'] = False # (N/m); ;
Morison['M3N3FAMzi'] = False # (N/m); ;
Morison['M3N4FAMzi'] = False # (N/m); ;
Morison['M3N5FAMzi'] = False # (N/m); ;
Morison['M3N6FAMzi'] = False # (N/m); ;
Morison['M3N7FAMzi'] = False # (N/m); ;
Morison['M3N8FAMzi'] = False # (N/m); ;
Morison['M3N9FAMzi'] = False # (N/m); ;
Morison['M4N1FAMzi'] = False # (N/m); ;
Morison['M4N2FAMzi'] = False # (N/m); ;
Morison['M4N3FAMzi'] = False # (N/m); ;
Morison['M4N4FAMzi'] = False # (N/m); ;
Morison['M4N5FAMzi'] = False # (N/m); ;
Morison['M4N6FAMzi'] = False # (N/m); ;
Morison['M4N7FAMzi'] = False # (N/m); ;
Morison['M4N8FAMzi'] = False # (N/m); ;
Morison['M4N9FAMzi'] = False # (N/m); ;
Morison['M5N1FAMzi'] = False # (N/m); ;
Morison['M5N2FAMzi'] = False # (N/m); ;
Morison['M5N3FAMzi'] = False # (N/m); ;
Morison['M5N4FAMzi'] = False # (N/m); ;
Morison['M5N5FAMzi'] = False # (N/m); ;
Morison['M5N6FAMzi'] = False # (N/m); ;
Morison['M5N7FAMzi'] = False # (N/m); ;
Morison['M5N8FAMzi'] = False # (N/m); ;
Morison['M5N9FAMzi'] = False # (N/m); ;
Morison['M6N1FAMzi'] = False # (N/m); ;
Morison['M6N2FAMzi'] = False # (N/m); ;
Morison['M6N3FAMzi'] = False # (N/m); ;
Morison['M6N4FAMzi'] = False # (N/m); ;
Morison['M6N5FAMzi'] = False # (N/m); ;
Morison['M6N6FAMzi'] = False # (N/m); ;
Morison['M6N7FAMzi'] = False # (N/m); ;
Morison['M6N8FAMzi'] = False # (N/m); ;
Morison['M6N9FAMzi'] = False # (N/m); ;
Morison['M7N1FAMzi'] = False # (N/m); ;
Morison['M7N2FAMzi'] = False # (N/m); ;
Morison['M7N3FAMzi'] = False # (N/m); ;
Morison['M7N4FAMzi'] = False # (N/m); ;
Morison['M7N5FAMzi'] = False # (N/m); ;
Morison['M7N6FAMzi'] = False # (N/m); ;
Morison['M7N7FAMzi'] = False # (N/m); ;
Morison['M7N8FAMzi'] = False # (N/m); ;
Morison['M7N9FAMzi'] = False # (N/m); ;
Morison['M8N1FAMzi'] = False # (N/m); ;
Morison['M8N2FAMzi'] = False # (N/m); ;
Morison['M8N3FAMzi'] = False # (N/m); ;
Morison['M8N4FAMzi'] = False # (N/m); ;
Morison['M8N5FAMzi'] = False # (N/m); ;
Morison['M8N6FAMzi'] = False # (N/m); ;
Morison['M8N7FAMzi'] = False # (N/m); ;
Morison['M8N8FAMzi'] = False # (N/m); ;
Morison['M8N9FAMzi'] = False # (N/m); ;
Morison['M9N1FAMzi'] = False # (N/m); ;
Morison['M9N2FAMzi'] = False # (N/m); ;
Morison['M9N3FAMzi'] = False # (N/m); ;
Morison['M9N4FAMzi'] = False # (N/m); ;
Morison['M9N5FAMzi'] = False # (N/m); ;
Morison['M9N6FAMzi'] = False # (N/m); ;
Morison['M9N7FAMzi'] = False # (N/m); ;
Morison['M9N8FAMzi'] = False # (N/m); ;
Morison['M9N9FAMzi'] = False # (N/m); ;
Morison['M1N1FAGxi'] = False # (N/m); x-component of the distributed added mass force due to the marine growth, expressed in the inertial coordinate system;
Morison['M1N2FAGxi'] = False # (N/m); ;
Morison['M1N3FAGxi'] = False # (N/m); ;
Morison['M1N4FAGxi'] = False # (N/m); ;
Morison['M1N5FAGxi'] = False # (N/m); ;
Morison['M1N6FAGxi'] = False # (N/m); ;
Morison['M1N7FAGxi'] = False # (N/m); ;
Morison['M1N8FAGxi'] = False # (N/m); ;
Morison['M1N9FAGxi'] = False # (N/m); ;
Morison['M2N1FAGxi'] = False # (N/m); ;
Morison['M2N2FAGxi'] = False # (N/m); ;
Morison['M2N3FAGxi'] = False # (N/m); ;
Morison['M2N4FAGxi'] = False # (N/m); ;
Morison['M2N5FAGxi'] = False # (N/m); ;
Morison['M2N6FAGxi'] = False # (N/m); ;
Morison['M2N7FAGxi'] = False # (N/m); ;
Morison['M2N8FAGxi'] = False # (N/m); ;
Morison['M2N9FAGxi'] = False # (N/m); ;
Morison['M3N1FAGxi'] = False # (N/m); ;
Morison['M3N2FAGxi'] = False # (N/m); ;
Morison['M3N3FAGxi'] = False # (N/m); ;
Morison['M3N4FAGxi'] = False # (N/m); ;
Morison['M3N5FAGxi'] = False # (N/m); ;
Morison['M3N6FAGxi'] = False # (N/m); ;
Morison['M3N7FAGxi'] = False # (N/m); ;
Morison['M3N8FAGxi'] = False # (N/m); ;
Morison['M3N9FAGxi'] = False # (N/m); ;
Morison['M4N1FAGxi'] = False # (N/m); ;
Morison['M4N2FAGxi'] = False # (N/m); ;
Morison['M4N3FAGxi'] = False # (N/m); ;
Morison['M4N4FAGxi'] = False # (N/m); ;
Morison['M4N5FAGxi'] = False # (N/m); ;
Morison['M4N6FAGxi'] = False # (N/m); ;
Morison['M4N7FAGxi'] = False # (N/m); ;
Morison['M4N8FAGxi'] = False # (N/m); ;
Morison['M4N9FAGxi'] = False # (N/m); ;
Morison['M5N1FAGxi'] = False # (N/m); ;
Morison['M5N2FAGxi'] = False # (N/m); ;
Morison['M5N3FAGxi'] = False # (N/m); ;
Morison['M5N4FAGxi'] = False # (N/m); ;
Morison['M5N5FAGxi'] = False # (N/m); ;
Morison['M5N6FAGxi'] = False # (N/m); ;
Morison['M5N7FAGxi'] = False # (N/m); ;
Morison['M5N8FAGxi'] = False # (N/m); ;
Morison['M5N9FAGxi'] = False # (N/m); ;
Morison['M6N1FAGxi'] = False # (N/m); ;
Morison['M6N2FAGxi'] = False # (N/m); ;
Morison['M6N3FAGxi'] = False # (N/m); ;
Morison['M6N4FAGxi'] = False # (N/m); ;
Morison['M6N5FAGxi'] = False # (N/m); ;
Morison['M6N6FAGxi'] = False # (N/m); ;
Morison['M6N7FAGxi'] = False # (N/m); ;
Morison['M6N8FAGxi'] = False # (N/m); ;
Morison['M6N9FAGxi'] = False # (N/m); ;
Morison['M7N1FAGxi'] = False # (N/m); ;
Morison['M7N2FAGxi'] = False # (N/m); ;
Morison['M7N3FAGxi'] = False # (N/m); ;
Morison['M7N4FAGxi'] = False # (N/m); ;
Morison['M7N5FAGxi'] = False # (N/m); ;
Morison['M7N6FAGxi'] = False # (N/m); ;
Morison['M7N7FAGxi'] = False # (N/m); ;
Morison['M7N8FAGxi'] = False # (N/m); ;
Morison['M7N9FAGxi'] = False # (N/m); ;
Morison['M8N1FAGxi'] = False # (N/m); ;
Morison['M8N2FAGxi'] = False # (N/m); ;
Morison['M8N3FAGxi'] = False # (N/m); ;
Morison['M8N4FAGxi'] = False # (N/m); ;
Morison['M8N5FAGxi'] = False # (N/m); ;
Morison['M8N6FAGxi'] = False # (N/m); ;
Morison['M8N7FAGxi'] = False # (N/m); ;
Morison['M8N8FAGxi'] = False # (N/m); ;
Morison['M8N9FAGxi'] = False # (N/m); ;
Morison['M9N1FAGxi'] = False # (N/m); ;
Morison['M9N2FAGxi'] = False # (N/m); ;
Morison['M9N3FAGxi'] = False # (N/m); ;
Morison['M9N4FAGxi'] = False # (N/m); ;
Morison['M9N5FAGxi'] = False # (N/m); ;
Morison['M9N6FAGxi'] = False # (N/m); ;
Morison['M9N7FAGxi'] = False # (N/m); ;
Morison['M9N8FAGxi'] = False # (N/m); ;
Morison['M9N9FAGxi'] = False # (N/m); ;
Morison['M1N1FAGyi'] = False # (N/m); y-component of the distributed added mass force due to the marine growth, expressed in the inertial coordinate system;
Morison['M1N2FAGyi'] = False # (N/m); ;
Morison['M1N3FAGyi'] = False # (N/m); ;
Morison['M1N4FAGyi'] = False # (N/m); ;
Morison['M1N5FAGyi'] = False # (N/m); ;
Morison['M1N6FAGyi'] = False # (N/m); ;
Morison['M1N7FAGyi'] = False # (N/m); ;
Morison['M1N8FAGyi'] = False # (N/m); ;
Morison['M1N9FAGyi'] = False # (N/m); ;
Morison['M2N1FAGyi'] = False # (N/m); ;
Morison['M2N2FAGyi'] = False # (N/m); ;
Morison['M2N3FAGyi'] = False # (N/m); ;
Morison['M2N4FAGyi'] = False # (N/m); ;
Morison['M2N5FAGyi'] = False # (N/m); ;
Morison['M2N6FAGyi'] = False # (N/m); ;
Morison['M2N7FAGyi'] = False # (N/m); ;
Morison['M2N8FAGyi'] = False # (N/m); ;
Morison['M2N9FAGyi'] = False # (N/m); ;
Morison['M3N1FAGyi'] = False # (N/m); ;
Morison['M3N2FAGyi'] = False # (N/m); ;
Morison['M3N3FAGyi'] = False # (N/m); ;
Morison['M3N4FAGyi'] = False # (N/m); ;
Morison['M3N5FAGyi'] = False # (N/m); ;
Morison['M3N6FAGyi'] = False # (N/m); ;
Morison['M3N7FAGyi'] = False # (N/m); ;
Morison['M3N8FAGyi'] = False # (N/m); ;
Morison['M3N9FAGyi'] = False # (N/m); ;
Morison['M4N1FAGyi'] = False # (N/m); ;
Morison['M4N2FAGyi'] = False # (N/m); ;
Morison['M4N3FAGyi'] = False # (N/m); ;
Morison['M4N4FAGyi'] = False # (N/m); ;
Morison['M4N5FAGyi'] = False # (N/m); ;
Morison['M4N6FAGyi'] = False # (N/m); ;
Morison['M4N7FAGyi'] = False # (N/m); ;
Morison['M4N8FAGyi'] = False # (N/m); ;
Morison['M4N9FAGyi'] = False # (N/m); ;
Morison['M5N1FAGyi'] = False # (N/m); ;
Morison['M5N2FAGyi'] = False # (N/m); ;
Morison['M5N3FAGyi'] = False # (N/m); ;
Morison['M5N4FAGyi'] = False # (N/m); ;
Morison['M5N5FAGyi'] = False # (N/m); ;
Morison['M5N6FAGyi'] = False # (N/m); ;
Morison['M5N7FAGyi'] = False # (N/m); ;
Morison['M5N8FAGyi'] = False # (N/m); ;
Morison['M5N9FAGyi'] = False # (N/m); ;
Morison['M6N1FAGyi'] = False # (N/m); ;
Morison['M6N2FAGyi'] = False # (N/m); ;
Morison['M6N3FAGyi'] = False # (N/m); ;
Morison['M6N4FAGyi'] = False # (N/m); ;
Morison['M6N5FAGyi'] = False # (N/m); ;
Morison['M6N6FAGyi'] = False # (N/m); ;
Morison['M6N7FAGyi'] = False # (N/m); ;
Morison['M6N8FAGyi'] = False # (N/m); ;
Morison['M6N9FAGyi'] = False # (N/m); ;
Morison['M7N1FAGyi'] = False # (N/m); ;
Morison['M7N2FAGyi'] = False # (N/m); ;
Morison['M7N3FAGyi'] = False # (N/m); ;
Morison['M7N4FAGyi'] = False # (N/m); ;
Morison['M7N5FAGyi'] = False # (N/m); ;
Morison['M7N6FAGyi'] = False # (N/m); ;
Morison['M7N7FAGyi'] = False # (N/m); ;
Morison['M7N8FAGyi'] = False # (N/m); ;
Morison['M7N9FAGyi'] = False # (N/m); ;
Morison['M8N1FAGyi'] = False # (N/m); ;
Morison['M8N2FAGyi'] = False # (N/m); ;
Morison['M8N3FAGyi'] = False # (N/m); ;
Morison['M8N4FAGyi'] = False # (N/m); ;
Morison['M8N5FAGyi'] = False # (N/m); ;
Morison['M8N6FAGyi'] = False # (N/m); ;
Morison['M8N7FAGyi'] = False # (N/m); ;
Morison['M8N8FAGyi'] = False # (N/m); ;
Morison['M8N9FAGyi'] = False # (N/m); ;
Morison['M9N1FAGyi'] = False # (N/m); ;
Morison['M9N2FAGyi'] = False # (N/m); ;
Morison['M9N3FAGyi'] = False # (N/m); ;
Morison['M9N4FAGyi'] = False # (N/m); ;
Morison['M9N5FAGyi'] = False # (N/m); ;
Morison['M9N6FAGyi'] = False # (N/m); ;
Morison['M9N7FAGyi'] = False # (N/m); ;
Morison['M9N8FAGyi'] = False # (N/m); ;
Morison['M9N9FAGyi'] = False # (N/m); ;
Morison['M1N1FAGzi'] = False # (N/m); z-component of the distributed added mass force due to the marine growth, expressed in the inertial coordinate system;
Morison['M1N2FAGzi'] = False # (N/m); ;
Morison['M1N3FAGzi'] = False # (N/m); ;
Morison['M1N4FAGzi'] = False # (N/m); ;
Morison['M1N5FAGzi'] = False # (N/m); ;
Morison['M1N6FAGzi'] = False # (N/m); ;
Morison['M1N7FAGzi'] = False # (N/m); ;
Morison['M1N8FAGzi'] = False # (N/m); ;
Morison['M1N9FAGzi'] = False # (N/m); ;
Morison['M2N1FAGzi'] = False # (N/m); ;
Morison['M2N2FAGzi'] = False # (N/m); ;
Morison['M2N3FAGzi'] = False # (N/m); ;
Morison['M2N4FAGzi'] = False # (N/m); ;
Morison['M2N5FAGzi'] = False # (N/m); ;
Morison['M2N6FAGzi'] = False # (N/m); ;
Morison['M2N7FAGzi'] = False # (N/m); ;
Morison['M2N8FAGzi'] = False # (N/m); ;
Morison['M2N9FAGzi'] = False # (N/m); ;
Morison['M3N1FAGzi'] = False # (N/m); ;
Morison['M3N2FAGzi'] = False # (N/m); ;
Morison['M3N3FAGzi'] = False # (N/m); ;
Morison['M3N4FAGzi'] = False # (N/m); ;
Morison['M3N5FAGzi'] = False # (N/m); ;
Morison['M3N6FAGzi'] = False # (N/m); ;
Morison['M3N7FAGzi'] = False # (N/m); ;
Morison['M3N8FAGzi'] = False # (N/m); ;
Morison['M3N9FAGzi'] = False # (N/m); ;
Morison['M4N1FAGzi'] = False # (N/m); ;
Morison['M4N2FAGzi'] = False # (N/m); ;
Morison['M4N3FAGzi'] = False # (N/m); ;
Morison['M4N4FAGzi'] = False # (N/m); ;
Morison['M4N5FAGzi'] = False # (N/m); ;
Morison['M4N6FAGzi'] = False # (N/m); ;
Morison['M4N7FAGzi'] = False # (N/m); ;
Morison['M4N8FAGzi'] = False # (N/m); ;
Morison['M4N9FAGzi'] = False # (N/m); ;
Morison['M5N1FAGzi'] = False # (N/m); ;
Morison['M5N2FAGzi'] = False # (N/m); ;
Morison['M5N3FAGzi'] = False # (N/m); ;
Morison['M5N4FAGzi'] = False # (N/m); ;
Morison['M5N5FAGzi'] = False # (N/m); ;
Morison['M5N6FAGzi'] = False # (N/m); ;
Morison['M5N7FAGzi'] = False # (N/m); ;
Morison['M5N8FAGzi'] = False # (N/m); ;
Morison['M5N9FAGzi'] = False # (N/m); ;
Morison['M6N1FAGzi'] = False # (N/m); ;
Morison['M6N2FAGzi'] = False # (N/m); ;
Morison['M6N3FAGzi'] = False # (N/m); ;
Morison['M6N4FAGzi'] = False # (N/m); ;
Morison['M6N5FAGzi'] = False # (N/m); ;
Morison['M6N6FAGzi'] = False # (N/m); ;
Morison['M6N7FAGzi'] = False # (N/m); ;
Morison['M6N8FAGzi'] = False # (N/m); ;
Morison['M6N9FAGzi'] = False # (N/m); ;
Morison['M7N1FAGzi'] = False # (N/m); ;
Morison['M7N2FAGzi'] = False # (N/m); ;
Morison['M7N3FAGzi'] = False # (N/m); ;
Morison['M7N4FAGzi'] = False # (N/m); ;
Morison['M7N5FAGzi'] = False # (N/m); ;
Morison['M7N6FAGzi'] = False # (N/m); ;
Morison['M7N7FAGzi'] = False # (N/m); ;
Morison['M7N8FAGzi'] = False # (N/m); ;
Morison['M7N9FAGzi'] = False # (N/m); ;
Morison['M8N1FAGzi'] = False # (N/m); ;
Morison['M8N2FAGzi'] = False # (N/m); ;
Morison['M8N3FAGzi'] = False # (N/m); ;
Morison['M8N4FAGzi'] = False # (N/m); ;
Morison['M8N5FAGzi'] = False # (N/m); ;
Morison['M8N6FAGzi'] = False # (N/m); ;
Morison['M8N7FAGzi'] = False # (N/m); ;
Morison['M8N8FAGzi'] = False # (N/m); ;
Morison['M8N9FAGzi'] = False # (N/m); ;
Morison['M9N1FAGzi'] = False # (N/m); ;
Morison['M9N2FAGzi'] = False # (N/m); ;
Morison['M9N3FAGzi'] = False # (N/m); ;
Morison['M9N4FAGzi'] = False # (N/m); ;
Morison['M9N5FAGzi'] = False # (N/m); ;
Morison['M9N6FAGzi'] = False # (N/m); ;
Morison['M9N7FAGzi'] = False # (N/m); ;
Morison['M9N8FAGzi'] = False # (N/m); ;
Morison['M9N9FAGzi'] = False # (N/m); ;
Morison['M1N1FAFxi'] = False # (N/m); x-component of the distributed added mass force due to the ballast, expressed in the inertial coordinate system;
Morison['M1N2FAFxi'] = False # (N/m); ;
Morison['M1N3FAFxi'] = False # (N/m); ;
Morison['M1N4FAFxi'] = False # (N/m); ;
Morison['M1N5FAFxi'] = False # (N/m); ;
Morison['M1N6FAFxi'] = False # (N/m); ;
Morison['M1N7FAFxi'] = False # (N/m); ;
Morison['M1N8FAFxi'] = False # (N/m); ;
Morison['M1N9FAFxi'] = False # (N/m); ;
Morison['M2N1FAFxi'] = False # (N/m); ;
Morison['M2N2FAFxi'] = False # (N/m); ;
Morison['M2N3FAFxi'] = False # (N/m); ;
Morison['M2N4FAFxi'] = False # (N/m); ;
Morison['M2N5FAFxi'] = False # (N/m); ;
Morison['M2N6FAFxi'] = False # (N/m); ;
Morison['M2N7FAFxi'] = False # (N/m); ;
Morison['M2N8FAFxi'] = False # (N/m); ;
Morison['M2N9FAFxi'] = False # (N/m); ;
Morison['M3N1FAFxi'] = False # (N/m); ;
Morison['M3N2FAFxi'] = False # (N/m); ;
Morison['M3N3FAFxi'] = False # (N/m); ;
Morison['M3N4FAFxi'] = False # (N/m); ;
Morison['M3N5FAFxi'] = False # (N/m); ;
Morison['M3N6FAFxi'] = False # (N/m); ;
Morison['M3N7FAFxi'] = False # (N/m); ;
Morison['M3N8FAFxi'] = False # (N/m); ;
Morison['M3N9FAFxi'] = False # (N/m); ;
Morison['M4N1FAFxi'] = False # (N/m); ;
Morison['M4N2FAFxi'] = False # (N/m); ;
Morison['M4N3FAFxi'] = False # (N/m); ;
Morison['M4N4FAFxi'] = False # (N/m); ;
Morison['M4N5FAFxi'] = False # (N/m); ;
Morison['M4N6FAFxi'] = False # (N/m); ;
Morison['M4N7FAFxi'] = False # (N/m); ;
Morison['M4N8FAFxi'] = False # (N/m); ;
Morison['M4N9FAFxi'] = False # (N/m); ;
Morison['M5N1FAFxi'] = False # (N/m); ;
Morison['M5N2FAFxi'] = False # (N/m); ;
Morison['M5N3FAFxi'] = False # (N/m); ;
Morison['M5N4FAFxi'] = False # (N/m); ;
Morison['M5N5FAFxi'] = False # (N/m); ;
Morison['M5N6FAFxi'] = False # (N/m); ;
Morison['M5N7FAFxi'] = False # (N/m); ;
Morison['M5N8FAFxi'] = False # (N/m); ;
Morison['M5N9FAFxi'] = False # (N/m); ;
Morison['M6N1FAFxi'] = False # (N/m); ;
Morison['M6N2FAFxi'] = False # (N/m); ;
Morison['M6N3FAFxi'] = False # (N/m); ;
Morison['M6N4FAFxi'] = False # (N/m); ;
Morison['M6N5FAFxi'] = False # (N/m); ;
Morison['M6N6FAFxi'] = False # (N/m); ;
Morison['M6N7FAFxi'] = False # (N/m); ;
Morison['M6N8FAFxi'] = False # (N/m); ;
Morison['M6N9FAFxi'] = False # (N/m); ;
Morison['M7N1FAFxi'] = False # (N/m); ;
Morison['M7N2FAFxi'] = False # (N/m); ;
Morison['M7N3FAFxi'] = False # (N/m); ;
Morison['M7N4FAFxi'] = False # (N/m); ;
Morison['M7N5FAFxi'] = False # (N/m); ;
Morison['M7N6FAFxi'] = False # (N/m); ;
Morison['M7N7FAFxi'] = False # (N/m); ;
Morison['M7N8FAFxi'] = False # (N/m); ;
Morison['M7N9FAFxi'] = False # (N/m); ;
Morison['M8N1FAFxi'] = False # (N/m); ;
Morison['M8N2FAFxi'] = False # (N/m); ;
Morison['M8N3FAFxi'] = False # (N/m); ;
Morison['M8N4FAFxi'] = False # (N/m); ;
Morison['M8N5FAFxi'] = False # (N/m); ;
Morison['M8N6FAFxi'] = False # (N/m); ;
Morison['M8N7FAFxi'] = False # (N/m); ;
Morison['M8N8FAFxi'] = False # (N/m); ;
Morison['M8N9FAFxi'] = False # (N/m); ;
Morison['M9N1FAFxi'] = False # (N/m); ;
Morison['M9N2FAFxi'] = False # (N/m); ;
Morison['M9N3FAFxi'] = False # (N/m); ;
Morison['M9N4FAFxi'] = False # (N/m); ;
Morison['M9N5FAFxi'] = False # (N/m); ;
Morison['M9N6FAFxi'] = False # (N/m); ;
Morison['M9N7FAFxi'] = False # (N/m); ;
Morison['M9N8FAFxi'] = False # (N/m); ;
Morison['M9N9FAFxi'] = False # (N/m); ;
Morison['M1N1FAFyi'] = False # (N/m); y-component of the distributed added mass force due to the ballast, expressed in the inertial coordinate system;
Morison['M1N2FAFyi'] = False # (N/m); ;
Morison['M1N3FAFyi'] = False # (N/m); ;
Morison['M1N4FAFyi'] = False # (N/m); ;
Morison['M1N5FAFyi'] = False # (N/m); ;
Morison['M1N6FAFyi'] = False # (N/m); ;
Morison['M1N7FAFyi'] = False # (N/m); ;
Morison['M1N8FAFyi'] = False # (N/m); ;
Morison['M1N9FAFyi'] = False # (N/m); ;
Morison['M2N1FAFyi'] = False # (N/m); ;
Morison['M2N2FAFyi'] = False # (N/m); ;
Morison['M2N3FAFyi'] = False # (N/m); ;
Morison['M2N4FAFyi'] = False # (N/m); ;
Morison['M2N5FAFyi'] = False # (N/m); ;
Morison['M2N6FAFyi'] = False # (N/m); ;
Morison['M2N7FAFyi'] = False # (N/m); ;
Morison['M2N8FAFyi'] = False # (N/m); ;
Morison['M2N9FAFyi'] = False # (N/m); ;
Morison['M3N1FAFyi'] = False # (N/m); ;
Morison['M3N2FAFyi'] = False # (N/m); ;
Morison['M3N3FAFyi'] = False # (N/m); ;
Morison['M3N4FAFyi'] = False # (N/m); ;
Morison['M3N5FAFyi'] = False # (N/m); ;
Morison['M3N6FAFyi'] = False # (N/m); ;
Morison['M3N7FAFyi'] = False # (N/m); ;
Morison['M3N8FAFyi'] = False # (N/m); ;
Morison['M3N9FAFyi'] = False # (N/m); ;
Morison['M4N1FAFyi'] = False # (N/m); ;
Morison['M4N2FAFyi'] = False # (N/m); ;
Morison['M4N3FAFyi'] = False # (N/m); ;
Morison['M4N4FAFyi'] = False # (N/m); ;
Morison['M4N5FAFyi'] = False # (N/m); ;
Morison['M4N6FAFyi'] = False # (N/m); ;
Morison['M4N7FAFyi'] = False # (N/m); ;
Morison['M4N8FAFyi'] = False # (N/m); ;
Morison['M4N9FAFyi'] = False # (N/m); ;
Morison['M5N1FAFyi'] = False # (N/m); ;
Morison['M5N2FAFyi'] = False # (N/m); ;
Morison['M5N3FAFyi'] = False # (N/m); ;
Morison['M5N4FAFyi'] = False # (N/m); ;
Morison['M5N5FAFyi'] = False # (N/m); ;
Morison['M5N6FAFyi'] = False # (N/m); ;
Morison['M5N7FAFyi'] = False # (N/m); ;
Morison['M5N8FAFyi'] = False # (N/m); ;
Morison['M5N9FAFyi'] = False # (N/m); ;
Morison['M6N1FAFyi'] = False # (N/m); ;
Morison['M6N2FAFyi'] = False # (N/m); ;
Morison['M6N3FAFyi'] = False # (N/m); ;
Morison['M6N4FAFyi'] = False # (N/m); ;
Morison['M6N5FAFyi'] = False # (N/m); ;
Morison['M6N6FAFyi'] = False # (N/m); ;
Morison['M6N7FAFyi'] = False # (N/m); ;
Morison['M6N8FAFyi'] = False # (N/m); ;
Morison['M6N9FAFyi'] = False # (N/m); ;
Morison['M7N1FAFyi'] = False # (N/m); ;
Morison['M7N2FAFyi'] = False # (N/m); ;
Morison['M7N3FAFyi'] = False # (N/m); ;
Morison['M7N4FAFyi'] = False # (N/m); ;
Morison['M7N5FAFyi'] = False # (N/m); ;
Morison['M7N6FAFyi'] = False # (N/m); ;
Morison['M7N7FAFyi'] = False # (N/m); ;
Morison['M7N8FAFyi'] = False # (N/m); ;
Morison['M7N9FAFyi'] = False # (N/m); ;
Morison['M8N1FAFyi'] = False # (N/m); ;
Morison['M8N2FAFyi'] = False # (N/m); ;
Morison['M8N3FAFyi'] = False # (N/m); ;
Morison['M8N4FAFyi'] = False # (N/m); ;
Morison['M8N5FAFyi'] = False # (N/m); ;
Morison['M8N6FAFyi'] = False # (N/m); ;
Morison['M8N7FAFyi'] = False # (N/m); ;
Morison['M8N8FAFyi'] = False # (N/m); ;
Morison['M8N9FAFyi'] = False # (N/m); ;
Morison['M9N1FAFyi'] = False # (N/m); ;
Morison['M9N2FAFyi'] = False # (N/m); ;
Morison['M9N3FAFyi'] = False # (N/m); ;
Morison['M9N4FAFyi'] = False # (N/m); ;
Morison['M9N5FAFyi'] = False # (N/m); ;
Morison['M9N6FAFyi'] = False # (N/m); ;
Morison['M9N7FAFyi'] = False # (N/m); ;
Morison['M9N8FAFyi'] = False # (N/m); ;
Morison['M9N9FAFyi'] = False # (N/m); ;
Morison['M1N1FAFzi'] = False # (N/m); z-component of the distributed added mass force due to the ballast, expressed in the inertial coordinate system;
Morison['M1N2FAFzi'] = False # (N/m); ;
Morison['M1N3FAFzi'] = False # (N/m); ;
Morison['M1N4FAFzi'] = False # (N/m); ;
Morison['M1N5FAFzi'] = False # (N/m); ;
Morison['M1N6FAFzi'] = False # (N/m); ;
Morison['M1N7FAFzi'] = False # (N/m); ;
Morison['M1N8FAFzi'] = False # (N/m); ;
Morison['M1N9FAFzi'] = False # (N/m); ;
Morison['M2N1FAFzi'] = False # (N/m); ;
Morison['M2N2FAFzi'] = False # (N/m); ;
Morison['M2N3FAFzi'] = False # (N/m); ;
Morison['M2N4FAFzi'] = False # (N/m); ;
Morison['M2N5FAFzi'] = False # (N/m); ;
Morison['M2N6FAFzi'] = False # (N/m); ;
Morison['M2N7FAFzi'] = False # (N/m); ;
Morison['M2N8FAFzi'] = False # (N/m); ;
Morison['M2N9FAFzi'] = False # (N/m); ;
Morison['M3N1FAFzi'] = False # (N/m); ;
Morison['M3N2FAFzi'] = False # (N/m); ;
Morison['M3N3FAFzi'] = False # (N/m); ;
Morison['M3N4FAFzi'] = False # (N/m); ;
Morison['M3N5FAFzi'] = False # (N/m); ;
Morison['M3N6FAFzi'] = False # (N/m); ;
Morison['M3N7FAFzi'] = False # (N/m); ;
Morison['M3N8FAFzi'] = False # (N/m); ;
Morison['M3N9FAFzi'] = False # (N/m); ;
Morison['M4N1FAFzi'] = False # (N/m); ;
Morison['M4N2FAFzi'] = False # (N/m); ;
Morison['M4N3FAFzi'] = False # (N/m); ;
Morison['M4N4FAFzi'] = False # (N/m); ;
Morison['M4N5FAFzi'] = False # (N/m); ;
Morison['M4N6FAFzi'] = False # (N/m); ;
Morison['M4N7FAFzi'] = False # (N/m); ;
Morison['M4N8FAFzi'] = False # (N/m); ;
Morison['M4N9FAFzi'] = False # (N/m); ;
Morison['M5N1FAFzi'] = False # (N/m); ;
Morison['M5N2FAFzi'] = False # (N/m); ;
Morison['M5N3FAFzi'] = False # (N/m); ;
Morison['M5N4FAFzi'] = False # (N/m); ;
Morison['M5N5FAFzi'] = False # (N/m); ;
Morison['M5N6FAFzi'] = False # (N/m); ;
Morison['M5N7FAFzi'] = False # (N/m); ;
Morison['M5N8FAFzi'] = False # (N/m); ;
Morison['M5N9FAFzi'] = False # (N/m); ;
Morison['M6N1FAFzi'] = False # (N/m); ;
Morison['M6N2FAFzi'] = False # (N/m); ;
Morison['M6N3FAFzi'] = False # (N/m); ;
Morison['M6N4FAFzi'] = False # (N/m); ;
Morison['M6N5FAFzi'] = False # (N/m); ;
Morison['M6N6FAFzi'] = False # (N/m); ;
Morison['M6N7FAFzi'] = False # (N/m); ;
Morison['M6N8FAFzi'] = False # (N/m); ;
Morison['M6N9FAFzi'] = False # (N/m); ;
Morison['M7N1FAFzi'] = False # (N/m); ;
Morison['M7N2FAFzi'] = False # (N/m); ;
Morison['M7N3FAFzi'] = False # (N/m); ;
Morison['M7N4FAFzi'] = False # (N/m); ;
Morison['M7N5FAFzi'] = False # (N/m); ;
Morison['M7N6FAFzi'] = False # (N/m); ;
Morison['M7N7FAFzi'] = False # (N/m); ;
Morison['M7N8FAFzi'] = False # (N/m); ;
Morison['M7N9FAFzi'] = False # (N/m); ;
Morison['M8N1FAFzi'] = False # (N/m); ;
Morison['M8N2FAFzi'] = False # (N/m); ;
Morison['M8N3FAFzi'] = False # (N/m); ;
Morison['M8N4FAFzi'] = False # (N/m); ;
Morison['M8N5FAFzi'] = False # (N/m); ;
Morison['M8N6FAFzi'] = False # (N/m); ;
Morison['M8N7FAFzi'] = False # (N/m); ;
Morison['M8N8FAFzi'] = False # (N/m); ;
Morison['M8N9FAFzi'] = False # (N/m); ;
Morison['M9N1FAFzi'] = False # (N/m); ;
Morison['M9N2FAFzi'] = False # (N/m); ;
Morison['M9N3FAFzi'] = False # (N/m); ;
Morison['M9N4FAFzi'] = False # (N/m); ;
Morison['M9N5FAFzi'] = False # (N/m); ;
Morison['M9N6FAFzi'] = False # (N/m); ;
Morison['M9N7FAFzi'] = False # (N/m); ;
Morison['M9N8FAFzi'] = False # (N/m); ;
Morison['M9N9FAFzi'] = False # (N/m); ;
Morison['M1N1FAxi'] = False # (N/m); x-component of the combined distributed added mass force, expressed in the inertial coordinate system;
Morison['M1N2FAxi'] = False # (N/m); ;
Morison['M1N3FAxi'] = False # (N/m); ;
Morison['M1N4FAxi'] = False # (N/m); ;
Morison['M1N5FAxi'] = False # (N/m); ;
Morison['M1N6FAxi'] = False # (N/m); ;
Morison['M1N7FAxi'] = False # (N/m); ;
Morison['M1N8FAxi'] = False # (N/m); ;
Morison['M1N9FAxi'] = False # (N/m); ;
Morison['M2N1FAxi'] = False # (N/m); ;
Morison['M2N2FAxi'] = False # (N/m); ;
Morison['M2N3FAxi'] = False # (N/m); ;
Morison['M2N4FAxi'] = False # (N/m); ;
Morison['M2N5FAxi'] = False # (N/m); ;
Morison['M2N6FAxi'] = False # (N/m); ;
Morison['M2N7FAxi'] = False # (N/m); ;
Morison['M2N8FAxi'] = False # (N/m); ;
Morison['M2N9FAxi'] = False # (N/m); ;
Morison['M3N1FAxi'] = False # (N/m); ;
Morison['M3N2FAxi'] = False # (N/m); ;
Morison['M3N3FAxi'] = False # (N/m); ;
Morison['M3N4FAxi'] = False # (N/m); ;
Morison['M3N5FAxi'] = False # (N/m); ;
Morison['M3N6FAxi'] = False # (N/m); ;
Morison['M3N7FAxi'] = False # (N/m); ;
Morison['M3N8FAxi'] = False # (N/m); ;
Morison['M3N9FAxi'] = False # (N/m); ;
Morison['M4N1FAxi'] = False # (N/m); ;
Morison['M4N2FAxi'] = False # (N/m); ;
Morison['M4N3FAxi'] = False # (N/m); ;
Morison['M4N4FAxi'] = False # (N/m); ;
Morison['M4N5FAxi'] = False # (N/m); ;
Morison['M4N6FAxi'] = False # (N/m); ;
Morison['M4N7FAxi'] = False # (N/m); ;
Morison['M4N8FAxi'] = False # (N/m); ;
Morison['M4N9FAxi'] = False # (N/m); ;
Morison['M5N1FAxi'] = False # (N/m); ;
Morison['M5N2FAxi'] = False # (N/m); ;
Morison['M5N3FAxi'] = False # (N/m); ;
Morison['M5N4FAxi'] = False # (N/m); ;
Morison['M5N5FAxi'] = False # (N/m); ;
Morison['M5N6FAxi'] = False # (N/m); ;
Morison['M5N7FAxi'] = False # (N/m); ;
Morison['M5N8FAxi'] = False # (N/m); ;
Morison['M5N9FAxi'] = False # (N/m); ;
Morison['M6N1FAxi'] = False # (N/m); ;
Morison['M6N2FAxi'] = False # (N/m); ;
Morison['M6N3FAxi'] = False # (N/m); ;
Morison['M6N4FAxi'] = False # (N/m); ;
Morison['M6N5FAxi'] = False # (N/m); ;
Morison['M6N6FAxi'] = False # (N/m); ;
Morison['M6N7FAxi'] = False # (N/m); ;
Morison['M6N8FAxi'] = False # (N/m); ;
Morison['M6N9FAxi'] = False # (N/m); ;
Morison['M7N1FAxi'] = False # (N/m); ;
Morison['M7N2FAxi'] = False # (N/m); ;
Morison['M7N3FAxi'] = False # (N/m); ;
Morison['M7N4FAxi'] = False # (N/m); ;
Morison['M7N5FAxi'] = False # (N/m); ;
Morison['M7N6FAxi'] = False # (N/m); ;
Morison['M7N7FAxi'] = False # (N/m); ;
Morison['M7N8FAxi'] = False # (N/m); ;
Morison['M7N9FAxi'] = False # (N/m); ;
Morison['M8N1FAxi'] = False # (N/m); ;
Morison['M8N2FAxi'] = False # (N/m); ;
Morison['M8N3FAxi'] = False # (N/m); ;
Morison['M8N4FAxi'] = False # (N/m); ;
Morison['M8N5FAxi'] = False # (N/m); ;
Morison['M8N6FAxi'] = False # (N/m); ;
Morison['M8N7FAxi'] = False # (N/m); ;
Morison['M8N8FAxi'] = False # (N/m); ;
Morison['M8N9FAxi'] = False # (N/m); ;
Morison['M9N1FAxi'] = False # (N/m); ;
Morison['M9N2FAxi'] = False # (N/m); ;
Morison['M9N3FAxi'] = False # (N/m); ;
Morison['M9N4FAxi'] = False # (N/m); ;
Morison['M9N5FAxi'] = False # (N/m); ;
Morison['M9N6FAxi'] = False # (N/m); ;
Morison['M9N7FAxi'] = False # (N/m); ;
Morison['M9N8FAxi'] = False # (N/m); ;
Morison['M9N9FAxi'] = False # (N/m); ;
Morison['M1N1FAyi'] = False # (N/m); y-component of the combined distributed added mass force, expressed in the inertial coordinate system;
Morison['M1N2FAyi'] = False # (N/m); ;
Morison['M1N3FAyi'] = False # (N/m); ;
Morison['M1N4FAyi'] = False # (N/m); ;
Morison['M1N5FAyi'] = False # (N/m); ;
Morison['M1N6FAyi'] = False # (N/m); ;
Morison['M1N7FAyi'] = False # (N/m); ;
Morison['M1N8FAyi'] = False # (N/m); ;
Morison['M1N9FAyi'] = False # (N/m); ;
Morison['M2N1FAyi'] = False # (N/m); ;
Morison['M2N2FAyi'] = False # (N/m); ;
Morison['M2N3FAyi'] = False # (N/m); ;
Morison['M2N4FAyi'] = False # (N/m); ;
Morison['M2N5FAyi'] = False # (N/m); ;
Morison['M2N6FAyi'] = False # (N/m); ;
Morison['M2N7FAyi'] = False # (N/m); ;
Morison['M2N8FAyi'] = False # (N/m); ;
Morison['M2N9FAyi'] = False # (N/m); ;
Morison['M3N1FAyi'] = False # (N/m); ;
Morison['M3N2FAyi'] = False # (N/m); ;
Morison['M3N3FAyi'] = False # (N/m); ;
Morison['M3N4FAyi'] = False # (N/m); ;
Morison['M3N5FAyi'] = False # (N/m); ;
Morison['M3N6FAyi'] = False # (N/m); ;
Morison['M3N7FAyi'] = False # (N/m); ;
Morison['M3N8FAyi'] = False # (N/m); ;
Morison['M3N9FAyi'] = False # (N/m); ;
Morison['M4N1FAyi'] = False # (N/m); ;
Morison['M4N2FAyi'] = False # (N/m); ;
Morison['M4N3FAyi'] = False # (N/m); ;
Morison['M4N4FAyi'] = False # (N/m); ;
Morison['M4N5FAyi'] = False # (N/m); ;
Morison['M4N6FAyi'] = False # (N/m); ;
Morison['M4N7FAyi'] = False # (N/m); ;
Morison['M4N8FAyi'] = False # (N/m); ;
Morison['M4N9FAyi'] = False # (N/m); ;
Morison['M5N1FAyi'] = False # (N/m); ;
Morison['M5N2FAyi'] = False # (N/m); ;
Morison['M5N3FAyi'] = False # (N/m); ;
Morison['M5N4FAyi'] = False # (N/m); ;
Morison['M5N5FAyi'] = False # (N/m); ;
Morison['M5N6FAyi'] = False # (N/m); ;
Morison['M5N7FAyi'] = False # (N/m); ;
Morison['M5N8FAyi'] = False # (N/m); ;
Morison['M5N9FAyi'] = False # (N/m); ;
Morison['M6N1FAyi'] = False # (N/m); ;
Morison['M6N2FAyi'] = False # (N/m); ;
Morison['M6N3FAyi'] = False # (N/m); ;
Morison['M6N4FAyi'] = False # (N/m); ;
Morison['M6N5FAyi'] = False # (N/m); ;
Morison['M6N6FAyi'] = False # (N/m); ;
Morison['M6N7FAyi'] = False # (N/m); ;
Morison['M6N8FAyi'] = False # (N/m); ;
Morison['M6N9FAyi'] = False # (N/m); ;
Morison['M7N1FAyi'] = False # (N/m); ;
Morison['M7N2FAyi'] = False # (N/m); ;
Morison['M7N3FAyi'] = False # (N/m); ;
Morison['M7N4FAyi'] = False # (N/m); ;
Morison['M7N5FAyi'] = False # (N/m); ;
Morison['M7N6FAyi'] = False # (N/m); ;
Morison['M7N7FAyi'] = False # (N/m); ;
Morison['M7N8FAyi'] = False # (N/m); ;
Morison['M7N9FAyi'] = False # (N/m); ;
Morison['M8N1FAyi'] = False # (N/m); ;
Morison['M8N2FAyi'] = False # (N/m); ;
Morison['M8N3FAyi'] = False # (N/m); ;
Morison['M8N4FAyi'] = False # (N/m); ;
Morison['M8N5FAyi'] = False # (N/m); ;
Morison['M8N6FAyi'] = False # (N/m); ;
Morison['M8N7FAyi'] = False # (N/m); ;
Morison['M8N8FAyi'] = False # (N/m); ;
Morison['M8N9FAyi'] = False # (N/m); ;
Morison['M9N1FAyi'] = False # (N/m); ;
Morison['M9N2FAyi'] = False # (N/m); ;
Morison['M9N3FAyi'] = False # (N/m); ;
Morison['M9N4FAyi'] = False # (N/m); ;
Morison['M9N5FAyi'] = False # (N/m); ;
Morison['M9N6FAyi'] = False # (N/m); ;
Morison['M9N7FAyi'] = False # (N/m); ;
Morison['M9N8FAyi'] = False # (N/m); ;
Morison['M9N9FAyi'] = False # (N/m); ;
Morison['M1N1FAzi'] = False # (N/m); z-component of the combined distributed added mass force, expressed in the inertial coordinate system;
Morison['M1N2FAzi'] = False # (N/m); ;
Morison['M1N3FAzi'] = False # (N/m); ;
Morison['M1N4FAzi'] = False # (N/m); ;
Morison['M1N5FAzi'] = False # (N/m); ;
Morison['M1N6FAzi'] = False # (N/m); ;
Morison['M1N7FAzi'] = False # (N/m); ;
Morison['M1N8FAzi'] = False # (N/m); ;
Morison['M1N9FAzi'] = False # (N/m); ;
Morison['M2N1FAzi'] = False # (N/m); ;
Morison['M2N2FAzi'] = False # (N/m); ;
Morison['M2N3FAzi'] = False # (N/m); ;
Morison['M2N4FAzi'] = False # (N/m); ;
Morison['M2N5FAzi'] = False # (N/m); ;
Morison['M2N6FAzi'] = False # (N/m); ;
Morison['M2N7FAzi'] = False # (N/m); ;
Morison['M2N8FAzi'] = False # (N/m); ;
Morison['M2N9FAzi'] = False # (N/m); ;
Morison['M3N1FAzi'] = False # (N/m); ;
Morison['M3N2FAzi'] = False # (N/m); ;
Morison['M3N3FAzi'] = False # (N/m); ;
Morison['M3N4FAzi'] = False # (N/m); ;
Morison['M3N5FAzi'] = False # (N/m); ;
Morison['M3N6FAzi'] = False # (N/m); ;
Morison['M3N7FAzi'] = False # (N/m); ;
Morison['M3N8FAzi'] = False # (N/m); ;
Morison['M3N9FAzi'] = False # (N/m); ;
Morison['M4N1FAzi'] = False # (N/m); ;
Morison['M4N2FAzi'] = False # (N/m); ;
Morison['M4N3FAzi'] = False # (N/m); ;
Morison['M4N4FAzi'] = False # (N/m); ;
Morison['M4N5FAzi'] = False # (N/m); ;
Morison['M4N6FAzi'] = False # (N/m); ;
Morison['M4N7FAzi'] = False # (N/m); ;
Morison['M4N8FAzi'] = False # (N/m); ;
Morison['M4N9FAzi'] = False # (N/m); ;
Morison['M5N1FAzi'] = False # (N/m); ;
Morison['M5N2FAzi'] = False # (N/m); ;
Morison['M5N3FAzi'] = False # (N/m); ;
Morison['M5N4FAzi'] = False # (N/m); ;
Morison['M5N5FAzi'] = False # (N/m); ;
Morison['M5N6FAzi'] = False # (N/m); ;
Morison['M5N7FAzi'] = False # (N/m); ;
Morison['M5N8FAzi'] = False # (N/m); ;
Morison['M5N9FAzi'] = False # (N/m); ;
Morison['M6N1FAzi'] = False # (N/m); ;
Morison['M6N2FAzi'] = False # (N/m); ;
Morison['M6N3FAzi'] = False # (N/m); ;
Morison['M6N4FAzi'] = False # (N/m); ;
Morison['M6N5FAzi'] = False # (N/m); ;
Morison['M6N6FAzi'] = False # (N/m); ;
Morison['M6N7FAzi'] = False # (N/m); ;
Morison['M6N8FAzi'] = False # (N/m); ;
Morison['M6N9FAzi'] = False # (N/m); ;
Morison['M7N1FAzi'] = False # (N/m); ;
Morison['M7N2FAzi'] = False # (N/m); ;
Morison['M7N3FAzi'] = False # (N/m); ;
Morison['M7N4FAzi'] = False # (N/m); ;
Morison['M7N5FAzi'] = False # (N/m); ;
Morison['M7N6FAzi'] = False # (N/m); ;
Morison['M7N7FAzi'] = False # (N/m); ;
Morison['M7N8FAzi'] = False # (N/m); ;
Morison['M7N9FAzi'] = False # (N/m); ;
Morison['M8N1FAzi'] = False # (N/m); ;
Morison['M8N2FAzi'] = False # (N/m); ;
Morison['M8N3FAzi'] = False # (N/m); ;
Morison['M8N4FAzi'] = False # (N/m); ;
Morison['M8N5FAzi'] = False # (N/m); ;
Morison['M8N6FAzi'] = False # (N/m); ;
Morison['M8N7FAzi'] = False # (N/m); ;
Morison['M8N8FAzi'] = False # (N/m); ;
Morison['M8N9FAzi'] = False # (N/m); ;
Morison['M9N1FAzi'] = False # (N/m); ;
Morison['M9N2FAzi'] = False # (N/m); ;
Morison['M9N3FAzi'] = False # (N/m); ;
Morison['M9N4FAzi'] = False # (N/m); ;
Morison['M9N5FAzi'] = False # (N/m); ;
Morison['M9N6FAzi'] = False # (N/m); ;
Morison['M9N7FAzi'] = False # (N/m); ;
Morison['M9N8FAzi'] = False # (N/m); ;
Morison['M9N9FAzi'] = False # (N/m); ;
# Joint-level Wave Kinematics
Morison['J1Vxi'] = False # (m/s); fluid velocity at the joint;
Morison['J2Vxi'] = False # (m/s); ;
Morison['J3Vxi'] = False # (m/s); ;
Morison['J4Vxi'] = False # (m/s); ;
Morison['J5Vxi'] = False # (m/s); ;
Morison['J6Vxi'] = False # (m/s); ;
Morison['J7Vxi'] = False # (m/s); ;
Morison['J8Vxi'] = False # (m/s); ;
Morison['J9Vxi'] = False # (m/s); ;
Morison['J1Vyi'] = False # (m/s); ;
Morison['J2Vyi'] = False # (m/s); ;
Morison['J3Vyi'] = False # (m/s); ;
Morison['J4Vyi'] = False # (m/s); ;
Morison['J5Vyi'] = False # (m/s); ;
Morison['J6Vyi'] = False # (m/s); ;
Morison['J7Vyi'] = False # (m/s); ;
Morison['J8Vyi'] = False # (m/s); ;
Morison['J9Vyi'] = False # (m/s); ;
Morison['J1Vzi'] = False # (m/s); ;
Morison['J2Vzi'] = False # (m/s); ;
Morison['J3Vzi'] = False # (m/s); ;
Morison['J4Vzi'] = False # (m/s); ;
Morison['J5Vzi'] = False # (m/s); ;
Morison['J6Vzi'] = False # (m/s); ;
Morison['J7Vzi'] = False # (m/s); ;
Morison['J8Vzi'] = False # (m/s); ;
Morison['J9Vzi'] = False # (m/s); ;
Morison['J1Axi'] = False # (m/s^2); fluid acceleration at the joint;
Morison['J2Axi'] = False # (m/s^2); ;
Morison['J3Axi'] = False # (m/s^2); ;
Morison['J4Axi'] = False # (m/s^2); ;
Morison['J5Axi'] = False # (m/s^2); ;
Morison['J6Axi'] = False # (m/s^2); ;
Morison['J7Axi'] = False # (m/s^2); ;
Morison['J8Axi'] = False # (m/s^2); ;
Morison['J9Axi'] = False # (m/s^2); ;
Morison['J1Ayi'] = False # (m/s^2); ;
Morison['J2Ayi'] = False # (m/s^2); ;
Morison['J3Ayi'] = False # (m/s^2); ;
Morison['J4Ayi'] = False # (m/s^2); ;
Morison['J5Ayi'] = False # (m/s^2); ;
Morison['J6Ayi'] = False # (m/s^2); ;
Morison['J7Ayi'] = False # (m/s^2); ;
Morison['J8Ayi'] = False # (m/s^2); ;
Morison['J9Ayi'] = False # (m/s^2); ;
Morison['J1Azi'] = False # (m/s^2); ;
Morison['J2Azi'] = False # (m/s^2); ;
Morison['J3Azi'] = False # (m/s^2); ;
Morison['J4Azi'] = False # (m/s^2); ;
Morison['J5Azi'] = False # (m/s^2); ;
Morison['J6Azi'] = False # (m/s^2); ;
Morison['J7Azi'] = False # (m/s^2); ;
Morison['J8Azi'] = False # (m/s^2); ;
Morison['J9Azi'] = False # (m/s^2); ;
Morison['J1DynP'] = False # (Pa); fluid dynamic pressure at the joint;
Morison['J2DynP'] = False # (Pa); ;
Morison['J3DynP'] = False # (Pa); ;
Morison['J4DynP'] = False # (Pa); ;
Morison['J5DynP'] = False # (Pa); ;
Morison['J6DynP'] = False # (Pa); ;
Morison['J7DynP'] = False # (Pa); ;
Morison['J8DynP'] = False # (Pa); ;
Morison['J9DynP'] = False # (Pa); ;
Morison['J1STVxi'] = False # (m/s); structural translational velocity at the joint;
Morison['J2STVxi'] = False # (m/s); ;
Morison['J3STVxi'] = False # (m/s); ;
Morison['J4STVxi'] = False # (m/s); ;
Morison['J5STVxi'] = False # (m/s); ;
Morison['J6STVxi'] = False # (m/s); ;
Morison['J7STVxi'] = False # (m/s); ;
Morison['J8STVxi'] = False # (m/s); ;
Morison['J9STVxi'] = False # (m/s); ;
Morison['J1STVyi'] = False # (m/s); ;
Morison['J2STVyi'] = False # (m/s); ;
Morison['J3STVyi'] = False # (m/s); ;
Morison['J4STVyi'] = False # (m/s); ;
Morison['J5STVyi'] = False # (m/s); ;
Morison['J6STVyi'] = False # (m/s); ;
Morison['J7STVyi'] = False # (m/s); ;
Morison['J8STVyi'] = False # (m/s); ;
Morison['J9STVyi'] = False # (m/s); ;
Morison['J1STVzi'] = False # (m/s); ;
Morison['J2STVzi'] = False # (m/s); ;
Morison['J3STVzi'] = False # (m/s); ;
Morison['J4STVzi'] = False # (m/s); ;
Morison['J5STVzi'] = False # (m/s); ;
Morison['J6STVzi'] = False # (m/s); ;
Morison['J7STVzi'] = False # (m/s); ;
Morison['J8STVzi'] = False # (m/s); ;
Morison['J9STVzi'] = False # (m/s); ;
Morison['J1STAxi'] = False # (m/s^2); structural translational acceleration at the joint;
Morison['J2STAxi'] = False # (m/s^2); ;
Morison['J3STAxi'] = False # (m/s^2); ;
Morison['J4STAxi'] = False # (m/s^2); ;
Morison['J5STAxi'] = False # (m/s^2); ;
Morison['J6STAxi'] = False # (m/s^2); ;
Morison['J7STAxi'] = False # (m/s^2); ;
Morison['J8STAxi'] = False # (m/s^2); ;
Morison['J9STAxi'] = False # (m/s^2); ;
Morison['J1STAyi'] = False # (m/s^2); ;
Morison['J2STAyi'] = False # (m/s^2); ;
Morison['J3STAyi'] = False # (m/s^2); ;
Morison['J4STAyi'] = False # (m/s^2); ;
Morison['J5STAyi'] = False # (m/s^2); ;
Morison['J6STAyi'] = False # (m/s^2); ;
Morison['J7STAyi'] = False # (m/s^2); ;
Morison['J8STAyi'] = False # (m/s^2); ;
Morison['J9STAyi'] = False # (m/s^2); ;
Morison['J1STAzi'] = False # (m/s^2); ;
Morison['J2STAzi'] = False # (m/s^2); ;
Morison['J3STAzi'] = False # (m/s^2); ;
Morison['J4STAzi'] = False # (m/s^2); ;
Morison['J5STAzi'] = False # (m/s^2); ;
Morison['J6STAzi'] = False # (m/s^2); ;
Morison['J7STAzi'] = False # (m/s^2); ;
Morison['J8STAzi'] = False # (m/s^2); ;
Morison['J9STAzi'] = False # (m/s^2); ;
# Joint Loads
Morison['J1FDxi'] = False # (N); axial drag forces;
Morison['J2FDxi'] = False # (N); ;
Morison['J3FDxi'] = False # (N); ;
Morison['J4FDxi'] = False # (N); ;
Morison['J5FDxi'] = False # (N); ;
Morison['J6FDxi'] = False # (N); ;
Morison['J7FDxi'] = False # (N); ;
Morison['J8FDxi'] = False # (N); ;
Morison['J9FDxi'] = False # (N); ;
Morison['J1FDyi'] = False # (N); ;
Morison['J2FDyi'] = False # (N); ;
Morison['J3FDyi'] = False # (N); ;
Morison['J4FDyi'] = False # (N); ;
Morison['J5FDyi'] = False # (N); ;
Morison['J6FDyi'] = False # (N); ;
Morison['J7FDyi'] = False # (N); ;
Morison['J8FDyi'] = False # (N); ;
Morison['J9FDyi'] = False # (N); ;
Morison['J1FDzi'] = False # (N); ;
Morison['J2FDzi'] = False # (N); ;
Morison['J3FDzi'] = False # (N); ;
Morison['J4FDzi'] = False # (N); ;
Morison['J5FDzi'] = False # (N); ;
Morison['J6FDzi'] = False # (N); ;
Morison['J7FDzi'] = False # (N); ;
Morison['J8FDzi'] = False # (N); ;
Morison['J9FDzi'] = False # (N); ;
Morison['J1FBxi'] = False # (N); end-effect buoyancy forces;
Morison['J2FBxi'] = False # (N); ;
Morison['J3FBxi'] = False # (N); ;
Morison['J4FBxi'] = False # (N); ;
Morison['J5FBxi'] = False # (N); ;
Morison['J6FBxi'] = False # (N); ;
Morison['J7FBxi'] = False # (N); ;
Morison['J8FBxi'] = False # (N); ;
Morison['J9FBxi'] = False # (N); ;
Morison['J1FByi'] = False # (N); ;
Morison['J2FByi'] = False # (N); ;
Morison['J3FByi'] = False # (N); ;
Morison['J4FByi'] = False # (N); ;
Morison['J5FByi'] = False # (N); ;
Morison['J6FByi'] = False # (N); ;
Morison['J7FByi'] = False # (N); ;
Morison['J8FByi'] = False # (N); ;
Morison['J9FByi'] = False # (N); ;
Morison['J1FBzi'] = False # (N); ;
Morison['J2FBzi'] = False # (N); ;
Morison['J3FBzi'] = False # (N); ;
Morison['J4FBzi'] = False # (N); ;
Morison['J5FBzi'] = False # (N); ;
Morison['J6FBzi'] = False # (N); ;
Morison['J7FBzi'] = False # (N); ;
Morison['J8FBzi'] = False # (N); ;
Morison['J9FBzi'] = False # (N); ;
Morison['J1MBxi'] = False # (N-m); end-effect buoyancy moments;
Morison['J2MBxi'] = False # (N-m); ;
Morison['J3MBxi'] = False # (N-m); ;
Morison['J4MBxi'] = False # (N-m); ;
Morison['J5MBxi'] = False # (N-m); ;
Morison['J6MBxi'] = False # (N-m); ;
Morison['J7MBxi'] = False # (N-m); ;
Morison['J8MBxi'] = False # (N-m); ;
Morison['J9MBxi'] = False # (N-m); ;
Morison['J1MByi'] = False # (N-m); ;
Morison['J2MByi'] = False # (N-m); ;
Morison['J3MByi'] = False # (N-m); ;
Morison['J4MByi'] = False # (N-m); ;
Morison['J5MByi'] = False # (N-m); ;
Morison['J6MByi'] = False # (N-m); ;
Morison['J7MByi'] = False # (N-m); ;
Morison['J8MByi'] = False # (N-m); ;
Morison['J9MByi'] = False # (N-m); ;
Morison['J1MBzi'] = False # (N-m); ;
Morison['J2MBzi'] = False # (N-m); ;
Morison['J3MBzi'] = False # (N-m); ;
Morison['J4MBzi'] = False # (N-m); ;
Morison['J5MBzi'] = False # (N-m); ;
Morison['J6MBzi'] = False # (N-m); ;
Morison['J7MBzi'] = False # (N-m); ;
Morison['J8MBzi'] = False # (N-m); ;
Morison['J9MBzi'] = False # (N-m); ;
Morison['J1FBFxi'] = False # (N); end-effect buoyancy forces due to ballasting/flooding;
Morison['J2FBFxi'] = False # (N); ;
Morison['J3FBFxi'] = False # (N); ;
Morison['J4FBFxi'] = False # (N); ;
Morison['J5FBFxi'] = False # (N); ;
Morison['J6FBFxi'] = False # (N); ;
Morison['J7FBFxi'] = False # (N); ;
Morison['J8FBFxi'] = False # (N); ;
Morison['J9FBFxi'] = False # (N); ;
Morison['J1FBFyi'] = False # (N); ;
Morison['J2FBFyi'] = False # (N); ;
Morison['J3FBFyi'] = False # (N); ;
Morison['J4FBFyi'] = False # (N); ;
Morison['J5FBFyi'] = False # (N); ;
Morison['J6FBFyi'] = False # (N); ;
Morison['J7FBFyi'] = False # (N); ;
Morison['J8FBFyi'] = False # (N); ;
Morison['J9FBFyi'] = False # (N); ;
Morison['J1FBFzi'] = False # (N); ;
Morison['J2FBFzi'] = False # (N); ;
Morison['J3FBFzi'] = False # (N); ;
Morison['J4FBFzi'] = False # (N); ;
Morison['J5FBFzi'] = False # (N); ;
Morison['J6FBFzi'] = False # (N); ;
Morison['J7FBFzi'] = False # (N); ;
Morison['J8FBFzi'] = False # (N); ;
Morison['J9FBFzi'] = False # (N); ;
Morison['J1MBFxi'] = False # (N-m); end-effect buoyancy moments due to ballasting/flooding;
Morison['J2MBFxi'] = False # (N-m); ;
Morison['J3MBFxi'] = False # (N-m); ;
Morison['J4MBFxi'] = False # (N-m); ;
Morison['J5MBFxi'] = False # (N-m); ;
Morison['J6MBFxi'] = False # (N-m); ;
Morison['J7MBFxi'] = False # (N-m); ;
Morison['J8MBFxi'] = False # (N-m); ;
Morison['J9MBFxi'] = False # (N-m); ;
Morison['J1MBFyi'] = False # (N-m); ;
Morison['J2MBFyi'] = False # (N-m); ;
Morison['J3MBFyi'] = False # (N-m); ;
Morison['J4MBFyi'] = False # (N-m); ;
Morison['J5MBFyi'] = False # (N-m); ;
Morison['J6MBFyi'] = False # (N-m); ;
Morison['J7MBFyi'] = False # (N-m); ;
Morison['J8MBFyi'] = False # (N-m); ;
Morison['J9MBFyi'] = False # (N-m); ;
Morison['J1MBFzi'] = False # (N-m); ;
Morison['J2MBFzi'] = False # (N-m); ;
Morison['J3MBFzi'] = False # (N-m); ;
Morison['J4MBFzi'] = False # (N-m); ;
Morison['J5MBFzi'] = False # (N-m); ;
Morison['J6MBFzi'] = False # (N-m); ;
Morison['J7MBFzi'] = False # (N-m); ;
Morison['J8MBFzi'] = False # (N-m); ;
Morison['J9MBFzi'] = False # (N-m); ;
Morison['J1FIxi'] = False # (N); end-effect inertial forces ;
Morison['J2FIxi'] = False # (N); ;
Morison['J3FIxi'] = False # (N); ;
Morison['J4FIxi'] = False # (N); ;
Morison['J5FIxi'] = False # (N); ;
Morison['J6FIxi'] = False # (N); ;
Morison['J7FIxi'] = False # (N); ;
Morison['J8FIxi'] = False # (N); ;
Morison['J9FIxi'] = False # (N); ;
Morison['J1FIyi'] = False # (N); ;
Morison['J2FIyi'] = False # (N); ;
Morison['J3FIyi'] = False # (N); ;
Morison['J4FIyi'] = False # (N); ;
Morison['J5FIyi'] = False # (N); ;
Morison['J6FIyi'] = False # (N); ;
Morison['J7FIyi'] = False # (N); ;
Morison['J8FIyi'] = False # (N); ;
Morison['J9FIyi'] = False # (N); ;
Morison['J1FIzi'] = False # (N); ;
Morison['J2FIzi'] = False # (N); ;
Morison['J3FIzi'] = False # (N); ;
Morison['J4FIzi'] = False # (N); ;
Morison['J5FIzi'] = False # (N); ;
Morison['J6FIzi'] = False # (N); ;
Morison['J7FIzi'] = False # (N); ;
Morison['J8FIzi'] = False # (N); ;
Morison['J9FIzi'] = False # (N); ;
Morison['J1FAMxi'] = False # (N); added mass forces;
Morison['J2FAMxi'] = False # (N); ;
Morison['J3FAMxi'] = False # (N); ;
Morison['J4FAMxi'] = False # (N); ;
Morison['J5FAMxi'] = False # (N); ;
Morison['J6FAMxi'] = False # (N); ;
Morison['J7FAMxi'] = False # (N); ;
Morison['J8FAMxi'] = False # (N); ;
Morison['J9FAMxi'] = False # (N); ;
Morison['J1FAMyi'] = False # (N); ;
Morison['J2FAMyi'] = False # (N); ;
Morison['J3FAMyi'] = False # (N); ;
Morison['J4FAMyi'] = False # (N); ;
Morison['J5FAMyi'] = False # (N); ;
Morison['J6FAMyi'] = False # (N); ;
Morison['J7FAMyi'] = False # (N); ;
Morison['J8FAMyi'] = False # (N); ;
Morison['J9FAMyi'] = False # (N); ;
Morison['J1FAMzi'] = False # (N); ;
Morison['J2FAMzi'] = False # (N); ;
Morison['J3FAMzi'] = False # (N); ;
Morison['J4FAMzi'] = False # (N); ;
Morison['J5FAMzi'] = False # (N); ;
Morison['J6FAMzi'] = False # (N); ;
Morison['J7FAMzi'] = False # (N); ;
Morison['J8FAMzi'] = False # (N); ;
Morison['J9FAMzi'] = False # (N); ;
""" SubDyn """
SubDyn = {}
# Member Forces
SubDyn['M1N1FKxe'] = False # (N); xe component of the shear at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2FKxe'] = False # (N); ;
SubDyn['M1N3FKxe'] = False # (N); ;
SubDyn['M1N4FKxe'] = False # (N); ;
SubDyn['M1N5FKxe'] = False # (N); ;
SubDyn['M1N6FKxe'] = False # (N); ;
SubDyn['M1N7FKxe'] = False # (N); ;
SubDyn['M1N8FKxe'] = False # (N); ;
SubDyn['M1N9FKxe'] = False # (N); ;
SubDyn['M2N1FKxe'] = False # (N); ;
SubDyn['M2N2FKxe'] = False # (N); ;
SubDyn['M2N3FKxe'] = False # (N); ;
SubDyn['M2N4FKxe'] = False # (N); ;
SubDyn['M2N5FKxe'] = False # (N); ;
SubDyn['M2N6FKxe'] = False # (N); ;
SubDyn['M2N7FKxe'] = False # (N); ;
SubDyn['M2N8FKxe'] = False # (N); ;
SubDyn['M2N9FKxe'] = False # (N); ;
SubDyn['M3N1FKxe'] = False # (N); ;
SubDyn['M3N2FKxe'] = False # (N); ;
SubDyn['M3N3FKxe'] = False # (N); ;
SubDyn['M3N4FKxe'] = False # (N); ;
SubDyn['M3N5FKxe'] = False # (N); ;
SubDyn['M3N6FKxe'] = False # (N); ;
SubDyn['M3N7FKxe'] = False # (N); ;
SubDyn['M3N8FKxe'] = False # (N); ;
SubDyn['M3N9FKxe'] = False # (N); ;
SubDyn['M4N1FKxe'] = False # (N); ;
SubDyn['M4N2FKxe'] = False # (N); ;
SubDyn['M4N3FKxe'] = False # (N); ;
SubDyn['M4N4FKxe'] = False # (N); ;
SubDyn['M4N5FKxe'] = False # (N); ;
SubDyn['M4N6FKxe'] = False # (N); ;
SubDyn['M4N7FKxe'] = False # (N); ;
SubDyn['M4N8FKxe'] = False # (N); ;
SubDyn['M4N9FKxe'] = False # (N); ;
SubDyn['M5N1FKxe'] = False # (N); ;
SubDyn['M5N2FKxe'] = False # (N); ;
SubDyn['M5N3FKxe'] = False # (N); ;
SubDyn['M5N4FKxe'] = False # (N); ;
SubDyn['M5N5FKxe'] = False # (N); ;
SubDyn['M5N6FKxe'] = False # (N); ;
SubDyn['M5N7FKxe'] = False # (N); ;
SubDyn['M5N8FKxe'] = False # (N); ;
SubDyn['M5N9FKxe'] = False # (N); ;
SubDyn['M6N1FKxe'] = False # (N); ;
SubDyn['M6N2FKxe'] = False # (N); ;
SubDyn['M6N3FKxe'] = False # (N); ;
SubDyn['M6N4FKxe'] = False # (N); ;
SubDyn['M6N5FKxe'] = False # (N); ;
SubDyn['M6N6FKxe'] = False # (N); ;
SubDyn['M6N7FKxe'] = False # (N); ;
SubDyn['M6N8FKxe'] = False # (N); ;
SubDyn['M6N9FKxe'] = False # (N); ;
SubDyn['M7N1FKxe'] = False # (N); ;
SubDyn['M7N2FKxe'] = False # (N); ;
SubDyn['M7N3FKxe'] = False # (N); ;
SubDyn['M7N4FKxe'] = False # (N); ;
SubDyn['M7N5FKxe'] = False # (N); ;
SubDyn['M7N6FKxe'] = False # (N); ;
SubDyn['M7N7FKxe'] = False # (N); ;
SubDyn['M7N8FKxe'] = False # (N); ;
SubDyn['M7N9FKxe'] = False # (N); ;
SubDyn['M8N1FKxe'] = False # (N); ;
SubDyn['M8N2FKxe'] = False # (N); ;
SubDyn['M8N3FKxe'] = False # (N); ;
SubDyn['M8N4FKxe'] = False # (N); ;
SubDyn['M8N5FKxe'] = False # (N); ;
SubDyn['M8N6FKxe'] = False # (N); ;
SubDyn['M8N7FKxe'] = False # (N); ;
SubDyn['M8N8FKxe'] = False # (N); ;
SubDyn['M8N9FKxe'] = False # (N); ;
SubDyn['M9N1FKxe'] = False # (N); ;
SubDyn['M9N2FKxe'] = False # (N); ;
SubDyn['M9N3FKxe'] = False # (N); ;
SubDyn['M9N4FKxe'] = False # (N); ;
SubDyn['M9N5FKxe'] = False # (N); ;
SubDyn['M9N6FKxe'] = False # (N); ;
SubDyn['M9N7FKxe'] = False # (N); ;
SubDyn['M9N8FKxe'] = False # (N); ;
SubDyn['M9N9FKxe'] = False # (N); ;
SubDyn['M1N1FKye'] = False # (N); ye component of the shear at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2FKye'] = False # (N); ;
SubDyn['M1N3FKye'] = False # (N); ;
SubDyn['M1N4FKye'] = False # (N); ;
SubDyn['M1N5FKye'] = False # (N); ;
SubDyn['M1N6FKye'] = False # (N); ;
SubDyn['M1N7FKye'] = False # (N); ;
SubDyn['M1N8FKye'] = False # (N); ;
SubDyn['M1N9FKye'] = False # (N); ;
SubDyn['M2N1FKye'] = False # (N); ;
SubDyn['M2N2FKye'] = False # (N); ;
SubDyn['M2N3FKye'] = False # (N); ;
SubDyn['M2N4FKye'] = False # (N); ;
SubDyn['M2N5FKye'] = False # (N); ;
SubDyn['M2N6FKye'] = False # (N); ;
SubDyn['M2N7FKye'] = False # (N); ;
SubDyn['M2N8FKye'] = False # (N); ;
SubDyn['M2N9FKye'] = False # (N); ;
SubDyn['M3N1FKye'] = False # (N); ;
SubDyn['M3N2FKye'] = False # (N); ;
SubDyn['M3N3FKye'] = False # (N); ;
SubDyn['M3N4FKye'] = False # (N); ;
SubDyn['M3N5FKye'] = False # (N); ;
SubDyn['M3N6FKye'] = False # (N); ;
SubDyn['M3N7FKye'] = False # (N); ;
SubDyn['M3N8FKye'] = False # (N); ;
SubDyn['M3N9FKye'] = False # (N); ;
SubDyn['M4N1FKye'] = False # (N); ;
SubDyn['M4N2FKye'] = False # (N); ;
SubDyn['M4N3FKye'] = False # (N); ;
SubDyn['M4N4FKye'] = False # (N); ;
SubDyn['M4N5FKye'] = False # (N); ;
SubDyn['M4N6FKye'] = False # (N); ;
SubDyn['M4N7FKye'] = False # (N); ;
SubDyn['M4N8FKye'] = False # (N); ;
SubDyn['M4N9FKye'] = False # (N); ;
SubDyn['M5N1FKye'] = False # (N); ;
SubDyn['M5N2FKye'] = False # (N); ;
SubDyn['M5N3FKye'] = False # (N); ;
SubDyn['M5N4FKye'] = False # (N); ;
SubDyn['M5N5FKye'] = False # (N); ;
SubDyn['M5N6FKye'] = False # (N); ;
SubDyn['M5N7FKye'] = False # (N); ;
SubDyn['M5N8FKye'] = False # (N); ;
SubDyn['M5N9FKye'] = False # (N); ;
SubDyn['M6N1FKye'] = False # (N); ;
SubDyn['M6N2FKye'] = False # (N); ;
SubDyn['M6N3FKye'] = False # (N); ;
SubDyn['M6N4FKye'] = False # (N); ;
SubDyn['M6N5FKye'] = False # (N); ;
SubDyn['M6N6FKye'] = False # (N); ;
SubDyn['M6N7FKye'] = False # (N); ;
SubDyn['M6N8FKye'] = False # (N); ;
SubDyn['M6N9FKye'] = False # (N); ;
SubDyn['M7N1FKye'] = False # (N); ;
SubDyn['M7N2FKye'] = False # (N); ;
SubDyn['M7N3FKye'] = False # (N); ;
SubDyn['M7N4FKye'] = False # (N); ;
SubDyn['M7N5FKye'] = False # (N); ;
SubDyn['M7N6FKye'] = False # (N); ;
SubDyn['M7N7FKye'] = False # (N); ;
SubDyn['M7N8FKye'] = False # (N); ;
SubDyn['M7N9FKye'] = False # (N); ;
SubDyn['M8N1FKye'] = False # (N); ;
SubDyn['M8N2FKye'] = False # (N); ;
SubDyn['M8N3FKye'] = False # (N); ;
SubDyn['M8N4FKye'] = False # (N); ;
SubDyn['M8N5FKye'] = False # (N); ;
SubDyn['M8N6FKye'] = False # (N); ;
SubDyn['M8N7FKye'] = False # (N); ;
SubDyn['M8N8FKye'] = False # (N); ;
SubDyn['M8N9FKye'] = False # (N); ;
SubDyn['M9N1FKye'] = False # (N); ;
SubDyn['M9N2FKye'] = False # (N); ;
SubDyn['M9N3FKye'] = False # (N); ;
SubDyn['M9N4FKye'] = False # (N); ;
SubDyn['M9N5FKye'] = False # (N); ;
SubDyn['M9N6FKye'] = False # (N); ;
SubDyn['M9N7FKye'] = False # (N); ;
SubDyn['M9N8FKye'] = False # (N); ;
SubDyn['M9N9FKye'] = False # (N); ;
SubDyn['M1N1FKze'] = False # (N); Axial Force at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2FKze'] = False # (N); ;
SubDyn['M1N3FKze'] = False # (N); ;
SubDyn['M1N4FKze'] = False # (N); ;
SubDyn['M1N5FKze'] = False # (N); ;
SubDyn['M1N6FKze'] = False # (N); ;
SubDyn['M1N7FKze'] = False # (N); ;
SubDyn['M1N8FKze'] = False # (N); ;
SubDyn['M1N9FKze'] = False # (N); ;
SubDyn['M2N1FKze'] = False # (N); ;
SubDyn['M2N2FKze'] = False # (N); ;
SubDyn['M2N3FKze'] = False # (N); ;
SubDyn['M2N4FKze'] = False # (N); ;
SubDyn['M2N5FKze'] = False # (N); ;
SubDyn['M2N6FKze'] = False # (N); ;
SubDyn['M2N7FKze'] = False # (N); ;
SubDyn['M2N8FKze'] = False # (N); ;
SubDyn['M2N9FKze'] = False # (N); ;
SubDyn['M3N1FKze'] = False # (N); ;
SubDyn['M3N2FKze'] = False # (N); ;
SubDyn['M3N3FKze'] = False # (N); ;
SubDyn['M3N4FKze'] = False # (N); ;
SubDyn['M3N5FKze'] = False # (N); ;
SubDyn['M3N6FKze'] = False # (N); ;
SubDyn['M3N7FKze'] = False # (N); ;
SubDyn['M3N8FKze'] = False # (N); ;
SubDyn['M3N9FKze'] = False # (N); ;
SubDyn['M4N1FKze'] = False # (N); ;
SubDyn['M4N2FKze'] = False # (N); ;
SubDyn['M4N3FKze'] = False # (N); ;
SubDyn['M4N4FKze'] = False # (N); ;
SubDyn['M4N5FKze'] = False # (N); ;
SubDyn['M4N6FKze'] = False # (N); ;
SubDyn['M4N7FKze'] = False # (N); ;
SubDyn['M4N8FKze'] = False # (N); ;
SubDyn['M4N9FKze'] = False # (N); ;
SubDyn['M5N1FKze'] = False # (N); ;
SubDyn['M5N2FKze'] = False # (N); ;
SubDyn['M5N3FKze'] = False # (N); ;
SubDyn['M5N4FKze'] = False # (N); ;
SubDyn['M5N5FKze'] = False # (N); ;
SubDyn['M5N6FKze'] = False # (N); ;
SubDyn['M5N7FKze'] = False # (N); ;
SubDyn['M5N8FKze'] = False # (N); ;
SubDyn['M5N9FKze'] = False # (N); ;
SubDyn['M6N1FKze'] = False # (N); ;
SubDyn['M6N2FKze'] = False # (N); ;
SubDyn['M6N3FKze'] = False # (N); ;
SubDyn['M6N4FKze'] = False # (N); ;
SubDyn['M6N5FKze'] = False # (N); ;
SubDyn['M6N6FKze'] = False # (N); ;
SubDyn['M6N7FKze'] = False # (N); ;
SubDyn['M6N8FKze'] = False # (N); ;
SubDyn['M6N9FKze'] = False # (N); ;
SubDyn['M7N1FKze'] = False # (N); ;
SubDyn['M7N2FKze'] = False # (N); ;
SubDyn['M7N3FKze'] = False # (N); ;
SubDyn['M7N4FKze'] = False # (N); ;
SubDyn['M7N5FKze'] = False # (N); ;
SubDyn['M7N6FKze'] = False # (N); ;
SubDyn['M7N7FKze'] = False # (N); ;
SubDyn['M7N8FKze'] = False # (N); ;
SubDyn['M7N9FKze'] = False # (N); ;
SubDyn['M8N1FKze'] = False # (N); ;
SubDyn['M8N2FKze'] = False # (N); ;
SubDyn['M8N3FKze'] = False # (N); ;
SubDyn['M8N4FKze'] = False # (N); ;
SubDyn['M8N5FKze'] = False # (N); ;
SubDyn['M8N6FKze'] = False # (N); ;
SubDyn['M8N7FKze'] = False # (N); ;
SubDyn['M8N8FKze'] = False # (N); ;
SubDyn['M8N9FKze'] = False # (N); ;
SubDyn['M9N1FKze'] = False # (N); ;
SubDyn['M9N2FKze'] = False # (N); ;
SubDyn['M9N3FKze'] = False # (N); ;
SubDyn['M9N4FKze'] = False # (N); ;
SubDyn['M9N5FKze'] = False # (N); ;
SubDyn['M9N6FKze'] = False # (N); ;
SubDyn['M9N7FKze'] = False # (N); ;
SubDyn['M9N8FKze'] = False # (N); ;
SubDyn['M9N9FKze'] = False # (N); ;
SubDyn['M1N1FMxe'] = False # (N); xe component of the shear at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2FMxe'] = False # (N); ;
SubDyn['M1N3FMxe'] = False # (N); ;
SubDyn['M1N4FMxe'] = False # (N); ;
SubDyn['M1N5FMxe'] = False # (N); ;
SubDyn['M1N6FMxe'] = False # (N); ;
SubDyn['M1N7FMxe'] = False # (N); ;
SubDyn['M1N8FMxe'] = False # (N); ;
SubDyn['M1N9FMxe'] = False # (N); ;
SubDyn['M2N1FMxe'] = False # (N); ;
SubDyn['M2N2FMxe'] = False # (N); ;
SubDyn['M2N3FMxe'] = False # (N); ;
SubDyn['M2N4FMxe'] = False # (N); ;
SubDyn['M2N5FMxe'] = False # (N); ;
SubDyn['M2N6FMxe'] = False # (N); ;
SubDyn['M2N7FMxe'] = False # (N); ;
SubDyn['M2N8FMxe'] = False # (N); ;
SubDyn['M2N9FMxe'] = False # (N); ;
SubDyn['M3N1FMxe'] = False # (N); ;
SubDyn['M3N2FMxe'] = False # (N); ;
SubDyn['M3N3FMxe'] = False # (N); ;
SubDyn['M3N4FMxe'] = False # (N); ;
SubDyn['M3N5FMxe'] = False # (N); ;
SubDyn['M3N6FMxe'] = False # (N); ;
SubDyn['M3N7FMxe'] = False # (N); ;
SubDyn['M3N8FMxe'] = False # (N); ;
SubDyn['M3N9FMxe'] = False # (N); ;
SubDyn['M4N1FMxe'] = False # (N); ;
SubDyn['M4N2FMxe'] = False # (N); ;
SubDyn['M4N3FMxe'] = False # (N); ;
SubDyn['M4N4FMxe'] = False # (N); ;
SubDyn['M4N5FMxe'] = False # (N); ;
SubDyn['M4N6FMxe'] = False # (N); ;
SubDyn['M4N7FMxe'] = False # (N); ;
SubDyn['M4N8FMxe'] = False # (N); ;
SubDyn['M4N9FMxe'] = False # (N); ;
SubDyn['M5N1FMxe'] = False # (N); ;
SubDyn['M5N2FMxe'] = False # (N); ;
SubDyn['M5N3FMxe'] = False # (N); ;
SubDyn['M5N4FMxe'] = False # (N); ;
SubDyn['M5N5FMxe'] = False # (N); ;
SubDyn['M5N6FMxe'] = False # (N); ;
SubDyn['M5N7FMxe'] = False # (N); ;
SubDyn['M5N8FMxe'] = False # (N); ;
SubDyn['M5N9FMxe'] = False # (N); ;
SubDyn['M6N1FMxe'] = False # (N); ;
SubDyn['M6N2FMxe'] = False # (N); ;
SubDyn['M6N3FMxe'] = False # (N); ;
SubDyn['M6N4FMxe'] = False # (N); ;
SubDyn['M6N5FMxe'] = False # (N); ;
SubDyn['M6N6FMxe'] = False # (N); ;
SubDyn['M6N7FMxe'] = False # (N); ;
SubDyn['M6N8FMxe'] = False # (N); ;
SubDyn['M6N9FMxe'] = False # (N); ;
SubDyn['M7N1FMxe'] = False # (N); ;
SubDyn['M7N2FMxe'] = False # (N); ;
SubDyn['M7N3FMxe'] = False # (N); ;
SubDyn['M7N4FMxe'] = False # (N); ;
SubDyn['M7N5FMxe'] = False # (N); ;
SubDyn['M7N6FMxe'] = False # (N); ;
SubDyn['M7N7FMxe'] = False # (N); ;
SubDyn['M7N8FMxe'] = False # (N); ;
SubDyn['M7N9FMxe'] = False # (N); ;
SubDyn['M8N1FMxe'] = False # (N); ;
SubDyn['M8N2FMxe'] = False # (N); ;
SubDyn['M8N3FMxe'] = False # (N); ;
SubDyn['M8N4FMxe'] = False # (N); ;
SubDyn['M8N5FMxe'] = False # (N); ;
SubDyn['M8N6FMxe'] = False # (N); ;
SubDyn['M8N7FMxe'] = False # (N); ;
SubDyn['M8N8FMxe'] = False # (N); ;
SubDyn['M8N9FMxe'] = False # (N); ;
SubDyn['M9N1FMxe'] = False # (N); ;
SubDyn['M9N2FMxe'] = False # (N); ;
SubDyn['M9N3FMxe'] = False # (N); ;
SubDyn['M9N4FMxe'] = False # (N); ;
SubDyn['M9N5FMxe'] = False # (N); ;
SubDyn['M9N6FMxe'] = False # (N); ;
SubDyn['M9N7FMxe'] = False # (N); ;
SubDyn['M9N8FMxe'] = False # (N); ;
SubDyn['M9N9FMxe'] = False # (N); ;
SubDyn['M1N1FMye'] = False # (N); ye component of the shear at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2FMye'] = False # (N); ;
SubDyn['M1N3FMye'] = False # (N); ;
SubDyn['M1N4FMye'] = False # (N); ;
SubDyn['M1N5FMye'] = False # (N); ;
SubDyn['M1N6FMye'] = False # (N); ;
SubDyn['M1N7FMye'] = False # (N); ;
SubDyn['M1N8FMye'] = False # (N); ;
SubDyn['M1N9FMye'] = False # (N); ;
SubDyn['M2N1FMye'] = False # (N); ;
SubDyn['M2N2FMye'] = False # (N); ;
SubDyn['M2N3FMye'] = False # (N); ;
SubDyn['M2N4FMye'] = False # (N); ;
SubDyn['M2N5FMye'] = False # (N); ;
SubDyn['M2N6FMye'] = False # (N); ;
SubDyn['M2N7FMye'] = False # (N); ;
SubDyn['M2N8FMye'] = False # (N); ;
SubDyn['M2N9FMye'] = False # (N); ;
SubDyn['M3N1FMye'] = False # (N); ;
SubDyn['M3N2FMye'] = False # (N); ;
SubDyn['M3N3FMye'] = False # (N); ;
SubDyn['M3N4FMye'] = False # (N); ;
SubDyn['M3N5FMye'] = False # (N); ;
SubDyn['M3N6FMye'] = False # (N); ;
SubDyn['M3N7FMye'] = False # (N); ;
SubDyn['M3N8FMye'] = False # (N); ;
SubDyn['M3N9FMye'] = False # (N); ;
SubDyn['M4N1FMye'] = False # (N); ;
SubDyn['M4N2FMye'] = False # (N); ;
SubDyn['M4N3FMye'] = False # (N); ;
SubDyn['M4N4FMye'] = False # (N); ;
SubDyn['M4N5FMye'] = False # (N); ;
SubDyn['M4N6FMye'] = False # (N); ;
SubDyn['M4N7FMye'] = False # (N); ;
SubDyn['M4N8FMye'] = False # (N); ;
SubDyn['M4N9FMye'] = False # (N); ;
SubDyn['M5N1FMye'] = False # (N); ;
SubDyn['M5N2FMye'] = False # (N); ;
SubDyn['M5N3FMye'] = False # (N); ;
SubDyn['M5N4FMye'] = False # (N); ;
SubDyn['M5N5FMye'] = False # (N); ;
SubDyn['M5N6FMye'] = False # (N); ;
SubDyn['M5N7FMye'] = False # (N); ;
SubDyn['M5N8FMye'] = False # (N); ;
SubDyn['M5N9FMye'] = False # (N); ;
SubDyn['M6N1FMye'] = False # (N); ;
SubDyn['M6N2FMye'] = False # (N); ;
SubDyn['M6N3FMye'] = False # (N); ;
SubDyn['M6N4FMye'] = False # (N); ;
SubDyn['M6N5FMye'] = False # (N); ;
SubDyn['M6N6FMye'] = False # (N); ;
SubDyn['M6N7FMye'] = False # (N); ;
SubDyn['M6N8FMye'] = False # (N); ;
SubDyn['M6N9FMye'] = False # (N); ;
SubDyn['M7N1FMye'] = False # (N); ;
SubDyn['M7N2FMye'] = False # (N); ;
SubDyn['M7N3FMye'] = False # (N); ;
SubDyn['M7N4FMye'] = False # (N); ;
SubDyn['M7N5FMye'] = False # (N); ;
SubDyn['M7N6FMye'] = False # (N); ;
SubDyn['M7N7FMye'] = False # (N); ;
SubDyn['M7N8FMye'] = False # (N); ;
SubDyn['M7N9FMye'] = False # (N); ;
SubDyn['M8N1FMye'] = False # (N); ;
SubDyn['M8N2FMye'] = False # (N); ;
SubDyn['M8N3FMye'] = False # (N); ;
SubDyn['M8N4FMye'] = False # (N); ;
SubDyn['M8N5FMye'] = False # (N); ;
SubDyn['M8N6FMye'] = False # (N); ;
SubDyn['M8N7FMye'] = False # (N); ;
SubDyn['M8N8FMye'] = False # (N); ;
SubDyn['M8N9FMye'] = False # (N); ;
SubDyn['M9N1FMye'] = False # (N); ;
SubDyn['M9N2FMye'] = False # (N); ;
SubDyn['M9N3FMye'] = False # (N); ;
SubDyn['M9N4FMye'] = False # (N); ;
SubDyn['M9N5FMye'] = False # (N); ;
SubDyn['M9N6FMye'] = False # (N); ;
SubDyn['M9N7FMye'] = False # (N); ;
SubDyn['M9N8FMye'] = False # (N); ;
SubDyn['M9N9FMye'] = False # (N); ;
SubDyn['M1N1FMze'] = False # (N); axial force at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2FMze'] = False # (N); ;
SubDyn['M1N3FMze'] = False # (N); ;
SubDyn['M1N4FMze'] = False # (N); ;
SubDyn['M1N5FMze'] = False # (N); ;
SubDyn['M1N6FMze'] = False # (N); ;
SubDyn['M1N7FMze'] = False # (N); ;
SubDyn['M1N8FMze'] = False # (N); ;
SubDyn['M1N9FMze'] = False # (N); ;
SubDyn['M2N1FMze'] = False # (N); ;
SubDyn['M2N2FMze'] = False # (N); ;
SubDyn['M2N3FMze'] = False # (N); ;
SubDyn['M2N4FMze'] = False # (N); ;
SubDyn['M2N5FMze'] = False # (N); ;
SubDyn['M2N6FMze'] = False # (N); ;
SubDyn['M2N7FMze'] = False # (N); ;
SubDyn['M2N8FMze'] = False # (N); ;
SubDyn['M2N9FMze'] = False # (N); ;
SubDyn['M3N1FMze'] = False # (N); ;
SubDyn['M3N2FMze'] = False # (N); ;
SubDyn['M3N3FMze'] = False # (N); ;
SubDyn['M3N4FMze'] = False # (N); ;
SubDyn['M3N5FMze'] = False # (N); ;
SubDyn['M3N6FMze'] = False # (N); ;
SubDyn['M3N7FMze'] = False # (N); ;
SubDyn['M3N8FMze'] = False # (N); ;
SubDyn['M3N9FMze'] = False # (N); ;
SubDyn['M4N1FMze'] = False # (N); ;
SubDyn['M4N2FMze'] = False # (N); ;
SubDyn['M4N3FMze'] = False # (N); ;
SubDyn['M4N4FMze'] = False # (N); ;
SubDyn['M4N5FMze'] = False # (N); ;
SubDyn['M4N6FMze'] = False # (N); ;
SubDyn['M4N7FMze'] = False # (N); ;
SubDyn['M4N8FMze'] = False # (N); ;
SubDyn['M4N9FMze'] = False # (N); ;
SubDyn['M5N1FMze'] = False # (N); ;
SubDyn['M5N2FMze'] = False # (N); ;
SubDyn['M5N3FMze'] = False # (N); ;
SubDyn['M5N4FMze'] = False # (N); ;
SubDyn['M5N5FMze'] = False # (N); ;
SubDyn['M5N6FMze'] = False # (N); ;
SubDyn['M5N7FMze'] = False # (N); ;
SubDyn['M5N8FMze'] = False # (N); ;
SubDyn['M5N9FMze'] = False # (N); ;
SubDyn['M6N1FMze'] = False # (N); ;
SubDyn['M6N2FMze'] = False # (N); ;
SubDyn['M6N3FMze'] = False # (N); ;
SubDyn['M6N4FMze'] = False # (N); ;
SubDyn['M6N5FMze'] = False # (N); ;
SubDyn['M6N6FMze'] = False # (N); ;
SubDyn['M6N7FMze'] = False # (N); ;
SubDyn['M6N8FMze'] = False # (N); ;
SubDyn['M6N9FMze'] = False # (N); ;
SubDyn['M7N1FMze'] = False # (N); ;
SubDyn['M7N2FMze'] = False # (N); ;
SubDyn['M7N3FMze'] = False # (N); ;
SubDyn['M7N4FMze'] = False # (N); ;
SubDyn['M7N5FMze'] = False # (N); ;
SubDyn['M7N6FMze'] = False # (N); ;
SubDyn['M7N7FMze'] = False # (N); ;
SubDyn['M7N8FMze'] = False # (N); ;
SubDyn['M7N9FMze'] = False # (N); ;
SubDyn['M8N1FMze'] = False # (N); ;
SubDyn['M8N2FMze'] = False # (N); ;
SubDyn['M8N3FMze'] = False # (N); ;
SubDyn['M8N4FMze'] = False # (N); ;
SubDyn['M8N5FMze'] = False # (N); ;
SubDyn['M8N6FMze'] = False # (N); ;
SubDyn['M8N7FMze'] = False # (N); ;
SubDyn['M8N8FMze'] = False # (N); ;
SubDyn['M8N9FMze'] = False # (N); ;
SubDyn['M9N1FMze'] = False # (N); ;
SubDyn['M9N2FMze'] = False # (N); ;
SubDyn['M9N3FMze'] = False # (N); ;
SubDyn['M9N4FMze'] = False # (N); ;
SubDyn['M9N5FMze'] = False # (N); ;
SubDyn['M9N6FMze'] = False # (N); ;
SubDyn['M9N7FMze'] = False # (N); ;
SubDyn['M9N8FMze'] = False # (N); ;
SubDyn['M9N9FMze'] = False # (N); ;
SubDyn['M1N1MKxe'] = False # (N*m); xe component of the bending moment at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2MKxe'] = False # (N*m); ;
SubDyn['M1N3MKxe'] = False # (N*m); ;
SubDyn['M1N4MKxe'] = False # (N*m); ;
SubDyn['M1N5MKxe'] = False # (N*m); ;
SubDyn['M1N6MKxe'] = False # (N*m); ;
SubDyn['M1N7MKxe'] = False # (N*m); ;
SubDyn['M1N8MKxe'] = False # (N*m); ;
SubDyn['M1N9MKxe'] = False # (N*m); ;
SubDyn['M2N1MKxe'] = False # (N*m); ;
SubDyn['M2N2MKxe'] = False # (N*m); ;
SubDyn['M2N3MKxe'] = False # (N*m); ;
SubDyn['M2N4MKxe'] = False # (N*m); ;
SubDyn['M2N5MKxe'] = False # (N*m); ;
SubDyn['M2N6MKxe'] = False # (N*m); ;
SubDyn['M2N7MKxe'] = False # (N*m); ;
SubDyn['M2N8MKxe'] = False # (N*m); ;
SubDyn['M2N9MKxe'] = False # (N*m); ;
SubDyn['M3N1MKxe'] = False # (N*m); ;
SubDyn['M3N2MKxe'] = False # (N*m); ;
SubDyn['M3N3MKxe'] = False # (N*m); ;
SubDyn['M3N4MKxe'] = False # (N*m); ;
SubDyn['M3N5MKxe'] = False # (N*m); ;
SubDyn['M3N6MKxe'] = False # (N*m); ;
SubDyn['M3N7MKxe'] = False # (N*m); ;
SubDyn['M3N8MKxe'] = False # (N*m); ;
SubDyn['M3N9MKxe'] = False # (N*m); ;
SubDyn['M4N1MKxe'] = False # (N*m); ;
SubDyn['M4N2MKxe'] = False # (N*m); ;
SubDyn['M4N3MKxe'] = False # (N*m); ;
SubDyn['M4N4MKxe'] = False # (N*m); ;
SubDyn['M4N5MKxe'] = False # (N*m); ;
SubDyn['M4N6MKxe'] = False # (N*m); ;
SubDyn['M4N7MKxe'] = False # (N*m); ;
SubDyn['M4N8MKxe'] = False # (N*m); ;
SubDyn['M4N9MKxe'] = False # (N*m); ;
SubDyn['M5N1MKxe'] = False # (N*m); ;
SubDyn['M5N2MKxe'] = False # (N*m); ;
SubDyn['M5N3MKxe'] = False # (N*m); ;
SubDyn['M5N4MKxe'] = False # (N*m); ;
SubDyn['M5N5MKxe'] = False # (N*m); ;
SubDyn['M5N6MKxe'] = False # (N*m); ;
SubDyn['M5N7MKxe'] = False # (N*m); ;
SubDyn['M5N8MKxe'] = False # (N*m); ;
SubDyn['M5N9MKxe'] = False # (N*m); ;
SubDyn['M6N1MKxe'] = False # (N*m); ;
SubDyn['M6N2MKxe'] = False # (N*m); ;
SubDyn['M6N3MKxe'] = False # (N*m); ;
SubDyn['M6N4MKxe'] = False # (N*m); ;
SubDyn['M6N5MKxe'] = False # (N*m); ;
SubDyn['M6N6MKxe'] = False # (N*m); ;
SubDyn['M6N7MKxe'] = False # (N*m); ;
SubDyn['M6N8MKxe'] = False # (N*m); ;
SubDyn['M6N9MKxe'] = False # (N*m); ;
SubDyn['M7N1MKxe'] = False # (N*m); ;
SubDyn['M7N2MKxe'] = False # (N*m); ;
SubDyn['M7N3MKxe'] = False # (N*m); ;
SubDyn['M7N4MKxe'] = False # (N*m); ;
SubDyn['M7N5MKxe'] = False # (N*m); ;
SubDyn['M7N6MKxe'] = False # (N*m); ;
SubDyn['M7N7MKxe'] = False # (N*m); ;
SubDyn['M7N8MKxe'] = False # (N*m); ;
SubDyn['M7N9MKxe'] = False # (N*m); ;
SubDyn['M8N1MKxe'] = False # (N*m); ;
SubDyn['M8N2MKxe'] = False # (N*m); ;
SubDyn['M8N3MKxe'] = False # (N*m); ;
SubDyn['M8N4MKxe'] = False # (N*m); ;
SubDyn['M8N5MKxe'] = False # (N*m); ;
SubDyn['M8N6MKxe'] = False # (N*m); ;
SubDyn['M8N7MKxe'] = False # (N*m); ;
SubDyn['M8N8MKxe'] = False # (N*m); ;
SubDyn['M8N9MKxe'] = False # (N*m); ;
SubDyn['M9N1MKxe'] = False # (N*m); ;
SubDyn['M9N2MKxe'] = False # (N*m); ;
SubDyn['M9N3MKxe'] = False # (N*m); ;
SubDyn['M9N4MKxe'] = False # (N*m); ;
SubDyn['M9N5MKxe'] = False # (N*m); ;
SubDyn['M9N6MKxe'] = False # (N*m); ;
SubDyn['M9N7MKxe'] = False # (N*m); ;
SubDyn['M9N8MKxe'] = False # (N*m); ;
SubDyn['M9N9MKxe'] = False # (N*m); ;
SubDyn['M1N1MKye'] = False # (N*m); ye component of the bending moment at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2MKye'] = False # (N*m); ;
SubDyn['M1N3MKye'] = False # (N*m); ;
SubDyn['M1N4MKye'] = False # (N*m); ;
SubDyn['M1N5MKye'] = False # (N*m); ;
SubDyn['M1N6MKye'] = False # (N*m); ;
SubDyn['M1N7MKye'] = False # (N*m); ;
SubDyn['M1N8MKye'] = False # (N*m); ;
SubDyn['M1N9MKye'] = False # (N*m); ;
SubDyn['M2N1MKye'] = False # (N*m); ;
SubDyn['M2N2MKye'] = False # (N*m); ;
SubDyn['M2N3MKye'] = False # (N*m); ;
SubDyn['M2N4MKye'] = False # (N*m); ;
SubDyn['M2N5MKye'] = False # (N*m); ;
SubDyn['M2N6MKye'] = False # (N*m); ;
SubDyn['M2N7MKye'] = False # (N*m); ;
SubDyn['M2N8MKye'] = False # (N*m); ;
SubDyn['M2N9MKye'] = False # (N*m); ;
SubDyn['M3N1MKye'] = False # (N*m); ;
SubDyn['M3N2MKye'] = False # (N*m); ;
SubDyn['M3N3MKye'] = False # (N*m); ;
SubDyn['M3N4MKye'] = False # (N*m); ;
SubDyn['M3N5MKye'] = False # (N*m); ;
SubDyn['M3N6MKye'] = False # (N*m); ;
SubDyn['M3N7MKye'] = False # (N*m); ;
SubDyn['M3N8MKye'] = False # (N*m); ;
SubDyn['M3N9MKye'] = False # (N*m); ;
SubDyn['M4N1MKye'] = False # (N*m); ;
SubDyn['M4N2MKye'] = False # (N*m); ;
SubDyn['M4N3MKye'] = False # (N*m); ;
SubDyn['M4N4MKye'] = False # (N*m); ;
SubDyn['M4N5MKye'] = False # (N*m); ;
SubDyn['M4N6MKye'] = False # (N*m); ;
SubDyn['M4N7MKye'] = False # (N*m); ;
SubDyn['M4N8MKye'] = False # (N*m); ;
SubDyn['M4N9MKye'] = False # (N*m); ;
SubDyn['M5N1MKye'] = False # (N*m); ;
SubDyn['M5N2MKye'] = False # (N*m); ;
SubDyn['M5N3MKye'] = False # (N*m); ;
SubDyn['M5N4MKye'] = False # (N*m); ;
SubDyn['M5N5MKye'] = False # (N*m); ;
SubDyn['M5N6MKye'] = False # (N*m); ;
SubDyn['M5N7MKye'] = False # (N*m); ;
SubDyn['M5N8MKye'] = False # (N*m); ;
SubDyn['M5N9MKye'] = False # (N*m); ;
SubDyn['M6N1MKye'] = False # (N*m); ;
SubDyn['M6N2MKye'] = False # (N*m); ;
SubDyn['M6N3MKye'] = False # (N*m); ;
SubDyn['M6N4MKye'] = False # (N*m); ;
SubDyn['M6N5MKye'] = False # (N*m); ;
SubDyn['M6N6MKye'] = False # (N*m); ;
SubDyn['M6N7MKye'] = False # (N*m); ;
SubDyn['M6N8MKye'] = False # (N*m); ;
SubDyn['M6N9MKye'] = False # (N*m); ;
SubDyn['M7N1MKye'] = False # (N*m); ;
SubDyn['M7N2MKye'] = False # (N*m); ;
SubDyn['M7N3MKye'] = False # (N*m); ;
SubDyn['M7N4MKye'] = False # (N*m); ;
SubDyn['M7N5MKye'] = False # (N*m); ;
SubDyn['M7N6MKye'] = False # (N*m); ;
SubDyn['M7N7MKye'] = False # (N*m); ;
SubDyn['M7N8MKye'] = False # (N*m); ;
SubDyn['M7N9MKye'] = False # (N*m); ;
SubDyn['M8N1MKye'] = False # (N*m); ;
SubDyn['M8N2MKye'] = False # (N*m); ;
SubDyn['M8N3MKye'] = False # (N*m); ;
SubDyn['M8N4MKye'] = False # (N*m); ;
SubDyn['M8N5MKye'] = False # (N*m); ;
SubDyn['M8N6MKye'] = False # (N*m); ;
SubDyn['M8N7MKye'] = False # (N*m); ;
SubDyn['M8N8MKye'] = False # (N*m); ;
SubDyn['M8N9MKye'] = False # (N*m); ;
SubDyn['M9N1MKye'] = False # (N*m); ;
SubDyn['M9N2MKye'] = False # (N*m); ;
SubDyn['M9N3MKye'] = False # (N*m); ;
SubDyn['M9N4MKye'] = False # (N*m); ;
SubDyn['M9N5MKye'] = False # (N*m); ;
SubDyn['M9N6MKye'] = False # (N*m); ;
SubDyn['M9N7MKye'] = False # (N*m); ;
SubDyn['M9N8MKye'] = False # (N*m); ;
SubDyn['M9N9MKye'] = False # (N*m); ;
SubDyn['M1N1MKze'] = False # (N*m); Torsion moment at Node Nj of member Mi- Local Reference System- Static Component;
SubDyn['M1N2MKze'] = False # (N*m); ;
SubDyn['M1N3MKze'] = False # (N*m); ;
SubDyn['M1N4MKze'] = False # (N*m); ;
SubDyn['M1N5MKze'] = False # (N*m); ;
SubDyn['M1N6MKze'] = False # (N*m); ;
SubDyn['M1N7MKze'] = False # (N*m); ;
SubDyn['M1N8MKze'] = False # (N*m); ;
SubDyn['M1N9MKze'] = False # (N*m); ;
SubDyn['M2N1MKze'] = False # (N*m); ;
SubDyn['M2N2MKze'] = False # (N*m); ;
SubDyn['M2N3MKze'] = False # (N*m); ;
SubDyn['M2N4MKze'] = False # (N*m); ;
SubDyn['M2N5MKze'] = False # (N*m); ;
SubDyn['M2N6MKze'] = False # (N*m); ;
SubDyn['M2N7MKze'] = False # (N*m); ;
SubDyn['M2N8MKze'] = False # (N*m); ;
SubDyn['M2N9MKze'] = False # (N*m); ;
SubDyn['M3N1MKze'] = False # (N*m); ;
SubDyn['M3N2MKze'] = False # (N*m); ;
SubDyn['M3N3MKze'] = False # (N*m); ;
SubDyn['M3N4MKze'] = False # (N*m); ;
SubDyn['M3N5MKze'] = False # (N*m); ;
SubDyn['M3N6MKze'] = False # (N*m); ;
SubDyn['M3N7MKze'] = False # (N*m); ;
SubDyn['M3N8MKze'] = False # (N*m); ;
SubDyn['M3N9MKze'] = False # (N*m); ;
SubDyn['M4N1MKze'] = False # (N*m); ;
SubDyn['M4N2MKze'] = False # (N*m); ;
SubDyn['M4N3MKze'] = False # (N*m); ;
SubDyn['M4N4MKze'] = False # (N*m); ;
SubDyn['M4N5MKze'] = False # (N*m); ;
SubDyn['M4N6MKze'] = False # (N*m); ;
SubDyn['M4N7MKze'] = False # (N*m); ;
SubDyn['M4N8MKze'] = False # (N*m); ;
SubDyn['M4N9MKze'] = False # (N*m); ;
SubDyn['M5N1MKze'] = False # (N*m); ;
SubDyn['M5N2MKze'] = False # (N*m); ;
SubDyn['M5N3MKze'] = False # (N*m); ;
SubDyn['M5N4MKze'] = False # (N*m); ;
SubDyn['M5N5MKze'] = False # (N*m); ;
SubDyn['M5N6MKze'] = False # (N*m); ;
SubDyn['M5N7MKze'] = False # (N*m); ;
SubDyn['M5N8MKze'] = False # (N*m); ;
SubDyn['M5N9MKze'] = False # (N*m); ;
SubDyn['M6N1MKze'] = False # (N*m); ;
SubDyn['M6N2MKze'] = False # (N*m); ;
SubDyn['M6N3MKze'] = False # (N*m); ;
SubDyn['M6N4MKze'] = False # (N*m); ;
SubDyn['M6N5MKze'] = False # (N*m); ;
SubDyn['M6N6MKze'] = False # (N*m); ;
SubDyn['M6N7MKze'] = False # (N*m); ;
SubDyn['M6N8MKze'] = False # (N*m); ;
SubDyn['M6N9MKze'] = False # (N*m); ;
SubDyn['M7N1MKze'] = False # (N*m); ;
SubDyn['M7N2MKze'] = False # (N*m); ;
SubDyn['M7N3MKze'] = False # (N*m); ;
SubDyn['M7N4MKze'] = False # (N*m); ;
SubDyn['M7N5MKze'] = False # (N*m); ;
SubDyn['M7N6MKze'] = False # (N*m); ;
SubDyn['M7N7MKze'] = False # (N*m); ;
SubDyn['M7N8MKze'] = False # (N*m); ;
SubDyn['M7N9MKze'] = False # (N*m); ;
SubDyn['M8N1MKze'] = False # (N*m); ;
SubDyn['M8N2MKze'] = False # (N*m); ;
SubDyn['M8N3MKze'] = False # (N*m); ;
SubDyn['M8N4MKze'] = False # (N*m); ;
SubDyn['M8N5MKze'] = False # (N*m); ;
SubDyn['M8N6MKze'] = False # (N*m); ;
SubDyn['M8N7MKze'] = False # (N*m); ;
SubDyn['M8N8MKze'] = False # (N*m); ;
SubDyn['M8N9MKze'] = False # (N*m); ;
SubDyn['M9N1MKze'] = False # (N*m); ;
SubDyn['M9N2MKze'] = False # (N*m); ;
SubDyn['M9N3MKze'] = False # (N*m); ;
SubDyn['M9N4MKze'] = False # (N*m); ;
SubDyn['M9N5MKze'] = False # (N*m); ;
SubDyn['M9N6MKze'] = False # (N*m); ;
SubDyn['M9N7MKze'] = False # (N*m); ;
SubDyn['M9N8MKze'] = False # (N*m); ;
SubDyn['M9N9MKze'] = False # (N*m); ;
SubDyn['M1N1MMxe'] = False # (N*m); xe component of the bending moment at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2MMxe'] = False # (N*m); ;
SubDyn['M1N3MMxe'] = False # (N*m); ;
SubDyn['M1N4MMxe'] = False # (N*m); ;
SubDyn['M1N5MMxe'] = False # (N*m); ;
SubDyn['M1N6MMxe'] = False # (N*m); ;
SubDyn['M1N7MMxe'] = False # (N*m); ;
SubDyn['M1N8MMxe'] = False # (N*m); ;
SubDyn['M1N9MMxe'] = False # (N*m); ;
SubDyn['M2N1MMxe'] = False # (N*m); ;
SubDyn['M2N2MMxe'] = False # (N*m); ;
SubDyn['M2N3MMxe'] = False # (N*m); ;
SubDyn['M2N4MMxe'] = False # (N*m); ;
SubDyn['M2N5MMxe'] = False # (N*m); ;
SubDyn['M2N6MMxe'] = False # (N*m); ;
SubDyn['M2N7MMxe'] = False # (N*m); ;
SubDyn['M2N8MMxe'] = False # (N*m); ;
SubDyn['M2N9MMxe'] = False # (N*m); ;
SubDyn['M3N1MMxe'] = False # (N*m); ;
SubDyn['M3N2MMxe'] = False # (N*m); ;
SubDyn['M3N3MMxe'] = False # (N*m); ;
SubDyn['M3N4MMxe'] = False # (N*m); ;
SubDyn['M3N5MMxe'] = False # (N*m); ;
SubDyn['M3N6MMxe'] = False # (N*m); ;
SubDyn['M3N7MMxe'] = False # (N*m); ;
SubDyn['M3N8MMxe'] = False # (N*m); ;
SubDyn['M3N9MMxe'] = False # (N*m); ;
SubDyn['M4N1MMxe'] = False # (N*m); ;
SubDyn['M4N2MMxe'] = False # (N*m); ;
SubDyn['M4N3MMxe'] = False # (N*m); ;
SubDyn['M4N4MMxe'] = False # (N*m); ;
SubDyn['M4N5MMxe'] = False # (N*m); ;
SubDyn['M4N6MMxe'] = False # (N*m); ;
SubDyn['M4N7MMxe'] = False # (N*m); ;
SubDyn['M4N8MMxe'] = False # (N*m); ;
SubDyn['M4N9MMxe'] = False # (N*m); ;
SubDyn['M5N1MMxe'] = False # (N*m); ;
SubDyn['M5N2MMxe'] = False # (N*m); ;
SubDyn['M5N3MMxe'] = False # (N*m); ;
SubDyn['M5N4MMxe'] = False # (N*m); ;
SubDyn['M5N5MMxe'] = False # (N*m); ;
SubDyn['M5N6MMxe'] = False # (N*m); ;
SubDyn['M5N7MMxe'] = False # (N*m); ;
SubDyn['M5N8MMxe'] = False # (N*m); ;
SubDyn['M5N9MMxe'] = False # (N*m); ;
SubDyn['M6N1MMxe'] = False # (N*m); ;
SubDyn['M6N2MMxe'] = False # (N*m); ;
SubDyn['M6N3MMxe'] = False # (N*m); ;
SubDyn['M6N4MMxe'] = False # (N*m); ;
SubDyn['M6N5MMxe'] = False # (N*m); ;
SubDyn['M6N6MMxe'] = False # (N*m); ;
SubDyn['M6N7MMxe'] = False # (N*m); ;
SubDyn['M6N8MMxe'] = False # (N*m); ;
SubDyn['M6N9MMxe'] = False # (N*m); ;
SubDyn['M7N1MMxe'] = False # (N*m); ;
SubDyn['M7N2MMxe'] = False # (N*m); ;
SubDyn['M7N3MMxe'] = False # (N*m); ;
SubDyn['M7N4MMxe'] = False # (N*m); ;
SubDyn['M7N5MMxe'] = False # (N*m); ;
SubDyn['M7N6MMxe'] = False # (N*m); ;
SubDyn['M7N7MMxe'] = False # (N*m); ;
SubDyn['M7N8MMxe'] = False # (N*m); ;
SubDyn['M7N9MMxe'] = False # (N*m); ;
SubDyn['M8N1MMxe'] = False # (N*m); ;
SubDyn['M8N2MMxe'] = False # (N*m); ;
SubDyn['M8N3MMxe'] = False # (N*m); ;
SubDyn['M8N4MMxe'] = False # (N*m); ;
SubDyn['M8N5MMxe'] = False # (N*m); ;
SubDyn['M8N6MMxe'] = False # (N*m); ;
SubDyn['M8N7MMxe'] = False # (N*m); ;
SubDyn['M8N8MMxe'] = False # (N*m); ;
SubDyn['M8N9MMxe'] = False # (N*m); ;
SubDyn['M9N1MMxe'] = False # (N*m); ;
SubDyn['M9N2MMxe'] = False # (N*m); ;
SubDyn['M9N3MMxe'] = False # (N*m); ;
SubDyn['M9N4MMxe'] = False # (N*m); ;
SubDyn['M9N5MMxe'] = False # (N*m); ;
SubDyn['M9N6MMxe'] = False # (N*m); ;
SubDyn['M9N7MMxe'] = False # (N*m); ;
SubDyn['M9N8MMxe'] = False # (N*m); ;
SubDyn['M9N9MMxe'] = False # (N*m); ;
SubDyn['M1N1MMye'] = False # (N*m); ye component of the bending moment at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2MMye'] = False # (N*m); ;
SubDyn['M1N3MMye'] = False # (N*m); ;
SubDyn['M1N4MMye'] = False # (N*m); ;
SubDyn['M1N5MMye'] = False # (N*m); ;
SubDyn['M1N6MMye'] = False # (N*m); ;
SubDyn['M1N7MMye'] = False # (N*m); ;
SubDyn['M1N8MMye'] = False # (N*m); ;
SubDyn['M1N9MMye'] = False # (N*m); ;
SubDyn['M2N1MMye'] = False # (N*m); ;
SubDyn['M2N2MMye'] = False # (N*m); ;
SubDyn['M2N3MMye'] = False # (N*m); ;
SubDyn['M2N4MMye'] = False # (N*m); ;
SubDyn['M2N5MMye'] = False # (N*m); ;
SubDyn['M2N6MMye'] = False # (N*m); ;
SubDyn['M2N7MMye'] = False # (N*m); ;
SubDyn['M2N8MMye'] = False # (N*m); ;
SubDyn['M2N9MMye'] = False # (N*m); ;
SubDyn['M3N1MMye'] = False # (N*m); ;
SubDyn['M3N2MMye'] = False # (N*m); ;
SubDyn['M3N3MMye'] = False # (N*m); ;
SubDyn['M3N4MMye'] = False # (N*m); ;
SubDyn['M3N5MMye'] = False # (N*m); ;
SubDyn['M3N6MMye'] = False # (N*m); ;
SubDyn['M3N7MMye'] = False # (N*m); ;
SubDyn['M3N8MMye'] = False # (N*m); ;
SubDyn['M3N9MMye'] = False # (N*m); ;
SubDyn['M4N1MMye'] = False # (N*m); ;
SubDyn['M4N2MMye'] = False # (N*m); ;
SubDyn['M4N3MMye'] = False # (N*m); ;
SubDyn['M4N4MMye'] = False # (N*m); ;
SubDyn['M4N5MMye'] = False # (N*m); ;
SubDyn['M4N6MMye'] = False # (N*m); ;
SubDyn['M4N7MMye'] = False # (N*m); ;
SubDyn['M4N8MMye'] = False # (N*m); ;
SubDyn['M4N9MMye'] = False # (N*m); ;
SubDyn['M5N1MMye'] = False # (N*m); ;
SubDyn['M5N2MMye'] = False # (N*m); ;
SubDyn['M5N3MMye'] = False # (N*m); ;
SubDyn['M5N4MMye'] = False # (N*m); ;
SubDyn['M5N5MMye'] = False # (N*m); ;
SubDyn['M5N6MMye'] = False # (N*m); ;
SubDyn['M5N7MMye'] = False # (N*m); ;
SubDyn['M5N8MMye'] = False # (N*m); ;
SubDyn['M5N9MMye'] = False # (N*m); ;
SubDyn['M6N1MMye'] = False # (N*m); ;
SubDyn['M6N2MMye'] = False # (N*m); ;
SubDyn['M6N3MMye'] = False # (N*m); ;
SubDyn['M6N4MMye'] = False # (N*m); ;
SubDyn['M6N5MMye'] = False # (N*m); ;
SubDyn['M6N6MMye'] = False # (N*m); ;
SubDyn['M6N7MMye'] = False # (N*m); ;
SubDyn['M6N8MMye'] = False # (N*m); ;
SubDyn['M6N9MMye'] = False # (N*m); ;
SubDyn['M7N1MMye'] = False # (N*m); ;
SubDyn['M7N2MMye'] = False # (N*m); ;
SubDyn['M7N3MMye'] = False # (N*m); ;
SubDyn['M7N4MMye'] = False # (N*m); ;
SubDyn['M7N5MMye'] = False # (N*m); ;
SubDyn['M7N6MMye'] = False # (N*m); ;
SubDyn['M7N7MMye'] = False # (N*m); ;
SubDyn['M7N8MMye'] = False # (N*m); ;
SubDyn['M7N9MMye'] = False # (N*m); ;
SubDyn['M8N1MMye'] = False # (N*m); ;
SubDyn['M8N2MMye'] = False # (N*m); ;
SubDyn['M8N3MMye'] = False # (N*m); ;
SubDyn['M8N4MMye'] = False # (N*m); ;
SubDyn['M8N5MMye'] = False # (N*m); ;
SubDyn['M8N6MMye'] = False # (N*m); ;
SubDyn['M8N7MMye'] = False # (N*m); ;
SubDyn['M8N8MMye'] = False # (N*m); ;
SubDyn['M8N9MMye'] = False # (N*m); ;
SubDyn['M9N1MMye'] = False # (N*m); ;
SubDyn['M9N2MMye'] = False # (N*m); ;
SubDyn['M9N3MMye'] = False # (N*m); ;
SubDyn['M9N4MMye'] = False # (N*m); ;
SubDyn['M9N5MMye'] = False # (N*m); ;
SubDyn['M9N6MMye'] = False # (N*m); ;
SubDyn['M9N7MMye'] = False # (N*m); ;
SubDyn['M9N8MMye'] = False # (N*m); ;
SubDyn['M9N9MMye'] = False # (N*m); ;
SubDyn['M1N1MMze'] = False # (N*m); Torsion moment at Node Nj of member Mi- Local Reference System- Dynamic Component;
SubDyn['M1N2MMze'] = False # (N*m); ;
SubDyn['M1N3MMze'] = False # (N*m); ;
SubDyn['M1N4MMze'] = False # (N*m); ;
SubDyn['M1N5MMze'] = False # (N*m); ;
SubDyn['M1N6MMze'] = False # (N*m); ;
SubDyn['M1N7MMze'] = False # (N*m); ;
SubDyn['M1N8MMze'] = False # (N*m); ;
SubDyn['M1N9MMze'] = False # (N*m); ;
SubDyn['M2N1MMze'] = False # (N*m); ;
SubDyn['M2N2MMze'] = False # (N*m); ;
SubDyn['M2N3MMze'] = False # (N*m); ;
SubDyn['M2N4MMze'] = False # (N*m); ;
SubDyn['M2N5MMze'] = False # (N*m); ;
SubDyn['M2N6MMze'] = False # (N*m); ;
SubDyn['M2N7MMze'] = False # (N*m); ;
SubDyn['M2N8MMze'] = False # (N*m); ;
SubDyn['M2N9MMze'] = False # (N*m); ;
SubDyn['M3N1MMze'] = False # (N*m); ;
SubDyn['M3N2MMze'] = False # (N*m); ;
SubDyn['M3N3MMze'] = False # (N*m); ;
SubDyn['M3N4MMze'] = False # (N*m); ;
SubDyn['M3N5MMze'] = False # (N*m); ;
SubDyn['M3N6MMze'] = False # (N*m); ;
SubDyn['M3N7MMze'] = False # (N*m); ;
SubDyn['M3N8MMze'] = False # (N*m); ;
SubDyn['M3N9MMze'] = False # (N*m); ;
SubDyn['M4N1MMze'] = False # (N*m); ;
SubDyn['M4N2MMze'] = False # (N*m); ;
SubDyn['M4N3MMze'] = False # (N*m); ;
SubDyn['M4N4MMze'] = False # (N*m); ;
SubDyn['M4N5MMze'] = False # (N*m); ;
SubDyn['M4N6MMze'] = False # (N*m); ;
SubDyn['M4N7MMze'] = False # (N*m); ;
SubDyn['M4N8MMze'] = False # (N*m); ;
SubDyn['M4N9MMze'] = False # (N*m); ;
SubDyn['M5N1MMze'] = False # (N*m); ;
SubDyn['M5N2MMze'] = False # (N*m); ;
SubDyn['M5N3MMze'] = False # (N*m); ;
SubDyn['M5N4MMze'] = False # (N*m); ;
SubDyn['M5N5MMze'] = False # (N*m); ;
SubDyn['M5N6MMze'] = False # (N*m); ;
SubDyn['M5N7MMze'] = False # (N*m); ;
SubDyn['M5N8MMze'] = False # (N*m); ;
SubDyn['M5N9MMze'] = False # (N*m); ;
SubDyn['M6N1MMze'] = False # (N*m); ;
SubDyn['M6N2MMze'] = False # (N*m); ;
SubDyn['M6N3MMze'] = False # (N*m); ;
SubDyn['M6N4MMze'] = False # (N*m); ;
SubDyn['M6N5MMze'] = False # (N*m); ;
SubDyn['M6N6MMze'] = False # (N*m); ;
SubDyn['M6N7MMze'] = False # (N*m); ;
SubDyn['M6N8MMze'] = False # (N*m); ;
SubDyn['M6N9MMze'] = False # (N*m); ;
SubDyn['M7N1MMze'] = False # (N*m); ;
SubDyn['M7N2MMze'] = False # (N*m); ;
SubDyn['M7N3MMze'] = False # (N*m); ;
SubDyn['M7N4MMze'] = False # (N*m); ;
SubDyn['M7N5MMze'] = False # (N*m); ;
SubDyn['M7N6MMze'] = False # (N*m); ;
SubDyn['M7N7MMze'] = False # (N*m); ;
SubDyn['M7N8MMze'] = False # (N*m); ;
SubDyn['M7N9MMze'] = False # (N*m); ;
SubDyn['M8N1MMze'] = False # (N*m); ;
SubDyn['M8N2MMze'] = False # (N*m); ;
SubDyn['M8N3MMze'] = False # (N*m); ;
SubDyn['M8N4MMze'] = False # (N*m); ;
SubDyn['M8N5MMze'] = False # (N*m); ;
SubDyn['M8N6MMze'] = False # (N*m); ;
SubDyn['M8N7MMze'] = False # (N*m); ;
SubDyn['M8N8MMze'] = False # (N*m); ;
SubDyn['M8N9MMze'] = False # (N*m); ;
SubDyn['M9N1MMze'] = False # (N*m); ;
SubDyn['M9N2MMze'] = False # (N*m); ;
SubDyn['M9N3MMze'] = False # (N*m); ;
SubDyn['M9N4MMze'] = False # (N*m); ;
SubDyn['M9N5MMze'] = False # (N*m); ;
SubDyn['M9N6MMze'] = False # (N*m); ;
SubDyn['M9N7MMze'] = False # (N*m); ;
SubDyn['M9N8MMze'] = False # (N*m); ;
SubDyn['M9N9MMze'] = False # (N*m); ;
# Displacements
SubDyn['M1N1TDxss'] = False # (m); xss component of the displacement at Node Nj of member Mi- SS Reference System;
SubDyn['M1N2TDxss'] = False # (m); ;
SubDyn['M1N3TDxss'] = False # (m); ;
SubDyn['M1N4TDxss'] = False # (m); ;
SubDyn['M1N5TDxss'] = False # (m); ;
SubDyn['M1N6TDxss'] = False # (m); ;
SubDyn['M1N7TDxss'] = False # (m); ;
SubDyn['M1N8TDxss'] = False # (m); ;
SubDyn['M1N9TDxss'] = False # (m); ;
SubDyn['M2N1TDxss'] = False # (m); ;
SubDyn['M2N2TDxss'] = False # (m); ;
SubDyn['M2N3TDxss'] = False # (m); ;
SubDyn['M2N4TDxss'] = False # (m); ;
SubDyn['M2N5TDxss'] = False # (m); ;
SubDyn['M2N6TDxss'] = False # (m); ;
SubDyn['M2N7TDxss'] = False # (m); ;
SubDyn['M2N8TDxss'] = False # (m); ;
SubDyn['M2N9TDxss'] = False # (m); ;
SubDyn['M3N1TDxss'] = False # (m); ;
SubDyn['M3N2TDxss'] = False # (m); ;
SubDyn['M3N3TDxss'] = False # (m); ;
SubDyn['M3N4TDxss'] = False # (m); ;
SubDyn['M3N5TDxss'] = False # (m); ;
SubDyn['M3N6TDxss'] = False # (m); ;
SubDyn['M3N7TDxss'] = False # (m); ;
SubDyn['M3N8TDxss'] = False # (m); ;
SubDyn['M3N9TDxss'] = False # (m); ;
SubDyn['M4N1TDxss'] = False # (m); ;
SubDyn['M4N2TDxss'] = False # (m); ;
SubDyn['M4N3TDxss'] = False # (m); ;
SubDyn['M4N4TDxss'] = False # (m); ;
SubDyn['M4N5TDxss'] = False # (m); ;
SubDyn['M4N6TDxss'] = False # (m); ;
SubDyn['M4N7TDxss'] = False # (m); ;
SubDyn['M4N8TDxss'] = False # (m); ;
SubDyn['M4N9TDxss'] = False # (m); ;
SubDyn['M5N1TDxss'] = False # (m); ;
SubDyn['M5N2TDxss'] = False # (m); ;
SubDyn['M5N3TDxss'] = False # (m); ;
SubDyn['M5N4TDxss'] = False # (m); ;
SubDyn['M5N5TDxss'] = False # (m); ;
SubDyn['M5N6TDxss'] = False # (m); ;
SubDyn['M5N7TDxss'] = False # (m); ;
SubDyn['M5N8TDxss'] = False # (m); ;
SubDyn['M5N9TDxss'] = False # (m); ;
SubDyn['M6N1TDxss'] = False # (m); ;
SubDyn['M6N2TDxss'] = False # (m); ;
SubDyn['M6N3TDxss'] = False # (m); ;
SubDyn['M6N4TDxss'] = False # (m); ;
SubDyn['M6N5TDxss'] = False # (m); ;
SubDyn['M6N6TDxss'] = False # (m); ;
SubDyn['M6N7TDxss'] = False # (m); ;
SubDyn['M6N8TDxss'] = False # (m); ;
SubDyn['M6N9TDxss'] = False # (m); ;
SubDyn['M7N1TDxss'] = False # (m); ;
SubDyn['M7N2TDxss'] = False # (m); ;
SubDyn['M7N3TDxss'] = False # (m); ;
SubDyn['M7N4TDxss'] = False # (m); ;
SubDyn['M7N5TDxss'] = False # (m); ;
SubDyn['M7N6TDxss'] = False # (m); ;
SubDyn['M7N7TDxss'] = False # (m); ;
SubDyn['M7N8TDxss'] = False # (m); ;
SubDyn['M7N9TDxss'] = False # (m); ;
SubDyn['M8N1TDxss'] = False # (m); ;
SubDyn['M8N2TDxss'] = False # (m); ;
SubDyn['M8N3TDxss'] = False # (m); ;
SubDyn['M8N4TDxss'] = False # (m); ;
SubDyn['M8N5TDxss'] = False # (m); ;
SubDyn['M8N6TDxss'] = False # (m); ;
SubDyn['M8N7TDxss'] = False # (m); ;
SubDyn['M8N8TDxss'] = False # (m); ;
SubDyn['M8N9TDxss'] = False # (m); ;
SubDyn['M9N1TDxss'] = False # (m); ;
SubDyn['M9N2TDxss'] = False # (m); ;
SubDyn['M9N3TDxss'] = False # (m); ;
SubDyn['M9N4TDxss'] = False # (m); ;
SubDyn['M9N5TDxss'] = False # (m); ;
SubDyn['M9N6TDxss'] = False # (m); ;
SubDyn['M9N7TDxss'] = False # (m); ;
SubDyn['M9N8TDxss'] = False # (m); ;
SubDyn['M9N9TDxss'] = False # (m); ;
SubDyn['M1N1TDyss'] = False # (m); yss component of the displacement at Node Nj of member Mi- SS Reference System;
SubDyn['M1N2TDyss'] = False # (m); ;
SubDyn['M1N3TDyss'] = False # (m); ;
SubDyn['M1N4TDyss'] = False # (m); ;
SubDyn['M1N5TDyss'] = False # (m); ;
SubDyn['M1N6TDyss'] = False # (m); ;
SubDyn['M1N7TDyss'] = False # (m); ;
SubDyn['M1N8TDyss'] = False # (m); ;
SubDyn['M1N9TDyss'] = False # (m); ;
SubDyn['M2N1TDyss'] = False # (m); ;
SubDyn['M2N2TDyss'] = False # (m); ;
SubDyn['M2N3TDyss'] = False # (m); ;
SubDyn['M2N4TDyss'] = False # (m); ;
SubDyn['M2N5TDyss'] = False # (m); ;
SubDyn['M2N6TDyss'] = False # (m); ;
SubDyn['M2N7TDyss'] = False # (m); ;
SubDyn['M2N8TDyss'] = False # (m); ;
SubDyn['M2N9TDyss'] = False # (m); ;
SubDyn['M3N1TDyss'] = False # (m); ;
SubDyn['M3N2TDyss'] = False # (m); ;
SubDyn['M3N3TDyss'] = False # (m); ;
SubDyn['M3N4TDyss'] = False # (m); ;
SubDyn['M3N5TDyss'] = False # (m); ;
SubDyn['M3N6TDyss'] = False # (m); ;
SubDyn['M3N7TDyss'] = False # (m); ;
SubDyn['M3N8TDyss'] = False # (m); ;
SubDyn['M3N9TDyss'] = False # (m); ;
SubDyn['M4N1TDyss'] = False # (m); ;
SubDyn['M4N2TDyss'] = False # (m); ;
SubDyn['M4N3TDyss'] = False # (m); ;
SubDyn['M4N4TDyss'] = False # (m); ;
SubDyn['M4N5TDyss'] = False # (m); ;
SubDyn['M4N6TDyss'] = False # (m); ;
SubDyn['M4N7TDyss'] = False # (m); ;
SubDyn['M4N8TDyss'] = False # (m); ;
SubDyn['M4N9TDyss'] = False # (m); ;
SubDyn['M5N1TDyss'] = False # (m); ;
SubDyn['M5N2TDyss'] = False # (m); ;
SubDyn['M5N3TDyss'] = False # (m); ;
SubDyn['M5N4TDyss'] = False # (m); ;
SubDyn['M5N5TDyss'] = False # (m); ;
SubDyn['M5N6TDyss'] = False # (m); ;
SubDyn['M5N7TDyss'] = False # (m); ;
SubDyn['M5N8TDyss'] = False # (m); ;
SubDyn['M5N9TDyss'] = False # (m); ;
SubDyn['M6N1TDyss'] = False # (m); ;
SubDyn['M6N2TDyss'] = False # (m); ;
SubDyn['M6N3TDyss'] = False # (m); ;
SubDyn['M6N4TDyss'] = False # (m); ;
SubDyn['M6N5TDyss'] = False # (m); ;
SubDyn['M6N6TDyss'] = False # (m); ;
SubDyn['M6N7TDyss'] = False # (m); ;
SubDyn['M6N8TDyss'] = False # (m); ;
SubDyn['M6N9TDyss'] = False # (m); ;
SubDyn['M7N1TDyss'] = False # (m); ;
SubDyn['M7N2TDyss'] = False # (m); ;
SubDyn['M7N3TDyss'] = False # (m); ;
SubDyn['M7N4TDyss'] = False # (m); ;
SubDyn['M7N5TDyss'] = False # (m); ;
SubDyn['M7N6TDyss'] = False # (m); ;
SubDyn['M7N7TDyss'] = False # (m); ;
SubDyn['M7N8TDyss'] = False # (m); ;
SubDyn['M7N9TDyss'] = False # (m); ;
SubDyn['M8N1TDyss'] = False # (m); ;
SubDyn['M8N2TDyss'] = False # (m); ;
SubDyn['M8N3TDyss'] = False # (m); ;
SubDyn['M8N4TDyss'] = False # (m); ;
SubDyn['M8N5TDyss'] = False # (m); ;
SubDyn['M8N6TDyss'] = False # (m); ;
SubDyn['M8N7TDyss'] = False # (m); ;
SubDyn['M8N8TDyss'] = False # (m); ;
SubDyn['M8N9TDyss'] = False # (m); ;
SubDyn['M9N1TDyss'] = False # (m); ;
SubDyn['M9N2TDyss'] = False # (m); ;
SubDyn['M9N3TDyss'] = False # (m); ;
SubDyn['M9N4TDyss'] = False # (m); ;
SubDyn['M9N5TDyss'] = False # (m); ;
SubDyn['M9N6TDyss'] = False # (m); ;
SubDyn['M9N7TDyss'] = False # (m); ;
SubDyn['M9N8TDyss'] = False # (m); ;
SubDyn['M9N9TDyss'] = False # (m); ;
SubDyn['M1N1TDzss'] = False # (m); zss component of the displacement at Node Nj of member Mi- SS Reference System;
SubDyn['M1N2TDzss'] = False # (m); ;
SubDyn['M1N3TDzss'] = False # (m); ;
SubDyn['M1N4TDzss'] = False # (m); ;
SubDyn['M1N5TDzss'] = False # (m); ;
SubDyn['M1N6TDzss'] = False # (m); ;
SubDyn['M1N7TDzss'] = False # (m); ;
SubDyn['M1N8TDzss'] = False # (m); ;
SubDyn['M1N9TDzss'] = False # (m); ;
SubDyn['M2N1TDzss'] = False # (m); ;
SubDyn['M2N2TDzss'] = False # (m); ;
SubDyn['M2N3TDzss'] = False # (m); ;
SubDyn['M2N4TDzss'] = False # (m); ;
SubDyn['M2N5TDzss'] = False # (m); ;
SubDyn['M2N6TDzss'] = False # (m); ;
SubDyn['M2N7TDzss'] = False # (m); ;
SubDyn['M2N8TDzss'] = False # (m); ;
SubDyn['M2N9TDzss'] = False # (m); ;
SubDyn['M3N1TDzss'] = False # (m); ;
SubDyn['M3N2TDzss'] = False # (m); ;
SubDyn['M3N3TDzss'] = False # (m); ;
SubDyn['M3N4TDzss'] = False # (m); ;
SubDyn['M3N5TDzss'] = False # (m); ;
SubDyn['M3N6TDzss'] = False # (m); ;
SubDyn['M3N7TDzss'] = False # (m); ;
SubDyn['M3N8TDzss'] = False # (m); ;
SubDyn['M3N9TDzss'] = False # (m); ;
SubDyn['M4N1TDzss'] = False # (m); ;
SubDyn['M4N2TDzss'] = False # (m); ;
SubDyn['M4N3TDzss'] = False # (m); ;
SubDyn['M4N4TDzss'] = False # (m); ;
SubDyn['M4N5TDzss'] = False # (m); ;
SubDyn['M4N6TDzss'] = False # (m); ;
SubDyn['M4N7TDzss'] = False # (m); ;
SubDyn['M4N8TDzss'] = False # (m); ;
SubDyn['M4N9TDzss'] = False # (m); ;
SubDyn['M5N1TDzss'] = False # (m); ;
SubDyn['M5N2TDzss'] = False # (m); ;
SubDyn['M5N3TDzss'] = False # (m); ;
SubDyn['M5N4TDzss'] = False # (m); ;
SubDyn['M5N5TDzss'] = False # (m); ;
SubDyn['M5N6TDzss'] = False # (m); ;
SubDyn['M5N7TDzss'] = False # (m); ;
SubDyn['M5N8TDzss'] = False # (m); ;
SubDyn['M5N9TDzss'] = False # (m); ;
SubDyn['M6N1TDzss'] = False # (m); ;
SubDyn['M6N2TDzss'] = False # (m); ;
SubDyn['M6N3TDzss'] = False # (m); ;
SubDyn['M6N4TDzss'] = False # (m); ;
SubDyn['M6N5TDzss'] = False # (m); ;
SubDyn['M6N6TDzss'] = False # (m); ;
SubDyn['M6N7TDzss'] = False # (m); ;
SubDyn['M6N8TDzss'] = False # (m); ;
SubDyn['M6N9TDzss'] = False # (m); ;
SubDyn['M7N1TDzss'] = False # (m); ;
SubDyn['M7N2TDzss'] = False # (m); ;
SubDyn['M7N3TDzss'] = False # (m); ;
SubDyn['M7N4TDzss'] = False # (m); ;
SubDyn['M7N5TDzss'] = False # (m); ;
SubDyn['M7N6TDzss'] = False # (m); ;
SubDyn['M7N7TDzss'] = False # (m); ;
SubDyn['M7N8TDzss'] = False # (m); ;
SubDyn['M7N9TDzss'] = False # (m); ;
SubDyn['M8N1TDzss'] = False # (m); ;
SubDyn['M8N2TDzss'] = False # (m); ;
SubDyn['M8N3TDzss'] = False # (m); ;
SubDyn['M8N4TDzss'] = False # (m); ;
SubDyn['M8N5TDzss'] = False # (m); ;
SubDyn['M8N6TDzss'] = False # (m); ;
SubDyn['M8N7TDzss'] = False # (m); ;
SubDyn['M8N8TDzss'] = False # (m); ;
SubDyn['M8N9TDzss'] = False # (m); ;
SubDyn['M9N1TDzss'] = False # (m); ;
SubDyn['M9N2TDzss'] = False # (m); ;
SubDyn['M9N3TDzss'] = False # (m); ;
SubDyn['M9N4TDzss'] = False # (m); ;
SubDyn['M9N5TDzss'] = False # (m); ;
SubDyn['M9N6TDzss'] = False # (m); ;
SubDyn['M9N7TDzss'] = False # (m); ;
SubDyn['M9N8TDzss'] = False # (m); ;
SubDyn['M9N9TDzss'] = False # (m); ;
SubDyn['M1N1RDxe'] = False # (rad); xe component of the rotational displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RDxe'] = False # (rad); ;
SubDyn['M1N3RDxe'] = False # (rad); ;
SubDyn['M1N4RDxe'] = False # (rad); ;
SubDyn['M1N5RDxe'] = False # (rad); ;
SubDyn['M1N6RDxe'] = False # (rad); ;
SubDyn['M1N7RDxe'] = False # (rad); ;
SubDyn['M1N8RDxe'] = False # (rad); ;
SubDyn['M1N9RDxe'] = False # (rad); ;
SubDyn['M2N1RDxe'] = False # (rad); ;
SubDyn['M2N2RDxe'] = False # (rad); ;
SubDyn['M2N3RDxe'] = False # (rad); ;
SubDyn['M2N4RDxe'] = False # (rad); ;
SubDyn['M2N5RDxe'] = False # (rad); ;
SubDyn['M2N6RDxe'] = False # (rad); ;
SubDyn['M2N7RDxe'] = False # (rad); ;
SubDyn['M2N8RDxe'] = False # (rad); ;
SubDyn['M2N9RDxe'] = False # (rad); ;
SubDyn['M3N1RDxe'] = False # (rad); ;
SubDyn['M3N2RDxe'] = False # (rad); ;
SubDyn['M3N3RDxe'] = False # (rad); ;
SubDyn['M3N4RDxe'] = False # (rad); ;
SubDyn['M3N5RDxe'] = False # (rad); ;
SubDyn['M3N6RDxe'] = False # (rad); ;
SubDyn['M3N7RDxe'] = False # (rad); ;
SubDyn['M3N8RDxe'] = False # (rad); ;
SubDyn['M3N9RDxe'] = False # (rad); ;
SubDyn['M4N1RDxe'] = False # (rad); ;
SubDyn['M4N2RDxe'] = False # (rad); ;
SubDyn['M4N3RDxe'] = False # (rad); ;
SubDyn['M4N4RDxe'] = False # (rad); ;
SubDyn['M4N5RDxe'] = False # (rad); ;
SubDyn['M4N6RDxe'] = False # (rad); ;
SubDyn['M4N7RDxe'] = False # (rad); ;
SubDyn['M4N8RDxe'] = False # (rad); ;
SubDyn['M4N9RDxe'] = False # (rad); ;
SubDyn['M5N1RDxe'] = False # (rad); ;
SubDyn['M5N2RDxe'] = False # (rad); ;
SubDyn['M5N3RDxe'] = False # (rad); ;
SubDyn['M5N4RDxe'] = False # (rad); ;
SubDyn['M5N5RDxe'] = False # (rad); ;
SubDyn['M5N6RDxe'] = False # (rad); ;
SubDyn['M5N7RDxe'] = False # (rad); ;
SubDyn['M5N8RDxe'] = False # (rad); ;
SubDyn['M5N9RDxe'] = False # (rad); ;
SubDyn['M6N1RDxe'] = False # (rad); ;
SubDyn['M6N2RDxe'] = False # (rad); ;
SubDyn['M6N3RDxe'] = False # (rad); ;
SubDyn['M6N4RDxe'] = False # (rad); ;
SubDyn['M6N5RDxe'] = False # (rad); ;
SubDyn['M6N6RDxe'] = False # (rad); ;
SubDyn['M6N7RDxe'] = False # (rad); ;
SubDyn['M6N8RDxe'] = False # (rad); ;
SubDyn['M6N9RDxe'] = False # (rad); ;
SubDyn['M7N1RDxe'] = False # (rad); ;
SubDyn['M7N2RDxe'] = False # (rad); ;
SubDyn['M7N3RDxe'] = False # (rad); ;
SubDyn['M7N4RDxe'] = False # (rad); ;
SubDyn['M7N5RDxe'] = False # (rad); ;
SubDyn['M7N6RDxe'] = False # (rad); ;
SubDyn['M7N7RDxe'] = False # (rad); ;
SubDyn['M7N8RDxe'] = False # (rad); ;
SubDyn['M7N9RDxe'] = False # (rad); ;
SubDyn['M8N1RDxe'] = False # (rad); ;
SubDyn['M8N2RDxe'] = False # (rad); ;
SubDyn['M8N3RDxe'] = False # (rad); ;
SubDyn['M8N4RDxe'] = False # (rad); ;
SubDyn['M8N5RDxe'] = False # (rad); ;
SubDyn['M8N6RDxe'] = False # (rad); ;
SubDyn['M8N7RDxe'] = False # (rad); ;
SubDyn['M8N8RDxe'] = False # (rad); ;
SubDyn['M8N9RDxe'] = False # (rad); ;
SubDyn['M9N1RDxe'] = False # (rad); ;
SubDyn['M9N2RDxe'] = False # (rad); ;
SubDyn['M9N3RDxe'] = False # (rad); ;
SubDyn['M9N4RDxe'] = False # (rad); ;
SubDyn['M9N5RDxe'] = False # (rad); ;
SubDyn['M9N6RDxe'] = False # (rad); ;
SubDyn['M9N7RDxe'] = False # (rad); ;
SubDyn['M9N8RDxe'] = False # (rad); ;
SubDyn['M9N9RDxe'] = False # (rad); ;
SubDyn['M1N1RDye'] = False # (rad); ye component of the rotational displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RDye'] = False # (rad); ;
SubDyn['M1N3RDye'] = False # (rad); ;
SubDyn['M1N4RDye'] = False # (rad); ;
SubDyn['M1N5RDye'] = False # (rad); ;
SubDyn['M1N6RDye'] = False # (rad); ;
SubDyn['M1N7RDye'] = False # (rad); ;
SubDyn['M1N8RDye'] = False # (rad); ;
SubDyn['M1N9RDye'] = False # (rad); ;
SubDyn['M2N1RDye'] = False # (rad); ;
SubDyn['M2N2RDye'] = False # (rad); ;
SubDyn['M2N3RDye'] = False # (rad); ;
SubDyn['M2N4RDye'] = False # (rad); ;
SubDyn['M2N5RDye'] = False # (rad); ;
SubDyn['M2N6RDye'] = False # (rad); ;
SubDyn['M2N7RDye'] = False # (rad); ;
SubDyn['M2N8RDye'] = False # (rad); ;
SubDyn['M2N9RDye'] = False # (rad); ;
SubDyn['M3N1RDye'] = False # (rad); ;
SubDyn['M3N2RDye'] = False # (rad); ;
SubDyn['M3N3RDye'] = False # (rad); ;
SubDyn['M3N4RDye'] = False # (rad); ;
SubDyn['M3N5RDye'] = False # (rad); ;
SubDyn['M3N6RDye'] = False # (rad); ;
SubDyn['M3N7RDye'] = False # (rad); ;
SubDyn['M3N8RDye'] = False # (rad); ;
SubDyn['M3N9RDye'] = False # (rad); ;
SubDyn['M4N1RDye'] = False # (rad); ;
SubDyn['M4N2RDye'] = False # (rad); ;
SubDyn['M4N3RDye'] = False # (rad); ;
SubDyn['M4N4RDye'] = False # (rad); ;
SubDyn['M4N5RDye'] = False # (rad); ;
SubDyn['M4N6RDye'] = False # (rad); ;
SubDyn['M4N7RDye'] = False # (rad); ;
SubDyn['M4N8RDye'] = False # (rad); ;
SubDyn['M4N9RDye'] = False # (rad); ;
SubDyn['M5N1RDye'] = False # (rad); ;
SubDyn['M5N2RDye'] = False # (rad); ;
SubDyn['M5N3RDye'] = False # (rad); ;
SubDyn['M5N4RDye'] = False # (rad); ;
SubDyn['M5N5RDye'] = False # (rad); ;
SubDyn['M5N6RDye'] = False # (rad); ;
SubDyn['M5N7RDye'] = False # (rad); ;
SubDyn['M5N8RDye'] = False # (rad); ;
SubDyn['M5N9RDye'] = False # (rad); ;
SubDyn['M6N1RDye'] = False # (rad); ;
SubDyn['M6N2RDye'] = False # (rad); ;
SubDyn['M6N3RDye'] = False # (rad); ;
SubDyn['M6N4RDye'] = False # (rad); ;
SubDyn['M6N5RDye'] = False # (rad); ;
SubDyn['M6N6RDye'] = False # (rad); ;
SubDyn['M6N7RDye'] = False # (rad); ;
SubDyn['M6N8RDye'] = False # (rad); ;
SubDyn['M6N9RDye'] = False # (rad); ;
SubDyn['M7N1RDye'] = False # (rad); ;
SubDyn['M7N2RDye'] = False # (rad); ;
SubDyn['M7N3RDye'] = False # (rad); ;
SubDyn['M7N4RDye'] = False # (rad); ;
SubDyn['M7N5RDye'] = False # (rad); ;
SubDyn['M7N6RDye'] = False # (rad); ;
SubDyn['M7N7RDye'] = False # (rad); ;
SubDyn['M7N8RDye'] = False # (rad); ;
SubDyn['M7N9RDye'] = False # (rad); ;
SubDyn['M8N1RDye'] = False # (rad); ;
SubDyn['M8N2RDye'] = False # (rad); ;
SubDyn['M8N3RDye'] = False # (rad); ;
SubDyn['M8N4RDye'] = False # (rad); ;
SubDyn['M8N5RDye'] = False # (rad); ;
SubDyn['M8N6RDye'] = False # (rad); ;
SubDyn['M8N7RDye'] = False # (rad); ;
SubDyn['M8N8RDye'] = False # (rad); ;
SubDyn['M8N9RDye'] = False # (rad); ;
SubDyn['M9N1RDye'] = False # (rad); ;
SubDyn['M9N2RDye'] = False # (rad); ;
SubDyn['M9N3RDye'] = False # (rad); ;
SubDyn['M9N4RDye'] = False # (rad); ;
SubDyn['M9N5RDye'] = False # (rad); ;
SubDyn['M9N6RDye'] = False # (rad); ;
SubDyn['M9N7RDye'] = False # (rad); ;
SubDyn['M9N8RDye'] = False # (rad); ;
SubDyn['M9N9RDye'] = False # (rad); ;
SubDyn['M1N1RDze'] = False # (rad); ze component of the rotational displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RDze'] = False # (rad); ;
SubDyn['M1N3RDze'] = False # (rad); ;
SubDyn['M1N4RDze'] = False # (rad); ;
SubDyn['M1N5RDze'] = False # (rad); ;
SubDyn['M1N6RDze'] = False # (rad); ;
SubDyn['M1N7RDze'] = False # (rad); ;
SubDyn['M1N8RDze'] = False # (rad); ;
SubDyn['M1N9RDze'] = False # (rad); ;
SubDyn['M2N1RDze'] = False # (rad); ;
SubDyn['M2N2RDze'] = False # (rad); ;
SubDyn['M2N3RDze'] = False # (rad); ;
SubDyn['M2N4RDze'] = False # (rad); ;
SubDyn['M2N5RDze'] = False # (rad); ;
SubDyn['M2N6RDze'] = False # (rad); ;
SubDyn['M2N7RDze'] = False # (rad); ;
SubDyn['M2N8RDze'] = False # (rad); ;
SubDyn['M2N9RDze'] = False # (rad); ;
SubDyn['M3N1RDze'] = False # (rad); ;
SubDyn['M3N2RDze'] = False # (rad); ;
SubDyn['M3N3RDze'] = False # (rad); ;
SubDyn['M3N4RDze'] = False # (rad); ;
SubDyn['M3N5RDze'] = False # (rad); ;
SubDyn['M3N6RDze'] = False # (rad); ;
SubDyn['M3N7RDze'] = False # (rad); ;
SubDyn['M3N8RDze'] = False # (rad); ;
SubDyn['M3N9RDze'] = False # (rad); ;
SubDyn['M4N1RDze'] = False # (rad); ;
SubDyn['M4N2RDze'] = False # (rad); ;
SubDyn['M4N3RDze'] = False # (rad); ;
SubDyn['M4N4RDze'] = False # (rad); ;
SubDyn['M4N5RDze'] = False # (rad); ;
SubDyn['M4N6RDze'] = False # (rad); ;
SubDyn['M4N7RDze'] = False # (rad); ;
SubDyn['M4N8RDze'] = False # (rad); ;
SubDyn['M4N9RDze'] = False # (rad); ;
SubDyn['M5N1RDze'] = False # (rad); ;
SubDyn['M5N2RDze'] = False # (rad); ;
SubDyn['M5N3RDze'] = False # (rad); ;
SubDyn['M5N4RDze'] = False # (rad); ;
SubDyn['M5N5RDze'] = False # (rad); ;
SubDyn['M5N6RDze'] = False # (rad); ;
SubDyn['M5N7RDze'] = False # (rad); ;
SubDyn['M5N8RDze'] = False # (rad); ;
SubDyn['M5N9RDze'] = False # (rad); ;
SubDyn['M6N1RDze'] = False # (rad); ;
SubDyn['M6N2RDze'] = False # (rad); ;
SubDyn['M6N3RDze'] = False # (rad); ;
SubDyn['M6N4RDze'] = False # (rad); ;
SubDyn['M6N5RDze'] = False # (rad); ;
SubDyn['M6N6RDze'] = False # (rad); ;
SubDyn['M6N7RDze'] = False # (rad); ;
SubDyn['M6N8RDze'] = False # (rad); ;
SubDyn['M6N9RDze'] = False # (rad); ;
SubDyn['M7N1RDze'] = False # (rad); ;
SubDyn['M7N2RDze'] = False # (rad); ;
SubDyn['M7N3RDze'] = False # (rad); ;
SubDyn['M7N4RDze'] = False # (rad); ;
SubDyn['M7N5RDze'] = False # (rad); ;
SubDyn['M7N6RDze'] = False # (rad); ;
SubDyn['M7N7RDze'] = False # (rad); ;
SubDyn['M7N8RDze'] = False # (rad); ;
SubDyn['M7N9RDze'] = False # (rad); ;
SubDyn['M8N1RDze'] = False # (rad); ;
SubDyn['M8N2RDze'] = False # (rad); ;
SubDyn['M8N3RDze'] = False # (rad); ;
SubDyn['M8N4RDze'] = False # (rad); ;
SubDyn['M8N5RDze'] = False # (rad); ;
SubDyn['M8N6RDze'] = False # (rad); ;
SubDyn['M8N7RDze'] = False # (rad); ;
SubDyn['M8N8RDze'] = False # (rad); ;
SubDyn['M8N9RDze'] = False # (rad); ;
SubDyn['M9N1RDze'] = False # (rad); ;
SubDyn['M9N2RDze'] = False # (rad); ;
SubDyn['M9N3RDze'] = False # (rad); ;
SubDyn['M9N4RDze'] = False # (rad); ;
SubDyn['M9N5RDze'] = False # (rad); ;
SubDyn['M9N6RDze'] = False # (rad); ;
SubDyn['M9N7RDze'] = False # (rad); ;
SubDyn['M9N8RDze'] = False # (rad); ;
SubDyn['M9N9RDze'] = False # (rad); ;
# Accelerations
SubDyn['M1N1TAxe'] = False # (m/s^2); xe component of the translational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2TAxe'] = False # (m/s^2); ;
SubDyn['M1N3TAxe'] = False # (m/s^2); ;
SubDyn['M1N4TAxe'] = False # (m/s^2); ;
SubDyn['M1N5TAxe'] = False # (m/s^2); ;
SubDyn['M1N6TAxe'] = False # (m/s^2); ;
SubDyn['M1N7TAxe'] = False # (m/s^2); ;
SubDyn['M1N8TAxe'] = False # (m/s^2); ;
SubDyn['M1N9TAxe'] = False # (m/s^2); ;
SubDyn['M2N1TAxe'] = False # (m/s^2); ;
SubDyn['M2N2TAxe'] = False # (m/s^2); ;
SubDyn['M2N3TAxe'] = False # (m/s^2); ;
SubDyn['M2N4TAxe'] = False # (m/s^2); ;
SubDyn['M2N5TAxe'] = False # (m/s^2); ;
SubDyn['M2N6TAxe'] = False # (m/s^2); ;
SubDyn['M2N7TAxe'] = False # (m/s^2); ;
SubDyn['M2N8TAxe'] = False # (m/s^2); ;
SubDyn['M2N9TAxe'] = False # (m/s^2); ;
SubDyn['M3N1TAxe'] = False # (m/s^2); ;
SubDyn['M3N2TAxe'] = False # (m/s^2); ;
SubDyn['M3N3TAxe'] = False # (m/s^2); ;
SubDyn['M3N4TAxe'] = False # (m/s^2); ;
SubDyn['M3N5TAxe'] = False # (m/s^2); ;
SubDyn['M3N6TAxe'] = False # (m/s^2); ;
SubDyn['M3N7TAxe'] = False # (m/s^2); ;
SubDyn['M3N8TAxe'] = False # (m/s^2); ;
SubDyn['M3N9TAxe'] = False # (m/s^2); ;
SubDyn['M4N1TAxe'] = False # (m/s^2); ;
SubDyn['M4N2TAxe'] = False # (m/s^2); ;
SubDyn['M4N3TAxe'] = False # (m/s^2); ;
SubDyn['M4N4TAxe'] = False # (m/s^2); ;
SubDyn['M4N5TAxe'] = False # (m/s^2); ;
SubDyn['M4N6TAxe'] = False # (m/s^2); ;
SubDyn['M4N7TAxe'] = False # (m/s^2); ;
SubDyn['M4N8TAxe'] = False # (m/s^2); ;
SubDyn['M4N9TAxe'] = False # (m/s^2); ;
SubDyn['M5N1TAxe'] = False # (m/s^2); ;
SubDyn['M5N2TAxe'] = False # (m/s^2); ;
SubDyn['M5N3TAxe'] = False # (m/s^2); ;
SubDyn['M5N4TAxe'] = False # (m/s^2); ;
SubDyn['M5N5TAxe'] = False # (m/s^2); ;
SubDyn['M5N6TAxe'] = False # (m/s^2); ;
SubDyn['M5N7TAxe'] = False # (m/s^2); ;
SubDyn['M5N8TAxe'] = False # (m/s^2); ;
SubDyn['M5N9TAxe'] = False # (m/s^2); ;
SubDyn['M6N1TAxe'] = False # (m/s^2); ;
SubDyn['M6N2TAxe'] = False # (m/s^2); ;
SubDyn['M6N3TAxe'] = False # (m/s^2); ;
SubDyn['M6N4TAxe'] = False # (m/s^2); ;
SubDyn['M6N5TAxe'] = False # (m/s^2); ;
SubDyn['M6N6TAxe'] = False # (m/s^2); ;
SubDyn['M6N7TAxe'] = False # (m/s^2); ;
SubDyn['M6N8TAxe'] = False # (m/s^2); ;
SubDyn['M6N9TAxe'] = False # (m/s^2); ;
SubDyn['M7N1TAxe'] = False # (m/s^2); ;
SubDyn['M7N2TAxe'] = False # (m/s^2); ;
SubDyn['M7N3TAxe'] = False # (m/s^2); ;
SubDyn['M7N4TAxe'] = False # (m/s^2); ;
SubDyn['M7N5TAxe'] = False # (m/s^2); ;
SubDyn['M7N6TAxe'] = False # (m/s^2); ;
SubDyn['M7N7TAxe'] = False # (m/s^2); ;
SubDyn['M7N8TAxe'] = False # (m/s^2); ;
SubDyn['M7N9TAxe'] = False # (m/s^2); ;
SubDyn['M8N1TAxe'] = False # (m/s^2); ;
SubDyn['M8N2TAxe'] = False # (m/s^2); ;
SubDyn['M8N3TAxe'] = False # (m/s^2); ;
SubDyn['M8N4TAxe'] = False # (m/s^2); ;
SubDyn['M8N5TAxe'] = False # (m/s^2); ;
SubDyn['M8N6TAxe'] = False # (m/s^2); ;
SubDyn['M8N7TAxe'] = False # (m/s^2); ;
SubDyn['M8N8TAxe'] = False # (m/s^2); ;
SubDyn['M8N9TAxe'] = False # (m/s^2); ;
SubDyn['M9N1TAxe'] = False # (m/s^2); ;
SubDyn['M9N2TAxe'] = False # (m/s^2); ;
SubDyn['M9N3TAxe'] = False # (m/s^2); ;
SubDyn['M9N4TAxe'] = False # (m/s^2); ;
SubDyn['M9N5TAxe'] = False # (m/s^2); ;
SubDyn['M9N6TAxe'] = False # (m/s^2); ;
SubDyn['M9N7TAxe'] = False # (m/s^2); ;
SubDyn['M9N8TAxe'] = False # (m/s^2); ;
SubDyn['M9N9TAxe'] = False # (m/s^2); ;
SubDyn['M1N1TAye'] = False # (m/s^2); ye component of the translational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2TAye'] = False # (m/s^2); ;
SubDyn['M1N3TAye'] = False # (m/s^2); ;
SubDyn['M1N4TAye'] = False # (m/s^2); ;
SubDyn['M1N5TAye'] = False # (m/s^2); ;
SubDyn['M1N6TAye'] = False # (m/s^2); ;
SubDyn['M1N7TAye'] = False # (m/s^2); ;
SubDyn['M1N8TAye'] = False # (m/s^2); ;
SubDyn['M1N9TAye'] = False # (m/s^2); ;
SubDyn['M2N1TAye'] = False # (m/s^2); ;
SubDyn['M2N2TAye'] = False # (m/s^2); ;
SubDyn['M2N3TAye'] = False # (m/s^2); ;
SubDyn['M2N4TAye'] = False # (m/s^2); ;
SubDyn['M2N5TAye'] = False # (m/s^2); ;
SubDyn['M2N6TAye'] = False # (m/s^2); ;
SubDyn['M2N7TAye'] = False # (m/s^2); ;
SubDyn['M2N8TAye'] = False # (m/s^2); ;
SubDyn['M2N9TAye'] = False # (m/s^2); ;
SubDyn['M3N1TAye'] = False # (m/s^2); ;
SubDyn['M3N2TAye'] = False # (m/s^2); ;
SubDyn['M3N3TAye'] = False # (m/s^2); ;
SubDyn['M3N4TAye'] = False # (m/s^2); ;
SubDyn['M3N5TAye'] = False # (m/s^2); ;
SubDyn['M3N6TAye'] = False # (m/s^2); ;
SubDyn['M3N7TAye'] = False # (m/s^2); ;
SubDyn['M3N8TAye'] = False # (m/s^2); ;
SubDyn['M3N9TAye'] = False # (m/s^2); ;
SubDyn['M4N1TAye'] = False # (m/s^2); ;
SubDyn['M4N2TAye'] = False # (m/s^2); ;
SubDyn['M4N3TAye'] = False # (m/s^2); ;
SubDyn['M4N4TAye'] = False # (m/s^2); ;
SubDyn['M4N5TAye'] = False # (m/s^2); ;
SubDyn['M4N6TAye'] = False # (m/s^2); ;
SubDyn['M4N7TAye'] = False # (m/s^2); ;
SubDyn['M4N8TAye'] = False # (m/s^2); ;
SubDyn['M4N9TAye'] = False # (m/s^2); ;
SubDyn['M5N1TAye'] = False # (m/s^2); ;
SubDyn['M5N2TAye'] = False # (m/s^2); ;
SubDyn['M5N3TAye'] = False # (m/s^2); ;
SubDyn['M5N4TAye'] = False # (m/s^2); ;
SubDyn['M5N5TAye'] = False # (m/s^2); ;
SubDyn['M5N6TAye'] = False # (m/s^2); ;
SubDyn['M5N7TAye'] = False # (m/s^2); ;
SubDyn['M5N8TAye'] = False # (m/s^2); ;
SubDyn['M5N9TAye'] = False # (m/s^2); ;
SubDyn['M6N1TAye'] = False # (m/s^2); ;
SubDyn['M6N2TAye'] = False # (m/s^2); ;
SubDyn['M6N3TAye'] = False # (m/s^2); ;
SubDyn['M6N4TAye'] = False # (m/s^2); ;
SubDyn['M6N5TAye'] = False # (m/s^2); ;
SubDyn['M6N6TAye'] = False # (m/s^2); ;
SubDyn['M6N7TAye'] = False # (m/s^2); ;
SubDyn['M6N8TAye'] = False # (m/s^2); ;
SubDyn['M6N9TAye'] = False # (m/s^2); ;
SubDyn['M7N1TAye'] = False # (m/s^2); ;
SubDyn['M7N2TAye'] = False # (m/s^2); ;
SubDyn['M7N3TAye'] = False # (m/s^2); ;
SubDyn['M7N4TAye'] = False # (m/s^2); ;
SubDyn['M7N5TAye'] = False # (m/s^2); ;
SubDyn['M7N6TAye'] = False # (m/s^2); ;
SubDyn['M7N7TAye'] = False # (m/s^2); ;
SubDyn['M7N8TAye'] = False # (m/s^2); ;
SubDyn['M7N9TAye'] = False # (m/s^2); ;
SubDyn['M8N1TAye'] = False # (m/s^2); ;
SubDyn['M8N2TAye'] = False # (m/s^2); ;
SubDyn['M8N3TAye'] = False # (m/s^2); ;
SubDyn['M8N4TAye'] = False # (m/s^2); ;
SubDyn['M8N5TAye'] = False # (m/s^2); ;
SubDyn['M8N6TAye'] = False # (m/s^2); ;
SubDyn['M8N7TAye'] = False # (m/s^2); ;
SubDyn['M8N8TAye'] = False # (m/s^2); ;
SubDyn['M8N9TAye'] = False # (m/s^2); ;
SubDyn['M9N1TAye'] = False # (m/s^2); ;
SubDyn['M9N2TAye'] = False # (m/s^2); ;
SubDyn['M9N3TAye'] = False # (m/s^2); ;
SubDyn['M9N4TAye'] = False # (m/s^2); ;
SubDyn['M9N5TAye'] = False # (m/s^2); ;
SubDyn['M9N6TAye'] = False # (m/s^2); ;
SubDyn['M9N7TAye'] = False # (m/s^2); ;
SubDyn['M9N8TAye'] = False # (m/s^2); ;
SubDyn['M9N9TAye'] = False # (m/s^2); ;
SubDyn['M1N1TAze'] = False # (m/s^2); ze component of the translational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2TAze'] = False # (m/s^2); ;
SubDyn['M1N3TAze'] = False # (m/s^2); ;
SubDyn['M1N4TAze'] = False # (m/s^2); ;
SubDyn['M1N5TAze'] = False # (m/s^2); ;
SubDyn['M1N6TAze'] = False # (m/s^2); ;
SubDyn['M1N7TAze'] = False # (m/s^2); ;
SubDyn['M1N8TAze'] = False # (m/s^2); ;
SubDyn['M1N9TAze'] = False # (m/s^2); ;
SubDyn['M2N1TAze'] = False # (m/s^2); ;
SubDyn['M2N2TAze'] = False # (m/s^2); ;
SubDyn['M2N3TAze'] = False # (m/s^2); ;
SubDyn['M2N4TAze'] = False # (m/s^2); ;
SubDyn['M2N5TAze'] = False # (m/s^2); ;
SubDyn['M2N6TAze'] = False # (m/s^2); ;
SubDyn['M2N7TAze'] = False # (m/s^2); ;
SubDyn['M2N8TAze'] = False # (m/s^2); ;
SubDyn['M2N9TAze'] = False # (m/s^2); ;
SubDyn['M3N1TAze'] = False # (m/s^2); ;
SubDyn['M3N2TAze'] = False # (m/s^2); ;
SubDyn['M3N3TAze'] = False # (m/s^2); ;
SubDyn['M3N4TAze'] = False # (m/s^2); ;
SubDyn['M3N5TAze'] = False # (m/s^2); ;
SubDyn['M3N6TAze'] = False # (m/s^2); ;
SubDyn['M3N7TAze'] = False # (m/s^2); ;
SubDyn['M3N8TAze'] = False # (m/s^2); ;
SubDyn['M3N9TAze'] = False # (m/s^2); ;
SubDyn['M4N1TAze'] = False # (m/s^2); ;
SubDyn['M4N2TAze'] = False # (m/s^2); ;
SubDyn['M4N3TAze'] = False # (m/s^2); ;
SubDyn['M4N4TAze'] = False # (m/s^2); ;
SubDyn['M4N5TAze'] = False # (m/s^2); ;
SubDyn['M4N6TAze'] = False # (m/s^2); ;
SubDyn['M4N7TAze'] = False # (m/s^2); ;
SubDyn['M4N8TAze'] = False # (m/s^2); ;
SubDyn['M4N9TAze'] = False # (m/s^2); ;
SubDyn['M5N1TAze'] = False # (m/s^2); ;
SubDyn['M5N2TAze'] = False # (m/s^2); ;
SubDyn['M5N3TAze'] = False # (m/s^2); ;
SubDyn['M5N4TAze'] = False # (m/s^2); ;
SubDyn['M5N5TAze'] = False # (m/s^2); ;
SubDyn['M5N6TAze'] = False # (m/s^2); ;
SubDyn['M5N7TAze'] = False # (m/s^2); ;
SubDyn['M5N8TAze'] = False # (m/s^2); ;
SubDyn['M5N9TAze'] = False # (m/s^2); ;
SubDyn['M6N1TAze'] = False # (m/s^2); ;
SubDyn['M6N2TAze'] = False # (m/s^2); ;
SubDyn['M6N3TAze'] = False # (m/s^2); ;
SubDyn['M6N4TAze'] = False # (m/s^2); ;
SubDyn['M6N5TAze'] = False # (m/s^2); ;
SubDyn['M6N6TAze'] = False # (m/s^2); ;
SubDyn['M6N7TAze'] = False # (m/s^2); ;
SubDyn['M6N8TAze'] = False # (m/s^2); ;
SubDyn['M6N9TAze'] = False # (m/s^2); ;
SubDyn['M7N1TAze'] = False # (m/s^2); ;
SubDyn['M7N2TAze'] = False # (m/s^2); ;
SubDyn['M7N3TAze'] = False # (m/s^2); ;
SubDyn['M7N4TAze'] = False # (m/s^2); ;
SubDyn['M7N5TAze'] = False # (m/s^2); ;
SubDyn['M7N6TAze'] = False # (m/s^2); ;
SubDyn['M7N7TAze'] = False # (m/s^2); ;
SubDyn['M7N8TAze'] = False # (m/s^2); ;
SubDyn['M7N9TAze'] = False # (m/s^2); ;
SubDyn['M8N1TAze'] = False # (m/s^2); ;
SubDyn['M8N2TAze'] = False # (m/s^2); ;
SubDyn['M8N3TAze'] = False # (m/s^2); ;
SubDyn['M8N4TAze'] = False # (m/s^2); ;
SubDyn['M8N5TAze'] = False # (m/s^2); ;
SubDyn['M8N6TAze'] = False # (m/s^2); ;
SubDyn['M8N7TAze'] = False # (m/s^2); ;
SubDyn['M8N8TAze'] = False # (m/s^2); ;
SubDyn['M8N9TAze'] = False # (m/s^2); ;
SubDyn['M9N1TAze'] = False # (m/s^2); ;
SubDyn['M9N2TAze'] = False # (m/s^2); ;
SubDyn['M9N3TAze'] = False # (m/s^2); ;
SubDyn['M9N4TAze'] = False # (m/s^2); ;
SubDyn['M9N5TAze'] = False # (m/s^2); ;
SubDyn['M9N6TAze'] = False # (m/s^2); ;
SubDyn['M9N7TAze'] = False # (m/s^2); ;
SubDyn['M9N8TAze'] = False # (m/s^2); ;
SubDyn['M9N9TAze'] = False # (m/s^2); ;
SubDyn['M1N1RAxe'] = False # (rad/s^2); xe component of the rotational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RAxe'] = False # (rad/s^2); ;
SubDyn['M1N3RAxe'] = False # (rad/s^2); ;
SubDyn['M1N4RAxe'] = False # (rad/s^2); ;
SubDyn['M1N5RAxe'] = False # (rad/s^2); ;
SubDyn['M1N6RAxe'] = False # (rad/s^2); ;
SubDyn['M1N7RAxe'] = False # (rad/s^2); ;
SubDyn['M1N8RAxe'] = False # (rad/s^2); ;
SubDyn['M1N9RAxe'] = False # (rad/s^2); ;
SubDyn['M2N1RAxe'] = False # (rad/s^2); ;
SubDyn['M2N2RAxe'] = False # (rad/s^2); ;
SubDyn['M2N3RAxe'] = False # (rad/s^2); ;
SubDyn['M2N4RAxe'] = False # (rad/s^2); ;
SubDyn['M2N5RAxe'] = False # (rad/s^2); ;
SubDyn['M2N6RAxe'] = False # (rad/s^2); ;
SubDyn['M2N7RAxe'] = False # (rad/s^2); ;
SubDyn['M2N8RAxe'] = False # (rad/s^2); ;
SubDyn['M2N9RAxe'] = False # (rad/s^2); ;
SubDyn['M3N1RAxe'] = False # (rad/s^2); ;
SubDyn['M3N2RAxe'] = False # (rad/s^2); ;
SubDyn['M3N3RAxe'] = False # (rad/s^2); ;
SubDyn['M3N4RAxe'] = False # (rad/s^2); ;
SubDyn['M3N5RAxe'] = False # (rad/s^2); ;
SubDyn['M3N6RAxe'] = False # (rad/s^2); ;
SubDyn['M3N7RAxe'] = False # (rad/s^2); ;
SubDyn['M3N8RAxe'] = False # (rad/s^2); ;
SubDyn['M3N9RAxe'] = False # (rad/s^2); ;
SubDyn['M4N1RAxe'] = False # (rad/s^2); ;
SubDyn['M4N2RAxe'] = False # (rad/s^2); ;
SubDyn['M4N3RAxe'] = False # (rad/s^2); ;
SubDyn['M4N4RAxe'] = False # (rad/s^2); ;
SubDyn['M4N5RAxe'] = False # (rad/s^2); ;
SubDyn['M4N6RAxe'] = False # (rad/s^2); ;
SubDyn['M4N7RAxe'] = False # (rad/s^2); ;
SubDyn['M4N8RAxe'] = False # (rad/s^2); ;
SubDyn['M4N9RAxe'] = False # (rad/s^2); ;
SubDyn['M5N1RAxe'] = False # (rad/s^2); ;
SubDyn['M5N2RAxe'] = False # (rad/s^2); ;
SubDyn['M5N3RAxe'] = False # (rad/s^2); ;
SubDyn['M5N4RAxe'] = False # (rad/s^2); ;
SubDyn['M5N5RAxe'] = False # (rad/s^2); ;
SubDyn['M5N6RAxe'] = False # (rad/s^2); ;
SubDyn['M5N7RAxe'] = False # (rad/s^2); ;
SubDyn['M5N8RAxe'] = False # (rad/s^2); ;
SubDyn['M5N9RAxe'] = False # (rad/s^2); ;
SubDyn['M6N1RAxe'] = False # (rad/s^2); ;
SubDyn['M6N2RAxe'] = False # (rad/s^2); ;
SubDyn['M6N3RAxe'] = False # (rad/s^2); ;
SubDyn['M6N4RAxe'] = False # (rad/s^2); ;
SubDyn['M6N5RAxe'] = False # (rad/s^2); ;
SubDyn['M6N6RAxe'] = False # (rad/s^2); ;
SubDyn['M6N7RAxe'] = False # (rad/s^2); ;
SubDyn['M6N8RAxe'] = False # (rad/s^2); ;
SubDyn['M6N9RAxe'] = False # (rad/s^2); ;
SubDyn['M7N1RAxe'] = False # (rad/s^2); ;
SubDyn['M7N2RAxe'] = False # (rad/s^2); ;
SubDyn['M7N3RAxe'] = False # (rad/s^2); ;
SubDyn['M7N4RAxe'] = False # (rad/s^2); ;
SubDyn['M7N5RAxe'] = False # (rad/s^2); ;
SubDyn['M7N6RAxe'] = False # (rad/s^2); ;
SubDyn['M7N7RAxe'] = False # (rad/s^2); ;
SubDyn['M7N8RAxe'] = False # (rad/s^2); ;
SubDyn['M7N9RAxe'] = False # (rad/s^2); ;
SubDyn['M8N1RAxe'] = False # (rad/s^2); ;
SubDyn['M8N2RAxe'] = False # (rad/s^2); ;
SubDyn['M8N3RAxe'] = False # (rad/s^2); ;
SubDyn['M8N4RAxe'] = False # (rad/s^2); ;
SubDyn['M8N5RAxe'] = False # (rad/s^2); ;
SubDyn['M8N6RAxe'] = False # (rad/s^2); ;
SubDyn['M8N7RAxe'] = False # (rad/s^2); ;
SubDyn['M8N8RAxe'] = False # (rad/s^2); ;
SubDyn['M8N9RAxe'] = False # (rad/s^2); ;
SubDyn['M9N1RAxe'] = False # (rad/s^2); ;
SubDyn['M9N2RAxe'] = False # (rad/s^2); ;
SubDyn['M9N3RAxe'] = False # (rad/s^2); ;
SubDyn['M9N4RAxe'] = False # (rad/s^2); ;
SubDyn['M9N5RAxe'] = False # (rad/s^2); ;
SubDyn['M9N6RAxe'] = False # (rad/s^2); ;
SubDyn['M9N7RAxe'] = False # (rad/s^2); ;
SubDyn['M9N8RAxe'] = False # (rad/s^2); ;
SubDyn['M9N9RAxe'] = False # (rad/s^2); ;
SubDyn['M1N1RAye'] = False # (rad/s^2); ye component of the rotational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RAye'] = False # (rad/s^2); ;
SubDyn['M1N3RAye'] = False # (rad/s^2); ;
SubDyn['M1N4RAye'] = False # (rad/s^2); ;
SubDyn['M1N5RAye'] = False # (rad/s^2); ;
SubDyn['M1N6RAye'] = False # (rad/s^2); ;
SubDyn['M1N7RAye'] = False # (rad/s^2); ;
SubDyn['M1N8RAye'] = False # (rad/s^2); ;
SubDyn['M1N9RAye'] = False # (rad/s^2); ;
SubDyn['M2N1RAye'] = False # (rad/s^2); ;
SubDyn['M2N2RAye'] = False # (rad/s^2); ;
SubDyn['M2N3RAye'] = False # (rad/s^2); ;
SubDyn['M2N4RAye'] = False # (rad/s^2); ;
SubDyn['M2N5RAye'] = False # (rad/s^2); ;
SubDyn['M2N6RAye'] = False # (rad/s^2); ;
SubDyn['M2N7RAye'] = False # (rad/s^2); ;
SubDyn['M2N8RAye'] = False # (rad/s^2); ;
SubDyn['M2N9RAye'] = False # (rad/s^2); ;
SubDyn['M3N1RAye'] = False # (rad/s^2); ;
SubDyn['M3N2RAye'] = False # (rad/s^2); ;
SubDyn['M3N3RAye'] = False # (rad/s^2); ;
SubDyn['M3N4RAye'] = False # (rad/s^2); ;
SubDyn['M3N5RAye'] = False # (rad/s^2); ;
SubDyn['M3N6RAye'] = False # (rad/s^2); ;
SubDyn['M3N7RAye'] = False # (rad/s^2); ;
SubDyn['M3N8RAye'] = False # (rad/s^2); ;
SubDyn['M3N9RAye'] = False # (rad/s^2); ;
SubDyn['M4N1RAye'] = False # (rad/s^2); ;
SubDyn['M4N2RAye'] = False # (rad/s^2); ;
SubDyn['M4N3RAye'] = False # (rad/s^2); ;
SubDyn['M4N4RAye'] = False # (rad/s^2); ;
SubDyn['M4N5RAye'] = False # (rad/s^2); ;
SubDyn['M4N6RAye'] = False # (rad/s^2); ;
SubDyn['M4N7RAye'] = False # (rad/s^2); ;
SubDyn['M4N8RAye'] = False # (rad/s^2); ;
SubDyn['M4N9RAye'] = False # (rad/s^2); ;
SubDyn['M5N1RAye'] = False # (rad/s^2); ;
SubDyn['M5N2RAye'] = False # (rad/s^2); ;
SubDyn['M5N3RAye'] = False # (rad/s^2); ;
SubDyn['M5N4RAye'] = False # (rad/s^2); ;
SubDyn['M5N5RAye'] = False # (rad/s^2); ;
SubDyn['M5N6RAye'] = False # (rad/s^2); ;
SubDyn['M5N7RAye'] = False # (rad/s^2); ;
SubDyn['M5N8RAye'] = False # (rad/s^2); ;
SubDyn['M5N9RAye'] = False # (rad/s^2); ;
SubDyn['M6N1RAye'] = False # (rad/s^2); ;
SubDyn['M6N2RAye'] = False # (rad/s^2); ;
SubDyn['M6N3RAye'] = False # (rad/s^2); ;
SubDyn['M6N4RAye'] = False # (rad/s^2); ;
SubDyn['M6N5RAye'] = False # (rad/s^2); ;
SubDyn['M6N6RAye'] = False # (rad/s^2); ;
SubDyn['M6N7RAye'] = False # (rad/s^2); ;
SubDyn['M6N8RAye'] = False # (rad/s^2); ;
SubDyn['M6N9RAye'] = False # (rad/s^2); ;
SubDyn['M7N1RAye'] = False # (rad/s^2); ;
SubDyn['M7N2RAye'] = False # (rad/s^2); ;
SubDyn['M7N3RAye'] = False # (rad/s^2); ;
SubDyn['M7N4RAye'] = False # (rad/s^2); ;
SubDyn['M7N5RAye'] = False # (rad/s^2); ;
SubDyn['M7N6RAye'] = False # (rad/s^2); ;
SubDyn['M7N7RAye'] = False # (rad/s^2); ;
SubDyn['M7N8RAye'] = False # (rad/s^2); ;
SubDyn['M7N9RAye'] = False # (rad/s^2); ;
SubDyn['M8N1RAye'] = False # (rad/s^2); ;
SubDyn['M8N2RAye'] = False # (rad/s^2); ;
SubDyn['M8N3RAye'] = False # (rad/s^2); ;
SubDyn['M8N4RAye'] = False # (rad/s^2); ;
SubDyn['M8N5RAye'] = False # (rad/s^2); ;
SubDyn['M8N6RAye'] = False # (rad/s^2); ;
SubDyn['M8N7RAye'] = False # (rad/s^2); ;
SubDyn['M8N8RAye'] = False # (rad/s^2); ;
SubDyn['M8N9RAye'] = False # (rad/s^2); ;
SubDyn['M9N1RAye'] = False # (rad/s^2); ;
SubDyn['M9N2RAye'] = False # (rad/s^2); ;
SubDyn['M9N3RAye'] = False # (rad/s^2); ;
SubDyn['M9N4RAye'] = False # (rad/s^2); ;
SubDyn['M9N5RAye'] = False # (rad/s^2); ;
SubDyn['M9N6RAye'] = False # (rad/s^2); ;
SubDyn['M9N7RAye'] = False # (rad/s^2); ;
SubDyn['M9N8RAye'] = False # (rad/s^2); ;
SubDyn['M9N9RAye'] = False # (rad/s^2); ;
SubDyn['M1N1RAze'] = False # (rad/s^2); ze component of the rotational acceleration displacement at Node Nj of member Mi-Element Reference System;
SubDyn['M1N2RAze'] = False # (rad/s^2); ;
SubDyn['M1N3RAze'] = False # (rad/s^2); ;
SubDyn['M1N4RAze'] = False # (rad/s^2); ;
SubDyn['M1N5RAze'] = False # (rad/s^2); ;
SubDyn['M1N6RAze'] = False # (rad/s^2); ;
SubDyn['M1N7RAze'] = False # (rad/s^2); ;
SubDyn['M1N8RAze'] = False # (rad/s^2); ;
SubDyn['M1N9RAze'] = False # (rad/s^2); ;
SubDyn['M2N1RAze'] = False # (rad/s^2); ;
SubDyn['M2N2RAze'] = False # (rad/s^2); ;
SubDyn['M2N3RAze'] = False # (rad/s^2); ;
SubDyn['M2N4RAze'] = False # (rad/s^2); ;
SubDyn['M2N5RAze'] = False # (rad/s^2); ;
SubDyn['M2N6RAze'] = False # (rad/s^2); ;
SubDyn['M2N7RAze'] = False # (rad/s^2); ;
SubDyn['M2N8RAze'] = False # (rad/s^2); ;
SubDyn['M2N9RAze'] = False # (rad/s^2); ;
SubDyn['M3N1RAze'] = False # (rad/s^2); ;
SubDyn['M3N2RAze'] = False # (rad/s^2); ;
SubDyn['M3N3RAze'] = False # (rad/s^2); ;
SubDyn['M3N4RAze'] = False # (rad/s^2); ;
SubDyn['M3N5RAze'] = False # (rad/s^2); ;
SubDyn['M3N6RAze'] = False # (rad/s^2); ;
SubDyn['M3N7RAze'] = False # (rad/s^2); ;
SubDyn['M3N8RAze'] = False # (rad/s^2); ;
SubDyn['M3N9RAze'] = False # (rad/s^2); ;
SubDyn['M4N1RAze'] = False # (rad/s^2); ;
SubDyn['M4N2RAze'] = False # (rad/s^2); ;
SubDyn['M4N3RAze'] = False # (rad/s^2); ;
SubDyn['M4N4RAze'] = False # (rad/s^2); ;
SubDyn['M4N5RAze'] = False # (rad/s^2); ;
SubDyn['M4N6RAze'] = False # (rad/s^2); ;
SubDyn['M4N7RAze'] = False # (rad/s^2); ;
SubDyn['M4N8RAze'] = False # (rad/s^2); ;
SubDyn['M4N9RAze'] = False # (rad/s^2); ;
SubDyn['M5N1RAze'] = False # (rad/s^2); ;
SubDyn['M5N2RAze'] = False # (rad/s^2); ;
SubDyn['M5N3RAze'] = False # (rad/s^2); ;
SubDyn['M5N4RAze'] = False # (rad/s^2); ;
SubDyn['M5N5RAze'] = False # (rad/s^2); ;
SubDyn['M5N6RAze'] = False # (rad/s^2); ;
SubDyn['M5N7RAze'] = False # (rad/s^2); ;
SubDyn['M5N8RAze'] = False # (rad/s^2); ;
SubDyn['M5N9RAze'] = False # (rad/s^2); ;
SubDyn['M6N1RAze'] = False # (rad/s^2); ;
SubDyn['M6N2RAze'] = False # (rad/s^2); ;
SubDyn['M6N3RAze'] = False # (rad/s^2); ;
SubDyn['M6N4RAze'] = False # (rad/s^2); ;
SubDyn['M6N5RAze'] = False # (rad/s^2); ;
SubDyn['M6N6RAze'] = False # (rad/s^2); ;
SubDyn['M6N7RAze'] = False # (rad/s^2); ;
SubDyn['M6N8RAze'] = False # (rad/s^2); ;
SubDyn['M6N9RAze'] = False # (rad/s^2); ;
SubDyn['M7N1RAze'] = False # (rad/s^2); ;
SubDyn['M7N2RAze'] = False # (rad/s^2); ;
SubDyn['M7N3RAze'] = False # (rad/s^2); ;
SubDyn['M7N4RAze'] = False # (rad/s^2); ;
SubDyn['M7N5RAze'] = False # (rad/s^2); ;
SubDyn['M7N6RAze'] = False # (rad/s^2); ;
SubDyn['M7N7RAze'] = False # (rad/s^2); ;
SubDyn['M7N8RAze'] = False # (rad/s^2); ;
SubDyn['M7N9RAze'] = False # (rad/s^2); ;
SubDyn['M8N1RAze'] = False # (rad/s^2); ;
SubDyn['M8N2RAze'] = False # (rad/s^2); ;
SubDyn['M8N3RAze'] = False # (rad/s^2); ;
SubDyn['M8N4RAze'] = False # (rad/s^2); ;
SubDyn['M8N5RAze'] = False # (rad/s^2); ;
SubDyn['M8N6RAze'] = False # (rad/s^2); ;
SubDyn['M8N7RAze'] = False # (rad/s^2); ;
SubDyn['M8N8RAze'] = False # (rad/s^2); ;
SubDyn['M8N9RAze'] = False # (rad/s^2); ;
SubDyn['M9N1RAze'] = False # (rad/s^2); ;
SubDyn['M9N2RAze'] = False # (rad/s^2); ;
SubDyn['M9N3RAze'] = False # (rad/s^2); ;
SubDyn['M9N4RAze'] = False # (rad/s^2); ;
SubDyn['M9N5RAze'] = False # (rad/s^2); ;
SubDyn['M9N6RAze'] = False # (rad/s^2); ;
SubDyn['M9N7RAze'] = False # (rad/s^2); ;
SubDyn['M9N8RAze'] = False # (rad/s^2); ;
SubDyn['M9N9RAze'] = False # (rad/s^2); ;
# Reactions
SubDyn['ReactFXss'] = False # (N); Base Reaction Force along Xss;
SubDyn['ReactFYss'] = False # (N); Base Reaction Force along Yss;
SubDyn['ReactFZss'] = False # (N); Base Reaction Force along Zss;
SubDyn['ReactMXss'] = False # (Nm); Base Reaction Moment along Xss;
SubDyn['ReactMYss'] = False # (Nm); Base Reaction Moment along Yss;
SubDyn['ReactMZss'] = False # (Nm); Base Reaction Moment along Zss;
SubDyn['IntfFXss'] = False # (N); Interface Reaction Force along Xss;
SubDyn['IntfFYss'] = False # (N); Interface Reaction Force along Yss;
SubDyn['IntfFZss'] = False # (N); Interface Reaction Force along Zss;
SubDyn['IntfMXss'] = False # (Nm); Interface Reaction Moment along Xss;
SubDyn['IntfMYss'] = False # (Nm); Interface Reaction Moment along Yss;
SubDyn['IntfMZss'] = False # (Nm); Interface Reaction Moment along Zss;
# Interface Deflections
SubDyn['IntfTDXss'] = False # (m); Interface Deflection along Xss;
SubDyn['IntfTDYss'] = False # (m); Interface Deflection along Yss;
SubDyn['IntfTDZss'] = False # (m); Interface Deflection along Zss;
SubDyn['IntfRDXss'] = False # (rad); Interface Angular Deflection along Xss;
SubDyn['IntfRDYss'] = False # (rad); Interface Angular Deflection along Yss;
SubDyn['IntfRDZss'] = False # (rad); Interface Angular Deflection along Zss;
# Interface Accelerations
SubDyn['IntfTAXss'] = False # (m/s^2); Interface Acceleration along Xss;
SubDyn['IntfTAYss'] = False # (m/s^2); Interface Acceleration along Yss;
SubDyn['IntfTAZss'] = False # (m/s^2); Interface Acceleration along Zss;
SubDyn['IntfRAXss'] = False # (rad/s^2); Interface Angular Acceleration along Xss;
SubDyn['IntfRAYss'] = False # (rad/s^2); Interface Angular Acceleration along Yss;
SubDyn['IntfRAZss'] = False # (rad/s^2); Interface Angular Acceleration along Zss;
# Modal Parameters
SubDyn['SSqm01'] = False # (--); Modal Parameter (01-99) values;
SubDyn['SSqm02'] = False # (--); ;
SubDyn['SSqm03'] = False # (--); ;
SubDyn['SSqm04'] = False # (--); ;
SubDyn['SSqm05'] = False # (--); ;
SubDyn['SSqm06'] = False # (--); ;
SubDyn['SSqm07'] = False # (--); ;
SubDyn['SSqm08'] = False # (--); ;
SubDyn['SSqm09'] = False # (--); ;
SubDyn['SSqm10'] = False # (--); ;
SubDyn['SSqm11'] = False # (--); ;
SubDyn['SSqm12'] = False # (--); ;
SubDyn['SSqm13'] = False # (--); ;
SubDyn['SSqm14'] = False # (--); ;
SubDyn['SSqm15'] = False # (--); ;
SubDyn['SSqm16'] = False # (--); ;
SubDyn['SSqm17'] = False # (--); ;
SubDyn['SSqm18'] = False # (--); ;
SubDyn['SSqm19'] = False # (--); ;
SubDyn['SSqm20'] = False # (--); ;
SubDyn['SSqm21'] = False # (--); ;
SubDyn['SSqm22'] = False # (--); ;
SubDyn['SSqm23'] = False # (--); ;
SubDyn['SSqm24'] = False # (--); ;
SubDyn['SSqm25'] = False # (--); ;
SubDyn['SSqm26'] = False # (--); ;
SubDyn['SSqm27'] = False # (--); ;
SubDyn['SSqm28'] = False # (--); ;
SubDyn['SSqm29'] = False # (--); ;
SubDyn['SSqm30'] = False # (--); ;
SubDyn['SSqm31'] = False # (--); ;
SubDyn['SSqm32'] = False # (--); ;
SubDyn['SSqm33'] = False # (--); ;
SubDyn['SSqm34'] = False # (--); ;
SubDyn['SSqm35'] = False # (--); ;
SubDyn['SSqm36'] = False # (--); ;
SubDyn['SSqm37'] = False # (--); ;
SubDyn['SSqm38'] = False # (--); ;
SubDyn['SSqm39'] = False # (--); ;
SubDyn['SSqm40'] = False # (--); ;
SubDyn['SSqm41'] = False # (--); ;
SubDyn['SSqm42'] = False # (--); ;
SubDyn['SSqm43'] = False # (--); ;
SubDyn['SSqm44'] = False # (--); ;
SubDyn['SSqm45'] = False # (--); ;
SubDyn['SSqm46'] = False # (--); ;
SubDyn['SSqm47'] = False # (--); ;
SubDyn['SSqm48'] = False # (--); ;
SubDyn['SSqm49'] = False # (--); ;
SubDyn['SSqm50'] = False # (--); ;
SubDyn['SSqm51'] = False # (--); ;
SubDyn['SSqm52'] = False # (--); ;
SubDyn['SSqm53'] = False # (--); ;
SubDyn['SSqm54'] = False # (--); ;
SubDyn['SSqm55'] = False # (--); ;
SubDyn['SSqm56'] = False # (--); ;
SubDyn['SSqm57'] = False # (--); ;
SubDyn['SSqm58'] = False # (--); ;
SubDyn['SSqm59'] = False # (--); ;
SubDyn['SSqm60'] = False # (--); ;
SubDyn['SSqm61'] = False # (--); ;
SubDyn['SSqm62'] = False # (--); ;
SubDyn['SSqm63'] = False # (--); ;
SubDyn['SSqm64'] = False # (--); ;
SubDyn['SSqm65'] = False # (--); ;
SubDyn['SSqm66'] = False # (--); ;
SubDyn['SSqm67'] = False # (--); ;
SubDyn['SSqm68'] = False # (--); ;
SubDyn['SSqm69'] = False # (--); ;
SubDyn['SSqm70'] = False # (--); ;
SubDyn['SSqm71'] = False # (--); ;
SubDyn['SSqm72'] = False # (--); ;
SubDyn['SSqm73'] = False # (--); ;
SubDyn['SSqm74'] = False # (--); ;
SubDyn['SSqm75'] = False # (--); ;
SubDyn['SSqm76'] = False # (--); ;
SubDyn['SSqm77'] = False # (--); ;
SubDyn['SSqm78'] = False # (--); ;
SubDyn['SSqm79'] = False # (--); ;
SubDyn['SSqm80'] = False # (--); ;
SubDyn['SSqm81'] = False # (--); ;
SubDyn['SSqm82'] = False # (--); ;
SubDyn['SSqm83'] = False # (--); ;
SubDyn['SSqm84'] = False # (--); ;
SubDyn['SSqm85'] = False # (--); ;
SubDyn['SSqm86'] = False # (--); ;
SubDyn['SSqm87'] = False # (--); ;
SubDyn['SSqm88'] = False # (--); ;
SubDyn['SSqm89'] = False # (--); ;
SubDyn['SSqm90'] = False # (--); ;
SubDyn['SSqm91'] = False # (--); ;
SubDyn['SSqm92'] = False # (--); ;
SubDyn['SSqm93'] = False # (--); ;
SubDyn['SSqm94'] = False # (--); ;
SubDyn['SSqm95'] = False # (--); ;
SubDyn['SSqm96'] = False # (--); ;
SubDyn['SSqm97'] = False # (--); ;
SubDyn['SSqm98'] = False # (--); ;
SubDyn['SSqm99'] = False # (--); ;
SubDyn['SSqmd01'] = False # (1/s); Modal Parameter (01-99) time derivatives;
SubDyn['SSqmd02'] = False # (1/s); ;
SubDyn['SSqmd03'] = False # (1/s); ;
SubDyn['SSqmd04'] = False # (1/s); ;
SubDyn['SSqmd05'] = False # (1/s); ;
SubDyn['SSqmd06'] = False # (1/s); ;
SubDyn['SSqmd07'] = False # (1/s); ;
SubDyn['SSqmd08'] = False # (1/s); ;
SubDyn['SSqmd09'] = False # (1/s); ;
SubDyn['SSqmd10'] = False # (1/s); ;
SubDyn['SSqmd11'] = False # (1/s); ;
SubDyn['SSqmd12'] = False # (1/s); ;
SubDyn['SSqmd13'] = False # (1/s); ;
SubDyn['SSqmd14'] = False # (1/s); ;
SubDyn['SSqmd15'] = False # (1/s); ;
SubDyn['SSqmd16'] = False # (1/s); ;
SubDyn['SSqmd17'] = False # (1/s); ;
SubDyn['SSqmd18'] = False # (1/s); ;
SubDyn['SSqmd19'] = False # (1/s); ;
SubDyn['SSqmd20'] = False # (1/s); ;
SubDyn['SSqmd21'] = False # (1/s); ;
SubDyn['SSqmd22'] = False # (1/s); ;
SubDyn['SSqmd23'] = False # (1/s); ;
SubDyn['SSqmd24'] = False # (1/s); ;
SubDyn['SSqmd25'] = False # (1/s); ;
SubDyn['SSqmd26'] = False # (1/s); ;
SubDyn['SSqmd27'] = False # (1/s); ;
SubDyn['SSqmd28'] = False # (1/s); ;
SubDyn['SSqmd29'] = False # (1/s); ;
SubDyn['SSqmd30'] = False # (1/s); ;
SubDyn['SSqmd31'] = False # (1/s); ;
SubDyn['SSqmd32'] = False # (1/s); ;
SubDyn['SSqmd33'] = False # (1/s); ;
SubDyn['SSqmd34'] = False # (1/s); ;
SubDyn['SSqmd35'] = False # (1/s); ;
SubDyn['SSqmd36'] = False # (1/s); ;
SubDyn['SSqmd37'] = False # (1/s); ;
SubDyn['SSqmd38'] = False # (1/s); ;
SubDyn['SSqmd39'] = False # (1/s); ;
SubDyn['SSqmd40'] = False # (1/s); ;
SubDyn['SSqmd41'] = False # (1/s); ;
SubDyn['SSqmd42'] = False # (1/s); ;
SubDyn['SSqmd43'] = False # (1/s); ;
SubDyn['SSqmd44'] = False # (1/s); ;
SubDyn['SSqmd45'] = False # (1/s); ;
SubDyn['SSqmd46'] = False # (1/s); ;
SubDyn['SSqmd47'] = False # (1/s); ;
SubDyn['SSqmd48'] = False # (1/s); ;
SubDyn['SSqmd49'] = False # (1/s); ;
SubDyn['SSqmd50'] = False # (1/s); ;
SubDyn['SSqmd51'] = False # (1/s); ;
SubDyn['SSqmd52'] = False # (1/s); ;
SubDyn['SSqmd53'] = False # (1/s); ;
SubDyn['SSqmd54'] = False # (1/s); ;
SubDyn['SSqmd55'] = False # (1/s); ;
SubDyn['SSqmd56'] = False # (1/s); ;
SubDyn['SSqmd57'] = False # (1/s); ;
SubDyn['SSqmd58'] = False # (1/s); ;
SubDyn['SSqmd59'] = False # (1/s); ;
SubDyn['SSqmd60'] = False # (1/s); ;
SubDyn['SSqmd61'] = False # (1/s); ;
SubDyn['SSqmd62'] = False # (1/s); ;
SubDyn['SSqmd63'] = False # (1/s); ;
SubDyn['SSqmd64'] = False # (1/s); ;
SubDyn['SSqmd65'] = False # (1/s); ;
SubDyn['SSqmd66'] = False # (1/s); ;
SubDyn['SSqmd67'] = False # (1/s); ;
SubDyn['SSqmd68'] = False # (1/s); ;
SubDyn['SSqmd69'] = False # (1/s); ;
SubDyn['SSqmd70'] = False # (1/s); ;
SubDyn['SSqmd71'] = False # (1/s); ;
SubDyn['SSqmd72'] = False # (1/s); ;
SubDyn['SSqmd73'] = False # (1/s); ;
SubDyn['SSqmd74'] = False # (1/s); ;
SubDyn['SSqmd75'] = False # (1/s); ;
SubDyn['SSqmd76'] = False # (1/s); ;
SubDyn['SSqmd77'] = False # (1/s); ;
SubDyn['SSqmd78'] = False # (1/s); ;
SubDyn['SSqmd79'] = False # (1/s); ;
SubDyn['SSqmd80'] = False # (1/s); ;
SubDyn['SSqmd81'] = False # (1/s); ;
SubDyn['SSqmd82'] = False # (1/s); ;
SubDyn['SSqmd83'] = False # (1/s); ;
SubDyn['SSqmd84'] = False # (1/s); ;
SubDyn['SSqmd85'] = False # (1/s); ;
SubDyn['SSqmd86'] = False # (1/s); ;
SubDyn['SSqmd87'] = False # (1/s); ;
SubDyn['SSqmd88'] = False # (1/s); ;
SubDyn['SSqmd89'] = False # (1/s); ;
SubDyn['SSqmd90'] = False # (1/s); ;
SubDyn['SSqmd91'] = False # (1/s); ;
SubDyn['SSqmd92'] = False # (1/s); ;
SubDyn['SSqmd93'] = False # (1/s); ;
SubDyn['SSqmd94'] = False # (1/s); ;
SubDyn['SSqmd95'] = False # (1/s); ;
SubDyn['SSqmd96'] = False # (1/s); ;
SubDyn['SSqmd97'] = False # (1/s); ;
SubDyn['SSqmd98'] = False # (1/s); ;
SubDyn['SSqmd99'] = False # (1/s); ;
SubDyn['SSqmdd01'] = False # (1/s^2); Modal Parameter (01-99) 2nd time derivatives;
SubDyn['SSqmdd02'] = False # (1/s^2); ;
SubDyn['SSqmdd03'] = False # (1/s^2); ;
SubDyn['SSqmdd04'] = False # (1/s^2); ;
SubDyn['SSqmdd05'] = False # (1/s^2); ;
SubDyn['SSqmdd06'] = False # (1/s^2); ;
SubDyn['SSqmdd07'] = False # (1/s^2); ;
SubDyn['SSqmdd08'] = False # (1/s^2); ;
SubDyn['SSqmdd09'] = False # (1/s^2); ;
SubDyn['SSqmdd10'] = False # (1/s^2); ;
SubDyn['SSqmdd11'] = False # (1/s^2); ;
SubDyn['SSqmdd12'] = False # (1/s^2); ;
SubDyn['SSqmdd13'] = False # (1/s^2); ;
SubDyn['SSqmdd14'] = False # (1/s^2); ;
SubDyn['SSqmdd15'] = False # (1/s^2); ;
SubDyn['SSqmdd16'] = False # (1/s^2); ;
SubDyn['SSqmdd17'] = False # (1/s^2); ;
SubDyn['SSqmdd18'] = False # (1/s^2); ;
SubDyn['SSqmdd19'] = False # (1/s^2); ;
