text string |
|---|
<filename>membranequant/autofluorescence.py<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
from scipy.ndimage.filters import gaussian_filter
import random
import glob
import scipy.odr as odr
from sklearn.metrics import r2_score
from sklearn.linear_model import LinearRegression
from .funcs import load_ima... |
<reponame>MFE5290/Hidden-Markov-Model-for-Stock-Trading
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# ### Libraries
import warnings
import numpy as np
import pandas as pd
import statsmodels.api as sm
from scipy import stats
from matplotlib import cm, pyplot as plt
from matplotlib.dates import YearLocator, MonthLoca... |
<filename>vizer.py
import torch
import numpy as np
import scipy
import librosa
import test
import os
import sys
if len(sys.argv) < 2:
print("usage: vizer.py input.mp3 [outdir]")
sys.exit(1)
infile = sys.argv[1]
if len(sys.argv) > 2:
basename = sys.argv[2]
else:
basename = os.path.splitext(os.path.ba... |
<reponame>fmqa/image-approximation
#!/usr/bin/env python3
import operator
import sys
import random
import argparse
from math import inf, sqrt
import numpy as np
from PIL import Image
from PIL.ImageOps import colorize
from scipy.cluster.vq import kmeans, whiten
def hc(cmp=operator.le):
"""Hill-climbing algorithm."... |
<reponame>jshermeyer/CometTS<filename>CometTS/CometTS.py
import os
import glob
import gdal
import rasterio
from rasterstats import zonal_stats
import numpy as np
import pandas as pd
import geopandas as gpd
import shapely.wkt
import matplotlib.pyplot as plt
from tqdm import tqdm as tqdm
import matplotlib.dates as mdates... |
import numpy as np
import pandas as pd
from scipy.stats import zscore
from qualipy.anomaly.base import AnomalyModelImplementation
class STDCheck(AnomalyModelImplementation):
def __init__(
self, config_dir, metric_name, project_name=None, arguments=None,
):
super(STDCheck, self).__init__(confi... |
<reponame>Jimmy-INL/pysensors<gh_stars>10-100
from scipy.linalg import qr
from sklearn.base import BaseEstimator
from sklearn.utils.validation import check_is_fitted
class QR(BaseEstimator):
"""
Greedy QR optimizer for sensor selection.
Ranks sensors in descending order of "importance" by applying
the... |
# (c) 2019 by Authors
# This file is a part of centroFlye program.
# Released under the BSD license (see LICENSE file)
import argparse
import os
import statistics
import subprocess
from unit_extractor import get_period_info
from utils.bio import read_bio_seq, read_bio_seqs, write_bio_seqs
from utils.os_utils import s... |
# Adopted form SfePy project, see http://sfepy.org
# Thanks to <NAME>
import numpy as nm
import os
import os.path as op
import fnmatch
import shutil
from .base import output, Struct, basestr
try:
import tables as pt
except:
pt = None
class InDir(Struct):
"""
Store the directory name a file is in, an... |
"""
Module for customising opensim segmented muscle points
"""
import os
import numpy as np
import copy
from gias2.fieldwork.field import geometric_field
from gias2.fieldwork.field.tools import fitting_tools
from gias2.common import transform3D
from gias2.registration import alignment_fitting as af
from gias2.musculos... |
<filename>vis_imagine_static_voxels/utils/imports.py
import math
import tensorflow as tf
import numpy as np
from scipy.misc import imsave, toimage
import scipy.stats as st
from os import makedirs
from os.path import exists, join
import pickle
import constants as const
import os
from PIL import Image, ImageFont, ImageDr... |
<gh_stars>0
""" Implementation of Cosmic RIM estimator"""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
physical_devices = tf.config.experimental.list_physical_devices('GPU')
world_size = len(physical_devices)
print("\nphysical_devi... |
"""
Linear_Regession.py
Written by <NAME> and <NAME>, Last Edit: 1/27/17
Purpose: Calculate the calibration curves via linear regression of the calibration data
Input:
1) cal_data_file: data file containing the calibration data
2) output_dir: where to save the output results
Note that the script will look for the ca... |
import sys
import os
import time
import numpy as np
from scipy.special import erf
from scipy.optimize import minimize
from fortesfit import FortesFit_Settings
from fortesfit import FortesFit_Filters
from fortesfit import FortesFit_ModelManagement
""" A module with functions that are used by the model fitting routi... |
import numpy as np
import argparse
from scipy import io
from sklearn.metrics import confusion_matrix
parser = argparse.ArgumentParser(description="ESZSL")
parser.add_argument('-data', '--dataset', help='choose between APY, AWA2, AWA1, CUB, SUN', default='AWA2', type=str)
parser.add_argument('-mode', '--mode', help='t... |
<filename>rmgpy/molecule/utilTest.py
import unittest
from scipy.special import comb
from .util import *
class PartitionTest(unittest.TestCase):
def test_singleton(self):
"""
Test that a index not part of the parameter list, results in a key-value pair with
an empty list.
