text string |
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Feb 12 14:16:53 2021
@author: alef
4. Implementar uma função que receba um dicionário e retorne a soma, a
média e a variação dos valores.
"""
import statistics
def analise_dados(saldo_filiais):
total = 0
count = 0
data = []
for filia... |
# -*- coding: utf-8 -*-
import argparse
import cPickle as pickle
import json
import numpy as np
import scipy.io
import random
import chainer
from chainer import cuda, optimizers, serializers, functions as F
from chainer.functions.evaluation import accuracy
from net import ImageCaption
import time
parser = argparse.Ar... |
<reponame>Steven1791/seq2seq<filename>Walkest1_Code/old_versions/notworking_Version_downsampling_with_scipy/main_convert_split_downsample_walkest1.py
#!/usr/bin/env python3
from pydub import AudioSegment
import argparse
import os
from _helper_downsample_wav_walkest1 import main
import tarfile
from scipy.io.wavfile imp... |
<reponame>stjude/SICER2<gh_stars>0
# Authors: <NAME>, <NAME>
# Modified by: <NAME>
import multiprocessing as mp
import os
from functools import partial
from math import *
import numpy as np
import scipy
import scipy.stats
from sicer.lib import associate_tags_with_regions
def associate_tag_count_to_regions(args, s... |
import numpy as np
import pandas as pd
import torch
import warnings
import numba
import rpy2.robjects as robjects
import scipy.integrate as integrate
from dataclasses import InitVar, dataclass, field
from Evaluations.custom_types import NumericArrayLike
def check_and_convert(*args):
""" Makes sure that the given... |
import warnings
warnings.simplefilter(action='ignore', category=FutureWarning)
from pathlib import Path
from collections import defaultdict
import csv
import scanpy as sc
import diffxpy.api as de
import pandas as pd
import anndata
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
from scipy.s... |
<reponame>oaoni/modAL
"""
Functions to select certain element indices from an estimators current predictions.
"""
from scipy.sparse import coo_matrix, triu
import pandas as pd
import numpy as np
import random
from scipy.stats import entropy
from scipy.linalg import svd
# effective rank of matrix = entropy of singular ... |
<reponame>mritools/mrrt.operators
"""
Extended version of the LinearOperator class from pykrylov
class `LinearOperatorMulti` supports multiplication with n-dimensional vectors
and has flexible input/output reshaping options.
A few basic `LinearOperatorMulti` subclasses are also defined here:
`ZeroOperatorMulti`, `Ide... |
#!/usr/bin/python3
"""
Written by <NAME>, 2018
Functional Test: MNIST-SP
This tests that the spatial pooler can recognise basic patterns in its input.
The system consists of a simple black & white image encoder, a spatial pool, and
an SDR classifier. The task is to recognise images of hand written numbers 0-9.
This ... |
<filename>lecarb/dataset/gen_dataset.py
import random
import logging
import numpy as np
import pandas as pd
from scipy.stats import truncnorm, truncexpon, genpareto
from typing import Dict, Any
from .dataset import load_table
from ..constants import DATA_ROOT
L = logging.getLogger(__name__)
def get_truncated_normal(... |
import pandas as pd
from scipy.interpolate import LinearNDInterpolator
from scipy.optimize import fsolve
import sqlite3
import molmass
class Calculator:
def __init__(self, salt, check_bounds=True):
self.salt = salt
self.solute_molar_mass = molmass.Formula(salt).mass
self.solvent_molar_mass = molmass.Fo... |
<gh_stars>1-10
import numpy as np
import onnx
from onnx_tf.backend import prepare
from scipy.stats import norm
import matplotlib.pyplot as plt
# Load the model and sample inputs and outputs
X_test = np.zeros((1001, 20))
xvals = np.linspace(-1, 1, 1001)
X_test[:, 0] = xvals
model = onnx.load('../best_saved_mo... |
<reponame>caporaso-lab/exmp-paper1<filename>code/exmp.py
import bisect
import os.path
from pathlib import Path
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import qiime2