SubDyn['SSqmdd20'] = False # (1/s^2); ;
SubDyn['SSqmdd21'] = False # (1/s^2); ;
SubDyn['SSqmdd22'] = False # (1/s^2); ;
SubDyn['SSqmdd23'] = False # (1/s^2); ;
SubDyn['SSqmdd24'] = False # (1/s^2); ;
SubDyn['SSqmdd25'] = False # (1/s^2); ;
SubDyn['SSqmdd26'] = False # (1/s^2); ;
SubDyn['SSqmdd27'] = False # (1/s^2); ;
SubDyn['SSqmdd28'] = False # (1/s^2); ;
SubDyn['SSqmdd29'] = False # (1/s^2); ;
SubDyn['SSqmdd30'] = False # (1/s^2); ;
SubDyn['SSqmdd31'] = False # (1/s^2); ;
SubDyn['SSqmdd32'] = False # (1/s^2); ;
SubDyn['SSqmdd33'] = False # (1/s^2); ;
SubDyn['SSqmdd34'] = False # (1/s^2); ;
SubDyn['SSqmdd35'] = False # (1/s^2); ;
SubDyn['SSqmdd36'] = False # (1/s^2); ;
SubDyn['SSqmdd37'] = False # (1/s^2); ;
SubDyn['SSqmdd38'] = False # (1/s^2); ;
SubDyn['SSqmdd39'] = False # (1/s^2); ;
SubDyn['SSqmdd40'] = False # (1/s^2); ;
SubDyn['SSqmdd41'] = False # (1/s^2); ;
SubDyn['SSqmdd42'] = False # (1/s^2); ;
SubDyn['SSqmdd43'] = False # (1/s^2); ;
SubDyn['SSqmdd44'] = False # (1/s^2); ;
SubDyn['SSqmdd45'] = False # (1/s^2); ;
SubDyn['SSqmdd46'] = False # (1/s^2); ;
SubDyn['SSqmdd47'] = False # (1/s^2); ;
SubDyn['SSqmdd48'] = False # (1/s^2); ;
SubDyn['SSqmdd49'] = False # (1/s^2); ;
SubDyn['SSqmdd50'] = False # (1/s^2); ;
SubDyn['SSqmdd51'] = False # (1/s^2); ;
SubDyn['SSqmdd52'] = False # (1/s^2); ;
SubDyn['SSqmdd53'] = False # (1/s^2); ;
SubDyn['SSqmdd54'] = False # (1/s^2); ;
SubDyn['SSqmdd55'] = False # (1/s^2); ;
SubDyn['SSqmdd56'] = False # (1/s^2); ;
SubDyn['SSqmdd57'] = False # (1/s^2); ;
SubDyn['SSqmdd58'] = False # (1/s^2); ;
SubDyn['SSqmdd59'] = False # (1/s^2); ;
SubDyn['SSqmdd60'] = False # (1/s^2); ;
SubDyn['SSqmdd61'] = False # (1/s^2); ;
SubDyn['SSqmdd62'] = False # (1/s^2); ;
SubDyn['SSqmdd63'] = False # (1/s^2); ;
SubDyn['SSqmdd64'] = False # (1/s^2); ;
SubDyn['SSqmdd65'] = False # (1/s^2); ;
SubDyn['SSqmdd66'] = False # (1/s^2); ;
SubDyn['SSqmdd67'] = False # (1/s^2); ;
SubDyn['SSqmdd68'] = False # (1/s^2); ;
SubDyn['SSqmdd69'] = False # (1/s^2); ;
SubDyn['SSqmdd70'] = False # (1/s^2); ;
SubDyn['SSqmdd71'] = False # (1/s^2); ;
SubDyn['SSqmdd72'] = False # (1/s^2); ;
SubDyn['SSqmdd73'] = False # (1/s^2); ;
SubDyn['SSqmdd74'] = False # (1/s^2); ;
SubDyn['SSqmdd75'] = False # (1/s^2); ;
SubDyn['SSqmdd76'] = False # (1/s^2); ;
SubDyn['SSqmdd77'] = False # (1/s^2); ;
SubDyn['SSqmdd78'] = False # (1/s^2); ;
SubDyn['SSqmdd79'] = False # (1/s^2); ;
SubDyn['SSqmdd80'] = False # (1/s^2); ;
SubDyn['SSqmdd81'] = False # (1/s^2); ;
SubDyn['SSqmdd82'] = False # (1/s^2); ;
SubDyn['SSqmdd83'] = False # (1/s^2); ;
SubDyn['SSqmdd84'] = False # (1/s^2); ;
SubDyn['SSqmdd85'] = False # (1/s^2); ;
SubDyn['SSqmdd86'] = False # (1/s^2); ;
SubDyn['SSqmdd87'] = False # (1/s^2); ;
SubDyn['SSqmdd88'] = False # (1/s^2); ;
SubDyn['SSqmdd89'] = False # (1/s^2); ;
SubDyn['SSqmdd90'] = False # (1/s^2); ;
SubDyn['SSqmdd91'] = False # (1/s^2); ;
SubDyn['SSqmdd92'] = False # (1/s^2); ;
SubDyn['SSqmdd93'] = False # (1/s^2); ;
SubDyn['SSqmdd94'] = False # (1/s^2); ;
SubDyn['SSqmdd95'] = False # (1/s^2); ;
SubDyn['SSqmdd96'] = False # (1/s^2); ;
SubDyn['SSqmdd97'] = False # (1/s^2); ;
SubDyn['SSqmdd98'] = False # (1/s^2); ;
SubDyn['SSqmdd99'] = False # (1/s^2); ;
""" MoorDyn """
# THIS IS NOT A COMPLETE LIST!
# the "flexible naming system" discussed on page 7-8 of the documentation is not included
# http://www.matt-hall.ca/files/MoorDyn-Users-Guide-2017-08-16.pdf
# also assuming that like other OpenFAST variables, it is limited to 9 output locations per veriable, i.e. FairTen1-FairTen9
MoorDyn = {}
MoorDyn['FairTen1'] = False # (); ;
MoorDyn['FairTen2'] = False # (); ;
MoorDyn['FairTen3'] = False # (); ;
MoorDyn['FairTen4'] = False # (); ;
MoorDyn['FairTen5'] = False # (); ;
MoorDyn['FairTen6'] = False # (); ;
MoorDyn['FairTen7'] = False # (); ;
MoorDyn['FairTen8'] = False # (); ;
MoorDyn['FairTen9'] = False # (); ;
MoorDyn['AnchTen1'] = False # (); ;
MoorDyn['AnchTen2'] = False # (); ;
MoorDyn['AnchTen3'] = False # (); ;
MoorDyn['AnchTen4'] = False # (); ;
MoorDyn['AnchTen5'] = False # (); ;
MoorDyn['AnchTen6'] = False # (); ;
MoorDyn['AnchTen7'] = False # (); ;
MoorDyn['AnchTen8'] = False # (); ;
MoorDyn['AnchTen9'] = False # (); ;
""" BeamDyn """
BeamDyn = {}
# Reaction Loads
BeamDyn['RootFxr'] = False # (N); x-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootFyr'] = False # (N); y-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootFzr'] = False # (N); z-component of the root reaction force expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMxr'] = False # (N-m); x-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMyr'] = False # (N-m); y-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['RootMzr'] = False # (N-m); z-component of the root reaction moment expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
# Tip Motions
BeamDyn['TipTDxr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTDyr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTDzr'] = False # (m); Tip translational deflection (relative to the undeflected position) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDxr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDyr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipRDzr'] = False # (-); Tip angular/rotational deflection Wiener-Milenkovi parameter (relative to the undeflected orientation) expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['TipTVXg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTVYg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTVZg'] = False # (m/s); Tip translational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVXg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVYg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipRVZg'] = False # (deg/s); Tip angular/rotational velocities (absolute) expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['TipTAXl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipTAYl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipTAZl'] = False # (m/s^2); Tip translational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAXl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAYl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['TipRAZl'] = False # (deg/s^2); Tip angular/rotational accelerations (absolute) expressed in l; l: a floating coordinate system local to the deflected beam
# Sectional Loads
BeamDyn['N1Fxl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Fyl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Fzl'] = False # (N); Sectional force resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fxl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fyl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Fzl'] = False # (N); Sectional force resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fxl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fyl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Fzl'] = False # (N); Sectional force resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fxl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fyl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Fzl'] = False # (N); Sectional force resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fxl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fyl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Fzl'] = False # (N); Sectional force resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fxl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fyl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Fzl'] = False # (N); Sectional force resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fxl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fyl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Fzl'] = False # (N); Sectional force resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fxl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fyl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Fzl'] = False # (N); Sectional force resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fxl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fyl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Fzl'] = False # (N); Sectional force resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Mxl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Myl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1Mzl'] = False # (N-m); Sectional moment resultants at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Mxl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Myl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2Mzl'] = False # (N-m); Sectional moment resultants at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Mxl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Myl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3Mzl'] = False # (N-m); Sectional moment resultants at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Mxl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Myl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4Mzl'] = False # (N-m); Sectional moment resultants at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Mxl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Myl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5Mzl'] = False # (N-m); Sectional moment resultants at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Mxl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Myl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6Mzl'] = False # (N-m); Sectional moment resultants at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Mxl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Myl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7Mzl'] = False # (N-m); Sectional moment resultants at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Mxl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Myl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8Mzl'] = False # (N-m); Sectional moment resultants at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Mxl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Myl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9Mzl'] = False # (N-m); Sectional moment resultants at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Sectional Motions
BeamDyn['N1TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 1 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N2RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 2 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N3RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 3 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N4RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 4 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N5RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 5 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N6RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 6 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N7RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 7 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N8RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 8 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N9RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at Node 9 expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system
BeamDyn['N1TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVXg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVYg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9TVZg'] = False # (m/s); Sectional translational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 1 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N2RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 2 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N3RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 3 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N4RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 4 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N5RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 5 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N6RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 6 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N7RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 7 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N8RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 8 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVXg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVYg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N9RVZg'] = False # (deg/s); Sectional angular/rotational velocities (absolute) at Node 9 expressed in g; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system
BeamDyn['N1TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAXl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAYl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9TAZl'] = False # (m/s^2); Sectional translational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAXl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAYl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9RAZl'] = False # (deg/s^2); Sectional angular/rotational accelerations (absolute) at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Applied Loads
BeamDyn['N1PFxl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PFyl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PFzl'] = False # (N); Applied point forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFxl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFyl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PFzl'] = False # (N); Applied point forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFxl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFyl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PFzl'] = False # (N); Applied point forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFxl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFyl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PFzl'] = False # (N); Applied point forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFxl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFyl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PFzl'] = False # (N); Applied point forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFxl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFyl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PFzl'] = False # (N); Applied point forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFxl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFyl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PFzl'] = False # (N); Applied point forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFxl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFyl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PFzl'] = False # (N); Applied point forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFxl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFyl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PFzl'] = False # (N); Applied point forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMxl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMyl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1PMzl'] = False # (N-m); Applied point moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMxl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMyl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2PMzl'] = False # (N-m); Applied point moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMxl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMyl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3PMzl'] = False # (N-m); Applied point moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMxl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMyl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4PMzl'] = False # (N-m); Applied point moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMxl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMyl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5PMzl'] = False # (N-m); Applied point moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMxl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMyl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6PMzl'] = False # (N-m); Applied point moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMxl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMyl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7PMzl'] = False # (N-m); Applied point moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMxl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMyl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8PMzl'] = False # (N-m); Applied point moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMxl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMyl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9PMzl'] = False # (N-m); Applied point moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFxl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFyl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DFzl'] = False # (N/m); Applied distributed forces at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFxl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFyl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DFzl'] = False # (N/m); Applied distributed forces at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFxl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFyl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DFzl'] = False # (N/m); Applied distributed forces at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFxl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFyl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DFzl'] = False # (N/m); Applied distributed forces at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFxl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFyl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DFzl'] = False # (N/m); Applied distributed forces at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFxl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFyl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DFzl'] = False # (N/m); Applied distributed forces at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFxl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFyl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DFzl'] = False # (N/m); Applied distributed forces at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFxl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFyl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DFzl'] = False # (N/m); Applied distributed forces at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFxl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFyl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DFzl'] = False # (N/m); Applied distributed forces at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMxl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMyl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N1DMzl'] = False # (N-m/m); Applied distributed moments at Node 1 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMxl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMyl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N2DMzl'] = False # (N-m/m); Applied distributed moments at Node 2 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMxl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMyl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N3DMzl'] = False # (N-m/m); Applied distributed moments at Node 3 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMxl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMyl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N4DMzl'] = False # (N-m/m); Applied distributed moments at Node 4 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMxl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMyl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N5DMzl'] = False # (N-m/m); Applied distributed moments at Node 5 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMxl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMyl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N6DMzl'] = False # (N-m/m); Applied distributed moments at Node 6 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMxl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMyl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N7DMzl'] = False # (N-m/m); Applied distributed moments at Node 7 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMxl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMyl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N8DMzl'] = False # (N-m/m); Applied distributed moments at Node 8 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMxl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMyl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
BeamDyn['N9DMzl'] = False # (N-m/m); Applied distributed moments at Node 9 expressed in l; l: a floating coordinate system local to the deflected beam
# Pitch Actuator
BeamDyn['PAngInp'] = False # (deg); Pitch angle input;
BeamDyn['PAngAct'] = False # (deg); Actual pitch angle ;
BeamDyn['PRatAct'] = False # (deg/s); Actual pitch rate;
BeamDyn['PAccAct'] = False # (deg/s^2); Actual pitch acceleration;
""" Final Output Dictionary """
FstOutput = {}
FstOutput['ElastoDyn'] = ElastoDyn
FstOutput['BeamDyn'] = BeamDyn
FstOutput['ServoDyn'] = ServoDyn
FstOutput['AeroDyn'] = AeroDyn
FstOutput['InflowWind'] = InflowWind
FstOutput['WAMIT'] = WAMIT
FstOutput['HydroDyn'] = HydroDyn
FstOutput['Morison'] = Morison
FstOutput['SubDyn'] = SubDyn
FstOutput['BeamDyn'] = BeamDyn
FstOutput['MoorDyn'] = MoorDyn
""" Generated from FAST OutListParameters.xlsx files with AeroelasticSE/src/AeroelasticSE/Util/create_output_vars.py """
""" OutList """
OutList = {}
# Wind Motions
OutList['WindVxi'] = False # (m/s); Nominally downwind component of the hub-height wind velocity; Directed along the xi-axis
OutList['uWind'] = False # (m/s); Nominally downwind component of the hub-height wind velocity; Directed along the xi-axis
OutList['WindVyi'] = False # (m/s); Cross-wind component of the hub-height wind velocity; Directed along the yi-axis
OutList['vWind'] = False # (m/s); Cross-wind component of the hub-height wind velocity; Directed along the yi-axis
OutList['WindVzi'] = False # (m/s); Vertical component of the hub-height wind velocity; Directed along the zi-axis
OutList['wWind'] = False # (m/s); Vertical component of the hub-height wind velocity; Directed along the zi-axis
OutList['TotWindV'] = False # (m/s); Total hub-height wind velocity magnitude; N/A
OutList['HorWindV'] = False # (m/s); Horizontal hub-height wind velocity magnitude; In the xi- and yi-plane
OutList['HorWndDir'] = False # (deg); Horizontal hub-height wind direction. Please note that FAST uses the opposite sign convention that AeroDyn uses. Put a "-", "_", "m", or "M" character in front of this variable name if you want to use the AeroDyn convention.; About the zi-axis
OutList['VerWndDir'] = False # (deg); Vertical hub-height wind direction; About an axis orthogonal to the zi-axis and the HorWindV-vector
# Blade 1 Tip Motions
OutList['TipDxc1'] = False # (m); Blade 1 out-of-plane tip deflection (relative to the undeflected position); Directed along the xc1-axis
OutList['OoPDefl1'] = False # (m); Blade 1 out-of-plane tip deflection (relative to the undeflected position); Directed along the xc1-axis
OutList['TipDyc1'] = False # (m); Blade 1 in-plane tip deflection (relative to the undeflected position); Directed along the yc1-axis
OutList['IPDefl1'] = False # (m); Blade 1 in-plane tip deflection (relative to the undeflected position); Directed along the yc1-axis
OutList['TipDzc1'] = False # (m); Blade 1 axial tip deflection (relative to the undeflected position); Directed along the zc1- and zb1-axes
OutList['TipDzb1'] = False # (m); Blade 1 axial tip deflection (relative to the undeflected position); Directed along the zc1- and zb1-axes
OutList['TipDxb1'] = False # (m); Blade 1 flapwise tip deflection (relative to the undeflected position); Directed along the xb1-axis
OutList['TipDyb1'] = False # (m); Blade 1 edgewise tip deflection (relative to the undeflected position); Directed along the yb1-axis
OutList['TipALxb1'] = False # (m/s^2); Blade 1 local flapwise tip acceleration (absolute); Directed along the local xb1-axis
OutList['TipALyb1'] = False # (m/s^2); Blade 1 local edgewise tip acceleration (absolute); Directed along the local yb1-axis
OutList['TipALzb1'] = False # (m/s^2); Blade 1 local axial tip acceleration (absolute); Directed along the local zb1-axis
OutList['TipRDxb1'] = False # (deg); Blade 1 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb1-axis
OutList['RollDefl1'] = False # (deg); Blade 1 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb1-axis
OutList['TipRDyb1'] = False # (deg); Blade 1 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb1-axis
OutList['PtchDefl1'] = False # (deg); Blade 1 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb1-axis
OutList['TipRDzc1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
OutList['TipRDzb1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
OutList['TwstDefl1'] = False # (deg); Blade 1 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc1- and zb1-axes
OutList['TipClrnc1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['TwrClrnc1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['Tip2Twr1'] = False # (m); Blade 1 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 2 Tip Motions
OutList['TipDxc2'] = False # (m); Blade 2 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc2-axis
OutList['OoPDefl2'] = False # (m); Blade 2 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc2-axis
OutList['TipDyc2'] = False # (m); Blade 2 in-plane tip deflection (relative to the pitch axis); Directed along the yc2-axis
OutList['IPDefl2'] = False # (m); Blade 2 in-plane tip deflection (relative to the pitch axis); Directed along the yc2-axis
OutList['TipDzc2'] = False # (m); Blade 2 axial tip deflection (relative to the pitch axis); Directed along the zc2- and zb2-axes
OutList['TipDzb2'] = False # (m); Blade 2 axial tip deflection (relative to the pitch axis); Directed along the zc2- and zb2-axes
OutList['TipDxb2'] = False # (m); Blade 2 flapwise tip deflection (relative to the pitch axis); Directed along the xb2-axis
OutList['TipDyb2'] = False # (m); Blade 2 edgewise tip deflection (relative to the pitch axis); Directed along the yb2-axis
OutList['TipALxb2'] = False # (m/s^2); Blade 2 local flapwise tip acceleration (absolute); Directed along the local xb2-axis
OutList['TipALyb2'] = False # (m/s^2); Blade 2 local edgewise tip acceleration (absolute); Directed along the local yb2-axis
OutList['TipALzb2'] = False # (m/s^2); Blade 2 local axial tip acceleration (absolute); Directed along the local zb2-axis
OutList['TipRDxb2'] = False # (deg); Blade 2 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb2-axis
OutList['RollDefl2'] = False # (deg); Blade 2 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb2-axis
OutList['TipRDyb2'] = False # (deg); Blade 2 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb2-axis
OutList['PtchDefl2'] = False # (deg); Blade 2 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb2-axis
OutList['TipRDzc2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
OutList['TipRDzb2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
OutList['TwstDefl2'] = False # (deg); Blade 2 torsional (angular/rotational) tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc2- and zb2-axes
OutList['TipClrnc2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['TwrClrnc2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['Tip2Twr2'] = False # (m); Blade 2 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 3 Tip Motions
OutList['TipDxc3'] = False # (m); Blade 3 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc3-axis
OutList['OoPDefl3'] = False # (m); Blade 3 out-of-plane tip deflection (relative to the pitch axis); Directed along the xc3-axis
OutList['TipDyc3'] = False # (m); Blade 3 in-plane tip deflection (relative to the pitch axis); Directed along the yc3-axis
OutList['IPDefl3'] = False # (m); Blade 3 in-plane tip deflection (relative to the pitch axis); Directed along the yc3-axis
OutList['TipDzc3'] = False # (m); Blade 3 axial tip deflection (relative to the pitch axis); Directed along the zc3- and zb3-axes
OutList['TipDzb3'] = False # (m); Blade 3 axial tip deflection (relative to the pitch axis); Directed along the zc3- and zb3-axes
OutList['TipDxb3'] = False # (m); Blade 3 flapwise tip deflection (relative to the pitch axis); Directed along the xb3-axis
OutList['TipDyb3'] = False # (m); Blade 3 edgewise tip deflection (relative to the pitch axis); Directed along the yb3-axis
OutList['TipALxb3'] = False # (m/s^2); Blade 3 local flapwise tip acceleration (absolute); Directed along the local xb3-axis
OutList['TipALyb3'] = False # (m/s^2); Blade 3 local edgewise tip acceleration (absolute); Directed along the local yb3-axis
OutList['TipALzb3'] = False # (m/s^2); Blade 3 local axial tip acceleration (absolute); Directed along the local zb3-axis
OutList['TipRDxb3'] = False # (deg); Blade 3 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb3-axis
OutList['RollDefl3'] = False # (deg); Blade 3 roll (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the xb3-axis
OutList['TipRDyb3'] = False # (deg); Blade 3 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb3-axis
OutList['PtchDefl3'] = False # (deg); Blade 3 pitch (angular/rotational) tip deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the yb3-axis
OutList['TipRDzc3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
OutList['TipRDzb3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
OutList['TwstDefl3'] = False # (deg); Blade 3 torsional tip deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the zc3- and zb3-axes
OutList['TipClrnc3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['TwrClrnc3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
OutList['Tip2Twr3'] = False # (m); Blade 3 tip-to-tower clearance estimate. This is computed as the perpendicular distance from the yaw axis to the tip of blade 1 when the blade tip is below the yaw bearing. When the tip of blade 1 is above the yaw bearing, it is computed as the absolute distance from the yaw bearing to the blade tip. Please note that you should reduce this value by the tower radius to obtain the actual tower clearance.; N/A
# Blade 1 Local Span Motions
OutList['Spn1ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 1; Directed along the local xb1-axis
OutList['Spn1ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 1; Directed along the local yb1-axis
OutList['Spn1ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 1; Directed along the local zb1-axis
OutList['Spn2ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 2; Directed along the local xb1-axis
OutList['Spn2ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 2; Directed along the local yb1-axis
OutList['Spn2ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 2; Directed along the local zb1-axis
OutList['Spn3ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 3; Directed along the local xb1-axis
OutList['Spn3ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 3; Directed along the local yb1-axis
OutList['Spn3ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 3; Directed along the local zb1-axis
OutList['Spn4ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 4; Directed along the local xb1-axis
OutList['Spn4ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 4; Directed along the local yb1-axis
OutList['Spn4ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 4; Directed along the local zb1-axis
OutList['Spn5ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 5; Directed along the local xb1-axis
OutList['Spn5ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 5; Directed along the local yb1-axis
OutList['Spn5ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 5; Directed along the local zb1-axis
OutList['Spn6ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 6; Directed along the local xb1-axis
OutList['Spn6ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 6; Directed along the local yb1-axis
OutList['Spn6ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 6; Directed along the local zb1-axis
OutList['Spn7ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 7; Directed along the local xb1-axis
OutList['Spn7ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 7; Directed along the local yb1-axis
OutList['Spn7ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 7; Directed along the local zb1-axis
OutList['Spn8ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 8; Directed along the local xb1-axis
OutList['Spn8ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 8; Directed along the local yb1-axis
OutList['Spn8ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 8; Directed along the local zb1-axis
OutList['Spn9ALxb1'] = False # (m/s^2); Blade 1 local flapwise acceleration (absolute) of span station 9; Directed along the local xb1-axis
OutList['Spn9ALyb1'] = False # (m/s^2); Blade 1 local edgewise acceleration (absolute) of span station 9; Directed along the local yb1-axis
OutList['Spn9ALzb1'] = False # (m/s^2); Blade 1 local axial acceleration (absolute) of span station 9; Directed along the local zb1-axis
OutList['Spn1TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb1-axis
OutList['Spn1TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb1-axis
OutList['Spn1TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb1-axis
OutList['Spn2TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb1-axis
OutList['Spn2TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb1-axis
OutList['Spn2TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb1-axis
OutList['Spn3TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb1-axis
OutList['Spn3TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb1-axis
OutList['Spn3TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb1-axis
OutList['Spn4TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb1-axis
OutList['Spn4TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb1-axis
OutList['Spn4TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb1-axis
OutList['Spn5TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb1-axis
OutList['Spn5TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb1-axis
OutList['Spn5TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb1-axis
OutList['Spn6TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb1-axis
OutList['Spn6TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb1-axis
OutList['Spn6TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb1-axis
OutList['Spn7TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb1-axis
OutList['Spn7TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb1-axis
OutList['Spn7TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb1-axis
OutList['Spn8TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb1-axis
OutList['Spn8TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb1-axis
OutList['Spn8TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb1-axis
OutList['Spn9TDxb1'] = False # (m); Blade 1 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb1-axis
OutList['Spn9TDyb1'] = False # (m); Blade 1 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb1-axis
OutList['Spn9TDzb1'] = False # (m); Blade 1 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb1-axis
OutList['Spn1RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn1RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn1RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn2RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn2RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn2RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn3RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn3RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn3RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn4RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn4RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn4RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn5RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn5RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn5RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn6RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn6RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn6RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn7RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn7RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn7RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn8RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn8RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn8RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
OutList['Spn9RDxb1'] = False # (deg); Blade 1 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb1-axis
OutList['Spn9RDyb1'] = False # (deg); Blade 1 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb1-axis
OutList['Spn9RDzb1'] = False # (deg); Blade 1 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb1-axis
# Blade 2 Local Span Motions
OutList['Spn1ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 1; Directed along the local xb2-axis
OutList['Spn1ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 1; Directed along the local yb2-axis
OutList['Spn1ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 1; Directed along the local zb2-axis
OutList['Spn2ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 2; Directed along the local xb2-axis
OutList['Spn2ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 2; Directed along the local yb2-axis
OutList['Spn2ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 2; Directed along the local zb2-axis
OutList['Spn3ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 3; Directed along the local xb2-axis
OutList['Spn3ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 3; Directed along the local yb2-axis
OutList['Spn3ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 3; Directed along the local zb2-axis
OutList['Spn4ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 4; Directed along the local xb2-axis
OutList['Spn4ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 4; Directed along the local yb2-axis
OutList['Spn4ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 4; Directed along the local zb2-axis
OutList['Spn5ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 5; Directed along the local xb2-axis
OutList['Spn5ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 5; Directed along the local yb2-axis
OutList['Spn5ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 5; Directed along the local zb2-axis
OutList['Spn6ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 6; Directed along the local xb2-axis
OutList['Spn6ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 6; Directed along the local yb2-axis
OutList['Spn6ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 6; Directed along the local zb2-axis
OutList['Spn7ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 7; Directed along the local xb2-axis
OutList['Spn7ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 7; Directed along the local yb2-axis
OutList['Spn7ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 7; Directed along the local zb2-axis
OutList['Spn8ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 8; Directed along the local xb2-axis
OutList['Spn8ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 8; Directed along the local yb2-axis
OutList['Spn8ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 8; Directed along the local zb2-axis
OutList['Spn9ALxb2'] = False # (m/s^2); Blade 2 local flapwise acceleration (absolute) of span station 9; Directed along the local xb2-axis
OutList['Spn9ALyb2'] = False # (m/s^2); Blade 2 local edgewise acceleration (absolute) of span station 9; Directed along the local yb2-axis
OutList['Spn9ALzb2'] = False # (m/s^2); Blade 2 local axial acceleration (absolute) of span station 9; Directed along the local zb2-axis
OutList['Spn1TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb2-axis
OutList['Spn1TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb2-axis
OutList['Spn1TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb2-axis
OutList['Spn2TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb2-axis
OutList['Spn2TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb2-axis
OutList['Spn2TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb2-axis
OutList['Spn3TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb2-axis
OutList['Spn3TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb2-axis
OutList['Spn3TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb2-axis
OutList['Spn4TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb2-axis
OutList['Spn4TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb2-axis
OutList['Spn4TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb2-axis
OutList['Spn5TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb2-axis
OutList['Spn5TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb2-axis
OutList['Spn5TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb2-axis
OutList['Spn6TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb2-axis
OutList['Spn6TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb2-axis
OutList['Spn6TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb2-axis
OutList['Spn7TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb2-axis
OutList['Spn7TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb2-axis
OutList['Spn7TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb2-axis
OutList['Spn8TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb2-axis
OutList['Spn8TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb2-axis
OutList['Spn8TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb2-axis
OutList['Spn9TDxb2'] = False # (m); Blade 2 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb2-axis
OutList['Spn9TDyb2'] = False # (m); Blade 2 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb2-axis
OutList['Spn9TDzb2'] = False # (m); Blade 2 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb2-axis
OutList['Spn1RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn1RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn1RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn2RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn2RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn2RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn3RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn3RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn3RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn4RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn4RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn4RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn5RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn5RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn5RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn6RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn6RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn6RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn7RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn7RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn7RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn8RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn8RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn8RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
OutList['Spn9RDxb2'] = False # (deg); Blade 2 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb2-axis
OutList['Spn9RDyb2'] = False # (deg); Blade 2 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb2-axis
OutList['Spn9RDzb2'] = False # (deg); Blade 2 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb2-axis
# Blade 3 Local Span Motions
OutList['Spn1ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 1; Directed along the local xb3-axis
OutList['Spn1ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 1; Directed along the local yb3-axis
OutList['Spn1ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 1; Directed along the local zb3-axis
OutList['Spn2ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 2; Directed along the local xb3-axis
OutList['Spn2ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 2; Directed along the local yb3-axis
OutList['Spn2ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 2; Directed along the local zb3-axis
OutList['Spn3ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 3; Directed along the local xb3-axis
OutList['Spn3ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 3; Directed along the local yb3-axis
OutList['Spn3ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 3; Directed along the local zb3-axis
OutList['Spn4ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 4; Directed along the local xb3-axis
OutList['Spn4ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 4; Directed along the local yb3-axis
OutList['Spn4ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 4; Directed along the local zb3-axis
OutList['Spn5ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 5; Directed along the local xb3-axis
OutList['Spn5ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 5; Directed along the local yb3-axis
OutList['Spn5ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 5; Directed along the local zb3-axis
OutList['Spn6ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 6; Directed along the local xb3-axis
OutList['Spn6ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 6; Directed along the local yb3-axis
OutList['Spn6ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 6; Directed along the local zb3-axis
OutList['Spn7ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 7; Directed along the local xb3-axis
OutList['Spn7ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 7; Directed along the local yb3-axis
OutList['Spn7ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 7; Directed along the local zb3-axis
OutList['Spn8ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 8; Directed along the local xb3-axis
OutList['Spn8ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 8; Directed along the local yb3-axis
OutList['Spn8ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 8; Directed along the local zb3-axis
OutList['Spn9ALxb3'] = False # (m/s^2); Blade 3 local flapwise acceleration (absolute) of span station 9; Directed along the local xb3-axis
OutList['Spn9ALyb3'] = False # (m/s^2); Blade 3 local edgewise acceleration (absolute) of span station 9; Directed along the local yb3-axis
OutList['Spn9ALzb3'] = False # (m/s^2); Blade 3 local axial acceleration (absolute) of span station 9; Directed along the local zb3-axis
OutList['Spn1TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the xb3-axis
OutList['Spn1TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 1; Directed along the yb3-axis
OutList['Spn1TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 1; Directed along the zb3-axis
OutList['Spn2TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the xb3-axis
OutList['Spn2TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 2; Directed along the yb3-axis
OutList['Spn2TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 2; Directed along the zb3-axis
OutList['Spn3TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the xb3-axis
OutList['Spn3TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 3; Directed along the yb3-axis
OutList['Spn3TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 3; Directed along the zb3-axis
OutList['Spn4TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the xb3-axis
OutList['Spn4TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 4; Directed along the yb3-axis
OutList['Spn4TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 4; Directed along the zb3-axis
OutList['Spn5TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the xb3-axis
OutList['Spn5TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 5; Directed along the yb3-axis
OutList['Spn5TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 5; Directed along the zb3-axis
OutList['Spn6TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the xb3-axis
OutList['Spn6TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 6; Directed along the yb3-axis
OutList['Spn6TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 6; Directed along the zb3-axis
OutList['Spn7TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the xb3-axis
OutList['Spn7TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 7; Directed along the yb3-axis
OutList['Spn7TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 7; Directed along the zb3-axis
OutList['Spn8TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the xb3-axis
OutList['Spn8TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 8; Directed along the yb3-axis
OutList['Spn8TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 8; Directed along the zb3-axis
OutList['Spn9TDxb3'] = False # (m); Blade 3 local flapwise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the xb3-axis
OutList['Spn9TDyb3'] = False # (m); Blade 3 local edgewise (translational) deflection (relative to the undeflected position) of span station 9; Directed along the yb3-axis
OutList['Spn9TDzb3'] = False # (m); Blade 3 local axial (translational) deflection (relative to the undeflected position) of span station 9; Directed along the zb3-axis
OutList['Spn1RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn1RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn1RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 1. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn2RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn2RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn2RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 2. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn3RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn3RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn3RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 3. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn4RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn4RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn4RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 4. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn5RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn5RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn5RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 5. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn6RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn6RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn6RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 6. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn7RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn7RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn7RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 7. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn8RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn8RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn8RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 8. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
OutList['Spn9RDxb3'] = False # (deg); Blade 3 local roll (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local xb3-axis
OutList['Spn9RDyb3'] = False # (deg); Blade 3 local pitch (angular/rotational) deflection (relative to the undeflected position) of span station 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small blade deflections, so that the rotation sequence does not matter.; About the local yb3-axis
OutList['Spn9RDzb3'] = False # (deg); Blade 3 local torsional (angular/rotational) deflection (relative to the undeflected position) of span station 9. This output will always be zero for FAST simulation results. Use it for examining blade torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. Please note that this output uses the opposite of the sign convention used for blade pitch angles.; About the local zb3-axis
# Blade Pitch Motions
OutList['PtchPMzc1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
OutList['PtchPMzb1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
OutList['BldPitch1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
OutList['BlPitch1'] = False # (deg); Blade 1 pitch angle (position); Positive towards feather about the minus zc1- and minus zb1-axes
OutList['PtchPMzc2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
OutList['PtchPMzb2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
OutList['BldPitch2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
OutList['BlPitch2'] = False # (deg); Blade 2 pitch angle (position); Positive towards feather about the minus zc2- and minus zb2-axes
OutList['PtchPMzc3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
OutList['PtchPMzb3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
OutList['BldPitch3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
OutList['BlPitch3'] = False # (deg); Blade 3 pitch angle (position); Positive towards feather about the minus zc3- and minus zb3-axes
# Teeter Motions
OutList['TeetPya'] = False # (deg); Rotor teeter angle (position); About the ya-axis
OutList['RotTeetP'] = False # (deg); Rotor teeter angle (position); About the ya-axis
OutList['TeetDefl'] = False # (deg); Rotor teeter angle (position); About the ya-axis
OutList['TeetVya'] = False # (deg/s); Rotor teeter angular velocity; About the ya-axis
OutList['RotTeetV'] = False # (deg/s); Rotor teeter angular velocity; About the ya-axis
OutList['TeetAya'] = False # (deg/s^2); Rotor teeter angular acceleration; About the ya-axis
OutList['RotTeetA'] = False # (deg/s^2); Rotor teeter angular acceleration; About the ya-axis
# Shaft Motions
OutList['LSSTipPxa'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
OutList['LSSTipPxs'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
OutList['LSSTipP'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
OutList['Azimuth'] = False # (deg); Rotor azimuth angle (position); About the xa- and xs-axes
OutList['LSSTipVxa'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
OutList['LSSTipVxs'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
OutList['LSSTipV'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
OutList['RotSpeed'] = False # (rpm); Rotor azimuth angular speed; About the xa- and xs-axes
OutList['LSSTipAxa'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
OutList['LSSTipAxs'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
OutList['LSSTipA'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
OutList['RotAccel'] = False # (deg/s^2); Rotor azimuth angular acceleration; About the xa- and xs-axes
OutList['LSSGagPxa'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagPxs'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagP'] = False # (deg); Low-speed shaft strain gage azimuth angle (position) (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagVxa'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagVxs'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagV'] = False # (rpm); Low-speed shaft strain gage angular speed (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagAxa'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagAxs'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['LSSGagA'] = False # (deg/s^2); Low-speed shaft strain gage angular acceleration (on the gearbox side of the low-speed shaft); About the xa- and xs-axes
OutList['HSShftV'] = False # (rpm); Angular speed of the high-speed shaft and generator; Same sign as LSSGagVxa / LSSGagVxs / LSSGagV
OutList['GenSpeed'] = False # (rpm); Angular speed of the high-speed shaft and generator; Same sign as LSSGagVxa / LSSGagVxs / LSSGagV
OutList['HSShftA'] = False # (deg/s^2); Angular acceleration of the high-speed shaft and generator; Same sign as LSSGagAxa / LSSGagAxs / LSSGagA
OutList['GenAccel'] = False # (deg/s^2); Angular acceleration of the high-speed shaft and generator; Same sign as LSSGagAxa / LSSGagAxs / LSSGagA
OutList['TipSpdRat'] = False # (-); Rotor blade tip speed ratio; N/A
OutList['TSR'] = False # (-); Rotor blade tip speed ratio; N/A
# Nacelle IMU Motions
OutList['NcIMUTVxs'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the xs-axis
OutList['NcIMUTVys'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the ys-axis
OutList['NcIMUTVzs'] = False # (m/s); Nacelle inertial measurement unit translational velocity (absolute); Directed along the zs-axis
OutList['NcIMUTAxs'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the xs-axis
OutList['NcIMUTAys'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the ys-axis
OutList['NcIMUTAzs'] = False # (m/s^2); Nacelle inertial measurement unit translational acceleration (absolute); Directed along the zs-axis
OutList['NcIMURVxs'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the xs-axis
OutList['NcIMURVys'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the ys-axis
OutList['NcIMURVzs'] = False # (deg/s); Nacelle inertial measurement unit angular (rotational) velocity (absolute); About the zs-axis
OutList['NcIMURAxs'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the xs-axis
OutList['NcIMURAys'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the ys-axis
OutList['NcIMURAzs'] = False # (deg/s^2); Nacelle inertial measurement unit angular (rotational) acceleration (absolute); About the zs-axis
# Rotor-Furl Motions
OutList['RotFurlP'] = False # (deg); Rotor-furl angle (position); About the rotor-furl axis
OutList['RotFurl'] = False # (deg); Rotor-furl angle (position); About the rotor-furl axis
OutList['RotFurlV'] = False # (deg/s); Rotor-furl angular velocity; About the rotor-furl axis
OutList['RotFurlA'] = False # (deg/s^2); Rotor-furl angular acceleration; About the rotor-furl axis
# Tail-Furl Motions
OutList['TailFurlP'] = False # (deg); Tail-furl angle (position); About the tail-furl axis
OutList['TailFurl'] = False # (deg); Tail-furl angle (position); About the tail-furl axis
OutList['TailFurlV'] = False # (deg/s); Tail-furl angular velocity; About the tail-furl axis
OutList['TailFurlA'] = False # (deg/s^2); Tail-furl angular acceleration; About the tail-furl axis
# Nacelle Yaw Motions
OutList['YawPzn'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
OutList['YawPzp'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
OutList['NacYawP'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
OutList['NacYaw'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
OutList['YawPos'] = False # (deg); Nacelle yaw angle (position); About the zn- and zp-axes
OutList['YawVzn'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
OutList['YawVzp'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
OutList['NacYawV'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
OutList['YawRate'] = False # (deg/s); Nacelle yaw angular velocity; About the zn- and zp-axes
OutList['YawAzn'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
OutList['YawAzp'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
OutList['NacYawA'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
OutList['YawAccel'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes
OutList['NacYawErr'] = False # (deg); Nacelle yaw error estimate. This is computed as follows: NacYawErr = HorWndDir - YawPzn - YawBrRDzt - PtfmRDzi. This estimate is not accurate instantaneously in the presence of significant tower deflection or platform angular (rotational) displacement since the angles used in the computation are not all defined about the same axis of rotation. However, the estimate should be useful in a yaw controller if averaged over a time scale long enough to diminish the effects of tower and platform motions (i.e., much longer than the period of oscillation).; About the zi-axis
# Tower-Top / Yaw Bearing Motions
OutList['YawBrTDxp'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xp-axis
OutList['YawBrTDyp'] = False # (m); Tower-top / yaw bearing side-to-side (translational) deflection (relative to the undeflected position); Directed along the yp-axis
OutList['YawBrTDzp'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zp-axis
OutList['YawBrTDxt'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xt-axis
OutList['TTDspFA'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xt-axis
OutList['YawBrTDyt'] = False # (m); Tower-top / yaw bearing side-to-side (translation) deflection (relative to the undeflected position); Directed along the yt-axis
OutList['TTDspSS'] = False # (m); Tower-top / yaw bearing side-to-side (translation) deflection (relative to the undeflected position); Directed along the yt-axis
OutList['YawBrTDzt'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis
OutList['TTDspAx'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis
OutList['YawBrTAxp'] = False # (m/s^2); Tower-top / yaw bearing fore-aft (translational) acceleration (absolute); Directed along the xp-axis
OutList['YawBrTAyp'] = False # (m/s^2); Tower-top / yaw bearing side-to-side (translational) acceleration (absolute); Directed along the yp-axis
OutList['YawBrTAzp'] = False # (m/s^2); Tower-top / yaw bearing axial (translational) acceleration (absolute); Directed along the zp-axis
OutList['YawBrRDxt'] = False # (deg); Tower-top / yaw bearing angular (rotational) roll deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the xt-axis
OutList['TTDspRoll'] = False # (deg); Tower-top / yaw bearing angular (rotational) roll deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the xt-axis
OutList['YawBrRDyt'] = False # (deg); Tower-top / yaw bearing angular (rotational) pitch deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the yt-axis
OutList['TTDspPtch'] = False # (deg); Tower-top / yaw bearing angular (rotational) pitch deflection (relative to the undeflected position). In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the yt-axis
OutList['YawBrRDzt'] = False # (deg); Tower-top / yaw bearing angular (rotational) torsion deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the zt-axis
OutList['TTDspTwst'] = False # (deg); Tower-top / yaw bearing angular (rotational) torsion deflection (relative to the undeflected position). This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the zt-axis
OutList['YawBrRVxp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) roll velocity (absolute); About the xp-axis
OutList['YawBrRVyp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) pitch velocity (absolute); About the yp-axis
OutList['YawBrRVzp'] = False # (deg/s); Tower-top / yaw bearing angular (rotational) torsion velocity. This output will always be very close to zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. (absolute); About the zp-axis
OutList['YawBrRAxp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) roll acceleration (absolute); About the xp-axis
OutList['YawBrRAyp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) pitch acceleration (absolute); About the yp-axis
OutList['YawBrRAzp'] = False # (deg/s^2); Tower-top / yaw bearing angular (rotational) torsion acceleration. This output will always be very close to zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. (absolute); About the zp-axis
# Local Tower Motions
OutList['TwHt1ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 1 ; Directed along the local xt-axis
OutList['TwHt1ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 1 ; Directed along the local yt-axis
OutList['TwHt1ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 1 ; Directed along the local zt-axis
OutList['TwHt2ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 2; Directed along the local xt-axis
OutList['TwHt2ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 2; Directed along the local yt-axis
OutList['TwHt2ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 2; Directed along the local zt-axis
OutList['TwHt3ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 3; Directed along the local xt-axis
OutList['TwHt3ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 3; Directed along the local yt-axis
OutList['TwHt3ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 3; Directed along the local zt-axis
OutList['TwHt4ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 4; Directed along the local xt-axis
OutList['TwHt4ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 4; Directed along the local yt-axis
OutList['TwHt4ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 4; Directed along the local zt-axis
OutList['TwHt5ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 5; Directed along the local xt-axis
OutList['TwHt5ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 5; Directed along the local yt-axis
OutList['TwHt5ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 5; Directed along the local zt-axis
OutList['TwHt6ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 6; Directed along the local xt-axis
OutList['TwHt6ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 6; Directed along the local yt-axis
OutList['TwHt6ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 6; Directed along the local zt-axis
OutList['TwHt7ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 7; Directed along the local xt-axis
OutList['TwHt7ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 7; Directed along the local yt-axis
OutList['TwHt7ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 7; Directed along the local zt-axis
OutList['TwHt8ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 8; Directed along the local xt-axis
OutList['TwHt8ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 8; Directed along the local yt-axis
OutList['TwHt8ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 8; Directed along the local zt-axis
OutList['TwHt9ALxt'] = False # (m/s^2); Local tower fore-aft (translational) acceleration (absolute) of tower gage 9; Directed along the local xt-axis
OutList['TwHt9ALyt'] = False # (m/s^2); Local tower side-to-side (translational) acceleration (absolute) of tower gage 9; Directed along the local yt-axis
OutList['TwHt9ALzt'] = False # (m/s^2); Local tower axial (translational) acceleration (absolute) of tower gage 9; Directed along the local zt-axis
OutList['TwHt1TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local xt-axis
OutList['TwHt1TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local yt-axis
OutList['TwHt1TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 1; Directed along the local zt-axis
OutList['TwHt2TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local xt-axis
OutList['TwHt2TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local yt-axis
OutList['TwHt2TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 2; Directed along the local zt-axis
OutList['TwHt3TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local xt-axis
OutList['TwHt3TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local yt-axis
OutList['TwHt3TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 3; Directed along the local zt-axis
OutList['TwHt4TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local xt-axis
OutList['TwHt4TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local yt-axis
OutList['TwHt4TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 4; Directed along the local zt-axis
OutList['TwHt5TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local xt-axis
OutList['TwHt5TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local yt-axis
OutList['TwHt5TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 5; Directed along the local zt-axis
OutList['TwHt6TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local xt-axis
OutList['TwHt6TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local yt-axis
OutList['TwHt6TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 6; Directed along the local zt-axis
OutList['TwHt7TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local xt-axis
OutList['TwHt7TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local yt-axis
OutList['TwHt7TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 7; Directed along the local zt-axis
OutList['TwHt8TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local xt-axis
OutList['TwHt8TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local yt-axis
OutList['TwHt8TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 8; Directed along the local zt-axis
OutList['TwHt9TDxt'] = False # (m); Local tower fore-aft (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local xt-axis
OutList['TwHt9TDyt'] = False # (m); Local tower side-to-side (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local yt-axis
OutList['TwHt9TDzt'] = False # (m); Local tower axial (translational) deflection (relative to the undeflected position) of tower gage 9; Directed along the local zt-axis
OutList['TwHt1RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt1RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt1RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 1. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt2RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt2RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt2RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 2. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt3RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt3RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt3RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 3. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt4RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt4RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt4RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 4. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt5RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt5RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt5RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 5. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt6RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt6RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt6RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 6. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt7RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt7RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt7RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 7. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt8RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt8RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt8RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 8. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt9RDxt'] = False # (deg); Local tower angular (rotational) roll deflection (relative to the undeflected position) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local xt-axis
OutList['TwHt9RDyt'] = False # (deg); Local tower angular (rotational) pitch deflection (relative to the undeflected position) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower deflections, so that the rotation sequence does not matter.; About the local yt-axis
OutList['TwHt9RDzt'] = False # (deg); Local tower angular (rotational) torsion deflection (relative to the undeflected position) of tower gage 9. This output will always be zero for FAST simulation results. Use it for examining tower torsional deflections of ADAMS simulations run using ADAMS datasets created using the FAST-to-ADAMS preprocessor. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence.; About the local zt-axis
OutList['TwHt1TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 1; Directed along the local xi-axis
OutList['TwHt1TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 1; Directed along the local yi-axis
OutList['TwHt1TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 1; Directed along the local zi-axis
OutList['TwHt2TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 2; Directed along the local xi-axis
OutList['TwHt2TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 2; Directed along the local yi-axis
OutList['TwHt2TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 2; Directed along the local zi-axis
OutList['TwHt3TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 3; Directed along the local xi-axis
OutList['TwHt3TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 3; Directed along the local yi-axis
OutList['TwHt3TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 3; Directed along the local zi-axis
OutList['TwHt4TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 4; Directed along the local xi-axis
OutList['TwHt4TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 4; Directed along the local yi-axis
OutList['TwHt4TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 4; Directed along the local zi-axis
OutList['TwHt5TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 5; Directed along the local xi-axis
OutList['TwHt5TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 5; Directed along the local yi-axis
OutList['TwHt5TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 5; Directed along the local zi-axis
OutList['TwHt6TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 6; Directed along the local xi-axis
OutList['TwHt6TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 6; Directed along the local yi-axis
OutList['TwHt6TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 6; Directed along the local zi-axis
OutList['TwHt7TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 7; Directed along the local xi-axis
OutList['TwHt7TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 7; Directed along the local yi-axis
OutList['TwHt7TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 7; Directed along the local zi-axis
OutList['TwHt8TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 8; Directed along the local xi-axis
OutList['TwHt8TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 8; Directed along the local yi-axis
OutList['TwHt8TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 8; Directed along the local zi-axis
OutList['TwHt9TPxi'] = False # (m); xi-component of the translational position (relative to the inertia frame) of tower gage 9; Directed along the local xi-axis
OutList['TwHt9TPyi'] = False # (m); yi-component of the translational position (relative to the inertia frame) of tower gage 9; Directed along the local yi-axis
OutList['TwHt9TPzi'] = False # (m); zi-component of the translational position (relative to ground level [onshore] or MSL [offshore]) of tower gage 9; Directed along the local zi-axis
OutList['TwHt1RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt1RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt1RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 1. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt2RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt2RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt2RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 2. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt3RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt3RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt3RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 3. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt4RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt4RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt4RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 4. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt5RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt5RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt5RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 5. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt6RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt6RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt6RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 6. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt7RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt7RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt7RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 7. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt8RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt8RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt8RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 8. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
OutList['TwHt9RPxi'] = False # (deg); xi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local xi-axis
OutList['TwHt9RPyi'] = False # (deg); yi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local yi-axis
OutList['TwHt9RPzi'] = False # (deg); zi-component of the rotational position (relative to the inertia frame) of tower gage 9. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small tower and platform rotational deflections, so that the rotation sequence does not matter.; About the local zi-axis
# Platform Motions
OutList['PtfmTDxt'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xt-axis
OutList['PtfmTDyt'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yt-axis
OutList['PtfmTDzt'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zt-axis
OutList['PtfmTDxi'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xi-axis
OutList['PtfmSurge'] = False # (m); Platform horizontal surge (translational) displacement; Directed along the xi-axis
OutList['PtfmTDyi'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yi-axis
OutList['PtfmSway'] = False # (m); Platform horizontal sway (translational) displacement; Directed along the yi-axis
OutList['PtfmTDzi'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zi-axis
OutList['PtfmHeave'] = False # (m); Platform vertical heave (translational) displacement; Directed along the zi-axis
OutList['PtfmTVxt'] = False # (m/s); Platform horizontal surge (translational) velocity; Directed along the xt-axis
OutList['PtfmTVyt'] = False # (m/s); Platform horizontal sway (translational) velocity; Directed along the yt-axis
OutList['PtfmTVzt'] = False # (m/s); Platform vertical heave (translational) velocity; Directed along the zt-axis
OutList['PtfmTVxi'] = False # (m/s); Platform horizontal surge (translational) velocity; Directed along the xi-axis
OutList['PtfmTVyi'] = False # (m/s); Platform horizontal sway (translational) velocity; Directed along the yi-axis
OutList['PtfmTVzi'] = False # (m/s); Platform vertical heave (translational) velocity; Directed along the zi-axis
OutList['PtfmTAxt'] = False # (m/s^2); Platform horizontal surge (translational) acceleration; Directed along the xt-axis
OutList['PtfmTAyt'] = False # (m/s^2); Platform horizontal sway (translational) acceleration; Directed along the yt-axis
OutList['PtfmTAzt'] = False # (m/s^2); Platform vertical heave (translational) acceleration; Directed along the zt-axis
OutList['PtfmTAxi'] = False # (m/s^2); Platform horizontal surge (translational) acceleration; Directed along the xi-axis
OutList['PtfmTAyi'] = False # (m/s^2); Platform horizontal sway (translational) acceleration; Directed along the yi-axis
OutList['PtfmTAzi'] = False # (m/s^2); Platform vertical heave (translational) acceleration; Directed along the zi-axis
OutList['PtfmRDxi'] = False # (deg); Platform roll tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the xi-axis
OutList['PtfmRoll'] = False # (deg); Platform roll tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 3rd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the xi-axis
OutList['PtfmRDyi'] = False # (deg); Platform pitch tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the yi-axis
OutList['PtfmPitch'] = False # (deg); Platform pitch tilt angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 2nd rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the yi-axis
OutList['PtfmRDzi'] = False # (deg); Platform yaw angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the zi-axis
OutList['PtfmYaw'] = False # (deg); Platform yaw angular (rotational) displacement. In ADAMS, it is output as an Euler angle computed as the 1st rotation in the yaw-pitch-roll rotation sequence. It is not output as an Euler angle in FAST, which assumes small rotational platform displacements, so that the rotation sequence does not matter.; About the zi-axis
OutList['PtfmRVxt'] = False # (deg/s); Platform roll tilt angular (rotational) velocity; About the xt-axis
OutList['PtfmRVyt'] = False # (deg/s); Platform pitch tilt angular (rotational) velocity; About the yt-axis
OutList['PtfmRVzt'] = False # (deg/s); Platform yaw angular (rotational) velocity; About the zt-axis
OutList['PtfmRVxi'] = False # (deg/s); Platform roll tilt angular (rotational) velocity; About the xi-axis
OutList['PtfmRVyi'] = False # (deg/s); Platform pitch tilt angular (rotational) velocity; About the yi-axis
OutList['PtfmRVzi'] = False # (deg/s); Platform yaw angular (rotational) velocity; About the zi-axis
OutList['PtfmRAxt'] = False # (deg/s^2); Platform roll tilt angular (rotational) acceleration; About the xt-axis
OutList['PtfmRAyt'] = False # (deg/s^2); Platform pitch tilt angular (rotational) acceleration; About the yt-axis
OutList['PtfmRAzt'] = False # (deg/s^2); Platform yaw angular (rotational) acceleration; About the zt-axis
OutList['PtfmRAxi'] = False # (deg/s^2); Platform roll tilt angular (rotational) acceleration; About the xi-axis
OutList['PtfmRAyi'] = False # (deg/s^2); Platform pitch tilt angular (rotational) acceleration; About the yi-axis
OutList['PtfmRAzi'] = False # (deg/s^2); Platform yaw angular (rotational) acceleration; About the zi-axis
# Blade 1 Root Loads
OutList['RootFxc1'] = False # (kN); Blade 1 out-of-plane shear force at the blade root; Directed along the xc1-axis
OutList['RootFyc1'] = False # (kN); Blade 1 in-plane shear force at the blade root; Directed along the yc1-axis
OutList['RootFzc1'] = False # (kN); Blade 1 axial force at the blade root; Directed along the zc1- and zb1-axes
OutList['RootFzb1'] = False # (kN); Blade 1 axial force at the blade root; Directed along the zc1- and zb1-axes
OutList['RootFxb1'] = False # (kN); Blade 1 flapwise shear force at the blade root; Directed along the xb1-axis
OutList['RootFyb1'] = False # (kN); Blade 1 edgewise shear force at the blade root; Directed along the yb1-axis
OutList['RootMxc1'] = False # (kN m); Blade 1 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc1-axis
OutList['RootMIP1'] = False # (kN m); Blade 1 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc1-axis
OutList['RootMyc1'] = False # (kN m); Blade 1 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc1-axis
OutList['RootMOoP1'] = False # (kN m); Blade 1 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc1-axis
OutList['RootMzc1'] = False # (kN m); Blade 1 pitching moment at the blade root; About the zc1- and zb1-axes
OutList['RootMzb1'] = False # (kN m); Blade 1 pitching moment at the blade root; About the zc1- and zb1-axes
OutList['RootMxb1'] = False # (kN m); Blade 1 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb1-axis
OutList['RootMEdg1'] = False # (kN m); Blade 1 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb1-axis
OutList['RootMyb1'] = False # (kN m); Blade 1 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb1-axis
OutList['RootMFlp1'] = False # (kN m); Blade 1 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb1-axis
# Blade 2 Root Loads
OutList['RootFxc2'] = False # (kN); Blade 2 out-of-plane shear force at the blade root; Directed along the xc2-axis
OutList['RootFyc2'] = False # (kN); Blade 2 in-plane shear force at the blade root; Directed along the yc2-axis
OutList['RootFzc2'] = False # (kN); Blade 2 axial force at the blade root; Directed along the zc2- and zb2-axes
OutList['RootFzb2'] = False # (kN); Blade 2 axial force at the blade root; Directed along the zc2- and zb2-axes
OutList['RootFxb2'] = False # (kN); Blade 2 flapwise shear force at the blade root; Directed along the xb2-axis
OutList['RootFyb2'] = False # (kN); Blade 2 edgewise shear force at the blade root; Directed along the yb2-axis
OutList['RootMxc2'] = False # (kN m); Blade 2 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc2-axis
OutList['RootMIP2'] = False # (kN m); Blade 2 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc2-axis
OutList['RootMyc2'] = False # (kN m); Blade 2 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc2-axis
OutList['RootMOoP2'] = False # (kN m); Blade 2 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc2-axis
OutList['RootMzc2'] = False # (kN m); Blade 2 pitching moment at the blade root; About the zc2- and zb2-axes
OutList['RootMzb2'] = False # (kN m); Blade 2 pitching moment at the blade root; About the zc2- and zb2-axes
OutList['RootMxb2'] = False # (kN m); Blade 2 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb2-axis
OutList['RootMEdg2'] = False # (kN m); Blade 2 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb2-axis
OutList['RootMyb2'] = False # (kN m); Blade 2 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb2-axis
OutList['RootMFlp2'] = False # (kN m); Blade 2 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb2-axis
# Blade 3 Root Loads
OutList['RootFxc3'] = False # (kN); Blade 3 out-of-plane shear force at the blade root; Directed along the xc3-axis
OutList['RootFyc3'] = False # (kN); Blade 3 in-plane shear force at the blade root; Directed along the yc3-axis
OutList['RootFzc3'] = False # (kN); Blade 3 axial force at the blade root; Directed along the zc3- and zb3-axes
OutList['RootFzb3'] = False # (kN); Blade 3 axial force at the blade root; Directed along the zc3- and zb3-axes
OutList['RootFxb3'] = False # (kN); Blade 3 flapwise shear force at the blade root; Directed along the xb3-axis
OutList['RootFyb3'] = False # (kN); Blade 3 edgewise shear force at the blade root; Directed along the yb3-axis
OutList['RootMxc3'] = False # (kN m); Blade 3 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc3-axis
OutList['RootMIP3'] = False # (kN m); Blade 3 in-plane moment (i.e., the moment caused by in-plane forces) at the blade root; About the xc3-axis
OutList['RootMyc3'] = False # (kN m); Blade 3 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc3-axis
OutList['RootMOoP3'] = False # (kN m); Blade 3 out-of-plane moment (i.e., the moment caused by out-of-plane forces) at the blade root; About the yc3-axis
OutList['RootMzc3'] = False # (kN m); Blade 3 pitching moment at the blade root; About the zc3- and zb3-axes
OutList['RootMzb3'] = False # (kN m); Blade 3 pitching moment at the blade root; About the zc3- and zb3-axes
OutList['RootMxb3'] = False # (kN m); Blade 3 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb3-axis
OutList['RootMEdg3'] = False # (kN m); Blade 3 edgewise moment (i.e., the moment caused by edgewise forces) at the blade root; About the xb3-axis
OutList['RootMyb3'] = False # (kN m); Blade 3 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb3-axis
OutList['RootMFlp3'] = False # (kN m); Blade 3 flapwise moment (i.e., the moment caused by flapwise forces) at the blade root; About the yb3-axis
# Blade 1 Local Span Loads
OutList['Spn1MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 1; About the local xb1-axis
OutList['Spn1MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 1; About the local yb1-axis
OutList['Spn1MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 1; About the local zb1-axis
OutList['Spn2MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 2; About the local xb1-axis
OutList['Spn2MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 2; About the local yb1-axis
OutList['Spn2MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 2; About the local zb1-axis
OutList['Spn3MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 3; About the local xb1-axis
OutList['Spn3MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 3; About the local yb1-axis
OutList['Spn3MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 3; About the local zb1-axis
OutList['Spn4MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 4; About the local xb1-axis
OutList['Spn4MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 4; About the local yb1-axis
OutList['Spn4MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 4; About the local zb1-axis
OutList['Spn5MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 5; About the local xb1-axis
OutList['Spn5MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 5; About the local yb1-axis
OutList['Spn5MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 5; About the local zb1-axis
OutList['Spn6MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 6; About the local xb1-axis
OutList['Spn6MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 6; About the local yb1-axis
OutList['Spn6MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 6; About the local zb1-axis
OutList['Spn7MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 7; About the local xb1-axis
OutList['Spn7MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 7; About the local yb1-axis
OutList['Spn7MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 7; About the local zb1-axis
OutList['Spn8MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 8; About the local xb1-axis
OutList['Spn8MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 8; About the local yb1-axis
OutList['Spn8MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 8; About the local zb1-axis
OutList['Spn9MLxb1'] = False # (kN m); Blade 1 local edgewise moment at span station 9; About the local xb1-axis
OutList['Spn9MLyb1'] = False # (kN m); Blade 1 local flapwise moment at span station 9; About the local yb1-axis
OutList['Spn9MLzb1'] = False # (kN m); Blade 1 local pitching moment at span station 9; About the local zb1-axis
OutList['Spn1FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 1; Directed along the local xb1-axis
OutList['Spn1FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 1; Directed along the local yb1-axis
OutList['Spn1FLzb1'] = False # (kN); Blade 1 local axial force at span station 1; Directed along the local zb1-axis
OutList['Spn2FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 2; Directed along the local xb1-axis
OutList['Spn2FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 2; Directed along the local yb1-axis
OutList['Spn2FLzb1'] = False # (kN); Blade 1 local axial force at span station 2; Directed along the local zb1-axis
OutList['Spn3FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 3; Directed along the local xb1-axis
OutList['Spn3FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 3; Directed along the local yb1-axis
OutList['Spn3FLzb1'] = False # (kN); Blade 1 local axial force at span station 3; Directed along the local zb1-axis
OutList['Spn4FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 4; Directed along the local xb1-axis
OutList['Spn4FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 4; Directed along the local yb1-axis
OutList['Spn4FLzb1'] = False # (kN); Blade 1 local axial force at span station 4; Directed along the local zb1-axis
OutList['Spn5FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 5; Directed along the local xb1-axis
OutList['Spn5FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 5; Directed along the local yb1-axis
OutList['Spn5FLzb1'] = False # (kN); Blade 1 local axial force at span station 5; Directed along the local zb1-axis
OutList['Spn6FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 6; Directed along the local xb1-axis
OutList['Spn6FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 6; Directed along the local yb1-axis
OutList['Spn6FLzb1'] = False # (kN); Blade 1 local axial force at span station 6; Directed along the local zb1-axis
OutList['Spn7FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 7; Directed along the local xb1-axis
OutList['Spn7FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 7; Directed along the local yb1-axis
OutList['Spn7FLzb1'] = False # (kN); Blade 1 local axial force at span station 7; Directed along the local zb1-axis
OutList['Spn8FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 8; Directed along the local xb1-axis
OutList['Spn8FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 8; Directed along the local yb1-axis
OutList['Spn8FLzb1'] = False # (kN); Blade 1 local axial force at span station 8; Directed along the local zb1-axis
OutList['Spn9FLxb1'] = False # (kN); Blade 1 local flapwise shear force at span station 9; Directed along the local xb1-axis
OutList['Spn9FLyb1'] = False # (kN); Blade 1 local edgewise shear force at span station 9; Directed along the local yb1-axis
OutList['Spn9FLzb1'] = False # (kN); Blade 1 local axial force at span station 9; Directed along the local zb1-axis
# Blade 2 Local Span Loads
OutList['Spn1MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 1; About the local xb2-axis
OutList['Spn1MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 1; About the local yb2-axis
OutList['Spn1MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 1; About the local zb2-axis
OutList['Spn2MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 2; About the local xb2-axis
OutList['Spn2MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 2; About the local yb2-axis
OutList['Spn2MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 2; About the local zb2-axis
OutList['Spn3MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 3; About the local xb2-axis
OutList['Spn3MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 3; About the local yb2-axis
OutList['Spn3MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 3; About the local zb2-axis
OutList['Spn4MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 4; About the local xb2-axis
OutList['Spn4MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 4; About the local yb2-axis
OutList['Spn4MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 4; About the local zb2-axis
OutList['Spn5MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 5; About the local xb2-axis
OutList['Spn5MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 5; About the local yb2-axis
OutList['Spn5MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 5; About the local zb2-axis
OutList['Spn6MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 6; About the local xb2-axis
OutList['Spn6MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 6; About the local yb2-axis
OutList['Spn6MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 6; About the local zb2-axis
OutList['Spn7MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 7; About the local xb2-axis
OutList['Spn7MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 7; About the local yb2-axis
OutList['Spn7MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 7; About the local zb2-axis
OutList['Spn8MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 8; About the local xb2-axis
OutList['Spn8MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 8; About the local yb2-axis
OutList['Spn8MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 8; About the local zb2-axis
OutList['Spn9MLxb2'] = False # (kN m); Blade 2 local edgewise moment at span station 9; About the local xb2-axis
OutList['Spn9MLyb2'] = False # (kN m); Blade 2 local flapwise moment at span station 9; About the local yb2-axis
OutList['Spn9MLzb2'] = False # (kN m); Blade 2 local pitching moment at span station 9; About the local zb2-axis
OutList['Spn1FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 1; Directed along the local xb2-axis
OutList['Spn1FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 1; Directed along the local yb2-axis
OutList['Spn1FLzb2'] = False # (kN); Blade 2 local axial force at span station 1; Directed along the local zb2-axis
OutList['Spn2FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 2; Directed along the local xb2-axis
OutList['Spn2FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 2; Directed along the local yb2-axis
OutList['Spn2FLzb2'] = False # (kN); Blade 2 local axial force at span station 2; Directed along the local zb2-axis
OutList['Spn3FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 3; Directed along the local xb2-axis
OutList['Spn3FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 3; Directed along the local yb2-axis
OutList['Spn3FLzb2'] = False # (kN); Blade 2 local axial force at span station 3; Directed along the local zb2-axis
OutList['Spn4FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 4; Directed along the local xb2-axis
OutList['Spn4FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 4; Directed along the local yb2-axis
OutList['Spn4FLzb2'] = False # (kN); Blade 2 local axial force at span station 4; Directed along the local zb2-axis
OutList['Spn5FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 5; Directed along the local xb2-axis
OutList['Spn5FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 5; Directed along the local yb2-axis
OutList['Spn5FLzb2'] = False # (kN); Blade 2 local axial force at span station 5; Directed along the local zb2-axis
OutList['Spn6FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 6; Directed along the local xb2-axis
OutList['Spn6FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 6; Directed along the local yb2-axis
OutList['Spn6FLzb2'] = False # (kN); Blade 2 local axial force at span station 6; Directed along the local zb2-axis
OutList['Spn7FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 7; Directed along the local xb2-axis
OutList['Spn7FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 7; Directed along the local yb2-axis
OutList['Spn7FLzb2'] = False # (kN); Blade 2 local axial force at span station 7; Directed along the local zb2-axis
OutList['Spn8FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 8; Directed along the local xb2-axis
OutList['Spn8FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 8; Directed along the local yb2-axis
OutList['Spn8FLzb2'] = False # (kN); Blade 2 local axial force at span station 8; Directed along the local zb2-axis
OutList['Spn9FLxb2'] = False # (kN); Blade 2 local flapwise shear force at span station 9; Directed along the local xb2-axis
OutList['Spn9FLyb2'] = False # (kN); Blade 2 local edgewise shear force at span station 9; Directed along the local yb2-axis
OutList['Spn9FLzb2'] = False # (kN); Blade 2 local axial force at span station 9; Directed along the local zb2-axis
# Blade 3 Local Span Loads
OutList['Spn1MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 1; About the local xb3-axis
OutList['Spn1MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 1; About the local yb3-axis
OutList['Spn1MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 1; About the local zb3-axis
OutList['Spn2MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 2; About the local xb3-axis
OutList['Spn2MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 2; About the local yb3-axis
OutList['Spn2MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 2; About the local zb3-axis
OutList['Spn3MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 3; About the local xb3-axis
OutList['Spn3MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 3; About the local yb3-axis
OutList['Spn3MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 3; About the local zb3-axis
OutList['Spn4MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 4; About the local xb3-axis
OutList['Spn4MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 4; About the local yb3-axis
OutList['Spn4MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 4; About the local zb3-axis
OutList['Spn5MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 5; About the local xb3-axis
OutList['Spn5MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 5; About the local yb3-axis
OutList['Spn5MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 5; About the local zb3-axis
OutList['Spn6MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 6; About the local xb3-axis
OutList['Spn6MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 6; About the local yb3-axis
OutList['Spn6MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 6; About the local zb3-axis
OutList['Spn7MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 7; About the local xb3-axis
OutList['Spn7MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 7; About the local yb3-axis
OutList['Spn7MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 7; About the local zb3-axis
OutList['Spn8MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 8; About the local xb3-axis
OutList['Spn8MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 8; About the local yb3-axis
OutList['Spn8MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 8; About the local zb3-axis
OutList['Spn9MLxb3'] = False # (kN m); Blade 3 local edgewise moment at span station 9; About the local xb3-axis
OutList['Spn9MLyb3'] = False # (kN m); Blade 3 local flapwise moment at span station 9; About the local yb3-axis
OutList['Spn9MLzb3'] = False # (kN m); Blade 3 local pitching moment at span station 9; About the local zb3-axis
OutList['Spn1FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 1; Directed along the local xb3-axis
OutList['Spn1FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 1; Directed along the local yb3-axis
OutList['Spn1FLzb3'] = False # (kN); Blade 3 local axial force at span station 1; Directed along the local zb3-axis
OutList['Spn2FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 2; Directed along the local xb3-axis
OutList['Spn2FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 2; Directed along the local yb3-axis
OutList['Spn2FLzb3'] = False # (kN); Blade 3 local axial force at span station 2; Directed along the local zb3-axis
OutList['Spn3FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 3; Directed along the local xb3-axis
OutList['Spn3FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 3; Directed along the local yb3-axis
OutList['Spn3FLzb3'] = False # (kN); Blade 3 local axial force at span station 3; Directed along the local zb3-axis
OutList['Spn4FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 4; Directed along the local xb3-axis
OutList['Spn4FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 4; Directed along the local yb3-axis
OutList['Spn4FLzb3'] = False # (kN); Blade 3 local axial force at span station 4; Directed along the local zb3-axis
OutList['Spn5FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 5; Directed along the local xb3-axis
OutList['Spn5FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 5; Directed along the local yb3-axis
OutList['Spn5FLzb3'] = False # (kN); Blade 3 local axial force at span station 5; Directed along the local zb3-axis
OutList['Spn6FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 6; Directed along the local xb3-axis
OutList['Spn6FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 6; Directed along the local yb3-axis
OutList['Spn6FLzb3'] = False # (kN); Blade 3 local axial force at span station 6; Directed along the local zb3-axis
OutList['Spn7FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 7; Directed along the local xb3-axis
OutList['Spn7FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 7; Directed along the local yb3-axis
OutList['Spn7FLzb3'] = False # (kN); Blade 3 local axial force at span station 7; Directed along the local zb3-axis
OutList['Spn8FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 8; Directed along the local xb3-axis
OutList['Spn8FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 8; Directed along the local yb3-axis
OutList['Spn8FLzb3'] = False # (kN); Blade 3 local axial force at span station 8; Directed along the local zb3-axis
OutList['Spn9FLxb3'] = False # (kN); Blade 3 local flapwise shear force at span station 9; Directed along the local xb3-axis
OutList['Spn9FLyb3'] = False # (kN); Blade 3 local edgewise shear force at span station 9; Directed along the local yb3-axis
OutList['Spn9FLzb3'] = False # (kN); Blade 3 local axial force at span station 9; Directed along the local zb3-axis
# Hub and Rotor Loads
OutList['LSShftFxa'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
OutList['LSShftFxs'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
OutList['LSSGagFxa'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
OutList['LSSGagFxs'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
OutList['RotThrust'] = False # (kN); Low-speed shaft thrust force (this is constant along the shaft and is equivalent to the rotor thrust force); Directed along the xa- and xs-axes
OutList['LSShftFya'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the ya-axis
OutList['LSSGagFya'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the ya-axis
OutList['LSShftFza'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the za-axis
OutList['LSSGagFza'] = False # (kN); Rotating low-speed shaft shear force (this is constant along the shaft); Directed along the za-axis
OutList['LSShftFys'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the ys-axis
OutList['LSSGagFys'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the ys-axis
OutList['LSShftFzs'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the zs-axis
OutList['LSSGagFzs'] = False # (kN); Nonrotating low-speed shaft shear force (this is constant along the shaft); Directed along the zs-axis
OutList['LSShftMxa'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['LSShftMxs'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['LSSGagMxa'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['LSSGagMxs'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['RotTorq'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['LSShftTq'] = False # (kN m); Low-speed shaft torque (this is constant along the shaft and is equivalent to the rotor torque); About the xa- and xs-axes
OutList['LSSTipMya'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the ya-axis
OutList['LSSTipMza'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the za-axis
OutList['LSSTipMys'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the ys-axis
OutList['LSSTipMzs'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft tip (teeter pin for 2-blader, apex of rotation for 3-blader); About the zs-axis
OutList['CThrstAzm'] = False # (deg); Azimuth location of the center of thrust. This is estimated using values of LSSTipMys, LSSTipMzs, and RotThrust.; About the xa- and xs-axes
OutList['CThrstRad'] = False # (-); Dimensionless radial (arm) location of the center of thrust. This is estimated using values of LSSTipMys, LSSTipMzs, and RotThrust. (nondimensionalized using the undeflected tip radius normal to the shaft and limited to values between 0 and 1 (inclusive)); Always positive (directed radially outboard at azimuth angle CThrstAzm)
OutList['CThrstArm'] = False # (-); Dimensionless radial (arm) location of the center of thrust. This is estimated using values of LSSTipMys, LSSTipMzs, and RotThrust. (nondimensionalized using the undeflected tip radius normal to the shaft and limited to values between 0 and 1 (inclusive)); Always positive (directed radially outboard at azimuth angle CThrstAzm)
OutList['RotPwr'] = False # (kW); Rotor power (this is equivalent to the low-speed shaft power); N/A
OutList['LSShftPwr'] = False # (kW); Rotor power (this is equivalent to the low-speed shaft power); N/A
OutList['RotCq'] = False # (-); Rotor torque coefficient (this is equivalent to the low-speed shaft torque coefficient); N/A
OutList['LSShftCq'] = False # (-); Rotor torque coefficient (this is equivalent to the low-speed shaft torque coefficient); N/A
OutList['RotCp'] = False # (-); Rotor power coefficient (this is equivalent to the low-speed shaft power coefficient); N/A
OutList['LSShftCp'] = False # (-); Rotor power coefficient (this is equivalent to the low-speed shaft power coefficient); N/A
OutList['RotCt'] = False # (-); Rotor thrust coefficient (this is equivalent to the low-speed shaft thrust coefficient); N/A
OutList['LSShftCt'] = False # (-); Rotor thrust coefficient (this is equivalent to the low-speed shaft thrust coefficient); N/A
# Shaft Strain Gage Loads
OutList['LSSGagMya'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the ya-axis
OutList['LSSGagMza'] = False # (kN m); Rotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the za-axis
OutList['LSSGagMys'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the ys-axis
OutList['LSSGagMzs'] = False # (kN m); Nonrotating low-speed shaft bending moment at the shaft's strain gage (shaft strain gage located by input ShftGagL); About the zs-axis
# Generator and High-Speed Shaft Loads
OutList['HSShftTq'] = False # (kN m); High-speed shaft torque (this is constant along the shaft); Same sign as LSShftTq / RotTorq / LSShftMxa / LSShftMxs / LSSGagMxa / LSSGagMxs
OutList['HSShftPwr'] = False # (kW); High-speed shaft power; Same sign as HSShftTq
OutList['HSShftCq'] = False # (-); High-speed shaft torque coefficient; N/A
OutList['HSShftCp'] = False # (-); High-speed shaft power coefficient; N/A
OutList['GenTq'] = False # (kN m); Electrical generator torque; Positive reflects power extracted and negative represents a motoring-up situation (power input)
OutList['GenPwr'] = False # (kW); Electrical generator power; Same sign as GenTq
OutList['GenCq'] = False # (-); Electrical generator torque coefficient; N/A
OutList['GenCp'] = False # (-); Electrical generator power coefficient; N/A
OutList['HSSBrTq'] = False # (kN m); High-speed shaft brake torque (i.e., the moment applied to the high-speed shaft by the brake); Always positive (indicating dissipation of power)
# Rotor-Furl Bearing Loads
OutList['RFrlBrM'] = False # (kN m); Rotor-furl bearing moment; About the rotor-furl axis
# Tail-Furl Bearing Loads
OutList['TFrlBrM'] = False # (kN m); Tail-furl bearing moment; About the tail-furl axis
# Tail Fin Aerodynamic Loads
OutList['TFinAlpha'] = False # (deg); Tail fin angle of attack. This is the angle between the relative velocity of the wind-inflow at the tail fin center-of-pressure and the tail fin chordline.; About the tail fin z-axis, which is the axis in the tail fin plane normal to the chordline
OutList['TFinCLift'] = False # (-); Tail fin dimensionless lift coefficient; N/A
OutList['TFinCDrag'] = False # (-); Tail fin dimensionless drag coefficient; N/A
OutList['TFinDnPrs'] = False # (Pa); Tail fin dynamic pressure, equal to 1/2*AirDens*Vrel^2 where Vrel is the relative velocity of the wind-inflow at the tail fin center-of-pressure; N/A
OutList['TFinCPFx'] = False # (kN); Tangential aerodynamic force at the tail fin center-of-pressure; Directed along the tail fin x-axis, which is the axis along the chordline, positive towards the trailing edge
OutList['TFinCPFy'] = False # (kN); Normal aerodynamic force at the tail fin center-of-pressure; Directed along the tail fin y-axis, which is orthogonal to the tail fin plane
# Tower-Top / Yaw Bearing Loads
OutList['YawBrFxn'] = False # (kN); Rotating (with nacelle) tower-top / yaw bearing shear force; Directed along the xn-axis
OutList['YawBrFyn'] = False # (kN); Rotating (with nacelle) tower-top / yaw bearing shear force; Directed along the yn-axis
OutList['YawBrFzn'] = False # (kN); Tower-top / yaw bearing axial force; Directed along the zn- and zp-axes
OutList['YawBrFzp'] = False # (kN); Tower-top / yaw bearing axial force; Directed along the zn- and zp-axes
OutList['YawBrFxp'] = False # (kN); Tower-top / yaw bearing fore-aft (nonrotating) shear force; Directed along the xp-axis
OutList['YawBrFyp'] = False # (kN); Tower-top / yaw bearing side-to-side (nonrotating) shear force; Directed along the yp-axis
OutList['YawBrMxn'] = False # (kN m); Rotating (with nacelle) tower-top / yaw bearing roll moment; About the xn-axis
OutList['YawBrMyn'] = False # (kN m); Rotating (with nacelle) tower-top / yaw bearing pitch moment; About the yn-axis
OutList['YawBrMzn'] = False # (kN m); Tower-top / yaw bearing yaw moment; About the zn- and zp-axes
OutList['YawBrMzp'] = False # (kN m); Tower-top / yaw bearing yaw moment; About the zn- and zp-axes
OutList['YawMom'] = False # (kN m); Tower-top / yaw bearing yaw moment; About the zn- and zp-axes
OutList['YawBrMxp'] = False # (kN m); Nonrotating tower-top / yaw bearing roll moment; About the xp-axis
OutList['YawBrMyp'] = False # (kN m); Nonrotating tower-top / yaw bearing pitch moment; About the yp-axis
# Tower Base Loads
OutList['TwrBsFxt'] = False # (kN); Tower base fore-aft shear force; Directed along the xt-axis
OutList['TwrBsFyt'] = False # (kN); Tower base side-to-side shear force; Directed along the yt-axis
OutList['TwrBsFzt'] = False # (kN); Tower base axial force; Directed along the zt-axis
OutList['TwrBsMxt'] = False # (kN m); Tower base roll (or side-to-side) moment (i.e., the moment caused by side-to-side forces); About the xt-axis
OutList['TwrBsMyt'] = False # (kN m); Tower base pitching (or fore-aft) moment (i.e., the moment caused by fore-aft forces); About the yt-axis
OutList['TwrBsMzt'] = False # (kN m); Tower base yaw (or torsional) moment; About the zt-axis
# Local Tower Loads
OutList['TwHt1MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 1; About the local xt-axis
OutList['TwHt1MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 1; About the local yt-axis
OutList['TwHt1MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 1; About the local zt-axis
OutList['TwHt2MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 2; About the local xt-axis
OutList['TwHt2MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 2; About the local yt-axis
OutList['TwHt2MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 2; About the local zt-axis
OutList['TwHt3MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 3; About the local xt-axis
OutList['TwHt3MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 3; About the local yt-axis
OutList['TwHt3MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 3; About the local zt-axis
OutList['TwHt4MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 4; About the local xt-axis
OutList['TwHt4MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 4; About the local yt-axis
OutList['TwHt4MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 4; About the local zt-axis
OutList['TwHt5MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 5; About the local xt-axis
OutList['TwHt5MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 5; About the local yt-axis
OutList['TwHt5MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 5; About the local zt-axis
OutList['TwHt6MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 6; About the local xt-axis
OutList['TwHt6MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 6; About the local yt-axis
OutList['TwHt6MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 6; About the local zt-axis
OutList['TwHt7MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 7; About the local xt-axis
OutList['TwHt7MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 7; About the local yt-axis
OutList['TwHt7MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 7; About the local zt-axis
OutList['TwHt8MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 8; About the local xt-axis
OutList['TwHt8MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 8; About the local yt-axis
OutList['TwHt8MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 8; About the local zt-axis
OutList['TwHt9MLxt'] = False # (kN m); Local tower roll (or side-to-side) moment of tower gage 9; About the local xt-axis
OutList['TwHt9MLyt'] = False # (kN m); Local tower pitching (or fore-aft) moment of tower gage 9; About the local yt-axis
OutList['TwHt9MLzt'] = False # (kN m); Local tower yaw (or torsional) moment of tower gage 9; About the local zt-axis
OutList['TwHt1FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 1; About the local xt-axis
OutList['TwHt1FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 1; About the local yt-axis
OutList['TwHt1FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 1; About the local zt-axis
OutList['TwHt2FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 2; About the local xt-axis
OutList['TwHt2FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 2; About the local yt-axis
OutList['TwHt2FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 2; About the local zt-axis
OutList['TwHt3FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 3; About the local xt-axis
OutList['TwHt3FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 3; About the local yt-axis
OutList['TwHt3FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 3; About the local zt-axis
OutList['TwHt4FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 4; About the local xt-axis
OutList['TwHt4FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 4; About the local yt-axis
OutList['TwHt4FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 4; About the local zt-axis
OutList['TwHt5FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 5; About the local xt-axis
OutList['TwHt5FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 5; About the local yt-axis
OutList['TwHt5FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 5; About the local zt-axis
OutList['TwHt6FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 6; About the local xt-axis
OutList['TwHt6FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 6; About the local yt-axis
OutList['TwHt6FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 6; About the local zt-axis
OutList['TwHt7FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 7; About the local xt-axis
OutList['TwHt7FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 7; About the local yt-axis
OutList['TwHt7FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 7; About the local zt-axis
OutList['TwHt8FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 8; About the local xt-axis
OutList['TwHt8FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 8; About the local yt-axis
OutList['TwHt8FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 8; About the local zt-axis
OutList['TwHt9FLxt'] = False # (kN); Local tower roll (or side-to-side) force of tower gage 9; About the local xt-axis
OutList['TwHt9FLyt'] = False # (kN); Local tower pitching (or fore-aft) force of tower gage 9; About the local yt-axis
OutList['TwHt9FLzt'] = False # (kN); Local tower yaw (or torsional) force of tower gage 9; About the local zt-axis
# Platform Loads
OutList['PtfmFxt'] = False # (kN); Platform horizontal surge shear force; Directed along the xt-axis
OutList['PtfmFyt'] = False # (kN); Platform horizontal sway shear force; Directed along the yt-axis
OutList['PtfmFzt'] = False # (kN); Platform vertical heave force; Directed along the zt-axis
OutList['PtfmFxi'] = False # (kN); Platform horizontal surge shear force; Directed along the xi-axis
OutList['PtfmFyi'] = False # (kN); Platform horizontal sway shear force; Directed along the yi-axis
OutList['PtfmFzi'] = False # (kN); Platform vertical heave force; Directed along the zi-axis
OutList['PtfmMxt'] = False # (kN m); Platform roll tilt moment; About the xt-axis
OutList['PtfmMyt'] = False # (kN m); Platform pitch tilt moment; About the yt-axis
OutList['PtfmMzt'] = False # (kN m); Platform yaw moment; About the zt-axis
OutList['PtfmMxi'] = False # (kN m); Platform roll tilt moment; About the xi-axis
OutList['PtfmMyi'] = False # (kN m); Platform pitch tilt moment; About the yi-axis
OutList['PtfmMzi'] = False # (kN m); Platform yaw moment; About the zi-axis
# Mooring Line Loads
OutList['Fair1Ten'] = False # (kN); ;
OutList['Fair1Ang'] = False # (deg); ;
OutList['Anch1Ten'] = False # (kN); ;
OutList['Anch1Ang'] = False # (deg); ;
OutList['Fair2Ten'] = False # (kN); ;
OutList['Fair2Ang'] = False # (deg); ;
OutList['Anch2Ten'] = False # (kN); ;
OutList['Anch2Ang'] = False # (deg); ;
OutList['Fair3Ten'] = False # (kN); ;
OutList['Fair3Ang'] = False # (deg); ;
OutList['Anch3Ten'] = False # (kN); ;
OutList['Anch3Ang'] = False # (deg); ;
OutList['Fair4Ten'] = False # (kN); ;
OutList['Fair4Ang'] = False # (deg); ;
OutList['Anch4Ten'] = False # (kN); ;
OutList['Anch4Ang'] = False # (deg); ;
OutList['Fair5Ten'] = False # (kN); ;
OutList['Fair5Ang'] = False # (deg); ;
OutList['Anch5Ten'] = False # (kN); ;
OutList['Anch5Ang'] = False # (deg); ;
OutList['Fair6Ten'] = False # (kN); ;
OutList['Fair6Ang'] = False # (deg); ;
OutList['Anch6Ten'] = False # (kN); ;
OutList['Anch6Ang'] = False # (deg); ;
OutList['Fair7Ten'] = False # (kN); ;
OutList['Fair7Ang'] = False # (deg); ;
OutList['Anch7Ten'] = False # (kN); ;
OutList['Anch7Ang'] = False # (deg); ;
OutList['Fair8Ten'] = False # (kN); ;
OutList['Fair8Ang'] = False # (deg); ;
OutList['Anch8Ten'] = False # (kN); ;
OutList['Anch8Ang'] = False # (deg); ;
OutList['Fair9Ten'] = False # (kN); ;
OutList['Fair9Ang'] = False # (deg); ;
OutList['Anch9Ten'] = False # (kN); ;
OutList['Anch9Ang'] = False # (deg); ;
# Wave Motions
OutList['WaveElev'] = False # (m); ;
OutList['Wave1Vxi'] = False # (m/s); ;
OutList['Wave1Vyi'] = False # (m/s); ;
OutList['Wave1Vzi'] = False # (m/s); ;
OutList['Wave1Axi'] = False # (m/s^2); ;
OutList['Wave1Ayi'] = False # (m/s^2); ;
OutList['Wave1Azi'] = False # (m/s^2); ;
OutList['Wave2Vxi'] = False # (m/s); ;
OutList['Wave2Vyi'] = False # (m/s); ;
OutList['Wave2Vzi'] = False # (m/s); ;
OutList['Wave2Axi'] = False # (m/s^2); ;
OutList['Wave2Ayi'] = False # (m/s^2); ;
OutList['Wave2Azi'] = False # (m/s^2); ;
OutList['Wave3Vxi'] = False # (m/s); ;
OutList['Wave3Vyi'] = False # (m/s); ;
OutList['Wave3Vzi'] = False # (m/s); ;
OutList['Wave3Axi'] = False # (m/s^2); ;
OutList['Wave3Ayi'] = False # (m/s^2); ;
OutList['Wave3Azi'] = False # (m/s^2); ;
OutList['Wave4Vxi'] = False # (m/s); ;
OutList['Wave4Vyi'] = False # (m/s); ;
OutList['Wave4Vzi'] = False # (m/s); ;
OutList['Wave4Axi'] = False # (m/s^2); ;
OutList['Wave4Ayi'] = False # (m/s^2); ;
OutList['Wave4Azi'] = False # (m/s^2); ;
OutList['Wave5Vxi'] = False # (m/s); ;
OutList['Wave5Vyi'] = False # (m/s); ;
OutList['Wave5Vzi'] = False # (m/s); ;
OutList['Wave5Axi'] = False # (m/s^2); ;
OutList['Wave5Ayi'] = False # (m/s^2); ;
OutList['Wave5Azi'] = False # (m/s^2); ;
OutList['Wave6Vxi'] = False # (m/s); ;
OutList['Wave6Vyi'] = False # (m/s); ;
OutList['Wave6Vzi'] = False # (m/s); ;
OutList['Wave6Axi'] = False # (m/s^2); ;
OutList['Wave6Ayi'] = False # (m/s^2); ;
OutList['Wave6Azi'] = False # (m/s^2); ;
OutList['Wave7Vxi'] = False # (m/s); ;
OutList['Wave7Vyi'] = False # (m/s); ;
OutList['Wave7Vzi'] = False # (m/s); ;
OutList['Wave7Axi'] = False # (m/s^2); ;
OutList['Wave7Ayi'] = False # (m/s^2); ;
OutList['Wave7Azi'] = False # (m/s^2); ;
OutList['Wave8Vxi'] = False # (m/s); ;
OutList['Wave8Vyi'] = False # (m/s); ;
OutList['Wave8Vzi'] = False # (m/s); ;
OutList['Wave8Axi'] = False # (m/s^2); ;
OutList['Wave8Ayi'] = False # (m/s^2); ;
OutList['Wave8Azi'] = False # (m/s^2); ;
OutList['Wave9Vxi'] = False # (m/s); ;
OutList['Wave9Vyi'] = False # (m/s); ;
OutList['Wave9Vzi'] = False # (m/s); ;
OutList['Wave9Axi'] = False # (m/s^2); ;
OutList['Wave9Ayi'] = False # (m/s^2); ;
OutList['Wave9Azi'] = False # (m/s^2); ;
# Internal Degrees of Freedom
OutList['Q_B1E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 1;
OutList['Q_B2E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 2;
OutList['Q_B3E1'] = False # (m); Displacement of 1st edgewise bending-mode DOF of blade 3;
OutList['Q_B1F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 1;
OutList['Q_B2F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 2;
OutList['Q_B3F1'] = False # (m); Displacement of 1st flapwise bending-mode DOF of blade 3;
OutList['Q_B1F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 1;
OutList['Q_B2F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 2;
OutList['Q_B3F2'] = False # (m); Displacement of 2nd flapwise bending-mode DOF of blade 3;
OutList['Q_Teet'] = False # (rad); Displacement of hub teetering DOF;
OutList['Q_DrTr'] = False # (rad); Displacement of drivetrain rotational-flexibility DOF;
OutList['Q_GeAz'] = False # (rad); Displacement of variable speed generator DOF;
OutList['Q_RFrl'] = False # (rad); Displacement of rotor-furl DOF;
OutList['Q_TFrl'] = False # (rad); Displacement of tail-furl DOF;
OutList['Q_Yaw'] = False # (rad); Displacement of nacelle yaw DOF;
OutList['Q_TFA1'] = False # (m); Displacement of 1st tower fore-aft bending mode DOF;
OutList['Q_TSS1'] = False # (m); Displacement of 1st tower side-to-side bending mode DOF;
OutList['Q_TFA2'] = False # (m); Displacement of 2nd tower fore-aft bending mode DOF;
OutList['Q_TSS2'] = False # (m); Displacement of 2nd tower side-to-side bending mode DOF;
OutList['Q_Sg'] = False # (m); Displacement of platform horizontal surge translation DOF;
OutList['Q_Sw'] = False # (m); Displacement of platform horizontal sway translation DOF;
OutList['Q_Hv'] = False # (m); Displacement of platform vertical heave translation DOF;
OutList['Q_R'] = False # (rad); Displacement of platform roll tilt rotation DOF;
OutList['Q_P'] = False # (rad); Displacement of platform pitch tilt rotation DOF;
OutList['Q_Y'] = False # (rad); Displacement of platform yaw rotation DOF;
OutList['QD_B1E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 1;
OutList['QD_B2E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 2;
OutList['QD_B3E1'] = False # (m/s); Velocity of 1st edgewise bending-mode DOF of blade 3;
OutList['QD_B1F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 1;
OutList['QD_B2F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 2;
OutList['QD_B3F1'] = False # (m/s); Velocity of 1st flapwise bending-mode DOF of blade 3;
OutList['QD_B1F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 1;
OutList['QD_B2F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 2;
OutList['QD_B3F2'] = False # (m/s); Velocity of 2nd flapwise bending-mode DOF of blade 3;
OutList['QD_Teet'] = False # (rad/s); Velocity of hub teetering DOF;
OutList['QD_DrTr'] = False # (rad/s); Velocity of drivetrain rotational-flexibility DOF;
OutList['QD_GeAz'] = False # (rad/s); Velocity of variable speed generator DOF;
OutList['QD_RFrl'] = False # (rad/s); Velocity of rotor-furl DOF;
OutList['QD_TFrl'] = False # (rad/s); Velocity of tail-furl DOF;
OutList['QD_Yaw'] = False # (rad/s); Velocity of nacelle yaw DOF;
OutList['QD_TFA1'] = False # (m/s); Velocity of 1st tower fore-aft bending mode DOF;
OutList['QD_TSS1'] = False # (m/s); Velocity of 1st tower side-to-side bending mode DOF;
OutList['QD_TFA2'] = False # (m/s); Velocity of 2nd tower fore-aft bending mode DOF;
OutList['QD_TSS2'] = False # (m/s); Velocity of 2nd tower side-to-side bending mode DOF;
OutList['QD_Sg'] = False # (m/s); Velocity of platform horizontal surge translation DOF;
OutList['QD_Sw'] = False # (m/s); Velocity of platform horizontal sway translation DOF;
OutList['QD_Hv'] = False # (m/s); Velocity of platform vertical heave translation DOF;
OutList['QD_R'] = False # (rad/s); Velocity of platform roll tilt rotation DOF;
OutList['QD_P'] = False # (rad/s); Velocity of platform pitch tilt rotation DOF;
OutList['QD_Y'] = False # (rad/s); Velocity of platform yaw rotation DOF;
OutList['QD2_B1E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 1;
OutList['QD2_B2E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 2;
OutList['QD2_B3E1'] = False # (m/s^2); Acceleration of 1st edgewise bending-mode DOF of blade 3;
OutList['QD2_B1F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 1;
OutList['QD2_B2F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 2;
OutList['QD2_B3F1'] = False # (m/s^2); Acceleration of 1st flapwise bending-mode DOF of blade 3;
OutList['QD2_B1F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 1;
OutList['QD2_B2F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 2;
OutList['QD2_B3F2'] = False # (m/s^2); Acceleration of 2nd flapwise bending-mode DOF of blade 3;
OutList['QD2_Teet'] = False # (rad/s^2); Acceleration of hub teetering DOF;
OutList['QD2_DrTr'] = False # (rad/s^2); Acceleration of drivetrain rotational-flexibility DOF;
OutList['QD2_GeAz'] = False # (rad/s^2); Acceleration of variable speed generator DOF;
OutList['QD2_RFrl'] = False # (rad/s^2); Acceleration of rotor-furl DOF;
OutList['QD2_TFrl'] = False # (rad/s^2); Acceleration of tail-furl DOF;
OutList['QD2_Yaw'] = False # (rad/s^2); Acceleration of nacelle yaw DOF;
OutList['QD2_TFA1'] = False # (m/s^2); Acceleration of 1st tower fore-aft bending mode DOF;
OutList['QD2_TSS1'] = False # (m/s^2); Acceleration of 1st tower side-to-side bending mode DOF;
OutList['QD2_TFA2'] = False # (m/s^2); Acceleration of 2nd tower fore-aft bending mode DOF;
OutList['QD2_TSS2'] = False # (m/s^2); Acceleration of 2nd tower side-to-side bending mode DOF;
OutList['QD2_Sg'] = False # (m/s^2); Acceleration of platform horizontal surge translation DOF;
OutList['QD2_Sw'] = False # (m/s^2); Acceleration of platform horizontal sway translation DOF;
OutList['QD2_Hv'] = False # (m/s^2); Acceleration of platform vertical heave translation DOF;
OutList['QD2_R'] = False # (rad/s^2); Acceleration of platform roll tilt rotation DOF;
OutList['QD2_P'] = False # (rad/s^2); Acceleration of platform pitch tilt rotation DOF;
OutList['QD2_Y'] = False # (rad/s^2); Acceleration of platform yaw rotation DOF;
""" Final Output Dictionary """
Fst7Output = {}
Fst7Output['OutList'] = OutList | /rosco-toolbox-2.3.0.tar.gz/rosco-toolbox-2.3.0/ROSCO_toolbox/ofTools/fast_io/FAST_vars_out.py | 0.552298 | 0.728917 | FAST_vars_out.py | pypi |
# Author Tully Foote/tfoote@willowgarage.com
from __future__ import print_function
import os
import sys
import stat
import subprocess
import tempfile
from .core import rd_debug
if sys.hexversion > 0x03000000: # Python3
python3 = True
else:
python3 = False
env = dict(os.environ)
env['LANG'] = 'C'
def read_stdout(cmd, capture_stderr=False):
"""
Execute given command and return stdout and if requested also stderr.