"""
... |
import numpy as np
from scipy.stats import norm
# Obtains sum of normal distributions given centers and spreads and returns PMF
def normal_sum_pmf(min_val, max_val, centers, spreads):
assert len(centers) == len(spreads)
ret = np.zeros((max_val - min_val + 1))
for i in range(len(centers)):
r... |
<reponame>asathiya007/nba-crowdsourcing-comparisons
# import modules
from basketball_reference_utils import get_random_pair
from machine_learning import (construct_dataset, FEATURES, DEFAULT_HOLDOUT,
RF_MAX_DEPTH, RF_NUM_EST, RF_MAX_FEATURES)
import os
import pandas as pd
from predict_better_player import predict_... |
import pytest
import sys
sys.path.insert(0,"..")
import autogenes as ag
import numpy as np
import pandas as pd
import anndata
from sklearn.svm import NuSVR
from sklearn import linear_model
from scipy.optimize import nnls
def test_unpack_bulk():
unpack_bulk = ag.main._Interface__unpack_bulk
arr = np.ones((3,))... |
<filename>model.py
import bz2
import pickle
import _pickle as cPickle
import os
import time
import pandas as pd
import numpy as np
from tqdm import tqdm
tqdm.pandas(desc="progress-bar")
from gensim.models import Doc2Vec
from sklearn import utils
from sklearn.model_selection import train_test_split
import gensim
from s... |
'''
Astro.IQ - Trajectory
<NAME>
<EMAIL>
https://cisprague.github.io/Astro.IQ
'''
''' --------
Dependencies
-------- '''
from numpy import *
from scipy.integrate import odeint
import matplotlib.pyplot as plt
set_printoptions(suppress=True)
from ML import MLP
import os
from numba import jit
import tensorflow
''' -----... |
<gh_stars>0
# %% [markdown]
# # THE MIND OF A MAGGOT
# %% [markdown]
# ## Imports
import os
import time
import warnings
import colorcet as cc
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.transforms as transforms
import numpy as np
import pandas as pd
import seaborn as sns
from anytree im... |
"""Bayesian estimation for two groups
This module implements Bayesian estimation for two groups, providing
complete distributions for effect size, group means and their
difference, standard deviations and their difference, and the
normality of the data.
