text string |
|---|
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
import attitude_utils as attu
from scipy import signal
def make_airframe(tau=0.5, eta=0.7, w_m=30, w_z=5):
num = -w_m**2*np.asarray([1 , 0, -w_z**2])
den = w_z**2*np.asarray([tau , 2*tau*eta*w_m+... |
#!/usr/bin/env python
# -*- coding:UTF-8 -*-
# File Name : data_preprocess.py
# Purpose :
# Creation Date : 03-01-2019
# Author : <NAME> [sli[at]informatik[dot]uni-hamburg[dot]com]
# Author : <NAME> [liang[at]informatik[dot]uni-hamburg[dot]com]
from __future__ import division
from __future__ imp... |
'''Functions for providing you gameplay guidance in Wordle.
Copyright (c) 2022 <NAME>
'''
import logging
from collections import defaultdict, Counter
from itertools import islice, tee
from random import shuffle
from statistics import mean
from typing import Dict, List, Set, Pattern
import re
import data
log = loggi... |
<reponame>nanotech-empa/aiidalab-empa-nanoribbons
"""Viewers to display the results of the Nanoribbon work chain."""
# Base imports.
import gzip
import re
import io
import tempfile
from base64 import b64encode
from collections import OrderedDict
import nglview
import ipywidgets as ipw
import bqplot as bq
import numpy ... |
import code.book_plots as bp
import code.gh_internal as gh
import matplotlib.pyplot as plt
import numpy as np;
import time
from pylab import *
from drawnow import drawnow, figure
from filterpy.discrete_bayes import normalize
from filterpy.discrete_bayes import predict
from filterpy.discrete_bayes import update
from sc... |
<reponame>MoscowskyAnton/landmark_localization<gh_stars>1-10
#!/usr/bin/env python
# coding: utf-8
'''
2D Adaptive Monte-Carlo Localization for landmark localization task
'''
import landmark_localization.landmark_localization_core as llc
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm, ... |
<gh_stars>0
import numpy as np
from sklearn.neighbors import NearestNeighbors
from scipy import sparse
# data is an n x p matrix with rows as observations
# k is the number of neighbours (e.g. 20)
# d is the dimension of the embedding (e.g. 3)
# this implementation uses the zero-one kernel and diffusion time 0
... |
<reponame>openql-org/quantpy
# -*- coding:utf-8 -*-
"""definition of ClassicalSimulationExecutor class
"""
from collections import defaultdict
import numpy as np
import sympy
from quantpy.sympy.executor._base_quantum_executor import BaseQuantumExecutor
from quantpy.sympy.executor.simulator.numpy_simulator import Num... |
<reponame>hanswenzel/opticks<gh_stars>10-100
#!/usr/bin/env python
"""
https://docs.sympy.org/latest/modules/functions/elementary.html#piecewise
Hmm seems that sympy doesnt like a mix of symbolic and floating point
maybe better to use
"""
import logging
log = logging.getLogger(__name__)
import numpy as np
import... |
<filename>tests/genquad_test.py
"""Tests for the general quadratic algebra drudge."""
import pytest
from sympy import Integer
from drudge import Vec, GenQuadLatticeDrudge
def test_assume_comm(spark_ctx):
"""
Test the case where vectors are assumed to commute if there commutator
is not specified.
"""
... |
<reponame>PhracturedBlue/fava-portfolio-summary
#!/usr/bin/env python
"""
Calculate the MWRR and/or TWRR for a list of portfolios
This code is originally from https://github.com/hoostus/portfolio-returns
Copyright <NAME>
It was originally licensed under the Parity Public License 7.0.
This file is dual licensed under t... |
import pandas as pd
import numpy as np
import os
import csv
import pickle
import h5sparse
import scipy.sparse as ss
from itertools import compress
def write_gvm(gvm, output_fname, fmt='h5'):
'''
Writes a gvm to a .csv or .h5 file.
