text string |
|---|
<filename>data_augmentation.py<gh_stars>1-10
import cv2
import numpy as np
from scipy import linalg
import scipy.ndimage as ndi
def transform_matrix_offset_center(matrix, x, y):
o_x = float(x) / 2 + 0.5
o_y = float(y) / 2 + 0.5
offset_matrix = np.array([[1, 0, o_x], [0, 1, o_y], [0, 0, 1]])
reset_matr... |
<gh_stars>0
'''
Post-process the output of the vibration-record recorder.
'''
import matplotlib.pyplot as plt
from matplotlib import dates
import datetime
import numpy
import scipy.signal
import pickle
import os
import os.path
import sys
INPUT_FILE = "" # to be filled
def ReadFile(fn, DateTarget=None, DateR... |
# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import division, unicode_literals
import numpy as np
import warnings
import scipy.constants as const
from monty.json import MSONable
from pymatgen.analysis.structure_matcher import StructureMa... |
"""
Volatility processes for ARCH model estimation. All volatility processes must
inherit from :class:`VolatilityProcess` and provide the same methods with the
same inputs.
"""
from __future__ import annotations
from abc import ABCMeta, abstractmethod
import itertools
import operator
from typing import TYPE_CHECKING,... |
#!/usr/bin/python3
# FLYCOP
# Author: <NAME>
# April 2018
# See SMAC documentation for more details about *wrapper_vX.py, wrapper_scenario_vX.txt and *wrapper_params_vX.pcs
src='ecoliLongTerm_TemplateOptimizeConsortiumV0/'
dst='ecoliLongTerm_TestTempV12'
dirPlots='../smac-output/ecoliLongTerm_PlotsScenario12/'
fitF... |
<reponame>nschloe/pyamg<gh_stars>0
"""Compatible Relaxation."""
from copy import deepcopy
import numpy as np
from scipy.linalg import norm
from scipy.sparse import isspmatrix, spdiags, isspmatrix_csr
from pyamg import amg_core
from ..relaxation.relaxation import gauss_seidel, gauss_seidel_indexed
def _CRsweep(A, B,... |
<gh_stars>0
"""
偏微分一定要显示一个表达式，而不是直接一个函数名，这个看起来和数学里面用的不一样
或许应该直接写出来这个函数名形式的偏微分，而真正的表达式才让sympy来输出。
"""
from sympy import *
from common1 import plot_latex
x, y, z = symbols('x_{1}^2 y z1')
expr1 = exp(x*y*z)
# r2 = latex(diff(expr1, x, evaluate=False))
r3 = latex(diff((x, y), x, evaluate=False))
# plot_latex(r3)
fxy = ... |
<gh_stars>0
# https://github.com/ManuelTS/augmentedFaceMeshIndices/blob/master/Nose.jpg
import moviepy.editor as ed
from tqdm import tqdm
import mediapipe as mp
import dlib
import cv2
import os
import numpy as np
from scipy.spatial.transform import Rotation
from matplotlib import pyplot as plt
import json
import face_a... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import Voronoi
from shapely.geometry import Point, Polygon
import itertools
import voronoi_cut
import random
from deap import base
from deap import creator
from deap import tools
results, pcb_outline = voronoi_cut.parse_file('ItemsList1.txt')
loads... |
<gh_stars>0
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
from tensorflow import keras
# tf.compat.v1.enable_eager_execution()
physical_devices = tf.config.list_physical_devices('GPU')
for device in physical_devices:
tf.config.experimental.set_memory_growt... |
<gh_stars>0
from matplotlib import colors
from scipy import ndimage
from astropy.wcs import WCS
import matplotlib.patches as mpatches
from matplotlib.pyplot import figure
from astro_ghost.sourceCleaning import clean_dict
from astropy.io import ascii
from astropy.table import Table
import requests
from astropy import un... |
<gh_stars>0
import argparse
import io
import h5py
import numpy as np
from os.path import join, dirname, basename, splitext, sep
from scipy.spatial.transform import Rotation
import scipy.io
import cv2
import progressbar
import zipfile