Based on:
<NAME>. (2012) Bayesian estimation supersedes the t
... |
<reponame>NamelessCoder/fermentrack
# Tilt Hydrometer Tilt polling library
# <NAME> 22/01/2017
# <EMAIL>
#
# Version: 1.5 - Bug fix for debugging log and also adding connection resilliance. Will now reset
# bluetooth connection if dropped for any reason.
# Version: 1.4 - Added additional resiliance and ... |
<gh_stars>1-10
import numpy as np
from scipy import misc
import os
import scipy.io
from PIL import Image
def filter(base_root, config, crops_list='crops_LiTS_gt.txt', input_config='masked_out_lesion', results_list='detection_lesion_example', th=0.5):
# crops_list = base_root + 'utils/crops_list/' + crops_list
... |
<reponame>da5nsy/SAPS<gh_stars>0
#input between 0 and 1 converted to normalised linearized output, with respect to polynomial factors
import numpy as np
import cmath
from scipy import interpolate
def linz(input):
red= [1.127339114,-0.163569181,0.017654147]
green= [1.107403255,-0.138534706,0.009456395... |
import numpy #for numpy storage
import os #to find files
import time #for time to complete
from sklearn.ensemble import RandomForestClassifier
import pickle
from statistics import mean
start = time.time()
#Import Training Data & Labels
odata = numpy.load("Data/20ImpTrainingData.npy")
data = odata.reshape(9826,(3*3*78)... |
#!/usr/bin/python
#-*- coding: utf-8 -*-
"""
This script deals with embedding creation from sentences and
generation of offsets between pairs of norms.
"""
import logging
logger = logging.getLogger(__name__)
logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.INFO)
import argparse
im... |
"""
Models a simple photon travelling through 2D space and reflecting off circular mirrors at specific positions.
"""
from math import floor, ceil
from typing import Generator, Tuple, List
from sympy import Rational
from sympy.geometry import Point, Ray, Circle, intersection
from .turtle_helpers import *
class Pho... |
<reponame>Phionx/quantumnetworks
"""
Unittests
Run using:
python -m unittest tests/test_multimode.py
"""
import os
import sys
import unittest
sys.path.insert(0, ".." + os.sep)
from quantumnetworks import SingleModeSystem, DoubleModeSystem, MultiModeSystem
from scipy.integrate import odeint
import numpy as np
clas... |
<reponame>wmvanvliet/psychic
import numpy as np
from .basenode import BaseNode
from ..dataset import DataSet
from ..utils import get_samplerate
from ..trials import erp, baseline, concatenate_trials, slice
from scipy import linalg
class EOGCorr(BaseNode):
def __init__(self, mdict, heog='hEOG', veog='vEOG', reog='... |
"""
(c) 2011, 2012 Georgia Tech Research Corporation
This source code is released under the New BSD license. Please see
http://wiki.quantsoftware.org/index.php?title=QSTK_License
for license details.
This package is an implementation of a novel improvement to KNN which
speeds up query times
"""
import math,random,sys... |
<reponame>velocist/TS4CheatsInfo
# uncompyle6 version 3.7.4
# Python bytecode 3.7 (3394)
# Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)]
# Embedded file name: T:\InGame\Gameplay\Scripts\Server\event_testing\common_event_tests.py
# Compiled at: 2020-08-07 22:38... |
r"""
===============================================================================
Submodule -- molar_density
===============================================================================
"""
import scipy as sp
def standard(phase,
pore_MW='pore.molecular_weight',
pore_density='pore.dens... |
<reponame>cactaur/astropy-utils
import astropy.units as u
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import uniform
def list_sorted(lst, ascending=True):
'''Checks to see if the given list is sorted.
Function returns true or false depending on if the list is sorted. It by
default... |
"""
coral_model v3 - hydrodynamics
@author: <NAME>
@contributor: <NAME>
"""
import sys
import numpy as np
import os
from scipy.optimize import fsolve
import faulthandler
import bmi.wrapper
faulthandler.enable()
