text string |
|---|
import os
import csv
import math
import random
from scipy import ndimage #allows to import image as RGB instead of CV2's BGR
import numpy as np #because keras needs images as numpy arrays
from matplotlib import pyplot as plt
from PIL import Image
import cv2
# This function gathers sets of images and corresponding stee... |
import numpy as np
from scipy import sparse
from scipy.sparse.linalg import lobpcg
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch_sparse import spmm
from torch_geometric.utils import get_laplacian
import torch_geometric.transforms as T
# from ogb.nodeproppred import PygNodePropPredDataset... |
<filename>hmc/solvers.py
"""Solvers for non-linear systems of equations for implicit integrators."""
from hmc.errors import ConvergenceError
import numpy as np
import scipy.linalg as sla
def euclidean_norm(vct):
"""Calculate the Euclidean (L-2) norm of a vector."""
return np.sum(vct**2)**0.5
def maximum_no... |
from __future__ import absolute_import,print_function
from . import _ground_truth as __ground_truth
from ._ground_truth import *
import numpy
from scipy import ndimage as ndi
__all__ = []
for key in __ground_truth.__dict__.keys():
__all__.append(key)
try:
__ground_truth.__dict__[key].__module__='nift... |
<gh_stars>0
import argparse
import glob
import os
import sys
import numpy as np
import scipy.ndimage.measurements as measurements
import scipy.ndimage.morphology as morphology
import torch
import torch.nn as nn
import torch.optim
from torch.utils.data import DataLoader
from util.util import enumerateWithEstimate
fr... |
# Copyright (c) 2011, <NAME> [see LICENSE.txt]
# This software is funded in part by NIH Grant P20 RR016454.
# Python 2 to 3 workarounds
import sys
if sys.version_info[0] == 2:
_strobj = str
_xrange = xrange
elif sys.version_info[0] == 3:
_strobj = str
_xrange = range
import collections
import csv
im... |
#!/usr/bin/env python3
import argparse
from pathlib import Path
parser = argparse.ArgumentParser(
description="Run the watershed algorithm to produce segmented regions in an orthomosaic. Or run watershed with multiple overlapping segmented regions."
)
parser.add_argument(
"ortho", help="the path to the orthomo... |
<gh_stars>0
import numpy as np
import os.path
import scipy
import argparse
import scipy.io as sio
import matplotlib
import matplotlib.colors as colors
import matplotlib.cm as cmx
import matplotlib.pyplot as plt
import sys
import cv2 as cv
from skimage import data,filters,segmentation,measure,morphology,color... |
<reponame>Silenc3IsGold3n/RS3GEPredictionModel
import time
import sqlite3
import pandas as pd
import numpy as np
import scipy as sp
from scipy import stats
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt
traindataframes = []
testDataFrame = []
#this defines how many items we are looking at
#max = 20
pr... |
<reponame>RichardScottOZ/geoapps
import numpy as np
from scipy.interpolate import LinearNDInterpolator
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
from scipy.spatial import cKDTree
from scipy.interpolate.interpnd import _ndim_coords_from_arrays
from matplotlib.colors import LightSource, Norma... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tuesday 12 Dec 23:39:53 2017
@author: <NAME> & <NAME>
"""
# Import libralies
import csv
import serial
import time
import matplotlib.pyplot as plt
from scipy import signal
from scipy import stats
import seaborn as sns
import numpy as np
import smtplib
from email.MIM... |
<filename>mmd/utils/davidson.py
import numpy as np
import scipy
def davidson(A,roots,tol=1e-8):
mat_dim = A.shape[0]
sub_dim = 4*roots
V = np.eye(mat_dim,sub_dim)
converged = False
while not converged:
# subspace
S = np.dot(V.T,np.dot(A,V))
# diag subspace
E,C =... |
# IMPORTS
import itertools as it
from typing import Union
import numpy as np
import openpyxl as xl
import os
import pandas as pd
import scipy.interpolate as si
import scipy.linalg as sl
import scipy.signal as ss
import sympy as sy
import time
# CLASSES
class LinearRegression:
"""
Obtain the regression coef... |
<gh_stars>1-10
import os
import glob
import pickle
import re
import pymc
import ConfigParser
config = ConfigParser.RawConfigParser()
# Our numerical workhorses
import numpy as np
import pandas as pd
import scipy
# Import the project utils
import sys
sys.path.insert(0, '../')
import NB_sortseq_utils as utils
# Impor... |
<filename>play.py<gh_stars>1-10
from numpy import *
from scipy import fft
from scipy.io.wavfile import write
import os
output_file = "test.wav"
samples_per_sec = 44100
time = 1.5 # s
samples_total = samples_per_sec*time
t = linspace(0, time, samples_total)
def tone(f):
omega = 2*pi*f # RAD/s
signal = exp(-0.... |
"""
Test Cython optimize zeros API functions: ``bisect``, ``ridder``, ``brenth``,
and ``brentq``, in `scipy.optimize.cython_optimize`, by finding the roots of a
3rd order polynomial given a sequence of constant terms, ``a0``, and fixed 1st,
2nd, and 3rd order terms in ``args``.
