text string |
|---|
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 22 00:25:51 2019
@author: user
"""
import json
import csv
import numpy as np
import librosa
import matplotlib.pyplot as plt
from scipy.signal import medfilt, butter, filtfilt
from sklearn.metrics import f1_score, accuracy_score
from keras.models import load_model
from ke... |
import os
import datetime
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import numpy as np
import scipy.misc as misc
import torch
import torch.optim as optim
from utils.nadam import Nadam
from utils.n_adam import NAdam
import torch.optim.lr_scheduler as lrs
from utils.cls import CyclicLR
fr... |
import pandas as pd
from scipy import stats
import numpy as np
import logging
def missing_values_table(df):
mis_val = df.isnull().sum()
mis_val_percent = 100 * df.isnull().sum() / len(df)
mis_val_table = pd.concat([mis_val, mis_val_percent], axis=1)
mis_val_table_ren_columns = mis_val_table.rename(
... |
<reponame>ilnanny/Inkscape-addons<gh_stars>1-10
#! /usr/bin/env python
'''
<NAME> 2017 ("Do what you like with it, no liability" license)
Based on <NAME> (<EMAIL>) and <NAME> (<EMAIL>) 'Render Gear'
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warr... |
<filename>probdrift/MVN_helpers.py
from scipy.stats import chi2
from math import pi
import numpy as np
def elipse_points(sigma, alpha: float = 0.95) -> np.ndarray:
"""
Parameters
----------
alpha: the confidence level for the elipse.
L: The lower triangular of the covariance matrix.
Returns
... |
import scipy.sparse as sp
from sklearn.linear_model import LinearRegression
class RegressionEm:
def fit(self):
pass
def predict(self):
return 1
if __name__ == "__main__":
rem = RegressionEm()
x = sp.rand(100, 100)
lr = LinearRegression()
print(f"Prediction results: {rem.pre... |
<filename>all/plugin-dowker/errorMatrixToDowker.py<gh_stars>1-10
import csv
import json
import numpy
import networkx as nx
import matplotlib.pyplot as plt
from random import seed
import random
import scipy
import time
import math
import plotly.graph_objs as go
import plotly
from plotly.offline import iplot
pgCache =... |
<reponame>nmoisseeva/moist_adiabats
#INPUT
Tmin=-100.
Tmax=100.
THmin =-68. #because we don't start at standard pressure -86 is ~70C moist adiabat
THmax= 42.
Pbot = 105
Ptop = 1 #kPa - upper atmosphere limit surface
Plim = 1
degree =10 #degree of polinomial to model the curves
#=================================... |
<filename>STUDY2/ml_model_train_function_deprecated.py
# -*- coding: utf-8 -*-
from utils import *
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
import librosa
import torch.optim as optim
import torchvision
import torchvision.transforms as transforms
from torch.autograd... |
#!/usr/bin/env python
import os
import sys
import argparse
import pat3dem.star as p3s
import scipy.optimize as opt
from EMAN2 import EMData, Transform
#from sparx import generate_ctf, filt_ctf
def main():
progname = os.path.basename(sys.argv[0])
usage = progname + """ [options] <mrc>
Use one 2D image to derive the... |
<gh_stars>1-10
from scipy.optimize import linprog
def main() -> None:
C, D = map(int, input().split())
c = [-1000, -2000]
A = [[3/4, 2/7], [1/4, 5/7]]
b = [C, D]
bounds = [(0, None), (0, None)]
res = linprog(c, A_ub=A, b_ub=b, bounds=bounds, options={'tol': 1e-9})
print(-res.fun)
if __n... |
<gh_stars>0
# -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2018, 2019.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source tree or at http://www.apache.org/licenses/LICENSE-... |
# cython: language_level=3
# -*- coding: utf-8 -*-
"""
This module contains basic low-level functions that combines an Expression
with an Evaluation objects to produce a new Expression following generic
algorithms.
