text string |
|---|
<gh_stars>1000+
from math import ceil
import pytest
from scipy.stats import norm, randint
import numpy as np
from sklearn.datasets import make_classification
from sklearn.dummy import DummyClassifier
from sklearn.experimental import enable_halving_search_cv # noqa
from sklearn.model_selection import StratifiedKFold
... |
<reponame>take2rohit/monk_v1<gh_stars>100-1000
import os
import sys
import numpy as np
import torch
from PIL import Image
from torch.autograd import Variable
from scipy.stats import logistic
from scipy.special import softmax |
import sys
import random
import array
import math
import registers as gd3
from PIL import Image, ImageFont, ImageDraw, ImageChops, ImageFilter
from eve import align4, EVE
import zlib
import numpy as np
from scipy.ndimage import gaussian_filter
import common
def gentext(s, h):
fn = "../../.fonts/IBMPlexSans-SemiBo... |
<gh_stars>0
#!/usr/bin/python
# -*- coding utf-8 -*-
#
# Parallelogramm - Klasse von agla
#
#
# This file is part of agla
#
#
# Copyright (c) 2019 <NAME> <EMAIL>
#
#
# Licensed under the Apache License, Ve... |
<gh_stars>0
import numpy as np
import numpy.polynomial.polynomial as npp
import pandas as pd
from scipy.stats import norm
from scipy.signal import butter, filtfilt
from numba import njit, prange, guvectorize, float64, float32, int64
def camera_waveforms(t_pulse, noise_offset, noise_std):
n_samples = 96
pulse_... |
<filename>jigs/prom/source/we.py
"""Very simple example using a pair of Lennard-Jones particles.
This script has several pieces to pay attention to:
- Importing the pieces from wepy to run a WExplore simulation.
- Definition of a distance metric for this system and process.
- Definition of the components used in th... |
<gh_stars>0
""" A fantastic python code to determine the quenched SFH parameters of galaxies using emcee (http://dan.iel.fm/emcee/current/). This file contains all the functions needed to determine the mean SFH parameters of a population.
N.B. The data files .ised_ASCII contain the extracted bc03 models and ha... |
<filename>ebcic/__init__.py
# %load ./ebcic/ebcic.py
# %%writefile ./ebcic/ebcic.py
# To be synchronized with ebcic.py copy either of the above magic functions
# depending on whether to overwrite or to load, and then run this cell.
"""Exact Binomial Confidence Interval Calculator
This module provides functions to calc... |
"""
The primary module for user-interaction with the :mod:`hmf` package.
The module contains a single class, `MassFunction`, which wraps almost all the
functionality of :mod:`hmf` in an easy-to-use way.
"""
import numpy as np
import copy
from scipy.optimize import minimize
from scipy.interpolate import InterpolatedUn... |
<reponame>SwellMai/Terminator-800
#!/usr/bin/env python
import os
import rospy
import rosbag
import message_filters
from sensor_msgs.msg import LaserScan
from nav_msgs.msg import Odometry
from geometry_msgs.msg import PoseStamped, Twist
import numpy as np
from tf.transformations import euler_from_quaternion
import math... |
import scipy.io
def save_to_ascii_file(data_list, out_filepath):
write_list = []
for data in data_list:
output_str = ""
for val in data:
output_str += str(val) + "\t"
output_str = output_str[:-1]
output_str += "\n"
write_list.append(output_str)