.. math::
f(x, a0, args) = ((args[... |
<gh_stars>0
# function that makes last pre-process step to images, preparing data for training the CNNs
import numpy as np
import tensorflow as tf
import cv2
from scipy.fftpack import dct
class custom_image_normalizer():
def normalize(self, local_image_rgb):
local_image_rgb = cv2.cvtColor(local_image_rgb... |
<filename>comancpipeline/Analysis/AstroCalibration.py
import concurrent.futures
import numpy as np
from comancpipeline.Analysis import BaseClasses
from comancpipeline.Analysis import Calibration
from comancpipeline.Tools import WCS, Coordinates, Filtering, Fitting, Types, ffuncs, binFuncs, stats, CaliModels
from scipy... |
<reponame>nykabhishek/motion-planning
import networkx as nx
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import distance_matrix
import time
from itertools import chain
from tsp_heuristics.christofides import Christofides
def frederickson(adj_matrix, vehicles, depot):
tsp_tour, tsp_nodes, t... |
import scipy.misc as scimisc
from tkinter import *
from PIL import Image
from PIL import ImageTk
import MalmoPython
import os
import sys
import time
import random
import json
import numpy as np
import time
import gym
import gym_minecraft
from gym.wrappers import Monitor
class MinecraftWrapper(gym.Wrapper):
def... |
<reponame>vr25/long_doc<gh_stars>0
from scipy.sparse import csr_matrix
import collections
from sklearn.metrics import mean_squared_error, r2_score, mean_absolute_error
from sklearn.model_selection import train_test_split, cross_val_score, cross_val_predict
from sklearn import metrics
from multiscorer import MultiScorer... |
import os
import numpy as np
import pandas as pd
import random
from glob import glob
from scipy.io import wavfile
from scipy.signal import stft
from sklearn.model_selection import train_test_split
from keras.utils import to_categorical
class DatasetGenerator():
def __init__(self, label_set,
... |
import numpy as np
from scipy.special import loggamma, gammaln, gamma
from matplotlib import pyplot as plt
from scipy.optimize import minimize
from scipy.optimize import root
from mpl_toolkits import mplot3d
np.seterr(divide = 'raise')
logmoments = np.load("logmoments_Harmonic_4.npy")
moments = np.load("momen... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
<NAME> @ 2017
Implements a simulation of a titration, for a system of two main components,
N species and N-1 equilibrium constants.
Some species (composed usually of a combination of a metal (M) and of a ligand (L),
with a given UV-VIS spectrum) are contained in a flask. Mor... |
<gh_stars>0
#######################################################################
# Copyright (C) 2016 <NAME> (<EMAIL>) #
# Permission given to modify the code as long as you keep this #
# declaration at the top #
#################################################... |
from numpy import pi
import numpy as np
import math
#from sympy import Matrix
import pylab
#import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
#from scipy.interpolate import Rbf
import pickle
from scipy.sparse import csr_matrix
from scipy.sparse import lil_matrix
from scipy.sparse.linalg import sps... |
<reponame>amikey/audio_scripts
#!/Users/tkirke/anaconda/bin/python
# -*- coding: utf-8 -*-
import re,sys,os
from math import sqrt,log,pi,sin,cos,atan2,floor
import cmath
from scipy import signal,fft
import numpy
# Quinn's method in
# <NAME>, "Estimating Frequency by Interpolation Using Fourier
# Coefficients," IEEE T... |
<filename>src/lib/regression.py<gh_stars>0
#!/usr/bin/env python3
import numpy as np
import scipy.linalg
import numba as nb
import copy as cp
try:
import lib.metrics as metrics
except ModuleNotFoundError:
import metrics
__all__ = ["OLSRegression", "RidgeRegression", "LassoRegression"]
@nb.jit(nopython=Tru... |
#%%
"""
Created on July 05 2021
The Heston-Hull-White model and pricing European Options with Monte Carlo and the COS method
This code is purely educational and comes from "Financial Engineering" course by <NAME>
The course is based on the book “Mathematical Modeling and Computation
in Finance: With Exercises ... |
<filename>results.py
from collections import defaultdict
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy.stats import hypergeom
from sklearn.metrics import roc_auc_score, roc_curve
from statsmodels.nonparametric.smoothers_lowess import lowess
GROUP_NAMES = {
'Group_I_Introns': 'G... |
import argparse
import collections
import sys
import math
import cPickle as pickle
from StringIO import StringIO
import scipy
import scipy.stats
import sexpdata
import matplotlib
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from matplotlib.backends import backend_pdf
