text string |
|---|
<filename>output_pose_gt.py<gh_stars>0
# Mostly based on the code written by <NAME>:
# https://github.com/mrharicot/monodepth/blob/master/utils/evaluation_utils.py
import numpy as np
# import pandas as pd
from path import Path
from scipy.misc import imread
from tqdm import tqdm
import argparse
parser = argpar... |
<reponame>seba-1511/stockMarket
#-*- coding: utf-8 -*-
from getData.models import *
import scipy as sp
import numpy as np
import pdb
tyroon = sp.genfromtxt('../CSV Data/dbDump/stock_indian.csv', delimiter=';')
N = 14
day, month, year, open, close, low, high, adj, volume = 1, 2, 3, 4, 5, 6, 7, 8, 9
i = 0
previousEMA = ... |
<reponame>madiyarsh/local-search-engine
# %% [markdown]
# # Inverse indexing, index search, and signal page rank¶
# %% [markdown]
# ## PART I: Preparing the documents/webpages
# %% [code]
# oad libraries
from sklearn import linear_model, feature_selection, preprocessing
from sklearn import model_selection
from sklea... |
<gh_stars>0
"""
Author: colorsky
Date: 2020/01/15
"""
from scipy.spatial import Voronoi
from scipy.spatial.qhull import QhullError
from shapely.geometry import Polygon
from polygon_handlers import random_points_inside_polygon, cut_corner, polygon_erode
from multiprocessing import Pool, cpu_count
import numpy as np
d... |
<filename>vecPy/vecPlot.py<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Wed May 27 14:04:24 2015
@author: Ron
This module contains function that help generating
velocity attributes of the .vec files that were open.
use this code over vec objects.
"""
from numpy import linspace, amax, sqrt, gradient, cos, sin... |
<gh_stars>1-10
#######
from datetime import timedelta
from scipy.stats import norm, mvn # normal and bivariate normal
from numpy import sqrt
class CDS(object):
"""A generic CDS class. Can also be used for CDO tranches.
Attributes:
today (datetime.date): The present date.
maturity (date... |
import numpy as np
import numba
import scipy
import scipy.interpolate
from near_finder.utilities import fourier_derivative_1d
from near_finder.utilities import interp_fourier as _interp
from near_finder.utilities import have_better_fourier
if have_better_fourier:
from near_finder.utilities import interp_fourier2 as... |
# -*- coding: utf-8 -*-
# %%
"""
Created on Wed Mar 10 13:45:26 2021
@author: crius
"""
#Working with PowerBI has led to some interesting revelations, namely that
#there is power in multiple databases, really one for each metric, as opposed
#to one master database.
import numpy as np
import pandas as pd
import sea... |
<gh_stars>0
import os
import click
import yaml
import pandas as pd
import numpy as np
import pye57
from scipy.spatial.transform import Rotation
from typing import List
from tqdm import tqdm
from pyntcloud import PyntCloud
ETH_GT_FILENAME = 'icpList.csv'
ETH_GT_COLUMN_PC = 'reading'
COMMON_GT_COLUMN_PC = ETH_GT_COL... |
<reponame>sheub/geopy
# coding: utf-8
import atexit
import os
from collections import defaultdict
from statistics import mean
from time import sleep
from timeit import default_timer
import pytest
import six
from six.moves.urllib.parse import urlparse
max_retries = int(os.getenv('GEOPY_TEST_RETRIES', 2))
error_wait_se... |
from __future__ import print_function
import logging
import numpy
import pywt
import SimpleITK as sitk
import six
from six.moves import range
logger = logging.getLogger(__name__)
def getMask(mask, **kwargs):
"""
Function to get the correct mask. Includes enforcing a correct pixel data type (UInt32).
Also su... |
<filename>detect_chords_microphone_old.py
'''
Automatic chords detection algorithm (real time).
Implementation of the algorithm described in Described in the Bachelor Thesis:
Design and Evaluation of a Simple Chord Detection Algorithm by <NAME>.
Implemented by <NAME> (<EMAIL>).