with ope... |
<filename>ndmg/preproc/preproc_func.py<gh_stars>0
#!/usr/bin/env python
# Copyright 2016 NeuroData (http://neurodata.io)
#
# 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.ap... |
<gh_stars>10-100
# Copyright 2020 MIT Probabilistic Computing Project.
# See LICENSE.txt
import pytest
from sympy import exp as SymExp
from sympy import log as SymLog
from sympy import symbols
from sppl.sets import FiniteReal
from sppl.sym_util import get_symbols
from sppl.sym_util import partition_finite_real_conti... |
import sys
sys.path.insert(1, '../src/MyAIGuide/utilities')
import pickle
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from scipy import stats
from sklearn.preprocessing import MinMaxScaler
from dataFrameUtilities import check_if_zero_then_adjust_var_and_place_in_data, insert_data_to_tracker_m... |
# Standard library
from __future__ import division
import re
import os
from io import StringIO
from math import exp
from collections import namedtuple
import timeit
import json
import itertools
# Conda packages
import pandas
import scipy.spatial.distance
import numpy as np
import matplotlib.pyplot as plt
# From https... |
<gh_stars>0
import numpy as np
from utils import cost_function_logistic_regression_J , sigmoid_binari
from scipy import optimize
def train():
X1 = np.array([1 , 0 , 0 , 1])
X2 = np.array([1 , 0 , 1 , 0])
m = X1.size # should be same as the X2,y
x0= np.ones(m)
Y = np.array([1 , 0 , 0 , 0]) # logi... |
import csv
import numpy as np
import scipy
from sklearn import linear_model
from datetime import datetime
from dateutil.parser import parse
import matplotlib.pyplot as plt
from helperFunctions import printRSquared
from helperFunctions import predictNext
from helperFunctions import plotLearningCurve
from sklearn.model_s... |
# MIT License
#
# Copyright (c) 2020 <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, pu... |
# -*- coding: utf-8 -*-
"""
Created on Sun May 09 22:35:21 2010
Author: josef-pktd
License: BSD
todo:
change moment calculation, (currently uses default _ppf method - I think)
>>> lognormalg.moment(4)
Warning: The algorithm does not converge. Roundoff error is detected
in the extrapolation table. It is assumed t... |
<gh_stars>1-10
import argparse
import numpy as np
from scipy.special import logsumexp
import scipy
class Scorer (object):
def __init__ (self, word, early_input, early_output, later_input, later_output, ind):
self.word = word
sim_early = np.dot (early_output, early_input[ind])
sim_later = np.dot (later_output, l... |
<gh_stars>10-100
from __future__ import division
import scipy as sp
import numpy as np
from statsmodels import api as sm
import time
import sys
from DSTK.GAM.utils.p_splines import _get_percentiles, _get_basis_vector, R
from DSTK.utils.function_helpers import sigmoid
from DSTK.GAM.gam import ShapeFunction
from DSTK.GAM... |
# -*- coding: utf-8 -*-
#
# Copyright 2018-2020 Data61, CSIRO
#
# 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 applicabl... |
'''
Created on Oct 31, 2017
@author: udit.gupta
'''
import numpy as np
import matplotlib.pyplot as plt
import scipy
from scipy import misc
from lr_utils import load_dataset
# Loading the data (cat/non-cat)
train_set_x_orig, train_set_y, test_set_x_orig, test_set_y, classes = load_dataset()
# Example of a picture fro... |
<reponame>ahmedabdelazzim/pyABS<filename>PyABS.py
"""PyABS, light version of aspects of proprietary code."""
import pandas as pd
from pandas.compat import lmap
import numpy as np
from statsmodels.tsa.arima_model import ARMA
from scipy.linalg import cholesky
import matplotlib.pyplot as plt
from tqdm import tqdm
def au... |
# libraries
# simple graphical elements
import matplotlib.pyplot as plt
# numerical calulations
import numpy as np
# symbolic calculations
import sympy as sp
from sympy.abc import * # skip declaring symbols, eats up namespace though
#!pip install magpylib
# SMT solver
#!pip install z3-solver
import z3
# packaged ... |
<filename>courses/nik/niklib/w2v_model.py
import numpy as np
from tqdm import tqdm
import _pickle as pickle
from scipy.spatial.distance import cosine
from sklearn.neighbors import NearestNeighbors
class Word2VecModel:
# word index must start from 1
# word with idx=0 is empty word, which always has zero embeddi... |
<gh_stars>0
# <Copyright 2019, Argo AI, LLC. Released under the MIT license.>
"""Utility functions for converting quaternions to 3d rotation matrices.
Unit quaternions are a way to compactly represent 3D rotations
while avoiding singularities or discontinuities (e.g. gimbal lock).
If a quaternion is not normalized be... |
"""
Utility functions and constants for probabilistic dust models.