from sklearn.neural_net... |
#! /usr/bin/env python
# Write a CSV with meta data for each patch.
#### ---- Imports & Dependencies ---- ####
import sys
import os
import argparse
import csv
from configparser import ConfigParser
import pathlib
from glob import glob
from random import shuffle
import SimpleITK as sitk # pip install SimpleITK
from tqd... |
<gh_stars>0
import unittest
from scipy import stats
from src.simulation import *
# do not change, resources were generated using this values
POPULATION_SIZE = 100000
FREQ_A1 = 0.8
FREQ_B1 = 0.3
D = 0.01
BETA_A = 0.3
BETA_B = 0.2
class TestSimulations(unittest.TestCase):
def test_get_haplotypes_probabilities(se... |
from __future__ import absolute_import, print_function
import os
import sys
import numpy as np
from scipy import ndimage
sys.path.append('./')
import nibabel
import random
import SimpleITK as sitk
import pdb
def border_map(binary_img,neigh):
"""
Creates the border for a 3D image
"""
binary_map = np.asar... |
import numpy as np
import tensorflow as tf
from scipy import sparse as sp
from tensorflow.python.ops import gen_sparse_ops
from . import ops
def sp_matrix_to_sp_tensor(x):
"""
Converts a Scipy sparse matrix to a SparseTensor.
:param x: a Scipy sparse matrix.
:return: a SparseTensor.
"""
if le... |
from sympy import *
import math
def fixed_point_iter(phi, x_0, max_steps=25, verbose=False):
"""不动点迭代
Args:
phi: function, 迭代函数
x_0: float, 初值
max_steps: int, 最大迭代次数
verbose: bool, 打印出每一步的值，default False.
Returns:
x_final: float, 最终的近似根 x
"""
x = x_0
... |
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import gdal
import numpy as np
import geodepy.Height_filenames as Height_filenames
from scipy.interpolate import griddata
def mean_normal_grav(Lat,h):
# GRS 80 constants
a=6378137
b=6356752.3141
omega=7292115... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# MIT License <https://opensource.org/licenses/MIT>
#
# Copyright (C) 2018 <NAME>.
# Copyright (C) 2017-2018 -- mrJean1 at Gmail dot com
#
# Permission is hereby granted, free of charge, to any person obtaining a
# copy of this software and associated documentation files (... |
<filename>lab/experimental_sweeps/sweep_open_classification.py<gh_stars>10-100
# Imports
import os
import warnings
import tensorflow as tf
import wandb
from wandb.keras import WandbCallback
import sklearn
import numpy as np
from sklearn.metrics import confusion_matrix, precision_recall_fscore_support
from tensorflow.ke... |
<reponame>damaha/iasi-atmosphere<gh_stars>0
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from scipy.signal import convolve2d
import scipy.sparse.linalg as ssl
from mpl_toolkits.basemap import Basemap, cm
def pccs(x, n_comps = "all"):
if n_comps == "all":