"""
import sympy
from typing import Optional
from mathics.core.atoms import Number
from mathics.core.... |
<filename>src/figSnvPower.py
#!/usr/bin/env python
import sys
import matplotlib as mpl
if len(sys.argv) > 1:
mpl.use('Agg')
from pylab import *
from diData import persons, CN
from scipy import stats
from collections import defaultdict
def pltD(aAll,c,f,t,lw=1,onY=False,):
a = array(aAll)[logical_not(isnan(aA... |
<reponame>Seondong/Customs-Fraud-Detection
import numpy as np
import random
import sys
import math
from datetime import datetime, timedelta
import torch
from .DATE import DATESampling
from .drift import DriftSampling
from utils import timer_func
import scipy.io
import pandas as pd
import torch.nn as nn
import torch.nn... |
<reponame>fuyawangye/stereopy
#!/usr/bin/env python3
# coding: utf-8
"""
@author: <NAME> <EMAIL>
@last modified by: <NAME>
@file: find_markers.py
@time: 2021/3/14 14:52
change log:
2021/05/20 rst supplement. by: qindanhua.
2021/06/20 adjust for restructure base class . by: qindanhua.
"""
import pandas as pd
... |
<filename>pycst/pycst_data_analyser.py<gh_stars>1-10
import numpy as np
from scipy.signal import find_peaks
import os
import pycst_ctrl
class PyCstDataAnalyser:
""" Used to analyse data exported by CST"""
def __init__(self, opts):
# Initialize attributes
# Polarization indicator
sel... |
# -*- coding: utf-8 -*-
"""Format int of float."""
from fractions import Fraction
class Format: # pylint: disable=R0903
"""Output Formats for int or float."""
@staticmethod
def get_fraction(val_float: float) -> str: # noqa: WPS602
"""Format a fraction from a float."""
return str(Fracti... |
<filename>plugin/spikeTools/sort_spikes.py
# -------------------------------------------------------------------------------
# Copyright (c) 2015 <NAME>.
# All rights reserved. This program and the accompanying materials
# are made available under the terms of the Simplified BSD License
# which accompanies this distrib... |
import matplotlib.pyplot as plt
import numpy as np
from scipy import signal
from scipy.io import wavfile
from pydub import AudioSegment
#ASSUME THERE IS ALREADY A FILE IN MONO FORMAT NAMED test_mono.wav
yMax = (int)(input("Enter maximum frequency value to visualize: "))
sample_rate, samples = wavfile.read('Testing_F... |
<reponame>Self-guided-Approximate-Linear-Programs/Self-guided-ALPs-and-Related-Benchmarks
# -*- coding: utf-8 -*-
"""
-------------------------------------------------------------------------------
Authors: <NAME> | https://parshanpakiman.github.io/
<NAME> | https://selvan.people.uic.edu/
... |
<reponame>kingjr/jr-tools<gh_stars>10-100
import numpy as np
def least_square_reference(inst, empty_room=None, max_times_samples=2000,
bad_channels=None, scaler=None, mrk=None,
elp=None, hsp=None):
"""
Fits and applies Least Square projection of the refere... |
import cvxpy as cp
import numpy as np
import pandas as pd
from scipy.special import lambertw, kl_div
from numbers import Number
from scipy import stats
from emm.utils import onehot_hist
class EqualityLoss:
def __init__(self, fdes):
if isinstance(fdes, Number):
fdes = np.array([fdes])
s... |
<filename>recommender/src/helper.py
from tqdm import tqdm
from ast import literal_eval
from collections import defaultdict
from scipy.sparse import coo_matrix, csr_matrix
from sklearn.metrics.pairwise import cosine_similarity
import os
import heapq
import zipfile
import pandas as pd
import numpy as np
import scipy.spa... |
# ===============================================
# <NAME>
# Bootcamp Data Analytics
# Version 1.0.0 03/02/2020
# 1.0.1 03/04/2020
# 1.0.2 03/05/2020
# 1.0.3 03/06/2020
# File to run the PyPoll analysis
# ===============================================
# Add required modules
import os