from datasets.preprocessing import imdecode, rotation_conversion_from_hell,\
comp... |
import math
import time
import matplotlib.pyplot
import matplotlib.colors
import matplotlib.cm
import numpy
import scipy.io
import xlrd
import xlwt
time_start = time.time()
image_origin = numpy.zeros([180, 512])
image_number = numpy.zeros([1024, 1024])
image_target = numpy.zeros([1024, 1024])
image_d... |
<reponame>DEDZTBH/luojia1-cloud-detection<filename>core.py
from PIL import Image
import numpy as np
import cv2
from scipy import ndimage
import slidingwindow as sw
from global_const import data_dir, R, C
from multiprocessing import get_context
# Helper functions
def get_img(dirname):
im = Image.open('{}{}/{}_g... |
<reponame>adamoses/slab_fitter
import pandas as pd
import emcee
import corner
from astropy.constants import au,h,pc,c
from slabspec import *
from flux_calculator import *
from slab_fitter import *
from scipy.optimize import minimize
import random
import numpy as np
def logposterior(theta, data, sigma, myrun,lognmin... |
# Copyright 2019-2021 Cambridge Quantum Computing
#
# 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 a... |
# -*- coding: utf-8 -*-
"""
Functions for constructing surface graphs
"""
import numpy as np
import scipy.sparse as ssp
def get_edges(faces):
"""
Gets set of edges defined by `faces`
Parameters
----------
faces : (F, 3) array_like
Set of indices creating triangular faces of a mesh
R... |
<gh_stars>0
import numpy as np
import glob
from scipy.misc import imread
from skimage.io import imsave
from skimage.transform import rotate
import matplotlib.pyplot as plt
import os
from os.path import basename
import glob
import random
from functions import transforms, raw_to_labels
# This is a comment. Move along pe... |
import os
import scipy
import numpy as np
import tensorflow as tf
from config import cfg
def load_mnist(path, is_training):
fd = open(os.path.join(cfg.dataset, 'train-images-idx3-ubyte'))
loaded = np.fromfile(file=fd, dtype=np.uint8)
trX = loaded[16:].reshape((60000, 28, 28, 1)).astype(np.float)
fd =... |
# -*- coding: utf-8 -*-
if __name__ != '__main__':
raise Exception("ran example file as non-main")
import numpy as np
import scipy.signal as sig
from ssqueezepy import Wavelet, TestSignals
from ssqueezepy.utils import window_resolution
tsigs = TestSignals(N=2048)
#%%# Viz signals #################################... |
<reponame>kshitijd20/pyrsa
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Comparison methods for comparing two RDMs objects
"""
import numpy as np
import scipy.stats
from scipy.stats._stats import _kendall_dis
from pyrsa.util.matrix import pairwise_contrast_sparse
from pyrsa.util.rdm_utils import _get_n_from_reduce... |
"""
This module implements basic kinds of jobs for VASP runs.
"""
import logging
import math
import os
import shutil
import subprocess
import numpy as np
from monty.os.path import which
from monty.serialization import dumpfn, loadfn
from monty.shutil import decompress_dir
from pymatgen.core.structure import Structure... |
<reponame>ishatserka/MachineLearningAndDataAnalysisCoursera
"""
Trying to build a network with shared connections:
>>> from random import random
>>> n = buildSharedCrossedNetwork()
Check if the parameters are the same:
>>> (n.connections[n['a']][0].params == n.connections[n['a']][1].params).all()... |
<filename>pylbm/generator/ast.py<gh_stars>0
# FIXME: make pylint happy !
#pylint: disable=all
from sympy.core import Symbol, Expr, Tuple
from sympy.core.sympify import _sympify, sympify
from sympy.tensor import Idx, IndexedBase, Indexed
from sympy.core.basic import Basic
from sympy.core.relational import Relational
fr... |
"""
Link edge points in an image to lists.