n_comps = x.shape[0]-1
... |
<gh_stars>1-10
# Load library dependencies
import numpy as np
import numpy.linalg
import scipy as sp
import scipy.optimize
import scipy.stats
import pandas as pd
# Import logit() command in ipt module since ipw_att() calls it
from .logit import logit
from .ols import ols
# Define ipw_att() function
#---------------... |
<gh_stars>1-10
# -*- coding:UTF-8 -*-
# recon data combine by built model
import numpy as np
np.random.seed(1337) # for reproducibility
from sklearn.cross_validation import train_test_split
from sklearn.metrics.regression import r2_score, mean_squared_error
from sklearn.preprocessing import MinMaxScaler
from sklearn.... |
import re
import numpy as np
import torch
import torchvision
import torch.nn as nn
import torchvision.datasets as dset
from torch.autograd import Variable
from torch.utils.data import DataLoader, Dataset
from hanja import hangul
from scipy import signal
from scipy.io import wavfile
# 그저 one_hot ...
def one_hot(i,... |
import sys, os
import time
import cv2
import numpy as np
import math
from scipy.signal import convolve2d
from scipy.ndimage import label,sum
from scipy.misc import imrotate
from matplotlib import pyplot as plt
from skimage import morphology
from skimage.segmentation import slic
from bwmorph import bwmorph_thin
from c... |
<gh_stars>0
"""
Generic dataset implementation for loading, filtering and matching cubes.
"""
import numpy
import glob
from scipy.spatial import cKDTree as KDTree
from collections import defaultdict
from . import utility
def read_dataset(dataset_id, datatype, variable,
location_name=None, depth=None,... |
# Some helper functions
import numpy as np
import scipy.special
from scipy.signal import butter, lfilter
# Return real part of exponential integral, same as matlab expint()
def expint(v):
return np.real(-scipy.special.expi(-v)-np.pi*1j)
# Circular shift of an array
def circular_shift(x,t):
return [x[t:len(x)... |
import sys
import pdb
import scipy as sp
def read_fasta(filename):
"""Reads a sequence in FASTA format from filename and stores it
in a dictionary - one entry per contig"""
genome = dict()
for line in open(filename, 'r'):
if line[0] == '>':
if not is_first:
geno... |
<reponame>lf-shaw/operon<gh_stars>0
# SPDX-License-Identifier: MIT
# SPDX-FileCopyrightText: Copyright 2019-2021 Heal Research
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats
import random, time, sys, os, json
import operon as Operon
ds ... |
<filename>malaya_speech/utils/aligner.py<gh_stars>0
import numpy as np
from dataclasses import dataclass
from malaya_speech.utils.char import CTC_VOCAB as labels
def beta_binomial_prior_distribution(phoneme_count, mel_count, scaling_factor=1.0):
from scipy.stats import betabinom
x = np.arange(0, phoneme_coun... |
from datetime import datetime
from functools import reduce
from numpy.lib.arraypad import _pad_dispatcher
from numpy.testing._private.utils import build_err_msg
import pandas as pd
import numpy as np
import sys
import logging
from dmyplant2.dEngine import Engine
from dmyplant2.dMyplant import MyPlant, load_pkl, save_p... |
<reponame>Francisco95/ImageSearch
from scipy import spatial
from .validator import validate_keys
import numpy as np
import time
from .utils import paral_query, print_histo, parallel_query
_VALID_KWARGS = {"k1": None,
"k5": None,
"k10": None,
"min_dist_vec": None,
"n": None,
"MRR": None,
... |
from pyitab.io.loader import DataLoader
from pyitab.analysis.iterator import AnalysisIterator
from pyitab.analysis.configurator import AnalysisConfigurator
from pyitab.analysis.pipeline import AnalysisPipeline
from pyitab.analysis.decoding.temporal_decoding import TemporalDecoding
from sklearn.svm.classes import SVC
fr... |
<filename>flip_image.py
import numpy as np
from scipy import ndimage
from PIL import Image
name_in = 'figures/Right_center_lane_driving.jpg'
center_image = ndimage.imread(name_in)
center_image_mirror = np.fliplr(center_image)
name_out = 'figures/Mirror_Right_center_lane_driving.jpg'
im = Image.fromarray(center_image... |
<gh_stars>0
from pathlib import Path
import json
import shutil
import sys
import numpy as np
import scipy.io
from .utils import ShellScript
from .basesorter import get_job_kwargs
from spikeinterface.extractors import KiloSortSortingExtractor, BinaryRecordingExtractor
class KilosortBase:
"""
Shared class for... |
import numpy as np
from matplotlib import pyplot as plt
import glob
from matplotlib import patches as mpatches
from scipy.interpolate import PchipInterpolator
import scipy.ndimage
plt.style.use("../template.mplstyle")
# purple - green - darkgoldenrod - blue - red
colors = ['purple', '#306B37', 'darkgoldenrod', '#3F7BB... |
<gh_stars>1-10
'''
Runs the analysis on vector file
'''
import numpy as np
from numpy import mean
from numpy import std
import time
import configparser
import math
from sklearn.decomposition import PCA
from sklearn.neighbors import KNeighborsRegressor
from sklearn.neighbors import RadiusNeighborsRegressor
from sklearn... |
# !/usr/bin/env python
# -*- coding: utf-8 -*-
"""Core Classes and Functions.