i... |
<reponame>milo-lab/biomass_distribution<filename>animals/annelids/annelids.py
# coding: utf-8
# In[1]:
# Load dependencies
import pandas as pd
import numpy as np
from scipy.stats import gmean
import sys
sys.path.insert(0, '../../statistics_helper/')
from excel_utils import *
# # Estimating the biomass of Annelids
... |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
# Copyright (c) 2020, Sandflow Consulting LLC
#
# 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, ... |
<gh_stars>0
import os, sys
import csv
from os.path import isfile, join
from collections import Counter
import matplotlib.pyplot as plt
import streamlit as st
import pandas as pd
import numpy as np
import altair as alt
import sklearn
import numpy
from sklearn.cluster import DBSCAN
from sklearn import metrics
from sklear... |
import numpy as np
import matplotlib.pyplot as plt
import uncertainties
from scipy.signal import find_peaks
from scipy.optimize import curve_fit
import scipy.constants as sc
import scipy.integrate as integrate
from uncertainties import ufloat
from uncertainties import unumpy as unp
from uncertainties.unumpy import nomi... |
import numpy as np
from .diagnosis import get_AICc, get_AIC, get_BIC, get_CV
from scipy.spatial.distance import pdist
from .model import GWR, TWR, GTWR
from .search import golden_section, twostep_golden_section
getDiag = {'AICc': get_AICc, 'AIC': get_AIC, 'BIC': get_BIC, 'CV': get_CV}
delta = 0.38197
class s... |
<filename>src/phat/tseries.py
"""
Custom functionality for generating ARMA-GARCH time-series forecasts.
"""
from __future__ import annotations
from typing import Iterable, Union, Tuple, TYPE_CHECKING
import warnings
import numpy as np
import pandas as pd
import scipy
import matplotlib.pyplot as plt
import numba as nb... |
<gh_stars>0
import argparse
import glob, os, tempfile, zipfile
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import scipy as sc
from sklearn import metrics
from sklearn.metrics import f1_score, accuracy_score
from sklearn.metrics import roc_curve, confusion_matrix
import torch
import torch.nn a... |
<reponame>activityMonitoring/actipy
import numpy as np
import pandas as pd
import scipy.signal as signal
import statsmodels.api as sm
__all__ = ['lowpass', 'calibrate_gravity', 'detect_nonwear', 'resample', 'get_stationary_indicator']
def resample(data, sample_rate, dropna=False):
"""
Nearest neighbor resa... |
<reponame>trangnv/geb-simulations-h20<gh_stars>1-10
import math
import random
from decimal import *
import logging
import scipy
from .uniswap import get_output_price, get_input_price, buy_to_price, sell_to_price
import models.system_model_v3.model.parts.failure_modes as failure
def init_rate_traders(params, state):
... |
import numpy as np
import time
import scipy.ndimage.interpolation as inter
import cv2
import matplotlib.pyplot as plt
from skimage import morphology
def resize_mask(mask,img_size):
resized_volume=[]
for plot, each_slice in enumerate(mask):
resized_image,resized_volume=resize_mask_slice(each_slice, img_... |
import time
from collections import deque
import torch
import torch.nn.functional as F
from env.envs import create_atari_env
from models.model import ActorCritic
from env.Environment import Environment
#I must get totally known about the whole structure of the model. And I should have a taste or VITA tea to control ... |
<filename>vbsem_experiments/discrete.py
from scipy.io import arff
import numpy as np
import pandas as pd
data_name = "asia"
missing_percentage = 0.2
data_types = "cccccccc"
i = 1
percentage_string = "0" + str(int(missing_percentage * 10))
base_path = "../vbsem_data/discrete/" + data_name + "/" + percentage_string + "... |
import argparse
import os
import pypcd
