text string |
|---|
<gh_stars>1-10
import numpy as np
from numpy import ndarray
from scipy.optimize import minimize_scalar
from scipy.special import gamma
from scipy.stats.mstats import gmean
from statsmodels.distributions.empirical_distribution import ECDF
def brody_dist(s: ndarray, beta: float) -> ndarray:
"""See Eq. 8 of
<NA... |
<filename>xai/compiler/model.py
#!/usr/bin/python
# -*- coding: utf-8 -*-
# Copyright 2019 SAP SE or an SAP affiliate company. All rights reserved
# ============================================================================
""" Compiler - Model """
from __future__ import absolute_import
from __future__ import divis... |
<filename>src/structure_factor/utils.py
"""Collection of secondary functions used in the principal modules."""
import numpy as np
from scipy import stats
from scipy.special import j0, j1, jn_zeros, jv, y0, y1, yv
def get_random_number_generator(seed=None):
"""Turn seed into a np.random.Generator instance."""
... |
<gh_stars>100-1000
import functools
import os.path
import re
import imageio
import numpy as np
import scipy.optimize
import boxlib
import cameralib
import data.datasets3d as p3ds
import improc
import matlabfile
import paths
import util
@util.cache_result_on_disk(f'{paths.CACHE_DIR}/muco.pkl', min_time="2020-02-24T1... |
import io
import os
import scipy.misc
import numpy as np
import six
import time
import glob
import math
from six import BytesIO
from PIL import Image, ImageDraw, ImageFont
import tensorflow as tf
from object_detection.utils import ops as utils_ops
from object_detection.utils import label_map_util
from object_detectio... |
<reponame>AlanGamaonov/spbu-gdb2020<filename>src/alg/Utils.py
from pygraphblas import *
from classes.Graph import Graph
from statistics import fmean
from pyformlang.cfg import CFG, Variable, Production, Terminal
import timeit
class Utils:
@staticmethod
def get_transitive_closure_adj_matrix(graph):
res... |
<filename>scripts/permutation_test/permutation_test.py
#!/usr/bin/env python
"""
# usage: python %prog
# python3.7
"""
# permutation test; test enrichment
# linux
import os,sys,re,math,subprocess
from statistics import mean
original_pos='in.bed' # original position; bed file
target_poss=['target_1.bed', 'target_2.... |
# coding=utf-8
import sys
import os
import time
import io
import numpy as np
from glove_simple import Glove
from gensim.models import Word2Vec
from models_params import model_params
from scipy.spatial.distance import cosine, euclidean
class VectorModelWrap:
def __init__(self, model_name, glov... |
from __future__ import print_function
from random import sample, seed
import copy
from astropy.cosmology import FlatLambdaCDM
cosmo = FlatLambdaCDM(H0=73, Om0=0.25)
from os.path import dirname, abspath, join as pjoin
import re, os
import numpy as np
def galdtype_dusty(align=True):
'''Define the data-type for... |
<filename>trend_comparison.py
from app import app, files
import os
from preprocess_files import preprocess_file
from data_quality_assurance import equal_number_of_columns
from variance_filter import filter_variance
from scipy import stats
from clustering import cluster
import pandas as pd
from enums import Ptcf_file, C... |
"""
Module lib.calibration.plotting
This module provides some plots to graphically analyze the calibration of the outputs
of probabilistic binary classifiers.
"""
import numpy as np
import matplotlib.pyplot as plt
from scipy.special import expit as sigmoid
from .pav_rocch import PAV, ROCCH
from .bayes_error_rate im... |
<reponame>trigeorgis/menpofit
"""
This module contains a set of similarity measures that was designed for use
within the Lucas-Kanade framework. They therefore expose a number of methods
that make them useful for inverse compositional and forward additive
Lucas-Kanade.
These similarity measures are designed to be dime... |
'''
ZeusMP 2D planar simulation output file.