# class Hydrodynamics:
# """Interface for all hydrodynamic model modes."""
# __model = None
# ... |
import pickle
import json
from tqdm import tqdm
import configparser
from scipy import spatial
import numpy as np
import os
from os import sys, path
import random
# sys.path.append(path.dirname(path.dirname(path.abspath(__file__))))
# from embeddings.TransE import *
config = configparser.ConfigParser()
config.read(... |
#!/usr/bin/env python3
import sys
import random
from fractions import Fraction
N = int(sys.argv[1])
m = int(sys.argv[2])
sigma = float(sys.argv[3])
assert m < N
random.seed(int(sys.argv[-1]))
R = random.randint(N+1, 5*N)
def rand():
s = '%0.6f' % (1-abs(random.gauss(0, sigma)))
return Fraction(s)
print('%d %... |
import numpy as np
import scipy.sparse as sp
import time
import scipy.linalg as la
class CLPerceptron():
S_X = np.array([[0, 1], [1, 0]], dtype=complex)
S_Y = np.array([[0, complex(0, -1)], [complex(0, 1), 0]], dtype=complex)
S_Z = np.array([[1, 0], [0, -1]], dtype=complex)
S = np.array([S_X, S_Y, S_Z... |
import os
import copy
import torch
from tensorboardX import SummaryWriter
import time
import glob
import re
import h5py
import datetime
import argparse
import csv
import math
from pathlib import Path
import torch.distributed as dist
from pcdet.datasets import build_dataloader
from pcdet.models import build_network
from... |
import pandas as pd
import numpy as np
from scipy import interpolate
from scipy.optimize import curve_fit, root_scalar
import json
try:
import matplotlib.pyplot as plt
except:
pass
from ._emulator import Emulator
def build_emulator(
file_PV_loops,
period,
file_EDPV = None,
cycle... |
<reponame>patmloi/PalettePal
from PIL import Image
import numpy as np
from scipy.cluster.vq import whiten, kmeans
import pandas as pd
from typing import Union, Literal, Tuple, List
def getTextColours(paletteColours: list) -> List[tuple]:
textColourOptions = [(255, 255, 255), (0, 0, 0)]
textColours = []
... |
<reponame>ashayp22/Logistic-Regression-with-MNIST<filename>model.py
#imports
from mnist import MNIST
import random
import numpy as np
from numpy import *
import matplotlib.pyplot as plt
import tkinter as tk
import math
import time
import csv
import scipy
from scipy import optimize
from scipy.optimize import... |
<filename>lenstronomywrapper/LensSystem/LensSystemExtensions/solver.py
import numpy as np
from lenstronomy.LensModel.lens_model import LensModel
from scipy.optimize import minimize
from lenstronomywrapper.LensSystem.LensSystemExtensions.solver_functions import _solve_one_image, _source_plane_delta
from lenstronomywrap... |
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import numpy as np
from ogb.lsc.pcqm4m_pyg import PygPCQM4MDataset
from rdkit import Chem
import rdkit.Chem.AllChem as AllChem
import joblib
import numpy as np
import math
from scipy.spatial.distance import cdist
# ===============... |
<filename>IRtrack.py
# Copyright 2018 QIMR Berghofer Medical Research Institute
#
import os
import glob
import types
from collections import Sequence, namedtuple
import numpy as np
import scipy.io as sio
import cv2 as cv
class Error(Exception):
pass
def normFrame(data):
"""Convert floating poi... |
"""
Itt van az összes olyan felhasznált funkció, amit külön letöltött csomagban definiáltak.
