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/-
Copyright (c) 2019 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Bhavik Mehta
! This file was ported from Lean 3 source module category_theory.limits.shapes.terminal
! leanprover-community/mathlib commit f47581155c818e6361af4e4fda60... | {"author": "leanprover-community", "repo": "mathlib3port", "sha": "62505aa236c58c8559783b16d33e30df3daa54f4", "save_path": "github-repos/lean/leanprover-community-mathlib3port", "path": "github-repos/lean/leanprover-community-mathlib3port/mathlib3port-62505aa236c58c8559783b16d33e30df3daa54f4/Mathbin/CategoryTheory/Limi... |
SUBROUTINE QGAUS(FUNC,A,B,SS)
DIMENSION X(5),W(5)
DATA X/.1488743389,.4333953941,.6794095682,.8650633666,.9739065285
*/
DATA W/.2955242247,.2692667193,.2190863625,.1494513491,.0666713443
*/
XM=0.5*(B+A)
XR=0.5*(B-A)
SS=0
DO 11 J=1,5
DX=XR*X(J)
SS... | {"hexsha": "6dd325cbf9b4187b672a614da5ce1f0bd8fb96d7", "size": 408, "ext": "for", "lang": "FORTRAN", "max_stars_repo_path": "Math3/NumRec/source/qgaus.for", "max_stars_repo_name": "domijin/MM3", "max_stars_repo_head_hexsha": "cf696d0cf26ea8e8e24c86287cf8856cab7eaf77", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
import numpy as np
import cv2
import os
video = cv2.VideoCapture(0)
ORANGE = False
DARK = False
while True:
_, original = video.read()
gray = cv2.cvtColor(original, cv2.COLOR_BGR2GRAY)
h, w, c = original.shape
laplacian = cv2.Laplacian(original, cv2.CV_64F)
sobelx = cv2.Sobel(original, cv2.CV_64... | {"hexsha": "a729176274351437c1761ff800d50feea5fe5de8", "size": 708, "ext": "py", "lang": "Python", "max_stars_repo_path": "modules/open_cv/edge_and_gradients.py", "max_stars_repo_name": "GrzegorzKrug/face_morph", "max_stars_repo_head_hexsha": "64e5e47207d30ac8968a0b1b73e11a8ae74b3fec", "max_stars_repo_licenses": ["Apac... |
"""
AbstractZero <: AbstractDifferential
This is zero-like differential types.
If a AD system encounter a propagator taking as input only subtypes of `AbstractZero` then
it can stop performing any AD operations, as all propagator are linear functions, and thus
the final result will be zero.
All `AbstractZero` sub... | {"hexsha": "75bd7472701c199a41415772f34ed58ac8ec636a", "size": 2490, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/differentials/abstract_zero.jl", "max_stars_repo_name": "piever/ChainRulesCore.jl", "max_stars_repo_head_hexsha": "b90ee242228d9cda7c0a90deab816621da93cfaf", "max_stars_repo_licenses": ["MIT"],... |
module mod_monolis_shape_util
use mod_monolis_prm
contains
subroutine monolis_get_inverse_matrix_2d(xj, inv, det, is_fail)
implicit none
real(kdouble) :: xj(2,2), inv(2,2), det, detinv
logical, optional :: is_fail
det = xj(1,1) * xj(2,2) &
- xj(2,1) * xj(1,2)
if(det < 0.0d0)then
... | {"hexsha": "38f9782ab5c08416714dbb84aff8cd91dee971f9", "size": 1888, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/shape/shape_util.f90", "max_stars_repo_name": "nqomorita/monolis", "max_stars_repo_head_hexsha": "55d746a480fd7b9639216be19e0a253e6137dfe9", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import pandas as pd
import numpy as np
from scipy import optimize
import re
import copy
from datetime import timedelta
from collections import defaultdict
import logging
from .pool import Uniswapv3Pool
from uniswapv3_simulator.tick import MIN_TICK, MAX_TICK
from .math import *
logger = logging.getLogger('uniswap-v3.u... | {"hexsha": "37669f1aca62cca78cfdc6e86ddddc92e0f1e16a", "size": 24085, "ext": "py", "lang": "Python", "max_stars_repo_path": "uniswapv3_simulator/utils.py", "max_stars_repo_name": "pradeeptadas/uniswap-v3-project", "max_stars_repo_head_hexsha": "8f938dc5602fdb6e58b2cf42393a01994f48682d", "max_stars_repo_licenses": ["MIT... |
# ---------------------------------------------------------------------------------------------------------------------
# system
import sys
from math import sqrt
# ---------------------------------------------------------------------------------------------------------------------
# scientific
import numpy as np
# ----... | {"hexsha": "f36d0cffb2f07d82043a476029519f507c2fab53", "size": 3844, "ext": "py", "lang": "Python", "max_stars_repo_path": "prepare_sink.py", "max_stars_repo_name": "alexfmsu/pyquantum", "max_stars_repo_head_hexsha": "78b09987cbfecf549e67b919bb5cb2046b21ad44", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
from scipy import interpolate as interp
from typing import Union, Callable
import multiprocessing as mp
import numpy as np
import pyslm
class parallelprocess(mp.Process):
def __init__(self, inData, isPlayed, params):
# Inheriting the class multiprocessing.Process()
mp.Process.__init__(self)
... | {"hexsha": "680576a78a89a3028799e4c1cb5054d7eaac2691", "size": 41665, "ext": "py", "lang": "Python", "max_stars_repo_path": "pyslm/processing.py", "max_stars_repo_name": "leonardojacomussi/PySLM", "max_stars_repo_head_hexsha": "94283afa022cd113129b4f42f1745e22ad3730f9", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import numpy as np
import random
from torch.utils import data as data
import os.path as osp
from basicsr.utils import FileClient, imfrombytes, img2tensor
from basicsr.utils.registry import DATASET_REGISTRY
import os
import torch
import cv2
@DATASET_REGISTRY.register()
class SlidingWindowDataset(data.Dataset):
def ... | {"hexsha": "5cf80e5f1dedd44e3acdf23dfe50a1dbe560ea32", "size": 2107, "ext": "py", "lang": "Python", "max_stars_repo_path": "basicsr/data/sliding_window_dataset.py", "max_stars_repo_name": "ACALJJ32/BasicSR_ACALJJ32", "max_stars_repo_head_hexsha": "81235ad78102e194f7442ff600ff2dfd9992f857", "max_stars_repo_licenses": ["... |
#!/usr/bin/env python
"""
https://en.wikipedia.org/wiki/Trapezoidal_rule
Integral ( f(x) ) dx ~ (b - a) 0.5(f(a) + f(b))
a->b
https://numpy.org/doc/stable/reference/generated/numpy.trapz.html
"""
import numpy as np
import matplotlib.pyplot as plt
if __name__ == '__main__':
x = np.arange(10, dtype=n... | {"hexsha": "a2ade0b8b3a3aa5408fec86e3fcc47b6fb081d90", "size": 652, "ext": "py", "lang": "Python", "max_stars_repo_path": "ana/trapz.py", "max_stars_repo_name": "hanswenzel/opticks", "max_stars_repo_head_hexsha": "b75b5929b6cf36a5eedeffb3031af2920f75f9f0", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 1... |
import cv2
import numpy as np
import os
def empty(x):
pass
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars",600,300)
cv2.createTrackbar("Hue Min","TrackBars", 0, 179, empty)
cv2.createTrackbar("Hue Max","TrackBars", 179, 179, empty)
cv2.createTrackbar("Sat Min","TrackBars", 0, 255, empty)
cv2.createTrac... | {"hexsha": "beaeea3bede99775bba34af53137c585c7c9dcb3", "size": 1763, "ext": "py", "lang": "Python", "max_stars_repo_path": "opencv/findgoal.py", "max_stars_repo_name": "ftc8569/2020-ftc-vision", "max_stars_repo_head_hexsha": "ecf6bacb840059351a0734a037e9bca5dbaf3b7d", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
/-
Copyright (c) 2018 Scott Morrison. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Scott Morrison, Markus Himmel, Bhavik Mehta, Andrew Yang
-/
import category_theory.limits.shapes.wide_pullbacks
import category_theory.limits.shapes.binary_products
/-!