Parameters:
gvm (h5sparse): gvm to write
output_fname (str): file path to save to
... |
from __future__ import print_function
###########
# imports #
###########
import numpy as np
# from sklearn import manifold, datasets # not used, remove in next version
from sklearn.neighbors import kneighbors_graph
from scipy.spatial.distance import cdist
from scipy.cluster import hierarchy
from scipy.stats import p... |
# emacs: at the end of the file
# ex: set sts=4 ts=4 sw=4 et:
# ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### #
import os
import numpy as np
import nibabel as nib
import scipy.io as sio
from pyale.utils import (round2, tal2mni, mni2tal, vox2mm, mm2vox, thresh_str,
... |
import numpy as np
from random import sample
from some_bandits.bandit_options import bandit_args
from some_bandits.utilities import convert_conf, save_to_pickle, calculate_utility
from some_bandits.bandits.Bandit import Bandit
from some_bandits.bandits.Expert import Expert
from statistics import mean
ACTION = 0
REWARD... |
<filename>WeightedMinHashToolbox/WeightedMinHash.py
#!/usr/bin/env python
"""Toolbox for Weighted MinHash Algorithms
This module contains the following algorithms: the standard MinHash algorithm for binary sets and
weighted MinHash algorithms for weighted sets.
Each algorithm converts a data instance (i.e., vector) in... |
from lxml import html as lh
import requests
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
import numpy as np
from scipy.optimize import curve_fit
# from pandas.plotting import register_matplotlib_converters
import matplotlib.dates as mdates
from scipy.stats import norm
# register_ma... |
<filename>spec_plot.py
import glob
import pandas as pd
import os
import sys
#from Tkinter import *
import tkinter
from tkinter import *
from tkinter import filedialog
import matplotlib.mlab
import numpy as np
from matplotlib import pyplot as plt
import scipy.io.wavfile as wav
from numpy.lib import stride_tricks
im... |
<filename>examples/nist_sre/helpers.py<gh_stars>1-10
from __future__ import absolute_import, division, print_function
import os
import pickle
import shutil
import warnings
from collections import OrderedDict, defaultdict
from enum import Enum
from numbers import Number
import numba as nb
import numpy as np
from scipy... |
import keras
from keras.layers import Input, LSTM, Dense, Dropout, Activation, Flatten
from keras.models import Model
import numpy as np
from keras.utils import to_categorical
from numpy import array
from keras import regularizers
import numpy as np
import pandas as pd
import csv
import scipy.io as sio
from keras.layer... |
<filename>utils.py
import os, cv2
import numpy as np
from scipy import ndimage
from scipy.ndimage import convolve
from scipy.signal import medfilt2d
from skimage import color
import matplotlib.pyplot as plt
# from numba import jit
def resizeImage(image):
image = image[0:690, 180:1100]
image = cv2.re... |
import astropy.io.fits as fits
import copy
import numpy as np
from astropy import units as u
from astropy.modeling.fitting import LevMarLSQFitter
from astropy.nddata import NDData, CCDData
from astropy.stats import gaussian_sigma_to_fwhm, sigma_clipped_stats
from astropy.table import Table
from astropy.wcs import WCS
f... |
<gh_stars>0
import numpy as np
from sympy import Expr
from typing import Mapping, Any, Dict
import sidekick as sk
from toy.solvers import SOLVERS
from .meta import Meta
from .model_meta import ModelMeta
from .value import Value, fix_numeric, NumericType
from ..utils import substitute, coalesce
run = sk.import_later('... |
import os
import sys
import utils
import glob
import numpy as np
import cv2 as cv
import math
from PIL import Image
import copy
import random
from scipy.sparse import coo_matrix
from scipy.sparse.csgraph import minimum_spanning_tree, connected_components, breadth_first_order
from pathlib import Path
import torch
from o... |
<filename>src/unigo/stat_utils.py
"""
Basic statistical functions to compute pathway enrichment
"""
from scipy.stats import hypergeom
from scipy.stats import fisher_exact
import numpy as np
def computeSelfORA(node, proteinList):
"""computeSelfORA
Compute the probability of observing at least the k members o... |
<reponame>Napolepburn/Iterative_Input_Selection_with_Model-based_Method
import os
import math
import numpy as np
from pandas import Series
from scipy import stats
import matplotlib.pyplot as plt
#读取的文件路径(支持批量读取)
read_path=['../数据读取与预处理\\b2-PG-DAS数据读取_1d（归一化）.py',\
'../数据读取与预处理\\b2-PG-DAS数据读取_2d（归一化）.py',\... |
<filename>pyvotca/utils.py
"""Utilities and constants."""