import sklearn.cluster
import itertools
import tqdm
import hdbscan
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches
from kitti_bounding_box_provider import get_bounding_boxes, count_points_bboxes_matching, transform_points_velo_to_rect, get_2... |
# -*- coding: utf-8 -*-
import numpy as np
from geonetworkx.geograph import GeoGraph
from geonetworkx.utils import get_line_start
import geonetworkx as gnx
from shapely.geometry import Polygon, LineString, MultiPolygon
from shapely.ops import cascaded_union
import math
from typing import Union
from scipy.spatial import... |
<filename>CSIKit/filters/passband.py
from scipy import signal
import numpy as np
def lowpass(csi_vec: np.array, cutoff: float, fs: float, order: int) -> np.array:
nyq = 0.5*fs
normal_cutoff = cutoff/nyq
b, a = signal.butter(order, normal_cutoff, btype="low", analog=False)
return signal.filtfilt(b, a, ... |
<filename>model.py
import csv
import cv2
import numpy as np
import pandas as pd
import scipy.misc
from scipy.ndimage import rotate
from scipy.stats import bernoulli
from keras.models import Sequential
from keras.layers import Flatten, Dense, Lambda, Convolution2D, Dropout, MaxPooling2D, Activation
from keras.layers i... |
<reponame>j-m-dean/uravu
"""
Tests for sampling module
"""
# Copyright (c) <NAME>
# Distributed under the terms of the MIT License
# author: <NAME>
import unittest
import numpy as np
from numpy.testing import assert_equal
from scipy.stats import norm
from uravu import sampling, utils
from uravu import relationship
fr... |
<gh_stars>0
import scipy
from hydroDL.data import dbBasin
from hydroDL.master import basinFull
import os
import pandas as pd
from hydroDL import kPath, utils
import importlib
import time
import numpy as np
dirCode = os.path.join(kPath.dirData, 'USGS', 'inventory', 'ecoregion')
fileCode = os.path.join(dirCode, 'basinE... |
from PIL import Image, ImageDraw
import numpy as np
import math
from scipy import signal
import ncc
from functools import reduce
scaleFactor = 0.75
# creates a list of images with each image being 3/4 the size of the previous
def MakePyramid(im: Image, minSIze: (int, int)) -> list:
resizedImages = []
minx, m... |
# Name: PercentileScoreFields.py
# Purpose: Will add selected fields as percentile scores by extending a numpy array to the feature class.
# Author: <NAME>
# Last Modified: 4/15/2021
# Copyright: <NAME>
# Python Version: 2.7-3.1
# ArcGIS Version: 10.4 (Pro)
# --------------------------------
# Copyright 2017 <NAME>
#... |
import pprint
import numpy as np
from sklearn import preprocessing
from sklearn import svm
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import KFold
from scipy.stats.mstats import gmean
from sklearn.neural_network import MLPRegressor
from sklearn.metrics import r2_score
from sklearn.me... |
<reponame>joebentley/simba
from simba import transfer_function_to_graph, tf2rss
from sympy import symbols
s = symbols('s')
gamma = symbols('gamma', real=True, positive=True)
tf = (s - gamma) / (s + gamma)
transfer_function_to_graph(tf, 'unstable-filter.pdf')
tf = (s + gamma) / (s - gamma)
transfer_function_to_grap... |
<filename>dps/datasets/atari.py
import gym
import numpy as np
import os
import tensorflow as tf
import matplotlib.pyplot as plt
from collections import defaultdict
from pprint import pprint
from scipy import optimize
from gym_recording import scan_recorded_traces
from dps import cfg
from dps.datasets.base import Image... |
<reponame>eas342/jtow
from astropy.io import fits, ascii
import matplotlib.pyplot as plt
import csv
import numpy as np
import asdf
import astropy.units as u
import glob
import time
import yaml
import pdb
from scipy import ndimage
from copy import deepcopy
import pkg_resources
import os
import glob
import crds