# Pullbacks
>... | {"author": "leanprover-community", "repo": "mathlib", "sha": "5e526d18cea33550268dcbbddcb822d5cde40654", "save_path": "github-repos/lean/leanprover-community-mathlib", "path": "github-repos/lean/leanprover-community-mathlib/mathlib-5e526d18cea33550268dcbbddcb822d5cde40654/src/category_theory/limits/shapes/pullbacks.lea... |
#pragma once
#ifndef TRANSFORM_HPP
#define TRANSFORM_HPP
#include <stdio.h>
#include <armadillo>
class Transform
{
public:
Transform();
arma::dmat T(double tx, double ty, double tz);
arma::dmat S(double sx, double sy, double sz);
arma::dmat R(double ax, double ay, double az, double angle);
};
#endi... | {"hexsha": "0ddd0a494783ff37a400bb168b323c224a94166e", "size": 333, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "proyecto/Transform.hpp", "max_stars_repo_name": "Pedejeca135/GRAFICACION_UASLP", "max_stars_repo_head_hexsha": "51674129cc3a853450509acc7e8c579bb167da11", "max_stars_repo_licenses": ["MIT"], "max_sta... |
import json
import os
from random import choice
import jams
import librosa
import numpy as np
import scipy
from massage import SF_PATH, ACOUSTIC_SF_MFCC
def compute_avg_mfcc(fpath=None, y=None, sr=None):
""" Compute the average mfcc of a signal y
Parameters
----------
fpath : str default=None
... | {"hexsha": "1722e4f6b66fa2a8aabd8ef9322b933bc9ee30e4", "size": 11662, "ext": "py", "lang": "Python", "max_stars_repo_path": "massage/resynth/util.py", "max_stars_repo_name": "justinsalamon/massage", "max_stars_repo_head_hexsha": "b92888f3f8f14d2ad57aef7844e2cd03e6598b42", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
from __future__ import annotations # postpone evaluation of annotations
import logging
from typing import Any, Dict, List, Optional, Tuple
import cv2
import numpy as np
import numpy.typing as npt
from pyquaternion import Quaternion
from scipy import ndimage
from scipy.spatial.transform import Rotation as R
from sqla... | {"hexsha": "86ac9bfbee96df45102f38fd78fc1b01bd9b2d4d", "size": 19894, "ext": "py", "lang": "Python", "max_stars_repo_path": "nuplan/database/nuplan_db/ego_pose.py", "max_stars_repo_name": "motional/nuplan-devkit", "max_stars_repo_head_hexsha": "e39029e788b17f47f2fcadb774098ef8fbdd0d67", "max_stars_repo_licenses": ["Apa... |
[STATEMENT]
lemma used_appIR: "X \<in> used evs \<Longrightarrow> X \<in> used (evs @ evs')"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. X \<in> used evs \<Longrightarrow> X \<in> used (evs @ evs')
[PROOF STEP]
by (erule used_sub_app [THEN subsetD]) | {"llama_tokens": 105, "file": null, "length": 1} |
import matplotlib.pyplot as plt
import numpy as np
from scipy import fftpack
from scipy import signal
import math
def chromagram_stft(data, rate=1.0, winlen=2048, scale='sharp', winn='ret'):
'''
Calculates the chromagram of an audio sample.
Args:
data: array of... | {"hexsha": "f255ccebccfea944ca990cf6b631c783cfb47142", "size": 4369, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/chroma.py", "max_stars_repo_name": "rodrigocaus/chord_classifier", "max_stars_repo_head_hexsha": "2b9991d828bfa86685fdd971a3e7da5dfaba5699", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
#
# Copyright (c) 2021 Tobias Thummerer, Lars Mikelsons, Josef Kircher
# Licensed under the MIT license. See LICENSE file in the project root for details.
#
# What is included in the file `FMI2_comp_wraps.jl` (FMU component wrappers)?
# - wrappers to call fmi2ComponentFunctions from FMUs (FMI-functions, last in... | {"hexsha": "e563391382e28f86eaf1b6eb8ed0a9d102407bc3", "size": 13287, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/FMI2_comp_wraps.jl", "max_stars_repo_name": "adribrune/FMI.jl", "max_stars_repo_head_hexsha": "7fb390e56822fc7c99b2824bc4a3e59c61361d08", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
!
! AtmProfile_netCDF_IO
!
! Module containing routines to read and write AtmProfile netCDF
! format files.
!
!
! CREATION HISTORY:
! Written by: Paul van Delst, CIMSS/SSEC 08-Jul-2002
! paul.vandelst@noaa.gov
!
MODULE AtmProfile_netCDF_IO
! -----------------
! Environment setup
... | {"hexsha": "eb590bd4eff0add30ed9d26318583e9651e4db16", "size": 136195, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/TauRegress/ODAS/ODAS_Regress/TmpAtmProfile_netCDF_IO.f90", "max_stars_repo_name": "hsbadr/crtm", "max_stars_repo_head_hexsha": "bfeb9955637f361fc69fa0b7af0e8d92d40718b1", "max_stars_repo_l... |
"""
Support for example tables wrapping data stored on a PostgreSQL server.
"""
import functools
import logging
import threading
import warnings
from contextlib import contextmanager
from itertools import islice
from time import strftime
import numpy as np
from Orange.data import Table, Domain, Value, Instance, filter... | {"hexsha": "8dd48f406b84d8aa82f770b85a91233bc395bf81", "size": 24284, "ext": "py", "lang": "Python", "max_stars_repo_path": "orange3/Orange/data/sql/table.py", "max_stars_repo_name": "rgschmitz1/BioDepot-workflow-builder", "max_stars_repo_head_hexsha": "f74d904eeaf91ec52ec9b703d9fb38e9064e5a66", "max_stars_repo_license... |
SUBROUTINE GH_KGST ( iblk, iret )
C************************************************************************
C* GH_KGST *
C* *
C* This subroutine plots the U.S. two character state identifiers, *
C* tropical and Carribean country names. *
C* *
C* GH_KGST ( IBLK, IRET ) *
C* ... | {"hexsha": "492ee5dc7219e61cdcabd11a6120a587afabc851", "size": 4813, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "gempak/source/cgemlib/gh/ghkgst.f", "max_stars_repo_name": "oxelson/gempak", "max_stars_repo_head_hexsha": "e7c477814d7084c87d3313c94e192d13d8341fa1", "max_stars_repo_licenses": ["BSD-3-Clause"], ... |
"""
import_bibtex(file::String)
Import a BibTeX file and convert it to the internal bibliography format.
"""
function import_bibtex(file::String)
return BibParser.parse_file(file)
end
function int_to_spaces(n::Int)
str = ""
for i in 1:n
str *= " "
end
return str
end
# Dictionnary to ha... | {"hexsha": "4114b6e32bf25294fa3768e79c4bd751c939723b", "size": 3321, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/bibtex.jl", "max_stars_repo_name": "charleskawczynski/Bibliography.jl", "max_stars_repo_head_hexsha": "8d3f159387bc43df1ae899b68d3022de445bc5cc", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
import numpy as np
import pandas as pd
from build.chart_data_functions import get_cumulative_cases_chart_data
from build.chart_data_functions import get_cumulative_tests_chart_data
from build.chart_data_functions import get_hospital_data
from build.chart_data_functions import get_in_intensive_data
from build.chart_dat... | {"hexsha": "d96f1e62bdd82d919520c1c24355fa78fd881e5b", "size": 7831, "ext": "py", "lang": "Python", "max_stars_repo_path": "build/generate_stats_bar.py", "max_stars_repo_name": "jtagcat/koroonakaart", "max_stars_repo_head_hexsha": "16a6eb24a19b286589b063742b03a123315feefc", "max_stars_repo_licenses": ["CC0-1.0", "MIT"]... |
#encoding:utf-8
# -----------------------------------------------------------
# "Remote Sensing Cross-Modal Text-Image Retrieval Based on Global and Local Information"
# Yuan, Zhiqiang and Zhang, Wenkai and Changyuan Tian and Xuee, Rong and Zhengyuan Zhang and Wang, Hongqi and Fu, Kun and Sun, Xian
# Writen by YuanZhiq... | {"hexsha": "127740e7fd064366bbacb2b0187049c7d203b1af", "size": 14106, "ext": "py", "lang": "Python", "max_stars_repo_path": "utils.py", "max_stars_repo_name": "xiaoyuan1996/GaLR", "max_stars_repo_head_hexsha": "77075507482453f59bab3ae65fa99ba1b61d716c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 11, "max_st... |
from collections import deque
