text string |
|---|
<filename>qiskit_metal/renderers/renderer_gds/gds_renderer.py
# -*- coding: utf-8 -*-
# This code is part of Qiskit.
#
# (C) Copyright IBM 2017, 2021.
#
# This code is licensed under the Apache License, Version 2.0. You may
# obtain a copy of this license in the LICENSE.txt file in the root directory
# of this source ... |
<reponame>jonbmartin/sigpy_rf<filename>sigpy/mri/rf/b1sel.py
# -*- coding: utf-8 -*-
""":math:`B_1^{+}`-selective RF Pulse Design functions.
"""
import numpy as np
from sigpy.mri.rf import slr as slr
from sigpy.mri.rf.util import dinf, b12wbs, calc_kbs
from scipy.interpolate import interp1d
__all__ = ['dz_bssel_rf', ... |
#!/bin/python
###################################################################################################
### Name: Read zeTorch Data ### Developer: <NAME>
### Purpose: Reads zeTorch Data from a run where all of the run files are in the same directory
### Use: python read_zeTorch_data.py data_directory/ starti... |
import elevation
import tifffile
import numpy as np
import matplotlib.pyplot as plt
from ECMapProb_Functions import read_input , import_map , read_map_utm , read_map_deg , matrix_deg , matrix_utm , create_inputs , create_vent_deg , create_vent_utm , read_comparison_polygon_deg , read_comparison_polygon_utm , initial_de... |
import numpy as np
import os
import cv2
import PIL.Image as Image
from scipy.signal import savgol_filter
from itertools import product
from string import ascii_lowercase
import sys, math
sys.path.append("../../IAD-Generator/iad-generation/")
from csv_utils import read_csv
from multiprocessing import Pool
def op... |
<filename>hic3defdr/analysis/alternatives.py<gh_stars>0
"""
Experimental module exposing variants of the HiC3DeFDR model for benchmarking
purposes.
"""
import numpy as np
import scipy.stats as stats
from hic3defdr.analysis import HiC3DeFDR
from hic3defdr.util.printing import eprint
from hic3defdr.util.dispersion impo... |
<gh_stars>1-10
import numpy as np
import matplotlib.pyplot as plt
import csv
from VAWT_Wake_Model import velocity_field
from scipy.io import loadmat
from numpy import fabs
from os import path
from matplotlib import rcParams
rcParams['font.family'] = 'Times New Roman'
rom = True
# rom = False
r = 0.5 # radius
v = 1.... |
<filename>mcmc_gtb.py<gh_stars>0
#!/usr/bin/env python3
"""
Markov Chain Monte Carlo (MCMC) sampler for polygenic prediction with continuous shrinkage (CS) priors.
"""
import scipy as sp
from scipy import linalg
from scipy import random
import gigrnd
def mcmc(a, b, phi, sst_dict, n, ld_blk, blk_size, n_iter, n_b... |
import streamlit as st
from alphapept.gui.utils import files_in_folder, read_log, escape_markdown
from alphapept.paths import PROCESSED_PATH
from alphapept.settings import load_settings
import os
import yaml
import alphapept.io
import pandas as pd
import base64
import plotly.express as px
from plotly.subplots import ma... |
<filename>CaptionSaliency.py
# -*- coding: utf-8 -*-
"""
Created on Thu Aug 27 15:58:48 2015
@author: haoran
"""
from pycocotools.coco import COCO
import numpy as np
import skimage.io as io
import pickle
import os
#import nltk
import matplotlib.pyplot as plt
from nltk.corpus import wordnet as wn
import scipy.io as si... |
"""
Authors: <NAME>, <NAME>
Project: Graduation Thesis: GIAdog
This file provides an interface to control and monitor the simulation status.