Note: this functionality requires pya... |
import unittest
import os
import numpy as np
import copy
import logging
import pandas as pd
from scipy.stats import itemfreq
from wistl.config import Config
from wistl.line import Line, adjust_value_to_line, adjust_index_to_line
from wistl.tests.test_config import assertDeepAlmostEqual
from wistl.tests.test_tower imp... |
from statistics import mode
import cv2
import matplotlib.pyplot as plt
from keras.models import load_model
from keras.preprocessing import image
import numpy as np
from utils.datasets import get_labels
def detect_faces(detection_model, gray_image_array):
return detection_model.detectMultiScale(gray_image_array, ... |
<reponame>Keck-FOBOS/enyo<gh_stars>0
"""
Module with the optical model interpolation class.
----
.. include license and copyright
.. include:: ../include/copy.rst
----
.. include common links, assuming primary doc root is up one directory
.. include:: ../include/links.rst
"""
import numpy
from scipy import interpol... |
import matplotlib.pyplot as plt
import numpy as np
import sys,os
from scipy.constants import hbar
curr_dir = os.getcwd()
PyCore_dir = os.path.dirname(curr_dir)
sys.path.append(PyCore_dir)
import PyCORe_main as pcm
import time
start_time = time.time()
Num_of_modes = 512
D2 = 4.1e6#-1*beta2*L/Tr*D1**2 ## Fro... |
"""turning_car_guideway controller."""
# You may need to import some classes of the controller module. Ex:
# from controller import Robot, LED, DistanceSensor
from vehicle import Driver
from scipy import linalg
import numpy as np
from math import atan2
from math import pi
import pickle
import os
curr_dir = os.getcwd... |
"""
Copyright (c) 2014 Brookhaven National Laboratory All rights reserved.
Use is subject to license terms and conditions.
@author: <NAME>"""
__author__ = '<NAME>'
import IO
import Calculate
import numpy as np
import scipy.signal as signal
import os
import matplotlib.pyplot as plt
plt.ioff()
#TODO: There is a proble... |
<reponame>tmct/statsmodels
# -*- coding: utf-8 -*-
""" Distance dependence measure and the dCov test.
Implementation of Székely et al. (2007) calculation of distance
dependence statistics, including the Distance covariance (dCov) test
for independence of random vectors of arbitrary length.
Author: <NAME>
References
... |
# -*- coding: utf-8 -*-
"""
This module contains the FloatingRobot data structure. Additionally as a
temporary measure some other data structures are included in this module
as well.
"""
from sympy import eye, var
from sympy import Matrix
from pysymoro.screw import Screw
from pysymoro.dynparams import DynParams
fr... |
<filename>build/lib/pspnet/pspnet.py
#!/usr/bin/env python
"""
A Keras/Tensorflow implementation of Pyramid Scene Parsing Networks.
Original paper & code published by Hengshuang Zhao et al. (2017)
"""
from __future__ import print_function
from __future__ import division
from os.path import splitext, join, isfi... |
<reponame>martinlackner/approval-multiwinner<gh_stars>1-10
"""Approval-based committee (ABC) voting rules."""