import scipy.stats
import seaborn as sns
import statsmodels.api as sm
from qiime2.plugins.diversity.metho... |
import numpy as np
from sympy.solvers import solve
from sympy import Symbol
from scipy.interpolate import interp1d
from scipy.integrate import trapz
def steel_specific_heat_carbon_steel(temperature):
"""
DESCRIPTION:
[BS EN 1993-1-2:2005, 3.4.1.2]
Calculate steel specific heat acco... |
def time_average_of_TrigFunc(expr, t, method="Integrate_Then_Average", T=None):
from .characteristics import min_period
from sympy import integrate
if method=="Integrate_Then_Average":
from sympy import integrate
if len(T)==1:
return integrate(expr, (t, 0, T)) / T
... |
import sounddevice as sd
from scipy.io.wavfile import write
import csv
import time
sentence_list = []
with open('text.txt', 'r') as f:
for line in f:
sentence_list.append(line)
sample_rate = 44100
seconds = 10
id_prefix = "LJ-"
with open('transcript.csv', 'w') as f:
writer = csv.writer(f, delimiter='|')
fo... |
<filename>patch_sampling.py<gh_stars>1-10
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Created on Mon Dec 18 11:13:47 2017
@author: tzheng
"""
from PIL import Image
import scipy.io as sio
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
import time
#import math
import... |
# sparseToSBM
# scipy csr => 1x1 block
from numpy import finfo, double
eps = finfo(double).eps
from siconos.tests_setup import working_dir
import os
def test_from_csr1():
from siconos.numerics import sparseToSBM, getValueSBM
from scipy.sparse.csr import csr_matrix
M = csr_matrix([[1,2,3],
... |
import os
import pandas
from scipy.stats import lognorm
from tests.test_abnormal_task_perf_analyzer import gen_rows
WORKERS = ["alice", "bob", "carla", "dan", "ella", "felix"]
TASK_DEFS = [
("register person", 10, 16),
("register group", 100, 4),
("register community", 1000, 1),
("survey person", 20... |
import warnings
import time
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from ALDmodel import ALDGrowth
from core import plot_2d, plot_uq
from functools import partial
from scipy.stats import halfcauchy, triang
from scipy.interpolate import interp1d
from sopt import sbost... |
<filename>main_HRmonitoring.py
from heart_rate_monitoring import read_data, find_sampfreq,\
obtain_ECG, obtain_Pleth,\
estimate_instantaneous_HR, some_min_avg, file_size,\
heart_rate_insta, alert_brady_tachy, alert_log, parse_cli, main_arg
import collections
import os
import logging
from scipy.io import loa... |
<gh_stars>1-10
# Copyright (c) Meta Platforms, Inc. and affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from contextlib import ExitStack, contextmanager
from functools import wraps
from typing import Callable, Generator
from unit... |
# -*- coding: utf-8 -*-
from . import Market
from scipy.stats import uniform, norm, expon, gumbel_r
number_firms = 3
products_per_firms = [1] * number_firms
marginal_costs = [0] * number_firms
distributions = [gumbel_r()] * number_firms
market = Market(products_per_firms=products_per_firms,
... |
<reponame>biaalves/Metodos
from sympy import *
y, t = symbols('y, t')
arquivo_de_saida = None
def Printar_Arquivo(strr, y0, t0, h, qtde, vetor_y):
print("Metodo de", strr, file=arquivo_de_saida)
print("y(" + str(t0) + ") = " + str(y0), file=arquivo_de_saida)
print("h = " + str(h), file=arquivo_de_saida)
for j in... |
import os
from datetime import datetime
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
import pandas as pd
from matplotlib.collections import PatchCollection
from matplotlib.colors import ListedColormap
from matplotlib.patches import Rectangle
from netCDF4 import date2num, num2date
fro... |
<reponame>tdcosim/SolarPV-DER-simulation-utility
"""Single phase PV-DER code."""
from __future__ import division
import six
import pdb
import warnings
import numpy as np
import math
import cmath
import scipy
from scipy.optimize import fsolve, minimize
from pvder.DER_components import SolarPVDER,PVModule
from pvder... |
"""Plotting module for elements.