"""
import numpy as np
import scipy.integrate as integrate
import scipy.optimize as optimize
import scipy.special as special
import scipy.stats as stats
import model_list
import models
from utils import B_nu, G_nu
from fitting import noise_model
# Ph... |
<filename>project/utils/helpful_files/apply_affine.py
import numpy as np
import nibabel
from monai.transforms import LoadNifti
from scipy.ndimage import affine_transform
import matplotlib.pyplot as plt
import nibabel as nib
import numpy.linalg as npl
from nibabel.freesurfer.mghformat import MGHImage
np.set_printoptio... |
import numpy as np
from scipy.spatial.transform import Rotation as R
from radiosim.utils import get_exp
from radiosim.gauss import gauss
def create_jet(image, num_comps):
if len(image.shape) == 3:
image = image[None]
jets = []
jet_comps = []
source_lists = []
for img in image:
img... |
<reponame>valebru/HyperLogLog_s<gh_stars>1-10
#!/usr/bin/env python2.7
from multiprocessing import Process
import numbers
from operator import itemgetter
import math
import xxhash_cffi as xxhash
import socket
import numpy as np
import sys
import numpy
from scipy import stats
import dpkt
import time
import argparse
fr... |
import time
import scipy.io
from scipy.spatial.distance import pdist
from skimage.color import lab2rgb, rgb2lab
from mpl_toolkits.mplot3d import Axes3D
from tqdm import tqdm
from helpers import *
iterations = 0
def plot_data(data_by_types):
""" Show a scatter plot of the data by type, the first dimension group... |
<gh_stars>0
#!/usr/bin/env python
import dfl.dynamic_system
import dfl.dynamic_model as dm
import numpy as np
import matplotlib.pyplot as plt
from scipy import signal
plt.rcParams["font.family"] = "Times New Roman"
plt.rcParams["font.size"] = 30
plt.rcParams['pdf.fonttype'] = 42
plt.rcParams['ps.fonttype'] = 42
def... |
from __future__ import annotations
from collections.abc import Iterable
from pathlib import Path
import numpy as np
from lmfit import Parameters as ParametersLF
from scipy import stats
from chemex.containers.experiments import Experiments
from chemex.messages import print_chi2
from chemex.messages import print_group... |
<reponame>infmagic2047/arithgen
"""Quiz mode of arithgen.
Usage:
arithgen-quiz [options]
arithgen-quiz --help
arithgen-quiz --version
Options:
-d, --difficulty=<difficulty> Specify the complexity of
expressions. [default: 3]
-F, --format=<format> Specif... |
import numpy as np
from scipy import stats
from statsmodels.regression.linear_model import OLS
from statsmodels.tools.tools import add_constant
from . import utils
__all__ = ['qqplot']
def qqplot(data, dist=stats.norm, distargs=(), a=0, loc=0, scale=1, fit=False,
line=False, ax=None):
"""
q... |
<reponame>Ennosigaeon/scipy
#
# Tests for the lambertw function,
# Adapted from the MPMath tests [1] by <NAME>, <EMAIL>
# Distributed under the same license as SciPy itself.
#
# [1] mpmath source code, Subversion revision 992
# http://code.google.com/p/mpmath/source/browse/trunk/mpmath/tests/test_functions2.py?spec... |
"""
LIMBO Clustering Algorithm implementation
DOI: 10.1109/TSE.2005.25
Usage: limbo.py -h
"""
from scipy.sparse import *
import argparse
import copy
import pickle
import numpy as np
import sys
import bisect
import collections
import sade.helpers
np.warnings.filterwarnings('ignore')
def kl_div(p, q):
... |
#/usr/bin/env python
"""
Example of Most Descriptive compound selection.