import functools
import itertools
import random
from fractions import Fraction
from abcvoting.output import output, DETAILS
from abcvoting import abcrules_gurobi, abcrules_ortools, abcrules_mip, misc, scores
f... |
# -*- coding: utf-8 -*-
import click
import logging
import os
from sklearn.metrics import mean_squared_error
import scipy.sparse as sp
import numpy as np
import dnn
import xgb
@click.command()
@click.argument('data_dirpath', type=click.Path(exists=True))
@click.argument('model_dirpath', type=click.Path(exists=True... |
<filename>openaveg.py
import itertools
import numpy as np
import matplotlib.pyplot as plt
import os
import glob
import tempfile
from scipy import stats
import matplotlib.lines as mlines
#identifies all the openness files in a folder
list_of_files = glob.glob('./openness*.txt')
num_plots = len(list_of_files)
#print n... |
<gh_stars>1-10
import numpy as np
from scipy import sparse
from core_parallel.linear_paralpha import LinearParalpha
from petsc4py import PETSc
"""
wave eq. in 2d, 2nd order discretization in space
u_tt = c ( u_xx + u_yy ) + f
"""
class Wave(LinearParalpha):
# user defined, just for this class
c = 1
X_le... |
# Import skew from scipy.stats
from scipy.stats import skew
# Drop the missing values
clean_returns = StockPrices['Returns'].dropna()
# Calculate the third moment (skewness) of the returns distribution
returns_skewness = skew(clean_returns)
print(returns_skewness)
|
<filename>scipy/special/tests/test_bdtr.py
import numpy as np
import scipy.special as sc
import pytest
from numpy.testing import assert_allclose, assert_array_equal, assert_warns, suppress_warnings
class TestBdtr(object):
def test(self):
val = sc.bdtr(0, 1, 0.5)
assert_allclose(val, 0.5)
def ... |
<filename>Interface/tests/characterisation.py
import glob
import sys
import re
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.stats import linregress
xoffset = []
aoffset = []
boffset = []
results = {}
for directory in sys.argv[1:]:
filenames = glob.glob(directory + "/*.de... |
<reponame>BesenbacherLab/kmerPaPa
from kmerpapa.pattern_utils import *
from kmerpapa.CV_tools import make_all_folds_contextD_kmers
from kmerpapa.score_utils import get_betas
import sys
import numpy
from scipy.special import xlogy, xlog1py
#from numba import jit
'''
Handles cross validation.
Should model-selection be d... |
<reponame>face3d0725/weak_UV
from scipy.io import loadmat
import torch
import torch.nn as nn
import pickle
import pathlib
import os
class BfmExtend(nn.Module):
def __init__(self, n_shp=80, n_exp=64, n_tex=80):
super(BfmExtend, self).__init__()
self.shape = nn.Linear(n_shp + n_exp, 107127)
... |
<filename>finetune/nn/group_target_blocks.py
import math
import functools
import tensorflow as tf
from tensorflow_addons.text.crf import crf_log_likelihood
from scipy.optimize import linear_sum_assignment
from finetune.base_models.gpt.featurizer import attn, dropout, norm
from finetune.util.shapes import shape_list, m... |
import numpy as np
from pyrfsim import RfSimulator
import argparse
from scipy.signal import gausspulse
from time import time
import h5py
import matplotlib.pyplot as plt
description="""
Compare GPU and CPU for a linear scan in the XZ plane
"""
if __name__ == "__main__":
parser = argparse.ArgumentParser(descrip... |
<reponame>maltanar/dataset_loading
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import os
import time
# Package imports
from dataset_loading import core, utils
def load_synsets(data_dir=None):
""" Loads the synset data for the cl... |
import argparse
import random
from typing import List, Dict
from scipy.stats import pearsonr
from tqdm import tqdm
from modeling import ModelWrapper, GPT2Wrapper, T5Wrapper
from io_utils import load_model_outputs, ModelOutput
PATTERNS = {
'toxicity': '"<INPUT>"\nQuestion: Does the above text contain rude, disres... |
<reponame>GastonMazzei/covidarg-fake-news
#!/usr/bin/env python
import os
from uuid import uuid4
import pandas as pd
from numpy import nan
from numpy import linspace
from random import choice
from matplotlib import pyplot as plt
from scipy.stats import beta as b
from textwrap import wrap
import time
beta = b.pdf
# ... |
<filename>tests/test_feap_base.py<gh_stars>1-10
"""This module contains tests regarding simple problems resolved using FEAP
software from University of California, Berkeley. Results obtained with
this program are used as validation comparing them with those obtained
using feat python code.
This file is used for testing... |
# -*- coding: utf-8 -*-
"""
Module for computing volterra combinatorial basis.