This modules provides functions to plot the elements statistic data.
"""
import numpy as np
import plotly.graph_objects as go
import plotly.io as pio
from plotly.subplots import make_subplots
from scipy.stats import gaussian_kde
pio.renderers.default = "browser"
def plot_histogram(
... |
# This script analyzes the csv files output by main / pixel_distance.py
# uses some methods from pixel_distance.py
# Updated Feb 2021.
# This version separates the data into biological replicates instead of aggregating all data for each sample group.
# pixel_distance.py actually performs the measurement of minimum dis... |
# -- coding: utf-8 --
'''
Run a test on the argument convincingness dataset, but use something like ten-fold cross validation,
rather than splitting the data by topic.
Unlike standard cross validation, we use only 1/10th of the data in each fold as training data, and test on prediction
for all items. This means that w... |
<reponame>kapoorlab/FAQT
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Sep 27 13:08:41 2019
@author: aimachine
"""
from __future__ import print_function, unicode_literals, absolute_import, division
#import matplotlib.pyplot as plt
import numpy as np
import collections
import warnings
from skimage... |
import fractions
import numpy
import pdb
fact_memo = {}
def fact(n):
if n == 0:
return 1
if n not in fact_memo:
fact_memo[n] = n * fact(n - 1)
return fact_memo[n]
def choose(n, k):
return fact(n) / (fact(k) * fact(n-k))
'''
\sum_lb^ub gcd(i,k)
'''
def sum_gcd((lb, ub), k):
retu... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 30 15:49:39 2020
@author: Jyanqa
"""
import plotly.graph_objects as go
import Setting as s
#import plotly.express as px
import pandas as pd
#from plotly import io
from statsmodels.base.model import GenericLikelihoodModel
from scipy import stats
impo... |
import numpy as np
import pandas as pd
import tensorflow as tf
import scipy.sparse as sp
import pickle as pkl
from sklearn.metrics import mean_absolute_error,mean_squared_error
def round_list2D(lst):
lst = np.array(lst)
return np.around(lst,2)
def linear_normolization(feature):
maximum = feature.max()
... |
<gh_stars>1-10
import abc
import numpy as np
from scipy.signal import convolve, sosfiltfilt
from scipy.optimize import linear_sum_assignment
from detectsound.utils import get_1d_gauss_kernel, get_1d_LoG_kernel, first_true, last_true
class _BlobExtractor:
"""
A general-purpose detector for extracting blob-li... |
<filename>manuallists/modeling/train_probabilistic_models.py
#!/usr/bin/env python3
# main_experiment.py
# USAGE syntax:
# python3 main_experiment.py *command*
import sys, os, csv, random
import numpy as np
import pandas as pd
import versatiletrainer2
import metaselector
from math import sqrt
import matplotlib.pypl... |
from transcode.containers import basereader
import ass
import numpy
from fractions import Fraction as QQ
from itertools import islice
from transcode.util import Packet
class Track(basereader.Track):
def __getstate__(self):
state = super().__getstate__()
state["index"] = self.index
state["s... |
# -*- coding: utf-8 -*-
"""
Created on January 02, 2021
@author: <NAME>
"""
import sys
sys.path.append("../")
from pathlib2 import Path
from scipy import sparse
from scipy.sparse.linalg import svds, inv
from dataset import Dataset
import torch
import torch.nn as nn
class HOPE(nn.Module):
def __init__(self, ... |
import pdb
import os
import cv2
import time
from glob import glob
import torch
import scipy
import pandas as pd
import numpy as np
from tqdm import tqdm
import torch.backends.cudnn as cudnn
from torch.utils.data import DataLoader
from argparse import ArgumentParser
import albumentations
from albumentations import torch... |
import cv2
import torch
import tqdm
import os
import numpy as np
from tqdm import tqdm
from scipy.misc import imsave, imresize
import data.eecs442_challenge.ref as ds