from multiprocessing import RawArray
from multiprocessing import Lock as mpLock
from multiprocessing import Process
from multiprocessing import Value
from ctypes import c_bool, c_ubyte, c_long
import time
import numpy as np
import cv2
from trtis_client import TrtisClient
def infer... | {"hexsha": "cdeb1e5fb20b277dcf65cfdbaa519b09a47834cd", "size": 5382, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/agent.py", "max_stars_repo_name": "lazykyama/atari_trtis_demo", "max_stars_repo_head_hexsha": "521615bdd00aa02836dae174be6dae63bdeb5eb8", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
## Derivadas ##
```python
from sympy import *
x,f=symbols("x f")
f=-2*x**3-4*x**2+13*x-1
init_printing()
diff(f,x)
```
```python
from sympy import *
x,f=symbols("x f")
f=-2*x**5+23*x**3-7*x
diff(f,x)
```
```python
x,g=symbols("x g")
g=2*x+ln(x)
diff(g, x)
```
```python
x,h=symbols("x h")
h=sin(x)
diff(h, x)
```... | {"hexsha": "e6e8b33b82a7c328be4fb865da2c19c0d5c504c5", "size": 148946, "ext": "ipynb", "lang": "Jupyter Notebook", "max_stars_repo_path": "Operations/Derivada e Integral.ipynb", "max_stars_repo_name": "Edu-Kobus/Exercise-in-python", "max_stars_repo_head_hexsha": "44321dcaa8bb6f8fd574b2bc603f93eafbf76ce1", "max_stars_re... |
import pandas as pd
import numpy as np
import gym
from gym import error, spaces, utils
from sklearn.preprocessing import StandardScaler
from mikasa import *
ACTION_LOOKUP = {
0: 'nop',
1: 'buy',
2: 'sell'
}
class MikasaEnv(gym.Env):
metadata = {'render.modes': ['human']}
def __init__(self, sour... | {"hexsha": "623970068dc8b5fc0a2fae887197a2eae0e77e6f", "size": 2575, "ext": "py", "lang": "Python", "max_stars_repo_path": "mikasa_gym/mikasa_env.py", "max_stars_repo_name": "alifanov/mikasa_gym", "max_stars_repo_head_hexsha": "7cf23ec6ca69d835edbea980fc7959ea977b6668", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import xgboost as xgb
import numpy as np
from sklearn.cross_validation import KFold, train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.grid_search import GridSearchCV
from sklearn.datasets import load_iris, load_digits, load_boston
import unittest
rng = np.random.RandomState(1337)
class Tes... | {"hexsha": "fec7a6a62a4b496e2b47148d0eb15fa06f5222bb", "size": 2058, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/external/xgboost/tests/python/test_training_continuation.py", "max_stars_repo_name": "shreyasvj25/turicreate", "max_stars_repo_head_hexsha": "32e84ca16aef8d04aff3d49ae9984bd49326bffd", "max_st... |
[STATEMENT]
lemma matchPres:
fixes P :: pi
and Q :: pi
and a :: name
and b :: name
assumes "P \<simeq>\<^sup>s Q"
shows "[a\<frown>b]P \<simeq>\<^sup>s [a\<frown>b]Q"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. [a\<frown>b]P \<simeq>\<^sup>s [a\<frown>b]Q
[PROOF STEP]
using assms
[PROOF STATE]... | {"llama_tokens": 242, "file": "Pi_Calculus_Weak_Early_Cong_Subst_Pres", "length": 2} |
using Documenter, RxNav
makedocs(sitename = "RxNav Module Documentation", format = Documenter.HTML(prettyurls = false))
| {"hexsha": "5ccc25aa6fc0b261183e21657079284ab1016ac0", "size": 124, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "docs/make.jl", "max_stars_repo_name": "wherrera10/RxNav.jl", "max_stars_repo_head_hexsha": "54874be9ecf09dd41983ef5a5dfe7de68f3e7a38", "max_stars_repo_licenses": ["BSD-2-Clause"], "max_stars_count":... |
\chapter{Software tester}
\input{missions/testgeneralites}
%\glspl{pois} \\
%\glspl{vache} \\
%\glspl{pigeon} \\
% \glspl{TEM} \\
% \gls{latex} \\
%\glspl{lvm}
\input{missions/testtravailrealise}
\input{missions/testsynthese}
\input{missions/testbilanpremiereperiode}
| {"hexsha": "d85a46e5c2a730c7afaa4a061c0a076c7f8f8bf1", "size": 275, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "missions/Software-tester.tex", "max_stars_repo_name": "syncrase/reportContrat", "max_stars_repo_head_hexsha": "b9243c54744ace9e360fa48065ea5886851919ec", "max_stars_repo_licenses": ["MIT"], "max_star... |
import numpy as np
import healpy as hp
from plancklens.qcinv.util import read_map
class template:
def __init__(self):
self.nmodes = 0
assert 0
def apply(self, m, coeffs):
# map -> map*[coeffs combination of templates]
assert 0
def apply_mode(self, m, mode):
assert... | {"hexsha": "1d34d3c221d93c9f60e97ccd1df573fc73aaf1f2", "size": 4202, "ext": "py", "lang": "Python", "max_stars_repo_path": "plancklens/qcinv/template_removal.py", "max_stars_repo_name": "louisl3grand/plancklens", "max_stars_repo_head_hexsha": "2a7d832e044da87f2833628816e0d74fe83743f7", "max_stars_repo_licenses": ["MIT"... |
"""
This file defines the datatypes of variables to be used globally.
"""
import torch
import numpy as np
from functools import partial
mat = np.atleast_2d
tensor = partial(torch.tensor, dtype=torch.float32)
device = torch.device('cpu')
| {"hexsha": "80c16a933ebd2265e275e5e8d67d7c504c89858b", "size": 241, "ext": "py", "lang": "Python", "max_stars_repo_path": "worlds/utils.py", "max_stars_repo_name": "forgi86/RNN-adaptation", "max_stars_repo_head_hexsha": "d32e8185c6a746060dd726a0f5080231e0c9439b", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1... |
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | {"hexsha": "be46d31aaf11383efcdcd6e2346affef8098aff1", "size": 3756, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/util.py", "max_stars_repo_name": "monika19950721/PaddleNLP", "max_stars_repo_head_hexsha": "d8931a5253dfc4f110daec73d96b0cc78d150042", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_c... |
#! /usr/bin/env python3
'''
Author : BCC
Date : 2022/03/31
'''
import argparse
import math
import sys
import re
import copy
import numpy as np
import gzip
import matplotlib.pyplot as plt
from matplotlib.pyplot import MultipleLocator #for setting of scale of separating along with x-axis & y-axis.
#... | {"hexsha": "e156a5eff779a92906956542fc81922a7d0e99d1", "size": 5491, "ext": "py", "lang": "Python", "max_stars_repo_path": "HW3/python/Q1/hw3.py", "max_stars_repo_name": "Coslate/Machine_Learning", "max_stars_repo_head_hexsha": "fd1e51cfdb02e1249819aa7d54a18b91fcd4225e", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
(t::Todo) -> begin
el(
id = t.id |> Base.get,
todo = t.title,
completed = t.completed
)
end
| {"hexsha": "00e56eeca40db091ffa00daca87838ee16f98f03", "size": 99, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "app/resources/todos/views/partials/item.json.jl", "max_stars_repo_name": "essenciary/genie-todo-mvc", "max_stars_repo_head_hexsha": "bc18a5c0ab61481050daabee34eb3949e75de837", "max_stars_repo_license... |
import numpy as np
import pandas as pd
import tornado
from tornado.websocket import websocket_connect
from tornado.httpclient import HTTPRequest
import json
import sys
def message(**kwargs):
return json.dumps(kwargs)
class FlightGearProperty(object):
""" Manages a property transmitted from FlightGear. """
... | {"hexsha": "785331c5298d220ec38d7eb12f40ed1c977f66bf", "size": 3157, "ext": "py", "lang": "Python", "max_stars_repo_path": "flightgear.py", "max_stars_repo_name": "akloster/jupyter-flightgear", "max_stars_repo_head_hexsha": "7135884a31d648b0a768c151a11a47eff287f414", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
(*
Copyright (C) 2017 M.A.L. Marques
This Source Code Form is subject to the terms of the Mozilla Public
License, v. 2.0. If a copy of the MPL was not distributed with this
file, You can obtain one at http://mozilla.org/MPL/2.0/.