Convert from matlab code, author is <NAME>
Please see https://www.peterkovesi.com/matlabfns/
Copyright (c) 2018- <NAME>
mingzilaochongtu at gmail com
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation fi... |
<gh_stars>0
## plot a heatmap with the top 100 instance features across all SV types.
import sys
import numpy as np
import matplotlib.pyplot as plt
from sklearn.ensemble import RandomForestClassifier
import random
from scipy import stats
from statsmodels.sandbox.stats.multicomp import multipletests
import os
import os... |
<reponame>OttoJursch/DRL_robot_exploration<gh_stars>0
from copy import deepcopy
from scipy import spatial
from skimage import io
from skimage.transform import resize
from scipy import ndimage
from random import shuffle
import numpy as np
import numpy.ma as ma
import time
import copy
import sys
import os
import random
i... |
<reponame>daemonslayer/robond<gh_stars>1-10
# Copyright (c) 2017, Udacity
# 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 noti... |
<gh_stars>1-10
import numpy as np
from galpy.orbit import Orbit
from galpy.potential import MWPotential2014
import astropy.units as u
import matplotlib.pyplot as plt
from joblib import Parallel, delayed
from scipy.stats import gaussian_kde,rv_continuous
from scipy.integrate import quad
from scipy.interpolate import int... |
import sys
from mpi4py import MPI
import numpy as np
from scipy.interpolate import interp1d
sys.path.append('/Users/bl/Dropbox/repos/Delight/')
from delight.io import *
from delight.utils import *
from delight.photoz_gp import PhotozGP
from delight.photoz_kernels import Photoz_mean_function, Photoz_kernel
import scipy... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Fitting functions for use in The Cannon.
"""
from __future__ import (division, print_function, absolute_import,
unicode_literals)
__all__ = ["fit_spectrum", "fit_pixel_fixed_scatter", "fit_theta_by_linalg",
"chi_sq", "L1Norm_variation"]
i... |
import argparse
import pathlib
import shutil
import statistics
import subprocess
import time
from os.path import join
import constants
from constants import RESULTS_DIR, DISTANCE_NORMS, CONSISTENT_DRAWS, NUM_THREADS, MODEL_TYPES, DISTANCE_NORM, \
NUM_ADV_CHECKS
from datasets import get_epsilon
from result import g... |
import os
import sys
import matplotlib as plt
import numpy as np
import scipy.io as sio
import scipy.misc
import tensorflow as tf
from matplotlib.pyplot import imshow
from PIL import Image
from scipy import io as sio
OUTPUT_DIR = "output/"
STYLE_IMAGE = "data/starry_night.jpg"
CONTENT_IMAGE = "data/marilyn_monroe_in... |
<reponame>jaisw7/shenfun<gh_stars>100-1000
import sympy as sp
from mpi4py import MPI
import pytest
from shenfun import *
comm = MPI.COMM_WORLD
def test_lagrangian_particles():
N = (20, 20)
F0 = FunctionSpace(N[0], 'F', dtype='D', domain=(0., 1.))
F1 = FunctionSpace(N[1], 'F', dtype='d', domain=(0., 1.))