Code Source: <NAME>
License: BSD 3 clausole
"""
import os
import sys
path = os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))
if not path in sys.path:
sys.path.insert(1, path)
del path
import numpy as np
import matplotlib.py... |
from typing import List, overload
import numpy as np
import pandas as pd
def clip_hotspots(img: np.ndarray):
"""
Performs hotspot removal on an ion image to match the METASPACE website's ion image rendering
"""
min_visible = np.max(img) / 256
if min_visible > 0:
hotspot_threshold = np.qua... |
#!/usr/bin/env python3
#
# Copyright (c) 2019 Seoul National University
#
# 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... |
<gh_stars>0
#!/usr/bin/env python
import PID
import time
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import spline
#P=2.0, I=0.0, D=1.0, Derivator=0, Integrator=0, Integrator_max=100, Integrator_min=-100, reference=0.0
def PID_test(P=2.0, I=0.0, D=1.0, reference=0.0):
pidx = PID.PID(... |
<gh_stars>10-100
# Copyright 2019, 2020 DeepMind Technologies Limited, <NAME>
#
# 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
#
# Unl... |
<gh_stars>0
import numpy as np
import scipy.sparse as sp
import torch
def encode_onehot(labels):
classes = set(labels)
classes_dict = {c: np.identity(len(classes))[i, :] for i, c in
enumerate(classes)}
labels_onehot = np.array(list(map(classes_dict.get, labels)),
... |
<gh_stars>1-10
import numpy as np
from scipy.special import sph_harm
def get_box_geometry(vectors):
"""expects box vectors in rows of 'vectors'"""
# get box lengths, angles, and volume
lengths = np.linalg.norm(vectors, axis=1)
angles = np.empty(3)
angles[0] = np.arccos(
vectors[1,:].do... |
<gh_stars>0
# from insitro_core.utils.storage import makedirs
import os
import time
from os.path import basename, join
import numpy as np
import pandas as pd
import scipy.sparse as ssp
from insitro_core.utils.cloud.bucket_utils import check_exists, download_file
def get_hic_file(chromosome, hic_dir, allow_vc=True, ... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 13 10:38:35 2020
@author: <NAME> (<EMAIL>)
Additional functions for manuscript "Rapid processing and quantitative evaluation of multicontrast EPImix scans for adaptive multimodal imaging"
"""
# Additional functions to run EPImix comparison script... |
import numpy as np
import scipy.constants as sc
class SED(object):
def __init__(self,*args,filename=None):
self._lamb=[]
self._flam=[]
if filename is not None:
self.load_from_file(filename)
if len(args)==2:
self.load_from_data(*args)
... |
import skimage.measure
import scipy.ndimage
import numpy as np
import networkx as nx
from skimage.morphology import skeletonize
from numba import njit
def _build_neighborhood(kernel, n):
a = np.empty((3, 3), dtype=np.bool)
for i in range(3):
for j in range(3):
a[i, j] = 1 if (n & kernel[i, j] != 0) else 0
re... |
# -*- coding: utf-8 -*-
"""
Sections:
- import libraries and define functions
- loading all the data in a specific main folder into mainDataList
- load data corresponding to a specific experiment (subfolder or video) into variables
- load variables from postprocessed file corresponding to the specific experiment above
... |
<gh_stars>1-10
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Jan 21 19:05:06 2021
@author: saitel
"""
from periodic.no_contact_tracing import NoCT
from periodic.backward_tracing.recursive_bct import RecursiveBCT
from parameters.parameters import TestParameters1, TestParameters2
import numpy as np
f... |
<filename>enterprise_extensions/frequentist/chi_squared.py
# -*- coding: utf-8 -*-
import numpy as np
import scipy.linalg as sl
def get_chi2(pta, xs):
"""Compute generalize chisq for pta:
chisq = y^T (N + F phi F^T)^-1 y
= y^T N^-1 y - y^T N^-1 F (F^T N^-1 F + phi^-1)^-1 F^T N^-1 y
"""
... |
<reponame>knector01/pvc
import sys
import numpy as np
import scipy.signal
import matplotlib.pyplot as plt
import soundfile
import pvc
# TODO: This doesn't work correctly, and grabs small peaks rather than the larger-scale formants
if __name__ == "__main__":
block_size = 4096
n_blocks = 4
vol_thresh = 0.... |
import statistics as np
N = int(input())
A = list(map(int, input().split()[:N]))
A.sort()
Q2 = np.median(A)
if N % 2 == 0 :
A1 = A[:int((N/2))]
A2 = A[int((N/2)):N]
else :
m = (N//2)
A1 = A[:m]
A2 = A[(m+1):N]
Q1 = np.median(A1)
Q3 = np.median(A2)
print(int(Q1))
print(int(Q2))
print(int(Q3))
|
<gh_stars>1000+
from sympy import Integer
from sympy.core import Symbol
from sympy.utilities import public
@public
def approximants(l, X=Symbol('x'), simplify=False):
"""
Return a generator for consecutive Pade approximants for a series.