"""
import cv2, imageio, numpy, PIL, pytest, scipy, skimage, shapely.geometry, termcolor, keras, tensorflow
# valamiért nem működik
# import matplotlib
# formában
from matplotlib.pyplot import subplots, show, ion, cla, figure,... |
import mesh_to_sdf
import matplotlib.pyplot as plt
from drawnow import drawnow
import numpy as np
import argparse
import pickle
import trimesh
from klampt.io import resource
from scipy.spatial.transform.rotation import Rotation
import os
import sys
sys.path.append("./3rdparty/bop_toolkit")
sys.path.append("./3rdparty/b... |
<filename>lib/pysgpp/extensions/datadriven/uq/analysis/Analysis.py
# !/usr/bin/python
# Copyright (C) 2013 Technische Universitaet Muenchen
# This file is part of the SG++ project. For conditions of distribution and
# use, please see the copyright notice at http://www5.in.tum.de/SGpp
#
from pysgpp.extensions.datadriven... |
from __future__ import print_function, division
from six import string_types, iteritems
import numpy as np
from scipy.sparse import csr_matrix
from openmdao.api import ExplicitComponent
from dymos.phases.grid_data import GridData
from dymos.utils.misc import get_rate_units
class ODERateComp(ExplicitComponent):
... |
"""conftest.py - pytest local plugins and fixtures"""
from contextlib import contextmanager
from distutils.version import StrictVersion
import os
import sys
import matplotlib as mpl
import numpy as np
import scipy as sp
import pytest
import control
TEST_MATRIX_AND_ARRAY = os.getenv("PYTHON_CONTROL_ARRAY_AND_MATRIX"... |
<reponame>DamienIrving/climate-analysis<filename>data_processing/calc_vrot.py<gh_stars>10-100
"""
Filename: calc_vrot.py
Author: <NAME>, <EMAIL>
Description: Calculate the meridional wind for a rotated coordinate system
"""
# Import general Python modules
import sys, os, re, pdb
import argparse
import num... |
import sys
from os.path import isfile, isdir, join
from os import makedirs, listdir, remove
import shutil
import numpy as np
import numpy.linalg as la
import json
from scipy.optimize import linear_sum_assignment
from tqdm import tqdm
MAX_RANGE = 300
dataset_dir = sys.argv[1]
assert isdir(dataset_dir), dataset_dir
pri... |
<filename>dendroplot/plotting/pltprops.py
#!/usr/bin/env python
import numpy as np
from numpy.random import randint
from scipy import stats
from scipy import odr
import os
from os.path import join
import re
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
from astropy import units as u
from astro... |
"""
Compute pattern correlation between images
Reference : Kay et al. (2015, BAMS)
Author : <NAME>
Date : 24 November 2020
"""
### Import modules
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as sts
import read_LENS as LL
import calc_Utilities as UT
import seaborn as sns
from seaborn_q... |
"""
volreader.py
Author: <NAME>
Utilities for reading 3D volumetric data as a 3D OpenGL texture.
"""
import os
import numpy as np
from PIL import Image
import OpenGL
from OpenGL.GL import *
from scipy import misc
def loadVolume(dirName):
"""read volume from directory as a 3D texture"""
# list images in di... |
import sys
#this is for qt5, which didn't want to compile
#from PyQt5.QtWidgets import QDialog, QApplication, QPushButton, QVBoxLayout, QLineEdit, QLabel, QFileDialog, QHBoxLayout, QFrame, QGridLayout
#from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
#for qt4 try this
from PyQt4.QtGui i... |
<reponame>ahthaide/Rasch_Model<gh_stars>0
# imports
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import spearmanr, pearsonr
from sklearn import datasets, linear_model, metrics
import pandas as pd
import pickle
data = pd.read_csv('difficulty_.csv')