... |
<reponame>AlexPereverzyev/ml
import math
import numpy as np
from scipy import linalg
from generative.gaussian import GaussianClassifier
class LinearDescriminantClassifier(GaussianClassifier):
"""Classifier and data transformer based on linear descriminant analysis
(Eigen method)"""
def __init__(self, ... |
<filename>datasets.py
import os
import urllib.request
import numpy as np
import torch
import torch.utils.data
from torchvision import datasets, transforms
from torchvision.utils import save_image
from torch.utils.data import Dataset, DataLoader, TensorDataset
from scipy.io import loadmat
num_workers = 4
lamb = 0.05
c... |
from ..functions_on_data import iterable_data_array, data_array_builder
import pandas as pd
import numpy as np
from scipy.optimize import curve_fit
__all__ = (
"window",
"fit_sine",
"center_yaxis",
"shift",
"scale",
"invert",
"average_over_same_angle",
)
def window(data_dict, key="Y", wi... |
import os
import time
from datetime import datetime
import numpy as np
import numpy.random as npr
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import tensorflow as tf
print(tf.__version__)
from tensorflow.python.client import device_lib
device_lib.list_local_devices()
from tensorflow.contr... |
<gh_stars>0
import os
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
from GEN_Utils import FileHandling
from pykalman import KalmanFilter
from scipy.interpolate import UnivariateSpline
from scipy.stats import ttest_1samp
from loguru import logger
logger.info('Import OK')
... |
import math
import colorsys
import scipy
import scipy.cluster
import operator
import math
from PIL import Image
import numpy as np
import random
WIDTH = 1700
HEIGHT = 540
def rgb_to_gray(r, g, b, a = None):
return 0.299 * r + 0.587 * g + 0.114 * b
def get_avg_gray(pix, x, y, radius, sample_size = 0.1):
nsamp... |
<reponame>readthedocs-assistant/glum
import warnings
from typing import Any, Dict, Optional, Union
import numpy as np
import pandas as pd
import rpy2.robjects as ro
import rpy2.robjects.numpy2ri as n2r
from rpy2.robjects.packages import importr
from scipy import sparse as sps
from .util import benchmark_convergence_t... |
<filename>se_resnext50/src/models/resnet_bam_wider.py
# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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-... |
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
import matplotlib.cm as cm
## adaptado do curso do Schuster
def model1(migi,nx,nz,ntime,dt,app,rick,dx,dz,c):
data=np.zeros([nx,ntime]);
nl=len(rick);
data1=np.zeros([nx,nl+ntime-1]);
for ixtrace in range(0,nx):
istar... |
<gh_stars>10-100
import numpy as np
from scipy import fft
import matplotlib.pylab as plt
def make_fft(window, samplerate, df, every, iq_stream):
result_of_fft = []
counting_until_every_reached = 0
adc_offset = -127
# bringing the signal per kernel down around the average reduces the dc peak at f=0hz... |
# This file contains plots to show data
from itertools import product
import numpy as np
import pandas as pd
import seaborn as sns
from matplotlib import pyplot as plt, rcParams
from scipy import stats
PALETTE = ['#59b5e3', '#1aa075']
def tandem_distplot(
real_tandems_fn, count_sim_size_fn, family_name, show_pd... |
<gh_stars>0
import argparse
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import scipy.io
import numpy as np
import importlib
import time
import networkx as nx
from torch.autograd import Variable
from pdb import set_trace as bp
class EP_Env(object):
de... |
##############################################################################################
# PURPOSE
# Creates the multiple plots relating the Q_i parameter with the properties of the LCGs (oxygen abundances, sSFR and concentration)
#
# CREATED BY:
# <NAME>
#
# ADAPTED BY:
#
# CALLING SEQUENCE
# python Q_vs_... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.pipeline import make_pipeline
from sklearn.compose import ColumnTransformer
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import MinMaxScaler, StandardScaler
from sklearn.impute import Simpl... |
<filename>Scripts/lab2b/Main.py
from aSurname2312 import *
from aSurname241 import *
from scipy.io import wavfile as wvf
import numpy as np
import matplotlib.pyplot as plt
def plot2312(code, date):
amp, strAmp = 2, '2'
frq, strFrq = 1/11, '1/11'
phs, strPhs = 0, '0'