It can also be used for computing the rational generating function of... |
<filename>demo_wavelet.py
import numpy as np
from scipy import sparse
import sys
import random as rd
import matplotlib.pyplot as plt
from PIL import Image
import waveletDec as wd
import IAFNNESTA
import IAFNNesterov
def help():
return '''
Here we compare the tv reconstruction with the L1 reconstruction in the wave... |
<gh_stars>10-100
import argparse
import numpy as np
import os
import pickle
from scipy.io import loadmat
parser = argparse.ArgumentParser()
parser.add_argument('--data-dir', required=True, type=str, default=None)
args = parser.parse_args()
assert (args.data_dir is not None) and (os.path.isdir(args.data_dir))
def lo... |
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec
from matplotlib.collections import LineCollection
from matplotlib.gridspec import GridSpec
import matplotlib.gridspec as gridspec
import scipy.signal as signal
import os
plt.rcParams['figure.figsize'] = (12, 9)
plt.rcParam... |
from sympy import *
from . import commonFuncs as cf
from sympy.abc import p, q, x
from . import numericFuncs as nf
# basic components of a region
class RegionBase:
# (pl, pu, ql, qu) tuple representation,
# sgn: remove or add;
# eta: a gate function to control the support
# a, b: the eta function bound... |
import scipy.io as sio
import numpy as np
import os
import mne
import gigadata
import matplotlib.pyplot as plt
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.model_selection import ShuffleSplit, cross_val_score
from pyriemann.estimation import Covariances
from mne import Epochs, p... |
import os
from scipy.spatial.transform import Rotation as R
import numpy as np
import torch
import json
import cv2
import time
import imageio
#Helper functions
vec_to_rot_matrix = lambda x: R.as_matrix(R.from_rotvec(x))
rot_matrix_to_vec = lambda y: R.as_rotvec(R.from_matrix(y))
rot_x = lambda phi: torch.tensor([
... |
from __future__ import division
from numpy.testing import (TestCase, assert_equal, assert_array_equal,
assert_almost_equal, assert_array_almost_equal,
assert_allclose, assert_, assert_raises)
import numpy as np
from decimal import Decimal
from macroeco.models impo... |
<gh_stars>1-10
### generate plots of luciferase data:
### Import dependencies
import matplotlib
matplotlib.use('Agg') ### set backend
import matplotlib.pyplot as plt
plt.rcParams['pdf.fonttype'] = 42 # this keeps most text as actual text in PDFs, not outlines
plt.tight_layout()
import sys
import math
import matplot... |
#!/usr/bin/env python3
# importing functions
import pandas as pd
import numpy as np
import cv2
import sklearn
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from random import randint
import csv
from scipy import ndimage
from sklearn.utils import shuffle
# importing data
samples = []
with open('da... |
# Code written by: <NAME> (<EMAIL>)
# <NAME> (<EMAIL>)
"""
This class is a collection of functions for showing data with pymol.
Note that the limit of pymol is 100k monomers, therefore interpolateData is
useful to collapse the 200k-long simulation into a 100k-long conformation.
"""
import os
import te... |
<filename>pymatgen/core/lattice.py
# coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
"""
Defines the classes relating to 3D lattices.
"""
import math
import itertools
import warnings
from functools import reduce
import collections
from fractions import Fract... |
from unittest import TestCase, main
from sympy import sympify, symbols
from numpy import array, allclose
from tridiagonal import solve_diffeq
class TridiagonalTestCase(TestCase):
def setUp(self):
"""initial set up"""
def test_model_solution(self):
"""Verify the resulting approximation is corr... |
<gh_stars>1-10
"""
Test reload for trained models.
"""
import os
import pytest
import unittest
import tempfile
import numpy as np
import deepchem as dc
import tensorflow as tf
import scipy
from flaky import flaky
from sklearn.ensemble import RandomForestClassifier
from deepchem.molnet.load_function.chembl25_datasets im... |
import json
import os
import neurofinder
import pandas as pd
from scipy.io import savemat
def calc_stats(file_name, caiman, cidan, suite2p, true):
rows = []
caimain_file = [os.path.join(caiman, x) for x in os.listdir(caiman) if
file_name in x and "json" in x][0]
cidan_file = [os.path.... |
'''
Contains a generic algorithm object which can do vanilla ICP
Then, create plugin functions which can do naive, simple, and fast PFH
'''
import time
import numpy as np
import matplotlib.pyplot as plt
import scipy.special as sp
from sklearn.metrics.pairwise import euclidean_distances
from . import utils
class PFH... |
<filename>tools/capture_dataset.py
"""
Script to capture a set of test images.
Be sure to register beforehand!!!