Created on 27 Aug 2014
@author: chris
'''
from base import plot_file
import h5py
import numpy as np
# import matplotlib.pyplot as pl
class zeus_file(plot_file):
'''
classdocs
'''
def __init__(self,file_dir):
'''
Constructor
'''... |
import os
import numpy.linalg as la
import numpy as np
from os.path import join, expanduser
from dipy.io import read_bvals_bvecs
from dipy.io.image import save_nifti
from scipy.spatial.transform import Rotation
rel_path = '~/.dnn/datasets/synth'
axes = [[1, 0, 0], [0, 1, 1]]
name = 'synth'
width, height, depth = 30,... |
# -*- coding: utf-8 -*-
# Copyright (c) 2012, <NAME>
# All rights reserved.
# This file is part of PyDSM.
# PyDSM is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at yo... |
<filename>scftpy/fts_confined_1d.py<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
fts_confined_1d
===============
FTS for confined block copolymers in 1D space.
References
----------
1. <NAME>, "The Equilibrium Theory of Inhomogeneous Polymers", 2006, Oxford University Press: New York.
2. <NAME>.; Fredrickson, <NAME>. Ch... |
<filename>main.py
"""
By <NAME> (<EMAIL>), May 13, 2020.
All rights reserved.
"""
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import numpy as np
from post_clustering_pre import spectral_clustering, acc, nmi
import scipy.io as sio
import math
from sklearn.cluster import... |
# HaloFeedback
import warnings
from abc import ABC, abstractmethod
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import simpson
from scipy.special import ellipeinc, ellipkinc, ellipe, betainc
from scipy.special import gamma as Gamma
from scipy.special import beta as Beta
# -----------------... |
######## EPAUNI
with open (fn, 'r') as file:
list_lines = [line for line in file.readlines() if line.strip()]
# %%
list_time_ix=[]
regex = '[+-]?[0-9]+\.?[0-9]*'
for ix, line in enumerate(list_lines):
if 'TIME' in line:
list_time_ix.append((ix, int(float(re.findall(regex, line)[0]) ) ) )
# %% helper fu... |
<filename>search/scipy_minimize_optimization.py
# -*- coding:utf-8 -*-#
from scipy.optimize import minimize
|
import scipy.misc as misc
import numpy as np
import Reader
import cv2
import os
ImageDir="/media/sagi/9be0bc81-09a7-43be-856a-45a5ab241d90/Data_zoo/OpenSurface/OpenSurfaceMaterialsSmall/Images/"
AnnotationDir="/media/sagi/9be0bc81-09a7-43be-856a-45a5ab241d90/Data_zoo/OpenSurface/OpenSurfaceMaterialsSmall/TestLabels/"
... |
import numpy as np
import scipy.linalg as la
from auxiliary import *
a = np.matrix([
[+4 + 0j, 0 + 1j, -3 + 1j, 0 + 2j],
[+0 - 1j, 3 + 0j, +1 + 0j, 2 + 0j],
[-3 - 1j, 1 + 0j, +4 + 0j, 1 - 1j],
[+0 - 2j, 2 + 0j, +1 + 1j, 4 + 0j],
],dtype=complex)
print a - a.getH()
res = la.cholesky(a, lower=False)
mp... |
<reponame>peipeiwang6/Genomic_prediction_in_Switchgrass<gh_stars>0
import sys,os
import pandas as pd
import numpy as np
from scipy.stats import zscore
df = pd.read_csv('/mnt/ufs18/home-110/peipeiw/Documents/Genome_selection/Distribution_of_markers/Markers_distribution_all_unique.txt',header=None,index_col=None,sep='\t'... |
<reponame>OrganicIrradiation/pyLensBlurWigglegram
import argparse
import base64
import math
import numpy as np
import os
import re
import StringIO
import sys
from images2gif import writeGif
from PIL import Image
from scipy import interpolate
parser = argparse.ArgumentParser(description='Script that extracts the depth ... |
import numpy as np
import scipy.stats as ss
from scipy.stats import beta
class TS:
def __init__(self, nbArms, maxReward=1.):
self.A = nbArms
self.clear()
def clear(self):
self.NbPulls = np.zeros(self.A)
self.params = [(2, 2) for i in range(self.A)]
def chooseArmToPlay(sel... |
import numpy as np
from scipy.integrate import solve_ivp
def draw_alpha_d_matix(S, mu, sigma, gamma):
alpha_d_diag = np.random.normal(loc=mu/S, scale=sigma/np.sqrt(S), size=S)
off_diag_pair_cov = np.array([[1., gamma], [gamma, 1.]]) * sigma**2. / S
alpha_d_off_diag = np.random.multivariate_normal(mean=np.... |
from zipfile import ZipFile
import cv2
import os
import numpy as np
import scipy.io as sio
from tensorpack import *
import argparse
"""
python data_sampler.py --zip /tmp/WIDER_val.zip \
--mat /tmp/wider_face_val.mat \
--lmdb /tmp/WIDER_val.lmdb
img buffer is RGB
"""
def ... |
"""
A module that provides core algorithm for optimal matching of backgrounds of
N-dimensional images using (multi-variate) polynomials.