*)
(* type: lda_exc *)
a := [0.4581652932831429, 2.217058676663745, 0.74055517353... | {"hexsha": "3280d970aaab5871a640bdce5899edc57baa54dc", "size": 752, "ext": "mpl", "lang": "Maple", "max_stars_repo_path": "libxc-5.1.6/maple/lda_exc/lda_xc_teter93.mpl", "max_stars_repo_name": "pwang234/lsms", "max_stars_repo_head_hexsha": "6044153b6138512093e457bdc0c15c699c831778", "max_stars_repo_licenses": ["BSD-3-C... |
#include "../Includes/USBReader.h"
/* Copyright (c) 2021 [Rick de Bondt] - USBReader.cpp */
#include <array>
#include <chrono>
#include <cstdio>
#include <cstring>
#include <iostream>
#include <string>
#include <vector>
// Not needed for this file but xlinkconnection needs it and this solves an ordering issue on win... | {"hexsha": "fbd60330f91893fdcd96678ed77a4ec5b2961376", "size": 18892, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "Sources/USBReader.cpp", "max_stars_repo_name": "codedwrench/PSPXLinkBridge", "max_stars_repo_head_hexsha": "a95ffc602547d5b39f29bac0acbeb245bc294bc5", "max_stars_repo_licenses": ["MIT"], "max_stars... |
[STATEMENT]
lemma [simp]: "(typeof\<^bsub>h\<^esub> v = Some Integer) = (\<exists>i. v = Intg i)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (typeof\<^bsub>h\<^esub> v = \<lfloor>Integer\<rfloor>) = (\<exists>i. v = Intg i)
[PROOF STEP]
(*<*)
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (typeof\<^bsub>h\<^e... | {"llama_tokens": 180, "file": "Jinja_Common_Objects", "length": 2} |
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
from os import walk
import sys
import os
import math
from matplotlib.ticker import AutoMinorLocator
import fnmatch
def read_file():
'''
This function will take input from the user [e.g. name (half name*) of the file
containing data ('... | {"hexsha": "6fa13e3932a5a8687c690b1e78563cf7937b09b6", "size": 7630, "ext": "py", "lang": "Python", "max_stars_repo_path": "labview_plot/labview_plot.py", "max_stars_repo_name": "Pankwings/rough_python_practice_", "max_stars_repo_head_hexsha": "3a1e62630c92223b1f02995afa3947504e509858", "max_stars_repo_licenses": ["MIT... |
using LinearAlgebra
"""
implementation of the Limiter
"""
# functions to be called when there is a need of Limiting the slopes
# data= dofs of particular cell
# k = varible number . which column in dofs to be modify
# basis =basis of a problem , node informaton
# a = a in linear eqaution, of that particular k
# b... | {"hexsha": "290219379de40effbc6f96b32ef1792f6fad94a8", "size": 3207, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/kernels/limiter.jl", "max_stars_repo_name": "ashishdarekar/Modern-Wave-Propagation-Discontinuous-Galerkin-Julia", "max_stars_repo_head_hexsha": "b0fa6cda2fc2bdf3ad422abcba7f29a6c168db64", "max_... |
# preprocess_dream_prior.py
#
#
import pandas as pd
import numpy as np
import argparse
import json
def build_weighted_adj(eda_filename):
df = pd.read_csv(eda_filename, sep=" ")
df.reset_index(inplace=True)
antibodies = df["level_0"].unique()
print("ANTIBODIES: ", antibodies)
antibody_map = { a:i... | {"hexsha": "a67c3ac738601af7f85782663a44a8da602ef6b6", "size": 1360, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/preprocess_dream_prior.py", "max_stars_repo_name": "gitter-lab/ssps", "max_stars_repo_head_hexsha": "8557cb1961bcd951c5f78102070925e945567600", "max_stars_repo_licenses": ["MIT"], "max_sta... |
import numpy as np
import matplotlib
import datetime
matplotlib.use('TkAgg')
from fastai.text import *
import sys
sys.excepthook = sys.__excepthook__ # See https://groups.io/g/insync/topic/13778827?p=,,,20,0,0,0::recentpostdate%2Fsticky,,,20,2,0,13778827
import json
from vaderSentiment.vaderSentiment import SentimentI... | {"hexsha": "e524d90ccc700a700708f2816a20b8927510a619", "size": 5677, "ext": "py", "lang": "Python", "max_stars_repo_path": "inference/sentiment_inference.py", "max_stars_repo_name": "MiguelPeralvo/teslamonitor", "max_stars_repo_head_hexsha": "7e81ec47d028e847d44183542a1bf6d2b2ce024c", "max_stars_repo_licenses": ["MIT"]... |
from dataloader.DataloaderApi import *
import torch.nn as nn
import torch.optim
import time
import difflib
import torch.nn.functional as F
import datetime
from collections import Counter
from GPT.RAdam.radam.radam import RAdam
from math import log
from numpy import array
from numpy import argmax
from collections impor... | {"hexsha": "6d108f093373a078c118f2d2b91b96e40e31d12d", "size": 48312, "ext": "py", "lang": "Python", "max_stars_repo_path": "finetune/Classifier6.py", "max_stars_repo_name": "yuningkang/APIRecX", "max_stars_repo_head_hexsha": "aaef5f3f0b669d7a907ddb3273e6658c9267c68a", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
module Effekt.IteratedStaged
import Effekt.CpsStaged
import Effekt.IteratedUnstaged
STM : List Type -> Type -> Type
STM [] a = Exp a
STM (r :: rs) a = (Exp a -> STM rs r) -> STM rs r
pure : Exp a -> STM rs a
pure{ rs= []} a = a
pure{ rs= r :: rs} a = \k => k a
push : (Exp a -> STM (r :: rs) b) -> (Exp b ... | {"hexsha": "550454d1cb15f87fa2db8ae604cfe1a47b616af8", "size": 1774, "ext": "idr", "lang": "Idris", "max_stars_repo_path": "Effekt/IteratedStaged.idr", "max_stars_repo_name": "b-studios/idris-effekt", "max_stars_repo_head_hexsha": "d9c5094456677914e034ef1ade9525ac0c338108", "max_stars_repo_licenses": ["MIT"], "max_star... |
/*
Copyright (C) 2020 Skandinaviska Enskilda Banken AB (publ)
All rights reserved.
This file is part of ORE, a free-software/open-source library
for transparent pricing and risk analysis - http://opensourcerisk.org
ORE is free software: you can redistribute it and/or modify it
under the terms of the Modifie... | {"hexsha": "8534b6659a76ee66daec0d6407ee76914e3b6e0c", "size": 5946, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "OREData/ored/portfolio/commodityasianoption.cpp", "max_stars_repo_name": "mrslezak/Engine", "max_stars_repo_head_hexsha": "c46ff278a2c5f4162db91a7ab500a0bb8cef7657", "max_stars_repo_licenses": ["BSD... |
import cv2
import sys
from ..utils import model_utils
from ..utils.mtcnntf.utils import detect_face
import tensorflow as tf
import numpy as np
import os
os.environ['TF_FORCE_GPU_ALLOW_GROWTH'] = 'true'
ssd_model = None
pnet, rnet, onet = None, None, None
dlib_hog_model = None
dlib_68_landmark = N... | {"hexsha": "03f4cb36ca00d0b916cbe5cb5ccd371bcc602561", "size": 5629, "ext": "py", "lang": "Python", "max_stars_repo_path": "duyai/cv/face/detection.py", "max_stars_repo_name": "DuyNguyen-ai/duyai", "max_stars_repo_head_hexsha": "8c9ef23942f6e2965e487d57b67331c8c66b935a", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
# -*- coding: utf-8 -*-
"""
Title: Multimedia Data Formats
Date: 01.06.2018
Description:
"""
import cv2
import numpy as np
from scipy.spatial import distance
class Detect:
def __init__(self):
return None
def detect_all(self, keypoint_descriptors):
"""detect_... | {"hexsha": "63099394edd7daf52e6ab81c228c0b9cf63f648a", "size": 4576, "ext": "py", "lang": "Python", "max_stars_repo_path": "detect.py", "max_stars_repo_name": "Steinthor/MediaDataProject", "max_stars_repo_head_hexsha": "5137b96da7dce11499ae729ac6986c88ad3169e9", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 3,... |
[STATEMENT]
lemma dlex_pp_zero_min: "dlex_pp 0 s"
for s t::"(_, _::add_linorder_min) pp"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. dlex_pp 0 s
[PROOF STEP]
by (transfer, fact dlex_pm_zero_min) | {"llama_tokens": 99, "file": "Polynomials_PP_Type", "length": 1} |
From Ordinal Require Import sflib Basics.
From Ordinal Require Export Ordinal Arithmetic.
Require Import Coq.Classes.RelationClasses Coq.Classes.Morphisms.
Set Implicit Arguments.
Set Primitive Projections.
Module Hessenberg.
Section ADD.
Program Let _add: Ord.t * Ord.t -> Ord.t :=
Fix (double_rel_well_f... | {"author": "minkiminki", "repo": "Ordinal", "sha": "225f2f2b18ec8d65a637d964839528eeeb1829ce", "save_path": "github-repos/coq/minkiminki-Ordinal", "path": "github-repos/coq/minkiminki-Ordinal/Ordinal-225f2f2b18ec8d65a637d964839528eeeb1829ce/src/Hessenberg.v"} |
// __BEGIN_LICENSE__
// Copyright (C) 2006-2011 United States Government as represented by
// the Administrator of the National Aeronautics and Space Administration.
// All Rights Reserved.
