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{
"filename": "posterior_ensemble.py",
"repo_name": "mackelab/sbi",
"repo_path": "sbi_extracted/sbi-main/sbi/utils/posterior_ensemble.py",
"type": "Python"
}
|
# This file is part of sbi, a toolkit for simulation-based inference. sbi is licensed
# under the Apache License Version 2.0, see <https://www.apache.org/licenses/>
import warnings
from typing import List, Optional, Union
from torch import Tensor
from torch.distributions import Distribution
from sbi.inference.posteriors.ensemble_posterior import EnsemblePosterior
from sbi.inference.posteriors.ensemble_posterior import (
EnsemblePotential as EnsemblePotentialMoved,
)
from sbi.sbi_types import TorchTransform
warnings.filterwarnings("default", category=DeprecationWarning, module=__name__)
warnings.warn(
"""
NeuralPosteriorEnsemble was renamed EnsemblePosterior and moved to
sbi.inference.posteriors.ensemble_posterior along with EnsemblePotential.
sbi.utils.posterior_ensemble will be deprecated in v0.24.
""",
DeprecationWarning,
stacklevel=2,
)
def NeuralPosteriorEnsemble(
posteriors: List,
weights: Optional[Union[List[float], Tensor]] = None,
theta_transform: Optional[TorchTransform] = None,
):
warnings.warn(
"NeuralPosteriorEnsemble was renamed EnsemblePosterior and moved to \
sbi.inference.posteriors.ensemble_posterior. sbi.utils.posterior_ensemble \
will be deprecated in v0.24.",
DeprecationWarning,
stacklevel=2,
)
return EnsemblePosterior(posteriors, weights, theta_transform)
def EnsemblePotential(
potential_fns: List,
weights: Tensor,
prior: Distribution,
x_o: Optional[Tensor],
device: str = "cpu",
):
warnings.warn(
"EnsemblePotential was moved to sbi.inference.posteriors.ensemble_posterior. \
sbi.utils.posterior_ensemble will be deprecated in v0.24.",
DeprecationWarning,
stacklevel=2,
)
return EnsemblePotentialMoved(potential_fns, weights, prior, x_o, device)
|
mackelabREPO_NAMEsbiPATH_START.@sbi_extracted@sbi-main@sbi@utils@posterior_ensemble.py@.PATH_END.py
|
{
"filename": "CONTRIBUTING.md",
"repo_name": "mperrin/poppy",
"repo_path": "poppy_extracted/poppy-master/CONTRIBUTING.md",
"type": "Markdown"
}
|
Please open a new issue or new pull request for bugs, feedback, or new features you would like to see. If there is an issue you would like to work on, please leave a comment and we will be happy to assist. New contributions and contributors are very welcome!
New to github or open source projects? If you are unsure about where to start or haven't used github before, please feel free to contact the package maintainers.
Feedback and feature requests? Is there something missing you would like to see? Please open an issue or send an email to the maintainers. This package follows the Spacetelescope [Code of Conduct](CODE_OF_CONDUCT.md) strives to provide a welcoming community to all of our users and contributors.
|
mperrinREPO_NAMEpoppyPATH_START.@poppy_extracted@poppy-master@CONTRIBUTING.md@.PATH_END.py
|
{
"filename": "FITSBeamInterpolator.py",
"repo_name": "ratt-ru/CubiCal",
"repo_path": "CubiCal_extracted/CubiCal-master/cubical/degridder/FITSBeamInterpolator.py",
"type": "Python"
}
|
# CubiCal: a radio interferometric calibration suite
# (c) 2017 Rhodes University & Jonathan S. Kenyon
# http://github.com/ratt-ru/CubiCal
# This code is distributed under the terms of GPLv2, see LICENSE.md for details
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from multiprocessing.sharedctypes import Value
from DDFacet.compatibility import range
import DDFacet.Data.ClassFITSBeam as DDFacetFITSBeam
import DDFacet.Data.ClassMS as DDFacetClassMS
import numpy
import os
import os.path
import sys
import pyrap.tables
import numpy as np
from cubical.tools import logger, ModColor
log = logger.getLogger("FITSBeamInterpolator")
dm = pyrap.measures.measures()
dq = pyrap.quanta
# This a list of the Stokes enums (as defined in casacore header measures/Stokes.h)
# These are referenced by the CORR_TYPE column of the MS POLARIZATION subtable.
# E.g. 5,6,7,8 corresponds to RR,RL,LR,LL
MS_STOKES_ENUMS = DDFacetFITSBeam.MS_STOKES_ENUMS
# set of circular correlations
CIRCULAR_CORRS = DDFacetFITSBeam.CIRCULAR_CORRS
# set of linear correlations
LINEAR_CORRS = DDFacetFITSBeam.LINEAR_CORRS
class DDFacetMSLite:
def __init__ (self,
field_centre,
chunk_ctr_frequencies,
chunk_channel_widths,
correlation_ids,
station_positions,
station_names):
"""
Standin object for the ClassMS visibility reader of DDFacet
field_centre: radian ra dec coordinate of the original field phase centre
chunk_ctr_frequencies: center channel frequencies (Hz) of chunk to predict E terms for
chunk_channel_widths: channel widths of chunk channels
correlation_ids: hand labels per correlation term as defined in casacore Stokes.h
station_positions: ECEF coordinates for stations (na, 3) array
station_names: Station names
"""
self.ChanFreq = chunk_ctr_frequencies
self.OriginalRadec = field_centre
self.ChanWidth = chunk_channel_widths
self.CorrelationNames = list(map(lambda x: MS_STOKES_ENUMS[x],
sorted(correlation_ids)))
self.StationNames = station_names
self.na = len(station_names)
self.StationPos = station_positions
self.rarad, self.decrad = self.OriginalRadec
if len(self.StationNames) != len(self.StationPos):
raise ValueError("StationNames should be the length of StationPos")
def radec2lm_scalar(self, *args, **kwargs):
return DDFacetClassMS.ClassMS.radec2lm_scalar(self, *args, **kwargs)
class FITSBeamInterpolator (object):
def __init__ (self,
field_centre,
chunk_ctr_frequencies,
chunk_channel_widths,
correlation_ids,
station_positions,
station_names,
opts):
"""
Proxy object for DDFacet.ClassFITSBeam
field_centre: radian ra dec coordinate of the original field phase centre
chunk_ctr_frequencies: center channel frequencies (Hz) of chunk to predict E terms for
chunk_channel_widths: channel widths of chunk channels
correlation_ids: hand labels per correlation term as defined in casacore Stokes.h
station_positions: ECEF coordinates for stations (na, 3) array
station_names: Station names
opts: beam opts as defined in Parset
"""
self.__ms = DDFacetMSLite(field_centre,
chunk_ctr_frequencies,
chunk_channel_widths,
correlation_ids,
station_positions,
station_names)
self.__opts = opts
self.__vbinterpolator = DDFacetFITSBeam.ClassFITSBeam(self.__ms, self.__opts)
for method in ('evaluateBeam', 'getFreqDomains', 'getBeamSampleTimes'):
setattr(self, method, getattr(self.__vbinterpolator, method))
|
ratt-ruREPO_NAMECubiCalPATH_START.@CubiCal_extracted@CubiCal-master@cubical@degridder@FITSBeamInterpolator.py@.PATH_END.py
|
{
"filename": "readme.md",
"repo_name": "logan-pearce/LOFTI",
"repo_path": "LOFTI_extracted/LOFTI-master/Using_Position_Vector/readme.md",
"type": "Markdown"
}
|
# LOFTI
#### Or: Logan's OFTI
This is my implementation of Orbits for the Impatient developed by Blunt et.al. 2017 (http://iopscience.iop.org/article/10.3847/1538-3881/aa6930/pdf). It was developed independantly from that group's efforts based on this paper.
This is the version of LOFTI that fits in 6-d phasespace, one observation of RA/Dec position, RA/Dec proper motions, and radial velocity. It is optimal for fitting wide binaries in Gaia, for example.
Repository contents:
Solving_for_orbital_elements_given_velocities.pdf outlines the math and the methodology used in the fit.
lofti_phasespace.py the script for fitting Gaia astrometry to the wide binary pair GK Tau and GI Tau.
lofti_plots.py script which generates the plots and statistical results of the fit.
The script included in this repository is for the wide binary system of GK and GI Tau, which doesn't include radial velocity, so both Z position and Zdot are unconstrained in the fit.
The orbits from the fit of GK - GI Tau
## Author
The project was completed by Logan Pearce (http://www.loganpearcescience.com), under the mentorship of Dr Adam Kraus at the University of Texas at Austin.
## Acknowledgments
This work has made use of data from the European Space Agency (ESA) mission Gaia (https://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Analysis Consortium (DPAC, https://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions participating in the Gaia Multilateral Agreement.
Software:
numpy, astropy, MySQL Connector/Python
|
logan-pearceREPO_NAMELOFTIPATH_START.@LOFTI_extracted@LOFTI-master@Using_Position_Vector@readme.md@.PATH_END.py
|
{
"filename": "example_script_m.py",
"repo_name": "wfirst-cgi/emccd_detect",
"repo_path": "emccd_detect_extracted/emccd_detect-master/emccd_detect/example_script_m.py",
"type": "Python"
}
|
# -*- coding: utf-8 -*-
"""Example script for EMCCDDetect calls."""
import os
import sys
from pathlib import Path
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from emccd_detect.emccd_detect import EMCCDDetect, emccd_detect
def imagesc(data, title=None, vmin=None, vmax=None, cmap='viridis',
aspect='equal', colorbar=True):
"""Plot a scaled colormap."""
fig, ax = plt.subplots()
im = ax.imshow(data, vmin=vmin, vmax=vmax, cmap=cmap, aspect=aspect,
origin='lower')
if title:
ax.set_title(title)
if colorbar:
fig.colorbar(im, ax=ax)
return fig, ax
# Set up some inputs here
here = os.path.abspath(os.path.dirname(__file__))
# Get fluxmap
fits_path_py = Path(here, 'data', 'sci_fluxmap.fits')
#fits_path_py = Path(here, 'data', 'ref_frame.fits')
def read_func(fits_path=fits_path_py,frametime=100, em_gain=5000.,
full_well_image=60000., # e-
full_well_serial=100000., # e-
#status=1,
dark_current=0.0028, # e-/pix/s
cic=0.02, # e-/pix/frame
read_noise=100., # e-/pix/frame
bias=10000., # e-
qe=0.9,
cr_rate=0., # hits/cm^2/s
pixel_pitch=13e-6, # m
eperdn=1, #7.,
nbits=64,#14,
numel_gain_register=604,
choice='legacy'
):
fluxmap = fits.getdata(fits_path).astype(float) # (photons/pix/s)
# Put fluxmap in 1024x1024 image section
full_fluxmap = np.zeros((1024, 1024)).astype(float)
full_fluxmap[0:fluxmap.shape[0], 0:fluxmap.shape[1]] = fluxmap
# For the simplest possible use of EMCCDDetect, use its defaults
# emccd = EMCCDDetect()
# Simulate only the fluxmap
# sim_sub_frame = emccd.sim_sub_frame(fluxmap, frametime)
# Simulate the full frame (surround the full fluxmap with prescan, etc.)
# sim_full_frame = emccd.sim_full_frame(full_fluxmap, frametime)
# For more control, each of the following parameters can be specified
# Custom metadata path, if the user wants to use a different metadata file
meta_path = Path(here, 'emccd_detect', 'util', 'metadata.yaml')
# Note that the defaults for full_well_serial and eperdn are specified in
# the metadata file
if choice=='latest':
emccd = EMCCDDetect(
em_gain=em_gain,
full_well_image=full_well_image, # e-
full_well_serial=full_well_serial, # e-
#status=status,
dark_current=dark_current, # e-/pix/s
cic=cic, # e-/pix/frame
read_noise=read_noise, # e-/pix/frame
bias=bias, # e-
qe=qe,
cr_rate=cr_rate, # hits/cm^2/s
pixel_pitch=pixel_pitch, # m
eperdn=eperdn,
nbits=nbits,
numel_gain_register=numel_gain_register,
meta_path=meta_path
)
# Simulate only the fluxmap
sim_sub_frame = emccd.sim_sub_frame(fluxmap, frametime)
#np. set_printoptions(threshold=np. inf)
#print(np.array(sim_sub_frame))
return sim_sub_frame
# Simulate the full frame (surround the full fluxmap with prescan, etc.)
#sim_full_frame = emccd.sim_full_frame(full_fluxmap, frametime)
# The class also has some convenience functions to help with inspecting the
# simulated frame
# Get a gain divided, bias subtracted frame in units of e-
# frame_e = emccd.get_e_frame(sim_full_frame)
# Return just the 1024x1024 region of a full frame
# image = emccd.slice_fluxmap(sim_full_frame)
# Return the prescan region of a full frame
# prescan = emccd.slice_prescan(sim_full_frame)
if choice=='legacy':
# For legacy purposes, the class can also be called from a functon wrapper
sim_old_style = emccd_detect(fluxmap=fluxmap,
frametime=frametime,
em_gain=em_gain,
full_well_image=full_well_image,
full_well_serial=full_well_serial,
#status=status,
dark_current=dark_current,
cic=cic,
read_noise=read_noise,
bias=bias,
qe=qe,
cr_rate=cr_rate,
pixel_pitch=pixel_pitch,
shot_noise_on=None)
#np. set_printoptions(threshold=np. inf)
#print(np.array(sim_old_style))
return sim_old_style
# Plot images
#imagesc(full_fluxmap, 'Input Fluxmap')
#imagesc(sim_sub_frame, 'Output Sub Frame')
#imagesc(sim_full_frame, 'Output Full Frame')
#plt.show()
#print(read_func())
#imagesc(read_func(choice='latest'), 'Latest')
#imagesc(read_func(choice='legacy'),'Legacy')
#plt.show()
if __name__ == '__main__':
imagesc(read_func(choice='latest'), 'Latest')
imagesc(read_func(choice='legacy'),'Legacy')
plt.show()
#args = sys.argv
# args[0] = current file
# args[1] = function name
# args[2:] = function args : (*unpacked)
#globals()[args[1]](*args[2:])
#imagesc(np.array([[1,0],[1,1]]))
#plt.show()
|
wfirst-cgiREPO_NAMEemccd_detectPATH_START.@emccd_detect_extracted@emccd_detect-master@emccd_detect@example_script_m.py@.PATH_END.py
|
{
"filename": "discriminator.py",
"repo_name": "xwzhang98/SREmulator",
"repo_path": "SREmulator_extracted/SREmulator-main/map2map/map2map/models/discriminator.py",
"type": "Python"
}
|
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from scipy.special import hyp2f1
from functools import partial
class Downsample(nn.Module):
def __init__(
self,
in_channels,
use_conv,
out_channels=None,
padding=0,
padding_mode="zeros",
):
"""_summary_
Args:
in_channels (int): _description_
use_conv (bool): _description_
out_channels (Optional[int], optional): _description_. Defaults to None.
padding (int, optional): _description_. Defaults to 0.
"""
super().__init__()
self.in_channels = in_channels
self.out_channels = out_channels or in_channels
self.use_conv = use_conv
if use_conv:
self.down = nn.Conv3d(
self.in_channels,
self.out_channels,
kernel_size=2,
stride=2,
padding=0,
)
else:
assert (
self.in_channels == self.out_channels
), "If not using conv, in and out channels must be the same"
self.down = nn.AvgPool3d(kernel_size=2, stride=2, padding=0)
def forward(self, x, style=None):
x = self.down(x)
return x
class ResBlockDown(nn.Module):
def __init__(self, in_chan, out_chan, padding, padding_mode):
super().__init__()
self.in_chan = in_chan
self.out_chan = out_chan
self.padding = padding
self.padding_mode = padding_mode
self.skip = nn.Conv3d(in_chan, out_chan, kernel_size=1, padding=0)
self.op_skip = Downsample(out_chan, use_conv=False)
self.main_block = nn.ModuleList(
[
nn.SiLU(),
nn.Conv3d(
in_chan,
out_chan,
kernel_size=3,
padding=padding,
padding_mode=padding_mode,
),
nn.SiLU(),
nn.Conv3d(
out_chan,
out_chan,
kernel_size=3,
padding=padding,
padding_mode=padding_mode,
),
]
)
self.op_main = Downsample(in_chan, use_conv=False)
def forward(self, x):
x_skip = self.skip(x)
x_skip = self.op_skip(x_skip)
for op in self.main_block:
x = op(x)
x = self.op_main(x)
x = x + x_skip
return x
class Discriminator(nn.Module):
def __init__(
self,
in_chan,
out_chan,
style_size=1,
base_chan=32,
padding=1,
padding_mode="zeros",
eul_scale_factor=2,
input_shape=128,
use_inv_shuffle=True,
cat_eul=True,
use_fourier=False,
**kwargs,
):
super().__init__()
self.in_chan = in_chan
self.out_chan = out_chan
self.style_size = style_size
self.base_chan = base_chan
self.padding = padding
self.padding_mode = padding_mode
self.eul_scale_factor = eul_scale_factor
self.use_inv_shuffle = use_inv_shuffle
self.cat_eul = cat_eul
self.cat_dens = False
self.use_fourier = use_fourier
self.lag2eul = Lagrangian2Eulerian(eul_scale_factor=eul_scale_factor)
self.head = nn.Conv3d(
in_chan + eul_scale_factor**3,
base_chan,
kernel_size=3,
padding=padding,
padding_mode=padding_mode,
)
self.resdown1 = ResBlockDown(base_chan, base_chan * 2, padding, padding_mode)
self.resdown2 = ResBlockDown(
base_chan * 2, base_chan * 4, padding, padding_mode
)
self.resdown3 = ResBlockDown(
base_chan * 4, base_chan * 8, padding, padding_mode
)
self.out = nn.Sequential(
nn.SiLU(),
nn.Conv3d(
base_chan * 8,
base_chan * 8,
kernel_size=1,
padding=padding,
padding_mode=padding_mode,
),
nn.SiLU(),
nn.Conv3d(
base_chan * 8,
1,
kernel_size=1,
padding=padding,
padding_mode=padding_mode,
),
)
def forward(self, x, style, cond=None):
eul = self.lag2eul(x[:, :3], a=np.float64(style))
eul = pixel_shuffle_3d_inv(eul, self.eul_scale_factor)
x = torch.cat([eul, x], dim=1)
if cond is not None:
x = torch.cat([x, cond], dim=1)
x = self.head(x)
x = self.resdown1(x)
x = self.resdown2(x)
x = self.resdown3(x)
x = self.out(x)
return x
class Lagrangian2Eulerian(nn.Module):
def __init__(
self,
eul_scale_factor=2,
eul_pad=0,
rm_dis_mean=True,
periodic=False,
dis_std=6.0, # in Mpc/h
boxsize=100.0, # in Mpc/h
meshsize=512,
inv_shuffle=False,
**kwargs,
):
super().__init__()
self.eul_scale_factor = eul_scale_factor
self.eul_pad = eul_pad
self.rm_dis_mean = rm_dis_mean
self.periodic = periodic
self.dis_norm_coeff = dis_std * meshsize / boxsize * eul_scale_factor
self.inv_shuffle = inv_shuffle
def forward(self, dis, val=1.0, a=1.0):
eul_scale_factor = self.eul_scale_factor
eul_pad = self.eul_pad
dis_norm = self.dis_norm_coeff * D_growth(a)
if self.rm_dis_mean:
dis_mean = sum(dis.mean((2, 3, 4), keepdim=True))
dtype, device = dis.dtype, dis.device
N, DHW = dis.shape[0], dis.shape[2:]
DHW = torch.Size([s * eul_scale_factor + 2 * eul_pad for s in DHW])
mesh = torch.zeros(N, 1, *DHW, dtype=dtype, device=device)
pos = (dis - dis_mean) * dis_norm
del dis
pos[:, 0] += torch.arange(
0.5, DHW[0] - 2 * eul_pad, eul_scale_factor, dtype=dtype, device=device
)[:, None, None]
pos[:, 1] += torch.arange(
0.5, DHW[1] - 2 * eul_pad, eul_scale_factor, dtype=dtype, device=device
)[:, None]
pos[:, 2] += torch.arange(
0.5, DHW[2] - 2 * eul_pad, eul_scale_factor, dtype=dtype, device=device
)
pos = pos.contiguous().view(N, 3, -1, 1)
intpos = pos.floor().to(torch.int)
neighbors = (
torch.arange(8, device=device)
>> torch.arange(3, device=device)[:, None, None]
) & 1
tgtpos = intpos + neighbors
del intpos, neighbors
kernel = (1.0 - torch.abs(pos - tgtpos)).prod(1, keepdim=True)
val = val * kernel
del kernel
tgtpos = tgtpos.view(N, 3, -1) # fuse spatial and neighbor axes
val = val.view(N, 1, -1)
bounds = torch.tensor(DHW, device=device)[:, None]
for n in range(N): # because ind has variable length
bounds = torch.tensor(DHW, device=device)[:, None]
if self.periodic:
torch.remainder(tgtpos[n], bounds, out=tgtpos[n])
ind = (tgtpos[n, 0] * DHW[1] + tgtpos[n, 1]) * DHW[2] + tgtpos[n, 2]
src = val[n]
if not self.periodic:
mask = ((tgtpos[n] >= 0) & (tgtpos[n] < bounds)).all(0)
ind = ind[mask]
src = src[:, mask]
mesh[n].view(1, -1).index_add_(1, ind, src)
return mesh
def pixel_shuffle_3d_inv(x, r):
"""
Rearranges tensor x with shape ``[B,C,H,W,D]``
to a tensor of shape ``[B,C*r*r*r,H/r,W/r,D/r]``.
"""
[B, C, H, W, D] = list(x.size())
x = x.contiguous().view(B, C, H // r, r, W // r, r, D // r, r)
x = x.permute(0, 1, 3, 5, 7, 2, 4, 6)
x = x.contiguous().view(B, C * (r**3), H // r, W // r, D // r)
return x
def D_growth(a, Om=0.31):
"""linear growth function for flat LambdaCDM, normalized to 1 at redshift zero"""
OL = 1 - Om
return (
a
* hyp2f1(1, 1 / 3, 11 / 6, -OL * a**3 / Om)
/ hyp2f1(1, 1 / 3, 11 / 6, -OL / Om)
)
|
xwzhang98REPO_NAMESREmulatorPATH_START.@SREmulator_extracted@SREmulator-main@map2map@map2map@models@discriminator.py@.PATH_END.py
|
{
"filename": "human.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/llms/human.py",
"type": "Python"
}
|
from typing import Any, Callable, List, Mapping, Optional
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models.llms import LLM
from pydantic import Field
from langchain_community.llms.utils import enforce_stop_tokens
def _display_prompt(prompt: str) -> None:
"""Displays the given prompt to the user."""
print(f"\n{prompt}") # noqa: T201
def _collect_user_input(
separator: Optional[str] = None, stop: Optional[List[str]] = None
) -> str:
"""Collects and returns user input as a single string."""
separator = separator or "\n"
lines = []
while True:
line = input()
if not line:
break
lines.append(line)
if stop and any(seq in line for seq in stop):
break
# Combine all lines into a single string
multi_line_input = separator.join(lines)
return multi_line_input
class HumanInputLLM(LLM):
"""User input as the response."""
input_func: Callable = Field(default_factory=lambda: _collect_user_input)
prompt_func: Callable[[str], None] = Field(default_factory=lambda: _display_prompt)
separator: str = "\n"
input_kwargs: Mapping[str, Any] = {}
prompt_kwargs: Mapping[str, Any] = {}
@property
def _identifying_params(self) -> Mapping[str, Any]:
"""
Returns an empty dictionary as there are no identifying parameters.
"""
return {}
@property
def _llm_type(self) -> str:
"""Returns the type of LLM."""
return "human-input"
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> str:
"""
Displays the prompt to the user and returns their input as a response.
Args:
prompt (str): The prompt to be displayed to the user.
stop (Optional[List[str]]): A list of stop strings.
run_manager (Optional[CallbackManagerForLLMRun]): Currently not used.
Returns:
str: The user's input as a response.
"""
self.prompt_func(prompt, **self.prompt_kwargs)
user_input = self.input_func(
separator=self.separator, stop=stop, **self.input_kwargs
)
if stop is not None:
# I believe this is required since the stop tokens
# are not enforced by the human themselves
user_input = enforce_stop_tokens(user_input, stop)
return user_input
|
langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@llms@human.py@.PATH_END.py
|
{
"filename": "demo_starglm_agent.ipynb",
"repo_name": "Yu-Yang-Li/StarWhisper",
"repo_path": "StarWhisper_extracted/StarWhisper-main/Agent_demo/demo_starglm_agent.ipynb",
"type": "Jupyter Notebook"
}
|
### clone代码
```python
!git clone https://github.com/modelscope/modelscope-agent.git
```
### 安装特定依赖
```python
!cd modelscope-agent && pip install -r requirements.txt
! pip install transformers_stream_generator
! pip install invisible-watermark>=2.0
```
```python
import os
os.chdir('modelscope-agent/demo')
import sys
sys.path.append('../')
```
### 读取环境变量文件和工具config配置
```python
from dotenv import load_dotenv
import os
from modelscope.utils.config import Config
# 配置环境变量，里面需要配置modelscope token来remote调用AI模型
os.environ['TOOL_CONFIG_FILE'] ='../config/cfg_tool_template.json'
os.environ['OUTPUT_FILE_DIRECTORY'] = '/tmp'
# ModelScope Token从这里获取: https://modelscope.cn/my/myaccesstoken
print('请输入ModelScope Token，可以从这里获取: https://modelscope.cn/my/myaccesstoken')
os.environ['MODELSCOPE_API_TOKEN'] = input()
# 读取工具调用CONFIG文件，包括工具的名称和远程请求url
tool_cfg_file = os.getenv('TOOL_CONFIG_FILE')
print(tool_cfg_file)
tool_cfg = Config.from_file(tool_cfg_file)
```
### 构建工具调用向量检索
```python
from langchain.embeddings import ModelScopeEmbeddings, DashScopeEmbeddings
from langchain.vectorstores import FAISS
from modelscope_agent.retrieve import ToolRetrieval
# 第一种向量方案，基于阿里云DashScope向量API服务方式，需要开通DashScope文本向量服务()
# embeddings = DashScopeEmbeddings(model="text-embedding-v1")
# 第二种向量方案，基于魔搭社区开源向量模型
model_id = 'damo/nlp_corom_sentence-embedding_chinese-base'
embeddings = ModelScopeEmbeddings(model_id=model_id)
# 基于FAISS构建向量检索引擎
tool_retrieval = ToolRetrieval(embeddings, FAISS)
```
### 中枢大模型启动
```python
from modelscope_agent.llm import LLMFactory
from modelscope.hub.api import HubApi
from transformers import AutoModel
model_name = 'starglm'
model_cfg = {
'starglm':{
'model_id': 'your_path_to_starglm_model',
'use_raw_generation_config': False,
'custom_chat': False,
'model_cls': AutoModel,
'generate_cfg':{
'do_sample': True,
'max_new_tokens': 512,
'top_k': 10,
'temperature': 0.01,
'top_p': 0.8
}
}
}
llm = LLMFactory.build_llm(model_name, model_cfg)
```
### Agent构建
```python
from modelscope_agent.prompt import MSPromptGenerator
from modelscope_agent.agent import AgentExecutor
prompt_generator = MSPromptGenerator(system_template="你是司天工程的StarGPT，你是天文大模型， 是2023年司天工程的科学家训练得到的。\
你有多种能力，可以通过插件集成魔搭社区的模型api来回复用户的问题，还能解答用户使用模型遇到的问题和模型知识相关问答。")
# 构建Agent，需要传入llm，工具配置config以及工具检索
agent = AgentExecutor(llm, tool_cfg, tool_retrieval=tool_retrieval, prompt_generator=prompt_generator)
```
```python
# 重置对话，清空对话历史
agent.reset()
# Multi-turn tool-use try
agent.run('使用地址识别模型，从下面的地址中找到省市区等元素，地址：青海省海西蒙古族藏族自治州茫崖市冷湖镇', remote=False)
```
|
Yu-Yang-LiREPO_NAMEStarWhisperPATH_START.@StarWhisper_extracted@StarWhisper-main@Agent_demo@demo_starglm_agent.ipynb@.PATH_END.py
|
{
"filename": "jump.py",
"repo_name": "spacetelescope/jwst",
"repo_path": "jwst_extracted/jwst-main/jwst/jump/jump.py",
"type": "Python"
}
|
import logging
import numpy as np
from stcal.jump.jump import detect_jumps
from stdatamodels.jwst.datamodels import dqflags
from ..lib import reffile_utils
log = logging.getLogger(__name__)
log.setLevel(logging.DEBUG)
def run_detect_jumps(output_model, gain_model, readnoise_model,
rejection_thresh, three_grp_thresh, four_grp_thresh,
max_cores, max_jump_to_flag_neighbors,
min_jump_to_flag_neighbors, flag_4_neighbors,
after_jump_flag_dn1=0.0,
after_jump_flag_time1=0.0,
after_jump_flag_dn2=0.0,
after_jump_flag_time2=0.0,
min_sat_area=1.0, min_jump_area=5.0, min_sat_radius_extend=2.5,
expand_factor=2.0, use_ellipses=False,
sat_required_snowball=True, sat_expand=2,
expand_large_events=False, find_showers=False, edge_size=25, extend_snr_threshold=1.1,
extend_min_area=90, extend_inner_radius=1, extend_outer_radius=2.6, extend_ellipse_expand_ratio=1.1,
time_masked_after_shower=30, min_diffs_single_pass=10,
max_extended_radius=200,
minimum_groups=3,
minimum_sigclip_groups=100,
only_use_ints=True,
mask_snowball_persist_next_int=True,
snowball_time_masked_next_int=250,
max_shower_amplitude=4
):
# Runs `detect_jumps` in stcal
# extract data and info from input_model to pass to detect_jumps
frames_per_group = output_model.meta.exposure.nframes
# determine the number of groups that correspond to the after_jump times
# needed because the group time is not passed to detect_jumps
gtime = output_model.meta.exposure.group_time
after_jump_flag_n1 = int(after_jump_flag_time1 // gtime)
after_jump_flag_n2 = int(after_jump_flag_time2 // gtime)
grps_masked_after_shower = int(time_masked_after_shower // gtime)
snowball_grps_masked_next_int = int(snowball_time_masked_next_int // gtime)
# Likewise, convert a max MIRI shower amplitude in DN/s to DN/group
max_shower_amplitude = max_shower_amplitude * gtime
# Get 2D gain and read noise values from their respective models
if reffile_utils.ref_matches_sci(output_model, gain_model):
gain_2d = gain_model.data
else:
log.info('Extracting gain subarray to match science data')
gain_2d = reffile_utils.get_subarray_data(output_model, gain_model)
if reffile_utils.ref_matches_sci(output_model, readnoise_model):
readnoise_2d = readnoise_model.data
else:
log.info('Extracting readnoise subarray to match science data')
readnoise_2d = reffile_utils.get_subarray_data(output_model,
readnoise_model)
new_gdq, new_pdq, number_crs, number_extended_events, stddev\
= detect_jumps(frames_per_group, output_model.data, output_model.groupdq,
output_model.pixeldq, output_model.err,
gain_2d, readnoise_2d,
rejection_thresh, three_grp_thresh,
four_grp_thresh, max_cores,
max_jump_to_flag_neighbors,
min_jump_to_flag_neighbors,
flag_4_neighbors, dqflags.pixel,
after_jump_flag_dn1,
after_jump_flag_n1,
after_jump_flag_dn2,
after_jump_flag_n2,
min_sat_area=min_sat_area, min_jump_area=min_jump_area,
expand_factor=expand_factor, use_ellipses=use_ellipses,
min_sat_radius_extend=min_sat_radius_extend,
sat_required_snowball=sat_required_snowball, sat_expand=sat_expand,
expand_large_events=expand_large_events, find_showers=find_showers,
edge_size=edge_size, extend_snr_threshold=extend_snr_threshold,
extend_min_area=extend_min_area, extend_inner_radius=extend_inner_radius,
extend_outer_radius=extend_outer_radius,
extend_ellipse_expand_ratio=extend_ellipse_expand_ratio,
grps_masked_after_shower=grps_masked_after_shower,
min_diffs_single_pass=min_diffs_single_pass,
max_extended_radius=max_extended_radius,
minimum_groups=minimum_groups,
minimum_sigclip_groups=minimum_sigclip_groups,
only_use_ints=only_use_ints,
mask_persist_grps_next_int = mask_snowball_persist_next_int,
persist_grps_flagged = snowball_grps_masked_next_int,
max_shower_amplitude = max_shower_amplitude
)
# Update the DQ arrays of the output model with the jump detection results
output_model.groupdq = new_gdq
output_model.pixeldq = new_pdq
# determine the number of groups with all pixels set to DO_NOT_USE
dnu_flag = 1
num_flagged_grps = 0
datashape = np.shape(output_model.data)
for integ in range(datashape[0]):
for grp in range(datashape[1]):
if np.all(np.bitwise_and(output_model.groupdq[integ, grp, :, :], dnu_flag)):
num_flagged_grps += 1
total_groups = datashape[0] * datashape[1] - num_flagged_grps - datashape[0]
if total_groups >= 1:
total_time = output_model.meta.exposure.group_time * total_groups
total_pixels = datashape[2] * datashape[3]
output_model.meta.exposure.primary_cosmic_rays = 1000 * number_crs / (total_time * total_pixels)
output_model.meta.exposure.extended_emission_events = 1e6 * number_extended_events /\
(total_time * total_pixels)
return output_model
|
spacetelescopeREPO_NAMEjwstPATH_START.@jwst_extracted@jwst-main@jwst@jump@jump.py@.PATH_END.py
|
{
"filename": "einsum_utils.py",
"repo_name": "neuraloperator/neuraloperator",
"repo_path": "neuraloperator_extracted/neuraloperator-main/neuralop/layers/einsum_utils.py",
"type": "Python"
}
|
import torch
import opt_einsum
import tensorly as tl
from tensorly.plugins import use_opt_einsum
tl.set_backend('pytorch')
use_opt_einsum('optimal')
def einsum_complexhalf_two_input(eq, a, b):
"""
Compute (two-input) einsum for complexhalf tensors.
Because torch.einsum currently does not support complex32 (complexhalf) types.
The inputs and outputs are the same as in torch.einsum
"""
assert len(eq.split(',')) == 2, "Equation must have two inputs."
# cast both tensors to "view as real" form, and half precision
a = torch.view_as_real(a)
b = torch.view_as_real(b)
a = a.half()
b = b.half()
# create a new einsum equation that takes into account "view as real" form
input_output = eq.split('->')
new_output = 'xy' + input_output[1]
input_terms = input_output[0].split(',')
new_inputs = [input_terms[0] + 'x', input_terms[1] + 'y']
new_eqn = new_inputs[0] + ',' + new_inputs[1] + '->' + new_output
# convert back to complex form
tmp = tl.einsum(new_eqn, a, b)
res = torch.stack([tmp[0, 0, ...] - tmp[1, 1, ...], tmp[1, 0, ...] + tmp[0, 1, ...]], dim=-1)
return torch.view_as_complex(res)
def einsum_complexhalf(eq, *args):
"""
Compute einsum for complexhalf tensors.
Because torch.einsum currently does not support complex32 (complexhalf) types.
The inputs and outputs are the same as in torch.einsum
"""
if len(args) == 2:
# if there are two inputs, it is faster to call this method
return einsum_complexhalf_two_input(eq, *args)
# find the optimal path
_, path_info = opt_einsum.contract_path(eq, *args)
partial_eqns = [contraction_info[2] for contraction_info in path_info.contraction_list]
# create a dict of the input tensors by their label in the einsum equation
tensors = {}
input_labels = eq.split('->')[0].split(',')
output_label = eq.split('->')[1]
tensors = dict(zip(input_labels,args))
# convert all tensors to half precision and "view as real" form
for key, tensor in tensors.items():
tensor = torch.view_as_real(tensor)
tensor = tensor.half()
tensors[key] = tensor
for partial_eq in partial_eqns:
# get the input tensors to partial_eq
in_labels, out_label = partial_eq.split('->')
in_labels = in_labels.split(',')
in_tensors = [tensors[label] for label in in_labels]
# create new einsum equation that takes into account "view as real" form
input_output = partial_eq.split('->')
new_output = 'xy' + input_output[1]
input_terms = input_output[0].split(',')
new_inputs = [input_terms[0] + 'x', input_terms[1] + 'y']
new_eqn = new_inputs[0] + ',' + new_inputs[1] + '->' + new_output
# perform the einsum, and convert to "view as real" form
tmp = tl.einsum(new_eqn, *in_tensors)
result = torch.stack([tmp[0, 0, ...] - tmp[1, 1, ...], tmp[1, 0, ...] + tmp[0, 1, ...]], dim=-1)
tensors[out_label] = result
return torch.view_as_complex(tensors[output_label])
|
neuraloperatorREPO_NAMEneuraloperatorPATH_START.@neuraloperator_extracted@neuraloperator-main@neuralop@layers@einsum_utils.py@.PATH_END.py
|
{
"filename": "gps_test.py",
"repo_name": "LSSTDESC/snmachine",
"repo_path": "snmachine_extracted/snmachine-main/test/gps_test.py",
"type": "Python"
}
|
"""
Tests related to Gaussian Processes module.
"""
import os
import numpy as np
import pytest
import pandas as pd
from snmachine import example_data, gps
# Import test data
example_data_path = os.path.join(example_data, 'example_data_for_tests.pckl')
example_data = pd.read_pickle(example_data_path)
# Start the tests
@pytest.mark.gp
def test_1d_gps():
"""Test the 1 dimensional Gaussian Processes.
Run the Gaussian Processes for `example_data` (the first 5 PLAsTiCC's
objects) and verify the flux mean of each event is correct.
"""
# These are the objects in example_data.
mean_flux_true_values = {
'615': -23.22402573951826,
'713': -1.4359755792364706,
'730': 2.844743959137723,
'745': 21.13420610513882,
'1124': 16.099748055475427}
gps.compute_gps(example_data, number_gp=100, t_min=0, t_max=1100,
kernel_param=[500., 20.], output_root=None,
number_processes=1, gp_dim=1)
for obj in example_data.object_names:
mean_flux_obj = np.mean(example_data.models[obj]['flux'])
np.testing.assert_allclose(mean_flux_obj,
mean_flux_true_values[obj])
@pytest.mark.gp
def test_2d_gps():
"""Test the 2 dimensional Gaussian Processes.
Run the Gaussian Processes for `example_data` (the first 5 PLAsTiCC's
objects) and verify the flux mean of each event is correct.
"""
# These are the objects in example_data.
mean_flux_true_values = {
'615': -45.486487005741296,
'713': -0.9183076088586439,
'730': 3.673929979995239,
'745': 29.142299327650303,
'1124': 17.134494730329973}
gps.compute_gps(example_data, number_gp=100, t_min=0, t_max=1100,
kernel_param=[500., 20.], output_root=None,
number_processes=1, gp_dim=2)
for obj in example_data.object_names:
mean_flux_obj = np.mean(example_data.models[obj]['flux'])
np.testing.assert_allclose(mean_flux_obj,
mean_flux_true_values[obj])
@pytest.mark.gp
def test_gps_chisq_over_pts():
"""Test the X^2/number of datapoints values.
Run the Gaussian Processes for `example_data` (the first 5 PLAsTiCC's
objects) and verify it returns the expected values of X^2/number of
datapoints.
"""
# These are the objects in example_data.
chisq_over_pts_true_values = {
'615': 5695.7282978660587,
'713': 1.0678220723794234,
'730': 0.83081717132128197,
'745': 1.0721589469244539,
'1124': 0.77145060447736791}
gps.compute_gps(example_data, number_gp=100, t_min=0, t_max=1100,
kernel_param=[500., 20.], output_root=None,
number_processes=1, gp_dim=1)
chisq_over_pts = example_data.compute_chisq_over_pts()
for obj in chisq_over_pts.keys():
np.testing.assert_allclose(chisq_over_pts[obj],
chisq_over_pts_true_values[obj])
|
LSSTDESCREPO_NAMEsnmachinePATH_START.@snmachine_extracted@snmachine-main@test@gps_test.py@.PATH_END.py
|
{
"filename": "axislabels.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/astropy/visualization/wcsaxes/axislabels.py",
"type": "Python"
}
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import print_function, division, absolute_import
import numpy as np
from matplotlib.text import Text
import matplotlib.transforms as mtransforms
from .frame import RectangularFrame
class AxisLabels(Text):
def __init__(self, frame, minpad=1, *args, **kwargs):
self._frame = frame
super(AxisLabels, self).__init__(*args, **kwargs)
self.set_clip_on(True)
self.set_visible_axes('all')
self.set_ha('center')
self.set_va('center')
self._minpad = minpad
def get_minpad(self, axis):
try:
return self._minpad[axis]
except TypeError:
return self._minpad
def set_visible_axes(self, visible_axes):
self._visible_axes = visible_axes
def get_visible_axes(self):
if self._visible_axes == 'all':
return self._frame.keys()
else:
return [x for x in self._visible_axes if x in self._frame]
def set_minpad(self, minpad):
self._minpad = minpad
def draw(self, renderer, bboxes, ticklabels_bbox_list, visible_ticks):
if not self.get_visible():
return
text_size = renderer.points_to_pixels(self.get_size())
for axis in self.get_visible_axes():
padding = text_size * self.get_minpad(axis)
# Find position of the axis label. For now we pick the mid-point
# along the path but in future we could allow this to be a
# parameter.
x_disp, y_disp = self._frame[axis].pixel[:, 0], self._frame[axis].pixel[:, 1]
d = np.hstack([0., np.cumsum(np.sqrt(np.diff(x_disp) ** 2 + np.diff(y_disp) ** 2))])
xcen = np.interp(d[-1] / 2., d, x_disp)
ycen = np.interp(d[-1] / 2., d, y_disp)
# Find segment along which the mid-point lies
imin = np.searchsorted(d, d[-1] / 2.) - 1
# Find normal of the axis label facing outwards on that segment
normal_angle = self._frame[axis].normal_angle[imin] + 180.
label_angle = (normal_angle - 90.) % 360.
if 135 < label_angle < 225:
label_angle += 180
self.set_rotation(label_angle)
# Find label position by looking at the bounding box of ticks'
# labels and the image. It sets the default padding at 1 times the
# axis label font size which can also be changed by setting
# the minpad parameter.
if isinstance(self._frame, RectangularFrame):
if len(ticklabels_bbox_list) > 0:
ticklabels_bbox = mtransforms.Bbox.union(ticklabels_bbox_list)
else:
ticklabels_bbox = None
if axis == 'l':
if axis in visible_ticks and ticklabels_bbox is not None:
left = ticklabels_bbox.xmin
else:
left = xcen
xpos = left - padding
self.set_position((xpos, ycen))
elif axis == 'r':
if axis in visible_ticks and ticklabels_bbox is not None:
right = ticklabels_bbox.x1
else:
right = xcen
xpos = right + padding
self.set_position((xpos, ycen))
elif axis == 'b':
if axis in visible_ticks and ticklabels_bbox is not None:
bottom = ticklabels_bbox.ymin
else:
bottom = ycen
ypos = bottom - padding
self.set_position((xcen, ypos))
elif axis == 't':
if axis in visible_ticks and ticklabels_bbox is not None:
top = ticklabels_bbox.y1
else:
top = ycen
ypos = top + padding
self.set_position((xcen, ypos))
else: # arbitrary axis
dx = np.cos(np.radians(normal_angle)) * (padding + text_size * 1.5)
dy = np.sin(np.radians(normal_angle)) * (padding + text_size * 1.5)
self.set_position((xcen + dx, ycen + dy))
super(AxisLabels, self).draw(renderer)
bb = super(AxisLabels, self).get_window_extent(renderer)
bboxes.append(bb)
|
waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@astropy@visualization@wcsaxes@axislabels.py@.PATH_END.py
|
{
"filename": "_coloraxis.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/cone/_coloraxis.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class ColoraxisValidator(_plotly_utils.basevalidators.SubplotidValidator):
def __init__(self, plotly_name="coloraxis", parent_name="cone", **kwargs):
super(ColoraxisValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
dflt=kwargs.pop("dflt", None),
edit_type=kwargs.pop("edit_type", "calc"),
regex=kwargs.pop("regex", "/^coloraxis([2-9]|[1-9][0-9]+)?$/"),
**kwargs,
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@cone@_coloraxis.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "wmpg/Supracenter",
"repo_path": "Supracenter_extracted/Supracenter-master/supra/__init__.py",
"type": "Python"
}
|
wmpgREPO_NAMESupracenterPATH_START.@Supracenter_extracted@Supracenter-master@supra@__init__.py@.PATH_END.py
|
|
{
"filename": "drf.py",
"repo_name": "Keck-DataReductionPipelines/OsirisDRP",
"repo_path": "OsirisDRP_extracted/OsirisDRP-master/tests/drptestbones/drf.py",
"type": "Python"
}
|
# -*- coding: utf-8 -*-
"""
Functions for parsing and understanding DRFs.
"""
import os
import xml.etree.ElementTree as et
__all__ = ['expand_osiris_path']
def expand_osiris_path(path):
"""Expand an OSIRIS path which might contain environment variables."""
return os.path.normpath(os.path.expanduser(os.path.expandvars(path)))
class OsirisDRF(object):
"""A data reduction file for Osiris DRF"""
def __init__(self, tree, expand=True):
super(OsirisDRF, self).__init__()
self.tree = tree
self.expand = expand
@classmethod
def parse(cls, filename):
"""Parse an OSIRIS DRF"""
return cls(et.parse(filename))
@property
def log_directory(self):
"""Check that the log directory exists."""
path = self.tree.getroot().get('LogPath')
if self.expand:
path = expand_osiris_path(path)
return path
@property
def output_directory(self):
"""Output directory"""
path = self.tree.getroot().find("dataset").get("OutputDir")
if self.expand:
path = expand_osiris_path(path)
return path
@property
def input_directory(self):
"""Input directory."""
path = self.tree.getroot().find("dataset").get("InputDir")
if self.expand:
path = expand_osiris_path(path)
return path
def data_files(self):
"""A list of input data files."""
dataset = self.tree.getroot().find("dataset")
input_directory = dataset.get("InputDir")
paths = [ os.path.join(input_directory, fits.get("FileName"))
for fits in dataset.findall("fits") ]
if self.expand:
paths = [expand_osiris_path(path) for path in paths ]
return paths
def calibration_files(self):
"""A list of input calibration files."""
paths = [ module.get('CalibrationFile')
for module in self.tree.getroot().findall("module") if 'CalibrationFile' in module.attrib ]
if self.expand:
paths = [expand_osiris_path(path) for path in paths ]
return paths
def files(self):
"""A list of all files."""
return self.calibration_files() + self.data_files()
|
Keck-DataReductionPipelinesREPO_NAMEOsirisDRPPATH_START.@OsirisDRP_extracted@OsirisDRP-master@tests@drptestbones@drf.py@.PATH_END.py
|
{
"filename": "dome.py",
"repo_name": "astroufsc/chimera",
"repo_path": "chimera_extracted/chimera-master/src/chimera/instruments/dome.py",
"type": "Python"
}
|
#! /usr/bin/env python
# -*- coding: iso-8859-1 -*-
# chimera - observatory automation system
# Copyright (C) 2006-2007 P. Henrique Silva <henrique@astro.ufsc.br>
# Copyright (C) 2006-2007 Antonio Kanaan <kanaan@astro.ufsc.br>
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
# 02110-1301, USA.
import queue
import threading
from chimera.core.chimeraobject import ChimeraObject
from chimera.interfaces.dome import Mode, DomeSlew, DomeSlit, DomeFlap, DomeSync
from chimera.core.lock import lock
from chimera.core.exceptions import ObjectNotFoundException
from chimera.core.exceptions import ChimeraException
from chimera.util.coord import Coord
__all__ = ["DomeBase"]
class DomeBase(ChimeraObject, DomeSlew, DomeSlit, DomeFlap, DomeSync):
def __init__(self):
ChimeraObject.__init__(self)
self.queue = queue.Queue()
self._mode = None
# to reuse telescope proxy on control method
self._tel = None
self._telChanged = False
# to cache for az_resolution of the dome
self.controlAzRes = None
self._waitAfterSlew = threading.Event()
self._waitAfterSlew.clear()
def __start__(self):
self.setHz(1 / 4.0)
tel = self.getTelescope()
if tel:
self._connectTelEvents()
else:
self.log.warning(
"Couldn't find telescope. Telescope events would"
" not be monitored. Dome will stay in Stand mode."
)
self["mode"] = Mode.Stand
if self["mode"] == Mode.Track:
self.track()
elif self["mode"] == Mode.Stand:
self.stand()
else:
self.log.warning("Invalid dome mode: %s. " "Will use Stand mode instead.")
self.stand()
self.log.debug("Dome started in %s mode." % self.getMode())
return True
def __stop__(self):
if self["park_on_shutdown"]:
try:
self.stand()
self.log.info("Parking the dome...")
self.slewToAz(self["park_position"])
except Exception as e:
self.log.warning("Unable to park dome: %s", str(e))
if self["close_on_shutdown"] and self.isSlitOpen():
try:
self.log.info("Closing the slit...")
self.closeSlit()
except Exception as e:
self.log.warning("Unable to close dome: %s", str(e))
# telescope events
self._disconnectTelEvents()
return True
def _connectTelEvents(self):
tel = self.getTelescope()
if not tel:
self.log.warning(
"Couldn't find telescope. Telescope events would"
" not be monitored. Dome will stay in Stand mode."
)
self["mode"] == Mode.Stand
return False
tel.slewBegin += self.getProxy()._telSlewBeginClbk
tel.slewComplete += self.getProxy()._telSlewCompleteClbk
return True
def _disconnectTelEvents(self):
tel = self.getTelescope()
if tel:
tel.slewBegin -= self.getProxy()._telSlewBeginClbk
tel.slewComplete -= self.getProxy()._telSlewCompleteClbk
return True
return False
def _reconnectTelEvents(self):
self._disconnectTelEvents()
self._connectTelEvents()
# telescope callbacks
def _telSlewBeginClbk(self, target):
self.log.debug("[event] telescope slewing to %s." % target)
def _telSlewCompleteClbk(self, target, status):
self.log.debug(
"[event] telescope slew complete, position=%s status=%s." % (target, status)
)
# utilitaries
def getTelescope(self):
try:
p = self.getManager().getProxy(self["telescope"], lazy=True)
if not p.ping():
return False
else:
return p
except ObjectNotFoundException:
return False
def control(self):
if self.getMode() == Mode.Stand:
return True
if not self.queue.empty():
self._processQueue()
return True
try:
if not self._tel or self._telChanged:
self._tel = self.getTelescope()
self._telChanged = False
if not self._tel:
return True
if self._tel.isSlewing():
self.log.debug("[control] telescope slewing... not checking az.")
self._waitAfterSlew.set()
return True
self._telescopeChanged(self._tel.getAz())
# flag all waiting threads that the control loop already checked the new telescope position
# probably adding new azimuth to the queue
self._waitAfterSlew.clear()
except ObjectNotFoundException:
raise ChimeraException(
"Couldn't found the selected telescope." " Dome cannnot track."
)
return True
def _telescopeChanged(self, az):
if not isinstance(az, Coord):
az = Coord.fromDMS(az)
if self._needToMove(az):
self.log.debug(
"[control] adding %s to the queue (delta=%.2f)"
% (az, abs(self.getAz() - az))
)
self.queue.put(az)
else:
self.log.debug(
"[control] standing"
" (dome az=%.2f, tel az=%.2f, delta=%.2f.)"
% (self.getAz(), az, abs(self.getAz() - az))
)
def _needToMove(self, az):
return abs(az - self.getAz()) >= self["az_resolution"]
def _processQueue(self):
if self._waitAfterSlew.isSet():
self._telescopeChanged(self._tel.getAz())
if self.queue.empty():
return
self.log.debug("[control] processing queue... %d item(s)." % self.queue.qsize())
while not self.queue.empty():
target = self.queue.get()
try:
self.log.debug("[queue] slewing to %s" % target)
self.slewToAz(target)
finally:
self.log.debug("[queue] slew to %s complete" % target)
self.queue.task_done()
@lock
def track(self):
if self.getMode() == Mode.Track:
return
tel = self.getTelescope()
if tel:
self._reconnectTelEvents()
self._telChanged = True
self.log.debug("[mode] tracking...")
self._telescopeChanged(tel.getAz())
self._mode = Mode.Track
else:
self.log.warning(
"Could not contact the given telescope, staying in Stand mode."
)
@lock
def stand(self):
self._processQueue()
self.log.debug("[mode] standing...")
self._mode = Mode.Stand
@lock
def syncWithTel(self):
self.syncBegin()
if self.getMode() != Mode.Stand:
self._telescopeChanged(self._tel.getAz())
self._processQueue()
self.syncComplete()
@lock
def isSyncWithTel(self):
return self._needToMove(self._tel.getAz())
def getMode(self):
return self._mode
@lock
def slewToAz(self, az):
raise NotImplementedError()
def isSlewing(self):
raise NotImplementedError()
def abortSlew(self):
raise NotImplementedError()
@lock
def getAz(self):
raise NotImplementedError()
@lock
def openSlit(self):
raise NotImplementedError()
@lock
def closeSlit(self):
raise NotImplementedError()
def isSlitOpen(self):
raise NotImplementedError()
@lock
def openFlap(self):
raise NotImplementedError()
@lock
def closeFlap(self):
raise NotImplementedError()
def isFlapOpen(self):
raise NotImplementedError()
def getMetadata(self, request):
# Check first if there is metadata from an metadata override method.
md = self.getMetadataOverride(request)
if md is not None:
return md
# If not, just go on with the instrument's default metadata.
if self.isSlitOpen():
slit = "Open"
else:
slit = "Closed"
return [
("DOME_MDL", str(self["model"]), "Dome Model"),
("DOME_TYP", str(self["style"]), "Dome Type"),
("DOME_TRK", str(self["mode"]), "Dome Tracking/Standing"),
("DOME_SLT", str(slit), "Dome slit status"),
]
|
astroufscREPO_NAMEchimeraPATH_START.@chimera_extracted@chimera-master@src@chimera@instruments@dome.py@.PATH_END.py
|
{
"filename": "test_metacal.py",
"repo_name": "GalSim-developers/GalSim",
"repo_path": "GalSim_extracted/GalSim-main/tests/test_metacal.py",
"type": "Python"
}
|
# Copyright (c) 2012-2023 by the GalSim developers team on GitHub
# https://github.com/GalSim-developers
#
# This file is part of GalSim: The modular galaxy image simulation toolkit.
# https://github.com/GalSim-developers/GalSim
#
# GalSim is free software: redistribution and use in source and binary forms,
# with or without modification, are permitted provided that the following
# conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this
# list of conditions, and the disclaimer given in the accompanying LICENSE
# file.
# 2. Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions, and the disclaimer given in the documentation
# and/or other materials provided with the distribution.
#
import time
import numpy as np
import galsim
from galsim_test_helpers import *
VAR_NDECIMAL=4
CHECKNOISE_NDECIMAL=2
@timer
def test_metacal_tracking():
"""Test that the noise tracking works for the metacal use case involving deconvolution and
reconvolution by almost the same PSF.
This test is similar to the above test_uncorrelated_noise_tracking, except the modifications
are based on what is done for the metacal procedure.
"""
import math
def check_noise(noise_image, noise, msg):
# A helper function to check that the current noise in the image is properly described
# by the given CorrelatedNoise object
noise2 = galsim.CorrelatedNoise(noise_image)
print('noise = ',noise)
print('noise2 = ',noise2)
np.testing.assert_almost_equal(noise.getVariance(), noise2.getVariance(),
decimal=CHECKNOISE_NDECIMAL,
err_msg=msg + ': variance does not match.')
cf_im1 = galsim.Image(8,8, wcs=noise_image.wcs)
cf_im2 = cf_im1.copy()
noise.drawImage(image=cf_im1)
noise2.drawImage(image=cf_im2)
np.testing.assert_almost_equal(cf_im1.array, cf_im2.array,
decimal=CHECKNOISE_NDECIMAL,
err_msg=msg + ': image of cf does not match.')
def check_symm_noise(noise_image, msg):
# A helper funciton to see if a noise image has 4-fold symmetric noise.
im2 = noise_image.copy()
# Clear out any wcs to make the test simpler
im2.wcs = galsim.PixelScale(1.)
noise = galsim.CorrelatedNoise(im2)
cf = noise.drawImage(galsim.Image(bounds=galsim.BoundsI(-1,1,-1,1), scale=1))
# First check the variance
print('variance: ',cf(0,0), noise.getVariance())
np.testing.assert_almost_equal(cf(0,0)/noise.getVariance(), 1.0, decimal=VAR_NDECIMAL,
err_msg=msg + ':: noise variance is wrong.')
cf_plus = np.array([ cf(1,0), cf(-1,0), cf(0,1), cf(0,-1) ])
cf_cross = np.array([ cf(1,1), cf(-1,-1), cf(-1,1), cf(1,-1) ])
print('plus pattern: ',cf_plus)
print('diff relative to dc: ',(cf_plus-np.mean(cf_plus))/cf(0,0))
print('cross pattern: ',cf_cross)
print('diff relative to dc: ',(cf_cross-np.mean(cf_cross))/cf(0,0))
# For now, don't make these asserts. Just print whether they will pass or fail.
if True:
if np.all(np.abs((cf_plus-np.mean(cf_plus))/cf(0,0)) < 0.01):
print('plus test passes')
else:
print('*** FAIL ***')
print(msg + ': plus pattern is not constant')
if np.all(np.abs((cf_cross-np.mean(cf_cross))/cf(0,0)) < 0.01):
print('cross test passes')
else:
print('*** FAIL ***')
print(msg + ': cross pattern is not constant')
else:
np.testing.assert_almost_equal((cf_plus-np.mean(cf_plus))/cf(0,0), 0.0, decimal=2,
err_msg=msg + ': plus pattern is not constant')
np.testing.assert_almost_equal((cf_cross-np.mean(cf_cross))/cf(0,0), 0.0, decimal=2,
err_msg=msg + ': cross pattern is not constant')
seed = 1234567 # For use as a unit test, we need a specific seed
#seed = 0 # During testing, it's useful to see how numbers flop around to know if
# something is systematic or random.
rng = galsim.BaseDeviate(seed)
noise_var = 1.3
im_size = 1024
dg = 0.1 # This is bigger than metacal would use, but it makes the test easier.
# Use a non-trivial wcs...
#wcs = galsim.JacobianWCS(0.26, 0.04, -0.04, -0.26) # Rotation + flip. No shear.
wcs = galsim.JacobianWCS(0.26, 0.03, 0.08, -0.21) # Fully complex
#dudx = 0.12*0.26
#dudy = 1.10*0.26
#dvdx = -0.915*0.26
#dvdy = -0.04*0.26
#wcs = galsim.JacobianWCS(dudx, dudy, dvdx, dvdy) # Even more extreme
# And an asymmetric PSF
#orig_psf = galsim.Gaussian(fwhm=0.9).shear(g1=0.05, g2=0.03)
# This one is small enough not to be fully Nyquist sampled, which makes things harder.
orig_psf = galsim.Gaussian(fwhm=0.7).shear(g1=0.05, g2=0.03)
# pixel is the pixel in world coords
pixel = wcs.toWorld(galsim.Pixel(scale=1))
pixel_inv = galsim.Deconvolve(pixel)
psf_image = orig_psf.drawImage(nx=im_size, ny=im_size, wcs=wcs)
# Metacal only has access to the PSF as an image, so use this from here on.
psf = galsim.InterpolatedImage(psf_image)
psf_nopix = galsim.Convolve([psf, pixel_inv])
psf_inv = galsim.Deconvolve(psf)
# Not what is done currently, but using a smoother target PSF helps make sure the
# zeros in the deconvolved PSF get adequately zeroed out.
def get_target_psf(psf):
dk = 0.1 # The resolution in k space for the KImage
small_kval = 1.e-2 # Find the k where the given psf hits this kvalue
smaller_kval = 3.e-3 # Target PSF will have this kvalue at the same k
kim = psf.drawKImage(scale=dk)
karr_r = kim.real.array
# Find the smallest r where the kval < small_kval
nk = karr_r.shape[0]
kx, ky = np.meshgrid(np.arange(-nk/2,nk/2), np.arange(-nk/2,nk/2))
ksq = (kx**2 + ky**2) * dk**2
ksq_max = np.min(ksq[karr_r < small_kval * psf.flux])
# We take our target PSF to be the (round) Gaussian that is even smaller at this ksq
# exp(-0.5 * ksq_max * sigma_sq) = smaller_kval
sigma_sq = -2. * np.log(smaller_kval) / ksq_max
return galsim.Gaussian(sigma = np.sqrt(sigma_sq))
# The target PSF dilates the part without the pixel, but reconvolve by the real pixel.
#psf_target_nopix = psf_nopix.dilate(1. + 2.*dg)
#psf_target_nopix = orig_psf.dilate(1. + 4.*dg)
psf_target_nopix = get_target_psf(psf_nopix.shear(g1=dg))
print('PSF target HLR = ',psf_target_nopix.calculateHLR())
print('PSF target FWHM = ',psf_target_nopix.calculateFWHM())
psf_target = galsim.Convolve([psf_target_nopix, pixel])
# Make an image of pure (white) Gaussian noise
# Normally, there would be a galaxy in this image, but for the tests, we just have noise.
obs_image = galsim.Image(im_size, im_size, init_value=0, wcs=wcs)
obs_image.addNoise(galsim.GaussianNoise(rng=rng, sigma=math.sqrt(noise_var)))
# The noise on this image should be describable as an UncorrelatedNoise object:
noise = galsim.UncorrelatedNoise(variance=noise_var, wcs=wcs)
check_noise(obs_image, noise, 'initial UncorrelatedNoise model is wrong')
# Make an InterpolatedImage profile to use for manipulating this image
# We can get away with no padding here, since our image is so large, but normally, you would
# probably want to pad this with noise padding.
ii = galsim.InterpolatedImage(obs_image, pad_factor=1)
ii.noise = noise
# If we draw it back, the attached noise attribute should still be correct
check_noise(ii.drawImage(obs_image.copy(),method='no_pixel'), ii.noise,
'noise model is wrong for InterpolatedImage')
# Here is the metacal process for which we want to understand the noise.
# We'll try a few different methods.
shear = galsim.Shear(g1=dg)
sheared_obj = galsim.Convolve(ii, psf_inv).shear(shear)
final_obj = galsim.Convolve(psf_target, sheared_obj)
final_image = final_obj.drawImage(obs_image.copy(), method='no_pixel')
try:
check_symm_noise(final_image, 'Initial image')
#didnt_fail = True
# This bit doesn't work while we are not actually raising exceptions in check_symm_noise
# So we expect to see **FAIL** text at this point.
print('The above tests are expected to **FAIL**. This is not a problem.')
didnt_fail = False
except AssertionError as e:
print('As expected initial image fails symmetric noise test:')
print(e)
didnt_fail = False
if didnt_fail:
assert False, 'Initial image was expected to fail symmetric noise test, but passed.'
if True:
print('\n\nStrategy 1:')
# Strategy 1: Use the noise attribute attached to ii and use it to either whiten or
# symmetrize the noise in the final image.
# Note: The check_noise tests fail. I think because the convolve and deconvolve impose
# a maxk = that of the psf. Which is too small for an accurate rendering of the
# correlation function (here just an autocorrelation of a Pixel.
# The whiten tests kind of work, but they add a lot of extra noise. Much more than
# strategy 4 below. So the level of correlation remaining is pretty well below the
# dc variance. Symmetrize doesn't add much noise, but the residual correlation is about
# the same, which means it doesn't pass the test relative to the lower dc variance.
# First, deconvolve and reconvolve by the same PSF:
test_obj = galsim.Convolve([ii, psf, psf_inv])
# This fails...
if False:
check_noise(test_obj.drawImage(obs_image.copy(), method='no_pixel'), test_obj.noise,
'noise model is wrong after convolve/deconvolve by psf')
# Now use a slightly dilated PSF for the reconvolution:
test_obj = galsim.Convolve([ii, psf_target, psf_inv])
if False:
check_noise(test_obj.drawImage(obs_image.copy(), method='no_pixel'), test_obj.noise,
'noise model is wrong for dilated target psf')
# Finally, include the shear step. This was done above with sheared_obj, final_obj.
if False:
check_noise(final_image, final_obj.noise,
'noise model is wrong when including small shear')
# If we whiten using this noise model, we should get back to white noise.
t3 = time.time()
final_image2 = final_image.copy() # Don't clobber the original
final_var = final_image2.whitenNoise(final_obj.noise)
t4 = time.time()
print('Noise tracking method with whiten: final_var = ',final_var)
print('Check: direct variance = ',np.var(final_image2.array))
check_symm_noise(final_image2, 'noise whitening does not work')
print('Time for noise tracking with whiten = ',t4-t3)
# Using symmetrizeNoise should add less noise, but also work.
t3 = time.time()
final_image2 = final_image.copy()
final_var = final_image2.symmetrizeNoise(final_obj.noise)
t4 = time.time()
print('Noise tracking method with symmetrize: final_var = ',final_var)
print('Check: direct variance = ',np.var(final_image2.array))
check_symm_noise(final_image2, 'noise symmetrizing does not work')
print('Time for noise tracking with symmetrize = ',t4-t3)
if True:
print('\n\nStrategy 2:')
# Strategy 2: Don't trust the noise tracking. Track a noise image through the same process
# and then measure the noise from that image. Use it to either whiten or
# symmetrize the noise in the final image.
# Note: This method doesn't work any better. The added noise for whitening is even more
# than strategy 1. And the remaining correlations are still similarly significant for the
# symmetrize version. A little smaller than strategy 1, but not enough to pass our tests.
# Make another noise image, since we don't actually have access to a pure noise image
# for real objects. But we should be able to estimate the variance in the image.
t3 = time.time()
noise_image = galsim.Image(im_size,im_size, init_value=0, wcs=wcs)
noise_image.addNoise(galsim.GaussianNoise(rng=rng, sigma=math.sqrt(noise_var)))
noise_ii = galsim.InterpolatedImage(noise_image, pad_factor=1)
sheared_noise_obj = galsim.Convolve(noise_ii, psf_inv).shear(shear)
final_noise_obj = galsim.Convolve(psf_target, sheared_noise_obj)
final_noise_image = final_noise_obj.drawImage(obs_image.copy(), method='no_pixel')
# Use this to construct an appropriate CorrelatedNoise object
noise = galsim.CorrelatedNoise(final_noise_image)
t4 = time.time()
final_image2 = final_image.copy()
final_var = final_image2.whitenNoise(noise)
t5 = time.time()
check_noise(final_noise_image, noise,
'noise model is wrong when direct measuring the final noise image')
print('Direct noise method with whiten: final_var = ',final_var)
# Neither of these work currently, so maybe a bug in the whitening code?
# Or possibly in my logic here.
check_symm_noise(final_image2, 'whitening the noise using direct noise model failed')
print('Time for direct noise with whitening = ',t5-t3)
t6 = time.time()
final_image2 = final_image.copy()
final_var = final_image2.symmetrizeNoise(noise)
t7 = time.time()
print('Direct noise method with symmetrize: final_var = ',final_var)
check_symm_noise(final_image2, 'symmetrizing the noise using direct noise model failed')
print('Time for direct noise with symmetrizing = ',t7-t6 + t4-t3)
if False:
print('\n\nStrategy 3:')
# Strategy 3: Make a noise field and do the same operations as we do to the main image
# except use the opposite shear value. Add this noise field to the final
# image to get a symmetric noise field.
# Note: This method works! But only for square pixels. However, they may be rotated
# or flipped. Just not sheared.
# Update: I think this method won't ever work for non-square pixels. The reason it works
# for square pixels is that in that case, it is equivalent to strategy 4.
t3 = time.time()
# Make another noise image
rev_image = galsim.Image(im_size,im_size, init_value=0, wcs=wcs)
rev_image.addNoise(galsim.GaussianNoise(rng=rng, sigma=math.sqrt(noise_var)))
rev_ii = galsim.InterpolatedImage(rev_image, pad_factor=1)
rev_sheared_obj = galsim.Convolve(rev_ii, psf_inv).shear(-shear)
rev_final_obj = galsim.Convolve(psf_target, rev_sheared_obj)
rev_final_image = rev_final_obj.drawImage(obs_image.copy(), method='no_pixel')
# Add the reverse-sheared noise image to the original image.
final_image2 = final_image + rev_final_image
t4 = time.time()
# The noise variance in the end should be 2x as large as the original
final_var = np.var(final_image2.array)
print('Reverse shear method: final_var = ',final_var)
check_symm_noise(final_image2, 'using reverse shear does not work')
print('Time for reverse shear method = ',t4-t3)
if True:
print('\n\nStrategy 4:')
# Strategy 4: Make a noise field and do the same operations as we do to the main image,
# then rotate it by 90 degress and add it to the final image.
# This method works! Even for an arbitrarily sheared wcs.
t3 = time.time()
# Make another noise image
noise_image = galsim.Image(im_size,im_size, init_value=0, wcs=wcs)
noise_image.addNoise(galsim.GaussianNoise(rng=rng, sigma=math.sqrt(noise_var)))
noise_ii = galsim.InterpolatedImage(noise_image, pad_factor=1)
noise_sheared_obj = galsim.Convolve(noise_ii, psf_inv).shear(shear)
noise_final_obj = galsim.Convolve(psf_target, noise_sheared_obj)
noise_final_image = noise_final_obj.drawImage(obs_image.copy(), method='no_pixel')
# Rotate the image by 90 degrees
rot_noise_final_image = galsim.Image(np.ascontiguousarray(np.rot90(noise_final_image.array)))
# Add the rotated noise image to the original image.
final_image2 = final_image + rot_noise_final_image
t4 = time.time()
# The noise variance in the end should be 2x as large as the original
final_var = np.var(final_image2.array)
print('Rotate image method: final_var = ',final_var)
check_symm_noise(final_image2, 'using rotated noise image does not work')
print('Time for rotate image method = ',t4-t3)
if False:
print('\n\nStrategy 5:')
# Strategy 5: The same as strategy 3, except we target the effective net transformation
# done by strategy 4.
# I think this strategy probably can't work for non-square pixels, because the shear
# happens before the convolution by the PSF. And if the wcs is non-square, then the
# PSF is sheared relative to the pixels. That shear isn't being accounted for here,
# so the net result isn't equivalent to rotating by 90 degrees at the end.
t3 = time.time()
# Make another noise image
rev_image = galsim.Image(im_size,im_size, init_value=0, wcs=wcs)
rev_image.addNoise(galsim.GaussianNoise(rng=rng, sigma=math.sqrt(noise_var)))
rev_ii = galsim.InterpolatedImage(rev_image, pad_factor=1)
# Find the effective transformation to apply in sky coordinates that matches what
# you would get by applying the shear in sky coords, going to image coords and then
# rotating by 90 degrees.
#
# If J is the jacobian of the wcs, and S1 is the applied shear, then we want to find
# S2 such that J^-1 S2 = R90 J^-1 S1
jac = wcs.jacobian()
J = jac.getMatrix()
Jinv = jac.inverse().getMatrix()
S1 = shear.getMatrix()
R90 = np.array([[0,-1],[1,0]])
S2 = J.dot(R90).dot(Jinv).dot(S1)
scale, rev_shear, rev_theta, flip = galsim.JacobianWCS(*S2.flatten()).getDecomposition()
# Flip should be False, and scale should be essentially 1.0.
assert flip == False
assert abs(scale - 1.) < 1.e-8
rev_sheared_obj = galsim.Convolve(rev_ii, psf_inv).rotate(rev_theta).shear(rev_shear)
rev_final_obj = galsim.Convolve(psf_target, rev_sheared_obj)
rev_final_image = rev_final_obj.drawImage(obs_image.copy(), method='no_pixel')
# Add the reverse-sheared noise image to the original image.
final_image2 = final_image + rev_final_image
t4 = time.time()
# The noise variance in the end should be 2x as large as the original
final_var = np.var(final_image2.array)
print('Alternate reverse shear method: final_var = ',final_var)
check_symm_noise(final_image2, 'using alternate reverse shear does not work')
print('Time for alternate reverse shear method = ',t4-t3)
@timer
def test_wcs():
"""Reproduce an error Erin found and reported in #834. This was never an error in a released
version, just temporarily on master, but the mistake hadn't been caught by any of our unit
tests, so this test catches the error.
"""
wcs = galsim.JacobianWCS(0.01, -0.26, -0.28, -0.03)
gal = galsim.Exponential(half_light_radius=1.1, flux=237)
psf = galsim.Moffat(beta=3.5, half_light_radius=0.9)
obs = galsim.Convolve(gal,psf)
obs_im = obs.drawImage(nx=32, ny=32, offset=(0.3,-0.2), wcs=wcs)
psf_im = psf.drawImage(nx=32, ny=32, wcs=wcs)
ii = galsim.InterpolatedImage(obs_im)
psf_ii = galsim.InterpolatedImage(psf_im)
psf_inv = galsim.Deconvolve(psf_ii)
ii_nopsf = galsim.Convolve(ii, psf_inv)
newpsf=galsim.Moffat(beta=3.5, half_light_radius=0.95)
newpsf=newpsf.dilate(1.02)
new_ii = ii_nopsf.shear(g1=0.01,g2=0.0)
new_ii = galsim.Convolve(new_ii, newpsf)
new_im = new_ii.drawImage(image=obs_im.copy(), method='no_pixel')
np.testing.assert_almost_equal(new_im.array.sum()/237, obs_im.array.sum()/237, decimal=1)
if __name__ == "__main__":
runtests(__file__)
|
GalSim-developersREPO_NAMEGalSimPATH_START.@GalSim_extracted@GalSim-main@tests@test_metacal.py@.PATH_END.py
|
{
"filename": "subhalo_model_factory.py",
"repo_name": "astropy/halotools",
"repo_path": "halotools_extracted/halotools-master/halotools/empirical_models/factories/subhalo_model_factory.py",
"type": "Python"
}
|
"""
Module storing the
`~halotools.empirical_models.SubhaloModelFactory` class
that governs how all subhalo-based models are built.
"""
from copy import copy
from warnings import warn
import collections
from ..factories import ModelFactory, SubhaloMockFactory
from .. import model_helpers
from ...sim_manager import sim_defaults
from ...custom_exceptions import HalotoolsError
__all__ = ['SubhaloModelFactory']
__author__ = ['Andrew Hearin']
class SubhaloModelFactory(ModelFactory):
""" Class used to build models of the galaxy-halo connection
in which galaxies live at the centers of subhalos.
See :ref:`subhalo_modeling_tutorial0` for an in-depth description
of how to build subhalo-based models, demonstrated by a
sequence of increasingly complex examples.
If you do not wish to build your own model but want to use one
provided by Halotools,
instead see `~halotools.empirical_models.PrebuiltSubhaloModelFactory`.
All subhalo-based composite models can directly populate catalogs of dark matter halos.
For an in-depth description of how Halotools implements this mock-generation, see
:ref:`subhalo_mock_factory_source_notes`.
The arguments passed to the `SubhaloModelFactory` constructor determine
the features of the model that are returned by the factory. This works in one of two ways,
both of which have explicit examples provided below.
1. Building a new model from scratch.
You can build a model from scratch by passing in a sequence of
``model_features``, each of which are instances of component models.
The factory then composes these independently-defined
components into a composite model.
2. Building a new model from an existing model.
It is also possible to add/swap new features to a previously built composite model instance,
allowing you to create new models from existing ones. To do this, you pass in
a ``baseline_model_instance`` and any set of ``model_features``.
Any ``model_feature`` keyword that matches a feature name of the ``baseline_model_instance``
will replace that feature in the ``baseline_model_instance``;
all other ``model_features`` that you pass in will augment
the ``baseline_model_instance`` with new behavior.
Regardless what set of features you use to build your model,
the returned object can be used to directly populate a halo catalog
with mock galaxies using the
`~halotools.empirical_models.SubhaloModelFactory.populate_mock` method,
as shown in the example below.
"""
def __init__(self, **kwargs):
"""
Parameters
------------------------------------
*model_features : sequence of keyword arguments, optional
Each keyword you use will be interpreted as the name
of a feature in the composite model,
e.g. 'stellar_mass' or 'star_formation_rate';
the value bound to each keyword must be an instance of a
component model governing the behavior of that feature.
See the examples section below.
baseline_model_instance : `SubhaloModelFactory` instance, optional
If passed to the constructor, the ``model_dictionary`` bound to the
``baseline_model_instance`` will be treated as the baseline dictionary.
Any additional keyword arguments passed to the constructor that appear
in the baseline dictionary will be treated as model features that replace
the corresponding component model in the baseline dictionary. Any
model features passed to the constructor that do not
appear in the baseline dictionary will be treated as new features that
augment the baseline model with new behavior. See the examples section below.
model_feature_calling_sequence : list, optional
Determines the order in which your component features
will be called during mock population.
Some component models may have explicit dependence upon
the value of some other galaxy property being modeled.
In such a case, you must pass a ``model_feature_calling_sequence`` list,
ordered in the desired calling sequence.
A classic example is if the stellar-to-halo-mass relation
has explicit dependence on the star formation rate of the galaxy
(active or quiescent). For this example, the
``model_feature_calling_sequence`` would be
model_feature_calling_sequence = ['sfr_designation', 'stellar_mass', ...].
Default behavior is to assume that no model feature
has explicit dependence upon any other, in which case the component
models appearing in the ``model_features`` keyword arguments
will be called in random order, giving primacy to the potential presence
of `stellar_mass` and/or `luminosity` features.
galaxy_selection_func : function object, optional
Function object that imposes a cut on the mock galaxies.
Function should take a length-k Astropy table as a single positional argument,
and return a length-k numpy boolean array that will be
treated as a mask over the rows of the table. If not None,
the mask defined by ``galaxy_selection_func`` will be applied to the
``galaxy_table`` after the table is generated by the `populate_mock` method.
Default is None.
halo_selection_func : function object, optional
Function object used to place a cut on the input ``table``.
If the ``halo_selection_func`` keyword argument is passed,
the input to the function must be a single positional argument storing a
length-N structured numpy array or Astropy table;
the function output must be a length-N boolean array that will be used as a mask.
Halos that are masked will be entirely neglected during mock population.
Examples
------------------------------------
As described above, there are two different ways to build models using the
`SubhaloModelFactory`. Here we give demonstrations of each in turn.
In the first example we'll show how to build a model from scratch using
the ``model_features`` option.
We'll build a composite model from two component models: one modeling stellar mass,
one modeling star formation rate designation. We will use the
`~halotools.empirical_models.Behroozi10SmHm` class to model stellar mass,
and the `~halotools.empirical_models.BinaryGalpropInterpolModel` class to model
whether galaxies are quiescent or star-forming. See the docstrings of these
classes for more information about their behavior.
>>> from halotools.empirical_models import Behroozi10SmHm
>>> stellar_mass_model = Behroozi10SmHm(redshift = 0.5)
>>> from halotools.empirical_models import BinaryGalpropInterpolModel
>>> sfr_model = BinaryGalpropInterpolModel(galprop_name = 'quiescent_designation', galprop_abscissa = [12, 15], galprop_ordinates = [0.25, 0.75])
At this point we have two component model instances, ``stellar_mass_model`` and
``sfr_model``. The following call to the factory uses the ``model_features`` option
described above:
>>> model_instance = SubhaloModelFactory(stellar_mass = stellar_mass_model, sfr = sfr_model)
The feature names we have chosen are 'stellar_mass' and 'sfr', and to each feature
we have attached a component model instance.
In this particular example the assignment of stellar mass and SFR-designation
are entirely independent, and so no other arguments are necessary. However, if you are
building a model in which one or more of your components has explicit dependence on
some other feature, then you can use the ``model_feature_calling_sequence`` argument;
this is a list of the feature names whose order determines the sequence in which
the components will be called during mock population:
>>> model_instance = SubhaloModelFactory(stellar_mass = stellar_mass_model, sfr = sfr_model, model_feature_calling_sequence = ['stellar_mass', 'sfr'])
For more details about this optional argument,
see :ref:`model_feature_calling_sequence_mechanism`.
Whatever features your composite model has, you can use the `~SubhaloModelFactory.populate_mock` method
to create Monte Carlo realization of the model by populating any dark matter halo catalog
in your cache directory:
>>> from halotools.sim_manager import CachedHaloCatalog
>>> halocat = CachedHaloCatalog(simname = 'bolshoi', redshift = 0.5) # doctest: +SKIP
>>> model_instance.populate_mock(halocat) # doctest: +SKIP
Your ``model_instance`` now has a ``mock`` attribute storing a synthetic galaxy
population. See the `~SubhaloModelFactory.populate_mock` docstring for details.
There also convenience functions for estimating the clustering signal predicted by the model.
For example, the following method repeatedly populates the Bolshoi simulation with
galaxies, computes the 3-d galaxy clustering signal of each mock, computes the median
clustering signal in each bin, and returns the result:
>>> r, xi = model_instance.compute_average_galaxy_clustering(num_iterations = 5, simname = 'bolshoi', redshift = 0.5) # doctest: +SKIP
In this next example we'll show how to build a new model from an existing one
using the ``baseline_model_instance`` option. We will start from
the composite model built in Example 1 above. Here we'll build a
new model which is identical the ``model_instance`` above,
only we instead use
the `Moster13SmHm` class to model stellar mass.
>>> from halotools.empirical_models import Moster13SmHm
>>> moster_model = Moster13SmHm(redshift = 0.5)
>>> new_model_instance = SubhaloModelFactory(stellar_mass = moster_model, baseline_model_instance = model_instance)
The ``model_feature_calling_sequence`` works in the same way as it did in Example 1.
>>> new_model_instance = SubhaloModelFactory(stellar_mass = moster_model, baseline_model_instance = model_instance, model_feature_calling_sequence = ['stellar_mass', 'sfr'])
See also
---------
:ref:`subhalo_model_factory_source_notes`
:ref:`subhalo_mock_factory_source_notes`
"""
input_model_dictionary, supplementary_kwargs = (
self._parse_constructor_kwargs(**kwargs)
)
super(SubhaloModelFactory, self).__init__(input_model_dictionary, **supplementary_kwargs)
self.mock_factory = SubhaloMockFactory
self.model_factory = SubhaloModelFactory
self._model_feature_calling_sequence = (
self.build_model_feature_calling_sequence(supplementary_kwargs))
self.model_dictionary = collections.OrderedDict()
for key in self._model_feature_calling_sequence:
self.model_dictionary[key] = copy(self._input_model_dictionary[key])
# Build up and bind several lists from the component models
self.build_prim_sec_haloprop_list()
self.build_publication_list()
self.build_dtype_list()
self.set_warning_suppressions()
self.set_inherited_methods()
self.set_model_redshift()
self.build_init_param_dict()
# Create a set of bound methods with specific names
# that will be called by the mock factory
self.set_primary_behaviors()
self.set_calling_sequence()
self._test_dictionary_consistency()
def _parse_constructor_kwargs(self, **kwargs):
""" Method used to parse the arguments passed to
the constructor into a model dictionary and supplementary arguments.
`parse_constructor_kwargs` examines the keyword arguments passed to `__init__`,
and identifies the possible presence of ``galaxy_selection_func``, ``halo_selection_func`` and
``model_feature_calling_sequence``; all other keyword arguments will be treated as
component models, and it is enforced that the values bound to all such arguments
at the very least have a ``_methods_to_inherit`` attribute.
Parameters
-----------
**kwargs : optional keyword arguments
keywords will be interpreted as the ``feature name``; values must be instances of
Halotools component models
Returns
--------
input_model_dictionary : dict
Model dictionary defining the composite model.
supplementary_kwargs : dict
Dictionary of any possible remaining keyword arguments passed to the `__init__` constructor
that are not part of the composite model dictionary, e.g., ``model_feature_calling_sequence``.
See also
---------
:ref:`subhalo_model_factory_parsing_kwargs`
"""
if len(kwargs) == 0:
msg = ("You did not pass any model features to the factory")
raise HalotoolsError(msg)
if 'baseline_model_instance' in kwargs:
baseline_model_dictionary = kwargs['baseline_model_instance'].model_dictionary
input_model_dictionary = copy(kwargs)
del input_model_dictionary['baseline_model_instance']
# First parse the supplementary keyword arguments,
# such as 'model_feature_calling_sequence',
# from the keywords that are bound to component model instances
possible_supplementary_kwargs = ('galaxy_selection_func',
'halo_selection_func', 'model_feature_calling_sequence')
supplementary_kwargs = {}
for key in possible_supplementary_kwargs:
try:
supplementary_kwargs[key] = copy(input_model_dictionary[key])
del input_model_dictionary[key]
except KeyError:
pass
if 'model_feature_calling_sequence' not in supplementary_kwargs:
supplementary_kwargs['model_feature_calling_sequence'] = None
new_model_dictionary = copy(baseline_model_dictionary)
for key, value in input_model_dictionary.items():
new_model_dictionary[key] = value
return new_model_dictionary, supplementary_kwargs
else:
input_model_dictionary = copy(kwargs)
# First parse the supplementary keyword arguments,
# such as 'model_feature_calling_sequence',
# from the keywords that are bound to component model instances,
# such as 'stellar_mass'
possible_supplementary_kwargs = ('galaxy_selection_func',
'halo_selection_func', 'model_feature_calling_sequence')
supplementary_kwargs = {}
for key in possible_supplementary_kwargs:
try:
supplementary_kwargs[key] = copy(input_model_dictionary[key])
del input_model_dictionary[key]
except KeyError:
pass
if 'model_feature_calling_sequence' not in supplementary_kwargs:
supplementary_kwargs['model_feature_calling_sequence'] = None
self._enforce_component_model_format(input_model_dictionary)
return input_model_dictionary, supplementary_kwargs
def _enforce_component_model_format(self, candidate_model_dictionary):
""" Private method to ensure that the input model dictionary is properly formatted.
"""
msg_preface = ("\nYou passed the following keyword argument "
"to the SubhaloModelFactory: ``%s``\n")
msg_conclusion = ("See the `~halotools.empirical_models.SubhaloModelFactory` "
"docstring for further details.\n")
for feature_key, component_model in candidate_model_dictionary.items():
cl = component_model.__class__
clname = cl.__name__
if isinstance(component_model, cl):
pass
elif issubclass(component_model, cl):
msg = (msg_preface + "Instead of binding an instance of ``" + clname +
"`` to this keyword,\n"
"instead you bound the ``"+clname+"`` itself.\n"
"The structure of Halotools model dictionaries is strictly to accept \n"
"component model instances, not component model classes. \n" + msg_conclusion)
raise HalotoolsError(msg % feature_key)
def build_model_feature_calling_sequence(self, supplementary_kwargs):
""" Method uses the ``model_feature_calling_sequence`` passed to __init__, if available.
If no such argument was passed, the method chooses a *mostly* random order for the calling sequence,
excepting only for cases where either there is a feature named ``stellar_mass`` or ``luminosity``,
which are always called first in the absence of explicit instructions to the contrary.
Parameters
-----------
supplementary_kwargs : dict
Dictionary storing all keyword arguments passed to the `__init__` constructor that were
not part of the input model dictionary.
Returns
-------
model_feature_calling_sequence : list
List of strings specifying the order in which the component models will be called upon
during mock population to execute their methods.
See also
---------
:ref:`model_feature_calling_sequence_mechanism`
"""
########################
# Require that all elements of the input model_feature_calling_sequence
# were also keyword arguments to the __init__ constructor
try:
model_feature_calling_sequence = list(supplementary_kwargs['model_feature_calling_sequence'])
for model_feature in model_feature_calling_sequence:
try:
assert model_feature in list(self._input_model_dictionary.keys())
except AssertionError:
msg = ("\nYour input ``model_feature_calling_sequence`` has a ``%s`` element\n"
"that does not appear in the keyword arguments you passed to the SubhaloModelFactory.\n"
"For every element of the input ``model_feature_calling_sequence``, "
"there must be a corresponding \n"
"keyword argument to which a component model instance is bound.\n")
raise HalotoolsError(msg % model_feature)
except TypeError:
# The supplementary_kwargs['model_feature_calling_sequence'] was None, triggering a TypeError,
# so we will use the default calling sequence instead
# The default sequence will be to first use the centrals_occupation (if relevant),
# then any possible additional occupation features, then any possible remaining features
model_feature_calling_sequence = []
if 'stellar_mass' in self._input_model_dictionary:
model_feature_calling_sequence.append('stellar_mass')
remaining_keys = [key for key in self._input_model_dictionary if key != 'stellar_mass']
model_feature_calling_sequence.extend(remaining_keys)
elif 'luminosity' in self._input_model_dictionary:
model_feature_calling_sequence.append('luminosity')
remaining_keys = [key for key in self._input_model_dictionary if key != 'luminosity']
model_feature_calling_sequence.extend(remaining_keys)
else:
model_feature_calling_sequence = list(self._input_model_dictionary.keys())
########################
# Now conversely require that all remaining __init__ constructor keyword arguments
# appear in the model_feature_calling_sequence
for constructor_kwarg in self._input_model_dictionary:
try:
assert constructor_kwarg in model_feature_calling_sequence
except AssertionError:
msg = ("\nYou passed ``%s`` as a keyword argument to the SubhaloModelFactory constructor.\n"
"This keyword argument does not appear in your input ``model_feature_calling_sequence``\n"
"and is otherwise not recognized.\n")
raise HalotoolsError(msg % constructor_kwarg)
########################
return model_feature_calling_sequence
def set_inherited_methods(self):
""" Function determines which component model methods are inherited by the composite model.
Each component model *should* have a ``_mock_generation_calling_sequence`` attribute
that provides the sequence of method names to call during mock population. Additionally,
each component *should* have a ``_methods_to_inherit`` attribute that determines
which methods will be inherited by the composite model.
The ``_mock_generation_calling_sequence`` list *should* be a subset of ``_methods_to_inherit``.
If any of the above conditions fail, no exception will be raised during the construction
of the composite model. Instead, an empty list will be forcibly attached to each
component model for which these lists may have been missing.
Also, for each component model, if there are any elements of ``_mock_generation_calling_sequence``
that were missing from ``_methods_to_inherit``, all such elements will be forcibly added to
that component model's ``_methods_to_inherit``.
Finally, each component model *should* have an ``_attrs_to_inherit`` attribute that determines
which attributes will be inherited by the composite model. If any component models did not
implement the ``_attrs_to_inherit``, an empty list is forcibly added to the component model.
After calling the set_inherited_methods method, it will be therefore be entirely safe to
run a for loop over each component model's ``_methods_to_inherit`` and ``_attrs_to_inherit``,
even if these lists were forgotten or irrelevant to that particular component.
"""
_method_repetition_check = []
_attrs_repetition_check = []
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
# Ensure that all methods in the calling sequence are inherited
try:
mock_making_methods = component_model._mock_generation_calling_sequence
except AttributeError:
mock_making_methods = []
try:
inherited_methods = component_model._methods_to_inherit
except AttributeError:
inherited_methods = []
component_model._methods_to_inherit = []
missing_methods = (
set(mock_making_methods) -
set(inherited_methods).intersection(set(mock_making_methods)))
for methodname in missing_methods:
component_model._methods_to_inherit.append(methodname)
_method_repetition_check.extend(component_model._methods_to_inherit)
if not hasattr(component_model, '_attrs_to_inherit'):
component_model._attrs_to_inherit = []
_attrs_repetition_check.extend(component_model._attrs_to_inherit)
# Check that we do not have any method names to inherit that appear
# in more than one component model
repeated_method_msg = ("\n The method name ``%s`` appears "
"in more than one component model.\n You should rename this method in one of your "
"component models to disambiguate.\n")
repeated_method_list = ([methodname for methodname, count in
list(collections.Counter(_method_repetition_check).items()) if count > 1]
)
if repeated_method_list != []:
example_repeated_methodname = repeated_method_list[0]
raise HalotoolsError(repeated_method_msg % example_repeated_methodname)
# Check that we do not have any attributes to inherit that appear
# in more than one component model
repeated_attr_msg = ("\n The attribute name ``%s`` appears "
"in more than one component model.\n "
"Only ignore this message if you are confident "
"that this will not result in unintended behavior\n")
repeated_attr_list = ([attr for attr, count in
list(collections.Counter(_attrs_repetition_check).items()) if count > 1]
)
if repeated_attr_list != []:
example_repeated_attr = repeated_attr_list[0]
warn(repeated_attr_msg % example_repeated_attr)
def set_primary_behaviors(self, **kwargs):
""" Creates names and behaviors for the primary methods of `SubhaloModelFactory`
that will be used by the outside world.
Notes
-----
The new methods created here are given standardized names,
for consistent communication with the rest of the package.
This consistency is particularly important for mock-making,
so that the `SubhaloModelFactory` can always call the same functions
regardless of the complexity of the model.
The behaviors of the methods created here are defined elsewhere;
`set_primary_behaviors` just creates a symbolic link to those external behaviors.
See also
---------
:ref:`subhalo_model_factory_inheriting_behaviors`
"""
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
for methodname in component_model._methods_to_inherit:
new_method_name = methodname
new_method_behavior = self.update_param_dict_decorator(
component_model, methodname)
setattr(self, new_method_name, new_method_behavior)
docstring = getattr(component_model, methodname).__doc__
getattr(self, new_method_name).__doc__ = docstring
attrs_to_inherit = list(set(
component_model._attrs_to_inherit))
for attrname in attrs_to_inherit:
new_attr_name = attrname
attr = getattr(component_model, attrname)
setattr(self, new_attr_name, attr)
def update_param_dict_decorator(self, component_model, func_name):
"""
Decorator used to propagate any possible changes in the composite model param_dict
down to the appropriate component model param_dict.
The behavior of the methods bound to the composite model are decorated versions
of the methods defined in the component models. The decoration is done with
`update_param_dict_decorator`. For each function that gets bound to the
composite model, what this decorator does is search the param_dict of the
component_model associated with the function, and update all matching keys
in that param_dict with the param_dict of the composite.
This way, all the user needs to do is make changes to the composite model
param_dict. Then, when calling any method of the composite model,
the changed values of the param_dict automatically propagate down
to the component model before calling upon its behavior.
This allows the composite_model to control behavior
of functions that it does not define.
Parameters
-----------
component_model : obj
Instance of the component model in which the behavior of the function is defined.
func_name : string
Name of the method in the component model whose behavior is being decorated.
Returns
--------
decorated_func : function
Function object whose behavior is identical
to the behavior of the function in the component model,
except that the component model param_dict is first updated with any
possible changes to corresponding parameters in the composite model param_dict.
See also
--------
:ref:`update_param_dict_decorator_mechanism`
:ref:`param_dict_mechanism`
"""
return ModelFactory.update_param_dict_decorator(self, component_model, func_name)
def set_calling_sequence(self):
""" Method used to determine the sequence of function calls that will be made during
mock population. The methods of each component model will be called one after the other;
the order in which the component models are called upon is determined by
``_model_feature_calling_sequence``.
When each component model is called, the sequence of methods that are called for that
component is determined by the ``_mock_generation_calling_sequence`` attribute
bound to the component model instance.
See :ref:`model_feature_calling_sequence_mechanism` for further details.
"""
self._mock_generation_calling_sequence = []
missing_calling_sequence_msg = ("\nComponent models typically have a list attribute called "
"_mock_generation_calling_sequence.\nThis list determines the methods that are called "
"by the mock factory, and the order in which they are called.\n"
"The ``%s`` component model has no such method.\n"
"Only ignore this warning if you are sure this is not an error.\n")
repeated_calling_sequence_element_msg = ("\n The method name ``%s`` that appears "
"in the calling sequence of the \n``%s`` component model also appears in the "
"calling sequence of another model.\nYou should rename this method in one of your "
"component models to disambiguate.\n")
# The model dictionary is an OrderedDict that is already appropriately structured
feature_sequence = list(self.model_dictionary.keys())
###############
# Loop over feature_sequence and successively append each component model's
# calling sequence to the composite model calling sequence
for feature in feature_sequence:
component_model = self.model_dictionary[feature]
if hasattr(component_model, '_mock_generation_calling_sequence'):
component_method_list = (
[name for name in component_model._mock_generation_calling_sequence]
)
# test to make sure we have no repeated method names
intersection = set(component_method_list) & set(self._mock_generation_calling_sequence)
if intersection != set():
methodname = list(intersection)[0]
t = (methodname, component_model.__class__.__name__)
raise HalotoolsError(repeated_calling_sequence_element_msg % t)
self._mock_generation_calling_sequence.extend(component_method_list)
else:
warn(missing_calling_sequence_msg % component_model.__class__.__name__)
def set_model_redshift(self):
"""
"""
zlist = list(model.redshift for model in list(self.model_dictionary.values())
if hasattr(model, 'redshift'))
if len(set(zlist)) == 0:
self.redshift = sim_defaults.default_redshift
elif len(set(zlist)) == 1:
self.redshift = float(zlist[0])
else:
msg = ("Inconsistency between the redshifts of the component models:\n\n")
for modelname, model in self.model_dictionary.items():
clname = model.__class__.__name__
if hasattr(model, 'redshift'):
zs = str(model.redshift)
msg += ("For modelname = ``" + modelname + "``, the " +
clname+" instance has redshift = " + zs + "\n")
raise HalotoolsError(msg)
def build_prim_sec_haloprop_list(self):
""" Method builds the ``_haloprop_list`` of strings.
This list stores the names of all halo catalog columns
that appear as either ``prim_haloprop_key`` or ``sec_haloprop_key`` of any component model.
For all strings appearing in ``_haloprop_list``, the mock ``galaxy_table`` will have
a corresponding column storing the halo property inherited by the mock galaxy.
"""
haloprop_list = []
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
if hasattr(component_model, 'prim_haloprop_key'):
haloprop_list.append(component_model.prim_haloprop_key)
if hasattr(component_model, 'sec_haloprop_key'):
haloprop_list.append(component_model.sec_haloprop_key)
if hasattr(component_model, 'list_of_haloprops_needed'):
haloprop_list.extend(component_model.list_of_haloprops_needed)
self._haloprop_list = list(set(haloprop_list))
def build_publication_list(self):
""" Method collects together all publications from each of the component models.
"""
pub_list = []
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
try:
pubs = component_model.publications
if type(pubs) in [str, str]:
pub_list.append(pubs)
elif type(pubs) is list:
pub_list.extend(pubs)
else:
clname = component_model.__class__.__name__
msg = ("The ``publications`` attribute of the " + clname + " feature\n"
"must be a string or list of strings")
raise HalotoolsError(msg)
except AttributeError:
pass
self.publications = list(set(pub_list))
def set_warning_suppressions(self):
""" Method used to determine whether a warning should be issued if the
`build_init_param_dict` method detects the presence of multiple appearances
of the same parameter name.
If *any* of the component model instances have a
``_suppress_repeated_param_warning`` attribute that is set to the boolean True value,
then no warning will be issued even if there are multiple appearances of the same
parameter name. This allows the user to not be bothered with warning messages for cases
where it is understood that there will be no conflicting behavior.
See also
---------
build_init_param_dict
"""
self._suppress_repeated_param_warning = False
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
if hasattr(component_model, '_suppress_repeated_param_warning'):
self._suppress_repeated_param_warning += component_model._suppress_repeated_param_warning
def build_init_param_dict(self):
""" Create the ``param_dict`` attribute of the instance. The ``param_dict`` is a dictionary storing
the full collection of parameters controlling the behavior of the composite model.
The ``param_dict`` dictionary is determined by examining the
``param_dict`` attribute of every component model, and building up a composite
dictionary from them. It is permissible for the same parameter name to appear more than once
amongst a set of component models, but a warning will be issued in such cases.
Notes
-----
In MCMC applications, the items of ``param_dict`` defines the possible
parameter set explored by the likelihood engine.
Changing the values of the parameters in ``param_dict``
will propagate to the behavior of the component models
when the relevant methods are called.
See also
---------
set_warning_suppressions
:ref:`param_dict_mechanism`
"""
self.param_dict = {}
try:
suppress_warning = self._suppress_repeated_param_warning
except AttributeError:
suppress_warning = False
msg = ("\n\nThe param_dict key %s appears in more than one component model.\n"
"This is permissible, but if you are seeing this message you should be sure you "
"understand it.\nIn particular, double-check that this parameter does not have "
"conflicting meanings across components.\n"
"\nIf you do not wish to see this message every time you instantiate, \n"
"simply attach a _suppress_repeated_param_warning attribute \n"
"to any of your component models and set this variable to ``True``.\n")
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
if not hasattr(component_model, 'param_dict'):
component_model.param_dict = {}
intersection = set(self.param_dict) & set(component_model.param_dict)
if intersection != set():
for key in intersection:
if suppress_warning is False:
warn(msg % key)
for key, value in component_model.param_dict.items():
self.param_dict[key] = value
self._init_param_dict = copy(self.param_dict)
def build_dtype_list(self):
""" Create the `_galprop_dtypes_to_allocate` attribute that determines
the name and data type of every galaxy property that will appear in the mock ``galaxy_table``.
This attribute is determined by examining the
`_galprop_dtypes_to_allocate` attribute of every component model, and building a composite
set of all these dtypes, enforcing self-consistency in cases where the same galaxy property
appears more than once.
See also
---------
:ref:`galprop_dtypes_to_allocate_mechanism`
"""
dtype_list = []
# Loop over all component features in the composite model
for feature, component_model in self.model_dictionary.items():
# Column dtypes to add to mock galaxy_table
if hasattr(component_model, '_galprop_dtypes_to_allocate'):
dtype_list.append(component_model._galprop_dtypes_to_allocate)
self._galprop_dtypes_to_allocate = model_helpers.create_composite_dtype(dtype_list)
def restore_init_param_dict(self):
""" Reset all values of the current ``param_dict`` to the values
the class was instantiated with.
Primary behaviors are reset as well, as this is how the
inherited behaviors get bound to the values in ``param_dict``.
See also
---------
:ref:`param_dict_mechanism`
"""
self.param_dict = self._init_param_dict
self.set_primary_behaviors()
self.set_calling_sequence()
def populate_mock(self, halocat, masking_function=None, **kwargs):
"""
Method used to populate a simulation
with a Monte Carlo realization of a model.
After calling this method, the model instance
will have a new ``mock`` attribute.
You can then access the galaxy population via
``model.mock.galaxy_table``, an Astropy `~astropy.table.Table`.
See :ref:`subhalo_mock_factory_source_notes`
for an in-depth tutorial on the mock-making algorithm.
Parameters
----------
halocat : object
Either an instance of `~halotools.sim_manager.CachedHaloCatalog`
or `~halotools.sim_manager.UserSuppliedHaloCatalog`.
masking_function : function, optional
Function object used to place a mask on the halo table prior to
calling the mock generating functions. Calling signature of the
function should be to accept a single positional argument storing
a table, and returning a boolean numpy array that will be used
as a fancy indexing mask. All masked halos will be ignored during
mock population. Default is None.
Notes
-----
Note the difference between the
`halotools.empirical_models.SubhaloMockFactory.populate` method and the
closely related method
`halotools.empirical_models.SubhaloModelFactory.populate_mock`.
The `~halotools.empirical_models.SubhaloModelFactory.populate_mock` method
is bound to a composite model instance and is called the *first* time
a composite model is used to generate a mock. Calling the
`~halotools.empirical_models.SubhaloModelFactory.populate_mock` method creates
the `~halotools.empirical_models.SubhaloMockFactory` instance and binds it to
composite model. From then on, if you want to *repopulate* a new Universe
with the same composite model, you should instead call the
`~halotools.empirical_models.SubhaloMockFactory.populate` method
bound to ``model.mock``. The reason for this distinction is that
calling `~halotools.empirical_models.SubhaloModelFactory.populate_mock`
triggers a large number of relatively expensive pre-processing steps
and self-consistency checks that need only be carried out once.
See the Examples section below for an explicit demonstration.
In particular, if you are running an MCMC type analysis,
you will choose your halo catalog and completeness cuts, and call
`populate_mock` with the appropriate arguments. Thereafter, you can
explore parameter space by changing the values stored in the
``param_dict`` dictionary attached to the model, and then calling the
`~halotools.empirical_models.MockFactory.populate` method
bound to ``model.mock``. Any changes to the ``param_dict`` of the
model will automatically propagate into the behavior of
the `~halotools.empirical_models.MockFactory.populate` method.
Examples
----------
Here we'll use a pre-built model to demonstrate basic usage.
The syntax shown below is the same for all composite models,
whether they are pre-built by Halotools or built by you with `SubhaloModelFactory`.
>>> from halotools.empirical_models import PrebuiltSubhaloModelFactory
>>> model_instance = PrebuiltSubhaloModelFactory('behroozi10')
Here we will use a fake simulation, but you can populate mocks
using any instance of `~halotools.sim_manager.CachedHaloCatalog` or
`~halotools.sim_manager.UserSuppliedHaloCatalog`.
>>> from halotools.sim_manager import FakeSim
>>> halocat = FakeSim()
>>> model_instance.populate_mock(halocat)
Your ``model_instance`` now has a ``mock`` attribute bound to it.
You can call the `~halotools.empirical_models.SubhaloMockFactory.populate`
method bound to the ``mock``, which will repopulate the halo catalog
with a new Monte Carlo realization of the model.
>>> model_instance.mock.populate()
If you want to change the behavior of your model, just change the
values stored in the ``param_dict``. Differences in the parameter values
will change the behavior of the mock-population.
>>> model_instance.param_dict['scatter_model_param1'] = 0.25
>>> model_instance.mock.populate()
See also
-----------
:ref:`subhalo_mock_factory_source_notes`
"""
if masking_function is not None:
ModelFactory.populate_mock(self, halocat, masking_function=masking_function, **kwargs)
else:
ModelFactory.populate_mock(self, halocat, **kwargs)
def _test_dictionary_consistency(self):
"""
"""
for component_model in list(self.model_dictionary.values()):
try:
assert hasattr(component_model, '_methods_to_inherit')
for methodname in component_model._methods_to_inherit:
assert hasattr(component_model, methodname)
except AssertionError:
clname = component_model.__class__.__name__
msg = ("You bound an instance of the ``"+clname+"`` to this keyword,\n"
"but the instance does not have "
"a properly defined ``_methods_to_inherit`` attribute.\n"
"At a minimum, all component models must have this attribute, \n"
"even if there is only an empty list bound to it.\n"
"Any items in this list must be names of methods bound to "
"the component model.\n")
raise HalotoolsError(msg)
|
astropyREPO_NAMEhalotoolsPATH_START.@halotools_extracted@halotools-master@halotools@empirical_models@factories@subhalo_model_factory.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/statsmodels/regression/tests/results/__init__.py",
"type": "Python"
}
|
statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@statsmodels@regression@tests@results@__init__.py@.PATH_END.py
|
|
{
"filename": "propagate.py",
"repo_name": "jrenaud90/TidalPy",
"repo_path": "TidalPy_extracted/TidalPy-main/TidalPy/radial_solver/matrix/propagate.py",
"type": "Python"
}
|
""" Propagation of tidal solution using the fundamental matrix
References
----------
SVC16 : Sabadini, Vermeerson, & Cambiotti (2016, DOI: 10.1007/978-94-017-7552-6)
HH14 : Henning & Hurford (2014, DOI: 10.1088/0004-637X/789/1/30)
ID : IcyDwarf Code by Marc Neveu (https://github.com/MarcNeveu/IcyDwarf/blob/master/IcyDwarf/Thermal.h)
B13 : Beuthe (2013, DOI: 10.1016/j.icarus.2012.11.020)
"""
import numpy as np
from TidalPy.utilities.performance import njit
@njit(cacheable=True)
def propagate(
fundamental_matrix: np.ndarray, fundamental_matrix_inverse: np.ndarray, derivative_matrix: np.ndarray,
inner_boundary_condition: np.ndarray, world_radius: float,
order_l: int = 2
) -> np.ndarray:
""" This function will propagate the incompressible tidal equations, via the fundamental matrix, through a world or
layers sub-shells.
Assumptions:
- Each shell is homogeneous (However, it can have different properties from the shells above/below it).
References
----------
See appendix of HH14 and lines ~2355 of thermal.h in ID
Parameters
----------
fundamental_matrix : np.ndarray
Fundamental (incompressible) Matrix (6 x 6 x N); See fundamental.py
fundamental_matrix_inverse : np.ndarray
Inverse of the fundamental (incompressible) Matrix (6 x 6 x N); See fundamental.py
derivative_matrix : np.ndarray
Derivative matrix, A, defined by the function dy/dr = A dot y
inner_boundary_condition : np.ndarray
Boundary condition Matrix (6 x 3) of the tidal problem at the inner surface.
world_radius : float
Radius of the world [m]
order_l : int = 2
Tidal harmonic order
Returns
-------
tidal_y : np.ndarray
Matrix [6 x N] of tidal solutions. See decompression.py on how useful information is extracted.
"""
num_shells = fundamental_matrix.shape[2]
# Find propagation matrix
# Prop matrix has 6 rows but only 3 columns.
propagation_mtx = np.zeros((6, 3, num_shells), dtype=np.complex128)
# It is initialized with the inner boundary condition matrix.
propagation_mtx[:, :, 0] = inner_boundary_condition
# Step through the planet's shells
for i in range(num_shells):
if i == 0:
# Skip central shell - boundary conditions provided.
continue
# Dot product of between the fundamental matrix and (the dot product between the inverse fundamental matrix one
# layer below and the propagation matrix one layer below).
propagation_mtx[:, :, i] = \
fundamental_matrix[:, :, i] @ (fundamental_matrix_inverse[:, :, i - 1] @ propagation_mtx[:, :, i - 1])
# Surface condition matrix is a 3x3 matrix of the top-most shell of the aggregate matrix's rows [3, 4, 6]
surface_matrix = np.vstack((propagation_mtx[2, :, -1], propagation_mtx[3, :, -1], propagation_mtx[5, :, -1]))
# The surface boundary conditions are (always?) static and only based on the radius and order-l
surface_bc = np.zeros((3,), dtype=np.complex128)
surface_bc[2] = -1. * (2. * order_l + 1.) / world_radius
# Invert the surface matrix and solve using the surface boundary condition
surface_matrix_inv = np.linalg.inv(surface_matrix)
surface_solution = surface_matrix_inv @ surface_bc
# Using the aggregate matrix, solve for the tidal "y"s
y_sv = np.empty((6, num_shells), dtype=np.complex128)
y_derivative_sv = np.empty((6, num_shells), dtype=np.complex128)
for i in range(num_shells):
y_sv[:, i] = propagation_mtx[:, :, i] @ surface_solution
# Calculate the derivatives of the tidal solution with radius
y_derivative_sv[:, i] = derivative_matrix[:, :, i] @ y_sv[:, i]
# As discussed in B13 (discussed near their equation 7), SVC16 (and the earlier 2004 book) use a different
# convention for tidal_y than is used by Takeuchi and Saito (1972). Since a good chunk of the field follows the
# latter, we will do the same. Below are the conversions from SVC16 to TS72
y = np.empty_like(y_sv)
y[0, :] = y_sv[0, :]
y[1, :] = y_sv[2, :] # Flip y3 and y2
y[2, :] = y_sv[1, :] # Flip y3 and y2
y[3, :] = y_sv[3, :]
y[4, :] = y_sv[4, :] * -1.
y[5, :] = y_sv[5, :] * -1.
return y
|
jrenaud90REPO_NAMETidalPyPATH_START.@TidalPy_extracted@TidalPy-main@TidalPy@radial_solver@matrix@propagate.py@.PATH_END.py
|
{
"filename": "readme.md",
"repo_name": "STEllAR-GROUP/octotiger",
"repo_path": "octotiger_extracted/octotiger-master/tools/docker/base_image/readme.md",
"type": "Markdown"
}
|
# Supported tags and respective `Dockerfile` links
* `prerequisites-clang9-debug`, LLVM 9.0.0, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-clang.dockerfile)
* build arguments: `UBUNTU_RELEASE=18.04` `LLVM_RELEASE=9.0.0` `BUILD_TYPE=Debug`
* `prerequisites-clang8-debug`, LLVM 8.0.1, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-clang.dockerfile)
* build arguments: `UBUNTU_RELEASE=18.04` `LLVM_RELEASE=8.0.1` `BUILD_TYPE=Debug`
* `prerequisites-clang7-debug`, LLVM 7.0.1, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-clang.dockerfile)
* build arguments: `UBUNTU_RELEASE=18.04` `LLVM_RELEASE=7.0.1` `BUILD_TYPE=Debug`
* `prerequisites-clang6-debug`, LLVM 6.0.1, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-clang.dockerfile)
* build arguments: `UBUNTU_RELEASE=16.04` `LLVM_RELEASE=6.0.1` `BUILD_TYPE=Debug`
* `prerequisites-gcc9-relwithdebinfo`, GCC 9, HPX and Vc built in RelWithDebInfo mode, Boost built in release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=RelWithDebInfo`
* `prerequisites-gcc8-relwithdebinfo`, GCC 8, HPX and Vc built in RelWithDebInfo mode, Boost built in release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=RelWithDebInfo`
* `prerequisites-gcc7-relwithdebinfo`, GCC 7, HPX and Vc built in RelWithDebInfo mode, Boost built in release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=RelWithDebInfo`
* `prerequisites-gcc6-relwithdebinfo`, GCC 6, HPX and Vc built in RelWithDebInfo mode, Boost built in release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=RelWithDebInfo`
* `prerequisites-gcc9-debug`, GCC 9, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=9` `BUILD_TYPE=Debug`
* `prerequisites-gcc8-debug`, GCC 8, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=Debug`
* `prerequisites-gcc7-debug`, GCC 7, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=7` `BUILD_TYPE=Debug`
* `prerequisites-gcc6-debug`, GCC 6, HPX, Vc, and Boost built in Debug mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=6` `BUILD_TYPE=Debug`
* `prerequisites-gcc9`, GCC 9, HPX, Vc, and Boost built in Release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=9` `BUILD_TYPE=Release`
* `prerequisites-gcc8`, GCC 8, HPX, Vc, and Boost built in Release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=8` `BUILD_TYPE=Release`
* `prerequisites-gcc7`, GCC 7, HPX, Vc, and Boost built in Release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=7` `BUILD_TYPE=Release`
* `prerequisites-gcc6`, GCC 6, HPX, Vc, and Boost built in Release mode
* [Dockerfile](https://github.com/STEllAR-GROUP/octotiger/blob/master/tools/docker/base_image/prerequisites-gcc.dockerfile)
* build arguments: `GCC_RELEASE=6` `BUILD_TYPE=Release`
* **Supported architectures**:
`amd64`
# How to use this image
This image exists for sake of facilitating testing non-CUDA Octo-Tiger builds
with different versions of GCC and Clang. It contains Boost, HPX, Vc, HDF5,
Silo, and build tools needed to build Octo-Tiger. The most straightforward way
to use this image is creating a container with `docker run -it --rm
stellargroup/octotiger:prerequisites-gcc6` and building Octo-Tiger in the
container.
## Build Octo-Tiger inside the Docker container
If you would like to experiment with Octo-Tiger inside a container, you can try
a set of commands like this:
```console
$ docker run -it stellargroup/octotiger:prerequisites-gcc6-debug
$ git clone https://github.com/STEllAR-GROUP/octotiger.git --depth=1
$ cmake -H/octotiger -B/octotiger/build -DCMAKE_BUILD_TYPE=Debug -DHPX_DIR=/local/hpx/lib/cmake/HPX -DVc_DIR=/local/vc/lib/cmake/Vc -DSilo_DIR=/local/silo -DHDF5_ROOT=/local/hdf5 -DBOOST_ROOT=/local/boost -GNinja
$ cmake --build /octotiger/build
$ cd /octotiger/build
$ ctest --output-on-failure
```
This will clone the current Octo-Tiger HEAD on master and run all the tests.
# License
Distributed under the Boost Software License, Version 1.0. (See
<http://www.boost.org/LICENSE_1_0.txt>)
|
STEllAR-GROUPREPO_NAMEoctotigerPATH_START.@octotiger_extracted@octotiger-master@tools@docker@base_image@readme.md@.PATH_END.py
|
{
"filename": "_tickcolor.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scattermap/marker/colorbar/_tickcolor.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class TickcolorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self,
plotly_name="tickcolor",
parent_name="scattermap.marker.colorbar",
**kwargs,
):
super(TickcolorValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
**kwargs,
)
|
plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scattermap@marker@colorbar@_tickcolor.py@.PATH_END.py
|
{
"filename": "_clicktoshow.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/annotation/_clicktoshow.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class ClicktoshowValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="clicktoshow", parent_name="layout.annotation", **kwargs
):
super(ClicktoshowValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "arraydraw"),
values=kwargs.pop("values", [False, "onoff", "onout"]),
**kwargs,
)
|
plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@annotation@_clicktoshow.py@.PATH_END.py
|
{
"filename": "test_arpack.py",
"repo_name": "scipy/scipy",
"repo_path": "scipy_extracted/scipy-main/scipy/sparse/linalg/_eigen/arpack/tests/test_arpack.py",
"type": "Python"
}
|
__usage__ = """
To run tests locally:
python tests/test_arpack.py [-l<int>] [-v<int>]
"""
import threading
import itertools
import numpy as np
from numpy.testing import assert_allclose, assert_equal, suppress_warnings
from pytest import raises as assert_raises
import pytest
from numpy import dot, conj, random
from scipy.linalg import eig, eigh
from scipy.sparse import csc_array, csr_array, diags_array, random_array
from scipy.sparse.linalg import LinearOperator, aslinearoperator
from scipy.sparse.linalg._eigen.arpack import (eigs, eigsh, arpack,
ArpackNoConvergence)
from scipy._lib._gcutils import assert_deallocated, IS_PYPY
# precision for tests
_ndigits = {'f': 3, 'd': 11, 'F': 3, 'D': 11}
def _get_test_tolerance(type_char, mattype=None, D_type=None, which=None):
"""
Return tolerance values suitable for a given test:
Parameters
----------
type_char : {'f', 'd', 'F', 'D'}
Data type in ARPACK eigenvalue problem
mattype : {csr_array, aslinearoperator, asarray}, optional
Linear operator type
Returns
-------
tol
Tolerance to pass to the ARPACK routine
rtol
Relative tolerance for outputs
atol
Absolute tolerance for outputs
"""
rtol = {'f': 3000 * np.finfo(np.float32).eps,
'F': 3000 * np.finfo(np.float32).eps,
'd': 2000 * np.finfo(np.float64).eps,
'D': 2000 * np.finfo(np.float64).eps}[type_char]
atol = rtol
tol = 0
if mattype is aslinearoperator and type_char in ('f', 'F'):
# iterative methods in single precision: worse errors
# also: bump ARPACK tolerance so that the iterative method converges
tol = 30 * np.finfo(np.float32).eps
rtol *= 5
if (
isinstance(mattype, type) and issubclass(mattype, csr_array)
and type_char in ('f', 'F')
):
# sparse in single precision: worse errors
rtol *= 5
if (
which in ('LM', 'SM', 'LA')
and D_type.name == "gen-hermitian-Mc"
):
if type_char == 'F':
# missing case 1, 2, and more, from PR 14798
rtol *= 5
if type_char == 'D':
# missing more cases, from PR 14798
rtol *= 10
atol *= 10
return tol, rtol, atol
def generate_matrix(N, complex_=False, hermitian=False,
pos_definite=False, sparse=False, rng=None):
M = rng.random((N, N))
if complex_:
M = M + 1j * rng.random((N, N))
if hermitian:
if pos_definite:
if sparse:
i = np.arange(N)
j = rng.randint(N, size=N-2)
i, j = np.meshgrid(i, j)
M[i, j] = 0
M = np.dot(M.conj(), M.T)
else:
M = np.dot(M.conj(), M.T)
if sparse:
i = rng.randint(N, size=N * N // 4)
j = rng.randint(N, size=N * N // 4)
ind = np.nonzero(i == j)
j[ind] = (j[ind] + 1) % N
M[i, j] = 0
M[j, i] = 0
else:
if sparse:
i = rng.randint(N, size=N * N // 2)
j = rng.randint(N, size=N * N // 2)
M[i, j] = 0
return M
def generate_matrix_symmetric(N, pos_definite=False, sparse=False, rng=None):
M = rng.random((N, N))
M = 0.5 * (M + M.T) # Make M symmetric
if pos_definite:
Id = N * np.eye(N)
if sparse:
M = csr_array(M)
M += Id
else:
if sparse:
M = csr_array(M)
return M
def assert_allclose_cc(actual, desired, **kw):
"""Almost equal or complex conjugates almost equal"""
try:
assert_allclose(actual, desired, **kw)
except AssertionError:
assert_allclose(actual, conj(desired), **kw)
def argsort_which(eigenvalues, typ, k, which,
sigma=None, OPpart=None, mode=None):
"""Return sorted indices of eigenvalues using the "which" keyword
from eigs and eigsh"""
if sigma is None:
reval = np.round(eigenvalues, decimals=_ndigits[typ])
else:
if mode is None or mode == 'normal':
if OPpart is None:
reval = 1. / (eigenvalues - sigma)
elif OPpart == 'r':
reval = 0.5 * (1. / (eigenvalues - sigma)
+ 1. / (eigenvalues - np.conj(sigma)))
elif OPpart == 'i':
reval = -0.5j * (1. / (eigenvalues - sigma)
- 1. / (eigenvalues - np.conj(sigma)))
elif mode == 'cayley':
reval = (eigenvalues + sigma) / (eigenvalues - sigma)
elif mode == 'buckling':
reval = eigenvalues / (eigenvalues - sigma)
else:
raise ValueError(f"mode='{mode}' not recognized")
reval = np.round(reval, decimals=_ndigits[typ])
if which in ['LM', 'SM']:
ind = np.argsort(abs(reval))
elif which in ['LR', 'SR', 'LA', 'SA', 'BE']:
ind = np.argsort(np.real(reval))
elif which in ['LI', 'SI']:
# for LI,SI ARPACK returns largest,smallest abs(imaginary) why?
if typ.islower():
ind = np.argsort(abs(np.imag(reval)))
else:
ind = np.argsort(np.imag(reval))
else:
raise ValueError(f"which='{which}' is unrecognized")
if which in ['LM', 'LA', 'LR', 'LI']:
return ind[-k:]
elif which in ['SM', 'SA', 'SR', 'SI']:
return ind[:k]
elif which == 'BE':
return np.concatenate((ind[:k//2], ind[k//2-k:]))
def eval_evec(symmetric, d, typ, k, which, v0=None, sigma=None,
mattype=np.asarray, OPpart=None, mode='normal'):
general = ('bmat' in d)
if symmetric:
eigs_func = eigsh
else:
eigs_func = eigs
if general:
err = (f"error for {eigs_func.__name__}:general, typ={typ}, which={which}, "
f"sigma={sigma}, mattype={mattype.__name__},"
f" OPpart={OPpart}, mode={mode}")
else:
err = (f"error for {eigs_func.__name__}:standard, typ={typ}, which={which}, "
f"sigma={sigma}, mattype={mattype.__name__}, "
f"OPpart={OPpart}, mode={mode}")
a = d['mat'].astype(typ)
ac = mattype(a)
if general:
b = d['bmat'].astype(typ)
bc = mattype(b)
# get exact eigenvalues
exact_eval = d['eval'].astype(typ.upper())
ind = argsort_which(exact_eval, typ, k, which,
sigma, OPpart, mode)
exact_eval = exact_eval[ind]
# compute arpack eigenvalues
kwargs = dict(which=which, v0=v0, sigma=sigma)
if eigs_func is eigsh:
kwargs['mode'] = mode
else:
kwargs['OPpart'] = OPpart
# compute suitable tolerances
kwargs['tol'], rtol, atol = _get_test_tolerance(typ, mattype, d, which)
# on rare occasions, ARPACK routines return results that are proper
# eigenvalues and -vectors, but not necessarily the ones requested in
# the parameter which. This is inherent to the Krylov methods, and
# should not be treated as a failure. If such a rare situation
# occurs, the calculation is tried again (but at most a few times).
ntries = 0
while ntries < 5:
# solve
if general:
try:
eigenvalues, evec = eigs_func(ac, k, bc, **kwargs)
except ArpackNoConvergence:
kwargs['maxiter'] = 20*a.shape[0]
eigenvalues, evec = eigs_func(ac, k, bc, **kwargs)
else:
try:
eigenvalues, evec = eigs_func(ac, k, **kwargs)
except ArpackNoConvergence:
kwargs['maxiter'] = 20*a.shape[0]
eigenvalues, evec = eigs_func(ac, k, **kwargs)
ind = argsort_which(eigenvalues, typ, k, which,
sigma, OPpart, mode)
eigenvalues = eigenvalues[ind]
evec = evec[:, ind]
try:
# check eigenvalues
assert_allclose_cc(eigenvalues, exact_eval, rtol=rtol, atol=atol,
err_msg=err)
check_evecs = True
except AssertionError:
check_evecs = False
ntries += 1
if check_evecs:
# check eigenvectors
LHS = np.dot(a, evec)
if general:
RHS = eigenvalues * np.dot(b, evec)
else:
RHS = eigenvalues * evec
assert_allclose(LHS, RHS, rtol=rtol, atol=atol, err_msg=err)
break
# check eigenvalues
assert_allclose_cc(eigenvalues, exact_eval, rtol=rtol, atol=atol, err_msg=err)
class DictWithRepr(dict):
def __init__(self, name):
self.name = name
def __repr__(self):
return f"<{self.name}>"
class SymmetricParams:
def __init__(self):
self.eigs = eigsh
self.which = ['LM', 'SM', 'LA', 'SA', 'BE']
self.mattypes = [csr_array, aslinearoperator, np.asarray]
self.sigmas_modes = {None: ['normal'],
0.5: ['normal', 'buckling', 'cayley']}
# generate matrices
# these should all be float32 so that the eigenvalues
# are the same in float32 and float64
N = 6
rng = np.random.RandomState(2300)
Ar = generate_matrix(N, hermitian=True,
pos_definite=True,
rng=rng).astype('f').astype('d')
M = generate_matrix(N, hermitian=True,
pos_definite=True,
rng=rng).astype('f').astype('d')
Ac = generate_matrix(N, hermitian=True, pos_definite=True,
complex_=True, rng=rng).astype('F').astype('D')
Mc = generate_matrix(N, hermitian=True, pos_definite=True,
complex_=True, rng=rng).astype('F').astype('D')
v0 = rng.random(N)
# standard symmetric problem
SS = DictWithRepr("std-symmetric")
SS['mat'] = Ar
SS['v0'] = v0
SS['eval'] = eigh(SS['mat'], eigvals_only=True)
# general symmetric problem
GS = DictWithRepr("gen-symmetric")
GS['mat'] = Ar
GS['bmat'] = M
GS['v0'] = v0
GS['eval'] = eigh(GS['mat'], GS['bmat'], eigvals_only=True)
# standard hermitian problem
SH = DictWithRepr("std-hermitian")
SH['mat'] = Ac
SH['v0'] = v0
SH['eval'] = eigh(SH['mat'], eigvals_only=True)
# general hermitian problem
GH = DictWithRepr("gen-hermitian")
GH['mat'] = Ac
GH['bmat'] = M
GH['v0'] = v0
GH['eval'] = eigh(GH['mat'], GH['bmat'], eigvals_only=True)
# general hermitian problem with hermitian M
GHc = DictWithRepr("gen-hermitian-Mc")
GHc['mat'] = Ac
GHc['bmat'] = Mc
GHc['v0'] = v0
GHc['eval'] = eigh(GHc['mat'], GHc['bmat'], eigvals_only=True)
self.real_test_cases = [SS, GS]
self.complex_test_cases = [SH, GH, GHc]
class NonSymmetricParams:
def __init__(self):
self.eigs = eigs
self.which = ['LM', 'LR', 'LI'] # , 'SM', 'LR', 'SR', 'LI', 'SI']
self.mattypes = [csr_array, aslinearoperator, np.asarray]
self.sigmas_OPparts = {None: [None],
0.1: ['r'],
0.1 + 0.1j: ['r', 'i']}
# generate matrices
# these should all be float32 so that the eigenvalues
# are the same in float32 and float64
N = 6
rng = np.random.RandomState(2300)
Ar = generate_matrix(N, rng=rng).astype('f').astype('d')
M = generate_matrix(N, hermitian=True,
pos_definite=True, rng=rng).astype('f').astype('d')
Ac = generate_matrix(N, complex_=True, rng=rng).astype('F').astype('D')
v0 = rng.random(N)
# standard real nonsymmetric problem
SNR = DictWithRepr("std-real-nonsym")
SNR['mat'] = Ar
SNR['v0'] = v0
SNR['eval'] = eig(SNR['mat'], left=False, right=False)
# general real nonsymmetric problem
GNR = DictWithRepr("gen-real-nonsym")
GNR['mat'] = Ar
GNR['bmat'] = M
GNR['v0'] = v0
GNR['eval'] = eig(GNR['mat'], GNR['bmat'], left=False, right=False)
# standard complex nonsymmetric problem
SNC = DictWithRepr("std-cmplx-nonsym")
SNC['mat'] = Ac
SNC['v0'] = v0
SNC['eval'] = eig(SNC['mat'], left=False, right=False)
# general complex nonsymmetric problem
GNC = DictWithRepr("gen-cmplx-nonsym")
GNC['mat'] = Ac
GNC['bmat'] = M
GNC['v0'] = v0
GNC['eval'] = eig(GNC['mat'], GNC['bmat'], left=False, right=False)
self.real_test_cases = [SNR, GNR]
self.complex_test_cases = [SNC, GNC]
@pytest.mark.iterations(1)
@pytest.mark.thread_unsafe
def test_symmetric_modes(num_parallel_threads):
assert num_parallel_threads == 1
params = SymmetricParams()
k = 2
symmetric = True
for D in params.real_test_cases:
for typ in 'fd':
for which in params.which:
for mattype in params.mattypes:
for (sigma, modes) in params.sigmas_modes.items():
for mode in modes:
eval_evec(symmetric, D, typ, k, which,
None, sigma, mattype, None, mode)
def test_hermitian_modes():
params = SymmetricParams()
k = 2
symmetric = True
for D in params.complex_test_cases:
for typ in 'FD':
for which in params.which:
if which == 'BE':
continue # BE invalid for complex
for mattype in params.mattypes:
for sigma in params.sigmas_modes:
eval_evec(symmetric, D, typ, k, which,
None, sigma, mattype)
def test_symmetric_starting_vector():
params = SymmetricParams()
symmetric = True
for k in [1, 2, 3, 4, 5]:
for D in params.real_test_cases:
for typ in 'fd':
v0 = random.rand(len(D['v0'])).astype(typ)
eval_evec(symmetric, D, typ, k, 'LM', v0)
def test_symmetric_no_convergence():
rng = np.random.RandomState(1234)
m = generate_matrix(30, hermitian=True, pos_definite=True, rng=rng)
tol, rtol, atol = _get_test_tolerance('d')
try:
w, v = eigsh(m, 4, which='LM', v0=m[:, 0], maxiter=5, tol=tol, ncv=9)
raise AssertionError("Spurious no-error exit")
except ArpackNoConvergence as err:
k = len(err.eigenvalues)
if k <= 0:
raise AssertionError("Spurious no-eigenvalues-found case") from err
w, v = err.eigenvalues, err.eigenvectors
assert_allclose(dot(m, v), w * v, rtol=rtol, atol=atol)
def test_real_nonsymmetric_modes():
params = NonSymmetricParams()
k = 2
symmetric = False
for D in params.real_test_cases:
for typ in 'fd':
for which in params.which:
for mattype in params.mattypes:
for sigma, OPparts in params.sigmas_OPparts.items():
for OPpart in OPparts:
eval_evec(symmetric, D, typ, k, which,
None, sigma, mattype, OPpart)
def test_complex_nonsymmetric_modes():
params = NonSymmetricParams()
k = 2
symmetric = False
for D in params.complex_test_cases:
for typ in 'DF':
for which in params.which:
for mattype in params.mattypes:
for sigma in params.sigmas_OPparts:
eval_evec(symmetric, D, typ, k, which,
None, sigma, mattype)
def test_standard_nonsymmetric_starting_vector():
params = NonSymmetricParams()
sigma = None
symmetric = False
for k in [1, 2, 3, 4]:
for d in params.complex_test_cases:
for typ in 'FD':
A = d['mat']
n = A.shape[0]
v0 = random.rand(n).astype(typ)
eval_evec(symmetric, d, typ, k, "LM", v0, sigma)
def test_general_nonsymmetric_starting_vector():
params = NonSymmetricParams()
sigma = None
symmetric = False
for k in [1, 2, 3, 4]:
for d in params.complex_test_cases:
for typ in 'FD':
A = d['mat']
n = A.shape[0]
v0 = random.rand(n).astype(typ)
eval_evec(symmetric, d, typ, k, "LM", v0, sigma)
def test_standard_nonsymmetric_no_convergence():
rng = np.random.RandomState(1234)
m = generate_matrix(30, complex_=True, rng=rng)
tol, rtol, atol = _get_test_tolerance('d')
try:
w, v = eigs(m, 4, which='LM', v0=m[:, 0], maxiter=5, tol=tol)
raise AssertionError("Spurious no-error exit")
except ArpackNoConvergence as err:
k = len(err.eigenvalues)
if k <= 0:
raise AssertionError("Spurious no-eigenvalues-found case") from err
w, v = err.eigenvalues, err.eigenvectors
for ww, vv in zip(w, v.T):
assert_allclose(dot(m, vv), ww * vv, rtol=rtol, atol=atol)
def test_eigen_bad_shapes():
# A is not square.
A = csc_array(np.zeros((2, 3)))
assert_raises(ValueError, eigs, A)
def test_eigen_bad_kwargs():
# Test eigen on wrong keyword argument
A = csc_array(np.zeros((8, 8)))
assert_raises(ValueError, eigs, A, which='XX')
def test_ticket_1459_arpack_crash():
for dtype in [np.float32, np.float64]:
# This test does not seem to catch the issue for float32,
# but we made the same fix there, just to be sure
N = 6
k = 2
np.random.seed(2301)
A = np.random.random((N, N)).astype(dtype)
v0 = np.array([-0.71063568258907849895, -0.83185111795729227424,
-0.34365925382227402451, 0.46122533684552280420,
-0.58001341115969040629, -0.78844877570084292984e-01],
dtype=dtype)
# Should not crash:
evals, evecs = eigs(A, k, v0=v0)
@pytest.mark.skipif(IS_PYPY, reason="Test not meaningful on PyPy")
def test_linearoperator_deallocation():
# Check that the linear operators used by the Arpack wrappers are
# deallocatable by reference counting -- they are big objects, so
# Python's cyclic GC may not collect them fast enough before
# running out of memory if eigs/eigsh are called in a tight loop.
M_d = np.eye(10)
M_s = csc_array(M_d)
M_o = aslinearoperator(M_d)
with assert_deallocated(lambda: arpack.SpLuInv(M_s)):
pass
with assert_deallocated(lambda: arpack.LuInv(M_d)):
pass
with assert_deallocated(lambda: arpack.IterInv(M_s)):
pass
with assert_deallocated(lambda: arpack.IterOpInv(M_o, None, 0.3)):
pass
with assert_deallocated(lambda: arpack.IterOpInv(M_o, M_o, 0.3)):
pass
@pytest.mark.thread_unsafe
def test_parallel_threads():
results = []
v0 = np.random.rand(50)
def worker():
x = diags_array([1, -2, 1], offsets=[-1, 0, 1], shape=(50, 50))
w, v = eigs(x, k=3, v0=v0)
results.append(w)
w, v = eigsh(x, k=3, v0=v0)
results.append(w)
threads = [threading.Thread(target=worker) for k in range(10)]
for t in threads:
t.start()
for t in threads:
t.join()
worker()
for r in results:
assert_allclose(r, results[-1])
def test_reentering():
# Just some linear operator that calls eigs recursively
def A_matvec(x):
x = diags_array([1, -2, 1], offsets=[-1, 0, 1], shape=(50, 50))
w, v = eigs(x, k=1)
return v / w[0]
A = LinearOperator(matvec=A_matvec, dtype=float, shape=(50, 50))
# The Fortran code is not reentrant, so this fails (gracefully, not crashing)
assert_raises(RuntimeError, eigs, A, k=1)
assert_raises(RuntimeError, eigsh, A, k=1)
def test_regression_arpackng_1315():
# Check that issue arpack-ng/#1315 is not present.
# Adapted from arpack-ng/TESTS/bug_1315_single.c
# If this fails, then the installed ARPACK library is faulty.
for dtype in [np.float32, np.float64]:
np.random.seed(1234)
w0 = np.arange(1, 1000+1).astype(dtype)
A = diags_array([w0], offsets=[0], shape=(1000, 1000))
v0 = np.random.rand(1000).astype(dtype)
w, v = eigs(A, k=9, ncv=2*9+1, which="LM", v0=v0)
assert_allclose(np.sort(w), np.sort(w0[-9:]),
rtol=1e-4)
def test_eigs_for_k_greater():
# Test eigs() for k beyond limits.
rng = np.random.RandomState(1234)
A_sparse = diags_array([1, -2, 1], offsets=[-1, 0, 1], shape=(4, 4)) # sparse
A = generate_matrix(4, sparse=False, rng=rng)
M_dense = rng.random((4, 4))
M_sparse = generate_matrix(4, sparse=True, rng=rng)
M_linop = aslinearoperator(M_dense)
eig_tuple1 = eig(A, b=M_dense)
eig_tuple2 = eig(A, b=M_sparse)
with suppress_warnings() as sup:
sup.filter(RuntimeWarning)
assert_equal(eigs(A, M=M_dense, k=3), eig_tuple1)
assert_equal(eigs(A, M=M_dense, k=4), eig_tuple1)
assert_equal(eigs(A, M=M_dense, k=5), eig_tuple1)
assert_equal(eigs(A, M=M_sparse, k=5), eig_tuple2)
# M as LinearOperator
assert_raises(TypeError, eigs, A, M=M_linop, k=3)
# Test 'A' for different types
assert_raises(TypeError, eigs, aslinearoperator(A), k=3)
assert_raises(TypeError, eigs, A_sparse, k=3)
def test_eigsh_for_k_greater():
# Test eigsh() for k beyond limits.
rng = np.random.RandomState(1234)
A_sparse = diags_array([1, -2, 1], offsets=[-1, 0, 1], shape=(4, 4)) # sparse
A = generate_matrix(4, sparse=False, rng=rng)
M_dense = generate_matrix_symmetric(4, pos_definite=True, rng=rng)
M_sparse = generate_matrix_symmetric(
4, pos_definite=True, sparse=True, rng=rng)
M_linop = aslinearoperator(M_dense)
eig_tuple1 = eigh(A, b=M_dense)
eig_tuple2 = eigh(A, b=M_sparse)
with suppress_warnings() as sup:
sup.filter(RuntimeWarning)
assert_equal(eigsh(A, M=M_dense, k=4), eig_tuple1)
assert_equal(eigsh(A, M=M_dense, k=5), eig_tuple1)
assert_equal(eigsh(A, M=M_sparse, k=5), eig_tuple2)
# M as LinearOperator
assert_raises(TypeError, eigsh, A, M=M_linop, k=4)
# Test 'A' for different types
assert_raises(TypeError, eigsh, aslinearoperator(A), k=4)
assert_raises(TypeError, eigsh, A_sparse, M=M_dense, k=4)
def test_real_eigs_real_k_subset():
rng = np.random.default_rng(2)
n = 10
A = random_array(shape=(n, n), density=0.5, rng=rng)
A.data *= 2
A.data -= 1
A += A.T # make symmetric to test real eigenvalues
v0 = np.ones(n)
whichs = ['LM', 'SM', 'LR', 'SR', 'LI', 'SI']
dtypes = [np.float32, np.float64]
for which, sigma, dtype in itertools.product(whichs, [None, 0, 5], dtypes):
prev_w = np.array([], dtype=dtype)
eps = np.finfo(dtype).eps
for k in range(1, 9):
w, z = eigs(A.astype(dtype), k=k, which=which, sigma=sigma,
v0=v0.astype(dtype), tol=0)
assert_allclose(np.linalg.norm(A.dot(z) - z * w), 0, atol=np.sqrt(eps))
# Check that the set of eigenvalues for `k` is a subset of that for `k+1`
dist = abs(prev_w[:,None] - w).min(axis=1)
assert_allclose(dist, 0, atol=np.sqrt(eps))
prev_w = w
|
scipyREPO_NAMEscipyPATH_START.@scipy_extracted@scipy-main@scipy@sparse@linalg@_eigen@arpack@tests@test_arpack.py@.PATH_END.py
|
{
"filename": "master_script.py",
"repo_name": "benrendle/AIMS",
"repo_path": "AIMS_extracted/AIMS-master/AIMS-Py35/Binary_Grid_Generation/master_script.py",
"type": "Python"
}
|
# Makes script that extracts the tgz files
########################################
def get_lines(filename):
lines = []
with open(filename) as f:
for line in f:
lines.append(line.rstrip("\n"))
return lines
##########################################
root = "/home/miglioa/GridCLESAIMS_D" # location of .tgz folders
input_file = "files"
output_file = "extract"
lines = get_lines(input_file)
names = []
directs = []
for line in lines:
names.append(line[2:])
directs.append(root)
commands = []
for i in range(len(names)):
# command line to create extraction code for each input file
commands.append("cd " + directs[i] + "\ntar xzvf " + names[i] + "\n")
with open(output_file,"w") as f:
f.write("#!/bin/bash\n\n")
for command in commands:
f.write(command)
|
benrendleREPO_NAMEAIMSPATH_START.@AIMS_extracted@AIMS-master@AIMS-Py35@Binary_Grid_Generation@master_script.py@.PATH_END.py
|
{
"filename": "_family.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/indicator/delta/font/_family.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class FamilyValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self, plotly_name="family", parent_name="indicator.delta.font", **kwargs
):
super(FamilyValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "plot"),
no_blank=kwargs.pop("no_blank", True),
strict=kwargs.pop("strict", True),
**kwargs,
)
|
plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@indicator@delta@font@_family.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "ratt-ru/QuartiCal",
"repo_path": "QuartiCal_extracted/QuartiCal-main/quartical/weights/__init__.py",
"type": "Python"
}
|
ratt-ruREPO_NAMEQuartiCalPATH_START.@QuartiCal_extracted@QuartiCal-main@quartical@weights@__init__.py@.PATH_END.py
|
|
{
"filename": "runtime.py",
"repo_name": "desihub/LSS",
"repo_path": "LSS_extracted/LSS-main/py/LSS/DESI_ke/runtime.py",
"type": "Python"
}
|
import os
import sys
import time
import warnings
from astropy.io.fits.verify import VerifyWarning
from astropy.utils.metadata import MergeConflictWarning
# Suppress verify warnings, e.g. HIERARCH card length.
warnings.simplefilter('ignore', category=VerifyWarning)
warnings.simplefilter('ignore', category=MergeConflictWarning)
def sizeofMB(xx):
return sys.getsizeof(xx)
def calc_runtime(start, log=None, memuse=False, xx=None):
runtime = time.time() - start
runtime /= 60.
if memuse:
# COSMA5 has 302 compute nodes, each with 128GB RAM and 16 cores
# https://www.dur.ac.uk/icc/cosma/cosma5/
import psutil
process = psutil.Process(os.getpid())
memuse = process.memory_info().rss / 1.e6 # [MB]
memuse = ' (memuse {}: {:.2f}MB)'.format(os.getpid(), memuse)
else:
memuse = ''
if log != None:
msg = '{} after {:.4f} mins{}.'.format(log, runtime, memuse)
if xx is not None:
msg = msg.replace('Writing', 'Writing ({}MB)'.format(sizeofMB(xx)))
msg = msg.replace('Reading', 'Reading ({}MB)'.format(sizeofMB(xx)))
print(msg)
return runtime
if __name__ == '__main__':
start = time.time()
runtime = calc_runtime(start, 'Read randoms')
|
desihubREPO_NAMELSSPATH_START.@LSS_extracted@LSS-main@py@LSS@DESI_ke@runtime.py@.PATH_END.py
|
{
"filename": "tracer_relativistic_effects.ipynb",
"repo_name": "MikeSWang/HorizonGRound",
"repo_path": "HorizonGRound_extracted/HorizonGRound-master/application/publication/tracer_relativistic_effects.ipynb",
"type": "Jupyter Notebook"
}
|
# Relativistic Effects in Tracer Clustering
We consider relativistic corrections to the power spectrum multipoles as constrained by luminosity function results, and compare it to other effects such as redshift-space distortions (RSD) and scale-dependent linear bias from local primordial non-Gaussianity $f_\mathrm{NL}$ (PNG).
```python
import matplotlib.pyplot as plt
import numpy as np
import plotly.graph_objects as go
from astropy.constants import c
from astropy.cosmology import Planck15
from matplotlib.ticker import AutoMinorLocator
from nbodykit.cosmology import LinearPower, Planck15 as Planck_15
from conf import PATHEXT
from horizonground.clustering_modification import (
non_gaussianity_correction_factor,
relativistic_correction_factor,
relativistic_correction_value,
standard_kaiser_factor,
)
from horizonground.lumfunc_modeller import (
LumFuncModeller,
alpha_emitter_schechter_lumfunc,
quasar_PLE_lumfunc,
)
```
We choose a tracer, set the fiducial redshift, wavenumbers and $f_\mathrm{NL}$ value.
```python
FIDUCIAL_REDSHIFT = 2.
FIDUCIAL_DENSE_REDSHIFTS = np.r_[
np.linspace(0.7, 2.15, num=30), [2.19, 2.21], np.linspace(2.25, 4.0, num=36)
]
FIDUCIAL_NON_GAUSSNIANTY = 1.
FIDUCIAL_WAVENUMBERS = np.logspace(-4, -1, num=60+1)
```
```python
tracer = np.random.choice(['QSO', 'H-alpha'])
print(f"Tracer: {tracer}")
if tracer == 'QSO': # QSOs
b_1 = 0.278 * ((1 + FIDUCIAL_REDSHIFT) ** 2 - 6.565) + 2.393
# b_1 = 1.2 / Planck_15.scale_independent_growth_factor(FIDUCIAL_REDSHIFT)
p = 1.6
elif tracer == 'H-alpha': # H-alpha emitters
b_1 = np.sqrt(1 + FIDUCIAL_REDSHIFT)
p = 1.0
```
Tracer: QSO
## Evolution and magnification biases
We specify the luminosity function model depending on the tracer.
```python
if tracer == 'QSO':
modeller = LumFuncModeller.from_parameter_file(
parameter_file=PATHEXT/"eBOSS_QSO_LF_PLE_model_fits.txt",
model_lumfunc=quasar_PLE_lumfunc,
brightness_variable='magnitude',
threshold_value=-22.,
cosmology=Planck15
)
elif tracer == 'H-alpha':
modeller = LumFuncModeller.from_parameter_file(
parameter_file=PATHEXT/"H-alpha_LF_Schechter_model_fits.txt",
model_lumfunc=alpha_emitter_schechter_lumfunc,
brightness_variable='luminosity',
threshold_value=3.e-16,
normalisation_redshift=2.,
cosmology=Planck15
)
```
The tracer evolution bias $f_\mathrm{e}$ and magnification biase $s$ are obtained as functions of redshift.
```python
evolution_bias = list(map(modeller.evolution_bias, FIDUCIAL_DENSE_REDSHIFTS))
magnification_bias = list(map(modeller.magnification_bias, FIDUCIAL_DENSE_REDSHIFTS))
```
```python
lines = [
go.Scatter(x=FIDUCIAL_DENSE_REDSHIFTS, y=bias, name=name)
for name, bias in zip(
[r'$b_\mathrm{e}$', r'$s$'],
[evolution_bias, magnification_bias]
)
]
fig = go.Figure(data=lines)
fig.update_layout(
width=500, height=400,
title=dict(text=tracer, x=0.5, y=0.85, xanchor='center'),
xaxis=dict(
title=r"$z$",
showline=True, showgrid=True,
linecolor='#000000', linewidth=1.5,
tickmode='auto', ticks='inside', ticklen=6, tickwidth=2, nticks=10, mirror='ticks'
),
yaxis=dict(
title=r"bias",
showline=True, showgrid=True,
linecolor='#000000', linewidth=1.5,
tickmode='auto', ticks='inside', ticklen=6, tickwidth=2, nticks=10, mirror='ticks'
),
font=dict(family="Times New Roman", size=14),
plot_bgcolor='#ffffff'
)
```
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e,r;this.length>t.length?(e=this,r=t):(e=t,r=this);for(var n=0;n<r.length;n++)this.words[n]=e.words[n]^r.words[n];if(this!==e)for(;n<e.length;n++)this.words[n]=e.words[n];return this.length=e.length,this.strip()},i.prototype.ixor=function(t){return n(0==(this.negative|t.negative)),this.iuxor(t)},i.prototype.xor=function(t){return this.length>t.length?this.clone().ixor(t):t.clone().ixor(this)},i.prototype.uxor=function(t){return this.length>t.length?this.clone().iuxor(t):t.clone().iuxor(this)},i.prototype.inotn=function(t){n("number"==typeof t&&t>=0);var e=0|Math.ceil(t/26),r=t%26;this._expand(e),r>0&&e--;for(var a=0;a<e;a++)this.words[a]=67108863&~this.words[a];return r>0&&(this.words[a]=~this.words[a]&67108863>>26-r),this.strip()},i.prototype.notn=function(t){return this.clone().inotn(t)},i.prototype.setn=function(t,e){n("number"==typeof t&&t>=0);var r=t/26|0,a=t%26;return this._expand(r+1),this.words[r]=e?this.words[r]|1<<a:this.words[r]&~(1<<a),this.strip()},i.prototype.iadd=function(t){var e,r,n;if(0!==this.negative&&0===t.negative)return this.negative=0,e=this.isub(t),this.negative^=1,this._normSign();if(0===this.negative&&0!==t.negative)return t.negative=0,e=this.isub(t),t.negative=1,e._normSign();this.length>t.length?(r=this,n=t):(r=t,n=this);for(var a=0,i=0;i<n.length;i++)e=(0|r.words[i])+(0|n.words[i])+a,this.words[i]=67108863&e,a=e>>>26;for(;0!==a&&i<r.length;i++)e=(0|r.words[i])+a,this.words[i]=67108863&e,a=e>>>26;if(this.length=r.length,0!==a)this.words[this.length]=a,this.length++;else if(r!==this)for(;i<r.length;i++)this.words[i]=r.words[i];return this},i.prototype.add=function(t){var e;return 0!==t.negative&&0===this.negative?(t.negative=0,e=this.sub(t),t.negative^=1,e):0===t.negative&&0!==this.negative?(this.negative=0,e=t.sub(this),this.negative=1,e):this.length>t.length?this.clone().iadd(t):t.clone().iadd(this)},i.prototype.isub=function(t){if(0!==t.negative){t.negative=0;var e=this.iadd(t);return t.negative=1,e._normSign()}if(0!==this.negative)return this.negative=0,this.iadd(t),this.negative=1,this._normSign();var r,n,a=this.cmp(t);if(0===a)return this.negative=0,this.length=1,this.words[0]=0,this;a>0?(r=this,n=t):(r=t,n=this);for(var i=0,o=0;o<n.length;o++)i=(e=(0|r.words[o])-(0|n.words[o])+i)>>26,this.words[o]=67108863&e;for(;0!==i&&o<r.length;o++)i=(e=(0|r.words[o])+i)>>26,this.words[o]=67108863&e;if(0===i&&o<r.length&&r!==this)for(;o<r.length;o++)this.words[o]=r.words[o];return this.length=Math.max(this.length,o),r!==this&&(this.negative=1),this.strip()},i.prototype.sub=function(t){return this.clone().isub(t)};var p=function(t,e,r){var n,a,i,o=t.words,s=e.words,l=r.words,c=0,u=0|o[0],h=8191&u,f=u>>>13,p=0|o[1],d=8191&p,g=p>>>13,m=0|o[2],v=8191&m,y=m>>>13,x=0|o[3],b=8191&x,_=x>>>13,w=0|o[4],T=8191&w,k=w>>>13,A=0|o[5],M=8191&A,S=A>>>13,E=0|o[6],C=8191&E,L=E>>>13,P=0|o[7],I=8191&P,z=P>>>13,O=0|o[8],D=8191&O,R=O>>>13,F=0|o[9],B=8191&F,N=F>>>13,j=0|s[0],V=8191&j,U=j>>>13,q=0|s[1],H=8191&q,G=q>>>13,Y=0|s[2],W=8191&Y,Z=Y>>>13,X=0|s[3],J=8191&X,K=X>>>13,Q=0|s[4],$=8191&Q,tt=Q>>>13,et=0|s[5],rt=8191&et,nt=et>>>13,at=0|s[6],it=8191&at,ot=at>>>13,st=0|s[7],lt=8191&st,ct=st>>>13,ut=0|s[8],ht=8191&ut,ft=ut>>>13,pt=0|s[9],dt=8191&pt,gt=pt>>>13;r.negative=t.negative^e.negative,r.length=19;var mt=(c+(n=Math.imul(h,V))|0)+((8191&(a=(a=Math.imul(h,U))+Math.imul(f,V)|0))<<13)|0;c=((i=Math.imul(f,U))+(a>>>13)|0)+(mt>>>26)|0,mt&=67108863,n=Math.imul(d,V),a=(a=Math.imul(d,U))+Math.imul(g,V)|0,i=Math.imul(g,U);var vt=(c+(n=n+Math.imul(h,H)|0)|0)+((8191&(a=(a=a+Math.imul(h,G)|0)+Math.imul(f,H)|0))<<13)|0;c=((i=i+Math.imul(f,G)|0)+(a>>>13)|0)+(vt>>>26)|0,vt&=67108863,n=Math.imul(v,V),a=(a=Math.imul(v,U))+Math.imul(y,V)|0,i=Math.imul(y,U),n=n+Math.imul(d,H)|0,a=(a=a+Math.imul(d,G)|0)+Math.imul(g,H)|0,i=i+Math.imul(g,G)|0;var yt=(c+(n=n+Math.imul(h,W)|0)|0)+((8191&(a=(a=a+Math.imul(h,Z)|0)+Math.imul(f,W)|0))<<13)|0;c=((i=i+Math.imul(f,Z)|0)+(a>>>13)|0)+(yt>>>26)|0,yt&=67108863,n=Math.imul(b,V),a=(a=Math.imul(b,U))+Math.imul(_,V)|0,i=Math.imul(_,U),n=n+Math.imul(v,H)|0,a=(a=a+Math.imul(v,G)|0)+Math.imul(y,H)|0,i=i+Math.imul(y,G)|0,n=n+Math.imul(d,W)|0,a=(a=a+Math.imul(d,Z)|0)+Math.imul(g,W)|0,i=i+Math.imul(g,Z)|0;var xt=(c+(n=n+Math.imul(h,J)|0)|0)+((8191&(a=(a=a+Math.imul(h,K)|0)+Math.imul(f,J)|0))<<13)|0;c=((i=i+Math.imul(f,K)|0)+(a>>>13)|0)+(xt>>>26)|0,xt&=67108863,n=Math.imul(T,V),a=(a=Math.imul(T,U))+Math.imul(k,V)|0,i=Math.imul(k,U),n=n+Math.imul(b,H)|0,a=(a=a+Math.imul(b,G)|0)+Math.imul(_,H)|0,i=i+Math.imul(_,G)|0,n=n+Math.imul(v,W)|0,a=(a=a+Math.imul(v,Z)|0)+Math.imul(y,W)|0,i=i+Math.imul(y,Z)|0,n=n+Math.imul(d,J)|0,a=(a=a+Math.imul(d,K)|0)+Math.imul(g,J)|0,i=i+Math.imul(g,K)|0;var bt=(c+(n=n+Math.imul(h,$)|0)|0)+((8191&(a=(a=a+Math.imul(h,tt)|0)+Math.imul(f,$)|0))<<13)|0;c=((i=i+Math.imul(f,tt)|0)+(a>>>13)|0)+(bt>>>26)|0,bt&=67108863,n=Math.imul(M,V),a=(a=Math.imul(M,U))+Math.imul(S,V)|0,i=Math.imul(S,U),n=n+Math.imul(T,H)|0,a=(a=a+Math.imul(T,G)|0)+Math.imul(k,H)|0,i=i+Math.imul(k,G)|0,n=n+Math.imul(b,W)|0,a=(a=a+Math.imul(b,Z)|0)+Math.imul(_,W)|0,i=i+Math.imul(_,Z)|0,n=n+Math.imul(v,J)|0,a=(a=a+Math.imul(v,K)|0)+Math.imul(y,J)|0,i=i+Math.imul(y,K)|0,n=n+Math.imul(d,$)|0,a=(a=a+Math.imul(d,tt)|0)+Math.imul(g,$)|0,i=i+Math.imul(g,tt)|0;var _t=(c+(n=n+Math.imul(h,rt)|0)|0)+((8191&(a=(a=a+Math.imul(h,nt)|0)+Math.imul(f,rt)|0))<<13)|0;c=((i=i+Math.imul(f,nt)|0)+(a>>>13)|0)+(_t>>>26)|0,_t&=67108863,n=Math.imul(C,V),a=(a=Math.imul(C,U))+Math.imul(L,V)|0,i=Math.imul(L,U),n=n+Math.imul(M,H)|0,a=(a=a+Math.imul(M,G)|0)+Math.imul(S,H)|0,i=i+Math.imul(S,G)|0,n=n+Math.imul(T,W)|0,a=(a=a+Math.imul(T,Z)|0)+Math.imul(k,W)|0,i=i+Math.imul(k,Z)|0,n=n+Math.imul(b,J)|0,a=(a=a+Math.imul(b,K)|0)+Math.imul(_,J)|0,i=i+Math.imul(_,K)|0,n=n+Math.imul(v,$)|0,a=(a=a+Math.imul(v,tt)|0)+Math.imul(y,$)|0,i=i+Math.imul(y,tt)|0,n=n+Math.imul(d,rt)|0,a=(a=a+Math.imul(d,nt)|0)+Math.imul(g,rt)|0,i=i+Math.imul(g,nt)|0;var wt=(c+(n=n+Math.imul(h,it)|0)|0)+((8191&(a=(a=a+Math.imul(h,ot)|0)+Math.imul(f,it)|0))<<13)|0;c=((i=i+Math.imul(f,ot)|0)+(a>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(I,V),a=(a=Math.imul(I,U))+Math.imul(z,V)|0,i=Math.imul(z,U),n=n+Math.imul(C,H)|0,a=(a=a+Math.imul(C,G)|0)+Math.imul(L,H)|0,i=i+Math.imul(L,G)|0,n=n+Math.imul(M,W)|0,a=(a=a+Math.imul(M,Z)|0)+Math.imul(S,W)|0,i=i+Math.imul(S,Z)|0,n=n+Math.imul(T,J)|0,a=(a=a+Math.imul(T,K)|0)+Math.imul(k,J)|0,i=i+Math.imul(k,K)|0,n=n+Math.imul(b,$)|0,a=(a=a+Math.imul(b,tt)|0)+Math.imul(_,$)|0,i=i+Math.imul(_,tt)|0,n=n+Math.imul(v,rt)|0,a=(a=a+Math.imul(v,nt)|0)+Math.imul(y,rt)|0,i=i+Math.imul(y,nt)|0,n=n+Math.imul(d,it)|0,a=(a=a+Math.imul(d,ot)|0)+Math.imul(g,it)|0,i=i+Math.imul(g,ot)|0;var Tt=(c+(n=n+Math.imul(h,lt)|0)|0)+((8191&(a=(a=a+Math.imul(h,ct)|0)+Math.imul(f,lt)|0))<<13)|0;c=((i=i+Math.imul(f,ct)|0)+(a>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(D,V),a=(a=Math.imul(D,U))+Math.imul(R,V)|0,i=Math.imul(R,U),n=n+Math.imul(I,H)|0,a=(a=a+Math.imul(I,G)|0)+Math.imul(z,H)|0,i=i+Math.imul(z,G)|0,n=n+Math.imul(C,W)|0,a=(a=a+Math.imul(C,Z)|0)+Math.imul(L,W)|0,i=i+Math.imul(L,Z)|0,n=n+Math.imul(M,J)|0,a=(a=a+Math.imul(M,K)|0)+Math.imul(S,J)|0,i=i+Math.imul(S,K)|0,n=n+Math.imul(T,$)|0,a=(a=a+Math.imul(T,tt)|0)+Math.imul(k,$)|0,i=i+Math.imul(k,tt)|0,n=n+Math.imul(b,rt)|0,a=(a=a+Math.imul(b,nt)|0)+Math.imul(_,rt)|0,i=i+Math.imul(_,nt)|0,n=n+Math.imul(v,it)|0,a=(a=a+Math.imul(v,ot)|0)+Math.imul(y,it)|0,i=i+Math.imul(y,ot)|0,n=n+Math.imul(d,lt)|0,a=(a=a+Math.imul(d,ct)|0)+Math.imul(g,lt)|0,i=i+Math.imul(g,ct)|0;var kt=(c+(n=n+Math.imul(h,ht)|0)|0)+((8191&(a=(a=a+Math.imul(h,ft)|0)+Math.imul(f,ht)|0))<<13)|0;c=((i=i+Math.imul(f,ft)|0)+(a>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,V),a=(a=Math.imul(B,U))+Math.imul(N,V)|0,i=Math.imul(N,U),n=n+Math.imul(D,H)|0,a=(a=a+Math.imul(D,G)|0)+Math.imul(R,H)|0,i=i+Math.imul(R,G)|0,n=n+Math.imul(I,W)|0,a=(a=a+Math.imul(I,Z)|0)+Math.imul(z,W)|0,i=i+Math.imul(z,Z)|0,n=n+Math.imul(C,J)|0,a=(a=a+Math.imul(C,K)|0)+Math.imul(L,J)|0,i=i+Math.imul(L,K)|0,n=n+Math.imul(M,$)|0,a=(a=a+Math.imul(M,tt)|0)+Math.imul(S,$)|0,i=i+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,a=(a=a+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,i=i+Math.imul(k,nt)|0,n=n+Math.imul(b,it)|0,a=(a=a+Math.imul(b,ot)|0)+Math.imul(_,it)|0,i=i+Math.imul(_,ot)|0,n=n+Math.imul(v,lt)|0,a=(a=a+Math.imul(v,ct)|0)+Math.imul(y,lt)|0,i=i+Math.imul(y,ct)|0,n=n+Math.imul(d,ht)|0,a=(a=a+Math.imul(d,ft)|0)+Math.imul(g,ht)|0,i=i+Math.imul(g,ft)|0;var At=(c+(n=n+Math.imul(h,dt)|0)|0)+((8191&(a=(a=a+Math.imul(h,gt)|0)+Math.imul(f,dt)|0))<<13)|0;c=((i=i+Math.imul(f,gt)|0)+(a>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),a=(a=Math.imul(B,G))+Math.imul(N,H)|0,i=Math.imul(N,G),n=n+Math.imul(D,W)|0,a=(a=a+Math.imul(D,Z)|0)+Math.imul(R,W)|0,i=i+Math.imul(R,Z)|0,n=n+Math.imul(I,J)|0,a=(a=a+Math.imul(I,K)|0)+Math.imul(z,J)|0,i=i+Math.imul(z,K)|0,n=n+Math.imul(C,$)|0,a=(a=a+Math.imul(C,tt)|0)+Math.imul(L,$)|0,i=i+Math.imul(L,tt)|0,n=n+Math.imul(M,rt)|0,a=(a=a+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,i=i+Math.imul(S,nt)|0,n=n+Math.imul(T,it)|0,a=(a=a+Math.imul(T,ot)|0)+Math.imul(k,it)|0,i=i+Math.imul(k,ot)|0,n=n+Math.imul(b,lt)|0,a=(a=a+Math.imul(b,ct)|0)+Math.imul(_,lt)|0,i=i+Math.imul(_,ct)|0,n=n+Math.imul(v,ht)|0,a=(a=a+Math.imul(v,ft)|0)+Math.imul(y,ht)|0,i=i+Math.imul(y,ft)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(a=(a=a+Math.imul(d,gt)|0)+Math.imul(g,dt)|0))<<13)|0;c=((i=i+Math.imul(g,gt)|0)+(a>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,W),a=(a=Math.imul(B,Z))+Math.imul(N,W)|0,i=Math.imul(N,Z),n=n+Math.imul(D,J)|0,a=(a=a+Math.imul(D,K)|0)+Math.imul(R,J)|0,i=i+Math.imul(R,K)|0,n=n+Math.imul(I,$)|0,a=(a=a+Math.imul(I,tt)|0)+Math.imul(z,$)|0,i=i+Math.imul(z,tt)|0,n=n+Math.imul(C,rt)|0,a=(a=a+Math.imul(C,nt)|0)+Math.imul(L,rt)|0,i=i+Math.imul(L,nt)|0,n=n+Math.imul(M,it)|0,a=(a=a+Math.imul(M,ot)|0)+Math.imul(S,it)|0,i=i+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,a=(a=a+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,i=i+Math.imul(k,ct)|0,n=n+Math.imul(b,ht)|0,a=(a=a+Math.imul(b,ft)|0)+Math.imul(_,ht)|0,i=i+Math.imul(_,ft)|0;var St=(c+(n=n+Math.imul(v,dt)|0)|0)+((8191&(a=(a=a+Math.imul(v,gt)|0)+Math.imul(y,dt)|0))<<13)|0;c=((i=i+Math.imul(y,gt)|0)+(a>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,J),a=(a=Math.imul(B,K))+Math.imul(N,J)|0,i=Math.imul(N,K),n=n+Math.imul(D,$)|0,a=(a=a+Math.imul(D,tt)|0)+Math.imul(R,$)|0,i=i+Math.imul(R,tt)|0,n=n+Math.imul(I,rt)|0,a=(a=a+Math.imul(I,nt)|0)+Math.imul(z,rt)|0,i=i+Math.imul(z,nt)|0,n=n+Math.imul(C,it)|0,a=(a=a+Math.imul(C,ot)|0)+Math.imul(L,it)|0,i=i+Math.imul(L,ot)|0,n=n+Math.imul(M,lt)|0,a=(a=a+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,i=i+Math.imul(S,ct)|0,n=n+Math.imul(T,ht)|0,a=(a=a+Math.imul(T,ft)|0)+Math.imul(k,ht)|0,i=i+Math.imul(k,ft)|0;var Et=(c+(n=n+Math.imul(b,dt)|0)|0)+((8191&(a=(a=a+Math.imul(b,gt)|0)+Math.imul(_,dt)|0))<<13)|0;c=((i=i+Math.imul(_,gt)|0)+(a>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,$),a=(a=Math.imul(B,tt))+Math.imul(N,$)|0,i=Math.imul(N,tt),n=n+Math.imul(D,rt)|0,a=(a=a+Math.imul(D,nt)|0)+Math.imul(R,rt)|0,i=i+Math.imul(R,nt)|0,n=n+Math.imul(I,it)|0,a=(a=a+Math.imul(I,ot)|0)+Math.imul(z,it)|0,i=i+Math.imul(z,ot)|0,n=n+Math.imul(C,lt)|0,a=(a=a+Math.imul(C,ct)|0)+Math.imul(L,lt)|0,i=i+Math.imul(L,ct)|0,n=n+Math.imul(M,ht)|0,a=(a=a+Math.imul(M,ft)|0)+Math.imul(S,ht)|0,i=i+Math.imul(S,ft)|0;var Ct=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(a=(a=a+Math.imul(T,gt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((i=i+Math.imul(k,gt)|0)+(a>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),a=(a=Math.imul(B,nt))+Math.imul(N,rt)|0,i=Math.imul(N,nt),n=n+Math.imul(D,it)|0,a=(a=a+Math.imul(D,ot)|0)+Math.imul(R,it)|0,i=i+Math.imul(R,ot)|0,n=n+Math.imul(I,lt)|0,a=(a=a+Math.imul(I,ct)|0)+Math.imul(z,lt)|0,i=i+Math.imul(z,ct)|0,n=n+Math.imul(C,ht)|0,a=(a=a+Math.imul(C,ft)|0)+Math.imul(L,ht)|0,i=i+Math.imul(L,ft)|0;var Lt=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(a=(a=a+Math.imul(M,gt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((i=i+Math.imul(S,gt)|0)+(a>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,it),a=(a=Math.imul(B,ot))+Math.imul(N,it)|0,i=Math.imul(N,ot),n=n+Math.imul(D,lt)|0,a=(a=a+Math.imul(D,ct)|0)+Math.imul(R,lt)|0,i=i+Math.imul(R,ct)|0,n=n+Math.imul(I,ht)|0,a=(a=a+Math.imul(I,ft)|0)+Math.imul(z,ht)|0,i=i+Math.imul(z,ft)|0;var Pt=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(a=(a=a+Math.imul(C,gt)|0)+Math.imul(L,dt)|0))<<13)|0;c=((i=i+Math.imul(L,gt)|0)+(a>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,lt),a=(a=Math.imul(B,ct))+Math.imul(N,lt)|0,i=Math.imul(N,ct),n=n+Math.imul(D,ht)|0,a=(a=a+Math.imul(D,ft)|0)+Math.imul(R,ht)|0,i=i+Math.imul(R,ft)|0;var It=(c+(n=n+Math.imul(I,dt)|0)|0)+((8191&(a=(a=a+Math.imul(I,gt)|0)+Math.imul(z,dt)|0))<<13)|0;c=((i=i+Math.imul(z,gt)|0)+(a>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,ht),a=(a=Math.imul(B,ft))+Math.imul(N,ht)|0,i=Math.imul(N,ft);var zt=(c+(n=n+Math.imul(D,dt)|0)|0)+((8191&(a=(a=a+Math.imul(D,gt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((i=i+Math.imul(R,gt)|0)+(a>>>13)|0)+(zt>>>26)|0,zt&=67108863;var Ot=(c+(n=Math.imul(B,dt))|0)+((8191&(a=(a=Math.imul(B,gt))+Math.imul(N,dt)|0))<<13)|0;return c=((i=Math.imul(N,gt))+(a>>>13)|0)+(Ot>>>26)|0,Ot&=67108863,l[0]=mt,l[1]=vt,l[2]=yt,l[3]=xt,l[4]=bt,l[5]=_t,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=Lt,l[15]=Pt,l[16]=It,l[17]=zt,l[18]=Ot,0!==c&&(l[19]=c,r.length++),r};function d(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(p=f),i.prototype.mulTo=function(t,e){var r=this.length+t.length;return 10===this.length&&10===t.length?p(this,t,e):r<63?f(this,t,e):r<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,a=0,i=0;i<r.length-1;i++){var o=a;a=0;for(var s=67108863&n,l=Math.min(i,e.length-1),c=Math.max(0,i-t.length+1);c<=l;c++){var u=i-c,h=(0|t.words[u])*(0|e.words[c]),f=67108863&h;s=67108863&(f=f+s|0),a+=(o=(o=o+(h/67108864|0)|0)+(f>>>26)|0)>>>26,o&=67108863}r.words[i]=s,n=o,o=a}return 0!==n?r.words[i]=n:r.length--,r.strip()}(this,t,e):d(this,t,e)},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=i.prototype._countBits(t)-1,n=0;n<t;n++)e[n]=this.revBin(n,r,t);return e},g.prototype.revBin=function(t,e,r){if(0===t||t===r-1)return t;for(var n=0,a=0;a<e;a++)n|=(1&t)<<e-a-1,t>>=1;return n},g.prototype.permute=function(t,e,r,n,a,i){for(var o=0;o<i;o++)n[o]=e[t[o]],a[o]=r[t[o]]},g.prototype.transform=function(t,e,r,n,a,i){this.permute(i,t,e,r,n,a);for(var o=1;o<a;o<<=1)for(var s=o<<1,l=Math.cos(2*Math.PI/s),c=Math.sin(2*Math.PI/s),u=0;u<a;u+=s)for(var h=l,f=c,p=0;p<o;p++){var d=r[u+p],g=n[u+p],m=r[u+p+o],v=n[u+p+o],y=h*m-f*v;v=h*v+f*m,m=y,r[u+p]=d+m,n[u+p]=g+v,r[u+p+o]=d-m,n[u+p+o]=g-v,p!==s&&(y=l*h-c*f,f=l*f+c*h,h=y)}},g.prototype.guessLen13b=function(t,e){var r=1|Math.max(e,t),n=1&r,a=0;for(r=r/2|0;r;r>>>=1)a++;return 1<<a+1+n},g.prototype.conjugate=function(t,e,r){if(!(r<=1))for(var n=0;n<r/2;n++){var a=t[n];t[n]=t[r-n-1],t[r-n-1]=a,a=e[n],e[n]=-e[r-n-1],e[r-n-1]=-a}},g.prototype.normalize13b=function(t,e){for(var r=0,n=0;n<e/2;n++){var a=8192*Math.round(t[2*n+1]/e)+Math.round(t[2*n]/e)+r;t[n]=67108863&a,r=a<67108864?0:a/67108864|0}return t},g.prototype.convert13b=function(t,e,r,a){for(var i=0,o=0;o<e;o++)i+=0|t[o],r[2*o]=8191&i,i>>>=13,r[2*o+1]=8191&i,i>>>=13;for(o=2*e;o<a;++o)r[o]=0;n(0===i),n(0==(-8192&i))},g.prototype.stub=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=0;return e},g.prototype.mulp=function(t,e,r){var n=2*this.guessLen13b(t.length,e.length),a=this.makeRBT(n),i=this.stub(n),o=new Array(n),s=new Array(n),l=new Array(n),c=new Array(n),u=new Array(n),h=new Array(n),f=r.words;f.length=n,this.convert13b(t.words,t.length,o,n),this.convert13b(e.words,e.length,c,n),this.transform(o,i,s,l,n,a),this.transform(c,i,u,h,n,a);for(var p=0;p<n;p++){var d=s[p]*u[p]-l[p]*h[p];l[p]=s[p]*h[p]+l[p]*u[p],s[p]=d}return this.conjugate(s,l,n),this.transform(s,l,f,i,n,a),this.conjugate(f,i,n),this.normalize13b(f,n),r.negative=t.negative^e.negative,r.length=t.length+e.length,r.strip()},i.prototype.mul=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),this.mulTo(t,e)},i.prototype.mulf=function(t){var e=new i(null);return e.words=new Array(this.length+t.length),d(this,t,e)},i.prototype.imul=function(t){return this.clone().mulTo(t,this)},i.prototype.imuln=function(t){n("number"==typeof t),n(t<67108864);for(var e=0,r=0;r<this.length;r++){var a=(0|this.words[r])*t,i=(67108863&a)+(67108863&e);e>>=26,e+=a/67108864|0,e+=i>>>26,this.words[r]=67108863&i}return 0!==e&&(this.words[r]=e,this.length++),this},i.prototype.muln=function(t){return this.clone().imuln(t)},i.prototype.sqr=function(){return this.mul(this)},i.prototype.isqr=function(){return this.imul(this.clone())},i.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r<e.length;r++){var n=r/26|0,a=r%26;e[r]=(t.words[n]&1<<a)>>>a}return e}(t);if(0===e.length)return new i(1);for(var r=this,n=0;n<e.length&&0===e[n];n++,r=r.sqr());if(++n<e.length)for(var a=r.sqr();n<e.length;n++,a=a.sqr())0!==e[n]&&(r=r.mul(a));return r},i.prototype.iushln=function(t){n("number"==typeof t&&t>=0);var e,r=t%26,a=(t-r)/26,i=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e<this.length;e++){var s=this.words[e]&i,l=(0|this.words[e])-s<<r;this.words[e]=l|o,o=s>>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==a){for(e=this.length-1;e>=0;e--)this.words[e+a]=this.words[e];for(e=0;e<a;e++)this.words[e]=0;this.length+=a}return this.strip()},i.prototype.ishln=function(t){return n(0===this.negative),this.iushln(t)},i.prototype.iushrn=function(t,e,r){var a;n("number"==typeof t&&t>=0),a=e?(e-e%26)/26:0;var i=t%26,o=Math.min((t-i)/26,this.length),s=67108863^67108863>>>i<<i,l=r;if(a-=o,a=Math.max(0,a),l){for(var c=0;c<o;c++)l.words[c]=this.words[c];l.length=o}if(0===o);else if(this.length>o)for(this.length-=o,c=0;c<this.length;c++)this.words[c]=this.words[c+o];else this.words[0]=0,this.length=1;var u=0;for(c=this.length-1;c>=0&&(0!==u||c>=a);c--){var h=0|this.words[c];this.words[c]=u<<26-i|h>>>i,u=h&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},i.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},i.prototype.shln=function(t){return this.clone().ishln(t)},i.prototype.ushln=function(t){return this.clone().iushln(t)},i.prototype.shrn=function(t){return this.clone().ishrn(t)},i.prototype.ushrn=function(t){return this.clone().iushrn(t)},i.prototype.testn=function(t){n("number"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,a=1<<e;return!(this.length<=r)&&!!(this.words[r]&a)},i.prototype.imaskn=function(t){n("number"==typeof t&&t>=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,"imaskn works only with positive numbers"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var a=67108863^67108863>>>e<<e;this.words[this.length-1]&=a}return this.strip()},i.prototype.maskn=function(t){return this.clone().imaskn(t)},i.prototype.iaddn=function(t){return n("number"==typeof t),n(t<67108864),t<0?this.isubn(-t):0!==this.negative?1===this.length&&(0|this.words[0])<t?(this.words[0]=t-(0|this.words[0]),this.negative=0,this):(this.negative=0,this.isubn(t),this.negative=1,this):this._iaddn(t)},i.prototype._iaddn=function(t){this.words[0]+=t;for(var e=0;e<this.length&&this.words[e]>=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},i.prototype.isubn=function(t){if(n("number"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e<this.length&&this.words[e]<0;e++)this.words[e]+=67108864,this.words[e+1]-=1;return this.strip()},i.prototype.addn=function(t){return this.clone().iaddn(t)},i.prototype.subn=function(t){return this.clone().isubn(t)},i.prototype.iabs=function(){return this.negative=0,this},i.prototype.abs=function(){return this.clone().iabs()},i.prototype._ishlnsubmul=function(t,e,r){var a,i,o=t.length+r;this._expand(o);var s=0;for(a=0;a<t.length;a++){i=(0|this.words[a+r])+s;var l=(0|t.words[a])*e;s=((i-=67108863&l)>>26)-(l/67108864|0),this.words[a+r]=67108863&i}for(;a<this.length-r;a++)s=(i=(0|this.words[a+r])+s)>>26,this.words[a+r]=67108863&i;if(0===s)return this.strip();for(n(-1===s),s=0,a=0;a<this.length;a++)s=(i=-(0|this.words[a])+s)>>26,this.words[a]=67108863&i;return this.negative=1,this.strip()},i.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),a=t,o=0|a.words[a.length-1];0!==(r=26-this._countBits(o))&&(a=a.ushln(r),n.iushln(r),o=0|a.words[a.length-1]);var s,l=n.length-a.length;if("mod"!==e){(s=new i(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c<s.length;c++)s.words[c]=0}var u=n.clone()._ishlnsubmul(a,1,l);0===u.negative&&(n=u,s&&(s.words[l]=1));for(var h=l-1;h>=0;h--){var f=67108864*(0|n.words[a.length+h])+(0|n.words[a.length+h-1]);for(f=Math.min(f/o|0,67108863),n._ishlnsubmul(a,f,h);0!==n.negative;)f--,n.negative=0,n._ishlnsubmul(a,1,h),n.isZero()||(n.negative^=1);s&&(s.words[h]=f)}return s&&s.strip(),n.strip(),"div"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},i.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new i(0),mod:new i(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),"mod"!==e&&(a=s.div.neg()),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:a,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),"mod"!==e&&(a=s.div.neg()),{div:a,mod:s.mod}):0!=(this.negative&t.negative)?(s=this.neg().divmod(t.neg(),e),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new i(0),mod:this}:1===t.length?"div"===e?{div:this.divn(t.words[0]),mod:null}:"mod"===e?{div:null,mod:new i(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new i(this.modn(t.words[0]))}:this._wordDiv(t,e);var a,o,s},i.prototype.div=function(t){return this.divmod(t,"div",!1).div},i.prototype.mod=function(t){return this.divmod(t,"mod",!1).mod},i.prototype.umod=function(t){return this.divmod(t,"mod",!0).mod},i.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),a=t.andln(1),i=r.cmp(n);return i<0||1===a&&0===i?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},i.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,a=this.length-1;a>=0;a--)r=(e*r+(0|this.words[a]))%t;return r},i.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var a=(0|this.words[r])+67108864*e;this.words[r]=a/t|0,e=a%t}return this.strip()},i.prototype.divn=function(t){return this.clone().idivn(t)},i.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a=new i(1),o=new i(0),s=new i(0),l=new i(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),h=e.clone();!e.isZero();){for(var f=0,p=1;0==(e.words[0]&p)&&f<26;++f,p<<=1);if(f>0)for(e.iushrn(f);f-- >0;)(a.isOdd()||o.isOdd())&&(a.iadd(u),o.isub(h)),a.iushrn(1),o.iushrn(1);for(var d=0,g=1;0==(r.words[0]&g)&&d<26;++d,g<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(h)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),a.isub(s),o.isub(l)):(r.isub(e),s.isub(a),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},i.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var a,o=new i(1),s=new i(0),l=r.clone();e.cmpn(1)>0&&r.cmpn(1)>0;){for(var c=0,u=1;0==(e.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(e.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var h=0,f=1;0==(r.words[0]&f)&&h<26;++h,f<<=1);if(h>0)for(r.iushrn(h);h-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);e.cmp(r)>=0?(e.isub(r),o.isub(s)):(r.isub(e),s.isub(o))}return(a=0===e.cmpn(1)?o:s).cmpn(0)<0&&a.iadd(t),a},i.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var a=e.cmp(r);if(a<0){var i=e;e=r,r=i}else if(0===a||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},i.prototype.invm=function(t){return this.egcd(t).a.umod(t)},i.prototype.isEven=function(){return 0==(1&this.words[0])},i.prototype.isOdd=function(){return 1==(1&this.words[0])},i.prototype.andln=function(t){return this.words[0]&t},i.prototype.bincn=function(t){n("number"==typeof t);var e=t%26,r=(t-e)/26,a=1<<e;if(this.length<=r)return this._expand(r+1),this.words[r]|=a,this;for(var i=a,o=r;0!==i&&o<this.length;o++){var s=0|this.words[o];i=(s+=i)>>>26,s&=67108863,this.words[o]=s}return 0!==i&&(this.words[o]=i,this.length++),this},i.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},i.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,"Number is too big");var a=0|this.words[0];e=a===t?0:a<t?-1:1}return 0!==this.negative?0|-e:e},i.prototype.cmp=function(t){if(0!==this.negative&&0===t.negative)return-1;if(0===this.negative&&0!==t.negative)return 1;var e=this.ucmp(t);return 0!==this.negative?0|-e:e},i.prototype.ucmp=function(t){if(this.length>t.length)return 1;if(this.length<t.length)return-1;for(var e=0,r=this.length-1;r>=0;r--){var n=0|this.words[r],a=0|t.words[r];if(n!==a){n<a?e=-1:n>a&&(e=1);break}}return e},i.prototype.gtn=function(t){return 1===this.cmpn(t)},i.prototype.gt=function(t){return 1===this.cmp(t)},i.prototype.gten=function(t){return this.cmpn(t)>=0},i.prototype.gte=function(t){return this.cmp(t)>=0},i.prototype.ltn=function(t){return-1===this.cmpn(t)},i.prototype.lt=function(t){return-1===this.cmp(t)},i.prototype.lten=function(t){return this.cmpn(t)<=0},i.prototype.lte=function(t){return this.cmp(t)<=0},i.prototype.eqn=function(t){return 0===this.cmpn(t)},i.prototype.eq=function(t){return 0===this.cmp(t)},i.red=function(t){return new w(t)},i.prototype.toRed=function(t){return n(!this.red,"Already a number in reduction context"),n(0===this.negative,"red works only with positives"),t.convertTo(this)._forceRed(t)},i.prototype.fromRed=function(){return n(this.red,"fromRed works only with numbers in reduction context"),this.red.convertFrom(this)},i.prototype._forceRed=function(t){return this.red=t,this},i.prototype.forceRed=function(t){return n(!this.red,"Already a number in reduction 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/*!
* @overview es6-promise - a tiny implementation of Promises/A+.