:Author: <NAME> (contact: <EMAIL>)
:License: :doc:`../LICENSE`
"""
import numpy as np
from .utils import create_coordinate_arrays
__all__ = ['build_lsq_eqs', 'pinv_solve', 'rlu_... |
import numpy as np
from netCDF4 import Dataset
def sigma(n_layer):
n = n_layer+1 # no of faces
tol = 1.0e-10
x = np.arange(0,1+tol,1.0/n)
f = np.pi/2.0
s_face = np.tanh(f*x)/np.tanh(f)
s_mid = 0.5*(s_face[0:n-1] + s_face[1:n])
return s_face, s_mid
def morlighem_temperature_nc(out_... |
import torch
from sentence_transformers import SentenceTransformer
from sentence_transformers import models, losses
import pandas as pd
from sentence_splitter import SentenceSplitter, split_text_into_sentences
from sklearn.model_selection import train_test_split
from sklearn.neighbors import LocalOutlierFactor
from skl... |
<filename>sandbox/TTLinearityChecker.py
import scipy
import matplotlib.pyplot as pyplot
import numpy
import pyfits
import os
datadir = '/diska/data/SPARTA/2015-04-17/TTMap_1/'
pupilShiftFile = open(os.path.expanduser('~')+'/data/TTMapping/TTMCommandSequence.txt', 'r')
Tip = []
Tilt = []
gradX = []
gradY = []
"""
fo... |
<reponame>Konstantin8105/py4go<gh_stars>1-10
############################################################################
# This Python file is part of PyFEM, the code that accompanies the book: #
# #
# 'Non-Linear Finite Element Analysis ... |
import time
import itertools
import datetime
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
from sklearn.neighbors import KNeighborsClassifier
from sklearn.cross_validation import train_test_split
from sklearn import metrics
import scipy
class BigBoat(object):
def __init__(self, fil... |
<reponame>laygond/CarND
#!/usr/bin/env python
import rospy
from geometry_msgs.msg import PoseStamped
from styx_msgs.msg import Lane, Waypoint
from scipy.spatial import KDTree
import math
import numpy as np
'''
This node will publish waypoints from the car's current position to some `x` distance ahead.