"""
import numpy as np
import pybullet_utils.bullet_client as bc
from scipy import interpolate
from gym import spaces
from Scene import TerrainScene
from typing impo... |
<gh_stars>1-10
import unittest
import ros
import numpy
from scipy.stats import norm
TOLERENCE = 0.2
class TestROS(unittest.TestCase):
def test_ros(self):
print "Testing on synthesized data"
m = 10.0
s = 30.0
print "actual mean", m
print "actual std", s
... |
<gh_stars>1-10
# -*- coding: utf-8 -*-
"""
Created on Sun May 24 22:02:49 2015
@author: <NAME>
"""
import numpy as np
from scipy.stats import norm
from scipy.ndimage.filters import gaussian_filter
from scipy.ndimage.filters import median_filter
import xarray as xr
""" learn from this example
import xarray as xr
... |
"""
A combinatorial specification is a set rules of the form a -> b1, ..., bk
where each of the bi appear exactly once on the left hand side of some rule.
"""
from copy import copy
from functools import reduce
from operator import mul
from typing import Dict, Generic, Iterable, Iterator, List, Sequence, Set, Tuple, Uni... |
import numpy as np
import os
from os.path import isfile, join
from os import listdir
import scipy.misc as misc
import cv2
from PIL import Image
import pdb
from matplotlib import pyplot as plt
import Crop_disc
import parse as par
import Inference as Inf
from label_image import run_inference
#import classifier.Inference ... |
import numpy as np
from scipy.linalg import eigh_tridiagonal
class BNMatrix:
"""
Define a class to compute the B_N matrix ( with elements of b^N_mn) denoting the matrix of the operator L_c
with respect to the basis T_Nn(x) by elements of b^N_mn. The matrix element b^N_mn is calculated as
< T_Nm, L_c T... |
#!/usr/bin/env ../../../../../dependencies/python/install/bin/python3
# -*- coding: utf-8 -*-
#
# This script extracts horizontal rings of edges from the stl mesh of biceps. The rings are not planar (but almost).
# Use create_rings.py instead, which samples the mesh at prescribed z values and produces planar rings.
#
... |
<filename>merlion/models/anomaly/base.py<gh_stars>1000+
#
# Copyright (c) 2022 salesforce.com, inc.
# All rights reserved.
# SPDX-License-Identifier: BSD-3-Clause
# For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause
#
"""
Base class for anomaly detectors.
"""
fr... |
<filename>pypi/scipy.py
import numpy as np
from scipy import stats
# trim mean
stats.trim_mean([1,2,3,4,5,6,7,8,9], .1) # 5
# linear regression
x = np.array([1,2,3,4])
y = [2,3,2,1]
res = stats.linregress(x, y)
list(res.intercept + res.slope * x) # [2.6, 2.2, 1.79, 1.4]
# pearson corrolation
r, _ = stats.pearsonr([1... |
# Original Version: <NAME> (http://carpedm20.github.io)
# + Source: https://github.com/carpedm20/DCGAN-tensorflow/blob/e30539fb5e20d5a0fed40935853da97e9e55eee8/main.py
# + License: MIT
# [2016-08-05] Modifications for Inpainting: <NAME> (http://bamos.github.io)
# + License: MIT
# [2017-07] Modifications for sText... |
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""Folium ... |
<reponame>apoorvam/smart-sensing
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import style
import scipy.fftpack
import scipy as sp
from scipy.stats import zscore
import pandas as pd
from scipy.signal import butter, filtfilt
from scipy import signal
import warnings
warnings.filterwarnings(action="i... |
import os
import numpy as np
import scipy
import cupy as cp
from cupy.cuda import Device
from cupy.cuda.runtime import getDeviceCount
from mpi4py import MPI
# import socket
from ..common import _start, _finish
# 計測開始
def start(method_name='', k=None):
_start(method_name, k)
return MPI.Wtime()
# 計測終了
def f... |
__doc__ = """\
a module holding simple utilities for reading bayesline chains. The conventions assumed herein are taken from the BayesWave source code:
spline file structure: BayesWaveIO.c line 1737
spline model: BayesLine.c lines 1105-1139
line file structure: BayesWaveIO.c line 1773
line mo... |
<reponame>LBJ-Wade/Neutron-Star-Structure
import numpy as np
import matplotlib.pyplot as plt
from scipy.interpolate import CubicSpline
global G,c
G=6.67e-8
c=3e10
#Interpolating the EOS
sly=np.genfromtxt("SLy.txt",delimiter=" ")
nbs=sly[:,1]
rhos=sly[:,2]
Ps=sly[:,3]
cPs=CubicSpline(rhos,Ps)
crs=CubicSpline(Ps,rho... |
<filename>experiment/process_activities.py
import numpy as np
import re
import sys
sys.path.insert(0, '../')
import paths
from scipy.constants import N_A
from scipy.integrate import odeint
from scipy.interpolate import interp1d
class Au_Foil_Data(object):
"""This object is responsible for handling the postproces... |
import numpy as np
from PIL import Image
import os
from scipy.io import savemat
def create_arrays():
for task_dir in os.listdir('images_background'):
X = []
y = []
if not task_dir.startswith('.'):
for label_dir in os.listdir('images_background/' + task_dir):
if n... |
<reponame>Lennart-Ma/data-efficient-gans
from . import metric_utils
import os
import copy
import dnnlib
import torch
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
from skimage.metrics import structural_similarity as ssim
from scipy.spatial import distance
def get_ssim(**kwargs):
"""
... |
#use the nonlocal topological method to detect tips.
# also records topologcially preserved values.
#<NAME>
#9.13.2021
from skimage import measure
from numba import jit, njit
from numba.typed import List
import numpy as np, os
from . import *
# from .intersection import *
from scipy.interpolate import interp2d
from .i... |
<reponame>talonchandler/polaris
from polaris import spang, util
import numpy as np
from scipy.special import hyp1f1
from dipy.data import get_sphere
import logging
log = logging.getLogger('log')
def three_helix(vox_dim=(130,130,130), px=(64,64,64), radius=600, scale=[1,1,1]):
phant = spang.Spang(np.zeros(px + (15,... |
<reponame>clean-code-craft-tcq-1/start-stats-python-AkshayUHegde
import statistics
class EmailAlert:
def __init__(self):
self.emailSent = False
def trigger(self):
self.emailSent = True
class LEDAlert:
def __init__(self):
self.ledGlows = False
def trigger(self):
self... |
import numpy as np
from scipy.special import erfinv, gammainc
from scipy.stats import gamma
from scipy.linalg import lstsq
from copy import deepcopy
from obspy.geodetics.base import calc_vincenty_inverse
""" Contains the auxilliary functions called by fast_lts_array.py
Many of these codes are Python3 translations of... |
"""
Demonstration of the GazeTracking library.
Check the README.md for complete documentation.
"""
from KalmanFilter1D import Kalman1D
import cv2
from gaze_tracking import GazeTracking
from scipy.interpolate import interp1d
import numpy as np
gaze = GazeTracking()
webcam = cv2.VideoCapture("v4l2src device=/dev/video0... |
__all__ = 'X', 'Y'
from sympy.core.symbol import Symbol
from .._r1.coord import X
# coordinates of real Y axis
Y = Symbol(name='y', real=True)
|
<reponame>stsievert/diff_classifier
import matplotlib as mpl
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy.spatial import Voronoi
import scipy.stats as stats
import os
import os.path as op
from shapely.geometry import Point
from shapely.geometry.polygon import Polygon
import numpy.ma... |
<filename>RData.py
import csv
import os
import numpy as np
from scipy.interpolate import interp1d
from ActualData import ActualData
# noinspection PyBroadException
class RData:
Rt = None
Rt_t1 = []
Rt_interpolate = []
@staticmethod
def load_file(file_name):
if os.path.exists(file_name):