from scipy.constants import physical_constants
H2EV = physical_constants['Hartree energy in eV'][0]
BOHR2ANG = physical_constants['Bohr radius'][0] * 1.e10
|
<filename>Script_All_Algo.py
import scipy
import argparse
import numpy as np
import pandas as pd
from tqdm import tqdm
from scipy import stats
import scipy.stats as st
from scipy.sparse.linalg import svds
from scipy.sparse import csr_matrix, coo_matrix
from numpy.linalg import qr as QR_decomp
######################... |
import timeit
import unittest
import numpy as np
import pytest
from scipy import stats
from pfrl.utils.random import sample_n_k
@pytest.mark.parametrize(
"n,k", [(2, 2), (5, 1), (5, 4), (7, 2), (20, 10), (100, 5), (1, 0), (0, 0)]
)
class TestSampleNK:
@pytest.fixture(autouse=True)
def setUp(self, n, k):... |
<filename>plot_scripts/plot_utils.py
import pandas as pd
import numpy as np
import math
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression
def read_data(filename, region, boolean_region):
# Read and preprocess data file
df = pd.read_csv(filename)
df['Datum'] = pd.to... |
import itertools
import math
import os
import random
import string
import sys
import urllib.request
from datetime import date
from datetime import datetime as dt
from types import FunctionType, GeneratorType
from typing import List, Tuple, Union, Any
THIS_FOLDER = os.path.dirname(os.path.abspath(__file__)) + "/.."
sys... |
import torch
import cv2
import os
import datetime
import numpy as np
import pandas as pd
from tqdm import tqdm
from network.utils import bbox_iou
from datetime import datetime
import multiprocessing
from scipy.optimize import linear_sum_assignment
class Track:
'''
Track is the class of track. it contains all ... |
<gh_stars>10-100
"""Calculation of semi-analytical noise biases module.
"""
from __future__ import print_function
import os
import pickle as pk
import numpy as np
import healpy as hp
from plancklens import qresp, utils, utils_spin as uspin
from plancklens.helpers import mpi, sql
def get_nhl(qe_key1, qe_key2, cls_w... |
#!/usr/bin/env python3
#FAST ROLLING HOUGH TRANSFORM
#<NAME>, <NAME>
#-----------------------------------------------------------------------------------------
#Imports
#-----------------------------------------------------------------------------------------
from __future__ import division #Must be first line of code... |
<gh_stars>1-10
"""
asist.utility -- Various utility functions used to process data.
"""
import numpy as np
from scipy.signal import detrend
def binavg(x, binsize):
"""Simple binned average over binsize elements."""
return np.array([np.mean(x[n:n+binsize])\
for n in range(0, len(x), binsize)])
def bl... |
"""
Generates a partition function and fraction folded expressions for an NRXC
capped heteropolymer repeat array.
"""
from __future__ import division
import sympy as sp
import numpy as np
import json
import time
import os
PATH = os.path.dirname(os.path.abspath(__file__))
proj_name = "T4V_NRC_2mi"
start = time.time(... |
<reponame>A-Raafat/ML_BoneSuppression
from __future__ import division
from configparser import ConfigParser
import argparse
from utils import extract_image_path, extract_n_preprocess_dicom, check_and_create_dir, extract_image, augment_image_pair
import imreg_dft as ird
import os
import cv2
from scipy.misc import imsave... |
"""