As mentioned i... |
from coopihc.agents.BaseAgent import BaseAgent
from coopihc.observation.RuleObservationEngine import RuleObservationEngine
from coopihc.observation.utils import base_user_engine_specification
from coopihc.policy.LinearFeedback import LinearFeedback
from coopihc.space.State import State
from coopihc.space.StateElemen... |
import numpy as np
import pandas as pd
import os
from pyens.models import Flywheel, OCV, EcmCell
from pyens.utilities import ivp
from pyens.simulations import Simulator, Data, Current
import matplotlib.pyplot as plt
from scipy import optimize
TESTDATA_FILEPATH = os.path.join(os.path.dirname(__file__), 'CS2_3_9_28_11.c... |
<filename>propensity.py
from sklearn import linear_model
from scipy.sparse import coo_matrix
from scipy.stats import ttest_rel, binom
#from scipy.stats import chisqprob # old version
from scipy.stats import chi2
import numpy as np
from math import log
import sys
filename = sys.argv[1]
param_reg = float(sys.argv[2])
pa... |
from __future__ import division
import argparse
import numpy as np
import scipy as sp
from scipy.spatial.distance import cdist
from icd9 import ICD9
tree = ICD9('codes.json')
def get_icd9_pairs(icd9_set):
icd9_pairs = {}
with open('icd9_grp_file.txt', 'r') as infile:
data = infile.readlines()
... |
def get_image_parameters(
particle_center_x_list=lambda : [0, ],
particle_center_y_list=lambda : [0, ],
particle_radius_list=lambda : [3, ],
particle_bessel_orders_list=lambda : [[1, ], ],
particle_intensities_list=lambda : [[.5, ], ],
particle_speed_list = lambda : [10, ],
particle_dire... |
<reponame>GenoML/genoml<gh_stars>10-100
# -*- coding: utf-8 -*-
"""get_the_SEs.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1Cn5yCIzU5Gtc7Cn4b3py7I6BaKtJj0m0
"""
# Imports
import argparse
import sys
import sklearn
import h5py
import pandas as... |
<filename>src/glove_solution.py
#!/usr/bin/env python3
from scipy.sparse import *
import numpy as np
import pickle
import random
from build_embeddings import store_embeddings_to_txt_file
from options import *
def main():
print("loading cooccurrence matrix")
with open(COOC_FILE, 'rb') as f:
... |
import sys
from functools import partial
from typing import Optional, Tuple
import numpy as np
import pandas as pd
import tqdm
from scipy.spatial import distance as dist
from sklearn.base import (
BaseEstimator,
ClusterMixin,
TransformerMixin,
)
from sklearn.utils.validation import check_is_fitted
from di... |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
get_ipython().system('pip install albumentations > /dev/null')
get_ipython().system('git clone https://github.com/qubvel/efficientnet.git')
get_ipython().system('pip install console_progressbar')
# In[2]:
# This preprocessing portion of the code is provided by foaml... |
#python3 my_detect_faces_video.py --prototxt deploy.prototxt.txt --model res10_300x300_ssd_iter_140000.caffemodel --shape-predictor shape_predictor_68_face_landmarks.data
# import the necessary packages
from imutils import face_utils
import imutils
from scipy.spatial import distance as dist
from imutils.video import Vi... |
<filename>test_depth.py
from __future__ import division
import tensorflow as tf
import numpy as np
import os
import PIL.Image as pil
from PIL import ImageFile
ImageFile.LOAD_TRUNCATED_IMAGES = True # fix PIL image truncated issue
import scipy.misc
import matplotlib.pyplot as plt
import cv2
from deep_slam import DeepSl... |
from .core import mofa_model
from .utils import *
import sys
from warnings import warn
from typing import Union, Optional, List, Iterable, Sequence
from functools import partial
import numpy as np
from scipy.stats import pearsonr
import pandas as pd
from pandas.api.types import is_numeric_dtype
import matplotlib.pypl... |
<filename>dynamo/tl/velocity.py<gh_stars>0
import numpy as np
from scipy.optimize import least_squares
from sklearn.cluster import KMeans
from sklearn.neighbors import NearestNeighbors
def sol_u(t, u0, alpha, beta):
return u0*np.exp(-beta*t) + alpha/beta*(1-np.exp(-beta*t))
def sol_s(t, s0, u0, alpha, beta, gamma... |
<reponame>lxf8519/GAN-cov-matrix
import numpy as np
from scipy.ndimage import imread
import matplotlib.pyplot as plt
import scipy.io as scio
import h5py
def dense_to_one_hot(labels_dense, num_classes):
"""Convert class labels from scalars to one-hot vectors."""
num_labels = labels_dense.shape[0]
#labels_de... |
# -*- coding: utf-8 -*-
# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the... |
import bet.sample as sample
import bet.sampling.basicSampling as bsam
from scipy.stats import distributions as dists
import numpy as np
def baseline_discretization(model,
num_samples=1000,
input_dim=2,
param_ref=None,
... |
import csv
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import font_manager
import scipy.stats
from PIL import Image
# used to pplot and evaluate send new and old polygons
def mean_confidence_interval(data, confidence=0.95):
a = 1.0 * np.array(data)
n = len(a)
m, se = np.mean(a), sci... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""Facility to provide quick fitting of x-y data
For fitting of equation of state, use fitBMEOS instead.