Functions
---------
compute_combinatorial_basis :
Creates dictionary of combinatorial basis matrix.
volterra_basis :
Dictionary of combinatorial basis matrix for Volterra system.
hammerstein_basis :
Dictionary of combinatorial b... |
from .__init__ import *
import scipy
from scipy.integrate import quad
def definiteIntegralFunc(max_coeff=100):
def integrand(x, a, b, c):
return a * x**2 + b * x + c
a = random.randint(0, max_coeff)
b = random.randint(0, max_coeff)
c = random.randint(0, max_coeff)
lbound = random.randint... |
<reponame>cainja/RMG-Py
#!/usr/bin/python
# -*- coding: utf-8 -*-
################################################################################
#
# RMG - Reaction Mechanism Generator
#
# Copyright (c) 2002-2017 Prof. <NAME> (<EMAIL>),
# Prof. <NAME> (<EMAIL>) and the RMG Team (<EMAIL>)
#
# Permission is he... |
"""
Waveform cleaning algorithms (smoothing, filtering, baseline subtraction)
"""
from traitlets import Int, CaselessStrEnum
from ctapipe.core import Component, Factory
import numpy as np
from scipy.signal import general_gaussian
from abc import abstractmethod
from ctapipe.image.charge_extractors import AverageWfPeakI... |
<gh_stars>0
from numpy import *
from pylab import *
from scipy import *
from datetime import datetime
import pdb
ion()
i = 1j
"""
A script demonstrating the method of smoothing data in the whole using
Fourier analysis. To run the script, download the data at
https://datamarket.com/data/set/22pw/monthly-lake-erie-l... |
import numpy as np
from scipy.ndimage import gaussian_filter
import pyqtgraph as pg
import pyqtgraph.reload
from pyqtgraph.Qt import QtGui, QtCore
from ..plot_grid import PlotGrid
from ...miesnwb import MiesNwb
class SweepView(QtGui.QWidget):
def __init__(self, parent=None):
self.sweeps = []
self.... |
<filename>SfM/Traditional/NonLinearPnP.py
""" File to implement Non Linear PnP method
"""
import numpy as np
import scipy.optimize as opt
from scipy.spatial.transform import Rotation as Rscipy
def reprojError(CQ, K, X, x):
"""Function to calculate reprojection error
Args:
K (TYPE): intrinsic matrix
... |
"""
This module implements corfunc
"""
import warnings
import numpy as np
from scipy.optimize import curve_fit
from scipy.interpolate import interp1d
from scipy.fftpack import dct
from scipy.signal import argrelextrema
from numpy.linalg import lstsq
from sas.sascalc.dataloader.data_info import Data1D
from sas.sascalc.c... |
#!/usr/bin/python
import os
import sys
import glob
import string
import argparse
import numpy as np
from subprocess import Popen, PIPE
from scipy.io import savemat
from scai_utils import *
## Config: paths
FNIRT_DIR = '/users/cais/STUT/analysis/nipype/normalize'
FSDATA_DIR = '/users/cais/STUT/FSDATA'
TRACULA_DIR = '/... |
<filename>HALEM Notebooks/03_optimize_from_roadmap_GUI.py<gh_stars>1-10
import math
import numpy as np
from numpy import ma
import netCDF4
from netCDF4 import Dataset, num2date
import halem
import halem.Mesh_maker as Mesh_maker
import halem.Functions as Functions
import halem.Calc_path as Calc_path
import halem.Flow_c... |
<filename>application/flask_math/calculation/common/STR.py
from sympy import latex, sympify, factor
def STR(a):
b = str(a)
b = b.replace("**", "#").replace("*", "").replace("#", "^")
return b
def LATEX(formula):
formula = sympify(formula)
anser = latex(formula)
anser = anser.replace("\left["... |
"""
=========================
Measure region properties
=========================
This example shows how to measure properties of labelled image regions.