# Event source for MAGIC calibrated data files.
# Requires uproot package (https://github.com/scikit-hep/uproot).
"""
import re
import uproot
import logging
import scipy
import scipy.interpolate
import numpy as np
from decimal import Decimal
from enum import Enum, auto
from astropy.coordinates import Angle
from as... |
<reponame>JohnGoertz/Gumbi<filename>gumbi/regression/base.py
import warnings
from abc import ABC, abstractmethod
import numpy as np
import pandas as pd
from scipy.interpolate import interpn
from itertools import product
from gumbi.utils.misc import assert_in, assert_is_subset
from gumbi.utils.gp_utils import g... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# vim: ai ts=4 sts=4 et sw=4 ft=python
# author : Prakash [प्रकाश]
# date : 2019-09-22 17:40
import os
import numpy as np
import matplotlib.pyplot as plt
from . import textutil as utl
class Heatmap():
def __init__(self,layout='qwerty'):
self.layout = la... |
import code.book_plots as bp
import code.gh_internal as gh
import matplotlib.pyplot as plt
import numpy as np;
import time
from pylab import *
from drawnow import drawnow, figure
from filterpy.discrete_bayes import normalize
from filterpy.discrete_bayes import predict
from filterpy.discrete_bayes import update
from sc... |
<filename>Python/extractFN2.py
#!/anaconda3/bin/python
import os
from numpy import array
from scipy.io import savemat, loadmat
var = loadmat('input.mat')
filename = var['filename'].flatten()[0]
# filename = ' '.join(sys.argv[1:])
path, name = os.path.split(filename)
name, ext = os.path.splitext(name)
outdict = {'S... |
<reponame>esemi/blogpost_clustering
#! /usr/bin/env python
# -*- coding: utf-8 -*-
__author__ = "esemi"
from collections import deque
import matplotlib.pyplot as plt
import networkx as nx
from scipy.spatial.distance import pdist
from shared import get_data
def graph_draw(g):
"""Draw graph"""
plt.figure()... |
import scipy.misc
import os
import os
import numpy as np
import tensorflow as tf
from .base import Callback
from ..utils.common import check_dir
__all__ = ['ModelSaver']
class ModelSaver(Callback):
def __init__(self, max_to_keep=5,
keep_checkpoint_every_n_hours=0.5,
... |
<reponame>anna-naden/qalgebra
from functools import partial
from textwrap import dedent
import pytest
from symbolic_equation import Eq
from sympy import I, Idx, IndexedBase, exp, sqrt, symbols
from qalgebra import (
Adjoint,
BasisKet,
Bra,
BraKet,
CoherentStateKet,
Commutator,
Create,
... |
<filename>jjp068/Statistical_Analysis_Models.py<gh_stars>0
import numpy as np
import pandas as pd
import math
from sklearn.tree import DecisionTreeClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.neighbors import KNeighborsClassifier
from sklearn.svm import SVC
from sklearn.ensemble im... |
<reponame>intuited/5edb
import re
from lxml import etree
from logging import debug, warning, error
from functools import reduce, partial
from pprint import pprint, pformat
from textwrap import dedent
from fractions import Fraction
from dnd5edb import predicates, datatypes
from dnd5edb.datatypes import Reference
from dn... |
<reponame>betairylia/Pokemon-Showdown-Win-Rate-Prediction
import tensorflow as tf
import tensorlayer as tl
import numpy as np
import scipy
import time
import math
import argparse
import random
import sys
import os
import matplotlib.pyplot as plt
from modelv2 import network_model as network_model
from tensorlayer.prep... |
<reponame>nilswagner/pyExSi<filename>tests/generate_freezed_data.py
import sys, os
my_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, my_path + '/../')
import numpy as np
from scipy import stats
from scipy import signal
import matplotlib.pyplot as plt
import pickle
import pyExSi as es
def get_n... |
import pandas as pd
from scipy.sparse import csr_matrix
def sparse_matrix_from_df(df, groupby, indicator):
""" Make a scipy sparse matrix from a pandas Dataframe
Args:
df (pd.DataFrame): Dataframe with the matrix desired rows as index
groupby (str): Name of the column to set as matrix column
... |
<gh_stars>0
import pandas as pd
import os
from scipy import interpolate
import numpy as np
import sys
from thermocouples_reference import thermocouples
import minimalmodbus as mm
import time
import matplotlib.pyplot as plt
import pyqtgraph as pg
"""
1. Define input temperature and heating rate
2. Define how frequently ... |
'''
prepare shape data
include:
point clouds: P x N x 3
part ids: P # the class index in partnet dataset
geo part ids: P # the class index according to the geo information
part poses: P x 7 # T and R
T: center of a part
R: quaternion
'''
imp... |
import cv2
import os
import sys
import pcl
from math import copysign, log10
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
from scipy.spatial import ConvexHull
import random
import math
import itertools
from sklearn.mixture import GaussianMixture
from sklearn.neighbors import... |
<gh_stars>10-100
import os
from . import utils
from .log import log, LogLevel
if not utils.display():
log('[Error] DISPLAY not found, plot not available!', LogLevel.ERROR)
raise Exception("DISPLAY not found, plot not available!")