"""
from io import StringIO
from argparse import ArgumentParser, RawDescriptionHelpFormatter
from scipy.optimize import curve_fit
from scipy.stats impo... |
<filename>utils/save_net.py<gh_stars>10-100
import os
from parameters import Parameters
from scipy.io.matlab.mio import savemat
params = Parameters()
def saveTensorToMat(x, varName='x', fileName='', save_dir=params.net_save_dir):
'''
x: is the variable to be saved
name: is the name of the file and name o... |
from googleapiclient.discovery import build
import intent_parser.constants.google_api_constants as doc_constants
import logging
import statistics
class GoogleDocAccessor(object):
"""
A list of APIs to access Google Doc.
Refer to https://developers.google.com/docs/api/reference/rest to get information on ho... |
<reponame>kaungsgit/Python_DSP
# packages used
import numpy as np
import scipy.signal as sig
import matplotlib.pyplot as plt
import sys
import pprint as pp
import numpy.random as random
sys.path.append("../")
import custom_tools.fftplot as fftplot
import control as con
import control.matlab as ctrl
import custom_too... |
<filename>low_level_interface/mixture_impianto_senza_eiettore_sep_function.py<gh_stars>0
import numpy as np
import CoolProp.CoolProp as CP
#import grafici_termodinamici as gt
import grafici_termodinamici_mixture as gt
from scipy.optimize import fsolve
import compressore as c
import matplotlib.pyplot as plt
class Funz... |
import xarray as xr
import numpy as np
import scipy.sparse as sps
import cf_xarray
def remap_camse(ds, dsw, varlst=[]):
#dso = xr.full_like(ds.drop_dims('ncol'), np.nan)
dso = ds.drop_dims('ncol').copy()
lonb = dsw.xc_b.values.reshape([dsw.dst_grid_dims[1].values, dsw.dst_grid_dims[0].values])
latb = d... |
from utils.evaluator import Evaluator
from utils.post_processing import *
from utils.pre_processing import *
from utils.submitter import Submitter
from utils.ensembler import *
import sys
from scipy import sparse
import utils.pre_processing as pre
def diversity(rec_list, datareader):
track_to_art = datareader.get... |
from Bio.PDB import Polypeptide
import numpy as np
import random
from collections import Counter
import scipy.sparse as scsp
def aa_to_index(aa):
"""
:param aa: Three character amino acid name.
:returns: Integer index as per BioPython, unknown/non-standard amino acids return 20.
"""
if Polypeptide.... |
<reponame>bhussain89/TestRepository
import pandas as pd
from netCDF4 import Dataset
import numpy as np
import itertools
from scipy import spatial
from scipy.interpolate import interp1d
from rasterstats import zonal_stats
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
import os
import pvl... |
<gh_stars>1-10
"""
File for processing random mesh segmentations.