... |
<reponame>bmoretz/Python-Playground
# The distance of a particle from some fixed point is given by the following function.
from sympy import symbols, Limit, Derivative, Integral
def rate_of_change( f, a, b ):
return ( f.subs( { t: b } ) - f.subs( { t: a } ) ) \
/ ( b - a )
t,h = symbols( 't,h' )
sT = t**2 + 3*t - ... |
from scipy.optimize import leastsq
from copy import deepcopy
import numpy as np
import warnings
def standardize_vector(vector):
if vector[0] != 0:
if vector[0] < 0:
vector = np.array(vector) * -1
vector = vector.tolist()
elif vector[1] != 0:
if vector[1] < 0:
... |
<reponame>charlesblakemore/opt_lev_analysis
import numpy as np
import matplotlib.pyplot as plt
from hs_digitizer import *
import glob
import scipy.signal as signal
import scipy.optimize as opti
import re, sys
from tqdm import tqdm
from joblib import Parallel, delayed
ncore = 30
import dill as pickle
import bead_util... |
<filename>DeepLearningAI/Harp.py
from scipy.spatial import distance
from imutils import face_utils
import imutils
import dlib
import sys
import cv2
import requests
import datetime
import notification
import TkinterInitialScreen
import pickle
import json
import webbrowser
def eye_aspect_ratio(eye):
A = distance.euclid... |
<reponame>p-chambers/astra_simulator
# coding=utf-8
"""
This module contains classes for modelling the weather and atmosphere.
The environment classes providing the simulator module with all the atmospheric
data throughout a simulation. There are two environment
subclasses defined here:
forecastEnvironment : GFS-... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.4'
# jupytext_version: 1.1.4
# kernelspec:
# display_name: Python 3
# language: python
# name: python3
# ---
# # s_st... |
<reponame>elizabethnewman/tensor-fmri
import numpy as np
from numpy.linalg import norm
from numpy.testing import assert_array_almost_equal
from tensor.utils import assert_compatile_sizes_facewise, reshape
import tensor.f_product as fprod
from scipy.fft import dct, idct
# choose dimensions to input (this will yield an... |
<gh_stars>10-100
from ..utils import matrices
from scipy.sparse.linalg import spsolve
import numpy as np
def solve_heat_flow(mesh, heat_sources, time):
heat_sources = np.array(heat_sources)
#hs = heat_sources.shape[0]
L = matrices.laplacian_matrix(mesh)
MM = matrices.mass_matrix(mesh)
rhs = np... |
<reponame>yujing1997/CTcnn
import matplotlib
matplotlib.use('Agg') #to actually be able to use matplotlib
import numpy as np
from scipy.misc import imsave,imread
import time
from keras import backend as K
from vis.visualization import visualize_activation,visualize_saliency,visualize_cam,get_num_filters
from vis.utils... |
# Copyright 2018-2021 Xanadu Quantum Technologies Inc.
# 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 applicable law or... |
<filename>tvd/tvd.py
import geometry
import networkx as nx
import point
import scipy.spatial as spatial
class TVD(object):
def __init__(self, grid, b_dist=1, n_size=1, auto=True):
self.grid = grid
self.auto = auto
if auto:
self.generate_graph(b_dist=b_dist, n_size=n_size)
... |
<gh_stars>0
import random
import numpy as np
from biclustering import Construct_Binary_Clustering
import matplotlib.pyplot as plt
import scipy
from functools import reduce
import os
import argparse
import faulthandler; faulthandler.enable()
class Winnow:
def __init__(self,dims,i,string,data_normal=False,lr=None,d... |
<reponame>chuckie82/psgeom<filename>psgeom/camera.py<gh_stars>0
#!/usr/bin/env python
"""
Detector Geometries
===================
Briefly, geometries are organized heriarchically: there are `SensorElements`
that compose the leaves of a tree. These represent arbitrary objects that