:param cmd: command in a form that Popen understands (list of strings or one string)
:param suppress_stderr: If evaluates to True, capture output from stderr as
well and return it as well.
:return: if `capture_stderr` is evaluates to False, return the stdout of
the program as string (Note: stderr will be printed to the running
terminal). If it evaluates to True, tuple of strings: stdout output and
standard error output each as string.
"""
if capture_stderr:
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, env=env)
std_out, std_err = p.communicate()
if python3:
return std_out.decode(), std_err.decode()
else:
return std_out, std_err
else:
p = subprocess.Popen(cmd, stdout=subprocess.PIPE, env=env)
std_out, std_err = p.communicate() # ignore stderr
if python3:
return std_out.decode()
else:
return std_out
def create_tempfile_from_string_and_execute(string_script, path=None, exec_fn=None):
"""
:param path: (optional) path to temp directory, or ``None`` to use default temp directory, ``str``
:param exec_fn: override subprocess.call with alternate executor (for testing)
"""
if path is None:
path = tempfile.gettempdir()
result = 1
try:
script_ext = '.bat' if os.name == 'nt' else ''
fh = tempfile.NamedTemporaryFile('w', suffix=script_ext, delete=False)
fh.write(string_script)
fh.close()
rd_debug('Executing script below with cwd=%s\n{{{\n%s\n}}}\n' % (path, string_script))
try:
os.chmod(fh.name, stat.S_IRWXU)
if exec_fn is None:
result = subprocess.call(fh.name, cwd=path)
else:
result = exec_fn(fh.name, cwd=path)
except OSError as ex:
print('Execution failed with OSError: %s' % (ex), file=sys.stderr)
finally:
if os.path.exists(fh.name):
os.remove(fh.name)
rd_debug('Return code was: %s' % (result))
return result == 0 | /rosdep-0.22.2.tar.gz/rosdep-0.22.2/src/rosdep2/shell_utils.py | 0.47171 | 0.185467 | shell_utils.py | pypi |
# Author Ken Conley/kwc@willowgarage.com
"""
Base API for loading rosdep information by package or stack name.
This API is decoupled from the ROS packaging system to enable multiple
implementations of rosdep, including ones that don't rely on the ROS
packaging system. This is necessary, for example, to implement a
version of rosdep that works against tarballs of released stacks.
"""
import yaml
from .core import InvalidData
ROSDEP_YAML = 'rosdep.yaml'
class RosdepLoader:
"""
Base API for loading rosdep information by package or stack name.
"""
def load_rosdep_yaml(self, yaml_contents, origin):
"""
Utility routine for unmarshalling rosdep data encoded as YAML.
:param origin: origin of yaml contents (for error messages)
:raises: :exc:`yaml.YAMLError`
"""
try:
return yaml.safe_load(yaml_contents)
except yaml.YAMLError as e:
raise InvalidData('Invalid YAML in [%s]: %s' % (origin, e), origin=origin)
def load_view(self, view_name, rosdep_db, verbose=False):
"""
Load view data into rosdep_db. If the view has already been
loaded into rosdep_db, this method does nothing.
:param view_name: name of ROS stack to load, ``str``
:param rosdep_db: database to load stack data into, :class:`RosdepDatabase`
:raises: :exc:`InvalidData`
:raises: :exc:`rospkg.ResourceNotFound` if view cannot be located
"""
raise NotImplementedError(view_name, rosdep_db, verbose) # pychecker
def get_loadable_resources(self):
raise NotImplementedError()
def get_loadable_views(self):
raise NotImplementedError()
def get_rosdeps(self, resource_name, implicit=True):
"""
:raises: :exc:`rospkg.ResourceNotFound` if *resource_name* cannot be found.
"""
raise NotImplementedError(resource_name, implicit) # pychecker
def get_view_key(self, resource_name):
"""
Map *resource_name* to a view key. In rospkg, this maps a ROS
package name to a ROS stack name. If *resource_name* is a ROS
stack name, it returns the ROS stack name.
:returns: Name of view that *resource_name* is in, ``None`` if no associated view.
:raises: :exc:`rospkg.ResourceNotFound` if *resource_name* cannot be found.
"""
raise NotImplementedError(resource_name) | /rosdep-0.22.2.tar.gz/rosdep-0.22.2/src/rosdep2/loader.py | 0.856902 | 0.309506 | loader.py | pypi |
# Author Ken Conley/kwc@willowgarage.com
"""
Underlying model of rosdep data. The basic data model of rosdep is to
store a dictionary of data indexed by view name (i.e. ROS stack name).
This data includes a dictionary mapping rosdep dependency names to
rules and the view dependencies.
This is a lower-level representation. Higher-level representation can
combine these rosdep dependency maps and view dependencies together
into a combined view on which queries can be made.
"""
class RosdepDatabaseEntry(object):
"""
Stores rosdep data and metadata for a single view.
"""
def __init__(self, rosdep_data, view_dependencies, origin):
"""
:param rosdep_data: raw rosdep dictionary map for view
:param view_dependencies: list of view dependency names
:param origin: name of where data originated, e.g. filename
"""
assert isinstance(rosdep_data, dict), 'RosdepDatabaseEntry() rosdep_data is not a dict: %s' % rosdep_data
self.rosdep_data = rosdep_data
self.view_dependencies = view_dependencies
self.origin = origin
class RosdepDatabase(object):
"""
Stores loaded rosdep data for multiple views.
"""
def __init__(self):
self._rosdep_db = {} # {view_name: RosdepDatabaseEntry}
def is_loaded(self, view_name):
"""
:param view_name: name of view to check, ``str``
:returns: ``True`` if *view_name* has been loaded into this
database.
"""
return view_name in self._rosdep_db
def mark_loaded(self, view_name):
"""
If view is not already loaded, this will mark it as such. This in effect sets the data for the view to be empty.
:param view_name: name of view to mark as loaded
"""
self.set_view_data(view_name, {}, [], None)
def set_view_data(self, view_name, rosdep_data, view_dependencies, origin):
"""
Set data associated with view. This will create a new
:class:`RosdepDatabaseEntry`.
:param rosdep_data: rosdep data map to associated with view.
This will be copied.
:param origin: origin of view data, e.g. filepath of ``rosdep.yaml``
"""
self._rosdep_db[view_name] = RosdepDatabaseEntry(rosdep_data.copy(), view_dependencies, origin)
def get_view_names(self):
"""
:returns: list of view names that are loaded into this database.
"""
return self._rosdep_db.keys()
def get_view_data(self, view_name):
"""
:returns: :class:`RosdepDatabaseEntry` of given view.
:raises: :exc:`KeyError` if no entry for *view_name*
"""
return self._rosdep_db[view_name]
def get_view_dependencies(self, view_name):
"""
:raises: :exc:`KeyError` if *view_name* is not an entry, or if
all of view's dependencies have not been properly loaded.
"""
entry = self.get_view_data(view_name)
dependencies = entry.view_dependencies[:]
# compute full set of dependencies by iterating over
# dependencies in reverse order and prepending.
for s in reversed(entry.view_dependencies):
dependencies = self.get_view_dependencies(s) + dependencies
# make unique preserving order
unique_deps = []
for d in dependencies:
if d not in unique_deps:
unique_deps.append(d)
return unique_deps | /rosdep-0.22.2.tar.gz/rosdep-0.22.2/src/rosdep2/model.py | 0.891764 | 0.586967 | model.py | pypi |
# Author William Woodall/wjwwood@gmail.com
from collections import defaultdict
class Resolution(dict):
"""A default dictionary for use in the :class:`DependencyGraph`."""
def __init__(self):
super(Resolution, self).__init__()
self['installer_key'] = None
self['install_keys'] = []
self['dependencies'] = []
self['is_root'] = True
class DependencyGraph(defaultdict):
"""
Provides a mechanism for generating a list of resolutions which preserves the dependency order.
The :class:`DependencyGraph` inherits from a *defaultdict*, so it can be used as such to load
the dependency graph data into it.
Example::
# Dependency graph:: A-B-C
dg = DependencyGraph()
dg['A']['installer_key'] = 'a_installer'
dg['A']['install_keys'] = ['a']
dg['A']['dependencies'] = ['B']
dg['B']['installer_key'] = 'b_installer'
dg['B']['install_keys'] = ['b']
dg['B']['dependencies'] = ['C']
dg['C']['installer_key'] = 'c_installer'
dg['C']['install_keys'] = ['c']
dg['C']['dependencies'] = []
result = dg.get_ordered_uninstalled()
"""
def __init__(self):
defaultdict.__init__(self, Resolution)
def detect_cycles(self, rosdep_key, traveled_keys):
"""
Recursive function to detect cycles in the dependency graph.
:param rosdep_key: This is the rosdep key to use as the root in the cycle exploration.
:param traveled_keys: A list of rosdep_keys that have been traversed thus far.
:raises: :exc:`AssertionError` if the rosdep_key is in the traveled keys, indicating a cycle has occurred.
"""
assert rosdep_key not in traveled_keys, 'A cycle in the dependency graph occurred with key `%s`.' % rosdep_key
traveled_keys.append(rosdep_key)
for dependency in self[rosdep_key]['dependencies']:
self.detect_cycles(dependency, traveled_keys)
def validate(self):
"""
Performs validations on the dependency graph, like cycle detection and invalid rosdep key detection.
:raises: :exc:`AssertionError` if a cycle is detected.
:raises: :exc:`KeyError` if an invalid rosdep_key is found in the dependency graph.
"""
for rosdep_key in self:
# Ensure all dependencies have definitions
# i.e.: Ensure we aren't pointing to invalid rosdep keys
for dependency in self[rosdep_key]['dependencies']:
if dependency not in self:
raise KeyError(
'Invalid Graph Structure: rosdep key `%s` does not exist in the dictionary of resolutions.'
% dependency)
self[dependency]['is_root'] = False
# Check each entry for cyclical dependencies
for rosdep_key in self:
self.detect_cycles(rosdep_key, [])
def get_ordered_dependency_list(self):
"""
Generates an ordered list of dependencies using the dependency graph.
:returns: *[(installer_key, [install_keys])]*, ``[(str, [str])]``. *installer_key* is the key
that denotes which installed the accompanying *install_keys* are for. *installer_key* are something
like ``apt`` or ``homebrew``. *install_keys* are something like ``boost`` or ``ros-fuerte-ros_comm``.
:raises: :exc:`AssertionError` if a cycle is detected.
:raises: :exc:`KeyError` if an invalid rosdep_key is found in the dependency graph.
"""
# Validate the graph
self.validate()
# Generate the dependency list
dep_list = []
for rosdep_key in self:
if self[rosdep_key]['is_root']:
dep_list.extend(self.__get_ordered_uninstalled(rosdep_key))
# Make the list unique and remove empty entries
result = []
for item in dep_list:
if item not in result and item[1] != []:
result.append(item)
# Squash the results by installer_key
squashed_result = []
previous_installer_key = None
for installer_key, resolved in result:
if previous_installer_key != installer_key:
squashed_result.append((installer_key, []))
previous_installer_key = installer_key
squashed_result[-1][1].extend(resolved)
return squashed_result
def __get_ordered_uninstalled(self, key):
uninstalled = []
for dependency in self[key]['dependencies']:
uninstalled.extend(self.__get_ordered_uninstalled(dependency))
uninstalled.append((self[key]['installer_key'], self[key]['install_keys']))
return uninstalled | /rosdep-0.22.2.tar.gz/rosdep-0.22.2/src/rosdep2/dependency_graph.py | 0.922395 | 0.289334 | dependency_graph.py | pypi |
from collections.abc import Sequence
import numpy as np
import pandas as pd
ALPHA = np.exp(2 / 3 * np.pi * 1j)
"""complex: Phasor rotation operator `alpha`, which rotates a phasor vector counterclockwise by 120
degrees when multiplied by it."""
A = np.array(
[
[1, 1, 1],
[1, ALPHA**2, ALPHA],
[1, ALPHA, ALPHA**2],
],
dtype=complex,
)
"""numpy.ndarray[complex]: "A" matrix: transformation matrix from phasor to symmetrical components."""
_A_INV = np.linalg.inv(A)
def phasor_to_sym(v_abc: Sequence[complex]) -> np.ndarray[complex]:
"""Compute the symmetrical components `(0, +, -)` from the phasor components `(a, b, c)`."""
v_012 = _A_INV @ np.asarray(v_abc).reshape((3, 1))
return v_012
def sym_to_phasor(v_012: Sequence[complex]) -> np.ndarray[complex]:
"""Compute the phasor components `(a, b, c)` from the symmetrical components `(0, +, -)`."""
v_abc = A @ np.asarray(v_012).reshape((3, 1))
return v_abc
def series_phasor_to_sym(s_abc: pd.Series) -> pd.Series:
"""Compute the symmetrical components `(0, +, -)` from the phasor components `(a, b, c)` of a series.
Args:
s_abc:
Series of phasor components (voltage, current, ...). The series must have a
multi-index with a `'phase'` level containing the phases in order (a -> b -> c).
Returns:
Series of the symmetrical components representing the input phasor series. The series has
a multi-index with the phase level replaced by a `'sequence'` level of values
`('zero', 'pos', 'neg')`.
Example:
Say we have a pandas series of three-phase voltages of every bus in the network:
>>> voltage
bus_id phase
vs an 200000000000.0+0.00000000j
bn -10000.000000-17320.508076j
cn -10000.000000+17320.508076j
bus an 19999.00000095+0.00000000j
bn -9999.975000-17320.464775j
cn -9999.975000+17320.464775j
Name: voltage, dtype: complex128
We can get the `zero`, `positive`, and `negative` sequences of the voltage using:
>>> voltage_sym_components = series_phasor_to_sym(voltage)
>>> voltage_sym_components
bus_id sequence
bus zero 3.183231e-12-9.094947e-13j
pos 1.999995e+04+3.283594e-12j
neg -1.796870e-07-2.728484e-12j
vs zero 5.002221e-12-9.094947e-13j
pos 2.000000e+04+3.283596e-12j
neg -1.796880e-07-1.818989e-12j
Name: voltage, dtype: complex128
We can now access each sequence of the symmetrical components individually:
>>> voltage_sym_components.loc[:, "zero"] # get zero sequence values
bus_id
bus 3.183231e-12-9.094947e-13j
vs 5.002221e-12-9.094947e-13j
Name: voltage, dtype: complex128
"""
if not isinstance(s_abc, pd.Series):
raise TypeError("Input must be a pandas Series.")
s_012: pd.Series = (
s_abc.unstack("phase")
.apply(lambda x: phasor_to_sym(x).flatten(), axis="columns", result_type="expand")
.rename(columns={0: "zero", 1: "pos", 2: "neg"})
.stack()
)
s_012.name = s_abc.name
s_012.index = s_012.index.set_names("sequence", level=-1).set_levels(
s_012.index.levels[-1].astype(pd.CategoricalDtype(categories=["zero", "pos", "neg"], ordered=True)), level=-1
)
return s_012
def calculate_voltages(potentials: np.ndarray, phases: str) -> np.ndarray:
"""Calculate the voltages between phases given the potentials of each phase.
Args:
potentials:
Array of the complex potentials of each phase.
phases:
String of the phases in order. If a neutral exists, it must be the last.
Returns:
Array of the voltages between phases. If a neutral exists, the voltages are Phase-Neutral.
Otherwise, the voltages are Phase-Phase.
Example:
>>> potentials = 230 * np.array([1, np.exp(-2j*np.pi/3), np.exp(2j*np.pi/3), 0], dtype=complex)
>>> calculate_voltages(potentials, "abcn")
array([ 230. +0.j , -115.-199.18584287j, -115.+199.18584287j])
>>> potentials = np.array([230, 230 * np.exp(-2j*np.pi/3)], dtype=complex)
>>> calculate_voltages(potentials, "ab")
array([345.+199.18584287j])
>>> calculate_voltages(np.array([230, 0], dtype=complex), "an")
array([230.+0.j])
"""
assert len(potentials) == len(phases), "Number of potentials must match number of phases."
if "n" in phases: # Van, Vbn, Vcn
# we know "n" is the last phase
voltages = potentials[:-1] - potentials[-1]
else: # Vab, Vbc, Vca
if len(phases) == 2: # noqa: SIM108
# V = potentials[0] - potentials[1] (but as array)
voltages = potentials[:1] - potentials[1:]
else:
# np.roll(["a", "b", "c"], -1) -> ["b", "c", "a"]
voltages = potentials - np.roll(potentials, -1)
return voltages
def calculate_voltage_phases(phases: str) -> list[str]:
"""Calculate the composite phases of the voltages given the phases of an element.
Args:
phases:
String of the phases in order. If a neutral exists, it must be the last.
Returns:
List of the composite phases of the voltages.
Example:
>>> calculate_voltage_phases("an")
['an']
>>> calculate_voltage_phases("ab")
['ab']
>>> calculate_voltage_phases("abc")
['ab', 'bc', 'ca']
>>> calculate_voltage_phases("abcn")
['an', 'bn', 'cn']
"""
if "n" in phases: # "an", "bn", "cn"
return [p + "n" for p in phases[:-1]]
else: # "ab", "bc", "ca"
if len(phases) == 2:
return [phases]
else:
return [p1 + p2 for p1, p2 in zip(phases, np.roll(list(phases), -1))] | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/converters.py | 0.943764 | 0.680786 | converters.py | pypi |
import unicodedata
from enum import Enum, auto
from typing import Union
from typing_extensions import Self
class RoseauLoadFlowExceptionCode(Enum):
"""Error codes used by Roseau Load Flow."""
# Generic
BAD_GEOMETRY_TYPE = auto()
BAD_PHASE = auto()
BAD_ID_TYPE = auto()
# Grounds and Potential references
BAD_GROUND_ID = auto()
BAD_POTENTIAL_REF_ID = auto()
# Buses
BAD_BUS_ID = auto()
BAD_BUS_TYPE = auto()
BAD_POTENTIALS_SIZE = auto()
BAD_VOLTAGES_SIZE = auto()
BAD_SHORT_CIRCUIT = auto()
# Branches
BAD_BRANCH_ID = auto()
BAD_BRANCH_TYPE = auto()
BAD_Z_LINE_SHAPE = auto()
BAD_Y_SHUNT_SHAPE = auto()
BAD_LINE_MODEL = auto()
BAD_LINE_TYPE = auto()
BAD_CONDUCTOR_TYPE = auto()
BAD_INSULATOR_TYPE = auto()
BAD_Z_LINE_VALUE = auto()
BAD_Y_SHUNT_VALUE = auto()
BAD_TRANSFORMER_WINDINGS = auto()
BAD_TRANSFORMER_TYPE = auto()
BAD_TRANSFORMER_VOLTAGES = auto()
BAD_TRANSFORMER_PARAMETERS = auto()
BAD_TYPE_NAME_SYNTAX = auto()
BAD_LENGTH_VALUE = auto()
# Control
BAD_CONTROL_TYPE = auto()
BAD_CONTROL_VALUE = auto()
# Projection
BAD_PROJECTION_TYPE = auto()
BAD_PROJECTION_VALUE = auto()
# Flexible parameter
BAD_SMAX_VALUE = auto()
# Load
BAD_LOAD_ID = auto()
BAD_LOAD_TYPE = auto()
BAD_I_SIZE = auto()
BAD_Z_SIZE = auto()
BAD_Z_VALUE = auto()
BAD_S_SIZE = auto()
BAD_S_VALUE = auto()
BAD_PARAMETERS_SIZE = auto()
# Source
BAD_SOURCE_ID = auto()
# Network
BAD_VOLTAGES_SOURCES_CONNECTION = auto()
SWITCHES_LOOP = auto()
NO_POTENTIAL_REFERENCE = auto()
SEVERAL_POTENTIAL_REFERENCE = auto()
UNKNOWN_ELEMENT = auto()
NO_VOLTAGE_SOURCE = auto()
BAD_ELEMENT_OBJECT = auto()
DISCONNECTED_ELEMENT = auto()
BAD_ELEMENT_ID = auto()
NO_LOAD_FLOW_CONVERGENCE = auto()
BAD_REQUEST = auto()
BAD_LOAD_FLOW_RESULT = auto()
LOAD_FLOW_NOT_RUN = auto()
SEVERAL_NETWORKS = auto()
TOO_MANY_BUSES = auto()
BAD_JACOBIAN = auto()
# Solver
BAD_SOLVER_NAME = auto()
BAD_SOLVER_PARAMS = auto()
NETWORK_SOLVER_MISMATCH = auto()
# DGS export
DGS_BAD_PHASE_TECHNOLOGY = auto()
DGS_BAD_PHASE_NUMBER = auto()
# JSON export
JSON_LINE_PARAMETERS_DUPLICATES = auto()
JSON_TRANSFORMER_PARAMETERS_DUPLICATES = auto()
JSON_PREF_INVALID = auto()
JSON_NO_RESULTS = auto()
# Catalogue Mixin
CATALOGUE_MISSING = auto()
CATALOGUE_NOT_FOUND = auto()
CATALOGUE_SEVERAL_FOUND = auto()
@classmethod
def package_name(cls) -> str:
return "roseau.load_flow"
def __str__(self) -> str:
return f"{self.package_name()}.{self.name}".lower()
def __eq__(self, other) -> bool:
if isinstance(other, str):
return other.lower() == str(self).lower()
return super().__eq__(other)
@classmethod
def from_string(cls, string: Union[str, "RoseauLoadFlowExceptionCode"]) -> Self:
"""A method to convert a string into an error code enumerated type.
Args:
string:
The string depicted the error code. If a good element is given
Returns:
The enumerated type value corresponding with `string`.
"""
if isinstance(string, cls):
return string
elif isinstance(string, str):
pass
else:
string = str(string)
# Withdraw accents and make lowercase
string = unicodedata.normalize("NFKD", string.lower()).encode("ASCII", "ignore").decode()
# Withdraw the package prefix (e.g. roseau.core)
error_str = string.removeprefix(f"{cls.package_name()}.")
# Get the value of this string
return cls[error_str.upper()]
class RoseauLoadFlowException(Exception):
"""Base exception for Roseau Load Flow."""
def __init__(self, msg: str, code: RoseauLoadFlowExceptionCode, *args: object) -> None:
"""Constructor of RoseauLoadFlowException.
Args:
msg:
A text description that provides the reason of the exception and potential
solution.
code:
The code that identifies the reason of the exception.
"""
super().__init__(msg, code, *args)
self.msg = msg
self.code = code
def __str__(self) -> str:
return f"{self.msg} [{self.code.name.lower()}]" | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/exceptions.py | 0.85817 | 0.19671 | exceptions.py | pypi |
import logging
import warnings
from abc import ABC
from typing import TYPE_CHECKING, Any, ClassVar, NoReturn, Optional, TypeVar, Union
import shapely
from shapely.geometry import shape
from shapely.geometry.base import BaseGeometry
from roseau.load_flow.exceptions import RoseauLoadFlowException, RoseauLoadFlowExceptionCode
from roseau.load_flow.typing import Id
from roseau.load_flow.utils import Identifiable, JsonMixin
if TYPE_CHECKING:
from roseau.load_flow.network import ElectricalNetwork
logger = logging.getLogger(__name__)
_T = TypeVar("_T")
class Element(ABC, Identifiable, JsonMixin):
"""An abstract class of an element in an Electrical network."""
allowed_phases: ClassVar[frozenset[str]] # frozenset for immutability and uniqueness
"""The allowed phases for this element type.
It is a frozen set of strings like ``"abc"`` or ``"an"`` etc. The order of the phases is
important. For a full list of supported phases, use ``print(<Element class>.allowed_phases)``.
"""
def __init__(self, id: Id, **kwargs: Any) -> None:
"""Element constructor.
Args:
id:
A unique ID of the element in the network. Two elements of the same type cannot
have the same ID.
"""
super().__init__(id)
self._connected_elements: list[Element] = []
self._network: Optional[ElectricalNetwork] = None
@property
def network(self) -> Optional["ElectricalNetwork"]:
"""Return the network the element belong to (if any)."""
return self._network
@classmethod
def _check_phases(cls, id: Id, allowed_phases: Optional[frozenset[str]] = None, **kwargs: str) -> None:
if allowed_phases is None:
allowed_phases = cls.allowed_phases
name, phases = kwargs.popitem() # phases, phases1 or phases2
if phases not in allowed_phases:
msg = (
f"{cls.__name__} of id {id!r} got invalid {name} {phases!r}, allowed values are: "
f"{sorted(allowed_phases)}"
)
logger.error(msg)
raise RoseauLoadFlowException(msg, RoseauLoadFlowExceptionCode.BAD_PHASE)
def _set_network(self, value: Optional["ElectricalNetwork"]) -> None:
"""Network setter with the ability to set the network to `None`. This method must not be exposed through a
traditional public setter. It is internally used in the `_connect` and `_disconnect` methods.
Args:
value:
The new network for `self`. May also be None.
"""
# The setter cannot be used to replace an existing network
if self._network is not None and value is not None and self._network != value:
self._raise_several_network()
# Add/remove the element to the dictionaries of elements in the network
if value is None:
if self._network is not None:
self._network._disconnect_element(element=self)
else:
value._connect_element(element=self)
# Assign the new network to self
self._network = value
# In case of disconnection, do nothing to connected elements
if value is None:
return
# Recursively call this method to the elements connected to self
for e in self._connected_elements:
if e.network == value:
continue
else:
# Recursive call
e._set_network(value)
def _connect(self, *elements: "Element") -> None:
"""Connect this element to another element.
Args:
elements:
The elements to connect to self.
"""
# Get the common network. May raise exception
network = self.network
for element in elements:
if network is None:
network = element.network
elif element.network is not None and element.network != network:
element._raise_several_network()
# Modify objects. Append to the connected_elements
for element in elements:
if element not in self._connected_elements:
self._connected_elements.append(element)
if self not in element._connected_elements:
element._connected_elements.append(self)
# Propagate the new network to `self` and other newly connected elements (recursively)`
if network is not None:
self._set_network(network)
def _disconnect(self) -> None:
"""Remove all the connections with the other elements."""
for element in self._connected_elements:
element._connected_elements.remove(self)
self._connected_elements = []
self._set_network(None)
def _invalidate_network_results(self) -> None:
"""Invalidate the network making the result"""
if self.network is not None:
self.network._results_valid = False
def _res_getter(self, value: Optional[_T], warning: bool) -> _T:
"""A safe getter for load flow results.
Args:
value:
The optional array(s) of results.
warning:
If True and if the results may be invalid (because of an invalid network), a warning log is emitted.
Returns:
The input if valid. May also emit a warning for potential invalid results.
"""
if value is None:
msg = (
f"Results for {type(self).__name__} {self.id!r} are not available because the load "
f"flow has not been run yet."
)
logger.error(msg)
raise RoseauLoadFlowException(msg, RoseauLoadFlowExceptionCode.LOAD_FLOW_NOT_RUN)
if warning and self.network is not None and not self.network._results_valid:
warnings.warn(
message=(
"The results of this element may be outdated. Please re-run a load flow to "
"ensure the validity of results."
),
category=UserWarning,
stacklevel=2,
)
return value
@staticmethod
def _parse_geometry(geometry: Union[str, None, Any]) -> Optional[BaseGeometry]:
if geometry is None:
return None
elif isinstance(geometry, str):
return shapely.from_wkt(geometry)
else:
return shape(geometry)
def _raise_several_network(self) -> NoReturn:
"""Raise an exception when there are several networks involved during a connection of elements."""
msg = f"The {type(self).__name__} {self.id!r} is already assigned to another network."
logger.error(msg)
raise RoseauLoadFlowException(msg, code=RoseauLoadFlowExceptionCode.SEVERAL_NETWORKS) | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/models/core.py | 0.893555 | 0.291532 | core.py | pypi |
import logging
from typing import Any, Optional
from shapely import Point
from roseau.load_flow.exceptions import RoseauLoadFlowException, RoseauLoadFlowExceptionCode
from roseau.load_flow.models.branches import AbstractBranch
from roseau.load_flow.models.buses import Bus
from roseau.load_flow.models.transformers.parameters import TransformerParameters
from roseau.load_flow.typing import Id, JsonDict
logger = logging.getLogger(__name__)
class Transformer(AbstractBranch):
"""A generic transformer model.
The model parameters are defined in the ``parameters``.
See Also:
:doc:`Transformer models documentation </models/Transformer/index>`
"""
branch_type = "transformer"
allowed_phases = Bus.allowed_phases
"""The allowed phases for a transformer are:
- P-P-P or P-P-P-N: ``"abc"``, ``"abcn"`` (three-phase transformer)
- P-P or P-N: ``"ab"``, ``"bc"``, ``"ca"``, ``"an"``, ``"bn"``, ``"cn"`` (single-phase
transformer or primary of center-tapped transformer)
- P-P-N: ``"abn"``, ``"bcn"``, ``"can"`` (secondary of center-tapped transformer)
"""
_allowed_phases_three = frozenset({"abc", "abcn"})
_allowed_phases_single = frozenset({"ab", "bc", "ca", "an", "bn", "cn"})
_allowed_phases_center_secondary = frozenset({"abn", "bcn", "can"})
def __init__(
self,
id: Id,
bus1: Bus,
bus2: Bus,
*,
parameters: TransformerParameters,
tap: float = 1.0,
phases1: Optional[str] = None,
phases2: Optional[str] = None,
geometry: Optional[Point] = None,
**kwargs: Any,
) -> None:
"""Transformer constructor.
Args:
id:
A unique ID of the transformer in the network branches.
bus1:
Bus to connect the first extremity of the transformer.
bus2:
Bus to connect the first extremity of the transformer.
tap:
The tap of the transformer, for example 1.02.
parameters:
The parameters of the transformer.
phases1:
The phases of the first extremity of the transformer. A string like ``"abc"`` or
``"abcn"`` etc. The order of the phases is important. For a full list of supported
phases, see the class attribute :attr:`allowed_phases`. All phases must be present
in the connected bus. By default determined from the transformer type.
phases2:
The phases of the second extremity of the transformer. See ``phases1``.
geometry:
The geometry of the transformer.
"""
if geometry is not None and not isinstance(geometry, Point):
msg = f"The geometry for a {type(self)} must be a point: {geometry.geom_type} provided."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_GEOMETRY_TYPE)
if parameters.type == "single":
phases1, phases2 = self._compute_phases_single(
id=id, bus1=bus1, bus2=bus2, phases1=phases1, phases2=phases2
)
elif parameters.type == "center":
phases1, phases2 = self._compute_phases_center(
id=id, bus1=bus1, bus2=bus2, phases1=phases1, phases2=phases2
)
else:
phases1, phases2 = self._compute_phases_three(
id=id, bus1=bus1, bus2=bus2, parameters=parameters, phases1=phases1, phases2=phases2
)
super().__init__(id, bus1, bus2, phases1=phases1, phases2=phases2, geometry=geometry, **kwargs)
self.tap = tap
self._parameters = parameters
@property
def tap(self) -> float:
"""The tap of the transformer, for example 1.02."""
return self._tap
@tap.setter
def tap(self, value: float) -> None:
if value > 1.1:
logger.warning(f"The provided tap {value:.2f} is higher than 1.1. A good value is between 0.9 and 1.1.")
if value < 0.9:
logger.warning(f"The provided tap {value:.2f} is lower than 0.9. A good value is between 0.9 and 1.1.")
self._tap = value
self._invalidate_network_results()
@property
def parameters(self) -> TransformerParameters:
"""The parameters of the transformer."""
return self._parameters
@parameters.setter
def parameters(self, value: TransformerParameters) -> None:
type1 = self._parameters.type
type2 = value.type
if type1 != type2:
msg = f"The updated type changed for transformer {self.id!r}: {type1} to {type2}."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_TRANSFORMER_TYPE)
self._parameters = value
self._invalidate_network_results()
def to_dict(self, include_geometry: bool = True) -> JsonDict:
return {**super().to_dict(include_geometry=include_geometry), "params_id": self.parameters.id, "tap": self.tap}
def _compute_phases_three(
self,
id: Id,
bus1: Bus,
bus2: Bus,
parameters: TransformerParameters,
phases1: Optional[str],
phases2: Optional[str],
) -> tuple[str, str]:
w1_has_neutral = "y" in parameters.winding1.lower() or "z" in parameters.winding1.lower()
w2_has_neutral = "y" in parameters.winding2.lower() or "z" in parameters.winding2.lower()
if phases1 is None:
phases1 = "abcn" if w1_has_neutral else "abc"
phases1 = "".join(p for p in bus1.phases if p in phases1)
self._check_phases(id, allowed_phases=self._allowed_phases_three, phases1=phases1)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_three, phases1=phases1)
self._check_bus_phases(id, bus1, phases1=phases1)
transformer_phases = "abcn" if w1_has_neutral else "abc"
phases_not_in_transformer = set(phases1) - set(transformer_phases)
if phases_not_in_transformer:
msg = (
f"Phases (1) {phases1!r} of transformer {id!r} are not compatible with its "
f"winding {parameters.winding1!r}."
)
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
if phases2 is None:
phases2 = "abcn" if w2_has_neutral else "abc"
phases2 = "".join(p for p in bus2.phases if p in phases2)
self._check_phases(id, allowed_phases=self._allowed_phases_three, phases2=phases2)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_three, phases2=phases2)
self._check_bus_phases(id, bus2, phases2=phases2)
transformer_phases = "abcn" if w2_has_neutral else "abc"
phases_not_in_transformer = set(phases2) - set(transformer_phases)
if phases_not_in_transformer:
msg = (
f"Phases (2) {phases2!r} of transformer {id!r} are not compatible with its "
f"winding {parameters.winding2!r}."
)
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
return phases1, phases2
def _compute_phases_single(
self, id: Id, bus1: Bus, bus2: Bus, phases1: Optional[str], phases2: Optional[str]
) -> tuple[str, str]:
if phases1 is None:
phases1 = "".join(p for p in bus1.phases if p in bus2.phases) # can't use set because order is important
phases1 = phases1.replace("ac", "ca")
if phases1 not in self._allowed_phases_single:
msg = f"Phases (1) of transformer {id!r} cannot be deduced from the buses, they need to be specified."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_single, phases1=phases1)
self._check_bus_phases(id, bus1, phases1=phases1)
if phases2 is None:
phases2 = "".join(p for p in bus1.phases if p in bus2.phases) # can't use set because order is important
phases2 = phases2.replace("ac", "ca")
if phases2 not in self._allowed_phases_single:
msg = f"Phases (2) of transformer {id!r} cannot be deduced from the buses, they need to be specified."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_single, phases2=phases2)
self._check_bus_phases(id, bus2, phases2=phases2)
return phases1, phases2
def _compute_phases_center(
self, id: Id, bus1: Bus, bus2: Bus, phases1: Optional[str], phases2: Optional[str]
) -> tuple[str, str]:
if phases1 is None:
phases1 = "".join(p for p in bus2.phases if p in bus1.phases and p != "n")
phases1 = phases1.replace("ac", "ca")
if phases1 not in self._allowed_phases_single:
msg = f"Phases (1) of transformer {id!r} cannot be deduced from the buses, they need to be specified."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_single, phases1=phases1)
self._check_bus_phases(id, bus1, phases1=phases1)
if phases2 is None:
phases2 = "".join(p for p in bus2.phases if p in bus1.phases or p == "n")
if phases2 not in self._allowed_phases_center_secondary:
msg = f"Phases (2) of transformer {id!r} cannot be deduced from the buses, they need to be specified."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE)
else:
self._check_phases(id, allowed_phases=self._allowed_phases_center_secondary, phases2=phases2)
self._check_bus_phases(id, bus2, phases2=phases2)
return phases1, phases2
@staticmethod
def _check_bus_phases(id: Id, bus: Bus, **kwargs: str) -> None:
name, phases = kwargs.popitem() # phases1 or phases2
name = "Phases (1)" if name == "phases1" else "Phases (2)"
phases_not_in_bus = set(phases) - set(bus.phases)
if phases_not_in_bus:
msg = (
f"{name} {sorted(phases_not_in_bus)} of transformer {id!r} are not in phases "
f"{bus.phases!r} of bus {bus.id!r}."
)
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_PHASE) | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/models/transformers/transformers.py | 0.93828 | 0.337449 | transformers.py | pypi |
import logging
from typing import TYPE_CHECKING
from roseau.load_flow.exceptions import RoseauLoadFlowException, RoseauLoadFlowExceptionCode
from roseau.load_flow.models import (
AbstractBranch,
AbstractLoad,
Bus,
Ground,
Line,
LineParameters,
PotentialRef,
Transformer,
TransformerParameters,
VoltageSource,
)
from roseau.load_flow.typing import Id, JsonDict
if TYPE_CHECKING:
from roseau.load_flow.network import ElectricalNetwork
logger = logging.getLogger(__name__)
NETWORK_JSON_VERSION = 1
"""The current version of the network JSON file format."""
def network_from_dict(
data: JsonDict, en_class: type["ElectricalNetwork"]
) -> tuple[
dict[Id, Bus],
dict[Id, AbstractBranch],
dict[Id, AbstractLoad],
dict[Id, VoltageSource],
dict[Id, Ground],
dict[Id, PotentialRef],
]:
"""Create the electrical network elements from a dictionary.
Args:
data:
The dictionary containing the network data.
en_class:
The ElectricalNetwork class to create.
Returns:
The buses, branches, loads, sources, grounds and potential refs to construct the electrical
network.
"""
version = data.get("version", 0)
if version == 0:
logger.warning(
f"Got an outdated network file (version 0), trying to update to the current format "
f"(version {NETWORK_JSON_VERSION}). Please save the network again."
)
data = v0_to_v1_converter(data)
else:
# If we arrive here, we dealt with all legacy versions, it must be the current one
assert version == NETWORK_JSON_VERSION, f"Unsupported network file version {version}."
# Lines and transformers parameters
lines_params = {lp["id"]: LineParameters.from_dict(lp) for lp in data["lines_params"]}
transformers_params = {tp["id"]: TransformerParameters.from_dict(tp) for tp in data["transformers_params"]}
# Buses, loads and sources
buses = {bd["id"]: en_class._bus_class.from_dict(bd) for bd in data["buses"]}
loads = {ld["id"]: en_class._load_class.from_dict(ld | {"bus": buses[ld["bus"]]}) for ld in data["loads"]}
sources = {
sd["id"]: en_class._voltage_source_class.from_dict(sd | {"bus": buses[sd["bus"]]}) for sd in data["sources"]
}
# Grounds and potential refs
grounds: dict[Id, Ground] = {}
for ground_data in data["grounds"]:
ground = en_class._ground_class(ground_data["id"])
for ground_bus in ground_data["buses"]:
ground.connect(buses[ground_bus["id"]], ground_bus["phase"])
grounds[ground_data["id"]] = ground
potential_refs: dict[Id, PotentialRef] = {}
for pref_data in data["potential_refs"]:
if "bus" in pref_data:
bus_or_ground = buses[pref_data["bus"]]
elif "ground" in pref_data:
bus_or_ground = grounds[pref_data["ground"]]
else:
msg = f"Potential reference data {pref_data['id']} missing bus or ground."
logger.error(msg)
raise RoseauLoadFlowException(msg, RoseauLoadFlowExceptionCode.JSON_PREF_INVALID)
potential_refs[pref_data["id"]] = en_class._pref_class(
pref_data["id"], element=bus_or_ground, phase=pref_data.get("phases")
)
# Branches
branches_dict: dict[Id, AbstractBranch] = {}
for branch_data in data["branches"]:
id = branch_data["id"]
phases1 = branch_data["phases1"]
phases2 = branch_data["phases2"]
bus1 = buses[branch_data["bus1"]]
bus2 = buses[branch_data["bus2"]]
geometry = AbstractBranch._parse_geometry(branch_data.get("geometry"))
if branch_data["type"] == "line":
assert phases1 == phases2
length = branch_data["length"]
lp = lines_params[branch_data["params_id"]]
gid = branch_data.get("ground")
ground = grounds[gid] if gid is not None else None
branches_dict[id] = en_class._line_class(
id, bus1, bus2, parameters=lp, phases=phases1, length=length, ground=ground, geometry=geometry
)
elif branch_data["type"] == "transformer":
tp = transformers_params[branch_data["params_id"]]
branches_dict[id] = en_class._transformer_class(
id, bus1, bus2, parameters=tp, phases1=phases1, phases2=phases2, geometry=geometry
)
elif branch_data["type"] == "switch":
assert phases1 == phases2
branches_dict[id] = en_class._switch_class(id, bus1, bus2, phases=phases1, geometry=geometry)
else:
msg = f"Unknown branch type for branch {id}: {branch_data['type']}"
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.BAD_BRANCH_TYPE)
# Short-circuits
short_circuits = data.get("short_circuits")
if short_circuits is not None:
for sc in short_circuits:
ground_id = sc["short_circuit"]["ground"]
ground = grounds[ground_id] if ground_id is not None else None
buses[sc["bus_id"]].add_short_circuit(*sc["short_circuit"]["phases"], ground=ground)
return buses, branches_dict, loads, sources, grounds, potential_refs
def network_to_dict(en: "ElectricalNetwork", include_geometry: bool) -> JsonDict:
"""Return a dictionary of the current network data.
Args:
en:
The electrical network.
include_geometry:
If False, the geometry will not be added to the network dictionary.
Returns:
The created dictionary.
"""
# Export the grounds and the pref
grounds = [ground.to_dict() for ground in en.grounds.values()]
potential_refs = [p_ref.to_dict() for p_ref in en.potential_refs.values()]
# Export the buses, loads and sources
buses: list[JsonDict] = []
loads: list[JsonDict] = []
sources: list[JsonDict] = []
short_circuits: list[JsonDict] = []
for bus in en.buses.values():
buses.append(bus.to_dict(include_geometry=include_geometry))
for element in bus._connected_elements:
if isinstance(element, AbstractLoad):
assert element.bus is bus
loads.append(element.to_dict())
elif isinstance(element, VoltageSource):
assert element.bus is bus
sources.append(element.to_dict())
for sc in bus.short_circuits:
short_circuits.append({"bus_id": bus.id, "short_circuit": sc})
# Export the branches with their parameters
branches: list[JsonDict] = []
lines_params_dict: dict[Id, LineParameters] = {}
transformers_params_dict: dict[Id, TransformerParameters] = {}
for branch in en.branches.values():
branches.append(branch.to_dict(include_geometry=include_geometry))
if isinstance(branch, Line):
params_id = branch.parameters.id
if params_id in lines_params_dict and branch.parameters != lines_params_dict[params_id]:
msg = f"There are multiple line parameters with id {params_id!r}"
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.JSON_LINE_PARAMETERS_DUPLICATES)
lines_params_dict[branch.parameters.id] = branch.parameters
elif isinstance(branch, Transformer):
params_id = branch.parameters.id
if params_id in transformers_params_dict and branch.parameters != transformers_params_dict[params_id]:
msg = f"There are multiple transformer parameters with id {params_id!r}"
logger.error(msg)
raise RoseauLoadFlowException(
msg=msg, code=RoseauLoadFlowExceptionCode.JSON_TRANSFORMER_PARAMETERS_DUPLICATES
)
transformers_params_dict[params_id] = branch.parameters
# Line parameters
line_params: list[JsonDict] = []
for lp in lines_params_dict.values():
line_params.append(lp.to_dict())
line_params.sort(key=lambda x: x["id"]) # Always keep the same order
# Transformer parameters
transformer_params: list[JsonDict] = []
for tp in transformers_params_dict.values():
transformer_params.append(tp.to_dict())
transformer_params.sort(key=lambda x: x["id"]) # Always keep the same order
res = {
"version": NETWORK_JSON_VERSION,
"grounds": grounds,
"potential_refs": potential_refs,
"buses": buses,
"branches": branches,
"loads": loads,
"sources": sources,
"lines_params": line_params,
"transformers_params": transformer_params,
}
if short_circuits:
res["short_circuits"] = short_circuits
return res
def v0_to_v1_converter(data: JsonDict) -> JsonDict: # noqa: C901
"""Convert a v0 network dict to a v1 network dict.
Args:
data:
The v0 network data.
Returns:
The v1 network data.
"""
# V0 had only 3-phase networks
assert data.get("version", 0) == 0, data["version"]
# Only one ground in V0
ground = {"id": "ground", "buses": []}
grounds = [ground]
# There is always a potential ref connected to ground in V0
potential_refs = [{"id": "pref", "ground": ground["id"]}]
used_potential_refs_ids = {"pref"}
# Buses, loads and sources
loads = []
sources = []
buses = {}
for old_bus in data["buses"]:
bus_id = old_bus["id"]
bus = {"id": bus_id}
if old_bus["type"] == "slack":
# Old slack bus is a bus with a voltage source, it has "abcn" phases
source = {
"id": bus_id, # We didn't have sources in V0, set source id to bus id
"bus": bus_id,
"phases": "abcn",
"voltages": list(old_bus["voltages"].values()),
}
sources.append(source)
phases = "abcn"
ground["buses"].append({"id": bus_id, "phase": "n"}) # All slack buses had a ground in V0
elif old_bus["type"] == "bus_neutral":
phases = "abcn"
else:
assert old_bus["type"] == "bus"
phases = "abc"
bus["phases"] = phases
# buses in V0 didn't have (initial) potentials, they were ignored
if "geometry" in old_bus: # geometry is optional
bus["geometry"] = Bus._parse_geometry(old_bus["geometry"]).__geo_interface__
buses[bus_id] = bus
for old_load in old_bus["loads"]:
func = old_load["function"]
flexible_params = None
if func.startswith("y"): # Star loads
load_phases = "abcn"
if func.endswith("_neutral"):
assert phases == "abcn" # y*_neutral loads are only for buses with neutral
else:
assert phases == "abc" # y* loads are only for buses without neutral
elif func.startswith("d"): # Delta loads
load_phases = "abc"
else: # Flexible loads
assert func == "flexible"
assert "powers" in old_load
load_phases = "abcn"
flexible_params = old_load["parameters"]
load = {"id": old_load["id"], "bus": bus_id, "phases": load_phases}
load_powers = old_load.get("powers")
load_currents = old_load.get("currents")
load_impedances = old_load.get("impedances")
if load_powers is not None:
assert load_currents is None
assert load_impedances is None
load["powers"] = list(load_powers.values())
if flexible_params is not None:
load["flexible_params"] = flexible_params
elif load_currents is not None:
assert load_impedances is None
load["currents"] = list(load_currents.values())
else:
assert load_impedances is not None
load["impedances"] = list(load_impedances.values())
loads.append(load)
assert sources, "No slack bus found"
# Branches
branches = []
lines_params = {}
transformers_params = {}
for line_type in data["line_types"]:
lp = {"id": line_type["name"], "model": line_type["model"], "z_line": line_type["z_line"]}
if "y_shunt" in line_type:
lp["y_shunt"] = line_type["y_shunt"]
lines_params[lp["id"]] = lp
for transformer_type in data["transformer_types"]:
tp = {
"id": transformer_type["name"],
"sn": transformer_type["sn"],
"uhv": transformer_type["uhv"],
"ulv": transformer_type["ulv"],
"i0": transformer_type["i0"],
"p0": transformer_type["p0"],
"psc": transformer_type["psc"],
"vsc": transformer_type["vsc"],
"type": transformer_type["type"],
}
transformers_params[tp["id"]] = tp
for old_branch in data["branches"]:
branch_id = old_branch["id"]
bus1_id = old_branch["bus1"]
bus2_id = old_branch["bus2"]
branch_type = old_branch["type"]
branch = {"id": branch_id, "bus1": bus1_id, "bus2": bus2_id}
if "geometry" in old_branch:
branch["geometry"] = AbstractBranch._parse_geometry(old_branch["geometry"]).__geo_interface__
if branch_type == "line":
params_id = old_branch["type_name"]
branch["length"] = old_branch["length"]
branch["params_id"] = params_id
branch["type"] = branch_type
# Lines have no phases information, we need to infer it from the line parameters
n = len(lines_params[params_id]["z_line"][0]) # Size of the line resistance matrix
phases1 = phases2 = "abcn" if n == 4 else "abc"
if "y_shunt" in lines_params[params_id]:
branch["ground"] = ground["id"] # Shunt lines all connected to the same ground
elif branch_type == "transformer":
params_id = old_branch["type_name"]
branch["params_id"] = params_id
branch["tap"] = old_branch["tap"]
branch["type"] = branch_type
# Transformers have no phases information, we need to infer it from the windings
w1, w2, _ = TransformerParameters.extract_windings(transformers_params[params_id]["type"])
phases1 = "abcn" if ("y" in w1.lower() or "z" in w1.lower()) else "abc"
phases2 = "abcn" if ("y" in w2.lower() or "z" in w2.lower()) else "abc"
# Determine the "special element" connected to bus2 of the transformer
if phases2 == "abcn": # ground if it has neutral
ground["buses"].append({"id": bus2_id, "phase": "n"})
else: # potential reference if it has no neutral
# Construct a unique id for the potential ref
pref_id = f"{branch_id}{bus2_id}"
i = 2
while pref_id in used_potential_refs_ids:
pref_id = f"{branch_id}{bus2_id}-{i}"
i += 1
used_potential_refs_ids.add(pref_id)
pref = {"id": pref_id, "bus": bus2_id, "phases": None}
potential_refs.append(pref)
else:
assert branch_type == "switch"
branch["type"] = branch_type
# Switches have no phases information, we need to infer it from the buses
if buses[bus1_id]["phases"] == buses[bus2_id]["phases"] == "abcn":
# Only if both buses have neutral the switch has neutral
phases1 = phases2 = "abcn"
else:
phases1 = phases2 = "abc"
branch["phases1"] = phases1
branch["phases2"] = phases2
branches.append(branch)
return {
"version": NETWORK_JSON_VERSION,
"grounds": grounds,
"potential_refs": potential_refs,
"buses": list(buses.values()),
"branches": branches,
"loads": loads,
"sources": sources,
"lines_params": list(lines_params.values()),
"transformers_params": list(transformers_params.values()),
} | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/io/dict.py | 0.846006 | 0.422505 | dict.py | pypi |
import json
import logging
from typing import TYPE_CHECKING
import numpy as np
import pandas as pd
from roseau.load_flow.exceptions import RoseauLoadFlowException, RoseauLoadFlowExceptionCode
from roseau.load_flow.models import (
AbstractBranch,
AbstractLoad,
Bus,
Ground,
LineParameters,
PotentialRef,
TransformerParameters,
VoltageSource,
)
from roseau.load_flow.typing import StrPath
from roseau.load_flow.units import Q_
if TYPE_CHECKING:
from roseau.load_flow.network import ElectricalNetwork
logger = logging.getLogger(__name__)
def network_from_dgs( # noqa: C901
filename: StrPath,
en_class: type["ElectricalNetwork"],
) -> tuple[
dict[str, Bus],
dict[str, AbstractBranch],
dict[str, AbstractLoad],
dict[str, VoltageSource],
dict[str, Ground],
dict[str, PotentialRef],
]:
"""Create the electrical elements from a JSON file in DGS format.
Args:
filename: name of the JSON file
Returns:
The elements of the network: buses, branches, loads, sources, grounds and potential refs.
"""
# Read files
(
elm_xnet,
elm_term,
sta_cubic,
elm_tr,
typ_tr,
elm_coup,
elm_lne,
typ_lne,
elm_lod_lv,
elm_lod_mv,
elm_gen_stat,
elm_pv_sys,
) = _read_dgs_json_file(filename=filename)
# Ground and potential reference
ground = en_class._ground_class("ground")
p_ref = en_class._pref_class("pref", element=ground)
grounds = {ground.id: ground}
potential_refs = {p_ref.id: p_ref}
# Buses
buses: dict[str, Bus] = {}
for bus_id in elm_term.index:
ph_tech = elm_term.at[bus_id, "phtech"]
if ph_tech == 0:
phases = "abc"
elif ph_tech == 1:
phases = "abcn"
else:
msg = f"The Ph tech {ph_tech!r} for bus {bus_id!r} cannot be handled."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.DGS_BAD_PHASE_TECHNOLOGY)
buses[bus_id] = en_class._bus_class(id=bus_id, phases=phases)
# Sources
sources: dict[str, VoltageSource] = {}
for source_id in elm_xnet.index:
id_sta_cubic_source = elm_xnet.at[source_id, "bus1"] # id of the cubicle connecting the source and its bus
bus_id = sta_cubic.at[id_sta_cubic_source, "cterm"] # id of the bus to which the source is connected
un = elm_term.at[bus_id, "uknom"] / np.sqrt(3) * 1e3 # phase-to-neutral voltage (V)
tap = elm_xnet.at[source_id, "usetp"] # tap voltage (p.u.)
voltages = [un * tap, un * np.exp(-np.pi * 2 / 3 * 1j) * tap, un * np.exp(np.pi * 2 / 3 * 1j) * tap]
source_bus = buses[bus_id]
sources[source_id] = en_class._voltage_source_class(
id=source_id, phases="abcn", bus=source_bus, voltages=voltages
)
source_bus._connect(ground)
# LV loads
loads: dict[str, AbstractLoad] = {}
if elm_lod_lv is not None:
_generate_loads(en_class, elm_lod_lv, loads, buses, sta_cubic, 1e3, production=False)
# LV Production loads
if elm_pv_sys is not None:
_generate_loads(en_class, elm_pv_sys, loads, buses, sta_cubic, 1e3, production=True)
if elm_gen_stat is not None:
_generate_loads(en_class, elm_gen_stat, loads, buses, sta_cubic, 1e3, production=True)
# MV loads
if elm_lod_mv is not None:
_generate_loads(en_class, elm_lod_mv, loads, buses, sta_cubic, 1e6, production=False)
# Lines
branches: dict[str, AbstractBranch] = {}
if elm_lne is not None:
lines_params_dict: dict[str, LineParameters] = {}
for type_id in typ_lne.index:
# TODO: use the detailed phase information instead of n
n = typ_lne.at[type_id, "nlnph"] + typ_lne.at[type_id, "nneutral"]
if n not in (3, 4):
msg = f"The number of phases ({n}) of line type {type_id!r} cannot be handled, it should be 3 or 4."
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.DGS_BAD_PHASE_NUMBER)
lp = LineParameters.from_sym(
type_id,
z0=complex(typ_lne.at[type_id, "rline0"], typ_lne.at[type_id, "xline0"]),
z1=complex(typ_lne.at[type_id, "rline"], typ_lne.at[type_id, "xline"]),
y0=Q_(complex(typ_lne.at[type_id, "gline0"], typ_lne.at[type_id, "bline0"]), "uS/km"),
y1=Q_(complex(typ_lne.at[type_id, "gline"], typ_lne.at[type_id, "bline"]), "uS/km"),
zn=complex(typ_lne.at[type_id, "rnline"], typ_lne.at[type_id, "xnline"]),
xpn=typ_lne.at[type_id, "xpnline"],
bn=Q_(typ_lne.at[type_id, "bnline"], "uS/km"),
bpn=Q_(typ_lne.at[type_id, "bpnline"], "uS/km"),
)
actual_shape = lp.z_line.shape[0]
if actual_shape > n: # 4x4 matrix while a 3x3 matrix was expected
# Extract the 3x3 underlying matrix
lp = LineParameters(
id=lp.id,
z_line=lp.z_line[:actual_shape, :actual_shape],
y_shunt=lp.y_shunt[:actual_shape, :actual_shape] if lp.with_shunt else None,
)
elif actual_shape == n:
# Everything ok
pass
else:
# Something unexpected happened
msg = (
f"A {n}x{n} impedance matrix was expected for the line type {type_id!r} but a "
f"{actual_shape}x{actual_shape} matrix was generated."
)
logger.error(msg)
raise RoseauLoadFlowException(msg=msg, code=RoseauLoadFlowExceptionCode.DGS_BAD_PHASE_NUMBER)
lines_params_dict[type_id] = lp
for line_id in elm_lne.index:
type_id = elm_lne.at[line_id, "typ_id"] # id of the line type
lp = lines_params_dict[type_id]
branches[line_id] = en_class._line_class(
id=line_id,
bus1=buses[sta_cubic.at[elm_lne.at[line_id, "bus1"], "cterm"]],
bus2=buses[sta_cubic.at[elm_lne.at[line_id, "bus2"], "cterm"]],
length=elm_lne.at[line_id, "dline"],
parameters=lp,
ground=ground if lp.with_shunt else None,
)
# Transformers
if elm_tr is not None:
# Transformers type
transformers_params_dict: dict[str, TransformerParameters] = {}
transformers_tap: dict[str, int] = {}
for idx in typ_tr.index:
# Extract data
name = typ_tr.at[idx, "loc_name"]
sn = Q_(typ_tr.at[idx, "strn"], "MVA") # The nominal voltages of the transformer (MVA)
uhv = Q_(typ_tr.at[idx, "utrn_h"], "kV") # Phase-to-phase nominal voltages of the high voltages side (kV)
ulv = Q_(typ_tr.at[idx, "utrn_l"], "kV") # Phase-to-phase nominal voltages of the low voltages side (kV)
i0 = Q_(typ_tr.at[idx, "curmg"] / 3, "percent") # Current during off-load test (%)
p0 = Q_(typ_tr.at[idx, "pfe"] / 3, "kW") # Losses during off-load test (kW)
psc = Q_(typ_tr.at[idx, "pcutr"], "kW") # Losses during short-circuit test (kW)
vsc = Q_(typ_tr.at[idx, "uktr"], "percent") # Voltages on LV side during short-circuit test (%)
# Windings of the transformer
windings = f"{typ_tr.at[idx, 'tr2cn_h']}{typ_tr.at[idx, 'tr2cn_l']}{typ_tr.at[idx, 'nt2ag']}"
# Generate transformer parameters
transformers_params_dict[idx] = TransformerParameters(
id=name, type=windings, uhv=uhv, ulv=ulv, sn=sn, p0=p0, i0=i0, psc=psc, vsc=vsc
)
transformers_tap[idx] = typ_tr.at[idx, "dutap"]
# Create transformers
for idx in elm_tr.index:
type_id = elm_tr.at[idx, "typ_id"] # id of the line type
tap = 1.0 + elm_tr.at[idx, "nntap"] * transformers_tap[type_id] / 100
branches[idx] = en_class._transformer_class(
id=idx,
bus1=buses[sta_cubic.at[elm_tr.at[idx, "bushv"], "cterm"]],
bus2=buses[sta_cubic.at[elm_tr.at[idx, "buslv"], "cterm"]],
parameters=transformers_params_dict[type_id],
tap=tap,
)
ground.connect(bus=buses[sta_cubic.at[elm_tr.at[idx, "buslv"], "cterm"]])
# Create switches
if elm_coup is not None:
for switch_id in elm_coup.index:
# TODO: use the detailed phase information instead of n
n = elm_coup.at[switch_id, "nphase"] + elm_coup.at[switch_id, "nneutral"]
branches[switch_id] = en_class._switch_class(
id=switch_id,
phases="abc" if n == 3 else "abcn",
bus1=buses[sta_cubic.at[elm_coup.at[switch_id, "bus1"], "cterm"]],
bus2=buses[sta_cubic.at[elm_coup.at[switch_id, "bus2"], "cterm"]],
)
return buses, branches, loads, sources, grounds, potential_refs
def _read_dgs_json_file(filename: StrPath):
"""Read a JSON file in DGS format.
Args:
filename: name of the JSON file
Returns:
elm_xnet: dataframe of external sources
elm_term: dataframe of terminals (i.e. buses)
sta_cubic: dataframe of cubicles
elm_tr: dataframe of transformers
typ_tr: dataframe of types of transformer
elm_coup: dataframe of switches
elm_lne: dataframe of electrical line
typ_lne: dataframe of types of line
elm_lod_lv: dataframe of LV loads
elm_lod_mv: dataframe of MV loads
elm_gen_stat: dataframe of generators
"""
# Create dataframe from JSON file
with open(filename, encoding="ISO-8859-10") as f:
data = json.load(f)
# External sources
elm_xnet = pd.DataFrame(columns=data["ElmXnet"]["Attributes"], data=data["ElmXnet"]["Values"]).set_index("FID")
# Terminals (buses)
elm_term = pd.DataFrame(columns=data["ElmTerm"]["Attributes"], data=data["ElmTerm"]["Values"]).set_index("FID")
# Cubicles
sta_cubic = pd.DataFrame(columns=data["StaCubic"]["Attributes"], data=data["StaCubic"]["Values"]).set_index("FID")
# Transformers
if "ElmTr2" in data:
elm_tr = pd.DataFrame(columns=data["ElmTr2"]["Attributes"], data=data["ElmTr2"]["Values"]).set_index("FID")
else:
elm_tr = None
# Transformer types
if "TypTr2" in data:
typ_tr = pd.DataFrame(columns=data["TypTr2"]["Attributes"], data=data["TypTr2"]["Values"]).set_index("FID")
else:
typ_tr = None
# Switch
if "ElmCoup" in data:
elm_coup = pd.DataFrame(columns=data["ElmCoup"]["Attributes"], data=data["ElmCoup"]["Values"]).set_index("FID")
else:
elm_coup = None
# Lines
if "ElmLne" in data:
elm_lne = pd.DataFrame(columns=data["ElmLne"]["Attributes"], data=data["ElmLne"]["Values"]).set_index("FID")
else:
elm_lne = None
# Line types
if "TypLne" in data:
typ_lne = pd.DataFrame(columns=data["TypLne"]["Attributes"], data=data["TypLne"]["Values"]).set_index("FID")
else:
typ_lne = None
# LV loads
if "ElmLodLV" in data:
elm_lod_lv = pd.DataFrame(columns=data["ElmLodLV"]["Attributes"], data=data["ElmLodLV"]["Values"]).set_index(
"FID"
)
else:
elm_lod_lv = None
# MV loads
if "ElmLodmv" in data:
elm_lod_mv = pd.DataFrame(columns=data["ElmLodmv"]["Attributes"], data=data["ElmLodmv"]["Values"]).set_index(
"FID"
)
else:
elm_lod_mv = None
# Generators
if "ElmGenStat" in data:
elm_gen_stat = pd.DataFrame(
columns=data["ElmGenStat"]["Attributes"], data=data["ElmGenStat"]["Values"]
).set_index("FID")
else:
elm_gen_stat = None
# LV generators
# Generators
if "ElmPvsys" in data:
elm_pv_sys = pd.DataFrame(columns=data["ElmPvsys"]["Attributes"], data=data["ElmPvsys"]["Values"]).set_index(
"FID"
)
else:
elm_pv_sys = None
return (
elm_xnet,
elm_term,
sta_cubic,
elm_tr,
typ_tr,
elm_coup,
elm_lne,
typ_lne,
elm_lod_lv,
elm_lod_mv,
elm_gen_stat,
elm_pv_sys,
)
def _generate_loads(
en_class: type["ElectricalNetwork"],
elm_lod: pd.DataFrame,
loads: dict[str, AbstractLoad],
buses: dict[str, Bus],
sta_cubic: pd.DataFrame,
factor: float,
production: bool,
) -> None:
"""Generate the loads of a given dataframe.
Args:
elm_lod:
The dataframe of loads.
loads:
The dictionary the loads will be added to.
buses:
The dataframe of buses.
sta_cubic:
The dataframe of cubicles.
factor:
The factor to multiply the load power (ex: 1e3 for kVA -> VA)
production:
True for production loads, False otherwise.
"""
for load_id in elm_lod.index:
sta_cubic_id = elm_lod.at[load_id, "bus1"] # id of the cubicle connecting the load and its bus
bus_id = sta_cubic.at[sta_cubic_id, "cterm"] # id of the bus to which the load is connected
if production:
s_phase = _compute_production_load_power(elm_lod, load_id, "") * factor
sa = sb = sc = 0
else:
s_phase = _compute_load_power(elm_lod, load_id, "") * factor
sa = _compute_load_power(elm_lod, load_id, "r") * factor
sb = _compute_load_power(elm_lod, load_id, "s") * factor
sc = _compute_load_power(elm_lod, load_id, "t") * factor
# Balanced or Unbalanced
s = [s_phase / 3, s_phase / 3, s_phase / 3] if sa == 0 and sb == 0 and sc == 0 else [sa, sb, sc]
loads[load_id] = en_class._load_class._power_load_class(id=load_id, phases="abcn", bus=buses[bus_id], powers=s)
def _compute_load_power(elm_lod: pd.DataFrame, load_id: str, suffix: str) -> complex:
"""Compute a load power in PWF format.
Args:
elm_lod:
The dataframe of loads.
load_id:
The load id.
suffix:
The phase of the load (empty for balanced loads, or r, s, t for phases a, b, c)
Returns:
The apparent power.
"""
p = elm_lod.at[load_id, "plini" + suffix]
q = np.sqrt(elm_lod.at[load_id, "slini" + suffix] ** 2 - elm_lod.at[load_id, "plini" + suffix] ** 2)
q *= np.sign(p) * (-1 if elm_lod.at[load_id, "pf_recap" + suffix] else 1)
return p + 1j * q
def _compute_production_load_power(elm_lod: pd.DataFrame, load_id: str, suffix: str) -> complex:
"""Compute a production load power in PWF format.
Args:
elm_lod:
The dataframe of loads.
load_id:
The load id.
suffix:
The phase of the load (empty for balanced loads, or r, s, t for phases a, b, c)
Returns:
The apparent power.
"""
p = elm_lod.at[load_id, "pgini" + suffix]
q = elm_lod.at[load_id, "qgini" + suffix]
q *= np.sign(p) * (-1 if elm_lod.at[load_id, "pf_recap" + suffix] else 1)
return -(p + 1j * q) | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/io/dgs.py | 0.595728 | 0.227544 | dgs.py | pypi |
import json
import logging
import re
from abc import ABCMeta, abstractmethod
from pathlib import Path
from typing import Generic, TypeVar
from typing_extensions import Self
from roseau.load_flow.exceptions import RoseauLoadFlowException, RoseauLoadFlowExceptionCode
from roseau.load_flow.typing import Id, JsonDict, StrPath
logger = logging.getLogger(__name__)
_T = TypeVar("_T")
class Identifiable(metaclass=ABCMeta):
"""An identifiable object."""
def __init__(self, id: Id) -> None:
if not isinstance(id, (int, str)):
msg = f"{type(self).__name__} expected id to be int or str, got {type(id)}"
logger.error(msg)
raise RoseauLoadFlowException(msg, code=RoseauLoadFlowExceptionCode.BAD_ID_TYPE)
self.id = id
def __repr__(self) -> str:
return f"{type(self).__name__}(id={self.id!r})"
class JsonMixin(metaclass=ABCMeta):
"""Mixin for classes that can be serialized to and from JSON."""
@classmethod
@abstractmethod
def from_dict(cls, data: JsonDict) -> Self:
"""Create an element from a dictionary."""
raise NotImplementedError
@classmethod
def from_json(cls, path: StrPath) -> Self:
"""Construct an electrical network from a json file created with :meth:`to_json`.
Args:
path:
The path to the network data file.
Returns:
The constructed network.
"""
data = json.loads(Path(path).read_text())
return cls.from_dict(data=data)
@abstractmethod
def to_dict(self, include_geometry: bool = True) -> JsonDict:
"""Return the element information as a dictionary format.
Args:
include_geometry:
If False, the geometry will not be added to the result dictionary.
"""
raise NotImplementedError
def to_json(self, path: StrPath) -> Path:
"""Save the current network to a json file.
.. note::
The path is `expanded`_ then `resolved`_ before writing the file.
.. _expanded: https://docs.python.org/3/library/pathlib.html#pathlib.Path.expanduser
.. _resolved: https://docs.python.org/3/library/pathlib.html#pathlib.Path.resolve
.. warning::
If the file exists, it will be overwritten.
Args:
path:
The path to the output file to write the network to.
Returns:
The expanded and resolved path of the written file.
"""
res = self.to_dict()
output = json.dumps(res, ensure_ascii=False, indent=2)
output = re.sub(r"\[\s+(.*),\s+(.*)\s+]", r"[\1, \2]", output)
if not output.endswith("\n"):
output += "\n"
path = Path(path).expanduser().resolve()
path.write_text(output)
return path
def results_to_dict(self) -> JsonDict:
"""Return the results of the element as a dictionary format"""
return self._results_to_dict(True)
@abstractmethod
def _results_to_dict(self, warning: bool) -> JsonDict:
"""Return the results of the element as a dictionary format"""
raise NotImplementedError
def results_to_json(self, path: StrPath) -> Path:
"""Write the results of the load flow to a json file.
.. note::
The path is `expanded`_ then `resolved`_ before writing the file.
.. _expanded: https://docs.python.org/3/library/pathlib.html#pathlib.Path.expanduser
.. _resolved: https://docs.python.org/3/library/pathlib.html#pathlib.Path.resolve
.. warning::
If the file exists, it will be overwritten.
Args:
path:
The path to the output file to write the results to.
Returns:
The expanded and resolved path of the written file.
"""
dict_results = self.results_to_dict()
output = json.dumps(dict_results, indent=4)
output = re.sub(r"\[\s+(.*),\s+(.*)\s+]", r"[\1, \2]", output)
path = Path(path).expanduser().resolve()
if not output.endswith("\n"):
output += "\n"
path.write_text(output)
return path
@abstractmethod
def results_from_dict(self, data: JsonDict) -> None:
"""Fill an element with the provided results' dictionary."""
raise NotImplementedError
def results_from_json(self, path: StrPath) -> None:
"""Load the results of a load flow from a json file created by :meth:`results_to_json`.
The results are stored in the network elements.
Args:
path:
The path to the JSON file containing the results.
"""
data = json.loads(Path(path).read_text())
self.results_from_dict(data)
class CatalogueMixin(Generic[_T], metaclass=ABCMeta):
"""A mixin class for objects which can be built from a catalogue. It adds the `from_catalogue` class method."""
@classmethod
@abstractmethod
def catalogue_path(cls) -> Path:
"""Get the path to the catalogue."""
raise NotImplementedError
@classmethod
@abstractmethod
def catalogue_data(cls) -> _T:
"""Get the catalogue data."""
raise NotImplementedError
@classmethod
@abstractmethod
def from_catalogue(cls, **kwargs) -> Self:
"""Build an instance from the catalogue.
Keyword Args:
Arguments that can be used to select the options of the instance to create.
Returns:
The instance of the selected object.
"""
raise NotImplementedError
@classmethod
@abstractmethod
def print_catalogue(cls, **kwargs) -> None:
"""Print the catalogue.
Keyword Args:
Arguments that can be used to filter the printed part of the catalogue.
"""
raise NotImplementedError | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/utils/mixins.py | 0.895999 | 0.368264 | mixins.py | pypi |
import numpy as np
from roseau.load_flow.units import Q_
from roseau.load_flow.utils.types import ConductorType, InsulatorType, LineType
PI = np.pi
"""The famous constant :math:`\\pi`."""
MU_0 = Q_(1.25663706212e-6, "H/m")
"""Magnetic permeability of the vacuum (H/m)."""
EPSILON_0 = Q_(8.8541878128e-12, "F/m")
"""Permittivity of the vacuum (F/m)."""
F = Q_(50.0, "Hz")
"""Network frequency :math:`=50` (Hz)."""
OMEGA = Q_(2 * PI * F, "rad/s")
"""Pulsation :math:`\\omega = 2 \\pi f` (rad/s)."""
RHO = {
ConductorType.CU: Q_(1.72e-8, "ohm*m"),
ConductorType.AL: Q_(2.82e-8, "ohm*m"),
ConductorType.AM: Q_(3.26e-8, "ohm*m"),
ConductorType.AA: Q_(4.0587e-8, "ohm*m"),
ConductorType.LA: Q_(3.26e-8, "ohm*m"),
}
"""Resistivity of common conductor materials (ohm.m)."""
CX = {
LineType.OVERHEAD: Q_(0.35, "ohm/km"),
LineType.UNDERGROUND: Q_(0.1, "ohm/km"),
LineType.TWISTED: Q_(0.1, "ohm/km"),
}
"""Reactance parameter for a typical line in France (Ohm/km)."""
MU_R = {
ConductorType.CU: Q_(1.2566e-8, "H/m"),
ConductorType.AL: Q_(1.2566e-8, "H/m"),
ConductorType.AM: Q_(1.2566e-8, "H/m"),
ConductorType.AA: np.nan, # TODO
ConductorType.LA: np.nan, # TODO
}
"""Magnetic permeability of common conductor materials (H/m)."""
DELTA_P = {
ConductorType.CU: Q_(9.3, "mm"),
ConductorType.AL: Q_(112, "mm"),
ConductorType.AM: Q_(12.9, "mm"),
ConductorType.AA: np.nan, # TODO
ConductorType.LA: np.nan, # TODO
}
"""Skin effect of common conductor materials (mm)."""
TAN_D = {
InsulatorType.PVC: Q_(600e-4),
InsulatorType.HDPE: Q_(6e-4),
InsulatorType.LDPE: Q_(6e-4),
InsulatorType.PEX: Q_(30e-4),
InsulatorType.EPR: Q_(125e-4),
}
"""Loss angles of common insulator materials."""
EPSILON_R = {
InsulatorType.PVC: Q_(6.5),
InsulatorType.HDPE: Q_(2.3),
InsulatorType.LDPE: Q_(2.2),
InsulatorType.PEX: Q_(2.5),
InsulatorType.EPR: Q_(3.1),
}
"""Relative permittivity of common insulator materials.""" | /roseau_load_flow-0.5.0-py3-none-any.whl/roseau/load_flow/utils/constants.py | 0.725065 | 0.494873 | constants.py | pypi |
import time
import json
import boto3
import hashlib
import logging
from airflow.providers.amazon.aws.hooks.base_aws import AwsGenericHook as AwsHook
from airflow.providers.amazon.aws.waiters.base_waiter import BaseBotoWaiter
def get_efs_filesystem(aws_conn_id, identifier, region = None, **context):
"""
Get EFS filesystem by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
return filesystems['FileSystems'][0]
else:
return None
def create_efs_filesystem(aws_conn_id, identifier, args, region = None, **context):
"""
Create EFS filesystem by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:param subnets: Subnets to create mount targets in
:type subnets: list
:param security_groups: Security groups to assign to mount targets
:type security_groups: list
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
filesystem = filesystems['FileSystems'][0]
logging.info('Filesystem already exists: %s', filesystem)
else:
logging.info('Filesystem does not exist yet, creating...')
filesystem = client.create_file_system(CreationToken=str(identifier), **args)
logging.info('Filesystem created: %s', filesystem)
waiter_config = {
"version": 2,
"waiters": {
"EFSLifeCycleStateWaiter": {
"operation": "DescribeFileSystems",
"delay": 5,
"maxAttempts": 5,
"acceptors": [
{
"state": "success",
"matcher": "path",
"argument": f"length(FileSystems[?FileSystemId == '{filesystem['FileSystemId']}'] | [?"
f"LifeCycleState == 'available'"
"]) > `0`",
"expected": True
}
]
}
}
}
base_waiter = BaseBotoWaiter(client, waiter_config)
waiter = base_waiter.waiter('EFSLifeCycleStateWaiter')
waiter.wait()
logging.info('Filesystem available: %s', filesystem)
return filesystem
def delete_efs_filesystem(aws_conn_id, identifier, region = None, **context):
"""
Delete EFS filesystem by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
filesystem = filesystems['FileSystems'][0]
logging.info('Filesystem exists: %s', filesystem)
client.delete_file_system(FileSystemId=filesystem['FileSystemId'])
logging.info('Filesystem deleted: %s', filesystem)
else:
logging.info('Filesystem does not exist: %s', identifier)
return None
return filesystems
def create_mount_targets(aws_conn_id, identifier, subnets, security_groups, region = None, **context):
"""
Create EFS mount targets by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:param subnets: Subnets to create mount targets in
:type subnets: list
:param security_groups: Security groups to assign to mount targets
:type security_groups: list
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
filesystem = filesystems['FileSystems'][0]
logging.info('Filesystem exists: %s', filesystem)
else:
logging.info('Filesystem does not exist: %s', identifier)
return None
mount_targets = client.describe_mount_targets(
FileSystemId=filesystem['FileSystemId']
)
# For each subnets, check if mount target exists and update security group if required
for subnet in subnets:
mount_target = next((x for x in mount_targets['MountTargets'] if x['SubnetId'] == subnet), None)
if mount_target is not None:
logging.info('Mount target already exists: %s', mount_target)
else:
logging.info('Mount target does not exist yet, creating...')
mount_target = client.create_mount_target(FileSystemId=filesystem['FileSystemId'], SubnetId=subnet, SecurityGroups=security_groups)
logging.info('Mount target created: %s', mount_target)
waiter_config = {
"version": 2,
"waiters": {
"EFSMountTargetLifeCycleStateWaiter": {
"operation": "DescribeMountTargets",
"delay": 30,
"maxAttempts": 10,
"acceptors": [
{
"state": "success",
"matcher": "path",
"argument": f"length(MountTargets[?MountTargetId == '{mount_target['MountTargetId']}'] | [?"
f"LifeCycleState == 'available'"
"]) > `0`",
"expected": True
}
]
}
}
}
base_waiter = BaseBotoWaiter(client, waiter_config)
waiter = base_waiter.waiter('EFSMountTargetLifeCycleStateWaiter')
waiter.wait(MountTargetId=mount_target['MountTargetId'])
logging.info('Mount target available: %s', mount_target)
mount_targets = client.describe_mount_targets(
FileSystemId=filesystem['FileSystemId']
)
return mount_targets
def delete_mount_targets(aws_conn_id, identifier, region = None, **context):
"""
Delete EFS mount targets by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
filesystem = filesystems['FileSystems'][0]
logging.info('Filesystem exists: %s', filesystem)
else:
logging.info('Filesystem does not exist: %s', identifier)
return None
mount_targets = client.describe_mount_targets(
FileSystemId=filesystem['FileSystemId']
)
# For each mount target, check if mount target exists and update security group if required
for mount_target in mount_targets['MountTargets']:
logging.info('Mount target exists: %s', mount_target)
client.delete_mount_target(MountTargetId=mount_target['MountTargetId'])
logging.info('Mount target deleted: %s', mount_target)
waiter_config = {
"version": 2,
"waiters": {
"EFSMountTargetLifeCycleStateWaiter": {
"operation": "DescribeFileSystems",
"delay": 30,
"maxAttempts": 10 * len(mount_targets),
"acceptors": [
{
"state": "success",
"matcher": "path",
"argument": f"length(FileSystems[?FileSystemId == '{filesystem['FileSystemId']}'] | [?"
f"NumberOfMountTargets == `0`"
"]) > `0`",
"expected": True
}
]
}
}
}
base_waiter = BaseBotoWaiter(client, waiter_config)
waiter = base_waiter.waiter('EFSMountTargetLifeCycleStateWaiter')
waiter.wait()
return mount_targets
def put_efs_filesystem_policy(aws_conn_id, identifier, policy, region = None, **context):
"""
Put EFS filesystem policy by identifier.
:param aws_conn_id: AWS connection ID
:type aws_conn_id: str
:param identifier: EFS filesystem identifier
:type identifier: str
:param policy: EFS filesystem policy
:type policy: str
:return: EFS filesystem
:rtype: dict
"""
hook = AwsHook(aws_conn_id, client_type='efs', region_name=region)
client = hook.get_client_type()
filesystems = client.describe_file_systems(
CreationToken=str(identifier)
)
if len(filesystems['FileSystems']) > 0:
filesystem = filesystems['FileSystems'][0]
logging.info('Filesystem exists: %s', filesystem)
else:
logging.info('Filesystem does not exist: %s', identifier)
return None
policy_string = json.dumps(policy)
client.put_file_system_policy(FileSystemId=filesystem['FileSystemId'], Policy=policy_string)
return filesystem | /rosecape_airflow-0.0.13-py3-none-any.whl/rosecape_airflow/aws/efs.py | 0.524151 | 0.155238 | efs.py | pypi |
import pygame;import pygame_gui;from pygame_gui.ui_manager import UIManager;from pygame_gui.elements.ui_window import UIWindow;from pygame_gui.elements.ui_image import UIImage;from pygame.locals import *;import math;import random
class Score:
def __init__(self, font):self.player_1_score = 0;self.player_2_score = 0;self.font = font;self.score_string = None;self.score_text_render = None;self.update_score_text()
def update_score_text(self):self.score_string = str(self.player_1_score) + " - " + str(self.player_2_score);self.score_text_render = self.font.render(self.score_string, True, pygame.Color(200, 200, 200))
def render(self, screen, size):screen.blit(self.score_text_render,self.score_text_render.get_rect(centerx=size[0] / 2, centery=size[1] / 10),)
def increase_player_1_score(self):self.player_1_score += 1;self.update_score_text()
def increase_player_2_score(self):self.player_2_score += 1;self.update_score_text()
class ControlScheme:
def __init__(self):self.up = K_UP;self.down = K_DOWN
class Bat:
def __init__(self, start_pos, control_scheme, court_size):self.control_scheme = control_scheme;self.move_up = False;self.move_down = False;self.move_speed = 450.0;self.court_size = court_size;self.length = 30.0;self.width = 5.0;self.position = [float(start_pos[0]), float(start_pos[1])];self.rect = pygame.Rect((start_pos[0], start_pos[1]), (self.width, self.length));self.colour = pygame.Color("#FFFFFF")
def process_event(self, event):
if event.type == KEYDOWN and event.key == self.control_scheme.up:self.move_up = True
if event.type == KEYDOWN and event.key == self.control_scheme.down:self.move_down = True
if event.type == KEYUP and event.key == self.control_scheme.up:self.move_up = False
if event.type == KEYUP and event.key == self.control_scheme.down:self.move_down = False
def update(self, dt):
if self.move_up:self.position[1] -= dt * self.move_speed
if self.move_up and self.position[1] < 10.0:self.position[1] = 10.0
if self.move_up:self.rect.y = self.position[1]
if self.move_down:self.position[1] += dt * self.move_speed
if self.move_down and self.position[1] > self.court_size[1] - self.length - 10:self.position[1] = self.court_size[1] - self.length - 10
if self.move_down:self.rect.y = self.position[1]
def render(self, screen):pygame.draw.rect(screen, self.colour, self.rect)
class Ball:
def __init__(self, start_position):self.rect = pygame.Rect(start_position, (5, 5));self.colour = pygame.Color(255, 255, 255);self.position = [float(start_position[0]), float(start_position[1])];self.start_position = [self.position[0], self.position[1]];self.ball_speed = 120.0;self.max_bat_bounce_angle = 5.0 * math.pi / 12.0;self.collided = False;self.velocity = [0.0, 0.0];self.create_random_start_vector()
def render(self, screen):pygame.draw.rect(screen, self.colour, self.rect)
def create_random_start_vector(self):
y_random = random.uniform(-0.5, 0.5);x_random = 1.0 - abs(y_random)
if random.randint(0, 1) == 1:x_random = x_random * -1.0
self.velocity = [x_random * self.ball_speed, y_random * self.ball_speed]
def reset(self):self.position = [self.start_position[0], self.start_position[1]];self.create_random_start_vector()
def update(self, dt, bats, walls):
self.position[0] += self.velocity[0] * dt;self.position[1] += self.velocity[1] * dt;self.rect.x = self.position[0];self.rect.y = self.position[1];collided_this_frame = False
for wall in walls:
if self.rect.colliderect(wall.rect):collided_this_frame = True
if self.rect.colliderect(wall.rect) and not self.collided:self.collided = True;self.velocity[1] = self.velocity[1] * -1
for bat in bats:
if self.rect.colliderect(bat.rect):collided_this_frame = True
if self.rect.colliderect(bat.rect) and not self.collided:self.collided = True;bat_y_centre = bat.position[1] + (bat.length / 2);ball_y_centre = self.position[1] + 5;relative_intersect_y = (bat_y_centre - ball_y_centre);normalized_relative_intersect_y = relative_intersect_y / (bat.length / 2);bounce_angle = (normalized_relative_intersect_y * self.max_bat_bounce_angle);self.velocity[0] = self.velocity[0] * -1;self.velocity[1] = self.ball_speed * -math.sin(bounce_angle)
if not collided_this_frame:self.collided = False
class Wall:
def __init__(self, top_left, bottom_right):self.rect = pygame.Rect(top_left, (bottom_right[0] - top_left[0], bottom_right[1] - top_left[1]));self.colour = pygame.Color("#C8C8C8")
def render(self, screen):pygame.draw.rect(screen, self.colour, self.rect)
class PongGame:
def __init__(self, size):self.size = size;self.background = pygame.Surface(size);self.background = self.background.convert();self.background.fill((0, 0, 0));font = pygame.font.Font(None, 24);self.score = Score(font);self.walls = [Wall((5, 5), (size[0] - 10, 10)),Wall((5, size[1] - 10), (size[0] - 10, size[1] - 5)),];self.bats = [];control_scheme_1 = ControlScheme();control_scheme_1.up = K_w;control_scheme_1.down = K_s;control_scheme_2 = ControlScheme();control_scheme_2.up = K_UP;control_scheme_2.down = K_DOWN;self.bats.append(Bat((5, int(size[1] / 2)), control_scheme_1, self.size));self.bats.append(Bat((size[0] - 10, int(size[1] / 2)), control_scheme_2, self.size));self.ball = Ball((int(size[0] / 2), int(size[1] / 2)))
def process_event(self, event):
for bat in self.bats:bat.process_event(event)
def update(self, time_delta):
for bat in self.bats:bat.update(time_delta)
self.ball.update(time_delta, self.bats, self.walls)
if self.ball.position[0] < 0:self.ball.reset();self.score.increase_player_2_score()
elif self.ball.position[0] > self.size[0]:self.ball.reset();self.score.increase_player_1_score()
def draw(self, surface):
surface.blit(self.background, (0, 0))
for wall in self.walls:wall.render(surface)
for bat in self.bats:bat.render(surface)
self.ball.render(surface);self.score.render(surface, self.size)
class PongWindow(UIWindow):
def __init__(self, position, ui_manager):super().__init__(pygame.Rect(position, (320, 240)),ui_manager,window_display_title="pong",object_id="#pong_window",);game_surface_size = self.get_container().get_size();self.game_surface_element = UIImage(pygame.Rect((0, 0), game_surface_size),pygame.Surface(game_surface_size).convert(),manager=ui_manager,container=self,parent_element=self,);self.pong_game = PongGame(game_surface_size);self.is_active = False
def focus(self):self.is_active = True
def unfocus(self):self.is_active = False
def process_event(self, event):
handled = super().process_event(event)
if event.type == pygame.USEREVENT and event.user_type == pygame_gui.UI_BUTTON_PRESSED and event.ui_object_id == "#pong_window.#title_bar" and event.ui_element == self.title_bar:handled = True;event_data = {"user_type": "window_selected","ui_element": self,"ui_object_id": self.most_specific_combined_id,};window_selected_event = pygame.event.Event(pygame.USEREVENT, event_data);pygame.event.post(window_selected_event)
if self.is_active:handled = self.pong_game.process_event(event)
return handled
def update(self, time_delta):
if self.alive() and self.is_active:self.pong_game.update(time_delta)
super().update(time_delta)
self.pong_game.draw(self.game_surface_element.image)
def load(manager, params):
pos = (50, 50)
if params is not None and len(params) > 0:pos = params[0]
PongWindow(pos, manager) | /rosehip-1.1.0-py3-none-any.whl/Rosehip/apps/util/pong/__init__.py | 0.408985 | 0.200851 | __init__.py | pypi |
[](https://snyk.io/test/github/my-soc/Rosetta)
[](https://go-rosetta.slack.com)
# Rosetta
Rosetta is a Python package that can be used to fake security logs and alerts for testing different detection and response use cases. It provides the following functions:
- Generate bad and random observables/indicators that include IP Addresses, Urls, File hashes , CVE's and more
- Fake log messages in different formats like CEF, LEEF and JSON.
- Convert one log format into another, for example from CEF to LEEF.
- Send the fake log message to different log management and analytics tools.
## Installation
- You can install rosetta via pip:
```sh
pip install rosetta-ce
```
- Or you can install it from the source code:
```sh
git clone https://github.com/ayman-m/rosetta.git
cd rosetta
python setup.py install
```
- Once installed, you can import the library in your Python code like this:
```python
from rosetta import Observables, Events
```
## Usage
Here are some examples of how to use Rosetta:
```python
from rosetta import Converter, ConverterToEnum, ConverterFromEnum, Events, ObservableType, ObservableKnown, \
Observables, Sender
# Example usage of the Converter class to convert a CEF log into a LEEF log.
converted_log = Converter.convert(from_type=ConverterFromEnum.CEF, to_type=ConverterToEnum.LEEF,
data="cef_log=CEF:0|Security|Intrusion Detection System|1.0|Alert|10|src=192.168.0.1 dst=192.168.0.2 act=blocked")
print(
converted_log) # {'message': 'converted', 'data': 'LEEF=1.0!Vendor=Security!Product=Intrusion Detection System!Version=1.0!EventID=Alert!Name=10!src=192.168.0.1!dst=192.168.0.2!act=blocked'}
# Example usage of the Observables class to generate bad IP indicators.
bad_ip = Observables.generator(count=2, observable_type=ObservableType.IP, known=ObservableKnown.BAD)
print(bad_ip) # ['ip1', 'ip2']
# Example usage of the Observables class to generate good IP indicators.
good_ip = Observables.generator(count=2, observable_type=ObservableType.IP, known=ObservableKnown.GOOD)
print(good_ip) # ['ip1', 'ip2']
# Example usage of the Observables class to generate bad URL indicators.
bad_url = Observables.generator(count=2, observable_type=ObservableType.URL, known=ObservableKnown.BAD)
print(bad_url) # ['url1', 'url2']
# Example usage of the Observables class to generate good URL indicators.
good_url = Observables.generator(count=2, observable_type=ObservableType.URL, known=ObservableKnown.GOOD)
print(good_url) # ['url1', 'url2']
# Example usage of the Observables class to generate bad Hash indicators.
bad_hash = Observables.generator(count=2, observable_type=ObservableType.SHA256, known=ObservableKnown.BAD)
print(bad_hash) # ['hash1', 'hash2']
# Example usage of the Observables class to generate good Hash indicators.
good_hash = Observables.generator(count=2, observable_type=ObservableType.SHA256, known=ObservableKnown.GOOD)
print(good_hash) # ['hash1', 'hash2']
# Example usage of the Observables class to generate CVE indicators.
cve = Observables.generator(count=2, observable_type=ObservableType.CVE)
print(cve) # Example: ['CVE-2023-2136', 'CVE-2023-29582']
# Example usage of the Observables class to generate random Terms.
terms = Observables.generator(count=2, observable_type=ObservableType.TERMS)
print(terms) # Example: ['Create or Modify System Process', 'Stage Capabilities: Drive-by Target']
# You can create an instance of the Observables class to contain your own observables that are to be used in the fake security events
src_ip, dst_ip, src_host, dst_host = ["192.168.10.10", "192.168.10.20"], ["1.1.1.1", "1.1.1.2"], ["abc"], ["xyz", "wlv"]
url, port = ["https://example.org", "https://wikipedia.com"], ["555", "666"]
protocol, app = ["ftp", "dns", "ssl"], ["explorer.exe", "chrome.exe"]
user = ["ayman", "mahmoud"]
file_name, file_hash = ["test.zip", "image.ps"], ["719283fd5600eb631c23b290530e4dac9029bae72f15299711edbc800e8e02b2"]
cmd, process = ["sudo restart", "systemctl stop firewalld"], ["bind", "crond"]
severity = ["high", "critical"]
sensor = ["fw", "edr"]
action = ["block", "allow"]
observables_list = Observables(src_ip=src_ip, dst_ip=dst_ip, src_host=src_host, dst_host=dst_host, url=url, port=port,
protocol=protocol, app=app, user=user, file_name=file_name, file_hash=file_hash, cmd=cmd,
process=process, severity=severity, sensor=sensor, action=action)
# Example usage of the Events class to generate generic SYSLOG events.
generic_syslog_with_random_observables = Events.syslog(count=1)
print(generic_syslog_with_random_observables) # ['Jan 20 16:04:53 db-88.zuniga.net sudo[34675]: ryansandy : COMMAND ; iptables -F']
generic_syslog_with_my_observables = Events.syslog(count=1, observables=observables_list)
print(generic_syslog_with_my_observables) # ['Apr 07 10:21:43 abc crond[17458]: ayman : COMMAND ; sudo restart']
# Example usage of the Events class to generate CEF events.
generic_cef_with_my_observables = Events.cef(count=1, observables=observables_list)
print(generic_cef_with_my_observables) # ['CEF:0|Novak LLC|Firewall|1.0.6|3019ab69-2d0e-4b3f-a240-4e8c93042dc3|Firewall allow dns traffic from abc:33504 to 1.1.1.1:666|5|src=abc spt=33504 dst=1.1.1.1 url=https://example.org dpt=666 proto=dns act=allow']
leef_with_my_observables = Events.leef(count=1, observables=observables_list)
print(leef_with_my_observables) # ["LEEF:1.0|Leef|Payment Portal|1.0|210.12.108.86|abc|9a:1e:9d:00:4c:ba|3b:a0:4b:24:f7:59|src=192.168.10.10 dst=abc spt=61549 dpt=443 request=https://example.com/search.php?q=<script>alert('xss')</script> method=Web-GET proto=HTTP/1.1 status=500 hash=719283fd5600eb631c23b290530e4dac9029bae72f15299711edbc800e8e02b2request_size=6173 response_size=8611 user_agent=Mozilla/5.0 (iPhone; CPU iPhone OS 9_3_5 like Mac OS X) AppleWebKit/536.1 (KHTML, like Gecko) FxiOS/12.1s4879.0 Mobile/00Y135 Safari/536.1"]
winevent_with_my_observables = Events.winevent(count=1, observables=observables_list)
print(winevent_with_my_observables) # ['<Event xmlns="http://schemas.microsoft.com/win/2004/08/events/event"><System><Provider Name="Microsoft-Windows-Security-Auditing" Guid="5fc4a88c-97b0-4061-adc3-052159c10ef4"/><EventID>4648</EventID><Version>0</Version><Level>0</Level><Task>13824</Task><Opcode>0</Opcode><Keywords>0x8020000000000000</Keywords><TimeCreated SystemTime="2023-04-07T18:45:17"/><EventRecordID>575</EventRecordID><Correlation/><Execution ProcessID="1071" ThreadID="5317" Channel="Security"/><Computer>abc</Computer><Security UserID="S-1-2915"/><EventData><Data Name="SubjectUserSid">S-1-2915</Data><Data Name="SubjectUserName">mahmoud</Data><Data Name="SubjectDomainName">johnson.org</Data><Data Name="SubjectLogonId">S-1-2915</Data><Data Name="NewProcessId">3371</Data><Data Name="ProcessId">1071</Data><Data Name="CommandLine">sudo restart</Data><Data Name="TargetUserSid">S-1-2915</Data><Data Name="TargetUserName">mahmoud</Data><Data Name="TargetDomainName">johnson.org</Data><Data Name="TargetLogonId">S-1-2915</Data><Data Name="LogonType">3</Data></EventData></Event>']
json_with_my_observables = Events.json(count=1, observables=observables_list)
print(json_with_my_observables) # [{'event_type': 'vulnerability_discovered', 'timestamp': '2023-02-12T16:28:46', 'severity': 'high', 'host': 'abc', 'file_hash': '719283fd5600eb631c23b290530e4dac9029bae72f15299711edbc800e8e02b2', 'cve': ['CVE-3941-1955']}]
incident_with_my_observables = Events.incidents(count=1, fields="id,type,duration,analyst,description,events", observables=observables_list)
print(incident_with_my_observables) # [{'id': 1, 'duration': 2, 'type': 'Lateral Movement', 'analyst': 'Elizabeth', 'description': 'Software Discovery Forge Web Credentials: SAML Tokens Escape to Host System Binary Proxy Execution: Control Panel Hide Artifacts: Process Argument Spoofing Office Application Startup: Add-ins Compromise Infrastructure: Botnet.', 'events': [{'event': 'Apr 09 19:39:57 abc bind[56294]: ayman : COMMAND ; systemctl stop firewalld'}, {'event': 'CEF:0|Todd, Guzman and Morales|Firewall|1.0.4|afe3d30f-cff4-4084-a7a3-7de9ea21d0e9|Firewall block dns traffic from abc:26806 to 1.1.1.1:555|10|src=abc spt=26806 dst=1.1.1.1 url=https://example.org dpt=555 proto=dns act=block'}, {'event': 'LEEF:1.0|Leef|Payment Portal|1.0|19.90.247.108|abc|d4:27:4c:a7:40:50|2a:3f:f3:37:81:eb|src=192.168.10.20 dst=abc spt=47335 dpt=443 request=https://example.com/index.php method=Web-GET proto=HTTP/1.1 status=500 hash=719283fd5600eb631c23b290530e4dac9029bae72f15299711edbc800e8e02b2request_size=3640 response_size=4766 user_agent=Mozilla/5.0 (Macintosh; Intel Mac OS X 10_5_1) AppleWebKit/533.0 (KHTML, like Gecko) Chrome/47.0.819.0 Safari/533.0'}, {'event': '<Event xmlns="http://schemas.microsoft.com/win/2004/08/events/event"><System><Provider Name="Microsoft-Windows-Security-Auditing" Guid="67eb0bb0-ab24-43ce-b7f1-6d6a6bb0ac27"/><EventID>4672</EventID><Version>0</Version><Level>0</Level><Task>12544</Task><Opcode>0</Opcode><Keywords>0x8020000000000000</Keywords><TimeCreated SystemTime="2023-01-15T04:07:58"/><EventRecordID>38</EventRecordID><Correlation/><Execution ProcessID="7182" ThreadID="7703" Channel="Security"/><Computer>abc</Computer><Security UserID="S-1-7181"/><EventData><Data Name="SubjectUserSid">S-1-7181</Data><Data Name="SubjectUserName">mahmoud</Data><Data Name="SubjectDomainName">johnson.net</Data><Data Name="SubjectLogonId">9638</Data><Data Name="PrivilegeList">Through moment tonight.</Data></EventData></Event>'}, {'event': {'event_type': 'vulnerability_discovered', 'timestamp': '2023-01-18T23:49:45', 'severity': 'critical', 'host': 'abc', 'file_hash': '719283fd5600eb631c23b290530e4dac9029bae72f15299711edbc800e8e02b2', 'cve': ['CVE-2023-29067']}}]}]
# Example usage of the Sender class to send faked events to log analysis tool.
worker = Sender(data_type="SYSLOG", destination="udp:127.0.0.1:514", observables=observables_list, count=5, interval=2)
worker.start()
# Starting worker: worker_2023-04-26 17:50:15.671101
# Worker: worker_2023-04-26 17:50:15.671101 sending log message to 127.0.0.1
# Worker: worker_2023-04-26 17:50:15.671101 sending log message to 127.0.0.1
# Worker: worker_2023-04-26 17:50:15.671101 sending log message to 127.0.0.1
# Worker: worker_2023-04-26 17:50:15.671101 sending log message to 127.0.0.1
# Worker: worker_2023-04-26 17:50:15.671101 sending log message to 127.0.0.1
```
| /rosetta-ce-1.6.4.tar.gz/rosetta-ce-1.6.4/README.md | 0.800965 | 0.879768 | README.md | pypi |
from enum import Enum
class ConverterFromEnum(Enum):
CEF = 'cef'
class ConverterToEnum(Enum):
JSON = 'json'
LEEF = 'leef'
class Converter:
@classmethod
def convert(cls, from_type: ConverterFromEnum, to_type: ConverterToEnum, data: str) -> dict:
"""
Converts a CEF log message to JSON format.
Args:
from_type (ConverterFromEnum): The "from" data type, currently supported options are CEF.
to_type (to_type): The "to" data type, currently supported options are JSON and LEEF.
data (str): The data message to be converted.
Returns:
str: The converted data message.
Raises:
ValueError: If the data message is invalid.
Example:
>>> data = "CEF:0|Security|threatmanager|1.0|100|detected an attack|10|src=192.168.1.1 dst=192.168.1.2"
>>> Converter.convert(from_type=ConverterFromEnum.CEF, to_type=ConverterToEnum.JSON, data=data)
'{"message": "converted", "data": {"version": "0", "device_vendor": "Security", "device_product":
"threatmanager", "device_version": "1.0", "device_event_class_id": "100", "name": "detected an attack",
"extensions": {"src": "192.168.1.1", "dst": "192.168.1.2"}}}'
"""
converted_data = None
if from_type == ConverterFromEnum.CEF:
parts = data.split('|')
if len(parts) < 6:
raise ValueError('Invalid CEF log format')
if to_type == ConverterToEnum.JSON:
converted_data = {
'version': parts[0],
'device_vendor': parts[1],
'device_product': parts[2],
'device_version': parts[3],
'device_event_class_id': parts[4],
'name': parts[5],
'extensions': {}
}
if len(parts) > 6:
for ext in parts[6].split(' '):
key, value = ext.split('=', 1)
converted_data['extensions'][key] = value
elif to_type == ConverterToEnum.LEEF:
leef_dict = {
'LEEF': '1.0',
'Vendor': parts[1],
'Product': parts[2],
'Version': parts[3],
'EventID': parts[4],
'Name': parts[5]
}
if len(parts) > 6:
for ext in parts[6].split(' '):
key, value = ext.split('=', 1)
leef_dict[key] = value
converted_data = '!'.join([f"{k}={v}" for k, v in leef_dict.items()])
if converted_data:
return {
"message": "converted",
"data": converted_data
}
else:
return {
"message": "inputs invalid",
"data": converted_data
} | /rosetta-ce-1.6.4.tar.gz/rosetta-ce-1.6.4/rosetta/rconverter.py | 0.864009 | 0.374676 | rconverter.py | pypi |
from datetime import datetime
import time
import threading
import socket
import requests
import warnings
from typing import Optional
from urllib3.exceptions import InsecureRequestWarning
from rosetta.rfaker import Observables, Events
class Sender:
"""
A class for sending fake data to a destination via a TCP or UDP socket or HTTP request.
Args:
worker_name (str): Name of the worker.
data_type (str): Type of the data to send.
count (int): Number of messages to send.
interval (int): Time interval (in seconds) between each message sent.
destination (str): Destination address in the format <protocol>://<ip_address>:<port>.
observables (Observables): Host name or IP address to use for fake data.
fields (str): Comma-separated list of incident fields to include in the fake data.
Attributes:
thread (threading.Thread): Thread object for the worker.
worker_name (str): Name of the worker.
data_type (WorkerTypeEnum): Type of the data to send.
count (int): Number of messages to send.
interval (int): Time interval (in seconds) between each message sent.
destination (str): Destination address in the format <protocol>://<ip_address>:<port>.
created_at (datetime): Timestamp of when the worker was created.
status (str): Status of the worker (Running, Stopped, Connection Error).
observables (list): Host name or IP address to use for fake data.
fields (str): Comma-separated list of incident fields to include in the fake data.
Methods:
start() -> str:
Starts the worker thread.
Returns:
str: Current status of the worker (Running, Stopped).
stop() -> str:
Stops the worker thread.
Returns:
str: Current status of the worker (Running, Stopped).
send_data() -> None:
Sends fake data to the destination address.
Returns:
None.
"""
def __init__(self, data_type: str, destination: str, headers: Optional[dict] = None,
worker_name: Optional[str] = 'worker_'+str(datetime.now()), count: Optional[int] = 1,
interval: Optional[int] = 1, vendor: Optional[str] = None, product: Optional[str] = None,
version: Optional[str] = None, required_fields: Optional[str] = None,
observables: Optional[Observables] = None, fields: Optional[str] = None,
verify_ssl: Optional[bool] = None, datetime_obj: Optional[datetime] = None,
data_json: Optional[dict] = None, data_text: Optional[str] = None):
"""
Constructor for DataSenderWorker class.
:param data_type: A value from the WorkerTypeEnum indicating the type of data to send. Options include:
- SYSLOG
- CEF
- LEEF
- WINEVENT
- JSON
- INCIDENT
:param destination: str, destination address and port in the format <scheme>://<address>:<port>.
:param worker_name: str, name of the worker.
:param count: int, number of times to send the data.
:param interval: int, time interval between two consecutive data sends.
:param vendor: Optional. The vendor.
:param product: Optional. The product.
:param version: Optional. The version.
:param required_fields: Optional. A list of fields that are required to present in the generated data, whether
from observables or randomely.
:param observables: Optional. Observables, list of observables.
:param fields: Optional. comma-separated list of fields to include in incident data.
:param verify_ssl: Optional. handling ssl verification errors.
:param datetime_obj: Optional. time to start from.
:param data_json: Optional. JSON data to send.
:param data_text: Optional. Text data to send.
:return: None
"""
if headers is None:
self.headers = {}
else:
self.headers = headers
self.thread = None
self.worker_name = worker_name
self.data_type = data_type
self.count = count
self.interval = interval
self.vendor = vendor
self.product = product
self.version = version
self.required_fields = required_fields
self.destination = destination
self.created_at = datetime.now()
self.status = "Stopped"
self.response = None
self.observables = observables
self.fields = fields
self.verify_ssl = verify_ssl
self.datetime_obj = datetime_obj
self.data_json = data_json
self.data_text = data_text
def start(self) -> str:
"""
Starts the worker thread.
Returns:
str: Current status of the worker (Running, Stopped).
"""
if self.status == "Stopped":
self.thread = threading.Thread(target=self.send_data, args=())
self.status = "Running"
print(f"Starting worker: {self.worker_name}")
self.thread.start()
return self.status
def stop(self) -> str:
"""
Stops the worker thread.
Returns:
str: Current status of the worker (Running, Stopped).
"""
if self.status == "Running":
self.thread.join()
self.status = "Stopped"
return self.status
def send_data(self) -> None:
"""
Sends fake data to the destination address.
Returns:
None.
"""
fake_message = None
while self.status == "Running" and self.count > 0:
try:
self.count -= 1
if self.data_type in ["SYSLOG", "CEF", "LEEF"]:
if self.data_text:
fake_message = [self.data_text]
else:
if self.data_type == "SYSLOG":
fake_message = Events.syslog(count=1, datetime_iso=self.datetime_obj,
observables=self.observables, required_fields=self.required_fields)
if self.data_type == "CEF":
fake_message = Events.cef(count=1, datetime_iso=self.datetime_obj, vendor=self.vendor,
product=self.product, version=self.version,
required_fields=self.required_fields, observables=self.observables)
if self.data_type == "LEEF":
fake_message = Events.leef(count=1, datetime_iso=self.datetime_obj, vendor=self.vendor,
product=self.product, version=self.version,
required_fields=self.required_fields,
observables=self.observables)
ip_address = self.destination.split(':')[1]
port = self.destination.split(':')[2]
if 'tcp' in self.destination:
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.settimeout(5)
sock.connect((ip_address, int(port)))
print(f"Worker: {self.worker_name} sending log message to {ip_address} ")
sock.sendall(fake_message[0].encode())
sock.close()
else:
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.settimeout(5)
print(f"Worker: {self.worker_name} sending log message to {ip_address} ")
sock.sendto(fake_message[0].encode(), (ip_address, int(port)))
elif self.data_type in ["JSON", "INCIDENT"]:
if self.data_json:
fake_message = [self.data_json]
else:
if self.data_type == "JSON":
fake_message = Events.json(count=1, datetime_iso=self.datetime_obj,
observables=self.observables, vendor=self.vendor,
product=self.product, version=self.version,
required_fields=self.required_fields,)
if self.data_type == "INCIDENT":
fake_message = [{
"alert": Events.incidents(count=1, observables=self.observables, vendor=self.vendor,
version=self.version, product=self.product,
datetime_iso=self.datetime_obj,
required_fields=self.required_fields, fields=self.fields)
}]
if '://' not in self.destination:
url = 'http://' + self.destination
else:
url = self.destination
warnings.filterwarnings("ignore", category=InsecureRequestWarning)
print(f"Worker: {self.worker_name} sending log message to {url} ")
response = requests.post(url, json=fake_message[0], timeout=(2, 5), headers=self.headers,
verify=self.verify_ssl)
self.response = response.text
response.raise_for_status()
except (ConnectionRefusedError, socket.timeout, requests.exceptions.RequestException) as e:
print(f"Connection error: {e}")
self.status = "Connection Error"
break
except requests.exceptions.SSLError as e:
print(f"SSL error: {e}")
self.status = "SSL Error"
break
except Exception as e:
print(f"Unexpected error: {e}")
self.status = "Stopped"
break
time.sleep(self.interval)
if self.status == "Running":
self.status = "Stopped" | /rosetta-ce-1.6.4.tar.gz/rosetta-ce-1.6.4/rosetta/rsender.py | 0.883676 | 0.300011 | rsender.py | pypi |
This package provides an implementation of **Rosetta**, a neural
network-based model for predicting unasturated soil hydraulic parameters
from basic soil characterization data.
How to avoid installing this package
====================================
For most Rosetta use cases, we recommend using the web browser interface
to ``rosetta-soil`` that is available at
`<https://www.handbook60.org/rosetta>`_
There is also an api available at ``handbook60.org``. For example::
import requests
data = {
"soildata": [
[30, 30, 40, 1.5, 0.3, 0.1],
[20, 60, 20],
[55, 25, 20, 1.1],
]
}
def url(rosetta_version: int) -> str:
return f"http://www.handbook60.org/api/v1/rosetta/{rosetta_version}"
r = requests.post(url(3), json=data)
returns the following::
print(r.json())
{'model_codes': [5, 2, 3], 'rosetta_version': 3, 'stdev':
[[0.013628985468838103, 0.01496917525020338, 0.12948704319399928,
0.0347739236276485, 0.1747797749074611], [0.0067075928037543765,
0.00878582437678383, 0.07413139323912403, 0.013230683219936165,
0.08709445948355408], [0.01277140708670187, 0.013062170576228887,
0.10020312250396954, 0.01763982447621485, 0.14163566888667592]],
'van_genuchten_params': [[0.06872133198419336, 0.38390508534751433,
-2.452968871563431, 0.17827394547955497, 0.9827227259550619],
[0.08994502219206943, 0.4301366480210401, -2.4262357492034043,
0.17568732926631986, 1.192731130984082], [0.09130753033144606,
0.485031958049669, -2.0223880878467875, 0.151071612216524,
1.9060147751706147]]}
See below for information on the expected structure and content of the
submitted ``soildata`` and returned json payload.
[If your use case involves, e.g., thousands of repeated requests, then
please install and use ``rosetta-soil`` locally rather than use the api.]
Installation
============
::
pip install rosetta-soil
Quickstart
==========
::
>>> from rosetta import rosetta, SoilData
>>> data = [
[30,30,40,1.5,0.3,0.1],
[20,60,20],
[55,25,20,1.1]
]
>>> mean, stdev, codes = rosetta(3, SoilData.from_array(data))
>>> print(mean)
[[ 0.06872133 0.38390509 -2.45296887 0.17827395 0.98272273]
[ 0.08994502 0.43013665 -2.42623575 0.17568733 1.19273113]
[ 0.09130753 0.48503196 -2.02238809 0.15107161 1.90601478]]
>>> print(stdev)
[[ 0.01362899 0.01496918 0.12948704 0.03477392 0.17477977]
[ 0.00670759 0.00878582 0.07413139 0.01323068 0.08709446]
[ 0.01277141 0.01306217 0.10020312 0.01763982 0.14163567]]
>>> print(codes)
[5 2 3]
Background
==========
The Rosetta pedotransfer function predicts five parameters for the van
Genuchten model of unsaturated soil hydraulic properties
* theta_r : residual volumetric water content
* theta_s : saturated volumetric water content
* log10(alpha) : retention shape parameter [log10(1/cm)]
* log10(n) : retention shape parameter
* log10(ksat) : saturated hydraulic conductivity [log10(cm/d)]
Rosetta provides four models for predicting the five parameters from soil
characterization data. The models differ in the required input data
+------------+------------------------+
| Model Code | Input Data |
+============+========================+
| 2 | sa, si, cl (SSC) |
+------------+------------------------+
| 3 | SSC, bulk density (BD) |
+------------+------------------------+
| 4 | SSC, BD, th33 |
+------------+------------------------+
| 5 | SSC, BD, th33, th1500 |
+------------+------------------------+
where
* sa, si, cl are percentages of sand, silt and clay
* BD is soil bulk density (g/cm3)
* th33 is the soil volumetric water content at 33 kPa
* th1500 is the soil volumetric water content at 1500 kPa
Three versions of Rosetta are available. The versions effectively represent
three alternative calibrations of the four Rosetta models.
The references that should be cited when using Rosetta versions 1, 2,
and 3 are, respectively:
[1] Schaap, M.G., Leij, F.J., and Van Genuchten, M.T. 2001. ROSETTA: a
computer program for estimating soil hydraulic parameters with
hierarchical pedotransfer functions. Journal of Hydrology 251(3-4): 163-176.
doi: `10.1016/S0022-1694(01)00466-8 <https://doi.org/10.1016/S0022-1694(01)00466-8)>`_
[2] Schaap, M.G., A. Nemes, and M.T. van Genuchten. 2004. Comparison of Models
for Indirect Estimation of Water Retention and Available Water in Surface Soils.
Vadose Zone Journal 3(4): 1455-1463.
doi: `10.2136/vzj2004.1455 <https://doi.org/10.2136/vzj2004.1455>`_
[3] Zhang, Y. and Schaap, M.G. 2017. Weighted recalibration of the Rosetta
pedotransfer model with improved estimates of hydraulic parameter
distributions and summary statistics (Rosetta3). Journal of Hydrology 547: 39-53.
doi: `10.1016/j.jhydrol.2017.01.004 <https://doi.org/10.1016/j.jhydrol.2017.01.004>`_
Usage
=====
::
from rosetta import rosetta, SoilData
The imported function ``rosetta`` predicts soil hydraulic parameters from
soil characterization data. It has two required arguments::
rosetta_version : int, {1, 2, 3}
soildata : SoilData
The second argument is a ``SoilData`` instance. Normally, the instance is
created from an array-like collection of soil characterization data
using the ``from_array`` method.
::
data = [
[30,30,40,1.5,0.3,0.1],
[20,60,20],
[55,25,20,1.1]
]
soildata = SoilData.from_array(data)
Each element of the array-like data contains soil data in this order::
[%sand, %silt, %clay, buld density, th33, th1500]
Sand, silt, and clay are required; the others are optional. For each
entry, ``rosetta`` selects the best availabe Rosetta model based on
the given data. Note that even if you are predicting for only a single
soil record, ``data`` still needs to 2D array-like::
data = [[30,30,40]]
soildata = SoilData.from_array(data)
The function ``rosetta`` returns a 3-tuple
::
mean, stdev, codes = rosetta(3, soildata)
``mean`` is a 2D numpy array. The ith row holds predicted soil hydraulic
parameters for ith entry in ``soildata``. The array columns are
+-------+---------------------------------------------------------------+
|Column | Parameter |
+=======+===============================================================+
| 0 | theta_r, residual water content |
+-------+---------------------------------------------------------------+
| 1 | theta_s, saturated water content |
+-------+---------------------------------------------------------------+
| 2 | log10(alpha), 'alpha' shape parameter, log10(1/cm) |
+-------+---------------------------------------------------------------+
| 3 | log10(npar), 'n' shape parameter |
+-------+---------------------------------------------------------------+
| 4 | log10(Ksat), saturated hydraulic conductivity, log10(cm/day) |
+-------+---------------------------------------------------------------+
``stdev`` is 2D numpy array holding the corresponding parameter standard
deviations.
``codes`` is a 1D numpy array with the ith entry indicating the
Rosetta model and input data used to predict the ith row of ``mean``
and ``stdev``.
+------+--------------------------------------------------------+
| Code | Data used |
+======+========================================================+
| 2 | sand, silt, clay (SSC) |
+------+--------------------------------------------------------+
| 3 | SSC + bulk density (BD) |
+------+--------------------------------------------------------+
| 4 | SSC + BD + field capacity water content (TH33) |
+------+--------------------------------------------------------+
| 5 | SSC + BD + TH33 + wilting point water content (TH1500) |
+------+--------------------------------------------------------+
| -1 | no result returned, inadequate or erroneous data |
+------+--------------------------------------------------------+
Alternative usage
-----------------
Predictions can also be made using the Rostta class
::
import numpy as np
from rosetta import Rosetta
The class is instantiated for a particular Rosetta version and model.
Predictions are then made using a numpy array of soil data.
::
rose33 = Rosetta(rosetta_version=3, model_code=3)
data = np.array([[30,30,40,1.5],[55,25,20,1.1]], dtype=float)
mean, stdev = rose33.predict(data)
The 2D numpy array ``data`` has to be ``data.shape[1] = model_code + 1``.
Compared with the function rosetta.rosetta, Rosetta.predict offers
fewer checks on arguments and data.
Notes
=====
This module wraps files taken from
`research code <http://www.u.arizona.edu/~ygzhang/download.html>`_
developed by Marcel Schaap and Yonggen Zhang at the University of
Arizona.
The Rosetta class described above has another method,
Rosetta.ann_predict, which returns additional statistical quantities
computed by the Schaap and Zhang code and which may be of interest to
researchers. The usage is the same as Rosetta.predict,
::
rose33 = Rosetta(rosetta_version=3, model_code=3)
data = np.array([[30,30,40,1.5],[55,25,20,1.1]], dtype=float)
results = rose33.ann_predict(data, sum_data=True)
However, in this case, the returned ``results`` is a dictionay of parameters
and statistical results. Note the arrays in ``results`` are the transpose
of what is returned by other functions and methods in ``rosetta-soil``
See the file ``ANN_Module.py`` and the code base of
`Schaap and Zhang <http://www.u.arizona.edu/~ygzhang/download.html>`_
for more information.
| /rosetta-soil-0.1.1.tar.gz/rosetta-soil-0.1.1/README.rst | 0.912026 | 0.806891 | README.rst | pypi |
from __future__ import annotations
import pkg_resources
from typing import NamedTuple, Sequence, Tuple, Union, Optional, List
import numpy as np
from . import ANN_Module
from . import DB_Module
Array1D = Union[np.ndarray]
Array2D = Union[np.ndarray]
ROSETTA_DB = pkg_resources.resource_filename("rosetta", "sqlite/Rosetta.sqlite")
ROSETTA_VERSIONS = {1, 2, 3}
ROSETTA_MODEL_CODES = {2, 3, 4, 5}
ROSE2_COEFFICIENTS = {
2: [(0.969, 0.000), (1.103, -0.048), (1.050, 0.159), (0.655, 0.004)],
3: [(0.995, 0.000), (1.000, 0.002), (1.028, 0.162), (0.660, 0.003)],
4: [(1.156, 0.000), (0.974, 0.011), (1.039, 0.067), (0.796, 0.006)],
5: [(1.220, 0.000), (1.045, -0.020), (0.956, -0.040), (0.877, -0.003)],
}
class RosettaError(Exception):
def __init__(self, message):
self.message = message
def to_floats(seq: Sequence) -> List[float]:
floats = []
for s in seq:
try:
floats.append(float(s))
except (ValueError, TypeError):
floats.append(np.nan)
return floats
class SoilDatum(NamedTuple):
sand: float
silt: float
clay: float
rhob: Optional[float] = None
th33: Optional[float] = None
th1500: Optional[float] = None
def is_valid_separates(self) -> bool:
return (
99.0 <= sum([self.sand, self.silt, self.clay]) <= 101.0
and self.sand >= 0.0
and self.silt >= 0.0
and self.clay >= 0.0
)
def is_valid_bulkdensity(self) -> bool:
return False if self.rhob is None else 0.5 <= self.rhob <= 2.0
def is_valid_fieldcap(self) -> bool:
return False if self.th33 is None else 0.0 < self.th33 < 1.0
def is_valid_wiltpoint(self) -> bool:
return False if self.th1500 is None else 0.0 < self.th1500 < 1.0
def is_valid_fieldcap_and_wiltpoint(self) -> bool:
if self.th33 is None or self.th1500 is None:
return False
return 0.0 < self.th1500 < self.th33 < 1.0
def is_valid(self, index: int = None) -> bool:
"""Test validity of data in self[:index].
Requirements for valid data:
99 <= sand + silt + clay <= 101
0.5 <= rho_b <= 2
0 < th1500 < th33 < 1
"""
if index is None:
index = len(self)
if not (3 <= index <= len(self)):
return False
tests = [
self.is_valid_separates(),
self.is_valid_bulkdensity(),
self.is_valid_fieldcap(),
self.is_valid_fieldcap_and_wiltpoint(),
]
return all(tests[: index - 2])
def best_index(self) -> int:
"""Max value of index for which self.is_valid(index) is True."""
count = 0
for index in range(3, len(self) + 1):
if self.is_valid(index):
count = index
else:
break
return count
class SoilData(List[SoilDatum]):
@classmethod
def from_array(cls, array: Array2D) -> SoilData:
return SoilData([SoilDatum(*to_floats(row)) for row in array])
def to_array(self) -> Array2D:
return np.array([list(datum) for datum in self], dtype=float)
def is_valid(self, index: int = None) -> List[bool]:
# Returned List[i] is validity of self[i][SoilDatum[:index]]
return [datum.is_valid(index) for datum in self]
class Rosetta:
def __init__(self, rosetta_version: int, model_code: int) -> None:
if rosetta_version not in ROSETTA_VERSIONS:
raise RosettaError(f"rosetta_version must be in {ROSETTA_VERSIONS}")
if model_code not in ROSETTA_MODEL_CODES:
raise RosettaError(f"model_code must be in {ROSETTA_MODEL_CODES}")
self.rosetta_version = rosetta_version
self.model_code = model_code
code = model_code if rosetta_version == 3 else model_code + 100
with DB_Module.DB(0, 0, 0, sqlite_path=ROSETTA_DB) as db:
self.ptf_model = ANN_Module.PTF_MODEL(code, db)
def predict(self, X: Array2D) -> Tuple[Array2D, Array2D]:
predicted_params = self.ptf_model.predict(X.T, sum_data=True)
mean = predicted_params["sum_res_mean"].T
stdev = predicted_params["sum_res_std"].T
if self.rosetta_version == 2:
for jcol, (slope, offset) in enumerate(ROSE2_COEFFICIENTS[self.model_code]):
mean[:, jcol] = slope * mean[:, jcol] + offset
stdev[:, jcol] *= slope
return mean, stdev
def ann_predict(self, X: Array2D, sum_data: bool = True) -> dict:
if self.rosetta_version == 2:
raise RosettaError("ann_predict not enabled for Rosetta version 2")
return self.ptf_model.predict(X.T, sum_data=sum_data)
def rosetta(
rosetta_version: int, soildata: SoilData
) -> Tuple[Array2D, Array2D, Array1D]:
"""Predict soil hydraulic parameters from soil characterization data.
Parameters
----------
rosetta_version : {1, 2, 3}
soildata : :class:`~rosetta.rosetta.SoilData`
List of soil characterization data, one entry per soil
Returns
-------
(mean, stdev, codes)
mean : 2D np.array, dtype=float
ith row holds predicted soil hydraulic parameters for ith entry
in `soildata`.
array |
column | parameter
-----------------
0 | theta_r, residual water content
1 | theta_s, saturated water content
2 | log10(alpha), van Genuchten 'alpha' parameter (1/cm)
3 | log10(npar), van Genuchten 'n' parameter
4 | log10(Ksat), saturated hydraulic conductivity (cm/day)
stdev: 2D np.array, dtype=float
Standard deviations for parameters in `mean`.
codes : 1D np.array, dtype=int
ith entry is a code indicating the neural network model and
input data used to predict the ith row of `mean` and `stdev`.
code | data used
---------------
2 | sand, silt, clay (SSC)
3 | SSC + bulk density (BD)
4 | SSC + BD + field capacity water content (TH33)
5 | SSC + BD + TH33 + wilting point water content (TH1500))
-1 | no result returned, insufficient or erroneous data
Example
-------
>>> from rosetta import rosetta, SoilData
# required ordering for data records:
# [sa (%), si (%), cl (%), bd (g/cm3), th33, th1500]
# sa, si, and cl are required; others optional
>>> data = [
[30,30,40,1.5,0.3,0.1],
[20,60,20],
[55,25,20,1.1]
]
>>> mean, stdev, codes = rosetta(3, SoilData.from_array(data))
>>> print(mean)
[[ 0.06872133 0.38390509 -2.45296887 0.17827395 0.98272273]
[ 0.08994502 0.43013665 -2.42623575 0.17568733 1.19273113]
[ 0.09130753 0.48503196 -2.02238809 0.15107161 1.90601478]]
>>> print(stdev)
[[ 0.01362899 0.01496918 0.12948704 0.03477392 0.17477977]
[ 0.00670759 0.00878582 0.07413139 0.01323068 0.08709446]
[ 0.01277141 0.01306217 0.10020312 0.01763982 0.14163567]]
>>> print(codes)
[5 2 3]
"""
if rosetta_version not in ROSETTA_VERSIONS:
raise RosettaError(f"rosetta_version must be in {ROSETTA_VERSIONS}")
if not isinstance(soildata, SoilData):
raise RosettaError("soildata must be a SoilData instance")
# codes[i] is -1 if soildata[i] lacks minimun required data
codes = np.array([data.best_index() - 1 for data in soildata], dtype=int)
features = soildata.to_array()
mean = np.full((features.shape[0], 5), np.nan, dtype=float)
stdev = np.full((features.shape[0], 5), np.nan, dtype=float)
for code in set(codes) - {-1}:
rose = Rosetta(rosetta_version, code)
rows = codes == code
mean[rows], stdev[rows] = rose.predict(features[rows, : code + 1])
return mean, stdev, codes | /rosetta-soil-0.1.1.tar.gz/rosetta-soil-0.1.1/rosetta/rosetta.py | 0.883726 | 0.487185 | rosetta.py | pypi |
from packaging.version import Version
import mrcz as _mrcz
import logging
from rsciio._docstrings import (
FILENAME_DOC,
LAZY_DOC,
ENDIANESS_DOC,
RETURNS_DOC,
SIGNAL_DOC,
)
from rsciio.utils.tools import DTBox
_logger = logging.getLogger(__name__)
_POP_FROM_HEADER = [
"compressor",
"MRCtype",
"C3",
"dimensions",
"dtype",
"extendedBytes",
"gain",
"maxImage",
"minImage",
"meanImage",
"metaId",
"packedBytes",
"pixelsize",
"pixelunits",
"voltage",
]
# Hyperspy uses an unusual mixed Fortran- and C-ordering scheme
_READ_ORDER = [1, 2, 0]
_WRITE_ORDER = [0, 1, 2]
# API changes in mrcz 0.5
def _parse_metadata(metadata):
if Version(_mrcz.__version__) < Version("0.5"):
return metadata[0]
else:
return metadata
mapping = {
"mrcz_header.voltage": ("Acquisition_instrument.TEM.beam_energy", _parse_metadata),
"mrcz_header.gain": (
"Signal.Noise_properties.Variance_linear_model.gain_factor",
_parse_metadata,
),
# There is no metadata field for spherical aberration
#'mrcz_header.C3':
# ("Acquisition_instrument.TEM.C3", lambda x: x),
}
def file_reader(filename, lazy=False, endianess="<", mmap_mode="c", **kwds):
"""File reader for the MRCZ format for tomographic data.
Parameters
----------
%s
%s
%s
mmap_mode : str, Default="c"
The MRCZ reader currently only supports C-ordering memory-maps.
%s
Examples
--------
>>> from rsciio.mrcz import file_reader
>>> new_signal = file_reader('file.mrcz')
"""
_logger.debug("Reading MRCZ file: %s" % filename)
if mmap_mode != "c":
# Note also that MRCZ does not support memory-mapping of compressed data.
# Perhaps we could use the zarr package for that
raise ValueError("MRCZ supports only C-ordering memory-maps")
mrcz_endian = "le" if endianess == "<" else "be"
data, mrcz_header = _mrcz.readMRC(
filename, endian=mrcz_endian, useMemmap=lazy, pixelunits="nm", **kwds
)
# Create the axis objects for each axis
names = ["y", "x", "z"]
navigate = [False, False, True]
axes = [
{
"size": data.shape[hsIndex],
"index_in_array": hsIndex,
"name": names[index],
"scale": mrcz_header["pixelsize"][hsIndex],
"offset": 0.0,
"units": mrcz_header["pixelunits"],
"navigate": nav,
}
for index, (hsIndex, nav) in enumerate(zip(_READ_ORDER, navigate))
]
axes.insert(0, axes.pop(2)) # re-order the axes
metadata = mrcz_header.copy()
# Remove non-standard fields
for popTarget in _POP_FROM_HEADER:
metadata.pop(popTarget)
dictionary = {
"data": data,
"axes": axes,
"metadata": metadata,
"original_metadata": {"mrcz_header": mrcz_header},
"mapping": mapping,
}
return [
dictionary,
]
file_reader.__doc__ %= (FILENAME_DOC, LAZY_DOC, ENDIANESS_DOC, RETURNS_DOC)
def file_writer(
filename, signal, do_async=False, compressor=None, clevel=1, n_threads=None, **kwds
):
"""
Write signal to MRCZ format.
Parameters
----------
%s
%s
%s
do_async : bool, Default=False
Currently supported within RosettaSciIO for writing only, this will
save the file in a background thread and return immediately.
Warning: there is no method currently implemented within RosettaSciIO
to tell if an asychronous write has finished.
compressor : {None, "zlib", "zstd", "lz4"}, Default=None
The compression codec.
clevel : int, Default=1
The compression level, an ``int`` from 1 to 9.
n_threads : int
The number of threads to use for ``blosc`` compression. Defaults to
the maximum number of virtual cores (including Intel Hyperthreading)
on your system, which is recommended for best performance. If
``do_async = True`` you may wish to leave one thread free for the
Python GIL.
Notes
-----
The recommended compression codec is ``zstd`` (zStandard) with ``clevel=1`` for
general use. If speed is critical, use ``lz4`` (LZ4) with ``clevel=9``. Integer data
compresses more redably than floating-point data, and in general the histogram
of values in the data reflects how compressible it is.
To save files that are compatible with other programs that can use MRC such as
GMS, IMOD, Relion, MotionCorr, etc. save with ``compressor=None``, extension ``.mrc``.
JSON metadata will not be recognized by other MRC-supporting software but should
not cause crashes.
Examples
--------
>>> from rsciio.mrcz import file_writer
>>> file_writer('file.mrcz', signal, do_async=True, compressor='zstd', clevel=1)
"""
endianess = kwds.pop("endianess", "<")
mrcz_endian = "le" if endianess == "<" else "be"
md = DTBox(signal["metadata"], box_dots=True)
# Get pixelsize and pixelunits from the axes
pixelunits = signal["axes"][-1]["units"]
pixelsize = [signal["axes"][I]["scale"] for I in _WRITE_ORDER]
# Strip out voltage from meta-data
voltage = md.get("Acquisition_instrument.TEM.beam_energy")
# There aren't hyperspy fields for spherical aberration or detector gain
C3 = 0.0
gain = md.get("Signal.Noise_properties.Variance_linear_model.gain_factor", 1.0)
if do_async:
_mrcz.asyncWriteMRC(
signal["data"],
filename,
meta=md,
endian=mrcz_endian,
pixelsize=pixelsize,
pixelunits=pixelunits,
voltage=voltage,
C3=C3,
gain=gain,
compressor=compressor,
clevel=clevel,
n_threads=n_threads,
)
else:
_mrcz.writeMRC(
signal["data"],
filename,
meta=md,
endian=mrcz_endian,
pixelsize=pixelsize,
pixelunits=pixelunits,
voltage=voltage,
C3=C3,
gain=gain,
compressor=compressor,
clevel=clevel,
n_threads=n_threads,
)
file_writer.__doc__ %= (
FILENAME_DOC.replace("read", "write to"),
SIGNAL_DOC,
ENDIANESS_DOC,
) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/mrcz/_api.py | 0.723602 | 0.335922 | _api.py | pypi |
import logging
from collections.abc import MutableMapping
import dask.array as da
import numcodecs
import zarr
from rsciio._docstrings import (
FILENAME_DOC,
LAZY_DOC,
RETURNS_DOC,
SIGNAL_DOC,
)
from rsciio._hierarchical import HierarchicalWriter, HierarchicalReader, version
_logger = logging.getLogger(__name__)
# -----------------------
# File format description
# -----------------------
# The root must contain a group called Experiments
# The experiments group can contain any number of subgroups
# Each subgroup is an experiment or signal
# Each subgroup must contain at least one dataset called data
# The data is an array of arbitrary dimension
# In addition a number equal to the number of dimensions of the data
# dataset + 1 of empty groups called coordinates followed by a number
# must exists with the following attributes:
# 'name'
# 'offset'
# 'scale'
# 'units'
# 'size'
# 'index_in_array'
# The experiment group contains a number of attributes that will be
# directly assigned as class attributes of the Signal instance. In
# addition the experiment groups may contain 'original_metadata' and
# 'metadata'subgroup that will be
# assigned to the same name attributes of the Signal instance as a
# Dictionary Browsers
# The Experiments group can contain attributes that may be common to all
# the experiments and that will be accessible as attributes of the
# Experiments instance
class ZspyReader(HierarchicalReader):
_file_type = "zspy"
def __init__(self, file):
super().__init__(file)
self.Dataset = zarr.Array
self.Group = zarr.Group
class ZspyWriter(HierarchicalWriter):
target_size = 1e8
def __init__(self, file, signal, expg, **kwargs):
super().__init__(file, signal, expg, **kwargs)
self.Dataset = zarr.Array
self.unicode_kwds = {"dtype": object, "object_codec": numcodecs.JSON()}
self.ragged_kwds = {
"dtype": object,
"object_codec": numcodecs.VLenArray(int),
"exact": True,
}
@staticmethod
def _get_object_dset(group, data, key, chunks, **kwds):
"""Creates a Zarr Array object for saving ragged data"""
these_kwds = kwds.copy()
these_kwds.update(dict(dtype=object, exact=True, chunks=chunks))
dset = group.require_dataset(
key, data.shape, object_codec=numcodecs.VLenArray(int), **these_kwds
)
return dset
@staticmethod
def _store_data(data, dset, group, key, chunks):
"""Write data to zarr format."""
if isinstance(data, da.Array):
if data.chunks != dset.chunks:
data = data.rechunk(dset.chunks)
# lock=False is necessary with the distributed scheduler
data.store(dset, lock=False)
else:
dset[:] = data
def file_writer(filename, signal, close_file=True, **kwds):
"""Writes data to HyperSpy's zarr format.
Parameters
----------
%s
%s
close_file : bool, default=True
Close the file after writing. Only relevant for some zarr storages
(:py:class:`zarr.storage.ZipStore`, :py:class:`zarr.storage.DBMStore`)
requiring store to flush data to disk. If ``False``, doesn't close the
file after writing. The file should not be closed if the data needs to be
accessed lazily after saving.
chunks : tuple of integer or None, default=None
Define the chunking used for saving the dataset. If None, calculates
chunks for the signal, with preferably at least one chunk per signal
space.
compressor : numcodecs compression, optional
A compressor can be passed to the save function to compress the data
efficiently, see `Numcodecs codec <https://numcodecs.readthedocs.io/en/stable>`_.
The default is to use a Blosc compressor.
write_dataset : bool, default=True
If ``False``, doesn't write the dataset when writing the file. This can
be useful to overwrite signal attributes only (for example ``axes_manager``)
without having to write the whole dataset, which can take time.
**kwds
The keyword arguments are passed to the
:py:meth:`zarr.hierarchy.Group.require_dataset` function.
Examples
--------
>>> from numcodecs import Blosc
>>> compressor=Blosc(cname='zstd', clevel=1, shuffle=Blosc.SHUFFLE) # Used by default
>>> file_writer('test.zspy', s, compressor = compressor) # will save with Blosc compression
"""
if "compressor" not in kwds:
kwds["compressor"] = numcodecs.Blosc(
cname="zstd", clevel=1, shuffle=numcodecs.Blosc.SHUFFLE
)
if isinstance(filename, MutableMapping):
store = filename
else:
store = zarr.storage.NestedDirectoryStore(
filename,
)
write_dataset = kwds.get("write_dataset", True)
if not isinstance(write_dataset, bool):
raise ValueError("`write_dataset` argument must a boolean.")
mode = "w" if kwds.get("write_dataset", True) else "a"
_logger.debug(f"File mode: {mode}")
_logger.debug(f"Zarr store: {store}")
f = zarr.open_group(store=store, mode=mode)
f.attrs["file_format"] = "ZSpy"
f.attrs["file_format_version"] = version
exps = f.require_group("Experiments")
title = signal["metadata"]["General"]["title"]
group_name = title if title else "__unnamed__"
# / is a invalid character, see https://github.com/hyperspy/hyperspy/issues/942
if "/" in group_name:
group_name = group_name.replace("/", "-")
expg = exps.require_group(group_name)
# Add record_by metadata for backward compatibility
signal_dimension = len([axis for axis in signal["axes"] if not axis["navigate"]])
smd = signal["metadata"]["Signal"]
if signal_dimension == 1:
smd["record_by"] = "spectrum"
elif signal_dimension == 2:
smd["record_by"] = "image"
else:
smd["record_by"] = ""
try:
writer = ZspyWriter(f, signal, expg, **kwds)
writer.write()
except Exception:
raise
finally:
del smd["record_by"]
if isinstance(store, (zarr.ZipStore, zarr.DBMStore, zarr.LMDBStore)):
if close_file:
store.close()
else:
store.flush()
file_writer.__doc__ %= (FILENAME_DOC.replace("read", "write to"), SIGNAL_DOC)
def file_reader(filename, lazy=False, **kwds):
"""Read data from zspy files saved with the HyperSpy zarr format
specification.
Parameters
----------
%s
%s
**kwds: optional
Pass keyword arguments to the :py:meth:`zarr.open` function.
%s
"""
mode = kwds.pop("mode", "r")
try:
f = zarr.open(filename, mode=mode, **kwds)
except Exception:
_logger.error(
"The file can't be read. It may be possible that the zspy file is "
"saved with a different store than a zarr directory store. Try "
"passing a different zarr store instead of the file name."
)
raise
reader = ZspyReader(f)
return reader.read(lazy=lazy)
file_reader.__doc__ %= (FILENAME_DOC, LAZY_DOC, RETURNS_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/zspy/_api.py | 0.742141 | 0.34715 | _api.py | pypi |
# The details of the format were taken from
# https://www.biochem.mpg.de/doc_tom/TOM_Release_2008/IOfun/tom_mrcread.html
# and https://ami.scripps.edu/software/mrctools/mrc_specification.php
import logging
import importlib.util
import xml.etree.ElementTree as ET
from pathlib import Path
from copy import deepcopy
import numpy as np
from numpy.polynomial.polynomial import polyfit
from rsciio._docstrings import FILENAME_DOC, RETURNS_DOC
_logger = logging.getLogger(__name__)
def _remove_none_from_dict(dict_in):
for key, value in list(dict_in.items()):
if isinstance(value, dict):
_remove_none_from_dict(value)
elif value is None:
del dict_in[key]
class JobinYvonXMLReader:
"""Class to read Jobin Yvon .xml-files.
The file is read using xml.etree.ElementTree.
Each element can have the following attributes: attrib, tag, text.
Moreover, non-leaf-elements are iterable (iterate over child-nodes).
In this specific format, the tags do not contain useful information.
Instead, the "ID"-entry in attrib is used to identify the sort of information.
The IDs are consistent for the tested files.
Parameters
----------
file_path: pathlib.Path
Path to the to be read file.
use_uniform_signal_axis: bool, default=False
Decides whether to use uniform or non-uniform signal-axis.
Attributes
----------
data, metadata, original_metadata, axes
Methods
-------
parse_file, get_original_metadata, get_axes, get_data, map_metadata
"""
def __init__(self, file_path, use_uniform_signal_axis=False):
self._file_path = file_path
self._use_uniform_signal_axis = use_uniform_signal_axis
if importlib.util.find_spec("lumispy") is None:
self._lumispy_installed = False
_logger.warning(
"Cannot find package lumispy, using BaseSignal1D as signal class."
)
else:
self._lumispy_installed = True # pragma: no cover
@property
def _signal_type(self):
if self._lumispy_installed:
return "Luminescence" # pragma: no cover
else:
return ""
@staticmethod
def _get_id(xml_element):
return xml_element.attrib["ID"]
@staticmethod
def _get_size(xml_element):
return int(xml_element.attrib["Size"])
def parse_file(self):
"""First parse through file to extract data/metadata positions."""
tree = ET.parse(self._file_path)
root = tree.getroot()
lsx_tree_list = root.findall("LSX_Tree")
if len(lsx_tree_list) > 1:
_logger.critical(
"File contains multiple positions to read metadata from.\n"
"The first location is choosen."
) # pragma: no cover
elif len(lsx_tree_list) == 0:
_logger.critical("No metadata found.") # pragma: no cover
lsx_tree = lsx_tree_list[0]
lsx_matrix_list = root.findall("LSX_Matrix")
if len(lsx_matrix_list) > 1:
_logger.critical(
"File contains multiple positions to read data from.\n"
"The first location is choosen."
) # pragma: no cover
elif len(lsx_matrix_list) == 0:
_logger.critical("No data found.") # pragma: no cover
self._lsx_matrix = lsx_matrix_list[0]
for child in lsx_tree:
id = self._get_id(child)
if id == "0x6C62D4D9":
self._metadata_root = child
if id == "0x6C7469D9":
self._title = child.text
if id == "0x6D707974":
self._measurement_type = child.text
if id == "0x6C676EC6":
for child2 in child:
if self._get_id(child2) == "0x0":
self._angle = child2.text
if id == "0x7A74D9D6":
for child2 in child:
if self._get_id(child2) == "0x7B697861":
self._axis_root = child2
if not hasattr(self, "_metadata_root"):
_logger.critical("Could not extract metadata") # pragma: no cover
if not hasattr(self, "_axis_root"):
_logger.critical("Could not extract axis") # pragma: no cover
def _get_metadata_values(self, xml_element, tag):
"""Helper method to extract information from metadata xml-element.
Parameters
----------
xml_element: xml.etree.ElementTree.Element
Head level metadata element.
tag: Str
Used as the corresponding key in the original_metadata dictionary.
Example
-------
<LSX Format="9" ID="0x6D7361DE" Size="5">
<LSX Format="7" ID="0x6D6D616E">Laser (nm)</LSX>
<LSX Format="7" ID="0x7D6C61DB">633 </LSX>
<LSX Format="5" ID="0x8736F70">632.817</LSX>
<LSX Format="4" ID="0x6A6DE7D3">0</LSX>
</LSX>
This corresponds to child-level (xml-element would be multiple of those elements).
ID="0x6D6D616E" -> key name for original metadata
ID="0x7D6C61DB" -> first value
ID="0x8736F70" -> second value
Which value is used is decided in _clean_up_metadata (in this case the second value is used).
"""
metadata_xml_element = dict()
for child in xml_element:
values = {}
for child2 in child:
if self._get_id(child2) == "0x6D6D616E":
key = child2.text
if self._get_id(child2) == "0x7D6C61DB":
values["1"] = child2.text
if self._get_id(child2) == "0x8736F70":
values["2"] = child2.text
metadata_xml_element[key] = values
self.original_metadata[tag] = metadata_xml_element
def _clean_up_metadata(self):
"""Cleans up original metadata to meet standardized format.
This means converting numbers from strings to floats,
deciding which value shall be used (when 2 values are extracted,
see _get_metadata_values() for more information).
Moreover, some names are slightly modified.