* @copyright Copyright (c) 2014 Yehuda Katz, Tom Dale, Stefan Penner and contributors (Conversion to ES6 API by Jake Archibald)
* @license Licensed under MIT license
* See https://raw.githubusercontent.com/stefanpenner/es6-promise/master/LICENSE
* @version v4.2.8+1e68dce6
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n=t("./lib/text.js"),a=t("./lib/lines.js"),i=t("./lib/background.js"),o=t("./lib/cube.js"),s=t("./lib/ticks.js"),l=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]);function c(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function u(t){this.gl=t,this.pixelRatio=1,this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.autoTicks=!0,this.tickSpacing=[1,1,1],this.tickEnable=[!0,!0,!0],this.tickFont=["sans-serif","sans-serif","sans-serif"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickAlign=["auto","auto","auto"],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[10,10,10],this.lastCubeProps={cubeEdges:[0,0,0],axis:[0,0,0]},this.labels=["x","y","z"],this.labelEnable=[!0,!0,!0],this.labelFont="sans-serif",this.labelSize=[20,20,20],this.labelAngle=[0,0,0],this.labelAlign=["auto","auto","auto"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[10,10,10],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[0,0,0],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!1,!1,!1],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._firstInit=!0,this._text=null,this._lines=null,this._background=i(t)}var h=u.prototype;function f(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}h.update=function(t){function e(e,r,n){if(n in t){var a,i=t[n],o=this[n];(e?Array.isArray(i)&&Array.isArray(i[0]):Array.isArray(i))?this[n]=a=[r(i[0]),r(i[1]),r(i[2])]:this[n]=a=[r(i),r(i),r(i)];for(var s=0;s<3;++s)if(a[s]!==o[s])return!0}return!1}t=t||{};var r,i=e.bind(this,!1,Number),o=e.bind(this,!1,Boolean),l=e.bind(this,!1,String),c=e.bind(this,!0,(function(t){if(Array.isArray(t)){if(3===t.length)return[+t[0],+t[1],+t[2],1];if(4===t.length)return[+t[0],+t[1],+t[2],+t[3]]}return[0,0,0,1]})),u=!1,h=!1;if("bounds"in t)for(var f=t.bounds,p=0;p<2;++p)for(var d=0;d<3;++d)f[p][d]!==this.bounds[p][d]&&(h=!0),this.bounds[p][d]=f[p][d];if("ticks"in t){r=t.ticks,u=!0,this.autoTicks=!1;for(p=0;p<3;++p)this.tickSpacing[p]=0}else i("tickSpacing")&&(this.autoTicks=!0,h=!0);if(this._firstInit&&("ticks"in t||"tickSpacing"in t||(this.autoTicks=!0),h=!0,u=!0,this._firstInit=!1),h&&this.autoTicks&&(r=s.create(this.bounds,this.tickSpacing),u=!0),u){for(p=0;p<3;++p)r[p].sort((function(t,e){return t.x-e.x}));s.equal(r,this.ticks)?u=!1:this.ticks=r}o("tickEnable"),l("tickFont")&&(u=!0),i("tickSize"),i("tickAngle"),i("tickPad"),c("tickColor");var g=l("labels");l("labelFont")&&(g=!0),o("labelEnable"),i("labelSize"),i("labelPad"),c("labelColor"),o("lineEnable"),o("lineMirror"),i("lineWidth"),c("lineColor"),o("lineTickEnable"),o("lineTickMirror"),i("lineTickLength"),i("lineTickWidth"),c("lineTickColor"),o("gridEnable"),i("gridWidth"),c("gridColor"),o("zeroEnable"),c("zeroLineColor"),i("zeroLineWidth"),o("backgroundEnable"),c("backgroundColor"),this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont):this._text=n(this.gl,this.bounds,this.labels,this.labelFont,this.ticks,this.tickFont),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=a(this.gl,this.bounds,this.ticks))};var p=[new f,new f,new f];function d(t,e,r,n,a){for(var i=t.primalOffset,o=t.primalMinor,s=t.mirrorOffset,l=t.mirrorMinor,c=n[e],u=0;u<3;++u)if(e!==u){var h=i,f=s,p=o,d=l;c&1<<u&&(h=s,f=i,p=l,d=o),h[u]=r[0][u],f[u]=r[1][u],a[u]>0?(p[u]=-1,d[u]=0):(p[u]=0,d[u]=1)}}var g=[0,0,0],m={model:l,view:l,projection:l,_ortho:!1};h.isOpaque=function(){return!0},h.isTransparent=function(){return!1},h.drawTransparent=function(t){};var v=[0,0,0],y=[0,0,0],x=[0,0,0];h.draw=function(t){t=t||m;for(var e=this.gl,r=t.model||l,n=t.view||l,a=t.projection||l,i=this.bounds,s=t._ortho||!1,u=o(r,n,a,i,s),h=u.cubeEdges,f=u.axis,b=n[12],_=n[13],w=n[14],T=n[15],k=(s?2:1)*this.pixelRatio*(a[3]*b+a[7]*_+a[11]*w+a[15]*T)/e.drawingBufferHeight,A=0;A<3;++A)this.lastCubeProps.cubeEdges[A]=h[A],this.lastCubeProps.axis[A]=f[A];var M=p;for(A=0;A<3;++A)d(p[A],A,this.bounds,h,f);e=this.gl;var S,E=g;for(A=0;A<3;++A)this.backgroundEnable[A]?E[A]=f[A]:E[A]=0;this._background.draw(r,n,a,i,E,this.backgroundColor),this._lines.bind(r,n,a,this);for(A=0;A<3;++A){var C=[0,0,0];f[A]>0?C[A]=i[1][A]:C[A]=i[0][A];for(var L=0;L<2;++L){var P=(A+1+L)%3,I=(A+1+(1^L))%3;this.gridEnable[P]&&this._lines.drawGrid(P,I,this.bounds,C,this.gridColor[P],this.gridWidth[P]*this.pixelRatio)}for(L=0;L<2;++L){P=(A+1+L)%3,I=(A+1+(1^L))%3;this.zeroEnable[I]&&Math.min(i[0][I],i[1][I])<=0&&Math.max(i[0][I],i[1][I])>=0&&this._lines.drawZero(P,I,this.bounds,C,this.zeroLineColor[I],this.zeroLineWidth[I]*this.pixelRatio)}}for(A=0;A<3;++A){this.lineEnable[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].primalOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio),this.lineMirror[A]&&this._lines.drawAxisLine(A,this.bounds,M[A].mirrorOffset,this.lineColor[A],this.lineWidth[A]*this.pixelRatio);var z=c(v,M[A].primalMinor),O=c(y,M[A].mirrorMinor),D=this.lineTickLength;for(L=0;L<3;++L){var R=k/r[5*L];z[L]*=D[L]*R,O[L]*=D[L]*R}this.lineTickEnable[A]&&this._lines.drawAxisTicks(A,M[A].primalOffset,z,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio),this.lineTickMirror[A]&&this._lines.drawAxisTicks(A,M[A].mirrorOffset,O,this.lineTickColor[A],this.lineTickWidth[A]*this.pixelRatio)}this._lines.unbind(),this._text.bind(r,n,a,this.pixelRatio);var F,B;function N(t){(B=[0,0,0])[t]=1}function j(t,e,r){var n=(t+1)%3,a=(t+2)%3,i=e[n],o=e[a],s=r[n],l=r[a];i>0&&l>0||i>0&&l<0||i<0&&l>0||i<0&&l<0?N(n):(o>0&&s>0||o>0&&s<0||o<0&&s>0||o<0&&s<0)&&N(a)}for(A=0;A<3;++A){var V=M[A].primalMinor,U=M[A].mirrorMinor,q=c(x,M[A].primalOffset);for(L=0;L<3;++L)this.lineTickEnable[A]&&(q[L]+=k*V[L]*Math.max(this.lineTickLength[L],0)/r[5*L]);var H=[0,0,0];if(H[A]=1,this.tickEnable[A]){-3600===this.tickAngle[A]?(this.tickAngle[A]=0,this.tickAlign[A]="auto"):this.tickAlign[A]=-1,F=1,"auto"===(S=[this.tickAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(""+S[0]),B=[0,0,0],j(A,V,U);for(L=0;L<3;++L)q[L]+=k*V[L]*this.tickPad[L]/r[5*L];this._text.drawTicks(A,this.tickSize[A],this.tickAngle[A],q,this.tickColor[A],H,B,S)}if(this.labelEnable[A]){F=0,B=[0,0,0],this.labels[A].length>4&&(N(A),F=1),"auto"===(S=[this.labelAlign[A],.5,F])[0]?S[0]=0:S[0]=parseInt(""+S[0]);for(L=0;L<3;++L)q[L]+=k*V[L]*this.labelPad[L]/r[5*L];q[A]+=.5*(i[0][A]+i[1][A]),this._text.drawLabel(A,this.labelSize[A],this.labelAngle[A],q,this.labelColor[A],[0,0,0],B,S)}}this._text.unbind()},h.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null}},{"./lib/background.js":246,"./lib/cube.js":247,"./lib/lines.js":248,"./lib/text.js":250,"./lib/ticks.js":251}],246:[function(t,e,r){"use strict";e.exports=function(t){for(var e=[],r=[],s=0,l=0;l<3;++l)for(var c=(l+1)%3,u=(l+2)%3,h=[0,0,0],f=[0,0,0],p=-1;p<=1;p+=2){r.push(s,s+2,s+1,s+1,s+2,s+3),h[l]=p,f[l]=p;for(var d=-1;d<=1;d+=2){h[c]=d;for(var g=-1;g<=1;g+=2)h[u]=g,e.push(h[0],h[1],h[2],f[0],f[1],f[2]),s+=1}var m=c;c=u,u=m}var v=n(t,new Float32Array(e)),y=n(t,new Uint16Array(r),t.ELEMENT_ARRAY_BUFFER),x=a(t,[{buffer:v,type:t.FLOAT,size:3,offset:0,stride:24},{buffer:v,type:t.FLOAT,size:3,offset:12,stride:24}],y),b=i(t);return b.attributes.position.location=0,b.attributes.normal.location=1,new o(t,v,x,b)};var n=t("gl-buffer"),a=t("gl-vao"),i=t("./shaders").bg;function o(t,e,r,n){this.gl=t,this.buffer=e,this.vao=r,this.shader=n}var s=o.prototype;s.draw=function(t,e,r,n,a,i){for(var o=!1,s=0;s<3;++s)o=o||a[s];if(o){var l=this.gl;l.enable(l.POLYGON_OFFSET_FILL),l.polygonOffset(1,2),this.shader.bind(),this.shader.uniforms={model:t,view:e,projection:r,bounds:n,enable:a,colors:i},this.vao.bind(),this.vao.draw(this.gl.TRIANGLES,36),this.vao.unbind(),l.disable(l.POLYGON_OFFSET_FILL)}},s.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()}},{"./shaders":249,"gl-buffer":253,"gl-vao":327}],247:[function(t,e,r){"use strict";e.exports=function(t,e,r,i,p){a(s,e,t),a(s,r,s);for(var y=0,x=0;x<2;++x){u[2]=i[x][2];for(var b=0;b<2;++b){u[1]=i[b][1];for(var _=0;_<2;++_)u[0]=i[_][0],f(l[y],u,s),y+=1}}var w=-1;for(x=0;x<8;++x){for(var T=l[x][3],k=0;k<3;++k)c[x][k]=l[x][k]/T;p&&(c[x][2]*=-1),T<0&&(w<0||c[x][2]<c[w][2])&&(w=x)}if(w<0){w=0;for(var A=0;A<3;++A){for(var M=(A+2)%3,S=(A+1)%3,E=-1,C=-1,L=0;L<2;++L){var P=(z=L<<A)+(L<<M)+(1-L<<S),I=z+(1-L<<M)+(L<<S);o(c[z],c[P],c[I],h)<0||(L?E=1:C=1)}if(E<0||C<0)C>E&&(w|=1<<A);else{for(L=0;L<2;++L){P=(z=L<<A)+(L<<M)+(1-L<<S),I=z+(1-L<<M)+(L<<S);var z,O=d([l[z],l[P],l[I],l[z+(1<<M)+(1<<S)]]);L?E=O:C=O}C>E&&(w|=1<<A)}}}var D=7^w,R=-1;for(x=0;x<8;++x)x!==w&&x!==D&&(R<0||c[R][1]>c[x][1])&&(R=x);var F=-1;for(x=0;x<3;++x){if((N=R^1<<x)!==w&&N!==D)F<0&&(F=N),(S=c[N])[0]<c[F][0]&&(F=N)}var B=-1;for(x=0;x<3;++x){var N;if((N=R^1<<x)!==w&&N!==D&&N!==F)B<0&&(B=N),(S=c[N])[0]>c[B][0]&&(B=N)}var j=g;j[0]=j[1]=j[2]=0,j[n.log2(F^R)]=R&F,j[n.log2(R^B)]=R&B;var V=7^B;V===w||V===D?(V=7^F,j[n.log2(B^V)]=V&B):j[n.log2(F^V)]=V&F;var U=m,q=w;for(A=0;A<3;++A)U[A]=q&1<<A?-1:1;return v};var n=t("bit-twiddle"),a=t("gl-mat4/multiply"),i=t("split-polygon"),o=t("robust-orientation"),s=new Array(16),l=new Array(8),c=new Array(8),u=new Array(3),h=[0,0,0];function f(t,e,r){for(var n=0;n<4;++n){t[n]=r[12+n];for(var a=0;a<3;++a)t[n]+=e[a]*r[4*a+n]}}!function(){for(var t=0;t<8;++t)l[t]=[1,1,1,1],c[t]=[1,1,1]}();var p=[[0,0,1,0,0],[0,0,-1,1,0],[0,-1,0,1,0],[0,1,0,1,0],[-1,0,0,1,0],[1,0,0,1,0]];function d(t){for(var e=0;e<p.length;++e)if((t=i.positive(t,p[e])).length<3)return 0;var r=t[0],n=r[0]/r[3],a=r[1]/r[3],o=0;for(e=1;e+1<t.length;++e){var s=t[e],l=t[e+1],c=s[0]/s[3]-n,u=s[1]/s[3]-a,h=l[0]/l[3]-n,f=l[1]/l[3]-a;o+=Math.abs(c*f-u*h)}return o}var g=[1,1,1],m=[0,0,0],v={cubeEdges:g,axis:m}},{"bit-twiddle":95,"gl-mat4/multiply":275,"robust-orientation":500,"split-polygon":518}],248:[function(t,e,r){"use strict";e.exports=function(t,e,r){var o=[],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[0,0,0];o.push(0,0,1,0,1,1,0,0,-1,0,0,-1,0,1,1,0,1,-1);for(var h=0;h<3;++h){for(var f=o.length/3|0,d=0;d<r[h].length;++d){var g=+r[h][d].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}var m=o.length/3|0;s[h]=f,l[h]=m-f;f=o.length/3|0;for(var v=0;v<r[h].length;++v){g=+r[h][v].x;o.push(g,0,1,g,1,1,g,0,-1,g,0,-1,g,1,1,g,1,-1)}m=o.length/3|0;c[h]=f,u[h]=m-f}var y=n(t,new Float32Array(o)),x=a(t,[{buffer:y,type:t.FLOAT,size:3,stride:0,offset:0}]),b=i(t);return b.attributes.position.location=0,new p(t,y,x,b,l,s,u,c)};var n=t("gl-buffer"),a=t("gl-vao"),i=t("./shaders").line,o=[0,0,0],s=[0,0,0],l=[0,0,0],c=[0,0,0],u=[1,1];function h(t){return t[0]=t[1]=t[2]=0,t}function f(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t}function p(t,e,r,n,a,i,o,s){this.gl=t,this.vertBuffer=e,this.vao=r,this.shader=n,this.tickCount=a,this.tickOffset=i,this.gridCount=o,this.gridOffset=s}var d=p.prototype;d.bind=function(t,e,r){this.shader.bind(),this.shader.uniforms.model=t,this.shader.uniforms.view=e,this.shader.uniforms.projection=r,u[0]=this.gl.drawingBufferWidth,u[1]=this.gl.drawingBufferHeight,this.shader.uniforms.screenShape=u,this.vao.bind()},d.unbind=function(){this.vao.unbind()},d.drawAxisLine=function(t,e,r,n,a){var i=h(s);this.shader.uniforms.majorAxis=s,i[t]=e[1][t]-e[0][t],this.shader.uniforms.minorAxis=i;var o,u=f(c,r);u[t]+=e[0][t],this.shader.uniforms.offset=u,this.shader.uniforms.lineWidth=a,this.shader.uniforms.color=n,(o=h(l))[(t+2)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6),(o=h(l))[(t+1)%3]=1,this.shader.uniforms.screenAxis=o,this.vao.draw(this.gl.TRIANGLES,6)},d.drawAxisTicks=function(t,e,r,n,a){if(this.tickCount[t]){var i=h(o);i[t]=1,this.shader.uniforms.majorAxis=i,this.shader.uniforms.offset=e,this.shader.uniforms.minorAxis=r,this.shader.uniforms.color=n,this.shader.uniforms.lineWidth=a;var s=h(l);s[t]=1,this.shader.uniforms.screenAxis=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t])}},d.drawGrid=function(t,e,r,n,a,i){if(this.gridCount[t]){var u=h(s);u[e]=r[1][e]-r[0][e],this.shader.uniforms.minorAxis=u;var p=f(c,n);p[e]+=r[0][e],this.shader.uniforms.offset=p;var d=h(o);d[t]=1,this.shader.uniforms.majorAxis=d;var g=h(l);g[t]=1,this.shader.uniforms.screenAxis=g,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,this.gridCount[t],this.gridOffset[t])}},d.drawZero=function(t,e,r,n,a,i){var o=h(s);this.shader.uniforms.majorAxis=o,o[t]=r[1][t]-r[0][t],this.shader.uniforms.minorAxis=o;var u=f(c,n);u[t]+=r[0][t],this.shader.uniforms.offset=u;var p=h(l);p[e]=1,this.shader.uniforms.screenAxis=p,this.shader.uniforms.lineWidth=i,this.shader.uniforms.color=a,this.vao.draw(this.gl.TRIANGLES,6)},d.dispose=function(){this.vao.dispose(),this.vertBuffer.dispose(),this.shader.dispose()}},{"./shaders":249,"gl-buffer":253,"gl-vao":327}],249:[function(t,e,r){"use strict";var n=t("glslify"),a=t("gl-shader"),i=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\nuniform vec3 offset, majorAxis, minorAxis, screenAxis;\nuniform float lineWidth;\nuniform vec2 screenShape;\n\nvec3 project(vec3 p) {\n vec4 pp = projection * view * model * vec4(p, 1.0);\n return pp.xyz / max(pp.w, 0.0001);\n}\n\nvoid main() {\n vec3 major = position.x * majorAxis;\n vec3 minor = position.y * minorAxis;\n\n vec3 vPosition = major + minor + offset;\n vec3 pPosition = project(vPosition);\n vec3 offset = project(vPosition + screenAxis * position.z);\n\n vec2 screen = normalize((offset - pPosition).xy * screenShape) / screenShape;\n\n gl_Position = vec4(pPosition + vec3(0.5 * screen * lineWidth, 0), 1.0);\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec4 color;\nvoid main() {\n gl_FragColor = color;\n}"]);r.line=function(t){return a(t,i,o,null,[{name:"position",type:"vec3"}])};var s=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\nuniform vec3 offset, axis, alignDir, alignOpt;\nuniform float scale, angle, pixelScale;\nuniform vec2 resolution;\n\nvec3 project(vec3 p) {\n vec4 pp = projection * view * model * vec4(p, 1.0);\n return pp.xyz / max(pp.w, 0.0001);\n}\n\nfloat computeViewAngle(vec3 a, vec3 b) {\n vec3 A = project(a);\n vec3 B = project(b);\n\n return atan(\n (B.y - A.y) * resolution.y,\n (B.x - A.x) * resolution.x\n );\n}\n\nconst float PI = 3.141592;\nconst float TWO_PI = 2.0 * PI;\nconst float HALF_PI = 0.5 * PI;\nconst float ONE_AND_HALF_PI = 1.5 * PI;\n\nint option = int(floor(alignOpt.x + 0.001));\nfloat hv_ratio = alignOpt.y;\nbool enableAlign = (alignOpt.z != 0.0);\n\nfloat mod_angle(float a) {\n return mod(a, PI);\n}\n\nfloat positive_angle(float a) {\n return mod_angle((a < 0.0) ?\n a + TWO_PI :\n a\n );\n}\n\nfloat look_upwards(float a) {\n float b = positive_angle(a);\n return ((b > HALF_PI) && (b <= ONE_AND_HALF_PI)) ?\n b - PI :\n b;\n}\n\nfloat look_horizontal_or_vertical(float a, float ratio) {\n // ratio controls the ratio between being horizontal to (vertical + horizontal)\n // if ratio is set to 0.5 then it is 50%, 50%.\n // when using a higher ratio e.g. 0.75 the result 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HALF_PI :\n computeViewAngle(dataPosition, dataPosition + axis);\n clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir);\n\n axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0;\n clipAngle += (sin(clipAngle) < 0.0) ? 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bounds[2];\n\nvarying vec3 colorChannel;\n\nvoid main() {\n\n vec3 signAxis = sign(bounds[1] - bounds[0]);\n\n vec3 realNormal = signAxis * normal;\n\n if(dot(realNormal, enable) > 0.0) {\n vec3 minRange = min(bounds[0], bounds[1]);\n vec3 maxRange = max(bounds[0], bounds[1]);\n vec3 nPosition = mix(minRange, maxRange, 0.5 * (position + 1.0));\n gl_Position = projection * view * model * vec4(nPosition, 1.0);\n } else {\n gl_Position = vec4(0,0,0,0);\n }\n\n colorChannel = abs(realNormal);\n}"]),u=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec4 colors[3];\n\nvarying vec3 colorChannel;\n\nvoid main() {\n gl_FragColor = colorChannel.x * colors[0] +\n colorChannel.y * colors[1] +\n colorChannel.z * colors[2];\n}"]);r.bg=function(t){return a(t,c,u,null,[{name:"position",type:"vec3"},{name:"normal",type:"vec3"}])}},{"gl-shader":307,glslify:408}],250:[function(t,e,r){(function(r){"use strict";e.exports=function(t,e,r,i,s,l){var 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g=0;g<n[d].length;++g)n[d][g].text&&s(n[d][g].x,n[d][g].text,n[d][g].font||a,n[d][g].fontSize||12,1.25,p);u[d]=(o.length/3|0)-c[d]}this.buffer.update(o),this.tickOffset=c,this.tickCount=u,this.labelOffset=h,this.labelCount=f},u.drawTicks=function(t,e,r,n,a,i,o,s){this.tickCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.tickCount[t],this.tickOffset[t]))},u.drawLabel=function(t,e,r,n,a,i,o,s){this.labelCount[t]&&(this.shader.uniforms.axis=i,this.shader.uniforms.color=a,this.shader.uniforms.angle=r,this.shader.uniforms.scale=e,this.shader.uniforms.offset=n,this.shader.uniforms.alignDir=o,this.shader.uniforms.alignOpt=s,this.vao.draw(this.gl.TRIANGLES,this.labelCount[t],this.labelOffset[t]))},u.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()}}).call(this,t("_process"))},{"./shaders":249,_process:480,"gl-buffer":253,"gl-vao":327,"vectorize-text":552}],251:[function(t,e,r){"use 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f=e.model||c,p=e.view||c,v=e.projection||c,y=e._ortho||!1,x=t.bounds,b=(h=h||i(f,p,v,x,y)).axis;o(u,p,f),o(u,v,u);for(var _=g,w=0;w<3;++w)_[w].lo=1/0,_[w].hi=-1/0,_[w].pixelsPerDataUnit=1/0;var T=n(s(u,u));s(u,u);for(var k=0;k<3;++k){var A=(k+1)%3,M=(k+2)%3,S=m;t:for(w=0;w<2;++w){var E=[];if(b[k]<0!=!!w){S[k]=x[w][k];for(var C=0;C<2;++C){S[A]=x[C^w][A];for(var L=0;L<2;++L)S[M]=x[L^C^w][M],E.push(S.slice())}var P=y?5:4;for(C=P;C===P;++C){if(0===E.length)continue t;E=a.positive(E,T[C])}for(C=0;C<E.length;++C){M=E[C];var I=d(m,u,M,r,l);for(L=0;L<3;++L)_[L].lo=Math.min(_[L].lo,M[L]),_[L].hi=Math.max(_[L].hi,M[L]),L!==k&&(_[L].pixelsPerDataUnit=Math.min(_[L].pixelsPerDataUnit,Math.abs(I[L])))}}}}return _};var n=t("extract-frustum-planes"),a=t("split-polygon"),i=t("./lib/cube.js"),o=t("gl-mat4/multiply"),s=t("gl-mat4/transpose"),l=t("gl-vec4/transformMat4"),c=new Float32Array([1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1]),u=new Float32Array(16);function h(t,e,r){this.lo=t,this.hi=e,this.pixelsPerDataUnit=r}var f=[0,0,0,1],p=[0,0,0,1];function d(t,e,r,n,a){for(var i=0;i<3;++i){for(var o=f,s=p,c=0;c<3;++c)s[c]=o[c]=r[c];s[3]=o[3]=1,s[i]+=1,l(s,s,e),s[3]<0&&(t[i]=1/0),o[i]-=1,l(o,o,e),o[3]<0&&(t[i]=1/0);var u=(o[0]/o[3]-s[0]/s[3])*n,h=(o[1]/o[3]-s[1]/s[3])*a;t[i]=.25*Math.sqrt(u*u+h*h)}return t}var g=[new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0),new h(1/0,-1/0,1/0)],m=[0,0,0]},{"./lib/cube.js":247,"extract-frustum-planes":235,"gl-mat4/multiply":275,"gl-mat4/transpose":284,"gl-vec4/transformMat4":398,"split-polygon":518}],253:[function(t,e,r){"use strict";var n=t("typedarray-pool"),a=t("ndarray-ops"),i=t("ndarray"),o=["uint8","uint8_clamped","uint16","uint32","int8","int16","int32","float32"];function s(t,e,r,n,a){this.gl=t,this.type=e,this.handle=r,this.length=n,this.usage=a}var l=s.prototype;function c(t,e,r,n,a,i){var o=a.length*a.BYTES_PER_ELEMENT;if(i<0)return t.bufferData(e,a,n),o;if(o+i>r)throw new Error("gl-buffer: If resizing buffer, must not specify offset");return t.bufferSubData(e,i,a),r}function u(t,e){for(var r=n.malloc(t.length,e),a=t.length,i=0;i<a;++i)r[i]=t[i];return r}l.bind=function(){this.gl.bindBuffer(this.type,this.handle)},l.unbind=function(){this.gl.bindBuffer(this.type,null)},l.dispose=function(){this.gl.deleteBuffer(this.handle)},l.update=function(t,e){if("number"!=typeof e&&(e=-1),this.bind(),"object"==typeof t&&"undefined"!=typeof t.shape){var r=t.dtype;if(o.indexOf(r)<0&&(r="float32"),this.type===this.gl.ELEMENT_ARRAY_BUFFER)r=gl.getExtension("OES_element_index_uint")&&"uint16"!==r?"uint32":"uint16";if(r===t.dtype&&function(t,e){for(var r=1,n=e.length-1;n>=0;--n){if(e[n]!==r)return!1;r*=t[n]}return!0}(t.shape,t.stride))0===t.offset&&t.data.length===t.shape[0]?this.length=c(this.gl,this.type,this.length,this.usage,t.data,e):this.length=c(this.gl,this.type,this.length,this.usage,t.data.subarray(t.offset,t.shape[0]),e);else{var s=n.malloc(t.size,r),l=i(s,t.shape);a.assign(l,t),this.length=c(this.gl,this.type,this.length,this.usage,e<0?s:s.subarray(0,t.size),e),n.free(s)}}else if(Array.isArray(t)){var h;h=this.type===this.gl.ELEMENT_ARRAY_BUFFER?u(t,"uint16"):u(t,"float32"),this.length=c(this.gl,this.type,this.length,this.usage,e<0?h:h.subarray(0,t.length),e),n.free(h)}else if("object"==typeof t&&"number"==typeof t.length)this.length=c(this.gl,this.type,this.length,this.usage,t,e);else{if("number"!=typeof t&&void 0!==t)throw new Error("gl-buffer: Invalid data type");if(e>=0)throw new Error("gl-buffer: Cannot specify offset when resizing buffer");(t|=0)<=0&&(t=1),this.gl.bufferData(this.type,0|t,this.usage),this.length=t}},e.exports=function(t,e,r,n){if(r=r||t.ARRAY_BUFFER,n=n||t.DYNAMIC_DRAW,r!==t.ARRAY_BUFFER&&r!==t.ELEMENT_ARRAY_BUFFER)throw new Error("gl-buffer: Invalid type for webgl buffer, must be either gl.ARRAY_BUFFER or gl.ELEMENT_ARRAY_BUFFER");if(n!==t.DYNAMIC_DRAW&&n!==t.STATIC_DRAW&&n!==t.STREAM_DRAW)throw new Error("gl-buffer: Invalid usage for buffer, must be either gl.DYNAMIC_DRAW, gl.STATIC_DRAW or gl.STREAM_DRAW");var a=t.createBuffer(),i=new s(t,r,a,0,n);return i.update(e),i}},{ndarray:448,"ndarray-ops":443,"typedarray-pool":547}],254:[function(t,e,r){"use strict";var n=t("gl-vec3");e.exports=function(t,e){var r=t.positions,a=t.vectors,i={positions:[],vertexIntensity:[],vertexIntensityBounds:t.vertexIntensityBounds,vectors:[],cells:[],coneOffset:t.coneOffset,colormap:t.colormap};if(0===t.positions.length)return e&&(e[0]=[0,0,0],e[1]=[0,0,0]),i;for(var o=0,s=1/0,l=-1/0,c=1/0,u=-1/0,h=1/0,f=-1/0,p=null,d=null,g=[],m=1/0,v=!1,y=0;y<r.length;y++){var x=r[y];s=Math.min(x[0],s),l=Math.max(x[0],l),c=Math.min(x[1],c),u=Math.max(x[1],u),h=Math.min(x[2],h),f=Math.max(x[2],f);var b=a[y];if(n.length(b)>o&&(o=n.length(b)),y){var 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e.exports.createMesh(t,r,{shaders:a,traceType:"cone"})}},{"./create_mesh":255,"./lib/shaders":256,"gl-vec3":346}],255:[function(t,e,r){"use strict";var n=t("gl-shader"),a=t("gl-buffer"),i=t("gl-vao"),o=t("gl-texture2d"),s=t("gl-mat4/multiply"),l=t("gl-mat4/invert"),c=t("ndarray"),u=t("colormap"),h=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function f(t,e,r,n,a,i,o,s,l,c,u){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.pickShader=n,this.trianglePositions=a,this.triangleVectors=i,this.triangleColors=s,this.triangleUVs=l,this.triangleIds=o,this.triangleVAO=c,this.triangleCount=0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.traceType=u,this.tubeScale=1,this.coneScale=2,this.vectorScale=1,this.coneOffset=.25,this._model=h,this._view=h,this._projection=h,this._resolution=[1,1]}var p=f.prototype;function d(t,e){var r=n(t,e.meshShader.vertex,e.meshShader.fragment,null,e.meshShader.attributes);return r.attributes.position.location=0,r.attributes.color.location=2,r.attributes.uv.location=3,r.attributes.vector.location=4,r}function g(t,e){var r=n(t,e.pickShader.vertex,e.pickShader.fragment,null,e.pickShader.attributes);return r.attributes.position.location=0,r.attributes.id.location=1,r.attributes.vector.location=4,r}p.isOpaque=function(){return this.opacity>=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(t){this.pickId=t},p.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,"lightPosition"in t&&(this.lightPosition=t.lightPosition),"opacity"in t&&(this.opacity=t.opacity),"ambient"in t&&(this.ambientLight=t.ambient),"diffuse"in t&&(this.diffuseLight=t.diffuse),"specular"in t&&(this.specularLight=t.specular),"roughness"in t&&(this.roughness=t.roughness),"fresnel"in t&&(this.fresnel=t.fresnel),void 0!==t.tubeScale&&(this.tubeScale=t.tubeScale),void 0!==t.vectorScale&&(this.vectorScale=t.vectorScale),void 0!==t.coneScale&&(this.coneScale=t.coneScale),void 0!==t.coneOffset&&(this.coneOffset=t.coneOffset),t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t){for(var e=u({colormap:t,nshades:256,format:"rgba"}),r=new Uint8Array(1024),n=0;n<256;++n){for(var a=e[n],i=0;i<3;++i)r[4*n+i]=a[i];r[4*n+3]=255*a[3]}return c(r,[256,256,4],[4,0,1])}(t.colormap)),this.texture.generateMipmap());var r=t.cells,n=t.positions,a=t.vectors;if(n&&r&&a){var i=[],o=[],s=[],l=[],h=[];this.cells=r,this.positions=n,this.vectors=a;var f=t.meshColor||[1,1,1,1],p=t.vertexIntensity,d=1/0,g=-1/0;if(p)if(t.vertexIntensityBounds)d=+t.vertexIntensityBounds[0],g=+t.vertexIntensityBounds[1];else for(var m=0;m<p.length;++m){var v=p[m];d=Math.min(d,v),g=Math.max(g,v)}else for(m=0;m<n.length;++m){v=n[m][2];d=Math.min(d,v),g=Math.max(g,v)}this.intensity=p||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n),this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(m=0;m<n.length;++m)for(var y=n[m],x=0;x<3;++x)!isNaN(y[x])&&isFinite(y[x])&&(this.bounds[0][x]=Math.min(this.bounds[0][x],y[x]),this.bounds[1][x]=Math.max(this.bounds[1][x],y[x]));var b=0;t:for(m=0;m<r.length;++m){var _=r[m];switch(_.length){case 3:for(x=0;x<3;++x){y=n[T=_[x]];for(var w=0;w<3;++w)if(isNaN(y[w])||!isFinite(y[w]))continue t}for(x=0;x<3;++x){var T;y=n[T=_[2-x]];i.push(y[0],y[1],y[2],y[3]);var k=a[T];o.push(k[0],k[1],k[2],k[3]||0);var A,M=f;3===M.length?s.push(M[0],M[1],M[2],1):s.push(M[0],M[1],M[2],M[3]),A=p?[(p[T]-d)/(g-d),0]:[(y[2]-d)/(g-d),0],l.push(A[0],A[1]),h.push(m)}b+=1}}this.triangleCount=b,this.trianglePositions.update(i),this.triangleVectors.update(o),this.triangleColors.update(s),this.triangleUVs.update(l),this.triangleIds.update(new Uint32Array(h))}},p.drawTransparent=p.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||h,n=t.view||h,a=t.projection||h,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);var c={model:r,view:n,projection:a,inverseModel:h.slice(),clipBounds:i,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],opacity:this.opacity,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,texture:0};c.inverseModel=l(c.inverseModel,c.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);s(u,c.view,c.model),s(u,c.projection,u),l(u,u);for(o=0;o<3;++o)c.eyePosition[o]=u[12+o]/u[15];var f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];c.lightPosition[o]=p/f}if(this.triangleCount>0){var g=this.triShader;g.bind(),g.uniforms=c,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()}},p.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||h,n=t.view||h,a=t.projection||h,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(a),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s={model:r,view:n,projection:a,clipBounds:i,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},l=this.pickShader;l.bind(),l.uniforms=s,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind())},p.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions[r[1]].slice(0,3),a={position:n,dataCoordinate:n,index:Math.floor(r[1]/48)};return"cone"===this.traceType?a.index=Math.floor(r[1]/48):"streamtube"===this.traceType&&(a.intensity=this.intensity[r[1]],a.velocity=this.vectors[r[1]].slice(0,3),a.divergence=this.vectors[r[1]][3],a.index=e),a},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()},e.exports=function(t,e,r){var n=r.shaders;1===arguments.length&&(t=(e=t).gl);var s=d(t,n),l=g(t,n),u=o(t,c(new Uint8Array([255,255,255,255]),[1,1,4]));u.generateMipmap(),u.minFilter=t.LINEAR_MIPMAP_LINEAR,u.magFilter=t.LINEAR;var h=a(t),p=a(t),m=a(t),v=a(t),y=a(t),x=i(t,[{buffer:h,type:t.FLOAT,size:4},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:m,type:t.FLOAT,size:4},{buffer:v,type:t.FLOAT,size:2},{buffer:p,type:t.FLOAT,size:4}]),b=new f(t,u,s,l,h,p,y,m,v,x,r.traceType||"cone");return b.update(e),b}},{colormap:128,"gl-buffer":253,"gl-mat4/invert":273,"gl-mat4/multiply":275,"gl-shader":307,"gl-texture2d":322,"gl-vao":327,ndarray:448}],256:[function(t,e,r){var n=t("glslify"),a=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n // Return up-vector for only-z vector.\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\n // Assign z = 0, x = -b, y = a:\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n return normalize(vec3(-v.y, v.x, 0.0));\n } else {\n return normalize(vec3(0.0, v.z, -v.y));\n }\n}\n\n// Calculate the cone vertex and normal at the given index.\n//\n// The returned vertex is for a cone with its top at origin and height of 1.0,\n// pointing in the direction of the vector attribute.\n//\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n// These vertices are used to make up the triangles of the cone by the following:\n// segment + 0 top vertex\n// segment + 1 perimeter vertex a+1\n// segment + 2 perimeter vertex a\n// segment + 3 center base vertex\n// segment + 4 perimeter vertex a\n// segment + 5 perimeter vertex a+1\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n// To go from index to segment, floor(index / 6)\n// To go from segment to angle, 2*pi * (segment/segmentCount)\n// To go from index to segment index, index - (segment*6)\n//\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n\n const float segmentCount = 8.0;\n\n float index = rawIndex - floor(rawIndex /\n (segmentCount * 6.0)) *\n (segmentCount * 6.0);\n\n float segment = floor(0.001 + index/6.0);\n float segmentIndex = index - (segment*6.0);\n\n normal = -normalize(d);\n\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n return mix(vec3(0.0), -d, coneOffset);\n }\n\n float nextAngle = (\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\n (segmentIndex > 4.99 && segmentIndex < 5.01)\n ) ? 1.0 : 0.0;\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\n vec3 v2 = v1 - d;\n\n vec3 u = getOrthogonalVector(d);\n vec3 v = normalize(cross(u, d));\n\n vec3 x = u * cos(angle) * length(d)*0.25;\n vec3 y = v * sin(angle) * length(d)*0.25;\n vec3 v3 = v2 + x + y;\n if (segmentIndex < 3.0) {\n vec3 tx = u * sin(angle);\n vec3 ty = v * -cos(angle);\n vec3 tangent = tx + ty;\n normal = normalize(cross(v3 - v1, tangent));\n }\n\n if (segmentIndex == 0.0) {\n return mix(d, vec3(0.0), coneOffset);\n }\n return v3;\n}\n\nattribute vec3 vector;\nattribute vec4 color, position;\nattribute vec2 uv;\n\nuniform float vectorScale, coneScale, coneOffset;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 eyePosition, lightPosition;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n // Scale the vector magnitude to stay constant with\n // model & view changes.\n vec3 normal;\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * conePosition;\n cameraCoordinate.xyz /= cameraCoordinate.w;\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n // vec4 m_position = model * vec4(conePosition, 1.0);\n vec4 t_position = view * conePosition;\n gl_Position = projection * t_position;\n\n f_color = color;\n f_data = conePosition.xyz;\n f_position = position.xyz;\n f_uv = uv;\n}\n"]),i=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness,\n float fresnel) {\n\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n //Half angle vector\n vec3 H = normalize(lightDirection + viewDirection);\n\n //Geometric term\n float NdotH = max(dot(surfaceNormal, H), 0.0);\n float VdotH = max(dot(viewDirection, H), 0.000001);\n float LdotH = max(dot(lightDirection, H), 0.000001);\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\n float G = min(1.0, min(G1, G2));\n \n //Distribution term\n float D = beckmannDistribution(NdotH, roughness);\n\n //Fresnel term\n float F = pow(1.0 - VdotN, fresnel);\n\n //Multiply terms and done\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform sampler2D texture;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n vec3 N = normalize(f_normal);\n vec3 L = normalize(f_lightDirection);\n vec3 V = normalize(f_eyeDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = litColor * opacity;\n}\n"]),o=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n // Return up-vector for only-z vector.\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\n // Assign z = 0, x = -b, y = a:\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n return normalize(vec3(-v.y, v.x, 0.0));\n } else {\n return normalize(vec3(0.0, v.z, -v.y));\n }\n}\n\n// Calculate the cone vertex and normal at the given index.\n//\n// The returned vertex is for a cone with its top at origin and height of 1.0,\n// pointing in the direction of the vector attribute.\n//\n// Each cone is made up of a top vertex, a center base vertex and base perimeter vertices.\n// These vertices are used to make up the triangles of the cone by the following:\n// segment + 0 top vertex\n// segment + 1 perimeter vertex a+1\n// segment + 2 perimeter vertex a\n// segment + 3 center base vertex\n// segment + 4 perimeter vertex a\n// segment + 5 perimeter vertex a+1\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n// To go from index to segment, floor(index / 6)\n// To go from segment to angle, 2*pi * (segment/segmentCount)\n// To go from index to segment index, index - (segment*6)\n//\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n\n const float segmentCount = 8.0;\n\n float index = rawIndex - floor(rawIndex /\n (segmentCount * 6.0)) *\n (segmentCount * 6.0);\n\n float segment = floor(0.001 + index/6.0);\n float segmentIndex = index - (segment*6.0);\n\n normal = -normalize(d);\n\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n return mix(vec3(0.0), -d, coneOffset);\n }\n\n float nextAngle = (\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\n (segmentIndex > 4.99 && segmentIndex < 5.01)\n ) ? 1.0 : 0.0;\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\n vec3 v2 = v1 - d;\n\n vec3 u = getOrthogonalVector(d);\n vec3 v = normalize(cross(u, d));\n\n vec3 x = u * cos(angle) * length(d)*0.25;\n vec3 y = v * sin(angle) * length(d)*0.25;\n vec3 v3 = v2 + x + y;\n if (segmentIndex < 3.0) {\n vec3 tx = u * sin(angle);\n vec3 ty = v * -cos(angle);\n vec3 tangent = tx + ty;\n normal = normalize(cross(v3 - v1, tangent));\n }\n\n if (segmentIndex == 0.0) {\n return mix(d, vec3(0.0), coneOffset);\n }\n return v3;\n}\n\nattribute vec4 vector;\nattribute vec4 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform float vectorScale, coneScale, coneOffset;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n vec3 normal;\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector.xyz), position.w, coneOffset, normal);\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n gl_Position = projection * view * conePosition;\n f_id = id;\n f_position = position.xyz;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n gl_FragColor = vec4(pickId, f_id.xyz);\n}"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:"position",type:"vec4"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"vector",type:"vec3"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec4"},{name:"id",type:"vec4"},{name:"vector",type:"vec3"}]}},{glslify:408}],257:[function(t,e,r){e.exports={0:"NONE",1:"ONE",2:"LINE_LOOP",3:"LINE_STRIP",4:"TRIANGLES",5:"TRIANGLE_STRIP",6:"TRIANGLE_FAN",256:"DEPTH_BUFFER_BIT",512:"NEVER",513:"LESS",514:"EQUAL",515:"LEQUAL",516:"GREATER",517:"NOTEQUAL",518:"GEQUAL",519:"ALWAYS",768:"SRC_COLOR",769:"ONE_MINUS_SRC_COLOR",770:"SRC_ALPHA",771:"ONE_MINUS_SRC_ALPHA",772:"DST_ALPHA",773:"ONE_MINUS_DST_ALPHA",774:"DST_COLOR",775:"ONE_MINUS_DST_COLOR",776:"SRC_ALPHA_SATURATE",1024:"STENCIL_BUFFER_BIT",1028:"FRONT",1029:"BACK",1032:"FRONT_AND_BACK",1280:"INVALID_ENUM",1281:"INVALID_VALUE",1282:"INVALID_OPERATION",1285:"OUT_OF_MEMORY",1286:"INVALID_FRAMEBUFFER_OPERATION",2304:"CW",2305:"CCW",2849:"LINE_WIDTH",2884:"CULL_FACE",2885:"CULL_FACE_MODE",2886:"FRONT_FACE",2928:"DEPTH_RANGE",2929:"DEPTH_TEST",2930:"DEPTH_WRITEMASK",2931:"DEPTH_CLEAR_VALUE",2932:"DEPTH_FUNC",2960:"STENCIL_TEST",2961:"STENCIL_CLEAR_VALUE",2962:"STENCIL_FUNC",2963:"STENCIL_VALUE_MASK",2964:"STENCIL_FAIL",2965:"STENCIL_PASS_DEPTH_FAIL",2966:"STENCIL_PASS_DEPTH_PASS",2967:"STENCIL_REF",2968:"STENCIL_WRITEMASK",2978:"VIEWPORT",3024:"DITHER",3042:"BLEND",3088:"SCISSOR_BOX",3089:"SCISSOR_TEST",3106:"COLOR_CLEAR_VALUE",3107:"COLOR_WRITEMASK",3317:"UNPACK_ALIGNMENT",3333:"PACK_ALIGNMENT",3379:"MAX_TEXTURE_SIZE",3386:"MAX_VIEWPORT_DIMS",3408:"SUBPIXEL_BITS",3410:"RED_BITS",3411:"GREEN_BITS",3412:"BLUE_BITS",3413:"ALPHA_BITS",3414:"DEPTH_BITS",3415:"STENCIL_BITS",3553:"TEXTURE_2D",4352:"DONT_CARE",4353:"FASTEST",4354:"NICEST",5120:"BYTE",5121:"UNSIGNED_BYTE",5122:"SHORT",5123:"UNSIGNED_SHORT",5124:"INT",5125:"UNSIGNED_INT",5126:"FLOAT",5386:"INVERT",5890:"TEXTURE",6401:"STENCIL_INDEX",6402:"DEPTH_COMPONENT",6406:"ALPHA",6407:"RGB",6408:"RGBA",6409:"LUMINANCE",6410:"LUMINANCE_ALPHA",7680:"KEEP",7681:"REPLACE",7682:"INCR",7683:"DECR",7936:"VENDOR",7937:"RENDERER",7938:"VERSION",9728:"NEAREST",9729:"LINEAR",9984:"NEAREST_MIPMAP_NEAREST",9985:"LINEAR_MIPMAP_NEAREST",9986:"NEAREST_MIPMAP_LINEAR",9987:"LINEAR_MIPMAP_LINEAR",10240:"TEXTURE_MAG_FILTER",10241:"TEXTURE_MIN_FILTER",10242:"TEXTURE_WRAP_S",10243:"TEXTURE_WRAP_T",10497:"REPEAT",10752:"POLYGON_OFFSET_UNITS",16384:"COLOR_BUFFER_BIT",32769:"CONSTANT_COLOR",32770:"ONE_MINUS_CONSTANT_COLOR",32771:"CONSTANT_ALPHA",32772:"ONE_MINUS_CONSTANT_ALPHA",32773:"BLEND_COLOR",32774:"FUNC_ADD",32777:"BLEND_EQUATION_RGB",32778:"FUNC_SUBTRACT",32779:"FUNC_REVERSE_SUBTRACT",32819:"UNSIGNED_SHORT_4_4_4_4",32820:"UNSIGNED_SHORT_5_5_5_1",32823:"POLYGON_OFFSET_FILL",32824:"POLYGON_OFFSET_FACTOR",32854:"RGBA4",32855:"RGB5_A1",32873:"TEXTURE_BINDING_2D",32926:"SAMPLE_ALPHA_TO_COVERAGE",32928:"SAMPLE_COVERAGE",32936:"SAMPLE_BUFFERS",32937:"SAMPLES",32938:"SAMPLE_COVERAGE_VALUE",32939:"SAMPLE_COVERAGE_INVERT",32968:"BLEND_DST_RGB",32969:"BLEND_SRC_RGB",32970:"BLEND_DST_ALPHA",32971:"BLEND_SRC_ALPHA",33071:"CLAMP_TO_EDGE",33170:"GENERATE_MIPMAP_HINT",33189:"DEPTH_COMPONENT16",33306:"DEPTH_STENCIL_ATTACHMENT",33635:"UNSIGNED_SHORT_5_6_5",33648:"MIRRORED_REPEAT",33901:"ALIASED_POINT_SIZE_RANGE",33902:"ALIASED_LINE_WIDTH_RANGE",33984:"TEXTURE0",33985:"TEXTURE1",33986:"TEXTURE2",33987:"TEXTURE3",33988:"TEXTURE4",33989:"TEXTURE5",33990:"TEXTURE6",33991:"TEXTURE7",33992:"TEXTURE8",33993:"TEXTURE9",33994:"TEXTURE10",33995:"TEXTURE11",33996:"TEXTURE12",33997:"TEXTURE13",33998:"TEXTURE14",33999:"TEXTURE15",34e3:"TEXTURE16",34001:"TEXTURE17",34002:"TEXTURE18",34003:"TEXTURE19",34004:"TEXTURE20",34005:"TEXTURE21",34006:"TEXTURE22",34007:"TEXTURE23",34008:"TEXTURE24",34009:"TEXTURE25",34010:"TEXTURE26",34011:"TEXTURE27",34012:"TEXTURE28",34013:"TEXTURE29",34014:"TEXTURE30",34015:"TEXTURE31",34016:"ACTIVE_TEXTURE",34024:"MAX_RENDERBUFFER_SIZE",34041:"DEPTH_STENCIL",34055:"INCR_WRAP",34056:"DECR_WRAP",34067:"TEXTURE_CUBE_MAP",34068:"TEXTURE_BINDING_CUBE_MAP",34069:"TEXTURE_CUBE_MAP_POSITIVE_X",34070:"TEXTURE_CUBE_MAP_NEGATIVE_X",34071:"TEXTURE_CUBE_MAP_POSITIVE_Y",34072:"TEXTURE_CUBE_MAP_NEGATIVE_Y",34073:"TEXTURE_CUBE_MAP_POSITIVE_Z",34074:"TEXTURE_CUBE_MAP_NEGATIVE_Z",34076:"MAX_CUBE_MAP_TEXTURE_SIZE",34338:"VERTEX_ATTRIB_ARRAY_ENABLED",34339:"VERTEX_ATTRIB_ARRAY_SIZE",34340:"VERTEX_ATTRIB_ARRAY_STRIDE",34341:"VERTEX_ATTRIB_ARRAY_TYPE",34342:"CURRENT_VERTEX_ATTRIB",34373:"VERTEX_ATTRIB_ARRAY_POINTER",34466:"NUM_COMPRESSED_TEXTURE_FORMATS",34467:"COMPRESSED_TEXTURE_FORMATS",34660:"BUFFER_SIZE",34661:"BUFFER_USAGE",34816:"STENCIL_BACK_FUNC",34817:"STENCIL_BACK_FAIL",34818:"STENCIL_BACK_PASS_DEPTH_FAIL",34819:"STENCIL_BACK_PASS_DEPTH_PASS",34877:"BLEND_EQUATION_ALPHA",34921:"MAX_VERTEX_ATTRIBS",34922:"VERTEX_ATTRIB_ARRAY_NORMALIZED",34930:"MAX_TEXTURE_IMAGE_UNITS",34962:"ARRAY_BUFFER",34963:"ELEMENT_ARRAY_BUFFER",34964:"ARRAY_BUFFER_BINDING",34965:"ELEMENT_ARRAY_BUFFER_BINDING",34975:"VERTEX_ATTRIB_ARRAY_BUFFER_BINDING",35040:"STREAM_DRAW",35044:"STATIC_DRAW",35048:"DYNAMIC_DRAW",35632:"FRAGMENT_SHADER",35633:"VERTEX_SHADER",35660:"MAX_VERTEX_TEXTURE_IMAGE_UNITS",35661:"MAX_COMBINED_TEXTURE_IMAGE_UNITS",35663:"SHADER_TYPE",35664:"FLOAT_VEC2",35665:"FLOAT_VEC3",35666:"FLOAT_VEC4",35667:"INT_VEC2",35668:"INT_VEC3",35669:"INT_VEC4",35670:"BOOL",35671:"BOOL_VEC2",35672:"BOOL_VEC3",35673:"BOOL_VEC4",35674:"FLOAT_MAT2",35675:"FLOAT_MAT3",35676:"FLOAT_MAT4",35678:"SAMPLER_2D",35680:"SAMPLER_CUBE",35712:"DELETE_STATUS",35713:"COMPILE_STATUS",35714:"LINK_STATUS",35715:"VALIDATE_STATUS",35716:"INFO_LOG_LENGTH",35717:"ATTACHED_SHADERS",35718:"ACTIVE_UNIFORMS",35719:"ACTIVE_UNIFORM_MAX_LENGTH",35720:"SHADER_SOURCE_LENGTH",35721:"ACTIVE_ATTRIBUTES",35722:"ACTIVE_ATTRIBUTE_MAX_LENGTH",35724:"SHADING_LANGUAGE_VERSION",35725:"CURRENT_PROGRAM",36003:"STENCIL_BACK_REF",36004:"STENCIL_BACK_VALUE_MASK",36005:"STENCIL_BACK_WRITEMASK",36006:"FRAMEBUFFER_BINDING",36007:"RENDERBUFFER_BINDING",36048:"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE",36049:"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME",36050:"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL",36051:"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE",36053:"FRAMEBUFFER_COMPLETE",36054:"FRAMEBUFFER_INCOMPLETE_ATTACHMENT",36055:"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT",36057:"FRAMEBUFFER_INCOMPLETE_DIMENSIONS",36061:"FRAMEBUFFER_UNSUPPORTED",36064:"COLOR_ATTACHMENT0",36096:"DEPTH_ATTACHMENT",36128:"STENCIL_ATTACHMENT",36160:"FRAMEBUFFER",36161:"RENDERBUFFER",36162:"RENDERBUFFER_WIDTH",36163:"RENDERBUFFER_HEIGHT",36164:"RENDERBUFFER_INTERNAL_FORMAT",36168:"STENCIL_INDEX8",36176:"RENDERBUFFER_RED_SIZE",36177:"RENDERBUFFER_GREEN_SIZE",36178:"RENDERBUFFER_BLUE_SIZE",36179:"RENDERBUFFER_ALPHA_SIZE",36180:"RENDERBUFFER_DEPTH_SIZE",36181:"RENDERBUFFER_STENCIL_SIZE",36194:"RGB565",36336:"LOW_FLOAT",36337:"MEDIUM_FLOAT",36338:"HIGH_FLOAT",36339:"LOW_INT",36340:"MEDIUM_INT",36341:"HIGH_INT",36346:"SHADER_COMPILER",36347:"MAX_VERTEX_UNIFORM_VECTORS",36348:"MAX_VARYING_VECTORS",36349:"MAX_FRAGMENT_UNIFORM_VECTORS",37440:"UNPACK_FLIP_Y_WEBGL",37441:"UNPACK_PREMULTIPLY_ALPHA_WEBGL",37442:"CONTEXT_LOST_WEBGL",37443:"UNPACK_COLORSPACE_CONVERSION_WEBGL",37444:"BROWSER_DEFAULT_WEBGL"}},{}],258:[function(t,e,r){var n=t("./1.0/numbers");e.exports=function(t){return n[t]}},{"./1.0/numbers":257}],259:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e),o=a(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),l=i(e);l.attributes.position.location=0,l.attributes.color.location=1,l.attributes.offset.location=2;var c=new s(e,r,o,l);return c.update(t),c};var n=t("gl-buffer"),a=t("gl-vao"),i=t("./shaders/index"),o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var l=s.prototype;function c(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,a=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var i=n[12],s=n[13],l=n[14],c=n[15],u=(t._ortho||!1?2:1)*this.pixelRatio*(a[3]*i+a[7]*s+a[11]*l+a[15]*c)/e.drawingBufferHeight;this.vao.bind();for(var h=0;h<3;++h)e.lineWidth(this.lineWidth[h]*this.pixelRatio),r.capSize=this.capSize[h]*u,this.lineCount[h]&&e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var u=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var a=-1;a<=1;a+=2){var i=[0,0,0];i[(n+e)%3]=a,r.push(i)}t[e]=r}return t}();function h(t,e,r,n){for(var a=u[n],i=0;i<a.length;++i){var o=a[i];t.push(e[0],e[1],e[2],r[0],r[1],r[2],r[3],o[0],o[1],o[2])}return a.length}l.update=function(t){"lineWidth"in(t=t||{})&&(this.lineWidth=t.lineWidth,Array.isArray(this.lineWidth)||(this.lineWidth=[this.lineWidth,this.lineWidth,this.lineWidth])),"capSize"in t&&(this.capSize=t.capSize,Array.isArray(this.capSize)||(this.capSize=[this.capSize,this.capSize,this.capSize])),this.hasAlpha=!1,"opacity"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var e=t.color||[[0,0,0],[0,0,0],[0,0,0]],r=t.position,n=t.error;if(Array.isArray(e[0])||(e=[e,e,e]),r&&n){var a=[],i=r.length,o=0;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.lineCount=[0,0,0];for(var s=0;s<3;++s){this.lineOffset[s]=o;t:for(var l=0;l<i;++l){for(var u=r[l],f=0;f<3;++f)if(isNaN(u[f])||!isFinite(u[f]))continue t;var p=n[l],d=e[s];if(Array.isArray(d[0])&&(d=e[l]),3===d.length?d=[d[0],d[1],d[2],1]:4===d.length&&(d=[d[0],d[1],d[2],d[3]],!this.hasAlpha&&d[3]<1&&(this.hasAlpha=!0)),!isNaN(p[0][s])&&!isNaN(p[1][s])){var g;if(p[0][s]<0)(g=u.slice())[s]+=p[0][s],a.push(u[0],u[1],u[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),c(this.bounds,g),o+=2+h(a,g,d,s);if(p[1][s]>0)(g=u.slice())[s]+=p[1][s],a.push(u[0],u[1],u[2],d[0],d[1],d[2],d[3],0,0,0,g[0],g[1],g[2],d[0],d[1],d[2],d[3],0,0,0),c(this.bounds,g),o+=2+h(a,g,d,s)}}this.lineCount[s]=o-this.lineOffset[s]}this.buffer.update(a)}},l.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},{"./shaders/index":260,"gl-buffer":253,"gl-vao":327}],260:[function(t,e,r){"use strict";var n=t("glslify"),a=t("gl-shader"),i=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, offset;\nattribute vec4 color;\nuniform mat4 model, view, projection;\nuniform float capSize;\nvarying vec4 fragColor;\nvarying vec3 fragPosition;\n\nvoid main() {\n vec4 worldPosition = model * vec4(position, 1.0);\n worldPosition = (worldPosition / worldPosition.w) + vec4(capSize * offset, 0.0);\n gl_Position = projection * view * worldPosition;\n fragColor = color;\n fragPosition = position;\n}"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float opacity;\nvarying vec3 fragPosition;\nvarying vec4 fragColor;\n\nvoid main() {\n if (\n outOfRange(clipBounds[0], clipBounds[1], fragPosition) ||\n fragColor.a * opacity == 0.\n ) discard;\n\n gl_FragColor = opacity * fragColor;\n}"]);e.exports=function(t){return a(t,i,o,null,[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"offset",type:"vec3"}])}},{"gl-shader":307,glslify:408}],261:[function(t,e,r){"use strict";var n=t("gl-texture2d");e.exports=function(t,e,r,n){a||(a=t.FRAMEBUFFER_UNSUPPORTED,i=t.FRAMEBUFFER_INCOMPLETE_ATTACHMENT,o=t.FRAMEBUFFER_INCOMPLETE_DIMENSIONS,s=t.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT);var c=t.getExtension("WEBGL_draw_buffers");!l&&c&&function(t,e){var r=t.getParameter(e.MAX_COLOR_ATTACHMENTS_WEBGL);l=new Array(r+1);for(var n=0;n<=r;++n){for(var a=new Array(r),i=0;i<n;++i)a[i]=t.COLOR_ATTACHMENT0+i;for(i=n;i<r;++i)a[i]=t.NONE;l[n]=a}}(t,c);Array.isArray(e)&&(n=r,r=0|e[1],e=0|e[0]);if("number"!=typeof e)throw new Error("gl-fbo: Missing shape parameter");var u=t.getParameter(t.MAX_RENDERBUFFER_SIZE);if(e<0||e>u||r<0||r>u)throw new Error("gl-fbo: Parameters are too large for FBO");var h=1;if("color"in(n=n||{})){if((h=Math.max(0|n.color,0))<0)throw new Error("gl-fbo: Must specify a nonnegative number of colors");if(h>1){if(!c)throw new Error("gl-fbo: Multiple draw buffer extension not supported");if(h>t.getParameter(c.MAX_COLOR_ATTACHMENTS_WEBGL))throw new Error("gl-fbo: Context does not support "+h+" draw buffers")}}var f=t.UNSIGNED_BYTE,p=t.getExtension("OES_texture_float");if(n.float&&h>0){if(!p)throw new Error("gl-fbo: Context does not support floating point textures");f=t.FLOAT}else n.preferFloat&&h>0&&p&&(f=t.FLOAT);var g=!0;"depth"in n&&(g=!!n.depth);var m=!1;"stencil"in n&&(m=!!n.stencil);return new d(t,e,r,f,h,g,m,c)};var a,i,o,s,l=null;function c(t){return[t.getParameter(t.FRAMEBUFFER_BINDING),t.getParameter(t.RENDERBUFFER_BINDING),t.getParameter(t.TEXTURE_BINDING_2D)]}function u(t,e){t.bindFramebuffer(t.FRAMEBUFFER,e[0]),t.bindRenderbuffer(t.RENDERBUFFER,e[1]),t.bindTexture(t.TEXTURE_2D,e[2])}function h(t){switch(t){case a:throw new Error("gl-fbo: Framebuffer unsupported");case i:throw new Error("gl-fbo: Framebuffer incomplete attachment");case o:throw new Error("gl-fbo: Framebuffer incomplete dimensions");case s:throw new Error("gl-fbo: Framebuffer incomplete missing attachment");default:throw new Error("gl-fbo: Framebuffer failed for unspecified reason")}}function f(t,e,r,a,i,o){if(!a)return null;var s=n(t,e,r,i,a);return s.magFilter=t.NEAREST,s.minFilter=t.NEAREST,s.mipSamples=1,s.bind(),t.framebufferTexture2D(t.FRAMEBUFFER,o,t.TEXTURE_2D,s.handle,0),s}function p(t,e,r,n,a){var i=t.createRenderbuffer();return t.bindRenderbuffer(t.RENDERBUFFER,i),t.renderbufferStorage(t.RENDERBUFFER,n,e,r),t.framebufferRenderbuffer(t.FRAMEBUFFER,a,t.RENDERBUFFER,i),i}function d(t,e,r,n,a,i,o,s){this.gl=t,this._shape=[0|e,0|r],this._destroyed=!1,this._ext=s,this.color=new Array(a);for(var d=0;d<a;++d)this.color[d]=null;this._color_rb=null,this.depth=null,this._depth_rb=null,this._colorType=n,this._useDepth=i,this._useStencil=o;var g=this,m=[0|e,0|r];Object.defineProperties(m,{0:{get:function(){return g._shape[0]},set:function(t){return g.width=t}},1:{get:function(){return g._shape[1]},set:function(t){return g.height=t}}}),this._shapeVector=m,function(t){var e=c(t.gl),r=t.gl,n=t.handle=r.createFramebuffer(),a=t._shape[0],i=t._shape[1],o=t.color.length,s=t._ext,d=t._useStencil,g=t._useDepth,m=t._colorType;r.bindFramebuffer(r.FRAMEBUFFER,n);for(var v=0;v<o;++v)t.color[v]=f(r,a,i,m,r.RGBA,r.COLOR_ATTACHMENT0+v);0===o?(t._color_rb=p(r,a,i,r.RGBA4,r.COLOR_ATTACHMENT0),s&&s.drawBuffersWEBGL(l[0])):o>1&&s.drawBuffersWEBGL(l[o]);var y=r.getExtension("WEBGL_depth_texture");y?d?t.depth=f(r,a,i,y.UNSIGNED_INT_24_8_WEBGL,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g&&(t.depth=f(r,a,i,r.UNSIGNED_SHORT,r.DEPTH_COMPONENT,r.DEPTH_ATTACHMENT)):g&&d?t._depth_rb=p(r,a,i,r.DEPTH_STENCIL,r.DEPTH_STENCIL_ATTACHMENT):g?t._depth_rb=p(r,a,i,r.DEPTH_COMPONENT16,r.DEPTH_ATTACHMENT):d&&(t._depth_rb=p(r,a,i,r.STENCIL_INDEX,r.STENCIL_ATTACHMENT));var x=r.checkFramebufferStatus(r.FRAMEBUFFER);if(x!==r.FRAMEBUFFER_COMPLETE){t._destroyed=!0,r.bindFramebuffer(r.FRAMEBUFFER,null),r.deleteFramebuffer(t.handle),t.handle=null,t.depth&&(t.depth.dispose(),t.depth=null),t._depth_rb&&(r.deleteRenderbuffer(t._depth_rb),t._depth_rb=null);for(v=0;v<t.color.length;++v)t.color[v].dispose(),t.color[v]=null;t._color_rb&&(r.deleteRenderbuffer(t._color_rb),t._color_rb=null),u(r,e),h(x)}u(r,e)}(this)}var g=d.prototype;function m(t,e,r){if(t._destroyed)throw new Error("gl-fbo: Can't resize destroyed FBO");if(t._shape[0]!==e||t._shape[1]!==r){var n=t.gl,a=n.getParameter(n.MAX_RENDERBUFFER_SIZE);if(e<0||e>a||r<0||r>a)throw new Error("gl-fbo: Can't resize FBO, invalid dimensions");t._shape[0]=e,t._shape[1]=r;for(var i=c(n),o=0;o<t.color.length;++o)t.color[o].shape=t._shape;t._color_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._color_rb),n.renderbufferStorage(n.RENDERBUFFER,n.RGBA4,t._shape[0],t._shape[1])),t.depth&&(t.depth.shape=t._shape),t._depth_rb&&(n.bindRenderbuffer(n.RENDERBUFFER,t._depth_rb),t._useDepth&&t._useStencil?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_STENCIL,t._shape[0],t._shape[1]):t._useDepth?n.renderbufferStorage(n.RENDERBUFFER,n.DEPTH_COMPONENT16,t._shape[0],t._shape[1]):t._useStencil&&n.renderbufferStorage(n.RENDERBUFFER,n.STENCIL_INDEX,t._shape[0],t._shape[1])),n.bindFramebuffer(n.FRAMEBUFFER,t.handle);var s=n.checkFramebufferStatus(n.FRAMEBUFFER);s!==n.FRAMEBUFFER_COMPLETE&&(t.dispose(),u(n,i),h(s)),u(n,i)}}Object.defineProperties(g,{shape:{get:function(){return this._destroyed?[0,0]:this._shapeVector},set:function(t){if(Array.isArray(t)||(t=[0|t,0|t]),2!==t.length)throw new Error("gl-fbo: Shape vector must be length 2");var e=0|t[0],r=0|t[1];return m(this,e,r),[e,r]},enumerable:!1},width:{get:function(){return this._destroyed?0:this._shape[0]},set:function(t){return m(this,t|=0,this._shape[1]),t},enumerable:!1},height:{get:function(){return this._destroyed?0:this._shape[1]},set:function(t){return t|=0,m(this,this._shape[0],t),t},enumerable:!1}}),g.bind=function(){if(!this._destroyed){var t=this.gl;t.bindFramebuffer(t.FRAMEBUFFER,this.handle),t.viewport(0,0,this._shape[0],this._shape[1])}},g.dispose=function(){if(!this._destroyed){this._destroyed=!0;var t=this.gl;t.deleteFramebuffer(this.handle),this.handle=null,this.depth&&(this.depth.dispose(),this.depth=null),this._depth_rb&&(t.deleteRenderbuffer(this._depth_rb),this._depth_rb=null);for(var e=0;e<this.color.length;++e)this.color[e].dispose(),this.color[e]=null;this._color_rb&&(t.deleteRenderbuffer(this._color_rb),this._color_rb=null)}}},{"gl-texture2d":322}],262:[function(t,e,r){var n=t("sprintf-js").sprintf,a=t("gl-constants/lookup"),i=t("glsl-shader-name"),o=t("add-line-numbers");e.exports=function(t,e,r){"use strict";var s=i(e)||"of unknown name (see npm glsl-shader-name)",l="unknown type";void 0!==r&&(l=r===a.FRAGMENT_SHADER?"fragment":"vertex");for(var c=n("Error compiling %s shader %s:\n",l,s),u=n("%s%s",c,t),h=t.split("\n"),f={},p=0;p<h.length;p++){var d=h[p];if(""!==d&&"\0"!==d){var g=parseInt(d.split(":")[2]);if(isNaN(g))throw new Error(n("Could not parse error: %s",d));f[g]=d}}var m=o(e).split("\n");for(p=0;p<m.length;p++)if(f[p+3]||f[p+2]||f[p+1]){var v=m[p];if(c+=v+"\n",f[p+1]){var y=f[p+1];y=y.substr(y.split(":",3).join(":").length+1).trim(),c+=n("^^^ %s\n\n",y)}}return{long:c.trim(),short:u.trim()}}},{"add-line-numbers":64,"gl-constants/lookup":258,"glsl-shader-name":400,"sprintf-js":519}],263:[function(t,e,r){"use strict";e.exports=function(t,e){var r=t.gl,n=o(r,l.vertex,l.fragment),a=o(r,l.pickVertex,l.pickFragment),i=s(r),u=s(r),h=s(r),f=s(r),p=new c(t,n,a,i,u,h,f);return p.update(e),t.addObject(p),p};var n=t("binary-search-bounds"),a=t("iota-array"),i=t("typedarray-pool"),o=t("gl-shader"),s=t("gl-buffer"),l=t("./lib/shaders");function c(t,e,r,n,a,i,o){this.plot=t,this.shader=e,this.pickShader=r,this.positionBuffer=n,this.weightBuffer=a,this.colorBuffer=i,this.idBuffer=o,this.xData=[],this.yData=[],this.shape=[0,0],this.bounds=[1/0,1/0,-1/0,-1/0],this.pickOffset=0}var u,h=c.prototype,f=[0,0,1,0,0,1,1,0,1,1,0,1];h.draw=(u=[1,0,0,0,1,0,0,0,1],function(){var t=this.plot,e=this.shader,r=this.bounds,n=this.numVertices;if(!(n<=0)){var a=t.gl,i=t.dataBox,o=r[2]-r[0],s=r[3]-r[1],l=i[2]-i[0],c=i[3]-i[1];u[0]=2*o/l,u[4]=2*s/c,u[6]=2*(r[0]-i[0])/l-1,u[7]=2*(r[1]-i[1])/c-1,e.bind();var h=e.uniforms;h.viewTransform=u,h.shape=this.shape;var f=e.attributes;this.positionBuffer.bind(),f.position.pointer(),this.weightBuffer.bind(),f.weight.pointer(a.UNSIGNED_BYTE,!1),this.colorBuffer.bind(),f.color.pointer(a.UNSIGNED_BYTE,!0),a.drawArrays(a.TRIANGLES,0,n)}}),h.drawPick=function(){var t=[1,0,0,0,1,0,0,0,1],e=[0,0,0,0];return function(r){var n=this.plot,a=this.pickShader,i=this.bounds,o=this.numVertices;if(!(o<=0)){var s=n.gl,l=n.dataBox,c=i[2]-i[0],u=i[3]-i[1],h=l[2]-l[0],f=l[3]-l[1];t[0]=2*c/h,t[4]=2*u/f,t[6]=2*(i[0]-l[0])/h-1,t[7]=2*(i[1]-l[1])/f-1;for(var p=0;p<4;++p)e[p]=r>>8*p&255;this.pickOffset=r,a.bind();var d=a.uniforms;d.viewTransform=t,d.pickOffset=e,d.shape=this.shape;var g=a.attributes;return this.positionBuffer.bind(),g.position.pointer(),this.weightBuffer.bind(),g.weight.pointer(s.UNSIGNED_BYTE,!1),this.idBuffer.bind(),g.pickId.pointer(s.UNSIGNED_BYTE,!1),s.drawArrays(s.TRIANGLES,0,o),r+this.shape[0]*this.shape[1]}}}(),h.pick=function(t,e,r){var n=this.pickOffset,a=this.shape[0]*this.shape[1];if(r<n||r>=n+a)return null;var i=r-n,o=this.xData,s=this.yData;return{object:this,pointId:i,dataCoord:[o[i%this.shape[0]],s[i/this.shape[0]|0]]}},h.update=function(t){var e=(t=t||{}).shape||[0,0],r=t.x||a(e[0]),o=t.y||a(e[1]),s=t.z||new Float32Array(e[0]*e[1]);this.xData=r,this.yData=o;var l=t.colorLevels||[0],c=t.colorValues||[0,0,0,1],u=l.length,h=this.bounds,p=h[0]=r[0],d=h[1]=o[0],g=1/((h[2]=r[r.length-1])-p),m=1/((h[3]=o[o.length-1])-d),v=e[0],y=e[1];this.shape=[v,y];var x=(v-1)*(y-1)*(f.length>>>1);this.numVertices=x;for(var b=i.mallocUint8(4*x),_=i.mallocFloat32(2*x),w=i.mallocUint8(2*x),T=i.mallocUint32(x),k=0,A=0;A<y-1;++A)for(var M=m*(o[A]-d),S=m*(o[A+1]-d),E=0;E<v-1;++E)for(var C=g*(r[E]-p),L=g*(r[E+1]-p),P=0;P<f.length;P+=2){var I,z,O,D,R=f[P],F=f[P+1],B=s[(A+F)*v+(E+R)],N=n.le(l,B);if(N<0)I=c[0],z=c[1],O=c[2],D=c[3];else if(N===u-1)I=c[4*u-4],z=c[4*u-3],O=c[4*u-2],D=c[4*u-1];else{var j=(B-l[N])/(l[N+1]-l[N]),V=1-j,U=4*N,q=4*(N+1);I=V*c[U]+j*c[q],z=V*c[U+1]+j*c[q+1],O=V*c[U+2]+j*c[q+2],D=V*c[U+3]+j*c[q+3]}b[4*k]=255*I,b[4*k+1]=255*z,b[4*k+2]=255*O,b[4*k+3]=255*D,_[2*k]=.5*C+.5*L,_[2*k+1]=.5*M+.5*S,w[2*k]=R,w[2*k+1]=F,T[k]=A*v+E,k+=1}this.positionBuffer.update(_),this.weightBuffer.update(w),this.colorBuffer.update(b),this.idBuffer.update(T),i.free(_),i.free(b),i.free(w),i.free(T)},h.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.positionBuffer.dispose(),this.weightBuffer.dispose(),this.colorBuffer.dispose(),this.idBuffer.dispose(),this.plot.removeObject(this)}},{"./lib/shaders":264,"binary-search-bounds":94,"gl-buffer":253,"gl-shader":307,"iota-array":416,"typedarray-pool":547}],264:[function(t,e,r){"use strict";var n=t("glslify");e.exports={fragment:n(["precision lowp float;\n#define GLSLIFY 1\nvarying vec4 fragColor;\nvoid main() {\n gl_FragColor = vec4(fragColor.rgb * fragColor.a, fragColor.a);\n}\n"]),vertex:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 color;\nattribute vec2 weight;\n\nuniform vec2 shape;\nuniform mat3 viewTransform;\n\nvarying vec4 fragColor;\n\nvoid main() {\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\n fragColor = color;\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\n}\n"]),pickFragment:n(["precision mediump float;\n#define GLSLIFY 1\n\nvarying vec4 fragId;\nvarying vec2 vWeight;\n\nuniform vec2 shape;\nuniform vec4 pickOffset;\n\nvoid main() {\n vec2 d = step(.5, vWeight);\n vec4 id = fragId + pickOffset;\n id.x += d.x + d.y*shape.x;\n\n id.y += floor(id.x / 256.0);\n id.x -= floor(id.x / 256.0) * 256.0;\n\n id.z += floor(id.y / 256.0);\n id.y -= floor(id.y / 256.0) * 256.0;\n\n id.w += floor(id.z / 256.0);\n id.z -= floor(id.z / 256.0) * 256.0;\n\n gl_FragColor = id/255.;\n}\n"]),pickVertex:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 pickId;\nattribute vec2 weight;\n\nuniform vec2 shape;\nuniform mat3 viewTransform;\n\nvarying vec4 fragId;\nvarying vec2 vWeight;\n\nvoid main() {\n vWeight = weight;\n\n fragId = pickId;\n\n vec3 vPosition = viewTransform * vec3( position + (weight-.5)/(shape-1.) , 1.0);\n gl_Position = vec4(vPosition.xy, 0, vPosition.z);\n}\n"])}},{glslify:408}],265:[function(t,e,r){var n=t("glslify"),a=t("gl-shader"),i=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, nextPosition;\nattribute float arcLength, lineWidth;\nattribute vec4 color;\n\nuniform vec2 screenShape;\nuniform float pixelRatio;\nuniform mat4 model, view, projection;\n\nvarying vec4 fragColor;\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\n\nvec4 project(vec3 p) {\n return projection * view * model * vec4(p, 1.0);\n}\n\nvoid main() {\n vec4 startPoint = project(position);\n vec4 endPoint = project(nextPosition);\n\n vec2 A = startPoint.xy / startPoint.w;\n vec2 B = endPoint.xy / endPoint.w;\n\n float clipAngle = atan(\n (B.y - A.y) * screenShape.y,\n (B.x - A.x) * screenShape.x\n );\n\n vec2 offset = 0.5 * pixelRatio * lineWidth * vec2(\n sin(clipAngle),\n -cos(clipAngle)\n ) / screenShape;\n\n gl_Position = vec4(startPoint.xy + startPoint.w * offset, startPoint.zw);\n\n worldPosition = position;\n pixelArcLength = arcLength;\n fragColor = color;\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform sampler2D dashTexture;\nuniform float dashScale;\nuniform float opacity;\n\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\nvarying vec4 fragColor;\n\nvoid main() {\n if (\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\n fragColor.a * opacity == 0.\n ) discard;\n\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\n if(dashWeight < 0.5) {\n discard;\n }\n gl_FragColor = fragColor * opacity;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\n#define FLOAT_MAX 1.70141184e38\n#define FLOAT_MIN 1.17549435e-38\n\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\nvec4 packFloat(float v) {\n float av = abs(v);\n\n //Handle special cases\n if(av < FLOAT_MIN) {\n return vec4(0.0, 0.0, 0.0, 0.0);\n } else if(v > FLOAT_MAX) {\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\n } else if(v < -FLOAT_MAX) {\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\n }\n\n vec4 c = vec4(0,0,0,0);\n\n //Compute exponent and mantissa\n float e = floor(log2(av));\n float m = av * pow(2.0, -e) - 1.0;\n\n //Unpack mantissa\n c[1] = floor(128.0 * m);\n m -= c[1] / 128.0;\n c[2] = floor(32768.0 * m);\n m -= c[2] / 32768.0;\n c[3] = floor(8388608.0 * m);\n\n //Unpack exponent\n float ebias = e + 127.0;\n c[0] = floor(ebias / 2.0);\n ebias -= c[0] * 2.0;\n c[1] += floor(ebias) * 128.0;\n\n //Unpack sign bit\n c[0] += 128.0 * step(0.0, -v);\n\n //Scale back to range\n return c / 255.0;\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform float pickId;\nuniform vec3 clipBounds[2];\n\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\nvarying vec4 fragColor;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\n\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\n}"]),l=[{name:"position",type:"vec3"},{name:"nextPosition",type:"vec3"},{name:"arcLength",type:"float"},{name:"lineWidth",type:"float"},{name:"color",type:"vec4"}];r.createShader=function(t){return a(t,i,o,null,l)},r.createPickShader=function(t){return a(t,i,s,null,l)}},{"gl-shader":307,glslify:408}],266:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl||t.scene&&t.scene.gl,r=h(e);r.attributes.position.location=0,r.attributes.nextPosition.location=1,r.attributes.arcLength.location=2,r.attributes.lineWidth.location=3,r.attributes.color.location=4;var o=f(e);o.attributes.position.location=0,o.attributes.nextPosition.location=1,o.attributes.arcLength.location=2,o.attributes.lineWidth.location=3,o.attributes.color.location=4;for(var s=n(e),l=a(e,[{buffer:s,size:3,offset:0,stride:48},{buffer:s,size:3,offset:12,stride:48},{buffer:s,size:1,offset:24,stride:48},{buffer:s,size:1,offset:28,stride:48},{buffer:s,size:4,offset:32,stride:48}]),u=c(new Array(1024),[256,1,4]),p=0;p<1024;++p)u.data[p]=255;var d=i(e,u);d.wrap=e.REPEAT;var g=new v(e,r,o,s,l,d);return g.update(t),g};var n=t("gl-buffer"),a=t("gl-vao"),i=t("gl-texture2d"),o=new Uint8Array(4),s=new Float32Array(o.buffer);var l=t("binary-search-bounds"),c=t("ndarray"),u=t("./lib/shaders"),h=u.createShader,f=u.createPickShader,p=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function d(t,e){for(var r=0,n=0;n<3;++n){var a=t[n]-e[n];r+=a*a}return Math.sqrt(r)}function g(t){for(var e=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],r=0;r<3;++r)e[0][r]=Math.max(t[0][r],e[0][r]),e[1][r]=Math.min(t[1][r],e[1][r]);return e}function m(t,e,r,n){this.arcLength=t,this.position=e,this.index=r,this.dataCoordinate=n}function v(t,e,r,n,a,i){this.gl=t,this.shader=e,this.pickShader=r,this.buffer=n,this.vao=a,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.points=[],this.arcLength=[],this.vertexCount=0,this.bounds=[[0,0,0],[0,0,0]],this.pickId=0,this.lineWidth=1,this.texture=i,this.dashScale=1,this.opacity=1,this.hasAlpha=!1,this.dirty=!0,this.pixelRatio=1}var y=v.prototype;y.isTransparent=function(){return this.hasAlpha},y.isOpaque=function(){return!this.hasAlpha},y.pickSlots=1,y.setPickBase=function(t){this.pickId=t},y.drawTransparent=y.draw=function(t){if(this.vertexCount){var e=this.gl,r=this.shader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,clipBounds:g(this.clipBounds),dashTexture:this.texture.bind(),dashScale:this.dashScale/this.arcLength[this.arcLength.length-1],opacity:this.opacity,screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.drawPick=function(t){if(this.vertexCount){var e=this.gl,r=this.pickShader,n=this.vao;r.bind(),r.uniforms={model:t.model||p,view:t.view||p,projection:t.projection||p,pickId:this.pickId,clipBounds:g(this.clipBounds),screenShape:[e.drawingBufferWidth,e.drawingBufferHeight],pixelRatio:this.pixelRatio},n.bind(),n.draw(e.TRIANGLE_STRIP,this.vertexCount),n.unbind()}},y.update=function(t){var e,r;this.dirty=!0;var n=!!t.connectGaps;"dashScale"in t&&(this.dashScale=t.dashScale),this.hasAlpha=!1,"opacity"in t&&(this.opacity=+t.opacity,this.opacity<1&&(this.hasAlpha=!0));var a=[],i=[],o=[],s=0,u=0,h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],f=t.position||t.positions;if(f){var p=t.color||t.colors||[0,0,0,1],g=t.lineWidth||1,m=!1;t:for(e=1;e<f.length;++e){var v,y,x,b=f[e-1],_=f[e];for(i.push(s),o.push(b.slice()),r=0;r<3;++r){if(isNaN(b[r])||isNaN(_[r])||!isFinite(b[r])||!isFinite(_[r])){if(!n&&a.length>0){for(var w=0;w<24;++w)a.push(a[a.length-12]);u+=2,m=!0}continue t}h[0][r]=Math.min(h[0][r],b[r],_[r]),h[1][r]=Math.max(h[1][r],b[r],_[r])}Array.isArray(p[0])?(v=p.length>e-1?p[e-1]:p.length>0?p[p.length-1]:[0,0,0,1],y=p.length>e?p[e]:p.length>0?p[p.length-1]:[0,0,0,1]):v=y=p,3===v.length&&(v=[v[0],v[1],v[2],1]),3===y.length&&(y=[y[0],y[1],y[2],1]),!this.hasAlpha&&v[3]<1&&(this.hasAlpha=!0),x=Array.isArray(g)?g.length>e-1?g[e-1]:g.length>0?g[g.length-1]:[0,0,0,1]:g;var T=s;if(s+=d(b,_),m){for(r=0;r<2;++r)a.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3]);u+=2,m=!1}a.push(b[0],b[1],b[2],_[0],_[1],_[2],T,x,v[0],v[1],v[2],v[3],b[0],b[1],b[2],_[0],_[1],_[2],T,-x,v[0],v[1],v[2],v[3],_[0],_[1],_[2],b[0],b[1],b[2],s,-x,y[0],y[1],y[2],y[3],_[0],_[1],_[2],b[0],b[1],b[2],s,x,y[0],y[1],y[2],y[3]),u+=4}}if(this.buffer.update(a),i.push(s),o.push(f[f.length-1].slice()),this.bounds=h,this.vertexCount=u,this.points=o,this.arcLength=i,"dashes"in t){var k=t.dashes.slice();for(k.unshift(0),e=1;e<k.length;++e)k[e]=k[e-1]+k[e];var A=c(new Array(1024),[256,1,4]);for(e=0;e<256;++e){for(r=0;r<4;++r)A.set(e,0,r,0);1&l.le(k,k[k.length-1]*e/255)?A.set(e,0,0,0):A.set(e,0,0,255)}this.texture.setPixels(A)}},y.dispose=function(){this.shader.dispose(),this.vao.dispose(),this.buffer.dispose()},y.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=function(t,e,r,n){return o[0]=n,o[1]=r,o[2]=e,o[3]=t,s[0]}(t.value[0],t.value[1],t.value[2],0),r=l.le(this.arcLength,e);if(r<0)return null;if(r===this.arcLength.length-1)return new m(this.arcLength[this.arcLength.length-1],this.points[this.points.length-1].slice(),r);for(var n=this.points[r],a=this.points[Math.min(r+1,this.points.length-1)],i=(e-this.arcLength[r])/(this.arcLength[r+1]-this.arcLength[r]),c=1-i,u=[0,0,0],h=0;h<3;++h)u[h]=c*n[h]+i*a[h];var f=Math.min(i<.5?r:r+1,this.points.length-1);return new m(e,u,f,this.points[f])}},{"./lib/shaders":265,"binary-search-bounds":94,"gl-buffer":253,"gl-texture2d":322,"gl-vao":327,ndarray:448}],267:[function(t,e,r){e.exports=function(t){var e=new Float32Array(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e}},{}],268:[function(t,e,r){e.exports=function(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],269:[function(t,e,r){e.exports=function(t){var e=t[0],r=t[1],n=t[2],a=t[3],i=t[4],o=t[5],s=t[6],l=t[7],c=t[8],u=t[9],h=t[10],f=t[11],p=t[12],d=t[13],g=t[14],m=t[15];return(e*o-r*i)*(h*m-f*g)-(e*s-n*i)*(u*m-f*d)+(e*l-a*i)*(u*g-h*d)+(r*s-n*o)*(c*m-f*p)-(r*l-a*o)*(c*g-h*p)+(n*l-a*s)*(c*d-u*p)}},{}],270:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=r+r,s=n+n,l=a+a,c=r*o,u=n*o,h=n*s,f=a*o,p=a*s,d=a*l,g=i*o,m=i*s,v=i*l;return t[0]=1-h-d,t[1]=u+v,t[2]=f-m,t[3]=0,t[4]=u-v,t[5]=1-c-d,t[6]=p+g,t[7]=0,t[8]=f+m,t[9]=p-g,t[10]=1-c-h,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],271:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=n+n,l=a+a,c=i+i,u=n*s,h=n*l,f=n*c,p=a*l,d=a*c,g=i*c,m=o*s,v=o*l,y=o*c;return t[0]=1-(p+g),t[1]=h+y,t[2]=f-v,t[3]=0,t[4]=h-y,t[5]=1-(u+g),t[6]=d+m,t[7]=0,t[8]=f+v,t[9]=d-m,t[10]=1-(u+p),t[11]=0,t[12]=r[0],t[13]=r[1],t[14]=r[2],t[15]=1,t}},{}],272:[function(t,e,r){e.exports=function(t){return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},{}],273:[function(t,e,r){e.exports=function(t,e){var r=e[0],n=e[1],a=e[2],i=e[3],o=e[4],s=e[5],l=e[6],c=e[7],u=e[8],h=e[9],f=e[10],p=e[11],d=e[12],g=e[13],m=e[14],v=e[15],y=r*s-n*o,x=r*l-a*o,b=r*c-i*o,_=n*l-a*s,w=n*c-i*s,T=a*c-i*l,k=u*g-h*d,A=u*m-f*d,M=u*v-p*d,S=h*m-f*g,E=h*v-p*g,C=f*v-p*m,L=y*C-x*E+b*S+_*M-w*A+T*k;if(!L)return null;return L=1/L,t[0]=(s*C-l*E+c*S)*L,t[1]=(a*E-n*C-i*S)*L,t[2]=(g*T-m*w+v*_)*L,t[3]=(f*w-h*T-p*_)*L,t[4]=(l*M-o*C-c*A)*L,t[5]=(r*C-a*M+i*A)*L,t[6]=(m*b-d*T-v*x)*L,t[7]=(u*T-f*b+p*x)*L,t[8]=(o*E-s*M+c*k)*L,t[9]=(n*M-r*E-i*k)*L,t[10]=(d*w-g*b+v*y)*L,t[11]=(h*b-u*w-p*y)*L,t[12]=(s*A-o*S-l*k)*L,t[13]=(r*S-n*A+a*k)*L,t[14]=(g*x-d*_-m*y)*L,t[15]=(u*_-h*x+f*y)*L,t}},{}],274:[function(t,e,r){var n=t("./identity");e.exports=function(t,e,r,a){var i,o,s,l,c,u,h,f,p,d,g=e[0],m=e[1],v=e[2],y=a[0],x=a[1],b=a[2],_=r[0],w=r[1],T=r[2];if(Math.abs(g-_)<1e-6&&Math.abs(m-w)<1e-6&&Math.abs(v-T)<1e-6)return n(t);h=g-_,f=m-w,p=v-T,d=1/Math.sqrt(h*h+f*f+p*p),i=x*(p*=d)-b*(f*=d),o=b*(h*=d)-y*p,s=y*f-x*h,(d=Math.sqrt(i*i+o*o+s*s))?(i*=d=1/d,o*=d,s*=d):(i=0,o=0,s=0);l=f*s-p*o,c=p*i-h*s,u=h*o-f*i,(d=Math.sqrt(l*l+c*c+u*u))?(l*=d=1/d,c*=d,u*=d):(l=0,c=0,u=0);return t[0]=i,t[1]=l,t[2]=h,t[3]=0,t[4]=o,t[5]=c,t[6]=f,t[7]=0,t[8]=s,t[9]=u,t[10]=p,t[11]=0,t[12]=-(i*g+o*m+s*v),t[13]=-(l*g+c*m+u*v),t[14]=-(h*g+f*m+p*v),t[15]=1,t}},{"./identity":272}],275:[function(t,e,r){e.exports=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],g=e[12],m=e[13],v=e[14],y=e[15],x=r[0],b=r[1],_=r[2],w=r[3];return t[0]=x*n+b*s+_*h+w*g,t[1]=x*a+b*l+_*f+w*m,t[2]=x*i+b*c+_*p+w*v,t[3]=x*o+b*u+_*d+w*y,x=r[4],b=r[5],_=r[6],w=r[7],t[4]=x*n+b*s+_*h+w*g,t[5]=x*a+b*l+_*f+w*m,t[6]=x*i+b*c+_*p+w*v,t[7]=x*o+b*u+_*d+w*y,x=r[8],b=r[9],_=r[10],w=r[11],t[8]=x*n+b*s+_*h+w*g,t[9]=x*a+b*l+_*f+w*m,t[10]=x*i+b*c+_*p+w*v,t[11]=x*o+b*u+_*d+w*y,x=r[12],b=r[13],_=r[14],w=r[15],t[12]=x*n+b*s+_*h+w*g,t[13]=x*a+b*l+_*f+w*m,t[14]=x*i+b*c+_*p+w*v,t[15]=x*o+b*u+_*d+w*y,t}},{}],276:[function(t,e,r){e.exports=function(t,e,r,n,a,i,o){var s=1/(e-r),l=1/(n-a),c=1/(i-o);return t[0]=-2*s,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=-2*l,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=2*c,t[11]=0,t[12]=(e+r)*s,t[13]=(a+n)*l,t[14]=(o+i)*c,t[15]=1,t}},{}],277:[function(t,e,r){e.exports=function(t,e,r,n,a){var i=1/Math.tan(e/2),o=1/(n-a);return t[0]=i/r,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=i,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=(a+n)*o,t[11]=-1,t[12]=0,t[13]=0,t[14]=2*a*n*o,t[15]=0,t}},{}],278:[function(t,e,r){e.exports=function(t,e,r,n){var a,i,o,s,l,c,u,h,f,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E=n[0],C=n[1],L=n[2],P=Math.sqrt(E*E+C*C+L*L);if(Math.abs(P)<1e-6)return null;E*=P=1/P,C*=P,L*=P,a=Math.sin(r),i=Math.cos(r),o=1-i,s=e[0],l=e[1],c=e[2],u=e[3],h=e[4],f=e[5],p=e[6],d=e[7],g=e[8],m=e[9],v=e[10],y=e[11],x=E*E*o+i,b=C*E*o+L*a,_=L*E*o-C*a,w=E*C*o-L*a,T=C*C*o+i,k=L*C*o+E*a,A=E*L*o+C*a,M=C*L*o-E*a,S=L*L*o+i,t[0]=s*x+h*b+g*_,t[1]=l*x+f*b+m*_,t[2]=c*x+p*b+v*_,t[3]=u*x+d*b+y*_,t[4]=s*w+h*T+g*k,t[5]=l*w+f*T+m*k,t[6]=c*w+p*T+v*k,t[7]=u*w+d*T+y*k,t[8]=s*A+h*M+g*S,t[9]=l*A+f*M+m*S,t[10]=c*A+p*M+v*S,t[11]=u*A+d*M+y*S,e!==t&&(t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t}},{}],279:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[4],o=e[5],s=e[6],l=e[7],c=e[8],u=e[9],h=e[10],f=e[11];e!==t&&(t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=e[3],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[4]=i*a+c*n,t[5]=o*a+u*n,t[6]=s*a+h*n,t[7]=l*a+f*n,t[8]=c*a-i*n,t[9]=u*a-o*n,t[10]=h*a-s*n,t[11]=f*a-l*n,t}},{}],280:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[0],o=e[1],s=e[2],l=e[3],c=e[8],u=e[9],h=e[10],f=e[11];e!==t&&(t[4]=e[4],t[5]=e[5],t[6]=e[6],t[7]=e[7],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=i*a-c*n,t[1]=o*a-u*n,t[2]=s*a-h*n,t[3]=l*a-f*n,t[8]=i*n+c*a,t[9]=o*n+u*a,t[10]=s*n+h*a,t[11]=l*n+f*a,t}},{}],281:[function(t,e,r){e.exports=function(t,e,r){var n=Math.sin(r),a=Math.cos(r),i=e[0],o=e[1],s=e[2],l=e[3],c=e[4],u=e[5],h=e[6],f=e[7];e!==t&&(t[8]=e[8],t[9]=e[9],t[10]=e[10],t[11]=e[11],t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15]);return t[0]=i*a+c*n,t[1]=o*a+u*n,t[2]=s*a+h*n,t[3]=l*a+f*n,t[4]=c*a-i*n,t[5]=u*a-o*n,t[6]=h*a-s*n,t[7]=f*a-l*n,t}},{}],282:[function(t,e,r){e.exports=function(t,e,r){var n=r[0],a=r[1],i=r[2];return t[0]=e[0]*n,t[1]=e[1]*n,t[2]=e[2]*n,t[3]=e[3]*n,t[4]=e[4]*a,t[5]=e[5]*a,t[6]=e[6]*a,t[7]=e[7]*a,t[8]=e[8]*i,t[9]=e[9]*i,t[10]=e[10]*i,t[11]=e[11]*i,t[12]=e[12],t[13]=e[13],t[14]=e[14],t[15]=e[15],t}},{}],283:[function(t,e,r){e.exports=function(t,e,r){var n,a,i,o,s,l,c,u,h,f,p,d,g=r[0],m=r[1],v=r[2];e===t?(t[12]=e[0]*g+e[4]*m+e[8]*v+e[12],t[13]=e[1]*g+e[5]*m+e[9]*v+e[13],t[14]=e[2]*g+e[6]*m+e[10]*v+e[14],t[15]=e[3]*g+e[7]*m+e[11]*v+e[15]):(n=e[0],a=e[1],i=e[2],o=e[3],s=e[4],l=e[5],c=e[6],u=e[7],h=e[8],f=e[9],p=e[10],d=e[11],t[0]=n,t[1]=a,t[2]=i,t[3]=o,t[4]=s,t[5]=l,t[6]=c,t[7]=u,t[8]=h,t[9]=f,t[10]=p,t[11]=d,t[12]=n*g+s*m+h*v+e[12],t[13]=a*g+l*m+f*v+e[13],t[14]=i*g+c*m+p*v+e[14],t[15]=o*g+u*m+d*v+e[15]);return t}},{}],284:[function(t,e,r){e.exports=function(t,e){if(t===e){var r=e[1],n=e[2],a=e[3],i=e[6],o=e[7],s=e[11];t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=r,t[6]=e[9],t[7]=e[13],t[8]=n,t[9]=i,t[11]=e[14],t[12]=a,t[13]=o,t[14]=s}else t[0]=e[0],t[1]=e[4],t[2]=e[8],t[3]=e[12],t[4]=e[1],t[5]=e[5],t[6]=e[9],t[7]=e[13],t[8]=e[2],t[9]=e[6],t[10]=e[10],t[11]=e[14],t[12]=e[3],t[13]=e[7],t[14]=e[11],t[15]=e[15];return t}},{}],285:[function(t,e,r){"use strict";var n=t("barycentric"),a=t("polytope-closest-point/lib/closest_point_2d.js");function i(t,e){for(var r=[0,0,0,0],n=0;n<4;++n)for(var a=0;a<4;++a)r[a]+=t[4*n+a]*e[n];return r}function o(t,e,r,n,a){for(var o=i(n,i(r,i(e,[t[0],t[1],t[2],1]))),s=0;s<3;++s)o[s]/=o[3];return[.5*a[0]*(1+o[0]),.5*a[1]*(1-o[1])]}function s(t,e){for(var r=[0,0,0],n=0;n<t.length;++n)for(var a=t[n],i=e[n],o=0;o<3;++o)r[o]+=i*a[o];return r}e.exports=function(t,e,r,i,l,c){if(1===t.length)return[0,t[0].slice()];for(var u=new Array(t.length),h=0;h<t.length;++h)u[h]=o(t[h],r,i,l,c);var f=0,p=1/0;for(h=0;h<u.length;++h){for(var d=0,g=0;g<2;++g)d+=Math.pow(u[h][g]-e[g],2);d<p&&(p=d,f=h)}var m=function(t,e){if(2===t.length){for(var r=0,i=0,o=0;o<2;++o)r+=Math.pow(e[o]-t[0][o],2),i+=Math.pow(e[o]-t[1][o],2);return r=Math.sqrt(r),i=Math.sqrt(i),r+i<1e-6?[1,0]:[i/(r+i),r/(i+r)]}if(3===t.length){var s=[0,0];return a(t[0],t[1],t[2],e,s),n(t,s)}return[]}(u,e),v=0;for(h=0;h<3;++h){if(m[h]<-.001||m[h]>1.0001)return null;v+=m[h]}if(Math.abs(v-1)>.001)return null;return[f,s(t,m),m]}},{barycentric:76,"polytope-closest-point/lib/closest_point_2d.js":479}],286:[function(t,e,r){var n=t("glslify"),a=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, normal;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model\n , view\n , projection\n , inverseModel;\nuniform vec3 eyePosition\n , lightPosition;\n\nvarying vec3 f_normal\n , f_lightDirection\n , f_eyeDirection\n , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvec4 project(vec3 p) {\n return projection * view * model * vec4(p, 1.0);\n}\n\nvoid main() {\n gl_Position = project(position);\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * vec4(position , 1.0);\n cameraCoordinate.xyz /= cameraCoordinate.w;\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n f_color = color;\n f_data = position;\n f_uv = uv;\n}\n"]),i=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness,\n float fresnel) {\n\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n //Half angle vector\n vec3 H = normalize(lightDirection + viewDirection);\n\n //Geometric term\n float NdotH = max(dot(surfaceNormal, H), 0.0);\n float VdotH = max(dot(viewDirection, H), 0.000001);\n float LdotH = max(dot(lightDirection, H), 0.000001);\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\n float G = min(1.0, min(G1, G2));\n \n //Distribution term\n float D = beckmannDistribution(NdotH, roughness);\n\n //Fresnel term\n float F = pow(1.0 - VdotN, fresnel);\n\n //Multiply terms and done\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness\n , fresnel\n , kambient\n , kdiffuse\n , kspecular;\nuniform sampler2D texture;\n\nvarying vec3 f_normal\n , f_lightDirection\n , f_eyeDirection\n , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (f_color.a == 0.0 ||\n outOfRange(clipBounds[0], clipBounds[1], f_data)\n ) discard;\n\n vec3 N = normalize(f_normal);\n vec3 L = normalize(f_lightDirection);\n vec3 V = normalize(f_eyeDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\n\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = litColor * f_color.a;\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model, view, projection;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n gl_Position = projection * view * model * vec4(position, 1.0);\n f_color = color;\n f_data = position;\n f_uv = uv;\n}"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\n\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),l=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\nattribute float pointSize;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\n } else {\n gl_Position = projection * view * model * vec4(position, 1.0);\n }\n gl_PointSize = pointSize;\n f_color = color;\n f_uv = uv;\n}"]),c=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\n if(dot(pointR, pointR) > 0.25) {\n discard;\n }\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),u=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n gl_Position = projection * view * model * vec4(position, 1.0);\n f_id = id;\n f_position = position;\n}"]),h=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n gl_FragColor = vec4(pickId, f_id.xyz);\n}"]),f=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute float pointSize;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\n } else {\n gl_Position = projection * view * model * vec4(position, 1.0);\n gl_PointSize = pointSize;\n }\n f_id = id;\n f_position = position;\n}"]),p=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\n\nvoid main() {\n gl_Position = projection * view * model * vec4(position, 1.0);\n}"]),d=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec3 contourColor;\n\nvoid main() {\n gl_FragColor = vec4(contourColor, 1.0);\n}\n"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:"position",type:"vec3"},{name:"normal",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},r.wireShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},r.pointShader={vertex:l,fragment:c,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"pointSize",type:"float"}]},r.pickShader={vertex:u,fragment:h,attributes:[{name:"position",type:"vec3"},{name:"id",type:"vec4"}]},r.pointPickShader={vertex:f,fragment:h,attributes:[{name:"position",type:"vec3"},{name:"pointSize",type:"float"},{name:"id",type:"vec4"}]},r.contourShader={vertex:p,fragment:d,attributes:[{name:"position",type:"vec3"}]}},{glslify:408}],287:[function(t,e,r){"use strict";var n=t("gl-shader"),a=t("gl-buffer"),i=t("gl-vao"),o=t("gl-texture2d"),s=t("normals"),l=t("gl-mat4/multiply"),c=t("gl-mat4/invert"),u=t("ndarray"),h=t("colormap"),f=t("simplicial-complex-contour"),p=t("typedarray-pool"),d=t("./lib/shaders"),g=t("./lib/closest-point"),m=d.meshShader,v=d.wireShader,y=d.pointShader,x=d.pickShader,b=d.pointPickShader,_=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m,v,y,x,b,_,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=a,this.pickShader=i,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=m,this.edgeUVs=v,this.edgeIds=g,this.edgeVAO=y,this.edgeCount=0,this.pointPositions=x,this.pointColors=_,this.pointUVs=T,this.pointSizes=k,this.pointIds=b,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}function M(t){var e=n(t,m.vertex,m.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.normal.location=4,e}function S(t){var e=n(t,v.vertex,v.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e}function E(t){var e=n(t,y.vertex,y.fragment);return e.attributes.position.location=0,e.attributes.color.location=2,e.attributes.uv.location=3,e.attributes.pointSize.location=4,e}function C(t){var e=n(t,x.vertex,x.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e}function L(t){var e=n(t,b.vertex,b.fragment);return e.attributes.position.location=0,e.attributes.id.location=1,e.attributes.pointSize.location=4,e}function P(t){var e=n(t,_.vertex,_.fragment);return e.attributes.position.location=0,e}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=f(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,a=e.vertexWeights,i=r.length,o=p.mallocFloat32(6*i),s=0,l=0;l<i;++l)for(var c=r[l],u=0;u<2;++u){var h=c[0];2===c.length&&(h=c[u]);for(var d=n[h][0],g=n[h][1],m=a[h],v=1-m,y=this.positions[d],x=this.positions[g],b=0;b<3;++b)o[s++]=m*y[b]+v*x[b]}this.contourCount=s/3|0,this.contourPositions.update(o.subarray(0,s)),p.free(o)}else this.contourCount=0},k.update=function(t){t=t||{};var e=this.gl;this.dirty=!0,"contourEnable"in t&&(this.contourEnable=t.contourEnable),"contourColor"in t&&(this.contourColor=t.contourColor),"lineWidth"in t&&(this.lineWidth=t.lineWidth),"lightPosition"in t&&(this.lightPosition=t.lightPosition),this.hasAlpha=!1,"opacity"in t&&(this.opacity=t.opacity,this.opacity<1&&(this.hasAlpha=!0)),"opacityscale"in t&&(this.opacityscale=t.opacityscale,this.hasAlpha=!0),"ambient"in t&&(this.ambientLight=t.ambient),"diffuse"in t&&(this.diffuseLight=t.diffuse),"specular"in t&&(this.specularLight=t.specular),"roughness"in t&&(this.roughness=t.roughness),"fresnel"in t&&(this.fresnel=t.fresnel),t.texture?(this.texture.dispose(),this.texture=o(e,t.texture)):t.colormap&&(this.texture.shape=[256,256],this.texture.minFilter=e.LINEAR_MIPMAP_LINEAR,this.texture.magFilter=e.LINEAR,this.texture.setPixels(function(t,e){for(var r=h({colormap:t,nshades:256,format:"rgba"}),n=new Uint8Array(1024),a=0;a<256;++a){for(var i=r[a],o=0;o<3;++o)n[4*a+o]=i[o];n[4*a+3]=e?255*A(a/255,e):255*i[3]}return u(n,[256,256,4],[4,0,1])}(t.colormap,this.opacityscale)),this.texture.generateMipmap());var r=t.cells,n=t.positions;if(n&&r){var a=[],i=[],l=[],c=[],f=[],p=[],d=[],g=[],m=[],v=[],y=[],x=[],b=[],_=[];this.cells=r,this.positions=n;var w=t.vertexNormals,T=t.cellNormals,k=void 0===t.vertexNormalsEpsilon?1e-6:t.vertexNormalsEpsilon,M=void 0===t.faceNormalsEpsilon?1e-6:t.faceNormalsEpsilon;t.useFacetNormals&&!T&&(T=s.faceNormals(r,n,M)),T||w||(w=s.vertexNormals(r,n,k));var S=t.vertexColors,E=t.cellColors,C=t.meshColor||[1,1,1,1],L=t.vertexUVs,P=t.vertexIntensity,I=t.cellUVs,z=t.cellIntensity,O=1/0,D=-1/0;if(!L&&!I)if(P)if(t.vertexIntensityBounds)O=+t.vertexIntensityBounds[0],D=+t.vertexIntensityBounds[1];else for(var R=0;R<P.length;++R){var F=P[R];O=Math.min(O,F),D=Math.max(D,F)}else if(z)if(t.cellIntensityBounds)O=+t.cellIntensityBounds[0],D=+t.cellIntensityBounds[1];else for(R=0;R<z.length;++R){F=z[R];O=Math.min(O,F),D=Math.max(D,F)}else for(R=0;R<n.length;++R){F=n[R][2];O=Math.min(O,F),D=Math.max(D,F)}this.intensity=P||(z||function(t){for(var e=t.length,r=new Array(e),n=0;n<e;++n)r[n]=t[n][2];return r}(n)),this.pickVertex=!(z||E);var B=t.pointSizes,N=t.pointSize||1;this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(R=0;R<n.length;++R)for(var j=n[R],V=0;V<3;++V)!isNaN(j[V])&&isFinite(j[V])&&(this.bounds[0][V]=Math.min(this.bounds[0][V],j[V]),this.bounds[1][V]=Math.max(this.bounds[1][V],j[V]));var U=0,q=0,H=0;t:for(R=0;R<r.length;++R){var G=r[R];switch(G.length){case 1:for(j=n[W=G[0]],V=0;V<3;++V)if(isNaN(j[V])||!isFinite(j[V]))continue t;v.push(j[0],j[1],j[2]),Z=S?S[W]:E?E[R]:C,this.opacityscale&&P?i.push(Z[0],Z[1],Z[2],this.opacity*A((P[W]-O)/(D-O),this.opacityscale)):3===Z.length?y.push(Z[0],Z[1],Z[2],this.opacity):(y.push(Z[0],Z[1],Z[2],Z[3]*this.opacity),Z[3]<1&&(this.hasAlpha=!0)),X=L?L[W]:P?[(P[W]-O)/(D-O),0]:I?I[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],x.push(X[0],X[1]),B?b.push(B[W]):b.push(N),_.push(R),H+=1;break;case 2:for(V=0;V<2;++V){j=n[W=G[V]];for(var Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t}for(V=0;V<2;++V){j=n[W=G[V]];p.push(j[0],j[1],j[2]),Z=S?S[W]:E?E[R]:C,this.opacityscale&&P?i.push(Z[0],Z[1],Z[2],this.opacity*A((P[W]-O)/(D-O),this.opacityscale)):3===Z.length?d.push(Z[0],Z[1],Z[2],this.opacity):(d.push(Z[0],Z[1],Z[2],Z[3]*this.opacity),Z[3]<1&&(this.hasAlpha=!0)),X=L?L[W]:P?[(P[W]-O)/(D-O),0]:I?I[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],g.push(X[0],X[1]),m.push(R)}q+=1;break;case 3:for(V=0;V<3;++V)for(j=n[W=G[V]],Y=0;Y<3;++Y)if(isNaN(j[Y])||!isFinite(j[Y]))continue t;for(V=0;V<3;++V){var W,Z,X,J;j=n[W=G[2-V]];a.push(j[0],j[1],j[2]),(Z=S?S[W]:E?E[R]:C)?this.opacityscale&&P?i.push(Z[0],Z[1],Z[2],this.opacity*A((P[W]-O)/(D-O),this.opacityscale)):3===Z.length?i.push(Z[0],Z[1],Z[2],this.opacity):(i.push(Z[0],Z[1],Z[2],Z[3]*this.opacity),Z[3]<1&&(this.hasAlpha=!0)):i.push(.5,.5,.5,1),X=L?L[W]:P?[(P[W]-O)/(D-O),0]:I?I[R]:z?[(z[R]-O)/(D-O),0]:[(j[2]-O)/(D-O),0],c.push(X[0],X[1]),J=w?w[W]:T[R],l.push(J[0],J[1],J[2]),f.push(R)}U+=1}}this.pointCount=H,this.edgeCount=q,this.triangleCount=U,this.pointPositions.update(v),this.pointColors.update(y),this.pointUVs.update(x),this.pointSizes.update(b),this.pointIds.update(new Uint32Array(_)),this.edgePositions.update(p),this.edgeColors.update(d),this.edgeUVs.update(g),this.edgeIds.update(new Uint32Array(m)),this.trianglePositions.update(a),this.triangleColors.update(i),this.triangleUVs.update(c),this.triangleNormals.update(l),this.triangleIds.update(new Uint32Array(f))}},k.drawTransparent=k.draw=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,a=t.projection||w,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);var s={model:r,view:n,projection:a,inverseModel:w.slice(),clipBounds:i,kambient:this.ambientLight,kdiffuse:this.diffuseLight,kspecular:this.specularLight,roughness:this.roughness,fresnel:this.fresnel,eyePosition:[0,0,0],lightPosition:[0,0,0],contourColor:this.contourColor,texture:0};s.inverseModel=c(s.inverseModel,s.model),e.disable(e.CULL_FACE),this.texture.bind(0);var u=new Array(16);l(u,s.view,s.model),l(u,s.projection,u),c(u,u);for(o=0;o<3;++o)s.eyePosition[o]=u[12+o]/u[15];var h,f=u[15];for(o=0;o<3;++o)f+=this.lightPosition[o]*u[4*o+3];for(o=0;o<3;++o){for(var p=u[12+o],d=0;d<3;++d)p+=u[4*d+o]*this.lightPosition[d];s.lightPosition[o]=p/f}this.triangleCount>0&&((h=this.triShader).bind(),h.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind());this.edgeCount>0&&this.lineWidth>0&&((h=this.lineShader).bind(),h.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind());this.pointCount>0&&((h=this.pointShader).bind(),h.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind());this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((h=this.contourShader).bind(),h.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,a=t.projection||w,i=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)i[0][o]=Math.max(i[0][o],this.clipBounds[0][o]),i[1][o]=Math.min(i[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(a),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:a,clipBounds:i,pickId:this.pickId/255};((s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0)&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,a=new Array(r.length),i=0;i<r.length;++i)a[i]=n[r[i]];var o=t.coord[0],s=t.coord[1];if(!this.pickVertex){var l=this.positions[r[0]],c=this.positions[r[1]],u=this.positions[r[2]],h=[(l[0]+c[0]+u[0])/3,(l[1]+c[1]+u[1])/3,(l[2]+c[2]+u[2])/3];return{_cellCenter:!0,position:[o,s],index:e,cell:r,cellId:e,intensity:this.intensity[e],dataCoordinate:h}}var f=g(a,[o*this.pixelRatio,this._resolution[1]-s*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!f)return null;var p=f[2],d=0;for(i=0;i<r.length;++i)d+=p[i]*this.intensity[r[i]];return{position:f[1],index:r[f[0]],cell:r,cellId:e,intensity:d,dataCoordinate:this.positions[r[f[0]]]}},k.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()},e.exports=function(t,e){1===arguments.length&&(t=(e=t).gl);var r=t.getExtension("OES_standard_derivatives")||t.getExtension("MOZ_OES_standard_derivatives")||t.getExtension("WEBKIT_OES_standard_derivatives");if(!r)throw new Error("derivatives not supported");var n=M(t),s=S(t),l=E(t),c=C(t),h=L(t),f=P(t),p=o(t,u(new Uint8Array([255,255,255,255]),[1,1,4]));p.generateMipmap(),p.minFilter=t.LINEAR_MIPMAP_LINEAR,p.magFilter=t.LINEAR;var d=a(t),g=a(t),m=a(t),v=a(t),y=a(t),x=i(t,[{buffer:d,type:t.FLOAT,size:3},{buffer:y,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:g,type:t.FLOAT,size:4},{buffer:m,type:t.FLOAT,size:2},{buffer:v,type:t.FLOAT,size:3}]),b=a(t),_=a(t),w=a(t),k=a(t),A=i(t,[{buffer:b,type:t.FLOAT,size:3},{buffer:k,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:_,type:t.FLOAT,size:4},{buffer:w,type:t.FLOAT,size:2}]),I=a(t),z=a(t),O=a(t),D=a(t),R=a(t),F=i(t,[{buffer:I,type:t.FLOAT,size:3},{buffer:R,type:t.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:z,type:t.FLOAT,size:4},{buffer:O,type:t.FLOAT,size:2},{buffer:D,type:t.FLOAT,size:1}]),B=a(t),N=i(t,[{buffer:B,type:t.FLOAT,size:3}]),j=new T(t,p,n,s,l,c,h,f,d,y,g,m,v,x,b,k,_,w,A,I,R,z,O,D,F,B,N);return j.update(e),j}},{"./lib/closest-point":285,"./lib/shaders":286,colormap:128,"gl-buffer":253,"gl-mat4/invert":273,"gl-mat4/multiply":275,"gl-shader":307,"gl-texture2d":322,"gl-vao":327,ndarray:448,normals:451,"simplicial-complex-contour":508,"typedarray-pool":547}],288:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e,[0,0,0,1,1,0,1,1]),s=a(e,i.boxVert,i.lineFrag);return new o(t,r,s)};var n=t("gl-buffer"),a=t("gl-shader"),i=t("./shaders");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawBox=(s=[0,0],l=[0,0],function(t,e,r,n,a){var i=this.plot,o=this.shader,c=i.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,o.uniforms.lo=s,o.uniforms.hi=l,o.uniforms.color=a,c.drawArrays(c.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{"./shaders":291,"gl-buffer":253,"gl-shader":307}],289:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e),i=a(e,o.gridVert,o.gridFrag),l=a(e,o.tickVert,o.gridFrag);return new s(t,r,i,l)};var n=t("gl-buffer"),a=t("gl-shader"),i=t("binary-search-bounds"),o=t("./shaders");function s(t,e,r,n){this.plot=t,this.vbo=e,this.shader=r,this.tickShader=n,this.ticks=[[],[]]}function l(t,e){return t-e}var c,u,h,f,p,d=s.prototype;d.draw=(c=[0,0],u=[0,0],h=[0,0],function(){for(var t=this.plot,e=this.vbo,r=this.shader,n=this.ticks,a=t.gl,i=t._tickBounds,o=t.dataBox,s=t.viewBox,l=t.gridLineWidth,f=t.gridLineColor,p=t.gridLineEnable,d=t.pixelRatio,g=0;g<2;++g){var m=i[g],v=i[g+2]-m,y=.5*(o[g+2]+o[g]),x=o[g+2]-o[g];u[g]=2*v/x,c[g]=2*(m-y)/x}r.bind(),e.bind(),r.attributes.dataCoord.pointer(),r.uniforms.dataShift=c,r.uniforms.dataScale=u;var b=0;for(g=0;g<2;++g){h[0]=h[1]=0,h[g]=1,r.uniforms.dataAxis=h,r.uniforms.lineWidth=l[g]/(s[g+2]-s[g])*d,r.uniforms.color=f[g];var _=6*n[g].length;p[g]&&_&&a.drawArrays(a.TRIANGLES,b,_),b+=_}}),d.drawTickMarks=function(){var t=[0,0],e=[0,0],r=[1,0],n=[0,1],a=[0,0],o=[0,0];return function(){for(var s=this.plot,c=this.vbo,u=this.tickShader,h=this.ticks,f=s.gl,p=s._tickBounds,d=s.dataBox,g=s.viewBox,m=s.pixelRatio,v=s.screenBox,y=v[2]-v[0],x=v[3]-v[1],b=g[2]-g[0],_=g[3]-g[1],w=0;w<2;++w){var T=p[w],k=p[w+2]-T,A=.5*(d[w+2]+d[w]),M=d[w+2]-d[w];e[w]=2*k/M,t[w]=2*(T-A)/M}e[0]*=b/y,t[0]*=b/y,e[1]*=_/x,t[1]*=_/x,u.bind(),c.bind(),u.attributes.dataCoord.pointer();var S=u.uniforms;S.dataShift=t,S.dataScale=e;var E=s.tickMarkLength,C=s.tickMarkWidth,L=s.tickMarkColor,P=6*h[0].length,I=Math.min(i.ge(h[0],(d[0]-p[0])/(p[2]-p[0]),l),h[0].length),z=Math.min(i.gt(h[0],(d[2]-p[0])/(p[2]-p[0]),l),h[0].length),O=0+6*I,D=6*Math.max(0,z-I),R=Math.min(i.ge(h[1],(d[1]-p[1])/(p[3]-p[1]),l),h[1].length),F=Math.min(i.gt(h[1],(d[3]-p[1])/(p[3]-p[1]),l),h[1].length),B=P+6*R,N=6*Math.max(0,F-R);a[0]=2*(g[0]-E[1])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=E[1]*m/y,o[1]=C[1]*m/x,N&&(S.color=L[1],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,N)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[1]-E[0])/x-1,o[0]=C[0]*m/y,o[1]=E[0]*m/x,D&&(S.color=L[0],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,D)),a[0]=2*(g[2]+E[3])/y-1,a[1]=(g[3]+g[1])/x-1,o[0]=E[3]*m/y,o[1]=C[3]*m/x,N&&(S.color=L[3],S.tickScale=o,S.dataAxis=n,S.screenOffset=a,f.drawArrays(f.TRIANGLES,B,N)),a[0]=(g[2]+g[0])/y-1,a[1]=2*(g[3]+E[2])/x-1,o[0]=C[2]*m/y,o[1]=E[2]*m/x,D&&(S.color=L[2],S.tickScale=o,S.dataAxis=r,S.screenOffset=a,f.drawArrays(f.TRIANGLES,O,D))}}(),d.update=(f=[1,1,-1,-1,1,-1],p=[1,-1,1,1,-1,-1],function(t){for(var e=t.ticks,r=t.bounds,n=new Float32Array(18*(e[0].length+e[1].length)),a=(this.plot.zeroLineEnable,0),i=[[],[]],o=0;o<2;++o)for(var s=i[o],l=e[o],c=r[o],u=r[o+2],h=0;h<l.length;++h){var d=(l[h].x-c)/(u-c);s.push(d);for(var g=0;g<6;++g)n[a++]=d,n[a++]=f[g],n[a++]=p[g]}this.ticks=i,this.vbo.update(n)}),d.dispose=function(){this.vbo.dispose(),this.shader.dispose(),this.tickShader.dispose()}},{"./shaders":291,"binary-search-bounds":94,"gl-buffer":253,"gl-shader":307}],290:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e,[-1,-1,-1,1,1,-1,1,1]),s=a(e,i.lineVert,i.lineFrag);return new o(t,r,s)};var n=t("gl-buffer"),a=t("gl-shader"),i=t("./shaders");function o(t,e,r){this.plot=t,this.vbo=e,this.shader=r}var s,l,c=o.prototype;c.bind=function(){var t=this.shader;this.vbo.bind(),this.shader.bind(),t.attributes.coord.pointer(),t.uniforms.screenBox=this.plot.screenBox},c.drawLine=(s=[0,0],l=[0,0],function(t,e,r,n,a,i){var o=this.plot,c=this.shader,u=o.gl;s[0]=t,s[1]=e,l[0]=r,l[1]=n,c.uniforms.start=s,c.uniforms.end=l,c.uniforms.width=a*o.pixelRatio,c.uniforms.color=i,u.drawArrays(u.TRIANGLE_STRIP,0,4)}),c.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{"./shaders":291,"gl-buffer":253,"gl-shader":307}],291:[function(t,e,r){"use strict";var n=t("glslify"),a=n(["precision lowp float;\n#define GLSLIFY 1\nuniform vec4 color;\nvoid main() {\n gl_FragColor = vec4(color.xyz * color.w, color.w);\n}\n"]);e.exports={lineVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 coord;\n\nuniform vec4 screenBox;\nuniform vec2 start, end;\nuniform float width;\n\nvec2 perp(vec2 v) {\n return vec2(v.y, -v.x);\n}\n\nvec2 screen(vec2 v) {\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\n}\n\nvoid main() {\n vec2 delta = normalize(perp(start - end));\n vec2 offset = mix(start, end, 0.5 * (coord.y+1.0));\n gl_Position = vec4(screen(offset + 0.5 * width * delta * coord.x), 0, 1);\n}\n"]),lineFrag:a,textVert:n(["#define GLSLIFY 1\nattribute vec3 textCoordinate;\n\nuniform vec2 dataScale, dataShift, dataAxis, screenOffset, textScale;\nuniform float angle;\n\nvoid main() {\n float dataOffset = textCoordinate.z;\n vec2 glyphOffset = textCoordinate.xy;\n mat2 glyphMatrix = mat2(cos(angle), sin(angle), -sin(angle), cos(angle));\n vec2 screenCoordinate = dataAxis * (dataScale * dataOffset + dataShift) +\n glyphMatrix * glyphOffset * textScale + screenOffset;\n gl_Position = vec4(screenCoordinate, 0, 1);\n}\n"]),textFrag:a,gridVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec3 dataCoord;\n\nuniform vec2 dataAxis, dataShift, dataScale;\nuniform float lineWidth;\n\nvoid main() {\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\n pos += 10.0 * dataCoord.y * vec2(dataAxis.y, -dataAxis.x) + dataCoord.z * lineWidth;\n gl_Position = vec4(pos, 0, 1);\n}\n"]),gridFrag:a,boxVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 coord;\n\nuniform vec4 screenBox;\nuniform vec2 lo, hi;\n\nvec2 screen(vec2 v) {\n return 2.0 * (v - screenBox.xy) / (screenBox.zw - screenBox.xy) - 1.0;\n}\n\nvoid main() {\n gl_Position = vec4(screen(mix(lo, hi, coord)), 0, 1);\n}\n"]),tickVert:n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec3 dataCoord;\n\nuniform vec2 dataAxis, dataShift, dataScale, screenOffset, tickScale;\n\nvoid main() {\n vec2 pos = dataAxis * (dataScale * dataCoord.x + dataShift);\n gl_Position = vec4(pos + tickScale*dataCoord.yz + screenOffset, 0, 1);\n}\n"])}},{glslify:408}],292:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e),i=a(e,s.textVert,s.textFrag);return new l(t,r,i)};var n=t("gl-buffer"),a=t("gl-shader"),i=t("text-cache"),o=t("binary-search-bounds"),s=t("./shaders");function l(t,e,r){this.plot=t,this.vbo=e,this.shader=r,this.tickOffset=[[],[]],this.tickX=[[],[]],this.labelOffset=[0,0],this.labelCount=[0,0]}var c,u,h,f,p,d,g=l.prototype;g.drawTicks=(c=[0,0],u=[0,0],h=[0,0],function(t){var e=this.plot,r=this.shader,n=this.tickX[t],a=this.tickOffset[t],i=e.gl,s=e.viewBox,l=e.dataBox,f=e.screenBox,p=e.pixelRatio,d=e.tickEnable,g=e.tickPad,m=e.tickColor,v=e.tickAngle,y=e.labelEnable,x=e.labelPad,b=e.labelColor,_=e.labelAngle,w=this.labelOffset[t],T=this.labelCount[t],k=o.lt(n,l[t]),A=o.le(n,l[t+2]);c[0]=c[1]=0,c[t]=1,u[t]=(s[2+t]+s[t])/(f[2+t]-f[t])-1;var M=2/f[2+(1^t)]-f[1^t];u[1^t]=M*s[1^t]-1,d[t]&&(u[1^t]-=M*p*g[t],k<A&&a[A]>a[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t],r.uniforms.angle=v[t],i.drawArrays(i.TRIANGLES,a[k],a[A]-a[k]))),y[t]&&T&&(u[1^t]-=M*p*x[t],r.uniforms.dataAxis=h,r.uniforms.screenOffset=u,r.uniforms.color=b[t],r.uniforms.angle=_[t],i.drawArrays(i.TRIANGLES,w,T)),u[1^t]=M*s[2+(1^t)]-1,d[t+2]&&(u[1^t]+=M*p*g[t+2],k<A&&a[A]>a[k]&&(r.uniforms.dataAxis=c,r.uniforms.screenOffset=u,r.uniforms.color=m[t+2],r.uniforms.angle=v[t+2],i.drawArrays(i.TRIANGLES,a[k],a[A]-a[k]))),y[t+2]&&T&&(u[1^t]+=M*p*x[t+2],r.uniforms.dataAxis=h,r.uniforms.screenOffset=u,r.uniforms.color=b[t+2],r.uniforms.angle=_[t+2],i.drawArrays(i.TRIANGLES,w,T))}),g.drawTitle=function(){var t=[0,0],e=[0,0];return function(){var r=this.plot,n=this.shader,a=r.gl,i=r.screenBox,o=r.titleCenter,s=r.titleAngle,l=r.titleColor,c=r.pixelRatio;if(this.titleCount){for(var u=0;u<2;++u)e[u]=2*(o[u]*c-i[u])/(i[2+u]-i[u])-1;n.bind(),n.uniforms.dataAxis=t,n.uniforms.screenOffset=e,n.uniforms.angle=s,n.uniforms.color=l,a.drawArrays(a.TRIANGLES,this.titleOffset,this.titleCount)}}}(),g.bind=(f=[0,0],p=[0,0],d=[0,0],function(){var t=this.plot,e=this.shader,r=t._tickBounds,n=t.dataBox,a=t.screenBox,i=t.viewBox;e.bind();for(var o=0;o<2;++o){var s=r[o],l=r[o+2]-s,c=.5*(n[o+2]+n[o]),u=n[o+2]-n[o],h=i[o],g=i[o+2]-h,m=a[o],v=a[o+2]-m;p[o]=2*l/u*g/v,f[o]=2*(s-c)/u*g/v}d[1]=2*t.pixelRatio/(a[3]-a[1]),d[0]=d[1]*(a[3]-a[1])/(a[2]-a[0]),e.uniforms.dataScale=p,e.uniforms.dataShift=f,e.uniforms.textScale=d,this.vbo.bind(),e.attributes.textCoordinate.pointer()}),g.update=function(t){var e,r,n,a,o,s=[],l=t.ticks,c=t.bounds;for(o=0;o<2;++o){var u=[Math.floor(s.length/3)],h=[-1/0],f=l[o];for(e=0;e<f.length;++e){var p=f[e],d=p.x,g=p.text,m=p.font||"sans-serif";a=p.fontSize||12;for(var v=1/(c[o+2]-c[o]),y=c[o],x=g.split("\n"),b=0;b<x.length;b++)for(n=i(m,x[b]).data,r=0;r<n.length;r+=2)s.push(n[r]*a,-n[r+1]*a-b*a*1.2,(d-y)*v);u.push(Math.floor(s.length/3)),h.push(d)}this.tickOffset[o]=u,this.tickX[o]=h}for(o=0;o<2;++o){for(this.labelOffset[o]=Math.floor(s.length/3),n=i(t.labelFont[o],t.labels[o],{textAlign:"center"}).data,a=t.labelSize[o],e=0;e<n.length;e+=2)s.push(n[e]*a,-n[e+1]*a,0);this.labelCount[o]=Math.floor(s.length/3)-this.labelOffset[o]}for(this.titleOffset=Math.floor(s.length/3),n=i(t.titleFont,t.title).data,a=t.titleSize,e=0;e<n.length;e+=2)s.push(n[e]*a,-n[e+1]*a,0);this.titleCount=Math.floor(s.length/3)-this.titleOffset,this.vbo.update(s)},g.dispose=function(){this.vbo.dispose(),this.shader.dispose()}},{"./shaders":291,"binary-search-bounds":94,"gl-buffer":253,"gl-shader":307,"text-cache":527}],293:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=n(e,[e.drawingBufferWidth,e.drawingBufferHeight]),c=new l(e,r);return c.grid=a(c),c.text=i(c),c.line=o(c),c.box=s(c),c.update(t),c};var n=t("gl-select-static"),a=t("./lib/grid"),i=t("./lib/text"),o=t("./lib/line"),s=t("./lib/box");function l(t,e){this.gl=t,this.pickBuffer=e,this.screenBox=[0,0,t.drawingBufferWidth,t.drawingBufferHeight],this.viewBox=[0,0,0,0],this.dataBox=[-10,-10,10,10],this.gridLineEnable=[!0,!0],this.gridLineWidth=[1,1],this.gridLineColor=[[0,0,0,1],[0,0,0,1]],this.pixelRatio=1,this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickEnable=[!0,!0,!0,!0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[15,15,15,15],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelEnable=[!0,!0,!0,!0],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.titleCenter=[0,0],this.titleEnable=!0,this.titleAngle=0,this.titleColor=[0,0,0,1],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[4,4],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderLineEnable=[!0,!0,!0,!0],this.borderLineWidth=[2,2,2,2],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.grid=null,this.text=null,this.line=null,this.box=null,this.objects=[],this.overlays=[],this._tickBounds=[1/0,1/0,-1/0,-1/0],this.static=!1,this.dirty=!1,this.pickDirty=!1,this.pickDelay=120,this.pickRadius=10,this._pickTimeout=null,this._drawPick=this.drawPick.bind(this),this._depthCounter=0}var c=l.prototype;function u(t){for(var e=t.slice(),r=0;r<e.length;++r)e[r]=e[r].slice();return e}function h(t,e){return t.x-e.x}c.setDirty=function(){this.dirty=this.pickDirty=!0},c.setOverlayDirty=function(){this.dirty=!0},c.nextDepthValue=function(){return this._depthCounter++/65536},c.draw=function(){var t=this.gl,e=this.screenBox,r=this.viewBox,n=this.dataBox,a=this.pixelRatio,i=this.grid,o=this.line,s=this.text,l=this.objects;if(this._depthCounter=0,this.pickDirty&&(this._pickTimeout&&clearTimeout(this._pickTimeout),this.pickDirty=!1,this._pickTimeout=setTimeout(this._drawPick,this.pickDelay)),this.dirty){if(this.dirty=!1,t.bindFramebuffer(t.FRAMEBUFFER,null),t.enable(t.SCISSOR_TEST),t.disable(t.DEPTH_TEST),t.depthFunc(t.LESS),t.depthMask(!1),t.enable(t.BLEND),t.blendEquation(t.FUNC_ADD,t.FUNC_ADD),t.blendFunc(t.ONE,t.ONE_MINUS_SRC_ALPHA),this.borderColor){t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]);var c=this.borderColor;t.clearColor(c[0]*c[3],c[1]*c[3],c[2]*c[3],c[3]),t.clear(t.COLOR_BUFFER_BIT|t.DEPTH_BUFFER_BIT)}t.scissor(r[0],r[1],r[2]-r[0],r[3]-r[1]),t.viewport(r[0],r[1],r[2]-r[0],r[3]-r[1]);var u=this.backgroundColor;t.clearColor(u[0]*u[3],u[1]*u[3],u[2]*u[3],u[3]),t.clear(t.COLOR_BUFFER_BIT),i.draw();var h=this.zeroLineEnable,f=this.zeroLineColor,p=this.zeroLineWidth;if(h[0]||h[1]){o.bind();for(var d=0;d<2;++d)if(h[d]&&n[d]<=0&&n[d+2]>=0){var g=e[d]-n[d]*(e[d+2]-e[d])/(n[d+2]-n[d]);0===d?o.drawLine(g,e[1],g,e[3],p[d],f[d]):o.drawLine(e[0],g,e[2],g,p[d],f[d])}}for(d=0;d<l.length;++d)l[d].draw();t.viewport(e[0],e[1],e[2]-e[0],e[3]-e[1]),t.scissor(e[0],e[1],e[2]-e[0],e[3]-e[1]),this.grid.drawTickMarks(),o.bind();var m=this.borderLineEnable,v=this.borderLineWidth,y=this.borderLineColor;for(m[1]&&o.drawLine(r[0],r[1]-.5*v[1]*a,r[0],r[3]+.5*v[3]*a,v[1],y[1]),m[0]&&o.drawLine(r[0]-.5*v[0]*a,r[1],r[2]+.5*v[2]*a,r[1],v[0],y[0]),m[3]&&o.drawLine(r[2],r[1]-.5*v[1]*a,r[2],r[3]+.5*v[3]*a,v[3],y[3]),m[2]&&o.drawLine(r[0]-.5*v[0]*a,r[3],r[2]+.5*v[2]*a,r[3],v[2],y[2]),s.bind(),d=0;d<2;++d)s.drawTicks(d);this.titleEnable&&s.drawTitle();var x=this.overlays;for(d=0;d<x.length;++d)x[d].draw();t.disable(t.SCISSOR_TEST),t.disable(t.BLEND),t.depthMask(!0)}},c.drawPick=function(){if(!this.static){var t=this.pickBuffer;this.gl,this._pickTimeout=null,t.begin();for(var e=1,r=this.objects,n=0;n<r.length;++n)e=r[n].drawPick(e);t.end()}},c.pick=function(t,e){if(!this.static){var r=this.pixelRatio,n=this.pickPixelRatio,a=this.viewBox,i=0|Math.round((t-a[0]/r)*n),o=0|Math.round((e-a[1]/r)*n),s=this.pickBuffer.query(i,o,this.pickRadius);if(!s)return null;for(var l=s.id+(s.value[0]<<8)+(s.value[1]<<16)+(s.value[2]<<24),c=this.objects,u=0;u<c.length;++u){var h=c[u].pick(i,o,l);if(h)return h}return null}},c.setScreenBox=function(t){var e=this.screenBox,r=this.pixelRatio;e[0]=0|Math.round(t[0]*r),e[1]=0|Math.round(t[1]*r),e[2]=0|Math.round(t[2]*r),e[3]=0|Math.round(t[3]*r),this.setDirty()},c.setDataBox=function(t){var e=this.dataBox;(e[0]!==t[0]||e[1]!==t[1]||e[2]!==t[2]||e[3]!==t[3])&&(e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],this.setDirty())},c.setViewBox=function(t){var e=this.pixelRatio,r=this.viewBox;r[0]=0|Math.round(t[0]*e),r[1]=0|Math.round(t[1]*e),r[2]=0|Math.round(t[2]*e),r[3]=0|Math.round(t[3]*e);var n=this.pickPixelRatio;this.pickBuffer.shape=[0|Math.round((t[2]-t[0])*n),0|Math.round((t[3]-t[1])*n)],this.setDirty()},c.update=function(t){t=t||{};var e=this.gl;this.pixelRatio=t.pixelRatio||1;var r=this.pixelRatio;this.pickPixelRatio=Math.max(r,1),this.setScreenBox(t.screenBox||[0,0,e.drawingBufferWidth/r,e.drawingBufferHeight/r]);this.screenBox;this.setViewBox(t.viewBox||[.125*(this.screenBox[2]-this.screenBox[0])/r,.125*(this.screenBox[3]-this.screenBox[1])/r,.875*(this.screenBox[2]-this.screenBox[0])/r,.875*(this.screenBox[3]-this.screenBox[1])/r]);var n=this.viewBox,a=(n[2]-n[0])/(n[3]-n[1]);this.setDataBox(t.dataBox||[-10,-10/a,10,10/a]),this.borderColor=!1!==t.borderColor&&(t.borderColor||[0,0,0,0]).slice(),this.backgroundColor=(t.backgroundColor||[0,0,0,0]).slice(),this.gridLineEnable=(t.gridLineEnable||[!0,!0]).slice(),this.gridLineWidth=(t.gridLineWidth||[1,1]).slice(),this.gridLineColor=u(t.gridLineColor||[[.5,.5,.5,1],[.5,.5,.5,1]]),this.zeroLineEnable=(t.zeroLineEnable||[!0,!0]).slice(),this.zeroLineWidth=(t.zeroLineWidth||[4,4]).slice(),this.zeroLineColor=u(t.zeroLineColor||[[0,0,0,1],[0,0,0,1]]),this.tickMarkLength=(t.tickMarkLength||[0,0,0,0]).slice(),this.tickMarkWidth=(t.tickMarkWidth||[0,0,0,0]).slice(),this.tickMarkColor=u(t.tickMarkColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.titleCenter=(t.titleCenter||[.5*(n[0]+n[2])/r,(n[3]+120)/r]).slice(),this.titleEnable=!("titleEnable"in t)||!!t.titleEnable,this.titleAngle=t.titleAngle||0,this.titleColor=(t.titleColor||[0,0,0,1]).slice(),this.labelPad=(t.labelPad||[15,15,15,15]).slice(),this.labelAngle=(t.labelAngle||[0,Math.PI/2,0,3*Math.PI/2]).slice(),this.labelEnable=(t.labelEnable||[!0,!0,!0,!0]).slice(),this.labelColor=u(t.labelColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.tickPad=(t.tickPad||[15,15,15,15]).slice(),this.tickAngle=(t.tickAngle||[0,0,0,0]).slice(),this.tickEnable=(t.tickEnable||[!0,!0,!0,!0]).slice(),this.tickColor=u(t.tickColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]),this.borderLineEnable=(t.borderLineEnable||[!0,!0,!0,!0]).slice(),this.borderLineWidth=(t.borderLineWidth||[2,2,2,2]).slice(),this.borderLineColor=u(t.borderLineColor||[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]]);var i=t.ticks||[[],[]],o=this._tickBounds;o[0]=o[1]=1/0,o[2]=o[3]=-1/0;for(var s=0;s<2;++s){var l=i[s].slice(0);0!==l.length&&(l.sort(h),o[s]=Math.min(o[s],l[0].x),o[s+2]=Math.max(o[s+2],l[l.length-1].x))}this.grid.update({bounds:o,ticks:i}),this.text.update({bounds:o,ticks:i,labels:t.labels||["x","y"],labelSize:t.labelSize||[12,12],labelFont:t.labelFont||["sans-serif","sans-serif"],title:t.title||"",titleSize:t.titleSize||18,titleFont:t.titleFont||"sans-serif"}),this.static=!!t.static,this.setDirty()},c.dispose=function(){this.box.dispose(),this.grid.dispose(),this.text.dispose(),this.line.dispose();for(var t=this.objects.length-1;t>=0;--t)this.objects[t].dispose();this.objects.length=0;for(t=this.overlays.length-1;t>=0;--t)this.overlays[t].dispose();this.overlays.length=0,this.gl=null},c.addObject=function(t){this.objects.indexOf(t)<0&&(this.objects.push(t),this.setDirty())},c.removeObject=function(t){for(var e=this.objects,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setDirty();break}},c.addOverlay=function(t){this.overlays.indexOf(t)<0&&(this.overlays.push(t),this.setOverlayDirty())},c.removeOverlay=function(t){for(var e=this.overlays,r=0;r<e.length;++r)if(e[r]===t){e.splice(r,1),this.setOverlayDirty();break}}},{"./lib/box":288,"./lib/grid":289,"./lib/line":290,"./lib/text":292,"gl-select-static":306}],294:[function(t,e,r){"use strict";e.exports=function(t,e){t=t||document.body,e=e||{};var r=[.01,1/0];"distanceLimits"in e&&(r[0]=e.distanceLimits[0],r[1]=e.distanceLimits[1]);"zoomMin"in e&&(r[0]=e.zoomMin);"zoomMax"in e&&(r[1]=e.zoomMax);var c=a({center:e.center||[0,0,0],up:e.up||[0,1,0],eye:e.eye||[0,0,10],mode:e.mode||"orbit",distanceLimits:r}),u=[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0],h=0,f=t.clientWidth,p=t.clientHeight,d={keyBindingMode:"rotate",enableWheel:!0,view:c,element:t,delay:e.delay||16,rotateSpeed:e.rotateSpeed||1,zoomSpeed:e.zoomSpeed||1,translateSpeed:e.translateSpeed||1,flipX:!!e.flipX,flipY:!!e.flipY,modes:c.modes,_ortho:e._ortho||e.projection&&"orthographic"===e.projection.type||!1,tick:function(){var e=n(),r=this.delay,a=e-2*r;c.idle(e-r),c.recalcMatrix(a),c.flush(e-(100+2*r));for(var i=!0,o=c.computedMatrix,s=0;s<16;++s)i=i&&u[s]===o[s],u[s]=o[s];var l=t.clientWidth===f&&t.clientHeight===p;return f=t.clientWidth,p=t.clientHeight,i?!l:(h=Math.exp(c.computedRadius[0]),!0)},lookAt:function(t,e,r){c.lookAt(c.lastT(),t,e,r)},rotate:function(t,e,r){c.rotate(c.lastT(),t,e,r)},pan:function(t,e,r){c.pan(c.lastT(),t,e,r)},translate:function(t,e,r){c.translate(c.lastT(),t,e,r)}};return Object.defineProperties(d,{matrix:{get:function(){return c.computedMatrix},set:function(t){return c.setMatrix(c.lastT(),t),c.computedMatrix},enumerable:!0},mode:{get:function(){return c.getMode()},set:function(t){var e=c.computedUp.slice(),r=c.computedEye.slice(),a=c.computedCenter.slice();if(c.setMode(t),"turntable"===t){var i=n();c._active.lookAt(i,r,a,e),c._active.lookAt(i+500,r,a,[0,0,1]),c._active.flush(i)}return c.getMode()},enumerable:!0},center:{get:function(){return c.computedCenter},set:function(t){return c.lookAt(c.lastT(),null,t),c.computedCenter},enumerable:!0},eye:{get:function(){return c.computedEye},set:function(t){return c.lookAt(c.lastT(),t),c.computedEye},enumerable:!0},up:{get:function(){return c.computedUp},set:function(t){return c.lookAt(c.lastT(),null,null,t),c.computedUp},enumerable:!0},distance:{get:function(){return h},set:function(t){return c.setDistance(c.lastT(),t),t},enumerable:!0},distanceLimits:{get:function(){return c.getDistanceLimits(r)},set:function(t){return c.setDistanceLimits(t),t},enumerable:!0}}),t.addEventListener("contextmenu",(function(t){return t.preventDefault(),!1})),d._lastX=-1,d._lastY=-1,d._lastMods={shift:!1,control:!1,alt:!1,meta:!1},d.enableMouseListeners=function(){function e(e,r,a,i){var o=d.keyBindingMode;if(!1!==o){var s="rotate"===o,l="pan"===o,u="zoom"===o,f=!!i.control,p=!!i.alt,g=!!i.shift,m=!!(1&e),v=!!(2&e),y=!!(4&e),x=1/t.clientHeight,b=x*(r-d._lastX),_=x*(a-d._lastY),w=d.flipX?1:-1,T=d.flipY?1:-1,k=Math.PI*d.rotateSpeed,A=n();if(-1!==d._lastX&&-1!==d._lastY&&((s&&m&&!f&&!p&&!g||m&&!f&&!p&&g)&&c.rotate(A,w*k*b,-T*k*_,0),(l&&m&&!f&&!p&&!g||v||m&&f&&!p&&!g)&&c.pan(A,-d.translateSpeed*b*h,d.translateSpeed*_*h,0),u&&m&&!f&&!p&&!g||y||m&&!f&&p&&!g)){var M=-d.zoomSpeed*_/window.innerHeight*(A-c.lastT())*100;c.pan(A,0,0,h*(Math.exp(M)-1))}return d._lastX=r,d._lastY=a,d._lastMods=i,!0}}d.mouseListener=i(t,e),t.addEventListener("touchstart",(function(r){var n=s(r.changedTouches[0],t);e(0,n[0],n[1],d._lastMods),e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener("touchmove",(function(r){var n=s(r.changedTouches[0],t);e(1,n[0],n[1],d._lastMods),r.preventDefault()}),!!l&&{passive:!1}),t.addEventListener("touchend",(function(t){e(0,d._lastX,d._lastY,d._lastMods),t.preventDefault()}),!!l&&{passive:!1}),d.wheelListener=o(t,(function(t,e){if(!1!==d.keyBindingMode&&d.enableWheel){var r=d.flipX?1:-1,a=d.flipY?1:-1,i=n();if(Math.abs(t)>Math.abs(e))c.rotate(i,0,0,-t*r*Math.PI*d.rotateSpeed/window.innerWidth);else if(!d._ortho){var o=-d.zoomSpeed*a*e/window.innerHeight*(i-c.lastT())/20;c.pan(i,0,0,h*(Math.exp(o)-1))}}}),!0)},d.enableMouseListeners(),d};var n=t("right-now"),a=t("3d-view"),i=t("mouse-change"),o=t("mouse-wheel"),s=t("mouse-event-offset"),l=t("has-passive-events")},{"3d-view":54,"has-passive-events":410,"mouse-change":436,"mouse-event-offset":437,"mouse-wheel":439,"right-now":494}],295:[function(t,e,r){var n=t("glslify"),a=t("gl-shader"),i=n(["precision mediump float;\n#define GLSLIFY 1\nattribute vec2 position;\nvarying vec2 uv;\nvoid main() {\n uv = position;\n gl_Position = vec4(position, 0, 1);\n}"]),o=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform sampler2D accumBuffer;\nvarying vec2 uv;\n\nvoid main() {\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\n gl_FragColor = min(vec4(1,1,1,1), accum);\n}"]);e.exports=function(t){return a(t,i,o,null,[{name:"position",type:"vec2"}])}},{"gl-shader":307,glslify:408}],296:[function(t,e,r){"use strict";var n=t("./camera.js"),a=t("gl-axes3d"),i=t("gl-axes3d/properties"),o=t("gl-spikes3d"),s=t("gl-select-static"),l=t("gl-fbo"),c=t("a-big-triangle"),u=t("mouse-change"),h=t("gl-mat4/perspective"),f=t("gl-mat4/ortho"),p=t("./lib/shader"),d=t("is-mobile")({tablet:!0,featureDetect:!0});function g(){this.mouse=[-1,-1],this.screen=null,this.distance=1/0,this.index=null,this.dataCoordinate=null,this.dataPosition=null,this.object=null,this.data=null}function m(t){var e=Math.round(Math.log(Math.abs(t))/Math.log(10));if(e<0){var r=Math.round(Math.pow(10,-e));return Math.ceil(t*r)/r}if(e>0){r=Math.round(Math.pow(10,e));return Math.ceil(t/r)*r}return Math.ceil(t)}function v(t){return"boolean"!=typeof t||t}e.exports={createScene:function(t){(t=t||{}).camera=t.camera||{};var e=t.canvas;if(!e){if(e=document.createElement("canvas"),t.container)t.container.appendChild(e);else document.body.appendChild(e)}var r=t.gl;r||(t.glOptions&&(d=!!t.glOptions.preserveDrawingBuffer),r=function(t,e){var r=null;try{(r=t.getContext("webgl",e))||(r=t.getContext("experimental-webgl",e))}catch(t){return null}return r}(e,t.glOptions||{premultipliedAlpha:!0,antialias:!0,preserveDrawingBuffer:d}));if(!r)throw new Error("webgl not supported");var y=t.bounds||[[-10,-10,-10],[10,10,10]],x=new g,b=l(r,r.drawingBufferWidth,r.drawingBufferHeight,{preferFloat:!d}),_=p(r),w=t.cameraObject&&!0===t.cameraObject._ortho||t.camera.projection&&"orthographic"===t.camera.projection.type||!1,T={eye:t.camera.eye||[2,0,0],center:t.camera.center||[0,0,0],up:t.camera.up||[0,1,0],zoomMin:t.camera.zoomMax||.1,zoomMax:t.camera.zoomMin||100,mode:t.camera.mode||"turntable",_ortho:w},k=t.axes||{},A=a(r,k);A.enable=!k.disable;var M=t.spikes||{},S=o(r,M),E=[],C=[],L=[],P=[],I=!0,z=!0,O=new Array(16),D=new Array(16),R={view:null,projection:O,model:D,_ortho:!1},F=(z=!0,[r.drawingBufferWidth,r.drawingBufferHeight]),B=t.cameraObject||n(e,T),N={gl:r,contextLost:!1,pixelRatio:t.pixelRatio||1,canvas:e,selection:x,camera:B,axes:A,axesPixels:null,spikes:S,bounds:y,objects:E,shape:F,aspect:t.aspectRatio||[1,1,1],pickRadius:t.pickRadius||10,zNear:t.zNear||.01,zFar:t.zFar||1e3,fovy:t.fovy||Math.PI/4,clearColor:t.clearColor||[0,0,0,0],autoResize:v(t.autoResize),autoBounds:v(t.autoBounds),autoScale:!!t.autoScale,autoCenter:v(t.autoCenter),clipToBounds:v(t.clipToBounds),snapToData:!!t.snapToData,onselect:t.onselect||null,onrender:t.onrender||null,onclick:t.onclick||null,cameraParams:R,oncontextloss:null,mouseListener:null,_stopped:!1,getAspectratio:function(){return{x:this.aspect[0],y:this.aspect[1],z:this.aspect[2]}},setAspectratio:function(t){this.aspect[0]=t.x,this.aspect[1]=t.y,this.aspect[2]=t.z,z=!0},setBounds:function(t,e){this.bounds[0][t]=e.min,this.bounds[1][t]=e.max},setClearColor:function(t){this.clearColor=t},clearRGBA:function(){this.gl.clearColor(this.clearColor[0],this.clearColor[1],this.clearColor[2],this.clearColor[3]),this.gl.clear(this.gl.COLOR_BUFFER_BIT|this.gl.DEPTH_BUFFER_BIT)}},j=[r.drawingBufferWidth/N.pixelRatio|0,r.drawingBufferHeight/N.pixelRatio|0];function V(){if(!N._stopped&&N.autoResize){var t=e.parentNode,r=1,n=1;t&&t!==document.body?(r=t.clientWidth,n=t.clientHeight):(r=window.innerWidth,n=window.innerHeight);var a=0|Math.ceil(r*N.pixelRatio),i=0|Math.ceil(n*N.pixelRatio);if(a!==e.width||i!==e.height){e.width=a,e.height=i;var o=e.style;o.position=o.position||"absolute",o.left="0px",o.top="0px",o.width=r+"px",o.height=n+"px",I=!0}}}N.autoResize&&V();function U(){for(var t=E.length,e=P.length,n=0;n<e;++n)L[n]=0;t:for(n=0;n<t;++n){var a=E[n],i=a.pickSlots;if(i){for(var o=0;o<e;++o)if(L[o]+i<255){C[n]=o,a.setPickBase(L[o]+1),L[o]+=i;continue t}var l=s(r,F);C[n]=e,P.push(l),L.push(i),a.setPickBase(1),e+=1}else C[n]=-1}for(;e>0&&0===L[e-1];)L.pop(),P.pop().dispose()}function q(){if(N.contextLost)return!0;r.isContextLost()&&(N.contextLost=!0,N.mouseListener.enabled=!1,N.selection.object=null,N.oncontextloss&&N.oncontextloss())}window.addEventListener("resize",V),N.update=function(t){N._stopped||(t=t||{},I=!0,z=!0)},N.add=function(t){N._stopped||(t.axes=A,E.push(t),C.push(-1),I=!0,z=!0,U())},N.remove=function(t){if(!N._stopped){var e=E.indexOf(t);e<0||(E.splice(e,1),C.pop(),I=!0,z=!0,U())}},N.dispose=function(){if(!N._stopped&&(N._stopped=!0,window.removeEventListener("resize",V),e.removeEventListener("webglcontextlost",q),N.mouseListener.enabled=!1,!N.contextLost)){A.dispose(),S.dispose();for(var t=0;t<E.length;++t)E[t].dispose();b.dispose();for(t=0;t<P.length;++t)P[t].dispose();_.dispose(),r=null,A=null,S=null,E=[]}},N._mouseRotating=!1,N._prevButtons=0,N.enableMouseListeners=function(){N.mouseListener=u(e,(function(t,e,r){if(!N._stopped){var n=P.length,a=E.length,i=x.object;x.distance=1/0,x.mouse[0]=e,x.mouse[1]=r,x.object=null,x.screen=null,x.dataCoordinate=x.dataPosition=null;var o=!1;if(t&&N._prevButtons)N._mouseRotating=!0;else{N._mouseRotating&&(z=!0),N._mouseRotating=!1;for(var s=0;s<n;++s){var l=P[s].query(e,j[1]-r-1,N.pickRadius);if(l){if(l.distance>x.distance)continue;for(var c=0;c<a;++c){var u=E[c];if(C[c]===s){var h=u.pick(l);h&&(x.buttons=t,x.screen=l.coord,x.distance=l.distance,x.object=u,x.index=h.distance,x.dataPosition=h.position,x.dataCoordinate=h.dataCoordinate,x.data=h,o=!0)}}}}}i&&i!==x.object&&(i.highlight&&i.highlight(null),I=!0),x.object&&(x.object.highlight&&x.object.highlight(x.data),I=!0),(o=o||x.object!==i)&&N.onselect&&N.onselect(x),1&t&&!(1&N._prevButtons)&&N.onclick&&N.onclick(x),N._prevButtons=t}}))},e.addEventListener("webglcontextlost",q);var H=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],G=[H[0].slice(),H[1].slice()];function Y(){if(!q()){V();var t=N.camera.tick();R.view=N.camera.matrix,I=I||t,z=z||t,A.pixelRatio=N.pixelRatio,S.pixelRatio=N.pixelRatio;var e=E.length,n=H[0],a=H[1];n[0]=n[1]=n[2]=1/0,a[0]=a[1]=a[2]=-1/0;for(var o=0;o<e;++o){(L=E[o]).pixelRatio=N.pixelRatio,L.axes=N.axes,I=I||!!L.dirty,z=z||!!L.dirty;var s=L.bounds;if(s)for(var l=s[0],u=s[1],p=0;p<3;++p)n[p]=Math.min(n[p],l[p]),a[p]=Math.max(a[p],u[p])}var d=N.bounds;if(N.autoBounds)for(p=0;p<3;++p){if(a[p]<n[p])n[p]=-1,a[p]=1;else{n[p]===a[p]&&(n[p]-=1,a[p]+=1);var g=.05*(a[p]-n[p]);n[p]=n[p]-g,a[p]=a[p]+g}d[0][p]=n[p],d[1][p]=a[p]}var v=!1;for(p=0;p<3;++p)v=v||G[0][p]!==d[0][p]||G[1][p]!==d[1][p],G[0][p]=d[0][p],G[1][p]=d[1][p];if(z=z||v,I=I||v){if(v){var y=[0,0,0];for(o=0;o<3;++o)y[o]=m((d[1][o]-d[0][o])/10);A.autoTicks?A.update({bounds:d,tickSpacing:y}):A.update({bounds:d})}var T=r.drawingBufferWidth,k=r.drawingBufferHeight;F[0]=T,F[1]=k,j[0]=0|Math.max(T/N.pixelRatio,1),j[1]=0|Math.max(k/N.pixelRatio,1),function(t,e){var r=t.bounds,n=t.cameraParams,a=n.projection,i=n.model,o=t.gl.drawingBufferWidth,s=t.gl.drawingBufferHeight,l=t.zNear,c=t.zFar,u=t.fovy,p=o/s;e?(f(a,-p,p,-1,1,l,c),n._ortho=!0):(h(a,u,p,l,c),n._ortho=!1);for(var d=0;d<16;++d)i[d]=0;i[15]=1;var g=0;for(d=0;d<3;++d)g=Math.max(g,r[1][d]-r[0][d]);for(d=0;d<3;++d)t.autoScale?i[5*d]=t.aspect[d]/(r[1][d]-r[0][d]):i[5*d]=1/g,t.autoCenter&&(i[12+d]=.5*-i[5*d]*(r[0][d]+r[1][d]))}(N,w);for(o=0;o<e;++o){(L=E[o]).axesBounds=d,N.clipToBounds&&(L.clipBounds=d)}x.object&&(N.snapToData?S.position=x.dataCoordinate:S.position=x.dataPosition,S.bounds=d),z&&(z=!1,function(){if(!q()){r.colorMask(!0,!0,!0,!0),r.depthMask(!0),r.disable(r.BLEND),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL);for(var t=E.length,e=P.length,n=0;n<e;++n){var a=P[n];a.shape=j,a.begin();for(var i=0;i<t;++i)if(C[i]===n){var o=E[i];o.drawPick&&(o.pixelRatio=1,o.drawPick(R))}a.end()}}}()),N.axesPixels=i(N.axes,R,T,k),N.onrender&&N.onrender(),r.bindFramebuffer(r.FRAMEBUFFER,null),r.viewport(0,0,T,k),N.clearRGBA(),r.depthMask(!0),r.colorMask(!0,!0,!0,!0),r.enable(r.DEPTH_TEST),r.depthFunc(r.LEQUAL),r.disable(r.BLEND),r.disable(r.CULL_FACE);var M=!1;A.enable&&(M=M||A.isTransparent(),A.draw(R)),S.axes=A,x.object&&S.draw(R),r.disable(r.CULL_FACE);for(o=0;o<e;++o){(L=E[o]).axes=A,L.pixelRatio=N.pixelRatio,L.isOpaque&&L.isOpaque()&&L.draw(R),L.isTransparent&&L.isTransparent()&&(M=!0)}if(M){b.shape=F,b.bind(),r.clear(r.DEPTH_BUFFER_BIT),r.colorMask(!1,!1,!1,!1),r.depthMask(!0),r.depthFunc(r.LESS),A.enable&&A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){(L=E[o]).isOpaque&&L.isOpaque()&&L.draw(R)}r.enable(r.BLEND),r.blendEquation(r.FUNC_ADD),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.colorMask(!0,!0,!0,!0),r.depthMask(!1),r.clearColor(0,0,0,0),r.clear(r.COLOR_BUFFER_BIT),A.isTransparent()&&A.drawTransparent(R);for(o=0;o<e;++o){var L;(L=E[o]).isTransparent&&L.isTransparent()&&L.drawTransparent(R)}r.bindFramebuffer(r.FRAMEBUFFER,null),r.blendFunc(r.ONE,r.ONE_MINUS_SRC_ALPHA),r.disable(r.DEPTH_TEST),_.bind(),b.color[0].bind(0),_.uniforms.accumBuffer=0,c(r),r.disable(r.BLEND)}I=!1;for(o=0;o<e;++o)E[o].dirty=!1}}}return N.enableMouseListeners(),function t(){if(N._stopped||N.contextLost)return;Y(),requestAnimationFrame(t)}(),N.redraw=function(){N._stopped||(I=!0,Y())},N},createCamera:n}},{"./camera.js":294,"./lib/shader":295,"a-big-triangle":62,"gl-axes3d":245,"gl-axes3d/properties":252,"gl-fbo":261,"gl-mat4/ortho":276,"gl-mat4/perspective":277,"gl-select-static":306,"gl-spikes3d":316,"is-mobile":420,"mouse-change":436}],297:[function(t,e,r){var n=t("glslify");r.pointVertex=n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\n\nuniform mat3 matrix;\nuniform float pointSize;\nuniform float pointCloud;\n\nhighp float rand(vec2 co) {\n highp float a = 12.9898;\n highp float b = 78.233;\n highp float c = 43758.5453;\n highp float d = dot(co.xy, vec2(a, b));\n highp float e = mod(d, 3.14);\n return fract(sin(e) * c);\n}\n\nvoid main() {\n vec3 hgPosition = matrix * vec3(position, 1);\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\n // if we don't jitter the point size a bit, overall point cloud\n // saturation 'jumps' on zooming, which is disturbing and confusing\n gl_PointSize = pointSize * ((19.5 + rand(position)) / 20.0);\n if(pointCloud != 0.0) { // pointCloud is truthy\n // get the same square surface as circle would be\n gl_PointSize *= 0.886;\n }\n}"]),r.pointFragment=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform vec4 color, borderColor;\nuniform float centerFraction;\nuniform float pointCloud;\n\nvoid main() {\n float radius;\n vec4 baseColor;\n if(pointCloud != 0.0) { // pointCloud is truthy\n if(centerFraction == 1.0) {\n gl_FragColor = color;\n } else {\n gl_FragColor = mix(borderColor, color, centerFraction);\n }\n } else {\n radius = length(2.0 * gl_PointCoord.xy - 1.0);\n if(radius > 1.0) {\n discard;\n }\n baseColor = mix(borderColor, color, step(radius, centerFraction));\n gl_FragColor = vec4(baseColor.rgb * baseColor.a, baseColor.a);\n }\n}\n"]),r.pickVertex=n(["precision mediump float;\n#define GLSLIFY 1\n\nattribute vec2 position;\nattribute vec4 pickId;\n\nuniform mat3 matrix;\nuniform float pointSize;\nuniform vec4 pickOffset;\n\nvarying vec4 fragId;\n\nvoid main() {\n vec3 hgPosition = matrix * vec3(position, 1);\n gl_Position = vec4(hgPosition.xy, 0, hgPosition.z);\n gl_PointSize = pointSize;\n\n vec4 id = pickId + pickOffset;\n id.y += floor(id.x / 256.0);\n id.x -= floor(id.x / 256.0) * 256.0;\n\n id.z += floor(id.y / 256.0);\n id.y -= floor(id.y / 256.0) * 256.0;\n\n id.w += floor(id.z / 256.0);\n id.z -= floor(id.z / 256.0) * 256.0;\n\n fragId = id;\n}\n"]),r.pickFragment=n(["precision mediump float;\n#define GLSLIFY 1\n\nvarying vec4 fragId;\n\nvoid main() {\n float radius = length(2.0 * gl_PointCoord.xy - 1.0);\n if(radius > 1.0) {\n discard;\n }\n gl_FragColor = fragId / 255.0;\n}\n"])},{glslify:408}],298:[function(t,e,r){"use strict";var n=t("gl-shader"),a=t("gl-buffer"),i=t("typedarray-pool"),o=t("./lib/shader");function s(t,e,r,n,a){this.plot=t,this.offsetBuffer=e,this.pickBuffer=r,this.shader=n,this.pickShader=a,this.sizeMin=.5,this.sizeMinCap=2,this.sizeMax=20,this.areaRatio=1,this.pointCount=0,this.color=[1,0,0,1],this.borderColor=[0,0,0,1],this.blend=!1,this.pickOffset=0,this.points=null}e.exports=function(t,e){var r=t.gl,i=a(r),l=a(r),c=n(r,o.pointVertex,o.pointFragment),u=n(r,o.pickVertex,o.pickFragment),h=new s(t,i,l,c,u);return h.update(e),t.addObject(h),h};var l,c,u=s.prototype;u.dispose=function(){this.shader.dispose(),this.pickShader.dispose(),this.offsetBuffer.dispose(),this.pickBuffer.dispose(),this.plot.removeObject(this)},u.update=function(t){var e;function r(e,r){return e in t?t[e]:r}t=t||{},this.sizeMin=r("sizeMin",.5),this.sizeMax=r("sizeMax",20),this.color=r("color",[1,0,0,1]).slice(),this.areaRatio=r("areaRatio",1),this.borderColor=r("borderColor",[0,0,0,1]).slice(),this.blend=r("blend",!1);var n=t.positions.length>>>1,a=t.positions instanceof Float32Array,o=t.idToIndex instanceof Int32Array&&t.idToIndex.length>=n,s=t.positions,l=a?s:i.mallocFloat32(s.length),c=o?t.idToIndex:i.mallocInt32(n);if(a||l.set(s),!o)for(l.set(s),e=0;e<n;e++)c[e]=e;this.points=s,this.offsetBuffer.update(l),this.pickBuffer.update(c),a||i.free(l),o||i.free(c),this.pointCount=n,this.pickOffset=0},u.unifiedDraw=(l=[1,0,0,0,1,0,0,0,1],c=[0,0,0,0],function(t){var e=void 0!==t,r=e?this.pickShader:this.shader,n=this.plot.gl,a=this.plot.dataBox;if(0===this.pointCount)return t;var i=a[2]-a[0],o=a[3]-a[1],s=function(t,e){var r,n=0,a=t.length>>>1;for(r=0;r<a;r++){var i=t[2*r],o=t[2*r+1];i>=e[0]&&i<=e[2]&&o>=e[1]&&o<=e[3]&&n++}return n}(this.points,a),u=this.plot.pickPixelRatio*Math.max(Math.min(this.sizeMinCap,this.sizeMin),Math.min(this.sizeMax,this.sizeMax/Math.pow(s,.33333)));l[0]=2/i,l[4]=2/o,l[6]=-2*a[0]/i-1,l[7]=-2*a[1]/o-1,this.offsetBuffer.bind(),r.bind(),r.attributes.position.pointer(),r.uniforms.matrix=l,r.uniforms.color=this.color,r.uniforms.borderColor=this.borderColor,r.uniforms.pointCloud=u<5,r.uniforms.pointSize=u,r.uniforms.centerFraction=Math.min(1,Math.max(0,Math.sqrt(1-this.areaRatio))),e&&(c[0]=255&t,c[1]=t>>8&255,c[2]=t>>16&255,c[3]=t>>24&255,this.pickBuffer.bind(),r.attributes.pickId.pointer(n.UNSIGNED_BYTE),r.uniforms.pickOffset=c,this.pickOffset=t);var h=n.getParameter(n.BLEND),f=n.getParameter(n.DITHER);return h&&!this.blend&&n.disable(n.BLEND),f&&n.disable(n.DITHER),n.drawArrays(n.POINTS,0,this.pointCount),h&&!this.blend&&n.enable(n.BLEND),f&&n.enable(n.DITHER),t+this.pointCount}),u.draw=u.unifiedDraw,u.drawPick=u.unifiedDraw,u.pick=function(t,e,r){var n=this.pickOffset,a=this.pointCount;if(r<n||r>=n+a)return null;var i=r-n,o=this.points;return{object:this,pointId:i,dataCoord:[o[2*i],o[2*i+1]]}}},{"./lib/shader":297,"gl-buffer":253,"gl-shader":307,"typedarray-pool":547}],299:[function(t,e,r){e.exports=function(t,e,r,n){var a,i,o,s,l,c=e[0],u=e[1],h=e[2],f=e[3],p=r[0],d=r[1],g=r[2],m=r[3];(i=c*p+u*d+h*g+f*m)<0&&(i=-i,p=-p,d=-d,g=-g,m=-m);1-i>1e-6?(a=Math.acos(i),o=Math.sin(a),s=Math.sin((1-n)*a)/o,l=Math.sin(n*a)/o):(s=1-n,l=n);return t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*h+l*g,t[3]=s*f+l*m,t}},{}],300:[function(t,e,r){"use strict";e.exports=function(t){return t||0===t?t.toString():""}},{}],301:[function(t,e,r){"use strict";var n=t("vectorize-text");e.exports=function(t,e,r){var i=a[e];i||(i=a[e]={});if(t in i)return i[t];var o={textAlign:"center",textBaseline:"middle",lineHeight:1,font:e,lineSpacing:1.25,styletags:{breaklines:!0,bolds:!0,italics:!0,subscripts:!0,superscripts:!0},triangles:!0},s=n(t,o);o.triangles=!1;var l,c,u=n(t,o);if(r&&1!==r){for(l=0;l<s.positions.length;++l)for(c=0;c<s.positions[l].length;++c)s.positions[l][c]/=r;for(l=0;l<u.positions.length;++l)for(c=0;c<u.positions[l].length;++c)u.positions[l][c]/=r}var h=[[1/0,1/0],[-1/0,-1/0]],f=u.positions.length;for(l=0;l<f;++l){var p=u.positions[l];for(c=0;c<2;++c)h[0][c]=Math.min(h[0][c],p[c]),h[1][c]=Math.max(h[1][c],p[c])}return i[t]=[s,u,h]};var a={}},{"vectorize-text":552}],302:[function(t,e,r){var n=t("gl-shader"),a=t("glslify"),i=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform vec4 highlightId;\nuniform float highlightScale;\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0,0,0,0);\n } else {\n float scale = 1.0;\n if(distance(highlightId, id) < 0.0001) {\n scale = highlightScale;\n }\n\n vec4 worldPosition = model * vec4(position, 1);\n vec4 viewPosition = view * worldPosition;\n viewPosition = viewPosition / viewPosition.w;\n vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0));\n\n gl_Position = clipPosition;\n interpColor = color;\n pickId = id;\n dataCoordinate = position;\n }\n}"]),o=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform vec2 screenSize;\nuniform vec3 clipBounds[2];\nuniform float highlightScale, pixelRatio;\nuniform vec4 highlightId;\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0,0,0,0);\n } else {\n float scale = pixelRatio;\n if(distance(highlightId.bgr, id.bgr) < 0.001) {\n scale *= highlightScale;\n }\n\n vec4 worldPosition = model * vec4(position, 1.0);\n vec4 viewPosition = view * worldPosition;\n vec4 clipPosition = projection * viewPosition;\n clipPosition /= clipPosition.w;\n\n gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\n interpColor = color;\n pickId = id;\n dataCoordinate = position;\n }\n}"]),s=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform float highlightScale;\nuniform vec4 highlightId;\nuniform vec3 axes[2];\nuniform mat4 model, view, projection;\nuniform vec2 screenSize;\nuniform vec3 clipBounds[2];\nuniform float scale, pixelRatio;\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0,0,0,0);\n } else {\n float lscale = pixelRatio * scale;\n if(distance(highlightId, id) < 0.0001) {\n lscale *= highlightScale;\n }\n\n vec4 clipCenter = projection * view * model * vec4(position, 1);\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\n vec4 clipPosition = projection * view * model * vec4(dataPosition, 1);\n\n gl_Position = clipPosition;\n interpColor = color;\n pickId = id;\n dataCoordinate = dataPosition;\n }\n}\n"]),l=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 fragClipBounds[2];\nuniform float opacity;\n\nvarying vec4 interpColor;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (\n outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) ||\n interpColor.a * opacity == 0.\n ) discard;\n gl_FragColor = interpColor * opacity;\n}\n"]),c=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 fragClipBounds[2];\nuniform float pickGroup;\n\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard;\n\n gl_FragColor = vec4(pickGroup, pickId.bgr);\n}"]),u=[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"glyph",type:"vec2"},{name:"id",type:"vec4"}],h={vertex:i,fragment:l,attributes:u},f={vertex:o,fragment:l,attributes:u},p={vertex:s,fragment:l,attributes:u},d={vertex:i,fragment:c,attributes:u},g={vertex:o,fragment:c,attributes:u},m={vertex:s,fragment:c,attributes:u};function v(t,e){var r=n(t,e),a=r.attributes;return a.position.location=0,a.color.location=1,a.glyph.location=2,a.id.location=3,r}r.createPerspective=function(t){return v(t,h)},r.createOrtho=function(t){return v(t,f)},r.createProject=function(t){return v(t,p)},r.createPickPerspective=function(t){return v(t,d)},r.createPickOrtho=function(t){return v(t,g)},r.createPickProject=function(t){return v(t,m)}},{"gl-shader":307,glslify:408}],303:[function(t,e,r){"use strict";var n=t("is-string-blank"),a=t("gl-buffer"),i=t("gl-vao"),o=t("typedarray-pool"),s=t("gl-mat4/multiply"),l=t("./lib/shaders"),c=t("./lib/glyphs"),u=t("./lib/get-simple-string"),h=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function f(t,e){var r=t[0],n=t[1],a=t[2],i=t[3];return t[0]=e[0]*r+e[4]*n+e[8]*a+e[12]*i,t[1]=e[1]*r+e[5]*n+e[9]*a+e[13]*i,t[2]=e[2]*r+e[6]*n+e[10]*a+e[14]*i,t[3]=e[3]*r+e[7]*n+e[11]*a+e[15]*i,t}function p(t,e,r,n){return f(n,n),f(n,n),f(n,n)}function d(t,e){this.index=t,this.dataCoordinate=this.position=e}function g(t){return!0===t||t>1?1:t}function m(t,e,r,n,a,i,o,s,l,c,u,h){this.gl=t,this.pixelRatio=1,this.shader=e,this.orthoShader=r,this.projectShader=n,this.pointBuffer=a,this.colorBuffer=i,this.glyphBuffer=o,this.idBuffer=s,this.vao=l,this.vertexCount=0,this.lineVertexCount=0,this.opacity=1,this.hasAlpha=!1,this.lineWidth=0,this.projectScale=[2/3,2/3,2/3],this.projectOpacity=[1,1,1],this.projectHasAlpha=!1,this.pickId=0,this.pickPerspectiveShader=c,this.pickOrthoShader=u,this.pickProjectShader=h,this.points=[],this._selectResult=new d(0,[0,0,0]),this.useOrtho=!0,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.axesProject=[!0,!0,!0],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.highlightId=[1,1,1,1],this.highlightScale=2,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.dirty=!0}e.exports=function(t){var e=t.gl,r=l.createPerspective(e),n=l.createOrtho(e),o=l.createProject(e),s=l.createPickPerspective(e),c=l.createPickOrtho(e),u=l.createPickProject(e),h=a(e),f=a(e),p=a(e),d=a(e),g=i(e,[{buffer:h,size:3,type:e.FLOAT},{buffer:f,size:4,type:e.FLOAT},{buffer:p,size:2,type:e.FLOAT},{buffer:d,size:4,type:e.UNSIGNED_BYTE,normalized:!0}]),v=new m(e,r,n,o,h,f,p,d,g,s,c,u);return v.update(t),v};var v=m.prototype;v.pickSlots=1,v.setPickBase=function(t){this.pickId=t},v.isTransparent=function(){if(this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&this.projectHasAlpha)return!0;return!1},v.isOpaque=function(){if(!this.hasAlpha)return!0;for(var t=0;t<3;++t)if(this.axesProject[t]&&!this.projectHasAlpha)return!0;return!1};var y=[0,0],x=[0,0,0],b=[0,0,0],_=[0,0,0,1],w=[0,0,0,1],T=h.slice(),k=[0,0,0],A=[[0,0,0],[0,0,0]];function M(t){return t[0]=t[1]=t[2]=0,t}function S(t,e){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[3]=1,t}function E(t,e,r,n){return t[0]=e[0],t[1]=e[1],t[2]=e[2],t[r]=n,t}function C(t,e,r,n){var a,i=e.axesProject,o=e.gl,l=t.uniforms,c=r.model||h,u=r.view||h,f=r.projection||h,d=e.axesBounds,g=function(t){for(var e=A,r=0;r<2;++r)for(var n=0;n<3;++n)e[r][n]=Math.max(Math.min(t[r][n],1e8),-1e8);return e}(e.clipBounds);a=e.axes&&e.axes.lastCubeProps?e.axes.lastCubeProps.axis:[1,1,1],y[0]=2/o.drawingBufferWidth,y[1]=2/o.drawingBufferHeight,t.bind(),l.view=u,l.projection=f,l.screenSize=y,l.highlightId=e.highlightId,l.highlightScale=e.highlightScale,l.clipBounds=g,l.pickGroup=e.pickId/255,l.pixelRatio=n;for(var m=0;m<3;++m)if(i[m]){l.scale=e.projectScale[m],l.opacity=e.projectOpacity[m];for(var v=T,C=0;C<16;++C)v[C]=0;for(C=0;C<4;++C)v[5*C]=1;v[5*m]=0,a[m]<0?v[12+m]=d[0][m]:v[12+m]=d[1][m],s(v,c,v),l.model=v;var L=(m+1)%3,P=(m+2)%3,I=M(x),z=M(b);I[L]=1,z[P]=1;var O=p(0,0,0,S(_,I)),D=p(0,0,0,S(w,z));if(Math.abs(O[1])>Math.abs(D[1])){var R=O;O=D,D=R,R=I,I=z,z=R;var F=L;L=P,P=F}O[0]<0&&(I[L]=-1),D[1]>0&&(z[P]=-1);var B=0,N=0;for(C=0;C<4;++C)B+=Math.pow(c[4*L+C],2),N+=Math.pow(c[4*P+C],2);I[L]/=Math.sqrt(B),z[P]/=Math.sqrt(N),l.axes[0]=I,l.axes[1]=z,l.fragClipBounds[0]=E(k,g[0],m,-1e8),l.fragClipBounds[1]=E(k,g[1],m,1e8),e.vao.bind(),e.vao.draw(o.TRIANGLES,e.vertexCount),e.lineWidth>0&&(o.lineWidth(e.lineWidth*n),e.vao.draw(o.LINES,e.lineVertexCount,e.vertexCount)),e.vao.unbind()}}var L=[[-1e8,-1e8,-1e8],[1e8,1e8,1e8]];function P(t,e,r,n,a,i,o){var s=r.gl;if((i===r.projectHasAlpha||o)&&C(e,r,n,a),i===r.hasAlpha||o){t.bind();var l=t.uniforms;l.model=n.model||h,l.view=n.view||h,l.projection=n.projection||h,y[0]=2/s.drawingBufferWidth,y[1]=2/s.drawingBufferHeight,l.screenSize=y,l.highlightId=r.highlightId,l.highlightScale=r.highlightScale,l.fragClipBounds=L,l.clipBounds=r.axes.bounds,l.opacity=r.opacity,l.pickGroup=r.pickId/255,l.pixelRatio=a,r.vao.bind(),r.vao.draw(s.TRIANGLES,r.vertexCount),r.lineWidth>0&&(s.lineWidth(r.lineWidth*a),r.vao.draw(s.LINES,r.lineVertexCount,r.vertexCount)),r.vao.unbind()}}function I(t,e,r,a){var i;i=Array.isArray(t)?e<t.length?t[e]:void 0:t,i=u(i);var o=!0;n(i)&&(i="\u25bc",o=!1);var s=c(i,r,a);return{mesh:s[0],lines:s[1],bounds:s[2],visible:o}}v.draw=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!1,!1)},v.drawTransparent=function(t){P(this.useOrtho?this.orthoShader:this.shader,this.projectShader,this,t,this.pixelRatio,!0,!1)},v.drawPick=function(t){P(this.useOrtho?this.pickOrthoShader:this.pickPerspectiveShader,this.pickProjectShader,this,t,1,!0,!0)},v.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=t.value[2]+(t.value[1]<<8)+(t.value[0]<<16);if(e>=this.pointCount||e<0)return null;var r=this.points[e],n=this._selectResult;n.index=e;for(var a=0;a<3;++a)n.position[a]=n.dataCoordinate[a]=r[a];return n},v.highlight=function(t){if(t){var e=t.index,r=255&e,n=e>>8&255,a=e>>16&255;this.highlightId=[r/255,n/255,a/255,0]}else this.highlightId=[1,1,1,1]},v.update=function(t){if("perspective"in(t=t||{})&&(this.useOrtho=!t.perspective),"orthographic"in 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u=[1/0,1/0,1/0],h=[-1/0,-1/0,-1/0],f=t.glyph,p=t.color,d=t.size,m=t.angle,v=t.lineColor,y=-1,x=0,b=0,_=0;if(s.length){_=s.length;t:for(n=0;n<_;++n){for(var w=s[n],T=0;T<3;++T)if(isNaN(w[T])||!isFinite(w[T]))continue t;var k=(N=I(f,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;x+=3*k.cells.length,b+=2*A.edges.length}}var S=x+b,E=o.mallocFloat(3*S),C=o.mallocFloat(4*S),L=o.mallocFloat(2*S),P=o.mallocUint32(S);if(S>0){var z=0,O=x,D=[0,0,0,1],R=[0,0,0,1],F=Array.isArray(p)&&Array.isArray(p[0]),B=Array.isArray(v)&&Array.isArray(v[0]);t:for(n=0;n<_;++n){y+=1;for(w=s[n],T=0;T<3;++T){if(isNaN(w[T])||!isFinite(w[T]))continue t;h[T]=Math.max(h[T],w[T]),u[T]=Math.min(u[T],w[T])}k=(N=I(f,n,l,this.pixelRatio)).mesh,A=N.lines,M=N.bounds;var N,j=N.visible;if(j)if(Array.isArray(p)){if(3===(V=F?n<p.length?p[n]:[0,0,0,0]:p).length){for(T=0;T<3;++T)D[T]=V[T];D[3]=1}else if(4===V.length){for(T=0;T<4;++T)D[T]=V[T];!this.hasAlpha&&V[3]<1&&(this.hasAlpha=!0)}}else D[0]=D[1]=D[2]=0,D[3]=1;else 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n={FLOAT:"float",FLOAT_VEC2:"vec2",FLOAT_VEC3:"vec3",FLOAT_VEC4:"vec4",INT:"int",INT_VEC2:"ivec2",INT_VEC3:"ivec3",INT_VEC4:"ivec4",BOOL:"bool",BOOL_VEC2:"bvec2",BOOL_VEC3:"bvec3",BOOL_VEC4:"bvec4",FLOAT_MAT2:"mat2",FLOAT_MAT3:"mat3",FLOAT_MAT4:"mat4",SAMPLER_2D:"sampler2D",SAMPLER_CUBE:"samplerCube"},a=null;function i(t,e){if(!a){var r=Object.keys(n);a={};for(var i=0;i<r.length;++i){var o=r[i];a[t[o]]=n[o]}}return a[e]}},{}],313:[function(t,e,r){"use strict";r.shader=function(t,e,r){return u(t).getShaderReference(e,r)},r.program=function(t,e,r,n,a){return u(t).getProgram(e,r,n,a)};var n=t("./GLError"),a=t("gl-format-compiler-error"),i=new("undefined"==typeof WeakMap?t("weakmap-shim"):WeakMap),o=0;function s(t,e,r,n,a,i,o){this.id=t,this.src=e,this.type=r,this.shader=n,this.count=i,this.programs=[],this.cache=o}function l(t){this.gl=t,this.shaders=[{},{}],this.programs={}}s.prototype.dispose=function(){if(0==--this.count){for(var 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length(d), pointing in the direction of d.\n//\n// Each tube segment is made up of a ring of vertices.\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\n// The indexes of tube segments run from 0 to 8.\n//\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\n float segmentCount = 8.0;\n\n float angle = 2.0 * 3.14159 * (index / segmentCount);\n\n vec3 u = getOrthogonalVector(d);\n vec3 v = normalize(cross(u, d));\n\n vec3 x = u * cos(angle) * length(d);\n vec3 y = v * sin(angle) * length(d);\n vec3 v3 = x + y;\n\n normal = normalize(v3);\n\n return v3;\n}\n\nattribute vec4 vector;\nattribute vec4 color, position;\nattribute vec2 uv;\n\nuniform float vectorScale, tubeScale;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 eyePosition, lightPosition;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n // Scale the vector magnitude to stay constant with\n // model & view changes.\n vec3 normal;\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * tubePosition;\n cameraCoordinate.xyz /= cameraCoordinate.w;\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n // vec4 m_position = model * vec4(tubePosition, 1.0);\n vec4 t_position = view * tubePosition;\n gl_Position = projection * t_position;\n\n f_color = color;\n f_data = tubePosition.xyz;\n f_position = position.xyz;\n f_uv = uv;\n}\n"]),i=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness,\n float fresnel) {\n\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n //Half angle vector\n vec3 H = normalize(lightDirection + viewDirection);\n\n //Geometric term\n float NdotH = max(dot(surfaceNormal, H), 0.0);\n float VdotH = max(dot(viewDirection, H), 0.000001);\n float LdotH = max(dot(lightDirection, H), 0.000001);\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\n float G = min(1.0, min(G1, G2));\n \n //Distribution term\n float D = beckmannDistribution(NdotH, roughness);\n\n //Fresnel term\n float F = pow(1.0 - VdotN, fresnel);\n\n //Multiply terms and done\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform sampler2D texture;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n vec3 N = normalize(f_normal);\n vec3 L = normalize(f_lightDirection);\n vec3 V = normalize(f_eyeDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = litColor * opacity;\n}\n"]),o=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n // Return up-vector for only-z vector.\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\n // Assign z = 0, x = -b, y = a:\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n if (v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) {\n return normalize(vec3(-v.y, v.x, 0.0));\n } else {\n return normalize(vec3(0.0, v.z, -v.y));\n }\n}\n\n// Calculate the tube vertex and normal at the given index.\n//\n// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d.\n//\n// Each tube segment is made up of a ring of vertices.\n// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array.\n// The indexes of tube segments run from 0 to 8.\n//\nvec3 getTubePosition(vec3 d, float index, out vec3 normal) {\n float segmentCount = 8.0;\n\n float angle = 2.0 * 3.14159 * (index / segmentCount);\n\n vec3 u = getOrthogonalVector(d);\n vec3 v = normalize(cross(u, d));\n\n vec3 x = u * cos(angle) * length(d);\n vec3 y = v * sin(angle) * length(d);\n vec3 v3 = x + y;\n\n normal = normalize(v3);\n\n return v3;\n}\n\nattribute vec4 vector;\nattribute vec4 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform float tubeScale;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n vec3 normal;\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n gl_Position = projection * view * tubePosition;\n f_id = id;\n f_position = position.xyz;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n gl_FragColor = vec4(pickId, f_id.xyz);\n}"]);r.meshShader={vertex:a,fragment:i,attributes:[{name:"position",type:"vec4"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"vector",type:"vec4"}]},r.pickShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec4"},{name:"id",type:"vec4"},{name:"vector",type:"vec4"}]}},{glslify:408}],318:[function(t,e,r){"use strict";var n=t("gl-vec3"),a=t("gl-vec4"),i=["xyz","xzy","yxz","yzx","zxy","zyx"],o=function(t,e,r,i){for(var o=0,s=0;s<t.length;s++)for(var l=t[s].velocities,c=0;c<l.length;c++)o=Math.max(o,n.length(l[c]));var u=t.map((function(t){return function(t,e,r,i){for(var o=t.points,s=t.velocities,l=t.divergences,c=[],u=[],h=[],f=[],p=[],d=[],g=0,m=0,v=a.create(),y=a.create(),x=0;x<o.length;x++){var b=o[x],_=s[x],w=l[x];0===e&&(w=.05*r),m=n.length(_)/i,v=a.create(),n.copy(v,_),v[3]=w;for(var T=0;T<8;T++)p[T]=[b[0],b[1],b[2],T];if(f.length>0)for(T=0;T<8;T++){var k=(T+1)%8;c.push(f[T],p[T],p[k],p[k],f[k],f[T]),h.push(y,v,v,v,y,y),d.push(g,m,m,m,g,g);var A=c.length;u.push([A-6,A-5,A-4],[A-3,A-2,A-1])}var M=f;f=p,p=M;var S=y;y=v,v=S;var E=g;g=m,m=E}return{positions:c,cells:u,vectors:h,vertexIntensity:d}}(t,r,i,o)})),h=[],f=[],p=[],d=[];for(s=0;s<u.length;s++){var g=u[s],m=h.length;h=h.concat(g.positions),p=p.concat(g.vectors),d=d.concat(g.vertexIntensity);for(c=0;c<g.cells.length;c++){var v=g.cells[c],y=[];f.push(y);for(var x=0;x<v.length;x++)y.push(v[x]+m)}}return{positions:h,cells:f,vectors:p,vertexIntensity:d,colormap:e}},s=function(t,e){var r,n=t.length;for(r=0;r<n;r++){var a=t[r];if(a===e)return r;if(a>e)return r-1}return r},l=function(t,e,r){return t<e?e:t>r?r:t},c=function(t){var e=1/0;t.sort((function(t,e){return t-e}));for(var r=t.length,n=1;n<r;n++){var a=Math.abs(t[n]-t[n-1]);a<e&&(e=a)}return e};e.exports=function(t,e){var r=t.startingPositions,a=t.maxLength||1e3,u=t.tubeSize||1,h=t.absoluteTubeSize,f=t.gridFill||"+x+y+z",p={};-1!==f.indexOf("-x")&&(p.reversedX=!0),-1!==f.indexOf("-y")&&(p.reversedY=!0),-1!==f.indexOf("-z")&&(p.reversedZ=!0),p.filled=i.indexOf(f.replace(/-/g,"").replace(/\+/g,""));var d=t.getVelocity||function(e){return function(t,e,r){var a=e.vectors,i=e.meshgrid,o=t[0],c=t[1],u=t[2],h=i[0].length,f=i[1].length,p=i[2].length,d=s(i[0],o),g=s(i[1],c),m=s(i[2],u),v=d+1,y=g+1,x=m+1;if(d=l(d,0,h-1),v=l(v,0,h-1),g=l(g,0,f-1),y=l(y,0,f-1),m=l(m,0,p-1),x=l(x,0,p-1),d<0||g<0||m<0||v>h-1||y>f-1||x>p-1)return n.create();var b,_,w,T,k,A,M=i[0][d],S=i[0][v],E=i[1][g],C=i[1][y],L=i[2][m],P=(o-M)/(S-M),I=(c-E)/(C-E),z=(u-L)/(i[2][x]-L);switch(isFinite(P)||(P=.5),isFinite(I)||(I=.5),isFinite(z)||(z=.5),r.reversedX&&(d=h-1-d,v=h-1-v),r.reversedY&&(g=f-1-g,y=f-1-y),r.reversedZ&&(m=p-1-m,x=p-1-x),r.filled){case 5:k=m,A=x,w=g*p,T=y*p,b=d*p*f,_=v*p*f;break;case 4:k=m,A=x,b=d*p,_=v*p,w=g*p*h,T=y*p*h;break;case 3:w=g,T=y,k=m*f,A=x*f,b=d*f*p,_=v*f*p;break;case 2:w=g,T=y,b=d*f,_=v*f,k=m*f*h,A=x*f*h;break;case 1:b=d,_=v,k=m*h,A=x*h,w=g*h*p,T=y*h*p;break;default:b=d,_=v,w=g*h,T=y*h,k=m*h*f,A=x*h*f}var O=a[b+w+k],D=a[b+w+A],R=a[b+T+k],F=a[b+T+A],B=a[_+w+k],N=a[_+w+A],j=a[_+T+k],V=a[_+T+A],U=n.create(),q=n.create(),H=n.create(),G=n.create();n.lerp(U,O,B,P),n.lerp(q,D,N,P),n.lerp(H,R,j,P),n.lerp(G,F,V,P);var Y=n.create(),W=n.create();n.lerp(Y,U,H,I),n.lerp(W,q,G,I);var Z=n.create();return n.lerp(Z,Y,W,z),Z}(e,t,p)},g=t.getDivergence||function(t,e){var r=n.create(),a=1e-4;n.add(r,t,[a,0,0]);var i=d(r);n.subtract(i,i,e),n.scale(i,i,1/a),n.add(r,t,[0,a,0]);var o=d(r);n.subtract(o,o,e),n.scale(o,o,1/a),n.add(r,t,[0,0,a]);var s=d(r);return n.subtract(s,s,e),n.scale(s,s,1/a),n.add(r,i,o),n.add(r,r,s),r},m=[],v=e[0][0],y=e[0][1],x=e[0][2],b=e[1][0],_=e[1][1],w=e[1][2],T=function(t){var e=t[0],r=t[1],n=t[2];return!(e<v||e>b||r<y||r>_||n<x||n>w)},k=10*n.distance(e[0],e[1])/a,A=k*k,M=1,S=0,E=r.length;E>1&&(M=function(t){for(var e=[],r=[],n=[],a={},i={},o={},s=t.length,l=0;l<s;l++){var u=t[l],h=u[0],f=u[1],p=u[2];a[h]||(e.push(h),a[h]=!0),i[f]||(r.push(f),i[f]=!0),o[p]||(n.push(p),o[p]=!0)}var d=c(e),g=c(r),m=c(n),v=Math.min(d,g,m);return isFinite(v)?v:1}(r));for(var C=0;C<E;C++){var L=n.create();n.copy(L,r[C]);var P=[L],I=[],z=d(L),O=L;I.push(z);var D=[],R=g(L,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F),m.push({points:P,velocities:I,divergences:D});for(var B=0;B<100*a&&P.length<a&&T(L);){B++;var N=n.clone(z),j=n.squaredLength(N);if(0===j)break;if(j>A&&n.scale(N,N,k/Math.sqrt(j)),n.add(N,N,L),z=d(N),n.squaredDistance(O,N)-A>-1e-4*A){P.push(N),O=N,I.push(z);R=g(N,z),F=n.length(R);isFinite(F)&&F>S&&(S=F),D.push(F)}L=N}}var V=o(m,t.colormap,S,M);return h?V.tubeScale=h:(0===S&&(S=1),V.tubeScale=.5*u*M/S),V};var u=t("./lib/shaders"),h=t("gl-cone3d").createMesh;e.exports.createTubeMesh=function(t,e){return h(t,e,{shaders:u,traceType:"streamtube"})}},{"./lib/shaders":317,"gl-cone3d":254,"gl-vec3":346,"gl-vec4":382}],319:[function(t,e,r){var n=t("gl-shader"),a=t("glslify"),i=a(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec4 uv;\nattribute vec3 f;\nattribute vec3 normal;\n\nuniform vec3 objectOffset;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 lightPosition, eyePosition;\nuniform sampler2D colormap;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n vec3 localCoordinate = vec3(uv.zw, f.x);\n worldCoordinate = objectOffset + localCoordinate;\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\n vec4 clipPosition = projection * view * worldPosition;\n gl_Position = clipPosition;\n kill = f.y;\n value = f.z;\n planeCoordinate = uv.xy;\n\n vColor = texture2D(colormap, vec2(value, value));\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * worldPosition;\n cameraCoordinate.xyz /= cameraCoordinate.w;\n lightDirection = lightPosition - cameraCoordinate.xyz;\n eyeDirection = eyePosition - cameraCoordinate.xyz;\n surfaceNormal = normalize((vec4(normal,0) * inverseModel).xyz);\n}\n"]),o=a(["precision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat beckmannSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness) {\n return beckmannDistribution(dot(surfaceNormal, normalize(lightDirection + viewDirection)), roughness);\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 lowerBound, upperBound;\nuniform float contourTint;\nuniform vec4 contourColor;\nuniform sampler2D colormap;\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform float vertexColor;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n if (\n kill > 0.0 ||\n vColor.a == 0.0 ||\n outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\n ) discard;\n\n vec3 N = normalize(surfaceNormal);\n vec3 V = normalize(eyeDirection);\n vec3 L = normalize(lightDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n //decide how to interpolate color \u2014 in vertex or in fragment\n vec4 surfaceColor =\n step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\n step(.5, vertexColor) * vColor;\n\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = mix(litColor, contourColor, contourTint) * opacity;\n}\n"]),s=a(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec4 uv;\nattribute float f;\n\nuniform vec3 objectOffset;\nuniform mat3 permutation;\nuniform mat4 model, view, projection;\nuniform float height, zOffset;\nuniform sampler2D colormap;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n vec3 dataCoordinate = permutation * vec3(uv.xy, height);\n worldCoordinate = objectOffset + dataCoordinate;\n vec4 worldPosition = model * vec4(worldCoordinate, 1.0);\n\n vec4 clipPosition = projection * view * worldPosition;\n clipPosition.z += zOffset;\n\n gl_Position = clipPosition;\n value = f + objectOffset.z;\n kill = -1.0;\n planeCoordinate = uv.zw;\n\n vColor = texture2D(colormap, vec2(value, value));\n\n //Don't do lighting for contours\n surfaceNormal = vec3(1,0,0);\n eyeDirection = vec3(0,1,0);\n lightDirection = vec3(0,0,1);\n}\n"]),l=a(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec2 shape;\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 surfaceNormal;\n\nvec2 splitFloat(float v) {\n float vh = 255.0 * v;\n float upper = floor(vh);\n float lower = fract(vh);\n return vec2(upper / 255.0, floor(lower * 16.0) / 16.0);\n}\n\nvoid main() {\n if ((kill > 0.0) ||\n (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard;\n\n vec2 ux = splitFloat(planeCoordinate.x / shape.x);\n vec2 uy = splitFloat(planeCoordinate.y / shape.y);\n gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0));\n}\n"]);r.createShader=function(t){var e=n(t,i,o,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createPickShader=function(t){var e=n(t,i,l,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e.attributes.normal.location=2,e},r.createContourShader=function(t){var e=n(t,s,o,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e},r.createPickContourShader=function(t){var e=n(t,s,l,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return e.attributes.uv.location=0,e.attributes.f.location=1,e}},{"gl-shader":307,glslify:408}],320:[function(t,e,r){"use strict";e.exports=function(t){var e=t.gl,r=y(e),n=b(e),s=x(e),l=_(e),c=a(e),u=i(e,[{buffer:c,size:4,stride:40,offset:0},{buffer:c,size:3,stride:40,offset:16},{buffer:c,size:3,stride:40,offset:28}]),h=a(e),f=i(e,[{buffer:h,size:4,stride:20,offset:0},{buffer:h,size:1,stride:20,offset:16}]),p=a(e),d=i(e,[{buffer:p,size:2,type:e.FLOAT}]),g=o(e,1,256,e.RGBA,e.UNSIGNED_BYTE);g.minFilter=e.LINEAR,g.magFilter=e.LINEAR;var m=new M(e,[0,0],[[0,0,0],[0,0,0]],r,n,c,u,g,s,l,h,f,p,d,[0,0,0]),v={levels:[[],[],[]]};for(var w in t)v[w]=t[w];return v.colormap=v.colormap||"jet",m.update(v),m};var n=t("bit-twiddle"),a=t("gl-buffer"),i=t("gl-vao"),o=t("gl-texture2d"),s=t("typedarray-pool"),l=t("colormap"),c=t("ndarray-ops"),u=t("ndarray-pack"),h=t("ndarray"),f=t("surface-nets"),p=t("gl-mat4/multiply"),d=t("gl-mat4/invert"),g=t("binary-search-bounds"),m=t("ndarray-gradient"),v=t("./lib/shaders"),y=v.createShader,x=v.createContourShader,b=v.createPickShader,_=v.createPickContourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1],T=[[0,0],[0,1],[1,0],[1,1],[1,0],[0,1]],k=[[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]];function A(t,e,r,n,a){this.position=t,this.index=e,this.uv=r,this.level=n,this.dataCoordinate=a}!function(){for(var t=0;t<3;++t){var e=k[t],r=(t+2)%3;e[(t+1)%3+0]=1,e[r+3]=1,e[t+6]=1}}();function M(t,e,r,n,a,i,o,l,c,u,f,p,d,g,m){this.gl=t,this.shape=e,this.bounds=r,this.objectOffset=m,this.intensityBounds=[],this._shader=n,this._pickShader=a,this._coordinateBuffer=i,this._vao=o,this._colorMap=l,this._contourShader=c,this._contourPickShader=u,this._contourBuffer=f,this._contourVAO=p,this._contourOffsets=[[],[],[]],this._contourCounts=[[],[],[]],this._vertexCount=0,this._pickResult=new A([0,0,0],[0,0],[0,0],[0,0,0],[0,0,0]),this._dynamicBuffer=d,this._dynamicVAO=g,this._dynamicOffsets=[0,0,0],this._dynamicCounts=[0,0,0],this.contourWidth=[1,1,1],this.contourLevels=[[1],[1],[1]],this.contourTint=[0,0,0],this.contourColor=[[.5,.5,.5,1],[.5,.5,.5,1],[.5,.5,.5,1]],this.showContour=!0,this.showSurface=!0,this.enableHighlight=[!0,!0,!0],this.highlightColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.highlightTint=[1,1,1],this.highlightLevel=[-1,-1,-1],this.enableDynamic=[!0,!0,!0],this.dynamicLevel=[NaN,NaN,NaN],this.dynamicColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.dynamicTint=[1,1,1],this.dynamicWidth=[1,1,1],this.axesBounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.surfaceProject=[!1,!1,!1],this.contourProject=[[!1,!1,!1],[!1,!1,!1],[!1,!1,!1]],this.colorBounds=[!1,!1],this._field=[h(s.mallocFloat(1024),[0,0]),h(s.mallocFloat(1024),[0,0]),h(s.mallocFloat(1024),[0,0])],this.pickId=1,this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.snapToData=!1,this.pixelRatio=1,this.opacity=1,this.opacityscale=!1,this.lightPosition=[10,1e4,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.vertexColor=0,this.dirty=!0}var S=M.prototype;S.isTransparent=function(){return this.opacity<1||this.opacityscale},S.isOpaque=function(){if(this.opacityscale)return!1;if(this.opacity<1)return!1;if(this.opacity>=1)return!0;for(var t=0;t<3;++t)if(this._contourCounts[t].length>0)return!0;return!1},S.pickSlots=1,S.setPickBase=function(t){this.pickId=t};var E=[0,0,0],C={showSurface:!1,showContour:!1,projections:[w.slice(),w.slice(),w.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function L(t,e){var r,n,a,i=e.axes&&e.axes.lastCubeProps.axis||E,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=C.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(i[r]>0)][r],p(l,t.model,l);var c=C.clipBounds[r];for(a=0;a<2;++a)for(n=0;n<3;++n)c[a][n]=t.clipBounds[a][n];c[0][r]=-1e8,c[1][r]=1e8}return C.showSurface=o,C.showContour=s,C}var P={model:w,view:w,projection:w,inverseModel:w.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},I=w.slice(),z=[1,0,0,0,1,0,0,0,1];function O(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=P;n.model=t.model||w,n.view=t.view||w,n.projection=t.projection||w,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var a=0;a<2;++a)for(var i=n.clipBounds[a],o=0;o<3;++o)i[o]=Math.min(Math.max(this.clipBounds[a][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=z,n.vertexColor=this.vertexColor;var s=I;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),a=0;a<3;++a)n.eyePosition[a]=s[12+a]/s[15];var l=s[15];for(a=0;a<3;++a)l+=this.lightPosition[a]*s[4*a+3];for(a=0;a<3;++a){var c=s[12+a];for(o=0;o<3;++o)c+=s[4*o+a]*this.lightPosition[o];n.lightPosition[a]=c/l}var u=L(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),a=0;a<3;++a)this.surfaceProject[a]&&this.vertexCount&&(this._shader.uniforms.model=u.projections[a],this._shader.uniforms.clipBounds=u.clipBounds[a],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var f=this._contourVAO;for(f.bind(),a=0;a<3;++a)for(h.uniforms.permutation=k[a],r.lineWidth(this.contourWidth[a]*this.pixelRatio),o=0;o<this.contourLevels[a].length;++o)o===this.highlightLevel[a]?(h.uniforms.contourColor=this.highlightColor[a],h.uniforms.contourTint=this.highlightTint[a]):0!==o&&o-1!==this.highlightLevel[a]||(h.uniforms.contourColor=this.contourColor[a],h.uniforms.contourTint=this.contourTint[a]),this._contourCounts[a][o]&&(h.uniforms.height=this.contourLevels[a][o],f.draw(r.LINES,this._contourCounts[a][o],this._contourOffsets[a][o]));for(a=0;a<3;++a)for(h.uniforms.model=u.projections[a],h.uniforms.clipBounds=u.clipBounds[a],o=0;o<3;++o)if(this.contourProject[a][o]){h.uniforms.permutation=k[o],r.lineWidth(this.contourWidth[o]*this.pixelRatio);for(var g=0;g<this.contourLevels[o].length;++g)g===this.highlightLevel[o]?(h.uniforms.contourColor=this.highlightColor[o],h.uniforms.contourTint=this.highlightTint[o]):0!==g&&g-1!==this.highlightLevel[o]||(h.uniforms.contourColor=this.contourColor[o],h.uniforms.contourTint=this.contourTint[o]),this._contourCounts[o][g]&&(h.uniforms.height=this.contourLevels[o][g],f.draw(r.LINES,this._contourCounts[o][g],this._contourOffsets[o][g]))}for(f.unbind(),(f=this._dynamicVAO).bind(),a=0;a<3;++a)if(0!==this._dynamicCounts[a])for(h.uniforms.model=n.model,h.uniforms.clipBounds=n.clipBounds,h.uniforms.permutation=k[a],r.lineWidth(this.dynamicWidth[a]*this.pixelRatio),h.uniforms.contourColor=this.dynamicColor[a],h.uniforms.contourTint=this.dynamicTint[a],h.uniforms.height=this.dynamicLevel[a],f.draw(r.LINES,this._dynamicCounts[a],this._dynamicOffsets[a]),o=0;o<3;++o)this.contourProject[o][a]&&(h.uniforms.model=u.projections[o],h.uniforms.clipBounds=u.clipBounds[o],f.draw(r.LINES,this._dynamicCounts[a],this._dynamicOffsets[a]));f.unbind()}}S.draw=function(t){return O.call(this,t,!1)},S.drawTransparent=function(t){return O.call(this,t,!0)};var D={model:w,view:w,projection:w,inverseModel:w,clipBounds:[[0,0,0],[0,0,0]],height:0,shape:[0,0],pickId:0,lowerBound:[0,0,0],upperBound:[0,0,0],zOffset:0,objectOffset:[0,0,0],permutation:[1,0,0,0,1,0,0,0,1],lightPosition:[0,0,0],eyePosition:[0,0,0]};function R(t,e){return Array.isArray(t)?[e(t[0]),e(t[1]),e(t[2])]:[e(t),e(t),e(t)]}function F(t){return Array.isArray(t)?3===t.length?[t[0],t[1],t[2],1]:[t[0],t[1],t[2],t[3]]:[0,0,0,1]}function B(t){if(Array.isArray(t)){if(Array.isArray(t))return[F(t[0]),F(t[1]),F(t[2])];var e=F(t);return[e.slice(),e.slice(),e.slice()]}}S.drawPick=function(t){t=t||{};var e=this.gl;e.disable(e.CULL_FACE);var r=D;r.model=t.model||w,r.view=t.view||w,r.projection=t.projection||w,r.shape=this._field[2].shape,r.pickId=this.pickId/255,r.lowerBound=this.bounds[0],r.upperBound=this.bounds[1],r.objectOffset=this.objectOffset,r.permutation=z;for(var n=0;n<2;++n)for(var a=r.clipBounds[n],i=0;i<3;++i)a[i]=Math.min(Math.max(this.clipBounds[n][i],-1e8),1e8);var o=L(r,this);if(o.showSurface){for(this._pickShader.bind(),this._pickShader.uniforms=r,this._vao.bind(),this._vao.draw(e.TRIANGLES,this._vertexCount),n=0;n<3;++n)this.surfaceProject[n]&&(this._pickShader.uniforms.model=o.projections[n],this._pickShader.uniforms.clipBounds=o.clipBounds[n],this._vao.draw(e.TRIANGLES,this._vertexCount));this._vao.unbind()}if(o.showContour){var s=this._contourPickShader;s.bind(),s.uniforms=r;var l=this._contourVAO;for(l.bind(),i=0;i<3;++i)for(e.lineWidth(this.contourWidth[i]*this.pixelRatio),s.uniforms.permutation=k[i],n=0;n<this.contourLevels[i].length;++n)this._contourCounts[i][n]&&(s.uniforms.height=this.contourLevels[i][n],l.draw(e.LINES,this._contourCounts[i][n],this._contourOffsets[i][n]));for(n=0;n<3;++n)for(s.uniforms.model=o.projections[n],s.uniforms.clipBounds=o.clipBounds[n],i=0;i<3;++i)if(this.contourProject[n][i]){s.uniforms.permutation=k[i],e.lineWidth(this.contourWidth[i]*this.pixelRatio);for(var c=0;c<this.contourLevels[i].length;++c)this._contourCounts[i][c]&&(s.uniforms.height=this.contourLevels[i][c],l.draw(e.LINES,this._contourCounts[i][c],this._contourOffsets[i][c]))}l.unbind()}},S.pick=function(t){if(!t)return null;if(t.id!==this.pickId)return null;var e=this._field[2].shape,r=this._pickResult,n=e[0]*(t.value[0]+(t.value[2]>>4)/16)/255,a=Math.floor(n),i=n-a,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;a+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var h=u?i:1-i,f=0;f<2;++f)for(var p=a+u,d=s+f,m=h*(f?l:1-l),v=0;v<3;++v)c[v]+=this._field[v].get(p,d)*m;for(var y=this._pickResult.level,x=0;x<3;++x)if(y[x]=g.le(this.contourLevels[x],c[x]),y[x]<0)this.contourLevels[x].length>0&&(y[x]=0);else if(y[x]<this.contourLevels[x].length-1){var b=this.contourLevels[x][y[x]],_=this.contourLevels[x][y[x]+1];Math.abs(b-c[x])>Math.abs(_-c[x])&&(y[x]+=1)}for(r.index[0]=i<.5?a:a+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],v=0;v<3;++v)r.dataCoordinate[v]=this._field[v].get(r.index[0],r.index[1]);return r},S.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},S.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,"contourWidth"in t&&(this.contourWidth=R(t.contourWidth,Number)),"showContour"in t&&(this.showContour=R(t.showContour,Boolean)),"showSurface"in t&&(this.showSurface=!!t.showSurface),"contourTint"in t&&(this.contourTint=R(t.contourTint,Boolean)),"contourColor"in t&&(this.contourColor=B(t.contourColor)),"contourProject"in t&&(this.contourProject=R(t.contourProject,(function(t){return R(t,Boolean)}))),"surfaceProject"in t&&(this.surfaceProject=t.surfaceProject),"dynamicColor"in t&&(this.dynamicColor=B(t.dynamicColor)),"dynamicTint"in t&&(this.dynamicTint=R(t.dynamicTint,Number)),"dynamicWidth"in t&&(this.dynamicWidth=R(t.dynamicWidth,Number)),"opacity"in t&&(this.opacity=t.opacity),"opacityscale"in t&&(this.opacityscale=t.opacityscale),"colorBounds"in t&&(this.colorBounds=t.colorBounds),"vertexColor"in t&&(this.vertexColor=t.vertexColor?1:0);var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),"field"in t||"coords"in t){var a=(e.shape[0]+2)*(e.shape[1]+2);a>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(a))),this._field[2]=h(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var i=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=h(this._field[o].data,[i[0]+2,i[1]+2]);if(t.coords){var p=t.coords;if(!Array.isArray(p)||3!==p.length)throw new Error("gl-surface: invalid coordinates for x/y");for(o=0;o<2;++o){var d=p[o];for(b=0;b<2;++b)if(d.shape[b]!==i[b])throw new Error("gl-surface: coords have incorrect shape");this.padField(this._field[o],d)}}else if(t.ticks){var g=t.ticks;if(!Array.isArray(g)||2!==g.length)throw new Error("gl-surface: invalid ticks");for(o=0;o<2;++o){var v=g[o];if((Array.isArray(v)||v.length)&&(v=h(v)),v.shape[0]!==i[o])throw new Error("gl-surface: invalid tick length");var y=h(v.data,i);y.stride[o]=v.stride[0],y.stride[1^o]=0,this.padField(this._field[o],y)}}else{for(o=0;o<2;++o){var x=[0,0];x[o]=1,this._field[o]=h(this._field[o].data,[i[0]+2,i[1]+2],x,0)}this._field[0].set(0,0,0);for(var b=0;b<i[0];++b)this._field[0].set(b+1,0,b);for(this._field[0].set(i[0]+1,0,i[0]-1),this._field[1].set(0,0,0),b=0;b<i[1];++b)this._field[1].set(0,b+1,b);this._field[1].set(0,i[1]+1,i[1]-1)}var _=this._field,w=h(s.mallocFloat(3*_[2].size*2),[3,i[0]+2,i[1]+2,2]);for(o=0;o<3;++o)m(w.pick(o),_[o],"mirror");var k=h(s.mallocFloat(3*_[2].size),[i[0]+2,i[1]+2,3]);for(o=0;o<i[0]+2;++o)for(b=0;b<i[1]+2;++b){var A=w.get(0,o,b,0),M=w.get(0,o,b,1),S=w.get(1,o,b,0),E=w.get(1,o,b,1),C=w.get(2,o,b,0),L=w.get(2,o,b,1),P=S*L-E*C,I=C*M-L*A,z=A*E-M*S,O=Math.sqrt(P*P+I*I+z*z);O<1e-8?(O=Math.max(Math.abs(P),Math.abs(I),Math.abs(z)))<1e-8?(z=1,I=P=0,O=1):O=1/O:O=1/Math.sqrt(O),k.set(o,b,0,P*O),k.set(o,b,1,I*O),k.set(o,b,2,z*O)}s.free(w.data);var D=[1/0,1/0,1/0],F=[-1/0,-1/0,-1/0],N=1/0,j=-1/0,V=(i[0]-1)*(i[1]-1)*6,U=s.mallocFloat(n.nextPow2(10*V)),q=0,H=0;for(o=0;o<i[0]-1;++o)t:for(b=0;b<i[1]-1;++b){for(var G=0;G<2;++G)for(var Y=0;Y<2;++Y)for(var W=0;W<3;++W){var Z=this._field[W].get(1+o+G,1+b+Y);if(isNaN(Z)||!isFinite(Z))continue t}for(W=0;W<6;++W){var X=o+T[W][0],J=b+T[W][1],K=this._field[0].get(X+1,J+1),Q=this._field[1].get(X+1,J+1);Z=this._field[2].get(X+1,J+1),P=k.get(X+1,J+1,0),I=k.get(X+1,J+1,1),z=k.get(X+1,J+1,2),t.intensity&&($=t.intensity.get(X,J));var $=t.intensity?t.intensity.get(X,J):Z+this.objectOffset[2];U[q++]=X,U[q++]=J,U[q++]=K,U[q++]=Q,U[q++]=Z,U[q++]=0,U[q++]=$,U[q++]=P,U[q++]=I,U[q++]=z,D[0]=Math.min(D[0],K+this.objectOffset[0]),D[1]=Math.min(D[1],Q+this.objectOffset[1]),D[2]=Math.min(D[2],Z+this.objectOffset[2]),N=Math.min(N,$),F[0]=Math.max(F[0],K+this.objectOffset[0]),F[1]=Math.max(F[1],Q+this.objectOffset[1]),F[2]=Math.max(F[2],Z+this.objectOffset[2]),j=Math.max(j,$),H+=1}}for(t.intensityBounds&&(N=+t.intensityBounds[0],j=+t.intensityBounds[1]),o=6;o<q;o+=10)U[o]=(U[o]-N)/(j-N);this._vertexCount=H,this._coordinateBuffer.update(U.subarray(0,q)),s.freeFloat(U),s.free(k.data),this.bounds=[D,F],this.intensity=t.intensity||this._field[2],this.intensityBounds[0]===N&&this.intensityBounds[1]===j||(r=!0),this.intensityBounds=[N,j]}if("levels"in t){var tt=t.levels;for(tt=Array.isArray(tt[0])?tt.slice():[[],[],tt],o=0;o<3;++o)tt[o]=tt[o].slice(),tt[o].sort((function(t,e){return t-e}));for(o=0;o<3;++o)for(b=0;b<tt[o].length;++b)tt[o][b]-=this.objectOffset[o];t:for(o=0;o<3;++o){if(tt[o].length!==this.contourLevels[o].length){r=!0;break}for(b=0;b<tt[o].length;++b)if(tt[o][b]!==this.contourLevels[o][b]){r=!0;break t}}this.contourLevels=tt}if(r){_=this._field,i=this.shape;for(var et=[],rt=0;rt<3;++rt){var nt=this.contourLevels[rt],at=[],it=[],ot=[0,0,0];for(o=0;o<nt.length;++o){var st=f(this._field[rt],nt[o]);at.push(et.length/5|0),H=0;t:for(b=0;b<st.cells.length;++b){var lt=st.cells[b];for(W=0;W<2;++W){var ct=st.positions[lt[W]],ut=ct[0],ht=0|Math.floor(ut),ft=ut-ht,pt=ct[1],dt=0|Math.floor(pt),gt=pt-dt,mt=!1;e:for(var vt=0;vt<3;++vt){ot[vt]=0;var yt=(rt+vt+1)%3;for(G=0;G<2;++G){var xt=G?ft:1-ft;for(X=0|Math.min(Math.max(ht+G,0),i[0]),Y=0;Y<2;++Y){var bt=Y?gt:1-gt;if(J=0|Math.min(Math.max(dt+Y,0),i[1]),Z=vt<2?this._field[yt].get(X,J):(this.intensity.get(X,J)-this.intensityBounds[0])/(this.intensityBounds[1]-this.intensityBounds[0]),!isFinite(Z)||isNaN(Z)){mt=!0;break e}var _t=xt*bt;ot[vt]+=_t*Z}}}if(mt){if(W>0){for(var wt=0;wt<5;++wt)et.pop();H-=1}continue t}et.push(ot[0],ot[1],ct[0],ct[1],ot[2]),H+=1}}it.push(H)}this._contourOffsets[rt]=at,this._contourCounts[rt]=it}var Tt=s.mallocFloat(et.length);for(o=0;o<et.length;++o)Tt[o]=et[o];this._contourBuffer.update(Tt),s.freeFloat(Tt)}t.colormap&&this._colorMap.setPixels(function(t,e){var r=u([l({colormap:t,nshades:256,format:"rgba"}).map((function(t,r){var n=e?function(t,e){if(!e)return 1;if(!e.length)return 1;for(var r=0;r<e.length;++r){if(e.length<2)return 1;if(e[r][0]===t)return e[r][1];if(e[r][0]>t&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(r/255,e):1;return[t[0],t[1],t[2],255*n]}))]);return c.divseq(r,255),r}(t.colormap,this.opacityscale))},S.dispose=function(){this._shader.dispose(),this._vao.dispose(),this._coordinateBuffer.dispose(),this._colorMap.dispose(),this._contourBuffer.dispose(),this._contourVAO.dispose(),this._contourShader.dispose(),this._contourPickShader.dispose(),this._dynamicBuffer.dispose(),this._dynamicVAO.dispose();for(var t=0;t<3;++t)s.freeFloat(this._field[t].data)},S.highlight=function(t){var e,r;if(!t)return this._dynamicCounts=[0,0,0],this.dyanamicLevel=[NaN,NaN,NaN],void(this.highlightLevel=[-1,-1,-1]);for(e=0;e<3;++e)this.enableHighlight[e]?this.highlightLevel[e]=t.level[e]:this.highlightLevel[e]=-1;for(r=this.snapToData?t.dataCoordinate:t.position,e=0;e<3;++e)r[e]-=this.objectOffset[e];if(this.enableDynamic[0]&&r[0]!==this.dynamicLevel[0]||this.enableDynamic[1]&&r[1]!==this.dynamicLevel[1]||this.enableDynamic[2]&&r[2]!==this.dynamicLevel[2]){for(var n=0,a=this.shape,i=s.mallocFloat(12*a[0]*a[1]),o=0;o<3;++o)if(this.enableDynamic[o]){this.dynamicLevel[o]=r[o];var l=(o+1)%3,c=(o+2)%3,u=this._field[o],h=this._field[l],p=this._field[c],d=f(u,r[o]),g=d.cells,m=d.positions;for(this._dynamicOffsets[o]=n,e=0;e<g.length;++e)for(var v=g[e],y=0;y<2;++y){var x=m[v[y]],b=+x[0],_=0|b,w=0|Math.min(_+1,a[0]),T=b-_,k=1-T,A=+x[1],M=0|A,S=0|Math.min(M+1,a[1]),E=A-M,C=1-E,L=k*C,P=k*E,I=T*C,z=T*E,O=L*h.get(_,M)+P*h.get(_,S)+I*h.get(w,M)+z*h.get(w,S),D=L*p.get(_,M)+P*p.get(_,S)+I*p.get(w,M)+z*p.get(w,S);if(isNaN(O)||isNaN(D)){y&&(n-=1);break}i[2*n+0]=O,i[2*n+1]=D,n+=1}this._dynamicCounts[o]=n-this._dynamicOffsets[o]}else this.dynamicLevel[o]=NaN,this._dynamicCounts[o]=0;this._dynamicBuffer.update(i.subarray(0,2*n)),s.freeFloat(i)}}},{"./lib/shaders":319,"binary-search-bounds":94,"bit-twiddle":95,colormap:128,"gl-buffer":253,"gl-mat4/invert":273,"gl-mat4/multiply":275,"gl-texture2d":322,"gl-vao":327,ndarray:448,"ndarray-gradient":441,"ndarray-ops":443,"ndarray-pack":444,"surface-nets":522,"typedarray-pool":547}],321:[function(t,e,r){"use strict";var n=t("css-font"),a=t("pick-by-alias"),i=t("regl"),o=t("gl-util/context"),s=t("es6-weak-map"),l=t("color-normalize"),c=t("font-atlas"),u=t("typedarray-pool"),h=t("parse-rect"),f=t("is-plain-obj"),p=t("parse-unit"),d=t("to-px"),g=t("detect-kerning"),m=t("object-assign"),v=t("font-measure"),y=t("flatten-vertex-data"),x=t("bit-twiddle").nextPow2,b=new s,_=!1;if(document.body){var w=document.body.appendChild(document.createElement("div"));w.style.font="italic small-caps bold condensed 16px/2 cursive",getComputedStyle(w).fontStretch&&(_=!0),document.body.removeChild(w)}var T=function(t){!function(t){return"function"==typeof t&&t._gl&&t.prop&&t.texture&&t.buffer}(t)?this.gl=o(t):(t={regl:t},this.gl=t.regl._gl),this.shader=b.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||i({gl:this.gl}),this.charBuffer=this.regl.buffer({type:"uint8",usage:"stream"}),this.sizeBuffer=this.regl.buffer({type:"float",usage:"stream"}),this.shader||(this.shader=this.createShader(),b.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(f(t)?t:{})};T.prototype.createShader=function(){var t=this.regl,e=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:"src alpha",dstRGB:"one minus src alpha",srcAlpha:"one minus dst alpha",dstAlpha:"one"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop("count"),offset:t.prop("offset"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this("sizeBuffer")},width:{offset:0,stride:8,buffer:t.this("sizeBuffer")},char:t.this("charBuffer"),position:t.this("position")},uniforms:{atlasSize:function(t,e){return[e.atlas.width,e.atlas.height]},atlasDim:function(t,e){return[e.atlas.cols,e.atlas.rows]},atlas:function(t,e){return e.atlas.texture},charStep:function(t,e){return e.atlas.step},em:function(t,e){return e.atlas.em},color:t.prop("color"),opacity:t.prop("opacity"),viewport:t.this("viewportArray"),scale:t.this("scale"),align:t.prop("align"),baseline:t.prop("baseline"),translate:t.this("translate"),positionOffset:t.prop("positionOffset")},primitive:"points",viewport:t.this("viewport"),vert:"\n\t\t\tprecision highp float;\n\t\t\tattribute float width, charOffset, char;\n\t\t\tattribute vec2 position;\n\t\t\tuniform float fontSize, charStep, em, align, baseline;\n\t\t\tuniform vec4 viewport;\n\t\t\tuniform vec4 color;\n\t\t\tuniform vec2 atlasSize, atlasDim, scale, translate, positionOffset;\n\t\t\tvarying vec2 charCoord, charId;\n\t\t\tvarying float charWidth;\n\t\t\tvarying vec4 fontColor;\n\t\t\tvoid main () {\n\t\t\t\t"+(T.normalViewport?"":"vec2 positionOffset = vec2(positionOffset.x,- positionOffset.y);")+"\n\n\t\t\t\tvec2 offset = floor(em * (vec2(align + charOffset, baseline)\n\t\t\t\t\t+ positionOffset))\n\t\t\t\t\t/ (viewport.zw * scale.xy);\n\n\t\t\t\tvec2 position = (position + translate) * scale;\n\t\t\t\tposition += offset * scale;\n\n\t\t\t\t"+(T.normalViewport?"position.y = 1. - position.y;":"")+"\n\n\t\t\t\tcharCoord = position * viewport.zw + viewport.xy;\n\n\t\t\t\tgl_Position = vec4(position * 2. - 1., 0, 1);\n\n\t\t\t\tgl_PointSize = charStep;\n\n\t\t\t\tcharId.x = mod(char, atlasDim.x);\n\t\t\t\tcharId.y = floor(char / atlasDim.x);\n\n\t\t\t\tcharWidth = width * em;\n\n\t\t\t\tfontColor = color / 255.;\n\t\t\t}",frag:"\n\t\t\tprecision highp float;\n\t\t\tuniform sampler2D atlas;\n\t\t\tuniform float fontSize, charStep, opacity;\n\t\t\tuniform vec2 atlasSize;\n\t\t\tuniform vec4 viewport;\n\t\t\tvarying vec4 fontColor;\n\t\t\tvarying vec2 charCoord, charId;\n\t\t\tvarying float charWidth;\n\n\t\t\tfloat lightness(vec4 color) {\n\t\t\t\treturn color.r * 0.299 + color.g * 0.587 + color.b * 0.114;\n\t\t\t}\n\n\t\t\tvoid main () {\n\t\t\t\tvec2 uv = gl_FragCoord.xy - charCoord + charStep * .5;\n\t\t\t\tfloat halfCharStep = floor(charStep * .5 + .5);\n\n\t\t\t\t// invert y and shift by 1px (FF expecially needs that)\n\t\t\t\tuv.y = charStep - uv.y;\n\n\t\t\t\t// ignore points outside of character bounding box\n\t\t\t\tfloat halfCharWidth = ceil(charWidth * .5);\n\t\t\t\tif (floor(uv.x) > halfCharStep + halfCharWidth ||\n\t\t\t\t\tfloor(uv.x) < halfCharStep - halfCharWidth) return;\n\n\t\t\t\tuv += charId * charStep;\n\t\t\t\tuv = uv / atlasSize;\n\n\t\t\t\tvec4 color = fontColor;\n\t\t\t\tvec4 mask = texture2D(atlas, uv);\n\n\t\t\t\tfloat maskY = lightness(mask);\n\t\t\t\t// float colorY = lightness(color);\n\t\t\t\tcolor.a *= maskY;\n\t\t\t\tcolor.a *= opacity;\n\n\t\t\t\t// color.a += .1;\n\n\t\t\t\t// antialiasing, see yiq color space y-channel formula\n\t\t\t\t// color.rgb += (1. - color.rgb) * (1. - mask.rgb);\n\n\t\t\t\tgl_FragColor = color;\n\t\t\t}"});return{regl:t,draw:e,atlas:{}}},T.prototype.update=function(t){var e=this;if("string"==typeof t)t={text:t};else if(!t)return;null!=(t=a(t,{position:"position positions coord coords coordinates",font:"font fontFace fontface typeface cssFont css-font family fontFamily",fontSize:"fontSize fontsize size font-size",text:"text texts chars characters value values symbols",align:"align alignment textAlign textbaseline",baseline:"baseline textBaseline textbaseline",direction:"dir direction textDirection",color:"color colour fill fill-color fillColor textColor textcolor",kerning:"kerning kern",range:"range dataBox",viewport:"vp viewport viewBox viewbox viewPort",opacity:"opacity alpha transparency visible visibility opaque",offset:"offset positionOffset padding shift indent indentation"},!0)).opacity&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map((function(t){return parseFloat(t)})):this.opacity=parseFloat(t.opacity)),null!=t.viewport&&(this.viewport=h(t.viewport),T.normalViewport&&(this.viewport.y=this.canvas.height-this.viewport.y-this.viewport.height),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null==this.viewport&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),null!=t.kerning&&(this.kerning=t.kerning),null!=t.offset&&("number"==typeof t.offset&&(t.offset=[t.offset,0]),this.positionOffset=y(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),this.font.length||t.font||(t.font=T.baseFontSize+"px sans-serif");var r,i=!1,o=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach((function(t,r){if("string"==typeof t)try{t=n.parse(t)}catch(e){t=n.parse(T.baseFontSize+"px "+t)}else t=n.parse(n.stringify(t));var a=n.stringify({size:T.baseFontSize,family:t.family,stretch:_?t.stretch:void 0,variant:t.variant,weight:t.weight,style:t.style}),s=p(t.size),l=Math.round(s[0]*d(s[1]));if(l!==e.fontSize[r]&&(o=!0,e.fontSize[r]=l),!(e.font[r]&&a==e.font[r].baseString||(i=!0,e.font[r]=T.fonts[a],e.font[r]))){var c=t.family.join(", "),u=[t.style];t.style!=t.variant&&u.push(t.variant),t.variant!=t.weight&&u.push(t.weight),_&&t.weight!=t.stretch&&u.push(t.stretch),e.font[r]={baseString:a,family:c,weight:t.weight,stretch:t.stretch,style:t.style,variant:t.variant,width:{},kerning:{},metrics:v(c,{origin:"top",fontSize:T.baseFontSize,fontStyle:u.join(" ")})},T.fonts[a]=e.font[r]}})),(i||o)&&this.font.forEach((function(r,a){var i=n.stringify({size:e.fontSize[a],family:r.family,stretch:_?r.stretch:void 0,variant:r.variant,weight:r.weight,style:r.style});if(e.fontAtlas[a]=e.shader.atlas[i],!e.fontAtlas[a]){var o=r.metrics;e.shader.atlas[i]=e.fontAtlas[a]={fontString:i,step:2*Math.ceil(e.fontSize[a]*o.bottom*.5),em:e.fontSize[a],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:e.regl.texture()}}null==t.text&&(t.text=e.text)})),"string"==typeof t.text&&t.position&&t.position.length>2){for(var s=Array(.5*t.position.length),f=0;f<s.length;f++)s[f]=t.text;t.text=s}if(null!=t.text||i){if(this.textOffsets=[0],Array.isArray(t.text)){this.count=t.text[0].length,this.counts=[this.count];for(var b=1;b<t.text.length;b++)this.textOffsets[b]=this.textOffsets[b-1]+t.text[b-1].length,this.count+=t.text[b].length,this.counts.push(t.text[b].length);this.text=t.text.join("")}else this.text=t.text,this.count=this.text.length,this.counts=[this.count];r=[],this.font.forEach((function(t,n){T.atlasContext.font=t.baseString;for(var a=e.fontAtlas[n],i=0;i<e.text.length;i++){var o=e.text.charAt(i);if(null==a.ids[o]&&(a.ids[o]=a.chars.length,a.chars.push(o),r.push(o)),null==t.width[o]&&(t.width[o]=T.atlasContext.measureText(o).width/T.baseFontSize,e.kerning)){var s=[];for(var l in t.width)s.push(l+o,o+l);m(t.kerning,g(t.family,{pairs:s}))}}}))}if(t.position)if(t.position.length>2){for(var w=!t.position[0].length,k=u.mallocFloat(2*this.count),A=0,M=0;A<this.counts.length;A++){var S=this.counts[A];if(w)for(var E=0;E<S;E++)k[M++]=t.position[2*A],k[M++]=t.position[2*A+1];else for(var C=0;C<S;C++)k[M++]=t.position[A][0],k[M++]=t.position[A][1]}this.position.call?this.position({type:"float",data:k}):this.position=this.regl.buffer({type:"float",data:k}),u.freeFloat(k)}else this.position.destroy&&this.position.destroy(),this.position={constant:t.position};if(t.text||i){var L=u.mallocUint8(this.count),P=u.mallocFloat(2*this.count);this.textWidth=[];for(var I=0,z=0;I<this.counts.length;I++){for(var O=this.counts[I],D=this.font[I]||this.font[0],R=this.fontAtlas[I]||this.fontAtlas[0],F=0;F<O;F++){var B=this.text.charAt(z),N=this.text.charAt(z-1);if(L[z]=R.ids[B],P[2*z]=D.width[B],F){var j=P[2*z-2],V=P[2*z],U=P[2*z-1]+.5*j+.5*V;if(this.kerning){var q=D.kerning[N+B];q&&(U+=.001*q)}P[2*z+1]=U}else P[2*z+1]=.5*P[2*z];z++}this.textWidth.push(P.length?.5*P[2*z-2]+P[2*z-1]:0)}t.align||(t.align=this.align),this.charBuffer({data:L,type:"uint8",usage:"stream"}),this.sizeBuffer({data:P,type:"float",usage:"stream"}),u.freeUint8(L),u.freeFloat(P),r.length&&this.font.forEach((function(t,r){var n=e.fontAtlas[r],a=n.step,i=Math.floor(T.maxAtlasSize/a),o=Math.min(i,n.chars.length),s=Math.ceil(n.chars.length/o),l=x(o*a),u=x(s*a);n.width=l,n.height=u,n.rows=s,n.cols=o,n.em&&n.texture({data:c({canvas:T.atlasCanvas,font:n.fontString,chars:n.chars,shape:[l,u],step:[a,a]})})}))}if(t.align&&(this.align=t.align,this.alignOffset=this.textWidth.map((function(t,r){var n=Array.isArray(e.align)?e.align.length>1?e.align[r]:e.align[0]:e.align;if("number"==typeof n)return n;switch(n){case"right":case"end":return-t;case"center":case"centre":case"middle":return.5*-t}return 0}))),null==this.baseline&&null==t.baseline&&(t.baseline=0),null!=t.baseline&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map((function(t,r){var n=(e.font[r]||e.font[0]).metrics,a=0;return a+=.5*n.bottom,a+="number"==typeof t?t-n.baseline:-n[t],T.normalViewport||(a*=-1),a}))),null!=t.color)if(t.color||(t.color="transparent"),"string"!=typeof t.color&&isNaN(t.color)){var H;if("number"==typeof t.color[0]&&t.color.length>this.counts.length){var G=t.color.length;H=u.mallocUint8(G);for(var Y=(t.color.subarray||t.color.slice).bind(t.color),W=0;W<G;W+=4)H.set(l(Y(W,W+4),"uint8"),W)}else{var Z=t.color.length;H=u.mallocUint8(4*Z);for(var X=0;X<Z;X++)H.set(l(t.color[X]||0,"uint8"),4*X)}this.color=H}else this.color=l(t.color,"uint8");if(t.position||t.text||t.color||t.baseline||t.align||t.font||t.offset||t.opacity)if(this.color.length>4||this.baselineOffset.length>1||this.align&&this.align.length>1||this.fontAtlas.length>1||this.positionOffset.length>2){var J=Math.max(.5*this.position.length||0,.25*this.color.length||0,this.baselineOffset.length||0,this.alignOffset.length||0,this.font.length||0,this.opacity.length||0,.5*this.positionOffset.length||0);this.batch=Array(J);for(var K=0;K<this.batch.length;K++)this.batch[K]={count:this.counts.length>1?this.counts[K]:this.counts[0],offset:this.textOffsets.length>1?this.textOffsets[K]:this.textOffsets[0],color:this.color?this.color.length<=4?this.color:this.color.subarray(4*K,4*K+4):[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[K]:this.opacity,baseline:null!=this.baselineOffset[K]?this.baselineOffset[K]:this.baselineOffset[0],align:this.align?null!=this.alignOffset[K]?this.alignOffset[K]:this.alignOffset[0]:0,atlas:this.fontAtlas[K]||this.fontAtlas[0],positionOffset:this.positionOffset.length>2?this.positionOffset.subarray(2*K,2*K+2):this.positionOffset}}else this.count?this.batch=[{count:this.count,offset:0,color:this.color||[0,0,0,255],opacity:Array.isArray(this.opacity)?this.opacity[0]:this.opacity,baseline:this.baselineOffset[0],align:this.alignOffset?this.alignOffset[0]:0,atlas:this.fontAtlas[0],positionOffset:this.positionOffset}]:this.batch=[]},T.prototype.destroy=function(){},T.prototype.kerning=!0,T.prototype.position={constant:new Float32Array(2)},T.prototype.translate=null,T.prototype.scale=null,T.prototype.font=null,T.prototype.text="",T.prototype.positionOffset=[0,0],T.prototype.opacity=1,T.prototype.color=new Uint8Array([0,0,0,255]),T.prototype.alignOffset=[0,0],T.normalViewport=!1,T.maxAtlasSize=1024,T.atlasCanvas=document.createElement("canvas"),T.atlasContext=T.atlasCanvas.getContext("2d",{alpha:!1}),T.baseFontSize=64,T.fonts={},e.exports=T},{"bit-twiddle":95,"color-normalize":122,"css-font":141,"detect-kerning":167,"es6-weak-map":228,"flatten-vertex-data":239,"font-atlas":240,"font-measure":241,"gl-util/context":323,"is-plain-obj":422,"object-assign":452,"parse-rect":457,"parse-unit":459,"pick-by-alias":463,regl:492,"to-px":530,"typedarray-pool":547}],322:[function(t,e,r){"use strict";var n=t("ndarray"),a=t("ndarray-ops"),i=t("typedarray-pool");e.exports=function(t){if(arguments.length<=1)throw new Error("gl-texture2d: Missing arguments for texture2d constructor");o||c(t);if("number"==typeof arguments[1])return v(t,arguments[1],arguments[2],arguments[3]||t.RGBA,arguments[4]||t.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return 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y=u.size,x=c.indexOf(o)<0;x&&c.push(o);if(d===l&&v)0===u.offset&&u.data.length===y?x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data):x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,u.data.subarray(u.offset,u.offset+y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,u.data.subarray(u.offset,u.offset+y));else{var b;b=l===t.FLOAT?i.mallocFloat32(y):i.mallocUint8(y);var _=n(b,p,[p[2],p[2]*p[0],1]);d===t.FLOAT&&l===t.UNSIGNED_BYTE?h(_,u):a.assign(_,u),x?t.texImage2D(t.TEXTURE_2D,o,s,p[0],p[1],0,s,l,b.subarray(0,y)):t.texSubImage2D(t.TEXTURE_2D,o,e,r,p[0],p[1],s,l,b.subarray(0,y)),l===t.FLOAT?i.freeFloat32(b):i.freeUint8(b)}}(s,e,r,o,this.format,this.type,this._mipLevels,t)}}},{ndarray:448,"ndarray-ops":443,"typedarray-pool":547}],323:[function(t,e,r){(function(r){"use strict";var n=t("pick-by-alias");function 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t=0;t<this._attribs.length;++t)this._attribs[t].bind(this.gl)},i.prototype.unbind=function(){this._ext.bindVertexArrayOES(null)},i.prototype.dispose=function(){this._ext.deleteVertexArrayOES(this.handle)},i.prototype.update=function(t,e,r){if(this.bind(),n(this.gl,e,t),this.unbind(),this._attribs.length=0,t)for(var i=0;i<t.length;++i){var o=t[i];"number"==typeof o?this._attribs.push(new a(i,1,o)):Array.isArray(o)&&this._attribs.push(new a(i,o.length,o[0],o[1],o[2],o[3]))}this._useElements=!!e,this._elementsType=r||this.gl.UNSIGNED_SHORT},i.prototype.draw=function(t,e,r){r=r||0;var n=this.gl;this._useElements?n.drawElements(t,e,this._elementsType,r):n.drawArrays(t,r,e)},e.exports=function(t,e){return new i(t,e,e.createVertexArrayOES())}},{"./do-bind.js":324}],327:[function(t,e,r){"use strict";var n=t("./lib/vao-native.js"),a=t("./lib/vao-emulated.js");function 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* @license MIT