actually measure e.g. photon intensit... |
<reponame>shorohml/SuperComp<gh_stars>0
import numpy as np
from scipy import integrate
def f(x, y, z):
xz_sq = x*x + z*z
if xz_sq + y * y <= 1:
return np.sin(xz_sq) * y
else:
return 0.0
if __name__ == '__main__':
options = {'limit': 300}
y, abserr = integrate.nquad(
f,
... |
import numpy as np
import scipy.stats
import matplotlib.pyplot as plt
import time
import os
import pickle
import pandas as pd
# import seaborn as sns
from sklearn.manifold import TSNE
from matplotlib.ticker import FormatStrFormatter
# sns.set_style("white")
def get_bias(d1, d2, d3=None):
z = d1 + d2
bias = 0... |
<filename>single_step/ranking/candidates_extracting.py<gh_stars>1-10
import os
import sys
import pickle
from pathlib import Path
import numpy as np
import pandas as pd
import shutil
import scipy.sparse as sp
from utils.fingerprint_utils import SparseFingerprintCsrMatrix
from utils.draw_utils import draw_mol_smi
from ut... |
<reponame>wolferobert3/vast_aaai_2022<filename>WEAT.py
import numpy as np
from helper_functions import cosine_similarity, std_deviation, create_permutation
from scipy.stats import norm
import random
def permutation_test(A, B, X, Y, test_stat, permutations):
distribution = []
for _ in range(permutati... |
import numpy as np
import matplotlib.pyplot as plt
from scipy import optimize
# lets just generate some data from known beta parameters
x = np.linspace(0,10,30)
beta0 = 2.7
beta1 = 1.3
y = (beta0*x)/(beta1+x)
# determine beta0 and beta1 by minimizing the mean abs residual error
def my_func(X):
... |
import pathlib
import numpy as np
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
from scipy.optimize import linear_sum_assignment
from dicodile.config import DATA_HOME
from dicodile.utils.viz import display_dictionaries
OUTPUT_DIR = pathlib.Path('benchmarks_results')
DATA_DIR = DATA_HO... |
<reponame>goujou/CompartmentalSystems
#!/usr/bin/env python
# all array-like data structures are numpy.array
import numpy as np
from copy import copy
from string import Template
from sympy import Matrix, symbols, Symbol, Function, latex, atan, pi, sin, lambdify, Piecewise
import matplotlib.pyplot as plt
# load the com... |
import collections
import dataclasses
import enum
import functools
import itertools
import operator
import random
import re
import typing
from typing import (
Any,
Mapping,
Union,
MutableMapping,
Optional,
TypeVar,
Callable,
NamedTuple,
Type,
Tuple,
Sequence,
)
import matpl... |
<filename>spectrochempy/core/fitting/optimization.py
# -*- coding: utf-8 -*-
# ======================================================================================================================
# Copyright (©) 2015-2021 LCS - Laboratoire Catalyse et Spectrochimie, Caen, France. =
... |
from datetime import time
import os
import pandas as pd
import matplotlib.pyplot as plt
from scipy.signal import find_peaks, butter, lfilter, filtfilt
import numpy
import math
def normalizeData(data : list):
maxv = max(data)
minv = min(data)
res = []
for i in data:
res.append((i - minv)/(maxv... |
<reponame>wenbin-hu/allegro_hand_ros_v4
import rospy
from sensor_msgs.msg import JointState
import numpy as np
import scipy.io as sio
import time
from datetime import datetime
from scipy.io import loadmat, savemat
class AllegroController:
def __init__(self):
# define the publisher and subscriber
s... |
<filename>openmdao/surrogate_models/nn_interpolators/nn_base.py
"""Define the NNBase class."""
import numpy as np
from math import ceil
from scipy.spatial import cKDTree
class NNBase(object):
"""
Base class for common functionality between nearest neighbor interpolants.