// __END_LICENSE__
#include <vw/Mosaic/GigapanQuadTreeConfig.h>
#include <boost/bind.hpp>
#include <boost/filesystem/path.hpp>... | {"hexsha": "66fc1ae8e1e8793148115791883df0745f64e44b", "size": 5128, "ext": "cc", "lang": "C++", "max_stars_repo_path": "src/vw/Mosaic/GigapanQuadTreeConfig.cc", "max_stars_repo_name": "digimatronics/ComputerVision", "max_stars_repo_head_hexsha": "2af5da17dfd277f0cb3f19a97e3d49ba19cc9d24", "max_stars_repo_licenses": ["... |
# This file is a part of BAT.jl, licensed under the MIT License (MIT).
"""
NamedTupleTransform <: VariateTransform
*BAT-internal, not part of stable public API.*
"""
struct NamedTupleTransform{
names,
ST <: VariateSpace,
SF <: VariateSpace,
N,
TT <: NTuple{N,VariateTransform{<:VariateForm}},
... | {"hexsha": "27cdefa79db64cfb4d54a568a0e125bf6a5baa86", "size": 2736, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/transforms/named_tuple_transform.jl", "max_stars_repo_name": "Cornelius-G/BAT.jl", "max_stars_repo_head_hexsha": "1bb577c8d976066c1f52070984d86020728f599c", "max_stars_repo_licenses": ["MIT"], ... |
# Loading the required modules
import numpy as np
from scipy.spatial.distance import cdist
# Defining our function
def kmeans(x, k, no_of_iterations):
idx = np.random.choice(len(x), k, replace=False)
# Randomly choosing Centroids
centroids = x[idx, :] # Step 1 #to jest tablica z centroidami [[x,y],[x,y]... | {"hexsha": "fc6fd9168bc401840eccb166dcba4b5da51e7163", "size": 1179, "ext": "py", "lang": "Python", "max_stars_repo_path": "kmean.py", "max_stars_repo_name": "gitgeoman/Astar_algorigtm", "max_stars_repo_head_hexsha": "93eaf7b27a42a392f1d5b1f5f928b26f77c08696", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
# -*- coding: utf-8 -*-
"""Provides an ability to serialise Stone Soup objects into and from YAML.
Stone Soup utilises YAML_ for serialisation. The :doc:`stonesoup.base`
feature of components is exploited in order to store the data of the
components and data types.
This module functions as a plug-in for ruamel.yaml_,... | {"hexsha": "d9ff647e5222be23f4b20e59b74e00dc7c81cbe9", "size": 9143, "ext": "py", "lang": "Python", "max_stars_repo_path": "stonesoup/serialise.py", "max_stars_repo_name": "io8ex/Stone-Soup", "max_stars_repo_head_hexsha": "071abc8f6004296ab35094db04c7ec410103c419", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
#!/usr/bin/python3
# -*- coding: UTF-8 -*-
import numpy as np
import cv2
from tensorflow.python.platform import test
from tensorflow.python.framework import test_util
from custom_helper_op import DepthProjectLayer
import tensorflow as tf
from scipy import interpolate
class DepthProjectTest(test_util.parameterized.Te... | {"hexsha": "d3855aa6f62d028eeb237ed93e2733b724101908", "size": 2131, "ext": "py", "lang": "Python", "max_stars_repo_path": "custom_helper_op/python/layers/depth_projection_layer_test.py", "max_stars_repo_name": "zhuimeng999/custom_helper_op", "max_stars_repo_head_hexsha": "439c01a9112160ab0a1589454393139d213dcc63", "ma... |
"""
apply_axis!(g, a)
Internal function to apply an `Axis` object `a` in a GLE context.
"""
function apply_axis!(g::GLE, a::Axis, parent_font::String)
parent_font = ifelse(isdef(a.textstyle.font), a.textstyle.font, parent_font)
apply_ticks!(g, a.ticks, a.prefix, parent_font)
if isdef(a.title)
a... | {"hexsha": "f2e4a5d587626bdca79cbde5c572346e55886632", "size": 5299, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/apply_gle/ax.jl", "max_stars_repo_name": "tlienart/GPlot.jl", "max_stars_repo_head_hexsha": "c9dc537329b237b45dfb38442a89ad1868fdd0db", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 10... |
# -*- coding: utf-8 -*-
"""
Created on Wed Apr 14 19:02:25 2021
@author: Administrator
"""
import os
import pandas as pd
import numpy as np
# import matplotlib
import matplotlib.pyplot as plt
import seaborn as sns; sns.set()
from matplotlib import pyplot as pl
from MyClass_python import base_function as bf
#--figur... | {"hexsha": "3013b277eb9a8613aa437ba99ea2e14a1eb4e985", "size": 4249, "ext": "py", "lang": "Python", "max_stars_repo_path": "Project_FrogLossFunctionCNN_Aus/Aus_plot_step2_Loss_repeat.py", "max_stars_repo_name": "Frog-Analysis/Project_FrogLossFunctionCNN", "max_stars_repo_head_hexsha": "c2a1d440d5eb45577f5e3b28b3d29ab42... |
#include "FeaturesComputer.hpp"
#include <itkImageRegionIteratorWithIndex.h>
#include <boost/program_options.hpp>
#include <iostream>
#include <string>
namespace po = boost::program_options;
typedef itk::ImageRegionIteratorWithIndex< OutputImageType > OutputImageIterator;
class CoordinatesComputer : public Featu... | {"hexsha": "a96af74005c5a304cdd5eb26ee213afdc2b5ee8a", "size": 2672, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "CoordinatesComputer.cpp", "max_stars_repo_name": "Sigill/ImageFeaturesComputer", "max_stars_repo_head_hexsha": "3e1058d7e97413d0a3e928bdc802535e85a73a59", "max_stars_repo_licenses": ["MIT"], "max_st... |
#!/usr/bin/python
"""
Plot sigma(fNL) as a fn. of z, for different fiducial fNL
"""
import numpy as np
import pylab as P
from rfwrapper import rf
# Load sigma(fNL) and z bins
fNL = [0., 1., 10.]
sigmas = []; sigmas_bz = []
sigma_fNL = []; sigma_fNL_bz = []
sigma_bias = []
for j in range(len(fNL)):
zc = np.load("... | {"hexsha": "6285bf02703d68f94bdbb6815561d95b1e169b4e", "size": 1708, "ext": "py", "lang": "Python", "max_stars_repo_path": "plotting/plot_pub_nongaussianity_fn_fnl.py", "max_stars_repo_name": "sjforeman/RadioFisher", "max_stars_repo_head_hexsha": "fe25f969de9a700c5697168ba9e0d2645c55ed81", "max_stars_repo_licenses": ["... |
Load LFindLoad.
Load LFindLoad.
From adtind Require Import goal82.
From lfind Require Import LFind.
Require Import Arith.
Require Import Extraction.
Extract Inductive nat => nat [ "(O)" "S" ].
Extract Inductive list => list [ "Nil" "Cons" ].
Extraction "/home/yousef/lemmafinder/benchmark/_lfind_clam_lf_goal82_rev_app... | {"author": "yalhessi", "repo": "lemmaranker", "sha": "53bc2ad63ad7faba0d7fc9af4e1e34216173574a", "save_path": "github-repos/coq/yalhessi-lemmaranker", "path": "github-repos/coq/yalhessi-lemmaranker/lemmaranker-53bc2ad63ad7faba0d7fc9af4e1e34216173574a/benchmark/clam/_lfind_clam_lf_goal82_rev_append_49_append_nil/lfind_m... |
/*
microsoft-oms-auditd-plugin
Copyright (c) Microsoft Corporation
All rights reserved.
MIT License
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, in... | {"hexsha": "f5147b9419e3274527b2ec0d0e1033facfef732c", "size": 15575, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "EventProcessorTests.cpp", "max_stars_repo_name": "kovdan01/OMS-Auditd-Plugin", "max_stars_repo_head_hexsha": "529db434129f43f5763a405eb3357bedad757968", "max_stars_repo_licenses": ["MIT"], "max_sta... |
# -*- coding: utf-8 -*-
"""
@date: 2021/7/20 下午10:23
@file: prune_mobilenet_v2.py
@author: zj
@description:
"""
import numpy as np
import torch
import torch.nn as nn
from torchvision.models.mobilenetv2 import ConvBNActivation, ConvBNReLU, InvertedResidual
from slim.prune.layers import create_conv2d, create_batchnor... | {"hexsha": "0575af71198a2d4cd1727af7eda389873fae9eca", "size": 16030, "ext": "py", "lang": "Python", "max_stars_repo_path": "slim/prune/prune_mobilenet_v2.py", "max_stars_repo_name": "ZJCV/NetworkSlimming", "max_stars_repo_head_hexsha": "1d3d355e538ad8c2d29ec388a57b397aaf387d8c", "max_stars_repo_licenses": ["Apache-2.0... |
using Dash, DashHtmlComponents, DashCoreComponents
app = dash()
app.layout = html_div() do
dcc_input(id = "input-3", value = "initial value", type = "text"),
html_div(id="output-1")
end
callback!(app, Output("output-1", "children"), Input("input-3", "value")) do input_value
"You've entered $(input_value)... | {"hexsha": "2cd2f0fb883570d25227feffc12e58f022f73739", "size": 366, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "dash_docs/chapters/basic_callbacks/examples/simple-callback.jl", "max_stars_repo_name": "joelostblom/dash-docs", "max_stars_repo_head_hexsha": "7be5aed7795f61ac32375ce33a18046b8f2f5254", "max_stars_... |
import argparse, os, csv, sys, errno
import networkx as nx
"""
This is functionally equivalent to the mkdir -p [fname] bash command
"""
def mkdir_p(path):
try:
os.makedirs(path)
except OSError as exc: # Python >2.5
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
e... | {"hexsha": "57e18a84335ef291318206d15647d590ab1e612d", "size": 6568, "ext": "py", "lang": "Python", "max_stars_repo_path": "experiments/2020-11-28-bool-calc-prefix/analysis/genIGraphsByTestID.py", "max_stars_repo_name": "mmore500/Tag-based-Genetic-Regulation-for-LinearGP", "max_stars_repo_head_hexsha": "eda84198123cce3... |
//////////////////////////////////////////////////////////////////////////////
//
// (C) Copyright Ion Gaztanaga 2014-2014.