import math
import matplotlib
from matplotlib import pyplot
import numpy
impor... |
# import numpy as np
import os
# import glob
import statistics
import cv2
import scipy
from matplotlib import pyplot as plt
# from scipy import signal
import numpy as np
# from sklearn import datasets, linear_model
# from sklearn.linear_model import LinearRegression
# import statsmodels.api as sm
# from scipy import s... |
from abc import ABCMeta, abstractmethod
import numpy as np
from numba import njit, vectorize, float64, int64
from sstcam_simulation import Photoelectrons
from scipy.spatial import cKDTree as KDTree
from scipy.stats import norm
__all__ = [
"single_gaussian",
"sipm_gentile_spe",
"SPESpectrum",
"SiPMGenti... |
<reponame>rcooke-ast/PYPIT<gh_stars>0
"""
Provide basic mosaicing functions.
.. include common links, assuming primary doc root is up one directory
.. include:: ../include/links.rst
"""
from IPython import embed
import numpy as np
from scipy import ndimage
from pypeit import msgs
from pypeit.core import transform
f... |
import itertools
import pandas as pd
import scipy.stats as st
from mne.stats import fdr_correction
from plots import update_names
def load_data(dataset):
return pd.read_csv(f"../tables/raw/{dataset}.csv")
def calc_stats(dataset, reverse_grouping=False):
groupings, S1, S2, tval, pval = [], [], [], [], []
... |
import numpy as np
from meshparty import utils
from scipy import spatial, sparse
from dataclasses import dataclass, fields, asdict, make_dataclass
try:
from pykdtree.kdtree import KDTree as pyKDTree
except:
pyKDTree = spatial.cKDTree
from meshparty import skeleton_io
from collections.abc import Iterable
from .... |
'''
Tools for computing topological features in Riemannian space.
Code taken from https://morphomatics.github.io/,
created by <NAME> and <NAME> and <NAME>, 2021.
'''
import numpy as np
import numpy.random as rnd
import numpy.linalg as la
from scipy.linalg import logm, expm_frechet
from pymanopt.manifolds.manifold i... |
<filename>RDF2Vec_Experiments/rdf2vec/RDF2VecEval/DocumentSimilarityEval/model.py
import pandas as pd
import numpy as np
from scipy.stats import spearmanr, pearsonr
from sklearn.metrics import pairwise_distances
# DISCLAIMER
# File modified from https://github.com/mariaangelapellegrino/Evaluation-Framework
class Doc... |
<reponame>CVML-Lab-NUS/hand-kinematic-layer
import torch.nn as nn
import torch
from handPoseLegitimize import *
from utils import *
from config import *
class KinematicLayer(nn.Module):
def __init__(self,RHDtemplate=False,useRHDAngle=False,flex=True,fingerPlanarize=True,abductionLegitimize=True,planeRotationLegiti... |
<reponame>sdres/eventRelatedVASO<filename>code/06_extractRunTimecourses.py
import numpy as np
import glob
import nibabel as nb
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from scipy.interpolate import interp1d
import os
subs = ['sub-13']
ses = 'ses-001'
root = '/media/sebastian/Data/EVENT... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Phase visualization for fidelity weighting.