"""
convert_to_numeric = [
"Acq. time (s)",
"Accumulations",
"Delay time (s)",
"Binning",
"Detector temperature (°C)",
"Objective",
"Grating",
"ND Filter",
"Laser (nm)",
"Spectro (nm)",
"Hole",
"Laser Pol. (°)",
"Raman Pol. (°)",
"X (µm)",
"Y (µm)",
"Z (µm)",
"Full time(s)",
"rotation angle (rad)",
"Windows",
]
change_to_second_value = [
"Objective",
"Grating",
"ND Filter",
"Laser (nm)",
"Spectro (nm)",
]
## use second extracted value
for key in change_to_second_value:
try:
self.original_metadata["experimental_setup"][
key
] = self.original_metadata["experimental_setup"][key]["2"]
except KeyError:
pass
## use first extracted value
for key, value in self.original_metadata["experimental_setup"].items():
if isinstance(value, dict):
# only if there is an entry/value
if bool(value):
self.original_metadata["experimental_setup"][
key
] = self.original_metadata["experimental_setup"][key]["1"]
for key, value in self.original_metadata["date"].items():
if isinstance(value, dict):
if bool(value):
self.original_metadata["date"][key] = self.original_metadata[
"date"
][key]["1"]
for key, value in self.original_metadata["file_information"].items():
if isinstance(value, dict):
if bool(value):
self.original_metadata["file_information"][
key
] = self.original_metadata["file_information"][key]["1"]
## convert strings to float
for key in convert_to_numeric:
try:
self.original_metadata["experimental_setup"][key] = float(
self.original_metadata["experimental_setup"][key]
)
except KeyError:
pass
## move the unit from grating to the key name
try:
self.original_metadata["experimental_setup"][
"Grating (gr/mm)"
] = self.original_metadata["experimental_setup"].pop("Grating")
except KeyError: # pragma: no cover
pass # pragma: no cover
## add percentage for filter key name
try:
self.original_metadata["experimental_setup"][
"ND Filter (%)"
] = self.original_metadata["experimental_setup"].pop("ND Filter")
except KeyError: # pragma: no cover
pass # pragma: no cover
def get_original_metadata(self):
"""Extracts metadata from file."""
self.original_metadata = {}
for child in self._metadata_root:
id = self._get_id(child)
if id == "0x7CECDBD7":
date = child
if id == "0x8716361":
metadata = child
if id == "0x7C73E2D2":
file_specs = child
## setup tree structure original_metadata -> date{...}, experimental_setup{...}, file_information{...}
## based on structure in file
self._get_metadata_values(date, "date")
self._get_metadata_values(metadata, "experimental_setup")
self._get_metadata_values(file_specs, "file_information")
try:
self.original_metadata["experimental_setup"][
"measurement_type"
] = self._measurement_type
except AttributeError: # pragma: no cover
pass # pragma: no cover
try:
self.original_metadata["experimental_setup"]["title"] = self._title
except AttributeError: # pragma: no cover
pass # pragma: no cover
try:
self.original_metadata["experimental_setup"][
"rotation angle (rad)"
] = self._angle
except AttributeError:
pass
self._clean_up_metadata()
def _set_signal_type(self, xml_element):
"""Sets signal type and units based on metadata from file.
Extra method, because this information is stored seperate from the rest of the metadata.
Parameters
----------
xml_element: xml.etree.ElementTree.Element
Head level metadata element.
"""
for child in xml_element:
id = self._get_id(child)
## contains also intensity-minima/maxima-values for each data-row (ignored by this reader)
if id == "0x6D707974":
self.original_metadata["experimental_setup"]["signal type"] = child.text
if id == "0x7C696E75":
self.original_metadata["experimental_setup"][
"signal units"
] = child.text
def _set_nav_axis(self, xml_element, tag):
"""Helper method for setting navigation axes.
Parameters
----------
xml_element: xml.etree.ElementTree.Element
Head level metadata element.
tag: Str
Axis name.
"""
has_nav = True
nav_dict = dict()
for child in xml_element:
id = self._get_id(child)
if id == "0x6D707974":
nav_dict["name"] = child.text
if id == "0x7C696E75":
nav_dict["units"] = child.text
if id == "0x7D6CD4DB":
nav_array = np.fromstring(child.text.strip(), sep=" ")
nav_size = nav_array.size
if nav_size < 2:
has_nav = False
else:
nav_dict["scale"] = nav_array[1] - nav_array[0]
nav_dict["offset"] = nav_array[0]
nav_dict["size"] = nav_size
nav_dict["navigate"] = True
if has_nav:
self.axes[tag] = nav_dict
return has_nav, nav_size
def _set_signal_axis(self, xml_element):
"""Helper method to extract signal axis information.
Parameters
----------
xml_element: xml.etree.ElementTree.Element
Head level metadata element.
tag: Str
Axis name.
"""
signal_dict = dict()
signal_dict["navigate"] = False
for child in xml_element:
id = self._get_id(child)
if id == "0x7D6CD4DB":
signal_array = np.fromstring(child.text.strip(), sep=" ")
if signal_array.size > 1:
if signal_array[0] > signal_array[1]:
signal_array = signal_array[::-1]
self._reverse_signal = True
else:
self._reverse_signal = False
if self._use_uniform_signal_axis:
offset, scale = polyfit(
np.arange(signal_array.size), signal_array, deg=1
)
signal_dict["offset"] = offset
signal_dict["scale"] = scale
signal_dict["size"] = signal_array.size
scale_compare = 100 * np.max(
np.abs(np.diff(signal_array) - scale) / scale
)
if scale_compare > 1:
_logger.warning(
f"The relative variation of the signal-axis-scale ({scale_compare:.2f}%) exceeds 1%.\n"
" "
"Using a non-uniform-axis is recommended."
)
else:
signal_dict["axis"] = signal_array
else: # pragma: no cover
if self._use_uniform_signal_axis: # pragma: no cover
_logger.warning( # pragma: no cover
"Signal only contains one entry.\n" # pragma: no cover
" " # pragma: no cover
"Using non-uniform-axis independent of use_uniform_signal_axis setting" # pragma: no cover
) # pragma: no cover
signal_dict["axis"] = signal_array # pragma: no cover
if id == "0x7C696E75":
units = child.text
if "/" in units and units[-3:] == "abs":
signal_dict["name"] = "Wavenumber"
signal_dict["units"] = units[:-4]
elif "/" in units and units[-1] == "m":
signal_dict["name"] = "Raman Shift"
signal_dict["units"] = units
elif units[-2:] == "eV":
signal_dict["name"] = "Energy"
signal_dict["units"] = units
elif "/" not in units and units[-1] == "m":
signal_dict["name"] = "Wavelength"
signal_dict["units"] = units
else:
_logger.warning(
"Cannot extract type of signal axis from units, using wavelength as name."
) # pragma: no cover
signal_dict["name"] = "Wavelength" # pragma: no cover
signal_dict["units"] = units # pragma: no cover
self.axes["signal_dict"] = signal_dict
def _sort_nav_axes(self):
"""Sort the navigation/signal axes, such that (X, Y, Spectrum) = (1, 0, 2) (for map)
or (X/Y, Spectrum) = (0, 1) or (Spectrum) = (0) (for linescan/spectrum).
"""
self.axes["signal_dict"]["index_in_array"] = len(self.axes) - 1
if self._has_nav2:
self.axes["nav2_dict"]["index_in_array"] = 0
if self._has_nav1:
self.axes["nav1_dict"]["index_in_array"] = 1
elif self._has_nav1 and not self._has_nav2:
self.axes["nav1_dict"]["index_in_array"] = 0
self.axes = sorted(self.axes.values(), key=lambda item: item["index_in_array"])
def get_axes(self):
"""Extract navigation/signal axes data from file."""
self.axes = dict()
self._has_nav1 = False
self._has_nav2 = False
for child in self._axis_root:
if self._get_id(child) == "0x0":
self._set_signal_type(child)
if self._get_id(child) == "0x1":
self._set_signal_axis(child)
if self._get_id(child) == "0x2":
self._has_nav1, self._nav1_size = self._set_nav_axis(child, "nav1_dict")
if self._get_id(child) == "0x3":
self._has_nav2, self._nav2_size = self._set_nav_axis(child, "nav2_dict")
self._sort_nav_axes()
def get_data(self):
"""Extract data from file."""
data_raw = self._lsx_matrix.findall("LSX_Row")
## lexicographical ordering -> 3x3 map -> 9 rows
num_rows = len(data_raw)
if num_rows == 0:
_logger.critical("No data found.") # pragma: no cover
elif num_rows == 1:
## Spectrum
self.data = np.fromstring(data_raw[0].text.strip(), sep=" ")
if self._reverse_signal:
self.data = self.data[::-1]
else:
## linescan or map
num_cols = self._get_size(data_raw[0])
self.data = np.empty((num_rows, num_cols))
for i, row in enumerate(data_raw):
row_array = np.fromstring(row.text.strip(), sep=" ")
if self._reverse_signal:
row_array = row_array[::-1]
self.data[i, :] = row_array
## reshape the array (lexicographic -> cartesian)
## reshape depends on available axes
if self._has_nav2:
if self._has_nav1:
self.data = np.reshape(
self.data, (self._nav2_size, self._nav1_size, num_cols)
)
else:
self.data = np.reshape(
self.data, (self._nav2_size, num_cols)
) # pragma: no cover
elif self._has_nav1 and not self._has_nav2:
self.data = np.reshape(self.data, (self._nav1_size, num_cols))
def map_metadata(self):
"""Maps original_metadata to metadata dictionary."""
general = {}
signal = {}
laser = {"Filter": {}, "Polarizer": {}}
spectrometer = {"Grating": {}, "Polarizer": {}}
detector = {"processing": {}}
spectral_image = {}
sample = {}
sample["description"] = self.original_metadata["file_information"].get("Sample")
general["title"] = self._title
general["original_filename"] = self._file_path.name
general["notes"] = self.original_metadata["file_information"].get("Remark")
try:
date, time = self.original_metadata["date"]["Acquired"].split(" ")
except KeyError: # pragma: no cover
pass # pragma: no cover
else:
general["date"] = date
general["time"] = time
signal["signal_type"] = self._signal_type
signal["signal_dimension"] = 1
try:
intensity_axis = self.original_metadata["experimental_setup"]["signal type"]
intensity_units = self.original_metadata["experimental_setup"][
"signal units"
]
except KeyError: # pragma: no cover
pass # pragma: no cover
else:
if intensity_axis == "Intens":
intensity_axis = "Intensity"
if intensity_units == "Cnt/sec":
intensity_units = "Counts/s"
if intensity_units == "Cnt":
intensity_units = "Counts"
signal["quantity"] = f"{intensity_axis} ({intensity_units})"
laser["wavelength"] = self.original_metadata["experimental_setup"].get(
"Laser (nm)"
)
laser["objective_magnification"] = self.original_metadata[
"experimental_setup"
].get("Objective")
laser["Filter"]["optical_density"] = self.original_metadata[
"experimental_setup"
].get("ND Filter (%)")
laser["Polarizer"]["polarizer_type"] = self.original_metadata[
"experimental_setup"
].get("Laser. Pol.")
laser["Polarizer"]["angle"] = self.original_metadata["experimental_setup"].get(
"Laser Pol. (°)"
)
spectrometer["central_wavelength"] = self.original_metadata[
"experimental_setup"
].get("Spectro (nm)")
spectrometer["model"] = self.original_metadata["experimental_setup"].get(
"Instrument"
)
spectrometer["Grating"]["groove_density"] = self.original_metadata[
"experimental_setup"
].get("Grating (gr/mm)")
spectrometer["entrance_slit_width"] = self.original_metadata[
"experimental_setup"
].get("Hole")
spectrometer["spectral_range"] = self.original_metadata[
"experimental_setup"
].get("Range")
spectrometer["Polarizer"]["polarizer_type"] = self.original_metadata[
"experimental_setup"
].get("Raman. Pol.")
spectrometer["Polarizer"]["angle"] = self.original_metadata[
"experimental_setup"
].get("Raman Pol. (°)")
detector["model"] = self.original_metadata["experimental_setup"].get("Detector")
detector["delay_time"] = self.original_metadata["experimental_setup"].get(
"Delay time (s)"
)
detector["binning"] = self.original_metadata["experimental_setup"].get(
"Binning"
)
detector["temperature"] = self.original_metadata["experimental_setup"].get(
"Detector temperature (°C)"
)
detector["exposure_per_frame"] = self.original_metadata[
"experimental_setup"
].get("Acq. time (s)")
detector["frames"] = self.original_metadata["experimental_setup"].get(
"Accumulations"
)
detector["processing"]["autofocus"] = self.original_metadata[
"experimental_setup"
].get("Autofocus")
detector["processing"]["swift"] = self.original_metadata[
"experimental_setup"
].get("SWIFT")
detector["processing"]["auto_exposure"] = self.original_metadata[
"experimental_setup"
].get("AutoExposure")
detector["processing"]["spike_filter"] = self.original_metadata[
"experimental_setup"
].get("Spike filter")
detector["processing"]["de_noise"] = self.original_metadata[
"experimental_setup"
].get("DeNoise")
detector["processing"]["ics_correction"] = self.original_metadata[
"experimental_setup"
].get("ICS correction")
detector["processing"]["dark_correction"] = self.original_metadata[
"experimental_setup"
].get("Dark correction")
detector["processing"]["inst_process"] = self.original_metadata[
"experimental_setup"
].get("Inst. Process")
## extra units here, because rad vs. deg
if "rotation angle (rad)" in self.original_metadata["experimental_setup"]:
spectral_image["rotation_angle"] = self.original_metadata[
"experimental_setup"
]["rotation angle (rad)"] * (180 / np.pi)
spectral_image["rotation_angle_units"] = "°"
## settings for glued spectra
if "Windows" in self.original_metadata["experimental_setup"]:
detector["glued_spectrum"] = True
detector["glued_spectrum_windows"] = self.original_metadata[
"experimental_setup"
]["Windows"]
else:
detector["glued_spectrum"] = False
## calculate and set integration time
try:
integration_time = (
self.original_metadata["experimental_setup"]["Accumulations"]
* self.original_metadata["experimental_setup"]["Acq. time (s)"]
)
except KeyError: # pragma: no cover
pass # pragma: no cover
else:
detector["integration_time"] = integration_time
## convert filter range from percentage (0-100) to (0-1)
try:
laser["Filter"]["optical_density"] /= 100
except KeyError: # pragma: no cover
pass # pragma: no cover
## convert entrance_hole_width to mm
try:
spectrometer["entrance_slit_width"] /= 100
spectrometer["pinhole"] = spectrometer["entrance_slit_width"]
except KeyError: # pragma: no cover
pass # pragma: no cover
self.metadata = {
"General": general,
"Signal": signal,
"Sample": sample,
"Acquisition_instrument": {
"Laser": laser,
"Spectrometer": spectrometer,
"Detector": detector,
"Spectral_image": spectral_image,
},
}
_remove_none_from_dict(self.metadata)
def file_reader(filename, use_uniform_signal_axis=False, **kwds):
"""
Read data from .xml files saved using Horiba Jobin Yvon's LabSpec software.
Parameters
----------
%s
use_uniform_signal_axis: bool, default=False
Can be specified to choose between non-uniform or uniform signal axis.
If ``True``, the ``scale`` attribute is calculated from the average delta
along the signal axis and a warning is raised in case the delta varies
by more than 1 percent.
%s
"""
if not isinstance(filename, Path):
filename = Path(filename)
jy = JobinYvonXMLReader(
file_path=filename, use_uniform_signal_axis=use_uniform_signal_axis
)
jy.parse_file()
jy.get_original_metadata()
jy.get_axes()
jy.get_data()
jy.map_metadata()
dictionary = {
"data": jy.data,
"axes": jy.axes,
"metadata": deepcopy(jy.metadata),
"original_metadata": deepcopy(jy.original_metadata),
}
return [
dictionary,
]
file_reader.__doc__ %= (FILENAME_DOC, RETURNS_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/jobinyvon/_api.py | 0.873768 | 0.33158 | _api.py | pypi |
import os
import logging
import warnings
import datetime
import dateutil
import numpy as np
import dask
from dask.diagnostics import ProgressBar
from skimage import dtype_limits
from rsciio._docstrings import (
FILENAME_DOC,
LAZY_DOC,
ENDIANESS_DOC,
MMAP_DOC,
RETURNS_DOC,
SIGNAL_DOC,
)
from rsciio.utils.skimage_exposure import rescale_intensity
from rsciio.utils.tools import DTBox, sarray2dict, dict2sarray
from rsciio.utils.date_time_tools import (
serial_date_to_ISO_format,
datetime_to_serial_date,
)
from rsciio.utils.tools import dummy_context_manager, convert_units
_logger = logging.getLogger(__name__)
magics = [0x0102]
mapping = {
"blockfile_header.Beam_energy": (
"Acquisition_instrument.TEM.beam_energy",
lambda x: x * 1e-3,
),
"blockfile_header.Camera_length": (
"Acquisition_instrument.TEM.camera_length",
lambda x: x * 1e-4,
),
"blockfile_header.Scan_rotation": (
"Acquisition_instrument.TEM.rotation",
lambda x: x * 1e-2,
),
}
def get_header_dtype_list(endianess="<"):
end = endianess
dtype_list = (
[
("ID", (bytes, 6)),
("MAGIC", end + "u2"),
("Data_offset_1", end + "u4"), # Offset VBF
("Data_offset_2", end + "u4"), # Offset DPs
("UNKNOWN1", end + "u4"), # Flags for ASTAR software?
("DP_SZ", end + "u2"), # Pixel dim DPs
("DP_rotation", end + "u2"), # [degrees ( * 100 ?)]
("NX", end + "u2"), # Scan dim 1
("NY", end + "u2"), # Scan dim 2
("Scan_rotation", end + "u2"), # [100 * degrees]
("SX", end + "f8"), # Pixel size [nm]
("SY", end + "f8"), # Pixel size [nm]
("Beam_energy", end + "u4"), # [V]
("SDP", end + "u2"), # Pixel size [100 * ppcm]
("Camera_length", end + "u4"), # [10 * mm]
("Acquisition_time", end + "f8"), # [Serial date]
]
+ [("Centering_N%d" % i, "f8") for i in range(8)]
+ [("Distortion_N%02d" % i, "f8") for i in range(14)]
)
return dtype_list
def get_default_header(endianess="<"):
"""Returns a header pre-populated with default values."""
dt = np.dtype(get_header_dtype_list())
header = np.zeros((1,), dtype=dt)
header["ID"][0] = "IMGBLO".encode()
header["MAGIC"][0] = magics[0]
header["Data_offset_1"][0] = 0x1000 # Always this value observed
header["UNKNOWN1"][0] = 131141 # Very typical value (always?)
header["Acquisition_time"][0] = datetime_to_serial_date(
datetime.datetime.fromtimestamp(86400, dateutil.tz.tzutc())
)
# Default to UNIX epoch + 1 day
# Have to add 1 day, as dateutil's timezones dont work before epoch
return header
def get_header_from_signal(signal, endianess="<"):
header = get_default_header(endianess)
if "blockfile_header" in signal["original_metadata"]:
header = dict2sarray(
signal["original_metadata"]["blockfile_header"], sarray=header
)
note = signal["original_metadata"]["blockfile_header"]["Note"]
else:
note = ""
# The navigation and signal units are 'nm' and 'cm', respectively, so we
# convert the units accordingly before saving the signal
axes = signal["axes"]
sig_axes = [axis for axis in axes if not axis["navigate"]]
nav_axes = [axis for axis in axes if axis["navigate"]]
for axis in sig_axes:
if axis["units"]:
try:
axis["scale"] = convert_units(axis["scale"], axis["units"], "cm")
axis["offset"] = convert_units(axis["offset"], axis["units"], "cm")
except Exception:
warnings.warn(
"BLO file expects cm units in signal dimensions. "
f"Existing units, {axis['units']} could not be converted; saving "
"axes scales as is. Beware that scales "
"will likely be incorrect in the file.",
UserWarning,
)
else:
warnings.warn(
"BLO file expects cm units in signal dimensions. "
f"The {axis['name']} does not have units; saving "
"axes scales as is. Beware that scales "
"will likely be incorrect in the file.",
UserWarning,
)
for axis in nav_axes:
if axis["units"]:
try:
axis["scale"] = convert_units(axis["scale"], axis["units"], "nm")
axis["offset"] = convert_units(axis["offset"], axis["units"], "nm")
except Exception:
warnings.warn(
"BLO file expects nm units in navigation dimensions. "
f"Existing units, {axis['units']} could not be converted; saving "
"axes scales as is. Beware that scales "
"will likely be incorrect in the file.",
UserWarning,
)
else:
warnings.warn(
"BLO file expects nm units in navigation dimensions. "
f"The {axis['name']} does not have units; saving "
"axes scales as is. Beware that scales "
"will likely be incorrect in the file.",
UserWarning,
)
if len(nav_axes) == 2:
NX = nav_axes[1]["size"]
NY = nav_axes[0]["size"]
SX = nav_axes[1]["scale"]
SY = nav_axes[0]["scale"]
elif len(nav_axes) == 1:
NX = nav_axes[0]["size"]
NY = 1
SX = nav_axes[0]["scale"]
SY = SX
elif len(nav_axes) == 0:
NX = NY = SX = SY = 1
DP_SZ = [axis["size"] for axis in sig_axes][::-1]
if DP_SZ[0] != DP_SZ[1]:
raise ValueError("Blockfiles require signal shape to be square!")
DP_SZ = DP_SZ[0]
SDP = 100.0 / sig_axes[1]["scale"]
offset2 = NX * NY + header["Data_offset_1"]
# Based on inspected files, the DPs are stored at 16-bit boundary...
# Normally, you'd expect word alignment (32-bits) ¯\_(°_o)_/¯
offset2 += offset2 % 16
header = dict2sarray(
{
"NX": NX,
"NY": NY,
"DP_SZ": DP_SZ,
"SX": SX,
"SY": SY,
"SDP": SDP,
"Data_offset_2": offset2,
},
sarray=header,
)
return header, note
def file_reader(filename, lazy=False, mmap_mode=None, endianess="<"):
"""
Read a blockfile.
Parameters
----------
%s
%s
%s
%s
%s
"""
_logger.debug("Reading blockfile: %s" % filename)
metadata = {}
if mmap_mode is None:
mmap_mode = "r" if lazy else "c"
# Makes sure we open in right mode:
if "+" in mmap_mode or ("write" in mmap_mode and "copyonwrite" != mmap_mode):
if lazy:
raise ValueError("Lazy loading does not support in-place writing")
f = open(filename, "r+b")
else:
f = open(filename, "rb")
_logger.debug("File opened")
# Get header
header = np.fromfile(f, dtype=get_header_dtype_list(endianess), count=1)
if header["MAGIC"][0] not in magics:
warnings.warn(
"Blockfile has unrecognized header signature. "
"Will attempt to read, but correcteness not guaranteed!",
UserWarning,
)
header = sarray2dict(header)
note = f.read(header["Data_offset_1"] - f.tell())
# It seems it uses "\x00" for padding, so we remove it
try:
header["Note"] = note.decode("latin1").strip("\x00")
except Exception:
# Not sure about the encoding so, if it fails, we carry on
_logger.warning(
"Reading the Note metadata of this file failed. "
"You can help improving "
"HyperSpy by reporting the issue in "
"https://github.com/hyperspy/hyperspy"
)
_logger.debug("File header: " + str(header))
NX, NY = int(header["NX"]), int(header["NY"])
DP_SZ = int(header["DP_SZ"])
if header["SDP"]:
SDP = 100.0 / header["SDP"]
else:
SDP = 1 # Set default scale to 1
original_metadata = {"blockfile_header": header}
# Get data:
# TODO A Virtual BF/DF is stored first, may be loaded as navigator in future
# offset1 = header['Data_offset_1']
# f.seek(offset1)
# navigator = np.fromfile(f, dtype=endianess+"u1", shape=(NX, NY)).T
# Then comes actual blockfile
offset2 = header["Data_offset_2"]
if not lazy:
f.seek(offset2)
data = np.fromfile(f, dtype=endianess + "u1")
else:
data = np.memmap(f, mode=mmap_mode, offset=offset2, dtype=endianess + "u1")
try:
data = data.reshape((NY, NX, DP_SZ * DP_SZ + 6))
except ValueError:
warnings.warn(
"Blockfile header dimensions larger than file size! "
"Will attempt to load by zero padding incomplete frames."
)
# Data is stored DP by DP:
pw = [(0, NX * NY * (DP_SZ * DP_SZ + 6) - data.size)]
data = np.pad(data, pw, mode="constant")
data = data.reshape((NY, NX, DP_SZ * DP_SZ + 6))
# Every frame is preceeded by a 6 byte sequence (AA 55, and then a 4 byte
# integer specifying frame number)
data = data[:, :, 6:]
data = data.reshape((NY, NX, DP_SZ, DP_SZ), order="C").squeeze()
units = ["nm", "nm", "cm", "cm"]
names = ["y", "x", "dy", "dx"]
navigate = [True, True, False, False]
scales = [header["SY"], header["SX"], SDP, SDP]
date, time, time_zone = serial_date_to_ISO_format(header["Acquisition_time"])
metadata = {
"General": {
"original_filename": os.path.split(filename)[1],
"date": date,
"time": time,
"time_zone": time_zone,
"notes": header["Note"],
},
"Signal": {"signal_type": "diffraction"},
}
# Create the axis objects for each axis
dim = data.ndim
axes = [
{
"size": data.shape[i],
"index_in_array": i,
"name": names[i],
"scale": scales[i],
"offset": 0.0,
"units": units[i],
"navigate": navigate[i],
}
for i in range(dim)
]
dictionary = {
"data": data,
"axes": axes,
"metadata": metadata,
"original_metadata": original_metadata,
"mapping": mapping,
}
f.close()
return [
dictionary,
]
file_reader.__doc__ %= (FILENAME_DOC, LAZY_DOC, ENDIANESS_DOC, MMAP_DOC, RETURNS_DOC)
def file_writer(
filename,
signal,
intensity_scaling=None,
navigator="navigator",
show_progressbar=True,
endianess="<",
):
"""
Write signal to blockfile.
Parameters
----------
%s
%s
intensity_scaling : str or 2-Tuple of float/int
If the signal datatype is not :py:class:`numpy.uint8`, casting to this
datatype without intensity rescaling results in overflow errors (default behavior)
This argument provides intensity scaling strategies and the options are:
- ``'dtype'``: the limits of the datatype of the dataset, e.g. 0-65535 for
:py:class:`numpy.uint16`, are mapped onto 0-255, respectively. Does not work
for ``float`` data types.
- ``'minmax'``: the minimum and maximum in the dataset are mapped to 0-255.
- ``'crop'``: everything below 0 and above 255 is set to 0 and 255, respectively
- 2-tuple of `floats` or `ints`: the intensities between these values are
scaled between 0-255, everything below is 0 and everything above is 255.
navigator : str or array-like
A ``.blo`` file also saves a virtual bright field image for navigation.
This option determines what kind of data is stored for this image.
By default this is set to ``'navigator'``, which results in using the
:py:attr:`hyperspy.signal.BaseSignal.navigator` attribute if used with HyperSpy.
Otherwise, it is calculated during saving which can take some time for large
datasets. Alternatively, an array-like of the right shape may also be provided.
If set to None, a zero array is stored in the file.
show_progressbar : bool
Whether to show the progressbar or not.
endianess : str
``'<'`` (default) or ``'>'`` determining how the bits are written to the file
"""
smetadata = DTBox(signal["metadata"], box_dots=True)
if intensity_scaling is None:
# to distinguish from the tuple case
if signal["data"].dtype != "u1":
warnings.warn(
"Data does not have uint8 dtype: values outside the "
"range 0-255 may result in overflow. To avoid this "
"use the 'intensity_scaling' keyword argument.",
UserWarning,
)
elif intensity_scaling == "dtype":
original_scale = dtype_limits(signal["data"])
if original_scale[1] == 1.0:
raise ValueError("Signals with float dtype can not use 'dtype'")
elif intensity_scaling == "minmax":
minimum = signal["data"].min()
maximum = signal["data"].max()
if signal["attributes"]["_lazy"]:
minimum, maximum = dask.compute(minimum, maximum)
original_scale = (minimum, maximum)
elif intensity_scaling == "crop":
original_scale = (0, 255)
else:
# we leave the error checking for incorrect tuples to skimage
original_scale = intensity_scaling
header, note = get_header_from_signal(signal, endianess=endianess)
with open(filename, "wb") as f:
# Write header
header.tofile(f)
# Write header note field:
if len(note) > int(header["Data_offset_1"]) - f.tell():
note = note[: int(header["Data_offset_1"]) - f.tell() - len(note)]
f.write(note.encode())
# Zero pad until next data block
zero_pad = int(header["Data_offset_1"]) - f.tell()
np.zeros((zero_pad,), np.byte).tofile(f)
# Write virtual bright field
if navigator is None:
navigator = np.zeros((signal["data"].shape[0], signal["data"].shape[1]))
elif isinstance(navigator, str) and (navigator == "navigator"):
if smetadata.get("_HyperSpy._sig_navigator", False):
navigator = smetadata["_HyperSpy._sig_navigator.data"]
else:
navigator = signal["data"].mean(axis=(-2, -1))
elif hasattr(navigator, "shape"):
# Is numpy array-like
# check that the shape is ok
if navigator.shape != signal["data"].shape[:2]:
raise ValueError(
"Size of the provided `navigator` does not match the "
"navigation dimensions of the dataset."
)
else:
raise ValueError("The `navigator` argument is expected to be array-like")
if intensity_scaling is not None:
navigator = rescale_intensity(
navigator, in_range=original_scale, out_range=np.uint8
)
navigator = navigator.astype(endianess + "u1")
np.asanyarray(navigator).tofile(f)
# Zero pad until next data block
if f.tell() > int(header["Data_offset_2"]):
raise ValueError(
"Signal navigation size does not match " "data dimensions."
)
zero_pad = int(header["Data_offset_2"]) - f.tell()
np.zeros((zero_pad,), np.byte).tofile(f)
file_location = f.tell()
if intensity_scaling is not None:
array_data = rescale_intensity(
signal["data"],
in_range=original_scale,
out_range=np.uint8,
)
else:
array_data = signal["data"]
array_data = array_data.astype(endianess + "u1")
# Write full data stack:
# We need to pad each image with magic 'AA55', then a u32 serial
pixels = array_data.shape[-2:]
records = array_data.shape[:-2]
record_dtype = [
("MAGIC", endianess + "u2"),
("ID", endianess + "u4"),
("IMG", endianess + "u1", pixels),
]
magics = np.full(records, 0x55AA, dtype=endianess + "u2")
ids = np.arange(np.product(records), dtype=endianess + "u4").reshape(records)
file_memmap = np.memmap(
filename, dtype=record_dtype, mode="r+", offset=file_location, shape=records
)
file_memmap["MAGIC"] = magics
file_memmap["ID"] = ids
if signal["attributes"]["_lazy"]:
cm = ProgressBar if show_progressbar else dummy_context_manager
with cm():
array_data.store(file_memmap["IMG"])
else:
file_memmap["IMG"] = array_data
file_memmap.flush()
file_writer.__doc__ %= (FILENAME_DOC.replace("read", "write to"), SIGNAL_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/blockfile/_api.py | 0.551815 | 0.288155 | _api.py | pypi |
import numpy as np
import os
import scipy
from datetime import datetime
from rsciio._docstrings import FILENAME_DOC, RETURNS_DOC
def _cnv_time(timestr):
try:
t = datetime.strptime(timestr.decode(), "%H:%M:%S.%f")
dt = t - datetime(t.year, t.month, t.day)
r = float(dt.seconds) + float(dt.microseconds) * 1e-6
except ValueError:
r = float(timestr)
return r
def _bad_file(filename):
raise AssertionError("Cannot interpret as DENS heater log: %s" % filename)
def file_reader(filename, *args, **kwds):
"""Read a DENSsolutions DigiHeater logfile.
Parameters
----------
%s
%s
"""
with open(filename, "rt") as f:
# Strip leading, empty lines
line = str(f.readline())
while line.strip() == "" and not f.closed:
line = str(f.readline())
try:
date, version = line.split("\t")
except ValueError:
_bad_file(filename)
if version.strip() != "Digiheater 3.1":
_bad_file(filename)
calib = str(f.readline()).split("\t")
str(f.readline()) # delta_t
header_line = str(f.readline())
try:
R0, a, b, c = [float(v.split("=")[1]) for v in calib]
date0 = datetime.strptime(date, "%d/%m/'%y %H:%M")
date = "%s" % date0.date()
time = "%s" % date0.time()
except ValueError:
_bad_file(filename)
original_metadata = dict(R0=R0, a=a, b=b, c=c, date=date0, version=version)
if header_line.strip() != (
"sample\ttime\tTset[C]\tTmeas[C]\tRheat[ohm]\tVheat[V]\t"
"Iheat[mA]\tPheat [mW]\tc"
):
_bad_file(filename)
try:
rawdata = np.loadtxt(
f, converters={1: _cnv_time}, usecols=(1, 3), unpack=True
)
except ValueError:
_bad_file(filename)
times = rawdata[0]
# Add a day worth of seconds to any values after a detected rollover
# Hopefully unlikely that there is more than one, but we can handle it
for rollover in 1 + np.where(np.diff(times) < 0)[0]:
times[rollover:] += 60 * 60 * 24
# Raw data is not necessarily grid aligned. Interpolate onto grid.
dt = np.diff(times).mean()
temp = rawdata[1]
interp = scipy.interpolate.interp1d(
times, temp, copy=False, assume_sorted=True, bounds_error=False
)
interp_axis = times[0] + dt * np.array(range(len(times)))
temp_interp = interp(interp_axis)
metadata = {
"General": {
"original_filename": os.path.split(filename)[1],
"date": date,
"time": time,
},
"Signal": {"signal_type": "", "quantity": "Temperature (Celsius)"},
}
axes = [
{
"size": len(temp_interp),
"index_in_array": 0,
"name": "Time",
"scale": dt,
"offset": times[0],
"units": "s",
"navigate": False,
}
]
dictionary = {
"data": temp_interp,
"axes": axes,
"metadata": metadata,
"original_metadata": {"DENS_header": original_metadata},
}
return [
dictionary,
]
file_reader.__doc__ %= (FILENAME_DOC, RETURNS_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/dens/_api.py | 0.47244 | 0.299361 | _api.py | pypi |
import numpy as np
import os
from datetime import datetime as dt
import csv
import logging
from rsciio._docstrings import FILENAME_DOC, RETURNS_DOC
_logger = logging.getLogger(__name__)
# At some point, if there is another readerw, whith also use csv file, it will
# be necessary to mention the other reader in this message (and to add an
# argument in the load function to specify the correct reader)
invalid_file_error = (
"The csv reader can't import the file, please"
" make sure, that this is a valid Impulse log file."
)
invalid_filenaming_error = {
"The filename does not match Impulse naming, please"
" make sure that the filenames for the logfile and metadata file are unchanged."
}
def file_reader(filename, *args, **kwds):
"""Read a DENSsolutions Impulse logfile.
Parameters
----------
%s
%s
"""
csv_file = ImpulseCSV(filename)
return _impulseCSV_log_reader(csv_file)
file_reader.__doc__ %= (FILENAME_DOC, RETURNS_DOC)
def _impulseCSV_log_reader(csv_file):
csvs = []
for key in csv_file.logged_quantity_name_list:
csvs.append(csv_file.get_dictionary(key))
return csvs
class ImpulseCSV:
def __init__(self, filename):
self.filename = filename
self._parse_header()
self._read_data()
def _parse_header(self):
with open(self.filename, "r") as f:
s = f.readline()
self.column_names = s.strip().split(",")
if not self._is_impulse_csv_file():
raise IOError(invalid_file_error)
self._read_metadatafile()
self.logged_quantity_name_list = self.column_names[2:]
def _is_impulse_csv_file(self):
return "TimeStamp" in self.column_names and len(self.column_names) >= 3
def get_dictionary(self, quantity):
return {
"data": self._data_dictionary[quantity],
"axes": self._get_axes(),
"metadata": self._get_metadata(quantity),
"original_metadata": {"Impulse_header": self.original_metadata},
}
def _get_metadata(self, quantity):
return {
"General": {
"original_filename": os.path.split(self.filename)[1],
"title": "%s" % quantity,
"date": self.original_metadata["Experiment_date"],
"time": self.original_metadata["Experiment_time"],
},
"Signal": {
"quantity": self._parse_quantity_units(quantity),
},
}
def _parse_quantity_units(self, quantity):
quantity_split = quantity.strip().split(" ")
if (
len(quantity_split) > 1
and quantity_split[-1][0] == "("
and quantity_split[-1][-1] == ")"
):
return quantity_split[-1].replace("(", "").replace(")", "")
else:
return ""
def _read_data(self):
names = [
name.replace(" ", "_")
.replace("°C", "C")
.replace("#", "No")
.replace("(", "")
.replace(")", "")
.replace("/", "_")
.replace("%", "Perc")
for name in self.column_names
]
data = np.genfromtxt(
self.filename,
delimiter=",",
dtype=None,
names=names,
skip_header=1,
encoding="latin1",
)
self._data_dictionary = dict()
for i, (name, name_dtype) in enumerate(zip(self.column_names, names)):
if name == "Experiment time":
self.time_axis = data[name_dtype]
elif name == "MixValve":
mixvalvedatachanged = data[name_dtype]
for index, item in enumerate(data[name_dtype]):
mixvalvedatachanged[index] = (
int(int(item.split(";")[0]) + 2) * 100
+ (int(item.split(";")[1]) + 2) * 10
+ (int(item.split(";")[2]) + 2)
)
mixvalvedatachangedint = np.array(mixvalvedatachanged, dtype=np.int32)
self._data_dictionary[name] = mixvalvedatachangedint
else:
self._data_dictionary[name] = data[name_dtype]
def _read_metadatafile(self):
# Locate the experiment metadata file
self.original_metadata = {}
notes = []
notes_section = False
if "_Synchronized data" in str(self.filename) or "raw" in str(
self.filename
): # Check if Impulse filename formatting is intact
metadata_file = (
"_".join(str(self.filename).split("_")[:-1]) + "_Metadata.log"
).replace("\\", "/")
if os.path.isfile(metadata_file):
with open(metadata_file, newline="") as csvfile:
metadata_file_reader = csv.reader(csvfile, delimiter=",")
for row in metadata_file_reader:
if notes_section:
notes.append(row[0])
elif row[0] == "Live notes":
notes_section = True
notes = [row[1].strip()]
else:
self.original_metadata[row[0].replace(" ", "_")] = row[
1
].strip()
self.original_metadata["Notes"] = notes
else:
_logger.warning("No metadata file found in folder")
else:
raise IOError(invalid_filenaming_error)
def _get_axes(self):
return [
{
"size": self.time_axis.shape[0],
"index_in_array": 0,
"name": "Time",
"scale": np.diff(self.time_axis[1:-1]).mean(),
"offset": 0,
"units": "Seconds",
"navigate": False,
}
] | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/impulse/_api.py | 0.482185 | 0.212784 | _api.py | pypi |
import os
import logging
import numpy as np
from rsciio._docstrings import FILENAME_DOC, RETURNS_DOC
_logger = logging.getLogger(__name__)
no_netcdf = False
try:
from netCDF4 import Dataset
which_netcdf = "netCDF4"
except Exception:
try:
from netCDF3 import Dataset
which_netcdf = "netCDF3"
except Exception:
try:
from Scientific.IO.NetCDF import NetCDFFile as Dataset
which_netcdf = "Scientific Python"
except Exception:
no_netcdf = True
attrib2netcdf = {
"energyorigin": "energy_origin",
"energyscale": "energy_scale",
"energyunits": "energy_units",
"xorigin": "x_origin",
"xscale": "x_scale",
"xunits": "x_units",
"yorigin": "y_origin",
"yscale": "y_scale",
"yunits": "y_units",
"zorigin": "z_origin",
"zscale": "z_scale",
"zunits": "z_units",
"exposure": "exposure",
"title": "title",
"binning": "binning",
"readout_frequency": "readout_frequency",
"ccd_height": "ccd_height",
"blanking": "blanking",
}
acquisition2netcdf = {
"exposure": "exposure",
"binning": "binning",
"readout_frequency": "readout_frequency",
"ccd_height": "ccd_height",
"blanking": "blanking",
"gain": "gain",
"pppc": "pppc",
}
treatments2netcdf = {
"dark_current": "dark_current",
"readout": "readout",
}
def file_reader(filename, *args, **kwds):
"""
Read netCDF ``.nc`` files saved using the HyperSpy predecessor EELSlab.
Parameters
----------
%s
%s
"""
if no_netcdf is True:
raise ImportError(
"No netCDF library installed. "
"To read EELSLab netcdf files install "
"one of the following packages:"
"netCDF4, netCDF3, netcdf, scientific"
)
ncfile = Dataset(filename, "r")
if (
hasattr(ncfile, "file_format_version")
and ncfile.file_format_version == "EELSLab 0.1"
):
dictionary = nc_hyperspy_reader_0dot1(ncfile, filename, *args, **kwds)
else:
ncfile.close()
raise IOError("Unsupported netCDF file")
return (dictionary,)
file_reader.__doc__ %= (FILENAME_DOC, RETURNS_DOC)
def nc_hyperspy_reader_0dot1(ncfile, filename, *args, **kwds):
calibration_dict, acquisition_dict, treatments_dict = {}, {}, {}
dc = ncfile.variables["data_cube"]
data = dc[:]
if "history" in calibration_dict:
calibration_dict["history"] = eval(ncfile.history)
for attrib in attrib2netcdf.items():
if hasattr(dc, attrib[1]):
value = eval("dc." + attrib[1])
if isinstance(value, np.ndarray):
calibration_dict[attrib[0]] = value[0]
else:
calibration_dict[attrib[0]] = value
else:
_logger.warning(
"Warning: the attribute '%s' is not defined in " "the file '%s'",
attrib[0],
filename,
)
for attrib in acquisition2netcdf.items():
if hasattr(dc, attrib[1]):
value = eval("dc." + attrib[1])
if isinstance(value, np.ndarray):
acquisition_dict[attrib[0]] = value[0]
else:
acquisition_dict[attrib[0]] = value
else:
_logger.warning(
"Warning: the attribute '%s' is not defined in " "the file '%s'",
attrib[0],
filename,
)
for attrib in treatments2netcdf.items():
if hasattr(dc, attrib[1]):
treatments_dict[attrib[0]] = eval("dc." + attrib[1])
else:
_logger.warning(
"Warning: the attribute '%s' is not defined in " "the file '%s'",
attrib[0],
filename,
)
original_metadata = {
"record_by": ncfile.type,
"calibration": calibration_dict,
"acquisition": acquisition_dict,
"treatments": treatments_dict,
}
ncfile.close()
# Now we'll map some parameters
record_by = "image" if original_metadata["record_by"] == "image" else "spectrum"
if record_by == "image":
dim = len(data.shape)
names = ["Z", "Y", "X"][3 - dim :]
scaleskeys = ["zscale", "yscale", "xscale"]
originskeys = ["zorigin", "yorigin", "xorigin"]
unitskeys = ["zunits", "yunits", "xunits"]
navigate = [True, False, False]
elif record_by == "spectrum":
dim = len(data.shape)
names = ["Y", "X", "Energy"][3 - dim :]
scaleskeys = ["yscale", "xscale", "energyscale"]
originskeys = ["yorigin", "xorigin", "energyorigin"]
unitskeys = ["yunits", "xunits", "energyunits"]
navigate = [True, True, False]
# The images are recorded in the Fortran order
data = data.T.copy()
try:
scales = [calibration_dict[key] for key in scaleskeys[3 - dim :]]
except KeyError:
scales = [1, 1, 1][3 - dim :]
try:
origins = [calibration_dict[key] for key in originskeys[3 - dim :]]
except KeyError:
origins = [0, 0, 0][3 - dim :]
try:
units = [calibration_dict[key] for key in unitskeys[3 - dim :]]
except KeyError:
units = ["", "", ""]
axes = [
{
"size": int(data.shape[i]),
"index_in_array": i,
"name": names[i],
"scale": scales[i],
"offset": origins[i],
"units": units[i],
"navigate": navigate[i],
}
for i in range(dim)
]
metadata = {"General": {}, "Signal": {}}
metadata["General"]["original_filename"] = os.path.split(filename)[1]
metadata["General"]["signal_type"] = ""
dictionary = {
"data": data,
"axes": axes,
"metadata": metadata,
"original_metadata": original_metadata,
}
return dictionary | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/netcdf/_api.py | 0.565779 | 0.309441 | _api.py | pypi |
# The details of the format were taken from
# https://www.biochem.mpg.de/doc_tom/TOM_Release_2008/IOfun/tom_mrcread.html
# and https://ami.scripps.edu/software/mrctools/mrc_specification.php
import os
import logging
import numpy as np
from rsciio._docstrings import (
FILENAME_DOC,
LAZY_DOC,
ENDIANESS_DOC,
MMAP_DOC,
RETURNS_DOC,
)
from rsciio.utils.tools import sarray2dict
_logger = logging.getLogger(__name__)
def get_std_dtype_list(endianess="<"):
end = endianess
dtype_list = [
("NX", end + "u4"),
("NY", end + "u4"),
("NZ", end + "u4"),
("MODE", end + "u4"),
("NXSTART", end + "u4"),
("NYSTART", end + "u4"),
("NZSTART", end + "u4"),
("MX", end + "u4"),
("MY", end + "u4"),
("MZ", end + "u4"),
("Xlen", end + "f4"),
("Ylen", end + "f4"),
("Zlen", end + "f4"),
("ALPHA", end + "f4"),
("BETA", end + "f4"),
("GAMMA", end + "f4"),
("MAPC", end + "u4"),
("MAPR", end + "u4"),
("MAPS", end + "u4"),
("AMIN", end + "f4"),
("AMAX", end + "f4"),
("AMEAN", end + "f4"),
("ISPG", end + "u2"),
("NSYMBT", end + "u2"),
("NEXT", end + "u4"),
("CREATID", end + "u2"),
("EXTRA", (np.void, 30)),
("NINT", end + "u2"),
("NREAL", end + "u2"),
("EXTRA2", (np.void, 28)),
("IDTYPE", end + "u2"),
("LENS", end + "u2"),
("ND1", end + "u2"),
("ND2", end + "u2"),
("VD1", end + "u2"),
("VD2", end + "u2"),
("TILTANGLES", (np.float32, 6)),
("XORIGIN", end + "f4"),
("YORIGIN", end + "f4"),
("ZORIGIN", end + "f4"),
("CMAP", (bytes, 4)),
("STAMP", (bytes, 4)),
("RMS", end + "f4"),
("NLABL", end + "u4"),
("LABELS", (bytes, 800)),
]
return dtype_list
def get_fei_dtype_list(endianess="<"):
end = endianess
dtype_list = [
("a_tilt", end + "f4"), # Alpha tilt (deg)
("b_tilt", end + "f4"), # Beta tilt (deg)
# Stage x position (Unit=m. But if value>1, unit=???m)
("x_stage", end + "f4"),
# Stage y position (Unit=m. But if value>1, unit=???m)
("y_stage", end + "f4"),
# Stage z position (Unit=m. But if value>1, unit=???m)
("z_stage", end + "f4"),
# Signal2D shift x (Unit=m. But if value>1, unit=???m)
("x_shift", end + "f4"),
# Signal2D shift y (Unit=m. But if value>1, unit=???m)
("y_shift", end + "f4"),
("defocus", end + "f4"), # Defocus Unit=m. But if value>1, unit=???m)
("exp_time", end + "f4"), # Exposure time (s)
("mean_int", end + "f4"), # Mean value of image
("tilt_axis", end + "f4"), # Tilt axis (deg)
("pixel_size", end + "f4"), # Pixel size of image (m)
("magnification", end + "f4"), # Magnification used
# Not used (filling up to 128 bytes)
("empty", (np.void, 128 - 13 * 4)),
]
return dtype_list
def get_data_type(mode):
mode_to_dtype = {
0: np.int8,
1: np.int16,
2: np.float32,
4: np.complex64,
6: np.uint16,
12: np.float16,
}
mode = int(mode)
if mode in mode_to_dtype:
return np.dtype(mode_to_dtype[mode])
else:
raise ValueError(f"Unrecognised mode '{mode}'.")
def file_reader(
filename, lazy=False, mmap_mode=None, navigation_shape=None, endianess="<", **kwds
):
"""
File reader for the MRC format for tomographic data.
Parameters
----------
%s
%s
%s
navigation_shape : tuple, None
Specify the shape of the navigation space.
%s
%s
"""
metadata = {}
f = open(filename, "rb")
std_header = np.fromfile(f, dtype=get_std_dtype_list(endianess), count=1)
fei_header = None
if std_header["NEXT"] / 1024 == 128:
_logger.info(f"{filename} seems to contain an extended FEI header")
fei_header = np.fromfile(f, dtype=get_fei_dtype_list(endianess), count=1024)
if f.tell() == 1024 + std_header["NEXT"]:
_logger.debug("The FEI header was correctly loaded")
else:
f.seek(1024 + std_header["NEXT"][0])
fei_header = None
NX, NY, NZ = std_header["NX"], std_header["NY"], std_header["NZ"]
if mmap_mode is None:
mmap_mode = "r" if lazy else "c"
shape = (NX[0], NY[0], NZ[0])
if navigation_shape is not None:
shape = shape[:2] + navigation_shape
data = (
np.memmap(
f,
mode=mmap_mode,
offset=f.tell(),
dtype=get_data_type(std_header["MODE"]),
)
.reshape(shape, order="F")
.squeeze()
.T
)
original_metadata = {"std_header": sarray2dict(std_header)}
# Convert bytes to unicode
for key in ["CMAP", "STAMP", "LABELS"]:
original_metadata["std_header"][key] = original_metadata["std_header"][
key
].decode()
if fei_header is not None:
fei_dict = sarray2dict(
fei_header,
)
del fei_dict["empty"]
original_metadata["fei_header"] = fei_dict
if fei_header is None:
# The scale is in Angstroms, we convert it to nm
scales = [
float(std_header["Zlen"] / std_header["MZ"]) / 10
if float(std_header["Zlen"]) != 0 and float(std_header["MZ"]) != 0
else 1,
float(std_header["Ylen"] / std_header["MY"]) / 10
if float(std_header["MY"]) != 0
else 1,
float(std_header["Xlen"] / std_header["MX"]) / 10
if float(std_header["MX"]) != 0
else 1,
]
offsets = [
float(std_header["ZORIGIN"]) / 10,
float(std_header["YORIGIN"]) / 10,
float(std_header["XORIGIN"]) / 10,
]
else:
# FEI does not use the standard header to store the scale
# It does store the spatial scale in pixel_size, one per angle in
# meters
scales = [
1,
] + [
fei_header["pixel_size"][0] * 10**9,
] * 2
offsets = [
0,
] * 3
units = [None, "nm", "nm"]
names = ["z", "y", "x"]
navigate = [True, False, False]
nav_axis_to_add = 0
if navigation_shape is not None:
nav_axis_to_add = len(navigation_shape) - 1
for i in range(nav_axis_to_add):
print(i)
units.insert(0, None)
names.insert(0, "")
navigate.insert(0, True)
scales.insert(0, 1)
offsets.insert(0, 0)
metadata = {
"General": {"original_filename": os.path.split(filename)[1]},
"Signal": {"signal_type": ""},
}
# create the axis objects for each axis
dim = len(data.shape)
axes = [
{
"size": data.shape[i],
"index_in_array": i,
"name": names[i + nav_axis_to_add + 3 - dim],
"scale": scales[i + nav_axis_to_add + 3 - dim],
"offset": offsets[i + nav_axis_to_add + 3 - dim],
"units": units[i + nav_axis_to_add + 3 - dim],
"navigate": navigate[i + nav_axis_to_add + 3 - dim],
}
for i in range(dim)
]
dictionary = {
"data": data,
"axes": axes,
"metadata": metadata,
"original_metadata": original_metadata,
"mapping": mapping,
}
return [
dictionary,
]
mapping = {
"fei_header.a_tilt": ("Acquisition_instrument.TEM.Stage.tilt_alpha", None),
"fei_header.b_tilt": ("Acquisition_instrument.TEM.Stage.tilt_beta", None),
"fei_header.x_stage": ("Acquisition_instrument.TEM.Stage.x", None),
"fei_header.y_stage": ("Acquisition_instrument.TEM.Stage.y", None),
"fei_header.z_stage": ("Acquisition_instrument.TEM.Stage.z", None),
"fei_header.exp_time": (
"Acquisition_instrument.TEM.Detector.Camera.exposure",
None,
),
"fei_header.magnification": ("Acquisition_instrument.TEM.magnification", None),
}
file_reader.__doc__ %= (FILENAME_DOC, LAZY_DOC, ENDIANESS_DOC, MMAP_DOC, RETURNS_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/mrc/_api.py | 0.729134 | 0.335201 | _api.py | pypi |
import bz2
import math
import numpy as np
import copy
import os
import struct
import io
from datetime import datetime
from dateutil import tz
import tifffile
import xml.etree.ElementTree as ET
from rsciio._docstrings import FILENAME_DOC, LAZY_DOC, RETURNS_DOC
def element_symbol(z):
elements = [
"",
"H",
"He",
"Li",
"Be",
"B",
"C",
"N",
"O",
"F",
"Ne",
"Na",
"Mg",
"Al",
"Si",
"P",
"S",
"Cl",
"Ar",
"K",
"Ca",
"Sc",
"Ti",
"V",
"Cr",
"Mn",
"Fe",
"Co",
"Ni",
"Cu",
"Zn",
"Ga",
"Ge",
"As",
"Se",
"Br",
"Kr",
"Rb",
"Sr",
"Y",
"Zr",
"Nb",
"Mo",
"Tc",
"Ru",
"Rh",
"Pd",
"Ag",
"Cd",
"In",
"Sn",
"Sb",
"Te",
"I",
"Xe",
"Cs",
"Ba",
"La",
"Ce",
"Pr",
"Nd",
"Pm",
"Sm",
"Eu",
"Gd",
"Tb",
"Dy",
"Ho",
"Er",
"Tm",
"Yb",
"Lu",
"Hf",
"Ta",
"W",
"Re",
"Os",
"Ir",
"Pt",
"Au",
"Hg",
"Tl",
"Pb",
"Bi",
"Po",
"At",
"Rn",
"Fr",
"Ra",
"Ac",
"Th",
"Pa",
"U",
"Np",
"Pu",
"Am",
"Cm",
"Bk",
"Cf",
"Es",
"Fm",
"Md",
"No",
"Lr",
"Rf",
"Db",
"Sg",
"Bh",
"Hs",
"Mt",
"Ds",
"Rg",
"Cn",
"Nh",
"Fl",
"Mc",
"Lv",
"Ts",
"Og",
]
if z < 1 or z >= len(elements):
raise Exception("Invalid atomic number")
return elements[z]
def family_symbol(i):
families = ["", "K", "L", "M", "N", "O", "P"]
if i < 1 or i >= len(families):
raise Exception("Invalid atomic number")
return families[i]
def IsGZip(pathname):
with open(pathname, "rb") as f:
(magic,) = struct.unpack("2s", f.read(2))
return magic == b"\x1f\x8b"
def IsBZip2(pathname):
with open(pathname, "rb") as f:
(magic, _, bytes) = struct.unpack("2s2s6s", f.read(10))
return magic == b"BZ" and bytes == b"\x31\x41\x59\x26\x53\x59"
class ElidReader:
def __init__(self, pathname, block_size=1024 * 1024):
if IsGZip(pathname):
raise Exception("pre EID 3.8 files are not supported")
if not IsBZip2(pathname):
raise Exception("not an ELID file")
self._pathname = pathname
with open(pathname, "rb") as self._file:
self._decompressor = bz2.BZ2Decompressor()
self._block_size = block_size
(id, version) = struct.unpack("<4si", self._read(8))
if id != b"EID2":
raise Exception("Not an ELID file.")
if version > 4:
raise Exception(f"unsupported ELID format {version}.")
self._version = version
self.dictionaries = self._read_Project()
def _read(self, size=1):
data = self._decompressor.decompress(b"", size)
while self._decompressor.needs_input:
data += self._decompressor.decompress(
self._file.read(self._block_size), size - len(data)
)
return data
def _read_bool(self):
return struct.unpack("?", self._read(1))[0]
def _read_uint8(self):
return struct.unpack("B", self._read(1))[0]
def _read_int32(self):
return struct.unpack("<i", self._read(4))[0]
def _read_uint32(self):
return struct.unpack("<I", self._read(4))[0]
def _read_string(self):
n = self._read_uint32()
return self._read(n).decode("utf-8")
def _get_unit_factor(self, unit):
if len(unit) < 2:
return 1
elif unit[0] == "M":
return 1e6
elif unit[0] == "k":
return 1e3
elif unit[0] == "m":
return 1e-3
elif unit[0] == "u" or unit[0] == "µ":
return 1e-6
elif unit[0] == "n":
return 1e-9
elif unit[0] == "p":
return 1e-12
else:
raise Exception("Unknown unit: " + unit)
def _get_value_with_unit(self, item):
if isinstance(item, dict):
return float(item["value"]) * self._get_unit_factor(item["unit"])
else:
return float(item)
def _read_tiff(self):
def xml_element_to_dict(element):
dict = {}
if len(element) == 0:
if len(element.items()) > 0:
dict[element.tag] = {"value": element.text}
for attrib, value in element.items():
dict[element.tag].update({attrib: value})
else:
dict[element.tag] = element.text
else:
dict[element.tag] = {}
for child in element:
dict[element.tag].update(xml_element_to_dict(child))
return dict
def make_metadata_dict(xml):
dict = xml_element_to_dict(ET.fromstring(xml))
return dict["FeiImage"] if dict else {}
n = self._read_uint32()
if n == 0:
return (None, None)
bytes = io.BytesIO(self._read(n))
with tifffile.TiffFile(bytes) as tiff:
data = tiff.asarray()
if len(data.shape) > 2:
# HyperSpy uses struct arrays to store RGB data
from rsciio.utils import rgb_tools
data = rgb_tools.regular_array2rgbx(data)
tags = tiff.pages[0].tags
if "FEI_TITAN" in tags:
metadata = make_metadata_dict(tags["FEI_TITAN"].value)
metadata["acquisition"]["scan"]["fieldSize"] = max(
self._get_value_with_unit(metadata["pixelHeight"]) * data.shape[0],
self._get_value_with_unit(metadata["pixelWidth"]) * data.shape[1],
)
else:
metadata = {}
return (metadata, data)
def _read_int32s(self):
n = self._read_uint32()
return [self._read_int32() for _ in range(n)]
def _read_float64(self):
return struct.unpack("<d", self._read(8))[0]
def _read_float64s(self):
n = self._read_uint32()
return [self._read_float64() for _ in range(n)]
def _read_varuint32(self):
value = 0
shift = 0
while True:
b = self._read_uint8()
value = value | ((b & 127) << shift)
if (b & 128) == 0:
break
shift += 7
return value
def _read_spectrum(self):
offset = self._read_float64()
dispersion = self._read_float64()
n = self._read_uint32()
return (offset, dispersion, [self._read_varuint32() for _ in range(n)])
def _read_uint8s(self):
n = self._read_uint32()
return [self._read_uint8() for _ in range(n)]
def _read_oxide(self):
element = self._read_uint8()
num_element = self._read_uint8()
num_oxygen = self._read_uint8()
oxide = element_symbol(element)
if num_element > 1:
oxide += str(num_element)
oxide += "O"
if num_oxygen > 1:
oxide += str(num_oxygen)
return oxide
def _read_oxides(self):
n = self._read_uint32()
return [self._read_oxide() for _ in range(n)]
def _read_element_family(self):
element = element_symbol(self._read_uint8())
family = family_symbol(self._read_uint8())
return (element, family)
def _read_element_families(self):
n = self._read_uint32()
return [self._read_element_family() for _ in range(n)]
def _read_drift_correction(self):
dc = self._read_uint8()
if dc == 1:
return "on"
elif dc == 2:
return "off"
else:
return "unknown"
def _read_detector_type(self):
dt = self._read_uint8()
if dt == 0:
return "Empty"
elif dt == 1:
return "FastSDD_C2"
elif dt == 2:
return "FastSDD_C5"
elif dt == 3:
return "FastSDD_WLS"
else:
return "Unknown"
def _read_spectrum_correction(self):
sc = self._read_uint8()
if sc == 1:
return "linearized"
elif sc == 2:
return "raw"
else:
return "unknown"
def _read_element_collection(self):
return [element_symbol(z) for z in self._read_uint8s()]
def _read_eds_metadata(self, om):
metadata = {}
metadata["high_tension"] = self._read_float64()
detector_elevation = self._read_float64()
if self._version == 0:
detector_elevation = math.radians(detector_elevation)
metadata["detector_elevation"] = detector_elevation
metadata["detector_azimuth"] = self._read_float64()
metadata["live_time"] = self._read_float64()
metadata["real_time"] = self._read_float64()
metadata["slow_peaking_time"] = self._read_float64()
metadata["fast_peaking_time"] = self._read_float64()
metadata["detector_resolution"] = self._read_float64()
metadata["instrument_id"] = self._read_string()
if self._version == 0 and "workingDistance" in om:
metadata["working_distance"] = self._get_value_with_unit(
om["workingDistance"]
)
metadata["slow_peaking_time"] = (
11.2e-6 if float(om["acquisition"]["scan"]["spotSize"]) < 4.5 else 2e-6
)
metadata["fast_peaking_time"] = 100e-9
metadata["detector_surface_area"] = 25e-6
elif self._version > 0:
metadata["optical_working_distance"] = self._read_float64()
metadata["working_distance"] = self._read_float64()
metadata["detector_surface_area"] = self._read_float64()
metadata["detector_distance"] = self._read_float64()
metadata["sample_tilt_angle"] = self._read_float64()
if self._version >= 3:
metadata["ccorrection"] = self._read_float64()
metadata["detector_type"] = self._read_detector_type()
metadata["spectrum_correction"] = self._read_spectrum_correction()
else:
metadata["ccorrection"] = 0
metadata["detector_type"] = "FastSDD_C2"
metadata["spectrum_correction"] = "unknown"
return metadata
def _read_CommonAnalysis(self, am):
(metadata, cutout) = self._read_tiff()
sum_spectrum = self._read_spectrum()
eds_metadata = self._read_eds_metadata(am)
eds_metadata["offset"] = sum_spectrum[0]
eds_metadata["dispersion"] = sum_spectrum[1]
data = sum_spectrum[2]
eds_metadata["included_elements"] = self._read_element_collection()
eds_metadata["excluded_elements"] = self._read_element_collection()
eds_metadata["background_fit_bins"] = self._read_int32s()
eds_metadata["selected_oxides"] = self._read_oxides()
eds_metadata["auto_id"] = self._read_bool()
eds_metadata["order_nr"] = self._read_int32()
eds_metadata["family_overrides"] = self._read_element_families()
if self._version >= 2:
eds_metadata["drift_correction"] = self._read_drift_correction()
else:
eds_metadata["drift_correction"] = "unknown"
if self._version >= 4:
eds_metadata["ignored_elements"] = self._read_element_collection()
else:
eds_metadata["ignored_elements"] = []
if metadata:
metadata["acquisition"]["scan"]["detectors"]["EDS"] = eds_metadata
else:
metadata = {}
metadata.update({"acquisition": {"scan": {"detectors": {}}}})
metadata["acquisition"]["scan"]["detectors"]["EDS"] = eds_metadata
return (metadata, data)
def _make_metadata_dict(self, signal_type=None, title="", datetime=None):
metadata_dict = {
"General": {
"original_filename": os.path.split(self._pathname)[1],
"title": title,
}
}
if signal_type:
metadata_dict["Signal"] = {"signal_type": signal_type}
if datetime:
metadata_dict["General"].update(
{
"date": datetime[0],
"time": datetime[1],
"time_zone": self._get_local_time_zone(),
}
)
return metadata_dict
def _get_local_time_zone(self):
return tz.tzlocal().tzname(datetime.today())
def _make_mapping(self):
return {
"acquisition.scan.detectors.EDS.detector_azimuth": (
"Acquisition_instrument.SEM.Detector.EDS.azimuth_angle",
lambda x: math.degrees(float(x)),
),
"acquisition.scan.detectors.EDS.detector_elevation": (
"Acquisition_instrument.SEM.Detector.EDS.elevation_angle",
lambda x: math.degrees(float(x)),
),
"acquisition.scan.detectors.EDS.detector_resolution": (
"Acquisition_instrument.SEM.Detector.EDS.energy_resolution_MnKa",
float,
),
"acquisition.scan.detectors.EDS.live_time": (
"Acquisition_instrument.SEM.Detector.EDS.live_time",
float,
),
"acquisition.scan.detectors.EDS.real_time": (
"Acquisition_instrument.SEM.Detector.EDS.real_time",
float,
),
"acquisition.scan.detectors.EDS.high_tension": (
"Acquisition_instrument.SEM.beam_energy",
lambda x: float(x) / 1e3,
),
"acquisition.scan.highVoltage.value": (
"Acquisition_instrument.SEM.beam_energy",
lambda x: -float(x),
),
"instrument.uniqueID": (
"Acquisition_instrument.SEM.microscope",
lambda x: x,
),
"samplePosition.x": (
"Acquisition_instrument.SEM.Stage.x",
lambda x: float(x) / 1e-3,
),
"samplePosition.y": (
"Acquisition_instrument.SEM.Stage.y",
lambda x: float(x) / 1e-3,
),
"acquisition.scan.detectors.EDS.sample_tilt_angle": (
"Acquisition_instrument.SEM.Stage.tilt_alpha",
lambda x: math.degrees(float(x)),
),
"acquisition.scan.detectors.EDS.working_distance": (
"Acquisition_instrument.SEM.working_distance",
lambda x: float(x) / 1e-3,
),
}
def _make_spot_spectrum_dict(self, om, offset, dispersion, data, title):
axes = [
{
"name": "Energy",
"offset": offset / 1e3,
"scale": dispersion / 1e3,
"size": len(data),
"units": "keV",
"navigate": False,
}
]
dict = {
"data": data,
"axes": axes,
"metadata": self._make_metadata_dict(
"EDS_SEM", title, self._get_datetime(om)
),
"original_metadata": om,
"mapping": self._make_mapping(),
}
return dict
def _get_datetime(self, metadata):
if "time" in metadata:
return metadata["time"].split("T")
else:
return None
def _make_line_spectrum_dict(self, om, offset, dispersion, data, title):
axes = [
{
"index_in_array": 0,
"name": "i",
"offset": 0,
"scale": 1,
"size": data.shape[0],
"units": "points",
"navigate": True,
},
{
"index_in_array": 1,
"name": "X-ray energy",
"offset": offset / 1e3,
"scale": dispersion / 1e3,
"size": data.shape[1],
"units": "keV",
"navigate": False,
},
]
dict = {
"data": data,
"axes": axes,
"metadata": self._make_metadata_dict(
"EDS_SEM", title, self._get_datetime(om)
),
"original_metadata": om,
"mapping": self._make_mapping(),
}
return dict
def _get_unit(self, value):
if value > 1:
return (1, "")
elif value > 1e-3:
return (1e-3, "m")
elif value > 1e-6:
return (1e-6, "µ")
elif value > 1e-9:
return (1e-9, "n")
else:
return (1, "")
def _make_map_spectrum_dict(self, om, offset, dispersion, data, title):
size = om["acquisition"]["scan"]["fieldSize"] * float(
om["acquisition"]["scan"]["scanScale"]
)
(scale, prefix) = self._get_unit(size)
unit = prefix + "m"
size = size / scale
axes = [
{
"index_in_array": 0,
"name": "y",
"offset": 0,
"scale": size / data.shape[0],
"size": data.shape[0],
"units": unit,
"navigate": True,
},
{
"index_in_array": 1,
"name": "x",
"offset": 0,
"scale": size / data.shape[1],
"size": data.shape[1],
"units": unit,
"navigate": True,
},
{
"index_in_array": 2,
"name": "X-ray energy",
"offset": offset / 1e3,
"scale": dispersion / 1e3,
"size": data.shape[2],
"units": "keV",
"navigate": False,
},
]
dict = {
"data": data,
"axes": axes,
"metadata": self._make_metadata_dict(
"EDS_SEM", title, self._get_datetime(om)
),
"original_metadata": om,
"mapping": self._make_mapping(),
}
return dict
def _make_image_dict(self, om, data, title):
if om:
(scale, prefix) = self._get_unit(
0.2 * om["acquisition"]["scan"]["fieldSize"]
)
scale_x = self._get_value_with_unit(om["pixelWidth"]) / scale
scale_y = self._get_value_with_unit(om["pixelHeight"]) / scale
unit = prefix + "m"
else:
scale_x = 1
scale_y = 1
unit = "points"
axes = [
{
"index_in_array": 0,
"name": "y",
"offset": 0,
"scale": scale_y,
"size": data.shape[0],
"units": unit,
"navigate": True,
},
{
"index_in_array": 1,
"name": "x",
"offset": 0,
"scale": scale_x,
"size": data.shape[1],
"units": unit,
"navigate": True,
},
]
dict = {
"data": data,
"axes": axes,
"metadata": self._make_metadata_dict("", title, self._get_datetime(om)),
"original_metadata": om,
"mapping": self._make_mapping(),
}
return dict
def _read_MsaAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
original_metadata = copy.deepcopy(am)
original_metadata.update(om)
return self._make_spot_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
np.array(sum_spectrum),
"{}, MSA {}".format(
label, om["acquisition"]["scan"]["detectors"]["EDS"]["order_nr"]
),
)
def _read_SpotAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
x = self._read_float64()
y = self._read_float64()
original_metadata = copy.deepcopy(am)
original_metadata["acquisition"]["scan"]["detectors"]["EDS"] = om[
"acquisition"
]["scan"]["detectors"]["EDS"]
original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["position"] = {
"x": x,
"y": y,
}
return self._make_spot_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
np.array(sum_spectrum),
"{}, Spot {}".format(
label, om["acquisition"]["scan"]["detectors"]["EDS"]["order_nr"]
),
)
def _read_LineScanAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
x1 = self._read_float64()
y1 = self._read_float64()
x2 = self._read_float64()
y2 = self._read_float64()
size = self._read_uint32()
bins = self._read_uint32()
offset = self._read_float64()
dispersion = self._read_float64()
eds_metadata = self._read_eds_metadata(am)
eds_metadata["live_time"] = om["acquisition"]["scan"]["detectors"]["EDS"][
"live_time"
]
eds_metadata["real_time"] = om["acquisition"]["scan"]["detectors"]["EDS"][
"real_time"
]
eds_metadata["begin"] = {"x": x1, "y": y1}
eds_metadata["end"] = {"x": x2, "y": y2}
eds_metadata["offset"] = offset
eds_metadata["dispersion"] = dispersion
has_variable_real_time = self._read_bool()
has_variable_live_time = self._read_bool()
data = np.empty([size, bins], dtype=np.uint32)
for i in range(size):
for bin in range(bins):
data[i, bin] = self._read_varuint32()
if has_variable_real_time:
eds_metadata["real_time_values"] = [
self._read_float64() for _ in range(size)
]
else:
eds_metadata["real_time_values"] = [self._read_float64()] * size
if has_variable_live_time:
eds_metadata["live_time_values"] = [
self._read_float64() for _ in range(size)
]
else:
eds_metadata["live_time_values"] = [self._read_float64()] * size
eds_metadata["high_accuracy_quantification"] = self._read_bool()
original_metadata = copy.deepcopy(am)
original_metadata["acquisition"]["scan"]["detectors"]["EDS"] = eds_metadata
return self._make_line_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
data,
"{}, Line {}".format(
label, om["acquisition"]["scan"]["detectors"]["EDS"]["order_nr"]
),
)
def _read_MapAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
left = self._read_float64()
top = self._read_float64()
right = self._read_float64()
bottom = self._read_float64()
color_intensities = self._read_float64s()
width = self._read_uint32()
height = self._read_uint32()
bins = self._read_uint32()
offset = self._read_float64()
dispersion = self._read_float64()
original_metadata = copy.deepcopy(am)
eds_metadata = self._read_eds_metadata(am)
eds_metadata["live_time"] = om["acquisition"]["scan"]["detectors"]["EDS"][
"live_time"
]
eds_metadata["real_time"] = om["acquisition"]["scan"]["detectors"]["EDS"][
"real_time"
]
original_metadata["acquisition"]["scan"]["detectors"]["EDS"] = eds_metadata
has_variable_real_time = self._read_bool()
has_variable_live_time = self._read_bool()
data = np.empty([height, width, bins], dtype=np.uint32)
for y in range(height):
for x in range(width):
for bin in range(bins):
data[y, x, bin] = self._read_varuint32()
if has_variable_real_time:
real_time_values = np.empty([height, width], dtype=float)
for y in range(height):
for x in range(width):
real_time_values[y, x] = self._read_float64()
eds_metadata["real_time_values"] = real_time_values
else:
eds_metadata["real_time_values"] = np.full(
[height, width], self._read_float64()
)
if has_variable_live_time:
live_time_values = np.empty([height, width], dtype=float)
for y in range(height):
for x in range(width):
live_time_values[y, x] = self._read_float64()
eds_metadata["live_time_values"] = live_time_values
else:
eds_metadata["live_time_values"] = np.full(
[height, width], self._read_float64()
)
return self._make_map_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
data,
"{}, Map {}".format(
label, om["acquisition"]["scan"]["detectors"]["EDS"]["order_nr"]
),
)
def _read_DifferenceAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
minuend = self._read_uint32()
subtrahend = self._read_uint32()
original_metadata = copy.deepcopy(am)
original_metadata["acquisition"]["scan"]["detectors"]["EDS"] = om[
"acquisition"
]["scan"]["detectors"]["EDS"]
return self._make_spot_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
np.array(sum_spectrum),
"{}, Difference {} - {}".format(label, minuend, subtrahend),
)
def _read_RegionAnalysis(self, label, am):
(om, sum_spectrum) = self._read_CommonAnalysis(am)
left = self._read_float64()
top = self._read_float64()
right = self._read_float64()
bottom = self._read_float64()
original_metadata = copy.deepcopy(am)
original_metadata["acquisition"]["scan"]["detectors"]["EDS"] = om[
"acquisition"
]["scan"]["detectors"]["EDS"]
original_metadata["acquisition"]["scan"]["detectors"]["EDS"]["rectangle"] = {
"left": left,
"top": top,
"right": right,
"bottom": bottom,
}
return self._make_spot_spectrum_dict(
original_metadata,
om["acquisition"]["scan"]["detectors"]["EDS"]["offset"],
om["acquisition"]["scan"]["detectors"]["EDS"]["dispersion"],
np.array(sum_spectrum),
"{}, Region {}".format(
label, om["acquisition"]["scan"]["detectors"]["EDS"]["order_nr"]
),
)
def _read_ConstructiveAnalysisSource(self):
analysis_index = self._read_uint32()
weight_factor = self._read_float64()
return (analysis_index, weight_factor)
def _read_ConstructiveAnalysisSources(self):
n = self._read_uint32()
return [self._read_ConstructiveAnalysisSource() for _ in range(n)]
def _read_ConstructiveAnalysis(self, label, am):
self._read_CommonAnalysis(am)
description = self._read_string()
sources = self._read_ConstructiveAnalysisSources()
def _read_ConstructiveAnalyses(self):
return self._read_Analyses("", {})
def _read_Analysis(self, label, am):
type = self._read_uint8()
if type == 1:
return self._read_MsaAnalysis(label, am)
elif type == 2:
return self._read_SpotAnalysis(label, am)
elif type == 3:
return self._read_LineScanAnalysis(label, am)
elif type == 4:
return self._read_MapAnalysis(label, am)
elif type == 5:
return self._read_DifferenceAnalysis(label, am)
elif type == 6:
return self._read_RegionAnalysis(label, am)
elif type == 7:
return self._read_ConstructiveAnalysis(label, am)
else:
raise Exception("Unknown Analysis type")
def _read_Analyses(self, label, metadata):
n = self._read_uint32()
return [self._read_Analysis(label, metadata) for _ in range(n)]
def _read_Image(self):
tiff = self._read_tiff()
label = self._read_string()
dictionaries = []
if tiff:
dictionaries.append(self._make_image_dict(tiff[0], tiff[1], label))
dictionaries.extend(self._read_Analyses(label, tiff[0]))
return dictionaries
def _read_Images(self):
n = self._read_uint32()
dictionaries = []
for _ in range(n):
dictionaries.extend(self._read_Image())
return dictionaries
def _read_Project(self):
dictionaries = self._read_Images()
if self._version >= 1:
self._read_Analyses("", {})
self._read_ConstructiveAnalyses()
return [dict for dict in dictionaries if dict]
def file_reader(filename, lazy=False, **kwds):
"""
Read a Phenom ``.elid`` file from the software Element Identification (>v3.8.0)
used by the Thermo Fisher Scientific Phenom desktop SEMs.
Parameters
----------
%s
%s
%s
"""
reader = ElidReader(filename)
return reader.dictionaries
file_reader.__doc__ %= (FILENAME_DOC, LAZY_DOC, RETURNS_DOC) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/phenom/_api.py | 0.443118 | 0.310315 | _api.py | pypi |
import numpy as np
from dask.array import Array
from rsciio.utils.array import get_numpy_kwargs
rgba8 = np.dtype({"names": ["R", "G", "B", "A"], "formats": ["u1", "u1", "u1", "u1"]})
rgb8 = np.dtype({"names": ["R", "G", "B"], "formats": ["u1", "u1", "u1"]})
rgba16 = np.dtype({"names": ["R", "G", "B", "A"], "formats": ["u2", "u2", "u2", "u2"]})
rgb16 = np.dtype({"names": ["R", "G", "B"], "formats": ["u2", "u2", "u2"]})
rgb_dtypes = {"rgb8": rgb8, "rgb16": rgb16, "rgba8": rgba8, "rgba16": rgba16}
def is_rgba(array):
if array.dtype in (rgba8, rgba16):
return True
else:
return False
def is_rgb(array):
if array.dtype in (rgb8, rgb16):
return True
else:
return False
def is_rgbx(array):
if is_rgb(array) or is_rgba(array):
return True
else:
return False
def rgbx2regular_array(data, plot_friendly=False):
"""Transforms a RGBx array into a standard one
Parameters
----------
data : numpy array of RGBx dtype
plot_friendly : bool
If True change the dtype to float when dtype is not uint8 and
normalize the array so that it is ready to be plotted by matplotlib.
"""
# Make sure that the data is contiguous
if isinstance(data, Array):
from dask.diagnostics import ProgressBar
# an expensive thing, but nothing to be done for now...
with ProgressBar():
data = data.compute()
if data.flags["C_CONTIGUOUS"] is False:
if np.ma.is_masked(data):
data = data.copy(order="C")
else:
data = np.ascontiguousarray(data, **get_numpy_kwargs(data))
if is_rgba(data) is True:
dt = data.dtype.fields["B"][0]
data = data.view((dt, 4))
elif is_rgb(data) is True:
dt = data.dtype.fields["B"][0]
data = data.view((dt, 3))
else:
return data
if plot_friendly is True and data.dtype == np.dtype("uint16"):
data = data.astype("float")
data /= 2**16 - 1
return data
def regular_array2rgbx(data):
# Make sure that the data is contiguous
if data.flags["C_CONTIGUOUS"] is False:
if np.ma.is_masked(data):
data = data.copy(order="C")
else:
data = np.ascontiguousarray(data, **get_numpy_kwargs(data))
if data.shape[-1] == 3:
names = rgb8.names
elif data.shape[-1] == 4:
names = rgba8.names
else:
raise ValueError("The last dimension size of the array must be 3 or 4")
if data.dtype in (np.dtype("u1"), np.dtype("u2")):
formats = [data.dtype] * len(names)
else:
raise ValueError("The data dtype must be uint16 or uint8")
return data.view(np.dtype({"names": names, "formats": formats})).reshape(
data.shape[:-1]
) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/utils/rgb_tools.py | 0.746693 | 0.452052 | rgb_tools.py | pypi |
import datetime
from dateutil import tz, parser
import logging
import numpy as np
_logger = logging.getLogger(__name__)
def serial_date_to_ISO_format(serial):
"""
Convert serial_date to a tuple of string (date, time, time_zone) in ISO
format. By default, the serial date is converted in local time zone.
"""
dt_utc = serial_date_to_datetime(serial)
dt_local = dt_utc.astimezone(tz.tzlocal())
return dt_local.date().isoformat(), dt_local.time().isoformat(), dt_local.tzname()
def ISO_format_to_serial_date(date, time, timezone="UTC"):
"""Convert ISO format to a serial date."""
if timezone is None or timezone == "Coordinated Universal Time":
timezone = "UTC"
dt = parser.parse("%sT%s" % (date, time)).replace(tzinfo=tz.gettz(timezone))
return datetime_to_serial_date(dt)
def datetime_to_serial_date(dt):
"""Convert datetime.datetime object to a serial date."""
if dt.tzname() is None:
dt = dt.replace(tzinfo=tz.tzutc())
origin = datetime.datetime(1899, 12, 30, tzinfo=tz.tzutc())
delta = dt - origin
return float(delta.days) + (float(delta.seconds) / 86400.0)
def serial_date_to_datetime(serial):
"""Convert serial date to a datetime.datetime object."""
# Excel date&time format
origin = datetime.datetime(1899, 12, 30, tzinfo=tz.tzutc())
secs = (serial % 1.0) * 86400
delta = datetime.timedelta(int(serial), secs)
return origin + delta
def get_date_time_from_metadata(metadata, formatting="ISO"):
"""
Get the date and time from a metadata tree.
Parameters
----------
metadata : metadata dict
formatting : string, ('ISO', 'datetime', 'datetime64')
Default: 'ISO'. This parameter set the formatting of the date,
and the time, it can be ISO 8601 string, datetime.datetime
or a numpy.datetime64 object. In the later case, the time zone
is not supported.
Returns
-------
string, datetime.datetime or numpy.datetime64 object
"""
md_gen = metadata["General"]
date, time = md_gen.get("date"), md_gen.get("time")
if date and time:
dt = parser.parse(f"{date}T{time}")
time_zone = md_gen.get("time_zone")
if time_zone:
dt = dt.replace(tzinfo=tz.gettz(time_zone))
if dt.tzinfo is None:
# time_zone metadata must be offset string
dt = parser.parse(f"{date}T{time}{time_zone}")
elif not date and time:
dt = parser.parse(f"{time}").time()
elif date and not time:
dt = parser.parse(f"{date}").date()
else:
return None
if formatting == "ISO":
res = dt.isoformat()
elif formatting == "datetime":
res = dt
# numpy.datetime64 doesn't support time zone
elif formatting == "datetime64":
res = np.datetime64(f"{date}T{time}")
return res
def msfiletime_to_unix(msfiletime):
"""Convert microsoft's filetime to unix datetime used in python
built-in datetime
Parameters
----------
msfiletime: 64-bit integer representing number of 10 microsecond ticks
from 1601
Returns
-------
datetime.datetime object"""
return datetime.datetime(1601, 1, 1) + datetime.timedelta(
microseconds=msfiletime / 10
) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/utils/date_time_tools.py | 0.883412 | 0.298907 | date_time_tools.py | pypi |
from packaging.version import Version
import warnings
import numpy as np
import skimage
from skimage.exposure.exposure import intensity_range, _output_dtype
def rescale_intensity(image, in_range="image", out_range="dtype"):
"""Return image after stretching or shrinking its intensity levels.
The desired intensity range of the input and output, `in_range` and
`out_range` respectively, are used to stretch or shrink the intensity range
of the input image. See examples below.
Parameters
----------
image : array
Image array.
in_range, out_range : str or 2-tuple, optional
Min and max intensity values of input and output image.
The possible values for this parameter are enumerated below.
'image'
Use image min/max as the intensity range.
'dtype'
Use min/max of the image's dtype as the intensity range.
dtype-name
Use intensity range based on desired `dtype`. Must be valid key
in `DTYPE_RANGE`.
2-tuple
Use `range_values` as explicit min/max intensities.
Returns
-------
out : array
Image array after rescaling its intensity. This image is the same dtype
as the input image.
Notes
-----
.. versionchanged:: 0.17
The dtype of the output array has changed to match the input dtype, or
float if the output range is specified by a pair of floats.
See Also
--------
equalize_hist
Examples
--------
By default, the min/max intensities of the input image are stretched to
the limits allowed by the image's dtype, since `in_range` defaults to
'image' and `out_range` defaults to 'dtype':
>>> image = np.array([51, 102, 153], dtype=np.uint8)
>>> rescale_intensity(image)
array([ 0, 127, 255], dtype=uint8)
It's easy to accidentally convert an image dtype from uint8 to float:
>>> 1.0 * image
array([ 51., 102., 153.])
Use `rescale_intensity` to rescale to the proper range for float dtypes:
>>> image_float = 1.0 * image
>>> rescale_intensity(image_float)
array([0. , 0.5, 1. ])
To maintain the low contrast of the original, use the `in_range` parameter:
>>> rescale_intensity(image_float, in_range=(0, 255))
array([0.2, 0.4, 0.6])
If the min/max value of `in_range` is more/less than the min/max image
intensity, then the intensity levels are clipped:
>>> rescale_intensity(image_float, in_range=(0, 102))
array([0.5, 1. , 1. ])
If you have an image with signed integers but want to rescale the image to
just the positive range, use the `out_range` parameter. In that case, the
output dtype will be float:
>>> image = np.array([-10, 0, 10], dtype=np.int8)
>>> rescale_intensity(image, out_range=(0, 127))
array([ 0. , 63.5, 127. ])
To get the desired range with a specific dtype, use ``.astype()``:
>>> rescale_intensity(image, out_range=(0, 127)).astype(np.int8)
array([ 0, 63, 127], dtype=int8)
If the input image is constant, the output will be clipped directly to the
output range:
>>> image = np.array([130, 130, 130], dtype=np.int32)
>>> rescale_intensity(image, out_range=(0, 127)).astype(np.int32)
array([127, 127, 127], dtype=int32)
"""
args = ()
if Version(skimage.__version__) >= Version("0.19.0"):
args = (image.dtype,)
if out_range in ["dtype", "image"]:
out_dtype = _output_dtype(image.dtype.type, *args)
else:
out_dtype = _output_dtype(out_range, *args)
imin, imax = map(float, intensity_range(image, in_range))
omin, omax = map(
float, intensity_range(image, out_range, clip_negative=(imin >= 0))
)
if np.any(np.isnan([imin, imax, omin, omax])):
warnings.warn(
"One or more intensity levels are NaN. Rescaling will broadcast "
"NaN to the full image. Provide intensity levels yourself to "
"avoid this. E.g. with np.nanmin(image), np.nanmax(image).",
stacklevel=2,
)
image = np.clip(image, imin, imax)
if imin != imax:
image = (image - imin) / (imax - imin)
return (image * (omax - omin) + omin).astype(dtype=out_dtype)
else:
return np.clip(image, omin, omax).astype(out_dtype) | /rosettasciio-0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl/rsciio/utils/skimage_exposure.py | 0.948632 | 0.71408 | skimage_exposure.py | pypi |
# rosewater
[](https://badge.fury.io/py/rosewater)
**rosewater** assigns genes to (super-) enhancer output from [ROSE](https://bitbucket.org/young_computation/rose/src/master/) in an expression-aware manner. It allows users to set a TPM threshold to filter genes that are not expressed on a sample-by-sample basis.
## Installation
`rosewater` can be installed via pip. For use, it **requires `bedtools` be available on your PATH**.
```pip install rosewater```
## Usage
`rosewater` is fairly simple to use. It requires an annotation GTF file, a TSV file of TPMs with the gene name column named 'gene' (these should match the 'gene_name' attributes in the annotation GTF), the name of the sample column in the TPM file, and an output file from [ROSE](https://bitbucket.org/young_computation/rose/src/master/). Optionally, users can set a TPM threshold (set to 5 by default) for filtering out lowly/non-expressed genes prior to assignment.
```
Usage: rosewater [OPTIONS]
rosewater assigns genes to ROSE output in an expression-aware manner.
Options:
-a, --annotation PATH Path to annotation GTF file. [required]
-s, --sample TEXT Sample name that should match a column in the
TPM file. [required]
-e, --enh_file PATH Output from ROSE ending with
'ENHANCER_TO_GENE.txt'. [required]
-t, --tpm_file PATH A file containing a matrix of TPMs with genes as
rows and samples as columns. The gene label
column should be named 'gene'. [required]
-th, --tpm_threshold FLOAT The minimum TPM to retain genes for assignment.
[default: 5]
-o, --output_dir PATH The output directory. [default:
./EnhancerGeneAssignments]
--version Show the version and exit.
-h, --help Show this message and exit.
```
## Output
Two output files will be generated, named after the ROSE enhancer input file appended with either `.rosewater.GeneAssignment.log` or `.rosewater.GeneAssignment.bed`. The **log file** will contain useful stats such as how many TSSes are filtered by the TPM threshold, how many TSSes overlap each enhancer, the average enhancer size, and how many assignments change from the original ROSE assignments.
The **BED-like file** will contain the assignments for each enhancer. Two assignments are made for each enhancer - one utilizing all TSSes in the annotation file that meet the TPM threshold and another utilizing only the protein-coding TSSes. These assignments are the last 4 columns of the file. The additional columns are fairly self-explanatory. In short, they contain the overlapping TSSes, the closest TSS using all transcripts that meet the TPM threshold, the closest TSS using only protein-coding transcripts that meet the TPM threshold, and the TPMs for each of those.
## Assignment Logic
The original ROSE gene mapper just assigns the TSS that is closest to the center of the enhancer. `rosewater` takes a more sophisticated (and therefore complicated approach):
- If the enhancer overlaps no TSSes for a gene that meets the TPM threshold:
- The "final_allgene_assignment" will be set to the gene that meets the TPM threshold for the closest TSS while "final_proteincoding_assignment" will be set to the gene that meets the TPM threshold for the closest 'protein_coding' TSS.
- If the enhancer overlaps a single TSS for a gene that meets the TPM threshold:
- If the 'gene_type' of the gene is `protein_coding`, the "final_allgene_assignment" and "final_proteincoding_assignment" will both be set to that gene.
- If the 'gene_type' of the gene is **not** `protein_coding`, the "final_allgene_assignment" will be set to that gene while the "final_proteincoding_assignment" will be set to the gene for the closest 'protein_coding' TSS.
- If the enhancer overlaps two or more TSS for a gene that meets the TPM threshold:
- If the 'gene_type' of the most highly-expressed gene is `protein_coding`, the "final_allgene_assignment" and "final_proteincoding_assignment" will both be set to that gene.
- If the 'gene_type' of the most highly-expressed gene is **not** `protein_coding`, the "final_allgene_assignment" will be set to that gene while the "final_proteincoding_assignment" will be set to the most highly-expressed overlapping 'protein_coding' gene. If there are no overlapping TSSes for 'protein_coding' genes, the "final_proteincoding_assignment" will be set to the gene for the closest 'protein_coding' TSS.
Users are free to use whichever assignment they feel is most appropriate for their use case.
## Known Issues
Users may get a warning like `RuntimeWarning: line buffering (buffering=1) isn't supported in binary mode` depending on their version of python. This can be safely ignored. It stems from `pybedtools` and should be fixed in their next release.
## Contributing
Feel free to submit a [pull request](https://github.com/j-andrews7/rosewater/pulls) or open an [issue](https://github.com/j-andrews7/rosewater/issues) if you have an idea to enhance this tool.
## License
`rosewater` is available under the [GNU-GPLv3 license](https://github.com/j-andrews7/rosewater/blob/master/LICENSE). It is provided as-is, with no warranty or guarantees. | /rosewater-0.1.1.tar.gz/rosewater-0.1.1/README.md | 0.698535 | 0.983629 | README.md | pypi |
from pathlib import Path
import pandas as pd
import pybedtools as pyb
from pybedtools.featurefuncs import TSS
import click
def parse_annotation(anno_gtf, out_dir):
# Get base filename.
base = Path(anno_gtf).stem
anno = pyb.BedTool(anno_gtf)
all_tss = anno.filter(lambda b: b[2] == "transcript").each(
TSS, upstream=0, downstream=1).saveas()
pc_tss = all_tss.filter(
lambda x: x.attrs["transcript_type"] == "protein_coding").saveas()
return all_tss, pc_tss
def filter_annotations(sample, tpm_threshold, tpm_file, all_tss, pc_tss):
# Get and filter TPMs for sample.
tpms = pd.read_table(tpm_file)
tpms = dict(zip(tpms["gene"], tpms[sample]))
filt_tpms = [key for (key, value) in tpms.items()
if value >= tpm_threshold]
filt_all_tss = all_tss.filter(
lambda x: x.attrs['gene_name'] in filt_tpms).sort().saveas()
filt_pc_tss = pc_tss.filter(
lambda x: x.attrs['gene_name'] in filt_tpms).sort().saveas()
return tpms, filt_all_tss, filt_pc_tss
def gene_intersects(enh_file, filt_all_tss, filt_pc_tss):
enh_df = pd.read_table(enh_file)
enh_df.drop(enh_df.columns[0], axis=1, inplace=True)
enhancers = enh_df.to_string(header=False, index=False, columns=[
"CHROM", "START", "STOP", "CLOSEST_GENE", "enhancerRank"])
enhancers = pyb.BedTool(enhancers, from_string=True).sort().saveas()
ovlps = enhancers.intersect(filt_all_tss, loj=True).each(parse_ovlp_gene_info).merge(c=[4, 5, 15, 16, 17],
o=["distinct", "distinct", "distinct", "collapse", "distinct"]).saveas()
return ovlps
def parse_ovlp_gene_info(feature):
# If TSS overlaps enhancer, get relevant transcript and gene info.
fields = feature.fields
info = fields[-1]
symb = "."
t_id = "."
ttype = "."
if info != ".":
symb = info.strip().split(";")[4]
symb = symb.split()[1]
symb = symb.strip('"')
t_id = info.strip().split(";")[1]
t_id = t_id.split()[1]
t_id = t_id.strip('"')
ttype = info.strip().split(";")[5]
ttype = ttype.split()[1]
ttype = ttype.strip('"')
fields.extend([t_id, ttype, symb])
interval = pyb.cbedtools.create_interval_from_list(fields)
return interval
def get_closest_genes(ovlps, filt_all_tss, filt_pc_tss):
closest_genes = ovlps.closest(filt_all_tss, d=True, t="first").closest(filt_pc_tss, d=True, t="first").each(
parse_closest_gene_info).cut([0, 1, 2, 4, 3, 5, 6, 7, 28, 29, 17, 30, 27]).saveas()
return closest_genes
def parse_closest_gene_info(feature):
# For nearest all and protein coding TSS, get gene type and symbol.
fields = feature.fields
all_info = fields[16]
pc_info = fields[-2]
all_ttype = all_info.strip().split(";")[5]
all_ttype = all_ttype.split()[1]
all_ttype = all_ttype.strip('"')
all_symb = all_info.strip().split(";")[4]
all_symb = all_symb.split()[1]
all_symb = all_symb.strip('"')
pc_symb = pc_info.strip().split(";")[4]
pc_symb = pc_symb.split()[1]
pc_symb = pc_symb.strip('"')
fields.extend([all_symb, all_ttype, pc_symb])
interval = pyb.cbedtools.create_interval_from_list(fields)
return interval
def assign_genes(enh_bedtools, tpms, transcript_dict, genetype_dict, out_file, log_file):
# For logging.
total_enh = 0
no_tss = 0
one_tss = 0
two_tss = 0
three_or_more_tss = 0
all_diff_from_rose = 0
pc_diff_from_rose = 0
# Parse enhancer and get TPM, transcript_type, and gene_type values.
for enh in enh_bedtools:
total_enh += 1
pos = "\t".join(enh.fields[0:4])
rose_assignment = transcript_dict[enh.fields[4]]
rose_gtype = genetype_dict[rose_assignment]
if rose_assignment not in tpms.keys():
rose_tpm = "NA"
else:
rose_tpm = tpms[rose_assignment]
ovlp_tss = enh.fields[5]
ovlp_ttypes = enh.fields[6]
ovlp_genes = enh.fields[7].split(",")
ovlp_gtypes = "."
ovlp_tpms = "."
closest_tss = enh.fields[8]
closest_tss_ttype = enh.fields[9]
closest_tss_gtype = genetype_dict[closest_tss]
if closest_tss not in tpms.keys():
closest_tss_tpm = "NA"
else:
closest_tss_tpm = tpms[closest_tss]
closest_tss_distance = enh.fields[10]
closest_pc_tss = enh.fields[11]
if closest_pc_tss not in tpms.keys():
closest_pc_tss_tpm = "NA"
else:
closest_pc_tss_tpm = tpms[closest_pc_tss]
closest_pc_tss_distance = enh.fields[-1]
if ovlp_genes[0] != ".":
ovlp_gtypes = [genetype_dict[x] for x in ovlp_genes]
ovlp_tpms = [tpms[x] for x in ovlp_genes]
# Check for no overlapping TSSs.
if ovlp_genes[0] == ".":
no_tss += 1
final_pc_assignment = closest_pc_tss
final_pc_assignment_tpm = closest_pc_tss_tpm
final_all_assignment = closest_tss
final_all_assignment_gtype = closest_tss_gtype
final_all_assignment_tpm = closest_tss_tpm
# If only one TSS is overlapped and it's protein coding, assignment will be the same.
elif len(ovlp_genes) == 1 and ovlp_gtypes[0] != ".":
one_tss += 1
final_all_assignment = ovlp_genes[0]
final_all_assignment_gtype = ovlp_gtypes[0]
final_all_assignment_tpm = ovlp_tpms[0]
if ovlp_gtypes[0] == "protein_coding":
final_pc_assignment = ovlp_genes[0]
final_pc_assignment_tpm = ovlp_tpms[0]
else:
final_pc_assignment = closest_pc_tss
final_pc_assignment_tpm = closest_pc_tss_tpm
elif len(ovlp_genes) > 1:
if len(ovlp_genes) == 2:
two_tss += 1
elif len(ovlp_genes) > 2:
three_or_more_tss += 1
# Get tpms, find max, get associated gene and change assignment if necessary.
index_max = max(range(len(ovlp_tpms)), key=ovlp_tpms.__getitem__)
highest_tpm_ovlp = ovlp_genes[index_max]
highest_tpm_gtype = ovlp_gtypes[index_max]
if highest_tpm_gtype == "protein_coding":
final_pc_assignment = highest_tpm_ovlp
final_pc_assignment_tpm = max(ovlp_tpms)
final_all_assignment = highest_tpm_ovlp
final_all_assignment_gtype = highest_tpm_gtype
final_all_assignment_tpm = max(ovlp_tpms)
elif highest_tpm_gtype != "protein_coding":
# Get max protein coding gene.
pc_gtypes_index = [idx for idx, element in enumerate(
ovlp_gtypes) if element == "protein_coding"]
pc_ovlp_tpms = [ovlp_tpms[x] for x in pc_gtypes_index]
pc_gene = [ovlp_genes[x] for x in pc_gtypes_index]
pc_index_max = max(range(len(pc_ovlp_tpms)),
key=pc_ovlp_tpms.__getitem__)
highest_pc_tpm = pc_ovlp_tpms[pc_index_max]
highest_pc_tpm_ovlp = pc_gene[pc_index_max]
final_all_assignment = highest_tpm_ovlp
final_all_assignment_gtype = highest_tpm_gtype
final_all_assignment_tpm = max(ovlp_tpms)
if highest_pc_tpm > closest_pc_tss_tpm:
final_pc_assignment = highest_pc_tpm_ovlp
final_pc_assignment_tpm = highest_pc_tpm
else:
final_pc_assignment = closest_pc_tss
final_pc_assignment_tpm = closest_pc_tss_tpm
# Construct and print new line.
print("\t".join([pos, rose_assignment, rose_gtype, str(rose_tpm),
ovlp_tss, ovlp_ttypes, ",".join(ovlp_genes), ",".join(
ovlp_gtypes), ",".join([str(x) for x in ovlp_tpms]),
closest_tss, closest_tss_ttype, closest_tss_gtype, str(
closest_tss_tpm), str(closest_tss_distance),
closest_pc_tss, str(closest_pc_tss_tpm), str(
closest_pc_tss_distance),
final_all_assignment, final_all_assignment_gtype, str(final_all_assignment_tpm),
final_pc_assignment, str(final_pc_assignment_tpm)]),
file=out_file)
if final_all_assignment != rose_assignment:
all_diff_from_rose += 1
if final_pc_assignment != rose_assignment:
pc_diff_from_rose += 1
# Print stats to log.
print("Total enhancers: " + str(total_enh), file=log_file)
print("Average enhancer size (bp): " + str(enh_bedtools.total_coverage() /
enh_bedtools.count()), file=log_file)
print("Enhancers overlapping no TSS: " + str(no_tss) + ", " +
str(100 * (no_tss / total_enh)) + "% of total enhancers", file=log_file)
print("Enhancers overlapping TSSes from one gene: " + str(one_tss) + ", " +
str(100 * (one_tss / total_enh)) + "% of total enhancers", file=log_file)
print("Enhancers overlapping TSSes from two genes: " + str(two_tss) + ", " +
str(100 * (two_tss / total_enh)) + "% of total enhancers", file=log_file)
print("Enhancers overlapping TSSes from three or more genes: " + str(three_or_more_tss) + ", " + str(100 * (three_or_more_tss / total_enh)) + "% of total enhancers",
file=log_file)
print("Enhancers using all TSSes where assignment differed from ROSE: " + str(all_diff_from_rose) + ", " +
str(100 * (all_diff_from_rose / total_enh)) + "% of total enhancers", file=log_file)
print("Enhancers using only protein-coding TSSes where assignment differed from ROSE: " + str(pc_diff_from_rose) + ", " +
str(100 * (pc_diff_from_rose / total_enh)) + "% of total enhancers", file=log_file)
@click.command(context_settings=dict(help_option_names=['-h', '--help']))
@click.option("-a", "--annotation", help="Path to annotation GTF file.", required=True, type=click.Path())
@click.option("-s", "--sample", help="Sample name that should match a column in the TPM file.", required=True, type=str)
@click.option("-e", "--enh_file", help="Output from ROSE ending with 'ENHANCER_TO_GENE.txt'.", required=True, type=click.Path())
@click.option("-t", "--tpm_file", help="A file containing a matrix of TPMs with genes as rows and samples as columns. The gene label column should be named 'gene'.",
required=True, type=click.Path())
@click.option("-th", "--tpm_threshold", default=5, help="The minimum TPM to retain genes for assignment.", show_default=True, type=float)
@click.option("-o", "--output_dir", default="./EnhancerGeneAssignments", help="The output directory.", show_default=True, type=click.Path())
@click.version_option()
def rosewater(annotation, sample, enh_file, tpm_file, tpm_threshold, output_dir):
"""rosewater assigns genes to ROSE output in an expression-aware manner."""
# Make output directory and open file for logging.
Path(output_dir).mkdir(parents=True, exist_ok=True)
base = Path(enh_file).stem
log_file = open(
Path(output_dir, base + ".rosewater.GeneAssignment.log"), "w")
print("Annotation: " + annotation, file=log_file)
print("Sample: " + sample, file=log_file)
print("ROSE file: " + enh_file, file=log_file)
print("TPM file: " + tpm_file, file=log_file)
print("TPM threshold: " + str(tpm_threshold), file=log_file)
print("Output directory: " + output_dir + "\n", file=log_file)
# Get all TSSes and only protein coding ones.
all_tss, pc_tss = parse_annotation(annotation, output_dir)
print("Total TSSes: " + str(len(all_tss)), file=log_file)
print("Protein coding TSSes: " + str(len(pc_tss)), file=log_file)
# Filter them to get only genes that meet the TPM threshold.
tpms, filt_all_tss, filt_pc_tss = filter_annotations(
sample, tpm_threshold, tpm_file, all_tss, pc_tss)
print("TSSes that met TPM threshold (" +
str(tpm_threshold) + "): " + str(len(filt_all_tss)), file=log_file)
print("Protein coding TSSes that met TPM threshold (" +
str(tpm_threshold) + "): " + str(len(filt_pc_tss)) + "\n", file=log_file)
# Make dicts of transcript IDs and gene symbols and gene types.
transcript_dict = {transcript.attrs["transcript_id"]: transcript.attrs["gene_name"] for transcript in all_tss}
genetype_dict = {transcript.attrs["gene_name"]: transcript.attrs["gene_type"] for transcript in all_tss}
# Get overlapping TSSes.
ovlps = gene_intersects(enh_file, filt_all_tss, filt_pc_tss)
# Get closest genes with all TSSes and only protein-coding ones.
closest_genes = get_closest_genes(ovlps, filt_all_tss, filt_pc_tss)
# Collect and print output for each SE.
header = ["chrom", "start", "stop", "enhancerRank", "ROSE_assignment", "ROSE_assignment_genetype", "ROSE_assignment_TPM",
"overlapping_TSS", "overlapping_TSS_transcripttype", "overlapping_genes", "overlapping_genetypes", "overlapping_genes_TPMs",
"closest_TSS", "closest_TSS_transcripttype", "closest_TSS_genetype", "closest_TSS_gene_TPM", "closest_TSS_distance",
"closest_proteincoding_TSS", "closest_proteincoding_TSS_gene_TPM", "closest_proteincoding_TSS_distance",
"final_allgene_assignment", "final_allgene_assignment_genetype","final_allgene_assignment_TPM", "final_proteincoding_assignment", "final_proteincoding_assignment_TPM"]
out_file = open(
Path(output_dir, base + ".rosewater.GeneAssignment.bed"), "w")
print("\t".join(header), file=out_file)
assign_genes(closest_genes, tpms, transcript_dict,
genetype_dict, out_file, log_file)
out_file.close()
log_file.close() | /rosewater-0.1.1.tar.gz/rosewater-0.1.1/rosewater.py | 0.553747 | 0.527317 | rosewater.py | pypi |
import matplotlib.pyplot as graph
__version__ = '1.2021.10.02' # Major.YYYY.MM.DD
import numpy as np
colors_538 = [
'#30a2da',
'#fc4f30',
'#e5ae38',
'#6d904f',
'#8b8b8b',
]
def plot_roc_curve(
prediction_probability,
true,
label='',
plot_curve_only=False,
estimate_intervals=False,
show_graph=False
):
"""
ROC Curves
:param prediction_probability:
:param true:
:param label:
:param plot_curve_only:
:param estimate_intervals: estimates the 95% interval for the AUC
:param show_graph:
:return:
"""
from sklearn.metrics import roc_curve, roc_auc_score
from sklearn.utils import resample
fpr, tpr, thres = roc_curve(true, prediction_probability)
auc = roc_auc_score(true, prediction_probability)
plot_label = label if label == '' else label + ' '
plot_label = f'{plot_label}AUC = {auc:.5f}'
if estimate_intervals:
auc_dist = []
for seed in range(1000):
true_resample, prediction_probability_resample = resample(true, prediction_probability)
auc_dist.append(roc_auc_score(true_resample, prediction_probability_resample))
auc_dist = np.array(auc_dist)
plot_label += f' ({np.percentile(auc_dist, 2.5):.5f}, {np.percentile(auc_dist, 97.5):.5f})'
graph.plot(fpr, tpr, label=plot_label)
if not plot_curve_only:
graph.plot([0, 1], [0, 1], linestyle='--', color='k', label='Guessing')
graph.xlim([0, 1])
graph.ylim([0, 1])
graph.legend(loc=0)
graph.xlabel('False Positive Rate')
graph.ylabel('True Positive Rate')
if show_graph:
graph.show()
return {'fpr': fpr, 'tpr': tpr, 'threshold': thres}
def _plot_pr(
y_pred_proba,
y_true,
is_precision_plot: bool,
class_labels,
estimate_intervals: bool,
show_graph
):
import itertools
from sklearn.metrics import precision_recall_curve
from sklearn.utils import resample
for class_i, color in zip(range(y_pred_proba.shape[1]), itertools.cycle(colors_538)):
precision, recall, threshold = precision_recall_curve(
y_true=y_true,
probas_pred=y_pred_proba[:, class_i]
)
graph.plot(
threshold,
precision[:-1] if is_precision_plot else recall[:-1],
linewidth=2,
color=color,
label=f'{class_i}' if class_labels is None else f'{class_labels[class_i]}'
)
if estimate_intervals:
for seed in range(1000):
y_true_resample, y_pred_proba_resample = resample(y_true, y_pred_proba, random_state=seed)
precision_i, recall_i, threshold_i = precision_recall_curve(
y_true=y_true_resample,
probas_pred=y_pred_proba_resample[:, class_i]
)
graph.plot(
threshold_i,
precision_i[:-1] if is_precision_plot else recall_i[:-1],
linewidth=0.5,
color=color,
alpha=0.1
)
graph.xlabel('Probability Threshold')
graph.ylabel('Precision' if is_precision_plot else 'Recall')
graph.legend()
if show_graph:
graph.show()
def plot_precision(prediction_probability, true, class_labels=None, estimate_intervals=False, show_graph=False):
"""
This plots the precision | probability
Reminder that precision is the ratio ``tp / (tp + fp)`` where ``tp`` is the number of
true positives and ``fp`` the number of false positives. The precision is
intuitively the ability of the classifier not to label as positive a sample
that is negative.
>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.linear_model import LogisticRegression
>>> import matplotlib.pyplot as graph
>>> x, y = load_breast_cancer(return_X_y=True)
>>> model = LogisticRegression().fit(x, y)
>>> ypp = model.predict_proba(x)
>>> plot_precision(ypp, y)
>>> graph.show()
>>> plot_precision(ypp, y, class_labels=['Malignant', 'Benign'])
>>> graph.show()
>>> plot_precision(ypp, y, estimate_intervals=True, class_labels=['Malignant', 'Benign'])
>>> graph.show()
:return:
"""
_plot_pr(
y_pred_proba=prediction_probability,
y_true=true,
is_precision_plot=True,
class_labels=class_labels,
estimate_intervals=estimate_intervals,
show_graph=show_graph
)
def plot_recall(prediction_probability, true, class_labels=None, estimate_intervals=False, show_graph=False):
"""
Plots the recall | probability
Reminder that recall is the ratio ``tp / (tp + fn)`` where ``tp`` is the number of
true positives and ``fn`` the number of false negatives. The recall is
intuitively the ability of the classifier to find all the positive samples.
>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.linear_model import LogisticRegression
>>> import matplotlib.pyplot as graph
>>> x, y = load_breast_cancer(return_X_y=True)
>>> model = LogisticRegression().fit(x, y)
>>> ypp = model.predict_proba(x)
>>> plot_recall(ypp, y)
>>> graph.show()
>>> plot_recall(ypp, y, class_labels=['Malignant', 'Benign'])
>>> graph.show()
>>> plot_recall(ypp, y, estimate_intervals=True, class_labels=['Malignant', 'Benign'])
>>> graph.show()
:return:
"""
_plot_pr(
y_pred_proba=prediction_probability,
y_true=true,
is_precision_plot=False,
class_labels=class_labels,
estimate_intervals=estimate_intervals,
show_graph=show_graph
)
def plot_biplot(pca, x_axis=0, y_axis=1, data=None, feature_names=None, c=None, show_graph=False):
"""
Plots the kind of biplot R creates for PCA
:param pca: SKLearn PCA object
:param c: Matplotlib scatterplot c param for coloring by class
:param x_axis:
:param y_axis:
:param feature_names:
:param data: X data you want to see in the biplot
:param show_graph:
:return:
"""
x_axis_upscale_coef, y_axis_upscale_coef = 1, 1
if data is not None:
data = pca.transform(data)
pc_0, pc_1 = data[:, x_axis], data[:, y_axis]
x_axis_upscale_coef = pc_0.max() - pc_0.min()
y_axis_upscale_coef = pc_1.max() - pc_1.min()
graph.scatter(pc_0, pc_1, c=c, alpha=0.66)
projected_rotation = pca.components_[[x_axis, y_axis], :]
projected_rotation = projected_rotation.T
for i_feature in range(projected_rotation.shape[0]):
graph.scatter(
[0, projected_rotation[i_feature, x_axis] * x_axis_upscale_coef * 1.2],
[0, projected_rotation[i_feature, y_axis] * y_axis_upscale_coef * 1.2],
alpha=0
)
graph.arrow(
0,
0,
projected_rotation[i_feature, x_axis] * x_axis_upscale_coef,
projected_rotation[i_feature, y_axis] * y_axis_upscale_coef,
alpha=0.7
)
graph.text(
projected_rotation[i_feature, x_axis] * 1.15 * x_axis_upscale_coef,
projected_rotation[i_feature, y_axis] * 1.15 * y_axis_upscale_coef,
f'col {i_feature}' if feature_names is None else feature_names[i_feature],
ha='center', va='center'
)
graph.xlabel(f'PC {x_axis}')
graph.ylabel(f'PC {y_axis}')
if show_graph:
graph.show()
def plot_learning_curve(means, stds, xs=None, n=None, show_graph=False):
"""
Plot learning curve with confidence intervals
:param xs: What the units on the x-axis should be
:param n: sample size, usually the number of CV intervals
:param means:
:param stds:
:param show_graph:
:return:
"""
import numpy as np
xs = xs if xs is not None else np.arange(len(means))
# If N is given, compute the standard error
stds = stds / np.sqrt(n) if n is not None else stds
ci95 = stds * 1.96
graph.plot(xs, means)
graph.fill_between(
xs,
means - ci95, means + ci95,
alpha=0.4
)
if show_graph:
graph.show()
def plot_confusion_matrix(y_true, y_pred, labels: list = None, axis=1, show_graph=False):
"""
Normalised Confusion Matrix
:param y_true:
:param y_pred:
:param labels:
:param axis: 0 if you want to know the probabilities given a predication. 1 if you want to know class confusion.
:param show_graph:
:return:
"""
import seaborn as sns
from sklearn.metrics import confusion_matrix
labels = True if labels is None else labels
cm = confusion_matrix(y_true, y_pred)
cm = cm.astype('float') / cm.sum(axis=axis, keepdims=True)
sns.heatmap(
cm,
annot=True, square=True, cmap='Blues',
xticklabels=labels, yticklabels=labels
)
graph.xlabel('Predicted')
graph.ylabel('True')
if show_graph:
graph.show()
def plot_ecdf(x, plot_kwargs=None, show_graph=False):
"""
Create the plot of the empricial distribution function
>>> import numpy as np
>>> import matplotlib.pyplot as graph
>>> plot_ecdf(np.random.normal(100, 15, size=100), {'label': 'blah'})
>>> graph.show()
:param x:
:param plot_kwargs:
:param show_graph:
:return:
"""
def _ecdf(data):
"""
Empirical CDF (x, y) generator
"""
import numpy as np
x = np.sort(data)
cdf = np.linspace(0, 1, len(x))
return cdf, x
cdf, x = _ecdf(x)
plot_kwargs = dict() if plot_kwargs is None else plot_kwargs
graph.plot(x, cdf, **plot_kwargs)
if show_graph:
graph.show()
def plot_confusion_probability_matrix(
y_true, y_pred, y_pred_proba,
labels: list = None, figsize=(8, 8), rug_height=0.05, show_graph=False
):
"""
Confusion matrix where you can see the histogram of the
>>> from sklearn.datasets import load_breast_cancer
>>> from sklearn.linear_model import LogisticRegression
>>> import matplotlib.pyplot as graph
>>> x, y = load_breast_cancer(return_X_y=True)
>>> model = LogisticRegression().fit(x, y)
>>> ypp = model.predict_proba(x)[:, 1]
>>> plot_confusion_probability_matrix(y, model.predict(x), model.predict_proba(x))
>>> graph.show()
>>> plot_confusion_probability_matrix(y, model.predict(x), model.predict_proba(x), labels=['Malignant', 'Benign'])
>>> graph.show()
:param y_true:
:param y_pred:
:param y_pred_proba:
:param labels:
:param figsize:
:param rug_height:
:param show_graph:
:return:
"""
import numpy as np
from itertools import product
from sklearn.metrics import confusion_matrix
def solve_n_bins(x):
"""
Uses the Freedman Diaconis Rule for generating the number of bins required
https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule
Bin Size = 2 IQR(x) / (n)^(1/3)
"""
import numpy as np
from scipy.stats import iqr
x = np.asarray(x)
hat = 2 * iqr(x) / (len(x) ** (1 / 3))
if hat == 0:
return int(np.sqrt(len(x)))
else:
return int(np.ceil((x.max() - x.min()) / hat))
n_classes = y_pred_proba.shape[1]
labels = list(range(n_classes)) if labels is None else labels
cm = confusion_matrix(y_true, y_pred)
# Create subplots
figure, box = graph.subplots(n_classes, n_classes, sharex='all', figsize=figsize)
# Create histograms
for i, j in product(range(n_classes), range(n_classes)):
selection_mask = (y_true == i) & (y_pred == j)
assert selection_mask.sum() == cm[i, j]
subset_probabilities = y_pred_proba[selection_mask, i]
box[i, j].set_title(f'N: {cm[i, j]}')
box[i, j].hist(subset_probabilities, density=True, bins=solve_n_bins(subset_probabilities), alpha=0.7)
box[i, j].plot(subset_probabilities, np.ones(len(subset_probabilities)) * rug_height, '|', alpha=0.7)
box[i, j].set_yticks([])
# Axis labels
for k in range(n_classes):
box[-1, k].set_xlabel(f'Pred = {labels[k]}')
box[k, 0].set_ylabel(f'True = {labels[k]}')
if show_graph:
graph.show()
def plot_barplot(d: dict, orient: str = 'h', show_graph=False):
"""
Create bar plot from a dictionary that maps a name to the size of the bar
>>> dictionary = {'dogs': 10, 'cats': 4, 'birbs': 8}
>>> plot_barplot(dictionary, show_graph=True)
:param d:
:param orient:
:param show_graph:
:return:
"""
orient = orient.lower()
if 'h' not in orient and 'v' not in orient:
raise ValueError('`orient` must be either `h` for horizontal and `v` for vertical')
bar_plot = graph.barh if 'h' in orient else graph.bar
bar_plot(
range(len(d.values())),
list(d.values()),
tick_label=list(d.keys())
)
if show_graph:
graph.show()
def plot_2d_histogram(x, y, bins=100, transform=lambda z: z, plot_kwargs: dict = None, show_graph=False):
"""
Creates a 2D histogram AND allows you to transform the colors of the histogram with the transform function
Datashader like functionality without all the hassle
:param x:
:param y:
:param bins:
:param transform: function that takes 1 argument used to transform the histogram
:param plot_kwargs: arguments to pass to the internal imshow()
:param show_graph:
:return:
"""
import numpy as np
required_kwargs = {'aspect': 'auto'}
if plot_kwargs is None:
plot_kwargs = required_kwargs
else:
plot_kwargs.update(required_kwargs)
h, *_ = np.histogram2d(x, y, bins=bins)
h = np.rot90(h)
graph.imshow(transform(h), **plot_kwargs)
if show_graph:
graph.show()
def plot_forest(point_estimate, lower_bound=None, upper_bound=None, labels=None, show_graph=False):
"""
Create forest plot using summary data.
:param point_estimate: Where the center of the point should be located
:param lower_bound:
:param upper_bound:
:param labels:
:param show_graph:
:return:
"""
# Validate input
import pandas as pd
from operator import xor
if xor(bool(lower_bound), bool(upper_bound)):
raise ValueError('You must supply both an `upper_bound` and `lower_bound`')
if not all((len(x) for x in (point_estimate, lower_bound, upper_bound, labels) if x is not None)):
raise AssertionError('All inputs must be the same lengths')
# Setup
indices = list(range(len(point_estimate)))
labels = labels.values if isinstance(labels, pd.Series) else labels
# Plot
graph.plot(point_estimate, indices, 'D', markersize=10, color='seagreen')
if lower_bound and upper_bound:
graph.hlines(indices, xmin=lower_bound, xmax=upper_bound, colors='seagreen')
graph.yticks(indices, labels)
if show_graph:
graph.show()
if __name__ == '__main__':
import doctest
doctest.testmod() | /rosey-graph-1.2021.10.2.tar.gz/rosey-graph-1.2021.10.2/rosey_graph/__init__.py | 0.844601 | 0.50531 | __init__.py | pypi |
import tensorflow.keras as k
import tensorflow.keras.backend as K
class Fusion(k.regularizers.Regularizer):
"""
Base class for all of the fusion regularizers.
Fused Lasso -> https://web.stanford.edu/group/SOL/papers/fused-lasso-JRSSB.pdf
Absolute Fused Lasso -> http://www.kdd.org/kdd2016/papers/files/rpp0343-yangA.pdf
"""
def __init__(self, l1: float = 0, fusion: float = 0, absolute_fusion: float = 0):
self.l1 = K.cast_to_floatx(l1)
self.fuse = K.cast_to_floatx(fusion)
self.abs_fuse = K.cast_to_floatx(absolute_fusion)
def __call__(self, x):
regularization = 0.
x_rolled = self._roll_tensor(x)
# Add components if they are given
if self.l1:
# \lambda ||x||
regularization += self.l1 * K.sum(K.abs(x))
if self.fuse:
# \lambda \sum{ |x - x_+1| }
regularization += self.fuse * K.sum(K.abs(x - x_rolled))
if self.abs_fuse:
# \lambda \sum{ ||x| - |x_+1|| }
regularization += self.abs_fuse * K.sum(K.abs(K.abs(x) - K.abs(x_rolled)))
return regularization
def get_config(self):
return {
'l1': float(self.l1),
'fusion': float(self.fuse),
'abs_fusion': float(self.abs_fuse)
}
@staticmethod
def _roll_tensor(x):
vector_length = K.int_shape(x)[0]
x_tile = K.tile(x, [2, 1])
return x_tile[vector_length - 1:-1]
@staticmethod
def check_alpha_and_ratio(alpha, l1_ratio):
assert alpha >= 0, 'alpha must be >= 0'
assert 0.0 <= l1_ratio <= 1.0, 'l1_ratio must be between [0, 1]'
@staticmethod
def check_l1_and_fusion(l1, fuse):
assert l1 is not None and fuse is not None, 'Both l1 and fuse must be given'
def fused_lasso(alpha=2.0, l1_ratio=0.5, l1=None, fuse=None) -> k.regularizers.Regularizer:
"""
Either alpha and l1_ratio must be given or l1 and fuse
:param alpha: Regularization strength
:param l1_ratio: Proportion of alpha to transfer to the l1 regularization term
:param l1:
:param fuse:
:return:
"""
if l1 is None and fuse is None:
# Use the alpha and l1 ratio
Fusion.check_alpha_and_ratio(alpha, l1_ratio)
return Fusion(l1=alpha * l1_ratio, fusion=alpha * (1 - l1_ratio))
elif l1 is not None or fuse is not None:
Fusion.check_l1_and_fusion(l1, fuse)
return Fusion(l1=l1, fusion=fuse)
else:
raise ValueError('`l1` and `fuse` must be given OR `alpha` and `l1_ratio`')
def absolute_fused_lasso(alpha=2.0, l1_ratio=0.5, l1=None, abs_fuse=None):
"""
Either alpha and l1_ratio must be given or l1 and abs_fuse
:param alpha: Regularization strength
:param l1_ratio: Proportion of alpha to transfer to the l1 regularization term
:param l1:
:param abs_fuse:
:return:
"""
if l1 is None and abs_fuse is None:
# Use the alpha and l1 ratio
Fusion.check_alpha_and_ratio(alpha, l1_ratio)
return Fusion(l1=alpha * l1_ratio, absolute_fusion=alpha * (1 - l1_ratio))
elif l1 is not None or abs_fuse is not None:
Fusion.check_l1_and_fusion(l1, abs_fuse)
return Fusion(l1=l1, absolute_fusion=abs_fuse)
else:
raise ValueError('`l1` and `fuse` must be given OR `alpha` and `l1_ratio`') | /rosey-keras-1.20210930.tar.gz/rosey-keras-1.20210930/rosey_keras/regularizers.py | 0.912194 | 0.559952 | regularizers.py | pypi |
import tensorflow as tf
import tensorflow.keras as k
import tensorflow.keras.backend as K
def _diff(x):
return x[1:] - x[:-1]
def _wasserstein_distance(a, b):
"""
Wasserstein distance function
:param a: data points from distribution A
:param b: data points from distribution B
:return:
"""
# Compute the cdf distance
a_sorter = tf.argsort(a)
b_sorter = tf.argsort(b)
# Pooled value from both a and b
all_values = K.concatenate([a, b])
all_values = tf.sort(all_values)
# Compute the difference between the sorted pooled values
deltas = _diff(all_values)
# Get the positions of the values of a and b between the 2 distributions
a_cdf_indices = tf.searchsorted(
tf.gather(a, a_sorter),
all_values[:-1],
side='right'
)
b_cdf_indices = tf.searchsorted(
tf.gather(b, b_sorter),
all_values[:-1],
side='right'
)
# Calculate CDF
a_cdf = tf.cast(a_cdf_indices / tf.size(a), 'float')
b_cdf = tf.cast(b_cdf_indices / tf.size(b), 'float')
# Wasserstein distance
return K.sum(
tf.multiply(
K.abs(a_cdf - b_cdf),
deltas
)
)
def wasserstein_loss(a_and_b, label):
"""
This implements the truest Wasserstein distance and therefore no need to worry about how a or b is encoded
:param a_and_b: all data
:param label: binary labels about something is from distribution b or not
:return: Wasserstein metric
"""
bool_labels = K.cast(label, 'bool')
a = tf.boolean_mask(a_and_b, ~bool_labels)
b = tf.boolean_mask(a_and_b, bool_labels)
return _wasserstein_distance(a, b)
def huber_loss(y_true, y_pred, delta=1):
"""
a = y - f(x)
0.5 * a ** 2 if np.abs(a) <= delta else (delta * np.abs(a)) - 0.5 * delta ** 2
"""
a = y_true - y_pred
cost_i = K.switch(
a <= delta,
0.5 * K.pow(a, 2),
(delta * K.abs(a)) - 0.5 * delta ** 2
)
return K.mean(cost_i, axis=-1)
def pseudo_huber_loss(y_true, y_pred, delta=1):
"""
a = y - f(x)
(delta^2) * (np.sqrt(1 + (a / delta)^2) - 1)
"""
return K.mean((delta ** 2) * (K.sqrt(1 + K.pow((y_true - y_pred) / delta, 2)) - 1))
def log_cosh_loss(y_true, y_pred, delta=1):
"""
Log of the Hyperbolic Cosine. This is an approximation of the Pseudo Huber Loss
"""
def _cosh(x):
return (K.exp(x) + K.exp(-x)) / 2
return K.mean(K.log(_cosh(y_pred - y_true)), axis=-1)
def get_quantile_loss(quantile):
"""
q * residual [if residual > 0]
(q-1) * residual [if residual < 0]
Unlike most loss functions this one needs to be called with the desired quantile to yield the loss function
"""
def quantile_loss(y_true, quantile_hat):
residual = y_true - quantile_hat
tilt = K.maximum(
quantile*residual,
(quantile - 1) * residual
)
return K.mean(tilt, axis=-1)
return quantile_loss | /rosey-keras-1.20210930.tar.gz/rosey-keras-1.20210930/rosey_keras/losses.py | 0.947381 | 0.727855 | losses.py | pypi |
import numpy as np
import pandas as pd
__version__ = '1.2021.10.01.1336'
def solve_n_bins(x):
"""
Uses the Freedman Diaconis Rule for generating the number of bins required
https://en.wikipedia.org/wiki/Freedman%E2%80%93Diaconis_rule
Bin Size = 2 IQR(x) / (n)^(1/3)
"""
from scipy.stats import iqr
x = np.asarray(x)
hat = 2 * iqr(x) / (len(x) ** (1 / 3))
if hat == 0:
return int(np.sqrt(len(x)))
else:
return int(np.ceil((x.max() - x.min()) / hat))
def neg_log_p(p):
"""
Negative Log P value
"""
return np.nan_to_num(-np.log10(p))
def most_common(iterable):
"""
>>> most_common([1, 2, 2, 3, 4, 4, 4, 4])
4
>>> most_common(list('Anthony'))
'n'
>>> most_common('Stephen')
'e'
Exceptionally quick! Benchmark at 12.1 us
:param iterable:
:return:
"""
from collections import Counter
data = Counter(iterable)
return data.most_common(1)[0][0]
def lambda_test(p_values, df=1):
"""
Test for p-value inflation for hinting at population stratification or cryptic species.
Paper: https://neurogenetics.qimrberghofer.edu.au/papers/Yang2011EJHG.pdf
:param p_values: array of p-values
:param df: Degrees of freedom for the Chi sq distribution
:return: lambda gc
"""
from scipy.stats import chi2
assert np.max(p_values) <= 1 and np.min(p_values) >= 0, 'These do not appear to be p-values'
chi_sq_scores = chi2.ppf(1 - p_values, df)
return np.median(chi_sq_scores) / chi2.ppf(0.5, df)
def p_value_inflation_test(p_values):
"""
Test for p-value inflation using the Kolmogorov-Smirnov test.
However there are no assumptions to fail for this test.
:param p_values: array of p-values
:return: p-value (significant is bad)
"""
from scipy.stats import ks_2samp
h_null = np.random.uniform(0, 1, size=int(1e6))
d, p_value = ks_2samp(p_values, h_null)
return p_value, d
def bonferroni(p_values, alpha=0.05):
"""
Bonferroni Correction
:param p_values:
:param alpha:
:return:
"""
return alpha / len(p_values)
def bh_procedure(p_values: pd.Series, alpha=0.05):
"""
Benjamini–Hochberg procedure
https://en.wikipedia.org/wiki/False_discovery_rate#BH_procedure
http://www.math.tau.ac.il/~ybenja/MyPapers/benjamini_hochberg1995.pdf
"""
assert len(p_values) > 0, 'p-value list in empty'
assert sum(np.isnan(p_values)) == 0, 'You cannot have nans in the p-value list'
p_values, m = sorted(p_values), len(p_values)
max_condition = 0
for i, p in enumerate(p_values):
rank = i + 1
if p <= (rank * alpha) / m:
max_condition = p
else:
break
return max_condition
def ecdf(data):
"""
Empirical CDF (x, y) generator
"""
x = np.sort(data)
cdf = np.linspace(0, 1, len(x))
return cdf, x
def elbow_detection(data, threshold=1, tune=0.01, get_index=False):
cdf, ordered = ecdf(data)
data_2nd_deriv = np.diff(np.diff(ordered))
elbow_point = np.argmax(data_2nd_deriv > threshold) - int(len(cdf) * tune)
return elbow_point if get_index else ordered[elbow_point]
def normalise_percents(x: np.ndarray or pd.Series, should_impute=False) -> np.ndarray or pd.Series:
"""
If the vector contains numbers whose numbers are [0, 1] then this is transformation that properly handles the
difference in how the variance of the kind of a feature is computed.
x_norm = (x - mu) / sqrt(mu * (1 - mu))
:param should_impute: If True then nans are imputed with the mean of x
:param x:
:return:
"""
# NOTE Currently python doesn't allow you to write this as 0 <= x <= 1
assert (0 <= x[~np.isnan(x)]).all() and (x[~np.isnan(x)] <= 1).all(), 'Values must be [0, 1]'
mu = np.nanmean(x)
if should_impute:
x[np.isnan(x)] = mu
return (x - mu) / np.sqrt(mu * (1 - mu))
def is_positive_definite(x):
"""
If all eigenvalues are greater than 0 then the matrix is positive definite!
"""
return np.all(np.linalg.eigvals(x) > 0)
def is_positive_semi_definite(x):
return np.all(np.linalg.eigvals(x) >= 0) | /rosey-stats-1.2021.10.1.1336.tar.gz/rosey-stats-1.2021.10.1.1336/rosey_stats/__init__.py | 0.864325 | 0.736235 | __init__.py | pypi |
import math
import matplotlib.pyplot as plt
from .Generaldistribution import Distribution
class Gaussian(Distribution):
""" Gaussian distribution class for calculating and
visualizing a Gaussian distribution.
Attributes:
mean (float) representing the mean value of the distribution
stdev (float) representing the standard deviation of the distribution
data_list (list of floats) a list of floats extracted from the data file
"""
def __init__(self, mu=0, sigma=1):
Distribution.__init__(self, mu, sigma)
def calculate_mean(self):
"""Function to calculate the mean of the data set.
Args:
None
Returns:
float: mean of the data set
"""
avg = 1.0 * sum(self.data) / len(self.data)
self.mean = avg
return self.mean
def calculate_stdev(self, sample=True):
"""Function to calculate the standard deviation of the data set.
Args:
sample (bool): whether the data represents a sample or population
Returns:
float: standard deviation of the data set
"""
if sample:
n = len(self.data) - 1
else:
n = len(self.data)
mean = self.calculate_mean()
sigma = 0
for d in self.data:
sigma += (d - mean) ** 2
sigma = math.sqrt(sigma / n)
self.stdev = sigma
return self.stdev
def plot_histogram(self):
"""Function to output a histogram of the instance variable data using
matplotlib pyplot library.
Args:
None
Returns:
None
"""
plt.hist(self.data)
plt.title('Histogram of Data')
plt.xlabel('data')
plt.ylabel('count')
def pdf(self, x):
"""Probability density function calculator for the gaussian distribution.
Args:
x (float): point for calculating the probability density function
Returns:
float: probability density function output
"""
return (1.0 / (self.stdev * math.sqrt(2*math.pi))) * math.exp(-0.5*((x - self.mean) / self.stdev) ** 2)
def plot_histogram_pdf(self, n_spaces = 50):
"""Function to plot the normalized histogram of the data and a plot of the
probability density function along the same range
Args:
n_spaces (int): number of data points
Returns:
list: x values for the pdf plot
list: y values for the pdf plot
"""
mu = self.mean
sigma = self.stdev
min_range = min(self.data)
max_range = max(self.data)
# calculates the interval between x values
interval = 1.0 * (max_range - min_range) / n_spaces
x = []
y = []
# calculate the x values to visualize
for i in range(n_spaces):
tmp = min_range + interval*i
x.append(tmp)
y.append(self.pdf(tmp))
# make the plots
fig, axes = plt.subplots(2,sharex=True)
fig.subplots_adjust(hspace=.5)
axes[0].hist(self.data, density=True)
axes[0].set_title('Normed Histogram of Data')
axes[0].set_ylabel('Density')
axes[1].plot(x, y)
axes[1].set_title('Normal Distribution for \n Sample Mean and Sample Standard Deviation')
axes[0].set_ylabel('Density')
plt.show()
return x, y
def __add__(self, other):
"""Function to add together two Gaussian distributions
Args:
other (Gaussian): Gaussian instance
Returns:
Gaussian: Gaussian distribution
"""
result = Gaussian()
result.mean = self.mean + other.mean
result.stdev = math.sqrt(self.stdev ** 2 + other.stdev ** 2)
return result
def __repr__(self):
"""Function to output the characteristics of the Gaussian instance
Args:
None
Returns:
string: characteristics of the Gaussian
"""
return "mean {}, standard deviation {}".format(self.mean, self.stdev) | /roshan_dist_pack-1.2.tar.gz/roshan_dist_pack-1.2/roshan_dist_pack/Gaussiandistribution.py | 0.688364 | 0.853058 | Gaussiandistribution.py | pypi |
from __future__ import print_function
import json
import logging
# Python 2/3 compatibility import list
try:
from collections import UserDict
except ImportError:
from UserDict import UserDict
LOGGER = logging.getLogger('roslibpy')
__all__ = ['Message',
'ServiceRequest',
'ServiceResponse',
'Topic',
'Service',
'Param']
class Message(UserDict):
"""Message objects used for publishing and subscribing to/from topics.
A message is fundamentally a dictionary and behaves as one."""
def __init__(self, values=None):
self.data = {}
if values is not None:
self.update(values)
class ServiceRequest(UserDict):
"""Request for a service call."""
def __init__(self, values=None):
self.data = {}
if values is not None:
self.update(values)
class ServiceResponse(UserDict):
"""Response returned from a service call."""
def __init__(self, values=None):
self.data = {}
if values is not None:
self.update(values)
class Topic(object):
"""Publish and/or subscribe to a topic in ROS.
Args:
ros (:class:`.Ros`): Instance of the ROS connection.
name (:obj:`str`): Topic name, e.g. ``/cmd_vel``.
message_type (:obj:`str`): Message type, e.g. ``std_msgs/String``.
compression (:obj:`str`): Type of compression to use, e.g. `png`. Defaults to `None`.
throttle_rate (:obj:`int`): Rate (in ms between messages) at which to throttle the topics.
queue_size (:obj:`int`): Queue size created at bridge side for re-publishing webtopics.
latch (:obj:`bool`): True to latch the topic when publishing, False otherwise.
queue_length (:obj:`int`): Queue length at bridge side used when subscribing.
reconnect_on_close (:obj:`bool`): Reconnect the topic (both for publisher and subscribers) if a reconnection is detected.
"""
SUPPORTED_COMPRESSION_TYPES = ('png', 'none')
def __init__(self, ros, name, message_type, compression=None, latch=False, throttle_rate=0,
queue_size=100, queue_length=0, reconnect_on_close=True):
self.ros = ros
self.name = name
self.message_type = message_type
self.compression = compression
self.latch = latch
self.throttle_rate = throttle_rate
self.queue_size = queue_size
self.queue_length = queue_length
self._subscribe_id = None
self._advertise_id = None
if self.compression is None:
self.compression = 'none'
if self.compression not in self.SUPPORTED_COMPRESSION_TYPES:
raise ValueError(
'Unsupported compression type. Must be one of: ' + str(self.SUPPORTED_COMPRESSION_TYPES))
self.reconnect_on_close = reconnect_on_close
@property
def is_advertised(self):
"""Indicate if the topic is currently advertised or not.
Returns:
bool: True if advertised as publisher of this topic, False otherwise.
"""
return self._advertise_id is not None
@property
def is_subscribed(self):
"""Indicate if the topic is currently subscribed or not.
Returns:
bool: True if subscribed to this topic, False otherwise.
"""
return self._subscribe_id is not None
def subscribe(self, callback):
"""Register a subscription to the topic.
Every time a message is published for the given topic,
the callback will be called with the message object.
Args:
callback: Function to be called when messages of this topic are published.
"""
# Avoid duplicate subscription
if self._subscribe_id:
return
self._subscribe_id = 'subscribe:%s:%d' % (
self.name, self.ros.id_counter)
self.ros.on(self.name, callback)
self._connect_topic(Message({
'op': 'subscribe',
'id': self._subscribe_id,
'type': self.message_type,
'topic': self.name,
'compression': self.compression,
'throttle_rate': self.throttle_rate,
'queue_length': self.queue_length
}))
def unsubscribe(self):
"""Unregister from a subscribed the topic."""
if not self._subscribe_id:
return
# Do not try to reconnect when manually unsubscribing
if self.reconnect_on_close:
self.ros.off('close', self._reconnect_topic)
self.ros.off(self.name)
self.ros.send_on_ready(Message({
'op': 'unsubscribe',
'id': self._subscribe_id,
'topic': self.name
}))
self._subscribe_id = None
def publish(self, message):
"""Publish a message to the topic.
Args:
message (:class:`.Message`): ROS Bridge Message to publish.
"""
if not self.is_advertised:
self.advertise()
self.ros.send_on_ready(Message({
'op': 'publish',
'id': 'publish:%s:%d' % (self.name, self.ros.id_counter),
'topic': self.name,
'msg': dict(message),
'latch': self.latch
}))
def advertise(self):
"""Register as a publisher for the topic."""
if self.is_advertised:
return
self._advertise_id = 'advertise:%s:%d' % (
self.name, self.ros.id_counter)
self._connect_topic(Message({
'op': 'advertise',
'id': self._advertise_id,
'type': self.message_type,
'topic': self.name,
'latch': self.latch,
'queue_size': self.queue_size
}))
if not self.reconnect_on_close:
self.ros.on('close', self._reset_advertise_id)
def _reset_advertise_id(self, _proto):
self._advertise_id = None
def _connect_topic(self, message):
self._connect_message = message
self.ros.send_on_ready(message)
if self.reconnect_on_close:
self.ros.on('close', self._reconnect_topic)
def _reconnect_topic(self, _proto):
# Delay a bit the event hookup because
# 1) _proto is not yet nullified, and
# 2) reconnect anyway takes a few seconds
self.ros.call_later(1, lambda: self.ros.send_on_ready(self._connect_message))
def unadvertise(self):
"""Unregister as a publisher for the topic."""
if not self.is_advertised:
return
# Do not try to reconnect when manually unadvertising
if self.reconnect_on_close:
self.ros.off('close', self._reconnect_topic)
self.ros.send_on_ready(Message({
'op': 'unadvertise',
'id': self._advertise_id,
'topic': self.name,
}))
self._advertise_id = None
class Service(object):
"""Client/server of ROS services.
This class can be used both to consume other ROS services as a client,
or to provide ROS services as a server.
Args:
ros (:class:`.Ros`): Instance of the ROS connection.
name (:obj:`str`): Service name, e.g. ``/add_two_ints``.
service_type (:obj:`str`): Service type, e.g. ``rospy_tutorials/AddTwoInts``.
"""
def __init__(self, ros, name, service_type):
self.ros = ros
self.name = name
self.service_type = service_type
self._service_callback = None
self._is_advertised = False
@property
def is_advertised(self):
"""Service servers are registered as advertised on ROS.
This class can be used to be a service client or a server.
Returns:
bool: True if this is a server, False otherwise.
"""
return self._is_advertised
def call(self, request, callback=None, errback=None, timeout=None):
"""Start a service call.
Note:
The service can be used either as blocking or non-blocking.
If the ``callback`` parameter is ``None``, then the call will
block until receiving a response. Otherwise, the service response
will be returned in the callback.
Args:
request (:class:`.ServiceRequest`): Service request.
callback: Callback invoked on successful execution.
errback: Callback invoked on error.
timeout: Timeout for the operation, in seconds. Only used if blocking.
Returns:
object: Service response if used as a blocking call, otherwise ``None``.
"""
if self.is_advertised:
return
service_call_id = 'call_service:%s:%d' % (
self.name, self.ros.id_counter)
message = Message({
'op': 'call_service',
'id': service_call_id,
'service': self.name,
'args': dict(request),
})
# Non-blocking mode
if callback:
self.ros.call_async_service(message, callback, errback)
return
# Blocking mode
call_results = self.ros.call_sync_service(message, timeout)
if 'exception' in call_results:
raise Exception(call_results['exception'])
return call_results['result']
def advertise(self, callback):
"""Start advertising the service.
This turns the instance from a client into a server. The callback will be
invoked with every request that is made to the service.
If the service is already advertised, this call does nothing.
Args:
callback: Callback invoked on every service call. It should accept two parameters: `service_request` and
`service_response`. It should return `True` if executed correctly, otherwise `False`.
"""
if self.is_advertised:
return
if not callable(callback):
raise ValueError('Callback is not a valid callable')
self._service_callback = callback
self.ros.on(self.name, self._service_response_handler)
self.ros.send_on_ready(Message({
'op': 'advertise_service',
'type': self.service_type,
'service': self.name
}))
self._is_advertised = True
def unadvertise(self):
"""Unregister as a service server."""
if not self.is_advertised:
return
self.ros.send_on_ready(Message({
'op': 'unadvertise_service',
'service': self.name,
}))
self.ros.off(self.name, self._service_response_handler)
self._is_advertised = False
def _service_response_handler(self, request):
response = ServiceResponse()
success = self._service_callback(request['args'], response)
call = Message({'op': 'service_response',
'service': self.name,
'values': dict(response),
'result': success
})
if 'id' in request:
call['id'] = request['id']
self.ros.send_on_ready(call)
class Param(object):
"""A ROS parameter.
Args:
ros (:class:`.Ros`): Instance of the ROS connection.
name (:obj:`str`): Parameter name, e.g. ``max_vel_x``.
"""
def __init__(self, ros, name):
self.ros = ros
self.name = name
def get(self, callback=None, errback=None, timeout=None):
"""Fetch the current value of the parameter.
Note:
This method can be used either as blocking or non-blocking.
If the ``callback`` parameter is ``None``, the call will
block and return the parameter value. Otherwise, the parameter
value will be passed on to the callback.
Args:
callback: Callable function to be invoked when the operation is completed.
errback: Callback invoked on error.
timeout: Timeout for the operation, in seconds. Only used if blocking.
Returns:
object: Parameter value if used as a blocking call, otherwise ``None``.
"""
client = Service(self.ros, '/rosapi/get_param', 'rosapi/GetParam')
request = ServiceRequest({'name': self.name})
if not callback:
result = client.call(request, timeout=timeout)
return json.loads(result['value'])
else:
client.call(request, lambda result: callback(
json.loads(result['value'])), errback)
def set(self, value, callback=None, errback=None, timeout=None):
"""Set a new value to the parameter.
Note:
This method can be used either as blocking or non-blocking.
If the ``callback`` parameter is ``None``, the call will
block until completion.
Args:
callback: Callable function to be invoked when the operation is completed.
errback: Callback invoked on error.
timeout: Timeout for the operation, in seconds. Only used if blocking.
"""
client = Service(self.ros, '/rosapi/set_param', 'rosapi/SetParam')
request = ServiceRequest(
{'name': self.name, 'value': json.dumps(value)})
client.call(request, callback, errback, timeout=timeout)
def delete(self, callback=None, errback=None, timeout=None):
"""Delete the parameter.
Note:
This method can be used either as blocking or non-blocking.
If the ``callback`` parameter is ``None``, the call will
block until completion.
Args:
callback: Callable function to be invoked when the operation is completed.
errback: Callback invoked on error.
timeout: Timeout for the operation, in seconds. Only used if blocking.
"""
client = Service(self.ros, '/rosapi/delete_param',
'rosapi/DeleteParam')
request = ServiceRequest({'name': self.name})
client.call(request, callback, errback, timeout=timeout)
if __name__ == '__main__':
import time
from . import Ros
FORMAT = '%(asctime)-15s [%(levelname)s] %(message)s'
logging.basicConfig(level=logging.DEBUG, format=FORMAT)
ros_client = Ros('127.0.0.1', 9090)
def run_subscriber_example():
listener = Topic(ros_client, '/chatter', 'std_msgs/String')
listener.subscribe(lambda message: LOGGER.info(
'Received message on: %s', message['data']))
def run_unsubscriber_example():
listener = Topic(ros_client, '/chatter', 'std_msgs/String')
def print_message(message):
LOGGER.info('Received message on: %s', message['data'])
listener.subscribe(print_message)
ros_client.call_later(5, lambda: listener.unsubscribe())
ros_client.call_later(10, lambda: listener.subscribe(print_message))
def run_publisher_example():
publisher = Topic(ros_client, '/chatter',
'std_msgs/String', compression='png')
def start_sending():
i = 0
while ros_client.is_connected and i < 5:
i += 1
message = Message({'data': 'test'})
LOGGER.info('Publishing message to /chatter. %s', message)
publisher.publish(message)
time.sleep(0.75)
publisher.unadvertise()
ros_client.on_ready(start_sending, run_in_thread=True)
def run_service_example():
def h1(x):
print('ok', x)
def h2(x):
print('error', x)
service = Service(ros_client, '/turtle1/teleport_relative',
'turtlesim/TeleportRelative')
service.call(ServiceRequest({'linear': 2, 'angular': 2}), h1, h2)
def run_turtle_subscriber_example():
listener = Topic(ros_client, '/turtle1/pose',
'turtlesim/Pose', throttle_rate=500)
def print_message(message):
LOGGER.info('Received message on: %s', message)
listener.subscribe(print_message)
def run_get_example():
param = Param(ros_client, 'run_id')
param.get(print)
def run_set_example():
param = Param(ros_client, 'test_param')
param.set('test_value')
def run_delete_example():
param = Param(ros_client, 'test_param')
param.delete()
def run_server_example():
service = Service(ros_client, '/test_server',
'rospy_tutorials/AddTwoInts')
def dispose_server():
service.unadvertise()
ros_client.call_later(1, service.ros.terminate)
def add_two_ints(request, response):
response['sum'] = request['a'] + request['b']
if response['sum'] == 42:
ros_client.call_later(2, dispose_server)
return True
service.advertise(add_two_ints)
run_server_example()
ros_client.run_forever() | /roslibpy_vincentbaetenpxl-1.1.1.tar.gz/roslibpy_vincentbaetenpxl-1.1.1/src/roslibpy/core.py | 0.849535 | 0.181517 | core.py | pypi |
from __future__ import print_function
import logging
import math
from . import Service
from . import ServiceRequest
from . import Topic
__all__ = ['TFClient']
LOGGER = logging.getLogger('roslibpy.tf')
class TFClient(object):
"""A TF Client that listens to TFs from tf2_web_republisher.
Args:
ros (:class:`.Ros`): Instance of the ROS connection.
fixed_frame (:obj:`str`): Fixed frame, e.g. ``/base_link``.
angular_threshold (:obj:`float`): Angular threshold for the TF republisher.
translation_threshold (:obj:`float`): Translation threshold for the TF republisher.
rate (:obj:`float`): Rate for the TF republisher.
update_delay (:obj:`int`): Time expressed in milliseconds to wait after a new subscription to update the TF republisher's list of TFs.
topic_timeout (:obj:`int`): Timeout parameter for the TF republisher expressed in milliseconds.
repub_service_name (:obj:`str`): Name of the republish tfs service, e.g. ``/republish_tfs``.
"""
def __init__(self, ros, fixed_frame='/base_link', angular_threshold=2.0, translation_threshold=0.01, rate=10.0, update_delay=50, topic_timeout=2000.0,
server_name='/tf2_web_republisher', repub_service_name='/republish_tfs'):
self.ros = ros
self.fixed_frame = fixed_frame
self.angular_threshold = angular_threshold
self.translation_threshold = translation_threshold
self.rate = rate
self.update_delay = update_delay
seconds = topic_timeout / 1000.
secs = math.floor(seconds)
nsecs = math.floor((seconds - secs) * 1000000000)
self.topic_timeout = dict(secs=secs, nsecs=nsecs)
self.repub_service_name = repub_service_name
self.current_topic = False
self.frame_info = {}
self.republisher_update_requested = False
self.service_client = Service(ros, self.repub_service_name,
'tf2_web_republisher/RepublishTFs')
def _process_tf_array(self, tf):
"""Process an incoming TF message and send it out using the callback functions.
Args:
tf (:obj:`list`): TF message from the server.