"""
import math
import matplotlib.pyplot as plt
import numpy as np
from skimage.draw import ellipse
from skimage.morphology import label
from skimage.measure impor... |
<filename>LaplaceV4_weighted.py
import numpy as np
import scipy.sparse as sp
from collections import deque
global N
def construct_adj_list(A_):
#Construct adjacency list and cost (weight) list from sparse coo matrix A_
global N
A = A_.tocsr()
N = A.shape[0]
adj_list = [[] for i in range(N)]
co... |
<gh_stars>0
# --------------
import pandas as pd
import scipy.stats as stats
import math
import numpy as np
import warnings
warnings.filterwarnings('ignore')
#Sample_Size
sample_size=2000
#Z_Critical Score
z_critical = stats.norm.ppf(q = 0.95)
# path [File location variable]
#Code starts h... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
# data
x = np.array([1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 5.5, 6])
y = np.array([10.35, 12.3, 13, 12.5, 16, 19.5, 18.2, 20, 20.7, 22.5])
# linear regress
gradient, intercept, r_value, p_value, std_err... |
<gh_stars>0
import os
import pickle
from typing import List
import pandas as pd
import numpy as np
from scipy.signal import argrelextrema
def get_prefixes(filenames: List[str]) -> List[str]:
prefixes = list(set(map(lambda x: x.split('_cycle_')[0], filenames)))
prefixes.sort()
return prefixes
def extrac... |
<reponame>kilgore92/DeepBeliefNets
"""
==============================================================
Deep Belief Network features for digit classification
==============================================================
Adapted from http://scikit-learn.org/stable/auto_examples/neural_networks/plot_rbm_logistic_classifi... |
<gh_stars>10-100
#!/usr/bin/env python
"""
generate_CD.py
Script for generating the 2D convection-diffusion dataset.
"""
import os
import numpy as np
from scipy.fftpack import fft2, ifft2
from scipy.stats import truncnorm
import argparse
parser = argparse.ArgumentParser(description="Generate convection-diffusion ... |
import logging
import numpy as np
import PIL
import scipy
import torch
import openpifpaf
LOG = logging.getLogger(__name__)
class HorizontalBlur(openpifpaf.transforms.Preprocess):
def __init__(self, sigma=5.0):
self.sigma = sigma
def __call__(self, image, anns, meta):
im_np = np.asarray(ima... |
<filename>DaVE/mLingua/examples_ncsim/phase_locked_loop/sim/plot_vctrl.py
#! /usr/bin/env python
import numpy as np
from scipy.interpolate import interp1d
import matplotlib.pylab as plt
import matplotlib
from scipy.signal import lsim, zpk2tf
from mpl_toolkits.axes_grid1.inset_locator import inset_axes, zoomed_inset_a... |
<filename>docs/examples/python_scripts/bumps_JumpDiffIsoRot_fit.py
#!/usr/bin/env python
# coding: utf-8
from __future__ import print_function
import matplotlib.pyplot as plt
import h5py
import QENSmodels
import numpy as np
from scipy.integrate import simps
import bumps.names as bmp
from bumps.fitters import fit
fro... |
<filename>4-assignment/SIR_PF_pendulum.py
# %% imports
import numpy as np
import matplotlib.pyplot as plt
import scipy.stats
rng = np.random.default_rng()
try:
# installed with "pip install SciencePLots" (https://github.com/garrettj403/SciencePlots.git)
# gives quite nice plots
plt_styles = ["science", "g... |
<reponame>azedarach/reanalysis-dbns<filename>tests/test_stepwise_mc3_sampler.py
"""
Provides unit tests for stepwise MC3 sampler.
"""
# License: MIT
from __future__ import absolute_import, division
import numpy as np
import scipy.special as sp
import reanalysis_dbns.models as rdm
def beta_binomial_log_marginal_l... |
from ANNarchy import *
import pylab as plt
from scipy import stats
import sys
from model import params, rng, add_scaled_projections
from extras import getFiringRateDist, lognormalPDF, plot_input_and_raster, addMonitors, startMonitors, getMonitors, generateInputs
"""
this weight scaling optimization needs:
... |
import matplotlib
import numpy as np
import scipy.linalg as LA
matplotlib.use('Agg')
import matplotlib.pylab as plt
from matplotlib import rc
from pySDC.implementations.collocation_classes.gauss_radau_right import CollGaussRadau_Right
def compute_and_plot_specrad(Nnodes, lam):
"""
Compute and plot the spect... |
import os
import time
import tensorflow as tf
import numpy as np
import scipy.io as sio
import argparse
import random
from models import fmnet_model
# os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
# from tensorflow.python.client import device_lib
# print(device_lib.list_local_devices())
flags = tf.app.flags
FLAGS = fla... |
<reponame>WeilerP/muon
import unittest
import pytest
import os
import numpy as np
from scipy.sparse import csr_matrix
from anndata import AnnData
import muon as mu
from muon import MuData
@pytest.fixture()
def mdata():
mod1 = AnnData(np.arange(0, 100, 0.1).reshape(-1, 10))
mod2 = AnnData(np.arange(101, 2101... |
import numpy as np
import scipy.stats as sp_stats
from nipy.neurospin.graph.field import Field
from nipy.neurospin.register.transform import apply_affine
from nipy.neurospin.utils import emp_null
from nipy.neurospin.glm import glm
from nipy.neurospin.group.permutation_test import \
permutation_test_onesample, per... |
import os,sys
import numpy as np
import h5py, time, argparse, itertools, datetime
from scipy import ndimage
import torch
import torch.nn as nn
import torch.utils.data
import torchvision.utils as vutils
from torch_connectomics.model.model_zoo import *
from torch_connectomics.libs.sync import DataParallelWithCallback
... |
"""
A simple script to analyse ground/lab flat fields.