n, x = genSinusoid(amp, frq, phs, ... |
<filename>gimmemotifs/plot.py
# Copyright (c) 2009-2019 <NAME> <<EMAIL>>
#
# This module is free software. You can redistribute it and/or modify it under
# the terms of the MIT License, see the file COPYING included with this
# distribution.
""" Various plotting functions """
from __future__ import print_function
from ... |
<filename>tutorials/Bayes_HT.py
from math import pi, log, sqrt
import numpy as np
from scipy.optimize import minimize
from scipy.stats import multivariate_normal as MVN
def compute_A_re(freq_vec, tau_vec, flag='impedance'):
omega_vec = 2.*pi*freq_vec
N_freqs = freq_vec.size
N_taus = tau_vec.size
... |
<reponame>DNPLab/dnpLab<gh_stars>0
import numpy as np
from scipy.special import wofz
def voigtian(x, x0, sigma, gamma, integral=1.0):
r"""Voigtian distribution. Lineshape given by a convolution of Gaussian and Lorentzian distributions.
Args:
x (array_like): input x
x0 (float): center of distr... |
<filename>pyatsa/tests/test_pyatsa.py
import numpy as np
import rasterio as rio
from rasterio import fill
import skimage as ski
import matplotlib.pyplot as plt
import glob
import os
from rasterio.plot import reshape_as_raster, reshape_as_image
import json
import scipy.stats as stats
from scipy import io
import statsmod... |
# normal_cf_ds_classification_by_ufl_w_t_dis.py
# 1. fix a_max a_conf S_jam for a driver; mix seq points and random points for initialization: failed
# 2. fix S_jam for a driver; mix seq points and random points for initialization: still tried
# 3. add temporal distance when calculating distance for assigning labels... |
import os
import sys
import numpy as np
import scipy.io
import zipfile
import types
import PIL
from PIL import Image, ImageOps
import math
import tensorflow as tf
from tensorflow.contrib.learn.python.learn.datasets import mnist
sys.path.append('/home/leminen/Documents/RoboWeedMaps/GAN/weed-gan-v1')
import src.utils ... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 31 13:41:32 2019
@author: s146959
"""
# ========================================================================== #
# ========================================================================== #
from __future__ import absolute_import, with_statement, absolu... |
<reponame>shilpiprd/sympy
from sympy import I, log, apart, exp
from sympy.core.symbol import Dummy
from sympy.external import import_module
from sympy.functions import arg, Abs
from sympy.integrals.transforms import _fast_inverse_laplace
from sympy.physics.control.lti import SISOLinearTimeInvariant
from sympy.plotting.... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import sys
sys.path.append("./nets")
sys.path.append("../")
sys.path.append("/home/hanson/facetools/lib/FaceRecognition/method/tensorflow")
sys.path.append("/h... |
<filename>examples/Old Format/prob_not_solenoidal.py
from __future__ import print_function
from sympy import symbols,sin,cos,factor_terms,simplify
from galgebra.printer import enhance_print
from galgebra.deprecated import MV
def main():
enhance_print()
X = (x,y,z) = symbols('x y z')
(ex,ey,ez,grad) = MV.... |
<gh_stars>10-100
import os
import numpy as np
import scipy.io as sio
# import cv2
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from biosppy.signals import ecg
from tqdm import tqdm
ANO_RATIO=0 # add ANO_RATIO(e.g. 0.1%) anomalous to training data
LEFT=140
RIGHT=180
DATA_DIR="./datase... |
""" file: test_history.py
"""
from __future__ import print_function, division
import unittest
from collections import defaultdict
from numpy import array, sqrt, pi, linspace, sin, cos, arange, median
from scipy.special import fresnel
from maxr.integrator import history
def solution(time):
""" Solution to sinu... |
<reponame>greschd/NodeFinder
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# © 2017-2019, ETH Zurich, Institut für Theoretische Physik
# Author: <NAME> <<EMAIL>>
import json
import math
import cmath
import numpy as np
with open('data/fit.json', 'r') as f:
FIT = json.load(f)
def c00(k, a, j, m, o, q, **kwargs)... |
import scipy.spatial
import numpy as np
class RWO(object):
def __init__(self, d, threshold=0.45, bag=None, metric='euclidean'):
if bag is not None and "data" in bag and len(bag["data"])>0:
self.bag = np.array(self.bag["data"])
else:
self.bag = None
... |
# Question 04, Lab 04
# AB Satyaprakash - 180123062
# imports ----------------------------------------------------------------------------
from sympy.abc import t
from sympy import evalf, integrate
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# functions -------------------------------------... |
<gh_stars>1-10
# Standard Python Imports
import io
import json
import logging
from math import floor
from random import random
import numpy as np
from flask import Response, current_app, render_template, request, send_file
# External modules imports
from requests_toolbelt import MultipartEncoder
# Dependencies used ... |
<gh_stars>10-100
import numpy as np
from scipy.integrate import quad
def func1(tau, p0, p1, f):
rv = np.exp(-tau) * np.cos(-p1 / p0 * tau) * f(tau / p0)
return rv
def func2(tau, p0, p1, f):
rv = np.exp(-tau) * np.sin(-p1 / p0 * tau) * f(tau / p0)
return rv
def func(t):
return np.exp(-t)