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e.exports=function(t){return null!=t&&(n(t)||function(t){return"function"==typeof t.readFloatLE&&"function"==typeof t.slice&&n(t.slice(0,0))}(t)||!!t._isBuffer)}},{}],419:[function(t,e,r){"use strict";e.exports="undefined"!=typeof navigator&&(/MSIE/.test(navigator.userAgent)||/Trident\//.test(navigator.appVersion))},{}],420:[function(t,e,r){"use strict";e.exports=i,e.exports.isMobile=i,e.exports.default=i;var n=/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series[46]0|symbian|treo|up\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,a=/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( 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t={},e=0,r=Object.keys(this._values);e<r.length;e+=1){var n=r[e],a=this.getValue(n);void 0!==a&&(t[n]=a)}return t},ua.prototype.possiblyEvaluate=function(t,e,r){for(var n=new fa(this._properties),a=0,i=Object.keys(this._values);a<i.length;a+=1){var o=i[a];n._values[o]=this._values[o].possiblyEvaluate(t,e,r)}return n};var ha=function(t,e,r){this.property=t,this.value=e,this.parameters=r};ha.prototype.isConstant=function(){return"constant"===this.value.kind},ha.prototype.constantOr=function(t){return"constant"===this.value.kind?this.value.value:t},ha.prototype.evaluate=function(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)};var fa=function(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)};fa.prototype.get=function(t){return this._values[t]};var pa=function(t){this.specification=t};pa.prototype.possiblyEvaluate=function(t,e){return t.expression.evaluate(e)},pa.prototype.interpolate=function(t,e,r){var n=Ue[this.specification.type];return n?n(t,e,r):t};var da=function(t,e){this.specification=t,this.overrides=e};da.prototype.possiblyEvaluate=function(t,e,r,n){return new ha(this,"constant"===t.expression.kind||"camera"===t.expression.kind?{kind:"constant",value:t.expression.evaluate(e,null,{},r,n)}:t.expression,e)},da.prototype.interpolate=function(t,e,r){if("constant"!==t.value.kind||"constant"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new ha(this,{kind:"constant",value:void 0},t.parameters);var n=Ue[this.specification.type];return n?new ha(this,{kind:"constant",value:n(t.value.value,e.value.value,r)},t.parameters):t},da.prototype.evaluate=function(t,e,r,n,a,i){return"constant"===t.kind?t.value:t.evaluate(e,r,n,a,i)};var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0===t.value)return new ha(this,{kind:"constant",value:void 0},e);if("constant"===t.expression.kind){var a=t.expression.evaluate(e,null,{},r,n),i="resolvedImage"===t.property.specification.type&&"string"!=typeof a?a.name:a,o=this._calculate(i,i,i,e);return new ha(this,{kind:"constant",value:o},e)}if("camera"===t.expression.kind){var s=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new ha(this,{kind:"constant",value:s},e)}return new ha(this,t.expression,e)},e.prototype.evaluate=function(t,e,r,n,a,i){if("source"===t.kind){var o=t.evaluate(e,r,n,a,i);return this._calculate(o,o,o,e)}return"composite"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value},e.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},e.prototype.interpolate=function(t){return t},e}(da),ma=function(t){this.specification=t};ma.prototype.possiblyEvaluate=function(t,e,r,n){if(void 0!==t.value){if("constant"===t.expression.kind){var a=t.expression.evaluate(e,null,{},r,n);return this._calculate(a,a,a,e)}return this._calculate(t.expression.evaluate(new aa(Math.floor(e.zoom-1),e)),t.expression.evaluate(new aa(Math.floor(e.zoom),e)),t.expression.evaluate(new aa(Math.floor(e.zoom+1),e)),e)}},ma.prototype._calculate=function(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}},ma.prototype.interpolate=function(t){return t};var va=function(t){this.specification=t};va.prototype.possiblyEvaluate=function(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)},va.prototype.interpolate=function(){return!1};var ya=function(t){for(var e in this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[],t){var r=t[e];r.specification.overridable&&this.overridableProperties.push(e);var n=this.defaultPropertyValues[e]=new ia(r,void 0),a=this.defaultTransitionablePropertyValues[e]=new oa(r);this.defaultTransitioningPropertyValues[e]=a.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}};Dn("DataDrivenProperty",da),Dn("DataConstantProperty",pa),Dn("CrossFadedDataDrivenProperty",ga),Dn("CrossFadedProperty",ma),Dn("ColorRampProperty",va);var xa=function(t){function e(e,r){if(t.call(this),this.id=e.id,this.type=e.type,this._featureFilter={filter:function(){return!0},needGeometry:!1},"custom"!==e.type&&(this.metadata=(e=e).metadata,this.minzoom=e.minzoom,this.maxzoom=e.maxzoom,"background"!==e.type&&(this.source=e.source,this.sourceLayer=e["source-layer"],this.filter=e.filter),r.layout&&(this._unevaluatedLayout=new ua(r.layout)),r.paint)){for(var n in this._transitionablePaint=new sa(r.paint),e.paint)this.setPaintProperty(n,e.paint[n],{validate:!1});for(var a in e.layout)this.setLayoutProperty(a,e.layout[a],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new fa(r.paint)}}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getCrossfadeParameters=function(){return this._crossfadeParameters},e.prototype.getLayoutProperty=function(t){return"visibility"===t?this.visibility:this._unevaluatedLayout.getValue(t)},e.prototype.setLayoutProperty=function(t,e,r){void 0===r&&(r={}),null!=e&&this._validate(En,"layers."+this.id+".layout."+t,t,e,r)||("visibility"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e)},e.prototype.getPaintProperty=function(t){return m(t,"-transition")?this._transitionablePaint.getTransition(t.slice(0,-"-transition".length)):this._transitionablePaint.getValue(t)},e.prototype.setPaintProperty=function(t,e,r){if(void 0===r&&(r={}),null!=e&&this._validate(Sn,"layers."+this.id+".paint."+t,t,e,r))return!1;if(m(t,"-transition"))return this._transitionablePaint.setTransition(t.slice(0,-"-transition".length),e||void 0),!1;var n=this._transitionablePaint._values[t],a="cross-faded-data-driven"===n.property.specification["property-type"],i=n.value.isDataDriven(),o=n.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);var s=this._transitionablePaint._values[t].value;return s.isDataDriven()||i||a||this._handleOverridablePaintPropertyUpdate(t,o,s)},e.prototype._handleSpecialPaintPropertyUpdate=function(t){},e.prototype._handleOverridablePaintPropertyUpdate=function(t,e,r){return!1},e.prototype.isHidden=function(t){return!!(this.minzoom&&t<this.minzoom)||!!(this.maxzoom&&t>=this.maxzoom)||"none"===this.visibility},e.prototype.updateTransitions=function(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)},e.prototype.hasTransition=function(){return this._transitioningPaint.hasTransition()},e.prototype.recalculate=function(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)},e.prototype.serialize=function(){var t={id:this.id,type:this.type,source:this.source,"source-layer":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),y(t,(function(t,e){return!(void 0===t||"layout"===e&&!Object.keys(t).length||"paint"===e&&!Object.keys(t).length)}))},e.prototype._validate=function(t,e,r,n,a){return void 0===a&&(a={}),(!a||!1!==a.validate)&&Cn(this,t.call(An,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Mt,style:{glyphs:!0,sprite:!0}}))},e.prototype.is3D=function(){return!1},e.prototype.isTileClipped=function(){return!1},e.prototype.hasOffscreenPass=function(){return!1},e.prototype.resize=function(){},e.prototype.isStateDependent=function(){for(var t in this.paint._values){var e=this.paint.get(t);if(e instanceof ha&&Lr(e.property.specification)&&("source"===e.value.kind||"composite"===e.value.kind)&&e.value.isStateDependent)return!0}return!1},e}(At),ba={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array},_a=function(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8},wa=function(){this.isTransferred=!1,this.capacity=-1,this.resize(0)};function Ta(t,e){void 0===e&&(e=1);var r=0,n=0;return{members:t.map((function(t){var a=ba[t.type].BYTES_PER_ELEMENT,i=r=ka(r,Math.max(e,a)),o=t.components||1;return n=Math.max(n,a),r+=a*o,{name:t.name,type:t.type,components:o,offset:i}})),size:ka(r,Math.max(n,e)),alignment:e}}function ka(t,e){return Math.ceil(t/e)*e}wa.serialize=function(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}},wa.deserialize=function(t){var e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e},wa.prototype._trim=function(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())},wa.prototype.clear=function(){this.length=0},wa.prototype.resize=function(t){this.reserve(t),this.length=t},wa.prototype.reserve=function(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);var e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}},wa.prototype._refreshViews=function(){throw new Error("_refreshViews() must be implemented by each concrete StructArray layout")};var Aa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t},e}(wa);Aa.prototype.bytesPerElement=4,Dn("StructArrayLayout2i4",Aa);var Ma=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=4*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,this.int16[i+3]=a,t},e}(wa);Ma.prototype.bytesPerElement=8,Dn("StructArrayLayout4i8",Ma);var Sa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=a,this.int16[s+4]=i,this.int16[s+5]=o,t},e}(wa);Sa.prototype.bytesPerElement=12,Dn("StructArrayLayout2i4i12",Sa);var Ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=a,this.uint8[l+6]=i,this.uint8[l+7]=o,t},e}(wa);Ea.prototype.bytesPerElement=8,Dn("StructArrayLayout2i4ub8",Ea);var Ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c){var u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,a,i,o,s,l,c)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u){var h=9*t,f=18*t;return this.uint16[h+0]=e,this.uint16[h+1]=r,this.uint16[h+2]=n,this.uint16[h+3]=a,this.uint16[h+4]=i,this.uint16[h+5]=o,this.uint16[h+6]=s,this.uint16[h+7]=l,this.uint8[f+16]=c,this.uint8[f+17]=u,t},e}(wa);Ca.prototype.bytesPerElement=18,Dn("StructArrayLayout8ui2ub18",Ca);var La=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u,h){var f=this.length;return this.resize(f+1),this.emplace(f,t,e,r,n,a,i,o,s,l,c,u,h)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h,f){var p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=a,this.uint16[p+4]=i,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=h,this.int16[p+11]=f,t},e}(wa);La.prototype.bytesPerElement=24,Dn("StructArrayLayout4i4ui4i24",La);var Pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,t},e}(wa);Pa.prototype.bytesPerElement=12,Dn("StructArrayLayout3f12",Pa);var Ia=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.uint32[1*t+0]=e,t},e}(wa);Ia.prototype.bytesPerElement=4,Dn("StructArrayLayout1ul4",Ia);var za=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l){var c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,a,i,o,s,l)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c){var u=10*t,h=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=a,this.int16[u+4]=i,this.int16[u+5]=o,this.uint32[h+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t},e}(wa);za.prototype.bytesPerElement=20,Dn("StructArrayLayout6i1ul2ui20",za);var Oa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i){var o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,a,i)},e.prototype.emplace=function(t,e,r,n,a,i,o){var s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=a,this.int16[s+4]=i,this.int16[s+5]=o,t},e}(wa);Oa.prototype.bytesPerElement=12,Dn("StructArrayLayout2i2i2i12",Oa);var Da=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n,a)},e.prototype.emplace=function(t,e,r,n,a,i){var o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=a,this.int16[s+7]=i,t},e}(wa);Da.prototype.bytesPerElement=16,Dn("StructArrayLayout2f1f2i16",Da);var Ra=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=12*t,o=3*t;return this.uint8[i+0]=e,this.uint8[i+1]=r,this.float32[o+1]=n,this.float32[o+2]=a,t},e}(wa);Ra.prototype.bytesPerElement=12,Dn("StructArrayLayout2ub2f12",Ra);var Fa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.uint16[a+0]=e,this.uint16[a+1]=r,this.uint16[a+2]=n,t},e}(wa);Fa.prototype.bytesPerElement=6,Dn("StructArrayLayout3ui6",Fa);var Ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m){var v=this.length;return this.resize(v+1),this.emplace(v,t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m,v){var y=24*t,x=12*t,b=48*t;return this.int16[y+0]=e,this.int16[y+1]=r,this.uint16[y+2]=n,this.uint16[y+3]=a,this.uint32[x+2]=i,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[y+10]=l,this.uint16[y+11]=c,this.uint16[y+12]=u,this.float32[x+7]=h,this.float32[x+8]=f,this.uint8[b+36]=p,this.uint8[b+37]=d,this.uint8[b+38]=g,this.uint32[x+10]=m,this.int16[y+22]=v,t},e}(wa);Ba.prototype.bytesPerElement=48,Dn("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",Ba);var Na=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g,m,v,y,x,b,_,w,T,k,A,M,S,E){var C=34*t,L=17*t;return this.int16[C+0]=e,this.int16[C+1]=r,this.int16[C+2]=n,this.int16[C+3]=a,this.int16[C+4]=i,this.int16[C+5]=o,this.int16[C+6]=s,this.int16[C+7]=l,this.uint16[C+8]=c,this.uint16[C+9]=u,this.uint16[C+10]=h,this.uint16[C+11]=f,this.uint16[C+12]=p,this.uint16[C+13]=d,this.uint16[C+14]=g,this.uint16[C+15]=m,this.uint16[C+16]=v,this.uint16[C+17]=y,this.uint16[C+18]=x,this.uint16[C+19]=b,this.uint16[C+20]=_,this.uint16[C+21]=w,this.uint16[C+22]=T,this.uint32[L+12]=k,this.float32[L+13]=A,this.float32[L+14]=M,this.float32[L+15]=S,this.float32[L+16]=E,t},e}(wa);Na.prototype.bytesPerElement=68,Dn("StructArrayLayout8i15ui1ul4f68",Na);var ja=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.float32[1*t+0]=e,t},e}(wa);ja.prototype.bytesPerElement=4,Dn("StructArrayLayout1f4",ja);var Va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=3*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,t},e}(wa);Va.prototype.bytesPerElement=6,Dn("StructArrayLayout3i6",Va);var Ua=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var a=4*t;return this.uint32[2*t+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(wa);Ua.prototype.bytesPerElement=8,Dn("StructArrayLayout1ul2ui8",Ua);var qa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(wa);qa.prototype.bytesPerElement=4,Dn("StructArrayLayout2ui4",qa);var Ha=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){return this.uint16[1*t+0]=e,t},e}(wa);Ha.prototype.bytesPerElement=2,Dn("StructArrayLayout1ui2",Ha);var Ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t},e}(wa);Ga.prototype.bytesPerElement=8,Dn("StructArrayLayout2f8",Ga);var Ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,a){var i=4*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,this.float32[i+3]=a,t},e}(wa);Ya.prototype.bytesPerElement=16,Dn("StructArrayLayout4f16",Ya);var Wa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(_a);Wa.prototype.size=20;var Za=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.get=function(t){return new Wa(this,t)},e}(za);Dn("CollisionBoxArray",Za);var Xa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(_a);Xa.prototype.size=48;var Ja=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.get=function(t){return new Xa(this,t)},e}(Ba);Dn("PlacedSymbolArray",Ja);var Ka=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+12]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},r.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},r.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},r.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(e.prototype,r),e}(_a);Ka.prototype.size=68;var Qa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.get=function(t){return new Ka(this,t)},e}(Na);Dn("SymbolInstanceArray",Qa);var $a=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e}(ja);Dn("GlyphOffsetArray",$a);var ti=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e}(Va);Dn("SymbolLineVertexArray",ti);var ei=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+3]},Object.defineProperties(e.prototype,r),e}(_a);ei.prototype.size=8;var ri=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.get=function(t){return new ei(this,t)},e}(Ua);Dn("FeatureIndexArray",ri);var ni=Ta([{name:"a_pos",components:2,type:"Int16"}],4).members,ai=function(t){void 0===t&&(t=[]),this.segments=t};function ii(t,e){return 256*(t=l(Math.floor(t),0,255))+l(Math.floor(e),0,255)}ai.prototype.prepareSegment=function(t,e,r,n){var a=this.segments[this.segments.length-1];return t>ai.MAX_VERTEX_ARRAY_LENGTH&&_("Max vertices per segment is "+ai.MAX_VERTEX_ARRAY_LENGTH+": bucket requested "+t),(!a||a.vertexLength+t>ai.MAX_VERTEX_ARRAY_LENGTH||a.sortKey!==n)&&(a={vertexOffset:e.length,primitiveOffset:r.length,vertexLength:0,primitiveLength:0},void 0!==n&&(a.sortKey=n),this.segments.push(a)),a},ai.prototype.get=function(){return this.segments},ai.prototype.destroy=function(){for(var t=0,e=this.segments;t<e.length;t+=1){var r=e[t];for(var n in r.vaos)r.vaos[n].destroy()}},ai.simpleSegment=function(t,e,r,n){return new ai([{vertexOffset:t,primitiveOffset:e,vertexLength:r,primitiveLength:n,vaos:{},sortKey:0}])},ai.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,Dn("SegmentVector",ai);var oi=Ta([{name:"a_pattern_from",components:4,type:"Uint16"},{name:"a_pattern_to",components:4,type:"Uint16"},{name:"a_pixel_ratio_from",components:1,type:"Uint8"},{name:"a_pixel_ratio_to",components:1,type:"Uint8"}]),si=e((function(t){t.exports=function(t,e){var r,n,a,i,o,s,l,c;for(n=t.length-(r=3&t.length),a=e,o=3432918353,s=461845907,c=0;c<n;)l=255&t.charCodeAt(c)|(255&t.charCodeAt(++c))<<8|(255&t.charCodeAt(++c))<<16|(255&t.charCodeAt(++c))<<24,++c,a=27492+(65535&(i=5*(65535&(a=(a^=l=(65535&(l=(l=(65535&l)*o+(((l>>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295)<<13|a>>>19))+((5*(a>>>16)&65535)<<16)&4294967295))+((58964+(i>>>16)&65535)<<16);switch(l=0,r){case 3:l^=(255&t.charCodeAt(c+2))<<16;case 2:l^=(255&t.charCodeAt(c+1))<<8;case 1:a^=l=(65535&(l=(l=(65535&(l^=255&t.charCodeAt(c)))*o+(((l>>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295}return a^=t.length,a=2246822507*(65535&(a^=a>>>16))+((2246822507*(a>>>16)&65535)<<16)&4294967295,a=3266489909*(65535&(a^=a>>>13))+((3266489909*(a>>>16)&65535)<<16)&4294967295,(a^=a>>>16)>>>0}})),li=e((function(t){t.exports=function(t,e){for(var r,n=t.length,a=e^n,i=0;n>=4;)r=1540483477*(65535&(r=255&t.charCodeAt(i)|(255&t.charCodeAt(++i))<<8|(255&t.charCodeAt(++i))<<16|(255&t.charCodeAt(++i))<<24))+((1540483477*(r>>>16)&65535)<<16),a=1540483477*(65535&a)+((1540483477*(a>>>16)&65535)<<16)^(r=1540483477*(65535&(r^=r>>>24))+((1540483477*(r>>>16)&65535)<<16)),n-=4,++i;switch(n){case 3:a^=(255&t.charCodeAt(i+2))<<16;case 2:a^=(255&t.charCodeAt(i+1))<<8;case 1:a=1540483477*(65535&(a^=255&t.charCodeAt(i)))+((1540483477*(a>>>16)&65535)<<16)}return a=1540483477*(65535&(a^=a>>>13))+((1540483477*(a>>>16)&65535)<<16),(a^=a>>>15)>>>0}})),ci=si,ui=li;ci.murmur3=si,ci.murmur2=ui;var hi=function(){this.ids=[],this.positions=[],this.indexed=!1};hi.prototype.add=function(t,e,r,n){this.ids.push(pi(t)),this.positions.push(e,r,n)},hi.prototype.getPositions=function(t){for(var e=pi(t),r=0,n=this.ids.length-1;r<n;){var a=r+n>>1;this.ids[a]>=e?n=a:r=a+1}for(var i=[];this.ids[r]===e;)i.push({index:this.positions[3*r],start:this.positions[3*r+1],end:this.positions[3*r+2]}),r++;return i},hi.serialize=function(t,e){var r=new Float64Array(t.ids),n=new Uint32Array(t.positions);return function t(e,r,n,a){for(;n<a;){for(var i=e[n+a>>1],o=n-1,s=a+1;;){do{o++}while(e[o]<i);do{s--}while(e[s]>i);if(o>=s)break;di(e,o,s),di(r,3*o,3*s),di(r,3*o+1,3*s+1),di(r,3*o+2,3*s+2)}s-n<a-s?(t(e,r,n,s),n=s+1):(t(e,r,s+1,a),a=s)}}(r,n,0,r.length-1),e&&e.push(r.buffer,n.buffer),{ids:r,positions:n}},hi.deserialize=function(t){var e=new hi;return e.ids=t.ids,e.positions=t.positions,e.indexed=!0,e};var fi=Math.pow(2,53)-1;function pi(t){var e=+t;return!isNaN(e)&&e<=fi?e:ci(String(t))}function di(t,e,r){var n=t[e];t[e]=t[r],t[r]=n}Dn("FeaturePositionMap",hi);var gi=function(t,e){this.gl=t.gl,this.location=e},mi=function(t){function e(e,r){t.call(this,e,r),this.current=0}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1i(this.location,t))},e}(gi),vi=function(t){function e(e,r){t.call(this,e,r),this.current=0}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){this.current!==t&&(this.current=t,this.gl.uniform1f(this.location,t))},e}(gi),yi=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0]}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]||(this.current=t,this.gl.uniform2f(this.location,t[0],t[1]))},e}(gi),xi=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0,0]}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]&&t[2]===this.current[2]||(this.current=t,this.gl.uniform3f(this.location,t[0],t[1],t[2]))},e}(gi),bi=function(t){function e(e,r){t.call(this,e,r),this.current=[0,0,0,0]}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){t[0]===this.current[0]&&t[1]===this.current[1]&&t[2]===this.current[2]&&t[3]===this.current[3]||(this.current=t,this.gl.uniform4f(this.location,t[0],t[1],t[2],t[3]))},e}(gi),_i=function(t){function e(e,r){t.call(this,e,r),this.current=Kt.transparent}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){t.r===this.current.r&&t.g===this.current.g&&t.b===this.current.b&&t.a===this.current.a||(this.current=t,this.gl.uniform4f(this.location,t.r,t.g,t.b,t.a))},e}(gi),wi=new Float32Array(16),Ti=function(t){function e(e,r){t.call(this,e,r),this.current=wi}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){if(t[12]!==this.current[12]||t[0]!==this.current[0])return this.current=t,void this.gl.uniformMatrix4fv(this.location,!1,t);for(var e=1;e<16;e++)if(t[e]!==this.current[e]){this.current=t,this.gl.uniformMatrix4fv(this.location,!1,t);break}},e}(gi);function ki(t){return[ii(255*t.r,255*t.g),ii(255*t.b,255*t.a)]}var Ai=function(t,e,r){this.value=t,this.uniformNames=e.map((function(t){return"u_"+t})),this.type=r};Ai.prototype.setUniform=function(t,e,r){t.set(r.constantOr(this.value))},Ai.prototype.getBinding=function(t,e,r){return"color"===this.type?new _i(t,e):new vi(t,e)};var Mi=function(t,e){this.uniformNames=e.map((function(t){return"u_"+t})),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1};Mi.prototype.setConstantPatternPositions=function(t,e){this.pixelRatioFrom=e.pixelRatio,this.pixelRatioTo=t.pixelRatio,this.patternFrom=e.tlbr,this.patternTo=t.tlbr},Mi.prototype.setUniform=function(t,e,r,n){var a="u_pattern_to"===n?this.patternTo:"u_pattern_from"===n?this.patternFrom:"u_pixel_ratio_to"===n?this.pixelRatioTo:"u_pixel_ratio_from"===n?this.pixelRatioFrom:null;a&&t.set(a)},Mi.prototype.getBinding=function(t,e,r){return"u_pattern"===r.substr(0,9)?new bi(t,e):new vi(t,e)};var Si=function(t,e,r,n){this.expression=t,this.type=r,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:"a_"+t,type:"Float32",components:"color"===r?2:1,offset:0}})),this.paintVertexArray=new n};Si.prototype.populatePaintArray=function(t,e,r,n,a){var i=this.paintVertexArray.length,o=this.expression.evaluate(new aa(0),e,{},n,[],a);this.paintVertexArray.resize(t),this._setPaintValue(i,t,o)},Si.prototype.updatePaintArray=function(t,e,r,n){var a=this.expression.evaluate({zoom:0},r,n);this._setPaintValue(t,e,a)},Si.prototype._setPaintValue=function(t,e,r){if("color"===this.type)for(var n=ki(r),a=t;a<e;a++)this.paintVertexArray.emplace(a,n[0],n[1]);else{for(var i=t;i<e;i++)this.paintVertexArray.emplace(i,r);this.maxValue=Math.max(this.maxValue,Math.abs(r))}},Si.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Si.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()};var Ei=function(t,e,r,n,a,i){this.expression=t,this.uniformNames=e.map((function(t){return"u_"+t+"_t"})),this.type=r,this.useIntegerZoom=n,this.zoom=a,this.maxValue=0,this.paintVertexAttributes=e.map((function(t){return{name:"a_"+t,type:"Float32",components:"color"===r?4:2,offset:0}})),this.paintVertexArray=new i};Ei.prototype.populatePaintArray=function(t,e,r,n,a){var i=this.expression.evaluate(new aa(this.zoom),e,{},n,[],a),o=this.expression.evaluate(new aa(this.zoom+1),e,{},n,[],a),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,i,o)},Ei.prototype.updatePaintArray=function(t,e,r,n){var a=this.expression.evaluate({zoom:this.zoom},r,n),i=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,a,i)},Ei.prototype._setPaintValue=function(t,e,r,n){if("color"===this.type)for(var a=ki(r),i=ki(n),o=t;o<e;o++)this.paintVertexArray.emplace(o,a[0],a[1],i[0],i[1]);else{for(var s=t;s<e;s++)this.paintVertexArray.emplace(s,r,n);this.maxValue=Math.max(this.maxValue,Math.abs(r),Math.abs(n))}},Ei.prototype.upload=function(t){this.paintVertexArray&&this.paintVertexArray.arrayBuffer&&(this.paintVertexBuffer&&this.paintVertexBuffer.buffer?this.paintVertexBuffer.updateData(this.paintVertexArray):this.paintVertexBuffer=t.createVertexBuffer(this.paintVertexArray,this.paintVertexAttributes,this.expression.isStateDependent))},Ei.prototype.destroy=function(){this.paintVertexBuffer&&this.paintVertexBuffer.destroy()},Ei.prototype.setUniform=function(t,e){var r=this.useIntegerZoom?Math.floor(e.zoom):e.zoom,n=l(this.expression.interpolationFactor(r,this.zoom,this.zoom+1),0,1);t.set(n)},Ei.prototype.getBinding=function(t,e,r){return new vi(t,e)};var Ci=function(t,e,r,n,a,i){this.expression=t,this.type=e,this.useIntegerZoom=r,this.zoom=n,this.layerId=i,this.zoomInPaintVertexArray=new a,this.zoomOutPaintVertexArray=new a};Ci.prototype.populatePaintArray=function(t,e,r){var n=this.zoomInPaintVertexArray.length;this.zoomInPaintVertexArray.resize(t),this.zoomOutPaintVertexArray.resize(t),this._setPaintValues(n,t,e.patterns&&e.patterns[this.layerId],r)},Ci.prototype.updatePaintArray=function(t,e,r,n,a){this._setPaintValues(t,e,r.patterns&&r.patterns[this.layerId],a)},Ci.prototype._setPaintValues=function(t,e,r,n){if(n&&r){var a=n[r.min],i=n[r.mid],o=n[r.max];if(a&&i&&o)for(var s=t;s<e;s++)this.zoomInPaintVertexArray.emplace(s,i.tl[0],i.tl[1],i.br[0],i.br[1],a.tl[0],a.tl[1],a.br[0],a.br[1],i.pixelRatio,a.pixelRatio),this.zoomOutPaintVertexArray.emplace(s,i.tl[0],i.tl[1],i.br[0],i.br[1],o.tl[0],o.tl[1],o.br[0],o.br[1],i.pixelRatio,o.pixelRatio)}},Ci.prototype.upload=function(t){this.zoomInPaintVertexArray&&this.zoomInPaintVertexArray.arrayBuffer&&this.zoomOutPaintVertexArray&&this.zoomOutPaintVertexArray.arrayBuffer&&(this.zoomInPaintVertexBuffer=t.createVertexBuffer(this.zoomInPaintVertexArray,oi.members,this.expression.isStateDependent),this.zoomOutPaintVertexBuffer=t.createVertexBuffer(this.zoomOutPaintVertexArray,oi.members,this.expression.isStateDependent))},Ci.prototype.destroy=function(){this.zoomOutPaintVertexBuffer&&this.zoomOutPaintVertexBuffer.destroy(),this.zoomInPaintVertexBuffer&&this.zoomInPaintVertexBuffer.destroy()};var Li=function(t,e,r,n){this.binders={},this.layoutAttributes=n,this._buffers=[];var a=[];for(var i in t.paint._values)if(r(i)){var o=t.paint.get(i);if(o instanceof ha&&Lr(o.property.specification)){var s=Ii(i,t.type),l=o.value,c=o.property.specification.type,u=o.property.useIntegerZoom,h=o.property.specification["property-type"],f="cross-faded"===h||"cross-faded-data-driven"===h;if("constant"===l.kind)this.binders[i]=f?new Mi(l.value,s):new Ai(l.value,s,c),a.push("/u_"+i);else if("source"===l.kind||f){var p=zi(i,c,"source");this.binders[i]=f?new Ci(l,c,u,e,p,t.id):new Si(l,s,c,p),a.push("/a_"+i)}else{var d=zi(i,c,"composite");this.binders[i]=new Ei(l,s,c,u,e,d),a.push("/z_"+i)}}}this.cacheKey=a.sort().join("")};Li.prototype.getMaxValue=function(t){var e=this.binders[t];return e instanceof Si||e instanceof Ei?e.maxValue:0},Li.prototype.populatePaintArrays=function(t,e,r,n,a){for(var i in this.binders){var o=this.binders[i];(o instanceof Si||o instanceof Ei||o instanceof Ci)&&o.populatePaintArray(t,e,r,n,a)}},Li.prototype.setConstantPatternPositions=function(t,e){for(var r in this.binders){var n=this.binders[r];n instanceof Mi&&n.setConstantPatternPositions(t,e)}},Li.prototype.updatePaintArrays=function(t,e,r,n,a){var i=!1;for(var o in t)for(var s=0,l=e.getPositions(o);s<l.length;s+=1){var c=l[s],u=r.feature(c.index);for(var h in this.binders){var f=this.binders[h];if((f instanceof Si||f instanceof Ei||f instanceof Ci)&&!0===f.expression.isStateDependent){var p=n.paint.get(h);f.expression=p.value,f.updatePaintArray(c.start,c.end,u,t[o],a),i=!0}}}return i},Li.prototype.defines=function(){var t=[];for(var e in this.binders){var r=this.binders[e];(r instanceof Ai||r instanceof Mi)&&t.push.apply(t,r.uniformNames.map((function(t){return"#define HAS_UNIFORM_"+t})))}return t},Li.prototype.getPaintVertexBuffers=function(){return this._buffers},Li.prototype.getUniforms=function(t,e){var r=[];for(var n in this.binders){var a=this.binders[n];if(a instanceof Ai||a instanceof Mi||a instanceof Ei)for(var i=0,o=a.uniformNames;i<o.length;i+=1){var s=o[i];if(e[s]){var l=a.getBinding(t,e[s],s);r.push({name:s,property:n,binding:l})}}}return r},Li.prototype.setUniforms=function(t,e,r,n){for(var a=0,i=e;a<i.length;a+=1){var o=i[a],s=o.name,l=o.property;this.binders[l].setUniform(o.binding,n,r.get(l),s)}},Li.prototype.updatePaintBuffers=function(t){for(var e in this._buffers=[],this.binders){var r=this.binders[e];if(t&&r instanceof Ci){var n=2===t.fromScale?r.zoomInPaintVertexBuffer:r.zoomOutPaintVertexBuffer;n&&this._buffers.push(n)}else(r instanceof Si||r instanceof Ei)&&r.paintVertexBuffer&&this._buffers.push(r.paintVertexBuffer)}},Li.prototype.upload=function(t){for(var e in this.binders){var r=this.binders[e];(r instanceof Si||r instanceof Ei||r instanceof Ci)&&r.upload(t)}this.updatePaintBuffers()},Li.prototype.destroy=function(){for(var t in this.binders){var e=this.binders[t];(e instanceof Si||e instanceof Ei||e instanceof Ci)&&e.destroy()}};var Pi=function(t,e,r,n){void 0===n&&(n=function(){return!0}),this.programConfigurations={};for(var a=0,i=e;a<i.length;a+=1){var o=i[a];this.programConfigurations[o.id]=new Li(o,r,n,t)}this.needsUpload=!1,this._featureMap=new hi,this._bufferOffset=0};function Ii(t,e){return{"text-opacity":["opacity"],"icon-opacity":["opacity"],"text-color":["fill_color"],"icon-color":["fill_color"],"text-halo-color":["halo_color"],"icon-halo-color":["halo_color"],"text-halo-blur":["halo_blur"],"icon-halo-blur":["halo_blur"],"text-halo-width":["halo_width"],"icon-halo-width":["halo_width"],"line-gap-width":["gapwidth"],"line-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-extrusion-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"]}[t]||[t.replace(e+"-","").replace(/-/g,"_")]}function zi(t,e,r){var n={color:{source:Ga,composite:Ya},number:{source:ja,composite:Ga}},a=function(t){return{"line-pattern":{source:Ca,composite:Ca},"fill-pattern":{source:Ca,composite:Ca},"fill-extrusion-pattern":{source:Ca,composite:Ca}}[t]}(t);return a&&a[r]||n[e][r]}Pi.prototype.populatePaintArrays=function(t,e,r,n,a,i){for(var o in this.programConfigurations)this.programConfigurations[o].populatePaintArrays(t,e,n,a,i);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0},Pi.prototype.updatePaintArrays=function(t,e,r,n){for(var a=0,i=r;a<i.length;a+=1){var o=i[a];this.needsUpload=this.programConfigurations[o.id].updatePaintArrays(t,this._featureMap,e,o,n)||this.needsUpload}},Pi.prototype.get=function(t){return this.programConfigurations[t]},Pi.prototype.upload=function(t){if(this.needsUpload){for(var e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}},Pi.prototype.destroy=function(){for(var t in this.programConfigurations)this.programConfigurations[t].destroy()},Dn("ConstantBinder",Ai),Dn("CrossFadedConstantBinder",Mi),Dn("SourceExpressionBinder",Si),Dn("CrossFadedCompositeBinder",Ci),Dn("CompositeExpressionBinder",Ei),Dn("ProgramConfiguration",Li,{omit:["_buffers"]}),Dn("ProgramConfigurationSet",Pi);var Oi={min:-1*Math.pow(2,14),max:Math.pow(2,14)-1};function Di(t){for(var e=8192/t.extent,r=t.loadGeometry(),n=0;n<r.length;n++)for(var a=r[n],i=0;i<a.length;i++){var o=a[i];o.x=Math.round(o.x*e),o.y=Math.round(o.y*e),(o.x<Oi.min||o.x>Oi.max||o.y<Oi.min||o.y>Oi.max)&&(_("Geometry exceeds allowed extent, reduce your vector tile buffer size"),o.x=l(o.x,Oi.min,Oi.max),o.y=l(o.y,Oi.min,Oi.max))}return r}function Ri(t,e,r,n,a){t.emplaceBack(2*e+(n+1)/2,2*r+(a+1)/2)}var Fi=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new 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n=t.readVarint()>>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}function ds(t,e,r){if(3===t){var n=new hs(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}fs.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new ss(this._pbf,e,this.extent,this._keys,this._values)};var gs={VectorTile:function(t,e){this.layers=t.readFields(ds,{},e)},VectorTileFeature:ss,VectorTileLayer:hs},ms=gs.VectorTileFeature.types,vs=Math.pow(2,13);function ys(t,e,r,n,a,i,o,s){t.emplaceBack(e,r,2*Math.floor(n*vs)+o,a*vs*2,i*vs*2,Math.round(s))}var xs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new Sa,this.indexArray=new Fa,this.programConfigurations=new Pi(os,t.layers,t.zoom),this.segments=new ai,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};function bs(t,e){return t.x===e.x&&(t.x<0||t.x>8192)||t.y===e.y&&(t.y<0||t.y>8192)}xs.prototype.populate=function(t,e,r){this.features=[],this.hasPattern=ts("fill-extrusion",this.layers,e);for(var n=0,a=t;n<a.length;n+=1){var i=a[n],o=i.feature,s=i.id,l=i.index,c=i.sourceLayerIndex,u=this.layers[0]._featureFilter.needGeometry,h={type:o.type,id:s,properties:o.properties,geometry:u?Di(o):[]};if(this.layers[0]._featureFilter.filter(new aa(this.zoom),h,r)){var f={id:s,sourceLayerIndex:c,index:l,geometry:u?h.geometry:Di(o),properties:o.properties,type:o.type,patterns:{}};void 0!==o.id&&(f.id=o.id),this.hasPattern?this.features.push(es("fill-extrusion",this.layers,f,this.zoom,e)):this.addFeature(f,f.geometry,l,r,{}),e.featureIndex.insert(o,f.geometry,l,c,this.index,!0)}}},xs.prototype.addFeatures=function(t,e,r){for(var n=0,a=this.features;n<a.length;n+=1){var i=a[n];this.addFeature(i,i.geometry,i.index,e,r)}},xs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},xs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},xs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},xs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,os),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},xs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},xs.prototype.addFeature=function(t,e,r,n,a){for(var i=0,o=Qo(e,500);i<o.length;i+=1){for(var s=o[i],l=0,c=0,u=s;c<u.length;c+=1)l+=u[c].length;for(var h=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray),f=0,p=s;f<p.length;f+=1){var d=p[f];if(0!==d.length&&!((I=d).every((function(t){return t.x<0}))||I.every((function(t){return t.x>8192}))||I.every((function(t){return t.y<0}))||I.every((function(t){return t.y>8192}))))for(var g=0,m=0;m<d.length;m++){var v=d[m];if(m>=1){var y=d[m-1];if(!bs(v,y)){h.vertexLength+4>ai.MAX_VERTEX_ARRAY_LENGTH&&(h=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var x=v.sub(y)._perp()._unit(),b=y.dist(v);g+b>32768&&(g=0),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,0,g),ys(this.layoutVertexArray,v.x,v.y,x.x,x.y,0,1,g),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,0,g+=b),ys(this.layoutVertexArray,y.x,y.y,x.x,x.y,0,1,g);var _=h.vertexLength;this.indexArray.emplaceBack(_,_+2,_+1),this.indexArray.emplaceBack(_+1,_+2,_+3),h.vertexLength+=4,h.primitiveLength+=2}}}}if(h.vertexLength+l>ai.MAX_VERTEX_ARRAY_LENGTH&&(h=this.segments.prepareSegment(l,this.layoutVertexArray,this.indexArray)),"Polygon"===ms[t.type]){for(var w=[],T=[],k=h.vertexLength,A=0,M=s;A<M.length;A+=1){var S=M[A];if(0!==S.length){S!==s[0]&&T.push(w.length/2);for(var E=0;E<S.length;E++){var C=S[E];ys(this.layoutVertexArray,C.x,C.y,0,0,1,1,0),w.push(C.x),w.push(C.y)}}}for(var L=_o(w,T),P=0;P<L.length;P+=3)this.indexArray.emplaceBack(k+L[P],k+L[P+2],k+L[P+1]);h.primitiveLength+=L.length/3,h.vertexLength+=l}}var I;this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,a,n)},Dn("FillExtrusionBucket",xs,{omit:["layers","features"]});var _s={paint:new ya({"fill-extrusion-opacity":new pa(Mt["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new da(Mt["paint_fill-extrusion"]["fill-extrusion-color"]),"fill-extrusion-translate":new pa(Mt["paint_fill-extrusion"]["fill-extrusion-translate"]),"fill-extrusion-translate-anchor":new pa(Mt["paint_fill-extrusion"]["fill-extrusion-translate-anchor"]),"fill-extrusion-pattern":new ga(Mt["paint_fill-extrusion"]["fill-extrusion-pattern"]),"fill-extrusion-height":new da(Mt["paint_fill-extrusion"]["fill-extrusion-height"]),"fill-extrusion-base":new da(Mt["paint_fill-extrusion"]["fill-extrusion-base"]),"fill-extrusion-vertical-gradient":new pa(Mt["paint_fill-extrusion"]["fill-extrusion-vertical-gradient"])})},ws=function(t){function e(e){t.call(this,e,_s)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.createBucket=function(t){return new xs(t)},e.prototype.queryRadius=function(){return Ji(this.paint.get("fill-extrusion-translate"))},e.prototype.is3D=function(){return!0},e.prototype.queryIntersectsFeature=function(t,e,r,n,i,o,s,l){var c=Ki(t,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),o.angle,s),u=this.paint.get("fill-extrusion-height").evaluate(e,r),h=this.paint.get("fill-extrusion-base").evaluate(e,r),f=function(t,e,r,n){for(var i=[],o=0,s=t;o<s.length;o+=1){var l=s[o],c=[l.x,l.y,0,1];io(c,c,e),i.push(new a(c[0]/c[3],c[1]/c[3]))}return i}(c,l),p=function(t,e,r,n){for(var i=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,h=n[8]*r,f=n[9]*r,p=n[10]*r,d=n[11]*r,g=0,m=t;g<m.length;g+=1){for(var v=[],y=[],x=0,b=m[g];x<b.length;x+=1){var _=b[x],w=_.x,T=_.y,k=n[0]*w+n[4]*T+n[12],A=n[1]*w+n[5]*T+n[13],M=n[2]*w+n[6]*T+n[14],S=n[3]*w+n[7]*T+n[15],E=M+c,C=S+u,L=k+h,P=A+f,I=M+p,z=S+d,O=new a((k+s)/C,(A+l)/C);O.z=E/C,v.push(O);var D=new a(L/z,P/z);D.z=I/z,y.push(D)}i.push(v),o.push(y)}return[i,o]}(n,h,u,l);return function(t,e,r){var n=1/0;ji(r,e)&&(n=ks(r,e[0]));for(var a=0;a<e.length;a++)for(var i=e[a],o=t[a],s=0;s<i.length-1;s++){var l=i[s],c=[l,i[s+1],o[s+1],o[s],l];Bi(r,c)&&(n=Math.min(n,ks(r,c)))}return n!==1/0&&n}(p[0],p[1],f)},e}(xa);function Ts(t,e){return t.x*e.x+t.y*e.y}function ks(t,e){if(1===t.length){for(var r,n=0,a=e[n++];!r||a.equals(r);)if(!(r=e[n++]))return 1/0;for(;n<e.length;n++){var i=e[n],o=t[0],s=r.sub(a),l=i.sub(a),c=o.sub(a),u=Ts(s,s),h=Ts(s,l),f=Ts(l,l),p=Ts(c,s),d=Ts(c,l),g=u*f-h*h,m=(f*p-h*d)/g,v=(u*d-h*p)/g,y=a.z*(1-m-v)+r.z*m+i.z*v;if(isFinite(y))return y}return 1/0}for(var x=1/0,b=0,_=e;b<_.length;b+=1)x=Math.min(x,_[b].z);return x}var As=Ta([{name:"a_pos_normal",components:2,type:"Int16"},{name:"a_data",components:4,type:"Uint8"}],4).members,Ms=gs.VectorTileFeature.types,Ss=Math.cos(Math.PI/180*37.5),Es=Math.pow(2,14)/.5,Cs=function(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Ea,this.indexArray=new Fa,this.programConfigurations=new Pi(As,t.layers,t.zoom),this.segments=new ai,this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id}))};Cs.prototype.populate=function(t,e,r){this.hasPattern=ts("line",this.layers,e);for(var n=this.layers[0].layout.get("line-sort-key"),a=[],i=0,o=t;i<o.length;i+=1){var s=o[i],l=s.feature,c=s.id,u=s.index,h=s.sourceLayerIndex,f=this.layers[0]._featureFilter.needGeometry,p={type:l.type,id:c,properties:l.properties,geometry:f?Di(l):[]};if(this.layers[0]._featureFilter.filter(new aa(this.zoom),p,r)){f||(p.geometry=Di(l));var d=n?n.evaluate(p,{},r):void 0;a.push({id:c,properties:l.properties,type:l.type,sourceLayerIndex:h,index:u,geometry:p.geometry,patterns:{},sortKey:d})}}n&&a.sort((function(t,e){return t.sortKey-e.sortKey}));for(var g=0,m=a;g<m.length;g+=1){var v=m[g],y=v.geometry,x=v.index,b=v.sourceLayerIndex;if(this.hasPattern){var _=es("line",this.layers,v,this.zoom,e);this.patternFeatures.push(_)}else this.addFeature(v,y,x,r,{});e.featureIndex.insert(t[x].feature,y,x,b,this.index)}},Cs.prototype.update=function(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)},Cs.prototype.addFeatures=function(t,e,r){for(var n=0,a=this.patternFeatures;n<a.length;n+=1){var i=a[n];this.addFeature(i,i.geometry,i.index,e,r)}},Cs.prototype.isEmpty=function(){return 0===this.layoutVertexArray.length},Cs.prototype.uploadPending=function(){return!this.uploaded||this.programConfigurations.needsUpload},Cs.prototype.upload=function(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,As),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0},Cs.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())},Cs.prototype.addFeature=function(t,e,r,n,a){for(var i=this.layers[0].layout,o=i.get("line-join").evaluate(t,{}),s=i.get("line-cap"),l=i.get("line-miter-limit"),c=i.get("line-round-limit"),u=0,h=e;u<h.length;u+=1)this.addLine(h[u],t,o,s,l,c);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,a,n)},Cs.prototype.addLine=function(t,e,r,n,a,i){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,e.properties&&e.properties.hasOwnProperty("mapbox_clip_start")&&e.properties.hasOwnProperty("mapbox_clip_end")){this.clipStart=+e.properties.mapbox_clip_start,this.clipEnd=+e.properties.mapbox_clip_end;for(var o=0;o<t.length-1;o++)this.totalDistance+=t[o].dist(t[o+1]);this.updateScaledDistance()}for(var s="Polygon"===Ms[e.type],l=t.length;l>=2&&t[l-1].equals(t[l-2]);)l--;for(var c=0;c<l-1&&t[c].equals(t[c+1]);)c++;if(!(l<(s?3:2))){"bevel"===r&&(a=1.05);var u,h=this.overscaling<=16?122880/(512*this.overscaling):0,f=this.segments.prepareSegment(10*l,this.layoutVertexArray,this.indexArray),p=void 0,d=void 0,g=void 0,m=void 0;this.e1=this.e2=-1,s&&(m=t[c].sub(u=t[l-2])._unit()._perp());for(var v=c;v<l;v++)if(!(d=v===l-1?s?t[c+1]:void 0:t[v+1])||!t[v].equals(d)){m&&(g=m),u&&(p=u),u=t[v],m=d?d.sub(u)._unit()._perp():g;var y=(g=g||m).add(m);0===y.x&&0===y.y||y._unit();var x=g.x*m.x+g.y*m.y,b=y.x*m.x+y.y*m.y,_=0!==b?1/b:1/0,w=2*Math.sqrt(2-2*b),T=b<Ss&&p&&d,k=g.x*m.y-g.y*m.x>0;if(T&&v>c){var A=u.dist(p);if(A>2*h){var M=u.sub(u.sub(p)._mult(h/A)._round());this.updateDistance(p,M),this.addCurrentVertex(M,g,0,0,f),p=M}}var S=p&&d,E=S?r:s?"butt":n;if(S&&"round"===E&&(_<i?E="miter":_<=2&&(E="fakeround")),"miter"===E&&_>a&&(E="bevel"),"bevel"===E&&(_>2&&(E="flipbevel"),_<a&&(E="miter")),p&&this.updateDistance(p,u),"miter"===E)y._mult(_),this.addCurrentVertex(u,y,0,0,f);else if("flipbevel"===E){if(_>100)y=m.mult(-1);else{var C=_*g.add(m).mag()/g.sub(m).mag();y._perp()._mult(C*(k?-1:1))}this.addCurrentVertex(u,y,0,0,f),this.addCurrentVertex(u,y.mult(-1),0,0,f)}else if("bevel"===E||"fakeround"===E){var L=-Math.sqrt(_*_-1),P=k?L:0,I=k?0:L;if(p&&this.addCurrentVertex(u,g,P,I,f),"fakeround"===E)for(var z=Math.round(180*w/Math.PI/20),O=1;O<z;O++){var D=O/z;if(.5!==D){var R=D-.5;D+=D*R*(D-1)*((1.0904+x*(x*(3.55645-1.43519*x)-3.2452))*R*R+(.848013+x*(.215638*x-1.06021)))}var F=m.sub(g)._mult(D)._add(g)._unit()._mult(k?-1:1);this.addHalfVertex(u,F.x,F.y,!1,k,0,f)}d&&this.addCurrentVertex(u,m,-P,-I,f)}else if("butt"===E)this.addCurrentVertex(u,y,0,0,f);else if("square"===E){var B=p?1:-1;this.addCurrentVertex(u,y,B,B,f)}else"round"===E&&(p&&(this.addCurrentVertex(u,g,0,0,f),this.addCurrentVertex(u,g,1,1,f,!0)),d&&(this.addCurrentVertex(u,m,-1,-1,f,!0),this.addCurrentVertex(u,m,0,0,f)));if(T&&v<l-1){var N=u.dist(d);if(N>2*h){var j=u.add(d.sub(u)._mult(h/N)._round());this.updateDistance(u,j),this.addCurrentVertex(j,m,0,0,f),u=j}}}}},Cs.prototype.addCurrentVertex=function(t,e,r,n,a,i){void 0===i&&(i=!1);var o=e.y*n-e.x,s=-e.y-e.x*n;this.addHalfVertex(t,e.x+e.y*r,e.y-e.x*r,i,!1,r,a),this.addHalfVertex(t,o,s,i,!0,-n,a),this.distance>Es/2&&0===this.totalDistance&&(this.distance=0,this.addCurrentVertex(t,e,r,n,a,i))},Cs.prototype.addHalfVertex=function(t,e,r,n,a,i,o){var s=.5*this.scaledDistance;this.layoutVertexArray.emplaceBack((t.x<<1)+(n?1:0),(t.y<<1)+(a?1:0),Math.round(63*e)+128,Math.round(63*r)+128,1+(0===i?0:i<0?-1:1)|(63&s)<<2,s>>6);var l=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,l),o.primitiveLength++),a?this.e2=l:this.e1=l},Cs.prototype.updateScaledDistance=function(){this.scaledDistance=this.totalDistance>0?(this.clipStart+(this.clipEnd-this.clipStart)*this.distance/this.totalDistance)*(Es-1):this.distance},Cs.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},Dn("LineBucket",Cs,{omit:["layers","patternFeatures"]});var Ls=new ya({"line-cap":new pa(Mt.layout_line["line-cap"]),"line-join":new da(Mt.layout_line["line-join"]),"line-miter-limit":new pa(Mt.layout_line["line-miter-limit"]),"line-round-limit":new pa(Mt.layout_line["line-round-limit"]),"line-sort-key":new da(Mt.layout_line["line-sort-key"])}),Ps={paint:new ya({"line-opacity":new da(Mt.paint_line["line-opacity"]),"line-color":new da(Mt.paint_line["line-color"]),"line-translate":new pa(Mt.paint_line["line-translate"]),"line-translate-anchor":new pa(Mt.paint_line["line-translate-anchor"]),"line-width":new da(Mt.paint_line["line-width"]),"line-gap-width":new da(Mt.paint_line["line-gap-width"]),"line-offset":new da(Mt.paint_line["line-offset"]),"line-blur":new da(Mt.paint_line["line-blur"]),"line-dasharray":new ma(Mt.paint_line["line-dasharray"]),"line-pattern":new ga(Mt.paint_line["line-pattern"]),"line-gradient":new va(Mt.paint_line["line-gradient"])}),layout:Ls},Is=new(function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.possiblyEvaluate=function(e,r){return r=new aa(Math.floor(r.zoom),{now:r.now,fadeDuration:r.fadeDuration,zoomHistory:r.zoomHistory,transition:r.transition}),t.prototype.possiblyEvaluate.call(this,e,r)},e.prototype.evaluate=function(e,r,n,a){return r=u({},r,{zoom:Math.floor(r.zoom)}),t.prototype.evaluate.call(this,e,r,n,a)},e}(da))(Ps.paint.properties["line-width"].specification);Is.useIntegerZoom=!0;var zs=function(t){function e(e){t.call(this,e,Ps)}return 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n,a,i=0;i<e.length;i++){if((n=e.charCodeAt(i))>55295&&n<57344){if(!a){n>56319||i+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):a=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,a=n;continue}n=a-55296<<10|n-56320|65536,a=null}else a&&(t[r++]=239,t[r++]=191,t[r++]=189,a=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&Xs(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),qs(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),qs(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r<e;r++)this.buf[this.pos++]=t[r]},writeRawMessage:function(t,e){this.pos++;var r=this.pos;t(e,this);var n=this.pos-r;n>=128&&Xs(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Gs.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,Js,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Ks,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,tl,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,Qs,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,$s,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,el,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,rl,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,nl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,al,e)},writeBytesField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Gs.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Gs.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Gs.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Gs.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,Boolean(e))}};var fl=function(t,e){var r=e.pixelRatio,n=e.version,a=e.stretchX,i=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=a,this.stretchY=i,this.content=o,this.version=n},pl={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};pl.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},pl.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},pl.tlbr.get=function(){return this.tl.concat(this.br)},pl.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(fl.prototype,pl);var dl=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var a=[];this.addImages(t,r,a),this.addImages(e,n,a);var i=hl(a),o=new po({width:i.w||1,height:i.h||1});for(var s in t){var l=t[s],c=r[s].paddedRect;po.copy(l.data,o,{x:0,y:0},{x:c.x+1,y:c.y+1},l.data)}for(var u in e){var h=e[u],f=n[u].paddedRect,p=f.x+1,d=f.y+1,g=h.data.width,m=h.data.height;po.copy(h.data,o,{x:0,y:0},{x:p,y:d},h.data),po.copy(h.data,o,{x:0,y:m-1},{x:p,y:d-1},{width:g,height:1}),po.copy(h.data,o,{x:0,y:0},{x:p,y:d+m},{width:g,height:1}),po.copy(h.data,o,{x:g-1,y:0},{x:p-1,y:d},{width:1,height:m}),po.copy(h.data,o,{x:0,y:0},{x:p+g,y:d},{width:1,height:m})}this.image=o,this.iconPositions=r,this.patternPositions=n};dl.prototype.addImages=function(t,e,r){for(var n in t){var a=t[n],i={x:0,y:0,w:a.data.width+2,h:a.data.height+2};r.push(i),e[n]=new fl(i,a),a.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},dl.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},dl.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var n=t.tl;r.update(e.data,void 0,{x:n[0],y:n[1]})}},Dn("ImagePosition",fl),Dn("ImageAtlas",dl);var gl={horizontal:1,vertical:2,horizontalOnly:3},ml=function(){this.scale=1,this.fontStack="",this.imageName=null};ml.forText=function(t,e){var r=new ml;return r.scale=t||1,r.fontStack=e,r},ml.forImage=function(t){var e=new ml;return e.imageName=t,e};var vl=function(){this.text="",this.sectionIndex=[],this.sections=[],this.imageSectionID=null};function yl(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g){var m,v=vl.fromFeature(t,a);h===gl.vertical&&v.verticalizePunctuation();var y=na.processBidirectionalText,x=na.processStyledBidirectionalText;if(y&&1===v.sections.length){m=[];for(var b=0,_=y(v.toString(),Al(v,c,i,e,n,p,d));b<_.length;b+=1){var w=_[b],T=new vl;T.text=w,T.sections=v.sections;for(var k=0;k<w.length;k++)T.sectionIndex.push(0);m.push(T)}}else if(x){m=[];for(var A=0,M=x(v.text,v.sectionIndex,Al(v,c,i,e,n,p,d));A<M.length;A+=1){var S=M[A],E=new vl;E.text=S[0],E.sectionIndex=S[1],E.sections=v.sections,m.push(E)}}else m=function(t,e){for(var r=[],n=t.text,a=0,i=0,o=e;i<o.length;i+=1){var s=o[i];r.push(t.substring(a,s)),a=s}return a<n.length&&r.push(t.substring(a,n.length)),r}(v,Al(v,c,i,e,n,p,d));var C=[],L={positionedLines:C,text:v.toString(),top:u[1],bottom:u[1],left:u[0],right:u[0],writingMode:h,iconsInText:!1,verticalizable:!1};return function(t,e,r,n,a,i,o,s,l,c,u,h){for(var f=0,p=-17,d=0,g=0,m="right"===s?1:"left"===s?0:.5,v=0,y=0,x=a;y<x.length;y+=1){var b=x[y];b.trim();var _=b.getMaxScale(),w=24*(_-1),T={positionedGlyphs:[],lineOffset:0};t.positionedLines[v]=T;var k=T.positionedGlyphs,A=0;if(b.length()){for(var M=0;M<b.length();M++){var S=b.getSection(M),E=b.getSectionIndex(M),C=b.getCharCode(M),L=0,P=null,I=null,z=null,O=24,D=!(l===gl.horizontal||!u&&!Hn(C)||u&&(xl[C]||(H=C,Un.Arabic(H)||Un["Arabic Supplement"](H)||Un["Arabic Extended-A"](H)||Un["Arabic Presentation Forms-A"](H)||Un["Arabic Presentation Forms-B"](H))));if(S.imageName){var R=n[S.imageName];if(!R)continue;z=S.imageName,t.iconsInText=t.iconsInText||!0,I=R.paddedRect;var F=R.displaySize;S.scale=24*S.scale/h,L=w+(24-F[1]*S.scale),O=(P={width:F[0],height:F[1],left:1,top:-3,advance:D?F[1]:F[0]}).advance;var B=D?F[0]*S.scale-24*_:F[1]*S.scale-24*_;B>0&&B>A&&(A=B)}else{var N=r[S.fontStack],j=N&&N[C];if(j&&j.rect)I=j.rect,P=j.metrics;else{var V=e[S.fontStack],U=V&&V[C];if(!U)continue;P=U.metrics}L=24*(_-S.scale)}D?(t.verticalizable=!0,k.push({glyph:C,imageName:z,x:f,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),f+=O*S.scale+c):(k.push({glyph:C,imageName:z,x:f,y:p+L,vertical:D,scale:S.scale,fontStack:S.fontStack,sectionIndex:E,metrics:P,rect:I}),f+=P.advance*S.scale+c)}0!==k.length&&(d=Math.max(f-c,d),Sl(k,0,k.length-1,m,A)),f=0;var q=i*_+A;T.lineOffset=Math.max(A,w),p+=q,g=Math.max(q,g),++v}else p+=i,++v}var H,G=p- -17,Y=Ml(o),W=Y.horizontalAlign,Z=Y.verticalAlign;(function(t,e,r,n,a,i,o,s,l){var c,u=(e-r)*a;c=i!==o?-s*n- 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n=t.charCodeAt(r+1)||null,a=t.charCodeAt(r-1)||null;e+=n&&Gn(n)&&!Vs[t[r+1]]||a&&Gn(a)&&!Vs[t[r-1]]||!Vs[t[r]]?t[r]:Vs[t[r]]}return e}(this.text)},vl.prototype.trim=function(){for(var t=0,e=0;e<this.text.length&&xl[this.text.charCodeAt(e)];e++)t++;for(var r=this.text.length,n=this.text.length-1;n>=0&&n>=t&&xl[this.text.charCodeAt(n)];n--)r--;this.text=this.text.substring(t,r),this.sectionIndex=this.sectionIndex.slice(t,r)},vl.prototype.substring=function(t,e){var r=new vl;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r},vl.prototype.toString=function(){return this.text},vl.prototype.getMaxScale=function(){var t=this;return this.sectionIndex.reduce((function(e,r){return Math.max(e,t.sections[r].scale)}),0)},vl.prototype.addTextSection=function(t,e){this.text+=t.text,this.sections.push(ml.forText(t.scale,t.fontStack||e));for(var r=this.sections.length-1,n=0;n<t.text.length;++n)this.sectionIndex.push(r)},vl.prototype.addImageSection=function(t){var e=t.image?t.image.name:"";if(0!==e.length){var r=this.getNextImageSectionCharCode();r?(this.text+=String.fromCharCode(r),this.sections.push(ml.forImage(e)),this.sectionIndex.push(this.sections.length-1)):_("Reached maximum number of images 6401")}else _("Can't add FormattedSection with an empty image.")},vl.prototype.getNextImageSectionCharCode=function(){return this.imageSectionID?this.imageSectionID>=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)};var xl={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},bl={};function _l(t,e,r,n,a,i){if(e.imageName){var o=n[e.imageName];return o?o.displaySize[0]*e.scale*24/i+a:0}var s=r[e.fontStack],l=s&&s[t];return l?l.metrics.advance*e.scale+a:0}function wl(t,e,r,n){var a=Math.pow(t-e,2);return n?t<e?a/2:2*a:a+Math.abs(r)*r}function Tl(t,e,r){var n=0;return 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ai,this.collisionVertexArray=new Ra};uc.prototype.upload=function(t){this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,this.layoutAttributes),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.collisionVertexBuffer=t.createVertexBuffer(this.collisionVertexArray,Fs.members,!0)},uc.prototype.destroy=function(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.collisionVertexBuffer.destroy())},Dn("CollisionBuffers",uc);var hc=function(t){this.collisionBoxArray=t.collisionBoxArray,this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((function(t){return t.id})),this.index=t.index,this.pixelRatio=t.pixelRatio,this.sourceLayerIndex=t.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=eo([]),this.placementViewportMatrix=eo([]);var e=this.layers[0]._unevaluatedLayout._values;this.textSizeData=Ll(this.zoom,e["text-size"]),this.iconSizeData=Ll(this.zoom,e["icon-size"]);var r=this.layers[0].layout,n=r.get("symbol-sort-key"),a=r.get("symbol-z-order");this.sortFeaturesByKey="viewport-y"!==a&&void 0!==n.constantOr(1),this.sortFeaturesByY=("viewport-y"===a||"auto"===a&&!this.sortFeaturesByKey)&&(r.get("text-allow-overlap")||r.get("icon-allow-overlap")||r.get("text-ignore-placement")||r.get("icon-ignore-placement")),"point"===r.get("symbol-placement")&&(this.writingModes=r.get("text-writing-mode").map((function(t){return gl[t]}))),this.stateDependentLayerIds=this.layers.filter((function(t){return t.isStateDependent()})).map((function(t){return t.id})),this.sourceID=t.sourceID};hc.prototype.createArrays=function(){this.text=new cc(new Pi(Ds.members,this.layers,this.zoom,(function(t){return/^text/.test(t)}))),this.icon=new cc(new Pi(Ds.members,this.layers,this.zoom,(function(t){return/^icon/.test(t)}))),this.glyphOffsetArray=new $a,this.lineVertexArray=new ti,this.symbolInstances=new Qa},hc.prototype.calculateGlyphDependencies=function(t,e,r,n,a){for(var i=0;i<t.length;i++)if(e[t.charCodeAt(i)]=!0,(r||n)&&a){var o=Vs[t.charAt(i)];o&&(e[o.charCodeAt(0)]=!0)}},hc.prototype.populate=function(t,e,r){var n=this.layers[0],a=n.layout,i=a.get("text-font"),o=a.get("text-field"),s=a.get("icon-image"),l=("constant"!==o.value.kind||o.value.value instanceof te&&!o.value.value.isEmpty()||o.value.value.toString().length>0)&&("constant"!==i.value.kind||i.value.value.length>0),c="constant"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=a.get("symbol-sort-key");if(this.features=[],l||c){for(var h=e.iconDependencies,f=e.glyphDependencies,p=e.availableImages,d=new aa(this.zoom),g=0,m=t;g<m.length;g+=1){var v=m[g],y=v.feature,x=v.id,b=v.index,_=v.sourceLayerIndex,w=n._featureFilter.needGeometry,T={type:y.type,id:x,properties:y.properties,geometry:w?Di(y):[]};if(n._featureFilter.filter(d,T,r)){w||(T.geometry=Di(y));var k=void 0;if(l){var A=n.getValueAndResolveTokens("text-field",T,r,p),M=te.factory(A);lc(M)&&(this.hasRTLText=!0),(!this.hasRTLText||"unavailable"===ea()||this.hasRTLText&&na.isParsed())&&(k=js(M,n,T))}var S=void 0;if(c){var E=n.getValueAndResolveTokens("icon-image",T,r,p);S=E instanceof ee?E:ee.fromString(E)}if(k||S){var C=this.sortFeaturesByKey?u.evaluate(T,{},r):void 0,L={id:x,text:k,icon:S,index:b,sourceLayerIndex:_,geometry:Di(y),properties:y.properties,type:ac[y.type],sortKey:C};if(this.features.push(L),S&&(h[S.name]=!0),k){var P=i.evaluate(T,{},r).join(","),I="map"===a.get("text-rotation-alignment")&&"point"!==a.get("symbol-placement");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(gl.vertical)>=0;for(var z=0,O=k.sections;z<O.length;z+=1){var D=O[z];if(D.image)h[D.image.name]=!0;else{var R=qn(k.toString()),F=D.fontStack||P,B=f[F]=f[F]||{};this.calculateGlyphDependencies(D.text,B,I,this.allowVerticalPlacement,R)}}}}}}"line"===a.get("symbol-placement")&&(this.features=function(t){var e={},r={},n=[],a=0;function i(e){n.push(t[e]),a++}function o(t,e,a){var i=r[t];return delete r[t],r[e]=i,n[i].geometry[0].pop(),n[i].geometry[0]=n[i].geometry[0].concat(a[0]),i}function s(t,r,a){var i=e[r];return delete e[r],e[t]=i,n[i].geometry[0].shift(),n[i].geometry[0]=a[0].concat(n[i].geometry[0]),i}function l(t,e,r){var n=r?e[0][e[0].length-1]:e[0][0];return t+":"+n.x+":"+n.y}for(var c=0;c<t.length;c++){var u=t[c],h=u.geometry,f=u.text?u.text.toString():null;if(f){var p=l(f,h),d=l(f,h,!0);if(p in r&&d in e&&r[p]!==e[d]){var g=s(p,d,h),m=o(p,d,n[g].geometry);delete e[p],delete r[d],r[l(f,n[m].geometry,!0)]=m,n[g].geometry=null}else p in r?o(p,d,h):d in e?s(p,d,h):(i(c),e[p]=a-1,r[d]=a-1)}else i(c)}return n.filter((function(t){return t.geometry}))}(this.features)),this.sortFeaturesByKey&&this.features.sort((function(t,e){return t.sortKey-e.sortKey}))}},hc.prototype.update=function(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))},hc.prototype.isEmpty=function(){return 0===this.symbolInstances.length&&!this.hasRTLText},hc.prototype.uploadPending=function(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload},hc.prototype.upload=function(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0},hc.prototype.destroyDebugData=function(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()},hc.prototype.destroy=function(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()},hc.prototype.addToLineVertexArray=function(t,e){var r=this.lineVertexArray.length;if(void 0!==t.segment){for(var n=t.dist(e[t.segment+1]),a=t.dist(e[t.segment]),i={},o=t.segment+1;o<e.length;o++)i[o]={x:e[o].x,y:e[o].y,tileUnitDistanceFromAnchor:n},o<e.length-1&&(n+=e[o+1].dist(e[o]));for(var s=t.segment||0;s>=0;s--)i[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:a},s>0&&(a+=e[s-1].dist(e[s]));for(var l=0;l<e.length;l++){var c=i[l];this.lineVertexArray.emplaceBack(c.x,c.y,c.tileUnitDistanceFromAnchor)}}return{lineStartIndex:r,lineLength:this.lineVertexArray.length-r}},hc.prototype.addSymbols=function(t,e,r,n,a,i,o,s,l,c,u,h){for(var f=t.indexArray,p=t.layoutVertexArray,d=t.segments.prepareSegment(4*e.length,p,f,i.sortKey),g=this.glyphOffsetArray.length,m=d.vertexLength,v=this.allowVerticalPlacement&&o===gl.vertical?Math.PI/2:0,y=i.text&&i.text.sections,x=0;x<e.length;x++){var b=e[x],_=b.tl,w=b.tr,T=b.bl,k=b.br,A=b.tex,M=b.pixelOffsetTL,S=b.pixelOffsetBR,E=b.minFontScaleX,C=b.minFontScaleY,L=b.glyphOffset,P=b.isSDF,I=b.sectionIndex,z=d.vertexLength,O=L[1];oc(p,s.x,s.y,_.x,O+_.y,A.x,A.y,r,P,M.x,M.y,E,C),oc(p,s.x,s.y,w.x,O+w.y,A.x+A.w,A.y,r,P,S.x,M.y,E,C),oc(p,s.x,s.y,T.x,O+T.y,A.x,A.y+A.h,r,P,M.x,S.y,E,C),oc(p,s.x,s.y,k.x,O+k.y,A.x+A.w,A.y+A.h,r,P,S.x,S.y,E,C),sc(t.dynamicLayoutVertexArray,s,v),f.emplaceBack(z,z+1,z+2),f.emplaceBack(z+1,z+2,z+3),d.vertexLength+=4,d.primitiveLength+=2,this.glyphOffsetArray.emplaceBack(L[0]),x!==e.length-1&&I===e[x+1].sectionIndex||t.programConfigurations.populatePaintArrays(p.length,i,i.index,{},h,y&&y[I])}t.placedSymbolArray.emplaceBack(s.x,s.y,g,this.glyphOffsetArray.length-g,m,l,c,s.segment,r?r[0]:0,r?r[1]:0,n[0],n[1],o,0,!1,0,u)},hc.prototype._addCollisionDebugVertex=function(t,e,r,n,a,i){return e.emplaceBack(0,0),t.emplaceBack(r.x,r.y,n,a,Math.round(i.x),Math.round(i.y))},hc.prototype.addCollisionDebugVertices=function(t,e,r,n,i,o,s){var l=i.segments.prepareSegment(4,i.layoutVertexArray,i.indexArray),c=l.vertexLength,u=i.layoutVertexArray,h=i.collisionVertexArray,f=s.anchorX,p=s.anchorY;this._addCollisionDebugVertex(u,h,o,f,p,new a(t,e)),this._addCollisionDebugVertex(u,h,o,f,p,new a(r,e)),this._addCollisionDebugVertex(u,h,o,f,p,new a(r,n)),this._addCollisionDebugVertex(u,h,o,f,p,new a(t,n)),l.vertexLength+=4;var d=i.indexArray;d.emplaceBack(c,c+1),d.emplaceBack(c+1,c+2),d.emplaceBack(c+2,c+3),d.emplaceBack(c+3,c),l.primitiveLength+=4},hc.prototype.addDebugCollisionBoxes=function(t,e,r,n){for(var a=t;a<e;a++){var i=this.collisionBoxArray.get(a);this.addCollisionDebugVertices(i.x1,i.y1,i.x2,i.y2,n?this.textCollisionBox:this.iconCollisionBox,i.anchorPoint,r)}},hc.prototype.generateCollisionDebugBuffers=function(){this.hasDebugData()&&this.destroyDebugData(),this.textCollisionBox=new uc(Oa,Bs.members,qa),this.iconCollisionBox=new uc(Oa,Bs.members,qa);for(var t=0;t<this.symbolInstances.length;t++){var e=this.symbolInstances.get(t);this.addDebugCollisionBoxes(e.textBoxStartIndex,e.textBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.verticalTextBoxStartIndex,e.verticalTextBoxEndIndex,e,!0),this.addDebugCollisionBoxes(e.iconBoxStartIndex,e.iconBoxEndIndex,e,!1),this.addDebugCollisionBoxes(e.verticalIconBoxStartIndex,e.verticalIconBoxEndIndex,e,!1)}},hc.prototype._deserializeCollisionBoxesForSymbol=function(t,e,r,n,a,i,o,s,l){for(var c={},u=e;u<r;u++){var h=t.get(u);c.textBox={x1:h.x1,y1:h.y1,x2:h.x2,y2:h.y2,anchorPointX:h.anchorPointX,anchorPointY:h.anchorPointY},c.textFeatureIndex=h.featureIndex;break}for(var f=n;f<a;f++){var p=t.get(f);c.verticalTextBox={x1:p.x1,y1:p.y1,x2:p.x2,y2:p.y2,anchorPointX:p.anchorPointX,anchorPointY:p.anchorPointY},c.verticalTextFeatureIndex=p.featureIndex;break}for(var d=i;d<o;d++){var g=t.get(d);c.iconBox={x1:g.x1,y1:g.y1,x2:g.x2,y2:g.y2,anchorPointX:g.anchorPointX,anchorPointY:g.anchorPointY},c.iconFeatureIndex=g.featureIndex;break}for(var m=s;m<l;m++){var v=t.get(m);c.verticalIconBox={x1:v.x1,y1:v.y1,x2:v.x2,y2:v.y2,anchorPointX:v.anchorPointX,anchorPointY:v.anchorPointY},c.verticalIconFeatureIndex=v.featureIndex;break}return c},hc.prototype.deserializeCollisionBoxes=function(t){this.collisionArrays=[];for(var e=0;e<this.symbolInstances.length;e++){var r=this.symbolInstances.get(e);this.collisionArrays.push(this._deserializeCollisionBoxesForSymbol(t,r.textBoxStartIndex,r.textBoxEndIndex,r.verticalTextBoxStartIndex,r.verticalTextBoxEndIndex,r.iconBoxStartIndex,r.iconBoxEndIndex,r.verticalIconBoxStartIndex,r.verticalIconBoxEndIndex))}},hc.prototype.hasTextData=function(){return this.text.segments.get().length>0},hc.prototype.hasIconData=function(){return this.icon.segments.get().length>0},hc.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},hc.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},hc.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},hc.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,a=r.vertexStartIndex;a<n;a+=4)t.indexArray.emplaceBack(a,a+1,a+2),t.indexArray.emplaceBack(a+1,a+2,a+3)},hc.prototype.getSortedSymbolIndexes=function(t){if(this.sortedAngle===t&&void 0!==this.symbolInstanceIndexes)return this.symbolInstanceIndexes;for(var e=Math.sin(t),r=Math.cos(t),n=[],a=[],i=[],o=0;o<this.symbolInstances.length;++o){i.push(o);var s=this.symbolInstances.get(o);n.push(0|Math.round(e*s.anchorX+r*s.anchorY)),a.push(s.featureIndex)}return i.sort((function(t,e){return n[t]-n[e]||a[e]-a[t]})),i},hc.prototype.addToSortKeyRanges=function(t,e){var r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})},hc.prototype.sortFeatures=function(t){var e=this;if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r<n.length;r+=1){var a=this.symbolInstances.get(n[r]);this.featureSortOrder.push(a.featureIndex),[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t,r,n){t>=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},Dn("SymbolBucket",hc,{omit:["layers","collisionBoxArray","features","compareText"]}),hc.MAX_GLYPHS=65535,hc.addDynamicAttributes=sc;var fc=new ya({"symbol-placement":new pa(Mt.layout_symbol["symbol-placement"]),"symbol-spacing":new pa(Mt.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new pa(Mt.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new da(Mt.layout_symbol["symbol-sort-key"]),"symbol-z-order":new pa(Mt.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new pa(Mt.layout_symbol["icon-allow-overlap"]),"icon-ignore-placement":new pa(Mt.layout_symbol["icon-ignore-placement"]),"icon-optional":new pa(Mt.layout_symbol["icon-optional"]),"icon-rotation-alignment":new pa(Mt.layout_symbol["icon-rotation-alignment"]),"icon-size":new da(Mt.layout_symbol["icon-size"]),"icon-text-fit":new pa(Mt.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new pa(Mt.layout_symbol["icon-text-fit-padding"]),"icon-image":new da(Mt.layout_symbol["icon-image"]),"icon-rotate":new da(Mt.layout_symbol["icon-rotate"]),"icon-padding":new pa(Mt.layout_symbol["icon-padding"]),"icon-keep-upright":new pa(Mt.layout_symbol["icon-keep-upright"]),"icon-offset":new da(Mt.layout_symbol["icon-offset"]),"icon-anchor":new da(Mt.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new pa(Mt.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new pa(Mt.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new pa(Mt.layout_symbol["text-rotation-alignment"]),"text-field":new da(Mt.layout_symbol["text-field"]),"text-font":new da(Mt.layout_symbol["text-font"]),"text-size":new da(Mt.layout_symbol["text-size"]),"text-max-width":new da(Mt.layout_symbol["text-max-width"]),"text-line-height":new pa(Mt.layout_symbol["text-line-height"]),"text-letter-spacing":new da(Mt.layout_symbol["text-letter-spacing"]),"text-justify":new da(Mt.layout_symbol["text-justify"]),"text-radial-offset":new da(Mt.layout_symbol["text-radial-offset"]),"text-variable-anchor":new pa(Mt.layout_symbol["text-variable-anchor"]),"text-anchor":new da(Mt.layout_symbol["text-anchor"]),"text-max-angle":new pa(Mt.layout_symbol["text-max-angle"]),"text-writing-mode":new pa(Mt.layout_symbol["text-writing-mode"]),"text-rotate":new da(Mt.layout_symbol["text-rotate"]),"text-padding":new pa(Mt.layout_symbol["text-padding"]),"text-keep-upright":new pa(Mt.layout_symbol["text-keep-upright"]),"text-transform":new da(Mt.layout_symbol["text-transform"]),"text-offset":new da(Mt.layout_symbol["text-offset"]),"text-allow-overlap":new pa(Mt.layout_symbol["text-allow-overlap"]),"text-ignore-placement":new pa(Mt.layout_symbol["text-ignore-placement"]),"text-optional":new pa(Mt.layout_symbol["text-optional"])}),pc={paint:new ya({"icon-opacity":new da(Mt.paint_symbol["icon-opacity"]),"icon-color":new da(Mt.paint_symbol["icon-color"]),"icon-halo-color":new da(Mt.paint_symbol["icon-halo-color"]),"icon-halo-width":new da(Mt.paint_symbol["icon-halo-width"]),"icon-halo-blur":new da(Mt.paint_symbol["icon-halo-blur"]),"icon-translate":new pa(Mt.paint_symbol["icon-translate"]),"icon-translate-anchor":new pa(Mt.paint_symbol["icon-translate-anchor"]),"text-opacity":new da(Mt.paint_symbol["text-opacity"]),"text-color":new da(Mt.paint_symbol["text-color"],{runtimeType:Bt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),"text-halo-color":new da(Mt.paint_symbol["text-halo-color"]),"text-halo-width":new da(Mt.paint_symbol["text-halo-width"]),"text-halo-blur":new da(Mt.paint_symbol["text-halo-blur"]),"text-translate":new pa(Mt.paint_symbol["text-translate"]),"text-translate-anchor":new pa(Mt.paint_symbol["text-translate-anchor"])}),layout:fc},dc=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:Ot,this.defaultValue=t};dc.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},dc.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},dc.prototype.outputDefined=function(){return!1},dc.prototype.serialize=function(){return null},Dn("FormatSectionOverride",dc,{omit:["defaultValue"]});var gc=function(t){function e(e){t.call(this,e,pc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),"auto"===this.layout.get("icon-rotation-alignment")&&(this.layout._values["icon-rotation-alignment"]="point"!==this.layout.get("symbol-placement")?"map":"viewport"),"auto"===this.layout.get("text-rotation-alignment")&&(this.layout._values["text-rotation-alignment"]="point"!==this.layout.get("symbol-placement")?"map":"viewport"),"auto"===this.layout.get("text-pitch-alignment")&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")),"auto"===this.layout.get("icon-pitch-alignment")&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),"point"===this.layout.get("symbol-placement")){var n=this.layout.get("text-writing-mode");if(n){for(var a=[],i=0,o=n;i<o.length;i+=1){var s=o[i];a.indexOf(s)<0&&a.push(s)}this.layout._values["text-writing-mode"]=a}else this.layout._values["text-writing-mode"]=["horizontal"]}this._setPaintOverrides()},e.prototype.getValueAndResolveTokens=function(t,e,r,n){var a=this.layout.get(t).evaluate(e,{},r,n),i=this._unevaluatedLayout._values[t];return i.isDataDriven()||Ur(i.value)||!a?a:function(t,e){return e.replace(/{([^{}]+)}/g,(function(e,r){return r in t?String(t[r]):""}))}(e.properties,a)},e.prototype.createBucket=function(t){return new hc(t)},e.prototype.queryRadius=function(){return 0},e.prototype.queryIntersectsFeature=function(){return!1},e.prototype._setPaintOverrides=function(){for(var t=0,r=pc.paint.overridableProperties;t<r.length;t+=1){var n=r[t];if(e.hasPaintOverride(this.layout,n)){var a,i=this.paint.get(n),o=new dc(i),s=new Vr(o,i.property.specification);a="constant"===i.value.kind||"source"===i.value.kind?new Hr("source",s):new Gr("composite",s,i.value.zoomStops,i.value._interpolationType),this.paint._values[n]=new ha(i.property,a,i.parameters)}}},e.prototype._handleOverridablePaintPropertyUpdate=function(t,r,n){return!(!this.layout||r.isDataDriven()||n.isDataDriven())&&e.hasPaintOverride(this.layout,t)},e.hasPaintOverride=function(t,e){var r=t.get("text-field"),n=pc.paint.properties[e],a=!1,i=function(t){for(var e=0,r=t;e<r.length;e+=1)if(n.overrides&&n.overrides.hasOverride(r[e]))return void(a=!0)};if("constant"===r.value.kind&&r.value.value instanceof te)i(r.value.value.sections);else if("source"===r.value.kind){var o=function(t){a||(t instanceof oe&&ae(t.value)===Ut?i(t.value.sections):t instanceof ue?i(t.sections):t.eachChild(o))},s=r.value;s._styleExpression&&o(s._styleExpression.expression)}return a},e}(xa),mc={paint:new ya({"background-color":new pa(Mt.paint_background["background-color"]),"background-pattern":new ma(Mt.paint_background["background-pattern"]),"background-opacity":new pa(Mt.paint_background["background-opacity"])})},vc=function(t){function e(e){t.call(this,e,mc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xa),yc={paint:new ya({"raster-opacity":new pa(Mt.paint_raster["raster-opacity"]),"raster-hue-rotate":new pa(Mt.paint_raster["raster-hue-rotate"]),"raster-brightness-min":new pa(Mt.paint_raster["raster-brightness-min"]),"raster-brightness-max":new pa(Mt.paint_raster["raster-brightness-max"]),"raster-saturation":new pa(Mt.paint_raster["raster-saturation"]),"raster-contrast":new pa(Mt.paint_raster["raster-contrast"]),"raster-resampling":new pa(Mt.paint_raster["raster-resampling"]),"raster-fade-duration":new pa(Mt.paint_raster["raster-fade-duration"])})},xc=function(t){function e(e){t.call(this,e,yc)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(xa),bc=function(t){function e(e){t.call(this,e,{}),this.implementation=e}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.is3D=function(){return"3d"===this.implementation.renderingMode},e.prototype.hasOffscreenPass=function(){return void 0!==this.implementation.prerender},e.prototype.recalculate=function(){},e.prototype.updateTransitions=function(){},e.prototype.hasTransition=function(){},e.prototype.serialize=function(){},e.prototype.onAdd=function(t){this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},e.prototype.onRemove=function(t){this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},e}(xa),_c={circle:oo,heatmap:vo,hillshade:xo,fill:is,"fill-extrusion":ws,line:zs,symbol:gc,background:vc,raster:xc},wc=self.HTMLImageElement,Tc=self.HTMLCanvasElement,kc=self.HTMLVideoElement,Ac=self.ImageData,Mc=self.ImageBitmap,Sc=function(t,e,r,n){this.context=t,this.format=r,this.texture=t.gl.createTexture(),this.update(e,n)};Sc.prototype.update=function(t,e,r){var n=t.width,a=t.height,i=!(this.size&&this.size[0]===n&&this.size[1]===a||r),o=this.context,s=o.gl;if(this.useMipmap=Boolean(e&&e.useMipmap),s.bindTexture(s.TEXTURE_2D,this.texture),o.pixelStoreUnpackFlipY.set(!1),o.pixelStoreUnpack.set(1),o.pixelStoreUnpackPremultiplyAlpha.set(this.format===s.RGBA&&(!e||!1!==e.premultiply)),i)this.size=[n,a],t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Ac||Mc&&t instanceof Mc?s.texImage2D(s.TEXTURE_2D,0,this.format,this.format,s.UNSIGNED_BYTE,t):s.texImage2D(s.TEXTURE_2D,0,this.format,n,a,0,this.format,s.UNSIGNED_BYTE,t.data);else{var l=r||{x:0,y:0},c=l.x,u=l.y;t instanceof wc||t instanceof Tc||t instanceof kc||t instanceof Ac||Mc&&t instanceof Mc?s.texSubImage2D(s.TEXTURE_2D,0,c,u,s.RGBA,s.UNSIGNED_BYTE,t):s.texSubImage2D(s.TEXTURE_2D,0,c,u,n,a,s.RGBA,s.UNSIGNED_BYTE,t.data)}this.useMipmap&&this.isSizePowerOfTwo()&&s.generateMipmap(s.TEXTURE_2D)},Sc.prototype.bind=function(t,e,r){var n=this.context.gl;n.bindTexture(n.TEXTURE_2D,this.texture),r!==n.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(r=n.LINEAR),t!==this.filter&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,t),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,r||t),this.filter=t),e!==this.wrap&&(n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,e),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,e),this.wrap=e)},Sc.prototype.isSizePowerOfTwo=function(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0},Sc.prototype.destroy=function(){this.context.gl.deleteTexture(this.texture),this.texture=null};var Ec=function(t){var e=this;this._callback=t,this._triggered=!1,"undefined"!=typeof MessageChannel&&(this._channel=new MessageChannel,this._channel.port2.onmessage=function(){e._triggered=!1,e._callback()})};Ec.prototype.trigger=function(){var t=this;this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((function(){t._triggered=!1,t._callback()}),0))},Ec.prototype.remove=function(){delete this._channel,this._callback=function(){}};var Cc=function(t,e,r){this.target=t,this.parent=e,this.mapId=r,this.callbacks={},this.tasks={},this.taskQueue=[],this.cancelCallbacks={},g(["receive","process"],this),this.invoker=new Ec(this.process),this.target.addEventListener("message",this.receive,!1),this.globalScope=k()?t:self};function Lc(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}Cc.prototype.send=function(t,e,r,n,a){var i=this;void 0===a&&(a=!1);var o=Math.round(1e18*Math.random()).toString(36).substring(0,10);r&&(this.callbacks[o]=r);var s=S(this.globalScope)?void 0:[];return this.target.postMessage({id:o,type:t,hasCallback:!!r,targetMapId:n,mustQueue:a,sourceMapId:this.mapId,data:Nn(e,s)},s),{cancel:function(){r&&delete i.callbacks[o],i.target.postMessage({id:o,type:"<cancel>",targetMapId:n,sourceMapId:i.mapId})}}},Cc.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if("<cancel>"===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else k()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Cc.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Cc.prototype.processTask=function(t,e){var r=this;if("<response>"===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(jn(e.error)):n(null,jn(e.data)))}else{var a=!1,i=S(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){a=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:"<response>",sourceMapId:r.mapId,error:e?Nn(e):null,data:Nn(n,i)},i)}:function(t){a=!0},s=null,l=jn(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(".");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error("Could not find function "+e.type));!a&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Cc.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener("message",this.receive,!1)};var Pc=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Pc.prototype.setNorthEast=function(t){return this._ne=t instanceof Ic?new Ic(t.lng,t.lat):Ic.convert(t),this},Pc.prototype.setSouthWest=function(t){return this._sw=t instanceof Ic?new Ic(t.lng,t.lat):Ic.convert(t),this},Pc.prototype.extend=function(t){var e,r,n=this._sw,a=this._ne;if(t instanceof Ic)e=t,r=t;else{if(!(t instanceof Pc))return Array.isArray(t)?4===t.length||t.every(Array.isArray)?this.extend(Pc.convert(t)):this.extend(Ic.convert(t)):this;if(r=t._ne,!(e=t._sw)||!r)return this}return n||a?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),a.lng=Math.max(r.lng,a.lng),a.lat=Math.max(r.lat,a.lat)):(this._sw=new Ic(e.lng,e.lat),this._ne=new Ic(r.lng,r.lat)),this},Pc.prototype.getCenter=function(){return new Ic((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Pc.prototype.getSouthWest=function(){return this._sw},Pc.prototype.getNorthEast=function(){return this._ne},Pc.prototype.getNorthWest=function(){return new Ic(this.getWest(),this.getNorth())},Pc.prototype.getSouthEast=function(){return new Ic(this.getEast(),this.getSouth())},Pc.prototype.getWest=function(){return this._sw.lng},Pc.prototype.getSouth=function(){return this._sw.lat},Pc.prototype.getEast=function(){return this._ne.lng},Pc.prototype.getNorth=function(){return this._ne.lat},Pc.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Pc.prototype.toString=function(){return"LngLatBounds("+this._sw.toString()+", "+this._ne.toString()+")"},Pc.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Pc.prototype.contains=function(t){var e=Ic.convert(t),r=e.lng,n=e.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),this._sw.lat<=n&&n<=this._ne.lat&&a},Pc.convert=function(t){return!t||t instanceof Pc?t:new Pc(t)};var Ic=function(t,e){if(isNaN(t)||isNaN(e))throw new Error("Invalid LngLat object: ("+t+", "+e+")");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")};Ic.prototype.wrap=function(){return new Ic(c(this.lng,-180,180),this.lat)},Ic.prototype.toArray=function(){return[this.lng,this.lat]},Ic.prototype.toString=function(){return"LngLat("+this.lng+", "+this.lat+")"},Ic.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,a=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return 6371008.8*Math.acos(Math.min(a,1))},Ic.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Pc(new Ic(this.lng-r,this.lat-e),new Ic(this.lng+r,this.lat+e))},Ic.convert=function(t){if(t instanceof Ic)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Ic(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&"object"==typeof t&&null!==t)return new Ic(Number("lng"in t?t.lng:t.lon),Number(t.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: <lng>, lat: <lat>}, an object {lon: <lng>, lat: <lat>}, or an array of [<lng>, <lat>]")};var zc=2*Math.PI*6371008.8;function Oc(t){return zc*Math.cos(t*Math.PI/180)}function Dc(t){return(180+t)/360}function Rc(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Fc(t,e){return t/Oc(e)}function Bc(t){return 360/Math.PI*Math.atan(Math.exp((180-360*t)*Math.PI/180))-90}var Nc=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Nc.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Ic.convert(t);return new Nc(Dc(r.lng),Rc(r.lat),Fc(e,r.lat))},Nc.prototype.toLngLat=function(){return new Ic(360*this.x-180,Bc(this.y))},Nc.prototype.toAltitude=function(){return this.z*Oc(Bc(this.y))},Nc.prototype.meterInMercatorCoordinateUnits=function(){return 1/zc*(t=Bc(this.y),1/Math.cos(t*Math.PI/180));var t};var jc=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=qc(0,t,t,e,r)};jc.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},jc.prototype.url=function(t,e){var r,n,a,i,o,s=(n=this.y,a=this.z,i=Lc(256*(r=this.x),256*(n=Math.pow(2,a)-n-1),a),o=Lc(256*(r+1),256*(n+1),a),i[0]+","+i[1]+","+o[0]+","+o[1]),l=function(t,e,r){for(var n,a="",i=t;i>0;i--)a+=(e&(n=1<<i-1)?1:0)+(r&n?2:0);return a}(this.z,this.x,this.y);return t[(this.x+this.y)%t.length].replace("{prefix}",(this.x%16).toString(16)+(this.y%16).toString(16)).replace("{z}",String(this.z)).replace("{x}",String(this.x)).replace("{y}",String("tms"===e?Math.pow(2,this.z)-this.y-1:this.y)).replace("{quadkey}",l).replace("{bbox-epsg-3857}",s)},jc.prototype.getTilePoint=function(t){var e=Math.pow(2,this.z);return new a(8192*(t.x*e-this.x),8192*(t.y*e-this.y))},jc.prototype.toString=function(){return this.z+"/"+this.x+"/"+this.y};var Vc=function(t,e){this.wrap=t,this.canonical=e,this.key=qc(t,e.z,e.z,e.x,e.y)},Uc=function(t,e,r,n,a){this.overscaledZ=t,this.wrap=e,this.canonical=new jc(r,+n,+a),this.key=qc(e,t,r,n,a)};function qc(t,e,r,n,a){(t*=2)<0&&(t=-1*t-1);var i=1<<r;return(i*i*t+i*a+n).toString(36)+r.toString(36)+e.toString(36)}Uc.prototype.equals=function(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)},Uc.prototype.scaledTo=function(t){var e=this.canonical.z-t;return t>this.canonical.z?new Uc(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Uc(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Uc.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?qc(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):qc(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Uc.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ<this.overscaledZ&&t.canonical.x===this.canonical.x>>e&&t.canonical.y===this.canonical.y>>e},Uc.prototype.children=function(t){if(this.overscaledZ>=t)return[new Uc(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Uc(e,this.wrap,e,r,n),new Uc(e,this.wrap,e,r+1,n),new Uc(e,this.wrap,e,r,n+1),new Uc(e,this.wrap,e,r+1,n+1)]},Uc.prototype.isLessThan=function(t){return this.wrap<t.wrap||!(this.wrap>t.wrap)&&(this.overscaledZ<t.overscaledZ||!(this.overscaledZ>t.overscaledZ)&&(this.canonical.x<t.canonical.x||!(this.canonical.x>t.canonical.x)&&this.canonical.y<t.canonical.y))},Uc.prototype.wrapped=function(){return new Uc(this.overscaledZ,0,this.canonical.z,this.canonical.x,this.canonical.y)},Uc.prototype.unwrapTo=function(t){return new Uc(this.overscaledZ,t,this.canonical.z,this.canonical.x,this.canonical.y)},Uc.prototype.overscaleFactor=function(){return Math.pow(2,this.overscaledZ-this.canonical.z)},Uc.prototype.toUnwrapped=function(){return new Vc(this.wrap,this.canonical)},Uc.prototype.toString=function(){return this.overscaledZ+"/"+this.canonical.x+"/"+this.canonical.y},Uc.prototype.getTilePoint=function(t){return this.canonical.getTilePoint(new Nc(t.x-this.wrap,t.y))},Dn("CanonicalTileID",jc),Dn("OverscaledTileID",Uc,{omit:["posMatrix"]});var Hc=function(t,e,r){if(this.uid=t,e.height!==e.width)throw new RangeError("DEM tiles must be square");if(r&&"mapbox"!==r&&"terrarium"!==r)return _('"'+r+'" is not a valid encoding type. Valid types include "mapbox" and "terrarium".');this.stride=e.height;var n=this.dim=e.height-2;this.data=new Uint32Array(e.data.buffer),this.encoding=r||"mapbox";for(var a=0;a<n;a++)this.data[this._idx(-1,a)]=this.data[this._idx(0,a)],this.data[this._idx(n,a)]=this.data[this._idx(n-1,a)],this.data[this._idx(a,-1)]=this.data[this._idx(a,0)],this.data[this._idx(a,n)]=this.data[this._idx(a,n-1)];this.data[this._idx(-1,-1)]=this.data[this._idx(0,0)],this.data[this._idx(n,-1)]=this.data[this._idx(n-1,0)],this.data[this._idx(-1,n)]=this.data[this._idx(0,n-1)],this.data[this._idx(n,n)]=this.data[this._idx(n-1,n-1)]};Hc.prototype.get=function(t,e){var r=new Uint8Array(this.data.buffer),n=4*this._idx(t,e);return("terrarium"===this.encoding?this._unpackTerrarium:this._unpackMapbox)(r[n],r[n+1],r[n+2])},Hc.prototype.getUnpackVector=function(){return"terrarium"===this.encoding?[256,1,1/256,32768]:[6553.6,25.6,.1,1e4]},Hc.prototype._idx=function(t,e){if(t<-1||t>=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(e+1)*this.stride+(t+1)},Hc.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},Hc.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},Hc.prototype.getPixels=function(){return new po({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Hc.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error("dem dimension mismatch");var n=e*this.dim,a=e*this.dim+this.dim,i=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=a-1;break;case 1:a=n+1}switch(r){case-1:i=o-1;break;case 1:o=i+1}for(var s=-e*this.dim,l=-r*this.dim,c=i;c<o;c++)for(var u=n;u<a;u++)this.data[this._idx(u,c)]=t.data[this._idx(u+s,c+l)]},Dn("DEMData",Hc);var Gc=function(t){this._stringToNumber={},this._numberToString=[];for(var e=0;e<t.length;e++){var r=t[e];this._stringToNumber[r]=e,this._numberToString[e]=r}};Gc.prototype.encode=function(t){return this._stringToNumber[t]},Gc.prototype.decode=function(t){return this._numberToString[t]};var Yc=function(t,e,r,n,a){this.type="Feature",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=a},Wc={geometry:{configurable:!0}};Wc.geometry.get=function(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry},Wc.geometry.set=function(t){this._geometry=t},Yc.prototype.toJSON=function(){var t={geometry:this.geometry};for(var e in this)"_geometry"!==e&&"_vectorTileFeature"!==e&&(t[e]=this[e]);return t},Object.defineProperties(Yc.prototype,Wc);var Zc=function(){this.state={},this.stateChanges={},this.deletedStates={}};Zc.prototype.updateState=function(t,e,r){var n=String(e);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][n]=this.stateChanges[t][n]||{},u(this.stateChanges[t][n],r),null===this.deletedStates[t])for(var a in this.deletedStates[t]={},this.state[t])a!==n&&(this.deletedStates[t][a]=null);else if(this.deletedStates[t]&&null===this.deletedStates[t][n])for(var i in this.deletedStates[t][n]={},this.state[t][n])r[i]||(this.deletedStates[t][n][i]=null);else for(var o in r)this.deletedStates[t]&&this.deletedStates[t][n]&&null===this.deletedStates[t][n][o]&&delete this.deletedStates[t][n][o]},Zc.prototype.removeFeatureState=function(t,e,r){if(null!==this.deletedStates[t]){var n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}},Zc.prototype.getState=function(t,e){var r=String(e),n=u({},(this.state[t]||{})[r],(this.stateChanges[t]||{})[r]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){var a=this.deletedStates[t][e];if(null===a)return{};for(var i in a)delete n[i]}return n},Zc.prototype.initializeTileState=function(t,e){t.setFeatureState(this.state,e)},Zc.prototype.coalesceChanges=function(t,e){var r={};for(var n in this.stateChanges){this.state[n]=this.state[n]||{};var a={};for(var i in this.stateChanges[n])this.state[n][i]||(this.state[n][i]={}),u(this.state[n][i],this.stateChanges[n][i]),a[i]=this.state[n][i];r[n]=a}for(var o in this.deletedStates){this.state[o]=this.state[o]||{};var s={};if(null===this.deletedStates[o])for(var l in this.state[o])s[l]={},this.state[o][l]={};else for(var c in this.deletedStates[o]){if(null===this.deletedStates[o][c])this.state[o][c]={};else for(var h=0,f=Object.keys(this.deletedStates[o][c]);h<f.length;h+=1)delete this.state[o][c][f[h]];s[c]=this.state[o][c]}r[o]=r[o]||{},u(r[o],s)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(r).length)for(var p in t)t[p].setFeatureState(r,e)};var Xc=function(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new Ln(8192,16,0),this.grid3D=new Ln(8192,16,0),this.featureIndexArray=new ri,this.promoteId=e};function Jc(t,e,r,n,a){return v(t,(function(t,i){var o=e instanceof fa?e.get(i):null;return o&&o.evaluate?o.evaluate(r,n,a):o}))}function Kc(t){for(var e=1/0,r=1/0,n=-1/0,a=-1/0,i=0,o=t;i<o.length;i+=1){var s=o[i];e=Math.min(e,s.x),r=Math.min(r,s.y),n=Math.max(n,s.x),a=Math.max(a,s.y)}return{minX:e,minY:r,maxX:n,maxY:a}}function Qc(t,e){return e-t}Xc.prototype.insert=function(t,e,r,n,a,i){var o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,a);for(var s=i?this.grid3D:this.grid,l=0;l<e.length;l++){for(var c=e[l],u=[1/0,1/0,-1/0,-1/0],h=0;h<c.length;h++){var f=c[h];u[0]=Math.min(u[0],f.x),u[1]=Math.min(u[1],f.y),u[2]=Math.max(u[2],f.x),u[3]=Math.max(u[3],f.y)}u[0]<8192&&u[1]<8192&&u[2]>=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},Xc.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new gs.VectorTile(new Hs(this.rawTileData)).layers,this.sourceLayerCoder=new Gc(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers},Xc.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=8192/t.tileSize/t.scale,l=rn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,h=Kc(c),f=this.grid.query(h.minX-u,h.minY-u,h.maxX+u,h.maxY+u),p=Kc(t.cameraQueryGeometry),d=0,g=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o<s.length;o+=1){var l=s[o];if(e<=l.x&&r<=l.y&&n>=l.x&&i>=l.y)return!0}var c=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var u=0,h=c;u<h.length;u+=1)if(Wi(t,h[u]))return!0;for(var f=0;f<t.length-1;f++)if(Zi(t[f],t[f+1],c))return!0;return!1}(t.cameraQueryGeometry,e-u,r-u,n+u,i+u)}));d<g.length;d+=1)f.push(g[d]);f.sort(Qc);for(var m,v={},y=function(a){var u=f[a];if(u!==m){m=u;var h=i.featureIndexArray.get(u),p=null;i.loadMatchingFeature(v,h.bucketIndex,h.sourceLayerIndex,h.featureIndex,l,o.layers,o.availableImages,e,r,n,(function(e,r,n){return p||(p=Di(e)),r.queryIntersectsFeature(c,e,n,p,i.z,t.transform,s,t.pixelPosMatrix)}))}},x=0;x<f.length;x++)y(x);return v},Xc.prototype.loadMatchingFeature=function(t,e,r,n,a,i,o,s,l,c,u){var h=this.bucketLayerIDs[e];if(!i||function(t,e){for(var r=0;r<t.length;r++)if(e.indexOf(t[r])>=0)return!0;return!1}(i,h)){var f=this.sourceLayerCoder.decode(r),p=this.vtLayers[f].feature(n);if(a.filter(new aa(this.tileID.overscaledZ),p))for(var d=this.getId(p,f),g=0;g<h.length;g++){var m=h[g];if(!(i&&i.indexOf(m)<0)){var v=s[m];if(v){var y={};void 0!==d&&c&&(y=c.getState(v.sourceLayer||"_geojsonTileLayer",d));var x=l[m];x.paint=Jc(x.paint,v.paint,p,y,o),x.layout=Jc(x.layout,v.layout,p,y,o);var b=!u||u(p,v,y);if(b){var _=new Yc(p,this.z,this.x,this.y,d);_.layer=x;var w=t[m];void 0===w&&(w=t[m]=[]),w.push({featureIndex:n,feature:_,intersectionZ:b})}}}}}},Xc.prototype.lookupSymbolFeatures=function(t,e,r,n,a,i,o,s){var l={};this.loadVTLayers();for(var c=rn(a),u=0,h=t;u<h.length;u+=1)this.loadMatchingFeature(l,r,n,h[u],c,i,o,s,e);return l},Xc.prototype.hasLayer=function(t){for(var e=0,r=this.bucketLayerIDs;e<r.length;e+=1)for(var n=0,a=r[e];n<a.length;n+=1)if(t===a[n])return!0;return!1},Xc.prototype.getId=function(t,e){var r=t.id;return this.promoteId&&"boolean"==typeof(r=t.properties["string"==typeof this.promoteId?this.promoteId:this.promoteId[e]])&&(r=Number(r)),r},Dn("FeatureIndex",Xc,{omit:["rawTileData","sourceLayerCoder"]});var $c=function(t,e){this.tileID=t,this.uid=f(),this.uses=0,this.tileSize=e,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.expiredRequestCount=0,this.state="loading"};$c.prototype.registerFadeDuration=function(t){var e=t+this.timeAdded;e<R.now()||this.fadeEndTime&&e<this.fadeEndTime||(this.fadeEndTime=e)},$c.prototype.wasRequested=function(){return"errored"===this.state||"loaded"===this.state||"reloading"===this.state},$c.prototype.loadVectorData=function(t,e,r){if(this.hasData()&&this.unloadVectorData(),this.state="loaded",t){for(var n in t.featureIndex&&(this.latestFeatureIndex=t.featureIndex,t.rawTileData?(this.latestRawTileData=t.rawTileData,this.latestFeatureIndex.rawTileData=t.rawTileData):this.latestRawTileData&&(this.latestFeatureIndex.rawTileData=this.latestRawTileData)),this.collisionBoxArray=t.collisionBoxArray,this.buckets=function(t,e){var r={};if(!e)return r;for(var n=function(){var t=i[a],n=t.layerIds.map((function(t){return e.getLayer(t)})).filter(Boolean);if(0!==n.length){t.layers=n,t.stateDependentLayerIds&&(t.stateDependentLayers=t.stateDependentLayerIds.map((function(t){return n.filter((function(e){return e.id===t}))[0]})));for(var o=0,s=n;o<s.length;o+=1)r[s[o].id]=t}},a=0,i=t;a<i.length;a+=1)n();return r}(t.buckets,e.style),this.hasSymbolBuckets=!1,this.buckets){var a=this.buckets[n];if(a instanceof hc){if(this.hasSymbolBuckets=!0,!r)break;a.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(var i in this.buckets){var o=this.buckets[i];if(o instanceof hc&&o.hasRTLText){this.hasRTLText=!0,na.isLoading()||na.isLoaded()||"deferred"!==ea()||ra();break}}for(var s in this.queryPadding=0,this.buckets){var l=this.buckets[s];this.queryPadding=Math.max(this.queryPadding,e.style.getLayer(s).queryRadius(l))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new Za},$c.prototype.unloadVectorData=function(){for(var t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state="unloaded"},$c.prototype.getBucket=function(t){return this.buckets[t.id]},$c.prototype.upload=function(t){for(var e in this.buckets){var r=this.buckets[e];r.uploadPending()&&r.upload(t)}var n=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new Sc(t,this.imageAtlas.image,n.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new Sc(t,this.glyphAtlasImage,n.ALPHA),this.glyphAtlasImage=null)},$c.prototype.prepare=function(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)},$c.prototype.queryRenderedFeatures=function(t,e,r,n,a,i,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:a,scale:i,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}},$c.prototype.querySourceFeatures=function(t,e){var r=this.latestFeatureIndex;if(r&&r.rawTileData){var n=r.loadVTLayers(),a=e?e.sourceLayer:"",i=n._geojsonTileLayer||n[a];if(i)for(var o=rn(e&&e.filter),s=this.tileID.canonical,l=s.z,c=s.x,u=s.y,h={z:l,x:c,y:u},f=0;f<i.length;f++){var p=i.feature(f);if(o.filter(new aa(this.tileID.overscaledZ),p)){var d=r.getId(p,a),g=new Yc(p,l,c,u,d);g.tile=h,t.push(g)}}}},$c.prototype.hasData=function(){return"loaded"===this.state||"reloading"===this.state||"expired"===this.state},$c.prototype.patternsLoaded=function(){return this.imageAtlas&&!!Object.keys(this.imageAtlas.patternPositions).length},$c.prototype.setExpiryData=function(t){var e=this.expirationTime;if(t.cacheControl){var r=A(t.cacheControl);r["max-age"]&&(this.expirationTime=Date.now()+1e3*r["max-age"])}else t.expires&&(this.expirationTime=new Date(t.expires).getTime());if(this.expirationTime){var n=Date.now(),a=!1;if(this.expirationTime>n)a=!1;else if(e)if(this.expirationTime<e)a=!0;else{var i=this.expirationTime-e;i?this.expirationTime=n+Math.max(i,3e4):a=!0}else a=!0;a?(this.expiredRequestCount++,this.state="expired"):this.expiredRequestCount=0}},$c.prototype.getExpiryTimeout=function(){if(this.expirationTime)return this.expiredRequestCount?1e3*(1<<Math.min(this.expiredRequestCount-1,31)):Math.min(this.expirationTime-(new Date).getTime(),Math.pow(2,31)-1)},$c.prototype.setFeatureState=function(t,e){if(this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData&&0!==Object.keys(t).length){var r=this.latestFeatureIndex.loadVTLayers();for(var n in this.buckets)if(e.style.hasLayer(n)){var a=this.buckets[n],i=a.layers[0].sourceLayer||"_geojsonTileLayer",o=r[i],s=t[i];if(o&&s&&0!==Object.keys(s).length){a.update(s,o,this.imageAtlas&&this.imageAtlas.patternPositions||{});var l=e&&e.style&&e.style.getLayer(n);l&&(this.queryPadding=Math.max(this.queryPadding,l.queryRadius(a)))}}}},$c.prototype.holdingForFade=function(){return void 0!==this.symbolFadeHoldUntil},$c.prototype.symbolFadeFinished=function(){return!this.symbolFadeHoldUntil||this.symbolFadeHoldUntil<R.now()},$c.prototype.clearFadeHold=function(){this.symbolFadeHoldUntil=void 0},$c.prototype.setHoldDuration=function(t){this.symbolFadeHoldUntil=R.now()+t},$c.prototype.setDependencies=function(t,e){for(var r={},n=0,a=e;n<a.length;n+=1)r[a[n]]=!0;this.dependencies[t]=r},$c.prototype.hasDependency=function(t,e){for(var r=0,n=t;r<n.length;r+=1){var a=this.dependencies[n[r]];if(a)for(var i=0,o=e;i<o.length;i+=1)if(a[o[i]])return!0}return!1};var tu=self.performance,eu=function(t){this._marks={start:[t.url,"start"].join("#"),end:[t.url,"end"].join("#"),measure:t.url.toString()},tu.mark(this._marks.start)};eu.prototype.finish=function(){tu.mark(this._marks.end);var t=tu.getEntriesByName(this._marks.measure);return 0===t.length&&(tu.measure(this._marks.measure,this._marks.start,this._marks.end),t=tu.getEntriesByName(this._marks.measure),tu.clearMarks(this._marks.start),tu.clearMarks(this._marks.end),tu.clearMeasures(this._marks.measure)),t},t.Actor=Cc,t.AlphaImage=fo,t.CanonicalTileID=jc,t.CollisionBoxArray=Za,t.Color=Kt,t.DEMData=Hc,t.DataConstantProperty=pa,t.DictionaryCoder=Gc,t.EXTENT=8192,t.ErrorEvent=kt,t.EvaluationParameters=aa,t.Event=Tt,t.Evented=At,t.FeatureIndex=Xc,t.FillBucket=rs,t.FillExtrusionBucket=xs,t.ImageAtlas=dl,t.ImagePosition=fl,t.LineBucket=Cs,t.LngLat=Ic,t.LngLatBounds=Pc,t.MercatorCoordinate=Nc,t.ONE_EM=24,t.OverscaledTileID=Uc,t.Point=a,t.Point$1=a,t.Properties=ya,t.Protobuf=Hs,t.RGBAImage=po,t.RequestManager=q,t.RequestPerformance=eu,t.ResourceType=ft,t.SegmentVector=ai,t.SourceFeatureState=Zc,t.StructArrayLayout1ui2=Ha,t.StructArrayLayout2f1f2i16=Da,t.StructArrayLayout2i4=Aa,t.StructArrayLayout3ui6=Fa,t.StructArrayLayout4i8=Ma,t.SymbolBucket=hc,t.Texture=Sc,t.Tile=$c,t.Transitionable=sa,t.Uniform1f=vi,t.Uniform1i=mi,t.Uniform2f=yi,t.Uniform3f=xi,t.Uniform4f=bi,t.UniformColor=_i,t.UniformMatrix4f=Ti,t.UnwrappedTileID=Vc,t.ValidationError=St,t.WritingMode=gl,t.ZoomHistory=Vn,t.add=function(t,e,r){return t[0]=e[0]+r[0],t[1]=e[1]+r[1],t[2]=e[2]+r[2],t},t.addDynamicAttributes=sc,t.asyncAll=function(t,e,r){if(!t.length)return r(null,[]);var n=t.length,a=new Array(t.length),i=null;t.forEach((function(t,o){e(t,(function(t,e){t&&(i=t),a[o]=e,0==--n&&r(i,a)}))}))},t.bezier=o,t.bindAll=g,t.browser=R,t.cacheEntryPossiblyAdded=function(t){++ut>ot&&(t.getActor().send("enforceCacheSizeLimit",it),ut=0)},t.clamp=l,t.clearTileCache=function(t){var e=self.caches.delete("mapbox-tiles");t&&e.catch(t).then((function(){return t()}))},t.clipLine=jl,t.clone=function(t){var e=new to(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=x,t.clone$2=function(t){var e=new to(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=Ns,t.config=F,t.create=function(){var t=new to(16);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new to(9);return to!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[5]=0,t[6]=0,t[7]=0),t[0]=1,t[4]=1,t[8]=1,t},t.create$2=function(){var t=new to(4);return to!=Float32Array&&(t[1]=0,t[2]=0),t[0]=1,t[3]=1,t},t.createCommonjsModule=e,t.createExpression=qr,t.createLayout=Ta,t.createStyleLayer=function(t){return"custom"===t.type?new bc(t):new _c[t.type](t)},t.cross=function(t,e,r){var n=e[0],a=e[1],i=e[2],o=r[0],s=r[1],l=r[2];return t[0]=a*l-i*s,t[1]=i*o-n*l,t[2]=n*s-a*o,t},t.deepEqual=function t(e,r){if(Array.isArray(e)){if(!Array.isArray(r)||e.length!==r.length)return!1;for(var n=0;n<e.length;n++)if(!t(e[n],r[n]))return!1;return!0}if("object"==typeof e&&null!==e&&null!==r){if("object"!=typeof r)return!1;if(Object.keys(e).length!==Object.keys(r).length)return!1;for(var a in e)if(!t(e[a],r[a]))return!1;return!0}return 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ht(t,e){var r=[];r.size=t.size,void 0!==t.start&&(r.start=t.start,r.end=t.end);for(var n=0;n<t.length;n+=3)r.push(t[n]+e,t[n+1],t[n+2]);return r}function ft(t,e){if(t.transformed)return t;var r,n,a,i=1<<t.z,o=t.x,s=t.y;for(r=0;r<t.features.length;r++){var l=t.features[r],c=l.geometry,u=l.type;if(l.geometry=[],1===u)for(n=0;n<c.length;n+=2)l.geometry.push(pt(c[n],c[n+1],e,i,o,s));else for(n=0;n<c.length;n++){var h=[];for(a=0;a<c[n].length;a+=2)h.push(pt(c[n][a],c[n][a+1],e,i,o,s));l.geometry.push(h)}}return t.transformed=!0,t}function pt(t,e,r,n,a,i){return[Math.round(r*(t*n-a)),Math.round(r*(e*n-i))]}function dt(t,e,r,n,a){for(var i=e===a.maxZoom?0:a.tolerance/((1<<e)*a.extent),o={features:[],numPoints:0,numSimplified:0,numFeatures:0,source:null,x:r,y:n,z:e,transformed:!1,minX:2,minY:1,maxX:-1,maxY:0},s=0;s<t.length;s++){o.numFeatures++,gt(o,t[s],i,a);var l=t[s].minX,c=t[s].minY,u=t[s].maxX,h=t[s].maxY;l<o.minX&&(o.minX=l),c<o.minY&&(o.minY=c),u>o.maxX&&(o.maxX=u),h>o.maxY&&(o.maxY=h)}return o}function gt(t,e,r,n){var a=e.geometry,i=e.type,o=[];if("Point"===i||"MultiPoint"===i)for(var s=0;s<a.length;s+=3)o.push(a[s]),o.push(a[s+1]),t.numPoints++,t.numSimplified++;else if("LineString"===i)mt(o,a,t,r,!1,!1);else if("MultiLineString"===i||"Polygon"===i)for(s=0;s<a.length;s++)mt(o,a[s],t,r,"Polygon"===i,0===s);else if("MultiPolygon"===i)for(var l=0;l<a.length;l++){var c=a[l];for(s=0;s<c.length;s++)mt(o,c[s],t,r,!0,0===s)}if(o.length){var u=e.tags||null;if("LineString"===i&&n.lineMetrics){for(var h in u={},e.tags)u[h]=e.tags[h];u.mapbox_clip_start=a.start/a.size,u.mapbox_clip_end=a.end/a.size}var f={geometry:o,type:"Polygon"===i||"MultiPolygon"===i?3:"LineString"===i||"MultiLineString"===i?2:1,tags:u};null!==e.id&&(f.id=e.id),t.features.push(f)}}function mt(t,e,r,n,a,i){var o=n*n;if(n>0&&e.size<(a?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;l<e.length;l+=3)(0===n||e[l+2]>o)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;a&&function(t,e){for(var r=0,n=0,a=t.length,i=a-2;n<a;i=n,n+=2)r+=(t[n]-t[i])*(t[n+1]+t[i+1]);if(r>0===e)for(n=0,a=t.length;n<a/2;n+=2){var o=t[n],s=t[n+1];t[n]=t[a-2-n],t[n+1]=t[a-1-n],t[a-2-n]=o,t[a-1-n]=s}}(s,i),t.push(s)}}function vt(t,e){var r=(e=this.options=function(t,e){for(var r in e)t[r]=e[r];return t}(Object.create(this.options),e)).debug;if(r&&console.time("preprocess data"),e.maxZoom<0||e.maxZoom>24)throw new Error("maxZoom should be in the 0-24 range");if(e.promoteId&&e.generateId)throw new Error("promoteId and generateId cannot be used together.");var n=function(t,e){var r=[];if("FeatureCollection"===t.type)for(var n=0;n<t.features.length;n++)J(r,t.features[n],e,n);else J(r,"Feature"===t.type?t:{geometry:t},e);return r}(t,e);this.tiles={},this.tileCoords=[],r&&(console.timeEnd("preprocess data"),console.log("index: maxZoom: %d, maxPoints: %d",e.indexMaxZoom,e.indexMaxPoints),console.time("generate tiles"),this.stats={},this.total=0),(n=function(t,e){var r=e.buffer/e.extent,n=t,a=rt(t,1,-1-r,r,0,-1,2,e),i=rt(t,1,1-r,2+r,0,-1,2,e);return(a||i)&&(n=rt(t,1,-r,1+r,0,-1,2,e)||[],a&&(n=ut(a,1).concat(n)),i&&(n=n.concat(ut(i,-1)))),n}(n,e)).length&&this.splitTile(n,0,0,0),r&&(n.length&&console.log("features: %d, points: %d",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd("generate tiles"),console.log("tiles generated:",this.total,JSON.stringify(this.stats)))}function yt(t,e,r){return 32*((1<<t)*r+e)+t}function xt(t,e){var r=t.tileID.canonical;if(!this._geoJSONIndex)return e(null,null);var n=this._geoJSONIndex.getTile(r.z,r.x,r.y);if(!n)return e(null,null);var a=new g(n.features),i=b(a);0===i.byteOffset&&i.byteLength===i.buffer.byteLength||(i=new Uint8Array(i)),e(null,{vectorTile:a,rawData:i.buffer})}F.prototype.load=function(t){var e=this.options,r=e.log,n=e.minZoom,a=e.maxZoom,i=e.nodeSize;r&&console.time("total time");var o="prepare "+t.length+" points";r&&console.time(o),this.points=t;for(var s=[],l=0;l<t.length;l++)t[l].geometry&&s.push(N(t[l],l));this.trees[a+1]=new D(s,G,Y,i,Float32Array),r&&console.timeEnd(o);for(var c=a;c>=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new D(s,G,Y,i,Float32Array),r&&console.log("z%d: %d clusters in %dms",c,s.length,+Date.now()-u)}return r&&console.timeEnd("total time"),this},F.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),a=180===t[2]?180:((t[2]+180)%360+360)%360-180,i=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,a=180;else if(r>a){var o=this.getClusters([r,n,180,i],e),s=this.getClusters([-180,n,a,i],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,h=l.range(U(r),q(i),U(a),q(n));u<h.length;u+=1){var f=l.points[h[u]];c.push(f.numPoints?j(f):this.points[f.index])}return c},F.prototype.getChildren=function(t){var e=this._getOriginId(t),r=this._getOriginZoom(t),n="No cluster with the specified id.",a=this.trees[r];if(!a)throw new Error(n);var i=a.points[e];if(!i)throw new Error(n);for(var o=this.options.radius/(this.options.extent*Math.pow(2,r-1)),s=[],l=0,c=a.within(i.x,i.y,o);l<c.length;l+=1){var u=a.points[c[l]];u.parentId===t&&s.push(u.numPoints?j(u):this.points[u.index])}if(0===s.length)throw new Error(n);return s},F.prototype.getLeaves=function(t,e,r){var n=[];return this._appendLeaves(n,t,e=e||10,r=r||0,0),n},F.prototype.getTile=function(t,e,r){var n=this.trees[this._limitZoom(t)],a=Math.pow(2,t),i=this.options,o=i.radius/i.extent,s=(r-o)/a,l=(r+1+o)/a,c={features:[]};return this._addTileFeatures(n.range((e-o)/a,s,(e+1+o)/a,l),n.points,e,r,a,c),0===e&&this._addTileFeatures(n.range(1-o/a,s,1,l),n.points,a,r,a,c),e===a-1&&this._addTileFeatures(n.range(0,s,o/a,l),n.points,-1,r,a,c),c.features.length?c:null},F.prototype.getClusterExpansionZoom=function(t){for(var e=this._getOriginZoom(t)-1;e<=this.options.maxZoom;){var r=this.getChildren(t);if(e++,1!==r.length)break;t=r[0].properties.cluster_id}return e},F.prototype._appendLeaves=function(t,e,r,n,a){for(var i=0,o=this.getChildren(e);i<o.length;i+=1){var s=o[i],l=s.properties;if(l&&l.cluster?a+l.point_count<=n?a+=l.point_count:a=this._appendLeaves(t,l.cluster_id,r,n,a):a<n?a++:t.push(s),t.length===r)break}return a},F.prototype._addTileFeatures=function(t,e,r,n,a,i){for(var o=0,s=t;o<s.length;o+=1){var l=e[s[o]],c=l.numPoints,u={type:1,geometry:[[Math.round(this.options.extent*(l.x*a-r)),Math.round(this.options.extent*(l.y*a-n))]],tags:c?V(l):this.points[l.index].properties},h=void 0;c?h=l.id:this.options.generateId?h=l.index:this.points[l.index].id&&(h=this.points[l.index].id),void 0!==h&&(u.id=h),i.features.push(u)}},F.prototype._limitZoom=function(t){return Math.max(this.options.minZoom,Math.min(t,this.options.maxZoom+1))},F.prototype._cluster=function(t,e){for(var r=[],n=this.options,a=n.reduce,i=n.radius/(n.extent*Math.pow(2,e)),o=0;o<t.length;o++){var s=t[o];if(!(s.zoom<=e)){s.zoom=e;for(var l=this.trees[e+1],c=l.within(s.x,s.y,i),u=s.numPoints||1,h=s.x*u,f=s.y*u,p=a&&u>1?this._map(s,!0):null,d=(o<<5)+(e+1)+this.points.length,g=0,m=c;g<m.length;g+=1){var v=l.points[m[g]];if(!(v.zoom<=e)){v.zoom=e;var y=v.numPoints||1;h+=v.x*y,f+=v.y*y,u+=y,v.parentId=d,a&&(p||(p=this._map(s,!0)),a(p,this._map(v)))}}1===u?r.push(s):(s.parentId=d,r.push(B(h/u,f/u,d,u,p)))}}return r},F.prototype._getOriginId=function(t){return t-this.points.length>>5},F.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},F.prototype._map=function(t,e){if(t.numPoints)return e?H({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?H({},n):n},vt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},vt.prototype.splitTile=function(t,e,r,n,a,i,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<<e,h=yt(e,r,n),f=this.tiles[h];if(!f&&(c>1&&console.time("creation"),f=this.tiles[h]=dt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",e,r,n,f.numFeatures,f.numPoints,f.numSimplified),console.timeEnd("creation"));var p="z"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(f.source=t,a){if(e===l.maxZoom||e===a)continue;var d=1<<a-e;if(r!==Math.floor(i/d)||n!==Math.floor(o/d))continue}else if(e===l.indexMaxZoom||f.numPoints<=l.indexMaxPoints)continue;if(f.source=null,0!==t.length){c>1&&console.time("clipping");var g,m,v,y,x,b,_=.5*l.buffer/l.extent,w=.5-_,T=.5+_,k=1+_;g=m=v=y=null,x=rt(t,u,r-_,r+T,0,f.minX,f.maxX,l),b=rt(t,u,r+w,r+k,0,f.minX,f.maxX,l),t=null,x&&(g=rt(x,u,n-_,n+T,1,f.minY,f.maxY,l),m=rt(x,u,n+w,n+k,1,f.minY,f.maxY,l),x=null),b&&(v=rt(b,u,n-_,n+T,1,f.minY,f.maxY,l),y=rt(b,u,n+w,n+k,1,f.minY,f.maxY,l),b=null),c>1&&console.timeEnd("clipping"),s.push(g||[],e+1,2*r,2*n),s.push(m||[],e+1,2*r,2*n+1),s.push(v||[],e+1,2*r+1,2*n),s.push(y||[],e+1,2*r+1,2*n+1)}}},vt.prototype.getTile=function(t,e,r){var n=this.options,a=n.extent,i=n.debug;if(t<0||t>24)return null;var o=1<<t,s=yt(t,e=(e%o+o)%o,r);if(this.tiles[s])return ft(this.tiles[s],a);i>1&&console.log("drilling down to z%d-%d-%d",t,e,r);for(var l,c=t,u=e,h=r;!l&&c>0;)c--,u=Math.floor(u/2),h=Math.floor(h/2),l=this.tiles[yt(c,u,h)];return l&&l.source?(i>1&&console.log("found parent tile z%d-%d-%d",c,u,h),i>1&&console.time("drilling down"),this.splitTile(l.source,c,u,h,t,e,r),i>1&&console.timeEnd("drilling down"),this.tiles[s]?ft(this.tiles[s],a):null):null};var bt=function(e){function r(t,r,n,a){e.call(this,t,r,n,xt),a&&(this.loadGeoJSON=a)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&"Idle"!==this._state?this._state="NeedsLoadData":(this._state="Coalescing",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var a=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(i,o){if(i||!o)return r(i);if("object"!=typeof o)return r(new Error("Input data given to '"+n.source+"' is not a valid GeoJSON object."));!function t(e,r){var n,a=e&&e.type;if("FeatureCollection"===a)for(n=0;n<e.features.length;n++)t(e.features[n],r);else if("GeometryCollection"===a)for(n=0;n<e.geometries.length;n++)t(e.geometries[n],r);else if("Feature"===a)t(e.geometry,r);else if("Polygon"===a)h(e.coordinates,r);else if("MultiPolygon"===a)for(n=0;n<e.coordinates.length;n++)h(e.coordinates[n],r);return e}(o,!0);try{e._geoJSONIndex=n.cluster?new F(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var a={},i={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c<u.length;c+=1){var h=u[c],f=n[h],p=f[0],d=t.createExpression(f[1]),g=t.createExpression("string"==typeof p?[p,["accumulated"],["get",h]]:p);a[h]=d.value,i[h]=g.value}return r.map=function(t){s.properties=t;for(var e={},r=0,n=l;r<n.length;r+=1){var i=n[r];e[i]=a[i].evaluate(o,s)}return e},r.reduce=function(t,e){s.properties=e;for(var r=0,n=l;r<n.length;r+=1){var a=n[r];o.accumulated=t[a],t[a]=i[a].evaluate(o,s)}},r}(n)).load(o.features):function(t,e){return new vt(t,e)}(o,n.geojsonVtOptions)}catch(i){return r(i)}e.loaded={};var s={};if(a){var l=a.finish();l&&(s.resourceTiming={},s.resourceTiming[n.source]=JSON.parse(JSON.stringify(l)))}r(null,s)}))}},r.prototype.coalesce=function(){"Coalescing"===this._state?this._state="Idle":"NeedsLoadData"===this._state&&(this._state="Coalescing",this._loadData())},r.prototype.reloadTile=function(t,r){var n=this.loaded;return n&&n[t.uid]?e.prototype.reloadTile.call(this,t,r):this.loadTile(t,r)},r.prototype.loadGeoJSON=function(e,r){if(e.request)t.getJSON(e.request,r);else{if("string"!=typeof e.data)return r(new Error("Input data given to '"+e.source+"' is not a valid GeoJSON object."));try{return r(null,JSON.parse(e.data))}catch(t){return r(new Error("Input data given to '"+e.source+"' is not a valid GeoJSON 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registered.");t.plugin.applyArabicShaping=e.applyArabicShaping,t.plugin.processBidirectionalText=e.processBidirectionalText,t.plugin.processStyledBidirectionalText=e.processStyledBidirectionalText}};return _t.prototype.setReferrer=function(t,e){this.referrer=e},_t.prototype.setImages=function(t,e,r){for(var n in this.availableImages[t]=e,this.workerSources[t]){var a=this.workerSources[t][n];for(var i in a)a[i].availableImages=e}r()},_t.prototype.setLayers=function(t,e,r){this.getLayerIndex(t).replace(e),r()},_t.prototype.updateLayers=function(t,e,r){this.getLayerIndex(t).update(e.layers,e.removedIds),r()},_t.prototype.loadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).loadTile(e,r)},_t.prototype.loadDEMTile=function(t,e,r){this.getDEMWorkerSource(t,e.source).loadTile(e,r)},_t.prototype.reloadTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).reloadTile(e,r)},_t.prototype.abortTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).abortTile(e,r)},_t.prototype.removeTile=function(t,e,r){this.getWorkerSource(t,e.type,e.source).removeTile(e,r)},_t.prototype.removeDEMTile=function(t,e){this.getDEMWorkerSource(t,e.source).removeTile(e)},_t.prototype.removeSource=function(t,e,r){if(this.workerSources[t]&&this.workerSources[t][e.type]&&this.workerSources[t][e.type][e.source]){var n=this.workerSources[t][e.type][e.source];delete this.workerSources[t][e.type][e.source],void 0!==n.removeSource?n.removeSource(e,r):r()}},_t.prototype.loadWorkerSource=function(t,e,r){try{this.self.importScripts(e.url),r()}catch(t){r(t.toString())}},_t.prototype.syncRTLPluginState=function(e,r,n){try{t.plugin.setState(r);var a=t.plugin.getPluginURL();if(t.plugin.isLoaded()&&!t.plugin.isParsed()&&null!=a){this.self.importScripts(a);var i=t.plugin.isParsed();n(i?void 0:new Error("RTL Text Plugin failed to import scripts from "+a),i)}}catch(t){n(t.toString())}},_t.prototype.getAvailableImages=function(t){var e=this.availableImages[t];return e||(e=[]),e},_t.prototype.getLayerIndex=function(t){var e=this.layerIndexes[t];return e||(e=this.layerIndexes[t]=new n),e},_t.prototype.getWorkerSource=function(t,e,r){var n=this;return this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),this.workerSources[t][e][r]||(this.workerSources[t][e][r]=new 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c=Object.defineProperty({},"passive",{get:function(){l=!0}});t.window.addEventListener("test",c,c),t.window.removeEventListener("test",c,c)}catch(t){l=!1}r.addEventListener=function(t,e,r,n){void 0===n&&(n={}),t.addEventListener(e,r,"passive"in n&&l?n:n.capture)},r.removeEventListener=function(t,e,r,n){void 0===n&&(n={}),t.removeEventListener(e,r,"passive"in n&&l?n:n.capture)};var u=function(e){e.preventDefault(),e.stopPropagation(),t.window.removeEventListener("click",u,!0)};function h(t){var e=t.userImage;return!!(e&&e.render&&e.render())&&(t.data.replace(new Uint8Array(e.data.buffer)),!0)}r.suppressClick=function(){t.window.addEventListener("click",u,!0),t.window.setTimeout((function(){t.window.removeEventListener("click",u,!0)}),0)},r.mousePos=function(e,r){var n=e.getBoundingClientRect();return new t.Point(r.clientX-n.left-e.clientLeft,r.clientY-n.top-e.clientTop)},r.touchPos=function(e,r){for(var n=e.getBoundingClientRect(),a=[],i=0;i<r.length;i++)a.push(new 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o.resize({width:a||1,height:i||1}),this.patterns){var l=this.patterns[s].bin,c=l.x+1,u=l.y+1,h=this.images[s].data,f=h.width,p=h.height;t.RGBAImage.copy(h,o,{x:0,y:0},{x:c,y:u},{width:f,height:p}),t.RGBAImage.copy(h,o,{x:0,y:p-1},{x:c,y:u-1},{width:f,height:1}),t.RGBAImage.copy(h,o,{x:0,y:0},{x:c,y:u+p},{width:f,height:1}),t.RGBAImage.copy(h,o,{x:f-1,y:0},{x:c-1,y:u},{width:1,height:p}),t.RGBAImage.copy(h,o,{x:0,y:0},{x:c+f,y:u},{width:1,height:p})}this.dirty=!0},r.prototype.beginFrame=function(){this.callbackDispatchedThisFrame={}},r.prototype.dispatchRenderCallbacks=function(t){for(var e=0,r=t;e<r.length;e+=1){var n=r[e];if(!this.callbackDispatchedThisFrame[n]){this.callbackDispatchedThisFrame[n]=!0;var a=this.images[n];h(a)&&this.updateImage(n,a)}}},r}(t.Evented),p=m,d=m,g=1e20;function m(t,e,r,n,a,i){this.fontSize=t||24,this.buffer=void 0===e?3:e,this.cutoff=n||.25,this.fontFamily=a||"sans-serif",this.fontWeight=i||"normal",this.radius=r||8;var o=this.size=this.fontSize+2*this.buffer;this.canvas=document.createElement("canvas"),this.canvas.width=this.canvas.height=o,this.ctx=this.canvas.getContext("2d"),this.ctx.font=this.fontWeight+" "+this.fontSize+"px "+this.fontFamily,this.ctx.textBaseline="middle",this.ctx.fillStyle="black",this.gridOuter=new Float64Array(o*o),this.gridInner=new Float64Array(o*o),this.f=new Float64Array(o),this.d=new Float64Array(o),this.z=new Float64Array(o+1),this.v=new Int16Array(o),this.middle=Math.round(o/2*(navigator.userAgent.indexOf("Gecko/")>=0?1.2:1))}function v(t,e,r,n,a,i,o){for(var s=0;s<e;s++){for(var l=0;l<r;l++)n[l]=t[l*e+s];for(y(n,a,i,o,r),l=0;l<r;l++)t[l*e+s]=a[l]}for(l=0;l<r;l++){for(s=0;s<e;s++)n[s]=t[l*e+s];for(y(n,a,i,o,e),s=0;s<e;s++)t[l*e+s]=Math.sqrt(a[s])}}function y(t,e,r,n,a){r[0]=0,n[0]=-g,n[1]=+g;for(var i=1,o=0;i<a;i++){for(var s=(t[i]+i*i-(t[r[o]]+r[o]*r[o]))/(2*i-2*r[o]);s<=n[o];)o--,s=(t[i]+i*i-(t[r[o]]+r[o]*r[o]))/(2*i-2*r[o]);r[++o]=i,n[o]=s,n[o+1]=+g}for(i=0,o=0;i<a;i++){for(;n[o+1]<i;)o++;e[i]=(i-r[o])*(i-r[o])+t[r[o]]}}m.prototype.draw=function(t){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(t,this.buffer,this.middle);for(var e=this.ctx.getImageData(0,0,this.size,this.size),r=new Uint8ClampedArray(this.size*this.size),n=0;n<this.size*this.size;n++){var a=e.data[4*n+3]/255;this.gridOuter[n]=1===a?0:0===a?g:Math.pow(Math.max(0,.5-a),2),this.gridInner[n]=1===a?g:0===a?0:Math.pow(Math.max(0,a-.5),2)}for(v(this.gridOuter,this.size,this.size,this.f,this.d,this.v,this.z),v(this.gridInner,this.size,this.size,this.f,this.d,this.v,this.z),n=0;n<this.size*this.size;n++)r[n]=Math.max(0,Math.min(255,Math.round(255-255*((this.gridOuter[n]-this.gridInner[n])/this.radius+this.cutoff))));return r},p.default=d;var x=function(t,e){this.requestManager=t,this.localIdeographFontFamily=e,this.entries={}};x.prototype.setURL=function(t){this.url=t},x.prototype.getGlyphs=function(e,r){var n=this,a=[];for(var i in e)for(var o=0,s=e[i];o<s.length;o+=1)a.push({stack:i,id:s[o]});t.asyncAll(a,(function(t,e){var r=t.stack,a=t.id,i=n.entries[r];i||(i=n.entries[r]={glyphs:{},requests:{},ranges:{}});var o=i.glyphs[a];if(void 0===o){if(o=n._tinySDF(i,r,a))return i.glyphs[a]=o,void e(null,{stack:r,id:a,glyph:o});var s=Math.floor(a/256);if(256*s>65535)e(new Error("glyphs > 65535 not supported"));else if(i.ranges[s])e(null,{stack:r,id:a,glyph:o});else{var l=i.requests[s];l||(l=i.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(i.glyphs[+r]=e[+r]);i.ranges[s]=!0}for(var a=0,o=l;a<o.length;a+=1)(0,o[a])(t,e);delete i.requests[s]}))),l.push((function(t,n){t?e(t):n&&e(null,{stack:r,id:a,glyph:n[a]||null})}))}}else e(null,{stack:r,id:a,glyph:o})}),(function(t,e){if(t)r(t);else if(e){for(var n={},a=0,i=e;a<i.length;a+=1){var o=i[a],s=o.stack,l=o.id,c=o.glyph;(n[s]||(n[s]={}))[l]=c&&{id:c.id,bitmap:c.bitmap.clone(),metrics:c.metrics}}r(null,n)}}))},x.prototype._doesCharSupportLocalGlyph=function(e){return!!this.localIdeographFontFamily&&(t.isChar["CJK Unified Ideographs"](e)||t.isChar["Hangul Syllables"](e)||t.isChar.Hiragana(e)||t.isChar.Katakana(e))},x.prototype._tinySDF=function(e,r,n){var a=this.localIdeographFontFamily;if(a&&this._doesCharSupportLocalGlyph(n)){var i=e.tinySDF;if(!i){var o="400";/bold/i.test(r)?o="900":/medium/i.test(r)?o="500":/light/i.test(r)&&(o="200"),i=e.tinySDF=new x.TinySDF(24,3,8,.25,a,o)}return{id:n,bitmap:new t.AlphaImage({width:30,height:30},i.draw(String.fromCharCode(n))),metrics:{width:24,height:24,left:0,top:-8,advance:24}}}},x.loadGlyphRange=function(e,r,n,a,i){var o=256*r,s=o+255,l=a.transformRequest(a.normalizeGlyphsURL(n).replace("{fontstack}",e).replace("{range}",o+"-"+s),t.ResourceType.Glyphs);t.getArrayBuffer(l,(function(e,r){if(e)i(e);else if(r){for(var n={},a=0,o=t.parseGlyphPBF(r);a<o.length;a+=1){var s=o[a];n[s.id]=s}i(null,n)}}))},x.TinySDF=p;var b=function(){this.specification=t.styleSpec.light.position};b.prototype.possiblyEvaluate=function(e,r){return t.sphericalToCartesian(e.expression.evaluate(r))},b.prototype.interpolate=function(e,r,n){return{x:t.number(e.x,r.x,n),y:t.number(e.y,r.y,n),z:t.number(e.z,r.z,n)}};var _=new t.Properties({anchor:new t.DataConstantProperty(t.styleSpec.light.anchor),position:new b,color:new t.DataConstantProperty(t.styleSpec.light.color),intensity:new t.DataConstantProperty(t.styleSpec.light.intensity)}),w=function(e){function r(r){e.call(this),this._transitionable=new t.Transitionable(_),this.setLight(r),this._transitioning=this._transitionable.untransitioned()}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getLight=function(){return this._transitionable.serialize()},r.prototype.setLight=function(e,r){if(void 0===r&&(r={}),!this._validate(t.validateLight,e,r))for(var n in e){var a=e[n];t.endsWith(n,"-transition")?this._transitionable.setTransition(n.slice(0,-"-transition".length),a):this._transitionable.setValue(n,a)}},r.prototype.updateTransitions=function(t){this._transitioning=this._transitionable.transitioned(t,this._transitioning)},r.prototype.hasTransition=function(){return this._transitioning.hasTransition()},r.prototype.recalculate=function(t){this.properties=this._transitioning.possiblyEvaluate(t)},r.prototype._validate=function(e,r,n){return(!n||!1!==n.validate)&&t.emitValidationErrors(this,e.call(t.validateStyle,t.extend({value:r,style:{glyphs:!0,sprite:!0},styleSpec:t.styleSpec})))},r}(t.Evented),T=function(t,e){this.width=t,this.height=e,this.nextRow=0,this.data=new Uint8Array(this.width*this.height),this.dashEntry={}};T.prototype.getDash=function(t,e){var r=t.join(",")+String(e);return this.dashEntry[r]||(this.dashEntry[r]=this.addDash(t,e)),this.dashEntry[r]},T.prototype.getDashRanges=function(t,e,r){var n=[],a=t.length%2==1?-t[t.length-1]*r:0,i=t[0]*r,o=!0;n.push({left:a,right:i,isDash:o,zeroLength:0===t[0]});for(var s=t[0],l=1;l<t.length;l++){var c=t[l];n.push({left:a=s*r,right:i=(s+=c)*r,isDash:o=!o,zeroLength:0===c})}return n},T.prototype.addRoundDash=function(t,e,r){for(var n=e/2,a=-r;a<=r;a++)for(var i=this.width*(this.nextRow+r+a),o=0,s=t[o],l=0;l<this.width;l++){l/s.right>1&&(s=t[++o]);var c=Math.abs(l-s.left),u=Math.abs(l-s.right),h=Math.min(c,u),f=void 0,p=a/r*(n+1);if(s.isDash){var d=n-Math.abs(p);f=Math.sqrt(h*h+d*d)}else f=n-Math.sqrt(h*h+p*p);this.data[i+l]=Math.max(0,Math.min(255,f+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var a=t[0],i=t[t.length-1];a.isDash===i.isDash&&(a.left=i.left-this.width,i.right=a.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c<this.width;c++){c/l.right>1&&(l=t[++s]);var u=Math.abs(c-l.left),h=Math.abs(c-l.right),f=Math.min(u,h);this.data[o+c]=Math.max(0,Math.min(255,(l.isDash?f:-f)+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,a=2*n+1;if(this.nextRow+a>this.height)return t.warnOnce("LineAtlas out of space"),null;for(var i=0,o=0;o<e.length;o++)i+=e[o];if(0!==i){var s=this.width/i,l=this.getDashRanges(e,this.width,s);r?this.addRoundDash(l,s,n):this.addRegularDash(l)}var c={y:(this.nextRow+n+.5)/this.height,height:2*n/this.height,width:i};return this.nextRow+=a,this.dirty=!0,c},T.prototype.bind=function(t){var e=t.gl;this.texture?(e.bindTexture(e.TEXTURE_2D,this.texture),this.dirty&&(this.dirty=!1,e.texSubImage2D(e.TEXTURE_2D,0,0,0,this.width,this.height,e.ALPHA,e.UNSIGNED_BYTE,this.data))):(this.texture=e.createTexture(),e.bindTexture(e.TEXTURE_2D,this.texture),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_S,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_WRAP_T,e.REPEAT),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MIN_FILTER,e.LINEAR),e.texParameteri(e.TEXTURE_2D,e.TEXTURE_MAG_FILTER,e.LINEAR),e.texImage2D(e.TEXTURE_2D,0,e.ALPHA,this.width,this.height,0,e.ALPHA,e.UNSIGNED_BYTE,this.data))};var k=function e(r,n){this.workerPool=r,this.actors=[],this.currentActor=0,this.id=t.uniqueId();for(var a=this.workerPool.acquire(this.id),i=0;i<a.length;i++){var o=new e.Actor(a[i],n,this.id);o.name="Worker "+i,this.actors.push(o)}};function A(e,r,n){var a=function(a,i){if(a)return n(a);if(i){var o=t.pick(t.extend(i,e),["tiles","minzoom","maxzoom","attribution","mapbox_logo","bounds","scheme","tileSize","encoding"]);i.vector_layers&&(o.vectorLayers=i.vector_layers,o.vectorLayerIds=o.vectorLayers.map((function(t){return t.id}))),o.tiles=r.canonicalizeTileset(o,e.url),n(null,o)}};return e.url?t.getJSON(r.transformRequest(r.normalizeSourceURL(e.url),t.ResourceType.Source),a):t.browser.frame((function(){return a(null,e)}))}k.prototype.broadcast=function(e,r,n){t.asyncAll(this.actors,(function(t,n){t.send(e,r,n)}),n=n||function(){})},k.prototype.getActor=function(){return this.currentActor=(this.currentActor+1)%this.actors.length,this.actors[this.currentActor]},k.prototype.remove=function(){this.actors.forEach((function(t){t.remove()})),this.actors=[],this.workerPool.release(this.id)},k.Actor=t.Actor;var M=function(e,r,n){this.bounds=t.LngLatBounds.convert(this.validateBounds(e)),this.minzoom=r||0,this.maxzoom=n||24};M.prototype.validateBounds=function(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]},M.prototype.contains=function(e){var r=Math.pow(2,e.z),n=Math.floor(t.mercatorXfromLng(this.bounds.getWest())*r),a=Math.floor(t.mercatorYfromLat(this.bounds.getNorth())*r),i=Math.ceil(t.mercatorXfromLng(this.bounds.getEast())*r),o=Math.ceil(t.mercatorYfromLat(this.bounds.getSouth())*r);return e.x>=n&&e.x<i&&e.y>=a&&e.y<o};var S=function(e){function r(r,n,a,i){if(e.call(this),this.id=r,this.dispatcher=a,this.type="vector",this.minzoom=0,this.maxzoom=22,this.scheme="xyz",this.tileSize=512,this.reparseOverscaled=!0,this.isTileClipped=!0,this._loaded=!1,t.extend(this,t.pick(n,["url","scheme","tileSize","promoteId"])),this._options=t.extend({type:"vector"},n),this._collectResourceTiming=n.collectResourceTiming,512!==this.tileSize)throw new Error("vector tile sources must have a tileSize of 512");this.setEventedParent(i)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles,e.map._requestManager._customAccessToken),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken,e.map._requestManager._customAccessToken),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme)),a={request:this.map._requestManager.transformRequest(n,t.ResourceType.Tile),uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,tileSize:this.tileSize*e.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};function i(n,a){return delete e.request,e.aborted?r(null):n&&404!==n.status?r(n):(a&&a.resourceTiming&&(e.resourceTiming=a.resourceTiming),this.map._refreshExpiredTiles&&a&&e.setExpiryData(a),e.loadVectorData(a,this.map.painter),t.cacheEntryPossiblyAdded(this.dispatcher),r(null),void(e.reloadCallback&&(this.loadTile(e,e.reloadCallback),e.reloadCallback=null)))}a.request.collectResourceTiming=this._collectResourceTiming,e.actor&&"expired"!==e.state?"loading"===e.state?e.reloadCallback=r:e.request=e.actor.send("reloadTile",a,i.bind(this)):(e.actor=this.dispatcher.getActor(),e.request=e.actor.send("loadTile",a,i.bind(this)))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.actor&&t.actor.send("abortTile",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.unloadTile=function(t){t.unloadVectorData(),t.actor&&t.actor.send("removeTile",{uid:t.uid,type:this.type,source:this.id},void 0)},r.prototype.hasTransition=function(){return!1},r}(t.Evented),E=function(e){function r(r,n,a,i){e.call(this),this.id=r,this.dispatcher=a,this.setEventedParent(i),this.type="raster",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme="xyz",this.tileSize=512,this._loaded=!1,this._options=t.extend({type:"raster"},n),t.extend(this,t.pick(n,["url","scheme","tileSize"]))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this._tileJSONRequest=A(this._options,this.map._requestManager,(function(r,n){e._tileJSONRequest=null,e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(t.extend(e,n),n.bounds&&(e.tileBounds=new M(n.bounds,e.minzoom,e.maxzoom)),t.postTurnstileEvent(n.tiles),t.postMapLoadEvent(n.tiles,e.map._getMapId(),e.map._requestManager._skuToken),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})),e.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.onRemove=function(){this._tileJSONRequest&&(this._tileJSONRequest.cancel(),this._tileJSONRequest=null)},r.prototype.serialize=function(){return t.extend({},this._options)},r.prototype.hasTile=function(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)},r.prototype.loadTile=function(e,r){var n=this,a=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);e.request=t.getImage(this.map._requestManager.transformRequest(a,t.ResourceType.Tile),(function(a,i){if(delete e.request,e.aborted)e.state="unloaded",r(null);else if(a)e.state="errored",r(a);else if(i){n.map._refreshExpiredTiles&&e.setExpiryData(i),delete i.cacheControl,delete i.expires;var o=n.map.painter.context,s=o.gl;e.texture=n.map.painter.getTileTexture(i.width),e.texture?e.texture.update(i,{useMipmap:!0}):(e.texture=new t.Texture(o,i,s.RGBA,{useMipmap:!0}),e.texture.bind(s.LINEAR,s.CLAMP_TO_EDGE,s.LINEAR_MIPMAP_NEAREST),o.extTextureFilterAnisotropic&&s.texParameterf(s.TEXTURE_2D,o.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,o.extTextureFilterAnisotropicMax)),e.state="loaded",t.cacheEntryPossiblyAdded(n.dispatcher),r(null)}}))},r.prototype.abortTile=function(t,e){t.request&&(t.request.cancel(),delete t.request),e()},r.prototype.unloadTile=function(t,e){t.texture&&this.map.painter.saveTileTexture(t.texture),e()},r.prototype.hasTransition=function(){return!1},r}(t.Evented),C=function(e){function r(r,n,a,i){e.call(this,r,n,a,i),this.type="raster-dem",this.maxzoom=22,this._options=t.extend({type:"raster-dem"},n),this.encoding=n.encoding||"mapbox"}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.serialize=function(){return{type:"raster-dem",url:this.url,tileSize:this.tileSize,tiles:this.tiles,bounds:this.bounds,encoding:this.encoding}},r.prototype.loadTile=function(e,r){var n=this.map._requestManager.normalizeTileURL(e.tileID.canonical.url(this.tiles,this.scheme),this.tileSize);function a(t,n){t&&(e.state="errored",r(t)),n&&(e.dem=n,e.needsHillshadePrepare=!0,e.state="loaded",r(null))}e.request=t.getImage(this.map._requestManager.transformRequest(n,t.ResourceType.Tile),function(n,i){if(delete e.request,e.aborted)e.state="unloaded",r(null);else if(n)e.state="errored",r(n);else if(i){this.map._refreshExpiredTiles&&e.setExpiryData(i),delete i.cacheControl,delete i.expires;var o=t.window.ImageBitmap&&i instanceof t.window.ImageBitmap&&t.offscreenCanvasSupported()?i:t.browser.getImageData(i,1),s={uid:e.uid,coord:e.tileID,source:this.id,rawImageData:o,encoding:this.encoding};e.actor&&"expired"!==e.state||(e.actor=this.dispatcher.getActor(),e.actor.send("loadDEMTile",s,a.bind(this)))}}.bind(this)),e.neighboringTiles=this._getNeighboringTiles(e.tileID)},r.prototype._getNeighboringTiles=function(e){var r=e.canonical,n=Math.pow(2,r.z),a=(r.x-1+n)%n,i=0===r.x?e.wrap-1:e.wrap,o=(r.x+1+n)%n,s=r.x+1===n?e.wrap+1:e.wrap,l={};return l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+1<n&&(l[new t.OverscaledTileID(e.overscaledZ,i,r.z,a,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y+1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y+1).key]={backfilled:!1}),l},r.prototype.unloadTile=function(t){t.demTexture&&this.map.painter.saveTileTexture(t.demTexture),t.fbo&&(t.fbo.destroy(),delete t.fbo),t.dem&&delete t.dem,delete t.neighboringTiles,t.state="unloaded",t.actor&&t.actor.send("removeDEMTile",{uid:t.uid,source:this.id})},r}(E),L=function(e){function r(r,n,a,i){e.call(this),this.id=r,this.type="geojson",this.minzoom=0,this.maxzoom=18,this.tileSize=512,this.isTileClipped=!0,this.reparseOverscaled=!0,this._removed=!1,this._loaded=!1,this.actor=a.getActor(),this.setEventedParent(i),this._data=n.data,this._options=t.extend({},n),this._collectResourceTiming=n.collectResourceTiming,this._resourceTiming=[],void 0!==n.maxzoom&&(this.maxzoom=n.maxzoom),n.type&&(this.type=n.type),n.attribution&&(this.attribution=n.attribution),this.promoteId=n.promoteId;var o=t.EXTENT/this.tileSize;this.workerOptions=t.extend({source:this.id,cluster:n.cluster||!1,geojsonVtOptions:{buffer:(void 0!==n.buffer?n.buffer:128)*o,tolerance:(void 0!==n.tolerance?n.tolerance:.375)*o,extent:t.EXTENT,maxZoom:this.maxzoom,lineMetrics:n.lineMetrics||!1,generateId:n.generateId||!1},superclusterOptions:{maxZoom:void 0!==n.clusterMaxZoom?Math.min(n.clusterMaxZoom,this.maxzoom-1):this.maxzoom-1,extent:t.EXTENT,radius:(n.clusterRadius||50)*o,log:!1,generateId:n.generateId||!1},clusterProperties:n.clusterProperties},n.workerOptions)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this.fire(new t.Event("dataloading",{dataType:"source"})),this._updateWorkerData((function(r){if(r)e.fire(new t.ErrorEvent(r));else{var n={dataType:"source",sourceDataType:"metadata"};e._collectResourceTiming&&e._resourceTiming&&e._resourceTiming.length>0&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event("data",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event("dataloading",{dataType:"source"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:"source",sourceDataType:"content"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event("data",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send("geojson.getClusterExpansionZoom",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send("geojson.getClusterChildren",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send("geojson.getClusterLeaves",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),a=this._data;"string"==typeof a?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(a),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(a),this.actor.send(this.type+".loadData",n,(function(t,a){r._removed||a&&a.abandoned||(r._loaded=!0,a&&a.resourceTiming&&a.resourceTiming[r.id]&&(r._resourceTiming=a.resourceTiming[r.id].slice(0)),r.actor.send(r.type+".coalesce",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,a=e.actor?"reloadTile":"loadTile";e.actor=this.actor,e.request=this.actor.send(a,{type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId},(function(t,i){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(i,n.map.painter,"reloadTile"===a),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send("removeTile",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send("removeSource",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),P=t.createLayout([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]),I=function(e){function r(t,r,n,a){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(a),this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(a,i){n._loaded=!0,a?n.fire(new t.ErrorEvent(a)):i&&(n.image=i,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,a=-1/0,i=-1/0,o=0,s=e;o<s.length;o+=1){var l=s[o];r=Math.min(r,l.x),n=Math.min(n,l.y),a=Math.max(a,l.x),i=Math.max(i,l.y)}var c=Math.max(a-r,i-n),u=Math.max(0,Math.floor(-Math.log(c)/Math.LN2)),h=Math.pow(2,u);return new t.CanonicalTileID(u,Math.floor((r+a)/2*h),Math.floor((n+i)/2*h))}(n),this.minzoom=this.maxzoom=this.tileID.z;var a=n.map((function(t){return r.tileID.getTilePoint(t)._round()}));return this._boundsArray=new t.StructArrayLayout4i8,this._boundsArray.emplaceBack(a[0].x,a[0].y,0,0),this._boundsArray.emplaceBack(a[1].x,a[1].y,t.EXTENT,0),this._boundsArray.emplaceBack(a[3].x,a[3].y,0,t.EXTENT),this._boundsArray.emplaceBack(a[2].x,a[2].y,t.EXTENT,t.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.Event("data",{dataType:"source",sourceDataType:"content"})),this},r.prototype.prepare=function(){if(0!==Object.keys(this.tiles).length&&this.image){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new t.Texture(e,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var a=this.tiles[n];"loaded"!==a.state&&(a.state="loaded",a.texture=this.texture)}}},r.prototype.loadTile=function(t,e){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={},e(null)):(t.state="errored",e(null))},r.prototype.serialize=function(){return{type:"image",url:this.options.url,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return!1},r}(t.Evented),z=function(e){function r(t,r,n,a){e.call(this,t,r,n,a),this.roundZoom=!0,this.type="video",this.options=r}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){var e=this;this._loaded=!1;var r=this.options;this.urls=[];for(var n=0,a=r.urls;n<a.length;n+=1)this.urls.push(this.map._requestManager.transformRequest(a[n],t.ResourceType.Source).url);t.getVideo(this.urls,(function(r,n){e._loaded=!0,r?e.fire(new t.ErrorEvent(r)):n&&(e.video=n,e.video.loop=!0,e.video.addEventListener("playing",(function(){e.map.triggerRepaint()})),e.map&&e.video.play(),e._finishLoading())}))},r.prototype.pause=function(){this.video&&this.video.pause()},r.prototype.play=function(){this.video&&this.video.play()},r.prototype.seek=function(e){if(this.video){var r=this.video.seekable;e<r.start(0)||e>r.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError("sources."+this.id,null,"Playback for this video can be set only between the "+r.start(0)+" and "+r.end(0)+"-second mark."))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var a=this.tiles[n];"loaded"!==a.state&&(a.state="loaded",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"video",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(I),O=function(e){function r(r,n,a,i){e.call(this,r,n,a,i),n.coordinates?Array.isArray(n.coordinates)&&4===n.coordinates.length&&!n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return"number"!=typeof t}))}))||this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "coordinates"'))),n.animate&&"boolean"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'optional "animate" property must be a boolean value'))),n.canvas?"string"==typeof n.canvas||n.canvas instanceof t.window.HTMLCanvasElement||this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "canvas"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var a in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,P.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var i=this.tiles[a];"loaded"!==i.state&&(i.state="loaded",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"canvas",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];t<e.length;t+=1){var r=e[t];if(isNaN(r)||r<=0)return!0}return!1},r}(I),D={vector:S,raster:E,"raster-dem":C,geojson:L,video:z,image:I,canvas:O};function R(e,r){var n=t.identity([]);return t.translate(n,n,[1,1,0]),t.scale(n,n,[.5*e.width,.5*e.height,1]),t.multiply(n,n,e.calculatePosMatrix(r.toUnwrapped()))}function F(t,e,r,n,a,i){var o=function(t,e,r){if(t)for(var n=0,a=t;n<a.length;n+=1){var i=e[a[n]];if(i&&i.source===r&&"fill-extrusion"===i.type)return!0}else for(var o in e){var s=e[o];if(s.source===r&&"fill-extrusion"===s.type)return!0}return!1}(a&&a.layers,e,t.id),s=i.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(B);for(var c=[],u=0,h=l;u<h.length;u+=1){var f=h[u];c.push({wrappedTileID:f.tileID.wrapped().key,queryResults:f.tile.queryRenderedFeatures(e,r,t._state,f.queryGeometry,f.cameraQueryGeometry,f.scale,a,i,s,R(t.transform,f.tileID))})}var p=function(t){for(var e={},r={},n=0,a=t;n<a.length;n+=1){var i=a[n],o=i.queryResults,s=i.wrappedTileID,l=r[s]=r[s]||{};for(var c in o)for(var u=o[c],h=l[c]=l[c]||{},f=e[c]=e[c]||[],p=0,d=u;p<d.length;p+=1){var g=d[p];h[g.featureIndex]||(h[g.featureIndex]=!0,f.push(g))}}return e}(c);for(var d in p)p[d].forEach((function(e){var r=e.feature,n=t.getFeatureState(r.layer["source-layer"],r.id);r.source=r.layer.source,r.layer["source-layer"]&&(r.sourceLayer=r.layer["source-layer"]),r.state=n}));return p}function B(t,e){var r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}var N=function(t,e){this.max=t,this.onRemove=e,this.reset()};N.prototype.reset=function(){for(var t in this.data)for(var e=0,r=this.data[t];e<r.length;e+=1){var n=r[e];n.timeout&&clearTimeout(n.timeout),this.onRemove(n.value)}return this.data={},this.order=[],this},N.prototype.add=function(t,e,r){var n=this,a=t.wrapped().key;void 0===this.data[a]&&(this.data[a]=[]);var i={value:e,timeout:void 0};if(void 0!==r&&(i.timeout=setTimeout((function(){n.remove(t,i)}),r)),this.data[a].push(i),this.order.push(a),this.order.length>this.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},N.prototype.has=function(t){return t.wrapped().key in this.data},N.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},N.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},N.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},N.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},N.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),a=this.data[r][n];return this.data[r].splice(n,1),a.timeout&&clearTimeout(a.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(a.value),this.order.splice(this.order.indexOf(r),1),this},N.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},N.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,a=this.data[r];n<a.length;n+=1){var i=a[n];t(i.value)||e.push(i)}for(var o=0,s=e;o<s.length;o+=1){var l=s[o];this.remove(l.value.tileID,l)}};var j=function(t,e,r){this.context=t;var n=t.gl;this.buffer=n.createBuffer(),this.dynamicDraw=Boolean(r),this.context.unbindVAO(),t.bindElementBuffer.set(this.buffer),n.bufferData(n.ELEMENT_ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?n.DYNAMIC_DRAW:n.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};j.prototype.bind=function(){this.context.bindElementBuffer.set(this.buffer)},j.prototype.updateData=function(t){var e=this.context.gl;this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)},j.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var V={Int8:"BYTE",Uint8:"UNSIGNED_BYTE",Int16:"SHORT",Uint16:"UNSIGNED_SHORT",Int32:"INT",Uint32:"UNSIGNED_INT",Float32:"FLOAT"},U=function(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;var a=t.gl;this.buffer=a.createBuffer(),t.bindVertexBuffer.set(this.buffer),a.bufferData(a.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?a.DYNAMIC_DRAW:a.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer};U.prototype.bind=function(){this.context.bindVertexBuffer.set(this.buffer)},U.prototype.updateData=function(t){var e=this.context.gl;this.bind(),e.bufferSubData(e.ARRAY_BUFFER,0,t.arrayBuffer)},U.prototype.enableAttributes=function(t,e){for(var r=0;r<this.attributes.length;r++){var n=e.attributes[this.attributes[r].name];void 0!==n&&t.enableVertexAttribArray(n)}},U.prototype.setVertexAttribPointers=function(t,e,r){for(var n=0;n<this.attributes.length;n++){var a=this.attributes[n],i=e.attributes[a.name];void 0!==i&&t.vertexAttribPointer(i,a.components,t[V[a.type]],!1,this.itemSize,a.offset+this.itemSize*(r||0))}},U.prototype.destroy=function(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)};var q=function(t){this.gl=t.gl,this.default=this.getDefault(),this.current=this.default,this.dirty=!1};q.prototype.get=function(){return this.current},q.prototype.set=function(t){},q.prototype.getDefault=function(){return this.default},q.prototype.setDefault=function(){this.set(this.default)};var H=function(e){function r(){e.apply(this,arguments)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getDefault=function(){return t.Color.transparent},r.prototype.set=function(t){var e=this.current;(t.r!==e.r||t.g!==e.g||t.b!==e.b||t.a!==e.a||this.dirty)&&(this.gl.clearColor(t.r,t.g,t.b,t.a),this.current=t,this.dirty=!1)},r}(q),G=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.getDefault=function(){return 1},e.prototype.set=function(t){(t!==this.current||this.dirty)&&(this.gl.clearDepth(t),this.current=t,this.dirty=!1)},e}(q),Y=function(t){function 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t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.set=function(t){if(t!==this.current||this.dirty){this.context.bindFramebuffer.set(this.parent);var e=this.gl;e.framebufferRenderbuffer(e.FRAMEBUFFER,e.DEPTH_ATTACHMENT,e.RENDERBUFFER,t),this.current=t,this.dirty=!1}},e}(_t),kt=function(t,e,r,n){this.context=t,this.width=e,this.height=r;var a=this.framebuffer=t.gl.createFramebuffer();this.colorAttachment=new wt(t,a),n&&(this.depthAttachment=new Tt(t,a))};kt.prototype.destroy=function(){var t=this.context.gl,e=this.colorAttachment.get();if(e&&t.deleteTexture(e),this.depthAttachment){var r=this.depthAttachment.get();r&&t.deleteRenderbuffer(r)}t.deleteFramebuffer(this.framebuffer)};var At=function(t,e,r){this.func=t,this.mask=e,this.range=r};At.ReadOnly=!1,At.ReadWrite=!0,At.disabled=new At(519,At.ReadOnly,[0,1]);var Mt=function(t,e,r,n,a,i){this.test=t,this.ref=e,this.mask=r,this.fail=n,this.depthFail=a,this.pass=i};Mt.disabled=new Mt({func:519,mask:0},0,0,7680,7680,7680);var St=function(t,e,r){this.blendFunction=t,this.blendColor=e,this.mask=r};St.disabled=new St(St.Replace=[1,0],t.Color.transparent,[!1,!1,!1,!1]),St.unblended=new St(St.Replace,t.Color.transparent,[!0,!0,!0,!0]),St.alphaBlended=new St([1,771],t.Color.transparent,[!0,!0,!0,!0]);var Et=function(t,e,r){this.enable=t,this.mode=e,this.frontFace=r};Et.disabled=new Et(!1,1029,2305),Et.backCCW=new Et(!0,1029,2305);var Ct=function(t){this.gl=t,this.extVertexArrayObject=this.gl.getExtension("OES_vertex_array_object"),this.clearColor=new H(this),this.clearDepth=new G(this),this.clearStencil=new Y(this),this.colorMask=new W(this),this.depthMask=new Z(this),this.stencilMask=new X(this),this.stencilFunc=new J(this),this.stencilOp=new K(this),this.stencilTest=new Q(this),this.depthRange=new $(this),this.depthTest=new tt(this),this.depthFunc=new et(this),this.blend=new rt(this),this.blendFunc=new nt(this),this.blendColor=new at(this),this.blendEquation=new it(this),this.cullFace=new ot(this),this.cullFaceSide=new st(this),this.frontFace=new lt(this),this.program=new ct(this),this.activeTexture=new ut(this),this.viewport=new ht(this),this.bindFramebuffer=new ft(this),this.bindRenderbuffer=new pt(this),this.bindTexture=new dt(this),this.bindVertexBuffer=new gt(this),this.bindElementBuffer=new mt(this),this.bindVertexArrayOES=this.extVertexArrayObject&&new vt(this),this.pixelStoreUnpack=new yt(this),this.pixelStoreUnpackPremultiplyAlpha=new xt(this),this.pixelStoreUnpackFlipY=new bt(this),this.extTextureFilterAnisotropic=t.getExtension("EXT_texture_filter_anisotropic")||t.getExtension("MOZ_EXT_texture_filter_anisotropic")||t.getExtension("WEBKIT_EXT_texture_filter_anisotropic"),this.extTextureFilterAnisotropic&&(this.extTextureFilterAnisotropicMax=t.getParameter(this.extTextureFilterAnisotropic.MAX_TEXTURE_MAX_ANISOTROPY_EXT)),this.extTextureHalfFloat=t.getExtension("OES_texture_half_float"),this.extTextureHalfFloat&&(t.getExtension("OES_texture_half_float_linear"),this.extRenderToTextureHalfFloat=t.getExtension("EXT_color_buffer_half_float")),this.extTimerQuery=t.getExtension("EXT_disjoint_timer_query")};Ct.prototype.setDefault=function(){this.unbindVAO(),this.clearColor.setDefault(),this.clearDepth.setDefault(),this.clearStencil.setDefault(),this.colorMask.setDefault(),this.depthMask.setDefault(),this.stencilMask.setDefault(),this.stencilFunc.setDefault(),this.stencilOp.setDefault(),this.stencilTest.setDefault(),this.depthRange.setDefault(),this.depthTest.setDefault(),this.depthFunc.setDefault(),this.blend.setDefault(),this.blendFunc.setDefault(),this.blendColor.setDefault(),this.blendEquation.setDefault(),this.cullFace.setDefault(),this.cullFaceSide.setDefault(),this.frontFace.setDefault(),this.program.setDefault(),this.activeTexture.setDefault(),this.bindFramebuffer.setDefault(),this.pixelStoreUnpack.setDefault(),this.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.pixelStoreUnpackFlipY.setDefault()},Ct.prototype.setDirty=function(){this.clearColor.dirty=!0,this.clearDepth.dirty=!0,this.clearStencil.dirty=!0,this.colorMask.dirty=!0,this.depthMask.dirty=!0,this.stencilMask.dirty=!0,this.stencilFunc.dirty=!0,this.stencilOp.dirty=!0,this.stencilTest.dirty=!0,this.depthRange.dirty=!0,this.depthTest.dirty=!0,this.depthFunc.dirty=!0,this.blend.dirty=!0,this.blendFunc.dirty=!0,this.blendColor.dirty=!0,this.blendEquation.dirty=!0,this.cullFace.dirty=!0,this.cullFaceSide.dirty=!0,this.frontFace.dirty=!0,this.program.dirty=!0,this.activeTexture.dirty=!0,this.viewport.dirty=!0,this.bindFramebuffer.dirty=!0,this.bindRenderbuffer.dirty=!0,this.bindTexture.dirty=!0,this.bindVertexBuffer.dirty=!0,this.bindElementBuffer.dirty=!0,this.extVertexArrayObject&&(this.bindVertexArrayOES.dirty=!0),this.pixelStoreUnpack.dirty=!0,this.pixelStoreUnpackPremultiplyAlpha.dirty=!0,this.pixelStoreUnpackFlipY.dirty=!0},Ct.prototype.createIndexBuffer=function(t,e){return new j(this,t,e)},Ct.prototype.createVertexBuffer=function(t,e,r){return new U(this,t,e,r)},Ct.prototype.createRenderbuffer=function(t,e,r){var n=this.gl,a=n.createRenderbuffer();return this.bindRenderbuffer.set(a),n.renderbufferStorage(n.RENDERBUFFER,t,e,r),this.bindRenderbuffer.set(null),a},Ct.prototype.createFramebuffer=function(t,e,r){return new kt(this,t,e,r)},Ct.prototype.clear=function(t){var e=t.color,r=t.depth,n=this.gl,a=0;e&&(a|=n.COLOR_BUFFER_BIT,this.clearColor.set(e),this.colorMask.set([!0,!0,!0,!0])),void 0!==r&&(a|=n.DEPTH_BUFFER_BIT,this.depthRange.set([0,1]),this.clearDepth.set(r),this.depthMask.set(!0)),n.clear(a)},Ct.prototype.setCullFace=function(t){!1===t.enable?this.cullFace.set(!1):(this.cullFace.set(!0),this.cullFaceSide.set(t.mode),this.frontFace.set(t.frontFace))},Ct.prototype.setDepthMode=function(t){t.func!==this.gl.ALWAYS||t.mask?(this.depthTest.set(!0),this.depthFunc.set(t.func),this.depthMask.set(t.mask),this.depthRange.set(t.range)):this.depthTest.set(!1)},Ct.prototype.setStencilMode=function(t){t.test.func!==this.gl.ALWAYS||t.mask?(this.stencilTest.set(!0),this.stencilMask.set(t.mask),this.stencilOp.set([t.fail,t.depthFail,t.pass]),this.stencilFunc.set({func:t.test.func,ref:t.ref,mask:t.test.mask})):this.stencilTest.set(!1)},Ct.prototype.setColorMode=function(e){t.deepEqual(e.blendFunction,St.Replace)?this.blend.set(!1):(this.blend.set(!0),this.blendFunc.set(e.blendFunction),this.blendColor.set(e.blendColor)),this.colorMask.set(e.mask)},Ct.prototype.unbindVAO=function(){this.extVertexArrayObject&&this.bindVertexArrayOES.set(null)};var Lt=function(e){function r(r,n,a){var i=this;e.call(this),this.id=r,this.dispatcher=a,this.on("data",(function(t){"source"===t.dataType&&"metadata"===t.sourceDataType&&(i._sourceLoaded=!0),i._sourceLoaded&&!i._paused&&"source"===t.dataType&&"content"===t.sourceDataType&&(i.reload(),i.transform&&i.update(i.transform))})),this.on("error",(function(){i._sourceErrored=!0})),this._source=function(e,r,n,a){var i=new D[r.type](e,r,n,a);if(i.id!==e)throw new Error("Expected Source id to be "+e+" instead of "+i.id);return t.bindAll(["load","abort","unload","serialize","prepare"],i),i}(r,n,a,this),this._tiles={},this._cache=new N(0,this._unloadTile.bind(this)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new t.SourceFeatureState}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.onAdd=function(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._source&&this._source.onAdd&&this._source.onAdd(t)},r.prototype.onRemove=function(t){this._source&&this._source.onRemove&&this._source.onRemove(t)},r.prototype.loaded=function(){if(this._sourceErrored)return!0;if(!this._sourceLoaded)return!1;if(!this._source.loaded())return!1;for(var t in this._tiles){var e=this._tiles[t];if("loaded"!==e.state&&"errored"!==e.state)return!1}return!0},r.prototype.getSource=function(){return this._source},r.prototype.pause=function(){this._paused=!0},r.prototype.resume=function(){if(this._paused){var t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform)}},r.prototype._loadTile=function(t,e){return this._source.loadTile(t,e)},r.prototype._unloadTile=function(t){if(this._source.unloadTile)return this._source.unloadTile(t,(function(){}))},r.prototype._abortTile=function(t){if(this._source.abortTile)return this._source.abortTile(t,(function(){}))},r.prototype.serialize=function(){return this._source.serialize()},r.prototype.prepare=function(t){for(var e in this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null),this._tiles){var r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}},r.prototype.getIds=function(){return t.values(this._tiles).map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.getRenderableIds=function(e){var r=this,n=[];for(var a in this._tiles)this._isIdRenderable(a,e)&&n.push(this._tiles[a]);return e?n.sort((function(e,n){var a=e.tileID,i=n.tileID,o=new t.Point(a.canonical.x,a.canonical.y)._rotate(r.transform.angle),s=new t.Point(i.canonical.x,i.canonical.y)._rotate(r.transform.angle);return a.overscaledZ-i.overscaledZ||s.y-o.y||s.x-o.x})).map((function(t){return t.tileID.key})):n.map((function(t){return t.tileID})).sort(Pt).map((function(t){return t.key}))},r.prototype.hasRenderableParent=function(t){var e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)},r.prototype._isIdRenderable=function(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())},r.prototype.reload=function(){if(this._paused)this._shouldReloadOnResume=!0;else for(var t in this._cache.reset(),this._tiles)"errored"!==this._tiles[t].state&&this._reloadTile(t,"reloading")},r.prototype._reloadTile=function(t,e){var r=this._tiles[t];r&&("loading"!==r.state&&(r.state=e),this._loadTile(r,this._tileLoaded.bind(this,r,t,e)))},r.prototype._tileLoaded=function(e,r,n,a){if(a)return e.state="errored",void(404!==a.status?this._source.fire(new t.ErrorEvent(a,{tile:e})):this.update(this.transform));e.timeAdded=t.browser.now(),"expired"===n&&(e.refreshedUponExpiration=!0),this._setTileReloadTimer(r,e),"raster-dem"===this.getSource().type&&e.dem&&this._backfillDEM(e),this._state.initializeTileState(e,this.map?this.map.painter:null),this._source.fire(new t.Event("data",{dataType:"source",tile:e,coord:e.tileID}))},r.prototype._backfillDEM=function(t){for(var e=this.getRenderableIds(),r=0;r<e.length;r++){var n=e[r];if(t.neighboringTiles&&t.neighboringTiles[n]){var a=this.getTileByID(n);i(t,a),i(a,t)}}function i(t,e){t.needsHillshadePrepare=!0;var r=e.tileID.canonical.x-t.tileID.canonical.x,n=e.tileID.canonical.y-t.tileID.canonical.y,a=Math.pow(2,t.tileID.canonical.z),i=e.tileID.key;0===r&&0===n||Math.abs(n)>1||(Math.abs(r)>1&&(1===Math.abs(r+a)?r+=a:1===Math.abs(r-a)&&(r-=a)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[i]&&(t.neighboringTiles[i].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var a in this._tiles){var i=this._tiles[a];if(!(n[a]||!i.hasData()||i.tileID.overscaledZ<=e||i.tileID.overscaledZ>r)){for(var o=i.tileID;i&&i.tileID.overscaledZ>e+1;){var s=i.tileID.scaledTo(i.tileID.overscaledZ-1);(i=this._tiles[s.key])&&i.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var a=t.scaledTo(n),i=this._getLoadedTile(a);if(i)return i}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=Math.ceil(t.width/this._source.tileSize)+1,r=Math.ceil(t.height/this._source.tileSize)+1,n=Math.floor(e*r*5),a="number"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,n):n;this._cache.setMaxSize(a)},r.prototype.handleWrapJump=function(t){var e=Math.round((t-(void 0===this._prevLng?t:this._prevLng))/360);if(this._prevLng=t,e){var r={};for(var n in this._tiles){var a=this._tiles[n];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+e),r[a.tileID.key]=a}for(var i in this._tiles=r,this._timers)clearTimeout(this._timers[i]),delete this._timers[i];for(var o in this._tiles)this._setTileReloadTimer(o,this._tiles[o])}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var a;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?a=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(a=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(a=a.filter((function(t){return n._source.hasTile(t)})))):a=[];var i=e.coveringZoomLevel(this._source),o=Math.max(i-r.maxOverzooming,this._source.minzoom),s=Math.max(i+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(a,i);if(It(this._source.type)){for(var c={},u={},h=0,f=Object.keys(l);h<f.length;h+=1){var p=f[h],d=l[p],g=this._tiles[p];if(g&&!(g.fadeEndTime&&g.fadeEndTime<=t.browser.now())){var m=this.findLoadedParent(d,o);m&&(this._addTile(m.tileID),c[m.tileID.key]=m.tileID),u[p]=d}}for(var v in this._retainLoadedChildren(u,i,s,l),c)l[v]||(this._coveredTiles[v]=!0,l[v]=c[v])}for(var y in l)this._tiles[y].clearFadeHold();for(var x=0,b=t.keysDifference(this._tiles,l);x<b.length;x+=1){var _=b[x],w=this._tiles[_];w.hasSymbolBuckets&&!w.holdingForFade()?w.setHoldDuration(this.map._fadeDuration):w.hasSymbolBuckets&&!w.symbolFadeFinished()||this._removeTile(_)}this._updateLoadedParentTileCache()}},r.prototype.releaseSymbolFadeTiles=function(){for(var t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)},r.prototype._updateRetainedTiles=function(t,e){for(var n={},a={},i=Math.max(e-r.maxOverzooming,this._source.minzoom),o=Math.max(e+r.maxUnderzooming,this._source.minzoom),s={},l=0,c=t;l<c.length;l+=1){var u=c[l],h=this._addTile(u);n[u.key]=u,h.hasData()||e<this._source.maxzoom&&(s[u.key]=u)}this._retainLoadedChildren(s,e,o,n);for(var f=0,p=t;f<p.length;f+=1){var d=p[f],g=this._tiles[d.key];if(!g.hasData()){if(e+1>this._source.maxzoom){var m=d.children(this._source.maxzoom)[0],v=this.getTile(m);if(v&&v.hasData()){n[m.key]=m;continue}}else{var y=d.children(this._source.maxzoom);if(n[y[0].key]&&n[y[1].key]&&n[y[2].key]&&n[y[3].key])continue}for(var x=g.wasRequested(),b=d.overscaledZ-1;b>=i;--b){var _=d.scaledTo(b);if(a[_.key])break;if(a[_.key]=!0,!(g=this.getTile(_))&&x&&(g=this._addTile(_)),g&&(n[_.key]=_,x=g.wasRequested(),g.hasData()))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var a=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(a))break;n=a}for(var i=0,o=e;i<o.length;i+=1)this._loadedParentTiles[o[i]]=r}},r.prototype._addTile=function(e){var r=this._tiles[e.key];if(r)return r;(r=this._cache.getAndRemove(e))&&(this._setTileReloadTimer(e.key,r),r.tileID=e,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[e.key]&&(clearTimeout(this._cacheTimers[e.key]),delete this._cacheTimers[e.key],this._setTileReloadTimer(e.key,r)));var n=Boolean(r);return n||(r=new t.Tile(e,this._source.tileSize*e.overscaleFactor()),this._loadTile(r,this._tileLoaded.bind(this,r,e.key,r.state))),r?(r.uses++,this._tiles[e.key]=r,n||this._source.fire(new t.Event("dataloading",{tile:r,coord:r.tileID,dataType:"source"})),r):null},r.prototype._setTileReloadTimer=function(t,e){var r=this;t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);var n=e.getExpiryTimeout();n&&(this._timers[t]=setTimeout((function(){r._reloadTile(t,"expired"),delete r._timers[t]}),n))},r.prototype._removeTile=function(t){var e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&"reloading"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var a=this,i=[],o=this.transform;if(!o)return i;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),h=1/0,f=1/0,p=-1/0,d=-1/0,g=0,m=c;g<m.length;g+=1){var v=m[g];h=Math.min(h,v.x),f=Math.min(f,v.y),p=Math.max(p,v.x),d=Math.max(d,v.y)}for(var y=function(e){var n=a._tiles[u[e]];if(!n.holdingForFade()){var s=n.tileID,g=Math.pow(2,o.zoom-n.tileID.overscaledZ),m=r*n.queryPadding*t.EXTENT/n.tileSize/g,v=[s.getTilePoint(new t.MercatorCoordinate(h,f)),s.getTilePoint(new t.MercatorCoordinate(p,d))];if(v[0].x-m<t.EXTENT&&v[0].y-m<t.EXTENT&&v[1].x+m>=0&&v[1].y+m>=0){var y=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));i.push({tile:n,tileID:s,queryGeometry:y,cameraQueryGeometry:x,scale:g})}}},x=0;x<u.length;x++)y(x);return i},r.prototype.getVisibleCoordinates=function(t){for(var e=this,r=this.getRenderableIds(t).map((function(t){return e._tiles[t].tileID})),n=0,a=r;n<a.length;n+=1){var i=a[n];i.posMatrix=this.transform.calculatePosMatrix(i.toUnwrapped())}return r},r.prototype.hasTransition=function(){if(this._source.hasTransition())return!0;if(It(this._source.type))for(var e in this._tiles){var r=this._tiles[e];if(void 0!==r.fadeEndTime&&r.fadeEndTime>=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){this._state.updateState(t=t||"_geojsonTileLayer",e,r)},r.prototype.removeFeatureState=function(t,e,r){this._state.removeFeatureState(t=t||"_geojsonTileLayer",e,r)},r.prototype.getFeatureState=function(t,e){return this._state.getState(t=t||"_geojsonTileLayer",e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,"reloading");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function It(t){return"raster"===t||"image"===t||"video"===t}function zt(){return new t.window.Worker(Ya.workerUrl)}Lt.maxOverzooming=10,Lt.maxUnderzooming=3;var Ot="mapboxgl_preloaded_worker_pool",Dt=function(){this.active={}};Dt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length<Dt.workerCount;)this.workers.push(new zt);return this.active[t]=!0,this.workers.slice()},Dt.prototype.release=function(t){delete this.active[t],0===this.numActive()&&(this.workers.forEach((function(t){t.terminate()})),this.workers=null)},Dt.prototype.isPreloaded=function(){return!!this.active[Ot]},Dt.prototype.numActive=function(){return Object.keys(this.active).length};var Rt,Ft=Math.floor(t.browser.hardwareConcurrency/2);function Bt(){return Rt||(Rt=new Dt),Rt}function Nt(e,r){var n={};for(var a in e)"ref"!==a&&(n[a]=e[a]);return t.refProperties.forEach((function(t){t in r&&(n[t]=r[t])})),n}function jt(t){t=t.slice();for(var e=Object.create(null),r=0;r<t.length;r++)e[t[r].id]=t[r];for(var n=0;n<t.length;n++)"ref"in t[n]&&(t[n]=Nt(t[n],e[t[n].ref]));return t}Dt.workerCount=Math.max(Math.min(Ft,6),1);var Vt={setStyle:"setStyle",addLayer:"addLayer",removeLayer:"removeLayer",setPaintProperty:"setPaintProperty",setLayoutProperty:"setLayoutProperty",setFilter:"setFilter",addSource:"addSource",removeSource:"removeSource",setGeoJSONSourceData:"setGeoJSONSourceData",setLayerZoomRange:"setLayerZoomRange",setLayerProperty:"setLayerProperty",setCenter:"setCenter",setZoom:"setZoom",setBearing:"setBearing",setPitch:"setPitch",setSprite:"setSprite",setGlyphs:"setGlyphs",setTransition:"setTransition",setLight:"setLight"};function Ut(t,e,r){r.push({command:Vt.addSource,args:[t,e[t]]})}function qt(t,e,r){e.push({command:Vt.removeSource,args:[t]}),r[t]=!0}function Ht(t,e,r,n){qt(t,r,n),Ut(t,e,r)}function Gt(e,r,n){var a;for(a in e[n])if(e[n].hasOwnProperty(a)&&"data"!==a&&!t.deepEqual(e[n][a],r[n][a]))return!1;for(a in r[n])if(r[n].hasOwnProperty(a)&&"data"!==a&&!t.deepEqual(e[n][a],r[n][a]))return!1;return!0}function Yt(e,r,n,a,i,o){var s;for(s in r=r||{},e=e||{})e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[a,s,r[s],i]}));for(s in r)r.hasOwnProperty(s)&&!e.hasOwnProperty(s)&&(t.deepEqual(e[s],r[s])||n.push({command:o,args:[a,s,r[s],i]}))}function Wt(t){return t.id}function Zt(t,e){return t[e.id]=e,t}var Xt=function(t,e){this.reset(t,e)};Xt.prototype.reset=function(t,e){this.points=t||[],this._distances=[0];for(var r=1;r<this.points.length;r++)this._distances[r]=this._distances[r-1]+this.points[r].dist(this.points[r-1]);this.length=this._distances[this._distances.length-1],this.padding=Math.min(e||0,.5*this.length),this.paddedLength=this.length-2*this.padding},Xt.prototype.lerp=function(e){if(1===this.points.length)return this.points[0];e=t.clamp(e,0,1);for(var r=1,n=this._distances[r],a=e*this.paddedLength+this.padding;n<a&&r<this._distances.length;)n=this._distances[++r];var i=r-1,o=this._distances[i],s=n-o,l=s>0?(a-o)/s:0;return this.points[i].mult(1-l).add(this.points[r].mult(l))};var Jt=function(t,e,r){var n=this.boxCells=[],a=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var i=0;i<this.xCellCount*this.yCellCount;i++)n.push([]),a.push([]);this.circleKeys=[],this.boxKeys=[],this.bboxes=[],this.circles=[],this.width=t,this.height=e,this.xScale=this.xCellCount/t,this.yScale=this.yCellCount/e,this.boxUid=0,this.circleUid=0};function Kt(e,r,n,a,i){var o=t.create();return r?(t.scale(o,o,[1/i,1/i,1]),n||t.rotateZ(o,o,a.angle)):t.multiply(o,a.labelPlaneMatrix,e),o}function Qt(e,r,n,a,i){if(r){var o=t.clone(e);return t.scale(o,o,[i,i,1]),n||t.rotateZ(o,o,-a.angle),o}return a.glCoordMatrix}function $t(e,r){var n=[e.x,e.y,0,1];ue(n,n,r);var a=n[3];return{point:new t.Point(n[0]/a,n[1]/a),signedDistanceFromCamera:a}}function te(t,e){return.5+t/e*.5}function ee(t,e){var r=t[0]/t[3],n=t[1]/t[3];return r>=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function re(e,r,n,a,i,o,s,l){var c=a?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),h=[256/n.width*2+1,256/n.height*2+1],f=a?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;f.clear();for(var p=e.lineVertexArray,d=a?e.text.placedSymbolArray:e.icon.placedSymbolArray,g=n.transform.width/n.transform.height,m=!1,v=0;v<d.length;v++){var y=d.get(v);if(y.hidden||y.writingMode===t.WritingMode.vertical&&!m)ce(y.numGlyphs,f);else{m=!1;var x=[y.anchorX,y.anchorY,0,1];if(t.transformMat4(x,x,r),ee(x,h)){var b=te(n.transform.cameraToCenterDistance,x[3]),_=t.evaluateSizeForFeature(c,u,y),w=s?_/b:_*b,T=new t.Point(y.anchorX,y.anchorY),k=$t(T,i).point,A={},M=ie(y,w,!1,l,r,i,o,e.glyphOffsetArray,p,f,k,T,A,g);m=M.useVertical,(M.notEnoughRoom||m||M.needsFlipping&&ie(y,w,!0,l,r,i,o,e.glyphOffsetArray,p,f,k,T,A,g).notEnoughRoom)&&ce(y.numGlyphs,f)}else ce(y.numGlyphs,f)}}a?e.text.dynamicLayoutVertexBuffer.updateData(f):e.icon.dynamicLayoutVertexBuffer.updateData(f)}function ne(t,e,r,n,a,i,o,s,l,c,u){var h=s.glyphStartIndex+s.numGlyphs,f=s.lineStartIndex,p=s.lineStartIndex+s.lineLength,d=e.getoffsetX(s.glyphStartIndex),g=e.getoffsetX(h-1),m=se(t*d,r,n,a,i,o,s.segment,f,p,l,c,u);if(!m)return null;var v=se(t*g,r,n,a,i,o,s.segment,f,p,l,c,u);return v?{first:m,last:v}:null}function ae(e,r,n,a){return e===t.WritingMode.horizontal&&Math.abs(n.y-r.y)>Math.abs(n.x-r.x)*a?{useVertical:!0}:(e===t.WritingMode.vertical?r.y<n.y:r.x>n.x)?{needsFlipping:!0}:null}function ie(e,r,n,a,i,o,s,l,c,u,h,f,p,d){var g,m=r/24,v=e.lineOffsetX*m,y=e.lineOffsetY*m;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,b=e.lineStartIndex,_=e.lineStartIndex+e.lineLength,w=ne(m,l,v,y,n,h,f,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=$t(w.first.point,s).point,k=$t(w.last.point,s).point;if(a&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}g=[w.first];for(var M=e.glyphStartIndex+1;M<x-1;M++)g.push(se(m*l.getoffsetX(M),v,y,n,h,f,e.segment,b,_,c,o,p));g.push(w.last)}else{if(a&&!n){var S=$t(f,i).point,E=e.lineStartIndex+e.segment+1,C=new t.Point(c.getx(E),c.gety(E)),L=$t(C,i),P=L.signedDistanceFromCamera>0?L.point:oe(f,C,S,1,i),I=ae(e.writingMode,S,P,d);if(I)return I}var z=se(m*l.getoffsetX(e.glyphStartIndex),v,y,n,h,f,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!z)return{notEnoughRoom:!0};g=[z]}for(var O=0,D=g;O<D.length;O+=1){var R=D[O];t.addDynamicAttributes(u,R.point,R.angle)}return{}}function oe(t,e,r,n,a){var i=$t(t.add(t.sub(e)._unit()),a).point,o=r.sub(i);return r.add(o._mult(n/o.mag()))}function se(e,r,n,a,i,o,s,l,c,u,h,f){var p=a?e-r:e+r,d=p>0?1:-1,g=0;a&&(d*=-1,g=Math.PI),d<0&&(g+=Math.PI);for(var m=d>0?l+s:l+s+1,v=i,y=i,x=0,b=0,_=Math.abs(p),w=[];x+b<=_;){if((m+=d)<l||m>=c)return null;if(y=v,w.push(v),void 0===(v=f[m])){var T=new t.Point(u.getx(m),u.gety(m)),k=$t(T,h);if(k.signedDistanceFromCamera>0)v=f[m]=k.point;else{var A=m-d;v=oe(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,y,_-x+1,h)}}x+=b,b=y.dist(v)}var M=(_-x)/b,S=v.sub(y),E=S.mult(M)._add(y);E._add(S._unit()._perp()._mult(n*d));var C=g+Math.atan2(v.y-y.y,v.x-y.x);return w.push(E),{point:E,angle:C,path:w}}Jt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Jt.prototype.insert=function(t,e,r,n,a){this._forEachCell(e,r,n,a,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(a)},Jt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Jt.prototype._insertBoxCell=function(t,e,r,n,a,i){this.boxCells[a].push(i)},Jt.prototype._insertCircleCell=function(t,e,r,n,a,i){this.circleCells[a].push(i)},Jt.prototype._query=function(t,e,r,n,a,i){if(r<0||t>this.width||n<0||e>this.height)return!a&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(a)return!0;for(var s=0;s<this.boxKeys.length;s++)o.push({key:this.boxKeys[s],x1:this.bboxes[4*s],y1:this.bboxes[4*s+1],x2:this.bboxes[4*s+2],y2:this.bboxes[4*s+3]});for(var l=0;l<this.circleKeys.length;l++){var c=this.circles[3*l],u=this.circles[3*l+1],h=this.circles[3*l+2];o.push({key:this.circleKeys[l],x1:c-h,y1:u-h,x2:c+h,y2:u+h})}return i?o.filter(i):o}return this._forEachCell(t,e,r,n,this._queryCell,o,{hitTest:a,seenUids:{box:{},circle:{}}},i),a?o.length>0:o},Jt.prototype._queryCircle=function(t,e,r,n,a){var i=t-r,o=t+r,s=e-r,l=e+r;if(o<0||i>this.width||l<0||s>this.height)return!n&&[];var c=[];return this._forEachCell(i,s,o,l,this._queryCellCircle,c,{hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}},a),n?c.length>0:c},Jt.prototype.query=function(t,e,r,n,a){return this._query(t,e,r,n,!1,a)},Jt.prototype.hitTest=function(t,e,r,n,a){return this._query(t,e,r,n,!0,a)},Jt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Jt.prototype._queryCell=function(t,e,r,n,a,i,o,s){var l=o.seenUids,c=this.boxCells[a];if(null!==c)for(var u=this.bboxes,h=0,f=c;h<f.length;h+=1){var p=f[h];if(!l.box[p]){l.box[p]=!0;var d=4*p;if(t<=u[d+2]&&e<=u[d+3]&&r>=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return i.push(!0),!0;i.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var g=this.circleCells[a];if(null!==g)for(var m=this.circles,v=0,y=g;v<y.length;v+=1){var x=y[v];if(!l.circle[x]){l.circle[x]=!0;var b=3*x;if(this._circleAndRectCollide(m[b],m[b+1],m[b+2],t,e,r,n)&&(!s||s(this.circleKeys[x]))){if(o.hitTest)return i.push(!0),!0;var _=m[b],w=m[b+1],T=m[b+2];i.push({key:this.circleKeys[x],x1:_-T,y1:w-T,x2:_+T,y2:w+T})}}}},Jt.prototype._queryCellCircle=function(t,e,r,n,a,i,o,s){var l=o.circle,c=o.seenUids,u=this.boxCells[a];if(null!==u)for(var h=this.bboxes,f=0,p=u;f<p.length;f+=1){var d=p[f];if(!c.box[d]){c.box[d]=!0;var g=4*d;if(this._circleAndRectCollide(l.x,l.y,l.radius,h[g+0],h[g+1],h[g+2],h[g+3])&&(!s||s(this.boxKeys[d])))return i.push(!0),!0}}var m=this.circleCells[a];if(null!==m)for(var v=this.circles,y=0,x=m;y<x.length;y+=1){var b=x[y];if(!c.circle[b]){c.circle[b]=!0;var _=3*b;if(this._circlesCollide(v[_],v[_+1],v[_+2],l.x,l.y,l.radius)&&(!s||s(this.circleKeys[b])))return i.push(!0),!0}}},Jt.prototype._forEachCell=function(t,e,r,n,a,i,o,s){for(var l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),h=this._convertToYCellCoord(n),f=l;f<=u;f++)for(var p=c;p<=h;p++)if(a.call(this,t,e,r,n,this.xCellCount*p+f,i,o,s))return},Jt.prototype._convertToXCellCoord=function(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))},Jt.prototype._convertToYCellCoord=function(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))},Jt.prototype._circlesCollide=function(t,e,r,n,a,i){var o=n-t,s=a-e,l=r+i;return l*l>o*o+s*s},Jt.prototype._circleAndRectCollide=function(t,e,r,n,a,i,o){var s=(i-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-a)/2,u=Math.abs(e-(a+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var h=l-s,f=u-c;return h*h+f*f<=r*r};var le=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ce(t,e){for(var r=0;r<t;r++){var n=e.length;e.resize(n+4),e.float32.set(le,3*n)}}function ue(t,e,r){var n=e[0],a=e[1];return t[0]=r[0]*n+r[4]*a+r[12],t[1]=r[1]*n+r[5]*a+r[13],t[3]=r[3]*n+r[7]*a+r[15],t}var he=function(t,e,r){void 0===e&&(e=new Jt(t.width+200,t.height+200,25)),void 0===r&&(r=new Jt(t.width+200,t.height+200,25)),this.transform=t,this.grid=e,this.ignoredGrid=r,this.pitchfactor=Math.cos(t._pitch)*t.cameraToCenterDistance,this.screenRightBoundary=t.width+100,this.screenBottomBoundary=t.height+100,this.gridRightBoundary=t.width+200,this.gridBottomBoundary=t.height+200};function fe(e,r,n){return r*(t.EXTENT/(e.tileSize*Math.pow(2,n-e.tileID.overscaledZ)))}he.prototype.placeCollisionBox=function(t,e,r,n,a){var i=this.projectAndGetPerspectiveRatio(n,t.anchorPointX,t.anchorPointY),o=r*i.perspectiveRatio,s=t.x1*o+i.point.x,l=t.y1*o+i.point.y,c=t.x2*o+i.point.x,u=t.y2*o+i.point.y;return!this.isInsideGrid(s,l,c,u)||!e&&this.grid.hitTest(s,l,c,u,a)?{box:[],offscreen:!1}:{box:[s,l,c,u],offscreen:this.isOffscreen(s,l,c,u)}},he.prototype.placeCollisionCircles=function(e,r,n,a,i,o,s,l,c,u,h,f,p){var d=[],g=new t.Point(r.anchorX,r.anchorY),m=$t(g,o),v=te(this.transform.cameraToCenterDistance,m.signedDistanceFromCamera),y=(u?i/v:i*v)/t.ONE_EM,x=$t(g,s).point,b=ne(y,a,r.lineOffsetX*y,r.lineOffsetY*y,!1,x,g,r,n,s,{}),_=!1,w=!1,T=!0;if(b){for(var k=.5*f*v+p,A=new t.Point(-100,-100),M=new t.Point(this.screenRightBoundary,this.screenBottomBoundary),S=new Xt,E=b.first,C=b.last,L=[],P=E.path.length-1;P>=1;P--)L.push(E.path[P]);for(var I=1;I<C.path.length;I++)L.push(C.path[I]);var z=2.5*k;if(l){var O=L.map((function(t){return $t(t,l)}));L=O.some((function(t){return t.signedDistanceFromCamera<=0}))?[]:O.map((function(t){return t.point}))}var D=[];if(L.length>0){for(var R=L[0].clone(),F=L[0].clone(),B=1;B<L.length;B++)R.x=Math.min(R.x,L[B].x),R.y=Math.min(R.y,L[B].y),F.x=Math.max(F.x,L[B].x),F.y=Math.max(F.y,L[B].y);D=R.x>=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[L]:F.x<A.x||R.x>M.x||F.y<A.y||R.y>M.y?[]:t.clipLine([L],A.x,A.y,M.x,M.y)}for(var N=0,j=D;N<j.length;N+=1){var V;S.reset(j[N],.25*k),V=S.length<=.5*k?1:Math.ceil(S.paddedLength/z)+1;for(var U=0;U<V;U++){var q=U/Math.max(V-1,1),H=S.lerp(q),G=H.x+100,Y=H.y+100;d.push(G,Y,k,0);var W=G-k,Z=Y-k,X=G+k,J=Y+k;if(T=T&&this.isOffscreen(W,Z,X,J),w=w||this.isInsideGrid(W,Z,X,J),!e&&this.grid.hitTestCircle(G,Y,k,h)&&(_=!0,!c))return{circles:[],offscreen:!1,collisionDetected:_}}}}return{circles:!c&&_||!w?[]:d,offscreen:T,collisionDetected:_}},he.prototype.queryRenderedSymbols=function(e){if(0===e.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};for(var r=[],n=1/0,a=1/0,i=-1/0,o=-1/0,s=0,l=e;s<l.length;s+=1){var c=l[s],u=new t.Point(c.x+100,c.y+100);n=Math.min(n,u.x),a=Math.min(a,u.y),i=Math.max(i,u.x),o=Math.max(o,u.y),r.push(u)}for(var h={},f={},p=0,d=this.grid.query(n,a,i,o).concat(this.ignoredGrid.query(n,a,i,o));p<d.length;p+=1){var g=d[p],m=g.key;if(void 0===h[m.bucketInstanceId]&&(h[m.bucketInstanceId]={}),!h[m.bucketInstanceId][m.featureIndex]){var v=[new t.Point(g.x1,g.y1),new t.Point(g.x2,g.y1),new t.Point(g.x2,g.y2),new t.Point(g.x1,g.y2)];t.polygonIntersectsPolygon(r,v)&&(h[m.bucketInstanceId][m.featureIndex]=!0,void 0===f[m.bucketInstanceId]&&(f[m.bucketInstanceId]=[]),f[m.bucketInstanceId].push(m.featureIndex))}}return f},he.prototype.insertCollisionBox=function(t,e,r,n,a){(e?this.ignoredGrid:this.grid).insert({bucketInstanceId:r,featureIndex:n,collisionGroupID:a},t[0],t[1],t[2],t[3])},he.prototype.insertCollisionCircles=function(t,e,r,n,a){for(var i=e?this.ignoredGrid:this.grid,o={bucketInstanceId:r,featureIndex:n,collisionGroupID:a},s=0;s<t.length;s+=4)i.insertCircle(o,t[s],t[s+1],t[s+2])},he.prototype.projectAndGetPerspectiveRatio=function(e,r,n){var a=[r,n,0,1];return ue(a,a,e),{point:new t.Point((a[0]/a[3]+1)/2*this.transform.width+100,(-a[1]/a[3]+1)/2*this.transform.height+100),perspectiveRatio:.5+this.transform.cameraToCenterDistance/a[3]*.5}},he.prototype.isOffscreen=function(t,e,r,n){return r<100||t>=this.screenRightBoundary||n<100||e>this.screenBottomBoundary},he.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t<this.gridRightBoundary&&n>=0&&e<this.gridBottomBoundary},he.prototype.getViewportMatrix=function(){var e=t.identity([]);return t.translate(e,e,[-100,-100,0]),e};var pe=function(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r};pe.prototype.isHidden=function(){return 0===this.opacity&&!this.placed};var de=function(t,e,r,n,a){this.text=new pe(t?t.text:null,e,r,a),this.icon=new pe(t?t.icon:null,e,n,a)};de.prototype.isHidden=function(){return this.text.isHidden()&&this.icon.isHidden()};var ge=function(t,e,r){this.text=t,this.icon=e,this.skipFade=r},me=function(){this.invProjMatrix=t.create(),this.viewportMatrix=t.create(),this.circles=[]},ve=function(t,e,r,n,a){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=a},ye=function(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}};function xe(e,r,n,a,i){var o=t.getAnchorAlignment(e),s=-(o.horizontalAlign-.5)*r,l=-(o.verticalAlign-.5)*n,c=t.evaluateVariableOffset(e,a);return new t.Point(s+c[0]*i,l+c[1]*i)}function be(e,r,n,a,i,o){var s=e.x1,l=e.x2,c=e.y1,u=e.y2,h=e.anchorPointX,f=e.anchorPointY,p=new t.Point(r,n);return a&&p._rotate(i?o:-o),{x1:s+p.x,y1:c+p.y,x2:l+p.x,y2:u+p.y,anchorPointX:h,anchorPointY:f}}ye.prototype.get=function(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){var e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:function(t){return t.collisionGroupID===e}}}return this.collisionGroups[t]};var _e=function(t,e,r,n){this.transform=t.clone(),this.collisionIndex=new he(this.transform),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=e,this.retainedQueryData={},this.collisionGroups=new ye(r),this.collisionCircleArrays={},this.prevPlacement=n,n&&(n.prevPlacement=void 0),this.placedOrientations={}};function we(t,e,r,n,a){t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0),t.emplaceBack(e?1:0,r?1:0,n||0,a||0)}_e.prototype.getBucketParts=function(e,r,n,a){var i=n.getBucket(r),o=n.latestFeatureIndex;if(i&&o&&r.id===i.layerIds[0]){var s=n.collisionBoxArray,l=i.layers[0].layout,c=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),u=n.tileSize/t.EXTENT,h=this.transform.calculatePosMatrix(n.tileID.toUnwrapped()),f="map"===l.get("text-pitch-alignment"),p="map"===l.get("text-rotation-alignment"),d=fe(n,1,this.transform.zoom),g=Kt(h,f,p,this.transform,d),m=null;if(f){var v=Qt(h,f,p,this.transform,d);m=t.multiply([],this.transform.labelPlaneMatrix,v)}this.retainedQueryData[i.bucketInstanceId]=new ve(i.bucketInstanceId,o,i.sourceLayerIndex,i.index,n.tileID);var y={bucket:i,layout:l,posMatrix:h,textLabelPlaneMatrix:g,labelToScreenMatrix:m,scale:c,textPixelRatio:u,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:t.evaluateSizeForZoom(i.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(i.sourceID)};if(a)for(var x=0,b=i.sortKeyRanges;x<b.length;x+=1){var _=b[x];e.push({sortKey:_.sortKey,symbolInstanceStart:_.symbolInstanceStart,symbolInstanceEnd:_.symbolInstanceEnd,parameters:y})}else e.push({symbolInstanceStart:0,symbolInstanceEnd:i.symbolInstances.length,parameters:y})}},_e.prototype.attemptAnchorPlacement=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d){var g,m=[h.textOffset0,h.textOffset1],v=xe(t,r,n,m,a),y=this.collisionIndex.placeCollisionBox(be(e,v.x,v.y,i,o,this.transform.angle),u,s,l,c.predicate);if(!d||0!==this.collisionIndex.placeCollisionBox(be(d,v.x,v.y,i,o,this.transform.angle),u,s,l,c.predicate).box.length)return y.box.length>0?(this.prevPlacement&&this.prevPlacement.variableOffsets[h.crossTileID]&&this.prevPlacement.placements[h.crossTileID]&&this.prevPlacement.placements[h.crossTileID].text&&(g=this.prevPlacement.variableOffsets[h.crossTileID].anchor),this.variableOffsets[h.crossTileID]={textOffset:m,width:r,height:n,anchor:t,textBoxScale:a,prevAnchor:g},this.markUsedJustification(f,t,h,p),f.allowVerticalPlacement&&(this.markUsedOrientation(f,p,h),this.placedOrientations[h.crossTileID]=p),{shift:v,placedGlyphBoxes:y}):void 0},_e.prototype.placeLayerBucketPart=function(e,r,n){var a=this,i=e.parameters,o=i.bucket,s=i.layout,l=i.posMatrix,c=i.textLabelPlaneMatrix,u=i.labelToScreenMatrix,h=i.textPixelRatio,f=i.holdingForFade,p=i.collisionBoxArray,d=i.partiallyEvaluatedTextSize,g=i.collisionGroup,m=s.get("text-optional"),v=s.get("icon-optional"),y=s.get("text-allow-overlap"),x=s.get("icon-allow-overlap"),b="map"===s.get("text-rotation-alignment"),_="map"===s.get("text-pitch-alignment"),w="none"!==s.get("icon-text-fit"),T="viewport-y"===s.get("symbol-z-order"),k=y&&(x||!o.hasIconData()||v),A=x&&(y||!o.hasTextData()||m);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,i){if(!r[e.crossTileID])if(f)a.placements[e.crossTileID]=new ge(!1,!1,!1);else{var p,T=!1,M=!1,S=!0,E=null,C={box:null,offscreen:null},L={box:null,offscreen:null},P=null,I=null,z=0,O=0,D=0;i.textFeatureIndex?z=i.textFeatureIndex:e.useRuntimeCollisionCircles&&(z=e.featureIndex),i.verticalTextFeatureIndex&&(O=i.verticalTextFeatureIndex);var R=i.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&a.prevPlacement){var i=a.prevPlacement.placedOrientations[e.crossTileID];i&&(a.placedOrientations[e.crossTileID]=i,a.markUsedOrientation(o,n=i,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&i.verticalTextBox)for(var a=0,s=o.writingModes;a<s.length&&(s[a]===t.WritingMode.vertical?(C=n(),L=C):C=r(),!(C&&C.box&&C.box.length));a+=1);else C=r()};if(s.get("text-variable-anchor")){var N=s.get("text-variable-anchor");if(a.prevPlacement&&a.prevPlacement.variableOffsets[e.crossTileID]){var j=a.prevPlacement.variableOffsets[e.crossTileID];N.indexOf(j.anchor)>0&&(N=N.filter((function(t){return t!==j.anchor}))).unshift(j.anchor)}var V=function(t,r,n){for(var i=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,f={box:[],offscreen:!1},p=y?2*N.length:N.length,d=0;d<p;++d){var m=a.attemptAnchorPlacement(N[d%N.length],t,i,s,c,b,_,h,l,g,d>=N.length,e,o,n,u);if(m&&(f=m.placedGlyphBoxes)&&f.box&&f.box.length){T=!0,E=m.shift;break}}return f};B((function(){return V(R,i.iconBox,t.WritingMode.horizontal)}),(function(){var r=i.verticalTextBox;return o.allowVerticalPlacement&&!(C&&C.box&&C.box.length)&&e.numVerticalGlyphVertices>0&&r?V(r,i.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),C&&(T=C.box,S=C.offscreen);var U=F(C&&C.box);if(!T&&a.prevPlacement){var q=a.prevPlacement.variableOffsets[e.crossTileID];q&&(a.variableOffsets[e.crossTileID]=q,a.markUsedJustification(o,q.anchor,e,U))}}else{var H=function(t,r){var n=a.collisionIndex.placeCollisionBox(t,y,h,l,g.predicate);return n&&n.box&&n.box.length&&(a.markUsedOrientation(o,r,e),a.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=i.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(C&&C.box&&C.box.length)}}if(T=(p=C)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),Y=t.evaluateSizeForFeature(o.textSizeData,d,G),W=s.get("text-padding");P=a.collisionIndex.placeCollisionCircles(y,G,o.lineVertexArray,o.glyphOffsetArray,Y,l,c,u,n,_,g.predicate,e.collisionCircleDiameter,W),T=y||P.circles.length>0&&!P.collisionDetected,S=S&&P.offscreen}if(i.iconFeatureIndex&&(D=i.iconFeatureIndex),i.iconBox){var Z=function(t){var e=w&&E?be(t,E.x,E.y,b,_,a.transform.angle):t;return a.collisionIndex.placeCollisionBox(e,x,h,l,g.predicate)};M=L&&L.box&&L.box.length&&i.verticalIconBox?(I=Z(i.verticalIconBox)).box.length>0:(I=Z(i.iconBox)).box.length>0,S=S&&I.offscreen}var X=m||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,J=v||0===e.numIconVertices;if(X||J?J?X||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&a.collisionIndex.insertCollisionBox(p.box,s.get("text-ignore-placement"),o.bucketInstanceId,L&&L.box&&O?O:z,g.ID),M&&I&&a.collisionIndex.insertCollisionBox(I.box,s.get("icon-ignore-placement"),o.bucketInstanceId,D,g.ID),P&&(T&&a.collisionIndex.insertCollisionCircles(P.circles,s.get("text-ignore-placement"),o.bucketInstanceId,z,g.ID),n)){var K=o.bucketInstanceId,Q=a.collisionCircleArrays[K];void 0===Q&&(Q=a.collisionCircleArrays[K]=new me);for(var $=0;$<P.circles.length;$+=4)Q.circles.push(P.circles[$+0]),Q.circles.push(P.circles[$+1]),Q.circles.push(P.circles[$+2]),Q.circles.push(P.collisionDetected?1:0)}a.placements[e.crossTileID]=new ge(T||k,M||A,S||o.justReloaded),r[e.crossTileID]=!0}};if(T)for(var S=o.getSortedSymbolIndexes(this.transform.angle),E=S.length-1;E>=0;--E){var C=S[E];M(o.symbolInstances.get(C),o.collisionArrays[C])}else for(var L=e.symbolInstanceStart;L<e.symbolInstanceEnd;L++)M(o.symbolInstances.get(L),o.collisionArrays[L]);if(n&&o.bucketInstanceId in this.collisionCircleArrays){var P=this.collisionCircleArrays[o.bucketInstanceId];t.invert(P.invProjMatrix,l),P.viewportMatrix=this.collisionIndex.getViewportMatrix()}o.justReloaded=!1},_e.prototype.markUsedJustification=function(e,r,n,a){var i;i=a===t.WritingMode.vertical?n.verticalPlacedTextSymbolIndex:{left:n.leftJustifiedTextSymbolIndex,center:n.centerJustifiedTextSymbolIndex,right:n.rightJustifiedTextSymbolIndex}[t.getAnchorJustification(r)];for(var o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex,n.verticalPlacedTextSymbolIndex];o<s.length;o+=1){var l=s[o];l>=0&&(e.text.placedSymbolArray.get(l).crossTileID=i>=0&&l!==i?0:n.crossTileID)}},_e.prototype.markUsedOrientation=function(e,r,n){for(var a=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,i=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o<s.length;o+=1)e.text.placedSymbolArray.get(s[o]).placedOrientation=a;n.verticalPlacedTextSymbolIndex&&(e.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=i)},_e.prototype.commit=function(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;var e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;var n=e?e.symbolFadeChange(t):1,a=e?e.opacities:{},i=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(var s in this.placements){var l=this.placements[s],c=a[s];c?(this.opacities[s]=new de(c,n,l.text,l.icon),r=r||l.text!==c.text.placed||l.icon!==c.icon.placed):(this.opacities[s]=new de(null,n,l.text,l.icon,l.skipFade),r=r||l.text||l.icon)}for(var u in a){var h=a[u];if(!this.opacities[u]){var f=new de(h,n,!1,!1);f.isHidden()||(this.opacities[u]=f,r=r||h.text.placed||h.icon.placed)}}for(var p in i)this.variableOffsets[p]||!this.opacities[p]||this.opacities[p].isHidden()||(this.variableOffsets[p]=i[p]);for(var d in o)this.placedOrientations[d]||!this.opacities[d]||this.opacities[d].isHidden()||(this.placedOrientations[d]=o[d]);r?this.lastPlacementChangeTime=t:"number"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)},_e.prototype.updateLayerOpacities=function(t,e){for(var r={},n=0,a=e;n<a.length;n+=1){var i=a[n],o=i.getBucket(t);o&&i.latestFeatureIndex&&t.id===o.layerIds[0]&&this.updateBucketOpacities(o,r,i.collisionBoxArray)}},_e.prototype.updateBucketOpacities=function(e,r,n){var a=this;e.hasTextData()&&e.text.opacityVertexArray.clear(),e.hasIconData()&&e.icon.opacityVertexArray.clear(),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexArray.clear(),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexArray.clear();var i=e.layers[0].layout,o=new de(null,0,!1,!1,!0),s=i.get("text-allow-overlap"),l=i.get("icon-allow-overlap"),c=i.get("text-variable-anchor"),u="map"===i.get("text-rotation-alignment"),h="map"===i.get("text-pitch-alignment"),f="none"!==i.get("icon-text-fit"),p=new de(null,0,s&&(l||!e.hasIconData()||i.get("icon-optional")),l&&(s||!e.hasTextData()||i.get("text-optional")),!0);!e.collisionArrays&&n&&(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData())&&e.deserializeCollisionBoxes(n);for(var d=function(t,e,r){for(var n=0;n<e/4;n++)t.opacityVertexArray.emplaceBack(r)},g=function(n){var i=e.symbolInstances.get(n),s=i.numHorizontalGlyphVertices,l=i.numVerticalGlyphVertices,g=i.crossTileID,m=a.opacities[g];r[g]?m=o:m||(a.opacities[g]=m=p),r[g]=!0;var v=i.numIconVertices>0,y=a.placedOrientations[i.crossTileID],x=y===t.WritingMode.vertical,b=y===t.WritingMode.horizontal||y===t.WritingMode.horizontalOnly;if(s>0||l>0){var _=Le(m.text);d(e.text,s,x?Pe:_),d(e.text,l,b?Pe:_);var w=m.text.isHidden();[i.rightJustifiedTextSymbolIndex,i.centerJustifiedTextSymbolIndex,i.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=w||x?1:0)})),i.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(i.verticalPlacedTextSymbolIndex).hidden=w||b?1:0);var T=a.variableOffsets[i.crossTileID];T&&a.markUsedJustification(e,T.anchor,i,y);var k=a.placedOrientations[i.crossTileID];k&&(a.markUsedJustification(e,"left",i,k),a.markUsedOrientation(e,k,i))}if(v){var A=Le(m.icon),M=!(f&&i.verticalPlacedIconSymbolIndex&&x);i.placedIconSymbolIndex>=0&&(d(e.icon,i.numIconVertices,M?A:Pe),e.icon.placedSymbolArray.get(i.placedIconSymbolIndex).hidden=m.icon.isHidden()),i.verticalPlacedIconSymbolIndex>=0&&(d(e.icon,i.numVerticalIconVertices,M?Pe:A),e.icon.placedSymbolArray.get(i.verticalPlacedIconSymbolIndex).hidden=m.icon.isHidden())}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var S=e.collisionArrays[n];if(S){var E=new t.Point(0,0);if(S.textBox||S.verticalTextBox){var C=!0;if(c){var L=a.variableOffsets[g];L?(E=xe(L.anchor,L.width,L.height,L.textOffset,L.textBoxScale),u&&E._rotate(h?a.transform.angle:-a.transform.angle)):C=!1}S.textBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||x,E.x,E.y),S.verticalTextBox&&we(e.textCollisionBox.collisionVertexArray,m.text.placed,!C||b,E.x,E.y)}var P=Boolean(!b&&S.verticalIconBox);S.iconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,P,f?E.x:0,f?E.y:0),S.verticalIconBox&&we(e.iconCollisionBox.collisionVertexArray,m.icon.placed,!P,f?E.x:0,f?E.y:0)}}},m=0;m<e.symbolInstances.length;m++)g(m);if(e.sortFeatures(this.transform.angle),this.retainedQueryData[e.bucketInstanceId]&&(this.retainedQueryData[e.bucketInstanceId].featureSortOrder=e.featureSortOrder),e.hasTextData()&&e.text.opacityVertexBuffer&&e.text.opacityVertexBuffer.updateData(e.text.opacityVertexArray),e.hasIconData()&&e.icon.opacityVertexBuffer&&e.icon.opacityVertexBuffer.updateData(e.icon.opacityVertexArray),e.hasIconCollisionBoxData()&&e.iconCollisionBox.collisionVertexBuffer&&e.iconCollisionBox.collisionVertexBuffer.updateData(e.iconCollisionBox.collisionVertexArray),e.hasTextCollisionBoxData()&&e.textCollisionBox.collisionVertexBuffer&&e.textCollisionBox.collisionVertexBuffer.updateData(e.textCollisionBox.collisionVertexArray),e.bucketInstanceId in this.collisionCircleArrays){var v=this.collisionCircleArrays[e.bucketInstanceId];e.placementInvProjMatrix=v.invProjMatrix,e.placementViewportMatrix=v.viewportMatrix,e.collisionCircleArray=v.circles,delete this.collisionCircleArrays[e.bucketInstanceId]}},_e.prototype.symbolFadeChange=function(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment},_e.prototype.zoomAdjustment=function(t){return Math.max(0,(this.transform.zoom-t)/1.5)},_e.prototype.hasTransitions=function(t){return this.stale||t-this.lastPlacementChangeTime<this.fadeDuration},_e.prototype.stillRecent=function(t,e){var r=this.zoomAtLastRecencyCheck===e?1-this.zoomAdjustment(e):1;return this.zoomAtLastRecencyCheck=e,this.commitTime+this.fadeDuration*r>t},_e.prototype.setStale=function(){this.stale=!0};var Te=Math.pow(2,25),ke=Math.pow(2,24),Ae=Math.pow(2,17),Me=Math.pow(2,16),Se=Math.pow(2,9),Ee=Math.pow(2,8),Ce=Math.pow(2,1);function Le(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Te+e*ke+r*Ae+e*Me+r*Se+e*Ee+r*Ce+e}var Pe=0,Ie=function(t){this._sortAcrossTiles="viewport-y"!==t.layout.get("symbol-z-order")&&void 0!==t.layout.get("symbol-sort-key").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Ie.prototype.continuePlacement=function(t,e,r,n,a){for(var i=this._bucketParts;this._currentTileIndex<t.length;)if(e.getBucketParts(i,n,t[this._currentTileIndex],this._sortAcrossTiles),this._currentTileIndex++,a())return!0;for(this._sortAcrossTiles&&(this._sortAcrossTiles=!1,i.sort((function(t,e){return t.sortKey-e.sortKey})));this._currentPartIndex<i.length;)if(e.placeLayerBucketPart(i[this._currentPartIndex],this._seenCrossTileIDs,r),this._currentPartIndex++,a())return!0;return!1};var ze=function(t,e,r,n,a,i,o){this.placement=new _e(t,a,i,o),this._currentPlacementIndex=e.length-1,this._forceFullPlacement=r,this._showCollisionBoxes=n,this._done=!1};ze.prototype.isDone=function(){return this._done},ze.prototype.continuePlacement=function(e,r,n){for(var a=this,i=t.browser.now(),o=function(){var e=t.browser.now()-i;return!a._forceFullPlacement&&e>2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if("symbol"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new Ie(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},ze.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Oe=512/t.EXTENT/2,De=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;n<e.length;n++){var a=e.get(n),i=a.key;this.indexedSymbolInstances[i]||(this.indexedSymbolInstances[i]=[]),this.indexedSymbolInstances[i].push({crossTileID:a.crossTileID,coord:this.getScaledCoordinates(a,t)})}};De.prototype.getScaledCoordinates=function(e,r){var n=Oe/Math.pow(2,r.canonical.z-this.tileID.canonical.z);return{x:Math.floor((r.canonical.x*t.EXTENT+e.anchorX)*n),y:Math.floor((r.canonical.y*t.EXTENT+e.anchorY)*n)}},De.prototype.findMatches=function(t,e,r){for(var n=this.tileID.canonical.z<e.canonical.z?1:Math.pow(2,this.tileID.canonical.z-e.canonical.z),a=0;a<t.length;a++){var i=t.get(a);if(!i.crossTileID){var o=this.indexedSymbolInstances[i.key];if(o)for(var s=this.getScaledCoordinates(i,e),l=0,c=o;l<c.length;l+=1){var u=c[l];if(Math.abs(u.coord.x-s.x)<=n&&Math.abs(u.coord.y-s.y)<=n&&!r[u.crossTileID]){r[u.crossTileID]=!0,i.crossTileID=u.crossTileID;break}}}}};var Re=function(){this.maxCrossTileID=0};Re.prototype.generate=function(){return++this.maxCrossTileID};var Fe=function(){this.indexes={},this.usedCrossTileIDs={},this.lng=0};Fe.prototype.handleWrapJump=function(t){var e=Math.round((t-this.lng)/360);if(0!==e)for(var r in this.indexes){var n=this.indexes[r],a={};for(var i in n){var o=n[i];o.tileID=o.tileID.unwrapTo(o.tileID.wrap+e),a[o.tileID.key]=o}this.indexes[r]=a}this.lng=t},Fe.prototype.addBucket=function(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(var n=0;n<e.symbolInstances.length;n++)e.symbolInstances.get(n).crossTileID=0;this.usedCrossTileIDs[t.overscaledZ]||(this.usedCrossTileIDs[t.overscaledZ]={});var a=this.usedCrossTileIDs[t.overscaledZ];for(var i in this.indexes){var o=this.indexes[i];if(Number(i)>t.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,a)}else{var c=o[t.scaledTo(Number(i)).key];c&&c.findMatches(e.symbolInstances,t,a)}}for(var u=0;u<e.symbolInstances.length;u++){var h=e.symbolInstances.get(u);h.crossTileID||(h.crossTileID=r.generate(),a[h.crossTileID]=!0)}return void 0===this.indexes[t.overscaledZ]&&(this.indexes[t.overscaledZ]={}),this.indexes[t.overscaledZ][t.key]=new De(t,e.symbolInstances,e.bucketInstanceId),!0},Fe.prototype.removeBucketCrossTileIDs=function(t,e){for(var r in e.indexedSymbolInstances)for(var n=0,a=e.indexedSymbolInstances[r];n<a.length;n+=1)delete this.usedCrossTileIDs[t][a[n].crossTileID]},Fe.prototype.removeStaleBuckets=function(t){var e=!1;for(var r in this.indexes){var n=this.indexes[r];for(var a in n)t[n[a].bucketInstanceId]||(this.removeBucketCrossTileIDs(r,n[a]),delete n[a],e=!0)}return e};var Be=function(){this.layerIndexes={},this.crossTileIDs=new Re,this.maxBucketInstanceId=0,this.bucketsInCurrentPlacement={}};Be.prototype.addLayer=function(t,e,r){var n=this.layerIndexes[t.id];void 0===n&&(n=this.layerIndexes[t.id]=new Fe);var a=!1,i={};n.handleWrapJump(r);for(var o=0,s=e;o<s.length;o+=1){var l=s[o],c=l.getBucket(t);c&&t.id===c.layerIds[0]&&(c.bucketInstanceId||(c.bucketInstanceId=++this.maxBucketInstanceId),n.addBucket(l.tileID,c,this.crossTileIDs)&&(a=!0),i[c.bucketInstanceId]=!0)}return n.removeStaleBuckets(i)&&(a=!0),a},Be.prototype.pruneUnusedLayers=function(t){var e={};for(var r in t.forEach((function(t){e[t]=!0})),this.layerIndexes)e[r]||delete this.layerIndexes[r]};var Ne=function(e,r){return t.emitValidationErrors(e,r&&r.filter((function(t){return"source.canvas"!==t.identifier})))},je=t.pick(Vt,["addLayer","removeLayer","setPaintProperty","setLayoutProperty","setFilter","addSource","removeSource","setLayerZoomRange","setLight","setTransition","setGeoJSONSourceData"]),Ve=t.pick(Vt,["setCenter","setZoom","setBearing","setPitch"]),Ue=function(){var e={},r=t.styleSpec.$version;for(var n in t.styleSpec.$root){var a,i=t.styleSpec.$root[n];i.required&&null!=(a="version"===n?r:"array"===i.type?[]:{})&&(e[n]=a)}return e}(),qe=function(e){function r(n,a){var i=this;void 0===a&&(a={}),e.call(this),this.map=n,this.dispatcher=new k(Bt(),this),this.imageManager=new f,this.imageManager.setEventedParent(this),this.glyphManager=new x(n._requestManager,a.localIdeographFontFamily),this.lineAtlas=new T(256,512),this.crossTileSymbolIndex=new Be,this._layers={},this._serializedLayers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ZoomHistory,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast("setReferrer",t.getReferrer());var o=this;this._rtlTextPluginCallback=r.registerForPluginStateChange((function(e){o.dispatcher.broadcast("syncRTLPluginState",{pluginStatus:e.pluginStatus,pluginURL:e.pluginURL},(function(e,r){if(t.triggerPluginCompletionEvent(e),r&&r.every((function(t){return t})))for(var n in o.sourceCaches)o.sourceCaches[n].reload()}))})),this.on("data",(function(t){if("source"===t.dataType&&"metadata"===t.sourceDataType){var e=i.sourceCaches[t.sourceId];if(e){var r=e.getSource();if(r&&r.vectorLayerIds)for(var n in i._layers){var a=i._layers[n];a.source===r.id&&i._validateLayer(a)}}}}))}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.loadURL=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event("dataloading",{dataType:"style"}));var a="boolean"==typeof r.validate?r.validate:!t.isMapboxURL(e);e=this.map._requestManager.normalizeStyleURL(e,r.accessToken);var i=this.map._requestManager.transformRequest(e,t.ResourceType.Style);this._request=t.getJSON(i,(function(e,r){n._request=null,e?n.fire(new t.ErrorEvent(e)):r&&n._load(r,a)}))},r.prototype.loadJSON=function(e,r){var n=this;void 0===r&&(r={}),this.fire(new t.Event("dataloading",{dataType:"style"})),this._request=t.browser.frame((function(){n._request=null,n._load(e,!1!==r.validate)}))},r.prototype.loadEmpty=function(){this.fire(new t.Event("dataloading",{dataType:"style"})),this._load(Ue,!1)},r.prototype._load=function(e,r){if(!r||!Ne(this,t.validateStyle(e))){for(var n in this._loaded=!0,this.stylesheet=e,e.sources)this.addSource(n,e.sources[n],{validate:!1});e.sprite?this._loadSprite(e.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(e.glyphs);var a=jt(this.stylesheet.layers);this._order=a.map((function(t){return t.id})),this._layers={},this._serializedLayers={};for(var i=0,o=a;i<o.length;i+=1){var s=o[i];(s=t.createStyleLayer(s)).setEventedParent(this,{layer:{id:s.id}}),this._layers[s.id]=s,this._serializedLayers[s.id]=s.serialize()}this.dispatcher.broadcast("setLayers",this._serializeLayers(this._order)),this.light=new w(this.stylesheet.light),this.fire(new t.Event("data",{dataType:"style"})),this.fire(new t.Event("style.load"))}},r.prototype._loadSprite=function(e){var r=this;this._spriteRequest=function(e,r,n){var a,i,o,s=t.browser.devicePixelRatio>1?"@2x":"",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,".json"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,a=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,".png"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,i=e,u())}));function u(){if(o)n(o);else if(a&&i){var e=t.browser.getImageData(i),r={};for(var s in a){var l=a[s],c=l.width,u=l.height,h=l.x,f=l.y,p=l.sdf,d=l.pixelRatio,g=l.stretchX,m=l.stretchY,v=l.content,y=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,y,{x:h,y:f},{x:0,y:0},{width:c,height:u}),r[s]={data:y,pixelRatio:d,sdf:p,stretchX:g,stretchY:m,content:v}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var a in n)r.imageManager.addImage(a,n[a]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast("setImages",r._availableImages),r.fire(new t.Event("data",{dataType:"style"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var a=r.getSource();("geojson"===a.type||a.vectorLayerIds&&-1===a.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer "'+n+'" does not exist on source "'+a.id+'" as specified by style layer "'+e.id+'"')))}}},r.prototype.loaded=function(){if(!this._loaded)return!1;if(Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var a=this._layers[n[r]];"custom"!==a.type&&e.push(a.serialize())}return e},r.prototype.hasTransitions=function(){if(this.light&&this.light.hasTransition())return!0;for(var t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(var e in this._layers)if(this._layers[e].hasTransition())return!0;return!1},r.prototype._checkLoaded=function(){if(!this._loaded)throw new Error("Style is not done loading")},r.prototype.update=function(e){if(this._loaded){var r=this._changed;if(this._changed){var n=Object.keys(this._updatedLayers),a=Object.keys(this._removedLayers);for(var i in(n.length||a.length)&&this._updateWorkerLayers(n,a),this._updatedSources){var o=this._updatedSources[i];"reload"===o?this._reloadSource(i):"clear"===o&&this._clearSource(i)}for(var s in this._updateTilesForChangedImages(),this._updatedPaintProps)this._layers[s].updateTransitions(e);this.light.updateTransitions(e),this._resetUpdates()}for(var l in this.sourceCaches)this.sourceCaches[l].used=!1;for(var c=0,u=this._order;c<u.length;c+=1){var h=this._layers[u[c]];h.recalculate(e,this._availableImages),!h.isHidden(e.zoom)&&h.source&&(this.sourceCaches[h.source].used=!0)}this.light.recalculate(e),this.z=e.zoom,r&&this.fire(new t.Event("data",{dataType:"style"}))}},r.prototype._updateTilesForChangedImages=function(){var t=Object.keys(this._changedImages);if(t.length){for(var e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies(["icons","patterns"],t);this._changedImages={}}},r.prototype._updateWorkerLayers=function(t,e){this.dispatcher.broadcast("updateLayers",{layers:this._serializeLayers(t),removedIds:e})},r.prototype._resetUpdates=function(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={}},r.prototype.setState=function(e){var r=this;if(this._checkLoaded(),Ne(this,t.validateStyle(e)))return!1;(e=t.clone$1(e)).layers=jt(e.layers);var n=function(e,r){if(!e)return[{command:Vt.setStyle,args:[r]}];var n=[];try{if(!t.deepEqual(e.version,r.version))return[{command:Vt.setStyle,args:[r]}];t.deepEqual(e.center,r.center)||n.push({command:Vt.setCenter,args:[r.center]}),t.deepEqual(e.zoom,r.zoom)||n.push({command:Vt.setZoom,args:[r.zoom]}),t.deepEqual(e.bearing,r.bearing)||n.push({command:Vt.setBearing,args:[r.bearing]}),t.deepEqual(e.pitch,r.pitch)||n.push({command:Vt.setPitch,args:[r.pitch]}),t.deepEqual(e.sprite,r.sprite)||n.push({command:Vt.setSprite,args:[r.sprite]}),t.deepEqual(e.glyphs,r.glyphs)||n.push({command:Vt.setGlyphs,args:[r.glyphs]}),t.deepEqual(e.transition,r.transition)||n.push({command:Vt.setTransition,args:[r.transition]}),t.deepEqual(e.light,r.light)||n.push({command:Vt.setLight,args:[r.light]});var a={},i=[];!function(e,r,n,a){var i;for(i in r=r||{},e=e||{})e.hasOwnProperty(i)&&(r.hasOwnProperty(i)||qt(i,n,a));for(i in r)r.hasOwnProperty(i)&&(e.hasOwnProperty(i)?t.deepEqual(e[i],r[i])||("geojson"===e[i].type&&"geojson"===r[i].type&&Gt(e,r,i)?n.push({command:Vt.setGeoJSONSourceData,args:[i,r[i].data]}):Ht(i,r,n,a)):Ut(i,r,n))}(e.sources,r.sources,i,a);var o=[];e.layers&&e.layers.forEach((function(t){a[t.source]?n.push({command:Vt.removeLayer,args:[t.id]}):o.push(t)})),n=n.concat(i),function(e,r,n){r=r||[];var a,i,o,s,l,c,u,h=(e=e||[]).map(Wt),f=r.map(Wt),p=e.reduce(Zt,{}),d=r.reduce(Zt,{}),g=h.slice(),m=Object.create(null);for(a=0,i=0;a<h.length;a++)d.hasOwnProperty(o=h[a])?i++:(n.push({command:Vt.removeLayer,args:[o]}),g.splice(g.indexOf(o,i),1));for(a=0,i=0;a<f.length;a++)g[g.length-1-a]!==(o=f[f.length-1-a])&&(p.hasOwnProperty(o)?(n.push({command:Vt.removeLayer,args:[o]}),g.splice(g.lastIndexOf(o,g.length-i),1)):i++,n.push({command:Vt.addLayer,args:[d[o],c=g[g.length-a]]}),g.splice(g.length-a,0,o),m[o]=!0);for(a=0;a<f.length;a++)if(s=p[o=f[a]],l=d[o],!m[o]&&!t.deepEqual(s,l))if(t.deepEqual(s.source,l.source)&&t.deepEqual(s["source-layer"],l["source-layer"])&&t.deepEqual(s.type,l.type)){for(u in Yt(s.layout,l.layout,n,o,null,Vt.setLayoutProperty),Yt(s.paint,l.paint,n,o,null,Vt.setPaintProperty),t.deepEqual(s.filter,l.filter)||n.push({command:Vt.setFilter,args:[o,l.filter]}),t.deepEqual(s.minzoom,l.minzoom)&&t.deepEqual(s.maxzoom,l.maxzoom)||n.push({command:Vt.setLayerZoomRange,args:[o,l.minzoom,l.maxzoom]}),s)s.hasOwnProperty(u)&&"layout"!==u&&"paint"!==u&&"filter"!==u&&"metadata"!==u&&"minzoom"!==u&&"maxzoom"!==u&&(0===u.indexOf("paint.")?Yt(s[u],l[u],n,o,u.slice(6),Vt.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Vt.setLayerProperty,args:[o,u,l[u]]}));for(u in l)l.hasOwnProperty(u)&&!s.hasOwnProperty(u)&&"layout"!==u&&"paint"!==u&&"filter"!==u&&"metadata"!==u&&"minzoom"!==u&&"maxzoom"!==u&&(0===u.indexOf("paint.")?Yt(s[u],l[u],n,o,u.slice(6),Vt.setPaintProperty):t.deepEqual(s[u],l[u])||n.push({command:Vt.setLayerProperty,args:[o,u,l[u]]}))}else n.push({command:Vt.removeLayer,args:[o]}),c=g[g.lastIndexOf(o)+1],n.push({command:Vt.addLayer,args:[l,c]})}(o,r.layers,n)}catch(t){console.warn("Unable to compute style diff:",t),n=[{command:Vt.setStyle,args:[r]}]}return n}(this.serialize(),e).filter((function(t){return!(t.command in Ve)}));if(0===n.length)return!1;var a=n.filter((function(t){return!(t.command in je)}));if(a.length>0)throw new Error("Unimplemented: "+a.map((function(t){return t.command})).join(", ")+".");return n.forEach((function(t){"setTransition"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error("An image with this name already exists.")));this.imageManager.addImage(e,r),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event("data",{dataType:"style"}))},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error("No image with this name exists.")));this.imageManager.removeImage(e),this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.fire(new t.Event("data",{dataType:"style"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var a=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error("There is already a source with this ID");if(!r.type)throw new Error("The type property must be defined, but the only the following properties were given: "+Object.keys(r).join(", ")+".");if(!(["vector","raster","geojson","video","image"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,"sources."+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var i=this.sourceCaches[e]=new Lt(e,r,this.dispatcher);i.style=this,i.setEventedParent(this,(function(){return{isSourceLoaded:a.loaded(),source:i.serialize(),sourceId:e}})),i.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error("There is no source with this ID");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source "'+e+'" cannot be removed while layer "'+r+'" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event("data",{sourceDataType:"metadata",dataType:"source",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var a=e.id;if(this.getLayer(a))this.fire(new t.ErrorEvent(new Error('Layer with id "'+a+'" already exists on this map')));else{var i;if("custom"===e.type){if(Ne(this,t.validateCustomStyleLayer(e)))return;i=t.createStyleLayer(e)}else{if("object"==typeof e.source&&(this.addSource(a,e.source),e=t.clone$1(e),e=t.extend(e,{source:a})),this._validate(t.validateStyle.layer,"layers."+a,e,{arrayIndex:-1},n))return;i=t.createStyleLayer(e),this._validateLayer(i),i.setEventedParent(this,{layer:{id:a}}),this._serializedLayers[i.id]=i.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.')));else{if(this._order.splice(o,0,a),this._layerOrderChanged=!0,this._layers[a]=i,this._removedLayers[a]&&i.source&&"custom"!==i.type){var s=this._removedLayers[a];delete this._removedLayers[a],s.type!==i.type?this._updatedSources[i.source]="clear":(this._updatedSources[i.source]="reload",this.sourceCaches[i.source].pause())}this._updateLayer(i),i.onAdd&&i.