import tq... |
<reponame>joepatmckenna/fem
import numpy as np
import numpy.linalg as nplin
import scipy as sp
from scipy.special import erf as sperf
from scipy.linalg import pinv as spinv
from matplotlib.backends.backend_pdf import PdfPages
import matplotlib.pyplot as plt
import multiprocessing
import os
import sys
dt, T, N_var = 0.... |
import warnings
import numpy as np
import scipy.signal as signal
import torch
from scipy.ndimage.filters import gaussian_filter1d
from .builder import FILTERS
@FILTERS.register_module(name=['Gaus1dFilter', 'gaus1d'])
class Gaus1dFilter:
"""Applies median filter and then gaussian filter. code from:
https://g... |
<filename>2_analise_visualizacao_dos_dados/utils.py<gh_stars>0
import scipy.stats
import numpy as np
import pandas as pd
from math import ceil
import matplotlib.pyplot as plt
from scipy.stats import kurtosis, skew
def dfa1d(time_series, degree):
# 1. A série temporal {Xk} com k = 1, ..., N é integrada na chamada ... |
############ SYMMETRY PLOTS ############
# ==========> https://docs.bokeh.org/en/latest/docs/user_guide/plotting.html
# Configure for Jupyter Notebook Display
from bokeh.plotting import figure
from bokeh.io import output_notebook, push_notebook, show
output_notebook()
plot = figure()
plot.circle([1,2,3], ... |
<filename>data_management/Excel Work/Filter by zscore.py
# -*- coding: utf-8 -*-
"""
Created on Sat Mar 17 11:43:14 2018
@author: james
"""
# Import zscore
from scipy.stats import zscore
import pandas as pd
file = ""
df = pd.read_csv(file)
# Group the df and standardize
standardized = df.groupby("")["", ""].transfo... |
<gh_stars>10-100
#!/usr/bin/env python
# -*- coding: utf-8 -*-
""" A module containing a number of interesting image filter effects,
such as:
* Black-and-white pencil sketch
* Warming/cooling filters
* Cartoonizer
"""
import numpy as np
import cv2
from scipy.interpolate import UnivariateSpline
__aut... |
<reponame>EdwardZheng0312/3d-data-diver
import h5py
import itertools
import matplotlib
matplotlib.use('TkAgg')
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import animation
import mpldatacursor
import numpy as np
... |
<reponame>MetaboKit/metabokit
import glob
import collections
import statistics
import operator
import re
import sys
import os
from bisect import bisect_left
import bisect
import DDAreadlib
import DDAcommonfn
from DDAcommonfn import bound_ppm
param_set={
"mzML_files",
"library",
"ms1_ppm",
... |
<filename>tests/test_stats.py
import pytest
from timspyutils.stats import *
import numpy as np
from scipy import stats
def test_one_scaled_uniform_sample():
a = 1e-1
b = 1e1
lsd_uniform = LogScaledDistribution(stats.uniform, a, b)
s = lsd_uniform.rvs()
assert b >= s >= a
assert s.dtype.type ==... |
import os
import csv
import json
import torch
import scipy.misc
import torch.nn as nn
import torchvision.transforms as transforms
from torch.utils.data import Dataset
from PIL import Image
MEAN = [0.5, 0.5, 0.5]
STD = [0.5, 0.5, 0.5]
def number_value(path_name):
num_start = path_name.find('/')
num_str = path_na... |
<reponame>vvoelz/ratespec
#!/usr/bin/env python
import os, sys, glob
import scipy
from scipy.linalg import pinv
import numpy as np
import matplotlib
from pylab import *
from RateSpecClass import *
from RateSpecTools import *
UsePlotting = False
try:
from PlottingTools import *
UsePlotting = True
except:
... |
"""Problem 69
07 May 2004
Euler's Totient function, φ(n) [sometimes called the phi function], is
used to determine the number of numbers less than n which are
relatively prime to n. For example, as 1, 2, 4, 5, 7, and 8, are all
less than nine and relatively prime to nine, φ(9)=6.
n Relatively Prime φ(n) n/φ(n)
2 1 1 ... |
"""Core of CASA-type sound analysis system."""