# defining feature inputs and outp... |
<gh_stars>1-10
# Copyright 2021 <NAME>. All Rights Reserved.
#
# 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 applica... |
import pandas as pd
import numpy as np
from scipy.interpolate import interp1d
def loadWind(filename, interp_kind='linear'):
df = pd.read_csv(filename)
altitudes = np.array(df['altitude'])
# 風のu, vの方向
# U: 西→東に吹く風を正
# V: 南→北を正
wind_u = np.array(df['wind_u'])
wind_v = np.array(df['wind_v'])
... |
#### -——————————————— Zoom-PPG ———————————————— ####
#### —————————————————————————————————————————— ####
#### /\ /\ /\ /\ /\ /\ ####
#### / \/\ / \ /\/ \ / \ /\ / \/ \ ####
#### \/ \/ \/ \/ \/ \ ####
#### —————————————————————————————————————————— ####
##... |
import functools
import logging
import typing
import numpy as np
import pandas as pd
from pandas.api.types import is_numeric_dtype
import scipy.sparse
import sklearn.utils
from sklearn import preprocessing
from sklearn.base import BaseEstimator
from sklearn.compose import make_column_transformer
from sklearn.except... |
<filename>retailbox/implicit_als.py
import pandas as pd
import scipy.sparse as sparse
import numpy as np
from scipy.sparse.linalg import spsolve
def implicit_weighted_als(training_set, lambda_val = 0.1, alpha = 40, iterations = 10, rank_size = 20, seed = 0):
conf = (alpha*training_set)
num_user = conf.sh... |
import pkg_resources
try:
pkg_resources.get_distribution('numpy')
except pkg_resources.DistributionNotFound:
numpyPresent = False
print("Error: Numpy package not available.")
else:
numpyPresent = True
import numpy as np
try:
pkg_resources.get_distribution('pandas')
except pkg_resources.Distri... |
<reponame>williamhowardsnyder/OnClass
import numpy as np
import os
#Pytorch
import torch
import torch.nn as nn
import torch.nn.functional as F
import sys
from scipy.special import softmax
import time
import math
from sklearn.metrics import roc_auc_score, average_precision_score
from scipy import stats
from torch.nn.m... |
<gh_stars>1-10
from operator import index
import os
import sys
sys.path.append(".")
from torchvision.transforms.functional import scale
import torchvision.transforms.functional as TF
from utils import class_array_histogram_equalization,split_path
import numpy as np
import torch
from torch.utils.data import DataLoader,... |
import subprocess
import numpy as np
from matplotlib import pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import itertools
import os
from scipy import stats
import csv
SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
PROJECT_DIR = os.path.dirname(SCRIPT_DIR)
DATA_PATH = os.pat... |
<filename>Chapter09/Edge_detection_Kernel.py
#Edge dection kernel
#Built with SciPy
#Copyright 2018 <NAME> MIT License. READ LICENSE.
import matplotlib.image as mpimg
import numpy as np
import scipy.ndimage.filters as filter
import matplotlib.pyplot as plt
#I.An edge dectection kernel
kernel_edge_detection = np.array... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 4 16:48:57 2018
keyframes extract tool
this key frame extract algorithm is based on interframe difference.
The principle is very simple
First, we load the video and compute the interframe difference between each frames
Then, we can choose one of these thre... |
import datamaker
import time
import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import pyplot
import matplotlib as mpl
from statistics import mean
plt.style.use('seaborn-whitegrid')
max_reps = 100 # How many iterations-Measurements of Spectrum
frequencies = [2.407,2.412,2.417,2.422,2.427,2... |
import os
import random
import sys
from scipy import misc
from data.abstract.data_set import DataSet
class Inputs(DataSet):
def __init__(self, config):
DataSet.__init__(self)
self.config = config
self.training_set.x = []
self.validation_set.x = []
self.testing_set.x = []
... |
<reponame>alex-w/vplanet
import numpy as np
import matplotlib.pyplot as plt
import vplot as vpl
import sys
import scipy.signal as sig
import subprocess
# Check correct number of arguments
if (len(sys.argv) != 2):
print('ERROR: Incorrect number of arguments.')