Author: <NAME>
"""
import heapq
import math
import os
import numpy as np
import networkx as nx
import cvxopt as cvx
from sympy import Matrix
from visualization import Visualizer3D
from meshpy import Mesh3D
from d2_descriptor import D2Descriptor
from d... |
<reponame>siddharthbharthulwar/Synthetic-Vision-System
#file containing functions useful in initial aggregation of DSM data
import numpy as np
import gdal
import rasterio as rio
import matplotlib.pyplot as plt
import numpy.ma as ma
import math
import cv2 as cv
import rasterio.warp
import rasterio.features
import sci... |
<reponame>alexburky/rflexa
import numpy as np
import obspy
from scipy import signal
import matplotlib
matplotlib.use('Qt4Agg')
import matplotlib.pyplot as plt
# import plotly.graph_objects as go
# from plotly.offline import iplot
# This script makes a contour plot of receiver function data in the time domain as a func... |
import os
import glob
import sacred as sc
import cv2
import scipy.misc
import numpy as np
import tensorflow as tf
from sacred.utils import apply_backspaces_and_linefeeds
from experiments.utils import get_observer, load_data
from xview.datasets import Cityscapes
from experiments.evaluation import evaluate, import_weight... |
import numpy as np
from scipy.spatial.distance import cdist
def compute_ap(good_idx, junk_idx, pred_idx):
cmc = np.zeros(pred_idx.shape)
ngood = good_idx.shape[0]
old_recall = 0.0
old_precision = 1.0
ap = 0
intersect_size = 0
j = 0
good_now = 0
njunk = 0
for i,idx in enumerate(p... |
<filename>src/happy/io.py
# ------------------------------------------------------------------------------
# File: io.py
# Author: <NAME>
# Date: 11/2018
# ------------------------------------------------------------------------------
# Common functions for input/output operations
# --------------------------------... |
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scikit_posthocs as sp
import warnings
import seaborn as sns
import statsmodels.api as sm
from bevel.linear_ordinal_regression import OrderedLogit
import scipy.stats as stats
warnings.filterwarnings("ignore")
from statsmodels.miscmodels.ordina... |
<filename>quantzie/research/match_trading.py<gh_stars>0
import operator
import numpy as np
import statsmodels.tsa.stattools as sts
import matplotlib.pyplot as plt
import tushare as ts
import pandas as pd
from datetime import datetime
from scipy.stats.stats import pearsonr
if __name__ == '__main__':
a = range(10)
... |
<reponame>tung44/janalysis<gh_stars>0
"""Implements the DCT."""
from math import cos, pi, sqrt
import numpy
import scipy.fftpack
def dct2(x_list, n_point=None):
"""Implements the n_point dct2.
:param x_list: The time domain sequence.
:type x_list: list.
:param n_point: The n point size of the DCT to b... |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import interpolate #插值引用
plt.rcParams['font.sans-serif']=['Microsoft YaHei']
plt.rcParams['axes.unicode_minus']=False
#加载数据
data=pd.read_excel('ds-contour-matrix.xlsx',sheet_name='sheet-01',index_col=0)
#自定义插值函数---二维
def extend_dat... |
#!/usr/bin/env python3
import __pystruct_internals__
import fractions
import decimal
class frac:
def __init__(self, num=None, den=None, whl=None):
if num is not None and den is None and whl is None:
if isinstance(num, int):
whl = num
den = 1
num = 0
elif isinstance(num, float... |
<gh_stars>0
# -*- coding:utf-8 -*-
import numpy as np
import scipy as sp
import pandas as pd
import matplotlib.pyplot as plt
import inspect
# それがラムダ式か
def islambda(f):
return inspect.isfunction(f) and f.__name__ == (lambda: True).__name__
class SVM():
def __init__(self, kernel='liner', C=2, tol=0.01, eps=0.01):
... |
<gh_stars>1-10
import open3d as o3d
from sys import argv, exit
from PIL import Image
import math
import numpy as np
import copy
import os
import re
import cv2
import matplotlib.pyplot as plt
from shapely.geometry import Point, Polygon
from scipy.spatial.transform import Rotation as R
def natural_sort(l):
convert = ... |
# Script containing classes and functions for analysis
from sklearn.feature_extraction.text import TfidfVectorizer
from datetime import datetime, timedelta, date
from gensim.models import KeyedVectors
from scipy.cluster.vq import kmeans,vq
from collections import OrderedDict
import matplotlib.pyplot as plt
from collec... |
<filename>tools/avatar/head_rig.py
from arena import *
import numpy as np
from scipy.spatial import distance
from utils import MeanFilter
from face import Face
EXP_HIST_WINDOW = 3
EYE_THRES = 0.17
MOUTH_THRES = 0.05
class HeadRig(object):
def __init__(self, scene, user_id, camera):
self.scene = scene
... |
import numpy as np
from scipy import stats
from clustering_genomic_signatures.util.parse_signatures import (
parse_signatures,
add_parse_signature_args,
)
from clustering_genomic_signatures.util.parse_distance import (
add_distance_arguments,
parse_distance_method,
)
def distance_function_stats(eleme... |
<filename>example_scripts/wod_bgc_ragged_example.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 23 13:53:33 2022
@author: annkat
"""
#%reset
# ====================== LOAD MODULES =========================
import coast
import glob # For getting file paths
import gsw
import matplotlib.pyplot ... |
import numpy as np
import pywt
from pyentrp import entropy as ent
import nolds
import scipy
from scipy import stats
from PyEMD import CEEMDAN
from tqdm import tqdm
def sig_fft(sig, fftn = 35):
features = np.fft.fft(sig, fftn).real
return features
def sig_spectrum(sig, fftn = 35):
features = np.fft.fft(sig... |
<reponame>autocorr/VLA_17A-146_analysis_scripts
#!/usr/bin/env python3
"""
Process the GBT KFPA data cubes.