import numpy as np
import scipy.interpolate
import scipy.signal
import sbpca
import SAcC
# pitchogram
#
# track_pitch
#
# track_multi_pitch
#
# spectrum_for_pitch
"""
Plan:
- calculate pitch posteriors with SAcC
- Find one or more pitch tracks with multi-hyp viterbi... |
from sklearn.preprocessing import Normalizer
from collections import defaultdict
import scipy.io
import os
import requests
import numpy as np
import pandas as pd
import utils
import IPython.display as ipd
import matplotlib
import resource
import features as ft
import heapq
from sklearn.metrics.pairwise import pairwise_... |
from mechtest_ufmg.Utils import *
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import simps, trapz
from scipy.optimize import curve_fit
import os
import csv
# from mechtest_ufmg.Utils import *
# Conversion factor from psi to MPa
psi_to_mpa = 0.00689476
class Tensile_test:
'''
Tensile... |
import cv2
import numpy as np
from matplotlib import pyplot as plt
from PIL import Image
from numpy import asarray
from mtcnn.mtcnn import MTCNN
from scipy.spatial.distance import cosine
from keras_vggface.vggface import VGGFace
from keras_vggface.utils import preprocess_input
import sys
# extract a single f... |
# Copyright (c) 2016,2017 MetPy Developers.
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""Contains a collection of generally useful calculation tools."""
import functools
import warnings
import numpy as np
import numpy.ma as ma
from scipy.spatial import cKDTree
... |
<gh_stars>1-10
import numpy as np
import scipy.linalg as la
from parla.comps.qb import QBDecomposer, QB2
from parla.comps.rangefinders import RF1
from parla.comps.sketchers.aware import RS1
import parla.comps.sketchers.oblivious as oblivious
import parla.utils.linalg_wrappers as ulaw
class SVDecomposer:
def __ca... |
# Units : SI Units
import numpy as np
import scipy
from scipy.integrate import quad as integrate
from matplotlib import pyplot as plt
pi = np.pi
mu0 = 4e-7 * pi
def vec(*args):
return np.atleast_2d(args).T
def R(x,y,z):
# Rotation Matrix
np.matrix()
class Pose(object):
def __init__(self):
se... |
<reponame>THU-luvision/Occuseg<filename>examples/ScanNet/train_instance.py
# import open3d
from datasets import ScanNet
from utils import evaluate_scannet, evaluate_stanford3D,WeightedCrossEntropyLoss, FocalLoss, label2color,evaluate_single_scan,cost2color
from model import ThreeVoxelKernel
from model import DenseUNet... |
<reponame>collector-m/pole-localization
import numpy as np
import os
import matplotlib.pyplot as plt
import cluster
import scipy.special
import scipy.stats
globalmapname_gt = "globalmap_gt_cluster"
globalmapfile = os.path.join('data/pole-dataset/NCLT', globalmapname_gt + '.npz')
data = np.load(globalmapfile)
evalmapd... |
# -*- coding: utf-8 -*-
import csv
import os
from mantarray_desktop_app import mc_simulator
from mantarray_desktop_app import MICRO_TO_BASE_CONVERSION
from mantarray_desktop_app import SERIAL_COMM_ADDITIONAL_BYTES_INDEX
from mantarray_desktop_app import SERIAL_COMM_CHECKSUM_LENGTH_BYTES
from mantarray_desktop_app impo... |
<gh_stars>1-10
from numpy import asarray, diag, median, random
from numpy.testing import assert_allclose
from scipy.stats import ncx2
from chiscore import davies_pvalue, liu_sf
def test_pval_calibration1():
dof = [1, 1, 1]
w = [0.5, 0.4, 0.1]
loc = [0.0, 0.0, 0.0]
random.seed(1)
samples = _sampl... |
import numpy as np
import theano
import theano.tensor as T
from scipy.misc import logsumexp
from pdb import set_trace
def index2onehot(index, N):
"""
Transforms index to one-hot representation, for example
Input: e.g. index = [1, 2, 0], N = 4
Output: [[0, 1, 0, 0], [0, 0, 1, 0], [1, 0, 0, 0]]
... |
<filename>twitter-aq/utils.py
import zipfile
import pandas as pd
import numpy as np
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix
from scipy.sparse import vstack
from scipy.sparse import hstack
from sklearn.preprocessing import normalize
pd.options.mode.chained_assignment = None
np.seterr(divi... |
#!/usr/bin/env python3
import sys
import numpy as np
import cv2
import roslib
import rospy
# import tf
import struct
import time
import os
import rospkg
import math
import argparse
import PIL
import pandas as pd
import scipy.misc
import random
from sensor_msgs import point_cloud2
from sensor_msgs.msg import Image
fro... |
<gh_stars>1-10
import numpy as np
from scipy import linalg
def main():
'''
线性代数方程组：
（1） x + y + z = 6
（2） 2y + 5z = -4
（3） 2x + 5y - z = 27
求解：
'''
A = np.array([[1, 1, 1], [0, 2, 5], [2, 5, -1]])
B = np.array([6, -4, 27])
x = linalg.solve(A, B)
print(x)
if __name__ == '... |
<filename>pylearn2/format/target_format.py<gh_stars>1-10
"""Code for reformatting supervised learning targets."""