@author: rouhinen
"""
### Phase visualization
import glob
import matplotlib.pyplot as plt
import numpy as np
from numpy.random import randn
from numpy.linalg import norm
from scipy import signal
"""Load source identities, forwar... |
<filename>QC.py
"""
Created on Sun Feb 10 11:21:31 2019, Last update on Sun Mar 15 00:01:05 2020
@author: <NAME>
"""
import os
import numpy as np
import argparse
import datetime
import QCF
import time
from medpy.io import load # for .mha, .nii, or .nii.gz files
import matplotlib.pyplot as plt
import ... |
<gh_stars>0
"""Useful fitting functions."""
from scipy.optimize import curve_fit
from scipy.signal import medfilt
import numpy as np
import traceback
import warnings
from collections.abc import Iterable
import copy
from .utils import mad, HAS_MPL
__all__ = ["contiguous_regions", "ref_std", "ref_mad", "linear_fun",
... |
<reponame>CalvinNeo/Melotation
#coding:utf8
import numpy as np
import wave, scipy
from scipy.io import wavfile
# include entire numpy/scipy/matplotlib suite to avoid namespace pollute
import pylab as pl
import matplotlib.pyplot as plt
import math
from ada_config import *
from note import *
def test_pitching(config, ... |
'''
This module provides functions for generating RBF-FD weights
'''
from __future__ import division
import logging
import numpy as np
import scipy.sparse as sp
from rbf.basis import phs3, get_rbf
from rbf.poly import count, powers, mvmonos
from rbf.utils import assert_shape, Memoize, KDTree
from rbf.linalg import P... |
import os
import numpy as np
import torch
import torchvision.transforms as trn
import torchvision.transforms.functional as trn_F
import cv2
from PIL import Image as PILImage
import skimage.color as skcolor
from skimage.util import random_noise
from wand.image import Image as WandImage
from wand.api import library as wa... |
import arrow
import conf
import logbook
import datetime
import posixpath
from api import request_base_url
from task.main import celery, exception_safe_task
from task.mail import send_email
from model import Customer, MessageTemplate
from utils.i18n import preferred_language
from urllib.parse import urljoin
def send_e... |
<gh_stars>0
from typing import Dict, Any, Optional
import numpy as np
import logging
from scipy import linalg
from scipy.signal import lfilter, lfilter_zi
from mne.io.eeglab.eeglab import RawEEGLAB
from helpers.fit_eeg_distribution import fit_eeg_distribution
from helpers.block_geometric_median import block_geometric_... |
<filename>studies/event/gw151226_ias_points_no_m1m2_reweighting/plot_caches.py
from deep_gw_pe_followup.restricted_prior import RestrictedPrior
import matplotlib.pyplot as plt
from deep_gw_pe_followup import get_mpl_style
from deep_gw_pe_followup.plotting.hist2d import make_colormap_to_white, plot_heatmap
import os
fro... |
<reponame>qaohv/retinanet-examples
import json
from statistics import mean
from math import isfinite
import torch
from torch.optim import SGD
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch.utils.data import DataLoader
from apex import amp, optimizers
from apex.parallel import DistributedDataParallel... |
<filename>lymph/vgg19.py
# -*- coding: utf-8 -*-
"""
Spyder Editor
This is a temporary script file.