print('Usage: '+sys.argv[0]+' <pdf | png>')
exi... |
import scipy
import scipy.stats as ss
import numpy as np
import pandas as pd
import random
import math
import sys
import sklearn.decomposition as decomp
import sklearn.linear_model as linear_model
import sklearn.datasets as sk_data
from sklearn.preprocessing import StandardScaler
import numpy.linalg as nla
import sklea... |
<reponame>xrick/Lcj-DSP-in-Python<gh_stars>0
import numpy as np
import wave
from scipy.io.wavfile import read, write
import struct
import scipy.signal as signal
def downsampling( x, method = 1 ):
N = int( len( x ) / 2 )
y = np.zeros( N )
if method == 1: # Decimation
for n in range( N ):
y[n] = x[2*n]
... |
# Author: <NAME> <<EMAIL>>
from itertools import product
from math import floor
import os
from warnings import catch_warnings, filterwarnings
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose
import pickle
import pytest
from pytest import approx
import scipy.io
from eelbrain import (
... |
"""
Train and validate the RNN approach
Author: <NAME>
"""
from __future__ import division, print_function, absolute_import
import random
from datetime import datetime
from os import listdir, makedirs
import numpy as np
from scipy.io import loadmat, savemat
from sklearn.linear_model import LogisticRegression
from skl... |
## Runs biophysical simulations of MF-GC network
# Designed to write files to be run in parallel
# on a server or cluster, but can also be used to run
# individually
# python run_mf_grc_network.py runID sigma NADT
# Generates xml and nml files for model, saved in tempdata
# To simulate, switch run to True, spike times... |
"""
This is a simple application for sentence embeddings: semantic search
We have a corpus with various sentences. Then, for a given query sentence,
we want to find the most similar sentence in this corpus.
This script outputs for various queries the top 5 most similar sentences in the corpus.
"""
from sentence_trans... |
<reponame>daniellehot/ROB10
#!/usr/bin/env python3
import sys
import copy
import rospy
import math
import numpy as np
import time
import open3d as o3d
import cv2
import random
import sys, signal
from scipy.spatial.transform import Rotation as R
#import actionlib
import geometry_msgs.msg
from geometry_msgs.msg import P... |
<filename>Demos/pi0_spectra.py
###############################################################
# Reconstruct the pi0 mass peak using ND MC in h5 files
#
# @
#
###############################################################
# Includes
import sys
# PandAna import
from pandana.core import... |
<gh_stars>1-10
#!/usr/bin/env python3
"""Train with 1000"""
from __future__ import annotations
import argparse
import functools
import logging
import pathlib
import random
import typing
import albumentations as A
import cv2
import horovod.tensorflow.keras as hvd
import numpy as np
import scipy
import sklearn.metrics
... |
<gh_stars>1-10
#Implementation of Kmeans from scratch and using sklearn
#Loading the required modules
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.datasets import load_digits
from sklearn.decomposition import PCA
from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_sco... |
# -*- coding: utf-8 -*-
"""
Ionospheric delay analysis module
"""
import logging
log = logging.getLogger(__name__)
import numpy as np
import os
import re
from scipy.interpolate import RegularGridInterpolator
from arepytools.geometry.conversions import xyz2llh
from sct.support.geometry_extended import find_ellipso... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Fri Jul 28 17:39:02 2017
@author: gawe
"""