from operator import mul
import numpy as np
import scipy
import scipy.sparse
import theano.sparse
from theano import tensor, config
class OneHotFormatter(object):
"""
A target formatter that tran... |
# -*- coding: utf-8 -*-
#
# Authors: Swolf <<EMAIL>>
# Date: 2021/1/07
# License: MIT License
"""
Discriminal Spatial Patterns.
"""
from typing import Optional, Union, List, Tuple, Dict
from itertools import combinations
import numpy as np
from scipy.linalg import eigh
from scipy.stats import pearsonr
from numpy impor... |
import os
import errno
import sys
import time
import traceback
import re
import hashlib
import numpy as np
import scipy
from sigvisa.database.dataset import *
from sigvisa.database.signal_data import *
from sigvisa.database import db
import sigvisa.utils.geog
import obspy.signal.util
from sigvisa import *
from sigvi... |
"""
experiment6_2.py
Extension to experiment6 that uses the NEAT algorithm to evolve the network's weights.
"""
import argparse
import csv
import multiprocessing as mp
import os
import shutil
import time
from collections import Counter
import matplotlib.pyplot as plt
from numpy import mean
from scipy.stats import gme... |
<reponame>hebinalee/human_PAC_parcellation
#################################################################
## STATISTICAL TEST
##
## roiconn : To save the FC matrix in target ROI-wise
## ttest : To perform two-sample t-test for each pair of ROIs
## and correct multiple comparison problem
##########... |
<filename>FIR-design1.py
#coding:utf-8
# approximate minimum-phase FIR filter design from specified frequency characteristic by use Hilbert transform
#
# Check version
# Python 3.6.4 on win32 (Windows 10)
# numpy 1.16.3
# scipy 1.4.1
# matplotlib 2.1.1
import argparse
import csv
import math
import matplotlib.p... |
__author__ = 'jhaux'
# -*- coding: utf8 -*-
import cv2
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.colors as colors
import matplotlib.cm as cmx
from matplotlib.colors import BoundaryNorm
from matplotlib.ticker import MaxNLocator
import scipy.ndimage as n... |
<reponame>Thundzz/advent-of-code-2021
from scipy import ndimage
from functools import lru_cache
import numpy as np
def to_int(c):
return 1 if c == "#" else 0
def parse_input(filename):
with open(filename) as file:
content = file.read()
algo, img = content.split("\n\n")
img = np.matrix([ list(... |
"""
Created on Tue July 13 12:01 2021
@author: juliaroquette
Spin evolution model implemented in the development of the study by
Roquette et al. 2021.