"""
import numpy as np
import os
import scipy.misc
import scipy
from scipy.io import loadmat
import matplotlib.pyplot as plt
import tensorflow as tf
# functions
def _conv_layer(input, weights, bias, name):
conv =... |
import codecs
import csv
import math
import multiprocessing
import os
import xml.etree.cElementTree as et
from functools import partial
import multiprocessing
from pathlib import Path
import sys
from PyQt5.QtCore import pyqtSlot
from tqdm import tqdm
import time as clock
import matplotlib.pyplot as plt
import napari
im... |
<reponame>YichaoOU/TF_target_finder
#!/usr/bin/env python
"""
Given two TFBS bed file, check overlap and output p-value
Parameters
-----------
d distance between the two peaks to consider as co binding
Dependency
-----------
bedtools
Output
------
Venn, FG overlap, mean BG overlap, p-value
"""
from tf_targe... |
<reponame>dpopadic/arpmRes
from numpy import arange, unique, exp, sqrt
from numpy.linalg import norm
from scipy.interpolate import interp1d
from scipy.stats import norm, lognorm
def QuantileMixture(p, alpha, mu_Y, sigma_Y, mu_Z, sigma_Z):
# This function computes the quantiles, corresponding to probability levels... |
#!/usr/bin/env python
"""
Reads GLA12 Release 634 HDF5.
Reads several files in parallel if njobs > 1 is specified.
Extracts a subset of the data based on a mask.tif file.
Example:
python readgla.py /mnt/devon-r0/shared_data/icesat/GLAH12.034/ /mnt/devon-r0/shared_data/icesat/grou... |
import numpy as np
from numpy.random import default_rng
from typing import Callable
from prep_data import load_data, load_data_npy
from models import Node
import models
from utils import save_run, deprecated
from scipy.sparse import csr_matrix, coo_matrix
from tensorflow.keras.metrics import Recall
import warnings
imp... |
r"""
Pore-scale models relevant to multiphase simulations.
"""
import numpy as np
import scipy as sp
__all__ = ["conduit_conductance", "late_filling"]
def conduit_conductance(target, throat_conductance,
throat_occupancy='throat.occupancy',
pore_occupancy='pore.occupanc... |
from __future__ import print_function
import matplotlib.pyplot as plt
import numpy as np
import random
import csv
import json
from scipy.misc import imresize
import os
CLASS_FILE = '/Users/Joshua.Newnham/Documents/Data/quickdraw_dataset/sketch_classes.csv'
SOURCE_DIR = '/Users/Joshua.Newnham/Documents/Data/quickdraw_d... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import time
import numpy as np
import matplotlib.pyplot as plt
import csv
import time
from scipy import signal
from koheron import connect
from drivers import Oscillo
from drivers import Laser
host = os.getenv('HOST','192.168.1.100')
client = connect(host, name... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Krumhansl and Shepard key estimation
"""
import numpy as np
from scipy.linalg import circulant
__all__ = ['estimate_key']
# List of labels for each key (Use enharmonics as needed).
# Each tuple is (key root name, mode, fifths)
# The key root name is equal to that with the smal... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Written by <NAME>
Email: danaukes<at>gmail.com
Please see LICENSE for full license.
"""
import sympy
sympy.init_printing(pretty_print=False)
import pynamics
from pynamics.frame import Frame
from pynamics.variable_types import Differentiable,Constant,Variable
from pynamics.sys... |
<gh_stars>0
from matplotlib.pyplot import show, imshow
from numpy import exp, shape, sqrt, reshape
import numpy as np
from scipy.spatial.distance import squareform, pdist, cdist
from kerpy.Kernel import Kernel
from tools.GenericTests import GenericTests
class MaternKernel(Kernel):
def __init__(self, width=1.0, ... |
<gh_stars>1-10
"""Markov chain scenario trees.
Computes optimally pruned Markov chain scenario trees.
Notes
-----
Uses the polynomial-time algorithm published in [1]_.
References
----------
.. [1] <NAME>, <NAME>, <NAME>, <NAME>, "Fast optimal
pruning for Markov chain scenario tree NMPC", 2019.