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var a=r?this._order.indexOf(r):this._order.length;r&&-1===a?this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.'))):(this._order.splice(a,0,e),this._layerOrderChanged=!0)}}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be moved.")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be removed.")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var a=this.getLayer(e);a?a.minzoom===r&&a.maxzoom===n||(null!=r&&(a.minzoom=r),null!=n&&(a.maxzoom=n),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot have zoom extent.")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var a=this.getLayer(e);if(a){if(!t.deepEqual(a.filter,r))return null==r?(a.filter=void 0,void this._updateLayer(a)):void(this._validate(t.validateStyle.filter,"layers."+a.id+".filter",r,null,n)||(a.filter=t.clone$1(r),this._updateLayer(a)))}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be filtered.")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,a){void 0===a&&(a={}),this._checkLoaded();var i=this.getLayer(e);i?t.deepEqual(i.getLayoutProperty(r),n)||(i.setLayoutProperty(r,n,a),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style.")))},r.prototype.setPaintProperty=function(e,r,n,a){void 0===a&&(a={}),this._checkLoaded();var i=this.getLayer(e);i?t.deepEqual(i.getPaintProperty(r),n)||(i.setPaintProperty(r,n,a)&&this._updateLayer(i),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,a=e.sourceLayer,i=this.sourceCaches[n];if(void 0!==i){var o=i.getSource().type;"geojson"===o&&a?this.fire(new t.ErrorEvent(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):"vector"!==o||a?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),i.setFeatureState(a,e.id,r)):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,a=this.sourceCaches[n];if(void 0!==a){var i=a.getSource().type,o="vector"===i?e.sourceLayer:void 0;"vector"!==i||o?r&&"string"!=typeof e.id&&"number"!=typeof e.id?this.fire(new t.ErrorEvent(new Error("A feature id is requred to remove its specific state property."))):a.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,a=this.sourceCaches[r];if(void 0!==a){if("vector"!==a.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),a.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+r+"' does not exist in the map's style.")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&"raster"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]="reload",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return"fill-extrusion"===e._layers[t].type},n={},a=[],i=this._order.length-1;i>=0;i--){var o=this._order[i];if(r(o)){n[o]=i;for(var s=0,l=t;s<l.length;s+=1){var c=l[s][o];if(c)for(var u=0,h=c;u<h.length;u+=1)a.push(h[u])}}}a.sort((function(t,e){return e.intersectionZ-t.intersectionZ}));for(var f=[],p=this._order.length-1;p>=0;p--){var d=this._order[p];if(r(d))for(var g=a.length-1;g>=0;g--){var m=a[g].feature;if(n[m.layer.id]<p)break;f.push(m),a.pop()}else for(var v=0,y=t;v<y.length;v+=1){var x=y[v][d];if(x)for(var b=0,_=x;b<_.length;b+=1)f.push(_[b].feature)}}return f},r.prototype.queryRenderedFeatures=function(e,r,n){r&&r.filter&&this._validate(t.validateStyle.filter,"queryRenderedFeatures.filter",r.filter,null,r);var a={};if(r&&r.layers){if(!Array.isArray(r.layers))return this.fire(new t.ErrorEvent(new Error("parameters.layers must be an Array."))),[];for(var i=0,o=r.layers;i<o.length;i+=1){var s=o[i],l=this._layers[s];if(!l)return this.fire(new t.ErrorEvent(new Error("The layer '"+s+"' does not exist in the map's style and cannot be queried for features."))),[];a[l.source]=!0}}var c=[];for(var u in r.availableImages=this._availableImages,this.sourceCaches)r.layers&&!a[u]||c.push(F(this.sourceCaches[u],this._layers,this._serializedLayers,e,r,n));return this.placement&&c.push(function(t,e,r,n,a,i,o){for(var s={},l=i.queryRenderedSymbols(n),c=[],u=0,h=Object.keys(l).map(Number);u<h.length;u+=1)c.push(o[h[u]]);c.sort(B);for(var f=function(){var r=d[p],n=r.featureIndex.lookupSymbolFeatures(l[r.bucketInstanceId],e,r.bucketIndex,r.sourceLayerIndex,a.filter,a.layers,a.availableImages,t);for(var i in n){var o=s[i]=s[i]||[],c=n[i];c.sort((function(t,e){var n=r.featureSortOrder;if(n){var a=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-a}return e.featureIndex-t.featureIndex}));for(var u=0,h=c;u<h.length;u+=1)o.push(h[u])}},p=0,d=c;p<d.length;p+=1)f();var g=function(e){s[e].forEach((function(n){var a=n.feature,i=r[t[e].source].getFeatureState(a.layer["source-layer"],a.id);a.source=a.layer.source,a.layer["source-layer"]&&(a.sourceLayer=a.layer["source-layer"]),a.state=i}))};for(var m in s)g(m);return s}(this._layers,this._serializedLayers,this.sourceCaches,e,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(c)},r.prototype.querySourceFeatures=function(e,r){r&&r.filter&&this._validate(t.validateStyle.filter,"querySourceFeatures.filter",r.filter,null,r);var n=this.sourceCaches[e];return n?function(t,e){for(var r=t.getRenderableIds().map((function(e){return t.getTileByID(e)})),n=[],a={},i=0;i<r.length;i++){var o=r[i],s=o.tileID.canonical.key;a[s]||(a[s]=!0,o.querySourceFeatures(n,e))}return n}(n,r):[]},r.prototype.addSourceType=function(t,e,n){return r.getSourceType(t)?n(new Error('A source type called "'+t+'" already exists.')):(r.setSourceType(t,e),e.workerSourceURL?void this.dispatcher.broadcast("loadWorkerSource",{name:t,url:e.workerSourceURL},n):n(null,null))},r.prototype.getLight=function(){return this.light.getLight()},r.prototype.setLight=function(e,r){void 0===r&&(r={}),this._checkLoaded();var n=this.light.getLight(),a=!1;for(var i in e)if(!t.deepEqual(e[i],n[i])){a=!0;break}if(a){var o={now:t.browser.now(),transition:t.extend({duration:300,delay:0},this.stylesheet.transition)};this.light.setLight(e,r),this.light.updateTransitions(o)}},r.prototype._validate=function(e,r,n,a,i){return void 0===i&&(i={}),(!i||!1!==i.validate)&&Ne(this,e.call(t.validateStyle,t.extend({key:r,style:this.serialize(),value:n,styleSpec:t.styleSpec},a)))},r.prototype._remove=function(){for(var e in this._request&&(this._request.cancel(),this._request=null),this._spriteRequest&&(this._spriteRequest.cancel(),this._spriteRequest=null),t.evented.off("pluginStateChange",this._rtlTextPluginCallback),this._layers)this._layers[e].setEventedParent(null);for(var r in this.sourceCaches)this.sourceCaches[r].clearTiles(),this.sourceCaches[r].setEventedParent(null);this.imageManager.setEventedParent(null),this.setEventedParent(null),this.dispatcher.remove()},r.prototype._clearSource=function(t){this.sourceCaches[t].clearTiles()},r.prototype._reloadSource=function(t){this.sourceCaches[t].resume(),this.sourceCaches[t].reload()},r.prototype._updateSources=function(t){for(var e in this.sourceCaches)this.sourceCaches[e].update(t)},r.prototype._generateCollisionBoxes=function(){for(var t in this.sourceCaches)this._reloadSource(t)},r.prototype._updatePlacement=function(e,r,n,a,i){void 0===i&&(i=!1);for(var o=!1,s=!1,l={},c=0,u=this._order;c<u.length;c+=1){var h=this._layers[u[c]];if("symbol"===h.type){if(!l[h.source]){var f=this.sourceCaches[h.source];l[h.source]=f.getRenderableIds(!0).map((function(t){return f.getTileByID(t)})).sort((function(t,e){return e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)}))}var p=this.crossTileSymbolIndex.addLayer(h,l[h.source],e.center.lng);o=o||p}}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((i=i||this._layerOrderChanged||0===n)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(t.browser.now(),e.zoom))&&(this.pauseablePlacement=new ze(e,this._order,i,r,n,a,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(t.browser.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(var d=0,g=this._order;d<g.length;d+=1){var m=this._layers[g[d]];"symbol"===m.type&&this.placement.updateLayerOpacities(m,l[m.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(t.browser.now())},r.prototype._releaseSymbolFadeTiles=function(){for(var t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()},r.prototype.getImages=function(t,e,r){this.imageManager.getImages(e.icons,r),this._updateTilesForChangedImages();var n=this.sourceCaches[e.source];n&&n.setDependencies(e.tileID.key,e.type,e.icons)},r.prototype.getGlyphs=function(t,e,r){this.glyphManager.getGlyphs(e.stacks,r)},r.prototype.getResource=function(e,r,n){return t.makeRequest(r,n)},r}(t.Evented);qe.getSourceType=function(t){return D[t]},qe.setSourceType=function(t,e){D[t]=e},qe.registerForPluginStateChange=t.registerForPluginStateChange;var He=t.createLayout([{name:"a_pos",type:"Int16",components:2}]),Ge=vr("#ifdef GL_ES\nprecision mediump float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif","#ifdef GL_ES\nprecision highp float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}"),Ye=vr("uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),We=vr("uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}"),Ze=vr("varying vec3 v_data;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);lowp float antialiasblur=v_data.z;float antialiased_blur=-max(blur,antialiasblur);float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main(void) {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,0,1);} else {gl_Position=u_matrix*vec4(circle_center,0,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}lowp float antialiasblur=1.0/u_device_pixel_ratio/(radius+stroke_width);v_data=vec3(extrude.x,extrude.y,antialiasblur);}"),Xe=vr("void main() {gl_FragColor=vec4(1.0);}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),Je=vr("uniform highp float u_intensity;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#define GAUSS_COEF 0.3989422804014327\nvoid main() {\n#pragma mapbox: initialize highp float weight\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#pragma mapbox: define mediump float radius\nconst highp float ZERO=1.0/255.0/16.0;\n#define GAUSS_COEF 0.3989422804014327\nvoid main(void) {\n#pragma mapbox: initialize highp float weight\n#pragma mapbox: initialize mediump float radius\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,0,1);gl_Position=u_matrix*pos;}"),Ke=vr("uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(0.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}"),Qe=vr("varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}"),$e=vr("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),tr=vr("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}"),er=vr("#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_FragColor=color*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);}"),rr=vr("varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),nr=vr("uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),ar=vr("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}"),ir=vr("varying vec4 v_color;void main() {gl_FragColor=v_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\n#pragma mapbox: define highp float base\n#pragma mapbox: define highp float height\n#pragma mapbox: define highp vec4 color\nvoid main() {\n#pragma mapbox: initialize highp float base\n#pragma mapbox: initialize highp float height\n#pragma mapbox: initialize highp vec4 color\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}"),or=vr("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n? a_pos\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}"),sr=vr("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform float u_maxzoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggeration=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/ pow(2.0,(u_zoom-u_maxzoom)*exaggeration+19.2562-u_zoom);gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),lr=vr("uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n#define PI 3.141592653589793\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),cr=vr("uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),ur=vr("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp float v_lineprogress;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,vec2(v_lineprogress,0.5));gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define MAX_LINE_DISTANCE 32767.0\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_lineprogress;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_lineprogress=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0/MAX_LINE_DISTANCE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),hr=vr("uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}"),fr=vr("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}"),pr=vr("uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),dr=vr("uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}"),gr=vr("#define SDF_PX 8.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}"),mr=vr("#define SDF_PX 8.0\n#define SDF 1.0\n#define ICON 0.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}");function vr(t,e){var r=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,n={};return{fragmentSource:t=t.replace(r,(function(t,e,r,a,i){return n[i]=!0,"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nvarying "+r+" "+a+" "+i+";\n#else\nuniform "+r+" "+a+" u_"+i+";\n#endif\n":"\n#ifdef HAS_UNIFORM_u_"+i+"\n "+r+" "+a+" "+i+" = u_"+i+";\n#endif\n"})),vertexSource:e=e.replace(r,(function(t,e,r,a,i){var o="float"===a?"vec2":"vec4",s=i.match(/color/)?"color":o;return n[i]?"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nuniform lowp float u_"+i+"_t;\nattribute "+r+" "+o+" a_"+i+";\nvarying "+r+" "+a+" "+i+";\n#else\nuniform "+r+" "+a+" u_"+i+";\n#endif\n":"vec4"===s?"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+i+" = a_"+i+";\n#else\n "+r+" "+a+" "+i+" = u_"+i+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+i+" = unpack_mix_"+s+"(a_"+i+", u_"+i+"_t);\n#else\n "+r+" "+a+" "+i+" = u_"+i+";\n#endif\n":"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nuniform lowp float u_"+i+"_t;\nattribute "+r+" "+o+" a_"+i+";\n#else\nuniform "+r+" "+a+" u_"+i+";\n#endif\n":"vec4"===s?"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+r+" "+a+" "+i+" = a_"+i+";\n#else\n "+r+" "+a+" "+i+" = u_"+i+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+r+" "+a+" "+i+" = unpack_mix_"+s+"(a_"+i+", u_"+i+"_t);\n#else\n "+r+" "+a+" "+i+" = u_"+i+";\n#endif\n"}))}}var yr=Object.freeze({__proto__:null,prelude:Ge,background:Ye,backgroundPattern:We,circle:Ze,clippingMask:Xe,heatmap:Je,heatmapTexture:Ke,collisionBox:Qe,collisionCircle:$e,debug:tr,fill:er,fillOutline:rr,fillOutlinePattern:nr,fillPattern:ar,fillExtrusion:ir,fillExtrusionPattern:or,hillshadePrepare:sr,hillshade:lr,line:cr,lineGradient:ur,linePattern:hr,lineSDF:fr,raster:pr,symbolIcon:dr,symbolSDF:gr,symbolTextAndIcon:mr}),xr=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};xr.prototype.bind=function(t,e,r,n,a,i,o,s){this.context=t;for(var l=this.boundPaintVertexBuffers.length!==n.length,c=0;!l&&c<n.length;c++)this.boundPaintVertexBuffers[c]!==n[c]&&(l=!0);t.extVertexArrayObject&&this.vao&&this.boundProgram===e&&this.boundLayoutVertexBuffer===r&&!l&&this.boundIndexBuffer===a&&this.boundVertexOffset===i&&this.boundDynamicVertexBuffer===o&&this.boundDynamicVertexBuffer2===s?(t.bindVertexArrayOES.set(this.vao),o&&o.bind(),a&&a.dynamicDraw&&a.bind(),s&&s.bind()):this.freshBind(e,r,n,a,i,o,s)},xr.prototype.freshBind=function(t,e,r,n,a,i,o){var s,l=t.numAttributes,c=this.context,u=c.gl;if(c.extVertexArrayObject)this.vao&&this.destroy(),this.vao=c.extVertexArrayObject.createVertexArrayOES(),c.bindVertexArrayOES.set(this.vao),s=0,this.boundProgram=t,this.boundLayoutVertexBuffer=e,this.boundPaintVertexBuffers=r,this.boundIndexBuffer=n,this.boundVertexOffset=a,this.boundDynamicVertexBuffer=i,this.boundDynamicVertexBuffer2=o;else{s=c.currentNumAttributes||0;for(var h=l;h<s;h++)u.disableVertexAttribArray(h)}e.enableAttributes(u,t);for(var f=0,p=r;f<p.length;f+=1)p[f].enableAttributes(u,t);i&&i.enableAttributes(u,t),o&&o.enableAttributes(u,t),e.bind(),e.setVertexAttribPointers(u,t,a);for(var d=0,g=r;d<g.length;d+=1){var m=g[d];m.bind(),m.setVertexAttribPointers(u,t,a)}i&&(i.bind(),i.setVertexAttribPointers(u,t,a)),n&&n.bind(),o&&(o.bind(),o.setVertexAttribPointers(u,t,a)),c.currentNumAttributes=l},xr.prototype.destroy=function(){this.vao&&(this.context.extVertexArrayObject.deleteVertexArrayOES(this.vao),this.vao=null)};var br=function(t,e,r,n,a){var i=t.gl;this.program=i.createProgram();var o=r?r.defines():[];a&&o.push("#define OVERDRAW_INSPECTOR;");var s=o.concat(Ge.fragmentSource,e.fragmentSource).join("\n"),l=o.concat(Ge.vertexSource,e.vertexSource).join("\n"),c=i.createShader(i.FRAGMENT_SHADER);if(i.isContextLost())this.failedToCreate=!0;else{i.shaderSource(c,s),i.compileShader(c),i.attachShader(this.program,c);var u=i.createShader(i.VERTEX_SHADER);if(i.isContextLost())this.failedToCreate=!0;else{i.shaderSource(u,l),i.compileShader(u),i.attachShader(this.program,u);for(var h=r?r.layoutAttributes:[],f=0;f<h.length;f++)i.bindAttribLocation(this.program,f,h[f].name);i.linkProgram(this.program),i.deleteShader(u),i.deleteShader(c),this.numAttributes=i.getProgramParameter(this.program,i.ACTIVE_ATTRIBUTES),this.attributes={};for(var p={},d=0;d<this.numAttributes;d++){var g=i.getActiveAttrib(this.program,d);g&&(this.attributes[g.name]=i.getAttribLocation(this.program,g.name))}for(var m=i.getProgramParameter(this.program,i.ACTIVE_UNIFORMS),v=0;v<m;v++){var y=i.getActiveUniform(this.program,v);y&&(p[y.name]=i.getUniformLocation(this.program,y.name))}this.fixedUniforms=n(t,p),this.binderUniforms=r?r.getUniforms(t,p):[]}}};function _r(t,e,r){var n=1/fe(r,1,e.transform.tileZoom),a=Math.pow(2,r.tileID.overscaledZ),i=r.tileSize*Math.pow(2,e.transform.tileZoom)/a,o=i*(r.tileID.canonical.x+r.tileID.wrap*a),s=i*r.tileID.canonical.y;return{u_image:0,u_texsize:r.imageAtlasTexture.size,u_scale:[n,t.fromScale,t.toScale],u_fade:t.t,u_pixel_coord_upper:[o>>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}br.prototype.draw=function(t,e,r,n,a,i,o,s,l,c,u,h,f,p,d,g){var m,v=t.gl;if(!this.failedToCreate){for(var y in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(a),t.setCullFace(i),this.fixedUniforms)this.fixedUniforms[y].set(o[y]);p&&p.setUniforms(t,this.binderUniforms,h,{zoom:f});for(var x=(m={},m[v.LINES]=2,m[v.TRIANGLES]=3,m[v.LINE_STRIP]=1,m)[e],b=0,_=u.get();b<_.length;b+=1){var w=_[b],T=w.vaos||(w.vaos={});(T[s]||(T[s]=new xr)).bind(t,this,l,p?p.getPaintVertexBuffers():[],c,w.vertexOffset,d,g),v.drawElements(e,w.primitiveLength*x,v.UNSIGNED_SHORT,w.primitiveOffset*x*2)}}};var wr=function(e,r,n,a){var i=r.style.light,o=i.properties.get("position"),s=[o.x,o.y,o.z],l=t.create$1();"viewport"===i.properties.get("anchor")&&t.fromRotation(l,-r.transform.angle),t.transformMat3(s,s,l);var c=i.properties.get("color");return{u_matrix:e,u_lightpos:s,u_lightintensity:i.properties.get("intensity"),u_lightcolor:[c.r,c.g,c.b],u_vertical_gradient:+n,u_opacity:a}},Tr=function(e,r,n,a,i,o,s){return t.extend(wr(e,r,n,a),_r(o,r,s),{u_height_factor:-Math.pow(2,i.overscaledZ)/s.tileSize/8})},kr=function(t){return{u_matrix:t}},Ar=function(e,r,n,a){return t.extend(kr(e),_r(n,r,a))},Mr=function(t,e){return{u_matrix:t,u_world:e}},Sr=function(e,r,n,a,i){return t.extend(Ar(e,r,n,a),{u_world:i})},Er=function(e,r,n,a){var i,o,s=e.transform;if("map"===a.paint.get("circle-pitch-alignment")){var l=fe(n,1,s.zoom);i=!0,o=[l,l]}else i=!1,o=s.pixelsToGLUnits;return{u_camera_to_center_distance:s.cameraToCenterDistance,u_scale_with_map:+("map"===a.paint.get("circle-pitch-scale")),u_matrix:e.translatePosMatrix(r.posMatrix,n,a.paint.get("circle-translate"),a.paint.get("circle-translate-anchor")),u_pitch_with_map:+i,u_device_pixel_ratio:t.browser.devicePixelRatio,u_extrude_scale:o}},Cr=function(t,e,r){var n=fe(r,1,e.zoom),a=Math.pow(2,e.zoom-r.tileID.overscaledZ),i=r.tileID.overscaleFactor();return{u_matrix:t,u_camera_to_center_distance:e.cameraToCenterDistance,u_pixels_to_tile_units:n,u_extrude_scale:[e.pixelsToGLUnits[0]/(n*a),e.pixelsToGLUnits[1]/(n*a)],u_overscale_factor:i}},Lr=function(t,e,r){return{u_matrix:t,u_inv_matrix:e,u_camera_to_center_distance:r.cameraToCenterDistance,u_viewport_size:[r.width,r.height]}},Pr=function(t,e,r){return void 0===r&&(r=1),{u_matrix:t,u_color:e,u_overlay:0,u_overlay_scale:r}},Ir=function(t){return{u_matrix:t}},zr=function(t,e,r,n){return{u_matrix:t,u_extrude_scale:fe(e,1,r),u_intensity:n}},Or=function(e,r,n){var a=e.transform;return{u_matrix:Nr(e,r,n),u_ratio:1/fe(r,1,a.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_units_to_pixels:[1/a.pixelsToGLUnits[0],1/a.pixelsToGLUnits[1]]}},Dr=function(e,r,n){return t.extend(Or(e,r,n),{u_image:0})},Rr=function(e,r,n,a){var i=e.transform,o=Br(r,i);return{u_matrix:Nr(e,r,n),u_texsize:r.imageAtlasTexture.size,u_ratio:1/fe(r,1,i.zoom),u_device_pixel_ratio:t.browser.devicePixelRatio,u_image:0,u_scale:[o,a.fromScale,a.toScale],u_fade:a.t,u_units_to_pixels:[1/i.pixelsToGLUnits[0],1/i.pixelsToGLUnits[1]]}},Fr=function(e,r,n,a,i){var o=e.lineAtlas,s=Br(r,e.transform),l="round"===n.layout.get("line-cap"),c=o.getDash(a.from,l),u=o.getDash(a.to,l),h=c.width*i.fromScale,f=u.width*i.toScale;return t.extend(Or(e,r,n),{u_patternscale_a:[s/h,-c.height/2],u_patternscale_b:[s/f,-u.height/2],u_sdfgamma:o.width/(256*Math.min(h,f)*t.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:c.y,u_tex_y_b:u.y,u_mix:i.t})};function Br(t,e){return 1/fe(t,1,e.tileZoom)}function Nr(t,e,r){return t.translatePosMatrix(e.tileID.posMatrix,e,r.paint.get("line-translate"),r.paint.get("line-translate-anchor"))}var jr=function(t,e,r,n,a){return{u_matrix:t,u_tl_parent:e,u_scale_parent:r,u_buffer_scale:1,u_fade_t:n.mix,u_opacity:n.opacity*a.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:a.paint.get("raster-brightness-min"),u_brightness_high:a.paint.get("raster-brightness-max"),u_saturation_factor:(o=a.paint.get("raster-saturation"),o>0?1-1/(1.001-o):-o),u_contrast_factor:(i=a.paint.get("raster-contrast"),i>0?1/(1-i):1+i),u_spin_weights:Vr(a.paint.get("raster-hue-rotate"))};var i,o};function Vr(t){t*=Math.PI/180;var e=Math.sin(t),r=Math.cos(t);return[(2*r+1)/3,(-Math.sqrt(3)*e-r+1)/3,(Math.sqrt(3)*e-r+1)/3]}var Ur,qr=function(t,e,r,n,a,i,o,s,l,c){var u=a.transform;return{u_is_size_zoom_constant:+("constant"===t||"source"===t),u_is_size_feature_constant:+("constant"===t||"camera"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:a.options.fadeDuration?a.symbolFadeChange:1,u_matrix:i,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},Hr=function(e,r,n,a,i,o,s,l,c,u,h){var f=i.transform;return t.extend(qr(e,r,n,a,i,o,s,l,c,u),{u_gamma_scale:a?Math.cos(f._pitch)*f.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+h})},Gr=function(e,r,n,a,i,o,s,l,c,u){return t.extend(Hr(e,r,n,a,i,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Yr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Wr=function(e,r,n,a,i,o){return t.extend(function(t,e,r,n){var a=r.imageManager.getPattern(t.from.toString()),i=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,h=u*(n.tileID.canonical.x+n.tileID.wrap*c),f=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:a.tl,u_pattern_br_a:a.br,u_pattern_tl_b:i.tl,u_pattern_br_b:i.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:a.displaySize,u_pattern_size_b:i.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/fe(n,1,r.transform.tileZoom),u_pixel_coord_upper:[h>>16,f>>16],u_pixel_coord_lower:[65535&h,65535&f]}}(a,o,n,i),{u_matrix:e,u_opacity:r})},Zr={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_maxzoom:new t.Uniform1f(e,r.u_maxzoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function Xr(e,r,n,a,i,o,s){for(var l=e.context,c=l.gl,u=e.useProgram("collisionBox"),h=[],f=0,p=0,d=0;d<a.length;d++){var g=a[d],m=r.getTile(g),v=m.getBucket(n);if(v){var y=g.posMatrix;0===i[0]&&0===i[1]||(y=e.translatePosMatrix(g.posMatrix,m,i,o));var x=s?v.textCollisionBox:v.iconCollisionBox,b=v.collisionCircleArray;if(b.length>0){var _=t.create(),w=y;t.mul(_,v.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(_,_,v.placementViewportMatrix),h.push({circleArray:b,circleOffset:p,transform:w,invTransform:_}),p=f+=b.length/4}x&&u.draw(l,c.LINES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,Cr(y,e.transform,m),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&h.length){var T=e.useProgram("collisionCircle"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*f),k._trim();for(var A=0,M=0,S=h;M<S.length;M+=1)for(var E=S[M],C=0;C<E.circleArray.length/4;C++){var L=4*C,P=E.circleArray[L+0],I=E.circleArray[L+1],z=E.circleArray[L+2],O=E.circleArray[L+3];k.emplace(A++,P,I,z,O,0),k.emplace(A++,P,I,z,O,1),k.emplace(A++,P,I,z,O,2),k.emplace(A++,P,I,z,O,3)}(!Ur||Ur.length<2*f)&&(Ur=function(e){var r=2*e,n=new t.StructArrayLayout3ui6;n.resize(r),n._trim();for(var a=0;a<r;a++){var i=6*a;n.uint16[i+0]=4*a+0,n.uint16[i+1]=4*a+1,n.uint16[i+2]=4*a+2,n.uint16[i+3]=4*a+2,n.uint16[i+4]=4*a+3,n.uint16[i+5]=4*a+0}return n}(f));for(var D=l.createIndexBuffer(Ur,!0),R=l.createVertexBuffer(k,t.collisionCircleLayout.members,!0),F=0,B=h;F<B.length;F+=1){var N=B[F],j=Lr(N.transform,N.invTransform,e.transform);T.draw(l,c.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,j,n.id,R,D,t.SegmentVector.simpleSegment(0,2*N.circleOffset,N.circleArray.length,N.circleArray.length/2),null,e.transform.zoom,null,null,null)}R.destroy(),D.destroy()}}var Jr=t.identity(new Float32Array(16));function Kr(e,r,n,a,i,o){var s=t.getAnchorAlignment(e),l=-(s.horizontalAlign-.5)*r,c=-(s.verticalAlign-.5)*n,u=t.evaluateVariableOffset(e,a);return new t.Point((l/i+u[0])*o,(c/i+u[1])*o)}function Qr(e,r,n,a,i,o,s,l,c,u,h){var f=e.text.placedSymbolArray,p=e.text.dynamicLayoutVertexArray,d=e.icon.dynamicLayoutVertexArray,g={};p.clear();for(var m=0;m<f.length;m++){var v=f.get(m),y=v.hidden||!v.crossTileID||e.allowVerticalPlacement&&!v.placedOrientation?null:a[v.crossTileID];if(y){var x=new t.Point(v.anchorX,v.anchorY),b=$t(x,n?l:s),_=te(o.cameraToCenterDistance,b.signedDistanceFromCamera),w=i.evaluateSizeForFeature(e.textSizeData,u,v)*_/t.ONE_EM;n&&(w*=e.tilePixelRatio/c);for(var T=Kr(y.anchor,y.width,y.height,y.textOffset,y.textBoxScale,w),k=n?$t(x.add(T),s).point:b.point.add(r?T.rotate(-o.angle):T),A=e.allowVerticalPlacement&&v.placedOrientation===t.WritingMode.vertical?Math.PI/2:0,M=0;M<v.numGlyphs;M++)t.addDynamicAttributes(p,k,A);h&&v.associatedIconIndex>=0&&(g[v.associatedIconIndex]={shiftedAnchor:k,angle:A})}else ce(v.numGlyphs,p)}if(h){d.clear();for(var S=e.icon.placedSymbolArray,E=0;E<S.length;E++){var C=S.get(E);if(C.hidden)ce(C.numGlyphs,d);else{var L=g[E];if(L)for(var P=0;P<C.numGlyphs;P++)t.addDynamicAttributes(d,L.shiftedAnchor,L.angle);else ce(C.numGlyphs,d)}}e.icon.dynamicLayoutVertexBuffer.updateData(d)}e.text.dynamicLayoutVertexBuffer.updateData(p)}function $r(t,e,r){return r.iconsInText&&e?"symbolTextAndIcon":t?"symbolSDF":"symbolIcon"}function tn(e,r,n,a,i,o,s,l,c,u,h,f){for(var p=e.context,d=p.gl,g=e.transform,m="map"===l,v="map"===c,y=m&&"point"!==n.layout.get("symbol-placement"),x=m&&!v&&!y,b=void 0!==n.layout.get("symbol-sort-key").constantOr(1),_=e.depthModeForSublayer(0,At.ReadOnly),w=n.layout.get("text-variable-anchor"),T=[],k=0,A=a;k<A.length;k+=1){var M=A[k],S=r.getTile(M),E=S.getBucket(n);if(E){var C=i?E.text:E.icon;if(C&&C.segments.get().length){var L=C.programConfigurations.get(n.id),P=i||E.sdfIcons,I=i?E.textSizeData:E.iconSizeData,z=v||0!==g.pitch,O=e.useProgram($r(P,i,E),L),D=t.evaluateSizeForZoom(I,g.zoom),R=void 0,F=[0,0],B=void 0,N=void 0,j=null,V=void 0;if(i)B=S.glyphAtlasTexture,N=d.LINEAR,R=S.glyphAtlasTexture.size,E.iconsInText&&(F=S.imageAtlasTexture.size,j=S.imageAtlasTexture,V=z||e.options.rotating||e.options.zooming||"composite"===I.kind||"camera"===I.kind?d.LINEAR:d.NEAREST);else{var U=1!==n.layout.get("icon-size").constantOr(0)||E.iconsNeedLinear;B=S.imageAtlasTexture,N=P||e.options.rotating||e.options.zooming||U||z?d.LINEAR:d.NEAREST,R=S.imageAtlasTexture.size}var q=fe(S,1,e.transform.zoom),H=Kt(M.posMatrix,v,m,e.transform,q),G=Qt(M.posMatrix,v,m,e.transform,q),Y=w&&E.hasTextData(),W="none"!==n.layout.get("icon-text-fit")&&Y&&E.hasIconData();y&&re(E,M.posMatrix,e,i,H,G,v,u);var Z=e.translatePosMatrix(M.posMatrix,S,o,s),X=y||i&&w||W?Jr:H,J=e.translatePosMatrix(G,S,o,s,!0),K=P&&0!==n.paint.get(i?"text-halo-width":"icon-halo-width").constantOr(1),Q={program:O,buffers:C,uniformValues:P?E.iconsInText?Gr(I.kind,D,x,v,e,Z,X,J,R,F):Hr(I.kind,D,x,v,e,Z,X,J,i,R,!0):qr(I.kind,D,x,v,e,Z,X,J,i,R),atlasTexture:B,atlasTextureIcon:j,atlasInterpolation:N,atlasInterpolationIcon:V,isSDF:P,hasHalo:K};if(b)for(var $=0,tt=C.segments.get();$<tt.length;$+=1){var et=tt[$];T.push({segments:new t.SegmentVector([et]),sortKey:et.sortKey,state:Q})}else T.push({segments:C.segments,sortKey:0,state:Q})}}}b&&T.sort((function(t,e){return t.sortKey-e.sortKey}));for(var rt=0,nt=T;rt<nt.length;rt+=1){var at=nt[rt],it=at.state;if(p.activeTexture.set(d.TEXTURE0),it.atlasTexture.bind(it.atlasInterpolation,d.CLAMP_TO_EDGE),it.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),it.atlasTextureIcon&&it.atlasTextureIcon.bind(it.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),it.isSDF){var ot=it.uniformValues;it.hasHalo&&(ot.u_is_halo=1,en(it.buffers,at.segments,n,e,it.program,_,h,f,ot)),ot.u_is_halo=0}en(it.buffers,at.segments,n,e,it.program,_,h,f,it.uniformValues)}}function en(t,e,r,n,a,i,o,s,l){var c=n.context;a.draw(c,c.gl.TRIANGLES,i,o,s,Et.disabled,l,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function rn(t,e,r,n,a,i,o){var s,l,c,u,h,f=t.context.gl,p=r.paint.get("fill-pattern"),d=p&&p.constantOr(1),g=r.getCrossfadeParameters();o?(l=d&&!r.getPaintProperty("fill-outline-color")?"fillOutlinePattern":"fillOutline",s=f.LINES):(l=d?"fillPattern":"fill",s=f.TRIANGLES);for(var m=0,v=n;m<v.length;m+=1){var y=v[m],x=e.getTile(y);if(!d||x.patternsLoaded()){var b=x.getBucket(r);if(b){var _=b.programConfigurations.get(r.id),w=t.useProgram(l,_);d&&(t.context.activeTexture.set(f.TEXTURE0),x.imageAtlasTexture.bind(f.LINEAR,f.CLAMP_TO_EDGE),_.updatePaintBuffers(g));var T=p.constantOr(null);if(T&&x.imageAtlas){var k=x.imageAtlas,A=k.patternPositions[T.to.toString()],M=k.patternPositions[T.from.toString()];A&&M&&_.setConstantPatternPositions(A,M)}var S=t.translatePosMatrix(y.posMatrix,x,r.paint.get("fill-translate"),r.paint.get("fill-translate-anchor"));if(o){u=b.indexBuffer2,h=b.segments2;var E=[f.drawingBufferWidth,f.drawingBufferHeight];c="fillOutlinePattern"===l&&d?Sr(S,t,g,x,E):Mr(S,E)}else u=b.indexBuffer,h=b.segments,c=d?Ar(S,t,g,x):kr(S);w.draw(t.context,s,a,t.stencilModeForClipping(y),i,Et.disabled,c,r.id,b.layoutVertexBuffer,u,h,r.paint,t.transform.zoom,_)}}}}function nn(t,e,r,n,a,i,o){for(var s=t.context,l=s.gl,c=r.paint.get("fill-extrusion-pattern"),u=c.constantOr(1),h=r.getCrossfadeParameters(),f=r.paint.get("fill-extrusion-opacity"),p=0,d=n;p<d.length;p+=1){var g=d[p],m=e.getTile(g),v=m.getBucket(r);if(v){var y=v.programConfigurations.get(r.id),x=t.useProgram(u?"fillExtrusionPattern":"fillExtrusion",y);u&&(t.context.activeTexture.set(l.TEXTURE0),m.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(h));var b=c.constantOr(null);if(b&&m.imageAtlas){var _=m.imageAtlas,w=_.patternPositions[b.to.toString()],T=_.patternPositions[b.from.toString()];w&&T&&y.setConstantPatternPositions(w,T)}var k=t.translatePosMatrix(g.posMatrix,m,r.paint.get("fill-extrusion-translate"),r.paint.get("fill-extrusion-translate-anchor")),A=r.paint.get("fill-extrusion-vertical-gradient"),M=u?Tr(k,t,A,f,g,h,m):wr(k,t,A,f);x.draw(s,s.gl.TRIANGLES,a,i,o,Et.backCCW,M,r.id,v.layoutVertexBuffer,v.indexBuffer,v.segments,r.paint,t.transform.zoom,y)}}}function an(e,r,n,a,i,o){var s=e.context,l=s.gl,c=r.fbo;if(c){var u=e.useProgram("hillshade");s.activeTexture.set(l.TEXTURE0),l.bindTexture(l.TEXTURE_2D,c.colorAttachment.get());var h=function(e,r,n){var a=n.paint.get("hillshade-shadow-color"),i=n.paint.get("hillshade-highlight-color"),o=n.paint.get("hillshade-accent-color"),s=n.paint.get("hillshade-illumination-direction")*(Math.PI/180);"viewport"===n.paint.get("hillshade-illumination-anchor")&&(s-=e.transform.angle);var l,c,u,h=!e.options.moving;return{u_matrix:e.transform.calculatePosMatrix(r.tileID.toUnwrapped(),h),u_image:0,u_latrange:(l=r.tileID,c=Math.pow(2,l.canonical.z),u=l.canonical.y,[new t.MercatorCoordinate(0,u/c).toLngLat().lat,new t.MercatorCoordinate(0,(u+1)/c).toLngLat().lat]),u_light:[n.paint.get("hillshade-exaggeration"),s],u_shadow:a,u_highlight:i,u_accent:o}}(e,r,n);u.draw(s,l.TRIANGLES,a,i,o,Et.disabled,h,n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments)}}function on(e,r,n,a,i,o,s){var l=e.context,c=l.gl,u=r.dem;if(u&&u.data){var h=u.dim,f=u.stride,p=u.getPixels();if(l.activeTexture.set(c.TEXTURE1),l.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||e.getTileTexture(f),r.demTexture){var d=r.demTexture;d.update(p,{premultiply:!1}),d.bind(c.NEAREST,c.CLAMP_TO_EDGE)}else r.demTexture=new t.Texture(l,p,c.RGBA,{premultiply:!1}),r.demTexture.bind(c.NEAREST,c.CLAMP_TO_EDGE);l.activeTexture.set(c.TEXTURE0);var g=r.fbo;if(!g){var m=new t.Texture(l,{width:h,height:h,data:null},c.RGBA);m.bind(c.LINEAR,c.CLAMP_TO_EDGE),(g=r.fbo=l.createFramebuffer(h,h,!0)).colorAttachment.set(m.texture)}l.bindFramebuffer.set(g.framebuffer),l.viewport.set([0,0,h,h]),e.useProgram("hillshadePrepare").draw(l,c.TRIANGLES,i,o,s,Et.disabled,function(e,r,n){var a=r.stride,i=t.create();return t.ortho(i,0,t.EXTENT,-t.EXTENT,0,0,1),t.translate(i,i,[0,-t.EXTENT,0]),{u_matrix:i,u_image:1,u_dimension:[a,a],u_zoom:e.overscaledZ,u_maxzoom:n,u_unpack:r.getUnpackVector()}}(r.tileID,u,a),n.id,e.rasterBoundsBuffer,e.quadTriangleIndexBuffer,e.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function sn(e,r,n,a,i){var o=a.paint.get("raster-fade-duration");if(o>0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),h=i.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),f=!r||Math.abs(r.tileID.overscaledZ-h)>Math.abs(e.tileID.overscaledZ-h),p=f&&e.refreshedUponExpiration?1:t.clamp(f?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var ln=new t.Color(1,0,0,1),cn=new t.Color(0,1,0,1),un=new t.Color(0,0,1,1),hn=new t.Color(1,0,1,1),fn=new t.Color(0,1,1,1);function pn(t,e,r,n){gn(t,0,e+r/2,t.transform.width,r,n)}function dn(t,e,r,n){gn(t,e-r/2,0,r,t.transform.height,n)}function gn(e,r,n,a,i,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function mn(e,r,n){var a=e.context,i=a.gl,o=n.posMatrix,s=e.useProgram("debug"),l=At.disabled,c=Mt.disabled,u=e.colorModeForRenderPass();a.activeTexture.set(i.TEXTURE0),e.emptyTexture.bind(i.LINEAR,i.CLAMP_TO_EDGE),s.draw(a,i.LINE_STRIP,l,c,u,Et.disabled,Pr(o,t.Color.red),"$debug",e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var h=r.getTileByID(n.key).latestRawTileData,f=Math.floor((h&&h.byteLength||0)/1024),p=r.getTile(n).tileSize,d=512/Math.min(p,512)*(n.overscaledZ/e.transform.zoom)*.5,g=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(g+=" => "+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,a=t.debugOverlayCanvas.getContext("2d");a.clearRect(0,0,r.width,r.height),a.shadowColor="white",a.shadowBlur=2,a.lineWidth=1.5,a.strokeStyle="white",a.textBaseline="top",a.font="bold 36px Open Sans, sans-serif",a.fillText(e,5,5),a.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,g+" "+f+"kb"),s.draw(a,i.TRIANGLES,l,c,St.alphaBlended,Et.disabled,Pr(o,t.Color.transparent,d),"$debug",e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var vn={symbol:function(e,r,n,a,i){if("translucent"===e.renderPass){var o=Mt.disabled,s=e.colorModeForRenderPass();n.layout.get("text-variable-anchor")&&function(e,r,n,a,i,o,s){for(var l=r.transform,c="map"===i,u="map"===o,h=0,f=e;h<f.length;h+=1){var p=f[h],d=a.getTile(p),g=d.getBucket(n);if(g&&g.text&&g.text.segments.get().length){var m=t.evaluateSizeForZoom(g.textSizeData,l.zoom),v=fe(d,1,r.transform.zoom),y=Kt(p.posMatrix,u,c,r.transform,v),x="none"!==n.layout.get("icon-text-fit")&&g.hasIconData();if(m){var b=Math.pow(2,l.zoom-d.tileID.overscaledZ);Qr(g,c,u,s,t.symbolSize,l,y,p.posMatrix,b,m,x)}}}}(a,e,n,r,n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),i),0!==n.paint.get("icon-opacity").constantOr(1)&&tn(e,r,n,a,!1,n.paint.get("icon-translate"),n.paint.get("icon-translate-anchor"),n.layout.get("icon-rotation-alignment"),n.layout.get("icon-pitch-alignment"),n.layout.get("icon-keep-upright"),o,s),0!==n.paint.get("text-opacity").constantOr(1)&&tn(e,r,n,a,!0,n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),n.layout.get("text-keep-upright"),o,s),r.map.showCollisionBoxes&&(Xr(e,r,n,a,n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),!0),Xr(e,r,n,a,n.paint.get("icon-translate"),n.paint.get("icon-translate-anchor"),!1))}},circle:function(e,r,n,a){if("translucent"===e.renderPass){var i=n.paint.get("circle-opacity"),o=n.paint.get("circle-stroke-width"),s=n.paint.get("circle-stroke-opacity"),l=void 0!==n.layout.get("circle-sort-key").constantOr(1);if(0!==i.constantOr(1)||0!==o.constantOr(1)&&0!==s.constantOr(1)){for(var c=e.context,u=c.gl,h=e.depthModeForSublayer(0,At.ReadOnly),f=Mt.disabled,p=e.colorModeForRenderPass(),d=[],g=0;g<a.length;g++){var m=a[g],v=r.getTile(m),y=v.getBucket(n);if(y){var x=y.programConfigurations.get(n.id),b={programConfiguration:x,program:e.useProgram("circle",x),layoutVertexBuffer:y.layoutVertexBuffer,indexBuffer:y.indexBuffer,uniformValues:Er(e,m,v,n)};if(l)for(var _=0,w=y.segments.get();_<w.length;_+=1){var T=w[_];d.push({segments:new t.SegmentVector([T]),sortKey:T.sortKey,state:b})}else d.push({segments:y.segments,sortKey:0,state:b})}}l&&d.sort((function(t,e){return t.sortKey-e.sortKey}));for(var k=0,A=d;k<A.length;k+=1){var M=A[k],S=M.state;S.program.draw(c,u.TRIANGLES,h,f,p,Et.disabled,S.uniformValues,n.id,S.layoutVertexBuffer,S.indexBuffer,M.segments,n.paint,e.transform.zoom,S.programConfiguration)}}}},heatmap:function(e,r,n,a){if(0!==n.paint.get("heatmap-opacity"))if("offscreen"===e.renderPass){var i=e.context,o=i.gl,s=Mt.disabled,l=new St([o.ONE,o.ONE],t.Color.transparent,[!0,!0,!0,!0]);!function(t,e,r){var n=t.gl;t.activeTexture.set(n.TEXTURE1),t.viewport.set([0,0,e.width/4,e.height/4]);var a=r.heatmapFbo;if(a)n.bindTexture(n.TEXTURE_2D,a.colorAttachment.get()),t.bindFramebuffer.set(a.framebuffer);else{var i=n.createTexture();n.bindTexture(n.TEXTURE_2D,i),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_S,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_WRAP_T,n.CLAMP_TO_EDGE),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MIN_FILTER,n.LINEAR),n.texParameteri(n.TEXTURE_2D,n.TEXTURE_MAG_FILTER,n.LINEAR),a=r.heatmapFbo=t.createFramebuffer(e.width/4,e.height/4,!1),function(t,e,r,n){var a=t.gl;a.texImage2D(a.TEXTURE_2D,0,a.RGBA,e.width/4,e.height/4,0,a.RGBA,t.extRenderToTextureHalfFloat?t.extTextureHalfFloat.HALF_FLOAT_OES:a.UNSIGNED_BYTE,null),n.colorAttachment.set(r)}(t,e,i,a)}}(i,e,n),i.clear({color:t.Color.transparent});for(var c=0;c<a.length;c++){var u=a[c];if(!r.hasRenderableParent(u)){var h=r.getTile(u),f=h.getBucket(n);if(f){var p=f.programConfigurations.get(n.id);e.useProgram("heatmap",p).draw(i,o.TRIANGLES,At.disabled,s,l,Et.disabled,zr(u.posMatrix,h,e.transform.zoom,n.paint.get("heatmap-intensity")),n.id,f.layoutVertexBuffer,f.indexBuffer,f.segments,n.paint,e.transform.zoom,p)}}}i.viewport.set([0,0,e.width,e.height])}else"translucent"===e.renderPass&&(e.context.setColorMode(e.colorModeForRenderPass()),function(e,r){var n=e.context,a=n.gl,i=r.heatmapFbo;if(i){n.activeTexture.set(a.TEXTURE0),a.bindTexture(a.TEXTURE_2D,i.colorAttachment.get()),n.activeTexture.set(a.TEXTURE1);var o=r.colorRampTexture;o||(o=r.colorRampTexture=new t.Texture(n,r.colorRamp,a.RGBA)),o.bind(a.LINEAR,a.CLAMP_TO_EDGE),e.useProgram("heatmapTexture").draw(n,a.TRIANGLES,At.disabled,Mt.disabled,e.colorModeForRenderPass(),Et.disabled,function(e,r,n,a){var i=t.create();t.ortho(i,0,e.width,e.height,0,0,1);var o=e.context.gl;return{u_matrix:i,u_world:[o.drawingBufferWidth,o.drawingBufferHeight],u_image:0,u_color_ramp:1,u_opacity:r.paint.get("heatmap-opacity")}}(e,r),r.id,e.viewportBuffer,e.quadTriangleIndexBuffer,e.viewportSegments,r.paint,e.transform.zoom)}}(e,n))},line:function(e,r,n,a){if("translucent"===e.renderPass){var i=n.paint.get("line-opacity"),o=n.paint.get("line-width");if(0!==i.constantOr(1)&&0!==o.constantOr(1)){var s=e.depthModeForSublayer(0,At.ReadOnly),l=e.colorModeForRenderPass(),c=n.paint.get("line-dasharray"),u=n.paint.get("line-pattern"),h=u.constantOr(1),f=n.paint.get("line-gradient"),p=n.getCrossfadeParameters(),d=h?"linePattern":c?"lineSDF":f?"lineGradient":"line",g=e.context,m=g.gl,v=!0;if(f){g.activeTexture.set(m.TEXTURE0);var y=n.gradientTexture;if(!n.gradient)return;y||(y=n.gradientTexture=new t.Texture(g,n.gradient,m.RGBA)),y.bind(m.LINEAR,m.CLAMP_TO_EDGE)}for(var x=0,b=a;x<b.length;x+=1){var _=b[x],w=r.getTile(_);if(!h||w.patternsLoaded()){var T=w.getBucket(n);if(T){var k=T.programConfigurations.get(n.id),A=e.context.program.get(),M=e.useProgram(d,k),S=v||M.program!==A,E=u.constantOr(null);if(E&&w.imageAtlas){var C=w.imageAtlas,L=C.patternPositions[E.to.toString()],P=C.patternPositions[E.from.toString()];L&&P&&k.setConstantPatternPositions(L,P)}var I=h?Rr(e,w,n,p):c?Fr(e,w,n,c,p):f?Dr(e,w,n):Or(e,w,n);h?(g.activeTexture.set(m.TEXTURE0),w.imageAtlasTexture.bind(m.LINEAR,m.CLAMP_TO_EDGE),k.updatePaintBuffers(p)):c&&(S||e.lineAtlas.dirty)&&(g.activeTexture.set(m.TEXTURE0),e.lineAtlas.bind(g)),M.draw(g,m.TRIANGLES,s,e.stencilModeForClipping(_),l,Et.disabled,I,n.id,T.layoutVertexBuffer,T.indexBuffer,T.segments,n.paint,e.transform.zoom,k),v=!1}}}}}},fill:function(e,r,n,a){var i=n.paint.get("fill-color"),o=n.paint.get("fill-opacity");if(0!==o.constantOr(1)){var s=e.colorModeForRenderPass(),l=n.paint.get("fill-pattern"),c=e.opaquePassEnabledForLayer()&&!l.constantOr(1)&&1===i.constantOr(t.Color.transparent).a&&1===o.constantOr(0)?"opaque":"translucent";if(e.renderPass===c){var u=e.depthModeForSublayer(1,"opaque"===e.renderPass?At.ReadWrite:At.ReadOnly);rn(e,r,n,a,u,s,!1)}if("translucent"===e.renderPass&&n.paint.get("fill-antialias")){var h=e.depthModeForSublayer(n.getPaintProperty("fill-outline-color")?2:0,At.ReadOnly);rn(e,r,n,a,h,s,!0)}}},"fill-extrusion":function(t,e,r,n){var a=r.paint.get("fill-extrusion-opacity");if(0!==a&&"translucent"===t.renderPass){var i=new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D);if(1!==a||r.paint.get("fill-extrusion-pattern").constantOr(1))nn(t,e,r,n,i,Mt.disabled,St.disabled),nn(t,e,r,n,i,t.stencilModeFor3D(),t.colorModeForRenderPass());else{var o=t.colorModeForRenderPass();nn(t,e,r,n,i,Mt.disabled,o)}}},hillshade:function(t,e,r,n){if("offscreen"===t.renderPass||"translucent"===t.renderPass){for(var a=t.context,i=e.getSource().maxzoom,o=t.depthModeForSublayer(0,At.ReadOnly),s=t.colorModeForRenderPass(),l="translucent"===t.renderPass?t.stencilConfigForOverlap(n):[{},n],c=l[0],u=0,h=l[1];u<h.length;u+=1){var f=h[u],p=e.getTile(f);p.needsHillshadePrepare&&"offscreen"===t.renderPass?on(t,p,r,i,o,Mt.disabled,s):"translucent"===t.renderPass&&an(t,p,r,o,c[f.overscaledZ],s)}a.viewport.set([0,0,t.width,t.height])}},raster:function(t,e,r,n){if("translucent"===t.renderPass&&0!==r.paint.get("raster-opacity")&&n.length)for(var a=t.context,i=a.gl,o=e.getSource(),s=t.useProgram("raster"),l=t.colorModeForRenderPass(),c=o instanceof I?[{},n]:t.stencilConfigForOverlap(n),u=c[0],h=c[1],f=h[h.length-1].overscaledZ,p=!t.options.moving,d=0,g=h;d<g.length;d+=1){var m=g[d],v=t.depthModeForSublayer(m.overscaledZ-f,1===r.paint.get("raster-opacity")?At.ReadWrite:At.ReadOnly,i.LESS),y=e.getTile(m),x=t.transform.calculatePosMatrix(m.toUnwrapped(),p);y.registerFadeDuration(r.paint.get("raster-fade-duration"));var b=e.findLoadedParent(m,0),_=sn(y,b,e,r,t.transform),w=void 0,T=void 0,k="nearest"===r.paint.get("raster-resampling")?i.NEAREST:i.LINEAR;a.activeTexture.set(i.TEXTURE0),y.texture.bind(k,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST),a.activeTexture.set(i.TEXTURE1),b?(b.texture.bind(k,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST),w=Math.pow(2,b.tileID.overscaledZ-y.tileID.overscaledZ),T=[y.tileID.canonical.x*w%1,y.tileID.canonical.y*w%1]):y.texture.bind(k,i.CLAMP_TO_EDGE,i.LINEAR_MIPMAP_NEAREST);var A=jr(x,T||[0,0],w||1,_,r);o instanceof I?s.draw(a,i.TRIANGLES,v,Mt.disabled,l,Et.disabled,A,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(a,i.TRIANGLES,v,u[m.overscaledZ],l,Et.disabled,A,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}},background:function(t,e,r){var n=r.paint.get("background-color"),a=r.paint.get("background-opacity");if(0!==a){var i=t.context,o=i.gl,s=t.transform,l=s.tileSize,c=r.paint.get("background-pattern");if(!t.isPatternMissing(c)){var u=!c&&1===n.a&&1===a&&t.opaquePassEnabledForLayer()?"opaque":"translucent";if(t.renderPass===u){var h=Mt.disabled,f=t.depthModeForSublayer(0,"opaque"===u?At.ReadWrite:At.ReadOnly),p=t.colorModeForRenderPass(),d=t.useProgram(c?"backgroundPattern":"background"),g=s.coveringTiles({tileSize:l});c&&(i.activeTexture.set(o.TEXTURE0),t.imageManager.bind(t.context));for(var m=r.getCrossfadeParameters(),v=0,y=g;v<y.length;v+=1){var x=y[v],b=t.transform.calculatePosMatrix(x.toUnwrapped()),_=c?Wr(b,a,t,c,{tileID:x,tileSize:l},m):Yr(b,a,n);d.draw(i,o.TRIANGLES,f,h,p,Et.disabled,_,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}}}},debug:function(t,e,r){for(var n=0;n<r.length;n++)mn(t,e,r[n])},custom:function(t,e,r){var n=t.context,a=r.implementation;if("offscreen"===t.renderPass){var i=a.prerender;i&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),i.call(a,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if("translucent"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Mt.disabled);var o="3d"===a.renderingMode?new At(t.context.gl.LEQUAL,At.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,At.ReadOnly);n.setDepthMode(o),a.render(n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}},yn=function(t,e){this.context=new Ct(t),this.transform=e,this._tileTextures={},this.setup(),this.numSublayers=Lt.maxUnderzooming+Lt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Be,this.gpuTimers={}};yn.prototype.resize=function(e,r){if(this.width=e*t.browser.devicePixelRatio,this.height=r*t.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var n=0,a=this.style._order;n<a.length;n+=1)this.style._layers[a[n]].resize()},yn.prototype.setup=function(){var e=this.context,r=new t.StructArrayLayout2i4;r.emplaceBack(0,0),r.emplaceBack(t.EXTENT,0),r.emplaceBack(0,t.EXTENT),r.emplaceBack(t.EXTENT,t.EXTENT),this.tileExtentBuffer=e.createVertexBuffer(r,He.members),this.tileExtentSegments=t.SegmentVector.simpleSegment(0,0,4,2);var n=new t.StructArrayLayout2i4;n.emplaceBack(0,0),n.emplaceBack(t.EXTENT,0),n.emplaceBack(0,t.EXTENT),n.emplaceBack(t.EXTENT,t.EXTENT),this.debugBuffer=e.createVertexBuffer(n,He.members),this.debugSegments=t.SegmentVector.simpleSegment(0,0,4,5);var a=new t.StructArrayLayout4i8;a.emplaceBack(0,0,0,0),a.emplaceBack(t.EXTENT,0,t.EXTENT,0),a.emplaceBack(0,t.EXTENT,0,t.EXTENT),a.emplaceBack(t.EXTENT,t.EXTENT,t.EXTENT,t.EXTENT),this.rasterBoundsBuffer=e.createVertexBuffer(a,P.members),this.rasterBoundsSegments=t.SegmentVector.simpleSegment(0,0,4,2);var i=new t.StructArrayLayout2i4;i.emplaceBack(0,0),i.emplaceBack(1,0),i.emplaceBack(0,1),i.emplaceBack(1,1),this.viewportBuffer=e.createVertexBuffer(i,He.members),this.viewportSegments=t.SegmentVector.simpleSegment(0,0,4,2);var o=new t.StructArrayLayout1ui2;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=e.createIndexBuffer(o);var s=new t.StructArrayLayout3ui6;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=e.createIndexBuffer(s),this.emptyTexture=new t.Texture(e,{width:1,height:1,data:new Uint8Array([0,0,0,0])},e.gl.RGBA);var l=this.context.gl;this.stencilClearMode=new Mt({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)},yn.prototype.clearStencil=function(){var e=this.context,r=e.gl;this.nextStencilID=1,this.currentStencilSource=void 0;var n=t.create();t.ortho(n,0,this.width,this.height,0,0,1),t.scale(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram("clippingMask").draw(e,r.TRIANGLES,At.disabled,this.stencilClearMode,St.disabled,Et.disabled,Ir(n),"$clipping",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)},yn.prototype._renderTileClippingMasks=function(t,e){if(this.currentStencilSource!==t.source&&t.isTileClipped()&&e&&e.length){this.currentStencilSource=t.source;var r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(St.disabled),r.setDepthMode(At.disabled);var a=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(var i=0,o=e;i<o.length;i+=1){var s=o[i],l=this._tileClippingMaskIDs[s.key]=this.nextStencilID++;a.draw(r,n.TRIANGLES,At.disabled,new Mt({func:n.ALWAYS,mask:0},l,255,n.KEEP,n.KEEP,n.REPLACE),St.disabled,Et.disabled,Ir(s.posMatrix),"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},yn.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new Mt({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new Mt({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},yn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),a=n[n.length-1].overscaledZ,i=n[0].overscaledZ-a+1;if(i>1){this.currentStencilSource=void 0,this.nextStencilID+i>256&&this.clearStencil();for(var o={},s=0;s<i;s++)o[s+a]=new Mt({func:r.GEQUAL,mask:255},s+this.nextStencilID,255,r.KEEP,r.KEEP,r.REPLACE);return this.nextStencilID+=i,[o,n]}return[(e={},e[a]=Mt.disabled,e),n]},yn.prototype.colorModeForRenderPass=function(){var e=this.context.gl;return this._showOverdrawInspector?new St([e.CONSTANT_COLOR,e.ONE],new t.Color(1/8,1/8,1/8,0),[!0,!0,!0,!0]):"opaque"===this.renderPass?St.unblended:St.alphaBlended},yn.prototype.depthModeForSublayer=function(t,e,r){if(!this.opaquePassEnabledForLayer())return At.disabled;var n=1-((1+this.currentLayer)*this.numSublayers+t)*this.depthEpsilon;return new At(r||this.context.gl.LEQUAL,e,[n,n])},yn.prototype.opaquePassEnabledForLayer=function(){return this.currentLayer<this.opaquePassCutoff},yn.prototype.render=function(e,r){var n=this;this.style=e,this.options=r,this.lineAtlas=e.lineAtlas,this.imageManager=e.imageManager,this.glyphManager=e.glyphManager,this.symbolFadeChange=e.placement.symbolFadeChange(t.browser.now()),this.imageManager.beginFrame();var a=this.style._order,i=this.style.sourceCaches;for(var o in i){var s=i[o];s.used&&s.prepare(this.context)}var l,c,u={},h={},f={};for(var p in i){var d=i[p];u[p]=d.getVisibleCoordinates(),h[p]=u[p].slice().reverse(),f[p]=d.getVisibleCoordinates(!0).reverse()}this.opaquePassCutoff=1/0;for(var g=0;g<a.length;g++)if(this.style._layers[a[g]].is3D()){this.opaquePassCutoff=g;break}this.renderPass="offscreen";for(var m=0,v=a;m<v.length;m+=1){var y=this.style._layers[v[m]];if(y.hasOffscreenPass()&&!y.isHidden(this.transform.zoom)){var x=h[y.source];("custom"===y.type||x.length)&&this.renderLayer(this,i[y.source],y,x)}}for(this.context.bindFramebuffer.set(null),this.context.clear({color:r.showOverdrawInspector?t.Color.black:t.Color.transparent,depth:1}),this.clearStencil(),this._showOverdrawInspector=r.showOverdrawInspector,this.depthRangeFor3D=[0,1-(e._order.length+2)*this.numSublayers*this.depthEpsilon],this.renderPass="opaque",this.currentLayer=a.length-1;this.currentLayer>=0;this.currentLayer--){var b=this.style._layers[a[this.currentLayer]],_=i[b.source],w=u[b.source];this._renderTileClippingMasks(b,w),this.renderLayer(this,_,b,w)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayer<a.length;this.currentLayer++){var T=this.style._layers[a[this.currentLayer]],k=i[T.source],A=("symbol"===T.type?f:h)[T.source];this._renderTileClippingMasks(T,u[T.source]),this.renderLayer(this,k,T,A)}this.options.showTileBoundaries&&(t.values(this.style._layers).forEach((function(t){t.source&&!t.isHidden(n.transform.zoom)&&(t.source!==(c&&c.id)&&(c=n.style.sourceCaches[t.source]),(!l||l.getSource().maxzoom<c.getSource().maxzoom)&&(l=c))})),l&&vn.debug(this,l,l.getVisibleCoordinates())),this.options.showPadding&&function(t){var e=t.transform.padding;pn(t,t.transform.height-(e.top||0),3,ln),pn(t,e.bottom||0,3,cn),dn(t,e.left||0,3,un),dn(t,t.transform.width-(e.right||0),3,hn);var r=t.transform.centerPoint;!function(t,e,r,n){gn(t,e-1,r-10,2,20,n),gn(t,e-10,r-1,20,2,n)}(t,r.x,t.transform.height-r.y,fn)}(this),this.context.setDefault()},yn.prototype.renderLayer=function(t,e,r,n){r.isHidden(this.transform.zoom)||("background"===r.type||"custom"===r.type||n.length)&&(this.id=r.id,this.gpuTimingStart(r),vn[r.type](t,e,r,n,this.style.placement.variableOffsets),this.gpuTimingEnd())},yn.prototype.gpuTimingStart=function(t){if(this.options.gpuTiming){var e=this.context.extTimerQuery,r=this.gpuTimers[t.id];r||(r=this.gpuTimers[t.id]={calls:0,cpuTime:0,query:e.createQueryEXT()}),r.calls++,e.beginQueryEXT(e.TIME_ELAPSED_EXT,r.query)}},yn.prototype.gpuTimingEnd=function(){if(this.options.gpuTiming){var t=this.context.extTimerQuery;t.endQueryEXT(t.TIME_ELAPSED_EXT)}},yn.prototype.collectGpuTimers=function(){var t=this.gpuTimers;return this.gpuTimers={},t},yn.prototype.queryGpuTimers=function(t){var e={};for(var r in t){var n=t[r],a=this.context.extTimerQuery,i=a.getQueryObjectEXT(n.query,a.QUERY_RESULT_EXT)/1e6;a.deleteQueryEXT(n.query),e[r]=i}return e},yn.prototype.translatePosMatrix=function(e,r,n,a,i){if(!n[0]&&!n[1])return e;var o=i?"map"===a?this.transform.angle:0:"viewport"===a?-this.transform.angle:0;if(o){var s=Math.sin(o),l=Math.cos(o);n=[n[0]*l-n[1]*s,n[0]*s+n[1]*l]}var c=[i?n[0]:fe(r,n[0],this.transform.zoom),i?n[1]:fe(r,n[1],this.transform.zoom),0],u=new Float32Array(16);return t.translate(u,e,c),u},yn.prototype.saveTileTexture=function(t){var e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]},yn.prototype.getTileTexture=function(t){var e=this._tileTextures[t];return e&&e.length>0?e.pop():null},yn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},yn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=""+t+(e?e.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"");return this.cache[r]||(this.cache[r]=new br(this.context,yr[t],e,Zr[t],this._showOverdrawInspector)),this.cache[r]},yn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},yn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},yn.prototype.initDebugOverlayCanvas=function(){null==this.debugOverlayCanvas&&(this.debugOverlayCanvas=t.window.document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))},yn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var xn=function(t,e){this.points=t,this.planes=e};xn.fromInvProjectionMatrix=function(e,r,n){var a=Math.pow(2,n),i=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*a)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],i[e[0]],i[e[1]]),n=t.sub([],i[e[2]],i[e[1]]),a=t.normalize([],t.cross([],r,n)),o=-t.dot(a,i[e[1]]);return a.concat(o)}));return new xn(i,o)};var bn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};bn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),a=t.clone$2(this.max),i=0;i<r.length;i++)n[i]=r[i]?this.min[i]:this.center[i],a[i]=r[i]?this.center[i]:this.max[i];return a[2]=this.max[2],new bn(n,a)},bn.prototype.distanceX=function(t){return Math.max(Math.min(this.max[0],t[0]),this.min[0])-t[0]},bn.prototype.distanceY=function(t){return Math.max(Math.min(this.max[1],t[1]),this.min[1])-t[1]},bn.prototype.intersects=function(e){for(var r=[[this.min[0],this.min[1],0,1],[this.max[0],this.min[1],0,1],[this.max[0],this.max[1],0,1],[this.min[0],this.max[1],0,1]],n=!0,a=0;a<e.planes.length;a++){for(var i=e.planes[a],o=0,s=0;s<r.length;s++)o+=t.dot$1(i,r[s])>=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,h=0;h<e.points.length;h++){var f=e.points[h][l]-this.min[l];c=Math.min(c,f),u=Math.max(u,f)}if(u<0||c>this.max[l]-this.min[l])return 0}return 1};var _n=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=t,this.bottom=e,this.left=r,this.right=n};_n.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},_n.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),a=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,a)},_n.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},_n.prototype.clone=function(){return new _n(this.top,this.bottom,this.left,this.right)},_n.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var wn=function(e,r,n,a,i){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===i||i,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=null==n?0:n,this._maxPitch=null==a?60:a,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new _n,this._posMatrixCache={},this._alignedPosMatrixCache={}},Tn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};wn.prototype.clone=function(){var t=new wn(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Tn.minZoom.get=function(){return this._minZoom},Tn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Tn.maxZoom.get=function(){return this._maxZoom},Tn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Tn.minPitch.get=function(){return this._minPitch},Tn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Tn.maxPitch.get=function(){return this._maxPitch},Tn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Tn.renderWorldCopies.get=function(){return this._renderWorldCopies},Tn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Tn.worldSize.get=function(){return this.tileSize*this.scale},Tn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Tn.size.get=function(){return new t.Point(this.width,this.height)},Tn.bearing.get=function(){return-this.angle/Math.PI*180},Tn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Tn.pitch.get=function(){return this._pitch/Math.PI*180},Tn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Tn.fov.get=function(){return this._fov/Math.PI*180},Tn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Tn.zoom.get=function(){return this._zoom},Tn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Tn.center.get=function(){return this._center},Tn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Tn.padding.get=function(){return this._edgeInsets.toJSON()},Tn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Tn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},wn.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},wn.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},wn.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},wn.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),a=this.pointCoordinate(new t.Point(this.width,0)),i=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,a.x,i.x,o.x)),l=Math.floor(Math.max(n.x,a.x,i.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},wn.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&r<e.minzoom)return[];void 0!==e.maxzoom&&r>e.maxzoom&&(r=e.maxzoom);var a=t.MercatorCoordinate.fromLngLat(this.center),i=Math.pow(2,r),o=[i*a.x,i*a.y,0],s=xn.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new bn([t*i,0,0],[(t+1)*i,i,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],h=[],f=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var g=u.pop(),m=g.x,v=g.y,y=g.fullyVisible;if(!y){var x=g.aabb.intersects(s);if(0===x)continue;y=2===x}var b=g.aabb.distanceX(o),_=g.aabb.distanceY(o),w=Math.max(Math.abs(b),Math.abs(_));if(g.zoom===f||w>3+(1<<f-g.zoom)-2&&g.zoom>=l)h.push({tileID:new t.OverscaledTileID(g.zoom===f?p:g.zoom,g.wrap,g.zoom,m,v),distanceSq:t.sqrLen([o[0]-.5-m,o[1]-.5-v])});else for(var T=0;T<4;T++){var k=(m<<1)+T%2,A=(v<<1)+(T>>1);u.push({aabb:g.aabb.quadrant(T),zoom:g.zoom+1,x:k,y:A,wrap:g.wrap,fullyVisible:y})}}return h.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},wn.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Tn.unmodified.get=function(){return this._unmodified},wn.prototype.zoomScale=function(t){return Math.pow(2,t)},wn.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},wn.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},wn.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Tn.point.get=function(){return this.project(this.center)},wn.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),a=this.pointCoordinate(this.centerPoint),i=this.locationCoordinate(e),o=new t.MercatorCoordinate(i.x-(n.x-a.x),i.y-(n.y-a.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},wn.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},wn.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},wn.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},wn.prototype.coordinateLocation=function(t){return t.toLngLat()},wn.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var a=r[3],i=n[3],o=r[1]/a,s=n[1]/i,l=r[2]/a,c=n[2]/i,u=l===c?0:(0-l)/(c-l);return new t.MercatorCoordinate(t.number(r[0]/a,n[0]/i,u)/this.worldSize,t.number(o,s,u)/this.worldSize)},wn.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},wn.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},wn.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},wn.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},wn.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,a=r?this._alignedPosMatrixCache:this._posMatrixCache;if(a[n])return a[n];var i=e.canonical,o=this.worldSize/this.zoomScale(i.z),s=i.x+Math.pow(2,i.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,i.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),a[n]=new Float32Array(l),a[n]},wn.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},wn.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,a,i=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var h=this.latRange;i=t.mercatorYfromLat(h[1])*this.worldSize,e=(o=t.mercatorYfromLat(h[0])*this.worldSize)-i<c.y?c.y/(o-i):0}if(this.lngRange){var f=this.lngRange;s=t.mercatorXfromLng(f[0])*this.worldSize,r=(l=t.mercatorXfromLng(f[1])*this.worldSize)-s<c.x?c.x/(l-s):0}var p=this.point,d=Math.max(r||0,e||0);if(d)return this.center=this.unproject(new t.Point(r?(l+s)/2:p.x,e?(o+i)/2:p.y)),this.zoom+=this.scaleZoom(d),this._unmodified=u,void(this._constraining=!1);if(this.latRange){var g=p.y,m=c.y/2;g-m<i&&(a=i+m),g+m>o&&(a=o-m)}if(this.lngRange){var v=p.x,y=c.x/2;v-y<s&&(n=s+y),v+y>l&&(n=l-y)}void 0===n&&void 0===a||(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==a?a:p.y))),this._unmodified=u,this._constraining=!1}},wn.prototype._calcMatrices=function(){if(this.height){var e=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height;var r=Math.PI/2+this._pitch,n=this._fov*(.5+e.y/this.height),a=Math.sin(n)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-r-n,.01,Math.PI-.01)),i=this.point,o=i.x,s=i.y,l=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),c=this.height/50,u=new Float64Array(16);t.perspective(u,this._fov,this.width/this.height,c,l),u[8]=2*-e.x/this.width,u[9]=2*e.y/this.height,t.scale(u,u,[1,-1,1]),t.translate(u,u,[0,0,-this.cameraToCenterDistance]),t.rotateX(u,u,this._pitch),t.rotateZ(u,u,this.angle),t.translate(u,u,[-o,-s,0]),this.mercatorMatrix=t.scale([],u,[this.worldSize,this.worldSize,this.worldSize]),t.scale(u,u,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=u,this.invProjMatrix=t.invert([],this.projMatrix);var h=this.width%2/2,f=this.height%2/2,p=Math.cos(this.angle),d=Math.sin(this.angle),g=o-Math.round(o)+p*h+d*f,m=s-Math.round(s)+p*f+d*h,v=new Float64Array(u);if(t.translate(v,v,[g>.5?g-1:g,m>.5?m-1:m,0]),this.alignedProjMatrix=v,u=t.create(),t.scale(u,u,[this.width/2,-this.height/2,1]),t.translate(u,u,[1,-1,0]),this.labelPlaneMatrix=u,u=t.create(),t.scale(u,u,[1,-1,1]),t.translate(u,u,[-1,-1,0]),t.scale(u,u,[2/this.width,2/this.height,1]),this.glCoordMatrix=u,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(u=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error("failed to invert matrix");this.pixelMatrixInverse=u,this._posMatrixCache={},this._alignedPosMatrixCache={}}},wn.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},wn.prototype.getCameraPoint=function(){var e=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,e))},wn.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,a=r.y,i=r.x,o=r.y,s=0,l=e;s<l.length;s+=1){var c=l[s];n=Math.min(n,c.x),a=Math.min(a,c.y),i=Math.max(i,c.x),o=Math.max(o,c.y)}return[new t.Point(n,a),new t.Point(i,a),new t.Point(i,o),new t.Point(n,o),new t.Point(n,a)]},Object.defineProperties(wn.prototype,Tn);var kn=function(e){var r,n,a,i;this._hashName=e&&encodeURIComponent(e),t.bindAll(["_getCurrentHash","_onHashChange","_updateHash"],this),this._updateHash=(r=this._updateHashUnthrottled.bind(this),n=!1,a=null,i=function(){a=null,n&&(r(),a=setTimeout(i,300),n=!1)},function(){return n=!0,a||i(),a})};kn.prototype.addTo=function(e){return this._map=e,t.window.addEventListener("hashchange",this._onHashChange,!1),this._map.on("moveend",this._updateHash),this},kn.prototype.remove=function(){return t.window.removeEventListener("hashchange",this._onHashChange,!1),this._map.off("moveend",this._updateHash),clearTimeout(this._updateHash()),delete this._map,this},kn.prototype.getHashString=function(e){var r=this._map.getCenter(),n=Math.round(100*this._map.getZoom())/100,a=Math.ceil((n*Math.LN2+Math.log(512/360/.5))/Math.LN10),i=Math.pow(10,a),o=Math.round(r.lng*i)/i,s=Math.round(r.lat*i)/i,l=this._map.getBearing(),c=this._map.getPitch(),u="";if(u+=e?"/"+o+"/"+s+"/"+n:n+"/"+s+"/"+o,(l||c)&&(u+="/"+Math.round(10*l)/10),c&&(u+="/"+Math.round(c)),this._hashName){var h=this._hashName,f=!1,p=t.window.location.hash.slice(1).split("&").map((function(t){var e=t.split("=")[0];return e===h?(f=!0,e+"="+u):t})).filter((function(t){return t}));return f||p.push(h+"="+u),"#"+p.join("&")}return"#"+u},kn.prototype._getCurrentHash=function(){var e,r=this,n=t.window.location.hash.replace("#","");return this._hashName?(n.split("&").map((function(t){return t.split("=")})).forEach((function(t){t[0]===r._hashName&&(e=t)})),(e&&e[1]||"").split("/")):n.split("/")},kn.prototype._onHashChange=function(){var t=this._getCurrentHash();if(t.length>=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},kn.prototype._updateHashUnthrottled=function(){var e=this.getHashString();try{t.window.history.replaceState(t.window.history.state,"",e)}catch(t){}};var An={linearity:.3,easing:t.bezier(0,0,.3,1)},Mn=t.extend({deceleration:2500,maxSpeed:1400},An),Sn=t.extend({deceleration:20,maxSpeed:1400},An),En=t.extend({deceleration:1e3,maxSpeed:360},An),Cn=t.extend({deceleration:1e3,maxSpeed:90},An),Ln=function(t){this._map=t,this.clear()};function Pn(t,e){(!t.duration||t.duration<e.duration)&&(t.duration=e.duration,t.easing=e.easing)}function In(e,r,n){var a=n.maxSpeed,i=n.linearity,o=n.deceleration,s=t.clamp(e*i/(r/1e3),-a,a),l=Math.abs(s)/(o*i);return{easing:n.easing,duration:1e3*l,amount:s*(l/2)}}Ln.prototype.clear=function(){this._inertiaBuffer=[]},Ln.prototype.record=function(e){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:t.browser.now(),settings:e})},Ln.prototype._drainInertiaBuffer=function(){for(var e=this._inertiaBuffer,r=t.browser.now();e.length>0&&r-e[0].time>160;)e.shift()},Ln.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,a=this._inertiaBuffer;n<a.length;n+=1){var i=a[n].settings;r.zoom+=i.zoomDelta||0,r.bearing+=i.bearingDelta||0,r.pitch+=i.pitchDelta||0,i.panDelta&&r.pan._add(i.panDelta),i.around&&(r.around=i.around),i.pinchAround&&(r.pinchAround=i.pinchAround)}var o=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,s={};if(r.pan.mag()){var l=In(r.pan.mag(),o,t.extend({},Mn,e||{}));s.offset=r.pan.mult(l.amount/r.pan.mag()),s.center=this._map.transform.center,Pn(s,l)}if(r.zoom){var c=In(r.zoom,o,Sn);s.zoom=this._map.transform.zoom+c.amount,Pn(s,c)}if(r.bearing){var u=In(r.bearing,o,En);s.bearing=this._map.transform.bearing+t.clamp(u.amount,-179,179),Pn(s,u)}if(r.pitch){var h=In(r.pitch,o,Cn);s.pitch=this._map.transform.pitch+h.amount,Pn(s,h)}if(s.zoom||s.bearing){var f=void 0===r.pinchAround?r.around:r.pinchAround;s.around=f?this._map.unproject(f):this._map.getCenter()}return this.clear(),t.extend(s,{noMoveStart:!0})}};var zn=function(e){function n(n,a,i,o){void 0===o&&(o={});var s=r.mousePos(a.getCanvasContainer(),i),l=a.unproject(s);e.call(this,n,t.extend({point:s,lngLat:l,originalEvent:i},o)),this._defaultPrevented=!1,this.target=a}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var a={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},a.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,a),n}(t.Event),On=function(e){function n(n,a,i){var o="touchend"===n?i.changedTouches:i.touches,s=r.touchPos(a.getCanvasContainer(),o),l=s.map((function(t){return a.unproject(t)})),c=s.reduce((function(t,e,r,n){return t.add(e.div(n.length))}),new t.Point(0,0)),u=a.unproject(c);e.call(this,n,{points:s,point:c,lngLats:l,lngLat:u,originalEvent:i}),this._defaultPrevented=!1}e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n;var a={defaultPrevented:{configurable:!0}};return n.prototype.preventDefault=function(){this._defaultPrevented=!0},a.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(n.prototype,a),n}(t.Event),Dn=function(t){function e(e,r,n){t.call(this,e,{originalEvent:n}),this._defaultPrevented=!1}t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e;var r={defaultPrevented:{configurable:!0}};return e.prototype.preventDefault=function(){this._defaultPrevented=!0},r.defaultPrevented.get=function(){return this._defaultPrevented},Object.defineProperties(e.prototype,r),e}(t.Event),Rn=function(t,e){this._map=t,this._clickTolerance=e.clickTolerance};Rn.prototype.reset=function(){delete this._mousedownPos},Rn.prototype.wheel=function(t){return this._firePreventable(new Dn(t.type,this._map,t))},Rn.prototype.mousedown=function(t,e){return this._mousedownPos=e,this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseup=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.click=function(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.dblclick=function(t){return this._firePreventable(new zn(t.type,this._map,t))},Rn.prototype.mouseover=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.mouseout=function(t){this._map.fire(new zn(t.type,this._map,t))},Rn.prototype.touchstart=function(t){return this._firePreventable(new On(t.type,this._map,t))},Rn.prototype.touchmove=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchend=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype.touchcancel=function(t){this._map.fire(new On(t.type,this._map,t))},Rn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Rn.prototype.isEnabled=function(){return!0},Rn.prototype.isActive=function(){return!1},Rn.prototype.enable=function(){},Rn.prototype.disable=function(){};var Fn=function(t){this._map=t};Fn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Fn.prototype.mousemove=function(t){this._map.fire(new zn(t.type,this._map,t))},Fn.prototype.mousedown=function(){this._delayContextMenu=!0},Fn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new zn("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Fn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new zn(t.type,this._map,t)),this._map.listens("contextmenu")&&t.preventDefault()},Fn.prototype.isEnabled=function(){return!0},Fn.prototype.isActive=function(){return!1},Fn.prototype.enable=function(){},Fn.prototype.disable=function(){};var Bn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Nn(t,e){for(var r={},n=0;n<t.length;n++)r[t[n].identifier]=e[n];return r}Bn.prototype.isEnabled=function(){return!!this._enabled},Bn.prototype.isActive=function(){return!!this._active},Bn.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},Bn.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Bn.prototype.mousedown=function(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(r.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)},Bn.prototype.mousemoveWindow=function(t,e){if(this._active){var n=e;if(!(this._lastPos.equals(n)||!this._box&&n.dist(this._startPos)<this._clickTolerance)){var a=this._startPos;this._lastPos=n,this._box||(this._box=r.create("div","mapboxgl-boxzoom",this._container),this._container.classList.add("mapboxgl-crosshair"),this._fireEvent("boxzoomstart",t));var i=Math.min(a.x,n.x),o=Math.max(a.x,n.x),s=Math.min(a.y,n.y),l=Math.max(a.y,n.y);r.setTransform(this._box,"translate("+i+"px,"+s+"px)"),this._box.style.width=o-i+"px",this._box.style.height=l-s+"px"}}},Bn.prototype.mouseupWindow=function(e,n){var a=this;if(this._active&&0===e.button){var i=this._startPos,o=n;if(this.reset(),r.suppressClick(),i.x!==o.x||i.y!==o.y)return this._map.fire(new t.Event("boxzoomend",{originalEvent:e})),{cameraAnimation:function(t){return t.fitScreenCoordinates(i,o,a._map.getBearing(),{linear:!0})}};this._fireEvent("boxzoomcancel",e)}},Bn.prototype.keydown=function(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent("boxzoomcancel",t))},Bn.prototype.reset=function(){this._active=!1,this._container.classList.remove("mapboxgl-crosshair"),this._box&&(r.remove(this._box),this._box=null),r.enableDrag(),delete this._startPos,delete this._lastPos},Bn.prototype._fireEvent=function(e,r){return this._map.fire(new t.Event(e,{originalEvent:r}))};var jn=function(t){this.reset(),this.numTouches=t.numTouches};jn.prototype.reset=function(){delete this.centroid,delete this.startTime,delete this.touches,this.aborted=!1},jn.prototype.touchstart=function(e,r,n){(this.centroid||n.length>this.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,a=e;n<a.length;n+=1)r._add(a[n]);return r.div(e.length)}(r),this.touches=Nn(n,r)))},jn.prototype.touchmove=function(t,e,r){if(!this.aborted&&this.centroid){var n=Nn(r,e);for(var a in this.touches){var i=n[a];(!i||i.dist(this.touches[a])>30)&&(this.aborted=!0)}}},jn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Vn=function(t){this.singleTap=new jn(t),this.numTaps=t.numTaps,this.reset()};Vn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Vn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Vn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Vn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var a=t.timeStamp-this.lastTime<500,i=!this.lastTap||this.lastTap.dist(n)<30;if(a&&i||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Un=function(){this._zoomIn=new Vn({numTouches:1,numTaps:2}),this._zoomOut=new Vn({numTouches:2,numTaps:1}),this.reset()};Un.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Un.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Un.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Un.prototype.touchend=function(t,e,r){var n=this,a=this._zoomIn.touchend(t,e,r),i=this._zoomOut.touchend(t,e,r);return a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(a)},{originalEvent:t})}}):i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(i)},{originalEvent:t})}}):void 0},Un.prototype.touchcancel=function(){this.reset()},Un.prototype.enable=function(){this._enabled=!0},Un.prototype.disable=function(){this._enabled=!1,this.reset()},Un.prototype.isEnabled=function(){return this._enabled},Un.prototype.isActive=function(){return this._active};var qn=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};qn.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},qn.prototype._correctButton=function(t,e){return!1},qn.prototype._move=function(t,e){return{}},qn.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},qn.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r&&(t.preventDefault(),this._moved||!(e.dist(r)<this._clickTolerance)))return this._moved=!0,this._lastPoint=e,this._move(r,e)},qn.prototype.mouseupWindow=function(t){r.mouseButton(t)===this._eventButton&&(this._moved&&r.suppressClick(),this.reset())},qn.prototype.enable=function(){this._enabled=!0},qn.prototype.disable=function(){this._enabled=!1,this.reset()},qn.prototype.isEnabled=function(){return this._enabled},qn.prototype.isActive=function(){return this._active};var Hn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.mousedown=function(e,r){t.prototype.mousedown.call(this,e,r),this._lastPoint&&(this._active=!0)},e.prototype._correctButton=function(t,e){return 0===e&&!t.ctrlKey},e.prototype._move=function(t,e){return{around:e,panDelta:e.sub(t)}},e}(qn),Gn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=.8*(e.x-t.x);if(r)return this._active=!0,{bearingDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Yn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype._correctButton=function(t,e){return 0===e&&t.ctrlKey||2===e},e.prototype._move=function(t,e){var r=-.5*(e.y-t.y);if(r)return this._active=!0,{pitchDelta:r}},e.prototype.contextmenu=function(t){t.preventDefault()},e}(qn),Wn=function(t){this._minTouches=1,this._clickTolerance=t.clickTolerance||1,this.reset()};Wn.prototype.reset=function(){this._active=!1,this._touches={},this._sum=new t.Point(0,0)},Wn.prototype.touchstart=function(t,e,r){return this._calculateTransform(t,e,r)},Wn.prototype.touchmove=function(t,e,r){if(this._active)return t.preventDefault(),this._calculateTransform(t,e,r)},Wn.prototype.touchend=function(t,e,r){this._calculateTransform(t,e,r),this._active&&r.length<this._minTouches&&this.reset()},Wn.prototype.touchcancel=function(){this.reset()},Wn.prototype._calculateTransform=function(e,r,n){n.length>0&&(this._active=!0);var a=Nn(n,r),i=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in a){var c=a[l],u=this._touches[l];u&&(i._add(c),o._add(c.sub(u)),s++,a[l]=c)}if(this._touches=a,!(s<this._minTouches)&&o.mag()){var h=o.div(s);if(this._sum._add(h),!(this._sum.mag()<this._clickTolerance))return{around:i.div(s),panDelta:h}}},Wn.prototype.enable=function(){this._enabled=!0},Wn.prototype.disable=function(){this._enabled=!1,this.reset()},Wn.prototype.isEnabled=function(){return this._enabled},Wn.prototype.isActive=function(){return this._active};var Zn=function(){this.reset()};function Xn(t,e,r){for(var n=0;n<t.length;n++)if(t[n].identifier===r)return e[n]}function Jn(t,e){return Math.log(t/e)/Math.LN2}Zn.prototype.reset=function(){this._active=!1,delete this._firstTwoTouches},Zn.prototype._start=function(t){},Zn.prototype._move=function(t,e,r){return{}},Zn.prototype.touchstart=function(t,e,r){this._firstTwoTouches||r.length<2||(this._firstTwoTouches=[r[0].identifier,r[1].identifier],this._start([e[0],e[1]]))},Zn.prototype.touchmove=function(t,e,r){if(this._firstTwoTouches){t.preventDefault();var n=this._firstTwoTouches,a=n[1],i=Xn(r,e,n[0]),o=Xn(r,e,a);if(i&&o){var s=this._aroundCenter?null:i.add(o).div(2);return this._move([i,o],s,t)}}},Zn.prototype.touchend=function(t,e,n){if(this._firstTwoTouches){var a=this._firstTwoTouches,i=a[1],o=Xn(n,e,a[0]),s=Xn(n,e,i);o&&s||(this._active&&r.suppressClick(),this.reset())}},Zn.prototype.touchcancel=function(){this.reset()},Zn.prototype.enable=function(t){this._enabled=!0,this._aroundCenter=!!t&&"center"===t.around},Zn.prototype.disable=function(){this._enabled=!1,this.reset()},Zn.prototype.isEnabled=function(){return this._enabled},Zn.prototype.isActive=function(){return this._active};var Kn=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._distance,delete this._startDistance},e.prototype._start=function(t){this._startDistance=this._distance=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._distance;if(this._distance=t[0].dist(t[1]),this._active||!(Math.abs(Jn(this._distance,this._startDistance))<.1))return this._active=!0,{zoomDelta:Jn(this._distance,r),pinchAround:e}},e}(Zn);function Qn(t,e){return 180*t.angleWith(e)/Math.PI}var $n=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),delete this._minDiameter,delete this._startVector,delete this._vector},e.prototype._start=function(t){this._startVector=this._vector=t[0].sub(t[1]),this._minDiameter=t[0].dist(t[1])},e.prototype._move=function(t,e){var r=this._vector;if(this._vector=t[0].sub(t[1]),this._active||!this._isBelowThreshold(this._vector))return this._active=!0,{bearingDelta:Qn(this._vector,r),pinchAround:e}},e.prototype._isBelowThreshold=function(t){this._minDiameter=Math.min(this._minDiameter,t.mag());var e=25/(Math.PI*this._minDiameter)*360,r=Qn(t,this._startVector);return Math.abs(r)<e},e}(Zn);function ta(t){return Math.abs(t.y)>Math.abs(t.x)}var ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,ta(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),a=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,a,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+a.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,a=e.mag()>=2;if(n||a){if(!n||!a)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var i=t.y>0==e.y>0;return ta(t)&&ta(e)&&i}},e}(Zn),ra={panStep:100,bearingStep:15,pitchStep:10},na=function(){var t=ra;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep};function aa(t){return t*(2-t)}na.prototype.reset=function(){this._active=!1},na.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,a=0,i=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),i=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),i=1);break;case 38:t.shiftKey?a=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?a=-1:(t.preventDefault(),o=1);break;default:return}return{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:"keyboardHandler",easing:aa,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+a*e._pitchStep,offset:[-i*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},na.prototype.enable=function(){this._enabled=!0},na.prototype.disable=function(){this._enabled=!1,this.reset()},na.prototype.isEnabled=function(){return this._enabled},na.prototype.isActive=function(){return this._active};var ia=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=1/450,t.bindAll(["_onWheel","_onTimeout","_onScrollFrame","_onScrollFinished"],this)};ia.prototype.setZoomRate=function(t){this._defaultZoomRate=t},ia.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},ia.prototype.isEnabled=function(){return!!this._enabled},ia.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},ia.prototype.isZooming=function(){return!!this._zooming},ia.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&"center"===t.around)},ia.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},ia.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),a=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%4.000244140625==0?this._type="wheel":0!==r&&Math.abs(r)<4?this._type="trackpad":a>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(a*r)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},ia.prototype._onTimeout=function(t){this._type="wheel",this._delta-=this._lastValue,this._active||this._start(t)},ia.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},ia.prototype.renderFrame=function(){return this._onScrollFrame()},ia.prototype._onScrollFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n="wheel"===this._type&&Math.abs(this._delta)>4.000244140625?this._wheelZoomRate:this._defaultZoomRate,a=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==a&&(a=1/a);var i="number"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(i*a))),"wheel"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s="number"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if("wheel"===this._type&&l&&c){var h=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),f=c(h);o=t.number(l,s,f),h<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},ia.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,a=(t.browser.now()-n.start)/n.duration,i=n.easing(a+.01)-n.easing(a),o=.27/Math.sqrt(i*i+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},ia.prototype.reset=function(){this._active=!1};var oa=function(t,e){this._clickZoom=t,this._tapZoom=e};oa.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},oa.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},oa.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},oa.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var sa=function(){this.reset()};sa.prototype.reset=function(){this._active=!1},sa.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},sa.prototype.enable=function(){this._enabled=!0},sa.prototype.disable=function(){this._enabled=!1,this.reset()},sa.prototype.isEnabled=function(){return this._enabled},sa.prototype.isActive=function(){return this._active};var la=function(){this._tap=new Vn({numTouches:1,numTaps:1}),this.reset()};la.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},la.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},la.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],a=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:a/128}}}else this._tap.touchmove(t,e,r)},la.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},la.prototype.touchcancel=function(){this.reset()},la.prototype.enable=function(){this._enabled=!0},la.prototype.disable=function(){this._enabled=!1,this.reset()},la.prototype.isEnabled=function(){return this._enabled},la.prototype.isActive=function(){return this._active};var ca=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};ca.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("mapboxgl-touch-drag-pan")},ca.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("mapboxgl-touch-drag-pan")},ca.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},ca.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var ua=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};ua.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},ua.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},ua.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},ua.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var ha=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};ha.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add("mapboxgl-touch-zoom-rotate")},ha.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("mapboxgl-touch-zoom-rotate")},ha.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},ha.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},ha.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},ha.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var fa=function(t){return t.zoom||t.drag||t.pitch||t.rotate},pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),(e.prototype=Object.create(t&&t.prototype)).constructor=e,e}(t.Event);function da(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ga=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Ln(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll(["handleEvent","handleWindowEvent"],this);var a=this._el;this._listeners=[[a,"touchstart",{passive:!1}],[a,"touchmove",{passive:!1}],[a,"touchend",void 0],[a,"touchcancel",void 0],[a,"mousedown",void 0],[a,"mousemove",void 0],[a,"mouseup",void 0],[t.window.document,"mousemove",{capture:!0}],[t.window.document,"mouseup",void 0],[a,"mouseover",void 0],[a,"mouseout",void 0],[a,"dblclick",void 0],[a,"click",void 0],[a,"keydown",{capture:!1}],[a,"keyup",void 0],[a,"wheel",{passive:!1}],[a,"contextmenu",void 0],[t.window,"blur",void 0]];for(var i=0,o=this._listeners;i<o.length;i+=1){var s=o[i],l=s[0];r.addEventListener(l,s[1],l===t.window.document?this.handleWindowEvent:this.handleEvent,s[2])}};ga.prototype.destroy=function(){for(var e=0,n=this._listeners;e<n.length;e+=1){var a=n[e],i=a[0];r.removeEventListener(i,a[1],i===t.window.document?this.handleWindowEvent:this.handleEvent,a[2])}},ga.prototype._addDefaultHandlers=function(t){var e=this._map,r=e.getCanvasContainer();this._add("mapEvent",new Rn(e,t));var n=e.boxZoom=new Bn(e,t);this._add("boxZoom",n);var a=new Un,i=new sa;e.doubleClickZoom=new oa(i,a),this._add("tapZoom",a),this._add("clickZoom",i);var o=new la;this._add("tapDragZoom",o);var s=e.touchPitch=new ea;this._add("touchPitch",s);var l=new Gn(t),c=new Yn(t);e.dragRotate=new ua(t,l,c),this._add("mouseRotate",l,["mousePitch"]),this._add("mousePitch",c,["mouseRotate"]);var u=new Hn(t),h=new Wn(t);e.dragPan=new ca(r,u,h),this._add("mousePan",u),this._add("touchPan",h,["touchZoom","touchRotate"]);var f=new $n,p=new Kn;e.touchZoomRotate=new ha(r,p,f,o),this._add("touchRotate",f,["touchPan","touchZoom"]),this._add("touchZoom",p,["touchPan","touchRotate"]);var d=e.scrollZoom=new ia(e,this);this._add("scrollZoom",d,["mousePan"]);var g=e.keyboard=new na;this._add("keyboard",g),this._add("blockableMapEvent",new Fn(e));for(var m=0,v=["boxZoom","doubleClickZoom","tapDragZoom","touchPitch","dragRotate","dragPan","touchZoomRotate","scrollZoom","keyboard"];m<v.length;m+=1){var y=v[m];t.interactive&&t[y]&&e[y].enable(t[y])}},ga.prototype._add=function(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e},ga.prototype.stop=function(){if(!this._updatingCamera){for(var t=0,e=this._handlers;t<e.length;t+=1)e[t].handler.reset();this._inertia.clear(),this._fireEvents({},{}),this._changes=[]}},ga.prototype.isActive=function(){for(var t=0,e=this._handlers;t<e.length;t+=1)if(e[t].handler.isActive())return!0;return!1},ga.prototype.isZooming=function(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()},ga.prototype.isRotating=function(){return!!this._eventsInProgress.rotate},ga.prototype.isMoving=function(){return Boolean(fa(this._eventsInProgress))||this.isZooming()},ga.prototype._blockedByActive=function(t,e,r){for(var n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1},ga.prototype.handleWindowEvent=function(t){this.handleEvent(t,t.type+"Window")},ga.prototype._getMapTouches=function(t){for(var e=[],r=0,n=t;r<n.length;r+=1){var a=n[r];this._el.contains(a.target)&&e.push(a)}return e},ga.prototype.handleEvent=function(t,e){if("blur"!==t.type){this._updatingCamera=!0;for(var n="renderFrame"===t.type?void 0:t,a={needsRenderFrame:!1},i={},o={},s=t.touches?this._getMapTouches(t.touches):void 0,l=s?r.touchPos(this._el,s):r.mousePos(this._el,t),c=0,u=this._handlers;c<u.length;c+=1){var h=u[c],f=h.handlerName,p=h.handler,d=h.allowed;if(p.isEnabled()){var g=void 0;this._blockedByActive(o,d,f)?p.reset():p[e||t.type]&&(g=p[e||t.type](t,l,s),this.mergeHandlerResult(a,i,g,f,n),g&&g.needsRenderFrame&&this._triggerRenderFrame()),(g||p.isActive())&&(o[f]=p)}}var m={};for(var v in this._previousActiveHandlers)o[v]||(m[v]=n);this._previousActiveHandlers=o,(Object.keys(m).length||da(a))&&(this._changes.push([a,i,m]),this._triggerRenderFrame()),(Object.keys(o).length||da(a))&&this._map._stop(!0),this._updatingCamera=!1;var y=a.cameraAnimation;y&&(this._inertia.clear(),this._fireEvents({},{}),this._changes=[],y(this._map))}else this.stop()},ga.prototype.mergeHandlerResult=function(e,r,n,a,i){if(n){t.extend(e,n);var o={handlerName:a,originalEvent:n.originalEvent||i};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}},ga.prototype._applyChanges=function(){for(var e={},r={},n={},a=0,i=this._changes;a<i.length;a+=1){var o=i[a],s=o[0],l=o[1],c=o[2];s.panDelta&&(e.panDelta=(e.panDelta||new t.Point(0,0))._add(s.panDelta)),s.zoomDelta&&(e.zoomDelta=(e.zoomDelta||0)+s.zoomDelta),s.bearingDelta&&(e.bearingDelta=(e.bearingDelta||0)+s.bearingDelta),s.pitchDelta&&(e.pitchDelta=(e.pitchDelta||0)+s.pitchDelta),void 0!==s.around&&(e.around=s.around),void 0!==s.pinchAround&&(e.pinchAround=s.pinchAround),s.noInertia&&(e.noInertia=s.noInertia),t.extend(r,l),t.extend(n,c)}this._updateMapTransform(e,r,n),this._changes=[]},ga.prototype._updateMapTransform=function(t,e,r){var n=this._map,a=n.transform;if(!da(t))return this._fireEvents(e,r);var i=t.panDelta,o=t.zoomDelta,s=t.bearingDelta,l=t.pitchDelta,c=t.around,u=t.pinchAround;void 0!==u&&(c=u),n._stop(!0),c=c||n.transform.centerPoint;var h=a.pointLocation(i?c.sub(i):c);s&&(a.bearing+=s),l&&(a.pitch+=l),o&&(a.zoom+=o),a.setLocationAtPoint(h,c),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r)},ga.prototype._fireEvents=function(e,r){var n=this,a=fa(this._eventsInProgress),i=fa(e),o={};for(var s in e)this._eventsInProgress[s]||(o[s+"start"]=e[s].originalEvent),this._eventsInProgress[s]=e[s];for(var l in!a&&i&&this._fireEvent("movestart",i.originalEvent),o)this._fireEvent(l,o[l]);for(var c in e.rotate&&(this._bearingChanged=!0),i&&this._fireEvent("move",i.originalEvent),e)this._fireEvent(c,e[c].originalEvent);var u,h={};for(var f in this._eventsInProgress){var p=this._eventsInProgress[f],d=p.handlerName,g=p.originalEvent;this._handlersById[d].isActive()||(delete this._eventsInProgress[f],h[f+"end"]=u=r[d]||g)}for(var m in h)this._fireEvent(m,h[m]);var v=fa(this._eventsInProgress);if((a||i)&&!v){this._updatingCamera=!0;var y=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),x=function(t){return 0!==t&&-n._bearingSnap<t&&t<n._bearingSnap};y?(x(y.bearing||this._map.getBearing())&&(y.bearing=0),this._map.easeTo(y,{originalEvent:u})):(this._map.fire(new t.Event("moveend",{originalEvent:u})),x(this._map.getBearing())&&this._map.resetNorth()),this._bearingChanged=!1,this._updatingCamera=!1}},ga.prototype._fireEvent=function(e,r){this._map.fire(new t.Event(e,r?{originalEvent:r}:{}))},ga.prototype._triggerRenderFrame=function(){var t=this;void 0===this._frameId&&(this._frameId=this._map._requestRenderFrame((function(e){delete t._frameId,t.handleEvent(new pa("renderFrame",{timeStamp:e})),t._applyChanges()})))};var ma=function(e){function r(r,n){e.call(this),this._moving=!1,this._zooming=!1,this.transform=r,this._bearingSnap=n.bearingSnap,t.bindAll(["_renderFrameCallback"],this)}return e&&(r.__proto__=e),(r.prototype=Object.create(e&&e.prototype)).constructor=r,r.prototype.getCenter=function(){return new t.LngLat(this.transform.center.lng,this.transform.center.lat)},r.prototype.setCenter=function(t,e){return this.jumpTo({center:t},e)},r.prototype.panBy=function(e,r,n){return e=t.Point.convert(e).mult(-1),this.panTo(this.transform.center,t.extend({offset:e},r),n)},r.prototype.panTo=function(e,r,n){return this.easeTo(t.extend({center:e},r),n)},r.prototype.getZoom=function(){return this.transform.zoom},r.prototype.setZoom=function(t,e){return this.jumpTo({zoom:t},e),this},r.prototype.zoomTo=function(e,r,n){return this.easeTo(t.extend({zoom:e},r),n)},r.prototype.zoomIn=function(t,e){return this.zoomTo(this.getZoom()+1,t,e),this},r.prototype.zoomOut=function(t,e){return this.zoomTo(this.getZoom()-1,t,e),this},r.prototype.getBearing=function(){return this.transform.bearing},r.prototype.setBearing=function(t,e){return this.jumpTo({bearing:t},e),this},r.prototype.getPadding=function(){return this.transform.padding},r.prototype.setPadding=function(t,e){return this.jumpTo({padding:t},e),this},r.prototype.rotateTo=function(e,r,n){return this.easeTo(t.extend({bearing:e},r),n)},r.prototype.resetNorth=function(e,r){return this.rotateTo(0,t.extend({duration:1e3},e),r),this},r.prototype.resetNorthPitch=function(e,r){return this.easeTo(t.extend({bearing:0,pitch:0,duration:1e3},e),r),this},r.prototype.snapToNorth=function(t,e){return Math.abs(this.getBearing())<this._bearingSnap?this.resetNorth(t,e):this},r.prototype.getPitch=function(){return this.transform.pitch},r.prototype.setPitch=function(t,e){return this.jumpTo({pitch:t},e),this},r.prototype.cameraForBounds=function(e,r){return e=t.LngLatBounds.convert(e),this._cameraForBoxAndBearing(e.getNorthWest(),e.getSouthEast(),0,r)},r.prototype._cameraForBoxAndBearing=function(e,r,n,a){var i={top:0,bottom:0,right:0,left:0};if("number"==typeof(a=t.extend({padding:i,offset:[0,0],maxZoom:this.transform.maxZoom},a)).padding){var o=a.padding;a.padding={top:o,bottom:o,right:o,left:o}}a.padding=t.extend(i,a.padding);var s=this.transform,l=s.padding,c=s.project(t.LngLat.convert(e)),u=s.project(t.LngLat.convert(r)),h=c.rotate(-n*Math.PI/180),f=u.rotate(-n*Math.PI/180),p=new t.Point(Math.max(h.x,f.x),Math.max(h.y,f.y)),d=new t.Point(Math.min(h.x,f.x),Math.min(h.y,f.y)),g=p.sub(d),m=(s.width-(l.left+l.right+a.padding.left+a.padding.right))/g.x,v=(s.height-(l.top+l.bottom+a.padding.top+a.padding.bottom))/g.y;if(!(v<0||m<0)){var y=Math.min(s.scaleZoom(s.scale*Math.min(m,v)),a.maxZoom),x=t.Point.convert(a.offset),b=new t.Point(x.x+(a.padding.left-a.padding.right)/2,x.y+(a.padding.top-a.padding.bottom)/2).mult(s.scale/s.zoomScale(y));return{center:s.unproject(c.add(u).div(2).sub(b)),zoom:y,bearing:n}}t.warnOnce("Map cannot fit within canvas with the given bounds, padding, and/or offset.")},r.prototype.fitBounds=function(t,e,r){return this._fitInternal(this.cameraForBounds(t,e),e,r)},r.prototype.fitScreenCoordinates=function(e,r,n,a,i){return this._fitInternal(this._cameraForBoxAndBearing(this.transform.pointLocation(t.Point.convert(e)),this.transform.pointLocation(t.Point.convert(r)),n,a),a,i)},r.prototype._fitInternal=function(e,r,n){return e?(delete(r=t.extend(e,r)).padding,r.linear?this.easeTo(r,n):this.flyTo(r,n)):this},r.prototype.jumpTo=function(e,r){this.stop();var n=this.transform,a=!1,i=!1,o=!1;return"zoom"in e&&n.zoom!==+e.zoom&&(a=!0,n.zoom=+e.zoom),void 0!==e.center&&(n.center=t.LngLat.convert(e.center)),"bearing"in e&&n.bearing!==+e.bearing&&(i=!0,n.bearing=+e.bearing),"pitch"in e&&n.pitch!==+e.pitch&&(o=!0,n.pitch=+e.pitch),null==e.padding||n.isPaddingEqual(e.padding)||(n.padding=e.padding),this.fire(new t.Event("movestart",r)).fire(new t.Event("move",r)),a&&this.fire(new t.Event("zoomstart",r)).fire(new t.Event("zoom",r)).fire(new t.Event("zoomend",r)),i&&this.fire(new t.Event("rotatestart",r)).fire(new t.Event("rotate",r)).fire(new t.Event("rotateend",r)),o&&this.fire(new t.Event("pitchstart",r)).fire(new t.Event("pitch",r)).fire(new t.Event("pitchend",r)),this.fire(new t.Event("moveend",r))},r.prototype.easeTo=function(e,r){var n=this;this._stop(!1,e.easeId),(!1===(e=t.extend({offset:[0,0],duration:500,easing:t.ease},e)).animate||!e.essential&&t.browser.prefersReducedMotion)&&(e.duration=0);var a=this.transform,i=this.getZoom(),o=this.getBearing(),s=this.getPitch(),l=this.getPadding(),c="zoom"in e?+e.zoom:i,u="bearing"in e?this._normalizeBearing(e.bearing,o):o,h="pitch"in e?+e.pitch:s,f="padding"in e?e.padding:a.padding,p=t.Point.convert(e.offset),d=a.centerPoint.add(p),g=a.pointLocation(d),m=t.LngLat.convert(e.center||g);this._normalizeCenter(m);var v,y,x=a.project(g),b=a.project(m).sub(x),_=a.zoomScale(c-i);e.around&&(v=t.LngLat.convert(e.around),y=a.locationPoint(v));var w={moving:this._moving,zooming:this._zooming,rotating:this._rotating,pitching:this._pitching};return this._zooming=this._zooming||c!==i,this._rotating=this._rotating||o!==u,this._pitching=this._pitching||h!==s,this._padding=!a.isPaddingEqual(f),this._easeId=e.easeId,this._prepareEase(r,e.noMoveStart,w),clearTimeout(this._easeEndTimeoutID),this._ease((function(e){if(n._zooming&&(a.zoom=t.number(i,c,e)),n._rotating&&(a.bearing=t.number(o,u,e)),n._pitching&&(a.pitch=t.number(s,h,e)),n._padding&&(a.interpolatePadding(l,f,e),d=a.centerPoint.add(p)),v)a.setLocationAtPoint(v,y);else{var g=a.zoomScale(a.zoom-i),m=c>i?Math.min(2,_):Math.max(.5,_),w=Math.pow(m,1-e),T=a.unproject(x.add(b.mult(e*w)).mult(g));a.setLocationAtPoint(a.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,r||n.moving||this.fire(new t.Event("movestart",e)),this._zooming&&!n.zooming&&this.fire(new t.Event("zoomstart",e)),this._rotating&&!n.rotating&&this.fire(new t.Event("rotatestart",e)),this._pitching&&!n.pitching&&this.fire(new t.Event("pitchstart",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event("move",e)),this._zooming&&this.fire(new t.Event("zoom",e)),this._rotating&&this.fire(new t.Event("rotate",e)),this._pitching&&this.fire(new t.Event("pitch",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,a=this._rotating,i=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event("zoomend",e)),a&&this.fire(new t.Event("rotateend",e)),i&&this.fire(new t.Event("pitchend",e)),this.fire(new t.Event("moveend",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var a=t.pick(e,["center","zoom","bearing","pitch","around"]);return this.jumpTo(a,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var i=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u="zoom"in e?t.clamp(+e.zoom,i.minZoom,i.maxZoom):o,h="bearing"in e?this._normalizeBearing(e.bearing,s):s,f="pitch"in e?+e.pitch:l,p="padding"in e?e.padding:i.padding,d=i.zoomScale(u-o),g=t.Point.convert(e.offset),m=i.centerPoint.add(g),v=i.pointLocation(m),y=t.LngLat.convert(e.center||v);this._normalizeCenter(y);var x=i.project(v),b=i.project(y).sub(x),_=e.curve,w=Math.max(i.width,i.height),T=w/d,k=b.mag();if("minZoom"in e){var A=t.clamp(Math.min(e.minZoom,o,u),i.minZoom,i.maxZoom),M=w/i.zoomScale(A-o);_=Math.sqrt(M/k*2)}var S=_*_;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function C(t){return(Math.exp(t)-Math.exp(-t))/2}function L(t){return(Math.exp(t)+Math.exp(-t))/2}var P=E(0),I=function(t){return L(P)/L(P+_*t)},z=function(t){return w*((L(P)*(C(e=P+_*t)/L(e))-C(P))/S)/k;var e},O=(E(1)-P)/_;if(Math.abs(k)<1e-6||!isFinite(O)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var D=T<w?-1:1;O=Math.abs(Math.log(T/w))/_,z=function(){return 0},I=function(t){return Math.exp(D*_*t)}}return e.duration="duration"in e?+e.duration:1e3*O/("screenSpeed"in e?+e.screenSpeed/_:+e.speed),e.maxDuration&&e.duration>e.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==h,this._pitching=f!==l,this._padding=!i.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var a=e*O,d=1/I(a);i.zoom=1===e?u:o+i.scaleZoom(d),n._rotating&&(i.bearing=t.number(s,h,e)),n._pitching&&(i.pitch=t.number(l,f,e)),n._padding&&(i.interpolatePadding(c,p,e),m=i.centerPoint.add(g));var v=1===e?y:i.unproject(x.add(b.mult(z(a))).mult(d));i.setLocationAtPoint(i.renderWorldCopies?v.wrap():v,m),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop()}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)<n&&(e-=360),Math.abs(e+360-r)<n&&(e+=360),e},r.prototype._normalizeCenter=function(t){var e=this.transform;if(e.renderWorldCopies&&!e.lngRange){var r=t.lng-e.center.lng;t.lng+=r>180?-360:r<-180?360:0}},r}(t.Evented),va=function(e){void 0===e&&(e={}),this.options=e,t.bindAll(["_updateEditLink","_updateData","_updateCompact"],this)};va.prototype.getDefaultPosition=function(){return"bottom-right"},va.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-attrib"),this._innerContainer=r.create("div","mapboxgl-ctrl-attrib-inner",this._container),e&&this._container.classList.add("mapboxgl-compact"),this._updateAttributions(),this._updateEditLink(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("moveend",this._updateEditLink),void 0===e&&(this._map.on("resize",this._updateCompact),this._updateCompact()),this._container},va.prototype.onRemove=function(){r.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("moveend",this._updateEditLink),this._map.off("resize",this._updateCompact),this._map=void 0,this._attribHTML=void 0},va.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(".mapbox-improve-map"));var r=[{key:"owner",value:this.styleOwner},{key:"id",value:this.styleId},{key:"access_token",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+"="+e.value+(n<r.length-1?"&":"")),t}),"?");e.href=t.config.FEEDBACK_URL+"/"+n+(this._map._hash?this._map._hash.getHashString(!0):""),e.rel="noopener nofollow"}},va.prototype._updateData=function(t){!t||"metadata"!==t.sourceDataType&&"style"!==t.dataType||(this._updateAttributions(),this._updateEditLink())},va.prototype._updateAttributions=function(){if(this._map.style){var t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((function(t){return"string"!=typeof t?"":t}))):"string"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){var e=this._map.style.stylesheet;this.styleOwner=e.owner,this.styleId=e.id}var r=this._map.style.sourceCaches;for(var n in r){var a=r[n];if(a.used){var i=a.getSource();i.attribution&&t.indexOf(i.attribution)<0&&t.push(i.attribution)}}t.sort((function(t,e){return t.length-e.length}));var o=(t=t.filter((function(e,r){for(var n=r+1;n<t.length;n++)if(t[n].indexOf(e)>=0)return!1;return!0}))).join(" | ");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove("mapboxgl-attrib-empty")):this._container.classList.add("mapboxgl-attrib-empty"),this._editLink=null)}},va.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add("mapboxgl-compact"):this._container.classList.remove("mapboxgl-compact")};var ya=function(){t.bindAll(["_updateLogo"],this),t.bindAll(["_updateCompact"],this)};ya.prototype.onAdd=function(t){this._map=t,this._container=r.create("div","mapboxgl-ctrl");var e=r.create("a","mapboxgl-ctrl-logo");return e.target="_blank",e.rel="noopener nofollow",e.href="https://www.mapbox.com/",e.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),e.setAttribute("rel","noopener nofollow"),this._container.appendChild(e),this._container.style.display="none",this._map.on("sourcedata",this._updateLogo),this._updateLogo(),this._map.on("resize",this._updateCompact),this._updateCompact(),this._container},ya.prototype.onRemove=function(){r.remove(this._container),this._map.off("sourcedata",this._updateLogo),this._map.off("resize",this._updateCompact)},ya.prototype.getDefaultPosition=function(){return"bottom-left"},ya.prototype._updateLogo=function(t){t&&"metadata"!==t.sourceDataType||(this._container.style.display=this._logoRequired()?"block":"none")},ya.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},ya.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add("mapboxgl-compact"):e.classList.remove("mapboxgl-compact")}};var xa=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};xa.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},xa.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;r<n.length;r+=1){var a=n[r];if(a.id===t)return void(a.cancelled=!0)}},xa.prototype.run=function(t){void 0===t&&(t=0);var e=this._currentlyRunning=this._queue;this._queue=[];for(var r=0,n=e;r<n.length;r+=1){var a=n[r];if(!a.cancelled&&(a.callback(t),this._cleared))break}this._cleared=!1,this._currentlyRunning=!1},xa.prototype.clear=function(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]};var ba={"FullscreenControl.Enter":"Enter fullscreen","FullscreenControl.Exit":"Exit fullscreen","GeolocateControl.FindMyLocation":"Find my location","GeolocateControl.LocationNotAvailable":"Location not available","LogoControl.Title":"Mapbox logo","NavigationControl.ResetBearing":"Reset bearing to north","NavigationControl.ZoomIn":"Zoom in","NavigationControl.ZoomOut":"Zoom out","ScaleControl.Feet":"ft","ScaleControl.Meters":"m","ScaleControl.Kilometers":"km","ScaleControl.Miles":"mi","ScaleControl.NauticalMiles":"nm"},_a=t.window.HTMLImageElement,wa=t.window.HTMLElement,Ta=t.window.ImageBitmap,ka={center:[0,0],zoom:0,bearing:0,pitch:0,minZoom:-2,maxZoom:22,minPitch:0,maxPitch:60,interactive:!0,scrollZoom:!0,boxZoom:!0,dragRotate:!0,dragPan:!0,keyboard:!0,doubleClickZoom:!0,touchZoomRotate:!0,touchPitch:!0,bearingSnap:7,clickTolerance:3,pitchWithRotate:!0,hash:!1,attributionControl:!0,failIfMajorPerformanceCaveat:!1,preserveDrawingBuffer:!1,trackResize:!0,renderWorldCopies:!0,refreshExpiredTiles:!0,maxTileCacheSize:null,localIdeographFontFamily:"sans-serif",transformRequest:null,accessToken:null,fadeDuration:300,crossSourceCollisions:!0},Aa=function(n){function a(e){var r=this;if(null!=(e=t.extend({},ka,e)).minZoom&&null!=e.maxZoom&&e.minZoom>e.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(null!=e.minPitch&&e.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error("maxPitch must be less than or equal to 60");var a=new wn(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,a,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new xa,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},ba,e.locale),this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),"string"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error("Container '"+e.container+"' not found.")}else{if(!(e.container instanceof wa))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll(["_onWindowOnline","_onWindowResize","_contextLost","_contextRestored"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error("Failed to initialize WebGL.");this.on("move",(function(){return r._update(!1)})),this.on("moveend",(function(){return r._update(!1)})),this.on("zoom",(function(){return r._update(!0)})),void 0!==t.window&&(t.window.addEventListener("online",this._onWindowOnline,!1),t.window.addEventListener("resize",this._onWindowResize,!1)),this.handlers=new ga(this,e),this._hash=e.hash&&new kn("string"==typeof e.hash&&e.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new va({customAttribution:e.customAttribution})),this.addControl(new ya,e.logoPosition),this.on("style.load",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on("data",(function(e){r._update("style"===e.dataType),r.fire(new t.Event(e.dataType+"data",e))})),this.on("dataloading",(function(e){r.fire(new t.Event(e.dataType+"dataloading",e))}))}n&&(a.__proto__=n),(a.prototype=Object.create(n&&n.prototype)).constructor=a;var i={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return a.prototype._getMapId=function(){return this._mapId},a.prototype.addControl=function(e,r){if(void 0===r&&e.getDefaultPosition&&(r=e.getDefaultPosition()),void 0===r&&(r="top-right"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));var n=e.onAdd(this);this._controls.push(e);var a=this._controlPositions[r];return-1!==r.indexOf("bottom")?a.insertBefore(n,a.firstChild):a.appendChild(n),this},a.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},a.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],a=r[1];this._resizeCanvas(n,a),this.transform.resize(n,a),this.painter.resize(n,a);var i=!this._moving;return i&&(this.stop(),this.fire(new t.Event("movestart",e)).fire(new t.Event("move",e))),this.fire(new t.Event("resize",e)),i&&this.fire(new t.Event("moveend",e)),this},a.prototype.getBounds=function(){return this.transform.getBounds()},a.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},a.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},a.prototype.setMinZoom=function(t){if((t=null==t?-2:t)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()<t&&this.setZoom(t),this;throw new Error("minZoom must be between -2 and the current maxZoom, inclusive")},a.prototype.getMinZoom=function(){return this.transform.minZoom},a.prototype.setMaxZoom=function(t){if((t=null==t?22:t)>=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error("maxZoom must be greater than the current minZoom")},a.prototype.getMaxZoom=function(){return this.transform.maxZoom},a.prototype.setMinPitch=function(t){if((t=null==t?0:t)<0)throw new Error("minPitch must be greater than or equal to 0");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()<t&&this.setPitch(t),this;throw new Error("minPitch must be between 0 and the current maxPitch, inclusive")},a.prototype.getMinPitch=function(){return this.transform.minPitch},a.prototype.setMaxPitch=function(t){if((t=null==t?60:t)>60)throw new Error("maxPitch must be less than or equal to 60");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error("maxPitch must be greater than the current minPitch")},a.prototype.getMaxPitch=function(){return this.transform.maxPitch},a.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},a.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},a.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},a.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},a.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},a.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},a.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},a.prototype._createDelegatedListener=function(t,e,r){var n,a=this;if("mouseenter"===t||"mouseover"===t){var i=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=a.getLayer(e)?a.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?i||(i=!0,r.call(a,new zn(t,a,n.originalEvent,{features:o}))):i=!1},mouseout:function(){i=!1}}}}if("mouseleave"===t||"mouseout"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(a.getLayer(e)?a.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(a,new zn(t,a,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(a,new zn(t,a,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=a.getLayer(e)?a.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(a,t),delete t.features)},n)}},a.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var a=this._createDelegatedListener(t,e,r);for(var i in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(a),a.delegates)this.on(i,a.delegates[i]);return this},a.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var a=this._createDelegatedListener(t,e,r);for(var i in a.delegates)this.once(i,a.delegates[i]);return this},a.prototype.off=function(t,e,r){var a=this;return void 0===r?n.prototype.off.call(this,t,e):(this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var i=n[t],o=0;o<i.length;o++){var s=i[o];if(s.layer===e&&s.listener===r){for(var l in s.delegates)a.off(l,s.delegates[l]);return i.splice(o,1),a}}}(this._delegatedListeners),this)},a.prototype.queryRenderedFeatures=function(e,r){if(!this.style)return[];var n;if(void 0!==r||void 0===e||e instanceof t.Point||Array.isArray(e)||(r=e,e=void 0),r=r||{},(e=e||[[0,0],[this.transform.width,this.transform.height]])instanceof t.Point||"number"==typeof e[0])n=[t.Point.convert(e)];else{var a=t.Point.convert(e[0]),i=t.Point.convert(e[1]);n=[a,new t.Point(i.x,a.y),i,new t.Point(a.x,i.y),a]}return this.style.queryRenderedFeatures(n,r,this.transform)},a.prototype.querySourceFeatures=function(t,e){return this.style.querySourceFeatures(t,e)},a.prototype.setStyle=function(e,r){return!1!==(r=t.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&e?(this._diffStyle(e,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(e,r))},a.prototype._getUIString=function(t){var e=this._locale[t];if(null==e)throw new Error("Missing UI string '"+t+"'");return e},a.prototype._updateStyle=function(t,e){return this.style&&(this.style.setEventedParent(null),this.style._remove()),t?(this.style=new qe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),"string"==typeof t?this.style.loadURL(t):this.style.loadJSON(t),this):(delete this.style,this)},a.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new qe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},a.prototype._diffStyle=function(e,r){var n=this;if("string"==typeof e){var a=this._requestManager.normalizeStyleURL(e),i=this._requestManager.transformRequest(a,t.ResourceType.Style);t.getJSON(i,(function(e,a){e?n.fire(new t.ErrorEvent(e)):a&&n._updateDiff(a,r)}))}else"object"==typeof e&&this._updateDiff(e,r)},a.prototype._updateDiff=function(e,r){try{this.style.setState(e)&&this._update(!0)}catch(n){t.warnOnce("Unable to perform style diff: "+(n.message||n.error||n)+". Rebuilding the style from scratch."),this._updateStyle(e,r)}},a.prototype.getStyle=function(){if(this.style)return this.style.serialize()},a.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():t.warnOnce("There is no style added to the map.")},a.prototype.addSource=function(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)},a.prototype.isSourceLoaded=function(e){var r=this.style&&this.style.sourceCaches[e];if(void 0!==r)return r.loaded();this.fire(new t.ErrorEvent(new Error("There is no source with ID '"+e+"'")))},a.prototype.areTilesLoaded=function(){var t=this.style&&this.style.sourceCaches;for(var e in t){var r=t[e]._tiles;for(var n in r){var a=r[n];if("loaded"!==a.state&&"errored"!==a.state)return!1}}return!0},a.prototype.addSourceType=function(t,e,r){return this._lazyInitEmptyStyle(),this.style.addSourceType(t,e,r)},a.prototype.removeSource=function(t){return this.style.removeSource(t),this._update(!0)},a.prototype.getSource=function(t){return this.style.getSource(t)},a.prototype.addImage=function(e,r,n){void 0===n&&(n={});var a=n.pixelRatio;void 0===a&&(a=1);var i=n.sdf;void 0===i&&(i=!1);var o=n.stretchX,s=n.stretchY,l=n.content;if(this._lazyInitEmptyStyle(),r instanceof _a||Ta&&r instanceof Ta){var c=t.browser.getImageData(r);this.style.addImage(e,{data:new t.RGBAImage({width:c.width,height:c.height},c.data),pixelRatio:a,stretchX:o,stretchY:s,content:l,sdf:i,version:0})}else{if(void 0===r.width||void 0===r.height)return this.fire(new t.ErrorEvent(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));var u=r;this.style.addImage(e,{data:new t.RGBAImage({width:r.width,height:r.height},new Uint8Array(r.data)),pixelRatio:a,stretchX:o,stretchY:s,content:l,sdf:i,version:0,userImage:u}),u.onAdd&&u.onAdd(this,e)}},a.prototype.updateImage=function(e,r){var n=this.style.getImage(e);if(!n)return this.fire(new t.ErrorEvent(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));var a=r instanceof _a||Ta&&r instanceof Ta?t.browser.getImageData(r):r,i=a.width,o=a.height,s=a.data;return void 0===i||void 0===o?this.fire(new t.ErrorEvent(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`"))):i!==n.data.width||o!==n.data.height?this.fire(new t.ErrorEvent(new Error("The width and height of the updated image must be that same as the previous version of the image"))):(n.data.replace(s,!(r instanceof _a||Ta&&r instanceof Ta)),void this.style.updateImage(e,n))},a.prototype.hasImage=function(e){return e?!!this.style.getImage(e):(this.fire(new t.ErrorEvent(new Error("Missing required image id"))),!1)},a.prototype.removeImage=function(t){this.style.removeImage(t)},a.prototype.loadImage=function(e,r){t.getImage(this._requestManager.transformRequest(e,t.ResourceType.Image),r)},a.prototype.listImages=function(){return this.style.listImages()},a.prototype.addLayer=function(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)},a.prototype.moveLayer=function(t,e){return this.style.moveLayer(t,e),this._update(!0)},a.prototype.removeLayer=function(t){return this.style.removeLayer(t),this._update(!0)},a.prototype.getLayer=function(t){return this.style.getLayer(t)},a.prototype.setLayerZoomRange=function(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)},a.prototype.setFilter=function(t,e,r){return void 0===r&&(r={}),this.style.setFilter(t,e,r),this._update(!0)},a.prototype.getFilter=function(t){return this.style.getFilter(t)},a.prototype.setPaintProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setPaintProperty(t,e,r,n),this._update(!0)},a.prototype.getPaintProperty=function(t,e){return this.style.getPaintProperty(t,e)},a.prototype.setLayoutProperty=function(t,e,r,n){return void 0===n&&(n={}),this.style.setLayoutProperty(t,e,r,n),this._update(!0)},a.prototype.getLayoutProperty=function(t,e){return this.style.getLayoutProperty(t,e)},a.prototype.setLight=function(t,e){return void 0===e&&(e={}),this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)},a.prototype.getLight=function(){return this.style.getLight()},a.prototype.setFeatureState=function(t,e){return this.style.setFeatureState(t,e),this._update()},a.prototype.removeFeatureState=function(t,e){return this.style.removeFeatureState(t,e),this._update()},a.prototype.getFeatureState=function(t){return this.style.getFeatureState(t)},a.prototype.getContainer=function(){return this._container},a.prototype.getCanvasContainer=function(){return this._canvasContainer},a.prototype.getCanvas=function(){return this._canvas},a.prototype._containerDimensions=function(){var t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]},a.prototype._detectMissingCSS=function(){"rgb(250, 128, 114)"!==t.window.getComputedStyle(this._missingCSSCanary).getPropertyValue("background-color")&&t.warnOnce("This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.")},a.prototype._setupContainer=function(){var t=this._container;t.classList.add("mapboxgl-map"),(this._missingCSSCanary=r.create("div","mapboxgl-canary",t)).style.visibility="hidden",this._detectMissingCSS();var e=this._canvasContainer=r.create("div","mapboxgl-canvas-container",t);this._interactive&&e.classList.add("mapboxgl-interactive"),this._canvas=r.create("canvas","mapboxgl-canvas",e),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex","0"),this._canvas.setAttribute("aria-label","Map");var n=this._containerDimensions();this._resizeCanvas(n[0],n[1]);var a=this._controlContainer=r.create("div","mapboxgl-control-container",t),i=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach((function(t){i[t]=r.create("div","mapboxgl-ctrl-"+t,a)}))},a.prototype._resizeCanvas=function(e,r){var n=t.browser.devicePixelRatio||1;this._canvas.width=n*e,this._canvas.height=n*r,this._canvas.style.width=e+"px",this._canvas.style.height=r+"px"},a.prototype._setupPainter=function(){var r=t.extend({},e.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),n=this._canvas.getContext("webgl",r)||this._canvas.getContext("experimental-webgl",r);n?(this.painter=new yn(n,this.transform),t.webpSupported.testSupport(n)):this.fire(new t.ErrorEvent(new Error("Failed to initialize WebGL")))},a.prototype._contextLost=function(e){e.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new t.Event("webglcontextlost",{originalEvent:e}))},a.prototype._contextRestored=function(e){this._setupPainter(),this.resize(),this._update(),this.fire(new t.Event("webglcontextrestored",{originalEvent:e}))},a.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},a.prototype._update=function(t){return this.style?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this},a.prototype._requestRenderFrame=function(t){return this._update(),this._renderTaskQueue.add(t)},a.prototype._cancelRenderFrame=function(t){this._renderTaskQueue.remove(t)},a.prototype._render=function(e){var r,n=this,a=0,i=this.painter.context.extTimerQuery;if(this.listens("gpu-timing-frame")&&(r=i.createQueryEXT(),i.beginQueryEXT(i.TIME_ELAPSED_EXT,r),a=t.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(e),!this._removed){var o=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var s=this.transform.zoom,l=t.browser.now();this.style.zoomHistory.update(s,l);var c=new t.EvaluationParameters(s,{now:l,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),u=c.crossFadingFactor();1===u&&u===this._crossFadingFactor||(o=!0,this._crossFadingFactor=u),this.style.update(c)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens("gpu-timing-layer")}),this.fire(new t.Event("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new t.Event("load"))),this.style&&(this.style.hasTransitions()||o)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens("gpu-timing-frame")){var h=t.browser.now()-a;i.endQueryEXT(i.TIME_ELAPSED_EXT,r),setTimeout((function(){var e=i.getQueryObjectEXT(r,i.QUERY_RESULT_EXT)/1e6;i.deleteQueryEXT(r),n.fire(new t.Event("gpu-timing-frame",{cpuTime:h,gpuTime:e}))}),50)}if(this.listens("gpu-timing-layer")){var f=this.painter.collectGpuTimers();setTimeout((function(){var e=n.painter.queryGpuTimers(f);n.fire(new t.Event("gpu-timing-layer",{layerTimes:e}))}),50)}return this._sourcesDirty||this._styleDirty||this._placementDirty||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&(this._fullyLoaded||(this._fullyLoaded=!0),this.fire(new t.Event("idle"))),this}},a.prototype.remove=function(){this._hash&&this._hash.remove();for(var e=0,r=this._controls;e<r.length;e+=1)r[e].onRemove(this);this._controls=[],this._frame&&(this._frame.cancel(),this._frame=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),void 0!==t.window&&(t.window.removeEventListener("resize",this._onWindowResize,!1),t.window.removeEventListener("online",this._onWindowOnline,!1));var n=this.painter.context.gl.getExtension("WEBGL_lose_context");n&&n.loseContext(),Ma(this._canvasContainer),Ma(this._controlContainer),Ma(this._missingCSSCanary),this._container.classList.remove("mapboxgl-map"),this._removed=!0,this.fire(new t.Event("remove"))},a.prototype.triggerRepaint=function(){var e=this;this.style&&!this._frame&&(this._frame=t.browser.frame((function(t){e._frame=null,e._render(t)})))},a.prototype._onWindowOnline=function(){this._update()},a.prototype._onWindowResize=function(t){this._trackResize&&this.resize({originalEvent:t})._update()},i.showTileBoundaries.get=function(){return!!this._showTileBoundaries},i.showTileBoundaries.set=function(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())},i.showPadding.get=function(){return!!this._showPadding},i.showPadding.set=function(t){this._showPadding!==t&&(this._showPadding=t,this._update())},i.showCollisionBoxes.get=function(){return!!this._showCollisionBoxes},i.showCollisionBoxes.set=function(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())},i.showOverdrawInspector.get=function(){return!!this._showOverdrawInspector},i.showOverdrawInspector.set=function(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())},i.repaint.get=function(){return!!this._repaint},i.repaint.set=function(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())},i.vertices.get=function(){return!!this._vertices},i.vertices.set=function(t){this._vertices=t,this._update()},a.prototype._setCacheLimits=function(e,r){t.setCacheLimits(e,r)},i.version.get=function(){return t.version},Object.defineProperties(a.prototype,i),a}(ma);function Ma(t){t.parentNode&&t.parentNode.removeChild(t)}var Sa={showCompass:!0,showZoom:!0,visualizePitch:!1},Ea=function(e){var n=this;this.options=t.extend({},Sa,e),this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._container.addEventListener("contextmenu",(function(t){return t.preventDefault()})),this.options.showZoom&&(t.bindAll(["_setButtonTitle","_updateZoomButtons"],this),this._zoomInButton=this._createButton("mapboxgl-ctrl-zoom-in",(function(t){return n._map.zoomIn({},{originalEvent:t})})),r.create("span","mapboxgl-ctrl-icon",this._zoomInButton).setAttribute("aria-hidden",!0),this._zoomOutButton=this._createButton("mapboxgl-ctrl-zoom-out",(function(t){return n._map.zoomOut({},{originalEvent:t})})),r.create("span","mapboxgl-ctrl-icon",this._zoomOutButton).setAttribute("aria-hidden",!0)),this.options.showCompass&&(t.bindAll(["_rotateCompassArrow"],this),this._compass=this._createButton("mapboxgl-ctrl-compass",(function(t){n.options.visualizePitch?n._map.resetNorthPitch({},{originalEvent:t}):n._map.resetNorth({},{originalEvent:t})})),this._compassIcon=r.create("span","mapboxgl-ctrl-icon",this._compass),this._compassIcon.setAttribute("aria-hidden",!0))};Ea.prototype._updateZoomButtons=function(){var t=this._map.getZoom();this._zoomInButton.disabled=t===this._map.getMaxZoom(),this._zoomOutButton.disabled=t===this._map.getMinZoom()},Ea.prototype._rotateCompassArrow=function(){var t=this.options.visualizePitch?"scale("+1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)+") rotateX("+this._map.transform.pitch+"deg) rotateZ("+this._map.transform.angle*(180/Math.PI)+"deg)":"rotate("+this._map.transform.angle*(180/Math.PI)+"deg)";this._compassIcon.style.transform=t},Ea.prototype.onAdd=function(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,"ZoomIn"),this._setButtonTitle(this._zoomOutButton,"ZoomOut"),this._map.on("zoom",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,"ResetBearing"),this.options.visualizePitch&&this._map.on("pitch",this._rotateCompassArrow),this._map.on("rotate",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ca(this._map,this._compass,this.options.visualizePitch)),this._container},Ea.prototype.onRemove=function(){r.remove(this._container),this.options.showZoom&&this._map.off("zoom",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off("pitch",this._rotateCompassArrow),this._map.off("rotate",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map},Ea.prototype._createButton=function(t,e){var n=r.create("button",t,this._container);return n.type="button",n.addEventListener("click",e),n},Ea.prototype._setButtonTitle=function(t,e){var r=this._map._getUIString("NavigationControl."+e);t.title=r,t.setAttribute("aria-label",r)};var Ca=function(e,n,a){void 0===a&&(a=!1),this._clickTolerance=10,this.element=n,this.mouseRotate=new Gn({clickTolerance:e.dragRotate._mouseRotate._clickTolerance}),this.map=e,a&&(this.mousePitch=new Yn({clickTolerance:e.dragRotate._mousePitch._clickTolerance})),t.bindAll(["mousedown","mousemove","mouseup","touchstart","touchmove","touchend","reset"],this),r.addEventListener(n,"mousedown",this.mousedown),r.addEventListener(n,"touchstart",this.touchstart,{passive:!1}),r.addEventListener(n,"touchmove",this.touchmove),r.addEventListener(n,"touchend",this.touchend),r.addEventListener(n,"touchcancel",this.reset)};function La(e,r,n){if(e=new t.LngLat(e.lng,e.lat),r){var a=new t.LngLat(e.lng-360,e.lat),i=new t.LngLat(e.lng+360,e.lat),o=n.locationPoint(e).distSqr(r);n.locationPoint(a).distSqr(r)<o?e=a:n.locationPoint(i).distSqr(r)<o&&(e=i)}for(;Math.abs(e.lng-n.center.lng)>180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Ca.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Ca.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var a=this.mousePitch.mousemoveWindow(t,e);a&&a.pitchDelta&&r.setPitch(r.getPitch()+a.pitchDelta)}},Ca.prototype.off=function(){var t=this.element;r.removeEventListener(t,"mousedown",this.mousedown),r.removeEventListener(t,"touchstart",this.touchstart,{passive:!1}),r.removeEventListener(t,"touchmove",this.touchmove),r.removeEventListener(t,"touchend",this.touchend),r.removeEventListener(t,"touchcancel",this.reset),this.offTemp()},Ca.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,"mousemove",this.mousemove),r.removeEventListener(t.window,"mouseup",this.mouseup)},Ca.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,"mousemove",this.mousemove),r.addEventListener(t.window,"mouseup",this.mouseup)},Ca.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Ca.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Ca.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:"mousedown",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Ca.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Ca.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)<this._clickTolerance&&this.element.click(),this.reset()},Ca.prototype.reset=function(){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()};var Pa={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function Ia(t,e,r){var n=t.classList;for(var a in Pa)n.remove("mapboxgl-"+r+"-anchor-"+a);n.add("mapboxgl-"+r+"-anchor-"+e)}var za,Oa=function(e){function n(n,a){var i=this;if(e.call(this),(n instanceof 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s=r.createNS("http://www.w3.org/2000/svg","g");s.setAttributeNS(null,"stroke","none"),s.setAttributeNS(null,"stroke-width","1"),s.setAttributeNS(null,"fill","none"),s.setAttributeNS(null,"fill-rule","evenodd");var l=r.createNS("http://www.w3.org/2000/svg","g");l.setAttributeNS(null,"fill-rule","nonzero");var c=r.createNS("http://www.w3.org/2000/svg","g");c.setAttributeNS(null,"transform","translate(3.0, 29.0)"),c.setAttributeNS(null,"fill","#000000");for(var u=0,h=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}];u<h.length;u+=1){var f=h[u],p=r.createNS("http://www.w3.org/2000/svg","ellipse");p.setAttributeNS(null,"opacity","0.04"),p.setAttributeNS(null,"cx","10.5"),p.setAttributeNS(null,"cy","5.80029008"),p.setAttributeNS(null,"rx",f.rx),p.setAttributeNS(null,"ry",f.ry),c.appendChild(p)}var 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_=r.createNS("http://www.w3.org/2000/svg","circle");_.setAttributeNS(null,"fill","#FFFFFF"),_.setAttributeNS(null,"cx","5.5"),_.setAttributeNS(null,"cy","5.5"),_.setAttributeNS(null,"r","5.4999962"),x.appendChild(b),x.appendChild(_),l.appendChild(c),l.appendChild(d),l.appendChild(m),l.appendChild(y),l.appendChild(x),o.appendChild(l),this._element.appendChild(o),this._offset=t.Point.convert(n&&n.offset||[0,-14])}this._element.classList.add("mapboxgl-marker"),this._element.addEventListener("dragstart",(function(t){t.preventDefault()})),this._element.addEventListener("mousedown",(function(t){t.preventDefault()})),this._element.addEventListener("focus",(function(){var t=i._map.getContainer();t.scrollTop=0,t.scrollLeft=0})),Ia(this._element,this._anchor,"marker"),this._popup=null}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(t){return this.remove(),this._map=t,t.getCanvasContainer().appendChild(this._element),t.on("move",this._update),t.on("moveend",this._update),this.setDraggable(this._draggable),this._update(),this._map.on("click",this._onMapClick),this},n.prototype.remove=function(){return this._map&&(this._map.off("click",this._onMapClick),this._map.off("move",this._update),this._map.off("moveend",this._update),this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler),this._map.off("mouseup",this._onUp),this._map.off("touchend",this._onUp),this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),delete this._map),r.remove(this._element),this._popup&&this._popup.remove(),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this},n.prototype.getElement=function(){return this._element},n.prototype.setPopup=function(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener("keypress",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute("tabindex")),t){if(!("offset"in t.options)){var e=Math.sqrt(Math.pow(13.5,2)/2);t.options.offset=this._defaultMarker?{top:[0,0],"top-left":[0,0],"top-right":[0,0],bottom:[0,-38.1],"bottom-left":[e,-1*(24.6+e)],"bottom-right":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._lngLat&&this._popup.setLngLat(this._lngLat),this._originalTabIndex=this._element.getAttribute("tabindex"),this._originalTabIndex||this._element.setAttribute("tabindex","0"),this._element.addEventListener("keypress",this._onKeyPress)}return this},n.prototype._onKeyPress=function(t){var e=t.code,r=t.charCode||t.keyCode;"Space"!==e&&"Enter"!==e&&32!==r&&13!==r||this.togglePopup()},n.prototype._onMapClick=function(t){var e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},n.prototype.getPopup=function(){return this._popup},n.prototype.togglePopup=function(){var t=this._popup;return t?(t.isOpen()?t.remove():t.addTo(this._map),this):this},n.prototype._update=function(t){if(this._map){this._map.transform.renderWorldCopies&&(this._lngLat=La(this._lngLat,this._pos,this._map.transform)),this._pos=this._map.project(this._lngLat)._add(this._offset);var e="";"viewport"===this._rotationAlignment||"auto"===this._rotationAlignment?e="rotateZ("+this._rotation+"deg)":"map"===this._rotationAlignment&&(e="rotateZ("+(this._rotation-this._map.getBearing())+"deg)");var n="";"viewport"===this._pitchAlignment||"auto"===this._pitchAlignment?n="rotateX(0deg)":"map"===this._pitchAlignment&&(n="rotateX("+this._map.getPitch()+"deg)"),t&&"moveend"!==t.type||(this._pos=this._pos.round()),r.setTransform(this._element,Pa[this._anchor]+" translate("+this._pos.x+"px, "+this._pos.y+"px) "+n+" "+e)}},n.prototype.getOffset=function(){return this._offset},n.prototype.setOffset=function(e){return this._offset=t.Point.convert(e),this._update(),this},n.prototype._onMove=function(e){this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none","pending"===this._state&&(this._state="active",this.fire(new t.Event("dragstart"))),this.fire(new t.Event("drag"))},n.prototype._onUp=function(){this._element.style.pointerEvents="auto",this._positionDelta=null,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),"active"===this._state&&this.fire(new t.Event("dragend")),this._state="inactive"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||"auto",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&"auto"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Da={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},Ra=0,Fa=!1,Ba=function(e){function n(r){e.call(this),this.options=t.extend({},Da,r),t.bindAll(["_onSuccess","_onError","_onZoom","_finish","_setupUI","_updateCamera","_updateMarker"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.onAdd=function(e){var n;return this._map=e,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),n=this._setupUI,void 0!==za?n(za):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:"geolocation"}).then((function(t){n(za="denied"!==t.state)})):n(za=!!t.window.navigator.geolocation),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,Ra=0,Fa=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitude<e.getWest()||r.longitude>e.getEast()||r.latitude<e.getSouth()||r.latitude>e.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event("outofmaxbounds",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background")}this.options.showUserLocation&&"OFF"!==this._watchState&&this._updateMarker(e),this.options.trackUserLocation&&"ACTIVE_LOCK"!==this._watchState||this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("geolocate",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,a=this._map.getBearing(),i=t.extend({bearing:a},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),i,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),a=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=a+"px",this._circleElement.style.height=a+"px"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;var r=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=r,this._geolocateButton.setAttribute("aria-label",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Fa)return;this._setErrorState()}"OFF"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("error",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener("contextmenu",(function(t){return t.preventDefault()})),this._geolocateButton=r.create("button","mapboxgl-ctrl-geolocate",this._container),r.create("span","mapboxgl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden",!0),this._geolocateButton.type="button",!1===e){t.warnOnce("Geolocation support is not available so the GeolocateControl will be disabled.");var a=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=a,this._geolocateButton.setAttribute("aria-label",a)}else{var i=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.title=i,this._geolocateButton.setAttribute("aria-label",i)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=r.create("div","mapboxgl-user-location-dot"),this._userLocationDotMarker=new Oa(this._dotElement),this._circleElement=r.create("div","mapboxgl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Oa({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",(function(e){e.geolocateSource||"ACTIVE_LOCK"!==n._watchState||e.originalEvent&&"resize"===e.originalEvent.type||(n._watchState="BACKGROUND",n._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background"),n._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),n.fire(new t.Event("trackuserlocationend")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new t.Event("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":Ra--,Fa=!1,this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this.fire(new t.Event("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event("trackuserlocationstart"))}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"BACKGROUND":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break;case"BACKGROUND_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error")}if("OFF"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),++Ra>1?(e={maximumAge:6e5,timeout:0},Fa=!0):(e=this.options.positionOptions,Fa=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Na={maxWidth:100,unit:"metric"},ja=function(e){this.options=t.extend({},Na,e),t.bindAll(["_onMove","setUnit"],this)};function Va(t,e,r){var n=r&&r.maxWidth||100,a=t._container.clientHeight/2,i=t.unproject([0,a]),o=t.unproject([n,a]),s=i.distanceTo(o);if(r&&"imperial"===r.unit){var l=3.2808*s;l>5280?Ua(e,n,l/5280,t._getUIString("ScaleControl.Miles")):Ua(e,n,l,t._getUIString("ScaleControl.Feet"))}else r&&"nautical"===r.unit?Ua(e,n,s/1852,t._getUIString("ScaleControl.NauticalMiles")):s>=1e3?Ua(e,n,s/1e3,t._getUIString("ScaleControl.Kilometers")):Ua(e,n,s,t._getUIString("ScaleControl.Meters"))}function Ua(t,e,r,n){var a,i,o,s=(a=r,(i=Math.pow(10,(""+Math.floor(a)).length-1))*(o=(o=a/i)>=10?10:o>=5?5:o>=3?3:o>=2?2:o>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(o)));t.style.width=e*(s/r)+"px",t.innerHTML=s+" "+n}ja.prototype.getDefaultPosition=function(){return"bottom-left"},ja.prototype._onMove=function(){Va(this._map,this._container,this.options)},ja.prototype.onAdd=function(t){return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-scale",t.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container},ja.prototype.onRemove=function(){r.remove(this._container),this._map.off("move",this._onMove),this._map=void 0},ja.prototype.setUnit=function(t){this.options.unit=t,Va(this._map,this._container,this.options)};var qa=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce("Full screen control 'container' must be a DOM element.")),t.bindAll(["_onClickFullscreen","_changeIcon"],this),"onfullscreenchange"in t.window.document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in t.window.document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in t.window.document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in t.window.document&&(this._fullscreenchange="MSFullscreenChange")};qa.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display="none",t.warnOnce("This device does not support fullscreen mode.")),this._controlContainer},qa.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},qa.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},qa.prototype._setupUI=function(){var e=this._fullscreenButton=r.create("button","mapboxgl-ctrl-fullscreen",this._controlContainer);r.create("span","mapboxgl-ctrl-icon",e).setAttribute("aria-hidden",!0),e.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},qa.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute("aria-label",t),this._fullscreenButton.title=t},qa.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")},qa.prototype._isFullscreen=function(){return this._fullscreen},qa.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("mapboxgl-ctrl-shrink"),this._fullscreenButton.classList.toggle("mapboxgl-ctrl-fullscreen"),this._updateTitle())},qa.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Ha={closeButton:!0,closeOnClick:!0,className:"",maxWidth:"240px"},Ga=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Ha),r),t.bindAll(["_update","_onClose","remove","_onMouseMove","_onMouseUp","_onDrag"],this)}return e&&(n.__proto__=e),(n.prototype=Object.create(e&&e.prototype)).constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")):this._map.on("move",this._update),this.fire(new t.Event("open")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),delete this._map),this.fire(new t.Event("close")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.remove("mapboxgl-track-pointer")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),a=t.window.document.createElement("body");for(a.innerHTML=e;r=a.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){return this._createContent(),this._content.appendChild(t),this._update(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createContent=function(){this._content&&r.remove(this._content),this._content=r.create("div","mapboxgl-popup-content",this._container),this.options.closeButton&&(this._closeButton=r.create("button","mapboxgl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.setAttribute("aria-label","Close popup"),this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))},n.prototype._onMouseUp=function(t){this._update(t.point)},n.prototype._onMouseMove=function(t){this._update(t.point)},n.prototype._onDrag=function(t){this._update(t.point)},n.prototype._update=function(e){var n=this;if(this._map&&(this._lngLat||this._trackPointer)&&this._content&&(this._container||(this._container=r.create("div","mapboxgl-popup",this._map.getContainer()),this._tip=r.create("div","mapboxgl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(" ").forEach((function(t){return n._container.classList.add(t)})),this._trackPointer&&this._container.classList.add("mapboxgl-popup-track-pointer")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=La(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||e)){var a=this._pos=this._trackPointer&&e?e:this._map.project(this._lngLat),i=this.options.anchor,o=function e(r){if(r){if("number"==typeof r){var n=Math.round(Math.sqrt(.5*Math.pow(r,2)));return{center:new t.Point(0,0),top:new t.Point(0,r),"top-left":new t.Point(n,n),"top-right":new t.Point(-n,n),bottom:new t.Point(0,-r),"bottom-left":new t.Point(n,-n),"bottom-right":new t.Point(-n,-n),left:new t.Point(r,0),right:new t.Point(-r,0)}}if(r instanceof t.Point||Array.isArray(r)){var a=t.Point.convert(r);return{center:a,top:a,"top-left":a,"top-right":a,bottom:a,"bottom-left":a,"bottom-right":a,left:a,right:a}}return{center:t.Point.convert(r.center||[0,0]),top:t.Point.convert(r.top||[0,0]),"top-left":t.Point.convert(r["top-left"]||[0,0]),"top-right":t.Point.convert(r["top-right"]||[0,0]),bottom:t.Point.convert(r.bottom||[0,0]),"bottom-left":t.Point.convert(r["bottom-left"]||[0,0]),"bottom-right":t.Point.convert(r["bottom-right"]||[0,0]),left:t.Point.convert(r.left||[0,0]),right:t.Point.convert(r.right||[0,0])}}return e(new t.Point(0,0))}(this.options.offset);if(!i){var s,l=this._container.offsetWidth,c=this._container.offsetHeight;s=a.y+o.bottom.y<c?["top"]:a.y>this._map.transform.height-c?["bottom"]:[],a.x<l/2?s.push("left"):a.x>this._map.transform.width-l/2&&s.push("right"),i=0===s.length?"bottom":s.join("-")}var u=a.add(o[i]).round();r.setTransform(this._container,Pa[i]+" translate("+u.x+"px,"+u.y+"px)"),Ia(this._container,i,"popup")}},n.prototype._onClose=function(){this.remove()},n}(t.Evented),Ya={version:t.version,supported:e,setRTLTextPlugin:t.setRTLTextPlugin,getRTLTextPluginStatus:t.getRTLTextPluginStatus,Map:Aa,NavigationControl:Ea,GeolocateControl:Ba,AttributionControl:va,ScaleControl:ja,FullscreenControl:qa,Popup:Ga,Marker:Oa,Style:qe,LngLat:t.LngLat,LngLatBounds:t.LngLatBounds,Point:t.Point,MercatorCoordinate:t.MercatorCoordinate,Evented:t.Evented,config:t.config,prewarm:function(){Bt().acquire(Ot)},clearPrewarmedResources:function(){var t=Rt;t&&(t.isPreloaded()&&1===t.numActive()?(t.release(Ot),Rt=null):console.warn("Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()"))},get accessToken(){return t.config.ACCESS_TOKEN},set accessToken(e){t.config.ACCESS_TOKEN=e},get baseApiUrl(){return t.config.API_URL},set baseApiUrl(e){t.config.API_URL=e},get workerCount(){return Dt.workerCount},set workerCount(t){Dt.workerCount=t},get maxParallelImageRequests(){return t.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(e){t.config.MAX_PARALLEL_IMAGE_REQUESTS=e},clearStorage:function(e){t.clearTileCache(e)},workerUrl:""};return Ya})),r}))},{}],427:[function(t,e,r){"use strict";e.exports=function(t){for(var e=1<<t+1,r=new Array(e),n=0;n<e;++n)r[n]=i(t,n);return r};var n=t("convex-hull");function a(t,e,r){for(var n=new Array(t),a=0;a<t;++a)n[a]=0,a===e&&(n[a]+=.5),a===r&&(n[a]+=.5);return n}function i(t,e){if(0===e||e===(1<<t+1)-1)return[];for(var r=[],i=[],o=0;o<=t;++o)if(e&1<<o){r.push(a(t,o-1,o-1)),i.push(null);for(var s=0;s<=t;++s)~e&1<<s&&(r.push(a(t,o-1,s-1)),i.push([o,s]))}var l=n(r),c=[];t:for(o=0;o<l.length;++o){var u=l[o],h=[];for(s=0;s<u.length;++s){if(!i[u[s]])continue t;h.push(i[u[s]].slice())}c.push(h)}return c}},{"convex-hull":132}],428:[function(t,e,r){var n=t("./normalize"),a=t("gl-mat4/create"),i=t("gl-mat4/clone"),o=t("gl-mat4/determinant"),s=t("gl-mat4/invert"),l=t("gl-mat4/transpose"),c={length:t("gl-vec3/length"),normalize:t("gl-vec3/normalize"),dot:t("gl-vec3/dot"),cross:t("gl-vec3/cross")},u=a(),h=a(),f=[0,0,0,0],p=[[0,0,0],[0,0,0],[0,0,0]],d=[0,0,0];function g(t,e,r,n,a){t[0]=e[0]*n+r[0]*a,t[1]=e[1]*n+r[1]*a,t[2]=e[2]*n+r[2]*a}e.exports=function(t,e,r,a,m,v){if(e||(e=[0,0,0]),r||(r=[0,0,0]),a||(a=[0,0,0]),m||(m=[0,0,0,1]),v||(v=[0,0,0,1]),!n(u,t))return!1;if(i(h,u),h[3]=0,h[7]=0,h[11]=0,h[15]=1,Math.abs(o(h)<1e-8))return!1;var y,x,b,_,w,T,k,A=u[3],M=u[7],S=u[11],E=u[12],C=u[13],L=u[14],P=u[15];if(0!==A||0!==M||0!==S){if(f[0]=A,f[1]=M,f[2]=S,f[3]=P,!s(h,h))return!1;l(h,h),y=m,b=h,_=(x=f)[0],w=x[1],T=x[2],k=x[3],y[0]=b[0]*_+b[4]*w+b[8]*T+b[12]*k,y[1]=b[1]*_+b[5]*w+b[9]*T+b[13]*k,y[2]=b[2]*_+b[6]*w+b[10]*T+b[14]*k,y[3]=b[3]*_+b[7]*w+b[11]*T+b[15]*k}else m[0]=m[1]=m[2]=0,m[3]=1;if(e[0]=E,e[1]=C,e[2]=L,function(t,e){t[0][0]=e[0],t[0][1]=e[1],t[0][2]=e[2],t[1][0]=e[4],t[1][1]=e[5],t[1][2]=e[6],t[2][0]=e[8],t[2][1]=e[9],t[2][2]=e[10]}(p,u),r[0]=c.length(p[0]),c.normalize(p[0],p[0]),a[0]=c.dot(p[0],p[1]),g(p[1],p[1],p[0],1,-a[0]),r[1]=c.length(p[1]),c.normalize(p[1],p[1]),a[0]/=r[1],a[1]=c.dot(p[0],p[2]),g(p[2],p[2],p[0],1,-a[1]),a[2]=c.dot(p[1],p[2]),g(p[2],p[2],p[1],1,-a[2]),r[2]=c.length(p[2]),c.normalize(p[2],p[2]),a[1]/=r[2],a[2]/=r[2],c.cross(d,p[1],p[2]),c.dot(p[0],d)<0)for(var I=0;I<3;I++)r[I]*=-1,p[I][0]*=-1,p[I][1]*=-1,p[I][2]*=-1;return v[0]=.5*Math.sqrt(Math.max(1+p[0][0]-p[1][1]-p[2][2],0)),v[1]=.5*Math.sqrt(Math.max(1-p[0][0]+p[1][1]-p[2][2],0)),v[2]=.5*Math.sqrt(Math.max(1-p[0][0]-p[1][1]+p[2][2],0)),v[3]=.5*Math.sqrt(Math.max(1+p[0][0]+p[1][1]+p[2][2],0)),p[2][1]>p[1][2]&&(v[0]=-v[0]),p[0][2]>p[2][0]&&(v[1]=-v[1]),p[1][0]>p[0][1]&&(v[2]=-v[2]),!0}},{"./normalize":429,"gl-mat4/clone":267,"gl-mat4/create":268,"gl-mat4/determinant":269,"gl-mat4/invert":273,"gl-mat4/transpose":284,"gl-vec3/cross":334,"gl-vec3/dot":339,"gl-vec3/length":349,"gl-vec3/normalize":356}],429:[function(t,e,r){e.exports=function(t,e){var r=e[15];if(0===r)return!1;for(var n=1/r,a=0;a<16;a++)t[a]=e[a]*n;return!0}},{}],430:[function(t,e,r){var n=t("gl-vec3/lerp"),a=t("mat4-recompose"),i=t("mat4-decompose"),o=t("gl-mat4/determinant"),s=t("quat-slerp"),l=h(),c=h(),u=h();function h(){return{translate:f(),scale:f(1),skew:f(),perspective:[0,0,0,1],quaternion:[0,0,0,1]}}function f(t){return[t||0,t||0,t||0]}e.exports=function(t,e,r,h){if(0===o(e)||0===o(r))return!1;var f=i(e,l.translate,l.scale,l.skew,l.perspective,l.quaternion),p=i(r,c.translate,c.scale,c.skew,c.perspective,c.quaternion);return!(!f||!p)&&(n(u.translate,l.translate,c.translate,h),n(u.skew,l.skew,c.skew,h),n(u.scale,l.scale,c.scale,h),n(u.perspective,l.perspective,c.perspective,h),s(u.quaternion,l.quaternion,c.quaternion,h),a(t,u.translate,u.scale,u.skew,u.perspective,u.quaternion),!0)}},{"gl-mat4/determinant":269,"gl-vec3/lerp":350,"mat4-decompose":428,"mat4-recompose":431,"quat-slerp":481}],431:[function(t,e,r){var n={identity:t("gl-mat4/identity"),translate:t("gl-mat4/translate"),multiply:t("gl-mat4/multiply"),create:t("gl-mat4/create"),scale:t("gl-mat4/scale"),fromRotationTranslation:t("gl-mat4/fromRotationTranslation")},a=(n.create(),n.create());e.exports=function(t,e,r,i,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(a),0!==i[2]&&(a[9]=i[2],n.multiply(t,t,a)),0!==i[1]&&(a[9]=0,a[8]=i[1],n.multiply(t,t,a)),0!==i[0]&&(a[8]=0,a[4]=i[0],n.multiply(t,t,a)),n.scale(t,t,r),t}},{"gl-mat4/create":268,"gl-mat4/fromRotationTranslation":271,"gl-mat4/identity":272,"gl-mat4/multiply":275,"gl-mat4/scale":282,"gl-mat4/translate":283}],432:[function(t,e,r){"use strict";e.exports=Math.log2||function(t){return Math.log(t)*Math.LOG2E}},{}],433:[function(t,e,r){"use strict";var n=t("binary-search-bounds"),a=t("mat4-interpolate"),i=t("gl-mat4/invert"),o=t("gl-mat4/rotateX"),s=t("gl-mat4/rotateY"),l=t("gl-mat4/rotateZ"),c=t("gl-mat4/lookAt"),u=t("gl-mat4/translate"),h=(t("gl-mat4/scale"),t("gl-vec3/normalize")),f=[0,0,0];function p(t){this._components=t.slice(),this._time=[0],this.prevMatrix=t.slice(),this.nextMatrix=t.slice(),this.computedMatrix=t.slice(),this.computedInverse=t.slice(),this.computedEye=[0,0,0],this.computedUp=[0,0,0],this.computedCenter=[0,0,0],this.computedRadius=[0],this._limits=[-1/0,1/0]}e.exports=function(t){return new p((t=t||{}).matrix||[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1])};var d=p.prototype;d.recalcMatrix=function(t){var e=this._time,r=n.le(e,t),o=this.computedMatrix;if(!(r<0)){var s=this._components;if(r===e.length-1)for(var l=16*r,c=0;c<16;++c)o[c]=s[l++];else{var u=e[r+1]-e[r],f=(l=16*r,this.prevMatrix),p=!0;for(c=0;c<16;++c)f[c]=s[l++];var d=this.nextMatrix;for(c=0;c<16;++c)d[c]=s[l++],p=p&&f[c]===d[c];if(u<1e-6||p)for(c=0;c<16;++c)o[c]=f[c];else a(o,f,d,(t-e[r])/u)}var g=this.computedUp;g[0]=o[1],g[1]=o[5],g[2]=o[9],h(g,g);var m=this.computedInverse;i(m,o);var v=this.computedEye,y=m[15];v[0]=m[12]/y,v[1]=m[13]/y,v[2]=m[14]/y;var 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/*
* @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc
* @license MIT
* @preserve Project Home: https://github.com/voidqk/polybooljs
*/
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t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=h(e.scale),e.translateFract=h(e.translate),t},viewport:function(t){var e;return Array.isArray(t)?e={x:t[0],y:t[1],width:t[2]-t[0],height:t[3]-t[1]}:t?(e={x:t.x||t.left||0,y:t.y||t.top||0},t.right?e.width=t.right-e.x:e.width=t.w||t.width||0,t.bottom?e.height=t.bottom-e.y:e.height=t.h||t.height||0):e={x:0,y:0,width:v.drawingBufferWidth,height:v.drawingBufferHeight},e}}]),u):u})),e||r){var f=x.reduce((function(t,e,r){return t+(e?e.count:0)}),0),m=new Float64Array(2*f),_=new Uint8Array(4*f),w=new Float32Array(4*f);x.forEach((function(t,e){if(t){var r=t.positions,n=t.count,a=t.offset,i=t.color,o=t.errors;n&&(_.set(i,4*a),w.set(o,4*a),m.set(r,2*a))}})),c(u(m)),p(h(m)),d(_),g(w)}}}function k(){c.destroy(),p.destroy(),d.destroy(),g.destroy(),m.destroy()}};var f=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]]},{"array-bounds":68,"color-normalize":122,"flatten-vertex-data":239,"object-assign":452,"pick-by-alias":463,"to-float32":529,"update-diff":551}],489:[function(t,e,r){"use strict";var n=t("color-normalize"),a=t("array-bounds"),i=t("object-assign"),o=t("glslify"),s=t("pick-by-alias"),l=t("flatten-vertex-data"),c=t("earcut"),u=t("array-normalize"),h=t("to-float32"),f=h.float32,p=h.fract32,d=t("es6-weak-map"),g=t("parse-rect");function m(t,e){if(!(this instanceof m))return new m(t,e);if("function"==typeof t?(e||(e={}),e.regl=t):e=t,e.length&&(e.positions=e),!(t=e.regl).hasExtension("ANGLE_instanced_arrays"))throw Error("regl-error2d: `ANGLE_instanced_arrays` extension should be enabled");this.gl=t._gl,this.regl=t,this.passes=[],this.shaders=m.shaders.has(t)?m.shaders.get(t):m.shaders.set(t,m.createShaders(t)).get(t),this.update(e)}e.exports=m,m.dashMult=2,m.maxPatternLength=256,m.precisionThreshold=3e6,m.maxPoints=1e4,m.maxLines=2048,m.shaders=new d,m.createShaders=function(t){var e,r=t.buffer({usage:"static",type:"float",data:[0,1,0,0,1,1,1,0]}),n={primitive:"triangle strip",instances:t.prop("count"),count:4,offset:0,uniforms:{miterMode:function(t,e){return"round"===e.join?2:1},miterLimit:t.prop("miterLimit"),scale:t.prop("scale"),scaleFract:t.prop("scaleFract"),translateFract:t.prop("translateFract"),translate:t.prop("translate"),thickness:t.prop("thickness"),dashPattern:t.prop("dashTexture"),opacity:t.prop("opacity"),pixelRatio:t.context("pixelRatio"),id:t.prop("id"),dashSize:t.prop("dashLength"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]},depth:t.prop("depth")},blend:{enable:!0,color:[0,0,0,0],equation:{rgb:"add",alpha:"add"},func:{srcRGB:"src alpha",dstRGB:"one minus src alpha",srcAlpha:"one minus dst alpha",dstAlpha:"one"}},depth:{enable:function(t,e){return!e.overlay}},stencil:{enable:!1},scissor:{enable:!0,box:t.prop("viewport")},viewport:t.prop("viewport")},a=t(i({vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 aCoord, bCoord, aCoordFract, bCoordFract;\nattribute vec4 color;\nattribute float lineEnd, lineTop;\n\nuniform vec2 scale, scaleFract, translate, translateFract;\nuniform float thickness, pixelRatio, id, depth;\nuniform vec4 viewport;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\n\nvec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) {\n\t// the order is important\n\treturn position * scale + translate\n + positionFract * scale + translateFract\n + position * scaleFract\n + positionFract * scaleFract;\n}\n\nvoid main() {\n\tfloat lineStart = 1. - lineEnd;\n\tfloat lineOffset = lineTop * 2. - 1.;\n\n\tvec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract);\n\ttangent = normalize(diff * scale * viewport.zw);\n\tvec2 normal = vec2(-tangent.y, tangent.x);\n\n\tvec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart\n\t\t+ project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd\n\n\t\t+ thickness * normal * .5 * lineOffset / viewport.zw;\n\n\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n\n\tfragColor = color / 255.;\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nuniform sampler2D dashPattern;\n\nuniform float dashSize, pixelRatio, thickness, opacity, id;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\n\nvoid main() {\n\tfloat alpha = 1.;\n\n\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\n\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\n\n\tgl_FragColor = fragColor;\n\tgl_FragColor.a *= alpha * opacity * dash;\n}\n"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:16,divisor:1},color:{buffer:t.prop("colorBuffer"),stride:4,offset:0,divisor:1}}},n));try{e=t(i({cull:{enable:!0,face:"back"},vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 aCoord, bCoord, nextCoord, prevCoord;\nattribute vec4 aColor, bColor;\nattribute float lineEnd, lineTop;\n\nuniform vec2 scale, translate;\nuniform float thickness, pixelRatio, id, depth;\nuniform vec4 viewport;\nuniform float miterLimit, miterMode;\n\nvarying vec4 fragColor;\nvarying vec4 startCutoff, endCutoff;\nvarying vec2 tangent;\nvarying vec2 startCoord, endCoord;\nvarying float enableStartMiter, enableEndMiter;\n\nconst float REVERSE_THRESHOLD = -.875;\nconst float MIN_DIFF = 1e-6;\n\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\n// TODO: precalculate dot products, normalize things beforehead etc.\n// TODO: refactor to rectangular algorithm\n\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\n\tvec2 diff = b - a;\n\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n\treturn dot(p - a, perp);\n}\n\nbool isNaN( float val ){\n return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\n}\n\nvoid main() {\n\tvec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord;\n\n vec2 adjustedScale;\n adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x;\n adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y;\n\n vec2 scaleRatio = adjustedScale * viewport.zw;\n\tvec2 normalWidth = thickness / scaleRatio;\n\n\tfloat lineStart = 1. - lineEnd;\n\tfloat lineBot = 1. - lineTop;\n\n\tfragColor = (lineStart * aColor + lineEnd * bColor) / 255.;\n\n\tif (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return;\n\n\tif (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord);\n\tif (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord);\n\n\tvec2 prevDiff = aCoord - prevCoord;\n\tvec2 currDiff = bCoord - aCoord;\n\tvec2 nextDiff = nextCoord - bCoord;\n\n\tvec2 prevTangent = normalize(prevDiff * scaleRatio);\n\tvec2 currTangent = normalize(currDiff * scaleRatio);\n\tvec2 nextTangent = normalize(nextDiff * scaleRatio);\n\n\tvec2 prevNormal = vec2(-prevTangent.y, prevTangent.x);\n\tvec2 currNormal = vec2(-currTangent.y, currTangent.x);\n\tvec2 nextNormal = vec2(-nextTangent.y, nextTangent.x);\n\n\tvec2 startJoinDirection = normalize(prevTangent - currTangent);\n\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\n\n\t// collapsed/unidirectional segment cases\n\t// FIXME: there should be more elegant solution\n\tvec2 prevTanDiff = abs(prevTangent - currTangent);\n\tvec2 nextTanDiff = abs(nextTangent - currTangent);\n\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\n\t\tstartJoinDirection = currNormal;\n\t}\n\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\n\t\tendJoinDirection = currNormal;\n\t}\n\tif (aCoord == bCoord) {\n\t\tendJoinDirection = startJoinDirection;\n\t\tcurrNormal = prevNormal;\n\t\tcurrTangent = prevTangent;\n\t}\n\n\ttangent = currTangent;\n\n\t//calculate join shifts relative to normals\n\tfloat startJoinShift = dot(currNormal, startJoinDirection);\n\tfloat endJoinShift = dot(currNormal, endJoinDirection);\n\n\tfloat startMiterRatio = abs(1. / startJoinShift);\n\tfloat endMiterRatio = abs(1. / endJoinShift);\n\n\tvec2 startJoin = startJoinDirection * startMiterRatio;\n\tvec2 endJoin = endJoinDirection * endMiterRatio;\n\n\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\n\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\n\tstartBotJoin = -startTopJoin;\n\n\tendTopJoin = sign(endJoinShift) * endJoin * .5;\n\tendBotJoin = -endTopJoin;\n\n\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\n\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\n\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\n\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\n\n\t//miter anti-clipping\n\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\n\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\n\n\t//prevent close to reverse direction switch\n\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal);\n\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal);\n\n\tif (prevReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\n\t\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\n\t\t//handle miter clipping\n\t\tbTopCoord -= normalWidth * endTopJoin;\n\t\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\n\t}\n\n\tif (nextReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\n\t\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\n\t\t//handle miter clipping\n\t\taBotCoord -= normalWidth * startBotJoin;\n\t\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\n\t}\n\n\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\n\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\n\n\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\n\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\n\n\t//position is normalized 0..1 coord on the screen\n\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd;\n\n\tstartCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n\tendCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy;\n\n\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n\n\tenableStartMiter = step(dot(currTangent, prevTangent), .5);\n\tenableEndMiter = step(dot(currTangent, nextTangent), .5);\n\n\t//bevel miter cutoffs\n\tif (miterMode == 1.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5;\n\t\t\tstartCutoff = vec4(aCoord, aCoord);\n\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tstartCutoff += viewport.xyxy;\n\t\t\tstartCutoff += startMiterWidth.xyxy;\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5;\n\t\t\tendCutoff = vec4(bCoord, bCoord);\n\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\n\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tendCutoff += viewport.xyxy;\n\t\t\tendCutoff += endMiterWidth.xyxy;\n\t\t}\n\t}\n\n\t//round miter cutoffs\n\telse if (miterMode == 2.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tvec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5;\n\t\t\tstartCutoff = vec4(aCoord, aCoord);\n\t\t\tstartCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio;\n\t\t\tstartCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tstartCutoff += viewport.xyxy;\n\t\t\tstartCutoff += startMiterWidth.xyxy;\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tvec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5;\n\t\t\tendCutoff = vec4(bCoord, bCoord);\n\t\t\tendCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio;\n\t\t\tendCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw;\n\t\t\tendCutoff += viewport.xyxy;\n\t\t\tendCutoff += endMiterWidth.xyxy;\n\t\t}\n\t}\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nuniform sampler2D dashPattern;\nuniform float dashSize, pixelRatio, thickness, opacity, id, miterMode;\n\nvarying vec4 fragColor;\nvarying vec2 tangent;\nvarying vec4 startCutoff, endCutoff;\nvarying vec2 startCoord, endCoord;\nvarying float enableStartMiter, enableEndMiter;\n\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\n\tvec2 diff = b - a;\n\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n\treturn dot(p - a, perp);\n}\n\nvoid main() {\n\tfloat alpha = 1., distToStart, distToEnd;\n\tfloat cutoff = thickness * .5;\n\n\t//bevel miter\n\tif (miterMode == 1.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n\t\t\tif (distToStart < -1.) {\n\t\t\t\tdiscard;\n\t\t\t\treturn;\n\t\t\t}\n\t\t\talpha *= min(max(distToStart + 1., 0.), 1.);\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n\t\t\tif (distToEnd < -1.) {\n\t\t\t\tdiscard;\n\t\t\t\treturn;\n\t\t\t}\n\t\t\talpha *= min(max(distToEnd + 1., 0.), 1.);\n\t\t}\n\t}\n\n\t// round miter\n\telse if (miterMode == 2.) {\n\t\tif (enableStartMiter == 1.) {\n\t\t\tdistToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw);\n\t\t\tif (distToStart < 0.) {\n\t\t\t\tfloat radius = length(gl_FragCoord.xy - startCoord);\n\n\t\t\t\tif(radius > cutoff + .5) {\n\t\t\t\t\tdiscard;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\n\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n\t\t\t}\n\t\t}\n\n\t\tif (enableEndMiter == 1.) {\n\t\t\tdistToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw);\n\t\t\tif (distToEnd < 0.) {\n\t\t\t\tfloat radius = length(gl_FragCoord.xy - endCoord);\n\n\t\t\t\tif(radius > cutoff + .5) {\n\t\t\t\t\tdiscard;\n\t\t\t\t\treturn;\n\t\t\t\t}\n\n\t\t\t\talpha -= smoothstep(cutoff - .5, cutoff + .5, radius);\n\t\t\t}\n\t\t}\n\t}\n\n\tfloat t = fract(dot(tangent, gl_FragCoord.xy) / dashSize) * .5 + .25;\n\tfloat dash = texture2D(dashPattern, vec2(t, .5)).r;\n\n\tgl_FragColor = fragColor;\n\tgl_FragColor.a *= alpha * opacity * dash;\n}\n"]),attributes:{lineEnd:{buffer:r,divisor:0,stride:8,offset:0},lineTop:{buffer:r,divisor:0,stride:8,offset:4},aColor:{buffer:t.prop("colorBuffer"),stride:4,offset:0,divisor:1},bColor:{buffer:t.prop("colorBuffer"),stride:4,offset:4,divisor:1},prevCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:0,divisor:1},aCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:16,divisor:1},nextCoord:{buffer:t.prop("positionBuffer"),stride:8,offset:24,divisor:1}}},n))}catch(t){e=a}return{fill:t({primitive:"triangle",elements:function(t,e){return e.triangles},offset:0,vert:o(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec2 position, positionFract;\n\nuniform vec4 color;\nuniform vec2 scale, scaleFract, translate, translateFract;\nuniform float pixelRatio, id;\nuniform vec4 viewport;\nuniform float opacity;\n\nvarying vec4 fragColor;\n\nconst float MAX_LINES = 256.;\n\nvoid main() {\n\tfloat depth = (MAX_LINES - 4. - id) / (MAX_LINES);\n\n\tvec2 position = position * scale + translate\n + positionFract * scale + translateFract\n + position * scaleFract\n + positionFract * scaleFract;\n\n\tgl_Position = vec4(position * 2.0 - 1.0, depth, 1);\n\n\tfragColor = color / 255.;\n\tfragColor.a *= opacity;\n}\n"]),frag:o(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor;\n\nvoid main() {\n\tgl_FragColor = fragColor;\n}\n"]),uniforms:{scale:t.prop("scale"),color:t.prop("fill"),scaleFract:t.prop("scaleFract"),translateFract:t.prop("translateFract"),translate:t.prop("translate"),opacity:t.prop("opacity"),pixelRatio:t.context("pixelRatio"),id:t.prop("id"),viewport:function(t,e){return[e.viewport.x,e.viewport.y,t.viewportWidth,t.viewportHeight]}},attributes:{position:{buffer:t.prop("positionBuffer"),stride:8,offset:8},positionFract:{buffer:t.prop("positionFractBuffer"),stride:8,offset:8}},blend:n.blend,depth:{enable:!1},scissor:n.scissor,stencil:n.stencil,viewport:n.viewport}),rect:a,miter:e}},m.defaults={dashes:null,join:"miter",miterLimit:1,thickness:10,cap:"square",color:"black",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null},m.prototype.render=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];e.length&&(t=this).update.apply(t,e),this.draw()},m.prototype.draw=function(){for(var t=this,e=[],r=arguments.length;r--;)e[r]=arguments[r];return(e.length?e:this.passes).forEach((function(e,r){var n;if(e&&Array.isArray(e))return(n=t).draw.apply(n,e);"number"==typeof e&&(e=t.passes[e]),e&&e.count>1&&e.opacity&&(t.regl._refresh(),e.fill&&e.triangles&&e.triangles.length>2&&t.shaders.fill(e),e.thickness&&(e.scale[0]*e.viewport.width>m.precisionThreshold||e.scale[1]*e.viewport.height>m.precisionThreshold||"rect"===e.join||!e.join&&(e.thickness<=2||e.count>=m.maxPoints)?t.shaders.rect(e):t.shaders.miter(e)))})),this},m.prototype.update=function(t){var e=this;if(t){null!=t.length?"number"==typeof t[0]&&(t=[{positions:t}]):Array.isArray(t)||(t=[t]);var r=this.regl,o=this.gl;if(t.forEach((function(t,h){var d=e.passes[h];if(void 0!==t)if(null!==t){if("number"==typeof t[0]&&(t={positions:t}),t=s(t,{positions:"positions points data coords",thickness:"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth",join:"lineJoin linejoin join type mode",miterLimit:"miterlimit miterLimit",dashes:"dash dashes dasharray dash-array dashArray",color:"color colour stroke colors colours stroke-color strokeColor",fill:"fill fill-color fillColor",opacity:"alpha opacity",overlay:"overlay crease overlap intersect",close:"closed close closed-path closePath",range:"range dataBox",viewport:"viewport viewBox",hole:"holes hole hollow"}),d||(e.passes[h]=d={id:h,scale:null,scaleFract:null,translate:null,translateFract:null,count:0,hole:[],depth:0,dashLength:1,dashTexture:r.texture({channels:1,data:new Uint8Array([255]),width:1,height:1,mag:"linear",min:"linear"}),colorBuffer:r.buffer({usage:"dynamic",type:"uint8",data:new Uint8Array}),positionBuffer:r.buffer({usage:"dynamic",type:"float",data:new Uint8Array}),positionFractBuffer:r.buffer({usage:"dynamic",type:"float",data:new Uint8Array})},t=i({},m.defaults,t)),null!=t.thickness&&(d.thickness=parseFloat(t.thickness)),null!=t.opacity&&(d.opacity=parseFloat(t.opacity)),null!=t.miterLimit&&(d.miterLimit=parseFloat(t.miterLimit)),null!=t.overlay&&(d.overlay=!!t.overlay,h<m.maxLines&&(d.depth=2*(m.maxLines-1-h%m.maxLines)/m.maxLines-1)),null!=t.join&&(d.join=t.join),null!=t.hole&&(d.hole=t.hole),null!=t.fill&&(d.fill=t.fill?n(t.fill,"uint8"):null),null!=t.viewport&&(d.viewport=g(t.viewport)),d.viewport||(d.viewport=g([o.drawingBufferWidth,o.drawingBufferHeight])),null!=t.close&&(d.close=t.close),null===t.positions&&(t.positions=[]),t.positions){var v,y;if(t.positions.x&&t.positions.y){var x=t.positions.x,b=t.positions.y;y=d.count=Math.max(x.length,b.length),v=new Float64Array(2*y);for(var _=0;_<y;_++)v[2*_]=x[_],v[2*_+1]=b[_]}else v=l(t.positions,"float64"),y=d.count=Math.floor(v.length/2);var w=d.bounds=a(v,2);if(d.fill){for(var T=[],k={},A=0,M=0,S=0,E=d.count;M<E;M++){var C=v[2*M],L=v[2*M+1];isNaN(C)||isNaN(L)||null==C||null==L?(C=v[2*A],L=v[2*A+1],k[M]=A):A=M,T[S++]=C,T[S++]=L}for(var P=c(T,d.hole||[]),I=0,z=P.length;I<z;I++)null!=k[P[I]]&&(P[I]=k[P[I]]);d.triangles=P}var O=new Float64Array(v);u(O,2,w);var D=new Float64Array(2*y+6);d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[0]=O[2*y-4],D[1]=O[2*y-3]):(D[0]=O[2*y-2],D[1]=O[2*y-1]):(D[0]=O[0],D[1]=O[1]),D.set(O,2),d.close?v[0]===v[2*y-2]&&v[1]===v[2*y-1]?(D[2*y+2]=O[2],D[2*y+3]=O[3],d.count-=1):(D[2*y+2]=O[0],D[2*y+3]=O[1],D[2*y+4]=O[2],D[2*y+5]=O[3]):(D[2*y+2]=O[2*y-2],D[2*y+3]=O[2*y-1],D[2*y+4]=O[2*y-2],D[2*y+5]=O[2*y-1]),d.positionBuffer(f(D)),d.positionFractBuffer(p(D))}if(t.range?d.range=t.range:d.range||(d.range=d.bounds),(t.range||t.positions)&&d.count){var R=d.bounds,F=R[2]-R[0],B=R[3]-R[1],N=d.range[2]-d.range[0],j=d.range[3]-d.range[1];d.scale=[F/N,B/j],d.translate=[-d.range[0]/N+R[0]/N||0,-d.range[1]/j+R[1]/j||0],d.scaleFract=p(d.scale),d.translateFract=p(d.translate)}if(t.dashes){var V,U=0;if(!t.dashes||t.dashes.length<2)U=1,V=new Uint8Array([255,255,255,255,255,255,255,255]);else{U=0;for(var q=0;q<t.dashes.length;++q)U+=t.dashes[q];V=new Uint8Array(U*m.dashMult);for(var H=0,G=255,Y=0;Y<2;Y++)for(var W=0;W<t.dashes.length;++W){for(var Z=0,X=t.dashes[W]*m.dashMult*.5;Z<X;++Z)V[H++]=G;G^=255}}d.dashLength=U,d.dashTexture({channels:1,data:V,width:V.length,height:1,mag:"linear",min:"linear"},0,0)}if(t.color){var J=d.count,K=t.color;K||(K="transparent");var Q=new Uint8Array(4*J+4);if(Array.isArray(K)&&"number"!=typeof K[0]){for(var $=0;$<J;$++){var tt=n(K[$],"uint8");Q.set(tt,4*$)}Q.set(n(K[0],"uint8"),4*J)}else for(var et=n(K,"uint8"),rt=0;rt<J+1;rt++)Q.set(et,4*rt);d.colorBuffer({usage:"dynamic",type:"uint8",data:Q})}}else e.passes[h]=null})),t.length<this.passes.length){for(var h=t.length;h<this.passes.length;h++){var d=this.passes[h];d&&(d.colorBuffer.destroy(),d.positionBuffer.destroy(),d.dashTexture.destroy())}this.passes.length=t.length}for(var v=[],y=0;y<this.passes.length;y++)null!==this.passes[y]&&v.push(this.passes[y]);return this.passes=v,this}},m.prototype.destroy=function(){return this.passes.forEach((function(t){t.colorBuffer.destroy(),t.positionBuffer.destroy(),t.dashTexture.destroy()})),this.passes.length=0,this}},{"array-bounds":68,"array-normalize":69,"color-normalize":122,earcut:172,"es6-weak-map":228,"flatten-vertex-data":239,glslify:408,"object-assign":452,"parse-rect":457,"pick-by-alias":463,"to-float32":529}],490:[function(t,e,r){"use strict";function n(t,e){return function(t){if(Array.isArray(t))return t}(t)||function(t,e){if("undefined"==typeof Symbol||!(Symbol.iterator in Object(t)))return;var r=[],n=!0,a=!1,i=void 0;try{for(var o,s=t[Symbol.iterator]();!(n=(o=s.next()).done)&&(r.push(o.value),!e||r.length!==e);n=!0);}catch(t){a=!0,i=t}finally{try{n||null==s.return||s.return()}finally{if(a)throw i}}return r}(t,e)||i(t,e)||function(){throw new TypeError("Invalid attempt to destructure non-iterable 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s=t("color-normalize"),l=t("array-bounds"),c=t("color-id"),u=t("point-cluster"),h=t("object-assign"),f=t("glslify"),p=t("pick-by-alias"),d=t("update-diff"),g=t("flatten-vertex-data"),m=t("is-iexplorer"),v=t("to-float32"),y=t("parse-rect"),x=b;function b(t,e){var r=this;if(!(this instanceof b))return new b(t,e);"function"==typeof t?(e||(e={}),e.regl=t):(e=t,t=null),e&&e.length&&(e.positions=e);var n,a=(t=e.regl)._gl,i=[];this.tooManyColors=m,n=t.texture({data:new Uint8Array(1020),width:255,height:1,type:"uint8",format:"rgba",wrapS:"clamp",wrapT:"clamp",mag:"nearest",min:"nearest"}),h(this,{regl:t,gl:a,groups:[],markerCache:[null],markerTextures:[null],palette:i,paletteIds:{},paletteTexture:n,maxColors:255,maxSize:100,canvas:a.canvas}),this.update(e);var o={uniforms:{pixelRatio:t.context("pixelRatio"),palette:n,paletteSize:function(t,e){return[r.tooManyColors?0:255,n.height]},scale:t.prop("scale"),scaleFract:t.prop("scaleFract"),translate:t.prop("translate"),translateFract:t.prop("translateFract"),opacity:t.prop("opacity"),marker:t.prop("markerTexture")},attributes:{x:function(t,e){return e.xAttr||{buffer:e.positionBuffer,stride:8,offset:0}},y:function(t,e){return e.yAttr||{buffer:e.positionBuffer,stride:8,offset:4}},xFract:function(t,e){return e.xAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:0}},yFract:function(t,e){return e.yAttr?{constant:[0,0]}:{buffer:e.positionFractBuffer,stride:8,offset:4}},size:function(t,e){return e.size.length?{buffer:e.sizeBuffer,stride:2,offset:0}:{constant:[Math.round(255*e.size/r.maxSize)]}},borderSize:function(t,e){return e.borderSize.length?{buffer:e.sizeBuffer,stride:2,offset:1}:{constant:[Math.round(255*e.borderSize/r.maxSize)]}},colorId:function(t,e){return e.color.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:0}:{constant:r.tooManyColors?i.slice(4*e.color,4*e.color+4):[e.color]}},borderColorId:function(t,e){return e.borderColor.length?{buffer:e.colorBuffer,stride:r.tooManyColors?8:4,offset:r.tooManyColors?4:2}:{constant:r.tooManyColors?i.slice(4*e.borderColor,4*e.borderColor+4):[e.borderColor]}},isActive:function(t,e){return!0===e.activation?{constant:[1]}:e.activation?e.activation:{constant:[0]}}},blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:"src alpha",dstRGB:"one minus src alpha",srcAlpha:"one minus dst alpha",dstAlpha:"one"}},scissor:{enable:!0,box:t.prop("viewport")},viewport:t.prop("viewport"),stencil:{enable:!1},depth:{enable:!1},elements:t.prop("elements"),count:t.prop("count"),offset:t.prop("offset"),primitive:"points"},s=h({},o);s.frag=f(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor, fragBorderColor;\nvarying float fragWidth, fragBorderColorLevel, fragColorLevel;\n\nuniform sampler2D marker;\nuniform float pixelRatio, opacity;\n\nfloat smoothStep(float x, float y) {\n return 1.0 / (1.0 + exp(50.0*(x - y)));\n}\n\nvoid main() {\n float dist = texture2D(marker, gl_PointCoord).r, delta = fragWidth;\n\n // max-distance alpha\n if (dist < 0.003) discard;\n\n // null-border case\n if (fragBorderColorLevel == fragColorLevel || fragBorderColor.a == 0.) {\n float colorAmt = smoothstep(.5 - delta, .5 + delta, dist);\n gl_FragColor = vec4(fragColor.rgb, colorAmt * fragColor.a * opacity);\n }\n else {\n float borderColorAmt = smoothstep(fragBorderColorLevel - delta, fragBorderColorLevel + delta, dist);\n float colorAmt = smoothstep(fragColorLevel - delta, fragColorLevel + delta, dist);\n\n vec4 color = fragBorderColor;\n color.a *= borderColorAmt;\n color = mix(color, fragColor, colorAmt);\n color.a *= opacity;\n\n gl_FragColor = color;\n }\n\n}\n"]),s.vert=f(["precision highp float;\n#define GLSLIFY 1\n\nattribute float x, y, xFract, yFract;\nattribute float size, borderSize;\nattribute vec4 colorId, borderColorId;\nattribute float isActive;\n\nuniform vec2 scale, scaleFract, translate, translateFract, paletteSize;\nuniform float pixelRatio;\nuniform sampler2D palette;\n\nconst float maxSize = 100.;\nconst float borderLevel = .5;\n\nvarying vec4 fragColor, fragBorderColor;\nvarying float fragPointSize, fragBorderRadius, fragWidth, fragBorderColorLevel, fragColorLevel;\n\nbool isDirect = (paletteSize.x < 1.);\n\nvec4 getColor(vec4 id) {\n return isDirect ? id / 255. : texture2D(palette,\n vec2(\n (id.x + .5) / paletteSize.x,\n (id.y + .5) / paletteSize.y\n )\n );\n}\n\nvoid main() {\n if (isActive == 0.) return;\n\n vec2 position = vec2(x, y);\n vec2 positionFract = vec2(xFract, yFract);\n\n vec4 color = getColor(colorId);\n vec4 borderColor = getColor(borderColorId);\n\n float size = size * maxSize / 255.;\n float borderSize = borderSize * maxSize / 255.;\n\n gl_PointSize = 2. * size * pixelRatio;\n fragPointSize = size * pixelRatio;\n\n vec2 pos = (position + translate) * scale\n + (positionFract + translateFract) * scale\n + (position + translate) * scaleFract\n + (positionFract + translateFract) * scaleFract;\n\n gl_Position = vec4(pos * 2. - 1., 0, 1);\n\n fragColor = color;\n fragBorderColor = borderColor;\n fragWidth = 1. / gl_PointSize;\n\n fragBorderColorLevel = clamp(borderLevel - borderLevel * borderSize / size, 0., 1.);\n fragColorLevel = clamp(borderLevel + (1. - borderLevel) * borderSize / size, 0., 1.);\n}"]),this.drawMarker=t(s);var l=h({},o);l.frag=f(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor, fragBorderColor;\n\nuniform float opacity;\nvarying float fragBorderRadius, fragWidth;\n\nfloat smoothStep(float edge0, float edge1, float x) {\n\tfloat t;\n\tt = clamp((x - edge0) / (edge1 - edge0), 0.0, 1.0);\n\treturn t * t * (3.0 - 2.0 * t);\n}\n\nvoid main() {\n\tfloat radius, alpha = 1.0, delta = fragWidth;\n\n\tradius = length(2.0 * gl_PointCoord.xy - 1.0);\n\n\tif (radius > 1.0 + delta) {\n\t\tdiscard;\n\t}\n\n\talpha -= smoothstep(1.0 - delta, 1.0 + delta, radius);\n\n\tfloat borderRadius = fragBorderRadius;\n\tfloat ratio = smoothstep(borderRadius - delta, borderRadius + delta, radius);\n\tvec4 color = mix(fragColor, fragBorderColor, ratio);\n\tcolor.a *= alpha * opacity;\n\tgl_FragColor = color;\n}\n"]),l.vert=f(["precision highp float;\n#define GLSLIFY 1\n\nattribute float x, y, xFract, yFract;\nattribute float size, borderSize;\nattribute vec4 colorId, borderColorId;\nattribute float isActive;\n\nuniform vec2 scale, scaleFract, translate, translateFract;\nuniform float pixelRatio;\nuniform sampler2D palette;\nuniform vec2 paletteSize;\n\nconst float maxSize = 100.;\n\nvarying vec4 fragColor, fragBorderColor;\nvarying float fragBorderRadius, fragWidth;\n\nbool isDirect = (paletteSize.x < 1.);\n\nvec4 getColor(vec4 id) {\n return isDirect ? id / 255. : texture2D(palette,\n vec2(\n (id.x + .5) / paletteSize.x,\n (id.y + .5) / paletteSize.y\n )\n );\n}\n\nvoid main() {\n // ignore inactive points\n if (isActive == 0.) return;\n\n vec2 position = vec2(x, y);\n vec2 positionFract = vec2(xFract, yFract);\n\n vec4 color = getColor(colorId);\n vec4 borderColor = getColor(borderColorId);\n\n float size = size * maxSize / 255.;\n float borderSize = borderSize * maxSize / 255.;\n\n gl_PointSize = (size + borderSize) * pixelRatio;\n\n vec2 pos = (position + translate) * scale\n + (positionFract + translateFract) * scale\n + (position + translate) * scaleFract\n + (positionFract + translateFract) * scaleFract;\n\n gl_Position = vec4(pos * 2. - 1., 0, 1);\n\n fragBorderRadius = 1. - 2. * borderSize / (size + borderSize);\n fragColor = color;\n fragBorderColor = borderColor.a == 0. || borderSize == 0. ? vec4(color.rgb, 0.) : borderColor;\n fragWidth = 1. / gl_PointSize;\n}\n"]),m&&(l.frag=l.frag.replace("smoothstep","smoothStep"),s.frag=s.frag.replace("smoothstep","smoothStep")),this.drawCircle=t(l)}b.defaults={color:"black",borderColor:"transparent",borderSize:0,size:12,opacity:1,marker:void 0,viewport:null,range:null,pixelSize:null,count:0,offset:0,bounds:null,positions:[],snap:1e4},b.prototype.render=function(){return arguments.length&&this.update.apply(this,arguments),this.draw(),this},b.prototype.draw=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];var a=this.groups;if(1===r.length&&Array.isArray(r[0])&&(null===r[0][0]||Array.isArray(r[0][0]))&&(r=r[0]),this.regl._refresh(),r.length)for(var i=0;i<r.length;i++)this.drawItem(i,r[i]);else a.forEach((function(e,r){t.drawItem(r)}));return this},b.prototype.drawItem=function(t,e){var r=this.groups,n=r[t];if("number"==typeof e&&(t=e,n=r[e],e=null),n&&n.count&&n.opacity){n.activation[0]&&this.drawCircle(this.getMarkerDrawOptions(0,n,e));for(var i=[],o=1;o<n.activation.length;o++)n.activation[o]&&(!0===n.activation[o]||n.activation[o].data.length)&&i.push.apply(i,a(this.getMarkerDrawOptions(o,n,e)));i.length&&this.drawMarker(i)}},b.prototype.getMarkerDrawOptions=function(t,e,r){var a=e.range,i=e.tree,o=e.viewport,s=e.activation,l=e.selectionBuffer,c=e.count;this.regl;if(!i)return r?[h({},e,{markerTexture:this.markerTextures[t],activation:s[t],count:r.length,elements:r,offset:0})]:[h({},e,{markerTexture:this.markerTextures[t],activation:s[t],offset:0})];var u=[],f=i.range(a,{lod:!0,px:[(a[2]-a[0])/o.width,(a[3]-a[1])/o.height]});if(r){for(var p=s[t].data,d=new Uint8Array(c),g=0;g<r.length;g++){var m=r[g];d[m]=p?p[m]:1}l.subdata(d)}for(var v=f.length;v--;){var y=n(f[v],2),x=y[0],b=y[1];u.push(h({},e,{markerTexture:this.markerTextures[t],activation:r?l:s[t],offset:x,count:b-x}))}return u},b.prototype.update=function(){for(var t=this,e=arguments.length,r=new Array(e),n=0;n<e;n++)r[n]=arguments[n];if(r.length){1===r.length&&Array.isArray(r[0])&&(r=r[0]);var a=this.groups,i=this.gl,o=this.regl,s=this.maxSize,c=this.maxColors,f=this.palette;this.groups=a=r.map((function(e,r){var n=a[r];if(void 0===e)return n;null===e?e={positions:null}:"function"==typeof e?e={ondraw:e}:"number"==typeof e[0]&&(e={positions:e}),null===(e=p(e,{positions:"positions data points",snap:"snap cluster lod tree",size:"sizes size radius",borderSize:"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline",color:"colors color fill fill-color fillColor",borderColor:"borderColors borderColor stroke stroke-color strokeColor",marker:"markers marker shape",range:"range dataBox databox",viewport:"viewport viewPort viewBox viewbox",opacity:"opacity alpha transparency",bounds:"bound bounds boundaries limits",tooManyColors:"tooManyColors palette paletteMode optimizePalette enablePalette"})).positions&&(e.positions=[]),null!=e.tooManyColors&&(t.tooManyColors=e.tooManyColors),n||(a[r]=n={id:r,scale:null,translate:null,scaleFract:null,translateFract:null,activation:[],selectionBuffer:o.buffer({data:new Uint8Array(0),usage:"stream",type:"uint8"}),sizeBuffer:o.buffer({data:new Uint8Array(0),usage:"dynamic",type:"uint8"}),colorBuffer:o.buffer({data:new Uint8Array(0),usage:"dynamic",type:"uint8"}),positionBuffer:o.buffer({data:new Uint8Array(0),usage:"dynamic",type:"float"}),positionFractBuffer:o.buffer({data:new Uint8Array(0),usage:"dynamic",type:"float"})},e=h({},b.defaults,e)),e.positions&&!("marker"in e)&&(e.marker=n.marker,delete n.marker),e.marker&&!("positions"in e)&&(e.positions=n.positions,delete n.positions);var m=0,x=0;if(d(n,e,[{snap:!0,size:function(t,e){return null==t&&(t=b.defaults.size),m+=t&&t.length?1:0,t},borderSize:function(t,e){return null==t&&(t=b.defaults.borderSize),m+=t&&t.length?1:0,t},opacity:parseFloat,color:function(e,r){return null==e&&(e=b.defaults.color),e=t.updateColor(e),x++,e},borderColor:function(e,r){return null==e&&(e=b.defaults.borderColor),e=t.updateColor(e),x++,e},bounds:function(t,e,r){return"range"in r||(r.range=null),t},positions:function(t,e,r){var n=e.snap,a=e.positionBuffer,i=e.positionFractBuffer,s=e.selectionBuffer;if(t.x||t.y)return t.x.length?e.xAttr={buffer:o.buffer(t.x),offset:0,stride:4,count:t.x.length}:e.xAttr={buffer:t.x.buffer,offset:4*t.x.offset||0,stride:4*(t.x.stride||1),count:t.x.count},t.y.length?e.yAttr={buffer:o.buffer(t.y),offset:0,stride:4,count:t.y.length}:e.yAttr={buffer:t.y.buffer,offset:4*t.y.offset||0,stride:4*(t.y.stride||1),count:t.y.count},e.count=Math.max(e.xAttr.count,e.yAttr.count),t;t=g(t,"float64");var c=e.count=Math.floor(t.length/2),h=e.bounds=c?l(t,2):null;if(r.range||e.range||(delete e.range,r.range=h),r.marker||e.marker||(delete e.marker,r.marker=null),n&&(!0===n||c>n)?e.tree=u(t,{bounds:h}):n&&n.length&&(e.tree=n),e.tree){var f={primitive:"points",usage:"static",data:e.tree,type:"uint32"};e.elements?e.elements(f):e.elements=o.elements(f)}return a({data:v.float(t),usage:"dynamic"}),i({data:v.fract(t),usage:"dynamic"}),s({data:new Uint8Array(c),type:"uint8",usage:"stream"}),t}},{marker:function(e,r,n){var a=r.activation;if(a.forEach((function(t){return t&&t.destroy&&t.destroy()})),a.length=0,e&&"number"!=typeof e[0]){for(var i=[],s=0,l=Math.min(e.length,r.count);s<l;s++){var c=t.addMarker(e[s]);i[c]||(i[c]=new Uint8Array(r.count)),i[c][s]=1}for(var u=0;u<i.length;u++)if(i[u]){var h={data:i[u],type:"uint8",usage:"static"};a[u]?a[u](h):a[u]=o.buffer(h),a[u].data=i[u]}}else{a[t.addMarker(e)]=!0}return e},range:function(t,e,r){var n=e.bounds;if(n)return t||(t=n),e.scale=[1/(t[2]-t[0]),1/(t[3]-t[1])],e.translate=[-t[0],-t[1]],e.scaleFract=v.fract(e.scale),e.translateFract=v.fract(e.translate),t},viewport:function(t){return y(t||[i.drawingBufferWidth,i.drawingBufferHeight])}}]),m){var _=n,w=_.count,T=_.size,k=_.borderSize,A=_.sizeBuffer,M=new Uint8Array(2*w);if(T.length||k.length)for(var S=0;S<w;S++)M[2*S]=Math.round(255*(null==T[S]?T:T[S])/s),M[2*S+1]=Math.round(255*(null==k[S]?k:k[S])/s);A({data:M,usage:"dynamic"})}if(x){var E,C=n,L=C.count,P=C.color,I=C.borderColor,z=C.colorBuffer;if(t.tooManyColors){if(P.length||I.length){E=new Uint8Array(8*L);for(var O=0;O<L;O++){var D=P[O];E[8*O]=f[4*D],E[8*O+1]=f[4*D+1],E[8*O+2]=f[4*D+2],E[8*O+3]=f[4*D+3];var R=I[O];E[8*O+4]=f[4*R],E[8*O+5]=f[4*R+1],E[8*O+6]=f[4*R+2],E[8*O+7]=f[4*R+3]}}}else if(P.length||I.length){E=new Uint8Array(4*L+2);for(var F=0;F<L;F++)null!=P[F]&&(E[4*F]=P[F]%c,E[4*F+1]=Math.floor(P[F]/c)),null!=I[F]&&(E[4*F+2]=I[F]%c,E[4*F+3]=Math.floor(I[F]/c))}z({data:E||new Uint8Array(0),type:"uint8",usage:"dynamic"})}return n}))}},b.prototype.addMarker=function(t){var e,r=this.markerTextures,n=this.regl,a=this.markerCache,i=null==t?0:a.indexOf(t);if(i>=0)return i;if(t instanceof Uint8Array||t instanceof Uint8ClampedArray)e=t;else{e=new Uint8Array(t.length);for(var o=0,s=t.length;o<s;o++)e[o]=255*t[o]}var l=Math.floor(Math.sqrt(e.length));return i=r.length,a.push(t),r.push(n.texture({channels:1,data:e,radius:l,mag:"linear",min:"linear"})),i},b.prototype.updateColor=function(t){var e=this.paletteIds,r=this.palette,n=this.maxColors;Array.isArray(t)||(t=[t]);var a=[];if("number"==typeof t[0]){var i=[];if(Array.isArray(t))for(var o=0;o<t.length;o+=4)i.push(t.slice(o,o+4));else for(var l=0;l<t.length;l+=4)i.push(t.subarray(l,l+4));t=i}for(var u=0;u<t.length;u++){var h=t[u];h=s(h,"uint8");var f=c(h,!1);if(null==e[f]){var p=r.length;e[f]=Math.floor(p/4),r[p]=h[0],r[p+1]=h[1],r[p+2]=h[2],r[p+3]=h[3]}a[u]=e[f]}return!this.tooManyColors&&r.length>4*n&&(this.tooManyColors=!0),this.updatePalette(r),1===a.length?a[0]:a},b.prototype.updatePalette=function(t){if(!this.tooManyColors){var e=this.maxColors,r=this.paletteTexture,n=Math.ceil(.25*t.length/e);if(n>1)for(var a=.25*(t=t.slice()).length%e;a<n*e;a++)t.push(0,0,0,0);r.height<n&&r.resize(e,n),r.subimage({width:Math.min(.25*t.length,e),height:n,data:t},0,0)}},b.prototype.destroy=function(){return this.groups.forEach((function(t){t.sizeBuffer.destroy(),t.positionBuffer.destroy(),t.positionFractBuffer.destroy(),t.colorBuffer.destroy(),t.activation.forEach((function(t){return t&&t.destroy&&t.destroy()})),t.selectionBuffer.destroy(),t.elements&&t.elements.destroy()})),this.groups.length=0,this.paletteTexture.destroy(),this.markerTextures.forEach((function(t){return t&&t.destroy&&t.destroy()})),this};var _=t("object-assign");e.exports=function(t,e){var r=new x(t,e),n=r.render.bind(r);return _(n,{render:n,update:r.update.bind(r),draw:r.draw.bind(r),destroy:r.destroy.bind(r),regl:r.regl,gl:r.gl,canvas:r.gl.canvas,groups:r.groups,markers:r.markerCache,palette:r.palette}),n}},{"array-bounds":68,"color-id":120,"color-normalize":122,"flatten-vertex-data":239,glslify:408,"is-iexplorer":419,"object-assign":452,"parse-rect":457,"pick-by-alias":463,"point-cluster":467,"to-float32":529,"update-diff":551}],491:[function(t,e,r){"use strict";var n=t("regl-scatter2d"),a=t("pick-by-alias"),i=t("array-bounds"),o=t("raf"),s=t("array-range"),l=t("parse-rect"),c=t("flatten-vertex-data");function u(t,e){if(!(this instanceof u))return new u(t,e);this.traces=[],this.passes={},this.regl=t,this.scatter=n(t),this.canvas=this.scatter.canvas}function h(t,e,r){return(null!=t.id?t.id:t)<<16|(255&e)<<8|255&r}function f(t,e,r){var n,a,i,o,s=t[e],l=t[r];return s.length>2?(s[0],s[2],n=s[1],a=s[3]):s.length?(n=s[0],a=s[1]):(s.x,n=s.y,s.x+s.width,a=s.y+s.height),l.length>2?(i=l[0],o=l[2],l[1],l[3]):l.length?(i=l[0],o=l[1]):(i=l.x,l.y,o=l.x+l.width,l.y+l.height),[i,n,o,a]}function p(t){if("number"==typeof t)return[t,t,t,t];if(2===t.length)return[t[0],t[1],t[0],t[1]];var e=l(t);return[e.x,e.y,e.x+e.width,e.y+e.height]}e.exports=u,u.prototype.render=function(){for(var t,e=this,r=[],n=arguments.length;n--;)r[n]=arguments[n];return r.length&&(t=this).update.apply(t,r),this.regl.attributes.preserveDrawingBuffer?this.draw():(this.dirty?null==this.planned&&(this.planned=o((function(){e.draw(),e.dirty=!0,e.planned=null}))):(this.draw(),this.dirty=!0,o((function(){e.dirty=!1}))),this)},u.prototype.update=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=0;n<e.length;n++)this.updateItem(n,e[n]);this.traces=this.traces.filter(Boolean);for(var a=[],i=0,o=0;o<this.traces.length;o++){for(var s=this.traces[o],l=this.traces[o].passes,c=0;c<l.length;c++)a.push(this.passes[l[c]]);s.passOffset=i,i+=s.passes.length}return(t=this.scatter).update.apply(t,a),this}},u.prototype.updateItem=function(t,e){var r=this.regl;if(null===e)return this.traces[t]=null,this;if(!e)return this;var n,o=a(e,{data:"data items columns rows values dimensions samples x",snap:"snap cluster",size:"sizes size radius",color:"colors color fill fill-color fillColor",opacity:"opacity alpha transparency opaque",borderSize:"borderSizes borderSize border-size bordersize borderWidth borderWidths border-width borderwidth stroke-width strokeWidth strokewidth outline",borderColor:"borderColors borderColor bordercolor stroke stroke-color strokeColor",marker:"markers marker shape",range:"range ranges databox dataBox",viewport:"viewport viewBox viewbox",domain:"domain domains area areas",padding:"pad padding paddings pads margin margins",transpose:"transpose transposed",diagonal:"diagonal diag showDiagonal",upper:"upper up top upperhalf upperHalf showupperhalf showUpper showUpperHalf",lower:"lower low bottom lowerhalf lowerHalf showlowerhalf showLowerHalf showLower"}),s=this.traces[t]||(this.traces[t]={id:t,buffer:r.buffer({usage:"dynamic",type:"float",data:new Uint8Array}),color:"black",marker:null,size:12,borderColor:"transparent",borderSize:1,viewport:l([r._gl.drawingBufferWidth,r._gl.drawingBufferHeight]),padding:[0,0,0,0],opacity:1,diagonal:!0,upper:!0,lower:!0});if(null!=o.color&&(s.color=o.color),null!=o.size&&(s.size=o.size),null!=o.marker&&(s.marker=o.marker),null!=o.borderColor&&(s.borderColor=o.borderColor),null!=o.borderSize&&(s.borderSize=o.borderSize),null!=o.opacity&&(s.opacity=o.opacity),o.viewport&&(s.viewport=l(o.viewport)),null!=o.diagonal&&(s.diagonal=o.diagonal),null!=o.upper&&(s.upper=o.upper),null!=o.lower&&(s.lower=o.lower),o.data){s.buffer(c(o.data)),s.columns=o.data.length,s.count=o.data[0].length,s.bounds=[];for(var u=0;u<s.columns;u++)s.bounds[u]=i(o.data[u],1)}o.range&&(s.range=o.range,n=s.range&&"number"!=typeof s.range[0]),o.domain&&(s.domain=o.domain);var d=!1;null!=o.padding&&(Array.isArray(o.padding)&&o.padding.length===s.columns&&"number"==typeof o.padding[o.padding.length-1]?(s.padding=o.padding.map(p),d=!0):s.padding=p(o.padding));var g=s.columns,m=s.count,v=s.viewport.width,y=s.viewport.height,x=s.viewport.x,b=s.viewport.y,_=v/g,w=y/g;s.passes=[];for(var T=0;T<g;T++)for(var k=0;k<g;k++)if((s.diagonal||k!==T)&&(s.upper||!(T>k))&&(s.lower||!(T<k))){var A=h(s.id,T,k),M=this.passes[A]||(this.passes[A]={});if(o.data&&(o.transpose?M.positions={x:{buffer:s.buffer,offset:k,count:m,stride:g},y:{buffer:s.buffer,offset:T,count:m,stride:g}}:M.positions={x:{buffer:s.buffer,offset:k*m,count:m},y:{buffer:s.buffer,offset:T*m,count:m}},M.bounds=f(s.bounds,T,k)),o.domain||o.viewport||o.data){var S=d?f(s.padding,T,k):s.padding;if(s.domain){var E=f(s.domain,T,k),C=E[0],L=E[1],P=E[2],I=E[3];M.viewport=[x+C*v+S[0],b+L*y+S[1],x+P*v-S[2],b+I*y-S[3]]}else M.viewport=[x+k*_+_*S[0],b+T*w+w*S[1],x+(k+1)*_-_*S[2],b+(T+1)*w-w*S[3]]}o.color&&(M.color=s.color),o.size&&(M.size=s.size),o.marker&&(M.marker=s.marker),o.borderSize&&(M.borderSize=s.borderSize),o.borderColor&&(M.borderColor=s.borderColor),o.opacity&&(M.opacity=s.opacity),o.range&&(M.range=n?f(s.range,T,k):s.range||M.bounds),s.passes.push(A)}return this},u.prototype.draw=function(){for(var t,e=[],r=arguments.length;r--;)e[r]=arguments[r];if(e.length){for(var n=[],a=0;a<e.length;a++)if("number"==typeof e[a]){var i=this.traces[e[a]],o=i.passes,l=i.passOffset;n.push.apply(n,s(l,l+o.length))}else if(e[a].length){var c=e[a],u=this.traces[a],h=u.passes,f=u.passOffset;h=h.map((function(t,e){n[f+e]=c}))}(t=this.scatter).draw.apply(t,n)}else this.scatter.draw();return this},u.prototype.destroy=function(){return this.traces.forEach((function(t){t.buffer&&t.buffer.destroy&&t.buffer.destroy()})),this.traces=null,this.passes=null,this.scatter.destroy(),this}},{"array-bounds":68,"array-range":70,"flatten-vertex-data":239,"parse-rect":457,"pick-by-alias":463,raf:482,"regl-scatter2d":490}],492:[function(t,e,r){!function(t,n){"object"==typeof r&&"undefined"!