The class SpinEvolutionCode performs the spin evolution modeling of stars
in the mass range 0.1-1.3 Msun. For a details on the theoretical background
in the model, s... |
<reponame>Kate-Willett/Climate_Explorer
#!/usr/local/sci/bin/python
# PYTHON3
#
# Author: <NAME>
# Created: 16 October 2015
# Last update: 20 July 2020
# Location: /data/local/hadkw/HADCRUH2/UPDATE2014/PROGS/PYTHON/
# GitHub: https://github.com/Kate-Willett/Climate_Explorer/tree/master/PYTHON/
# ---------------------... |
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 10
@author: jaehyuk
"""
import numpy as np
import scipy.stats as ss
import scipy.optimize as sopt
from . import normal
from . import bsm
import pyfeng as pf
'''
MC model class for Beta=1
'''
class ModelBsmMC:
beta = 1.0 # fixed (not used)
vov, rho = 0.0, 0... |
<filename>frp.py
#!/usr/bin/python
from scipy import ndimage
import numpy as np
from osgeo import gdal
import datetime
from scipy.stats import gmean
import math
import argparse
import os.path
import time
# Start time
start = time.time()
# Maximum latitude default, minimum and maximum
DEF_MAX_LAT = 65.525
MIN_MAX_LAT... |
<reponame>HSE-LAMBDA/RheologyReconstruction
import os
import re
import numpy as np
import torch
from torch.utils.data import Dataset
from transforms import DifferentialTransform
from functools import reduce
from scipy.ndimage import gaussian_filter
class SeismogramBatch():
"""
Custom batch with memory pinnin... |
import numpy as np
from numpy import array
from sympy import symbols, cos, sin, pi, simplify, sqrt, atan2, acos
from sympy.matrices import Matrix
from math import radians
class Kinematics(object):
"""description of class"""
def transformation_matrix(self, q, d, a, alpha):
return Matrix([[ co... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Fri May 21 20:23:28 2021
@author: lnajt
"""
import pandas as pd
import itertools
from scipy.stats import powerlaw
import nltk
import re
import gensim.models
#import numba
import numpy as np
import sklearn
import numpy as np
from sklearn.base import BaseEstim... |
import numpy as np
from typing import Optional
from pathlib import Path
from matplotlib import pyplot as plt
from scipy.cluster.hierarchy import dendrogram, linkage, cophenet
from scipy.spatial.distance import pdist, squareform
from scipy.stats import sem, t
from ludwig.results import gen_param_paths
from entropicst... |
from statistics import variance
from numpy import var
from aggregate.PUMS.count_PUMS_households import PUMSCountHouseholds
from ingest.load_data import load_PUMS
from aggregate.PUMS.count_PUMS_economics import PUMSCountEconomics
from aggregate.PUMS.count_PUMS_demographics import PUMSCountDemographics
from aggregate.PUM... |
####
#### Echo State Network (Reservoir computing) implemented with python
####
# Import modules
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt # For visualization only
from scipy import linalg
from sklearn import preprocessing
from sklearn.model_selection import train_test_split # For data sel... |
<filename>preprocess.py<gh_stars>1-10
import numpy as np
from scipy.io import loadmat
from torch_geometric.data import Data
import torch
from config import N_TARGET_NODES_F, N_SOURCE_NODES_F,N_TARGET_NODES,N_SOURCE_NODES
def convert_vector_to_graph_RH(data):
"""
convert subject vector to adjacenc... |
<filename>selection_albedos.py
#!/usr/bin/env python3
import os
import sys
import argparse
import warnings
import string
warnings.simplefilter(action='ignore', category=FutureWarning)
import h5py
import numpy as np
from mpl_toolkits.basemap import Basemap
import scipy as sp
from scipy.interpolate import griddata
#from... |
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
# Name: romanText/writeRoman.py
# Purpose: Writer for the 'RomanText' format
#
# Authors: <NAME>
#
# Copyright: Copyright © 2020 <NAME> and the music21 Project
# License: BSD, see license.t... |
<filename>psoDemo.py<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import freqz
from collections import Counter
import filters
import PSO
def filterModel(x):
# [fc, bandwidth, gain]
w_final = None
db_final = 0
fs = 44100
for fc, BW, gain in x:
... |
# -*- coding: utf-8 -*-
"""
Main file for SEIR model
"""
from . import school_closure
# DEBUG - dev_utils decorator
from . import dev_utils
dev_utils.decorate_all_in_module(school_closure, dev_utils.base_decorator)
import numpy as np
import pandas as pd
import datetime as dt
from scipy import stats
np... |
from scipy.stats import shapiro, norm, kstest
import pandas as pd
import statsmodels.api as sm
from statsmodels.tsa.stattools import kpss
from statsmodels.tsa.stattools import adfuller
# normality test
def shapiro_wilk_test(data, alpha=0.05):
"""
H0: sample was drawn from a Gaussian distribution
For a seri... |
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