"""
from itertools... |
"""PyMC4 discrete random variables."""
import tensorflow as tf
from tensorflow_probability import distributions as tfd
from pymc4.distributions.distribution import (
PositiveDiscreteDistribution,
BoundedDiscreteDistribution,
)
__all__ = [
"Bernoulli",
"Binomial",
"BetaBinomial",
"DiscreteUnifor... |
<gh_stars>10-100
import scipy.stats as sc
import numpy as np
def test_lognorm_pdf():
from numba_stats import lognorm
x = np.linspace(0, 5, 10)
got = lognorm.pdf(x, 1.5, 0.1, 1.2)
expected = sc.lognorm.pdf(x, 1.5, 0.1, 1.2)
np.testing.assert_allclose(got, expected)
def test_lognorm_cdf():
fr... |
<filename>case1_remote_controller/RL_optimizer.py
__author__ = "<NAME>"
__copyright__ = "Copyright (c) 2018, Aalto Speech Research"
# Trains RL agent and evaluates the form.
# Returns best path and the KLM estimate.
import pybrain
from scipy import *
import numpy as np
import math
from UIEnv import UI, UITask
from... |
# -*- encoding: utf-8 -*-
# Functions performing various input/output operations for the ChaLearn
# AutoML challenge
import os
import re
import warnings
import numpy as np
import scipy.sparse
from autosklearn.constants import MULTILABEL_CLASSIFICATION, \
STRING_TO_TASK_TYPES, MULTICLASS_CLASSIFICATION
from auto... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 13 13:18:07 2021
@author: saitel
"""
import numpy as np
import scipy.integrate as integrate
from math import exp
from parameters.parameters import TestParameters2
from helper.plotter import Plotter
class NoCT():
def __init__(self, parameters, ... |
# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... |
<reponame>gnulinooks/sympy
from sympy.polys.specialpolys import (
fateman_poly_F_1, zzX_fateman_poly_F_1,
fateman_poly_F_2, zzX_fateman_poly_F_2,
fateman_poly_F_3, zzX_fateman_poly_F_3)
from sympy.polys.integerpolys import (
zzX_from_poly)
def test_fateman_poly_F_1():
f,g,h = fateman_poly_F_1(1)
... |
#!/usr/bin/env python
"""model_sensitivity.py: Sensitivity test experiments python program for Doppler shift"""
__author__ = "<NAME>."
__copyright__ = "Copyright 2020, SuperDARN<EMAIL>"
__credits__ = []
__license__ = "MIT"
__version__ = "1.0."
__maintainer__ = "<NAME>."
__email__ = "<EMAIL>"
__status__ = "Research"
... |
import itertools
import scipy.cluster.hierarchy as cluster
import matplotlib.pyplot as plt
import os.path
import rsabias.core.features as features
import rsabias.core.dataset as dataset
class TableException(Exception):
pass
def show_dendrogram(linkage, labels, threshold):
d = cluster.dendrogram(linkage, lab... |
from math import sqrt
from math import fabs
from math import log
from scipy.special import binom
def norm_chisq(vector1, vector2):
r"""Compare sequences vector1, vector2 with a Chi^2 test.
Assumes they have the same binning.
Output:
chisq : float
A Chi^2 sum over all bins.
"... |
<filename>cormultipipe.py
#!/usr/bin/python3
"""
The cormultipipe module implements the IoIO coronagraph data reduction
pipeline using ccdmultipipe/bigmultipipe as its base
"""
import inspect
import os
import re
import time
import datetime
import glob
import psutil
import argparse
from pathlib import Path
import num... |
<reponame>valory-xyz/agents-aea
# ------------------------------------------------------------------------------
#
# Copyright 2018-2019 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy... |
import numpy as np
from scipy.integrate import solve_ivp
import matplotlib.pyplot as plt
def SIR_continuous_mask(b,k,time,ii,q):
"""
Simulates continuous SIR model
ii = initial percentage of infected
time = Days of simulation
b = probability that people getting infectious
k = probability that ... |
<reponame>fjxmlinyang/arc<filename>arc/methods.py
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.model_selection import KFold
from scipy.stats.mstats import mquantiles
import sys
from tqdm import tqdm
from arc.classification import ProbabilityAccumulator as ProbAccum
###这个是你的meth... |
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