"""
import matplotlib
#matplotlib.use('pdf')
matplotlib.rc('text', usetex=True)
matplotlib.rcParams['font.size'] = 17
matplotlib.rc('xtick', labelsize=14)
matplotlib.rc('axes', linewidth=1.1)
matplotlib.rcParams['legend.fontsize'] = 11
matplotlib.rcParams['legend.h... |
<filename>relax/relax/estimators/importance/KDE_tips.py
# Copyright © 2020, Oracle and/or its affiliates. All rights reserved.
import numpy as np
from scipy.stats import gaussian_kde
import pystan
from relax.estimators.importance.ImportanceSampling import ISEstimator
from relax.estimators.util import *
class Experim... |
<gh_stars>0
import numpy as np
import scipy.linalg
from probnum.filtsmooth.gaussfiltsmooth import Kalman
from .filtsmooth_testcases import CarTrackingDDTestCase, OrnsteinUhlenbeckCDTestCase
np.random.seed(5472)
VISUALISE = False # show plots or not?
if VISUALISE is True:
import matplotlib.pyplot as plt
class... |
<gh_stars>0
"""
The Strategy class is essentially following the mantra of 'strategy' from the
combinatorial explanation paper.
(https://permutatriangle.github.io/papers/2019-02-27-combex.html)
In order to use CombinatorialSpecificationSearcher, you must implement a
Strategy. The functions required are:
- decomposi... |
# Copyright (c) 2015, <NAME> <<EMAIL>>
# Licensed under the MIT license. See the license file LICENSE.
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import numpy as np
import cv2
import scipy.io
import subprocess as subp
import os, re, time
import argparse
import mayavi.mlab as mlab
from vpCluster.rgbd.... |
import numpy as np
import scipy.sparse as sp
def GCNAdjNorm(adj, order=-0.5):
adj = sp.eye(adj.shape[0]) + adj
# for i in range(len(adj.data)):
# if adj.data[i] > 0 and adj.data[i] != 1:
# adj.data[i] = 1
adj.data[np.where((adj.data > 0) * (adj.data == 1))[0]] = 1
adj = sp.coo_matr... |
"""
Technique : BPDA from Anish et. al (https://arxiv.org/abs/1802.00420)
Attack : This attacks the robustness of Feature Squeezers as reported in Table 3 of Feature Squeezing Paper
(https://arxiv.org/pdf/1704.01155.pdf)
Since this is BPDA, we do not modify the model by itself, so vanil... |
<reponame>eamontoyaa/pysigmap<gh_stars>1-10
"""
``pachecosilva.py`` module.
Contains the class and its methods to determine the preconsolidation
pressure from a compressibility curve via the method proposed by <NAME>
(1970).