//
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
// See http://www.boost.org/libs/c... | {"hexsha": "ce5582bcc57c8bd2e083fa8c62b670b7b22da92a", "size": 4525, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "ReactNativeFrontend/ios/Pods/boost/boost/container/detail/algorithm.hpp", "max_stars_repo_name": "Harshitha91/Tmdb-react-native-node", "max_stars_repo_head_hexsha": "e06e3f25a7ee6946ef07a1f524fdf62e... |
/*****************************************************************************
* slicing.cpp Blitz++ Array slicing & subarrays example
*****************************************************************************/
#include <blitz/array.h>
BZ_USING_NAMESPACE(blitz)
int main()
{
Array<int,2> A(6,6), B(3,3... | {"hexsha": "aa83a8eebf58b74fc494cc9abae8da483b844d48", "size": 1025, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "depspawn-blitz-0.10/examples/slicing.cpp", "max_stars_repo_name": "fraguela/depspawn", "max_stars_repo_head_hexsha": "b5760f4c0d38a1b245ee5274e2ccc5c5fe2d3d45", "max_stars_repo_licenses": ["MIT"], "... |
# Python script to run DaCapo benchmarks and collect performance statistics
# Usage: python3 runDaCapo.py
# Note: dacapo-9.12-MR1-bach.jar msut be present in current directory
# The script can be customized as follows:
# 1. Specify which benchmarks to run ==> change "benchmark" list below
# 2. Specify the number ite... | {"hexsha": "4aaa84c620ef8d8234d2b4cb966c0fbc84199c25", "size": 5809, "ext": "py", "lang": "Python", "max_stars_repo_path": "runDaCapo.py", "max_stars_repo_name": "mpirvu/Utils", "max_stars_repo_head_hexsha": "60884803de9d499ef79527c5a6386aabc876c85e", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max_st... |
SUBROUTINE icsd_t1_7(d_a,k_a_offset,d_b,k_b_offset,d_c,k_c_offset,ctx,ex)
IMPLICIT NONE
INTEGER :: POSTPROCESSMARKER1
INTEGER :: ga_max_dim
parameter(ga_max_dim = 7)
INTEGER :: ga_nnodes, ga_nodeid, ga_read_inc
INTEGER :: ga_pgroup_nnodes, ga_pgroup_nodeid
INTEGER :: nga... | {"hexsha": "e256218f0b8bcec114201b2ef4c08221ac717997", "size": 19322, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "projects/minitermite/regression/fortran/expanded.f90", "max_stars_repo_name": "haiwangcat/ROSE", "max_stars_repo_head_hexsha": "75bf4106a5febe40269ea0361a024b7811668d45", "max_stars_repo_licens... |
#!/usr/bin/python3
'''
Function and data integration tools
'''
try:
import numpy as np
except ModuleNotFoundError:
print("\"numpy\" not found. This module requires numpy")
try:
import matplotlib.pyplot as plt
except ModuleNotFoundError:
print("\"matplotlib\" not found. This module requires matplotlib... | {"hexsha": "1490583d27b8405095f62a1f436ec1dbc79ac1de", "size": 5611, "ext": "py", "lang": "Python", "max_stars_repo_path": "Integration.py", "max_stars_repo_name": "santiagohenao/santiagohenao_tools", "max_stars_repo_head_hexsha": "81a772114b482b83639c835b0a2096f11ca45075", "max_stars_repo_licenses": ["MIT"], "max_star... |
#include "PyInlineReductions.h"
#include <boost/python.hpp>
#include <string>
#include "Halide.h"
#include "PyExpr.h"
namespace h = Halide;
namespace p = boost::python;
h::Expr sum0(h::Expr e, const std::string name) {
return h::sum(e, name);
}
h::Expr sum1(h::RDom r, h::Expr e, const std::string name) {
... | {"hexsha": "0772c731eabd90cc95b051dc43f3487053e894ea", "size": 2974, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "python_bindings/src/PyInlineReductions.cpp", "max_stars_repo_name": "jrayzero/Halide", "max_stars_repo_head_hexsha": "174bfe850d225e5e3644cd14fb4ea06b50173ae3", "max_stars_repo_licenses": ["MIT"], "... |
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 30 19:38:41 2019
@author: Yadnyesh
"""
# -*- coding: utf-8 -*-
"""
Created on Tue Apr 30 18:24:14 2019
@author: Yadnyesh
"""
# Import libraries
import numpy as np
import os
from PIL import Image
import cv2 as cv
import matplotlib.pyplot as plt
# S... | {"hexsha": "86c5973035833661ee5d057ea65b19db4d72d29f", "size": 9065, "ext": "py", "lang": "Python", "max_stars_repo_path": "added_data_aug.py", "max_stars_repo_name": "Yashgh7076/CPSC-8810-Project", "max_stars_repo_head_hexsha": "81a32072e4888f6bbdaf4a74fd5ab9ef386b299b", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
import sys
import random
import json
import re
import numpy as np
# remove non-ascii text in a string
def remove_nonascii(text):
return str(''.join([i if ord(i) < 128 else "" for i in text]))
# kepp characters in a string iff it's in the alphabet
# For training
def filter_with_alphabet(text, alphabet):
return ''.jo... | {"hexsha": "a26b288c13d86550ccc818b87d419bc2e8168e8b", "size": 1241, "ext": "py", "lang": "Python", "max_stars_repo_path": "helper.py", "max_stars_repo_name": "pearfish16/ngram_sentiment", "max_stars_repo_head_hexsha": "1f20f30b5eaaffdc791802b8ce8ce6e177404344", "max_stars_repo_licenses": ["MIT"], "max_stars_count": nu... |
[STATEMENT]
theorem from_dtree_fin_list_dir: "fin_list_directed_tree (root t) (from_dtree dt dh t)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. fin_list_directed_tree (dtree.root t) (from_dtree dt dh t)
[PROOF STEP]
unfolding fin_list_directed_tree_def fin_list_directed_tree_axioms_def
[PROOF STATE]
proof (prove)... | {"llama_tokens": 336, "file": "Query_Optimization_List_Dtree", "length": 2} |
import tensorflow as tf
from tensorflow.contrib import rnn
import numpy as np
from gensim.models.keyedvectors import KeyedVectors
class Model(object):
def __init__(self, article_max_len, summary_max_len, embedding_dim, hidden_dim, layers_num,
learning_rate, beam_width, keep_prob, vocabulary_size... | {"hexsha": "33035f88d835eb00149ee3bce26752e537111aee", "size": 9328, "ext": "py", "lang": "Python", "max_stars_repo_path": "model.py", "max_stars_repo_name": "KrisG04/encoder-decoder-text-summarizer", "max_stars_repo_head_hexsha": "db2680a89bc4d6a0651cf734445a376da73d4ffb", "max_stars_repo_licenses": ["MIT"], "max_star... |
from ocdata.vasp import run_vasp, write_vasp_input_files
from ocdata.adsorbates import Adsorbate
from ocdata.bulk_obj import Bulk
from ocdata.surfaces import Surface
from ocdata.combined import Combined
import argparse
import logging
import math
import numpy as np
import os
import pickle
import time
class StructureS... | {"hexsha": "f061782062de2d88c6e498ee3486a1c1a62e8d38", "size": 10284, "ext": "py", "lang": "Python", "max_stars_repo_path": "sample_structure.py", "max_stars_repo_name": "cesmix-mit/Open-Catalyst-Dataset", "max_stars_repo_head_hexsha": "ffd73a9bf5c5ec26efd15e3cf66c1c0b376886d5", "max_stars_repo_licenses": ["CC-BY-4.0"]... |
SUBROUTINE TSTIVF (WKID, INCSIZ,INCSET, EXCSIZ,EXCSET)
C TSTIVF tests that the appropriate primitives are invisible for
C a given inclusion and exclusion set used as the invisibility
C filter.