"""
# TODO: Test this function
for transform in tf['transforms']:
frame_id = self._normalize_frame_id(transform['child_frame_id'])
frame = self.frame_info.get(frame_id, None)
if frame:
frame['transform'] = dict(
translation=transform['transform']['translation'],
rotation=transform['transform']['rotation']
)
for callback in frame['cbs']:
callback(frame['transform'])
def update_goal(self):
"""Send a new service request to the tf2_web_republisher based on the current list of TFs."""
message = dict(source_frames=list(self.frame_info.keys()),
target_frame=self.fixed_frame,
angular_thres=self.angular_threshold,
trans_thres=self.translation_threshold,
rate=self.rate)
# In contrast to roslibjs, we do not support groovy compatibility mode
# and only use the service interface to the TF republisher
message['timeout'] = self.topic_timeout
request = ServiceRequest(message)
self.service_client.call(
request, self._process_response, self._process_error)
self.republisher_update_requested = False
def _process_error(self, response):
LOGGER.error(
'The TF republisher service interface returned an error. %s', str(response))
def _process_response(self, response):
"""Process the service response and subscribe to the tf republisher topic."""
LOGGER.info('Received response from TF Republisher service interface')
if self.current_topic:
self.current_topic.unsubscribe()
self.current_topic = Topic(
self.ros, response['topic_name'], 'tf2_web_republisher/TFArray')
self.current_topic.subscribe(self._process_tf_array)
def _normalize_frame_id(self, frame_id):
# Remove leading slash, if it's there
if frame_id[0] == '/':
return frame_id[1:]
return frame_id
def subscribe(self, frame_id, callback):
"""Subscribe to the given TF frame.
Args:
frame_id (:obj:`str`): TF frame identifier to subscribe to.
callback (:obj:`callable`): A callable functions receiving one parameter with `transform` data.
"""
frame_id = self._normalize_frame_id(frame_id)
frame = self.frame_info.get(frame_id, None)
# If there is no callback registered for the given frame, create emtpy callback list
if not frame:
frame = dict(cbs=[])
self.frame_info[frame_id] = frame
if not self.republisher_update_requested:
self.ros.call_later(self.update_delay / 1000., self.update_goal)
self.republisher_update_requested = True
else:
# If we already have a transform, call back immediately
if 'transform' in frame:
callback(frame['transform'])
frame['cbs'].append(callback)
def unsubscribe(self, frame_id, callback):
"""Unsubscribe from the given TF frame.
Args:
frame_id (:obj:`str`): TF frame identifier to unsubscribe from.
callback (:obj:`callable`): The callback function to remove.
"""
frame_id = self._normalize_frame_id(frame_id)
frame = self.frame_info.get(frame_id, None)
if 'cbs' in frame:
frame['cbs'].pop(callback)
if not callback or ('cbs' in frame and len(frame['cbs']) == 0):
self.frame_info.pop(frame_id)
def dispose(self):
"""Unsubscribe and unadvertise all topics associated with this instance."""
if self.current_topic:
self.current_topic.unsubscribe()
if __name__ == '__main__':
from roslibpy import Ros
FORMAT = '%(asctime)-15s [%(levelname)s] %(message)s'
logging.basicConfig(level=logging.DEBUG, format=FORMAT)
ros_client = Ros('127.0.0.1', 9090)
def run_tf_example():
tfclient = TFClient(ros_client, fixed_frame='world',
angular_threshold=0.01, translation_threshold=0.01)
tfclient.subscribe('turtle2', print)
def dispose_server():
tfclient.dispose()
ros_client.call_later(10, dispose_server)
ros_client.call_later(11, ros_client.close)
ros_client.call_later(12, ros_client.terminate)
run_tf_example()
ros_client.run_forever() | /roslibpy_vincentbaetenpxl-1.1.1.tar.gz/roslibpy_vincentbaetenpxl-1.1.1/src/roslibpy/tf.py | 0.765856 | 0.1585 | tf.py | pypi |
Examples
========
Getting started with **roslibpy** is simple. The following examples will help you
on the first steps using it to connect to a ROS environment. Before you start, make sure
you have ROS and `rosbridge` running (see :ref:`ros-setup`).
These examples assume ROS is running on the same computer where you run the examples.
If that is not the case, change the ``host`` argument from ``'localhost'``
to the *IP Address* of your ROS master.
First connection
----------------
We start importing ``roslibpy`` as follows::
>>> import roslibpy
And we initialize the connection with::
>>> ros = roslibpy.Ros(host='localhost', port=9090)
>>> ros.run()
Easy, right?
Let's check the status::
>>> ros.is_connected
True
**Yay! Our first connection to ROS!**
Putting it all together
-----------------------
Let's build a full example into a python file. Create a file named
``ros-hello-world.py`` and paste the following content:
.. literalinclude :: files/ros-hello-world.py
:language: python
Now run it from the command prompt typing::
$ python ros-hello-world.py
The program will run, print once we are connected and terminate the connection.
Controlling the event loop
^^^^^^^^^^^^^^^^^^^^^^^^^^
In the previous examples, we started the ROS connection with a call to ``run()``,
which starts the event loop in the background. In some cases, we want to handle the
main event loop more explicitely in the foreground. :class:`roslibpy.Ros` provides
the method ``run_forever()`` for this purpose.
If we use this method to start the event loop, we need to setup all connection handlers
beforehand. We will use the :meth:`roslibpy.Ros.on_ready` method to do this.
We will pass a function to it, that will be invoked when the connection is ready.
The following snippet shows the same connection example above but
using ``run_forever()`` and ``on_ready``:
.. literalinclude :: files/ros-hello-world-run-forever.py
:language: python
.. note::
The difference between ``run()`` and ``run_forever()`` is that the former
starts the event processing in a separate thread, while the latter
blocks the calling thread.
Disconnecting
-------------
Once your task is done, you should disconnect cleanly from ``rosbridge``. There are two related methods available for this:
- :meth:`roslibpy.Ros.close`: Disconnect the websocket connection. Once the connection is closed,
it is still possible to reconnect by calling :meth:`roslibpy.Ros.connect`: again.
- :meth:`roslibpy.Ros.terminate`: Terminate the main event loop. If the connection is still open,
it will first close it.
.. note::
Terminating the event loop is an irreversible action when using the ``twisted/authbahn`` loop because ``twisted``
reactors cannot be restarted. This operation should be reserved to be executed at the very end of your program.
Reconnecting
------------
If ``rosbridge`` is not responsive when the connection is started or if an established connection drops uncleanly, ``roslibpy``
will try to reconnect automatically, and reconnect subscriber and publisher topics as well. Reconnect will be retried
with an exponential back-off.
Hello World: Topics
-------------------
The ``Hello world`` of ROS is to start two nodes that communicate using
topic subscription/publishing. The nodes (a talker and a listener) are
extremely simple but they exemplify a distributed system with communication
between two processes over the ROS infrastructure.
Writing the talker node
^^^^^^^^^^^^^^^^^^^^^^^
The following example starts a ROS node and begins to publish
messages in loop (to terminate, press ``ctrl+c``):
.. literalinclude :: files/ros-hello-world-talker.py
:language: python
* :download:`ros-hello-world-talker.py <files/ros-hello-world-talker.py>`
Writing the listener node
^^^^^^^^^^^^^^^^^^^^^^^^^
Now let's move on to the listener side:
.. literalinclude :: files/ros-hello-world-listener.py
:language: python
* :download:`ros-hello-world-listener.py <files/ros-hello-world-listener.py>`
Running the example
^^^^^^^^^^^^^^^^^^^
Open a command prompt and start the talker:
::
python ros-hello-world-talker.py
Now open a second command prompt and start the listener:
::
python ros-hello-world-listener.py
.. note::
It is not relevant where the files are located. They can be in different
folders or even in different computers as long as the ROS master is the same.
Using services
--------------
Another way for nodes to communicate between each other is through ROS Services.
Services require the definition of request and response types so the following
example shows how to use an existing service called ``get_loggers``:
.. literalinclude :: files/ros-service-call-logger.py
:language: python
* :download:`ros-service-call-logger.py <files/ros-service-call-logger.py>`
Creating services
-----------------
It is also possible to create new services, as long as the service type
definition is present in your ROS environment.
The following example shows how to create a simple service that uses
one of the standard service types defined in ROS (``std_srvs/SetBool``):
.. literalinclude :: files/ros-service.py
:language: python
* :download:`ros-service.py <files/ros-service.py>`
Download it and run it from the command prompt typing::
$ python ros-service.py
The service will be active while the program is running (to terminate,
press ``ctrl+c``).
Leave this service running and download and run the following service calling
code example to verify the service is working:
* :download:`ros-service-call-set-bool.py <files/ros-service-call-set-bool.py>`
Download it and run it from the command prompt typing::
$ python ros-service-call-set-bool.py
.. note::
Now that you have a grasp of the basics of ``roslibpy``,
check out more details in the :ref:`ros-api-reference`.
Actions
-------
Besides Topics and Services, ROS provides **Actions**, which are intended for
long-running tasks, such as navigation, because they are non-blocking and allow
the cancellation (preempting) of an action while it is executing.
``roslibpy`` supports both consuming actions (i.e. action clients) and also
providing actions, through the :class:`roslibpy.actionlib.SimpleActionServer`.
The following examples use the **Fibonacci** action, which is defined in the
`actionlib_tutorials <http://wiki.ros.org/actionlib_tutorials>`_.
Action servers
^^^^^^^^^^^^^^
Let's start with the definition of the fibonacci server:
.. literalinclude :: files/ros-action-server.py
:language: python
* :download:`ros-action-server.py <files/ros-action-server.py>`
Download it and run it from the command prompt typing::
$ python ros-action-server.py
The action server will be active while the program is running (to terminate,
press ``ctrl+c``).
Leave this window running if you want to test it with the next example.
Action clients
^^^^^^^^^^^^^^
Now let's see how to write an action client for our newly created server.
The following program shows a simple action client:
.. literalinclude :: files/ros-action-client.py
:language: python
* :download:`ros-action-client.py <files/ros-action-client.py>`
Download it and run it from the command prompt typing::
$ python ros-action-client.py
You will immediately see all the intermediate calculations of our action server,
followed by a line indicating the resulting fibonacci sequence.
This example is very simplified and uses the :meth:`roslibpy.actionlib.Goal.wait`
function to make the code easier to read as an example. A more robust way to handle
results is to hook up to the ``result`` event with a callback.
Querying ROS API
----------------
ROS provides an API to inspect topics, services, nodes and much more. This API can be
used programmatically from Python code, and also be invoked from the command line.
Usage from the command-line
^^^^^^^^^^^^^^^^^^^^^^^^^^^
The command line mimics closely that of ROS itself.
The following commands are available::
$ roslibpy topic list
$ roslibpy topic type /rosout
$ roslibpy topic find std_msgs/Int32
$ roslibpy msg info rosgraph_msgs/Log
$ roslibpy service list
$ roslibpy service type /rosout/get_loggers
$ roslibpy service find roscpp/GetLoggers
$ roslibpy srv info roscpp/GetLoggers
$ roslibpy param list
$ roslibpy param set /foo "[\"1\", 1, 1.0]"
$ roslibpy param get /foo
$ roslibpy param delete /foo
Usage from Python code
^^^^^^^^^^^^^^^^^^^^^^
And conversely, the following methods allow to query the ROS API from Python code.
Topics
""""""
* :meth:`roslibpy.Ros.get_topics`
* :meth:`roslibpy.Ros.get_topic_type`
* :meth:`roslibpy.Ros.get_topics_for_type`
* :meth:`roslibpy.Ros.get_message_details`
Services
""""""""
* :meth:`roslibpy.Ros.get_services`
* :meth:`roslibpy.Ros.get_service_type`
* :meth:`roslibpy.Ros.get_services_for_type`
* :meth:`roslibpy.Ros.get_service_request_details`
* :meth:`roslibpy.Ros.get_service_response_details`
Params
""""""
* :meth:`roslibpy.Ros.get_params`
* :meth:`roslibpy.Ros.get_param`
* :meth:`roslibpy.Ros.set_param`
* :meth:`roslibpy.Ros.delete_param`
Advanced examples
-----------------
The following list is a compilation of more elaborate examples of the usage of ``roslibpy``.
We encourage everyone to submit suggestions for new examples, either send a pull request or request it via the issue tracker.
.. toctree::
:maxdepth: 2
:glob:
examples/*
| /roslibpy_vincentbaetenpxl-1.1.1.tar.gz/roslibpy_vincentbaetenpxl-1.1.1/docs/examples.rst | 0.92686 | 0.78436 | examples.rst | pypi |
Examples
========
Getting started with **roslibpy** is simple. The following examples will help you
on the first steps using it to connect to a ROS environment. Before you start, make sure
you have ROS and `rosbridge` running (see :ref:`ros-setup`).
These examples assume ROS is running on the same computer where you run the examples.
If that is not the case, change the ``host`` argument from ``'localhost'``
to the *IP Address* of your ROS instance.
First connection
----------------
We start importing ``roslibpy`` as follows::
>>> import roslibpy
And we initialize the connection with::
>>> ros = roslibpy.Ros(host='localhost', port=9090)
>>> ros.run()
Easy, right?
Let's check the status::
>>> ros.is_connected
True
**Yay! Our first connection to ROS!**
Putting it all together
-----------------------
Let's build a full example into a python file. Create a file named
``ros-hello-world.py`` and paste the following content:
.. literalinclude :: files/ros-hello-world.py
:language: python
Now run it from the command prompt typing::
$ python ros-hello-world.py
The program will run, print once we are connected and terminate the connection.
Controlling the event loop
^^^^^^^^^^^^^^^^^^^^^^^^^^
In the previous examples, we started the ROS connection with a call to ``run()``,
which starts the event loop in the background. In some cases, we want to handle the
main event loop more explicitely in the foreground. :class:`roslibpy.Ros` provides
the method ``run_forever()`` for this purpose.
If we use this method to start the event loop, we need to setup all connection handlers
beforehand. We will use the :meth:`roslibpy.Ros.on_ready` method to do this.
We will pass a function to it, that will be invoked when the connection is ready.
The following snippet shows the same connection example above but
using ``run_forever()`` and ``on_ready``:
.. literalinclude :: files/ros-hello-world-run-forever.py
:language: python
.. note::
The difference between ``run()`` and ``run_forever()`` is that the former
starts the event processing in a separate thread, while the latter
blocks the calling thread.
Disconnecting
-------------
Once your task is done, you should disconnect cleanly from ``rosbridge``. There are two related methods available for this:
- :meth:`roslibpy.Ros.close`: Disconnect the websocket connection. Once the connection is closed,
it is still possible to reconnect by calling :meth:`roslibpy.Ros.connect`: again.
- :meth:`roslibpy.Ros.terminate`: Terminate the main event loop. If the connection is still open,
it will first close it.
.. note::
Terminating the event loop is an irreversible action when using the ``twisted/authbahn`` loop because ``twisted``
reactors cannot be restarted. This operation should be reserved to be executed at the very end of your program.
Reconnecting
------------
If ``rosbridge`` is not responsive when the connection is started or if an established connection drops uncleanly, ``roslibpy``
will try to reconnect automatically, and reconnect subscriber and publisher topics as well. Reconnect will be retried
with an exponential back-off.
Hello World: Topics
-------------------
The ``Hello world`` of ROS is to start two nodes that communicate using
topic subscription/publishing. The nodes (a talker and a listener) are
extremely simple but they exemplify a distributed system with communication
between two processes over the ROS infrastructure.
Writing the talker node
^^^^^^^^^^^^^^^^^^^^^^^
The following example starts a ROS node and begins to publish
messages in loop (to terminate, press ``ctrl+c``):
.. literalinclude :: files/ros-hello-world-talker.py
:language: python
* :download:`ros-hello-world-talker.py <files/ros-hello-world-talker.py>`
Writing the listener node
^^^^^^^^^^^^^^^^^^^^^^^^^
Now let's move on to the listener side:
.. literalinclude :: files/ros-hello-world-listener.py
:language: python
* :download:`ros-hello-world-listener.py <files/ros-hello-world-listener.py>`
Running the example
^^^^^^^^^^^^^^^^^^^
Open a command prompt and start the talker:
::
python ros-hello-world-talker.py
Now open a second command prompt and start the listener:
::
python ros-hello-world-listener.py
.. note::
It is not relevant where the files are located. They can be in different
folders or even in different computers as long as the ROS instance is the same.
Using services
--------------
Another way for nodes to communicate between each other is through ROS Services.
Services require the definition of request and response types so the following
example shows how to use an existing service called ``get_loggers``:
.. literalinclude :: files/ros-service-call-logger.py
:language: python
* :download:`ros-service-call-logger.py <files/ros-service-call-logger.py>`
Creating services
-----------------
It is also possible to create new services, as long as the service type
definition is present in your ROS environment.
The following example shows how to create a simple service that uses
one of the standard service types defined in ROS (``std_srvs/SetBool``):
.. literalinclude :: files/ros-service.py
:language: python
* :download:`ros-service.py <files/ros-service.py>`
Download it and run it from the command prompt typing::
$ python ros-service.py
The service will be active while the program is running (to terminate,
press ``ctrl+c``).
Leave this service running and download and run the following service calling
code example to verify the service is working:
* :download:`ros-service-call-set-bool.py <files/ros-service-call-set-bool.py>`
Download it and run it from the command prompt typing::
$ python ros-service-call-set-bool.py
.. note::
Now that you have a grasp of the basics of ``roslibpy``,
check out more details in the :ref:`ros-api-reference`.
Actions
-------
Besides Topics and Services, ROS provides **Actions**, which are intended for
long-running tasks, such as navigation, because they are non-blocking and allow
the cancellation (preempting) of an action while it is executing.
``roslibpy`` supports both consuming actions (i.e. action clients) and also
providing actions, through the :class:`roslibpy.actionlib.SimpleActionServer`.
The following examples use the **Fibonacci** action, which is defined in the
`actionlib_tutorials <http://wiki.ros.org/actionlib_tutorials>`_.
Action servers
^^^^^^^^^^^^^^
Let's start with the definition of the fibonacci server:
.. literalinclude :: files/ros-action-server.py
:language: python
* :download:`ros-action-server.py <files/ros-action-server.py>`
Download it and run it from the command prompt typing::
$ python ros-action-server.py
The action server will be active while the program is running (to terminate,
press ``ctrl+c``).
Leave this window running if you want to test it with the next example.
Action clients
^^^^^^^^^^^^^^
Now let's see how to write an action client for our newly created server.
The following program shows a simple action client:
.. literalinclude :: files/ros-action-client.py
:language: python
* :download:`ros-action-client.py <files/ros-action-client.py>`
Download it and run it from the command prompt typing::
$ python ros-action-client.py
You will immediately see all the intermediate calculations of our action server,
followed by a line indicating the resulting fibonacci sequence.
This example is very simplified and uses the :meth:`roslibpy.actionlib.Goal.wait`
function to make the code easier to read as an example. A more robust way to handle
results is to hook up to the ``result`` event with a callback.
Querying ROS API
----------------
ROS provides an API to inspect topics, services, nodes and much more. This API can be
used programmatically from Python code, and also be invoked from the command line.
Usage from the command-line
^^^^^^^^^^^^^^^^^^^^^^^^^^^
The command line mimics closely that of ROS itself.
The following commands are available::
$ roslibpy topic list
$ roslibpy topic type /rosout
$ roslibpy topic find std_msgs/Int32
$ roslibpy msg info rosgraph_msgs/Log
$ roslibpy service list
$ roslibpy service type /rosout/get_loggers
$ roslibpy service find roscpp/GetLoggers
$ roslibpy srv info roscpp/GetLoggers
$ roslibpy param list
$ roslibpy param set /foo "[\"1\", 1, 1.0]"
$ roslibpy param get /foo
$ roslibpy param delete /foo
Usage from Python code
^^^^^^^^^^^^^^^^^^^^^^
And conversely, the following methods allow to query the ROS API from Python code.
Topics
""""""
* :meth:`roslibpy.Ros.get_topics`
* :meth:`roslibpy.Ros.get_topic_type`
* :meth:`roslibpy.Ros.get_topics_for_type`
* :meth:`roslibpy.Ros.get_message_details`
Services
""""""""
* :meth:`roslibpy.Ros.get_services`
* :meth:`roslibpy.Ros.get_service_type`
* :meth:`roslibpy.Ros.get_services_for_type`
* :meth:`roslibpy.Ros.get_service_request_details`
* :meth:`roslibpy.Ros.get_service_response_details`
Params
""""""
* :meth:`roslibpy.Ros.get_params`
* :meth:`roslibpy.Ros.get_param`
* :meth:`roslibpy.Ros.set_param`
* :meth:`roslibpy.Ros.delete_param`
Time
""""
* :meth:`roslibpy.Ros.get_time`
Advanced examples
-----------------
The following list is a compilation of more elaborate examples of the usage of ``roslibpy``.
We encourage everyone to submit suggestions for new examples, either send a pull request or request it via the issue tracker.
.. toctree::
:maxdepth: 2
:glob:
examples/*
| /roslibpy-1.5.0.tar.gz/roslibpy-1.5.0/docs/examples.rst | 0.926204 | 0.783906 | examples.rst | pypi |
from .registry import converts_from_numpy, converts_to_numpy
from geometry_msgs.msg import Transform, Vector3, Quaternion, Point, Pose
from . import numpify
import numpy as np
# basic types
@converts_to_numpy(Vector3)
def vector3_to_numpy(msg, hom=False):
if hom:
return np.array([msg.x, msg.y, msg.z, 0])
else:
return np.array([msg.x, msg.y, msg.z])
@converts_from_numpy(Vector3)
def numpy_to_vector3(arr):
if arr.shape[-1] == 4:
assert np.all(arr[...,-1] == 0)
arr = arr[...,:-1]
if len(arr.shape) == 1:
return Vector3(*arr)
else:
return np.apply_along_axis(lambda v: Vector3(*v), axis=-1, arr=arr)
@converts_to_numpy(Point)
def point_to_numpy(msg, hom=False):
if hom:
return np.array([msg.x, msg.y, msg.z, 1])
else:
return np.array([msg.x, msg.y, msg.z])
@converts_from_numpy(Point)
def numpy_to_point(arr):
if arr.shape[-1] == 4:
arr = arr[...,:-1] / arr[...,-1]
if len(arr.shape) == 1:
return Point(*arr)
else:
return np.apply_along_axis(lambda v: Point(*v), axis=-1, arr=arr)
@converts_to_numpy(Quaternion)
def quat_to_numpy(msg):
return np.array([msg.x, msg.y, msg.z, msg.w])
@converts_from_numpy(Quaternion)
def numpy_to_quat(arr):
assert arr.shape[-1] == 4
if len(arr.shape) == 1:
return Quaternion(*arr)
else:
return np.apply_along_axis(lambda v: Quaternion(*v), axis=-1, arr=arr)
# compound types
# all of these take ...x4x4 homogeneous matrices
@converts_to_numpy(Transform)
def transform_to_numpy(msg):
from . import transformations
return np.dot(
transformations.translation_matrix(numpify(msg.translation)),
transformations.quaternion_matrix(numpify(msg.rotation))
)
@converts_from_numpy(Transform)
def numpy_to_transform(arr):
from . import transformations
shape, rest = arr.shape[:-2], arr.shape[-2:]
assert rest == (4,4)
if len(shape) == 0:
trans = transformations.translation_from_matrix(arr)
quat = transformations.quaternion_from_matrix(arr)
return Transform(
translation=Vector3(*trans),
rotation=Quaternion(*quat)
)
else:
res = np.empty(shape, dtype=np.object_)
for idx in np.ndindex(shape):
res[idx] = Transform(
translation=Vector3(*transformations.translation_from_matrix(arr[idx])),
rotation=Quaternion(*transformations.quaternion_from_matrix(arr[idx]))
)
@converts_to_numpy(Pose)
def pose_to_numpy(msg):
from . import transformations
return np.dot(
transformations.translation_matrix(numpify(msg.position)),
transformations.quaternion_matrix(numpify(msg.orientation))
)
@converts_from_numpy(Pose)
def numpy_to_pose(arr):
from . import transformations
shape, rest = arr.shape[:-2], arr.shape[-2:]
assert rest == (4,4)
if len(shape) == 0:
trans = transformations.translation_from_matrix(arr)
quat = transformations.quaternion_from_matrix(arr)
return Pose(
position=Vector3(*trans),
orientation=Quaternion(*quat)
)
else:
res = np.empty(shape, dtype=np.object_)
for idx in np.ndindex(shape):
res[idx] = Pose(
position=Vector3(*transformations.translation_from_matrix(arr[idx])),
orientation=Quaternion(*transformations.quaternion_from_matrix(arr[idx]))
) | /rosnumpy-0.0.5.2-py3-none-any.whl/ros_numpy/geometry.py | 0.466846 | 0.514888 | geometry.py | pypi |
import roslib.message
import rospy
import re
import base64
import sys
python3 = True if sys.hexversion > 0x03000000 else False
python_to_ros_type_map = {
'bool' : ['bool'],
'int' : ['int8', 'byte', 'uint8', 'char',
'int16', 'uint16', 'int32', 'uint32',
'int64', 'uint64', 'float32', 'float64'],
'float' : ['float32', 'float64'],
'str' : ['string'],
'unicode' : ['string'],
'long' : ['uint64']
}
if python3:
python_string_types = [str]
else:
python_string_types = [str, unicode]
python_list_types = [list, tuple]
ros_time_types = ['time', 'duration']
ros_primitive_types = ['bool', 'byte', 'char', 'int8', 'uint8', 'int16',
'uint16', 'int32', 'uint32', 'int64', 'uint64',
'float32', 'float64', 'string']
ros_header_types = ['Header', 'std_msgs/Header', 'roslib/Header']
ros_binary_types_regexp = re.compile(r'(uint8|char)\[[^\]]*\]')
list_brackets = re.compile(r'\[[^\]]*\]')
def convert_dictionary_to_ros_message(message_type, dictionary, kind='message', strict_mode=True):
"""
Takes in the message type and a Python dictionary and returns a ROS message.
Example:
message_type = "std_msgs/String"
dict_message = { "data": "Hello, Robot" }
ros_message = convert_dictionary_to_ros_message(message_type, dict_message)
message_type = "std_srvs/SetBool"
dict_message = { "data": True }
kind = "request"
ros_message = convert_dictionary_to_ros_message(message_type, dict_message, kind)
"""
if kind == 'message':
message_class = roslib.message.get_message_class(message_type)
message = message_class()
elif kind == 'request':
service_class = roslib.message.get_service_class(message_type)
message = service_class._request_class()
elif kind == 'response':
service_class = roslib.message.get_service_class(message_type)
message = service_class._response_class()
else:
raise ValueError('Unknown kind "%s".' % kind)
message_fields = dict(_get_message_fields(message))
for field_name, field_value in dictionary.items():
if field_name in message_fields:
field_type = message_fields[field_name]
field_value = _convert_to_ros_type(field_type, field_value)
setattr(message, field_name, field_value)
else:
error_message = 'ROS message type "{0}" has no field named "{1}"'\
.format(message_type, field_name)
if strict_mode:
raise ValueError(error_message)
else:
rospy.logerr('{}! It will be ignored.'.format(error_message))
return message
def _convert_to_ros_type(field_type, field_value):
if is_ros_binary_type(field_type, field_value):
field_value = _convert_to_ros_binary(field_type, field_value)
elif field_type in ros_time_types:
field_value = _convert_to_ros_time(field_type, field_value)
elif field_type in ros_primitive_types:
field_value = _convert_to_ros_primitive(field_type, field_value)
elif _is_field_type_a_primitive_array(field_type):
field_value = field_value
elif _is_field_type_an_array(field_type):
field_value = _convert_to_ros_array(field_type, field_value)
else:
field_value = convert_dictionary_to_ros_message(field_type, field_value)
return field_value
def _convert_to_ros_binary(field_type, field_value):
if type(field_value) in python_string_types:
binary_value_as_string = base64.standard_b64decode(field_value)
else:
binary_value_as_string = str(bytearray(field_value))
return binary_value_as_string
def _convert_to_ros_time(field_type, field_value):
time = None
if field_type == 'time' and field_value == 'now':
time = rospy.get_rostime()
else:
if field_type == 'time':
time = rospy.rostime.Time()
elif field_type == 'duration':
time = rospy.rostime.Duration()
if 'secs' in field_value:
setattr(time, 'secs', field_value['secs'])
if 'nsecs' in field_value:
setattr(time, 'nsecs', field_value['nsecs'])
return time
def _convert_to_ros_primitive(field_type, field_value):
# std_msgs/msg/_String.py always calls encode() on python3, so don't do it here
if field_type == "string" and not python3:
field_value = field_value.encode('utf-8')
return field_value
def _convert_to_ros_array(field_type, list_value):
list_type = list_brackets.sub('', field_type)
return [_convert_to_ros_type(list_type, value) for value in list_value]
def convert_ros_message_to_dictionary(message):
"""
Takes in a ROS message and returns a Python dictionary.
Example:
ros_message = std_msgs.msg.String(data="Hello, Robot")
dict_message = convert_ros_message_to_dictionary(ros_message)
"""
dictionary = {}
message_fields = _get_message_fields(message)
for field_name, field_type in message_fields:
field_value = getattr(message, field_name)
dictionary[field_name] = _convert_from_ros_type(field_type, field_value)
return dictionary
def _convert_from_ros_type(field_type, field_value):
if is_ros_binary_type(field_type, field_value):
field_value = _convert_from_ros_binary(field_type, field_value)
elif field_type in ros_time_types:
field_value = _convert_from_ros_time(field_type, field_value)
elif field_type in ros_primitive_types:
field_value = field_value
elif _is_field_type_a_primitive_array(field_type):
field_value = list(field_value)
elif _is_field_type_an_array(field_type):
field_value = _convert_from_ros_array(field_type, field_value)
else:
field_value = convert_ros_message_to_dictionary(field_value)
return field_value
def is_ros_binary_type(field_type, field_value):
""" Checks if the field is a binary array one, fixed size or not
is_ros_binary_type("uint8", 42)
>>> False
is_ros_binary_type("uint8[]", [42, 18])
>>> True
is_ros_binary_type("uint8[3]", [42, 18, 21]
>>> True
is_ros_binary_type("char", 42)
>>> False
is_ros_binary_type("char[]", [42, 18])
>>> True
is_ros_binary_type("char[3]", [42, 18, 21]
>>> True
"""
return re.search(ros_binary_types_regexp, field_type) is not None
def _convert_from_ros_binary(field_type, field_value):
field_value = base64.standard_b64encode(field_value).decode('utf-8')
return field_value
def _convert_from_ros_time(field_type, field_value):
field_value = {
'secs' : field_value.secs,
'nsecs' : field_value.nsecs
}
return field_value
def _convert_from_ros_array(field_type, field_value):
list_type = list_brackets.sub('', field_type)
return [_convert_from_ros_type(list_type, value) for value in field_value]
def _get_message_fields(message):
return zip(message.__slots__, message._slot_types)
def _is_field_type_an_array(field_type):
return list_brackets.search(field_type) is not None
def _is_field_type_a_primitive_array(field_type):
list_type = list_brackets.sub('', field_type)
return list_type in ros_primitive_types | /rospy_message_converter-0.5.2.tar.gz/rospy_message_converter-0.5.2/src/rospy_message_converter/message_converter.py | 0.428233 | 0.192103 | message_converter.py | pypi |
from typing import Literal
AllLiteral = Literal["all"]
AnyLiteral = Literal["any"]
ARPLiteral = Literal[
"disabled", "enabled", "local-proxy-arp", "proxy-arp", "reply-only"
]
IPProtocol = Literal[
"dccp",
"ddp",
"egp",
"encap",
"etherip",
"ggp",
"gre",
"hmp",
"icmp",
"icmpv6",
"idpr-cmtp",
"igmp",
"ipencap",
"ipip",
"ipsec-ah",
"ipsec-esp",
"ipv6-encap",
"ipv6-frag",
"ipv6-nonxt",
"ipv6-opts",
"ipv6-route",
"iso-tp4",
"l2tp",
"ospf",
"pim",
"pup",
"rdp",
"rspf",
"rsvp",
"sctp",
"st",
"tcp",
"udp",
"udp-lite",
"vmtp",
"vrrp",
"xns-idp",
"xtp",
]
MACProtocol = Literal[
"802.2",
"arp",
"homeplug-av",
"ip",
"ipv6",
"ipx",
"lldp",
"loop-protect",
"mpls-multicast",
"mpls-unicast",
"packing-compr",
"packing-simple",
"pppoe",
"pppoe-discovery",
"rarp",
"service-vlan",
"vlan",
]
PortLiteral = Literal[
"acap",
"activision",
"afpovertcp",
"agentx",
"aol",
"apple-licman",
"appleqtc",
"appleqtcsrvr",
"appleugcontrol",
"arcp",
"asia",
"asip-webadmin",
"asipregistry",
"aurp",
"auth",
"avt-profile-1",
"avt-profile-2",
"bdp",
"bftp",
"bgp",
"biff",
"bootpc",
"bootps",
"btserv",
"buddyphone",
"ccmail",
"cfdptkt",
"chargen",
"cops",
"cpq-wbem",
"csnet-ns",
"daytime",
"dict",
"discard",
"discovery",
"distributed-net",
"dixie",
"dlsrap",
"dlsrpn",
"dlswpn",
"dns",
"dns2go",
"doom",
"dsp",
"dtspcd",
"echo",
"epmap",
"eppc",
"esro-emsdp",
"esro-gen",
"etftp",
"fcp-addr-srvr1",
"fcp-addr-srvr2",
"fcp-cics-gw1",
"fcp-srvr-inst1",
"fcp-srvr-inst2",
"finger",
"ftp",
"ftp-data",
"glimpse",
"gopher",
"h323gatestat",
"h323hostcall",
"half-life",
"hbci",
"hostname",
"hotsync-1",
"hotsync-2",
"hsrp",
"htcp",
"http",
"http-alt",
"https",
"ica",
"icabrowser",
"icpv2",
"icq",
"imail-www",
"imap3",
"imaps",
"ipp",
"irc",
"ircu",
"isakmp",
"iso-tsap",
"kerberos",
"klogin",
"l2tp",
"ldap",
"ldaps",
"link",
"linuxconf",
"liquidaudio",
"lotusnote",
"lpr",
"mac-srvr-admin",
"madcap",
"matip-type-a",
"matip-type-b",
"mc-ftp",
"mgcp-callagent",
"mgcp-gateway",
"microcom-sbp",
"mobileip",
"mountd",
"mpp",
"ms-rpc",
"ms-sql-m",
"ms-sql-s",
"ms-streaming",
"ms-wbt-server",
"msbd",
"msg-auth",
"msg-icp",
"msql",
"mtp",
"mysql",
"mzap",
"name",
"napster",
"napster-2",
"napster-3",
"net-assistant",
"netbios-dgm",
"netbios-ns",
"netbios-ssn",
"netrek",
"netstat",
"nextstep",
"nfile",
"nfs",
"nicname",
"nntp",
"nntps",
"ntp",
"odette-ftp",
"odmr",
"oracle-sql",
"pcanywheredata",
"pcanywherestat",
"pdap-np",
"pgp5-key",
"photuris",
"pop2",
"pop3",
"pop3s",
"poppassd",
"pptp",
"prospero-np",
"pwdgen",
"qotd",
"quake",
"quake-world",
"quake3",
"radius",
"radius-acct",
"rap",
"re-mail-ck",
"realsecure",
"reftek",
"rip",
"ripng",
"rje",
"rlogin",
"rlp",
"rrp",
"rsvp-tunnel",
"rtp",
"rtsp",
"rwhois",
"rwp",
"secureid",
"sftp",
"sgmp",
"sift-uft",
"sip",
"slmail",
"smb",
"smtp",
"smux",
"snmp",
"snpp",
"socks",
"sql*net",
"sql-net",
"squid",
"ssh",
"statsrv",
"sunrpc",
"supdup",
"swat",
"syslog",
"systat",
"t.120",
"tacacs",
"talk",
"tcp-id-port",
"tcpmux",
"telnet",
"tftp",
"tftp-mcast",
"timbuktu",
"timbuktu-srv1",
"timbuktu-srv2",
"timbuktu-srv3",
"timbuktu-srv4",
"time",
"tinc",
"tlisrv",
"uls",
"unreal",
"uucp-path",
"vemmi",
"veracity",
"virtualuser",
"vmnet",
"vnc-1",
"vnc-2",
"webobjects",
"whois++",
"winbox",
"winbox-old",
"winbox-old-tls",
"wingate",
"wlbs",
"x11",
"xdmcp",
"yahoo",
"z39.50",
]
TCPState = Literal[
"close",
"close-wait",
"established",
"fin-wait",
"last-ack",
"listen",
"none",
"syn-recv",
"syn-sent",
"time-wait",
] | /rosrestpy-0.10.0.tar.gz/rosrestpy-0.10.0/ros/_literals.py | 0.476336 | 0.291233 | _literals.py | pypi |
try:
import ujson as json
except ImportError:
import json # type: ignore[no-redef]
from attr import define
from requests import Session
from requests.auth import HTTPBasicAuth
from typing import Any, Dict, List, Type, TypeVar
from . import (
InterfaceModule,
IPModule,
PPPModule,
QueueModule,
RoutingModule,
SystemModule,
ToolModule,
UserModule,
)
from . import Error, Log
from .inteface import BridgeModule
from ._utils import clean_data, clean_filters, make_converter
_converter = make_converter()
T = TypeVar("T", bound=object)
@define
class BaseRos:
server: str
username: str
password: str
session: Session = Session()
secure: bool = False
filename: str = "rest"
url: str = ""
def __attrs_post_init__(self) -> None:
if not self.server.endswith("/"):
self.server += "/"
# Authentication to the REST API is performed via HTTP Basic Auth.
self.session.auth = HTTPBasicAuth(self.username, self.password)
self.session.verify = self.secure
self.password = ""
self.url = self.server + self.filename
def get_as(self, filename: str, cl: Type[T], filters: Dict[str, Any] = None) -> T:
"""To get the records.
Args:
filename (str): Path
cl (Type[T]): Class
filters (Dict[str, Any], optional): Query for specific obj. Defaults to None.
Raises:
_converter.structure: Error parser
e: Exception
Returns:
T: Object of cl
"""
res = self.session.get(
self.url + filename,
params=clean_filters(filters),
verify=self.secure,
)
odata = json.loads(res.text)
data: Any = clean_data(odata)
if data and "error" in data:
raise _converter.structure(data, Error)
try:
return _converter.structure(data, cl)
except Exception as e:
raise e
def post_as(
self,
filename: str,
cl: Type[T],
json_: Any = None,
data: Any = None,
) -> T:
"""Universal method to get access to all console commands.
Args:
filename (str): Path
cl (Type[T]): Class of the should be returned object
json_ (Any, optional): data to be sent in json format. Defaults to None.
data (Any, optional): data to be sent in form format. Defaults to None.
Raises:
_converter.structure: Error parser
Returns:
T: Object of cl
"""
res = self.session.post(
self.url + filename,
data=data,
json=json_,
)
odata = json.loads(res.text)
data = clean_data(odata)
if data and "error" in data:
raise _converter.structure(data, Error)
return _converter.structure(data, cl)
def patch_as(
self,
filename: str,
cl: Type[T],
json_: Any = None,
data: Any = None,
) -> T:
"""To update a single record.
Args:
filename (str): Path
cl (Type[T]): Class of object that should be returned
json_ (Any, optional): data to be sent in json format. Defaults to None.
data (Any, optional): data to be sent in form format. Defaults to None.
Raises:
_converter.structure: Error parser
Returns:
T: Object of cl
"""
res = self.session.patch(
self.url + filename,
data=data,
json=json_,
)
odata = json.loads(res.text)
data = clean_data(odata)
if data and "error" in data:
raise _converter.structure(data, Error)
return _converter.structure(data, cl)
def put_as(
self,
filename: str,
cl: Type[T],
json_: Any = None,
data: Any = None,
) -> T:
"""To create a new record.
Args:
filename (str): Path
cl (Type[T]): Class of object that should be returned
json_ (Any, optional): data to be sent in json format. Defaults to None.
data (Any, optional): data to be sent in form format. Defaults to None.
Raises:
_converter.structure: Error parser
Returns:
T: Object of cl
"""
res = self.session.put(
self.url + filename,
data=data,
json=json_,
)
odata = json.loads(res.text)
data = clean_data(odata)
if data and "error" in data:
raise _converter.structure(data, Error)
return _converter.structure(data, cl)
class Ros(BaseRos):
_interface: InterfaceModule = None
_ip: IPModule = None
_ppp: PPPModule = None
_queue: QueueModule = None
_routing: RoutingModule = None
_system: SystemModule = None
_tool: ToolModule = None
_user: UserModule = None
"""
Ros class that represent a routeros device.
Attributes
----------
:param str server: The device's Rest API url, example https://192.168.88.1/
:param str username: Username
:param str password: Password
:param requests.Session session: A requests.Session instance
:param bool secure: Valdiate ssl cert
:param str filename: Base filename of the rest API, default to `rest`
:param str url: The device's Rest API url with base filename, default to https://server/rest
"""
@property
def bridge(self) -> BridgeModule:
"""/interface/bridge"""
return self.interface.bridge
@property
def wireguard(self):
"""/interface/wireguard"""
return self.interface.wireguard
@property
def interface(self):
"""/interface"""
if not self._interface:
self._interface = InterfaceModule(self)
return self._interface
@property
def ip(self):
"""/ip"""
if not self._ip:
self._ip = IPModule(self)
return self._ip
@property
def ppp(self):
"""/ppp"""
if not self._ppp:
self._ppp = PPPModule(self)
return self._ppp
@property
def queue(self):
"""/queue"""
if not self._queue:
self._queue = QueueModule(self)
return self._queue
@property
def routing(self):
"""/routing"""
if not self._routing:
self._routing = RoutingModule(self)
return self._routing
@property
def system(self):
"""/system"""
if not self._system:
self._system = SystemModule(self)
return self._system
@property
def tool(self):
"""/tool"""
if not self._tool:
self._tool = ToolModule(self, "/tool")
return self._tool
@property
def user(self):
"""/user"""
if not self._user:
self._user = UserModule(self, "/user")
return self._user
def log(self, **kwds: Any):
"""Get logs"""
return self.get_as("/log", List[Log], kwds)
def ping(self, address: str, count: int = 4):
return self.tool.ping(address, count) | /rosrestpy-0.10.0.tar.gz/rosrestpy-0.10.0/ros/ros.py | 0.779532 | 0.207797 | ros.py | pypi |
from typing import List, Literal, Union
from ros._base import BaseModule, BaseProps
from ros._literals import AnyLiteral, IPProtocol, MACProtocol, PortLiteral
from .bandwith_server import BandwithServer
from .bandwith_test import BandwithTest
from .ip_scan import IPScan
from .netwatch import Netwatch
from .ping import Ping
from .profile import Profile
from .torch import Torch
from .traceroute import Traceroute
class ToolModule(BaseModule):
_netwatch: BaseProps[Netwatch] = None
@property
def bandwith_server(self) -> BandwithServer:
return self.ros.get_as(self.url + "/bandwidth-server", BandwithServer)
def ping(
self,
address: str,
count: int = 4,
interface: str = None,
arp_ping: bool = False,
src_address: str = None,
size: int = 56,
dscp: int = 0,
ttl: int = 0,
vrf: str = "main",
):
data = {
"address": address,
"count": count,
"arp-ping": arp_ping,
"size": size,
"dscp": dscp,
"vrf": vrf,
}
if interface:
data["interface"] = interface
if src_address:
data["src-address"] = src_address
if ttl > 0:
data["ttl"] = ttl
return self.ros.post_as("/ping", List[Ping], data)
def profile(
self,
cpu: Literal["total", "all"] = "total",
duration: str = "5s",
) -> List[Profile]:
data = {"cpu": cpu, "duration": duration}
return self.ros.post_as("/tool/profile", List[Profile], data)
def bandwith_test(
self,
address: str,
duration: str,
user: str = None,
password: str = None,
protocol: Literal["tcp", "udp"] = "udp",
direction: Literal["receive", "send", "both"] = "receive",
random_data: bool = False,
) -> List[BandwithTest]:
data = {
"address": address,
"duration": duration,
"user": user,
"password": password,
"protocol": protocol,
"direction": direction,
"random-data": random_data,
}
return self.ros.post_as(self.url + "/bandwidth-test", List[BandwithTest], data)
def ip_scan(
self,
interface: str,
duration: str,
address_range: str = None,
freeze_frame_interval: str = None,
) -> List[IPScan]:
data = {"interface": interface, "duration": duration}
if address_range:
data["address-range"] = address_range
if freeze_frame_interval:
data["freeze-frame-interval"] = freeze_frame_interval
return self.ros.post_as(self.url + "/ip-scan", List[IPScan], data)
@property
def netwatch(self):
if not self._netwatch:
self._netwatch = BaseProps(self.ros, "/tool/netwatch", Netwatch)
return self._netwatch
def torch(
self,
interface: str,
duration: str = "5s",
src_address: str = "0.0.0.0/0",
dst_address: str = "0.0.0.0/0",
src_address6: str = "::/0",
dst_address6: str = "::/0",
mac_protocol: Union[AnyLiteral, MACProtocol] = None,
port: Union[AnyLiteral, PortLiteral] = None,
ip_protocol: Union[AnyLiteral, IPProtocol] = None,
vlan_id: Union[AnyLiteral, int] = None,
dscp: Union[AnyLiteral, int] = None,
cpu: str = None,
freeze_frame_interval: str = None,
):
data = {"interface": interface, "duration": duration}
if src_address:
data["src-address"] = src_address
if dst_address:
data["dst-address"] = dst_address
if src_address6:
data["src-address6"] = src_address6
if dst_address6:
data["dst-address6"] = dst_address6
if mac_protocol:
data["mac-protocol"] = mac_protocol
if port:
data["port"] = port
if ip_protocol:
data["ip-protocol"] = ip_protocol
if vlan_id:
data["vlan-id"] = vlan_id
if dscp:
data["dscp"] = dscp
if cpu:
data["cpu"] = cpu
if freeze_frame_interval:
data["freeze-frame-interval"] = freeze_frame_interval
return self.ros.post_as(self.url + "/torch", List[Torch], data)
def traceroute(
self,
address: str,
duration: str = "5s",
size: int = 56,
timeout: str = "1000ms",
protocol: str = "icmp",
port: int = "33434",
use_dns: bool = False,
count: int = None,
max_hops: int = None,
src_address: str = None,
interface: str = None,
dscp: int = 0,
vrf: str = "main",
) -> List[Traceroute]:
data = {
"address": address,
"duration": duration,
"size": size,
"timeout": timeout,
"protocol": protocol,
"port": port,
"use-dns": use_dns,
"dscp": dscp,
"vrf": vrf,
}
if count and count > 0:
data["count"] = count
if max_hops and max_hops > 0:
data["max-hops"] = max_hops
if interface:
data["interface"] = interface
if src_address:
data["src-address"] = src_address
return self.ros.post_as(self.url + "/traceroute", List[Traceroute], data)
def torch(
self,
interface: str,
duration: str = "3s",
src_address: str = "0.0.0.0/0",
dst_address: str = "0.0.0.0/0",
src_address6: str = "::/0",
dst_address6: str = "::/0",
mac_protocol: Union[AnyLiteral, MACProtocol] = "any",
ip_protocol: Union[AnyLiteral, IPProtocol] = "any",
port: PortLiteral = "any",
vlan_id: Union[AnyLiteral, int] = "any",
dscp: Union[AnyLiteral, int] = "any",
cpu: Union[AnyLiteral, int] = "any",
freeze_frame_interval: str = None,
) -> List[Torch]:
data = {
"interface": interface,
"dst-address": dst_address,
"mac-protocol": mac_protocol,
"src-address6": src_address6,
"cpu": cpu,
"dst-address6": dst_address6,
"port": port,
"vlan-id": vlan_id,
"dscp": dscp,
"duration": duration,
"ip-protocol": ip_protocol,
"src-address": src_address,
}
if freeze_frame_interval:
data["freeze-frame-interval"] = freeze_frame_interval
return self.ros.post_as(self.url + "/torch", List[Torch], data)
def wol(self, interface: str, mac: str) -> List[dict]:
data = {"interface": interface, "mac": mac}
return self.ros.post_as(self.url + "/wol", List[dict], data)
__all__ = [
"BandwithServer",
"BandwithTest",
"IPScan",
"Ping",
"ToolModule",
"Torch",
"Traceroute",
] | /rosrestpy-0.10.0.tar.gz/rosrestpy-0.10.0/ros/tool/__init__.py | 0.721841 | 0.223123 | __init__.py | pypi |
import numpy as np
import pandas as pd
from matplotlib import pyplot as plt
from scipy.interpolate import interp1d
from scipy.optimize import linprog
from statsmodels.distributions.empirical_distribution import ECDF
__all__ = ["in_hull", "transforms", "mapping", "sampler"]
def in_hull(points, x):
"""
Parameters
----------
points : TYPE
DESCRIPTION.
x : TYPE
DESCRIPTION.
Returns
-------
TYPE
DESCRIPTION.
"""
n_points = len(points)
n_dim = len(x)
c = np.zeros(n_points)
A = np.r_[points.T, np.ones((1, n_points))]
b = np.r_[x, np.ones(1)]
lp = linprog(c, A_eq=A, b_eq=b, method="interior-point")
return lp.success
def transforms(df, cols):
"""
Parameters
----------
df : TYPE
DESCRIPTION.
cols : TYPE
DESCRIPTION.
Returns
-------
CDF : TYPE
DESCRIPTION.
ICDF : TYPE
DESCRIPTION.
Examples
--------
>>> import pandas as pd
>>> import rossml as rsml
>>> df = pd.read_csv('xllaby_data-componentes.csv')
>>> df.fillna(value=df.describe().loc["mean"], inplace=True)
>>> CDF, ICDF = rsml.transforms(df, df.columns)
"""
CDF = [ECDF(df[col]) for col in cols]
ICDF = [
interp1d(
ECDF(df[col]).y,
ECDF(df[col]).x,
kind="zero",
bounds_error=False,
fill_value=(ECDF(df[col]).y[1], ECDF(df[col]).y[-2]),
)
for col in cols
]
return CDF, ICDF
def mapping(df, transform):
"""
Parameters
----------
df : TYPE
DESCRIPTION.
transform : TYPE
DESCRIPTION.
Returns
-------
df_transf : TYPE
DESCRIPTION.
Examples
--------
>>> import pandas as pd
>>> import rossml as rsml
>>> df = pd.read_csv('xllaby_data-componentes.csv')
>>> df.fillna(value=df.describe().loc["mean"], inplace=True)
>>> df_U = rsml.mapping(df, CDF)
>>> df_O = rsml.mapping(rsml.sampler(df_U, 500, 0.01), ICDF)
"""
N = len(df)
df_transf = pd.DataFrame(columns=df.columns)
df.replace([np.inf, -np.inf], np.nan, inplace=True)
if df.isnull().values.any():
df.dropna(inplace=True)
df = pd.concat([df, df.sample(n=N - len(df), replace=True)])
for transf, var in zip(transform, df.columns):
df_transf[var] = transf(df[var])
df_transf.replace([np.inf, -np.inf], np.nan, inplace=True)
if df_transf.isnull().values.any():
df_transf.dropna(inplace=True)
df_transf = pd.concat(
[df_transf, df_transf.sample(n=N - len(df_transf), replace=True)]
)
return df_transf
def sampler(df, samples, frac):
"""
Parameters
----------
df : TYPE
DESCRIPTION.
samples : TYPE
DESCRIPTION.
frac : TYPE
DESCRIPTION.
Returns
-------
TYPE
DESCRIPTION.
Examples
--------
>>> import pandas as pd
>>> import rossml as rsml
>>> df = pd.read_csv('xllaby_data-componentes.csv')
>>> df_new = rsml.sampler(df, 500, 0.01)
"""
samples = []
for i in range(samples):
weights = np.random.dirichlet(np.ones(int(frac * len(df))) / len(df))
samples.append(
df.sample(frac=int(frac * (len(df))) / len(df), replace=False).values.T.dot(
weights
)
)
return pd.DataFrame(np.array(samples), columns=df.columns) | /ross_ml-0.0.1-py3-none-any.whl/rossml/random_sampler.py | 0.668772 | 0.522872 | random_sampler.py | pypi |
import shutil
import webbrowser
from pathlib import Path
from pickle import dump, load
import numpy as np
import pandas as pd
from plotly import graph_objects as go
from plotly.figure_factory import create_scatterplotmatrix
from plotly.subplots import make_subplots
from scipy.stats import (chisquare, entropy, ks_2samp, normaltest, skew,
ttest_1samp, ttest_ind)
from sklearn.decomposition import PCA
from sklearn.feature_selection import (SelectKBest, f_regression,
mutual_info_regression)
from sklearn.metrics import (explained_variance_score, mean_absolute_error,
mean_squared_error, r2_score)
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import (MaxAbsScaler, MinMaxScaler, Normalizer,
PowerTransformer, QuantileTransformer,
RobustScaler, StandardScaler)
from sklearn.tree import DecisionTreeRegressor
from statsmodels.distributions.empirical_distribution import ECDF
from statsmodels.stats.diagnostic import het_breuschpagan
from tensorflow.keras.layers import Activation, Dense, Dropout
from tensorflow.keras.models import Sequential, load_model
from tensorflow.keras.optimizers import Adam
# fmt: on
__all__ = ["HTML_formater", "available_models", "Pipeline", "Model", "PostProcessing"]
def HTML_formater(df, name, file):
"""
Parameters
----------
df : pd.DataFrame
DESCRIPTION.
name : str
Neural network tag, indicating from which model it refers to.
file : str
The file name to save the DataFrame.
"""
path = Path(__file__).parent
html_string = """
<html>
<head><title>HTML Pandas Dataframe with CSS</title></head>
<link rel="stylesheet" type="text/css" href="css/panda_style.css"/>
<body>
{table}
</body>
</html>.
"""
with open(path / f"models/{name}/tables/{file}.html", "w") as f:
f.write(html_string.format(table=df.to_html(classes="mystyle")))
def available_models():
"""Check for available neural network models.
This function returns a list of all neural network models saved.
If None is available, it returns a message informing there's no models previously
saved.
Returns
-------
dirs : list
List of all neural network models saved.
"""
try:
path = Path(__file__).parent / "models"
dirs = [folder for folder in path.iterdir() if folder.is_dir()]
if len(dirs) == 0:
dirs = "No neural network models available."
except FileNotFoundError:
dirs = "No neural network models available."
return dirs
class Pipeline:
"""
Parameters
----------
df : pd.Dataframe
name : str
A tag for the neural network. This name is used to save the model, figures and
tables within a folder named after this string.
Examples
--------
>>> import pandas as pd
>>> import rossml as rsml
Importing and collecting data
>>> df = pd.read_csv('seal_fake.csv')
>>> df_val= pd.read_csv('xllaby_data-componentes.csv')
>>> df_val.fillna(df.mean)
>>> D = rsml.Pipeline(df)
>>> D.set_features(0, 20)
>>> D.set_labels(20, len(D.df.columns))
>>> D.feature_reduction(15)
>>> D.data_scaling(0.1, scalers=[RobustScaler(), RobustScaler()], scaling=True)
>>> D.build_Sequential_ANN(4, [50, 50, 50, 50])
>>> model, predictions = D.model_run(batch_size=300, epochs=1000)
Get the model configurations to change it afterwards
>>> # model.get_config()
>>> D.model_history()
>>> D.metrics()
Post-processing data
>>> results = D.postprocessing()
>>> fig = results.plot_overall_results()
>>> fig = results.plot_confidence_bounds(a = 0.01)
>>> fig = results.plot_standardized_error()
>>> fig = results.plot_qq()
Displays the HTML report
>>> url = 'results'
>>> # results.report(url)
>>> D.hypothesis_test()
>>> D.save()
>>> model = rsml.Model('Model')
>>> X = Pipeline(df_val).set_features(0,20)
>>> results = model.predict(X)
"""
def __init__(self, df, name="Model"):
path_model = Path(__file__).parent / f"models/{name}"
path_img = Path(__file__).parent / f"models/{name}/img"
path_table = Path(__file__).parent / f"models/{name}/tables"
if not path_model.exists():
path_model.mkdir()
path_img.mkdir()
path_table.mkdir()
self.df = df
self.df.dropna(inplace=True)
self.name = name
def set_features(self, start, end):
"""Select the features from the input DataFrame.
This methods takes the DataFrame and selects all the columns from "start"
to "end" values to indicate which columns should be treated as features.
Parameters
----------
start : int
Start column of dataframe features
end : int
End column of dataframe features
Returns
-------
x : pd.DataFrame
DataFrame with features parameters
Example
-------
"""
self.x = self.df[self.df.columns[start:end]]
self.columns = self.x.columns
return self.x
def set_labels(self, start, end):
"""Select the labels from the input DataFrame.
This methods takes the DataFrame and selects all the columns from "start"
to "end" values to indicate which columns should be treated as labels.
Parameters
----------
start : int
Start column of dataframe labels
end : int
End column of dataframe labels
Returns
-------
y : pd.DataFrame
DataFrame with labels parameters
Example
-------
"""
self.y = self.df[self.df.columns[start:end]]
return self.y
def feature_reduction(self, n):
"""
Parameters
----------
n : int
Number of relevant features.
Returns
-------
Minimum number of features that satisfies "n" for each label.
"""
# define the model
model = DecisionTreeRegressor()
# fit the model
model.fit(self.x, self.y)
# get importance
importance = model.feature_importances_
# summarize feature importance
featureScores = pd.concat(
[pd.DataFrame(self.x.columns), pd.DataFrame(importance)], axis=1
)
featureScores.columns = ["Specs", "Score"]
self.best = featureScores.nlargest(n, "Score")["Specs"].values
self.x = self.x[self.best]
return self.x
def data_scaling(self, test_size, scaling=False, scalers=None):
"""
Parameters
----------
test_size : float
Percentage of data destined for testing.
scaling : boolean, optional
Choose between scaling the data or not.
The default is False.
scalers : scikit-learn object
scikit-learn scalers.
Returns
-------
x_train : array
Features destined for training.
x_test : array
Features destined for test.
y_train : array
Labels destined for training.
y_test : array
Labels destined for test.
Examples
--------
"""
if scalers is None:
scalers = []
self.x_train, self.x_test, self.y_train, self.y_test = train_test_split(
self.x, self.y, test_size=test_size
)
if scaling:
if len(scalers) >= 1:
self.scaler1 = scalers[0]
self.x_train = self.scaler1.fit_transform(self.x_train)
self.x_test = self.scaler1.transform(self.x_test)
if len(scalers) == 2:
self.scaler2 = scalers[1]
self.y_train = self.scaler2.fit_transform(self.y_train)
self.y_test = self.scaler2.transform(self.y_test)
else:
self.scaler1 = None
self.scaler2 = None
return self.x_train, self.x_test, self.y_train, self.y_test
def build_Sequential_ANN(self, hidden, neurons, dropout_layers=None, dropout=None):
"""
Parameters
----------
hidden : int
Number of hidden layers.
neurons : list
Number of neurons per layer.
dropout_layers : list, optional
Dropout layers position.
The default is [].
dropout : list, optional
List with dropout values.
The default is [].
Returns
-------
model : keras neural network
"""
if dropout_layers is None:
dropout_layers = []
if dropout is None:
dropout = []
self.model = Sequential()
self.model.add(Dense(len(self.x.columns), activation="relu"))
j = 0 # Dropout counter
for i in range(hidden):
if i in dropout_layers:
self.model.add(Dropout(dropout[j]))
j += 1
self.model.add(Dense(neurons[i], activation="relu"))
self.model.add(Dense(len(self.y.columns)))
self.config = self.model.get_config()
return self.model
def model_run(self, optimizer="adam", loss="mse", batch_size=16, epochs=500):
"""
Parameters
----------
optimizer : string, optional
Choose a optimizer. The default is 'adam'.
loss : string, optional
Choose a loss. The default is 'mse'.
batch_size : int, optional
batch_size . The default is 16.
epochs : int, optional
Choose number of epochs. The default is 500.
Returns
-------
model : keras neural network
predictions :
"""
self.model.compile(optimizer=optimizer, loss=loss)
self.history = self.model.fit(
x=self.x_train,
y=self.y_train,
validation_data=(self.x_test, self.y_test),
batch_size=batch_size,
epochs=epochs,
)
self.predictions = self.model.predict(self.x_test)
self.train = pd.DataFrame(
self.scaler2.inverse_transform(self.predictions), columns=self.y.columns
)
self.test = pd.DataFrame(
self.scaler2.inverse_transform(self.y_test), columns=self.y.columns
)
return self.model, self.predictions
def model_history(self):
"""Plot model history.
Examples
--------
"""
path = Path(__file__).parent
hist = pd.DataFrame(self.history.history)
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="none",
)
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=list(range(hist["loss"].size)),
y=np.log10(hist["loss"]),
mode="lines",
line=dict(color="blue"),
name="Loss",
legendgroup="Loss",
hoverinfo="none",
)
)
fig.add_trace(
go.Scatter(
x=list(range(hist["val_loss"].size)),
y=np.log10(hist["val_loss"]),
mode="lines",
line=dict(color="orange"),
name="Val_loss",
legendgroup="Val_loss",
hoverinfo="none",
)
)
fig.update_xaxes(
title=dict(text="Epoch", font=dict(size=15)),
**axes_default,
)
fig.update_yaxes(
title=dict(text="Log<sub>10</sub>Loss", font=dict(size=15)),
**axes_default,
)
fig.update_layout(
plot_bgcolor="white",
legend=dict(
bgcolor="white",
bordercolor="black",
borderwidth=1,
),
)
fig.write_html(str(path / f"models/{self.name}/img/history.html"))
return fig
def metrics(self, save=False):
"""Print model metrics.
This function displays the model metrics while the neural network is being
built.
Prints
------
The mean absolute error (MAE).
The mean squared error (MSE).
The coefficient of determination (R-squared).
The adjusted coefficient of determination (adjusted R-squared).
The explained variance (discrepancy between a model and actual data).
"""
R2_a = 1 - (
(len(self.predictions) - 1)
* (1 - r2_score(self.y_test, self.predictions))
/ (len(self.predictions) - (1 + len(self.x.columns)))
)
MAE = mean_absolute_error(self.y_test, self.predictions)
MSE = mean_squared_error(self.y_test, self.predictions)
R2 = r2_score(self.y_test, self.predictions)
explained_variance = explained_variance_score(self.y_test, self.predictions)
metrics = pd.DataFrame(
np.round([MAE, MSE, R2, R2_a, explained_variance], 3),
index=["MAE", "MSE", "R2", "R2_adj", "explained variance"],
columns=["Metric"],
)
if save:
HTML_formater(metrics, self.name, "Metrics")
print(
"Scores:\nMAE: {}\nMSE: {}\nR^2:{}\nR^2 adjusted:{}\nExplained variance:{}".format(
MAE, MSE, R2, R2_a, explained_variance
)
)
def hypothesis_test(self, kind="ks", p_value=0.05, save=False):
"""Run a hypothesis test.
Parameters
----------
kind : string, optional
Hypothesis test kind. Options are:
"w": Welch test
Calculate the T-test for the means of two independent samples of
scores. This is a two-sided test for the null hypothesis that 2
independent samples have identical average (expected) values.
This test assumes that the populations have identical variances by
default.
"ks": Komolgorov-Smirnov test
Compute the Kolmogorov-Smirnov statistic on 2 samples. This is a
two-sided test for the null hypothesis that 2 independent samples
are drawn from the same continuous distribution.
The default is 'ks'.
* See scipy.stats.ks_2samp and scipy.stats.ttest_ind documentation for more
informations.
p_value : float, optional
Critical value. Must be within 0 and 1.
The default is 0.05.
save : boolean
If True, saves the hypothesis test. If False, the hypothesis_test won't be
saved.
Returns
-------
p_df : pd.DataFrame
Hypothesis test results.
Examples
--------
"""
if kind == "ks":
p_values = np.round(
[
ks_2samp(self.train[var], self.test[var]).pvalue
for var in self.train.columns
],
3,
)
p_df = pd.DataFrame(
p_values, index=self.test.columns, columns=["p-value: train"]
)
p_df["status"] = [
"Not Reject H0" if p > p_value else "Reject H0"
for p in p_df["p-value: train"]
]
if save:
HTML_formater(p_df, self.name, "KS Test")
elif kind == "w":
p_values = np.round(
[
ttest_ind(self.train[var], self.test[var], equal_var=False).pvalue
for var in self.train.columns
],
3,
)
p_df = pd.DataFrame(
p_values, index=self.train.columns, columns=["p-value: acc"]
)
p_df["status"] = [
"Not Reject H0" if p > p_value else "Reject H0"
for p in p_df["p-value: acc"]
]
if save:
HTML_formater(p_df, self.name, "Welch Test")
return p_df
def validation(self, x, y):
"""
Parameters
----------
x : pd.DataFrame
DESCRIPTION.
y : pd.DataFrame
DESCRIPTION.
Returns
-------
train : pd.DataFrame
DESCRIPTION.
test : pd.DataFrame
DESCRIPTION.
"""
self.test = y
if self.scaler1 is not None:
x_scaled = self.scaler1.transform(x.values.reshape(-1, len(x.columns)))
if self.scaler2 is not None:
self.train = pd.DataFrame(
self.scaler2.inverse_transform(self.model.predict(x_scaled)),
columns=y.columns,
)
else:
self.train = pd.DataFrame(self.model.predict(x_scaled), columns=y.columns)
return self.train, self.test
def postprocessing(self):
"""Create an instance to plot results for neural networks.
This method returns an instance from PostProcessing class. It allows plotting
some analyzes for neural networks and a HTML report with a result summary.
- plot_overall_results
- plot_confidence_bounds
- plot_qq
- plot_standardized_error
- plot_residuals_resume
- show
Returns
-------
results : PostProcessing object
An instance from PostProcessing class that allows plotting some analyzes
for neural networks.
Examples
--------
"""
results = PostProcessing(self.train, self.test, self.name)
return results
def save(self):
"""Save a neural netowork model.
Examples
--------
"""
path = Path(__file__).parent / f"models/{self.name}"
if not path.exists():
path.mkdir()
self.model.save(path / r"{}.h5".format(self.name))
dump(self.y.columns, open(path / r"{}_columns.pkl".format(self.name), "wb"))
dump(self.best, open(path / r"{}_best_features.pkl".format(self.name), "wb"))
dump(self.columns, open(path / r"{}_features.pkl".format(self.name), "wb"))
dump(
self.df.describe(), open(path / r"{}_describe.pkl".format(self.name), "wb")
)
if self.scaler1 is not None:
dump(self.scaler1, open(path / r"{}_scaler1.pkl".format(self.name), "wb"))
if self.scaler2 is not None:
dump(self.scaler2, open(path / r"{}_scaler2.pkl".format(self.name), "wb"))
class Model:
def __init__(self, name):
self.name = name
self.load()
def load(self):
"""Load a neural network model from rossml folder.
Examples
--------
"""
path = Path(__file__).parent / f"models/{self.name}"
self.model = load_model(path / r"{}.h5".format(self.name))
self.columns = load(open(path / r"{}_columns.pkl".format(self.name), "rb"))
self.features = load(open(path / r"{}_features.pkl".format(self.name), "rb"))
self.describe = load(open(path / r"{}_describe.pkl".format(self.name), "rb"))
# load best features
try:
self.best = load(
open(path / r"{}_best_features.pkl".format(self.name), "rb")
)
except:
self.best = None
# load the scaler
try:
self.scaler1 = load(open(path / r"{}_scaler1.pkl".format(self.name), "rb"))
except:
self.scaler1 = None
try:
self.scaler2 = load(open(path / r"{}_scaler2.pkl".format(self.name), "rb"))
except:
self.scaler2 = None
def predict(self, x):
"""
Parameters
----------
x : TYPE
DESCRIPTION.
Returns
-------
TYPE
DESCRIPTION.
"""
if self.best is None:
self.x = x
else:
self.x = x[self.best]
if len(self.x.shape) == 1:
self.x = self.x.values.reshape(1, -1)
if self.scaler1 is not None:
self.x = self.scaler1.transform(self.x)
else:
self.x = x
if self.scaler2 is not None:
predictions = self.model.predict(self.x)
self.results = pd.DataFrame(
self.scaler2.inverse_transform(predictions), columns=self.columns
)
else:
self.results = pd.DataFrame(predictions, columns=self.columns)
return self.results
def coefficients(self):
self.K = []
self.C = []
for results in self.results.values:
self.K.append(results[0:4].reshape(2, 2))
self.C.append(results[4:].reshape(2, 2))
return self.K, self.C
class PostProcessing:
def __init__(self, train, test, name):
self.train = train
self.test = test
self.test.index = self.train.index
self.name = name
def plot_overall_results(self, save_fig=False):
"""
Parameters
----------
save_fig : bool, optional
If save_fig is True, saves the result in img folder. If False, does not
save. The default is True.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
path = Path(__file__).parent
df = pd.concat([self.train, self.test], axis=0)
df["label"] = [
"train" if x < len(self.train) else "test" for x in range(len(df))
]
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="power",
zerolinecolor="lightgray",
)
fig = create_scatterplotmatrix(
df,
diag="box",
index="label",
title="",
)
fig.update_layout(
width=1500,
height=1500,
plot_bgcolor="white",
hovermode=False,
)
fig.update_xaxes(**axes_default)
fig.update_yaxes(**axes_default)
if save_fig:
fig.write_html(str(path / f"models/{self.name}/img/pairplot.html"))
return fig
def plot_confidence_bounds(self, a=0.01, percentile=0.05, save_fig=False):
"""Plot a confidence interval based on DKW inequality.
Parameters
----------
a : float
Significance level.A number between 0 and 1.
percentile : float, optional
Percentile to compute, which must be between 0 and 100 inclusive.
save_fig : bool, optional
If save_fig is True, saves the result in img folder. If False, does not
save. The default is True.
Returns
-------
figures : list
List of figures plotting DKW inequality for each variable in dataframe.
"""
path = Path(__file__).parent
P = np.arange(0, 100, percentile)
en = np.sqrt((1 / (2 * len(P))) * np.log(2 / a))
var = list(self.train.columns)
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="power",
)
figures = []
for v in var:
F = ECDF(self.train[v])
G = ECDF(self.test[v])
Gu = [min(Gn + en, 1) for Gn in G.y]
Gl = [max(Gn - en, 0) for Gn in G.y]
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=np.concatenate((G.x, G.x[::-1])),
y=np.concatenate((Gl, Gu[::-1])),
mode="lines",
line=dict(color="lightblue"),
fill="toself",
fillcolor="lightblue",
opacity=0.6,
name=f"{v} - {100 * (1 - percentile)}% Confidence Interval",
legendgroup=f"CI - {v}",
hoverinfo="none",
)
)
fig.add_trace(
go.Scatter(
x=G.x,
y=G.y,
mode="lines",
line=dict(color="darkblue", dash="dash"),
name=f"test {v}",
legendgroup=f"test {v}",
hoverinfo="none",
)
)
fig.add_trace(
go.Scatter(
x=F.x,
y=F.y,
mode="lines",
line=dict(color="magenta", width=2.0, dash="dot"),
name=f"test {v}",
legendgroup=f"train {v}",
hoverinfo="none",
)
)
fig.update_xaxes(
title=dict(text=f"{v}", font=dict(size=15)),
**axes_default,
)
fig.update_yaxes(
title=dict(text="Cumulative Distribution Function", font=dict(size=15)),
**axes_default,
)
fig.update_layout(
plot_bgcolor="white",
legend=dict(
bgcolor="white",
bordercolor="black",
borderwidth=1,
),
)
figures.append(fig)
if save_fig:
fig.write_html(str(path / f"models/{self.name}/img/CI_{v}.html"))
return figures
def plot_qq(self, save_fig=False):
"""
Parameters
----------
save_fig : bool, optional
If save_fig is True, saves the result in img folder. If False, does not
save. The default is True.
Returns
-------
figures : list
List of figures plotting quantile-quantile for each variable in dataframe.
"""
path = Path(__file__).parent
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="power",
)
figures = []
var = list(self.train.columns)
for v in var:
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=self.test[v],
y=self.train[v],
mode="markers",
marker=dict(size=8, color="orange"),
name=f"Test points - {v}",
legendgroup=f"Test points - {v}",
hovertemplate=(
f"{v}<sub>test</sub> : %{{x:.2f}}<br>{v}<sub>train</sub> : %{{y:.2f}}"
),
)
)
fig.add_trace(
go.Scatter(
x=self.test[v],
y=self.test[v],
mode="lines",
line=dict(color="blue", dash="dash"),
name="Y<sub>test</sub> = Y<sub>train</sub>",
legendgroup="test_test",
hoverinfo="none",
)
)
fig.update_xaxes(
title=dict(text=f"{v} <sub>test</sub>", font=dict(size=15)),
**axes_default,
)
fig.update_yaxes(
title=dict(text=f"{v} <sub>train</sub>", font=dict(size=15)),
**axes_default,
)
fig.update_layout(
plot_bgcolor="white",
legend=dict(
bgcolor="white",
bordercolor="black",
borderwidth=1,
),
)
figures.append(fig)
if save_fig:
fig.write_html(str(path / f"models/{self.name}/img/qq_plot_{v}.html"))
return figures
def plot_standardized_error(self, save_fig=False):
"""Plot and save the graphic for standardized error.
Parameters
----------
save_fig : bool, optional
If save_fig is True, saves the result in img folder. If False, does not
save. The default is False.
Returns
-------
figures : list
List of figures plotting standardized error for each variable in dataframe.
"""
path = Path(__file__).parent
var = list(self.train.columns)
error = self.test - self.train
error = error / error.std()
error.dropna(inplace=True)
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="power",
)
figures = []
for v in var:
error = self.test[v] - self.train[v]
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=self.test[v],
y=error,
mode="markers",
marker=dict(size=8, color="orange"),
name=f"Test points - {v}",
legendgroup=f"Test points - {v}",
showlegend=True,
hovertemplate=(
f"{v}<sub>test</sub> : %{{x:.2f}}<br>error : %{{y:.2f}}"
),
)
)
fig.update_xaxes(
title=dict(text=f"{v} <sub>test</sub>", font=dict(size=15)),
**axes_default,
)
fig.update_yaxes(
title=dict(text=f"Standardized Error", font=dict(size=15)),
**axes_default,
)
fig.update_layout(
plot_bgcolor="white",
legend=dict(
bgcolor="white",
bordercolor="black",
borderwidth=1,
),
shapes=[
dict(
type="line",
xref="paper",
x0=0,
x1=1,
yref="y",
y0=0,
y1=0,
line=dict(color="blue", dash="dash"),
)
],
)
figures.append(fig)
if save_fig:
fig.write_html(
str(
path
/ f"models/{self.name}/img/standardized_error_{v}_plot.html"
)
)
return figures
def plot_residuals_resume(self, save_fig=False):
"""Plot and save the graphic for residuals distribution.
Parameters
----------
save_fig : bool, optional
If save_fig is True, saves the result in img folder. If False, does not
save. The default is False.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
path = Path(__file__).parent
N = self.train.shape[1]
colors = [
"hsl(" + str(h) + ",50%" + ",50%)" for h in np.linspace(0, 360, N + 1)
]
error_std = (self.test - self.train) / (self.test - self.train).std()
labels = list(self.train.columns)
axes_default = dict(
gridcolor="lightgray",
showline=True,
linewidth=1.5,
linecolor="black",
mirror=True,
exponentformat="power",
)
fig = go.Figure(
data=[
go.Box(
x=error_std[labels[i]],
marker_color=colors[i],
jitter=0.2,
pointpos=0,
boxpoints="all",
name=labels[i],
hoverinfo="none",
orientation="h",
)
for i in range(N)
]
)
fig.update_xaxes(
title=dict(text="Standard Deviation", font=dict(size=15)),
range=[-10, 10],
tickvals=[-10, -5, -3, -2, -1, 0, 1, 2, 3, 5, 10],
tickmode="array",
**axes_default,
)
fig.update_yaxes(**axes_default)
n = 7
shape_x = np.linspace(-3, 3, n)
shape_color = ["green", "blue", "red", "black", "red", "blue", "green"]
fig.update_layout(
plot_bgcolor="white",
legend=dict(bgcolor="white", bordercolor="black", borderwidth=1),
shapes=[
dict(
type="line",
xref="x",
x0=shape_x[i],
x1=shape_x[i],
yref="paper",
y0=0,
y1=1,
line=dict(color=shape_color[i], dash="dash"),
name=f"σ = {abs(shape_x[i])}",
)
for i in range(n)
],
)
if save_fig:
fig.write_html(str(path / f"models/{self.name}/img/residuals_resume.html"))
return fig
def report(self, file="results", **kwargs):
"""Display the HTML report on browser.
The report contains a brief content about the neural network built.
Parameters
----------
name : srt, optional
The report file name.
The default is "results".
kwargs : optional inputs to plot the confidence bounds.
a : float
Significance level.A number between 0 and 1.
percentile : float, optional
Percentile to compute, which must be between 0 and 100 inclusive.
Returns
-------
HTML report
A interactive HTML report.
"""
_ = self.plot_overall_results(save_fig=True)
_ = self.plot_confidence_bounds(save_fig=True, **kwargs)
_ = self.plot_qq(save_fig=True)
_ = self.plot_standardized_error(save_fig=True)
_ = self.plot_residuals_resume(save_fig=True)
from_path = Path(__file__).parent / "template"
to_path = Path(__file__).parent / f"models/{self.name}"
for file in from_path.glob("**/*"):
shutil.copy(file, to_path)
return webbrowser.open(str(to_path / f"{file}.html"), new=2) | /ross_ml-0.0.1-py3-none-any.whl/rossml/pipeline.py | 0.847274 | 0.432003 | pipeline.py | pypi |
# ROSS Report
This package aims to build a report for [ROSS](https://github.com/ross-rotordynamics/ross), a rotordynamics python package.
## Quick start to graphics submodule
The ross-report's structure is very simple, in the highest level we have an object called Layout, which constructs the whole html page.
Layout is composed of Pages which is composed of Content objects (like Text or PlotlyFigure), to arrange all the components on the html version you can simply put them in order.
For a static PDF version of the report you can use `CTRL + P` on a browser like [chrome](https://www.google.com/intl/pt-BR/chrome/).
In this first example we're going to see how to construct a simple `hello_world.html` with some text and an Plotly Figure.
```Python
from report.graphics import *
import plotly.graph_objects as go
simple_text = """Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
"""
another_simple_text = simple_text[:-2][::-1].capitalize() + '.' # actually the same
fig = go.FigureWidget(data=go.Bar(y=[2, 3, 1]))
fig.layout["title"]["text"] = "Boring bars"
fig.layout["height"] = 500
fig.layout["width"] = 750
page = Page(content=[
Text(simple_text),
PlotlyFigure(fig),
Text(another_simple_text),
]
)
layout = Layout(pages=page, main_title="Hello World")
html_str = layout.render_html_str()
with open("hello_world.html", "w") as f:
f.write(html_str)
```
The `hello_world.html` should look like [this](https://rawcdn.githack.com/ross-rotordynamics/ross-report/eb0d73c4462cd584f0f2ec4cc40047a91e952918/hello_world.html).
## Complete example
In this example we first instantiate a ross.Report, run some analysis with the analysis subpackage and then export an html file containing the graphical report.
```python
from report.analysis import *
from report.graphics import *
import ross as rs
i_d = 0
o_d = 0.05
n = 6
L = [0.25 for _ in range(n)]
shaft_elem = [
rs.ShaftElement(
l,
i_d,
o_d,
material=rs.steel,
shear_effects=True,
rotary_inertia=True,
gyroscopic=True,
)
for l in L
]
disk0 = rs.DiskElement.from_geometry(
n=2, material=steel, width=0.07, i_d=0.05, o_d=0.28
)
disk1 = rs.DiskElement.from_geometry(
n=4, material=steel, width=0.07, i_d=0.05, o_d=0.28
)
stfx = [0.4e7, 0.5e7, 0.6e7, 0.7e7]
stfy = [0.8e7, 0.9e7, 1.0e7, 1.1e7]
freq = [400, 800, 1200, 1600]
bearing0 = rs.BearingElement(0, kxx=stfx, kyy=stfy, cxx=2e3, frequency=freq)
bearing1 = rs.BearingElement(6, kxx=stfx, kyy=stfy, cxx=2e3, frequency=freq)
rotor = rs.Rotor(shaft_elem, [disk0, disk1], [bearing0, bearing1])
# coefficients for minimum clearance
stfx = [0.7e7, 0.8e7, 0.9e7, 1.0e7]
dampx = [2.0e3, 1.9e3, 1.8e3, 1.7e3]
freq = [400, 800, 1200, 1600]
bearing0 = rs.BearingElement(0, kxx=stfx, cxx=dampx, frequency=freq)
bearing1 = rs.BearingElement(6, kxx=stfx, cxx=dampx, frequency=freq)
min_clearance_brg = [bearing0, bearing1]
# coefficients for maximum clearance
stfx = [0.4e7, 0.5e7, 0.6e7, 0.7e7]
dampx = [2.8e3, 2.7e3, 2.6e3, 2.5e3]
freq = [400, 800, 1200, 1600]
bearing0 = rs.BearingElement(0, kxx=stfx, cxx=dampx, frequency=freq)
bearing1 = rs.BearingElement(6, kxx=stfx, cxx=dampx, frequency=freq)
max_clearance_brg = [bearing0, bearing1]
bearings = [min_clearance_brg, max_clearance_brg]
report = Report(
rotor=rotor,
speed_range=(400, 1000),
tripspeed=1200,
bearing_stiffness_range=(5, 8),
bearing_clearance_lists=bearings,
speed_units="rad/s",
)
D = [0.35, 0.35]
H = [0.08, 0.08]
HP = [10000, 10000]
RHO_ratio = [1.11, 1.14]
RHOd = 30.45
RHOs = 37.65
oper_speed = 1000.0
data = report.run(D, H, HP, oper_speed, RHO_ratio, RHOs, RHOd)
plot_rotor_1, ucs_fig_1, mode_fig_1 = report.assets_prep(data)["figs"]
text1 = """This is a report automatically generated using <a href= https://github.com/ross-rotordynamics/ross> ROSS</a>, a python package for rotordynamics analysis.
<br>Below there's a graphical representation of the rotor analyzed."""
text2 = """In this section the calculations carried out to evaluate the critical speed map and the rotor response to unbalance are described.
The results of each calculation are shown at the end of this paragraph."""
text3 = """The undamped critical speed analysis is carried out according to API 617 7th edition para. 2.6.2.3. The rotor system as described in Appendix 1 is used. The bearings are represented by an equivalent spring constant between rotor and pedestals, which may then be considered as elastically mounted. Isotropic, linear bearing characteristics are assumed and no damping is considered present in the system. The stiffness range selected for the calculation is such to properly describe the behavior of the rotor and provide the required information to perform the next analysis steps. The actual stiffness range (achievable by adjusting bearing clearance) is much more limited and always inside the calculation range. The rotordynamic system is solved and the undamped lateral critical speeds are calculated as a function of support equivalent stiffness over the user defined stiffness range. The results are summarized in the critical speed maps as shown in the following pages. Superimposed on the same plot are the horizontal and vertical Bearing Clearance curves (Kxx and Kzz ) either for maximum and minimum Bearing Clearance. The intersections of the vertical Bearing Clearance and critical speed curves provide the undamped critical speed values and give, in a preliminary way, a rough estimation of the critical speed and Bearing Clearance range in operation. The 1st and 2nd mode shapes for maximum and minimum Bearing Clearance are also attached, with the only intent of mode shape identification. Therefore, the vibration amplitudes are normalized with respect to the maximum level.
"""
page1 = Page(
content=[Text(text=text1),
PlotlyFigure(figure=plot_rotor_1),
Title(title="Critical Speed Analysis"),
Text(text=text2),
Title("Undamped Critical Speed Analysis"),
Text(text=text3),
]
)
page2 = Page(content=[PlotlyFigure(figure=ucs_fig_1), PlotlyFigure(figure=mode_fig_1),])
pages = [page1, page2]
html = Layout(pages=pages).render_html_str()
with open("report.html", "w") as f:
f.write(html)
```
The `report.html` file should look like [this](https://raw.githack.com/ross-rotordynamics/ross-report/master/examples/report.html).
| /ross-report-0.0.1.tar.gz/ross-report-0.0.1/README.md | 0.73431 | 0.878887 | README.md | pypi |
import black
__all__ = ["Config"]
class _Dict:
"""Set keys and values as attribute for the Config object.
Subclass to organize nested dictionaries and set each key / value as attribute for
the config object.
Return
------
A dictionary as attribute for the Config() object.
Examples
--------
>>> param = _Dict({
... "stiffness_range": None,
... "num": 30,
... "num_modes": 16,
... "synchronous": False,
... })
>>> param.num
30
"""
def __init__(self, dictionary):
for k, v in dictionary.items():
if isinstance(v, dict):
setattr(self, k, self.__class__(v))
else:
setattr(self, k, v)
def __repr__(self):
"""Return a string representation for the dict attribute.
This method uses Black code formatting for better visualization.
Returns
-------
A string representation for the dictionary options.
Examples
--------
>>> param = _Dict({
... "oper_clearance": None,
... "min_clearance": None,
... "max_clearance": None,
... })
>>> param # doctest: +ELLIPSIS
{"oper_clearance": None, "min_clearance": None, "max_clearance": None}...
"""
return black.format_file_contents(
repr(self.__dict__), fast=True, mode=black.FileMode()
)
def __getitem__(self, option):
"""Return the value for a given option from the dictionary.
Parameters
----------
option : str
A dictionary key corresponding to config options as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the dictionary.
Returns
-------
Return the value for the given key.
Examples
--------
>>> param = _Dict({
... "stiffness_range": None,
... "num": 30,
... "num_modes": 16,
... "synchronous": False,
... })
>>> param["num"]
30
"""
if option not in self.__dict__.keys():
raise KeyError("Option '{}' not found.".format(option))
return self.__dict__[option]
def _update(self, **kwargs):
"""Update the dict values.
This is an axuliar method for Config.update_config() to set new values for the
config dictionary according to kwargs input.
The kwargs must respect Config attributes. It's only possible to update
existing values from Config dictionary.
**See Config attributes reference for infos about the dict options.
Parameters
----------
**kwargs : dict
Dictionary with new values for corresponding keys.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the dictionary.
Examples
--------
>>> param = _Dict({
... "stiffness_range": None,
... "num": 30,
... "num_modes": 16,
... "synchronous": False,
... })
>>> param._update(num=20, num_modes=10)
>>> param # doctest: +ELLIPSIS
{"stiffness_range": None, "num": 20, "num_modes": 10, "synchronous": False}...
"""
for k, v in kwargs.items():
if k not in self.__dict__.keys():
raise KeyError("Option '{}' not found.".format(k))
if isinstance(v, dict):
getattr(self, k)._update(**v)
else:
self.__dict__[k] = v
class Config:
"""Configurate parameters for rotordynamic report.
This class generates an object with several preset parameters to run the
rotordynamics analyses. It's a must to check all the options for a correct
functioning.
The attributes are automatically generated and it's not possible to remove then or
add new ones.
Attributes
----------
rotor_properties : dict
Dictionary of rotor properties.
rotor_speeds : dict
Dictionary indicating the operational speeds which will be used in the
analyses.
min_speed : float
The machine minimum operational speed.
max_speed : float
The machine maximum operational speed.
oper_speed : float
The machine nominal operational speed.
trip_speed : float
The machine overspeed trip.
speed_factor : float
Multiplicative factor of the speed range - according to API 684.
Default is 1.50.
unit : str
Unit system to speed values. Options: "rad/s", "rpm".
Default is "rpm".
rotor_id : dict
Dictionary with rotor identifications.
type : str
Machine type: Options are: "compressor", "turbine", "axial_flow". Each
options has it's own considerations (according to API 684). If a different
option is input, it will be the software will treat as a "compressor".
tag : str
Tag for the rotor. If None, it'll copy the tag from rotor object.
bearings : dict
The analyses consider different configurations for the bearings. It should be done
for minimum, maximum and the nominal clearance.
oper_clearance : list
List of bearing elements. The coefficients should be calculated for the nominal
clearance.
min_clearance : list
List of bearing elements. The coefficients should be calculated for the minimum
clearance.
max_clearance : list
List of bearing elements. The coefficients should be calculated for the maximum
clearance.
mode_shape : dict
Dictionary configurating the mode shape analysis
frequency_units : str
Unit for the frequency values.
Default is "rad/s"
run_campbell : dict
Dictionary configurating run_campbell parameters.
speed_range : list, array
Array with the speed range (must be in rad/s).
num_modes : float, optional
Number of frequencies that will be calculated.
Default is 6.
harmonics : list, optional
List with the harmonics to be plotted.
The default is to plot 1x.
frequency_units : str, optional
Unit for the frequency values.
Default is "rad/s".
plot_ucs : dict
Dictionary configurating plot_ucs parameters.
stiffness_range : tuple, optional
Tuple with (start, end) for stiffness range.
num : int, optional
Number of steps in the range.
Default is 30.
num_modes : int, optional
Number of modes to be calculated.
Default is 16.
synchronous : bool, optional
If True a synchronous analysis is carried out and the frequency of
the first forward model will be equal to the speed.
Default is False.
stiffness_units : str, optional
Unit for the stiffness values.
Default is "N/m".
frequency_units : str, optional
Unit for the frequency values.
Default is "rad/s".
run_unbalance_response : dict
Dictionary configurating run_unbalance_response parameters.
probes : dict
Dictionary with the node where the probe is set and its respective
orientation angle.
node : list
List with the nodes where probes are located.
orientation : list
List with the respective orientation angle for the probes.
0 or π (rad) corresponds to the X orientation and
π / 2 or 3 * π / 2 (rad) corresponds to the Y orientation.
unit : str
Unit system for the orientation angle. Can be "rad" or "degree".
Default is "rad".
frequency_range : list, array
Array with the desired range of frequencies (must be in rad/s).
If None and cluster_points is False, it creates an array from 0 to the max
continuos speed times the speed_factor.
If None and cluster_points is True, it creates and automatic array based on
the number of modes selected.
Default is None with cluster_points False.
modes : list, optional
Modes that will be used to calculate the frequency response
(all modes will be used if a list is not given).
cluster_points : bool, optional
Boolean to activate the automatic frequency spacing method. If True, the
method uses _clustering_points() to create an speed_range.
Default is False
num_points : int, optional
The number of points generated per critical speed.
The method set the same number of points for slightly less and slightly
higher than the natural circular frequency. It means there'll be num_points
greater and num_points smaller than a given critical speed.
num_points may be between 2 and 12. Anything above this range defaults
to 10 and anything below this range defaults to 4.
The default is 10.
num_modes
The number of eigenvalues and eigenvectors to be calculated using ARPACK.
It also defines the range for the output array, since the method generates
points only for the critical speed calculated by Rotor.run_critical_speed().
Default is 12.
rtol : float, optional
Tolerance (relative) for termination. Applied to scipy.optimize.newton to
calculate the approximated critical speeds.
Default is 0.005 (0.5%).
frequency_units : str, optional
Frequency units.
Default is "rad/s"
amplitude_units : str, optional
Amplitude units.
Default is "m/N"
phase_units : str, optional
Phase units.
Default is "rad".
rotor_length_units : str, optional
Units for rotor length.
Default is "m".
plot_deflected_shape : dict
Options to configurate the deflected shape plot.
speed : list, array
List with selected speed to plot the deflected shape.
The speed values must be elements from frequency_range option,
otherwise it returns an error.
speed_units : str, optional
Units for selected speed in deflected shape analisys.
Default is "rad/s".
stability_level1 : dict
Dictionary configurating stability_level_1 parameters.
D : list, array
Impeller diameter, m (in.) or Blade pitch diameter, m (in).
The disk elements order must be observed to input this list.
H : list, array
Minimum diffuser width per impeller, m (in) or Effective blade height, m (in).
The disk elements order must be observed to input this list.
rated_power : list
Rated power per stage/impeller, W (HP),
The disk elements order must be observed to input this list.
rho_ratio : list
Density ratio between the discharge gas density and the suction
gas density per impeller, kg/m3 (lbm/in.3),
The disk elements order must be observed to input this list.
rho_suction : float
Suction gas density in the first stage, kg/m3 (lbm/in.3).
rho_discharge : float
Discharge gas density in the last stage, kg/m3 (lbm/in.3),
unit: str, optional
Unit system. Options are "m" (meter) and "in" (inch).
Default is "m".
length_unit : str
Length units for D and H arguments.
Default is "m".
power_unit : str
Power unit for rated_power argument.
Default is "hp".
density_unit : str
Density unit for rho_suction and rho_discharge arguments.
Default is "kg/m**3".
Returns
-------
A config object to rotordynamic report.
Examples
--------
There are two possible syntax to return the options setup. One is using the
object.attribute syntax and the other is the dicionary syntax
First syntax opion:
>>> configs = Config()
>>> configs.rotor_properties.rotor_id # doctest: +ELLIPSIS
{"type": "compressor", "tag": None}...
Second syntax opion:
>>> configs = Config()
>>> configs["rotor_properties"]["rotor_id"] # doctest: +ELLIPSIS
{"type": "compressor", "tag": None}...
"""
def __init__(self):
# fmt: off
# Configurating rotor properties
self.rotor_properties = _Dict({
"rotor_speeds": {
"min_speed": None,
"max_speed": None,
"oper_speed": None,
"trip_speed": None,
"speed_factor": 1.50,
"unit": "rpm",
},
"rotor_id": {
"type": "compressor",
"tag": None,
},
})
# Configurating bearing elements for diferent clearances
self.bearings = _Dict({
"oper_clearance": None,
"min_clearance": None,
"max_clearance": None,
})
# Configurating modal analysis
self.mode_shape = _Dict({
"frequency_units": "rad/s"
})
# Configurating campbell options
self.run_campbell = _Dict({
"speed_range": None,
"num_modes": 6,
"harmonics": [1],
"frequency_units": "rad/s"
})
# Configurating UCS options
self.plot_ucs = _Dict({
"stiffness_range": None,
"num": 30,
"num_modes": 16,
"synchronous": False,
"stiffness_units": "N/m",
"frequency_units": "rad/s",
})
# Configurating unbalance response options
self.run_unbalance_response = _Dict({
"probes": {
"node": None,
"orientation": None,
"unit": "rad",
},
"frequency_range": None,
"modes": None,
"cluster_points": False,
"num_modes": 12,
"num_points": 10,
"rtol": 0.005,
"frequency_units": "rad/s",
"amplitude_units": "m",
"phase_units": "rad",
"rotor_length_units": "m",
"plot_deflected_shape": {
"speed": [],
"speed_units": "rad/s",
},
})
# Configurating stability level 1 analysis
self.stability_level1 = _Dict({
"D": None,
"H": None,
"rated_power": None,
"rho_ratio": None,
"rho_suction": None,
"rho_discharge": None,
"length_unit": "m",
"power_unit": "hp",
"density_unit": "kg/m**3",
})
# fmt: on
def __repr__(self):
"""Return a string representation for the config options.
This method uses Black code formatting for better visualization.
Returns
-------
A string representation for the config dictionary.
Examples
--------
>>> configs = Config()
>>> configs # doctest: +ELLIPSIS
{
"rotor_properties": {
"rotor_speeds": {
"min_speed": None,
"max_speed": None,
"oper_speed": None...
"""
return black.format_file_contents(
repr(self.__dict__), fast=True, mode=black.FileMode()
)
def __getitem__(self, option):
"""Return the value for a given option from config dictionary.
Parameters
----------
option : str
A dictionary key corresponding to config options as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the dictionary.
Returns
-------
Return the value for the given key.
Examples
--------
>>> configs = Config()
>>> configs["bearings"] # doctest: +ELLIPSIS
{"oper_clearance": None, "min_clearance": None, "max_clearance": None}...
"""
if option not in self.__dict__.keys():
raise KeyError("Option '{}' not found.".format(option))
return self.__dict__[option]
def update_config(self, **kwargs):
"""Update the config options.
This method set new values for the config dictionary according to kwargs input.
The kwargs must respect Config attributes. It's only possible to update
existing values from Config dictionary.
**See Config attributes reference for infos about the dict options.
Parameters
----------
**kwargs : dict
Dictionary with new values for corresponding keys.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the dictionary.
Examples
--------
>>> configs = Config()
>>> configs.update_config(
... rotor_properties=dict(
... rotor_speeds=dict(min_speed=1000.0, max_speed=10000.0),
... rotor_id=dict(type="turbine", tag="Model"),
... )
... )
>>> configs.rotor_properties # doctest: +ELLIPSIS
{
"rotor_speeds": {
"min_speed": 1000.0,
"max_speed": 10000.0,
"oper_speed": None,
"trip_speed": None,
"speed_factor": 1.5,
"unit": "rpm",
},
"rotor_id": {"type": "turbine", "tag": "Model"},
}...
"""
for k, v in kwargs.items():
if k not in self.__dict__.keys():
raise KeyError("Option '{}' not found.".format(k))
else:
getattr(self, k)._update(**v) | /ross-report-0.0.1.tar.gz/ross-report-0.0.1/report/config.py | 0.934133 | 0.44089 | config.py | pypi |
from pathlib import Path
import report
import base64 as b64
from plotly.graph_objs import Figure
class CSS:
def __init__(self, path=Path(report.__file__).parent / "style.css"):
self.path = Path(path)
def __str__(self):
with open(self.path) as css_file:
css_code = css_file.read()
return css_code
def __repr__(self):
return "CSS"
class Content:
def __init__(self):
pass
def render_html_str(self):
pass
class Text(Content):
def __init__(self, text, style=""):
super().__init__()
self.text = text
self.style = style
def render_html_str(self):
html = f"""
<div class="row offset-2">\n
<div class="col-9 mt-3 mb-0 pb-0">\n
<p style="{self.style}"class="text-justify">\n
{self.text} \n
</p>\n
</div>\n
</div>\n
"""
return html
class Img(Content):
"""
"""
def __init__(self, path_to_img):
self.path_to_img = Path(path_to_img)
def render_html_str(self):
html = ""
return html
def __repr__(self):
return f"{self.path_to_img}"
class Title(Content):
"""
"""
def __init__(self, title):
self.title = title
self.id = title
def render_html_str(self):
html = f"""
<div class="row offset-2">
<div class="col-9">
<h1 class="h1"><a id="{self.id}"></a>
{self.title}
</h1>
</div>
</div>
"""
return html
class Page:
"""
"""
def __init__(
self, content=None,
):
for item in content:
assert isinstance(item, Content) or isinstance(
item, str
), "Every item of content must be either content or a string"
self.content = content
self._titles = []
self._figures = []
content = []
for item in self.content:
if isinstance(item, str):
content.append(Text(item))
else:
content.append(item)
if isinstance(item, Title):
self._titles.append(item)
if isinstance(item, PlotlyFigure) or isinstance(item, Img):
self._figures.append(item)
def render_html_str(self, figures_list):
html = ""
for item in self.content:
if isinstance(item, PlotlyFigure):
figure_numb = len(figures_list)
item = PlotlyFigure(
item.figure, item.width, id="Figure " + f"{figure_numb}"
)
figures_list.append(item)
html += item.render_html_str()
return html, figures_list
class PlotlyFigure(Content):
def __init__(self, figure, width=900, id=""):
self.figure = figure
self.figure.update_layout(width=width)
self.id = id
self.width = width
def render_html_str(self):
html = f"""
<div style="width: {self.figure.layout["width"]}px;height: {self.figure.layout["height"]}px" class="mx-auto" id="{self.id}">\n
{self.figure.to_html(full_html=False)}
</div>
"""
return html
class Table(Content):
def __init__(self, pandas_data_frame, width):
self.table = pandas_data_frame
self.width = width
def render_html_str(self):
html = f"""
<div style="width: {self.width}px;" class="mx-auto">\n
{self.table.to_html(classes="table table-striped table-hover table-responsive")}
</div>
"""
return html
class Listing(Content):
def __init__(self, items):
self.items = items
def __str__(self):
return str(self.render_html_str())
def render_html_str(self):
html = """
<div class="offset-2 mb-4 row">
<div class="col-9">
<ui>
"""
for item in self.items:
html += f""" <li style = "color: #555555; text-align: -webkit-match-parent;">{item}</li>\n"""
html += """
</ui>
</div>
</div>
"""
return html
class Link(Content):
def __init__(self, title, href, style="", internal=True):
self.href = href
self.title = title
self.internal = internal
self.style = style
def render_html_str(self):
return f"""<a style="{self.style}" class="text-justify" href = "{self._internal()}{self.href}">{self.title}</a>"""
def _internal(self):
if self.internal:
return "#"
else:
return ""
def __str__(self):
return self.render_html_str()
def __repr__(self):
return self.render_html_str()
class Layout:
"""Report Layout
"""
def __init__(
self,
summary=True,
figures_list_ref=True,
css=CSS(),
pages=None,
main_title="ROSS Report",
):
assert (
isinstance(pages, list) or isinstance(pages, Page) or pages is None
), "pages argument must be either a Page or a list of Pages."
if isinstance(pages, list):
for page in pages:
assert isinstance(page, Page), "All items in page must be Pages."
self.pages = pages
else:
self.pages = [pages]
assert isinstance(css, CSS), "css must be an CSS object."
self.css = css
assert isinstance(main_title, str), "main_title must be a str."
self.main_title = main_title
self.summary = summary
self.figures_list = []
self.figures_list_ref = figures_list_ref
def __repr__(self):
rep = {}
if isinstance(self.pages, list):
for page in range(len(self.pages)):
rep[self.pages[page]] = self.pages[page]
elif isinstance(self.pages, Page):
rep[self.pages] = self.pages.content
return str(rep)
def summary_renderer(self):
layout_titles = []
for page in self.pages:
for title in page._titles:
layout_titles.append(Link(title=title.title, href=title.title))
if self.figures_list_ref:
layout_titles.append(Link(title="Figures List", href="Figures List"))
summary = f"""
<div class="mt-4 pb-4 offset-2 row">
<div class="col-9">
<h1 class="h1">
Summary
</h1>
</div>
</div>
"""
summary += str(Listing(layout_titles))
return summary
def figures_list_renderer(self):
content = [Title("Figures List")]
image_titles = []
for figure in range(len(self.figures_list)):
image_titles.append(
Link(title=f"Figure {figure + 1}", href=f"Figure {figure}")
)
content.append(Listing(image_titles))
print(len(self.figures_list))
return content
def render_pages(self, figures_list_ref=True):
html = ""
if self.summary is True:
if isinstance(self.pages, list):
figures_list = []
for page in range(len(self.pages)):
rendered_page = self.pages[page].render_html_str(
figures_list=figures_list
)
html += rendered_page[0]
figures_list = rendered_page[1]
if page != len(self.pages) - 1:
html += """<<p class="page-break-before" style="page-break-before: always" /> \n>"""
elif figures_list_ref:
self.figures_list = figures_list
rendered_page = Page(
content=self.figures_list_renderer()
).render_html_str(figures_list=figures_list)
html += rendered_page[0]
print(len(figures_list))
elif isinstance(self.pages, Page):
html += self.pages.render_html_str()
return html
def render_html_str(self):
rendered_pages = self.render_pages(figures_list_ref=self.figures_list_ref)
summary = self.summary_renderer()
html = (
"""
<!DOCTYPE html>
<html lang="en">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
"""
+ """
<script src="https://code.jquery.com/jquery-3.5.1.slim.min.js" integrity="sha384-DfXdz2htPH0lsSSs5nCTpuj/zy4C+OGpamoFVy38MVBnE+IbbVYUew+OrCXaRkfj" crossorigin="anonymous"></script>
<script src="https://cdn.jsdelivr.net/npm/popper.js@1.16.1/dist/umd/popper.min.js" integrity="sha384-9/reFTGAW83EW2RDu2S0VKaIzap3H66lZH81PoYlFhbGU+6BZp6G7niu735Sk7lN" crossorigin="anonymous"></script>
<script src="https://stackpath.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js" integrity="sha384-B4gt1jrGC7Jh4AgTPSdUtOBvfO8shuf57BaghqFfPlYxofvL8/KUEfYiJOMMV+rV" crossorigin="anonymous"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.3.1/jquery.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js"></script>
<script type="text/javascript" id="MathJax-script" async
src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-svg.js">
</script>
"""
)
html = (
html
+ "<style>"
+ str(self.css)
+ "</style>"
+ """
<style>
@media print {
@page {
size: A4; /* DIN A4 standard, Europe */
margin: 1cm;
}
.offset-2{
margin-left: 3cm;
margin-right: 0;
margin-top: .5cm;
}
.mt-img{
margin-top: 5cm;
}
p{
width: 100ch;
}
a,li{
margin-top: 0;
margin-bottom: 1rem;
color: #555555;
}
}
</style>
<meta charset="UTF-8">
<title>ROSS Report</title>
<link rel="icon" href="data:image/svg+xml;base64,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">
</head>
<body>
"""
+ f"""
<div class="container-fluid">
<div class="mt-4 offset-2 row">
<div class="col-9">
<h1 style= "font-size: 2.5rem" class="h1">
{self.main_title}
</h1>
</div>
<div class="col-3">
<a href="https://github.com/ross-rotordynamics/ross-report">
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</a>
</div>
</div>
"""
)
html += summary
html += rendered_pages
html += """
</div>
</body>
</html>
"""
return html | /ross-report-0.0.1.tar.gz/ross-report-0.0.1/report/graphics.py | 0.796411 | 0.167287 | graphics.py | pypi |
import os
import warnings
from inspect import signature
import numpy as np
import toml
from numpy.polynomial import Polynomial
from plotly import graph_objects as go
from scipy import interpolate as interpolate
from ross.element import Element
from ross.fluid_flow import fluid_flow as flow
from ross.fluid_flow.fluid_flow_coefficients import (
calculate_stiffness_and_damping_coefficients,
)
from ross.units import Q_, check_units
from ross.utils import read_table_file
__all__ = [
"BearingElement",
"SealElement",
"BallBearingElement",
"RollerBearingElement",
"BearingFluidFlow",
"BearingElement6DoF",
"MagneticBearingElement",
"CylindricalBearing",
]
class BearingElement(Element):
"""A bearing element.
This class will create a bearing element.
Parameters can be a constant value or speed dependent.
For speed dependent parameters, each argument should be passed
as an array and the correspondent speed values should also be
passed as an array.
Values for each parameter will be_interpolated for the speed.
Parameters
----------
n : int
Node which the bearing will be located in
kxx : float, array, pint.Quantity
Direct stiffness in the x direction (N/m).
cxx : float, array, pint.Quantity
Direct damping in the x direction (N*s/m).
mxx : float, array, pint.Quantity
Direct mass in the x direction (kg).
kyy : float, array, pint.Quantity, optional
Direct stiffness in the y direction (N/m).
(defaults to kxx)
cyy : float, array, pint.Quantity, optional
Direct damping in the y direction (N*s/m).
(defaults to cxx)
myy : float, array, pint.Quantity, optional
Direct mass in the y direction (kg).
(defaults to mxx)
kxy : float, array, pint.Quantity, optional
Cross coupled stiffness in the x direction (N/m).
(defaults to 0)
cxy : float, array, pint.Quantity, optional
Cross coupled damping in the x direction (N*s/m).
(defaults to 0)
mxy : float, array, pint.Quantity, optional
Cross coupled mass in the x direction (kg).
(defaults to 0)
kyx : float, array, pint.Quantity, optional
Cross coupled stiffness in the y direction (N/m).
(defaults to 0)
cyx : float, array, pint.Quantity, optional
Cross coupled damping in the y direction (N*s/m).
(defaults to 0)
myx : float, array, pint.Quantity, optional
Cross coupled mass in the y direction (kg).
(defaults to 0)
frequency : array, pint.Quantity, optional
Array with the frequencies (rad/s).
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is '#355d7a' (Cardinal).
Examples
--------
>>> # A bearing element located in the first rotor node, with these
>>> # following stiffness and damping coefficients and speed range from
>>> # 0 to 200 rad/s
>>> import ross as rs
>>> kxx = 1e6
>>> kyy = 0.8e6
>>> cxx = 2e2
>>> cyy = 1.5e2
>>> frequency = np.linspace(0, 200, 11)
>>> bearing0 = rs.BearingElement(n=0, kxx=kxx, kyy=kyy, cxx=cxx, cyy=cyy, frequency=frequency)
>>> bearing0.K(frequency) # doctest: +ELLIPSIS
array([[[1000000., 1000000., ...
>>> bearing0.C(frequency) # doctest: +ELLIPSIS
array([[[200., 200., ...
"""
@check_units
def __init__(
self,
n,
kxx,
cxx,
mxx=None,
kyy=None,
kxy=0,
kyx=0,
cyy=None,
cxy=0,
cyx=0,
myy=None,
mxy=0,
myx=0,
frequency=None,
tag=None,
n_link=None,
scale_factor=1,
color="#355d7a",
**kwargs,
):
if frequency is not None:
self.frequency = np.array(frequency, dtype=np.float64)
else:
self.frequency = frequency
args = [
"kxx",
"kyy",
"kxy",
"kyx",
"cxx",
"cyy",
"cxy",
"cyx",
"mxx",
"myy",
"mxy",
"myx",
]
# all args to coefficients
args_dict = locals()
if kyy is None:
args_dict["kyy"] = kxx
if cyy is None:
args_dict["cyy"] = cxx
if myy is None:
if mxx is None:
args_dict["mxx"] = 0
args_dict["myy"] = 0
else:
args_dict["myy"] = mxx
# check coefficients len for consistency
coefficients_len = []
for arg in args:
coefficient, interpolated = self._process_coefficient(args_dict[arg])
setattr(self, arg, coefficient)
setattr(self, f"{arg}_interpolated", interpolated)
coefficients_len.append(len(coefficient))
if frequency is not None and type(frequency) != float:
coefficients_len.append(len(args_dict["frequency"]))
if len(set(coefficients_len)) > 1:
raise ValueError(
"Arguments (coefficients and frequency)"
" must have the same dimension"
)
else:
for c in coefficients_len:
if c != 1:
raise ValueError(
"Arguments (coefficients and frequency)"
" must have the same dimension"
)
self.n = n
self.n_link = n_link
self.tag = tag
self.color = color
self.scale_factor = scale_factor
self.dof_global_index = None
def _process_coefficient(self, coefficient):
"""Helper function used to process the coefficient data."""
interpolated = None
if isinstance(coefficient, (int, float)):
if self.frequency is not None and type(self.frequency) != float:
coefficient = [coefficient for _ in range(len(self.frequency))]
else:
coefficient = [coefficient]
if len(coefficient) > 1:
try:
with warnings.catch_warnings():
warnings.simplefilter("ignore")
interpolated = interpolate.UnivariateSpline(
self.frequency, coefficient
)
# dfitpack.error is not exposed by scipy
# so a bare except is used
except:
try:
if len(self.frequency) in (2, 3):
interpolated = interpolate.interp1d(
self.frequency,
coefficient,
kind=len(self.frequency) - 1,
fill_value="extrapolate",
)
except:
raise ValueError(
"Arguments (coefficients and frequency)"
" must have the same dimension"
)
else:
interpolated = interpolate.interp1d(
[0, 1],
[coefficient[0], coefficient[0]],
kind="linear",
fill_value="extrapolate",
)
return coefficient, interpolated
def plot(
self,
coefficients=None,
frequency_units="rad/s",
stiffness_units="N/m",
damping_units="N*s/m",
mass_units="kg",
fig=None,
**kwargs,
):
"""Plot coefficient vs frequency.
Parameters
----------
coefficients : list, str
List or str with the coefficients to plot.
frequency_units : str, optional
Frequency units.
Default is rad/s.
stiffness_units : str, optional
Stiffness units.
Default is N/m.
damping_units : str, optional
Damping units.
Default is N*s/m.
mass_units : str, optional
Mass units.
Default is kg.
**kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Example
-------
>>> bearing = bearing_example()
>>> fig = bearing.plot('kxx')
>>> # fig.show()
"""
if fig is None:
fig = go.Figure()
if isinstance(coefficients, str):
coefficients = [coefficients]
# check coefficients consistency
coefficients_set = set([coeff[0] for coeff in coefficients])
if len(coefficients_set) > 1:
raise ValueError(
"Can only plot stiffness, damping or mass in the same plot."
)
coeff_to_plot = coefficients_set.pop()
if coeff_to_plot == "k":
default_units = "N/m"
y_units = stiffness_units
elif coeff_to_plot == "c":
default_units = "N*s/m"
y_units = damping_units
else:
default_units = "kg"
y_units = mass_units
_frequency_range = np.linspace(min(self.frequency), max(self.frequency), 30)
for coeff in coefficients:
y_value = (
Q_(
getattr(self, f"{coeff}_interpolated")(_frequency_range),
default_units,
)
.to(y_units)
.m
)
frequency_range = Q_(_frequency_range, "rad/s").to(frequency_units).m
fig.add_trace(
go.Scatter(
x=frequency_range,
y=y_value,
mode="lines",
showlegend=True,
hovertemplate=f"Frequency ({frequency_units}): %{{x:.2f}}<br> Coefficient ({y_units}): %{{y:.3e}}",
name=f"{coeff}",
)
)
fig.update_xaxes(title_text=f"Frequency ({frequency_units})")
fig.update_yaxes(exponentformat="power")
fig.update_layout(**kwargs)
return fig
def __repr__(self):
"""Return a string representation of a bearing element.
Returns
-------
A string representation of a bearing element object.
Examples
--------
>>> bearing = bearing_example()
>>> bearing # doctest: +ELLIPSIS
BearingElement(n=0, n_link=None,
kxx=[...
"""
return (
f"{self.__class__.__name__}"
f"(n={self.n}, n_link={self.n_link},\n"
f" kxx={self.kxx}, kxy={self.kxy},\n"
f" kyx={self.kyx}, kyy={self.kyy},\n"
f" cxx={self.cxx}, cxy={self.cxy},\n"
f" cyx={self.cyx}, cyy={self.cyy},\n"
f" mxx={self.mxx}, mxy={self.mxy},\n"
f" myx={self.myx}, myy={self.myy},\n"
f" frequency={self.frequency}, tag={self.tag!r})"
)
def __eq__(self, other):
"""Equality method for comparasions.
Parameters
----------
other: object
The second object to be compared with.
Returns
-------
bool
True if the comparison is true; False otherwise.
Examples
--------
>>> bearing1 = bearing_example()
>>> bearing2 = bearing_example()
>>> bearing1 == bearing2
True
"""
compared_attributes = [
"kxx",
"kyy",
"kxy",
"kyx",
"cxx",
"cyy",
"cxy",
"cyx",
"mxx",
"myy",
"mxy",
"myx",
"frequency",
]
if isinstance(other, self.__class__):
init_args = []
for arg in signature(self.__init__).parameters:
if arg not in ["kwargs"]:
init_args.append(arg)
init_args_comparison = []
for arg in init_args:
comparison = getattr(self, arg) == getattr(other, arg)
try:
comparison = all(comparison)
except TypeError:
pass
init_args_comparison.append(comparison)
init_args_comparison = all(init_args_comparison)
attributes_comparison = all(
(
(
np.array(getattr(self, attr)) == np.array(getattr(other, attr))
).all()
for attr in compared_attributes
)
)
return init_args_comparison and attributes_comparison
return False
def __hash__(self):
return hash(self.tag)
def save(self, file):
try:
data = toml.load(file)
except FileNotFoundError:
data = {}
# save initialization args and coefficients
args = list(signature(self.__init__).parameters)
args += [
"kxx",
"kyy",
"kxy",
"kyx",
"cxx",
"cyy",
"cxy",
"cyx",
"mxx",
"myy",
"mxy",
"myx",
]
brg_data = {}
for arg in args:
if arg not in ["kwargs"]:
brg_data[arg] = self.__dict__[arg]
# change np.array to lists so that we can save in .toml as list(floats)
for k, v in brg_data.items():
if isinstance(v, np.generic):
brg_data[k] = brg_data[k].item()
elif isinstance(v, np.ndarray):
brg_data[k] = brg_data[k].tolist()
# case for a container with np.float (e.g. list(np.float))
else:
try:
brg_data[k] = [i.item() for i in brg_data[k]]
except (TypeError, AttributeError):
pass
data[f"{self.__class__.__name__}_{self.tag}"] = brg_data
with open(file, "w") as f:
toml.dump(data, f)
def dof_mapping(self):
"""Degrees of freedom mapping.
Returns a dictionary with a mapping between degree of freedom and its
index.
Returns
-------
dof_mapping : dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
The numbering of the degrees of freedom for each node.
Being the following their ordering for a node:
x_0 - horizontal translation
y_0 - vertical translation
>>> bearing = bearing_example()
>>> bearing.dof_mapping()
{'x_0': 0, 'y_0': 1}
"""
return dict(x_0=0, y_0=1)
def M(self, frequency):
"""Mass matrix for an instance of a bearing element.
This method returns the mass matrix for an instance of a bearing
element.
Returns
-------
M : np.ndarray
Mass matrix (kg).
Examples
--------
>>> bearing = bearing_example()
>>> bearing.M(0)
array([[0., 0.],
[0., 0.]])
"""
mxx = self.mxx_interpolated(frequency)
myy = self.myy_interpolated(frequency)
mxy = self.mxy_interpolated(frequency)
myx = self.myx_interpolated(frequency)
M = np.array([[mxx, mxy], [myx, myy]])
if self.n_link is not None:
# fmt: off
M = np.vstack((np.hstack([M, -M]),
np.hstack([-M, M])))
# fmt: on
return M
@check_units
def K(self, frequency):
"""Stiffness matrix for an instance of a bearing element.
This method returns the stiffness matrix for an instance of a bearing
element.
Parameters
----------
frequency : float
The excitation frequency (rad/s).
Returns
-------
K : np.ndarray
A 2x2 matrix of floats containing the kxx, kxy, kyx, and kyy values.
Examples
--------
>>> bearing = bearing_example()
>>> bearing.K(0)
array([[1000000., 0.],
[ 0., 800000.]])
"""
kxx = self.kxx_interpolated(frequency)
kyy = self.kyy_interpolated(frequency)
kxy = self.kxy_interpolated(frequency)
kyx = self.kyx_interpolated(frequency)
K = np.array([[kxx, kxy], [kyx, kyy]])
if self.n_link is not None:
# fmt: off
K = np.vstack((np.hstack([K, -K]),
np.hstack([-K, K])))
# fmt: on
return K
@check_units
def C(self, frequency):
"""Damping matrix for an instance of a bearing element.
This method returns the damping matrix for an instance of a bearing
element.
Parameters
----------
frequency : float
The excitation frequency (rad/s).
Returns
-------
C : np.ndarray
A 2x2 matrix of floats containing the cxx, cxy, cyx, and cyy values (N*s/m).
Examples
--------
>>> bearing = bearing_example()
>>> bearing.C(0)
array([[200., 0.],
[ 0., 150.]])
"""
cxx = self.cxx_interpolated(frequency)
cyy = self.cyy_interpolated(frequency)
cxy = self.cxy_interpolated(frequency)
cyx = self.cyx_interpolated(frequency)
C = np.array([[cxx, cxy], [cyx, cyy]])
if self.n_link is not None:
# fmt: off
C = np.vstack((np.hstack([C, -C]),
np.hstack([-C, C])))
# fmt: on
return C
def G(self):
"""Gyroscopic matrix for an instance of a bearing element.
This method returns the mass matrix for an instance of a bearing
element.
Returns
-------
G : np.ndarray
A 2x2 matrix of floats.
Examples
--------
>>> bearing = bearing_example()
>>> bearing.G()
array([[0., 0.],
[0., 0.]])
"""
G = np.zeros_like(self.K(0))
return G
def _patch(self, position, fig):
"""Bearing element patch.
Patch that will be used to draw the bearing element using Plotly library.
Parameters
----------
position : tuple
Position (z, y_low, y_upp) in which the patch will be drawn.
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
Returns
-------
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
"""
default_values = dict(
mode="lines",
line=dict(width=1, color=self.color),
name=self.tag,
legendgroup="bearings",
showlegend=False,
hoverinfo="none",
)
# geometric factors
zpos, ypos, ypos_s = position
icon_h = ypos_s - ypos # bearing icon height
icon_w = icon_h / 2.0 # bearing icon width
coils = 6 # number of points to generate spring
n = 5 # number of ground lines
step = icon_w / (coils + 1) # spring step
zs0 = zpos - (icon_w / 3.5)
zs1 = zpos + (icon_w / 3.5)
ys0 = ypos + 0.25 * icon_h
# plot bottom base
x_bot = [zpos, zpos, zs0, zs1]
yl_bot = [ypos, ys0, ys0, ys0]
yu_bot = [-y for y in yl_bot]
fig.add_trace(go.Scatter(x=x_bot, y=yl_bot, **default_values))
fig.add_trace(go.Scatter(x=x_bot, y=yu_bot, **default_values))
# plot top base
x_top = [zpos, zpos, zs0, zs1]
yl_top = [
ypos + icon_h,
ypos + 0.75 * icon_h,
ypos + 0.75 * icon_h,
ypos + 0.75 * icon_h,
]
yu_top = [-y for y in yl_top]
fig.add_trace(go.Scatter(x=x_top, y=yl_top, **default_values))
fig.add_trace(go.Scatter(x=x_top, y=yu_top, **default_values))
# plot ground
if self.n_link is None:
zl_g = [zs0 - step, zs1 + step]
yl_g = [yl_top[0], yl_top[0]]
yu_g = [-y for y in yl_g]
fig.add_trace(go.Scatter(x=zl_g, y=yl_g, **default_values))
fig.add_trace(go.Scatter(x=zl_g, y=yu_g, **default_values))
step2 = (zl_g[1] - zl_g[0]) / n
for i in range(n + 1):
zl_g2 = [(zs0 - step) + step2 * (i), (zs0 - step) + step2 * (i + 1)]
yl_g2 = [yl_g[0], 1.1 * yl_g[0]]
yu_g2 = [-y for y in yl_g2]
fig.add_trace(go.Scatter(x=zl_g2, y=yl_g2, **default_values))
fig.add_trace(go.Scatter(x=zl_g2, y=yu_g2, **default_values))
# plot spring
z_spring = np.array([zs0, zs0, zs0, zs0])
yl_spring = np.array([ys0, ys0 + step, ys0 + icon_w - step, ys0 + icon_w])
for i in range(coils):
z_spring = np.insert(z_spring, i + 2, zs0 - (-1) ** i * step)
yl_spring = np.insert(yl_spring, i + 2, ys0 + (i + 1) * step)
yu_spring = [-y for y in yl_spring]
fig.add_trace(go.Scatter(x=z_spring, y=yl_spring, **default_values))
fig.add_trace(go.Scatter(x=z_spring, y=yu_spring, **default_values))
# plot damper - base
z_damper1 = [zs1, zs1]
yl_damper1 = [ys0, ys0 + 2 * step]
yu_damper1 = [-y for y in yl_damper1]
fig.add_trace(go.Scatter(x=z_damper1, y=yl_damper1, **default_values))
fig.add_trace(go.Scatter(x=z_damper1, y=yu_damper1, **default_values))
# plot damper - center
z_damper2 = [zs1 - 2 * step, zs1 - 2 * step, zs1 + 2 * step, zs1 + 2 * step]
yl_damper2 = [ys0 + 5 * step, ys0 + 2 * step, ys0 + 2 * step, ys0 + 5 * step]
yu_damper2 = [-y for y in yl_damper2]
fig.add_trace(go.Scatter(x=z_damper2, y=yl_damper2, **default_values))
fig.add_trace(go.Scatter(x=z_damper2, y=yu_damper2, **default_values))
# plot damper - top
z_damper3 = [z_damper2[0], z_damper2[2], zs1, zs1]
yl_damper3 = [
ys0 + 4 * step,
ys0 + 4 * step,
ys0 + 4 * step,
ypos + 1.5 * icon_w,
]
yu_damper3 = [-y for y in yl_damper3]
fig.add_trace(go.Scatter(x=z_damper3, y=yl_damper3, **default_values))
fig.add_trace(go.Scatter(x=z_damper3, y=yu_damper3, **default_values))
return fig
@classmethod
def table_to_toml(cls, n, file):
"""Convert bearing parameters to toml.
Convert a table with parameters of a bearing element to a dictionary ready to
save to a toml file that can be later loaded by ross.
Parameters
----------
n : int
The node in which the bearing will be located in the rotor.
file : str
Path to the file containing the bearing parameters.
Returns
-------
data : dict
A dict that is ready to save to toml and readable by ross.
Examples
--------
>>> import os
>>> file_path = os.path.dirname(os.path.realpath(__file__)) + '/tests/data/bearing_seal_si.xls'
>>> BearingElement.table_to_toml(0, file_path) # doctest: +ELLIPSIS
{'n': 0, 'kxx': array([...
"""
b_elem = cls.from_table(n, file)
data = {
"n": b_elem.n,
"kxx": b_elem.kxx,
"cxx": b_elem.cxx,
"kyy": b_elem.kyy,
"kxy": b_elem.kxy,
"kyx": b_elem.kyx,
"cyy": b_elem.cyy,
"cxy": b_elem.cxy,
"cyx": b_elem.cyx,
"frequency": b_elem.frequency,
}
return data
@classmethod
def from_table(
cls,
n,
file,
sheet_name=0,
tag=None,
n_link=None,
scale_factor=1,
color="#355d7a",
):
"""Instantiate a bearing using inputs from an Excel table.
A header with the names of the columns is required. These names should match the
names expected by the routine (usually the names of the parameters, but also
similar ones). The program will read every row bellow the header
until they end or it reaches a NaN.
Parameters
----------
n : int
The node in which the bearing will be located in the rotor.
file : str
Path to the file containing the bearing parameters.
sheet_name : int or str, optional
Position of the sheet in the file (starting from 0) or its name. If none is
passed, it is assumed to be the first sheet in the file.
tag : str, optional
A tag to name the element.
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is connected to
ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is '#355d7a' (Cardinal).
Returns
-------
bearing : rs.BearingElement
A bearing object.
Examples
--------
>>> import os
>>> file_path = os.path.dirname(os.path.realpath(__file__)) + '/tests/data/bearing_seal_si.xls'
>>> BearingElement.from_table(0, file_path, n_link=1) # doctest: +ELLIPSIS
BearingElement(n=0, n_link=1,
kxx=[1.379...
"""
parameters = read_table_file(file, "bearing", sheet_name, n)
return cls(
n=parameters["n"],
kxx=parameters["kxx"],
cxx=parameters["cxx"],
kyy=parameters["kyy"],
kxy=parameters["kxy"],
kyx=parameters["kyx"],
cyy=parameters["cyy"],
cxy=parameters["cxy"],
cyx=parameters["cyx"],
frequency=parameters["frequency"],
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
color=color,
)
class BearingFluidFlow(BearingElement):
"""Instantiate a bearing using inputs from its fluid flow.
This method always creates elements with frequency-dependent coefficients.
It calculates a set of coefficients for each frequency value appendend to
"omega".
Parameters
----------
n : int
The node in which the bearing will be located in the rotor.
Grid related
^^^^^^^^^^^^
Describes the discretization of the problem
nz: int
Number of points along the Z direction (direction of flow).
ntheta: int
Number of points along the direction theta. NOTE: ntheta must be odd.
nradius: int
Number of points along the direction r.
length: float
Length in the Z direction (m).
Operation conditions
^^^^^^^^^^^^^^^^^^^^
Describes the operation conditions.
omega: list
List of frequencies (rad/s) used to calculate the coefficients.
If the length is greater than 1, an array of coefficients is returned.
p_in: float
Input Pressure (Pa).
p_out: float
Output Pressure (Pa).
load: float
Load applied to the rotor (N).
Geometric data of the problem
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Describes the geometric data of the problem.
radius_rotor: float
Rotor radius (m).
radius_stator: float
Stator Radius (m).
eccentricity: float
Eccentricity (m) is the euclidean distance between rotor and stator centers.
The center of the stator is in position (0,0).
Fluid characteristics
^^^^^^^^^^^^^^^^^^^^^
Describes the fluid characteristics.
visc: float
Viscosity (Pa.s).
rho: float
Fluid density(Kg/m^3).
Others
^^^^^^
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
Returns
-------
bearing: rs.BearingElement
A bearing object.
Examples
--------
>>> nz = 30
>>> ntheta = 20
>>> length = 0.03
>>> omega = [157.1]
>>> p_in = 0.
>>> p_out = 0.
>>> radius_rotor = 0.0499
>>> radius_stator = 0.05
>>> load = 525
>>> visc = 0.1
>>> rho = 860.
>>> BearingFluidFlow(0, nz, ntheta, length, omega, p_in,
... p_out, radius_rotor, radius_stator,
... visc, rho, load=load) # doctest: +ELLIPSIS
BearingFluidFlow(n=0, n_link=None,
kxx=[145...
"""
def __init__(
self,
n,
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
visc,
rho,
eccentricity=None,
load=None,
tag=None,
n_link=None,
scale_factor=1.0,
color="#355d7a",
):
K = np.zeros((4, len(omega)))
C = np.zeros((4, len(omega)))
for i, w in enumerate(omega):
fluid_flow = flow.FluidFlow(
nz,
ntheta,
length,
w,
p_in,
p_out,
radius_rotor,
radius_stator,
visc,
rho,
eccentricity=eccentricity,
load=load,
)
K[:, i], C[:, i] = calculate_stiffness_and_damping_coefficients(fluid_flow)
super().__init__(
n,
kxx=K[0],
kxy=K[1],
kyx=K[2],
kyy=K[3],
cxx=C[0],
cxy=C[1],
cyx=C[2],
cyy=C[3],
frequency=omega,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
color=color,
)
class SealElement(BearingElement):
"""A seal element.
This class will create a seal element.
Parameters can be a constant value or speed dependent.
For speed dependent parameters, each argument should be passed
as an array and the correspondent speed values should also be
passed as an array.
Values for each parameter will be_interpolated for the speed.
SealElement objects are handled differently in the Rotor class, even though it
inherits from BearingElement class. Seal elements are not considered in static
analysis, i.e., it does not add reaction forces (only bearings support the rotor).
In stability level 1 analysis, seal elements are removed temporarily from the model,
so that the cross coupled coefficients are calculated and replace the seals from
the rotor model.
SealElement data is stored in an individual data frame, separate from other
bearing elements.
Notes
-----
SealElement class is strongly recommended to represent seals.
Avoid using BearingElement class for this purpose.
Parameters
----------
n: int
Node which the bearing will be located in
kxx : float, array, pint.Quantity
Direct stiffness in the x direction (N/m).
cxx : float, array, pint.Quantity
Direct damping in the x direction (N*s/m).
kyy : float, array, pint.Quantity, optional
Direct stiffness in the y direction (N/m).
(defaults to kxx)
cyy : float, array, pint.Quantity, optional
Direct damping in the y direction (N*s/m).
(defaults to cxx)
kxy : float, array, pint.Quantity, optional
Cross coupled stiffness in the x direction (N/m).
(defaults to 0)
cxy : float, array, pint.Quantity, optional
Cross coupled damping in the x direction (N*s/m).
(defaults to 0)
kyx : float, array, pint.Quantity, optional
Cross coupled stiffness in the y direction (N/m).
(defaults to 0)
cyx : float, array, pint.Quantity, optional
Cross coupled damping in the y direction (N*s/m).
(defaults to 0)
frequency : array, pint.Quantity, optional
Array with the frequencies (rad/s).
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is "#77ACA2".
Examples
--------
>>> # A seal element located in the first rotor node, with these
>>> # following stiffness and damping coefficients and speed range from
>>> # 0 to 200 rad/s
>>> import ross as rs
>>> kxx = 1e6
>>> kyy = 0.8e6
>>> cxx = 2e2
>>> cyy = 1.5e2
>>> frequency = np.linspace(0, 200, 11)
>>> seal = rs.SealElement(n=0, kxx=kxx, kyy=kyy, cxx=cxx, cyy=cyy, frequency=frequency)
>>> seal.K(frequency) # doctest: +ELLIPSIS
array([[[1000000., 1000000., ...
>>> seal.C(frequency) # doctest: +ELLIPSIS
array([[[200., 200., ...
"""
@check_units
def __init__(
self,
n,
kxx,
cxx,
mxx=None,
kyy=None,
kxy=0,
kyx=0,
cyy=None,
cxy=0,
cyx=0,
myy=None,
mxy=0,
myx=0,
frequency=None,
seal_leakage=None,
tag=None,
n_link=None,
scale_factor=1.0,
color="#77ACA2",
**kwargs,
):
# make seals with half the bearing size as a default
seal_scale_factor = scale_factor / 2
super().__init__(
n=n,
frequency=frequency,
kxx=kxx,
kxy=kxy,
kyx=kyx,
kyy=kyy,
cxx=cxx,
cxy=cxy,
cyx=cyx,
cyy=cyy,
mxx=mxx,
mxy=mxy,
myx=myx,
myy=myy,
tag=tag,
n_link=n_link,
scale_factor=seal_scale_factor,
color=color,
)
self.seal_leakage = seal_leakage
class BallBearingElement(BearingElement):
"""A bearing element for ball bearings.
This class will create a bearing element based on some geometric and
constructive parameters of ball bearings. The main difference is that
cross-coupling stiffness and damping are not modeled in this case.
The theory used to calculate the stiffness coeficients is based on
:cite:`friswell2010dynamics` (pages 182-185). Damping is low in rolling-element
bearings and the direct damping coefficient is typically in the range of
(0.25 ~ 2.5) x 10e-5 x Kxx (or Kyy).
Parameters
----------
n : int
Node which the bearing will be located in.
n_balls : float
Number of steel spheres in the bearing.
d_balls : float
Diameter of the steel sphere.
fs : float,optional
Static bearing loading force.
alpha : float, optional
Contact angle between the steel sphere and the inner / outer raceway.
cxx : float, optional
Direct stiffness in the x direction.
Default is 1.25*10e-5 * kxx.
cyy : float, optional
Direct damping in the y direction.
Default is 1.25*10e-5 * kyy.
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
References
----------
.. bibliography::
:filter: docname in docnames
Examples
--------
>>> n = 0
>>> n_balls= 8
>>> d_balls = 0.03
>>> fs = 500.0
>>> alpha = np.pi / 6
>>> tag = "ballbearing"
>>> bearing = BallBearingElement(n=n, n_balls=n_balls, d_balls=d_balls,
... fs=fs, alpha=alpha, tag=tag)
>>> bearing.K(0)
array([[4.64168838e+07, 0.00000000e+00],
[0.00000000e+00, 1.00906269e+08]])
"""
def __init__(
self,
n,
n_balls,
d_balls,
fs,
alpha,
cxx=None,
cyy=None,
tag=None,
n_link=None,
scale_factor=1,
):
Kb = 13.0e6
kyy = (
Kb
* n_balls ** (2.0 / 3)
* d_balls ** (1.0 / 3)
* fs ** (1.0 / 3)
* (np.cos(alpha)) ** (5.0 / 3)
)
nb = [8, 12, 16]
ratio = [0.46, 0.64, 0.73]
dict_ratio = dict(zip(nb, ratio))
if n_balls in dict_ratio.keys():
kxx = dict_ratio[n_balls] * kyy
else:
f = interpolate.interp1d(nb, ratio, "quadratic", fill_value="extrapolate")
kxx = f(n_balls) * kyy
if cxx is None:
cxx = 1.25e-5 * kxx
if cyy is None:
cyy = 1.25e-5 * kyy
super().__init__(
n=n,
frequency=None,
kxx=kxx,
kxy=0.0,
kyx=0.0,
kyy=kyy,
cxx=cxx,
cxy=0.0,
cyx=0.0,
cyy=cyy,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
)
self.color = "#77ACA2"
class RollerBearingElement(BearingElement):
"""A bearing element for roller bearings.
This class will create a bearing element based on some geometric and
constructive parameters of roller bearings. The main difference is that
cross-coupling stiffness and damping are not modeled in this case.
The theory used to calculate the stiffness coeficients is based on
:cite:`friswell2010dynamics` (pages 182-185). Damping is low in rolling-element
bearings and the direct damping coefficient is typically in the range of
(0.25 ~ 2.5) x 10e-5 x Kxx (or Kyy).
Parameters
----------
n : int
Node which the bearing will be located in.
n_rollers : float
Number of steel spheres in the bearing.
l_rollers : float
Length of the steel rollers.
fs : float, optional
Static bearing loading force.
alpha : float, optional
Contact angle between the steel sphere and the inner / outer raceway.
cxx : float, optional
Direct stiffness in the x direction.
Default is 1.25*10e-5 * kxx.
cyy : float, optional
Direct damping in the y direction.
Default is 1.25*10e-5 * kyy.
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
References
----------
.. bibliography::
:filter: docname in docnames
Examples
--------
>>> n = 0
>>> n_rollers = 8
>>> l_rollers = 0.03
>>> fs = 500.0
>>> alpha = np.pi / 6
>>> tag = "rollerbearing"
>>> bearing = RollerBearingElement(n=n, n_rollers=n_rollers, l_rollers=l_rollers,
... fs=fs, alpha=alpha, tag=tag)
>>> bearing.K(0)
array([[2.72821927e+08, 0.00000000e+00],
[0.00000000e+00, 5.56779444e+08]])
"""
def __init__(
self,
n,
n_rollers,
l_rollers,
fs,
alpha,
cxx=None,
cyy=None,
tag=None,
n_link=None,
scale_factor=1,
):
Kb = 1.0e9
kyy = (
Kb
* n_rollers**0.9
* l_rollers**0.8
* fs**0.1
* (np.cos(alpha)) ** 1.9
)
nr = [8, 12, 16]
ratio = [0.49, 0.66, 0.74]
dict_ratio = dict(zip(nr, ratio))
if n_rollers in dict_ratio.keys():
kxx = dict_ratio[n_rollers] * kyy
else:
f = interpolate.interp1d(nr, ratio, "quadratic", fill_value="extrapolate")
kxx = f(n_rollers) * kyy
if cxx is None:
cxx = 1.25e-5 * kxx
if cyy is None:
cyy = 1.25e-5 * kyy
super().__init__(
n=n,
frequency=None,
kxx=kxx,
kxy=0.0,
kyx=0.0,
kyy=kyy,
cxx=cxx,
cxy=0.0,
cyx=0.0,
cyy=cyy,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
)
self.color = "#77ACA2"
class MagneticBearingElement(BearingElement):
"""Magnetic bearing.
This class creates a magnetic bearing element.
Converts electromagnetic parameters and PID gains to stiffness and damping
coefficients.
Parameters
----------
n : int
The node in which the magnetic bearing will be located in the rotor.
g0 : float
Air gap in m^2.
i0 : float
Bias current in Ampere
ag : float
Pole area in m^2.
nw : float or int
Number of windings
alpha : float or int
Pole angle in radians.
kp_pid : float or int
Proportional gain of the PID controller.
kd_pid : float or int
Derivative gain of the PID controller.
k_amp : float or int
Gain of the amplifier model.
k_sense : float or int
Gain of the sensor model.
tag : str, optional
A tag to name the element
Default is None.
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
----------
See the following reference for the electromagnetic parameters g0, i0, ag, nw, alpha:
Book: Magnetic Bearings. Theory, Design, and Application to Rotating Machinery
Authors: Gerhard Schweitzer and Eric H. Maslen
Page: 69-80
Examples
--------
>>> n = 0
>>> g0 = 1e-3
>>> i0 = 1.0
>>> ag = 1e-4
>>> nw = 200
>>> alpha = 0.392
>>> kp_pid = 1.0
>>> kd_pid = 1.0
>>> k_amp = 1.0
>>> k_sense = 1.0
>>> tag = "magneticbearing"
>>> mbearing = MagneticBearingElement(n=n, g0=g0, i0=i0, ag=ag, nw=nw,alpha=alpha,
... kp_pid=kp_pid, kd_pid=kd_pid, k_amp=k_amp,
... k_sense=k_sense)
>>> mbearing.kxx
[-4640.623377181318]
"""
def __init__(
self,
n,
g0,
i0,
ag,
nw,
alpha,
kp_pid,
kd_pid,
k_amp,
k_sense,
tag=None,
n_link=None,
scale_factor=1,
**kwargs,
):
self.g0 = g0
self.i0 = i0
self.ag = ag
self.nw = nw
self.alpha = alpha
self.kp_pid = kp_pid
self.kd_pid = kd_pid
self.k_amp = k_amp
self.k_sense = k_sense
pL = [g0, i0, ag, nw, alpha, kp_pid, kd_pid, k_amp, k_sense]
pA = [0, 0, 0, 0, 0, 0, 0, 0, 0]
# Check if it is a number or a list with 2 items
for i in range(9):
if type(pL[i]) == float or int:
pA[i] = np.array(pL[i])
else:
if type(pL[i]) == list:
if len(pL[i]) > 2:
raise ValueError(
"Parameters must be scalar or a list with 2 items"
)
else:
pA[i] = np.array(pL[i])
else:
raise ValueError("Parameters must be scalar or a list with 2 items")
# From: "Magnetic Bearings. Theory, Design, and Application to Rotating Machinery"
# Authors: Gerhard Schweitzer and Eric H. Maslen
# Page: 343
ks = (
-4.0
* pA[1] ** 2.0
* np.cos(pA[4])
* 4.0
* np.pi
* 1e-7
* pA[3] ** 2.0
* pA[2]
/ (4.0 * pA[0] ** 3)
)
ki = (
4.0
* pA[1]
* np.cos(pA[4])
* 4.0
* np.pi
* 1e-7
* pA[3] ** 2.0
* pA[2]
/ (4.0 * pA[0] ** 2)
)
k = ki * pA[7] * pA[8] * (pA[5] + np.divide(ks, ki * pA[7] * pA[8]))
c = ki * pA[7] * pA[6] * pA[8]
# k = ki * k_amp*k_sense*(kp_pid+ np.divide(ks, ki*k_amp*k_sense))
# c = ki*k_amp*kd_pid*k_sense
# Get the parameters from k and c
if np.isscalar(k):
# If k is scalar, symmetry is assumed
kxx = k
kyy = k
else:
kxx = k[0]
kyy = k[1]
if np.isscalar(c):
# If c is scalar, symmetry is assumed
cxx = c
cyy = c
else:
cxx = c[0]
cyy = c[1]
super().__init__(
n=n,
frequency=None,
kxx=kxx,
kxy=0.0,
kyx=0.0,
kyy=kyy,
cxx=cxx,
cxy=0.0,
cyx=0.0,
cyy=cyy,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
)
class CylindricalBearing(BearingElement):
"""Cylindrical hydrodynamic bearing.
A cylindrical hydrodynamic bearing modeled as per
:cite:`friswell2010dynamics` (page 177) assuming the following:
- the flow is laminar and Reynolds’s equation applies
- the bearing is very short, so that L /D << 1, where L is the bearing length and
D is the bearing diameter, which means that the pressure gradients are much
larger in the axial than in the circumferential direction
- the lubricant pressure is zero at the edges of the bearing
- the bearing is operating under steady running conditions
- the lubricant properties do not vary substantially throughout the oil film
- the shaft does not tilt in the bearing
Parameters
----------
n : int
Node which the bearing will be located in.
speed : list, pint.Quantity
List with shaft speeds frequency (rad/s).
weight : float, pint.Quantity
Gravity load (N).
It is a positive value in the -Y direction. For a symmetric rotor that is
supported by two journal bearings, it is half of the total rotor weight.
bearing_length : float, pint.Quantity
Bearing axial length (m).
journal_diameter : float, pint.Quantity
Journal diameter (m).
radial_clearance : float, pint.Quantity
Bore assembly radial clearance (m).
oil_viscosity : float, pint.Quantity
Oil viscosity (Pa.s).
Returns
-------
CylindricalBearing element.
References
----------
.. bibliography::
:filter: docname in docnames
Examples
--------
>>> import ross as rs
>>> Q_ = rs.Q_
>>> cylindrical = CylindricalBearing(
... n=0,
... speed=Q_([1500, 2000], "RPM"),
... weight=525,
... bearing_length=Q_(30, "mm"),
... journal_diameter=Q_(100, "mm"),
... radial_clearance=Q_(0.1, "mm"),
... oil_viscosity=0.1,
... )
>>> cylindrical.K(Q_(1500, "RPM")) # doctest: +ELLIPSIS
array([[ 12807959..., 16393593...],
[-25060393..., 8815302...]])
"""
@check_units
def __init__(
self,
n,
speed=None,
weight=None,
bearing_length=None,
journal_diameter=None,
radial_clearance=None,
oil_viscosity=None,
**kwargs,
):
self.n = n
self.speed = []
for spd in speed:
if spd == 0:
# replace 0 speed with small value to avoid errors
self.speed.append(0.1)
else:
self.speed.append(spd)
self.weight = weight
self.bearing_length = bearing_length
self.journal_diameter = journal_diameter
self.radial_clearance = radial_clearance
self.oil_viscosity = oil_viscosity
# modified Sommerfeld number or the Ocvirk number
Ss = (
journal_diameter
* speed
* oil_viscosity
* bearing_length**3
/ (8 * radial_clearance**2 * weight)
)
self.modified_sommerfeld = Ss
self.sommerfeld = (Ss / np.pi) * (journal_diameter / bearing_length) ** 2
# find roots
self.roots = []
for s in Ss:
poly = Polynomial(
[
1,
-(4 + np.pi**2 * s**2),
(6 - s**2 * (16 - np.pi**2)),
-4,
1,
]
)
self.roots.append(poly.roots())
# select real root between 0 and 1
self.root = []
for roots in self.roots:
for root in roots:
if (0 < root < 1) and np.isreal(root):
self.root.append(np.real(root))
self.eccentricity = [np.sqrt(root) for root in self.root]
self.attitude_angle = [
np.arctan(np.pi * np.sqrt(1 - e**2) / 4 * e) for e in self.eccentricity
]
coefficients = [
"kxx",
"kxy",
"kyx",
"kyy",
"cxx",
"cxy",
"cyx",
"cyy",
]
coefficients_dict = {coeff: [] for coeff in coefficients}
for e, spd in zip(self.eccentricity, self.speed):
π = np.pi
# fmt: off
h0 = 1 / (π ** 2 * (1 - e ** 2) + 16 * e ** 2) ** (3 / 2)
auu = h0 * 4 * (π ** 2 * (2 - e ** 2) + 16 * e ** 2)
auv = h0 * π * (π ** 2 * (1 - e ** 2) ** 2 - 16 * e ** 4) / (e * np.sqrt(1 - e ** 2))
avu = - h0 * π * (π ** 2 * (1 - e ** 2) * (1 + 2 * e ** 2) + 32 * e ** 2 * (1 + e ** 2)) / (e * np.sqrt(1 - e ** 2))
avv = h0 * 4 * (π ** 2 * (1 + 2 * e ** 2) + 32 * e ** 2 * (1 + e ** 2) / (1 - e ** 2))
buu = h0 * 2 * π * np.sqrt(1 - e ** 2) * (π ** 2 * (1 + 2 * e ** 2) - 16 * e ** 2) / e
buv = bvu = -h0 * 8 * (π ** 2 * (1 + 2 * e ** 2) - 16 * e ** 2)
bvv = h0 * 2 * π * (π ** 2 * (1 - e ** 2) ** 2 + 48 * e ** 2) / (e * np.sqrt(1 - e ** 2))
# fmt: on
for coeff, term in zip(
coefficients, [auu, auv, avu, avv, buu, buv, bvu, bvv]
):
if coeff[0] == "k":
coefficients_dict[coeff].append(weight / radial_clearance * term)
elif coeff[0] == "c":
coefficients_dict[coeff].append(
weight / (radial_clearance * spd) * term
)
super().__init__(self.n, frequency=self.speed, **coefficients_dict, **kwargs)
class BearingElement6DoF(BearingElement):
"""A generalistic 6 DoF bearing element.
This class will create a bearing
element based on the user supplied stiffness and damping coefficients. These
are determined alternatively, via purposefully built codes.
Parameters
----------
kxx : float, array, pint.Quantity
Direct stiffness in the x direction (N/m).
cxx : float, array, pint.Quantity
Direct damping in the x direction (N*s/m).
kyy : float, array, pint.Quantity, optional
Direct stiffness in the y direction (N/m).
Defaults to kxx
cyy : float, array, pint.Quantity, optional
Direct damping in the y direction (N*s/m).
Default is to cxx
kxy : float, array, pint.Quantity, optional
Cross stiffness between xy directions (N/m).
Default is 0
kyx : float, array, pint.Quantity, optional
Cross stiffness between yx directions (N/m).
Default is 0
kzz : float, array, pint.Quantity, optional
Direct stiffness in the z direction (N/m).
Default is 0
cxy : float, array, pint.Quantity, optional
Cross damping between xy directions (N*s/m).
Default is 0
cyx : float, array, pint.Quantity, optional
Cross damping between yx directions (N*s/m).
Default is 0
czz : float, array, pint.Quantity, optional
Direct damping in the z direction (N*s/m).
Default is 0
frequency : array, pint.Quantity, optional
Array with the frequencies (rad/s).
tag : str, optional
A tag to name the element
Default is None
n_link : int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor : float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
Examples
--------
>>> n = 0
>>> kxx = 1.0e7
>>> kyy = 1.5e7
>>> kzz = 5.0e5
>>> bearing = BearingElement6DoF(n=n, kxx=kxx, kyy=kyy, kzz=kzz,
... cxx=0, cyy=0)
>>> bearing.K(0)
array([[10000000., 0., 0.],
[ 0., 15000000., 0.],
[ 0., 0., 500000.]])