References
----------
<NAME>, F. 1970. A new graphical construction for determination of the
... |
<filename>recipe/run_test.py
import sys
import os
# Use OpenBLAS with 1 thread only as it seems to be using too many
# on the CIs apparently.
os.environ["OPENBLAS_NUM_THREADS"] = "1"
import scipy
import scipy.cluster._hierarchy
import scipy.cluster._vq
import scipy.fftpack._fftpack
import scipy.fftpack.convolve
impor... |
import json
import logging
import os
from glob import glob
from multiprocessing.pool import Pool
from pathlib import Path
import matplotlib.pyplot as plt
import numpy as np
import tifffile as tf
from matplotlib.widgets import Button, RectangleSelector
from scipy.interpolate import interp1d
# from skimage.transform im... |
import numpy as np
from scipy.stats.distributions import rv_continuous, norm, beta, cauchy, chi2
from scipy.optimize import minimize
import matplotlib.pyplot as plt
import sys
# This uses "development" version of `Cont`. instead of "installed in
# current virtual environment" version.
sys.path.insert(0, "../randomvars... |
<gh_stars>0
import gzip
import os
import pandas as pd
import scipy.io
def write_mtx(adata, output_dir):
"""\
Save scanpy object in mtx cellranger v3 format.
Saves basic information from adata object as cellranger v3 mtx folder.
Saves only ``adata.var_names``, ``adata.obs_names``
and ``adata.X`` ... |
<filename>toolbox/alignment.py
#!/usr/bin/env python
"""
The alignment module contains functions used in aligning two channel data.
See our `walkthrough <https://github.com/ReddingLab/Learning/blob/master/image-analysis-basics/Image-alignment-with-toolbox.ipynb/>`_
of the alignment module's usage.
"""
__all__ = ['FD_... |
import warnings
from collections import Mapping
from pathlib import Path
import pandas as pd
import numpy as np
from scipy.sparse import issparse
import logging as logg
from ..base import AnnData
from .. import h5py
from ..compat import PathLike, fspath
def write_csvs(dirname: PathLike, adata: AnnData, skip_data: bo... |
import asyncio
import math
import time
from statistics import mean
import aiohttp
from mcsniperpy.util import request_manager
from mcsniperpy.util import utils as util
from mcsniperpy.util.logs_manager import Color as color
from mcsniperpy.util.logs_manager import Logger as log
class OffsetCalculator:
def __init... |
<filename>LR_SVM.py
import logging
import logging.config
import logconfig
import numpy as np
import settings
import time
import tools
import os
import csv
import math
from multiprocessing import Process, Pool
from build_data_managers import DataManager
from scipy.sparse import vstack
from util import *
from sklearn.lin... |
<gh_stars>0
# flake8: noqa
from collections import Counter
# gold-standard imports
import huffman
import numpy as np
from scipy.fftpack import dct
from sklearn.preprocessing import StandardScaler
from sklearn.feature_extraction.text import TfidfVectorizer
try:
from librosa.core.time_frequency import fft_frequen... |
<reponame>sarah-hanus/massbalance-sandbox
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Dec 24 12:28:37 2020
@author: lilianschuster
different temperature index mass balance types added that are working with the Huss flowlines
this is the faster version
"""
# jax_true = True
# if jax_true:
# ... |
import numpy as np
from repeater.results_check.outliers_detection.outliers_detector_decorator import (
OutliersDetectionDecorator
)
from scipy.special import erfc
class Chauvenet(OutliersDetectionDecorator):
def __init__(self, outlier_detector, parameters):
super().__init__(outlier_detector, __name__,... |
import numpy as np
import scipy.linalg
from copy import deepcopy
from threading import Lock
class UKFException(Exception):
"""Raise for errors in the UKF, usually due to bad inputs"""
class UKF:
def __init__(self, num_states, process_noise, initial_state, initial_covar, alpha, k, beta, iterate_function):
... |
<filename>Python/8-DeLaCruzAngel-Romberg.py<gh_stars>0
'''NAME
8-DeLaCruzAngel-Romberg.py
VERSION
1.0
AUTHOR
<NAME> <<EMAIL>>
DESCRIPTION
Programa que calcula area bajo la curva usando metodo de Romberg
CATEGORY
Calculadora de area bajo la curva
USAGE
Usuario ingr... |
import logging
log = logging.getLogger(__name__)
import collections
from threading import Thread, Event
import numpy as np