Attributes
----------
_t... |
from typing import Optional, Dict, List, Any
from ausseabed.qajson.model import QajsonParam, QajsonOutputs, QajsonExecution
from ausseabed.mbesgc.lib.data import InputFileDetails
from ausseabed.mbesgc.lib.tiling import Tile
import collections
import numpy as np
import numpy.ma as ma
import scipy.ndimage as ndimage
imp... |
<gh_stars>1-10
import numpy as np
import quinoa as qu
import matplotlib.pyplot as plt
import GPy as gpy
from scipy import linalg
#np.random.seed(31051985)
X = np.random.normal(scale = 1, size = (100,1))
Y = np.sin(X) + 0.01 * np.random.normal(size = (100,1))
#kern = qu.RBF(1, 1, 1)
ker = gpy.kern.RBF(1, 1, 1)
kern ... |
<filename>preprocessing/lineRemoval.py
import numpy as np
import cv2
# Hough line detection
# Credit: https://vzaguskin.github.io/fourielines1/
def houghLines(img):
from skimage.draw import line
w, h = img.shape
acc = []
for i in range(h):
rr, cc = line(0, i, w-1, h-i-1)
acc.append(np.s... |
<gh_stars>0
#!/usr/bin/env python3
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import os
import re
from sys import argv
from astropy.io import fits
from scipy import ndimage
from scipy.optimize import curve_fit
from time import sleep
from datetime import datetime, timedelta
... |
<gh_stars>0
# coding: utf-8
# In[ ]:
"""
Microkinetic model for ammonia oxidation
Inspired by Grabow, <NAME>.
"Computational catalyst screening."
Computational Catalysis. RSC Publishing, 2013. 1-58.
"""
# In[ ]:
import numpy as np
from scipy.integrate import odeint
import matplotlib.pyplot as plt
import pickle... |
<reponame>mbuhot/mbuhot-euler-solutions<filename>python/problem-033.py
#! /usr/bin/env python3
description = """
Digit canceling fractions
Problem 33
The fraction 49/98 is a curious fraction, as an inexperienced mathematician in attempting to simplify it may incorrectly believe that 49/98 = 4/8, which is correct, is o... |
<filename>PrimalInteractive/python/PrimalInteractive/plotting/phz_plots.py
"""
Overview
--------
general info about this module
Module API
----------
"""
from __future__ import absolute_import, division, print_function
from builtins import (bytes, str, open, super, range,
zip, round, input,... |
import numpy as np
import tensorflow as tf
import theano.tensor as tht
import scipy.misc
from time import time
from os.path import dirname, join
import keras.backend as K
from keras.models import Model
from keras.layers import Layer, Input, InputLayer, Conv2D, MaxPooling2D, Activation, Conv2DTranspose
from keras.prep... |
<reponame>CSAILVision/placeschallenge<gh_stars>100-1000
# This script converts image annotations in a val/test into a RLE format json dataset
import os
import glob
import argparse
import json
import numpy as np
from scipy.misc import imread
from pycocotools import mask as COCOmask
def parse_args():
parser = argpar... |
<reponame>charlesblakemore/opt_lev_analysis<filename>scripts/spinning/ringdown_analysis_parallel.py<gh_stars>0
import os, time, sys
import numpy as np
import matplotlib.pyplot as plt
from iminuit import Minuit, describe
from obspy.signal.detrend import polynomial
import bead_util as bu
import peakdetect as pdet
impor... |
"""Implements Exact Maximum Entropy IRL from my thesis"""
import numpy as np
from numba import jit
from numba import types
from numba.typed import Dict, List
from scipy.optimize import minimize
from mdp_extras import (
Linear,
Disjoint,
trajectory_reward,
DiscreteExplicitExtras,
DiscreteImplicit... |
# coding=utf-8
"""
Problem 57
21 November 2013
It is possible to show that the square root of two can be expressed as an infinite continued fraction.
√ 2 = 1 + 1/(2 + 1/(2 + 1/(2 + ... ))) = 1.414213...
By expanding this for the first four iterations, we get:
1 + 1/2 = 3/2 = 1.5
1 + 1/(2 + 1/2) = 7/5 = ... |
<gh_stars>0
import sys
sys.path.append("NumPy_path")
import cv2
import scipy.misc
import numpy as np
import pcl
import math
import pcl.pcl_visualization
import matplotlib.image as mpimg
# from imresize import *
from PIL import Image
# import pcl.pcl_visualization
# p = pcl.PointCloud(10) # "empty" point cloud
# a = n... |
<reponame>apahl/cellpainting2
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
#####
Tools
#####
*Created on Thu Jun 7 14:45 2017 by <NAME>*
Helper Tools acting on individual data..