import train as net
def generate(test_set, is_train=True):
func, config = net.init()
for idx in tqdm(test_set):
img = ds.load_image(id... |
import numpy as np
from scipy.stats import mode
from . import AbstractClassifier
class ModeClassifier(AbstractClassifier):
"""Classifier which naively guesses the most common class for all test samples"""
def __init__(self):
super(ModeClassifier, self).__init__("Mode")
# train a KNN classifier ... |
import pandas as pd
from sklearn.utils import shuffle
from sklearn.model_selection import train_test_split
from sklearn.feature_extraction.text import TfidfVectorizer
import string
import numpy as np
from scipy import sparse
import re
from gram_maker import make_n_grams
from fuzzy_string_group import stem_group
def t... |
import argparse
from pathlib import Path
import numpy as np
import pandas as pd
from scipy.optimize import linear_sum_assignment
import utils
from challenge.dataset import EXP_TRAIN
from utils.neighbors import k_neighbors_classify, k_neighbors_classify_scores
def parse_args() -> argparse.Namespace:
parser = arg... |
import numpy as np
import seaborn as sns
import pandas
import mcmc_tools
import matplotlib.pyplot as plt
from scipy.stats import norm
# ファイルの読み込み
# y: 生存していた種子数 応答変数
# N: 調査した種子数
# x: 体サイズ
# f: 処理の違い（CまたはT）
data4a = pandas.read_csv('data4a.csv')
print(data4a.head())
print(data4a.describe())
# ここでは、2項ロジスティック回帰を利用して推定を... |
#!/usr/bin/env python3
from __future__ import absolute_import, division, print_function, unicode_literals
import json
import os
from os import path
import cv2
import numpy as np
import numpy
np.set_printoptions(threshold=np.inf)
import open3d
import torch
import pytorch3d
from pytorch3d.io import load_obj
from scipy.s... |
from lightning_model import NuWave
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks import ModelCheckpoint
from omegaconf import OmegaConf as OC
import os
import argparse
import datetime
from glob import glob
import torch
from tqdm import tqdm
from scipy.io.wavfile import write as swrite
def test(... |
<reponame>yokian/csaf<filename>examples/f16/components/fgbase.py
import threading
import socket
import time
import math
import typing
import numpy as np
import pymap3d as pm
from abc import ABC
from scipy.spatial.transform import Rotation
import csaf.core.trace
class Dubins2DConverter():
"""
Originally from... |
<reponame>datree-demo/SROMPy<gh_stars>0
# Copyright 2018 United States Government as represented by the Administrator of
# the National Aeronautics and Space Administration. No copyright is claimed in
# the United States under Title 17, U.S. Code. All Other Rights Reserved.
# The Stochastic Reduced Order Models with P... |
<reponame>SeVEnMY/hyper-reconstruction
import numpy as np
import torch
import cv2
from torch.utils.data import Dataset, DataLoader, TensorDataset
from torch.autograd import Variable
import scipy.ndimage as scin
from scipy import ndimage
from get_name import get_name
import scipy.io as scio
import h5py
new_loa... |
<filename>matPlot.py
# matplotlib
# python 에서 데이터과학관련 시각화 패키지
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# %matplotlib inline #주피터 노트북에서 show() 없이 호출가능
data = np.arange(10)
plt.plot(data)
plt.show()
#산점도 - 100의 표준 정규분포 난수 생성
list =[]
for i in range(100):
x=np.random.normal(0.1)
... |
import numpy as np
from scipy.special import comb
from enum import Enum, auto
import matplotlib.pyplot as plt
class Point:
def __init__(self, *args):
msg = "Invalid arguments"
self._point = np.array(args).flatten()
if not len(self._point) == 2:
raise ValueError(msg)
elif not all([self._point... |
import numpy as np
import re
import json
from markdown2 import Markdown
from Bio import Entrez
from Bio import SeqIO
from collections import defaultdict, OrderedDict
from scipy import stats
from utils import getBindingCore, importBindData,\
importData, reference_retreive, div0, getBindingCore, getRandomColor