p0 = 0.2... |
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#
# Distributed under terms of the MIT license.
import os
import datetime
import json
import numpy as np
from numpy.linalg import norm
import math
import argparse
from platt import *
from sklearn.metrics import f1_score
import time
import scipy.stats
from ... |
<gh_stars>10-100
# -*- coding: utf-8 -*-
"""
CALFEM Solver module
*** EXPERIMENTAL ***
"""
import calfem.core as cfc
import calfem.utils as cfu
import logging as cflog
import numpy as np
from scipy.sparse import lil_matrix
def error(msg):
cflog.error(" calfem.solver: "+msg)
def info(msg):
cflog.info(" cal... |
import math
import numpy as np
from scipy.optimize import least_squares
from Resources.helpers import *
class BaseMeasurement:
'''
Base class for all measurements. Child classes need to implement the _measure method that takes a
dictionary of landmark positions and returns a float value and a s... |
<gh_stars>0
import re
from scipy.spatial.distance import cdist
from .pbc import pbc_diff
from .checksum import checksum
import numpy as np
import scipy
if scipy.version.version >= '0.17.0':
from scipy.spatial import cKDTree as KDTree
else:
from scipy.spatial import KDTree
from pygmx import TPXReader
from pyg... |
#-*- coding:utf-8 -*-
import os, csv
import numpy as np
import scipy.cluster.hierarchy as sch
from variables import APPS
from variables import DISTANCE_BASE_PATH, DUPLICATES_REPORT_PATH
from variables import CORPUS_PATH
from variables import T_THRESHOLD
from util_corpus import get_all_reports_id
# ------------------... |
<reponame>guanjue/imputed_cistrome_2022
import fire
import pandas as pd
import numpy as np
from scipy.stats import gamma
from scipy.stats import poisson
def get_gammap(x, mostfreq):
### remove lower half
used = (x>np.quantile(x,0.5))