"""
@check_units
def __init__(
self,
n,
kxx,
cxx,
mxx=None,
kyy=None,
cyy=None,
myy=None,
kxy=0.0,
kyx=0.0,
kzz=0.0,
cxy=0.0,
cyx=0.0,
czz=0.0,
mxy=0.0,
myx=0.0,
mzz=0.0,
frequency=None,
tag=None,
n_link=None,
scale_factor=1,
color="#355d7a",
):
super().__init__(
n=n,
kxx=kxx,
cxx=cxx,
mxx=mxx,
kyy=kyy,
kxy=kxy,
kyx=kyx,
cyy=cyy,
cxy=cxy,
cyx=cyx,
myy=myy,
mxy=mxy,
myx=myx,
frequency=frequency,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
color=color,
)
new_args = ["kzz", "czz", "mzz"]
args_dict = locals()
coefficients = {}
if kzz is None:
args_dict["kzz"] = kxx * 0.0
if czz is None:
args_dict["czz"] = cxx * 0.0
if mzz is None:
if mxx is None:
args_dict["mxx"] = 0
args_dict["mzz"] = 0
else:
args_dict["mzz"] = mxx * 0.0
# check coefficients len for consistency
coefficients_len = []
for arg in new_args:
coefficient, interpolated = self._process_coefficient(args_dict[arg])
setattr(self, arg, coefficient)
setattr(self, f"{arg}_interpolated", interpolated)
coefficients_len.append(len(coefficient))
coefficients_len = [len(v.coefficient) for v in coefficients.values()]
if frequency is not None and type(frequency) != float:
coefficients_len.append(len(args_dict["frequency"]))
if len(set(coefficients_len)) > 1:
raise ValueError(
"Arguments (coefficients and frequency)"
" must have the same dimension"
)
else:
for c in coefficients_len:
if c != 1:
raise ValueError(
"Arguments (coefficients and frequency)"
" must have the same dimension"
)
def __hash__(self):
return hash(self.tag)
def __repr__(self):
"""Return a string representation of a bearing element.
Returns
-------
A string representation of a bearing element object.
Examples
--------
>>> bearing = bearing_example()
>>> bearing # doctest: +ELLIPSIS
BearingElement(n=0, n_link=None,
kxx=[...
"""
return (
f"{self.__class__.__name__}"
f"(n={self.n}, n_link={self.n_link},\n"
f" kxx={self.kxx}, kxy={self.kxy},\n"
f" kyx={self.kyx}, kyy={self.kyy},\n"
f" kzz={self.kzz}, cxx={self.cxx},\n"
f" cxy={self.cxy}, cyx={self.cyx},\n"
f" cyy={self.cyy}, czz={self.czz},\n"
f" mxx={self.mxx}, mxy={self.mxy},\n"
f" myx={self.myx}, myy={self.myy},\n"
f" mzz={self.mzz},\n"
f" frequency={self.frequency}, tag={self.tag!r})"
)
def __eq__(self, other):
"""Equality method for comparasions.
Parameters
----------
other : object
The second object to be compared with.
Returns
-------
bool
True if the comparison is true; False otherwise.
Examples
--------
>>> bearing1 = bearing_example()
>>> bearing2 = bearing_example()
>>> bearing1 == bearing2
True
"""
compared_attributes = [
"kxx",
"kyy",
"kxy",
"kyx",
"kzz",
"cxx",
"cyy",
"cxy",
"cyx",
"czz",
"mxx",
"myy",
"mxy",
"myx",
"mzz",
"frequency",
]
if isinstance(other, self.__class__):
init_args = []
for arg in signature(self.__init__).parameters:
if arg not in ["kwargs"]:
init_args.append(arg)
init_args_comparison = []
for arg in init_args:
comparison = getattr(self, arg) == getattr(other, arg)
try:
comparison = all(comparison)
except TypeError:
pass
init_args_comparison.append(comparison)
init_args_comparison = all(init_args_comparison)
attributes_comparison = all(
(
(
np.array(getattr(self, attr)) == np.array(getattr(other, attr))
).all()
for attr in compared_attributes
)
)
return init_args_comparison and attributes_comparison
return False
def save(self, file):
try:
data = toml.load(file)
except FileNotFoundError:
data = {}
# remove some info before saving
brg_data = self.__dict__.copy()
params_to_remove = [
"kxx_interpolated",
"kyy_interpolated",
"kxy_interpolated",
"kyx_interpolated",
"kzz_interpolated",
"cxx_interpolated",
"cyy_interpolated",
"cxy_interpolated",
"cyx_interpolated",
"czz_interpolated",
"dof_global_index",
]
for p in params_to_remove:
brg_data.pop(p)
# change np.array to lists so that we can save in .toml as list(floats)
params = [
"kxx",
"kyy",
"kxy",
"kyx",
"kzz",
"cxx",
"cyy",
"cxy",
"cyx",
"czz",
"mxx",
"myy",
"mxy",
"myx",
"mzz",
"frequency",
]
for p in params:
try:
brg_data[p] = [float(i) for i in brg_data[p]]
except TypeError:
pass
data[f"{self.__class__.__name__}_{self.tag}"] = brg_data
with open(file, "w") as f:
toml.dump(data, f)
@classmethod
def load(cls, file):
data = toml.load(file)
# extract single dictionary in the data
data = list(data.values())[0]
params = [
"kxx",
"kyy",
"kxy",
"kyx",
"kzz",
"cxx",
"cyy",
"cxy",
"cyx",
"czz",
"mxx",
"myy",
"mxy",
"myx",
"mzz",
"frequency",
"n",
"tag",
"n_link",
"scale_factor",
]
kwargs = {}
for p in params:
try:
kwargs[p] = data.pop(p)
except KeyError:
pass
bearing = cls(**kwargs)
for k, v in data.items():
setattr(bearing, k, v)
return bearing
def dof_mapping(self):
"""Degrees of freedom mapping.
Returns a dictionary with a mapping between degree of freedom and its index.
Returns
-------
dof_mapping : dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
The numbering of the degrees of freedom for each node.
Being the following their ordering for a node:
x_0 - horizontal translation
y_0 - vertical translation
z_0 - axial translation
>>> bearing = bearing_6dof_example()
>>> bearing.dof_mapping()
{'x_0': 0, 'y_0': 1, 'z_0': 2}
"""
return dict(x_0=0, y_0=1, z_0=2)
def M(self, frequency):
"""Mass matrix for an instance of a bearing element.
This method returns the mass matrix for an instance of a bearing
element.
Returns
-------
M : np.ndarray
Mass matrix (kg).
Examples
--------
>>> bearing = bearing_6dof_example()
>>> bearing.M(0)
array([[0., 0., 0.],
[0., 0., 0.],
[0., 0., 0.]])
"""
mxx = self.mxx_interpolated(frequency)
myy = self.myy_interpolated(frequency)
mxy = self.mxy_interpolated(frequency)
myx = self.myx_interpolated(frequency)
mzz = self.mzz_interpolated(frequency)
M = np.array([[mxx, mxy, 0], [myx, myy, 0], [0, 0, mzz]])
return M
def K(self, frequency):
"""Stiffness matrix for an instance of a bearing element.
This method returns the stiffness matrix for an instance of a bearing element.
Parameters
----------
frequency : float
The excitation frequency (rad/s).
Returns
-------
K : np.ndarray
A 3x3 matrix of floats containing the kxx, kxy, kyx, kyy and kzz values (N/m).
Examples
--------
>>> bearing = bearing_6dof_example()
>>> bearing.K(0)
array([[1000000., 0., 0.],
[ 0., 800000., 0.],
[ 0., 0., 100000.]])
"""
kxx = self.kxx_interpolated(frequency)
kyy = self.kyy_interpolated(frequency)
kxy = self.kxy_interpolated(frequency)
kyx = self.kyx_interpolated(frequency)
kzz = self.kzz_interpolated(frequency)
K = np.array([[kxx, kxy, 0], [kyx, kyy, 0], [0, 0, kzz]])
return K
def C(self, frequency):
"""Damping matrix for an instance of a bearing element.
This method returns the damping matrix for an instance of a bearing element.
Parameters
----------
frequency : float
The excitation frequency (rad/s).
Returns
-------
C: np.ndarray
A 3x3 matrix of floats containing the cxx, cxy, cyx, cyy, and czz values (N/m).
Examples
--------
>>> bearing = bearing_6dof_example()
>>> bearing.C(0)
array([[200., 0., 0.],
[ 0., 150., 0.],
[ 0., 0., 50.]])
"""
cxx = self.cxx_interpolated(frequency)
cyy = self.cyy_interpolated(frequency)
cxy = self.cxy_interpolated(frequency)
cyx = self.cyx_interpolated(frequency)
czz = self.czz_interpolated(frequency)
C = np.array([[cxx, cxy, 0], [cyx, cyy, 0], [0, 0, czz]])
return C
def bearing_example():
"""Create an example of bearing element.
This function returns an instance of a simple seal. The purpose is to make
available a simple model so that doctest can be written using it.
Returns
-------
An instance of a bearing object.
Examples
--------
>>> bearing = bearing_example()
>>> bearing.frequency[0]
0.0
"""
w = np.linspace(0, 200, 11)
bearing = BearingElement(n=0, kxx=1e6, kyy=0.8e6, cxx=2e2, cyy=1.5e2, frequency=w)
return bearing
def seal_example():
"""Create an example of seal element.
This function returns an instance of a simple seal. The purpose is to make
available a simple model so that doctest can be written using it.
Returns
-------
seal : ross.SealElement
An instance of a bearing object.
Examples
--------
>>> seal = seal_example()
>>> seal.frequency[0]
0.0
"""
w = np.linspace(0, 200, 11)
seal = SealElement(n=0, kxx=1e6, kyy=0.8e6, cxx=2e2, cyy=1.5e2, frequency=w)
return seal
def bearing_6dof_example():
"""Create an example of bearing element.
This function returns an instance of a simple bearing. The purpose is to make
available a simple model so that doctest can be written using it.
Returns
-------
bearing : ross.BearingElement6DoF
An instance of a bearing object.
Examples
--------
>>> bearing = bearing_6dof_example()
>>> bearing.kxx
[1000000.0]"""
bearing = BearingElement6DoF(
n=0, kxx=1e6, kyy=0.8e6, cxx=2e2, cyy=1.5e2, kzz=1e5, czz=0.5e2
)
return bearing | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/bearing_seal_element.py | 0.842183 | 0.552238 | bearing_seal_element.py | pypi |
import os
from pathlib import Path
import numpy as np
import toml
from plotly import graph_objects as go
from ross.element import Element
from ross.units import check_units
__all__ = ["PointMass"]
class PointMass(Element):
"""A point mass element.
This class will create a point mass element.
This element can be used to link other elements in the analysis.
The mass provided to the element can be different on the x and y direction
(e.g. different support inertia for x and y directions).
Parameters
----------
n: int
Node which the bearing will be located in.
m: float, pint.Quantity, optional
Mass for the element.
mx: float, pint.Quantity, optional
Mass for the element on the x direction.
my: float, pint.Quantity, optional
Mass for the element on the y direction.
tag: str
A tag to name the element
color : str, optional
A color to be used when the element is represented.
Default is "DarkSalmon".
Examples
--------
>>> p0 = PointMass(n=0, m=2)
>>> p0.M()
array([[2., 0.],
[0., 2.]])
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.M()
array([[2., 0.],
[0., 3.]])
"""
@check_units
def __init__(self, n=None, m=None, mx=None, my=None, tag=None, color="DarkSalmon"):
self.n = n
self.m = m
if mx is None and my is None:
mx = float(m)
my = float(m)
self.mx = float(mx)
self.my = float(my)
self.tag = tag
self.dof_global_index = None
self.color = color
def __hash__(self):
return hash(self.tag)
def __eq__(self, other):
"""Equality method for comparasions.
Parameters
----------
other : obj
parameter for comparasion
Returns
-------
True if other is equal to the reference parameter.
False if not.
Example
-------
>>> pointmass1 = point_mass_example()
>>> pointmass2 = point_mass_example()
>>> pointmass1 == pointmass2
True
"""
if self.__dict__ == other.__dict__:
return True
else:
return False
def __repr__(self):
"""Return a string representation of a point mass element.
Returns
-------
A string representation of a point mass element object.
Examples
--------
>>> point_mass = point_mass_example()
>>> point_mass
PointMass(n=0, mx=1.0, my=2.0, tag='pointmass')
"""
return (
f"{self.__class__.__name__}"
f"(n={self.n}, mx={self.mx:{0}.{5}},"
f" my={self.my:{0}.{5}}, tag={self.tag!r})"
)
def __str__(self):
"""Convert object into string.
Returns
-------
The object's parameters translated to strings
Example
-------
>>> print(PointMass(n=0, mx=2.5, my=3.25, tag="PointMass"))
Tag: PointMass
Node: 0
Mass X dir. (kg): 2.5
Mass Y dir. (kg): 3.25
"""
return (
f"Tag: {self.tag}"
f"\nNode: {self.n}"
f"\nMass X dir. (kg): {self.mx:{2}.{5}}"
f"\nMass Y dir. (kg): {self.my:{2}.{5}}"
)
def M(self):
"""Mass matrix for an instance of a point mass element.
This method will return the mass matrix for an instance of a point mass element.
Returns
-------
M : np.ndarray
A matrix of floats containing the values of the mass matrix.
Examples
--------
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.M()
array([[2., 0.],
[0., 3.]])
"""
mx = self.mx
my = self.my
# fmt: off
M = np.array([[mx, 0],
[0, my]])
# fmt: on
return M
def C(self):
"""Damping matrix for an instance of a point mass element.
This method will return the damping matrix for an instance of a point mass
element.
Returns
-------
C : np.ndarray
A matrix of floats containing the values of the damping matrix.
Examples
--------
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.C()
array([[0., 0.],
[0., 0.]])
"""
C = np.zeros((2, 2))
return C
def K(self):
"""Stiffness matrix for an instance of a point mass element.
This method will return the stiffness matrix for an instance of a point mass
element.
Returns
-------
K : np.ndarray
A matrix of floats containing the values of the stiffness matrix.
Examples
--------
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.K()
array([[0., 0.],
[0., 0.]])
"""
K = np.zeros((2, 2))
return K
def G(self):
"""Gyroscopic matrix for an instance of a point mass element.
This method will return the gyroscopic matrix for an instance of a point mass
element.
Returns
-------
G : np.ndarray
A matrix of floats containing the values of the gyroscopic matrix.
Examples
--------
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.G()
array([[0., 0.],
[0., 0.]])
"""
G = np.zeros((2, 2))
return G
def dof_mapping(self):
"""Degrees of freedom mapping.
Returns a dictionary with a mapping between degree of freedom and its index.
Returns
-------
dof_mapping : dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
The numbering of the degrees of freedom for each node.
Being the following their ordering for a node:
x_0 - horizontal translation
y_0 - vertical translation
>>> p1 = PointMass(n=0, mx=2, my=3)
>>> p1.dof_mapping()
{'x_0': 0, 'y_0': 1}
"""
return dict(x_0=0, y_0=1)
def _patch(self, position, fig):
"""Point mass element patch.
Patch that will be used to draw the point mass element using Plotly library.
Parameters
----------
position : float
Position in which the patch will be drawn.
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
Returns
-------
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
"""
zpos, ypos = position
radius = ypos / 12
customdata = [self.n, self.mx, self.my]
hovertemplate = (
f"PointMass Node: {customdata[0]}<br>"
+ f"Mass (X): {customdata[1]:.3f}<br>"
+ f"Mass (Y): {customdata[2]:.3f}<br>"
)
fig.add_trace(
go.Scatter(
x=[zpos, zpos],
y=[ypos, -ypos],
customdata=[customdata] * 2,
text=hovertemplate,
mode="markers",
marker=dict(size=5.0, color=self.color),
showlegend=False,
name=self.tag,
legendgroup="pointmass",
hoverinfo="text",
hovertemplate=hovertemplate,
hoverlabel=dict(bgcolor=self.color),
)
)
fig.add_shape(
dict(
type="circle",
xref="x",
yref="y",
x0=zpos - radius,
y0=ypos - radius,
x1=zpos + radius,
y1=ypos + radius,
fillcolor=self.color,
line_color="black",
)
)
fig.add_shape(
dict(
type="circle",
xref="x",
yref="y",
x0=zpos - radius,
y0=-ypos - radius,
x1=zpos + radius,
y1=-ypos + radius,
fillcolor=self.color,
line_color="black",
)
)
return fig
def point_mass_example():
"""Create an example of point mass element.
This function returns an instance of a simple point mass. The purpose is to make
available a simple model so that doctest can be written using it.
Returns
-------
point_mass : ross.PointMass
An instance of a point mass object.
Examples
--------
>>> pointmass = point_mass_example()
>>> pointmass.mx
1.0
"""
n = 0
mx = 1.0
my = 2.0
point_mass = PointMass(n=n, mx=mx, my=my, tag="pointmass")
return point_mass | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/point_mass.py | 0.909926 | 0.672795 | point_mass.py | pypi |
import inspect
import warnings
from functools import wraps
from pathlib import Path
import pint
new_units_path = Path(__file__).parent / "new_units.txt"
ureg = pint.get_application_registry()
if isinstance(ureg.get(), pint.registry.LazyRegistry):
ureg = pint.UnitRegistry()
ureg.load_definitions(str(new_units_path))
# set ureg to make pickle possible
pint.set_application_registry(ureg)
Q_ = ureg.Quantity
with warnings.catch_warnings():
warnings.simplefilter("ignore")
pint.Quantity([])
__all__ = ["Q_", "check_units"]
units = {
"E": "N/m**2",
"G_s": "N/m**2",
"rho": "kg/m**3",
"density": "kg/m**3",
"L": "meter",
"idl": "meter",
"idr": "meter",
"odl": "meter",
"odr": "meter",
"id": "meter",
"od": "meter",
"i_d": "meter",
"o_d": "meter",
"speed": "radian/second",
"frequency": "radian/second",
"m": "kg",
"mx": "kg",
"my": "kg",
"Ip": "kg*m**2",
"Id": "kg*m**2",
"width": "meter",
"depth": "meter",
"thickness": "meter",
"pitch": "meter",
"height": "meter",
"radius": "meter",
"diameter": "meter",
"clearance": "meter",
"length": "meter",
"area": "meter**2",
"unbalance_magnitude": "kg*m",
"unbalance_phase": "rad",
"pressure": "pascal",
"pressure_ratio": "dimensionless",
"p": "pascal",
"temperature": "degK",
"T": "degK",
"velocity": "m/s",
"angle": "rad",
"arc": "rad",
"convection": "W/(m²*degK)",
"conductivity": "W/(m*degK)",
"expansion": "1/degK",
"stiffness": "N/m",
"weight": "N",
"load": "N",
"force": "N",
"torque": "N*m",
"flow_v": "meter**3/second",
"flow_m": "kilogram/second",
"fit": "m",
"viscosity": "pascal*s",
"h": "joule/kilogram",
"s": "joule/(kelvin kilogram)",
"b": "meter",
"D": "meter",
"d": "meter",
"roughness": "meter",
"head": "joule/kilogram",
"eff": "dimensionless",
"power": "watt",
}
for i, unit in zip(["k", "c", "m"], ["N/m", "N*s/m", "kg"]):
for j in ["x", "y", "z"]:
for k in ["x", "y", "z"]:
units["".join([i, j, k])] = unit
def check_units(func):
"""Wrapper to check and convert units to base_units.
If we use the check_units decorator in a function the arguments are checked,
and if they are in the dictionary, they are converted to the 'default' unit given
in the dictionary.
The check is carried out by splitting the argument name on '_', and checking
if any of the names are in the dictionary. So an argument such as 'inlet_pressure',
will be split into ['inlet', 'pressure'], and since we have the name 'pressure'
in the dictionary mapped to 'Pa', we will automatically convert the value to
this default unit.
For example:
>>> units = {
... "L": "meter",
... }
>>> @check_units
... def foo(L=None):
... print(L)
...
If we call the function with the argument as a float:
>>> foo(L=0.5)
0.5
If we call the function with a pint.Quantity object the value is automatically
converted to the default:
>>> foo(L=Q_(0.5, 'inches'))
0.0127
"""
@wraps(func)
def inner(*args, **kwargs):
base_unit_args = []
args_names = inspect.getfullargspec(func)[0]
for arg_name, arg_value in zip(args_names, args):
names = arg_name.split("_")
if "units" in names:
base_unit_args.append(arg_value)
continue
# treat flow_v and flow_m separately
if "flow_v" in arg_name:
names.insert(0, "flow_v")
if "flow_m" in arg_name:
names.insert(0, "flow_m")
if arg_name not in names:
# check first for arg_name in units
names.insert(0, arg_name)
for name in names:
if name in units and arg_value is not None:
# For now, we only return the magnitude for the converted Quantity
# If pint is fully adopted by ross in the future, and we have all Quantities
# using it, we could remove this, which would allows us to use pint in its full capability
try:
base_unit_args.append(arg_value.to(units[name]).m)
except AttributeError:
try:
base_unit_args.append(Q_(arg_value, units[name]).m)
except TypeError:
# Handle erros that we get with bool for example
base_unit_args.append(arg_value)
break
else:
base_unit_args.append(arg_value)
base_unit_kwargs = {}
for k, v in kwargs.items():
names = k.split("_")
if "units" in names:
base_unit_kwargs[k] = v
continue
# treat flow_v and flow_m separately
if "flow_v" in k:
names.insert(0, "flow_v")
if "flow_m" in k:
names.insert(0, "flow_m")
if k not in names:
# check first for arg_name in units
names.insert(0, k)
for name in names:
if name in units and v is not None:
try:
base_unit_kwargs[k] = v.to(units[name]).m
except AttributeError:
try:
base_unit_kwargs[k] = Q_(v, units[name]).m
except TypeError:
# Handle errors that we get with bool for example
base_unit_kwargs[k] = v
break
else:
base_unit_kwargs[k] = v
return func(*base_unit_args, **base_unit_kwargs)
return inner | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/units.py | 0.575111 | 0.38318 | units.py | pypi |
import os
from pathlib import Path
import numpy as np
import toml
from plotly import graph_objects as go
from ross.element import Element
from ross.units import check_units
from ross.utils import read_table_file
__all__ = ["DiskElement", "DiskElement6DoF"]
class DiskElement(Element):
"""A disk element.
This class creates a disk element from input data of inertia and mass.
Parameters
----------
n: int
Node in which the disk will be inserted.
m : float, pint.Quantity
Mass of the disk element.
Id : float, pint.Quantity
Diametral moment of inertia.
Ip : float, pint.Quantity
Polar moment of inertia
tag : str, optional
A tag to name the element
Default is None
scale_factor: float or str, optional
The scale factor is used to scale the disk drawing.
For disks it is also possible to provide 'mass' as the scale factor.
In this case the code will calculate scale factors for each disk based
on the disk with the higher mass. Notice that in this case you have to
create all disks with the scale_factor='mass'.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is 'Firebrick'.
Examples
--------
>>> disk = DiskElement(n=0, m=32, Id=0.2, Ip=0.3)
>>> disk.Ip
0.3
"""
@check_units
def __init__(self, n, m, Id, Ip, tag=None, scale_factor=1.0, color="Firebrick"):
self.n = int(n)
self.n_l = n
self.n_r = n
self.m = float(m)
self.Id = float(Id)
self.Ip = float(Ip)
self.tag = tag
self.color = color
self.scale_factor = scale_factor
self.dof_global_index = None
def __eq__(self, other):
"""Equality method for comparasions.
Parameters
----------
other: object
The second object to be compared with.
Returns
-------
bool
True if the comparison is true; False otherwise.
Examples
--------
>>> disk1 = disk_example()
>>> disk2 = disk_example()
>>> disk1 == disk2
True
"""
false_number = 0
for i in self.__dict__:
try:
if np.allclose(self.__dict__[i], other.__dict__[i]):
pass
else:
false_number += 1
except TypeError:
if self.__dict__[i] == other.__dict__[i]:
pass
else:
false_number += 1
if false_number == 0:
return True
else:
return False
def __repr__(self):
"""Return a string representation of a disk element.
Returns
-------
A string representation of a disk element object.
Examples
--------
>>> disk = disk_example()
>>> disk # doctest: +ELLIPSIS
DiskElement(Id=0.17809, Ip=0.32956...
"""
return (
f"{self.__class__.__name__}"
f"(Id={self.Id:{0}.{5}}, Ip={self.Ip:{0}.{5}}, "
f"m={self.m:{0}.{5}}, color={self.color!r}, "
f"n={self.n}, scale_factor={self.scale_factor}, tag={self.tag!r})"
)
def __str__(self):
"""Convert object into string.
Returns
-------
The object's parameters translated to strings
Example
-------
>>> print(DiskElement(n=0, m=32, Id=0.223, Ip=0.31223, tag="Disk"))
Tag: Disk
Node: 0
Mass (kg): 32.0
Diam. inertia (kg*m**2): 0.223
Polar. inertia (kg*m**2): 0.31223
"""
return (
f"Tag: {self.tag}"
f"\nNode: {self.n}"
f"\nMass (kg): {self.m:{2}.{5}}"
f"\nDiam. inertia (kg*m**2): {self.Id:{2}.{5}}"
f"\nPolar. inertia (kg*m**2): {self.Ip:{2}.{5}}"
)
def __hash__(self):
return hash(self.tag)
def dof_mapping(self):
"""Degrees of freedom mapping.
Returns a dictionary with a mapping between degree of freedom and its index.
Returns
-------
dof_mapping : dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
The numbering of the degrees of freedom for each node.
Being the following their ordering for a node:
x_0 - horizontal translation
y_0 - vertical translation
alpha_0 - rotation around horizontal
beta_0 - rotation around vertical
>>> disk = disk_example()
>>> disk.dof_mapping()
{'x_0': 0, 'y_0': 1, 'alpha_0': 2, 'beta_0': 3}
"""
return dict(x_0=0, y_0=1, alpha_0=2, beta_0=3)
def M(self):
"""Mass matrix for an instance of a disk element.
This method will return the mass matrix for an instance of a disk element.
Returns
-------
M : np.ndarray
A matrix of floats containing the values of the mass matrix.
Examples
--------
>>> disk = DiskElement(0, 32.58972765, 0.17808928, 0.32956362)
>>> disk.M()
array([[32.58972765, 0. , 0. , 0. ],
[ 0. , 32.58972765, 0. , 0. ],
[ 0. , 0. , 0.17808928, 0. ],
[ 0. , 0. , 0. , 0.17808928]])
"""
m = self.m
Id = self.Id
# fmt: off
M = np.array([[m, 0, 0, 0],
[0, m, 0, 0],
[0, 0, Id, 0],
[0, 0, 0, Id]])
# fmt: on
return M
def K(self):
"""Stiffness matrix for an instance of a disk element.
This method will return the stiffness matrix for an instance of a disk
element.
Returns
-------
K : np.ndarray
A matrix of floats containing the values of the stiffness matrix.
Examples
--------
>>> disk = disk_example()
>>> disk.K()
array([[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]])
"""
K = np.zeros((4, 4))
return K
def C(self):
"""Damping matrix for an instance of a disk element.
This method will return the damping matrix for an instance of a disk
element.
Returns
-------
C : np.ndarray
A matrix of floats containing the values of the damping matrix.
Examples
--------
>>> disk = disk_example()
>>> disk.C()
array([[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.],
[0., 0., 0., 0.]])
"""
C = np.zeros((4, 4))
return C
def G(self):
"""Gyroscopic matrix for an instance of a disk element.
This method will return the gyroscopic matrix for an instance of a disk
element.
Returns
-------
G: np.ndarray
Gyroscopic matrix for the disk element.
Examples
--------
>>> disk = DiskElement(0, 32.58972765, 0.17808928, 0.32956362)
>>> disk.G()
array([[ 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0.32956362],
[ 0. , 0. , -0.32956362, 0. ]])
"""
Ip = self.Ip
# fmt: off
G = np.array([[0, 0, 0, 0],
[0, 0, 0, 0],
[0, 0, 0, Ip],
[0, 0, -Ip, 0]])
# fmt: on
return G
def _patch(self, position, fig):
"""Disk element patch.
Patch that will be used to draw the shaft element using plotly library.
Parameters
----------
position : float
Position in which the patch will be drawn.
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
Returns
-------
fig : plotly.graph_objects.Figure
The figure object which traces are added on.
"""
zpos, ypos, scale_factor = position
radius = scale_factor / 8
# coordinates to plot disks elements
z_upper = [zpos, zpos + scale_factor / 25, zpos - scale_factor / 25, zpos]
y_upper = [ypos, ypos + 2 * scale_factor, ypos + 2 * scale_factor, ypos]
z_lower = [zpos, zpos + scale_factor / 25, zpos - scale_factor / 25, zpos]
y_lower = [-ypos, -ypos - 2 * scale_factor, -ypos - 2 * scale_factor, -ypos]
z_pos = z_upper
z_pos.append(None)
z_pos.extend(z_lower)
y_pos = y_upper
y_upper.append(None)
y_pos.extend(y_lower)
customdata = [self.n, self.Ip, self.Id, self.m]
hovertemplate = (
f"Disk Node: {customdata[0]}<br>"
+ f"Polar Inertia: {customdata[1]:.3e}<br>"
+ f"Diametral Inertia: {customdata[2]:.3e}<br>"
+ f"Disk mass: {customdata[3]:.3f}<br>"
)
fig.add_trace(
go.Scatter(
x=z_pos,
y=y_pos,
customdata=[customdata] * len(z_pos),
text=hovertemplate,
mode="lines",
fill="toself",
fillcolor=self.color,
opacity=0.8,
line=dict(width=2.0, color=self.color),
showlegend=False,
name=self.tag,
legendgroup="disks",
hoveron="points+fills",
hoverinfo="text",
hovertemplate=hovertemplate,
hoverlabel=dict(bgcolor=self.color),
)
)
fig.add_shape(
dict(
type="circle",
xref="x",
yref="y",
x0=zpos - radius,
y0=y_upper[1] - radius,
x1=zpos + radius,
y1=y_upper[1] + radius,
fillcolor=self.color,
line_color=self.color,
)
)
fig.add_shape(
dict(
type="circle",
xref="x",
yref="y",
x0=zpos - radius,
y0=y_lower[1] - radius,
x1=zpos + radius,
y1=y_lower[1] + radius,
fillcolor=self.color,
line_color=self.color,
)
)
return fig
@classmethod
@check_units
def from_geometry(
cls, n, material, width, i_d, o_d, tag=None, scale_factor=1.0, color="Firebrick"
):
"""Create a disk element from geometry properties.
This class method will create a disk element from geometry data.
Parameters
----------
n : int
Node in which the disk will be inserted.
material: ross.Material
Disk material.
width : float, pint.Quantity
The disk width.
i_d : float, pint.Quantity
Inner diameter.
o_d : float, pint.Quantity
Outer diameter.
tag : str, optional
A tag to name the element
Default is None
scale_factor: float, optional
The scale factor is used to scale the disk drawing.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is 'Firebrick' (Cardinal).
Attributes
----------
m : float
Mass of the disk element.
Id : float
Diametral moment of inertia.
Ip : float
Polar moment of inertia
Examples
--------
>>> from ross.materials import steel
>>> disk = DiskElement.from_geometry(0, steel, 0.07, 0.05, 0.28)
>>> disk.Ip
0.32956362089137037
"""
m = 0.25 * material.rho * np.pi * width * (o_d**2 - i_d**2)
# fmt: off
Id = (
0.015625 * material.rho * np.pi * width * (o_d ** 4 - i_d ** 4)
+ m * (width ** 2) / 12
)
# fmt: on
Ip = 0.03125 * material.rho * np.pi * width * (o_d**4 - i_d**4)
tag = tag
return cls(n, m, Id, Ip, tag, scale_factor, color)
@classmethod
def from_table(cls, file, sheet_name=0, tag=None, scale_factor=None, color=None):
"""Instantiate one or more disks using inputs from an Excel table.
A header with the names of the columns is required. These names should
match the names expected by the routine (usually the names of the
parameters, but also similar ones). The program will read every row
bellow the header until they end or it reaches a NaN.
Parameters
----------
file : str
Path to the file containing the disk parameters.
sheet_name : int or str, optional
Position of the sheet in the file (starting from 0) or its name.
If none is passed, it is assumed to be the first sheet in the file.
tag_list : list, optional
list of tags for the disk elements.
Default is None
scale_factor: list, optional
List of scale factors for the disk elements patches.
The scale factor is used to scale the disk drawing.
Default is 1.
color : list, optional
A color to be used when the element is represented.
Default is 'Firebrick'.
Returns
-------
disk : list
A list of disk objects.
Examples
--------
>>> import os
>>> file_path = os.path.dirname(os.path.realpath(__file__)) + '/tests/data/shaft_si.xls'
>>> list_of_disks = DiskElement.from_table(file_path, sheet_name="More")
>>> list_of_disks[0]
DiskElement(Id=0.0, Ip=0.0, m=15.12, color='Firebrick', n=3, scale_factor=1, tag=None)
"""
parameters = read_table_file(file, "disk", sheet_name=sheet_name)
if tag is None:
tag = [None] * len(parameters["n"])
if scale_factor is None:
scale_factor = [1] * len(parameters["n"])
if color is None:
color = ["Firebrick"] * len(parameters["n"])
list_of_disks = []
for i in range(0, len(parameters["n"])):
list_of_disks.append(
cls(
n=parameters["n"][i],
m=parameters["m"][i],
Id=float(parameters["Id"][i]),
Ip=float(parameters["Ip"][i]),
tag=tag[i],
scale_factor=scale_factor[i],
color=color[i],
)
)
return list_of_disks
class DiskElement6DoF(DiskElement):
"""A disk element for 6 DoFs.
This class will create a disk element with 6 DoF from input data of inertia and
mass.
Parameters
----------
n: int
Node in which the disk will be inserted.
m : float, pint.Quantity
Mass of the disk element.
Id : float, pint.Quantity
Diametral moment of inertia.
Ip : float, pint.Quantity
Polar moment of inertia
tag : str, optional
A tag to name the element
Default is None
scale_factor: float, optional
The scale factor is used to scale the disk drawing.
Default is 1.
color : str, optional
A color to be used when the element is represented.
Default is 'Firebrick'.
Examples
--------
>>> disk = DiskElement6DoF(n=0, m=32, Id=0.2, Ip=0.3)
>>> disk.Ip
0.3
"""
def dof_mapping(self):
"""Degrees of freedom mapping.
Returns a dictionary with a mapping between degree of freedom and its index.
Returns
-------
dof_mapping : dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
The numbering of the degrees of freedom for each node.
Being the following their ordering for a node:
x_0 - horizontal translation
y_0 - vertical translation
z_0 - axial translation
alpha_0 - rotation around horizontal
beta_0 - rotation around vertical
theta_0 - torsion around axial
>>> disk = disk_example_6dof()
>>> disk.dof_mapping()
{'x_0': 0, 'y_0': 1, 'z_0': 2, 'alpha_0': 3, 'beta_0': 4, 'theta_0': 5}
"""
return dict(x_0=0, y_0=1, z_0=2, alpha_0=3, beta_0=4, theta_0=5)
def M(self):
"""Mass matrix for an instance of a 6 DoF disk element.
This method will return the mass matrix for an instance of a disk
element with 6DoFs.
Returns
-------
M : np.ndarray
Mass matrix for the 6DoFs disk element.
Examples
--------
>>> disk = DiskElement6DoF(0, 32.58972765, 0.17808928, 0.32956362)
>>> disk.M().round(2)
array([[32.59, 0. , 0. , 0. , 0. , 0. ],
[ 0. , 32.59, 0. , 0. , 0. , 0. ],
[ 0. , 0. , 32.59, 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0.18, 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0.18, 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0.33]])
"""
m = self.m
Id = self.Id
Ip = self.Ip
# fmt: off
M = np.array([
[m, 0, 0, 0, 0, 0],
[0, m, 0, 0, 0, 0],
[0, 0, m, 0, 0, 0],
[0, 0, 0, Id, 0, 0],
[0, 0, 0, 0, Id, 0],
[0, 0, 0, 0, 0, Ip],
])
# fmt: on
return M
def K(self):
"""Stiffness matrix for an instance of a 6 DoF disk element.
This method will return the stiffness matrix for an instance of a disk
element with 6DoFs.
Returns
-------
K : np.ndarray
A matrix of floats containing the values of the stiffness matrix.
Examples
--------
>>> disk = disk_example_6dof()
>>> disk.K().round(2)
array([[0. , 0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0. , 0. , 0. ],
[0. , 0. , 0. , 0.33, 0. , 0. ]])
"""
Ip = self.Ip
# fmt: off
K = np.array([
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, Ip, 0, 0],
])
# fmt: on
return K
def C(self):
"""Damping matrix for an instance of a 6 DoF disk element.
Returns
-------
C : np.ndarray
A matrix of floats containing the values of the damping matrix.
Examples
--------
>>> disk = disk_example_6dof()
>>> disk.C()
array([[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.],
[0., 0., 0., 0., 0., 0.]])
"""
C = np.zeros((6, 6))
return C
def G(self):
"""Gyroscopic matrix for an instance of a 6 DoF disk element.
This method will return the gyroscopic matrix for an instance of a disk
element.
Returns
-------
G : np.ndarray
Gyroscopic matrix for the disk element.
Examples
--------
>>> disk = DiskElement6DoF(0, 32.58972765, 0.17808928, 0.32956362)
>>> disk.G().round(2)
array([[ 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0.33, 0. ],
[ 0. , 0. , 0. , -0.33, 0. , 0. ],
[ 0. , 0. , 0. , 0. , 0. , 0. ]])
"""
Ip = self.Ip
# fmt: off
G = np.array([
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, Ip, 0],
[0, 0, 0, -Ip, 0, 0],
[0, 0, 0, 0, 0, 0],
])
# fmt: on
return G
def disk_example():
"""Create an example of disk element.
This function returns an instance of a simple disk. The purpose is to make available
a simple model so that doctest can be written using it.
Returns
-------
disk : ross.DiskElement
An instance of a disk object.
Examples
--------
>>> disk = disk_example()
>>> disk.Ip
0.32956362
"""
disk = DiskElement(0, 32.589_727_65, 0.178_089_28, 0.329_563_62)
return disk
def disk_example_6dof():
"""Create an example of disk element.
This function returns an instance of a simple disk. The purpose is to make available
a simple model so that doctest can be written using it.
Returns
-------
disk : ross.DiskElement6DoF
An instance of a disk object.
Examples
--------
>>> disk = disk_example_6dof()
>>> disk.Ip
0.32956362
"""
disk = DiskElement6DoF(0, 32.589_727_65, 0.178_089_28, 0.329_563_62)
return disk | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/disk_element.py | 0.849535 | 0.478346 | disk_element.py | pypi |
from pathlib import Path
import numpy as np
import toml
from .units import check_units
__all__ = ["Material", "steel"]
ROSS_PATH = Path(__file__).parent
AVAILABLE_MATERIALS_PATH = ROSS_PATH / "available_materials.toml"
class Material:
"""Material used on shaft and disks.
Class used to create a material and define its properties.
Density and at least 2 arguments from E, G_s and Poisson should be
provided.
You can run rs.Material.available_materials() to get a list of materials
already provided.
Parameters
----------
name : str
Material name.
rho : float, pint.Quantity
Density (kg/m**3).
E : float, pint.Quantity, optional
Young's modulus (N/m**2).
G_s : float, pint.Quantity, optional
Shear modulus (N/m**2).
Poisson : float, optional
Poisson ratio (dimensionless).
color : str, optional
Color that will be used on plots.
Examples
--------
>>> from ross.units import Q_
>>> AISI4140 = Material(name="AISI4140", rho=7850, E=203.2e9, G_s=80e9)
>>> Steel = Material(name="Steel", rho=Q_(7.81, 'g/cm**3'), E=211e9, G_s=81.2e9)
>>> AISI4140.Poisson
0.27
>>> Steel.rho
7809.999999999999
"""
@check_units
def __init__(
self, name, rho, E=None, G_s=None, Poisson=None, color="#525252", **kwargs
):
self.name = str(name)
if " " in name:
raise ValueError("Spaces are not allowed in Material name")
given_args = []
for arg in ["E", "G_s", "Poisson"]:
if locals()[arg] is not None:
given_args.append(arg)
if len(given_args) != 2:
raise ValueError(
"Exactly 2 arguments from E, G_s and Poisson should be provided"
)
if E is None:
E = G_s * (2 * (1 + Poisson))
elif G_s is None:
G_s = E / (2 * (1 + Poisson))
elif Poisson is None:
Poisson = (E / (2 * G_s)) - 1
self.rho = float(rho)
self.E = float(E)
self.G_s = float(G_s)
self.Poisson = float(Poisson)
self.color = color
def __eq__(self, other):
"""Equality method for comparasions.
Parameters
----------
other: object
The second object to be compared with.
Returns
-------
bool
True if the comparison is true; False otherwise.
Examples
--------
>>> import ross as rs
>>> steel = rs.Material.load_material('Steel')
>>> AISI4140 = rs.Material.load_material('AISI4140')
>>> steel == AISI4140
False
"""
self_list = [v for v in self.__dict__.values() if isinstance(v, (float, int))]
other_list = [v for v in other.__dict__.values() if isinstance(v, (float, int))]
if np.allclose(self_list, other_list):
return True
else:
return False
def __repr__(self):
"""Return a string representation of a material.
Returns
-------
A string representation of a material object.
Examples
--------
>>> import ross as rs
>>> steel = rs.Material.load_material('Steel')
>>> steel # doctest: +ELLIPSIS
Material(name="Steel", rho=7.81000e+03, G_s=8.12000e+10, E=2.11000e+11, color='#525252')
"""
selfE = "{:.5e}".format(self.E)
selfrho = "{:.5e}".format(self.rho)
selfGs = "{:.5e}".format(self.G_s)
return (
f"Material"
f'(name="{self.name}", rho={selfrho}, G_s={selfGs}, '
f"E={selfE}, color={self.color!r})"
)
def __str__(self):
"""Convert object into string.
Returns
-------
The object's parameters translated to strings
Examples
--------
>>> import ross as rs
>>> print(rs.Material.load_material('Steel'))
Steel
-----------------------------------
Density (kg/m**3): 7810.0
Young`s modulus (N/m**2): 2.11e+11
Shear modulus (N/m**2): 8.12e+10
Poisson coefficient : 0.29926108
"""
return (
f"{self.name}"
f'\n{35*"-"}'
f"\nDensity (kg/m**3): {self.rho:{2}.{8}}"
f"\nYoung`s modulus (N/m**2): {self.E:{2}.{8}}"
f"\nShear modulus (N/m**2): {self.G_s:{2}.{8}}"
f"\nPoisson coefficient : {self.Poisson:{2}.{8}}"
)
@staticmethod
def dump_data(data):
"""Save material properties.
This is an auxiliary function to save the materials properties in the save
method.
Parameters
----------
data : dict
Dictionary containing all data needed to instantiate the Object.
"""
with open(AVAILABLE_MATERIALS_PATH, "w") as f:
toml.dump(data, f)
@staticmethod
def get_data():
"""Load material properties.
This is an auxiliary function to load all saved materials properties in the
load_material method.
Returns
-------
data : dict
Containing all data needed to instantiate a Material Object.
"""
try:
with open(AVAILABLE_MATERIALS_PATH, "r") as f:
data = toml.load(f)
except FileNotFoundError:
data = {"Materials": {}}
Material.dump_data(data)
return data
@staticmethod
def load_material(name):
"""Load a material that is available in the data file.
Returns
-------
ross.Material
An object with the material properties.
Raises
------
KeyError
Error raised if argument name does not match any material name in the file.
Examples
--------
>>> import ross as rs
>>> steel = rs.Material.load_material('Steel')
"""
data = Material.get_data()
try:
# Remove Poisson from dict and create material from E and G_s
data["Materials"][name].pop("Poisson")
material = data["Materials"][name]
return Material(**material)
except KeyError:
raise KeyError("There isn't a instanced material with this name.")
@staticmethod
def remove_material(name):
"""Delete a saved ross.Material.
Parameters
----------
name : string
Name of Material Object to be deleted.
Examples
--------
>>> import ross as rs
>>> steel = rs.Material.load_material('Steel')
>>> steel.name = 'test_material'
>>> steel.save_material()
>>> steel.remove_material('test_material')
"""
data = Material.get_data()
try:
del data["Materials"][name]
except KeyError:
return "There isn't a saved material with this name."
Material.dump_data(data)
@staticmethod
def available_materials():
"""Return a list of all saved material's name.
Returns
-------
available_materials : list
A list containing all saved material's names.
Examples
--------
>>> import ross as rs
>>> steel = rs.Material.load_material('Steel')
>>> steel.name = 'test_material'
>>> steel.save_material()
>>> steel.remove_material('test_material')
"""
try:
data = Material.get_data()
return list(data["Materials"].keys())
except FileNotFoundError:
return "There is no saved materials."
def save_material(self):
"""Save the material in the available_materials list."""
data = Material.get_data()
data["Materials"][self.name] = self.__dict__
Material.dump_data(data)
steel = Material(name="Steel", rho=7810, E=211e9, G_s=81.2e9) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/materials.py | 0.897922 | 0.468061 | materials.py | pypi |
from plotly import graph_objects as go
from plotly import io as pio
# tableau colors
tableau_colors = {
"blue": "#1f77b4",
"orange": "#ff7f0e",
"green": "#2ca02c",
"red": "#d62728",
"purple": "#9467bd",
"brown": "#8c564b",
"pink": "#e377c2",
"gray": "#7f7f7f",
"olive": "#bcbd22",
"cyan": "#17becf",
}
pio.templates["ross"] = go.layout.Template(
layout={
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1,
},
"coloraxis": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"colorscale": {
"diverging": [
[0, "#8e0152"],
[0.1, "#c51b7d"],
[0.2, "#de77ae"],
[0.3, "#f1b6da"],
[0.4, "#fde0ef"],
[0.5, "#f7f7f7"],
[0.6, "#e6f5d0"],
[0.7, "#b8e186"],
[0.8, "#7fbc41"],
[0.9, "#4d9221"],
[1, "#276419"],
],
"sequential": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"sequentialminus": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
},
"colorway": list(tableau_colors.values()),
"font": {"color": "#2a3f5f"},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "white",
"showlakes": True,
"showland": True,
"subunitcolor": "#C8D4E3",
},
"hoverlabel": {"align": "left"},
"hovermode": "closest",
"mapbox": {"style": "light"},
"paper_bgcolor": "white",
"plot_bgcolor": "white",
"polar": {
"angularaxis": {
"gridcolor": "#EBF0F8",
"linecolor": "#EBF0F8",
"ticks": "",
},
"bgcolor": "white",
"radialaxis": {"gridcolor": "#EBF0F8", "linecolor": "#EBF0F8", "ticks": ""},
},
"scene": {
"xaxis": {
"backgroundcolor": "white",
"gridcolor": "#DFE8F3",
"gridwidth": 2,
"linecolor": "#EBF0F8",
"showbackground": True,
"ticks": "",
"zerolinecolor": "#EBF0F8",
"showspikes": False,
},
"yaxis": {
"backgroundcolor": "white",
"gridcolor": "#DFE8F3",
"gridwidth": 2,
"linecolor": "#EBF0F8",
"showbackground": True,
"ticks": "",
"zerolinecolor": "#EBF0F8",
"showspikes": False,
},
"zaxis": {
"backgroundcolor": "white",
"gridcolor": "#DFE8F3",
"gridwidth": 2,
"linecolor": "#EBF0F8",
"showbackground": True,
"ticks": "",
"zerolinecolor": "#EBF0F8",
"showspikes": False,
},
"camera": {
"up": {"x": 0, "y": 0, "z": 1},
"center": {"x": 0, "y": 0, "z": 0},
"eye": {"x": 2.0, "y": 2.0, "z": 2.0},
},
},
"shapedefaults": {"line": {"color": "#2a3f5f"}},
"ternary": {
"aaxis": {"gridcolor": "#DFE8F3", "linecolor": "#A2B1C6", "ticks": ""},
"baxis": {"gridcolor": "#DFE8F3", "linecolor": "#A2B1C6", "ticks": ""},
"bgcolor": "white",
"caxis": {"gridcolor": "#DFE8F3", "linecolor": "#A2B1C6", "ticks": ""},
},
"title": {"x": 0.05},
"xaxis": {
"automargin": True,
"gridcolor": "#EBF0F8",
"showline": True,
"linecolor": "black",
"linewidth": 2.0,
"mirror": True,
"ticks": "",
"title": {"standoff": 15},
"zeroline": False,
"zerolinecolor": "#EBF0F8",
"zerolinewidth": 2,
},
"yaxis": {
"automargin": True,
"gridcolor": "#EBF0F8",
"showline": True,
"linecolor": "black",
"linewidth": 2.0,
"mirror": True,
"ticks": "",
"title": {"standoff": 15},
"zeroline": False,
"zerolinecolor": "#EBF0F8",
"zerolinewidth": 2,
},
},
data={
"bar": [
{
"error_x": {"color": "#2a3f5f"},
"error_y": {"color": "#2a3f5f"},
"marker": {"line": {"color": "white", "width": 0.5}},
"type": "bar",
}
],
"barpolar": [
{"marker": {"line": {"color": "white", "width": 0.5}}, "type": "barpolar"}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "#C8D4E3",
"linecolor": "#C8D4E3",
"minorgridcolor": "#C8D4E3",
"startlinecolor": "#2a3f5f",
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "#C8D4E3",
"linecolor": "#C8D4E3",
"minorgridcolor": "#C8D4E3",
"startlinecolor": "#2a3f5f",
},
"type": "carpet",
}
],
"choropleth": [
{"colorbar": {"outlinewidth": 0, "ticks": ""}, "type": "choropleth"}
],
"contour": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "contour",
}
],
"contourcarpet": [
{"colorbar": {"outlinewidth": 0, "ticks": ""}, "type": "contourcarpet"}
],
"heatmap": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "heatmap",
}
],
"heatmapgl": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "heatmapgl",
}
],
"histogram": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "histogram",
}
],
"histogram2d": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "histogram2d",
}
],
"histogram2dcontour": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "histogram2dcontour",
}
],
"mesh3d": [{"colorbar": {"outlinewidth": 0, "ticks": ""}, "type": "mesh3d"}],
"parcoords": [
{
"line": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "parcoords",
}
],
"pie": [{"automargin": True, "type": "pie"}],
"scatter": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scatter",
}
],
"scatter3d": [
{
"line": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}, "size": 4},
"type": "scatter3d",
}
],
"scattercarpet": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scattercarpet",
}
],
"scattergeo": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scattergeo",
}
],
"scattergl": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scattergl",
}
],
"scattermapbox": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scattermapbox",
}
],
"scatterpolar": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scatterpolar",
}
],
"scatterpolargl": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scatterpolargl",
}
],
"scatterternary": [
{
"marker": {"colorbar": {"outlinewidth": 0, "ticks": ""}},
"type": "scatterternary",
}
],
"surface": [
{
"colorbar": {"outlinewidth": 0, "ticks": ""},
"colorscale": [
[0.0, "#0d0887"],
[0.1111111111111111, "#46039f"],
[0.2222222222222222, "#7201a8"],
[0.3333333333333333, "#9c179e"],
[0.4444444444444444, "#bd3786"],
[0.5555555555555556, "#d8576b"],
[0.6666666666666666, "#ed7953"],
[0.7777777777777778, "#fb9f3a"],
[0.8888888888888888, "#fdca26"],
[1.0, "#f0f921"],
],
"type": "surface",
}
],
"table": [
{
"cells": {"fill": {"color": "#EBF0F8"}, "line": {"color": "white"}},
"header": {"fill": {"color": "#C8D4E3"}, "line": {"color": "white"}},
"type": "table",
}
],
},
) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/plotly_theme.py | 0.58439 | 0.533458 | plotly_theme.py | pypi |
import re
import numpy as np
import pandas as pd
from plotly import graph_objects as go
class DataNotFoundError(Exception):
"""
An exception indicating that the data could not be found in the file.
"""
pass
def read_table_file(file, element, sheet_name=0, n=0, sheet_type="Model"):
"""Instantiate one or more element objects using inputs from an Excel table.
Parameters
----------
file: str
Path to the file containing the shaft parameters.
element: str
Specify the type of element to be instantiated: bearing, shaft or disk.
sheet_name: int or str, optional
Position of the sheet in the file (starting from 0) or its name. If none is
passed, it is assumed to be the first sheet in the file.
n: int
Exclusive for bearing elements, since this parameter is given outside the table
file.
sheet_type: str
Exclusive for shaft elements, as they have a Model table in which more
information can be passed, such as the material parameters.
Returns
-------
A dictionary of parameters.
Examples
--------
>>> import os
>>> file_path = os.path.dirname(os.path.realpath(__file__)) + '/tests/data/shaft_si.xls'
>>> read_table_file(file_path, "shaft", sheet_type="Model", sheet_name="Model") # doctest: +ELLIPSIS
{'L': [0.03...
"""
df = pd.read_excel(file, header=None, sheet_name=sheet_name)
# Assign specific values to variables
parameter_columns = {}
optional_parameter_columns = {}
header_key_word = ""
default_dictionary = {}
parameters = {}
if element == "bearing":
header_key_word = "kxx"
parameter_columns["kxx"] = ["kxx"]
parameter_columns["cxx"] = ["cxx"]
optional_parameter_columns["kyy"] = ["kyy"]
optional_parameter_columns["kxy"] = ["kxy"]
optional_parameter_columns["kyx"] = ["kyx"]
optional_parameter_columns["cyy"] = ["cyy"]
optional_parameter_columns["cxy"] = ["cxy"]
optional_parameter_columns["cyx"] = ["cyx"]
optional_parameter_columns["frequency"] = ["frequency", "speed"]
default_dictionary["kyy"] = None
default_dictionary["kxy"] = 0
default_dictionary["kyx"] = 0
default_dictionary["cyy"] = None
default_dictionary["cxy"] = 0
default_dictionary["cyx"] = 0
default_dictionary["frequency"] = None
elif element == "shaft":
if sheet_type == "Model":
header_key_word = "od_left"
else:
header_key_word = "material"
parameter_columns["L"] = ["length"]
parameter_columns["idl"] = ["i_d_l", "idl", "id_left"]
parameter_columns["odl"] = ["o_d_l", "odl", "od_left"]
parameter_columns["idr"] = ["i_d_r", "idr", "id_right"]
parameter_columns["odr"] = ["o_d_r", "odr", "od_right"]
parameter_columns["material"] = ["material", "matnum"]
optional_parameter_columns["n"] = ["n", "elemnum"]
optional_parameter_columns["axial_force"] = [
"axial_force",
"axial force",
"axial",
]
optional_parameter_columns["torque"] = ["torque"]
optional_parameter_columns["shear_effects"] = ["shear_effects", "shear effects"]
optional_parameter_columns["rotary_inertia"] = [
"rotary_inertia",
"rotary inertia",
]
optional_parameter_columns["gyroscopic"] = ["gyroscopic"]
optional_parameter_columns["shear_method_calc"] = [
"shear_method_calc",
"shear method calc",
]
default_dictionary["n"] = None
default_dictionary["axial_force"] = 0
default_dictionary["torque"] = 0
default_dictionary["shear_effects"] = True
default_dictionary["rotary_inertia"] = True
default_dictionary["gyroscopic"] = True
default_dictionary["shear_method_calc"] = "cowper"
elif element == "disk":
header_key_word = "ip"
parameter_columns["n"] = ["unnamed: 0", "n"]
parameter_columns["m"] = ["m", "mass"]
parameter_columns["Id"] = ["it", "id"]
parameter_columns["Ip"] = ["ip"]
# Find table header and define if conversion is needed
header_index = -1
header_found = False
convert_to_metric = False
convert_to_rad_per_sec = False
for index, row in df.iterrows():
for i in range(0, row.size):
if isinstance(row[i], str):
if not header_found:
if row[i].lower() == header_key_word:
header_index = index
header_found = True
if (
"inches" in row[i].lower()
or "lbm" in row[i].lower()
or "lb" in row[i].lower()
):
convert_to_metric = True
if "rpm" in row[i].lower():
convert_to_rad_per_sec = True
if header_found and convert_to_metric and convert_to_rad_per_sec:
break
if header_found and convert_to_metric:
break
if not header_found:
raise ValueError(
"Could not find the header. Make sure the table has a header "
"containing the names of the columns. In the case of a " + element + ", "
"there should be a column named " + header_key_word + "."
)
# Get specific data from the file
new_materials = {}
if element == "shaft" and sheet_type == "Model":
material_header_index = -1
material_header_found = False
material_header_key_word = "matno"
for index, row in df.iterrows():
for i in range(0, row.size):
if isinstance(row[i], str):
if row[i].lower() == material_header_key_word:
material_header_index = index
material_header_found = True
break
if material_header_found:
break
if not material_header_found:
raise ValueError(
"Could not find the header for the materials. Make sure the table has a header "
"with the parameters for the materials that will be used. There should be a column "
"named " + material_header_key_word + "."
)
df_material = pd.read_excel(
file, header=material_header_index, sheet_name=sheet_name
)
material_name = []
material_rho = []
material_e = []
material_g_s = []
material_color = []
for index, row in df_material.iterrows():
if not pd.isna(row["matno"]):
material_name.append(int(row["matno"]))
material_rho.append(row["rhoa"])
material_e.append(row["ea"])
material_g_s.append(row["ga"])
if "color" in df_material.columns:
if pd.isna(row["color"]):
material_color.append("#525252")
else:
material_color.append(row["color"])
else:
material_color.append("#525252")
else:
break
if convert_to_metric:
for i in range(0, len(material_name)):
material_rho[i] = material_rho[i] * 27679.904
material_e[i] = material_e[i] * 6894.757
material_g_s[i] = material_g_s[i] * 6894.757
new_materials["matno"] = material_name
new_materials["rhoa"] = material_rho
new_materials["ea"] = material_e
new_materials["ga"] = material_g_s
new_materials["color"] = material_color
df = pd.read_excel(file, header=header_index, sheet_name=sheet_name)
df.columns = df.columns.str.lower()
# Find and isolate data rows
first_data_row_found = False
last_data_row_found = False
indexes_to_drop = []
for index, row in df.iterrows():
if (
not first_data_row_found
and (
isinstance(row[header_key_word], int)
or isinstance(row[header_key_word], float)
)
and not pd.isna(row[header_key_word])
):
first_data_row_found = True
elif not first_data_row_found:
indexes_to_drop.append(index)
elif first_data_row_found and not last_data_row_found:
if (
isinstance(row[header_key_word], int)
or isinstance(row[header_key_word], float)
) and not pd.isna(row[header_key_word]):
continue
else:
last_data_row_found = True
indexes_to_drop.append(index)
elif last_data_row_found:
indexes_to_drop.append(index)
if not first_data_row_found:
raise DataNotFoundError(
"Could not find the data. Make sure you have at least one row containing "
"data below the header."
)
if len(indexes_to_drop) > 0:
df = df.drop(indexes_to_drop)
# Build parameters list
if element == "bearing":
parameters["n"] = n
for key, value in parameter_columns.items():
for name in value:
try:
parameters[key] = df[name].tolist()
break
except KeyError:
if name == value[-1]:
raise ValueError(
"Could not find a column with one of these names: " + str(value)
)
continue
for key, value in optional_parameter_columns.items():
for name in value:
try:
parameters[key] = df[name].tolist()
break
except KeyError:
if name == value[-1]:
parameters[key] = [default_dictionary[key]] * df.shape[0]
else:
continue
if element == "shaft":
if sheet_type == "Model":
new_material = parameters["material"]
for i in range(0, df.shape[0]):
new_material[i] = "shaft_mat_" + str(int(new_material[i]))
parameters["material"] = new_material
# change xltrc index to python index (0 based)
if element in ("shaft", "disk"):
new_n = parameters["n"]
for i in range(0, df.shape[0]):
new_n[i] -= 1
parameters["n"] = new_n
if convert_to_metric:
for i in range(0, df.shape[0]):
if element == "bearing":
parameters["kxx"][i] = parameters["kxx"][i] * 175.126_836_986_4
parameters["cxx"][i] = parameters["cxx"][i] * 175.126_836_986_4
parameters["kyy"][i] = parameters["kyy"][i] * 175.126_836_986_4
parameters["kxy"][i] = parameters["kxy"][i] * 175.126_836_986_4
parameters["kyx"][i] = parameters["kyx"][i] * 175.126_836_986_4
parameters["cyy"][i] = parameters["cyy"][i] * 175.126_836_986_4
parameters["cxy"][i] = parameters["cxy"][i] * 175.126_836_986_4
parameters["cyx"][i] = parameters["cyx"][i] * 175.126_836_986_4
if element == "shaft":
parameters["L"][i] = parameters["L"][i] * 0.0254
parameters["idl"][i] = parameters["idl"][i] * 0.0254
parameters["odl"][i] = parameters["odl"][i] * 0.0254
parameters["idr"][i] = parameters["idr"][i] * 0.0254
parameters["odr"][i] = parameters["odr"][i] * 0.0254
parameters["axial_force"][i] = (
parameters["axial_force"][i] * 4.448_221_615_255
)
elif element == "disk":
parameters["m"][i] = parameters["m"][i] * 0.453_592_37
parameters["Id"][i] = parameters["Id"][i] * 0.000_292_639_7
parameters["Ip"][i] = parameters["Ip"][i] * 0.000_292_639_7
if convert_to_rad_per_sec:
for i in range(0, df.shape[0]):
if element == "bearing":
parameters["frequency"][i] = (
parameters["frequency"][i] * 0.104_719_755_119_7
)
parameters.update(new_materials)
return parameters
def visualize_matrix(rotor, matrix, frequency=None, **kwargs):
"""Visualize global matrix.
This function gives some visualization of a given matrix, displaying
values on a heatmap.
Parameters
----------
rotor: rs.Rotor
The rotor object.
matrix: str
String for the desired matrix.
frequency: float, optional
Excitation frequency. Defaults to rotor speed.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. coloraixs=dict(colorscale="Rainbow"), width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> import ross as rs
>>> rotor = rs.rotor_example()
Visualizing Mass Matrix:
>>> fig = rs.visualize_matrix(rotor, "M", frequency=100)
Visualizing Stiffness Matrix:
>>> fig = rs.visualize_matrix(rotor, "K", frequency=100)
Visualizing Gyroscopic Matrix:
>>> fig = rs.visualize_matrix(rotor, "G")
"""
A = np.zeros((rotor.ndof, rotor.ndof))
# E will store element's names and contributions to the global matrix
E = np.zeros((rotor.ndof, rotor.ndof), dtype=object)
M, N = E.shape
for i in range(M):
for j in range(N):
E[i, j] = []
for elm in rotor.elements:
g_dofs = list(elm.dof_global_index.values())
l_dofs = elm.dof_local_index()
try:
elm_matrix = getattr(elm, matrix)(frequency)
except TypeError:
elm_matrix = getattr(elm, matrix)()
A[np.ix_(g_dofs, g_dofs)] += elm_matrix
for l0, g0 in zip(l_dofs, g_dofs):
for l1, g1 in zip(l_dofs, g_dofs):
if elm_matrix[l0, l1] != 0:
E[g0, g1].append(
"<br>"
+ elm.__class__.__name__
+ f"(n={elm.n})"
+ f": {elm_matrix[l0, l1]:.2E}"
)
# list for dofs -> ['x0', 'y0', 'alpha0', 'beta0', 'x1'...]
dof_list = [0 for i in range(rotor.ndof)]
for elm in rotor.elements:
for k, v in elm.dof_global_index.items():
dof_list[v] = k
data = {"row": [], "col": [], "value": [], "pos_value": [], "elements": []}
for i, dof_row in enumerate(dof_list):
for j, dof_col in enumerate(dof_list):
data["row"].append(i)
data["col"].append(j)
data["value"].append(A[i, j])
data["pos_value"].append(abs(A[i, j]))
data["elements"].append(E[i, j])
dof_string_list = []
sub = str.maketrans("0123456789", "₀₁₂₃₄₅₆₇₈₉")
for d in dof_list:
d = d.replace("alpha", "α")
d = d.replace("beta", "β")
d = d.replace("_", "")
d = d.translate(sub)
dof_string_list.append(d)
x_axis = dof_string_list
y_axis = dof_string_list[::-1]
fig = go.Figure()
fig.add_trace(
go.Heatmap(
x=x_axis,
y=y_axis,
z=A[::-1],
customdata=np.array(data["elements"], dtype=object).reshape(A.shape)[::-1],
coloraxis="coloraxis",
hovertemplate=(
"<b>Value: %{z:.3e}<b><br>" + "<b>Elements:<b><br> %{customdata}"
),
name="<b>Matrix {}</b>".format(matrix),
)
)
fig.update_layout(
coloraxis=dict(
cmin=np.amin(A),
cmax=np.amax(A),
colorscale="Rainbow",
colorbar=dict(
title=dict(text="<b>Value</b>", side="top"), exponentformat="power"
),
),
**kwargs,
)
return fig
def convert(name):
"""Converts a CamelCase str to a underscore_case str
Parameters
----------
file: str
Path to the file containing the shaft parameters.
Returns
-------
underscore_case string
Examples
--------
>>> convert('CamelCase')
'camel_case'
"""
s1 = re.sub("(.)([A-Z][a-z]+)", r"\1_\2", name)
return re.sub("([a-z0-9])([A-Z])", r"\1_\2", s1).lower()
def intersection(x1, y1, x2, y2):
"""
Intersection code from https://github.com/sukhbinder/intersection
MIT License
Copyright (c) 2017 Sukhbinder Singh
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
INTERSECTIONS Intersections of curves.
Computes the (x,y) locations where two curves intersect. The curves
can be broken with NaNs or have vertical segments.
Usage:
x, y = intersection(x1, y1, x2, y2)
Example:
a, b = 1, 2
phi = np.linspace(3, 10, 100)
x1 = a*phi - b*np.sin(phi)
y1 = a - b*np.cos(phi)
x2=phi
y2=np.sin(phi)+2
x,y=intersection(x1,y1,x2,y2)
plt.plot(x1,y1,c='r')
plt.plot(x2,y2,c='g')
plt.plot(x,y,'*k')
plt.show()
"""
def _rect_inter_inner(x1, x2):
n1 = x1.shape[0] - 1
n2 = x2.shape[0] - 1
X1 = np.c_[x1[:-1], x1[1:]]
X2 = np.c_[x2[:-1], x2[1:]]
S1 = np.tile(X1.min(axis=1), (n2, 1)).T
S2 = np.tile(X2.max(axis=1), (n1, 1))
S3 = np.tile(X1.max(axis=1), (n2, 1)).T
S4 = np.tile(X2.min(axis=1), (n1, 1))
return S1, S2, S3, S4
def _rectangle_intersection_(x1, y1, x2, y2):
S1, S2, S3, S4 = _rect_inter_inner(x1, x2)
S5, S6, S7, S8 = _rect_inter_inner(y1, y2)
C1 = np.less_equal(S1, S2)
C2 = np.greater_equal(S3, S4)
C3 = np.less_equal(S5, S6)
C4 = np.greater_equal(S7, S8)
ii, jj = np.nonzero(C1 & C2 & C3 & C4)
return ii, jj
x1 = np.asarray(x1)
x2 = np.asarray(x2)
y1 = np.asarray(y1)
y2 = np.asarray(y2)
ii, jj = _rectangle_intersection_(x1, y1, x2, y2)
n = len(ii)
dxy1 = np.diff(np.c_[x1, y1], axis=0)
dxy2 = np.diff(np.c_[x2, y2], axis=0)
T = np.zeros((4, n))
AA = np.zeros((4, 4, n))
AA[0:2, 2, :] = -1
AA[2:4, 3, :] = -1
AA[0::2, 0, :] = dxy1[ii, :].T
AA[1::2, 1, :] = dxy2[jj, :].T
BB = np.zeros((4, n))
BB[0, :] = -x1[ii].ravel()
BB[1, :] = -x2[jj].ravel()
BB[2, :] = -y1[ii].ravel()
BB[3, :] = -y2[jj].ravel()
for i in range(n):
try:
T[:, i] = np.linalg.solve(AA[:, :, i], BB[:, i])
except:
T[:, i] = np.Inf
in_range = (T[0, :] >= 0) & (T[1, :] >= 0) & (T[0, :] <= 1) & (T[1, :] <= 1)
xy0 = T[2:, in_range]
xy0 = xy0.T
return xy0[:, 0], xy0[:, 1]
def get_data_from_figure(fig):
"""Get data from a Plotly ccatter plot (XY) and convert to a pd.DataFrame.
This function takes a go.Figure() object from Plotly and converts the data to a
DataFrame from Pandas. It works only for Scatter Plots (XY) and does no support
subplots or polar plots.
This function is suitable to the following analyzes:
- run_freq_response()
- run_unbalance_response()
- run_time_response()
Parameters
----------
fig : go.Figure
A Plotly figure generated by go.Figure() command.
Returns
-------
df : pd.DataFrame
A DataFrame with the fig.data.
Examples
--------
>>> import ross as rs
>>> rotor = rs.rotor_example()
Get post-processed data from an unbalance response
>>> resp = rotor.run_unbalance_response(
... 3, 0.001, 0.0, np.linspace(0, 1000, 101)
... )
>>> fig = resp.plot_magnitude(probe=[(3, 0.0, "probe1"), (3, np.pi/2, "probe2")])
>>> df = rs.get_data_from_figure(fig)
Use the probe tag to navigate through pandas data
Index 0 for frequency array
>>> df["probe1"][0] # doctest: +ELLIPSIS
array([ 0., 10., 20., 30.,...
Index 1 for amplitude array
>>> df["probe1"][1] # doctest: +ELLIPSIS
array([0.00000000e+00,...
Or use "iloc" to obtain the desired array from pandas
>>> df.iloc[1, 0] # doctest: +ELLIPSIS
array([0.00000000e+00, 1.6057...
"""
dict_data = {data["name"]: {} for data in fig.data}
xaxis_label = fig.layout.xaxis.title.text
yaxis_label = fig.layout.yaxis.title.text
for i, data in enumerate(fig.data):
dict_data[data["name"]][xaxis_label] = data.x
dict_data[data["name"]][yaxis_label] = data.y
df = pd.DataFrame(dict_data)
return df | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/utils.py | 0.717408 | 0.371336 | utils.py | pypi |
import inspect
from abc import ABC, abstractmethod
from collections import namedtuple
from pathlib import Path
import pandas as pd
import toml
class Element(ABC):
"""Element class.
This class is a general abstract class to be implemented in other files, in order to
create specific elements for the user.
"""
def __init__(self, n, tag=None):
self.n = n
self.tag = tag
def save(self, file):
"""Save the element in a .toml file.
This function will save the element to a .toml file.
The file will have all the argument's names and values that are needed to
reinstantiate the element.
Parameters
----------
file : str, pathlib.Path
The name of the file the element will be saved in.
Examples
--------
>>> # Example using DiskElement
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> from ross.disk_element import disk_example
>>> # create path for a temporary file
>>> file = Path(tempdir) / 'disk.toml'
>>> disk = disk_example()
>>> disk.save(file)
"""
# get __init__ arguments
signature = inspect.signature(self.__init__)
args_list = list(signature.parameters)
args = {arg: getattr(self, arg) for arg in args_list}
try:
data = toml.load(file)
except FileNotFoundError:
data = {}
data[f"{self.__class__.__name__}_{self.tag}"] = args
with open(file, "w") as f:
toml.dump(data, f)
@classmethod
def read_toml_data(cls, data):
"""Read and parse data stored in a .toml file.
The data passed to this method needs to be according to the
format saved in the .toml file by the .save() method.
Parameters
----------
data : dict
Dictionary obtained from toml.load().
Returns
-------
The element object.
Examples
--------
>>> # Example using BearingElement
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> from ross.bearing_seal_element import bearing_example
>>> from ross.bearing_seal_element import BearingElement
>>> # create path for a temporary file
>>> file = Path(tempdir) / 'bearing1.toml'
>>> bearing1 = bearing_example()
>>> bearing1.save(file)
>>> bearing1_loaded = BearingElement.load(file)
>>> bearing1 == bearing1_loaded
True
"""
return cls(**data)
@classmethod
def load(cls, file):
data = toml.load(file)
# extract single dictionary in the data
data = list(data.values())[0]
return cls.read_toml_data(data)
@abstractmethod
def M(self):
"""Mass matrix.
Returns
-------
A matrix of floats.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.M(0)
array([[0., 0.],
[0., 0.]])
"""
pass
@abstractmethod
def C(self, frequency):
"""Frequency dependent damping coefficients matrix.
Parameters
----------
frequency: float
The frequency in which the coefficients depend on.
Returns
-------
A matrix of floats.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.C(0)
array([[200., 0.],
[ 0., 150.]])
"""
pass
@abstractmethod
def K(self, frequency):
"""Frequency dependent stiffness coefficients matrix.
Parameters
----------
frequency: float
The frequency in which the coefficients depend on.
Returns
-------
A matrix of floats.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.K(0)
array([[1000000., 0.],
[ 0., 800000.]])
"""
pass
@abstractmethod
def G(self):
"""Gyroscopic matrix.
Returns
-------
A matrix of floats.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.G()
array([[0., 0.],
[0., 0.]])
"""
pass
def summary(self):
"""Present a summary for the element.
A pandas series with the element properties as variables.
Returns
-------
A pandas series.
Examples
--------
>>> # Example using DiskElement
>>> from ross.disk_element import disk_example
>>> disk = disk_example()
>>> disk.summary() # doctest: +ELLIPSIS
n 0
n_l 0
n_r 0...
"""
attributes = self.__dict__
attributes["type"] = self.__class__.__name__
return pd.Series(attributes)
@abstractmethod
def dof_mapping(self):
"""Degrees of freedom mapping.
Should return a dictionary with a mapping between degree of freedom
and its index.
Returns
-------
dof_mapping: dict
A dictionary containing the degrees of freedom and their indexes.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.dof_mapping()
{'x_0': 0, 'y_0': 1}
"""
pass
def dof_local_index(self):
"""Get the local index for a element specific degree of freedom.
Returns
-------
local_index: namedtupple
A named tuple containing the local index.
Examples
--------
>>> # Example using BearingElement
>>> from ross.bearing_seal_element import bearing_example
>>> bearing = bearing_example()
>>> bearing.dof_local_index()
LocalIndex(x_0=0, y_0=1)
"""
dof_mapping = self.dof_mapping()
dof_tuple = namedtuple("LocalIndex", dof_mapping)
local_index = dof_tuple(**dof_mapping)
return local_index | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/element.py | 0.881449 | 0.461623 | element.py | pypi |
from ross.shaft_element import ShaftElement
from ross.stochastic.st_materials import ST_Material
from ross.stochastic.st_results_elements import plot_histogram
from ross.units import Q_, check_units
__all__ = ["ST_ShaftElement", "st_shaft_example"]
class ST_ShaftElement:
"""Random shaft element.
Creates an object containing a generator with random instances of
ShaftElement.
Parameters
----------
L : float, pint.Quantity, list
Element length.
Input a list to make it random.
idl : float, pint.Quantity, list
Inner diameter of the element at the left position.
Input a list to make it random.
odl : float, pint.Quantity, list
Outer diameter of the element at the left position.
Input a list to make it random.
idr : float, pint.Quantity, list, optional
Inner diameter of the element at the right position
Default is equal to idl value (cylindrical element)
Input a list to make it random.
odr : float, pint.Quantity, list, optional
Outer diameter of the element at the right position.
Default is equal to odl value (cylindrical element)
Input a list to make it random.
material : ross.material, list of ross.material
Shaft material.
Input a list to make it random.
n : int, optional
Element number (coincident with it's first node).
If not given, it will be set when the rotor is assembled
according to the element's position in the list supplied to
axial_force : float, list, optional
Axial force.
Input a list to make it random.
Default is 0.
torque : float, list, optional
Torque
Input a list to make it random.
Default is 0.
shear_effects : bool, optional
Determine if shear effects are taken into account.
Default is True.
rotary_inertia : bool, optional
Determine if rotary_inertia effects are taken into account.
Default is True.
gyroscopic : bool, optional
Determine if gyroscopic effects are taken into account.
Default is True.
shear_method_calc : str, optional
Determines which shear calculation method the user will adopt.
Default is 'cowper'
is_random : list
List of the object attributes to become random.
Possibilities:
["L", "idl", "odl", "idr", "odr", "material", "axial_force", "torque"]
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> size = 5
>>> E = np.random.uniform(208e9, 211e9, size)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> elms = srs.ST_ShaftElement(L=1,
... idl=0,
... odl=np.random.uniform(0.1, 0.2, size),
... material=st_steel,
... is_random=["odl", "material"],
... )
>>> len(list(iter(elms)))
5
"""
@check_units
def __init__(
self,
L,
idl,
odl,
idr=None,
odr=None,
material=None,
n=None,
axial_force=0,
torque=0,
shear_effects=True,
rotary_inertia=True,
gyroscopic=True,
shear_method_calc="cowper",
is_random=None,
):
if idr is None:
idr = idl
if "idl" in is_random and "idr" not in is_random:
is_random.append("idr")
if odr is None:
odr = odl
if "odl" in is_random and "odr" not in is_random:
is_random.append("odr")
if isinstance(material, ST_Material):
material = list(iter(material))
attribute_dict = dict(
L=L,
idl=idl,
odl=odl,
idr=idr,
odr=odr,
material=material,
n=n,
axial_force=axial_force,
torque=torque,
shear_effects=shear_effects,
rotary_inertia=rotary_inertia,
gyroscopic=gyroscopic,
shear_method_calc=shear_method_calc,
tag=None,
)
self.is_random = is_random
self.attribute_dict = attribute_dict
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random shaft elements.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_shaft_example()
>>> len(list(iter(elm)))
2
"""
return iter(self.random_var(self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> size = 5
>>> E = np.random.uniform(208e9, 211e9, size)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> elms = srs.ST_ShaftElement(L=1,
... idl=0,
... odl=np.random.uniform(0.1, 0.2, size),
... material=st_steel,
... is_random=["odl", "material"],
... )
>>> elms["L"]
1
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_ShaftElement
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> size = 5
>>> E = np.random.uniform(208e9, 211e9, size)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> elms = srs.ST_ShaftElement(L=1,
... idl=0,
... odl=np.random.uniform(0.1, 0.2, size),
... material=st_steel,
... is_random=["odl", "material"],
... )
>>> elms["odl"] = np.linspace(0.1, 0.2, 5)
>>> elms["odl"]
array([0.1 , 0.125, 0.15 , 0.175, 0.2 ])
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def random_var(self, is_random, *args):
"""Generate a list of objects as random attributes.
This function creates a list of objects with random values for selected
attributes from ross.ShaftElement.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.ShaftElement class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = []
for i in range(len(args_dict[is_random[0]])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
f_list = (ShaftElement(*arg) for arg in new_args)
return f_list
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable
distribution.
Parameters
----------
var_list : list, optional
List of random variables, in string format, to plot.
Default is plotting all the random variables.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...).
*See Plotly API to more information.
Returns
-------
fig : Plotly graph_objects.Figure()
A figure with the histogram plots.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_shaft_example()
>>> fig = elm.plot_random_var(["odl"])
>>> # fig.show()
"""
label = dict(
L="Length",
idl="Left inner diameter",
odl="Left outer diameter",
idr="Right inner diameter",
odr="Right outer diameter",
)
is_random = self.is_random
if "material" in is_random:
is_random.remove("material")
if var_list is None:
var_list = is_random
elif not all(var in is_random for var in var_list):
raise ValueError(
"Random variable not in var_list. Select variables from {}".format(
is_random
)
)
return plot_histogram(
self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={}
)
def st_shaft_example():
"""Return an instance of a simple random shaft element.
The purpose is to make available a simple model so that doctest can be
written using it.
Returns
-------
elm : ross.stochastic.ST_ShaftElement
An instance of a random shaft element object.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_shaft_example()
>>> len(list(iter(elm)))
2
"""
from ross.materials import steel
elm = ST_ShaftElement(
L=[1.0, 1.1],
idl=0.0,
odl=[0.1, 0.2],
material=steel,
is_random=["L", "odl"],
)
return elm | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_shaft_element.py | 0.921873 | 0.435181 | st_shaft_element.py | pypi |
import numpy as np
from ross.bearing_seal_element import BearingElement
from ross.fluid_flow import fluid_flow as flow
from ross.fluid_flow.fluid_flow_coefficients import (
calculate_stiffness_and_damping_coefficients,
)
from ross.stochastic.st_results_elements import plot_histogram
from ross.units import check_units
__all__ = ["ST_BearingElement", "st_bearing_example"]
class ST_BearingElement:
"""Random bearing element.
Creates an object containing a list with random instances of
BearingElement.
Considering constant coefficients, use an 1-D array to make it random.
Considering varying coefficients to the frequency, use a 2-D array to
make it random (*see the Examples below).
Parameters
----------
n: int
Node which the bearing will be located in
kxx: float, 1-D array, 2-D array
Direct stiffness in the x direction.
cxx: float, 1-D array, 2-D array
Direct damping in the x direction.
kyy: float, 1-D array, 2-D array, optional
Direct stiffness in the y direction.
(defaults to kxx)
kxy: float, 1-D array, 2-D array, optional
Cross coupled stiffness in the x direction.
(defaults to 0)
kyx: float, 1-D array, 2-D array, optional
Cross coupled stiffness in the y direction.
(defaults to 0)
cyy: float, 1-D array, 2-D array, optional
Direct damping in the y direction.
(defaults to cxx)
cxy: float, 1-D array, 2-D array, optional
Cross coupled damping in the x direction.
(defaults to 0)
cyx: float, 1-D array, 2-D array, optional
Cross coupled damping in the y direction.
(defaults to 0)
frequency: array, optional
Array with the frequencies (rad/s).
tag: str, optional
A tag to name the element
Default is None.
n_link: int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor: float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
is_random : list
List of the object attributes to become stochastic.
Possibilities:
["kxx", "kxy", "kyx", "kyy", "cxx", "cxy", "cyx", "cyy"]
Attributes
----------
elements_list : list
display the list with random bearing elements.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
# Uncertanties on constant bearing coefficients
>>> s = 10
>>> kxx = np.random.uniform(1e6, 2e6, s)
>>> cxx = np.random.uniform(1e3, 2e3, s)
>>> elms = srs.ST_BearingElement(n=1,
... kxx=kxx,
... cxx=cxx,
... is_random = ["kxx", "cxx"],
... )
>>> len(list(iter(elms)))
10
# Uncertanties on bearing coefficients varying with frequency
>>> s = 5
>>> kxx = [np.random.uniform(1e6, 2e6, s),
... np.random.uniform(2.3e6, 3.3e6, s)]
>>> cxx = [np.random.uniform(1e3, 2e3, s),
... np.random.uniform(2.1e3, 3.1e3, s)]
>>> frequency = np.linspace(500, 800, len(kxx))
>>> elms = srs.ST_BearingElement(n=1,
... kxx=kxx,
... cxx=cxx,
... frequency=frequency,
... is_random = ["kxx", "cxx"],
... )
>>> len(list(iter(elms)))
5
"""
@check_units
def __init__(
self,
n,
kxx,
cxx,
mxx=None,
kyy=None,
kxy=0,
kyx=0,
cyy=None,
cxy=0,
cyx=0,
myy=None,
mxy=0,
myx=0,
frequency=None,
tag=None,
n_link=None,
scale_factor=1,
is_random=None,
):
if "frequency" in is_random:
raise ValueError("frequency can not be a random variable")
if kyy is None:
kyy = kxx
if "kxx" in is_random and "kyy" not in is_random:
is_random.append("kyy")
if cyy is None:
cyy = cxx
if "cxx" in is_random and "cyy" not in is_random:
is_random.append("cyy")
if myy is None:
if mxx is None:
myy = 0
mxx = 0
else:
myy = mxx
if "mxx" in is_random and "myy" not in is_random:
is_random.append("myy")
attribute_dict = dict(
n=n,
kxx=kxx,
cxx=cxx,
mxx=mxx,
kyy=kyy,
kxy=kxy,
kyx=kyx,
cyy=cyy,
cxy=cxy,
cyx=cyx,
myy=myy,
mxy=mxy,
myx=myx,
frequency=frequency,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
)
self.is_random = is_random
self.attribute_dict = attribute_dict
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random bearing elements.
Examples
--------
>>> import ross.stochastic as srs
>>> bearing = srs.st_bearing_example()
>>> len(list(iter(bearing)))
2
"""
return iter(self.random_var(self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> s = 5
>>> kxx = np.random.uniform(1e6, 2e6, s)
>>> cxx = np.random.uniform(1e3, 2e3, s)
>>> elms = srs.ST_BearingElement(n=1,
... kxx=kxx,
... cxx=cxx,
... is_random = ["kxx", "cxx"],
... )
>>> elms["n"]
1
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_BearingElement
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> s = 5
>>> kxx = np.random.uniform(1e6, 2e6, s)
>>> cxx = np.random.uniform(1e3, 2e3, s)
>>> elms = srs.ST_BearingElement(n=1,
... kxx=kxx,
... cxx=cxx,
... is_random = ["kxx", "cxx"],
... )
>>> elms["kxx"] = np.linspace(3e6, 5e6, 5)
>>> elms["kxx"]
array([3000000., 3500000., 4000000., 4500000., 5000000.])
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def random_var(self, is_random, *args):
"""Generate a list of objects as random attributes.
This function creates a list of objects with random values for selected
attributes from ross.BearingElement.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.BearingElement class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = []
try:
for i in range(len(args_dict[is_random[0]][0])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append([value[j][i] for j in range(len(value))])
else:
arg.append(value)
new_args.append(arg)
except TypeError:
for i in range(len(args_dict[is_random[0]])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
f_list = (BearingElement(*arg) for arg in new_args)
return f_list
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable
distribution.
Parameters
----------
var_list : list, optional
List of random variables, in string format, to plot.
Default is plotting all the random variables.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...).
*See Plotly API to more information.
Returns
-------
fig : Plotly graph_objects.Figure()
A figure with the histogram plots.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_bearing_example()
>>> fig = elm.plot_random_var(["kxx"])
>>> # fig.show()
"""
label = dict(
kxx="Kxx",
kxy="Kxy",
kyx="Kyx",
kyy="Kyy",
cxx="Cxx",
cxy="Cxy",
cyx="Cyx",
cyy="Cyy",
mxx="Mxx",
mxy="Mxy",
myx="Myx",
myy="Myy",
)
if var_list is None:
var_list = self.is_random
elif not all(var in self.is_random for var in var_list):
raise ValueError(
"Random variable not in var_list. Select variables from {}".format(
self.is_random
)
)
return plot_histogram(
self.attribute_dict, label, var_list, histogram_kwargs, plot_kwargs
)
@classmethod
def from_fluid_flow(
cls,
n,
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
viscosity,
density,
attitude_angle=None,
eccentricity=None,
load=None,
omegap=None,
immediately_calculate_pressure_matrix_numerically=True,
tag=None,
n_link=None,
scale_factor=1,
is_random=None,
):
"""Instantiate a bearing using inputs from its fluid flow.
Parameters
----------
n : int
The node in which the bearing will be located in the rotor.
is_random : list
List of the object attributes to become random.
Possibilities:
["length", "omega", "p_in", "p_out", "radius_rotor",
"radius_stator", "viscosity", "density", "attitude_angle",
"eccentricity", "load", "omegap"]
tag: str, optional
A tag to name the element
Default is None.
n_link: int, optional
Node to which the bearing will connect. If None the bearing is
connected to ground.
Default is None.
scale_factor: float, optional
The scale factor is used to scale the bearing drawing.
Default is 1.
Grid related
^^^^^^^^^^^^
Describes the discretization of the problem
nz: int
Number of points along the Z direction (direction of flow).
ntheta: int
Number of points along the direction theta. NOTE: ntheta must be odd.
nradius: int
Number of points along the direction r.
length: float, list
Length in the Z direction (m).
Input a list to make it random.
Operation conditions
^^^^^^^^^^^^^^^^^^^^
Describes the operation conditions.
omega: float, list
Rotation of the rotor (rad/s).
Input a list to make it random.
p_in: float, list
Input Pressure (Pa).
Input a list to make it random.
p_out: float, list
Output Pressure (Pa).
Input a list to make it random.
load: float, list
Load applied to the rotor (N).
Input a list to make it random.
Geometric data of the problem
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Describes the geometric data of the problem.
radius_rotor: float, list
Rotor radius (m).
Input a list to make it random.
radius_stator: float, list
Stator Radius (m).
Input a list to make it random.
eccentricity: float, list
Eccentricity (m) is the euclidean distance between rotor and stator
centers.
The center of the stator is in position (0,0).
Input a list to make it random.
Fluid characteristics
^^^^^^^^^^^^^^^^^^^^^
Describes the fluid characteristics.
viscosity: float, list
Viscosity (Pa.s).
Input a list to make it random.
density: float, list
Fluid density(Kg/m^3).
Input a list to make it random.
Returns
-------
random bearing: srs.ST_BearingElement
A random bearing object.
Examples
--------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> nz = 8
>>> ntheta = 64
>>> length = 1.5 * 0.0254
>>> omega = [157.1, 300]
>>> p_in = 0.
>>> p_out = 0.
>>> radius_rotor = 3 * 0.0254
>>> radius_stator = 3.003 * 0.0254
>>> viscosity = np.random.uniform(2.4e-03, 2.8e-03, 5)
>>> density = 860
>>> load = 1244.1
>>> elms = srs.ST_BearingElement.from_fluid_flow(
... 0, nz=nz, ntheta=ntheta, length=length,
... omega=omega, p_in=p_in, p_out=p_out, radius_rotor=radius_rotor,
... radius_stator=radius_stator, viscosity=viscosity, density=density,
... load=load, is_random=["viscosity"]
... )
>>> len(list(iter(elms)))
5
"""
attribute_dict = locals()
attribute_dict.pop("cls")
attribute_dict.pop("omega")
attribute_dict.pop("is_random")
size = len(attribute_dict[is_random[0]])
args_dict = {
"kxx": np.zeros((len(omega), size)),
"kxy": np.zeros((len(omega), size)),
"kyx": np.zeros((len(omega), size)),
"kyy": np.zeros((len(omega), size)),
"cxx": np.zeros((len(omega), size)),
"cxy": np.zeros((len(omega), size)),
"cyx": np.zeros((len(omega), size)),
"cyy": np.zeros((len(omega), size)),
}
for k, v in attribute_dict.items():
if k not in is_random:
attribute_dict[k] = np.full(size, v)
else:
attribute_dict[k] = np.asarray(v)
for j, frequency in enumerate(omega):
for i in range(size):
fluid_flow = flow.FluidFlow(
attribute_dict["nz"][i],
attribute_dict["ntheta"][i],
attribute_dict["length"][i],
frequency,
attribute_dict["p_in"][i],
attribute_dict["p_out"][i],
attribute_dict["radius_rotor"][i],
attribute_dict["radius_stator"][i],
attribute_dict["viscosity"][i],
attribute_dict["density"][i],
attribute_dict["attitude_angle"][i],
attribute_dict["eccentricity"][i],
attribute_dict["load"][i],
attribute_dict["omegap"][i],
)
k, c = calculate_stiffness_and_damping_coefficients(fluid_flow)
args_dict["kxx"][j, i] = k[0]
args_dict["kxy"][j, i] = k[1]
args_dict["kyx"][j, i] = k[2]
args_dict["kyy"][j, i] = k[3]
args_dict["cxx"][j, i] = c[0]
args_dict["cxy"][j, i] = c[1]
args_dict["cyx"][j, i] = c[2]
args_dict["cyy"][j, i] = c[3]
return cls(
n,
kxx=args_dict["kxx"],
cxx=args_dict["cxx"],
kyy=args_dict["kyy"],
kxy=args_dict["kxy"],
kyx=args_dict["kyx"],
cyy=args_dict["cyy"],
cxy=args_dict["cxy"],
cyx=args_dict["cyx"],
frequency=omega,
tag=tag,
n_link=n_link,
scale_factor=scale_factor,
is_random=list(args_dict.keys()),
)
def st_bearing_example():
"""Return an instance of a simple random bearing.
The purpose is to make available a simple model so that doctest can be
written using it.
Returns
-------
elm : ross.stochastic.ST_BearingElement
An instance of a random bearing element object.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_bearing_example()
>>> len(list(iter(elm)))
2
"""
kxx = [1e6, 2e6]
cxx = [1e3, 2e3]
elm = ST_BearingElement(n=1, kxx=kxx, cxx=cxx, is_random=["kxx", "cxx"])
return elm | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_bearing_seal_element.py | 0.915299 | 0.640355 | st_bearing_seal_element.py | pypi |
import copy
import inspect
from abc import ABC
from collections.abc import Iterable
from pathlib import Path
import numpy as np
import toml
from plotly import express as px
from plotly import graph_objects as go
from plotly.subplots import make_subplots
from ross.plotly_theme import tableau_colors
from ross.units import Q_
# set Plotly palette of colors
colors1 = px.colors.qualitative.Dark24
colors2 = px.colors.qualitative.Light24
__all__ = [
"ST_CampbellResults",
"ST_FrequencyResponseResults",
"ST_TimeResponseResults",
"ST_ForcedResponseResults",
"ST_Results",
]
class ST_Results(ABC):
"""Results class.
This class is a general abstract class to be implemented in other classes
for post-processing results, in order to add saving and loading data options.
"""
def save(self, file):
"""Save results in a .toml file.
This function will save the simulation results to a .toml file.
The file will have all the argument's names and values that are needed to
reinstantiate the class.
Parameters
----------
file : str, pathlib.Path
The name of the file the results will be saved in.
Examples
--------
>>> # Example running a stochastic unbalance response
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> import ross.stochastic as srs
>>> # Running an example
>>> rotors = srs.st_rotor_example()
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = np.random.uniform(0.001, 0.002, 10)
>>> p = 0.0
>>> results = rotors.run_unbalance_response(n, m, p, freq_range)
>>> # create path for a temporary file
>>> file = Path(tempdir) / 'results.toml'
>>> results.save(file)
"""
# get __init__ arguments
signature = inspect.signature(self.__init__)
args_list = list(signature.parameters)
args = {arg: getattr(self, arg) for arg in args_list}
try:
data = toml.load(file)
except FileNotFoundError:
data = {}
data[f"{self.__class__.__name__}"] = args
with open(file, "w") as f:
toml.dump(data, f, encoder=toml.TomlNumpyEncoder())
@classmethod
def read_toml_data(cls, data):
"""Read and parse data stored in a .toml file.
The data passed to this method needs to be according to the
format saved in the .toml file by the .save() method.
Parameters
----------
data : dict
Dictionary obtained from toml.load().
Returns
-------
The result object.
"""
return cls(**data)
@classmethod
def load(cls, file):
"""Load results from a .toml file.
This function will load the simulation results from a .toml file.
The file must have all the argument's names and values that are needed to
reinstantiate the class.
Parameters
----------
file : str, pathlib.Path
The name of the file the results will be loaded from.
Examples
--------
>>> # Example running a stochastic unbalance response
>>> from tempfile import tempdir
>>> from pathlib import Path
>>> import ross.stochastic as srs
>>> # Running an example
>>> rotors = srs.st_rotor_example()
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = np.random.uniform(0.001, 0.002, 10)
>>> p = 0.0
>>> results = rotors.run_unbalance_response(n, m, p, freq_range)
>>> # create path for a temporary file
>>> file = Path(tempdir) / 'results.toml'
>>> results.save(file)
>>> # Loading file
>>> results2 = srs.ST_ForcedResponseResults.load(file)
>>> results2.forced_resp.all() == results.forced_resp.all()
True
"""
data = toml.load(file)
# extract single dictionary in the data
data = list(data.values())[0]
for key, value in data.items():
if isinstance(value, Iterable):
data[key] = np.array(value)
if data[key].dtype == np.dtype("<U49"):
data[key] = np.array(value).astype(np.complex128)
return cls.read_toml_data(data)
class ST_CampbellResults(ST_Results):
"""Store stochastic results and provide plots for Campbell Diagram.
It's possible to visualize multiples harmonics in a single plot to check
other speeds which also excite a specific natural frequency.
Two options for plooting are available: Matplotlib and Bokeh. The user
chooses between them using the attribute plot_type. The default is bokeh
Parameters
----------
speed_range : array
Array with the speed range in rad/s.
wd : array
Array with the damped natural frequencies
log_dec : array
Array with the Logarithmic decrement
Returns
-------
subplots : Plotly graph_objects.make_subplots()
Plotly figure with diagrams for frequency and log dec.
"""
def __init__(self, speed_range, wd, log_dec):
self.speed_range = speed_range
self.wd = wd
self.log_dec = log_dec
def plot_nat_freq(
self,
percentile=[],
conf_interval=[],
harmonics=[1],
frequency_units="rad/s",
**kwargs,
):
"""Plot the damped natural frequencies vs frequency.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
harmonics: list, optional
List withe the harmonics to be plotted.
The default is to plot 1x.
frequency_units : str, optional
Frequency units.
Default is "rad/s"
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
wd = Q_(self.wd, "rad/s").to(frequency_units).m
speed_range = Q_(self.speed_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
fig = go.Figure()
x = np.concatenate((speed_range, speed_range[::-1]))
for j, h in enumerate(harmonics):
fig.add_trace(
go.Scatter(
x=speed_range,
y=speed_range * h,
mode="lines",
name="{}x speed".format(h),
line=dict(width=3, color=colors1[j], dash="dashdot"),
legendgroup="speed{}".format(j),
hovertemplate=("Frequency: %{x:.3f}<br>" + "Frequency: %{y:.3f}"),
)
)
for j in range(wd.shape[0]):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.mean(wd[j], axis=1),
name="Mean - Mode {}".format(j + 1),
mode="lines",
line=dict(width=3, color=colors1[j]),
legendgroup="mean{}".format(j),
hovertemplate=("Frequency: %{x:.3f}<br>" + "Frequency: %{y:.3f}"),
)
)
for i, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.percentile(wd[j], p, axis=1),
opacity=0.6,
mode="lines",
line=dict(width=2.5, color=colors2[j]),
name="percentile: {}%".format(p),
legendgroup="percentile{}{}".format(j, i),
hovertemplate=(
"Frequency: %{x:.3f}<br>" + "Frequency: %{y:.3f}"
),
)
)
for i, p in enumerate(conf_interval):
p1 = np.percentile(wd[j], 50 + p / 2, axis=1)
p2 = np.percentile(wd[j], 50 - p / 2, axis=1)
fig.add_trace(
go.Scatter(
x=x,
y=np.concatenate((p1, p2[::-1])),
mode="lines",
line=dict(width=1, color=colors1[j]),
fill="toself",
fillcolor=colors1[j],
opacity=0.3,
name="confidence interval: {}% - Mode {}".format(p, j + 1),
legendgroup="conf{}{}".format(j, i),
hovertemplate=(
"Frequency: %{x:.3f}<br>" + "Frequency: %{y:.3f}"
),
)
)
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(speed_range), np.max(speed_range)],
exponentformat="none",
)
fig.update_yaxes(
title_text=f"Natural Frequencies ({frequency_units})",
range=[0, 1.1 * np.max(wd)],
)
fig.update_layout(**kwargs)
return fig
def plot_log_dec(
self,
percentile=[],
conf_interval=[],
frequency_units="rad/s",
**kwargs,
):
"""Plot the log. decrement vs frequency.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
frequency_units : str, optional
Frequency units.
Default is "rad/s"
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
speed_range = Q_(self.speed_range, "rad/s").to(frequency_units).m
fig = go.Figure()
x = np.concatenate((speed_range, speed_range[::-1]))
for j in range(self.log_dec.shape[0]):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.mean(self.log_dec[j], axis=1),
opacity=1.0,
name="Mean - Mode {}".format(j + 1),
line=dict(width=3, color=colors1[j]),
legendgroup="mean{}".format(j),
hovertemplate=("Frequency: %{x:.3f}<br>" + "Log Dec: %{y:.3f}"),
)
)
for i, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.percentile(self.log_dec[j], p, axis=1),
opacity=0.6,
line=dict(width=2.5, color=colors2[j]),
name="percentile: {}%".format(p),
legendgroup="percentile{}{}".format(j, i),
hoverinfo="none",
)
)
for i, p in enumerate(conf_interval):
p1 = np.percentile(self.log_dec[j], 50 + p / 2, axis=1)
p2 = np.percentile(self.log_dec[j], 50 - p / 2, axis=1)
fig.add_trace(
go.Scatter(
x=x,
y=np.concatenate((p1, p2[::-1])),
line=dict(width=1, color=colors1[j]),
fill="toself",
fillcolor=colors1[j],
opacity=0.3,
name="confidence interval: {}% - Mode {}".format(p, j + 1),
legendgroup="conf{}{}".format(j, i),
hoverinfo="none",
)
)
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(speed_range), np.max(speed_range)],
exponentformat="none",
)
fig.update_yaxes(
title_text="Logarithmic decrement",
)
fig.update_layout(**kwargs)
return fig
def plot(
self,
percentile=[],
conf_interval=[],
harmonics=[1],
frequency_units="rad/s",
freq_kwargs=None,
logdec_kwargs=None,
fig_kwargs=None,
):
"""Plot Campbell Diagram.
This method plots Campbell Diagram.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
harmonics: list, optional
List withe the harmonics to be plotted.
The default is to plot 1x.
frequency_units : str, optional
Frequency units.
Default is "rad/s"
freq_kwargs : dict, optional
Additional key word arguments can be passed to change the natural frequency
vs frequency plot layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
logdec_kwargs : dict, optional
Additional key word arguments can be passed to change the log. decrement
vs frequency plot layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
fig_kwargs : dict, optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...). This kwargs override "freq_kwargs",
"logdec_kwargs" dictionaries.
*See Plotly Python make_subplots Reference for more information.
Returns
-------
subplots : Plotly graph_objects.make_subplots()
Plotly figure with diagrams for frequency and log dec.
"""
freq_kwargs = {} if freq_kwargs is None else copy.copy(freq_kwargs)
logdec_kwargs = {} if logdec_kwargs is None else copy.copy(logdec_kwargs)
fig_kwargs = {} if fig_kwargs is None else copy.copy(fig_kwargs)
fig0 = self.plot_nat_freq(
percentile, conf_interval, harmonics, frequency_units, **freq_kwargs
)
fig1 = self.plot_log_dec(
percentile, conf_interval, frequency_units, **logdec_kwargs
)
fig = make_subplots(rows=1, cols=2)
for data in fig0["data"]:
fig.add_trace(data, 1, 1)
for data in fig1["data"]:
data.showlegend = False
fig.add_trace(data, 1, 2)
fig.update_xaxes(fig0.layout.xaxis, row=1, col=1)
fig.update_yaxes(fig0.layout.yaxis, row=1, col=1)
fig.update_xaxes(fig1.layout.xaxis, row=1, col=2)
fig.update_yaxes(fig1.layout.yaxis, row=1, col=2)
fig.update_layout(**fig_kwargs)
return fig
class ST_FrequencyResponseResults(ST_Results):
"""Store stochastic results and provide plots for Frequency Response.
Parameters
----------
speed_range : array
Array with the speed range in rad/s.
magnitude : array
Array with the frequencies, magnitude (dB) of the frequency
response for each pair input/output.
phase : array
Array with the frequencies, phase of the frequency
response for each pair input/output.
Returns
-------
subplots : Plotly graph_objects.make_subplots()
Plotly figure with amplitude vs frequency phase angle vs frequency.
"""
def __init__(self, speed_range, freq_resp, velc_resp, accl_resp):
self.speed_range = speed_range
self.freq_resp = freq_resp
self.velc_resp = velc_resp
self.accl_resp = accl_resp
def plot_magnitude(
self,
percentile=[],
conf_interval=[],
frequency_units="rad/s",
amplitude_units="m/N",
fig=None,
**kwargs,
):
"""Plot stochastic frequency response (magnitude) using Plotly.
This method plots the frequency response magnitude given an output and
an input using Plotly.
It is possible to plot displacement, velocity and accelaration responses,
depending on the unit entered in 'amplitude_units'. If '[length]/[force]',
it displays the displacement; If '[speed]/[force]', it displays the velocity;
If '[acceleration]/[force]', it displays the acceleration.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0% and 100% inclusive.
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units are:
'[length]/[force]' - Displays the displacement;
'[speed]/[force]' - Displays the velocity;
'[acceleration]/[force]' - Displays the acceleration.
Default is "m/N" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m/N)
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
speed_range = Q_(self.speed_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
dummy_var = Q_(1, amplitude_units)
if dummy_var.check("[length]/[force]"):
mag = np.abs(self.freq_resp)
mag = Q_(mag, "m/N").to(amplitude_units).m
y_label = "Displacement"
elif dummy_var.check("[speed]/[force]"):
mag = np.abs(self.velc_resp)
mag = Q_(mag, "m/s/N").to(amplitude_units).m
y_label = "Velocity"
elif dummy_var.check("[acceleration]/[force]"):
mag = np.abs(self.accl_resp)
mag = Q_(mag, "m/s**2/N").to(amplitude_units).m
y_label = "Acceleration"
else:
raise ValueError(
"Not supported unit. Options are '[length]/[force]', '[speed]/[force]', '[acceleration]/[force]'"
)
if fig is None:
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.mean(mag, axis=1),
mode="lines",
name="Mean",
line=dict(width=3, color="black"),
legendgroup="mean",
hovertemplate=("Frequency: %{x:.2f}<br>" + "Amplitude: %{y:.2e}"),
)
)
for i, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.percentile(mag, p, axis=1),
mode="lines",
opacity=0.6,
line=dict(width=2.5, color=colors2[i]),
name="percentile: {}%".format(p),
legendgroup="percentile{}".format(i),
hovertemplate=("Frequency: %{x:.2f}<br>" + "Amplitude: %{y:.2e}"),
)
)
x = np.concatenate((speed_range, speed_range[::-1]))
for i, p in enumerate(conf_interval):
p1 = np.percentile(mag, 50 + p / 2, axis=1)
p2 = np.percentile(mag, 50 - p / 2, axis=1)
fig.add_trace(
go.Scatter(
x=x,
y=np.concatenate((p1, p2[::-1])),
mode="lines",
line=dict(width=1, color=colors1[i]),
fill="toself",
fillcolor=colors1[i],
opacity=0.5,
name="confidence interval: {}%".format(p),
legendgroup="conf{}".format(i),
hovertemplate=("Frequency: %{x:.2f}<br>" + "Amplitude: %{y:.2e}"),
)
)
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(speed_range), np.max(speed_range)],
)
fig.update_yaxes(title_text=f"{y_label} ({amplitude_units})")
fig.update_layout(**kwargs)
return fig
def plot_phase(
self,
percentile=[],
conf_interval=[],
frequency_units="rad/s",
amplitude_units="m/N",
phase_units="rad",
fig=None,
**kwargs,
):
"""Plot stochastic frequency response (phase) using Plotly.
This method plots the phase response given an output and an input
using Plotly.
It is possible to plot displacement, velocity and accelaration responses,
depending on the unit entered in 'amplitude_units'. If '[length]/[force]',
it displays the displacement; If '[speed]/[force]', it displays the velocity;
If '[acceleration]/[force]', it displays the acceleration.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units are:
'[length]/[force]' - Displays the displacement;
'[speed]/[force]' - Displays the velocity;
'[acceleration]/[force]' - Displays the acceleration.
Default is "m/N" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m/N)
phase_units : str, optional
Units for the x axis.
Default is "rad"
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
speed_range = Q_(self.speed_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
dummy_var = Q_(1, amplitude_units)
if dummy_var.check("[length]/[force]"):
phase = np.angle(self.freq_resp)
elif dummy_var.check("[speed]/[force]"):
phase = np.angle(self.velc_resp)
elif dummy_var.check("[acceleration]/[force]"):
phase = np.angle(self.accl_resp)
else:
raise ValueError(
"Not supported unit. Options are '[length]/[force]', '[speed]/[force]', '[acceleration]/[force]'"
)
phase = Q_(phase, "rad").to(phase_units).m
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.mean(phase, axis=1),
opacity=1.0,
mode="lines",
name="Mean",
line=dict(width=3, color="black"),
legendgroup="mean",
hovertemplate=("Frequency: %{x:.2f}<br>" + "Phase: %{y:.2f}"),
)
)
for i, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=speed_range,
y=np.percentile(phase, p, axis=1),
mode="lines",
opacity=0.6,
line=dict(width=2.5, color=colors2[i]),
name="percentile: {}%".format(p),
legendgroup="percentile{}".format(i),
hovertemplate=("Frequency: %{x:.2f}<br>" + "Phase: %{y:.2f}"),
)
)
x = np.concatenate((speed_range, speed_range[::-1]))
for i, p in enumerate(conf_interval):
p1 = np.percentile(phase, 50 + p / 2, axis=1)
p2 = np.percentile(phase, 50 - p / 2, axis=1)
fig.add_trace(
go.Scatter(
x=x,
y=np.concatenate((p1, p2[::-1])),
mode="lines",
line=dict(width=1, color=colors1[i]),
fill="toself",
fillcolor=colors1[i],
opacity=0.5,
name="confidence interval: {}%".format(p),
legendgroup="conf{}".format(i),
hovertemplate=("Frequency: %{x:.2f}<br>" + "Phase: %{y:.2f}"),
)
)
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(speed_range), np.max(speed_range)],
)
fig.update_yaxes(title_text=f"Phase ({phase_units})")
fig.update_layout(**kwargs)
return fig
def plot_polar_bode(
self,
percentile=[],
conf_interval=[],
frequency_units="rad/s",
amplitude_units="m/N",
phase_units="rad",
fig=None,
**kwargs,
):
"""Plot stochastic frequency response (polar) using Plotly.
This method plots the frequency response (polar graph) given an output and
an input using Plotly.
It is possible to plot displacement, velocity and accelaration responses,
depending on the unit entered in 'amplitude_units'. If '[length]/[force]',
it displays the displacement; If '[speed]/[force]', it displays the velocity;
If '[acceleration]/[force]', it displays the acceleration.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units are:
'[length]/[force]' - Displays the displacement;
'[speed]/[force]' - Displays the velocity;
'[acceleration]/[force]' - Displays the acceleration.
Default is "m/N" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m/N)
phase_units : str, optional
Units for the x axis.
Default is "rad"
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
speed_range = Q_(self.speed_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
dummy_var = Q_(1, amplitude_units)
if dummy_var.check("[length]/[force]"):
mag = np.abs(self.freq_resp)
mag = Q_(mag, "m/N").to(amplitude_units).m
phase = np.angle(self.freq_resp)
y_label = "Displacement"
elif dummy_var.check("[speed]/[force]"):
mag = np.abs(self.velc_resp)
mag = Q_(mag, "m/s/N").to(amplitude_units).m
phase = np.angle(self.velc_resp)
y_label = "Velocity"
elif dummy_var.check("[acceleration]/[force]"):
mag = np.abs(self.accl_resp)
mag = Q_(mag, "m/s**2/N").to(amplitude_units).m
phase = np.angle(self.accl_resp)
y_label = "Acceleration"
else:
raise ValueError(
"Not supported unit. Options are '[length]/[force]', '[speed]/[force]', '[acceleration]/[force]'"
)
phase = Q_(phase, "rad").to(phase_units).m
if phase_units in ["rad", "radian", "radians"]:
polar_theta_unit = "radians"
else:
polar_theta_unit = "degrees"
fig = go.Figure()
fig.add_trace(
go.Scatterpolar(
r=np.mean(mag, axis=1),
theta=np.mean(phase, axis=1),
customdata=speed_range,
thetaunit="radians",
line=dict(width=3.0, color="black"),
name="Mean",
legendgroup="mean",
hovertemplate=(
"<b>Amplitude: %{r:.2e}</b><br>"
+ "<b>Phase: %{theta:.2f}</b><br>"
+ "<b>Frequency: %{customdata:.2f}</b>"
),
**kwargs,
)
)
for i, p in enumerate(percentile):
fig.add_trace(
go.Scatterpolar(
r=np.percentile(mag, p, axis=1),
theta=np.percentile(phase, p, axis=1),
customdata=speed_range,
thetaunit="radians",
opacity=0.6,
line=dict(width=2.5, color=colors2[i]),
name="percentile: {}%".format(p),
legendgroup="percentile{}".format(i),
hovertemplate=(
"<b>Amplitude: %{r:.2e}</b><br>"
+ "<b>Phase: %{theta:.2f}</b><br>"
+ "<b>Frequency: %{customdata:.2f}</b>"
),
**kwargs,
)
)
for i, p in enumerate(conf_interval):
p1 = np.percentile(mag, 50 + p / 2, axis=1)
p2 = np.percentile(mag, 50 - p / 2, axis=1)
p3 = np.percentile(phase, 50 + p / 2, axis=1)
p4 = np.percentile(phase, 50 - p / 2, axis=1)
fig.add_trace(
go.Scatterpolar(
r=np.concatenate((p1, p2[::-1])),
theta=np.concatenate((p3, p4[::-1])),
thetaunit="radians",
line=dict(width=1, color=colors1[i]),
fill="toself",
fillcolor=colors1[i],
opacity=0.5,
name="confidence interval: {}%".format(p),
legendgroup="conf{}".format(i),
**kwargs,
)
)
fig.update_layout(
polar=dict(
radialaxis=dict(
title=dict(text=f"{y_label} ({amplitude_units})"),
exponentformat="power",
),
angularaxis=dict(thetaunit=polar_theta_unit),
),
**kwargs,
)
return fig
def plot(
self,
percentile=[],
conf_interval=[],
frequency_units="rad/s",
amplitude_units="m/N",
phase_units="rad",
fig=None,
mag_kwargs=None,
phase_kwargs=None,
polar_kwargs=None,
fig_kwargs=None,
):
"""Plot frequency response.
This method plots the frequency and phase response given an output
and an input.
This method returns a subplot with:
- Frequency vs Amplitude;
- Frequency vs Phase Angle;
- Polar plot Amplitude vs Phase Angle;
Amplitude can be displacement, velocity or accelaration responses,
depending on the unit entered in 'amplitude_units'. If '[length]/[force]',
it displays the displacement; If '[speed]/[force]', it displays the velocity;
If '[acceleration]/[force]', it displays the acceleration.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be
between 0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be
between 0 and 100 inclusive.
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units are:
'[length]/[force]' - Displays the displacement;
'[speed]/[force]' - Displays the velocity;
'[acceleration]/[force]' - Displays the acceleration.
Default is "m/N" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m/N)
phase_units : str, optional
Units for the x axis.
Default is "rad"
mag_kwargs : optional
Additional key word arguments can be passed to change the magnitude plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
phase_kwargs : optional
Additional key word arguments can be passed to change the phase plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
polar_kwargs : optional
Additional key word arguments can be passed to change the polar plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
fig_kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...). This kwargs override "mag_kwargs",
"phase_kwargs" and "polar_kwargs" dictionaries.
*See Plotly Python make_subplots Reference for more information.
Returns
-------
fig : Plotly graph_objects.make_subplots()
Plotly figure with amplitude vs frequency phase angle vs frequency.
"""
mag_kwargs = {} if mag_kwargs is None else copy.copy(mag_kwargs)
phase_kwargs = {} if phase_kwargs is None else copy.copy(phase_kwargs)
polar_kwargs = {} if polar_kwargs is None else copy.copy(polar_kwargs)
fig_kwargs = {} if fig_kwargs is None else copy.copy(fig_kwargs)
fig0 = self.plot_magnitude(
percentile,
conf_interval,
frequency_units,
amplitude_units,
None,
**mag_kwargs,
)
fig1 = self.plot_phase(
percentile,
conf_interval,
frequency_units,
amplitude_units,
phase_units,
None,
**phase_kwargs,
)
fig2 = self.plot_polar_bode(
percentile,
conf_interval,
frequency_units,
amplitude_units,
phase_units,
None,
**polar_kwargs,
)
if fig is None:
fig = make_subplots(
rows=2,
cols=2,
specs=[[{}, {"type": "polar", "rowspan": 2}], [{}, None]],
)
for data in fig0["data"]:
fig.add_trace(data, row=1, col=1)
for data in fig1["data"]:
data.showlegend = False
fig.add_trace(data, row=2, col=1)
for data in fig2["data"]:
data.showlegend = False
fig.add_trace(data, row=1, col=2)
fig.update_xaxes(fig0.layout.xaxis, row=1, col=1)
fig.update_yaxes(fig0.layout.yaxis, row=1, col=1)
fig.update_xaxes(fig1.layout.xaxis, row=2, col=1)
fig.update_yaxes(fig1.layout.yaxis, row=2, col=1)
fig.update_layout(
polar=dict(
radialaxis=fig2.layout.polar.radialaxis,
angularaxis=fig2.layout.polar.angularaxis,
),
**fig_kwargs,
)
return fig
class ST_TimeResponseResults(ST_Results):
"""Store stochastic results and provide plots for Time Response and Orbit Response.
Parameters
----------
t : 1-dimensional array
Time array.
yout : array
System response.
xout : array
Time evolution of the state vector.
nodes: array
list with nodes from a rotor model.
link_nodes: array
list with nodes created with "n_link" from a rotor model.
nodes_pos: array
Rotor nodes axial positions.
number_dof : int
Number of degrees of freedom per shaft element's node
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
def __init__(self, t, yout, xout, number_dof, nodes, link_nodes, nodes_pos):
self.t = t
self.yout = yout
self.xout = xout
self.nodes = nodes
self.link_nodes = link_nodes
self.nodes_pos = nodes_pos
self.number_dof = number_dof
def plot_1d(
self,
probe,
percentile=[],
conf_interval=[],
probe_units="rad",
displacement_units="m",
time_units="s",
fig=None,
**kwargs,
):
"""Plot stochastic time response.
This method plots the time response given a tuple of probes with their nodes
and orientations.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
percentile : list, optional
Sequence of percentiles to compute, which must be
between 0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be
between 0 and 100 inclusive.
probe_units : str, option
Units for probe orientation.
Default is "rad".
displacement_units : str, optional
Displacement units.
Default is 'm'.
time_units : str
Time units.
Default is 's'.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
nodes = self.nodes
link_nodes = self.link_nodes
ndof = self.number_dof
if fig is None:
fig = go.Figure()
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
for i, p in enumerate(probe):
fix_dof = (p[0] - nodes[-1] - 1) * ndof // 2 if p[0] in link_nodes else 0
dofx = ndof * p[0] - fix_dof
dofy = ndof * p[0] + 1 - fix_dof
angle = Q_(p[1], probe_units).to("rad").m
try:
probe_tag = p[2]
except IndexError:
probe_tag = f"Probe {i+1} - Node {p[0]}"
# fmt: off
operator = np.array(
[[np.cos(angle), - np.sin(angle)],
[np.cos(angle), + np.sin(angle)]]
)
probe_resp = np.zeros_like(self.yout[:, :, 0])
for j, y in enumerate(self.yout):
_probe_resp = operator @ np.vstack((y[:, dofx], y[:, dofy]))
probe_resp[j] = (
_probe_resp[0] * np.cos(angle) ** 2 +
_probe_resp[1] * np.sin(angle) ** 2
)
# fmt: on
fig.add_trace(
go.Scatter(
x=Q_(self.t, "s").to(time_units).m,
y=Q_(np.mean(probe_resp, axis=0), "m").to(displacement_units).m,
mode="lines",
opacity=1.0,
name=f"{probe_tag} - Mean",
line=dict(width=3.0),
hovertemplate=("Time: %{x:.3f}<br>" + "Amplitude: %{y:.2e}"),
)
)
for j, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=Q_(self.t, "s").to(time_units).m,
y=Q_(np.percentile(probe_resp, p, axis=0), "m")
.to(displacement_units)
.m,
# y=np.percentile(probe_resp, p, axis=0),
mode="lines",
opacity=0.6,
line=dict(width=2.5),
name=f"{probe_tag} - percentile: {p}%",
hovertemplate=("Time: %{x:.3f}<br>" + "Amplitude: %{y:.2e}"),
)
)
x = np.concatenate((self.t, self.t[::-1]))
for j, p in enumerate(conf_interval):
p1 = np.percentile(probe_resp, 50 + p / 2, axis=0)
p2 = np.percentile(probe_resp, 50 - p / 2, axis=0)
fig.add_trace(
go.Scatter(
x=Q_(x, "s").to(time_units).m,
y=Q_(np.concatenate((p1, p2[::-1])), "m")
.to(displacement_units)
.m,
mode="lines",
line=dict(width=1, color=colors1[j]),
fill="toself",
fillcolor=colors1[j],
opacity=0.5,
name=f"{probe_tag} - confidence interval: {p}%",
hovertemplate=("Time: %{x:.3f}<br>" + "Amplitude: %{y:.2e}"),
)
)
fig.update_xaxes(title_text=f"Time ({time_units})")
fig.update_yaxes(title_text=f"Amplitude ({displacement_units})")
fig.update_layout(**kwargs)
return fig
def plot_2d(
self,
node,
percentile=[],
conf_interval=[],
displacement_units="m",
fig=None,
**kwargs,
):
"""Plot orbit response (2D).
This function plots orbits for a given node on the rotor system in a 2D view.
Parameters
----------
node : int
Select the node to display the respective orbit response.
percentile : list, optional
Sequence of percentiles to compute, which must be
between 0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be
between 0 and 100 inclusive.
displacement_units : str, optional
Displacement units.
Default is 'm'.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
nodes = self.nodes
link_nodes = self.link_nodes
ndof = self.number_dof
fix_dof = (node - nodes[-1] - 1) * ndof // 2 if node in link_nodes else 0
dofx = ndof * node - fix_dof
dofy = ndof * node + 1 - fix_dof
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
if fig is None:
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=Q_(np.mean(self.yout[..., dofx], axis=0), "m")
.to(displacement_units)
.m,
y=Q_(np.mean(self.yout[..., dofy], axis=0), "m")
.to(displacement_units)
.m,
mode="lines",
opacity=1.0,
name="Mean",
line=dict(width=3, color="black"),
hovertemplate="X - Amplitude: %{x:.2e}<br>" + "Y - Amplitude: %{y:.2e}",
)
)
for i, p in enumerate(percentile):
p1 = np.percentile(self.yout[..., dofx], p, axis=0)
p2 = np.percentile(self.yout[..., dofy], p, axis=0)
fig.add_trace(
go.Scatter(
x=Q_(p1, "m").to(displacement_units).m,
y=Q_(p2, "m").to(displacement_units).m,
mode="lines",
opacity=0.6,
line=dict(width=2.5, color=colors2[i]),
name="percentile: {}%".format(p),
hovertemplate="X - Amplitude: %{x:.2e}<br>"
+ "Y - Amplitude: %{y:.2e}",
)
)
for i, p in enumerate(conf_interval):
p1 = np.percentile(self.yout[..., dofx], 50 + p / 2, axis=0)
p2 = np.percentile(self.yout[..., dofx], 50 - p / 2, axis=0)
p3 = np.percentile(self.yout[..., dofy], 50 + p / 2, axis=0)
p4 = np.percentile(self.yout[..., dofy], 50 - p / 2, axis=0)
fig.add_trace(
go.Scatter(
x=Q_(np.concatenate((p1, p2[::-1])), "m").to(displacement_units).m,
y=Q_(np.concatenate((p3, p4[::-1])), "m").to(displacement_units).m,
mode="lines",
line=dict(width=1, color=colors1[i]),
fill="toself",
fillcolor=colors1[i],
opacity=0.5,
name="confidence interval: {}%".format(p),
hovertemplate="X - Amplitude: %{x:.2e}<br>"
+ "Y - Amplitude: %{y:.2e}",
)
)
fig.update_xaxes(title_text=f"Amplitude ({displacement_units}) - X direction")
fig.update_yaxes(title_text=f"Amplitude ({displacement_units}) - Y direction")
fig.update_layout(
title=dict(text="Response for node {}".format(node)), **kwargs
)
return fig
def plot_3d(
self,
percentile=[],
conf_interval=[],
displacement_units="m",
rotor_length_units="m",
fig=None,
**kwargs,
):
"""Plot orbit response (3D).
This function plots orbits for each node on the rotor system in a 3D view.
Parameters
----------
percentile : list, optional
Sequence of percentiles to compute, which must be
between 0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be
between 0 and 100 inclusive.
displacement_units : str
Displacement units.
Default is 'm'.
rotor_length_units : str
Rotor Length units.
Default is 'm'.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. hoverlabel_align="center", ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
nodes_pos = self.nodes_pos
nodes = self.nodes
ndof = self.number_dof
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
if fig is None:
fig = go.Figure()
line = np.zeros(len(self.nodes_pos))
fig.add_trace(
go.Scatter3d(
x=Q_(nodes_pos, "m").to(rotor_length_units).m,
y=line,
z=line,
mode="lines",
line=dict(width=2.0, color="black", dash="dashdot"),
showlegend=False,
)
)
for j, n in enumerate(nodes):
dofx = ndof * n
dofy = ndof * n + 1
x = np.ones(self.yout.shape[1]) * self.nodes_pos[n]
fig.add_trace(
go.Scatter3d(
x=Q_(x, "m").to(rotor_length_units).m,
y=Q_(np.mean(self.yout[..., dofx], axis=0), "m")
.to(displacement_units)
.m,
z=Q_(np.mean(self.yout[..., dofy], axis=0), "m")
.to(displacement_units)
.m,
mode="lines",
line=dict(width=5, color="black"),
name="Mean",
legendgroup="mean",
showlegend=True if j == 0 else False,
hovertemplate=(
"Nodal Position: %{x:.2f}<br>"
+ "X - Amplitude: %{y:.2e}<br>"
+ "Y - Amplitude: %{z:.2e}"
),
)
)
for i, p in enumerate(percentile):
p1 = np.percentile(self.yout[..., dofx], p, axis=0)
p2 = np.percentile(self.yout[..., dofy], p, axis=0)
fig.add_trace(
go.Scatter3d(
x=Q_(x, "m").to(rotor_length_units).m,
y=Q_(p1, "m").to(displacement_units).m,
z=Q_(p2, "m").to(displacement_units).m,
mode="lines",
opacity=1.0,
name="percentile: {}%".format(p),
line=dict(width=3, color=colors2[i]),
legendgroup="perc{}".format(p),
showlegend=True if j == 0 else False,
hovertemplate=(
"Nodal Position: %{x:.2f}<br>"
+ "X - Amplitude: %{y:.2e}<br>"
+ "Y - Amplitude: %{z:.2e}"
),
)
)
for i, p in enumerate(conf_interval):
p1 = np.percentile(self.yout[..., dofx], 50 + p / 2, axis=0)
p2 = np.percentile(self.yout[..., dofx], 50 - p / 2, axis=0)
p3 = np.percentile(self.yout[..., dofy], 50 + p / 2, axis=0)
p4 = np.percentile(self.yout[..., dofy], 50 - p / 2, axis=0)
fig.add_trace(
go.Scatter3d(
x=Q_(x, "m").to(rotor_length_units).m,
y=Q_(p1, "m").to(displacement_units).m,
z=Q_(p3, "m").to(displacement_units).m,
mode="lines",
line=dict(width=3.5, color=colors1[i]),
opacity=0.6,
name="confidence interval: {}%".format(p),
legendgroup="conf_interval{}".format(p),
showlegend=False,
hovertemplate=(
"Nodal Position: %{x:.2f}<br>"
+ "X - Amplitude: %{y:.2e}<br>"
+ "Y - Amplitude: %{z:.2e}"
),
)
)
fig.add_trace(
go.Scatter3d(
x=x,
y=Q_(p2, "m").to(displacement_units).m,
z=Q_(p4, "m").to(displacement_units).m,
mode="lines",
line=dict(width=3.5, color=colors1[i]),
opacity=0.6,
name="confidence interval: {}%".format(p),
legendgroup="conf_interval{}".format(p),
showlegend=False,
hovertemplate=(
"Nodal Position: %{x:.2f}<br>"
+ "X - Amplitude: %{y:.2e}<br>"
+ "Y - Amplitude: %{z:.2e}"
),
)
)
fig.update_layout(
scene=dict(
xaxis=dict(
title=dict(text=f"Rotor Length ({rotor_length_units})"),
showspikes=False,
),
yaxis=dict(
title=dict(text=f"Amplitude - X ({displacement_units})"),
showspikes=False,
),
zaxis=dict(
title=dict(text=f"Amplitude - Y ({displacement_units})"),
showspikes=False,
),
),
**kwargs,
)
return fig
class ST_ForcedResponseResults(ST_Results):
"""Store stochastic results and provide plots for Forced Response.
Parameters
----------
force_resp : array
Array with the force response for each node for each frequency.
frequency_range : array
Array with the frequencies.
velc_resp : array
Array with the forced response (velocity) for each node for each frequency.
accl_resp : array
Array with the forced response (acceleration) for each node for each frequency.
number_dof = int
Number of degrees of freedom per shaft element's node.
nodes : list
List of shaft nodes.
link_nodes : list
List of n_link nodes.
Returns
-------
subplots : Plotly graph_objects.make_subplots()
Plotly figure with amplitude vs frequency phase angle vs frequency.
"""
def __init__(
self,
forced_resp,
velc_resp,
accl_resp,
frequency_range,
number_dof,
nodes,
link_nodes,
):
self.forced_resp = forced_resp
self.velc_resp = velc_resp
self.accl_resp = accl_resp
self.frequency_range = frequency_range
self.number_dof = number_dof
self.nodes = nodes
self.link_nodes = link_nodes
self.default_units = {
"[length]": ["m", "forced_resp"],
"[length] / [time]": ["m/s", "velc_resp"],
"[length] / [time] ** 2": ["m/s**2", "accl_resp"],
}
def _calculate_major_axis_per_node(self, node, angle, amplitude_units="m"):
"""Calculate the major axis for a node for each frequency.
Parameters
----------
node : float
A node from the rotor model.
angle : float, str
The orientation angle of the axis.
Options are:
float : angle in rad capture the response in a probe orientation;
str : "major" to capture the response for the major axis;
str : "minor" to capture the response for the minor axis.
amplitude_units : str, optional
Units for the y axis.
Acceptable units dimensionality are:
'[length]' - Displays the displacement;
'[speed]' - Displays the velocity;
'[acceleration]' - Displays the acceleration.
Default is "m" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m)
Returns
-------
major_axis_vector : np.ndarray
major_axis_vector[:, 0, :] = axis angle
major_axis_vector[:, 1, :] = axis vector response for the input angle
major_axis_vector[:, 2, :] = phase response for the input angle
"""
ndof = self.number_dof
nodes = self.nodes
link_nodes = self.link_nodes
unit_type = str(Q_(1, amplitude_units).dimensionality)
try:
response = self.__dict__[self.default_units[unit_type][1]]
except KeyError:
raise ValueError(
"Not supported unit. Dimensionality options are '[length]', '[speed]', '[acceleration]'"
)
size = response.shape[0]
major_axis_vector = np.zeros(
(size, 3, len(self.frequency_range)), dtype=complex
)
fix_dof = (node - nodes[-1] - 1) * ndof // 2 if node in link_nodes else 0
dofx = ndof * node - fix_dof
dofy = ndof * node + 1 - fix_dof
# Relative angle between probes (90°)
Rel_ang = np.exp(1j * np.pi / 2)
for j in range(size):
for i, f in enumerate(self.frequency_range):
# Foward and Backward vectors
fow = response[j, dofx, i] / 2 + Rel_ang * response[j, dofy, i] / 2
back = (
np.conj(response[j, dofx, i]) / 2
+ Rel_ang * np.conj(response[j, dofy, i]) / 2
)
ang_fow = np.angle(fow)
if ang_fow < 0:
ang_fow += 2 * np.pi
ang_back = np.angle(back)
if ang_back < 0:
ang_back += 2 * np.pi
if angle == "major":
# Major axis angle
axis_angle = (ang_back - ang_fow) / 2
if axis_angle > np.pi:
axis_angle -= np.pi
elif angle == "minor":
# Minor axis angle
axis_angle = (ang_back - ang_fow + np.pi) / 2
if axis_angle > np.pi:
axis_angle -= np.pi
else:
axis_angle = angle
major_axis_vector[j, 0, i] = axis_angle
major_axis_vector[j, 1, i] = np.abs(
fow * np.exp(1j * axis_angle) + back * np.exp(-1j * axis_angle)
)
major_axis_vector[j, 2, i] = np.angle(
fow * np.exp(1j * axis_angle) + back * np.exp(-1j * axis_angle)
)
return major_axis_vector
def plot_magnitude(
self,
probe,
percentile=[],
conf_interval=[],
probe_units="rad",
frequency_units="rad/s",
amplitude_units="m",
fig=None,
**kwargs,
):
"""Plot stochastic frequency response.
This method plots the unbalance response magnitude.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0% and 100% inclusive.
probe_units : str, option
Units for probe orientation.
Default is "rad".
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units dimensionality are:
'[length]' - Displays the displacement;
'[speed]' - Displays the velocity;
'[acceleration]' - Displays the acceleration.
Default is "m" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m)
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
Bokeh plot axes with magnitude plot.
"""
frequency_range = Q_(self.frequency_range, "rad/s").to(frequency_units).m
unit_type = str(Q_(1, amplitude_units).dimensionality)
try:
base_unit = self.default_units[unit_type][0]
except KeyError:
raise ValueError(
"Not supported unit. Dimensionality options are '[length]', '[speed]', '[acceleration]'"
)
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
if fig is None:
fig = go.Figure()
color_i = 0
color_p = 0
for i, p in enumerate(probe):
angle = Q_(p[1], probe_units).to("rad").m
vector = self._calculate_major_axis_per_node(
node=p[0], angle=angle, amplitude_units=amplitude_units
)[:, 1, :]
try:
probe_tag = p[2]
except IndexError:
probe_tag = f"Probe {i+1} - Node {p[0]}"
fig.add_trace(
go.Scatter(
x=frequency_range,
y=Q_(np.mean(np.abs(vector), axis=0), base_unit)
.to(amplitude_units)
.m,
opacity=1.0,
mode="lines",
line=dict(width=3, color=list(tableau_colors)[i]),
name=f"{probe_tag} - Mean",
legendgroup=f"{probe_tag} - Mean",
hovertemplate="Frequency: %{x:.2f}<br>Amplitude: %{y:.2e}",
)
)
for j, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=frequency_range,
y=Q_(np.percentile(np.abs(vector), p, axis=0), base_unit)
.to(amplitude_units)
.m,
opacity=0.6,
mode="lines",
line=dict(width=2.5, color=colors1[color_p]),
name=f"{probe_tag} - percentile: {p}%",
legendgroup=f"{probe_tag} - percentile: {p}%",
hovertemplate="Frequency: %{x:.2f}<br>Amplitude: %{y:.2e}",
)
)
color_p += 1
x = np.concatenate((frequency_range, frequency_range[::-1]))
for j, p in enumerate(conf_interval):
p1 = np.percentile(np.abs(vector), 50 + p / 2, axis=0)
p2 = np.percentile(np.abs(vector), 50 - p / 2, axis=0)
fig.add_trace(
go.Scatter(
x=x,
y=Q_(np.concatenate((p1, p2[::-1])), base_unit)
.to(amplitude_units)
.m,
mode="lines",
line=dict(width=1, color=colors2[color_i]),
fill="toself",
fillcolor=colors2[color_i],
opacity=0.5,
name=f"{probe_tag} - confidence interval: {p}%",
legendgroup=f"{probe_tag} - confidence interval: {p}%",
hovertemplate="Frequency: %{x:.2f}<br>Amplitude: %{y:.2e}",
)
)
color_i += 1
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(frequency_range), np.max(frequency_range)],
)
fig.update_yaxes(
title_text=f"Amplitude ({amplitude_units})", exponentformat="power"
)
fig.update_layout(**kwargs)
return fig
def plot_phase(
self,
probe,
percentile=[],
conf_interval=[],
probe_units="rad",
frequency_units="rad/s",
amplitude_units="m",
phase_units="rad",
fig=None,
**kwargs,
):
"""Plot stochastic frequency response.
This method plots the phase response given a set of probes.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
probe_units : str, option
Units for probe orientation.
Default is "rad".
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units dimensionality are:
'[length]' - Displays the displacement;
'[speed]' - Displays the velocity;
'[acceleration]' - Displays the acceleration.
Default is "m" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m)
phase_units : str, optional
Units for the x axis.
Default is "rad"
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
frequency_range = Q_(self.frequency_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
if fig is None:
fig = go.Figure()
color_p = 0
color_i = 0
x = np.concatenate((frequency_range, frequency_range[::-1]))
for i, p in enumerate(probe):
angle = Q_(p[1], probe_units).to("rad").m
vector = self._calculate_major_axis_per_node(
node=p[0], angle=angle, amplitude_units=amplitude_units
)[:, 2, :]
probe_phase = np.real(vector)
probe_phase = Q_(probe_phase, "rad").to(phase_units).m
try:
probe_tag = p[2]
except IndexError:
probe_tag = f"Probe {i+1} - Node {p[0]}"
fig.add_trace(
go.Scatter(
x=frequency_range,
y=np.mean(probe_phase, axis=0),
opacity=1.0,
mode="lines",
line=dict(width=3, color=list(tableau_colors)[i]),
name=f"{probe_tag} - Mean",
legendgroup=f"{probe_tag} - Mean",
hovertemplate="Frequency: %{x:.2f}<br>Phase: %{y:.2f}",
)
)
for j, p in enumerate(percentile):
fig.add_trace(
go.Scatter(
x=frequency_range,
y=np.percentile(probe_phase, p, axis=0),
opacity=0.6,
mode="lines",
line=dict(width=2.5, color=colors1[color_p]),
name=f"{probe_tag} - percentile: {p}%",
legendgroup=f"{probe_tag} - percentile: {p}%",
hovertemplate="Frequency: %{x:.2f}<br>Phase: %{y:.2f}",
)
)
color_p += 1
for j, p in enumerate(conf_interval):
p1 = np.percentile(probe_phase, 50 + p / 2, axis=0)
p2 = np.percentile(probe_phase, 50 - p / 2, axis=0)
fig.add_trace(
go.Scatter(
x=x,
y=np.concatenate((p1, p2[::-1])),
mode="lines",
line=dict(width=1, color=colors2[color_i]),
fill="toself",
fillcolor=colors2[color_i],
opacity=0.5,
name=f"{probe_tag} - confidence interval: {p}%",
legendgroup=f"{probe_tag} - confidence interval: {p}%",
hovertemplate="Frequency: %{x:.2f}<br>Phase: %{y:.2f}",
)
)
color_i += 1
fig.update_xaxes(
title_text=f"Frequency ({frequency_units})",
range=[np.min(frequency_range), np.max(frequency_range)],
)
fig.update_yaxes(title_text=f"Phase ({phase_units})")
fig.update_layout(**kwargs)
return fig
def plot_polar_bode(
self,
probe,
percentile=[],
conf_interval=[],
probe_units="rad",
frequency_units="rad/s",
amplitude_units="m",
phase_units="rad",
fig=None,
**kwargs,
):
"""Plot polar forced response using Plotly.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
percentile : list, optional
Sequence of percentiles to compute, which must be between
0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be between
0 and 100 inclusive.
probe_units : str, option
Units for probe orientation.
Default is "rad".
frequency_units : str, optional
Units for the x axis.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units dimensionality are:
'[length]' - Displays the displacement;
'[speed]' - Displays the velocity;
'[acceleration]' - Displays the acceleration.
Default is "m" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m)
phase_units : str, optional
Units for the x axis.
Default is "rad"
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
frequency_range = Q_(self.frequency_range, "rad/s").to(frequency_units).m
conf_interval = np.sort(conf_interval)
percentile = np.sort(percentile)
unit_type = str(Q_(1, amplitude_units).dimensionality)
try:
base_unit = self.default_units[unit_type][0]
except KeyError:
raise ValueError(
"Not supported unit. Dimensionality options are '[length]', '[speed]', '[acceleration]'"
)
if phase_units in ["rad", "radian", "radians"]:
polar_theta_unit = "radians"
else:
polar_theta_unit = "degrees"
if fig is None:
fig = go.Figure()
color_p = 0
color_i = 0
for i, p in enumerate(probe):
angle = Q_(p[1], probe_units).to("rad").m
mag = self._calculate_major_axis_per_node(
node=p[0], angle=angle, amplitude_units=amplitude_units
)[:, 1, :]
probe_phase = self._calculate_major_axis_per_node(
node=p[0], angle=angle, amplitude_units=amplitude_units
)[:, 2, :]
probe_phase = np.real(probe_phase)
probe_phase = Q_(probe_phase, "rad").to(phase_units).m
try:
probe_tag = p[2]
except IndexError:
probe_tag = f"Probe {i+1} - Node {p[0]}"
fig.add_trace(
go.Scatterpolar(
r=Q_(np.mean(np.abs(mag), axis=0), base_unit).to(amplitude_units).m,
theta=np.mean(probe_phase, axis=0),
customdata=frequency_range,
thetaunit=polar_theta_unit,
mode="lines",
line=dict(width=3.0, color=list(tableau_colors)[i]),
name=f"{probe_tag} - Mean",
legendgroup=f"{probe_tag} - Mean",
hovertemplate=(
"<b>Amplitude: %{r:.2e}</b><br>"
+ "<b>Phase: %{theta:.2f}</b><br>"
+ "<b>Frequency: %{customdata:.2f}</b>"
),
)
)
for j, p in enumerate(percentile):
fig.add_trace(
go.Scatterpolar(
r=Q_(np.percentile(np.abs(mag), p, axis=0), base_unit)
.to(amplitude_units)
.m,
theta=np.percentile(probe_phase, p, axis=0),
customdata=frequency_range,
thetaunit=polar_theta_unit,
opacity=0.6,
mode="lines",
line=dict(width=2.5, color=colors1[color_p]),
name=f"{probe_tag} - percentile: {p}%",
legendgroup=f"{probe_tag} - percentile{p}",
hovertemplate=(
"<b>Amplitude: %{r:.2e}</b><br>"
+ "<b>Phase: %{theta:.2f}</b><br>"
+ "<b>Frequency: %{customdata:.2f}</b>"
),
)
)
color_p += 1
for j, p in enumerate(conf_interval):
# fmt: off
p1 = Q_(np.percentile(np.abs(mag), 50 + p / 2, axis=0), base_unit).to(amplitude_units).m
p2 = Q_(np.percentile(np.abs(mag), 50 - p / 2, axis=0), base_unit).to(amplitude_units).m
p3 = np.percentile(probe_phase, 50 + p / 2, axis=0)
p4 = np.percentile(probe_phase, 50 - p / 2, axis=0)
# fmt: on
fig.add_trace(
go.Scatterpolar(
r=np.concatenate((p1, p2[::-1])),
theta=np.concatenate((p3, p4[::-1])),
thetaunit=polar_theta_unit,
mode="lines",
line=dict(width=1, color=colors2[color_i]),
fill="toself",
fillcolor=colors2[color_i],
opacity=0.5,
name=f"Probe {i + 1} - confidence interval: {p}%",
legendgroup=f"Probe {i + 1} - confidence interval: {p}%",
)
)
color_i += 1
fig.update_layout(
polar=dict(
radialaxis=dict(
title=dict(text=f"Amplitude ({amplitude_units})"),
),
angularaxis=dict(thetaunit=polar_theta_unit),
),
**kwargs,
)
return fig
def plot(
self,
probe,
percentile=[],
conf_interval=[],
probe_units="rad",
frequency_units="rad/s",
amplitude_units="m",
phase_units="rad",
mag_kwargs=None,
phase_kwargs=None,
polar_kwargs=None,
subplot_kwargs=None,
):
"""Plot stochastic forced response using Plotly.
This method plots the forced response given a set of probes.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
percentile : list, optional
Sequence of percentiles to compute, which must be
between 0 and 100 inclusive.
conf_interval : list, optional
Sequence of confidence intervals to compute, which must be
between 0 and 100 inclusive.
probe_units : str, option
Units for probe orientation.
Default is "rad".
frequency_units : str, optional
Frequency units.
Default is "rad/s"
amplitude_units : str, optional
Units for the y axis.
Acceptable units dimensionality are:
'[length]' - Displays the displacement;
'[speed]' - Displays the velocity;
'[acceleration]' - Displays the acceleration.
Default is "m" 0 to peak.
To use peak to peak use the prefix 'pkpk_' (e.g. pkpk_m)
phase_units : str, optional
Phase units.
Default is "rad"
mag_kwargs : optional
Additional key word arguments can be passed to change the magnitude plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
phase_kwargs : optional
Additional key word arguments can be passed to change the phase plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
polar_kwargs : optional
Additional key word arguments can be passed to change the polar plot
layout only (e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
subplot_kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...). This kwargs override "mag_kwargs" and
"phase_kwargs" dictionaries.
*See Plotly Python Figure Reference for more information.
Returns
-------
subplots : Plotly graph_objects.make_subplots()
Plotly figure with amplitude vs frequency phase angle vs frequency.
"""
mag_kwargs = {} if mag_kwargs is None else copy.copy(mag_kwargs)
phase_kwargs = {} if phase_kwargs is None else copy.copy(phase_kwargs)
polar_kwargs = {} if polar_kwargs is None else copy.copy(polar_kwargs)
subplot_kwargs = {} if subplot_kwargs is None else copy.copy(subplot_kwargs)
# fmt: off
fig0 = self.plot_magnitude(
probe, percentile, conf_interval, probe_units, frequency_units, amplitude_units, None, **mag_kwargs
)
fig1 = self.plot_phase(
probe, percentile, conf_interval, probe_units, frequency_units, amplitude_units, phase_units, None, **phase_kwargs
)
fig2 = self.plot_polar_bode(
probe, percentile, conf_interval, probe_units, frequency_units, amplitude_units, phase_units, None, **polar_kwargs,
)
# fmt: on
fig = make_subplots(
rows=2, cols=2, specs=[[{}, {"type": "polar", "rowspan": 2}], [{}, None]]
)
for data in fig0["data"]:
data.showlegend = False
fig.add_trace(data, row=1, col=1)
for data in fig1["data"]:
data.showlegend = False
fig.add_trace(data, row=2, col=1)
for data in fig2["data"]:
fig.add_trace(data, row=1, col=2)
fig.update_xaxes(fig0.layout.xaxis, row=1, col=1)
fig.update_yaxes(fig0.layout.yaxis, row=1, col=1)
fig.update_xaxes(fig1.layout.xaxis, row=2, col=1)
fig.update_yaxes(fig1.layout.yaxis, row=2, col=1)
fig.update_layout(
polar=dict(
radialaxis=fig2.layout.polar.radialaxis,
angularaxis=fig2.layout.polar.angularaxis,
),
)
return fig | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_results.py | 0.905766 | 0.400456 | st_results.py | pypi |
from copy import copy
import numpy as np
from plotly import graph_objects as go
from plotly import io as pio
from plotly.subplots import make_subplots
from scipy.stats import gaussian_kde
from ross.plotly_theme import tableau_colors
def plot_histogram(
attribute_dict, label={}, var_list=[], histogram_kwargs=None, plot_kwargs=None
):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable distribution.
Parameters
----------
attribute_dict : dict
Dictionary with element parameters.
label : dict
Dictionary with labels for each element parameter. Labels are displayed
on plotly figure.
var_list : list, optional
List of random variables, in string format, to plot.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0...).
*See Plotly API to more information.
Returns
-------
subplots : Plotly graph_objects.make_subplots()
A figure with the histogram plots.
"""
histogram_kwargs = {} if histogram_kwargs is None else copy(histogram_kwargs)
plot_kwargs = {} if plot_kwargs is None else copy(plot_kwargs)
hist_default_values = dict(
histnorm="probability density",
cumulative_enabled=False,
nbinsx=20,
marker_color=tableau_colors["red"],
opacity=1.0,
)
for k, v in hist_default_values.items():
histogram_kwargs.setdefault(k, v)
plot_default_values = dict(
line=dict(width=4.0, color=tableau_colors["blue"]), opacity=1.0
)
for k, v in plot_default_values.items():
plot_kwargs.setdefault(k, v)
rows = 1 if len(var_list) < 2 else 2
cols = len(var_list) // 2 + len(var_list) % 2
fig = make_subplots(rows=rows, cols=cols)
for i, var in enumerate(var_list):
row = i % 2 + 1
col = i // 2 + 1
if histogram_kwargs["histnorm"] == "probability density":
if histogram_kwargs["cumulative_enabled"] is True:
y_label = "CDF"
else:
y_label = "PDF"
else:
y_label = "Frequency"
fig.add_trace(
go.Histogram(
x=attribute_dict[var],
name="Histogram",
legendgroup="Histogram",
showlegend=True if i == 0 else False,
**histogram_kwargs,
),
row=row,
col=col,
)
if y_label == "PDF":
x = np.linspace(
min(attribute_dict[var]),
max(attribute_dict[var]),
len(attribute_dict[var]),
)
kernel = gaussian_kde(attribute_dict[var])
fig.add_trace(
go.Scatter(
x=x,
y=kernel(x),
mode="lines",
name="PDF Estimation",
legendgroup="PDF Estimation",
showlegend=True if i == 0 else False,
**plot_kwargs,
),
row=row,
col=col,
)
fig.update_xaxes(
title=dict(text="<b>{}</b>".format(label[var])),
exponentformat="E",
row=row,
col=col,
)
fig.update_yaxes(
title=dict(text="<b>{}</b>".format(y_label), standoff=0),
exponentformat="E",
row=row,
col=col,
)
fig.update_layout(bargroupgap=0.1, plot_bgcolor="white")
return fig | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_results_elements.py | 0.907765 | 0.490419 | st_results_elements.py | pypi |
from ross.point_mass import PointMass
from ross.stochastic.st_results_elements import plot_histogram
from ross.units import check_units
__all__ = ["ST_PointMass", "st_pointmass_example"]
class ST_PointMass:
"""Random point mass element.