def s... |
<filename>book/smoothing/offline_smoothing.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Illustrates the different off-line particle smoothing algorithms using the
bootstrap filter of the following model:
X_t|X_{t-1}=x_{t-1} ~ N(mu+phi(x_{t-1}-mu),sigma^2)
Y_t|X_t=x_t ~ Poisson(exp(x_t))
as in first example in... |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 29 18:38:57 2016
@author: aidanrocke
"""
from behavioral_syntax.visualization.view_postures import view_postures
from scipy import io
import numpy as np
from matplotlib import pyplot as plt
from scipy.stats import itemfreq
image_loc = '/Users/cyrilrocke/Documents/c_eleg... |
import anndata
from scipy.sparse import csc_matrix
import numpy as np
# VIASH START
par = {
"input_train_mod1": "resources_test/predict_modality/openproblems_bmmc_multiome_starter/openproblems_bmmc_multiome_starter.train_mod1.h5ad",
"input_test_mod1": "resources_test/predict_modality/openproblems_bmmc_multiome... |
"""
.. module:: ETFL
:platform: Unix, Windows
:synopsis: flux balance models accounting for expression, thermodynamics, and resource allocation constraints
.. moduleauthor:: ETFL team
Parsing utilities
"""
import re
import sympy
from sympy.parsing.sympy_parser import parse_expr
import ast
ESCAPE_CHARS = (
... |
# -*- coding: utf-8 -*-
"""
Created on Thu Jun 25 09:39:22 2020
@author: <NAME> and <NAME>
"""
"""
Created on Mon Jul 24 19:45:51 2017
@author: <NAME>
"""
import numpy as np
import h5py
import matplotlib.pyplot as plt
import matplotlib.colors as color
from matplotlib.widgets import Slider
from matplotlib.lines imp... |
"""
@Project : DuReader
@Module : sentence_vector_sts.py
@Author : Deco [<EMAIL>]
@Created : 5/9/18 2:50 PM
@Desc :
"""
import os
import pandas
import scipy.stats
import tensorflow as tf
import tensorflow_hub as hub
def load_sts_dataset(filename):
# Loads a subset of the STS dataset into a DataF... |
import os
import argparse
import numpy as np
from matplotlib import pyplot as plt
from scipy import signal
import read
import num2si
import runsliced
parser = argparse.ArgumentParser(prog='spec', description='Frequency spectrum of a LNGS wav or Proto0 root.')
parser.add_argument('filespec', metavar='path[:channel]',... |
<filename>utils/GLASSO/generate.py
import numpy as np
import scipy as sp
import scipy.sparse as spr
import scipy.spatial as spt
def numgrid(n):
grid = np.zeros((n,n),dtype='int64')
counter = 1
for j in range(1, n - 1):
for i in range(1,n-1):
grid[i,j] = counter
counter+=1
... |
from __future__ import print_function, division
import copy
import logging
import numpy as np
from scipy.optimize import fmin_l_bfgs_b
__all__ = ["guess_sky", "fit_galaxy_single", "fit_galaxy_sky_multi",
"fit_position_sky", "fit_position_sky_sn_multi",
"RegularizationPenalty"]
def _check_resu... |
import re
import tokenize
import sympy
import sympy.abc
from sympy.parsing import sympy_parser
from sympy.core.numbers import Integer, Float, Rational
from . import ParsingException, UnsafeInputException
from .utils import process_unicode_chars, auto_symbol, evaluateFalse
__all__ = ["cleanup_string", "is_valid_symbol... |
<reponame>beckrob/AvERA_ISW
import numpy as np
import sys
from scipy import integrate
sims=['BR','LCDM']
startPointNum = 3
simulationTypes = 3
pairings=[]
for i in range(len(sims)):
for j in range(startPointNum):
for k in [2]:#range(simulationTypes):
pairings.append([sims[i... |
<filename>entity_extraction/src/train_task1.py
import config_task1 as config
import statistics
from tqdm import tqdm, trange
import torch
from transformers import BertForTokenClassification, AdamW, get_linear_schedule_with_warmup
import numpy as np
from sklearn.metrics import classification_report, precision_score, f1_... |
<reponame>quentin-burthier/Dendritic_OT<gh_stars>0
"""Balanced Optimal Transport methods for roots."""