Author: <NAME>
"""
import argparse
import copy
import IPython
import logging
import numpy as np
import os
import pcl
import rosgraph.roslogging as rl
import rospy
import scipy.stats as ss
import sys
import t... |
import numpy as np
import dynesty
from scipy.special import erf
from utils import get_rstate, get_printing
nlive = 100
printing = get_printing()
win = 100
def loglike(x):
return -0.5 * x[1]**2
def prior_transform(x):
return (2 * x - 1) * win
def test_periodic():
# hard test of dynamic sampler with hi... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import numpy as np
from matplotlib import pyplot as plt; plt.ion()
from scipy.signal import lfilter
from itertools import chain
def getSpikes(t, v, setdvdt, output=False, plotRaster=True, newfigure=True):
'''
Expected matrices shapes:
t: [length] or [length... |
<reponame>garbagetrash/orbital<gh_stars>10-100
import unittest
from scipy.constants import kilo, mega, pi
from numpy import radians
from orbital import earth, KeplerianElements
from orbital.maneuver import *
class TestOperation(unittest.TestCase):
def setUp(self):
self.LEO = KeplerianElements... |
<reponame>akutta/hercules
#!/usr/bin/env python3
import argparse
from datetime import datetime, timedelta
from importlib import import_module
import io
import json
import os
import re
import shutil
import sys
import tempfile
import threading
import time
import warnings
try:
from clint.textui import progress
except... |
import itertools,subprocess
import numpy as np
import taskA_scorer
from scipy.special import softmax
def all_subsets(ss):
return itertools.chain(*map(lambda x: itertools.combinations(ss, x), range(0, len(ss)+1)))
#all_models=["models_bert/albert_4a_new_dev_nonaug/checkpoint-300/", "models_bert/albert_4a_new_d... |
from scipy.stats import loguniform, uniform
import numpy as np
from dask import compute
from gillespy2 import Model, Species, Reaction, Parameter, RateRule, AssignmentRule, FunctionDefinition
from gillespy2 import VariableSSACSolver
def minmax_normalize(data, min_=None, max_=None):
data_ = np.copy(data)
if mi... |
# import pyaudio
from scipy.io.wavfile import read, write
import scipy.signal as sig
import numpy as np
import scipy.interpolate as interp
import sys
import os.path
from os import path
def resample(file, target_rate):
if file['rate'] != target_rate:
return {'waveform':sig.resample(file['waveform'], target_... |
from learners.learner import Learner
import numpy as np
from sklearn.gaussian_process import GaussianProcessRegressor
from sklearn.gaussian_process.kernels import RBF, ConstantKernel as C
from sklearn.preprocessing import StandardScaler
from scipy.stats import norm
class GPTS(Learner):
LEARNER_NAME = "GPTS-Scale... |
################################################################################
# (c) [2013] The Johns Hopkins University / Applied Physics Laboratory All Rights Reserved.
# Contact the JHU/APL Office of Technology Transfer for any additional rights. www.jhuapl.edu/ott
#
# Licensed under the Apache License, Version ... |
import os
import time
import logging
import matplotlib.pyplot as plt
import numpy as np
import pdb
from scipy import optimize as opt
from stompy.spatial import field
from stompy import utils
from stompy.grid import (unstructured_grid, exact_delaunay, front)
import logging
logging.basicConfig(level=logging.INFO)
fr... |
<reponame>xxdreck/google-research
# coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# 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... |
import numpy as np
from scipy.interpolate import PchipInterpolator as Pchip
from refnx.reflect import Structure, Component
from refnx.analysis import Parameter, Parameters, possibly_create_parameter
EPS = np.finfo(float).eps
class Spline(Component):
"""
Freeform modelling of the real part of an SLD profil... |
from sympy import *
from common1 import plot_latex, plot_equation
x, y = symbols('x y')
eq = Eq(x**2 + y**2, 9)
plot_equation(eq)
|
import pandas as pd
import numpy as np
import plotly.express as px
import yaml
from scipy.integrate import odeint
from tqdm import tqdm
import sys
sys.path.insert(0,'.')