=typeof e?e.exports=n():t.createREGL=n()}(this,(function(){function t(t,e){this.id=U++,this.type=t,this.data=e}function e(t){return"["+function t(e){if(0===e.length)return[];var r=e.charAt(0),n=e.charAt(e.length-1);if(1<e.length&&r===n&&('"'===r||"'"===r))return['"'+e.substr(1,e.length-2).replace(/\\/g,"\\\\").replace(/"/g,'\\"')+'"'];if(r=/\[(false|true|null|\d+|'[^']*'|"[^"]*")\]/.exec(e))return t(e.substr(0,r.index)).concat(t(r[1])).concat(t(e.substr(r.index+r[0].length)));if(1===(r=e.split(".")).length)return['"'+e.replace(/\\/g,"\\\\").replace(/"/g,'\\"')+'"'];for(e=[],n=0;n<r.length;++n)e=e.concat(t(r[n]));return 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e=this.computedUp,r=this.computedRight,n=0,a=0,i=0;i<3;++i)a+=e[i]*r[i],n+=e[i]*e[i];var l=Math.sqrt(n),u=0;for(i=0;i<3;++i)r[i]-=e[i]*a/n,u+=r[i]*r[i],e[i]/=l;var h=Math.sqrt(u);for(i=0;i<3;++i)r[i]/=h;var f=this.computedToward;o(f,e,r),s(f,f);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],g=this.computedAngle[1],m=Math.cos(d),v=Math.sin(d),y=Math.cos(g),x=Math.sin(g),b=this.computedCenter,_=m*y,w=v*y,T=x,k=-m*x,A=-v*x,M=y,S=this.computedEye,E=this.computedMatrix;for(i=0;i<3;++i){var C=_*r[i]+w*f[i]+T*e[i];E[4*i+1]=k*r[i]+A*f[i]+M*e[i],E[4*i+2]=C,E[4*i+3]=0}var L=E[1],P=E[5],I=E[9],z=E[2],O=E[6],D=E[10],R=P*D-I*O,F=I*z-L*D,B=L*O-P*z,N=c(R,F,B);R/=N,F/=N,B/=N,E[0]=R,E[4]=F,E[8]=B;for(i=0;i<3;++i)S[i]=b[i]+E[2+4*i]*p;for(i=0;i<3;++i){u=0;for(var j=0;j<3;++j)u+=E[i+4*j]*S[j];E[12+i]=-u}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var a=this.computedMatrix;d[0]=a[2],d[1]=a[6],d[2]=a[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,c=0;c<3;++c)a[4*c]=o[c],a[4*c+1]=s[c],a[4*c+2]=l[c];i(a,a,n,d);for(c=0;c<3;++c)o[c]=a[4*c],s[c]=a[4*c+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var a=this.computedMatrix,i=(Math.exp(this.computedRadius[0]),a[1]),o=a[5],s=a[9],l=c(i,o,s);i/=l,o/=l,s/=l;var u=a[0],h=a[4],f=a[8],p=u*i+h*o+f*s,d=c(u-=i*p,h-=o*p,f-=s*p),g=(u/=d)*e+i*r,m=(h/=d)*e+o*r,v=(f/=d)*e+s*r;this.center.move(t,g,m,v);var y=Math.exp(this.computedRadius[0]);y=Math.max(1e-4,y+n),this.radius.set(t,Math.log(y))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var i=1;"number"==typeof r&&(i=0|r),(i<0||i>3)&&(i=1);var o=(i+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[i],l=e[i+4],h=e[i+8];if(n){var f=Math.abs(s),p=Math.abs(l),d=Math.abs(h),g=Math.max(f,p,d);f===g?(s=s<0?-1:1,l=h=0):d===g?(h=h<0?-1:1,s=l=0):(l=l<0?-1:1,s=h=0)}else{var m=c(s,l,h);s/=m,l/=m,h/=m}var v,y,x=e[o],b=e[o+4],_=e[o+8],w=x*s+b*l+_*h,T=c(x-=s*w,b-=l*w,_-=h*w),k=l*(_/=T)-h*(b/=T),A=h*(x/=T)-s*_,M=s*b-l*x,S=c(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,H,G,Y),this.radius.idle(t),this.up.jump(t,s,l,h),this.right.jump(t,x,b,_),2===i){var E=e[1],C=e[5],L=e[9],P=E*x+C*b+L*_,I=E*k+C*A+L*M;v=R<0?-Math.PI/2:Math.PI/2,y=Math.atan2(I,P)}else{var z=e[2],O=e[6],D=e[10],R=z*s+O*l+D*h,F=z*x+O*b+D*_,B=z*k+O*A+D*M;v=Math.asin(u(R)),y=Math.atan2(B,F)}this.angle.jump(t,y,v),this.recalcMatrix(t);var N=e[2],j=e[6],V=e[10],U=this.computedMatrix;a(U,e);var q=U[15],H=U[12]/q,G=U[13]/q,Y=U[14]/q,W=Math.exp(this.computedRadius[0]);this.center.jump(t,H-N*W,G-j*W,Y-V*W)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},p.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter;var a=(n=n||this.computedUp)[0],i=n[1],o=n[2],s=c(a,i,o);if(!(s<1e-6)){a/=s,i/=s,o/=s;var l=e[0]-r[0],h=e[1]-r[1],f=e[2]-r[2],p=c(l,h,f);if(!(p<1e-6)){l/=p,h/=p,f/=p;var d=this.computedRight,g=d[0],m=d[1],v=d[2],y=a*g+i*m+o*v,x=c(g-=y*a,m-=y*i,v-=y*o);if(!(x<.01&&(x=c(g=i*f-o*h,m=o*l-a*f,v=a*h-i*l))<1e-6)){g/=x,m/=x,v/=x,this.up.set(t,a,i,o),this.right.set(t,g,m,v),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var b=i*v-o*m,_=o*g-a*v,w=a*m-i*g,T=c(b,_,w),k=a*l+i*h+o*f,A=g*l+m*h+v*f,M=(b/=T)*l+(_/=T)*h+(w/=T)*f,S=Math.asin(u(k)),E=Math.atan2(M,A),C=this.angle._state,L=C[C.length-1],P=C[C.length-2];L%=2*Math.PI;var I=Math.abs(L+2*Math.PI-E),z=Math.abs(L-E),O=Math.abs(L-2*Math.PI-E);I<z&&(L+=2*Math.PI),O<z&&(L-=2*Math.PI),this.angle.jump(this.angle.lastT(),L,P),this.angle.set(t,E,S)}}}}},{"filtered-vector":237,"gl-mat4/invert":273,"gl-mat4/rotate":278,"gl-vec3/cross":334,"gl-vec3/dot":339,"gl-vec3/normalize":356}],534:[function(t,e,r){"use strict";e.exports=function(t,e,r){var a=t*e,i=n*t,o=i-(i-t),s=t-o,l=n*e,c=l-(l-e),u=e-c,h=s*u-(a-o*c-s*c-o*u);if(r)return r[0]=h,r[1]=a,r;return[h,a]};var n=+(Math.pow(2,27)+1)},{}],535:[function(t,e,r){"use strict";e.exports=function(t,e,r){var n=t+e,a=n-t,i=e-a,o=t-(n-a);if(r)return r[0]=o+i,r[1]=n,r;return[o+i,n]}},{}],536:[function(t,e,r){"use strict";var n=t("../prototype/is");e.exports=function(t){if("function"!=typeof 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e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()+(e.year()<0?1:0))%4==3||t%4==-1},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[""].invalidYear),13},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(13===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return(t=a.year())<0&&t++,a.day()+30*(a.month()-1)+365*(t-1)+Math.floor(t/4)+this.jdEpoch-1},fromJD:function(t){var e=Math.floor(t)+.5-this.jdEpoch,r=Math.floor((e-Math.floor((e+366)/1461))/365)+1;r<=0&&r--,e=Math.floor(t)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(e/30)+1,a=e-30*(n-1)+1;return 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n.baseCalendar,a(i.prototype,{name:"Islamic",jdEpoch:1948439.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Islamic",epochs:["BH","AH"],monthNames:["Muharram","Safar","Rabi' al-awwal","Rabi' al-thani","Jumada al-awwal","Jumada al-thani","Rajab","Sha'aban","Ramadan","Shawwal","Dhu al-Qi'dah","Dhu al-Hijjah"],monthNamesShort:["Muh","Saf","Rab1","Rab2","Jum1","Jum2","Raj","Sha'","Ram","Shaw","DhuQ","DhuH"],dayNames:["Yawm al-ahad","Yawm al-ithnayn","Yawm ath-thulaathaa'","Yawm al-arbi'aa'","Yawm al-kham\u012bs","Yawm al-jum'a","Yawm as-sabt"],dayNamesShort:["Aha","Ith","Thu","Arb","Kha","Jum","Sab"],dayNamesMin:["Ah","It","Th","Ar","Kh","Ju","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:6,isRTL:!1}},leapYear:function(t){return(11*this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year()+14)%30<11},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){return this.leapYear(t)?355:354},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return t=a.year(),e=a.month(),t=t<=0?t+1:t,(r=a.day())+Math.ceil(29.5*(e-1))+354*(t-1)+Math.floor((3+11*t)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),n.calendars.islamic=i},{"../main":573,"object-assign":452}],565:[function(t,e,r){var n=t("../main"),a=t("object-assign");function i(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}i.prototype=new n.baseCalendar,a(i.prototype,{name:"Julian",jdEpoch:1721423.5,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Julian",epochs:["BC","AD"],monthNames:["January","February","March","April","May","June","July","August","September","October","November","December"],monthNamesShort:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"mm/dd/yyyy",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return(t=e.year()<0?e.year()+1:e.year())%4==0},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(4-(n.dayOfWeek()||7),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(2===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return t=a.year(),e=a.month(),r=a.day(),t<0&&t++,e<=2&&(t--,e+=12),Math.floor(365.25*(t+4716))+Math.floor(30.6001*(e+1))+r-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),a=Math.floor((e-n)/30.6001),i=a-Math.floor(a<14?1:13),o=r-Math.floor(i>2?4716:4715),s=e-n-Math.floor(30.6001*a);return o<=0&&o--,this.newDate(o,i,s)}}),n.calendars.julian=i},{"../main":573,"object-assign":452}],566:[function(t,e,r){var n=t("../main"),a=t("object-assign");function i(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}function o(t,e){return t-e*Math.floor(t/e)}function s(t,e){return o(t-1,e)+1}i.prototype=new n.baseCalendar,a(i.prototype,{name:"Mayan",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{"":{name:"Mayan",epochs:["",""],monthNames:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17"],monthNamesShort:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17"],dayNames:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],dayNamesShort:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],dayNamesMin:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],digits:null,dateFormat:"YYYY.m.d",firstDay:0,isRTL:!1,haabMonths:["Pop","Uo","Zip","Zotz","Tzec","Xul","Yaxkin","Mol","Chen","Yax","Zac","Ceh","Mac","Kankin","Muan","Pax","Kayab","Cumku","Uayeb"],tzolkinMonths:["Imix","Ik","Akbal","Kan","Chicchan","Cimi","Manik","Lamat","Muluc","Oc","Chuen","Eb","Ben","Ix","Men","Cib","Caban","Etznab","Cauac","Ahau"]}},leapYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),!1},formatYear:function(t){t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year();var e=Math.floor(t/400);return t%=400,t+=t<0?400:0,e+"."+Math.floor(t/20)+"."+t%20},forYear:function(t){if((t=t.split(".")).length<3)throw"Invalid Mayan year";for(var e=0,r=0;r<t.length;r++){var n=parseInt(t[r],10);if(Math.abs(n)>19||r>0&&n<0)throw"Invalid Mayan year";e=20*e+n}return e},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),18},weekOfYear:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),0},daysInYear:function(t){return this._validate(t,this.minMonth,this.minDay,n.local.invalidYear),360},daysInMonth:function(t,e){return this._validate(t,e,this.minDay,n.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate).day()},weekDay:function(t,e,r){return this._validate(t,e,r,n.local.invalidDate),!0},extraInfo:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate).toJD(),i=this._toHaab(a),o=this._toTzolkin(a);return{haabMonthName:this.local.haabMonths[i[0]-1],haabMonth:i[0],haabDay:i[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=o((t-=this.jdEpoch)+8+340,365);return[Math.floor(e/20)+1,o(e,20)]},_toTzolkin:function(t){return[s((t-=this.jdEpoch)+20,20),s(t+4,13)]},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);return a.day()+20*a.month()+360*a.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),n.calendars.mayan=i},{"../main":573,"object-assign":452}],567:[function(t,e,r){var n=t("../main"),a=t("object-assign");function i(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}i.prototype=new n.baseCalendar;var o=n.instance("gregorian");a(i.prototype,{name:"Nanakshahi",jdEpoch:2257673.5,daysPerMonth:[31,31,31,31,31,30,30,30,30,30,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Nanakshahi",epochs:["BN","AN"],monthNames:["Chet","Vaisakh","Jeth","Harh","Sawan","Bhadon","Assu","Katak","Maghar","Poh","Magh","Phagun"],monthNamesShort:["Che","Vai","Jet","Har","Saw","Bha","Ass","Kat","Mgr","Poh","Mgh","Pha"],dayNames:["Somvaar","Mangalvar","Budhvaar","Veervaar","Shukarvaar","Sanicharvaar","Etvaar"],dayNamesShort:["Som","Mangal","Budh","Veer","Shukar","Sanichar","Et"],dayNamesMin:["So","Ma","Bu","Ve","Sh","Sa","Et"],digits:null,dateFormat:"dd-mm-yyyy",firstDay:0,isRTL:!1}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear||n.regionalOptions[""].invalidYear);return o.leapYear(e.year()+(e.year()<1?1:0)+1469)},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(1-(n.dayOfWeek()||7),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(t,e){var r=this._validate(t,e,this.minDay,n.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(12===r.month()&&this.leapYear(r.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidMonth);(t=a.year())<0&&t++;for(var i=a.day(),s=1;s<a.month();s++)i+=this.daysPerMonth[s-1];return i+o.toJD(t+1468,3,13)},fromJD:function(t){t=Math.floor(t+.5);for(var e=Math.floor((t-(this.jdEpoch-1))/366);t>=this.toJD(e+1,1,1);)e++;for(var r=t-Math.floor(this.toJD(e,1,1)+.5)+1,n=1;r>this.daysInMonth(e,n);)r-=this.daysInMonth(e,n),n++;return this.newDate(e,n,r)}}),n.calendars.nanakshahi=i},{"../main":573,"object-assign":452}],568:[function(t,e,r){var n=t("../main"),a=t("object-assign");function i(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}i.prototype=new n.baseCalendar,a(i.prototype,{name:"Nepali",jdEpoch:1700709.5,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{"":{name:"Nepali",epochs:["BBS","ABS"],monthNames:["Baisakh","Jestha","Ashadh","Shrawan","Bhadra","Ashwin","Kartik","Mangsir","Paush","Mangh","Falgun","Chaitra"],monthNamesShort:["Bai","Je","As","Shra","Bha","Ash","Kar","Mang","Pau","Ma","Fal","Chai"],dayNames:["Aaitabaar","Sombaar","Manglbaar","Budhabaar","Bihibaar","Shukrabaar","Shanibaar"],dayNamesShort:["Aaita","Som","Mangl","Budha","Bihi","Shukra","Shani"],dayNamesMin:["Aai","So","Man","Bu","Bi","Shu","Sha"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:1,isRTL:!1}},leapYear:function(t){return this.daysInYear(t)!==this.daysPerYear},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){if(t=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear).year(),"undefined"==typeof this.NEPALI_CALENDAR_DATA[t])return this.daysPerYear;for(var e=0,r=this.minMonth;r<=12;r++)e+=this.NEPALI_CALENDAR_DATA[t][r];return e},daysInMonth:function(t,e){return t.year&&(e=t.month(),t=t.year()),this._validate(t,e,this.minDay,n.local.invalidMonth),"undefined"==typeof this.NEPALI_CALENDAR_DATA[t]?this.daysPerMonth[e-1]:this.NEPALI_CALENDAR_DATA[t][e]},weekDay:function(t,e,r){return 6!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate);t=a.year(),e=a.month(),r=a.day();var i=n.instance(),o=0,s=e,l=t;this._createMissingCalendarData(t);var c=t-(s>9||9===s&&r>=this.NEPALI_CALENDAR_DATA[l][0]?56:57);for(9!==e&&(o=r,s--);9!==s;)s<=0&&(s=12,l--),o+=this.NEPALI_CALENDAR_DATA[l][s],s--;return 9===e?(o+=r-this.NEPALI_CALENDAR_DATA[l][0])<0&&(o+=i.daysInYear(c)):o+=this.NEPALI_CALENDAR_DATA[l][9]-this.NEPALI_CALENDAR_DATA[l][0],i.newDate(c,1,1).add(o,"d").toJD()},fromJD:function(t){var e=n.instance().fromJD(t),r=e.year(),a=e.dayOfYear(),i=r+56;this._createMissingCalendarData(i);for(var o=9,s=this.NEPALI_CALENDAR_DATA[i][0],l=this.NEPALI_CALENDAR_DATA[i][o]-s+1;a>l;)++o>12&&(o=1,i++),l+=this.NEPALI_CALENDAR_DATA[i][o];var c=this.NEPALI_CALENDAR_DATA[i][o]-(l-a);return this.newDate(i,o,c)},_createMissingCalendarData:function(t){var e=this.daysPerMonth.slice(0);e.unshift(17);for(var r=t-1;r<t+2;r++)"undefined"==typeof 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n.baseCalendar,a(i.prototype,{name:"UmmAlQura",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Umm al-Qura",epochs:["BH","AH"],monthNames:["Al-Muharram","Safar","Rabi' al-awwal","Rabi' Al-Thani","Jumada Al-Awwal","Jumada Al-Thani","Rajab","Sha'aban","Ramadan","Shawwal","Dhu al-Qi'dah","Dhu al-Hijjah"],monthNamesShort:["Muh","Saf","Rab1","Rab2","Jum1","Jum2","Raj","Sha'","Ram","Shaw","DhuQ","DhuH"],dayNames:["Yawm al-Ahad","Yawm al-Ithnain","Yawm al-Thal\u0101th\u0101\u2019","Yawm al-Arba\u2018\u0101\u2019","Yawm al-Kham\u012bs","Yawm al-Jum\u2018a","Yawm al-Sabt"],dayNamesMin:["Ah","Ith","Th","Ar","Kh","Ju","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:6,isRTL:!0}},leapYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,n.local.invalidYear);return 355===this.daysInYear(e.year())},weekOfYear:function(t,e,r){var n=this.newDate(t,e,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(t){for(var e=0,r=1;r<=12;r++)e+=this.daysInMonth(t,r);return e},daysInMonth:function(t,e){for(var r=this._validate(t,e,this.minDay,n.local.invalidMonth).toJD()-24e5+.5,a=0,i=0;i<o.length;i++){if(o[i]>r)return o[a]-o[a-1];a++}return 30},weekDay:function(t,e,r){return 5!==this.dayOfWeek(t,e,r)},toJD:function(t,e,r){var a=this._validate(t,e,r,n.local.invalidDate),i=12*(a.year()-1)+a.month()-15292;return a.day()+o[i-1]-1+24e5-.5},fromJD:function(t){for(var e=t-24e5+.5,r=0,n=0;n<o.length&&!(o[n]>e);n++)r++;var a=r+15292,i=Math.floor((a-1)/12),s=i+1,l=a-12*i,c=e-o[r-1]+1;return this.newDate(s,l,c)},isValid:function(t,e,r){var a=n.baseCalendar.prototype.isValid.apply(this,arguments);return a&&(a=(t=null!=t.year?t.year:t)>=1276&&t<=1500),a},_validate:function(t,e,r,a){var i=n.baseCalendar.prototype._validate.apply(this,arguments);if(i.year<1276||i.year>1500)throw a.replace(/\{0\}/,this.local.name);return i}}),n.calendars.ummalqura=i;var 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n=t("object-assign");function a(){this.regionalOptions=[],this.regionalOptions[""]={invalidCalendar:"Calendar {0} not found",invalidDate:"Invalid {0} date",invalidMonth:"Invalid {0} month",invalidYear:"Invalid {0} year",differentCalendars:"Cannot mix {0} and {1} dates"},this.local=this.regionalOptions[""],this.calendars={},this._localCals={}}function i(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(c.local.invalidDate||c.regionalOptions[""].invalidDate).replace(/\{0\}/,this._calendar.local.name)}function o(t,e){return"000000".substring(0,e-(t=""+t).length)+t}function s(){this.shortYearCutoff="+10"}function l(t){this.local=this.regionalOptions[t]||this.regionalOptions[""]}n(a.prototype,{instance:function(t,e){t=(t||"gregorian").toLowerCase(),e=e||"";var r=this._localCals[t+"-"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+"-"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[""].invalidCalendar).replace(/\{0\}/,t);return r},newDate:function(t,e,r,n,a){return(n=(null!=t&&t.year?t.calendar():"string"==typeof n?this.instance(n,a):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+"").replace(/[0-9]/g,(function(e){return t[e]}))}},substituteChineseDigits:function(t,e){return function(r){for(var n="",a=0;r>0;){var i=r%10;n=(0===i?"":t[i]+e[a])+n,a++,r=Math.floor(r/10)}return 0===n.indexOf(t[1]+e[1])&&(n=n.substr(1)),n||t[0]}}}),n(i.prototype,{newDate:function(t,e,r){return this._calendar.newDate(null==t?this:t,e,r)},year:function(t){return 0===arguments.length?this._year:this.set(t,"y")},month:function(t){return 0===arguments.length?this._month:this.set(t,"m")},day:function(t){return 0===arguments.length?this._day:this.set(t,"d")},date:function(t,e,r){if(!this._calendar.isValid(t,e,r))throw(c.local.invalidDate||c.regionalOptions[""].invalidDate).replace(/\{0\}/,this._calendar.local.name);return this._year=t,this._month=e,this._day=r,this},leapYear:function(){return this._calendar.leapYear(this)},epoch:function(){return this._calendar.epoch(this)},formatYear:function(){return this._calendar.formatYear(this)},monthOfYear:function(){return this._calendar.monthOfYear(this)},weekOfYear:function(){return this._calendar.weekOfYear(this)},daysInYear:function(){return this._calendar.daysInYear(this)},dayOfYear:function(){return this._calendar.dayOfYear(this)},daysInMonth:function(){return this._calendar.daysInMonth(this)},dayOfWeek:function(){return this._calendar.dayOfWeek(this)},weekDay:function(){return this._calendar.weekDay(this)},extraInfo:function(){return this._calendar.extraInfo(this)},add:function(t,e){return this._calendar.add(this,t,e)},set:function(t,e){return this._calendar.set(this,t,e)},compareTo:function(t){if(this._calendar.name!==t._calendar.name)throw(c.local.differentCalendars||c.regionalOptions[""].differentCalendars).replace(/\{0\}/,this._calendar.local.name).replace(/\{1\}/,t._calendar.local.name);var e=this._year!==t._year?this._year-t._year:this._month!==t._month?this.monthOfYear()-t.monthOfYear():this._day-t._day;return 0===e?0:e<0?-1:1},calendar:function(){return this._calendar},toJD:function(){return this._calendar.toJD(this)},fromJD:function(t){return this._calendar.fromJD(t)},toJSDate:function(){return this._calendar.toJSDate(this)},fromJSDate:function(t){return this._calendar.fromJSDate(t)},toString:function(){return(this.year()<0?"-":"")+o(Math.abs(this.year()),4)+"-"+o(this.month(),2)+"-"+o(this.day(),2)}}),n(s.prototype,{_validateLevel:0,newDate:function(t,e,r){return null==t?this.today():(t.year&&(this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[""].invalidDate),r=t.day(),e=t.month(),t=t.year()),new i(this,t,e,r))},today:function(){return this.fromJSDate(new Date)},epoch:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[""].invalidYear).year()<0?this.local.epochs[0]:this.local.epochs[1]},formatYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[""].invalidYear);return(e.year()<0?"-":"")+o(Math.abs(e.year()),4)},monthsInYear:function(t){return this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[""].invalidYear),12},monthOfYear:function(t,e){var r=this._validate(t,e,this.minDay,c.local.invalidMonth||c.regionalOptions[""].invalidMonth);return(r.month()+this.monthsInYear(r)-this.firstMonth)%this.monthsInYear(r)+this.minMonth},fromMonthOfYear:function(t,e){var r=(e+this.firstMonth-2*this.minMonth)%this.monthsInYear(t)+this.minMonth;return this._validate(t,r,this.minDay,c.local.invalidMonth||c.regionalOptions[""].invalidMonth),r},daysInYear:function(t){var e=this._validate(t,this.minMonth,this.minDay,c.local.invalidYear||c.regionalOptions[""].invalidYear);return this.leapYear(e)?366:365},dayOfYear:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[""].invalidDate);return n.toJD()-this.newDate(n.year(),this.fromMonthOfYear(n.year(),this.minMonth),this.minDay).toJD()+1},daysInWeek:function(){return 7},dayOfWeek:function(t,e,r){var n=this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[""].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,c.local.invalidDate||c.regionalOptions[""].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,c.local.invalidDate||c.regionalOptions[""].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,"d"===r||"w"===r){var n=t.toJD()+e*("w"===r?this.daysInWeek():1),a=t.calendar().fromJD(n);return this._validateLevel--,[a.year(),a.month(),a.day()]}try{var i=t.year()+("y"===r?e:0),o=t.monthOfYear()+("m"===r?e:0);a=t.day();"y"===r?(t.month()!==this.fromMonthOfYear(i,o)&&(o=this.newDate(i,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(i)),a=Math.min(a,this.daysInMonth(i,this.fromMonthOfYear(i,o)))):"m"===r&&(!function(t){for(;o<t.minMonth;)i--,o+=t.monthsInYear(i);for(var e=t.monthsInYear(i);o>e-1+t.minMonth;)i++,o-=e,e=t.monthsInYear(i)}(this),a=Math.min(a,this.daysInMonth(i,this.fromMonthOfYear(i,o))));var s=[i,this.fromMonthOfYear(i,o),a];return this._validateLevel--,s}catch(t){throw 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r,s,l=o(t,e),c=l.on,u=l.off.concat(l.explicitOff),h={},f=t._fullLayout.annotations;if(!c.length&&!u.length)return;for(r=0;r<c.length;r++)(s=i(t.layout,"annotations",f[c[r]])).modifyItem("visible",!0),n.extendFlat(h,s.getUpdateObj());for(r=0;r<u.length;r++)(s=i(t.layout,"annotations",f[u[r]])).modifyItem("visible",!1),n.extendFlat(h,s.getUpdateObj());return a.call("update",t,{},h)}}},{"../../lib":728,"../../plot_api/plot_template":766,"../../registry":859}],581:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../color");e.exports=function(t,e,r,i){i("opacity");var o=i("bgcolor"),s=i("bordercolor"),l=a.opacity(s);i("borderpad");var c=i("borderwidth"),u=i("showarrow");if(i("text",u?" 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l,c,u=t._fullLayout.annotations,h=e._id.charAt(0),f=0;f<u.length;f++)l=u[f],c="annotations["+f+"].",l[h+"ref"]===e._id&&p(h),l["a"+h+"ref"]===e._id&&p("a"+h);function p(t){var r=l[t],s=null;s=o?a(r,e.range):Math.pow(10,r),n(s)||(s=null),i(c+t,s)}}},{"../../lib/to_log_range":754,"fast-isnumeric":236}],583:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../plots/cartesian/axes"),i=t("../../plots/array_container_defaults"),o=t("./common_defaults"),s=t("./attributes");function l(t,e,r){function i(r,a){return n.coerce(t,e,s,r,a)}var l=i("visible"),c=i("clicktoshow");if(l||c){o(t,e,r,i);for(var u=e.showarrow,h=["x","y"],f=[-10,-30],p={_fullLayout:r},d=0;d<2;d++){var g=h[d],m=a.coerceRef(t,e,p,g,"","paper");if("paper"!==m)a.getFromId(p,m)._annIndices.push(e._index);if(a.coercePosition(e,p,i,m,g,.5),u){var v="a"+g,y=a.coerceRef(t,e,p,v,"pixel");"pixel"!==y&&y!==m&&(y=e[v]="pixel");var 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j=e.font,V=x._meta?o.templateString(e.text,x._meta):e.text,U=z.append("text").classed("annotation-text",!0).text(V);_.annotationText?U.call(h.makeEditable,{delegate:z,gd:t}).call(H).on("edit",(function(r){e.text=r,this.call(H),k("text",r),s&&s.autorange&&T(s._name+".autorange",!0),m&&m.autorange&&T(m._name+".autorange",!0),a.call("_guiRelayout",t,A())})):U.call(H)}else n.selectAll("#"+M).remove();function q(t){var n={index:r,annotation:e._input,fullAnnotation:e,event:t};return i&&(n.subplotId=i),n}function H(r){return r.call(c.font,j).attr({"text-anchor":{left:"start",right:"end"}[e.align]||"middle"}),h.convertToTspans(r,t,G),r}function G(){var r=U.selectAll("a");1===r.size()&&r.text()===U.text()&&z.insert("a",":first-child").attr({"xlink:xlink:href":r.attr("xlink:href"),"xlink:xlink:show":r.attr("xlink:show")}).style({cursor:"pointer"}).node().appendChild(F.node());var n=z.select(".annotation-text-math-group"),u=!n.empty(),d=c.bBox((u?n:U).node()),v=d.width,y=d.height,w=e.width||v,I=e.height||y,D=Math.round(w+2*R),j=Math.round(I+2*R);function V(t,e){return"auto"===e&&(e=t<1/3?"left":t>2/3?"right":"center"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var H=!1,G=["x","y"],Y=0;Y<G.length;Y++){var W,Z,X,J,K,Q=G[Y],$=e[Q+"ref"]||Q,tt=e["a"+Q+"ref"],et={x:s,y:m}[Q],rt=(E+("x"===Q?0:-90))*Math.PI/180,nt=D*Math.cos(rt),at=j*Math.sin(rt),it=Math.abs(nt)+Math.abs(at),ot=e[Q+"anchor"],st=e[Q+"shift"]*("x"===Q?1:-1),lt=S[Q];if(et){var ct=et.r2fraction(e[Q]);(ct<0||ct>1)&&(tt===$?((ct=et.r2fraction(e["a"+Q]))<0||ct>1)&&(H=!0):H=!0),W=et._offset+et.r2p(e[Q]),J=.5}else"x"===Q?(X=e[Q],W=b.l+b.w*X):(X=1-e[Q],W=b.t+b.h*X),J=e.showarrow?.5:X;if(e.showarrow){lt.head=W;var ut=e["a"+Q];K=nt*V(.5,e.xanchor)-at*V(.5,e.yanchor),tt===$?(lt.tail=et._offset+et.r2p(ut),Z=K):(lt.tail=W+ut,Z=K+ut),lt.text=lt.tail+K;var 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yt,xt=function(r,n){C.selectAll(".annotation-arrow-g").remove();var u=S.x.head,h=S.y.head,f=S.x.tail+r,d=S.y.tail+n,v=S.x.text+r,y=S.y.text+n,x=o.rotationXYMatrix(E,v,y),w=o.apply2DTransform(x),M=o.apply2DTransform2(x),P=+F.attr("width"),I=+F.attr("height"),O=v-.5*P,D=O+P,R=y-.5*I,B=R+I,N=[[O,R,O,B],[O,B,D,B],[D,B,D,R],[D,R,O,R]].map(M);if(!N.reduce((function(t,e){return t^!!o.segmentsIntersect(u,h,u+1e6,h+1e6,e[0],e[1],e[2],e[3])}),!1)){N.forEach((function(t){var e=o.segmentsIntersect(f,d,u,h,t[0],t[1],t[2],t[3]);e&&(f=e.x,d=e.y)}));var j=e.arrowwidth,V=e.arrowcolor,U=e.arrowside,q=C.append("g").style({opacity:l.opacity(V)}).classed("annotation-arrow-g",!0),H=q.append("path").attr("d","M"+f+","+d+"L"+u+","+h).style("stroke-width",j+"px").call(l.stroke,l.rgb(V));if(g(H,U,e),_.annotationPosition&&H.node().parentNode&&!i){var G=u,Y=h;if(e.standoff){var W=Math.sqrt(Math.pow(u-f,2)+Math.pow(h-d,2));G+=e.standoff*(f-u)/W,Y+=e.standoff*(d-h)/W}var Z,X,J=q.append("path").classed("annotation-arrow",!0).classed("anndrag",!0).classed("cursor-move",!0).attr({d:"M3,3H-3V-3H3ZM0,0L"+(f-G)+","+(d-Y),transform:"translate("+G+","+Y+")"}).style("stroke-width",j+6+"px").call(l.stroke,"rgba(0,0,0,0)").call(l.fill,"rgba(0,0,0,0)");p.init({element:J.node(),gd:t,prepFn:function(){var t=c.getTranslate(z);Z=t.x,X=t.y,s&&s.autorange&&T(s._name+".autorange",!0),m&&m.autorange&&T(m._name+".autorange",!0)},moveFn:function(t,r){var n=w(Z,X),a=n[0]+t,i=n[1]+r;z.call(c.setTranslate,a,i),k("x",s?s.p2r(s.r2p(e.x)+t):e.x+t/b.w),k("y",m?m.p2r(m.r2p(e.y)+r):e.y-r/b.h),e.axref===e.xref&&k("ax",s.p2r(s.r2p(e.ax)+t)),e.ayref===e.yref&&k("ay",m.p2r(m.r2p(e.ay)+r)),q.attr("transform","translate("+t+","+r+")"),L.attr({transform:"rotate("+E+","+a+","+i+")"})},doneFn:function(){a.call("_guiRelayout",t,A());var e=document.querySelector(".js-notes-box-panel");e&&e.redraw(e.selectedObj)}})}}};if(e.showarrow&&xt(0,0),P)p.init({element:z.node(),gd:t,prepFn:function(){yt=L.attr("transform")},moveFn:function(t,r){var n="pointer";if(e.showarrow)e.axref===e.xref?k("ax",s.p2r(s.r2p(e.ax)+t)):k("ax",e.ax+t),e.ayref===e.yref?k("ay",m.p2r(m.r2p(e.ay)+r)):k("ay",e.ay+r),xt(t,r);else{if(i)return;var a,o;if(s)a=s.p2r(s.r2p(e.x)+t);else{var l=e._xsize/b.w,c=e.x+(e._xshift-e.xshift)/b.w-l/2;a=p.align(c+t/b.w,l,0,1,e.xanchor)}if(m)o=m.p2r(m.r2p(e.y)+r);else{var u=e._ysize/b.h,h=e.y-(e._yshift+e.yshift)/b.h-u/2;o=p.align(h-r/b.h,u,0,1,e.yanchor)}k("x",a),k("y",o),s&&m||(n=p.getCursor(s?.5:a,m?.5:o,e.xanchor,e.yanchor))}L.attr({transform:"translate("+t+","+r+")"+yt}),f(z,n)},clickFn:function(r,n){e.captureevents&&t.emit("plotly_clickannotation",q(n))},doneFn:function(){f(z),a.call("_guiRelayout",t,A());var e=document.querySelector(".js-notes-box-panel");e&&e.redraw(e.selectedObj)}})}}}e.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(".annotation").remove();for(var r=0;r<e.annotations.length;r++)e.annotations[r].visible&&m(t,r);return i.previousPromises(t)},drawOne:m,drawRaw:v}},{"../../lib":728,"../../lib/setcursor":748,"../../lib/svg_text_utils":752,"../../plot_api/plot_template":766,"../../plots/cartesian/axes":776,"../../plots/plots":839,"../../registry":859,"../color":595,"../dragelement":614,"../drawing":617,"../fx":635,"./draw_arrow_head":585,d3:164}],585:[function(t,e,r){"use strict";var n=t("d3"),a=t("../color"),i=t("./arrow_paths");e.exports=function(t,e,r){var o,s,l,c,u=t.node(),h=i[r.arrowhead||0],f=i[r.startarrowhead||0],p=(r.arrowwidth||1)*(r.arrowsize||1),d=(r.arrowwidth||1)*(r.startarrowsize||1),g=e.indexOf("start")>=0,m=e.indexOf("end")>=0,v=h.backoff*p+r.standoff,y=f.backoff*d+r.startstandoff;if("line"===u.nodeName){o={x:+t.attr("x1"),y:+t.attr("y1")},s={x:+t.attr("x2"),y:+t.attr("y2")};var x=o.x-s.x,b=o.y-s.y;if(c=(l=Math.atan2(b,x))+Math.PI,v&&y&&v+y>Math.sqrt(x*x+b*b))return void P();if(v){if(v*v>x*x+b*b)return void P();var _=v*Math.cos(l),w=v*Math.sin(l);s.x+=_,s.y+=w,t.attr({x2:s.x,y2:s.y})}if(y){if(y*y>x*x+b*b)return void P();var T=y*Math.cos(l),k=y*Math.sin(l);o.x-=T,o.y-=k,t.attr({x1:o.x,y1:o.y})}}else if("path"===u.nodeName){var A=u.getTotalLength(),M="";if(A<v+y)return void P();var S=u.getPointAtLength(0),E=u.getPointAtLength(.1);l=Math.atan2(S.y-E.y,S.x-E.x),o=u.getPointAtLength(Math.min(y,A)),M="0px,"+y+"px,";var C=u.getPointAtLength(A),L=u.getPointAtLength(A-.1);c=Math.atan2(C.y-L.y,C.x-L.x),s=u.getPointAtLength(Math.max(0,A-v)),M+=A-(M?y+v:v)+"px,"+A+"px",t.style("stroke-dasharray",M)}function P(){t.style("stroke-dasharray","0px,100px")}function I(e,i,o,s){e.path&&(e.noRotate&&(o=0),n.select(u.parentNode).append("path").attr({class:t.attr("class"),d:e.path,transform:"translate("+i.x+","+i.y+")"+(o?"rotate("+180*o/Math.PI+")":"")+"scale("+s+")"}).style({fill:a.rgb(r.arrowcolor),"stroke-width":0}))}g&&I(f,o,l,d),m&&I(h,s,c,p)}},{"../color":595,"./arrow_paths":577,d3:164}],586:[function(t,e,r){"use strict";var n=t("./draw"),a=t("./click");e.exports={moduleType:"component",name:"annotations",layoutAttributes:t("./attributes"),supplyLayoutDefaults:t("./defaults"),includeBasePlot:t("../../plots/cartesian/include_components")("annotations"),calcAutorange:t("./calc_autorange"),draw:n.draw,drawOne:n.drawOne,drawRaw:n.drawRaw,hasClickToShow:a.hasClickToShow,onClick:a.onClick,convertCoords:t("./convert_coords")}},{"../../plots/cartesian/include_components":788,"./attributes":578,"./calc_autorange":579,"./click":580,"./convert_coords":582,"./defaults":583,"./draw":584}],587:[function(t,e,r){"use strict";var n=t("../annotations/attributes"),a=t("../../plot_api/edit_types").overrideAll,i=t("../../plot_api/plot_template").templatedArray;e.exports=a(i("annotation",{visible:n.visible,x:{valType:"any"},y:{valType:"any"},z:{valType:"any"},ax:{valType:"number"},ay:{valType:"number"},xanchor:n.xanchor,xshift:n.xshift,yanchor:n.yanchor,yshift:n.yshift,text:n.text,textangle:n.textangle,font:n.font,width:n.width,height:n.height,opacity:n.opacity,align:n.align,valign:n.valign,bgcolor:n.bgcolor,bordercolor:n.bordercolor,borderpad:n.borderpad,borderwidth:n.borderwidth,showarrow:n.showarrow,arrowcolor:n.arrowcolor,arrowhead:n.arrowhead,startarrowhead:n.startarrowhead,arrowside:n.arrowside,arrowsize:n.arrowsize,startarrowsize:n.startarrowsize,arrowwidth:n.arrowwidth,standoff:n.standoff,startstandoff:n.startstandoff,hovertext:n.hovertext,hoverlabel:n.hoverlabel,captureevents:n.captureevents}),"calc","from-root")},{"../../plot_api/edit_types":759,"../../plot_api/plot_template":766,"../annotations/attributes":578}],588:[function(t,e,r){"use 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a=t.map((function(t){return{color:t.color||h.defaultLine,x0:t.x0||t.x||0,x1:t.x1||t.x||0,y0:t.y0||t.y||0,y1:t.y1||t.y||0,xLabel:t.xLabel,yLabel:t.yLabel,zLabel:t.zLabel,text:t.text,name:t.name,idealAlign:t.idealAlign,borderColor:t.borderColor,fontFamily:t.fontFamily,fontSize:t.fontSize,fontColor:t.fontColor,nameLength:t.nameLength,textAlign:t.textAlign,trace:t.trace||{index:0,hoverinfo:""},xa:{_offset:0},ya:{_offset:0},index:0,hovertemplate:t.hovertemplate||!1,eventData:t.eventData||!1,hovertemplateLabels:t.hovertemplateLabels||!1}})),i=n.select(e.container),o=e.outerContainer?n.select(e.outerContainer):i,s={hovermode:"closest",rotateLabels:!1,bgColor:e.bgColor||h.background,container:i,outerContainer:o},l=E(a,s,e.gd),c=0,u=0;return l.sort((function(t,e){return t.y0-e.y0})).each((function(t,r){var n=t.y0-t.by/2;t.offset=n-5<c?c-n+5:0,c=n+t.by+t.offset,r===e.anchorIndex&&(u=t.offset)})).each((function(t){t.offset-=u})),L(l,s.rotateLabels),r?l:l.node()};var S=/<extra>([\s\S]*)<\/extra>/;function E(t,e,r){var a=r._fullLayout,i=e.hovermode,s=e.rotateLabels,c=e.bgColor,f=e.container,p=e.outerContainer,d=e.commonLabelOpts||{},b=e.fontFamily||m.HOVERFONT,_=e.fontSize||m.HOVERFONTSIZE,w=t[0],T=w.xa,S=w.ya,E="y"===i.charAt(0)?"yLabel":"xLabel",L=w[E],P=(String(L)||"").split(" ")[0],I=p.node().getBoundingClientRect(),z=I.top,O=I.width,D=I.height,R=void 0!==L&&w.distance<=e.hoverdistance&&("x"===i||"y"===i);if(R){var F,B,N=!0;for(F=0;F<t.length;F++)if(N&&void 0===t[F].zLabel&&(N=!1),B=t[F].hoverinfo||t[F].trace.hoverinfo){var j=Array.isArray(B)?B:B.split("+");if(-1===j.indexOf("all")&&-1===j.indexOf(i)){R=!1;break}}N&&(R=!1)}var V=f.selectAll("g.axistext").data(R?[0]:[]);function U(t){return t.filter((function(t){return void 0!==t.zLabelVal||(t[E]||"").split(" ")[0]===P}))}if(V.enter().append("g").classed("axistext",!0),V.exit().remove(),V.each((function(){var 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n=t("./constants"),a=t("../../plots/font_attributes")({editType:"none"});a.family.dflt=n.HOVERFONT,a.size.dflt=n.HOVERFONTSIZE,e.exports={clickmode:{valType:"flaglist",flags:["event","select"],dflt:"event",editType:"plot",extras:["none"]},dragmode:{valType:"enumerated",values:["zoom","pan","select","lasso","drawclosedpath","drawopenpath","drawline","drawrect","drawcircle","orbit","turntable",!1],dflt:"zoom",editType:"modebar"},hovermode:{valType:"enumerated",values:["x","y","closest",!1,"x unified","y 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c(t,e,r){var n=e[r+"axes"],a=Object.keys((t._splomAxes||{})[r]||{});return Array.isArray(n)?n:a.length?a:void 0}function u(t,e,r,n,a,i){var o=e(t+"gap",r),s=e("domain."+t);e(t+"side",n);for(var l=new Array(a),c=s[0],u=(s[1]-c)/(a-o),h=u*(1-o),f=0;f<a;f++){var p=c+u*f;l[i?a-1-f:f]=[p,p+h]}return l}function h(t,e,r,n,a){var i,o=new Array(r);function s(t,r){-1!==e.indexOf(r)&&void 0===n[r]?(o[t]=r,n[r]=t):o[t]=""}if(Array.isArray(t))for(i=0;i<r;i++)s(i,t[i]);else for(s(0,a),i=1;i<r;i++)s(i,a+(i+1));return o}e.exports={moduleType:"component",name:"grid",schema:{layout:{grid:l}},layoutAttributes:l,sizeDefaults:function(t,e){var r=t.grid||{},a=c(e,r,"x"),i=c(e,r,"y");if(t.grid||a||i){var o,h,f=Array.isArray(r.subplots)&&Array.isArray(r.subplots[0]),p=Array.isArray(a),d=Array.isArray(i),g=p&&a!==r.xaxes&&d&&i!==r.yaxes;f?(o=r.subplots.length,h=r.subplots[0].length):(d&&(o=i.length),p&&(h=a.length));var 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t=n.select(this),e=t.select(".selector-rect"),a=t.select(".selector-text"),i=a.node()&&s.bBox(a.node()).width,o=r.font.size*f,l=c.lineCount(a),p=Math.max(i+10,g.minButtonWidth);t.attr("transform","translate("+(m+u)+","+m+")"),e.attr({x:0,y:0,width:p,height:h}),c.positionText(a,p/2,h/2-(l-1)*o/2+3),u+=p+5}));var v=t._fullLayout._size,y=v.l+v.w*r.x,x=v.t+v.h*(1-r.y),b="left";l.isRightAnchor(r)&&(y-=u,b="right");l.isCenterAnchor(r)&&(y-=u/2,b="center");var _="top";l.isBottomAnchor(r)&&(x-=h,_="bottom");l.isMiddleAnchor(r)&&(x-=h/2,_="middle");u=Math.ceil(u),h=Math.ceil(h),y=Math.round(y),x=Math.round(x),i.autoMargin(t,a+"-range-selector",{x:r.x,y:r.y,l:u*p[b],r:u*d[b],b:h*d[_],t:h*p[_]}),o.attr("transform","translate("+y+","+x+")")}(t,h,u,o._name,r)}))}},{"../../constants/alignment":697,"../../lib":728,"../../lib/svg_text_utils":752,"../../plots/cartesian/axis_ids":779,"../../plots/plots":839,"../../registry":859,"../color":595,"../drawing":617,"./constants":659,"./get_update_object":662,d3:164}],662:[function(t,e,r){"use strict";var n=t("d3");e.exports=function(t,e){var r=t._name,a={};if("all"===e.step)a[r+".autorange"]=!0;else{var i=function(t,e){var r,a=t.range,i=new Date(t.r2l(a[1])),o=e.step,s=e.count;switch(e.stepmode){case"backward":r=t.l2r(+n.time[o].utc.offset(i,-s));break;case"todate":var l=n.time[o].utc.offset(i,-s);r=t.l2r(+n.time[o].utc.ceil(l))}var c=a[1];return[r,c]}(t,e);a[r+".range[0]"]=i[0],a[r+".range[1]"]=i[1]}return 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n=t("../../lib"),a=t("../../plot_api/plot_template"),i=t("../../plots/cartesian/axis_ids"),o=t("./attributes"),s=t("./oppaxis_attributes");e.exports=function(t,e,r){var l=t[r],c=e[r];if(l.rangeslider||e._requestRangeslider[c._id]){n.isPlainObject(l.rangeslider)||(l.rangeslider={});var u,h,f=l.rangeslider,p=a.newContainer(c,"rangeslider");if(_("visible")){_("bgcolor",e.plot_bgcolor),_("bordercolor"),_("borderwidth"),_("thickness"),_("autorange",!c.isValidRange(f.range)),_("range");var d=e._subplots;if(d)for(var g=d.cartesian.filter((function(t){return t.substr(0,t.indexOf("y"))===i.name2id(r)})).map((function(t){return t.substr(t.indexOf("y"),t.length)})),m=n.simpleMap(g,i.id2name),v=0;v<m.length;v++){var y=m[v];u=f[y]||{},h=a.newContainer(p,y,"yaxis");var x,b=e[y];u.range&&b.isValidRange(u.range)&&(x="fixed"),"match"!==w("rangemode",x)&&w("range",b.range.slice())}p._input=f}}function _(t,e){return n.coerce(f,p,o,t,e)}function w(t,e){return 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w=(p.range[0]+p.range[1])/2,k=(d.range[0]+d.range[1])/2;if(o._isScoped)y={lon:w,lat:k};else if(o._isClipped){y={lon:w,lat:k},x={lon:w,lat:k,roll:x.roll};var A=c.type,M=v.lonaxisSpan[A]/2||180,S=v.lataxisSpan[A]/2||180;b=[w-M,w+M],_=[k-S,k+S]}else y={lon:w,lat:k},x={lon:w,lat:x.lat,roll:x.roll}}g.center([y.lon-x.lon,y.lat-x.lat]).rotate([-x.lon,-x.lat,x.roll]).parallels(c.parallels);var E=T(b,_);g.fitExtent(m,E);var C=this.bounds=g.getBounds(E),L=this.fitScale=g.scale(),P=g.translate();if(!isFinite(C[0][0])||!isFinite(C[0][1])||!isFinite(C[1][0])||!isFinite(C[1][1])||isNaN(P[0])||isNaN(P[0])){for(var I=["fitbounds","projection.rotation","center","lonaxis.range","lataxis.range"],z="Invalid geo settings, relayout'ing to default view.",O={},D=0;D<I.length;D++)O[this.id+"."+I[D]]=null;return this.viewInitial=null,i.warn(z),r._promises.push(a.call("relayout",r,O)),z}if(o.fitbounds){var R=g.getBounds(T(p.range,d.range)),F=Math.min((C[1][0]-C[0][0])/(R[1][0]-R[0][0]),(C[1][1]-C[0][1])/(R[1][1]-R[0][1]));isFinite(F)?g.scale(F*L):i.warn("Something went wrong during"+this.id+"fitbounds computations.")}else g.scale(c.scale*L);var B=this.midPt=[(C[0][0]+C[1][0])/2,(C[0][1]+C[1][1])/2];if(g.translate([P[0]+(B[0]-P[0]),P[1]+(B[1]-P[1])]).clipExtent(C),o._isAlbersUsa){var N=g([y.lon,y.lat]),j=g.translate();g.translate([j[0]-(N[0]-j[0]),j[1]-(N[1]-j[1])])}},w.updateBaseLayers=function(t,e){var r=this,a=r.topojson,i=r.layers,l=r.basePaths;function c(t){return"lonaxis"===t||"lataxis"===t}function h(t){return Boolean(v.lineLayers[t])}function f(t){return Boolean(v.fillLayers[t])}var p=(this.hasChoropleth?v.layersForChoropleth:v.layers).filter((function(t){return h(t)||f(t)?e["show"+t]:!c(t)||e[t].showgrid})),d=r.framework.selectAll(".layer").data(p,String);d.exit().each((function(t){delete i[t],delete 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h={element:r.bgRect.node(),gd:i,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(t){2===t&&d(i)}};"pan"===s?(o.node().onmousedown=null,o.call(m(r,e)),o.on("dblclick.zoom",(function(){var t=r.viewInitial,e={};for(var n in t)e[r.id+"."+n]=t[n];a.call("_guiRelayout",i,e),i.emit("plotly_doubleclick",null)})),i._context._scrollZoom.geo||o.on("wheel.zoom",null)):"select"!==s&&"lasso"!==s||(o.on(".zoom",null),h.prepFn=function(t,e,r){p(t,e,r,h,s)},f.init(h)),o.on("mousemove",(function(){var t=r.projection.invert(n.mouse(this));if(!t||isNaN(t[0])||isNaN(t[1]))return f.unhover(i,n.event);r.xaxis.p2c=function(){return t[0]},r.yaxis.p2c=function(){return t[1]},l.hover(i,n.event,r.id)})),o.on("mouseout",(function(){i._dragging||f.unhover(i,n.event)})),o.on("click",(function(){"select"!==s&&"lasso"!==s&&(c.indexOf("select")>-1&&g(n.event,i,[r.xaxis],[r.yaxis],r.id,h),c.indexOf("event")>-1&&l.click(i,n.event))}))}function v(t){return r.projection.invert([t[0]+r.xaxis._offset,t[1]+r.yaxis._offset])}},w.makeFramework=function(){var t=this,e=t.graphDiv,r=e._fullLayout,a="clip"+r._uid+t.id;t.clipDef=r._clips.append("clipPath").attr("id",a),t.clipRect=t.clipDef.append("rect"),t.framework=n.select(t.container).append("g").attr("class","geo "+t.id).call(s.setClipUrl,a,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:"x",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:"y",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:"linear",showexponent:"all",exponentformat:"B"},u.setConvert(t.mockAxis,r)},w.saveViewInitial=function(t){var e,r=t.center||{},n=t.projection,a=n.rotation||{};this.viewInitial={fitbounds:t.fitbounds,"projection.scale":n.scale},e=t._isScoped?{"center.lon":r.lon,"center.lat":r.lat}:t._isClipped?{"projection.rotation.lon":a.lon,"projection.rotation.lat":a.lat}:{"center.lon":r.lon,"center.lat":r.lat,"projection.rotation.lon":a.lon},i.extendFlat(this.viewInitial,e)},w.render=function(){var t,e=this.projection,r=e.getPath();function n(t){var r=e(t.lonlat);return r?"translate("+r[0]+","+r[1]+")":null}function a(t){return e.isLonLatOverEdges(t.lonlat)?"none":null}for(t in this.basePaths)this.basePaths[t].attr("d",r);for(t in this.dataPaths)this.dataPaths[t].attr("d",(function(t){return r(t.geojson)}));for(t in this.dataPoints)this.dataPoints[t].attr("display",a).attr("transform",n)}},{"../../components/color":595,"../../components/dragelement":614,"../../components/drawing":617,"../../components/fx":635,"../../lib":728,"../../lib/geo_location_utils":722,"../../lib/topojson_utils":755,"../../registry":859,"../cartesian/autorange":775,"../cartesian/axes":776,"../cartesian/select":795,"../plots":839,"./constants":806,"./projections":811,"./zoom":812,d3:164,"topojson-client":531}],808:[function(t,e,r){"use strict";var n=t("../../plots/get_data").getSubplotCalcData,a=t("../../lib").counterRegex,i=t("./geo"),o="geo",s=a(o),l={};l.geo={valType:"subplotid",dflt:o,editType:"calc"},e.exports={attr:o,name:o,idRoot:o,idRegex:s,attrRegex:s,attributes:l,layoutAttributes:t("./layout_attributes"),supplyLayoutDefaults:t("./layout_defaults"),plot:function(t){for(var e=t._fullLayout,r=t.calcdata,a=e._subplots.geo,s=0;s<a.length;s++){var 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n=t("../../components/color/attributes"),a=t("../domain").attributes,i=t("./constants"),o=t("../../plot_api/edit_types").overrideAll,s={range:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},showgrid:{valType:"boolean",dflt:!1},tick0:{valType:"number",dflt:0},dtick:{valType:"number"},gridcolor:{valType:"color",dflt:n.lightLine},gridwidth:{valType:"number",min:0,dflt:1}};(e.exports=o({domain:a({name:"geo"},{}),fitbounds:{valType:"enumerated",values:[!1,"locations","geojson"],dflt:!1,editType:"plot"},resolution:{valType:"enumerated",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:"enumerated",values:Object.keys(i.scopeDefaults),dflt:"world"},projection:{type:{valType:"enumerated",values:Object.keys(i.projNames)},rotation:{lon:{valType:"number"},lat:{valType:"number"},roll:{valType:"number"}},parallels:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},scale:{valType:"number",min:0,dflt:1}},center:{lon:{valType:"number"},lat:{valType:"number"}},visible:{valType:"boolean",dflt:!0},showcoastlines:{valType:"boolean"},coastlinecolor:{valType:"color",dflt:n.defaultLine},coastlinewidth:{valType:"number",min:0,dflt:1},showland:{valType:"boolean",dflt:!1},landcolor:{valType:"color",dflt:i.landColor},showocean:{valType:"boolean",dflt:!1},oceancolor:{valType:"color",dflt:i.waterColor},showlakes:{valType:"boolean",dflt:!1},lakecolor:{valType:"color",dflt:i.waterColor},showrivers:{valType:"boolean",dflt:!1},rivercolor:{valType:"color",dflt:i.waterColor},riverwidth:{valType:"number",min:0,dflt:1},showcountries:{valType:"boolean"},countrycolor:{valType:"color",dflt:n.defaultLine},countrywidth:{valType:"number",min:0,dflt:1},showsubunits:{valType:"boolean"},subunitcolor:{valType:"color",dflt:n.defaultLine},subunitwidth:{valType:"number",min:0,dflt:1},showframe:{valType:"boolean"},framecolor:{valType:"color",dflt:n.defaultLine},framewidth:{valType:"number",min:0,dflt:1},bgcolor:{valType:"color",dflt:n.background},lonaxis:s,lataxis:s},"plot","from-root")).uirevision={valType:"any",editType:"none"}},{"../../components/color/attributes":594,"../../plot_api/edit_types":759,"../domain":803,"./constants":806}],810:[function(t,e,r){"use 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M=r(_+".range",b);r(_+".tick0"),r(_+".dtick",w),r(_+".showgrid",!!y&&void 0)&&(r(_+".gridcolor"),r(_+".gridwidth")),e[_]._ax={type:"linear",_id:_.slice(0,3),_traceIndices:s,setScale:n.identity,c2l:n.identity,r2l:n.identity,autorange:!0,range:M.slice(),_m:1,_input:{}}}var S=e.lonaxis.range,E=e.lataxis.range,C=S[0],L=S[1];C>0&&L<0&&(L+=360);var P,I,z,O=(C+L)/2;if(!p){var D=d?h.projRotate:[O,0,0];P=r("projection.rotation.lon",D[0]),r("projection.rotation.lat",D[1]),r("projection.rotation.roll",D[2]),r("showcoastlines",!d&&y)&&(r("coastlinecolor"),r("coastlinewidth")),r("showocean",!!y&&void 0)&&r("oceancolor")}(p?(I=-96.6,z=38.7):(I=d?O:P,z=(E[0]+E[1])/2),r("center.lon",I),r("center.lat",z),g)&&r("projection.parallels",h.projParallels||[0,60]);r("projection.scale"),r("showland",!!y&&void 0)&&r("landcolor"),r("showlakes",!!y&&void 0)&&r("lakecolor"),r("showrivers",!!y&&void 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a[i]=t[i]*l-t[s]*c,a[s]=t[s]*l+t[i]*c,a}function T(t){return[Math.atan2(2*(t[0]*t[1]+t[2]*t[3]),1-2*(t[1]*t[1]+t[2]*t[2]))*s,Math.asin(Math.max(-1,Math.min(1,2*(t[0]*t[2]-t[3]*t[1]))))*s,Math.atan2(2*(t[0]*t[3]+t[1]*t[2]),1-2*(t[2]*t[2]+t[3]*t[3]))*s]}function k(t,e){for(var r=0,n=0,a=t.length;n<a;++n)r+=t[n]*e[n];return r}e.exports=function(t,e){var r=t.projection;return(e._isScoped?f:e._isClipped?d:p)(t,r)}},{"../../lib":728,"../../registry":859,d3:164}],813:[function(t,e,r){"use strict";var n=t("../registry"),a=t("./cartesian/constants").SUBPLOT_PATTERN;r.getSubplotCalcData=function(t,e,r){var a=n.subplotsRegistry[e];if(!a)return[];for(var i=a.attr,o=[],s=0;s<t.length;s++){var l=t[s];l[0].trace[i]===r&&o.push(l)}return o},r.getModuleCalcData=function(t,e){var r,a=[],i=[];if(!(r="string"==typeof e?n.getModule(e).plot:"function"==typeof e?e:e.plot))return[a,t];for(var o=0;o<t.length;o++){var s=t[o],l=s[0].trace;!0===l.visible&&0!==l._length&&(l._module.plot===r?a.push(s):i.push(s))}return[a,i]},r.getSubplotData=function(t,e,r){if(!n.subplotsRegistry[e])return[];var i,o,s,l=n.subplotsRegistry[e].attr,c=[];if("gl2d"===e){var u=r.match(a);o="x"+u[1],s="y"+u[2]}for(var h=0;h<t.length;h++)i=t[h],"gl2d"===e&&n.traceIs(i,"gl2d")?i[l[0]]===o&&i[l[1]]===s&&c.push(i):i[l]===r&&c.push(i);return c}},{"../registry":859,"./cartesian/constants":782}],814:[function(t,e,r){"use strict";var n=t("mouse-change"),a=t("mouse-wheel"),i=t("mouse-event-offset"),o=t("../cartesian/constants"),s=t("has-passive-events");function l(t,e){this.element=t,this.plot=e,this.mouseListener=null,this.wheelListener=null,this.lastInputTime=Date.now(),this.lastPos=[0,0],this.boxEnabled=!1,this.boxInited=!1,this.boxStart=[0,0],this.boxEnd=[0,0],this.dragStart=[0,0]}e.exports=function(t){var e=t.mouseContainer,r=t.glplot,c=new l(e,r);function u(){t.xaxis.autorange=!1,t.yaxis.autorange=!1}function h(e,n,a){var i,s,l=t.calcDataBox(),h=r.viewBox,f=c.lastPos[0],p=c.lastPos[1],d=o.MINDRAG*r.pixelRatio,g=o.MINZOOM*r.pixelRatio;function m(e,r,n){var a=Math.min(r,n),i=Math.max(r,n);a!==i?(l[e]=a,l[e+2]=i,c.dataBox=l,t.setRanges(l)):(t.selectBox.selectBox=[0,0,1,1],t.glplot.setDirty())}switch(n*=r.pixelRatio,a*=r.pixelRatio,a=h[3]-h[1]-a,t.fullLayout.dragmode){case"zoom":if(e){var v=n/(h[2]-h[0])*(l[2]-l[0])+l[0],y=a/(h[3]-h[1])*(l[3]-l[1])+l[1];c.boxInited||(c.boxStart[0]=v,c.boxStart[1]=y,c.dragStart[0]=n,c.dragStart[1]=a),c.boxEnd[0]=v,c.boxEnd[1]=y,c.boxInited=!0,c.boxEnabled||c.boxStart[0]===c.boxEnd[0]&&c.boxStart[1]===c.boxEnd[1]||(c.boxEnabled=!0);var x=Math.abs(c.dragStart[0]-n)<g,b=Math.abs(c.dragStart[1]-a)<g;if(!function(){for(var e=t.graphDiv._fullLayout._axisConstraintGroups,r=t.xaxis._id,n=t.yaxis._id,a=0;a<e.length;a++)if(-1!==e[a][r]){if(-1!==e[a][n])return!0;break}return!1}()||x&&b)x&&(c.boxEnd[0]=c.boxStart[0]),b&&(c.boxEnd[1]=c.boxStart[1]);else{i=c.boxEnd[0]-c.boxStart[0],s=c.boxEnd[1]-c.boxStart[1];var _=(l[3]-l[1])/(l[2]-l[0]);Math.abs(i*_)>Math.abs(s)?(c.boxEnd[1]=c.boxStart[1]+Math.abs(i)*_*(s>=0?1:-1),c.boxEnd[1]<l[1]?(c.boxEnd[1]=l[1],c.boxEnd[0]=c.boxStart[0]+(l[1]-c.boxStart[1])/Math.abs(_)):c.boxEnd[1]>l[3]&&(c.boxEnd[1]=l[3],c.boxEnd[0]=c.boxStart[0]+(l[3]-c.boxStart[1])/Math.abs(_))):(c.boxEnd[0]=c.boxStart[0]+Math.abs(s)/_*(i>=0?1:-1),c.boxEnd[0]<l[0]?(c.boxEnd[0]=l[0],c.boxEnd[1]=c.boxStart[1]+(l[0]-c.boxStart[0])*Math.abs(_)):c.boxEnd[0]>l[2]&&(c.boxEnd[0]=l[2],c.boxEnd[1]=c.boxStart[1]+(l[2]-c.boxStart[0])*Math.abs(_)))}}else c.boxEnabled?(i=c.boxStart[0]!==c.boxEnd[0],s=c.boxStart[1]!==c.boxEnd[1],i||s?(i&&(m(0,c.boxStart[0],c.boxEnd[0]),t.xaxis.autorange=!1),s&&(m(1,c.boxStart[1],c.boxEnd[1]),t.yaxis.autorange=!1),t.relayoutCallback()):t.glplot.setDirty(),c.boxEnabled=!1,c.boxInited=!1):c.boxInited&&(c.boxInited=!1);break;case"pan":c.boxEnabled=!1,c.boxInited=!1,e?(c.panning||(c.dragStart[0]=n,c.dragStart[1]=a),Math.abs(c.dragStart[0]-n)<d&&(n=c.dragStart[0]),Math.abs(c.dragStart[1]-a)<d&&(a=c.dragStart[1]),i=(f-n)*(l[2]-l[0])/(r.viewBox[2]-r.viewBox[0]),s=(p-a)*(l[3]-l[1])/(r.viewBox[3]-r.viewBox[1]),l[0]+=i,l[2]+=i,l[1]+=s,l[3]+=s,t.setRanges(l),c.panning=!0,c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations()):c.panning&&(c.panning=!1,t.relayoutCallback())}c.lastPos[0]=n,c.lastPos[1]=a}return c.mouseListener=n(e,h),e.addEventListener("touchstart",(function(t){var r=i(t.changedTouches[0],e);h(0,r[0],r[1]),h(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener("touchmove",(function(t){t.preventDefault();var r=i(t.changedTouches[0],e);h(1,r[0],r[1]),t.preventDefault()}),!!s&&{passive:!1}),e.addEventListener("touchend",(function(t){h(0,c.lastPos[0],c.lastPos[1]),t.preventDefault()}),!!s&&{passive:!1}),c.wheelListener=a(e,(function(e,n){if(!t.scrollZoom)return!1;var a=t.calcDataBox(),i=r.viewBox,o=c.lastPos[0],s=c.lastPos[1],l=Math.exp(5*n/(i[3]-i[1])),h=o/(i[2]-i[0])*(a[2]-a[0])+a[0],f=s/(i[3]-i[1])*(a[3]-a[1])+a[1];return a[0]=(a[0]-h)*l+h,a[2]=(a[2]-h)*l+h,a[1]=(a[1]-f)*l+f,a[3]=(a[3]-f)*l+f,t.setRanges(a),c.lastInputTime=Date.now(),u(),t.cameraChanged(),t.handleAnnotations(),t.relayoutCallback(),!0}),!0),c}},{"../cartesian/constants":782,"has-passive-events":410,"mouse-change":436,"mouse-event-offset":437,"mouse-wheel":439}],815:[function(t,e,r){"use strict";var n=t("../cartesian/axes"),a=t("../../lib/str2rgbarray");function i(t){this.scene=t,this.gl=t.gl,this.pixelRatio=t.pixelRatio,this.screenBox=[0,0,1,1],this.viewBox=[0,0,1,1],this.dataBox=[-1,-1,1,1],this.borderLineEnable=[!1,!1,!1,!1],this.borderLineWidth=[1,1,1,1],this.borderLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.ticks=[[],[]],this.tickEnable=[!0,!0,!1,!1],this.tickPad=[15,15,15,15],this.tickAngle=[0,0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickMarkLength=[0,0,0,0],this.tickMarkWidth=[0,0,0,0],this.tickMarkColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labels=["x","y"],this.labelEnable=[!0,!0,!1,!1],this.labelAngle=[0,Math.PI/2,0,3*Math.PI/2],this.labelPad=[15,15,15,15],this.labelSize=[12,12],this.labelFont=["sans-serif","sans-serif"],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.title="",this.titleEnable=!0,this.titleCenter=[0,0,0,0],this.titleAngle=0,this.titleColor=[0,0,0,1],this.titleFont="sans-serif",this.titleSize=18,this.gridLineEnable=[!0,!0],this.gridLineColor=[[0,0,0,.5],[0,0,0,.5]],this.gridLineWidth=[1,1],this.zeroLineEnable=[!0,!0],this.zeroLineWidth=[1,1],this.zeroLineColor=[[0,0,0,1],[0,0,0,1]],this.borderColor=[0,0,0,0],this.backgroundColor=[0,0,0,0],this.static=this.scene.staticPlot}var o=i.prototype,s=["xaxis","yaxis"];o.merge=function(t){var e,r,n,i,o,l,c,u,h,f,p;for(this.titleEnable=!1,this.backgroundColor=a(t.plot_bgcolor),f=0;f<2;++f){var d=(e=s[f]).charAt(0);for(n=(r=t[this.scene[e]._name]).title.text===this.scene.fullLayout._dfltTitle[d]?"":r.title.text,p=0;p<=2;p+=2)this.labelEnable[f+p]=!1,this.labels[f+p]=n,this.labelColor[f+p]=a(r.title.font.color),this.labelFont[f+p]=r.title.font.family,this.labelSize[f+p]=r.title.font.size,this.labelPad[f+p]=this.getLabelPad(e,r),this.tickEnable[f+p]=!1,this.tickColor[f+p]=a((r.tickfont||{}).color),this.tickAngle[f+p]="auto"===r.tickangle?0:Math.PI*-r.tickangle/180,this.tickPad[f+p]=this.getTickPad(r),this.tickMarkLength[f+p]=0,this.tickMarkWidth[f+p]=r.tickwidth||0,this.tickMarkColor[f+p]=a(r.tickcolor),this.borderLineEnable[f+p]=!1,this.borderLineColor[f+p]=a(r.linecolor),this.borderLineWidth[f+p]=r.linewidth||0;c=this.hasSharedAxis(r),o=this.hasAxisInDfltPos(e,r)&&!c,l=this.hasAxisInAltrPos(e,r)&&!c,i=r.mirror||!1,u=c?-1!==String(i).indexOf("all"):!!i,h=c?"allticks"===i:-1!==String(i).indexOf("ticks"),o?this.labelEnable[f]=!0:l&&(this.labelEnable[f+2]=!0),o?this.tickEnable[f]=r.showticklabels:l&&(this.tickEnable[f+2]=r.showticklabels),(o||u)&&(this.borderLineEnable[f]=r.showline),(l||u)&&(this.borderLineEnable[f+2]=r.showline),(o||h)&&(this.tickMarkLength[f]=this.getTickMarkLength(r)),(l||h)&&(this.tickMarkLength[f+2]=this.getTickMarkLength(r)),this.gridLineEnable[f]=r.showgrid,this.gridLineColor[f]=a(r.gridcolor),this.gridLineWidth[f]=r.gridwidth,this.zeroLineEnable[f]=r.zeroline,this.zeroLineColor[f]=a(r.zerolinecolor),this.zeroLineWidth[f]=r.zerolinewidth}},o.hasSharedAxis=function(t){var e=this.scene,r=e.fullLayout._subplots.gl2d;return 0!==n.findSubplotsWithAxis(r,t).indexOf(e.id)},o.hasAxisInDfltPos=function(t,e){var r=e.side;return"xaxis"===t?"bottom"===r:"yaxis"===t?"left"===r:void 0},o.hasAxisInAltrPos=function(t,e){var r=e.side;return"xaxis"===t?"top"===r:"yaxis"===t?"right"===r:void 0},o.getLabelPad=function(t,e){var r=e.title.font.size,n=e.showticklabels;return"xaxis"===t?"top"===e.side?r*(1.5+(n?1:0))-10:r*(1.5+(n?.5:0))-10:"yaxis"===t?"right"===e.side?10+r*(1.5+(n?1:.5)):10+r*(1.5+(n?.5:0)):void 0},o.getTickPad=function(t){return"outside"===t.ticks?10+t.ticklen:15},o.getTickMarkLength=function(t){if(!t.ticks)return 0;var e=t.ticklen;return"inside"===t.ticks?-e:e},e.exports=function(t){return new i(t)}},{"../../lib/str2rgbarray":751,"../cartesian/axes":776}],816:[function(t,e,r){"use strict";var n=t("../../plot_api/edit_types").overrideAll,a=t("./scene2d"),i=t("../layout_attributes"),o=t("../../constants/xmlns_namespaces"),s=t("../cartesian/constants"),l=t("../cartesian"),c=t("../../components/fx/layout_attributes"),u=t("../get_data").getSubplotData;r.name="gl2d",r.attr=["xaxis","yaxis"],r.idRoot=["x","y"],r.idRegex=s.idRegex,r.attrRegex=s.attrRegex,r.attributes=t("../cartesian/attributes"),r.supplyLayoutDefaults=function(t,e,r){e._has("cartesian")||l.supplyLayoutDefaults(t,e,r)},r.layoutAttrOverrides=n(l.layoutAttributes,"plot","from-root"),r.baseLayoutAttrOverrides=n({plot_bgcolor:i.plot_bgcolor,hoverlabel:c.hoverlabel},"plot","nested"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl2d,i=0;i<n.length;i++){var o=n[i],s=e._plots[o],l=u(r,"gl2d",o),c=s._scene2d;void 0===c&&(c=new a({id:o,graphDiv:t,container:t.querySelector(".gl-container"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio},e),s._scene2d=c),c.plot(l,t.calcdata,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=n._subplots.gl2d||[],i=0;i<a.length;i++){var o=a[i],s=n._plots[o];if(s._scene2d){var c=u(t,"gl2d",o);0===c.length&&(s._scene2d.destroy(),delete n._plots[o])}}l.clean.apply(this,arguments)},r.drawFramework=function(t){t._context.staticPlot||l.drawFramework(t)},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){var a=e._plots[r[n]]._scene2d,i=a.toImage("png");e._glimages.append("svg:image").attr({xmlns:o.svg,"xlink:href":i,x:0,y:0,width:"100%",height:"100%",preserveAspectRatio:"none"}),a.destroy()}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl2d,n=0;n<r.length;n++){e._plots[r[n]]._scene2d.updateFx(e.dragmode)}}},{"../../components/fx/layout_attributes":636,"../../constants/xmlns_namespaces":705,"../../plot_api/edit_types":759,"../cartesian":789,"../cartesian/attributes":774,"../cartesian/constants":782,"../get_data":813,"../layout_attributes":830,"./scene2d":817}],817:[function(t,e,r){"use strict";var n,a,i=t("../../registry"),o=t("../../plots/cartesian/axes"),s=t("../../components/fx"),l=t("gl-plot2d"),c=t("gl-spikes2d"),u=t("gl-select-box"),h=t("webgl-context"),f=t("./convert"),p=t("./camera"),d=t("../../lib/show_no_webgl_msg"),g=t("../cartesian/constraints"),m=g.enforce,v=g.clean,y=t("../cartesian/autorange").doAutoRange,x=t("../../components/dragelement/helpers"),b=x.drawMode,_=x.selectMode,w=["xaxis","yaxis"],T=t("../cartesian/constants").SUBPLOT_PATTERN;function k(t,e){this.container=t.container,this.graphDiv=t.graphDiv,this.pixelRatio=t.plotGlPixelRatio||window.devicePixelRatio,this.id=t.id,this.staticPlot=!!t.staticPlot,this.scrollZoom=this.graphDiv._context._scrollZoom.cartesian,this.fullData=null,this.updateRefs(e),this.makeFramework(),this.stopped||(this.glplotOptions=f(this),this.glplotOptions.merge(e),this.glplot=l(this.glplotOptions),this.camera=p(this),this.traces={},this.spikes=c(this.glplot),this.selectBox=u(this.glplot,{innerFill:!1,outerFill:!0}),this.lastButtonState=0,this.pickResult=null,this.isMouseOver=!0,this.stopped=!1,this.redraw=this.draw.bind(this),this.redraw())}e.exports=k;var A=k.prototype;A.makeFramework=function(){if(this.staticPlot){if(!(a||(n=document.createElement("canvas"),a=h({canvas:n,preserveDrawingBuffer:!1,premultipliedAlpha:!0,antialias:!0}))))throw new Error("Error creating static canvas/context for image server");this.canvas=n,this.gl=a}else{var t=this.container.querySelector(".gl-canvas-focus"),e=h({canvas:t,preserveDrawingBuffer:!0,premultipliedAlpha:!0});if(!e)return d(this),void(this.stopped=!0);this.canvas=t,this.gl=e}var r=this.canvas;r.style.width="100%",r.style.height="100%",r.style.position="absolute",r.style.top="0px",r.style.left="0px",r.style["pointer-events"]="none",this.updateSize(r),r.className+=" user-select-none";var i=this.svgContainer=document.createElementNS("http://www.w3.org/2000/svg","svg");i.style.position="absolute",i.style.top=i.style.left="0px",i.style.width=i.style.height="100%",i.style["z-index"]=20,i.style["pointer-events"]="none";var o=this.mouseContainer=document.createElement("div");o.style.position="absolute",o.style["pointer-events"]="auto",this.pickCanvas=this.container.querySelector(".gl-canvas-pick");var s=this.container;s.appendChild(i),s.appendChild(o);var l=this;o.addEventListener("mouseout",(function(){l.isMouseOver=!1,l.unhover()})),o.addEventListener("mouseover",(function(){l.isMouseOver=!0}))},A.toImage=function(t){t||(t="png"),this.stopped=!0,this.staticPlot&&this.container.appendChild(n),this.updateSize(this.canvas);var e=this.glplot.gl,r=e.drawingBufferWidth,a=e.drawingBufferHeight;e.clearColor(1,1,1,0),e.clear(e.COLOR_BUFFER_BIT|e.DEPTH_BUFFER_BIT),this.glplot.setDirty(),this.glplot.draw(),e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*a*4);e.readPixels(0,0,r,a,e.RGBA,e.UNSIGNED_BYTE,i);for(var o=0,s=a-1;o<s;++o,--s)for(var l=0;l<r;++l)for(var c=0;c<4;++c){var u=i[4*(r*o+l)+c];i[4*(r*o+l)+c]=i[4*(r*s+l)+c],i[4*(r*s+l)+c]=u}var h=document.createElement("canvas");h.width=r,h.height=a;var f,p=h.getContext("2d"),d=p.createImageData(r,a);switch(d.data.set(i),p.putImageData(d,0,0),t){case"jpeg":f=h.toDataURL("image/jpeg");break;case"webp":f=h.toDataURL("image/webp");break;default:f=h.toDataURL("image/png")}return this.staticPlot&&this.container.removeChild(n),f},A.updateSize=function(t){t||(t=this.canvas);var e=this.pixelRatio,r=this.fullLayout,n=r.width,a=r.height,i=0|Math.ceil(e*n),o=0|Math.ceil(e*a);return t.width===i&&t.height===o||(t.width=i,t.height=o),t},A.computeTickMarks=function(){this.xaxis.setScale(),this.yaxis.setScale();for(var t=[o.calcTicks(this.xaxis),o.calcTicks(this.yaxis)],e=0;e<2;++e)for(var r=0;r<t[e].length;++r)t[e][r].text=t[e][r].text+"";return t},A.updateRefs=function(t){this.fullLayout=t;var e=this.id.match(T),r="xaxis"+e[1],n="yaxis"+e[2];this.xaxis=this.fullLayout[r],this.yaxis=this.fullLayout[n]},A.relayoutCallback=function(){var t=this.graphDiv,e=this.xaxis,r=this.yaxis,n=t.layout,a={},o=a[e._name+".range"]=e.range.slice(),s=a[r._name+".range"]=r.range.slice();a[e._name+".autorange"]=e.autorange,a[r._name+".autorange"]=r.autorange,i.call("_storeDirectGUIEdit",t.layout,t._fullLayout._preGUI,a);var l=n[e._name];l.range=o,l.autorange=e.autorange;var c=n[r._name];c.range=s,c.autorange=r.autorange,a.lastInputTime=this.camera.lastInputTime,t.emit("plotly_relayout",a)},A.cameraChanged=function(){var t=this.camera;this.glplot.setDataBox(this.calcDataBox());var e=this.computeTickMarks();(function(t,e){for(var r=0;r<2;++r){var n=t[r],a=e[r];if(n.length!==a.length)return!0;for(var i=0;i<n.length;++i)if(n[i].x!==a[i].x)return!0}return!1})(e,this.glplotOptions.ticks)&&(this.glplotOptions.ticks=e,this.glplotOptions.dataBox=t.dataBox,this.glplot.update(this.glplotOptions),this.handleAnnotations())},A.handleAnnotations=function(){for(var t=this.graphDiv,e=this.fullLayout.annotations,r=0;r<e.length;r++){var n=e[r];n.xref===this.xaxis._id&&n.yref===this.yaxis._id&&i.getComponentMethod("annotations","drawOne")(t,r)}},A.destroy=function(){if(this.glplot){var t=this.traces;t&&Object.keys(t).map((function(e){t[e].dispose(),delete t[e]})),this.glplot.dispose(),this.container.removeChild(this.svgContainer),this.container.removeChild(this.mouseContainer),this.fullData=null,this.glplot=null,this.stopped=!0,this.camera.mouseListener.enabled=!1,this.mouseContainer.removeEventListener("wheel",this.camera.wheelListener),this.camera=null}},A.plot=function(t,e,r){var n=this.glplot;this.updateRefs(r),this.xaxis.clearCalc(),this.yaxis.clearCalc(),this.updateTraces(t,e),this.updateFx(r.dragmode);var a=r.width,i=r.height;this.updateSize(this.canvas);var o=this.glplotOptions;o.merge(r),o.screenBox=[0,0,a,i];var s={_fullLayout:{_axisConstraintGroups:this.graphDiv._fullLayout._axisConstraintGroups,xaxis:this.xaxis,yaxis:this.yaxis}};v(s,this.xaxis),v(s,this.yaxis);var l,c,u=r._size,h=this.xaxis.domain,f=this.yaxis.domain;for(o.viewBox=[u.l+h[0]*u.w,u.b+f[0]*u.h,a-u.r-(1-h[1])*u.w,i-u.t-(1-f[1])*u.h],this.mouseContainer.style.width=u.w*(h[1]-h[0])+"px",this.mouseContainer.style.height=u.h*(f[1]-f[0])+"px",this.mouseContainer.height=u.h*(f[1]-f[0]),this.mouseContainer.style.left=u.l+h[0]*u.w+"px",this.mouseContainer.style.top=u.t+(1-f[1])*u.h+"px",c=0;c<2;++c)(l=this[w[c]])._length=o.viewBox[c+2]-o.viewBox[c],y(this.graphDiv,l),l.setScale();m(s),o.ticks=this.computeTickMarks(),o.dataBox=this.calcDataBox(),o.merge(r),n.update(o),this.glplot.draw()},A.calcDataBox=function(){var t=this.xaxis,e=this.yaxis,r=t.range,n=e.range,a=t.r2l,i=e.r2l;return[a(r[0]),i(n[0]),a(r[1]),i(n[1])]},A.setRanges=function(t){var e=this.xaxis,r=this.yaxis,n=e.l2r,a=r.l2r;e.range=[n(t[0]),n(t[2])],r.range=[a(t[1]),a(t[3])]},A.updateTraces=function(t,e){var r,n,a,i=Object.keys(this.traces);this.fullData=t;t:for(r=0;r<i.length;r++){var o=i[r],s=this.traces[o];for(n=0;n<t.length;n++)if((a=t[n]).uid===o&&a.type===s.type)continue t;s.dispose(),delete this.traces[o]}for(r=0;r<t.length;r++){a=t[r];var l=e[r],c=this.traces[a.uid];c?c.update(a,l):(c=a._module.plot(this,a,l),this.traces[a.uid]=c)}this.glplot.objects.sort((function(t,e){return t._trace.index-e._trace.index}))},A.updateFx=function(t){_(t)||b(t)?(this.pickCanvas.style["pointer-events"]="none",this.mouseContainer.style["pointer-events"]="none"):(this.pickCanvas.style["pointer-events"]="auto",this.mouseContainer.style["pointer-events"]="auto"),this.mouseContainer.style.cursor="pan"===t?"move":"zoom"===t?"crosshair":null},A.emitPointAction=function(t,e){for(var r,n=t.trace.uid,a=t.pointIndex,i=0;i<this.fullData.length;i++)this.fullData[i].uid===n&&(r=this.fullData[i]);var o={x:t.traceCoord[0],y:t.traceCoord[1],curveNumber:r.index,pointNumber:a,data:r._input,fullData:this.fullData,xaxis:this.xaxis,yaxis:this.yaxis};s.appendArrayPointValue(o,r,a),this.graphDiv.emit(e,{points:[o]})},A.draw=function(){if(!this.stopped){requestAnimationFrame(this.redraw);var t=this.glplot,e=this.camera,r=e.mouseListener,n=1===this.lastButtonState&&0===r.buttons,a=this.fullLayout;this.lastButtonState=r.buttons,this.cameraChanged();var i,o=r.x*t.pixelRatio,l=this.canvas.height-t.pixelRatio*r.y;if(e.boxEnabled&&"zoom"===a.dragmode){this.selectBox.enabled=!0;for(var c=this.selectBox.selectBox=[Math.min(e.boxStart[0],e.boxEnd[0]),Math.min(e.boxStart[1],e.boxEnd[1]),Math.max(e.boxStart[0],e.boxEnd[0]),Math.max(e.boxStart[1],e.boxEnd[1])],u=0;u<2;u++)e.boxStart[u]===e.boxEnd[u]&&(c[u]=t.dataBox[u],c[u+2]=t.dataBox[u+2]);t.setDirty()}else if(!e.panning&&this.isMouseOver){this.selectBox.enabled=!1;var h=a._size,f=this.xaxis.domain,p=this.yaxis.domain,d=(i=t.pick(o/t.pixelRatio+h.l+f[0]*h.w,l/t.pixelRatio-(h.t+(1-p[1])*h.h)))&&i.object._trace.handlePick(i);if(d&&n&&this.emitPointAction(d,"plotly_click"),i&&"skip"!==i.object._trace.hoverinfo&&a.hovermode&&d&&(!this.lastPickResult||this.lastPickResult.traceUid!==d.trace.uid||this.lastPickResult.dataCoord[0]!==d.dataCoord[0]||this.lastPickResult.dataCoord[1]!==d.dataCoord[1])){var g=d;this.lastPickResult={traceUid:d.trace?d.trace.uid:null,dataCoord:d.dataCoord.slice()},this.spikes.update({center:i.dataCoord}),g.screenCoord=[((t.viewBox[2]-t.viewBox[0])*(i.dataCoord[0]-t.dataBox[0])/(t.dataBox[2]-t.dataBox[0])+t.viewBox[0])/t.pixelRatio,(this.canvas.height-(t.viewBox[3]-t.viewBox[1])*(i.dataCoord[1]-t.dataBox[1])/(t.dataBox[3]-t.dataBox[1])-t.viewBox[1])/t.pixelRatio],this.emitPointAction(d,"plotly_hover");var m=this.fullData[g.trace.index]||{},v=g.pointIndex,y=s.castHoverinfo(m,a,v);if(y&&"all"!==y){var x=y.split("+");-1===x.indexOf("x")&&(g.traceCoord[0]=void 0),-1===x.indexOf("y")&&(g.traceCoord[1]=void 0),-1===x.indexOf("z")&&(g.traceCoord[2]=void 0),-1===x.indexOf("text")&&(g.textLabel=void 0),-1===x.indexOf("name")&&(g.name=void 0)}s.loneHover({x:g.screenCoord[0],y:g.screenCoord[1],xLabel:this.hoverFormatter("xaxis",g.traceCoord[0]),yLabel:this.hoverFormatter("yaxis",g.traceCoord[1]),zLabel:g.traceCoord[2],text:g.textLabel,name:g.name,color:s.castHoverOption(m,v,"bgcolor")||g.color,borderColor:s.castHoverOption(m,v,"bordercolor"),fontFamily:s.castHoverOption(m,v,"font.family"),fontSize:s.castHoverOption(m,v,"font.size"),fontColor:s.castHoverOption(m,v,"font.color"),nameLength:s.castHoverOption(m,v,"namelength"),textAlign:s.castHoverOption(m,v,"align")},{container:this.svgContainer,gd:this.graphDiv})}}i||this.unhover(),t.draw()}},A.unhover=function(){this.lastPickResult&&(this.spikes.update({}),this.lastPickResult=null,this.graphDiv.emit("plotly_unhover"),s.loneUnhover(this.svgContainer))},A.hoverFormatter=function(t,e){if(void 0!==e){var r=this[t];return o.tickText(r,r.c2l(e),"hover").text}}},{"../../components/dragelement/helpers":613,"../../components/fx":635,"../../lib/show_no_webgl_msg":749,"../../plots/cartesian/axes":776,"../../registry":859,"../cartesian/autorange":775,"../cartesian/constants":782,"../cartesian/constraints":783,"./camera":814,"./convert":815,"gl-plot2d":293,"gl-select-box":305,"gl-spikes2d":314,"webgl-context":558}],818:[function(t,e,r){"use strict";var n=t("../../plot_api/edit_types").overrideAll,a=t("../../components/fx/layout_attributes"),i=t("./scene"),o=t("../get_data").getSubplotData,s=t("../../lib"),l=t("../../constants/xmlns_namespaces");r.name="gl3d",r.attr="scene",r.idRoot="scene",r.idRegex=r.attrRegex=s.counterRegex("scene"),r.attributes=t("./layout/attributes"),r.layoutAttributes=t("./layout/layout_attributes"),r.baseLayoutAttrOverrides=n({hoverlabel:a.hoverlabel},"plot","nested"),r.supplyLayoutDefaults=t("./layout/defaults"),r.plot=function(t){for(var e=t._fullLayout,r=t._fullData,n=e._subplots.gl3d,a=0;a<n.length;a++){var s=n[a],l=o(r,"gl3d",s),c=e[s],u=c.camera,h=c._scene;h||(h=new i({id:s,graphDiv:t,container:t.querySelector(".gl-container"),staticPlot:t._context.staticPlot,plotGlPixelRatio:t._context.plotGlPixelRatio,camera:u},e),c._scene=h),h.viewInitial||(h.viewInitial={up:{x:u.up.x,y:u.up.y,z:u.up.z},eye:{x:u.eye.x,y:u.eye.y,z:u.eye.z},center:{x:u.center.x,y:u.center.y,z:u.center.z}}),h.plot(l,e,t.layout)}},r.clean=function(t,e,r,n){for(var a=n._subplots.gl3d||[],i=0;i<a.length;i++){var o=a[i];!e[o]&&n[o]._scene&&(n[o]._scene.destroy(),n._infolayer&&n._infolayer.selectAll(".annotation-"+o).remove())}},r.toSVG=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=e._size,a=0;a<r.length;a++){var i=e[r[a]],o=i.domain,s=i._scene,c=s.toImage("png");e._glimages.append("svg:image").attr({xmlns:l.svg,"xlink:href":c,x:n.l+n.w*o.x[0],y:n.t+n.h*(1-o.y[1]),width:n.w*(o.x[1]-o.x[0]),height:n.h*(o.y[1]-o.y[0]),preserveAspectRatio:"none"}),s.destroy()}},r.cleanId=function(t){if(t.match(/^scene[0-9]*$/)){var e=t.substr(5);return"1"===e&&(e=""),"scene"+e}},r.updateFx=function(t){for(var e=t._fullLayout,r=e._subplots.gl3d,n=0;n<r.length;n++){e[r[n]]._scene.updateFx(e.dragmode,e.hovermode)}}},{"../../components/fx/layout_attributes":636,"../../constants/xmlns_namespaces":705,"../../lib":728,"../../plot_api/edit_types":759,"../get_data":813,"./layout/attributes":819,"./layout/defaults":823,"./layout/layout_attributes":824,"./scene":828}],819:[function(t,e,r){"use strict";e.exports={scene:{valType:"subplotid",dflt:"scene",editType:"calc+clearAxisTypes"}}},{}],820:[function(t,e,r){"use strict";var n=t("../../../components/color"),a=t("../../cartesian/layout_attributes"),i=t("../../../lib/extend").extendFlat,o=t("../../../plot_api/edit_types").overrideAll;e.exports=o({visible:a.visible,showspikes:{valType:"boolean",dflt:!0},spikesides:{valType:"boolean",dflt:!0},spikethickness:{valType:"number",min:0,dflt:2},spikecolor:{valType:"color",dflt:n.defaultLine},showbackground:{valType:"boolean",dflt:!1},backgroundcolor:{valType:"color",dflt:"rgba(204, 204, 204, 0.5)"},showaxeslabels:{valType:"boolean",dflt:!0},color:a.color,categoryorder:a.categoryorder,categoryarray:a.categoryarray,title:{text:a.title.text,font:a.title.font},type:i({},a.type,{values:["-","linear","log","date","category"]}),autorange:a.autorange,rangemode:a.rangemode,range:i({},a.range,{items:[{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}},{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}}],anim:!1}),tickmode:a.tickmode,nticks:a.nticks,tick0:a.tick0,dtick:a.dtick,tickvals:a.tickvals,ticktext:a.ticktext,ticks:a.ticks,mirror:a.mirror,ticklen:a.ticklen,tickwidth:a.tickwidth,tickcolor:a.tickcolor,showticklabels:a.showticklabels,tickfont:a.tickfont,tickangle:a.tickangle,tickprefix:a.tickprefix,showtickprefix:a.showtickprefix,ticksuffix:a.ticksuffix,showticksuffix:a.showticksuffix,showexponent:a.showexponent,exponentformat:a.exponentformat,separatethousands:a.separatethousands,tickformat:a.tickformat,tickformatstops:a.tickformatstops,hoverformat:a.hoverformat,showline:a.showline,linecolor:a.linecolor,linewidth:a.linewidth,showgrid:a.showgrid,gridcolor:i({},a.gridcolor,{dflt:"rgb(204, 204, 204)"}),gridwidth:a.gridwidth,zeroline:a.zeroline,zerolinecolor:a.zerolinecolor,zerolinewidth:a.zerolinewidth,_deprecated:{title:a._deprecated.title,titlefont:a._deprecated.titlefont}},"plot","from-root")},{"../../../components/color":595,"../../../lib/extend":719,"../../../plot_api/edit_types":759,"../../cartesian/layout_attributes":790}],821:[function(t,e,r){"use strict";var n=t("tinycolor2").mix,a=t("../../../lib"),i=t("../../../plot_api/plot_template"),o=t("./axis_attributes"),s=t("../../cartesian/type_defaults"),l=t("../../cartesian/axis_defaults"),c=["xaxis","yaxis","zaxis"];e.exports=function(t,e,r){var u,h;function f(t,e){return a.coerce(u,h,o,t,e)}for(var p=0;p<c.length;p++){var d=c[p];u=t[d]||{},(h=i.newContainer(e,d))._id=d[0]+r.scene,h._name=d,s(u,h,f,r),l(u,h,f,{font:r.font,letter:d[0],data:r.data,showGrid:!0,noTickson:!0,bgColor:r.bgColor,calendar:r.calendar},r.fullLayout),f("gridcolor",n(h.color,r.bgColor,13600/187).toRgbString()),f("title.text",d[0]),h.setScale=a.noop,f("showspikes")&&(f("spikesides"),f("spikethickness"),f("spikecolor",h.color)),f("showaxeslabels"),f("showbackground")&&f("backgroundcolor")}}},{"../../../lib":728,"../../../plot_api/plot_template":766,"../../cartesian/axis_defaults":778,"../../cartesian/type_defaults":801,"./axis_attributes":820,tinycolor2:528}],822:[function(t,e,r){"use strict";var n=t("../../../lib/str2rgbarray"),a=t("../../../lib"),i=["xaxis","yaxis","zaxis"];function o(){this.bounds=[[-10,-10,-10],[10,10,10]],this.ticks=[[],[],[]],this.tickEnable=[!0,!0,!0],this.tickFont=["sans-serif","sans-serif","sans-serif"],this.tickSize=[12,12,12],this.tickAngle=[0,0,0],this.tickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.tickPad=[18,18,18],this.labels=["x","y","z"],this.labelEnable=[!0,!0,!0],this.labelFont=["Open Sans","Open Sans","Open Sans"],this.labelSize=[20,20,20],this.labelColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.labelPad=[30,30,30],this.lineEnable=[!0,!0,!0],this.lineMirror=[!1,!1,!1],this.lineWidth=[1,1,1],this.lineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.lineTickEnable=[!0,!0,!0],this.lineTickMirror=[!1,!1,!1],this.lineTickLength=[10,10,10],this.lineTickWidth=[1,1,1],this.lineTickColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.gridEnable=[!0,!0,!0],this.gridWidth=[1,1,1],this.gridColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroEnable=[!0,!0,!0],this.zeroLineColor=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.zeroLineWidth=[2,2,2],this.backgroundEnable=[!0,!0,!0],this.backgroundColor=[[.8,.8,.8,.5],[.8,.8,.8,.5],[.8,.8,.8,.5]],this._defaultTickPad=this.tickPad.slice(),this._defaultLabelPad=this.labelPad.slice(),this._defaultLineTickLength=this.lineTickLength.slice()}o.prototype.merge=function(t,e){for(var r=0;r<3;++r){var o=e[i[r]];o.visible?(this.labels[r]=t._meta?a.templateString(o.title.text,t._meta):o.title.text,"font"in o.title&&(o.title.font.color&&(this.labelColor[r]=n(o.title.font.color)),o.title.font.family&&(this.labelFont[r]=o.title.font.family),o.title.font.size&&(this.labelSize[r]=o.title.font.size)),"showline"in o&&(this.lineEnable[r]=o.showline),"linecolor"in o&&(this.lineColor[r]=n(o.linecolor)),"linewidth"in o&&(this.lineWidth[r]=o.linewidth),"showgrid"in o&&(this.gridEnable[r]=o.showgrid),"gridcolor"in o&&(this.gridColor[r]=n(o.gridcolor)),"gridwidth"in o&&(this.gridWidth[r]=o.gridwidth),"log"===o.type?this.zeroEnable[r]=!1:"zeroline"in o&&(this.zeroEnable[r]=o.zeroline),"zerolinecolor"in o&&(this.zeroLineColor[r]=n(o.zerolinecolor)),"zerolinewidth"in o&&(this.zeroLineWidth[r]=o.zerolinewidth),"ticks"in o&&o.ticks?this.lineTickEnable[r]=!0:this.lineTickEnable[r]=!1,"ticklen"in o&&(this.lineTickLength[r]=this._defaultLineTickLength[r]=o.ticklen),"tickcolor"in o&&(this.lineTickColor[r]=n(o.tickcolor)),"tickwidth"in o&&(this.lineTickWidth[r]=o.tickwidth),"tickangle"in o&&(this.tickAngle[r]="auto"===o.tickangle?-3600:Math.PI*-o.tickangle/180),"showticklabels"in o&&(this.tickEnable[r]=o.showticklabels),"tickfont"in o&&(o.tickfont.color&&(this.tickColor[r]=n(o.tickfont.color)),o.tickfont.family&&(this.tickFont[r]=o.tickfont.family),o.tickfont.size&&(this.tickSize[r]=o.tickfont.size)),"mirror"in o?-1!==["ticks","all","allticks"].indexOf(o.mirror)?(this.lineTickMirror[r]=!0,this.lineMirror[r]=!0):!0===o.mirror?(this.lineTickMirror[r]=!1,this.lineMirror[r]=!0):(this.lineTickMirror[r]=!1,this.lineMirror[r]=!1):this.lineMirror[r]=!1,"showbackground"in o&&!1!==o.showbackground?(this.backgroundEnable[r]=!0,this.backgroundColor[r]=n(o.backgroundcolor)):this.backgroundEnable[r]=!1):(this.tickEnable[r]=!1,this.labelEnable[r]=!1,this.lineEnable[r]=!1,this.lineTickEnable[r]=!1,this.gridEnable[r]=!1,this.zeroEnable[r]=!1,this.backgroundEnable[r]=!1)}},e.exports=function(t,e){var r=new o;return r.merge(t,e),r}},{"../../../lib":728,"../../../lib/str2rgbarray":751}],823:[function(t,e,r){"use strict";var n=t("../../../lib"),a=t("../../../components/color"),i=t("../../../registry"),o=t("../../subplot_defaults"),s=t("./axis_defaults"),l=t("./layout_attributes"),c=t("../../get_data").getSubplotData;function u(t,e,r,n){for(var o=r("bgcolor"),l=a.combine(o,n.paper_bgcolor),u=["up","center","eye"],h=0;h<u.length;h++)r("camera."+u[h]+".x"),r("camera."+u[h]+".y"),r("camera."+u[h]+".z");r("camera.projection.type");var f=!!r("aspectratio.x")&&!!r("aspectratio.y")&&!!r("aspectratio.z"),p=r("aspectmode",f?"manual":"auto");f||(t.aspectratio=e.aspectratio={x:1,y:1,z:1},"manual"===p&&(e.aspectmode="auto"),t.aspectmode=e.aspectmode);var d=c(n.fullData,"gl3d",n.id);s(t,e,{font:n.font,scene:n.id,data:d,bgColor:l,calendar:n.calendar,fullLayout:n.fullLayout}),i.getComponentMethod("annotations3d","handleDefaults")(t,e,n);var g=n.getDfltFromLayout("dragmode");if(!1!==g&&!g)if(g="orbit",t.camera&&t.camera.up){var m=t.camera.up.x,v=t.camera.up.y,y=t.camera.up.z;0!==y&&(m&&v&&y?y/Math.sqrt(m*m+v*v+y*y)>.999&&(g="turntable"):g="turntable")}else g="turntable";r("dragmode",g),r("hovermode",n.getDfltFromLayout("hovermode"))}e.exports=function(t,e,r){var a=e._basePlotModules.length>1;o(t,e,r,{type:"gl3d",attributes:l,handleDefaults:u,fullLayout:e,font:e.font,fullData:r,getDfltFromLayout:function(e){if(!a)return n.validate(t[e],l[e])?t[e]:void 0},paper_bgcolor:e.paper_bgcolor,calendar:e.calendar})}},{"../../../components/color":595,"../../../lib":728,"../../../registry":859,"../../get_data":813,"../../subplot_defaults":853,"./axis_defaults":821,"./layout_attributes":824}],824:[function(t,e,r){"use strict";var n=t("./axis_attributes"),a=t("../../domain").attributes,i=t("../../../lib/extend").extendFlat,o=t("../../../lib").counterRegex;function s(t,e,r){return{x:{valType:"number",dflt:t,editType:"camera"},y:{valType:"number",dflt:e,editType:"camera"},z:{valType:"number",dflt:r,editType:"camera"},editType:"camera"}}e.exports={_arrayAttrRegexps:[o("scene",".annotations",!0)],bgcolor:{valType:"color",dflt:"rgba(0,0,0,0)",editType:"plot"},camera:{up:i(s(0,0,1),{}),center:i(s(0,0,0),{}),eye:i(s(1.25,1.25,1.25),{}),projection:{type:{valType:"enumerated",values:["perspective","orthographic"],dflt:"perspective",editType:"calc"},editType:"calc"},editType:"camera"},domain:a({name:"scene",editType:"plot"}),aspectmode:{valType:"enumerated",values:["auto","cube","data","manual"],dflt:"auto",editType:"plot",impliedEdits:{"aspectratio.x":void 0,"aspectratio.y":void 0,"aspectratio.z":void 0}},aspectratio:{x:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},y:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},z:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},editType:"plot",impliedEdits:{aspectmode:"manual"}},xaxis:n,yaxis:n,zaxis:n,dragmode:{valType:"enumerated",values:["orbit","turntable","zoom","pan",!1],editType:"plot"},hovermode:{valType:"enumerated",values:["closest",!1],dflt:"closest",editType:"modebar"},uirevision:{valType:"any",editType:"none"},editType:"plot",_deprecated:{cameraposition:{valType:"info_array",editType:"camera"}}}},{"../../../lib":728,"../../../lib/extend":719,"../../domain":803,"./axis_attributes":820}],825:[function(t,e,r){"use strict";var n=t("../../../lib/str2rgbarray"),a=["xaxis","yaxis","zaxis"];function i(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}i.prototype.merge=function(t){for(var e=0;e<3;++e){var r=t[a[e]];r.visible?(this.enabled[e]=r.showspikes,this.colors[e]=n(r.spikecolor),this.drawSides[e]=r.spikesides,this.lineWidth[e]=r.spikethickness):(this.enabled[e]=!1,this.drawSides[e]=!1)}},e.exports=function(t){var e=new i;return e.merge(t),e}},{"../../../lib/str2rgbarray":751}],826:[function(t,e,r){"use strict";e.exports=function(t){for(var e=t.axesOptions,r=t.glplot.axesPixels,s=t.fullSceneLayout,l=[[],[],[]],c=0;c<3;++c){var u=s[i[c]];if(u._length=(r[c].hi-r[c].lo)*r[c].pixelsPerDataUnit/t.dataScale[c],Math.abs(u._length)===1/0||isNaN(u._length))l[c]=[];else{u._input_range=u.range.slice(),u.range[0]=r[c].lo/t.dataScale[c],u.range[1]=r[c].hi/t.dataScale[c],u._m=1/(t.dataScale[c]*r[c].pixelsPerDataUnit),u.range[0]===u.range[1]&&(u.range[0]-=1,u.range[1]+=1);var h=u.tickmode;if("auto"===u.tickmode){u.tickmode="linear";var f=u.nticks||a.constrain(u._length/40,4,9);n.autoTicks(u,Math.abs(u.range[1]-u.range[0])/f)}for(var p=n.calcTicks(u,{msUTC:!0}),d=0;d<p.length;++d)p[d].x=p[d].x*t.dataScale[c],"date"===u.type&&(p[d].text=p[d].text.replace(/\<br\>/g," "));l[c]=p,u.tickmode=h}}e.ticks=l;for(c=0;c<3;++c){o[c]=.5*(t.glplot.bounds[0][c]+t.glplot.bounds[1][c]);for(d=0;d<2;++d)e.bounds[d][c]=t.glplot.bounds[d][c]}t.contourLevels=function(t){for(var e=new Array(3),r=0;r<3;++r){for(var n=t[r],a=new Array(n.length),i=0;i<n.length;++i)a[i]=n[i].x;e[r]=a}return e}(l)};var n=t("../../cartesian/axes"),a=t("../../../lib"),i=["xaxis","yaxis","zaxis"],o=[0,0,0]},{"../../../lib":728,"../../cartesian/axes":776}],827:[function(t,e,r){"use strict";function n(t,e){var r,n,a=[0,0,0,0];for(r=0;r<4;++r)for(n=0;n<4;++n)a[n]+=t[4*r+n]*e[r];return a}e.exports=function(t,e){return n(t.projection,n(t.view,n(t.model,[e[0],e[1],e[2],1])))}},{}],828:[function(t,e,r){"use strict";var n,a,i=t("gl-plot3d"),o=i.createCamera,s=i.createScene,l=t("webgl-context"),c=t("has-passive-events"),u=t("../../registry"),h=t("../../lib"),f=t("../../plots/cartesian/axes"),p=t("../../components/fx"),d=t("../../lib/str2rgbarray"),g=t("../../lib/show_no_webgl_msg"),m=t("./project"),v=t("./layout/convert"),y=t("./layout/spikes"),x=t("./layout/tick_marks"),b=t("is-mobile")({tablet:!0,featureDetect:!0});function _(t,e){var r=document.createElement("div"),n=t.container;this.graphDiv=t.graphDiv;var a=document.createElementNS("http://www.w3.org/2000/svg","svg");a.style.position="absolute",a.style.top=a.style.left="0px",a.style.width=a.style.height="100%",a.style["z-index"]=20,a.style["pointer-events"]="none",r.appendChild(a),this.svgContainer=a,r.id=t.id,r.style.position="absolute",r.style.top=r.style.left="0px",r.style.width=r.style.height="100%",n.appendChild(r),this.fullLayout=e,this.id=t.id||"scene",this.fullSceneLayout=e[this.id],this.plotArgs=[[],{},{}],this.axesOptions=v(e,e[this.id]),this.spikeOptions=y(e[this.id]),this.container=r,this.staticMode=!!t.staticPlot,this.pixelRatio=this.pixelRatio||t.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=u.getComponentMethod("annotations3d","convert"),this.drawAnnotations=u.getComponentMethod("annotations3d","draw"),this.initializeGLPlot()}var w=_.prototype;w.prepareOptions=function(){var t={canvas:this.canvas,gl:this.gl,glOptions:{preserveDrawingBuffer:b,premultipliedAlpha:!0,antialias:!0},container:this.container,axes:this.axesOptions,spikes:this.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:this.camera,pixelRatio:this.pixelRatio};if(this.staticMode){if(!(a||(n=document.createElement("canvas"),a=l({canvas:n,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}))))throw new Error("error creating static canvas/context for image server");t.gl=a,t.canvas=n}return t},w.tryCreatePlot=function(){var t=this.prepareOptions(),e=!0;try{this.glplot=s(t)}catch(r){if(this.staticMode)e=!1;else try{h.warn(["webgl setup failed possibly due to",b?"disabling":"enabling","preserveDrawingBuffer config.","The device may not be supported by is-mobile module!","Inverting preserveDrawingBuffer option in second attempt to create webgl scene."].join(" ")),b=t.glOptions.preserveDrawingBuffer=!t.glOptions.preserveDrawingBuffer,this.glplot=s(t)}catch(t){e=!1}}return e},w.initializeGLCamera=function(){var t=this.fullSceneLayout.camera,e="orthographic"===t.projection.type;this.camera=o(this.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:e,zoomMin:.01,zoomMax:100,mode:"orbit"})},w.initializeGLPlot=function(){var t=this;if(t.initializeGLCamera(),!t.tryCreatePlot())return g(t);t.traces={},t.make4thDimension();var e=t.graphDiv,r=e.layout,n=function(){var e={};return t.isCameraChanged(r)&&(e[t.id+".camera"]=t.getCamera()),t.isAspectChanged(r)&&(e[t.id+".aspectratio"]=t.glplot.getAspectratio(),"manual"!==r[t.id].aspectmode&&(t.fullSceneLayout.aspectmode=r[t.id].aspectmode=e[t.id+".aspectmode"]="manual")),e},a=function(t){if(!1!==t.fullSceneLayout.dragmode){var e=n();t.saveLayout(r),t.graphDiv.emit("plotly_relayout",e)}};return t.glplot.canvas.addEventListener("mouseup",(function(){a(t)})),t.glplot.canvas.addEventListener("wheel",(function(r){if(e._context._scrollZoom.gl3d){if(t.camera._ortho){var n=r.deltaX>r.deltaY?1.1:1/1.1,i=t.glplot.getAspectratio();t.glplot.setAspectratio({x:n*i.x,y:n*i.y,z:n*i.z})}a(t)}}),!!c&&{passive:!1}),t.glplot.canvas.addEventListener("mousemove",(function(){if(!1!==t.fullSceneLayout.dragmode&&0!==t.camera.mouseListener.buttons){var e=n();t.graphDiv.emit("plotly_relayouting",e)}})),t.staticMode||t.glplot.canvas.addEventListener("webglcontextlost",(function(r){e&&e.emit&&e.emit("plotly_webglcontextlost",{event:r,layer:t.id})}),!1),t.glplot.oncontextloss=function(){t.recoverContext()},t.glplot.onrender=function(){t.render()},!0},w.render=function(){var t,e=this,r=e.graphDiv,n=e.svgContainer,a=e.container.getBoundingClientRect(),i=a.width,o=a.height;n.setAttributeNS(null,"viewBox","0 0 "+i+" "+o),n.setAttributeNS(null,"width",i),n.setAttributeNS(null,"height",o),x(e),e.glplot.axes.update(e.axesOptions);for(var s,l=Object.keys(e.traces),c=null,u=e.glplot.selection,d=0;d<l.length;++d)"skip"!==(t=e.traces[l[d]]).data.hoverinfo&&t.handlePick(u)&&(c=t),t.setContourLevels&&t.setContourLevels();function g(t,r){var n=e.fullSceneLayout[t];return f.tickText(n,n.d2l(r),"hover").text}if(null!==c){var v=m(e.glplot.cameraParams,u.dataCoordinate);t=c.data;var y,b=r._fullData[t.index],_=u.index,w={xLabel:g("xaxis",u.traceCoordinate[0]),yLabel:g("yaxis",u.traceCoordinate[1]),zLabel:g("zaxis",u.traceCoordinate[2])},T=p.castHoverinfo(b,e.fullLayout,_),k=(T||"").split("+"),A=T&&"all"===T;b.hovertemplate||A||(-1===k.indexOf("x")&&(w.xLabel=void 0),-1===k.indexOf("y")&&(w.yLabel=void 0),-1===k.indexOf("z")&&(w.zLabel=void 0),-1===k.indexOf("text")&&(u.textLabel=void 0),-1===k.indexOf("name")&&(c.name=void 0));var M=[];"cone"===t.type||"streamtube"===t.type?(w.uLabel=g("xaxis",u.traceCoordinate[3]),(A||-1!==k.indexOf("u"))&&M.push("u: "+w.uLabel),w.vLabel=g("yaxis",u.traceCoordinate[4]),(A||-1!==k.indexOf("v"))&&M.push("v: "+w.vLabel),w.wLabel=g("zaxis",u.traceCoordinate[5]),(A||-1!==k.indexOf("w"))&&M.push("w: "+w.wLabel),w.normLabel=u.traceCoordinate[6].toPrecision(3),(A||-1!==k.indexOf("norm"))&&M.push("norm: "+w.normLabel),"streamtube"===t.type&&(w.divergenceLabel=u.traceCoordinate[7].toPrecision(3),(A||-1!==k.indexOf("divergence"))&&M.push("divergence: "+w.divergenceLabel)),u.textLabel&&M.push(u.textLabel),y=M.join("<br>")):"isosurface"===t.type||"volume"===t.type?(w.valueLabel=f.tickText(e._mockAxis,e._mockAxis.d2l(u.traceCoordinate[3]),"hover").text,M.push("value: "+w.valueLabel),u.textLabel&&M.push(u.textLabel),y=M.join("<br>")):y=u.textLabel;var S={x:u.traceCoordinate[0],y:u.traceCoordinate[1],z:u.traceCoordinate[2],data:b._input,fullData:b,curveNumber:b.index,pointNumber:_};p.appendArrayPointValue(S,b,_),t._module.eventData&&(S=b._module.eventData(S,u,b,{},_));var E={points:[S]};e.fullSceneLayout.hovermode&&p.loneHover({trace:b,x:(.5+.5*v[0]/v[3])*i,y:(.5-.5*v[1]/v[3])*o,xLabel:w.xLabel,yLabel:w.yLabel,zLabel:w.zLabel,text:y,name:c.name,color:p.castHoverOption(b,_,"bgcolor")||c.color,borderColor:p.castHoverOption(b,_,"bordercolor"),fontFamily:p.castHoverOption(b,_,"font.family"),fontSize:p.castHoverOption(b,_,"font.size"),fontColor:p.castHoverOption(b,_,"font.color"),nameLength:p.castHoverOption(b,_,"namelength"),textAlign:p.castHoverOption(b,_,"align"),hovertemplate:h.castOption(b,_,"hovertemplate"),hovertemplateLabels:h.extendFlat({},S,w),eventData:[S]},{container:n,gd:r}),u.buttons&&u.distance<5?r.emit("plotly_click",E):r.emit("plotly_hover",E),s=E}else p.loneUnhover(n),r.emit("plotly_unhover",s);e.drawAnnotations(e)},w.recoverContext=function(){var t=this;t.glplot.dispose();var e=function(){t.glplot.gl.isContextLost()?requestAnimationFrame(e):t.initializeGLPlot()?t.plot.apply(t,t.plotArgs):h.error("Catastrophic and unrecoverable WebGL error. Context lost.")};requestAnimationFrame(e)};var T=["xaxis","yaxis","zaxis"];function k(t,e,r){for(var n=t.fullSceneLayout,a=0;a<3;a++){var i=T[a],o=i.charAt(0),s=n[i],l=e[o],c=e[o+"calendar"],u=e["_"+o+"length"];if(h.isArrayOrTypedArray(l))for(var f,p=0;p<(u||l.length);p++)if(h.isArrayOrTypedArray(l[p]))for(var d=0;d<l[p].length;++d)f=s.d2l(l[p][d],0,c),!isNaN(f)&&isFinite(f)&&(r[0][a]=Math.min(r[0][a],f),r[1][a]=Math.max(r[1][a],f));else f=s.d2l(l[p],0,c),!isNaN(f)&&isFinite(f)&&(r[0][a]=Math.min(r[0][a],f),r[1][a]=Math.max(r[1][a],f));else r[0][a]=Math.min(r[0][a],0),r[1][a]=Math.max(r[1][a],u-1)}}w.plot=function(t,e,r){if(this.plotArgs=[t,e,r],!this.glplot.contextLost){var n,a,i,o,s,l,c=e[this.id],u=r[this.id];this.fullLayout=e,this.fullSceneLayout=c,this.axesOptions.merge(e,c),this.spikeOptions.merge(c),this.setViewport(c),this.updateFx(c.dragmode,c.hovermode),this.camera.enableWheel=this.graphDiv._context._scrollZoom.gl3d,this.glplot.setClearColor(d(c.bgcolor)),this.setConvert(s),t?Array.isArray(t)||(t=[t]):t=[];var h=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]];for(i=0;i<t.length;++i)!0===(n=t[i]).visible&&0!==n._length&&k(this,n,h);!function(t,e){for(var r=t.fullSceneLayout,n=r.annotations||[],a=0;a<3;a++)for(var i=T[a],o=i.charAt(0),s=r[i],l=0;l<n.length;l++){var c=n[l];if(c.visible){var u=s.r2l(c[o]);!isNaN(u)&&isFinite(u)&&(e[0][a]=Math.min(e[0][a],u),e[1][a]=Math.max(e[1][a],u))}}}(this,h);var f=[1,1,1];for(o=0;o<3;++o)h[1][o]===h[0][o]?f[o]=1:f[o]=1/(h[1][o]-h[0][o]);for(this.dataScale=f,this.convertAnnotations(this),i=0;i<t.length;++i)!0===(n=t[i]).visible&&0!==n._length&&((a=this.traces[n.uid])?a.data.type===n.type?a.update(n):(a.dispose(),a=n._module.plot(this,n),this.traces[n.uid]=a):(a=n._module.plot(this,n),this.traces[n.uid]=a),a.name=n.name);var p=Object.keys(this.traces);t:for(i=0;i<p.length;++i){for(o=0;o<t.length;++o)if(t[o].uid===p[i]&&!0===t[o].visible&&0!==t[o]._length)continue t;(a=this.traces[p[i]]).dispose(),delete this.traces[p[i]]}this.glplot.objects.sort((function(t,e){return t._trace.data.index-e._trace.data.index}));var g,m=[[0,0,0],[0,0,0]],v=[],y={};for(i=0;i<3;++i){if((l=(s=c[T[i]]).type)in y?(y[l].acc*=f[i],y[l].count+=1):y[l]={acc:f[i],count:1},s.autorange){m[0][i]=1/0,m[1][i]=-1/0;var x=this.glplot.objects,b=this.fullSceneLayout.annotations||[],_=s._name.charAt(0);for(o=0;o<x.length;o++){var w=x[o],A=w.bounds,M=w._trace.data._pad||0;"ErrorBars"===w.constructor.name&&s._lowerLogErrorBound?m[0][i]=Math.min(m[0][i],s._lowerLogErrorBound):m[0][i]=Math.min(m[0][i],A[0][i]/f[i]-M),m[1][i]=Math.max(m[1][i],A[1][i]/f[i]+M)}for(o=0;o<b.length;o++){var S=b[o];if(S.visible){var E=s.r2l(S[_]);m[0][i]=Math.min(m[0][i],E),m[1][i]=Math.max(m[1][i],E)}}if("rangemode"in s&&"tozero"===s.rangemode&&(m[0][i]=Math.min(m[0][i],0),m[1][i]=Math.max(m[1][i],0)),m[0][i]>m[1][i])m[0][i]=-1,m[1][i]=1;else{var C=m[1][i]-m[0][i];m[0][i]-=C/32,m[1][i]+=C/32}if("reversed"===s.autorange){var L=m[0][i];m[0][i]=m[1][i],m[1][i]=L}}else{var P=s.range;m[0][i]=s.r2l(P[0]),m[1][i]=s.r2l(P[1])}m[0][i]===m[1][i]&&(m[0][i]-=1,m[1][i]+=1),v[i]=m[1][i]-m[0][i],this.glplot.setBounds(i,{min:m[0][i]*f[i],max:m[1][i]*f[i]})}var I=c.aspectmode;if("cube"===I)g=[1,1,1];else if("manual"===I){var z=c.aspectratio;g=[z.x,z.y,z.z]}else{if("auto"!==I&&"data"!==I)throw new Error("scene.js aspectRatio was not one of the enumerated types");var O=[1,1,1];for(i=0;i<3;++i){var D=y[l=(s=c[T[i]]).type];O[i]=Math.pow(D.acc,1/D.count)/f[i]}g="data"===I||Math.max.apply(null,O)/Math.min.apply(null,O)<=4?O:[1,1,1]}c.aspectratio.x=u.aspectratio.x=g[0],c.aspectratio.y=u.aspectratio.y=g[1],c.aspectratio.z=u.aspectratio.z=g[2],this.glplot.setAspectratio(c.aspectratio),this.viewInitial.aspectratio||(this.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),this.viewInitial.aspectmode||(this.viewInitial.aspectmode=c.aspectmode);var R=c.domain||null,F=e._size||null;if(R&&F){var B=this.container.style;B.position="absolute",B.left=F.l+R.x[0]*F.w+"px",B.top=F.t+(1-R.y[1])*F.h+"px",B.width=F.w*(R.x[1]-R.x[0])+"px",B.height=F.h*(R.y[1]-R.y[0])+"px"}this.glplot.redraw()}},w.destroy=function(){this.glplot&&(this.camera.mouseListener.enabled=!1,this.container.removeEventListener("wheel",this.camera.wheelListener),this.camera=null,this.glplot.dispose(),this.container.parentNode.removeChild(this.container),this.glplot=null)},w.getCamera=function(){var t;return this.camera.view.recalcMatrix(this.camera.view.lastT()),{up:{x:(t=this.camera).up[0],y:t.up[1],z:t.up[2]},center:{x:t.center[0],y:t.center[1],z:t.center[2]},eye:{x:t.eye[0],y:t.eye[1],z:t.eye[2]},projection:{type:!0===t._ortho?"orthographic":"perspective"}}},w.setViewport=function(t){var e,r=t.camera;this.camera.lookAt.apply(this,[[(e=r).eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]),this.glplot.setAspectratio(t.aspectratio),"orthographic"===r.projection.type!==this.camera._ortho&&(this.glplot.redraw(),this.glplot.clearRGBA(),this.glplot.dispose(),this.initializeGLPlot())},w.isCameraChanged=function(t){var e=this.getCamera(),r=h.nestedProperty(t,this.id+".camera").get();function n(t,e,r,n){var a=["up","center","eye"],i=["x","y","z"];return e[a[r]]&&t[a[r]][i[n]]===e[a[r]][i[n]]}var a=!1;if(void 0===r)a=!0;else{for(var i=0;i<3;i++)for(var o=0;o<3;o++)if(!n(e,r,i,o)){a=!0;break}(!r.projection||e.projection&&e.projection.type!==r.projection.type)&&(a=!0)}return a},w.isAspectChanged=function(t){var e=this.glplot.getAspectratio(),r=h.nestedProperty(t,this.id+".aspectratio").get();return void 0===r||r.x!==e.x||r.y!==e.y||r.z!==e.z},w.saveLayout=function(t){var e,r,n,a,i,o,s=this.fullLayout,l=this.isCameraChanged(t),c=this.isAspectChanged(t),f=l||c;if(f){var p={};if(l&&(e=this.getCamera(),n=(r=h.nestedProperty(t,this.id+".camera")).get(),p[this.id+".camera"]=n),c&&(a=this.glplot.getAspectratio(),o=(i=h.nestedProperty(t,this.id+".aspectratio")).get(),p[this.id+".aspectratio"]=o),u.call("_storeDirectGUIEdit",t,s._preGUI,p),l)r.set(e),h.nestedProperty(s,this.id+".camera").set(e);if(c)i.set(a),h.nestedProperty(s,this.id+".aspectratio").set(a),this.glplot.redraw()}return f},w.updateFx=function(t,e){var r=this.camera;if(r)if("orbit"===t)r.mode="orbit",r.keyBindingMode="rotate";else if("turntable"===t){r.up=[0,0,1],r.mode="turntable",r.keyBindingMode="rotate";var n=this.graphDiv,a=n._fullLayout,i=this.fullSceneLayout.camera,o=i.up.x,s=i.up.y,l=i.up.z;if(l/Math.sqrt(o*o+s*s+l*l)<.999){var c=this.id+".camera.up",f={x:0,y:0,z:1},p={};p[c]=f;var d=n.layout;u.call("_storeDirectGUIEdit",d,a._preGUI,p),i.up=f,h.nestedProperty(d,c).set(f)}}else r.keyBindingMode=t;this.fullSceneLayout.hovermode=e},w.toImage=function(t){t||(t="png"),this.staticMode&&this.container.appendChild(n),this.glplot.redraw();var e=this.glplot.gl,r=e.drawingBufferWidth,a=e.drawingBufferHeight;e.bindFramebuffer(e.FRAMEBUFFER,null);var i=new Uint8Array(r*a*4);e.readPixels(0,0,r,a,e.RGBA,e.UNSIGNED_BYTE,i),function(t,e,r){for(var n=0,a=r-1;n<a;++n,--a)for(var i=0;i<e;++i)for(var o=0;o<4;++o){var s=4*(e*n+i)+o,l=4*(e*a+i)+o,c=t[s];t[s]=t[l],t[l]=c}}(i,r,a),function(t,e,r){for(var n=0;n<r;++n)for(var a=0;a<e;++a){var i=4*(e*n+a),o=t[i+3];if(o>0)for(var s=255/o,l=0;l<3;++l)t[i+l]=Math.min(s*t[i+l],255)}}(i,r,a);var o=document.createElement("canvas");o.width=r,o.height=a;var s,l=o.getContext("2d"),c=l.createImageData(r,a);switch(c.data.set(i),l.putImageData(c,0,0),t){case"jpeg":s=o.toDataURL("image/jpeg");break;case"webp":s=o.toDataURL("image/webp");break;default:s=o.toDataURL("image/png")}return this.staticMode&&this.container.removeChild(n),s},w.setConvert=function(){for(var t=0;t<3;t++){var e=this.fullSceneLayout[T[t]];f.setConvert(e,this.fullLayout),e.setScale=h.noop}},w.make4thDimension=function(){var t=this.graphDiv._fullLayout;this._mockAxis={type:"linear",showexponent:"all",exponentformat:"B"},f.setConvert(this._mockAxis,t)},e.exports=_},{"../../components/fx":635,"../../lib":728,"../../lib/show_no_webgl_msg":749,"../../lib/str2rgbarray":751,"../../plots/cartesian/axes":776,"../../registry":859,"./layout/convert":822,"./layout/spikes":825,"./layout/tick_marks":826,"./project":827,"gl-plot3d":296,"has-passive-events":410,"is-mobile":420,"webgl-context":558}],829:[function(t,e,r){"use strict";e.exports=function(t,e,r,n){n=n||t.length;for(var a=new Array(n),i=0;i<n;i++)a[i]=[t[i],e[i],r[i]];return a}},{}],830:[function(t,e,r){"use strict";var n=t("./font_attributes"),a=t("./animation_attributes"),i=t("../components/color/attributes"),o=t("../components/shapes/draw_newshape/attributes"),s=t("./pad_attributes"),l=t("../lib/extend").extendFlat,c=n({editType:"calc"});c.family.dflt='"Open Sans", verdana, arial, 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strict";var n={"open-street-map":{id:"osm",version:8,sources:{"plotly-osm-tiles":{type:"raster",attribution:'<a href="http://www.openstreetmap.org/about/" target="_blank">\xa9 OpenStreetMap</a>',tiles:["https://a.tile.openstreetmap.org/{z}/{x}/{y}.png","https://b.tile.openstreetmap.org/{z}/{x}/{y}.png"],tileSize:256}},layers:[{id:"plotly-osm-tiles",type:"raster",source:"plotly-osm-tiles",minzoom:0,maxzoom:22}]},"white-bg":{id:"white-bg",version:8,sources:{},layers:[{id:"white-bg",type:"background",paint:{"background-color":"#FFFFFF"},minzoom:0,maxzoom:22}]},"carto-positron":{id:"carto-positron",version:8,sources:{"plotly-carto-positron":{type:"raster",attribution:'<a href="https://carto.com/" target="_blank">\xa9 CARTO</a>',tiles:["https://cartodb-basemaps-c.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png"],tileSize:256}},layers:[{id:"plotly-carto-positron",type:"raster",source:"plotly-carto-positron",minzoom:0,maxzoom:22}]},"carto-darkmatter":{id:"carto-darkmatter",version:8,sources:{"plotly-carto-darkmatter":{type:"raster",attribution:'<a href="https://carto.com/" target="_blank">\xa9 CARTO</a>',tiles:["https://cartodb-basemaps-c.global.ssl.fastly.net/dark_all/{z}/{x}/{y}.png"],tileSize:256}},layers:[{id:"plotly-carto-darkmatter",type:"raster",source:"plotly-carto-darkmatter",minzoom:0,maxzoom:22}]},"stamen-terrain":{id:"stamen-terrain",version:8,sources:{"plotly-stamen-terrain":{type:"raster",attribution:'Map tiles by <a href="http://stamen.com">Stamen Design</a>, under <a href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a> | Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, under <a 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href="http://creativecommons.org/licenses/by/3.0">CC BY 3.0</a> | Data by <a href="http://openstreetmap.org">OpenStreetMap</a>, under <a href="http://creativecommons.org/licenses/by-sa/3.0">CC BY SA</a>.',tiles:["https://stamen-tiles.a.ssl.fastly.net/watercolor/{z}/{x}/{y}.png"],tileSize:256}},layers:[{id:"plotly-stamen-watercolor",type:"raster",source:"plotly-stamen-watercolor",minzoom:0,maxzoom:22}]}},a=Object.keys(n);e.exports={requiredVersion:"1.10.1",styleUrlPrefix:"mapbox://styles/mapbox/",styleUrlSuffix:"v9",styleValuesMapbox:["basic","streets","outdoors","light","dark","satellite","satellite-streets"],styleValueDflt:"basic",stylesNonMapbox:n,styleValuesNonMapbox:a,traceLayerPrefix:"plotly-trace-layer-",layoutLayerPrefix:"plotly-layout-layer-",wrongVersionErrorMsg:["Your custom plotly.js bundle is not using the correct mapbox-gl version","Please install mapbox-gl@1.10.1."].join("\n"),noAccessTokenErrorMsg:["Missing Mapbox access token.","Mapbox trace type require a Mapbox access 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a=this,o=a.map,s=e[this.id];a.rejectOnError(n);var l=[],c=T(s.style);JSON.stringify(a.styleObj)!==JSON.stringify(c)&&(a.styleObj=c,o.setStyle(c.style),a.traceHash={},l.push(new Promise((function(t){o.once("styledata",t)})))),l=l.concat(i.fetchTraceGeoData(t)),Promise.all(l).then((function(){a.fillBelowLookup(t,e),a.updateData(t),a.updateLayout(e),a.resolveOnRender(r)})).catch(n)},_.fillBelowLookup=function(t,e){var r,n,a=e[this.id].layers,i=this.belowLookup={},o=!1;for(r=0;r<t.length;r++){var s=t[r][0].trace,l=s._module;"string"==typeof s.below?n=s.below:l.getBelow&&(n=l.getBelow(s,this)),""===n&&(o=!0),i["trace-"+s.uid]=n||""}for(r=0;r<a.length;r++){var c=a[r];n="string"==typeof c.below?c.below:o?"traces":"",i["layout-"+r]=n}var u,h,f={};for(u in i)f[n=i[u]]?f[n].push(u):f[n]=[u];for(n in f){var 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n=t("d3"),a=t("../../../lib").extendDeepAll,i=t("../../../constants/alignment").MID_SHIFT,o=e.exports={version:"0.2.2"};o.Axis=function(){var t,e,r,s,l={data:[],layout:{}},c={},u={},h=n.dispatch("hover"),f={};return f.render=function(c){return function(c){e=c||e;var h=l.data,f=l.layout;("string"==typeof e||e.nodeName)&&(e=n.select(e)),e.datum(h).each((function(e,l){var c=e.slice();u={data:o.util.cloneJson(c),layout:o.util.cloneJson(f)};var h=0;c.forEach((function(t,e){t.color||(t.color=f.defaultColorRange[h],h=(h+1)%f.defaultColorRange.length),t.strokeColor||(t.strokeColor="LinePlot"===t.geometry?t.color:n.rgb(t.color).darker().toString()),u.data[e].color=t.color,u.data[e].strokeColor=t.strokeColor,u.data[e].strokeDash=t.strokeDash,u.data[e].strokeSize=t.strokeSize}));var p=c.filter((function(t,e){var r=t.visible;return"undefined"==typeof r||!0===r})),d=!1,g=p.map((function(t,e){return d=d||"undefined"!=typeof t.groupId,t}));if(d){var 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n=t.map((function(t,e){return a(o[r].defaultConfig(),t)}));o[r]().config(n)()}))}var at,it,ot=t.select(".guides-group"),st=t.select(".tooltips-group"),lt=o.tooltipPanel().config({container:st,fontSize:8})(),ct=o.tooltipPanel().config({container:st,fontSize:8})(),ut=o.tooltipPanel().config({container:st,hasTick:!0})();if(!k){var ht=ot.select("line").attr({x1:0,y1:0,y2:0}).style({stroke:"grey","pointer-events":"none"});R.on("mousemove.angular-guide",(function(t,e){var r=o.util.getMousePos(Y).angle;ht.attr({x2:-x,transform:"rotate("+r+")"}).style({opacity:.5});var n=(r+180+360-f.orientation)%360;at=s.invert(n);var a=o.util.convertToCartesian(x+12,r+180);lt.text(o.util.round(at)).move([a[0]+_[0],a[1]+_[1]])})).on("mouseout.angular-guide",(function(t,e){ot.select("line").style({opacity:0})}))}var ft=ot.select("circle").style({stroke:"grey",fill:"none"});R.on("mousemove.radial-guide",(function(t,e){var 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y=f.select(".legend-marks").selectAll("path.legend-mark").data(o);y.enter().append("path").classed("legend-mark",!0),y.attr({transform:function(t,e){return"translate("+[c/2,m(e)+c/2]+")"},d:function(t,e){var r,a,i,o=t.symbol;return i=3*(a=c),"line"===(r=o)?"M"+[[-a/2,-a/12],[a/2,-a/12],[a/2,a/12],[-a/2,a/12]]+"Z":-1!=n.svg.symbolTypes.indexOf(r)?n.svg.symbol().type(r).size(i)():n.svg.symbol().type("square").size(i)()},fill:function(t,e){return g(e)}}),y.exit().remove()}var x=n.svg.axis().scale(m).orient("right"),b=f.select("g.legend-axis").attr({transform:"translate("+[u?e.colorBandWidth:c,c/2]+")"}).call(x);return b.selectAll(".domain").style({fill:"none",stroke:"none"}),b.selectAll("line").style({fill:"none",stroke:u?e.textColor:"none"}),b.selectAll("text").style({fill:e.textColor,"font-size":e.fontSize}).text((function(t,e){return o[e].name})),r}return r.config=function(e){return arguments.length?(a(t,e),this):t},n.rebind(r,e,"on"),r},o.Legend.defaultConfig=function(t,e){return{data:["a","b","c"],legendConfig:{elements:[{symbol:"line",color:"red"},{symbol:"square",color:"yellow"},{symbol:"diamond",color:"limegreen"}],height:150,colorBandWidth:30,fontSize:12,container:"body",isContinuous:null,textColor:"grey",reverseOrder:!1}}},o.tooltipPanel=function(){var t,e,r,i={container:null,hasTick:!1,fontSize:12,color:"white",padding:5},s="tooltip-"+o.tooltipPanel.uid++,l=10,c=function(){var n=(t=i.container.selectAll("g."+s).data([0])).enter().append("g").classed(s,!0).style({"pointer-events":"none",display:"none"});return r=n.append("path").style({fill:"white","fill-opacity":.9}).attr({d:"M0 0"}),e=n.append("text").attr({dx:i.padding+l,dy:.3*+i.fontSize}),c};return c.text=function(a){var o=n.hsl(i.color).l,s=o>=.5?"#aaa":"white",u=o>=.5?"black":"white",h=a||"";e.style({fill:u,"font-size":i.fontSize+"px"}).text(h);var f=i.padding,p=e.node().getBBox(),d={fill:i.color,stroke:s,"stroke-width":"2px"},g=p.width+2*f+l,m=p.height+2*f;return r.attr({d:"M"+[[l,-m/2],[l,-m/4],[i.hasTick?0:l,0],[l,m/4],[l,m/2],[g,m/2],[g,-m/2]].join("L")+"Z"}).style(d),t.attr({transform:"translate("+[l,-m/2+2*f]+")"}),t.style({display:"block"}),c},c.move=function(e){if(t)return t.attr({transform:"translate("+[e[0],e[1]]+")"}).style({display:"block"}),c},c.hide=function(){if(t)return t.style({display:"none"}),c},c.show=function(){if(t)return t.style({display:"block"}),c},c.config=function(t){return a(i,t),c},c},o.tooltipPanel.uid=1,o.adapter={},o.adapter.plotly=function(){var t={convert:function(t,e){var r={};if(t.data&&(r.data=t.data.map((function(t,r){var n=a({},t);return[[n,["marker","color"],["color"]],[n,["marker","opacity"],["opacity"]],[n,["marker","line","color"],["strokeColor"]],[n,["marker","line","dash"],["strokeDash"]],[n,["marker","line","width"],["strokeSize"]],[n,["marker","symbol"],["dotType"]],[n,["marker","size"],["dotSize"]],[n,["marker","barWidth"],["barWidth"]],[n,["line","interpolation"],["lineInterpolation"]],[n,["showlegend"],["visibleInLegend"]]].forEach((function(t,r){o.util.translator.apply(null,t.concat(e))})),e||delete n.marker,e&&delete n.groupId,e?("LinePlot"===n.geometry?(n.type="scatter",!0===n.dotVisible?(delete n.dotVisible,n.mode="lines+markers"):n.mode="lines"):"DotPlot"===n.geometry?(n.type="scatter",n.mode="markers"):"AreaChart"===n.geometry?n.type="area":"BarChart"===n.geometry&&(n.type="bar"),delete 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s=a({},t.layout);if([[s,["plot_bgcolor"],["backgroundColor"]],[s,["showlegend"],["showLegend"]],[s,["radialaxis"],["radialAxis"]],[s,["angularaxis"],["angularAxis"]],[s.angularaxis,["showline"],["gridLinesVisible"]],[s.angularaxis,["showticklabels"],["labelsVisible"]],[s.angularaxis,["nticks"],["ticksCount"]],[s.angularaxis,["tickorientation"],["tickOrientation"]],[s.angularaxis,["ticksuffix"],["ticksSuffix"]],[s.angularaxis,["range"],["domain"]],[s.angularaxis,["endpadding"],["endPadding"]],[s.radialaxis,["showline"],["gridLinesVisible"]],[s.radialaxis,["tickorientation"],["tickOrientation"]],[s.radialaxis,["ticksuffix"],["ticksSuffix"]],[s.radialaxis,["range"],["domain"]],[s.angularAxis,["showline"],["gridLinesVisible"]],[s.angularAxis,["showticklabels"],["labelsVisible"]],[s.angularAxis,["nticks"],["ticksCount"]],[s.angularAxis,["tickorientation"],["tickOrientation"]],[s.angularAxis,["ticksuffix"],["ticksSuffix"]],[s.angularAxis,["range"],["domain"]],[s.angularAxis,["endpadding"],["endPadding"]],[s.radialAxis,["showline"],["gridLinesVisible"]],[s.radialAxis,["tickorientation"],["tickOrientation"]],[s.radialAxis,["ticksuffix"],["ticksSuffix"]],[s.radialAxis,["range"],["domain"]],[s.font,["outlinecolor"],["outlineColor"]],[s.legend,["traceorder"],["reverseOrder"]],[s,["labeloffset"],["labelOffset"]],[s,["defaultcolorrange"],["defaultColorRange"]]].forEach((function(t,r){o.util.translator.apply(null,t.concat(e))})),e?("undefined"!=typeof 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r=t._fullLayout,n="clip"+r._uid+e;this.clipIds.forTraces=n+"-for-traces",this.clipPaths.forTraces=r._clips.append("clipPath").attr("id",this.clipIds.forTraces),this.clipPaths.forTraces.append("path"),this.framework=r._polarlayer.append("g").attr("class",e),this.radialTickLayout=null,this.angularTickLayout=null}var I=P.prototype;function z(t){var e=t.ticks+String(t.ticklen)+String(t.showticklabels);return"side"in t&&(e+=t.side),e}function O(t,e){return e[o.findIndexOfMin(e,(function(e){return o.angleDist(t,e)}))]}function D(t,e,r){return e?(t.attr("display",null),t.attr(r)):t&&t.attr("display","none"),t}function R(t,e){return"translate("+t+","+e+")"}function F(t){return"rotate("+t+")"}e.exports=function(t,e){return new P(t,e)},I.plot=function(t,e){var r=e[this.id];this._hasClipOnAxisFalse=!1;for(var 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e,r,n,a,i=t[0],o=t[1]-i,s=E(i,360),l=s+o,c=Math.cos(C(s)),u=Math.sin(C(s)),h=Math.cos(C(l)),f=Math.sin(C(l));a=s<=90&&l>=90||s>90&&l>=450?1:u<=0&&f<=0?0:Math.max(u,f);e=s<=180&&l>=180||s>180&&l>=540?-1:c>=0&&h>=0?0:Math.min(c,h);r=s<=270&&l>=270||s>270&&l>=630?-1:u>=0&&f>=0?0:Math.min(u,f);n=l>=360?1:c<=0&&h<=0?0:Math.max(c,h);return[e,r,n,a]}(f),x=y[2]-y[0],b=y[3]-y[1],_=h/u,w=Math.abs(b/x);_>w?(p=u,v=(h-(d=u*w))/n.h/2,g=[o[0],o[1]],m=[c[0]+v,c[1]-v]):(d=h,v=(u-(p=h/w))/n.w/2,g=[o[0]+v,o[1]-v],m=[c[0],c[1]]),this.xLength2=p,this.yLength2=d,this.xDomain2=g,this.yDomain2=m;var T=this.xOffset2=n.l+n.w*g[0],k=this.yOffset2=n.t+n.h*(1-m[1]),A=this.radius=p/x,M=this.innerRadius=e.hole*A,S=this.cx=T-A*y[0],L=this.cy=k+A*y[3],P=this.cxx=S-T,I=this.cyy=L-k;this.radialAxis=this.mockAxis(t,e,a,{_id:"x",side:{counterclockwise:"top",clockwise:"bottom"}[a.side],domain:[M/n.w,A/n.w]}),this.angularAxis=this.mockAxis(t,e,i,{side:"right",domain:[0,Math.PI],autorange:!1}),this.doAutoRange(t,e),this.updateAngularAxis(t,e),this.updateRadialAxis(t,e),this.updateRadialAxisTitle(t,e),this.xaxis=this.mockCartesianAxis(t,e,{_id:"x",domain:g}),this.yaxis=this.mockCartesianAxis(t,e,{_id:"y",domain:m});var z=this.pathSubplot();this.clipPaths.forTraces.select("path").attr("d",z).attr("transform",R(P,I)),r.frontplot.attr("transform",R(T,k)).call(l.setClipUrl,this._hasClipOnAxisFalse?null:this.clipIds.forTraces,this.gd),r.bg.attr("d",z).attr("transform",R(S,L)).call(s.fill,e.bgcolor)},I.mockAxis=function(t,e,r,n){var a=o.extendFlat({},r,n);return 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m=function(t){return"translate("+(d.l2p(t.x)+l)+",0)"},v=z(f);if(r.radialTickLayout!==v&&(a["radial-axis"].selectAll(".xtick").remove(),r.radialTickLayout=v),g){d.setScale();var y=u.calcTicks(d),x=u.clipEnds(d,y),b=u.getTickSigns(d)[2];u.drawTicks(n,d,{vals:y,layer:a["radial-axis"],path:u.makeTickPath(d,0,b),transFn:m,crisp:!1}),u.drawGrid(n,d,{vals:x,layer:a["radial-grid"],path:function(t){return r.pathArc(d.r2p(t.x)+l)},transFn:o.noop,crisp:!1}),u.drawLabels(n,d,{vals:y,layer:a["radial-axis"],transFn:m,labelFns:u.makeLabelFns(d,0)})}var _=r.radialAxisAngle=r.vangles?L(O(C(f.angle),r.vangles)):f.angle,w=R(c,h),T=w+F(-_);D(a["radial-axis"],g&&(f.showticklabels||f.ticks),{transform:T}),D(a["radial-grid"],g&&f.showgrid,{transform:w}),D(a["radial-line"].select("line"),g&&f.showline,{x1:l,y1:0,x2:i,y2:0,transform:T}).attr("stroke-width",f.linewidth).call(s.stroke,f.linecolor)},I.updateRadialAxisTitle=function(t,e,r){var n=this.gd,a=this.radius,i=this.cx,o=this.cy,s=e.radialaxis,c=this.id+"title",u=void 0!==r?r:this.radialAxisAngle,h=C(u),f=Math.cos(h),p=Math.sin(h),d=0;if(s.title){var g=l.bBox(this.layers["radial-axis"].node()).height,m=s.title.font.size;d="counterclockwise"===s.side?-g-.4*m:g+.8*m}this.layers["radial-axis-title"]=v.draw(n,c,{propContainer:s,propName:this.id+".radialaxis.title",placeholder:S(n,"Click to enter radial axis title"),attributes:{x:i+a/2*f+d*p,y:o-a/2*p+d*f,"text-anchor":"middle"},transform:{rotate:-u}})},I.updateAngularAxis=function(t,e){var r=this,n=r.gd,a=r.layers,i=r.radius,l=r.innerRadius,c=r.cx,h=r.cy,f=e.angularaxis,p=r.angularAxis;r.fillViewInitialKey("angularaxis.rotation",f.rotation),p.setGeometry(),p.setScale();var d=function(t){return p.t2g(t.x)};"linear"===p.type&&"radians"===p.thetaunit&&(p.tick0=L(p.tick0),p.dtick=L(p.dtick));var g=function(t){return R(c+i*Math.cos(t),h-i*Math.sin(t))},m=u.makeLabelFns(p,0).labelStandoff,v={xFn:function(t){var e=d(t);return 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z,O,D,F,B,N,j,V,U,q={element:I,gd:r,subplot:e.id,plotinfo:{id:e.id,xaxis:e.xaxis,yaxis:e.yaxis},xaxes:[e.xaxis],yaxes:[e.yaxis]};function H(t,e){return Math.sqrt(t*t+e*e)}function G(t,e){return H(t-v,e-_)}function Y(t,e){return Math.atan2(_-e,t-v)}function W(t,e){return[t*Math.cos(e),t*Math.sin(-e)]}function Z(t,r){if(0===t)return e.pathSector(2*L);var n=P/t,a=r-n,i=r+n,o=Math.max(0,Math.min(t,u)),s=o-L,l=o+L;return"M"+W(s,a)+"A"+[s,s]+" 0,0,0 "+W(s,i)+"L"+W(l,i)+"A"+[l,l]+" 0,0,1 "+W(l,a)+"Z"}function X(t,r,n){if(0===t)return e.pathSector(2*L);var a,i,o=W(t,r),s=W(t,n),l=S((o[0]+s[0])/2),c=S((o[1]+s[1])/2);if(l&&c){var u=c/l,h=-1/u,f=E(L,u,l,c);a=E(P,h,f[0][0],f[0][1]),i=E(P,h,f[1][0],f[1][1])}else{var p,d;c?(p=P,d=L):(p=L,d=P),a=[[l-p,c-d],[l+p,c-d]],i=[[l-p,c+d],[l+p,c+d]]}return"M"+a.join("L")+"L"+i.reverse().join("L")+"Z"}function J(t,e){return 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a=r._fullLayout.clickmode;if(d.removeZoombox(r),2===t){var o={};for(var s in e.viewInitial)o[e.id+"."+s]=e.viewInitial[s];r.emit("plotly_doubleclick",null),i.call("_guiRelayout",r,o)}a.indexOf("select")>-1&&1===t&&x(n,r,[e.xaxis],[e.yaxis],e.id,q),a.indexOf("event")>-1&&m.click(r,n,e.id)}q.prepFn=function(t,n,i){var o=r._fullLayout.dragmode,l=I.getBoundingClientRect();if(z=n-l.left,O=i-l.top,T){var c=M.findPolygonOffset(u,w[0],w[1],T);z+=v+c[0],O+=_+c[1]}switch(o){case"zoom":q.moveFn=T?tt:Q,q.clickFn=nt,q.doneFn=et,function(){D=null,F=null,B=e.pathSubplot(),N=!1;var t=r._fullLayout[e.id];j=a(t.bgcolor).getLuminance(),(V=d.makeZoombox(s,j,f,p,B)).attr("fill-rule","evenodd"),U=d.makeCorners(s,f,p),b(r)}();break;case"select":case"lasso":y(t,n,i,q,o)}},I.onmousemove=function(t){m.hover(r,t,e.id),r._fullLayout._lasthover=I,r._fullLayout._hoversubplot=e.id},I.onmouseout=function(t){r._dragging||g.unhover(r,t)},g.init(q)},I.updateRadialDrag=function(t,e,r){var a=this,s=a.gd,l=a.layers,c=a.radius,u=a.innerRadius,h=a.cx,f=a.cy,p=a.radialAxis,m=A.radialDragBoxSize,v=m/2;if(p.visible){var y,x,_,k=C(a.radialAxisAngle),M=p._rl,S=M[0],E=M[1],P=M[r],I=.75*(M[1]-M[0])/(1-e.hole)/c;r?(y=h+(c+v)*Math.cos(k),x=f-(c+v)*Math.sin(k),_="radialdrag"):(y=h+(u-v)*Math.cos(k),x=f-(u-v)*Math.sin(k),_="radialdrag-inner");var z,B,N,j=d.makeRectDragger(l,_,"crosshair",-v,-v,m,m),V={element:j,gd:s};D(n.select(j),p.visible&&u<c,{transform:R(y,x)}),V.prepFn=function(){z=null,B=null,N=null,V.moveFn=U,V.doneFn=q,b(s)},V.clampFn=function(t,e){return Math.sqrt(t*t+e*e)<A.MINDRAG&&(t=0,e=0),[t,e]},g.init(V)}function U(t,e){if(z)z(t,e);else{var n=[t,-e],i=[Math.cos(k),Math.sin(k)],l=Math.abs(o.dot(n,i)/Math.sqrt(o.dot(n,n)));isNaN(l)||(z=l<.5?H:G)}var c={};!function(t){null!==B?t[a.id+".radialaxis.angle"]=B:null!==N&&(t[a.id+".radialaxis.range["+r+"]"]=N)}(c),s.emit("plotly_relayouting",c)}function 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e=this,r=e.gd,a=e.layers,s=e.radius,c=e.angularAxis,u=e.cx,h=e.cy,f=e.cxx,p=e.cyy,m=A.angularDragBoxSize,v=d.makeDragger(a,"path","angulardrag","move"),y={element:v,gd:r};function x(t,e){return Math.atan2(p+m-e,t-f-m)}n.select(v).attr("d",e.pathAnnulus(s,s+m)).attr("transform",R(u,h)).call(_,"move");var k,M,S,E,C,P,I=a.frontplot.select(".scatterlayer").selectAll(".trace"),z=I.selectAll(".point"),O=I.selectAll(".textpoint");function D(t,s){var d=e.gd._fullLayout,g=d[e.id],m=x(k+t,M+s),v=L(m-P);if(E=S+v,a.frontplot.attr("transform",R(e.xOffset2,e.yOffset2)+F([-v,f,p])),e.vangles){C=e.radialAxisAngle+v;var y=R(u,h)+F(-v),b=R(u,h)+F(-C);a.bg.attr("transform",y),a["radial-grid"].attr("transform",y),a["radial-axis"].attr("transform",b),a["radial-line"].select("line").attr("transform",b),e.updateRadialAxisTitle(d,g,C)}else e.clipPaths.forTraces.select("path").attr("transform",R(f,p)+F(v));z.each((function(){var 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a,i=t.cd[0].trace.hoveron,o=[];return-1!==i.indexOf("boxes")&&(o=o.concat(l(t,e,r,n))),-1!==i.indexOf("points")&&(a=c(t,e,r)),"closest"===n?a?[a]:o:a?(o.push(a),o):o},hoverOnBoxes:l,hoverOnPoints:c}},{"../../components/color":595,"../../components/fx":635,"../../lib":728,"../../plots/cartesian/axes":776}],900:[function(t,e,r){"use 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o,s,l="h"===r.orientation,c=e.val,u=e.pos,h=!!u.rangebreaks,f=i.bPos,p=i.wdPos||0,d=i.bPosPxOffset||0,g=r.whiskerwidth||0,m=r.notched||!1,v=m?1-2*r.notchwidth:1;Array.isArray(i.bdPos)?(o=i.bdPos[0],s=i.bdPos[1]):(o=i.bdPos,s=i.bdPos);var y=t.selectAll("path.box").data("violin"!==r.type||r.box.visible?a.identity:[]);y.enter().append("path").style("vector-effect","non-scaling-stroke").attr("class","box"),y.exit().remove(),y.each((function(t){if(t.empty)return"M0,0Z";var e=u.c2l(t.pos+f,!0),i=u.l2p(e-o)+d,y=u.l2p(e+s)+d,x=h?(i+y)/2:u.l2p(e)+d,b=r.whiskerwidth,_=h?i*b+(1-b)*x:u.l2p(e-p)+d,w=h?y*b+(1-b)*x:u.l2p(e+p)+d,T=u.l2p(e-o*v)+d,k=u.l2p(e+s*v)+d,A=c.c2p(t.q1,!0),M=c.c2p(t.q3,!0),S=a.constrain(c.c2p(t.med,!0),Math.min(A,M)+1,Math.max(A,M)-1),E=void 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e,n,i=t.pts2,o=Math.max((t.max-t.min)/10,t.q3-t.q1),s=1e-9*o,h=.01*o,f=[],p=0;if(r.jitter){if(0===o)for(p=1,f=new Array(i.length),e=0;e<i.length;e++)f[e]=1;else for(e=0;e<i.length;e++){var d=Math.max(0,e-5),g=i[d].v,m=Math.min(i.length-1,e+5),v=i[m].v;"all"!==u&&(i[e].v<t.lf?v=Math.min(v,t.lf):g=Math.max(g,t.uf));var y=Math.sqrt(h*(m-d)/(v-g+s))||0;y=a.constrain(Math.abs(y),0,1),f.push(y),p=Math.max(y,p)}n=2*r.jitter/(p||1)}for(e=0;e<i.length;e++){var x=i[e],b=x.v,_=r.jitter?n*f[e]*(a.pseudoRandom()-.5):0,w=t.pos+c+l*(r.pointpos+_);"h"===r.orientation?(x.y=w,x.x=b):(x.x=w,x.y=b),"suspectedoutliers"===u&&b<t.uo&&b>t.lo&&(x.so=!0)}return i}));f.enter().append("path").classed("point",!0),f.exit().remove(),f.call(i.translatePoints,o,s)}function l(t,e,r,i){var o,s,l=e.val,c=e.pos,u=!!c.rangebreaks,h=i.bPos,f=i.bPosPxOffset||0,p=r.boxmean||(r.meanline||{}).visible;Array.isArray(i.bdPos)?(o=i.bdPos[0],s=i.bdPos[1]):(o=i.bdPos,s=i.bdPos);var 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n=t("./axis_defaults"),a=t("../../plot_api/plot_template");e.exports=function(t,e,r,i,o){i("a")||(i("da"),i("a0")),i("b")||(i("db"),i("b0")),function(t,e,r,i){["aaxis","baxis"].forEach((function(o){var s=o.charAt(0),l=t[o]||{},c=a.newContainer(e,o),u={tickfont:"x",id:s+"axis",letter:s,font:e.font,name:o,data:t[s],calendar:e.calendar,dfltColor:i,bgColor:r.paper_bgcolor,fullLayout:r};n(l,c,u),c._categories=c._categories||[],t[o]||"-"===l.type||(t[o]={type:l.type})}))}(t,e,r,o)}},{"../../plot_api/plot_template":766,"./axis_defaults":915}],911:[function(t,e,r){"use strict";var n=t("../../lib").isArrayOrTypedArray;e.exports=function(t){return function t(e,r){if(!n(e)||r>=10)return null;for(var a=1/0,i=-1/0,o=e.length,s=0;s<o;s++){var l=e[s];if(n(l)){var c=t(l,r+1);c&&(a=Math.min(c[0],a),i=Math.max(c[1],i))}else a=Math.min(l,a),i=Math.max(l,i)}return[a,i]}(t,0)}},{"../../lib":728}],912:[function(t,e,r){"use strict";var n=t("../../plots/font_attributes"),a=t("./axis_attributes"),i=t("../../components/color/attributes"),o=n({editType:"calc"});o.family.dflt='"Open Sans", verdana, arial, sans-serif',o.size.dflt=12,o.color.dflt=i.defaultLine,e.exports={carpet:{valType:"string",editType:"calc"},x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},a:{valType:"data_array",editType:"calc"},a0:{valType:"number",dflt:0,editType:"calc"},da:{valType:"number",dflt:1,editType:"calc"},b:{valType:"data_array",editType:"calc"},b0:{valType:"number",dflt:0,editType:"calc"},db:{valType:"number",dflt:1,editType:"calc"},cheaterslope:{valType:"number",dflt:1,editType:"calc"},aaxis:a,baxis:a,font:o,color:{valType:"color",dflt:i.defaultLine,editType:"plot"},transforms:void 0}},{"../../components/color/attributes":594,"../../plots/font_attributes":804,"./axis_attributes":914}],913:[function(t,e,r){"use strict";var n=t("../../lib").isArrayOrTypedArray;e.exports=function(t,e,r,a){var i,o,s,l,c,u,h,f,p,d,g,m,v,y=n(r)?"a":"b",x=("a"===y?t.aaxis:t.baxis).smoothing,b="a"===y?t.a2i:t.b2j,_="a"===y?r:a,w="a"===y?a:r,T="a"===y?e.a.length:e.b.length,k="a"===y?e.b.length:e.a.length,A=Math.floor("a"===y?t.b2j(w):t.a2i(w)),M="a"===y?function(e){return t.evalxy([],e,A)}:function(e){return t.evalxy([],A,e)};x&&(s=Math.max(0,Math.min(k-2,A)),l=A-s,o="a"===y?function(e,r){return t.dxydi([],e,s,r,l)}:function(e,r){return t.dxydj([],s,e,l,r)});var S=b(_[0]),E=b(_[1]),C=S<E?1:-1,L=1e-8*(E-S),P=C>0?Math.floor:Math.ceil,I=C>0?Math.ceil:Math.floor,z=C>0?Math.min:Math.max,O=C>0?Math.max:Math.min,D=P(S+L),R=I(E-L),F=[[h=M(S)]];for(i=D;i*C<R*C;i+=C)c=[],g=O(S,i),v=(m=z(E,i+C))-g,u=Math.max(0,Math.min(T-2,Math.floor(.5*(g+m)))),f=M(m),x&&(p=o(u,g-u),d=o(u,m-u),c.push([h[0]+p[0]/3*v,h[1]+p[1]/3*v]),c.push([f[0]-d[0]/3*v,f[1]-d[1]/3*v])),c.push(f),F.push(c),h=f;return F}},{"../../lib":728}],914:[function(t,e,r){"use 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n=t("../../plots/font_attributes"),a=t("../../components/color/attributes"),i=t("../../plots/cartesian/layout_attributes"),o=t("../../plot_api/edit_types").overrideAll;t("../../constants/docs").FORMAT_LINK,t("../../constants/docs").TIME_FORMAT_LINK;e.exports={color:{valType:"color",editType:"calc"},smoothing:{valType:"number",dflt:1,min:0,max:1.3,editType:"calc"},title:{text:{valType:"string",dflt:"",editType:"calc"},font:n({editType:"calc"}),offset:{valType:"number",dflt:10,editType:"calc"},editType:"calc"},type:{valType:"enumerated",values:["-","linear","date","category"],dflt:"-",editType:"calc"},autorange:{valType:"enumerated",values:[!0,!1,"reversed"],dflt:!0,editType:"calc"},rangemode:{valType:"enumerated",values:["normal","tozero","nonnegative"],dflt:"normal",editType:"calc"},range:{valType:"info_array",editType:"calc",items:[{valType:"any",editType:"calc"},{valType:"any",editType:"calc"}]},fixedrange:{valType:"boolean",dflt:!1,editType:"calc"},cheatertype:{valType:"enumerated",values:["index","value"],dflt:"value",editType:"calc"},tickmode:{valType:"enumerated",values:["linear","array"],dflt:"array",editType:"calc"},nticks:{valType:"integer",min:0,dflt:0,editType:"calc"},tickvals:{valType:"data_array",editType:"calc"},ticktext:{valType:"data_array",editType:"calc"},showticklabels:{valType:"enumerated",values:["start","end","both","none"],dflt:"start",editType:"calc"},tickfont:n({editType:"calc"}),tickangle:{valType:"angle",dflt:"auto",editType:"calc"},tickprefix:{valType:"string",dflt:"",editType:"calc"},showtickprefix:{valType:"enumerated",values:["all","first","last","none"],dflt:"all",editType:"calc"},ticksuffix:{valType:"string",dflt:"",editType:"calc"},showticksuffix:{valType:"enumerated",values:["all","first","last","none"],dflt:"all",editType:"calc"},showexponent:{valType:"enumerated",values:["all","first","last","none"],dflt:"all",editType:"calc"},exponentformat:{valType:"enumerated",values:["none","e","E","power","SI","B"],dflt:"B",editType:"calc"},separatethousands:{valType:"boolean",dflt:!1,editType:"calc"},tickformat:{valType:"string",dflt:"",editType:"calc"},tickformatstops:o(i.tickformatstops,"calc","from-root"),categoryorder:{valType:"enumerated",values:["trace","category ascending","category descending","array"],dflt:"trace",editType:"calc"},categoryarray:{valType:"data_array",editType:"calc"},labelpadding:{valType:"integer",dflt:10,editType:"calc"},labelprefix:{valType:"string",editType:"calc"},labelsuffix:{valType:"string",dflt:"",editType:"calc"},showline:{valType:"boolean",dflt:!1,editType:"calc"},linecolor:{valType:"color",dflt:a.defaultLine,editType:"calc"},linewidth:{valType:"number",min:0,dflt:1,editType:"calc"},gridcolor:{valType:"color",editType:"calc"},gridwidth:{valType:"number",min:0,dflt:1,editType:"calc"},showgrid:{valType:"boolean",dflt:!0,editType:"calc"},minorgridcount:{valType:"integer",min:0,dflt:0,editType:"calc"},minorgridwidth:{valType:"number",min:0,dflt:1,editType:"calc"},minorgridcolor:{valType:"color",dflt:a.lightLine,editType:"calc"},startline:{valType:"boolean",editType:"calc"},startlinecolor:{valType:"color",editType:"calc"},startlinewidth:{valType:"number",dflt:1,editType:"calc"},endline:{valType:"boolean",editType:"calc"},endlinewidth:{valType:"number",dflt:1,editType:"calc"},endlinecolor:{valType:"color",editType:"calc"},tick0:{valType:"number",min:0,dflt:0,editType:"calc"},dtick:{valType:"number",min:0,dflt:1,editType:"calc"},arraytick0:{valType:"integer",min:0,dflt:0,editType:"calc"},arraydtick:{valType:"integer",min:1,dflt:1,editType:"calc"},_deprecated:{title:{valType:"string",editType:"calc"},titlefont:n({editType:"calc"}),titleoffset:{valType:"number",dflt:10,editType:"calc"}},editType:"calc"}},{"../../components/color/attributes":594,"../../constants/docs":699,"../../plot_api/edit_types":759,"../../plots/cartesian/layout_attributes":790,"../../plots/font_attributes":804}],915:[function(t,e,r){"use 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n=t("../../components/colorscale/attributes"),a=t("../../plots/template_attributes").hovertemplateAttrs,i=t("../mesh3d/attributes"),o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat,l={x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},u:{valType:"data_array",editType:"calc"},v:{valType:"data_array",editType:"calc"},w:{valType:"data_array",editType:"calc"},sizemode:{valType:"enumerated",values:["scaled","absolute"],editType:"calc",dflt:"scaled"},sizeref:{valType:"number",editType:"calc",min:0},anchor:{valType:"enumerated",editType:"calc",values:["tip","tail","cm","center"],dflt:"cm"},text:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertemplate:a({editType:"calc"},{keys:["norm"]}),showlegend:s({},o.showlegend,{dflt:!1})};s(l,n("",{colorAttr:"u/v/w 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n=t("../../lib"),a=t("../../components/colorscale/defaults"),i=t("./attributes");e.exports=function(t,e,r,o){function s(r,a){return n.coerce(t,e,i,r,a)}var l=s("lon")||[],c=s("lat")||[],u=Math.min(l.length,c.length);u?(e._length=u,s("z"),s("radius"),s("below"),s("text"),s("hovertext"),s("hovertemplate"),a(t,e,o,s,{prefix:"",cLetter:"z"})):e.visible=!1}},{"../../components/colorscale/defaults":605,"../../lib":728,"./attributes":983}],987:[function(t,e,r){"use strict";e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.z=e.z,t}},{}],988:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../plots/cartesian/axes"),i=t("../scattermapbox/hover");e.exports=function(t,e,r){var o=i(t,e,r);if(o){var s=o[0],l=s.cd,c=l[0].trace,u=l[s.index];if(delete s.color,"z"in u){var h=s.subplot.mockAxis;s.z=u.z,s.zLabel=a.tickText(h,h.c2l(u.z),"hover").text}return s.extraText=function(t,e,r){if(t.hovertemplate)return;var 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n=t("../../lib"),a=t("./attributes"),i=t("../../plots/domain").defaults,o=t("../../plot_api/plot_template"),s=t("../../plots/array_container_defaults"),l=t("./constants.js"),c=t("../../plots/cartesian/tick_value_defaults"),u=t("../../plots/cartesian/tick_mark_defaults"),h=t("../../plots/cartesian/tick_label_defaults");function f(t,e){function r(r,i){return n.coerce(t,e,a.gauge.steps,r,i)}r("color"),r("line.color"),r("line.width"),r("range"),r("thickness")}e.exports={supplyDefaults:function(t,e,r,p){function d(r,i){return n.coerce(t,e,a,r,i)}i(e,p,d),d("mode"),e._hasNumber=-1!==e.mode.indexOf("number"),e._hasDelta=-1!==e.mode.indexOf("delta"),e._hasGauge=-1!==e.mode.indexOf("gauge");var g=d("value");e._range=[0,"number"==typeof g?1.5*g:1];var m,v,y,x,b,_,w=new Array(2);function T(t,e){return n.coerce(y,x,a.gauge,t,e)}function k(t,e){return 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0===e.delta.font.size&&(e.delta.font.size=(e._hasNumber?.5:1)*(m||l.defaultNumberFontSize),w[1]=!0),d("delta.reference",e.value),d("delta.relative"),d("delta.valueformat",e.delta.relative?"2%":""),d("delta.increasing.symbol"),d("delta.increasing.color"),d("delta.decreasing.symbol"),d("delta.decreasing.color"),d("delta.position"),v=e.delta.font.size),e._scaleNumbers=(!e._hasNumber||w[0])&&(!e._hasDelta||w[1])||!1,d("title.font.color",p.font.color),d("title.font.family",p.font.family),d("title.font.size",.25*(m||v||l.defaultNumberFontSize)),d("title.text"),e._hasGauge){(y=t.gauge)||(y={}),x=o.newContainer(e,"gauge"),T("shape"),(e._isBullet="bullet"===e.gauge.shape)||d("title.align","center"),(e._isAngular="angular"===e.gauge.shape)||d("align","center"),T("bgcolor",p.paper_bgcolor),T("borderwidth"),T("bordercolor"),T("bar.color"),T("bar.line.color"),T("bar.line.width"),T("bar.thickness",l.valueThickness*("bullet"===e.gauge.shape?.5:1)),s(y,x,{name:"steps",handleItemDefaults:f}),T("threshold.value"),T("threshold.thickness"),T("threshold.line.width"),T("threshold.line.color"),b={},y&&(b=y.axis||{}),_=o.newContainer(x,"axis"),k("visible"),e._range=k("range",e._range);var A={outerTicks:!0};c(b,_,k,"linear"),h(b,_,k,"linear",A),u(b,_,k,A)}else d("title.align","center"),d("align","center"),e._isAngular=e._isBullet=!1;e._length=null}}},{"../../lib":728,"../../plot_api/plot_template":766,"../../plots/array_container_defaults":772,"../../plots/cartesian/tick_label_defaults":797,"../../plots/cartesian/tick_mark_defaults":798,"../../plots/cartesian/tick_value_defaults":799,"../../plots/domain":803,"./attributes":1063,"./constants.js":1066}],1068:[function(t,e,r){"use strict";e.exports={moduleType:"trace",name:"indicator",basePlotModule:t("./base_plot"),categories:["svg","noOpacity","noHover"],animatable:!0,attributes:t("./attributes"),supplyDefaults:t("./defaults").supplyDefaults,calc:t("./calc").calc,plot:t("./plot"),meta:{}}},{"./attributes":1063,"./base_plot":1064,"./calc":1065,"./defaults":1067,"./plot":1069}],1069:[function(t,e,r){"use strict";var n=t("d3"),a=t("../../lib"),i=a.rad2deg,o=t("../../constants/alignment").MID_SHIFT,s=t("../../components/drawing"),l=t("./constants"),c=t("../../lib/svg_text_utils"),u=t("../../plots/cartesian/axes"),h=t("../../plots/cartesian/axis_defaults"),f=t("../../plots/cartesian/position_defaults"),p=t("../../plots/cartesian/layout_attributes"),d=t("../../components/color"),g={left:"start",center:"middle",right:"end"},m={left:0,center:.5,right:1},v=/[yzafpn\xb5mkMGTPEZY]/;function y(t){return t&&t.duration>0}function x(t){t.each((function(t){d.stroke(n.select(this),t.line.color)})).each((function(t){d.fill(n.select(this),t.color)})).style("stroke-width",(function(t){return t.line.width}))}function b(t,e,r){var n=t._fullLayout,i=a.extendFlat({type:"linear",ticks:"outside",range:r,showline:!0},e),o={type:"linear",_id:"x"+e._id},s={letter:"x",font:n.font,noHover:!0,noTickson:!0};function l(t,e){return a.coerce(i,o,p,t,e)}return h(i,o,l,s,n),f(i,o,l,s),o}function _(t,e){return"translate("+t+","+e+")"}function w(t,e,r){return[Math.min(e/t.width,r/t.height),t,e+"x"+r]}function T(t,e,r,a){var i=document.createElementNS("http://www.w3.org/2000/svg","text"),o=n.select(i);return o.text(t).attr("x",0).attr("y",0).attr("text-anchor",r).attr("data-unformatted",t).call(c.convertToTspans,a).call(s.font,e),s.bBox(o.node())}function k(t,e,r,n,i,o){var s="_cache"+e;t[s]&&t[s].key===i||(t[s]={key:i,value:r});var l=a.aggNums(o,null,[t[s].value,n],2);return t[s].value=l,l}e.exports=function(t,e,r,h){var f,p=t._fullLayout;y(r)&&h&&(f=h()),a.makeTraceGroups(p._indicatorlayer,e,"trace").each((function(e){var h,A,M,S,E,C=e[0].trace,L=n.select(this),P=C._hasGauge,I=C._isAngular,z=C._isBullet,O=C.domain,D={w:p._size.w*(O.x[1]-O.x[0]),h:p._size.h*(O.y[1]-O.y[0]),l:p._size.l+p._size.w*O.x[0],r:p._size.r+p._size.w*(1-O.x[1]),t:p._size.t+p._size.h*(1-O.y[1]),b:p._size.b+p._size.h*O.y[0]},R=D.l+D.w/2,F=D.t+D.h/2,B=Math.min(D.w/2,D.h),N=l.innerRadius*B,j=C.align||"center";if(A=F,P){if(I&&(h=R,A=F+B/2,M=function(t){return function(t,e){var r=Math.sqrt(t.width/2*(t.width/2)+t.height*t.height);return[e/r,t,e]}(t,.9*N)}),z){var V=l.bulletPadding,U=1-l.bulletNumberDomainSize+V;h=D.l+(U+(1-U)*m[j])*D.w,M=function(t){return w(t,(l.bulletNumberDomainSize-V)*D.w,D.h)}}}else h=D.l+m[j]*D.w,M=function(t){return w(t,D.w,D.h)};!function(t,e,r,i){var o,l,h,f=r[0].trace,p=i.numbersX,x=i.numbersY,w=f.align||"center",A=g[w],M=i.transitionOpts,S=i.onComplete,E=a.ensureSingle(e,"g","numbers"),C=[];f._hasNumber&&C.push("number");f._hasDelta&&(C.push("delta"),"left"===f.delta.position&&C.reverse());var L=E.selectAll("text").data(C);function P(e,r,n,a){if(!e.match("s")||n>=0==a>=0||r(n).slice(-1).match(v)||r(a).slice(-1).match(v))return r;var i=e.slice().replace("s","f").replace(/\d+/,(function(t){return parseInt(t)-1})),o=b(t,{tickformat:i});return function(t){return Math.abs(t)<1?u.tickText(o,t).text:r(t)}}L.enter().append("text"),L.attr("text-anchor",(function(){return A})).attr("class",(function(t){return t})).attr("x",null).attr("y",null).attr("dx",null).attr("dy",null),L.exit().remove();var I,z=f.mode+f.align;f._hasDelta&&(I=function(){var e=b(t,{tickformat:f.delta.valueformat},f._range);e.setScale(),u.prepTicks(e);var a=function(t){return u.tickText(e,t).text},i=function(t){return f.delta.relative?t.relativeDelta:t.delta},o=function(t,e){return 0===t||"number"!=typeof t||isNaN(t)?"-":(t>0?f.delta.increasing.symbol:f.delta.decreasing.symbol)+e(t)},h=function(t){return t.delta>=0?f.delta.increasing.color:f.delta.decreasing.color};void 0===f._deltaLastValue&&(f._deltaLastValue=i(r[0]));var p=E.select("text.delta");function g(){p.text(o(i(r[0]),a)).call(d.fill,h(r[0])).call(c.convertToTspans,t)}return p.call(s.font,f.delta.font).call(d.fill,h({delta:f._deltaLastValue})),y(M)?p.transition().duration(M.duration).ease(M.easing).tween("text",(function(){var t=n.select(this),e=i(r[0]),s=f._deltaLastValue,l=P(f.delta.valueformat,a,s,e),c=n.interpolateNumber(s,e);return f._deltaLastValue=e,function(e){t.text(o(c(e),l)),t.call(d.fill,h({delta:c(e)}))}})).each("end",(function(){g(),S&&S()})).each("interrupt",(function(){g(),S&&S()})):g(),l=T(o(i(r[0]),a),f.delta.font,A,t),p}(),z+=f.delta.position+f.delta.font.size+f.delta.font.family+f.delta.valueformat,z+=f.delta.increasing.symbol+f.delta.decreasing.symbol,h=l);f._hasNumber&&(!function(){var e=b(t,{tickformat:f.number.valueformat},f._range);e.setScale(),u.prepTicks(e);var a=function(t){return u.tickText(e,t).text},i=f.number.suffix,l=f.number.prefix,h=E.select("text.number");function p(){var e="number"==typeof r[0].y?l+a(r[0].y)+i:"-";h.text(e).call(s.font,f.number.font).call(c.convertToTspans,t)}y(M)?h.transition().duration(M.duration).ease(M.easing).each("end",(function(){p(),S&&S()})).each("interrupt",(function(){p(),S&&S()})).attrTween("text",(function(){var t=n.select(this),e=n.interpolateNumber(r[0].lastY,r[0].y);f._lastValue=r[0].y;var o=P(f.number.valueformat,a,r[0].lastY,r[0].y);return function(r){t.text(l+o(e(r))+i)}})):p(),o=T(l+a(r[0].y)+i,f.number.font,A,t)}(),z+=f.number.font.size+f.number.font.family+f.number.valueformat+f.number.suffix+f.number.prefix,h=o);if(f._hasDelta&&f._hasNumber){var O,D,R=[(o.left+o.right)/2,(o.top+o.bottom)/2],F=[(l.left+l.right)/2,(l.top+l.bottom)/2],B=.75*f.delta.font.size;"left"===f.delta.position&&(O=k(f,"deltaPos",0,-1*(o.width*m[f.align]+l.width*(1-m[f.align])+B),z,Math.min),D=R[1]-F[1],h={width:o.width+l.width+B,height:Math.max(o.height,l.height),left:l.left+O,right:o.right,top:Math.min(o.top,l.top+D),bottom:Math.max(o.bottom,l.bottom+D)}),"right"===f.delta.position&&(O=k(f,"deltaPos",0,o.width*(1-m[f.align])+l.width*m[f.align]+B,z,Math.max),D=R[1]-F[1],h={width:o.width+l.width+B,height:Math.max(o.height,l.height),left:o.left,right:l.right+O,top:Math.min(o.top,l.top+D),bottom:Math.max(o.bottom,l.bottom+D)}),"bottom"===f.delta.position&&(O=null,D=l.height,h={width:Math.max(o.width,l.width),height:o.height+l.height,left:Math.min(o.left,l.left),right:Math.max(o.right,l.right),top:o.bottom-o.height,bottom:o.bottom+l.height}),"top"===f.delta.position&&(O=null,D=o.top,h={width:Math.max(o.width,l.width),height:o.height+l.height,left:Math.min(o.left,l.left),right:Math.max(o.right,l.right),top:o.bottom-o.height-l.height,bottom:o.bottom}),I.attr({dx:O,dy:D})}(f._hasNumber||f._hasDelta)&&E.attr("transform",(function(){var t=i.numbersScaler(h);z+=t[2];var e,r=k(f,"numbersScale",1,t[0],z,Math.min);f._scaleNumbers||(r=1),e=f._isAngular?x-r*h.bottom:x-r*(h.top+h.bottom)/2,f._numbersTop=r*h.top+e;var n=h[w];"center"===w&&(n=(h.left+h.right)/2);var a=p-r*n;return _(a=k(f,"numbersTranslate",0,a,z,Math.max),e)+" scale("+r+")"}))}(t,L,e,{numbersX:h,numbersY:A,numbersScaler:M,transitionOpts:r,onComplete:f}),P&&(S={range:C.gauge.axis.range,color:C.gauge.bgcolor,line:{color:C.gauge.bordercolor,width:0},thickness:1},E={range:C.gauge.axis.range,color:"rgba(0, 0, 0, 0)",line:{color:C.gauge.bordercolor,width:C.gauge.borderwidth},thickness:1});var q=L.selectAll("g.angular").data(I?e:[]);q.exit().remove();var H=L.selectAll("g.angularaxis").data(I?e:[]);H.exit().remove(),I&&function(t,e,r,a){var s,l,c,h,f=r[0].trace,p=a.size,d=a.radius,g=a.innerRadius,m=a.gaugeBg,v=a.gaugeOutline,w=[p.l+p.w/2,p.t+p.h/2+d/2],T=a.gauge,k=a.layer,A=a.transitionOpts,M=a.onComplete,S=Math.PI/2;function E(t){var e=f.gauge.axis.range[0],r=(t-e)/(f.gauge.axis.range[1]-e)*Math.PI-S;return r<-S?-S:r>S?S:r}function C(t){return n.svg.arc().innerRadius((g+d)/2-t/2*(d-g)).outerRadius((g+d)/2+t/2*(d-g)).startAngle(-S)}function L(t){t.attr("d",(function(t){return C(t.thickness).startAngle(E(t.range[0])).endAngle(E(t.range[1]))()}))}T.enter().append("g").classed("angular",!0),T.attr("transform",_(w[0],w[1])),k.enter().append("g").classed("angularaxis",!0).classed("crisp",!0),k.selectAll("g.xangularaxistick,path,text").remove(),(s=b(t,f.gauge.axis)).type="linear",s.range=f.gauge.axis.range,s._id="xangularaxis",s.setScale();var P=function(t){return(s.range[0]-t.x)/(s.range[1]-s.range[0])*Math.PI+Math.PI},I={},z=u.makeLabelFns(s,0).labelStandoff;I.xFn=function(t){var e=P(t);return Math.cos(e)*z},I.yFn=function(t){var e=P(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(z+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*o)},I.anchorFn=function(t){var e=P(t),r=Math.cos(e);return Math.abs(r)<.1?"middle":r>0?"start":"end"},I.heightFn=function(t,e,r){var n=P(t);return-.5*(1+Math.sin(n))*r};var O=function(t){return _(w[0]+d*Math.cos(t),w[1]-d*Math.sin(t))};c=function(t){return O(P(t))};if(l=u.calcTicks(s),h=u.getTickSigns(s)[2],s.visible){h="inside"===s.ticks?-1:1;var D=(s.linewidth||1)/2;u.drawTicks(t,s,{vals:l,layer:k,path:"M"+h*D+",0h"+h*s.ticklen,transFn:function(t){var e=P(t);return O(e)+"rotate("+-i(e)+")"}}),u.drawLabels(t,s,{vals:l,layer:k,transFn:c,labelFns:I})}var R=[m].concat(f.gauge.steps),F=T.selectAll("g.bg-arc").data(R);F.enter().append("g").classed("bg-arc",!0).append("path"),F.select("path").call(L).call(x),F.exit().remove();var B=C(f.gauge.bar.thickness),N=T.selectAll("g.value-arc").data([f.gauge.bar]);N.enter().append("g").classed("value-arc",!0).append("path");var j=N.select("path");y(A)?(j.transition().duration(A.duration).ease(A.easing).each("end",(function(){M&&M()})).each("interrupt",(function(){M&&M()})).attrTween("d",(V=B,U=E(r[0].lastY),q=E(r[0].y),function(){var t=n.interpolate(U,q);return function(e){return V.endAngle(t(e))()}})),f._lastValue=r[0].y):j.attr("d","number"==typeof r[0].y?B.endAngle(E(r[0].y)):"M0,0Z");var V,U,q;j.call(x),N.exit().remove(),R=[];var H=f.gauge.threshold.value;H&&R.push({range:[H,H],color:f.gauge.threshold.color,line:{color:f.gauge.threshold.line.color,width:f.gauge.threshold.line.width},thickness:f.gauge.threshold.thickness});var G=T.selectAll("g.threshold-arc").data(R);G.enter().append("g").classed("threshold-arc",!0).append("path"),G.select("path").call(L).call(x),G.exit().remove();var Y=T.selectAll("g.gauge-outline").data([v]);Y.enter().append("g").classed("gauge-outline",!0).append("path"),Y.select("path").call(L).call(x),Y.exit().remove()}(t,0,e,{radius:B,innerRadius:N,gauge:q,layer:H,size:D,gaugeBg:S,gaugeOutline:E,transitionOpts:r,onComplete:f});var G=L.selectAll("g.bullet").data(z?e:[]);G.exit().remove();var Y=L.selectAll("g.bulletaxis").data(z?e:[]);Y.exit().remove(),z&&function(t,e,r,n){var a,i,o,s,c,h=r[0].trace,f=n.gauge,p=n.layer,g=n.gaugeBg,m=n.gaugeOutline,v=n.size,_=h.domain,w=n.transitionOpts,T=n.onComplete;f.enter().append("g").classed("bullet",!0),f.attr("transform","translate("+v.l+", "+v.t+")"),p.enter().append("g").classed("bulletaxis",!0).classed("crisp",!0),p.selectAll("g.xbulletaxistick,path,text").remove();var k=v.h,A=h.gauge.bar.thickness*k,M=_.x[0],S=_.x[0]+(_.x[1]-_.x[0])*(h._hasNumber||h._hasDelta?1-l.bulletNumberDomainSize:1);(a=b(t,h.gauge.axis))._id="xbulletaxis",a.domain=[M,S],a.setScale(),i=u.calcTicks(a),o=u.makeTransFn(a),s=u.getTickSigns(a)[2],c=v.t+v.h,a.visible&&(u.drawTicks(t,a,{vals:"inside"===a.ticks?u.clipEnds(a,i):i,layer:p,path:u.makeTickPath(a,c,s),transFn:o}),u.drawLabels(t,a,{vals:i,layer:p,transFn:o,labelFns:u.makeLabelFns(a,c)}));function E(t){t.attr("width",(function(t){return Math.max(0,a.c2p(t.range[1])-a.c2p(t.range[0]))})).attr("x",(function(t){return a.c2p(t.range[0])})).attr("y",(function(t){return.5*(1-t.thickness)*k})).attr("height",(function(t){return t.thickness*k}))}var C=[g].concat(h.gauge.steps),L=f.selectAll("g.bg-bullet").data(C);L.enter().append("g").classed("bg-bullet",!0).append("rect"),L.select("rect").call(E).call(x),L.exit().remove();var P=f.selectAll("g.value-bullet").data([h.gauge.bar]);P.enter().append("g").classed("value-bullet",!0).append("rect"),P.select("rect").attr("height",A).attr("y",(k-A)/2).call(x),y(w)?P.select("rect").transition().duration(w.duration).ease(w.easing).each("end",(function(){T&&T()})).each("interrupt",(function(){T&&T()})).attr("width",Math.max(0,a.c2p(Math.min(h.gauge.axis.range[1],r[0].y)))):P.select("rect").attr("width","number"==typeof r[0].y?Math.max(0,a.c2p(Math.min(h.gauge.axis.range[1],r[0].y))):0);P.exit().remove();var I=r.filter((function(){return h.gauge.threshold.value})),z=f.selectAll("g.threshold-bullet").data(I);z.enter().append("g").classed("threshold-bullet",!0).append("line"),z.select("line").attr("x1",a.c2p(h.gauge.threshold.value)).attr("x2",a.c2p(h.gauge.threshold.value)).attr("y1",(1-h.gauge.threshold.thickness)/2*k).attr("y2",(1-(1-h.gauge.threshold.thickness)/2)*k).call(d.stroke,h.gauge.threshold.line.color).style("stroke-width",h.gauge.threshold.line.width),z.exit().remove();var O=f.selectAll("g.gauge-outline").data([m]);O.enter().append("g").classed("gauge-outline",!0).append("rect"),O.select("rect").call(E).call(x),O.exit().remove()}(t,0,e,{gauge:G,layer:Y,size:D,gaugeBg:S,gaugeOutline:E,transitionOpts:r,onComplete:f});var W=L.selectAll("text.title").data(e);W.exit().remove(),W.enter().append("text").classed("title",!0),W.attr("text-anchor",(function(){return z?g.right:g[C.title.align]})).text(C.title.text).call(s.font,C.title.font).call(c.convertToTspans,t),W.attr("transform",(function(){var t,e=D.l+D.w*m[C.title.align],r=l.titlePadding,n=s.bBox(W.node());if(P){if(I)if(C.gauge.axis.visible)t=s.bBox(H.node()).top-r-n.bottom;else t=D.t+D.h/2-B/2-n.bottom-r;z&&(t=A-(n.top+n.bottom)/2,e=D.l-l.bulletPadding*D.w)}else t=C._numbersTop-r-n.bottom;return _(e,t)}))}))}},{"../../components/color":595,"../../components/drawing":617,"../../constants/alignment":697,"../../lib":728,"../../lib/svg_text_utils":752,"../../plots/cartesian/axes":776,"../../plots/cartesian/axis_defaults":778,"../../plots/cartesian/layout_attributes":790,"../../plots/cartesian/position_defaults":793,"./constants":1066,d3:164}],1070:[function(t,e,r){"use strict";var n=t("../../components/colorscale/attributes"),a=t("../../plots/template_attributes").hovertemplateAttrs,i=t("../mesh3d/attributes"),o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat,l=t("../../plot_api/edit_types").overrideAll;var 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r="slices."+t;i(r+".show")&&(i(r+".fill"),i(r+".locations"))})),i("spaceframe.show")&&i("spaceframe.fill"),i("surface.show")&&(i("surface.count"),i("surface.fill"),i("surface.pattern")),i("contour.show")&&(i("contour.color"),i("contour.width")),["text","hovertext","hovertemplate","lighting.ambient","lighting.diffuse","lighting.specular","lighting.roughness","lighting.fresnel","lighting.vertexnormalsepsilon","lighting.facenormalsepsilon","lightposition.x","lightposition.y","lightposition.z","flatshading","opacity"].forEach((function(t){i(t)})),o(t,e,n,i,{prefix:"",cLetter:"c"}),e._length=null):e.visible=!1}e.exports={supplyDefaults:function(t,e,r,a){s(t,e,r,a,(function(r,a){return n.coerce(t,e,i,r,a)}))},supplyIsoDefaults:s}},{"../../components/colorscale/defaults":605,"../../lib":728,"../../registry":859,"./attributes":1070}],1074:[function(t,e,r){"use 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n=t("../../components/colorscale/attributes"),a=t("../../plots/template_attributes").hovertemplateAttrs,i=t("../surface/attributes"),o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat;e.exports=s({x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},i:{valType:"data_array",editType:"calc"},j:{valType:"data_array",editType:"calc"},k:{valType:"data_array",editType:"calc"},text:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertemplate:a({editType:"calc"}),delaunayaxis:{valType:"enumerated",values:["x","y","z"],dflt:"z",editType:"calc"},alphahull:{valType:"number",dflt:-1,editType:"calc"},intensity:{valType:"data_array",editType:"calc"},intensitymode:{valType:"enumerated",values:["vertex","cell"],dflt:"vertex",editType:"calc"},color:{valType:"color",editType:"calc"},vertexcolor:{valType:"data_array",editType:"calc"},facecolor:{valType:"data_array",editType:"calc"},transforms:void 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n=t("../../components/colorscale/calc");e.exports=function(t,e){e.intensity&&n(t,e,{vals:e.intensity,containerStr:"",cLetter:"c"})}},{"../../components/colorscale/calc":603}],1077:[function(t,e,r){"use strict";var n=t("gl-mesh3d"),a=t("delaunay-triangulate"),i=t("alpha-shape"),o=t("convex-hull"),s=t("../../lib/gl_format_color").parseColorScale,l=t("../../lib/str2rgbarray"),c=t("../../components/colorscale").extractOpts,u=t("../../plots/gl3d/zip3");function h(t,e,r){this.scene=t,this.uid=r,this.mesh=e,this.name="",this.color="#fff",this.data=null,this.showContour=!1}var f=h.prototype;function p(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=l(t[n]);return e}function d(t,e,r,n){for(var a=[],i=e.length,o=0;o<i;o++)a[o]=t.d2l(e[o],0,n)*r;return a}function g(t){for(var e=[],r=t.length,n=0;n<r;n++)e[n]=Math.round(t[n]);return e}function m(t,e){for(var r=t.length,n=0;n<r;n++)if(t[n]<=-.5||t[n]>=e-.5)return!1;return!0}f.handlePick=function(t){if(t.object===this.mesh){var 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v={positions:f,cells:n,lightPosition:[t.lightposition.x,t.lightposition.y,t.lightposition.z],ambient:t.lighting.ambient,diffuse:t.lighting.diffuse,specular:t.lighting.specular,roughness:t.lighting.roughness,fresnel:t.lighting.fresnel,vertexNormalsEpsilon:t.lighting.vertexnormalsepsilon,faceNormalsEpsilon:t.lighting.facenormalsepsilon,opacity:t.opacity,contourEnable:t.contour.show,contourColor:l(t.contour.color).slice(0,3),contourWidth:t.contour.width,useFacetNormals:t.flatshading};if(t.intensity){var y=c(t);this.color="#fff";var x=t.intensitymode;v[x+"Intensity"]=t.intensity,v[x+"IntensityBounds"]=[y.min,y.max],v.colormap=s(t)}else t.vertexcolor?(this.color=t.vertexcolor[0],v.vertexColors=p(t.vertexcolor)):t.facecolor?(this.color=t.facecolor[0],v.cellColors=p(t.facecolor)):(this.color=t.color,v.meshColor=l(t.color));this.mesh.update(v)},f.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,a=n({gl:r}),i=new h(t,a,e.uid);return a._trace=i,i.update(e),t.glplot.add(a),i}},{"../../components/colorscale":607,"../../lib/gl_format_color":725,"../../lib/str2rgbarray":751,"../../plots/gl3d/zip3":829,"alpha-shape":67,"convex-hull":132,"delaunay-triangulate":166,"gl-mesh3d":287}],1078:[function(t,e,r){"use strict";var n=t("../../registry"),a=t("../../lib"),i=t("../../components/colorscale/defaults"),o=t("./attributes");e.exports=function(t,e,r,s){function l(r,n){return a.coerce(t,e,o,r,n)}function c(t){var e=t.map((function(t){var e=l(t);return e&&a.isArrayOrTypedArray(e)?e:null}));return e.every((function(t){return 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h(t){return{line:{color:n({},u.color,{dflt:t}),width:u.width,dash:i,editType:"style"},editType:"style"}}e.exports={x:{valType:"data_array",editType:"calc+clearAxisTypes"},open:{valType:"data_array",editType:"calc"},high:{valType:"data_array",editType:"calc"},low:{valType:"data_array",editType:"calc"},close:{valType:"data_array",editType:"calc"},line:{width:n({},u.width,{}),dash:n({},i,{}),editType:"style"},increasing:h(l),decreasing:h(c),text:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},tickwidth:{valType:"number",min:0,max:.5,dflt:.3,editType:"calc"},hoverlabel:n({},o.hoverlabel,{split:{valType:"boolean",dflt:!1,editType:"style"}})}},{"../../components/drawing/attributes":616,"../../components/fx/attributes":626,"../../constants/delta.js":698,"../../lib":728,"../scatter/attributes":1134}],1081:[function(t,e,r){"use strict";var n=t("../../lib"),a=n._,i=t("../../plots/cartesian/axes"),o=t("../../constants/numerical").BADNUM;function s(t,e,r,n){return{o:t,h:e,l:r,c:n}}function l(t,e,r,s,l){for(var c=s.makeCalcdata(e,"open"),u=s.makeCalcdata(e,"high"),h=s.makeCalcdata(e,"low"),f=s.makeCalcdata(e,"close"),p=Array.isArray(e.text),d=Array.isArray(e.hovertext),g=!0,m=null,v=[],y=0;y<r.length;y++){var x=r[y],b=c[y],_=u[y],w=h[y],T=f[y];if(x!==o&&b!==o&&_!==o&&w!==o&&T!==o){T===b?null!==m&&T!==m&&(g=T>m):g=T>b,m=T;var k=l(b,_,w,T);k.pos=x,k.yc=(b+T)/2,k.i=y,k.dir=g?"increasing":"decreasing",k.x=k.pos,k.y=[w,_],p&&(k.tx=e.text[y]),d&&(k.htx=e.hovertext[y]),v.push(k)}else v.push({pos:x,empty:!0})}return e._extremes[s._id]=i.findExtremes(s,n.concat(h,u),{padded:!0}),v.length&&(v[0].t={labels:{open:a(t,"open:")+" ",high:a(t,"high:")+" ",low:a(t,"low:")+" ",close:a(t,"close:")+" "}}),v}e.exports={calc:function(t,e){var r=i.getFromId(t,e.xaxis),a=i.getFromId(t,e.yaxis),o=function(t,e,r){var a=r._minDiff;if(!a){var i,o=t._fullData,s=[];for(a=1/0,i=0;i<o.length;i++){var l=o[i];if("ohlc"===l.type&&!0===l.visible&&l.xaxis===e._id){s.push(l);var c=e.makeCalcdata(l,"x");l._xcalc=c;var u=n.distinctVals(c).minDiff;u&&isFinite(u)&&(a=Math.min(a,u))}}for(a===1/0&&(a=1),i=0;i<s.length;i++)s[i]._minDiff=a}return a*r.tickwidth}(t,r,e),c=e._minDiff;e._minDiff=null;var u=e._xcalc;e._xcalc=null;var h=l(t,e,u,a,s);return e._extremes[r._id]=i.findExtremes(r,u,{vpad:c/2}),h.length?(n.extendFlat(h[0].t,{wHover:c/2,tickLen:o}),h):[{t:{empty:!0}}]},calcCommon:l}},{"../../constants/numerical":704,"../../lib":728,"../../plots/cartesian/axes":776}],1082:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("./ohlc_defaults"),i=t("./attributes");function o(t,e,r,n){r(n+".line.color"),r(n+".line.width",e.line.width),r(n+".line.dash",e.line.dash)}e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,i,r,a)}a(t,e,l,s)?(l("line.width"),l("line.dash"),o(t,e,l,"increasing"),o(t,e,l,"decreasing"),l("text"),l("hovertext"),l("tickwidth"),s._requestRangeslider[e.xaxis]=!0):e.visible=!1}},{"../../lib":728,"./attributes":1080,"./ohlc_defaults":1085}],1083:[function(t,e,r){"use strict";var n=t("../../plots/cartesian/axes"),a=t("../../lib"),i=t("../../components/fx"),o=t("../../components/color"),s=t("../../lib").fillText,l=t("../../constants/delta.js"),c={increasing:l.INCREASING.SYMBOL,decreasing:l.DECREASING.SYMBOL};function u(t,e,r,n){var a,s,l=t.cd,c=t.xa,u=l[0].trace,h=l[0].t,f=u.type,p="ohlc"===f?"l":"min",d="ohlc"===f?"h":"max",g=h.bPos||0,m=h.bdPos||h.tickLen,v=h.wHover,y=Math.min(1,m/Math.abs(c.r2c(c.range[1])-c.r2c(c.range[0])));function x(t){var r=function(t){return t.pos+g-e}(t);return i.inbox(r-v,r+v,a)}function b(t){var e=t[p],n=t[d];return e===n||i.inbox(e-r,n-r,a)}function _(t){return(x(t)+b(t))/2}a=t.maxHoverDistance-y,s=t.maxSpikeDistance-y;var w=i.getDistanceFunction(n,x,b,_);if(i.getClosest(l,w,t),!1===t.index)return null;var T=l[t.index];if(T.empty)return null;var k=u[T.dir],A=k.line.color;return o.opacity(A)&&k.line.width?t.color=A:t.color=k.fillcolor,t.x0=c.c2p(T.pos+g-m,!0),t.x1=c.c2p(T.pos+g+m,!0),t.xLabelVal=T.pos,t.spikeDistance=_(T)*s/a,t.xSpike=c.c2p(T.pos,!0),t}function h(t,e,r,i){var o=t.cd,s=t.ya,l=o[0].trace,c=o[0].t,h=[],f=u(t,e,r,i);if(!f)return[];var p=o[f.index].hi||l.hoverinfo,d=p.split("+");if(!("all"===p||-1!==d.indexOf("y")))return[];for(var g=["high","open","close","low"],m={},v=0;v<g.length;v++){var y,x=g[v],b=l[x][f.index],_=s.c2p(b,!0);b in m?(y=m[b]).yLabel+="<br>"+c.labels[x]+n.hoverLabelText(s,b):((y=a.extendFlat({},f)).y0=y.y1=_,y.yLabelVal=b,y.yLabel=c.labels[x]+n.hoverLabelText(s,b),y.name="",h.push(y),m[b]=y)}return h}function f(t,e,r,a){var i=t.cd,o=t.ya,l=i[0].trace,h=i[0].t,f=u(t,e,r,a);if(!f)return[];var p=i[f.index],d=f.index=p.i,g=p.dir;function m(t){return h.labels[t]+n.hoverLabelText(o,l[t][d])}var v=p.hi||l.hoverinfo,y=v.split("+"),x="all"===v,b=x||-1!==y.indexOf("y"),_=x||-1!==y.indexOf("text"),w=b?[m("open"),m("high"),m("low"),m("close")+" "+c[g]]:[];return _&&s(p,l,w),f.extraText=w.join("<br>"),f.y0=f.y1=o.c2p(p.yc,!0),[f]}e.exports={hoverPoints:function(t,e,r,n){return t.cd[0].trace.hoverlabel.split?h(t,e,r,n):f(t,e,r,n)},hoverSplit:h,hoverOnPoints:f}},{"../../components/color":595,"../../components/fx":635,"../../constants/delta.js":698,"../../lib":728,"../../plots/cartesian/axes":776}],1084:[function(t,e,r){"use 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o=e.yaxis,s=e.xaxis,l=!!s.rangebreaks;a.makeTraceGroups(i,r,"trace ohlc").each((function(t){var e=n.select(this),r=t[0],i=r.t;if(!0!==r.trace.visible||i.empty)e.remove();else{var c=i.tickLen,u=e.selectAll("path").data(a.identity);u.enter().append("path"),u.exit().remove(),u.attr("d",(function(t){if(t.empty)return"M0,0Z";var e=s.c2p(t.pos-c,!0),r=s.c2p(t.pos+c,!0),n=l?(e+r)/2:s.c2p(t.pos,!0);return"M"+e+","+o.c2p(t.o,!0)+"H"+n+"M"+n+","+o.c2p(t.h,!0)+"V"+o.c2p(t.l,!0)+"M"+r+","+o.c2p(t.c,!0)+"H"+n}))}}))}},{"../../lib":728,d3:164}],1087:[function(t,e,r){"use strict";e.exports=function(t,e){var r,n=t.cd,a=t.xaxis,i=t.yaxis,o=[],s=n[0].t.bPos||0;if(!1===e)for(r=0;r<n.length;r++)n[r].selected=0;else for(r=0;r<n.length;r++){var l=n[r];e.contains([a.c2p(l.pos+s),i.c2p(l.yc)],null,l.i,t)?(o.push({pointNumber:l.i,x:a.c2d(l.pos),y:i.c2d(l.yc)}),l.selected=1):l.selected=0}return o}},{}],1088:[function(t,e,r){"use strict";var n=t("d3"),a=t("../../components/drawing"),i=t("../../components/color");e.exports=function(t,e,r){var o=r||n.select(t).selectAll("g.ohlclayer").selectAll("g.trace");o.style("opacity",(function(t){return t[0].trace.opacity})),o.each((function(t){var e=t[0].trace;n.select(this).selectAll("path").each((function(t){if(!t.empty){var r=e[t.dir].line;n.select(this).style("fill","none").call(i.stroke,r.color).call(a.dashLine,r.dash,r.width).style("opacity",e.selectedpoints&&!t.selected?.3:1)}}))}))}},{"../../components/color":595,"../../components/drawing":617,d3:164}],1089:[function(t,e,r){"use strict";var n=t("../../lib/extend").extendFlat,a=t("../../plots/attributes"),i=t("../../plots/font_attributes"),o=t("../../components/colorscale/attributes"),s=t("../../plots/template_attributes").hovertemplateAttrs,l=t("../../plots/domain").attributes,c=n({editType:"calc"},o("line",{editTypeOverride:"calc"}),{shape:{valType:"enumerated",values:["linear","hspline"],dflt:"linear",editType:"plot"},hovertemplate:s({editType:"plot",arrayOk:!1},{keys:["count","probability"]})});e.exports={domain:l({name:"parcats",trace:!0,editType:"calc"}),hoverinfo:n({},a.hoverinfo,{flags:["count","probability"],editType:"plot",arrayOk:!1}),hoveron:{valType:"enumerated",values:["category","color","dimension"],dflt:"category",editType:"plot"},hovertemplate:s({editType:"plot",arrayOk:!1},{keys:["count","probability","category","categorycount","colorcount","bandcolorcount"]}),arrangement:{valType:"enumerated",values:["perpendicular","freeform","fixed"],dflt:"perpendicular",editType:"plot"},bundlecolors:{valType:"boolean",dflt:!0,editType:"plot"},sortpaths:{valType:"enumerated",values:["forward","backward"],dflt:"forward",editType:"plot"},labelfont:i({editType:"calc"}),tickfont:i({editType:"calc"}),dimensions:{_isLinkedToArray:"dimension",label:{valType:"string",editType:"calc"},categoryorder:{valType:"enumerated",values:["trace","category 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a=n._has&&n._has("parcats"),i=e._has&&e._has("parcats");a&&!i&&n._paperdiv.selectAll(".parcats").remove()}},{"../../plots/get_data":813,"./plot":1095}],1091:[function(t,e,r){"use strict";var n=t("../../lib/gup").wrap,a=t("../../components/colorscale/helpers").hasColorscale,i=t("../../components/colorscale/calc"),o=t("../../lib/filter_unique.js"),s=t("../../components/drawing"),l=t("../../lib"),c=t("fast-isnumeric");function u(t,e,r){t.valueInds.push(e),t.count+=r}function h(t,e,r){return{categoryInds:t,color:e,rawColor:r,valueInds:[],count:0}}function f(t,e,r){t.valueInds.push(e),t.count+=r}e.exports=function(t,e){var r=l.filterVisible(e.dimensions);if(0===r.length)return[];var p,d,g,m=r.map((function(t){var e;if("trace"===t.categoryorder)e=null;else if("array"===t.categoryorder)e=t.categoryarray;else{e=o(t.values);for(var r=!0,n=0;n<e.length;n++)if(!c(e[n])){r=!1;break}e.sort(r?l.sorterAsc:void 0),"category descending"===t.categoryorder&&(e=e.reverse())}return function(t,e){e=null==e?[]:e.map((function(t){return t}));var r={},n={},a=[];e.forEach((function(t,e){r[t]=0,n[t]=e}));for(var i=0;i<t.length;i++){var o,s=t[i];void 0===r[s]?(r[s]=1,o=e.push(s)-1,n[s]=o):(r[s]++,o=n[s]),a.push(o)}var l=e.map((function(t){return r[t]}));return{uniqueValues:e,uniqueCounts:l,inds:a}}(t.values,e)}));p=l.isArrayOrTypedArray(e.counts)?e.counts:[e.counts],function(t){var e;if(function(t){for(var e=new Array(t.length),r=0;r<t.length;r++){if(t[r]<0||t[r]>=t.length)return!1;if(void 0!==e[t[r]])return!1;e[t[r]]=!0}return!0}(t.map((function(t){return t.displayindex}))))for(e=0;e<t.length;e++)t[e]._displayindex=t[e].displayindex;else for(e=0;e<t.length;e++)t[e]._displayindex=e}(r),r.forEach((function(t,e){!function(t,e){t._categoryarray=e.uniqueValues,null===t.ticktext||void 0===t.ticktext?t._ticktext=[]:t._ticktext=t.ticktext.slice();for(var r=t._ticktext.length;r<e.uniqueValues.length;r++)t._ticktext.push(e.uniqueValues[r])}(t,m[e])}));var v,y=e.line;y?(a(e,"line")&&i(t,e,{vals:e.line.color,containerStr:"line",cLetter:"c"}),v=s.tryColorscale(y)):v=l.identity;var x,b,_,w,T,k=r[0].values.length,A={},M=m.map((function(t){return t.inds}));for(g=0,x=0;x<k;x++){var S=[];for(b=0;b<M.length;b++)S.push(M[b][x]);d=p[x%p.length],g+=d;var E=(_=x,w=void 0,T=void 0,l.isArrayOrTypedArray(y.color)?T=w=y.color[_%y.color.length]:w=y.color,{color:v(w),rawColor:T}),C=S+"-"+E.rawColor;void 0===A[C]&&(A[C]=h(S,E.color,E.rawColor)),f(A[C],x,d)}var L,P=r.map((function(t,e){return function(t,e,r,n,a){return{dimensionInd:t,containerInd:e,displayInd:r,dimensionLabel:n,count:a,categories:[],dragX:null}}(e,t._index,t._displayindex,t.label,g)}));for(x=0;x<k;x++)for(d=p[x%p.length],b=0;b<P.length;b++){var I=P[b].containerInd,z=m[b].inds[x],O=P[b].categories;if(void 0===O[z]){var D=e.dimensions[I]._categoryarray[z],R=e.dimensions[I]._ticktext[z];O[z]={dimensionInd:b,categoryInd:L=z,categoryValue:D,displayInd:L,categoryLabel:R,valueInds:[],count:0,dragY:null}}u(O[z],x,d)}return n(function(t,e,r){var n=t.map((function(t){return t.categories.length})).reduce((function(t,e){return Math.max(t,e)}));return{dimensions:t,paths:e,trace:void 0,maxCats:n,count:r}}(P,A,g))}},{"../../components/colorscale/calc":603,"../../components/colorscale/helpers":606,"../../components/drawing":617,"../../lib":728,"../../lib/filter_unique.js":720,"../../lib/gup":726,"fast-isnumeric":236}],1092:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../components/colorscale/helpers").hasColorscale,i=t("../../components/colorscale/defaults"),o=t("../../plots/domain").defaults,s=t("../../plots/array_container_defaults"),l=t("./attributes"),c=t("../parcoords/merge_length");function u(t,e){function r(r,a){return n.coerce(t,e,l.dimensions,r,a)}var a=r("values"),i=r("visible");if(a&&a.length||(i=e.visible=!1),i){r("label"),r("displayindex",e._index);var o,s=t.categoryarray,c=Array.isArray(s)&&s.length>0;c&&(o="array");var u=r("categoryorder",o);"array"===u?(r("categoryarray"),r("ticktext")):(delete t.categoryarray,delete t.ticktext),c||"array"!==u||(e.categoryorder="trace")}}e.exports=function(t,e,r,h){function f(r,a){return n.coerce(t,e,l,r,a)}var p=s(t,e,{name:"dimensions",handleItemDefaults:u}),d=function(t,e,r,o,s){s("line.shape"),s("line.hovertemplate");var l=s("line.color",o.colorway[0]);if(a(t,"line")&&n.isArrayOrTypedArray(l)){if(l.length)return s("line.colorscale"),i(t,e,o,s,{prefix:"line.",cLetter:"c"}),l.length;e.line.color=r}return 1/0}(t,e,r,h,f);o(e,h,f),Array.isArray(p)&&p.length||(e.visible=!1),c(e,p,"values",d),f("hoveron"),f("hovertemplate"),f("arrangement"),f("bundlecolors"),f("sortpaths"),f("counts");var g={family:h.font.family,size:Math.round(h.font.size),color:h.font.color};n.coerceFont(f,"labelfont",g);var 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i=t.map(D.bind(0,e,r)),l=a.selectAll("g.parcatslayer").data([null]);l.enter().append("g").attr("class","parcatslayer").style("pointer-events","all");var u=l.selectAll("g.trace.parcats").data(i,h),m=u.enter().append("g").attr("class","trace parcats");u.attr("transform",(function(t){return"translate("+t.x+", "+t.y+")"})),m.append("g").attr("class","paths");var v=u.select("g.paths").selectAll("path.path").data((function(t){return t.paths}),h);v.attr("fill",(function(t){return t.model.color}));var b=v.enter().append("path").attr("class","path").attr("stroke-opacity",0).attr("fill",(function(t){return t.model.color})).attr("fill-opacity",0);x(b),v.attr("d",(function(t){return t.svgD})),b.empty()||v.sort(p),v.exit().remove(),v.on("mouseover",d).on("mouseout",g).on("click",y),m.append("g").attr("class","dimensions");var T=u.select("g.dimensions").selectAll("g.dimension").data((function(t){return t.dimensions}),h);T.enter().append("g").attr("class","dimension"),T.attr("transform",(function(t){return"translate("+t.x+", 0)"})),T.exit().remove();var k=T.selectAll("g.category").data((function(t){return t.categories}),h),A=k.enter().append("g").attr("class","category");k.attr("transform",(function(t){return"translate(0, "+t.y+")"})),A.append("rect").attr("class","catrect").attr("pointer-events","none"),k.select("rect.catrect").attr("fill","none").attr("width",(function(t){return t.width})).attr("height",(function(t){return t.height})),_(A);var M=k.selectAll("rect.bandrect").data((function(t){return t.bands}),h);M.each((function(){o.raiseToTop(this)})),M.attr("fill",(function(t){return t.color}));var I=M.enter().append("rect").attr("class","bandrect").attr("stroke-opacity",0).attr("fill",(function(t){return t.color})).attr("fill-opacity",0);M.attr("fill",(function(t){return t.color})).attr("width",(function(t){return t.width})).attr("height",(function(t){return t.height})).attr("y",(function(t){return t.y})).attr("cursor",(function(t){return"fixed"===t.parcatsViewModel.arrangement?"default":"perpendicular"===t.parcatsViewModel.arrangement?"ns-resize":"move"})),w(I),M.exit().remove(),A.append("text").attr("class","catlabel").attr("pointer-events","none");var z=e._fullLayout.paper_bgcolor;k.select("text.catlabel").attr("text-anchor",(function(t){return f(t)?"start":"end"})).attr("alignment-baseline","middle").style("text-shadow",z+" -1px 1px 2px, "+z+" 1px 1px 2px, "+z+" 1px -1px 2px, "+z+" -1px -1px 2px").style("fill","rgb(0, 0, 0)").attr("x",(function(t){return f(t)?t.width+5:-5})).attr("y",(function(t){return t.height/2})).text((function(t){return t.model.categoryLabel})).each((function(t){s.font(n.select(this),t.parcatsViewModel.categorylabelfont),c.convertToTspans(n.select(this),e)})),A.append("text").attr("class","dimlabel"),k.select("text.dimlabel").attr("text-anchor","middle").attr("alignment-baseline","baseline").attr("cursor",(function(t){return"fixed"===t.parcatsViewModel.arrangement?"default":"ew-resize"})).attr("x",(function(t){return t.width/2})).attr("y",-5).text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})).each((function(t){s.font(n.select(this),t.parcatsViewModel.labelfont)})),k.selectAll("rect.bandrect").on("mouseover",S).on("mouseout",E),k.exit().remove(),T.call(n.behavior.drag().origin((function(t){return{x:t.x,y:0}})).on("dragstart",C).on("drag",L).on("dragend",P)),u.each((function(t){t.traceSelection=n.select(this),t.pathSelection=n.select(this).selectAll("g.paths").selectAll("path.path"),t.dimensionSelection=n.select(this).selectAll("g.dimensions").selectAll("g.dimension")})),u.exit().remove()}function h(t){return t.key}function f(t){var e=t.parcatsViewModel.dimensions.length,r=t.parcatsViewModel.dimensions[e-1].model.dimensionInd;return t.model.dimensionInd===r}function p(t,e){return t.model.rawColor>e.model.rawColor?1:t.model.rawColor<e.model.rawColor?-1:0}function d(t){if(!t.parcatsViewModel.dragDimension&&-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")){o.raiseToTop(this),b(n.select(this));var e=m(t),r=v(t);if(t.parcatsViewModel.graphDiv.emit("plotly_hover",{points:e,event:n.event,constraints:r}),-1===t.parcatsViewModel.hoverinfoItems.indexOf("none")){var a,s,c,u=n.mouse(this)[0],h=t.parcatsViewModel.graphDiv,f=t.parcatsViewModel.trace,p=h._fullLayout,d=p._paperdiv.node().getBoundingClientRect(),g=t.parcatsViewModel.graphDiv.getBoundingClientRect();for(c=0;c<t.leftXs.length-1;c++)if(t.leftXs[c]+t.dimWidths[c]-2<=u&&u<=t.leftXs[c+1]+2){var y=t.parcatsViewModel.dimensions[c],x=t.parcatsViewModel.dimensions[c+1];a=(y.x+y.width+x.x)/2,s=(t.topYs[c]+t.topYs[c+1]+t.height)/2;break}var _=t.parcatsViewModel.x+a,w=t.parcatsViewModel.y+s,T=l.mostReadable(t.model.color,["black","white"]),k=t.model.count,A=k/t.parcatsViewModel.model.count,M={countLabel:k,probabilityLabel:A.toFixed(3)},S=[];-1!==t.parcatsViewModel.hoverinfoItems.indexOf("count")&&S.push(["Count:",M.countLabel].join(" ")),-1!==t.parcatsViewModel.hoverinfoItems.indexOf("probability")&&S.push(["P:",M.probabilityLabel].join(" "));var E=S.join("<br>"),C=n.mouse(h)[0];i.loneHover({trace:f,x:_-d.left+g.left,y:w-d.top+g.top,text:E,color:t.model.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontSize:10,fontColor:T,idealAlign:C<_?"right":"left",hovertemplate:(f.line||{}).hovertemplate,hovertemplateLabels:M,eventData:[{data:f._input,fullData:f,count:k,probability:A}]},{container:p._hoverlayer.node(),outerContainer:p._paper.node(),gd:h})}}}function g(t){if(!t.parcatsViewModel.dragDimension&&(x(n.select(this)),i.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()),t.parcatsViewModel.pathSelection.sort(p),-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip"))){var e=m(t),r=v(t);t.parcatsViewModel.graphDiv.emit("plotly_unhover",{points:e,event:n.event,constraints:r})}}function m(t){for(var e=[],r=I(t.parcatsViewModel),n=0;n<t.model.valueInds.length;n++){var a=t.model.valueInds[n];e.push({curveNumber:r,pointNumber:a})}return e}function v(t){for(var e={},r=t.parcatsViewModel.model.dimensions,n=0;n<r.length;n++){var a=r[n],i=a.categories[t.model.categoryInds[n]];e[a.containerInd]=i.categoryValue}return void 0!==t.model.rawColor&&(e.color=t.model.rawColor),e}function y(t){if(-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")){var e=m(t),r=v(t);t.parcatsViewModel.graphDiv.emit("plotly_click",{points:e,event:n.event,constraints:r})}}function x(t){t.attr("fill",(function(t){return t.model.color})).attr("fill-opacity",.6).attr("stroke","lightgray").attr("stroke-width",.2).attr("stroke-opacity",1)}function b(t){t.attr("fill-opacity",.8).attr("stroke",(function(t){return l.mostReadable(t.model.color,["black","white"])})).attr("stroke-width",.3)}function _(t){t.select("rect.catrect").attr("stroke","black").attr("stroke-width",1).attr("stroke-opacity",1)}function w(t){t.attr("stroke","black").attr("stroke-width",.2).attr("stroke-opacity",1).attr("fill-opacity",1)}function T(t){var e=t.parcatsViewModel.pathSelection,r=t.categoryViewModel.model.dimensionInd,n=t.categoryViewModel.model.categoryInd;return e.filter((function(e){return e.model.categoryInds[r]===n&&e.model.color===t.color}))}function k(t,e,r){var a=n.select(t).datum(),i=a.categoryViewModel.model,o=a.parcatsViewModel.graphDiv,s=n.select(t.parentNode).selectAll("rect.bandrect"),l=[];s.each((function(t){T(t).each((function(t){Array.prototype.push.apply(l,m(t))}))}));var c={};c[i.dimensionInd]=i.categoryValue,o.emit(e,{points:l,event:r,constraints:c})}function A(t,e,r){var a=n.select(t).datum(),i=a.categoryViewModel.model,o=a.parcatsViewModel.graphDiv,s=T(a),l=[];s.each((function(t){Array.prototype.push.apply(l,m(t))}));var c={};c[i.dimensionInd]=i.categoryValue,void 0!==a.rawColor&&(c.color=a.rawColor),o.emit(e,{points:l,event:r,constraints:c})}function M(t,e){var r,a,i=n.select(e.parentNode).select("rect.catrect"),o=i.node().getBoundingClientRect(),s=i.datum(),l=s.parcatsViewModel,c=l.model.dimensions[s.model.dimensionInd],u=l.trace,h=o.top+o.height/2;l.dimensions.length>1&&c.displayInd===l.dimensions.length-1?(r=o.left,a="left"):(r=o.left+o.width,a="right");var f=s.model.count,p=s.model.categoryLabel,d=f/s.parcatsViewModel.model.count,g={countLabel:f,categoryLabel:p,probabilityLabel:d.toFixed(3)},m=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf("count")&&m.push(["Count:",g.countLabel].join(" 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t.color===e.color})).each((function(){o.raiseToTop(this),n.select(this).attr("stroke","black").attr("stroke-width",1.5)}))}(this),A(this,"plotly_hover",n.event)):(!function(t){n.select(t.parentNode).selectAll("rect.bandrect").each((function(t){var e=T(t);b(e),e.each((function(){o.raiseToTop(this)}))})),n.select(t.parentNode).select("rect.catrect").attr("stroke","black").attr("stroke-width",2.5)}(this),k(this,"plotly_hover",n.event)),-1===t.parcatsViewModel.hoverinfoItems.indexOf("none"))"category"===c?e=M(s,this):"color"===c?e=function(t,e){var r,a,i=e.getBoundingClientRect(),o=n.select(e).datum(),s=o.categoryViewModel,c=s.parcatsViewModel,u=c.model.dimensions[s.model.dimensionInd],h=c.trace,f=i.y+i.height/2;c.dimensions.length>1&&u.displayInd===c.dimensions.length-1?(r=i.left,a="left"):(r=i.left+i.width,a="right");var p=s.model.categoryLabel,d=o.parcatsViewModel.model.count,g=0;o.categoryViewModel.bands.forEach((function(t){t.color===o.color&&(g+=t.count)}));var m=s.model.count,v=0;c.pathSelection.each((function(t){t.model.color===o.color&&(v+=t.model.count)}));var y=g/d,x=g/v,b=g/m,_={countLabel:d,categoryLabel:p,probabilityLabel:y.toFixed(3)},w=[];-1!==s.parcatsViewModel.hoverinfoItems.indexOf("count")&&w.push(["Count:",_.countLabel].join(" ")),-1!==s.parcatsViewModel.hoverinfoItems.indexOf("probability")&&(w.push("P(color \u2229 "+p+"): "+_.probabilityLabel),w.push("P("+p+" | color): "+x.toFixed(3)),w.push("P(color | "+p+"): "+b.toFixed(3)));var T=w.join("<br>"),k=l.mostReadable(o.color,["black","white"]);return{trace:h,x:r-t.left,y:f-t.top,text:T,color:o.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontColor:k,fontSize:10,idealAlign:a,hovertemplate:h.hovertemplate,hovertemplateLabels:_,eventData:[{data:h._input,fullData:h,category:p,count:d,probability:y,categorycount:m,colorcount:v,bandcolorcount:g}]}}(s,this):"dimension"===c&&(e=function(t,e){var r=[];return n.select(e.parentNode.parentNode).selectAll("g.category").select("rect.catrect").each((function(){r.push(M(t,this))})),r}(s,this)),e&&i.loneHover(e,{container:a._hoverlayer.node(),outerContainer:a._paper.node(),gd:r})}}function E(t){var e=t.parcatsViewModel;if(!e.dragDimension&&(x(e.pathSelection),_(e.dimensionSelection.selectAll("g.category")),w(e.dimensionSelection.selectAll("g.category").selectAll("rect.bandrect")),i.loneUnhover(e.graphDiv._fullLayout._hoverlayer.node()),e.pathSelection.sort(p),-1===e.hoverinfoItems.indexOf("skip"))){"color"===t.parcatsViewModel.hoveron?A(this,"plotly_unhover",n.event):k(this,"plotly_unhover",n.event)}}function C(t){"fixed"!==t.parcatsViewModel.arrangement&&(t.dragDimensionDisplayInd=t.model.displayInd,t.initialDragDimensionDisplayInds=t.parcatsViewModel.model.dimensions.map((function(t){return t.displayInd})),t.dragHasMoved=!1,t.dragCategoryDisplayInd=null,n.select(this).selectAll("g.category").select("rect.catrect").each((function(e){var r=n.mouse(this)[0],a=n.mouse(this)[1];-2<=r&&r<=e.width+2&&-2<=a&&a<=e.height+2&&(t.dragCategoryDisplayInd=e.model.displayInd,t.initialDragCategoryDisplayInds=t.model.categories.map((function(t){return t.displayInd})),e.model.dragY=e.y,o.raiseToTop(this.parentNode),n.select(this.parentNode).selectAll("rect.bandrect").each((function(e){e.y<a&&a<=e.y+e.height&&(t.potentialClickBand=this)})))})),t.parcatsViewModel.dragDimension=t,i.loneUnhover(t.parcatsViewModel.graphDiv._fullLayout._hoverlayer.node()))}function L(t){if("fixed"!==t.parcatsViewModel.arrangement&&(t.dragHasMoved=!0,null!==t.dragDimensionDisplayInd)){var e=t.dragDimensionDisplayInd,r=e-1,a=e+1,i=t.parcatsViewModel.dimensions[e];if(null!==t.dragCategoryDisplayInd){var o=i.categories[t.dragCategoryDisplayInd];o.model.dragY+=n.event.dy;var s=o.model.dragY,l=o.model.displayInd,c=i.categories,u=c[l-1],h=c[l+1];void 0!==u&&s<u.y+u.height/2&&(o.model.displayInd=u.model.displayInd,u.model.displayInd=l),void 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t.displayInd})),o=t.initialDragDimensionDisplayInds.some((function(t,e){return t!==i[e]}));o&&i.forEach((function(r,n){var a=t.parcatsViewModel.model.dimensions[n].containerInd;e["dimensions["+a+"].displayindex"]=r}));var s=!1;if(null!==t.dragCategoryDisplayInd){var l=t.model.categories.map((function(t){return t.displayInd}));if(s=t.initialDragCategoryDisplayInds.some((function(t,e){return t!==l[e]}))){var c=t.model.categories.slice().sort((function(t,e){return t.displayInd-e.displayInd})),u=c.map((function(t){return t.categoryValue})),h=c.map((function(t){return t.categoryLabel}));e["dimensions["+t.model.containerInd+"].categoryarray"]=[u],e["dimensions["+t.model.containerInd+"].ticktext"]=[h],e["dimensions["+t.model.containerInd+"].categoryorder"]="array"}}if(-1===t.parcatsViewModel.hoverinfoItems.indexOf("skip")&&!t.dragHasMoved&&t.potentialClickBand&&("color"===t.parcatsViewModel.hoveron?A(t.potentialClickBand,"plotly_click",n.event.sourceEvent):k(t.potentialClickBand,"plotly_click",n.event.sourceEvent)),t.model.dragX=null,null!==t.dragCategoryDisplayInd)t.parcatsViewModel.dimensions[t.dragDimensionDisplayInd].categories[t.dragCategoryDisplayInd].model.dragY=null,t.dragCategoryDisplayInd=null;t.dragDimensionDisplayInd=null,t.parcatsViewModel.dragDimension=null,t.dragHasMoved=null,t.potentialClickBand=null,B(t.parcatsViewModel),F(t.parcatsViewModel),n.transition().duration(300).ease("cubic-in-out").each((function(){O(t.parcatsViewModel,!0),z(t.parcatsViewModel,!0)})).each("end",(function(){(o||s)&&a.restyle(t.parcatsViewModel.graphDiv,e,[r])}))}}function I(t){for(var e,r=t.graphDiv._fullData,n=0;n<r.length;n++)if(t.key===r[n].uid){e=n;break}return e}function z(t,e){var r;void 0===e&&(e=!1),t.pathSelection.data((function(t){return t.paths}),h),(r=t.pathSelection,e?r.transition():r).attr("d",(function(t){return t.svgD}))}function O(t,e){function r(t){return e?t.transition():t}void 0===e&&(e=!1),t.dimensionSelection.data((function(t){return t.dimensions}),h);var a=t.dimensionSelection.selectAll("g.category").data((function(t){return t.categories}),h);r(t.dimensionSelection).attr("transform",(function(t){return"translate("+t.x+", 0)"})),r(a).attr("transform",(function(t){return"translate(0, "+t.y+")"})),a.select(".dimlabel").text((function(t,e){return 0===e?t.parcatsViewModel.model.dimensions[t.model.dimensionInd].dimensionLabel:null})),a.select(".catlabel").attr("text-anchor",(function(t){return f(t)?"start":"end"})).attr("x",(function(t){return f(t)?t.width+5:-5})).each((function(t){var e,r;f(t)?(e=t.width+5,r="start"):(e=-5,r="end"),n.select(this).selectAll("tspan").attr("x",e).attr("text-anchor",r)}));var i=a.selectAll("rect.bandrect").data((function(t){return t.bands}),h),s=i.enter().append("rect").attr("class","bandrect").attr("cursor","move").attr("stroke-opacity",0).attr("fill",(function(t){return t.color})).attr("fill-opacity",0);i.attr("fill",(function(t){return t.color})).attr("width",(function(t){return t.width})).attr("height",(function(t){return t.height})).attr("y",(function(t){return t.y})),w(s),i.each((function(){o.raiseToTop(this)})),i.exit().remove()}function D(t,e,r){var n,a=r[0],i=e.margin||{l:80,r:80,t:100,b:80},o=a.trace,s=o.domain,l=e.width,c=e.height,u=Math.floor(l*(s.x[1]-s.x[0])),h=Math.floor(c*(s.y[1]-s.y[0])),f=s.x[0]*l+i.l,p=e.height-s.y[1]*e.height+i.t,d=o.line.shape;n="all"===o.hoverinfo?["count","probability"]:(o.hoverinfo||"").split("+");var g={trace:o,key:o.uid,model:a,x:f,y:p,width:u,height:h,hoveron:o.hoveron,hoverinfoItems:n,arrangement:o.arrangement,bundlecolors:o.bundlecolors,sortpaths:o.sortpaths,labelfont:o.labelfont,categorylabelfont:o.tickfont,pathShape:d,dragDimension:null,margin:i,paths:[],dimensions:[],graphDiv:t,traceSelection:null,pathSelection:null,dimensionSelection:null};return a.dimensions&&(B(g),F(g)),g}function R(t,e,r,a,i){var o,s,l=[],c=[];for(s=0;s<r.length-1;s++)o=n.interpolateNumber(r[s]+t[s],t[s+1]),l.push(o(i)),c.push(o(1-i));var u="M "+t[0]+","+e[0];for(u+="l"+r[0]+",0 ",s=1;s<r.length;s++)u+="C"+l[s-1]+","+e[s-1]+" "+c[s-1]+","+e[s]+" "+t[s]+","+e[s],u+="l"+r[s]+",0 ";for(u+="l0,"+a+" ",u+="l -"+r[r.length-1]+",0 ",s=r.length-2;s>=0;s--)u+="C"+c[s]+","+(e[s+1]+a)+" "+l[s]+","+(e[s]+a)+" "+(t[s]+r[s])+","+(e[s]+a),u+="l-"+r[s]+",0 ";return u+="Z"}function F(t){var e=t.dimensions,r=t.model,n=e.map((function(t){return t.categories.map((function(t){return t.y}))})),a=t.model.dimensions.map((function(t){return t.categories.map((function(t){return t.displayInd}))})),i=t.model.dimensions.map((function(t){return t.displayInd})),o=t.dimensions.map((function(t){return t.model.dimensionInd})),s=e.map((function(t){return t.x})),l=e.map((function(t){return t.width})),c=[];for(var u in r.paths)r.paths.hasOwnProperty(u)&&c.push(r.paths[u]);function h(t){var e=t.categoryInds.map((function(t,e){return a[e][t]}));return o.map((function(t){return e[t]}))}c.sort((function(e,r){var n=h(e),a=h(r);return"backward"===t.sortpaths&&(n.reverse(),a.reverse()),n.push(e.valueInds[0]),a.push(r.valueInds[0]),t.bundlecolors&&(n.unshift(e.rawColor),a.unshift(r.rawColor)),n<a?-1:n>a?1:0}));for(var f=new Array(c.length),p=e[0].model.count,d=e[0].categories.map((function(t){return t.height})).reduce((function(t,e){return t+e})),g=0;g<c.length;g++){var m,v=c[g];m=p>0?d*(v.count/p):0;for(var y,x=new Array(n.length),b=0;b<v.categoryInds.length;b++){var 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strict";var n=t("./constants"),a=t("d3"),i=t("../../lib/gup").keyFun,o=t("../../lib/gup").repeat,s=t("../../lib").sorterAsc,l=n.bar.snapRatio;function c(t,e){return t*(1-l)+e*l}var u=n.bar.snapClose;function h(t,e){return t*(1-u)+e*u}function f(t,e,r,n){if(function(t,e){for(var r=0;r<e.length;r++)if(t>=e[r][0]&&t<=e[r][1])return!0;return!1}(r,n))return r;var a=t?-1:1,i=0,o=e.length-1;if(a<0){var s=i;i=o,o=s}for(var l=e[i],u=l,f=i;a*f<a*o;f+=a){var p=f+a,d=e[p];if(a*r<a*h(l,d))return c(l,u);if(a*r<a*d||p===o)return c(d,l);u=l,l=d}}function p(t){t.attr("x",-n.bar.captureWidth/2).attr("width",n.bar.captureWidth)}function d(t){t.attr("visibility","visible").style("visibility","visible").attr("fill","yellow").attr("opacity",0)}function g(t){if(!t.brush.filterSpecified)return"0,"+t.height;for(var e,r,n,a=m(t.brush.filter.getConsolidated(),t.height),i=[0],o=a.length?a[0][0]:null,s=0;s<a.length;s++)r=(e=a[s])[1]-e[0],i.push(o),i.push(r),(n=s+1)<a.length&&(o=a[n][0]-e[1]);return i.push(t.height),i}function m(t,e){return t.map((function(t){return t.map((function(t){return Math.max(0,t*e)})).sort(s)}))}function v(){a.select(document.body).style("cursor",null)}function y(t){t.attr("stroke-dasharray",g)}function x(t,e){var r=a.select(t).selectAll(".highlight, .highlight-shadow");y(e?r.transition().duration(n.bar.snapDuration).each("end",e):r)}function b(t,e){var r,a=t.brush,i=NaN,o={};if(a.filterSpecified){var s=t.height,l=a.filter.getConsolidated(),c=m(l,s),u=NaN,h=NaN,f=NaN;for(r=0;r<=c.length;r++){var p=c[r];if(p&&p[0]<=e&&e<=p[1]){u=r;break}if(h=r?r-1:NaN,p&&p[0]>e){f=r;break}}if(i=u,isNaN(i)&&(i=isNaN(h)||isNaN(f)?isNaN(h)?f:h:e-c[h][1]<c[f][0]-e?h:f),!isNaN(i)){var d=c[i],g=function(t,e){var r=n.bar.handleHeight;if(!(e>t[1]+r||e<t[0]-r))return e>=.9*t[1]+.1*t[0]?"n":e<=.9*t[0]+.1*t[1]?"s":"ns"}(d,e);g&&(o.interval=l[i],o.intervalPix=d,o.region=g)}}if(t.ordinal&&!o.region){var v=t.unitTickvals,y=t.unitToPaddedPx.invert(e);for(r=0;r<v.length;r++){var x=[.25*v[Math.max(r-1,0)]+.75*v[r],.25*v[Math.min(r+1,v.length-1)]+.75*v[r]];if(y>=x[0]&&y<=x[1]){o.clickableOrdinalRange=x;break}}}return o}function _(t,e){a.event.sourceEvent.stopPropagation();var r=e.height-a.mouse(t)[1]-2*n.verticalPadding,i=e.brush.svgBrush;i.wasDragged=!0,i._dragging=!0,i.grabbingBar?i.newExtent=[r-i.grabPoint,r+i.barLength-i.grabPoint].map(e.unitToPaddedPx.invert):i.newExtent=[i.startExtent,e.unitToPaddedPx.invert(r)].sort(s),e.brush.filterSpecified=!0,i.extent=i.stayingIntervals.concat([i.newExtent]),i.brushCallback(e),x(t.parentNode)}function w(t,e){var r=b(e,e.height-a.mouse(t)[1]-2*n.verticalPadding),i="crosshair";r.clickableOrdinalRange?i="pointer":r.region&&(i=r.region+"-resize"),a.select(document.body).style("cursor",i)}function T(t){t.on("mousemove",(function(t){a.event.preventDefault(),t.parent.inBrushDrag||w(this,t)})).on("mouseleave",(function(t){t.parent.inBrushDrag||v()})).call(a.behavior.drag().on("dragstart",(function(t){!function(t,e){a.event.sourceEvent.stopPropagation();var r=e.height-a.mouse(t)[1]-2*n.verticalPadding,i=e.unitToPaddedPx.invert(r),o=e.brush,s=b(e,r),l=s.interval,c=o.svgBrush;if(c.wasDragged=!1,c.grabbingBar="ns"===s.region,c.grabbingBar){var u=l.map(e.unitToPaddedPx);c.grabPoint=r-u[0]-n.verticalPadding,c.barLength=u[1]-u[0]}c.clickableOrdinalRange=s.clickableOrdinalRange,c.stayingIntervals=e.multiselect&&o.filterSpecified?o.filter.getConsolidated():[],l&&(c.stayingIntervals=c.stayingIntervals.filter((function(t){return t[0]!==l[0]&&t[1]!==l[1]}))),c.startExtent=s.region?l["s"===s.region?1:0]:i,e.parent.inBrushDrag=!0,c.brushStartCallback()}(this,t)})).on("drag",(function(t){_(this,t)})).on("dragend",(function(t){!function(t,e){var r=e.brush,n=r.filter,i=r.svgBrush;i._dragging||(w(t,e),_(t,e),e.brush.svgBrush.wasDragged=!1),i._dragging=!1,a.event.sourceEvent.stopPropagation();var o=i.grabbingBar;if(i.grabbingBar=!1,i.grabLocation=void 0,e.parent.inBrushDrag=!1,v(),!i.wasDragged)return i.wasDragged=void 0,i.clickableOrdinalRange?r.filterSpecified&&e.multiselect?i.extent.push(i.clickableOrdinalRange):(i.extent=[i.clickableOrdinalRange],r.filterSpecified=!0):o?(i.extent=i.stayingIntervals,0===i.extent.length&&A(r)):A(r),i.brushCallback(e),x(t.parentNode),void i.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);var s=function(){n.set(n.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]<l[0]&&l.reverse(),i.newExtent=[f(0,l,i.newExtent[0],i.stayingIntervals),f(1,l,i.newExtent[1],i.stayingIntervals)];var c=i.newExtent[1]>i.newExtent[0];i.extent=i.stayingIntervals.concat(c?[i.newExtent]:[]),i.extent.length||A(r),i.brushCallback(e),c?x(t.parentNode,s):(s(),x(t.parentNode))}else s();i.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}(this,t)})))}function k(t,e){return t[0]-e[0]}function A(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function M(t){for(var e,r=t.slice(),n=[],a=r.shift();a;){for(e=a.slice();(a=r.shift())&&a[0]<=e[1];)e[1]=Math.max(e[1],a[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}e.exports={makeBrush:function(t,e,r,n,a,i){var o,l=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(s)})).sort(k)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=M(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return l.set(r),{filter:l,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:(o=a,function(t){var e=t.brush,r=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(e).slice();e.filter.set(r),o()}),brushEndCallback:i}}},ensureAxisBrush:function(t){var e=t.selectAll("."+n.cn.axisBrush).data(o,i);e.enter().append("g").classed(n.cn.axisBrush,!0),function(t){var e=t.selectAll(".background").data(o);e.enter().append("rect").classed("background",!0).call(p).call(d).style("pointer-events","auto").attr("transform","translate(0 "+n.verticalPadding+")"),e.call(T).attr("height",(function(t){return t.height-n.verticalPadding}));var r=t.selectAll(".highlight-shadow").data(o);r.enter().append("line").classed("highlight-shadow",!0).attr("x",-n.bar.width/2).attr("stroke-width",n.bar.width+n.bar.strokeWidth).attr("stroke",n.bar.strokeColor).attr("opacity",n.bar.strokeOpacity).attr("stroke-linecap","butt"),r.attr("y1",(function(t){return t.height})).call(y);var a=t.selectAll(".highlight").data(o);a.enter().append("line").classed("highlight",!0).attr("x",-n.bar.width/2).attr("stroke-width",n.bar.width-n.bar.strokeWidth).attr("stroke",n.bar.fillColor).attr("opacity",n.bar.fillOpacity).attr("stroke-linecap","butt"),a.attr("y1",(function(t){return t.height})).call(y)}(e)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(s)})),t=e.multiselect?M(t.sort(k)):[t[0]]):t=[t.sort(s)],e.tickvals){var r=e.tickvals.slice().sort(s);if(!(t=t.map((function(t){var e=[f(0,r,t[0],[]),f(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}},{"../../lib":728,"../../lib/gup":726,"./constants":1100,d3:164}],1098:[function(t,e,r){"use strict";var n=t("d3"),a=t("../../plots/get_data").getModuleCalcData,i=t("./plot"),o=t("../../constants/xmlns_namespaces");r.name="parcoords",r.plot=function(t){var e=a(t.calcdata,"parcoords")[0];e.length&&i(t,e)},r.clean=function(t,e,r,n){var a=n._has&&n._has("parcoords"),i=e._has&&e._has("parcoords");a&&!i&&(n._paperdiv.selectAll(".parcoords").remove(),n._glimages.selectAll("*").remove())},r.toSVG=function(t){var e=t._fullLayout._glimages,r=n.select(t).selectAll(".svg-container");r.filter((function(t,e){return e===r.size()-1})).selectAll(".gl-canvas-context, .gl-canvas-focus").each((function(){var t=this.toDataURL("image/png");e.append("svg:image").attr({xmlns:o.svg,"xlink:href":t,preserveAspectRatio:"none",x:0,y:0,width:this.width,height:this.height})})),window.setTimeout((function(){n.selectAll("#filterBarPattern").attr("id","filterBarPattern")}),60)}},{"../../constants/xmlns_namespaces":705,"../../plots/get_data":813,"./plot":1107,d3:164}],1099:[function(t,e,r){"use strict";var n=t("../../lib").isArrayOrTypedArray,a=t("../../components/colorscale"),i=t("../../lib/gup").wrap;e.exports=function(t,e){var r,o;return a.hasColorscale(e,"line")&&n(e.line.color)?(r=e.line.color,o=a.extractOpts(e.line).colorscale,a.calc(t,e,{vals:r,containerStr:"line",cLetter:"c"})):(r=function(t){for(var e=new Array(t),r=0;r<t;r++)e[r]=.5;return e}(e._length),o=[[0,e.line.color],[1,e.line.color]]),i({lineColor:r,cscale:o})}},{"../../components/colorscale":607,"../../lib":728,"../../lib/gup":726}],1100:[function(t,e,r){"use strict";e.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:["contextLineLayer","focusLineLayer","pickLineLayer"],axisTitleOffset:28,axisExtentOffset:10,deselectedLineColor:"#777",bar:{width:4,captureWidth:10,fillColor:"magenta",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeColor:"white",strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:"axis-extent-text",parcoordsLineLayers:"parcoords-line-layers",parcoordsLineLayer:"parcoords-lines",parcoords:"parcoords",parcoordsControlView:"parcoords-control-view",yAxis:"y-axis",axisOverlays:"axis-overlays",axis:"axis",axisHeading:"axis-heading",axisTitle:"axis-title",axisExtent:"axis-extent",axisExtentTop:"axis-extent-top",axisExtentTopText:"axis-extent-top-text",axisExtentBottom:"axis-extent-bottom",axisExtentBottomText:"axis-extent-bottom-text",axisBrush:"axis-brush"},id:{filterBarPattern:"filter-bar-pattern"}}},{}],1101:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../components/colorscale/helpers").hasColorscale,i=t("../../components/colorscale/defaults"),o=t("../../plots/domain").defaults,s=t("../../plots/array_container_defaults"),l=t("../../plots/cartesian/axes"),c=t("./attributes"),u=t("./axisbrush"),h=t("./constants").maxDimensionCount,f=t("./merge_length");function p(t,e,r,a){function i(r,a){return n.coerce(t,e,c.dimensions,r,a)}var o=i("values"),s=i("visible");if(o&&o.length||(s=e.visible=!1),s){i("label"),i("tickvals"),i("ticktext"),i("tickformat");var h=i("range");e._ax={_id:"y",type:"linear",showexponent:"all",exponentformat:"B",range:h},l.setConvert(e._ax,a.layout),i("multiselect");var f=i("constraintrange");f&&(e.constraintrange=u.cleanRanges(f,e))}}e.exports=function(t,e,r,l){function u(r,a){return n.coerce(t,e,c,r,a)}var d=t.dimensions;Array.isArray(d)&&d.length>h&&(n.log("parcoords traces support up to "+h+" dimensions at the moment"),d.splice(h));var g=s(t,e,{name:"dimensions",layout:l,handleItemDefaults:p}),m=function(t,e,r,o,s){var l=s("line.color",r);if(a(t,"line")&&n.isArrayOrTypedArray(l)){if(l.length)return s("line.colorscale"),i(t,e,o,s,{prefix:"line.",cLetter:"c"}),l.length;e.line.color=r}return 1/0}(t,e,r,l,u);o(e,l,u),Array.isArray(g)&&g.length||(e.visible=!1),f(e,g,"values",m);var v={family:l.font.family,size:Math.round(l.font.size/1.2),color:l.font.color};n.coerceFont(u,"labelfont",v),n.coerceFont(u,"tickfont",v),n.coerceFont(u,"rangefont",v),u("labelangle"),u("labelside")}},{"../../components/colorscale/defaults":605,"../../components/colorscale/helpers":606,"../../lib":728,"../../plots/array_container_defaults":772,"../../plots/cartesian/axes":776,"../../plots/domain":803,"./attributes":1096,"./axisbrush":1097,"./constants":1100,"./merge_length":1105}],1102:[function(t,e,r){"use strict";var n=t("../../lib").isTypedArray;r.convertTypedArray=function(t){return n(t)?Array.prototype.slice.call(t):t},r.isOrdinal=function(t){return!!t.tickvals},r.isVisible=function(t){return t.visible||!("visible"in t)}},{"../../lib":728}],1103:[function(t,e,r){"use strict";e.exports={attributes:t("./attributes"),supplyDefaults:t("./defaults"),calc:t("./calc"),plot:t("./plot"),colorbar:{container:"line",min:"cmin",max:"cmax"},moduleType:"trace",name:"parcoords",basePlotModule:t("./base_plot"),categories:["gl","regl","noOpacity","noHover"],meta:{}}},{"./attributes":1096,"./base_plot":1098,"./calc":1099,"./defaults":1101,"./plot":1107}],1104:[function(t,e,r){"use strict";var n=t("glslify"),a=n(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor;\n\nattribute vec4 p01_04, p05_08, p09_12, p13_16,\n p17_20, p21_24, p25_28, p29_32,\n p33_36, p37_40, p41_44, p45_48,\n p49_52, p53_56, p57_60, colors;\n\nuniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,\n loA, hiA, loB, hiB, loC, hiC, loD, hiD;\n\nuniform vec2 resolution, viewBoxPos, viewBoxSize;\nuniform sampler2D mask, palette;\nuniform float maskHeight;\nuniform float drwLayer; // 0: context, 1: focus, 2: pick\nuniform vec4 contextColor;\n\nbool isPick = (drwLayer > 1.5);\nbool isContext = (drwLayer < 0.5);\n\nconst vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);\nconst vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);\n\nfloat val(mat4 p, mat4 v) {\n return dot(matrixCompMult(p, v) * UNITS, UNITS);\n}\n\nfloat axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {\n float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);\n float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);\n return y1 * (1.0 - ratio) + y2 * ratio;\n}\n\nint iMod(int a, int b) {\n return a - b * (a / b);\n}\n\nbool fOutside(float p, float lo, float hi) {\n return (lo < hi) && (lo > p || p > hi);\n}\n\nbool vOutside(vec4 p, vec4 lo, vec4 hi) {\n return (\n fOutside(p[0], lo[0], hi[0]) ||\n fOutside(p[1], lo[1], hi[1]) ||\n fOutside(p[2], lo[2], hi[2]) ||\n fOutside(p[3], lo[3], hi[3])\n );\n}\n\nbool mOutside(mat4 p, mat4 lo, mat4 hi) {\n return (\n vOutside(p[0], lo[0], hi[0]) ||\n vOutside(p[1], lo[1], hi[1]) ||\n vOutside(p[2], lo[2], hi[2]) ||\n vOutside(p[3], lo[3], hi[3])\n );\n}\n\nbool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {\n return mOutside(A, loA, hiA) ||\n mOutside(B, loB, hiB) ||\n mOutside(C, loC, hiC) ||\n mOutside(D, loD, hiD);\n}\n\nbool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {\n mat4 pnts[4];\n pnts[0] = A;\n pnts[1] = B;\n pnts[2] = C;\n pnts[3] = D;\n\n for(int i = 0; i < 4; ++i) {\n for(int j = 0; j < 4; ++j) {\n for(int k = 0; k < 4; ++k) {\n if(0 == iMod(\n int(255.0 * texture2D(mask,\n vec2(\n (float(i * 2 + j / 2) + 0.5) / 8.0,\n (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight\n ))[3]\n ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),\n 2\n )) return true;\n }\n }\n }\n return false;\n}\n\nvec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {\n float x = 0.5 * sign(v) + 0.5;\n float y = axisY(x, A, B, C, D);\n float z = 1.0 - abs(v);\n\n z += isContext ? 