import ot
import numpy as np
from scipy.spatial import distance_matrix
from root import Root
def wasserstein(root_1: Root, root_2: Root):
"""Wasserstein distance between two roots."""
sq_dist_matrix = dist... |
# --------------
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]
data=pd.read_csv(path)
#Sam... |
<reponame>khaledghobashy/uraeus-nmbd-python<filename>uraeus/nmbd/python/engine/numerics/solvers/temp.py
# Standard library imports.
import time
# Third party imports.
import numpy as np
import scipy as sc
# Local imports.
from .base import abstract_solver, solve, progress_bar
from .integrators import BDF
###########... |
"""Implements the echo-top-based storm-tracking algorithm.
This algorithm is discussed in Section 3c of Homeyer et al. (2017). The main
advantage of this algorithm (in my experience) over segmotion (Lakshmanan and
Smith 2010) is that it provides more intuitive and longer storm tracks. The
main disadvantage of the ec... |
<gh_stars>1-10
import numpy as np
import itertools as it
import scipy.integrate as integrate
""" Module that gets exact data such as free energies and scaling
dimensions for known models. Most functions expect as arguments a
dictionary called pars, where one of the keys would be called "model"
and the value for that w... |
#!/usr/bin/env python
# coding: utf-8
import sys
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
reaction_num = sys.argv[1]
candidate_df = pd.read_pickle('tsne_embedding/reaction{}_sorted.pickle'.format(reaction_num)).iloc[::-1, :]
fig_tsne, ax_tsne = p... |
<gh_stars>0
# Copyright (c) 2019, Art Compiler LLC
from pint import UnitRegistry
from sympy.physics.units import *
from sympy.vector import StdCoordSys3D, Vector, VectorZero, matrix_to_vector
from sympy.matrices import ImmutableMatrix, Matrix
from sympy.integrals import integrate, Integral
from sympy.series.limits imp... |
# This is a demonstration of how to run The Cannon on RAVE Data
import numpy as np
import pickle
import glob
from scipy.io.idl import readsav
from cannon.dataset import Dataset
from cannon.model import CannonModel
# STEP 1: PREPARE DATA
# The Cannon needs: length-L wavelength vec
# an NxL block of training set pi... |
<filename>nineml/utils/comprehensive_example.py<gh_stars>1-10
"""
Contains an example document with every type 9ML element in it for use in
comprehensive testing over all 9ML elements
"""
from __future__ import absolute_import
from past.builtins import basestring
import pkgutil
from collections import defaultdict
from ... |
<filename>main.py
#! python3
import numpy as np
import sounddevice as sd
import time
import argparse
import queue
import sys
import os
from scipy.io.wavfile import read, write
import tensorflow as tf
import uuid
import random
import threading
import simpleaudio as sa
# Uncomment to disable GPU support
os.environ["CUD... |
from __future__ import print_function
import torch
import torch.nn as nn
from torch.nn import init
import torch.nn.functional as F
import functools
import math
import numpy as np
import torch.optim as optim
from torchvision import models
from torchvision.models.vgg import VGG
from config import config
import matplot... |
<filename>qlknn/plots/load_data.py
import os
import sys
import numpy as np
import scipy.stats as stats
import pandas as pd
from IPython import embed
from qlknn.NNDB.model import Network, NetworkJSON
from qlknn.models.ffnn import QuaLiKizNDNN
def load_data(id):
store = pd.HDFStore('../7D_nions0_flat.h5')
inpu... |
#!/usr/bin/env python3
import sys
import numpy as np
import argparse
import matplotlib.pyplot as plt
from plotTools import addToPlot, addImagePlotDict
from analysisTools import sensibleIds, groundOffset, discreteWaveletAnalysis
from waveletTools import wtDataset, Morlet
from netcdfTools import read3dDataFromNetCDF
from... |
"""Utility functions"""