This file stores the core classes and functions for the MRBLEs Analysis module.
"""
# [File header] | Copy and edit for each file in this project!
# title : core.py
# description : MRBLEs - Core Functions
# author ... |
<gh_stars>0
import h5py
import numpy as np
import matplotlib.pyplot as plt
from pathlib import Path
import click
from scipy.signal import decimate
from datetime import datetime
from scipy import signal
import logging
logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.DEBUG)
def downsample(
da... |
def test_sympy__physics__quantum__cartesian__PxKet():
from sympy.physics.quantum.cartesian import PxKet
assert _test_args(PxKet(x, y))
# Hello world to a function related to quantum physics...
|
<gh_stars>0
"""
Author: <NAME>
Version 3:
- Renamed to peak_plotter
- Using Matlibplot for subplot plotting
"""
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import pandas as pd
from tkinter.filedialog import askopenfilename
from tkinter.filedialog import asksaveasfile
fr... |
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from sklearn.decomposition import PCA
import scipy.io as sio
from scipy import sparse
import time
from CSMSSMTools import *
def getDiffusionMap(K, neigs = 4, thresh=5e-4):
"""
Perform diffusion maps with a unit timestep,... |
<gh_stars>0
from django.contrib.gis.geos import Point
from functools import reduce
import numpy as np
from scipy.optimize import minimize, basinhopping
from optimization.models import OptimizedBaseStation
from optimization.taguchi import taguchi
import random
class OptimizeLocation():
@staticmethod
def groupe... |
<gh_stars>0
import numpy as np
import scipy.stats as stats
from . import squareLaw
from utils.unit_conversions import lin_to_db, db_to_lin
import prop
def det_test(y1, y2, noise_var, num_samples, prob_fa):
"""
Apply cross-correlation to determine whether a signal (y2) is present or
absent in the provided ... |
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 8 00:21:38 2018
@author: JAE
"""
from keras.layers import Input, merge, Activation
from keras.layers import Conv2D, MaxPooling2D, UpSampling2D, Dropout
from keras.models import Model
from keras.optimizers import Adam
from keras import backend as K
import scipy.io
import... |
"""
Programming Project 1
<NAME>
15863
"""
import cmath as c
from random import random
import numpy as np
N = 3 # Number of qubits
psi = np.ndarray((2 ** N, 1), complex) # N-qubit register
'''
# psi is computational basis state
comp_state = 5
for i in range(2**N):
if i == comp_state:
psi[i] = 1
el... |
<reponame>BorgwardtLab/networkGWAS<filename>LMM/util/stats/chi2mixture_sum.py
'''
Adapted code from fastlmm implementation
'''
from __future__ import absolute_import
import scipy as sp
import scipy.stats as st
import scipy.special
import numpy as np
import pdb
import logging
from six.moves import range
from IPython im... |
# Copyright 2018 Xanadu Quantum Technologies 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 applicable law or agre... |
<gh_stars>1-10
import numpy as np
import time
import numpy as np
import matplotlib.pyplot as plt
from scipy import sparse
import osqp
import copy
from gym.envs.robotics.utils import reset_mocap2body_xpos
import safe_rl.pg.run_agent
def quadprog(H, f, A=None, b=None,
initvals=None, verbose=False):
... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 10
@author: jaehyuk
"""
import numpy as np
from . import normal
from . import bsm
import scipy.integrate as spint
import sys
sys.path.insert(sys.path.index('') + 1, 'C:/Users/cherr/Documents/GitHub/PyFeng')
import pyfeng as pf
'''
MC model class for Beta=1
... |
<reponame>danhey/Bunyip<filename>bunyip/ebai/ebai.py
# -*- coding: utf-8 -*-
from __future__ import division, print_function
from .knn import KNN
from .geometry import solve_geometry, from_geometry
import numpy as np
import ellc
from scipy import optimize
import lightkurve as lk
import matplotlib.pyplot as plt
__all... |
import numpy as np
import scipy as sp
import os.path as osp
from flowdec import data as fd_data
import cytokit
from cytokit import config as cytokit_config
def load_simulated_bars_experiment(blur=False, **kwargs):
ref_img = fd_data.bars_25pct().data if blur else fd_data.bars_25pct().actual
# Subset image to n... |
<filename>figs/slice/slice.py
import sys
import os
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
#import units as cgs
from math import pi
#from polytropes import monotrope, polytrope
#from crust import SLyCrust
#from eoslib import get_eos, glue_crust_and_core, eosLib
#from scipy.integrate import ... |
<reponame>stefanialvs/PyForecast
import numpy as np
from numpy.random import seed
seed(1)
import pandas as pd
from math import sqrt
from scipy.optimize import minimize
from sklearn.base import BaseEstimator, RegressorMixin, clone
from scipy.optimize import minimize
##################################################... |
import numpy as np
from python_utils.mathu import quat_identity, quat_mult, vector_quat, matrix_from_quat, rodmat
from scipy.spatial.transform import Rotation as R
def exp_quat(v):
""" See "Practical Parameterization of Rotations Using the Exponential Map"
- F. <NAME>
Section 3
"""