0.0 : 2.0 * float(\n outsideBoundingBox(A, B, C, D) ||\n outsideRasterMask(A, B, C, D)\n );\n\n return vec4(\n 2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,\n z,\n 1.0\n );\n}\n\nvoid main() {\n mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);\n mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);\n mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);\n mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);\n\n float v = colors[3];\n\n gl_Position = position(isContext, v, A, B, C, D);\n\n fragColor =\n isContext ? vec4(contextColor) :\n isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));\n}\n"]),i=n(["precision highp float;\n#define GLSLIFY 1\n\nvarying vec4 fragColor;\n\nvoid main() {\n gl_FragColor = fragColor;\n}\n"]),o=t("./constants").maxDimensionCount,s=t("../../lib"),l=new Uint8Array(4),c=new Uint8Array(4),u={shape:[256,1],format:"rgba",type:"uint8",mag:"nearest",min:"nearest"};function h(t,e,r,n,a){var i=t._gl;i.enable(i.SCISSOR_TEST),i.scissor(e,r,n,a),t.clear({color:[0,0,0,0],depth:1})}function f(t,e,r,n,a,i){var o=i.key;r.drawCompleted||(!function(t){t.read({x:0,y:0,width:1,height:1,data:l})}(t),r.drawCompleted=!0),function s(l){var c=Math.min(n,a-l*n);0===l&&(window.cancelAnimationFrame(r.currentRafs[o]),delete r.currentRafs[o],h(t,i.scissorX,i.scissorY,i.scissorWidth,i.viewBoxSize[1])),r.clearOnly||(i.count=2*c,i.offset=2*l*n,e(i),l*n+c<a&&(r.currentRafs[o]=window.requestAnimationFrame((function(){s(l+1)}))),r.drawCompleted=!1)}(0)}function p(t,e){for(var r=new Array(256),n=0;n<256;n++)r[n]=t(n/255).concat(e);return r}function d(t,e){return(t>>>8*e)%256/255}function g(t,e,r){for(var n=new Array(8*e),a=0,i=0;i<e;i++)for(var o=0;o<2;o++)for(var s=0;s<4;s++){var l=4*t+s,c=r[64*i+l];63===l&&0===o&&(c*=-1),n[a++]=c}return n}function m(t){var e="0"+t;return e.substr(e.length-2)}function v(t){return t<o?"p"+m(t+1)+"_"+m(t+4):"colors"}function y(t,e,r,n,a,i,o,l,c,u,h,f,p){for(var d=[[],[]],g=0;g<64;g++)d[0][g]=g===a?1:0,d[1][g]=g===i?1:0;var m=t.lines.canvasOverdrag,v=t.domain,y=t.canvasWidth,x=t.canvasHeight,b=t.deselectedLines.color;return s.extendFlat({key:h,resolution:[y,x],viewBoxPos:[o+m,l],viewBoxSize:[c,u],i0:a,i1:i,dim0A:d[0].slice(0,16),dim0B:d[0].slice(16,32),dim0C:d[0].slice(32,48),dim0D:d[0].slice(48,64),dim1A:d[1].slice(0,16),dim1B:d[1].slice(16,32),dim1C:d[1].slice(32,48),dim1D:d[1].slice(48,64),drwLayer:f,contextColor:[b[0]/255,b[1]/255,b[2]/255,b[3]<1?b[3]:Math.max(1/255,Math.pow(1/t.lines.color.length,1/3))],scissorX:(n===e?0:o+m)+(t.pad.l-m)+t.layoutWidth*v.x[0],scissorWidth:(n===r?y-o+m:c+.5)+(n===e?o+m:0),scissorY:l+t.pad.b+t.layoutHeight*v.y[0],scissorHeight:u,viewportX:t.pad.l-m+t.layoutWidth*v.x[0],viewportY:t.pad.b+t.layoutHeight*v.y[0],viewportWidth:y,viewportHeight:x},p)}function x(t){var e=Math.max(0,Math.floor(2047*t[0]),0),r=Math.min(2047,Math.ceil(2047*t[1]),2047);return[Math.min(e,r),Math.max(e,r)]}e.exports=function(t,e){var r,n,l,m,b,_=e.context,w=e.pick,T=e.regl,k={currentRafs:{},drawCompleted:!0,clearOnly:!1},A=function(t){for(var e={},r=0;r<=o;r+=4)e[v(r)]=t.buffer({usage:"dynamic",type:"float",data:new Uint8Array(0)});return e}(T),M=T.texture(u),S=[];C(e);var E=T({profile:!1,blend:{enable:_,func:{srcRGB:"src alpha",dstRGB:"one minus src 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C(t){r=t.model,n=t.viewModel,l=n.dimensions.slice(),m=l[0]?l[0].values.length:0;var e=r.lines,a=w?e.color.map((function(t,r){return r/e.color.length})):e.color,i=function(t,e,r){for(var n,a=new Array(t*(o+4)),i=0,s=0;s<t;s++){for(var l=0;l<o;l++)a[i++]=l<e.length?e[l].paddedUnitValues[s]:.5;a[i++]=d(s,2),a[i++]=d(s,1),a[i++]=d(s,0),a[i++]=(n=r[s],Math.max(1e-6,Math.min(.999999,n)))}return a}(m,l,a);!function(t,e,r){for(var n=0;n<=o;n+=4)t[v(n)](g(n/4,e,r))}(A,m,i),_||w||(M=T.texture(s.extendFlat({data:p(r.unitToColor,255)},u)))}return{render:function(t,e,n){var a,i,o,s=t.length,c=1/0,u=-1/0;for(a=0;a<s;a++)t[a].dim0.canvasX<c&&(c=t[a].dim0.canvasX,i=a),t[a].dim1.canvasX>u&&(u=t[a].dim1.canvasX,o=a);0===s&&h(T,0,0,r.canvasWidth,r.canvasHeight);var p=function(t){var e,r,n,a=[[],[]];for(n=0;n<64;n++){var i=!t&&n<l.length?l[n].brush.filter.getBounds():[-1/0,1/0];a[0][n]=i[0],a[1][n]=i[1]}var o=new Array(16384);for(e=0;e<16384;e++)o[e]=255;if(!t)for(e=0;e<l.length;e++){var s=e%8,c=(e-s)/8,u=Math.pow(2,s),h=l[e].brush.filter.get();if(!(h.length<2)){var f=x(h[0])[1];for(r=1;r<h.length;r++){var p=x(h[r]);for(n=f+1;n<p[0];n++)o[8*n+c]&=~u;f=Math.max(f,p[1])}}}var d={shape:[8,2048],format:"alpha",type:"uint8",mag:"nearest",min:"nearest",data:o};return b?b(d):b=T.texture(d),{maskTexture:b,maskHeight:2048,loA:a[0].slice(0,16),loB:a[0].slice(16,32),loC:a[0].slice(32,48),loD:a[0].slice(48,64),hiA:a[1].slice(0,16),hiB:a[1].slice(16,32),hiC:a[1].slice(32,48),hiD:a[1].slice(48,64)}}(_);for(a=0;a<s;a++){var d=t[a],g=d.dim0.crossfilterDimensionIndex,v=d.dim1.crossfilterDimensionIndex,A=d.canvasX,M=d.canvasY,C=A+d.panelSizeX;if(e||!S[g]||S[g][0]!==A||S[g][1]!==C){S[g]=[A,C];var L=y(r,i,o,a,g,v,A,M,d.panelSizeX,d.panelSizeY,d.dim0.crossfilterDimensionIndex,_?0:w?2:1,p);k.clearOnly=n;var P=e?r.lines.blockLineCount:m;f(T,E,k,P,m,L)}}},readPixel:function(t,e){return T.read({x:t,y:e,width:1,height:1,data:c}),c},readPixels:function(t,e,r,n){var a=new Uint8Array(4*r*n);return T.read({x:t,y:e,width:r,height:n,data:a}),a},destroy:function(){for(var e in t.style["pointer-events"]="none",M.destroy(),b&&b.destroy(),A)A[e].destroy()},update:C}}},{"../../lib":728,"./constants":1100,glslify:408}],1105:[function(t,e,r){"use strict";e.exports=function(t,e,r,n){var a,i;for(n||(n=1/0),a=0;a<e.length;a++)(i=e[a]).visible&&(n=Math.min(n,i[r].length));for(n===1/0&&(n=0),t._length=n,a=0;a<e.length;a++)(i=e[a]).visible&&(i._length=n);return n}},{}],1106:[function(t,e,r){"use strict";var n=t("d3"),a=t("color-rgba"),i=t("../../plots/cartesian/axes"),o=t("../../lib"),s=t("../../lib/svg_text_utils"),l=t("../../components/drawing"),c=t("../../components/colorscale"),u=t("../../lib/gup"),h=u.keyFun,f=u.repeat,p=u.unwrap,d=t("./helpers"),g=t("./constants"),m=t("./axisbrush"),v=t("./lines");function y(t,e,r){return o.aggNums(t,null,e,r)}function x(t,e){return _(y(Math.min,t,e),y(Math.max,t,e))}function b(t){var e=t.range;return e?_(e[0],e[1]):x(t.values,t._length)}function 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S(t,e,r){var a=r.width,i=r.height,s=r.dimensions,l=r.canvasPixelRatio,c=function(t){return a*t/Math.max(1,r.colCount-1)},u=g.verticalPadding/i,h=function(t,e){return n.scale.linear().range([e,t-e])}(i,g.verticalPadding),f={key:r.key,xScale:c,model:r,inBrushDrag:!1},p={};return f.dimensions=s.filter(d.isVisible).map((function(a,s){var v=function(t,e){return n.scale.linear().domain(b(t)).range([e,1-e])}(a,u),y=p[a.label];p[a.label]=(y||0)+1;var x=a.label+(y?"__"+y:""),_=a.constraintrange,k=_&&_.length;k&&!Array.isArray(_[0])&&(_=[_]);var M=k?_.map((function(t){return t.map(v)})):[[-1/0,1/0]],S=a.values;S.length>a._length&&(S=S.slice(0,a._length));var E,C=a.tickvals;function L(t,e){return{val:t,text:E[e]}}function P(t,e){return t.val-e.val}if(Array.isArray(C)&&C.length){E=a.ticktext,Array.isArray(E)&&E.length?E.length>C.length?E=E.slice(0,C.length):C.length>E.length&&(C=C.slice(0,E.length)):E=C.map(n.format(a.tickformat));for(var I=1;I<C.length;I++)if(C[I]<C[I-1]){for(var z=C.map(L).sort(P),O=0;O<C.length;O++)C[O]=z[O].val,E[O]=z[O].text;break}}else C=void 0;return S=d.convertTypedArray(S),{key:x,label:a.label,tickFormat:a.tickformat,tickvals:C,ticktext:E,ordinal:d.isOrdinal(a),multiselect:a.multiselect,xIndex:s,crossfilterDimensionIndex:s,visibleIndex:a._index,height:i,values:S,paddedUnitValues:S.map(v),unitTickvals:C&&C.map(v),xScale:c,x:c(s),canvasX:c(s)*l,unitToPaddedPx:h,domainScale:w(i,g.verticalPadding,a,C,E),ordinalScale:T(a),parent:f,model:r,brush:m.makeBrush(t,k,M,(function(){t.linePickActive(!1)}),(function(){var e=f;e.focusLayer&&e.focusLayer.render(e.panels,!0);var r=A(e);!t.contextShown()&&r?(e.contextLayer&&e.contextLayer.render(e.panels,!0),t.contextShown(!0)):t.contextShown()&&!r&&(e.contextLayer&&e.contextLayer.render(e.panels,!0,!0),t.contextShown(!1))}),(function(r){if(f.focusLayer.render(f.panels,!0),f.pickLayer&&f.pickLayer.render(f.panels,!0),t.linePickActive(!0),e&&e.filterChanged){var n=v.invert,i=r.map((function(t){return t.map(n).sort(o.sorterAsc)})).sort((function(t,e){return t[0]-e[0]}));e.filterChanged(f.key,a._index,i)}}))}})),f}function E(t){t.classed(g.cn.axisExtentText,!0).attr("text-anchor","middle").style("cursor","default").style("user-select","none")}function C(t,e){var r="top"===e?1:-1,n=t*Math.PI/180;return{dir:r,dx:Math.sin(n),dy:Math.cos(n),degrees:t}}function L(t,e){for(var r=e.panels||(e.panels=[]),n=t.data(),a=0;a<n.length-1;a++){var i=r[a]||(r[a]={}),o=n[a],s=n[a+1];i.dim0=o,i.dim1=s,i.canvasX=o.canvasX,i.panelSizeX=s.canvasX-o.canvasX,i.panelSizeY=e.model.canvasHeight,i.y=0,i.canvasY=0}}function P(t,e){return i.tickText(t._ax,e,!1).text}function I(t,e){if(t.ordinal)return"";var r=t.domainScale.domain(),n=r[e?r.length-1:0];return P(t.model.dimensions[t.visibleIndex],n)}e.exports=function(t,e,r,a){var c=t._fullLayout,u=c._toppaper,y=c._glcontainer;!function(t){for(var e=0;e<t.length;e++)for(var r=0;r<t[e].length;r++)for(var n=t[e][r].trace,a=n.dimensions,o=0;o<a.length;o++){var s=a[o].values,l=a[o]._ax;l&&(l.range?l.range=_(l.range[0],l.range[1]):l.range=x(s,n._length),l.dtick||(l.dtick=.01*(Math.abs(l.range[1]-l.range[0])||1)),l.tickformat=a[o].tickformat,i.calcTicks(l),l.cleanRange())}}(e);var b,w,T=(b=!0,w=!1,{linePickActive:function(t){return arguments.length?b=!!t:b},contextShown:function(t){return arguments.length?w=!!t:w}}),k=e.filter((function(t){return p(t).trace.visible})).map(M.bind(0,r)).map(S.bind(0,T,a));y.each((function(t,e){return o.extendFlat(t,k[e])}));var z=y.selectAll(".gl-canvas").each((function(t){t.viewModel=k[0],t.model=t.viewModel?t.viewModel.model:null})),O=null;z.filter((function(t){return t.pick})).style("pointer-events","auto").on("mousemove",(function(t){if(T.linePickActive()&&t.lineLayer&&a&&a.hover){var e=n.event,r=this.width,i=this.height,o=n.mouse(this),s=o[0],l=o[1];if(s<0||l<0||s>=r||l>=i)return;var c=t.lineLayer.readPixel(s,i-1-l),u=0!==c[3],h=u?c[2]+256*(c[1]+256*c[0]):null,f={x:s,y:l,clientX:e.clientX,clientY:e.clientY,dataIndex:t.model.key,curveNumber:h};h!==O&&(u?a.hover(f):a.unhover&&a.unhover(f),O=h)}})),z.style("opacity",(function(t){return t.pick?0:1})),u.style("background","rgba(255, 255, 255, 0)");var D=u.selectAll("."+g.cn.parcoords).data(k,h);D.exit().remove(),D.enter().append("g").classed(g.cn.parcoords,!0).style("shape-rendering","crispEdges").style("pointer-events","none"),D.attr("transform",(function(t){return"translate("+t.model.translateX+","+t.model.translateY+")"}));var R=D.selectAll("."+g.cn.parcoordsControlView).data(f,h);R.enter().append("g").classed(g.cn.parcoordsControlView,!0),R.attr("transform",(function(t){return"translate("+t.model.pad.l+","+t.model.pad.t+")"}));var F=R.selectAll("."+g.cn.yAxis).data((function(t){return t.dimensions}),h);F.enter().append("g").classed(g.cn.yAxis,!0),R.each((function(t){L(F,t)})),z.each((function(t){if(t.viewModel){!t.lineLayer||a?t.lineLayer=v(this,t):t.lineLayer.update(t),(t.key||0===t.key)&&(t.viewModel[t.key]=t.lineLayer);var e=!t.context||a;t.lineLayer.render(t.viewModel.panels,e)}})),F.attr("transform",(function(t){return"translate("+t.xScale(t.xIndex)+", 0)"})),F.call(n.behavior.drag().origin((function(t){return t})).on("drag",(function(t){var e=t.parent;T.linePickActive(!1),t.x=Math.max(-g.overdrag,Math.min(t.model.width+g.overdrag,n.event.x)),t.canvasX=t.x*t.model.canvasPixelRatio,F.sort((function(t,e){return t.x-e.x})).each((function(e,r){e.xIndex=r,e.x=t===e?e.x:e.xScale(e.xIndex),e.canvasX=e.x*e.model.canvasPixelRatio})),L(F,e),F.filter((function(e){return 0!==Math.abs(t.xIndex-e.xIndex)})).attr("transform",(function(t){return"translate("+t.xScale(t.xIndex)+", 0)"})),n.select(this).attr("transform","translate("+t.x+", 0)"),F.each((function(r,n,a){a===t.parent.key&&(e.dimensions[n]=r)})),e.contextLayer&&e.contextLayer.render(e.panels,!1,!A(e)),e.focusLayer.render&&e.focusLayer.render(e.panels)})).on("dragend",(function(t){var e=t.parent;t.x=t.xScale(t.xIndex),t.canvasX=t.x*t.model.canvasPixelRatio,L(F,e),n.select(this).attr("transform",(function(t){return"translate("+t.x+", 0)"})),e.contextLayer&&e.contextLayer.render(e.panels,!1,!A(e)),e.focusLayer&&e.focusLayer.render(e.panels),e.pickLayer&&e.pickLayer.render(e.panels,!0),T.linePickActive(!0),a&&a.axesMoved&&a.axesMoved(e.key,e.dimensions.map((function(t){return t.crossfilterDimensionIndex})))}))),F.exit().remove();var B=F.selectAll("."+g.cn.axisOverlays).data(f,h);B.enter().append("g").classed(g.cn.axisOverlays,!0),B.selectAll("."+g.cn.axis).remove();var N=B.selectAll("."+g.cn.axis).data(f,h);N.enter().append("g").classed(g.cn.axis,!0),N.each((function(t){var e=t.model.height/t.model.tickDistance,r=t.domainScale,a=r.domain();n.select(this).call(n.svg.axis().orient("left").tickSize(4).outerTickSize(2).ticks(e,t.tickFormat).tickValues(t.ordinal?a:null).tickFormat((function(e){return d.isOrdinal(t)?e:P(t.model.dimensions[t.visibleIndex],e)})).scale(r)),l.font(N.selectAll("text"),t.model.tickFont)})),N.selectAll(".domain, .tick>line").attr("fill","none").attr("stroke","black").attr("stroke-opacity",.25).attr("stroke-width","1px"),N.selectAll("text").style("text-shadow","1px 1px 1px #fff, -1px -1px 1px #fff, 1px -1px 1px #fff, -1px 1px 1px #fff").style("cursor","default").style("user-select","none");var j=B.selectAll("."+g.cn.axisHeading).data(f,h);j.enter().append("g").classed(g.cn.axisHeading,!0);var V=j.selectAll("."+g.cn.axisTitle).data(f,h);V.enter().append("text").classed(g.cn.axisTitle,!0).attr("text-anchor","middle").style("cursor","ew-resize").style("user-select","none").style("pointer-events","auto"),V.text((function(t){return t.label})).each((function(e){var r=n.select(this);l.font(r,e.model.labelFont),s.convertToTspans(r,t)})).attr("transform",(function(t){var e=C(t.model.labelAngle,t.model.labelSide),r=g.axisTitleOffset;return(e.dir>0?"":"translate(0,"+(2*r+t.model.height)+")")+"rotate("+e.degrees+")translate("+-r*e.dx+","+-r*e.dy+")"})).attr("text-anchor",(function(t){var e=C(t.model.labelAngle,t.model.labelSide);return 2*Math.abs(e.dx)>Math.abs(e.dy)?e.dir*e.dx<0?"start":"end":"middle"}));var U=B.selectAll("."+g.cn.axisExtent).data(f,h);U.enter().append("g").classed(g.cn.axisExtent,!0);var q=U.selectAll("."+g.cn.axisExtentTop).data(f,h);q.enter().append("g").classed(g.cn.axisExtentTop,!0),q.attr("transform","translate(0,"+-g.axisExtentOffset+")");var H=q.selectAll("."+g.cn.axisExtentTopText).data(f,h);H.enter().append("text").classed(g.cn.axisExtentTopText,!0).call(E),H.text((function(t){return I(t,!0)})).each((function(t){l.font(n.select(this),t.model.rangeFont)}));var G=U.selectAll("."+g.cn.axisExtentBottom).data(f,h);G.enter().append("g").classed(g.cn.axisExtentBottom,!0),G.attr("transform",(function(t){return"translate(0,"+(t.model.height+g.axisExtentOffset)+")"}));var Y=G.selectAll("."+g.cn.axisExtentBottomText).data(f,h);Y.enter().append("text").classed(g.cn.axisExtentBottomText,!0).attr("dy","0.75em").call(E),Y.text((function(t){return I(t,!1)})).each((function(t){l.font(n.select(this),t.model.rangeFont)})),m.ensureAxisBrush(B)}},{"../../components/colorscale":607,"../../components/drawing":617,"../../lib":728,"../../lib/gup":726,"../../lib/svg_text_utils":752,"../../plots/cartesian/axes":776,"./axisbrush":1097,"./constants":1100,"./helpers":1102,"./lines":1104,"color-rgba":124,d3:164}],1107:[function(t,e,r){"use strict";var n=t("./parcoords"),a=t("../../lib/prepare_regl"),i=t("./helpers").isVisible;function o(t,e,r){var n=e.indexOf(r),a=t.indexOf(n);return-1===a&&(a+=e.length),a}e.exports=function(t,e){var r=t._fullLayout;if(a(t)){var s={},l={},c={},u={},h=r._size;e.forEach((function(e,r){var n=e[0].trace;c[r]=n.index;var a=u[r]=n._fullInput.index;s[r]=t.data[a].dimensions,l[r]=t.data[a].dimensions.slice()}));n(t,e,{width:h.w,height:h.h,margin:{t:h.t,r:h.r,b:h.b,l:h.l}},{filterChanged:function(e,n,a){var i=l[e][n],o=a.map((function(t){return t.slice()})),s="dimensions["+n+"].constraintrange",h=r._tracePreGUI[t._fullData[c[e]]._fullInput.uid];if(void 0===h[s]){var f=i.constraintrange;h[s]=f||null}var p=t._fullData[c[e]].dimensions[n];o.length?(1===o.length&&(o=o[0]),i.constraintrange=o,p.constraintrange=o.slice(),o=[o]):(delete i.constraintrange,delete p.constraintrange,o=null);var d={};d[s]=o,t.emit("plotly_restyle",[d,[u[e]]])},hover:function(e){t.emit("plotly_hover",e)},unhover:function(e){t.emit("plotly_unhover",e)},axesMoved:function(e,r){var n=function(t,e){return function(r,n){return o(t,e,r)-o(t,e,n)}}(r,l[e].filter(i));s[e].sort(n),l[e].filter((function(t){return!i(t)})).sort((function(t){return l[e].indexOf(t)})).forEach((function(t){s[e].splice(s[e].indexOf(t),1),s[e].splice(l[e].indexOf(t),0,t)})),t.emit("plotly_restyle",[{dimensions:[s[e]]},[u[e]]])}})}}},{"../../lib/prepare_regl":741,"./helpers":1102,"./parcoords":1106}],1108:[function(t,e,r){"use strict";var n=t("../../plots/attributes"),a=t("../../plots/domain").attributes,i=t("../../plots/font_attributes"),o=t("../../components/color/attributes"),s=t("../../plots/template_attributes").hovertemplateAttrs,l=t("../../plots/template_attributes").texttemplateAttrs,c=t("../../lib/extend").extendFlat,u=i({editType:"plot",arrayOk:!0,colorEditType:"plot"});e.exports={labels:{valType:"data_array",editType:"calc"},label0:{valType:"number",dflt:0,editType:"calc"},dlabel:{valType:"number",dflt:1,editType:"calc"},values:{valType:"data_array",editType:"calc"},marker:{colors:{valType:"data_array",editType:"calc"},line:{color:{valType:"color",dflt:o.defaultLine,arrayOk:!0,editType:"style"},width:{valType:"number",min:0,dflt:0,arrayOk:!0,editType:"style"},editType:"calc"},editType:"calc"},text:{valType:"data_array",editType:"plot"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"style"},scalegroup:{valType:"string",dflt:"",editType:"calc"},textinfo:{valType:"flaglist",flags:["label","text","value","percent"],extras:["none"],editType:"calc"},hoverinfo:c({},n.hoverinfo,{flags:["label","text","value","percent","name"]}),hovertemplate:s({},{keys:["label","color","value","percent","text"]}),texttemplate:l({editType:"plot"},{keys:["label","color","value","percent","text"]}),textposition:{valType:"enumerated",values:["inside","outside","auto","none"],dflt:"auto",arrayOk:!0,editType:"plot"},textfont:c({},u,{}),insidetextorientation:{valType:"enumerated",values:["horizontal","radial","tangential","auto"],dflt:"auto",editType:"plot"},insidetextfont:c({},u,{}),outsidetextfont:c({},u,{}),automargin:{valType:"boolean",dflt:!1,editType:"plot"},title:{text:{valType:"string",dflt:"",editType:"plot"},font:c({},u,{}),position:{valType:"enumerated",values:["top left","top center","top right","middle center","bottom left","bottom center","bottom right"],editType:"plot"},editType:"plot"},domain:a({name:"pie",trace:!0,editType:"calc"}),hole:{valType:"number",min:0,max:1,dflt:0,editType:"calc"},sort:{valType:"boolean",dflt:!0,editType:"calc"},direction:{valType:"enumerated",values:["clockwise","counterclockwise"],dflt:"counterclockwise",editType:"calc"},rotation:{valType:"number",min:-360,max:360,dflt:0,editType:"calc"},pull:{valType:"number",min:0,max:1,dflt:0,arrayOk:!0,editType:"calc"},_deprecated:{title:{valType:"string",dflt:"",editType:"calc"},titlefont:c({},u,{}),titleposition:{valType:"enumerated",values:["top left","top center","top right","middle center","bottom left","bottom center","bottom right"],editType:"calc"}}}},{"../../components/color/attributes":594,"../../lib/extend":719,"../../plots/attributes":773,"../../plots/domain":803,"../../plots/font_attributes":804,"../../plots/template_attributes":854}],1109:[function(t,e,r){"use strict";var n=t("../../plots/plots");r.name="pie",r.plot=function(t,e,a,i){n.plotBasePlot(r.name,t,e,a,i)},r.clean=function(t,e,a,i){n.cleanBasePlot(r.name,t,e,a,i)}},{"../../plots/plots":839}],1110:[function(t,e,r){"use strict";var n=t("fast-isnumeric"),a=t("tinycolor2"),i=t("../../components/color"),o={};function s(t){return function(e,r){return!!e&&(!!(e=a(e)).isValid()&&(e=i.addOpacity(e,e.getAlpha()),t[r]||(t[r]=e),e))}}function l(t,e){var r,n=JSON.stringify(t),i=e[n];if(!i){for(i=t.slice(),r=0;r<t.length;r++)i.push(a(t[r]).lighten(20).toHexString());for(r=0;r<t.length;r++)i.push(a(t[r]).darken(20).toHexString());e[n]=i}return i}e.exports={calc:function(t,e){var r,a,i=[],o=t._fullLayout,l=o.hiddenlabels||[],c=e.labels,u=e.marker.colors||[],h=e.values,f=e._length,p=e._hasValues&&f;if(e.dlabel)for(c=new Array(f),r=0;r<f;r++)c[r]=String(e.label0+r*e.dlabel);var d={},g=s(o["_"+e.type+"colormap"]),m=0,v=!1;for(r=0;r<f;r++){var y,x,b;if(p){if(y=h[r],!n(y))continue;if((y=+y)<0)continue}else y=1;void 0!==(x=c[r])&&""!==x||(x=r);var _=d[x=String(x)];void 0===_?(d[x]=i.length,(b=-1!==l.indexOf(x))||(m+=y),i.push({v:y,label:x,color:g(u[r],x),i:r,pts:[r],hidden:b})):(v=!0,(a=i[_]).v+=y,a.pts.push(r),a.hidden||(m+=y),!1===a.color&&u[r]&&(a.color=g(u[r],x)))}return("funnelarea"===e.type?v:e.sort)&&i.sort((function(t,e){return e.v-t.v})),i[0]&&(i[0].vTotal=m),i},crossTraceCalc:function(t,e){var r=(e||{}).type;r||(r="pie");var n=t._fullLayout,a=t.calcdata,i=n[r+"colorway"],s=n["_"+r+"colormap"];n["extend"+r+"colors"]&&(i=l(i,o));for(var c=0,u=0;u<a.length;u++){var h=a[u];if(h[0].trace.type===r)for(var f=0;f<h.length;f++){var p=h[f];!1===p.color&&(s[p.label]?p.color=s[p.label]:(s[p.label]=p.color=i[c%i.length],c++))}}},makePullColorFn:s,generateExtendedColors:l}},{"../../components/color":595,"fast-isnumeric":236,tinycolor2:528}],1111:[function(t,e,r){"use strict";var n=t("fast-isnumeric"),a=t("../../lib"),i=t("./attributes"),o=t("../../plots/domain").defaults,s=t("../bar/defaults").handleText;function l(t,e){var r=Array.isArray(t),i=a.isArrayOrTypedArray(e),o=Math.min(r?t.length:1/0,i?e.length:1/0);if(isFinite(o)||(o=0),o&&i){for(var s,l=0;l<o;l++){var c=e[l];if(n(c)&&c>0){s=!0;break}}s||(o=0)}return{hasLabels:r,hasValues:i,len:o}}e.exports={handleLabelsAndValues:l,supplyDefaults:function(t,e,r,n){function c(r,n){return a.coerce(t,e,i,r,n)}var u=l(c("labels"),c("values")),h=u.len;if(e._hasLabels=u.hasLabels,e._hasValues=u.hasValues,!e._hasLabels&&e._hasValues&&(c("label0"),c("dlabel")),h){e._length=h,c("marker.line.width")&&c("marker.line.color"),c("marker.colors"),c("scalegroup");var f,p=c("text"),d=c("texttemplate");if(d||(f=c("textinfo",Array.isArray(p)?"text+percent":"percent")),c("hovertext"),c("hovertemplate"),d||f&&"none"!==f){var g=c("textposition");s(t,e,n,c,g,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1}),(Array.isArray(g)||"auto"===g||"outside"===g)&&c("automargin"),("inside"===g||"auto"===g||Array.isArray(g))&&c("insidetextorientation")}o(e,n,c);var m=c("hole");if(c("title.text")){var v=c("title.position",m?"middle center":"top center");m||"middle center"!==v||(e.title.position="top center"),a.coerceFont(c,"title.font",n.font)}c("sort"),c("direction"),c("rotation"),c("pull")}else e.visible=!1}}},{"../../lib":728,"../../plots/domain":803,"../bar/defaults":873,"./attributes":1108,"fast-isnumeric":236}],1112:[function(t,e,r){"use strict";var n=t("../../components/fx/helpers").appendArrayMultiPointValues;e.exports=function(t,e){var r={curveNumber:e.index,pointNumbers:t.pts,data:e._input,fullData:e,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,v:t.v};return 1===t.pts.length&&(r.pointNumber=r.i=t.pts[0]),n(r,e,t.pts),"funnelarea"===e.type&&(delete r.v,delete r.i),r}},{"../../components/fx/helpers":631}],1113:[function(t,e,r){"use strict";var n=t("../../lib");r.formatPiePercent=function(t,e){var r=(100*t).toPrecision(3);return-1!==r.lastIndexOf(".")&&(r=r.replace(/[.]?0+$/,"")),n.numSeparate(r,e)+"%"},r.formatPieValue=function(t,e){var r=t.toPrecision(10);return-1!==r.lastIndexOf(".")&&(r=r.replace(/[.]?0+$/,"")),n.numSeparate(r,e)},r.getFirstFilled=function(t,e){if(Array.isArray(t))for(var r=0;r<e.length;r++){var n=t[e[r]];if(n||0===n||""===n)return n}},r.castOption=function(t,e){return Array.isArray(t)?r.getFirstFilled(t,e):t||void 0}},{"../../lib":728}],1114:[function(t,e,r){"use strict";e.exports={attributes:t("./attributes"),supplyDefaults:t("./defaults").supplyDefaults,supplyLayoutDefaults:t("./layout_defaults"),layoutAttributes:t("./layout_attributes"),calc:t("./calc").calc,crossTraceCalc:t("./calc").crossTraceCalc,plot:t("./plot").plot,style:t("./style"),styleOne:t("./style_one"),moduleType:"trace",name:"pie",basePlotModule:t("./base_plot"),categories:["pie-like","pie","showLegend"],meta:{}}},{"./attributes":1108,"./base_plot":1109,"./calc":1110,"./defaults":1111,"./layout_attributes":1115,"./layout_defaults":1116,"./plot":1117,"./style":1118,"./style_one":1119}],1115:[function(t,e,r){"use strict";e.exports={hiddenlabels:{valType:"data_array",editType:"calc"},piecolorway:{valType:"colorlist",editType:"calc"},extendpiecolors:{valType:"boolean",dflt:!0,editType:"calc"}}},{}],1116:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("./layout_attributes");e.exports=function(t,e){function r(r,i){return n.coerce(t,e,a,r,i)}r("hiddenlabels"),r("piecolorway",e.colorway),r("extendpiecolors")}},{"../../lib":728,"./layout_attributes":1115}],1117:[function(t,e,r){"use strict";var n=t("d3"),a=t("../../plots/plots"),i=t("../../components/fx"),o=t("../../components/color"),s=t("../../components/drawing"),l=t("../../lib"),c=t("../../lib/svg_text_utils"),u=t("../bar/uniform_text"),h=u.recordMinTextSize,f=u.clearMinTextSize,p=t("../bar/constants").TEXTPAD,d=t("./helpers"),g=t("./event_data"),m=t("../../lib").isValidTextValue;function v(t,e,r){var a=r[0],o=a.trace,s=a.cx,c=a.cy;"_hasHoverLabel"in o||(o._hasHoverLabel=!1),"_hasHoverEvent"in o||(o._hasHoverEvent=!1),t.on("mouseover",(function(t){var r=e._fullLayout,u=e._fullData[o.index];if(!e._dragging&&!1!==r.hovermode){var h=u.hoverinfo;if(Array.isArray(h)&&(h=i.castHoverinfo({hoverinfo:[d.castOption(h,t.pts)],_module:o._module},r,0)),"all"===h&&(h="label+text+value+percent+name"),u.hovertemplate||"none"!==h&&"skip"!==h&&h){var f=t.rInscribed||0,p=s+t.pxmid[0]*(1-f),m=c+t.pxmid[1]*(1-f),v=r.separators,y=[];if(h&&-1!==h.indexOf("label")&&y.push(t.label),t.text=d.castOption(u.hovertext||u.text,t.pts),h&&-1!==h.indexOf("text")){var x=t.text;l.isValidTextValue(x)&&y.push(x)}t.value=t.v,t.valueLabel=d.formatPieValue(t.v,v),h&&-1!==h.indexOf("value")&&y.push(t.valueLabel),t.percent=t.v/a.vTotal,t.percentLabel=d.formatPiePercent(t.percent,v),h&&-1!==h.indexOf("percent")&&y.push(t.percentLabel);var b=u.hoverlabel,_=b.font;i.loneHover({trace:o,x0:p-f*a.r,x1:p+f*a.r,y:m,text:y.join("<br>"),name:u.hovertemplate||-1!==h.indexOf("name")?u.name:void 0,idealAlign:t.pxmid[0]<0?"left":"right",color:d.castOption(b.bgcolor,t.pts)||t.color,borderColor:d.castOption(b.bordercolor,t.pts),fontFamily:d.castOption(_.family,t.pts),fontSize:d.castOption(_.size,t.pts),fontColor:d.castOption(_.color,t.pts),nameLength:d.castOption(b.namelength,t.pts),textAlign:d.castOption(b.align,t.pts),hovertemplate:d.castOption(u.hovertemplate,t.pts),hovertemplateLabels:t,eventData:[g(t,u)]},{container:r._hoverlayer.node(),outerContainer:r._paper.node(),gd:e}),o._hasHoverLabel=!0}o._hasHoverEvent=!0,e.emit("plotly_hover",{points:[g(t,u)],event:n.event})}})),t.on("mouseout",(function(t){var r=e._fullLayout,a=e._fullData[o.index],s=n.select(this).datum();o._hasHoverEvent&&(t.originalEvent=n.event,e.emit("plotly_unhover",{points:[g(s,a)],event:n.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(i.loneUnhover(r._hoverlayer.node()),o._hasHoverLabel=!1)})),t.on("click",(function(t){var r=e._fullLayout,a=e._fullData[o.index];e._dragging||!1===r.hovermode||(e._hoverdata=[g(t,a)],i.click(e,n.event))}))}function y(t,e,r){var n=d.castOption(t.insidetextfont.color,e.pts);!n&&t._input.textfont&&(n=d.castOption(t._input.textfont.color,e.pts));var a=d.castOption(t.insidetextfont.family,e.pts)||d.castOption(t.textfont.family,e.pts)||r.family,i=d.castOption(t.insidetextfont.size,e.pts)||d.castOption(t.textfont.size,e.pts)||r.size;return{color:n||o.contrast(e.color),family:a,size:i}}function x(t,e){for(var r,n,a=0;a<t.length;a++)if((n=(r=t[a][0]).trace).title.text){var i=n.title.text;n._meta&&(i=l.templateString(i,n._meta));var o=s.tester.append("text").attr("data-notex",1).text(i).call(s.font,n.title.font).call(c.convertToTspans,e),u=s.bBox(o.node(),!0);r.titleBox={width:u.width,height:u.height},o.remove()}}function b(t,e,r){var n=r.r||e.rpx1,a=e.rInscribed;if(e.startangle===e.stopangle)return{rCenter:1-a,scale:0,rotate:0,textPosAngle:0};var i,o=e.ring,s=1===o&&Math.abs(e.startangle-e.stopangle)===2*Math.PI,l=e.halfangle,c=e.midangle,u=r.trace.insidetextorientation,h="horizontal"===u,f="tangential"===u,p="radial"===u,d="auto"===u,g=[];if(!d){var m,v=function(r,a){if(function(t,e){var r=t.startangle,n=t.stopangle;return r>e&&e>n||r<e&&e<n}(e,r)){var s=Math.abs(r-e.startangle),l=Math.abs(r-e.stopangle),c=s<l?s:l;(i="tan"===a?w(t,n,o,c,0):_(t,n,o,c,Math.PI/2)).textPosAngle=r,g.push(i)}};if(h||f){for(m=4;m>=-4;m-=2)v(Math.PI*m,"tan");for(m=4;m>=-4;m-=2)v(Math.PI*(m+1),"tan")}if(h||p){for(m=4;m>=-4;m-=2)v(Math.PI*(m+1.5),"rad");for(m=4;m>=-4;m-=2)v(Math.PI*(m+.5),"rad")}}if(s||d||h){var y=Math.sqrt(t.width*t.width+t.height*t.height);if((i={scale:a*n*2/y,rCenter:1-a,rotate:0}).textPosAngle=(e.startangle+e.stopangle)/2,i.scale>=1)return i;g.push(i)}(d||p)&&((i=_(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(i)),(d||f)&&((i=w(t,n,o,l,c)).textPosAngle=(e.startangle+e.stopangle)/2,g.push(i));for(var x=0,b=0,T=0;T<g.length;T++){var k=g[T].scale;if(b<k&&(b=k,x=T),!d&&b>=1)break}return g[x]}function _(t,e,r,n,a){e=Math.max(0,e-2*p);var i=t.width/t.height,o=A(i,n,e,r);return{scale:2*o/t.height,rCenter:T(i,o/e),rotate:k(a)}}function w(t,e,r,n,a){e=Math.max(0,e-2*p);var i=t.height/t.width,o=A(i,n,e,r);return{scale:2*o/t.width,rCenter:T(i,o/e),rotate:k(a+Math.PI/2)}}function T(t,e){return Math.cos(e)-t*e}function k(t){return(180/Math.PI*t+720)%180-90}function A(t,e,r,n){var a=t+1/(2*Math.tan(e));return r*Math.min(1/(Math.sqrt(a*a+.5)+a),n/(Math.sqrt(t*t+n/2)+t))}function M(t,e){return t.v!==e.vTotal||e.trace.hole?Math.min(1/(1+1/Math.sin(t.halfangle)),t.ring/2):1}function S(t,e){var r=e.pxmid[0],n=e.pxmid[1],a=t.width/2,i=t.height/2;return r<0&&(a*=-1),n<0&&(i*=-1),{scale:1,rCenter:1,rotate:0,x:a+Math.abs(i)*(a>0?1:-1)/2,y:i/(1+r*r/(n*n)),outside:!0}}function E(t,e){var r,n,a,i=t.trace,o={x:t.cx,y:t.cy},s={tx:0,ty:0};s.ty+=i.title.font.size,a=L(i),-1!==i.title.position.indexOf("top")?(o.y-=(1+a)*t.r,s.ty-=t.titleBox.height):-1!==i.title.position.indexOf("bottom")&&(o.y+=(1+a)*t.r);var l,c,u=(l=t.r,c=t.trace.aspectratio,l/(void 0===c?1:c)),h=e.w*(i.domain.x[1]-i.domain.x[0])/2;return-1!==i.title.position.indexOf("left")?(h+=u,o.x-=(1+a)*u,s.tx+=t.titleBox.width/2):-1!==i.title.position.indexOf("center")?h*=2:-1!==i.title.position.indexOf("right")&&(h+=u,o.x+=(1+a)*u,s.tx-=t.titleBox.width/2),r=h/t.titleBox.width,n=C(t,e)/t.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function C(t,e){var r=t.trace,n=e.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(t.titleBox.height,n/2)}function L(t){var e,r=t.pull;if(!r)return 0;if(Array.isArray(r))for(r=0,e=0;e<t.pull.length;e++)t.pull[e]>r&&(r=t.pull[e]);return r}function P(t,e){for(var r=[],n=0;n<t.length;n++){var a=t[n][0],i=a.trace,o=i.domain,s=e.w*(o.x[1]-o.x[0]),l=e.h*(o.y[1]-o.y[0]);i.title.text&&"middle center"!==i.title.position&&(l-=C(a,e));var c=s/2,u=l/2;"funnelarea"!==i.type||i.scalegroup||(u/=i.aspectratio),a.r=Math.min(c,u)/(1+L(i)),a.cx=e.l+e.w*(i.domain.x[1]+i.domain.x[0])/2,a.cy=e.t+e.h*(1-i.domain.y[0])-l/2,i.title.text&&-1!==i.title.position.indexOf("bottom")&&(a.cy-=C(a,e)),i.scalegroup&&-1===r.indexOf(i.scalegroup)&&r.push(i.scalegroup)}!function(t,e){for(var r,n,a,i=0;i<e.length;i++){var o=1/0,s=e[i];for(n=0;n<t.length;n++)if(r=t[n][0],(a=r.trace).scalegroup===s){var l;if("pie"===a.type)l=r.r*r.r;else if("funnelarea"===a.type){var c,u;a.aspectratio>1?(c=r.r,u=c/a.aspectratio):(u=r.r,c=u*a.aspectratio),c*=(1+a.baseratio)/2,l=c*u}o=Math.min(o,l/r.vTotal)}for(n=0;n<t.length;n++)if(r=t[n][0],(a=r.trace).scalegroup===s){var h=o*r.vTotal;"funnelarea"===a.type&&(h/=(1+a.baseratio)/2,h/=a.aspectratio),r.r=Math.sqrt(h)}}}(t,r)}function I(t,e){return[t*Math.sin(e),-t*Math.cos(e)]}function z(t,e,r){var n=t._fullLayout,a=r.trace,i=a.texttemplate,o=a.textinfo;if(!i&&o&&"none"!==o){var s,c=o.split("+"),u=function(t){return-1!==c.indexOf(t)},h=u("label"),f=u("text"),p=u("value"),g=u("percent"),v=n.separators;if(s=h?[e.label]:[],f){var y=d.getFirstFilled(a.text,e.pts);m(y)&&s.push(y)}p&&s.push(d.formatPieValue(e.v,v)),g&&s.push(d.formatPiePercent(e.v/r.vTotal,v)),e.text=s.join("<br>")}if(i){var x=l.castOption(a,e.i,"texttemplate");if(x){var b=function(t){return{label:t.label,value:t.v,valueLabel:d.formatPieValue(t.v,n.separators),percent:t.v/r.vTotal,percentLabel:d.formatPiePercent(t.v/r.vTotal,n.separators),color:t.color,text:t.text,customdata:l.castOption(a,t.i,"customdata")}}(e),_=d.getFirstFilled(a.text,e.pts);(m(_)||""===_)&&(b.text=_),e.text=l.texttemplateString(x,b,t._fullLayout._d3locale,b,a._meta||{})}else e.text=""}}function O(t,e){var r=t.rotate*Math.PI/180,n=Math.cos(r),a=Math.sin(r),i=(e.left+e.right)/2,o=(e.top+e.bottom)/2;t.textX=i*n-o*a,t.textY=i*a+o*n,t.noCenter=!0}e.exports={plot:function(t,e){var r=t._fullLayout,i=r._size;f("pie",r),x(e,t),P(e,i);var u=l.makeTraceGroups(r._pielayer,e,"trace").each((function(e){var u=n.select(this),f=e[0],p=f.trace;!function(t){var e,r,n,a=t[0],i=a.r,o=a.trace,s=o.rotation*Math.PI/180,l=2*Math.PI/a.vTotal,c="px0",u="px1";if("counterclockwise"===o.direction){for(e=0;e<t.length&&t[e].hidden;e++);if(e===t.length)return;s+=l*t[e].v,l*=-1,c="px1",u="px0"}for(n=I(i,s),e=0;e<t.length;e++)(r=t[e]).hidden||(r[c]=n,r.startangle=s,s+=l*r.v/2,r.pxmid=I(i,s),r.midangle=s,s+=l*r.v/2,n=I(i,s),r.stopangle=s,r[u]=n,r.largeArc=r.v>a.vTotal/2?1:0,r.halfangle=Math.PI*Math.min(r.v/a.vTotal,.5),r.ring=1-o.hole,r.rInscribed=M(r,a))}(e),u.attr("stroke-linejoin","round"),u.each((function(){var g=n.select(this).selectAll("g.slice").data(e);g.enter().append("g").classed("slice",!0),g.exit().remove();var m=[[[],[]],[[],[]]],x=!1;g.each((function(a,i){if(a.hidden)n.select(this).selectAll("path,g").remove();else{a.pointNumber=a.i,a.curveNumber=p.index,m[a.pxmid[1]<0?0:1][a.pxmid[0]<0?0:1].push(a);var o=f.cx,u=f.cy,g=n.select(this),_=g.selectAll("path.surface").data([a]);if(_.enter().append("path").classed("surface",!0).style({"pointer-events":"all"}),g.call(v,t,e),p.pull){var w=+d.castOption(p.pull,a.pts)||0;w>0&&(o+=w*a.pxmid[0],u+=w*a.pxmid[1])}a.cxFinal=o,a.cyFinal=u;var T=p.hole;if(a.v===f.vTotal){var k="M"+(o+a.px0[0])+","+(u+a.px0[1])+L(a.px0,a.pxmid,!0,1)+L(a.pxmid,a.px0,!0,1)+"Z";T?_.attr("d","M"+(o+T*a.px0[0])+","+(u+T*a.px0[1])+L(a.px0,a.pxmid,!1,T)+L(a.pxmid,a.px0,!1,T)+"Z"+k):_.attr("d",k)}else{var A=L(a.px0,a.px1,!0,1);if(T){var M=1-T;_.attr("d","M"+(o+T*a.px1[0])+","+(u+T*a.px1[1])+L(a.px1,a.px0,!1,T)+"l"+M*a.px0[0]+","+M*a.px0[1]+A+"Z")}else _.attr("d","M"+o+","+u+"l"+a.px0[0]+","+a.px0[1]+A+"Z")}z(t,a,f);var E=d.castOption(p.textposition,a.pts),C=g.selectAll("g.slicetext").data(a.text&&"none"!==E?[0]:[]);C.enter().append("g").classed("slicetext",!0),C.exit().remove(),C.each((function(){var g=l.ensureSingle(n.select(this),"text","",(function(t){t.attr("data-notex",1)})),m=l.ensureUniformFontSize(t,"outside"===E?function(t,e,r){var n=d.castOption(t.outsidetextfont.color,e.pts)||d.castOption(t.textfont.color,e.pts)||r.color,a=d.castOption(t.outsidetextfont.family,e.pts)||d.castOption(t.textfont.family,e.pts)||r.family,i=d.castOption(t.outsidetextfont.size,e.pts)||d.castOption(t.textfont.size,e.pts)||r.size;return{color:n,family:a,size:i}}(p,a,r.font):y(p,a,r.font));g.text(a.text).attr({class:"slicetext",transform:"","text-anchor":"middle"}).call(s.font,m).call(c.convertToTspans,t);var v,_=s.bBox(g.node());if("outside"===E)v=S(_,a);else if(v=b(_,a,f),"auto"===E&&v.scale<1){var w=l.ensureUniformFontSize(t,p.outsidetextfont);g.call(s.font,w),v=S(_=s.bBox(g.node()),a)}var T=v.textPosAngle,k=void 0===T?a.pxmid:I(f.r,T);if(v.targetX=o+k[0]*v.rCenter+(v.x||0),v.targetY=u+k[1]*v.rCenter+(v.y||0),O(v,_),v.outside){var A=v.targetY;a.yLabelMin=A-_.height/2,a.yLabelMid=A,a.yLabelMax=A+_.height/2,a.labelExtraX=0,a.labelExtraY=0,x=!0}v.fontSize=m.size,h(p.type,v,r),e[i].transform=v,g.attr("transform",l.getTextTransform(v))}))}function L(t,e,r,n){var i=n*(e[0]-t[0]),o=n*(e[1]-t[1]);return"a"+n*f.r+","+n*f.r+" 0 "+a.largeArc+(r?" 1 ":" 0 ")+i+","+o}}));var _=n.select(this).selectAll("g.titletext").data(p.title.text?[0]:[]);if(_.enter().append("g").classed("titletext",!0),_.exit().remove(),_.each((function(){var e,r=l.ensureSingle(n.select(this),"text","",(function(t){t.attr("data-notex",1)})),a=p.title.text;p._meta&&(a=l.templateString(a,p._meta)),r.text(a).attr({class:"titletext",transform:"","text-anchor":"middle"}).call(s.font,p.title.font).call(c.convertToTspans,t),e="middle center"===p.title.position?function(t){var e=Math.sqrt(t.titleBox.width*t.titleBox.width+t.titleBox.height*t.titleBox.height);return{x:t.cx,y:t.cy,scale:t.trace.hole*t.r*2/e,tx:0,ty:-t.titleBox.height/2+t.trace.title.font.size}}(f):E(f,i),r.attr("transform","translate("+e.x+","+e.y+")"+(e.scale<1?"scale("+e.scale+")":"")+"translate("+e.tx+","+e.ty+")")})),x&&function(t,e){var r,n,a,i,o,s,l,c,u,h,f,p,g;function m(t,e){return t.pxmid[1]-e.pxmid[1]}function v(t,e){return e.pxmid[1]-t.pxmid[1]}function y(t,r){r||(r={});var a,c,u,f,p=r.labelExtraY+(n?r.yLabelMax:r.yLabelMin),g=n?t.yLabelMin:t.yLabelMax,m=n?t.yLabelMax:t.yLabelMin,v=t.cyFinal+o(t.px0[1],t.px1[1]),y=p-g;if(y*l>0&&(t.labelExtraY=y),Array.isArray(e.pull))for(c=0;c<h.length;c++)(u=h[c])===t||(d.castOption(e.pull,t.pts)||0)>=(d.castOption(e.pull,u.pts)||0)||((t.pxmid[1]-u.pxmid[1])*l>0?(y=u.cyFinal+o(u.px0[1],u.px1[1])-g-t.labelExtraY)*l>0&&(t.labelExtraY+=y):(m+t.labelExtraY-v)*l>0&&(a=3*s*Math.abs(c-h.indexOf(t)),(f=u.cxFinal+i(u.px0[0],u.px1[0])+a-(t.cxFinal+t.pxmid[0])-t.labelExtraX)*s>0&&(t.labelExtraX+=f)))}for(n=0;n<2;n++)for(a=n?m:v,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(i=r?Math.max:Math.min,s=r?1:-1,(c=t[n][r]).sort(a),u=t[1-n][r],h=u.concat(c),p=[],f=0;f<c.length;f++)void 0!==c[f].yLabelMid&&p.push(c[f]);for(g=!1,f=0;n&&f<u.length;f++)if(void 0!==u[f].yLabelMid){g=u[f];break}for(f=0;f<p.length;f++){var x=f&&p[f-1];g&&!f&&(x=g),y(p[f],x)}}}(m,p),function(t,e){t.each((function(t){var r=n.select(this);if(t.labelExtraX||t.labelExtraY){var a=r.select("g.slicetext text");t.transform.targetX+=t.labelExtraX,t.transform.targetY+=t.labelExtraY,a.attr("transform",l.getTextTransform(t.transform));var i=t.cxFinal+t.pxmid[0],s="M"+i+","+(t.cyFinal+t.pxmid[1]),c=(t.yLabelMax-t.yLabelMin)*(t.pxmid[0]<0?-1:1)/4;if(t.labelExtraX){var u=t.labelExtraX*t.pxmid[1]/t.pxmid[0],h=t.yLabelMid+t.labelExtraY-(t.cyFinal+t.pxmid[1]);Math.abs(u)>Math.abs(h)?s+="l"+h*t.pxmid[0]/t.pxmid[1]+","+h+"H"+(i+t.labelExtraX+c):s+="l"+t.labelExtraX+","+u+"v"+(h-u)+"h"+c}else s+="V"+(t.yLabelMid+t.labelExtraY)+"h"+c;l.ensureSingle(r,"path","textline").call(o.stroke,e.outsidetextfont.color).attr({"stroke-width":Math.min(2,e.outsidetextfont.size/8),d:s,fill:"none"})}else r.select("path.textline").remove()}))}(g,p),x&&p.automargin){var w=s.bBox(u.node()),T=p.domain,k=i.w*(T.x[1]-T.x[0]),A=i.h*(T.y[1]-T.y[0]),M=(.5*k-f.r)/i.w,C=(.5*A-f.r)/i.h;a.autoMargin(t,"pie."+p.uid+".automargin",{xl:T.x[0]-M,xr:T.x[1]+M,yb:T.y[0]-C,yt:T.y[1]+C,l:Math.max(f.cx-f.r-w.left,0),r:Math.max(w.right-(f.cx+f.r),0),b:Math.max(w.bottom-(f.cy+f.r),0),t:Math.max(f.cy-f.r-w.top,0),pad:5})}}))}));setTimeout((function(){u.selectAll("tspan").each((function(){var t=n.select(this);t.attr("dy")&&t.attr("dy",t.attr("dy"))}))}),0)},formatSliceLabel:z,transformInsideText:b,determineInsideTextFont:y,positionTitleOutside:E,prerenderTitles:x,layoutAreas:P,attachFxHandlers:v,computeTransform:O}},{"../../components/color":595,"../../components/drawing":617,"../../components/fx":635,"../../lib":728,"../../lib/svg_text_utils":752,"../../plots/plots":839,"../bar/constants":871,"../bar/uniform_text":885,"./event_data":1112,"./helpers":1113,d3:164}],1118:[function(t,e,r){"use strict";var n=t("d3"),a=t("./style_one"),i=t("../bar/uniform_text").resizeText;e.exports=function(t){var e=t._fullLayout._pielayer.selectAll(".trace");i(t,e,"pie"),e.each((function(t){var e=t[0].trace,r=n.select(this);r.style({opacity:e.opacity}),r.selectAll("path.surface").each((function(t){n.select(this).call(a,t,e)}))}))}},{"../bar/uniform_text":885,"./style_one":1119,d3:164}],1119:[function(t,e,r){"use strict";var n=t("../../components/color"),a=t("./helpers").castOption;e.exports=function(t,e,r){var i=r.marker.line,o=a(i.color,e.pts)||n.defaultLine,s=a(i.width,e.pts)||0;t.style("stroke-width",s).call(n.fill,e.color).call(n.stroke,o)}},{"../../components/color":595,"./helpers":1113}],1120:[function(t,e,r){"use strict";var n=t("../scatter/attributes");e.exports={x:n.x,y:n.y,xy:{valType:"data_array",editType:"calc"},indices:{valType:"data_array",editType:"calc"},xbounds:{valType:"data_array",editType:"calc"},ybounds:{valType:"data_array",editType:"calc"},text:n.text,marker:{color:{valType:"color",arrayOk:!1,editType:"calc"},opacity:{valType:"number",min:0,max:1,dflt:1,arrayOk:!1,editType:"calc"},blend:{valType:"boolean",dflt:null,editType:"calc"},sizemin:{valType:"number",min:.1,max:2,dflt:.5,editType:"calc"},sizemax:{valType:"number",min:.1,dflt:20,editType:"calc"},border:{color:{valType:"color",arrayOk:!1,editType:"calc"},arearatio:{valType:"number",min:0,max:1,dflt:0,editType:"calc"},editType:"calc"},editType:"calc"},transforms:void 0}},{"../scatter/attributes":1134}],1121:[function(t,e,r){"use strict";var n=t("gl-pointcloud2d"),a=t("../../lib/str2rgbarray"),i=t("../../plots/cartesian/autorange").findExtremes,o=t("../scatter/get_trace_color");function s(t,e){this.scene=t,this.uid=e,this.type="pointcloud",this.pickXData=[],this.pickYData=[],this.xData=[],this.yData=[],this.textLabels=[],this.color="rgb(0, 0, 0)",this.name="",this.hoverinfo="all",this.idToIndex=new Int32Array(0),this.bounds=[0,0,0,0],this.pointcloudOptions={positions:new Float32Array(0),idToIndex:this.idToIndex,sizemin:.5,sizemax:12,color:[0,0,0,1],areaRatio:1,borderColor:[0,0,0,1]},this.pointcloud=n(t.glplot,this.pointcloudOptions),this.pointcloud._trace=this}var l=s.prototype;l.handlePick=function(t){var e=this.idToIndex[t.pointId];return{trace:this,dataCoord:t.dataCoord,traceCoord:this.pickXYData?[this.pickXYData[2*e],this.pickXYData[2*e+1]]:[this.pickXData[e],this.pickYData[e]],textLabel:Array.isArray(this.textLabels)?this.textLabels[e]:this.textLabels,color:this.color,name:this.name,pointIndex:e,hoverinfo:this.hoverinfo}},l.update=function(t){this.index=t.index,this.textLabels=t.text,this.name=t.name,this.hoverinfo=t.hoverinfo,this.bounds=[1/0,1/0,-1/0,-1/0],this.updateFast(t),this.color=o(t,{})},l.updateFast=function(t){var e,r,n,o,s,l,c=this.xData=this.pickXData=t.x,u=this.yData=this.pickYData=t.y,h=this.pickXYData=t.xy,f=t.xbounds&&t.ybounds,p=t.indices,d=this.bounds;if(h){if(n=h,e=h.length>>>1,f)d[0]=t.xbounds[0],d[2]=t.xbounds[1],d[1]=t.ybounds[0],d[3]=t.ybounds[1];else for(l=0;l<e;l++)o=n[2*l],s=n[2*l+1],o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);if(p)r=p;else for(r=new Int32Array(e),l=0;l<e;l++)r[l]=l}else for(e=c.length,n=new Float32Array(2*e),r=new Int32Array(e),l=0;l<e;l++)o=c[l],s=u[l],r[l]=l,n[2*l]=o,n[2*l+1]=s,o<d[0]&&(d[0]=o),o>d[2]&&(d[2]=o),s<d[1]&&(d[1]=s),s>d[3]&&(d[3]=s);this.idToIndex=r,this.pointcloudOptions.idToIndex=r,this.pointcloudOptions.positions=n;var g=a(t.marker.color),m=a(t.marker.border.color),v=t.opacity*t.marker.opacity;g[3]*=v,this.pointcloudOptions.color=g;var y=t.marker.blend;if(null===y){y=c.length<100||u.length<100}this.pointcloudOptions.blend=y,m[3]*=v,this.pointcloudOptions.borderColor=m;var x=t.marker.sizemin,b=Math.max(t.marker.sizemax,t.marker.sizemin);this.pointcloudOptions.sizeMin=x,this.pointcloudOptions.sizeMax=b,this.pointcloudOptions.areaRatio=t.marker.border.arearatio,this.pointcloud.update(this.pointcloudOptions);var _=this.scene.xaxis,w=this.scene.yaxis,T=b/2||.5;t._extremes[_._id]=i(_,[d[0],d[2]],{ppad:T}),t._extremes[w._id]=i(w,[d[1],d[3]],{ppad:T})},l.dispose=function(){this.pointcloud.dispose()},e.exports=function(t,e){var r=new s(t,e.uid);return 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s=t[n[_].index];s.x0>o+d&&(i+=1,e=s.x0),o=s.x0,a[i]||(a[i]=[]),a[i].push(s),r=e-s.x0,s.x0+=r,s.x1+=r}return a}(y=k.nodes));a.update(k)}return{circular:b,key:r,trace:s,guid:h.randstr(),horizontal:f,width:m,height:v,nodePad:s.node.pad,nodeLineColor:s.node.line.color,nodeLineWidth:s.node.line.width,linkLineColor:s.link.line.color,linkLineWidth:s.link.line.width,valueFormat:s.valueformat,valueSuffix:s.valuesuffix,textFont:s.textfont,translateX:u.x[0]*t.width+t.margin.l,translateY:t.height-u.y[1]*t.height+t.margin.t,dragParallel:f?v:m,dragPerpendicular:f?m:v,arrangement:s.arrangement,sankey:a,graph:k,forceLayouts:{},interactionState:{dragInProgress:!1,hovered:!1}}}function x(t,e,r){var n=i(e.color),a=e.source.label+"|"+e.target.label+"__"+r;return e.trace=t.trace,e.curveNumber=t.trace.index,{circular:t.circular,key:a,traceId:t.key,pointNumber:e.pointNumber,link:e,tinyColorHue:o.tinyRGB(n),tinyColorAlpha:n.getAlpha(),linkPath:b,linkLineColor:t.linkLineColor,linkLineWidth:t.linkLineWidth,valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,parent:t,interactionState:t.interactionState,flow:e.flow}}function b(){return function(t){if(t.link.circular)return e=t.link,r=e.width/2,n=e.circularPathData,"top"===e.circularLinkType?"M "+n.targetX+" "+(n.targetY+r)+" L"+n.rightInnerExtent+" "+(n.targetY+r)+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightSmallArcRadius+r)+" 0 0 1 "+(n.rightFullExtent-r)+" "+(n.targetY-n.rightSmallArcRadius)+"L"+(n.rightFullExtent-r)+" "+n.verticalRightInnerExtent+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightLargeArcRadius+r)+" 0 0 1 "+n.rightInnerExtent+" "+(n.verticalFullExtent-r)+"L"+n.leftInnerExtent+" "+(n.verticalFullExtent-r)+"A"+(n.leftLargeArcRadius+r)+" "+(n.leftLargeArcRadius+r)+" 0 0 1 "+(n.leftFullExtent+r)+" "+n.verticalLeftInnerExtent+"L"+(n.leftFullExtent+r)+" "+(n.sourceY-n.leftSmallArcRadius)+"A"+(n.leftLargeArcRadius+r)+" "+(n.leftSmallArcRadius+r)+" 0 0 1 "+n.leftInnerExtent+" "+(n.sourceY+r)+"L"+n.sourceX+" "+(n.sourceY+r)+"L"+n.sourceX+" "+(n.sourceY-r)+"L"+n.leftInnerExtent+" "+(n.sourceY-r)+"A"+(n.leftLargeArcRadius-r)+" "+(n.leftSmallArcRadius-r)+" 0 0 0 "+(n.leftFullExtent-r)+" "+(n.sourceY-n.leftSmallArcRadius)+"L"+(n.leftFullExtent-r)+" "+n.verticalLeftInnerExtent+"A"+(n.leftLargeArcRadius-r)+" "+(n.leftLargeArcRadius-r)+" 0 0 0 "+n.leftInnerExtent+" "+(n.verticalFullExtent+r)+"L"+n.rightInnerExtent+" "+(n.verticalFullExtent+r)+"A"+(n.rightLargeArcRadius-r)+" "+(n.rightLargeArcRadius-r)+" 0 0 0 "+(n.rightFullExtent+r)+" "+n.verticalRightInnerExtent+"L"+(n.rightFullExtent+r)+" "+(n.targetY-n.rightSmallArcRadius)+"A"+(n.rightLargeArcRadius-r)+" "+(n.rightSmallArcRadius-r)+" 0 0 0 "+n.rightInnerExtent+" "+(n.targetY-r)+"L"+n.targetX+" "+(n.targetY-r)+"Z":"M "+n.targetX+" "+(n.targetY-r)+" L"+n.rightInnerExtent+" "+(n.targetY-r)+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightSmallArcRadius+r)+" 0 0 0 "+(n.rightFullExtent-r)+" "+(n.targetY+n.rightSmallArcRadius)+"L"+(n.rightFullExtent-r)+" "+n.verticalRightInnerExtent+"A"+(n.rightLargeArcRadius+r)+" "+(n.rightLargeArcRadius+r)+" 0 0 0 "+n.rightInnerExtent+" "+(n.verticalFullExtent+r)+"L"+n.leftInnerExtent+" "+(n.verticalFullExtent+r)+"A"+(n.leftLargeArcRadius+r)+" "+(n.leftLargeArcRadius+r)+" 0 0 0 "+(n.leftFullExtent+r)+" "+n.verticalLeftInnerExtent+"L"+(n.leftFullExtent+r)+" "+(n.sourceY+n.leftSmallArcRadius)+"A"+(n.leftLargeArcRadius+r)+" "+(n.leftSmallArcRadius+r)+" 0 0 0 "+n.leftInnerExtent+" "+(n.sourceY-r)+"L"+n.sourceX+" "+(n.sourceY-r)+"L"+n.sourceX+" "+(n.sourceY+r)+"L"+n.leftInnerExtent+" "+(n.sourceY+r)+"A"+(n.leftLargeArcRadius-r)+" "+(n.leftSmallArcRadius-r)+" 0 0 1 "+(n.leftFullExtent-r)+" "+(n.sourceY+n.leftSmallArcRadius)+"L"+(n.leftFullExtent-r)+" "+n.verticalLeftInnerExtent+"A"+(n.leftLargeArcRadius-r)+" "+(n.leftLargeArcRadius-r)+" 0 0 1 "+n.leftInnerExtent+" "+(n.verticalFullExtent-r)+"L"+n.rightInnerExtent+" "+(n.verticalFullExtent-r)+"A"+(n.rightLargeArcRadius-r)+" "+(n.rightLargeArcRadius-r)+" 0 0 1 "+(n.rightFullExtent+r)+" "+n.verticalRightInnerExtent+"L"+(n.rightFullExtent+r)+" "+(n.targetY+n.rightSmallArcRadius)+"A"+(n.rightLargeArcRadius-r)+" "+(n.rightSmallArcRadius-r)+" 0 0 1 "+n.rightInnerExtent+" "+(n.targetY+r)+"L"+n.targetX+" "+(n.targetY+r)+"Z";var e,r,n,a=t.link.source.x1,i=t.link.target.x0,o=m(a,i),s=o(.5),l=o(.5),c=t.link.y0-t.link.width/2,u=t.link.y0+t.link.width/2,h=t.link.y1-t.link.width/2,f=t.link.y1+t.link.width/2;return"M"+a+","+c+"C"+s+","+c+" "+l+","+h+" "+i+","+h+"L"+i+","+f+"C"+l+","+f+" "+s+","+u+" "+a+","+u+"Z"}}function _(t,e){var r=i(e.color),a=n.nodePadAcross,s=t.nodePad/2;e.dx=e.x1-e.x0,e.dy=e.y1-e.y0;var l=e.dx,c=Math.max(.5,e.dy),u="node_"+e.pointNumber;return e.group&&(u=h.randstr()),e.trace=t.trace,e.curveNumber=t.trace.index,{index:e.pointNumber,key:u,partOfGroup:e.partOfGroup||!1,group:e.group,traceId:t.key,trace:t.trace,node:e,nodePad:t.nodePad,nodeLineColor:t.nodeLineColor,nodeLineWidth:t.nodeLineWidth,textFont:t.textFont,size:t.horizontal?t.height:t.width,visibleWidth:Math.ceil(l),visibleHeight:c,zoneX:-a,zoneY:-s,zoneWidth:l+2*a,zoneHeight:c+2*s,labelY:t.horizontal?e.dy/2+1:e.dx/2+1,left:1===e.originalLayer,sizeAcross:t.width,forceLayouts:t.forceLayouts,horizontal:t.horizontal,darkBackground:r.getBrightness()<=128,tinyColorHue:o.tinyRGB(r),tinyColorAlpha:r.getAlpha(),valueFormat:t.valueFormat,valueSuffix:t.valueSuffix,sankey:t.sankey,graph:t.graph,arrangement:t.arrangement,uniqueNodeLabelPathId:[t.guid,t.key,u].join("_"),interactionState:t.interactionState,figure:t}}function w(t){t.attr("transform",(function(t){return"translate("+t.node.x0.toFixed(3)+", "+t.node.y0.toFixed(3)+")"}))}function T(t){t.call(w)}function k(t,e){t.call(T),e.attr("d",b())}function A(t){t.attr("width",(function(t){return t.node.x1-t.node.x0})).attr("height",(function(t){return t.visibleHeight}))}function M(t){return t.link.width>1||t.linkLineWidth>0}function S(t){return"translate("+t.translateX+","+t.translateY+")"+(t.horizontal?"matrix(1 0 0 1 0 0)":"matrix(0 1 1 0 0 0)")}function E(t){return"translate("+(t.horizontal?0:t.labelY)+" "+(t.horizontal?t.labelY:0)+")"}function C(t){return a.svg.line()([[t.horizontal?t.left?-t.sizeAcross:t.visibleWidth+n.nodeTextOffsetHorizontal:n.nodeTextOffsetHorizontal,0],[t.horizontal?t.left?-n.nodeTextOffsetHorizontal:t.sizeAcross:t.visibleHeight-n.nodeTextOffsetHorizontal,0]])}function L(t){return t.horizontal?"matrix(1 0 0 1 0 0)":"matrix(0 1 1 0 0 0)"}function P(t){return t.horizontal?"scale(1 1)":"scale(-1 1)"}function I(t){return t.darkBackground&&!t.horizontal?"rgb(255,255,255)":"rgb(0,0,0)"}function z(t){return t.horizontal&&t.left?"100%":"0%"}function O(t,e,r){t.on(".basic",null).on("mouseover.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.hover(this,t,e),t.interactionState.hovered=[this,t])})).on("mousemove.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.follow(this,t),t.interactionState.hovered=[this,t])})).on("mouseout.basic",(function(t){t.interactionState.dragInProgress||t.partOfGroup||(r.unhover(this,t,e),t.interactionState.hovered=!1)})).on("click.basic",(function(t){t.interactionState.hovered&&(r.unhover(this,t,e),t.interactionState.hovered=!1),t.interactionState.dragInProgress||t.partOfGroup||r.select(this,t,e)}))}function D(t,e,r,i){var o=a.behavior.drag().origin((function(t){return{x:t.node.x0+t.visibleWidth/2,y:t.node.y0+t.visibleHeight/2}})).on("dragstart",(function(a){if("fixed"!==a.arrangement&&(h.ensureSingle(i._fullLayout._infolayer,"g","dragcover",(function(t){i._fullLayout._dragCover=t})),h.raiseToTop(this),a.interactionState.dragInProgress=a.node,F(a.node),a.interactionState.hovered&&(r.nodeEvents.unhover.apply(0,a.interactionState.hovered),a.interactionState.hovered=!1),"snap"===a.arrangement)){var o=a.traceId+"|"+a.key;a.forceLayouts[o]?a.forceLayouts[o].alpha(1):function(t,e,r,a){!function(t){for(var e=0;e<t.length;e++)t[e].y=(t[e].y0+t[e].y1)/2,t[e].x=(t[e].x0+t[e].x1)/2}(r.graph.nodes);var i=r.graph.nodes.filter((function(t){return t.originalX===r.node.originalX})).filter((function(t){return!t.partOfGroup}));r.forceLayouts[e]=u.forceSimulation(i).alphaDecay(0).force("collide",u.forceCollide().radius((function(t){return t.dy/2+r.nodePad/2})).strength(1).iterations(n.forceIterations)).force("constrain",function(t,e,r,a){return function(){for(var t=0,i=0;i<r.length;i++){var o=r[i];o===a.interactionState.dragInProgress?(o.x=o.lastDraggedX,o.y=o.lastDraggedY):(o.vx=(o.originalX-o.x)/n.forceTicksPerFrame,o.y=Math.min(a.size-o.dy/2,Math.max(o.dy/2,o.y))),t=Math.max(t,Math.abs(o.vx),Math.abs(o.vy))}!a.interactionState.dragInProgress&&t<.1&&a.forceLayouts[e].alpha()>0&&a.forceLayouts[e].alpha(0)}}(0,e,i,r)).stop()}(0,o,a),function(t,e,r,a,i){window.requestAnimationFrame((function o(){var s;for(s=0;s<n.forceTicksPerFrame;s++)r.forceLayouts[a].tick();if(function(t){for(var e=0;e<t.length;e++)t[e].y0=t[e].y-t[e].dy/2,t[e].y1=t[e].y0+t[e].dy,t[e].x0=t[e].x-t[e].dx/2,t[e].x1=t[e].x0+t[e].dx}(r.graph.nodes),r.sankey.update(r.graph),k(t.filter(B(r)),e),r.forceLayouts[a].alpha()>0)window.requestAnimationFrame(o);else{var l=r.node.originalX;r.node.x0=l-r.visibleWidth/2,r.node.x1=l+r.visibleWidth/2,R(r,i)}}))}(t,e,a,o,i)}})).on("drag",(function(r){if("fixed"!==r.arrangement){var n=a.event.x,i=a.event.y;"snap"===r.arrangement?(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2,r.node.y0=i-r.visibleHeight/2,r.node.y1=i+r.visibleHeight/2):("freeform"===r.arrangement&&(r.node.x0=n-r.visibleWidth/2,r.node.x1=n+r.visibleWidth/2),i=Math.max(0,Math.min(r.size-r.visibleHeight/2,i)),r.node.y0=i-r.visibleHeight/2,r.node.y1=i+r.visibleHeight/2),F(r.node),"snap"!==r.arrangement&&(r.sankey.update(r.graph),k(t.filter(B(r)),e))}})).on("dragend",(function(t){if("fixed"!==t.arrangement){t.interactionState.dragInProgress=!1;for(var e=0;e<t.node.childrenNodes.length;e++)t.node.childrenNodes[e].x=t.node.x,t.node.childrenNodes[e].y=t.node.y;"snap"!==t.arrangement&&R(t,i)}}));t.on(".drag",null).call(o)}function R(t,e){for(var r=[],n=[],a=0;a<t.graph.nodes.length;a++){var i=(t.graph.nodes[a].x0+t.graph.nodes[a].x1)/2,o=(t.graph.nodes[a].y0+t.graph.nodes[a].y1)/2;r.push(i/t.figure.width),n.push(o/t.figure.height)}v.call("_guiRestyle",e,{"node.x":[r],"node.y":[n]},t.trace.index).then((function(){e._fullLayout._dragCover&&e._fullLayout._dragCover.remove()}))}function F(t){t.lastDraggedX=t.x0+t.dx/2,t.lastDraggedY=t.y0+t.dy/2}function B(t){return function(e){return e.node.originalX===t.node.originalX}}e.exports=function(t,e,r,l,c){var u=!1;h.ensureSingle(t._fullLayout._infolayer,"g","first-render",(function(){u=!0}));var f=t._fullLayout._dragCover,m=r.filter((function(t){return g(t).trace.visible})).map(y.bind(null,l)),v=e.selectAll("."+n.cn.sankey).data(m,p);v.exit().remove(),v.enter().append("g").classed(n.cn.sankey,!0).style("box-sizing","content-box").style("position","absolute").style("left",0).style("shape-rendering","geometricPrecision").style("pointer-events","auto").attr("transform",S),v.each((function(e,r){t._fullData[r]._sankey=e;var n="bgsankey-"+e.trace.uid+"-"+r;h.ensureSingle(t._fullLayout._draggers,"rect",n),t._fullData[r]._bgRect=a.select("."+n),t._fullData[r]._bgRect.style("pointer-events","all").attr("width",e.width).attr("height",e.height).attr("x",e.translateX).attr("y",e.translateY).classed("bgsankey",!0).style({fill:"transparent","stroke-width":0})})),v.transition().ease(n.ease).duration(n.duration).attr("transform",S);var T=v.selectAll("."+n.cn.sankeyLinks).data(d,p);T.enter().append("g").classed(n.cn.sankeyLinks,!0).style("fill","none");var k=T.selectAll("."+n.cn.sankeyLink).data((function(t){return t.graph.links.filter((function(t){return t.value})).map(x.bind(null,t))}),p);k.enter().append("path").classed(n.cn.sankeyLink,!0).call(O,v,c.linkEvents),k.style("stroke",(function(t){return M(t)?o.tinyRGB(i(t.linkLineColor)):t.tinyColorHue})).style("stroke-opacity",(function(t){return M(t)?o.opacity(t.linkLineColor):t.tinyColorAlpha})).style("fill",(function(t){return t.tinyColorHue})).style("fill-opacity",(function(t){return t.tinyColorAlpha})).style("stroke-width",(function(t){return M(t)?t.linkLineWidth:1})).attr("d",b()),k.style("opacity",(function(){return t._context.staticPlot||u||f?1:0})).transition().ease(n.ease).duration(n.duration).style("opacity",1),k.exit().transition().ease(n.ease).duration(n.duration).style("opacity",0).remove();var R=v.selectAll("."+n.cn.sankeyNodeSet).data(d,p);R.enter().append("g").classed(n.cn.sankeyNodeSet,!0),R.style("cursor",(function(t){switch(t.arrangement){case"fixed":return"default";case"perpendicular":return"ns-resize";default:return"move"}}));var F=R.selectAll("."+n.cn.sankeyNode).data((function(t){var e=t.graph.nodes;return function(t){var e,r=[];for(e=0;e<t.length;e++)t[e].originalX=(t[e].x0+t[e].x1)/2,t[e].originalY=(t[e].y0+t[e].y1)/2,-1===r.indexOf(t[e].originalX)&&r.push(t[e].originalX);for(r.sort((function(t,e){return t-e})),e=0;e<t.length;e++)t[e].originalLayerIndex=r.indexOf(t[e].originalX),t[e].originalLayer=t[e].originalLayerIndex/(r.length-1)}(e),e.map(_.bind(null,t))}),p);F.enter().append("g").classed(n.cn.sankeyNode,!0).call(w).style("opacity",(function(e){return!t._context.staticPlot&&!u||e.partOfGroup?0:1})),F.call(O,v,c.nodeEvents).call(D,k,c,t),F.transition().ease(n.ease).duration(n.duration).call(w).style("opacity",(function(t){return t.partOfGroup?0:1})),F.exit().transition().ease(n.ease).duration(n.duration).style("opacity",0).remove();var B=F.selectAll("."+n.cn.nodeRect).data(d);B.enter().append("rect").classed(n.cn.nodeRect,!0).call(A),B.style("stroke-width",(function(t){return t.nodeLineWidth})).style("stroke",(function(t){return o.tinyRGB(i(t.nodeLineColor))})).style("stroke-opacity",(function(t){return o.opacity(t.nodeLineColor)})).style("fill",(function(t){return t.tinyColorHue})).style("fill-opacity",(function(t){return t.tinyColorAlpha})),B.transition().ease(n.ease).duration(n.duration).call(A);var N=F.selectAll("."+n.cn.nodeCapture).data(d);N.enter().append("rect").classed(n.cn.nodeCapture,!0).style("fill-opacity",0),N.attr("x",(function(t){return t.zoneX})).attr("y",(function(t){return t.zoneY})).attr("width",(function(t){return t.zoneWidth})).attr("height",(function(t){return t.zoneHeight}));var j=F.selectAll("."+n.cn.nodeCentered).data(d);j.enter().append("g").classed(n.cn.nodeCentered,!0).attr("transform",E),j.transition().ease(n.ease).duration(n.duration).attr("transform",E);var V=j.selectAll("."+n.cn.nodeLabelGuide).data(d);V.enter().append("path").classed(n.cn.nodeLabelGuide,!0).attr("id",(function(t){return t.uniqueNodeLabelPathId})).attr("d",C).attr("transform",L),V.transition().ease(n.ease).duration(n.duration).attr("d",C).attr("transform",L);var 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o,s=i("x"),l=i("y");if(a.getComponentMethod("calendars","handleTraceDefaults")(t,e,["x","y"],r),s){var c=n.minRowLength(s);l?o=Math.min(c,n.minRowLength(l)):(o=c,i("y0"),i("dy"))}else{if(!l)return 0;o=n.minRowLength(l),i("x0"),i("dx")}return e._length=o,o}},{"../../lib":728,"../../registry":859}],1161:[function(t,e,r){"use strict";var n=t("../scatter/attributes"),a=t("../../components/colorscale/attributes"),i=t("../../plots/template_attributes").hovertemplateAttrs,o=t("../../plots/template_attributes").texttemplateAttrs,s=t("../../plots/attributes"),l=t("../../constants/gl3d_dashes"),c=t("../../constants/gl3d_markers"),u=t("../../lib/extend").extendFlat,h=t("../../plot_api/edit_types").overrideAll,f=n.line,p=n.marker,d=p.line,g=u({width:f.width,dash:{valType:"enumerated",values:Object.keys(l),dflt:"solid"}},a("line"));var m=e.exports=h({x:n.x,y:n.y,z:{valType:"data_array"},text:u({},n.text,{}),texttemplate:o({},{}),hovertext:u({},n.hovertext,{}),hovertemplate:i(),mode:u({},n.mode,{dflt:"lines+markers"}),surfaceaxis:{valType:"enumerated",values:[-1,0,1,2],dflt:-1},surfacecolor:{valType:"color"},projection:{x:{show:{valType:"boolean",dflt:!1},opacity:{valType:"number",min:0,max:1,dflt:1},scale:{valType:"number",min:0,max:10,dflt:2/3}},y:{show:{valType:"boolean",dflt:!1},opacity:{valType:"number",min:0,max:1,dflt:1},scale:{valType:"number",min:0,max:10,dflt:2/3}},z:{show:{valType:"boolean",dflt:!1},opacity:{valType:"number",min:0,max:1,dflt:1},scale:{valType:"number",min:0,max:10,dflt:2/3}}},connectgaps:n.connectgaps,line:g,marker:u({symbol:{valType:"enumerated",values:Object.keys(c),dflt:"circle",arrayOk:!0},size:u({},p.size,{dflt:8}),sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode,opacity:u({},p.opacity,{arrayOk:!1}),colorbar:p.colorbar,line:u({width:u({},d.width,{arrayOk:!1})},a("marker.line"))},a("marker")),textposition:u({},n.textposition,{dflt:"top 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l=i(+t[s],s);if("log"===a.type){var c=a.c2l(t[s]),u=t[s]-l[0],h=t[s]+l[1];if(o[s]=[(a.c2l(u,!0)-c)*r,(a.c2l(h,!0)-c)*r],u>0){var f=a.c2l(u);a._lowerLogErrorBound||(a._lowerLogErrorBound=f),a._lowerErrorBound=Math.min(a._lowerLogErrorBound,f)}}else o[s]=[-l[0]*r,l[1]*r]}return o}e.exports=function(t,e,r){var n=[a(t.x,t.error_x,e[0],r.xaxis),a(t.y,t.error_y,e[1],r.yaxis),a(t.z,t.error_z,e[2],r.zaxis)],i=function(t){for(var e=0;e<t.length;e++)if(t[e])return t[e].length;return 0}(n);if(0===i)return null;for(var o=new Array(i),s=0;s<i;s++){for(var l=[[0,0,0],[0,0,0]],c=0;c<3;c++)if(n[c])for(var u=0;u<2;u++)l[u][c]=n[c][s][u];o[s]=l}return o}},{"../../registry":859}],1164:[function(t,e,r){"use strict";var n=t("gl-line3d"),a=t("gl-scatter3d"),i=t("gl-error3d"),o=t("gl-mesh3d"),s=t("delaunay-triangulate"),l=t("../../lib"),c=t("../../lib/str2rgbarray"),u=t("../../lib/gl_format_color").formatColor,h=t("../scatter/make_bubble_size_func"),f=t("../../constants/gl3d_dashes"),p=t("../../constants/gl3d_markers"),d=t("../../plots/cartesian/axes"),g=t("../../components/fx/helpers").appendArrayPointValue,m=t("./calc_errors");function v(t,e){this.scene=t,this.uid=e,this.linePlot=null,this.scatterPlot=null,this.errorBars=null,this.textMarkers=null,this.delaunayMesh=null,this.color=null,this.mode="",this.dataPoints=[],this.axesBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.textLabels=null,this.data=null}var y=v.prototype;function x(t){return null==t?0:t.indexOf("left")>-1?-1:t.indexOf("right")>-1?1:0}function b(t){return null==t?0:t.indexOf("top")>-1?-1:t.indexOf("bottom")>-1?1:0}function _(t,e){return e(4*t)}function w(t){return p[t]}function T(t,e,r,n,a){var i=null;if(l.isArrayOrTypedArray(t)){i=[];for(var o=0;o<e;o++)void 0===t[o]?i[o]=n:i[o]=r(t[o],a)}else i=r(t,l.identity);return i}function k(t,e){var r,n,a,i,o,s,f=[],p=t.fullSceneLayout,v=t.dataScale,y=p.xaxis,k=p.yaxis,A=p.zaxis,M=e.marker,S=e.line,E=e.x||[],C=e.y||[],L=e.z||[],P=E.length,I=e.xcalendar,z=e.ycalendar,O=e.zcalendar;for(o=0;o<P;o++)r=y.d2l(E[o],0,I)*v[0],n=k.d2l(C[o],0,z)*v[1],a=A.d2l(L[o],0,O)*v[2],f[o]=[r,n,a];if(Array.isArray(e.text))s=e.text;else if(void 0!==e.text)for(s=new Array(P),o=0;o<P;o++)s[o]=e.text;function D(t,e){var r=p[t];return d.tickText(r,r.d2l(e),!0).text}var R=e.texttemplate;if(R){var F=t.fullLayout._d3locale,B=Array.isArray(R),N=B?Math.min(R.length,P):P,j=B?function(t){return R[t]}:function(){return R};for(s=new Array(N),o=0;o<N;o++){var V={x:E[o],y:C[o],z:L[o]},U={xLabel:D("xaxis",E[o]),yLabel:D("yaxis",C[o]),zLabel:D("zaxis",L[o])},q={};g(q,e,o);var H=e._meta||{};s[o]=l.texttemplateString(j(o),U,F,q,V,H)}}if(i={position:f,mode:e.mode,text:s},"line"in e&&(i.lineColor=u(S,1,P),i.lineWidth=S.width,i.lineDashes=S.dash),"marker"in e){var G=h(e);i.scatterColor=u(M,1,P),i.scatterSize=T(M.size,P,_,20,G),i.scatterMarker=T(M.symbol,P,w,"\u25cf"),i.scatterLineWidth=M.line.width,i.scatterLineColor=u(M.line,1,P),i.scatterAngle=0}"textposition"in e&&(i.textOffset=function(t){var e=[0,0];if(Array.isArray(t))for(var r=0;r<t.length;r++)e[r]=[0,0],t[r]&&(e[r][0]=x(t[r]),e[r][1]=b(t[r]));else e[0]=x(t),e[1]=b(t);return e}(e.textposition),i.textColor=u(e.textfont,1,P),i.textSize=T(e.textfont.size,P,l.identity,12),i.textFont=e.textfont.family,i.textAngle=0);var Y=["x","y","z"];for(i.project=[!1,!1,!1],i.projectScale=[1,1,1],i.projectOpacity=[1,1,1],o=0;o<3;++o){var W=e.projection[Y[o]];(i.project[o]=W.show)&&(i.projectOpacity[o]=W.opacity,i.projectScale[o]=W.scale)}i.errorBounds=m(e,v,p);var Z=function(t){for(var e=[0,0,0],r=[[0,0,0],[0,0,0],[0,0,0]],n=[1,1,1],a=0;a<3;a++){var i=t[a];i&&!1!==i.copy_zstyle&&!1!==t[2].visible&&(i=t[2]),i&&i.visible&&(e[a]=i.width/2,r[a]=c(i.color),n[a]=i.thickness)}return{capSize:e,color:r,lineWidth:n}}([e.error_x,e.error_y,e.error_z]);return i.errorColor=Z.color,i.errorLineWidth=Z.lineWidth,i.errorCapSize=Z.capSize,i.delaunayAxis=e.surfaceaxis,i.delaunayColor=c(e.surfacecolor),i}function A(t){if(Array.isArray(t)){var e=t[0];return Array.isArray(e)&&(t=e),"rgb("+t.slice(0,3).map((function(t){return Math.round(255*t)}))+")"}return null}y.handlePick=function(t){if(t.object&&(t.object===this.linePlot||t.object===this.delaunayMesh||t.object===this.textMarkers||t.object===this.scatterPlot)){var e=t.index=t.data.index;return t.object.highlight&&t.object.highlight(null),this.scatterPlot&&(t.object=this.scatterPlot,this.scatterPlot.highlight(t.data)),t.textLabel="",this.textLabels&&(Array.isArray(this.textLabels)?(this.textLabels[e]||0===this.textLabels[e])&&(t.textLabel=this.textLabels[e]):t.textLabel=this.textLabels),t.traceCoordinate=[this.data.x[e],this.data.y[e],this.data.z[e]],!0}},y.update=function(t){var e,r,l,c,u=this.scene.glplot.gl,h=f.solid;this.data=t;var p=k(this.scene,t);"mode"in p&&(this.mode=p.mode),"lineDashes"in p&&p.lineDashes in f&&(h=f[p.lineDashes]),this.color=A(p.scatterColor)||A(p.lineColor),this.dataPoints=p.position,e={gl:this.scene.glplot.gl,position:p.position,color:p.lineColor,lineWidth:p.lineWidth||1,dashes:h[0],dashScale:h[1],opacity:t.opacity,connectGaps:t.connectgaps},-1!==this.mode.indexOf("lines")?this.linePlot?this.linePlot.update(e):(this.linePlot=n(e),this.linePlot._trace=this,this.scene.glplot.add(this.linePlot)):this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose(),this.linePlot=null);var d=t.opacity;if(t.marker&&t.marker.opacity&&(d*=t.marker.opacity),r={gl:this.scene.glplot.gl,position:p.position,color:p.scatterColor,size:p.scatterSize,glyph:p.scatterMarker,opacity:d,orthographic:!0,lineWidth:p.scatterLineWidth,lineColor:p.scatterLineColor,project:p.project,projectScale:p.projectScale,projectOpacity:p.projectOpacity},-1!==this.mode.indexOf("markers")?this.scatterPlot?this.scatterPlot.update(r):(this.scatterPlot=a(r),this.scatterPlot._trace=this,this.scatterPlot.highlightScale=1,this.scene.glplot.add(this.scatterPlot)):this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose(),this.scatterPlot=null),c={gl:this.scene.glplot.gl,position:p.position,glyph:p.text,color:p.textColor,size:p.textSize,angle:p.textAngle,alignment:p.textOffset,font:p.textFont,orthographic:!0,lineWidth:0,project:!1,opacity:t.opacity},this.textLabels=t.hovertext||t.text,-1!==this.mode.indexOf("text")?this.textMarkers?this.textMarkers.update(c):(this.textMarkers=a(c),this.textMarkers._trace=this,this.textMarkers.highlightScale=1,this.scene.glplot.add(this.textMarkers)):this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose(),this.textMarkers=null),l={gl:this.scene.glplot.gl,position:p.position,color:p.errorColor,error:p.errorBounds,lineWidth:p.errorLineWidth,capSize:p.errorCapSize,opacity:t.opacity},this.errorBars?p.errorBounds?this.errorBars.update(l):(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose(),this.errorBars=null):p.errorBounds&&(this.errorBars=i(l),this.errorBars._trace=this,this.scene.glplot.add(this.errorBars)),p.delaunayAxis>=0){var g=function(t,e,r){var n,a=(r+1)%3,i=(r+2)%3,o=[],l=[];for(n=0;n<t.length;++n){var c=t[n];!isNaN(c[a])&&isFinite(c[a])&&!isNaN(c[i])&&isFinite(c[i])&&(o.push([c[a],c[i]]),l.push(n))}var u=s(o);for(n=0;n<u.length;++n)for(var h=u[n],f=0;f<h.length;++f)h[f]=l[h[f]];return{positions:t,cells:u,meshColor:e}}(p.position,p.delaunayColor,p.delaunayAxis);g.opacity=t.opacity,this.delaunayMesh?this.delaunayMesh.update(g):(g.gl=u,this.delaunayMesh=o(g),this.delaunayMesh._trace=this,this.scene.glplot.add(this.delaunayMesh))}else this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose(),this.delaunayMesh=null)},y.dispose=function(){this.linePlot&&(this.scene.glplot.remove(this.linePlot),this.linePlot.dispose()),this.scatterPlot&&(this.scene.glplot.remove(this.scatterPlot),this.scatterPlot.dispose()),this.errorBars&&(this.scene.glplot.remove(this.errorBars),this.errorBars.dispose()),this.textMarkers&&(this.scene.glplot.remove(this.textMarkers),this.textMarkers.dispose()),this.delaunayMesh&&(this.scene.glplot.remove(this.delaunayMesh),this.delaunayMesh.dispose())},e.exports=function(t,e){var r=new v(t,e.uid);return r.update(e),r}},{"../../components/fx/helpers":631,"../../constants/gl3d_dashes":701,"../../constants/gl3d_markers":702,"../../lib":728,"../../lib/gl_format_color":725,"../../lib/str2rgbarray":751,"../../plots/cartesian/axes":776,"../scatter/make_bubble_size_func":1151,"./calc_errors":1163,"delaunay-triangulate":166,"gl-error3d":259,"gl-line3d":266,"gl-mesh3d":287,"gl-scatter3d":303}],1165:[function(t,e,r){"use strict";var n=t("../../registry"),a=t("../../lib"),i=t("../scatter/subtypes"),o=t("../scatter/marker_defaults"),s=t("../scatter/line_defaults"),l=t("../scatter/text_defaults"),c=t("./attributes");e.exports=function(t,e,r,u){function h(r,n){return a.coerce(t,e,c,r,n)}if(function(t,e,r,a){var i=0,o=r("x"),s=r("y"),l=r("z");n.getComponentMethod("calendars","handleTraceDefaults")(t,e,["x","y","z"],a),o&&s&&l&&(i=Math.min(o.length,s.length,l.length),e._length=e._xlength=e._ylength=e._zlength=i);return i}(t,e,h,u)){h("text"),h("hovertext"),h("hovertemplate"),h("mode"),i.hasLines(e)&&(h("connectgaps"),s(t,e,r,u,h)),i.hasMarkers(e)&&o(t,e,r,u,h,{noSelect:!0}),i.hasText(e)&&(h("texttemplate"),l(t,e,u,h,{noSelect:!0}));var f=(e.line||{}).color,p=(e.marker||{}).color;h("surfaceaxis")>=0&&h("surfacecolor",f||p);for(var d=["x","y","z"],g=0;g<3;++g){var m="projection."+d[g];h(m+".show")&&(h(m+".opacity"),h(m+".scale"))}var v=n.getComponentMethod("errorbars","supplyDefaults");v(t,e,f||p||r,{axis:"z"}),v(t,e,f||p||r,{axis:"y",inherit:"z"}),v(t,e,f||p||r,{axis:"x",inherit:"z"})}else e.visible=!1}},{"../../lib":728,"../../registry":859,"../scatter/line_defaults":1147,"../scatter/marker_defaults":1153,"../scatter/subtypes":1158,"../scatter/text_defaults":1159,"./attributes":1161}],1166:[function(t,e,r){"use strict";e.exports={plot:t("./convert"),attributes:t("./attributes"),markerSymbols:t("../../constants/gl3d_markers"),supplyDefaults:t("./defaults"),colorbar:[{container:"marker",min:"cmin",max:"cmax"},{container:"line",min:"cmin",max:"cmax"}],calc:t("./calc"),moduleType:"trace",name:"scatter3d",basePlotModule:t("../../plots/gl3d"),categories:["gl3d","symbols","showLegend","scatter-like"],meta:{}}},{"../../constants/gl3d_markers":702,"../../plots/gl3d":818,"./attributes":1161,"./calc":1162,"./convert":1164,"./defaults":1165}],1167:[function(t,e,r){"use strict";var n=t("../scatter/attributes"),a=t("../../plots/attributes"),i=t("../../plots/template_attributes").hovertemplateAttrs,o=t("../../plots/template_attributes").texttemplateAttrs,s=t("../../components/colorscale/attributes"),l=t("../../lib/extend").extendFlat,c=n.marker,u=n.line,h=c.line;e.exports={carpet:{valType:"string",editType:"calc"},a:{valType:"data_array",editType:"calc"},b:{valType:"data_array",editType:"calc"},mode:l({},n.mode,{dflt:"markers"}),text:l({},n.text,{}),texttemplate:o({editType:"plot"},{keys:["a","b","text"]}),hovertext:l({},n.hovertext,{}),line:{color:u.color,width:u.width,dash:u.dash,shape:l({},u.shape,{values:["linear","spline"]}),smoothing:u.smoothing,editType:"calc"},connectgaps:n.connectgaps,fill:l({},n.fill,{values:["none","toself","tonext"],dflt:"none"}),fillcolor:n.fillcolor,marker:l({symbol:c.symbol,opacity:c.opacity,maxdisplayed:c.maxdisplayed,size:c.size,sizeref:c.sizeref,sizemin:c.sizemin,sizemode:c.sizemode,line:l({width:h.width,editType:"calc"},s("marker.line")),gradient:c.gradient,editType:"calc"},s("marker")),textfont:n.textfont,textposition:n.textposition,selected:n.selected,unselected:n.unselected,hoverinfo:l({},a.hoverinfo,{flags:["a","b","text","name"]}),hoveron:n.hoveron,hovertemplate:i()}},{"../../components/colorscale/attributes":602,"../../lib/extend":719,"../../plots/attributes":773,"../../plots/template_attributes":854,"../scatter/attributes":1134}],1168:[function(t,e,r){"use 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n=t("../../lib"),a=t("../scatter/constants"),i=t("../scatter/subtypes"),o=t("../scatter/marker_defaults"),s=t("../scatter/line_defaults"),l=t("../scatter/line_shape_defaults"),c=t("../scatter/text_defaults"),u=t("../scatter/fillcolor_defaults"),h=t("./attributes");e.exports=function(t,e,r,f){function p(r,a){return n.coerce(t,e,h,r,a)}p("carpet"),e.xaxis="x",e.yaxis="y";var d=p("a"),g=p("b"),m=Math.min(d.length,g.length);if(m){e._length=m,p("text"),p("texttemplate"),p("hovertext"),p("mode",m<a.PTS_LINESONLY?"lines+markers":"lines"),i.hasLines(e)&&(s(t,e,r,f,p),l(t,e,p),p("connectgaps")),i.hasMarkers(e)&&o(t,e,r,f,p,{gradient:!0}),i.hasText(e)&&c(t,e,f,p);var v=[];(i.hasMarkers(e)||i.hasText(e))&&(p("marker.maxdisplayed"),v.push("points")),p("fill"),"none"!==e.fill&&(u(t,e,r,p),i.hasLines(e)||l(t,e,p)),"tonext"!==e.fill&&"toself"!==e.fill||v.push("fills"),"fills"!==p("hoveron",v.join("+")||"points")&&p("hovertemplate"),n.coerceSelectionMarkerOpacity(e,p)}else 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n=t("../../lib"),a=t("../scatter/subtypes"),i=t("../scatter/marker_defaults"),o=t("../scatter/line_defaults"),s=t("../scatter/text_defaults"),l=t("../scatter/fillcolor_defaults"),c=t("./attributes");e.exports=function(t,e,r,u){function h(r,a){return n.coerce(t,e,c,r,a)}var f,p=h("locations");if(p&&p.length){var d,g=h("geojson");("string"==typeof g&&""!==g||n.isPlainObject(g))&&(d="geojson-id"),"geojson-id"===h("locationmode",d)&&h("featureidkey"),f=p.length}else{var m=h("lon")||[],v=h("lat")||[];f=Math.min(m.length,v.length)}f?(e._length=f,h("text"),h("hovertext"),h("hovertemplate"),h("mode"),a.hasLines(e)&&(o(t,e,r,u,h),h("connectgaps")),a.hasMarkers(e)&&i(t,e,r,u,h,{gradient:!0}),a.hasText(e)&&(h("texttemplate"),s(t,e,u,h)),h("fill"),"none"!==e.fill&&l(t,e,r,h),n.coerceSelectionMarkerOpacity(e,h)):e.visible=!1}},{"../../lib":728,"../scatter/fillcolor_defaults":1142,"../scatter/line_defaults":1147,"../scatter/marker_defaults":1153,"../scatter/subtypes":1158,"../scatter/text_defaults":1159,"./attributes":1175}],1178:[function(t,e,r){"use strict";e.exports=function(t,e,r,n,a){t.lon=e.lon,t.lat=e.lat,t.location=e.loc?e.loc:null;var i=n[a];return i.fIn&&i.fIn.properties&&(t.properties=i.fIn.properties),t}},{}],1179:[function(t,e,r){"use strict";var n=t("../../plots/cartesian/axes");e.exports=function(t,e,r){var a={},i=r[e.geo]._subplot.mockAxis,o=t.lonlat;return 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n=t("../../plots/attributes"),a=t("../scatter/attributes"),i=t("../../components/colorscale/attributes"),o=t("../../lib/extend").extendFlat,s=t("../../plot_api/edit_types").overrideAll,l=t("./constants").DASHES,c=a.line,u=a.marker,h=u.line,f=e.exports=s({x:a.x,x0:a.x0,dx:a.dx,y:a.y,y0:a.y0,dy:a.dy,text:a.text,hovertext:a.hovertext,textposition:a.textposition,textfont:a.textfont,mode:{valType:"flaglist",flags:["lines","markers","text"],extras:["none"]},line:{color:c.color,width:c.width,shape:{valType:"enumerated",values:["linear","hv","vh","hvh","vhv"],dflt:"linear",editType:"plot"},dash:{valType:"enumerated",values:Object.keys(l),dflt:"solid"}},marker:o({},i("marker"),{symbol:u.symbol,size:u.size,sizeref:u.sizeref,sizemin:u.sizemin,sizemode:u.sizemode,opacity:u.opacity,colorbar:u.colorbar,line:o({},i("marker.line"),{width:h.width})}),connectgaps:a.connectgaps,fill:o({},a.fill,{dflt:"none"}),fillcolor:a.fillcolor,selected:{marker:a.selected.marker,textfont:a.selected.textfont},unselected:{marker:a.unselected.marker,textfont:a.unselected.textfont},opacity:n.opacity},"calc","nested");f.x.editType=f.y.editType=f.x0.editType=f.y0.editType="calc+clearAxisTypes",f.hovertemplate=a.hovertemplate,f.texttemplate=a.texttemplate},{"../../components/colorscale/attributes":602,"../../lib/extend":719,"../../plot_api/edit_types":759,"../../plots/attributes":773,"../scatter/attributes":1134,"./constants":1187}],1186:[function(t,e,r){"use 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T=y-_,k=y+w;p[v+u[0]]=x-a.c2l(T),p[v+u[1]]=a.c2l(k)-x,p[v+u[2]]=0,p[v+u[3]]=0,d=Math.min(d,y-_),g=Math.max(g,y+w)}}}f[i]={positions:r,errors:p,_bnds:[d,g]}}}return p(a,l),p(i,u),f},textPosition:function(t,e,r,n){var a,i=e._length,o={};if(h.hasMarkers(e)){var s=r.font,l=r.align,c=r.baseline;for(o.offset=new Array(i),a=0;a<i;a++){var u=n.sizes?n.sizes[a]:n.size,f=Array.isArray(s)?s[a].size:s.size,p=Array.isArray(l)?l.length>1?l[a]:l[0]:l,d=Array.isArray(c)?c.length>1?c[a]:c[0]:c,g=m[p],v=m[d],y=u?u/.8+1:0,x=-v*y-.5*v;o.offset[a]=[g*y/f,x/f]}}return o}}},{"../../components/drawing":617,"../../components/fx/helpers":631,"../../constants/interactions":703,"../../lib":728,"../../lib/gl_format_color":725,"../../plots/cartesian/axis_ids":779,"../../registry":859,"../scatter/make_bubble_size_func":1151,"../scatter/subtypes":1158,"./constants":1187,"./helpers":1192,"color-normalize":122,"fast-isnumeric":236,"svg-path-sdf":526}],1189:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../registry"),i=t("./helpers"),o=t("./attributes"),s=t("../scatter/constants"),l=t("../scatter/subtypes"),c=t("../scatter/xy_defaults"),u=t("../scatter/marker_defaults"),h=t("../scatter/line_defaults"),f=t("../scatter/fillcolor_defaults"),p=t("../scatter/text_defaults");e.exports=function(t,e,r,d){function g(r,a){return n.coerce(t,e,o,r,a)}var m=!!t.marker&&i.isOpenSymbol(t.marker.symbol),v=l.isBubble(t),y=c(t,e,d,g);if(y){var x=y<s.PTS_LINESONLY?"lines+markers":"lines";g("text"),g("hovertext"),g("hovertemplate"),g("mode",x),l.hasLines(e)&&(g("connectgaps"),h(t,e,r,d,g),g("line.shape")),l.hasMarkers(e)&&(u(t,e,r,d,g),g("marker.line.width",m||v?1:0)),l.hasText(e)&&(g("texttemplate"),p(t,e,d,g));var b=(e.line||{}).color,_=(e.marker||{}).color;g("fill"),"none"!==e.fill&&f(t,e,r,g);var w=a.getComponentMethod("errorbars","supplyDefaults");w(t,e,b||_||r,{axis:"y"}),w(t,e,b||_||r,{axis:"x",inherit:"y"}),n.coerceSelectionMarkerOpacity(e,g)}else 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v=s.c2p(f.x,!0),y=l.c2p(f.y,!0),x=f.mrc||1,b=o.hoverlabel;b&&(f.hbg=Array.isArray(b.bgcolor)?b.bgcolor[h]:b.bgcolor,f.hbc=Array.isArray(b.bordercolor)?b.bordercolor[h]:b.bordercolor,f.hts=a.isArrayOrTypedArray(b.font.size)?b.font.size[h]:b.font.size,f.htc=Array.isArray(b.font.color)?b.font.color[h]:b.font.color,f.htf=Array.isArray(b.font.family)?b.font.family[h]:b.font.family,f.hnl=a.isArrayOrTypedArray(b.namelength)?b.namelength[h]:b.namelength);var _=o.hoverinfo;_&&(f.hi=Array.isArray(_)?_[h]:_);var w=o.hovertemplate;w&&(f.ht=Array.isArray(w)?w[h]:w);var T={};T[t.index]=f;var k=a.extendFlat({},t,{color:i(o,f),x0:v-x,x1:v+x,xLabelVal:f.x,y0:y-x,y1:y+x,yLabelVal:f.y,cd:T,distance:c,spikeDistance:u,hovertemplate:f.ht});return f.htx?k.text=f.htx:f.tx?k.text=f.tx:o.text&&(k.text=o.text),a.fillText(f,o,k),n.getComponentMethod("errorbars","hoverInfo")(f,o,k),k}e.exports={hoverPoints:function(t,e,r,n){var a,i,s,l,c,u,h,f,p,d=t.cd,g=d[0].t,m=d[0].trace,v=t.xa,y=t.ya,x=g.x,b=g.y,_=v.c2p(e),w=y.c2p(r),T=t.distance;if(g.tree){var k=v.p2c(_-T),A=v.p2c(_+T),M=y.p2c(w-T),S=y.p2c(w+T);a="x"===n?g.tree.range(Math.min(k,A),Math.min(y._rl[0],y._rl[1]),Math.max(k,A),Math.max(y._rl[0],y._rl[1])):g.tree.range(Math.min(k,A),Math.min(M,S),Math.max(k,A),Math.max(M,S))}else a=g.ids;var E=T;if("x"===n)for(c=0;c<a.length;c++)s=x[a[c]],(u=Math.abs(v.c2p(s)-_))<E&&(E=u,h=y.c2p(b[a[c]])-w,p=Math.sqrt(u*u+h*h),i=a[c]);else for(c=a.length-1;c>-1;c--)s=x[a[c]],l=b[a[c]],u=v.c2p(s)-_,h=y.c2p(l)-w,(f=Math.sqrt(u*u+h*h))<E&&(E=p=f,i=a[c]);return t.index=i,t.distance=E,t.dxy=p,void 0===i?[t]:[o(t,x,b,m)]},calcHover:o}},{"../../lib":728,"../../registry":859,"../scatter/get_trace_color":1144}],1194:[function(t,e,r){"use strict";var n=t("./hover");e.exports={moduleType:"trace",name:"scattergl",basePlotModule:t("../../plots/cartesian"),categories:["gl","regl","cartesian","symbols","errorBarsOK","showLegend","scatter-like"],attributes:t("./attributes"),supplyDefaults:t("./defaults"),crossTraceDefaults:t("../scatter/cross_trace_defaults"),colorbar:t("../scatter/marker_colorbar"),formatLabels:t("./format_labels"),calc:t("./calc"),plot:t("./plot"),hoverPoints:n.hoverPoints,selectPoints:t("./select"),meta:{}}},{"../../plots/cartesian":789,"../scatter/cross_trace_defaults":1140,"../scatter/marker_colorbar":1152,"./attributes":1185,"./calc":1186,"./defaults":1189,"./format_labels":1191,"./hover":1193,"./plot":1195,"./select":1197}],1195:[function(t,e,r){"use strict";var n=t("regl-scatter2d"),a=t("regl-line2d"),i=t("regl-error2d"),o=t("gl-text"),s=t("../../lib"),l=t("../../components/dragelement/helpers").selectMode,c=t("../../lib/prepare_regl"),u=t("../scatter/subtypes"),h=t("../scatter/link_traces"),f=t("./edit_style").styleTextSelection;function p(t,e,r){var n=t._size,a=t.width,i=t.height;return[n.l+e.domain[0]*n.w,n.b+r.domain[0]*n.h,a-n.r-(1-e.domain[1])*n.w,i-n.t-(1-r.domain[1])*n.h]}e.exports=function(t,e,r){if(r.length){var d,g,m=t._fullLayout,v=e._scene,y=e.xaxis,x=e.yaxis;if(v)if(c(t,["ANGLE_instanced_arrays","OES_element_index_uint"])){var b=v.count,_=m._glcanvas.data()[0].regl;if(h(t,e,r),v.dirty){if(!0===v.error2d&&(v.error2d=i(_)),!0===v.line2d&&(v.line2d=a(_)),!0===v.scatter2d&&(v.scatter2d=n(_)),!0===v.fill2d&&(v.fill2d=a(_)),!0===v.glText)for(v.glText=new Array(b),d=0;d<b;d++)v.glText[d]=new o(_);if(v.glText){if(b>v.glText.length){var w=b-v.glText.length;for(d=0;d<w;d++)v.glText.push(new o(_))}else if(b<v.glText.length){var T=v.glText.length-b;v.glText.splice(b,T).forEach((function(t){t.destroy()}))}for(d=0;d<b;d++)v.glText[d].update(v.textOptions[d])}if(v.line2d&&(v.line2d.update(v.lineOptions),v.lineOptions=v.lineOptions.map((function(t){if(t&&t.positions){for(var e=t.positions,r=0;r<e.length&&(isNaN(e[r])||isNaN(e[r+1]));)r+=2;for(var n=e.length-2;n>r&&(isNaN(e[n])||isNaN(e[n+1]));)n-=2;t.positions=e.slice(r,n+2)}return t})),v.line2d.update(v.lineOptions)),v.error2d){var k=(v.errorXOptions||[]).concat(v.errorYOptions||[]);v.error2d.update(k)}v.scatter2d&&v.scatter2d.update(v.markerOptions),v.fillOrder=s.repeat(null,b),v.fill2d&&(v.fillOptions=v.fillOptions.map((function(t,e){var n=r[e];if(t&&n&&n[0]&&n[0].trace){var a,i,o=n[0],s=o.trace,l=o.t,c=v.lineOptions[e],u=[];s._ownfill&&u.push(e),s._nexttrace&&u.push(e+1),u.length&&(v.fillOrder[e]=u);var h,f,p=[],d=c&&c.positions||l.positions;if("tozeroy"===s.fill){for(h=0;h<d.length&&isNaN(d[h+1]);)h+=2;for(f=d.length-2;f>h&&isNaN(d[f+1]);)f-=2;0!==d[h+1]&&(p=[d[h],0]),p=p.concat(d.slice(h,f+2)),0!==d[f+1]&&(p=p.concat([d[f],0]))}else if("tozerox"===s.fill){for(h=0;h<d.length&&isNaN(d[h]);)h+=2;for(f=d.length-2;f>h&&isNaN(d[f]);)f-=2;0!==d[h]&&(p=[0,d[h+1]]),p=p.concat(d.slice(h,f+2)),0!==d[f]&&(p=p.concat([0,d[f+1]]))}else if("toself"===s.fill||"tonext"===s.fill){for(p=[],a=0,i=0;i<d.length;i+=2)(isNaN(d[i])||isNaN(d[i+1]))&&((p=p.concat(d.slice(a,i))).push(d[a],d[a+1]),a=i+2);p=p.concat(d.slice(a)),a&&p.push(d[a],d[a+1])}else{var g=s._nexttrace;if(g){var m=v.lineOptions[e+1];if(m){var y=m.positions;if("tonexty"===s.fill){for(p=d.slice(),e=Math.floor(y.length/2);e--;){var x=y[2*e],b=y[2*e+1];isNaN(x)||isNaN(b)||p.push(x,b)}t.fill=g.fillcolor}}}}if(s._prevtrace&&"tonext"===s._prevtrace.fill){var _=v.lineOptions[e-1].positions,w=p.length/2,T=[a=w];for(i=0;i<_.length;i+=2)(isNaN(_[i])||isNaN(_[i+1]))&&(T.push(i/2+w+1),a=i+2);p=p.concat(_),t.hole=T}return t.fillmode=s.fill,t.opacity=s.opacity,t.positions=p,t}})),v.fill2d.update(v.fillOptions))}var A=m.dragmode,M=l(A),S=m.clickmode.indexOf("select")>-1;for(d=0;d<b;d++){var E=r[d][0],C=E.trace,L=E.t,P=L.index,I=C._length,z=L.x,O=L.y;if(C.selectedpoints||M||S){if(M||(M=!0),C.selectedpoints){var D=v.selectBatch[P]=s.selIndices2selPoints(C),R={};for(g=0;g<D.length;g++)R[D[g]]=1;var F=[];for(g=0;g<I;g++)R[g]||F.push(g);v.unselectBatch[P]=F}var B=L.xpx=new Array(I),N=L.ypx=new Array(I);for(g=0;g<I;g++)B[g]=y.c2p(z[g]),N[g]=x.c2p(O[g])}else L.xpx=L.ypx=null}if(M){if(v.select2d||(v.select2d=n(m._glcanvas.data()[1].regl)),v.scatter2d){var j=new Array(b);for(d=0;d<b;d++)j[d]=v.selectBatch[d].length||v.unselectBatch[d].length?v.markerUnselectedOptions[d]:{};v.scatter2d.update(j)}v.select2d&&(v.select2d.update(v.markerOptions),v.select2d.update(v.markerSelectedOptions)),v.glText&&r.forEach((function(t){var e=((t||[])[0]||{}).trace||{};u.hasText(e)&&f(t)}))}else v.scatter2d&&v.scatter2d.update(v.markerOptions);var V={viewport:p(m,y,x),range:[(y._rl||y.range)[0],(x._rl||x.range)[0],(y._rl||y.range)[1],(x._rl||x.range)[1]]},U=s.repeat(V,v.count);v.fill2d&&v.fill2d.update(U),v.line2d&&v.line2d.update(U),v.error2d&&v.error2d.update(U.concat(U)),v.scatter2d&&v.scatter2d.update(U),v.select2d&&v.select2d.update(U),v.glText&&v.glText.forEach((function(t){t.update(V)}))}else v.init()}}},{"../../components/dragelement/helpers":613,"../../lib":728,"../../lib/prepare_regl":741,"../scatter/link_traces":1150,"../scatter/subtypes":1158,"./edit_style":1190,"gl-text":321,"regl-error2d":488,"regl-line2d":489,"regl-scatter2d":490}],1196:[function(t,e,r){"use strict";var n=t("../../lib");e.exports=function(t,e){var r=e._scene,a={count:0,dirty:!0,lineOptions:[],fillOptions:[],markerOptions:[],markerSelectedOptions:[],markerUnselectedOptions:[],errorXOptions:[],errorYOptions:[],textOptions:[],textSelectedOptions:[],textUnselectedOptions:[],selectBatch:[],unselectBatch:[]},i={fill2d:!1,scatter2d:!1,error2d:!1,line2d:!1,glText:!1,select2d:!1};return e._scene||((r=e._scene={}).init=function(){n.extendFlat(r,i,a)},r.init(),r.update=function(t){var e=n.repeat(t,r.count);if(r.fill2d&&r.fill2d.update(e),r.scatter2d&&r.scatter2d.update(e),r.line2d&&r.line2d.update(e),r.error2d&&r.error2d.update(e.concat(e)),r.select2d&&r.select2d.update(e),r.glText)for(var a=0;a<r.count;a++)r.glText[a].update(t)},r.draw=function(){for(var t=r.count,e=r.fill2d,a=r.error2d,i=r.line2d,o=r.scatter2d,s=r.glText,l=r.select2d,c=r.selectBatch,u=r.unselectBatch,h=0;h<t;h++){if(e&&r.fillOrder[h]&&e.draw(r.fillOrder[h]),i&&r.lineOptions[h]&&i.draw(h),a&&(r.errorXOptions[h]&&a.draw(h),r.errorYOptions[h]&&a.draw(h+t)),o&&r.markerOptions[h])if(u[h].length){var f=n.repeat([],r.count);f[h]=u[h],o.draw(f)}else c[h].length||o.draw(h);s[h]&&r.textOptions[h]&&s[h].render()}l&&l.draw(c),r.dirty=!1},r.destroy=function(){r.fill2d&&r.fill2d.destroy&&r.fill2d.destroy(),r.scatter2d&&r.scatter2d.destroy&&r.scatter2d.destroy(),r.error2d&&r.error2d.destroy&&r.error2d.destroy(),r.line2d&&r.line2d.destroy&&r.line2d.destroy(),r.select2d&&r.select2d.destroy&&r.select2d.destroy(),r.glText&&r.glText.forEach((function(t){t.destroy&&t.destroy()})),r.lineOptions=null,r.fillOptions=null,r.markerOptions=null,r.markerSelectedOptions=null,r.markerUnselectedOptions=null,r.errorXOptions=null,r.errorYOptions=null,r.textOptions=null,r.textSelectedOptions=null,r.textUnselectedOptions=null,r.selectBatch=null,r.unselectBatch=null,e._scene=null}),r.dirty||n.extendFlat(r,a),r}},{"../../lib":728}],1197:[function(t,e,r){"use strict";var n=t("../scatter/subtypes"),a=t("./edit_style").styleTextSelection;e.exports=function(t,e){var r=t.cd,i=[],o=r[0].trace,s=r[0].t,l=o._length,c=s.x,u=s.y,h=s._scene,f=s.index;if(!h)return i;var p=n.hasText(o),d=n.hasMarkers(o),g=!d&&!p;if(!0!==o.visible||g)return i;var m=[],v=[];if(!1!==e&&!e.degenerate)for(var y=0;y<l;y++)e.contains([s.xpx[y],s.ypx[y]],!1,y,t)?(m.push(y),i.push({pointNumber:y,x:c[y],y:u[y]})):v.push(y);if(d){var x=h.scatter2d;if(m.length||v.length){if(!h.selectBatch[f].length&&!h.unselectBatch[f].length){var b=new Array(h.count);b[f]=h.markerUnselectedOptions[f],x.update.apply(x,b)}}else{var _=new Array(h.count);_[f]=h.markerOptions[f],x.update.apply(x,_)}}return h.selectBatch[f]=m,h.unselectBatch[f]=v,p&&a(r),i}},{"../scatter/subtypes":1158,"./edit_style":1190}],1198:[function(t,e,r){"use strict";var n=t("../../plots/template_attributes").hovertemplateAttrs,a=t("../../plots/template_attributes").texttemplateAttrs,i=t("../scattergeo/attributes"),o=t("../scatter/attributes"),s=t("../../plots/mapbox/layout_attributes"),l=t("../../plots/attributes"),c=t("../../components/colorscale/attributes"),u=t("../../lib/extend").extendFlat,h=t("../../plot_api/edit_types").overrideAll,f=i.line,p=i.marker;e.exports=h({lon:i.lon,lat:i.lat,mode:u({},o.mode,{dflt:"markers"}),text:u({},o.text,{}),texttemplate:a({editType:"plot"},{keys:["lat","lon","text"]}),hovertext:u({},o.hovertext,{}),line:{color:f.color,width:f.width},connectgaps:o.connectgaps,marker:u({symbol:{valType:"string",dflt:"circle",arrayOk:!0},angle:{valType:"number",dflt:"auto",arrayOk:!0},allowoverlap:{valType:"boolean",dflt:!1},opacity:p.opacity,size:p.size,sizeref:p.sizeref,sizemin:p.sizemin,sizemode:p.sizemode},c("marker")),fill:i.fill,fillcolor:o.fillcolor,textfont:s.layers.symbol.textfont,textposition:s.layers.symbol.textposition,below:{valType:"string"},selected:{marker:o.selected.marker},unselected:{marker:o.unselected.marker},hoverinfo:u({},l.hoverinfo,{flags:["lon","lat","text","name"]}),hovertemplate:n()},"calc","nested")},{"../../components/colorscale/attributes":602,"../../lib/extend":719,"../../plot_api/edit_types":759,"../../plots/attributes":773,"../../plots/mapbox/layout_attributes":835,"../../plots/template_attributes":854,"../scatter/attributes":1134,"../scattergeo/attributes":1175}],1199:[function(t,e,r){"use strict";var n=t("fast-isnumeric"),a=t("../../lib"),i=t("../../constants/numerical").BADNUM,o=t("../../lib/geojson_utils"),s=t("../../components/colorscale"),l=t("../../components/drawing"),c=t("../scatter/make_bubble_size_func"),u=t("../scatter/subtypes"),h=t("../../plots/mapbox/convert_text_opts"),f=t("../../components/fx/helpers").appendArrayPointValue,p=t("../../lib/svg_text_utils").NEWLINES,d=t("../../lib/svg_text_utils").BR_TAG_ALL;function g(){return{geojson:o.makeBlank(),layout:{visibility:"none"},paint:{}}}function m(t,e){return a.isArrayOrTypedArray(t)?e?function(e){return n(t[e])?+t[e]:0}:function(e){return t[e]}:t?function(){return t}:v}function v(){return""}function y(t){return t[0]===i}e.exports=function(t,e){var r,i=e[0].trace,x=!0===i.visible&&0!==i._length,b="none"!==i.fill,_=u.hasLines(i),w=u.hasMarkers(i),T=u.hasText(i),k=w&&"circle"===i.marker.symbol,A=w&&"circle"!==i.marker.symbol,M=g(),S=g(),E=g(),C=g(),L={fill:M,line:S,circle:E,symbol:C};if(!x)return L;if((b||_)&&(r=o.calcTraceToLineCoords(e)),b&&(M.geojson=o.makePolygon(r),M.layout.visibility="visible",a.extendFlat(M.paint,{"fill-color":i.fillcolor})),_&&(S.geojson=o.makeLine(r),S.layout.visibility="visible",a.extendFlat(S.paint,{"line-width":i.line.width,"line-color":i.line.color,"line-opacity":i.opacity})),k){var P=function(t){var e,r,i,o,u=t[0].trace,h=u.marker,f=u.selectedpoints,p=a.isArrayOrTypedArray(h.color),d=a.isArrayOrTypedArray(h.size),g=a.isArrayOrTypedArray(h.opacity);function m(t){return u.opacity*t}p&&(r=s.hasColorscale(u,"marker")?s.makeColorScaleFuncFromTrace(h):a.identity);d&&(i=c(u));g&&(o=function(t){return m(n(t)?+a.constrain(t,0,1):0)});var v,x=[];for(e=0;e<t.length;e++){var b=t[e],_=b.lonlat;if(!y(_)){var w={};r&&(w.mcc=b.mcc=r(b.mc)),i&&(w.mrc=b.mrc=i(b.ms)),o&&(w.mo=o(b.mo)),f&&(w.selected=b.selected||0),x.push({type:"Feature",geometry:{type:"Point",coordinates:_},properties:w})}}if(f)for(v=l.makeSelectedPointStyleFns(u),e=0;e<x.length;e++){var T=x[e].properties;v.selectedOpacityFn&&(T.mo=m(v.selectedOpacityFn(T))),v.selectedColorFn&&(T.mcc=v.selectedColorFn(T)),v.selectedSizeFn&&(T.mrc=v.selectedSizeFn(T))}return{geojson:{type:"FeatureCollection",features:x},mcc:p||v&&v.selectedColorFn?{type:"identity",property:"mcc"}:h.color,mrc:d||v&&v.selectedSizeFn?{type:"identity",property:"mrc"}:(k=h.size,k/2),mo:g||v&&v.selectedOpacityFn?{type:"identity",property:"mo"}:m(h.opacity)};var k}(e);E.geojson=P.geojson,E.layout.visibility="visible",a.extendFlat(E.paint,{"circle-color":P.mcc,"circle-radius":P.mrc,"circle-opacity":P.mo})}if((A||T)&&(C.geojson=function(t,e){for(var r=e._fullLayout,n=t[0].trace,i=n.marker||{},o=i.symbol,s=i.angle,l="circle"!==o?m(o):v,c="auto"!==s?m(s,!0):v,h=u.hasText(n)?m(n.text):v,g=[],x=0;x<t.length;x++){var b=t[x];if(!y(b.lonlat)){var _,w=n.texttemplate;if(w){var T=Array.isArray(w)?w[x]||"":w,k=n._module.formatLabels(b,n,r),A={};f(A,n,b.i);var M=n._meta||{};_=a.texttemplateString(T,k,r._d3locale,A,b,M)}else 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L}},{"../../components/colorscale":607,"../../components/drawing":617,"../../components/fx/helpers":631,"../../constants/numerical":704,"../../lib":728,"../../lib/geojson_utils":723,"../../lib/svg_text_utils":752,"../../plots/mapbox/convert_text_opts":832,"../scatter/make_bubble_size_func":1151,"../scatter/subtypes":1158,"fast-isnumeric":236}],1200:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../scatter/subtypes"),i=t("../scatter/marker_defaults"),o=t("../scatter/line_defaults"),s=t("../scatter/text_defaults"),l=t("../scatter/fillcolor_defaults"),c=t("./attributes");e.exports=function(t,e,r,u){function h(r,a){return n.coerce(t,e,c,r,a)}if(function(t,e,r){var n=r("lon")||[],a=r("lat")||[],i=Math.min(n.length,a.length);return 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n=t("../../lib"),a=t("../scatter/subtypes"),i=t("../scatter/marker_defaults"),o=t("../scatter/line_defaults"),s=t("../scatter/line_shape_defaults"),l=t("../scatter/text_defaults"),c=t("../scatter/fillcolor_defaults"),u=t("../scatter/constants").PTS_LINESONLY,h=t("./attributes");function f(t,e,r,n){var a,i=n("r"),o=n("theta");if(i)o?a=Math.min(i.length,o.length):(a=i.length,n("theta0"),n("dtheta"));else{if(!o)return 0;a=e.theta.length,n("r0"),n("dr")}return e._length=a,a}e.exports={handleRThetaDefaults:f,supplyDefaults:function(t,e,r,p){function d(r,a){return n.coerce(t,e,h,r,a)}var g=f(t,e,p,d);if(g){d("thetaunit"),d("mode",g<u?"lines+markers":"lines"),d("text"),d("hovertext"),"fills"!==e.hoveron&&d("hovertemplate"),a.hasLines(e)&&(o(t,e,r,p,d),s(t,e,d),d("connectgaps")),a.hasMarkers(e)&&i(t,e,r,p,d,{gradient:!0}),a.hasText(e)&&(d("texttemplate"),l(t,e,p,d));var 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n=t("../scatterpolar/attributes"),a=t("../scattergl/attributes"),i=t("../../plots/template_attributes").texttemplateAttrs;e.exports={mode:n.mode,r:n.r,theta:n.theta,r0:n.r0,dr:n.dr,theta0:n.theta0,dtheta:n.dtheta,thetaunit:n.thetaunit,text:n.text,texttemplate:i({editType:"plot"},{keys:["r","theta","text"]}),hovertext:n.hovertext,hovertemplate:n.hovertemplate,line:a.line,connectgaps:a.connectgaps,marker:a.marker,fill:a.fill,fillcolor:a.fillcolor,textposition:a.textposition,textfont:a.textfont,hoverinfo:n.hoverinfo,selected:n.selected,unselected:n.unselected}},{"../../plots/template_attributes":854,"../scattergl/attributes":1185,"../scatterpolar/attributes":1207}],1215:[function(t,e,r){"use strict";var n=t("../scatter/colorscale_calc"),a=t("../scatter/calc").calcMarkerSize,i=t("../scattergl/convert"),o=t("../../plots/cartesian/axes"),s=t("../scattergl/constants").TOO_MANY_POINTS;e.exports=function(t,e){var 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n=t("../../components/colorscale/attributes"),a=t("../../plots/template_attributes").hovertemplateAttrs,i=t("../mesh3d/attributes"),o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat,l={x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},u:{valType:"data_array",editType:"calc"},v:{valType:"data_array",editType:"calc"},w:{valType:"data_array",editType:"calc"},starts:{x:{valType:"data_array",editType:"calc"},y:{valType:"data_array",editType:"calc"},z:{valType:"data_array",editType:"calc"},editType:"calc"},maxdisplayed:{valType:"integer",min:0,dflt:1e3,editType:"calc"},sizeref:{valType:"number",editType:"calc",min:0,dflt:1},text:{valType:"string",dflt:"",editType:"calc"},hovertext:{valType:"string",dflt:"",editType:"calc"},hovertemplate:a({editType:"calc"},{keys:["tubex","tubey","tubez","tubeu","tubev","tubew","norm","divergence"]}),showlegend:s({},o.showlegend,{dflt:!1})};s(l,n("",{colorAttr:"u/v/w 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v=n[u];r.xMax=Math.max(r.xMax,v),r.xMin=Math.min(r.xMin,v);var y=o[u];r.yMax=Math.max(r.yMax,y),r.yMin=Math.min(r.yMin,y);var x=l[u];r.zMax=Math.max(r.zMax,x),r.zMin=Math.min(r.zMin,x)}e._slen=c,e._normMax=h,e._xbnds=[r.xMin,r.xMax],e._ybnds=[r.yMin,r.yMax],e._zbnds=[r.zMin,r.zMax]},filter:s,processGrid:i}},{"../../components/colorscale/calc":603,"../../lib":728}],1242:[function(t,e,r){"use strict";var n=t("gl-streamtube3d"),a=n.createTubeMesh,i=t("../../lib"),o=t("../../lib/gl_format_color").parseColorScale,s=t("../../components/colorscale").extractOpts,l=t("../../plots/gl3d/zip3"),c={xaxis:0,yaxis:1,zaxis:2};function u(t,e){this.scene=t,this.uid=e,this.mesh=null,this.data=null}var h=u.prototype;function f(t){var e=t.length;return e>2?t.slice(1,e-1):2===e?[(t[0]+t[1])/2]:t}function p(t){var e=t.length;return 1===e?[.5,.5]:[t[1]-t[0],t[e-1]-t[e-2]]}function d(t,e){var r=t.fullSceneLayout,a=t.dataScale,u=e._len,h={};function d(t,e){var n=r[e],o=a[c[e]];return 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I.lightPosition=[O.x,O.y,O.z],I.ambient=e.lighting.ambient,I.diffuse=e.lighting.diffuse,I.specular=e.lighting.specular,I.roughness=e.lighting.roughness,I.fresnel=e.lighting.fresnel,I.opacity=e.opacity,e._pad=I.tubeScale*e.sizeref*2,I}h.handlePick=function(t){var e=this.scene.fullSceneLayout,r=this.scene.dataScale;function n(t,n){var a=e[n],i=r[c[n]];return a.l2c(t)/i}if(t.object===this.mesh){var a=t.data.position,i=t.data.velocity;return t.traceCoordinate=[n(a[0],"xaxis"),n(a[1],"yaxis"),n(a[2],"zaxis"),n(i[0],"xaxis"),n(i[1],"yaxis"),n(i[2],"zaxis"),t.data.intensity*this.data._normMax,t.data.divergence],t.textLabel=this.data.hovertext||this.data.text,!0}},h.update=function(t){this.data=t;var e=d(this.scene,t);this.mesh.update(e)},h.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()},e.exports=function(t,e){var r=t.glplot.gl,n=d(t,e),i=a(r,n),o=new u(t,e.uid);return 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e={rpx0:L,rpx1:L},o.extendFlat(e,Z(t));else e={rpx0:0,rpx1:0};else e={x0:0,x1:0};return n.interpolate(e,a)}(t);return function(t){return U(e(t))}})):u.attr("d",U),l.call(m,k,t,e,{eventDataKeys:v.eventDataKeys,transitionTime:v.CLICK_TRANSITION_TIME,transitionEasing:v.CLICK_TRANSITION_EASING}).call(y.setSliceCursor,t,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:t._transitioning}),u.call(d,a,w);var x=o.ensureSingle(l,"g","slicetext"),b=o.ensureSingle(x,"text","",(function(t){t.attr("data-notex",1)})),T=o.ensureUniformFontSize(t,y.determineTextFont(w,a,h.font));b.text(r.formatSliceLabel(a,k,w,e,h)).classed("slicetext",!0).attr("text-anchor","middle").call(i.font,T).call(s.convertToTspans,t);var A=i.bBox(b.node());a.transform=p(A,a,_),a.transform.targetX=q(a),a.transform.targetY=H(a);var M=function(t,e){var r=t.transform;return f(r,e),r.fontSize=T.size,c(w.type,r,h),o.getTextTransform(r)};g?b.transition().attrTween("transform",(function(t){var e=function(t){var e,r=O[y.getPtId(t)],a=t.transform;if(r)e=r;else if(e={rpx1:t.rpx1,transform:{textPosAngle:a.textPosAngle,scale:0,rotate:a.rotate,rCenter:a.rCenter,x:a.x,y:a.y}},z)if(t.parent)if(G){var i=t.x1>G?2*Math.PI:0;e.x0=e.x1=i}else o.extendFlat(e,Z(t));else e.x0=e.x1=0;else e.x0=e.x1=0;var s=n.interpolate(e.transform.textPosAngle,t.transform.textPosAngle),l=n.interpolate(e.rpx1,t.rpx1),u=n.interpolate(e.x0,t.x0),f=n.interpolate(e.x1,t.x1),p=n.interpolate(e.transform.scale,a.scale),d=n.interpolate(e.transform.rotate,a.rotate),g=0===a.rCenter?3:0===e.transform.rCenter?1/3:1,m=n.interpolate(e.transform.rCenter,a.rCenter);return function(t){var e=l(t),r=u(t),n=f(t),i=function(t){return m(Math.pow(t,g))}(t),o={pxmid:V(e,(r+n)/2),rpx1:e,transform:{textPosAngle:s(t),rCenter:i,x:a.x,y:a.y}};return c(w.type,a,h),{transform:{targetX:q(o),targetY:H(o),scale:p(t),rotate:d(t),rCenter:i}}}}(t);return function(t){return M(e(t),A)}})):b.attr("transform",M(a,A))}))}function b(t){return e=t.rpx1,r=t.transform.textPosAngle,[e*Math.sin(r),-e*Math.cos(r)];var e,r}r.plot=function(t,e,r,a){var i,o,s=t._fullLayout,l=s._sunburstlayer,c=!r,h=!s.uniformtext.mode&&y.hasTransition(r);(u("sunburst",s),(i=l.selectAll("g.trace.sunburst").data(e,(function(t){return t[0].trace.uid}))).enter().append("g").classed("trace",!0).classed("sunburst",!0).attr("stroke-linejoin","round"),i.order(),h)?(a&&(o=a()),n.transition().duration(r.duration).ease(r.easing).each("end",(function(){o&&o()})).each("interrupt",(function(){o&&o()})).each((function(){l.selectAll("g.trace").each((function(e){x(t,e,this,r)}))}))):(i.each((function(e){x(t,e,this,r)})),s.uniformtext.mode&&g(t,s._sunburstlayer.selectAll(".trace"),"sunburst"));c&&i.exit().remove()},r.formatSliceLabel=function(t,e,r,n,a){var i=r.texttemplate,s=r.textinfo;if(!(i||s&&"none"!==s))return"";var l=a.separators,c=n[0],u=t.data.data,h=c.hierarchy,f=y.isHierarchyRoot(t),p=y.getParent(h,t),d=y.getValue(t);if(!i){var g,m=s.split("+"),v=function(t){return-1!==m.indexOf(t)},x=[];if(v("label")&&u.label&&x.push(u.label),u.hasOwnProperty("v")&&v("value")&&x.push(y.formatValue(u.v,l)),!f){v("current path")&&x.push(y.getPath(t.data));var b=0;v("percent parent")&&b++,v("percent entry")&&b++,v("percent root")&&b++;var _=b>1;if(b){var w,T=function(t){g=y.formatPercent(w,l),_&&(g+=" of "+t),x.push(g)};v("percent parent")&&!f&&(w=d/y.getValue(p),T("parent")),v("percent entry")&&(w=d/y.getValue(e),T("entry")),v("percent root")&&(w=d/y.getValue(h),T("root"))}}return v("text")&&(g=o.castOption(r,u.i,"text"),o.isValidTextValue(g)&&x.push(g)),x.join("<br>")}var k=o.castOption(r,u.i,"texttemplate");if(!k)return"";var A={};u.label&&(A.label=u.label),u.hasOwnProperty("v")&&(A.value=u.v,A.valueLabel=y.formatValue(u.v,l)),A.currentPath=y.getPath(t.data),f||(A.percentParent=d/y.getValue(p),A.percentParentLabel=y.formatPercent(A.percentParent,l),A.parent=y.getPtLabel(p)),A.percentEntry=d/y.getValue(e),A.percentEntryLabel=y.formatPercent(A.percentEntry,l),A.entry=y.getPtLabel(e),A.percentRoot=d/y.getValue(h),A.percentRootLabel=y.formatPercent(A.percentRoot,l),A.root=y.getPtLabel(h),u.hasOwnProperty("color")&&(A.color=u.color);var M=o.castOption(r,u.i,"text");return(o.isValidTextValue(M)||""===M)&&(A.text=M),A.customdata=o.castOption(r,u.i,"customdata"),o.texttemplateString(k,A,a._d3locale,A,r._meta||{})}},{"../../components/drawing":617,"../../lib":728,"../../lib/svg_text_utils":752,"../bar/style":883,"../bar/uniform_text":885,"../pie/plot":1117,"./constants":1248,"./fx":1250,"./helpers":1251,"./style":1256,d3:164,"d3-hierarchy":158}],1256:[function(t,e,r){"use strict";var n=t("d3"),a=t("../../components/color"),i=t("../../lib"),o=t("../bar/uniform_text").resizeText;function s(t,e,r){var n=e.data.data,o=!e.children,s=n.i,l=i.castOption(r,s,"marker.line.color")||a.defaultLine,c=i.castOption(r,s,"marker.line.width")||0;t.style("stroke-width",c).call(a.fill,n.color).call(a.stroke,l).style("opacity",o?r.leaf.opacity:null)}e.exports={style:function(t){var e=t._fullLayout._sunburstlayer.selectAll(".trace");o(t,e,"sunburst"),e.each((function(t){var e=n.select(this),r=t[0].trace;e.style("opacity",r.opacity),e.selectAll("path.surface").each((function(t){n.select(this).call(s,t,r)}))}))},styleOne:s}},{"../../components/color":595,"../../lib":728,"../bar/uniform_text":885,d3:164}],1257:[function(t,e,r){"use strict";var n=t("../../components/color"),a=t("../../components/colorscale/attributes"),i=t("../../plots/template_attributes").hovertemplateAttrs,o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat,l=t("../../plot_api/edit_types").overrideAll;function c(t){return{show:{valType:"boolean",dflt:!1},start:{valType:"number",dflt:null,editType:"plot"},end:{valType:"number",dflt:null,editType:"plot"},size:{valType:"number",dflt:null,min:0,editType:"plot"},project:{x:{valType:"boolean",dflt:!1},y:{valType:"boolean",dflt:!1},z:{valType:"boolean",dflt:!1}},color:{valType:"color",dflt:n.defaultLine},usecolormap:{valType:"boolean",dflt:!1},width:{valType:"number",min:1,max:16,dflt:2},highlight:{valType:"boolean",dflt:!0},highlightcolor:{valType:"color",dflt:n.defaultLine},highlightwidth:{valType:"number",min:1,max:16,dflt:2}}}var u=e.exports=l(s({z:{valType:"data_array"},x:{valType:"data_array"},y:{valType:"data_array"},text:{valType:"string",dflt:"",arrayOk:!0},hovertext:{valType:"string",dflt:"",arrayOk:!0},hovertemplate:i(),connectgaps:{valType:"boolean",dflt:!1,editType:"calc"},surfacecolor:{valType:"data_array"}},a("",{colorAttr:"z or surfacecolor",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:"calc"}),{contours:{x:c(),y:c(),z:c()},hidesurface:{valType:"boolean",dflt:!1},lightposition:{x:{valType:"number",min:-1e5,max:1e5,dflt:10},y:{valType:"number",min:-1e5,max:1e5,dflt:1e4},z:{valType:"number",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:"number",min:0,max:1,dflt:.8},diffuse:{valType:"number",min:0,max:1,dflt:.8},specular:{valType:"number",min:0,max:2,dflt:.05},roughness:{valType:"number",min:0,max:1,dflt:.5},fresnel:{valType:"number",min:0,max:5,dflt:.2}},opacity:{valType:"number",min:0,max:1,dflt:1},opacityscale:{valType:"any",editType:"calc"},_deprecated:{zauto:s({},a.zauto,{}),zmin:s({},a.zmin,{}),zmax:s({},a.zmax,{})},hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),"calc","nested");u.x.editType=u.y.editType=u.z.editType="calc+clearAxisTypes",u.transforms=void 0},{"../../components/color":595,"../../components/colorscale/attributes":602,"../../lib/extend":719,"../../plot_api/edit_types":759,"../../plots/attributes":773,"../../plots/template_attributes":854}],1258:[function(t,e,r){"use strict";var n=t("../../components/colorscale/calc");e.exports=function(t,e){e.surfacecolor?n(t,e,{vals:e.surfacecolor,containerStr:"",cLetter:"c"}):n(t,e,{vals:e.z,containerStr:"",cLetter:"c"})}},{"../../components/colorscale/calc":603}],1259:[function(t,e,r){"use strict";var n=t("gl-surface3d"),a=t("ndarray"),i=t("ndarray-linear-interpolate").d2,o=t("../heatmap/interp2d"),s=t("../heatmap/find_empties"),l=t("../../lib").isArrayOrTypedArray,c=t("../../lib/gl_format_color").parseColorScale,u=t("../../lib/str2rgbarray"),h=t("../../components/colorscale").extractOpts;function f(t,e,r){this.scene=t,this.uid=r,this.surface=e,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var p=f.prototype;p.getXat=function(t,e,r,n){var a=l(this.data.x)?l(this.data.x[0])?this.data.x[e][t]:this.data.x[t]:t;return void 0===r?a:n.d2l(a,0,r)},p.getYat=function(t,e,r,n){var a=l(this.data.y)?l(this.data.y[0])?this.data.y[e][t]:this.data.y[e]:e;return void 0===r?a:n.d2l(a,0,r)},p.getZat=function(t,e,r,n){var a=this.data.z[e][t];return null===a&&this.data.connectgaps&&this.data._interpolatedZ&&(a=this.data._interpolatedZ[e][t]),void 0===r?a:n.d2l(a,0,r)},p.handlePick=function(t){if(t.object===this.surface){var e=(t.data.index[0]-1)/this.dataScaleX-1,r=(t.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(e),this.data.z[0].length-1),0),a=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);t.index=[n,a],t.traceCoordinate=[this.getXat(n,a),this.getYat(n,a),this.getZat(n,a)],t.dataCoordinate=[this.getXat(n,a,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,a,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,a,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var i=0;i<3;i++){var o=t.dataCoordinate[i];null!=o&&(t.dataCoordinate[i]*=this.scene.dataScale[i])}var s=this.data.hovertext||this.data.text;return Array.isArray(s)&&s[a]&&void 0!==s[a][n]?t.textLabel=s[a][n]:t.textLabel=s||"",t.data.dataCoordinate=t.dataCoordinate.slice(),this.surface.highlight(t.data),this.scene.glplot.spikes.position=t.dataCoordinate,!0}};var d=[2,3,5,7,11,13,17,19,23,29,31,37,41,43,47,53,59,61,67,71,73,79,83,89,97,101,103,107,109,113,127,131,137,139,149,151,157,163,167,173,179,181,191,193,197,199,211,223,227,229,233,239,241,251,257,263,269,271,277,281,283,293,307,311,313,317,331,337,347,349,353,359,367,373,379,383,389,397,401,409,419,421,431,433,439,443,449,457,461,463,467,479,487,491,499,503,509,521,523,541,547,557,563,569,571,577,587,593,599,601,607,613,617,619,631,641,643,647,653,659,661,673,677,683,691,701,709,719,727,733,739,743,751,757,761,769,773,787,797,809,811,821,823,827,829,839,853,857,859,863,877,881,883,887,907,911,919,929,937,941,947,953,967,971,977,983,991,997,1009,1013,1019,1021,1031,1033,1039,1049,1051,1061,1063,1069,1087,1091,1093,1097,1103,1109,1117,1123,1129,1151,1153,1163,1171,1181,1187,1193,1201,1213,1217,1223,1229,1231,1237,1249,1259,1277,1279,1283,1289,1291,1297,1301,1303,1307,1319,1321,1327,1361,1367,1373,1381,1399,1409,1423,1427,1429,1433,1439,1447,1451,1453,1459,1471,1481,1483,1487,1489,1493,1499,1511,1523,1531,1543,1549,1553,1559,1567,1571,1579,1583,1597,1601,1607,1609,1613,1619,1621,1627,1637,1657,1663,1667,1669,1693,1697,1699,1709,1721,1723,1733,1741,1747,1753,1759,1777,1783,1787,1789,1801,1811,1823,1831,1847,1861,1867,1871,1873,1877,1879,1889,1901,1907,1913,1931,1933,1949,1951,1973,1979,1987,1993,1997,1999,2003,2011,2017,2027,2029,2039,2053,2063,2069,2081,2083,2087,2089,2099,2111,2113,2129,2131,2137,2141,2143,2153,2161,2179,2203,2207,2213,2221,2237,2239,2243,2251,2267,2269,2273,2281,2287,2293,2297,2309,2311,2333,2339,2341,2347,2351,2357,2371,2377,2381,2383,2389,2393,2399,2411,2417,2423,2437,2441,2447,2459,2467,2473,2477,2503,2521,2531,2539,2543,2549,2551,2557,2579,2591,2593,2609,2617,2621,2633,2647,2657,2659,2663,2671,2677,2683,2687,2689,2693,2699,2707,2711,2713,2719,2729,2731,2741,2749,2753,2767,2777,2789,2791,2797,2801,2803,2819,2833,2837,2843,2851,2857,2861,2879,2887,2897,2903,2909,2917,2927,2939,2953,2957,2963,2969,2971,2999];function g(t,e){if(t<e)return 0;for(var r=0;0===Math.floor(t%e);)t/=e,r++;return r}function m(t){for(var e=[],r=0;r<d.length;r++){var n=d[r];e.push(g(t,n))}return e}function v(t){for(var e=m(t),r=t,n=0;n<d.length;n++)if(e[n]>0){r=d[n];break}return r}function y(t,e){if(!(t<1||e<1)){for(var r=m(t),n=m(e),a=1,i=0;i<d.length;i++)a*=Math.pow(d[i],Math.max(r[i],n[i]));return a}}p.calcXnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getXat(e-1,0),a=this.getXat(e,0);r[e-1]=a!==n&&null!=n&&null!=a?Math.abs(a-n):0}var i=0;for(e=1;e<t;e++)i+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(i/r[e-1]);return r},p.calcYnums=function(t){var e,r=[];for(e=1;e<t;e++){var n=this.getYat(0,e-1),a=this.getYat(0,e);r[e-1]=a!==n&&null!=n&&null!=a?Math.abs(a-n):0}var i=0;for(e=1;e<t;e++)i+=r[e-1];for(e=1;e<t;e++)0===r[e-1]?r[e-1]=1:r[e-1]=Math.round(i/r[e-1]);return r};var x=[1,2,4,6,12,24,36,48,60,120,180,240,360,720,840,1260],b=x[9],_=x[13];function w(t,e,r){var n=r[8]+r[2]*e[0]+r[5]*e[1];return 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t,e,r,n=[[],[],[]],a=[!1,!1,!1],i=!1;for(t=0;t<3;++t)if(this.showContour[t]&&(i=!0,this.contourSize[t]>0&&null!==this.contourStart[t]&&null!==this.contourEnd[t]&&this.contourEnd[t]>this.contourStart[t]))for(a[t]=!0,e=this.contourStart[t];e<this.contourEnd[t];e+=this.contourSize[t])r=e*this.scene.dataScale[t],k(n[t],r);if(i){var o=[[],[],[]];for(t=0;t<3;++t)this.showContour[t]&&(o[t]=a[t]?n[t]:this.scene.contourLevels[t]);this.surface.update({levels:o})}},p.update=function(t){var e,r,n,i,l=this.scene,f=l.fullSceneLayout,p=this.surface,d=t.opacity,g=c(t,d),m=l.dataScale,v=t.z[0].length,y=t._ylength,x=l.contourLevels;this.data=t;var 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n=t("../../components/annotations/attributes"),a=t("../../lib/extend").extendFlat,i=t("../../plot_api/edit_types").overrideAll,o=t("../../plots/font_attributes"),s=t("../../plots/domain").attributes;t("../../constants/docs").FORMAT_LINK;(e.exports=i({domain:s({name:"table",trace:!0}),columnwidth:{valType:"number",arrayOk:!0,dflt:null},columnorder:{valType:"data_array"},header:{values:{valType:"data_array",dflt:[]},format:{valType:"data_array",dflt:[]},prefix:{valType:"string",arrayOk:!0,dflt:null},suffix:{valType:"string",arrayOk:!0,dflt:null},height:{valType:"number",dflt:28},align:a({},n.align,{arrayOk:!0}),line:{width:{valType:"number",arrayOk:!0,dflt:1},color:{valType:"color",arrayOk:!0,dflt:"grey"}},fill:{color:{valType:"color",arrayOk:!0,dflt:"white"}},font:a({},o({arrayOk:!0}))},cells:{values:{valType:"data_array",dflt:[]},format:{valType:"data_array",dflt:[]},prefix:{valType:"string",arrayOk:!0,dflt:null},suffix:{valType:"string",arrayOk:!0,dflt:null},height:{valType:"number",dflt:20},align:a({},n.align,{arrayOk:!0}),line:{width:{valType:"number",arrayOk:!0,dflt:1},color:{valType:"color",arrayOk:!0,dflt:"grey"}},fill:{color:{valType:"color",arrayOk:!0,dflt:"white"}},font:a({},o({arrayOk:!0}))}},"calc","from-root")).transforms=void 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n=t("../box/cross_trace_calc").setPositionOffset,a=["v","h"];e.exports=function(t,e){for(var r=t.calcdata,i=e.xaxis,o=e.yaxis,s=0;s<a.length;s++){for(var l=a[s],c="h"===l?o:i,u=[],h=0;h<r.length;h++){var f=r[h],p=f[0].t,d=f[0].trace;!0!==d.visible||"violin"!==d.type||p.empty||d.orientation!==l||d.xaxis!==i._id||d.yaxis!==o._id||u.push(h)}n("violin",t,u,c)}}},{"../box/cross_trace_calc":896}],1287:[function(t,e,r){"use strict";var n=t("../../lib"),a=t("../../components/color"),i=t("../box/defaults"),o=t("./attributes");e.exports=function(t,e,r,s){function l(r,a){return n.coerce(t,e,o,r,a)}function c(r,a){return n.coerce2(t,e,o,r,a)}if(i.handleSampleDefaults(t,e,l,s),!1!==e.visible){l("bandwidth"),l("side"),l("width")||(l("scalegroup",e.name),l("scalemode"));var u,h=l("span");Array.isArray(h)&&(u="manual"),l("spanmode",u);var f=l("line.color",(t.marker||{}).color||r),p=l("line.width"),d=l("fillcolor",a.addOpacity(e.line.color,.5));i.handlePointsDefaults(t,e,l,{prefix:""});var 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n=t("../../components/colorscale/attributes"),a=t("../isosurface/attributes"),i=t("../surface/attributes"),o=t("../../plots/attributes"),s=t("../../lib/extend").extendFlat,l=t("../../plot_api/edit_types").overrideAll,c=e.exports=l(s({x:a.x,y:a.y,z:a.z,value:a.value,isomin:a.isomin,isomax:a.isomax,surface:a.surface,spaceframe:{show:{valType:"boolean",dflt:!1},fill:{valType:"number",min:0,max:1,dflt:1}},slices:a.slices,caps:a.caps,text:a.text,hovertext:a.hovertext,hovertemplate:a.hovertemplate},n("",{colorAttr:"`value`",showScaleDflt:!0,editTypeOverride:"calc"}),{colorbar:a.colorbar,opacity:a.opacity,opacityscale:i.opacityscale,lightposition:a.lightposition,lighting:a.lighting,flatshading:a.flatshading,contour:a.contour,hoverinfo:s({},o.hoverinfo),showlegend:s({},o.showlegend,{dflt:!1})}),"calc","nested");c.x.editType=c.y.editType=c.z.editType=c.value.editType="calc+clearAxisTypes",c.transforms=void 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"subunitcolor": "white"}, "hoverlabel": {"align": "left"}, "hovermode": "closest", "mapbox": {"style": "light"}, "paper_bgcolor": "white", "plot_bgcolor": "#E5ECF6", "polar": {"angularaxis": {"gridcolor": "white", "linecolor": "white", "ticks": ""}, "bgcolor": "#E5ECF6", "radialaxis": {"gridcolor": "white", "linecolor": "white", "ticks": ""}}, "scene": {"xaxis": {"backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white"}, "yaxis": {"backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white"}, "zaxis": {"backgroundcolor": "#E5ECF6", "gridcolor": "white", "gridwidth": 2, "linecolor": "white", "showbackground": true, "ticks": "", "zerolinecolor": "white"}}, "shapedefaults": {"line": {"color": "#2a3f5f"}}, "ternary": {"aaxis": {"gridcolor": "white", "linecolor": "white", "ticks": ""}, "baxis": {"gridcolor": "white", "linecolor": "white", "ticks": ""}, "bgcolor": "#E5ECF6", "caxis": {"gridcolor": "white", "linecolor": "white", "ticks": ""}}, "title": {"x": 0.05}, "xaxis": {"automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": {"standoff": 15}, "zerolinecolor": "white", "zerolinewidth": 2}, "yaxis": {"automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": {"standoff": 15}, "zerolinecolor": "white", "zerolinewidth": 2}}}, "title": {"text": "QSO", "x": 0.5, "xanchor": "center", "y": 0.85}, "width": 500, "xaxis": {"linecolor": "#000000", "linewidth": 1.5, "mirror": "ticks", "nticks": 10, "showgrid": true, "showline": true, "ticklen": 6, "tickmode": "auto", "ticks": "inside", "tickwidth": 2, "title": {"text": "$z$"}}, "yaxis": {"linecolor": "#000000", "linewidth": 1.5, "mirror": "ticks", "nticks": 10, "showgrid": true, "showline": true, "ticklen": 6, "tickmode": "auto", "ticks": "inside", "tickwidth": 2, "title": {"text": "bias"}}},
{"responsive": true}
).then(function(){
var gd = document.getElementById('ebe5c3d4-d021-485c-a064-d923ca4bc7ab');
var x = new MutationObserver(function (mutations, observer) {{
var display = window.getComputedStyle(gd).display;
if (!display || display === 'none') {{
console.log([gd, 'removed!']);
Plotly.purge(gd);
observer.disconnect();
}}
}});
// Listen for the removal of the full notebook cells
var notebookContainer = gd.closest('#notebook-container');
if (notebookContainer) {{
x.observe(notebookContainer, {childList: true});
}}
// Listen for the clearing of the current output cell
var outputEl = gd.closest('.output');
if (outputEl) {{
x.observe(outputEl, {childList: true});
}}
})
};
});
</script>
</div>
## Power spectrum multipole modifications
We compute the modification to power spectrum multipoles as multiples of the matter power spectrum.
```python
power_spectrum = LinearPower(Planck_15, FIDUCIAL_REDSHIFT)(FIDUCIAL_WAVENUMBERS)
```
```python
RSD_multipoles = {
ell: standard_kaiser_factor(ell, b_1, FIDUCIAL_REDSHIFT) * power_spectrum
for ell in [0, 2]
}
```
```python
PNG_multipoles = {
ell: RSD_multipoles[ell] + non_gaussianity_correction_factor(
FIDUCIAL_WAVENUMBERS, ell,
FIDUCIAL_NON_GAUSSNIANTY, b_1, FIDUCIAL_REDSHIFT,
tracer_p=p
) * power_spectrum
for ell in [0, 2]
}
```
```python
GR_multipoles = {
ell: RSD_multipoles[ell] + relativistic_correction_factor(
FIDUCIAL_WAVENUMBERS, ell, FIDUCIAL_REDSHIFT, bias=b_1,
evolution_bias=modeller.evolution_bias,
magnification_bias=modeller.magnification_bias
) * power_spectrum
for ell in [0, 2]
}
```
A comparison plot of all effects.
```python
fig = plt.figure("Power multipole factors", figsize=(3.2, 3.2), dpi=150, constrained_layout=True)
horizon = Planck15.scale_factor(FIDUCIAL_REDSHIFT) * Planck15.H(FIDUCIAL_REDSHIFT) / c.to('km/s')
monopole = plt.subplot2grid((2, 1), (0, 0))
monopole.loglog(FIDUCIAL_WAVENUMBERS, RSD_multipoles[0], label="Kaiser RSD")
monopole.loglog(FIDUCIAL_WAVENUMBERS, PNG_multipoles[0], label="+ non-Gaussianity")
monopole.loglog(FIDUCIAL_WAVENUMBERS, GR_multipoles[0], label="+ relativistic")
monopole.axvline(x=horizon.value, ls=':', c='0.5')
monopole.tick_params(axis='x', which='both', labelbottom=False)
monopole.set_xlim(min(FIDUCIAL_WAVENUMBERS), max(FIDUCIAL_WAVENUMBERS))
monopole.set_ylabel(r"$P_0(k)\ [(h/\mathrm{Mpc})^3]$", fontsize='small')
quadrupole = plt.subplot2grid((2, 1), (1, 0), sharex=monopole)
quadrupole.loglog(FIDUCIAL_WAVENUMBERS, RSD_multipoles[2])
quadrupole.loglog(FIDUCIAL_WAVENUMBERS, PNG_multipoles[2])
quadrupole.loglog(FIDUCIAL_WAVENUMBERS, GR_multipoles[2])
quadrupole.axvline(x=horizon.value, ls=':', c='0.5')
quadrupole.set_xlabel(r"$k$ [$h$/Mpc]", fontsize='small')
quadrupole.set_ylabel(r"$P_2(k)\ [(h/\mathrm{Mpc})^3]$", fontsize='small')
fig.legend(
bbox_to_anchor=[0.575, 0.95], loc='center', ncol=3, columnspacing=1,
handletextpad=0.5, fontsize='x-small'
)
```
<matplotlib.legend.Legend at 0x7fec79566940>
|
MikeSWangREPO_NAMEHorizonGRoundPATH_START.@HorizonGRound_extracted@HorizonGRound-master@application@publication@tracer_relativistic_effects.ipynb@.PATH_END.py
|
{
"filename": "formatter_locator.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/astropy/visualization/wcsaxes/formatter_locator.py",
"type": "Python"
}
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import print_function, division, absolute_import
# This file defines the AngleFormatterLocator class which is a class that
# provides both a method for a formatter and one for a locator, for a given
# label spacing. The advantage of keeping the two connected is that we need to
# make sure that the formatter can correctly represent the spacing requested and
# vice versa. For example, a format of dd:mm cannot work with a tick spacing
# that is not a multiple of one arcminute.
import re
import warnings
import numpy as np
from matplotlib import rcParams
from ...extern import six
from ... import units as u
from ...coordinates import Angle
DMS_RE = re.compile('^dd(:mm(:ss(.(s)+)?)?)?$')
HMS_RE = re.compile('^hh(:mm(:ss(.(s)+)?)?)?$')
DDEC_RE = re.compile('^d(.(d)+)?$')
DMIN_RE = re.compile('^m(.(m)+)?$')
DSEC_RE = re.compile('^s(.(s)+)?$')
SCAL_RE = re.compile('^x(.(x)+)?$')
class BaseFormatterLocator(object):
"""
A joint formatter/locator
"""
def __init__(self, values=None, number=None, spacing=None, format=None):
if (values, number, spacing).count(None) < 2:
raise ValueError("At most one of values/number/spacing can be specifed")
if values is not None:
self.values = values
elif number is not None:
self.number = number
elif spacing is not None:
self.spacing = spacing
else:
self.number = 5
self.format = format
@property
def values(self):
return self._values
@values.setter
def values(self, values):
if not isinstance(values, u.Quantity) or (not values.ndim == 1):
raise TypeError("values should be an astropy.units.Quantity array")
self._number = None
self._spacing = None
self._values = values
@property
def number(self):
return self._number
@number.setter
def number(self, number):
self._number = number
self._spacing = None
self._values = None
@property
def spacing(self):
return self._spacing
@spacing.setter
def spacing(self, spacing):
self._number = None
self._spacing = spacing
self._values = None
def minor_locator(self, spacing, frequency, value_min, value_max):
if self.values is not None:
return [] * self._unit
minor_spacing = spacing.value / frequency
values = self._locate_values(value_min, value_max, minor_spacing)
index = np.where((values % frequency) == 0)
index = index[0][0]
values = np.delete(values, np.s_[index::frequency])
return values * minor_spacing * self._unit
@staticmethod
def _locate_values(value_min, value_max, spacing):
imin = np.ceil(value_min / spacing)
imax = np.floor(value_max / spacing)
values = np.arange(imin, imax + 1, dtype=int)
return values
class AngleFormatterLocator(BaseFormatterLocator):
"""
A joint formatter/locator
"""
def __init__(self, values=None, number=None, spacing=None, format=None):
self._unit = u.degree
self._sep = None
super(AngleFormatterLocator, self).__init__(values=values,
number=number,
spacing=spacing,
format=format)
@property
def spacing(self):
return self._spacing
@spacing.setter
def spacing(self, spacing):
if spacing is not None and (not isinstance(spacing, u.Quantity) or
spacing.unit.physical_type != 'angle'):
raise TypeError("spacing should be an astropy.units.Quantity "
"instance with units of angle")
self._number = None
self._spacing = spacing
self._values = None
@property
def sep(self):
return self._sep
@sep.setter
def sep(self, separator):
self._sep = separator
@property
def format(self):
return self._format
@format.setter
def format(self, value):
self._format = value
if value is None:
return
if DMS_RE.match(value) is not None:
self._decimal = False
self._unit = u.degree
if '.' in value:
self._precision = len(value) - value.index('.') - 1
self._fields = 3
else:
self._precision = 0
self._fields = value.count(':') + 1
elif HMS_RE.match(value) is not None:
self._decimal = False
self._unit = u.hourangle
if '.' in value:
self._precision = len(value) - value.index('.') - 1
self._fields = 3
else:
self._precision = 0
self._fields = value.count(':') + 1
elif DDEC_RE.match(value) is not None:
self._decimal = True
self._unit = u.degree
self._fields = 1
if '.' in value:
self._precision = len(value) - value.index('.') - 1
else:
self._precision = 0
elif DMIN_RE.match(value) is not None:
self._decimal = True
self._unit = u.arcmin
self._fields = 1
if '.' in value:
self._precision = len(value) - value.index('.') - 1
else:
self._precision = 0
elif DSEC_RE.match(value) is not None:
self._decimal = True
self._unit = u.arcsec
self._fields = 1
if '.' in value:
self._precision = len(value) - value.index('.') - 1
else:
self._precision = 0
else:
raise ValueError("Invalid format: {0}".format(value))
if self.spacing is not None and self.spacing < self.base_spacing:
warnings.warn("Spacing is too small - resetting spacing to match format")
self.spacing = self.base_spacing
if self.spacing is not None:
ratio = (self.spacing / self.base_spacing).decompose().value
remainder = ratio - np.round(ratio)
if abs(remainder) > 1.e-10:
warnings.warn("Spacing is not a multiple of base spacing - resetting spacing to match format")
self.spacing = self.base_spacing * max(1, round(ratio))
@property
def base_spacing(self):
if self._decimal:
spacing = self._unit / (10. ** self._precision)
else:
if self._fields == 1:
spacing = 1. * u.degree
elif self._fields == 2:
spacing = 1. * u.arcmin
elif self._fields == 3:
if self._precision == 0:
spacing = 1. * u.arcsec
else:
spacing = u.arcsec / (10. ** self._precision)
if self._unit is u.hourangle:
spacing *= 15
return spacing
def locator(self, value_min, value_max):
if self.values is not None:
# values were manually specified
return self.values, 1.1 * u.arcsec
else:
# In the special case where value_min is the same as value_max, we
# don't locate any ticks. This can occur for example when taking a
# slice for a cube (along the dimension sliced).
if value_min == value_max:
return [] * u.deg, 0 * u.arcsec
if self.spacing is not None:
# spacing was manually specified
spacing_deg = self.spacing.to_value(u.degree)
elif self.number is not None:
# number of ticks was specified, work out optimal spacing
# first compute the exact spacing
dv = abs(float(value_max - value_min)) / self.number * u.degree
if self.format is not None and dv < self.base_spacing:
# if the spacing is less than the minimum spacing allowed by the format, simply
# use the format precision instead.
spacing_deg = self.base_spacing.to_value(u.degree)
else:
# otherwise we clip to the nearest 'sensible' spacing
if self._unit is u.degree:
from .utils import select_step_degree
spacing_deg = select_step_degree(dv).to_value(u.degree)
else:
from .utils import select_step_hour
spacing_deg = select_step_hour(dv).to_value(u.degree)
# We now find the interval values as multiples of the spacing and
# generate the tick positions from this.
values = self._locate_values(value_min, value_max, spacing_deg)
return values * spacing_deg * u.degree, spacing_deg * u.degree
def formatter(self, values, spacing):
if not isinstance(values, u.Quantity) and values is not None:
raise TypeError("values should be a Quantities array")
if len(values) > 0:
if self.format is None:
spacing = spacing.to_value(u.arcsec)
if spacing > 3600:
fields = 1
precision = 0
elif spacing > 60:
fields = 2
precision = 0
elif spacing > 1:
fields = 3
precision = 0
else:
fields = 3
precision = -int(np.floor(np.log10(spacing)))
decimal = False
unit = u.degree
else:
fields = self._fields
precision = self._precision
decimal = self._decimal
unit = self._unit
if decimal:
sep = None
elif self._sep is not None:
sep = self._sep
else:
if unit == u.degree:
if rcParams['text.usetex']:
deg = r'$^\circ$'
else:
deg = six.u('\xb0')
sep = (deg, "'", '"')
else:
sep = ('h', 'm', 's')
angles = Angle(values)
string = angles.to_string(unit=unit,
precision=precision,
decimal=decimal,
fields=fields,
sep=sep).tolist()
return string
else:
return []
class ScalarFormatterLocator(BaseFormatterLocator):
"""
A joint formatter/locator
"""
def __init__(self, values=None, number=None, spacing=None, format=None, unit=None):
if unit is not None:
self._unit = unit
self._format_unit = unit
elif spacing is not None:
self._unit = spacing.unit
self._format_unit = spacing.unit
elif values is not None:
self._unit = values.unit
self._format_unit = values.unit
super(ScalarFormatterLocator, self).__init__(values=values,
number=number,
spacing=spacing,
format=format)
@property
def format_unit(self):
return self._format_unit
@format_unit.setter
def format_unit(self, unit):
if not issubclass(unit.__class__, u.UnitBase):
raise TypeError("unit should be an astropy UnitBase subclass")
self._format_unit = unit
@property
def spacing(self):
return self._spacing
@spacing.setter
def spacing(self, spacing):
if spacing is not None and not isinstance(spacing, u.Quantity):
raise TypeError("spacing should be an astropy.units.Quantity instance")
self._number = None
self._spacing = spacing
self._values = None
@property
def format(self):
return self._format
@format.setter
def format(self, value):
self._format = value
if value is None:
return
if SCAL_RE.match(value) is not None:
if '.' in value:
self._precision = len(value) - value.index('.') - 1
else:
self._precision = 0
if self.spacing is not None and self.spacing < self.base_spacing:
warnings.warn("Spacing is too small - resetting spacing to match format")
self.spacing = self.base_spacing
if self.spacing is not None:
ratio = (self.spacing / self.base_spacing).decompose().value
remainder = ratio - np.round(ratio)
if abs(remainder) > 1.e-10:
warnings.warn("Spacing is not a multiple of base spacing - resetting spacing to match format")
self.spacing = self.base_spacing * max(1, round(ratio))
elif not value.startswith('%'):
raise ValueError("Invalid format: {0}".format(value))
@property
def base_spacing(self):
return self._unit / (10. ** self._precision)
def locator(self, value_min, value_max):
if self.values is not None:
# values were manually specified
return self.values, 1.1 * self._unit
else:
# In the special case where value_min is the same as value_max, we
# don't locate any ticks. This can occur for example when taking a
# slice for a cube (along the dimension sliced).
if value_min == value_max:
return [] * self._unit, 0 * self._unit
if self.spacing is not None:
# spacing was manually specified
spacing = self.spacing.to_value(self._unit)
elif self.number is not None:
# number of ticks was specified, work out optimal spacing
# first compute the exact spacing
dv = abs(float(value_max - value_min)) / self.number
if self.format is not None and (not self.format.startswith('%')) and dv < self.base_spacing.value:
# if the spacing is less than the minimum spacing allowed by the format, simply
# use the format precision instead.
spacing = self.base_spacing.to_value(self._unit)
else:
from .utils import select_step_scalar
spacing = select_step_scalar(dv)
# We now find the interval values as multiples of the spacing and
# generate the tick positions from this
values = self._locate_values(value_min, value_max, spacing)
return values * spacing * self._unit, spacing * self._unit
def formatter(self, values, spacing):
if len(values) > 0:
if self.format is None:
if spacing.value < 1.:
precision = -int(np.floor(np.log10(spacing.value)))
else:
precision = 0
elif self.format.startswith('%'):
return [(self.format % x.value) for x in values]
else:
precision = self._precision
return [("{0:." + str(precision) + "f}").format(x.to_value(self._format_unit)) for x in values]
else:
return []
|
waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@astropy@visualization@wcsaxes@formatter_locator.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "xraypy/xraylarch",
"repo_path": "xraylarch_extracted/xraylarch-master/larch/xafs/__init__.py",
"type": "Python"
}
|
__DOC__ = '''
XAFS Functions for Larch, essentially Ifeffit 2
The functions here include (but are not limited to):
function description
------------ ------------------------------
pre_edge pre_edge subtraction, normalization
autobk XAFS background subtraction (mu(E) to chi(k))
xftf forward XAFS Fourier transform (k -> R)
xftr backward XAFS Fourier transform, Filter (R -> q)
ftwindow create XAFS Fourier transform window
feffpath create a Feff Path from a feffNNNN.dat file
path2chi convert a single Feff Path to chi(k)
ff2chi sum a set of Feff Paths to chi(k)
feffit_dataset create a Dataset for Feffit
feffit_transform create a Feffit transform group
feffit fit a set of Feff Paths to Feffit Datasets
feffit_report create a report from feffit() results
'''
from .xafsutils import KTOE, ETOK, set_xafsGroup, etok, ktoe, guess_energy_units
from .xafsft import xftf, xftr, xftf_fast, xftr_fast, ftwindow, xftf_prep
from .pre_edge import pre_edge, preedge, find_e0, energy_align, find_energy_step
from .prepeaks import prepeaks_setup, pre_edge_baseline, prepeaks_fit
from .feffdat import FeffDatFile, FeffPathGroup, feffpath, path2chi, ff2chi, use_feffpath
from .feffit import (FeffitDataSet, TransformGroup, feffit,
feffit_dataset, feffit_transform, feffit_report,
feffit_conf_map)
from .autobk import autobk, autobk_lmfit, autobk_delta_chi
from .mback import mback, mback_norm
from .diffkk import diffkk, diffKKGroup
from .fluo import fluo_corr
## from .cif2feff import cif_sites, cif2feff6l
from .feffrunner import FeffRunner, feffrunner, feff6l, feff8l, find_exe
from .feff8lpath import feff8_xafs
from .feffutils import get_feff_pathinfo
from .cauchy_wavelet import cauchy_wavelet
from .deconvolve import xas_convolve, xas_deconvolve
from .estimate_noise import estimate_noise
from .rebin_xafs import rebin_xafs, sort_xafs
from .sigma2_models import sigma2_eins, sigma2_debye, sigma2_correldebye, gnxas
def _larch_init(_larch):
"""initialize xafs"""
# initialize _xafs._feff_executable
_larch.symtable.set_symbol('_xafs._feff_executable', find_exe('feff6l'))
_larch.symtable.set_symbol('_xafs._feff8_executable', find_exe('feff8l'))
_larch_groups = (diffKKGroup, FeffRunner, FeffDatFile, FeffPathGroup,
TransformGroup, FeffitDataSet)
_larch_builtins = {'_xafs': dict(autobk=autobk, autobk_lmfit=autobk_lmfit,
autobk_delta_chi=autobk_delta_chi,
etok=etok, ktoe=ktoe,
guess_energy_units=guess_energy_units,
diffkk=diffkk, xftf=xftf, xftr=xftr,
xftf_prep=xftf_prep, xftf_fast=xftf_fast,
xftr_fast=xftr_fast, ftwindow=ftwindow,
find_e0=find_e0, pre_edge=pre_edge,
find_energy_step=find_energy_step,
energy_align=energy_align,
prepeaks_setup=prepeaks_setup,
prepeaks_fit=prepeaks_fit,
pre_edge_baseline=pre_edge_baseline,
mback=mback, mback_norm=mback_norm,
cauchy_wavelet=cauchy_wavelet,
xas_deconvolve=xas_deconvolve,
xas_convolve=xas_convolve,
fluo_corr=fluo_corr,
estimate_noise=estimate_noise,
rebin_xafs=rebin_xafs,
sort_xafs=sort_xafs,
gnxas=gnxas,
sigma2_eins=sigma2_eins,
sigma2_debye=sigma2_debye, feffit=feffit,
feffit_dataset=feffit_dataset,
feffit_transform=feffit_transform,
feffit_report=feffit_report,
feffit_conf_map=feffit_conf_map,
feffrunner=feffrunner, feff6l=feff6l,
feff8l=feff8l,
feffpath= feffpath,
use_feffpath= use_feffpath,
path2chi=path2chi, ff2chi=ff2chi,
feff8_xafs=feff8_xafs,
get_feff_pathinfo=get_feff_pathinfo)}
|
xraypyREPO_NAMExraylarchPATH_START.@xraylarch_extracted@xraylarch-master@larch@xafs@__init__.py@.PATH_END.py
|
{
"filename": "_subplots.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/matplotlib/axes/_subplots.py",
"type": "Python"
}
|
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import map
from matplotlib.gridspec import GridSpec, SubplotSpec
from matplotlib import docstring
import matplotlib.artist as martist
from matplotlib.axes._axes import Axes
import warnings
from matplotlib.cbook import mplDeprecation
class SubplotBase(object):
"""
Base class for subplots, which are :class:`Axes` instances with
additional methods to facilitate generating and manipulating a set
of :class:`Axes` within a figure.
"""
def __init__(self, fig, *args, **kwargs):
"""
*fig* is a :class:`matplotlib.figure.Figure` instance.
*args* is the tuple (*numRows*, *numCols*, *plotNum*), where
the array of subplots in the figure has dimensions *numRows*,
*numCols*, and where *plotNum* is the number of the subplot
being created. *plotNum* starts at 1 in the upper left
corner and increases to the right.
If *numRows* <= *numCols* <= *plotNum* < 10, *args* can be the
decimal integer *numRows* * 100 + *numCols* * 10 + *plotNum*.
"""
self.figure = fig
if len(args) == 1:
if isinstance(args[0], SubplotSpec):
self._subplotspec = args[0]
else:
try:
s = str(int(args[0]))
rows, cols, num = map(int, s)
except ValueError:
raise ValueError(
'Single argument to subplot must be a 3-digit '
'integer')
self._subplotspec = GridSpec(rows, cols)[num - 1]
# num - 1 for converting from MATLAB to python indexing
elif len(args) == 3:
rows, cols, num = args
rows = int(rows)
cols = int(cols)
if isinstance(num, tuple) and len(num) == 2:
num = [int(n) for n in num]
self._subplotspec = GridSpec(rows, cols)[num[0] - 1:num[1]]
else:
if num < 1 or num > rows*cols:
raise ValueError(
"num must be 1 <= num <= {maxn}, not {num}".format(
maxn=rows*cols, num=num))
self._subplotspec = GridSpec(rows, cols)[int(num) - 1]
# num - 1 for converting from MATLAB to python indexing
else:
raise ValueError('Illegal argument(s) to subplot: %s' % (args,))
self.update_params()
# _axes_class is set in the subplot_class_factory
self._axes_class.__init__(self, fig, self.figbox, **kwargs)
def __reduce__(self):
# get the first axes class which does not
# inherit from a subplotbase
def not_subplotbase(c):
return issubclass(c, Axes) and not issubclass(c, SubplotBase)
axes_class = [c for c in self.__class__.mro()
if not_subplotbase(c)][0]
r = [_PicklableSubplotClassConstructor(),
(axes_class,),
self.__getstate__()]
return tuple(r)
def get_geometry(self):
"""get the subplot geometry, e.g., 2,2,3"""
rows, cols, num1, num2 = self.get_subplotspec().get_geometry()
return rows, cols, num1 + 1 # for compatibility
# COVERAGE NOTE: Never used internally or from examples
def change_geometry(self, numrows, numcols, num):
"""change subplot geometry, e.g., from 1,1,1 to 2,2,3"""
self._subplotspec = GridSpec(numrows, numcols)[num - 1]
self.update_params()
self.set_position(self.figbox)
def get_subplotspec(self):
"""get the SubplotSpec instance associated with the subplot"""
return self._subplotspec
def set_subplotspec(self, subplotspec):
"""set the SubplotSpec instance associated with the subplot"""
self._subplotspec = subplotspec
def update_params(self):
"""update the subplot position from fig.subplotpars"""
self.figbox, self.rowNum, self.colNum, self.numRows, self.numCols = \
self.get_subplotspec().get_position(self.figure,
return_all=True)
def is_first_col(self):
return self.colNum == 0
def is_first_row(self):
return self.rowNum == 0
def is_last_row(self):
return self.rowNum == self.numRows - 1
def is_last_col(self):
return self.colNum == self.numCols - 1
# COVERAGE NOTE: Never used internally.
def label_outer(self):
"""Only show "outer" labels and tick labels.
x-labels are only kept for subplots on the last row; y-labels only for
subplots on the first column.
"""
lastrow = self.is_last_row()
firstcol = self.is_first_col()
if not lastrow:
for label in self.get_xticklabels(which="both"):
label.set_visible(False)
self.get_xaxis().get_offset_text().set_visible(False)
self.set_xlabel("")
if not firstcol:
for label in self.get_yticklabels(which="both"):
label.set_visible(False)
self.get_yaxis().get_offset_text().set_visible(False)
self.set_ylabel("")
def _make_twin_axes(self, *kl, **kwargs):
"""
make a twinx axes of self. This is used for twinx and twiny.
"""
from matplotlib.projections import process_projection_requirements
kl = (self.get_subplotspec(),) + kl
projection_class, kwargs, key = process_projection_requirements(
self.figure, *kl, **kwargs)
ax2 = subplot_class_factory(projection_class)(self.figure,
*kl, **kwargs)
self.figure.add_subplot(ax2)
return ax2
_subplot_classes = {}
def subplot_class_factory(axes_class=None):
# This makes a new class that inherits from SubplotBase and the
# given axes_class (which is assumed to be a subclass of Axes).
# This is perhaps a little bit roundabout to make a new class on
# the fly like this, but it means that a new Subplot class does
# not have to be created for every type of Axes.
if axes_class is None:
axes_class = Axes
new_class = _subplot_classes.get(axes_class)
if new_class is None:
new_class = type(str("%sSubplot") % (axes_class.__name__),
(SubplotBase, axes_class),
{'_axes_class': axes_class})
_subplot_classes[axes_class] = new_class
return new_class
# This is provided for backward compatibility
Subplot = subplot_class_factory()
class _PicklableSubplotClassConstructor(object):
"""
This stub class exists to return the appropriate subplot
class when __call__-ed with an axes class. This is purely to
allow Pickling of Axes and Subplots.
"""
def __call__(self, axes_class):
# create a dummy object instance
subplot_instance = _PicklableSubplotClassConstructor()
subplot_class = subplot_class_factory(axes_class)
# update the class to the desired subplot class
subplot_instance.__class__ = subplot_class
return subplot_instance
docstring.interpd.update(Axes=martist.kwdoc(Axes))
docstring.interpd.update(Subplot=martist.kwdoc(Axes))
"""
# this is some discarded code I was using to find the minimum positive
# data point for some log scaling fixes. I realized there was a
# cleaner way to do it, but am keeping this around as an example for
# how to get the data out of the axes. Might want to make something
# like this a method one day, or better yet make get_verts an Artist
# method
minx, maxx = self.get_xlim()
if minx<=0 or maxx<=0:
# find the min pos value in the data
xs = []
for line in self.lines:
xs.extend(line.get_xdata(orig=False))
for patch in self.patches:
xs.extend([x for x,y in patch.get_verts()])
for collection in self.collections:
xs.extend([x for x,y in collection.get_verts()])
posx = [x for x in xs if x>0]
if len(posx):
minx = min(posx)
maxx = max(posx)
# warning, probably breaks inverted axis
self.set_xlim((0.1*minx, maxx))
"""
|
waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@matplotlib@axes@_subplots.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "lenstronomy/lenstronomy",
"repo_path": "lenstronomy_extracted/lenstronomy-main/test/test_Util/__init__.py",
"type": "Python"
}
|
lenstronomyREPO_NAMElenstronomyPATH_START.@lenstronomy_extracted@lenstronomy-main@test@test_Util@__init__.py@.PATH_END.py
|
|
{
"filename": "account.py",
"repo_name": "jabesq-org/pyatmo",
"repo_path": "pyatmo_extracted/pyatmo-master/src/pyatmo/account.py",
"type": "Python"
}
|
"""Support for a Netatmo account."""
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any
from uuid import uuid4
from pyatmo import modules
from pyatmo.const import (
GETEVENTS_ENDPOINT,
GETHOMECOACHDATA_ENDPOINT,
GETHOMESDATA_ENDPOINT,
GETHOMESTATUS_ENDPOINT,
GETPUBLIC_DATA_ENDPOINT,
GETSTATIONDATA_ENDPOINT,
HOME,
SETSTATE_ENDPOINT,
RawData,
)
from pyatmo.helpers import extract_raw_data
from pyatmo.home import Home
from pyatmo.modules.module import MeasureInterval, Module
if TYPE_CHECKING:
from pyatmo.auth import AbstractAsyncAuth
LOG = logging.getLogger(__name__)
class AsyncAccount:
"""Async class of a Netatmo account."""
def __init__(self, auth: AbstractAsyncAuth, favorite_stations: bool = True) -> None:
"""Initialize the Netatmo account."""
self.auth: AbstractAsyncAuth = auth
self.user: str | None = None
self.all_homes_id: dict[str, str] = {}
self.homes: dict[str, Home] = {}
self.raw_data: RawData = {}
self.favorite_stations: bool = favorite_stations
self.public_weather_areas: dict[str, modules.PublicWeatherArea] = {}
self.modules: dict[str, Module] = {}
def __repr__(self) -> str:
"""Return the representation."""
return (
f"{self.__class__.__name__}(user={self.user}, home_ids={self.homes.keys()}"
)
def process_topology(self, disabled_homes_ids: list[str] | None = None) -> None:
"""Process topology information from /homesdata."""
if disabled_homes_ids is None:
disabled_homes_ids = []
for home in self.raw_data["homes"]:
home_id = home.get("id", "Unknown")
home_name = home.get("name", "Unknown")
self.all_homes_id[home_id] = home_name
if home_id in disabled_homes_ids:
if home_id in self.homes:
del self.homes[home_id]
continue
if home_id in self.homes:
self.homes[home_id].update_topology(home)
else:
self.homes[home_id] = Home(self.auth, raw_data=home)
async def async_update_topology(
self, disabled_homes_ids: list[str] | None = None
) -> None:
"""Retrieve topology data from /homesdata."""
resp = await self.auth.async_post_api_request(
endpoint=GETHOMESDATA_ENDPOINT,
)
self.raw_data = extract_raw_data(await resp.json(), "homes")
self.user = self.raw_data.get("user", {}).get("email")
self.process_topology(disabled_homes_ids=disabled_homes_ids)
async def async_update_status(self, home_id: str) -> None:
"""Retrieve status data from /homestatus."""
resp = await self.auth.async_post_api_request(
endpoint=GETHOMESTATUS_ENDPOINT,
params={"home_id": home_id},
)
raw_data = extract_raw_data(await resp.json(), HOME)
await self.homes[home_id].update(raw_data, do_raise_for_reachability_error=True)
async def async_update_events(self, home_id: str) -> None:
"""Retrieve events from /getevents."""
resp = await self.auth.async_post_api_request(
endpoint=GETEVENTS_ENDPOINT,
params={"home_id": home_id},
)
raw_data = extract_raw_data(await resp.json(), HOME)
await self.homes[home_id].update(raw_data)
async def async_update_weather_stations(self) -> None:
"""Retrieve status data from /getstationsdata."""
params = {"get_favorites": ("true" if self.favorite_stations else "false")}
await self._async_update_data(
GETSTATIONDATA_ENDPOINT,
params=params,
)
async def async_update_air_care(self) -> None:
"""Retrieve status data from /gethomecoachsdata."""
await self._async_update_data(GETHOMECOACHDATA_ENDPOINT)
async def async_update_measures(
self,
home_id: str,
module_id: str,
start_time: int | None = None,
end_time: int | None = None,
interval: MeasureInterval = MeasureInterval.HOUR,
days: int = 7,
) -> None:
"""Retrieve measures data from /getmeasure."""
await getattr(self.homes[home_id].modules[module_id], "async_update_measures")(
start_time=start_time,
end_time=end_time,
interval=interval,
days=days,
)
def register_public_weather_area(
self,
lat_ne: str,
lon_ne: str,
lat_sw: str,
lon_sw: str,
required_data_type: str | None = None,
filtering: bool = False,
*,
area_id: str = str(uuid4()),
) -> str:
"""Register public weather area to monitor."""
self.public_weather_areas[area_id] = modules.PublicWeatherArea(
lat_ne,
lon_ne,
lat_sw,
lon_sw,
required_data_type,
filtering,
)
return area_id
async def async_update_public_weather(self, area_id: str) -> None:
"""Retrieve status data from /getpublicdata."""
params = {
"lat_ne": self.public_weather_areas[area_id].location.lat_ne,
"lon_ne": self.public_weather_areas[area_id].location.lon_ne,
"lat_sw": self.public_weather_areas[area_id].location.lat_sw,
"lon_sw": self.public_weather_areas[area_id].location.lon_sw,
"filtering": (
"true" if self.public_weather_areas[area_id].filtering else "false"
),
}
await self._async_update_data(
GETPUBLIC_DATA_ENDPOINT,
tag="body",
params=params,
area_id=area_id,
)
async def _async_update_data(
self,
endpoint: str,
params: dict[str, Any] | None = None,
tag: str = "devices",
area_id: str | None = None,
) -> None:
"""Retrieve status data from <endpoint>."""
resp = await self.auth.async_post_api_request(endpoint=endpoint, params=params)
raw_data = extract_raw_data(await resp.json(), tag)
await self.update_devices(raw_data, area_id)
async def async_set_state(self, home_id: str, data: dict[str, Any]) -> None:
"""Modify device state by passing JSON specific to the device."""
LOG.debug("Setting state: %s", data)
post_params = {
"json": {
HOME: {
"id": home_id,
**data,
},
},
}
resp = await self.auth.async_post_api_request(
endpoint=SETSTATE_ENDPOINT,
params=post_params,
)
LOG.debug("Response: %s", resp)
async def update_devices(
self,
raw_data: RawData,
area_id: str | None = None,
) -> None:
"""Update device states."""
for device_data in raw_data.get("devices", {}):
if home_id := device_data.get(
"home_id",
self.find_home_of_device(device_data),
):
if home_id not in self.homes:
modules_data = []
for module_data in device_data.get("modules", []):
module_data["home_id"] = home_id
module_data["id"] = module_data["_id"]
module_data["name"] = module_data.get("module_name")
modules_data.append(normalize_weather_attributes(module_data))
modules_data.append(normalize_weather_attributes(device_data))
self.homes[home_id] = Home(
self.auth,
raw_data={
"id": home_id,
"name": device_data.get("home_name", "Unknown"),
"modules": modules_data,
},
)
await self.homes[home_id].update(
{HOME: {"modules": [normalize_weather_attributes(device_data)]}},
)
else:
LOG.debug("No home %s (%s) found.", home_id, home_id)
for module_data in device_data.get("modules", []):
module_data["home_id"] = home_id
await self.update_devices({"devices": [module_data]})
if (
device_data["type"] == "NHC"
or self.find_home_of_device(device_data) is None
):
device_data["name"] = device_data.get(
"station_name",
device_data.get("module_name", "Unknown"),
)
device_data = normalize_weather_attributes(device_data)
if device_data["id"] not in self.modules:
self.modules[device_data["id"]] = getattr(
modules,
device_data["type"],
)(
home=self,
module=device_data,
)
await self.modules[device_data["id"]].update(device_data)
if device_data.get("modules", []):
self.modules[device_data["id"]].modules = [
module["_id"] for module in device_data["modules"]
]
if area_id is not None:
self.public_weather_areas[area_id].update(raw_data)
def find_home_of_device(self, device_data: dict[str, Any]) -> str | None:
"""Find home_id of device."""
return next(
(
home_id
for home_id, home in self.homes.items()
if device_data["_id"] in home.modules
),
None,
)
ATTRIBUTES_TO_FIX = {
"_id": "id",
"firmware": "firmware_revision",
"wifi_status": "wifi_strength",
"rf_status": "rf_strength",
"Temperature": "temperature",
"Humidity": "humidity",
"Pressure": "pressure",
"CO2": "co2",
"AbsolutePressure": "absolute_pressure",
"Noise": "noise",
"Rain": "rain",
"WindStrength": "wind_strength",
"WindAngle": "wind_angle",
"GustStrength": "gust_strength",
"GustAngle": "gust_angle",
}
def normalize_weather_attributes(raw_data: RawData) -> dict[str, Any]:
"""Normalize weather attributes."""
result: dict[str, Any] = {}
for attribute, value in raw_data.items():
if attribute == "dashboard_data":
result.update(**normalize_weather_attributes(value))
else:
result[ATTRIBUTES_TO_FIX.get(attribute, attribute)] = value
return result
|
jabesq-orgREPO_NAMEpyatmoPATH_START.@pyatmo_extracted@pyatmo-master@src@pyatmo@account.py@.PATH_END.py
|
{
"filename": "eventsManager.py",
"repo_name": "GeminiDRSoftware/DRAGONS",
"repo_path": "DRAGONS_extracted/DRAGONS-master/recipe_system/adcc/servers/eventsManager.py",
"type": "Python"
}
|
#
# QAP Gemini
#
# eventsManager.py
# ------------------------------------------------------------------------------
import json
import time
import re
from astrodata import AstroData
# ------------------------------------------------------------------------------
class EventsManager:
def __init__(self):
self.event_list = []
self.event_index = {}
def _get_stacklist(self, ad):
# Find a list of all images that went into a stack for a stacked image
#raw_rgx = re.compile(r'^(tmp)(\d+)(gemcombine)(N|S)(\d{8})(S)(\d{4})
# (\.fits)(\[SCI,)(\d+)(\])$')
# For quick reductions for the GUI, we are assuming that the same
# images are combined for all extensions
# Depracated:
# raw_rgx = re.compile(r'tmp\d+gemcombine[NS]\d{8}S\d{4}\.fits\[SCI,\d+\]')
return list(ad.phu.get('IMCMB***').values())
def get_metadict(self, ad):
# Key: metadata dictionary key, Value: descriptor name
descriptor_dict = {
"datalabel" : "data_label",
"local_time": "local_time",
"ut_time" : "ut_datetime",
"wavelength": "central_wavelength",
"filter" : "filter_name",
"waveband" : "wavelength_band",
"airmass" : "airmass",
"instrument": "instrument",
"object" : "object",
"wfs" : "wavefront_sensor",
}
options = {
"central_wavelength": dict(asMicrometers=True),
"filter_name" : dict(pretty=True),
}
postprocess = {
"local_time" : lambda x: x.strftime("%H:%M:%S.%f"),
"ut_datetime": lambda x: x.strftime("%Y-%m-%d %H:%M:%S.%f"),
}
mtd_dict = {
"raw_filename": ad.filename,
"types": list(ad.tags),
}
for mtd_name, desc_name in list(descriptor_dict.items()):
try:
descriptor = getattr(ad, desc_name)
except AttributeError:
mtd_dict[mtd_name] = None
else:
# Get the postprocessing transform. If there's none, use
# an identity function.
postproc = postprocess.get(desc_name, lambda x: x)
dv = descriptor(**options.get(desc_name, {}))
mtd_dict[mtd_name] = postproc(dv)
# If the file is a processed stack, then add the filenames of the
# data that went into the stack
if ad.phu.get('STACKFRM'):
stack_list = self._get_stacklist(ad)
mtd_dict["stack"] = stack_list
mtd = {"metadata": mtd_dict}
return mtd
def append_event(self, ad=None, name=None, mdict=None, metadata=None,
msgtype="qametric"):
curtime = time.time()
wholed = {
"msgtype" : msgtype,
name : mdict,
"timestamp": curtime
}
if isinstance(ad, AstroData):
if metadata is not None:
md = metadata
else:
md = self.get_metadict(ad)
wholed.update(md)
elif isinstance(ad, list):
for msg in ad:
if "timestamp" in msg:
msg.update({"reported_timestamp":msg["timestamp"]})
msg.update({"timestamp":time.time()})
self.event_list.extend(ad)
return
elif isinstance(ad, dict):
if "timestamp" not in ad:
ad.update({"timestamp":time.time()})
if "timestamp" in ad and "reported_timestamp" not in ad:
ad.update({"reported_timestamp":ad["timestamp"]})
wholed = ad
else:
raise TypeError("Bad Arguments")
self.event_list.append(wholed)
timestamp = wholed["timestamp"]
if timestamp not in self.event_index:
self.event_index.update({timestamp:[]})
ts_list = self.event_index[timestamp]
ts_list.append(self.event_list.index(wholed))
return
def get_list(self, fromtime=None):
if not fromtime:
return self.event_list
else:
for i in range(len(self.event_list)):
if self.event_list[i]["timestamp"] > fromtime:
return self.event_list[i:]
return []
def clear_list(self):
self.event_list = []
self.event_index = {}
return
|
GeminiDRSoftwareREPO_NAMEDRAGONSPATH_START.@DRAGONS_extracted@DRAGONS-master@recipe_system@adcc@servers@eventsManager.py@.PATH_END.py
|
{
"filename": "_uirevision.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/mesh3d/_uirevision.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class UirevisionValidator(_plotly_utils.basevalidators.AnyValidator):
def __init__(self, plotly_name="uirevision", parent_name="mesh3d", **kwargs):
super(UirevisionValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "none"),
role=kwargs.pop("role", "info"),
**kwargs
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@mesh3d@_uirevision.py@.PATH_END.py
|
{
"filename": "common.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/tests/apply/common.py",
"type": "Python"
}
|
from pandas.core.groupby.base import transformation_kernels
# There is no Series.cumcount or DataFrame.cumcount
series_transform_kernels = [
x for x in sorted(transformation_kernels) if x != "cumcount"
]
frame_transform_kernels = [x for x in sorted(transformation_kernels) if x != "cumcount"]
|
pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@tests@apply@common.py@.PATH_END.py
|
{
"filename": "_omnibus.py",
"repo_name": "maximtrp/scikit-posthocs",
"repo_path": "scikit-posthocs_extracted/scikit-posthocs-master/scikit_posthocs/_omnibus.py",
"type": "Python"
}
|
# -*- coding: utf-8 -*-
from typing import Optional, Union, List, cast
import itertools as it
import numpy as np
from numpy.typing import ArrayLike
import scipy.stats as ss
from pandas import DataFrame, Categorical, Series
from scikit_posthocs._posthocs import __convert_to_df, __convert_to_block_df
def test_mackwolfe(
data: Union[ArrayLike, DataFrame],
val_col: Optional[str] = None,
group_col: Optional[str] = None,
p: Optional[int] = None,
n_perm: int = 100,
sort: bool = False,
) -> tuple[float, float]:
"""Mack-Wolfe Test for Umbrella Alternatives.
In dose-finding studies one may assume an increasing treatment effect with
increasing dose level. However, the test subject may actually succumb to
toxic effects at high doses, which leads to decresing treatment
effects [1]_, [2]_.
The scope of the Mack-Wolfe Test is to test for umbrella alternatives for
either a known or unknown point P (i.e. dose-level), where the peak
(umbrella point) is present.
Parameters
----------
data : Union[List, numpy.ndarray, DataFrame]
An array, any object exposing the array interface or a pandas
DataFrame with data values.
val_col : str = None
Name of a DataFrame column that contains dependent variable values
(test or response variable). Values should have a non-nominal scale.
Must be specified if ``a`` is a pandas DataFrame object.
group_col : str = None
Name of a DataFrame column that contains independent variable values
(grouping or predictor variable). Values should have a nominal scale
(categorical). Must be specified if ``a`` is a pandas DataFrame object.
p : int = None
The a priori known peak as an ordinal number of the treatment group
including the zero dose level, i.e. p = {0, ..., k-1}.
Defaults to None.
n_perm: int = 100
Permutations number.
sort : bool = False
If ``True``, sort data by block and group columns.
Returns
-------
tuple[float, float]
P value and statistic.
References
----------
.. [1] Chen, I.Y. (1991) Notes on the Mack-Wolfe and Chen-Wolfe Tests for
Umbrella Alternatives. Biom. J., 33, 281-290.
.. [2] Mack, G.A., Wolfe, D. A. (1981) K-sample rank tests for umbrella
alternatives. J. Amer. Statist. Assoc., 76, 175-181.
Examples
--------
>>> x = [[22, 23, 35], [60, 59, 54], [98, 78, 50], [60, 82, 59], [22, 44, 33], [23, 21, 25]]
>>> sp.posthoc_mackwolfe(x)
"""
x, _val_col, _group_col = __convert_to_df(data, val_col, group_col)
if not sort:
x[_group_col] = Categorical(x[_group_col], categories=x[_group_col].unique(), ordered=True)
x.sort_values(by=[_group_col], ascending=True, inplace=True)
k = x[_group_col].unique().size
if p and p > k:
print("Selected 'p' > number of groups:", str(p), " > ", str(k))
return (np.nan, np.nan)
elif p is not None and p < 1:
print("Selected 'p' < 1: ", str(p))
return (np.nan, np.nan)
Rij = x[_val_col].rank()
n = cast(Series, x.groupby(_group_col, observed=False)[_val_col].count())
def _fn(Ri, Rj):
return np.sum(Ri.apply(lambda x: Rj[Rj > x].size))
def _ustat(Rij, g, k):
levels = np.unique(g)
U = np.identity(k)
for i in range(k):
for j in range(i):
U[i, j] = _fn(Rij[x[_group_col] == levels[i]], Rij[x[_group_col] == levels[j]])
U[j, i] = _fn(Rij[x[_group_col] == levels[j]], Rij[x[_group_col] == levels[i]])
return U
def _ap(p, U) -> float:
tmp1 = 0.0
if p > 0:
for i in range(p):
for j in range(i + 1, p + 1):
tmp1 += U[i, j]
tmp2 = 0.0
if p < k:
for i in range(p, k):
for j in range(i + 1, k):
tmp2 += U[j, i]
return tmp1 + tmp2
def _n1(p: int, n: Series) -> float:
return np.sum(n[: p + 1])
def _n2(p: int, n: Series) -> float:
return np.sum(n[p:k])
def _mean_at(p, n) -> float:
N1 = _n1(p, n)
N2 = _n2(p, n)
return (N1**2.0 + N2**2.0 - np.sum(n**2.0) - n.iloc[p] ** 2.0) / 4.0
def _var_at(p: int, n: Series) -> float:
N1 = _n1(p, n)
N2 = _n2(p, n)
N = np.sum(n)
var = (
2.0 * (N1**3 + N2**3)
+ 3.0 * (N1**2 + N2**2)
- np.sum(n**2 * (2 * n + 3.0))
- n.iloc[p] ** 2.0 * (2.0 * n.iloc[p] + 3.0)
+ 12.0 * n.iloc[p] * N1 * N2
- 12.0 * n.iloc[p] ** 2.0 * N
) / 72.0
return var
if p:
# if (x.groupby(_val_col).count() > 1).any().any():
# print("Ties are present")
U = _ustat(Rij, x[_group_col], k)
est = _ap(p, U)
mean = _mean_at(p, n)
sd = np.sqrt(_var_at(p, n))
stat = (est - mean) / sd
p_value = ss.norm.sf(stat).item()
else:
U = _ustat(Rij, x[_group_col], k)
Ap = np.array([_ap(i, U) for i in range(k)]).ravel()
mean = np.array([_mean_at(i, n) for i in range(k)]).ravel()
var = np.array([_var_at(i, n) for i in range(k)]).ravel()
A = (Ap - mean) / np.sqrt(var)
stat = float(np.max(A))
mt = []
for _ in range(n_perm):
ix = Series(np.random.permutation(Rij))
uix = _ustat(ix, x[_group_col], k)
apix = np.array([_ap(i, uix) for i in range(k)])
astarix = (apix - mean) / np.sqrt(var)
mt.append(np.max(astarix))
mt = np.array(mt)
p_value = mt[mt > stat].size / n_perm
return p_value, stat
def test_osrt(
data: Union[List, np.ndarray, DataFrame],
val_col: Optional[str] = None,
group_col: Optional[str] = None,
sort: bool = False,
) -> tuple[float, float, int]:
"""Hayter's one-sided studentised range test (OSRT)
Tests a hypothesis against an ordered alternative for normal data with
equal variances [1]_.
Parameters
----------
data : Union[List, numpy.ndarray, DataFrame]
An array, any object exposing the array interface or a pandas
DataFrame with data values.
val_col : str = None
Name of a DataFrame column that contains dependent variable values
(test or response variable). Values should have a non-nominal scale.
Must be specified if ``a`` is a pandas DataFrame object.
group_col : str = None
Name of a DataFrame column that contains independent variable values
(grouping or predictor variable). Values should have a nominal scale
(categorical). Must be specified if `a` is a pandas DataFrame object.
sort : bool = False
If True, sort data by block and group columns.
Returns
-------
tuple[float, float, int]
P value, statistic, and number of degrees of freedom.
Notes
-----
P values are computed from the Tukey distribution.
References
----------
.. [1] Hayter, A.J.(1990) A One-Sided Studentised Range Test for Testing
Against a Simple Ordered Alternative, Journal of the American
Statistical Association, 85, 778-785.
Examples
--------
>>> import scikit_posthocs as sp
>>> import pandas as pd
>>> x = pd.DataFrame({"a": [1,2,3,5,1], "b": [12,31,54,62,12], "c": [10,12,6,74,11]})
>>> x = x.melt(var_name='groups', value_name='values')
>>> sp.test_osrt(x, val_col='values', group_col='groups')
"""
x, _val_col, _group_col = __convert_to_df(data, val_col, group_col)
if not sort:
x[_group_col] = Categorical(x[_group_col], categories=x[_group_col].unique(), ordered=True)
x.sort_values(by=[_group_col], ascending=True, inplace=True)
groups = np.unique(x[_group_col])
x_grouped = x.groupby(_group_col, observed=False)[_val_col]
xi = x_grouped.mean()
ni = x_grouped.count()
k = groups.size
n = len(x.index)
df = n - k
sigma2 = 0
c = -1
for i in range(k):
for j in range(ni.iloc[i]):
c += 1
sigma2 += (x[_val_col].iloc[c] - xi.iloc[i]) ** 2.0 / df
sigma = np.sqrt(sigma2)
def compare(i, j):
dif = xi.loc[groups[j]] - xi.loc[groups[i]]
A = sigma / np.sqrt(2.0) * np.sqrt(1.0 / ni[groups[j]] + 1.0 / ni[groups[i]])
qval = np.abs(dif) / A
return qval
vs = np.zeros((k, k), dtype=float)
combs = it.combinations(range(k), 2)
for i, j in combs:
vs[i, j] = compare(i, j)
stat = np.max(vs)
pval = ss.studentized_range.sf(stat, k, df)
return pval, stat, df
def test_durbin(
data: Union[List, np.ndarray, DataFrame],
y_col: Optional[Union[str, int]] = None,
group_col: Optional[Union[str, int]] = None,
block_col: Optional[Union[str, int]] = None,
block_id_col: Optional[Union[str, int]] = None,
melted: bool = False,
sort: bool = True,
) -> tuple[float, float, int]:
"""Durbin's test whether k groups (or treatments) in a two-way
balanced incomplete block design (BIBD) have identical effects. See
references for additional information [1]_, [2]_.
Parameters
----------
data : Union[List, np.ndarray, DataFrame]
An array, any object exposing the array interface or a pandas
DataFrame with data values.
If ``melted`` argument is set to False (default), ``a`` is a typical
matrix of block design, i.e. rows are blocks, and columns are groups.
In this case, you do not need to specify col arguments.
If ``a`` is an array and ``melted`` is set to True,
y_col, block_col and group_col must specify the indices of columns
containing elements of correspondary type.
If ``a`` is a Pandas DataFrame and ``melted`` is set to True,
y_col, block_col and group_col must specify columns names (string).
y_col : Union[str, int] = None
Must be specified if ``a`` is a melted pandas DataFrame object.
Name of the column that contains y data.
group_col : Union[str, int] = None
Must be specified if ``a`` is a melted pandas DataFrame object.
Name of the column that contains group names.
block_col : Union[str, int] = None
Must be specified if ``a`` is a melted pandas DataFrame object.
Name of the column that contains block names.
block_id_col : Union[str, int] = None
Must be specified if ``a`` is a melted pandas DataFrame object.
Name of the column that contains identifiers of block names.
In most cases, this is the same as `block_col` except for those
cases when you have multiple instances of the same blocks.
melted : bool = False
Specifies if data are given as melted columns "y", "blocks", and
"groups".
sort : bool = False
If True, sort data by block and group columns.
Returns
-------
tuple[float, float, int]
P value, statistic, and number of degrees of freedom.
References
----------
.. [1] N. A. Heckert, J. J. Filliben. (2003) NIST Handbook 148: Dataplot Reference
Manual, Volume 2: Let Subcommands and Library Functions. National Institute of
Standards and Technology Handbook Series, June 2003.
.. [2] W. J. Conover (1999), Practical nonparametric Statistics,
3rd. edition, Wiley.
Examples
--------
>>> x = np.array([[31,27,24],[31,28,31],[45,29,46],[21,18,48],[42,36,46],[32,17,40]])
>>> sp.test_durbin(x)
"""
x, _y_col, _group_col, _block_col, _block_id_col = __convert_to_block_df(
data, y_col, group_col, block_col, block_id_col, melted
)
groups = x[_group_col].unique()
blocks = x[_block_id_col].unique()
if not sort:
x[_group_col] = Categorical(x[_group_col], categories=groups, ordered=True)
x[_block_col] = Categorical(x[_block_col], categories=blocks, ordered=True)
x.sort_values(by=[_block_col, _group_col], ascending=True, inplace=True)
x.dropna(inplace=True)
t = len(groups)
b = len(blocks)
r = float(b)
k = float(t)
x["y_ranks"] = x.groupby(_block_id_col)[_y_col].rank()
rs = x.groupby(_group_col)["y_ranks"].sum().to_numpy()
A = float(np.sum(x["y_ranks"] ** 2.0))
C = float(b * k * (k + 1) ** 2.0) / 4.0
D = float(np.sum(rs**2.0)) - r * C
T1 = (t - 1.0) / (A - C) * D
stat = T1
df = t - 1
pval = ss.chi2.sf(stat, df).item()
return pval, stat, df
|
maximtrpREPO_NAMEscikit-posthocsPATH_START.@scikit-posthocs_extracted@scikit-posthocs-master@scikit_posthocs@_omnibus.py@.PATH_END.py
|
{
"filename": "_ybingroup.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/histogram2d/_ybingroup.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class YbingroupValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(self, plotly_name="ybingroup", parent_name="histogram2d", **kwargs):
super(YbingroupValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
role=kwargs.pop("role", "info"),
**kwargs
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@histogram2d@_ybingroup.py@.PATH_END.py
|
{
"filename": "plot_fig7.py",
"repo_name": "masoncarney/stepped_luneburg",
"repo_path": "stepped_luneburg_extracted/stepped_luneburg-master/paper/fig7/plot_fig7.py",
"type": "Python"
}
|
import os, sys
import numpy as np
import pylab as pl
from matplotlib.ticker import MultipleLocator
'''
Script to plot enclosed intensity vs. theta exponent for multiple Luneburg lens runs.
Theta corresponds to the angle away from the initial wavefront focal point.
'''
###################################################################
### Update matplotlib rc params
params = {'axes.labelsize' : 20,
'font.size' : 20,
'legend.fontsize' : 12,
'xtick.labelsize' : 18,
'ytick.labelsize' : 18,
'xtick.major.size' : 8,
'ytick.major.size' : 8,
'xtick.minor.size' : 3,
'ytick.minor.size' : 3,
'xtick.direction' : 'in',
'ytick.direction' : 'in',
'text.usetex' : True,
'savefig.dpi' : 100,
'savefig.bbox' : 'tight',
'savefig.pad_inches': 0.05
}
pl.rcParams.update(params)
###################################################################
datadir = "./"
savedir = "./"
layers = 40 # must be integers
plaw_exp = 0.55
nrays = 1024.
### define output figure file name
figoutfile = "fig7.pdf"
###################################################################
### define file list for plotting
infile = ('luneburg_enc_int_%i_%.2f_%i_grid.dat'%(layers,plaw_exp,nrays)).replace('_0.','_0d')
### create figure
fig = pl.figure(figsize=(6.5,5), dpi=100, facecolor='w', edgecolor='k')
pl.subplots_adjust(left=0.15, bottom=0.15, right=0.95, top=0.95, wspace=0., hspace=0.)
### define color cycle for plotting
pl.gca().set_color_cycle(['k','g','r','c','y','m','k','#FF8000','brown'])
### import data from file
theta,enc_int,enc_int_norm = np.loadtxt(os.path.join(datadir,infile),unpack=True,usecols=[0,1,2])
### plot enclosed intensity vs. angle
pl.plot(np.log10(theta), enc_int_norm, lw=3.0)
### add legend
legend = pl.legend(([r"$%.2f$"%plaw_exp]),frameon=False,loc='upper left',handlelength=1.5,title="$\mathrm{power}$-$\mathrm{law}$ \n $\mathrm{exponent}$")
pl.setp(legend.get_title(),fontsize='xx-small')
### add line marking enclosed intensity at theta = 1 deg
pl.axvline(np.log10(1.),color='k',linestyle='--',lw=1.5)
### minor ticks
xminticks = MultipleLocator(0.1)
yminticks = MultipleLocator(0.05)
pl.gca().xaxis.set_minor_locator(xminticks)
pl.gca().yaxis.set_minor_locator(yminticks)
pl.xlim([-2.,2.])
pl.xlabel(r'$\mathrm{log}(\theta) \ [\mathrm{deg}]$')
pl.ylabel(r'$\mathrm{Normalized \ Enclosed \ Intensity}$')
#pl.title(r'$\mathrm{%i \ Layer \ Luneburg \ Lens}$'%layers[i])
print ""
print ">>> Saving enclosed intensity plot to "+os.path.join(savedir,figoutfile)
print ""
pl.savefig(os.path.join(savedir,figoutfile))
pl.show()
pl.close()
|
masoncarneyREPO_NAMEstepped_luneburgPATH_START.@stepped_luneburg_extracted@stepped_luneburg-master@paper@fig7@plot_fig7.py@.PATH_END.py
|
{
"filename": "core.py",
"repo_name": "gammapy/gammapy",
"repo_path": "gammapy_extracted/gammapy-main/gammapy/makers/core.py",
"type": "Python"
}
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import abc
import html
import numpy as np
__all__ = ["Maker"]
class Maker(abc.ABC):
"""Abstract maker base class."""
@property
@abc.abstractmethod
def tag(self):
pass
@abc.abstractmethod
def run(self):
pass
def __str__(self):
s = f"{self.__class__.__name__}\n"
s += "-" * (len(s) - 1) + "\n\n"
names = self.__init__.__code__.co_varnames
max_len = np.max([len(_) for _ in names]) + 1
for name in names:
value = getattr(self, name, None)
if value is None:
continue
else:
s += f"\t{name:{max_len}s}: {value}\n"
return s.expandtabs(tabsize=2)
def _repr_html_(self):
try:
return self.to_html()
except AttributeError:
return f"<pre>{html.escape(str(self))}</pre>"
|
gammapyREPO_NAMEgammapyPATH_START.@gammapy_extracted@gammapy-main@gammapy@makers@core.py@.PATH_END.py
|
{
"filename": "fred.py",
"repo_name": "dentalfloss1/RaTS",
"repo_path": "RaTS_extracted/RaTS-master/RaTS/fred.py",
"type": "Python"
}
|
import numpy as np
class fred:
"""fred lightcurve class"""
def __init__(self):
self.edges=[1,0] # 1 is a definite edge, tophat is the default and has a definite beginning and end. Therefore it is [1,1]
def earliest_crit_time(self, start_survey, tau):
return start_survey - tau
def latest_crit_time(self, end_survey, tau):
return end_survey
def fluxint(self, F0, tcrit, tau, end_obs, start_obs):
"""Return the integrated flux"""
tstart = np.maximum(tcrit, start_obs) - tcrit
tend = end_obs - tcrit # Burst is never really "Off" so, how long is it on? It's on from tcrit until the end of the universe.
exp1 = -np.divide(tstart,tau)
exp1res = np.nan_to_num(np.exp(exp1))
exp2 = -np.divide(tend,tau)
exp2res = np.nan_to_num(np.exp(exp2))
return np.multiply(F0, np.multiply(tau, np.divide(exp1res - exp2res, (end_obs-start_obs))))
def lines(self, xs, ys, durmax, max_distance, flux_err, obs):
gaps = np.zeros(len(obs)-1,dtype=np.float32)
for i in range(len(obs)-1):
gaps[i] = obs['start'][i+1] - obs['start'][i] + obs['duration'][i]
# gaps = np.append(gaps, obs[i+1,0] - obs[i,0])
min_sens = min(obs['sens'])
max_sens = max(obs['sens'])
sens_last = obs['sens'][-1]
sens_maxgap = obs['sens'][np.where((gaps[:] == max(gaps)))[0]+1][0]
durmax_y = np.zeros(xs.shape,dtype=np.float64)
maxdist_y = np.zeros(xs.shape,dtype=np.float64)
lastdayobs = obs['duration'][-1]
duration_maxgap = obs['duration'][np.where((gaps[:] == max(gaps)))[0]+1][0]
for i in range(len(xs)):
x = xs[i]
try:
durmax_y[i] = (1. + flux_err) * sens_last * lastdayobs / np.power(10,x) / (np.exp(-(durmax - lastdayobs ) / np.power(10,x)) - np.exp(-((durmax) / np.power(10,x))))
except:
durmax_y[i] = np.inf
try:
maxdist_y[i] = (((1. + flux_err) * sens_maxgap * duration_maxgap) / np.power(10,x)) / (np.exp(-(max_distance / np.power(10,x))) - np.exp(-(max_distance + duration_maxgap) / np.power(10,x)))
except:
maxdist_y[i] = np.inf
durmax_x = ' '
maxdist_x = ' '
durmax_y_indices = np.where((durmax_y < np.amax(10**ys)) & (durmax_y > np.amin(10**ys)))[0]
maxdist_y_indices = np.where((maxdist_y < np.amax(10**ys)) & (maxdist_y > np.amin(10**ys)))[0]
return durmax_x, maxdist_x, durmax_y, maxdist_y, durmax_y_indices, maxdist_y_indices
|
dentalfloss1REPO_NAMERaTSPATH_START.@RaTS_extracted@RaTS-master@RaTS@fred.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "tensorflow/tensorflow",
"repo_path": "tensorflow_extracted/tensorflow-master/tensorflow/python/client/__init__.py",
"type": "Python"
}
|
tensorflowREPO_NAMEtensorflowPATH_START.@tensorflow_extracted@tensorflow-master@tensorflow@python@client@__init__.py@.PATH_END.py
|
|
{
"filename": "b1.py",
"repo_name": "nickhand/pyRSD",
"repo_path": "pyRSD_extracted/pyRSD-master/pyRSD/rsd/power/qso/derivatives/b1.py",
"type": "Python"
}
|
from . import PqsoDerivative
from pyRSD.rsd.tools import k_AP, mu_AP
class dPqso_db1(PqsoDerivative):
"""
The partial derivative of :func:`QuasarSpectrum.power` with respect to
``b1``
"""
param = 'b1'
@staticmethod
def eval(m, pars, k, mu):
kprime = k_AP(k, mu, m.alpha_perp, m.alpha_par)
muprime = mu_AP(mu, m.alpha_perp, m.alpha_par)
# derivative of scale-dependent bias term
dbtot_db1 = 1 + 2*m.f_nl*m.delta_crit/m.alpha_png(kprime)
# finger-of-god
G = m.FOG(kprime, muprime, m.sigma_fog)
# the final derivative
btot = m.btot(kprime)
rescaling = (m.alpha_drag**3) / (m.alpha_perp**2 * m.alpha_par)
return rescaling * G**2 * (2*m.P_mu0(kprime) + muprime**2 * m.P_mu2(kprime)) * dbtot_db1 / btot
|
nickhandREPO_NAMEpyRSDPATH_START.@pyRSD_extracted@pyRSD-master@pyRSD@rsd@power@qso@derivatives@b1.py@.PATH_END.py
|
{
"filename": "test_aggregator_tracer.py",
"repo_name": "Jammy2211/PyAutoLens",
"repo_path": "PyAutoLens_extracted/PyAutoLens-main/test_autolens/aggregator/test_aggregator_tracer.py",
"type": "Python"
}
|
import autolens as al
from test_autolens.aggregator.conftest import clean, aggregator_from
database_file = "db_tracer"
def test__tracer_randomly_drawn_via_pdf_gen_from(
masked_imaging_7x7,
samples,
model,
):
analysis = al.AnalysisImaging(dataset=masked_imaging_7x7)
agg = aggregator_from(
database_file=database_file,
analysis=analysis,
model=model,
samples=samples,
)
tracer_agg = al.agg.TracerAgg(aggregator=agg)
tracer_pdf_gen = tracer_agg.randomly_drawn_via_pdf_gen_from(total_samples=2)
i = 0
for tracer_gen in tracer_pdf_gen:
for tracer_list in tracer_gen:
i += 1
assert tracer_list[0].galaxies[0].redshift == 0.5
assert tracer_list[0].galaxies[0].light.centre == (10.0, 10.0)
assert tracer_list[0].galaxies[1].redshift == 1.0
assert i == 2
clean(database_file=database_file)
def test__tracer_all_above_weight_gen(analysis_imaging_7x7, samples, model):
agg = aggregator_from(
database_file=database_file,
analysis=analysis_imaging_7x7,
model=model,
samples=samples,
)
tracer_agg = al.agg.TracerAgg(aggregator=agg)
tracer_pdf_gen = tracer_agg.all_above_weight_gen_from(minimum_weight=-1.0)
weight_pdf_gen = tracer_agg.weights_above_gen_from(minimum_weight=-1.0)
i = 0
for tracer_gen, weight_gen in zip(tracer_pdf_gen, weight_pdf_gen):
for tracer_list in tracer_gen:
i += 1
if i == 1:
assert tracer_list[0].galaxies[0].redshift == 0.5
assert tracer_list[0].galaxies[0].light.centre == (1.0, 1.0)
assert tracer_list[0].galaxies[1].redshift == 1.0
if i == 2:
assert tracer_list[0].galaxies[0].redshift == 0.5
assert tracer_list[0].galaxies[0].light.centre == (10.0, 10.0)
assert tracer_list[0].galaxies[1].redshift == 1.0
for weight in weight_gen:
if i == 0:
assert weight == 0.0
if i == 1:
assert weight == 1.0
assert i == 2
clean(database_file=database_file)
|
Jammy2211REPO_NAMEPyAutoLensPATH_START.@PyAutoLens_extracted@PyAutoLens-main@test_autolens@aggregator@test_aggregator_tracer.py@.PATH_END.py
|
{
"filename": "spacy_embeddings.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/langchain/langchain/embeddings/spacy_embeddings.py",
"type": "Python"
}
|
from typing import TYPE_CHECKING, Any
from langchain._api import create_importer
if TYPE_CHECKING:
from langchain_community.embeddings import SpacyEmbeddings
# Create a way to dynamically look up deprecated imports.
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {"SpacyEmbeddings": "langchain_community.embeddings"}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
def __getattr__(name: str) -> Any:
"""Look up attributes dynamically."""
return _import_attribute(name)
__all__ = [
"SpacyEmbeddings",
]
|
langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@langchain@langchain@embeddings@spacy_embeddings.py@.PATH_END.py
|
{
"filename": "_transpose.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/heatmap/_transpose.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class TransposeValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(self, plotly_name="transpose", parent_name="heatmap", **kwargs):
super(TransposeValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
role=kwargs.pop("role", "info"),
**kwargs
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@heatmap@_transpose.py@.PATH_END.py
|
{
"filename": "prepare_from_db.py",
"repo_name": "minzastro/unidam",
"repo_path": "unidam_extracted/unidam-master/unidam/tools/prepare_from_db.py",
"type": "Python"
}
|
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Sep 17 13:31:04 2018
@author: mints
"""
from sqlconnection import SQLConnection
conn = SQLConnection('convert', database='sage_gap')
for row in conn.exec_dict('select * from catalogs', return_all=True):
#keep = []
#for key in ['id', 'ra', 'de', 'l', 'b',
# 't', 'logg', 'feh',
# 'dt', 'dlogg', 'dfeh']:
# #if row[key] is not None:
# # keep.append("'" + row[key] + "'")
data = f"""keep=
[mapping]
# Mapping of columns. Columns will be renamed according to
# this mapping.
id={row['id']}
T={row['t']}
logg={row['logg']}
feh={row['feh']}
# uncertainties columns. If the format is !value
# than value is taken as an uncertainty.
dT={row['dt']}
dlogg={row['dlogg']}
dfeh={row['dfeh']}
[galactic]
longitude={row['l']}
lattitude={row['b']}"""
with open(f'{row["name"]}.conf', 'w') as file:
file.write(data)
print(row['name'])
|
minzastroREPO_NAMEunidamPATH_START.@unidam_extracted@unidam-master@unidam@tools@prepare_from_db.py@.PATH_END.py
|
{
"filename": "PathOption.py",
"repo_name": "rat-pac/rat-pac",
"repo_path": "rat-pac_extracted/rat-pac-master/python/SCons/Options/PathOption.py",
"type": "Python"
}
|
#
# Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009 The SCons Foundation
#
# 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.
#
__revision__ = "src/engine/SCons/Options/PathOption.py 4043 2009/02/23 09:06:45 scons"
__doc__ = """Place-holder for the old SCons.Options module hierarchy
This is for backwards compatibility. The new equivalent is the Variables/
class hierarchy. These will have deprecation warnings added (some day),
and will then be removed entirely (some day).
"""
import SCons.Variables
import SCons.Warnings
warned = False
class _PathOptionClass:
def warn(self):
global warned
if not warned:
msg = "The PathOption() function is deprecated; use the PathVariable() function instead."
SCons.Warnings.warn(SCons.Warnings.DeprecatedOptionsWarning, msg)
warned = True
def __call__(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable, args, kw)
def PathAccept(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable.PathAccept, args, kw)
def PathIsDir(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable.PathIsDir, args, kw)
def PathIsDirCreate(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable.PathIsDirCreate, args, kw)
def PathIsFile(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable.PathIsFile, args, kw)
def PathExists(self, *args, **kw):
self.warn()
return apply(SCons.Variables.PathVariable.PathExists, args, kw)
PathOption = _PathOptionClass()
# Local Variables:
# tab-width:4
# indent-tabs-mode:nil
# End:
# vim: set expandtab tabstop=4 shiftwidth=4:
|
rat-pacREPO_NAMErat-pacPATH_START.@rat-pac_extracted@rat-pac-master@python@SCons@Options@PathOption.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "mhammond/pywin32",
"repo_path": "pywin32_extracted/pywin32-main/adodbapi/__init__.py",
"type": "Python"
}
|
# nopycln: file # undecidable cases due to explicit re-exports https://github.com/hadialqattan/pycln/issues/205
"""adodbapi - A python DB API 2.0 (PEP 249) interface to Microsoft ADO
Copyright (C) 2002 Henrik Ekelund, version 2.1 by Vernon Cole
* http://sourceforge.net/projects/adodbapi
"""
import time
# Re-exports to keep backward compatibility with existing code
from .adodbapi import (
Connection as Connection,
Cursor as Cursor,
__version__,
connect as connect,
dateconverter,
)
from .apibase import (
BINARY as BINARY,
DATETIME as DATETIME,
NUMBER as NUMBER,
ROWID as ROWID,
STRING as STRING,
DatabaseError as DatabaseError,
DataError as DataError,
Error as Error,
FetchFailedError as FetchFailedError,
IntegrityError as IntegrityError,
InterfaceError as InterfaceError,
InternalError as InternalError,
NotSupportedError as NotSupportedError,
OperationalError as OperationalError,
ProgrammingError as ProgrammingError,
Warning as Warning,
apilevel as apilevel,
paramstyle as paramstyle,
threadsafety as threadsafety,
)
def Binary(aString):
"""This function constructs an object capable of holding a binary (long) string value."""
return bytes(aString)
def Date(year, month, day):
"This function constructs an object holding a date value."
return dateconverter.Date(year, month, day)
def Time(hour, minute, second):
"This function constructs an object holding a time value."
return dateconverter.Time(hour, minute, second)
def Timestamp(year, month, day, hour, minute, second):
"This function constructs an object holding a time stamp value."
return dateconverter.Timestamp(year, month, day, hour, minute, second)
def DateFromTicks(ticks):
"""This function constructs an object holding a date value from the given ticks value
(number of seconds since the epoch; see the documentation of the standard Python time module for details).
"""
return Date(*time.gmtime(ticks)[:3])
def TimeFromTicks(ticks):
"""This function constructs an object holding a time value from the given ticks value
(number of seconds since the epoch; see the documentation of the standard Python time module for details).
"""
return Time(*time.gmtime(ticks)[3:6])
def TimestampFromTicks(ticks):
"""This function constructs an object holding a time stamp value from the given
ticks value (number of seconds since the epoch;
see the documentation of the standard Python time module for details)."""
return Timestamp(*time.gmtime(ticks)[:6])
version = "adodbapi v" + __version__
|
mhammondREPO_NAMEpywin32PATH_START.@pywin32_extracted@pywin32-main@adodbapi@__init__.py@.PATH_END.py
|
{
"filename": "testPolygon.py",
"repo_name": "LLNL/spheral",
"repo_path": "spheral_extracted/spheral-main/tests/unit/Geometry/testPolygon.py",
"type": "Python"
}
|
#ATS:test(SELF, label="Polygon unit tests")
# Unit tests for the Polygon class
import unittest
import functools
from math import *
from SpheralTestUtilities import fuzzyEqual
from Spheral2d import *
# Create a global random number generator.
import random
random.seed(402)
rangen = random.Random()
plots = []
#===============================================================================
# Generate random points in the give box, optionally rotating the results to
# create a non-axis aligned distribution.
#===============================================================================
def randomPoints(numPoints,
xmin, xmax,
ymin, ymax,
theta = None):
result = vector_of_Vector()
# Determine the rotational transform.
if theta is None:
theta = rangen.uniform(0.0, 2.0*pi)
R = rotationMatrix(Vector(cos(theta), sin(theta)))
for i in range(numPoints):
result.append(R*Vector(rangen.uniform(xmin, xmax),
rangen.uniform(ymin, ymax)))
return R, result
#===============================================================================
# A local class for sorting points in a counter-clockwise fashion around a
# point.
#===============================================================================
class SortCounterClockwise:
def __init__(self, p0):
self.p0 = p0
return
def __call__(self, p1, p2):
t = (p1 - self.p0).cross(p2 - self.p0).z
if t > 0.0:
return 1
elif t < 0.0:
return -1
else:
return 0
#===============================================================================
# Test class
#===============================================================================
class TestPolygon(unittest.TestCase):
#---------------------------------------------------------------------------
# setUp
#---------------------------------------------------------------------------
def setUp(self):
self.ntests = 5000
self.npoints = 1000
self.xmin, self.xmax = -5.0, 2.0
self.ymin, self.ymax = -1.0, 3.0
self.R, self.points = randomPoints(self.npoints,
self.xmin, self.xmax,
self.ymin, self.ymax)
self.polygon = Polygon(self.points)
#self.plot = append(plotPolygon(self.polygon, False, True))
return
#---------------------------------------------------------------------------
# Find the inner & outer radii of the polygon.
#---------------------------------------------------------------------------
def innerOuterRadii(self, polygon):
rinner = 1e10
router = 0.0
centroid = polygon.centroid
for f in self.polygon.facets:
r = abs((f.point1 - centroid).dot(f.normal))
rinner = min(rinner, r)
for v in polygon.vertices:
r = (v - centroid).magnitude()
router = max(router, r)
router *= 1.0 + 1.0e-5
return rinner, router
#---------------------------------------------------------------------------
# Check that all the seed points are contained in the polygon.
#---------------------------------------------------------------------------
def testContainSeeds(self):
for p in self.points:
self.assertTrue(self.polygon.contains(p),
"Polygon does not contain seed point: %s" % str(p))
return
#---------------------------------------------------------------------------
# Check that all the seed points are contained in the polygon using generic
# contain method.
#---------------------------------------------------------------------------
def testGenericContainSeeds(self):
for p in self.points:
self.assertTrue(pointInPolygon(p, self.polygon, True),
"Polygon does not contain seed point: %s" % str(p))
return
#---------------------------------------------------------------------------
# Generate random points in the polygon and test they are contained.
#---------------------------------------------------------------------------
def testRandomInnerPoints(self):
rinner, router = self.innerOuterRadii(self.polygon)
centroid = self.polygon.centroid
for i in range(self.ntests):
theta = rangen.uniform(0.0, 2.0*pi)
p = centroid + rangen.uniform(0.0, rinner) * Vector(cos(theta), sin(theta))
self.assertTrue(self.polygon.contains(p),
"Polygon should contain %s but reports it does not." % str(p))
return
#---------------------------------------------------------------------------
# Generate random points outside the polygon and test they are not contained.
#---------------------------------------------------------------------------
def testRandomOuterPoints(self):
rinner, router = self.innerOuterRadii(self.polygon)
centroid = self.polygon.centroid
for i in range(self.ntests):
theta = rangen.uniform(0.0, 2.0*pi)
p = centroid + rangen.uniform(router, 2.0*router) * Vector(cos(theta), sin(theta))
self.assertTrue(not self.polygon.contains(p),
"%s should be outside polygon but polygon reports it is contained." % str(p))
return
#---------------------------------------------------------------------------
# Test vertex containment.
#---------------------------------------------------------------------------
def testVertexPointContainment(self):
vertices = self.polygon.vertices
for v in vertices:
self.assertTrue(self.polygon.contains(v),
"%s vertex position should be contained." % str(v))
self.assertTrue(not self.polygon.contains(v, False),
"%s vertex position should not be contained." % str(v))
return
#---------------------------------------------------------------------------
# Test that nested polygons intersect.
#---------------------------------------------------------------------------
def testIntersectInterior(self):
centroid = self.polygon.centroid
vertices = vector_of_Vector(self.polygon.vertices)
numVerts = len(vertices)
for i in range(numVerts):
vertices[i] = 0.5*(centroid + vertices[i])
assert self.polygon.contains(vertices[i])
polygon2 = Polygon(vertices)
self.assertTrue(self.polygon.intersect(polygon2),
"Failed to intersect with a contained polygon.")
self.assertTrue(polygon2.intersect(self.polygon),
"Failed to intersect when entirely contained within a polygon.")
return
#---------------------------------------------------------------------------
# Test that two polygons just touching intersect.
#---------------------------------------------------------------------------
def testIntersectTouchingPolygons(self):
xmin = self.polygon.xmin.x
vertices = vector_of_Vector(self.polygon.vertices)
numVerts = len(vertices)
for i in range(numVerts):
xv = vertices[i].x
vertices[i].x -= 2.0*(xv - xmin)
polygon2 = Polygon(vertices)
self.assertTrue(self.polygon.intersect(polygon2),
"Failed to intersect with polygon touching at a vertex")
self.assertTrue(polygon2.intersect(self.polygon),
"Failed to intersect with polygon touching at a vertex")
return
#---------------------------------------------------------------------------
# Test that two separate polygons do not intersect.
#---------------------------------------------------------------------------
def testNotIntersectPolygons(self):
xmin = self.polygon.xmin.x
xlength = self.polygon.xmax.x - self.polygon.xmin.x
vertices = vector_of_Vector(self.polygon.vertices)
numVerts = len(vertices)
for i in range(numVerts):
xv = vertices[i].x
vertices[i].x -= 2.0*(xv - xmin) + xlength
polygon2 = Polygon(vertices)
#plots.append(plotPolygon(self.polygon))
#plots.append(plotPolygon(polygon2))
self.assertTrue(not self.polygon.intersect(polygon2),
"Erroneously claiming polygons intersect : [[%g,%g], [%g,%g], [[%g,%g], [%g,%g]]" % (self.polygon.xmin.x,
self.polygon.xmax.x,
self.polygon.xmin.y,
self.polygon.xmax.y,
polygon2.xmin.x,
polygon2.xmax.x,
polygon2.xmin.y,
polygon2.xmax.y))
self.assertTrue(not polygon2.intersect(self.polygon),
"Erroneously claiming polygons intersect : [[%g,%g], [%g,%g], [[%g,%g], [%g,%g]]" % (self.polygon.xmin.x,
self.polygon.xmax.x,
self.polygon.xmin.y,
self.polygon.xmax.y,
polygon2.xmin.x,
polygon2.xmax.x,
polygon2.xmin.y,
polygon2.xmax.y))
return
#---------------------------------------------------------------------------
# Test that a nested box intersects.
#---------------------------------------------------------------------------
def testIntersectBoxInterior(self):
rinner, router = self.innerOuterRadii(self.polygon)
centroid = self.polygon.centroid
box = (centroid - 0.95*rinner*Vector.one,
centroid + 0.95*rinner*Vector.one)
self.assertTrue(self.polygon.intersect(box),
"Failed to intersect with a contained box.")
return
#---------------------------------------------------------------------------
# Test that a circumscribing box intersects.
#---------------------------------------------------------------------------
def testIntersectBoxExterior(self):
rinner, router = self.innerOuterRadii(self.polygon)
centroid = self.polygon.centroid
box = (centroid - 2.0*router*Vector.one,
centroid + 2.0*router*Vector.one)
self.assertTrue(self.polygon.intersect(box),
"Failed to intersect with a box we are in.")
return
#---------------------------------------------------------------------------
# Test that a box just touching a polygon intersects.
#---------------------------------------------------------------------------
def testIntersectTouchingBox(self):
xmin = self.polygon.xmin.x
vertex = None
for v in self.polygon.vertices:
if fuzzyEqual(v.x, xmin, 1.0e-10):
vertex = v
assert not vertex is None
box = (Vector(v.x - 2.0, v.y - 2.0), v)
self.assertTrue(self.polygon.intersect(box),
"Failed to intersect with a box touching on one side.")
#---------------------------------------------------------------------------
# Test that that we don't intersect a box outside the polygon.
#---------------------------------------------------------------------------
def testNotIntersectBox(self):
xmin, xmax = self.polygon.xmin, self.polygon.xmax
delta = xmax - xmin
box = (xmin - 2.0*delta, xmax - 2.0*delta)
self.assertTrue(not self.polygon.intersect(box),
"Erroneously intersect external box.")
#---------------------------------------------------------------------------
# Test reconstructing.
#---------------------------------------------------------------------------
def testReconstruct(self):
polygon2 = Polygon()
polygon2.reconstruct(self.polygon.vertices,
self.polygon.facetVertices)
self.assertTrue(polygon2 == self.polygon,
"Failed to properly reconstruct polygon from vertices and facets.")
return
#---------------------------------------------------------------------------
# Test volume
#---------------------------------------------------------------------------
def testVolume(self):
verts0 = self.polygon.vertices
c = self.polygon.centroid
cmpmethod = SortCounterClockwise(c)
keymethod = functools.cmp_to_key(cmpmethod)
verts = sorted(list(verts0), key=keymethod)
p0 = verts[0]
answer = 0.0
for i in range(2, len(verts)):
answer += (verts[i] - p0).cross(verts[i - 1] - p0).z
answer *= 0.5
vertstring = [str(x) for x in verts]
self.assertTrue(fuzzyEqual(self.polygon.volume, answer, 1.0e-10),
"Failed volume computation: %g != %g\n verts = %s" % (self.polygon.volume,
answer,
vertstring))
#---------------------------------------------------------------------------
# Closest point to vertices.
#---------------------------------------------------------------------------
def testClosestPointToVertices(self):
verts = self.polygon.vertices
for p in verts:
cp = self.polygon.closestPoint(p)
self.assertTrue(fuzzyEqual((cp - p).magnitude(), 0.0, 1.0e-10),
"Closest point to vertex %s : %s" % (p, cp))
#---------------------------------------------------------------------------
# Closest point on facets.
#---------------------------------------------------------------------------
def testClosestPointOnFacets(self):
facets = self.polygon.facets
for f in facets:
p = f.position
cp = self.polygon.closestPoint(p)
self.assertTrue(fuzzyEqual((cp - p).magnitude(), 0.0, 1.0e-10),
"Closest point to facet position %s : %s" % (p, cp))
#---------------------------------------------------------------------------
# Closest point above facets.
#---------------------------------------------------------------------------
def testClosestPointAboveFacets(self):
facets = self.polygon.facets
for f in facets:
chi = 0.0001
cp0 = f.position
p = cp0 + chi*f.normal
cp = self.polygon.closestPoint(p)
self.assertTrue(fuzzyEqual((cp0 - cp).magnitude(), 0.0, 1.0e-10),
"Closest point to position off of facet position %s : %s" % (cp0, cp))
#---------------------------------------------------------------------------
# Test ==
#---------------------------------------------------------------------------
def testEqual(self):
self.assertTrue(self.polygon == self.polygon,
"Failed self equivalence.")