from typing import Callable
import graphviz
import numpy as np
import pandas as pd
from fim import eclat # pylint: disable=no-name-in-module
from scipy.optimize import linear_sum_assignment
from sklearn.metrics import jaccard_score
def jaccard_index(prediction: np.ndarray, true_labels: np.n... |
#!/usr/bin/env python3
# Copyright 2020 <NAME> (STC-innovations Ltd)
# Apache 2.0.
"""This script modifies TS-VAD output probabilities applying
absolute threshold (--threshold) and relative threshold (--multispk_threshold) for pi/(p1+p2+p3+p4)
(to exclude overlapping regions from i-vectors estimation)"""
impor... |
<filename>kinematics.py
import rospy
import tf
from trajectory_msgs.msg import JointTrajectory, JointTrajectoryPoint
from geometry_msgs.msg import Pose
from mpmath import *
from sympy import *
import csv
class Kinematics:
#Compute and save in memory the transformation matrices when the object is created
#t... |
<reponame>artorious/python3_dojo<gh_stars>0
#!/usr/bin/env python3
""" Object Mutability and Aliasing
A play at Fraction variables and turtle objects
"""
from fractions import Fraction
from turtle import *
##################################################################
# Init: Assign some Fraction vars
f1 = Fractio... |
import numpy as np
import os
import sys
import cv2
import scipy.misc
from PIL import Image
ROOT_DIR = "/datadrive/roost_data"
directory = ROOT_DIR
data_directories = [
#"Roost_Reflectivity",
#"Roost_Velocity",
#"Roost_Zdr",
#"Roost_Rho_HV",
"NoRoost_Reflectivity",
"NoRoost_Velocity",
"NoRo... |
<reponame>jimmy0087/faceai-master
#coding=utf-8
import numpy as np
import tensorflow as tf
from ..utils.layers import AffineTransformLayer, TransformParamsLayer, LandmarkImageLayer, LandmarkTransformLayer
from ..utils.utils import bestFit,bestFitRect
from scipy import ndimage
IMGSIZE = 112
N_LANDMARK = 68
def NormRm... |
# This file is part of the Astrometry.net suite.
# Licensed under a 3-clause BSD style license - see LICENSE
from __future__ import print_function
"""
NAME:
image2xy
PURPOSE:
Extract sources from a FITS file
INPUTS:
Takes a single FITS file as input
OPTIONAL INPUTS:
KEYWORD PARAMETERS:
OUTPUTS:
... |
"""contains customized resampling tools
"""
import numpy as np
import pandas as pd
from scipy.stats import ks_2samp
# During sampling, we need to check if the distributions
# are similar to the original data by setting a
# significance level
# and using Kolmogorov-Smirnoff method.
# TODO refactor this function into ... |
<filename>Python/test_zipf.py
import generate_figs_zipf as gf
import macroeco_distributions as md
from scipy import stats
import signal
from scipy import stats, optimize
import os
import macroeco_distributions as md
import macroecotools
import numpy as np
import mete
import time
mydir = os.path.dirname(os.path.realpat... |
<reponame>rtoopal/CodenamesAI<gh_stars>10-100
from nltk.stem.lancaster import LancasterStemmer
from nltk.stem.wordnet import WordNetLemmatizer
import numpy as np
import scipy.spatial.distance
import itertools
from typing import Tuple, List
from players.codemaster import *
class VectorCodemaster(Codemaster):
"""Ge... |
<gh_stars>0
import inspect
from inspect import Parameter
from pathlib import Path
from typing import *
import copy
import numpy as np
import typing_inspect
from scipy import stats
class Utils:
@classmethod
def get_option_as_boolean(cls, options, opt, default=False, pop=False) -> bool:
if opt not in ... |
<reponame>muppetize/pyprika
import pyprika
from pyprika import Quantity
from .common import BaseTest
from fractions import Fraction
class StaticTest(BaseTest):
def test_parse_error(self):
self.assertRaises(pyprika.ParseError, Quantity.parse, "")
self.assertRaises(pyprika.ParseError, Quantity.parse... |