"""
from pathlib import Path
import h5py
import numpy as np
from scipy import ndimage
import aplpy
import radio_beam
import spectral_cube
from astropy import units as u
from astropy import (coordinates, convol... |
<reponame>maticomp/drcoffee-raw-image-guesser<filename>guesser.py<gh_stars>1-10
import numpy as np
import os
import operator
from scipy import ndimage
from PIL import Image
def get_possible_dimensions(path):
pixel_count = os.path.getsize(path) / 2
length_array = np.arange(1, pixel_count)
widths = length... |
<gh_stars>1-10
import numpy as np
from scipy.integrate import ode
class class_SDE:
# dx/dt = state_eqn(t, x)
# y = output_eqn(x) + v
def __init__(self, xdim, ydim, Q, R):
### システムのサイズ
self.xdim = xdim #状態の次元
self.ydim = ydim #観測の次元
### 雑音
self.Q = np.array(Q) ... |
<reponame>scottgigante/molecular-cross-validation
#!/usr/bin/env python
import argparse
import logging
import pathlib
import pickle
import numpy as np
import scipy.sparse
import scanpy as sc
from molecular_cross_validation.util import poisson_fit
def main():
parser = argparse.ArgumentParser()
parser.add_... |
<reponame>e96031413/DRAGON<filename>dataset_handler/dataset.py<gh_stars>10-100
import numpy as np
import pandas as pd
import os
import scipy.io
"""
Different Datasets for our model
Some of the code provided by <NAME>: https://github.com/yuvalatzmon/COSMO
"""
class Dataset(object):
"""
Dataset is an abstract cl... |
<reponame>robnvuurdraak/DataScienceTools
import math
from fractions import Fraction
from timeit import timeit
from linear_algebra.helpers.matrix_helpers import *
class Matrix:
"""
Matrix object which is internally a list of lists containing Fractions
Matrices return new matrices with results, they dont e... |
<reponame>BoxiLi/repeater-cut-off-optimization<filename>optimize_cutoff.py
import time
from copy import deepcopy
import multiprocessing as mp
from collections.abc import Iterable
from itertools import product
from functools import partial
import logging
import numpy as np
from scipy.optimize import differential_evolut... |
<filename>track_sim.py
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import pandas
import numpy as np
from psopy import _minimize_pso, init_feasible
from scipy.stats import norm
import matplotlib.pyplot as plt
def LapTimeSim(df, race_line):
df['Raceline_x'] = df.Left_x + (... |
<filename>Source/Datacustom.py
import os
import scipy.io
import numpy as np
import argparse
parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--file", type=str, default='/home/ljj/PycharmWork/CtoP/Data/Cylinder2D.mat')
parser.add_argument("--gap", type=int, d... |
from fractions import gcd
N, X = map(int, input().split())
print(3 * (N - gcd(N, X)))
|
"""
Author: <NAME>
Date: 11.10.2019
Contains classes for Chaos expansions, Exponential families (containing Beta, Bernoulli, Gauss and Gamma),
Optimizer for the standard RVM and sparse RVM.