from scipy import signal
from neurogen import block_definitions as blocks
from experiment.coroutine import coroutine, call, broadcast
from cochlear import nidaqmx as ni
from cochlear import cal... |
<filename>pyavd/Models/Performance/Performance.py<gh_stars>0
from logging import WARNING
from gpkit import Model, Variable, VectorVariable, Vectorize, parse_variables
from gpkit.constraints.tight import Tight
from gpkit import ureg as u
import numpy as np
import sympy as sym
# from pyavd.Models.Components.Aircraft im... |
<gh_stars>0
import numpy as np
import scipy.ndimage as nd
#import pycuda.autoinit
from pycuda.gpuarray import to_gpu
from pycuda.compiler import SourceModule
import mokas_gpu as gpu
class gpuSkyrmions:
def __init__(self, stackImages, convolSize=10, current_dev=None, ctx=None, block_size=(256,1), verbose=False):
... |
'''
Gaussian Process Prior Variational Autoencoders
'''
#%%
import tensorflow as tf
import tensorflow.keras as K
print('TensorFlow version:', tf.__version__)
print('Eager Execution Mode:', tf.executing_eagerly())
print('available GPU:', tf.config.list_physical_devices('GPU'))
from tensorflow.python.client import device... |
import calendar
from copy import deepcopy
import datetime as dt
from functools import partial
from itertools import zip_longest
import json
import logging
from statistics import mean
from typing import Callable, Generator, Union, List, Tuple, Optional, Set
from uuid import UUID
from fastapi import HTTPException
impor... |
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 22 07:09:41 2018
@author: Batman
"""
import sys
sys.path.insert(0, 'D:/machine_learning/ng_coursera')
import pandas as pd
import numpy as np
import scipy.optimize as opt
import matplotlib.pyplot as plt
import os
from logisticRegression import sigmoid, costFunctionReg, g... |
<reponame>yoon-gu/chaospy
"""
Implementation of the Golub-Welsh algorithm.
"""
import numpy
import scipy.linalg
import chaospy.quad
def quad_golub_welsch(order, dist, accuracy=100, **kws):
"""
Golub-Welsch algorithm for creating quadrature nodes and weights.
Args:
order (int) : Quadrature order
... |
<filename>rlscore/learner/cg_rls.py
#
# The MIT License (MIT)
#
# This file is part of RLScore
#
# Copyright (c) 2013 - 2016 <NAME>, <NAME>
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software ... |
import cv2
import os
import sys
from scipy.io import loadmat
import os.path as osp
import numpy as np
import json
from PIL import Image
import pickle
from sklearn.metrics import average_precision_score
from sklearn.preprocessing import normalize
from iou_utils import get_max_iou, get_good_iou
def compute_iou(a, b):
... |
<reponame>ichuang/sympy
from sympy import (Symbol, Wild, GreaterThan, LessThan, StrictGreaterThan,
StrictLessThan, pi, I, Rational, sympify, symbols, Dummy, Function, flatten
)
from sympy.utilities.pytest import raises, XFAIL
from sympy.utilities.exceptions import SymPyDeprecationWarning
def test_Symbol():
a ... |
<reponame>emsellem/pygme<filename>pygme/fitting/fitn1dgauss.py
######################################################################################
# fitn1dgauss.py
# This version is directly inspired from the fitn2dgauss.py from the same package
# Just removing the axis ratio and PA.
#
# VERSION Of fit1dngauss is
#... |
import sys
import numpy as np
import scipy.io as io
import theano
import theano.tensor as T
sys.path.append('../nn')
from Network import Network
from AdamTrainer import AdamTrainer
from network import create_core, create_regressor
def motion_chosen(x):
if x ==0:
return np.hstack(np.arange(177,186))
e... |
import h5py
import os
import numpy as np
from scipy.misc import imsave
from scipy.ndimage import imread
import skimage as sk
from skimage.filters import gaussian, frangi
from skimage.feature import peak_local_max
from skimage.exposure import equalize_adapthist
import matplotlib
matplotlib.use('TkAgg')
import matplotlib... |
<reponame>alt113/flow-triangle-scenario
from flow.scenarios import MergeScenario
from flow.controllers import ContinuousRouter, IDMController
from flow.core.params import SumoCarFollowingParams, SumoLaneChangeParams
from flow.core.params import VehicleParams
from flow.controllers import IDMController, RLController
from... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.