#---------------------------------------------------------------------------
# Test !=
#---------------------------------------------------------------------------
def testNotEqual(self):
polygon2 = Polygon()
self.assertTrue(polygon2 != self.polygon,
"Failed not equal.")
#---------------------------------------------------------------------------
# Test copy constructor
#---------------------------------------------------------------------------
def testCopy(self):
polygon2 = Polygon(self.polygon)
self.assertTrue(polygon2 == self.polygon,
"Failed to copy construct.")
#---------------------------------------------------------------------------
# Test shift in-place
#---------------------------------------------------------------------------
def testShiftInPlace(self):
shift = Vector(rangen.uniform(-10.0, -10.0),
rangen.uniform(-10.0, -10.0))
polygon2 = Polygon(self.polygon)
polygon2 += shift
for p0, p1 in zip([self.polygon.xmin, self.polygon.xmax] + list(self.polygon.vertices),
[polygon2.xmin, polygon2.xmax] + list(polygon2.vertices)):
pshift = p0 + shift
self.assertTrue(pshift == p1, "In-place shift point comparison failed: %s != %s" % (pshift, p1))
if __name__ == "__main__":
unittest.main()
|
LLNLREPO_NAMEspheralPATH_START.@spheral_extracted@spheral-main@tests@unit@Geometry@testPolygon.py@.PATH_END.py
|
{
"filename": "demo_data_time_evo.py",
"repo_name": "eelregit/pmwd",
"repo_path": "pmwd_extracted/pmwd-master/docs/papers/adjoint/demo_data_time_evo.py",
"type": "Python"
}
|
import numpy as np
import jax.numpy as jnp
from tqdm.notebook import tqdm
import h5py
import jax
from pmwd import (
Configuration,
SimpleLCDM,
boltzmann,
white_noise, linear_modes,
lpt,
nbody,
scatter,
)
from pmwd.nbody import nbody_init, nbody_step
ptcl_spacing = 10.
ptcl_grid_shape = (16, 27, 16)
mesh_shape = (32, 54, 32)
conf = Configuration(ptcl_spacing, ptcl_grid_shape, mesh_shape=2,
a_nbody_maxstep=1/512)
a_nbody = conf.a_nbody
cosmo = SimpleLCDM(conf)
seed = 0
modes = white_noise(seed, conf)
cosmo = boltzmann(cosmo, conf)
modes = linear_modes(modes, cosmo, conf)
ptcl, obsvbl = lpt(modes, cosmo, conf)
f = h5py.File('data/time_evo.h5', 'w')
def save_snap(f, i, a, ptcl, conf, prefix):
pos = np.asarray(ptcl.pos())
dset = f.create_dataset(f'{prefix}_{i}', data=pos)
dset.attrs.create('a', a)
# forward simulation
ptcl, obsvbl = nbody_init(a_nbody[0], ptcl, obsvbl, cosmo, conf)
save_snap(f, 0, a_nbody[0], ptcl, conf, 'fw')
for i, (a_prev, a_next) in enumerate(tqdm(zip(a_nbody[:-1], a_nbody[1:]), total=len(a_nbody)-1)):
ptcl, obsvbl = nbody_step(a_prev, a_next, ptcl, obsvbl, cosmo, conf)
save_snap(f, i+1, a_next, ptcl, conf, 'fw')
# reverse simulation
a_nbody_r = a_nbody[::-1]
save_snap(f, 0, a_nbody_r[0], ptcl, conf, 're')
for i, (a_prev, a_next) in enumerate(tqdm(zip(a_nbody_r[:-1], a_nbody_r[1:]), total=len(a_nbody_r)-1)):
ptcl, obsvbl = nbody_step(a_prev, a_next, ptcl, obsvbl, cosmo, conf)
save_snap(f, i+1, a_next, ptcl, conf, 're')
f.close()
|
eelregitREPO_NAMEpmwdPATH_START.@pmwd_extracted@pmwd-master@docs@papers@adjoint@demo_data_time_evo.py@.PATH_END.py
|
{
"filename": "_ticks.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/layout/xaxis/minor/_ticks.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class TicksValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(self, plotly_name="ticks", parent_name="layout.xaxis.minor", **kwargs):
super(TicksValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "ticks"),
values=kwargs.pop("values", ["outside", "inside", ""]),
**kwargs,
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@layout@xaxis@minor@_ticks.py@.PATH_END.py
|
{
"filename": "imessage.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/langchain/langchain/chat_loaders/imessage.py",
"type": "Python"
}
|
from typing import TYPE_CHECKING, Any
from langchain._api import create_importer
if TYPE_CHECKING:
from langchain_community.chat_loaders.imessage import IMessageChatLoader
# Create a way to dynamically look up deprecated imports.
# Used to consolidate logic for raising deprecation warnings and
# handling optional imports.
DEPRECATED_LOOKUP = {"IMessageChatLoader": "langchain_community.chat_loaders.imessage"}
_import_attribute = create_importer(__package__, deprecated_lookups=DEPRECATED_LOOKUP)
def __getattr__(name: str) -> Any:
"""Look up attributes dynamically."""
return _import_attribute(name)
__all__ = [
"IMessageChatLoader",
]
|
langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@langchain@langchain@chat_loaders@imessage.py@.PATH_END.py
|
{
"filename": "test_sampler.py",
"repo_name": "minaskar/pocomc",
"repo_path": "pocomc_extracted/pocomc-main/tests/test_sampler.py",
"type": "Python"
}
|
import unittest
import numpy as np
from scipy.stats import norm
from pocomc.sampler import Sampler
from pocomc.prior import Prior
class SamplerTestCase(unittest.TestCase):
@staticmethod
def log_likelihood_single(x):
return np.sum(-0.5 * np.log(2 * np.pi) - 0.5 * x ** 2)
@staticmethod
def log_likelihood_vectorized(x):
# Gaussian log likelihood with mu = 0, sigma = 1
return np.sum(-0.5 * np.log(2 * np.pi) - 0.5 * x ** 2, axis=1)
def test_run(self):
n_dim = 2
prior = Prior(n_dim*[norm(0, 1)])
sampler = Sampler(
prior=prior,
likelihood=self.log_likelihood_single,
train_config={'epochs': 1},
random_state=0,
)
sampler.run()
def test_run2(self):
n_dim = 2
prior = Prior(n_dim*[norm(0, 1)])
sampler = Sampler(
prior=prior,
likelihood=self.log_likelihood_vectorized,
vectorize=True,
train_config={'epochs': 1},
random_state=0,
)
sampler.run()
if __name__ == '__main__':
unittest.main()
|
minaskarREPO_NAMEpocomcPATH_START.@pocomc_extracted@pocomc-main@tests@test_sampler.py@.PATH_END.py
|
{
"filename": "target.py",
"repo_name": "ashleychontos/pySYD",
"repo_path": "pySYD_extracted/pySYD-master/dev/target.py",
"type": "Python"
}
|
import os
import glob
import numpy as np
import pandas as pd
from astropy.stats import mad_std
from scipy.optimize import curve_fit
from astropy.timeseries import LombScargle as lomb
from scipy.interpolate import InterpolatedUnivariateSpline
from astropy.convolution import Box1DKernel, Gaussian1DKernel, convolve, convolve_fft
import utils
import plots
import models
class LightCurve(object):
"""Light curve data
"""
def __init__(self):
"""
"""
for each in ['notes', 'warnings', 'errors']:
if not hasattr(self, each):
self.__setattr__(each, [])
def __repr__(self):
return "pysyd.target.LightCurve(name=%r)" % (self.name, os.path.exists(os.path.join(self.inpdir, '%s_LC.txt' % str(self.name))))
def __str__(self):
return "<%s LC>" % str(self.name)
def load_data(self, long=10**6):
"""Load LC
"""
# Try loading the light curve
if os.path.exists(os.path.join(self.inpdir, '%s_LC.txt' % str(self.name))):
self.time, self.flux = self.read_file(os.path.join(self.inpdir, '%s_LC.txt' % str(self.name)))
self.time -= min(self.time)
self.notes.append('LIGHT CURVE (LC): %d lines of data read' % len(self.time))
if len(self.time) >= long:
self.warnings.append('LC is long and may slow down the software')
self.cadence = int(round(np.nanmedian(np.diff(self.time)*24.0*60.0*60.0),0))
self.nyquist = 10**6./(2.0*self.cadence)
self.baseline = (max(self.time)-min(self.time))*24.*60.*60.
self.tau_upper = self.baseline/2.
self.notes.append('LC cadence: %d seconds' % self.cadence)
self.stitch_data()
else:
self.warnings.append('no time series data found')
def stitch_data(self, stitch=False, gap=20):
"""Stitch light curve
For computation purposes and for special cases that this does not affect the integrity of the results,
this module 'stitches' a light curve together for time series data with large gaps. For stochastic p-mode
oscillations, this is justified if the lifetimes of the modes are smaller than the gap.
Parameters
gap : int
how many consecutive missing cadences to be considered a 'gap'
Attributes
time : numpy.ndarray
original time series array to correct
new_time : numpy.ndarray
the corrected time series array
Raises
:mod:`pysyd.utils.InputWarning`
when using this method since it's technically not a great thing to do
.. warning::
USE THIS WITH CAUTION. This is technically not a great thing to do for primarily
two reasons:
#. you lose phase information *and*
#. can be problematic if mode lifetimes are shorter than gaps (i.e. more evolved stars)
.. note::
temporary solution for handling very long gaps in TESS data -- still need to
figure out a better way to handle this
"""
if self.stitch and hasattr(self, 'time'):
self.new_time = np.copy(self.time)
for i in range(1,len(self.time)):
if (self.new_time[i]-self.new_time[i-1]) > float(self.gap)*(self.cadence/24./60./60.):
self.new_time[i] = self.new_time[i-1]+(self.cadence/24./60./60.)
self.time = np.copy(self.new_time)
self.warnings.append('using stitch data module (which is dodgy and strongly discouraged)')
def compute_spectrum(self, oversampling_factor=1, long=10**6):
r"""Compute power spectrum
**NEW** function to calculate a power spectrum given time series data, which will
normalize the power spectrum to spectral density according to Parseval's theorem
Parameters
oversampling_factor : int
the oversampling factor to use when computing the power spectrum
Attributes
frequency, power : numpy.ndarray, numpy.ndarray
power spectrum computed from the 'time' and 'flux' attributes
using the :mod:`astropy.timeseries.LombScargle` module
.. important::
the newly-computed and normalized power spectrum is in units of :math:`\\rm \\mu Hz`
vs. :math:`\\rm ppm^{2} \\mu Hz^{-1}`. IF you are unsure if your power spectrum is in
the correct units, we recommend using this new module to compute and normalize the PS
for you -- this will ensure accurate results.
.. todo::
add equation for conversion
add in unit conversions
"""
freq, pow = lomb(self.time, self.flux).autopower(method='fast', samples_per_peak=self.oversampling_factor, maximum_frequency=self.nyquist)
# normalize PS according to Parseval's theorem
self.power = 4.*pow*np.var(self.flux*1e6)/(np.sum(pow)*(freq[1]-freq[0]))
self.frequency = freq*(10.**6/(24.*60.*60.))
self.notes.append('NEWLY-COMPUTED PS has length of %d' % len(self.frequency))
if len(self.frequency) >= long:
self.warnings.append('PS is large and may slow down software')
class PowerSpectrum(object):
"""Power spectrum data
"""
def __init__(self):
"""
"""
for each in ['notes', 'warnings', 'errors']:
if not hasattr(self, each):
self.__setattr__(each, [])
def __repr__(self):
return "pysyd.target.PowerSpectrum(name=%r, PS=%r)" % (self.name, os.path.exists(os.path.join(self.params['inpdir'], '%s_PS.txt' % str(self.name))))
def __str__(self):
return "<%s PS>" % str(self.name)
def load_data(self, long=10**6):
r"""Load PS
Loads in available power spectrum and computes relevant information -- also checks
for time series data and will raise a warning if there is none since it will have
to assume a :term:`critically-sampled power spectrum`
Attributes
note : str, optional
verbose output
ps : bool
`True` if star ID has an available (or newly-computed) power spectrum
Raises
:mod:`pysyd.utils.InputWarning`
if no information or time series data is provided (i.e. *has* to assume the PS is critically-sampled)
"""
# Try loading the power spectrum
if os.path.exists(os.path.join(self.inpdir, '%s_PS.txt' % str(self.name))):
self.frequency, self.power = self.read_file(os.path.join(self.inpdir, '%s_PS.txt' % str(self.name)))
self.notes.append('POWER SPECTRUM (PS): %d lines of data read' % len(self.frequency))
if len(self.frequency) >= long:
self.warnings.append('PS is large and may slow down software')
self.fix_data()
else:
self.warnings.append('no power spectrum found')
def fix_data(self):
"""Fix frequency domain data
"""
self.remove_artefact()
self.whiten_mixed()
if self.kep_corr or self.ech_mask is not None:
self.warnings.append('modifying the PS with optional module(s)')
def _get_seed(self):
if self.seed is None:
if os.path.exists(self.info):
df = pd.read_csv(self.info)
stars = [str(each) for each in df.star.values.tolist()]
# check if star is in file and if not, adds it and the seed for reproducibility
if str(self.name) in stars and 'seed' in df.columns.values.tolist():
idx = stars.index(str(self.name))
if not np.isnan(float(df.loc[idx,'seed'])):
self.seed = int(df.loc[idx,'seed'])
# if still None, generate new seed
if self.seed is None:
self._new_seed()
if self.save:
self._save_seed()
def _new_seed(self, lower=1, upper=10**7):
"""Set seed
For *Kepler* targets that require a correction via CLI (--kc), a random seed is generated
from U~[1,10^7] and stored in stars_info.csv for reproducible results in later runs.
Parameters
lower : int, default=1
lower limit for random seed value
upper : int, default=:math:`10^{7}`
arbitrary upper limit for random seed value
.. important:: this is now implemented for every star for every run (no longer used
just for correcting)
"""
self.seed = int(np.random.randint(lower,high=upper))
def _save_seed(self):
"""Save seed
"""
if os.path.exists(self.info):
df = pd.read_csv(self.info)
stars = [str(each) for each in df.star.values.tolist()]
if str(self.name) in stars:
idx = stars.index(str(self.name))
df.loc[idx,'seed'] = int(self.seed)
else:
idx = len(df)
df.loc[idx,'star'], df.loc[idx,'seed'] = str(self.name), int(self.seed)
else:
df = pd.DataFrame(columns=['star','seed'])
df.loc[0,'star'], df.loc[0,'seed'] = str(self.name), int(self.seed)
df.to_csv(self.info, index=False)
def remove_artefact(self, kep_corr=False, lcp=1.0/(29.4244*60*1e-6),
lf_lower=[240.0,500.0], lf_upper=[380.0,530.0],
hf_lower = [4530.0,5011.0,5097.0,5575.0,7020.0,7440.0,7864.0],
hf_upper = [4534.0,5020.0,5099.0,5585.0,7030.0,7450.0,7867.0],):
"""Remove Kepler (frequency-domain) artefacts
"""
if self.kep_corr and hasattr(self, 'frequency'):
resolution = self.frequency[1]-self.frequency[0]
if self.seed is None:
self._get_seed()
# LC period in Msec -> 1/LC ~muHz
artefact = (1.0+np.arange(14))*lcp
# Estimate white noise
white = np.mean(self.power[(self.frequency >= max(self.frequency)-100.0)&(self.frequency <= max(self.frequency)-50.0)])
# Routine 1: remove 1/LC artefacts by subtracting +/- 5 muHz given each artefact
np.random.seed(int(self.seed))
for i in range(len(artefact)):
if artefact[i] < np.max(self.frequency):
mask = np.ma.getmask(np.ma.masked_inside(self.frequency, artefact[i]-5.0*resolution, artefact[i]+5.0*resolution))
if np.sum(mask) != 0:
self.power[mask] = white*np.random.chisquare(2,np.sum(mask))/2.0
# Routine 2: fix high frequency artefacts
np.random.seed(int(self.seed))
for lower, upper in zip(hf_lower, hf_upper):
if lower < np.max(self.frequency):
mask = np.ma.getmask(np.ma.masked_inside(self.frequency, lower, upper))
if np.sum(mask) != 0:
self.power[mask] = white*np.random.chisquare(2,np.sum(mask))/2.0
# Routine 3: remove wider, low frequency artefacts
np.random.seed(int(self.seed))
for lower, upper in zip(lf_lower, lf_upper):
low = np.ma.getmask(np.ma.masked_outside(self.frequency, lower-20., lower))
upp = np.ma.getmask(np.ma.masked_outside(self.frequency, upper, upper+20.))
# Coeffs for linear fit
m, b = np.polyfit(self.frequency[~(low*upp)], self.power[~(low*upp)], 1)
mask = np.ma.getmask(np.ma.masked_inside(self.frequency, lower, upper))
# Fill artefact frequencies with noise
self.power[mask] = ((self.frequency[mask]*m)+b)*(np.random.chisquare(2, np.sum(mask))/2.0)
def whiten_mixed(self, ech_mask=None, dnu=None, lower_ech=None, upper_ech=None, notching=False,):
"""Whiten mixed modes
"""
if self.ech_mask is not None and hasattr(self, 'frequency'):
if self.seed is None:
self._get_seed()
# Estimate white noise
if not self.notching:
white = np.mean(self.power[(self.frequency >= max(self.frequency)-100.0)&(self.frequency <= max(self.frequency)-50.0)])
else:
white = min(self.power[(self.frequency >= max(self.frequency)-100.0)&(self.frequency <= max(self.frequency)-50.0)])
# Take the provided dnu and "fold" the power spectrum
mask = np.ma.getmask(np.ma.masked_inside((self.frequency%self.dnu), self.ech_mask[0], self.ech_mask[1]))
# Set seed for reproducibility purposes
np.random.seed(int(self.seed))
# Makes sure the mask is not empty
if np.sum(mask) != 0:
if self.notching:
self.power[mask] = white
else:
self.power[mask] = white*np.random.chisquare(2,np.sum(mask))/2.0
class Target(LightCurve, PowerSpectrum):
r"""Target object
A new instance is created for each processed star, which copies relevant (and
individualistic aka fully customizable) dictonaries and parameters. This used to
automatically load in available data too but this is now called separately with
the upgraded LightCurve and PowerSpectrum classes
"""
def __init__(self, name, args=None, width=65):
r"""pySYD target
Parameters
name : str
which target of interest to run
args : :mod:`pysyd.utils.Parameters`
container class of pysyd parameters
Attributes
notes : List[str]
if verbose is `True`, this saves information about the input data
warnings : List[str]
akin to the notes list, this saves all warnings related to loading in of
data, which will only raise a :mod:`pysyd.utils.InputWarning` iff verbose
and warnings are both `True`
errors : List[str]
similar to 'notes' and 'warnings' except that these are dealbreakers --
this will raise a :mod:`pysyd.utils.InputError` any time this isn't empty
params : Dict
copy of :mod:`pysyd.utils.Parameters` dictionary with target-specific
parameters and options
constants : Dict
copy of :mod:`pysyd.utils.Constants` container class
"""
self.name, self.width = name, width
for label in ['notes', 'warnings', 'errors']:
if not hasattr(self, label):
self.__setattr__(label, [])
if args is None:
params = utils.Parameters()
params.add_targets(stars=name)
else:
params = utils.Parameters(args)
for key, value in params.__dict__[self.name].items():
self.__dict__[key] = value
self.load_input()
def __repr__(self):
return "pysyd.target.Target(name=%r, LC=%r, PS=%r)" % (self.name, os.path.exists(os.path.join(self.inpdir, '%s_LC.txt' % str(self.name))), os.path.exists(os.path.join(self.inpdir, '%s_PS.txt' % str(self.name))))
def __str__(self):
return "<Star %s>" % (self.name)
def load_input(self):
r"""Load input data
Load data in for a single star by initiating both the LightCurve and
PowerSpectrum objects (via their 'load_data' methods - it has to be this
way otherwise init will create everything twice - still not sure how to
fix this -- there's probably a better way)
Methods
:mod:`pysyd.target.LightCurve.load_data`
:mod:`pysyd.target.PowerSpectrum.load_data`
:mod:`pysyd.target.Target.get_properties`
"""
line = ' TARGET: %s ' % str(self.name)
for msg in ['*'*self.width, line.center(self.width, '*'), '*'*self.width]:
self.notes.append(msg)
LightCurve.load_data(self)
print(self.__dict__)
PowerSpectrum.load_data(self)
print(self.__dict__)
self.get_properties()
print(self.__dict__)
def get_properties(self):
r"""Get data properties
After loading in available data, it determines what methods need to be called
or what needs to be corrected in order for the pipeline to run. For example,
after trying to load in the light curve and power spectrum, it will compute a
new power spectrum if there isn't one already.
Methods
:mod:`pysyd.target.LightCurve.compute_spectrum`
:mod:`pysyd.utils._save_file`
:mod:`pysyd.target.PowerSpectrum.fix_data`
Attributes
frequency, power : numpy.ndarray, numpy.ndarray
input power spectrum
freq_os, pow_os : numpy.ndarray, numpy.ndarray
copy of the oversampled power spectrum (i.e. `frequency` & `power`)
freq_cs, pow_cs : numpy.ndarray, numpy.ndarray
copy of the critically-sampled power spectrum (i.e. `frequency` & `power`)
iff the :term:`oversampling_factor<--of, --over, --oversample>` is provided,
otherwise these arrays are just copies of `freq_os` & `pow_os` since this factor
isn't known and needs to be assumed
Raises
:mod:`pysyd.utils.InputError`
if no data is found for a given target
:mod:`pysyd.utils.InputWarning`, optional
if warnings are turned on, it will raise whatever warnings popped up
"""
# CASE 1: LIGHT CURVE AND POWER SPECTRUM
if hasattr(self, 'time') and hasattr(self, 'frequency'):
ofactor = (1./((max(self.time)-min(self.time))*0.0864))/(self.frequency[1]-self.frequency[0])
if self.oversampling_factor is not None and ofactor != self.oversampling_factor:
self.warnings.append('the input ofactor (=%d) and calculated value (=%d) do NOT match' % (int(self.oversampling_factor), int(ofactor)))
else:
if not float(ofactor).is_integer():
self.errors.append('calculated an ofactor=%.1f but MUST be int type for array indexing' % float(ofactor))
self.oversampling_factor = int(float('%.0f' % ofactor))
# CASE 2: LIGHT CURVE AND NO POWER SPECTRUM
elif hasattr(self, 'time') and not hasattr(self, 'frequency'):
if self.oversampling_factor is None:
self.oversampling_factor = 1
LightCurve.compute_spectrum(self)
if self.save:
self.save_file(self.frequency, self.power, os.path.join(self.inpdir, '%s_PS.txt'%self.name), overwrite=self.overwrite)
PowerSpectrum.fix_data(self)
# CASE 3: NO LIGHT CURVE AND POWER SPECTRUM
elif not hasattr(self, 'time') and hasattr(self, 'frequency'):
if self.oversampling_factor is None:
self.warnings.append('using PS with no additional information (e.g., assuming critically-sampled)')
if self.mc_iter > 1:
self.warnings.append('uncertainties may not be reliable if PS is not critically-sampled')
self.oversampling_factor = 1
# CASE 4: NO LIGHT CURVE AND NO POWER SPECTRUM
else:
self.errors.append('no data found for target %s' % str(self.name))
errors, message = self.get_errors()
if errors:
print(message)
return
self.freq_os, self.pow_os = np.copy(self.frequency), np.copy(self.power)
self.freq_cs = np.array(self.frequency[self.oversampling_factor-1::self.oversampling_factor])
self.pow_cs = np.array(self.power[self.oversampling_factor-1::self.oversampling_factor])
if self.oversampling_factor != 1:
self.notes.append('PS is oversampled by a factor of %d' % self.oversampling_factor)
else:
self.notes.append('PS is critically-sampled')
self.notes.append('PS resolution: %.6f muHz' % (self.freq_cs[1]-self.freq_cs[0]))
warnings, message = self.get_warnings()
if self.verbose:
if warnings:
print(message)
output = ''
for note in self.notes:
output += '\n%s' % note
print(output)
def read_file(self, path):
r"""Load text file
Load a light curve or a power spectrum from a basic 2xN txt file
and stores the data into the `x` (independent variable) and `y`
(dependent variable) arrays, where N is the length of the series
Parameters
path : str
the file path of the data file
Returns
x, y : numpy.ndarray, numpy.ndarray
the independent and dependent variables, respectively
"""
# Open file
with open(path, "r") as f:
lines = f.readlines()
# Set values
x = np.array([float(line.strip().split()[0]) for line in lines])
y = np.array([float(line.strip().split()[1]) for line in lines])
return x, y
def save_file(self, x, y, path, overwrite=False, formats=[">15.8f", ">18.10e"]):
r"""Save text file
After determining the best-fit stellar background model, this module
saved the background-subtracted power spectrum
Parameters
x : numpy.ndarray
the independent variable i.e. the time or frequency array
y : numpy.ndarray
the dependent variable, in this case either the flux or power array
path : str
absolute path to save file to
overwrite : bool, optional
whether to overwrite existing files or not
formats : List[str], optional
2x1 list of formats to save arrays as
"""
if os.path.exists(path) and not overwrite:
path = self._get_next(path)
with open(path, "w") as f:
for xx, yy in zip(x, y):
values = [xx, yy]
text = '{:{}}'*len(values) + '\n'
fmt = sum(zip(values, formats), ())
f.write(text.format(*fmt))
def _get_next(self, path, count=1):
"""Get next integer
When the overwriting of files is disabled, this module determines what
the last saved file was
Parameters
path : str
absolute path to file name that already exists
count : int
starting count, which is incremented by 1 until a new path is determined
Returns
new_path : str
unused path name
"""
path, fname = os.path.split(path)[0], os.path.split(path)[-1]
new_fname = '%s_%d.%s'%(fname.split('.')[0], count, fname.split('.')[-1])
new_path = os.path.join(path, new_fname)
if os.path.exists(new_path):
while os.path.exists(new_path):
count += 1
new_fname = '%s_%d.%s'%(fname.split('.')[0], count, fname.split('.')[-1])
new_path = os.path.join(path, new_fname)
return new_path
def get_errors(self, delim='#'):
r"""Return errors
Concatenates all the various flags/messages/warnings during the
load into a single string for easy readability
(defaults -> '#' for errors, '-' for warnings, and ' ' for notes)
Parameters
witch : str
which attribute to concatenate
delim : str
delimiter for pretty formatting
Returns
message : str
the final concatenated message
"""
if self.errors != []:
errors = "%s\n ERROR(S):" % delim*self.width
for message in self.__dict__['errors']:
errors += '\n - %s' % message
errors += "\n%s" % (delim*self.width)
return True, errors
return False, ''
def get_warnings(self, delim='-'):
r"""Return warnings
Concatenates all the various flags/messages/warnings during the
load into a single string for easy readability
(defaults -> '#' for errors, '-' for warnings, and ' ' for notes)
Parameters
witch : str
which attribute to concatenate
delim : str
delimiter for pretty formatting
Returns
message : str
the final concatenated message
"""
if self.warnings != []:
warnings = "%s\n WARNING(S):" % delim*self.width
for message in self.__dict__['warnings']:
warnings += '\n - %s' % message
warnings += "\n%s" % (delim*self.width)
return True, warnings
return False, ''
def get_notes(self, delim=' '):
r"""Return warnings
Concatenates all the various flags/messages/warnings during the
load into a single string for easy readability
(defaults -> '#' for errors, '-' for warnings, and ' ' for notes)
Parameters
witch : str
which attribute to concatenate
delim : str
delimiter for pretty formatting
Returns
message : str
the final concatenated message
"""
notes = "%s\n Note(s):" % delim*self.width
for message in self.__dict__['notes']:
notes += '\n - %s' % message
notes += "\n%s" % (delim*self.width)
return notes
def output_parameters(self, note=''):
"""Verbose output
Prints verbose output from the global fit
"""
params = utils.get_dict()
if not self.params['overwrite']:
list_of_files = glob.glob(os.path.join(star.params['path'], 'global*'))
file = max(list_of_files, key=os.path.getctime)
else:
file = os.path.join(star.params['path'], 'global.csv')
df = pd.read_csv(file)
note += '%s\nOutput parameters\n%s' % ('-'*self.width, '-'*self.width)
if star.params['mc_iter'] > 1:
line = '\n%s: %.2f +/- %.2f %s'
for idx in df.index.values.tolist():
note += line%(df.loc[idx,'parameter'], df.loc[idx,'value'], df.loc[idx,'uncertainty'], params[df.loc[idx,'parameter']]['unit'])
else:
line = '\n%s: %.2f %s'
for idx in df.index.values.tolist():
note += line%(df.loc[idx,'parameter'], df.loc[idx,'value'], params[df.loc[idx,'parameter']]['unit'])
note += '\n%s' % '-'*self.width
print(note)
def bin_data(x, y, width, log=False, mode='mean'):
"""Bin data
Bins 2D series of data
Parameters
x, y : numpy.ndarray, numpy.ndarray
the x and y values of the data
width : float
bin width (typically in :math:`\\rm \\mu Hz`)
log : bool
creates equal bin sizes in logarithmic space when `True`
Returns
bin_x, bin_y, bin_yerr : numpy.ndarray, numpy.ndarray, numpy.ndarray
binned arrays (and error is computed using the standard deviation)
"""
if log:
mi = np.log10(min(x))
ma = np.log10(max(x))
no = int(np.ceil((ma-mi)/width))
bins = np.logspace(mi, mi+(no+1)*width, no)
else:
bins = np.arange(min(x), max(x)+width, width)
digitized = np.digitize(x, bins)
if mode == 'mean':
bin_x = np.array([x[digitized == i].mean() for i in range(1, len(bins)) if len(x[digitized == i]) > 0])
bin_y = np.array([y[digitized == i].mean() for i in range(1, len(bins)) if len(x[digitized == i]) > 0])
elif mode == 'median':
bin_x = np.array([np.median(x[digitized == i]) for i in range(1, len(bins)) if len(x[digitized == i]) > 0])
bin_y = np.array([np.median(y[digitized == i]) for i in range(1, len(bins)) if len(x[digitized == i]) > 0])
else:
pass
bin_yerr = np.array([y[digitized == i].std()/np.sqrt(len(y[digitized == i])) for i in range(1, len(bins)) if len(x[digitized == i]) > 0])
return bin_x, bin_y, bin_yerr
def process_star(self,):
"""Run `pySYD`
Process a given star with the main `pySYD` pipeline
Methods
- :mod:`pysyd.target.Target.estimate_parameters`
- :mod:`pysyd.target.Target.derive_parameters`
- :mod:`pysyd.utils.show_results`
"""
self.params['results'], self.params['plotting'] = {}, {}
self.estimate_parameters()
self.derive_parameters()
utils.show_results(self)
##########################################################################################
def estimate_parameters(self, estimate=True, module='estimate'):
"""Estimate parameters
Calls all methods related to the first module
Parameters
estimate : bool, default=True
if numax is already known, this will automatically be skipped since it is not needed
Methods
- :mod:`pysyd.target.Target.initial_estimates`
- :mod:`pysyd.target.Target.estimate_numax`
- :mod:`pysyd.utils._save_estimates`
"""
self.module = 'estimate'
if 'results' not in self.params:
self.params['results'] = {}
if 'plotting' not in self.params:
self.params['plotting'] = {}
self.params['results'][self.module], self.params['plotting'][self.module] = {}, {}
if self.params['estimate']:
# get initial values and fix data
self.estimate_initial()
# execute function
self.estimate_values()
# save results
self.save_estimates()
def estimate_initial(self, lower_ex=1.0, upper_ex=8000.0, max_trials=6,):
"""Initial guesses
Prepares data and parameters associated with the first module that identifies
solar-like oscillations and estimates :term:`numax`
Parameters
lower_ex : float
the lower frequency limit of the PS used to estimate numax
upper_ex : float
the upper frequency limit of the PS used to estimate numax
max_trials : int
(arbitrary) maximum number of "guesses" or trials to perform to estimate numax
Attributes
frequency, power : numpy.ndarray, numpy.ndarray
copy of the entire oversampled (or critically-sampled) power spectrum (i.e. `freq_os` & `pow_os`)
freq, pow : numpy.ndarray, numpy.ndarray
copy of the entire oversampled (or critically-sampled) power spectrum (i.e. `freq_os` & `pow_os`) after applying the mask~[lower_ex,upper_ex]
module : str, default='parameters'
which part of the pipeline is currently being used
"""
# If running the first module, mask out any unwanted frequency regions
self.frequency, self.power = np.copy(self.freq_os), np.copy(self.pow_os)
self.params['resolution'] = self.frequency[1]-self.frequency[0]
# mask out any unwanted frequencies
if self.params['lower_ex'] is not None:
lower = self.params['lower_ex']
else:
lower = min(self.frequency)
if self.params['upper_ex'] is not None:
upper = self.params['upper_ex']
else:
upper = max(self.frequency)
if self.nyquist is not None and self.nyquist < upper:
upper = self.nyquist
self.freq = self.frequency[(self.frequency >= lower)&(self.frequency <= upper)]
self.pow = self.power[(self.frequency >= lower)&(self.frequency <= upper)]
self.params['plotting'][self.module].update({'freq':np.copy(self.freq),'pow':np.copy(self.pow)})
if hasattr(self, 'time'):
self.params['plotting'][self.module].update({'time':np.copy(self.time),'flux':np.copy(self.flux)})
if self.params['n_trials'] > max_trials:
self.params['n_trials'] = max_trials
if (self.params['numax'] is not None and self.params['numax'] <= 500.) or (self.nyquist is not None and self.nyquist <= 300.) or (max(self.frequency) < 300.):
self.params['boxes'] = np.logspace(np.log10(0.5), np.log10(25.), self.params['n_trials'])
else:
self.params['boxes'] = np.logspace(np.log10(50.), np.log10(500.), self.params['n_trials'])
def estimate_values(self, binning=0.005, bin_mode='mean', smooth_width=20.0, ask=False,):
r"""Estimate :math:`\\rm \\nu_{max}`
Automated routine to identify power excess due to solar-like oscillations and estimate
an initial starting point for :term:`numax` (:math:`\\nu_{\\mathrm{max}}`)
Parameters
binning : float
logarithmic binning width (i.e. evenly spaced in log space)
bin_mode : str, {'mean', 'median', 'gaussian'}
mode to use when binning
smooth_width: float
box filter width (in :math:`\\rm \\mu Hz`) to smooth power spectrum
ask : bool, default=False
If `True`, it will ask which trial to use as the estimate for numax
Attributes
bin_freq, bin_pow : numpy.ndarray, numpy.ndarray
copy of the power spectrum (i.e. `freq` & `pow`) binned equally in logarithmic space
smooth_freq, smooth_pow : numpy.ndarray, numpy.ndarray
copy of the binned power spectrum (i.e. `bin_freq` & `bin_pow`) binned equally in linear space -- *yes, this is doubly binned intentionally*
interp_pow : numpy.ndarray
the smoothed power spectrum (i.e. `smooth_freq` & `smooth_pow`) interpolated back to the original frequency array (also referred to as "crude background model")
bgcorr_pow : numpy.ndarray
approximate :term:`background-corrected power spectrum` computed by dividing the original PS (`pow`) by the interpolated PS (`interp_pow`)
Methods
- :mod:`pysyd.target.Target._collapsed_acf`
"""
# Smooth the power in log-space
self.bin_freq, self.bin_pow, _ = self.bin_data(self.freq, self.pow, width=self.params['binning'], log=True, mode=self.params['bin_mode'])
# Smooth the power in linear-space
try:
self.smooth_freq, self.smooth_pow, _ = self.bin_data(self.bin_freq, self.bin_pow, width=self.params['smooth_width'])
if len(self.smooth_freq) <= 20:
self.errors = ['binned PS is too small (i.e. %d points)' % len(self.smooth_freq),
'please adjust the smoothing width (--sw) to a smaller value',
'default is currently set to => %d muHz' % int(self.params['smooth_width'])]
errors = self.get_message(witch='error', delim='#')
raise InputError(errors)
except InputError as error:
print(error.msg)
return
else:
if self.params['verbose']:
print('%s\nPS binned to %d datapoints\n\nNumax estimates\n---------------' % ('-'*self.width, len(self.smooth_freq)))
# Mask out frequency values that are lower than the smoothing width to avoid weird looking fits
if min(self.freq) < self.params['smooth_width']:
mask = (self.smooth_freq >= self.params['smooth_width'])
self.smooth_freq, self.smooth_pow = self.smooth_freq[mask], self.smooth_pow[mask]
s = InterpolatedUnivariateSpline(self.smooth_freq, self.smooth_pow, k=1)
# Interpolate and divide to get a crude background-corrected power spectrum
self.interp_pow = s(self.freq)
self.bgcorr_pow = self.pow/self.interp_pow
self.params['plotting'][self.module].update({'bin_freq':np.copy(self.bin_freq),'bin_pow':np.copy(self.bin_pow),
'interp_pow':np.copy(self.interp_pow),'bgcorr_pow':np.copy(self.bgcorr_pow)})
# Collapsed ACF to find numax
self._collapsed_acf()
self.params['best'] = self.params['compare'].index(max(self.params['compare']))+1
# Select trial that resulted with the highest SNR detection
if not self.params['ask']:
if self.params['verbose']:
print('Selecting model %d' % self.params['best'])
# Or ask which estimate to use
else:
self = plots.select_trial(self)
def _collapsed_acf(self, n_trials=3, step=0.25, max_snr=100.0,):
"""Collapsed ACF
Computes a collapsed autocorrelation function (ACF) using n different box sizes in
n different trials (i.e. `n_trials`)
Parameters
n_trials : int, default=3
the number of trials to run
step : float, default=0.25
fractional step size to use for the collapsed ACF calculation
max_snr : float, default=100.0
the maximum signal-to-noise of the estimate (this is primarily for plot formatting)
"""
c = utils.Constants()
self.params['compare'] = []
# Computes a collapsed ACF using different "box" (or bin) sizes
for b, box in enumerate(self.params['boxes']):
self.params['results'][self.module][b+1], self.params['plotting'][self.module][b] = {}, {}
start, snr, cumsum, md = 0, 0.0, [], []
subset = np.ceil(box/self.params['resolution'])
steps = np.ceil((box*self.params['step'])/self.params['resolution'])
# Iterates through entire power spectrum using box width
while True:
if (start+subset) > len(self.freq):
break
p = self.bgcorr_pow[int(start):int(start+subset)]
auto = np.real(np.fft.fft(np.fft.ifft(p)*np.conj(np.fft.ifft(p))))
cumsum.append(np.sum(np.absolute(auto-np.mean(auto))))
md.append(np.mean(self.freq[int(start):int(start+subset)]))
start += steps
# subtract/normalize the summed ACF and take the max
cumsum = np.array(cumsum)-min(cumsum)
csum = list(cumsum/max(cumsum))
# Pick the maximum value as an initial guess for numax
idx = csum.index(max(csum))
self.params['plotting'][self.module].update({b:{'x':np.array(md),'y':np.array(csum),'maxx':md[idx],'maxy':csum[idx]}})
# Fit Gaussian to get estimate value for numax
try:
best_vars, _ = curve_fit(models.gaussian, np.array(md), np.array(csum), p0=[np.median(csum), 1.0-np.median(csum), md[idx], c.width_sun*(md[idx]/c.numax_sun)], maxfev=5000, bounds=((-np.inf,-np.inf,1,-np.inf),(np.inf,np.inf,np.inf,np.inf)),)
except Exception as _:
self.params['plotting'][self.module][b].update({'good_fit':False,'fitx':np.linspace(min(md), max(md), 10000)})
else:
self.params['plotting'][self.module][b].update({'good_fit':True,})
self.params['plotting'][self.module][b].update({'fitx':np.linspace(min(md), max(md), 10000),'fity':models.gaussian(np.linspace(min(md), max(md), 10000), *best_vars)})
snr = max(self.params['plotting'][self.module][b]['fity'])/np.absolute(best_vars[0])
if snr > max_snr:
snr = max_snr
self.params['results'][self.module][b+1].update({'value':best_vars[2],'snr':snr})
self.params['plotting'][self.module][b].update({'value':best_vars[2],'snr':snr})
if self.params['verbose']:
print('Estimate %d: %.2f +/- %.2f'%(b+1, best_vars[2], np.absolute(best_vars[3])/2.0))
print('S/N: %.2f' % snr)
self.params['compare'].append(snr)
def save_estimates(self, variables=['star','numax','dnu','snr']):
"""Save results
Saves the parameter estimates (i.e. results from first module)
Parameters
star : pysyd.target.Target
processed pipeline target
variables : List[str]
list of estimated variables to save (e.g., :math:`\\rm \\nu_{max}`, :math:`\\Delta\\nu`)
Returns
star : pysyd.target.Target
updated pipeline target
"""
if 'best' in self.params:
best = self.params['best']
results = [self.name, self.params['results']['estimates'][best]['value'], delta_nu(self.params['results']['estimates'][best]['value']), self.params['results']['estimates'][best]['snr']]
if self.params['save']:
save_path = os.path.join(self.params['path'], 'estimates.csv')
if not self.params['overwrite']:
save_path = self._get_next(save_path)
ascii.write(np.array(results), save_path, names=variables, delimiter=',', overwrite=True)
self.params['numax'], self.params['dnu'], self.params['snr'] = results[1], results[2], results[3]
def check_numax(self, columns=['numax', 'dnu', 'snr']):
r"""Check :math:`\\rm \\nu_{max}`
Checks if there is an initial starting point or estimate for :term:`numax`
Parameters
columns : List[str]
saved columns if the estimate_numax() function was run
Raises
:mod:`pysyd.utils.InputError`
if an invalid value was provided as input for numax
:mod:`pysyd.utils.ProcessingError`
if it still cannot find any estimate for :term:`numax`
"""
self.errors = []
if self.params['numax'] is not None:
if np.isnan(float(self.params['numax'])):
self.errors.append('invalid value for numax')
else:
# If not, checks if estimate_numax module was run
if glob.glob(os.path.join(self.params['path'],'estimates*')):
if not self.params['overwrite']:
list_of_files = glob.glob(os.path.join(self.params['path'],'estimates*'))
file = max(list_of_files, key=os.path.getctime)
else:
file = os.path.join(self.params['path'],'estimates.csv')
df = pd.read_csv(file)
for col in columns:
self.params[col] = df.loc[0, col]
if np.isnan(self.params['numax']):
self.errors.append('invalid value for numax')
else:
self.errors.append('no decent numax value found, try providing one instead')
if self.errors != []:
try:
errors = self.get_message(witch='error', delim='#')
raise InputError(errors)
except InputError as error:
print(error.msg)
return False
else:
return True
##########################################################################################
def derive_parameters(self, mc_iter=1,):
"""Derive parameters
Main function to derive the background and global asteroseismic parameters (including
uncertainties when relevant), which does everything from finding the initial estimates
to plotting/saving results
Parameters
mc_iter : int, default=1
the number of iterations to run
Methods
:mod:`pysyd.target.Target.check_numax`
first checks to see if there is a valid estimate or input value provides
for numax
:mod:`pysyd.target.Target.initial_parameters`
if so, it will estimate the rest of the initial guesses required for the
background and global fitting (primarily using solar scaling relations)
:mod:`pysyd.target.Target.first_step`
the first iteration determines the best-fit background model and global
properties
:mod:`pysyd.target.Target.get_samples`
bootstrap uncertainties by attempting to recover the parameters from the
first step
"""
self.module = 'derive'
if 'results' not in self.params:
self.params['results'] = {}
if 'plotting' not in self.params:
self.params['plotting'] = {}
self.params['results'][self.module], self.params['plotting'][self.module] = {}, {}
# make sure there is an estimate for numax
if self.check_numax():
# get initial values and fix data
self.derive_initial()
self.first_step()
# if the first step is ok, carry on
if self.params['mc_iter'] > 1:
self.get_samples()
# Save results
utils._save_parameters(self)
def derive_initial(self, lower_bg=1.0, upper_bg=8000.0,):
"""Initial guesses
Gets initial guesses for granulation components (i.e. timescales and amplitudes) using
solar scaling relations. This resets the power spectrum and has its own independent
filter (i.e. [lower,upper] mask) to use for this subroutine.
Parameters
lower_bg : float, default=1.0
lower frequency limit of PS to use for the background fit
upper_bg : float, default=8000.0
upper frequency limit of PS to use for the background fit
Attributes
frequency, power : numpy.ndarray, numpy.ndarray
copy of the entire oversampled (or critically-sampled) power spectrum (i.e. `freq_os` & `pow_os`)
frequency, random_pow : numpy.ndarray, numpy.ndarray
copy of the entire oversampled (or critically-sampled) power spectrum (i.e. `freq_os` & `pow_os`) after applying the mask~[lower_bg,upper_bg]
module : str, default='parameters'
which part of the pipeline is currently being used
i : int, default=0
iteration number
Methods
:mod:`pysyd.target.Target.solar_scaling`
uses multiple solar scaling relations to determnie accurate initial guesses for
many of the derived parameters
.. warning::
This is typically sufficient for most stars but may affect evolved stars and
need to be adjusted!
"""
self.frequency, self.power = np.copy(self.freq_os), np.copy(self.pow_os)
self.params['resolution'] = self.frequency[1]-self.frequency[0]
if self.params['lower_bg'] is not None:
lower = self.params['lower_bg']
else:
lower = min(self.frequency)
if self.params['upper_bg'] is not None:
upper = self.params['upper_bg']
else:
upper = max(self.frequency)
if self.nyquist is not None and self.nyquist < upper:
upper = self.nyquist
self.params['bg_mask']=[lower,upper]
# Mask power spectrum for main module
mask = np.ma.getmask(np.ma.masked_inside(self.frequency, self.params['bg_mask'][0], self.params['bg_mask'][1]))
self.frequency, self.power = np.copy(self.frequency[mask]), np.copy(self.power[mask])
self.random_pow = np.copy(self.power)
self.params['plotting'][self.module].update({'frequency':np.copy(self.frequency),'random_pow':np.copy(self.power)})
if hasattr(self, 'time'):
self.params['plotting'][self.module].update({'time':np.copy(self.time),'flux':np.copy(self.flux)})
# Get other relevant initial conditions
self.i = 0
for parameter in utils.get_dict(type="columns")['params']:
self.params['results'][self.module].update({parameter:[]})
# Use scaling relations from sun to get starting points
self.solar_scaling()
if self.params['verbose']:
print('%s\nGLOBAL FIT\n%s' % ('-'*self.width, '-'*self.width))
def solar_scaling(self, numax=None, scaling='tau_sun_single', max_laws=3, ex_width=1.0,
lower_ps=None, upper_ps=None,):
"""Initial values
Using the initial starting value for :math:`\\rm \\nu_{max}`, estimates the rest of
the parameters needed for *both* the background and global fits. Uses scaling relations
from the Sun to:
#. estimate the width of the region of oscillations using numax
#. guess starting values for granulation time scales
Parameters
numax : float, default=None
provide initial value for numax to bypass the first module
scaling : str, default='tau_sun_single'
which solar scaling relation to use
max_laws : int, default=3
the maximum number of resolvable Harvey-like components
ex_width : float, default=1.0
fractional width to use for power excess centered on :term:`numax`
lower_ps : float, default=None
lower bound of power excess to use for :term:`ACF` [in :math:`\\rm \mu Hz`]
upper_ps : float, default=None
upper bound of power excess to use for :term:`ACF` [in :math:`\\rm \mu Hz`]
Attributes
converge : bool, default=True
`True` if all fitting converges
"""
c = utils.Constants()
if self.params['dnu'] is None:
self.params['dnu'] = utils.delta_nu(self.params['numax'])
# Use scaling relations to estimate width of oscillation region to mask out of the background fit
width = c.width_sun*(self.params['numax']/c.numax_sun)
maxpower = [self.params['numax']-(width*self.params['ex_width']), self.params['numax']+(width*self.params['ex_width'])]
if self.params['lower_ps'] is not None:
maxpower[0] = self.params['lower_ps']
if self.params['upper_ps'] is not None:
maxpower[1] = self.params['upper_ps']
self.params['ps_mask'] = [maxpower[0], maxpower[1]]
# make sure interval is not empty
if not list(self.frequency[(self.frequency>=self.params['ps_mask'][0])&(self.frequency<=self.params['ps_mask'][1])]):
raise utils.InputError("\nERROR: frequency region for power excess is null\nPlease specify an appropriate numax and/or frequency limits for the power excess (via --lp/--up)\n")
# Estimate granulation time scales
if scaling == 'tau_sun_single':
taus = np.array(c.tau_sun_single)*(c.numax_sun/self.params['numax'])
else:
taus = np.array(c.tau_sun)*(c.numax_sun/self.params['numax'])
taus = taus[taus <= self.baseline]
b = taus*10**-6.
mnu = (1.0/taus)*10**5.
self.params['b'] = b[mnu >= min(self.frequency)]
self.params['mnu'] = mnu[mnu >= min(self.frequency)]
if len(self.params['mnu']) == 0:
self.params['b'] = b[mnu >= 10.]
self.params['mnu'] = mnu[mnu >= 10.]
if len(self.params['mnu']) > max_laws:
self.params['b'] = self.params['b'][-max_laws:]
self.params['mnu'] = self.params['mnu'][-max_laws:]
self.converge = True
# Save copies for plotting after the analysis
self.params['nlaws'], self.params['a'] = len(self.params['mnu']), []
self.params['plotting'][self.module].update({'exp_numax':self.params['numax'],'nlaws_orig':len(self.params['mnu']),'b_orig':np.copy(self.params['b'])})
def first_step(self, background=True, globe=True,):
"""First step
Processes a given target for the first step, which has extra steps for each of the two
main parts of this method (i.e. background model and global fit):
#. **background model:** the automated best-fit model selection is only performed in the
first step, the results which are saved for future purposes (including the
background-corrected power spectrum)
#. **global fit:** while the :term:`ACF` is computed for every iteration, a mask is
created in the first step to prevent the estimate for dnu to latch on to a different
(i.e. incorrect) peak, since this is a multi-modal parameter space
Parameters
background : bool, default=True
run the automated background-fitting routine
globe : bool, default=True
perform global asteroseismic analysis (really only relevant if interested in the background model *only*)
Methods
:mod:`pysyd.target.Target.estimate_background`
estimates the amplitudes/levels of both correlated and frequency-independent noise
properties from the input power spectrum
:mod:`pysyd.target.Target.model_background`
automated best-fit background model selection that is a summed contribution of
various white + red noise componenets
:mod:`pysyd.target.Target.global_fit`
after correcting for the best-fit background model, this derives the :term:`global asteroseismic parameters`
.. seealso:: :mod:`pysyd.target.Target.single_step`
"""
# Background corrections
self.estimate_background()
self.model_background()
# Global fit
if self.params['globe']:
# global fit
self.global_fit()
if self.params['verbose'] and self.params['mc_iter'] > 1:
print('%s\nSampling routine:' % '-'*self.width)
def single_step(self,):
"""Single step
Similar to the first step, this function calls the same methods but uses the selected best-fit
background model from the first step to estimate the parameters
Attributes
converge : bool
removes any saved parameters if any fits did not converge (i.e. `False`)
Returns
converge : bool
returns `True` if all relevant fits converged
Methods
:mod:`pysyd.target.Target.estimate_background`
estimates the amplitudes/levels of both correlated and frequency-independent noise
properties from the input power spectrum
:mod:`pysyd.target.Target.get_background`
unlike the first step, which iterated through several models and performed a
best-fit model comparison, this only fits parameters from the selected model
in the first step
:mod:`pysyd.target.Target.global_fit`
after correcting for the background model, this derives the :term:`global asteroseismic parameters`
"""
self.converge = True
self.random_pow = (np.random.chisquare(2, len(self.frequency))*self.power)/2.
# Background corrections
self.estimate_background()
self.get_background()
# Requires bg fit to converge before moving on
if self.converge and self.params['globe']:
self.global_fit()
if not self.converge:
for parameter in self.params['results'][self.module]:
if len(self.params['results'][self.module][parameter]) > (self.i+1):
p = self.params['results'][self.module][parameter].pop(-1)
return self.converge
def get_samples(self,):
"""Get samples
Estimates uncertainties for parameters by randomizing the power spectrum and
attempting to recover the same parameters by calling the :mod:`pysyd.target.Target.single_step`
Attributes
frequency, power : numpy.ndarray, numpy.ndarray
copy of the critically-sampled power spectrum (i.e. `freq_cs` & `pow_cs`) after applying the mask~[lower_bg,upper_bg]
pbar : tqdm.tqdm, optional
optional progress bar used with verbose output when running multiple iterations
.. note::
all iterations except for the first step are applied to the :term:`critically-sampled power spectrum`
and *not* the :term:`oversampled power spectrum`
.. important:: if the verbose option is enabled, the `tqdm` package is required here
"""
# Switch to critically-sampled PS if sampling
mask = np.ma.getmask(np.ma.masked_inside(self.freq_cs, self.params['bg_mask'][0], self.params['bg_mask'][1]))
self.frequency, self.power = np.copy(self.freq_cs[mask]), np.copy(self.pow_cs[mask])
self.params['resolution'] = self.frequency[1]-self.frequency[0]
# Set seed for reproducibility
if self.params['seed'] is None:
self._get_seed()
np.random.seed(int(self.params['seed']))
if self.params['verbose']:
from tqdm import tqdm
self.pbar = tqdm(total=self.params['mc_iter'])
self.pbar.update(1)
# iterate for x steps
while self.i < self.params['mc_iter']:
if self.single_step():
self.i += 1
if self.params['verbose']:
self.pbar.update(1)
if self.i == self.params['mc_iter']:
self.pbar.close()
def estimate_background(self, ind_width=20.0,):
"""Background estimates
Estimates initial guesses for the stellar background contributions for both the
red and white noise components
Parameters
ind_width : float
the independent average smoothing width (:math:`\\rm \\mu Hz`)
Attributes
bin_freq, bin_pow, bin_err : numpy.ndarray, numpy.ndarray, numpy.ndarray
binned power spectrum using the :term:`ind_width<--iw, --indwidth>` bin size
"""
# Bin power spectrum to model stellar background/correlated red noise components
self.bin_freq, self.bin_pow, self.bin_err = self.bin_data(self.frequency, self.random_pow, width=self.params['ind_width'], mode=self.params['bin_mode'])
# Mask out region with power excess
mask = np.ma.getmask(np.ma.masked_outside(self.bin_freq, self.params['ps_mask'][0], self.params['ps_mask'][1]))
self.bin_freq, self.bin_pow, self.bin_err = self.bin_freq[mask], self.bin_pow[mask], self.bin_err[mask]
# Estimate white noise level
self.white_noise()
# Get initial guesses for the optimization of the background model
self.red_noise()
def white_noise(self):
"""Estimate white noise
Estimate the white noise level by taking the mean of the last 10% of the power spectrum
"""
mask = (self.frequency > (max(self.frequency)-0.1*max(self.frequency)))&(self.frequency < max(self.frequency))
self.params['noise'] = np.mean(self.random_pow[mask])
def red_noise(self, box_filter=1.0, n_rms=20,):
"""Estimate red noise
Estimates amplitudes of red noise components by using a smoothed version of the power
spectrum with the power excess region masked out -- which will take the mean of a specified
number of points (via -nrms, default=20) for each Harvey-like component
Parameters
box_filter : float, default=1.0
the size of the 1D box smoothing filter
n_rms : int, default=20
number of data points to average over to estimate red noise amplitudes
Attributes
smooth_pow : numpy.ndarray
smoothed power spectrum after applying the box filter
"""
# Exclude region with power excess and smooth to estimate red noise components
boxkernel = Box1DKernel(int(np.ceil(self.params['box_filter']/self.params['resolution'])))
mask = (self.frequency >= self.params['ps_mask'][0])&(self.frequency <= self.params['ps_mask'][1])
self.smooth_pow = convolve(self.random_pow, boxkernel)
# Temporary array for inputs into model optimization
self.params['guesses'] = np.zeros((self.params['nlaws']*2+1))
# Estimate amplitude for each harvey component
for n, nu in enumerate(self.params['mnu']):
diff = list(np.absolute(self.frequency-nu))
idx = diff.index(min(diff))
if idx < self.params['n_rms']:
self.params['guesses'][2*n+1] = np.sqrt((np.mean(self.smooth_pow[~mask][:self.params['n_rms']]))/(4.*self.params['b'][n]))
elif (len(self.smooth_pow[~mask])-idx) < self.params['n_rms']:
self.params['guesses'][2*n+1] = np.sqrt((np.mean(self.smooth_pow[~mask][-self.params['n_rms']:]))/(4.*self.params['b'][n]))
else:
self.params['guesses'][2*n+1] = np.sqrt((np.mean(self.smooth_pow[~mask][idx-int(self.params['n_rms']/2):idx+int(self.params['n_rms']/2)]))/(4.*self.params['b'][n]))
self.params['guesses'][2*n] = self.params['b'][n]
self.params['a'].append(self.params['guesses'][2*n+1])
self.params['guesses'][-1] = self.params['noise']
def model_background(self, n_laws=None, fix_wn=False, basis='tau_sigma',):
"""Model stellar background
If nothing is fixed, this method iterates through :math:`2\\dot(n_{\\mathrm{laws}}+1)`
models to determine the best-fit background model due to stellar granulation processes,
which uses a solar scaling relation to estimate the number of Harvey-like component(s)
(or `n_laws`)
Parameters
n_laws : int, default=None
specify number of Harvey-like components to use in background fit
fix_wn : bool, default=False
option to fix the white noise instead of it being an additional free parameter
basis : str, default='tau_sigma'
which basis to use for background fitting, e.g. {a,b} parametrization **TODO: not yet operational**
Methods
:mod:`pysyd.models.background`
- :mod:`scipy.curve_fit`
- :mod:`pysyd.models._compute_aic`
- :mod:`pysyd.models._compute_bic`
- :mod:`pysyd.target.Target.correct_background`
Returns
converge : bool
returns `False` if background model fails to converge
Raises
ProcessingError
if this failed to converge on a single model during the first iteration
"""
# save initial guesses for plotting purposes
self.params['plotting'][self.module].update({'bin_freq':np.copy(self.bin_freq),'bin_pow':np.copy(self.bin_pow),
'bin_err':np.copy(self.bin_err),'a_orig':np.copy(self.params['a']),
'smooth_pow':np.copy(self.smooth_pow),'noise':self.params['noise'],})
if self.params['background']:
if self.params['verbose']:
print('PS binned to %d data points\n\nBackground model\n----------------' % len(self.bin_freq))
# Get best-fit model
self.params['bounds'], self.params['bic'], self.params['aic'], self.params['paras'] = [], [], [], []
if self.params['n_laws'] is not None:
if not self.params['fix_wn']:
self.params['models'] = [self.params['n_laws']*2, self.params['n_laws']*2+1]
else:
self.params['models'] = [self.params['n_laws']*2]
else:
if self.params['fix_wn']:
self.params['models'] = np.arange(0,(self.params['nlaws']+1)*2,2)
else:
self.params['models'] = np.arange((self.params['nlaws']+1)*2)
if self.params['verbose'] and len(self.params['models']) > 1:
print('Comparing %d different models:' % len(self.params['models']))
for n, n_free in enumerate(self.params['models']):
b, a = np.inf, np.inf
note = 'Model %d: %d Harvey-like component(s) + '%(n, n_free//2)
if self.params['basis'] == 'a_b':
bounds = ([0.0,0.0]*(n_free//2), [np.inf,self.tau_upper]*(n_free//2))
else:
bounds = ([0.0,0.0]*(n_free//2), [np.inf,np.inf]*(n_free//2))
if not n_free%2:
note += 'white noise fixed'
*guesses, = self.params['guesses'][-int(2*(n_free//2)+1):-1]
else:
note += 'white noise term'
bounds[0].append(10.**-2)
bounds[1].append(np.inf)
*guesses, = self.params['guesses'][-int(2*(n_free//2)+1):]
self.params['bounds'].append(bounds)
if n_free == 0:
self.params['paras'].append([])
b = models.Likelihood(self.bin_pow, np.ones_like(self.bin_pow)*self.params['noise'], n_free).compute_bic()
a = models.Likelihood(self.bin_pow, np.ones_like(self.bin_pow)*self.params['noise'], n_free).compute_aic()
else:
try:
if not n_free%2:
# If white noise is fixed, pass "noise" estimate to lambda operator
pars, _ = curve_fit(self.params['functions'][n_free](self.params['noise']), self.bin_freq, self.bin_pow, p0=guesses, sigma=self.bin_err, bounds=bounds)
else:
# If white noise is a free parameter, good to go!
pars, _ = curve_fit(self.params['functions'][n_free], self.bin_freq, self.bin_pow, p0=guesses, sigma=self.bin_err, bounds=bounds)
except RuntimeError as _:
self.params['paras'].append([])
else:
self.params['paras'].append(pars)
model = models.background(self.bin_freq, pars, noise=self.params['noise'])
b, a = models.Likelihood(self.bin_pow, model, n_free).compute_bic(), models.Likelihood(self.bin_pow, model, n_free).compute_aic()
self.params['bic'].append(b)
self.params['aic'].append(a)
if self.params['verbose'] and np.isfinite(a) and np.isfinite(b):
note += '\n BIC = %.2f | AIC = %.2f'%(b, a)
print(note)
# Did the fit converge
if np.isfinite(min(self.params[self.params['metric']])):
self.correct_background()
# Otherwise raise error that fit did not converge
else:
self.converge = False
raise utils.ProcessingError("Background fit failed to converge for any models.\n\n We recommend disabling this feature using our boolean background flag ('-b' )")
else:
if self.params['verbose']:
raise utils.ProcessingWarning('%s\nWARNING: estimating global parameters from raw PS:' % '-'*self.width)
self.bg_corr = np.copy(self.random_pow)/self.params['noise']
self.params['pars'] = ([self.params['noise']])
# save final guesses for plotting purposes
self.params['plotting'][self.module].update({'pars':self.params['pars'],})
def correct_background(self, metric='bic'):
"""Correct background
Corrects for the stellar background contribution in the power spectrum by *both*
dividing and subtracting this out, which also saves copies of each (i.e. `bg_div`
:term:`background-divided power spectrum` to :ref:`ID_BDPS.txt <library-output-files-bdps>`
and `bg_sub` :term:`background-subtracted power spectrum to
:ref:`ID_BSPS.txt <library-output-files-bsps>`). After this is done, a copy of the
BDPS is saved to `bg_corr` and used for dnu calculations and the echelle diagram.
Parameters
metric : str, default='bic'
which metric to use (i.e. bic or aic) for model selection
Attributes
frequency, bg_div : numpy.ndarray, numpy.ndarray
background-divded power spectrum (BDPS -> higher S/N for echelle diagram)
frequency, bg_sub : numpy.ndarray, numpy.ndarray
background-subtracted power spectrum (BSPS -> preserves mode amplitudes)
frequency, bg_corr : numpy.ndarray, numpy.ndarray
background-corrected power spectrum, which is a copy of the :term:`BDPS`
"""
idx = self.params[self.params['metric']].index(min(self.params[self.params['metric']]))
self.params['selected'] = self.params['models'][idx]
self.params['bounds'] = self.params['bounds'][idx]
self.params['pars'] = self.params['paras'][idx]
# If model with fixed white noise is preferred, change 'fix_wn' option
if not int(self.params['selected']%2):
self.params['fix_wn'] = True
# Store model results for plotting
if self.params['nlaws'] != self.params['selected']//2:
self.params['nlaws'] = self.params['selected']//2
self.params['b'] = self.params['b'][:(self.params['nlaws'])]
self.params['mnu'] = self.params['mnu'][:(self.params['nlaws'])]
if self.params['verbose'] and len(self.params['models']) > 1:
print('Based on %s statistic: model %d'%(self.params['metric'].upper(),idx))
# Save background-corrected power spectrum
self.bg_div = self.random_pow/models.background(self.frequency, self.params['pars'], noise=self.params['noise'])
if self.params['save']:
self.save_file(self.frequency, self.bg_div, os.path.join(self.params['path'], '%s_BDPS.txt'%self.name), overwrite=self.params['overwrite'])
self.bg_sub = self.random_pow-models.background(self.frequency, self.params['pars'], noise=self.params['noise'])
if self.params['save']:
self.save_file(self.frequency, self.bg_sub, os.path.join(self.params['path'], '%s_BSPS.txt'%self.name), overwrite=self.params['overwrite'])
self.params['plotting'][self.module].update({'models':self.params['models'],'model':self.params['selected'],'paras':self.params['paras'],
'aic':self.params['aic'],'bic':self.params['bic'],})
# For the rest of the calculations, we'll use the background-divided power spectrum
self.bg_corr = np.copy(self.bg_div)
# Create appropriate keys for star based on best-fit model
for n in range(self.params['nlaws']):
self.params['results'][self.module]['tau_%d'%(n+1)] = []
self.params['results'][self.module]['sigma_%d'%(n+1)] = []
if not self.params['fix_wn']:
self.params['results'][self.module]['white'] = []
# Save the final values
for n in range(self.params['nlaws']):
self.params['results'][self.module]['tau_%d'%(n+1)].append(self.params['pars'][2*n]*10.**6)
self.params['results'][self.module]['sigma_%d'%(n+1)].append(self.params['pars'][2*n+1])
if not self.params['fix_wn']:
self.params['results'][self.module]['white'].append(self.params['pars'][-1])
def get_background(self):
"""Get background
Attempts to recover background model parameters in later iterations by using the
:mod:`scipy.curve_fit` module using the same best-fit background model settings
Returns
converge : bool
returns `False` if background model fails to converge
"""
if self.params['background']:
# Use as initial guesses for the optimized model
try:
if self.params['fix_wn']:
# If white noise is fixed, pass "noise" estimate to lambda operator
self.params['pars'], _ = curve_fit(self.params['functions'][self.params['selected']](self.params['noise']), self.bin_freq, self.bin_pow, p0=self.params['guesses'][:-1], sigma=self.bin_err, bounds=self.params['bounds'])
else:
# If white noise is a free parameter, good to go!
self.params['pars'], _ = curve_fit(self.params['functions'][self.params['selected']], self.bin_freq, self.bin_pow, p0=self.params['guesses'], sigma=self.bin_err, bounds=self.params['bounds'])
except RuntimeError as _:
self.converge = False
else:
self.bg_corr = self.random_pow/models.background(self.frequency, self.params['pars'], noise=self.params['noise'])
# save final values for Harvey components
for n in range(self.params['nlaws']):
self.params['results'][self.module]['tau_%d'%(n+1)].append(self.params['pars'][2*n]*10.**6)
self.params['results'][self.module]['sigma_%d'%(n+1)].append(self.params['pars'][2*n+1])
if not self.params['fix_wn']:
self.params['results'][self.module]['white'].append(self.params['pars'][-1])
else:
self.bg_corr = np.copy(self.random_pow)/self.params['noise']
self.params['pars'] = ([self.params['noise']])
def global_fit(self):
r"""Global fit
Fits global asteroseismic parameters :math:`\\rm \\nu{max}` and :math:`\\Delta\\nu`,
where the former is estimated two different ways.
Methods
:mod:`pysyd.target.Target.numax_smooth`
:mod:`pysyd.target.Target.numax_gaussian`
:mod:`pysyd.target.Target.compute_acf`
:mod:`pysyd.target.Target.frequency_spacing`
"""
# get numax
self.numax_smooth()
self.numax_gaussian()
# get dnu
self.compute_acf()
self.frequency_spacing()
def numax_smooth(self, sm_par=None):
r"""Smooth :math:`\\nu_{\\mathrm{max}}`
Estimate numax by taking the peak of the smoothed power spectrum
Parameters
sm_par : float, optional
smoothing width for power spectrum calculated from solar scaling relation (typically ~1-4)
Attributes
frequency, pssm : numpy.ndarray, numpy.ndarray
smoothed power spectrum
frequency, pssm_bgcorr : numpy.ndarray, numpy.ndarray
smoothed :term:`background-subtracted power spectrum`
region_freq, region_pow : numpy.ndarray, numpy.ndarray
oscillation region of the power spectrum ("zoomed in") by applying the mask~[lower_ps,upper_ps]
numax_smoo : float
the 'observed' numax (i.e. the peak of the smoothed power spectrum)
dnu_smoo : float
the 'expected' dnu based on a scaling relation using the `numax_smoo`
"""
# Smoothing width for determining numax
if self.params['sm_par'] is not None:
sm_par = self.params['sm_par']
else:
sm_par = 4.*(self.params['numax']/self.constants['numax_sun'])**0.2
if sm_par < 1.:
sm_par = 1.
sig = (sm_par*(self.params['dnu']/self.params['resolution']))/np.sqrt(8.0*np.log(2.0))
self.pssm = convolve_fft(np.copy(self.random_pow), Gaussian1DKernel(int(sig)))
self.pssm_bgcorr = self.pssm-models.background(self.frequency, self.params['pars'], noise=self.params['noise'])
mask = np.ma.getmask(np.ma.masked_inside(self.frequency, self.params['ps_mask'][0], self.params['ps_mask'][1]))
self.region_freq, self.region_pow = self.frequency[mask], self.pssm_bgcorr[mask]
idx, max_freq, max_pow = utils.return_max(self.region_freq, self.region_pow)
self.params['results'][self.module]['numax_smooth'].append(max_freq)
self.params['results'][self.module]['A_smooth'].append(max_pow)
self.params['numax_smoo'] = self.params['results'][self.module]['numax_smooth'][0]
self.params['exp_dnu'] = utils.delta_nu(self.params['numax_smoo'])
def numax_gaussian(self):
r"""Gaussian :math:`\\nu_{\\mathrm{max}}`
Estimate numax by fitting a Gaussian to the "zoomed-in" power spectrum (i.e. `region_freq`
and `region_pow`) using :mod:`scipy.curve_fit`
Returns
converge : bool
returns `False` if background model fails to converge
Raises
:mod:`pysyd.utils.ProcessingError`
if the Gaussian fit does not converge for the first step
"""
guesses = [0.0, np.absolute(max(self.region_pow)), self.params['numax_smoo'], (max(self.region_freq)-min(self.region_freq))/np.sqrt(8.0*np.log(2.0))]
bb = ([-np.inf,0.0,0.01,0.01],[np.inf,np.inf,np.inf,np.inf])
try:
gauss, _ = curve_fit(models.gaussian, self.region_freq, self.region_pow, p0=guesses, bounds=bb, maxfev=1000)
except RuntimeError as _:
self.converge = False
if self.i == 0:
raise ProcessingError("Gaussian fit for numax failed to converge.\n\nPlease check your power spectrum and try again.", width=self.width)
else:
if self.i == 0:
# Create an array with finer resolution for plotting
new_freq = np.linspace(min(self.region_freq), max(self.region_freq), 10000)
self.params['plotting'][self.module].update({'pssm':np.copy(self.pssm),'obs_numax':self.params['numax_smoo'],'new_freq':new_freq,
'numax_fit':models.gaussian(new_freq, *gauss),'exp_dnu':self.params['exp_dnu'],
'region_freq':np.copy(self.region_freq),'region_pow':np.copy(self.region_pow),})
# Save values
self.params['results'][self.module]['numax_gauss'].append(gauss[2])
self.params['results'][self.module]['A_gauss'].append(gauss[1])
self.params['results'][self.module]['FWHM'].append(gauss[3])
def compute_acf(self, fft=True, smooth_ps=2.5,):
r"""ACF
Compute the autocorrelation function (:term:`ACF`) of the background-divided power
spectrum (i.e. `bg_corr`), with an option to smooth the :term:`BCPS` first
Parameters
fft : bool, default=True
if `True`, uses FFTs to compute the ACF, otherwise it will use :mod:`numpy.correlate`
smooth_ps : float, optional
convolve the background-corrected PS with a box filter of this width (:math:`\\rm \\mu Hz`)
Attributes
bgcorr_smooth : numpy.ndarray
smoothed background-corrected power spectrum if `smooth_ps != 0` else copy of `bg_corr`
lag, auto : numpy.ndarray, numpy.ndarray
the autocorrelation of the "zoomed-in" power spectrum
"""
# Optional smoothing of PS to remove fine structure before computing ACF
if self.params['smooth_ps'] == 0.0:
self.bgcorr_smooth = np.copy(self.bg_corr)
else:
boxkernel = Box1DKernel(int(np.ceil(self.params['smooth_ps']/self.params['resolution'])))
self.bgcorr_smooth = convolve(self.bg_corr, boxkernel)
# Use only power near the expected numax to reduce additional noise in ACF
power = self.bgcorr_smooth[(self.frequency >= self.params['ps_mask'][0])&(self.frequency <= self.params['ps_mask'][1])]
lag = np.arange(0.0, len(power))*self.params['resolution']
if self.params['fft']:
auto = np.real(np.fft.fft(np.fft.ifft(power)*np.conj(np.fft.ifft(power))))
else:
auto = np.correlate(power-np.mean(power), power-np.mean(power), "full")
auto = auto[int(auto.size/2):]
mask = np.ma.getmask(np.ma.masked_inside(lag, self.params['exp_dnu']/4., 2.*self.params['exp_dnu']+self.params['exp_dnu']/4.))
lag, auto = lag[mask], auto[mask]
auto = (auto - min(auto))/(max(auto) - min(auto))
self.lag, self.auto = np.copy(lag), np.copy(auto)
def frequency_spacing(self, n_peaks=10,):
r"""Estimate :math:`\\Delta\\nu`
Estimates the large frequency separation (or :math:`\\Delta\\nu`) by fitting a
Gaussian to the peak of the ACF "cutout" using :mod:`scipy.curve_fit`.
Parameters
n_peaks : int, default=10
the number of peaks to identify in the ACF
Attributes
peaks_l, peaks_a : numpy.ndarray
the n highest peaks (`n_peaks`) in the ACF
zoom_lag, zoom_auto : numpy.ndarray
cutout from the ACF of the peak near dnu
Returns
converge : bool
returns `False` if a Gaussian could not be fit within the `1000` iterations
Raises
ProcessingError
if a Gaussian could not be fit to the provided peak
.. seealso:: :mod:`pysyd.target.Target.acf_cutout`, :mod:`pysyd.target.Target.optimize_ridges`,
:mod:`pysyd.target.Target.echelle_diagram`
.. note::
For the first step, a Gaussian weighting (centered on the expected value for dnu, or `exp_dnu`) is
automatically computed and applied by the pipeline to prevent the fit from latching
on to a peak that is a harmonic and not the actual spacing
"""
if self.i == 0:
# Get actual peaks from ACF for plotting purposes before any weighting
pl, pa, _ = utils.max_elements(self.lag, self.auto, npeaks=self.params['n_peaks'], distance=self.params['exp_dnu']/4.)
# Get peaks from ACF by providing dnu to weight the array
peaks_l, peaks_a, weights = utils.max_elements(self.lag, self.auto, npeaks=self.params['n_peaks'], distance=self.params['exp_dnu']/4., exp_dnu=self.params['exp_dnu'])
# Pick "best" peak in ACF (i.e. closest to expected dnu)
idx , self.params['best_lag'], self.params['best_auto'] = utils.return_max(peaks_l, peaks_a, exp_dnu=self.params['exp_dnu'])
self._acf_cutout()
self.zoom_lag = self.lag[(self.lag >= self.params['acf_mask'][0]) & (self.lag <= self.params['acf_mask'][1])]
self.zoom_auto = self.auto[(self.lag >= self.params['acf_mask'][0]) & (self.lag <= self.params['acf_mask'][1])]
# fit a Gaussian to the peak to estimate dnu
try:
gauss, _ = curve_fit(models.gaussian, self.zoom_lag, self.zoom_auto, p0=self.params['acf_guesses'], bounds=self.params['acf_bb'], maxfev=1000)
# did the fit converge
except RuntimeError:
self.converge = False
if self.i == 0:
# Raise error if it's the first step
raise ProcessingError("Gaussian fit for dnu failed to converge.\n\nPlease check your power spectrum and try again.", width=self.width)
# if fit converged, save appropriate results
else:
self.params['results'][self.module]['dnu'].append(gauss[2])
if self.i == 0:
self.params['obs_dnu'] = gauss[2]
idx, _, _ = utils.return_max(pl, pa, exp_dnu=self.params['obs_dnu'])
l, a = pl.pop(idx), pa.pop(idx)
self.params['plotting'][self.module].update({'obs_dnu':gauss[2],
'peaks_l':np.copy(pl),'peaks_a':np.copy(pa),'best_lag':self.params['best_lag'],
'best_auto':self.params['best_auto'],'weights':np.copy(weights/max(weights)),
'new_lag':np.linspace(min(self.zoom_lag),max(self.zoom_lag),2000),
'dnu_fit':models.gaussian(np.linspace(min(self.zoom_lag),max(self.zoom_lag),2000), *gauss),})
self.echelle_diagram()
def _acf_cutout(self, threshold=1.0,):
"""ACF cutout
Gets the region in the ACF centered on the correct peak to prevent pySYD
from getting stuck in a local maximum (i.e. fractional and integer harmonics)
Parameters
threshold : float, default=1.0
the threshold is multiplied by the full-width half-maximum value, centered on the peak
in the ACF to determine the width of the cutout region
"""
mask = (self.frequency >= self.params['ps_mask'][0]) & (self.frequency <= self.params['ps_mask'][1])
self.zoom_freq = self.frequency[mask]
self.zoom_pow = self.bgcorr_smooth[mask]
self.params['plotting'][self.module].update({'zoom_freq':np.copy(self.zoom_freq),
'zoom_pow':np.copy(self.zoom_pow),'lag':np.copy(self.lag),'auto':np.copy(self.auto),})
# Literally calculate FWHM
if list(self.lag[(self.lag<self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)]):
left_lag = self.lag[(self.lag<self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)][-1]
left_auto = self.auto[(self.lag<self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)][-1]
else:
left_lag = self.lag[0]
left_auto = self.auto[0]
if list(self.lag[(self.lag>self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)]):
right_lag = self.lag[(self.lag>self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)][0]
right_auto = self.auto[(self.lag>self.params['best_lag'])&(self.auto<=self.params['best_auto']/2.)][0]
else:
right_lag = self.lag[-1]
right_auto = self.auto[-1]
# Lag limits to use for ACF mask or "cutout"
self.params['acf_mask'] = [self.params['best_lag']-(self.params['best_lag']-left_lag)*self.params['threshold'], self.params['best_lag']+(right_lag-self.params['best_lag'])*self.params['threshold']]
zoom_lag = self.lag[(self.lag>=self.params['acf_mask'][0])&(self.lag<=self.params['acf_mask'][1])]
zoom_auto = self.auto[(self.lag>=self.params['acf_mask'][0])&(self.lag<=self.params['acf_mask'][1])]
self.params['plotting'][self.module].update({'zoom_lag':np.copy(zoom_lag),'zoom_auto':np.copy(zoom_auto)})
# Boundary conditions and initial guesses stay the same for all iterations
self.params['acf_guesses'] = [np.mean(zoom_auto), self.params['best_auto'], self.params['best_lag'], self.params['best_lag']*0.01*2.]
self.params['acf_bb'] = ((-np.inf,0.,min(zoom_lag),10**-2.),(np.inf,np.inf,max(zoom_lag),2.*(max(zoom_lag)-min(zoom_lag))))
def echelle_diagram(self, smooth_ech=None, nox=None, noy='0+0', hey=False, npb=10, nshift=0, clip_value=3.0,):
r"""Echelle diagram
Calculates everything required to plot an :term:`echelle diagram` **Note:** this does not
currently have the `get_ridges` method attached (i.e. not optimizing the spacing or stepechelle)
Parameters
smooth_ech : float
value to smooth (i.e. convolve) ED by
nox : int
number of grid points in x-axis of echelle diagram
noy : str
number of orders (y-axis) to plot in echelle diagram
npb : int
option to provide the number of points per bin as opposed to an arbitrary value (calculated from spacing and frequency resolution)
nshift : int
number of orders to shift echelle diagram (i.e. + is up, - is down)
hey : bool
plugin for Dan Hey's echelle package **(not currently implemented)**
clip_value : float
to clip any peaks higher than Nx the median value
Attributes
ed : numpy.meshgrid
smoothed + summed 2d power for echelle diagram
extent : List[float]
bounding box for echelle diagram
"""
self.optimize_ridges()
use_dnu = self.params['plotting'][self.module]['use_dnu']
if self.params['smooth_ech'] is not None:
boxkernel = Box1DKernel(int(np.ceil(self.params['smooth_ech']/self.params['resolution'])))
smooth_y = convolve(self.bg_corr, boxkernel)
else:
smooth_y = np.copy(self.bg_corr)
# If the number of desired orders is not provided
if self.params['noy'] == "0+0" or self.params['noy'] == "0-0":
width = self.constants['width_sun']*(self.params['numax_smoo']/self.constants['numax_sun'])
ny = int(np.ceil(width/use_dnu))
nshift = 0
else:
if '+' in self.params['noy']:
ny, nshift = int(self.params['noy'].split('+')[0]), int(self.params['noy'].split('+')[-1])
if '-' in self.params['noy']:
ny, nshift = int(self.params['noy'].split('-')[0]), int(self.params['noy'].split('-')[-1])
nshift *= -1
# Make sure n_across isn't finer than the actual resolution grid
if self.params['nox'] is None or (self.params['nox'] >= int(np.ceil(use_dnu/self.params['resolution']))):
# add function to check that the resolution isn't ridiculous
nx = int(np.ceil(use_dnu/self.params['resolution']/self.params['npb']))
else:
nx = int(self.params['nox'])
x = np.linspace(0.0, 2*use_dnu, 2*nx+1)
yy = np.arange(min(self.frequency),max(self.frequency),use_dnu)
lower = self.params['numax_smoo']-(use_dnu*(ny/2.))+(use_dnu*(nshift+0))
upper = self.params['numax_smoo']+(use_dnu*(ny/2.))+(use_dnu*(nshift+1))
y = yy[(yy >= lower)&(yy <= upper)]
z = np.zeros((ny+1,2*nx))
for i in range(1,ny+1):
y_mask = ((self.frequency >= y[i-1]) & (self.frequency < y[i]))
for j in range(nx):
x_mask = ((self.frequency%(use_dnu) >= x[j]) & (self.frequency%(use_dnu) < x[j+1]))
if smooth_y[x_mask & y_mask] != []:
z[i][j] = np.sum(smooth_y[x_mask & y_mask])
else:
z[i][j] = np.nan
z[0][:nx], z[-1][nx:] = np.nan, np.nan
for k in range(ny):
z[k][nx:] = z[k+1][:nx]
self.ed = np.copy(z)
self.extent = [min(x),max(x),min(y),max(y)]
# make copy of ED to flatten and clip outliers
ed_copy = self.ed.flatten()
if self.params['clip_value'] > 0:
cut = np.nanmedian(ed_copy)+(self.params['clip_value']*np.nanmedian(ed_copy))
ed_copy[ed_copy >= cut] = cut
self.ed = ed_copy.reshape((self.ed.shape[0], self.ed.shape[1]))
self.collapse_ed()
def collapse_ed(self, n_trials=3):
r"""Get ridges
Optimizes the large frequency separation by determining which spacing creates the
"best" ridges (but is currently under development) think similar to a step-echelle
but quicker and more hands off?
Attributes
x : numpy.ndarray
x-axis for the collapsed ED ~[0, :math:`2\\times\\Delta\\nu`]
y : numpy.ndarray
marginalized power along the y-axis (i.e. collapsed on to the x-axis)
.. important:: need to optimize this - currently does nothing really
"""
n = int(np.ceil(self.params['plotting'][self.module]['use_dnu']/self.params['resolution']))
xx = np.linspace(0.0, self.params['plotting'][self.module]['use_dnu'], n)
yy = np.zeros_like(xx)
modx = self.frequency%self.params['plotting'][self.module]['use_dnu']
for k in range(n-1):
mask = (modx >= xx[k])&(modx < xx[k+1])
if self.bg_corr[mask] != []:
xx[k] = np.median(modx[mask])
yy[k] = np.sum(self.bg_corr[mask])
mask = np.ma.getmask(np.ma.masked_where(yy == 0.0, yy))
xx, yy = xx[~mask], yy[~mask]
self.x = np.array(xx.tolist()+list(xx+self.params['plotting'][self.module]['use_dnu']))
self.y = np.array(list(yy)+list(yy))-min(yy)
self.params['plotting'][self.module].update({'ed':np.copy(self.ed),'extent':np.copy(self.extent),'x':np.copy(self.x),'y':np.copy(self.y),})
self.i += 1
def get_epsilon(self, n_trials=3):
r"""Get epsilon
Optimizes the large frequency separation by determining which spacing creates the
"best" ridges (but is currently under development) think similar to a step-echelle
but quicker and more hands off? ** WORK IN PROGRESS **
Attributes
x : numpy.ndarray
x-axis for the collapsed ED ~[0, :math:`2\\times\\Delta\\nu`]
y : numpy.ndarray
marginalized power along the y-axis (i.e. collapsed on to the x-axis)
.. important:: need to optimize this - currently does nothing really
"""
self.params['results']['trial'] = []
if not self.params['force']:
self.params['boxes'] = np.logspace(np.log10(0.01*self.params['obs_dnu']), np.log10(0.1*self.params['obs_dnu']), self.params['n_trials'])
self.freq, self.bgcorr_pow = np.copy(self.frequency%self.params['obs_dnu']), np.copy(self.bg_corr)
self._collapsed_acf()
print(self.params['results']['trial'])
best = self.params['compare'].index(max(self.params['compare']))+1
return self.params['results']['trial'][best]['value']
else:
if self.params['dnu'] is None:
return self.params['obs_dnu']
else:
return self.params['dnu']
def _collapsed_dnu(self, n_trials=3, step=0.25, max_snr=1000.0,):
r"""Collapsed ACF
Computes a collapsed autocorrelation function (ACF) using n different box sizes in
n different trials (i.e. `n_trials`)
Parameters
n_trials : int, default=3
the number of trials to run
step : float, default=0.25
fractional step size to use for the collapsed ACF calculation
max_snr : float, default=100.0
the maximum signal-to-noise of the estimate (this is primarily for plot formatting)
"""
self.params['compare2'], self.params['step2'], self.params['n_trials2'], self.module = [], 0.1, 6, 'trial'
self.params['results'][self.module], self.params['plotting'][self.module] = {}, {}
self.params['boxes2'] = np.logspace(np.log10(self.params['obs_dnu']/10.0), np.log10(2.*self.params['obs_dnu']), self.params['n_trials2'])
new_freq = np.copy(self.frequency%self.params['obs_dnu'])
s = np.argsort(new_freq)
freq, bgcorr_pow = new_freq[s], self.bg_corr[s]
# Computes a collapsed ACF using different "box" (or bin) sizes
for b, box in enumerate(self.params['boxes2']):
self.params['results'][self.module][b+1], self.params['plotting'][self.module][b] = {}, {}
start, snr, cumsum, md = 0, 0.0, [], []
subset = np.ceil(box/self.params['resolution'])
steps = np.ceil((box*self.params['step2'])/self.params['resolution'])
print(b, box, subset, steps)
# Iterates through entire power spectrum using box width
while True:
if (start+subset) > len(freq):
break
p = bgcorr_pow[int(start):int(start+subset)]
auto = np.real(np.fft.fft(np.fft.ifft(p)*np.conj(np.fft.ifft(p))))
cumsum.append(np.sum(np.absolute(auto-np.mean(auto))))
md.append(np.mean(freq[int(start):int(start+subset)]))
start += steps
# subtract/normalize the summed ACF and take the max
csum = list(np.copy(cumsum))
# Pick the maximum value as an initial guess for dnu
idx = csum.index(max(csum))
self.params['plotting'][self.module].update({b:{'x':np.array(md),'y':np.array(csum),'maxx':md[idx],'maxy':csum[idx]}})
# Fit Gaussian to get estimate value for numax
try:
best_vars, _ = curve_fit(models.gaussian, np.array(md), np.array(csum), p0=[np.median(csum), 1.0-np.median(csum), md[idx], self.params['acf_guesses'][-1]], maxfev=5000, bounds=self.params['acf_bb'],)
except Exception as _:
self.params['plotting'][self.module][b].update({'good_fit':False,'fitx':np.linspace(min(md), max(md), 10000)})
else:
self.params['plotting'][self.module][b].update({'good_fit':True,})
self.params['plotting'][self.module][b].update({'fitx':np.linspace(min(md), max(md), 10000),'fity':models.gaussian(np.linspace(min(md), max(md), 10000), *best_vars)})
snr = max(self.params['plotting'][self.module][b]['fity'])/np.absolute(best_vars[0])
if snr > max_snr:
snr = max_snr
self.params['results'][self.module][b+1].update({'value':best_vars[2],'snr':snr})
self.params['plotting'][self.module][b].update({'value':best_vars[2],'snr':snr})
if self.params['verbose']:
print('Estimate %d: %.2f +/- %.2f'%(b+1, best_vars[2], np.absolute(best_vars[3])/2.0))
print('S/N: %.2f' % snr)
self.params['compare2'].append(snr)
best = self.params['compare2'].index(max(self.params['compare2']))+1
def optimize_ridges(self, n=50, res=0.01):
"""Get ridges
Optimizes the large frequency separation by determining which spacing creates the
"best" ridges (but is currently under development) think similar to a step-echelle
but quicker and more hands off?
Attributes
x : numpy.ndarray
x-axis for the collapsed ED ~[0, :math:`2\\times\\Delta\\nu`]
y : numpy.ndarray
marginalized power along the y-axis (i.e. collapsed on to the x-axis)
.. important:: need to optimize this - currently does nothing really
"""
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.collections import LineCollection
if self.params['ridges']:
fig, ax = plt.subplots(figsize=(10,6))
dnu = float('%.2f'%self.params['obs_dnu'])
lower, upper, nox = dnu-1.0, dnu+1.0, int(np.floor(self.params['obs_dnu']/self.params['resolution']))
colors = plots.get_colors(np.arange(lower,upper,res))
if self.params['nox'] is not None and self.params['nox'] <= np.ceil(self.params['obs_dnu']/self.params['resolution']):
nox = self.params['nox']
note, sigma = '', 1.0
note_formats = [">10s",">10s",">10s",">10s",">10s"]
note_cols = ['dnu','med','std','peak','sig']
text = '{:{}}'*len(note_cols)+'\n'
fmt = sum(zip(note_cols,note_formats),())
note += text.format(*fmt)
for n, spacing in enumerate(np.arange(lower,upper,res)):
bins = np.linspace(0.0, spacing, nox)
x, y = self.frequency%spacing, np.copy(self.bg_corr)
digitized = np.digitize(self.frequency%spacing, bins)
x2 = np.array([x[digitized == i].mean() for i in range(len(bins)) if len(x[digitized == i]) > 0])
y2 = np.array([y[digitized == i].sum() for i in range(len(bins)) if len(x[digitized == i]) > 0])
ye = np.std(y2)
_, peaksy, _ = utils.max_elements(x2, y2, npeaks=1)
if (peaksy[0]-np.median(y2))/ye > sigma:
sigma = (peaksy[0]-np.median(y2))/ye
use_dnu = spacing
ax.plot(x2, y2, color=colors[n], alpha=0.75, linewidth=0.75)
values = ['%.2f'%spacing, '%.2f'%np.median(y2), '%.2f'%ye, '%.2f'%peaksy[0], '%.2f'%((peaksy[0]-np.median(y2))/ye)]
text = '{:{}}'*len(values)+'\n'
fmt = sum(zip(values,note_formats),())
note += text.format(*fmt)
if self.params['save']:
path = os.path.join(self.params['path'],'test_ridges.txt')
if not self.params['overwrite']:
path = utils._get_next(path)
with open(path,"w") as f:
f.write(note)
ax.set_xlabel(r'$\rm Folded \,\, Frequency \,\, [\mu Hz]$', fontsize=28)
ax.set_ylabel(r'$\rm Collapsed \,\, ED \,\, [power]$', fontsize=28)
ax.set_xlim([0.0,upper])
plt.tight_layout()
if self.params['save']:
path = os.path.join(self.params['path'],'1d_ed.png')
if not self.params['overwrite']:
path = utils._get_next(path)
plt.savefig(path, dpi=300)
plt.close()
else:
if self.params['force'] and self.params['dnu'] is not None:
use_dnu = self.params['dnu']
else:
use_dnu = self.params['obs_dnu']
self.params['plotting'][self.module]['use_dnu'] = use_dnu
class InputError(Exception):
"""Class for pySYD user input errors (i.e., halts execution)."""
def __init__(self, error, width=60):
self.msg, self.width = error, width
def __repr__(self):
return "pysyd.utils.InputError(error=%r)" % self.msg
def __str__(self):
return "<InputError>"
class ProcessingError(Exception):
"""Class for pySYD processing errors (i.e., halts execution)."""
def __init__(self, error, width=60):
self.msg, self.width = error, width
def __repr__(self):
return "pysyd.utils.ProcessingError(error=%r)" % self.msg
def __str__(self):
return "<ProcessingError>"
class InputWarning(Warning):
"""Class for pySYD user input warnings."""
def __init__(self, warning, width=60):
self.msg, self.width = warning, width
def __repr__(self):
return "pysyd.utils.InputWarning(warning=%r)" % self.msg
def __str__(self):
return "<InputWarning>"
class ProcessingWarning(Warning):
"""Class for pySYD user input warnings."""
def __init__(self, warning, width=60):
self.msg, self.width = warning, width
def __repr__(self):
return "pysyd.utils.ProcessingWarning(warning=%r)" % self.msg
def __str__(self):
return "<ProcessingWarning>"
|
ashleychontosREPO_NAMEpySYDPATH_START.@pySYD_extracted@pySYD-master@dev@target.py@.PATH_END.py
|
{
"filename": "mutual_node.py",
"repo_name": "rodluger/planetplanet",
"repo_path": "planetplanet_extracted/planetplanet-master/scripts/mutual_node.py",
"type": "Python"
}
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
'''
mutual_node.py |github|
-----------------------
For random draws from the prior, computes the duration of a
mutual transit between TRAPPIST-1 b and c as a function of the
difference in their longitude of ascending nodes. With some
scatter, the difference in this angle is inversely proportional
to the duration of the mutual transit. Observing such an event
can place constraints on the longitudes of ascending node
of the TRAPPIST-1 planets.
.. plot::
:align: center
from scripts import mutual_node
mutual_node._test()
.. role:: raw-html(raw)
:format: html
.. |github| replace:: :raw-html:`<a href = "https://github.com/rodluger/planetplanet/blob/master/scripts/mutual_node.py"><i class="fa fa-github" aria-hidden="true"></i></a>`
'''
from __future__ import division, print_function, absolute_import, unicode_literals
from planetplanet import Planet, Star, System
import matplotlib.pyplot as pl
import numpy as np
from tqdm import tqdm
import corner
np.random.seed(1234)
RSUN = 6.957e8
REARTH = 6.3781e6
def _test():
'''
'''
plot(niter = 50)
pl.show()
def plot(niter = 10000):
'''
'''
# Draw from prior several times and plot
time = np.linspace(-0.05, 0.05, 1000)
dt = (time[1] - time[0]) * 1440.
Omega = np.linspace(0, 180, 100)
Omega_zoom = np.linspace(0, 3, 100)
duration = np.zeros((niter, len(Omega)))
duration_zoom = np.zeros((niter, len(Omega)))
for n in tqdm(range(niter)):
# First run is the mean model
if n == 0:
N = lambda mu, sigma: mu
else:
N = lambda mu, sigma: mu + sigma * np.random.randn()
# Instantiate the star
mstar = N(0.0802, 0.0073)
rstar = N(0.117, 0.0036)
star = Star('A', m = mstar, r = rstar, color = 'k')
# Planet b
per = N(1.51087081, 0.60e-6)
m = 0
while m <= 0:
m = N(0.85, 0.72)
inc = N(89.65, 0.245)
if inc > 90:
inc = 180 - inc
w = 360. * np.random.rand()
ecc = 1
while (ecc < 0) or (ecc >= 1):
ecc = N(0.0005, 0.0001)
mu = np.sqrt(0.7266 / 100)
sig = 0.5 * 0.0088 / 100 / mu
RpRs = N(mu, sig)
r = RpRs * rstar * RSUN / REARTH
b = Planet('b', m = m, per = per, inc = inc, r = r, t0 = 0.,
Omega = 0, w = w, ecc = ecc, color = 'r')
# Planet c
per = N(2.4218233, 0.17e-5)
m = 0
while m <= 0:
m = N(1.38, 0.61)
inc = N(89.67, 0.17)
if inc > 90:
inc = 180 - inc
w = 360. * np.random.rand()
ecc = 1
while (ecc < 0) or (ecc >= 1):
ecc = N(0.004, 0.001)
mu = np.sqrt(0.687 / 100)
sig = 0.5 * 0.010 / 100 / mu
RpRs = N(mu, sig)
r = RpRs * rstar * RSUN / REARTH
c = Planet('c', m = m, per = per, inc = inc, r = r, t0 = 0.,
Omega = 0, w = w, ecc = ecc, color = 'b')
# The system
system = System(star, b, c, nbody = True,
adaptive = True, quiet = True)
# Compute
for i in range(len(Omega)):
system.bodies[2].Omega = Omega[i]
system.compute_orbits(time)
duration[n,i] = \
dt * len(np.where(system.bodies[1].occultor == 4)[0])
# Compute (zoom)
for i in range(len(Omega_zoom)):
system.bodies[2].Omega = Omega_zoom[i]
system.compute_orbits(time)
duration_zoom[n,i] = \
dt * len(np.where(system.bodies[1].occultor == 4)[0])
# Plot the heatmap
fig = pl.figure(figsize = (6, 8))
ax = [pl.subplot2grid((3,1), (0,0), rowspan = 2),
pl.subplot2grid((3,1), (2,0))]
# Top plot
duration = duration.reshape(-1)
Omega = np.concatenate([Omega for i in range(niter)])
iszero = np.where(duration == 0)
duration = np.delete(duration, iszero)
Omega = np.delete(Omega, iszero)
corner.hist2d(duration, Omega, bins = 100, ax = ax[0], plot_datapoints = False)
# Zoom inset
duration_zoom = duration_zoom.reshape(-1)
Omega_zoom = np.concatenate([Omega_zoom for i in range(niter)])
iszero = np.where(duration_zoom == 0)
duration_zoom = np.delete(duration_zoom, iszero)
Omega_zoom = np.delete(Omega_zoom, iszero)
corner.hist2d(duration_zoom, Omega_zoom, bins = 100, ax = ax[1], plot_datapoints = False)
# Appearance
ax[0].set_ylabel(r'$\mathbf{\Delta\Omega}$ [degrees]',
fontsize = 14, fontweight = 'bold')
ax[1].set_ylabel(r'$\mathbf{\Delta\Omega}$ [degrees]',
fontsize = 14, fontweight = 'bold')
ax[1].set_xlabel('Duration of mutual transit [minutes]',
fontsize = 14, fontweight = 'bold')
ax[0].set_ylim(0, 180)
ax[1].set_ylim(0, 3)
return fig, ax
if __name__ == '__main__':
fig, ax = plot(1000)
fig.savefig("mutual_node.pdf")
pl.show()
|
rodlugerREPO_NAMEplanetplanetPATH_START.@planetplanet_extracted@planetplanet-master@scripts@mutual_node.py@.PATH_END.py
|
{
"filename": "event_list.py",
"repo_name": "wilkinsdr/pylag",
"repo_path": "pylag_extracted/pylag-master/pylag/event_list.py",
"type": "Python"
}
|
"""
pylag.event_list
Class for handling FITS event lists
v1.0 - 09/04/2018 - D.R. Wilkins
"""
from .simulator import *
from .lightcurve import *
from .lag_frequency_spectrum import *
from .lag_energy_spectrum import *
import numpy as np
try:
import astropy.io.fits as pyfits
except:
import pyfits
from scipy.stats import binned_statistic
import matplotlib.pyplot as plt
import matplotlib.colors as col
from .binning import *
from .lightcurve import *
class EventList(object):
def __init__(self, filename=None, hduname=None, hdunum=0, time_col='TIME', x_col='X', y_col='Y', pha_col='PI', time=None, x=None, y=None, pha=None):
self.time = np.array([])
self.x = np.array([])
self.y = np.array([])
self.pha = np.array([])
if filename is not None:
self.time, self.x, self.y, self.pha = self.read_fits(filename, hduname, hdunum, time_col, x_col, y_col, pha_col)
else:
if time is not None:
self.time = time
if x is not None:
self.x = x
if y is not None:
self.y = y
if pha is not None:
self.pha = pha
@staticmethod
def read_fits(filename, hduname=None, hdunum=0, time_col='TIME', x_col='X', y_col='Y', pha_col='PI'):
try:
fitsfile = pyfits.open(filename)
except:
raise AssertionError("pyLag EventList ERROR: Could not open FITS file " + filename)
try:
if hduname is not None:
hdu = fitsfile[hduname]
else:
hdu = fitsfile[hdunum]
except:
raise AssertionError("pyLag EventList ERROR: Could not open HDU")
try:
time = hdu.data[time_col]
pha = hdu.data[pha_col]
x = hdu.data[x_col]
y = hdu.data[y_col]
except:
raise AssertionError("pyLag EventList ERROR: Could not read event list columns")
fitsfile.close()
return time, x, y, pha
def lightcurve(self, tbin=10, time=None, calc_rate=True):
if time is None:
time = np.arange(self.time.min(), self.time.max(), tbin)
counts, _ = np.histogram(self.time, time)
if calc_rate:
rate = counts / tbin
err = rate * (np.sqrt(counts) / counts)
return LightCurve(t=time[:-1], r=rate, e=err)
else:
err = np.sqrt(counts)
return LightCurve(t=time[:-1], r=counts, e=err)
def spectrum(self, phabins=None, Nbins=50):
if phabins is None:
phabins = LogBinning(self.pha.min(), self.pha.max(), Nbins)
counts = phabins.num_points_in_bins(self.pha)
rate = counts / (self.time.max() - self.time.min())
err = rate * np.sqrt(counts) / counts
return Spectrum(en=phabins.bin_cent, spec=rate, err=err)
def show_image(self, bins=50):
img, x_edges, y_edges = np.histogram2d(self.x, self.y, bins=bins)
plt.imshow(img, norm=col.LogNorm(0.1, 1.1*img.max()), cmap='hot')
plt.show()
def plot_image(self, bins=50):
img, x_edges, y_edges = np.histogram2d(self.x, self.y, bins=bins)
x = 0.5*(x_edges[:-1] + x_edges[1:])
y = 0.5 * (y_edges[:-1] + y_edges[1:])
plt.pcolormesh(x, y, img, norm=col.LogNorm(0.1, 1.1*img.max()), cmap='hot')
plt.show()
def filter_region_circle(self, x0, y0, r):
event_r = np.sqrt((self.x - x0)**2 + (self.y - y0)**2)
filt_time = self.time[event_r < r]
filt_pha = self.pha[event_r < r]
filt_x = self.x[event_r < r]
filt_y = self.y[event_r < r]
return EventList(time=filt_time, x=filt_x, y=filt_y, pha=filt_pha)
def filter_energy(self, enmin, enmax):
enfilt = np.logical_and(self.pha >= enmin, self.pha < enmax)
filt_time = self.time[enfilt]
filt_pha = self.pha[enfilt]
filt_x = self.x[enfilt]
filt_y = self.y[enfilt]
return EventList(time=filt_time, x=filt_x, y=filt_y, pha=filt_pha)
def filter_time(self, tmin, tmax):
tfilt = np.logical_and(self.time >= tmin, self.time < tmax)
filt_time = self.time[tfilt]
filt_pha = self.pha[tfilt]
filt_x = self.x[tfilt]
filt_y = self.y[tfilt]
return EventList(time=filt_time, x=filt_x, y=filt_y, pha=filt_pha)
def bayesian_lightcurve(self, gamma=1):
import astropy.stats.bayesian_blocks
bin_edges = astropy.stats.bayesian_blocks(self.time, fitness='events', gamma=gamma)
tcent = 0.5*(bin_edges[1:] + bin_edges[:-1])
terr = tcent - bin_edges[:-1]
bin_rate = np.array([np.sum(np.logical_and(self.time>=tstart, self.time<tend)) for tstart, tend in zip(bin_edges[:-1], bin_edges[1:])]).astype(float)
bin_rate /= (bin_edges[1:] - bin_edges[:-1])
return VariableBinLightCurve(tcent, terr, bin_rate)
|
wilkinsdrREPO_NAMEpylagPATH_START.@pylag_extracted@pylag-master@pylag@event_list.py@.PATH_END.py
|
{
"filename": "mlp_ood.py",
"repo_name": "devinamhn/RadioGalaxies-BNNs",
"repo_path": "RadioGalaxies-BNNs_extracted/RadioGalaxies-BNNs-main/radiogalaxies_bnns/eval/ood/mlp_ood.py",
"type": "Python"
}
|
import torch
import torch.optim as optim
import numpy as np
import torch.nn.functional as F
import matplotlib.pyplot as plt
import csv
import scipy
import pandas as pd
import seaborn as sns
from radiogalaxies_bnns.inference.models import LeNet, LeNetDrop
import radiogalaxies_bnns.inference.utils as utils
from radiogalaxies_bnns.inference.datamodules import MNISTDataModule, MiraBestDataModule, testloader_mb_uncert
from radiogalaxies_bnns.eval.uncertainty.uncertainty import entropy_MI, overlapping, GMM_logits, calibration
def energy_function(logits, T = 1):
# print(-torch.logsumexp(pred_list_mbconf, dim = 2))
mean_energy = torch.mean(-torch.logsumexp(logits, dim = 2), dim = 0).detach().numpy()
std_energy = torch.std(-torch.logsumexp(logits, dim = 2), dim = 0).detach().numpy()
return mean_energy
def energy_function_mlp(logits, T = 1):
# print(-torch.logsumexp(pred_list_mbconf, dim = 2))
mean_energy = -torch.logsumexp(logits, dim = 1).detach().numpy()
# std_energy = torch.std(-torch.logsumexp(logits, dim = 2), dim = 0).detach().numpy()
return mean_energy
energy_score_df = pd.read_csv('radiogalaxies_bnns/results/ood/mlp_energy_scores.csv', index_col=0)
binwidth = 1#0.10
ylim_lower = 0
ylim_upper = 7
bin_lower = -30 #-80
bin_upper = 2
plt.clf()
plt.figure(dpi=300)
sns.histplot(energy_score_df[['MLP MB Conf', 'MLP Galaxy MNIST', 'MLP MIGHTEE']], binrange = [bin_lower, bin_upper],
binwidth = binwidth)
plt.ylim(ylim_lower, ylim_upper)
plt.xlabel('Negative Energy')#Negative
plt.xticks(np.arange(bin_lower, bin_upper, 5))
plt.savefig('radiogalaxies_bnns/results/ood/energy_hist_mlp.png')
exit()
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
config_dict, config = utils.parse_config('/share/nas2/dmohan/RadioGalaxies-BNNs/radiogalaxies_bnns/inference/nonBayesianCNN/config_cnn.txt')
# seed = 123 #config['training']['seed']
# torch.manual_seed(seed)
path_out = config_dict['output']['path_out']
datamodule = MiraBestDataModule(config_dict, hmc=False)
train_loader = datamodule.train_dataloader()
validation_loader = datamodule.val_dataloader()
test_loader = datamodule.test_dataloader()
# print('TEST DATASET')
# print(config_dict['output']['test_data'])
# test_loader, test_data1, data_type, test_data = testloader_mb_uncert(config_dict['output']['test_data'], config_dict['data']['datadir'])
model = LeNet(in_channels=1, output_size=2).to(device)
model_path = path_out + str(8)
model.load_state_dict(torch.load(model_path+'/model', map_location=torch.device(device) ))
# test_error = eval(test_loader)
# print(test_error)
print("MBCONF")
pred_list_mbconf= utils.get_logits_mlp(model, test_data_uncert='MBFRConfident', device=device, path='./dataMiraBest')
mean_energy_conf = energy_function_mlp(pred_list_mbconf)
print("MBUNCERT")
pred_list_mbuncert= utils.get_logits_mlp(model, test_data_uncert='MBFRUncertain', device=device, path='./dataMiraBest')
mean_energy_uncert = energy_function_mlp(pred_list_mbuncert)
print("MBHYBRID")
pred_list_mbhybrid = utils.get_logits_mlp(model, test_data_uncert='MBHybrid', device=device, path='./dataMiraBest')
mean_energy_hybrid = energy_function_mlp(pred_list_mbhybrid)
print("GalaxyMNIST")
pred_list_gal_mnist= utils.get_logits_mlp(model, test_data_uncert='Galaxy_MNIST', device=device, path='./dataGalaxyMNISTHighres')
mean_energy_galmnist =energy_function_mlp(pred_list_gal_mnist)
print("MIGHTEE")
pred_list_mightee = utils.get_logits_mlp(model, test_data_uncert='mightee', device=device, path='./')
mean_energy_mightee =energy_function_mlp(pred_list_mightee)
s1 = pd.Series(mean_energy_conf, name = 'MLP MB Conf')
s2 = pd.Series(mean_energy_uncert, name = 'MLP MB Uncert')
s3 = pd.Series(mean_energy_hybrid, name = 'MLP MB Hybrid')
s4 = pd.Series(mean_energy_galmnist, name = 'MLP Galaxy MNIST')
s5 = pd.Series(mean_energy_mightee, name = 'MLP MIGHTEE')
energy_score_df = pd.DataFrame([s1, s2, s3, s4, s5]).T
energy_score_df.to_csv('radiogalaxies_bnns/results/ood/mlp_energy_scores.csv')
exit()
|
devinamhnREPO_NAMERadioGalaxies-BNNsPATH_START.@RadioGalaxies-BNNs_extracted@RadioGalaxies-BNNs-main@radiogalaxies_bnns@eval@ood@mlp_ood.py@.PATH_END.py
|
{
"filename": "fs_tools.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/build/scripts/fs_tools.py",
"type": "Python"
}
|
from __future__ import print_function
import os
import platform
import sys
import shutil
import errno
# Explicitly enable local imports
# Don't forget to add imported scripts to inputs of the calling command!
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
import process_command_files as pcf
def link_or_copy(src, dst, trace={}):
if dst not in trace:
trace[dst] = src
try:
if platform.system().lower() == 'windows':
shutil.copy(src, dst)
else:
os.link(src, dst)
except OSError as e:
if e.errno == errno.EEXIST:
if dst in trace:
print(
'[[bad]]link_or_copy: copy collision found - tried to copy {} to {} which was copied earlier from {}[[rst]]'.format(
src, dst, trace[dst]
),
file=sys.stderr,
)
else:
print('[[bad]]link_or_copy: destination file already exists: {}[[rst]]'.format(dst), file=sys.stderr)
if e.errno == errno.ENOENT:
print('[[bad]]link_or_copy: source file doesn\'t exists: {}[[rst]]'.format(src), file=sys.stderr)
raise
if __name__ == '__main__':
mode = sys.argv[1]
args = pcf.get_args(sys.argv[2:])
if mode == 'copy':
shutil.copy(args[0], args[1])
elif mode == 'copy_tree_no_link':
dst = args[1]
shutil.copytree(
args[0], dst, ignore=lambda dirname, names: [n for n in names if os.path.islink(os.path.join(dirname, n))]
)
elif mode == 'copy_files':
src = args[0]
dst = args[1]
files = open(args[2]).read().strip().split()
for f in files:
s = os.path.join(src, f)
d = os.path.join(dst, f)
if os.path.exists(d):
continue
try:
os.makedirs(os.path.dirname(d))
except OSError:
pass
shutil.copy(s, d)
elif mode == 'copy_all_files':
src = args[0]
dst = args[1]
for root, _, files in os.walk(src):
for f in files:
if os.path.islink(os.path.join(root, f)):
continue
file_dst = os.path.join(dst, os.path.relpath(root, src), f)
if os.path.exists(file_dst):
continue
try:
os.makedirs(os.path.dirname(file_dst))
except OSError:
pass
shutil.copy(os.path.join(root, f), file_dst)
elif mode == 'rename_if_exists':
if os.path.exists(args[0]):
shutil.move(args[0], args[1])
elif mode == 'rename':
targetdir = os.path.dirname(args[1])
if targetdir and not os.path.exists(targetdir):
os.makedirs(os.path.dirname(args[1]))
shutil.move(args[0], args[1])
elif mode == 'remove':
for f in args:
try:
if os.path.isfile(f) or os.path.islink(f):
os.remove(f)
else:
shutil.rmtree(f)
except OSError:
pass
elif mode == 'link_or_copy':
link_or_copy(args[0], args[1])
elif mode == 'link_or_copy_to_dir':
assert len(args) > 1
start = 0
if args[0] == '--no-check':
if args == 2:
sys.exit()
start = 1
dst = args[-1]
for src in args[start:-1]:
link_or_copy(src, os.path.join(dst, os.path.basename(src)))
elif mode == 'cat':
with open(args[0], 'w') as dst:
for input_name in args[1:]:
with open(input_name) as src:
dst.write(src.read())
elif mode == 'md':
try:
os.makedirs(args[0])
except OSError:
pass
else:
raise Exception('unsupported tool %s' % mode)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@build@scripts@fs_tools.py@.PATH_END.py
|
{
"filename": "_textfont.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/graph_objs/scattergl/_textfont.py",
"type": "Python"
}
|
from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Textfont(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "scattergl"
_path_str = "scattergl.textfont"
_valid_props = {"color", "colorsrc", "family", "familysrc", "size", "sizesrc"}
# color
# -----
@property
def color(self):
"""
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
- A list or array of any of the above
Returns
-------
str|numpy.ndarray
"""
return self["color"]
@color.setter
def color(self, val):
self["color"] = val
# colorsrc
# --------
@property
def colorsrc(self):
"""
Sets the source reference on Chart Studio Cloud for color .
The 'colorsrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["colorsrc"]
@colorsrc.setter
def colorsrc(self, val):
self["colorsrc"] = val
# family
# ------
@property
def family(self):
"""
HTML font family - the typeface that will be applied by the web
browser. The web browser will only be able to apply a font if
it is available on the system which it operates. Provide
multiple font families, separated by commas, to indicate the
preference in which to apply fonts if they aren't available on
the system. The Chart Studio Cloud (at https://chart-
studio.plotly.com or on-premise) generates images on a server,
where only a select number of fonts are installed and
supported. These include "Arial", "Balto", "Courier New",
"Droid Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas
One", "Old Standard TT", "Open Sans", "Overpass", "PT Sans
Narrow", "Raleway", "Times New Roman".
The 'family' property is a string and must be specified as:
- A non-empty string
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
str|numpy.ndarray
"""
return self["family"]
@family.setter
def family(self, val):
self["family"] = val
# familysrc
# ---------
@property
def familysrc(self):
"""
Sets the source reference on Chart Studio Cloud for family .
The 'familysrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["familysrc"]
@familysrc.setter
def familysrc(self, val):
self["familysrc"] = val
# size
# ----
@property
def size(self):
"""
The 'size' property is a number and may be specified as:
- An int or float in the interval [1, inf]
- A tuple, list, or one-dimensional numpy array of the above
Returns
-------
int|float|numpy.ndarray
"""
return self["size"]
@size.setter
def size(self, val):
self["size"] = val
# sizesrc
# -------
@property
def sizesrc(self):
"""
Sets the source reference on Chart Studio Cloud for size .
The 'sizesrc' property must be specified as a string or
as a plotly.grid_objs.Column object
Returns
-------
str
"""
return self["sizesrc"]
@sizesrc.setter
def sizesrc(self, val):
self["sizesrc"] = val
# Self properties description
# ---------------------------
@property
def _prop_descriptions(self):
return """\
color
colorsrc
Sets the source reference on Chart Studio Cloud for
color .
family
HTML font family - the typeface that will be applied by
the web browser. The web browser will only be able to
apply a font if it is available on the system which it
operates. Provide multiple font families, separated by
commas, to indicate the preference in which to apply
fonts if they aren't available on the system. The Chart
Studio Cloud (at https://chart-studio.plotly.com or on-
premise) generates images on a server, where only a
select number of fonts are installed and supported.
These include "Arial", "Balto", "Courier New", "Droid
Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas
One", "Old Standard TT", "Open Sans", "Overpass", "PT
Sans Narrow", "Raleway", "Times New Roman".
familysrc
Sets the source reference on Chart Studio Cloud for
family .
size
sizesrc
Sets the source reference on Chart Studio Cloud for
size .
"""
def __init__(
self,
arg=None,
color=None,
colorsrc=None,
family=None,
familysrc=None,
size=None,
sizesrc=None,
**kwargs
):
"""
Construct a new Textfont object
Sets the text font.
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of
:class:`plotly.graph_objs.scattergl.Textfont`
color
colorsrc
Sets the source reference on Chart Studio Cloud for
color .
family
HTML font family - the typeface that will be applied by
the web browser. The web browser will only be able to
apply a font if it is available on the system which it
operates. Provide multiple font families, separated by
commas, to indicate the preference in which to apply
fonts if they aren't available on the system. The Chart
Studio Cloud (at https://chart-studio.plotly.com or on-
premise) generates images on a server, where only a
select number of fonts are installed and supported.
These include "Arial", "Balto", "Courier New", "Droid
Sans",, "Droid Serif", "Droid Sans Mono", "Gravitas
One", "Old Standard TT", "Open Sans", "Overpass", "PT
Sans Narrow", "Raleway", "Times New Roman".
familysrc
Sets the source reference on Chart Studio Cloud for
family .
size
sizesrc
Sets the source reference on Chart Studio Cloud for
size .
Returns
-------
Textfont
"""
super(Textfont, self).__init__("textfont")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = _copy.copy(arg)
else:
raise ValueError(
"""\
The first argument to the plotly.graph_objs.scattergl.Textfont
constructor must be a dict or
an instance of :class:`plotly.graph_objs.scattergl.Textfont`"""
)
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
# Populate data dict with properties
# ----------------------------------
_v = arg.pop("color", None)
_v = color if color is not None else _v
if _v is not None:
self["color"] = _v
_v = arg.pop("colorsrc", None)
_v = colorsrc if colorsrc is not None else _v
if _v is not None:
self["colorsrc"] = _v
_v = arg.pop("family", None)
_v = family if family is not None else _v
if _v is not None:
self["family"] = _v
_v = arg.pop("familysrc", None)
_v = familysrc if familysrc is not None else _v
if _v is not None:
self["familysrc"] = _v
_v = arg.pop("size", None)
_v = size if size is not None else _v
if _v is not None:
self["size"] = _v
_v = arg.pop("sizesrc", None)
_v = sizesrc if sizesrc is not None else _v
if _v is not None:
self["sizesrc"] = _v
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@graph_objs@scattergl@_textfont.py@.PATH_END.py
|
{
"filename": "plot_iris_exercise.py",
"repo_name": "scikit-learn/scikit-learn",
"repo_path": "scikit-learn_extracted/scikit-learn-main/examples/exercises/plot_iris_exercise.py",
"type": "Python"
}
|
"""
================================
SVM Exercise
================================
A tutorial exercise for using different SVM kernels.
This exercise is used in the :ref:`using_kernels_tut` part of the
:ref:`supervised_learning_tut` section of the :ref:`stat_learn_tut_index`.
"""
# Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
import matplotlib.pyplot as plt
import numpy as np
from sklearn import datasets, svm
iris = datasets.load_iris()
X = iris.data
y = iris.target
X = X[y != 0, :2]
y = y[y != 0]
n_sample = len(X)
np.random.seed(0)
order = np.random.permutation(n_sample)
X = X[order]
y = y[order].astype(float)
X_train = X[: int(0.9 * n_sample)]
y_train = y[: int(0.9 * n_sample)]
X_test = X[int(0.9 * n_sample) :]
y_test = y[int(0.9 * n_sample) :]
# fit the model
for kernel in ("linear", "rbf", "poly"):
clf = svm.SVC(kernel=kernel, gamma=10)
clf.fit(X_train, y_train)
plt.figure()
plt.clf()
plt.scatter(
X[:, 0], X[:, 1], c=y, zorder=10, cmap=plt.cm.Paired, edgecolor="k", s=20
)
# Circle out the test data
plt.scatter(
X_test[:, 0], X_test[:, 1], s=80, facecolors="none", zorder=10, edgecolor="k"
)
plt.axis("tight")
x_min = X[:, 0].min()
x_max = X[:, 0].max()
y_min = X[:, 1].min()
y_max = X[:, 1].max()
XX, YY = np.mgrid[x_min:x_max:200j, y_min:y_max:200j]
Z = clf.decision_function(np.c_[XX.ravel(), YY.ravel()])
# Put the result into a color plot
Z = Z.reshape(XX.shape)
plt.pcolormesh(XX, YY, Z > 0, cmap=plt.cm.Paired)
plt.contour(
XX,
YY,
Z,
colors=["k", "k", "k"],
linestyles=["--", "-", "--"],
levels=[-0.5, 0, 0.5],
)
plt.title(kernel)
plt.show()
|
scikit-learnREPO_NAMEscikit-learnPATH_START.@scikit-learn_extracted@scikit-learn-main@examples@exercises@plot_iris_exercise.py@.PATH_END.py
|
{
"filename": "DiaSources.py",
"repo_name": "lsst-uk/lasair-lsst",
"repo_path": "lasair-lsst_extracted/lasair-lsst-main/utility/DP03/lasair_schema/DiaSources.py",
"type": "Python"
}
|
schema = {
"name": "DiaSources",
"fields": [
{
"name": "diaSourceId",
"type": "long",
"doc": "Unique id."
},
{
"name": "ccdVisitId",
"type": "long",
"doc": "Id of the ccdVisit where this diaSource was measured. Note that we are allowing a diaSource to belong to multiple amplifiers, but it may not span multiple ccds."
},
{
"name": "diaObjectId",
"type": "long",
"doc": "Id of the diaObject this source was associated with, if any. If not, it is set to NULL (each diaSource will be associated with either a diaObject or ssObject)."
},
{
"name": "ssObjectId",
"type": "long",
"doc": "Id of the ssObject this source was associated with, if any. If not, it is set to NULL (each diaSource will be associated with either a diaObject or ssObject)."
},
{
"name": "nameTrue",
"type": "string",
"doc": "MPC or simulation designation of the moving object"
},
{
"name": "ssObjectReassocTime",
"type": "timestamp",
"doc": "Time when this diaSource was reassociated from diaObject to ssObject (if such reassociation happens, otherwise NULL)."
},
{
"name": "midPointMjdTai",
"type": "double",
"doc": "Effective mid-exposure time for this diaSource."
},
{
"name": "ra",
"type": "double",
"doc": "RA-coordinate of the center of this diaSource."
},
{
"name": "raErr",
"type": "float",
"doc": "Uncertainty of ra."
},
{
"name": "decl",
"type": "double",
"doc": "Dec-coordinate of the center of this diaSource."
},
{
"name": "decErr",
"type": "float",
"doc": "Uncertainty of dec."
},
{
"name": "ra_dec_Cov",
"type": "float",
"doc": "Covariance between ra and dec."
},
{
"name": "snr",
"type": "float",
"doc": "The signal-to-noise ratio at which this source was detected in the difference image."
},
{
"name": "band",
"type": "string",
"doc": "Name of the band used to take the exposure where this source was measured"
},
{
"name": "mag",
"type": "float",
"doc": "Magnitude. This is a placeholder and should be replaced by flux."
},
{
"name": "magErr",
"type": "float",
"doc": "Magnitude error. This is a placeholder and should be replaced by flux error."
},
{
"name": "magTrueVband",
"type": "float",
"doc": "True (noiseless) V-band magnitude of the simulated diaSource"
},
{
"name": "raTrue",
"type": "double",
"doc": "True (noiseless) right ascension of the simulated diaSource"
},
{
"name": "decTrue",
"type": "double",
"doc": "True (noiseless) declination of the simulated diaSource"
}
],
"indexes": ["PRIMARY KEY (ssObjectId, diaSourceId)"]
}
|
lsst-ukREPO_NAMElasair-lsstPATH_START.@lasair-lsst_extracted@lasair-lsst-main@utility@DP03@lasair_schema@DiaSources.py@.PATH_END.py
|
{
"filename": "decomposer_base.py",
"repo_name": "PAHdb/pyPAHdb",
"repo_path": "pyPAHdb_extracted/pyPAHdb-master/pypahdb/decomposer_base.py",
"type": "Python"
}
|
#!/usr/bin/env python3
"""
decomposer_base.py
Using a precomputed matrix of theoretically calculated
PAH emission spectra, an input spectrum is fitted and decomposed into
contributing PAH subclasses using a non-negative least-squares (NNLS)
approach.
This file is part of pypahdb - see the module docs for more
information.
"""
import multiprocessing
import os
import pickle
from functools import partial
from urllib.request import urlretrieve
import importlib_resources
import numpy as np
from tqdm import tqdm
from astropy import units as u
from scipy import optimize
from specutils import Spectrum1D
SMALL_SIZE = 50
MEDIUM_SIZE = 70
def _decomposer_anion(w, m=None, p=None):
"""Do the anion decomposition in multiprocessing."""
return m.dot(w * (p < 0).astype(float))
def _decomposer_neutral(w, m=None, p=None):
"""Do the neutral decomposition in multiprocessing."""
return m.dot(w * (p == 0).astype(float))
def _decomposer_cation(w, m=None, p=None):
"""Do the cation decomposition in multiprocessing."""
return m.dot(w * (p > 0).astype(float))
def _decomposer_large(w, m=None, p=None):
"""Do the actual large decomposition in multiprocessing."""
return m.dot(w * (p > MEDIUM_SIZE).astype(float))
def _decomposer_medium(w, m=None, p=None):
"""Do the actual large decomposition in multiprocessing."""
return m.dot(w * ((p > SMALL_SIZE) & (p <= MEDIUM_SIZE)).astype(float))
def _decomposer_small(w, m=None, p=None):
"""Do the small decomposition in multiprocessing."""
return m.dot(w * (p <= 50).astype(float))
def _decomposer_fit(w, m=None):
"""Do the matrix manipulation to obtain the total fit in
multiprocessing."""
return m.dot(w)
def _decomposer_interp(fp, x=None, xp=None):
"""Do the grid interpolation in multiprocessing."""
return np.interp(x, xp, fp)
def _decomposer_nnls(y, m=None):
"""Do the NNLS in multiprocessing."""
return optimize.nnls(m, y)
class DecomposerBase(object):
"""Fit and decompose spectrum.
Attributes:
spectrum: A spectrum to fit and decompose.
"""
def __init__(self, spectrum):
"""Construct a decomposer object.
Args:
spectrum (specutil.Spectrum1D): The spectrum to fit and decompose.
"""
self._mask = None
self._yfit = None
self._yerror = None
self._charge_fractions = None
self._size_fractions = None
self._charge = None
self._size = None
self._nc = None
# Check if spectrum is a Spectrum1D.
if not isinstance(spectrum, Spectrum1D):
print("spectrum is not a specutils.Spectrum1D")
return None
self.spectrum = spectrum
# Convert units of spectrum to wavenumber and flux (density).
abscissa = self.spectrum.spectral_axis.to(
1.0 / u.cm, equivalencies=u.spectral()
)
try:
ordinate = self.spectrum.flux.to(
u.Unit("MJy/sr"), equivalencies=u.spectral()
).T
except u.UnitConversionError:
ordinate = self.spectrum.flux.to(u.Unit("Jy"), equivalencies=u.spectral()).T
pass
# For clarity, define a few quantities.
n_elements_yz = ordinate.shape[1] * ordinate.shape[2]
pool_shape = np.reshape(ordinate, (ordinate.shape[0], n_elements_yz))
# Avoid fitting -zero- spectra.
self._mask = np.where(np.sum(pool_shape, axis=0) > 0.0)[0]
if self._mask.size == 0:
print("spectral data is all zeros.")
return None
# Download the precomputed data if not present
remote_pkl = "https://www.astrochemistry.org/pahdb/pypahdb/pickle.php"
if os.getenv("GITHUB_ACTIONS") == "true":
remote_pkl += "?github_actions=true"
local_pkl = (
importlib_resources.files("pypahdb") / "resources/precomputed.pkl"
)
if not os.path.isfile(local_pkl):
def hook(t):
last_b = [0]
def inner(b=1, bsize=1, tsize=None):
if tsize is not None:
t.total = tsize
t.update((b - last_b[0]) * bsize)
last_b[0] = b
return inner
print("downloading pre-computed matrix")
with tqdm(
unit="B",
unit_scale=True,
leave=True,
miniters=1,
) as t:
urlretrieve(
remote_pkl, filename=local_pkl, reporthook=hook(t), data=None
)
with open(local_pkl, "rb") as f:
self._precomputed = pickle.load(f, encoding="latin1")
# Linearly interpolate the precomputed spectra onto the
# frequency grid of the input spectrum.
decomposer_interp = partial(
_decomposer_interp, x=abscissa, xp=self._precomputed["abscissa"] / u.cm
)
# Create multiprocessing pool.
if os.name == "posix":
multiprocessing.set_start_method("fork", force=True)
pool = multiprocessing.Pool(processes=multiprocessing.cpu_count() - 1)
self._matrix = pool.map(decomposer_interp, self._precomputed["matrix"].T)
pool.close()
pool.join()
self._matrix = np.array(self._matrix).T
# Copy and normalize the matrix.
m = self._matrix.copy()
scl = m.max()
m /= scl
# Setup the fitter.
decomposer_nnls = partial(_decomposer_nnls, m=m)
pool = multiprocessing.Pool(processes=multiprocessing.cpu_count() - 1)
# Perform the fit.
weights, _ = list(zip(*pool.map(decomposer_nnls, pool_shape[:, self._mask].T)))
pool.close()
pool.join()
# Rescale weights.
weights = np.array(weights)
weights /= scl
# Set weights.
self._weights = np.zeros((pool_shape.shape[1], self._matrix.shape[1]))
self._weights[self._mask] = np.array(weights)
# Reshape results.
new_shape = ordinate.shape[1:] + (self._matrix.shape[1],)
self._weights = np.transpose(np.reshape(self._weights, new_shape), (2, 0, 1))
def _fit(self):
"""Return the fit.
Returns:
self._yfit (quantity.Quantity): The fit.
"""
# Lazy Instantiation.
if self._yfit is None:
decomposer_fit = partial(_decomposer_fit, m=self._matrix)
# Create multiprocessing pool.
n_cpus = multiprocessing.cpu_count()
pool = multiprocessing.Pool(processes=n_cpus - 1)
# Convenience defintions.
ordinate = self.spectrum.flux.T
wt_elements_yz = self._weights.shape[1] * self._weights.shape[2]
wt_shape = np.reshape(
self._weights, (self._weights.shape[0], wt_elements_yz)
)
# Perform the fit.
self._yfit = np.zeros((wt_elements_yz, ordinate.shape[0]))
self._yfit[self._mask, :] = np.array(
pool.map(decomposer_fit, wt_shape[:, self._mask].T)
)
pool.close()
pool.join()
# Reshape results.
new_shape = ordinate.shape[1:] + (ordinate.shape[0],)
self._yfit = np.transpose(np.reshape(self._yfit, new_shape), (2, 0, 1))
# Set units.
self._yfit *= self.spectrum.flux.unit
return self._yfit
def _error(self):
"""Return the error as ∫|residual|dν / ∫observation dν.
Returns:
self._yerror (quantity.Quantity): The fit error.
"""
# Lazy Instantiation.
if self._yerror is None:
# Convert units of spectral_axis to wavenumber.
abscissa = self.spectrum.spectral_axis.to(
1.0 / u.cm, equivalencies=u.spectral()
)
# Convenience defintion.
ordinate = self.spectrum.flux.T
# Use Trapezium rule to integrate the absolute of the residual
# and the observations.
abs_residual = np.trapz(np.abs(self.fit - ordinate), x=abscissa, axis=0)
total = np.trapz(ordinate, x=abscissa, axis=0)
# Initialize result to NaN.
self._yerror = np.empty(ordinate.shape[1:])
self._yerror.fill(np.nan)
# Avoid division by -zero-.
nonzero = np.nonzero(total)
# Calculate the error.
self._yerror[nonzero] = abs_residual[nonzero] / total[nonzero]
# Set units.
self._yerror *= u.dimensionless_unscaled
return self._yerror
def _get_charge_fractions(self):
"""Return the charge fraction.
Returns:
self._charge_fraction (dict): Fraction of neutral,
cation and anion PAHs from fit.
"""
# Lazy Instantiation.
if self._charge_fractions is None:
# Compute ionized fraction.
charge_matrix = self._precomputed["properties"]["charge"]
neutrals = (charge_matrix == 0).astype(float)[:, None, None]
cations = (charge_matrix > 0).astype(float)[:, None, None]
anions = (charge_matrix < 0).astype(float)[:, None, None]
neutral_fraction = np.sum(self._weights * neutrals, axis=0)
cation_fraction = np.sum(self._weights * cations, axis=0)
anion_fraction = np.sum(self._weights * anions, axis=0)
neutral_fraction *= u.dimensionless_unscaled
cation_fraction *= u.dimensionless_unscaled
anion_fraction *= u.dimensionless_unscaled
charge_sum = neutral_fraction + cation_fraction + anion_fraction
nonzero = np.nonzero(charge_sum)
neutral_fraction[nonzero] /= charge_sum[nonzero]
cation_fraction[nonzero] /= charge_sum[nonzero]
anion_fraction[nonzero] /= charge_sum[nonzero]
# Make dictionary of charge fractions.
self._charge_fractions = {
"neutral": neutral_fraction,
"cation": cation_fraction,
"anion": anion_fraction,
}
return self._charge_fractions
def _get_average_nc(self):
"""Return the average number of carbon atoms.
Returns:
self._nc (quantity.Quantity): Average number of carbon atoms
"""
# Lazy Instantiation.
if self._nc is None:
size_array = self._precomputed["properties"]["size"]
size = size_array.astype(float)[:, None, None]
self._nc = np.sum(self._weights * size, axis=0)
nc_sum = np.sum(self._weights, axis=0)
nonzero = np.nonzero(nc_sum)
self._nc[nonzero] / nc_sum[nonzero]
self._nc *= u.dimensionless_unscaled
return self._nc
def _get_size_fractions(self):
"""Return the size fraction.
Returns:
self._size_fractions (dict): Size fractions from fit.
"""
# Lazy Instantiation.
if self._size_fractions is None:
# Compute large fraction.
size_matrix = self._precomputed["properties"]["size"]
large = (size_matrix > MEDIUM_SIZE).astype(float)[:, None, None]
large_fraction = np.sum(self._weights * large, axis=0)
large_fraction *= u.dimensionless_unscaled
# Compute medium fraction between 50 and 70.
medium = ((size_matrix > SMALL_SIZE) & (size_matrix <= MEDIUM_SIZE)).astype(float)[:, None, None]
medium_fraction = np.sum(self._weights * medium, axis=0)
medium_fraction *= u.dimensionless_unscaled
# Compute small fraction between 20 and 50.
small = (size_matrix <= SMALL_SIZE).astype(float)[:, None, None]
small_fraction = (np.sum(self._weights * small, axis=0))
small_fraction *= u.dimensionless_unscaled
size_sum = large_fraction + medium_fraction + small_fraction
nonzero = np.nonzero(size_sum)
# Update the size fractions.
large_fraction[nonzero] /= size_sum[nonzero]
medium_fraction[nonzero] /= size_sum[nonzero]
small_fraction[nonzero] /= size_sum[nonzero]
# Make dictionary of size fractions.
self._size_fractions = {
"large": large_fraction,
"medium": medium_fraction,
"small": small_fraction,
}
return self._size_fractions
def _get_charge(self):
"""Return the spectral charge breakdown from fit.
Returns:
self._charge (dictionary): Dictionary with keys
'anion', 'neutral' and 'cation'.
"""
# TODO: Should self._charge be a Spectrum1D-object?
# Lazy Instantiation.
if self._charge is None:
decomposer_anion = partial(
_decomposer_anion,
m=self._matrix,
p=self._precomputed["properties"]["charge"],
)
decomposer_neutral = partial(
_decomposer_neutral,
m=self._matrix,
p=self._precomputed["properties"]["charge"],
)
decomposer_cation = partial(
_decomposer_cation,
m=self._matrix,
p=self._precomputed["properties"]["charge"],
)
# Create multiprocessing pool.
n_cpus = multiprocessing.cpu_count()
pool = multiprocessing.Pool(processes=n_cpus - 1)
# Convenience definitions.
wt_shape_yz = self._weights.shape[1] * self._weights.shape[2]
new_dims = np.reshape(self._weights, (self._weights.shape[0], wt_shape_yz))
ordinate = self.spectrum.flux.T
mappings = {
"anion": decomposer_anion,
"neutral": decomposer_neutral,
"cation": decomposer_cation,
}
# Map the charge arrays.
self._charge = {
charge: np.zeros((wt_shape_yz, ordinate.shape[0]))
for charge in mappings.keys()
}
for charge, func in mappings.items():
self._charge[charge][self._mask, :] = np.array(
pool.map(func, new_dims[:, self._mask].T)
)
pool.close()
pool.join()
# Reshape results and set units.
interior = ordinate.shape[1:] + (ordinate.shape[0],)
for charge, spectrum in self._charge.items():
self._charge[charge] = (
np.transpose(np.reshape(spectrum, interior), (2, 0, 1))
* self.spectrum.flux.unit
)
return self._charge
def _get_size(self):
"""Return the spectral size breakdown from fit.
Returns:
self._size (dictionary): Dictionary with keys
'large', 'medium', 'small'.
"""
# TODO: Should self._size be a Spectrum1D-object?
# Lazy Instantiation.
if self._size is None:
decomposer_large = partial(
_decomposer_large,
m=self._matrix,
p=self._precomputed["properties"]["size"],
)
decomposer_medium = partial(
_decomposer_medium,
m=self._matrix,
p=self._precomputed["properties"]["size"],
)
decomposer_small = partial(
_decomposer_small,
m=self._matrix,
p=self._precomputed["properties"]["size"],
)
# Create multiprocessing pool.
n_cpus = multiprocessing.cpu_count()
pool = multiprocessing.Pool(processes=n_cpus - 1)
# Convenience definitions.
wt_shape_yz = self._weights.shape[1] * self._weights.shape[2]
new_dims = np.reshape(self._weights, (self._weights.shape[0], wt_shape_yz))
ordinate = self.spectrum.flux.T
mappings = {
"small": decomposer_small,
"medium": decomposer_medium,
"large": decomposer_large,
}
# Map the size arrays.
self._size = {
size: np.zeros((wt_shape_yz, ordinate.shape[0]))
for size in mappings.keys()
}
for size, func in mappings.items():
self._size[size][self._mask, :] = np.array(
pool.map(func, new_dims[:, self._mask].T)
)
pool.close()
pool.join()
# Reshape results and set units.
interior = ordinate.shape[1:] + (ordinate.shape[0],)
for size, spectrum in self._size.items():
self._size[size] = (
np.transpose(np.reshape(spectrum, interior), (2, 0, 1))
* self.spectrum.flux.unit
)
return self._size
# Make fit a property.
fit = property(_fit)
# Make error a property.
error = property(_error)
# Make charge fractions a property.
charge_fractions = property(_get_charge_fractions)
# Make size fractions a property.
size_fractions = property(_get_size_fractions)
# Make charge a property.
charge = property(_get_charge)
# Make size a property.
size = property(_get_size)
# Make nc a property.
nc = property(_get_average_nc)
|
PAHdbREPO_NAMEpyPAHdbPATH_START.@pyPAHdb_extracted@pyPAHdb-master@pypahdb@decomposer_base.py@.PATH_END.py
|
{
"filename": "layer.py",
"repo_name": "huggingface/peft",
"repo_path": "peft_extracted/peft-main/src/peft/tuners/xlora/layer.py",
"type": "Python"
}
|
# Copyright 2024-present the HuggingFace Inc. team.
#
# 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.
from __future__ import annotations
from typing import Any, Callable, Optional
import torch
import torch.nn as nn
from torch import Tensor
from peft.tuners import lora
from .config import XLoraConfig
class XLoraLayer:
"""
A XLoraLayer wraps any LoraLayer and performs the XLora operation on the LoRA adaptors specified. Its primary API
is the forward method, which uses the scalings to execute the XLora algorithm.
"""
def __init__(
self,
model: nn.Module, # XLoraModel
target: lora.LoraLayer,
target_forward: Callable[..., Any],
layer_number: int,
config: XLoraConfig,
) -> None:
self.model = model
self.target_forward = target_forward
self.target = target
self.layer_number = layer_number
self.config = config
"""
Apply the scalings for the adapter.
"""
@staticmethod
def apply_scalings_to_x(x: torch.Tensor, scalings_layer: torch.Tensor, adapter: int) -> torch.Tensor:
# scalings_layer = [batch_size, seq_len, n_classes]
scalings = scalings_layer[:, :, adapter].unsqueeze(-1)
# scalings_layer = [batch_size, seq_len, 1]
return x * scalings
"""
Get the scalings for this layer, potentially applying topk and topk+softmax. This is called before
`apply_scalings_to_x`
"""
def get_maybe_topk_scalings(self, scalings) -> torch.Tensor:
# xlora_scalings = [batch_size, seq_len, n_classes]
xlora_scalings: Tensor = scalings[:, :, self.layer_number, :] # type: ignore
if self.config.top_k_lora is not None:
_, topk_indices = torch.topk(xlora_scalings, k=self.config.top_k_lora, dim=-1)
# Mask the topk to True, the rest to False
mask = torch.zeros_like(xlora_scalings, dtype=torch.bool)
mask.scatter_(-1, topk_indices, True)
xlora_scalings = xlora_scalings * mask.to(xlora_scalings.dtype)
if self.config.enable_softmax_topk:
nonzero_mask = xlora_scalings != 0
softmax_res_nonzero = torch.softmax(xlora_scalings[nonzero_mask], dim=-1)
xlora_scalings[nonzero_mask] = softmax_res_nonzero
return xlora_scalings
class XLoraLinearLayer(XLoraLayer):
def __init__(
self,
model: nn.Module,
target: lora.Linear,
target_forward: Callable[..., Any],
layer_number: int,
config: XLoraConfig,
) -> None:
super().__init__(model, target, target_forward, layer_number, config)
def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
"""
This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
method must be created (bound to an instance of the XLoraLayer class).
"""
previous_dtype = x.dtype
if scalings is not None:
xlora_scalings = self.get_maybe_topk_scalings(scalings)
result = self.target.base_layer(x, *args, **kwargs)
# Ignore if disabled. We want to make sure this is always run.
if not self.target.merged:
for adapter_n, active_adapter in enumerate(self.target.active_adapters):
# TODO: implement X-LoRA with Lora+Dora layers
if self.target.use_dora[active_adapter]:
raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
if active_adapter not in self.target.lora_A.keys():
continue
lora_A = self.target.lora_A[active_adapter]
lora_B = self.target.lora_B[active_adapter]
dropout = self.target.lora_dropout[active_adapter]
scaling = self.target.scaling[active_adapter]
x = x.to(lora_A.weight.dtype) # type: ignore
if scalings is not None:
x_mod = self.apply_scalings_to_x(x, xlora_scalings, adapter_n)
scaling_weight = self.config.global_scaling_weight
else:
x_mod = x
scaling_weight = 1
result += lora_B(lora_A(dropout(x_mod))) * scaling * scaling_weight
result = result.to(previous_dtype)
return result
class XLoraEmbeddingLayer(XLoraLayer):
def __init__(
self,
model: nn.Module,
target: lora.Embedding,
target_forward: Callable[..., Any],
layer_number: int,
config: XLoraConfig,
) -> None:
super().__init__(model, target, target_forward, layer_number, config)
def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
"""
This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
method must be created (bound to an instance of the XLoraLayer class).
"""
if scalings is not None:
xlora_scalings = self.get_maybe_topk_scalings(scalings)
result = self.target.base_layer(x, *args, **kwargs)
# Ignore if disabled. We want to make sure this is always run.
if not self.target.merged:
for adapter_n, active_adapter in enumerate(self.target.active_adapters):
# TODO: implement X-LoRA with Lora+Dora layers
if self.target.use_dora.get(active_adapter, False):
raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
if active_adapter not in self.target.lora_embedding_A:
continue
embedding_A = self.target.lora_embedding_A[active_adapter].T
embedding_B = self.target.lora_embedding_B[active_adapter].T
scaling = self.target.scaling[active_adapter]
after_A = self.target._embed(x, embedding_A) # type: ignore
if scalings is not None:
after_A_mod = self.apply_scalings_to_x(after_A, xlora_scalings, adapter_n)
scaling_weight = self.config.global_scaling_weight
else:
after_A_mod = after_A
scaling_weight = 1
result += (after_A_mod @ embedding_B) * scaling * scaling_weight
return result
class XLoraConv2dLayer(XLoraLayer):
def __init__(
self,
model: nn.Module,
target: lora.Conv2d,
target_forward: Callable[..., Any],
layer_number: int,
config: XLoraConfig,
) -> None:
super().__init__(model, target, target_forward, layer_number, config)
def forward(self, x: Tensor, *args: Any, scalings: Optional[Tensor] = None, **kwargs: Any) -> Tensor:
"""
This method is designed to be a drop-in-replacement for the LoRA layers' .forward method. To use it, a bound
method must be created (bound to an instance of the XLoraLayer class).
"""
previous_dtype = x.dtype
if scalings is not None:
xlora_scalings = self.get_maybe_topk_scalings(scalings)
result = self.target.base_layer(x, *args, **kwargs)
# Ignore if disabled. We want to make sure this is always run.
if not self.target.merged:
for adapter_n, active_adapter in enumerate(self.target.active_adapters):
# TODO: implement X-LoRA with Lora+Dora layers
if self.target.use_dora[active_adapter]:
raise ValueError("X-LoRA currently does not support LoRA layers with DoRA")
if active_adapter not in self.target.lora_A.keys():
continue
lora_A = self.target.lora_A[active_adapter]
lora_B = self.target.lora_B[active_adapter]
dropout = self.target.lora_dropout[active_adapter]
scaling = self.target.scaling[active_adapter]
x = x.to(lora_A.weight.dtype) # type: ignore
if scalings is not None:
x_mod = self.apply_scalings_to_x(x, xlora_scalings, adapter_n)
scaling_weight = self.config.global_scaling_weight
else:
x_mod = x
scaling_weight = 1
result += lora_B(lora_A(dropout(x_mod))) * scaling * scaling_weight
result = result.to(previous_dtype)
return result
|
huggingfaceREPO_NAMEpeftPATH_START.@peft_extracted@peft-main@src@peft@tuners@xlora@layer.py@.PATH_END.py
|
{
"filename": "index.md",
"repo_name": "nichollsh/AGNI",
"repo_path": "AGNI_extracted/AGNI-main/docs/src/examples/index.md",
"type": "Markdown"
}
|
# Example outputs
## Pure steam runaway greenhouse effect
By assuming the atmosphere temperature profile follows a dry adiabat and the water vapour-condensate coexistance curve defined by the Clausius-Claperyron relation, we see a characteristic relationship between the outgoing longwave radiation (OLR) and the surface temperature ($T_s$). Initially OLR increases with $T_s$, but as the condensing layer (which is independent of $T_s$) overlaps with the photosphere, OLR and $T_s$ decouple. Eventually the atmosphere reaches a dry post-runaway state, and OLR increases rapidly with $T_s$.
```@raw html
<img src="assets/runaway/curve.png" width=75% class="center"/>
```
You can find a Jupyter notebook which reproduces this result in the [tutorials directory](https://github.com/nichollsh/AGNI/tree/main/tutorials) of the repository.
## Prescribed convective case
In this case, a temperature profile is prescribed to follow a dry adiabat from the surface to a moist region, and then a pseudoadiabat to the top of the atmosphere. This is in line with previous works and the OLR curve above.
```@raw html
<img src="assets/nosolve/plot_ptprofile.png" width=62% class="center"/>
```
Radiative fluxes are then calculated according to this temperature profile. Because the profile is prescribed, the fluxes are not balanced locally or globally across the column.
```@raw html
<img src="assets/nosolve/plot_fluxes.png" width=62% class="center"/>
```
## Radiative-convective solution
Instead, we can model an atmosphere such that that energy is globally and locally conserved. Convection is parameterised using mixing length theory in this case, allowing the system to be solved using a Newton-Raphson method. In the convective region at ~0.1 bar, we can see that the radiative fluxes and convective fluxes entirely cancel, because AGNI was asked to solve for a case with zero total flux transport.
```@raw html
<img src="assets/withsolve/plot_ptprofile.png" width=62% class="center"/>
<br />
<img src="assets/withsolve/plot_fluxes.png" width=62% class="center"/>
```
We can also plot the outgoing emission spectrum and normalised longwave contribution function (CF). The spectrum clearly demonstrates complex water absorption features, and exceeds blackbody emission at shorter wavelengths due to Rayleigh scattering. The CF quantifies how much each pressure level contributes to the outgoing emission spectrum at a given wavelength -- this is then plotted versus wavelength and pressure.
```@raw html
<img src="assets/withsolve/plot_emission.png" width=90% class="center"/>
<br />
<img src="assets/withsolve/plot_contfunc.png" width=90% class="center"/>
```
|
nichollshREPO_NAMEAGNIPATH_START.@AGNI_extracted@AGNI-main@docs@src@examples@index.md@.PATH_END.py
|
{
"filename": "_autobinx.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/histogram2d/_autobinx.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class AutobinxValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(self, plotly_name="autobinx", parent_name="histogram2d", **kwargs):
super(AutobinxValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
**kwargs,
)
|
plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram2d@_autobinx.py@.PATH_END.py
|
{
"filename": "test_imports.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/partners/openai/tests/unit_tests/embeddings/test_imports.py",
"type": "Python"
}
|
from langchain_openai.embeddings import __all__
EXPECTED_ALL = ["OpenAIEmbeddings", "AzureOpenAIEmbeddings"]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)
|
langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@partners@openai@tests@unit_tests@embeddings@test_imports.py@.PATH_END.py
|
{
"filename": "make_WebSky_LRG_mocks.py",
"repo_name": "NoahSailer/MaPar",
"repo_path": "MaPar_extracted/MaPar-main/mocks/websky/make_WebSky_LRG_mocks.py",
"type": "Python"
}
|
# Code to create mock LRG maps.
# Must run fetch_WebSky_products.sh and make_WebSky_LRG_subcatalogs.py first.
from scipy.special import erfc
import numpy as np
import healpy as hp
import copy
from scipy.interpolate import interp1d
def make_map(catalog,dN_dz,nside=2048,lnM_min=20,lnM_max=80,mask=None,f=1,Mc=10**12.89):
'''
Creates mock LRG map.
'''
##############################
# Zheng+07 HOD with best-fits from Sandy's paper (2306.06314)
M1 = 10**14.08
sigma = 0.27
alpha = 1.20
kappa = 0.65
# 0.68 accounts for M_sun -> M_sun/h
Nbar_central = lambda M: erfc(np.log10(Mc/(0.68*M))/np.sqrt(2)/sigma)/2
Nbar_sat = lambda M: (np.maximum((0.68*M)-kappa*Mc,0.)/M1)**alpha*Nbar_central(M)
##############################
# impose mass cut
# does nothing with default lnM_min/lnM_max values
lnM = np.log(catalog[:,3])
I = np.where((lnM>lnM_min) & (lnM<lnM_max))
z = catalog[:,0][I]
theta = catalog[:,1][I]
phi = catalog[:,2][I]
M = catalog[:,3][I]
# Apply Zheng et al. weighting
N_central = 1.-np.ceil(np.random.random(size=len(z)) - Nbar_central(M))
N_sat = np.random.poisson(lam=Nbar_sat(M))
weights = N_central + N_sat
# randomly downsample (by factor f) to increase shot noise
I = np.random.choice(range(len(z)), int(f*len(z)), replace=False)
z = z[I]
theta = theta[I]
phi = phi[I]
weights = weights[I]
# reweight to get dN/dz right
# first "flatten" the dN/dz distribution
nbar,zedges = np.histogram(z,bins=100)
zcs = (zedges[:-1]+zedges[1:])/2.
weights /= interp1d(zcs,nbar,bounds_error=False,fill_value=1e30)(z)
# and then rescale to the target dN/dz
weights *= interp1d(dN_dz[:,0],dN_dz[:,1],bounds_error=False,fill_value=0)(z)
# create mock LRG map
Map = np.zeros((hp.nside2npix(nside)))
pix = hp.ang2pix(nside, theta, phi)
np.add.at(Map, pix, weights)
delta = Map/np.mean(Map)-1.
lrg=hp.ma(delta)
if mask is not None:
lrg.mask=(mask<0.5)
lrg -= np.mean(lrg)
return lrg,z,weights
def get_catalog(s):
fname = 'LRG_halos_s'+str(s)+'.pksc'
catalog=np.fromfile(fname,count=-1,dtype=np.float32)
Nhalo = int(catalog.shape[0]/4)
return np.reshape(catalog,(Nhalo,4))
# columns are: redshift, theta, phi, mass
catalog_s1 = get_catalog(1)
catalog_s2 = get_catalog(2)
catalog_s3 = get_catalog(3)
catalog_s4 = get_catalog(4)
# load dn/dzs
dN_dz_s1 = np.genfromtxt('../../data/dNdzs/LRGz1_dNdz.txt')
dN_dz_s2 = np.genfromtxt('../../data/dNdzs/LRGz2_dNdz.txt')
dN_dz_s3 = np.genfromtxt('../../data/dNdzs/LRGz3_dNdz.txt')
dN_dz_s4 = np.genfromtxt('../../data/dNdzs/LRGz4_dNdz.txt')
delta_s1,z1,weights1 = make_map(catalog_s1,dN_dz_s1,f=0.71*1.20,Mc=10**13.05)
delta_s2,z2,weights2 = make_map(catalog_s2,dN_dz_s2,f=0.80*1.25,Mc=10**13.05)
delta_s3,z3,weights3 = make_map(catalog_s3,dN_dz_s3,f=0.71*1.25,Mc=10**13.05)
delta_s4,z4,weights4 = make_map(catalog_s4,dN_dz_s4,f=0.43*1.10,Mc=10**12.95)
hp.write_map('mock_lrg_z1.fits',delta_s1,overwrite=True)
hp.write_map('mock_lrg_z2.fits',delta_s2,overwrite=True)
hp.write_map('mock_lrg_z3.fits',delta_s3,overwrite=True)
hp.write_map('mock_lrg_z4.fits',delta_s4,overwrite=True)
|
NoahSailerREPO_NAMEMaParPATH_START.@MaPar_extracted@MaPar-main@mocks@websky@make_WebSky_LRG_mocks.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/volume/slices/y/__init__.py",
"type": "Python"
}
|
import sys
if sys.version_info < (3, 7):
from ._show import ShowValidator
from ._locationssrc import LocationssrcValidator
from ._locations import LocationsValidator
from ._fill import FillValidator
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_import(
__name__,
[],
[
"._show.ShowValidator",
"._locationssrc.LocationssrcValidator",
"._locations.LocationsValidator",
"._fill.FillValidator",
],
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@volume@slices@y@__init__.py@.PATH_END.py
|
{
"filename": "download.py",
"repo_name": "cta-observatory/ctapipe",
"repo_path": "ctapipe_extracted/ctapipe-main/src/ctapipe/utils/download.py",
"type": "Python"
}
|
import logging
import os
from pathlib import Path
from urllib.parse import urlparse
import requests
from tqdm.auto import tqdm
from .filelock import FileLock
__all__ = ["download_file", "download_cached", "download_file_cached"]
log = logging.getLogger(__name__)
def download_file(url, path, auth=None, chunk_size=10240, progress=False):
"""
Download a file. Will write to ``path + '.part'`` while downloading
and rename after successful download to the final name.
Parameters
----------
url: str or url
The URL to download
path: pathlib.Path or str
Where to store the downloaded data.
auth: None or tuple of (username, password) or a request.AuthBase instance.
chunk_size: int
Chunk size for writing the data file, 10 kB by default.
"""
log.info(f"Downloading {url} to {path}")
name = urlparse(url).path.split("/")[-1]
path = Path(path)
part_file = None
with requests.get(url, stream=True, auth=auth, timeout=5) as r:
# make sure the request is successful
r.raise_for_status()
total = float(r.headers.get("Content-Length", float("inf")))
pbar = tqdm(
total=total,
disable=not progress,
unit="B",
unit_scale=True,
desc=f"Downloading {name}",
)
try:
# open a .part file to avoid creating
# a broken file at the intended location
part_file = path.with_suffix(path.suffix + ".part")
part_file.parent.mkdir(parents=True, exist_ok=True)
with part_file.open("wb") as f:
for chunk in r.iter_content(chunk_size=chunk_size):
f.write(chunk)
pbar.update(len(chunk))
except BaseException: # we really want to catch everything here
# cleanup part file if something goes wrong
if part_file is not None and part_file.is_file():
part_file.unlink()
raise
# when successful, move to intended location
part_file.rename(path)
def get_cache_path(url, cache_name="ctapipe", env_override="CTAPIPE_CACHE"):
if os.getenv(env_override):
base = Path(os.environ["CTAPIPE_CACHE"])
else:
base = Path.home() / ".cache" / cache_name
url = urlparse(url)
path = os.path.join(url.netloc.rstrip("/"), url.path.lstrip("/"))
path = base / path
return path
def download_cached(
url, cache_name="ctapipe", auth=None, env_prefix="CTAPIPE_DATA_", progress=False
):
path = get_cache_path(url, cache_name=cache_name)
path.parent.mkdir(parents=True, exist_ok=True)
lock_file = path.with_suffix(path.suffix + ".lock")
with FileLock(lock_file):
# if we already downloaded the file, just use it
if path.is_file():
log.debug(f"{url} is available in cache.")
return path
if auth is True:
try:
auth = (
os.environ[env_prefix + "USER"],
os.environ[env_prefix + "PASSWORD"],
)
except KeyError:
raise KeyError(
f'You need to set the env variables "{env_prefix}USER"'
f' and "{env_prefix}PASSWORD" to download test files.'
) from None
download_file(url=url, path=path, auth=auth, progress=progress)
return path
def download_file_cached(
name,
cache_name="ctapipe",
auth=None,
env_prefix="CTAPIPE_DATA_",
default_url="http://cccta-dataserver.in2p3.fr/data/",
progress=False,
):
"""
Downloads a file from a dataserver and caches the result locally
in ``$HOME/.cache/<cache_name>``.
If the file is found in the cache, no new download is performed.
Parameters
----------
name: str or pathlib.Path
the name of the file, relative to the data server url
cache_name: str
What name to use for the cache directory
env_prefix: str
Prefix for the environt variables used for overriding the URL,
and providing username and password in case authentication is required.
auth: True, None or tuple of (username, password)
Authentication data for the request. Will be passed to ``requests.get``.
If ``True``, read username and password for the request from
the env variables ``env_prefix + 'USER'`` and ``env_prefix + PASSWORD``
default_url: str
The default url from which to download ``name``, can be overridden
by setting the env variable ``env_prefix + URL``
Returns
-------
path: pathlib.Path
the full path to the downloaded data.
"""
log.debug(f"File {name} is not available in cache, downloading.")
base_url = os.environ.get(env_prefix + "URL", default_url).rstrip("/")
url = base_url + "/" + str(name).lstrip("/")
return download_cached(
url, cache_name=cache_name, auth=auth, env_prefix=env_prefix, progress=progress
)
|
cta-observatoryREPO_NAMEctapipePATH_START.@ctapipe_extracted@ctapipe-main@src@ctapipe@utils@download.py@.PATH_END.py
|
{
"filename": "_tickfont.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/layout/coloraxis/colorbar/_tickfont.py",
"type": "Python"
}
|
from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType
import copy as _copy
class Tickfont(_BaseLayoutHierarchyType):
# class properties
# --------------------
_parent_path_str = "layout.coloraxis.colorbar"
_path_str = "layout.coloraxis.colorbar.tickfont"
_valid_props = {
"color",
"family",
"lineposition",
"shadow",
"size",
"style",
"textcase",
"variant",
"weight",
}
# color
# -----
@property
def color(self):
"""
The 'color' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
Returns
-------
str
"""
return self["color"]
@color.setter
def color(self, val):
self["color"] = val
# family
# ------
@property
def family(self):
"""
HTML font family - the typeface that will be applied by the web
browser. The web browser will only be able to apply a font if
it is available on the system which it operates. Provide
multiple font families, separated by commas, to indicate the
preference in which to apply fonts if they aren't available on
the system. The Chart Studio Cloud (at https://chart-
studio.plotly.com or on-premise) generates images on a server,
where only a select number of fonts are installed and
supported. These include "Arial", "Balto", "Courier New",
"Droid Sans", "Droid Serif", "Droid Sans Mono", "Gravitas One",
"Old Standard TT", "Open Sans", "Overpass", "PT Sans Narrow",
"Raleway", "Times New Roman".
The 'family' property is a string and must be specified as:
- A non-empty string
Returns
-------
str
"""
return self["family"]
@family.setter
def family(self, val):
self["family"] = val
# lineposition
# ------------
@property
def lineposition(self):
"""
Sets the kind of decoration line(s) with text, such as an
"under", "over" or "through" as well as combinations e.g.
"under+over", etc.
The 'lineposition' property is a flaglist and may be specified
as a string containing:
- Any combination of ['under', 'over', 'through'] joined with '+' characters
(e.g. 'under+over')
OR exactly one of ['none'] (e.g. 'none')
Returns
-------
Any
"""
return self["lineposition"]
@lineposition.setter
def lineposition(self, val):
self["lineposition"] = val
# shadow
# ------
@property
def shadow(self):
"""
Sets the shape and color of the shadow behind text. "auto"
places minimal shadow and applies contrast text font color. See
https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow
for additional options.
The 'shadow' property is a string and must be specified as:
- A string
- A number that will be converted to a string
Returns
-------
str
"""
return self["shadow"]
@shadow.setter
def shadow(self, val):
self["shadow"] = val
# size
# ----
@property
def size(self):
"""
The 'size' property is a number and may be specified as:
- An int or float in the interval [1, inf]
Returns
-------
int|float
"""
return self["size"]
@size.setter
def size(self, val):
self["size"] = val
# style
# -----
@property
def style(self):
"""
Sets whether a font should be styled with a normal or italic
face from its family.
The 'style' property is an enumeration that may be specified as:
- One of the following enumeration values:
['normal', 'italic']
Returns
-------
Any
"""
return self["style"]
@style.setter
def style(self, val):
self["style"] = val
# textcase
# --------
@property
def textcase(self):
"""
Sets capitalization of text. It can be used to make text appear
in all-uppercase or all-lowercase, or with each word
capitalized.
The 'textcase' property is an enumeration that may be specified as:
- One of the following enumeration values:
['normal', 'word caps', 'upper', 'lower']
Returns
-------
Any
"""
return self["textcase"]
@textcase.setter
def textcase(self, val):
self["textcase"] = val
# variant
# -------
@property
def variant(self):
"""
Sets the variant of the font.
The 'variant' property is an enumeration that may be specified as:
- One of the following enumeration values:
['normal', 'small-caps', 'all-small-caps',
'all-petite-caps', 'petite-caps', 'unicase']
Returns
-------
Any
"""
return self["variant"]
@variant.setter
def variant(self, val):
self["variant"] = val
# weight
# ------
@property
def weight(self):
"""
Sets the weight (or boldness) of the font.
The 'weight' property is a integer and may be specified as:
- An int (or float that will be cast to an int)
in the interval [1, 1000]
OR exactly one of ['normal', 'bold'] (e.g. 'bold')
Returns
-------
int
"""
return self["weight"]
@weight.setter
def weight(self, val):
self["weight"] = val
# Self properties description
# ---------------------------
@property
def _prop_descriptions(self):
return """\
color
family
HTML font family - the typeface that will be applied by
the web browser. The web browser will only be able to
apply a font if it is available on the system which it
operates. Provide multiple font families, separated by
commas, to indicate the preference in which to apply
fonts if they aren't available on the system. The Chart
Studio Cloud (at https://chart-studio.plotly.com or on-
premise) generates images on a server, where only a
select number of fonts are installed and supported.
These include "Arial", "Balto", "Courier New", "Droid
Sans", "Droid Serif", "Droid Sans Mono", "Gravitas
One", "Old Standard TT", "Open Sans", "Overpass", "PT
Sans Narrow", "Raleway", "Times New Roman".
lineposition
Sets the kind of decoration line(s) with text, such as
an "under", "over" or "through" as well as combinations
e.g. "under+over", etc.
shadow
Sets the shape and color of the shadow behind text.
"auto" places minimal shadow and applies contrast text
font color. See https://developer.mozilla.org/en-
US/docs/Web/CSS/text-shadow for additional options.
size
style
Sets whether a font should be styled with a normal or
italic face from its family.
textcase
Sets capitalization of text. It can be used to make
text appear in all-uppercase or all-lowercase, or with
each word capitalized.
variant
Sets the variant of the font.
weight
Sets the weight (or boldness) of the font.
"""
def __init__(
self,
arg=None,
color=None,
family=None,
lineposition=None,
shadow=None,
size=None,
style=None,
textcase=None,
variant=None,
weight=None,
**kwargs,
):
"""
Construct a new Tickfont object
Sets the color bar's tick label font
Parameters
----------
arg
dict of properties compatible with this constructor or
an instance of :class:`plotly.graph_objs.layout.colorax
is.colorbar.Tickfont`
color
family
HTML font family - the typeface that will be applied by
the web browser. The web browser will only be able to
apply a font if it is available on the system which it
operates. Provide multiple font families, separated by
commas, to indicate the preference in which to apply
fonts if they aren't available on the system. The Chart
Studio Cloud (at https://chart-studio.plotly.com or on-
premise) generates images on a server, where only a
select number of fonts are installed and supported.
These include "Arial", "Balto", "Courier New", "Droid
Sans", "Droid Serif", "Droid Sans Mono", "Gravitas
One", "Old Standard TT", "Open Sans", "Overpass", "PT
Sans Narrow", "Raleway", "Times New Roman".
lineposition
Sets the kind of decoration line(s) with text, such as
an "under", "over" or "through" as well as combinations
e.g. "under+over", etc.
shadow
Sets the shape and color of the shadow behind text.
"auto" places minimal shadow and applies contrast text
font color. See https://developer.mozilla.org/en-
US/docs/Web/CSS/text-shadow for additional options.
size
style
Sets whether a font should be styled with a normal or
italic face from its family.
textcase
Sets capitalization of text. It can be used to make
text appear in all-uppercase or all-lowercase, or with
each word capitalized.
variant
Sets the variant of the font.
weight
Sets the weight (or boldness) of the font.
Returns
-------
Tickfont
"""
super(Tickfont, self).__init__("tickfont")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = _copy.copy(arg)
else:
raise ValueError(
"""\
The first argument to the plotly.graph_objs.layout.coloraxis.colorbar.Tickfont
constructor must be a dict or
an instance of :class:`plotly.graph_objs.layout.coloraxis.colorbar.Tickfont`"""
)
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
# Populate data dict with properties
# ----------------------------------
_v = arg.pop("color", None)
_v = color if color is not None else _v
if _v is not None:
self["color"] = _v
_v = arg.pop("family", None)
_v = family if family is not None else _v
if _v is not None:
self["family"] = _v
_v = arg.pop("lineposition", None)
_v = lineposition if lineposition is not None else _v
if _v is not None:
self["lineposition"] = _v
_v = arg.pop("shadow", None)
_v = shadow if shadow is not None else _v
if _v is not None:
self["shadow"] = _v
_v = arg.pop("size", None)
_v = size if size is not None else _v
if _v is not None:
self["size"] = _v
_v = arg.pop("style", None)
_v = style if style is not None else _v
if _v is not None:
self["style"] = _v
_v = arg.pop("textcase", None)
_v = textcase if textcase is not None else _v
if _v is not None:
self["textcase"] = _v
_v = arg.pop("variant", None)
_v = variant if variant is not None else _v
if _v is not None:
self["variant"] = _v
_v = arg.pop("weight", None)
_v = weight if weight is not None else _v
if _v is not None:
self["weight"] = _v
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@layout@coloraxis@colorbar@_tickfont.py@.PATH_END.py
|
{
"filename": "test_automations.py",
"repo_name": "PrefectHQ/prefect",
"repo_path": "prefect_extracted/prefect-main/tests/events/client/cli/test_automations.py",
"type": "Python"
}
|
import sys
from datetime import timedelta
from typing import Generator, List
from unittest import mock
from uuid import UUID, uuid4
import orjson
import pytest
import yaml
from typer import Exit
from prefect.events.actions import CancelFlowRun, DoNothing, PauseAutomation
from prefect.events.schemas.automations import (
Automation,
EventTrigger,
MetricTrigger,
MetricTriggerOperator,
MetricTriggerQuery,
Posture,
PrefectMetric,
)
from prefect.testing.cli import invoke_and_assert
@pytest.fixture(autouse=True)
def interactive_console(monkeypatch):
monkeypatch.setattr("prefect.events.cli.automations.is_interactive", lambda: True)
# `readchar` does not like the fake stdin provided by typer isolation so we provide
# a version that does not require a fd to be attached
def readchar():
sys.stdin.flush()
position = sys.stdin.tell()
if not sys.stdin.read():
print("TEST ERROR: CLI is attempting to read input but stdin is empty.")
raise Exit(-2)
else:
sys.stdin.seek(position)
return sys.stdin.read(1)
monkeypatch.setattr("readchar._posix_read.readchar", readchar)
@pytest.fixture
def read_automations() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.read_automations", autospec=True
) as m:
yield m
def test_listing_automations_empty(read_automations: mock.AsyncMock):
read_automations.return_value = []
invoke_and_assert(
["automations", "ls"],
expected_code=0,
expected_output_contains="Automations",
)
@pytest.fixture
def various_automations(read_automations: mock.AsyncMock) -> List[Automation]:
automations = [
Automation(
id=UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"),
name="My First Reactive",
description="This one reacts to things!",
trigger=EventTrigger(
posture=Posture.Reactive, expect={"event.one", "event.two"}, threshold=1
),
actions=[DoNothing()],
),
Automation(
id=UUID("bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb"),
name="My Other Reactive Automation",
description="This one also reacts to things!",
trigger=EventTrigger(
posture=Posture.Reactive,
expect={"event.three", "event.four"},
threshold=2,
),
actions=[CancelFlowRun()],
),
Automation(
id=UUID("cccccccc-cccc-cccc-cccc-cccccccccccc"),
name="A Proactive one",
trigger=EventTrigger(
posture=Posture.Proactive,
expect={"event.five"},
threshold=2,
within=timedelta(minutes=5),
),
actions=[CancelFlowRun()],
),
Automation(
id=UUID("cccccccc-cccc-cccc-cccc-cccccccccccc"),
name="A Metric one",
trigger=MetricTrigger(
metric=MetricTriggerQuery(
name=PrefectMetric.successes,
operator=MetricTriggerOperator.LT,
threshold=0.78,
)
),
actions=[CancelFlowRun()],
actions_on_trigger=[DoNothing()],
actions_on_resolve=[PauseAutomation(automation_id=uuid4())],
),
Automation(
id=UUID("dddddddd-dddd-dddd-dddd-dddddddddddd"),
name="A Metric one",
trigger=MetricTrigger(
metric=MetricTriggerQuery(
name=PrefectMetric.successes,
operator=MetricTriggerOperator.LT,
threshold=0.78,
)
),
actions=[CancelFlowRun()],
actions_on_trigger=[DoNothing()],
actions_on_resolve=[PauseAutomation(automation_id=uuid4())],
),
]
read_automations.return_value = automations
return automations
def test_listing_various_automations(various_automations: List[Automation]):
invoke_and_assert(
["automations", "ls"],
expected_code=0,
expected_output_contains=[
# first reactive
"My First Reactive",
"aaaaaaaa-aaaa-",
"This one reacts",
"Reactive:",
"event.one",
"event.two",
"Do nothing",
# second reactive
"My Other Reactive",
"bbbbbbbb-bbbb-",
"This one also reacts",
"Reactive:",
"event.three",
"event.four",
"Cancel flow run",
# third proactive
"A Proactive one",
"cccccccc-cccc-",
"Proactive:",
"event.five",
"within 0:05:00",
# fourth metric
"A Metric one",
"successes <",
"0.78 for 0:05:00",
"(trigger) Cancel",
"(trigger) Do nothing",
"(resolve) Cancel",
"(resolve) Pause",
],
)
@pytest.fixture
def read_automation() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.read_automation", autospec=True
) as m:
yield m
def test_inspecting_by_id(
read_automation: mock.AsyncMock, various_automations: List[Automation]
):
read_automation.return_value = various_automations[1]
invoke_and_assert(
["automations", "inspect", "--id", "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb"],
expected_code=0,
expected_output_contains=[
"Automation(",
"My Other Reactive Automation",
"bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb",
"EventTrigger(",
],
)
read_automation.assert_awaited_once_with(
mock.ANY, UUID("bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb")
)
def test_inspecting_by_id_not_found(
various_automations: List[Automation],
):
invoke_and_assert(
["automations", "inspect", "--id", "zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz"],
expected_code=1,
expected_output_contains=[
"Automation with id 'zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz' not found"
],
)
def test_inspecting_by_name(
various_automations: List[Automation], read_automations_by_name: mock.AsyncMock
):
read_automations_by_name.return_value = [various_automations[0]]
invoke_and_assert(
["automations", "inspect", "My First Reactive"],
expected_code=0,
expected_output_contains=[
"Automation(",
"My First Reactive",
"aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa",
"EventTrigger(",
],
)
def test_inspecting_by_name_not_found(
various_automations: List[Automation], read_automations_by_name: mock.AsyncMock
):
read_automations_by_name.return_value = None
invoke_and_assert(
["automations", "inspect", "What is this?"],
expected_code=1,
expected_output_contains=["Automation 'What is this?' not found"],
)
def test_inspecting_by_name_in_json(
various_automations: List[Automation], read_automations_by_name: mock.AsyncMock
):
read_automations_by_name.return_value = [various_automations[0]]
result = invoke_and_assert(
["automations", "inspect", "My First Reactive", "--json"], expected_code=0
)
loaded = orjson.loads(result.output)
assert loaded[0]["name"] == "My First Reactive"
assert loaded[0]["id"] == "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"
def test_inspecting_by_id_in_json(
various_automations: List[Automation], read_automation: mock.AsyncMock
):
read_automation.return_value = various_automations[1]
result = invoke_and_assert(
[
"automations",
"inspect",
"--id",
"bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb",
"--json",
],
expected_code=0,
)
loaded = orjson.loads(result.output)
assert loaded["name"] == "My Other Reactive Automation"
assert loaded["id"] == "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb"
def test_inspecting_by_name_in_yaml(
various_automations: List[Automation], read_automations_by_name: mock.AsyncMock
):
read_automations_by_name.return_value = [various_automations[0]]
result = invoke_and_assert(
["automations", "inspect", "My First Reactive", "--yaml"], expected_code=0
)
loaded = yaml.safe_load(result.output)
assert loaded[0]["name"] == "My First Reactive"
assert loaded[0]["id"] == "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"
def test_inspecting_by_id_in_yaml(
various_automations: List[Automation], read_automation: mock.AsyncMock
):
read_automation.return_value = various_automations[1]
result = invoke_and_assert(
[
"automations",
"inspect",
"--id",
"bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb",
"--yaml",
],
expected_code=0,
)
loaded = yaml.safe_load(result.output)
assert loaded["name"] == "My Other Reactive Automation"
assert loaded["id"] == "bbbbbbbb-bbbb-bbbb-bbbb-bbbbbbbbbbbb"
@pytest.fixture
def pause_automation() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.pause_automation", autospec=True
) as m:
yield m
def test_pausing_by_name(
pause_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automations_by_name: mock.AsyncMock,
):
read_automations_by_name.return_value = [various_automations[0]]
invoke_and_assert(
["automations", "pause", "My First Reactive"],
expected_code=0,
expected_output_contains=[
"Paused automation(s) with name 'My First Reactive' and id(s) 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
],
)
pause_automation.assert_awaited_once_with(
mock.ANY, UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
)
def test_pausing_by_name_not_found(
pause_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automations_by_name: mock.AsyncMock,
):
read_automations_by_name.return_value = None
invoke_and_assert(
["automations", "pause", "Wha?"],
expected_code=1,
expected_output_contains=["Automation with name 'Wha?' not found"],
)
pause_automation.assert_not_awaited()
def test_pausing_by_id(
pause_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automation: mock.AsyncMock,
):
read_automation.return_value = various_automations[0]
invoke_and_assert(
["automations", "pause", "--id", "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"],
expected_code=0,
expected_output_contains=[
"Paused automation with id 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
],
)
pause_automation.assert_awaited_once_with(
mock.ANY, UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
)
def test_pausing_by_id_not_found(
pause_automation: mock.AsyncMock,
read_automation: mock.AsyncMock,
):
read_automation.return_value = None
invoke_and_assert(
["automations", "pause", "--id", "zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz"],
expected_code=1,
expected_output_contains=[
"Automation with id 'zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz' not found"
],
)
pause_automation.assert_not_awaited()
@pytest.fixture
def resume_automation() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.resume_automation", autospec=True
) as m:
yield m
def test_resuming_by_name(
resume_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automations_by_name: mock.AsyncMock,
):
read_automations_by_name.return_value = [various_automations[0]]
invoke_and_assert(
["automations", "resume", "My First Reactive"],
expected_code=0,
expected_output_contains=[
"Resumed automation(s) with name 'My First Reactive' and id(s) 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
],
)
resume_automation.assert_awaited_once_with(
mock.ANY, UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
)
def test_resuming_by_name_not_found(
resume_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automations_by_name: mock.AsyncMock,
):
read_automations_by_name.return_value = None
invoke_and_assert(
["automations", "resume", "Wha?"],
expected_code=1,
expected_output_contains=["Automation with name 'Wha?' not found"],
)
resume_automation.assert_not_awaited()
def test_resuming_by_id(
resume_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automation: mock.AsyncMock,
):
read_automation.return_value = various_automations[0]
invoke_and_assert(
["automations", "resume", "--id", "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"],
expected_code=0,
expected_output_contains=[
"Resumed automation with id 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
],
)
resume_automation.assert_awaited_once_with(
mock.ANY, UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
)
def test_resuming_by_id_not_found(
resume_automation: mock.AsyncMock, read_automation: mock.AsyncMock
):
read_automation.return_value = None
invoke_and_assert(
["automations", "resume", "--id", "zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz"],
expected_code=1,
expected_output_contains=[
"Automation with id 'zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz' not found"
],
)
resume_automation.assert_not_awaited()
@pytest.fixture
def delete_automation() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.delete_automation", autospec=True
) as m:
yield m
@pytest.fixture
def read_automations_by_name() -> Generator[mock.AsyncMock, None, None]:
with mock.patch(
"prefect.client.orchestration.PrefectClient.read_automations_by_name",
autospec=True,
) as mock_read:
yield mock_read
def test_deleting_by_name(
delete_automation: mock.AsyncMock,
read_automations_by_name: mock.AsyncMock,
various_automations: List[Automation],
):
read_automations_by_name.return_value = [various_automations[0]]
invoke_and_assert(
["automations", "delete", "My First Reactive"],
prompts_and_responses=[
(
"Are you sure you want to delete automation with name 'My First Reactive'?",
"y",
)
],
expected_code=0,
expected_output_contains=["Deleted automation with name 'My First Reactive'"],
)
delete_automation.assert_awaited_once_with(
mock.ANY, UUID("aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa")
)
def test_deleting_by_name_multiple_same_name(
delete_automation: mock.AsyncMock,
read_automations_by_name: mock.AsyncMock,
various_automations: List[Automation],
):
read_automations_by_name.return_value = various_automations[:2]
invoke_and_assert(
["automations", "delete", "A Metric one"],
expected_code=1,
expected_output_contains=[
"Multiple automations found with name 'A Metric one'. Please specify an id with the `--id` flag instead."
],
)
delete_automation.assert_not_called()
def test_deleting_by_id_not_found_is_a_noop(
delete_automation: mock.AsyncMock,
various_automations: List[Automation],
read_automations_by_name: mock.AsyncMock,
):
read_automations_by_name.return_value = None
invoke_and_assert(
["automations", "delete", "Who dis?"],
expected_code=1,
expected_output_contains=["Automation 'Who dis?' not found"],
)
delete_automation.assert_not_called()
def test_deleting_by_id(
delete_automation: mock.AsyncMock,
read_automation: mock.AsyncMock,
various_automations: List[Automation],
):
read_automation.return_value = various_automations[0]
invoke_and_assert(
["automations", "delete", "--id", "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"],
prompts_and_responses=[
(
"Are you sure you want to delete automation with id 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'?",
"y",
)
],
expected_code=0,
expected_output_contains=[
"Deleted automation with id 'aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa'"
],
)
delete_automation.assert_awaited_once_with(
mock.ANY, "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"
)
def test_deleting_by_nonexistent_id(
delete_automation: mock.AsyncMock,
read_automation: mock.AsyncMock,
):
read_automation.return_value = None
invoke_and_assert(
["automations", "delete", "--id", "zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz"],
expected_code=1,
expected_output_contains=[
"Automation with id 'zzzzzzzz-zzzz-zzzz-zzzz-zzzzzzzzzzzz' not found"
],
)
delete_automation.assert_not_called()
|
PrefectHQREPO_NAMEprefectPATH_START.@prefect_extracted@prefect-main@tests@events@client@cli@test_automations.py@.PATH_END.py
|
{
"filename": "_r.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/layout/slider/pad/_r.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class RValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(self, plotly_name="r", parent_name="layout.slider.pad", **kwargs):
super(RValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "arraydraw"),
role=kwargs.pop("role", "style"),
**kwargs
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@layout@slider@pad@_r.py@.PATH_END.py
|
{
"filename": "test_scheduling.py",
"repo_name": "astropy/astroplan",
"repo_path": "astroplan_extracted/astroplan-main/astroplan/tests/test_scheduling.py",
"type": "Python"
}
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
import numpy as np
from astropy.time import Time
import astropy.units as u
from astropy.coordinates import SkyCoord, EarthLocation
import pytest
from ..utils import time_grid_from_range
from ..observer import Observer
from ..target import FixedTarget, get_skycoord
from ..constraints import (AirmassConstraint, AtNightConstraint, _get_altaz,
MoonIlluminationConstraint, PhaseConstraint)
from ..periodic import EclipsingSystem
from ..scheduling import (ObservingBlock, PriorityScheduler, SequentialScheduler,
Transitioner, TransitionBlock, Schedule, Slot, Scorer)
vega = FixedTarget(coord=SkyCoord(ra=279.23473479 * u.deg, dec=38.78368896 * u.deg),
name="Vega")
rigel = FixedTarget(coord=SkyCoord(ra=78.63446707 * u.deg, dec=8.20163837 * u.deg),
name="Rigel")
polaris = FixedTarget(coord=SkyCoord(ra=37.95456067 * u.deg,
dec=89.26410897 * u.deg), name="Polaris")
apo = Observer(EarthLocation(-1463969.30185172, -5166673.34223433, 3434985.71204565, unit='m'),
name='APO')
targets = [vega, polaris, rigel]
default_time = Time('2016-02-06 03:00:00')
only_at_night = [AtNightConstraint()]
def test_observing_block():
block = ObservingBlock(rigel, 1*u.minute, 0, configuration={'filter': 'b'})
assert block.configuration['filter'] == 'b'
assert block.target == rigel
times_per_exposure = [1*u.minute, 4*u.minute, 15*u.minute, 5*u.minute]
numbers_of_exposures = [100, 4, 3, 12]
readout_time = 0.5*u.minute
for index in range(len(times_per_exposure)):
block = ObservingBlock.from_exposures(vega, 0, times_per_exposure[index],
numbers_of_exposures[index], readout_time)
assert (block.duration == numbers_of_exposures[index] *
(times_per_exposure[index] + readout_time))
def test_slot():
start_time = Time('2016-02-06 03:00:00')
end_time = start_time + 24 * u.hour
slot = Slot(start_time, end_time)
slots = slot.split_slot(start_time, start_time+1*u.hour)
assert len(slots) == 2
assert slots[0].end == slots[1].start
def test_schedule():
start_time = Time('2016-02-06 03:00:00')
end_time = start_time + 24 * u.hour
schedule = Schedule(start_time, end_time)
assert schedule.slots[0].start == start_time
assert schedule.slots[0].end == end_time
assert schedule.slots[0].duration == 24*u.hour
schedule.new_slots(0, start_time, end_time)
assert len(schedule.slots) == 1
new_slots = schedule.new_slots(0, start_time+1*u.hour, start_time+4*u.hour)
assert np.abs(new_slots[0].duration - 1*u.hour) < 1*u.second
assert np.abs(new_slots[1].duration - 3*u.hour) < 1*u.second
assert np.abs(new_slots[2].duration - 20*u.hour) < 1*u.second
def test_schedule_insert_slot():
start = Time('2016-02-06 03:00:00')
schedule = Schedule(start, start + 5*u.hour)
# testing for when float comparison doesn't work, does it start/end at the right time
duration = 2*u.hour + 1*u.second
end_time = start + duration
block = TransitionBlock.from_duration(duration)
schedule.insert_slot(end_time - duration, block)
assert end_time - duration == start
assert len(schedule.slots) == 2
assert schedule.slots[0].start == start
schedule = Schedule(start, start + 5*u.hour)
# testing for when float evaluation does work
duration = 2*u.hour
end_time = start + duration
block = TransitionBlock.from_duration(duration)
schedule.insert_slot(end_time - duration, block)
assert (end_time - duration).jd == start.jd
assert len(schedule.slots) == 2
assert schedule.slots[0].start.jd == start.jd
def test_schedule_change_slot_block():
start = Time('2016-02-06 03:00:00')
schedule = Schedule(start, start + 5 * u.hour)
duration = 2 * u.hour
block = TransitionBlock.from_duration(duration)
schedule.insert_slot(start, block)
# check that it has the correct duration
assert np.abs(schedule.slots[0].end - duration - start) < 1*u.second
new_duration = 1*u.minute
new_block = TransitionBlock.from_duration(new_duration)
schedule.change_slot_block(0, new_block)
# check the duration changed properly, and slots are still consecutive/don't overlap
assert np.abs(schedule.slots[0].end - new_duration - start) < 1*u.second
assert schedule.slots[1].start == schedule.slots[0].end
def test_transitioner():
blocks = [ObservingBlock(t, 55 * u.minute, i) for i, t in enumerate(targets)]
slew_rate = 1 * u.deg / u.second
trans = Transitioner(slew_rate=slew_rate)
start_time = Time('2016-02-06 03:00:00')
transition = trans(blocks[0], blocks[2], start_time, apo)
aaz = _get_altaz(start_time, apo,
get_skycoord([blocks[0].target, blocks[2].target]))['altaz']
sep = aaz[0].separation(aaz[1])
assert isinstance(transition, TransitionBlock)
assert transition.duration == sep/slew_rate
blocks = [ObservingBlock(vega, 10*u.minute, 0, configuration={'filter': 'v'}),
ObservingBlock(vega, 10*u.minute, 0, configuration={'filter': 'i'}),
ObservingBlock(rigel, 10*u.minute, 0, configuration={'filter': 'i'})]
trans = Transitioner(slew_rate, instrument_reconfig_times={'filter': {('v', 'i'): 2*u.minute,
'default': 5*u.minute}})
transition1 = trans(blocks[0], blocks[1], start_time, apo)
transition2 = trans(blocks[0], blocks[2], start_time, apo)
transition3 = trans(blocks[1], blocks[0], start_time, apo)
assert np.abs(transition1.duration - 2*u.minute) < 1*u.second
assert np.abs(transition2.duration - 2*u.minute - transition.duration) < 1*u.second
# to test the default transition
assert np.abs(transition3.duration - 5*u.minute) < 1*u.second
assert transition1.components is not None
default_transitioner = Transitioner(slew_rate=1 * u.deg / u.second)
def test_priority_scheduler():
constraints = [AirmassConstraint(3, boolean_constraint=False)]
blocks = [ObservingBlock(t, 55*u.minute, i) for i, t in enumerate(targets)]
start_time = Time('2016-02-06 03:00:00')
end_time = start_time + 18*u.hour
scheduler = PriorityScheduler(transitioner=default_transitioner,
constraints=constraints, observer=apo,
time_resolution=2*u.minute)
schedule = Schedule(start_time, end_time)
scheduler(blocks, schedule)
assert len(schedule.observing_blocks) == 3
assert all(np.abs(block.end_time - block.start_time - block.duration) <
1*u.second for block in schedule.scheduled_blocks)
assert all([schedule.observing_blocks[0].target == polaris,
schedule.observing_blocks[1].target == rigel,
schedule.observing_blocks[2].target == vega])
# polaris and rigel both peak just before the start time
assert schedule.slots[0].block.target == polaris
assert schedule.slots[2].block.target == rigel
# test that the scheduler does not error when called with a partially
# filled schedule
scheduler(blocks, schedule)
scheduler(blocks, schedule)
# Check if the order of equal values is respected:
# 1. For equal priorities in blocks
# 2. For equal scores (boolean_constraint)
constraints = [AirmassConstraint(3, boolean_constraint=True)]
scheduler.constraints = constraints
# Any resolution coarser than this may result in gaps between the blocks
scheduler.time_resolution = 20*u.second
# This only happens with more than 16 items or so
targets_18 = [polaris, polaris, polaris, polaris, polaris, polaris,
polaris, polaris, polaris, polaris, polaris, polaris,
polaris, polaris, polaris, polaris, polaris, polaris]
blocks = [ObservingBlock(t, 4*u.minute, 5, name=i) for i, t in enumerate(targets_18)]
schedule = Schedule(start_time, end_time)
scheduler(blocks, schedule)
for i, t in enumerate(targets_18):
# Order of blocks
block = schedule.observing_blocks[i]
assert block.name == i
if i < len(targets_18) - 1:
# Same score for all timeslots, should be filled from the start without gaps
assert block.end_time.isclose(schedule.observing_blocks[i+1].start_time)
def test_sequential_scheduler():
constraints = [AirmassConstraint(2.5, boolean_constraint=False)]
blocks = [ObservingBlock(t, 55 * u.minute, i) for i, t in enumerate(targets)]
start_time = Time('2016-02-06 03:00:00')
end_time = start_time + 18 * u.hour
scheduler = SequentialScheduler(constraints=constraints, observer=apo,
transitioner=default_transitioner,
gap_time=15*u.minute)
schedule = Schedule(start_time, end_time)
scheduler(blocks, schedule)
assert len(schedule.observing_blocks) > 0
assert all(np.abs(block.end_time - block.start_time - block.duration) <
1*u.second for block in schedule.scheduled_blocks)
assert all([schedule.observing_blocks[0].target == rigel,
schedule.observing_blocks[1].target == polaris,
schedule.observing_blocks[2].target == vega])
# vega rises late, so its start should be later
assert schedule.observing_blocks[2].start_time > start_time + 8*u.hour
# test that the scheduler does not error when called with a partially
# filled schedule
scheduler(blocks, schedule)
scheduler(blocks, schedule)
@pytest.mark.remote_data
def test_scheduling_target_down():
lco = Observer.at_site('lco')
block = [ObservingBlock(FixedTarget.from_name('polaris'), 1 * u.min, 0)]
start_time = Time('2016-02-06 03:00:00')
end_time = start_time + 3*u.day
scheduler1 = SequentialScheduler(only_at_night, lco, default_transitioner,
gap_time=2*u.hour)
schedule = Schedule(start_time, end_time)
schedule1 = scheduler1(block, schedule)
assert len(schedule1.observing_blocks) == 0
scheduler2 = PriorityScheduler(only_at_night, lco, default_transitioner,
time_resolution=30 * u.minute)
schedule = Schedule(start_time, end_time)
schedule2 = scheduler2(block, schedule)
assert len(schedule2.observing_blocks) == 0
@pytest.mark.remote_data
def test_scheduling_during_day():
block = [ObservingBlock(FixedTarget.from_name('polaris'), 1 * u.min, 0)]
day = Time('2016-02-06 03:00:00')
start_time = apo.midnight(day) + 10*u.hour
end_time = start_time + 6*u.hour
scheduler1 = SequentialScheduler(only_at_night, apo, default_transitioner,
gap_time=30*u.minute)
schedule = Schedule(start_time, end_time)
schedule1 = scheduler1(block, schedule)
assert len(schedule1.observing_blocks) == 0
scheduler2 = PriorityScheduler(only_at_night, apo, default_transitioner,
time_resolution=2 * u.minute)
schedule = Schedule(start_time, end_time)
schedule2 = scheduler2(block, schedule)
assert len(schedule2.observing_blocks) == 0
# bring this back when MoonIlluminationConstraint is working properly
@pytest.mark.remote_data
def test_scheduling_moon_up():
block = [ObservingBlock(FixedTarget.from_name('polaris'), 30 * u.min, 0)]
# on february 23 the moon was up between the start/end times defined below
day = Time('2016-02-23 03:00:00')
start_time = apo.midnight(day) - 2 * u.hour
end_time = start_time + 6 * u.hour
constraints = [AtNightConstraint(), MoonIlluminationConstraint(max=0)]
scheduler1 = SequentialScheduler(constraints, apo, default_transitioner,
gap_time=30*u.minute)
schedule = Schedule(start_time, end_time)
schedule1 = scheduler1(block, schedule)
assert len(schedule1.observing_blocks) == 0
scheduler2 = PriorityScheduler(constraints, apo, default_transitioner,
time_resolution=20*u.minute)
schedule = Schedule(start_time, end_time)
schedule2 = scheduler2(block, schedule)
assert len(schedule2.observing_blocks) == 0
def test_schedule_eclipsers():
loc = EarthLocation(*u.Quantity((5327448.9957829,
-1718665.73869569,
3051566.90295403), unit=u.m))
lapalma = Observer(location=loc)
nnser = FixedTarget(coord=SkyCoord("15 52 56.131 +12 54 44.68", unit=(u.hour, u.deg)),
name='NN Ser')
period = 0.1300801417*u.d
nnser_eclipses = EclipsingSystem(Time(57459.8372148, format='mjd'),
period, duration=0.15*period)
# schedule an eclipse. Do this by having a constraint which is only
# valid in the narrow phase range you want observed, and an OB whose
# duration is only slightly shorter than the phase constraint.
# This block can then only be scheduled covering the eclipse.
pc = PhaseConstraint(nnser_eclipses, min=0.9, max=0.1)
# make OB one minute shorter than duration to allow scheduling
block = [ObservingBlock(nnser, 0.2*period - 1*u.min, 0)]
constraints = [pc]
start_time = Time('2017-05-24 22:00:00')
end_time = Time('2017-05-24 23:20:00')
scheduler = PriorityScheduler(constraints, lapalma, default_transitioner,
time_resolution=10*u.s)
schedule = Schedule(start_time, end_time)
scheduled = scheduler(block, schedule)
# check scheduled at all
assert len(scheduled.observing_blocks) == 1
sblock = scheduled.observing_blocks[0]
ingress, egress = nnser_eclipses.next_primary_ingress_egress_time(Time('2017-05-24T22:00:00')).T
# check whole eclipse was scheduled
assert sblock.start_time < ingress
assert sblock.end_time > egress
def test_scorer():
constraint = AirmassConstraint(max=4)
times = time_grid_from_range(Time(['2016-02-06 00:00', '2016-02-06 08:00']),
time_resolution=20*u.minute)
c = constraint(apo, [vega, rigel], times, grid_times_targets=True)
block = ObservingBlock(vega, 1*u.hour, 0, constraints=[constraint])
block2 = ObservingBlock(rigel, 1*u.hour, 0, constraints=[constraint])
scorer = Scorer.from_start_end([block, block2], apo, Time('2016-02-06 00:00'),
Time('2016-02-06 08:00'))
scores = scorer.create_score_array(time_resolution=20*u.minute)
assert np.array_equal(c, scores)
constraint2 = AirmassConstraint(max=2, boolean_constraint=False)
c2 = constraint2(apo, [vega, rigel], times, grid_times_targets=True)
block = ObservingBlock(vega, 1*u.hour, 0, constraints=[constraint])
block2 = ObservingBlock(rigel, 1*u.hour, 0, constraints=[constraint2])
# vega's score should be = c[0], rigel's should be = c2[1]
scorer = Scorer.from_start_end([block, block2], apo, Time('2016-02-06 00:00'),
Time('2016-02-06 08:00'))
scores = scorer.create_score_array(time_resolution=20 * u.minute)
assert np.array_equal(c[0], scores[0])
assert np.array_equal(c2[1], scores[1])
block = ObservingBlock(vega, 1*u.hour, 0)
block2 = ObservingBlock(rigel, 1*u.hour, 0)
scorer = Scorer.from_start_end([block, block2], apo, Time('2016-02-06 00:00'),
Time('2016-02-06 08:00'), [constraint2])
scores = scorer.create_score_array(time_resolution=20 * u.minute)
# the ``global_constraint``: constraint2 should have applied to the blocks
assert np.array_equal(c2, scores)
|
astropyREPO_NAMEastroplanPATH_START.@astroplan_extracted@astroplan-main@astroplan@tests@test_scheduling.py@.PATH_END.py
|
{
"filename": "README.md",
"repo_name": "minoshim/qasMHD",
"repo_path": "qasMHD_extracted/qasMHD-main/1D/SERIAL/wave/README.md",
"type": "Markdown"
}
|
## Wave Propagation Problem
This problem demonstrates the propagation of MHD waves in homogeneous plasma to confirm that the code successfully satisfies the linear dispersion.<br>
Random white noise is added to the magnetic field and pressure, and their perturabations propagate as the Alfven and magnetosonic waves.
Example results for high and low beta cases are shown below:<br>
(Top...spatial profiles, bottom left...spectrum of the magnetic field, bottom right...spectrum of the pressure. Users can create the spectrum plot with the scripts `batch_a.py` and `wk_plt.py`)
1. `beta=10` in `mhd1d_init_.cpp`. The pressure perturbation propagates as the fast magnetosonic wave.
<img src="../../imgs/wave/wk_by_b1e+1.png" alt="Spectrum of by for beta=10" width="400px"><img src="../../imgs/wave/wk_pr_b1e+1.png" alt="Spectrum of pr for beta=10" width="400px">
2. `beta=0.1` in `mhd1d_init_.cpp`. The pressure perturbation propagates as the slow magnetosonic wave.
<img src="../../imgs/wave/wk_by_b1e-1.png" alt="Spectrum of by for beta=0.1" width="400px"><img src="../../imgs/wave/wk_pr_b1e-1.png" alt="Spectrum of pr for beta=0.1" width="400px">
## License
This project is licensed under the GNU General Public License v3.0 - see the [license](../../../license/COPYING) file for details.
|
minoshimREPO_NAMEqasMHDPATH_START.@qasMHD_extracted@qasMHD-main@1D@SERIAL@wave@README.md@.PATH_END.py
|
{
"filename": "_templateitemname.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/layout/shape/_templateitemname.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class TemplateitemnameValidator(_plotly_utils.basevalidators.StringValidator):
def __init__(
self, plotly_name="templateitemname", parent_name="layout.shape", **kwargs
):
super(TemplateitemnameValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
**kwargs,
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@layout@shape@_templateitemname.py@.PATH_END.py
|
{
"filename": "data_inspect_2458203.ipynb",
"repo_name": "HERA-Team/H1C_IDR3_Notebooks",
"repo_path": "H1C_IDR3_Notebooks-main/data_inspect/data_inspect_2458203.ipynb",
"type": "Jupyter Notebook"
}
|
```python
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter
import matplotlib.patches as mpatches
import matplotlib.gridspec as gridspec
import numpy as np
from pyuvdata import UVCal, UVData
import os
import sys
import glob
import uvtools as uvt
from astropy.time import Time
from astropy.coordinates import EarthLocation, AltAz, Angle
from astropy.coordinates import SkyCoord as sc
import pandas
import warnings
import copy
from hera_notebook_templates import utils_h1c as utils
import hera_qm
from hera_mc import cm_hookup
import h5py
import importlib
from scipy import stats
import yaml
from IPython.display import display, HTML
#warnings.filterwarnings('ignore')
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
display(HTML("<style>.container { width:100% !important; }</style>"))
```
<style>.container { width:100% !important; }</style>
```python
# If you want to run this notebook locally, copy the output of the next cell into the first few lines of this cell.
# JD = 2458045
# data_path = "/lustre/aoc/projects/hera/H1C_IDR3/IDR3_2/2458045"
# flag_yaml_path = "/lustre/aoc/projects/hera/H1C_IDR3/IDR3_2/h1c_idr3_software/hera_pipelines/pipelines/h1c/idr3/v2/a_priori_flags"
# os.environ["JULIANDATE"] = str(JD)
# os.environ["DATA_PATH"] = data_path
# os.environ["PATH_TO_A_PRIORI_FLAGS"] = flag_yaml_path
```
```python
#get data location
JD = os.environ['JULIANDATE']
data_path = os.environ['DATA_PATH']
flag_yaml_path = os.environ['PATH_TO_A_PRIORI_FLAGS']
print(f'JD = {JD}')
print(f'data_path = "{data_path}"')
print(f'flag_yaml_path = "{flag_yaml_path}"')
```
JD = 2458203
data_path = "/lustre/aoc/projects/hera/H1C_IDR3/IDR3_2/2458203"
flag_yaml_path = "/lustre/aoc/projects/hera/H1C_IDR3/IDR3_2/h1c_idr3_software/hera_pipelines/pipelines/h1c/idr3/v2/a_priori_flags"
```python
utc = Time(JD, format='jd').datetime
print(f'Date: {utc.month}-{utc.day}-{utc.year}')
```
Date: 3-25-2018
```python
# Load in data
HHfiles, uvdx, uvdy = utils.load_data(data_path,JD)
ex_ants = utils.read_a_priori_ant_flags(f'{flag_yaml_path}/{JD}.yaml')
uv = UVData()
unread = True
readInd=0
while unread and readInd<len(HHfiles):
try:
uv.read(HHfiles[readInd])
unread = False
except:
readInd += 1
continue
ants = uv.antenna_numbers
use_ants = [ant for ant in ants if ant not in ex_ants]
uvd = UVData()
uvd.read(HHfiles, ant_str='auto')
uvd.select(antenna_nums=use_ants)
lsts = uvd.lst_array
uvdx.select(antenna_nums=use_ants)
uvdy.select(antenna_nums=use_ants)
```
73 sum files found between JDs 2458203.12526 and 2458203.66213
## Sky Coverage Map
Map of the sky (made using the Haslam 408MHz map). The RA/DEC range covered by this night of observation is shaded based on a 12 degree FWHM of the beam. Horizontal dashed lines represent the stripe that HERA can observe, while the shaded region is what was observed on this night. Vertical lines represent the beginning and ending LSTs of this observation. Selected sources are labelled, sources included are those in the GLEAM 4Jy catalog with a flux >10.9 Jy. Note that the map is clipped at the northern horizon.
```python
sources = utils.gather_source_list()
utils.plot_sky_map(uvd,dec_pad=55,ra_pad=55,clip=False,sources=sources)
```
## LST Coverage
Shows the LSTs (in hours) and JDs for which data is collected. Green represents data, red means no data.
```python
utils.plot_lst_coverage(uvd)
```
## Autocorrelations for a single file
This plot shows autocorrelations for one timestamp of each antenna that is active and each polarization. For each node, antennas are ordered by SNAP number, and within that by SNAP input number. The antenna number label color corresponds to the a priori status of that antenna.
```python
### plot autos
utils.plot_autos(uvdx, uvdy)
```
## Waterfalls of Autocorrelation Amplitudes for each Antenna and Each polarization
These plots show autocorrelation waterfalls of each antenna that is active and whose status qualifies for this notebook. For each node, antennas are ordered by SNAP number, and within that by SNAP input number. The antenna number label color corresponds to the a priori status of that antenna.
```python
utils.plot_wfs(uvd, pol = 0)
```
```python
utils.plot_wfs(uvd, pol = 1)
```
## Correlation Metrics
The first plot shows the correlation metric (described below) for a set of baseline types, as calculated at several times throughout the night. It is expected that longer baselines (darker color) will exhibit lower values than the short baselines.
The matrices show the phase correlation between antennas. Using the even and odd visibilities, each pixel is calculated as (even/abs(even)) * (conj(odd)/abs(odd)), and then averaged across time and frequency. If the phases are noise-like, this value will average down to zero. If the antennas are well correlated, the phases should not be noise-like, and this value should average to 1. The lines denoting node boundaries are intended to help confirm that inter-node correlations are functioning - if they aren't, this plot will appear block-diagonal.
This metric has shown to be LST locked - when comparing to other nights, be sure to compare for the same LST. It is expected that some LSTs will look much better or worse than others.
Note: Within each node, the order of antennas is determined by snap, and within that by snap input number.
```python
badAnts = []
badAnts = utils.plotNodeAveragedSummary(uvd,HHfiles,JD,use_ants,mat_pols=['xx','yy','xy','yx'])
```
## Antenna Positions
Antennas outlined in black here have been identified by the correlation matrix as bad antennas. Antennas with a colorful outline correspond to their status as identified by ant_metrics (see above plot). Faded antennas are those not meeting the apriori status requirement for this notebook run. Gold stars are node box locations.
```python
uvd1 = UVData()
uvd1.read(HHfiles[readInd], skip_bad_files=True)
utils.plot_antenna_positions(uvd1, badAnts=badAnts,use_ants=use_ants)
```
## Mean-Subtracted Waterfalls
Here the mean value in each frequency bin has been subtracted out. This effectively subtracts out the bandpass shape, making time variations more visible.
```python
utils.plot_wfs(uvd,0,mean_sub=True,jd=JD)
utils.plot_wfs(uvd,1,mean_sub=True,jd=JD)
```
```python
```
|
HERA-TeamREPO_NAMEH1C_IDR3_NotebooksPATH_START.@H1C_IDR3_Notebooks-main@data_inspect@data_inspect_2458203.ipynb@.PATH_END.py
|
{
"filename": "_isomin.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/isosurface/_isomin.py",
"type": "Python"
}
|
import _plotly_utils.basevalidators
class IsominValidator(_plotly_utils.basevalidators.NumberValidator):
def __init__(self, plotly_name="isomin", parent_name="isosurface", **kwargs):
super(IsominValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edit_type=kwargs.pop("edit_type", "calc"),
role=kwargs.pop("role", "info"),
**kwargs
)
|
catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@isosurface@_isomin.py@.PATH_END.py
|
{
"filename": "PeriodicityDetector_quickstart.ipynb",
"repo_name": "SPARTA-dev/SPARTA",
"repo_path": "SPARTA_extracted/SPARTA-master/examples/PeriodicityDetector_quickstart.ipynb",
"type": "Jupyter Notebook"
}
|
# Periodicity detector class tutorial
-----------------------------------
### 1 Using the PeriodicityDetector class to run PDC on simulated velocity times series
`Observations` class enables one to load observation data from a given folder
and place it into a TimeSeries object, or to load an existing time series.
In this case we will choose the latter.
```python
import sys, numpy as np
```
```python
# A time series object is the place holder for the set
# of spectra an\or velocities we wish to analyze.
from sparta.Auxil.TimeSeries import TimeSeries
# Observations class recieves a TimeSeries object and
# manages the relevant routines.
from sparta import Observations
# Is we wish ot directly hangle datasets of spectra,
# this is done using the Spectrum class.
from sparta.UNICOR.Spectrum import Spectrum
# The Template class is a wrapper foor the spectrum class,
# that enables retrieval of spectra from online PHOENIX
# repositories, and some additional features.
from sparta.UNICOR.Template import Template
```
In the example below we simulate a sinewave of scalars. We can think of it as the radial velocity of a star.
```python
# Generate timeseries as a sinewave with some noise...
period = 5
size = 25
times = [(np.random.rand() * 100) for _ in range(size)]
vals = [np.sin(t * 2 * np.pi / period) + 0.3*np.random.randn() for t in times]
```
```python
# Read the data into the time series
time_series = TimeSeries(size=size, times=times, vals=vals, fold_period=period)
# You can plot it if you want
time_series.plot_velocities()
```
#### The Observations class recieves the TimeSeries object, and initialized
```python
# If we wish the Observations object to read a set of spectra
# we can initialize it with some requirements, such as the wavelength range
# that we wish to use of the SNR limits. The simplest thing to do, though,
# is probably feeding it with a timeseries object directly.
obs = Observations(time_series=time_series)
```
```python
# Another initizalization that is required, is the initialization of the frequency
# grid. This is slightly weird, but we have several different periodograms
# and dound it useful that they use the same rage by default.
# This row essentially initializes a PeriodicityDetector object and puts it in
# observations, where the data are stored.
obs.initialize_periodicity_detector(periodogram_grid_resolution=1000, freq_range=(0.01, 1))
```
<br />
Now using the PeriodicityDetector to detect periodicity in the data using the GLS and PDC method is posible:
<br />
```python
_ = obs.periodicity_detector.calc_PDC()
_ = obs.periodicity_detector.calc_GLS()
```
```python
# If we have a suspected period, we can provide it so that it is
# plotted as a vertical line inf the periodogram
obs.periodicity_detector.period_truth = [5]
obs.periodicity_detector.plot_periodograms(annotate_pval=[1e-2,1e-3])
```
### 2. Using the PeriodicityDetector class to run USuRPer on simulated spectra
In the following code segment we simulate a single-line stereoscopic binary system (SB1) and using sparta classes to detect
periodicity in the data using USuRPer.
First we initiate a Template object containing Phoenix library synthetic spectra.
```python
# Assigning sun-like stellar parameters to the simulated spectra
temp = 4900
log_g = 4.5
metal = 0
alpha = 0
# Choosing wavelength range (Angstrom units)
min_val = 4900
max_val = 5100
# Loading a Phoenix synthetic spectrum
template = Template(temp=temp, log_g=log_g, metal=metal,
alpha=alpha, min_val=min_val, max_val=max_val)
```
At this point, we use the template to simulate a single-line stereoscopic binary system (SB1) by generating 50 visits over 100 days,
and shifting them in sinusoidal wave velocities.
We represent the series in a TimeSeries object, then assigning it to an Observations object.
```python
p = 5 # Assigning a five-day long period to the system.
semi_amp = 100 # Assigning a 100 km/s amplitude to the velocity semi amplitude
N = 50 # Setting the number of observations to be 50
times = [(np.random.rand() * 100) for _ in range(N)]
vals = [semi_amp * np.sin(2 * t * np.pi / p) for t in times]
visit_spec_list = []
for i, v in enumerate(vals):
new_wl = template.doppler(v)
new_temp = Spectrum(wv=new_wl, sp=template.add_noise(-1)).SpecPreProccess()
visit_spec_list.append(new_temp)
ts = TimeSeries(size=N, times=times, vals=visit_spec_list,
calculated_vrad_list=[])
obs = Observations(time_series=ts)
```
Now we can run USURPER to detect periodicity in the observations, and print out the resulted periodogram.
```python
obs.initialize_periodicity_detector(freq_range=(1/1000, 1), periodogram_grid_resolution=1000)
obs.periodicity_detector.calc_USURPER()
obs.periodicity_detector.period_truth = [5]
obs.periodicity_detector.plot_periodograms(annotate_pval=[1e-2,1e-3])
```
|
SPARTA-devREPO_NAMESPARTAPATH_START.@SPARTA_extracted@SPARTA-master@examples@PeriodicityDetector_quickstart.ipynb@.PATH_END.py
|
{
"filename": "testing.py",
"repo_name": "ytree-project/ytree",
"repo_path": "ytree_extracted/ytree-main/ytree/utilities/testing.py",
"type": "Python"
}
|
"""
testing utilities
"""
#-----------------------------------------------------------------------------
# Copyright (c) ytree development team. All rights reserved.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file COPYING.txt, distributed with this software.
#-----------------------------------------------------------------------------
import h5py
import numpy as np
from numpy.testing import \
assert_equal, \
assert_almost_equal, \
assert_array_equal
import os
import shutil
import subprocess
import sys
import tempfile
from unittest import \
skipIf, TestCase
from yt.funcs import \
get_pbar
from ytree.data_structures.load import load
from ytree.frontends.ytree import YTreeArbor
from ytree.utilities.io import dirname
from ytree.utilities.loading import check_path, get_path
from ytree.utilities.logger import ytreeLogger as mylog
try:
from mpi4py import MPI
except ModuleNotFoundError:
MPI = None
generate_results = \
int(os.environ.get("YTREE_GENERATE_TEST_RESULTS", 0)) == 1
def requires_file(filename):
def ffalse(func):
return None
def ftrue(func):
return func
if not isinstance(filename, list):
filename = [filename]
try:
[get_path(fn) for fn in filename]
except IOError:
return ffalse
return ftrue
class TempDirTest(TestCase):
"""
A test class that runs in a temporary directory and
removes it afterward.
"""
def setUp(self):
self.curdir = os.getcwd()
self.tmpdir = tempfile.mkdtemp()
os.chdir(self.tmpdir)
def tearDown(self):
os.chdir(self.curdir)
shutil.rmtree(self.tmpdir)
class ParallelTest:
"""
Test class for ytree parallelism.
"""
base_filename = "tiny_ctrees/locations.dat"
test_filename = "test_arbor/test_arbor.h5"
test_script = None
ncores = 4
def check_values(self, arbor, my_args):
group = my_args[1]
assert_array_equal(arbor["test_field"], 2 * arbor["mass"])
for tree in arbor:
assert_array_equal(tree[group, "test_field"], 2 * tree[group, "mass"])
@skipIf(MPI is None, "mpi4py not installed")
def test_parallel(self):
for i, my_args in enumerate(self.arg_sets):
with self.subTest(i=i):
args = [self.test_script, self.base_filename, self.test_filename] + \
[str(arg) for arg in my_args]
comm = MPI.COMM_SELF.Spawn(sys.executable, args=args, maxprocs=self.ncores)
comm.Disconnect()
test_arbor = load(self.test_filename)
self.check_values(test_arbor, my_args)
def run_command(command, timeout=None):
try:
proc = subprocess.run(command, shell=True, timeout=timeout)
if proc.returncode == 0:
success = True
else:
success = False
except subprocess.TimeoutExpired:
print ("Process reached timeout of %d s. (%s)" % (timeout, command))
success = False
except KeyboardInterrupt:
print ("Killed by keyboard interrupt!")
success = False
return success
class ExampleScriptTest:
"""
Tests for the code examples.
"""
script_filename = None
input_filename = None
timeout = 60
output_files = ()
ncores = 1
def test_example(self):
if self.script_filename is None:
return
if self.input_filename is not None:
try:
check_path(self.input_filename)
except IOError:
self.skipTest("test file missing")
source_dir = dirname(__file__, level=3)
script_path = os.path.join(
source_dir, "doc", "source", "examples", self.script_filename)
if self.ncores > 1:
if MPI is None:
self.skipTest("mpi4py not installed")
comm = MPI.COMM_SELF.Spawn(sys.executable, args=[script_path],
maxprocs=self.ncores)
comm.Disconnect()
else:
command = f"{sys.executable} {script_path}"
assert run_command(command, timeout=self.timeout)
for fn in self.output_files:
assert os.path.exists(fn)
class ArborTest:
"""
A battery of tests for all frontends.
"""
arbor_type = None
test_filename = None
load_kwargs = None
groups = ("tree", "prog")
num_data_files = None
tree_skip = 1
_arbor = None
@property
def arbor(self):
if self._arbor is None:
try:
self.test_filename = get_path(self.test_filename)
except IOError:
self.skipTest("test file missing")
if self.load_kwargs is None:
self.load_kwargs = {}
self._arbor = load(self.test_filename, **self.load_kwargs)
return self._arbor
def test_arbor_type(self):
assert isinstance(self.arbor, self.arbor_type)
def test_data_files(self):
if self.num_data_files is None:
return
assert_equal(
len(self.arbor.data_files), self.num_data_files,
err_msg=f'Incorrect number of data files for {self.arbor}.')
def test_get_root_nodes(self):
for my_tree in get_random_trees(self.arbor, 47457, 5):
verify_get_root_nodes(my_tree)
def test_get_roor_nodes_nonroot(self):
my_tree = list(self.arbor[0].ancestors)[0]
verify_get_root_nodes(my_tree)
def test_get_leaf_nodes(self):
for my_tree in get_random_trees(self.arbor, 41153, 5):
verify_get_leaf_nodes(my_tree)
def test_get_leaf_nodes_ungrown_nonroot(self):
my_tree = list(self.arbor[0].ancestors)[0]
verify_get_leaf_nodes(my_tree)
def test_get_node(self):
for my_tree in get_random_trees(self.arbor, 47988, 5):
verify_get_node(my_tree)
ihalos = np.arange(1, my_tree.tree_size)
np.random.shuffle(ihalos)
for ihalo in ihalos[:3]:
my_halo = my_tree.get_node("forest", ihalo)
verify_get_node(my_halo)
def test_get_node_ungrown_nonroot(self):
my_tree = list(self.arbor[0].ancestors)[0]
my_halo = my_tree.get_node("forest", 0)
node_list = list(my_tree["forest"])
assert_equal(my_halo.uid, node_list[0].uid)
def test_reset_node(self):
t = self.arbor[0]
ts0 = len(list(t['tree']))
f0 = dict((field, t['tree', field])
for field in ['uid', 'desc_uid'])
assert self.arbor.is_setup(t)
assert self.arbor.is_grown(t)
self.arbor.reset_node(t)
for attr in self.arbor._reset_attrs:
assert getattr(t, attr) is None
assert_equal(len(t.field_data), 0)
assert not self.arbor.is_setup(t)
assert not self.arbor.is_grown(t)
assert_equal(
len(list(t['tree'])), ts0,
err_msg=f'Trees are not the same size after resetting for {self.arbor}.')
for field in f0:
assert_array_equal(
t['tree', field], f0[field],
err_msg=f"Tree field {field} not the same after resetting for {self.arbor}.")
def test_reset_nonroot(self):
t = self.arbor[0]
node = list(t['tree'])[1]
ts0 = len(list(node['tree']))
f0 = dict((field, node['tree', field])
for field in ['uid', 'desc_uid'])
self.arbor.reset_node(node)
assert_equal(
len(list(node['tree'])), ts0,
err_msg=f'Trees are not the same size after resetting for {self.arbor}.')
for field in f0:
assert_array_equal(
node['tree', field], f0[field],
err_msg=f"Tree field {field} not the same after resetting for {self.arbor}.")
def test_save_and_reload(self):
save_and_compare(self.arbor, groups=self.groups, skip=self.tree_skip)
def test_vector_fields(self):
a = self.arbor
t = a[0]
for field in a.field_info.vector_fields:
mylog.info(f"Comparing vector field: {field}.")
magfield = np.sqrt((a[field]**2).sum(axis=1))
assert_array_equal(a[f"{field}_magnitude"], magfield,
err_msg=f"Magnitude field incorrect: {field}.")
for i, ax in enumerate("xyz"):
assert_array_equal(
a[f"{field}_{ax}"], a[field][:, i],
err_msg=(f"Arbor vector field {field} does not match "
f"in dimension {i}."))
assert_array_equal(
t[f"{field}_{ax}"], t[field][i],
err_msg=(f"Tree vector field {field} does not match "
f"in dimension {i}."))
for group in ["prog", "tree"]:
assert_array_equal(
t[group, f"{field}_{ax}"], t[group, field][:, i],
err_msg=(f"{group} vector field {field} does not match "
f"in dimension {i}."))
def get_tree_split(arbor):
"""
Get a few separate ancestors from a tree.
"""
ancs = None
for tree in arbor:
for halo in tree["tree"]:
ancs = list(halo.ancestors)
if len(ancs) > 1:
break
if ancs is None:
raise RuntimeError("Could not find nodes to test with.")
return ancs
def get_random_trees(arbor, seed, n):
"""
Get n random trees from the arbor.
"""
np.random.seed(seed)
itrees = np.arange(arbor.size)
np.random.shuffle(itrees)
for itree in itrees[:5]:
yield arbor[itree]
def save_and_compare(arbor, skip=1, groups=None):
"""
Check that arbor saves correctly.
"""
if skip > 1:
trees = list(arbor[::skip])
else:
trees = None
fn = arbor.save_arbor(trees=trees)
save_arbor = load(fn)
assert isinstance(save_arbor, YTreeArbor)
compare_arbors(save_arbor, arbor, groups=groups, skip2=skip)
def compare_arbors(a1, a2, groups=None, fields=None, skip1=1, skip2=1):
"""
Compare all fields for all trees in two arbors.
"""
if groups is None:
groups = ["tree", "prog"]
if fields is None:
fields = a1.field_list
for i, field in enumerate(fields):
mylog.info(f"Comparing arbor field: {field} ({i+1}/{len(fields)}).")
assert_array_equal(a1[field][::skip1], a2[field][::skip2],
err_msg=f"Arbor field mismatch: {a1, a2, field}.")
trees1 = list(a1[::skip1])
trees2 = list(a2[::skip2])
ntot = len(trees1)
pbar = get_pbar("Comparing trees", ntot)
for i, (t1, t2) in enumerate(zip(trees1, trees2)):
compare_trees(t1, t2, groups=groups, fields=fields)
pbar.update(i+1)
pbar.finish()
def compare_trees(t1, t2, groups=None, fields=None):
"""
Compare all fields between two trees.
"""
if groups is None:
groups = ["tree", "prog"]
if fields is None:
fields = t1.arbor.field_list
for field in fields:
for group in groups:
assert_array_equal(
t1[group, field], t2[group, field],
err_msg=f"Tree comparison failed for {group} field: {field}.")
t1.arbor.reset_node(t1)
t2.arbor.reset_node(t2)
def compare_hdf5(fh1, fh2, compare=None, compare_groups=True,
**kwargs):
"""
Compare all datasets between two hdf5 files.
"""
if compare is None:
compare = assert_array_equal
if not isinstance(fh1, h5py.Group):
fh1 = h5py.File(fh1, "r")
if not isinstance(fh2, h5py.Group):
fh2 = h5py.File(fh2, "r")
if compare_groups:
err_msg = f"{fh1.file.filename} and {fh2.file.filename} have different datasets in group {fh1.name}."
assert_equal(sorted(list(fh1.keys())), sorted(list(fh2.keys())), err_msg=err_msg)
for key in fh1.keys():
if isinstance(fh1[key], h5py.Group):
compare_hdf5(fh1[key], fh2[key],
compare_groups=compare_groups,
compare=compare, **kwargs)
else:
err_msg = f"{key} field not equal for {fh1.file.filename} and {fh2.file.filename}"
if fh1[key].dtype == "int":
assert_array_equal(fh1[key][()], fh2[key][()],
err_msg=err_msg)
else:
compare(fh1[key][()], fh2[key][()],
err_msg=err_msg, **kwargs)
def assert_rel_equal(a1, a2, decimals, err_msg="", verbose=True):
# We have nan checks in here because occasionally we have fields that get
# weighted without non-zero weights. I'm looking at you, particle fields!
if isinstance(a1, np.ndarray):
assert a1.size == a2.size
# Mask out NaNs
assert (np.isnan(a1) == np.isnan(a2)).all()
a1[np.isnan(a1)] = 1.0
a2[np.isnan(a2)] = 1.0
# Mask out 0
ind1 = np.array(np.abs(a1) < np.finfo(a1.dtype).eps)
ind2 = np.array(np.abs(a2) < np.finfo(a2.dtype).eps)
assert (ind1 == ind2).all()
a1[ind1] = 1.0
a2[ind2] = 1.0
elif np.any(np.isnan(a1)) and np.any(np.isnan(a2)):
return True
if not isinstance(a1, np.ndarray) and a1 == a2 == 0.0:
# NANS!
a1 = a2 = 1.0
return assert_almost_equal(
np.array(a1) / np.array(a2), 1.0, decimals, err_msg=err_msg, verbose=verbose
)
def assert_array_rel_equal(a1, a2, decimals=16, **kwargs):
"""
Wraps assert_rel_equal with, but decimals is a keyword arg.
"""
assert_rel_equal(a1, a2, decimals, **kwargs)
def verify_get_node(my_tree, n=3):
"""
Unit tests for get_node.
"""
for selector in ["forest", "tree", "prog"]:
node_list = list(my_tree[selector])
inodes = np.arange(len(node_list))
np.random.shuffle(inodes)
for inode in inodes[:3]:
my_node = my_tree.get_node(selector, inode)
err_msg = f"get_node failed: {selector} " + \
f"with {str(my_tree.arbor)}."
assert_equal(my_node.uid, node_list[inode].uid, err_msg=err_msg)
if selector == "forest":
err_msg = "get_node index is not tree_id for " + \
f"{str(my_tree.arbor)}."
assert_equal(my_node.tree_id, inode, err_msg=err_msg)
def verify_get_leaf_nodes(my_tree):
"""
Unit tests for get_leaf_nodes.
"""
for selector in ["forest", "tree", "prog"]:
uids1 = np.array([node.uid for node in
my_tree.get_leaf_nodes(selector=selector)])
uids2 = np.array([my_halo.uid for my_halo in my_tree[selector]
if not list(my_halo.ancestors)])
err_msg=f"get_leaf_nodes failure for {selector} in {my_tree.arbor}."
assert_equal(uids1, uids2, err_msg=err_msg)
def verify_get_root_nodes(my_tree):
"""
Unit tests for get_root_nodes.
"""
root_nodes1 = list(my_tree.get_root_nodes())
for root_node in root_nodes1:
assert_equal(root_node["desc_uid"], -1)
root_nodes2 = [node for node in my_tree["forest"]
if node.descendent is None]
uids1 = np.sort([node.uid for node in root_nodes1])
uids2 = np.sort([node.uid for node in root_nodes2])
assert_array_equal(
uids1, uids2,
err_msg=f"get_root_nodes failure in {my_tree.arbor}.")
|
ytree-projectREPO_NAMEytreePATH_START.@ytree_extracted@ytree-main@ytree@utilities@testing.py@.PATH_END.py
|
{
"filename": "test_util.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/jax/_src/test_util.py",
"type": "Python"
}
|
# Copyright 2018 The JAX Authors.
#
# 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
#
# https://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.
# pyformat: disable
from __future__ import annotations
import collections
from collections.abc import Callable, Generator, Iterable, Sequence
from contextlib import ExitStack, contextmanager
import datetime
import functools
from functools import partial
import inspect
import logging
import math
import os
import platform
import re
import sys
import tempfile
import textwrap
from typing import Any, TextIO
import unittest
import warnings
import zlib
from absl.testing import absltest
from absl.testing import parameterized
import jax
from jax import lax
from jax._src import api
from jax._src import array
from jax._src import config
from jax._src import core
from jax._src import dispatch
from jax._src import dtypes as _dtypes
from jax._src import lib as _jaxlib
from jax._src import linear_util as lu
from jax._src import monitoring
from jax._src import pjit as pjit_lib
from jax._src import stages
from jax._src import xla_bridge
from jax._src import mesh as mesh_lib
from jax._src.cloud_tpu_init import running_in_cloud_tpu_vm
from jax._src.interpreters import mlir
from jax._src.interpreters import pxla
from jax._src.lib import xla_client as xc
from jax._src.numpy.util import promote_dtypes, promote_dtypes_inexact
from jax._src.public_test_util import ( # noqa: F401
_assert_numpy_allclose, _check_dtypes_match, _default_tolerance, _dtype, check_close, check_grads,
check_jvp, check_vjp, default_gradient_tolerance, default_tolerance, rand_like, tolerance)
from jax._src.util import unzip2
from jax.experimental.compilation_cache import compilation_cache
from jax.tree_util import tree_all, tree_flatten, tree_map, tree_unflatten
import numpy as np
import numpy.random as npr
# This submodule includes private test utilities that are not exported to
# jax.test_util. Functionality appearing here is for internal use only, and
# may be changed or removed at any time and without any deprecation cycle.
_TEST_DUT = config.string_flag(
'jax_test_dut', '',
help=
'Describes the device under test in case special consideration is required.'