"""
import os
import os.path as op
import sys
import glob
from collections import Counter, namedtuple
import yaml
import pandas as ... |
from collections import defaultdict
from math import log10, log
from threading import Thread
import threading
import math
import pyglet
import numpy as np
import geoplotlib.colors as colors
from geoplotlib.core import BatchPainter,FONT_NAME
from geoplotlib.utils import BoundingBox
import queue
from inspect import isfun... |
import urllib.request
import json
import dml
import prov.model
import datetime
import uuid
import statistics
import pandas as pd
from bson.code import Code
class transform_citibike_byday(dml.Algorithm):
contributor = 'anuragp1_jl101995'
reads = ['anuragp1_jl101995.citibike']
writes = ['anuragp1_jl101995.ci... |
# Copyright (c) 2018 <NAME>
# Universidad Carlos III de Madrid and University of Sheffield
import sys
import numpy as np
import GPy
from GPy.inference.latent_function_inference import LatentFunctionInference
from GPy.inference.latent_function_inference.posterior import Posterior
from GPy.util import choleskies
from GP... |
"""
TODO update description
based on this: https://raw.githubusercontent.com/explosion/spaCy/master/examples/deep_learning_keras.py
This example shows how to use an LSTM sentiment classification model trained
using Keras in spaCy. spaCy splits the document into sentences, and each
sentence is classified using the LSTM.... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""Smoothing ROAR_Sim_waypoints_Berk.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/drive/1AHfcoJq3pELWIY2u3ghwsyE1GIXcI868
"""
import numpy as np
from scipy.interpolate import interp1d
waypoints=np.array([[-809.3... |
<filename>NeuralNetwork/RNN.py
import numpy as np
import pylab as pl
import math
from sympy import *
class RNN:
def __init__(self):
pass
def set_input_layer(self, x):
self.input_layer = np.zeros(x)
return self.input_layer
def set_output_layer(self, x):
self.output... |
import pandas as pd
import streamlit as st
from sympy import lambdify, parse_expr
from src.common.consts import TRANSFORMATIONS
from src.common.methods.table_of_values_generators.equidistant_generator import EquidistantTableOfValuesGenerator
from src.common.methods.table_of_values_generators.random_generator import Ra... |
<filename>src/modeci_mdf/scheduler.py
import os
import sys
import sympy
from modeci_mdf.standard_functions import mdf_functions, create_python_expression
from neuromllite.utils import evaluate as evaluate_params_nmllite
from neuromllite.utils import _params_info, _val_info
from neuromllite.utils import FORMAT_NUMPY, ... |
<reponame>rokroskar/GPy
import numpy as np
import sympy as sp
from sympy.utilities.codegen import codegen
from sympy.core.cache import clear_cache
from scipy import weave
import re
import os
import sys
current_dir = os.path.dirname(os.path.abspath(__file__))
import tempfile
import pdb
import ast
from kernpart import Ke... |
import numpy as np
from matplotlib import pyplot as plt
import pickle
import scipy.stats as st
def read(dim):
file = open('../../data/simulation/clustering_group_{}D'.format(dim), 'rb')
data = pickle.load(file)
data = [dat[0] for dat in data]
return np.array(data)
def draw(dim, ax):
settings = [... |
<filename>specaugment.py
#!/usr/bin/env python3
import time
import random
import argparse
import sys
import numpy as np
import numpy.linalg as nl
import matplotlib.pyplot as plt
import librosa
import librosa.display
from scipy import interpolate
from scipy import signal
from scipy.io import wavfile
from scipy.fftpack... |
import sys
import copy
import numpy as np
from scipy.misc import logsumexp
import utils
from environment import *
class Fit():
def __init__(self, game_data = None, background_dir = None, player = None, test = False, stop_and_click = False):
if game_data is not None:
se... |
# ==================================================
#
# Copyright (c) 2018, Alibaba Inc.
# All Rights Reserved.
#
# ==================================================
# -*- coding: utf-8 -*-
"""
EvaluationMetrics class for evaluating input data.