# from seir import entrypoint
from seir import entrypoint
def iterate_simulation(current_state, seir_parameters, phase, initial):
"""
Iterate... |
<filename>MMR_IVs/rkhs_model_LMO_nystr_mendelian.py
import add_path,os
import autograd.numpy as np
from autograd import value_and_grad
from scipy.optimize import minimize
from util import get_median_inter_mnist, Kernel, load_data, ROOT_PATH,jitchol,_sqdist, remove_outliers,nystrom_decomp, chol_inv
import time
Nfeval ... |
<gh_stars>0
from scipy.special import gammaln
from scipy.stats import binom
import numpy, random
import pdb
def tool_hypergeomPMF(k, M, n, N):
tot, good = M, n
bad = tot - good
return numpy.exp(gammaln(good+1) - gammaln(good-k+1) - gammaln(k+1) + gammaln(bad+1) \
- gammaln(bad... |
<filename>ML_functions.py
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 28 2020
@author: <NAME>
"""
import numpy as np
import joblib
import pickle
from scipy import linalg
from scipy import sparse
import pyfftw
def create_HP_filt(flength,cutoff,TR):
cut=cutoff/TR
sigN2=(cut/np.sqrt(2)... |
<gh_stars>0
import pandas as pd
from sympy import Symbol, diff, factorial
from sympy.core.add import Add
from sympy.core.mul import Mul
from typing import Union
def n_diff(f: Union[Add, Mul], variable: Symbol, n: int):
for _ in range(n):
f = f.diff(variable)
return f
def taylor(f: Union[Add, Mul], variable: Sym... |
'''
swing up pendulum with limited torque
'''
import sympy as sp
import numpy as np
from ilqr import iLQR
from ilqr.utils import GetSyms, Constrain
from ilqr.containers import Dynamics, Cost
#state and action dimensions
n_x = 3
n_u = 1
#time step
dt = 0.025
#Construct pendulum dynamics
m, g, l = 1, 10, 1
def f(x, u... |
#!/usr/bin/env python
import argparse
import gzip
import os
import cPickle as pickle
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.backends.backend_pdf import PdfPages
from scipy import signal
import fileio
def process_image(pickle_file, image, output_file):
with gzip.open(pickle_file, mode... |
<filename>cat_tools.py
from astropy import units as u
from astropy.io import ascii
from astroquery.vizier import Vizier
from astropy import table
from astropy import coordinates as coord
from astropy import units as u
from misc import bcolors
import numpy as np
import os
from scipy.spatial import... |
import json
from nltk import word_tokenize
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
import os
import re
import math
from scipy import sparse
import numpy as np
from scipy import spatial
import time
ORIGINAL_ARTICLE_PATH = '../dataset/US_Financial_News_Articles/'
EDITED_TEXT_PATH = '... |
<reponame>puiseux/spleen<gh_stars>0
#!/usr/local/bin/python2.7
#-*-coding: utf-8 -*-
'''
Axile -- Outil de conception/simulation de parapentes Nervures
Classe NSpline
Description :
@author: puiseux
@copyright: 2016-2017-2018 Nervures. All rights reserved.
@contact: <EMAIL>
__updated__="2019-05-06"
'''
import ... |
import os
import sys
"""
Test 72 transform tf1 model on hits
"""
PROJECT_PATH = os.path.abspath(
os.path.join(os.path.dirname(__file__), '..'))
sys.path.append(PROJECT_PATH)
from modules import utils
import time
import transformations
import numpy as np
from models.wide_residual_network import create_wide_residua... |
<gh_stars>0
# -*- coding: utf-8 -*-
"""
Created on Wed Aug 31 13:04:09 2016
@author: diepencjv
"""
#%%
import numpy as np
import scipy.signal
import logging
import warnings
import qcodes
from qcodes import Instrument
from qcodes.plots.pyqtgraph import QtPlot
from qcodes import DataArray
import qtt
import qtt.utiliti... |
import os
import numpy as np
from scipy.io import wavfile as wf
'''
Read pitchmark file
Get 25 msec window around it ( if possible)
Read ccoeffs file and get the ccoeffs.
Read the wavefile and get corresponding wave.
Quantize the wave and store <ccoeffs,wav> in numpy array.
'''
def mulaw(x, mu=256):
return _sign(... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 16 16:18:45 2019
@author: matteo
"""
from potion.simulation.trajectory_generators import generate_batch
from potion.common.misc_utils import performance, avg_horizon
from potion.estimation.gradients import gpomdp_estimator
from potion.estimation.met... |
import numpy as np
import scipy.sparse as sp
from scipy.sparse.linalg import splu
from pySDC.core.Errors import ParameterError, ProblemError
from pySDC.core.Problem import ptype
from pySDC.implementations.datatype_classes.mesh import mesh
# noinspection PyUnusedLocal
class advection1d(ptype):
"""
Example imp... |
<gh_stars>0
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
import numpy as np
import scipy.io
######################################## FUNCTIONS
# Data loading.
def loadData(dataPath, isTrain=True):
Data = scipy.io.loadmat(dataPath)
proj_m = Data['Proj_M... |
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