x = x-mostfreq
x[x<0] = 0
### get gamma parameters
scale = np.var(x[used])/np.m... |
# Copyright 1999-2020 Alibaba Group Holding Ltd.
#
# 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 a... |
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
import numpy as np
from torch.optim.lr_scheduler import MultiStepLR
import shutil
import random
from numpy import linalg as LA
from scipy.stats import mode
import collections
import tqdm
import os
from architecture import *
... |
<reponame>TSchlosser13/Hexnet
'''****************************************************************************
* layers.py: Square and Hexagonal Layers for Use with Keras
******************************************************************************
* v0.1 - 01.03.2019
*
* Copyright (c) 2019 <NAME> (<EMAIL>)
*
* ... |
<reponame>JaviPardox/fk-trajectory-analysis
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 16 02:57:48 2019
@author: <NAME>
https://www.linkedin.com/in/javier-pardo-fernandez-87b565124/
<EMAIL>
"""
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as scp
from scipy import opt... |
<filename>hw3/unicycle_spline.py<gh_stars>1-10
import numpy as np
from scipy.interpolate import CubicSpline
import matplotlib.pyplot as plt
from random import uniform
def unicycle_spline(t0, tf, obs):
#UNICYCLE_SPLINE returns a spline object representing a path from
# (y(t0),z(t0)) = (0,0) to (y(t0),z(t0)) = (10,0... |
<gh_stars>0
'''
Code for the following paper:
<NAME>, <NAME>, <NAME>, ``Decentralized Multi-Agent Active Search for Sparse Signals",
2021 Conference On Uncertainty in Artificial Intelligence (UAI)
(c) <NAME>(<EMAIL>), <NAME>(<EMAIL>)
In this file, we are coding the RSI algorithm from reference:
<NAME>., <NAME>., and... |
<reponame>alon-albalak/XOR-COVID
import logging
import os
import random
from tqdm import tqdm
import numpy as np
import torch
from datetime import date
from torch.utils.data import DataLoader
import json
from transformers import AutoConfig, AutoTokenizer
from models.bert_retriever import BERTEncoder
from data_classes.... |
<reponame>calico/stimulated_emission_imaging
import numpy as np
try:
from scipy.optimize import minimize
except:
minimize = None #Won't be able to use 'phase_fitting' in stack_registration
try:
import np_tif
except:
np_tif = None #Won't be able to use the 'debug' option of stack_registration
def stack_... |
import numpy as np
import pandas as pd
import xarray as xr
from scipy.integrate import quad
import scipy.interpolate as spi
import pf_static_sph
from scipy import interpolate
from timeit import default_timer as timer
import mpmath as mpm
# ---- HELPER FUNCTIONS ----
def kcos_func(kgrid):
#
names = list(kgrid... |
<gh_stars>10-100
"""
@author: <NAME>
"""
# Code modified from https://github.com/maziarraissi/DeepHPMs written by <NAME>
import matplotlib.pyplot as plt
import scipy.io
from scipy.interpolate import griddata
from plotting import newfig, savefig
import matplotlib.gridspec as gridspec
from mpl_toolkits.axes_grid1 impor... |
# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
"""
Various classes to facilitate the code generation of structured control
flow elements (e.g., ``for``, ``if``, ``while``) from state machines in SDFGs.
SDFGs are state machines of dataflow graphs, where each node is a state and each
edge... |
# %%
import os
import sys
# temporary solution for relative imports in case combo is not installed
# if combo is installed, no need to use the following line
sys.path.append(
os.path.abspath(os.path.join(os.path.dirname("__file__"), '..')))
import time
import numpy as np
import scipy as sp
from sklearn.preproces... |
# Copyright (c) 2011, <NAME> [see LICENSE.txt]
# This software is funded in part by NIH Grant P20 RR016454.
"""
Implementation of Gleason's (1999) non-iterative upper quantile
studentized range approximation.