Currently supported evaluation metrics:
map,auc,mse,accuracy,ndcg@k,... |
import logging
import os
from dataclasses import dataclass
from string import Template
import numpy as np
import tables
import pyinotify
from phd.thunderstorm.convert_to_hdf5 import CylinderProtoSet
from phd.utils.hdf5_tools import ProtoSetReader
from phd.utils.run_tools import G4CinServer, CinServerParameters
from t... |
import numpy as np
from scipy.spatial.distance import euclidean
# Licence: GNU GPLv3
# Author: <NAME>
# 2018
# objectif :
# distribuer un nombre fixe d'items dans un nombre fixe de paniers
# chaque item a deux attributs : categorie, poids
# Cost function :
# la somme des distances distribution_de_categories vs dis... |
# # Autonomous driving - Car detection
import argparse
import os
import matplotlib.pyplot as plt
from matplotlib.pyplot import imshow
import scipy.io
import scipy.misc
import numpy as np
import pandas as pd
import PIL
import tensorflow as tf
from keras import backend as K
from keras.layers import Input, Lambda, Conv... |
import os
import sys
import numpy as np
from metrics_ddie import ddie_compute_metrics
from scipy.special import softmax
import glob
_, outputs_dir = sys.argv
cnt = 0
for path in glob.glob(os.path.join(outputs_dir, '*')):
labels = np.load(os.path.join(path, 'labels.npy'))
preds = np.load(os.path.join(path, 'pr... |
import argparse
import os
import pickle as pkl
from scipy.io import loadmat
import numpy as np
def parse_args():
parser = argparse.ArgumentParser(description="Generate database for RAPv2 dataset")
parser.add_argument("--dataset-split", help="dataset split, e.g. train, val, test",
defau... |
<gh_stars>1-10
from collections import Counter
import numpy as np
from scipy.spatial.distance import euclidean
from mla.base import BaseEstimator
class KNNBase(BaseEstimator):
def __init__(self, k=5, distance_func=euclidean):
"""Base for Nearest neighbors classifier and regressor.
Parameters
... |
<reponame>stairs1/memory-prosthetic-tools
import time
import deepspeech
import numpy as np
import threading
from scipy import signal
import pathlib
import os
class Buf:
"""
Assistant to Transcriber.
This buffer holds audio data for a Transcriber until it can be fed to a deepspeech stream. This is needed to... |
# MIT License
#
# Copyright (c) 2016 <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 without restriction, including without limitation the rights
# to use, copy, modify, merge, pub... |
<filename>h5pyViewerLib/FrmProcRoiStat.py<gh_stars>1-10
#!/usr/bin/env python
# *-----------------------------------------------------------------------*
# | |
# | Copyright (c) 2013 by Paul Scherrer Institute (http://www.psi.ch) |
# | ... |
import os
import numpy as np
import pandas as pd
import tensorflow as tf
import seaborn as sns
from scipy.stats import spearmanr
from scipy.stats.mstats import pearsonr
from sklearn.metrics import mean_squared_error
from sklearn.metrics import r2_score as r2
from tensorflow.core.util import event_pb2
def csr_to_spars... |
<filename>2D/train_2D_rt_v2.py<gh_stars>0
import numpy as np
import matplotlib.pyplot as plt
from scipy.fft import irfft2
import scipy
from scipy import integrate, stats
from numpy import linalg
import time
from scipy.special import gammaln
from itertools import repeat
import numdifftools
import torch
import multipro... |
<filename>tools/analysis/data.py
# read snapshot and obtain multiple systems
import collections
from scipy import spatial as sp
from .base import *
from .bse import *
G_MSUN_PC_MYR=0.00449830997959438 # Msun, pc, myr
G_HENON=1 # Henon unit
HEADER_OFFSET=24 # header offset in bytes for snapshots with the BINARY format
... |
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