ang = np.linalg.... |
<gh_stars>1-10
#
# Copyright © 2021 United States Government as represented by the Administrator
# of the National Aeronautics and Space Administration. No copyright is claimed
# in the United States under Title 17, U.S. Code. All Other Rights Reserved.
#
# SPDX-License-Identifier: NASA-1.3
#
"""Dorado sensitivity calc... |
<reponame>MapsPy/MapsPy<filename>fitting/leastsqbound.py
'''
Created on Nov 29, 2011
@author: <NAME>, 2nd Look Consulting
http://www.2ndlookconsulting.com/
Copyright (c) 2013, <NAME>, Argonne National Laboratory
All rights reserved.
Redistribution and use in source and binary forms, with or without mo... |
<gh_stars>10-100
from __future__ import print_function
import os, sys, argparse, ast, time, pdb
import numpy as np
from PIL import Image
from scipy.misc import imsave
import torch
from cirtorch.datasets.testdataset import configdataset
from cirtorch.utils.general import get_data_root
from cirtorchclone.imageretriev... |
import warnings
# Suppress warning errors from importing pandas
with warnings.catch_warnings():
warnings.simplefilter("ignore")
import pandas as pd # noqa: F401 see: https://github.com/ContinuumIO/anaconda-issues/issues/6678
import h5py # noqa: F401
import scipy # noqa: F401
from scipy import n... |
from .units import dimension, dimension_name, SI_symbol, pg_units
from .interfaces.astra import write_astra
from .interfaces.opal import write_opal
from .readers import particle_array
from .writers import write_pmd_bunch, pmd_init
from h5py import File
import numpy as np
import scipy.constants
mass_of = {'electron'... |
<gh_stars>0
import random
from scipy.special import lambertw
import numpy as np
import torch
import torch.utils.data
def compute_constants(reg, nz, R=1, num_random_samples=100, seed=49):
q = (1 / 2) + (R ** 2) / reg
y = R ** 2 / (reg * nz)
q = np.real((1 / 2) * np.exp(lambertw(y)))
C = (2 * q) ** (nz ... |
# !/usr/bin/env python
"""
Pose Detector Object for ROS
"""
import cv2 as cv
import numpy as np
import time
import math
import rospkg
from scipy.ndimage.filters import gaussian_filter
import os
# import sys
# caffe_root = '/home/asilva/caffe/python'
# sys.path.append(caffe_root)
import caffe
### Begin Config:
param... |
#
# BSD 3-Clause License
#
# Copyright (c) 2020, <NAME>
# All rights reserved.
#
# 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... |
<gh_stars>0
#!/usr/bin/env python
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import json
import os
import shutil
import anndata
import numpy as np
from sklearn.metrics import roc_auc_score, roc_curve
from scipy.sparse import issparse
from collections import defaultdict
import scvi
from scvi.da... |
<filename>species/analysis/fit_model.py<gh_stars>0
"""
Module with functionalities for fitting atmospheric model spectra.
"""
import os
import math
import warnings
from typing import Optional, Union, List, Tuple, Dict
from multiprocessing import Pool, cpu_count
import emcee
import numpy as np
import spectres
from s... |
#! /usr/bin/env python
# =======
# Imports
# =======
from __future__ import print_function
import sys
from special_functions import besseli
from scipy.special import i0, i1, iv, ivp
from math import isnan, isinf, copysign
import warnings
warnings.filterwarnings(
"ignore",
message="invalid value encoun... |
<reponame>sandeepdas05/lsm-crack-width
import skfmm
import numpy as np
from scipy.ndimage import gaussian_filter1d as gf1d
from skimage.measure import label
from lsml.initializer.initializer_base import InitializerBase
from lsml.initializer.provided.util import radii_from_mask as rfm
class RayTrimInitializer(Initia... |
"""
Calculates growth and non-growth associated maintenance to fit a diverse data set.