C Input parameters:
C WKID : workstation identifier
C INCSIZ,INCSET : inclusion set
C EXCSIZ,EXCS... | {"hexsha": "f5de0215fcf68d7a4cd1eda6eb5e71e7fab32c7d", "size": 789, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "third_party/Phigs/PVT/PVT_fort/V2LIB/tstivf.f", "max_stars_repo_name": "n1ckfg/Telidon", "max_stars_repo_head_hexsha": "f4e2c693ec7d67245974b73a602d5d40df6a6d69", "max_stars_repo_licenses": ["MIT"]... |
//Copyright 2019 CrazyOverdose
#ifndef INCLUDE_ANALYSIS_HPP_
#define INCLUDE_ANALYSIS_HPP_
#include <boost/filesystem.hpp>
#include <vector>
#include <string>
#include <cstdlib>
struct Date {
int day;
int month;
int year;
};
struct information {
std::string title; //название файла
std:: string ... | {"hexsha": "6cc08351d8363737a0780d9c5df9b00d1d1de980", "size": 3602, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "include/analysis.hpp", "max_stars_repo_name": "CrazyOverdose/lab-04-boost-filesystem", "max_stars_repo_head_hexsha": "b0ce1ab53ae3e9fe2f8a7e60bf56d0555bb7d42a", "max_stars_repo_licenses": ["MIT"], "... |
# -*- coding: utf-8 -*-
# @Time : 2021/2/15 23:03
# @Author : Zeqi@@
# @FileName: Prediction_Decoder.py
# @Software: PyCharm
import numpy as np
import tensorflow as tf
from tensorflow.keras.layers import MaxPooling2D
def nms(heat, kernel=3):
hmax = MaxPooling2D((kernel, kernel), strides=1, padding='SAME')(hea... | {"hexsha": "815f0cf687b46cab475a14a9637050f7f19943ac", "size": 4634, "ext": "py", "lang": "Python", "max_stars_repo_path": "Utils/Prediction_Decoder.py", "max_stars_repo_name": "monchhichizzq/CenterNet", "max_stars_repo_head_hexsha": "718bfbfa1940a8b068ab359aaca6737c3c173ad0", "max_stars_repo_licenses": ["MIT"], "max_s... |
import numpy
from generate import *
def generate():
vectors = []
x = random_float32(256)
vectors.append(TestVector([2], [x], [x[0::2], x[1::2]], "Deinterleave 2 channels, Float32 input"))
vectors.append(TestVector([3], [x], [x[0::3], x[1::3], x[2::3]], "Deinterleave 3 channels, Float32 input"))
... | {"hexsha": "dfda1843cb9153d682bebb653b1bdcbc603b6ebe", "size": 633, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/blocks/signal/deinterleave_spec.py", "max_stars_repo_name": "telent/luaradio", "max_stars_repo_head_hexsha": "c1cb47325e4eb2886915f810fff5324571aeb59d", "max_stars_repo_licenses": ["MIT"], "m... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# -*- coding: utf-8 -*-
"""Test desiutil.depend.
"""
import unittest
import sys
from collections import OrderedDict
from ..depend import (setdep, getdep, hasdep, iterdep, Dependencies,
add_dependencies)
from .. import __version__ as d... | {"hexsha": "86693ddb94efa4c74fb8da28b1740893d5c7b6c2", "size": 6905, "ext": "py", "lang": "Python", "max_stars_repo_path": "py/desiutil/test/test_depend.py", "max_stars_repo_name": "sdss/lvmutil", "max_stars_repo_head_hexsha": "1938f6e1d7f4074a90a55570a316886850c5c6af", "max_stars_repo_licenses": ["BSD-3-Clause"], "max... |
import numpy as np
import pandas as pd
def add_features(x: pd.DataFrame):
method_cols = ['financialDebt', 'CreditLeverage', 'FinancialIndependence', 'DebtBurden',
'CoverageDebtWithAccumulatedProfit',
'ReturnAssetsNetProfit', 'ReturnAssetsOperatingProfit', 'OperatingMargin', '... | {"hexsha": "9c7d92e79cb4d9eee8546158b2f2af4691da8fed", "size": 3650, "ext": "py", "lang": "Python", "max_stars_repo_path": "PythonBackend/feature_generation.py", "max_stars_repo_name": "goo-goo-goo-joob/CreditRisks", "max_stars_repo_head_hexsha": "c874941f3787a0c73063883a019a61672e7bef2f", "max_stars_repo_licenses": ["... |
# -*- coding: utf-8 -*-
# cheby_checker/cheby_checker/obs_pos.py
"""
--------------------------------------------------------------
Parse an obscode and figure out where the observer is at a given time.
Jan 2020
Matt Payne & Mike Alexandersen
*WRITE MORE STUFF*
------------------------------------------------------... | {"hexsha": "975bf77517f03c67185b9a3f7cad841a0d4f3d5a", "size": 3001, "ext": "py", "lang": "Python", "max_stars_repo_path": "cheby_checker/obs_pos.py", "max_stars_repo_name": "Smithsonian/cheby_checker", "max_stars_repo_head_hexsha": "ce1542e4b1b3303ac08ea823be1eaec06322fd48", "max_stars_repo_licenses": ["MIT"], "max_st... |
#!/usr/bin/env python
import math
import csv
import numpy as np
from floripy.mathutils import xform as tr
from floripy.mathutils.linalg import unitized
from .miura_sheet_trajectory import MiuraSheetTrajectory
def get_phi_theta(v):
'''
v: (3,) ndarray
Returns phi and theta in degrees.
phi: Angle measu... | {"hexsha": "08834223fcaad2875e4def020be85919bb2fb7e5", "size": 3755, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/miura_sheet/analyze_traj.py", "max_stars_repo_name": "saridut/FloriPy", "max_stars_repo_head_hexsha": "0117d358b9c2362ea32ecf9ec719fdaed87d3e14", "max_stars_repo_licenses": ["MIT"], "max_st... |
(* Sections 2.1 through 2.3 *)
theory AToyList
imports Datatype
begin
datatype 'a list = Nil ("[]") | Cons 'a "'a list" (infixr "#" 65)
(* append one list to another *)
primrec app :: "'a list \<Rightarrow> 'a list \<Rightarrow> 'a list" (infixr "@" 65) where
"([] @ ys) = ys" |
"(x # xs) @ ys = x # xs @ ys"
(* r... | {"author": "spl", "repo": "isabelle-tutorial", "sha": "56ee8d748d6d639ea7238e5fbb9edce4330637f2", "save_path": "github-repos/isabelle/spl-isabelle-tutorial", "path": "github-repos/isabelle/spl-isabelle-tutorial/isabelle-tutorial-56ee8d748d6d639ea7238e5fbb9edce4330637f2/AToyList.thy"} |
[STATEMENT]
lemma fps_Lcm:
assumes "A \<noteq> {}" "0 \<notin> A" "bdd_above (subdegree`A)"
shows "Lcm A = fps_X ^ (SUP f\<in>A. subdegree f)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. Lcm A = fps_X ^ Sup (subdegree ` A)
[PROOF STEP]
proof (rule sym, rule LcmI)
[PROOF STATE]
proof (state)
goal (3 subgoals... | {"llama_tokens": 3506, "file": null, "length": 33} |
/* Copyright © 2017 Apple Inc. All rights reserved.
*
* Use of this source code is governed by a BSD-3-clause license that can
* be found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
*/
#ifndef TURI_SERIALIZE_UNORDERED_MAP_HPP
#define TURI_SERIALIZE_UNORDERED_MAP_HPP
#include <boost/u... | {"hexsha": "cb26278575a258fb32e9fafdf978edb24b38dff5", "size": 2490, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/core/storage/serialization/unordered_map.hpp", "max_stars_repo_name": "Bpowers4/turicreate", "max_stars_repo_head_hexsha": "73dad213cc1c4f74337b905baea2b3a1e5a0266c", "max_stars_repo_licenses": ... |
import time
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from mpl_toolkits.mplot3d import Axes3D
from sources.pdesolver.finite_differences_method.FiniteDifferencesSolver_V2 import GridConfiguration, \
ConstantGridValueProvider, FiniteDifferencesMethod4
from sources.pdesolver.fini... | {"hexsha": "e1396e76d12a4e63a37841e8d4d310fcfb5a6249", "size": 13655, "ext": "py", "lang": "Python", "max_stars_repo_path": "sources/experiments/calc_charge_matrix.py", "max_stars_repo_name": "JohannOberleitner/pdesolver", "max_stars_repo_head_hexsha": "f01f83bde44e9f5aae424a4daa13219f986c5884", "max_stars_repo_license... |
!*******************************************************************
! *
SUBROUTINE NINE(J1,J2,J3,L1,L2,L3,K1,K2,K3,I,INN,AA)
!