"""
__all__ = ['ChaosModel', 'ExponFam', 'VariationalOptimizer', 'SparseVariationalOptimizer']
import numpy as np
import math ... |
from sympy import symbols, oo, Sum, harmonic
from sympy import difference_delta as dd
from sympy.utilities.pytest import raises
n, m, k = symbols('n m k', integer=True)
def test_difference_delta():
e = n*(n + 1)
e2 = e * k
assert dd(e) == 2*n + 2
assert dd(e2, n, 2) == k*(4*n + 6)
raises(ValueE... |
<reponame>wazenmai/Python-WORLD
#build-in imports
import sys
#3rd party imports
import numpy as np
from scipy.interpolate import interp1d
import numba
def cheaptrick(x, fs, source_object, q1=-0.15, fft_size=None):
'''
Generate smooth spectrogram from signal x, eliminating the affect of fundamental frequency F... |
import redis
import argparse
from collections import defaultdict
import json
# Install dependencies hiredis, redis
import math
import json
import numpy as np
from scipy import spatial
"""
This script again generates an input for tsne visualization. This script specifically reads VERSE embeddings (https://github.com/xgf... |
<reponame>20chase/cartpole_rl
#! /usr/bin/env python3
import argparse
import gym
import time
import ray
import threading
import roboschool
import util
import scipy.signal
import numpy as np
import tensorflow as tf
import tensorlayer as tl
from tabulate import tabulate
from gym import wrappers
from collections import ... |
<reponame>dominicrufa/aquaregia
#!/usr/bin/env python
# coding: utf-8
# generate droplet data
# In[1]:
from jax.config import config
config.update("jax_enable_x64", True)
config.update("jax_debug_nans", True)
config.parse_flags_with_absl()
import jax
import jax.numpy as jnp
from jax import random
import numpy as n... |
<reponame>judithabk6/Clonesig_analysis<filename>signature_code/evaluate_deconstructsig.py
#!/usr/bin/env python
# -*- coding:utf-8 -*-
import pandas as pd
import sys
from collections import Iterable
import numpy as np
import pickle
import scipy as sp
from clonesig.data_loader import SimLoader
from clonesig.evaluate imp... |
<filename>t2c/beam_convolve.py
import numpy as np
from .cosmology import angular_size
from scipy import signal
from .helper_functions import print_msg
from .smoothing import gauss_kernel, get_beam_w
from .helper_functions import fftconvolve
def beam_convolve(input_array, z, fov_mpc, beam_w = None, max_baseline = None,... |
"""Adaptive Memory Programming for Global Optimization (AMPGO).
added to lmfit by <NAME> (2018)
based on the Python implementation of <NAME>
(see: http://infinity77.net/global_optimization/)
Implementation details can be found in this paper:
http://leeds-faculty.colorado.edu/glover/fred%20pubs/416%20-%20AMP%20(T... |
<filename>PINN_7.py<gh_stars>0
import torch
from torch import autograd
import numpy as np
from pyDOE import lhs # Latin Hypercube Sampling
import torch.nn as nn
import time
import matplotlib.pyplot as plt
import scipy.special as sc
import scipy.io
def training_points(n_bd, n_int):
# n_bd number of points on boun... |
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import linregress
SortAndSearch_Means = np.asarray( [ 0.000002, 0.000002, 0.000002, 0.000002, 0.000003, 0.000004, 0.000006, 0.000010, 0.000019, 0.000036, 0.000075, 0.000163, 0.000343, 0.000755, 0.001597, 0.003263, 0.006755, 0.014400, 0.028883, 0.0580... |
from scipy.interpolate import spline, interp1d
from scipy.signal import hilbert
from numpy.fft import fft, ifft
from math import pi
import numpy as np
import matplotlib.pyplot as plt
from tkinter import filedialog
def normalize_image_(im, c1, c2):
im_norm = im - c1
im_norm *= 1/c2
im_norm[np.where(im_no... |
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