# python finetune.py --dump_path scratch/dump_bert --model_type bert --batch_size 256 --gpu 0
# python finetune.py --model_path scratch/finetune_bert-large_best --train --model_type bert-large --seed 45847 --optimize bert --lr 5e-05 --num_workers 4 --gpu 2
# python finetune.py --train --model_path scratch/finetune_bert... |
<reponame>rikithamanjunath/Visual-search<gh_stars>0
#!/usr/bin/env python
# coding: utf-8
# In[1]:
import matplotlib.pyplot as plt
get_ipython().run_line_magic('matplotlib', 'inline')
import keras
import tensorflow as tf
import numpy as np
import pandas as pd
from scipy.misc import imread
import cv2
import os
f... |
<reponame>AH-Merii/SpaceNet7_Application_Deployment<filename>src/data/postprocess.py<gh_stars>10-100
import os
import re
import time
import random
import sys
import multiprocessing
import warnings
warnings.filterwarnings('ignore')
import numpy as np
from PIL import Image
import cv2
import skimage.io
from skimage.draw ... |
<gh_stars>1-10
# main code that contains the neural network setup
# policy + critic updates
# see ddpg.py for other details in the network
from ddpg import DDPGAgent
import torch
from scipy.spatial import cKDTree
from utilities import soft_update, transpose_to_tensor, transpose_list, gumbel_softmax, register_hooks
im... |
<reponame>harryzhangOG/ManiSkill<filename>mani_skill/utils/osc.py
import os.path as osp
import numpy as np
import sapien.core as sapien
import yaml
from scipy.linalg import null_space
__this_folder__ = osp.dirname(__file__)
def nullspace_method(J, delta, regularization_strength=0.0):
"""
Find solution of JX =... |
<gh_stars>1-10
# %% Imports
import numpy as np
import copy
import cv2
from matplotlib import pyplot as plt
from skimage.morphology import watershed, binary_dilation, binary_erosion
from scipy import ndimage as ndi
from skimage import filters
import mahotas as mh
import matplotlib as mpl
# %% Parameters
# Color map
cma... |
<reponame>tbuffington7/fire-risk
import click
import pandas
from scipy.stats import lognorm
@click.command()
@click.argument('filename')
@click.option('--column', default='Total_Trav', help='Column to identify shape, location, and scale from.')
def response_time_dist(filename, column):
"""
Returns the lognorma... |
import time
from typing import List, Tuple, Dict, Optional
import numpy as np
import pandas as pd
from scipy.optimize import minimize
from .helpers import Float, Frame, Rebalance
from .assets import AssetList
class EfficientFrontierReb(AssetList):
"""
Efficient Frontier (EF) for rebalanced portfolios.
... |
<reponame>miguelandrs/QuantLib-SWIG
# Example of option baskets
# Distributed under BSD License
from enthought.mayavi.scripts import mayavi2
mayavi2.standalone(globals())
import scipy
import QuantLib as ql
from enthought.tvtk.tools import mlab
from enthought.mayavi.sources.vtk_data_source import VTKDataSource
from ... |
<filename>lodestar-backend/code/LineGeometry/line_geodesics_shapely.py<gh_stars>0
import numpy as np
from shapely.ops import nearest_points
import shapely.geometry as geom
from scipy.spatial.distance import cdist
from code.miscellaneous.utils import pairwise_loop
from code.LineGeometry.utils import is_between, distance... |
# -*- coding: utf-8 -*-
"""
Created on Thu Mar 08 14:42:14 2018
@author: asikora
"""
from air_equilibrium_properties import a_from_p_s, h_from_p_rho, rho_from_p_s, T_from_p_rho
from gas import initialize_gas_object, speed_of_sound
T = 8000
P = 100 * 101325
air = initialize_gas_object('air')
air.TP = T, P
air.equi... |
<gh_stars>1-10
import cv2
from scipy.spatial import distance as dist
cap = cv2.VideoCapture(0)
body_model = cv2.CascadeClassifier('haarcascade_upperbody.xml')
while True:
status , photo = cap.read()
body_cor = body_model.detectMultiScale(photo)
l = len(body_cor)
photo = cv2.putText(photo, st... |
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