! *
! THIS PACKAGE DETERMINES THE VALUES OF 9j COEFF... | {"hexsha": "0061219f3a7a1f0af4bb6a28f13bd5ea8ffc83c9", "size": 3293, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/lib/librang90/nine.f90", "max_stars_repo_name": "sylas/grasp-continuum", "max_stars_repo_head_hexsha": "f5e2fb18bb2bca4f715072190bf455fba889320f", "max_stars_repo_licenses": ["MIT"], "max_st... |
\documentclass{article}
\usepackage[T1]{fontenc}
\usepackage[utf8]{inputenc}
\usepackage{newtxtext,newtxmath}
\usepackage{microtype}
\usepackage{amsmath,amsfonts,amssymb}
\usepackage{microtype}
\usepackage{hyperref}
\usepackage{bookmark}
\begin{document}
I, William C. Dawn, originally prepared this document for co... | {"hexsha": "17f0c921de67549c40f564fe8e3980714c2eecf3", "size": 19901, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "tex_projects/arch_install/arch_install.tex", "max_stars_repo_name": "wcdawn/dotfiles", "max_stars_repo_head_hexsha": "d069b53b7f19b53767df9e8d67b38b1d6fbf4e28", "max_stars_repo_licenses": ["MIT"], ... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
The module provides several custom descriptor classes for attribute
validation of region classes.
"""
import abc
from astropy.coordinates import SkyCoord
from astropy.units import Quantity
import numpy as np
from .pixcoord import PixCoord
__all__ =... | {"hexsha": "9dd9d498d6adca8e8f5b83c90b3044b4a20affdd", "size": 3572, "ext": "py", "lang": "Python", "max_stars_repo_path": "regions/core/attributes.py", "max_stars_repo_name": "dhomeier/regions", "max_stars_repo_head_hexsha": "5055128abda57c3b463f51ede0a6ac0ef5a0c698", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_... |
% This is samplepaper.tex, a sample chapter demonstrating the
% LLNCS macro package for Springer Computer Science proceedings;
% Version 2.20 of 2017/10/04
%
\documentclass[runningheads]{llncs}
%
\usepackage{fixltx2e}
\usepackage[american]{babel}
\usepackage[utf8]{inputenc}
\usepackage{csquotes}
\usepackage{graphicx}
\... | {"hexsha": "4492d9c6f3d2f205e70b0f472a89c097f0b55407", "size": 11109, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "NetworkEvolution/NetworkEvolution.tex", "max_stars_repo_name": "Pat93h/hcii2020patrick", "max_stars_repo_head_hexsha": "21a91eda359f19682f6159840769f73ea4e3f5e2", "max_stars_repo_licenses": ["MIT"]... |
from __future__ import division
import time
import numpy as np
from torch import nn, optim
import torch.nn.functional as F
import torch
import itertools
from dim_red.support_func import loss_permutation, loss_top_1_in_lat_top_k, normalize_numpy,\
get_nearestneighbors, sanitize, forward_pass, Normalize, stopping_... | {"hexsha": "7be519d1c5a4b343914df04f9688657d3f25a2ef", "size": 11432, "ext": "py", "lang": "Python", "max_stars_repo_path": "dim_red/triplet.py", "max_stars_repo_name": "symphony233/gbnns_dim_red", "max_stars_repo_head_hexsha": "2403411600a60ad4365aba3d78a81da144a456b7", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
# Choose model and dimension of x array and y array, and nn output
model_type, kx, ky, ky_nn = "Plasticity", 1, 2, 1
#model_type, kx, ky, ky_nn = "Plasticity", 1, 2, 2
#model_type, kx, ky, ky_nn = "PlasticityLawBased", 1, 1, 1
nn_type = "piecewise2"
#nn_type = "ae"
include("CommonFuncs.jl")
# m set of data, each... | {"hexsha": "9551188ef4728f5c95fc6409659c242e29c9ba7c", "size": 1274, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "research/TransitionFunction/NN_Train.jl", "max_stars_repo_name": "PallHaraldsson/NNFEM.jl", "max_stars_repo_head_hexsha": "33deee97a5897a6f4df6581bd14e853805a2af7e", "max_stars_repo_licenses": ["MI... |
from __future__ import annotations
from typing import TYPE_CHECKING
import numpy as np
from ...utils.geometry import (
clamp_point_to_bounding_box,
point_in_bounding_box,
)
if TYPE_CHECKING:
from ...utils.events import Event
from .image import Image
def move_plane_along_normal(layer: Image, event:... | {"hexsha": "1e757b5fae6b763bd1a960390eabc0d753bbe225", "size": 3353, "ext": "py", "lang": "Python", "max_stars_repo_path": "napari/layers/image/_image_mouse_bindings.py", "max_stars_repo_name": "chili-chiu/napari", "max_stars_repo_head_hexsha": "eb6e672975ce105ac0125f71da3d0970d17cefb9", "max_stars_repo_licenses": ["BS... |
/**
* ex_gnuplot.h
*
* utility functions for plotting with gnuplot (v 4.6)
*
* - minimizes boilerplate needed to use
* - popen -> process piping available, less temp files
* - idea based on myexamples/gnuplot (syntax) and gnuplot_i by N. Devillard (pipes), except a bit simpler
*
* Aaro Salosensaari 2016
*
... | {"hexsha": "53374b58aa4e13606c7ec735ff962844b18d9143", "size": 2232, "ext": "h", "lang": "C", "max_stars_repo_path": "ex_gnuplot.h", "max_stars_repo_name": "aa-m-sa/ex_gnuplot_util", "max_stars_repo_head_hexsha": "17319213c85f65850c7b017bb4f3030d978ba936", "max_stars_repo_licenses": ["Unlicense"], "max_stars_count": 1.... |
"""
AbstractOperator
An abstract type for linear operators on Banach spaces.
"""
abstract type AbstractOperator end
"""
KernelOperator{K,S} <: AbstractOperator
A type for representing kernel integral operators over Hilbert spaces.
"""
struct KernelOperator{K,S} <: AbstractOperator
kernel::K
solver::... | {"hexsha": "b63ae7818668e3da77223279c3770182be7102de", "size": 1557, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/kernel_operators/kernel_operators.jl", "max_stars_repo_name": "csimal/SpectralLearning.jl", "max_stars_repo_head_hexsha": "4999657700a0d84dfff470a52ddb3e3b37a44aae", "max_stars_repo_licenses": ... |
using Keldysh, Test
@testset "contour" begin
let c = FullContour(tmax=2.0, β=5.0)
@test nbranches(c) == 3
b = map(x -> x.domain, c.branches)
@test b == (forward_branch, backward_branch, imaginary_branch)
c = twist(c)
b = map(x -> x.domain, c.branches)
@test b == (backward_branch, imaginary_... | {"hexsha": "0e1dfb74a889c6f7ca3c151a4dd622c9fad1585f", "size": 1295, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/contour.jl", "max_stars_repo_name": "kleinhenz/Keldysh.jl", "max_stars_repo_head_hexsha": "997cd6e06bff4d580ee7fc03dba7e218983caae4", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 23,... |
function [paramsOut] = globalTrendGUI(hObject, callbackdata, inputData)%#ok<INUSL>
theTitle ='Global trend parameters';
defaultStruct = inputData.userData.globalTrend;
while(true)
mainFigure = findobj('Type', 'Figure', '-and', 'Name', inputData.name);
userdata = get(mainFigure, 'UserData');... | {"author": "VisLab", "repo": "EEG-Clean-Tools", "sha": "9ac9ea0c21d44b57f9e9f93b62ca727c7b75c73e", "save_path": "github-repos/MATLAB/VisLab-EEG-Clean-Tools", "path": "github-repos/MATLAB/VisLab-EEG-Clean-Tools/EEG-Clean-Tools-9ac9ea0c21d44b57f9e9f93b62ca727c7b75c73e/PrepPipeline/interface/globalTrendGUI.m"} |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# write a correct test!
import unittest
import pygimli as pg
import numpy as np
class TestSparseMatrix(unittest.TestCase):
def test_Convert(self):
"""
"""
colIds = range(10)
rowIds = range(10)
vals = np.ones(10)
# Con... | {"hexsha": "868ef11c4d8a4c4702be3aeb6845834a169da208", "size": 6394, "ext": "py", "lang": "Python", "max_stars_repo_path": "pygimli/testing/test_SparseMatrix.py", "max_stars_repo_name": "JuliusHen/gimli", "max_stars_repo_head_hexsha": "a5c5779261acfe5a53015c9ee6f7c9ed2dd6c57f", "max_stars_repo_licenses": ["Apache-2.0"]... |
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