Creates an object containing a list with random instances of PointMass.
Parameters
----------
n: int
Node in which the disk will be inserted.
m: float, list, optional
Mass for the element.
Input a list to make it random.
mx: float, list optional
Mass for the element on the x direction.
Input a list to make it random.
my: float, optional
Mass for the element on the y direction.
Input a list to make it random.
tag : str, optional
A tag to name the element
Default is None
color : str, optional
A color to be used when the element is represented.
Default is "DarkSalmon".
is_random : list
List of the object attributes to become random.
Possibilities:
["m", "mx", "my"]
Attributes
----------
elements : list
display the list with random point mass elements.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_PointMass(n=1,
... mx=np.random.uniform(2.0, 2.5, 5),
... my=np.random.uniform(2.0, 2.5, 5),
... is_random=["mx", "my"],
... )
>>> len(list(iter(elms)))
5
"""
@check_units
def __init__(
self,
n,
m=None,
mx=None,
my=None,
tag=None,
color="DarkSalmon",
is_random=None,
):
attribute_dict = dict(
n=n,
m=m,
mx=mx,
my=my,
tag=tag,
color=color,
)
self.is_random = is_random
self.attribute_dict = attribute_dict
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random point mass elements.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_pointmass_example()
>>> len(list(iter(elm)))
2
"""
return iter(self.random_var(self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_PointMass(n=1,
... mx=np.random.uniform(2.0, 2.5, 5),
... my=np.random.uniform(2.0, 2.5, 5),
... is_random=["mx", "my"],
... )
>>> elms["n"]
1
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_PointMass
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_PointMass(n=1,
... mx=np.random.uniform(2.0, 2.5, 5),
... my=np.random.uniform(2.0, 2.5, 5),
... is_random=["mx", "my"],
... )
>>> elms["mx"] = np.linspace(1.0, 2.0, 5)
>>> elms["mx"]
array([1. , 1.25, 1.5 , 1.75, 2. ])
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def random_var(self, is_random, *args):
"""Generate a list of objects as random attributes.
This function creates a list of objects with random values for selected
attributes from ross.PointMass.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.PointMass class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = []
for i in range(len(args_dict[is_random[0]])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
f_list = (PointMass(*arg) for arg in new_args)
return f_list
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable
distribution.
Parameters
----------
var_list : list, optional
List of random variables, in string format, to plot.
Default is plotting all the random variables.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...).
*See Plotly API to more information.
Returns
-------
fig : Plotly graph_objects.Figure()
A figure with the histogram plots.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_pointmass_example()
>>> fig = elm.plot_random_var(["mx"])
>>> # fig.show()
"""
label = dict(
mx="Mass on the X direction",
my="Mass on the Y direction",
m="Mass",
)
if var_list is None:
var_list = self.is_random
elif not all(var in self.is_random for var in var_list):
raise ValueError(
"Random variable not in var_list. Select variables from {}".format(
self.is_random
)
)
return plot_histogram(
self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={}
)
def st_pointmass_example():
"""Return an instance of a simple random point mass.
The purpose is to make available a simple model so that doctest can be
written using it.
Returns
-------
elm : ross.stochastic.ST_PointMass
An instance of a random point mass element object.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_pointmass_example()
>>> len(list(iter(elm)))
2
"""
mx = [2.0, 2.5]
my = [3.0, 3.5]
elm = ST_PointMass(n=1, mx=mx, my=my, is_random=["mx", "my"])
return elm | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_point_mass.py | 0.939311 | 0.607838 | st_point_mass.py | pypi |
from collections.abc import Iterable
import numpy as np
from ross.rotor_assembly import Rotor
from ross.stochastic.st_bearing_seal_element import ST_BearingElement
from ross.stochastic.st_disk_element import ST_DiskElement
from ross.stochastic.st_point_mass import ST_PointMass
from ross.stochastic.st_results import (
ST_CampbellResults,
ST_ForcedResponseResults,
ST_FrequencyResponseResults,
ST_TimeResponseResults,
)
from ross.stochastic.st_shaft_element import ST_ShaftElement
from ross.units import check_units
__all__ = ["ST_Rotor", "st_rotor_example"]
class ST_Rotor(object):
r"""A random rotor object.
This class will create several rotors according to random elements passed
to the arguments.
The number of rotors to be created depends on the amount of random
elements instantiated and theirs respective sizes.
Parameters
----------
shaft_elements : list
List with the shaft elements
disk_elements : list
List with the disk elements
bearing_elements : list
List with the bearing elements
point_mass_elements: list
List with the point mass elements
tag : str
A tag for the rotor
Attributes
----------
RV_size : int
Number of random rotor instances.
ndof : int
Number of degrees of freedom for random rotor instances.
Returns
-------
Random rotors objects
Examples
--------
# Rotor with 2 shaft elements, 1 random disk element and 2 bearings
>>> import numpy as np
>>> import ross as rs
>>> import ross.stochastic as srs
>>> steel = rs.materials.steel
>>> le = 0.25
>>> i_d = 0
>>> o_d = 0.05
>>> tim0 = rs.ShaftElement(le, i_d, o_d, material=steel)
>>> tim1 = rs.ShaftElement(le, i_d, o_d, material=steel)
>>> shaft_elm = [tim0, tim1]
# Building random disk element
>>> size = 5
>>> i_d = np.random.uniform(0.05, 0.06, size)
>>> o_d = np.random.uniform(0.35, 0.39, size)
>>> disk0 = srs.ST_DiskElement.from_geometry(n=1,
... material=steel,
... width=0.07,
... i_d=i_d,
... o_d=o_d,
... is_random=["i_d", "o_d"],
... )
>>> stf = 1e6
>>> bearing0 = rs.BearingElement(0, kxx=stf, cxx=0)
>>> bearing1 = rs.BearingElement(2, kxx=stf, cxx=0)
>>> rand_rotor = srs.ST_Rotor(shaft_elm, [disk0], [bearing0, bearing1])
>>> len(list(iter(rand_rotor)))
5
"""
def __init__(
self,
shaft_elements,
disk_elements=None,
bearing_elements=None,
point_mass_elements=None,
min_w=None,
max_w=None,
rated_w=None,
tag=None,
):
if disk_elements is None:
disk_elements = []
if bearing_elements is None:
bearing_elements = []
if point_mass_elements is None:
point_mass_elements = []
# checking for random elements and matching sizes
is_random = []
len_list = []
if any(isinstance(elm, ST_ShaftElement) for elm in shaft_elements):
is_random.append("shaft_elements")
it = iter(
[elm for elm in shaft_elements if isinstance(elm, ST_ShaftElement)]
)
len_sh = len(list(next(iter(it))))
if not all(len(list(l)) == len_sh for l in it):
raise ValueError(
"not all random shaft elements lists have same length."
)
len_list.append(len_sh)
if any(isinstance(elm, ST_DiskElement) for elm in disk_elements):
is_random.append("disk_elements")
it = iter([elm for elm in disk_elements if isinstance(elm, ST_DiskElement)])
len_dk = len(list(next(iter(it))))
if not all(len(list(l)) == len_dk for l in it):
raise ValueError("not all random disk elements lists have same length.")
len_list.append(len_dk)
if any(isinstance(elm, ST_BearingElement) for elm in bearing_elements):
is_random.append("bearing_elements")
it = iter(
[elm for elm in bearing_elements if isinstance(elm, ST_BearingElement)]
)
len_brg = len(list(next(iter(it))))
if not all(len(list(l)) == len_brg for l in it):
raise ValueError(
"not all random bearing elements lists have same length."
)
len_list.append(len_brg)
if any(isinstance(elm, ST_PointMass) for elm in point_mass_elements):
is_random.append("point_mass_elements")
it = iter(
[elm for elm in point_mass_elements if isinstance(elm, ST_PointMass)]
)
len_pm = len(list(next(iter(it))))
if not all(len(list(l)) == len_pm for l in it):
raise ValueError("not all random point mass lists have same length.")
len_list.append(len_pm)
if len_list.count(len_list[0]) == len(len_list):
RV_size = len_list[0]
else:
raise ValueError("not all the random elements lists have the same length.")
for i, elm in enumerate(shaft_elements):
if isinstance(elm, ST_ShaftElement):
shaft_elements[i] = list(iter(elm))
for i, elm in enumerate(disk_elements):
if isinstance(elm, ST_DiskElement):
disk_elements[i] = list(iter(elm))
for i, elm in enumerate(bearing_elements):
if isinstance(elm, ST_BearingElement):
bearing_elements[i] = list(iter(elm))
for i, elm in enumerate(point_mass_elements):
if isinstance(elm, ST_PointMass):
point_mass_elements[i] = list(iter(elm))
attribute_dict = dict(
shaft_elements=shaft_elements,
disk_elements=disk_elements,
bearing_elements=bearing_elements,
point_mass_elements=point_mass_elements,
min_w=min_w,
max_w=max_w,
rated_w=rated_w,
tag=tag,
)
# Assembling random rotors
self.is_random = is_random
self.attribute_dict = attribute_dict
# common parameters
self.RV_size = RV_size
# collect a series of attributes from a rotor instance
self._get_rotor_args()
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random rotors.
Examples
--------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
>>> len(list(iter(rotors)))
10
"""
return iter(self.use_random_var(Rotor, self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
>>> rotors["shaft_elements"] # doctest: +ELLIPSIS
[ShaftElement...
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_Rotor
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
>>> rotors["tag"] = "rotor"
>>> rotors["tag"]
'rotor'
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def _get_rotor_args(self):
"""Get relevant attributes from a rotor system.
This auxiliary funtion get some relevant attributes from a rotor system, such as
the nodes numbers, nodes positions and number of degrees of freedom, and add it
to the stochastic rotor as attribute. If an attribute is somehow afected by a
random variable, the function returns its mean.
"""
self.iter_break = True
aux_rotor = list(iter(self))[0]
self.ndof = aux_rotor.ndof
self.nodes = aux_rotor.nodes
self.number_dof = aux_rotor.number_dof
self.link_nodes = aux_rotor.link_nodes
if "shaft_elements" in self.is_random:
if any(
"L" in sh.is_random
for sh in self.attribute_dict["shaft_elements"]
if isinstance(sh, ST_ShaftElement)
):
nodes_pos_matrix = np.zeros(len(self.nodes), self.RV_size)
for i, rotor in enumerate(iter(self)):
nodes_pos_matrix[:, i] = rotor.nodes_pos
self.nodes_pos = np.mean(nodes_pos_matrix, axis=1)
else:
self.nodes_pos = aux_rotor.nodes_pos
else:
self.nodes_pos = aux_rotor.nodes_pos
@staticmethod
def _get_args(idx, *args):
"""Build new list of arguments from a random list of arguments.
This funtion takes a list with random values or with lists of random
values and a build an organized list to instantiate functions
correctly.
Parameters
----------
idx : int
iterator index.
*args : list
list of mixed arguments.
Returns
-------
new_args : list
list of arranged arguments.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
>>> old_list = [1, 2, [3, 4], 5]
>>> index = [0, 1]
>>> new_list = [rotors._get_args(idx, old_list) for idx in index]
>>> new_list
[[1, 2, 3, 5], [1, 2, 4, 5]]
"""
new_args = []
for arg in list(args[0]):
if isinstance(arg, Iterable):
new_args.append(arg[idx])
else:
new_args.append(arg)
return new_args
def _random_var(self, is_random, *args):
"""Generate a list of random parameters.
This function creates a list of parameters with random values given
its own distribution.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.Rotor class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
new_args : generator
Generator of random parameters.
"""
args_dict = args[0]
new_args = []
var_size = None
if self.iter_break is True:
var_size = 1
self.iter_break = False
else:
for v in list(map(args_dict.get, is_random))[0]:
if isinstance(v, Iterable):
var_size = len(v)
break
if var_size is None:
var_size = len(list(map(args_dict.get, is_random))[0])
for i in range(var_size):
arg = []
for key, value in args_dict.items():
if key in is_random and key in self.is_random:
arg.append(self._get_args(i, value))
elif key in is_random and key not in self.is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
return iter(new_args)
def use_random_var(self, f, is_random, *args):
"""Generate a list of random objects from random attributes.
This function creates a list of objects with random values for selected
attributes from ross.Rotor class or its methods.
Parameters
----------
f : callable
Function to be instantiated randomly with its respective *args.
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.Rotor class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = self._random_var(is_random, args_dict)
f_list = (f(*arg) for arg in new_args)
return f_list
def run_campbell(self, speed_range, frequencies=6, frequency_type="wd"):
"""Stochastic Campbell diagram for multiples rotor systems.
This function will calculate the damped or undamped natural frequencies
for a speed range for every rotor instance.
Parameters
----------
speed_range : array
Array with the desired range of frequencies.
frequencies : int, optional
Number of frequencies that will be calculated.
Default is 6.
frequency_type : str, optional
Choose between displaying results related to the undamped natural
frequencies ("wn") or damped natural frequencies ("wd").
The default is "wd".
Returns
-------
results.speed_range : array
Array with the frequency range
results.wd : array
Array with the damped or undamped natural frequencies corresponding to
each speed of the speed_range array for each rotor instance.
results.log_dec : array
Array with the log dec corresponding to each speed of the speed_range
array for each rotor instance.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
# Running Campbell Diagram and saving the results
>>> speed_range = np.linspace(0, 500, 31)
>>> results = rotors.run_campbell(speed_range)
# Plotting Campbell Diagram with Plotly
>>> fig = results.plot(conf_interval=[90])
>>> # fig.show()
"""
CAMP_size = len(speed_range)
RV_size = self.RV_size
wd = np.zeros((frequencies, CAMP_size, RV_size))
log_dec = np.zeros((frequencies, CAMP_size, RV_size))
# Monte Carlo - results storage
for i, rotor in enumerate(iter(self)):
results = rotor.run_campbell(speed_range, frequencies, frequency_type)
for j in range(frequencies):
wd[j, :, i] = results.wd[:, j]
log_dec[j, :, i] = results.log_dec[:, j]
results = ST_CampbellResults(speed_range, wd, log_dec)
return results
def run_freq_response(
self,
inp,
out,
speed_range=None,
modes=None,
cluster_points=False,
num_modes=12,
num_points=10,
rtol=0.005,
):
"""Stochastic frequency response for multiples rotor systems.
This method returns the frequency response for every rotor instance,
given a range of frequencies, the degrees of freedom to be
excited and observed and the modes that will be used.
Parameters
----------
inp : int
Input DoF.
out : int
Output DoF.
speed_range : array, optional
Array with the desired range of frequencies.
Default is 0 to 1.5 x highest damped natural frequency.
modes : list, optional
Modes that will be used to calculate the frequency response
(all modes will be used if a list is not given).
cluster_points : bool, optional
boolean to activate the automatic frequency spacing method. If True, the
method uses _clustering_points() to create an speed_range.
Default is False
num_points : int, optional
The number of points generated per critical speed.
The method set the same number of points for slightly less and slightly
higher than the natural circular frequency. It means there'll be num_points
greater and num_points smaller than a given critical speed.
num_points may be between 2 and 12. Anything above this range defaults
to 10 and anything below this range defaults to 4.
The default is 10.
num_modes
The number of eigenvalues and eigenvectors to be calculated using ARPACK.
It also defines the range for the output array, since the method generates
points only for the critical speed calculated by run_critical_speed().
Default is 12.
rtol : float, optional
Tolerance (relative) for termination. Applied to scipy.optimize.newton to
calculate the approximated critical speeds.
Default is 0.005 (0.5%).
Returns
-------
results.speed_range : array
Array with the frequencies.
results.magnitude : array
Amplitude response for each rotor system.
results.phase : array
Phase response for each rotor system.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
# Running Frequency Response and saving the results
>>> speed_range = np.linspace(0, 500, 31)
>>> inp = 9
>>> out = 9
>>> results = rotors.run_freq_response(inp, out, speed_range)
# Plotting Frequency Response with Plotly
>>> fig = results.plot(conf_interval=[90])
>>> # fig.show()
"""
FRF_size = len(speed_range)
RV_size = self.RV_size
freq_resp = np.empty((FRF_size, RV_size), dtype=complex)
velc_resp = np.empty((FRF_size, RV_size), dtype=complex)
accl_resp = np.empty((FRF_size, RV_size), dtype=complex)
# Monte Carlo - results storage
for i, rotor in enumerate(iter(self)):
results = rotor.run_freq_response(
speed_range,
modes,
cluster_points,
num_modes,
num_points,
rtol,
)
freq_resp[:, i] = results.freq_resp[inp, out, :]
velc_resp[:, i] = results.velc_resp[inp, out, :]
accl_resp[:, i] = results.accl_resp[inp, out, :]
results = ST_FrequencyResponseResults(
speed_range, freq_resp, velc_resp, accl_resp
)
return results
def run_time_response(self, speed, force, time_range, ic=None):
"""Stochastic time response for multiples rotor systems.
This function will take a rotor object and plot its time response
given a force and a time. This method displays the amplitude vs time or the
rotor orbits.
The force and ic parameters can be passed as random variables.
Parameters
----------
speed: float
Rotor speed
force : 2-dimensional array, 3-dimensional array
Force array (needs to have the same number of rows as time array).
Each column corresponds to a dof and each row to a time step.
Inputing a 3-dimensional array, the method considers the force as
a random variable. The 3rd dimension must have the same size than
ST_Rotor.RV_size
time_range : 1-dimensional array
Time array.
ic : 1-dimensional array, 2-dimensional array, optional
The initial conditions on the state vector (zero by default).
Inputing a 2-dimensional array, the method considers the
initial condition as a random variable.
Returns
-------
results.time_range : array
Array containing the time array.
results.yout : array
System response.
results.xout
Time evolution of the state vector for each rotor system.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
# Running Time Response and saving the results
>>> size = 10
>>> ndof = rotors.ndof
>>> node = 3 # node where the force is applied
>>> dof = 9
>>> speed = 250.0
>>> t = np.linspace(0, 10, size)
>>> F = np.zeros((size, ndof))
>>> F[:, 4 * node] = 10 * np.cos(2 * t)
>>> F[:, 4 * node + 1] = 10 * np.sin(2 * t)
>>> results = rotors.run_time_response(speed, F, t)
# Plotting Time Response 1D, 2D and 3D
>>> fig = results.plot_1d(probe=[(3, np.pi / 2)], conf_interval=[90])
>>> # fig.show()
>>> fig = results.plot_2d(node=node, conf_interval=[90])
>>> # fig.show()
>>> fig = results.plot_3d(conf_interval=[90])
>>> # fig.show()
"""
t_size = len(time_range)
RV_size = self.RV_size
ndof = self.ndof
number_dof = self.number_dof
nodes = self.nodes
link_nodes = self.link_nodes
nodes_pos = self.nodes_pos
xout = np.zeros((RV_size, t_size, 2 * ndof))
yout = np.zeros((RV_size, t_size, ndof))
# force is not a random variable
if len(force.shape) == 2:
# Monte Carlo - results storage
for i, rotor in enumerate(iter(self)):
t_, y, x = rotor.time_response(speed, force, time_range, ic)
xout[i] = x
yout[i] = y
# force is a random variable
if len(force.shape) == 3:
# Monte Carlo - results storage
i = 0
for rotor, F in zip(iter(self), force):
t_, y, x = rotor.time_response(speed, F, time_range, ic)
xout[i] = x
yout[i] = y
i += 1
results = ST_TimeResponseResults(
time_range,
yout,
xout,
number_dof,
nodes,
link_nodes,
nodes_pos,
)
return results
@check_units
def run_unbalance_response(
self,
node,
unbalance_magnitude,
unbalance_phase,
frequency_range=None,
modes=None,
cluster_points=False,
num_modes=12,
num_points=10,
rtol=0.005,
):
"""Stochastic unbalance response for multiples rotor systems.
This method returns the unbalanced response for every rotor instance,
given magnitide and phase of the unbalance, the node where
it's applied and a frequency range.
Magnitude and phase parameters can be passed as random variables.
Parameters
----------
node : list, int
Node where the unbalance is applied.
unbalance_magnitude : list, float, pint.Quantity
Unbalance magnitude (kg.m).
If node is int, input a list to make make it random.
If node is list, input a list of lists to make it random.
If there're multiple unbalances and not all of the magnitudes are supposed
to be stochastic, input a list with repeated values to the unbalance
magnitude considered deterministic.
unbalance_phase : list, float, pint.Quantity
Unbalance phase (rad).
If node is int, input a list to make make it random.
If node is list, input a list of lists to make it random.
If there're multiple unbalances and not all of the phases are supposed
to be stochastic, input a list with repeated values to the unbalance phase
considered deterministic.
frequency_range : list, float
Array with the desired range of frequencies.
modes : list, optional
Modes that will be used to calculate the frequency response
(all modes will be used if a list is not given).
cluster_points : bool, optional
boolean to activate the automatic frequency spacing method. If True, the
method uses _clustering_points() to create an speed_range.
Default is False
num_points : int, optional
The number of points generated per critical speed.
The method set the same number of points for slightly less and slightly
higher than the natural circular frequency. It means there'll be num_points
greater and num_points smaller than a given critical speed.
num_points may be between 2 and 12. Anything above this range defaults
to 10 and anything below this range defaults to 4.
The default is 10.
num_modes
The number of eigenvalues and eigenvectors to be calculated using ARPACK.
It also defines the range for the output array, since the method generates
points only for the critical speed calculated by run_critical_speed().
Default is 12.
rtol : float, optional
Tolerance (relative) for termination. Applied to scipy.optimize.newton to
calculate the approximated critical speeds.
Default is 0.005 (0.5%).
Returns
-------
results.force_resp : array
Array with the force response for each node for each frequency
results.speed_range : array
Array with the frequencies.
results.magnitude : array
Magnitude of the frequency response for node for each frequency.
results.phase : array
Phase of the frequency response for node for each frequencye.
Example
-------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
# Running Frequency Response and saving the results
>>> freq_range = np.linspace(0, 500, 31)
>>> n = 3
>>> m = np.random.uniform(0.001, 0.002, 10)
>>> p = 0.0
>>> results = rotors.run_unbalance_response(n, m, p, freq_range)
Plot unbalance response:
>>> probe_node = 3
>>> probe_angle = np.pi / 2
>>> probe_tag = "my_probe" # optional
>>> fig = results.plot(probe=[(probe_node, probe_angle, probe_tag)])
To plot velocity and acceleration responses, you must change amplitude_units
from "[length]" units to "[length]/[time]" or "[length]/[time] ** 2" respectively
Plotting velocity response:
>>> fig = results.plot(
... probe=[(probe_node, probe_angle)],
... amplitude_units="m/s"
... )
Plotting acceleration response:
>>> fig = results.plot(
... probe=[(probe_node, probe_angle)],
... amplitude_units="m/s**2"
... )
"""
RV_size = self.RV_size
freq_size = len(frequency_range)
ndof = self.ndof
args_dict = dict(
node=node,
unbalance_magnitude=unbalance_magnitude,
unbalance_phase=unbalance_phase,
frequency_range=frequency_range,
modes=modes,
cluster_points=cluster_points,
num_modes=num_modes,
num_points=num_points,
rtol=rtol,
)
forced_resp = np.zeros((RV_size, ndof, freq_size), dtype=complex)
velc_resp = np.zeros((RV_size, ndof, freq_size), dtype=complex)
accl_resp = np.zeros((RV_size, ndof, freq_size), dtype=complex)
is_random = []
if (isinstance(node, int) and isinstance(unbalance_magnitude, Iterable)) or (
isinstance(node, Iterable) and isinstance(unbalance_magnitude[0], Iterable)
):
is_random.append("unbalance_magnitude")
if (isinstance(node, int) and isinstance(unbalance_phase, Iterable)) or (
isinstance(node, Iterable) and isinstance(unbalance_phase[0], Iterable)
):
is_random.append("unbalance_phase")
# Monte Carlo - results storage
if len(is_random):
i = 0
unbalance_args = self._random_var(is_random, args_dict)
for rotor, args in zip(iter(self), unbalance_args):
results = rotor.run_unbalance_response(*args)
forced_resp[i] = results.forced_resp
velc_resp[i] = results.velc_resp
accl_resp[i] = results.accl_resp
i += 1
else:
for i, rotor in enumerate(iter(self)):
results = rotor.run_unbalance_response(
node, unbalance_magnitude, unbalance_phase, frequency_range
)
forced_resp[i] = results.forced_resp
velc_resp[i] = results.velc_resp
accl_resp[i] = results.accl_resp
results = ST_ForcedResponseResults(
forced_resp=forced_resp,
frequency_range=frequency_range,
velc_resp=velc_resp,
accl_resp=accl_resp,
number_dof=self.number_dof,
nodes=self.nodes,
link_nodes=self.link_nodes,
)
return results
def st_rotor_example():
"""Return an instance of random rotors.
The purpose of this is to make available a simple model
so that doctest can be written using this.
Returns
-------
An instance of random rotors.
Examples
--------
>>> import ross.stochastic as srs
>>> rotors = srs.st_rotor_example()
>>> len(list(iter(rotors)))
10
"""
import ross as rs
from ross.materials import steel
i_d = 0
o_d = 0.05
n = 6
L = [0.25 for _ in range(n)]
shaft_elem = [rs.ShaftElement(l, i_d, o_d, material=steel) for l in L]
disk0 = rs.DiskElement.from_geometry(
n=2, material=steel, width=0.07, i_d=0.05, o_d=0.28
)
disk1 = rs.DiskElement.from_geometry(
n=4, material=steel, width=0.07, i_d=0.05, o_d=0.28
)
s = 10
kxx = np.random.uniform(1e6, 2e6, s)
cxx = np.random.uniform(1e3, 2e3, s)
bearing0 = ST_BearingElement(n=0, kxx=kxx, cxx=cxx, is_random=["kxx", "cxx"])
bearing1 = ST_BearingElement(n=6, kxx=kxx, cxx=cxx, is_random=["kxx", "cxx"])
return ST_Rotor(shaft_elem, [disk0, disk1], [bearing0, bearing1]) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_rotor_assembly.py | 0.839964 | 0.413714 | st_rotor_assembly.py | pypi |
from collections.abc import Iterable
import numpy as np
from ross.materials import Material
from ross.stochastic.st_results_elements import plot_histogram
from ross.units import check_units
__all__ = ["ST_Material"]
class ST_Material:
"""Create instance of Material with random parameters.
Class used to create a material and define its properties.
Density and at least 2 arguments from E, G_s and Poisson should be
provided.
If any material property is passed as iterable, the material becomes random.
Inputing 1 or 2 arguments from E, G_s or Poisson as iterable will turn the
third argument an iterable, but calculated based on the other two.
For example:
if E is iterable and G_s is float, then, Poisson is iterable and each
term is calculated based on E values and G_s single value.
You can run ross.Material.available_materials() to get a list of materials
already provided.
Parameters
----------
name : str
Material name.
rho : float, list, pint.Quantity
Density (kg/m**3).
Input a list to make it random.
E : float, list, pint.Quantity
Young's modulus (N/m**2).
Input a list to make it random.
G_s : float, list
Shear modulus (N/m**2).
Input a list to make it random.
Poisson : float, list
Poisson ratio (dimensionless).
Input a list to make it random.
color : str
Can be used on plots.
Examples
--------
>>> # Steel with random Young's modulus.
>>> import ross.stochastic as srs
>>> E = np.random.uniform(208e9, 211e9, 5)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> len(list(iter(st_steel)))
5
"""
@check_units
def __init__(
self, name, rho, E=None, G_s=None, Poisson=None, color="#525252", **kwargs
):
self.name = str(name)
if " " in name:
raise ValueError("Spaces are not allowed in Material name")
i = 0
for arg in ["E", "G_s", "Poisson"]:
if locals()[arg] is not None:
i += 1
if i != 2:
raise ValueError(
"Exactly 2 arguments from E, G_s and Poisson should be provided"
)
is_random = []
for par, _name in zip([rho, E, G_s, Poisson], ["rho", "E", "G_s", "Poisson"]):
if isinstance(par, Iterable):
is_random.append(_name)
if type(rho) == list:
rho = np.asarray(rho)
if type(E) == list:
E = np.asarray(E)
if type(G_s) == list:
G_s = np.asarray(G_s)
if type(Poisson) == list:
Poisson = np.asarray(Poisson)
attribute_dict = dict(
name=name,
rho=rho,
E=E,
G_s=G_s,
Poisson=Poisson,
color=color,
)
self.is_random = is_random
self.attribute_dict = attribute_dict
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random material properties.
Examples
--------
>>> import ross.stochastic as srs
>>> E = np.random.uniform(208e9, 211e9, 5)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> len(list(iter(st_steel)))
5
"""
return iter(self.random_var(self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import ross.stochastic as srs
>>> E = np.random.uniform(208e9, 211e9, 5)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> st_steel["rho"]
7810
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_Material
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import ross.stochastic as srs
>>> E = np.random.uniform(208e9, 211e9, 5)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> st_steel["E"] = np.linspace(200e9, 205e9, 5)
>>> st_steel["E"]
array([2.0000e+11, 2.0125e+11, 2.0250e+11, 2.0375e+11, 2.0500e+11])
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def random_var(self, is_random, *args):
"""Generate a list of objects as random attributes.
This function creates a list of objects with random values for selected
attributes from ross.Material.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.Material class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = []
for i in range(len(args_dict[is_random[0]])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
f_list = (Material(*arg) for arg in new_args)
return f_list
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable
distribution.
Parameters
----------
var_list : list, optional
List of random variables, in string format, to plot.
Default is plotting all the random variables.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...).
*See Plotly API to more information.
Returns
-------
fig : Plotly graph_objects.Figure()
A figure with the histogram plots.
Examples
--------
>>> import ross.stochastic as srs
>>> E = np.random.uniform(208e9, 211e9, 5)
>>> st_steel = srs.ST_Material(name="Steel", rho=7810, E=E, G_s=81.2e9)
>>> fig = st_steel.plot_random_var(["E"])
>>> # fig.show()
"""
label = dict(
E="Young's Modulus",
G_s="Shear Modulus",
Poisson="Poisson coefficient",
rho="Density",
)
if var_list is None:
var_list = self.is_random
elif not all(var in self.is_random for var in var_list):
raise ValueError(
"Random variable not in var_list. Select variables from {}".format(
self.is_random
)
)
return plot_histogram(
self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={}
) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_materials.py | 0.936263 | 0.563138 | st_materials.py | pypi |
import numpy as np
from ross.disk_element import DiskElement
from ross.stochastic.st_materials import ST_Material
from ross.stochastic.st_results_elements import plot_histogram
from ross.units import check_units
__all__ = ["ST_DiskElement", "st_disk_example"]
class ST_DiskElement:
"""Random disk element.
Creates an object containing a list with random instances of DiskElement.
Parameters
----------
n: int
Node in which the disk will be inserted.
m : float, list
Mass of the disk element.
Input a list to make it random.
Id : float, list
Diametral moment of inertia.
Input a list to make it random.
Ip : float, list
Polar moment of inertia
Input a list to make it random.
tag : str, optional
A tag to name the element
Default is None
color : str, optional
A color to be used when the element is represented.
Default is "Firebrick".
is_random : list
List of the object attributes to become random.
Possibilities:
["m", "Id", "Ip"]
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_DiskElement(n=1,
... m=30.0,
... Id=np.random.uniform(0.20, 0.40, 5),
... Ip=np.random.uniform(0.15, 0.25, 5),
... is_random=["Id", "Ip"],
... )
>>> len(list(iter(elms)))
5
"""
@check_units
def __init__(
self,
n,
m,
Id,
Ip,
tag=None,
color="Firebrick",
is_random=None,
):
attribute_dict = dict(n=n, m=m, Id=Id, Ip=Ip, tag=tag, color=color)
self.is_random = is_random
self.attribute_dict = attribute_dict
def __iter__(self):
"""Return an iterator for the container.
Returns
-------
An iterator over random disk elements.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_disk_example()
>>> len(list(iter(elm)))
2
"""
return iter(self.random_var(self.is_random, self.attribute_dict))
def __getitem__(self, key):
"""Return the value for a given key from attribute_dict.
Parameters
----------
key : str
A class parameter as string.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Returns
-------
Return the value for the given key.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_DiskElement(n=1,
... m=30.0,
... Id=np.random.uniform(0.20, 0.40, 5),
... Ip=np.random.uniform(0.15, 0.25, 5),
... is_random=["Id", "Ip"],
... )
>>> elms["m"]
30.0
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
return self.attribute_dict[key]
def __setitem__(self, key, value):
"""Set new parameter values for the object.
Function to change a parameter value.
It's not allowed to add new parameters to the object.
Parameters
----------
key : str
A class parameter as string.
value : The corresponding value for the attrbiute_dict's key.
***check the correct type for each key in ST_DiskElement
docstring.
Raises
------
KeyError
Raises an error if the parameter doesn't belong to the class.
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> elms = srs.ST_DiskElement(n=1,
... m=30.0,
... Id=np.random.uniform(0.20, 0.40, 5),
... Ip=np.random.uniform(0.15, 0.25, 5),
... is_random=["Id", "Ip"],
... )
>>> elms["Id"] = np.linspace(0.1, 0.3, 5)
>>> elms["Id"]
array([0.1 , 0.15, 0.2 , 0.25, 0.3 ])
"""
if key not in self.attribute_dict.keys():
raise KeyError("Object does not have parameter: {}.".format(key))
self.attribute_dict[key] = value
def random_var(self, is_random, *args):
"""Generate a list of objects as random attributes.
This function creates a list of objects with random values for selected
attributes from ross.DiskElement.
Parameters
----------
is_random : list
List of the object attributes to become stochastic.
*args : dict
Dictionary instanciating the ross.DiskElement class.
The attributes that are supposed to be stochastic should be
set as lists of random variables.
Returns
-------
f_list : generator
Generator of random objects.
"""
args_dict = args[0]
new_args = []
for i in range(len(args_dict[is_random[0]])):
arg = []
for key, value in args_dict.items():
if key in is_random:
arg.append(value[i])
else:
arg.append(value)
new_args.append(arg)
f_list = (DiskElement(*arg) for arg in new_args)
return f_list
def plot_random_var(self, var_list=None, histogram_kwargs=None, plot_kwargs=None):
"""Plot histogram and the PDF.
This function creates a histogram to display the random variable
distribution.
Parameters
----------
var_list : list, optional
List of random variables, in string format, to plot.
Default is plotting all the random variables.
histogram_kwargs : dict, optional
Additional key word arguments can be passed to change
the plotly.go.histogram (e.g. histnorm="probability density", nbinsx=20...).
*See Plotly API to more information.
plot_kwargs : dict, optional
Additional key word arguments can be passed to change the plotly go.figure
(e.g. line=dict(width=4.0, color="royalblue"), opacity=1.0, ...).
*See Plotly API to more information.
Returns
-------
fig : Plotly graph_objects.Figure()
A figure with the histogram plots.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_disk_example()
>>> fig = elm.plot_random_var(["m"])
>>> # fig.show()
"""
label = dict(
m="Mass",
Id="Diametral moment of inertia",
Ip="Polar moment of inertia",
)
if var_list is None:
var_list = self.is_random
elif not all(var in self.is_random for var in var_list):
raise ValueError(
"Random variable not in var_list. Select variables from {}".format(
self.is_random
)
)
return plot_histogram(
self.attribute_dict, label, var_list, histogram_kwargs={}, plot_kwargs={}
)
@classmethod
@check_units
def from_geometry(
cls,
n,
material,
width,
i_d,
o_d,
tag=None,
is_random=None,
):
"""Random disk element.
Creates an object containing a list with random instances of
DiskElement.from_geometry.
Parameters
----------
n: int
Node in which the disk will be inserted.
material: ross.Material, list of ross.Material
Disk material.
Input a list to make it random.
width: float, list
The disk width.
Input a list to make it random.
i_d: float, list
Inner diameter.
Input a list to make it random.
o_d: float, list
Outer diameter.
Input a list to make it random.
tag : str, optional
A tag to name the element
Default is None
is_random : list
List of the object attributes to become random.
Possibilities:
["material", "width", "i_d", "o_d"]
Example
-------
>>> import numpy as np
>>> import ross.stochastic as srs
>>> from ross.materials import steel
>>> i_d=np.random.uniform(0.05, 0.06, 5)
>>> o_d=np.random.uniform(0.35, 0.39, 5)
>>> elms = srs.ST_DiskElement.from_geometry(n=1,
... material=steel,
... width=0.07,
... i_d=i_d,
... o_d=o_d,
... is_random=["i_d", "o_d"],
... )
>>> len(list(iter(elms)))
5
"""
if isinstance(material, ST_Material):
material = list(material.__iter__())
rho = np.array([m.rho for m in material])
else:
rho = material.rho
if type(width) == list:
width = np.array(width)
if type(i_d) == list:
i_d = np.array(i_d)
if type(o_d) == list:
o_d = np.array(o_d)
attribute_dict = dict(
n=n,
material=material,
width=width,
i_d=i_d,
o_d=o_d,
tag=tag,
)
size = len(attribute_dict[is_random[0]])
for k, v in attribute_dict.items():
if k not in is_random:
v = np.full(size, v)
else:
v = np.array(v)
m = 0.25 * rho * np.pi * width * (o_d**2 - i_d**2)
# fmt: off
Id = (
0.015625 * rho * np.pi * width * (o_d ** 4 - i_d ** 4)
+ m * (width ** 2) / 12
)
# fmt: on
Ip = 0.03125 * rho * np.pi * width * (o_d**4 - i_d**4)
is_random = ["m", "Id", "Ip"]
return cls(n, m, Id, Ip, tag, is_random=is_random)
def st_disk_example():
"""Return an instance of a simple random disk.
The purpose is to make available a simple model so that doctest can be
written using it.
Returns
-------
elm : ross.stochastic.ST_DiskElement
An instance of a random disk element object.
Examples
--------
>>> import ross.stochastic as srs
>>> elm = srs.st_disk_example()
>>> len(list(iter(elm)))
2
"""
elm = ST_DiskElement(
n=1,
m=[30, 40],
Id=[0.2, 0.3],
Ip=[0.5, 0.7],
is_random=["m", "Id", "Ip"],
)
return elm | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/stochastic/st_disk_element.py | 0.903471 | 0.332161 | st_disk_element.py | pypi |
import sys
import numpy as np
import scipy as sp
from ross.fluid_flow.fluid_flow_coefficients import find_equilibrium_position
from ross.fluid_flow.fluid_flow_geometry import (
calculate_attitude_angle,
calculate_eccentricity_ratio,
calculate_rotor_load,
external_radius_function,
internal_radius_function,
modified_sommerfeld_number,
)
class FluidFlow:
r"""Generate dynamic coefficients for hydrodynamic bearings.
This class calculate the pressure matrix and the stiffness and damping matrices
of a fluid flow with the given parameters.
It is supposed to be an attribute of a bearing element,
but can work on its on to provide graphics for the user.
The complete FluidFlow theory can be found at :cite:`mota2020`
Parameters
----------
Grid related
^^^^^^^^^^^^
Describes the discretization of the problem
nz: int
Number of points along the Z direction (direction of flow).
ntheta: int
Number of points along the direction theta. NOTE: ntheta must be odd.
length: float
Length in the Z direction (m).
Operation conditions
^^^^^^^^^^^^^^^^^^^^
Describes the operation conditions.
omega: float
Rotation of the rotor (rad/s).
p_in: float
Input Pressure (Pa).
p_out: float
Output Pressure (Pa).
load: float
Load applied to the rotor (N).
omegap: float
Frequency of the rotor (rad/s).
Geometric data of the problem
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Describes the geometric data of the problem.
radius_rotor: float
Rotor radius (m).
radius_stator: float
Stator Radius (m).
eccentricity: float, optional
Eccentricity (m) is the euclidean distance between rotor and stator centers.
The center of the stator is in position (0,0).
attitude_angle: float, optional
Attitude angle. Angle between the load line and the eccentricity (rad).
bearing_type: str
type of structure. 'short_bearing': short; 'long_bearing': long;
The default is None. In this case it is automatically calculated
following the parameter:
'medium_size': in between short and long.
if length/diameter <= 1/4 it is short.
if length/diameter > 8 it is long.
bearing_type: str, optional
type of structure. 'short_bearing': short; 'long_bearing': long;
The default is None. In this case it is automatically calculated
following the parameter:
'medium_size': in between short and long.
if length/diameter <= 1/4 it is short.
if length/diameter > 8 it is long.
shape_geometry: str, optional
Determines the type of bearing geometry.
'cylindrical': cylindrical bearing; 'eliptical': eliptical bearing;
'wear': journal bearing wear.
The default is 'cylindrical'.
preload: float
Ellipticity ratio. The value must be between 0 and 1. If preload = 0
the bearing becomes cylindrical. Not used in cylindrical bearings.
The default is 0.4.
displacement : float, optional
Angular displacement of the bearing wear in relation to the vertical axis.
Only necessary if shape_geometry is wear.
max_depth: float
The maximum wear depth. Only necessary if shape_geometry is wear..
Fluid characteristics
^^^^^^^^^^^^^^^^^^^^^
Describes the fluid characteristics.
viscosity: float
Viscosity (Pa.s).
density: float
Fluid density(Kg/m^3).
User commands
^^^^^^^^^^^^^
Commands that can be passed as arguments.
immediately_calculate_pressure_matrix_numerically: bool, optional
If set True, calculates the pressure matrix numerically immediately.
Returns
-------
An object containing the fluid flow and its data.
Attributes
----------
ltheta: float
Length in the theta direction (rad).
dz: float
Range size in the Z direction.
dtheta: float
Range size in the theta direction.
ntotal: int
Number of nodes in the grid., ntheta, n_interv_z, n_interv_theta,
n_interv_z: int
Number of intervals on Z.
n_interv_theta: int
Number of intervals on theta.
p_mat_analytical : array of shape (nz, ntheta)
The analytical pressure matrix.
p_mat_numerical : array of shape (nz, ntheta)
The numerical pressure matrix.
xi: float
Eccentricity (m) (distance between rotor and stator centers) on the x-axis.
It is the position of the center of the rotor.
The center of the stator is in position (0,0).
yi: float
Eccentricity (m) (distance between rotor and stator centers) on the y-axis.
It is the position of the center of the rotor.
The center of the stator is in position (0,0).
re : array of shape (nz, ntheta)
The external radius in each position of the grid.
ri : array of shape (nz, ntheta)
The internal radius in each position of the grid.
xre : array of shape (nz, ntheta)
x value of the external radius.
xri : array of shape (nz, ntheta)
x value of the internal radius.
yre : array of shape (nz, ntheta)
y value of the external radius.
yri : array of shape (nz, ntheta)
y value of the internal radius.
z_list : array of shape (1, nz)
z along the object. It goes from 0 to lb.
gama : array of shape (nz, ntheta)
Points along the object in the tangential direction.
It ranges from 0 to 2 pi, starting at the largest spacing between rotor and stator.
t : float
Time.
xp : float
Perturbation along x.
yp : float
Perturbation along y.
eccentricity : float
distance between the center of the rotor and the stator.
radial_clearance: float
Difference between both stator and rotor radius, regardless of eccentricity.
eccentricity_ratio: float
eccentricity/radial_clearance
characteristic_speed: float
Characteristic fluid speeds.
In journal bearings, characteristic_speed = omega * radius_rotor
bearing_type: str
type of structure. 'short_bearing': short; 'long_bearing': long;
'medium_size': in between short and long.
if length/diameter <= 1/4 it is short.
if length/diameter > 8 it is long.
analytical_pressure_matrix_available: bool
True if analytically calculated pressure matrix is available.
numerical_pressure_matrix_available: bool
True if numerically calculated pressure matrix is available.
References
----------
.. bibliography:: ../../../docs/refs.bib
Examples
--------
>>> from ross.fluid_flow import fluid_flow as flow
>>> from ross.fluid_flow.fluid_flow_graphics import plot_pressure_theta
>>> import numpy as np
>>> nz = 8
>>> ntheta = 64
>>> length = 0.01
>>> omega = 100.*2*np.pi/60
>>> p_in = 0.
>>> p_out = 0.
>>> radius_rotor = 0.08
>>> radius_stator = 0.1
>>> viscosity = 0.015
>>> density = 860.
>>> eccentricity = 0.001
>>> attitude_angle = np.pi
>>> my_fluid_flow = flow.FluidFlow(nz, ntheta, length,
... omega, p_in, p_out, radius_rotor,
... radius_stator, viscosity, density,
... attitude_angle=attitude_angle, eccentricity=eccentricity,
... immediately_calculate_pressure_matrix_numerically=False)
>>> my_fluid_flow.calculate_pressure_matrix_analytical() # doctest: +ELLIPSIS
array([[...
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
>>> # to show the plots you can use:
>>> # my_fluid_flow.plot_eccentricity().show()
>>> # my_fluid_flow.plot_pressure_theta(z=int(nz/2)).show()
>>> fig = plot_pressure_theta(my_fluid_flow, z=int(nz/2)) # doctest: +ELLIPSIS
>>> # fig.show() to display the figure.
"""
def __init__(
self,
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
viscosity,
density,
attitude_angle=None,
eccentricity=None,
load=None,
omegap=None,
immediately_calculate_pressure_matrix_numerically=True,
bearing_type=None,
shape_geometry="cylindrical",
preload=0.4,
displacement=0,
max_depth=None,
):
self.nz = nz
self.ntheta = ntheta
self.n_interv_z = nz - 1
self.n_interv_theta = ntheta - 1
self.length = length
self.ltheta = 2.0 * np.pi
self.dz = length / self.n_interv_z
self.dtheta = self.ltheta / self.n_interv_theta
self.ntotal = self.nz * self.ntheta
self.omega = omega
self.p_in = p_in
self.p_out = p_out
self.radius_rotor = radius_rotor
self.radius_stator = radius_stator
self.viscosity = viscosity
self.density = density
self.characteristic_speed = self.omega * self.radius_rotor
self.radial_clearance = self.radius_stator - self.radius_rotor
self.bearing_type = bearing_type
if bearing_type is None:
if self.length / (2 * self.radius_stator) <= 1 / 4:
self.bearing_type = "short_bearing"
elif self.length / (2 * self.radius_stator) > 4:
self.bearing_type = "long_bearing"
else:
self.bearing_type = "medium_size"
self.shape_geometry = shape_geometry
self.preload = preload
self.displacement = displacement
self.max_depth = max_depth
self.eccentricity = eccentricity
self.attitude_angle = attitude_angle
self.eccentricity_ratio = None
self.load = load
self.omegap = omegap
if self.omegap is None:
self.omegap = self.omega
else:
self.omegap = omegap
self.z_list = np.zeros(self.nz)
self.re = np.zeros([self.nz, self.ntheta])
self.ri = np.zeros([self.nz, self.ntheta])
self.xre = np.zeros([self.nz, self.ntheta])
self.xri = np.zeros([self.nz, self.ntheta])
self.yre = np.zeros([self.nz, self.ntheta])
self.yri = np.zeros([self.nz, self.ntheta])
self.gama = np.zeros([self.nz, self.ntheta])
self.t = 0
self.xp = 0
self.yp = 0
if (
self.bearing_type == "short_bearing"
and self.shape_geometry == "cylindrical"
):
if self.eccentricity is None and load is not None:
modified_s = modified_sommerfeld_number(
self.radius_stator,
self.omega,
self.viscosity,
self.length,
self.load,
self.radial_clearance,
)
self.eccentricity_ratio = calculate_eccentricity_ratio(modified_s)
self.eccentricity = (
calculate_eccentricity_ratio(modified_s) * self.radial_clearance
)
if attitude_angle is None:
self.attitude_angle = calculate_attitude_angle(
self.eccentricity_ratio
)
elif self.eccentricity is not None and load is not None:
modified_s = modified_sommerfeld_number(
self.radius_stator,
self.omega,
self.viscosity,
self.length,
self.load,
self.radial_clearance,
)
self.eccentricity_ratio = calculate_eccentricity_ratio(modified_s)
if attitude_angle is None:
self.attitude_angle = calculate_attitude_angle(
self.eccentricity_ratio
)
elif eccentricity is not None and load is None:
self.eccentricity_ratio = self.eccentricity / self.radial_clearance
self.load = calculate_rotor_load(
self.radius_stator,
self.omega,
self.viscosity,
self.length,
self.radial_clearance,
self.eccentricity_ratio,
)
if attitude_angle is None:
self.attitude_angle = calculate_attitude_angle(
self.eccentricity_ratio
)
else:
sys.exit("Either load or eccentricity must be given.")
self.xi = self.eccentricity * np.cos(3 * np.pi / 2 + self.attitude_angle)
self.yi = self.eccentricity * np.sin(3 * np.pi / 2 + self.attitude_angle)
self.geometry_description()
else:
if load is not None:
find_equilibrium_position(self)
if eccentricity is not None:
self.eccentricity = eccentricity
if attitude_angle is not None:
self.attitude_angle = attitude_angle
else:
if attitude_angle is None:
sys.exit("Attitude angle or load must be given.")
if eccentricity is None:
sys.exit("Eccentricity or load must be given.")
self.geometry_description()
self.eccentricity_ratio = self.eccentricity / self.radial_clearance
self.xi = self.eccentricity * np.cos(3 * np.pi / 2 + self.attitude_angle)
self.yi = self.eccentricity * np.sin(3 * np.pi / 2 + self.attitude_angle)
self.p_mat_analytical = np.zeros([self.nz, self.ntheta])
self.p_mat_numerical = np.zeros([self.nz, self.ntheta])
self.analytical_pressure_matrix_available = False
self.numerical_pressure_matrix_available = False
if immediately_calculate_pressure_matrix_numerically:
self.calculate_pressure_matrix_numerical()
def calculate_pressure_matrix_analytical(self, method=0, force_type=None):
"""This function calculates the pressure matrix analytically
for the cylindrical bearing.
Parameters
----------
method: int
Determines the analytical method to be used, when more than one is available.
In case of a short bearing:
0: based on the book Tribology Series vol. 33, by Frene et al., chapter 5.
1: based on the chapter Linear and Nonlinear Rotordynamics, by Ishida and
Yamamoto, from the book Flow-Induced Vibrations.
In case of a long bearing:
0: based on the Fundamentals of Fluid Flow Lubrification, by Hamrock, chapter 10.
force_type: str
If set, calculates the pressure matrix analytically considering the chosen type: 'short' or 'long'.
Returns
-------
p_mat_analytical: matrix of float
Pressure matrix of size (nz x ntheta)
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_analytical() # doctest: +ELLIPSIS
array([[...
"""
if self.bearing_type == "short_bearing" or force_type == "short":
if method == 0:
for i in range(0, self.nz):
for j in range(0, self.ntheta):
# fmt: off
self.p_mat_analytical[i, j] = (
((-3 * self.viscosity * self.omega) / self.radial_clearance ** 2) *
((i * self.dz - (self.length / 2)) ** 2 - (self.length ** 2) / 4) *
(self.eccentricity_ratio * np.sin(j * self.dtheta)) /
(1 + self.eccentricity_ratio * np.cos(j * self.dtheta)) ** 3)
# fmt: on
if self.p_mat_analytical[i, j] < 0:
self.p_mat_analytical[i, j] = 0
elif method == 1:
for i in range(0, self.nz):
for j in range(0, self.ntheta):
# fmt: off
self.p_mat_analytical[i, j] = (3 * self.viscosity / ((self.radial_clearance ** 2) *
(1. + self.eccentricity_ratio * np.cos(
j * self.dtheta)) ** 3)) * \
(-self.eccentricity_ratio * self.omega * np.sin(
j * self.dtheta)) * \
(((i * self.dz - (self.length / 2)) ** 2) - (
self.length ** 2) / 4)
# fmt: on
if self.p_mat_analytical[i, j] < 0:
self.p_mat_analytical[i, j] = 0
elif self.bearing_type == "long_bearing" or force_type == "long":
if method == 0:
for i in range(0, self.nz):
for j in range(0, self.ntheta):
self.p_mat_analytical[i, j] = (
6
* self.viscosity
* self.omega
* (self.radius_rotor / self.radial_clearance) ** 2
* self.eccentricity_ratio
* np.sin(self.dtheta * j)
* (2 + self.eccentricity_ratio * np.cos(self.dtheta * j))
) / (
(2 + self.eccentricity_ratio**2)
* (1 + self.eccentricity_ratio * np.cos(self.dtheta * j))
** 2
) + self.p_in
if self.p_mat_analytical[i, j] < 0:
self.p_mat_analytical[i, j] = 0
elif self.bearing_type == "medium_size" or self.shape_geometry != "cylindrical":
raise ValueError(
"The pressure matrix can only be calculated analytically for short or long cylindrical "
"bearings. For cylindrical bearings: Try calling calculate_pressure_matrix_numerical "
"or setting force_type to either 'short' or 'long' in calculate_pressure_matrix_analytical. "
"For other geometries: Try calling calculate_pressure_matrix_numerical"
)
self.analytical_pressure_matrix_available = True
return self.p_mat_analytical
def geometry_description(self):
"""This function calculates the geometry description.
It is executed when the class is instantiated.
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.geometry_description()
"""
if self.shape_geometry == "cylindrical":
start = (np.pi / 2) + self.attitude_angle
else:
start = 0
for i in range(0, self.nz):
zno = i * self.dz
self.z_list[i] = zno
for j in range(0, self.ntheta):
# fmt: off
self.gama[i, j] = j * self.dtheta + start
[radius_external, self.xre[i, j], self.yre[i, j]] = \
external_radius_function(self.gama[i, j], self.radius_stator, self.radius_rotor,
shape=self.shape_geometry, preload=self.preload,
displacement=self.displacement, max_depth=self.max_depth)
[radius_internal, self.xri[i, j], self.yri[i, j]] = \
internal_radius_function(self.gama[i, j], self.attitude_angle, self.radius_rotor,
self.eccentricity)
self.re[i, j] = radius_external
self.ri[i, j] = radius_internal
# fmt: on
def calculate_coefficients(self, direction=None):
"""This function calculates the constants that form the Poisson equation
of the discrete pressure (central differences in the second
derivatives).
Parameters
----------
direction: str
If defined, it calculates the model based on the disturbance in the chosen direction: 'x' or 'y'.
Returns
--------
c1, c2, c0w: matrix of float
Constants that form the Poisson equation.
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_coefficients()# doctest: +ELLIPSIS
(array([[...
"""
c1 = np.zeros([self.nz, self.ntheta])
c2 = np.zeros([self.nz, self.ntheta])
c0w = np.zeros([self.nz, self.ntheta])
for i in range(0, self.nz):
eccentricity_error = False
for j in range(0, self.ntheta):
# fmt: off
w = self.omega * self.radius_rotor
k = (self.re[i, j] ** 2 * (np.log(self.re[i, j]) - 1 / 2) - self.ri[i, j] ** 2 *
(np.log(self.ri[i, j]) - 1 / 2)) / (self.ri[i, j] ** 2 - self.re[i, j] ** 2)
c1[i, j] = (1 / (4 * self.viscosity)) * ((self.re[i, j] ** 2 * np.log(self.re[i, j]) -
self.ri[i, j] ** 2 * np.log(self.ri[i, j]) +
(self.re[i, j] ** 2 - self.ri[i, j] ** 2) *
(k - 1)) - 2 * self.re[i, j] ** 2 * (
(np.log(self.re[i, j]) + k - 1 / 2) * np.log(
self.re[i, j] / self.ri[i, j])))
c2[i, j] = (- self.ri[i, j] ** 2) / (8 * self.viscosity) * \
((self.re[i, j] ** 2 - self.ri[i, j] ** 2 -
(self.re[i, j] ** 4 - self.ri[i, j] ** 4) /
(2 * self.ri[i, j] ** 2)) +
((self.re[i, j] ** 2 - self.ri[i, j] ** 2) /
(self.ri[i, j] ** 2 *
np.log(self.re[i, j] / self.ri[i, j]))) *
(self.re[i, j] ** 2 * np.log(self.re[i, j] / self.ri[i, j]) -
(self.re[i, j] ** 2 - self.ri[i, j] ** 2) / 2))
c0w[i, j] = (- w * self.ri[i, j] *
(np.log(self.re[i, j] / self.ri[i, j]) *
(1 + (self.ri[i, j] ** 2) / (self.re[i, j] ** 2 - self.ri[i, j] ** 2)) - 1 / 2))
if direction == "x":
a = self.omegap * self.xp * np.cos(self.omegap * self.t)
c0w[i, j] += self.ri[i, j] * a * np.sin(self.gama[i, j])
elif direction == "y":
b = self.omegap * self.yp * np.cos(self.omegap * self.t)
c0w[i, j] -= self.ri[i, j] * b * np.cos(self.gama[i, j])
else:
c0w[i, j] += 0
# fmt: on
if not eccentricity_error:
if abs(self.xri[i, j]) > abs(self.xre[i, j]) or abs(
self.yri[i, j]
) > abs(self.yre[i, j]):
eccentricity_error = True
if eccentricity_error:
raise ValueError(
"Error: The given parameters create a rotor that is not inside the stator. "
"Check parameters and fix accordingly."
)
return c1, c2, c0w
def mounting_matrix(self, c1, c2, c0w):
"""This function assembles the matrix M and the independent vector f.
Parameters
----------
c1, c2, c0w: matrix of float
Constants that form the Poisson equation.
Returns
--------
M: matrix of float
Matrix composed of coefficients that multiply the pressures at each point in the discrete domain.
f: array of float
Pressure independent terms.
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> c1, c2, c0w = my_fluid_flow.calculate_coefficients()
>>> my_fluid_flow.mounting_matrix(c1, c2, c0w)# doctest: +ELLIPSIS
(array([[...
"""
# fmt: off
M = np.zeros([self.ntotal, self.ntotal])
f = np.zeros([self.ntotal, 1])
count = 0
for x in range(self.ntheta):
M[count, count] = 1
f[count, 0] = self.p_in
count = count + self.nz - 1
M[count, count] = 1
f[count, 0] = self.p_out
count = count + 1
count = 0
for x in range(self.nz - 2):
M[self.ntotal - self.nz + 1 + count, 1 + count] = 1
M[self.ntotal - self.nz + 1 + count, self.ntotal - self.nz + 1 + count] = -1
count = count + 1
count = 1
j = 0
for i in range(1, self.nz - 1):
a = (1 / self.dtheta ** 2) * (c1[i, self.ntheta - 1])
M[count, self.ntotal - 2 * self.nz + count] = a
b = (1 / self.dz ** 2) * (c2[i - 1, j])
M[count, count - 1] = b
c = -((1 / self.dtheta ** 2) * ((c1[i, j]) + c1[i, self.ntheta - 1])
+ (1 / self.dz ** 2) * (c2[i, j] + c2[i - 1, j]))
M[count, count] = c
d = (1 / self.dz ** 2) * (c2[i, j])
M[count, count + 1] = d
e = (1 / self.dtheta ** 2) * (c1[i, j])
M[count, count + self.nz] = e
count = count + 1
count = self.nz + 1
for j in range(1, self.ntheta - 1):
for i in range(1, self.nz - 1):
a = (1 / self.dtheta ** 2) * (c1[i, j - 1])
M[count, count - self.nz] = a
b = (1 / self.dz ** 2) * (c2[i - 1, j])
M[count, count - 1] = b
c = -((1 / self.dtheta ** 2) * ((c1[i, j]) + c1[i, j - 1])
+ (1 / self.dz ** 2) * (c2[i, j] + c2[i - 1, j]))
M[count, count] = c
d = (1 / self.dz ** 2) * (c2[i, j])
M[count, count + 1] = d
e = (1 / self.dtheta ** 2) * (c1[i, j])
M[count, count + self.nz] = e
count = count + 1
count = count + 2
count = 1
for j in range(self.ntheta - 1):
for i in range(1, self.nz - 1):
if j == 0:
f[count, 0] = (c0w[i, j] - c0w[i, self.ntheta - 1]) / self.dtheta
else:
f[count, 0] = (c0w[i, j] - c0w[i, j - 1]) / self.dtheta
count = count + 1
count = count + 2
# fmt: on
return M, f
def resolves_matrix(self, M, f):
"""This function resolves the linear system [M]{P} = {f}.
Parameters
----------
M: matrix of float
Matrix composed of coefficients that multiply the pressures at each point in the discrete domain.
f: array of float
Pressure independent terms.
Returns
--------
P: array of floats
Pressure. Unknowns of the finite difference system.
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> c1, c2, c0w = my_fluid_flow.calculate_coefficients()
>>> M, f = my_fluid_flow.mounting_matrix(c1, c2, c0w)
>>> my_fluid_flow.resolves_matrix(M, f)# doctest: +ELLIPSIS
array([[...
"""
sparse_matrix = sp.sparse.csc_matrix(M)
P = sp.sparse.linalg.spsolve(sparse_matrix, f)
P.shape = (P.size, 1)
return P
def calculate_pressure_matrix_numerical(self, direction=None):
"""This function calculates the pressure matrix numerically.
Parameters
----------
direction: str
If defined, it calculates the model based on the disturbance in the chosen direction: 'x' or 'y'.
Returns
-------
p_mat_numerical: matrix of float
Pressure matrix of size (nz x ntheta)
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
"""
if direction == "x":
c1, c2, c0w = self.calculate_coefficients(direction="x")
elif direction == "y":
c1, c2, c0w = self.calculate_coefficients(direction="y")
else:
c1, c2, c0w = self.calculate_coefficients()
M, f = self.mounting_matrix(c1, c2, c0w)
P = self.resolves_matrix(M, f)
self.p_mat_numerical = np.clip(
P.reshape((self.ntheta, self.nz)), a_min=0, a_max=None
).T
self.numerical_pressure_matrix_available = True
return self.p_mat_numerical
def fluid_flow_example():
"""This function returns an instance of a simple fluid flow.
The purpose is to make available a simple short-bearing model
so that doctest can be written using it.
Parameters
----------
Returns
-------
An instance of a fluid flow object.
Examples
--------
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.eccentricity
0.0001
"""
my_pressure_matrix = FluidFlow(
nz=8,
ntheta=32,
length=0.04,
omega=100.0 * 2 * np.pi / 60,
p_in=0.0,
p_out=0.0,
radius_rotor=0.2,
radius_stator=0.2002,
viscosity=0.015,
density=860.0,
eccentricity=0.0001,
attitude_angle=np.pi / 4,
immediately_calculate_pressure_matrix_numerically=False,
)
return my_pressure_matrix
def fluid_flow_example2():
"""This function returns a different instance of a simple fluid flow.
The purpose is to make available a simple medium-bearing model
so that doctest can be written using it.
Parameters
----------
Returns
-------
An instance of a fluid flow object.
Examples
--------
>>> my_fluid_flow = fluid_flow_example2()
>>> my_fluid_flow.load
525
"""
nz = 8
ntheta = 16
length = 0.03
omega = 157.1
p_in = 0.0
p_out = 0.0
radius_rotor = 0.0499
radius_stator = 0.05
load = 525
visc = 0.1
rho = 860.0
return FluidFlow(
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
visc,
rho,
load=load,
immediately_calculate_pressure_matrix_numerically=True,
)
def fluid_flow_example3():
"""This function returns a different instance of a simple fluid flow.
The purpose is to make available a simple eliptical-bearing model
so that doctest can be written using it.
Parameters
----------
Returns
-------
An instance of a fluid flow object.
Examples
--------
>>> my_fluid_flow = fluid_flow_example3()
>>> my_fluid_flow.load
100
"""
nz = 8
ntheta = 32
omega = 2500 * np.pi / 30.0
p_in = 0.0
p_out = 0.0
radius_stator = (3 * 10 ** (-2)) / 2
cr = 9 * 10 ** (-5)
m = 0.4
radius_rotor = radius_stator - cr
length = 2 * 10 ** (-2)
load = 100
viscosity = 5.449 * 10 ** (-2)
density = 881
return FluidFlow(
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
viscosity,
density,
load=load,
shape_geometry="eliptical",
preload=m,
)
def fluid_flow_example4():
"""This function returns a different instance of a simple fluid flow.
The purpose is to make available a simple wear-bearing model
so that doctest can be written using it.
Parameters
----------
Returns
-------
An instance of a fluid flow object.
Examples
--------
>>> my_fluid_flow = fluid_flow_example4()
>>> my_fluid_flow.load
18.9
"""
nz = 8
ntheta = 32
omega = 1000 * np.pi / 30.0
p_in = 0.0
p_out = 0.0
radius_stator = (30 / 2) * 10 ** (-3)
cr = 90 * 10 ** (-6)
radius_rotor = radius_stator - cr
length = 20 * 10 ** (-3)
load = 18.9
viscosity = 1.044 / 10.0
density = 881
max_depth = 50 * 10 ** (-6)
y = 10 * np.pi / 180
return FluidFlow(
nz,
ntheta,
length,
omega,
p_in,
p_out,
radius_rotor,
radius_stator,
viscosity,
density,
load=load,
shape_geometry="wear",
max_depth=max_depth,
displacement=y,
) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/fluid_flow/fluid_flow.py | 0.831725 | 0.809201 | fluid_flow.py | pypi |
import numpy as np
from scipy.optimize import least_squares, root
def calculate_attitude_angle(eccentricity_ratio):
"""Calculates the attitude angle based on the eccentricity ratio.
Suitable only for short bearings.
Parameters
----------
eccentricity_ratio: float
The ratio between the journal displacement, called just eccentricity, and
the radial clearance.
Returns
-------
float
Attitude angle
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> calculate_attitude_angle(my_fluid_flow.eccentricity_ratio) # doctest: +ELLIPSIS
0.93...
"""
return np.arctan(
(np.pi * (1 - eccentricity_ratio**2) ** (1 / 2)) / (4 * eccentricity_ratio)
)
def internal_radius_function(gama, attitude_angle, radius_rotor, eccentricity):
"""This function calculates the x and y of the internal radius of the rotor,
as well as its distance from the origin, given the distance in the theta-axis,
the attitude angle, the radius of the rotor and the eccentricity.
Parameters
----------
gama: float
Gama is the distance in the theta-axis. It should range from 0 to 2*np.pi.
attitude_angle: float
Attitude angle. Angle between the origin and the eccentricity (rad).
radius_rotor: float
The radius of the journal.
eccentricity: float
The journal displacement from the center of the stator.
Returns
-------
radius_internal: float
The size of the internal radius at that point.
xri: float
The position x of the returned internal radius.
yri: float
The position y of the returned internal radius.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> attitude_angle = my_fluid_flow.attitude_angle
>>> radius_rotor = my_fluid_flow.radius_rotor
>>> eccentricity = my_fluid_flow.eccentricity
>>> radius_internal, xri, yri = internal_radius_function(0, attitude_angle, radius_rotor, eccentricity)
>>> radius_internal # doctest: +ELLIPSIS
0.2...
"""
if (np.pi / 2 + attitude_angle) < gama < (3 * np.pi / 2 + attitude_angle):
alpha = np.absolute(3 * np.pi / 2 - gama + attitude_angle)
else:
alpha = gama + np.pi / 2 - attitude_angle
radius_internal = np.sqrt(
radius_rotor**2 - (eccentricity * np.sin(alpha)) ** 2
) + eccentricity * np.cos(alpha)
xri = radius_internal * np.cos(gama)
yri = radius_internal * np.sin(gama)
return radius_internal, xri, yri
def external_radius_function(
gama,
radius_stator,
radius_rotor=None,
shape="cylindrical",
preload=None,
displacement=None,
max_depth=None,
):
"""This function returns the x and y of the radius of the stator, as well as its distance from the
origin, given the distance in the theta-axis and the radius of the bearing.
Parameters
----------
gama: float
Gama is the distance in the theta-axis. It should range from 0 to 2*np.pi.
radius_stator : float
The external radius of the bearing.
radius_rotor : float
The internal radius of the bearing.
shape : str
Determines the type of bearing geometry.
'cylindrical': cylindrical bearing;
'eliptical': eliptical bearing;
'wear': journal bearing wear.
The default is 'cylindrical'.
preload : float
The ellipticity ratio of the bearing if the shape is eliptical. Varies between 0 and 1.
The default is 0.05.
displacement : float
Angular displacement of the bearing wear in relation to the vertical axis.
max_depth: float
The maximum wear depth.
Returns
-------
radius_external: float
The size of the external radius at that point.
xre: float
The position x of the returned external radius.
yre: float
The position y of the returned external radius.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> radius_stator = my_fluid_flow.radius_stator
>>> radius_external, xre, yre = external_radius_function(0, radius_stator)
>>> radius_external
0.2002
"""
if shape == "eliptical":
cr = radius_stator - radius_rotor
elip = preload * cr
if 0 <= gama <= np.pi / 2:
alpha = np.pi / 2 + gama
elif np.pi / 2 < gama <= np.pi:
alpha = 3 * np.pi / 2 - gama
elif np.pi < gama <= 3 * np.pi / 2:
alpha = gama - np.pi / 2
else:
alpha = 5 * np.pi / 2 - gama
radius_external = elip * np.cos(alpha) + np.sqrt(
((radius_stator) ** 2) - (elip * np.sin(alpha)) ** 2
)
xre = radius_external * np.cos(gama)
yre = radius_external * np.sin(gama)
elif shape == "wear":
if max_depth == 0:
d_theta = 0
else:
cr = radius_stator - radius_rotor
theta_s = np.pi / 2 + np.arccos(max_depth / cr - 1) + displacement
theta_f_0 = np.pi / 2 - np.arccos(max_depth / cr - 1) + displacement
theta_f = 2 * np.pi + theta_f_0
if theta_f <= 2 * np.pi:
if theta_s <= gama <= theta_f:
d_theta = max_depth - cr * (
1 + np.cos(gama - np.pi / 2 - displacement)
)
else:
d_theta = 0
else:
if theta_s <= gama <= 2 * np.pi:
d_theta = max_depth - cr * (
1 + np.cos(gama - np.pi / 2 - displacement)
)
elif 0 <= gama <= theta_f_0:
gama2 = gama + 2 * np.pi
d_theta = max_depth - cr * (
1 + np.cos(gama2 - np.pi / 2 - displacement)
)
else:
d_theta = 0
radius_external = radius_stator + d_theta
xre = radius_external * np.cos(gama)
yre = radius_external * np.sin(gama)
else:
radius_external = radius_stator
xre = radius_external * np.cos(gama)
yre = radius_external * np.sin(gama)
return radius_external, xre, yre
def reynolds_number(density, characteristic_speed, radial_clearance, viscosity):
"""Returns the reynolds number based on the characteristic speed.
This number denotes the ratio between fluid inertia (advection) forces and viscous-shear forces.
Parameters
----------
density: float
Fluid density(Kg/m^3).
characteristic_speed: float
Characteristic fluid speeds.
radial_clearance: float
Difference between both stator and rotor radius, regardless of eccentricity.
viscosity: float
Viscosity (Pa.s).
Returns
-------
float
The reynolds number.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> density = my_fluid_flow.density
>>> characteristic_speed = my_fluid_flow.characteristic_speed
>>> radial_clearance = my_fluid_flow.radial_clearance
>>> viscosity = my_fluid_flow.viscosity
>>> reynolds_number(density, characteristic_speed, radial_clearance, viscosity) # doctest: +ELLIPSIS
24.01...
"""
return (density * characteristic_speed * radial_clearance) / viscosity
def modified_sommerfeld_number(
radius_stator, omega, viscosity, length, load, radial_clearance
):
"""Returns the modified sommerfeld number.
Parameters
----------
radius_stator : float
The external radius of the bearing.
omega: float
Rotation of the rotor (rad/s).
viscosity: float
Viscosity (Pa.s).
length: float
Length in the Z direction (m).
load: float
Load applied to the rotor (N).
radial_clearance: float
Difference between both stator and rotor radius, regardless of eccentricity.
Returns
-------
float
The modified sommerfeld number.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> radius_stator = my_fluid_flow.radius_stator
>>> omega = my_fluid_flow.omega
>>> viscosity = my_fluid_flow.viscosity
>>> length = my_fluid_flow.length
>>> load = my_fluid_flow.load
>>> radial_clearance = my_fluid_flow.radial_clearance
>>> modified_sommerfeld_number(radius_stator, omega, viscosity,
... length, load, radial_clearance) # doctest: +ELLIPSIS
0.33...
"""
return (radius_stator * 2 * omega * viscosity * (length**3)) / (
8 * load * (radial_clearance**2)
)
def sommerfeld_number(modified_s, radius_stator, length):
"""Returns the sommerfeld number, based on the modified sommerfeld number.
Parameters
----------
modified_s: float
The modified sommerfeld number.
radius_stator : float
The external radius of the bearing.
length: float
Length in the Z direction (m).
Returns
-------
float
The sommerfeld number.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> radius_stator = my_fluid_flow.radius_stator
>>> omega = my_fluid_flow.omega
>>> viscosity = my_fluid_flow.viscosity
>>> length = my_fluid_flow.length
>>> load = my_fluid_flow.load
>>> radial_clearance = my_fluid_flow.radial_clearance
>>> modified_s = modified_sommerfeld_number(radius_stator, omega, viscosity,
... length, load, radial_clearance) # doctest: +ELLIPSIS
>>> sommerfeld_number(modified_s, radius_stator, length) # doctest: +ELLIPSIS
10.62...
"""
return (modified_s / np.pi) * (radius_stator * 2 / length) ** 2
def calculate_eccentricity_ratio(modified_s):
"""Calculate the eccentricity ratio for a given load using the sommerfeld number.
Suitable only for short bearings.
Parameters
----------
modified_s: float
The modified sommerfeld number.
Returns
-------
float
The eccentricity ratio.
Examples
--------
>>> modified_s = 6.329494061103412
>>> calculate_eccentricity_ratio(modified_s) # doctest: +ELLIPSIS
0.04999...
"""
coefficients = [
1,
-4,
(6 - (modified_s**2) * (16 - np.pi**2)),
-(4 + (np.pi**2) * (modified_s**2)),
1,
]
roots = np.roots(coefficients)
roots = np.sort(roots[np.isclose(roots.imag, 1e-16)].real)
def f(x):
"""Fourth degree polynomial whose root is the square of the eccentricity ratio.
Parameters
----------
x: float
Fourth degree polynomial coefficients.
Returns
-------
float
Polynomial value f at x."""
c = coefficients
return (
c[0] * x**4
+ c[1] * x**3
+ c[2] * x**2
+ c[3] * x**1
+ c[4] * x**0
)
for i in roots:
if 0 <= i <= 1:
roots = root(f, i, tol=1e-10).x[0]
return np.sqrt(roots)
raise ValueError("Eccentricity ratio could not be calculated.")
def calculate_rotor_load(
radius_stator, omega, viscosity, length, radial_clearance, eccentricity_ratio
):
"""Returns the load applied to the rotor, based on the eccentricity ratio.
Suitable only for short bearings.
Parameters
----------
radius_stator : float
The external radius of the bearing.
omega: float
Rotation of the rotor (rad/s).
viscosity: float
Viscosity (Pa.s).
length: float
Length in the Z direction (m).
radial_clearance: float
Difference between both stator and rotor radius, regardless of eccentricity.
eccentricity_ratio: float
The ratio between the journal displacement, called just eccentricity, and
the radial clearance.
Returns
-------
float
Load applied to the rotor.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> radius_stator = my_fluid_flow.radius_stator
>>> omega = my_fluid_flow.omega
>>> viscosity = my_fluid_flow.viscosity
>>> length = my_fluid_flow.length
>>> radial_clearance = my_fluid_flow.radial_clearance
>>> eccentricity_ratio = my_fluid_flow.eccentricity_ratio
>>> calculate_rotor_load(radius_stator, omega, viscosity,
... length, radial_clearance, eccentricity_ratio) # doctest: +ELLIPSIS
37.75...
"""
return (
(
np.pi
* radius_stator
* 2
* omega
* viscosity
* (length**3)
* eccentricity_ratio
)
/ (8 * (radial_clearance**2) * ((1 - eccentricity_ratio**2) ** 2))
) * (np.sqrt((16 / (np.pi**2) - 1) * eccentricity_ratio**2 + 1))
def move_rotor_center(fluid_flow_object, dx, dy):
"""For a given step on x or y axis,
moves the rotor center and calculates new eccentricity, attitude angle,
and rotor center.
Parameters
----------
fluid_flow_object: A FluidFlow object.
dx: float
The step on x axis.
dy: float
The step on y axis.
Returns
-------
None
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example2
>>> my_fluid_flow = fluid_flow_example2()
>>> move_rotor_center(my_fluid_flow, 0, 0)
>>> my_fluid_flow.eccentricity # doctest: +ELLIPSIS
2.54...
"""
fluid_flow_object.xi = fluid_flow_object.xi + dx
fluid_flow_object.yi = fluid_flow_object.yi + dy
fluid_flow_object.eccentricity = np.sqrt(
fluid_flow_object.xi**2 + fluid_flow_object.yi**2
)
fluid_flow_object.eccentricity_ratio = (
fluid_flow_object.eccentricity / fluid_flow_object.radial_clearance
)
fluid_flow_object.attitude_angle = np.arccos(
abs(fluid_flow_object.yi / fluid_flow_object.eccentricity)
)
def move_rotor_center_abs(fluid_flow_object, x, y):
"""Moves the rotor center to the coordinates (x, y) and calculates new eccentricity,
attitude angle, and rotor center.
Parameters
----------
fluid_flow_object: A FluidFlow object.
x: float
Coordinate along x axis.
y: float
Coordinate along y axis.
Returns
-------
None
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> move_rotor_center_abs(my_fluid_flow, 0, -1e-3*my_fluid_flow.radial_clearance)
>>> my_fluid_flow.eccentricity # doctest: +ELLIPSIS
1.99...
"""
fluid_flow_object.xi = x
fluid_flow_object.yi = y
fluid_flow_object.eccentricity = np.sqrt(
fluid_flow_object.xi**2 + fluid_flow_object.yi**2
)
fluid_flow_object.eccentricity_ratio = (
fluid_flow_object.eccentricity / fluid_flow_object.radial_clearance
)
fluid_flow_object.attitude_angle = np.arccos(
abs(fluid_flow_object.yi / fluid_flow_object.eccentricity)
) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/fluid_flow/fluid_flow_geometry.py | 0.953405 | 0.782455 | fluid_flow_geometry.py | pypi |
import numpy as np
from plotly import graph_objects as go
from ross.plotly_theme import tableau_colors
def plot_eccentricity(fluid_flow_object, z=0, fig=None, scale_factor=1.0, **kwargs):
"""Plot the rotor eccentricity.
This function assembles pressure graphic along the z-axis.
The first few plots are of a different color to indicate where theta begins.
Parameters
----------
fluid_flow_object: a FluidFlow object
z: int, optional
The distance in z where to cut and plot.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
scale_factor : float, optional
Scaling factor to plot the rotor shape. Values must range between 0 and 1
inclusive. 1 is the true scale (1 : 1).
Default is to 1.0.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> fig = plot_eccentricity(my_fluid_flow, z=int(my_fluid_flow.nz/2))
>>> # to show the plots you can use:
>>> # fig.show()
"""
if not 0 <= scale_factor <= 1:
raise ValueError("scale_factor value must be between 0 and 1.")
s = 0.5 * scale_factor + 0.5
angle = fluid_flow_object.attitude_angle
xre = fluid_flow_object.xre[z]
xri = fluid_flow_object.xri[z]
yre = fluid_flow_object.yre[z]
yri = fluid_flow_object.yri[z]
val_min = np.min(
np.sqrt(xre**2 + yre**2) - np.sqrt((xri * s) ** 2 + (yri * s) ** 2)
)
val_ref = np.min(np.sqrt(xre**2 + yre**2) - np.sqrt(xri**2 + yri**2))
if fig is None:
fig = go.Figure()
customdata = [
fluid_flow_object.attitude_angle * 180 / np.pi,
fluid_flow_object.eccentricity,
fluid_flow_object.radius_rotor,
fluid_flow_object.radius_stator,
fluid_flow_object.preload,
fluid_flow_object.shape_geometry,
]
hovertemplate_rotor = (
"Attitude angle: {:.2f}°<br>"
+ "Eccentricity: {:.2e}<br>"
+ "Rotor radius: {:.2e}<br>"
).format(customdata[0], customdata[1], customdata[2])
hovertemplate_stator = (
"Stator radius: {:.2e}<br>"
+ "Ellipticity ratio: {:.2f}<br>"
+ "Shape Geometry: {}<br>"
).format(customdata[3], customdata[4], customdata[5])
fig.add_trace(
go.Scatter(
x=xre,
y=yre,
customdata=[customdata] * len(xre),
mode="markers+lines",
marker=dict(color=tableau_colors["red"]),
line=dict(color=tableau_colors["red"]),
name="Stator",
legendgroup="Stator",
hovertemplate=hovertemplate_stator,
)
)
fig.add_trace(
go.Scatter(
x=xri * s + s * (val_min - val_ref) * np.sin(angle),
y=yri * s - s * (val_min - val_ref) * np.cos(angle),
customdata=[customdata] * len(xre),
mode="markers+lines",
marker=dict(color=tableau_colors["blue"]),
line=dict(color=tableau_colors["blue"]),
name="Rotor",
legendgroup="Rotor",
hovertemplate=hovertemplate_rotor,
)
)
fig.add_trace(
go.Scatter(
x=np.array([fluid_flow_object.xi]) * s
+ s * (val_min - val_ref) * np.sin(angle),
y=np.array([fluid_flow_object.yi]) * s
- s * (val_min - val_ref) * np.cos(angle),
customdata=[customdata],
marker=dict(size=8, color=tableau_colors["blue"]),
name="Rotor",
legendgroup="Rotor",
showlegend=False,
hovertemplate=hovertemplate_rotor,
)
)
fig.add_trace(
go.Scatter(
x=[0],
y=[0],
customdata=[customdata],
marker=dict(size=8, color=tableau_colors["red"]),
name="Stator",
legendgroup="Stator",
showlegend=False,
hovertemplate=hovertemplate_stator,
)
)
fig.update_xaxes(title_text="<b>X axis</b>")
fig.update_yaxes(title_text="<b>Y axis</b>")
fig.update_layout(
title=dict(text="<b>Cut in plane Z={}</b>".format(z)),
yaxis=dict(scaleanchor="x", scaleratio=1),
**kwargs,
)
return fig
def plot_pressure_z(fluid_flow_object, theta=0, fig=None, **kwargs):
"""Plot the pressure distribution along the z-axis.
This function assembles pressure graphic along the z-axis for one or both the
numerically (blue) and analytically (red) calculated pressure matrices, depending
on if one or both were calculated.
Parameters
----------
fluid_flow_object: a FluidFlow object
theta: int, optional
The theta to be considered.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
>>> fig = plot_pressure_z(my_fluid_flow, theta=int(my_fluid_flow.ntheta/2))
>>> # to show the plots you can use:
>>> # fig.show()
"""
if (
not fluid_flow_object.numerical_pressure_matrix_available
and not fluid_flow_object.analytical_pressure_matrix_available
):
raise ValueError(
"Must calculate the pressure matrix. "
"Try calling calculate_pressure_matrix_numerical() or calculate_pressure_matrix_analytical() first."
)
if fig is None:
fig = go.Figure()
if fluid_flow_object.numerical_pressure_matrix_available:
fig.add_trace(
go.Scatter(
x=fluid_flow_object.z_list,
y=fluid_flow_object.p_mat_numerical[:, theta],
mode="markers+lines",
line=dict(color=tableau_colors["blue"]),
showlegend=True,
name="<b>Numerical pressure</b>",
hovertemplate=(
"<b>Axial Length: %{x:.2f}</b><br>"
+ "<b>Numerical pressure: %{y:.2f}</b>"
),
)
)
if fluid_flow_object.analytical_pressure_matrix_available:
fig.add_trace(
go.Scatter(
x=fluid_flow_object.z_list,
y=fluid_flow_object.p_mat_analytical[:, theta],
mode="markers+lines",
line=dict(color=tableau_colors["red"]),
showlegend=True,
name="<b>Analytical pressure</b>",
hovertemplate=(
"<b>Axial Length: %{x:.2f}</b><br>"
+ "<b>Analytical pressure: %{y:.2f}</b>"
),
)
)
fig.update_xaxes(title_text="<b>Axial Length</b>")
fig.update_yaxes(title_text="<b>Pressure</b>")
fig.update_layout(
title=dict(
text=(
"<b>Pressure along the flow (axial direction)<b><br>"
+ "<b>Theta={}</b>".format(theta)
)
),
**kwargs,
)
return fig
def plot_shape(fluid_flow_object, theta=0, fig=None, **kwargs):
"""Plot the surface geometry of the rotor.
This function assembles a graphic representing the geometry of the rotor.
Parameters
----------
fluid_flow_object: a FluidFlow object
theta: int, optional
The theta to be considered.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> fig = plot_shape(my_fluid_flow, theta=int(my_fluid_flow.ntheta/2))
>>> # to show the plots you can use:
>>> # fig.show()
"""
if fig is None:
fig = go.Figure()
fig.add_trace(
go.Scatter(
x=fluid_flow_object.z_list,
y=fluid_flow_object.re[:, theta],
mode="markers+lines",
line=dict(color=tableau_colors["red"]),
showlegend=True,
hoverinfo="none",
name="<b>Stator</b>",
)
)
fig.add_trace(
go.Scatter(
x=fluid_flow_object.z_list,
y=fluid_flow_object.ri[:, theta],
mode="markers+lines",
line=dict(color=tableau_colors["blue"]),
showlegend=True,
hoverinfo="none",
name="<b>Rotor</b>",
)
)
fig.update_xaxes(title_text="<b>Axial Length</b>")
fig.update_yaxes(title_text="<b>Radial direction</b>")
fig.update_layout(
title=dict(
text=(
"<b>Shapes of stator and rotor - Axial direction<b><br>"
+ "<b>Theta={}</b>".format(theta)
)
),
**kwargs,
)
return fig
def plot_pressure_theta(fluid_flow_object, z=0, fig=None, **kwargs):
"""Plot the pressure distribution along theta.
This function assembles pressure graphic in the theta direction for a given z
for one or both the numerically (blue) and analytically (red) calculated pressure
matrices, depending on if one or both were calculated.
Parameters
----------
fluid_flow_object: a FluidFlow object
z: int, optional
The distance along z-axis to be considered.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
>>> fig = plot_pressure_theta(my_fluid_flow, z=int(my_fluid_flow.nz/2))
>>> # to show the plots you can use:
>>> # fig.show()
"""
if (
not fluid_flow_object.numerical_pressure_matrix_available
and not fluid_flow_object.analytical_pressure_matrix_available
):
raise ValueError(
"Must calculate the pressure matrix. "
"Try calling calculate_pressure_matrix_numerical() or calculate_pressure_matrix_analytical() first."
)
if fig is None:
fig = go.Figure()
if fluid_flow_object.numerical_pressure_matrix_available:
fig.add_trace(
go.Scatter(
x=fluid_flow_object.gama[z],
y=fluid_flow_object.p_mat_numerical[z],
mode="markers+lines",
line=dict(color=tableau_colors["blue"]),
showlegend=True,
name="<b>Numerical pressure</b>",
hovertemplate=(
"<b>Theta: %{x:.2f}</b><br>" + "<b>Numerical pressure: %{y:.2f}</b>"
),
)
)
elif fluid_flow_object.analytical_pressure_matrix_available:
fig.add_trace(
go.Scatter(
x=fluid_flow_object.gama[z],
y=fluid_flow_object.p_mat_analytical[z],
mode="markers+lines",
line=dict(color=tableau_colors["red"]),
showlegend=True,
name="<b>Analytical pressure</b>",
hovertemplate=(
"<b>Theta: %{x:.2f}</b><br>"
+ "<b>Analytical pressure: %{y:.2f}</b>"
),
)
)
fig.update_xaxes(title_text="<b>Theta value</b>")
fig.update_yaxes(title_text="<b>Pressure</b>")
fig.update_layout(
title=dict(text=("<b>Pressure along Theta | Z={}<b>".format(z))), **kwargs
)
return fig
def plot_pressure_theta_cylindrical(
fluid_flow_object, z=0, from_numerical=True, fig=None, **kwargs
):
"""Plot cylindrical pressure graphic in the theta direction.
This function assembles cylindrical graphical visualization of the fluid pressure
in the theta direction for a given axial position (z).
Parameters
----------
fluid_flow_object: a FluidFlow object
z: int, optional
The distance along z-axis to be considered.
from_numerical: bool, optional
If True, takes the numerically calculated pressure matrix as entry.
If False, takes the analytically calculated one instead.
If condition cannot be satisfied (matrix not calculated), it will take the one
that is available and raise a warning.
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
>>> fig = plot_pressure_theta_cylindrical(my_fluid_flow, z=int(my_fluid_flow.nz/2))
>>> # to show the plots you can use:
>>> # fig.show()
"""
if (
not fluid_flow_object.numerical_pressure_matrix_available
and not fluid_flow_object.analytical_pressure_matrix_available
):
raise ValueError(
"Must calculate the pressure matrix. "
"Try calling calculate_pressure_matrix_numerical() or calculate_pressure_matrix_analytical() first."
)
if from_numerical:
if fluid_flow_object.numerical_pressure_matrix_available:
p_mat = fluid_flow_object.p_mat_numerical
else:
p_mat = fluid_flow_object.p_mat_analytical
else:
if fluid_flow_object.analytical_pressure_matrix_available:
p_mat = fluid_flow_object.p_mat_analytical
else:
p_mat = fluid_flow_object.p_mat_numerical
r = np.linspace(fluid_flow_object.radius_rotor, fluid_flow_object.radius_stator)
theta = np.linspace(
0.0, 2.0 * np.pi + fluid_flow_object.dtheta / 2, fluid_flow_object.ntheta
)
theta *= 180 / np.pi
pressure_along_theta = p_mat[z, :]
min_pressure = np.amin(pressure_along_theta)
r_matrix, theta_matrix = np.meshgrid(r, theta)
z_matrix = np.zeros((theta.size, r.size))
for i in range(0, theta.size):
inner_radius = np.sqrt(
fluid_flow_object.xri[z][i] * fluid_flow_object.xri[z][i]
+ fluid_flow_object.yri[z][i] * fluid_flow_object.yri[z][i]
)
for j in range(r.size):
if r_matrix[i][j] < inner_radius:
continue
z_matrix[i][j] = pressure_along_theta[i] - min_pressure + 0.01
if fig is None:
fig = go.Figure()
fig.add_trace(
go.Barpolar(
r=r_matrix.ravel(),
theta=theta_matrix.ravel(),
customdata=z_matrix.ravel(),
marker=dict(
color=z_matrix.ravel(),
colorscale="Viridis",
cmin=np.amin(z_matrix),
cmax=np.amax(z_matrix),
colorbar=dict(title=dict(text="<b>Pressure</b>", side="top")),
),
thetaunit="degrees",
name="Pressure",
showlegend=False,
hovertemplate=(
"<b>Raddi: %{r:.4e}</b><br>"
+ "<b>θ: %{theta:.2f}</b><br>"
+ "<b>Pressure: %{customdata:.4e}</b>"
),
)
)
fig.update_layout(
polar=dict(
hole=0.5,
bargap=0.0,
angularaxis=dict(
rotation=-90 - fluid_flow_object.attitude_angle * 180 / np.pi
),
),
**kwargs,
)
return fig
def plot_pressure_surface(fluid_flow_object, fig=None, **kwargs):
"""Assembles pressure surface graphic in the bearing, using Plotly.
Parameters
----------
fluid_flow_object: a FluidFlow object
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> my_fluid_flow.calculate_pressure_matrix_numerical() # doctest: +ELLIPSIS
array([[...
>>> fig = plot_pressure_surface(my_fluid_flow)
>>> # to show the plots you can use:
>>> # fig.show()
"""
if (
not fluid_flow_object.numerical_pressure_matrix_available
and not fluid_flow_object.analytical_pressure_matrix_available
):
raise ValueError(
"Must calculate the pressure matrix. "
"Try calling calculate_pressure_matrix_numerical() or calculate_pressure_matrix_analytical() first."
)
if fig is None:
fig = go.Figure()
if fluid_flow_object.numerical_pressure_matrix_available:
z, theta = np.meshgrid(fluid_flow_object.z_list, fluid_flow_object.gama[0])
fig.add_trace(
go.Surface(
x=z,
y=theta,
z=fluid_flow_object.p_mat_numerical.T,
colorscale="Viridis",
cmin=np.amin(fluid_flow_object.p_mat_numerical.T),
cmax=np.amax(fluid_flow_object.p_mat_numerical.T),
colorbar=dict(title=dict(text="<b>Pressure</b>", side="top")),
name="Pressure",
showlegend=False,
hovertemplate=(
"<b>Length: %{x:.2e}</b><br>"
+ "<b>Angular Position: %{y:.2f}</b><br>"
+ "<b>Pressure: %{z:.2f}</b>"
),
)
)
fig.update_layout(
scene=dict(
bgcolor="white",
xaxis=dict(title=dict(text="<b>Rotor Length</b>")),
yaxis=dict(title=dict(text="<b>Angular Position</b>")),
zaxis=dict(title=dict(text="<b>Pressure</b>")),
),
title=dict(text="<b>Bearing Pressure Field</b>"),
**kwargs,
)
return fig | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/fluid_flow/fluid_flow_graphics.py | 0.953546 | 0.769167 | fluid_flow_graphics.py | pypi |
import sys
from math import isnan
import numpy as np
from scipy import integrate
from scipy.optimize import least_squares
from ross.fluid_flow.fluid_flow_geometry import move_rotor_center, move_rotor_center_abs
def calculate_oil_film_force(fluid_flow_object, force_type=None):
"""This function calculates the forces of the oil film in the N and T directions, ie in the
opposite direction to the eccentricity and in the tangential direction.
Parameters
----------
fluid_flow_object: A FluidFlow object.
force_type: str
If set, calculates the oil film force matrix analytically considering the chosen type: 'short' or 'long'.
If set to 'numerical', calculates the oil film force numerically.
Returns
-------
radial_force: float
Force of the oil film in the opposite direction to the eccentricity direction.
tangential_force: float
Force of the oil film in the tangential direction
f_x: float
Components of forces in the x direction
f_y: float
Components of forces in the y direction
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> calculate_oil_film_force(my_fluid_flow) # doctest: +ELLIPSIS
(...
"""
if force_type != "numerical" and (
force_type == "short" or fluid_flow_object.bearing_type == "short_bearing"
):
radial_force = (
0.5
* fluid_flow_object.viscosity
* (fluid_flow_object.radius_rotor / fluid_flow_object.radial_clearance) ** 2
* (fluid_flow_object.length**3 / fluid_flow_object.radius_rotor)
* (
(
2
* fluid_flow_object.eccentricity_ratio**2
* fluid_flow_object.omega
)
/ (1 - fluid_flow_object.eccentricity_ratio**2) ** 2
)
)
tangential_force = (
0.5
* fluid_flow_object.viscosity
* (fluid_flow_object.radius_rotor / fluid_flow_object.radial_clearance) ** 2
* (fluid_flow_object.length**3 / fluid_flow_object.radius_rotor)
* (
(np.pi * fluid_flow_object.eccentricity_ratio * fluid_flow_object.omega)
/ (2 * (1 - fluid_flow_object.eccentricity_ratio**2) ** (3.0 / 2))
)
)
elif force_type != "numerical" and (
force_type == "long" or fluid_flow_object.bearing_type == "long_bearing"
):
radial_force = (
6
* fluid_flow_object.viscosity
* (fluid_flow_object.radius_rotor / fluid_flow_object.radial_clearance) ** 2
* fluid_flow_object.radius_rotor
* fluid_flow_object.length
* (
(
2
* fluid_flow_object.eccentricity_ratio**2
* fluid_flow_object.omega
)
/ (
(2 + fluid_flow_object.eccentricity_ratio**2)
* (1 - fluid_flow_object.eccentricity_ratio**2)
)
)
)
tangential_force = (
6
* fluid_flow_object.viscosity
* (fluid_flow_object.radius_rotor / fluid_flow_object.radial_clearance) ** 2
* fluid_flow_object.radius_rotor
* fluid_flow_object.length
* (
(np.pi * fluid_flow_object.eccentricity_ratio * fluid_flow_object.omega)
/ (
(2 + fluid_flow_object.eccentricity_ratio**2)
* (1 - fluid_flow_object.eccentricity_ratio**2) ** 0.5
)
)
)
else:
p_mat = fluid_flow_object.p_mat_numerical
a = np.zeros([fluid_flow_object.nz, fluid_flow_object.ntheta])
b = np.zeros([fluid_flow_object.nz, fluid_flow_object.ntheta])
g1 = np.zeros(fluid_flow_object.nz)
g2 = np.zeros(fluid_flow_object.nz)
base_vector = np.array(
[
fluid_flow_object.xre[0][0] - fluid_flow_object.xi,
fluid_flow_object.yre[0][0] - fluid_flow_object.yi,
]
)
for i in range(fluid_flow_object.nz):
for j in range(int(fluid_flow_object.ntheta)):
vector_from_rotor = np.array(
[
fluid_flow_object.xre[i][j] - fluid_flow_object.xi,
fluid_flow_object.yre[i][j] - fluid_flow_object.yi,
]
)
angle_between_vectors = np.arctan2(
vector_from_rotor[1], vector_from_rotor[0]
) - np.arctan2(base_vector[1], base_vector[0])
if angle_between_vectors < 0:
angle_between_vectors += 2 * np.pi
a[i][j] = p_mat[i][j] * np.cos(angle_between_vectors)
b[i][j] = p_mat[i][j] * np.sin(angle_between_vectors)
for i in range(fluid_flow_object.nz):
g1[i] = integrate.simps(a[i][:], fluid_flow_object.gama[0])
g2[i] = integrate.simps(b[i][:], fluid_flow_object.gama[0])
integral1 = integrate.simps(g1, fluid_flow_object.z_list)
integral2 = integrate.simps(g2, fluid_flow_object.z_list)
angle_corr = (
np.pi / 2
- np.arctan2(base_vector[1], base_vector[0])
+ fluid_flow_object.attitude_angle
)
radial_force_aux = fluid_flow_object.radius_rotor * integral1
tangential_force_aux = fluid_flow_object.radius_rotor * integral2
radial_force = radial_force_aux * np.cos(
angle_corr + np.pi
) + tangential_force_aux * np.cos(angle_corr + np.pi / 2)
tangential_force = radial_force_aux * np.cos(
angle_corr + np.pi / 2
) + tangential_force_aux * np.cos(angle_corr)
force_x = -radial_force * np.sin(
fluid_flow_object.attitude_angle
) + tangential_force * np.cos(fluid_flow_object.attitude_angle)
force_y = radial_force * np.cos(
fluid_flow_object.attitude_angle
) + tangential_force * np.sin(fluid_flow_object.attitude_angle)
return radial_force, tangential_force, force_x, force_y
def calculate_stiffness_and_damping_coefficients(fluid_flow_object):
"""This function calculates the bearing stiffness and damping matrices numerically.
Parameters
----------
fluid_flow_object: A FluidFlow object.
Returns
-------
Two lists of floats
A list of length four including stiffness floats in this order: kxx, kxy, kyx, kyy.
And another list of length four including damping floats in this order: cxx, cxy, cyx, cyy.
And
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> calculate_stiffness_and_damping_coefficients(my_fluid_flow) # doctest: +ELLIPSIS
([429...
"""
N = 6
t = np.linspace(0, 2 * np.pi / fluid_flow_object.omegap, N)
fluid_flow_object.xp = fluid_flow_object.radial_clearance * 0.0001
fluid_flow_object.yp = fluid_flow_object.radial_clearance * 0.0001
dx = np.zeros(N)
dy = np.zeros(N)
xdot = np.zeros(N)
ydot = np.zeros(N)
radial_force = np.zeros(N)
tangential_force = np.zeros(N)
force_xx = np.zeros(N)
force_yx = np.zeros(N)
force_xy = np.zeros(N)
force_yy = np.zeros(N)
X1 = np.zeros([N, 3])
X2 = np.zeros([N, 3])
F1 = np.zeros(N)
F2 = np.zeros(N)
F3 = np.zeros(N)
F4 = np.zeros(N)
for i in range(N):
fluid_flow_object.t = t[i]
delta_x = fluid_flow_object.xp * np.sin(
fluid_flow_object.omegap * fluid_flow_object.t
)
move_rotor_center(fluid_flow_object, delta_x, 0)
dx[i] = delta_x
xdot[i] = (
fluid_flow_object.omegap
* fluid_flow_object.xp
* np.cos(fluid_flow_object.omegap * fluid_flow_object.t)
)
fluid_flow_object.geometry_description()
fluid_flow_object.calculate_pressure_matrix_numerical(direction="x")
[
radial_force[i],
tangential_force[i],
force_xx[i],
force_yx[i],
] = calculate_oil_film_force(fluid_flow_object, force_type="numerical")
delta_y = fluid_flow_object.yp * np.sin(
fluid_flow_object.omegap * fluid_flow_object.t
)
move_rotor_center(fluid_flow_object, -delta_x, 0)
move_rotor_center(fluid_flow_object, 0, delta_y)
dy[i] = delta_y
ydot[i] = (
fluid_flow_object.omegap
* fluid_flow_object.yp
* np.cos(fluid_flow_object.omegap * fluid_flow_object.t)
)
fluid_flow_object.geometry_description()
fluid_flow_object.calculate_pressure_matrix_numerical(direction="y")
[
radial_force[i],
tangential_force[i],
force_xy[i],
force_yy[i],
] = calculate_oil_film_force(fluid_flow_object, force_type="numerical")
move_rotor_center(fluid_flow_object, 0, -delta_y)
fluid_flow_object.geometry_description()
fluid_flow_object.calculate_pressure_matrix_numerical()
X1[i] = [1, dx[i], xdot[i]]
X2[i] = [1, dy[i], ydot[i]]
F1[i] = -force_xx[i]
F2[i] = -force_xy[i]
F3[i] = -force_yx[i]
F4[i] = -force_yy[i]
P1 = np.dot(
np.dot(np.linalg.inv(np.dot(np.transpose(X1), X1)), np.transpose(X1)), F1
)
P2 = np.dot(
np.dot(np.linalg.inv(np.dot(np.transpose(X2), X2)), np.transpose(X2)), F2
)
P3 = np.dot(
np.dot(np.linalg.inv(np.dot(np.transpose(X1), X1)), np.transpose(X1)), F3
)
P4 = np.dot(
np.dot(np.linalg.inv(np.dot(np.transpose(X2), X2)), np.transpose(X2)), F4
)
K = [P1[1], P2[1], P3[1], P4[1]]
C = [P1[2], P2[2], P3[2], P4[2]]
return K, C
def calculate_short_stiffness_matrix(fluid_flow_object):
"""This function calculates the stiffness matrix for the short bearing.
Parameters
----------
fluid_flow_object: A FluidFlow object.
Returns
-------
list of floats
A list of length four including stiffness floats in this order: kxx, kxy, kyx, kyy
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> calculate_short_stiffness_matrix(my_fluid_flow) # doctest: +ELLIPSIS
[417...
"""
h0 = 1.0 / (
(
(np.pi**2) * (1 - fluid_flow_object.eccentricity_ratio**2)
+ 16 * fluid_flow_object.eccentricity_ratio**2
)
** 1.5
)
a = fluid_flow_object.load / fluid_flow_object.radial_clearance
kxx = (
a
* h0
* 4
* (
(np.pi**2) * (2 - fluid_flow_object.eccentricity_ratio**2)
+ 16 * fluid_flow_object.eccentricity_ratio**2
)
)
kxy = (
a
* h0
* np.pi
* (
(np.pi**2) * (1 - fluid_flow_object.eccentricity_ratio**2) ** 2
- 16 * fluid_flow_object.eccentricity_ratio**4
)
/ (
fluid_flow_object.eccentricity_ratio
* np.sqrt(1 - fluid_flow_object.eccentricity_ratio**2)
)
)
kyx = (
-a
* h0
* np.pi
* (
(np.pi**2)
* (1 - fluid_flow_object.eccentricity_ratio**2)
* (1 + 2 * fluid_flow_object.eccentricity_ratio**2)
+ (32 * fluid_flow_object.eccentricity_ratio**2)
* (1 + fluid_flow_object.eccentricity_ratio**2)
)
/ (
fluid_flow_object.eccentricity_ratio
* np.sqrt(1 - fluid_flow_object.eccentricity_ratio**2)
)
)
kyy = (
a
* h0
* 4
* (
(np.pi**2) * (1 + 2 * fluid_flow_object.eccentricity_ratio**2)
+ (
(32 * fluid_flow_object.eccentricity_ratio**2)
* (1 + fluid_flow_object.eccentricity_ratio**2)
)
/ (1 - fluid_flow_object.eccentricity_ratio**2)
)
)
return [kxx, kxy, kyx, kyy]
def calculate_short_damping_matrix(fluid_flow_object):
"""This function calculates the damping matrix for the short bearing.
Parameters
-------
fluid_flow_object: A FluidFlow object.
Returns
-------
list of floats
A list of length four including damping floats in this order: cxx, cxy, cyx, cyy
Examples
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example
>>> my_fluid_flow = fluid_flow_example()
>>> calculate_short_damping_matrix(my_fluid_flow) # doctest: +ELLIPSIS
[...
"""
# fmt: off
h0 = 1.0 / (((np.pi ** 2) * (1 - fluid_flow_object.eccentricity_ratio ** 2)
+ 16 * fluid_flow_object.eccentricity_ratio ** 2) ** 1.5)
a = fluid_flow_object.load / (fluid_flow_object.radial_clearance * fluid_flow_object.omega)
cxx = (a * h0 * 2 * np.pi * np.sqrt(1 - fluid_flow_object.eccentricity_ratio ** 2) *
((np.pi ** 2) * (1 + 2 * fluid_flow_object.eccentricity_ratio ** 2)
- 16 * fluid_flow_object.eccentricity_ratio ** 2) / fluid_flow_object.eccentricity_ratio)
cxy = (-a * h0 * 8 * ((np.pi ** 2) * (1 + 2 * fluid_flow_object.eccentricity_ratio ** 2)
- 16 * fluid_flow_object.eccentricity_ratio ** 2))
cyx = cxy
cyy = (a * h0 * (2 * np.pi * (
(np.pi ** 2) * (1 - fluid_flow_object.eccentricity_ratio ** 2) ** 2
+ 48 * fluid_flow_object.eccentricity_ratio ** 2)) /
(fluid_flow_object.eccentricity_ratio * np.sqrt(1 - fluid_flow_object.eccentricity_ratio ** 2)))
# fmt: on
return [cxx, cxy, cyx, cyy]
def find_equilibrium_position(fluid_flow_object, print_equilibrium_position=False):
"""This function finds the equilibrium position of the rotor such that the fluid flow
forces match the applied load.
Parameters
----------
fluid_flow_object: A FluidFlow object.
print_equilibrium_position: bool, optional
If True, prints the equilibrium position.
Returns
-------
None
--------
>>> from ross.fluid_flow.fluid_flow import fluid_flow_example2
>>> my_fluid_flow = fluid_flow_example2()
>>> find_equilibrium_position(my_fluid_flow)
>>> (my_fluid_flow.xi, my_fluid_flow.yi) # doctest: +ELLIPSIS
(2.24...
"""
def residuals(x, *args):
"""Calculates x component of the forces of the oil film and the
difference between the y component and the load.
Parameters
----------
x: array
Rotor center coordinates
*args : dict
Dictionary instantiating the ross.FluidFlow class.
Returns
-------
array
Array with the x component of the forces of the oil film and the difference
between the y component and the load.
"""
bearing = args[0]
move_rotor_center_abs(
bearing,
x[0] * fluid_flow_object.radial_clearance,
x[1] * fluid_flow_object.radial_clearance,
)
bearing.geometry_description()
bearing.calculate_pressure_matrix_numerical()
(_, _, fx, fy) = calculate_oil_film_force(bearing, force_type="numerical")
return np.array([fx, (fy - bearing.load)])
if fluid_flow_object.load is None:
sys.exit("Load must be given to calculate the equilibrium position.")
x0 = np.array(
[
0 * fluid_flow_object.radial_clearance,
-1e-3 * fluid_flow_object.radial_clearance,
]
)
move_rotor_center_abs(fluid_flow_object, x0[0], x0[1])
fluid_flow_object.geometry_description()
fluid_flow_object.calculate_pressure_matrix_numerical()
(_, _, fx, fy) = calculate_oil_film_force(fluid_flow_object, force_type="numerical")
result = least_squares(
residuals, x0, args=[fluid_flow_object], jac="3-point", bounds=([0, -1], [1, 0])
)
move_rotor_center_abs(
fluid_flow_object,
result.x[0] * fluid_flow_object.radial_clearance,
result.x[1] * fluid_flow_object.radial_clearance,
)
fluid_flow_object.geometry_description()
if print_equilibrium_position is True:
print(
"The equilibrium position (x0, y0) is: (",
result.x[0] * fluid_flow_object.radial_clearance,
",",
result.x[1] * fluid_flow_object.radial_clearance,
")",
) | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/fluid_flow/fluid_flow_coefficients.py | 0.795817 | 0.581392 | fluid_flow_coefficients.py | pypi |
from abc import ABC, abstractmethod
import numpy as np
import plotly.graph_objects as go
import scipy as sp
from ross.results import TimeResponseResults
from ross.units import Q_
__all__ = ["Defect"]
class Defect(ABC):
def __init__(self):
pass
@abstractmethod
def run(self):
pass
def run_time_response(self):
results = TimeResponseResults(
rotor=self.rotor,
t=self.time_vector,
yout=self.response.T,
xout=[],
)
return results
def plot_dfft(self, probe, probe_units="rad", range_freq=None, fig=None, **kwargs):
"""Plot response in frequency domain (dFFT - discrete Fourier Transform) using Plotly.
Parameters
----------
probe : list of tuples
List with tuples (node, orientation angle, tag).
node : int
indicate the node where the probe is located.
orientation : float
probe orientation angle about the shaft. The 0 refers to +X direction.
tag : str, optional
probe tag to be displayed at the legend.
probe_units : str, option
Units for probe orientation.
Default is "rad".
range_freq : list, optional
Units for the x axis.
Default is "Hz"
fig : Plotly graph_objects.Figure()
The figure object with the plot.
kwargs : optional
Additional key word arguments can be passed to change the plot layout only
(e.g. width=1000, height=800, ...).
*See Plotly Python Figure Reference for more information.
Returns
-------
fig : Plotly graph_objects.Figure()
The figure object with the plot.
"""
if fig is None:
fig = go.Figure()
for i, p in enumerate(probe):
dofx = p[0] * self.rotor.number_dof
dofy = p[0] * self.rotor.number_dof + 1
angle = Q_(p[1], probe_units).to("rad").m
# fmt: off
operator = np.array(
[[np.cos(angle), - np.sin(angle)],
[np.cos(angle), + np.sin(angle)]]
)
row, cols = self.response.shape
_probe_resp = operator @ np.vstack((self.response[dofx,int(2*cols/3):], self.response[dofy,int(2*cols/3):]))
probe_resp = (
_probe_resp[0] * np.cos(angle) ** 2 +
_probe_resp[1] * np.sin(angle) ** 2
)
# fmt: on
amp, freq = self._dfft(probe_resp, self.dt)
if range_freq is not None:
amp = amp[(freq >= range_freq[0]) & (freq <= range_freq[1])]
freq = freq[(freq >= range_freq[0]) & (freq <= range_freq[1])]
fig.add_trace(
go.Scatter(
x=freq,
y=amp,
mode="lines",
name=f"Probe {i + 1} - Node {p[0]}",
legendgroup=f"Probe {i + 1} - Node {p[0]}",
showlegend=True,
hovertemplate=f"Frequency (Hz): %{{x:.2f}}<br>Amplitude (m): %{{y:.2e}}",
)
)
fig.update_xaxes(title_text=f"Frequency (Hz)")
fig.update_yaxes(title_text=f"Amplitude (m)")
fig.update_layout(**kwargs)
return fig
def _dfft(self, x, dt):
"""Calculate dFFT - discrete Fourier Transform.
Parameters
----------
x : np.array
Magnitude of the response in time domain.
Default is "m".
dt : int
Time step.
Default is "s".
Returns
-------
x_amp : np.array
Amplitude of the response in frequency domain.
Default is "m".
freq : np.array
Frequency range.
Default is "Hz".
"""
b = np.floor(len(x) / 2)
c = len(x)
df = 1 / (c * dt)
x_amp = sp.fft.fft(x)[: int(b)]
x_amp = x_amp * 2 / c
x_phase = np.angle(x_amp)
x_amp = np.abs(x_amp)
freq = np.arange(0, df * b, df)
freq = freq[: int(b)] # Frequency vector
return x_amp, freq | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/defects/abs_defect.py | 0.934328 | 0.533519 | abs_defect.py | pypi |
import time
from pathlib import Path
import numpy as np
import pandas as pd
import scipy.integrate
import scipy.linalg
import ross
from ross.units import Q_, check_units
from .abs_defect import Defect
from .integrate_solver import Integrator
__all__ = [
"Crack",
]
class Crack(Defect):
"""Contains a :cite:`gasch1993survey` and :cite:`mayes1984analysis` transversal crack models for applications on
finite element models of rotative machinery.
The reference coordenates system is: z-axis throught the shaft center; x-axis and y-axis in the sensors' planes
Calculates the dynamic forces of a crack on a given shaft element.
Parameters
----------
dt : float
Time step
tI : float
Initial time
tF : float
Final time
depth_ratio : float
Crack depth ratio related to the diameter of the crack container element. A depth value of 0.1 is equal to 10%,
0.2 equal to 20%, and so on.
n_crack : float
Element where the crack is located
speed : float, pint.Quantity
Operational speed of the machine. Default unit is rad/s.
unbalance_magnitude : array
Array with the unbalance magnitude. The unit is kg.m.
unbalance_phase : array
Array with the unbalance phase. The unit is rad.
crack_type : string
String containing type of crack model chosed. The avaible types are: Mayes and Gasch.
print_progress : bool
Set it True, to print the time iterations and the total time spent, by default False.
Returns
-------
A force to be applied on the shaft.
References
----------
.. bibliography::
:filter: docname in docnames
Examples
--------
>>> from ross.defects.crack import crack_example
>>> probe1 = (14, 0)
>>> probe2 = (22, 0)
>>> response = crack_example()
>>> results = response.run_time_response()
>>> fig = response.plot_dfft(probe=[probe1, probe2], range_freq=[0, 100], yaxis_type="log")
>>> # fig.show()
"""
@check_units
def __init__(
self,
dt,
tI,
tF,
depth_ratio,
n_crack,
speed,
unbalance_magnitude,
unbalance_phase,
crack_type="Mayes",
print_progress=False,
):
self.dt = dt
self.tI = tI
self.tF = tF
self.depth_ratio = depth_ratio
self.n_crack = n_crack
self.speed = speed
self.speedI = speed
self.speedF = speed
self.unbalance_magnitude = unbalance_magnitude
self.unbalance_phase = unbalance_phase
self.print_progress = print_progress
if crack_type is None or crack_type == "Mayes":
self.crack_model = self._mayes
elif crack_type == "Gasch":
self.crack_model = self._gasch
else:
raise Exception("Check the crack model!")
if len(self.unbalance_magnitude) != len(self.unbalance_phase):
raise Exception(
"The unbalance magnitude vector and phase must have the same size!"
)
dir_path = Path(__file__).parents[2] / "tools/data/PAPADOPOULOS.csv"
self.data_coefs = pd.read_csv(dir_path)
def run(self, rotor):
"""Calculates the shaft angular position and the unbalance forces at X / Y directions.
Parameters
----------
rotor : ross.Rotor Object
6 DoF rotor model.
"""
self.rotor = rotor
self.n_disk = len(self.rotor.disk_elements)
if self.n_disk != len(self.unbalance_magnitude):
raise Exception("The number of discs and unbalances must agree!")
self.ndof = rotor.ndof
self.L = rotor.elements[self.n_crack].L
self.KK = rotor.elements[self.n_crack].K()
self.radius = rotor.elements[self.n_crack].odl / 2
self.Poisson = rotor.elements[self.n_crack].material.Poisson
self.E = rotor.elements[self.n_crack].material.E
self.ndofd = np.zeros(len(self.rotor.disk_elements))
for ii in range(self.n_disk):
self.ndofd[ii] = (self.rotor.disk_elements[ii].n) * 6
G_s = rotor.elements[self.n_crack].material.G_s
odr = rotor.elements[self.n_crack].odr
odl = rotor.elements[self.n_crack].odl
idr = rotor.elements[self.n_crack].idr
idl = rotor.elements[self.n_crack].idl
self.dof_crack = np.arange((self.n_crack * 6), (self.n_crack * 6 + 12))
tempS = np.pi * (
((odr / 2) ** 2 + (odl / 2) ** 2) / 2
- ((idr / 2) ** 2 + (idl / 2) ** 2) / 2
)
tempI = (
np.pi
/ 4
* (
((odr / 2) ** 4 + (odl / 2) ** 4) / 2
- ((idr / 2) ** 4 + (idl / 2) ** 4) / 2
)
)
kappa = (6 * (1 + self.Poisson) ** 2) / (
7 + 12 * self.Poisson + 4 * self.Poisson**2
)
A = 12 * self.E * tempI / (G_s * kappa * tempS * (self.L**2))
# fmt = off
Coxy = np.array(
[
[
(self.L**3) * (1 + A / 4) / (3 * self.E * tempI),
-(self.L**2) / (2 * self.E * tempI),
],
[-(self.L**2) / (2 * self.E * tempI), self.L / (self.E * tempI)],
]
)
Coyz = np.array(
[
[
(self.L**3) * (1 + A / 4) / (3 * self.E * tempI),
(self.L**2) / (2 * self.E * tempI),
],
[(self.L**2) / (2 * self.E * tempI), self.L / (self.E * tempI)],
]
)
Co = np.array(
[
[Coxy[0, 0], 0, 0, Coxy[0, 1]],
[0, Coyz[0, 0], Coyz[0, 1], 0],
[0, Coyz[1, 0], Coyz[1, 1], 0],
[Coxy[1, 0], 0, 0, Coxy[1, 1]],
]
)
# fmt = on
c44 = self._get_coefs("c44")
c55 = self._get_coefs("c55")
c45 = self._get_coefs("c45")
if self.depth_ratio == 0:
Cc = Co
else:
Cc = Co + np.array(
[[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, c55, c45], [0, 0, c45, c44]]
)
self.Kele = np.linalg.pinv(Co)
self.ko = self.Kele[0, 0]
self.kc = np.linalg.pinv(Cc)
self.kcx = self.kc[0, 0]
self.kcz = self.kc[1, 1]
self.fcrack = np.zeros(self.ndof)
self.iteration = 0
# parameters for the time integration
self.lambdat = 0.00001
Faxial = 0
TorqueI = 0
TorqueF = 0
# pre-processing of auxilary variuables for the time integration
self.sA = (
self.speedI * np.exp(-self.lambdat * self.tF)
- self.speedF * np.exp(-self.lambdat * self.tI)
) / (np.exp(-self.lambdat * self.tF) - np.exp(-self.lambdat * self.tI))
self.sB = (self.speedF - self.speedI) / (
np.exp(-self.lambdat * self.tF) - np.exp(-self.lambdat * self.tI)
)
# sAT = (
# TorqueI * np.exp(-lambdat * self.tF) - TorqueF * np.exp(-lambdat * self.tI)
# ) / (np.exp(-lambdat * self.tF) - np.exp(-lambdat * self.tI))
# sBT = (TorqueF - TorqueI) / (
# np.exp(-lambdat * self.tF) - np.exp(-lambdat * self.tI)
# )
# SpeedV = sA + sB * np.exp(-lambdat * self.t)
# TorqueV = sAT + sBT * np.exp(-lambdat * self.t)
# AccelV = -lambdat * sB * np.exp(-lambdat * self.t)
# Determining the modal matrix
self.K = self.rotor.K(self.speed)
self.C = self.rotor.C(self.speed)
self.G = self.rotor.G()
self.M = self.rotor.M(self.speed)
self.Kst = self.rotor.Kst()
_, ModMat = scipy.linalg.eigh(
self.K,
self.M,
type=1,
turbo=False,
)
ModMat = ModMat[:, :12]
self.ModMat = ModMat
# Modal transformations
self.Mmodal = ((ModMat.T).dot(self.M)).dot(ModMat)
self.Cmodal = ((ModMat.T).dot(self.C)).dot(ModMat)
self.Gmodal = ((ModMat.T).dot(self.G)).dot(ModMat)
self.Kmodal = ((ModMat.T).dot(self.K)).dot(ModMat)
self.Kstmodal = ((ModMat.T).dot(self.Kst)).dot(ModMat)
y0 = np.zeros(24)
t_eval = np.arange(self.tI, self.tF + self.dt, self.dt)
# t_eval = np.arange(self.dt, self.tF, self.dt)
T = t_eval
self.angular_position = (
self.sA * T
- (self.sB / self.lambdat) * np.exp(-self.lambdat * T)
+ (self.sB / self.lambdat)
)
self.Omega = self.sA + self.sB * np.exp(-self.lambdat * T)
self.AccelV = -self.lambdat * self.sB * np.exp(-self.lambdat * T)
self.tetaUNB = np.zeros((len(self.unbalance_phase), len(self.angular_position)))
unbx = np.zeros(len(self.angular_position))
unby = np.zeros(len(self.angular_position))
FFunb = np.zeros((self.ndof, len(t_eval)))
self.forces_crack = np.zeros((self.ndof, len(t_eval)))
for ii in range(self.n_disk):
self.tetaUNB[ii, :] = (
self.angular_position + self.unbalance_phase[ii] + np.pi / 2
)
unbx = self.unbalance_magnitude[ii] * (self.AccelV) * (
np.cos(self.tetaUNB[ii, :])
) - self.unbalance_magnitude[ii] * ((self.Omega**2)) * (
np.sin(self.tetaUNB[ii, :])
)
unby = -self.unbalance_magnitude[ii] * (self.AccelV) * (
np.sin(self.tetaUNB[ii, :])
) - self.unbalance_magnitude[ii] * (self.Omega**2) * (
np.cos(self.tetaUNB[ii, :])
)
FFunb[int(self.ndofd[ii]), :] += unbx
FFunb[int(self.ndofd[ii] + 1), :] += unby
self.Funbmodal = (self.ModMat.T).dot(FFunb)
self.inv_Mmodal = np.linalg.pinv(self.Mmodal)
t1 = time.time()
x = Integrator(
self.tI,
y0,
self.tF,
self.dt,
self._equation_of_movement,
self.print_progress,
)
x = x.rk45()
t2 = time.time()
if self.print_progress:
print(f"Time spent: {t2-t1} s")
self.displacement = x[:12, :]
self.velocity = x[12:, :]
self.time_vector = t_eval
self.response = self.ModMat.dot(self.displacement)
def _equation_of_movement(self, T, Y, i):
"""Calculates the displacement and velocity using state-space representation in the modal domain.
Parameters
----------
T : float
Iteration time.
Y : array
Array of displacement and velocity, in the modal domain.
i : int
Iteration step.
Returns
-------
new_Y : array
Array of the new displacement and velocity, in the modal domain.
"""
positions = Y[:12]
velocity = Y[12:] # velocity in space state
self.positionsFis = self.ModMat.dot(positions)
self.velocityFis = self.ModMat.dot(velocity)
self.T_matrix = np.array(
[
[np.cos(self.angular_position[i]), np.sin(self.angular_position[i])],
[-np.sin(self.angular_position[i]), np.cos(self.angular_position[i])],
]
)
self.tp = self.crack_model(self.angular_position[i])
FF_CRACK, ft = self._crack(self.tp, self.angular_position[i])
self.forces_crack[:, i] = ft
ftmodal = (self.ModMat.T).dot(ft)
# equation of movement to be integrated in time
new_V_dot = (
ftmodal
+ self.Funbmodal[:, i]
- ((self.Cmodal + self.Gmodal * self.Omega[i])).dot(velocity)
- ((self.Kmodal + self.Kstmodal * self.AccelV[i]).dot(positions))
).dot(self.inv_Mmodal)
new_X_dot = velocity
new_Y = np.zeros(24)
new_Y[:12] = new_X_dot
new_Y[12:] = new_V_dot
return new_Y
def _crack(self, func, ap):
"""Reaction forces of cracked element
Returns
-------
F_CRACK : array
Excitation force caused by the parallel misalignment on the node of application.
FF_CRACK : array
Excitation force caused by the parallel misalignment on the entire system.
"""
K = func
k11 = K[0, 0]
k12 = K[0, 1]
k22 = K[1, 1]
# Stiffness matrix of the cracked element
Toxy = np.array([[-1, 0], [self.L, -1], [1, 0], [0, 1]]) # OXY
kxy = np.array(
[[self.Kele[0, 0], self.Kele[0, 3]], [self.Kele[3, 0], self.Kele[3, 3]]]
)
kxy[0, 0] = k11
Koxy = ((Toxy).dot(kxy)).dot(Toxy.T)
Toyz = np.array([[-1, 0], [-self.L, -1], [1, 0], [0, 1]]) # OYZ
kyz = np.array(
[[self.Kele[1, 1], self.Kele[1, 2]], [self.Kele[2, 1], self.Kele[2, 2]]]
)
kyz[0, 0] = k22
Koyz = ((Toyz).dot(kyz)).dot(Toyz.T)
# fmt: off
KK_crack = np.array([[Koxy[0,0] ,0 ,0 ,0 ,Koxy[0,1] ,0 ,Koxy[0,2] ,0 ,0 ,0 ,Koxy[0,3] ,0],
[0 ,Koyz[0,0] ,0 ,Koyz[0,1] ,0 ,0 ,0 ,Koyz[0,2] ,0 ,Koyz[0,3] ,0 ,0],
[0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0],
[0 ,Koyz[1,0] ,0 ,Koyz[1,1] ,0 ,0 ,0 ,Koyz[1,2] ,0 ,Koyz[1,3] ,0 ,0],
[Koxy[1,0] ,0 ,0 ,0 ,Koxy[1,1] ,0 ,Koxy[1,2] ,0 ,0 ,0 ,Koxy[1,3] ,0],
[0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0],
[Koxy[2,0] ,0 ,0 ,0 ,Koxy[2,1] ,0 ,Koxy[2,2] ,0 ,0 ,0 ,Koxy[2,3] ,0],
[0 ,Koyz[2,0] ,0 ,Koyz[2,1] ,0 , 0 ,0 ,Koyz[2,2] ,0 ,Koyz[2,3] ,0 ,0],
[0 ,0 ,0 ,0 ,0 , 0 ,0 ,0 ,0 ,0 ,0 ,0],
[0 ,Koyz[3,0] ,0 ,Koyz[3,1] ,0 , 0 ,0 ,Koyz[3,2] ,0 ,Koyz[3,3] ,0 ,0],
[Koxy[3,0] ,0 ,0 , 0 ,Koxy[3,1] ,0 ,Koxy[3,2] ,0 ,0 ,0 ,Koxy[3,3] ,0],
[0 ,0 ,0 , 0 ,0 ,0 ,0 ,0 ,0 ,0 ,0 ,0]])
# fmt: on
F_CRACK = np.zeros(self.ndof)
KK_CRACK = self.KK - KK_crack
FF_CRACK = (KK_CRACK).dot(self.positionsFis[self.dof_crack])
F_CRACK[self.dof_crack] = FF_CRACK
self.KK_CRACK = KK_CRACK
return FF_CRACK, F_CRACK
def _gasch(self, ap):
"""Stiffness matrix of the cracked element according to the Gasch model.
Paramenters
-----------
ap : float
Angular position of the shaft.
Returns
-------
K : np.ndarray
Stiffness matrix of cracked element.
"""
# Gasch
kme = (self.ko + self.kcx) / 2
kmn = (self.ko + self.kcz) / 2
kde = (self.ko - self.kcx) / 2
kdn = (self.ko - self.kcz) / 2
size = 18
cosine_sum = np.sum(
[(-1) ** i * np.cos((2 * i + 1) * ap) / (2 * i + 1) for i in range(size)]
)
kee = kme + (4 / np.pi) * kde * cosine_sum
knn = kmn + (4 / np.pi) * kdn * cosine_sum
aux = np.array([[kee, 0], [0, knn]])
K = ((self.T_matrix.T).dot(aux)).dot(self.T_matrix)
return K
def _mayes(self, ap):
"""Stiffness matrix of the cracked element according to the Mayes model.
Paramenters
-----------
ap : float
Angular position of the shaft.
Returns
-------
K : np.ndarray
Stiffness matrix of cracked element.
"""
# Mayes
kee = 0.5 * (self.ko + self.kcx) + 0.5 * (self.ko - self.kcx) * np.cos(ap)
knn = 0.5 * (self.ko + self.kcz) + 0.5 * (self.ko - self.kcz) * np.cos(ap)
aux = np.array([[kee, 0], [0, knn]])
K = ((self.T_matrix.T).dot(aux)).dot(self.T_matrix)
return K
def _get_coefs(self, coef):
"""Terms os the compliance matrix.
Paramenters
-----------
coef : string
Name of the Coefficient according to the corresponding direction.
Returns
-------
c : np.ndarray
Compliance coefficient according to the crack depth.
"""
c = np.array(pd.eval(self.data_coefs[coef]))
aux = np.where(c[:, 1] >= self.depth_ratio * 2)[0]
c = c[aux[0], 0] * (1 - self.Poisson**2) / (self.E * (self.radius**3))
return c
def base_rotor_example():
"""Internal routine that create an example of a rotor, to be used in
the associated crack problems as a prerequisite.
This function returns an instance of a 6 DoF rotor, with a number of
components attached. As this is not the focus of the example here, but
only a requisite, see the example in "rotor assembly" for additional
information on the rotor object.
Returns
-------
rotor : ross.Rotor Object
An instance of a flexible 6 DoF rotor object.
Examples
--------
>>> rotor = base_rotor_example()
>>> rotor.Ip
0.015118294226367068
"""
steel2 = ross.Material(name="Steel", rho=7850, E=2.17e11, G_s=81.2e9)
# Rotor with 6 DoFs, with internal damping, with 10 shaft elements, 2 disks and 2 bearings.
i_d = 0
o_d = 0.019
n = 33
# fmt: off
L = np.array(
[0 , 25, 64, 104, 124, 143, 175, 207, 239, 271,
303, 335, 345, 355, 380, 408, 436, 466, 496, 526,
556, 586, 614, 647, 657, 667, 702, 737, 772, 807,
842, 862, 881, 914]
)/ 1000
# fmt: on
L = [L[i] - L[i - 1] for i in range(1, len(L))]
shaft_elem = [
ross.ShaftElement6DoF(
material=steel2,
L=l,
idl=i_d,
odl=o_d,
idr=i_d,
odr=o_d,
alpha=8.0501,
beta=1.0e-5,
rotary_inertia=True,
shear_effects=True,
)
for l in L
]
Id = 0.003844540885417
Ip = 0.007513248437500
disk0 = ross.DiskElement6DoF(n=12, m=2.6375, Id=Id, Ip=Ip)
disk1 = ross.DiskElement6DoF(n=24, m=2.6375, Id=Id, Ip=Ip)
kxx1 = 4.40e5
kyy1 = 4.6114e5
kzz = 0
cxx1 = 27.4
cyy1 = 2.505
czz = 0
kxx2 = 9.50e5
kyy2 = 1.09e8
cxx2 = 50.4
cyy2 = 100.4553
bearing0 = ross.BearingElement6DoF(
n=4, kxx=kxx1, kyy=kyy1, cxx=cxx1, cyy=cyy1, kzz=kzz, czz=czz
)
bearing1 = ross.BearingElement6DoF(
n=31, kxx=kxx2, kyy=kyy2, cxx=cxx2, cyy=cyy2, kzz=kzz, czz=czz
)
rotor = ross.Rotor(shaft_elem, [disk0, disk1], [bearing0, bearing1])
return rotor
def crack_example():
"""Create an example to evaluate the influence of transverse cracks in a rotating shaft.
This function returns an instance of a transversal crack
defect. The purpose is to make available a simple model so that a
doctest can be written using it.
Returns
-------
crack : ross.Crack Object
An instance of a crack model object.
Examples
--------
>>> crack = crack_example()
>>> crack.speed
125.66370614359172
"""
rotor = base_rotor_example()
crack = rotor.run_crack(
dt=0.0001,
tI=0,
tF=0.5,
depth_ratio=0.2,
n_crack=18,
speed=Q_(1200, "RPM"),
unbalance_magnitude=np.array([5e-4, 0]),
unbalance_phase=np.array([-np.pi / 2, 0]),
crack_type="Mayes",
print_progress=False,
)
return crack | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/defects/crack.py | 0.852767 | 0.592431 | crack.py | pypi |
import numpy as np
class Integrator:
"""A series of Runge-Kutta time integration algorithms.
Calculates the time response for the rotors input to the routine.
Parameters
----------
x0 : float
Initial time
y0 : float
Initial condition for the integration
x : float
Iteration time
h : float
Step height
func : object
Function to be integrated in time
Returns
-------
The rotor transient response.
References
----------
.. [1] BUTCHER, John Charles; GOODWIN, Nicolette. Numerical methods for ordinary differential equations. New York: Wiley, 2008. ..
.. [2] CASH, Jeff R.; KARP, Alan H. A variable order Runge-Kutta method for initial value problems with rapidly varying right-hand sides.
ACM Transactions on Mathematical Software (TOMS), v. 16, n. 3, p. 201-222, 1990. ..
"""
def __init__(self, x0, y0, x, h, func, print_progress=False):
self.x0 = x0
self.y0 = y0
self.x = x
self.h = h
self.func = func
self.print_progress = print_progress
def rk4(self):
# Runge-Kutta 4th order (RK4)
# Count number of iterations using step size or
# step height h
n = int((self.x - self.x0) / self.h)
# Iterate for number of iterations
y = self.y0
result = np.zeros((24, n + 1))
result[:, 0] = self.y0
# 4th-order Runge-Kutta
for i in range(1, n + 1):
if i % 10000 == 0 and self.print_progress:
print(f"Iteration: {i} \n Time: {self.x0}")
"Apply Runge Kutta Formulas to find next value of y"
k1 = self.h * self.func(self.x0, y, i)
k2 = self.h * self.func(self.x0 + 0.5 * self.h, y + 0.5 * k1, i)
k3 = self.h * self.func(self.x0 + 0.5 * self.h, y + 0.5 * k2, i)
k4 = self.h * self.func(self.x0 + self.h, y + k3, i)
# Update next value of y
y = y + (1.0 / 6.0) * (k1 + 2 * k2 + 2 * k3 + k4)
result[:, i] = np.copy(y)
# Update next value of x
self.x0 = self.x0 + self.h
return result
def rk45(self):
# Runge-Kutta Cash-Karp (CK45)
# Count number of iterations using step size or
# step height h
n = int((self.x - self.x0) / self.h)
# Iterate for number of iterations
y = self.y0
result = np.zeros((24, n + 1))
result[:, 0] = self.y0
for i in range(1, n + 1):
if i % 10000 == 0 and self.print_progress:
print(f"Iteration: {i} \n Time: {self.x0}")
"Apply Runge Kutta Formulas to find next value of y"
k1 = 1 * self.func(self.x0, y, i)
yp2 = y + k1 * (self.h / 5)
k2 = 1 * self.func(self.x0 + (self.h / 5), yp2, i)
yp3 = y + k1 * (3 * self.h / 40) + k2 * (9 * self.h / 40)
k3 = 1 * self.func(self.x0 + (3 * self.h / 10), yp3, i)
yp4 = (
y
+ k1 * (3 * self.h / 10)
- k2 * (9 * self.h / 10)
+ k3 * (6 * self.h / 5)
)
k4 = 1 * self.func(self.x0 + (3 * self.h / 5), yp4, i)
yp5 = (
y
- k1 * (11 * self.h / 54)
+ k2 * (5 * self.h / 2)
- k3 * (70 * self.h / 27)
+ k4 * (35 * self.h / 27)
)
k5 = 1 * self.func(self.x0 + self.h, yp5, i)
yp6 = (
y
+ k1 * (1631 * self.h / 55296)
+ k2 * (175 * self.h / 512)
+ k3 * (575 * self.h / 13824)
+ k4 * (44275 * self.h / 110592)
+ k5 * (253 * self.h / 4096)
)
k6 = 1 * self.func(self.x0 + (7 * self.h / 8), yp6, i)
# Update next value of y
y = y + self.h * (
37 * k1 / 378 + 250 * k3 / 621 + 125 * k4 / 594 + 512 * k6 / 1771
)
result[:, i] = np.copy(y)
# Update next value of x
self.x0 = self.x0 + self.h
return result | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/defects/integrate_solver.py | 0.927248 | 0.695629 | integrate_solver.py | pypi |
import time
import numpy as np
import scipy.integrate
import scipy.linalg
import ross
from ross.units import Q_, check_units
from .abs_defect import Defect
from .integrate_solver import Integrator
__all__ = [
"Rubbing",
]
class Rubbing(Defect):
"""Contains a rubbing model for applications on finite element models of rotative machinery.
The reference coordenates system is: z-axis throught the shaft center; x-axis and y-axis in the sensors' planes
Parameters
----------
dt : float
Time step.
tI : float
Initial time.
tF : float
Final time.
deltaRUB : float
Distance between the housing and shaft surface.
kRUB : float
Contact stiffness.
cRUB : float
Contact damping.
miRUB : float
Friction coefficient.
posRUB : int
Node where the rubbing is ocurring.
speed : float, pint.Quantity
Operational speed of the machine. Default unit is rad/s.
unbalance_magnitude : array
Array with the unbalance magnitude. The unit is kg.m.
unbalance_phase : array
Array with the unbalance phase. The unit is rad.
torque : bool
Set it as True to consider the torque provided by the rubbing, by default False.
print_progress : bool
Set it True, to print the time iterations and the total time spent, by default False.
Returns
-------
A force to be applied on the shaft.
References
----------
.. [1] Yamamoto, T., Ishida, Y., &Kirk, R.(2002). Linear and Nonlinear Rotordynamics: A Modern Treatment with Applications, pp. 215-222 ..
Examples
--------
>>> from ross.defects.rubbing import rubbing_example
>>> probe1 = (14, 0)
>>> probe2 = (22, 0)
>>> response = rubbing_example()
>>> results = response.run_time_response()
>>> fig = response.plot_dfft(probe=[probe1, probe2], range_freq=[0, 100], yaxis_type="log")
>>> # fig.show()
"""
@check_units
def __init__(
self,
dt,
tI,
tF,
deltaRUB,
kRUB,
cRUB,
miRUB,
posRUB,
speed,
unbalance_magnitude,
unbalance_phase,
torque=False,
print_progress=False,
):
self.dt = dt
self.tI = tI
self.tF = tF
self.deltaRUB = deltaRUB
self.kRUB = kRUB
self.cRUB = cRUB
self.miRUB = miRUB
self.posRUB = posRUB
self.speed = speed
self.speedI = speed
self.speedF = speed
self.DoF = np.arange((self.posRUB * 6), (self.posRUB * 6 + 6))
self.torque = torque
self.unbalance_magnitude = unbalance_magnitude
self.unbalance_phase = unbalance_phase
self.print_progress = print_progress
if len(self.unbalance_magnitude) != len(self.unbalance_phase):
raise Exception(
"The unbalance magnitude vector and phase must have the same size!"
)
def run(self, rotor):
"""Calculates the shaft angular position and the unbalance forces at X / Y directions.
Parameters
----------
rotor : ross.Rotor Object
6 DoF rotor model.
"""
self.rotor = rotor
self.n_disk = len(self.rotor.disk_elements)
if self.n_disk != len(self.unbalance_magnitude):
raise Exception("The number of discs and unbalances must agree!")
self.ndof = rotor.ndof
self.iteration = 0
self.radius = rotor.df_shaft.iloc[self.posRUB].o_d / 2
self.ndofd = np.zeros(len(self.rotor.disk_elements))
for ii in range(self.n_disk):
self.ndofd[ii] = (self.rotor.disk_elements[ii].n) * 6
self.lambdat = 0.00001
# Faxial = 0
# TorqueI = 0
# TorqueF = 0
self.sA = (
self.speedI * np.exp(-self.lambdat * self.tF)
- self.speedF * np.exp(-self.lambdat * self.tI)
) / (np.exp(-self.lambdat * self.tF) - np.exp(-self.lambdat * self.tI))
self.sB = (self.speedF - self.speedI) / (
np.exp(-self.lambdat * self.tF) - np.exp(-self.lambdat * self.tI)
)
# sAT = (
# TorqueI * np.exp(-lambdat * self.tF) - TorqueF * np.exp(-lambdat * self.tI)
# ) / (np.exp(-lambdat * self.tF) - np.exp(-lambdat * self.tI))
# sBT = (TorqueF - TorqueI) / (
# np.exp(-lambdat * self.tF) - np.exp(-lambdat * self.tI)
# )
# self.SpeedV = sA + sB * np.exp(-lambdat * t)
# self.TorqueV = sAT + sBT * np.exp(-lambdat * t)
# self.AccelV = -lambdat * sB * np.exp(-lambdat * t)
# Determining the modal matrix
self.K = self.rotor.K(self.speed)
self.C = self.rotor.C(self.speed)
self.G = self.rotor.G()
self.M = self.rotor.M(self.speed)
self.Kst = self.rotor.Kst()
V1, ModMat = scipy.linalg.eigh(
self.K,
self.M,
type=1,
turbo=False,
)
ModMat = ModMat[:, :12]
self.ModMat = ModMat
# Modal transformations
self.Mmodal = ((ModMat.T).dot(self.M)).dot(ModMat)
self.Cmodal = ((ModMat.T).dot(self.C)).dot(ModMat)
self.Gmodal = ((ModMat.T).dot(self.G)).dot(ModMat)
self.Kmodal = ((ModMat.T).dot(self.K)).dot(ModMat)
self.Kstmodal = ((ModMat.T).dot(self.Kst)).dot(ModMat)
y0 = np.zeros(24)
t_eval = np.arange(self.tI, self.tF + self.dt, self.dt)
# t_eval = np.arange(self.tI, self.tF, self.dt)
T = t_eval
self.angular_position = (
self.sA * T
- (self.sB / self.lambdat) * np.exp(-self.lambdat * T)
+ (self.sB / self.lambdat)
)
self.Omega = self.sA + self.sB * np.exp(-self.lambdat * T)
self.AccelV = -self.lambdat * self.sB * np.exp(-self.lambdat * T)
self.tetaUNB = np.zeros((len(self.unbalance_phase), len(self.angular_position)))
unbx = np.zeros(len(self.angular_position))
unby = np.zeros(len(self.angular_position))
FFunb = np.zeros((self.ndof, len(t_eval)))
self.forces_rub = np.zeros((self.ndof, len(t_eval)))
for ii in range(self.n_disk):
self.tetaUNB[ii, :] = (
self.angular_position + self.unbalance_phase[ii] + np.pi / 2
)
unbx = self.unbalance_magnitude[ii] * (self.AccelV) * (
np.cos(self.tetaUNB[ii, :])
) - self.unbalance_magnitude[ii] * ((self.Omega**2)) * (
np.sin(self.tetaUNB[ii, :])
)
unby = -self.unbalance_magnitude[ii] * (self.AccelV) * (
np.sin(self.tetaUNB[ii, :])
) - self.unbalance_magnitude[ii] * (self.Omega**2) * (
np.cos(self.tetaUNB[ii, :])
)
FFunb[int(self.ndofd[ii]), :] += unbx
FFunb[int(self.ndofd[ii] + 1), :] += unby
self.Funbmodal = (self.ModMat.T).dot(FFunb)
self.inv_Mmodal = np.linalg.pinv(self.Mmodal)
t1 = time.time()
x = Integrator(
self.tI,
y0,
self.tF,
self.dt,
self._equation_of_movement,
self.print_progress,
)
x = x.rk4()
t2 = time.time()
if self.print_progress:
print(f"Time spent: {t2-t1} s")
self.displacement = x[:12, :]
self.velocity = x[12:, :]
self.time_vector = t_eval
self.response = self.ModMat.dot(self.displacement)
def _equation_of_movement(self, T, Y, i):
"""Calculates the displacement and velocity using state-space representation in the modal domain.
Parameters
----------
T : float
Iteration time.
Y : array
Array of displacement and velocity, in the modal domain.
i : int
Iteration step.
Returns
-------
new_Y : array
Array of the new displacement and velocity, in the modal domain.
"""
positions = Y[:12]
velocity = Y[12:] # velocity in space state
positionsFis = self.ModMat.dot(positions)
velocityFis = self.ModMat.dot(velocity)
Frub, ft = self._rub(positionsFis, velocityFis, self.Omega[i])
self.forces_rub[:, i] = ft
ftmodal = (self.ModMat.T).dot(ft)
# proper equation of movement to be integrated in time
new_V_dot = (
ftmodal
+ self.Funbmodal[:, i]
- ((self.Cmodal + self.Gmodal * self.Omega[i])).dot(velocity)
- ((self.Kmodal + self.Kstmodal * self.AccelV[i]).dot(positions))
).dot(self.inv_Mmodal)
new_X_dot = velocity
new_Y = np.zeros(24)
new_Y[:12] = new_X_dot
new_Y[12:] = new_V_dot
return new_Y
def _rub(self, positionsFis, velocityFis, ang):
self.F_k = np.zeros(self.ndof)
self.F_c = np.zeros(self.ndof)
self.F_f = np.zeros(self.ndof)
self.y = np.concatenate((positionsFis, velocityFis))
ii = 0 + 6 * self.posRUB # rubbing position
self.radial_displ_node = np.sqrt(
self.y[ii] ** 2 + self.y[ii + 1] ** 2
) # radial displacement
self.radial_displ_vel_node = np.sqrt(
self.y[ii + self.ndof] ** 2 + self.y[ii + 1 + self.ndof] ** 2
) # velocity
self.phi_angle = np.arctan2(self.y[ii + 1], self.y[ii])
if self.radial_displ_node >= self.deltaRUB:
self.F_k[ii] = self._stiffness_force(self.y[ii])
self.F_k[ii + 1] = self._stiffness_force(self.y[ii + 1])
self.F_c[ii] = self._damping_force(self.y[ii + self.ndof])
self.F_c[ii + 1] = self._damping_force(self.y[ii + 1 + self.ndof])
Vt = -self.y[ii + self.ndof + 1] * np.sin(self.phi_angle) + self.y[
ii + self.ndof
] * np.cos(self.phi_angle)
if Vt + ang * self.radius > 0:
self.F_f[ii] = -self._tangential_force(self.F_k[ii], self.F_c[ii])
self.F_f[ii + 1] = self._tangential_force(
self.F_k[ii + 1], self.F_c[ii + 1]
)
if self.torque:
self.F_f[ii + 5] = self._torque_force(
self.F_f[ii], self.F_f[ii + 1], self.y[ii]
)
elif Vt + ang * self.radius < 0:
self.F_f[ii] = self._tangential_force(self.F_k[ii], self.F_c[ii])
self.F_f[ii + 1] = -self._tangential_force(
self.F_k[ii + 1], self.F_c[ii + 1]
)
if self.torque:
self.F_f[ii + 5] = self._torque_force(
self.F_f[ii], self.F_f[ii + 1], self.y[ii]
)
return self._combine_forces(self.F_k, self.F_c, self.F_f)
def _stiffness_force(self, y):
"""Calculates the stiffness force
Parameters
----------
y : float
Displacement value.
Returns
-------
force : numpy.float64
Force magnitude.
"""
force = (
-self.kRUB
* (self.radial_displ_node - self.deltaRUB)
* y
/ abs(self.radial_displ_node)
)
return force
def _damping_force(self, y):
"""Calculates the damping force
Parameters
----------
y : float
Displacement value.
Returns
-------
force : numpy.float64
Force magnitude.
"""
force = (
-self.cRUB
* (self.radial_displ_vel_node)
* y
/ abs(self.radial_displ_vel_node)
)
return force
def _tangential_force(self, F_k, F_c):
"""Calculates the tangential force
Parameters
----------
y : float
Displacement value.
Returns
-------
force : numpy.float64
Force magnitude.
"""
force = self.miRUB * (abs(F_k + F_c))
return force
def _torque_force(self, F_f, F_fp, y):
"""Calculates the torque force
Parameters
----------
y : float
Displacement value.
Returns
-------
force : numpy.float64
Force magnitude.
"""
force = self.radius * (
np.sqrt(F_f**2 + F_fp**2) * y / abs(self.radial_displ_node)
)
return force
def _combine_forces(self, F_k, F_c, F_f):
"""Mounts the final force vector.
Parameters
----------
F_k : numpy.ndarray
Stiffness force vector.
F_c : numpy.ndarray
Damping force vector.
F_f : numpy.ndarray
Tangential force vector.
Returns
-------
Frub : numpy.ndarray
Final force vector for each degree of freedom.
FFrub : numpy.ndarray
Final force vector.
"""
Frub = F_k[self.DoF] + F_c[self.DoF] + F_f[self.DoF]
FFrub = F_k + F_c + F_f
return Frub, FFrub
@property
def forces(self):
pass
def base_rotor_example():
"""Internal routine that create an example of a rotor, to be used in
the associated misalignment problems as a prerequisite.
This function returns an instance of a 6 DoF rotor, with a number of
components attached. As this is not the focus of the example here, but
only a requisite, see the example in "rotor assembly" for additional
information on the rotor object.