According to Gleason this method should be more accurate than the
AS190 FORTRAN algorithm of Lund and Lund (1... |
<filename>scripts/ATL14_browse_plots.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 24 10:45:47 2020
@author: ben05
"""
import numpy as np
from scipy import stats
import os, glob, sys
from netCDF4 import Dataset
import shutil
import h5py
#import pointCollection as pc
#from PointDatabase.mapDa... |
<reponame>falckt/raman
# Author: <NAME> <<EMAIL>>
#
# License: BSD 3 clause
#
# SPDX-License-Identifier: BSD-3-Clause
from typing import BinaryIO, Hashable, Mapping, Optional, Sequence, Union
import collections
import pathlib
import xarray as xr
import numpy as np
from scipy import io as sio
from . import _renisha... |
import argparse
import matplotlib.pyplot as plt
import numpy as np
import uproot
from scipy import interpolate
def mass(x):
return x[:, 0] ** 2 - x[:, 1] ** 2 - x[:, 2] ** 2 - x[:, 3] ** 2
def get_histogram_function(file_name, branch):
"""get histogram function from root file in branch"""
def fill_bou... |
"""
Tensorboard logger code referenced from:
https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/04-utils/
Other helper functions:
https://github.com/cs230-stanford/cs230-stanford.github.io
"""
import json
import logging
import os
import shutil
import torch
from collections import OrderedDict
import tens... |
<reponame>ningtangla/segmentation-expt4
import scipy.stats as stats
import pandas as pd
import numpy as np
import itertools as it
import networkx as nx
import math
import cv2
import pygame
import datetime
import generateTreeWithPrior as generateTree
import generatePartitionGivenTreeWithPrior as generatePartition
clas... |
<gh_stars>0
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
"""
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource
from bokeh.models.widgets import Slider
from bokeh.layouts import row, widgetbox
from bokeh.io import curdoc
from scipy.stats import beta
import numpy as np
def set_prior(a, b... |
<reponame>tk5/maximum_power_info_ratchet<filename>src/noisy_analysis/propagators.py
#!/usr/bin/env python3
#@author: jlucero
#date created: Fri Mar 19 22:08:03 PDT 2021
# purpose: define propagators needed for analysis of noisy system
from numpy import (
pi, exp, sqrt, sinh, sign, abs, logical_and, where, finfo,
... |
"""Homegrown Neural Network Framework"""
import sys
import numpy as np
from scipy.optimize import minimize, check_grad
from scipy.special import expit as sigmoid
class NeuralNet(object):
"""A multi-layer, feed-forward neural network."""
def __init__(self, *layers, lambda_=0.1, is_analog=False):
"""
... |
import argparse
import unittest
import numpy as np
from scipy import stats
import maintsim
class ProductionTest(unittest.TestCase):
'''
Test expected production volume according to Little's Law.
'''
def test_production1(self):
'''
Deterministic production volume of one machine.
... |
from __future__ import absolute_import
import torch
import numpy as np
import pandas as pd
import scipy
import copy
from pysurvival import HAS_GPU
from pysurvival import utils
from pysurvival.utils import neural_networks as nn
from pysurvival.utils import optimization as opt
from pysurvival.models import BaseModel
fro... |
<filename>srgan/data_loader.py
import scipy
from glob import glob
import numpy as np
import matplotlib.pyplot as plt
import posixpath
class DataLoader():
def __init__(self, parent_dir, dataset_name, img_res=(128, 128)):
self.dataset_name = dataset_name
self.img_res = img_res
self.parent_dir... |
<reponame>DangerMouseB/coppertop
# *******************************************************************************
#
# Copyright (c) 2021 <NAME>. All rights reserved.
#
# *******************************************************************************
import scipy.linalg, numpy
from coppertop.pipe import *
from cop... |
# Author: <NAME> <<EMAIL>>
#
# License: BSD 3 clause
import numba
import numpy as np
import scipy.stats
from sklearn.metrics import pairwise_distances
_mock_identity = np.eye(2, dtype=np.float64)
_mock_cost = 1.0 - _mock_identity
_mock_ones = np.ones(2, dtype=np.float64)
@numba.njit()
def sign(a):
if a < 0:
... |
import os, sys, re, io, json, tempfile
import subprocess
import argparse
import numpy as np
import scipy.stats
import pandas as pd
import plotly
import plotly.graph_objs as go
import pymultiscale.anscombe
import statsmodels.stats.multitest
from logging import getLogger, Formatter, StreamHandler, FileHandler, DEBUG, INF... |
from scipy import ndimage
import numpy as np
from nephelae.array import ScaledArray
from .FactoryBorder import FactoryBorder
from .MacroscopicFunctions import threshold_array
class BorderRaw(FactoryBorder):
def __init__(self, name, mapInterface):
super().__init__(name, threshold=mapInterface.threshold)
... |
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