)
NUM_GENERATED_CASES = config.int_flag(
'jax_num_generated_cases',
int(os.getenv('JAX_NUM_GENERATED_CASES', '10')),
help='Number of generated cases to test')
_MAX_CASES_SAMPLING_RETRIES = config.int_flag(
'max_cases_sampling_retries',
int(os.getenv('JAX_MAX_CASES_SAMPLING_RETRIES', '100')),
'Number of times a failed test sample should be retried. '
'When an unseen case cannot be generated in this many trials, the '
'sampling process is terminated.'
)
_SKIP_SLOW_TESTS = config.bool_flag(
'jax_skip_slow_tests',
config.bool_env('JAX_SKIP_SLOW_TESTS', False),
help='Skip tests marked as slow (> 5 sec).'
)
_TEST_TARGETS = config.string_flag(
'test_targets', os.getenv('JAX_TEST_TARGETS', ''),
'Regular expression specifying which tests to run, called via re.search on '
'the test name. If empty or unspecified, run all tests.'
)
_EXCLUDE_TEST_TARGETS = config.string_flag(
'exclude_test_targets', os.getenv('JAX_EXCLUDE_TEST_TARGETS', ''),
'Regular expression specifying which tests NOT to run, called via re.search '
'on the test name. If empty or unspecified, run all tests.'
)
TEST_WITH_PERSISTENT_COMPILATION_CACHE = config.bool_flag(
'jax_test_with_persistent_compilation_cache',
config.bool_env('JAX_TEST_WITH_PERSISTENT_COMPILATION_CACHE', False),
help='If enabled, the persistent compilation cache will be enabled for all '
'test cases. This can be used to increase compilation cache coverage.')
HYPOTHESIS_PROFILE = config.string_flag(
'hypothesis_profile',
os.getenv('JAX_HYPOTHESIS_PROFILE', 'deterministic'),
help=('Select the hypothesis profile to use for testing. Available values: '
'deterministic, interactive'),
)
# We sanitize test names to ensure they work with "unitttest -k" and
# "pytest -k" test filtering. pytest accepts '[' and ']' but unittest -k
# does not. We replace sequences of problematic characters with a single '_'.
kSanitizeNameRE = re.compile(r"[ \"'\[\](){}<>=,._]+")
def sanitize_test_name(s: str) -> str:
return kSanitizeNameRE.sub("_", s)
def num_float_bits(dtype):
return _dtypes.finfo(_dtypes.canonicalize_dtype(dtype)).bits
def to_default_dtype(arr):
"""Convert a value to an array with JAX's default dtype.
This is generally used for type conversions of values returned by numpy functions,
to make their dtypes take into account the state of the ``jax_enable_x64`` and
``jax_default_dtype_bits`` flags.
"""
arr = np.asarray(arr)
dtype = _dtypes._default_types.get(arr.dtype.kind)
return arr.astype(_dtypes.canonicalize_dtype(dtype)) if dtype else arr
def with_jax_dtype_defaults(func, use_defaults=True):
"""Return a version of a function with outputs that match JAX's default dtypes.
This is generally used to wrap numpy functions within tests, in order to make
their default output dtypes match those of corresponding JAX functions, taking
into account the state of the ``jax_enable_x64`` and ``jax_default_dtype_bits``
flags.
Args:
use_defaults : whether to convert any given output to the default dtype. May be
a single boolean, in which case it specifies the conversion for all outputs,
or may be a pytree with the same structure as the function output.
"""
@functools.wraps(func)
def wrapped(*args, **kwargs):
result = func(*args, **kwargs)
if isinstance(use_defaults, bool):
return tree_map(to_default_dtype, result) if use_defaults else result
else:
f = lambda arr, use_default: to_default_dtype(arr) if use_default else arr
return tree_map(f, result, use_defaults)
return wrapped
def is_sequence(x):
try:
iter(x)
except TypeError:
return False
else:
return True
def _normalize_tolerance(tol):
tol = tol or 0
if isinstance(tol, dict):
return {np.dtype(k): v for k, v in tol.items()}
else:
return dict.fromkeys(_default_tolerance, tol)
def join_tolerance(tol1, tol2):
tol1 = _normalize_tolerance(tol1)
tol2 = _normalize_tolerance(tol2)
out = tol1
for k, v in tol2.items():
out[k] = max(v, tol1.get(k, 0))
return out
def check_eq(xs, ys, err_msg=''):
assert_close = partial(_assert_numpy_allclose, err_msg=err_msg)
tree_all(tree_map(assert_close, xs, ys))
@contextmanager
def _capture_output(fp: TextIO) -> Generator[Callable[[], str], None, None]:
"""Context manager to capture all output written to a given file object.
Unlike ``contextlib.redirect_stdout``, this context manager works for
any file object and also for both pure Python and native code.
Example::
with capture_output(sys.stdout) as get_output:
print(42)
print("Captured": get_output())
Yields:
A function returning the captured output. The function must be called
*after* the context is no longer active.
"""
# ``None`` means nothing has not been captured yet.
captured = None
def get_output() -> str:
if captured is None:
raise ValueError("get_output() called while the context is active.")
return captured
with tempfile.NamedTemporaryFile(mode="w+", encoding='utf-8') as f:
original_fd = os.dup(fp.fileno())
os.dup2(f.fileno(), fp.fileno())
try:
yield get_output
finally:
# Python also has its own buffers, make sure everything is flushed.
fp.flush()
os.fsync(fp.fileno())
f.seek(0)
captured = f.read()
os.dup2(original_fd, fp.fileno())
capture_stdout = partial(_capture_output, sys.stdout)
capture_stderr = partial(_capture_output, sys.stderr)
@contextmanager
def count_device_put():
batched_device_put = pxla.batched_device_put
count = [0]
def make_fn_and_count(fn):
def fn_and_count(*args, **kwargs):
count[0] += 1
# device_put handlers might call `dispatch.device_put` (e.g. on an
# underlying payload or several). We only want to count these
# recursive puts once, so we skip counting more than the outermost
# one in such a call stack.
pxla.batched_device_put = batched_device_put
try:
return fn(*args, **kwargs)
finally:
pxla.batched_device_put = batched_device_put_and_count
return fn_and_count
batched_device_put_and_count = make_fn_and_count(batched_device_put)
pxla.batched_device_put = batched_device_put_and_count
try:
yield count
finally:
pxla.batched_device_put = batched_device_put
@contextmanager
def count_primitive_compiles():
dispatch.xla_primitive_callable.cache_clear()
count = [-1]
try:
yield count
finally:
count[0] = dispatch.xla_primitive_callable.cache_info().misses
@contextmanager
def count_device_put_fast_path_hit():
original_fn = xc.batched_copy_array_to_devices_with_sharding
count = [0]
def batched_copy_array_to_devices_with_sharding_and_count(*args, **kwargs):
count[0] += 1
return original_fn(*args, **kwargs)
xc.batched_copy_array_to_devices_with_sharding = batched_copy_array_to_devices_with_sharding_and_count
try:
yield count
finally:
xc.batched_copy_array_to_devices_with_sharding = original_fn
@contextmanager
def count_pjit_cpp_cache_miss():
original_pjit_lower = pjit_lib._pjit_lower
count = [0]
def pjit_lower_and_count(*args, **kwargs):
count[0] += 1
return original_pjit_lower(*args, **kwargs)
pjit_lib._pjit_lower = pjit_lower_and_count
try:
yield count
finally:
pjit_lib._pjit_lower = original_pjit_lower
@contextmanager
def count_cached_compilation_cache_miss():
original_cached_compilation = pxla._cached_compilation
count = [0]
def cached_compilation_and_count(*args, **kwargs):
count[0] += 1
return original_cached_compilation(*args, **kwargs)
pxla._cached_compilation = cached_compilation_and_count
try:
yield count
finally:
pxla._cached_compilation = original_cached_compilation
@contextmanager
def count_jit_tracing_cache_miss():
original_create_pjit_jaxpr = pjit_lib._create_pjit_jaxpr
count = [0]
@lu.cache
def create_pjit_jaxpr_and_count(*args):
count[0] += 1
return original_create_pjit_jaxpr(*args)
pjit_lib._create_pjit_jaxpr = create_pjit_jaxpr_and_count
try:
yield count
finally:
pjit_lib._create_pjit_jaxpr = original_create_pjit_jaxpr
@contextmanager
def count_jit_infer_params_cache_miss():
original_infer_params_impl = pjit_lib._infer_params_impl
count = collections.defaultdict(int)
def infer_params_impl_and_count(fun, *args, **kw):
count[fun] += 1
return original_infer_params_impl(fun, *args, **kw)
pjit_lib._infer_params_impl = infer_params_impl_and_count
try:
yield count
finally:
pjit_lib._infer_params_impl = original_infer_params_impl
@contextmanager
def count_aot_jit_cpp_cache_miss():
original_call = stages.Compiled.call
count = [0]
def compiled_call_count(*args, **kwargs):
count[0] += 1
return original_call(*args, **kwargs)
stages.Compiled.call = compiled_call_count
try:
yield count
finally:
stages.Compiled.call = original_call
@contextmanager
def count_jit_and_pmap_lowerings():
# No need to clear any caches since we generally jit and pmap fresh callables
# in tests.
mlir_lower = mlir.lower_jaxpr_to_module
count = [0]
def mlir_lower_and_count(*args, **kwargs):
count[0] += 1
return mlir_lower(*args, **kwargs)
mlir.lower_jaxpr_to_module = mlir_lower_and_count
try:
yield count
finally:
mlir.lower_jaxpr_to_module = mlir_lower
@contextmanager
def count_jax_array_shard_arg_calls():
# No need to clear any caches since we generally jit and pmap fresh callables
# in tests.
array_shard_arg = array._array_shard_arg
count = [0]
def array_shard_arg_and_count(*args, **kwargs):
count[0] += 1
return array_shard_arg(*args, **kwargs)
pxla.shard_arg_handlers[array.ArrayImpl] = array_shard_arg_and_count
try:
yield count
finally:
pxla.shard_arg_handlers[array.ArrayImpl] = array_shard_arg
@contextmanager
def count_jit_compilation_cache_miss():
# No need to clear any caches since we generally jit and pmap fresh callables
# in tests.
jit_compilation = pxla._cached_compilation
count = [0]
def compile_and_count(*args, **kwargs):
count[0] += 1
return jit_compilation(*args, **kwargs)
pxla._cached_compilation = compile_and_count
try:
yield count
finally:
pxla._cached_compilation = jit_compilation
@contextmanager
def count_subjaxpr_to_hlo_conversion(fun_name: str):
# No need to clear any caches since we generally jit and pmap fresh callables
# in tests.
mlir_lower = mlir.lower_jaxpr_to_fun
count = [0]
def mlir_lower_and_count(ctx, name, *args, **kwargs):
if name == fun_name:
count[0] += 1
return mlir_lower(ctx, name, *args, **kwargs)
mlir.lower_jaxpr_to_fun = mlir_lower_and_count
try:
yield count
finally:
mlir.lower_jaxpr_to_fun = mlir_lower
@contextmanager
def assert_num_jit_and_pmap_compilations(times):
with count_jit_and_pmap_lowerings() as count:
yield
if count[0] != times:
raise AssertionError(f"Expected exactly {times} XLA compilations, "
f"but executed {count[0]}")
def jaxlib_version() -> tuple[int, ...]:
return _jaxlib.version
def device_under_test():
return _TEST_DUT.value or xla_bridge.get_backend().platform
def supported_dtypes():
if device_under_test() == "tpu":
types = {np.bool_, np.int8, np.int16, np.int32, np.uint8, np.uint16,
np.uint32, _dtypes.bfloat16, np.float16, np.float32, np.complex64,
_dtypes.float8_e4m3fn, _dtypes.float8_e4m3b11fnuz,
_dtypes.float8_e5m2}
elif device_under_test() == "gpu":
types = {np.bool_, np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64,
_dtypes.bfloat16, np.float16, np.float32, np.float64,
np.complex64, np.complex128, _dtypes.float8_e4m3fn,
_dtypes.float8_e5m2}
elif device_under_test() == "METAL":
types = {np.int32, np.uint32, np.float32}
else:
types = {np.bool_, np.int8, np.int16, np.int32, np.int64,
np.uint8, np.uint16, np.uint32, np.uint64,
_dtypes.bfloat16, np.float16, np.float32, np.float64,
np.complex64, np.complex128}
if not config.enable_x64.value:
types -= {np.uint64, np.int64, np.float64, np.complex128}
return types
def is_device_rocm():
return 'rocm' in xla_bridge.get_backend().platform_version
def is_device_cuda():
return 'cuda' in xla_bridge.get_backend().platform_version
def is_cloud_tpu():
return running_in_cloud_tpu_vm
# Returns True if it is not cloud TPU. If it is cloud TPU, returns True if it is
# built at least `date``.
# TODO(b/327203806): after libtpu adds a XLA version and the oldest support
# libtpu contains the XLA version, remove using built time to skip tests.
def if_cloud_tpu_at_least(date: datetime.date):
if not is_cloud_tpu():
return True
# The format of Cloud TPU platform_version is like:
# PJRT C API
# TFRT TPU v2
# Built on Oct 30 2023 03:04:42 (1698660263) cl/577737722
platform_version = xla_bridge.get_backend().platform_version.split('\n')[-1]
results = re.findall(r'\(.*?\)', platform_version)
if len(results) != 1:
return True
build_date = date.fromtimestamp(int(results[0][1:-1]))
return build_date >= date
def pjrt_c_api_version_at_least(major_version: int, minor_version: int):
pjrt_c_api_versions = xla_bridge.backend_pjrt_c_api_version()
if pjrt_c_api_versions is None:
return True
return pjrt_c_api_versions >= (major_version, minor_version)
def get_tpu_version() -> int:
if device_under_test() != "tpu":
raise ValueError("Device is not TPU")
kind = jax.devices()[0].device_kind
if kind.endswith(' lite'):
kind = kind[:-len(' lite')]
assert kind[:-1] == "TPU v", kind
return int(kind[-1])
def is_device_tpu_at_least(version: int) -> bool:
if device_under_test() != "tpu":
return False
return get_tpu_version() >= version
def is_device_tpu(version: int | None = None, variant: str = "") -> bool:
if device_under_test() != "tpu":
return False
if version is None:
return True
device_kind = jax.devices()[0].device_kind
expected_version = f"v{version}{variant}"
# Special case v5e until the name is updated in device_kind
if expected_version == "v5e":
return "v5 lite" in device_kind
elif expected_version == "v6e":
return "v6 lite" in device_kind
return expected_version in device_kind
def is_cuda_compute_capability_at_least(capability: str) -> bool:
if not is_device_cuda():
return False
d, *_ = jax.local_devices(backend="gpu")
target = tuple(int(x) for x in capability.split("."))
current = tuple(int(x) for x in d.compute_capability.split("."))
return current >= target
def is_cuda_compute_capability_equal(capability: str) -> bool:
if not is_device_cuda():
return False
d, *_ = jax.local_devices(backend="gpu")
target = tuple(int(x) for x in capability.split("."))
current = tuple(int(x) for x in d.compute_capability.split("."))
return current == target
def _get_device_tags():
"""returns a set of tags defined for the device under test"""
if is_device_rocm():
device_tags = {device_under_test(), "rocm"}
elif is_device_cuda():
device_tags = {device_under_test(), "cuda"}
elif device_under_test() == "METAL":
device_tags = {device_under_test(), "gpu"}
else:
device_tags = {device_under_test()}
return device_tags
def test_device_matches(device_types: Iterable[str]) -> bool:
assert not isinstance(
device_types, str
), 'device_types should be a list of strings'
tags = _get_device_tags()
for device_type in device_types:
assert isinstance(device_type, str), device_type
if device_type in tags:
return True
return False
test_device_matches.__test__ = False # This isn't a test case, pytest.
def _device_filter(predicate):
def skip(test_method):
@functools.wraps(test_method)
def test_method_wrapper(self, *args, **kwargs):
device_tags = _get_device_tags()
if not predicate():
test_name = getattr(test_method, '__name__', '[unknown test]')
raise unittest.SkipTest(
f"{test_name} not supported on device with tags {device_tags}.")
return test_method(self, *args, **kwargs)
return test_method_wrapper
return skip
def skip_on_devices(*disabled_devices):
"""A decorator for test methods to skip the test on certain devices."""
return _device_filter(lambda: not test_device_matches(disabled_devices))
def run_on_devices(*enabled_devices):
"""A decorator for test methods to run the test only on certain devices."""
return _device_filter(lambda: test_device_matches(enabled_devices))
def device_supports_buffer_donation():
"""A decorator for test methods to run the test only on devices that support
buffer donation."""
return _device_filter(
lambda: test_device_matches(mlir._platforms_with_donation)
)
@contextmanager
def set_host_platform_device_count(nr_devices: int):
"""Context manager to set host platform device count if not specified by user.
This should only be used by tests at the top level in setUpModule(); it will
not work correctly if applied to individual test cases.
"""
prev_xla_flags = os.getenv("XLA_FLAGS")
flags_str = prev_xla_flags or ""
# Don't override user-specified device count, or other XLA flags.
if "xla_force_host_platform_device_count" not in flags_str:
os.environ["XLA_FLAGS"] = (flags_str +
f" --xla_force_host_platform_device_count={nr_devices}")
# Clear any cached backends so new CPU backend will pick up the env var.
xla_bridge.get_backend.cache_clear()
try:
yield
finally:
if prev_xla_flags is None:
del os.environ["XLA_FLAGS"]
else:
os.environ["XLA_FLAGS"] = prev_xla_flags
xla_bridge.get_backend.cache_clear()
def skip_on_flag(flag_name, skip_value):
"""A decorator for test methods to skip the test when flags are set."""
def skip(test_method): # pylint: disable=missing-docstring
@functools.wraps(test_method)
def test_method_wrapper(self, *args, **kwargs):
flag_value = config._read(flag_name)
if flag_value == skip_value:
test_name = getattr(test_method, '__name__', '[unknown test]')
raise unittest.SkipTest(
f"{test_name} not supported when FLAGS.{flag_name} is {flag_value}")
return test_method(self, *args, **kwargs)
return test_method_wrapper
return skip
def pytest_mark_if_available(marker: str):
"""A decorator for test classes or methods to pytest.mark if installed."""
def wrap(func_or_class):
try:
import pytest
except ImportError:
return func_or_class
return getattr(pytest.mark, marker)(func_or_class)
return wrap
def is_running_under_pytest():
return "pytest" in sys.modules
def skip_under_pytest(reason: str):
"""A decorator for test methods to skip the test when run under pytest."""
reason = "Running under pytest: " + reason
def skip(test_method):
return unittest.skipIf(is_running_under_pytest(), reason)(test_method)
return skip
def format_test_name_suffix(opname, shapes, dtypes):
arg_descriptions = (format_shape_dtype_string(shape, dtype)
for shape, dtype in zip(shapes, dtypes))
return '{}_{}'.format(opname.capitalize(), '_'.join(arg_descriptions))
# We use special symbols, represented as singleton objects, to distinguish
# between NumPy scalars, Python scalars, and 0-D arrays.
class ScalarShape:
def __len__(self): return 0
def __getitem__(self, i): raise IndexError(f"index {i} out of range.")
class _NumpyScalar(ScalarShape): pass
class _PythonScalar(ScalarShape): pass
NUMPY_SCALAR_SHAPE = _NumpyScalar()
PYTHON_SCALAR_SHAPE = _PythonScalar()
# Some shape combinations don't make sense.
def is_valid_shape(shape, dtype):
if shape == PYTHON_SCALAR_SHAPE:
return dtype == np.dtype(type(np.array(0, dtype=dtype).item()))
return True
def _dims_of_shape(shape):
"""Converts `shape` to a tuple of dimensions."""
if type(shape) in (list, tuple):
return shape
elif isinstance(shape, ScalarShape):
return ()
elif np.ndim(shape) == 0:
return (shape,)
else:
raise TypeError(type(shape))
def _cast_to_shape(value, shape, dtype):
"""Casts `value` to the correct Python type for `shape` and `dtype`."""
if shape is NUMPY_SCALAR_SHAPE:
# explicitly cast to NumPy scalar in case `value` is a Python scalar.
return np.dtype(dtype).type(value)
elif shape is PYTHON_SCALAR_SHAPE:
# explicitly cast to Python scalar via https://stackoverflow.com/a/11389998
return np.asarray(value).item()
elif type(shape) in (list, tuple):
assert np.shape(value) == tuple(shape)
return value
elif np.ndim(shape) == 0:
assert np.shape(value) == (shape,)
return value
else:
raise TypeError(type(shape))
def dtype_str(dtype):
return np.dtype(dtype).name
def format_shape_dtype_string(shape, dtype):
if isinstance(shape, np.ndarray):
return f'{dtype_str(dtype)}[{shape}]'
elif isinstance(shape, list):
shape = tuple(shape)
return _format_shape_dtype_string(shape, dtype)
@functools.lru_cache(maxsize=64)
def _format_shape_dtype_string(shape, dtype):
if shape is NUMPY_SCALAR_SHAPE:
return dtype_str(dtype)
elif shape is PYTHON_SCALAR_SHAPE:
return 'py' + dtype_str(dtype)
elif type(shape) is tuple:
shapestr = ','.join(str(dim) for dim in shape)
return f'{dtype_str(dtype)}[{shapestr}]'
elif type(shape) is int:
return f'{dtype_str(dtype)}[{shape},]'
else:
raise TypeError(type(shape))
def _rand_dtype(rand, shape, dtype, scale=1., post=lambda x: x):
"""Produce random values given shape, dtype, scale, and post-processor.
Args:
rand: a function for producing random values of a given shape, e.g. a
bound version of either np.RandomState.randn or np.RandomState.rand.
shape: a shape value as a tuple of positive integers.
dtype: a numpy dtype.
scale: optional, a multiplicative scale for the random values (default 1).
post: optional, a callable for post-processing the random values (default
identity).
Returns:
An ndarray of the given shape and dtype using random values based on a call
to rand but scaled, converted to the appropriate dtype, and post-processed.
"""
if _dtypes.issubdtype(dtype, np.unsignedinteger):
r = lambda: np.asarray(scale * abs(rand(*_dims_of_shape(shape)))).astype(dtype)
else:
r = lambda: np.asarray(scale * rand(*_dims_of_shape(shape))).astype(dtype)
if _dtypes.issubdtype(dtype, np.complexfloating):
vals = r() + 1.0j * r()
else:
vals = r()
return _cast_to_shape(np.asarray(post(vals), dtype), shape, dtype)
def rand_fullrange(rng, standardize_nans=False):
"""Random numbers that span the full range of available bits."""
def gen(shape, dtype, post=lambda x: x):
dtype = np.dtype(dtype)
size = dtype.itemsize * math.prod(_dims_of_shape(shape))
vals = rng.randint(0, np.iinfo(np.uint8).max, size=size, dtype=np.uint8)
vals = post(vals).view(dtype)
if shape is PYTHON_SCALAR_SHAPE:
# Sampling from the full range of the largest available uint type
# leads to overflows in this case; sample from signed ints instead.
if dtype == np.uint64:
vals = vals.astype(np.int64)
elif dtype == np.uint32 and not config.enable_x64.value:
vals = vals.astype(np.int32)
vals = vals.reshape(shape)
# Non-standard NaNs cause errors in numpy equality assertions.
if standardize_nans and np.issubdtype(dtype, np.floating):
vals[np.isnan(vals)] = np.nan
return _cast_to_shape(vals, shape, dtype)
return gen
def rand_default(rng, scale=3):
return partial(_rand_dtype, rng.randn, scale=scale)
def rand_nonzero(rng):
post = lambda x: np.where(x == 0, np.array(1, dtype=x.dtype), x)
return partial(_rand_dtype, rng.randn, scale=3, post=post)
def rand_positive(rng):
post = lambda x: x + 1
return partial(_rand_dtype, rng.rand, scale=2, post=post)
def rand_small(rng):
return partial(_rand_dtype, rng.randn, scale=1e-3)
def rand_not_small(rng, offset=10.):
post = lambda x: x + np.where(x > 0, offset, -offset)
return partial(_rand_dtype, rng.randn, scale=3., post=post)
def rand_small_positive(rng):
return partial(_rand_dtype, rng.rand, scale=2e-5)
def rand_uniform(rng, low=0.0, high=1.0):
assert low < high
post = lambda x: x * (high - low) + low
return partial(_rand_dtype, rng.rand, post=post)
def rand_some_equal(rng):
def post(x):
x_ravel = x.ravel()
if len(x_ravel) == 0:
return x
flips = rng.rand(*np.shape(x)) < 0.5
return np.where(flips, x_ravel[0], x)
return partial(_rand_dtype, rng.randn, scale=100., post=post)
def rand_some_inf(rng):
"""Return a random sampler that produces infinities in floating types."""
base_rand = rand_default(rng)
# TODO: Complex numbers are not correctly tested
# If blocks should be switched in order, and relevant tests should be fixed
def rand(shape, dtype):
"""The random sampler function."""
if not _dtypes.issubdtype(dtype, np.floating):
# only float types have inf
return base_rand(shape, dtype)
if _dtypes.issubdtype(dtype, np.complexfloating):
base_dtype = np.real(np.array(0, dtype=dtype)).dtype
out = (rand(shape, base_dtype) +
np.array(1j, dtype) * rand(shape, base_dtype))
return _cast_to_shape(out, shape, dtype)
dims = _dims_of_shape(shape)
posinf_flips = rng.rand(*dims) < 0.1
neginf_flips = rng.rand(*dims) < 0.1
vals = base_rand(shape, dtype)
vals = np.where(posinf_flips, np.array(np.inf, dtype=dtype), vals)
vals = np.where(neginf_flips, np.array(-np.inf, dtype=dtype), vals)
return _cast_to_shape(np.asarray(vals, dtype=dtype), shape, dtype)
return rand
def rand_some_nan(rng):
"""Return a random sampler that produces nans in floating types."""
base_rand = rand_default(rng)
def rand(shape, dtype):
"""The random sampler function."""
if _dtypes.issubdtype(dtype, np.complexfloating):
base_dtype = np.real(np.array(0, dtype=dtype)).dtype
out = (rand(shape, base_dtype) +
np.array(1j, dtype) * rand(shape, base_dtype))
return _cast_to_shape(out, shape, dtype)
if not _dtypes.issubdtype(dtype, np.floating):
# only float types have inf
return base_rand(shape, dtype)
dims = _dims_of_shape(shape)
r = rng.rand(*dims)
nan_flips = r < 0.1
neg_nan_flips = r < 0.05
vals = base_rand(shape, dtype)
vals = np.where(nan_flips, np.array(np.nan, dtype=dtype), vals)
vals = np.where(neg_nan_flips, np.array(-np.nan, dtype=dtype), vals)
return _cast_to_shape(np.asarray(vals, dtype=dtype), shape, dtype)
return rand
def rand_some_inf_and_nan(rng):
"""Return a random sampler that produces infinities in floating types."""
base_rand = rand_default(rng)
# TODO: Complex numbers are not correctly tested
# If blocks should be switched in order, and relevant tests should be fixed
def rand(shape, dtype):
"""The random sampler function."""
if not _dtypes.issubdtype(dtype, np.floating):
# only float types have inf
return base_rand(shape, dtype)
if _dtypes.issubdtype(dtype, np.complexfloating):
base_dtype = np.real(np.array(0, dtype=dtype)).dtype
out = (rand(shape, base_dtype) +
np.array(1j, dtype) * rand(shape, base_dtype))
return _cast_to_shape(out, shape, dtype)
dims = _dims_of_shape(shape)
posinf_flips = rng.rand(*dims) < 0.1
neginf_flips = rng.rand(*dims) < 0.1
nan_flips = rng.rand(*dims) < 0.1
vals = base_rand(shape, dtype)
vals = np.where(posinf_flips, np.array(np.inf, dtype=dtype), vals)
vals = np.where(neginf_flips, np.array(-np.inf, dtype=dtype), vals)
vals = np.where(nan_flips, np.array(np.nan, dtype=dtype), vals)
return _cast_to_shape(np.asarray(vals, dtype=dtype), shape, dtype)
return rand
# TODO(mattjj): doesn't handle complex types
def rand_some_zero(rng):
"""Return a random sampler that produces some zeros."""
base_rand = rand_default(rng)
def rand(shape, dtype):
"""The random sampler function."""
dims = _dims_of_shape(shape)
zeros = rng.rand(*dims) < 0.5
vals = base_rand(shape, dtype)
vals = np.where(zeros, np.array(0, dtype=dtype), vals)
return _cast_to_shape(np.asarray(vals, dtype=dtype), shape, dtype)
return rand
def rand_int(rng, low=0, high=None):
def fn(shape, dtype):
nonlocal high
gen_dtype = dtype if np.issubdtype(dtype, np.integer) else np.int64
if low == 0 and high is None:
if np.issubdtype(dtype, np.integer):
high = np.iinfo(dtype).max
else:
raise ValueError("rand_int requires an explicit `high` value for "
"non-integer types.")
return rng.randint(low, high=high, size=shape,
dtype=gen_dtype).astype(dtype)
return fn
def rand_unique_int(rng, high=None):
def fn(shape, dtype):
return rng.choice(np.arange(high or math.prod(shape), dtype=dtype),
size=shape, replace=False)
return fn
def rand_indices_unique_along_axis(rng):
"""Sample an array of given shape containing indices up to dim (exclusive),
such that the indices are unique along the given axis.
Optionally, convert some of the resulting indices to negative indices."""
def fn(dim, shape, axis, allow_negative=True):
batch_size = math.prod(shape[:axis] + shape[axis:][1:])
idx = [
rng.choice(dim, size=shape[axis], replace=False)
for _ in range(batch_size)
]
idx = np.array(idx).reshape(batch_size, shape[axis])
idx = idx.reshape(shape[:axis] + shape[axis:][1:] + (shape[axis],))
idx = np.moveaxis(idx, -1, axis)
# assert that indices are unique along the given axis
count = partial(np.bincount, minlength=dim)
assert (np.apply_along_axis(count, axis, idx) <= 1).all()
if allow_negative:
mask = rng.choice([False, True], idx.shape)
idx[mask] -= dim
return idx
return fn
def rand_bool(rng):
def generator(shape, dtype):
return _cast_to_shape(
np.asarray(rng.rand(*_dims_of_shape(shape)) < 0.5, dtype=dtype),
shape, dtype)
return generator
def check_raises(thunk, err_type, msg):
try:
thunk()
assert False
except err_type as e:
assert str(e).startswith(msg), f"\n{e}\n\n{msg}\n"
def check_raises_regexp(thunk, err_type, pattern):
try:
thunk()
assert False
except err_type as e:
assert re.match(pattern, str(e)), f"{e}\n\n{pattern}\n"
def iter_eqns(jaxpr):
# TODO(necula): why doesn't this search in params?
yield from jaxpr.eqns
for subjaxpr in core.subjaxprs(jaxpr):
yield from iter_eqns(subjaxpr)
def assert_dot_precision(expected_precision, fun, *args):
jaxpr = api.make_jaxpr(fun)(*args)
precisions = [eqn.params['precision'] for eqn in iter_eqns(jaxpr.jaxpr)
if eqn.primitive == lax.dot_general_p]
for precision in precisions:
msg = f"Unexpected precision: {expected_precision} != {precision}"
if isinstance(precision, tuple):
assert precision[0] == expected_precision, msg
assert precision[1] == expected_precision, msg
else:
assert precision == expected_precision, msg
def assert_dot_preferred_element_type(expected, fun, *args, **kwargs):
jaxpr = api.make_jaxpr(partial(fun, **kwargs))(*args)
pref_eltypes = [eqn.params['preferred_element_type'] for eqn in iter_eqns(jaxpr.jaxpr)
if eqn.primitive == lax.dot_general_p]
for pref_eltype in pref_eltypes:
msg = f"Unexpected preferred_element_type: {expected} != {pref_eltype}"
assert expected == pref_eltype, msg
def cases_from_gens(*gens):
sizes = [1, 3, 10]
cases_per_size = int(NUM_GENERATED_CASES.value / len(sizes)) + 1
for size in sizes:
for i in range(cases_per_size):
yield (f'_{size}_{i}',) + tuple(gen(size) for gen in gens)
def named_cases_from_sampler(gen):
seen = set()
retries = 0
rng = npr.RandomState(42)
def choose_one(x):
if not isinstance(x, (list, tuple)):
x = list(x)
return [x[rng.randint(len(x))]]
while (len(seen) < NUM_GENERATED_CASES.value and
retries < _MAX_CASES_SAMPLING_RETRIES.value):
retries += 1
cases = list(gen(choose_one))
if not cases:
continue
if len(cases) > 1:
raise RuntimeError("Generator is expected to only return a single case when sampling")
case = cases[0]
if case["testcase_name"] in seen:
continue
retries = 0
seen.add(case["testcase_name"])
yield case
# Random sampling for every parameterized test is expensive. Do it once and
# cache the result.
@functools.cache
def _choice(n, m):
rng = np.random.RandomState(42)
return rng.choice(n, size=m, replace=False)
def sample_product_testcases(*args, **kw):
"""Non-decorator form of sample_product."""
args = [list(arg) for arg in args]
kw = [(k, list(v)) for k, v in kw.items()]
n = math.prod(len(a) for a in args) * math.prod(len(v) for _, v in kw)
testcases = []
for i in _choice(n, min(n, NUM_GENERATED_CASES.value)):
testcase = {}
for a in args:
testcase.update(a[i % len(a)])
i //= len(a)
for k, v in kw:
testcase[k] = v[i % len(v)]
i //= len(v)
testcases.append(testcase)
return testcases
def sample_product(*args, **kw):
"""Decorator that samples from a cartesian product of test cases.
Similar to absltest.parameterized.product(), except that it samples from the
cartesian product rather than returning the whole thing.
Arguments:
*args: each positional argument is a list of dictionaries. The entries
in a dictionary correspond to name=value argument pairs; one dictionary
will be chosen for each test case. This allows multiple parameters to be
correlated.
**kw: each keyword argument is a list of values. One value will be chosen
for each test case.
"""
return parameterized.parameters(*sample_product_testcases(*args, **kw))
class JaxTestLoader(absltest.TestLoader):
def getTestCaseNames(self, testCaseClass):
names = super().getTestCaseNames(testCaseClass)
if _TEST_TARGETS.value:
pattern = re.compile(_TEST_TARGETS.value)
names = [name for name in names
if pattern.search(f"{testCaseClass.__name__}.{name}")]
if _EXCLUDE_TEST_TARGETS.value:
pattern = re.compile(_EXCLUDE_TEST_TARGETS.value)
names = [name for name in names
if not pattern.search(f"{testCaseClass.__name__}.{name}")]
return names
def with_config(**kwds):
"""Test case decorator for subclasses of JaxTestCase"""
def decorator(cls):
assert inspect.isclass(cls) and issubclass(cls, JaxTestCase), "@with_config can only wrap JaxTestCase class definitions."
cls._default_config = {}
for b in cls.__bases__:
cls._default_config.update(b._default_config)
cls._default_config.update(kwds)
return cls
return decorator
def promote_like_jnp(fun, inexact=False):
"""Decorator that promotes the arguments of `fun` to `jnp.result_type(*args)`.
jnp and np have different type promotion semantics; this decorator allows
tests make an np reference implementation act more like a jnp
implementation.
"""
_promote = promote_dtypes_inexact if inexact else promote_dtypes
def wrapper(*args, **kw):
flat_args, tree = tree_flatten(args)
args = tree_unflatten(tree, _promote(*flat_args))
return fun(*args, **kw)
return wrapper
@contextmanager
def global_config_context(**kwds):
original_config = {}
try:
for key, value in kwds.items():
original_config[key] = config._read(key)
config.update(key, value)
yield
finally:
for key, value in original_config.items():
config.update(key, value)
class NotPresent:
def __repr__(self):
return "<not present>"
@contextmanager
def assert_global_configs_unchanged():
starting_config = jax.config.values.copy()
yield
ending_config = jax.config.values
if starting_config == ending_config:
return
differing = {k: (starting_config.get(k, NotPresent()), ending_config.get(k, NotPresent()))
for k in (starting_config.keys() | ending_config.keys())
if (k not in starting_config or k not in ending_config
or starting_config[k] != ending_config[k])}
raise AssertionError(f"Test changed global config values. Differing values are: {differing}")
class JaxTestCase(parameterized.TestCase):
"""Base class for JAX tests including numerical checks and boilerplate."""
_default_config = {
'jax_enable_checks': True,
'jax_numpy_dtype_promotion': 'strict',
'jax_numpy_rank_promotion': 'raise',
'jax_traceback_filtering': 'off',
'jax_legacy_prng_key': 'error',
}
_compilation_cache_exit_stack: ExitStack | None = None
def tearDown(self) -> None:
assert core.reset_trace_state()
def setUp(self):
super().setUp()
self.enter_context(assert_global_configs_unchanged())
# We use the adler32 hash for two reasons.
# a) it is deterministic run to run, unlike hash() which is randomized.
# b) it returns values in int32 range, which RandomState requires.
self._rng = npr.RandomState(zlib.adler32(self._testMethodName.encode()))
@classmethod
def setUpClass(cls):
cls._compilation_cache_exit_stack = ExitStack()
stack = cls._compilation_cache_exit_stack
stack.enter_context(global_config_context(**cls._default_config))
if TEST_WITH_PERSISTENT_COMPILATION_CACHE.value:
stack.enter_context(config.enable_compilation_cache(True))
stack.enter_context(config.raise_persistent_cache_errors(True))
stack.enter_context(config.persistent_cache_min_compile_time_secs(0))
stack.enter_context(config.persistent_cache_min_entry_size_bytes(0))
tmp_dir = stack.enter_context(tempfile.TemporaryDirectory())
compilation_cache.set_cache_dir(tmp_dir)
stack.callback(lambda: compilation_cache.reset_cache())
@classmethod
def tearDownClass(cls):
cls._compilation_cache_exit_stack.close()
def rng(self):
return self._rng
def assertArraysEqual(self, x, y, *, check_dtypes=True, err_msg='',
allow_object_dtype=False, verbose=True):
"""Assert that x and y arrays are exactly equal."""
if check_dtypes:
self.assertDtypesMatch(x, y)
x = np.asarray(x)
y = np.asarray(y)
if (not allow_object_dtype) and (x.dtype == object or y.dtype == object):
# See https://github.com/jax-ml/jax/issues/17867
raise TypeError(
"assertArraysEqual may be poorly behaved when np.asarray casts to dtype=object. "
"If comparing PRNG keys, consider random_test.KeyArrayTest.assertKeysEqual. "
"If comparing collections of arrays, consider using assertAllClose. "
"To let this test proceed anyway, pass allow_object_dtype=True.")
# Work around https://github.com/numpy/numpy/issues/18992
with np.errstate(over='ignore'):
np.testing.assert_array_equal(x, y, err_msg=err_msg,
verbose=verbose)
def assertArraysAllClose(self, x, y, *, check_dtypes=True, atol=None,
rtol=None, err_msg=''):
"""Assert that x and y are close (up to numerical tolerances)."""
self.assertEqual(x.shape, y.shape)
atol = max(tolerance(_dtype(x), atol), tolerance(_dtype(y), atol))
rtol = max(tolerance(_dtype(x), rtol), tolerance(_dtype(y), rtol))
_assert_numpy_allclose(x, y, atol=atol, rtol=rtol, err_msg=err_msg)
if check_dtypes:
self.assertDtypesMatch(x, y)
def assertDtypesMatch(self, x, y, *, canonicalize_dtypes=True):
if not config.enable_x64.value and canonicalize_dtypes:
self.assertEqual(_dtypes.canonicalize_dtype(_dtype(x), allow_extended_dtype=True),
_dtypes.canonicalize_dtype(_dtype(y), allow_extended_dtype=True))
else:
self.assertEqual(_dtype(x), _dtype(y))
def assertAllClose(self, x, y, *, check_dtypes=True, atol=None, rtol=None,
canonicalize_dtypes=True, err_msg=''):
"""Assert that x and y, either arrays or nested tuples/lists, are close."""
if isinstance(x, dict):
self.assertIsInstance(y, dict)
self.assertEqual(set(x.keys()), set(y.keys()))
for k in x.keys():
self.assertAllClose(x[k], y[k], check_dtypes=check_dtypes, atol=atol,
rtol=rtol, canonicalize_dtypes=canonicalize_dtypes,
err_msg=err_msg)
elif is_sequence(x) and not hasattr(x, '__array__'):
self.assertTrue(is_sequence(y) and not hasattr(y, '__array__'))
self.assertEqual(len(x), len(y))
for x_elt, y_elt in zip(x, y):
self.assertAllClose(x_elt, y_elt, check_dtypes=check_dtypes, atol=atol,
rtol=rtol, canonicalize_dtypes=canonicalize_dtypes,
err_msg=err_msg)
elif hasattr(x, '__array__') or np.isscalar(x):
self.assertTrue(hasattr(y, '__array__') or np.isscalar(y))
if check_dtypes:
self.assertDtypesMatch(x, y, canonicalize_dtypes=canonicalize_dtypes)
x = np.asarray(x)
y = np.asarray(y)
self.assertArraysAllClose(x, y, check_dtypes=False, atol=atol, rtol=rtol,
err_msg=err_msg)
elif x == y:
return
else:
raise TypeError((type(x), type(y)))
def assertMultiLineStrippedEqual(self, expected, what):
"""Asserts two strings are equal, after dedenting and stripping each line."""
expected = textwrap.dedent(expected)
what = textwrap.dedent(what)
ignore_space_re = re.compile(r'\s*\n\s*')
expected_clean = re.sub(ignore_space_re, '\n', expected.strip())
what_clean = re.sub(ignore_space_re, '\n', what.strip())
if what_clean != expected_clean:
# Print it so we can copy-and-paste it into the test
print(f"Found\n{what}\n")
self.assertMultiLineEqual(expected_clean, what_clean,
msg=f"Found\n{what}\nExpecting\n{expected}")
@contextmanager
def assertNoWarnings(self):
with warnings.catch_warnings():
warnings.simplefilter("error")
yield
def _CompileAndCheck(self, fun, args_maker, *, check_dtypes=True, tol=None,
rtol=None, atol=None, check_cache_misses=True):
"""Helper method for running JAX compilation and allclose assertions."""
args = args_maker()
def wrapped_fun(*args):
self.assertTrue(python_should_be_executing)
return fun(*args)
python_should_be_executing = True
python_ans = fun(*args)
python_shapes = tree_map(lambda x: np.shape(x), python_ans)
np_shapes = tree_map(lambda x: np.shape(np.asarray(x)), python_ans)
self.assertEqual(python_shapes, np_shapes)
cache_misses = dispatch.xla_primitive_callable.cache_info().misses
python_ans = fun(*args)
if check_cache_misses:
self.assertEqual(
cache_misses, dispatch.xla_primitive_callable.cache_info().misses,
"Compilation detected during second call of {} in op-by-op "
"mode.".format(fun))
cfun = api.jit(wrapped_fun)
python_should_be_executing = True
monitored_ans = cfun(*args)
python_should_be_executing = False
compiled_ans = cfun(*args)
self.assertAllClose(python_ans, monitored_ans, check_dtypes=check_dtypes,
atol=atol or tol, rtol=rtol or tol)
self.assertAllClose(python_ans, compiled_ans, check_dtypes=check_dtypes,
atol=atol or tol, rtol=rtol or tol)
args = args_maker()
python_should_be_executing = True
python_ans = fun(*args)
python_should_be_executing = False
compiled_ans = cfun(*args)
self.assertAllClose(python_ans, compiled_ans, check_dtypes=check_dtypes,
atol=atol or tol, rtol=rtol or tol)
def _CheckAgainstNumpy(self, numpy_reference_op, lax_op, args_maker,
check_dtypes=True, tol=None, atol=None, rtol=None,
canonicalize_dtypes=True):
args = args_maker()
lax_ans = lax_op(*args)
numpy_ans = numpy_reference_op(*args)
self.assertAllClose(numpy_ans, lax_ans, check_dtypes=check_dtypes,
atol=atol or tol, rtol=rtol or tol,
canonicalize_dtypes=canonicalize_dtypes)
_PJIT_IMPLEMENTATION = jax.jit
_PJIT_IMPLEMENTATION._name = "jit"
_NOOP_JIT_IMPLEMENTATION = lambda x, *args, **kwargs: x
_NOOP_JIT_IMPLEMENTATION._name = "noop"
JIT_IMPLEMENTATION = (
_PJIT_IMPLEMENTATION,
_NOOP_JIT_IMPLEMENTATION,
)
class BufferDonationTestCase(JaxTestCase):
def assertDeleted(self, x):
self.assertTrue(x.is_deleted())
def assertNotDeleted(self, x):
self.assertFalse(x.is_deleted())
@contextmanager
def ignore_warning(*, message='', category=Warning, **kw):
with warnings.catch_warnings():
warnings.filterwarnings("ignore", message=message, category=category, **kw)
yield
# -------------------- Mesh parametrization helpers --------------------
MeshSpec = list[tuple[str, int]]
@contextmanager
def with_mesh(named_shape: MeshSpec) -> Generator[None, None, None]:
"""Test utility for setting up meshes given mesh data from `schedules`."""
# This is similar to the `with_mesh` function above, but isn't a decorator.
axis_names, shape = unzip2(named_shape)
size = math.prod(shape)
local_devices = list(jax.local_devices())
if len(local_devices) < size:
raise unittest.SkipTest(f"Test requires {size} local devices")
mesh_devices = np.array(local_devices[:size]).reshape(shape) # type: ignore
with jax.sharding.Mesh(mesh_devices, axis_names):
yield
def with_mesh_from_kwargs(f):
return lambda *args, **kwargs: with_mesh(kwargs['mesh'])(f)(*args, **kwargs)
def with_and_without_mesh(f):
return parameterized.named_parameters(
{"testcase_name": name, "mesh": mesh, "axis_resources": axis_resources}
for name, mesh, axis_resources in (
('', (), ()),
('Mesh', (('x', 2),), (('i', 'x'),))
))(with_mesh_from_kwargs(f))
def with_user_mesh(sizes, names, axis_types=None):
axis_types = ({mesh_lib.AxisTypes.User: names}
if axis_types is None else axis_types)
def decorator(fn):
def mesh_fn(*args, **kwargs):
mesh = create_mesh(sizes, names, axis_types=axis_types)
with mesh_lib.set_mesh(mesh):
return fn(*args, **kwargs, mesh=mesh)
return mesh_fn
return decorator
def create_mesh(mesh_shape, axis_names, iota_order=False, axis_types=None):
size = math.prod(mesh_shape)
if len(jax.devices()) < size:
raise unittest.SkipTest(f"Test requires {size} global devices.")
if iota_order:
devices = sorted(jax.devices(), key=lambda d: d.id)
mesh_devices = np.array(devices[:size]).reshape(mesh_shape)
return jax.sharding.Mesh(mesh_devices, axis_names, axis_types=axis_types)
else:
return jax.make_mesh(mesh_shape, axis_names, axis_types=axis_types)
class _cached_property:
null = object()
def __init__(self, method):
self._method = method
self._value = self.null
def __get__(self, obj, cls):
if self._value is self.null:
self._value = self._method(obj)
return self._value
class _LazyDtypes:
"""A class that unifies lists of supported dtypes.
These could be module-level constants, but device_under_test() is not always
known at import time, so we need to define these lists lazily.
"""
def supported(self, dtypes):
supported = supported_dtypes()
return type(dtypes)(d for d in dtypes if d in supported)
@_cached_property
def custom_floats(self):
float_dtypes = [
_dtypes.bfloat16,
_dtypes.float8_e4m3b11fnuz,
_dtypes.float8_e4m3fn,
_dtypes.float8_e4m3fnuz,
_dtypes.float8_e5m2,
_dtypes.float8_e5m2fnuz,
]
if _dtypes.float8_e3m4 is not None:
float_dtypes += [_dtypes.float8_e3m4]
if _dtypes.float8_e4m3 is not None:
float_dtypes += [_dtypes.float8_e4m3]
return self.supported(float_dtypes)
@_cached_property
def floating(self):
return self.supported([np.float32, np.float64])
@_cached_property
def all_floating(self):
return self.supported([_dtypes.bfloat16, np.float16, np.float32, np.float64])
@_cached_property
def integer(self):
return self.supported([np.int32, np.int64])
@_cached_property
def all_integer(self):
return self.supported([np.int8, np.int16, np.int32, np.int64])
@_cached_property
def unsigned(self):
return self.supported([np.uint32, np.uint64])
@_cached_property
def all_unsigned(self):
return self.supported([np.uint8, np.uint16, np.uint32, np.uint64])
@_cached_property
def complex(self):
return self.supported([np.complex64, np.complex128])
@_cached_property
def boolean(self):
return self.supported([np.bool_])
@_cached_property
def inexact(self):
return self.floating + self.complex
@_cached_property
def all_inexact(self):
return self.all_floating + self.complex
@_cached_property
def numeric(self):
return self.floating + self.integer + self.unsigned + self.complex
@_cached_property
def all(self):
return (self.all_floating + self.all_integer + self.all_unsigned +
self.complex + self.boolean)
dtypes = _LazyDtypes()
def strict_promotion_if_dtypes_match(dtypes):
"""
Context manager to enable strict promotion if all dtypes match,
and enable standard dtype promotion otherwise.
"""
if all(dtype == dtypes[0] for dtype in dtypes):
return jax.numpy_dtype_promotion('strict')
return jax.numpy_dtype_promotion('standard')
_version_regex = re.compile(r"([0-9]+(?:\.[0-9]+)*)(?:(rc|dev).*)?")
def parse_version(v: str) -> tuple[int, ...]:
m = _version_regex.match(v)
if m is None:
raise ValueError(f"Unable to parse version '{v}'")
return tuple(int(x) for x in m.group(1).split('.'))
def numpy_version():
return parse_version(np.__version__)
def parameterized_filterable(*,
kwargs: Sequence[dict[str, Any]],
testcase_name: Callable[[dict[str, Any]], str] | None = None,
one_containing: str | None = None,
):
"""Decorator for named parameterized tests, with filtering support.
Works like ``parameterized.named_parameters``, except that it sanitizes the test
names so that we can use ``pytest -k`` and ``python test.py -k`` test filtering.
This means, e.g., that many special characters are replaced with `_`.
It also supports the ``one_containing`` arg to select one of the tests, while
leaving the name unchanged, which is useful for IDEs to be able to easily
pick up the enclosing test name.
Usage:
@jtu.parameterized_filterable(
# one_containing="a_4",
[dict(a=4, b=5),
dict(a=5, b=4)])
def test_my_test(self, *, a, b): ...
Args:
kwargs: Each entry is a set of kwargs to be passed to the test function.
testcase_name: Optionally, a function to construct the testcase_name from
one kwargs dict. If not given then ``kwargs`` may contain ``testcase_name`` and
otherwise the test case name is constructed as ``str(kwarg)``.
We sanitize the test names to work with -k test filters. See
``sanitize_test_name``.
one_containing: If given, then leaves the test name unchanged, and use
only one of the ``kwargs`` whose `testcase_name` includes ``one_containing``.
"""
# Ensure that all kwargs contain a testcase_name
kwargs_with_testcase_name: Sequence[dict[str, Any]]
if testcase_name is not None:
kwargs_with_testcase_name = [
dict(testcase_name=sanitize_test_name(str(testcase_name(kw))), **kw)
for kw in kwargs]
else:
for kw in kwargs:
testcase_name = kw.get("testcase_name")
if testcase_name is None:
testcase_name = "_".join(f"{k}={kw[k]}" # type: ignore
for k in sorted(kw.keys()))
kw["testcase_name"] = sanitize_test_name(testcase_name) # type: ignore
kwargs_with_testcase_name = kwargs
if one_containing is not None:
filtered = tuple(kw for kw in kwargs_with_testcase_name
if one_containing in kw["testcase_name"])
assert filtered, (
f"No testcase_name contains '{one_containing}'. "
"The testcase_name values are\n " +
"\n ".join(kw["testcase_name"] for kw in kwargs_with_testcase_name))
kw = filtered[0]
kw["testcase_name"] = ""
return parameterized.named_parameters([kw])
else:
return parameterized.named_parameters(*kwargs_with_testcase_name)
@contextmanager
def register_event_duration_listener(callback):
"""Manages registering/unregistering an event duration listener callback."""
try:
monitoring.register_event_duration_secs_listener(callback)
yield
finally:
monitoring._unregister_event_duration_listener_by_callback(callback)
@contextmanager
def set_env(**kwargs):
"""Context manager to temporarily set/unset one or more environment variables.
Examples:
>>> import os
>>> os.environ['my_var'] = 'original'
>>> with set_env(my_var=None, other_var='some_value'):
... print("my_var is set:", 'my_var' in os.environ)
... print("other_var =", os.environ['other_var'])
...
my_var is set: False
other_var = some_value
>>> os.environ['my_var']
'original'
>>> 'other_var' in os.environ
False
"""
original = {key: os.environ.pop(key, None) for key in kwargs}
os.environ.update({k: v for k, v in kwargs.items() if v is not None})
try:
yield
finally:
_ = [os.environ.pop(key, None) for key in kwargs]
os.environ.update({k: v for k, v in original.items() if v is not None})
def fwd_bwd_jaxprs(f, *example_args):
fwd_jaxpr, (y_shape, res_shape) = jax.make_jaxpr(
lambda *args: jax.vjp(f, *args), return_shape=True)(*example_args)
bwd_jaxpr = jax.make_jaxpr(lambda res, outs: res(outs))(res_shape, y_shape)
return fwd_jaxpr, bwd_jaxpr
def numpy_vecdot(x, y, axis):
"""Implementation of numpy.vecdot for testing on numpy < 2.0.0"""
if numpy_version() >= (2, 0, 0):
raise ValueError("should be calling vecdot directly on numpy 2.0.0")
x = np.moveaxis(x, axis, -1)
y = np.moveaxis(y, axis, -1)
x, y = np.broadcast_arrays(x, y)
return np.matmul(np.conj(x[..., None, :]), y[..., None])[..., 0, 0]
def complex_plane_sample(dtype, size_re=10, size_im=None):
"""Return a 2-D array of complex numbers that covers the complex plane
with a grid of samples.
The size of the grid is (3 + 2 * size_im) x (3 + 2 * size_re)
that includes infinity points, extreme finite points, and the
specified number of points from real and imaginary axis.
For example:
>>> print(complex_plane_sample(np.complex64, 0, 3))
[[-inf -infj 0. -infj inf -infj]
[-inf-3.4028235e+38j 0.-3.4028235e+38j inf-3.4028235e+38j]
[-inf-2.0000000e+00j 0.-2.0000000e+00j inf-2.0000000e+00j]
[-inf-1.1754944e-38j 0.-1.1754944e-38j inf-1.1754944e-38j]
[-inf+0.0000000e+00j 0.+0.0000000e+00j inf+0.0000000e+00j]
[-inf+1.1754944e-38j 0.+1.1754944e-38j inf+1.1754944e-38j]
[-inf+2.0000000e+00j 0.+2.0000000e+00j inf+2.0000000e+00j]
[-inf+3.4028235e+38j 0.+3.4028235e+38j inf+3.4028235e+38j]
[-inf +infj 0. +infj inf +infj]]
"""
if size_im is None:
size_im = size_re
finfo = np.finfo(dtype)
machine = platform.machine()
is_arm_cpu = machine.startswith('aarch') or machine.startswith('arm')
smallest = np.nextafter(finfo.tiny, finfo.max) if is_arm_cpu and platform.system() == 'Darwin' else finfo.tiny
def make_axis_points(size):
prec_dps_ratio = 3.3219280948873626
logmin = logmax = finfo.maxexp / prec_dps_ratio
logtiny = finfo.minexp / prec_dps_ratio
axis_points = np.zeros(3 + 2 * size, dtype=finfo.dtype)
with warnings.catch_warnings():
# Silence RuntimeWarning: overflow encountered in cast
warnings.simplefilter("ignore")
half_neg_line = -np.logspace(logmin, logtiny, size, dtype=finfo.dtype)
half_line = -half_neg_line[::-1]
axis_points[-size - 1:-1] = half_line
axis_points[1:size + 1] = half_neg_line
if size > 1:
axis_points[1] = finfo.min
axis_points[-2] = finfo.max
if size > 0:
axis_points[size] = -smallest
axis_points[-size - 1] = smallest
axis_points[0] = -np.inf
axis_points[-1] = np.inf
return axis_points
real_axis_points = make_axis_points(size_re)
imag_axis_points = make_axis_points(size_im)
real_part = real_axis_points.reshape((-1, 3 + 2 * size_re)).repeat(3 + 2 * size_im, 0).astype(dtype)
imag_part = imag_axis_points.repeat(2).view(dtype)
imag_part.real[:] = 0
imag_part = imag_part.reshape((3 + 2 * size_im, -1)).repeat(3 + 2 * size_re, 1)
return real_part + imag_part
class vectorize_with_mpmath(np.vectorize):
"""Same as numpy.vectorize but using mpmath backend for function evaluation.
"""
map_float_to_complex = dict(float16='complex32', float32='complex64', float64='complex128', float128='complex256', longdouble='clongdouble')
map_complex_to_float = {v: k for k, v in map_float_to_complex.items()}
float_prec = dict(
# float16=11,
float32=24,
float64=53,
# float128=113,
# longdouble=113
)
float_minexp = dict(
float16=-14,
float32=-126,
float64=-1022,
float128=-16382
)
float_maxexp = dict(
float16=16,
float32=128,
float64=1024,
float128=16384,
)
def __init__(self, *args, **kwargs):
mpmath = kwargs.pop('mpmath', None)
if mpmath is None:
raise ValueError('vectorize_with_mpmath: no mpmath argument specified')
self.extra_prec_multiplier = kwargs.pop('extra_prec_multiplier', 0)
self.extra_prec = kwargs.pop('extra_prec', 0)
self.mpmath = mpmath
self.contexts = dict()
self.contexts_inv = dict()
for fp_format, prec in self.float_prec.items():
ctx = self.mpmath.mp.clone()
ctx.prec = prec
self.contexts[fp_format] = ctx
self.contexts_inv[ctx] = fp_format
super().__init__(*args, **kwargs)
def get_context(self, x):
if isinstance(x, (np.ndarray, np.floating, np.complexfloating)):
fp_format = str(x.dtype)
fp_format = self.map_complex_to_float.get(fp_format, fp_format)
return self.contexts[fp_format]
raise NotImplementedError(f'get mpmath context from {type(x).__name__} instance')
def nptomp(self, x):
"""Convert numpy array/scalar to an array/instance of mpmath number type.
"""
if isinstance(x, np.ndarray):
return np.fromiter(map(self.nptomp, x.flatten()), dtype=object).reshape(x.shape)
elif isinstance(x, np.floating):
mpmath = self.mpmath
ctx = self.get_context(x)
prec, rounding = ctx._prec_rounding
if np.isposinf(x):
return ctx.make_mpf(mpmath.libmp.finf)
elif np.isneginf(x):
return ctx.make_mpf(mpmath.libmp.fninf)
elif np.isnan(x):
return ctx.make_mpf(mpmath.libmp.fnan)
elif np.isfinite(x):
mantissa, exponent = np.frexp(x)
man = int(np.ldexp(mantissa, prec))
exp = int(exponent - prec)
r = ctx.make_mpf(mpmath.libmp.from_man_exp(man, exp, prec, rounding))
assert ctx.isfinite(r), r._mpf_
return r
elif isinstance(x, np.complexfloating):
re, im = self.nptomp(x.real), self.nptomp(x.imag)
return re.context.make_mpc((re._mpf_, im._mpf_))
raise NotImplementedError(f'convert {type(x).__name__} instance to mpmath number type')
def mptonp(self, x):
"""Convert mpmath instance to numpy array/scalar type.
"""
if isinstance(x, np.ndarray) and x.dtype.kind == 'O':
x_flat = x.flatten()
item = x_flat[0]
ctx = item.context
fp_format = self.contexts_inv[ctx]
if isinstance(item, ctx.mpc):
dtype = getattr(np, self.map_float_to_complex[fp_format])
elif isinstance(item, ctx.mpf):
dtype = getattr(np, fp_format)
else:
dtype = None
if dtype is not None:
return np.fromiter(map(self.mptonp, x_flat), dtype=dtype).reshape(x.shape)
elif isinstance(x, self.mpmath.ctx_mp.mpnumeric):
ctx = x.context
if isinstance(x, ctx.mpc):
fp_format = self.contexts_inv[ctx]
dtype = getattr(np, self.map_float_to_complex[fp_format])
r = dtype().reshape(1).view(getattr(np, fp_format))
r[0] = self.mptonp(x.real)
r[1] = self.mptonp(x.imag)
return r.view(dtype)[0]
elif isinstance(x, ctx.mpf):
fp_format = self.contexts_inv[ctx]
dtype = getattr(np, fp_format)
if ctx.isfinite(x):
sign, man, exp, bc = self.mpmath.libmp.normalize(*x._mpf_, *ctx._prec_rounding)
assert bc >= 0, (sign, man, exp, bc, x._mpf_)
if exp + bc < self.float_minexp[fp_format]:
return -ctx.zero if sign else ctx.zero
if exp + bc > self.float_maxexp[fp_format]:
return ctx.ninf if sign else ctx.inf
man = dtype(-man if sign else man)
r = np.ldexp(man, exp)
assert np.isfinite(r), (x, r, x._mpf_, man)
return r
elif ctx.isnan(x):
return dtype(np.nan)
elif ctx.isinf(x):
return dtype(-np.inf if x._mpf_[0] else np.inf)
raise NotImplementedError(f'convert {type(x)} instance to numpy floating point type')
def __call__(self, *args, **kwargs):
mp_args = []
context = None
for a in args:
if isinstance(a, (np.ndarray, np.floating, np.complexfloating)):
mp_args.append(self.nptomp(a))
if context is None:
context = self.get_context(a)
else:
assert context is self.get_context(a)
else:
mp_args.append(a)
extra_prec = int(context.prec * self.extra_prec_multiplier) + self.extra_prec
with context.extraprec(extra_prec):
result = super().__call__(*mp_args, **kwargs)
if isinstance(result, tuple):
lst = []
for r in result:
if ((isinstance(r, np.ndarray) and r.dtype.kind == 'O')
or isinstance(r, self.mpmath.ctx_mp.mpnumeric)):
r = self.mptonp(r)
lst.append(r)
return tuple(lst)
if ((isinstance(result, np.ndarray) and result.dtype.kind == 'O')
or isinstance(result, self.mpmath.ctx_mp.mpnumeric)):
return self.mptonp(result)
return result
class numpy_with_mpmath:
"""Namespace of universal functions on numpy arrays that use mpmath
backend for evaluation and return numpy arrays as outputs.
"""
_provides = [
'abs', 'absolute', 'sqrt', 'exp', 'expm1', 'exp2',
'log', 'log1p', 'log10', 'log2',
'sin', 'cos', 'tan', 'arcsin', 'arccos', 'arctan',
'sinh', 'cosh', 'tanh', 'arcsinh', 'arccosh', 'arctanh',
'square', 'positive', 'negative', 'conjugate', 'sign', 'sinc',
'normalize',
]
_mp_names = dict(
abs='absmin', absolute='absmin',
log='ln',
arcsin='asin', arccos='acos', arctan='atan',
arcsinh='asinh', arccosh='acosh', arctanh='atanh',
)
def __init__(self, mpmath, extra_prec_multiplier=0, extra_prec=0):
self.mpmath = mpmath
for name in self._provides:
mp_name = self._mp_names.get(name, name)
if hasattr(self, name):
op = getattr(self, name)
else:
def op(x, mp_name=mp_name):
return getattr(x.context, mp_name)(x)
setattr(self, name, vectorize_with_mpmath(op, mpmath=mpmath, extra_prec_multiplier=extra_prec_multiplier, extra_prec=extra_prec))
# The following function methods operate on mpmath number instances.
# The corresponding function names must be listed in
# numpy_with_mpmath._provides list.
def square(self, x):
return x * x
def positive(self, x):
return x
def negative(self, x):
return -x
def sqrt(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in sqrt(+-inf+-infj) evaluation (see mpmath/mpmath#776).
# TODO(pearu): remove this function when mpmath 1.4 or newer
# will be the required test dependency.
if ctx.isinf(x.imag):
return ctx.make_mpc((ctx.inf._mpf_, x.imag._mpf_))
return ctx.sqrt(x)
def expm1(self, x):
return x.context.expm1(x)
def log1p(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in log(+-inf+-infj) evaluation (see mpmath/mpmath#774).
# TODO(pearu): remove this function when mpmath 1.4 or newer
# will be the required test dependency.
if ctx.isinf(x.real) and ctx.isinf(x.imag):
pi = ctx.pi
if x.real > 0 and x.imag > 0:
return ctx.make_mpc((x.real._mpf_, (pi / 4)._mpf_))
if x.real > 0 and x.imag < 0:
return ctx.make_mpc((x.real._mpf_, (-pi / 4)._mpf_))
if x.real < 0 and x.imag < 0:
return ctx.make_mpc(((-x.real)._mpf_, (-3 * pi / 4)._mpf_))
if x.real < 0 and x.imag > 0:
return ctx.make_mpc(((-x.real)._mpf_, (3 * pi / 4)._mpf_))
return ctx.log1p(x)
def tan(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in tan(+-inf+-infj) evaluation (see mpmath/mpmath#781).
# TODO(pearu): remove this function when mpmath 1.4 or newer
# will be the required test dependency.
if ctx.isinf(x.imag) and (ctx.isinf(x.real) or ctx.isfinite(x.real)):
if x.imag > 0:
return ctx.make_mpc((ctx.zero._mpf_, ctx.one._mpf_))
return ctx.make_mpc((ctx.zero._mpf_, (-ctx.one)._mpf_))
if ctx.isinf(x.real) and ctx.isfinite(x.imag):
return ctx.make_mpc((ctx.nan._mpf_, ctx.nan._mpf_))
return ctx.tan(x)
def tanh(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in tanh(+-inf+-infj) evaluation (see mpmath/mpmath#781).
# TODO(pearu): remove this function when mpmath 1.4 or newer
# will be the required test dependency.
if ctx.isinf(x.imag) and (ctx.isinf(x.real) or ctx.isfinite(x.real)):
if x.imag > 0:
return ctx.make_mpc((ctx.zero._mpf_, ctx.one._mpf_))
return ctx.make_mpc((ctx.zero._mpf_, (-ctx.one)._mpf_))
if ctx.isinf(x.real) and ctx.isfinite(x.imag):
return ctx.make_mpc((ctx.nan._mpf_, ctx.nan._mpf_))
return ctx.tanh(x)
def log2(self, x):
return x.context.ln(x) / x.context.ln2
def log10(self, x):
return x.context.ln(x) / x.context.ln10
def exp2(self, x):
return x.context.exp(x * x.context.ln2)
def arcsin(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in asin(+-inf+-infj) evaluation (see
# mpmath/mpmath#793).
# TODO(pearu): remove the if-block below when mpmath 1.4 or
# newer will be the required test dependency.
pi = ctx.pi
inf = ctx.inf
zero = ctx.zero
if ctx.isinf(x.real):
sign_real = -1 if x.real < 0 else 1
real = sign_real * pi / (4 if ctx.isinf(x.imag) else 2)
imag = -inf if x.imag < 0 else inf
return ctx.make_mpc((real._mpf_, imag._mpf_))
elif ctx.isinf(x.imag):
return ctx.make_mpc((zero._mpf_, x.imag._mpf_))
# On branch cut, mpmath.mp.asin returns different value compared
# to mpmath.fp.asin and numpy.arcsin (see
# mpmath/mpmath#786). The following if-block ensures
# compatibility with numpy.arcsin.
if x.real > 1 and x.imag == 0:
return ctx.asin(x).conjugate()
return ctx.asin(x)
def arccos(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in acos(+-inf+-infj) evaluation (see
# mpmath/mpmath#793).
# TODO(pearu): remove the if-block below when mpmath 1.4 or
# newer will be the required test dependency.
pi = ctx.pi
inf = ctx.inf
zero = ctx.zero
if ctx.isinf(x.imag):
if ctx.isinf(x.real):
real = pi / 4 if x.real > 0 else 3 * pi / 4
else:
real = pi / 2
imag = inf if x.imag < 0 else -inf
return ctx.make_mpc((real._mpf_, imag._mpf_))
elif ctx.isinf(x.real):
inf = ctx.inf
sign_imag = -1 if x.imag < 0 else 1
real = zero if x.real > 0 else pi
return ctx.make_mpc((real._mpf_, (-sign_imag * inf)._mpf_))
# On branch cut, mpmath.mp.acos returns different value
# compared to mpmath.fp.acos and numpy.arccos. The
# following if-block ensures compatibility with
# numpy.arccos.
if x.imag == 0 and x.real > 1:
return -ctx.acos(x)
return ctx.acos(x)
def arcsinh(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in asinh(+-inf+-infj) evaluation
# (see mpmath/mpmath#749).
# TODO(pearu): remove the if-block below when mpmath 1.4 or
# newer will be the required test dependency.
pi = ctx.pi
inf = ctx.inf
zero = ctx.zero
if ctx.isinf(x.imag):
sign_imag = -1 if x.imag < 0 else 1
real = -inf if x.real < 0 else inf
imag = sign_imag * pi / (4 if ctx.isinf(x.real) else 2)
return ctx.make_mpc((real._mpf_, imag._mpf_))
elif ctx.isinf(x.real):
return ctx.make_mpc((x.real._mpf_, zero._mpf_))
# On branch cut, mpmath.mp.asinh returns different value
# compared to mpmath.fp.asinh and numpy.arcsinh (see
# mpmath/mpmath#786). The following if-block ensures
# compatibility with numpy.arcsinh.
if x.real == 0 and x.imag < -1:
return (-ctx.asinh(x)).conjugate()
return ctx.asinh(x)
def arccosh(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in acosh(+-inf+-infj) evaluation
# (see mpmath/mpmath#749).
pi = ctx.pi
inf = ctx.inf
zero = ctx.zero
if ctx.isinf(x.real):
sign_imag = -1 if x.imag < 0 else 1
imag = (
(3 if x.real < 0 else 1) * sign_imag * pi / 4
if ctx.isinf(x.imag)
else (sign_imag * pi if x.real < 0 else zero)
)
return ctx.make_mpc((inf._mpf_, imag._mpf_))
elif ctx.isinf(x.imag):
sign_imag = -1 if x.imag < 0 else 1
imag = sign_imag * pi / 2
return ctx.make_mpc((inf._mpf_, imag._mpf_))
return ctx.acosh(x)
def arctan(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in atan(+-inf+-infj) evaluation
# (see mpmath/mpmath#775 with the fix).
# TODO(pearu): remove the if-block below when mpmath 1.4 or
# newer will be the required test dependency.
pi = ctx.pi
zero = ctx.zero
if ctx.isinf(x.real) or ctx.isinf(x.imag):
if x.real < 0:
return ctx.make_mpc(((-pi / 2)._mpf_, zero._mpf_))
return ctx.make_mpc(((pi / 2)._mpf_, zero._mpf_))
# On branch cut, mpmath.mp.atan returns different value compared
# to mpmath.fp.atan and numpy.arctan (see mpmath/mpmath#865).
# The following if-block ensures compatibility with
# numpy.arctan.
if x.real == 0 and x.imag < -1:
return (-ctx.atan(x)).conjugate()
return ctx.atan(x)
def arctanh(self, x):
ctx = x.context
if isinstance(x, ctx.mpc):
# Workaround mpmath 1.3 bug in atanh(+-inf+-infj) evaluation
# (see mpmath/mpmath#775 with the fix).
# TODO(pearu): remove the if-block below when mpmath 1.4 or
# newer will be the required test dependency.
pi = ctx.pi
zero = ctx.zero
if ctx.isinf(x.real) or ctx.isinf(x.imag):
if x.imag < 0:
return ctx.make_mpc((zero._mpf_, (-pi / 2)._mpf_))
return ctx.make_mpc((zero._mpf_, (pi / 2)._mpf_))
# On branch cut, mpmath.mp.atanh returns different value
# compared to mpmath.fp.atanh and numpy.arctanh. The following
# if-block ensures compatibility with numpy.arctanh.
if x.imag == 0 and x.real > 1:
return ctx.atanh(x).conjugate()
return ctx.atanh(x)
def normalize(self, exact, reference, value):
"""Normalize reference and value using precision defined by the
difference of exact and reference.
"""
def worker(ctx, s, e, r, v):
ss, sm, se, sbc = s._mpf_
es, em, ee, ebc = e._mpf_
rs, rm, re, rbc = r._mpf_
vs, vm, ve, vbc = v._mpf_
if not (ctx.isfinite(e) and ctx.isfinite(r) and ctx.isfinite(v)):
return r, v
me = min(se, ee, re, ve)
# transform mantissa parts to the same exponent base
sm_e = sm << (se - me)
em_e = em << (ee - me)
rm_e = rm << (re - me)
vm_e = vm << (ve - me)
# find matching higher and non-matching lower bits of e and r
sm_b = bin(sm_e)[2:] if sm_e else ''
em_b = bin(em_e)[2:] if em_e else ''
rm_b = bin(rm_e)[2:] if rm_e else ''
vm_b = bin(vm_e)[2:] if vm_e else ''
m = max(len(sm_b), len(em_b), len(rm_b), len(vm_b))
em_b = '0' * (m - len(em_b)) + em_b
rm_b = '0' * (m - len(rm_b)) + rm_b
c1 = 0
for b0, b1 in zip(em_b, rm_b):
if b0 != b1:
break
c1 += 1
c0 = m - c1
# truncate r and v mantissa
rm_m = rm_e >> c0
vm_m = vm_e >> c0
# normalized r and v
nr = ctx.make_mpf((rs, rm_m, -c1, len(bin(rm_m)) - 2)) if rm_m else (-ctx.zero if rs else ctx.zero)
nv = ctx.make_mpf((vs, vm_m, -c1, len(bin(vm_m)) - 2)) if vm_m else (-ctx.zero if vs else ctx.zero)
return nr, nv
ctx = exact.context
scale = abs(exact)
if isinstance(exact, ctx.mpc):
rr, rv = worker(ctx, scale, exact.real, reference.real, value.real)
ir, iv = worker(ctx, scale, exact.imag, reference.imag, value.imag)
return ctx.make_mpc((rr._mpf_, ir._mpf_)), ctx.make_mpc((rv._mpf_, iv._mpf_))
elif isinstance(exact, ctx.mpf):
return worker(ctx, scale, exact, reference, value)
else:
assert 0 # unreachable
# Hypothesis testing support
def setup_hypothesis(max_examples=30) -> None:
"""Sets up the hypothesis profiles.
Sets up the hypothesis testing profiles, and selects the one specified by
the ``JAX_HYPOTHESIS_PROFILE`` environment variable (or the
``--jax_hypothesis_profile`` configuration.
Args:
max_examples: the maximum number of hypothesis examples to try, when using
the default "deterministic" profile.
"""
try:
import hypothesis as hp
except (ModuleNotFoundError, ImportError):
return
hp.settings.register_profile(
"deterministic",
database=None,
derandomize=True,
deadline=None,
max_examples=max_examples,
print_blob=True,
)
hp.settings.register_profile(
"interactive",
parent=hp.settings.load_profile("deterministic"),
max_examples=1,
report_multiple_bugs=False,
verbosity=hp.Verbosity.verbose,
# Don't try and shrink
phases=(
hp.Phase.explicit,
hp.Phase.reuse,
hp.Phase.generate,
hp.Phase.target,
hp.Phase.explain,
),
)
profile = HYPOTHESIS_PROFILE.value
logging.info("Using hypothesis profile: %s", profile)
hp.settings.load_profile(profile)
|
jax-mlREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@jax@_src@test_util.py@.PATH_END.py
|
{
"filename": "mlflow.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/chat_models/mlflow.py",
"type": "Python"
}
|
import json
import logging
from typing import (
Any,
Callable,
Dict,
Iterator,
List,
Literal,
Mapping,
Optional,
Sequence,
Type,
Union,
cast,
)
from urllib.parse import urlparse
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import BaseChatModel
from langchain_core.language_models.base import LanguageModelInput
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
BaseMessage,
BaseMessageChunk,
ChatMessage,
ChatMessageChunk,
FunctionMessage,
HumanMessage,
HumanMessageChunk,
InvalidToolCall,
SystemMessage,
SystemMessageChunk,
ToolCall,
ToolMessage,
ToolMessageChunk,
)
from langchain_core.messages.tool import tool_call_chunk
from langchain_core.output_parsers.openai_tools import (
make_invalid_tool_call,
parse_tool_call,
)
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
from langchain_core.runnables import Runnable, RunnableConfig
from langchain_core.tools import BaseTool
from langchain_core.utils.function_calling import convert_to_openai_tool
from pydantic import (
BaseModel,
Field,
PrivateAttr,
)
logger = logging.getLogger(__name__)
class ChatMlflow(BaseChatModel):
"""`MLflow` chat models API.
To use, you should have the `mlflow[genai]` python package installed.
For more information, see https://mlflow.org/docs/latest/llms/deployments.
Example:
.. code-block:: python
from langchain_community.chat_models import ChatMlflow
chat = ChatMlflow(
target_uri="http://localhost:5000",
endpoint="chat",
temperature=0.1,
)
"""
endpoint: str
"""The endpoint to use."""
target_uri: str
"""The target URI to use."""
temperature: float = 0.0
"""The sampling temperature."""
n: int = 1
"""The number of completion choices to generate."""
stop: Optional[List[str]] = None
"""The stop sequence."""
max_tokens: Optional[int] = None
"""The maximum number of tokens to generate."""
extra_params: dict = Field(default_factory=dict)
"""Any extra parameters to pass to the endpoint."""
_client: Any = PrivateAttr()
def __init__(self, **kwargs: Any):
super().__init__(**kwargs)
self._validate_uri()
try:
from mlflow.deployments import get_deploy_client
self._client = get_deploy_client(self.target_uri)
except ImportError as e:
raise ImportError(
"Failed to create the client. "
f"Please run `pip install mlflow{self._mlflow_extras}` to install "
"required dependencies."
) from e
@property
def _mlflow_extras(self) -> str:
return "[genai]"
def _validate_uri(self) -> None:
if self.target_uri == "databricks":
return
allowed = ["http", "https", "databricks"]
if urlparse(self.target_uri).scheme not in allowed:
raise ValueError(
f"Invalid target URI: {self.target_uri}. "
f"The scheme must be one of {allowed}."
)
@property
def _default_params(self) -> Dict[str, Any]:
params: Dict[str, Any] = {
"target_uri": self.target_uri,
"endpoint": self.endpoint,
"temperature": self.temperature,
"n": self.n,
"stop": self.stop,
"max_tokens": self.max_tokens,
"extra_params": self.extra_params,
}
return params
def _prepare_inputs(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
**kwargs: Any,
) -> Dict[str, Any]:
message_dicts = [
ChatMlflow._convert_message_to_dict(message) for message in messages
]
data: Dict[str, Any] = {
"messages": message_dicts,
"temperature": self.temperature,
"n": self.n,
**self.extra_params,
**kwargs,
}
if stop := self.stop or stop:
data["stop"] = stop
if self.max_tokens is not None:
data["max_tokens"] = self.max_tokens
return data
def _generate(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> ChatResult:
data = self._prepare_inputs(
messages,
stop,
**kwargs,
)
resp = self._client.predict(endpoint=self.endpoint, inputs=data)
return ChatMlflow._create_chat_result(resp)
def stream(
self,
input: LanguageModelInput,
config: Optional[RunnableConfig] = None,
*,
stop: Optional[List[str]] = None,
**kwargs: Any,
) -> Iterator[BaseMessageChunk]:
# We need to override `stream` to handle the case
# that `self._client` does not implement `predict_stream`
if not hasattr(self._client, "predict_stream"):
# MLflow deployment client does not implement streaming,
# so use default implementation
yield cast(
BaseMessageChunk, self.invoke(input, config=config, stop=stop, **kwargs)
)
else:
yield from super().stream(input, config, stop=stop, **kwargs)
def _stream(
self,
messages: List[BaseMessage],
stop: Optional[List[str]] = None,
run_manager: Optional[CallbackManagerForLLMRun] = None,
**kwargs: Any,
) -> Iterator[ChatGenerationChunk]:
data = self._prepare_inputs(
messages,
stop,
**kwargs,
)
# TODO: check if `_client.predict_stream` is available.
chunk_iter = self._client.predict_stream(endpoint=self.endpoint, inputs=data)
first_chunk_role = None
for chunk in chunk_iter:
if chunk["choices"]:
choice = chunk["choices"][0]
chunk_delta = choice["delta"]
if first_chunk_role is None:
first_chunk_role = chunk_delta.get("role")
chunk_message = ChatMlflow._convert_delta_to_message_chunk(
chunk_delta, first_chunk_role
)
generation_info = {}
if finish_reason := choice.get("finish_reason"):
generation_info["finish_reason"] = finish_reason
if logprobs := choice.get("logprobs"):
generation_info["logprobs"] = logprobs
chunk = ChatGenerationChunk(
message=chunk_message, generation_info=generation_info or None
)
if run_manager:
run_manager.on_llm_new_token(
chunk.text, chunk=chunk, logprobs=logprobs
)
yield chunk
else:
# Handle the case where choices are empty if needed
continue
@property
def _identifying_params(self) -> Dict[str, Any]:
return self._default_params
def _get_invocation_params(
self, stop: Optional[List[str]] = None, **kwargs: Any
) -> Dict[str, Any]:
"""Get the parameters used to invoke the model FOR THE CALLBACKS."""
return {
**self._default_params,
**super()._get_invocation_params(stop=stop, **kwargs),
}
@property
def _llm_type(self) -> str:
"""Return type of chat model."""
return "mlflow-chat"
@staticmethod
def _convert_dict_to_message(_dict: Mapping[str, Any]) -> BaseMessage:
role = _dict["role"]
content = cast(str, _dict.get("content"))
if role == "user":
return HumanMessage(content=content)
elif role == "assistant":
content = content or ""
additional_kwargs: Dict = {}
tool_calls = []
invalid_tool_calls = []
if raw_tool_calls := _dict.get("tool_calls"):
additional_kwargs["tool_calls"] = raw_tool_calls
for raw_tool_call in raw_tool_calls:
try:
tool_calls.append(
parse_tool_call(raw_tool_call, return_id=True)
)
except Exception as e:
invalid_tool_calls.append(
make_invalid_tool_call(raw_tool_call, str(e))
)
return AIMessage(
content=content,
additional_kwargs=additional_kwargs,
id=_dict.get("id"),
tool_calls=tool_calls,
invalid_tool_calls=invalid_tool_calls,
)
elif role == "system":
return SystemMessage(content=content)
else:
return ChatMessage(content=content, role=role)
@staticmethod
def _convert_delta_to_message_chunk(
_dict: Mapping[str, Any], default_role: str
) -> BaseMessageChunk:
role = _dict.get("role", default_role)
content = _dict.get("content") or ""
if role == "user":
return HumanMessageChunk(content=content)
elif role == "assistant":
additional_kwargs: Dict = {}
tool_call_chunks = []
if raw_tool_calls := _dict.get("tool_calls"):
additional_kwargs["tool_calls"] = raw_tool_calls
try:
tool_call_chunks = [
tool_call_chunk(
name=rtc["function"].get("name"),
args=rtc["function"].get("arguments"),
id=rtc.get("id"),
index=rtc["index"],
)
for rtc in raw_tool_calls
]
except KeyError:
pass
return AIMessageChunk(
content=content,
additional_kwargs=additional_kwargs,
id=_dict.get("id"),
tool_call_chunks=tool_call_chunks,
)
elif role == "system":
return SystemMessageChunk(content=content)
elif role == "tool":
return ToolMessageChunk(
content=content, tool_call_id=_dict["tool_call_id"], id=_dict.get("id")
)
else:
return ChatMessageChunk(content=content, role=role)
@staticmethod
def _raise_functions_not_supported() -> None:
raise ValueError(
"Function messages are not supported by Databricks. Please"
" create a feature request at https://github.com/mlflow/mlflow/issues."
)
@staticmethod
def _convert_message_to_dict(message: BaseMessage) -> dict:
message_dict = {"content": message.content}
if (name := message.name or message.additional_kwargs.get("name")) is not None:
message_dict["name"] = name
if isinstance(message, ChatMessage):
message_dict["role"] = message.role
elif isinstance(message, HumanMessage):
message_dict["role"] = "user"
elif isinstance(message, AIMessage):
message_dict["role"] = "assistant"
if message.tool_calls or message.invalid_tool_calls:
message_dict["tool_calls"] = [
_lc_tool_call_to_openai_tool_call(tc) for tc in message.tool_calls
] + [
_lc_invalid_tool_call_to_openai_tool_call(tc)
for tc in message.invalid_tool_calls
] # type: ignore[assignment]
elif "tool_calls" in message.additional_kwargs:
message_dict["tool_calls"] = message.additional_kwargs["tool_calls"]
tool_call_supported_props = {"id", "type", "function"}
message_dict["tool_calls"] = [
{
k: v
for k, v in tool_call.items() # type: ignore[union-attr]
if k in tool_call_supported_props
}
for tool_call in message_dict["tool_calls"]
]
else:
pass
# If tool calls present, content null value should be None not empty string.
if "tool_calls" in message_dict:
message_dict["content"] = message_dict["content"] or None # type: ignore[assignment]
elif isinstance(message, SystemMessage):
message_dict["role"] = "system"
elif isinstance(message, ToolMessage):
message_dict["role"] = "tool"
message_dict["tool_call_id"] = message.tool_call_id
supported_props = {"content", "role", "tool_call_id"}
message_dict = {
k: v for k, v in message_dict.items() if k in supported_props
}
elif isinstance(message, FunctionMessage):
raise ValueError(
"Function messages are not supported by Databricks. Please"
" create a feature request at https://github.com/mlflow/mlflow/issues."
)
else:
raise ValueError(f"Got unknown message type: {message}")
if "function_call" in message.additional_kwargs:
ChatMlflow._raise_functions_not_supported()
return message_dict
@staticmethod
def _create_chat_result(response: Mapping[str, Any]) -> ChatResult:
generations = []
for choice in response["choices"]:
message = ChatMlflow._convert_dict_to_message(choice["message"])
usage = choice.get("usage", {})
gen = ChatGeneration(
message=message,
generation_info=usage,
)
generations.append(gen)
usage = response.get("usage", {})
return ChatResult(generations=generations, llm_output=usage)
def bind_tools(
self,
tools: Sequence[Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool]],
*,
tool_choice: Optional[
Union[dict, str, Literal["auto", "none", "required", "any"], bool]
] = None,
**kwargs: Any,
) -> Runnable[LanguageModelInput, BaseMessage]:
"""Bind tool-like objects to this chat model.
Assumes model is compatible with OpenAI tool-calling API.
Args:
tools: A list of tool definitions to bind to this chat model.
Can be a dictionary, pydantic model, callable, or BaseTool. Pydantic
models, callables, and BaseTools will be automatically converted to
their schema dictionary representation.
tool_choice: Which tool to require the model to call.
Options are:
name of the tool (str): calls corresponding tool;
"auto": automatically selects a tool (including no tool);
"none": model does not generate any tool calls and instead must
generate a standard assistant message;
"required": the model picks the most relevant tool in tools and
must generate a tool call;
or a dict of the form:
{"type": "function", "function": {"name": <<tool_name>>}}.
**kwargs: Any additional parameters to pass to the
:class:`~langchain.runnable.Runnable` constructor.
"""
formatted_tools = [convert_to_openai_tool(tool) for tool in tools]
if tool_choice:
if isinstance(tool_choice, str):
# tool_choice is a tool/function name
if tool_choice not in ("auto", "none", "required"):
tool_choice = {
"type": "function",
"function": {"name": tool_choice},
}
elif isinstance(tool_choice, dict):
tool_names = [
formatted_tool["function"]["name"]
for formatted_tool in formatted_tools
]
if not any(
tool_name == tool_choice["function"]["name"]
for tool_name in tool_names
):
raise ValueError(
f"Tool choice {tool_choice} was specified, but the only "
f"provided tools were {tool_names}."
)
else:
raise ValueError(
f"Unrecognized tool_choice type. Expected str, bool or dict. "
f"Received: {tool_choice}"
)
kwargs["tool_choice"] = tool_choice
return super().bind(tools=formatted_tools, **kwargs)
def _lc_tool_call_to_openai_tool_call(tool_call: ToolCall) -> dict:
return {
"type": "function",
"id": tool_call["id"],
"function": {
"name": tool_call["name"],
"arguments": json.dumps(tool_call["args"]),
},
}
def _lc_invalid_tool_call_to_openai_tool_call(
invalid_tool_call: InvalidToolCall,
) -> dict:
return {
"type": "function",
"id": invalid_tool_call["id"],
"function": {
"name": invalid_tool_call["name"],
"arguments": invalid_tool_call["args"],
},
}
|
langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@chat_models@mlflow.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "macrocosme/shwirl",
"repo_path": "shwirl_extracted/shwirl-master/shwirl/extern/vispy/visuals/collections/__init__.py",
"type": "Python"
}
|
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# Copyright (c) 2015, Vispy Development Team.
# Distributed under the (new) BSD License. See LICENSE.txt for more info.
# -----------------------------------------------------------------------------
"""
Collections allow batch rendering of object of the same type:
- Points
- Line segments
- Polylines (paths)
- Raw Triangles
- Polygons
Each collection has several modes:
- raw (point, segment, path, triangle, polygon)
- agg (point, segment, path, polygon)
- agg+ (path, polygon)
Note: Storage of shared attributes requires non-clamped textures which is not
the case on all graphic cards. This means such shared attributes must be
normalized on CPU and scales back on GPU (in shader code).
"""
from . path_collection import PathCollection # noqa
from . point_collection import PointCollection # noqa
from . polygon_collection import PolygonCollection # noqa
from . segment_collection import SegmentCollection # noqa
from . triangle_collection import TriangleCollection # noqa
|
macrocosmeREPO_NAMEshwirlPATH_START.@shwirl_extracted@shwirl-master@shwirl@extern@vispy@visuals@collections@__init__.py@.PATH_END.py
|
{
"filename": "credentials.py",
"repo_name": "PrefectHQ/prefect",
"repo_path": "prefect_extracted/prefect-main/src/integrations/prefect-docker/prefect_docker/credentials.py",
"type": "Python"
}
|
"""Module containing docker credentials."""
import docker
from pydantic import Field, SecretStr
from prefect.blocks.core import Block
from prefect.logging import get_run_logger
from prefect.utilities.asyncutils import run_sync_in_worker_thread
class DockerRegistryCredentials(Block):
"""
Block used to manage credentials for interacting with a Docker Registry.
Examples:
Log into Docker Registry.
```python
from prefect_docker import DockerHost, DockerRegistryCredentials
docker_host = DockerHost()
docker_registry_credentials = DockerRegistryCredentials(
username="my_username",
password="my_password",
registry_url="registry.hub.docker.com",
)
with docker_host.get_client() as client:
docker_registry_credentials.login(client)
```
"""
_block_type_name = "Docker Registry Credentials"
_logo_url = "https://cdn.sanity.io/images/3ugk85nk/production/14a315b79990200db7341e42553e23650b34bb96-250x250.png" # noqa
_description = "Store credentials for interacting with a Docker Registry."
username: str = Field(
default=..., description="The username to log into the registry with."
)
password: SecretStr = Field(
default=..., description="The password to log into the registry with."
)
registry_url: str = Field(
default=...,
description=(
'The URL to the registry. Generally, "http" or "https" can be omitted.'
),
examples=["index.docker.io"],
)
reauth: bool = Field(
default=True,
description="Whether or not to reauthenticate on each interaction.",
)
async def login(self, client: docker.DockerClient):
"""
Authenticates a given Docker client with the configured Docker registry.
Args:
client: A Docker Client.
"""
logger = get_run_logger()
logger.debug(f"Logging into {self.registry_url}.")
await run_sync_in_worker_thread(
client.login,
username=self.username,
password=self.password.get_secret_value(),
registry=self.registry_url,
# See https://github.com/docker/docker-py/issues/2256 for information on
# the default value for reauth.
reauth=self.reauth,
)
|
PrefectHQREPO_NAMEprefectPATH_START.@prefect_extracted@prefect-main@src@integrations@prefect-docker@prefect_docker@credentials.py@.PATH_END.py
|
{
"filename": "bin_convert.py",
"repo_name": "IAS-Astrophysics/athenak",
"repo_path": "athenak_extracted/athenak-main/vis/python/bin_convert.py",
"type": "Python"
}
|
"""
Functions to:
(1) convert bin --> Python dictionary
(2) convert Python dictionary --> athdf(xdmf) files
This module contains a collection of helper functions for reading and
writing athena file data formats. More information is provided in the
function docstrings.
----
In order to translate a binary file into athdf and corresponding xdmf
files, you could do the following:
import bin_convert
import os
binary_fname = "path/to/file.bin"
athdf_fname = binary_fname.replace(".bin", ".athdf")
xdmf_fname = athdf_fname + ".xdmf"
filedata = bin_convert.read_binary(binary_fname)
bin_convert.write_athdf(athdf_fname, filedata)
bin_convert.write_xdmf_for(xdmf_fname, os.path.basename(athdf_fname), filedata)
Notice that write_xdmf_for(...) function expects the relative path to
the athdf file from the xdmf, so please be aware of this requirement.
----
The read_*(...) functions return a filedata dictionary-like object with
filedata['header'] = array of strings
ordered array of header, including all the header information
filedata['time'] = float
time from input file
filedata['cycle'] = int
cycle from input file
filedata['var_names'] = array of strings
ordered array of variable names, like ['dens', 'eint', ...]
filedata['n_mbs'] = int
total number of meshblocks in the file
filedata['nx1_mb'] = int
number of cells in x1 direction in MeshBlock
filedata['nx2_mb'] = int
number of cells in x2 direction in MeshBlock
filedata['nx3_mb'] = int
number of cells in x3 direction in MeshBlock
filedata['nx1_out_mb'] = int
number of output cells in x1 direction in MeshBlock (useful for slicing)
filedata['nx2_out_mb'] = int
number of output cells in x2 direction in MeshBlock (useful for slicing)
filedata['nx3_out_mb'] = int
number of output cells in x3 direction in MeshBlock (useful for slicing)
filedata['Nx1'] = int
total number of cell in x1 direction in root grid
filedata['Nx2'] = int
total number of cell in x2 direction in root grid
filedata['Nx3'] = int
total number of cell in x3 direction in root grid
filedata['x1min'] = float
coordinate minimum of root grid in x1 direction
filedata['x1max'] = float
coordinate maximum of root grid in x1 direction
filedata['x2min'] = float
coordinate minimum of root grid in x2 direction
filedata['x2max'] = float
coordinate maximum of root grid in x2 direction
filedata['x3min'] = float
coordinate minimum of root grid in x3 direction
filedata['x3max'] = float
coordinate maximum of root grid in x3 direction
filedata['nvars'] = int
number of output variables (including magnetic field if it exists)
filedata['mb_index'] = array with shape [n_mbs, 6]
is,ie,js,je,ks,ke range for output MeshBlock indexing (useful for slicing)
filedata['mb_logical'] = array with shape [n_mbs, 4]
i,j,k,level coordinates for each MeshBlock
filedata['mb_geometry'] = array with shape [n_mbs, 6]
x1i,x2i,x3i,dx1,dx2,dx3 including cell-centered location of left-most
cell and offsets between cells
filedata['mb_data'] = dict of arrays with shape [n_mbs, nx3, nx2, nx1]
{'var1':var1_array, 'var2':var2_array, ...} dictionary of fluid data arrays
for each variable in var_names
"""
import numpy as np
import struct
import h5py
import os
def read_binary(filename):
"""
Reads a bin file from filename to dictionary.
Originally written by Lev Arzamasskiy (leva@ias.edu) on 11/15/2021
Updated to support mesh refinement by George Wong (gnwong@ias.edu) on 01/27/2022
args:
filename - string
filename of bin file to read
returns:
filedata - dict
dictionary of fluid file data
"""
filedata = {}
# load file and get size
fp = open(filename, "rb")
fp.seek(0, 2)
filesize = fp.tell()
fp.seek(0, 0)
# load header information and validate file format
code_header = fp.readline().split()
if len(code_header) < 1:
raise TypeError("unknown file format")
if code_header[0] != b"Athena":
raise TypeError(
f"bad file format \"{code_header[0].decode('utf-8')}\" "
+ '(should be "Athena")'
)
version = code_header[-1].split(b"=")[-1]
if version != b"1.1":
raise TypeError(f"unsupported file format version {version.decode('utf-8')}")
pheader_count = int(fp.readline().split(b"=")[-1])
pheader = {}
for _ in range(pheader_count - 1):
key, val = [x.strip() for x in fp.readline().decode("utf-8").split("=")]
pheader[key] = val
time = float(pheader["time"])
cycle = int(pheader["cycle"])
locsizebytes = int(pheader["size of location"])
varsizebytes = int(pheader["size of variable"])
nvars = int(fp.readline().split(b"=")[-1])
var_list = [v.decode("utf-8") for v in fp.readline().split()[1:]]
header_size = int(fp.readline().split(b"=")[-1])
header = [
line.decode("utf-8").split("#")[0].strip()
for line in fp.read(header_size).split(b"\n")
]
header = [line for line in header if len(line) > 0]
if locsizebytes not in [4, 8]:
raise ValueError(f"unsupported location size (in bytes) {locsizebytes}")
if varsizebytes not in [4, 8]:
raise ValueError(f"unsupported variable size (in bytes) {varsizebytes}")
locfmt = "d" if locsizebytes == 8 else "f"
varfmt = "d" if varsizebytes == 8 else "f"
# load grid information from header and validate
def get_from_header(header, blockname, keyname):
blockname = blockname.strip()
keyname = keyname.strip()
if not blockname.startswith("<"):
blockname = "<" + blockname
if blockname[-1] != ">":
blockname += ">"
block = "<none>"
for line in [entry for entry in header]:
if line.startswith("<"):
block = line
continue
key, value = line.split("=")
if block == blockname and key.strip() == keyname:
return value
raise KeyError(f"no parameter called {blockname}/{keyname}")
Nx1 = int(get_from_header(header, "<mesh>", "nx1"))
Nx2 = int(get_from_header(header, "<mesh>", "nx2"))
Nx3 = int(get_from_header(header, "<mesh>", "nx3"))
nx1 = int(get_from_header(header, "<meshblock>", "nx1"))
nx2 = int(get_from_header(header, "<meshblock>", "nx2"))
nx3 = int(get_from_header(header, "<meshblock>", "nx3"))
nghost = int(get_from_header(header, "<mesh>", "nghost"))
x1min = float(get_from_header(header, "<mesh>", "x1min"))
x1max = float(get_from_header(header, "<mesh>", "x1max"))
x2min = float(get_from_header(header, "<mesh>", "x2min"))
x2max = float(get_from_header(header, "<mesh>", "x2max"))
x3min = float(get_from_header(header, "<mesh>", "x3min"))
x3max = float(get_from_header(header, "<mesh>", "x3max"))
# load data from each meshblock
n_vars = len(var_list)
mb_count = 0
mb_index = []
mb_logical = []
mb_geometry = []
mb_data = {}
for var in var_list:
mb_data[var] = []
while fp.tell() < filesize:
mb_index.append(np.array(struct.unpack("@6i", fp.read(24))) - nghost)
nx1_out = (mb_index[mb_count][1] - mb_index[mb_count][0]) + 1
nx2_out = (mb_index[mb_count][3] - mb_index[mb_count][2]) + 1
nx3_out = (mb_index[mb_count][5] - mb_index[mb_count][4]) + 1
mb_logical.append(np.array(struct.unpack("@4i", fp.read(16))))
mb_geometry.append(
np.array(struct.unpack("=6" + locfmt, fp.read(6 * locsizebytes)))
)
data = np.array(
struct.unpack(
f"={nx1_out*nx2_out*nx3_out*n_vars}" + varfmt,
fp.read(varsizebytes * nx1_out * nx2_out * nx3_out * n_vars),
)
)
data = data.reshape(nvars, nx3_out, nx2_out, nx1_out)
for vari, var in enumerate(var_list):
mb_data[var].append(data[vari])
mb_count += 1
fp.close()
filedata["header"] = header
filedata["time"] = time
filedata["cycle"] = cycle
filedata["var_names"] = var_list
filedata["Nx1"] = Nx1
filedata["Nx2"] = Nx2
filedata["Nx3"] = Nx3
filedata["nvars"] = nvars
filedata["x1min"] = x1min
filedata["x1max"] = x1max
filedata["x2min"] = x2min
filedata["x2max"] = x2max
filedata["x3min"] = x3min
filedata["x3max"] = x3max
filedata["n_mbs"] = mb_count
filedata["nx1_mb"] = nx1
filedata["nx2_mb"] = nx2
filedata["nx3_mb"] = nx3
filedata["nx1_out_mb"] = (mb_index[0][1] - mb_index[0][0]) + 1
filedata["nx2_out_mb"] = (mb_index[0][3] - mb_index[0][2]) + 1
filedata["nx3_out_mb"] = (mb_index[0][5] - mb_index[0][4]) + 1
filedata["mb_index"] = np.array(mb_index)
filedata["mb_logical"] = np.array(mb_logical)
filedata["mb_geometry"] = np.array(mb_geometry)
filedata["mb_data"] = mb_data
return filedata
def read_coarsened_binary(filename):
"""
Reads a bin file from filename to dictionary.
Originally written by Lev Arzamasskiy (leva@ias.edu) on 11/15/2021
Updated to support mesh refinement by George Wong (gnwong@ias.edu) on 01/27/2022
args:
filename - string
filename of bin file to read
returns:
filedata - dict
dictionary of fluid file data
"""
filedata = {}
# load file and get size
fp = open(filename, "rb")
fp.seek(0, 2)
filesize = fp.tell()
fp.seek(0, 0)
# load header information and validate file format
code_header = fp.readline().split()
if len(code_header) < 1:
raise TypeError("unknown file format")
if code_header[0] != b"Athena":
raise TypeError(
f"bad file format \"{code_header[0].decode('utf-8')}\" "
+ '(should be "Athena")'
)
version = code_header[-1].split(b"=")[-1]
if version != b"1.1":
raise TypeError(f"unsupported file format version {version.decode('utf-8')}")
pheader_count = int(fp.readline().split(b"=")[-1])
pheader = {}
for _ in range(pheader_count - 1):
key, val = [x.strip() for x in fp.readline().decode("utf-8").split("=")]
pheader[key] = val
time = float(pheader["time"])
cycle = int(pheader["cycle"])
locsizebytes = int(pheader["size of location"])
varsizebytes = int(pheader["size of variable"])
coarsen_factor = int(pheader["coarsening factor"])
nvars = int(fp.readline().split(b"=")[-1])
var_list = [v.decode("utf-8") for v in fp.readline().split()[1:]]
header_size = int(fp.readline().split(b"=")[-1])
header = [
line.decode("utf-8").split("#")[0].strip()
for line in fp.read(header_size).split(b"\n")
]
header = [line for line in header if len(line) > 0]
if locsizebytes not in [4, 8]:
raise ValueError(f"unsupported location size (in bytes) {locsizebytes}")
if varsizebytes not in [4, 8]:
raise ValueError(f"unsupported variable size (in bytes) {varsizebytes}")
locfmt = "d" if locsizebytes == 8 else "f"
varfmt = "d" if varsizebytes == 8 else "f"
# load grid information from header and validate
def get_from_header(header, blockname, keyname):
blockname = blockname.strip()
keyname = keyname.strip()
if not blockname.startswith("<"):
blockname = "<" + blockname
if blockname[-1] != ">":
blockname += ">"
block = "<none>"
for line in [entry for entry in header]:
if line.startswith("<"):
block = line
continue
key, value = line.split("=")
if block == blockname and key.strip() == keyname:
return value
raise KeyError(f"no parameter called {blockname}/{keyname}")
Nx1 = int(get_from_header(header, "<mesh>", "nx1"))
Nx2 = int(get_from_header(header, "<mesh>", "nx2"))
Nx3 = int(get_from_header(header, "<mesh>", "nx3"))
nx1 = int(get_from_header(header, "<meshblock>", "nx1"))
nx2 = int(get_from_header(header, "<meshblock>", "nx2"))
nx3 = int(get_from_header(header, "<meshblock>", "nx3"))
nghost = int(get_from_header(header, "<mesh>", "nghost"))
x1min = float(get_from_header(header, "<mesh>", "x1min"))
x1max = float(get_from_header(header, "<mesh>", "x1max"))
x2min = float(get_from_header(header, "<mesh>", "x2min"))
x2max = float(get_from_header(header, "<mesh>", "x2max"))
x3min = float(get_from_header(header, "<mesh>", "x3min"))
x3max = float(get_from_header(header, "<mesh>", "x3max"))
# load data from each meshblock
n_vars = len(var_list)
mb_count = 0
mb_index = []
mb_logical = []
mb_geometry = []
mb_data = {}
for var in var_list:
mb_data[var] = []
while fp.tell() < filesize:
mb_index.append(np.array(struct.unpack("@6i", fp.read(24))) - nghost)
nx1_out = (mb_index[mb_count][1] - mb_index[mb_count][0]) + 1
nx2_out = (mb_index[mb_count][3] - mb_index[mb_count][2]) + 1
nx3_out = (mb_index[mb_count][5] - mb_index[mb_count][4]) + 1
mb_logical.append(np.array(struct.unpack("@4i", fp.read(16))))
mb_geometry.append(
np.array(struct.unpack("=6" + locfmt, fp.read(6 * locsizebytes)))
)
data = np.array(
struct.unpack(
f"={nx1_out*nx2_out*nx3_out*n_vars}" + varfmt,
fp.read(varsizebytes * nx1_out * nx2_out * nx3_out * n_vars),
)
)
data = data.reshape(nvars, nx3_out, nx2_out, nx1_out)
for vari, var in enumerate(var_list):
mb_data[var].append(data[vari])
mb_count += 1
fp.close()
filedata["header"] = header
filedata["time"] = time
filedata["cycle"] = cycle
filedata["var_names"] = var_list
filedata["Nx1"] = Nx1 // coarsen_factor
filedata["Nx2"] = Nx2 // coarsen_factor
filedata["Nx3"] = Nx3 // coarsen_factor
filedata["nvars"] = nvars
filedata["number_of_moments"] = int(pheader["number of moments"])
filedata["x1min"] = x1min
filedata["x1max"] = x1max
filedata["x2min"] = x2min
filedata["x2max"] = x2max
filedata["x3min"] = x3min
filedata["x3max"] = x3max
filedata["n_mbs"] = mb_count
filedata["nx1_mb"] = nx1 // coarsen_factor
filedata["nx2_mb"] = nx2 // coarsen_factor
filedata["nx3_mb"] = nx3 // coarsen_factor
filedata["nx1_out_mb"] = (mb_index[0][1] - mb_index[0][0]) + 1
filedata["nx2_out_mb"] = (mb_index[0][3] - mb_index[0][2]) + 1
filedata["nx3_out_mb"] = (mb_index[0][5] - mb_index[0][4]) + 1
filedata["mb_index"] = np.array(mb_index)
filedata["mb_logical"] = np.array(mb_logical)
filedata["mb_geometry"] = np.array(mb_geometry)
filedata["mb_data"] = mb_data
return filedata
def write_athdf(filename, fdata, varsize_bytes=4, locsize_bytes=8):
"""
Writes an athdf (hdf5) file from a loaded python filedata object.
args:
filename - string
filename for output athdf (hdf5) file
fdata - dict
dictionary of fluid file data, e.g., as loaded from read_binary(...)
varsize_bytes - int (default=4, options=4,8)
number of bytes to use for output variable data
locsize_bytes - int (default=8, options=4,8)
number of bytes to use for output location data
"""
if varsize_bytes not in [4, 8]:
raise ValueError(f"varsizebytes must be 4 or 8, not {varsize_bytes}")
if locsize_bytes not in [4, 8]:
raise ValueError(f"locsizebytes must be 4 or 8, not {locsize_bytes}")
locfmt = "<f4" if locsize_bytes == 4 else "<f8"
varfmt = "<f4" if varsize_bytes == 4 else "<f8"
# extract Mesh/MeshBlock parameters
nmb = fdata["n_mbs"]
Nx1 = fdata["Nx1"] # noqa: F841
Nx2 = fdata["Nx2"]
Nx3 = fdata["Nx3"]
nx1 = fdata["nx1_mb"]
nx2 = fdata["nx2_mb"]
nx3 = fdata["nx3_mb"]
nx1_out = fdata["nx1_out_mb"]
nx2_out = fdata["nx2_out_mb"]
nx3_out = fdata["nx3_out_mb"]
number_of_moments = fdata.get("number_of_moments", 1)
# check dimensionality/slicing
nx1_out = fdata["nx1_out_mb"]
nx2_out = fdata["nx2_out_mb"]
nx3_out = fdata["nx3_out_mb"]
two_d = Nx2 != 1 and Nx3 == 1
three_d = Nx3 != 1
x1slice = nx1_out == 1
x2slice = nx2_out == 1 and (two_d or three_d)
x3slice = nx3_out == 1 and three_d
# keep variable order but separate out magnetic field
vars_without_b = [v for v in fdata["var_names"] if "bcc" not in v]
vars_only_b = [v for v in fdata["var_names"] if v not in vars_without_b]
if len(vars_only_b) > 0:
B = np.zeros((3*number_of_moments, nmb, nx3_out, nx2_out, nx1_out))
Levels = np.zeros(nmb)
LogicalLocations = np.zeros((nmb, 3))
uov = np.zeros((len(vars_without_b), nmb, nx3_out, nx2_out, nx1_out))
x1f = np.zeros((nmb, nx1_out + 1))
x1v = np.zeros((nmb, nx1_out))
x2f = np.zeros((nmb, nx2_out + 1))
x2v = np.zeros((nmb, nx2_out))
x3f = np.zeros((nmb, nx3_out + 1))
x3v = np.zeros((nmb, nx3_out))
for ivar, var in enumerate(vars_without_b):
uov[ivar] = fdata["mb_data"][var]
for ibvar, bvar in enumerate(vars_only_b):
B[ibvar] = fdata["mb_data"][bvar]
for mb in range(nmb):
logical = fdata["mb_logical"][mb]
LogicalLocations[mb] = logical[:3]
Levels[mb] = logical[-1]
geometry = fdata["mb_geometry"][mb]
mb_x1f = np.linspace(geometry[0], geometry[1], nx1 + 1)
mb_x1v = 0.5 * (mb_x1f[1:] + mb_x1f[:-1])
mb_x2f = np.linspace(geometry[2], geometry[3], nx2 + 1)
mb_x2v = 0.5 * (mb_x2f[1:] + mb_x2f[:-1])
mb_x3f = np.linspace(geometry[4], geometry[5], nx3 + 1)
mb_x3v = 0.5 * (mb_x3f[1:] + mb_x3f[:-1])
if x1slice:
x1f[mb] = np.array(
mb_x1f[(fdata["mb_index"][mb][0]):(fdata["mb_index"][mb][0] + 2)]
)
x1v[mb] = np.array([np.average(mb_x1f)])
else:
x1f[mb] = mb_x1f
x1v[mb] = mb_x1v
if x2slice:
x2f[mb] = np.array(
mb_x2f[(fdata["mb_index"][mb][2]):(fdata["mb_index"][mb][2] + 2)]
)
x2v[mb] = np.array([np.average(x2f[mb])])
else:
x2f[mb] = mb_x2f
x2v[mb] = mb_x2v
if x3slice:
x3f[mb] = np.array(
mb_x3f[(fdata["mb_index"][mb][4]):(fdata["mb_index"][mb][4] + 2)]
)
x3v[mb] = np.array([np.average(x3f[mb])])
else:
x3f[mb] = mb_x3f
x3v[mb] = mb_x3v
# set dataset names and number of variables
dataset_names = [np.array("uov", dtype="|S21")]
dataset_nvars = [len(vars_without_b)]
if len(vars_only_b) > 0:
dataset_names.append(np.array("B", dtype="|S21"))
dataset_nvars.append(len(vars_only_b))
# Set Attributes
hfp = h5py.File(filename, "w")
hfp.attrs["Header"] = fdata["header"]
hfp.attrs["Time"] = fdata["time"]
hfp.attrs["NumCycles"] = fdata["cycle"]
hfp.attrs["Coordinates"] = np.array("cartesian", dtype="|S11")
hfp.attrs["NumMeshBlocks"] = fdata["n_mbs"]
hfp.attrs["MaxLevel"] = int(max(Levels))
hfp.attrs["MeshBlockSize"] = [
fdata["nx1_out_mb"],
fdata["nx2_out_mb"],
fdata["nx3_out_mb"],
]
hfp.attrs["RootGridSize"] = [fdata["Nx1"], fdata["Nx2"], fdata["Nx3"]]
hfp.attrs["RootGridX1"] = [fdata["x1min"], fdata["x1max"], 1.0]
hfp.attrs["RootGridX2"] = [fdata["x2min"], fdata["x2max"], 1.0]
hfp.attrs["RootGridX3"] = [fdata["x3min"], fdata["x3max"], 1.0]
hfp.attrs["DatasetNames"] = dataset_names
hfp.attrs["NumVariables"] = dataset_nvars
hfp.attrs["VariableNames"] = [
np.array(i, dtype="|S21") for i in (vars_without_b + vars_only_b)
]
# Create Datasets
if len(vars_only_b) > 0:
hfp.create_dataset("B", data=B, dtype=varfmt)
hfp.create_dataset("Levels", data=Levels, dtype=">i4")
hfp.create_dataset("LogicalLocations", data=LogicalLocations, dtype=">i8")
hfp.create_dataset("uov", data=uov, dtype=varfmt)
hfp.create_dataset("x1f", data=x1f, dtype=locfmt)
hfp.create_dataset("x1v", data=x1v, dtype=locfmt)
hfp.create_dataset("x2f", data=x2f, dtype=locfmt)
hfp.create_dataset("x2v", data=x2v, dtype=locfmt)
hfp.create_dataset("x3f", data=x3f, dtype=locfmt)
hfp.create_dataset("x3v", data=x3v, dtype=locfmt)
hfp.close()
def write_xdmf_for(xdmfname, dumpname, fdata, mode="auto"):
"""
Writes an xdmf file for a fluid snapshot file.
args:
xdmfname - string
name of xdmf file
dumpname - string
location of fluid data file relative to xdmfname directory
fdata - dict
dictionary of fluid file data, e.g., as loaded from read_binary(...)
mode - string (unimplemented)
force xdmf for format (auto sets by extension)
"""
fp = open(xdmfname, "w")
def write_meshblock(fp, mb, nx1, nx2, nx3, nmb, dumpname, vars_no_b, vars_w_b):
fp.write(f""" <Grid Name="MeshBlock{mb}" GridType="Uniform">\n""")
fp.write(""" <Topology TopologyType="3DRectMesh" """)
fp.write(f""" NumberOfElements="{nx3+1} {nx2+1} {nx1+1}"/>\n""")
fp.write(""" <Geometry GeometryType="VXVYVZ">\n""")
fp.write(
f""" <DataItem ItemType="HyperSlab" Dimensions="{nx1+1}">
<DataItem Dimensions="3 2" NumberType="Int"> {mb} 0 1 1 1 {nx1+1} </DataItem>
<DataItem Dimensions="{nmb} {nx1+1}" Format="HDF"> {dumpname}:/x1f </DataItem>
</DataItem>
<DataItem ItemType="HyperSlab" Dimensions="{nx2+1}">
<DataItem Dimensions="3 2" NumberType="Int"> {mb} 0 1 1 1 {nx2+1} </DataItem>
<DataItem Dimensions="{nmb} {nx2+1}" Format="HDF"> {dumpname}:/x2f </DataItem>
</DataItem>
<DataItem ItemType="HyperSlab" Dimensions="{nx3+1}">
<DataItem Dimensions="3 2" NumberType="Int"> {mb} 0 1 1 1 {nx3+1} </DataItem>
<DataItem Dimensions="{nmb} {nx3+1}" Format="HDF"> {dumpname}:/x3f </DataItem>
</DataItem>
</Geometry>\n"""
)
nvar_no_b = len(vars_no_b)
for vi, var_name in enumerate(vars_no_b):
fp.write(
f""" <Attribute Name="{var_name}" Center="Cell">
<DataItem ItemType="HyperSlab" Dimensions="{nx3} {nx2} {nx1}">
<DataItem Dimensions="3 5" NumberType="Int">
{vi} {mb} 0 0 0 1 1 1 1 1 1 1 {nx3} {nx2} {nx1}
</DataItem>
<DataItem Dimensions="{nvar_no_b} {nmb} {nx3} {nx2} {nx1}" Format="HDF">
{dumpname}:/uov
</DataItem>
</DataItem>
</Attribute>\n"""
)
nvar_w_b = len(vars_w_b)
if nvar_w_b > 0:
for vi, var_name in enumerate(vars_w_b):
fp.write(
f""" <Attribute Name="{var_name}" Center="Cell">
<DataItem ItemType="HyperSlab" Dimensions="{nx3} {nx2} {nx1}">
<DataItem Dimensions="3 5" NumberType="Int">
{vi} {mb} 0 0 0 1 1 1 1 1 1 1 {nx3} {nx2} {nx1}
</DataItem>
<DataItem Dimensions="{nvar_w_b} {nmb} {nx3} {nx2} {nx1}" Format="HDF">
{dumpname}:/B
</DataItem>
</DataItem>
</Attribute>\n"""
)
fp.write(""" </Grid>\n""")
fp.write(
"""<?xml version="1.0" ?>
<!DOCTYPE Xdmf SYSTEM "Xdmf.dtd" []>
<Xdmf Version="2.0">
<Information Name="TimeVaryingMetaData" Value="True"/>\n"""
)
fp.write("""<Domain>\n""")
fp.write("""<Grid Name="Mesh" GridType="Collection">\n""")
fp.write(f""" <Time Value="{fdata['time']}"/>\n""")
vars_without_b = [v for v in fdata["var_names"] if "bcc" not in v]
vars_only_b = [v for v in fdata["var_names"] if v not in vars_without_b]
nx1 = fdata["nx1_out_mb"]
nx2 = fdata["nx2_out_mb"]
nx3 = fdata["nx3_out_mb"]
nmb = fdata["n_mbs"]
for mb in range(nmb):
write_meshblock(
fp, mb, nx1, nx2, nx3, nmb, dumpname, vars_without_b, vars_only_b
)
fp.write("""</Grid>\n""")
fp.write("""</Domain>\n""")
fp.write("""</Xdmf>\n""")
fp.close()
def convert_file(binary_fname):
"""
Converts a single file.
args:
binary_filename - string
filename of bin file to convert
This will create new files "binary_data.bin" -> "binary_data.athdf" and
"binary_data.athdf.xdmf"
"""
athdf_fname = binary_fname.replace(".bin", "") + ".athdf"
xdmf_fname = athdf_fname + ".xdmf"
filedata = read_binary(binary_fname)
write_athdf(athdf_fname, filedata)
write_xdmf_for(xdmf_fname, os.path.basename(athdf_fname), filedata)
if __name__ == "__main__":
import sys
try:
from tqdm import tqdm
except ModuleNotFoundError:
def tqdm(L):
for x in L:
print(x)
yield x
if len(sys.argv) < 2:
print(f"Usage: {sys.argv[0]} output_file_1.bin [output_file_2.bin [...]]")
exit(1)
for binary_fname in tqdm(sys.argv[1:]):
convert_file(binary_fname)
|
IAS-AstrophysicsREPO_NAMEathenakPATH_START.@athenak_extracted@athenak-main@vis@python@bin_convert.py@.PATH_END.py
|
{
"filename": "workQueue_knl_config.py",
"repo_name": "LSSTDESC/gen3_workflow",
"repo_path": "gen3_workflow_extracted/gen3_workflow-master/python/desc/gen3_workflow/config/workQueue_knl_config.py",
"type": "Python"
}
|
"""Parsl config for WorkQueueExecutor using a SlurmProvider"""
import parsl
from parsl.executors import WorkQueueExecutor, ThreadPoolExecutor
from parsl.providers import SlurmProvider
from parsl.launchers import SrunLauncher
PROVIDER_OPTIONS = dict(nodes_per_block=2,
exclusive=True,
init_blocks=0,
min_blocks=0,
max_blocks=1,
parallelism=0,
launcher=SrunLauncher(
overrides='-K0 -k --slurmd-debug=verbose'),
cmd_timeout=300)
SCHEDULER_OPTIONS = ("#SBATCH --constraint=knl\n"
"#SBATCH --qos=regular\n"
"#SBATCH --module=cvmfs\n"
"#SBATCH -L cvmfs")
provider = SlurmProvider('None', walltime='10:00:00',
scheduler_options=SCHEDULER_OPTIONS,
**PROVIDER_OPTIONS)
executors = [WorkQueueExecutor(label='work_queue', port=9000, shared_fs=True,
provider=provider, autolabel=False),
ThreadPoolExecutor(max_threads=1, label='submit-node')]
config = parsl.config.Config(strategy='simple',
garbage_collect=False,
app_cache=True,
executors=executors,
retries=1)
DFK = parsl.load(config)
|
LSSTDESCREPO_NAMEgen3_workflowPATH_START.@gen3_workflow_extracted@gen3_workflow-master@python@desc@gen3_workflow@config@workQueue_knl_config.py@.PATH_END.py
|
{
"filename": "roperator.py",
"repo_name": "pandas-dev/pandas",
"repo_path": "pandas_extracted/pandas-main/pandas/core/roperator.py",
"type": "Python"
}
|
"""
Reversed Operations not available in the stdlib operator module.
Defining these instead of using lambdas allows us to reference them by name.
"""
from __future__ import annotations
import operator
def radd(left, right):
return right + left
def rsub(left, right):
return right - left
def rmul(left, right):
return right * left
def rdiv(left, right):
return right / left
def rtruediv(left, right):
return right / left
def rfloordiv(left, right):
return right // left
def rmod(left, right):
# check if right is a string as % is the string
# formatting operation; this is a TypeError
# otherwise perform the op
if isinstance(right, str):
typ = type(left).__name__
raise TypeError(f"{typ} cannot perform the operation mod")
return right % left
def rdivmod(left, right):
return divmod(right, left)
def rpow(left, right):
return right**left
def rand_(left, right):
return operator.and_(right, left)
def ror_(left, right):
return operator.or_(right, left)
def rxor(left, right):
return operator.xor(right, left)
|
pandas-devREPO_NAMEpandasPATH_START.@pandas_extracted@pandas-main@pandas@core@roperator.py@.PATH_END.py
|
{
"filename": "detection.py",
"repo_name": "vortex-exoplanet/VIP",
"repo_path": "VIP_extracted/VIP-master/vip_hci/metrics/detection.py",
"type": "Python"
}
|
#! /usr/bin/env python
"""
Module with detection algorithms.
"""
__author__ = 'Carlos Alberto Gomez Gonzalez, Valentin Christiaens'
__all__ = ['detection',
'mask_source_centers',
'mask_sources',
'peak_coordinates']
import numpy as np
import pandas as pn
from hciplot import plot_frames
from scipy.ndimage import correlate
from astropy.stats import (sigma_clipped_stats, gaussian_fwhm_to_sigma,
gaussian_sigma_to_fwhm)
from astropy.modeling import models, fitting
from skimage.feature import peak_local_max, blob_log, blob_dog
from ..var import (mask_circle, get_square, frame_center, fit_2dgaussian,
frame_filter_lowpass, dist_matrix)
from ..config.utils_conf import sep
from .snr_source import snr, snrmap, frame_report
def detection(array, fwhm=4, psf=None, mode='lpeaks', bkg_sigma=5,
matched_filter=False, mask=True, snr_thresh=5, nproc=1, plot=True,
debug=False, full_output=False, verbose=True, **kwargs):
"""Automatically find point-like sources in a 2d array.
The algorithm is designed for automatically finding planets in
post-processed high contrast final frames. Blob can be defined as a region
of an image in which some properties are constant or vary within a
prescribed range of values. See ``Notes`` below to read about the algorithm
details.
Parameters
----------
array : numpy ndarray, 2d
Input frame.
fwhm : None or int, optional
Size of the FWHM in pixels. If None and a ``psf`` is provided, then the
FWHM is measured on the PSF image.
psf : numpy ndarray
Input PSF template. It must be normalized with the
``vip_hci.metrics.normalize_psf`` function.
mode : {'lpeaks', 'log', 'dog', 'snrmap', 'snrmapf'}, optional
Sets with algorithm to use. Each algorithm yields different results. See
notes for the details of each method.
bkg_sigma : int or float, optional
The number standard deviations above the clipped median for setting the
background level. Used when ``mode`` is either 'lpeaks', 'dog' or 'log'.
matched_filter : bool, optional
Whether to correlate with the psf of not. Used when ``mode`` is either
'lpeaks', 'dog' or 'log'.
mask : bool, optional
If True the central region (circular aperture of 2*FWHM radius) of the
image will be masked out.
snr_thresh : float, optional
S/N threshold for deciding whether the blob is a detection or not. Used
to threshold the S/N map when ``mode`` is set to 'snrmap' or 'snrmapf'.
nproc : None or int, optional
The number of processes for running the ``snrmap`` function.
plot : bool, optional
If True plots the frame showing the detected blobs on top.
debug : bool, optional
Whether to print and plot additional/intermediate results.
full_output : bool, optional
Whether to output just the coordinates of blobs that fulfill the SNR
constraint or a table with all the blobs and the peak pixels and SNR.
verbose : bool, optional
Whether to print to stdout information about found blobs.
**kwargs : dictionary, optional
Arguments to be passed to ``plot_frames`` to customize the plot (and to
save it to disk).
Returns
-------
yy, xx : numpy ndarray
Two vectors with the y and x coordinates of the centers of the sources
(potential planets).
If full_output is True then a table with all the candidates that passed the
2d Gaussian fit constrains and the S/N threshold is returned.
Note
----
When ``mode`` is either 'lpeaks', 'dog' or 'log', the detection might happen
in the input frame or in a match-filtered version of it (by setting
``matched_filter`` to True and providing a PSF template, to run a
correlation filter). Filtering the image will smooth the noise and maximize
detectability of objects with a shape similar to the kernel. When ``mode``
is either 'snrmap' or 'snrmapf', the detection is done on an S/N map
directly.
When ``mode`` is set to:
'lpeaks' (Local maxima): The local peaks above the background (computed
using sigma clipped statistics) on the (correlated) frame are detected.
A maximum filter is used for finding local maxima. This operation
dilates the original image and merges neighboring local maxima closer
than the size of the dilation. Locations where the original image is
equal to the dilated image are returned as local maxima. The minimum
separation between the peaks is 1*FWHM.
'log' (Laplacian of Gaussian): It computes the Laplacian of Gaussian
images with successively increasing standard deviation and stacks them
up in a cube. Blobs are local maximas in this cube. LOG assumes that the
blobs are again assumed to be bright on dark.
'dog' (Difference of Gaussians): This is a faster approximation of the
Laplacian of Gaussian approach. In this case the image is blurred with
increasing standard deviations and the difference between two
successively blurred images are stacked up in a cube. DOG assumes that
the blobs are again assumed to be bright on dark.
'snrmap' or 'snrmapf': A threshold is applied to the S/N map, computed
with the ``snrmap`` function (``snrmapf`` calls ``snrmap`` with
``approximated`` set to True). The threshold is given by ``snr_thresh``
and local maxima are found as in the case of 'lpeaks'.
Finally, a 2d Gaussian fit is done on each of the potential blobs
constraining the position on a cropped sub-image and the sigma of the fit
(to match the input FWHM). Finally the blobs are filtered based on its S/N
value, according to ``snr_thresh``.
"""
def check_blobs(array, coords_temp, fwhm, debug):
y_temp = coords_temp[:, 0]
x_temp = coords_temp[:, 1]
coords = []
# Fitting a 2d gaussian to each local maxima position
for y, x in zip(y_temp, x_temp):
subsi = 3 * int(np.ceil(fwhm))
if subsi % 2 == 0:
subsi += 1
if mode in ('lpeaks', 'log', 'dog'):
scy = y + pad
scx = x + pad
elif mode in ('snrmap', 'snrmapf'):
scy = y
scx = x
subim, suby, subx = get_square(array, subsi, scy, scx,
position=True, force=True,
verbose=False)
cy, cx = frame_center(subim)
gauss = models.Gaussian2D(amplitude=subim.max(), x_mean=cx,
y_mean=cy, theta=0,
x_stddev=fwhm*gaussian_fwhm_to_sigma,
y_stddev=fwhm*gaussian_fwhm_to_sigma)
sy, sx = np.indices(subim.shape)
fitter = fitting.LevMarLSQFitter()
fit = fitter(gauss, sx, sy, subim)
# checking that the amplitude is positive > 0
# checking whether the x and y centroids of the 2d gaussian fit
# coincide with the center of the subimage (within 2px error)
# checking whether the mean of the fwhm in y and x of the fit
# are close to the FWHM_PSF with a margin of 3px
fwhm_y = fit.y_stddev.value * gaussian_sigma_to_fwhm
fwhm_x = fit.x_stddev.value * gaussian_sigma_to_fwhm
mean_fwhm_fit = np.mean([np.abs(fwhm_x), np.abs(fwhm_y)])
condyf = np.allclose(fit.y_mean.value, cy, atol=2)
condxf = np.allclose(fit.x_mean.value, cx, atol=2)
condmf = np.allclose(mean_fwhm_fit, fwhm, atol=3)
if fit.amplitude.value > 0 and condxf and condyf and condmf:
coords.append((suby + fit.y_mean.value,
subx + fit.x_mean.value))
if debug:
print('Coordinates (Y,X): {:.3f},{:.3f}'.format(y, x))
print('fit peak = {:.3f}'.format(fit.amplitude.value))
msg = 'fwhm_y in px = {:.3f}, fwhm_x in px = {:.3f}'
print(msg.format(fwhm_y, fwhm_x))
print('mean fit fwhm = {:.3f}'.format(mean_fwhm_fit))
if plot:
plot_frames(subim, colorbar=True, axis=False, dpi=60)
return coords
def print_coords(coords):
print('Blobs found:', len(coords))
print(' ycen xcen')
print('------ ------')
for j in range(len(coords[:, 0])):
print('{:.3f} \t {:.3f}'.format(coords[j, 0], coords[j, 1]))
def print_abort():
if verbose:
print(sep)
print('No potential sources found')
print(sep)
# --------------------------------------------------------------------------
if array.ndim != 2:
raise TypeError('Input array is not a frame or 2d array')
if psf is not None:
if psf.ndim != 2 and psf.shape[0] < array.shape[0]:
raise TypeError('Input psf is not a 2d array or has wrong size')
else:
if matched_filter:
raise ValueError('`psf` must be provided when `matched_filter` is '
'True')
if fwhm is None:
if psf is not None:
# Getting the FWHM from the PSF array
cenpsf = frame_center(psf)
outdf = fit_2dgaussian(psf, cent=(cenpsf), debug=debug,
full_output=True)
fwhm_x, fwhm_y = outdf['fwhm_x'], outdf['fwhm_y']
fwhm = np.mean([fwhm_x, fwhm_y])
if verbose:
print('FWHM = {:.2f} pxs\n'.format(fwhm))
if debug:
print('FWHM_y', fwhm_y)
print('FWHM_x', fwhm_x)
else:
raise ValueError('`fwhm` or `psf` must be provided')
# Masking the center, 2*lambda/D is the expected IWA
if mask:
array = mask_circle(array, radius=fwhm)
# Generating a detection map: Match-filtered frame or SNRmap
# For 'lpeaks', 'dog', 'log' it is possible to skip this step
if mode in ('lpeaks', 'log', 'dog'):
if matched_filter:
frame_det = correlate(array, psf)
else:
frame_det = array
if debug and plot and matched_filter:
print('Match-filtered frame:')
plot_frames(frame_det, colorbar=True)
# Estimation of background level
_, median, stddev = sigma_clipped_stats(frame_det, sigma=5,
maxiters=None)
bkg_level = median + (stddev * bkg_sigma)
if debug:
print('Sigma clipped median = {:.3f}'.format(median))
print('Sigma clipped stddev = {:.3f}'.format(stddev))
print('Background threshold = {:.3f}'.format(bkg_level), '\n')
elif mode in ('snrmap', 'snrmapf'):
if mode == 'snrmap':
approx = False
elif mode == 'snrmapf':
approx = True
frame_det = snrmap(array, fwhm=fwhm, approximated=approx, plot=False,
nproc=nproc, verbose=verbose)
if debug and plot:
print('Signal-to-noise ratio map:')
plot_frames(frame_det, colorbar=True)
if mode in ('lpeaks', 'log', 'dog'):
# Padding the image with zeros to avoid errors at the edges
pad = 10
array_padded = np.pad(array, pad, 'constant', constant_values=0)
else:
pad = 0
if mode in ('lpeaks', 'snrmap', 'snrmapf'):
if mode == 'lpeaks':
threshold = bkg_level
else:
threshold = snr_thresh
coords_temp = peak_local_max(frame_det, threshold_abs=threshold,
min_distance=int(np.ceil(fwhm)),
num_peaks=20)
if mode == 'lpeaks':
coords = check_blobs(array_padded, coords_temp, fwhm, debug)
else:
coords = check_blobs(array, coords_temp, fwhm, debug)
coords = np.array(coords)
if verbose and coords.shape[0] > 0:
print_coords(coords-pad)
elif mode == 'log':
sigma = fwhm * gaussian_fwhm_to_sigma
coords = blob_log(frame_det.astype('float'),
threshold=bkg_level, min_sigma=sigma-.5,
max_sigma=sigma+.5)
if len(coords) == 0:
print_abort()
return 0, 0
coords = coords[:, :2]
coords = check_blobs(array_padded, coords, fwhm, debug)
coords = np.array(coords)
if coords.shape[0] > 0 and verbose:
print_coords(coords-pad)
elif mode == 'dog':
sigma = fwhm * gaussian_fwhm_to_sigma
coords = blob_dog(frame_det.astype('float'),
threshold=bkg_level, min_sigma=sigma-.5,
max_sigma=sigma+.5)
if len(coords) == 0:
print_abort()
return 0, 0
coords = coords[:, :2]
coords = check_blobs(array_padded, coords, fwhm, debug)
coords = np.array(coords)
if coords.shape[0] > 0 and verbose:
print_coords(coords-pad)
else:
raise ValueError('`mode` not recognized')
if coords.shape[0] == 0:
print_abort()
return 0, 0
yy = coords[:, 0]
xx = coords[:, 1]
yy_final = []
xx_final = []
yy_out = []
xx_out = []
snr_list = []
snr_final = []
if mode in ('lpeaks', 'log', 'dog'):
xx -= pad
yy -= pad
# Checking S/N for potential sources
for i in range(yy.shape[0]):
y = yy[i]
x = xx[i]
if verbose:
print('')
print(sep)
print('X,Y = ({:.1f},{:.1f})'.format(x, y))
snr_value = snr(array, (x, y), fwhm, False, verbose=False)
snr_list.append(snr_value)
if snr_value >= snr_thresh:
if verbose:
_ = frame_report(array, fwhm, (x, y), verbose=verbose)
yy_final.append(y)
xx_final.append(x)
snr_final.append(snr_value)
else:
yy_out.append(y)
xx_out.append(x)
if verbose:
msg = 'S/N constraint NOT fulfilled (S/N = {:.3f})'
print(msg.format(snr_value))
if debug:
_ = frame_report(array, fwhm, (x, y), verbose=verbose)
if verbose:
print(sep)
if debug:
table_full = pn.DataFrame({'y': yy.tolist(),
'x': xx.tolist(),
'px_snr': snr_list})
table_full.sort_values('px_snr')
print(table_full)
yy_final = np.array(yy_final)
xx_final = np.array(xx_final)
yy_out = np.array(yy_out)
xx_out = np.array(xx_out)
table = pn.DataFrame(
{'y': yy_final.tolist(), 'x': xx_final.tolist(), 'px_snr': snr_final})
if plot:
coords = tuple(zip(xx_out.tolist() + xx_final.tolist(),
yy_out.tolist() + yy_final.tolist()))
circlealpha = [0.3] * len(xx_out)
circlealpha += [1] * len(xx_final)
plot_frames(array, dpi=120, circle=coords, circle_alpha=circlealpha,
circle_label=True, circle_radius=fwhm, **kwargs)
if full_output:
return table
else:
return yy_final, xx_final
def peak_coordinates(obj_tmp, fwhm, approx_peak=None, search_box=None,
channels_peak=False):
"""Find the pixel coordinates of maximum in either a frame or a cube,
after convolution with gaussian. It first applies a gaussian filter, to
lower the probability of returning a hot pixel (although it may still
happen with clumps of hot pixels, hence parameter "approx_peak").
Parameters
----------
obj_tmp : cube_like or frame_like
Input 3d cube or image.
fwhm : float_like or 1d array
Input full width half maximum value of the PSF in pixels. This will be
used as the standard deviation for Gaussian kernel of the Gaussian
filtering. Can be a 1d array if obj_tmp is a 3D cube.
approx_peak: 2 components list or array, opt
Gives the approximate yx coordinates of the peak.
search_box: float or 2 components list or array, opt
Gives the half-size in pixels of a box in which the peak is searched,
around approx_peak. If float, it is assumed the same box size is wanted
in both y and x. Note that this parameter should be provided if
approx_peak is provided.
channels_peak: bool, {False, True}, opt
Whether returns the indices of the peak in each channel in addition to
the global indices of the peak in the cube. If True, it would hence
return two arrays. Note: only available if the input is a 3d cube.
Returns
-------
(zz_max,) yy_max, xx_max : integers
Indices of peak in either 3D or 2D array
ind_ch_max: 2d array
Coordinates of the peak in each channel
"""
ndims = len(obj_tmp.shape)
assert ndims == 2 or ndims == 3, "Array is not two or three dimensional"
if approx_peak is not None:
assert len(approx_peak) == 2, "Approx peak is not two dimensional"
if isinstance(search_box, float) or isinstance(search_box, int):
sbox_y = search_box
sbox_x = search_box
elif len(search_box) == 2:
sbox_y = search_box[0]
sbox_x = search_box[1]
else:
msg = "The search box does not have the right number of elements"
raise ValueError(msg)
if ndims == 3:
n_z = obj_tmp.shape[0]
sbox = np.zeros([n_z, 2*sbox_y+1, 2*sbox_x+1])
if ndims == 2:
med_filt_tmp = frame_filter_lowpass(obj_tmp, 'median',
median_size=int(fwhm))
if approx_peak is None:
ind_max = np.unravel_index(np.nanargmax(med_filt_tmp),
med_filt_tmp.shape)
else:
sbox = med_filt_tmp[approx_peak[0]-sbox_y:approx_peak[0]+sbox_y+1,
approx_peak[1]-sbox_x:approx_peak[1]+sbox_x+1]
ind_max_sbox = np.unravel_index(np.nanargmax(sbox), sbox.shape)
ind_max = (approx_peak[0]-sbox_y+ind_max_sbox[0],
approx_peak[1]-sbox_x+ind_max_sbox[1])
return ind_max
if ndims == 3:
n_z = obj_tmp.shape[0]
med_filt_tmp = np.zeros_like(obj_tmp)
ind_ch_max = np.zeros([n_z, 2])
if isinstance(fwhm, float) or isinstance(fwhm, int):
fwhm = [fwhm]*n_z
for zz in range(n_z):
med_filt_tmp[zz] = frame_filter_lowpass(obj_tmp[zz], 'median',
median_size=int(fwhm[zz]))
if approx_peak is None:
ind_ch_max[zz] = np.unravel_index(np.nanargmax(med_filt_tmp[zz]),
med_filt_tmp[zz].shape)
else:
sbox[zz] = med_filt_tmp[zz, approx_peak[0]-sbox_y:
approx_peak[0]+sbox_y+1,
approx_peak[1]-sbox_x:
approx_peak[1]+sbox_x+1]
ind_max_sbox = np.unravel_index(np.nanargmax(sbox[zz]),
sbox[zz].shape)
ind_ch_max[zz] = (approx_peak[0]-sbox_y+ind_max_sbox[0],
approx_peak[1]-sbox_x+ind_max_sbox[1])
if approx_peak is None:
ind_max = np.unravel_index(np.nanargmax(med_filt_tmp),
med_filt_tmp.shape)
else:
ind_max_tmp = np.unravel_index(np.nanargmax(sbox),
sbox.shape)
ind_max = (ind_max_tmp[0]+approx_peak[0]-sbox_y,
ind_max_tmp[1]+approx_peak[1]-sbox_x)
if channels_peak:
return ind_max, ind_ch_max
else:
return ind_max
def mask_source_centers(array, fwhm, y=None, x=None):
""" Creates a mask of ones with the size of the input frame and zeros at
the center of the sources (planets) with coordinates x, y.
If y and x are not provided, the sources will be found automatically using
'detection()' ('log' mode).
Parameters
----------
array : numpy ndarray
Input frame.
fwhm : float
Size in pixels of the FWHM.
y, x : tuples of int (optional)
Coordinates of the center of the sources.
Returns
-------
mask : numpy ndarray
Mask frame.
"""
if array.ndim != 2:
raise TypeError('Wrong input array shape.')
frame = array.copy()
if y is None or x is None:
frame = mask_circle(frame, radius=2*fwhm)
yy, xx = detection(frame, fwhm, plot=False, mode='log')
else:
yy = np.array(y)
xx = np.array(x)
mask = np.ones_like(array)
# center sources become zeros
mask[yy.astype('int'), xx.astype('int')] = 0
return mask
def mask_sources(mask, ap_rad):
""" Given an input mask with zeros only at the *center* of source locations
(ones elsewhere), returns a mask with zeros within a radius ap_rad of all
sources.
Parameters
----------
mask : numpy ndarray
Input mask with zeros at sources center. Mask has to be square.
ap_rad : float
Size in pixels of the apertures that should be filled with zeros
around each source in the mask.
Returns
-------
mask_out : numpy ndarray
Output mask frame.
"""
if mask.ndim != 2:
raise TypeError('Wrong input array shape.')
mask[np.where(mask > 1)] = 1
ny, nx = mask.shape
n_s = int(ny*nx - np.sum(mask))
mask_out = np.ones([ny, nx])
if n_s == 0:
return mask_out
else:
s_coords = np.where(mask == 0)
for s in range(n_s):
rad_arr = dist_matrix(ny, cx=s_coords[1][s], cy=s_coords[0][s])
mask_out[np.where(rad_arr < ap_rad)] = 0
return mask_out
|
vortex-exoplanetREPO_NAMEVIPPATH_START.@VIP_extracted@VIP-master@vip_hci@metrics@detection.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "pmelchior/skymapper",
"repo_path": "skymapper_extracted/skymapper-main/skymapper/survey/__init__.py",
"type": "Python"
}
|
import os, numpy as np
from .. import register_survey, with_metaclass, with_metaclass
class BaseSurvey(object):
def contains(self, ra, dec):
"""Whether ra, dec are inside the survey footprint"""
if not hasattr(ra, '__iter__'):
ra = (ra,)
return np.zeros(len(ra), dtype='bool')
# [blatant copy from six to avoid dependency]
# python 2 and 3 compatible metaclasses
# see http://python-future.org/compatible_idioms.html#metaclasses
class Meta(type):
def __new__(meta, name, bases, class_dict):
cls = type.__new__(meta, name, bases, class_dict)
# remove those that are directly derived from BaseProjection
if BaseSurvey not in bases:
register_survey(cls)
return cls
class Survey(with_metaclass(Meta, BaseSurvey)):
pass
try:
import pymangle
class MangleSurvey(pymangle.Mangle, Survey):
def __init__(self, filename, verbose=False):
pymangle.Mangle.__init__(self, filename, verbose=verbose)
class DES(MangleSurvey):
def __init__(self):
# get survey polygon data
this_dir, this_filename = os.path.split(__file__)
MangleSurvey.__init__(self, os.path.join(this_dir, "des-round17-poly_tidy.ply"))
class BOSS(MangleSurvey):
def __init__(self):
# get survey polygon data
this_dir, this_filename = os.path.split(__file__)
MangleSurvey.__init__(self, os.path.join(this_dir, "boss_survey.ply"))
except ImportError:
print("skymapper: survey definitions missing because pymangle is not installed")
|
pmelchiorREPO_NAMEskymapperPATH_START.@skymapper_extracted@skymapper-main@skymapper@survey@__init__.py@.PATH_END.py
|
{
"filename": "test_regression.py",
"repo_name": "waynebhayes/SpArcFiRe",
"repo_path": "SpArcFiRe_extracted/SpArcFiRe-master/scripts/SpArcFiRe-pyvenv/lib/python2.7/site-packages/scipy/optimize/tests/test_regression.py",
"type": "Python"
}
|
"""Regression tests for optimize.
"""
from __future__ import division, print_function, absolute_import
import numpy as np
from numpy.testing import assert_almost_equal
from pytest import raises as assert_raises
import scipy.optimize
class TestRegression(object):
def test_newton_x0_is_0(self):
# Regression test for gh-1601
tgt = 1
res = scipy.optimize.newton(lambda x: x - 1, 0)
assert_almost_equal(res, tgt)
def test_newton_integers(self):
# Regression test for gh-1741
root = scipy.optimize.newton(lambda x: x**2 - 1, x0=2,
fprime=lambda x: 2*x)
assert_almost_equal(root, 1.0)
def test_lmdif_errmsg(self):
# This shouldn't cause a crash on Python 3
class SomeError(Exception):
pass
counter = [0]
def func(x):
counter[0] += 1
if counter[0] < 3:
return x**2 - np.array([9, 10, 11])
else:
raise SomeError()
assert_raises(SomeError,
scipy.optimize.leastsq,
func, [1, 2, 3])
|
waynebhayesREPO_NAMESpArcFiRePATH_START.@SpArcFiRe_extracted@SpArcFiRe-master@scripts@SpArcFiRe-pyvenv@lib@python2.7@site-packages@scipy@optimize@tests@test_regression.py@.PATH_END.py
|
{
"filename": "sfr_forensics.py",
"repo_name": "ICRAR/shark",
"repo_path": "shark_extracted/shark-master/standard_plots/sfr_forensics.py",
"type": "Python"
}
|
#
# ICRAR - International Centre for Radio Astronomy Research
# (c) UWA - The University of Western Australia, 2018
# Copyright by UWA (in the framework of the ICRAR)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
#
"""Size plots"""
import functools
import numpy as np
import common
import utilities_statistics as us
##################################
#Constants
RExp = 1.67
MpcToKpc = 1e3
G = 4.299e-9 #Gravity constant in units of (km/s)^2 * Mpc/Msun
mlow = 6.5
mupp = 12.5
dm = 0.2
mbins = np.arange(mlow,mupp,dm)
xmf = mbins + dm/2.0
dmobs = 0.4
mbins_obs = np.arange(mlow,mupp,dmobs)
xmf_obs = mbins_obs + dmobs/2.0
vlow = 1.0
vupp = 3.0
dv = 0.1
vbins = np.arange(vlow,vupp,dv)
xv = vbins + dv/2.0
btbins = [0, 0.05, 0.95, 1]
btlow = 0.0
btupp = 1.0
dbt = 0.05
btbins2 = np.arange(btlow,btupp,dbt)
xbt = btbins2 + dbt/2.0
binsm = [8.5, 9.5, 10.5, 12.5]
recycle = 0.4588
def prepare_data(hdf5_data, sfh, hdf5_data_hist, LBT, delta_t):
(h0, volh, _, mstar, sfrdisk, sfrburst) = hdf5_data_hist
(h0, volh, mdisk, mbulge) = hdf5_data
(bulge_diskins_hist, bulge_mergers_hist, disk_hist) = sfh
vol_sim = volh / h0**3
print(sum(mdisk)/ sum(mdisk + mbulge))
ms_true = mstar / h0 / (volh / h0**3.0)
sfrall = (sfrdisk + sfrburst)/h0/ 1e9/(volh / h0**3.0)
mstars_tot = (mdisk+mbulge)/h0
bt = mbulge / (mdisk+mbulge)
ind = np.where(mstars_tot > 0)
mstars = np.log10(mstars_tot[ind])
sfhs_masses = np.zeros(shape= (len(LBT), len(mbins)))
sfhs_comp = np.zeros(shape= (len(LBT), 3))
sfr_tot = np.zeros(shape= (len(LBT)))
mshs_masses = np.zeros(shape= (len(LBT), len(mbins)))
mshs_comp = np.zeros(shape= (len(LBT), 3))
mshs_masses_cum = np.zeros(shape= (len(LBT), len(mbins)))
ms_tot = np.zeros(shape= (len(LBT)))
ms_tot_bycomp = np.zeros(shape= (len(LBT), 3))
ms_tot_bycomp_massivegals = np.zeros(shape= (len(LBT), 3))
for i in range(0,len(binsm)):
if ( i == 0 ):
ind = np.where((mstars <= binsm[i]) & (mstars >= 7))
else:
ind = np.where((mstars <= binsm[i]) & (mstars > binsm[i-1]))
for j in range(0,len(LBT)):
sfhs_masses[j,i] = np.sum(disk_hist[ind,j] + bulge_mergers_hist[ind,j] + bulge_diskins_hist[ind,j]) / h0/ (volh / h0**3.0)
mshs_masses[j,i] = np.sum(disk_hist[ind,j] + bulge_mergers_hist[ind,j] + bulge_diskins_hist[ind,j]) * delta_t[j] * 1e9 / h0 * (1.0 - recycle)
for j in range(0,len(LBT)):
sfr_tot[j] = np.sum(disk_hist[:,j] + bulge_mergers_hist[:,j] + bulge_diskins_hist[:,j]) / h0/ (volh / h0**3.0)
for i in range(0,len(binsm)):
mshs_masses_cum[j,i] = np.sum(mshs_masses[0:j,i]) / (volh / h0**3.0)
sfhs_comp[j,0] = np.sum(disk_hist[:,j]) / h0/ (volh / h0**3.0)
sfhs_comp[j,1] = np.sum(bulge_mergers_hist[:,j]) / h0/ (volh / h0**3.0)
sfhs_comp[j,2] = np.sum(bulge_diskins_hist[:,j]) / h0/ (volh / h0**3.0)
if j == 0:
mshs_comp[j,0] = np.sum(disk_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle)
mshs_comp[j,1] = np.sum(bulge_mergers_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle)
mshs_comp[j,2] = np.sum(bulge_diskins_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle)
else:
mshs_comp[j,0] = np.sum(disk_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle) + mshs_comp[j-1,0]
mshs_comp[j,1] = np.sum(bulge_mergers_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle) + mshs_comp[j-1,1]
mshs_comp[j,2] = np.sum(bulge_diskins_hist[:,j]) / h0/ (volh / h0**3.0) * 1e9 * delta_t[j] * (1.0 - recycle) + mshs_comp[j-1,2]
ms_tot[j] = np.sum(mshs_masses_cum[j,:])
ms_tot_bycomp[j,0] = np.sum(disk_hist[:,j]) / np.sum(disk_hist[:,j] + bulge_mergers_hist[:,j] + bulge_diskins_hist[:,j])
ms_tot_bycomp[j,1] = np.sum(bulge_mergers_hist[:,j]) / np.sum(disk_hist[:,j] + bulge_mergers_hist[:,j] + bulge_diskins_hist[:,j])
ms_tot_bycomp[j,2] = np.sum(bulge_diskins_hist[:,j]) / np.sum(disk_hist[:,j] + bulge_mergers_hist[:,j] + bulge_diskins_hist[:,j])
ind = np.where(mstars >= 9)
ms_tot_bycomp_massivegals[j,0] = np.sum(disk_hist[ind,j]) / np.sum(disk_hist[ind,j] + bulge_mergers_hist[ind,j] + bulge_diskins_hist[ind,j])
ms_tot_bycomp_massivegals[j,1] = np.sum(bulge_mergers_hist[ind,j]) / np.sum(disk_hist[ind,j] + bulge_mergers_hist[ind,j] + bulge_diskins_hist[ind,j])
ms_tot_bycomp_massivegals[j,2] = np.sum(bulge_diskins_hist[ind,j]) / np.sum(disk_hist[ind,j] + bulge_mergers_hist[ind,j] + bulge_diskins_hist[ind,j])
return (sfhs_masses, sfr_tot, sfrall, mshs_masses_cum, ms_tot, ms_tot_bycomp, ms_true, ms_tot_bycomp_massivegals, sfhs_comp, mshs_comp)
def plot_cosmic_sfr(plt, outdir, obsdir, sfhs_masses, sfr_tot, sfr_true, mshs_masses, ms_tot, ms_true, LBT, h0):
#load observations
#Baldry (Chabrier IMF), ['Baldry+2012, z<0.06']
redK11, SFRK11, err_upK11, err_dnK11 = common.load_observation(obsdir, 'Global/SFRD_Karim11.dat', [0,1,2,3])
hobs = 0.7
xobs = redK11
yobs = xobs*0. - 999.
indx = np.where( SFRK11 > 0)
yobs[indx] = np.log10(SFRK11[indx] * pow(hobs/h0, 2.0))
lerr = yobs*0. - 999.
indx = np.where( (SFRK11-err_dnK11) > 0)
lerr[indx] = np.log10(SFRK11[indx] - err_dnK11[indx])
herr = yobs*0. + 999.
indx = np.where( (SFRK11+err_upK11) > 0)
herr[indx] = np.log10(SFRK11[indx] + err_upK11[indx])
#Driver (Chabrier IMF), ['Baldry+2012, z<0.06']
redD17d, redD17u, sfrD17, err1, err2, err3, err4 = common.load_observation(obsdir, 'Global/Driver18_sfr.dat', [0,1,2,3,4,5,6])
hobs = 0.7
xobsD17 = (redD17d+redD17u)/2.0
yobsD17 = sfrD17 + np.log10(hobs/h0)
errD17 = yobs*0. - 999.
errD17 = np.sqrt(pow(err1,2.0)+pow(err2,2.0)+pow(err3,2.0)+pow(err4,2.0))
fig = plt.figure(figsize=(5,4.5))
ytit = "$\\rm log_{10} (\\rm \\rho_{\\rm SFR}/ M_{\\odot} yr^{-1} cMpc^{-3})$"
xtit = "lookback time/Gyr"
xmin, xmax, ymin, ymax = 0, 13, -4, 0
xleg = xmax - 0.2 * (xmax - xmin)
yleg = ymax - 0.1 * (ymax - ymin)
ax = fig.add_subplot(111)
common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1))
#Predicted relation
cols = ['Khaki','MediumSeaGreen','Turquoise', 'MediumBlue']
labels = ['$log(M_{\\star})<8.5$', '$8.5<log(M_{\\star})<9.5$','$9.5<log(M_{\\star})<10.5$','$log(M_{\\star})>10.5$']
for i in range(0,len(cols)):
ax.plot(LBT, np.log10(sfhs_masses[:,i]), linestyle='solid',color=cols[i], label=labels[i])
print("Will print Cosmic SFR history")
for a,b,c,d,e,f in zip(LBT, sfr_true[:], sfhs_masses[:,0], sfhs_masses[:,1], sfhs_masses[:,2], sfhs_masses[:,3]):
print(a,b,c,d,e,f)
ax.plot(LBT, np.log10(sfr_tot[:]), linestyle='solid', color='k')
ax.plot(LBT, np.log10(sfr_true[:]), linestyle='dashed', color='k')
ax.errorbar(us.look_back_time(xobs[0:8]), yobs[0:8], yerr=[yobs[0:8]-lerr[0:8],herr[0:8]-yobs[0:8]], ls='None', mfc='None', ecolor = 'grey', mec='grey',marker='D')
ax.errorbar(us.look_back_time(xobs[9:17]), yobs[9:17], yerr=[yobs[9:17]-lerr[9:17],herr[9:17]-yobs[9:17]], ls='None', mfc='None', ecolor = 'grey', mec='grey',marker='x')
ax.errorbar(us.look_back_time(xobsD17), yobsD17, yerr=[errD17,errD17], ls='None', mfc='None', ecolor = 'grey', mec='grey',marker='o')
common.prepare_legend(ax, cols, loc=2)
common.savefig(outdir, fig, 'cosmic_sfr_forensics.pdf')
redD17d, redD17u, smdD17, err1, err2, err3, err4 = common.load_observation(obsdir, 'Global/Driver18_smd.dat', [1,2,3,4,5,6,7])
hobs = 0.7
xobs = (redD17d+redD17u)/2.0
yobs = smdD17 + np.log10(hobs/h0)
err = yobs*0. - 999.
err = np.sqrt(pow(err1,2.0)+pow(err2,2.0)+pow(err3,2.0)+pow(err4,2.0))
fig = plt.figure(figsize=(5,4.5))
ytit = "$\\rm log_{10} (\\rm \\rho_{\\star}/ M_{\\odot} cMpc^{-3})$"
xtit = "lookback time/Gyr"
xmin, xmax, ymin, ymax = 0, 13, 4, 9
xleg = xmax - 0.2 * (xmax - xmin)
yleg = ymax - 0.1 * (ymax - ymin)
ax = fig.add_subplot(111)
common.prepare_ax(ax, xmin, xmax, ymin, ymax, xtit, ytit, locators=(0.1, 1, 0.1, 1))
#Predicted relation
for i in range(0,len(cols)):
ax.plot(LBT, np.log10(mshs_masses[:,i]), linestyle='solid',color=cols[i], label=labels[i])
ax.plot(LBT, np.log10(ms_tot[:]), linestyle='solid', color='k')
ax.plot(LBT, np.log10(ms_true[:]), linestyle='dashed', color='k')
ax.errorbar(us.look_back_time(xobs), yobs, yerr=[err,err], ls='None', mfc='None', ecolor = 'grey', mec='grey',marker='o')
print("Will print Cosmic SMD history")
for a,b,c,d,e,f in zip(LBT, ms_tot[:], mshs_masses[:,0], mshs_masses[:,1], mshs_masses[:,2], mshs_masses[:,3]):
print(a,b,c,d,e,f)
common.prepare_legend(ax, cols, loc=3)
common.savefig(outdir, fig, 'cosmic_smd_forensics.pdf')
def main(modeldir, outdir, redshift_table, subvols, obsdir):
plt = common.load_matplotlib()
fields = {'galaxies': ('mstars_disk', 'mstars_bulge')}
zlist = [0]
sfh_fields = {'bulges_diskins': ('star_formation_rate_histories'),
'bulges_mergers': ('star_formation_rate_histories'),
'disks': ('star_formation_rate_histories')}
fields_global = {'global': ('redshifts', 'mstars', 'sfr_quiescent', 'sfr_burst')}
# Read data from each subvolume at a time and add it up
# rather than appending it all together
for idx, subvol in enumerate(subvols):
subvol_data = common.read_data(modeldir, redshift_table[0], fields_global, [subvol])
if idx == 0:
hdf5_data_hist = subvol_data
else:
for subvol_datum, hdf5_datum in zip(subvol_data[3:], hdf5_data_hist[3:]):
hdf5_datum += subvol_datum
#select the most massive black hole from the last list item
# Also make sure that the total volume takes into account the number of subvolumes read
hdf5_data_hist[1] = hdf5_data_hist[1] * len(subvols)
h0, redshifts = hdf5_data_hist[0], hdf5_data_hist[2]
hdf5_data = common.read_data(modeldir, 199, fields, subvols)
sfh, delta_t, LBT = common.read_sfh(modeldir, 199, sfh_fields, subvols)
(sfhs_masses, sfr_tot, sfr_true, mshs_masses, ms_tot, ms_tot_bycomp, ms_true, ms_tot_bycomp_massivegals, sfhs_comp, mshs_comp) = prepare_data(hdf5_data, sfh, hdf5_data_hist, LBT, delta_t)
print("#SFRD Forensics")
print("#LBT/Gyr SFRD_disk[Msun/yr/Mpc^3] SFRD_bulge_mergers[Msun/yr/Mpc^3] SFRD_bulge_diskins[Msun/yr/Mpc^3]")
for a,b,c,d in zip(LBT, sfhs_comp[:,0], sfhs_comp[:,1], sfhs_comp[:,2]):
print(a,b,c,d)
print("#SMD Forensics")
print("#LBT/Gyr SMD_disk[Msun/Mpc^3] SMD_bulge_mergers[Msun/Mpc^3] SMD_bulge_diskins[Msun/Mpc^3]")
for a,b,c,d in zip(LBT, mshs_comp[:,0], mshs_comp[:,1], mshs_comp[:,2]):
print(a,b,c,d)
plot_cosmic_sfr(plt, outdir, obsdir, sfhs_masses, sfr_tot, sfr_true, mshs_masses, ms_tot, ms_true, LBT, h0)
if __name__ == '__main__':
main(*common.parse_args())
|
ICRARREPO_NAMEsharkPATH_START.@shark_extracted@shark-master@standard_plots@sfr_forensics.py@.PATH_END.py
|
{
"filename": "Line_analysis.py",
"repo_name": "madamow/pyEW",
"repo_path": "pyEW_extracted/pyEW-master/pyew/lib/Line_analysis.py",
"type": "Python"
}
|
import numpy as np
from Gauss_Voigt import *
from IO_functions import *
def pm_width(x, x01, s1, w_factor): # s1 is fwhm
iu = np.abs(x - x01 - w_factor * np.abs(s1)).argmin()
il = np.abs(x - x01 + w_factor * np.abs(s1)).argmin()
if iu == il or np.abs(iu - il) < 3.:
il = 0
iu = len(x)
return il, iu
def find_eqws(line, spec, strong_lines, cfile, logfile):
results = {}
# Fit multiple gaussian profile
params, mg_errs = fit_multi_gauss(spec[:, 0], spec[:, 1], strong_lines,
cfile.getfloat('Lines', 'det_level'))
if params.shape[0] == 0:
print('Line ', line, 'was not detected')
params = np.array([[-9.9, -9.9, -9.9]])
mgaus = multiple_gaus(spec[:, 0], params)
ip = np.abs(params[:, 0] - line).argmin()
x01, a1, s1 = params[ip, :]
eqw = get_gew(a1, s1)
eqw_err = eqw * (mg_errs[ip, 0] / a1 + mg_errs[ip, 2] / s1)
# Determine region close to gaussian line center#
il, iu = pm_width(spec[:, 0], x01, s1, cfile.getfloat('Lines', 'w_factor'))
oc_mg = np.std(np.abs(spec[il:iu, 1] - 1.0 + mgaus[il:iu]))
results['mg'] = mgaus, params, eqw, eqw_err, oc_mg
# Fit single Gauss
eqw_gf, eqw_gf_err, gparams = fit_single_gauss(spec[il:iu, 0], spec[il:iu, 1], a1, x01, s1)
gausf = gaus(spec[:, 0], gparams[0], gparams[1], gparams[2])
oc_g = np.std(np.abs(spec[il:iu, 1] - 1.0 + gausf[il:iu]))
results['g'] = gausf, gparams, eqw_gf, eqw_gf_err, oc_g
# If mg_ew > v_lvl, fit Voigt
if np.log10(0.001 * eqw / line) > cfile.getfloat('Lines', 'v_lvl'):
try:
I, v_errs, vpar = fit_Voigt(spec[il:iu, 0], spec[il:iu, 1], x01)
svoigt = Voigt(spec[:, 0], vpar[0], vpar[1], vpar[2], vpar[3], 0., 0.)
oc_v = np.std(np.abs(spec[il:iu, 1] - 1.0 + svoigt[il:iu]))
results['v'] = svoigt, vpar, I, v_errs, oc_v
except:
print_and_log(logfile, ["Not enough points to fit a reliable Voigt profile"])
return results
def evaluate_results(line, rslt, cfile, logfile):
print_line_info(rslt, logfile)
if rslt['mg'][3] > 0.5 * rslt['mg'][2]:
print_and_log(logfile, ['Huge error!', rslt['mg'][2], rslt['mg'][3]])
best_fit = 'mg'
for fit in rslt:
if rslt[fit][4] < rslt[best_fit][4]:
best_fit = fit
print_and_log(logfile, [best_info(best_fit)])
if best_fit == 'v':
v_fwhm = voigt_fwhm(rslt['v'][1][1], rslt['v'][1][2])
out = [line, rslt['v'][1][2], v_fwhm, rslt['v'][2], rslt['v'][3]]
elif best_fit == 'g':
out = [line, rslt['g'][1][1], rslt['g'][1][2], rslt['g'][2], rslt['g'][3]]
else:
out1 = rslt['mg'][1][np.abs(rslt['mg'][1][:, 0] - line).argmin()]
out = [line, out1[0], np.abs(out1[2]), rslt['mg'][2], rslt['mg'][3]]
if out[3] > cfile.getfloat('Lines', 'h_eqw') or out[3] < cfile.getfloat('Lines', 'l_eqw'):
print_and_log(logfile, ['Line is too strong or too weak'])
out[2] = -99.9
out[3] = -99.9
out[4] = 99.9
if np.abs(line - out[1]) > cfile.getfloat('Lines', 'det_level'):
print_and_log(logfile, [line, 'line outside the det_level range'])
out[2] = -99.9
out[3] = -99.9
out[4] = 99.9
return out
# EW analysis
def EW_analysis(line, spec, strong_lines, cfile, logfile):
# do all fits: multi gauss, sgauss (part of multi gauss),
# gauss fitted in small area, voigt fitted in small area
r_tab = find_eqws(line, spec, strong_lines, cfile, logfile) # results tab
print_mgauss_data(r_tab, logfile)
# Check if EW is reasonable
lr = evaluate_results(line, r_tab, cfile, logfile)
return r_tab, lr
|
madamowREPO_NAMEpyEWPATH_START.@pyEW_extracted@pyEW-master@pyew@lib@Line_analysis.py@.PATH_END.py
|
{
"filename": "base_slicer.py",
"repo_name": "lsst/rubin_sim",
"repo_path": "rubin_sim_extracted/rubin_sim-main/rubin_sim/maf/slicers/base_slicer.py",
"type": "Python"
}
|
# Base class for all 'Slicer' objects.
#
__all__ = ("SlicerRegistry", "BaseSlicer")
import inspect
import json
import warnings
from io import StringIO
import numpy as np
import numpy.ma as ma
from rubin_sim.maf.utils import get_date_version
class SlicerRegistry(type):
"""
Meta class for slicers, to build a registry of slicer classes.
"""
def __init__(cls, name, bases, dict):
super(SlicerRegistry, cls).__init__(name, bases, dict)
if not hasattr(cls, "registry"):
cls.registry = {}
modname = inspect.getmodule(cls).__name__ + "."
if modname.startswith("rubin_sim.maf.slicers"):
modname = ""
slicername = modname + name
if slicername in cls.registry:
raise Exception("Redefining metric %s! (there are >1 slicers with the same name)" % (slicername))
if slicername not in ["BaseSlicer", "BaseSpatialSlicer"]:
cls.registry[slicername] = cls
def get_class(cls, slicername):
return cls.registry[slicername]
def help(cls, doc=False):
for slicername in sorted(cls.registry):
if not doc:
print(slicername)
if doc:
print("---- ", slicername, " ----")
print(inspect.getdoc(cls.registry[slicername]))
class BaseSlicer(metaclass=SlicerRegistry):
"""
Base class for all slicers: sets required methods and
implements common functionality.
After first construction, the slicer should be ready for
`setup_slicer` which defines slice_points, allowing the slicer to "slice"
data and generate plots.
After init after a restore: everything necessary for using slicer for
plotting or saving/restoring metric data should be present, although
the slicer does not need to be able to slice data again and generally
will not be able to do so.
Parameters
----------
verbose: `bool`, optional
True/False flag to send extra output to screen.
badval: `int` or `float`, optional
The value the Slicer uses to fill masked metric data values
"""
def __init__(self, verbose=False, badval=-666):
self.verbose = verbose
self.badval = badval
# Set the cache_size.
# Currently only healpixSlicers (and their derivatives) use the cache.
# The size of the cache is set directly by those slicers.
self.cache_size = 0
# Set length of Slicer. This determines the endpoint for iteration.
self.nslice = None
# Set the length of the data (metric) values.
# This is often but not necessarily the same as nslice.
self.shape = None
self.slice_points = {}
self.slicer_name = self.__class__.__name__
self.columns_needed = []
# Create a dict that saves how to re-init the slicer.
# This may not be the whole set of args/kwargs, may only be
# those which carry useful metadata or are necesary for init.
self.slicer_init = {"badval": badval}
self.plot_funcs = []
def _run_maps(self, maps):
"""Add map metadata to slice_points."""
if maps is not None:
for m in maps:
self.slice_points = m.run(self.slice_points)
def setup_slicer(self, sim_data, maps=None):
"""Set up Slicer for data slicing.
Set up internal parameters necessary for slicer to slice data
and generates indexes on sim_data.
Also sets _slice_sim_data for a particular slicer.
Parameters
-----------
sim_data : `np.recarray`
The simulated data to be sliced.
maps : `list` of `rubin_sim.maf.maps` objects, optional.
Maps to apply at each slice_point,
to add to the slice_point metadata.
"""
raise NotImplementedError()
def get_slice_points(self):
"""Return the slice_point metadata, for all slice points."""
return self.slice_points
def __len__(self):
"""Return nslice, the number of slice_points in the slicer."""
return self.nslice
def __iter__(self):
"""Iterate over the slices."""
self.islice = 0
return self
def __next__(self):
"""Returns results of self._slice_sim_data when iterating over slicer.
Results of self._slice_sim_data should be dictionary of
{'idxs': the data indexes relevant for this slice of the slicer,
'slice_point': the metadata for the slice_point, which always
includes 'sid' key for ID of slice_point.}
"""
if self.islice >= self.nslice:
raise StopIteration
islice = self.islice
self.islice += 1
return self._slice_sim_data(islice)
def __getitem__(self, islice):
return self._slice_sim_data(islice)
def __eq__(self, other_slicer):
"""Evaluate if two slicers are equivalent."""
raise NotImplementedError()
def __ne__(self, other_slicer):
"""Evaluate if two slicers are not equivalent."""
if self == other_slicer:
return False
else:
return True
def _slice_sim_data(self, slice_point):
"""Slice the simulation data appropriately for the slicer.
Given the identifying slice_point metadata
The slice of data returned will be the indices of the
numpy rec array (the sim_data) which are appropriate for the metric
to be working on, for that slice_point.
"""
raise NotImplementedError('This method is set up by "setup_slicer" - run that first.')
def write_data(
self,
outfilename,
metric_values,
metric_name="",
sim_data_name="",
constraint=None,
info_label="",
plot_dict=None,
display_dict=None,
summary_values=None,
):
"""
Save metric values along with the information required to
re-build the slicer.
Parameters
-----------
outfilename : `str`
The output file name.
metric_values : `np.ma.MaskedArray` or `np.ndarray`
The metric values to save to disk.
metric_name : `str`
Name of the metric as configured when run
sim_data_name : `str`
Name of the simulation metric run on
constraint : `str`
Constraint used to subselect data
info_label : `str`
Descriptive additional information
plot_dict : `dict`
Dictionary of plotting parameters
display_dict : `dict`
Dictionary of display parameters, including caption
summary_values : `dict`
Dictionary of summary statistics
"""
header = {}
header["metric_name"] = metric_name
header["constraint"] = constraint
header["info_label"] = info_label
header["sim_data_name"] = sim_data_name
date, version_info = get_date_version()
header["date_ran"] = date
if display_dict is None:
display_dict = {"group": "Ungrouped"}
header["display_dict"] = display_dict
header["plot_dict"] = plot_dict
header["summary_values"] = summary_values
for key in version_info:
header[key] = version_info[key]
if hasattr(metric_values, "mask"): # If it is a masked array
data = metric_values.data
mask = metric_values.mask
fill = metric_values.fill_value
else:
data = metric_values
mask = None
fill = None
# npz file acts like dictionary: each keyword/value pair
# below acts as a dictionary in loaded NPZ file.
np.savez(
outfilename,
# header saved as dictionary
header=header,
# metric data values
metric_values=data,
# metric mask values
mask=mask,
# metric badval/fill val
fill=fill,
# dictionary of instantiation parameters
slicer_init=self.slicer_init,
# class name
slicer_name=self.slicer_name,
# slice_point metadata saved (is a dictionary)
slice_points=self.slice_points,
slicer_n_slice=self.nslice,
slicer_shape=self.shape,
)
def output_json(
self,
metric_values,
metric_name="",
sim_data_name="",
info_label="",
plot_dict=None,
):
"""
Send metric data to JSON streaming API,
along with a little bit of metadata.
This method will only work for metrics where the
metricDtype is float or int, as JSON will not interpret more
complex data properly. These values can't be plotted anyway though.
Parameters
-----------
metric_values : `np.ma.MaskedArray` or `np.ndarray`
The metric values.
metric_name : `str`, optional
The name of the metric.
sim_data_name : `str`, optional
The name of the simulated data source.
info_label : `str`, optional
Some additional information about this metric
and how it was calculated.
plot_dict : `dict`, optional.
The plot_dict for this metric bundle.
Returns
--------
io : `StringIO`
StringIO object containing a header dictionary with
metric_name/metadata/sim_data_name/slicer_name,
and plot labels from plot_dict, and metric values/data for plot.
if oneDSlicer,
the data is [ [bin_left_edge, value], [bin_left_edge, value]..].
if a spatial slicer,
the data is [ [lon, lat, value], [lon, lat, value] ..].
"""
# Bail if this is not a good data type for JSON.
if not (metric_values.dtype == "float") or (metric_values.dtype == "int"):
warnings.warn("Cannot generate JSON.")
io = StringIO()
json.dump(["Cannot generate JSON for this file."], io)
return None
# Else put everything together for JSON output.
if plot_dict is None:
plot_dict = {}
plot_dict["units"] = ""
# Preserve some of the metadata for the plot.
header = {}
header["metric_name"] = metric_name
header["info_label"] = info_label
header["sim_data_name"] = sim_data_name
header["slicer_name"] = self.slicer_name
header["slicer_len"] = int(self.nslice)
# Set some default plot labels if appropriate.
if "title" in plot_dict:
header["title"] = plot_dict["title"]
else:
header["title"] = "%s %s: %s" % (sim_data_name, info_label, metric_name)
if "xlabel" in plot_dict:
header["xlabel"] = plot_dict["xlabel"]
else:
if hasattr(self, "slice_col_name"):
header["xlabel"] = "%s (%s)" % (
self.slice_col_name,
self.slice_col_units,
)
else:
header["xlabel"] = "%s" % metric_name
if "units" in plot_dict:
header["xlabel"] += " (%s)" % (plot_dict["units"])
if "ylabel" in plot_dict:
header["ylabel"] = plot_dict["ylabel"]
else:
if hasattr(self, "slice_col_name"):
header["ylabel"] = "%s" % metric_name
if "units" in plot_dict:
header["ylabel"] += " (%s)" % (plot_dict["units"])
else:
# If it's not a oneDslicer and no ylabel given, don't need one.
pass
# Bundle up slicer and metric info.
metric = []
# If metric values is a masked array.
if hasattr(metric_values, "mask"):
if "ra" in self.slice_points:
# Spatial slicer.
# Translate ra/dec to lon/lat in degrees and
# output with metric value.
for ra, dec, value, mask in zip(
self.slice_points["ra"],
self.slice_points["dec"],
metric_values.data,
metric_values.mask,
):
if not mask:
lon = ra * 180.0 / np.pi
lat = dec * 180.0 / np.pi
metric.append([lon, lat, value])
elif "bins" in self.slice_points:
# OneD slicer. Translate bins into bin/left and
# output with metric value.
for i in range(len(metric_values)):
bin_left = self.slice_points["bins"][i]
value = metric_values.data[i]
mask = metric_values.mask[i]
if not mask:
metric.append([bin_left, value])
else:
metric.append([bin_left, 0])
metric.append([self.slice_points["bins"][i + 1], 0])
elif self.slicer_name == "UniSlicer":
metric.append([metric_values[0]])
# Else:
else:
if "ra" in self.slice_points:
for ra, dec, value in zip(self.slice_points["ra"], self.slice_points["dec"], metric_values):
lon = ra * 180.0 / np.pi
lat = dec * 180.0 / np.pi
metric.append([lon, lat, value])
elif "bins" in self.slice_points:
for i in range(len(metric_values)):
bin_left = self.slice_points["bins"][i]
value = metric_values[i]
metric.append([bin_left, value])
metric.append(self.slice_points["bins"][i + 1][0])
elif self.slicer_name == "UniSlicer":
metric.append([metric_values[0]])
# Write out JSON output.
io = StringIO()
json.dump([header, metric], io)
return io
def read_data(self, infilename):
"""
Read metric data from disk, along with the info to
rebuild the slicer (minus new slicing capability).
Parameters
-----------
infilename: `str`
The filename containing the metric data.
Returns
-------
metric_values, slicer, header : `np.ma.MaskedArray`,
`rubin_sim.maf.slicer`, `dict`
MetricValues stored in data file,
the slicer basis for those metric values,
and a dictionary containing header information
(run_name, metadata, etc.).
"""
import rubin_sim.maf.slicers as slicers
# Allowing pickles here is required, because otherwise we cannot
# restore data saved as objects.
restored = np.load(infilename, allow_pickle=True)
if "slicer_name" not in restored:
metric_values, slicer, header = self.read_backwards_compatible(restored, infilename)
return metric_values, slicer, header
# This is the standard behavior and will be the
# sole behavior at a future release point.
# Get metadata and other sim_data info.
header = restored["header"][()]
if "dateRan" in header:
header["date_ran"] = header["dateRan"]
# Get slicer information.
slicer_init = restored["slicer_init"][()]
slicer_name = str(restored["slicer_name"])
slice_points = restored["slice_points"][()]
slicer_nslice = restored["slicer_n_slice"]
slicer_shape = restored["slicer_shape"]
try:
slicer = getattr(slicers, slicer_name)(**slicer_init)
except TypeError:
if self.verbose:
warnings.warn(
f"Cannot use saved slicer init values; falling back to defaults for {infilename}"
)
slicer = getattr(slicers, slicer_name)()
# Restore slice_point information.
slicer.nslice = slicer_nslice
slicer.slice_points = slice_points
slicer.shape = slicer_shape
# Get metric data set
if restored["mask"][()] is None:
metric_values = ma.MaskedArray(data=restored["metric_values"])
else:
metric_values = ma.MaskedArray(
data=restored["metric_values"],
mask=restored["mask"],
fill_value=restored["fill"],
)
return metric_values, slicer, header
def read_backwards_compatible(self, restored, infilename):
"""Read pre v1.0 metric files."""
# Backwards compatibility for pre-v1.0 metric outputs.
# To be deprecated at a future release.
warnings.warn(
"Reading pre-v1.0 metric data. To be deprecated in a future release.",
FutureWarning,
)
import rubin_sim.maf.slicers as slicers
header = restored["header"][()]
header["metric_name"] = header["metricName"]
header["sim_data_name"] = header["simDataName"]
if "metadata" in header:
header["info_label"] = header["metadata"]
if "plotDict" in header:
header["plot_dict"] = header["plotDict"]
if "displayDict" in header:
header["display_dict"] = header["displayDict"]
if "dateRan" in header:
header["date_ran"] = header["dateRan"]
slicer_init = restored["slicer_init"][()]
slicer_name = str(restored["slicerName"])
slice_points = restored["slicePoints"][()]
slicer_nslice = restored["slicerNSlice"]
slicer_shape = restored["slicerShape"]
# Slicer init update
new = ["lat_col", "lon_col", "use_camera"]
old = ["latCol", "lonCol", "useCamera"]
for n, o in zip(new, old):
if o in slicer_init:
slicer_init[n] = slicer_init[o]
del slicer_init[o]
if "Hrange" in slicer_init:
slicer_init["h_range"] = slicer_init["Hrange"]
del slicer_init["Hrange"]
new = ["bin_min", "bin_max", "bin_size", "slice_col_name", "slice_col_units"]
old = ["binMin", "binMax", "binsize", "sliceColName", "sliceColUnits"]
for n, o in zip(new, old):
if o in slicer_init:
slicer_init[n] = slicer_init[o]
del slicer_init[o]
# An earlier backwards compatibility issue -
# map 'spatialkey1/spatialkey2' to 'lon_col/lat_col'.
if "spatialkey1" in slicer_init:
slicer_init["lon_col"] = slicer_init["spatialkey1"]
del slicer_init["spatialkey1"]
if "spatialkey2" in slicer_init:
slicer_init["lat_col"] = slicer_init["spatialkey2"]
del slicer_init["spatialkey2"]
try:
slicer = getattr(slicers, slicer_name)(**slicer_init)
except TypeError:
if self.verbose:
warnings.warn(
f"Cannot use saved slicer init values; falling back to defaults for {infilename}"
)
slicer = getattr(slicers, slicer_name)()
# Restore slice_point information.
slicer.nslice = slicer_nslice
slicer.slice_points = slice_points
slicer.shape = slicer_shape
# Get metric data set
if restored["mask"][()] is None:
metric_values = ma.MaskedArray(data=restored["metricValues"])
else:
metric_values = ma.MaskedArray(
data=restored["metricValues"],
mask=restored["mask"],
fill_value=restored["fill"],
)
return metric_values, slicer, header
|
lsstREPO_NAMErubin_simPATH_START.@rubin_sim_extracted@rubin_sim-main@rubin_sim@maf@slicers@base_slicer.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "PyEllips/pyElli",
"repo_path": "pyElli_extracted/pyElli-master/src/elli/importer/__init__.py",
"type": "Python"
}
|
import chardet
def detect_encoding(fname: str) -> str:
r"""Detects the encoding of file fname.
Args:
fname (str): Filename
Returns:
str: Encoding identifier string.
"""
with open(fname, "rb") as f:
raw_data = f.read()
result = chardet.detect(raw_data)
return result["encoding"]
|
PyEllipsREPO_NAMEpyElliPATH_START.@pyElli_extracted@pyElli-master@src@elli@importer@__init__.py@.PATH_END.py
|
{
"filename": "__init__.py",
"repo_name": "yqiuu/spectuner",
"repo_path": "spectuner_extracted/spectuner-master/spectuner/identify/__init__.py",
"type": "Python"
}
|
from .identify import *
from .ident_result import *
from .peaks import *
|
yqiuuREPO_NAMEspectunerPATH_START.@spectuner_extracted@spectuner-master@spectuner@identify@__init__.py@.PATH_END.py
|
{
"filename": "buildtiles.py",
"repo_name": "rainwoodman/gaepsi2",
"repo_path": "gaepsi2_extracted/gaepsi2-master/utils/buildtiles.py",
"type": "Python"
}
|
import bigfile
import numpy
from matplotlib.figure import Figure
from itertools import product
from tiles import tilename
f = bigfile.BigFile('image')
f1 = bigfile.BigFile('image2')
w = f.open('W')
v = f.open('V')
h = f.open('header')
tp = h.attrs['TilePadding']
size = h.attrs['ImageSize']
h.attrs['Level'] = 0
ntile = h.attrs['NTile']
h1 = f1.create('header')
h1.attrs['TilePadding'] = tp
h1.attrs['Level'] = h.attrs['Level'] + 1
ntile1 = ntile // 2
h1.attrs['NTile'] = ntile1
w1 = f1.create('W', ('f8', tp * tp), ntile1.prod())
v1 = f1.create('V', ('f8', tp * tp), ntile1.prod())
print(ntile1)
def readtile(f, h, w, v, i, j):
ntile = h.attrs['NTile']
tp = h.attrs['TilePadding']
if i >= ntile[0] or j >= ntile[1]:
return numpy.zeros((2, tp, tp), 'f8')
return (w.read(i * ntile[1] + j, 1)[0].reshape(tp, tp),
v.read(i * ntile[1] + j, 1)[0].reshape(tp, tp))
def combine(i, j, f, h, w, v):
i1 = 2 * i
j1 = 2 * j
i2 = 2 * i + 1
j2 = 2 * j + 1
wbig = numpy.zeros((2 * tp, 2 * tp))
vbig = numpy.zeros((2 * tp, 2 * tp))
wbig[:tp, :tp], vbig[:tp, :tp] = readtile(f, h, w, v, i1, j1)
wbig[tp:, :tp], vbig[tp:, :tp] = readtile(f, h, w, v, i2, j1)
wbig[:tp, tp:], vbig[:tp, tp:] = readtile(f, h, w, v, i1, j2)
wbig[tp:, tp:], vbig[tp:, tp:] = readtile(f, h, w, v, i2, j2)
print('reading', tilename(i1, j1, *ntile))
print('reading', tilename(i1, j2, *ntile))
print('reading', tilename(i2, j1, *ntile))
print('reading', tilename(i2, j2, *ntile))
wbigr = wbig.reshape(tp, 2, tp, 2)
vbigr = vbig.reshape(tp, 2, tp, 2)
return wbigr.sum(axis=(-1, -3)).ravel(), vbigr.sum(axis=(-1, -3)).ravel()
for j, i in product(range(ntile1[1]), range(ntile1[0])):
wbuf, vbuf = combine(i, j, f, h, w, v)
print('writing', tilename(i, j, *ntile1))
w1.write(i * ntile1[1] + j, wbuf.reshape(1, -1))
v1.write(i * ntile1[1] + j, vbuf.reshape(1, -1))
|
rainwoodmanREPO_NAMEgaepsi2PATH_START.@gaepsi2_extracted@gaepsi2-master@utils@buildtiles.py@.PATH_END.py
|
{
"filename": "reset_stage_metadata.py",
"repo_name": "pyDANDIA/pyDANDIA",
"repo_path": "pyDANDIA_extracted/pyDANDIA-main/pyDANDIA/reset_stage_metadata.py",
"type": "Python"
}
|
import os
import sys
from pyDANDIA import metadata
def reset_red_status_for_stage(red_dir,stage_number):
"""Function to reset the reduction status table entries for a given stage.
Note that the status for all images will be set to zero (process) except
for entries that were flagged as -1 (do not process) by the PREVIOUS
stage"""
reduction_metadata = metadata.MetaData()
reduction_metadata.load_all_metadata(red_dir, 'pyDANDIA_metadata.fits')
stage_name = 'STAGE_'+str(stage_number)
image_list = reduction_metadata.reduction_status[1]['IMAGES'].data
image_status = reduction_metadata.reduction_status[1]['STAGE_'+str(stage_number-1)].data
for i,image in enumerate(image_list):
if '-1' not in image_status[i]:
reduction_metadata.update_a_cell_to_layer('reduction_status', i, stage_name, '0')
reduction_metadata.save_updated_metadata(red_dir,'pyDANDIA_metadata.fits')
if __name__ == '__main__':
if len(sys.argv) == 1:
red_dir = input('Please enter the path to the reduction directory: ')
stage_number = input('Please enter the stage number to reset: ')
else:
red_dir = sys.argv[1]
stage_number = sys.argv[2]
stage_number = int(stage_number)
reset_red_status_for_stage(red_dir,stage_number)
|
pyDANDIAREPO_NAMEpyDANDIAPATH_START.@pyDANDIA_extracted@pyDANDIA-main@pyDANDIA@reset_stage_metadata.py@.PATH_END.py
|
{
"filename": "test_ultradeep.py",
"repo_name": "GeminiDRSoftware/DRAGONS",
"repo_path": "DRAGONS_extracted/DRAGONS-master/geminidr/niri/recipes/sq/tests/test_ultradeep.py",
"type": "Python"
}
|
import pytest
import os
from astrodata.testing import download_from_archive
from recipe_system.reduction.coreReduce import Reduce
niri_deep_dataset = [f"N20210512S{i:04d}.fits" for i in range(17, 35)]
niri_dark = "N20210512S0246_dark.fits"
@pytest.mark.slow
def test_ultradeep_recipe_niri(change_working_dir, path_to_inputs):
"""
Test that the ultradeep recipe runs on NIRI images. This is not a
regression test, it just confirms the absence of any errors.
It also runs the makeSkyFlat recipe.
"""
dark = os.path.join(path_to_inputs, niri_dark)
with change_working_dir():
input_files = [download_from_archive(f) for f in niri_deep_dataset]
skyflat = run_reduce(input_files, {"dark": dark},
recipe_name='makeSkyFlat')
run_reduce(input_files, {"dark":dark, "flat": skyflat},
recipe_name='ultradeep')
def run_reduce(file_list, user_pars, recipe_name=None):
r = Reduce()
r.files = file_list
r.uparms = user_pars
if recipe_name:
r.recipename = recipe_name
r.runr()
return r.output_filenames
|
GeminiDRSoftwareREPO_NAMEDRAGONSPATH_START.@DRAGONS_extracted@DRAGONS-master@geminidr@niri@recipes@sq@tests@test_ultradeep.py@.PATH_END.py
|
{
"filename": "test_connect.py",
"repo_name": "astropy/astropy",
"repo_path": "astropy_extracted/astropy-main/astropy/io/fits/tests/test_connect.py",
"type": "Python"
}
|
import gc
import warnings
import numpy as np
import pytest
from numpy.testing import assert_allclose, assert_array_equal
from astropy import units as u
from astropy.io import fits
from astropy.io.fits import (
BinTableHDU,
HDUList,
ImageHDU,
PrimaryHDU,
connect,
table_to_hdu,
)
from astropy.io.fits.column import (
_fortran_to_python_format,
_parse_tdisp_format,
python_to_tdisp,
)
from astropy.io.tests.mixin_columns import compare_attrs, mixin_cols, serialized_names
from astropy.table import Column, MaskedColumn, QTable, Table
from astropy.table.table_helpers import simple_table
from astropy.time import Time
from astropy.units import UnitScaleError
from astropy.units import allclose as quantity_allclose
from astropy.units.quantity import QuantityInfo
from astropy.utils.data import get_pkg_data_filename
from astropy.utils.exceptions import AstropyDeprecationWarning, AstropyUserWarning
from astropy.utils.misc import _NOT_OVERWRITING_MSG_MATCH
# FITS does not preserve precision, in_subfmt, and out_subfmt.
time_attrs = ["value", "shape", "format", "scale", "location"]
compare_attrs = {
name: (time_attrs if isinstance(col, Time) else compare_attrs[name])
for name, col in mixin_cols.items()
}
# FITS does not support multi-element location, array with object dtype,
# or logarithmic quantities.
unsupported_cols = {
name: col
for name, col in mixin_cols.items()
if (
(isinstance(col, Time) and col.location.shape != ())
or (isinstance(col, np.ndarray) and col.dtype.kind == "O")
or isinstance(col, u.LogQuantity)
)
}
mixin_cols = {
name: col for name, col in mixin_cols.items() if name not in unsupported_cols
}
def equal_data(a, b):
return all(np.all(a[name] == b[name]) for name in a.dtype.names)
class TestSingleTable:
def setup_class(self):
self.data = np.array(
list(zip([1, 2, 3, 4], ["a", "b", "c", "d"], [2.3, 4.5, 6.7, 8.9])),
dtype=[("a", int), ("b", "U1"), ("c", float)],
)
def test_simple(self, tmp_path):
filename = tmp_path / "test_simple.fts"
t1 = Table(self.data)
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert equal_data(t1, t2)
def test_simple_pathlib(self, tmp_path):
filename = tmp_path / "test_simple.fit"
t1 = Table(self.data)
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert equal_data(t1, t2)
def test_simple_meta(self, tmp_path):
filename = tmp_path / "test_simple.fits"
t1 = Table(self.data)
t1.meta["A"] = 1
t1.meta["B"] = 2.3
t1.meta["C"] = "spam"
t1.meta["comments"] = ["this", "is", "a", "long", "comment"]
t1.meta["HISTORY"] = ["first", "second", "third"]
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert equal_data(t1, t2)
for key in t1.meta:
if isinstance(t1.meta, list):
for i in range(len(t1.meta[key])):
assert t1.meta[key][i] == t2.meta[key][i]
else:
assert t1.meta[key] == t2.meta[key]
def test_simple_meta_conflicting(self, tmp_path):
filename = tmp_path / "test_simple.fits"
t1 = Table(self.data)
t1.meta["ttype1"] = "spam"
with pytest.warns(
AstropyUserWarning,
match=(
"Meta-data keyword ttype1 "
"will be ignored since it conflicts with a FITS "
"reserved keyword"
),
) as w:
t1.write(filename, overwrite=True)
assert len(w) == 1
def test_simple_noextension(self, tmp_path):
"""
Test that file type is recognized without extension
"""
filename = tmp_path / "test_simple"
t1 = Table(self.data)
t1.write(filename, overwrite=True, format="fits")
t2 = Table.read(filename)
assert equal_data(t1, t2)
@pytest.mark.parametrize("table_type", (Table, QTable))
def test_with_units(self, table_type, tmp_path):
filename = tmp_path / "test_with_units.fits"
t1 = table_type(self.data)
t1["a"].unit = u.m
t1["c"].unit = u.km / u.s
t1.write(filename, overwrite=True)
t2 = table_type.read(filename)
assert equal_data(t1, t2)
assert t2["a"].unit == u.m
assert t2["c"].unit == u.km / u.s
def test_with_custom_units_qtable(self, tmp_path):
# Test only for QTable - for Table's Column, new units are dropped
# (as is checked in test_write_drop_nonstandard_units).
filename = tmp_path / "test_with_units.fits"
unit = u.def_unit("bandpass_sol_lum")
t = QTable()
t["l"] = np.ones(5) * unit
with pytest.warns(AstropyUserWarning) as w:
t.write(filename, overwrite=True)
assert len(w) == 1
assert "bandpass_sol_lum" in str(w[0].message)
# Just reading back, the data is fine but the unit is not recognized.
with pytest.warns(
u.UnitsWarning, match="'bandpass_sol_lum' did not parse"
) as w:
t2 = QTable.read(filename)
assert len(w) == 1
assert isinstance(t2["l"].unit, u.UnrecognizedUnit)
assert str(t2["l"].unit) == "bandpass_sol_lum"
assert np.all(t2["l"].value == t["l"].value)
# But if we enable the unit, it should be recognized.
with u.add_enabled_units(unit):
t3 = QTable.read(filename)
assert t3["l"].unit is unit
assert equal_data(t3, t)
# Regression check for #8897; write used to fail when a custom
# unit was enabled.
with pytest.warns(AstropyUserWarning):
t3.write(filename, overwrite=True)
# It should also be possible to read the file in using a unit alias,
# even to a unit that may not be the same.
with u.set_enabled_aliases({"bandpass_sol_lum": u.Lsun}):
t3 = QTable.read(filename)
assert t3["l"].unit is u.Lsun
@pytest.mark.parametrize("table_type", (Table, QTable))
def test_read_with_unit_aliases(self, table_type):
hdu = BinTableHDU(self.data)
hdu.columns[0].unit = "Angstroms"
hdu.columns[2].unit = "ergs/(cm.s.Angstroms)"
with u.set_enabled_aliases({"Angstroms": u.AA, "ergs": u.erg}):
t = table_type.read(hdu)
assert t["a"].unit == u.AA
assert t["c"].unit == u.erg / (u.cm * u.s * u.AA)
@pytest.mark.parametrize("table_type", (Table, QTable))
def test_with_format(self, table_type, tmp_path):
filename = tmp_path / "test_with_format.fits"
t1 = table_type(self.data)
t1["a"].format = "{:5d}"
t1["b"].format = "{:>20}"
t1["c"].format = "{:6.2f}"
t1.write(filename, overwrite=True)
t2 = table_type.read(filename)
assert equal_data(t1, t2)
assert t2["a"].format == "{:5d}"
assert t2["b"].format == "{:>20}"
assert t2["c"].format == "{:6.2f}"
def test_masked(self, tmp_path):
filename = tmp_path / "test_masked.fits"
t1 = Table(self.data, masked=True)
t1.mask["a"] = [1, 0, 1, 0]
t1.mask["b"] = [1, 0, 0, 1]
t1.mask["c"] = [0, 1, 1, 0]
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert equal_data(t1, t2)
assert np.all(t1["a"].mask == t2["a"].mask)
assert np.all(t1["b"].mask == t2["b"].mask)
assert np.all(t1["c"].mask == t2["c"].mask)
@pytest.mark.parametrize("masked", [True, False])
def test_masked_nan(self, masked, tmp_path):
"""Check that masked values by default are replaced by NaN.
This should work for any shape and be independent of whether the
Table is formally masked or not.
"""
filename = tmp_path / "test_masked_nan.fits"
a = np.ma.MaskedArray([5.25, 8.5, 3.75, 6.25], mask=[1, 0, 1, 0])
b = np.ma.MaskedArray([2.5, 4.5, 6.75, 8.875], mask=[1, 0, 0, 1], dtype="f4")
c = np.ma.stack([a, b], axis=-1)
t1 = Table([a, b, c], names=["a", "b", "c"], masked=masked)
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert_array_equal(t2["a"].data, [np.nan, 8.5, np.nan, 6.25])
assert_array_equal(t2["b"].data, [np.nan, 4.5, 6.75, np.nan])
assert_array_equal(
t2["c"].data, np.stack([t2["a"].data, t2["b"].data], axis=-1)
)
assert np.all(t1["a"].mask == t2["a"].mask)
assert np.all(t1["b"].mask == t2["b"].mask)
assert np.all(t1["c"].mask == t2["c"].mask)
def test_masked_serialize_data_mask(self, tmp_path):
filename = tmp_path / "test_masked_nan.fits"
a = np.ma.MaskedArray([5.25, 8.5, 3.75, 6.25], mask=[1, 0, 1, 0])
b = np.ma.MaskedArray([2.5, 4.5, 6.75, 8.875], mask=[1, 0, 0, 1])
c = np.ma.stack([a, b], axis=-1)
t1 = Table([a, b, c], names=["a", "b", "c"])
t1.write(filename, overwrite=True)
t2 = Table.read(filename)
assert_array_equal(t2["a"].data, [5.25, 8.5, 3.75, 6.25])
assert_array_equal(t2["b"].data, [2.5, 4.5, 6.75, 8.875])
assert_array_equal(
t2["c"].data, np.stack([t2["a"].data, t2["b"].data], axis=-1)
)
assert np.all(t1["a"].mask == t2["a"].mask)
assert np.all(t1["b"].mask == t2["b"].mask)
assert np.all(t1["c"].mask == t2["c"].mask)
def test_read_from_fileobj(self, tmp_path):
filename = tmp_path / "test_read_from_fileobj.fits"
hdu = BinTableHDU(self.data)
hdu.writeto(filename, overwrite=True)
with open(filename, "rb") as f:
t = Table.read(f)
assert equal_data(t, self.data)
def test_read_with_nonstandard_units(self):
hdu = BinTableHDU(self.data)
hdu.columns[0].unit = "RADIANS"
hdu.columns[1].unit = "spam"
hdu.columns[2].unit = "millieggs"
with pytest.warns(u.UnitsWarning, match="did not parse as fits unit"):
t = Table.read(hdu)
assert equal_data(t, self.data)
@pytest.mark.parametrize("table_type", (Table, QTable))
def test_write_drop_nonstandard_units(self, table_type, tmp_path):
# While we are generous on input (see above), we are strict on
# output, dropping units not recognized by the fits standard.
filename = tmp_path / "test_nonstandard_units.fits"
spam = u.def_unit("spam")
t = table_type()
t["a"] = [1.0, 2.0, 3.0] * spam
with pytest.warns(AstropyUserWarning, match="spam") as w:
t.write(filename)
assert len(w) == 1
if table_type is Table:
assert "cannot be recovered in reading. " in str(w[0].message)
else:
assert "lost to non-astropy fits readers" in str(w[0].message)
with fits.open(filename) as ff:
hdu = ff[1]
assert "TUNIT1" not in hdu.header
def test_memmap(self, tmp_path):
filename = tmp_path / "test_simple.fts"
t1 = Table(self.data)
t1.write(filename, overwrite=True)
t2 = Table.read(filename, memmap=False)
t3 = Table.read(filename, memmap=True)
assert equal_data(t2, t3)
# To avoid issues with open files, we need to remove references to
# data that uses memory mapping and force the garbage collection
del t1, t2, t3
gc.collect()
@pytest.mark.parametrize("memmap", (False, True))
def test_character_as_bytes(self, tmp_path, memmap):
filename = tmp_path / "test_simple.fts"
t1 = Table(self.data)
t1.write(filename, overwrite=True)
t2 = Table.read(filename, character_as_bytes=False, memmap=memmap)
t3 = Table.read(filename, character_as_bytes=True, memmap=memmap)
assert t2["b"].dtype.kind == "U"
assert t3["b"].dtype.kind == "S"
assert equal_data(t2, t3)
# To avoid issues with open files, we need to remove references to
# data that uses memory mapping and force the garbage collection
del t1, t2, t3
gc.collect()
def test_oned_single_element(self, tmp_path):
filename = tmp_path / "test_oned_single_element.fits"
table = Table({"x": [[1], [2]]})
table.write(filename, overwrite=True)
read = Table.read(filename)
assert read["x"].shape == (2, 1)
assert len(read["x"][0]) == 1
def test_write_append(self, tmp_path):
t = Table(self.data)
hdu = table_to_hdu(t)
def check_equal(filename, expected, start_from=1):
with fits.open(filename) as hdu_list:
assert len(hdu_list) == expected
for hdu_table in hdu_list[start_from:]:
assert hdu_table.header == hdu.header
assert np.all(hdu_table.data == hdu.data)
filename = tmp_path / "test_write_append.fits"
t.write(filename, append=True)
t.write(filename, append=True)
check_equal(filename, 3)
# Check the overwrite works correctly.
t.write(filename, append=True, overwrite=True)
t.write(filename, append=True)
check_equal(filename, 3)
# Normal write, check it's not appending.
t.write(filename, overwrite=True)
t.write(filename, overwrite=True)
check_equal(filename, 2)
# Now write followed by append, with different shaped tables.
t2 = Table(np.array([1, 2]))
t2.write(filename, overwrite=True)
t.write(filename, append=True)
check_equal(filename, 3, start_from=2)
assert equal_data(t2, Table.read(filename, hdu=1))
def test_write_overwrite(self, tmp_path):
t = Table(self.data)
filename = tmp_path / "test_write_overwrite.fits"
t.write(filename)
with pytest.raises(OSError, match=_NOT_OVERWRITING_MSG_MATCH):
t.write(filename)
t.write(filename, overwrite=True)
def test_mask_nans_on_read(self, tmp_path):
filename = tmp_path / "test_inexact_format_parse_on_read.fits"
c1 = fits.Column(name="a", array=np.array([1, 2, np.nan]), format="E")
table_hdu = fits.TableHDU.from_columns([c1])
table_hdu.writeto(filename)
tab = Table.read(filename)
assert any(tab.mask)
assert tab.mask[2]
tab = Table.read(filename, mask_invalid=False)
assert tab.mask is None
# using memmap also deactivate the masking
tab = Table.read(filename, memmap=True)
assert tab.mask is None
def test_mask_null_on_read(self, tmp_path):
filename = tmp_path / "test_null_format_parse_on_read.fits"
col = fits.Column(
name="a",
array=np.array([1, 2, 99, 60000], dtype="u2"),
format="I",
null=99,
bzero=32768,
)
bin_table_hdu = fits.BinTableHDU.from_columns([col])
bin_table_hdu.writeto(filename, overwrite=True)
tab = Table.read(filename)
assert any(tab.mask)
assert tab.mask[2]
def test_mask_str_on_read(self, tmp_path):
filename = tmp_path / "test_null_format_parse_on_read.fits"
col = fits.Column(
name="a", array=np.array([b"foo", b"bar", b""], dtype="|S3"), format="A3"
)
bin_table_hdu = fits.BinTableHDU.from_columns([col])
bin_table_hdu.writeto(filename, overwrite=True)
tab = Table.read(filename)
assert any(tab.mask)
assert tab.mask[2]
tab = Table.read(filename, mask_invalid=False)
assert tab.mask is None
def test_heterogeneous_VLA_tables(self, tmp_path):
"""
Check the behaviour of heterogeneous VLA object.
"""
filename = tmp_path / "test_table_object.fits"
msg = "Column 'col1' contains unsupported object types or mixed types: "
# The column format fix the type of the arrays in the VLF object.
a = np.array([45, 30])
b = np.array([11.0, 12.0, 13])
var = np.array([a, b], dtype=object)
tab = Table({"col1": var})
with pytest.raises(TypeError, match=msg):
tab.write(filename)
# Strings in the VLF object can't be added to the table
a = np.array(["five", "thirty"])
b = np.array([11.0, 12.0, 13])
var = np.array([a, b], dtype=object)
with pytest.raises(TypeError, match=msg):
tab.write(filename)
def test_write_object_tables_with_unified(self, tmp_path):
"""
Write objects with the unified I/O interface.
See https://github.com/astropy/astropy/issues/1906
"""
filename = tmp_path / "test_table_object.fits"
msg = r"Column 'col1' contains unsupported object types or mixed types: {dtype\('O'\)}"
# Make a FITS table with an object column
tab = Table({"col1": [None]})
with pytest.raises(TypeError, match=msg):
tab.write(filename)
def test_write_VLA_tables_with_unified(self, tmp_path):
"""
Write VLA objects with the unified I/O interface.
See https://github.com/astropy/astropy/issues/11323
"""
filename = tmp_path / "test_table_VLA.fits"
# Make a FITS table with a variable-length array column
a = np.array([45, 30])
b = np.array([11, 12, 13])
c = np.array([45, 55, 65, 75])
var = np.array([a, b, c], dtype=object)
tabw = Table({"col1": var})
tabw.write(filename)
tab = Table.read(filename)
assert np.array_equal(tab[0]["col1"], np.array([45, 30]))
assert np.array_equal(tab[1]["col1"], np.array([11, 12, 13]))
assert np.array_equal(tab[2]["col1"], np.array([45, 55, 65, 75]))
class TestMultipleHDU:
def setup_class(self):
self.data1 = np.array(
list(zip([1, 2, 3, 4], ["a", "b", "c", "d"], [2.3, 4.5, 6.7, 8.9])),
dtype=[("a", int), ("b", "U1"), ("c", float)],
)
self.data2 = np.array(
list(zip([1.4, 2.3, 3.2, 4.7], [2.3, 4.5, 6.7, 8.9])),
dtype=[("p", float), ("q", float)],
)
self.data3 = np.array(
list(zip([1, 2, 3, 4], [2.3, 4.5, 6.7, 8.9])),
dtype=[("A", int), ("B", float)],
)
hdu0 = PrimaryHDU()
hdu1 = BinTableHDU(self.data1, name="first")
hdu2 = BinTableHDU(self.data2, name="second")
hdu3 = ImageHDU(np.ones((3, 3)), name="third")
hdu4 = BinTableHDU(self.data3)
self.hdus = HDUList([hdu0, hdu1, hdu2, hdu3, hdu4])
self.hdusb = HDUList([hdu0, hdu3, hdu2, hdu1])
self.hdus3 = HDUList([hdu0, hdu3, hdu2])
self.hdus2 = HDUList([hdu0, hdu1, hdu3])
self.hdus1 = HDUList([hdu0, hdu1])
def teardown_class(self):
del self.hdus
def setup_method(self, method):
warnings.filterwarnings("always")
def test_read(self, tmp_path):
filename = tmp_path / "test_read.fits"
self.hdus.writeto(filename)
with pytest.warns(
AstropyUserWarning,
match=r"hdu= was not specified but multiple tables "
r"are present, reading in first available "
r"table \(hdu=1\)",
):
t = Table.read(filename)
assert equal_data(t, self.data1)
filename = tmp_path / "test_read_2.fits"
self.hdusb.writeto(filename)
with pytest.warns(
AstropyUserWarning,
match=r"hdu= was not specified but multiple tables "
r"are present, reading in first available "
r"table \(hdu=2\)",
):
t3 = Table.read(filename)
assert equal_data(t3, self.data2)
def test_read_with_hdu_0(self, tmp_path):
filename = tmp_path / "test_read_with_hdu_0.fits"
self.hdus.writeto(filename)
with pytest.raises(ValueError) as exc:
Table.read(filename, hdu=0)
assert exc.value.args[0] == "No table found in hdu=0"
@pytest.mark.parametrize("hdu", [1, "first"])
def test_read_with_hdu_1(self, tmp_path, hdu):
filename = tmp_path / "test_read_with_hdu_1.fits"
self.hdus.writeto(filename)
t = Table.read(filename, hdu=hdu)
assert equal_data(t, self.data1)
@pytest.mark.parametrize("hdu", [2, "second"])
def test_read_with_hdu_2(self, tmp_path, hdu):
filename = tmp_path / "test_read_with_hdu_2.fits"
self.hdus.writeto(filename)
t = Table.read(filename, hdu=hdu)
assert equal_data(t, self.data2)
@pytest.mark.parametrize("hdu", [3, "third"])
def test_read_with_hdu_3(self, tmp_path, hdu):
filename = tmp_path / "test_read_with_hdu_3.fits"
self.hdus.writeto(filename)
with pytest.raises(ValueError, match="No table found in hdu=3"):
Table.read(filename, hdu=hdu)
def test_read_with_hdu_4(self, tmp_path):
filename = tmp_path / "test_read_with_hdu_4.fits"
self.hdus.writeto(filename)
t = Table.read(filename, hdu=4)
assert equal_data(t, self.data3)
@pytest.mark.parametrize("hdu", [2, 3, "1", "second", ""])
def test_read_with_hdu_missing(self, tmp_path, hdu):
filename = tmp_path / "test_warn_with_hdu_1.fits"
self.hdus1.writeto(filename)
with pytest.warns(
AstropyDeprecationWarning,
match=rf"Specified hdu={hdu} not found, "
r"reading in first available table \(hdu=1\)",
):
t1 = Table.read(filename, hdu=hdu)
assert equal_data(t1, self.data1)
@pytest.mark.parametrize("hdu", [0, 2, "third"])
def test_read_with_hdu_warning(self, tmp_path, hdu):
filename = tmp_path / "test_warn_with_hdu_2.fits"
self.hdus2.writeto(filename)
with pytest.warns(
AstropyDeprecationWarning,
match=rf"No table found in specified hdu={hdu}, "
r"reading in first available table \(hdu=1\)",
):
t2 = Table.read(filename, hdu=hdu)
assert equal_data(t2, self.data1)
@pytest.mark.parametrize("hdu", [0, 1, "third"])
def test_read_in_last_hdu(self, tmp_path, hdu):
filename = tmp_path / "test_warn_with_hdu_3.fits"
self.hdus3.writeto(filename)
with pytest.warns(
AstropyDeprecationWarning,
match=rf"No table found in specified hdu={hdu}, "
r"reading in first available table \(hdu=2\)",
):
t3 = Table.read(filename, hdu=hdu)
assert equal_data(t3, self.data2)
def test_read_from_hdulist(self):
with pytest.warns(
AstropyUserWarning,
match=r"hdu= was not specified but multiple tables "
r"are present, reading in first available "
r"table \(hdu=1\)",
):
t = Table.read(self.hdus)
assert equal_data(t, self.data1)
with pytest.warns(
AstropyUserWarning,
match=r"hdu= was not specified but multiple tables "
r"are present, reading in first available "
r"table \(hdu=2\)",
):
t3 = Table.read(self.hdusb)
assert equal_data(t3, self.data2)
def test_read_from_hdulist_with_hdu_0(self):
with pytest.raises(ValueError) as exc:
Table.read(self.hdus, hdu=0)
assert exc.value.args[0] == "No table found in hdu=0"
@pytest.mark.parametrize("hdu", [1, "first", None])
def test_read_from_hdulist_with_single_table(self, hdu):
t = Table.read(self.hdus1, hdu=hdu)
assert equal_data(t, self.data1)
@pytest.mark.parametrize("hdu", [1, "first"])
def test_read_from_hdulist_with_hdu_1(self, hdu):
t = Table.read(self.hdus, hdu=hdu)
assert equal_data(t, self.data1)
@pytest.mark.parametrize("hdu", [2, "second"])
def test_read_from_hdulist_with_hdu_2(self, hdu):
t = Table.read(self.hdus, hdu=hdu)
assert equal_data(t, self.data2)
@pytest.mark.parametrize("hdu", [3, "third"])
def test_read_from_hdulist_with_hdu_3(self, hdu):
with pytest.raises(ValueError, match="No table found in hdu=3"):
Table.read(self.hdus, hdu=hdu)
@pytest.mark.parametrize("hdu", [0, 2, "third"])
def test_read_from_hdulist_with_hdu_warning(self, hdu):
with pytest.warns(
AstropyDeprecationWarning,
match=rf"No table found in specified hdu={hdu}, "
r"reading in first available table \(hdu=1\)",
):
t2 = Table.read(self.hdus2, hdu=hdu)
assert equal_data(t2, self.data1)
@pytest.mark.parametrize("hdu", [2, 3, "1", "second", ""])
def test_read_from_hdulist_with_hdu_missing(self, hdu):
with pytest.warns(
AstropyDeprecationWarning,
match=rf"Specified hdu={hdu} not found, "
r"reading in first available table \(hdu=1\)",
):
t1 = Table.read(self.hdus1, hdu=hdu)
assert equal_data(t1, self.data1)
@pytest.mark.parametrize("hdu", [0, 1, "third"])
def test_read_from_hdulist_in_last_hdu(self, hdu):
with pytest.warns(
AstropyDeprecationWarning,
match=rf"No table found in specified hdu={hdu}, "
r"reading in first available table \(hdu=2\)",
):
t3 = Table.read(self.hdus3, hdu=hdu)
assert equal_data(t3, self.data2)
@pytest.mark.parametrize("hdu", [None, 1, "first"])
def test_read_from_single_hdu(self, hdu):
t = Table.read(self.hdus[1])
assert equal_data(t, self.data1)
def test_masking_regression_1795():
"""
Regression test for #1795 - this bug originally caused columns where TNULL
was not defined to have their first element masked.
"""
t = Table.read(get_pkg_data_filename("data/tb.fits"))
assert np.all(t["c1"].mask == np.array([False, False]))
assert not hasattr(t["c2"], "mask")
assert not hasattr(t["c3"], "mask")
assert not hasattr(t["c4"], "mask")
assert np.all(t["c1"].data == np.array([1, 2]))
assert np.all(t["c2"].data == np.array([b"abc", b"xy "]))
assert_allclose(t["c3"].data, np.array([3.70000007153, 6.6999997139]))
assert np.all(t["c4"].data == np.array([False, True]))
def test_scale_error():
a = [1, 4, 5]
b = [2.0, 5.0, 8.2]
c = ["x", "y", "z"]
t = Table([a, b, c], names=("a", "b", "c"), meta={"name": "first table"})
t["a"].unit = "1.2"
with pytest.raises(
UnitScaleError,
match=r"The column 'a' could not be "
r"stored in FITS format because it has a scale '\(1\.2\)'"
r" that is not recognized by the FITS standard\. Either "
r"scale the data or change the units\.",
):
t.write("t.fits", format="fits", overwrite=True)
@pytest.mark.parametrize(
"tdisp_str, format_return",
[
("EN10.5", ("EN", "10", "5", None)),
("F6.2", ("F", "6", "2", None)),
("F12.10", ("F", "12", "10", None)),
("ES12.11", ("ES", "12", "11", None)),
("EN12.11", ("EN", "12", "11", None)),
("B5.10", ("B", "5", "10", None)),
("E10.5E3", ("E", "10", "5", "3")),
("A21", ("A", "21", None, None)),
],
)
def test_parse_tdisp_format(tdisp_str, format_return):
assert _parse_tdisp_format(tdisp_str) == format_return
@pytest.mark.parametrize(
"tdisp_str, format_str_return",
[
("G15.4E2", "{:15.4g}"),
("Z5.10", "{:5x}"),
("I6.5", "{:6d}"),
("L8", "{:>8}"),
("E20.7", "{:20.7e}"),
],
)
def test_fortran_to_python_format(tdisp_str, format_str_return):
assert _fortran_to_python_format(tdisp_str) == format_str_return
@pytest.mark.parametrize(
"fmt_str, tdisp_str",
[
("{:3d}", "I3"),
("3d", "I3"),
("7.3f", "F7.3"),
("{:>4}", "A4"),
("{:7.4f}", "F7.4"),
("%5.3g", "G5.3"),
("%10s", "A10"),
("%.4f", "F13.4"),
],
)
def test_python_to_tdisp(fmt_str, tdisp_str):
assert python_to_tdisp(fmt_str) == tdisp_str
def test_logical_python_to_tdisp():
assert python_to_tdisp("{:>7}", logical_dtype=True) == "L7"
def test_bool_column(tmp_path):
"""
Regression test for https://github.com/astropy/astropy/issues/1953
Ensures that Table columns of bools are properly written to a FITS table.
"""
arr = np.ones(5, dtype=bool)
arr[::2] = False
t = Table([arr])
t.write(tmp_path / "test.fits", overwrite=True)
with fits.open(tmp_path / "test.fits") as hdul:
assert hdul[1].data["col0"].dtype == np.dtype("bool")
assert np.all(hdul[1].data["col0"] == arr)
def test_unicode_column(tmp_path):
"""
Test that a column of unicode strings is still written as one
byte-per-character in the FITS table (so long as the column can be ASCII
encoded).
Regression test for one of the issues fixed in
https://github.com/astropy/astropy/pull/4228
"""
t = Table([np.array(["a", "b", "cd"])])
t.write(tmp_path / "test.fits", overwrite=True)
with fits.open(tmp_path / "test.fits") as hdul:
assert np.all(hdul[1].data["col0"] == ["a", "b", "cd"])
assert hdul[1].header["TFORM1"] == "2A"
t2 = Table([np.array(["\N{SNOWMAN}"])])
with pytest.raises(UnicodeEncodeError):
t2.write(tmp_path / "test.fits", overwrite=True)
def test_unit_warnings_read_write(tmp_path):
filename = tmp_path / "test_unit.fits"
t1 = Table([[1, 2], [3, 4]], names=["a", "b"])
t1["a"].unit = "m/s"
t1["b"].unit = "not-a-unit"
with pytest.warns(
u.UnitsWarning, match="'not-a-unit' did not parse as fits unit"
) as w:
t1.write(filename, overwrite=True)
assert len(w) == 1
with pytest.warns(
u.UnitsWarning, match="'not-a-unit' did not parse as fits unit"
) as w:
Table.read(filename, hdu=1)
def test_convert_comment_convention():
"""
Regression test for https://github.com/astropy/astropy/issues/6079
"""
filename = get_pkg_data_filename("data/stddata.fits")
with pytest.warns(
AstropyUserWarning,
match=r"hdu= was not specified but multiple tables are present",
):
t = Table.read(filename)
assert t.meta["comments"] == [
"",
" *** End of mandatory fields ***",
"",
"",
" *** Column names ***",
"",
"",
" *** Column formats ***",
"",
]
def assert_objects_equal(obj1, obj2, attrs, compare_class=True):
if compare_class:
assert obj1.__class__ is obj2.__class__
info_attrs = [
"info.name",
"info.format",
"info.unit",
"info.description",
"info.meta",
"info.dtype",
]
for attr in attrs + info_attrs:
a1 = obj1
a2 = obj2
for subattr in attr.split("."):
try:
a1 = getattr(a1, subattr)
a2 = getattr(a2, subattr)
except AttributeError:
a1 = a1[subattr]
a2 = a2[subattr]
# Mixin info.meta can None instead of empty OrderedDict(), #6720 would
# fix this.
if attr == "info.meta":
if a1 is None:
a1 = {}
if a2 is None:
a2 = {}
if isinstance(a1, np.ndarray) and a1.dtype.kind == "f":
assert quantity_allclose(a1, a2, rtol=1e-15)
elif isinstance(a1, np.dtype):
# FITS does not perfectly preserve dtype: byte order can change, and
# unicode gets stored as bytes. So, we just check safe casting, to
# ensure we do not, e.g., accidentally change integer to float, etc.
assert np.can_cast(a2, a1, casting="safe")
else:
assert np.all(a1 == a2)
def test_fits_mixins_qtable_to_table(tmp_path):
"""Test writing as QTable and reading as Table. Ensure correct classes
come out.
"""
filename = tmp_path / "test_simple.fits"
names = sorted(mixin_cols)
t = QTable([mixin_cols[name] for name in names], names=names)
t.write(filename, format="fits")
t2 = Table.read(filename, format="fits", astropy_native=True)
assert t.colnames == t2.colnames
for name, col in t.columns.items():
col2 = t2[name]
# Special-case Time, which does not yet support round-tripping
# the format.
if isinstance(col2, Time):
col2.format = col.format
attrs = compare_attrs[name]
compare_class = True
if isinstance(col.info, QuantityInfo):
# Downgrade Quantity to Column + unit
assert type(col2) is Column
# Class-specific attributes like `value` or `wrap_angle` are lost.
attrs = ["unit"]
compare_class = False
# Compare data values here (assert_objects_equal doesn't know how in this case)
assert np.all(col.value == col2)
assert_objects_equal(col, col2, attrs, compare_class)
@pytest.mark.parametrize("table_cls", (Table, QTable))
def test_fits_mixins_as_one(table_cls, tmp_path):
"""Test write/read all cols at once and validate intermediate column names"""
filename = tmp_path / "test_simple.fits"
names = sorted(mixin_cols)
# FITS stores times directly, so we just get the column back.
all_serialized_names = []
for name in sorted(mixin_cols):
all_serialized_names.extend(
[name] if isinstance(mixin_cols[name], Time) else serialized_names[name]
)
t = table_cls([mixin_cols[name] for name in names], names=names)
t.meta["C"] = "spam"
t.meta["comments"] = ["this", "is", "a", "comment"]
t.meta["history"] = ["first", "second", "third"]
t.write(filename, format="fits")
t2 = table_cls.read(filename, format="fits", astropy_native=True)
assert t2.meta["C"] == "spam"
assert t2.meta["comments"] == ["this", "is", "a", "comment"]
assert t2.meta["HISTORY"] == ["first", "second", "third"]
assert t.colnames == t2.colnames
# Read directly via fits and confirm column names
with fits.open(filename) as hdus:
assert hdus[1].columns.names == all_serialized_names
@pytest.mark.parametrize("name_col", list(mixin_cols.items()))
@pytest.mark.parametrize("table_cls", (Table, QTable))
def test_fits_mixins_per_column(table_cls, name_col, tmp_path):
"""Test write/read one col at a time and do detailed validation"""
filename = tmp_path / "test_simple.fits"
name, col = name_col
c = [1.0, 2.0]
t = table_cls([c, col, c], names=["c1", name, "c2"])
t[name].info.description = "my \n\n\n description"
t[name].info.meta = {"list": list(range(50)), "dict": {"a": "b" * 200}}
if not t.has_mixin_columns:
pytest.skip("column is not a mixin (e.g. Quantity subclass in Table)")
t.write(filename, format="fits")
t2 = table_cls.read(filename, format="fits", astropy_native=True)
if isinstance(col, Time):
# FITS Time does not preserve format
t2[name].format = col.format
assert t.colnames == t2.colnames
for colname in t.colnames:
compare = ["data"] if colname in ("c1", "c2") else compare_attrs[colname]
assert_objects_equal(t[colname], t2[colname], compare)
# Special case to make sure Column type doesn't leak into Time class data
if name.startswith("tm"):
assert t2[name]._time.jd1.__class__ is np.ndarray
assert t2[name]._time.jd2.__class__ is np.ndarray
@pytest.mark.parametrize("name_col", unsupported_cols.items())
@pytest.mark.xfail(reason="column type unsupported")
def test_fits_unsupported_mixin(self, name_col, tmp_path):
# Check that we actually fail in writing unsupported columns defined
# on top.
filename = tmp_path / "test_simple.fits"
name, col = name_col
Table([col], names=[name]).write(filename, format="fits")
def test_info_attributes_with_no_mixins(tmp_path):
"""Even if there are no mixin columns, if there is metadata that would be lost it still
gets serialized
"""
filename = tmp_path / "test.fits"
t = Table([[1.0, 2.0]])
t["col0"].description = "hello" * 40
t["col0"].format = "{:8.4f}"
t["col0"].meta["a"] = {"b": "c"}
t.write(filename, overwrite=True)
t2 = Table.read(filename)
assert t2["col0"].description == "hello" * 40
assert t2["col0"].format == "{:8.4f}"
assert t2["col0"].meta["a"] == {"b": "c"}
@pytest.mark.parametrize("method", ["set_cols", "names", "class"])
def test_round_trip_masked_table_serialize_mask(tmp_path, method):
"""
Same as previous test but set the serialize_method to 'data_mask' so mask is
written out and the behavior is all correct.
"""
filename = tmp_path / "test.fits"
t = simple_table(masked=True) # int, float, and str cols with one masked element
# MaskedColumn but no masked elements. See table the MaskedColumnInfo class
# _represent_as_dict() method for info about we test a column with no masked elements.
t["d"] = [1, 2, 3]
if method == "set_cols":
for col in t.itercols():
col.info.serialize_method["fits"] = "data_mask"
t.write(filename)
elif method == "names":
t.write(
filename,
serialize_method={
"a": "data_mask",
"b": "data_mask",
"c": "data_mask",
"d": "data_mask",
},
)
elif method == "class":
t.write(filename, serialize_method="data_mask")
t2 = Table.read(filename)
assert t2.masked is False
assert t2.colnames == t.colnames
for name in t2.colnames:
assert np.all(t2[name].mask == t[name].mask)
assert np.all(t2[name] == t[name])
# Data under the mask round-trips also (unmask data to show this).
t[name].mask = False
t2[name].mask = False
assert np.all(t2[name] == t[name])
def test_meta_not_modified(tmp_path):
filename = tmp_path / "test.fits"
t = Table(data=[Column([1, 2], "a", description="spam")])
t.meta["comments"] = ["a", "b"]
assert len(t.meta) == 1
t.write(filename)
assert len(t.meta) == 1
assert t.meta["comments"] == ["a", "b"]
def test_is_fits_gh_14305():
"""Regression test for https://github.com/astropy/astropy/issues/14305"""
assert not connect.is_fits("", "foo.bar", None)
def test_keep_masked_state_integer_columns(tmp_path):
"""Regression test for https://github.com/astropy/astropy/issues/15417"""
filename = tmp_path / "test_masked.fits"
t = Table([[1, 2], [1.5, 2.5]], names=["a", "b"])
t["c"] = MaskedColumn([1, 2], mask=[True, False])
t.write(filename)
tr = Table.read(filename)
assert not isinstance(tr["a"], MaskedColumn)
assert not isinstance(tr["b"], MaskedColumn)
assert isinstance(tr["c"], MaskedColumn)
def test_null_propagation_in_table_read(tmp_path):
"""Checks that integer columns with a TNULL value set (e.g. masked columns)
have their TNULL value propagated when being read in by Table.read"""
# Could be anything except for 999999, which is the "default" fill_value
# for masked int arrays
NULL_VALUE = -1
output_filename = tmp_path / "null_table.fits"
data = np.asarray([1, 2, NULL_VALUE, 4], dtype=np.int32)
# Create table with BinTableHDU, with integer column containing a custom null
c = fits.Column(name="a", array=data, null=NULL_VALUE, format="J")
hdu = BinTableHDU.from_columns([c])
hdu.writeto(output_filename)
# Read the table in with Table.read, and ensure the column's fill_value is
# equal to NULL_VALUE
t = Table.read(output_filename)
assert t["a"].fill_value == NULL_VALUE
def test_unsigned_int_dtype_propagation_for_zero_length_table():
# Regression test for gh-16501
tbl = Table(
[
Column(name="unsigned16", dtype="uint16"),
Column(name="unsigned32", dtype="uint32"),
Column(name="unsigned64", dtype="uint64"),
]
)
hdu = BinTableHDU(tbl)
tbl2 = Table.read(hdu)
assert tbl.dtype == tbl2.dtype
@pytest.mark.parametrize("table_type", [Table, QTable])
def test_zero_length_string_columns_can_be_read_into_table(table_type, tmp_path):
filename = tmp_path / "zerodtable.fits"
data = np.array([("", 12)], dtype=[("a", "S"), ("b", "i4")])
hdu = fits.BinTableHDU(data)
hdu.writeto(filename)
t = table_type.read(filename)
assert t["a"].dtype.itemsize == 0
assert t["a"].dtype == data["a"].dtype
|
astropyREPO_NAMEastropyPATH_START.@astropy_extracted@astropy-main@astropy@io@fits@tests@test_connect.py@.PATH_END.py
|
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