Returns
-------
rotor : ross.Rotor Object
An instance of a flexible 6 DoF rotor object.
Examples
--------
>>> rotor = base_rotor_example()
>>> rotor.Ip
0.015118294226367068
"""
steel2 = ross.Material(
name="Steel", rho=7850, E=2.17e11, Poisson=0.2992610837438423
)
# Rotor with 6 DoFs, with internal damping, with 10 shaft elements, 2 disks and 2 bearings.
i_d = 0
o_d = 0.019
n = 33
# fmt: off
L = np.array(
[0 , 25, 64, 104, 124, 143, 175, 207, 239, 271,
303, 335, 345, 355, 380, 408, 436, 466, 496, 526,
556, 586, 614, 647, 657, 667, 702, 737, 772, 807,
842, 862, 881, 914]
)/ 1000
# fmt: on
L = [L[i] - L[i - 1] for i in range(1, len(L))]
shaft_elem = [
ross.ShaftElement6DoF(
material=steel2,
L=l,
idl=i_d,
odl=o_d,
idr=i_d,
odr=o_d,
alpha=8.0501,
beta=1.0e-5,
rotary_inertia=True,
shear_effects=True,
)
for l in L
]
Id = 0.003844540885417
Ip = 0.007513248437500
disk0 = ross.DiskElement6DoF(n=12, m=2.6375, Id=Id, Ip=Ip)
disk1 = ross.DiskElement6DoF(n=24, m=2.6375, Id=Id, Ip=Ip)
kxx1 = 4.40e5
kyy1 = 4.6114e5
kzz = 0
cxx1 = 27.4
cyy1 = 2.505
czz = 0
kxx2 = 9.50e5
kyy2 = 1.09e8
cxx2 = 50.4
cyy2 = 100.4553
bearing0 = ross.BearingElement6DoF(
n=4, kxx=kxx1, kyy=kyy1, cxx=cxx1, cyy=cyy1, kzz=kzz, czz=czz
)
bearing1 = ross.BearingElement6DoF(
n=31, kxx=kxx2, kyy=kyy2, cxx=cxx2, cyy=cyy2, kzz=kzz, czz=czz
)
rotor = ross.Rotor(shaft_elem, [disk0, disk1], [bearing0, bearing1])
return rotor
def rubbing_example():
"""Create an example of a rubbing defect.
This function returns an instance of a rubbing defect. The purpose is to make
available a simple model so that a doctest can be written using it.
Returns
-------
rubbing : ross.Rubbing Object
An instance of a rubbing model object.
Examples
--------
>>> rubbing = rubbing_example()
>>> rubbing.speed
125.66370614359172
"""
rotor = base_rotor_example()
rubbing = rotor.run_rubbing(
dt=0.0001,
tI=0,
tF=0.5,
deltaRUB=7.95e-5,
kRUB=1.1e6,
cRUB=40,
miRUB=0.3,
posRUB=12,
speed=Q_(1200, "RPM"),
unbalance_magnitude=np.array([5e-4, 0]),
unbalance_phase=np.array([-np.pi / 2, 0]),
torque=False,
print_progress=False,
)
return rubbing | /ross-rotordynamics-1.4.2.tar.gz/ross-rotordynamics-1.4.2/ross/defects/rubbing.py | 0.830766 | 0.600013 | rubbing.py | pypi |
from termcolor import colored # coloured standard output
from rocket import rocket
import matplotlib.pyplot as plt # module used for graphing
class graph:
# uses the rocket helper functions to make lists of x2, a2, v2 and values, which will be eventually displayed on graphs with time.
def drawGraph(self,vectors,specs):
crashed = False
thrust = specs['thrust']
m = specs['baseMass']
increment = 1 # how many seconds pass every iteration
tList = []
posList = []
aList = []
vList = [] #outputted values
#instantiating...
fuelLeft = 0
totalMass = 0
time = 0
while vectors['t2'] < specs['length']: #How many seconds the program lasts for.
vectors['t2'] += increment
time = vectors['t2']
tList.append(vectors['t2'])
fuelLeft = rocket().fuelRemaining(time,specs['fuelAmount'],specs['ejectionRate'])
if fuelLeft == 0: thrust = 0
totalMass = m + fuelLeft * specs['fuelMass']
gravAcc = rocket().accDueToGravity(vectors['x2'])
vectors['a2'] = rocket().acceleration(time,thrust,totalMass,gravAcc)
aList.append(vectors['a2'])
vectors.pop('x2',None)
vectors['x2'] = rocket().position(time,vectors)
if vectors['x2'] < 0:
print colored("Your craft has collided with the ground.\n", 'red')
crashed = True
break
posList.append(vectors['x2'])
vectors['v2'] = rocket().velocity(time,vectors['v2'],vectors['a2'],vectors['a1'])
vList.append(vectors['v2'])
if crashed == False:
self.display('Acceleration','M/S^2',aList,tList)
self.display('Displacement','M',posList,tList)
self.display('Velocity','M/S',vList,tList)
plt.show()
def display(self,s,unit,variable,time):
fig = plt.figure()
plt.plot(time,variable)
fig.suptitle('{0} vs. Time'.format(s), fontsize=18)
plt.xlabel('Time ($s$)', fontsize=14)
plt.ylabel("{0} (${1}$)".format(s,unit), fontsize=14)
ax = plt.gca()
ax.minorticks_on()
plt.grid(b=True, which='major', color='0.7', linestyle='-')
plt.grid(b=True, which='minor', color='0.9', linestyle='-')
plt.draw() | /rosshill-physics-0.23.tar.gz/rosshill-physics-0.23/physics/graph.py | 0.476336 | 0.682382 | graph.py | pypi |
import os
import shutil
import warnings
import subprocess
import torch
import atomium
import tempfile
import numpy as np
import pandas as pd
import concurrent.futures
from Bio.SeqUtils import seq1
from zipfile import ZipFile
from rossmann_toolbox.utils import sharpen_preds, corr_seq, custom_warning
from rossmann_toolbox.utils import SeqVec
from rossmann_toolbox.utils.encoders import SeqVecMemEncoder
from rossmann_toolbox.utils.generators import SeqChunker
from rossmann_toolbox.models import SeqCoreEvaluator, SeqCoreDetector
from conditional import conditional
from captum.attr import IntegratedGradients
from rossmann_toolbox.utils import MyFoldX, fix_TER, solveX
from rossmann_toolbox.utils import separate_beta_helix
from rossmann_toolbox.utils.tools import run_command, extract_core_dssp
from rossmann_toolbox.utils import Deepligand3D
from rossmann_toolbox.utils.graph_feat_prep import feats_from_stuct_file
from csb.bio.io.hhpred import HHOutputParser
warnings.showwarning = custom_warning
class RossmannToolbox:
struct_utils = None
def __init__(self, n_cpu = -1, use_gpu=True, foldx_loc=None, hhsearch_loc=None, dssp_loc=None):
"""
Rossmann Toolbox - A framework for predicting and engineering the cofactor specificity of Rossmann-fold proteins
:param n_cpu: Number of CPU cores to use in the CPU-dependent calculations. n_cpu=-1 will use all available cores
:param use_gpu: Use GPU to speed up predictions
:param foldx_loc: optional absolute path to foldx binary file required for structure-based predictions
:param hhsearch_loc: Location of hhsearch binary (v3.*) required for hhsearch-enabled Rossmann core detection
:param dssp_loc: Location of the DSSP binary required for structure-based predictions
"""
self.label_dict = {'FAD': 0, 'NAD': 1, 'NADP': 2, 'SAM': 3}
self.rev_label_dict = {value: key for key, value in self.label_dict.items()}
self.n_classes = 4
self.n_cpu = n_cpu if n_cpu != -1 else os.cpu_count()
# Handle GPU config
self.use_gpu = False
self.device = torch.device('cpu')
if use_gpu:
if torch.cuda.is_available():
self.device = torch.device('cuda')
self.use_gpu = True
else:
warnings.warn('No GPU detected, falling back to the CPU version!')
self._path = os.path.dirname(os.path.abspath(__file__))
self._seqvec = self._setup_seqvec()
self._weights_prefix = f'{self._path}/weights/'
self._foldx_loc = foldx_loc
if self._foldx_loc is not None:
if not self._check_foldx():
raise RuntimeError(
'Foldx v4 binary not detected in the specified location: \'{}\''.format(self._foldx_loc))
else:
warnings.warn('FoldX binary location was not provided. The structure-based prediction functionality will be disabled.')
self._hhsearch_loc = hhsearch_loc
if self._hhsearch_loc is not None:
if not self._check_hhsearch():
raise RuntimeError(
'HHsearch v3 binary not detected in the specified location: \'{}\''.format(self._hhsearch_loc))
else:
warnings.warn(
"HHpred path was not provided. The HHsearch-based prediction of Rossmann cores won't be available")
self._dssp_loc = dssp_loc
if self._dssp_loc is not None:
if not self._check_dssp():
raise RuntimeError(
'DSSP binary not detected in the specified location: \'{}\''.format(self._dssp_loc))
else:
warnings.warn('DSSP binary location was not provided. The structure-based prediction functionality will be disabled.')
if self._foldx_loc is not None and self._dssp_loc is not None:
self.dl3d = self._setup_dl3d()
def _check_hhsearch(self):
try:
output = subprocess.check_output(self._hhsearch_loc, universal_newlines=True)
except subprocess.CalledProcessError as e:
output = e.output
except (FileNotFoundError, PermissionError):
return False
return output.split('\n')[0].startswith('HHsearch 3')
def _check_foldx(self):
try:
output = subprocess.check_output(self._foldx_loc, universal_newlines=True)
except subprocess.CalledProcessError as e:
output = e.output
except (FileNotFoundError, PermissionError):
return False
if 'foldX time has expired' in output.split('\n')[-8]:
raise RuntimeError('FoldX5 license expired, renew the binary and restart RossmannToolbox!')
return False
return 'FoldX 4' in output.split('\n')[2]
def _check_dssp(self):
try:
output = subprocess.check_output(self._dssp_loc, universal_newlines=True, stderr=subprocess.STDOUT)
except subprocess.CalledProcessError as e:
output = e.output
except (FileNotFoundError, PermissionError):
return False
return output.split('\n')[0].startswith('mkdssp 3')
def _run_hhsearch(self, sequence, min_prob=0.5):
temp = tempfile.NamedTemporaryFile(mode='w+t')
temp.writelines(">seq\n{}\n".format(sequence))
temp.seek(0)
fn = temp.name
cmd = f'{self._hhsearch_loc} -i {fn} -d {self._path}/utils/hhdb/core -n 1'
result = subprocess.call(cmd, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
temp.close()
if result == 0:
out_fn = f'{fn}.hhr'
parser = HHOutputParser()
hits = {i: (hit.qstart, hit.qend, hit.probability) for i, hit in
enumerate(parser.parse_file(out_fn)) if hit.probability >= min_prob}
os.remove(out_fn)
# Choose highest prob hit from overlapping hits
hits_nr = {}
for (beg, end, prob) in hits.values():
found_overlap = False
res_set = {i for i in range(beg, end + 1)}
for key, hit in hits_nr.items():
hit_set = {i for i in range(hit[0], hit[1] + 1)}
if len(hit_set & res_set) >= 0:
if prob > hit[2]:
hits_nr[key] = (beg, end, prob)
found_overlap = True
break
if not found_overlap:
hits_nr[len(hits_nr)] = (beg, end, prob)
probs = [0]*len(sequence)
for (beg, end, prob) in hits_nr.values():
for i in range(beg, end+1):
probs[i] = prob
return hits_nr, probs
return {}, ()
def _process_input(self, data, full_length=False):
"""
Validate and process the input eventually filtering/correcting problematic sequences
:param data: Input data - a dictionary with ids and corresponding sequences as keys and values
:param full_length: Denotes whether full-length sequences are validated (True/False)
:return: pd.DataFrame for internal processing
"""
if not isinstance(data, dict):
raise ValueError('Input data must be a dictionary with ids and sequences as keys and values!')
valid_seqs = [isinstance(seq, str) for seq in data.values()]
if not all(valid_seqs):
raise ValueError('Input data must be a dictionary with ids and sequences as keys and values!')
if len(data) == 0:
raise ValueError('Empty dictionary was passed as an input!')
non_std_seqs = [sequence != corr_seq(sequence) for sequence in data.values()]
if not full_length:
too_short_seqs = [len(sequence) < 20 for sequence in data.values()]
too_long_seqs = [len(sequence) > 65 for sequence in data.values()]
if all(too_short_seqs):
raise ValueError('Input sequence(s) are below 20aa length!')
if all(too_short_seqs):
raise ValueError('Input sequence(s) are above 65aa length!')
# Convert input dict to pd.DataFrame for easy handling
data = pd.DataFrame.from_dict(data, orient='index', columns=['sequence'])
if any(non_std_seqs):
data['sequence'] = data['sequence'].apply(lambda x: corr_seq(x))
warnings.warn('Non-standard residues detected in input data were corrected to X token.', UserWarning)
if not full_length:
if any(too_short_seqs):
data = data[data['sequence'].str.len() >= 20]
warnings.warn('Filtered out input sequences shorter than 20 residues.', UserWarning)
if any(too_long_seqs):
data = data[data['sequence'].str.len() <= 65]
warnings.warn('Filtered out input sequences longer than 65 residues.', UserWarning)
return data
def _setup_seqvec(self):
"""
Load SeqVec model to either GPU or CPU, if weights are not cached - download them from the mirror.
:return: instance of SeqVec embedder
"""
seqvec_dir = f'{self._path}/weights/seqvec'
seqvec_conf_fn = f'{seqvec_dir}/uniref50_v2/options.json'
seqvec_weights_fn = f'{seqvec_dir}/uniref50_v2/weights.hdf5'
if not (os.path.isfile(seqvec_conf_fn) and os.path.isfile(seqvec_weights_fn)):
print('SeqVec weights are not available, downloading from the remote source (this\'ll happen only once)...')
torch.hub.download_url_to_file('https://rostlab.org/~deepppi/seqvec.zip',
f'{self._path}/weights/seqvec.zip')
archive = ZipFile(f'{self._path}/weights/seqvec.zip')
archive.extract('uniref50_v2/options.json', seqvec_dir)
archive.extract('uniref50_v2/weights.hdf5', seqvec_dir)
if self.use_gpu:
return SeqVec(model_dir=f'{seqvec_dir}/uniref50_v2', cuda_device=0, tokens_per_batch=8000)
else:
return SeqVec(model_dir=f'{seqvec_dir}/uniref50_v2', cuda_device=-1, tokens_per_batch=8000)
def _setup_dl3d(self):
"""
Load DL3D model to either GPU or CPU
:return: structural graph predictor instance
"""
weights_dir = f'{self._path}/weights'
device_type = 'cpu'
return Deepligand3D(weights_dir, device_type)
@staticmethod
def _filter_cores(data, detected_cores):
"""
Parses output of `seq_detect_cores` to dictionary with core sequences
:param data: Input data - a dictionary with ids and corresponding full sequences as keys and values
:param detected_cores: Input data - a dictionary with ids and corresponding sequences as keys and values
:return: dictionary with extracted Rossmann sequences
"""
# Check for undetected cores
detected_ids = {key for key, value in detected_cores.items() if len(value) > 0}
passed_ids = set(data.keys())
if len(set(detected_ids)) != len(set(passed_ids)):
missing_ids = set(passed_ids) - set(detected_ids)
warnings.warn('Rossmann cores were not detected for ids: {}'.format(', '.join(missing_ids)))
# Check for multiple cores in one sequence
multiple_hits_ids = {str(key) for key, value in detected_cores.items() if len(value[0]) > 1}
if len(multiple_hits_ids) > 0:
warnings.warn(
'Found multiple Rossmann cores for ids: \'{}\'. Passing first hit for further predictions'.format(
', '.join(multiple_hits_ids)))
cores_filtered = {key: data[key][value[0][0][0]:value[0][0][1]] for key, value in detected_cores.items() if len(value[0]) > 0}
data = cores_filtered
return data
def _setup_seq_core_detector(self):
return SeqCoreDetector().to(self.device)
def _run_seq_core_detector(self, data):
embeddings = self._seqvec.encode(data, to_file=False)
seqvec_enc = SeqVecMemEncoder(embeddings, pad_length=500)
gen = SeqChunker(data, batch_size=64, W_size=500, shuffle=False,
data_encoders=[seqvec_enc], data_cols=['sequence'])
model = self._setup_seq_core_detector()
model.load_state_dict(torch.load(f'{self._weights_prefix}/coredetector.pt'))
model = model.eval()
preds = []
# Predict core locations
with torch.no_grad():
for batch in gen:
batch = torch.tensor(batch[0].astype(dtype=np.float32), device=self.device)
batch_preds = model(batch)
preds.append(batch_preds.cpu().detach().numpy())
# Post-process predictions
preds = np.vstack(preds)
preds_depadded = {key: np.concatenate([preds[ix][ind[0]:ind[1]] for ix, ind in zip(*value)]) for key, value
in gen.indices.items()}
return {key: (sharpen_preds(value), value) for key, value in preds_depadded.items()}
def _setup_seq_core_evaluator(self):
return SeqCoreEvaluator().to(self.device)
def seq_detect_cores(self, data, mode='dl'):
"""
Detects Rossmann beta-alpha-beta cores in full-length protein sequences.
:param data: Input data - a dictionary with ids and corresponding sequences as keys and values
:param mode: Mode of Rossmann core detection - either 'hhsearch' or 'dl'.
:return: dictionary with ids and detected core locations as keys and values and per residue probabilities.
"""
data = self._process_input(data, full_length=True)
if mode == 'hhsearch':
executor_ = concurrent.futures.ThreadPoolExecutor(max_workers=self.n_cpu)
with executor_ as executor:
futures = {executor.submit(self._run_hhsearch, sequence): key for key, sequence in
data['sequence'].to_dict().items()}
cores = {futures[future]: future.result() for future in concurrent.futures.as_completed(futures)}
return cores
elif mode == 'dl':
cores = self._run_seq_core_detector(data)
return cores
def seq_evaluate_cores(self, data, importance = False):
"""
Predicts the cofactor specitificty of the Rossmann core sequences
:param data: Input data - a dictionary with ids and corresponding sequences as keys and values
:param importance: Return additional per-residue importances, i.e. contributions to the final
specificity predictions
:return: Dictionary with the sequence ids and per-sequence predictions of the cofactor specificties.
If importance is True each dictionary value will contain additional per-residue importances.
"""
data = self._process_input(data)
# Initialize importances and preds per fold values which latter will be averaged
preds_ens = []
attrs_ens = []
# Encode with SeqVec
embeddings = self._seqvec.encode(data, to_file=False)
# Setup generator that'll be evaluated
seqvec_enc = SeqVecMemEncoder(embeddings, pad_length=65)
gen = SeqChunker(data, batch_size=64, W_size=65, shuffle=False,
data_encoders=[seqvec_enc], data_cols=['sequence'])
# Predict with each of N predictors, depad predictions and average out for final output
model = self._setup_seq_core_evaluator()
model = model.eval()
for i in range(0, 5):
model.load_state_dict(torch.load(f'{self._weights_prefix}/{i}.pt'))
preds = []
attrs = []
with conditional(not importance, torch.no_grad()):
# Raw predictions
for batch in gen:
batch = torch.tensor(batch[0].transpose(0, 2, 1).astype(dtype=np.float32), device=self.device)
batch_preds = model(batch)
preds.append(batch_preds.cpu().detach().numpy())
if importance:
ig = IntegratedGradients(model)
baseline = torch.full_like(batch, 0, device=self.device)
batch_attrs = np.asarray(
[ig.attribute(batch, baseline, i).sum(axis=1).clip(min=0).cpu().detach().numpy() for i in
range(0, self.n_classes)])
attrs.append(batch_attrs.transpose(1, 0, 2))
preds_ens.append(np.vstack(preds))
if importance:
attrs_ens.append(np.vstack(attrs))
# Average predictions between all predictors
preds_ens = np.asarray(preds_ens)
attrs_ens = np.asarray(attrs_ens)
avgs = preds_ens.mean(axis=0)
stds = preds_ens.std(axis=0)
results = {key: {f'{self.rev_label_dict[i]}{suf}': val[i] for i in range(0, self.n_classes) for suf, val in
zip(['', '_std'], [avg, std])} for key, avg, std in zip(data.index, avgs, stds)}
if importance:
avgs = attrs_ens.mean(axis=0)
stds = attrs_ens.std(axis=0)
attrs = {key: {f'{self.rev_label_dict[j]}':
((np.concatenate([avgs[ix, j, ind[0]:ind[1]] for ix, ind in zip(*value)]),
np.concatenate([stds[ix, j, ind[0]:ind[1]] for ix, ind in zip(*value)]))
) for j in range(0, self.n_classes)}
for key, value in gen.indices.items()}
return results, attrs
return results
def _prepare_struct_files(self, pdb_chains):
"""
creates all files needed for futher calculations
:param pdb_chains: list of chains
"""
#checks if raw struct file exists
for chain in pdb_chains:
if not self.struct_utils.is_structure_file_cached(chain):
self.struct_utils.download_pdb_chain(chain)
#checks if foldx struct file exists
for chain in pdb_chains:
if not self.struct_utils.is_foldx_file_cached(chain):
self.struct_utils.repair_pdb_chain(chain)
#checks if foldx feat files exists
for chain in pdb_chains:
if not self.struct_utils.is_foldx_feat_file_cached(chain):
self.struct_utils.calc_struct_feats(chain)
def _prepare_struct_feats(self, pdb_chains, mode, core_detect_mode, core_list):
"""
extract all features needed to run DL3D
"""
if self.struct_utils is None:
raise RuntimeError(' structural utilities are not initialized properly')
for chain_pos, chain in enumerate(pdb_chains):
if chain is None:
raise ChainNotFound('chain %s not found in: %s ' %(chain, path))
_, chain_id = chain.split('_')
# raw structure as provided by the user
path_pdb_file = os.path.join(self.struct_utils.path, chain) + '.pdb'
chain_struct = atomium.open(path_pdb_file)
chain_struct = chain_struct.model.chain(chain_id)
# "...if seq1(res.name)!='X'" removed because we want to include non-canonical residues too
pdb_res = [res for res in chain_struct.residues() if res.full_name not in ['water']]
# pdb ids for each residue
pdbids = [res.id.split('.')[1] for res in pdb_res]
pdbseq = "".join([seq1(res.name) for res in pdb_res])
# detect cores
if mode=='seq':
data = {chain:pdbseq}
detected_cores = self.seq_detect_cores(data, mode=core_detect_mode)
filtred_cores = self._filter_cores(data, detected_cores)
# use core sequence provided by the user
else:
filtred_cores = {chain:core_list[chain_pos]}
# file minimised in foldX
path_pdb_rep_file = os.path.join(self.struct_utils.path, chain) + '_Repair.pdb'
frame_list = list()
for pdb_chain, core_seq in filtred_cores.items():
core_pos = solveX.solveX_rev(core_seq, pdbseq)[0]
if core_pos == -1:
raise ValueError(f'could not map the core ({core_seq}) onto the chain sequence:\n\n{pdbseq}')
pdb_list = pdbids[core_pos:core_pos+len(core_seq)]
assert len(pdb_list) == len(core_seq)
raw_ss = extract_core_dssp(path_pdb_rep_file, pdb_list, core_seq, dssp_loc=self._dssp_loc)
extended_ss = separate_beta_helix(raw_ss)
frame_list.append({
'pdb_chain' : pdb_chain,
'seq' : core_seq,
'pdb_list' : pdb_list,
'fname' : path_pdb_rep_file,
'secondary' : extended_ss
})
frame = pd.DataFrame(frame_list)
# extract and process foldX and other structural features
foldx_info, distances_dict, edge_dict = feats_from_stuct_file(frame, self._path)
return {'dataframe' : frame,
'contact_maps' : distances_dict,
'edge_feats' : edge_dict,
'foldx_info' : foldx_info}
def struct_evaluate_cores(self, path, chain_list, mode, core_detect_mode, core_list):
self.struct_utils = StructPrep(path, self._foldx_loc)
self._prepare_struct_files(chain_list)
data = self._prepare_struct_feats(chain_list, mode, core_detect_mode, core_list)
return data
def predict(self, data, mode = 'core', core_detect_mode = 'dl', importance = False):
"""
Evaluate cofactor specificity of full-length or Rossmann-core sequences.
:param data: Input data - a dictionary with ids and corresponding sequences as keys and values
:param mode: Prediction mode - either 'seq' for full-sequence input or 'core' for Rossmann-core sequences
:param core_detect_mode: Mode of Rossmann core detection. Either 'hhsearch' or 'dl'. Works only in the 'seq' mode.
:param importance: Return additional per-residue importances, i.e. contributions to the final
specificity predictions
:return: Dictionary with the sequence ids and per-sequence predictions of the cofactor specificties.
If importance is True will return additional dictionary with per-residue importances for each entry.
If mode is 'seq' output will additionally contain the 'sequence' keys for each input id indicating the detected
Rossmann core sequence.
"""
if mode not in ['seq', 'core']:
raise ValueError('Prediction mode must be either \'seq\' or \'core\'!')
if core_detect_mode not in ['hhsearch', 'dl']:
raise ValueError('Core dection mode must be either \'hhsearch\' or \'dl\'!')
# Full length sequence input
if mode == 'seq':
detected_cores = self.seq_detect_cores(data, mode=core_detect_mode)
data = self._filter_cores(data, detected_cores)
if importance:
predictions, attrs = self.seq_evaluate_cores(data, importance=importance)
else:
predictions = self.seq_evaluate_cores(data, importance=importance)
if mode == 'seq':
for key in predictions.keys():
predictions[key]['sequence'] = data[key]
if importance:
return predictions, attrs
else:
return predictions
def predict_structure(self, path_pdb='', chain_list=None, mode = 'core', core_detect_mode = 'dl', core_list=None, importance = False):
"""
structure-based prediction
:param path_pdb: path to directory with pdb structures & foldx data
:param chain_list: list of chains used in predictions, if chain is not available it will be downloaded
:return Dictionary with the sequence ids and per-sequence predictions of the cofactor specificties
If importance is True
"""
if not os.path.isabs(path_pdb):
raise ValueError('The variable \'path_pdb\' has to be the absolute path!')
if mode not in ['seq', 'core']:
raise ValueError('Prediction mode must be either \'seq\' or \'core\'!')
if core_detect_mode not in ['hhsearch', 'dl']:
raise ValueError('Core dection mode must be either \'hhsearch\' or \'dl\'!')
if mode == 'core':
if core_list==None:
raise ValueError('For the \'core\' mode please provide a list of core sequences \'core_list\'')
else:
assert len(chain_list) == len(core_list), 'the number of chains must equal to the number of cores'
if self._foldx_loc is None or self._dssp_loc is None:
raise RuntimeError(
'Locations of binaries (DSSP and FoldX) were not specified. Re-run `RossmannToolbox` with `foldx_loc`, and `dssp_loc`')
if not os.path.isdir(path_pdb):
raise NotADirectoryError(f'given path_pdb: {path_pdb} is not a directory')
if chain_list is None:
chain_list = os.listdir(path_pdb)
#uses only those files with format XXXX_Y.pdb where XXXX is protein id and Y is a chain
chain_list = [f.replace('.pdb', '') for f in chain_list if f.endswith('.pdb')]
chain_list = [f for f in chain_list if len(f) == 6]
self.feats3d = self.struct_evaluate_cores(path_pdb, chain_list, mode, core_detect_mode, core_list)
results = self.dl3d.predict(**self.feats3d).to_dict(orient='records')
if importance:
results_imp = self.dl3d.generate_embeddings(**self.feats3d)
return results, results_imp
else:
return results
class StructPrep:
foldx_suffix = '_Repair.pdb'
foldx_feat_suffix = '_Repair_PN.fxout'
rotabase = 'rotabase.txt'
def __init__(self, path, path_foldx_bin):
"""
structure preparation flow for node and edge features extraction
"""
self.path = path
self.path_foldx_bin = path_foldx_bin
self.path_foldx = os.path.dirname(path_foldx_bin)
if not os.path.isfile(self.path_foldx_bin):
raise FileNotFoundError('foldx binary not found in', self.path_foldx_bin)
self._read_cache()
if 'rotabase.txt' not in self.files:
shutil.copyfile(os.path.join(self.path_foldx, self.rotabase), os.path.join(self.path, self.rotabase))
def download_pdb_chain(self, pdb_chain):
"""
downloads certain protein chain via atomium library
:params: pdb_chain - wothout .pdb extension
"""
path_dest = os.path.join(self.path, pdb_chain)
struc_id, chain = pdb_chain.split('_')
temp = atomium.fetch(struc_id.upper())
temp.model.chain(chain.upper()).save(path_dest + '.pdb')
def repair_pdb_chain(self, pdb_chain):
"""
repairs pdb file with foldx `RepairPDB` command
"""
print(f'Preparing {pdb_chain} for FoldX. This may take a while but the result will be cached.')
pdb_chain = pdb_chain + '.pdb' if not pdb_chain.endswith('.pdb') else pdb_chain
work_dir = os.getcwd()
#change working directory to `PATH_CACHED_STRUCTURES` without that
#foldx cant find structure error `No pdbs for the run found at: "./" Foldx will end`
os.chdir(self.path)
cmd = f'{self.path_foldx_bin} --command=RepairPDB --pdb={pdb_chain}'
out = run_command(cmd)
fix_TER(pdb_chain)
os.chdir(work_dir)
def calc_struct_feats(self, pdb_chain):
# calculate structural features using foldX
fx = MyFoldX(self.path, self.path, self.path_foldx_bin)
fx._MyFoldX__calc_foldx_features(self.path, pdb_chain + self.foldx_suffix)
def _read_cache(self):
"""
read content of `path` variable
"""
if not os.path.isdir(self.path):
raise NotADirectoryError(f'structure dir :{self.path}')
self.files = os.listdir(self.path)
self.files_struct = [f for f in self.files if f.find(self.foldx_suffix) == -1]
self.files_foldx = [f for f in self.files if f.find(self.foldx_suffix) != -1]
self.files_foldx_feats = [f for f in self.files if f.find(self.foldx_feat_suffix) != -1]
def is_structure_file_cached(self, file_pdb):
condition = False
file_pdb = file_pdb + '.pdb' if not file_pdb.endswith('.pdb') else file_pdb
path_file_full = os.path.join(self.path, file_pdb)
if file_pdb in self.files_struct:
if os.path.getsize(path_file_full) > 0:
condition = True
return condition
def is_foldx_feat_file_cached(self, file_pdb):
res1 = f'SD_Optimized_{file_pdb.replace(".pdb", "")}_Repair.fxout'
res2 = f'InteractingResidues_Hbonds_Optimized_{file_pdb.replace(".pdb", "")}_Repair_PN.fxout'
if res2 not in self.files_foldx_feats: return False
# check whether the two files are empty
condition = False
for r in [res1, res2]:
path_file_full = os.path.join(self.path, r)
if os.path.getsize(path_file_full) > 0:
condition = True
return condition
def is_foldx_file_cached(self, file_pdb):
condition = False
file_pdb = file_pdb + self.foldx_suffix if not file_pdb.endswith(self.foldx_suffix) else file_pdb
path_file_full = os.path.join(self.path, file_pdb)
if file_pdb in self.files_foldx:
if os.path.getsize(path_file_full) > 0:
condition = True
return condition | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/rtb.py | 0.485112 | 0.172974 | rtb.py | pypi |
import torch
import numpy as np
import torch.nn as nn
import torch.nn.functional as F
class GATLayer(nn.Module):
'''
single head variation of edge-gat
'''
def __init__(self, in_dim_n, in_dim_e, out_dim_n, out_dim_e, attention_scaler = 'softmax', **kw_args):
super().__init__()
self.fc = nn.Linear(in_dim_n, out_dim_n, bias=False)
self.attn_fc_edge = nn.Linear(in_dim_e + 2 * out_dim_n, out_dim_e, bias=True)
self.attn_fc_coef = nn.Linear(out_dim_e, 1, bias=False)
self.reset_parameters()
self.attention_scaler = attention_scaler
if self.attention_scaler == 'sigmoid':
self.scaler = nn.Sigmoid()
def reset_parameters(self):
"""
Reinitialize learnable parameters.
"""
gain = nn.init.calculate_gain('relu')
nn.init.xavier_normal_(self.attn_fc_edge.weight, gain=gain)
nn.init.xavier_normal_(self.attn_fc_coef.weight, gain=gain)
def edge_attention(self, edges):
#extract features
src_data = edges.src['z']
dst_data = edges.dst['z']
feat_data = edges.data['feats']
#merge node_i - edge_ij - node_j features
stacked = torch.cat([src_data, feat_data, dst_data], dim=1)
# apply FC and activation
feat_data = self.attn_fc_edge(stacked)
feat_data = F.leaky_relu(feat_data)
# FC to reduce edge_feats to scalar
a = self.attn_fc_coef(feat_data)
return {'attn': a, 'feats' : feat_data}
def message_func(self, edges):
return {'z': edges.src['z'], 'attn': edges.data['attn']}
def reduce_func(self, nodes):
if self.attention_scaler == 'sigmoid':
alpha = self.scaler(nodes.mailbox['attn'])
else:
alpha = F.softmax(nodes.mailbox['attn'], dim=1)
h = torch.sum(alpha * nodes.mailbox['z'], dim=1)
return {'h': h}
def forward(self, g, nfeats, efeats):
z = self.fc(nfeats)
g.edata['feats'] = efeats
g.ndata['z'] = z
g.apply_edges(self.edge_attention)
g.update_all(message_func = self.message_func,
reduce_func = self.reduce_func)
return g.ndata.pop('h'), g.edata.pop('feats')
class MultiHeadEGATLayer(nn.Module):
'''
Multihead version of Edge-GAT layer. Variation over Deep Graph Library GAT tutorial:
https://docs.dgl.ai/en/0.4.x/tutorials/models/1_gnn/9_gat.html
Tips:
* avoid high dimensionality of `out_dim_e` - increases computations time
* edge features are returned in same form as nodes that is (Batch, num_heads, out_dim_e)
params:
most of them are same as in regular dgl.nn.pytorch.GATConv
in_dim_e (int) number of input edge features
out_dim_e (int) number of output edge features
in_dim_n (int) number of input node features
out_dim_n (int) number of output node features
num_heads (int) number of attention heads
activation (None, or torch activation eg: F.relu) default None
activation after concatenation
attention_scaler (str) `sigmoid` or `softmax` - tells how to scale attention
coefficients
returns:
(node_features, edge_features) (tuple of torch.(cuda)FloatTensor's)
'''
def __init__(self, in_dim_n, in_dim_e, out_dim_n, out_dim_e, num_heads, \
activation=None,attention_scaler='softmax', **kw_args):
super().__init__()
self.heads = nn.ModuleList()
self.activation = activation
for i in range(num_heads):
self.heads.append(GATLayer(in_dim_n, in_dim_e, out_dim_n, out_dim_e, attention_scaler))
def forward(self, g, nfeats, efeats):
nodes_stack, edges_stack = [], []
for attn_head in self.heads:
nodes, edges = attn_head(g, nfeats, efeats)
nodes_stack.append(nodes.unsqueeze(1))
edges_stack.append(edges.unsqueeze(1))
nodes_stack = torch.cat(nodes_stack, dim=1)
edges_stack = torch.cat(edges_stack, dim=1)
if self.activation is not None:
nodes_stack = self.activation(nodes_stack)
edges_stack = self.activation(edges_stack)
return nodes_stack, edges_stack | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/models/edge_gat_layer.py | 0.926362 | 0.509703 | edge_gat_layer.py | pypi |
import copy
import random
from packaging import version
import torch
import dgl
import numpy as np
import pandas as pd
import networkx as nx
from .bio_params import LABEL_DICT, ACIDS_MAP_DEF, SS_MAP_EXT, CM_THRESHOLD
def collate(samples):
(graphs, labels) = map(list, zip(*samples))
batched_graph = dgl.batch(graphs)
return batched_graph, torch.tensor(labels)
class GraphECMLoaderBalanced(torch.utils.data.Dataset):
needed_columns = {'seq', 'secondary'}
threshold = CM_THRESHOLD
FLOAT_DTYPE = np.float32
counter = 0
res_info = {}; graphs = {}; edge_features = {}; node_features = {}; labels_encoded = {}
def __init__(self, frame, contact_maps, edge_features, foldx_info, balance_classes=False, **kw_args):
'''
params:
frame (pd.DataFrame) with columns: seq, alnpositions, simplified_cofactor(can be none)
ss (np.ndarray) with locations of ss
adjecency_matrix (np.ndarray) regular adjecency matrix used in defining graph structure
device (str) cpu default
cofactor (str)
use_ohe_features (bool) tells if add one hot encoding residue to node features
add_epsilon (False, or float) if float adds add_epsilon value to empty alignment field
'''
columns = frame.columns.tolist()
assert not (self.needed_columns - set(columns)), f'no column(s) {self.needed_columns - set(columns)}'
assert isinstance(frame, pd.DataFrame), 'frame should be DataFrame'
assert isinstance(contact_maps, dict)
assert isinstance(edge_features, dict)
assert isinstance(foldx_info, dict)
assert frame.shape[0] != 0, 'given empty frame'
available_indices = list(foldx_info.keys())
if 'simplified_cofactor' not in frame.columns.tolist():
frame['simplified_cofactor'] = 'NAD'
self.balance_classes = balance_classes
self.indices = []
frame = frame[frame.index.isin(available_indices)]
for i, (idx, row) in enumerate(frame.iterrows()):
seq_emb = np.asarray([ACIDS_MAP_DEF[s] for s in row['seq']], dtype=np.int64)
sec_emb = np.asarray([SS_MAP_EXT[s] for s in row['secondary']], dtype=np.int64)
self.res_info[idx] = (seq_emb, sec_emb)
self.graphs[idx] = contact_maps[idx][0] < self.threshold
edge_dist_based = np.nan_to_num(edge_features[idx])
edge_foldx_based = foldx_info[idx]['edge_data']
self.edge_features[idx] = np.concatenate([edge_dist_based, edge_foldx_based], axis=1).astype(self.FLOAT_DTYPE)
self.node_features[idx] = foldx_info[idx]['node_data'].astype(self.FLOAT_DTYPE)
#print(self.node_features[idx], foldx_info)
self.labels_encoded[idx] = LABEL_DICT[row['simplified_cofactor']]
self.indices.append(idx)
self.NAD_indices, self.non_NAD_indices = [], []
for idx, cof in self.labels_encoded.items():
if cof == 0:
self.NAD_indices.append(idx)
else:
self.non_NAD_indices.append(idx)
#self._validate_dicts()
self._map_new_()
#self._fix_samples_balancing_()
self.num_samples_per_epoch = len(self.indices)
if self.num_samples_per_epoch == 0:
print(len(self.labels_encoded))
print(len(self.NAD_indices), len(self.non_NAD_indices))
raise ValueError('zero length loader')
def __len__(self):
return self.num_samples_per_epoch
def __getitem__(self, idx):
idx_m = self.index_map[idx]
features_edge = self.edge_features[idx_m]
features_node = self.node_features[idx_m]
g = dgl.from_networkx(nx.Graph(self.graphs[idx_m]))
seq_res_nb, sec_res_nb = self.res_info[idx_m]
if self.balance_classes:
if self.counter == self.num_samples_per_epoch:
self._fix_samples_balancing_()
else:
self.counter += 1
g.ndata['residues'] = torch.from_numpy(seq_res_nb)
g.ndata['secondary'] = torch.from_numpy(sec_res_nb)
g.edata['features'] = torch.from_numpy(features_edge)
g.ndata['features'] = torch.from_numpy(features_node)
return g, self.labels_encoded[idx_m]
def _fix_samples_balancing_(self):
if self.balance_classes:
NAD_subsample = len(self.NAD_indices)
NAD_subsample = int(self.SUBSAMPLE*len(self.NAD_indices))
random.shuffle(self.NAD_indices)
NAD_subsamples = self.NAD_indices[:NAD_subsample]
self.indices = NAD_subsamples + self.non_NAD_indices
random.shuffle(self.indices)
self.counter = 0
else:
self.indices = list(self.res_info.keys())
self._map_new_()
def _map_new_(self):
self.index_map = {num : idx for num, idx in enumerate(self.indices)}
def _validate_dicts(self):
pass
'''
for idx in self.adjecency_matrix.keys():
if self.embeddings[idx].shape[0] != self.res_info[idx][0].size:
raise ValueError(f'shape mismatch for idx {idx} between emb and res_info')
''' | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/utils/graph_loader_opt.py | 0.455441 | 0.411879 | graph_loader_opt.py | pypi |
import pandas as pd
import numpy as np
import os
from allennlp.commands.elmo import ElmoEmbedder
class SeqVec:
def __init__(self, model_dir, cuda_device=-1, tokens_per_batch=16000):
"""
Wrapper for efficient embedding of protein sequences with SeqVec (Heinzinger et al., 2019)
:param model_dir: Directory storing SeqVec files (weights.hdf5 and options.json)
:param cuda_device: Index of the CUDA device to use when encoding (-1 if CPU)
:param tokens_per_batch: Number of tokens (amino acids per encoded sequence batch) - depends on available RAM
"""
weights = model_dir + '/' + 'weights.hdf5'
options = model_dir + '/' + 'options.json'
self.seqvec = ElmoEmbedder(options, weights, cuda_device=cuda_device)
self.tokens_per_batch = tokens_per_batch
def encode(self, data, to_file=True, out_path=None, sum_axis=True, cut_out=False):
"""
Encodes sequences stored in 'data' DataFrame
:param data: pandas DataFrame storing sequences ('sequence' column) and optionally 'beg' and 'end' indices
to cut out the embeddings
:param to_file: If true save embedding for further use in 'out_path'
:param out_path: Directory to store embeddings if to_file is True. Filenames match the indexes of the 'data'.
:param sum_axis: Specifies whether first axis of the embedding will be summed up.
This will results in Nx1024 embedding for a protein sequence of length N.
:param cut_out: Optionally cut the embedding with the 'beg' and 'end' indices. Useful when calculating the
embedding for whole sequence and cutting out only part of it. If True data must contain 'beg' and 'end' columns.
:return results: if 'to_file' is false returns dictionary with data indexes as keys and embedding as values.
"""
# Validate input DataFrame
if not isinstance(data, pd.DataFrame):
raise TypeError('Data must be a pandas DataFrame!')
if 'sequence' not in data.columns:
raise ValueError('DataFrame must contain sequence column!')
if cut_out and 'beg' not in data.columns and 'end' not in data.columns:
raise ValueError('DataFrame must contain beg and end columns to if cut_out is True!')
if to_file and not os.path.isdir(out_path):
raise OSError('Output directory does not exist!')
# Process input DataFrame
tmp_df = data.copy()
tmp_df['seq_len'] = tmp_df['sequence'].apply(len) # Calculate length of each sequence in DataFrame
tmp_df = tmp_df.sort_values(by='seq_len') # Sort sequences by length
tmp_df['cum_seq_len'] = tmp_df['seq_len'].cumsum() # Calculate cumulative sequence lengths to split into batches
tmp_df['batch'] = tmp_df['cum_seq_len'] // self.tokens_per_batch
# Encode sequences in batches to speed up the process. Each batch contain at most 'tokens_per_batch' aa's.
results = {}
for batch in tmp_df['batch'].unique():
df = tmp_df[tmp_df['batch'] == batch]
sequences = df['sequence'].tolist()
if cut_out:
beg_indices = df['beg'].tolist()
end_indices = df['end'].tolist()
embs = self.seqvec.embed_sentences(sequences)
# Sum first axis if specified
if sum_axis:
embs = [emb.sum(axis=0) for emb in embs]
# Cut out sequence chunks if specified
if cut_out:
embs = [emb[beg:end] for emb, beg, end in zip(embs, beg_indices, end_indices)]
# Save results
for emb, _id in zip(embs, df.index.values):
if to_file:
np.save('{}/{}.npy'.format(out_path, _id), emb)
else:
results[_id] = emb
if not to_file:
return results | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/utils/seqvec.py | 0.689515 | 0.413892 | seqvec.py | pypi |
from collections.abc import Iterable
import numpy as np
import warnings
from scipy.signal import find_peaks
from itertools import groupby
def custom_warning(message, category, filename, lineno, file=None, line=None):
print(f'{filename}:{lineno} - {message}')
def sharpen_preds(probs, sep=15, min_prob=0.5):
"""
Sharpens raw probabilities to more human-readable format
:param probs: raw probabilities
:return: sharpened probabilities
"""
probs = probs.flatten()
above_threshold = probs > min_prob
peak_dict = {}
i = 0
for k, g in groupby(enumerate(above_threshold), key=lambda x: x[1]):
if k:
g = list(g)
beg, end = g[0][0], g[-1][0]
if end -beg >= 1:
peak_dict[i] = (beg, end, max(probs[beg:end]))
i += 1
if len(peak_dict) == 1:
merged_peaks = [list(peak_dict.keys())]
else:
merged_peaks = []
i = 0
while i <= len(peak_dict) -1:
merge_list = [i]
while True:
if peak_dict[i + 1][0] - peak_dict[i][1] <= sep:
merge_list.append(i + 1)
i += 1
if i == len(peak_dict) - 1:
merged_peaks.append(merge_list)
break
else:
merged_peaks.append(merge_list)
i += 1
break
if i == len(peak_dict) - 1:
break
merged_peak_dict = {i: (peak_dict[mp[0]][0], peak_dict[mp[-1]][1], max([peak_dict[idx][2] for idx in mp]))
for i, mp in enumerate(merged_peaks)}
return merged_peak_dict
def corr_seq(seq):
"""
Corrects sequence by mapping non-std residues to 'X'
:param seq: input sequence
:return: corrected sequence with non-std residues changed to 'X'
"""
letters = set(list('ACDEFGHIKLMNPQRSTVWYX'))
seq = ''.join([aa if aa in letters else 'X' for aa in seq])
return seq
def separate_beta_helix(secondary):
'''
changes labels of helices in dssp sequences, adding number for them for instance:
`H-E1-H-E2-H` to `'H1-E1-H2-E2-H3'
:params iterable with chars indicating dssp annotations
"return listo of chars enhanced dssp annotations"
'''
if isinstance(secondary, str):
secondary = list(secondary)
elif not isinstance(secondary, Iterable):
raise ValueError(f'secondary must be iterable, but passed {type(secondary)}')
sec_len = len(secondary)
#E1 E2 split condition
h_start = sec_len//2
#H split condition
e_indices = [i for i, letter in enumerate(secondary) if letter =='E']
e_min, e_max = min(e_indices), max(e_indices)
secondary_extended = list()
for i, letter in enumerate(secondary):
if letter == 'E':
if i <= h_start:
new_letter = 'E1'
else:
new_letter = 'E2'
elif letter == 'H':
if i < e_min:
new_letter = 'H1'
elif e_min < i < e_max:
new_letter = 'H2'
else:
new_letter = 'H3'
elif letter == ' ':
new_letter = '-'
else:
new_letter = letter
secondary_extended.append(new_letter)
return secondary_extended | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/utils/utils.py | 0.58261 | 0.298491 | utils.py | pypi |
import random
import pandas as pd
import numpy as np
class SeqChunker:
def __init__(self, data, W_size=64, batch_size=64, shuffle=True, neg_frac=1,
data_encoders=None, label_encoders=None, data_cols=None, label_cols=None):
"""
Generates sequence chunks of fixed sized window with defined overlap between windows
:param data: instance of the pandas DataFrame containing the dataset
:param W_size: size of the sequence windows
:param batch_size: size of the batches returned by the generator
:param shuffle: True/False - shuffle entries between each epoch
:param neg_frac: fraction of negatives used at each epoch. 'global_label' columns must be defined in the 'data'
if neg_frac < 1
:param data_encoders: list of data encoders
:param label_encoders: list of label encoders
:param data_cols: columns in the 'data' DataFrame that'll be used by the data_encoders
(length of data_cols list must be equal to the length of data_encoders list)
:param label_cols: columns in the 'data' DataFrame that'll be used by the label_encoders
(length of label_cols list must be equal to the length of label_encoders list)
"""
self.data = data.copy()
self.batch_size = batch_size
self.data_encoders = data_encoders
self.data_cols = data_cols
self.label_encoders = label_encoders
self.label_cols = label_cols
self.W_size = W_size
self.shuffle = shuffle
self.neg_frac = neg_frac
# Validate input
self._validate_input()
# Select only neccesary data
cols = []
if self.neg_frac < 1:
cols += ['global_label']
if self.label_cols is not None:
cols += self.label_cols
cols += self.data_cols
self.data = self.data[cols]
self._assign_batches()
def _validate_input(self):
if not isinstance(self.data, pd.DataFrame): # Input data must be pd.DataFrame
raise TypeError('Data must be a pandas DataFrame!')
if not isinstance(self.data_encoders, list): # Encoders must be passed as the list
raise ValueError('Data encoder(s) must be specified as list!')
if len(self.data_encoders) != len(self.data_cols): # Number of data encoders must be equal to number of columns
raise ValueError('Number of data encoders must be equal to number of data columns in the data df')
if self.label_encoders is not None:
if not isinstance(self.label_encoders, list): # Encoders must be passed as the list
raise ValueError('Label encoder(s) must be specified as list!')
if len(self.label_encoders) != len(self.label_cols): # Number of label encoders must be equal to number of columns
raise ValueError('Number of label encoders must be equal to number of label columns in the data df')
if self.neg_frac < 1 and 'global_label' not in self.data.columns: # 'global_label' must be passed for downsampling negatives
raise ValueError('Dataframe must contain global_label column for neg class downsampling')
if self.label_encoders is not None: # Check for the label format (single or seq2seq)
self._single_label = [all(len(str(label)) == 1 for label in self.data[label_col].values) for label_col in
self.label_cols]
self._single_data = [all(len(str(inp)) == 1 for inp in self.data[data_col].values) for data_col in
self.data_cols]
def _assign_batches(self):
if self.neg_frac < 1:
tmp_dict = self.data.loc[
set(self.data[self.data['global_label'] == 0].sample(frac=self.neg_frac).index) | set(
self.data[self.data['global_label'] == 1].index)].to_dict(orient='index')
else:
tmp_dict = self.data.to_dict(orient='index')
if self.label_encoders is not None:
windowed_data = {indice[0]: indice[1:] for name, value in tmp_dict.items() for indice in
self._split_seq(name, data=[value[col] for col in self.data_cols],
labels=[value[col] for col in self.label_cols])}
else:
windowed_data = {indice[0]: indice[1:] for name, value in tmp_dict.items() for indice in
self._split_seq(name, data=[value[col] for col in self.data_cols])}
self.windowed_data = pd.DataFrame.from_dict(windowed_data, orient='index',
columns=['id', 'data', 'label', 'beg', 'end', 'pad_left'])
miss_idxs = set(tmp_dict.keys()) - set(self.windowed_data.id.values)
for idx in miss_idxs:
tmp_dict.pop(idx)
if self.shuffle:
self.windowed_data = self.windowed_data.sample(frac=1)
indices = self.windowed_data.groupby(by='id').indices
pads_left = self.windowed_data.groupby(by='id').agg({'pad_left': list})['pad_left'].to_dict()
self.windowed_data['len'] = self.windowed_data['end'] - self.windowed_data['beg']
lens = self.windowed_data.groupby(by='id').agg({'len': list})['len'].to_dict()
self.indices = {key: (
list(indices[key]), [(pad_left, pad_left + len_) for pad_left, len_ in zip(pads_left[key], lens[key])]) for key in tmp_dict.keys()}
self.windowed_data['batch'] = np.arange(len(self.windowed_data)) // self.batch_size
def _split_seq(self, name, data=None, labels=None):
seq = data[0]
n_windows = 1 + len(seq) // self.W_size
pad_left = (n_windows * self.W_size - len(seq)) // 2
pad_right = (n_windows * self.W_size - len(seq)) // 2
if (n_windows * self.W_size - len(seq)) % 2 != 0:
pad_right += 1
windows = list(range(-pad_left, len(seq), self.W_size))
splitted_seq = []
for c, i in enumerate(windows):
beg = max(0, i)
end = min(len(seq), i + self.W_size)
label_ = labels
if labels:
label_ = [label if self._single_label[i] else label[beg:end] for i, label in enumerate(labels)]
data_ = [dat if self._single_data[i] else dat[beg:end] for i, dat in enumerate(data)]
if c == 0:
splitted_seq.append(('{}_{}'.format(name, c), name, data_, label_, beg, end, pad_left))
else:
splitted_seq.append(('{}_{}'.format(name, c), name, data_, label_, beg, end, 0))
return splitted_seq
def __len__(self):
return int(np.ceil(len(self.windowed_data) / self.batch_size))
def __getitem__(self, idx):
batch_data = self.windowed_data[self.windowed_data['batch'] == idx]
X = [encoder.encode_batch(batch_data, i) for i, encoder in enumerate(self.data_encoders)]
if self.label_encoders is not None:
y = [encoder.encode_batch(batch_data, i) for i, encoder in enumerate(self.label_encoders)]
return X, y
return X
def __iter__(self):
for item in (self[i] for i in range(len(self))):
yield item | /rossmann-toolbox-0.1.0.tar.gz/rossmann-toolbox-0.1.0/rossmann_toolbox/utils/generators.py | 0.694303 | 0.481759 | generators.py | pypi |
from math import gcd
from typing import Dict, List, Optional
from collections import defaultdict, namedtuple
from dataclasses import dataclass, InitVar, field as f
from lxml.etree import _ElementTree
from .helpers import SPEC_KEYS, MultiDict, str_int
ANY_SPEC = {'*'}
Title = namedtuple('Title', ['name', 'value'])
Column = namedtuple('Column', ['code', 'value'])
class EmptyIter:
def iter(self, *args):
return []
EMPTY_ITER = EmptyIter()
def max_divider(num, terms):
'''НОД для списка чисел'''
for term_id in terms:
num = gcd(num, int(term_id))
return num
class CodeIterable:
def iter(self, codes=None):
'''Метод получения итератора по элементам'''
if codes is None or codes == ['*']:
return self._iter_all()
else:
return self._iter_codes(codes)
@dataclass
class Row:
code: str
s1: str
s2: str
s3: str
_cols: Dict[str, Column] = f(default_factory=dict)
# ---
def add_col(self, col_code, col_text):
'''Добавление колонки в строку'''
self._cols[col_code] = Column(col_code, col_text)
# ---
def iter(self, codes=None, dimension=None):
'''Метод получения итератора по элементам'''
if codes is None and dimension is None:
return self._iter_all()
if codes is None or codes == ['*']:
return self._iter_codes(dimension)
else:
return self._iter_codes(codes)
def _iter_all(self):
'''Возвращает итератор по всем колонкам'''
return self._cols.values()
def _iter_codes(self, codes):
'''Итерируемся по кодам, возвращаем колонку либо "заглушку"'''
for code in codes:
yield self.get_column(code) or Column(code, None)
def get_column(self, code):
'''Возвращает колонку'''
return self._cols.get(code)
# ---
def match(self, specs):
'''Проверка, входит ли строка в список переданных специфик'''
for spec in specs:
row_spec = self.get_spec(spec.key) or spec.default
if spec == ANY_SPEC:
return True
elif row_spec not in spec:
return False
return True
def get_spec(self, key):
'''Возвращает указанную специфику строки или дефолтную'''
return getattr(self, key)
@dataclass
class Section(CodeIterable):
code: str
_rows: MultiDict = f(default_factory=MultiDict)
_rows_counter: defaultdict = f(default_factory=lambda: defaultdict(int))
@property
def rows(self):
return self._rows
@property
def rows_counter(self):
return self._rows_counter
# ---
def add_row(self, row):
'''Добавление строки в раздел и приращение счётчика'''
self._rows.add(row.code, row)
self._rows_counter[(row.code, row.s1, row.s2, row.s3)] += 1
# ---
def _iter_all(self):
'''Возвращает итератор по всем строкам'''
return iter(self._rows.getall())
def _iter_codes(self, codes):
'''Итерируемся по кодам, получаем строки с указанным кодом,
если список строк не пуст, возвращаем каждую строку,
иначе строку "заглушку"
'''
for code in codes:
for row in (self.get_rows(code) or [Row(code, None, None, None)]):
yield row
def get_rows(self, code):
'''Возвращает список строк"'''
return self._rows.get(code)
@dataclass
class Report(CodeIterable):
xml: InitVar[_ElementTree]
_blank: bool = True
_year: str = None
_title: List[Title] = None
_data: Dict[str, Section] = None
_period_raw: str = None
_period_type: Optional[str] = None
_period_code: Optional[str] = None
def __repr__(self):
return '<Report title={_title}\ndata={_data}>'.format(**self.__dict__)
def __post_init__(self, xml):
self._title = self._read_title(xml)
self._data = self._read_data(xml)
self._get_periods(xml)
self._get_year(xml)
@property
def year(self):
return self._year
@property
def blank(self):
return self._blank
@property
def title(self):
return self._title
@property
def period_type(self):
return self._period_type
@property
def period_code(self):
return self._period_code
# ---
def _iter_all(self):
'''Возвращает итератор по всем разделам'''
return self._data.values()
def _iter_codes(self, codes):
'''Итерируемся по кодам, возвращаем разделы'''
for code in codes:
yield self.get_section(code)
def get_section(self, code):
'''Возвращает раздел с указанным кодом'''
return self._data.get(code, EMPTY_ITER)
# ---
def _read_title(self, xml):
'''Чтение заголовков отчёта'''
title = []
for node in xml.xpath('/report/title/item'):
title.append(Title(node.attrib.get('name'),
node.attrib.get('value', '').strip()))
return title
# ---
def _read_data(self, xml):
'''Чтение тела отчёта (разделы/строки/колонки)'''
data = {}
for section_xml in xml.xpath('/report/sections/section'):
section = Section(self._get_code(section_xml))
for row_xml in section_xml.xpath('./row'):
row = Row(self._get_code(row_xml), **self._read_specs(row_xml))
for col_xml in row_xml.xpath('./col'):
row.add_col(self._get_code(col_xml), col_xml.text)
self._blank = False
section.add_row(row)
data[section.code] = section
return data
def _get_code(self, xml):
'''Возвращает код элемента (раздела/строки/колонки)'''
return str_int(xml.attrib.get('code'))
def _read_specs(self, xml):
'''Чтение спицифик строки'''
return {spec_key: xml.attrib.get(spec_key) for spec_key in SPEC_KEYS}
# ---
def _get_year(self, xml):
'''Получение года из корня отчёта'''
self._year = xml.xpath('/report/@year')[0]
def _get_periods(self, xml):
'''Получение и разбиение периода из корня отчёта'''
self._period_raw = xml.xpath('/report/@period')[0]
if len(self._period_raw) == 4:
self._period_type = str_int(self._period_raw[:2])
self._period_code = str_int(self._period_raw[2:])
# ---
def set_periods(self, catalogs, idp):
'''Попытка привести тип и код периода к формату
описанному в приказе Росстата
'''
try:
periods_id = self._get_periods_id(catalogs)
if int(self._period_raw) not in periods_id:
return False
max_code = max(periods_id)
if max_code <= int(idp):
self._period_type = idp
self._period_code = self._period_raw
return True
max_div = max_divider(max_code, periods_id)
if max_code <= int(idp) * max_div:
self._period_type = idp
self._period_code = str(int(int(self._period_raw) / max_div))
return True
return False
except Exception:
return False
def _get_periods_id(self, catalogs):
'''Получение идентификаторов допустимых периодов из справочника'''
try:
return [int(term_id) for term_id in catalogs['s_time']['ids']]
except KeyError:
return [int(term_id) for term_id in catalogs['s_mes']['ids']] | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/report.py | 0.712632 | 0.267008 | report.py | pypi |
import operator
from copy import deepcopy
from itertools import chain
from functools import reduce
from .value import nullablefloat
from .specific import Specific
from ..exceptions import NoElemToCompareError, NoFormatForRowError
from ....helpers import SPEC_KEYS
OPERATOR_MAP = {
'<': operator.lt,
'<=': operator.le,
'=': operator.eq,
'>': operator.gt,
'>=': operator.ge,
'<>': operator.ne,
'and': operator.and_,
'or': operator.or_,
'+': operator.add,
'-': operator.sub,
'*': operator.mul,
'/': operator.truediv,
}
BOOL_TYPE = {
'and': 'bool',
'or': 'bool'
}
class Elem:
def __init__(self, val, section=None, rows=None, columns=None):
self.section = set() if section is None else {section}
self.rows = set() if rows is None else {rows}
self.columns = set() if columns is None else {columns}
self._controls = []
self._func = None
self.bool = True
self.val = nullablefloat(val)
def __add__(self, elem):
return self.__modify(elem, operator.add)
def __sub__(self, elem):
return self.__modify(elem, operator.sub)
def __mul__(self, elem):
return self.__modify(elem, operator.mul)
def __truediv__(self, elem):
return self.__modify(elem, operator.truediv)
def __neg__(self):
self.val = self.val.neg()
return self
def __repr__(self):
return '<Elem {}{}{} value={} bool={}>'.format(
list(self.section),
list(self.rows),
list(self.columns),
repr(self.val),
self.bool
)
def __modify(self, elem, op_func):
self.rows |= elem.rows
self.columns |= elem.columns
try:
self.val = op_func(self.val, elem.val)
except ZeroDivisionError:
pass
return self
@property
def controls(self):
return self._controls
def controls_clear(self):
'''Очищение списка контролей'''
self._controls.clear()
def controls_extend(self, r_elem):
'''Расширение списка контролей, контролями из правого элемента'''
self._controls.extend(r_elem._controls)
def controls_append(self, r_elem, op_name):
'''Форматирование и добавление непройденного контроля'''
self._controls.append({
'left': self.val,
'operator': op_name,
'right': r_elem.val,
'delta': round(self.val - r_elem.val, 2)
})
def check(self, report, params, ctx_elem):
if self._func:
return self._apply_func(report, params, *self._func)
return [self]
def _apply_func(self, report, params, func, right_elem):
'''Выполнение функций на элементах массива'''
elems = []
for r_elem in right_elem.check(report, params, self):
elems.append(getattr(operator, func)(deepcopy(self), r_elem))
return elems
def isnull(self, replace):
'''Замена "нулёвого" значения на replace'''
if self.val.is_null:
self.val = nullablefloat(replace)
def round(self, ndig, trunc=0):
'''Округление/отсечение до ndig знаков'''
if trunc > 0:
self.val = self.val.truncate(ndig)
else:
self.val = self.val.round(ndig)
def abs(self):
'''Выполнение функции abs над значением'''
self.val = self.val.abs()
def floor(self):
'''Выполнение функции floor над значением'''
self.val = self.val.floor()
def add_func(self, func, arg):
'''Добавляем функцию элементу при парсинге'''
self._func = (func, arg)
class ElemList:
def __init__(self, sections, rows, columns, s1='*', s2='*', s3='*'):
self.sections = sections
self.rows = rows
self.columns = columns
self.s1 = s1
self.s2 = s2
self.s3 = s3
self.specs = {}
self.funcs = []
self.elems = []
def __repr__(self):
return "<ElemList {}{}{} specs={} funcs={} elems={}>".format(
self.sections,
self.rows,
self.columns,
self.specs,
self.funcs,
self.elems
)
def __neg__(self):
self._apply_unary('neg')
return self
def check(self, report, params, ctx_elem):
self._read_data(report, params)
self._apply_funcs(report, params, ctx_elem)
return self._flatten_elems()
def _read_data(self, report, params):
'''Чтение отчёта и конвертация его в массивы элементов'''
for section in self._read_sections(report):
for row in self._read_rows(params, section):
self.add_row(self._read_columns(params, section, row))
def _read_sections(self, report):
'''Получаем итератор по секциям'''
return report.iter(self.sections)
def _read_rows(self, params, section):
'''Итерируемся по строкам и проверяем их на соответствие спецификам'''
for row in section.iter(self.rows):
if not params.formats.has(section.code, row.code):
raise NoFormatForRowError()
if row.match(self._get_specs(section.code, row.code, params)):
yield row
def _get_specs(self, sec_code, row_code, params):
'''Подготавливаем и возвращаем специфики для строки,
либо возвращаем уже готовые
'''
if row_code not in self.specs:
self.specs[row_code] = list(self._prepare_specs(sec_code,
row_code,
params))
return self.specs[row_code]
def _prepare_specs(self, sec_code, row_code, params):
'''Подготавливаем специфики для строки. Создаём специфику и проверяем,
необходимо ли её "развернуть"
'''
for key in SPEC_KEYS:
spec = Specific(key, getattr(self, key))
if spec.need_expand():
spec.expand(sec_code, row_code, params)
yield spec
def _read_columns(self, params, section, row):
'''Читаем графы. Конвертируем их в элементы'''
dimension = self._get_dimension(section.code, params)
for col in row.iter(self.columns, dimension=dimension):
yield Elem(col.value, section.code, row.code, col.code)
def _get_dimension(self, sec_code, params):
'''Возвращаем "размерность" для секции" '''
return params.dimension[sec_code]
def _apply_funcs(self, report, params, ctx_elem):
'''Выполнение функций на элементах массива'''
for func, args in self.funcs:
if func == 'sum':
self._apply_sum(ctx_elem)
elif func in ('abs', 'floor'):
self._apply_unary(func)
elif func in ('round', 'isnull'):
self._apply_binary(report, params, func, args)
else:
self._apply_math(report, params, func, *args)
def _apply_sum(self, ctx_elem):
'''Суммирование строк и/или графов'''
if isinstance(ctx_elem, ElemLogic): # для случаев SUM{}|=|1|=|SUM{}
self.elems = [[reduce(operator.add, chain(*self.elems))]]
elif self.columns == ctx_elem.columns: # строк в каждой графе
self.elems = [[reduce(operator.add, l)] for l in zip(*self.elems)]
elif self.rows == ctx_elem.rows: # граф в каждой строке
self.elems = [[reduce(operator.add, l)] for l in self.elems]
elif not self.elems: # всех ячеек (секция пустая)
self.elems = [[Elem(None, self.sections[0], '*', '*')]]
else: # всех ячеек (секция не пустая)
self.elems = [[reduce(operator.add, chain(*self.elems))]]
def _apply_unary(self, func):
'''Выполнение унарных операций (abs, floor, neg)'''
for row in self.elems:
for elem in row:
getattr(elem, func)()
def _apply_binary(self, report, params, func, elems):
'''Выполнение бинарных операций (round, isnull)'''
args = [int(elem.check(report, params, self)[0].val) for elem in elems]
for row in self.elems:
for elem in row:
getattr(elem, func)(*args)
def _apply_math(self, report, params, func, elem):
'''Выполнение математических операций (add, sub, mul, truediv)'''
left_operand = self._flatten_elems()
right_operand = elem.check(report, params, self)
self.elems.clear()
for l_elem, r_elem in zip(left_operand, right_operand):
self.elems.append([getattr(operator, func)(l_elem, r_elem)])
def _zip(self, l_list, r_list):
'''Сбираем списки в список кортежей. Если короткий список пустой,
создаём "нулевой" элемент. Добиваем длину короткого списка
до длины длинного если они различаются.
[1, 2, 3], [4] > [1, 2, 3], [4, 4, 4] > [1, 4], [2, 4], [3, 4]
'''
lists = [l_list, r_list]
if len(l_list) != len(r_list):
short_list, long_list = self.__order_lists(l_list, r_list)
short_list_index = self.__get_short_list_index(lists, short_list)
lists[short_list_index] = self.__generate_short_list(short_list,
long_list)
return zip(*lists)
def __order_lists(self, l_list, r_list):
'''Упорядочивание двух списков от меньшего к большему'''
if len(l_list) < len(r_list):
return l_list, r_list
return r_list, l_list
def __get_short_list_index(self, lists, short_list):
'''Возвращаем индекс короткого списка'''
return lists.index(short_list)
def __generate_short_list(self, short_list, long_list):
'''Генерация списка, который заёмет место короткого'''
return [deepcopy(short_list[0]) for _ in range(len(long_list))]
def _flatten_elems(self):
'''Возвращаем плоский массив элементов'''
return list(chain(*self.elems))
def add_row(self, columns):
self.elems.append(list(columns))
def add_func(self, func, *args):
'''Добавляем функцию в "очередь" при парсинге'''
self.funcs.append((func, args))
class ElemLogic(ElemList):
def __init__(self, l_elem, operator, r_elem):
self.l_elem = l_elem
self.r_elem = r_elem
self.op_name = operator.lower()
self.op_func = OPERATOR_MAP.get(self.op_name)
self.elem_type = BOOL_TYPE.get(self.op_name, 'val')
self.funcs = []
self.elems = []
self.params = None
def __repr__(self):
return '<ElemLogic left={} operator="{}" right={} funcs={}>'.format(
self.l_elem,
self.op_name,
self.r_elem,
self.funcs
)
def check(self, report, params, ctx_elem=None):
'''Основной метод вызова проверки'''
self.params = params
self._control(report)
return self.elems
def _control(self, report):
'''Подготовка элементов, слияние, передача в метод контроля'''
l_elems = self.l_elem.check(report, self.params, self.r_elem)
r_elems = self.r_elem.check(report, self.params, self.l_elem)
self.__check_elems(l_elems, r_elems)
self.__apply_funcs(l_elems)
self.__control(self._zip(l_elems, r_elems))
def __check_elems(self, *elems):
if not all(elems):
raise NoElemToCompareError()
def __apply_funcs(self, elems):
'''Выполнение функций на элементах массива'''
for func, _ in self.funcs:
for elem in elems:
getattr(elem, func)()
def __control(self, elems_pairs):
'''Определение аттрибута контроля. Итерация по парам элементов,
выполнение проверок, обработка результата
'''
for l_elem, r_elem in elems_pairs:
if not self.__logic_control(l_elem, r_elem):
self.__get_result(l_elem, r_elem, success=False)
else:
self.__get_result(l_elem, r_elem, success=True)
self.elems.append(l_elem)
def __get_result(self, l_elem, r_elem, *, success):
'''Обработка результата. При проверке логического "or", если левый
элемент уже содержит ошибки, затираем их, инчае затираем список
контролей правого. При неуспешной проверке, формируется ошибка
которая прибавляется к списку контролей левого элемента.
Затем в левый элемент сливаются все ошибки из списка правого.
'''
if self.op_name == 'or':
if l_elem.controls:
l_elem.controls_clear()
else:
r_elem.controls_clear()
if not success:
l_elem.controls_append(r_elem, self.op_name)
l_elem.val = r_elem.val
l_elem.controls_extend(r_elem)
def __logic_control(self, l_elem, r_elem):
'''Получение значений и проведение проверки'''
if not self.op_func(*self.__get_elem_values(l_elem, r_elem)):
return self.__check_fault(l_elem, r_elem)
return True
def __get_elem_values(self, l_elem, r_elem):
'''Округление и возвращение значений которые будут сравниваться'''
l_elem.round(self.params.precision)
r_elem.round(self.params.precision)
return getattr(l_elem, self.elem_type), getattr(r_elem, self.elem_type)
def __check_fault(self, l_elem, r_elem):
'''Проверка погрешности'''
return abs(l_elem.val - r_elem.val) <= self.params.fault
class ElemSelector(ElemList):
def __init__(self, action, elems):
self.action = action.lower()
self.funcs = []
self.elems = elems
def __repr__(self):
return '<ElemSelector action={} funcs={} elems={}>'.format(
self.action,
self.funcs,
self.elems
)
def check(self, *args):
self._select(args)
self._apply_funcs(*args)
return self._flatten_elems()
def _select(self, args):
'''Подготовка элементов, слияние. Очистка списка элементов.
Вызов метода селектора по полю action
'''
elems_results = self._zip(*(elem.check(*args) for elem in self.elems))
self.elems.clear()
getattr(self, self.action)(elems_results)
def nullif(self, elems_results):
'''Сравнивает результаты левого и правого элементов. Добавляем к
результату элемент со значением None если значения равны,
иначе добавляем левый элемент
'''
for l_elem, r_elem in elems_results:
if l_elem.val == r_elem.val:
self.elems.append([Elem(None)])
else:
self.elems.append([l_elem])
def coalesce(self, elems_results):
'''Сравнивает результаты элементов каждой "линии" (строки/графа).
Добавляем к результату первый элемент значение которого не None
'''
for line_elems in elems_results:
first_elem = next([e] for e in line_elems if e.val is not None)
self.elems.append(first_elem) | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/control/parser/elements.py | 0.533884 | 0.178526 | elements.py | pypi |
class Specific:
def __init__(self, key, specs):
self._key = key
self._specs = set(specs)
self._default = None
def __repr__(self):
return "<Specific {} default={}>".format(self._specs, self._default)
def __iter__(self):
return iter(self._specs)
def __contains__(self, spec):
return spec in self._specs
def __eq__(self, other):
return self._specs == other
@property
def key(self):
return self._key
@property
def default(self):
return self._default
def need_expand(self):
return self._specs not in ({None}, {'*'})
def expand(self, sec_code, row_code, params):
'''Основной метод подготовки спефик. Получение формата,
каталога и развертывание.
'''
formats = self.__get_spec_formats(params.formats, sec_code, row_code)
catalog = self.__get_spec_catalog(params.catalogs, formats)
self._default = formats.get('default')
self._specs = set(self._expand(catalog))
def __get_spec_formats(self, formats, sec_code, row_code):
'''Определяем параметры для специфики указанной строки, раздела'''
return formats.get_spec_params(sec_code, row_code, self.key)
def __get_spec_catalog(self, catalogs, params):
'''Выбираем список специфик по имени справочника из параметров'''
return catalogs.get(params.get('dic'), {}).get('ids', [])
def _expand(self, dic):
'''Перебираем специфики. Простые специфики сразу возвращаем. Если
имеем диапазон, определяем индекс начальной и конечной специфик
из списка-справочника, итерируемся по определенному диапазону,
возвращая соответствующие специфики из списка-справочника
'''
for spec in self._specs:
if '-' in spec:
start, end = spec.split('-')
for i in range(dic.index(start.strip()),
dic.index(end.strip()) + 1):
yield dic[i]
else:
yield spec | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/control/parser/specific.py | 0.678966 | 0.286581 | specific.py | pypi |
from itertools import chain
from collections import namedtuple
from ..parser import parser
from ..exceptions import (
ConditionExprError,
RuleExprError,
PrevPeriodNotImpl,
StopEvaluation
)
ControlParams = namedtuple('ControlParams', ('is_rule',
'formats',
'catalogs',
'dimension',
'precision',
'fault'))
def wrap_exc(f):
def wrapper(*args, **kwargs):
try:
return f(*args, **kwargs)
except StopEvaluation:
return []
return wrapper
class FormulaInspector:
def __init__(self, control, *, formats, catalogs, dimension, skip_warns):
self._skip_warns = skip_warns
self.formats = formats
self.catalogs = catalogs
self.dimension = dimension
self.id = control.attrib['id']
self.name = control.attrib['name']
self.rule = control.attrib['rule'].strip()
self.condition = control.attrib['condition'].strip()
self.tip = int(control.attrib.get('tip', '1'))
self.fault = float(control.attrib.get('fault', '-1'))
self.precision = int(control.attrib.get('precision', '2'))
def __repr__(self):
return ('<FormulaInspector id={id} name={name} rule={rule} '
'condition={condition} fault={fault} '
'precision={precision}>').format(**self.__dict__)
def check(self, report):
if self._check_condition(report):
return self._check_rule(report)
return []
@wrap_exc
def _check_condition(self, report):
'''Проверка условия для выполнения контроля'''
if self.condition and not self._is_previous_period(self.condition):
evaluator = self.__parse(self.condition, ConditionExprError)
return not list(self.__check(report, evaluator, self.__params()))
return True
@wrap_exc
def _check_rule(self, report):
'''Проверка правила контроля'''
if self.rule and not self._is_previous_period(self.rule):
evaluator = self.__parse(self.rule, RuleExprError)
return self.__check(report, evaluator, self.__params(is_rule=True))
return []
def __params(self, is_rule=False):
'''Упаковка параметров для проверки в именованный кортеж'''
return ControlParams(is_rule,
self.formats,
self.catalogs,
self.dimension,
self.precision,
self.fault if is_rule else float(-1))
def __parse(self, formula, exc):
'''Парсинг формулы контроля'''
evaluator = parser.parse(formula)
if evaluator is None:
raise exc(self.id)
return evaluator
def __check(self, report, evaluator, params):
'''Выполнение проверки. Возвращает список проваленых проверок'''
results = evaluator.check(report, params)
return chain.from_iterable(result.controls for result in results)
def _is_previous_period(self, formula):
'''Проверка наличия в формуле элемента в двух фигурных скобках,
что говорит о том, что значение берётся за прошлый период.
Такой функционал пока неизвестно когда получится реализовать
'''
if '{{' in formula:
if self._skip_warns:
return True
else:
raise PrevPeriodNotImpl(self.id) | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/control/inspectors/formula.py | 0.587825 | 0.159152 | formula.py | pypi |
from ..base import AbstractValidator
from .inspectors import ValueInspector, SpecInspector
from .exceptions import (FormatError, DuplicateError, EmptyRowError,
EmptyColumnError, NoSectionReportError,
NoSectionTemplateError, NoRuleError)
class FormatValidator(AbstractValidator):
name = 'Проверка формата'
code = '3'
def __init__(self, schema):
self._schema = schema
self.errors = []
def __repr__(self):
return '<FormatValidator errors={errors}>'.format(**self.__dict__)
def validate(self, report):
try:
self._check_sections(report)
self._check_duplicates(report)
self._check_required(report)
self._check_format(report)
except FormatError as ex:
self.error(ex.msg, ex.code)
return not bool(self.errors)
def _check_sections(self, report):
'''Проверка целостности отчёта'''
report_sections = set(section.code for section in report.iter())
schema_sections = set(self._schema.dimension.keys())
for section in schema_sections - report_sections:
raise NoSectionReportError(section)
def _check_duplicates(self, report):
'''Проверка дубликатов строк'''
def __fmt_specs(specs):
return ' '.join(f's{i}={s}' for i, s in enumerate(specs, 1) if s)
for section in report.iter():
for row, counter in section.rows_counter.items():
if counter > 1:
row_code, *specs = row
if any(specs):
row_code = f'{row_code} {__fmt_specs(specs)}'
raise DuplicateError(section.code, row_code, counter)
def _check_required(self, report):
'''Проверка наличия обязательных к заполнению строк и значений'''
for sec_code, row_code, col_code in self._schema.required:
rows = list(report.get_section(sec_code).get_rows(row_code))
if not rows:
raise EmptyRowError(sec_code, row_code)
for row in rows:
if not row.get_column(col_code):
raise EmptyColumnError(sec_code, row_code, col_code)
def _check_format(self, report):
'''Проверка формата строк и значений в них'''
for section in report.iter():
for row in section.iter():
self.__check_row(section.code, row.code, row)
self.__check_cells(section.code, row.code, row)
def __check_row(self, sec_code, row_code, row):
'''Итерация по ожидаемым спецификам с их последующей проверкой'''
specs_map = self.__get_specs(sec_code)
for col_code, spec_idx in specs_map.items():
self.__check_format((sec_code, row_code, col_code),
SpecInspector, row, spec_idx, specs_map)
def __check_cells(self, sec_code, row_code, row):
'''Итерация по значениям строки с их последующей проверкой'''
for column in row.iter():
self.__check_format((sec_code, row_code, column.code),
ValueInspector, column.value)
def __check_format(self, coords, inspector_class, *args):
'''Инициализация инспектора, проверка'''
inspector = inspector_class(self.__get_format(*coords),
self._schema.catalogs)
inspector.check(coords, *args)
def __get_format(self, sec_code, row_code, col_code):
'''Возвращает словарь с условиями проверки'''
try:
return self._schema.formats[sec_code][row_code][col_code]
except KeyError:
raise NoRuleError(sec_code, row_code, col_code)
def __get_specs(self, sec_code):
'''Возвращает словарь со спецификами'''
try:
return self._schema.formats[sec_code]['specs']
except KeyError:
raise NoSectionTemplateError(sec_code) | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/format/format.py | 0.443962 | 0.173533 | format.py | pypi |
class FormatError(Exception):
pass
# ---
class NoSectionReportError(FormatError):
def __init__(self, sec_code):
self.code = '1'
self.msg = 'Раздел {} отсутствует в отчёте'.format(sec_code)
class DuplicateError(FormatError):
def __init__(self, sec_code, row_code, counter):
self.code = '2'
self.msg = ('Раздел {}, cтрока {} повторяется {} раз(а)'
.format(sec_code, row_code, counter))
class EmptyRowError(FormatError):
def __init__(self, sec_code, row_code):
self.code = '3'
self.msg = 'Раздел {}, строка {} не может быть пустой'.format(sec_code,
row_code)
class EmptyColumnError(FormatError):
def __init__(self, sec_code, row_code, col_code):
self.code = '4'
self.msg = ('Раздел {}, строка {}, графа {} не может быть пустой'
.format(sec_code, row_code, col_code))
class NoSectionTemplateError(FormatError):
def __init__(self, sec_code):
self.code = '5'
self.msg = 'Раздел {} не описан в шаблоне'.format(sec_code)
class NoRuleError(FormatError):
def __init__(self, sec_code, row_code, col_code):
self.code = '6'
self.msg = ('Раздел {}, строка {}, графа {}. '
'В шаблоне отсутствует правило для проверки этого поля'
.format(sec_code, row_code, col_code))
# ---
class SpecBaseError(FormatError):
def update(self, coords, spec):
self.msg = 'Раздел {}, строка {}, специфика {}. {}'.format(coords[0],
coords[1],
spec,
self.msg)
class SpecNotInDictError(SpecBaseError):
msg = 'Специфика отсутствует в справочнике'
code = '7'
class SpecValueError(SpecBaseError):
msg = 'Недопустмое значение'
code = '8'
# ---
class ValueBaseError(FormatError):
def update(self, coords):
self.msg = 'Раздел {}, строка {}, графа {}. {}'.format(*coords,
self.msg)
class ValueNotNumberError(ValueBaseError):
msg = 'Значение не является числом'
code = '9'
class ValueBadFormat(ValueBaseError):
msg = 'Число не соответствует формату'
code = '10'
class ValueLengthError(ValueBaseError):
msg = 'Длина строки больше допустимого'
code = '11'
class ValueNotInDictError(ValueBaseError):
msg = 'Значение отсутствует в справочнике'
code = '12'
class ValueNotInRangeError(ValueBaseError):
msg = 'Значение не входит в диапазон допустимых'
code = '13'
class ValueNotInListError(ValueBaseError):
msg = 'Значение не входит в список допустимых'
code = '14' | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/format/exceptions.py | 0.421314 | 0.192312 | exceptions.py | pypi |
from ..exceptions import (ValueBaseError, ValueNotNumberError, ValueBadFormat,
ValueNotInRangeError, ValueNotInListError,
ValueNotInDictError, ValueLengthError)
class ValueInspector:
def __init__(self, params, catalogs):
self._catalogs = catalogs
self.catalog = params.get('dic')
self.format = params.get('format')
self.vld_type = params.get('vldType')
self.vld_param = params.get('vld')
self.default = params.get('default')
self.format_funcs_map = {'N': self._is_num, 'C': self._is_chars}
def __repr__(self):
return ('<ValueInspector format={format} vld_type={vld_type} '
'vld_param={vld_param}>').format(**self.__dict__)
def _is_num(self, value, limits):
'''Проверка длины целой и дробной частей числового значения поля'''
try:
float(value)
except ValueError:
raise ValueNotNumberError()
value_parts = tuple(len(n) for n in value.split('.'))
if len(value_parts) == 1:
i_part_len, f_part_len = value_parts[0], 0
else:
i_part_len, f_part_len = value_parts[0], value_parts[1]
i_part_lim, f_part_lim = (int(n) for n in limits.split(','))
if not (i_part_len <= i_part_lim and f_part_len <= f_part_lim):
raise ValueBadFormat()
def _is_chars(self, value, limit):
'''Проверка длины символьного значения поля'''
if not len(value) <= int(limit):
raise ValueLengthError()
def check(self, coords, value):
try:
self.__check_format(value or self.default)
self.__check_value(value or self.default)
except ValueBaseError as ex:
ex.update(coords)
raise
def __check_format(self, value):
'''Разбор "формулы" проверки формата. Вызов метода проверки'''
alias, args = self.format.strip(' )').split('(')
format_check_func = self.format_funcs_map[alias]
format_check_func(value, args)
def __check_value(self, value):
if self.vld_type == '1':
self.__check_value_catalog(value)
elif self.vld_type == '2':
self.__check_value_range(value)
elif self.vld_type == '3':
self.__check_value_list(value)
def __check_value_catalog(self, value):
'''Проверка на вхождение в справочник'''
if value not in self._catalogs[self.catalog]['ids']:
raise ValueNotInDictError()
def __check_value_range(self, value):
'''Проверка на вхождение в диапазон'''
value = float(value)
start, end = (float(n) for n in self.vld_param.split('-'))
if not (value >= start and value <= end):
raise ValueNotInRangeError()
def __check_value_list(self, value):
'''Проверка на вхождение в список'''
if value not in self.vld_param.split(','):
raise ValueNotInListError() | /rosstat-flc-1.3.1.tar.gz/rosstat-flc-1.3.1/rosstat/validators/format/inspectors/value.py | 0.406744 | 0.212252 | value.py | pypi |
# rossum
[](https://pypi.python.org/pypi/rossum)
[](https://travis-ci.com/rossumai/rossum)
[](https://github.com/ambv/black)
[](https://codecov.io/gh/rossumai/rossum)
```
The elisctl package has been renamed to rossum.
You may want to uninstall elisctl before installing rossum.
```
**rossum** is a set of [tools for Rossum users](https://developers.rossum.ai/) that wrap
the [Rossum API](https://api.elis.rossum.ai/docs)
to provide an easy way to configure and customize a Rossum account programmatically. It is
the best buddy when it comes to making requests to Rossum API.
## Installation
See the [rossum setup tutorial](https://developers.rossum.ai/docs/setting-up-rossum-tool)
for detailed instructions.
### Windows
Download an installation file from
[GitHub releases](https://github.com/rossumai/rossum/releases).
Install it. And run it either from start menu or from command prompt.
### UNIX based systems
Install the package from PyPI:
```bash
pip install rossum
```
## Usage
### Python API Client Library
The **rossum** library can be used to communicate with Rossum API,
instead of using `requests` library directly. The advantages of using **rossum**:
* it contains a function that merges the paginated results into one list so the user does not need
to get results page by page and take care of their merging,
* it takes care of login and logout for the user,
* it includes many methods for frequent actions that you don't need to write by yourself from scratch,
* it includes configurable retry logic,
* in case the API version changes, the change will be implemented to the
library by Rossum for all the users.
To make any request to Rossum API, use `RossumClient()` class wrapper. You can use a Rossum
token to log in or use username and password. You need to either pass the credentials
including the URL directly to the client, or set `ROSSUM_URL` envvar and either a token
or `ROSSUM_USERNAME` and `ROSSUM_PASSWORD` envvars in your code. See the sample script
using **rossum** within a code to export the documents:
```python
import datetime
from rossum.lib.api_client import RossumClient
queue_id = 123456
username = "your_username"
password = "your_password"
endpoint = "https://api.elis.rossum.ai/v1"
def export_documents():
with RossumClient(context=None, user=username, password=password, url=endpoint) as client:
date_today = datetime.date.today()
date_end = date_today
date_start = date_today - datetime.timedelta(days=1)
response = client.get(
f"queues/{queue_id}/export?format=xml&"
f"exported_at_after={date_start.isoformat()}&"
f"exported_at_before={date_end.isoformat()}&"
f"ordering=exported_at&"
f"page_size=100&page=1"
)
if not response.ok:
raise ValueError(f"Failed to export: {response.status_code}")
if __name__ == "__main__":
export_documents()
```
### API Client command line tool
> :warning: CLI functionality is not actively developed anymore.
The **rossum** tool can be either used in a **command line interface** mode
by executing each command through `rossum` individually by passing it as an argument,
or in an **interactive shell** mode of executing `rossum` without parameters
and then typing the commands into the shown prompt.
Individual Rossum operations are triggered by passing specific *commands* to `rossum`.
Commands are organized by object type in a tree-like structure and thus are composed
of multiple words (e.g. `user create` or `schema transform`).
So either get the list of commands and execute them immediately such as:
```shell
rossum --help
rossum configure
```
or run the interactive shell by simply running
```shell
rossum
```
See the sample using **rossum** command line tool to create the main objects within an organization and
assign a user to a queue:
```shell
$ rossum configure
API URL [https://api.elis.rossum.ai]:
Username: your_username@company.com
Password:
$ rossum workspace create "My New Workspace"
12345
$ rossum queue create "My New Queue Via rossum" -s schema.json -w 12345 --email-prefix my-queue-email --bounce-email bounced-docs-here@company.com
50117, my-queue-email-ccddc6@elis.rossum.ai
$ rossum user create john.doe@company.com -q 50117 -g annotator -p my-secret-password-154568
59119, my-secret-password-154568
$ rossum user_assignment add -u 59119 -q 50117
```
## Configure profiles
To run commands described below under a chosen user, it is possible to use profiles defined by
configure function such as
```shell
rossum --profile profile_name configure
```
After defining necessary profiles and their credentials, the profile can be chosen the following way
```shell
rossum --profile profile_name queue list
```
## Edit Schema
Some of the most common advanced operations are related to setting up
the sidebar-describing schema according to business requirements. Using rossum
you can edit schema easily as a JSON or XLSX file.
List queues to obtain schema id:
```shell
$ rossum queue list
id name workspace inbox schema users
---- --------------------------- ----------- ---------------------------------------- -------- ----------------------
6 My Queue 1 6 myqueue-ab12ee@elis.rossum.ai 7 27
```
Download schema as a json:
```shell
rossum schema get 7 -O schema.json
```
Open the `schema.json` file in you favourite editor and upload modified version back to Rossum.
```shell
rossum schema update 7 --rewrite schema.json
```
You can also edit schema as an Excel (xlsx) file.
```shell
rossum schema get 7 --format xlsx -O schema.xlsx
rossum schema update 7 --rewrite schema.xlsx
```
From now on, documents will follow new schema. (Warning! If you don't use `--rewrite` option,
the new schema will receive a new id - obtain it by `queue list` again.)
## Schema Transformations
In addition, there is a scripting support for many common schema operations,
that may be easily used for schema management automation. See `rossum schema transform`
and `rossum tools` tools for further reference.
Run something like:
```shell
$ rossum schema transform substitute-options default_schema.json centre <( \
rossum tools xls_to_csv ~/Downloads/ERA_osnova_strediska.xlsx --header 0 --sheet 1 | rossum tools csv_to_options - ) \
| rossum schema transform substitute-options - gl_code <( \
rossum tools xls_to_csv ~/Downloads/ERA_osnova_strediska.xlsx --header 0 | rossum tools csv_to_options - ) \
| rossum schema transform remove - contract \
> era_schema.json
```
## License
MIT
## Contributing
* Use [`pre-commit`](https://pre-commit.com/#install) to avoid linting issues.
* Submit a pull request from forked version of this repo.
* Select any of the maintainers as a reviewer.
* After an approved review, when releasing, a `Collaborator` with `Admin` role shall do the following in `master` branch:
* Update the Changelog in README, describing all the changes included in the newest release
* run:
```bash
bump2version minor
git push
git push --tags
```
* In the end, to build a Windows installer, run:
```bash
pynsist installer.cfg
```
* Go to [releases](#https://github.com/rossumai/rossum/releases) and upload the newest .exe file from the
`.build` folder of your `rossum` repository to the newest release
## Changelog
### 2022-08-04 v3.15.0
* feat(.gitignore): ignore vscode
* feat(api_client): add email param for user creation
* feat(tox) add py39 test env
* ref(README) format file by linter
* build(pre-commit) update versions
### 2022-02-18 v3.14.0
* Ensure compatibility with click<8.1.0
### 2021-11-1 v3.13.1 and v3.13.2
* Update setup of the release process for pypi
### 2021-10-29 v3.13.0
* Add method for getting annotations
* Refactor sideloading functionality to enable sideloading of new objects
* Add sideloading option for get_paginated() method
### 2021-10-29 v3.12.1
* Propagate changelogs to the releases
### 2021-10-24 v3.12.0
* Allow sending new attributes to API when creating hooks
* Response is being propagated to the RossumException
* Added functions to iterate over hook payload easily
* Fix for library versioning due to incorrectly published tags
### 2021-09-06 v3.10.0
* Allow creation of inbox without passing bounce email
* Allow uploading documents by passing file as bytes to the API client
### 2021-04-18 v3.9.1
* Include tenacity library in the Windows build
### 2021-04-15 v3.9.0
* Allow filtering specific queue IDs when listing all user's queues
### 2021-04-06 v3.8.0
* Allow passing token_owner, test and run_after attributes when creating and changing hook objects
### 2021-04-01 v3.7.0
* Applied configurable retry mechanism to all requests done via rossum library
* Enable assigning annotator_limited role to user
### 2021-03-04 v3.6.0
* Allow setting rir_params for queues
### 2021-01-25 v3.5.0
* Allow setting custom timeout for APIClient requests
* Use openpyxl engine for xlsx files reading
* Apply minor code optimalization fixes
### 2020-11-16 v3.4.0
* Create password command
### 2020-11-11 v3.3.0
* Allow passing parameters when listing hooks
* Fix passing metadata when creating a workspace
### 2020-10-20 v3.2.1
* Remove Obsoletes-Dist
### 2020-10-20 v3.2.0
* Enable creating serverless functions
* Add method for creating workspaces
* Allow setting up sideloading on hooks
* Refactor _request_url() to allow custom logging
### 2020-09-29 v3.1.0
* Fix missing library in setup.py
* Remove references to old package names
* Update `setup.py`
### 2020-09-29 v3.0.0
* elisctl was renamed to rossum
### 2020-07-27 v2.10.1
* Fix attribute name for setting max token lifetime
### 2020-07-24 v2.10.0
* Add `schema list` command
* Fix `webhook change` command issue
* Remove `csv get` command
* Add example script for setting up a new organisation
* Enable assigning manager role to user
* Enable setting max token lifetime
* Catch ValueError when parsing schema in XLSX
* Fix Python3.8 support
### 2020-02-18 v2.9.0
* allow editing inbox attributes separately on queue-related commands
* add support for `can_collapse` in xlsx schema
* add sample usage of elisctl library in a Python code
* make queue option required on `user create`
### 2019-10-31 v2.8.0
* Add webhook command
* Allow creating and changing inbox properties on `queue change` command
### 2019-09-30 v2.7.1
* Improve documentation
### 2019-08-13 v2.7.0
* Add command `user_assignment` for bulk assignment of users to queues
* Change command `connector create`: `queue_id` parameter needs to be specified, if there is more than one queue in organization
* Support schema attribute `width` in XLSX schema format
* Fixed: booleans, in XLSX schema format, can be specified as boolean types
* Internal: filename can be specified in `ELISClient.upload_document`
### 2019-07-30 v2.6.0
* Enable passing custom filename with upload
### 2019-07-12 v2.5.0
* Add support for schema specified in XLSX when creating queue
* Remove the necessity to specify schema file type when uploading
* Fix XML and CSV formats of `elisctl document extract`
### 2019-07-09 v2.4.0
* Add support for can_export in xlsx schema format
* Add document command
### 2019-06-21 v2.3.1
* Fix: annotator cannot use `elisctl connector list` command
### 2019-06-13 v2.3.0
* Add connector command
### 2019-06-11 v2.2.1
* Update packages for windows build.
### 2019-06-03 v2.2.0
* Added support for [`--profile`](#configure-profiles) option to all `elisctl` commands
* Fix: remove extra whitespace in xlsx schema export/import
### 2019-04-02 v2.1.0
* Added support for `--output-file` to `elisctl tools` and `elisctl schema transform`
* Fix [Schema Transformations](#schema-transformations) description in README
### 2019-03-14 v2.0.1
* Fixed MS Windows application entry point (running elisctl from the start menu)
* Fixed parsing of boolean values in xlsx schema export/import
### 2019-03-14 v2.0.0
* Disable interpolation in config parsing, so that special characters are allowed in e.g. password
* Experimental support for schema modification using xlsx file format
* Allow to show help in schema transform add (backward incompatible change)
### 2019-03-08 v1.1.1
* Fixed bug with UnicodeDecodeError in `elisctl schema get ID -O file.json` on Windows
### 2019-03-03 v1.1.0
* Added support for python 3.6
* Added `User-Agent` header (`elisctl/{version} ({platform})`) for every request to ROSSUM API
* Improved error when login fails with the provided credentials
| /rossum-3.15.0.tar.gz/rossum-3.15.0/README.md | 0.483892 | 0.937096 | README.md | pypi |
from kedro.pipeline import Pipeline, node
from .nodes import *
def create_pipeline():
return Pipeline([
node(
func=create_features_targets,
inputs=dict(instances="instances",
target_ind_params="params:target_ind_params",
feature_ind_params="params:feature_ind_params",
lag_ind_params="params:lag_ind_params",
),
outputs=dict(features="features",
targets="targets"),
tags=["searching"]
),
node(
func=run_cross_validation,
inputs=dict(features="features",
targets="targets",
cv_search_params="params:cv_search_params",
search_params="params:search_params",
metrics="params:metrics",
),
outputs=dict(search_result="search_result"),
tags=["searching"]
),
node(
func=benchmark_best_model,
inputs=dict(features="features",
targets="targets",
best_params="params:best_params",
benchmark_cv_params="params:benchmark_cv_params",
metrics="params:metrics",
),
outputs=dict(benchmark_result="benchmark_result"),
tags=["benchmarking"]
),
node(
func=train_predict_best_params,
inputs=dict(instances="instances",
target_ind_params="params:target_ind_params",
feature_ind_params="params:feature_ind_params",
lag_ind_params="params:lag_ind_params",
best_params="params:best_params",
benchmark_cv_params="params:benchmark_cv_params"
),
outputs=dict(prediction_result="prediction_result"),
name="train_predict_best_params",
tags=["benchmarking"]
),
node(
func=create_alpha,
inputs=dict(instances="instances",
prediction_result="prediction_result",
),
outputs=dict(alphas="alphas"),
name="create_alphas",
tags=["benchmarking"]
),
node(
func=train_best_model,
inputs=dict(instances="instances",
target_ind_params="params:target_ind_params",
feature_ind_params="params:feature_ind_params",
lag_ind_params="params:lag_ind_params",
best_params="params:best_params",
last_train_len="params:last_train_len"
),
outputs=dict(best_model="best_model"),
name="training_name",
tags=["training"]
),
node(
func=inference_model,
inputs=dict(instances="instances", best_model="best_model", last_train_len="params:last_train_len"),
outputs="inference_result",
name="inference_userapp",
tags=["inference"]
)
]) | /rostam_pack-0.7-py3-none-any.whl/rostam_pack/pipelines/ml_app/pipeline.py | 0.72526 | 0.233903 | pipeline.py | pypi |
import pandas as pd
import logging
from moosir_feature.model_validations.basic_parameter_searcher import ParameterSearcher
from moosir_feature.model_validations.benchmarking import NaiveModel, run_benchmarking
from moosir_feature.model_validations.model_validator import CustomTsCv
from moosir_feature.transformers.managers.feature_manager import FeatureCreatorManager
from moosir_feature.model_validations.model_cv_runner import predict_on_cv
from moosir_feature.transformers.managers.settings import IndicatorTargetSettings, IndicatorFeatureSettings, \
IndicatorLagSettings
from sklearn.dummy import DummyRegressor
log = logging.getLogger(__name__)
def create_features_targets(instances: pd.DataFrame,
target_ind_params,
feature_ind_params,
lag_ind_params,
):
target_settings = IndicatorTargetSettings(**target_ind_params)
feature_ind_settings = [IndicatorFeatureSettings(**feature_ind_params)]
lag_ind_settings = [IndicatorLagSettings(**lag_ind_params)]
fc_mgr = FeatureCreatorManager(target_settings=target_settings,
feature_settings_list=feature_ind_settings,
lag_settings_list=lag_ind_settings)
features, targets, _ = fc_mgr.create_features_and_targets(instances=instances)
return dict(features=features, targets=targets)
def run_cross_validation(features: pd.DataFrame,
targets: pd.DataFrame,
cv_search_params: dict,
search_params: dict,
metrics: list
):
log.info("searching parameters and running cross validation")
searcher = ParameterSearcher()
estimator = DummyRegressor(strategy="mean")
search_result = searcher.run_parameter_search_multiple_cvs(X=features,
y=targets,
estimator=estimator,
cv_params=cv_search_params,
param_grid=search_params,
metrics=metrics,
)
return dict(search_result=search_result)
def benchmark_best_model(features: pd.DataFrame,
targets: pd.DataFrame,
best_params: dict,
benchmark_cv_params: dict,
metrics: list
):
best_model = DummyRegressor(**best_params)
models = [best_model, NaiveModel(targets=targets.copy(), look_back_len=1)]
cv = CustomTsCv(train_n=benchmark_cv_params["train_length"],
test_n=benchmark_cv_params["test_length"],
sample_n=len(features),
train_shuffle_block_size=benchmark_cv_params["train_shuffle_block_size"])
benchmark_result = run_benchmarking(models=models, targets=targets, features=features, cv=cv, metrics=metrics)
return dict(benchmark_result=benchmark_result)
def train_predict_best_params(instances: pd.DataFrame,
target_ind_params,
feature_ind_params,
lag_ind_params,
best_params,
benchmark_cv_params):
target_settings = IndicatorTargetSettings(**target_ind_params)
feature_ind_settings = [IndicatorFeatureSettings(**feature_ind_params)]
lag_ind_settings = [IndicatorLagSettings(**lag_ind_params)]
fc_mgr = FeatureCreatorManager(target_settings=target_settings,
feature_settings_list=feature_ind_settings,
lag_settings_list=lag_ind_settings)
features, targets, _ = fc_mgr.create_features_and_targets(instances=instances)
best_model = DummyRegressor(**best_params)
cv = CustomTsCv(train_n=benchmark_cv_params["train_length"],
test_n=benchmark_cv_params["test_length"],
sample_n=len(features),
train_shuffle_block_size=None)
prediction_result = predict_on_cv(model=best_model, features=features, targets=targets, cv=cv)
# print(prediction_result)
return dict(prediction_result=prediction_result)
def create_alpha(instances: pd.DataFrame, prediction_result: pd.DataFrame):
# todo: needs to be a package
alphas = prediction_result.copy()
alphas.columns = ["Signal"]
alphas = alphas[alphas.index.isin(prediction_result.index)]
alphas = pd.concat([alphas, instances], axis=1)
# todo: just dropped na
alphas = alphas.dropna()
print(alphas)
return dict(alphas=alphas)
def train_best_model(instances: pd.DataFrame,
target_ind_params,
feature_ind_params,
lag_ind_params,
best_params,
last_train_len: int):
target_settings = IndicatorTargetSettings(**target_ind_params)
feature_ind_settings = [IndicatorFeatureSettings(**feature_ind_params)]
lag_ind_settings = [IndicatorLagSettings(**lag_ind_params)]
fc_mgr = FeatureCreatorManager(target_settings=target_settings,
feature_settings_list=feature_ind_settings,
lag_settings_list=lag_ind_settings)
features, targets, _ = fc_mgr.create_features_and_targets(instances=instances)
best_model = DummyRegressor(**best_params)
best_model.fit(features, targets)
print("=" * 50)
print("here in train again")
print("=" * 50)
return dict(best_model=best_model)
def inference_model(instances: pd.DataFrame, best_model: DummyRegressor, last_train_len):
print(last_train_len)
result = best_model.predict(instances)
print("=" * 50)
print("here in inference!!!")
print("=" * 50)
return result | /rostam_pack-0.7-py3-none-any.whl/rostam_pack/pipelines/ml_app/nodes.py | 0.44348 | 0.158956 | nodes.py | pypi |
import argparse
import sys
from pathlib import Path
import yaml
from src.callbacks import get_callbacks, get_callbacks_pdb
from src.preprocessing import DataPreprocessor
from src.structurecontainer import StructureContainer
from src.visualization.visualizator import Visualizator
class LoadConfFile(argparse.Action):
def __call__(
self,
parser: argparse.ArgumentParser,
namespace: argparse.Namespace,
values: str,
option_string: str = None,
):
"""
Handling of conf file
:param parser: the argument parser itself
:param namespace: argument parser specific variable
:param values: value of conf argument
:param option_string: argument parser specific variable
:return: arguments in parser list format
"""
first_arg = sys.argv[1]
if first_arg == "-conf" or first_arg == "--configuration":
with open(values, "r") as f:
dictionary = yaml.full_load(f)
arguments = self.yaml_to_parser(dictionary)
parser.parse_args(arguments, namespace)
else:
raise Exception(
"Argument -conf or --configuration must be the first argument!"
)
@staticmethod
def yaml_to_parser(dictionary: dict):
"""
Transform the arguments from the yaml file format to the argument parser format
:param dictionary: arguments given in conf file
:return: arguemnts in parser format
"""
arguments = list()
if "o" in dictionary.keys():
arguments.append("-o")
arguments.append(str(dictionary["o"]))
if "output" in dictionary.keys():
arguments.append("--output")
arguments.append(str(dictionary["output"]))
if "hdf" in dictionary.keys():
arguments.append("--hdf")
arguments.append(str(dictionary["hdf"]))
if "csv" in dictionary.keys():
arguments.append("--csv")
arguments.append(str(dictionary["csv"]))
if "fasta" in dictionary.keys():
arguments.append("--fasta")
arguments.append(str(dictionary["fasta"]))
if "sep" in dictionary.keys():
arguments.append("--sep")
arguments.append(str(dictionary["sep"]))
if "uid_col" in dictionary.keys():
arguments.append("--uid_col")
arguments.append(str(dictionary["uid_col"]))
if "html_cols" in dictionary.keys():
arguments.append("--html_cols")
arguments.append(str(dictionary["html_cols"]))
if "pdb" in dictionary.keys():
arguments.append("--pdb")
arguments.append(str(dictionary["pdb"]))
if "json" in dictionary.keys():
arguments.append("--json")
arguments.append(str(dictionary["json"]))
if "reset" in dictionary.keys():
if dictionary["reset"]:
arguments.append("--reset")
if "pca" in dictionary.keys():
arguments.append("--pca")
if "tsne" in dictionary.keys():
arguments.append("--tsne")
if "iterations" in dictionary.keys():
arguments.append("--iterations")
arguments.append(str(dictionary["iterations"]))
if "perplexity" in dictionary.keys():
arguments.append("--perplexity")
arguments.append(str(dictionary["perplexity"]))
if "learning_rate" in dictionary.keys():
arguments.append("--learning_rate")
arguments.append(str(dictionary["learning_rate"]))
if "tsne_metric" in dictionary.keys():
arguments.append("--tsne_metric")
arguments.append(str(dictionary["tsne_metric"]))
if "n_neighbours" in dictionary.keys():
arguments.append("--n_neighbours")
arguments.append(str(dictionary["n_neighbours"]))
if "min_dist" in dictionary.keys():
arguments.append("--min_dist")
arguments.append(str(dictionary["min_dist"]))
if "metric" in dictionary.keys():
arguments.append("--metric")
arguments.append(str(dictionary["metric"]))
if "port" in dictionary.keys():
arguments.append("--port")
arguments.append(str(dictionary["port"]))
if "verbose" in dictionary.keys():
arguments.append("--verbose")
arguments.append(str(dictionary["verbose"]))
if "v" in dictionary.keys():
arguments.append("-v")
return arguments
class Parser:
def __init__(self):
(
self.output_d,
self.hdf_path,
self.csv_path,
self.fasta_path,
self.csv_sep,
self.uid_col,
self.html_cols,
self.pdb_d,
self.json_d,
self.reset,
self.conf,
self.pca_flag,
self.tsne_flag,
self.iterations,
self.perplexity,
self.learning_rate,
self.tsne_metric,
self.n_neighbours,
self.min_dist,
self.metric,
self.port,
self.verbose,
) = self._parse_args()
def get_params(self):
"""
:return: class parameters
"""
return (
self.output_d,
self.hdf_path,
self.csv_path,
self.fasta_path,
self.csv_sep,
self.uid_col,
self.html_cols,
self.pdb_d,
self.json_d,
self.reset,
self.conf,
self.pca_flag,
self.tsne_flag,
self.iterations,
self.perplexity,
self.learning_rate,
self.tsne_metric,
self.n_neighbours,
self.min_dist,
self.metric,
self.port,
self.verbose,
)
@staticmethod
def _parse_args():
"""
Creates and returns the ArgumentParser object
"""
# Instantiate the parser
parser = argparse.ArgumentParser(description="ProtSpace3D")
# Required argument
parser.add_argument(
"-o",
"--output",
required=False,
type=str,
help=(
"Name of the output folder where generated files will be"
" stored."
),
)
# Required argument
parser.add_argument(
"--hdf",
required=False,
type=str,
help=(
"Path to HDF5-file containing the per protein embeddings as a"
" key-value pair, aka UID-embedding"
),
)
# Required argument
parser.add_argument(
"--csv",
required=False,
type=str,
help=(
"Path to CSV-file containing groups/features by which the dots"
" in the 3D-plot are colored"
),
)
parser.add_argument(
"-f",
"--fasta",
required=False,
type=str,
help=(
"Path to fasta file containing the ID and the according"
" sequence."
),
)
# Optional argument
parser.add_argument(
"-conf",
"--configuration",
required=False,
type=str,
action=LoadConfFile,
help="Path to configuration file.",
)
# Optional argument
parser.add_argument(
"--sep",
required=False,
type=str,
default=",",
help="Separator of CSV file",
)
# Optional argument
parser.add_argument(
"--uid_col",
required=False,
type=int,
default=0,
help="CSV column index containing the unique identifiers",
)
# Optional argument
parser.add_argument(
"--html_cols",
required=False,
help=(
"CSV columns to be saved as html, either the column index(es)"
" or column name(s)."
),
nargs="+",
)
# Optional argument
parser.add_argument(
"--pdb",
required=False,
type=str,
help="Path the directory that holds the .pdb files.",
)
parser.add_argument(
"--json",
required=False,
type=str,
help="Path the directory that holds the .json files.",
)
# Optional argument
parser.add_argument(
"--reset",
required=False,
action="store_true",
help="Precomputed file df.csv is deleted and recalculated.",
)
# Optional argument
parser.add_argument(
"--pca",
required=False,
action="store_true",
help="PCA is initially used as dimensionality reduction",
)
# Optional argument
parser.add_argument(
"--tsne",
required=False,
action="store_true",
help="t-SNE is initially used as dimensionality reduction",
)
# Optional argument
parser.add_argument(
"--iterations",
required=False,
default=1000,
type=int,
help="t-SNE parameter n_iters, default: 1000",
)
# Optional argument
parser.add_argument(
"--perplexity",
required=False,
default=30.0,
type=float,
help="t-SNE parameter perplexity, default: 30.0",
)
# Optional argument
parser.add_argument(
"--learning_rate",
required=False,
default="auto",
help="t-SNE parameter learning_rate, default: auto",
)
# Optional argument
parser.add_argument(
"--tsne_metric",
required=False,
default="euclidean",
help="t-SNE parameter metric, default: euclidean",
)
# Optional argument
parser.add_argument(
"--n_neighbours",
required=False,
default=25,
type=int,
help="UMAP parameter n_neighbours, default: 25",
)
parser.add_argument(
"--min_dist",
required=False,
default=0.5,
type=float,
help="UMAP parameter min_dist, default: 0.5",
)
parser.add_argument(
"--metric",
required=False,
default="euclidean",
help="Metric used for UMAP calculation, default: euclidean",
)
parser.add_argument(
"--port",
required=False,
type=int,
default=8050,
help="Port on which the website is locally hosted.",
)
parser.add_argument(
"-v",
"--verbose",
required=False,
action="store_true",
help=(
"By setting the verbose parameter, the script prints its"
" internal operations."
),
)
args = parser.parse_args()
output_d = Path(args.output) if args.output is not None else None
hdf_path = Path(args.hdf) if args.hdf is not None else None
csv_path = Path(args.csv) if args.csv is not None else None
fasta_path = Path(args.fasta) if args.fasta is not None else None
csv_sep = args.sep
uid_col = args.uid_col
html_cols = args.html_cols
pdb_d = Path(args.pdb) if args.pdb is not None else None
json_d = Path(args.json) if args.json is not None else None
reset = args.reset
conf_file = args.configuration
pca_flag = args.pca
tsne_flag = args.tsne
iterations = args.iterations
perplexity = args.perplexity
learning_rate = args.learning_rate
tsne_metric = args.tsne_metric
n_neighbours = args.n_neighbours
min_dist = args.min_dist
metric = args.metric
port = args.port
verbose = args.verbose
return (
output_d,
hdf_path,
csv_path,
fasta_path,
csv_sep,
uid_col,
html_cols,
pdb_d,
json_d,
reset,
conf_file,
pca_flag,
tsne_flag,
iterations,
perplexity,
learning_rate,
tsne_metric,
n_neighbours,
min_dist,
metric,
port,
verbose,
)
def required_arguments_check(hdf_path: Path, output_d: Path):
"""
Checks whether the required arguments for the script are given after processing conf file and arguments
:param hdf_path: Path to the hdf file
:param output_d: Path to the output directory
:return: None
"""
if hdf_path is None or output_d is None:
if hdf_path is None and output_d is None:
raise Exception(
"hdf path and output directory must be given either in config"
" file or as argument!"
)
elif hdf_path is None:
raise Exception(
"hdf path must be given either in config file or as argument!"
)
else:
raise Exception(
"output directory must be given either in config file or as"
" argument!"
)
def setup():
"""
Handles the process of the application
:return: app & html_flag
"""
# Create Application object
parser = Parser()
# Parse arguments
(
output_d,
hdf_path,
csv_path,
fasta_path,
csv_sep,
uid_col,
html_cols,
pdb_d,
json_d,
reset,
conf,
pca_flag,
tsne_flag,
iterations,
perplexity,
learning_rate,
tsne_metric,
n_neighbours,
min_dist,
metric,
port,
verbose,
) = parser.get_params()
required_arguments_check(hdf_path, output_d)
dim_red = "UMAP"
if pca_flag:
dim_red = "PCA"
elif tsne_flag:
dim_red = "TSNE"
# put UMAP parameters in dictionary
umap_paras = dict()
umap_paras["n_neighbours"] = n_neighbours
umap_paras["min_dist"] = min_dist
umap_paras["metric"] = metric
# Put TSNE parameters in dictionary
tsne_paras = dict()
tsne_paras["iterations"] = iterations
tsne_paras["perplexity"] = perplexity
tsne_paras["learning_rate"] = learning_rate
tsne_paras["tsne_metric"] = tsne_metric
# Create data preprocessor object
data_preprocessor = DataPreprocessor(
output_d,
hdf_path,
csv_path,
fasta_path,
csv_sep,
uid_col,
html_cols,
reset,
dim_red,
umap_paras,
tsne_paras,
verbose,
)
# Preprocessing
(
df,
fig,
csv_header,
original_id_col,
embeddings,
embedding_uids,
distance_dic,
fasta_dict,
) = data_preprocessor.data_preprocessing()
# initialize structure container if flag set
structure_container = StructureContainer(pdb_d, json_d)
# Create visualization object
visualizator = Visualizator(fig, csv_header, dim_red)
# get ids of the proteins
if original_id_col is not None:
ids = original_id_col
else:
ids = df.index.to_list()
umap_paras_dict = data_preprocessor.get_umap_paras_dict(df)
tsne_paras_dict = data_preprocessor.get_tsne_paras_dict(df)
# --- APP creation ---
if structure_container.pdb_flag:
application = visualizator.get_pdb_app(ids, umap_paras, tsne_paras)
else:
application = visualizator.get_base_app(umap_paras, tsne_paras, ids)
return (
application,
True if html_cols is not None else False,
df,
structure_container,
original_id_col,
dim_red,
umap_paras,
umap_paras_dict,
tsne_paras,
tsne_paras_dict,
output_d,
csv_header,
port,
embeddings,
embedding_uids,
distance_dic,
fasta_dict,
)
def main():
"""
Most general processing of the script
:return: None
"""
(
app,
html,
df,
struct_container,
orig_id_col,
dim_red,
umap_paras,
umap_paras_dict,
tsne_paras,
tsne_paras_dict,
output_d,
csv_header,
port,
embeddings,
embedding_uids,
distance_dic,
fasta_dict,
) = setup()
# don't start server if html is needed
if not html:
# different callbacks for different layout
if struct_container.pdb_flag:
get_callbacks(
app,
df,
orig_id_col,
umap_paras,
tsne_paras,
output_d,
csv_header,
embeddings,
embedding_uids,
distance_dic,
umap_paras_dict,
tsne_paras_dict,
fasta_dict,
struct_container,
)
get_callbacks_pdb(app, df, struct_container, orig_id_col)
else:
get_callbacks(
app,
df,
orig_id_col,
umap_paras,
tsne_paras,
output_d,
csv_header,
embeddings,
embedding_uids,
distance_dic,
umap_paras_dict,
tsne_paras_dict,
fasta_dict,
struct_container,
)
app.run_server(debug=True, port=port)
if __name__ == "__main__":
main() | /rostspace-0.1.1-py3-none-any.whl/src/app.py | 0.418222 | 0.165559 | app.py | pypi |
import sys
from colorsys import hls_to_rgb
import numpy as np
import pandas as pd
import plotly.graph_objects as go
from matplotlib import cm
from pandas import DataFrame
from .base import init_app
from .pdb import init_app_pdb
class Visualizator:
SYMBOLS = [
"circle",
"square",
"diamond",
"cross",
"circle-open",
"diamond-open",
"square-open",
]
def __init__(self, fig: go.Figure, csv_header: list[str], dim_red: str):
self.fig = fig
self.csv_header = csv_header
self.dim_red = dim_red
@staticmethod
def n_symbols_equation(n: int):
"""
Output is the number of symbols used based on the number of groups
:param n: number of groups
:return: number of symbols
"""
if n <= 8:
return 1
elif n <= 11:
return 2
elif n <= 15:
return 3
elif n <= 20:
return 4
elif n <= 26:
return 5
elif n <= 33:
return 6
else:
return 7
@staticmethod
def n_samples_equation(n: int, val_range: int) -> float:
"""
Output is the range in which saturation and luminositiy of the coloring are picked,
dependent on the number of groups. The underlying equation is (x-10)/(x+10).
:param n: number of groups
:param val_range: maximal range
:return: calculated range
"""
numerator = n - 10
denominator = n + 10
res = numerator / denominator
if res < 0:
res = 0
res_range = res * val_range
return res_range
@staticmethod
def gen_distinct_colors(n: int, sort: bool = True):
"""
Creates are list in rgb format that holds the most distinct colors for the number of groups.
:param n: number of groups
:param sort: Whether colors should be sorted or not.
:return: list with colors
"""
color_list = list()
np.random.seed(42)
hues = np.arange(0, 360, 360 / n)
hues = hues[np.random.permutation(hues.size)]
for hue in hues:
# default saturation is 100 and range from 100-50
standard_sat = 100
sat_range = Visualizator.n_samples_equation(n, val_range=50)
saturation = standard_sat - np.random.ranf() * sat_range
# default luminosity is 50 and range from 35-65
standard_lum = 50
lum_range = Visualizator.n_samples_equation(n, val_range=30)
luminosity = (
standard_lum - lum_range / 2
) + np.random.ranf() * lum_range
# color list in hls style
color_list.append(
tuple([hue / 360, luminosity / 100, saturation / 100])
)
if sort:
color_list.sort()
# round small values, otherwise dash has difficulties to display
rgb_list = []
for h, l, s in color_list:
# Also convert to rgb values
rgb = hls_to_rgb(round(h, 2), round(l, 2), round(s, 2))
# change value range from 0-1 to 0-255, otherwise saturation=100 is black
rgb = list(rgb)
for idx, value in enumerate(rgb):
rgb[idx] = value * 255
rgb = tuple(rgb)
rgb_list.append(rgb)
return rgb_list
@staticmethod
def handle_colorbar(
col_groups: list,
fig: go.Figure,
n_symbols: int,
color_list: list,
two_d: bool,
):
"""
Creates a colorbar trace for the plot if only numeric values are in the group.
:param col_groups: the column groups
:param fig: the graph figure
:param n_symbols: number of different symbols to be displayed.
:param color_list: list with the different colors to be displayed.
:param two_d: if True graph should be displayed in 2D
:return: flag whether only numeric values are in the column and number of symbols to be used
"""
numeric_flag = False
if all(
[
isinstance(item, int) or isinstance(item, float)
for item in col_groups
]
):
# Only numeric values and np.nan in the group
numeric_flag = True
# Only one symbol to be used
n_symbols = 1
# Find min and max value of the group, excluding np.nan
min_val = sys.float_info.max
max_val = sys.float_info.min
for item in col_groups:
if (
isinstance(item, int)
or isinstance(item, float)
and not pd.isna(item)
):
if min_val > item:
min_val = item
if max_val < item:
max_val = item
if np.nan in col_groups:
no_na_len = len(col_groups) - 1
else:
no_na_len = len(col_groups)
viridis = cm.get_cmap("viridis", no_na_len)
color_list = list()
for i in range(len(col_groups)):
# change rgba to rgb and range of values from 0-1 to 0-255
rgba_tuple = viridis(i)
rgba_list = list(rgba_tuple)
red = rgba_list[0] * 255
green = rgba_list[1] * 255
blue = rgba_list[2] * 255
rgb_list = [red, green, blue]
rgb_tuple = tuple(rgb_list)
color_list.append(rgb_tuple)
# Use plotly Viridis as colorscale
colorscale = list()
for col in color_list:
colorscale.append(f"rgb{col}")
# create colorbar
colorbar = dict(
title="Colorbar",
lenmode="fraction",
len=0.5,
yanchor="bottom",
ypad=50,
)
# create and add a dummy trace that holds the colorbar
if not two_d:
color_trace = go.Scatter3d(
x=[None],
y=[None],
z=[None],
mode="markers",
marker=dict(
colorscale=colorscale,
showscale=True,
colorbar=colorbar,
cmin=min_val,
cmax=max_val,
),
showlegend=False,
)
else:
color_trace = go.Scatter(
x=[None],
y=[None],
mode="markers",
marker=dict(
colorscale=colorscale,
showscale=True,
colorbar=colorbar,
cmin=min_val,
cmax=max_val,
),
showlegend=False,
)
fig.add_trace(color_trace)
return numeric_flag, n_symbols, color_list
@staticmethod
def customize_axis_titles(
dim_red: str, fig: go.Figure, df: DataFrame, two_d: bool
):
"""
Axis titles are edited dependent on dimensionality reduction (UMAP or PCA)
:param dim_red: to be displayed dimensionality reduction
:param fig: graph figure
:param df: dataframe with all the data
:return: None
"""
if dim_red == "UMAP" or dim_red == "TSNE":
if not two_d:
fig.update_layout(
# Remove axes ticks and labels as they are usually not informative
scene=dict(
xaxis=dict(
showticklabels=False, showspikes=False, title=""
),
yaxis=dict(
showticklabels=False, showspikes=False, title=""
),
zaxis=dict(
showticklabels=False, showspikes=False, title=""
),
),
)
else:
fig.update_xaxes(showticklabels=False)
fig.update_yaxes(showticklabels=False)
else:
# extract variance column
unique_variance_column = df["variance"].unique().tolist()
pca_variance = list()
for value in unique_variance_column:
if not pd.isna(value):
pca_variance.append(value)
# Sort descending since the first component of PCA has more variance than the second and so on
pca_variance.sort(reverse=True)
if not two_d:
fig.update_layout(
# Remove axes ticks and labels as they are usually not informative
scene=dict(
xaxis=dict(
showticklabels=False,
showspikes=False,
title=f"PC1 ({float(pca_variance[0]):.1f}%)",
),
yaxis=dict(
showticklabels=False,
showspikes=False,
title=f"PC2 ({float(pca_variance[1]):.1f}%)",
),
zaxis=dict(
showticklabels=False,
showspikes=False,
title=f"PC3 ({float(pca_variance[2]):.1f}%)",
),
),
)
else:
fig.update_xaxes(
showticklabels=False,
title_text=f"PC1 ({float(pca_variance[0]):.1f}%)",
)
fig.update_yaxes(
showticklabels=False,
title_text=f"PC2 ({float(pca_variance[1]):.1f}%)",
title_standoff=0,
)
@staticmethod
def handle_title(
dim_red: str, umap_paras: dict, tsne_paras: dict, fig: go.Figure
):
"""
Sets up the title of the graph depending on the dimensionality reduction (UMAP or PCA)
:param dim_red: to be displayed dimensionality reduction
:param umap_paras: parameters of the UMAP calculation
:param tsne_paras: parameters of the TSNE calculation
:param fig: graph figure
:return: None
"""
# Update title
if dim_red == "UMAP":
title = (
"UMAP"
+ f"<br>n_neighbours: {umap_paras['n_neighbours']},"
f" min_dist: {umap_paras['min_dist']}, "
f"<br>metric: {umap_paras['metric']}"
)
elif dim_red == "PCA":
title = "PCA"
else:
title = (
"TSNE"
+ f"<br>iterations: {tsne_paras['iterations']}, perplexity:"
f" {tsne_paras['perplexity']}, <br>learning_rate:"
f" {tsne_paras['learning_rate']}, metric:"
f" {tsne_paras['tsne_metric']}"
)
fig.update_layout(
title={
"text": title,
"y": 0.98,
"x": 0.4,
}
)
@staticmethod
def update_layout(fig: go.Figure):
"""
Updates the layout of the graph figure. Margin, hoverinfo and legend positioning
:param fig: graph Figure
:return: None
"""
# Set legend in right upper corner of the plot
fig.update_layout(
legend=dict(yanchor="top", y=0.97, xanchor="right", x=0.99)
)
# change margins of the graph
fig.update_layout(margin=dict(l=1, r=1, t=1, b=1))
@staticmethod
# https://github.com/sacdallago/bio_embeddings/blob/develop/bio_embeddings/visualize/plotly_plots.py
def render(
df: DataFrame,
selected_column: str,
original_id_col: object,
umap_paras: dict,
tsne_paras: dict,
dim_red: str = "UMAP",
two_d: bool = False,
download: bool = False,
):
"""
Renders the plotly graph with the selected column in the dataframe df
:param df: dataframe
:param selected_column: column of the dataframe
:param original_id_col: the colum "original id" of the mapped csv file
:param umap_paras: dictionary holding the parameters of UMAP
:param dim_red: to be displayed dimensionality reduction
:param two_d: if True plot should be in 2D
:param download: boolean whether it is rendered for downloading or not
:return: plotly graphical object
"""
# custom separator to sort str, int and float (str case-insensitive)
# order: 1. int and float 2. str 3. rest 4. np.nan
def my_comparator(val):
if (
isinstance(val, float)
and not pd.isna(val)
or isinstance(val, int)
):
return 0, val
elif pd.isna(val):
return 3, val
elif isinstance(val, str):
val = val.lower()
return 1, val
else:
return 2, val
mapped_index = None
if original_id_col is not None:
# swap index
mapped_index = df.index
df.index = original_id_col
col_groups = df[selected_column].unique().tolist()
col_groups.sort(key=my_comparator)
# get nr of col groups without nan
if np.nan in col_groups:
n_col_groups = len(col_groups) - 1
else:
n_col_groups = len(col_groups)
color_list = Visualizator.gen_distinct_colors(n=n_col_groups)
# Figure out how many symbols to use depending on number of column groups
n_symbols = Visualizator.n_symbols_equation(n=n_col_groups)
fig = go.Figure()
numeric_flag, n_symbols, color_list = Visualizator.handle_colorbar(
col_groups, fig, n_symbols, color_list, two_d
)
df["class_index"] = np.ones(len(df)) * -100
if dim_red == "UMAP":
x = "x_umap"
y = "y_umap"
z = "z_umap"
elif dim_red == "PCA":
x = "x_pca"
y = "y_pca"
z = "z_pca"
else:
x = "x_tsne"
y = "y_tsne"
z = "z_tsne"
# iterate over different values of the selected column
for group_idx, group_value in enumerate(col_groups):
# Show only nan in legend if colorbar is shown
show_legend = True
if numeric_flag:
if not pd.isna(group_value):
show_legend = False
# set up opacity dependent on nan or not
if pd.isna(group_value):
opacity = 0.3
symbol = "circle"
color = "lightgrey"
else:
opacity = 1.0
symbol = Visualizator.SYMBOLS[group_idx % n_symbols]
color = f"rgb{color_list[group_idx]}"
# extract df with only group value
if not pd.isna(group_value):
df_group = df[df[selected_column] == group_value]
else:
df_group = df[df[selected_column].isna()]
if not two_d:
trace = go.Scatter3d(
x=df_group[x],
y=df_group[y],
z=df_group[z],
mode="markers",
name=group_value,
opacity=opacity,
marker=dict(
size=10,
color=color,
symbol=symbol,
line=dict(color="black", width=1),
),
text=df_group.index.to_list(),
showlegend=show_legend,
)
else:
trace = go.Scatter(
x=df_group[x],
y=df_group[y],
mode="markers",
name=group_value,
opacity=opacity,
marker=dict(
size=10,
color=color,
symbol=Visualizator.SYMBOLS[group_idx % n_symbols],
line=dict(color="black", width=1),
),
text=df_group.index.to_list(),
showlegend=show_legend,
)
fig.add_trace(trace)
# Give the different group values a number
df.loc[
df[selected_column] == group_value, "class_index"
] = group_idx
# Set hover-info
fig.update_traces(
hoverinfo=["name", "text"],
hoverlabel=dict(namelength=-1),
hovertemplate="%{text}",
)
if not two_d:
Visualizator.update_layout(fig)
else:
if not download:
# Safe space for displaying info toast and nearest neighbour
fig.update_layout(margin=dict(l=370))
Visualizator.handle_title(dim_red, umap_paras, tsne_paras, fig)
Visualizator.customize_axis_titles(dim_red, fig, df, two_d)
# swap index again
if original_id_col is not None:
df.index = mapped_index
return fig
def get_base_app(
self, umap_paras: dict, tsne_paras: dict, original_id_col: list
):
"""
Initializes the dash app in base.py
:param umap_paras: Parameters of the UMAP calculation
:param tsne_paras: Parameters of the TSNE calculation
:param original_id_col: list with the original IDs
:return: the application layout
"""
return init_app(
umap_paras,
self.csv_header,
self.fig,
self.dim_red,
tsne_paras,
original_id_col,
)
def get_pdb_app(
self, orig_id_col: list[str], umap_paras: dict, tsne_paras: dict
):
"""
Initializes the dash app in pdb.py
:param orig_id_col: List of the original IDs
:param umap_paras: Parameters of the UMAP calculation
:param tsne_paras: Parameters of the TSNE calculation
:return: the application layout
"""
return init_app_pdb(
orig_id_col,
umap_paras,
self.csv_header,
self.fig,
self.dim_red,
tsne_paras,
) | /rostspace-0.1.1-py3-none-any.whl/src/visualization/visualizator.py | 0.632049 | 0.375535 | visualizator.py | pypi |
import dash_bootstrap_components as dbc
import plotly.graph_objects as go
from dash import Dash, dcc, html
metric_options = [
"euclidean",
"cosine",
"manhattan",
"chebyshev",
"minkowski",
"canberra",
"braycurtis",
"haversine",
"mahalanobis",
"wminkowski",
"seuclidean",
"correlation",
"hamming",
"jaccard",
"dice",
"russellrao",
"kulsinski",
"rogerstanimoto",
"sokalmichener",
"sokalneath",
"yule",
]
main_button_style = {
"margin-top": "5px",
"margin-bottom": "5px",
"margin-right": "15px",
}
help_modal_icon_style = {
"position": "relative",
"bottom": "8px",
}
def get_app():
"""
Initializes dash application
:return: application
"""
app = Dash(
__name__,
external_stylesheets=[dbc.themes.BOOTSTRAP, dbc.icons.BOOTSTRAP],
)
return app
def init_app(
umap_paras: dict,
csv_header: list[str],
fig: go.Figure,
dim_red: str,
tsne_paras: dict,
original_id_col: list,
):
"""
Set up the layout of the application
:return: application
"""
app = get_app()
app.layout = dbc.Container(
[
# get all side components like header, toasts etc
get_side_components(app),
# modal with disclaimer that opens on startup
get_disclaimer_modal(),
# graph and controls
dbc.Row(
[
dbc.Col(
get_graph_container(
umap_paras,
False,
csv_header,
fig,
dim_red,
tsne_paras,
original_id_col,
),
width=12,
),
]
),
],
fluid=True,
)
return app
def get_side_components(app: Dash):
"""
Collection of side components like header, toasts etc. shared by normal and pdb app
:param app: the Dash application
:return: side components in a html Div object
"""
side_components = html.Div(
children=[
# Header
get_header(app),
# Storage to save the clicked on molecule in the graph,
# needed for replacing the clicked molecule in the list
dcc.Store(id="clicked_mol_storage"),
# toast that is displayed if a html file is created
get_download_toast(),
# Toasts in container, so they stack below each other...
dbc.Container(
[
# toast that displays the information of a selected protein
get_info_toast(),
html.Br(),
# toast that displays the nearest neighbours of the selected points
get_neighbour_toast(),
],
style={
"position": "fixed",
"top": 166,
"left": 10,
"width": 350,
},
),
]
)
return side_components
def get_graph_offcanvas(
umap_paras: dict,
umap_paras_string: str,
dim_red: str,
tsne_paras: dict,
tsne_paras_string: str,
):
"""
Creates layout of the offcanvas for the graph.
:param umap_paras: Parameters of the UMAP calculation
:param umap_paras_string: UMAP parameters in string format.
:param dim_red: the initial dimensionality reduction
:param tsne_paras: Parameters of the TSNE calculation
:return: graph offcanvas layout
"""
offcanvas = dbc.Offcanvas(
id="graph_offcanvas",
is_open=False,
title="Graph settings",
style={"width": "50%", "max-width": "600px"},
placement="end",
children=[
dbc.Spinner(
children=[
html.Div(
id="load_umap_spinner",
hidden=True,
)
],
fullscreen=True,
delay_show=80,
),
dcc.Markdown("Download"),
dbc.Button(
"Download all files",
id="button_graph_all",
color="dark",
outline=True,
),
html.Br(),
html.Br(),
dcc.Markdown("Dimensions"),
dbc.RadioItems(
options=[
{"label": "3D", "value": "3D"},
{"label": "2D", "value": "2D"},
],
value="3D",
id="dim_radio",
inline=True,
),
html.Br(),
# dbc.Switch(
# id="nearest_neighbours_switch",
# label="Display nearest neighbours",
# value=False,
# disabled=True,
# ),
# html.Br(),
dbc.Switch(
id="correlation_collapse_switch",
label="Display correlation scores",
value=False,
),
html.Br(),
dcc.Markdown("Dimensionality reduction"),
dbc.Tabs(
id="dim_red_tabs",
children=[
dbc.Tab(
label="UMAP",
tab_id="UMAP",
children=[
html.Br(),
dbc.Row(
[
dbc.Col(
[
dcc.Markdown("n_neighbours:"),
dbc.Input(
id="n_neighbours_input",
type="number",
min=0,
step=1,
value=umap_paras[
"n_neighbours"
],
),
],
width=4,
),
dbc.Col(
[
dcc.Markdown("min_dist:"),
dbc.Input(
id="min_dist_input",
type="number",
min=0,
# Set max to 1 since min_dist must be less than or equal to spread,
# which is 1.0 by default and not changed
max=1,
step=0.1,
value=umap_paras["min_dist"],
),
],
width=4,
),
dbc.Col(
[
dcc.Markdown("metric:"),
dcc.Dropdown(
id="metric_input",
options=metric_options,
value=umap_paras["metric"],
),
],
width=4,
),
],
),
html.Br(),
dbc.Button(
"Recalculate UMAP",
id="umap_recalculation_button",
color="dark",
outline=True,
),
html.Br(),
html.Br(),
dcc.Dropdown(
id="last_umap_paras_dd",
value=umap_paras_string,
options=[umap_paras_string],
clearable=False,
searchable=False,
),
],
),
dbc.Tab(label="PCA", tab_id="PCA"),
dbc.Tab(
label="t-SNE",
tab_id="TSNE",
children=[
html.Br(),
dbc.Row(
children=[
dbc.Col(
children=[
dcc.Markdown("Iterations:"),
dbc.Input(
id="iterations_input",
type="number",
min=250,
step=10,
value=tsne_paras["iterations"],
),
],
width=4,
),
dbc.Col(
children=[
dcc.Markdown("Perplexity:"),
dbc.Input(
id="perplexity_input",
type="number",
min=1,
step=1,
value=tsne_paras["perplexity"],
),
],
width=4,
),
dbc.Col(
children=[
dcc.Markdown("Learning rate:"),
dbc.Input(
id="learning_rate_input",
min=1,
step=1,
value=tsne_paras[
"learning_rate"
],
),
],
width=4,
),
]
),
html.Br(),
dcc.Markdown("Metric:"),
dcc.Dropdown(
id="tsne_metric_input",
options=metric_options,
value=tsne_paras["tsne_metric"],
),
html.Br(),
dbc.Button(
"Recalculate t-SNE",
id="tsne_recalculation_button",
color="dark",
outline=True,
),
html.Br(),
html.Br(),
dcc.Dropdown(
id="last_tsne_paras_dd",
value=tsne_paras_string,
options=[tsne_paras_string],
clearable=False,
searchable=False,
),
],
),
],
active_tab=dim_red,
),
],
)
return offcanvas
def get_settings_button_tooltip(button_id: str):
"""
Returns the tooltip for the settings buttons
:param button_id: target button id the tooltip is to be displayed
:return: tooltip
"""
tooltip = dbc.Tooltip(
"Settings",
target=button_id,
placement="bottom",
)
return tooltip
def get_graph_download_button_tooltip(button_id: str):
"""
Returns the tooltip for the download graph button
:param button_id: target button id the tooltip is to be displayed
:return: tooltip
"""
tooltip = dbc.Tooltip(
"Graph download", target=button_id, placement="bottom"
)
return tooltip
def get_graph_container(
umap_paras: dict,
pdb: bool,
csv_header: list[str],
fig: go.Figure,
dim_red: str,
tsne_paras: dict,
original_id_col: list,
):
"""
Creates the layout for the graph Row
:param umap_paras: umap parameters
:param pdb: flag whether pdb layout is needed or not.
:param csv_header: headers of the csv file
:param fig: graph Figure
:param dim_red: initial dimensionality reduction
:param tsne_paras: TSNE parameters
:param original_id_col: list with the original IDs
:return: Layout of the offcanvas
"""
# UMAP parameters in string format
umap_paras_string = str(
str(umap_paras["n_neighbours"])
+ " ; "
+ str(umap_paras["min_dist"])
+ " ; "
+ umap_paras["metric"],
)
# TSNE parameters in string format
tsne_paras_string = str(
str(tsne_paras["iterations"])
+ " ; "
+ str(tsne_paras["perplexity"])
+ " ; "
+ str(tsne_paras["learning_rate"])
+ " ; "
+ str(tsne_paras["tsne_metric"])
)
# width sizing of the dropdown menu column and whether 2 dropdowns are above the graph or not
if pdb:
xs = 6
sm = 7
md = 8
xxl = 9
dropdown_s = dcc.Dropdown(
csv_header,
csv_header[0],
id="dd_menu",
style={"margin-top": "5px"},
)
else:
xs = 8
sm = 9
md = 10
xxl = 11
dropdown_s = dbc.Row(
children=[
dbc.Col(
children=[
dcc.Dropdown(
csv_header,
csv_header[0],
id="dd_menu",
style={"margin-top": "5px"},
),
],
width=6,
),
dbc.Col(
children=[
dcc.Dropdown(
id="molecules_dropdown",
options=original_id_col,
multi=True,
style={"margin-top": "5px"},
),
],
width=6,
),
],
)
graph_container = (
# Storage to save whether Highlighting circle is already displayed or not
dcc.Store(id="highlighting_bool", storage_type="memory", data=False),
# Storage to save last camera data (relayoutData)
dcc.Store(id="relayoutData_save", storage_type="memory", data={}),
get_graph_offcanvas(
umap_paras,
umap_paras_string,
dim_red,
tsne_paras,
tsne_paras_string,
),
get_settings_button_tooltip(button_id="graph_settings_button"),
get_graph_download_button_tooltip(button_id="graph_download_button"),
get_correlation_scores_collapse(),
dbc.Row(
children=[
dbc.Col(
[
dropdown_s,
],
xs=xs,
sm=sm,
md=md,
xxl=xxl,
),
dbc.Col(
xs=12 - xs,
sm=12 - sm,
md=12 - md,
xxl=12 - xxl,
children=[
dbc.Stack(
direction="horizontal",
children=[
dbc.Button(
"",
class_name="bi bi-download",
id="graph_download_button",
outline=True,
color="dark",
style=main_button_style,
),
dbc.Button(
"",
id="graph_settings_button",
class_name="bi bi-gear-wide-connected",
outline=True,
color="dark",
style=main_button_style,
),
],
),
],
),
],
),
dcc.Graph(
id="graph",
figure=fig,
clear_on_unhover=True,
style={
"width": "100%",
"height": "80vh",
},
responsive=True,
),
)
return graph_container
def get_correlation_scores_collapse():
collapse = dbc.Collapse(
id="correlation_collapse",
is_open=False,
style={"margin-top": "5px"}
)
return collapse
def get_disclaimer_modal():
"""
Layout for the modal (window) with the disclaimer displayed at startup of the website.
:return: Disclaimer layout modal
"""
modal = dbc.Modal(
[
dbc.ModalHeader(dbc.ModalTitle("Disclaimer"), close_button=False),
dbc.ModalBody(
children=[
dbc.Alert(
color="warning",
children=[
dcc.Markdown(
"""
This is the ProtSpace3D tool. There is no usage summary statistics provided by
the developers.
"""
),
dcc.Markdown(
"""
Considering the data collection in the background and the displayed in the web application,
the Python library Dash is used and liable.
"""
),
dcc.Markdown(
"""
Please refer to the policy of its developers Plotly: https://plotly.com/privacy/
for more information.
"""
),
],
)
]
),
dbc.ModalFooter(dbc.Button("Agree", id="disclaimer_modal_button")),
],
id="disclaimer_modal",
size="xl",
is_open=True,
backdrop="static",
)
return modal
def get_help_modal():
"""
Layout for the modal (window) with the help text.
:return: Help layout modal
"""
modal = dbc.Modal(
[
dbc.ModalHeader(dbc.ModalTitle("Help"), close_button=True),
dbc.ModalBody(
children=[
dbc.ListGroup(
children=[
dbc.ListGroupItem(
children=[
html.H4("Graph"),
html.Br(),
html.H5("Group Selection"),
html.P(
"Group selection is done by clicking on"
" the dropdown menu above the graph and"
" selecting the wanted group."
),
html.H5("Buttons"),
dbc.Stack(
direction="horizontal",
gap=3,
children=[
html.I(
className="bi bi-download",
style=help_modal_icon_style,
),
html.P(
"Download a html or png file of"
" the selected group."
),
],
),
dbc.Stack(
direction="horizontal",
gap=3,
children=[
html.I(
className=(
"bi bi-gear-wide-connected"
),
style=help_modal_icon_style,
),
html.P(
"Open the settings to the"
" graph."
),
],
),
html.H5("Navigation"),
html.B("Orbital rotation:"),
html.P(
"Click and hold the left mouse button."
),
html.B("Pan:"),
html.P(
"Click and hold the right mouse button."
),
html.B("Zoom:"),
html.P(
"Scrolling with the mouse wheel zooms"
" in and out while in the graph with"
" the cursor"
),
html.H5("Legend"),
html.P(
"By clicking on a group in the legend,"
" it is hidden. Clicking on a hidden"
" group shows it again."
),
html.P(
"Double click on a displayed group to"
" only show the selected group. Double"
" click again on it displays all"
" groups."
),
]
),
dbc.ListGroupItem(
children=[
html.H4("Molecule selection"),
html.P(
"The drop-down menu showing the selected moleulce(s), is located either right "
"to the group selection, or above the molecule viewer. This depends on whether "
"the molecule viewer section is displayed or not."
),
html.P(
"A molecule is selected by clicking on the corresponding data point "
"in the graph. The selected molecule is then listed in the corresponding "
"drop-down menu and indicated with a black circle in the graph. It can be "
"deselected by deleting the entry in the drop-down menu."
),
html.P(
"In the drop-down menu the selected molecule(s) are displayed. More can"
" be selected by opening the drop-down menu. By doing so the selected "
"molecules are indicated with a white circle. With the x next to the "
"molecule ID it can be deselected, and with the x on the right side of "
"the drop-down menu everything can be deselected at once."
),
]
),
dbc.ListGroupItem(
children=[
html.H4("Molecule viewer"),
html.Br(),
html.H5("Buttons"),
dbc.Stack(
direction="horizontal",
gap=3,
children=[
html.I(
className=(
"bi bi-arrow-counterclockwise"
),
style=help_modal_icon_style,
),
html.P(
"Reset the view of the molecule"
" viewer."
),
],
),
dbc.Stack(
direction="horizontal",
gap=3,
children=[
html.I(
className=(
"bi bi-gear-wide-connected"
),
style=help_modal_icon_style,
),
html.P(
"Open the settings to the"
" molecule viewer."
),
],
),
html.H5("Navigation"),
html.B("Orbital rotation:"),
html.P(
"Click and hold the left mouse button."
),
html.B("Pan:"),
html.P(
"Click and hold the right mouse button."
),
html.B("Zoom:"),
html.P(
"Scrolling with the mouse wheel zooms"
" in and out while in the graph with"
" the cursor"
),
]
),
]
)
]
),
],
id="help_modal",
size="xl",
is_open=False,
backdrop=True,
)
return modal
def get_download_toast():
"""
Layout for the toast (infobox) shown when downloading the graph as file.
:return: download toast layout
"""
toast = dbc.Toast(
"File(s) successfully saved in output folder!",
header="Download graph",
id="graph_download_toast",
is_open=False,
dismissable=True,
duration=4000,
style={
"position": "fixed",
"top": 66,
"left": 10,
"width": 350,
},
)
return toast
def get_info_toast():
"""
Layout for the toast (infobox) shown when clicking on a molecule in the graph.
:return: info toast layout
"""
toast = dbc.Toast(
children=[
html.Div(id="expanded_seq_div"),
html.Div(id="collapsed_seq_div"),
html.Button(id="expand_seq_button"),
html.Button(id="collapse_seq_button"),
html.Div(id="group_info_expanded_div"),
html.Div(id="group_info_collapsed_div"),
dbc.Button(id="group_info_expand_button"),
dbc.Button(id="group_info_collapse_button"),
],
id="info_toast",
is_open=False,
dismissable=True,
body_style={
"max-height": "35vh",
"overflow": "auto",
},
style={"width": 200},
header_style={"overflow": "auto"},
)
return toast
def get_neighbour_toast():
"""
Layout for the toast (window showing nearest neighbours) shown when clicking on a molecule in the graph.
:return: neihgbour toast layout
"""
toast = dbc.Toast(
id="neighbour_toast",
is_open=False,
dismissable=True,
body_style={
"max-height": "35vh",
"overflow": "auto",
},
)
return toast
def get_help_button_tooltip(button_id: str):
"""
Returns the tooltip for the help button
:param button_id: target button id the tooltip is to be displayed
:return: tooltip
"""
tooltip = dbc.Tooltip(
"Help",
target=button_id,
placement="left",
)
return tooltip
def get_header(app: Dash):
"""
Layout for the black header of the application
:param app: the application itself
:return: layout of the header
"""
header = dbc.Row(
[
dbc.Col(
dbc.Stack(
direction="horizontal",
gap=5,
children=[
html.H1("RostSpace", style={"color": "white"}),
dcc.Loading(
color="white",
style={},
children=[
html.Div(
id="load_graph_spinner",
hidden=True,
)
],
),
dcc.Loading(
color="white",
style={},
children=[
html.Div(
id="load_nearest_neighbours_spinner",
hidden=True,
)
],
),
dcc.Loading(
color="white",
style={},
children=[
html.Div(
id="load_correlation_scores_spinner",
hidden=True,
)
],
),
],
),
style={"background-color": "black"},
xxl=10,
xl=10,
lg=9,
md=9,
sm=7,
xs=7,
),
dbc.Col(
[
dbc.Button(
"",
id="help_button",
class_name="bi bi-question-lg",
color="dark",
style={
"margin-top": "10px",
"margin-bottom": "5px",
"margin-right": "20px",
"background-color": "black",
},
),
get_help_button_tooltip(button_id="help_button"),
get_help_modal(),
],
xxl=1,
xl=1,
lg=2,
md=2,
sm=3,
xs=3,
style={"background-color": "black"},
),
dbc.Col(
html.A(
[
html.Img(
src=app.get_asset_url("logo.png"),
alt="Rostlab-logo",
style={"height": "60px", "width": "60px"},
),
],
href="https://rostlab.org/",
target="_blank",
),
style={"background-color": "black"},
xxl=1,
xl=1,
lg=1,
md=1,
sm=2,
xs=2,
),
]
)
return header | /rostspace-0.1.1-py3-none-any.whl/src/visualization/base.py | 0.632957 | 0.231072 | base.py | pypi |
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