#import scipy as _scipy
from scipy.special import jvp
import numpy as _np
import os as _os
import matplotlib.pyplot as _plt
from pybaseutils import speed_of_light
import cmath
#
#from matplotlib.patches import Ellipse
... |
<reponame>mihnea-chirila/gemx
# Copyright 2019 Xilinx, Inc.
#
# 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 ... |
<gh_stars>0
from __future__ import division
from __future__ import print_function
"""
This file serves as an example of how to
a) select a problem to be solved
b) select a network type
c) train the network to minimize recovery MSE
"""
import numpy as np
import os
import time
import tensorflow as tf
from... |
#MCCA (Multiview Canonical Correlation Analysis)
import numpy as np
from scipy import linalg as lin
from sklearn.preprocessing import StandardScaler
class MCCA:
def __init__(self,n_components=2,reg_param=0.01):
self.n_components = n_components
self.reg_param = reg_param
self.dimen =... |
# -*- coding: utf-8 -*-
"""
A module containing a number of functions used for performing common
optical calculations
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.constants as const
import seaborn as sns
sns.set_style('whitegrid')
def diff_limited_spot(wavelength, f,D):
... |
<filename>backend/app/database/Lumerical.py<gh_stars>1-10
from app.database.db import db
import mongoengine_goodjson as gj
import pandas as pd
import numpy as np
from decimal import Decimal
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import PolynomialFeatures
from sympy.solvers i... |
<gh_stars>0
""" FILE: main_MSE_EX2.py
Script performing exemplary solution of the Volterra kernel reconstruction
problem for the simplified optoacoustic problem on the beam-axis assuming a
Gaussian irradiation source profile, see Eq. (40) in section 1.3 "Diffraction
of laser-excited acoustic pulses" in the article
... |
import os
import pickle
import numpy as np
import PIL.Image
import dnnlib
import dnnlib.tflib as tflib
import config
import scipy
def main():
tflib.init_tf()
# Load pre-trained network.
# url = 'https://drive.google.com/uc?id=1MEGjdvVpUsu1jB4zrXZN7Y4kBBOzizDQ'
# with dnnlib.util.open_url(url, cache_d... |
<filename>assignment3/utils.py
import numpy as np
import pandas as pd
#################### choosing number of k for clustering ################################
def elbow_method(k_list, X, random_state_list, save=False, filename=None, **kmeans_kwargs):
"""
choose number of K for k-means clustering usi... |
#!/usr/bin/env python
#
# Copyright 2017 Fraunhofer Institute for Manufacturing Engineering and Automation (IPA)
#
# 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/li... |
import scipy.sparse as sps
import numpy as np
from tqdm import tqdm
from utils.pre_processing import norm_max_row
def transitivity_boost(sim):
sim_col = sps.csc_matrix(sim)
print("Similarity shape: " + str(sim.shape))
for row in tqdm(range(sim.shape[0])):
data_row = sim.data[sim.indptr[row]:sim.i... |
'''
This function calculates the kinetic energy of the structure controlled by a direct velocity feedback in series with an electronic compensator.
'''
from dtApp.dtData.soton_twin import Soton_twin_data
import numpy as np
import scipy.linalg as la
import control.matlab as ctrmat
from plotly.subplots import make_subplo... |
from typing import Tuple
import numpy as np
import globals as g
from data_preprocessing.physionet_data_loader.load_physionet_dataset import get_data
from scipy.io import loadmat
class BCI2aIVDataLoader:
"""
A BCI2aIVDataLoader object does the data loading and returns it as a python object.
"""
def __... |
#!/usr/bin/python -tt
from collections import defaultdict
from math import fabs, log
from numpy import array
import scipy.cluster.vq as scipy
import argparse
DEFAULT_VOWELS = set(['a','e','i','o','u','A','E','I','O','U'])
FREQUENCY_PROPORTION_LOWERBOUND = 0.0000001
GLOBAL = "GLOBAL"
LOCAL = "LOCAL"
ANTILOCAL = "ANTIL... |
from __future__ import division, print_function, absolute_import
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse.linalg import eigsh, inv
from numpy.linalg import norm, eig
from scipy.linalg import eigh
from itertools import product
from typing import Union
class framework(object):
"""B... |
<filename>ivf/core/sparse_interpolation/bilateral_normal_smoothing.py
# -*- coding: utf-8 -*-
## @package ivf.cmds.sparse_interpolation.bilateral_normal_smoothing
#
# ivf.cmds.sparse_interpolation.bilateral_normal_smoothing utility package.
# @author tody
# @date 2016/02/03
import numpy as np
from skle... |
#!/usr/bin/env python
# Copyright (C) 2017 Udacity Inc.
#
# This file is part of Robotic Arm: Pick and Place project for Udacity
# Robotics nano-degree program
#
# All Rights Reserved.
# Author: <NAME>
# IK_server.py
# Server script for controlling KUKA robotic arm in pick-and-place simulation.
# Service takes ... |
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