"""
from tools import conf_model
import pandas as pd
import settings
import numpy as np
import seaborn as sns
from scipy import stats
import matplotlib.pyplot as plt
plt.style.use('seaborn')
def train(model, exclude_data_index=[]... |
import itertools
import random
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
class FitClass:
"""
This class is used for sigma optimization via curve_fit.
"""
def __init__(self):
self.mu = []
def multi_modal(self, *args):
"""
This... |
"""
This program builds a Markov Random Field model
From there, the user can interactively segment an image
It will allow them to see the foreground and background
"""
import matplotlib.pyplot as plt
import numpy as np
import maxflow
from scipy.spatial import distance
from selectpoints import select_k_points
"""
Cre... |
import numpy as np
from scipy.sparse import csr_matrix,csc_matrix
#
def build2(size):
#how many coefficients ?
nc= 5*(size-2)**2+ 16*(size-2)+ 12
row= np.empty((nc),dtype=int)
col=np.empty((nc),dtype=int)
v=np.empty((nc),dtype=float)
h=1./(size-1)
h2=h*h
cd=-4/h2
hd=1./h2;
I=lamb... |
"""
Python script for compute lower and upper bounds for the
mnll and jsd metrics
License:
MIT License
Copyright (c) 2020 Kundaje Lab
Permission is hereby granted, free of charge, to any person
obtaining a copy of this software and associated documentation
files (the "Software"... |
def pre_build_hook(build_ext, ext):
from scipy._build_utils.compiler_helper import (
get_cxx_std_flag, has_flag, try_add_flag)
cc = build_ext._cxx_compiler
args = ext.extra_compile_args
std_flag = get_cxx_std_flag(cc)
if std_flag is not None:
args.append(std_flag)
if cc.compil... |
<reponame>mwong009/iclv_rbm<gh_stars>1-10
## File 01nestedEstimation.py
## Simple nested logit model for the Optima case study
## Wed May 10 10:55:12 2017
from biogeme import *
from headers import *
from loglikelihood import *
from statistics import *
from nested import *
### Three alternatives:
# CAR: automobile
# P... |
import numpy as np
import torch
from torch.utils.data import Dataset
import os
import time
import collections
import random
from DSB2017.layers import iou, nms
from scipy.ndimage import zoom
import warnings
from scipy.ndimage.interpolation import rotate
import pandas
class DataBowl3Classifier(Dataset):
def __init... |
<reponame>DominicTanzillo/srcdl
"""
Copyright (c) 2020 CRISP
Auxilary helper functions
:author: <NAME>
"""
import os
import sys
PATH = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", "..")
sys.path.append(PATH)
import numpy as np
from scipy.io import loadmat
from .evaluate import f... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Diagnostic script to calculate ECS following Gregory et al. (2004).
Description
-----------
Calculate the equilibrium climate sensitivity (ECS) using the regression method
proposed by Gregory et al. (2004).
Author
------
<NAME> (DLR, Germany)
Project
-------
CRESCENDO... |
import sys
import argparse
import statistics as stat
from config import *
import os
delay = 30
parser = argparse.ArgumentParser('Analysis Plots')
parser.add_argument('--topo',
type=str,
required=True,
help='what topology to generate summary for')
parser.add_argument('--payment-graph-type',
... |
<reponame>OneOneFour/ICSP_Monte_Carlo<filename>graphics.py
import matplotlib
# matplotlib.use("Agg")
import pygame
import sgc
from sgc.locals import *
import monte
import numpy as np
import time as tme
from multiprocessing import Pool
import os
from abc import ABC, abstractmethod
from datetime import datetime as dt
i... |
# Copyright (c) 2008-2011, <NAME>
# All rights reserved.
#
# 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 t... |
<filename>examples/realistic_example/user.py
'''
user.py
This is where the datasets (X, y), the parameter-space and the
objective function are defined.
- X: the features for the data
- y: the labels (targets)
- objective: function that returns a list of scores
(mean and standard deviation score will be
... |
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