text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
|---|---|
import madmom
import numpy as np
class SpectrogramProcessor(madmom.processors.SequentialProcessor):
SAMPLE_RATE_HZ = 44100
FRAMES_PER_SECOND = 100
def __init__(self, window_size_ms, formatted=False, fps=FRAMES_PER_SECOND,
sample_rate=SAMPLE_RATE_HZ, context_frames=7):
win_size_s... | {"hexsha": "5107afdbae60d0c0de90bcfb49b6dbaca054e112", "size": 2254, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/common/audio_preprocessor.py", "max_stars_repo_name": "Killy85/saber-maker", "max_stars_repo_head_hexsha": "da409691a511e2e8233c56b14c57a60df5e97040", "max_stars_repo_licenses": ["MIT"], "max_... |
#include <cstddef>
#include <iostream>
#include <iomanip>
#include <eigen-checks/gtest.h>
#include <gtest/gtest.h>
#include <Eigen/Core>
#include <Eigen/Dense>
#include <cholmod.h>
#include <SuiteSparseQR.hpp>
#include "truncated-svd-solver/tsvd-solver.h"
#include "truncated-svd-solver/linear-algebra-helpers.h"
#in... | {"hexsha": "5540c59baf6a09db299a237a525552da53ea86ef", "size": 9266, "ext": "cc", "lang": "C++", "max_stars_repo_path": "truncated_svd_solver/test/test-tsvd-solver.cc", "max_stars_repo_name": "ethz-asl/truncated_svd_solver", "max_stars_repo_head_hexsha": "12772b2e3a0282e77022f12f67497401ca020f57", "max_stars_repo_licen... |
import abc
from asyncio.queues import QueueEmpty
import json
import os
import threading
import time
import numpy as np
from sentence_transformers import SentenceTransformer
from onnx_sentence_transformers import ONNXSentenceTransformer
import simpleaudio as sa
import speech_recognition as sr
import yaml
from ibm_cloud... | {"hexsha": "0ad118cfa3a05de34b424002e148a18cf5fdb6d4", "size": 4206, "ext": "py", "lang": "Python", "max_stars_repo_path": "listen_user.py", "max_stars_repo_name": "xiong-jie-y/tsukuyomichan-ai", "max_stars_repo_head_hexsha": "e51763974bb3aa5306bcecba4832bc81c7501a5b", "max_stars_repo_licenses": ["RSA-MD"], "max_stars_... |
[STATEMENT]
lemma E_inf_lfp:
fixes g
defines "l \<equiv> \<lambda>f \<omega>. g (shd \<omega>) (f (stl \<omega>))"
assumes measurable_g[measurable]: "case_prod g \<in> borel_measurable (count_space UNIV \<Otimes>\<^sub>M borel)"
assumes cont_g: "\<And>s. sup_continuous (g s)"
assumes int_g: "\<And>f cfg. f \<... | {"llama_tokens": 22685, "file": "Markov_Models_Markov_Decision_Process", "length": 123} |
import rospy
from hybrid_control_api.srv import *
import numpy as np
from std_msgs.msg import String
import threading
from topicCartesianState import *
from std_msgs.msg import Float64
from std_srvs.srv import Empty
from keras.models import load_model
from keras.models import Model
import csv
from runOnThormang import ... | {"hexsha": "4e3ff9030677a16b0a882658ba711af30b8da421", "size": 24975, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/myHybridControl.py", "max_stars_repo_name": "ricardoGrando/hybrid_control_api", "max_stars_repo_head_hexsha": "837a0a268a49c5088259f89e8c83adb7638a44b8", "max_stars_repo_licenses": ["BSD-... |
# Using ctrl,shift,C to create Comments
# //step 1.Downloaded Marketing data from Github//
# reading r file marketing.rda for Analysis
setwd("/home/carol/Desktop/R-Code/Practice/marketing.rda")
load("/home/carol/Desktop/R-Code/Practice/marketing.rda")
# view data for analysis
View(marketing)
# transform data into a dat... | {"hexsha": "049faf2e7c284198dacf5933368d61bf6a40793e", "size": 2803, "ext": "r", "lang": "R", "max_stars_repo_path": "code.r", "max_stars_repo_name": "Carolkinyua-hub/R-Practical", "max_stars_repo_head_hexsha": "59826d523b56d1f6e20d0d46dc548a40b285e1bf", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max... |
using Test, GameOfLife
using SharedArrays
using DistributedArrays: distribute
interior(grid) = @view grid[2:end-1,2:end-1]
function generate(world, s=Serial())
m, n = size(world)
grid = BitArray(undef, m+2, n+2)
interior(grid) .= world
grid
end
function generate(world, ::ProcParallel)
m, n = size... | {"hexsha": "65f3eb9b3c617312a18d0c82ff8e5ec70ca14517", "size": 2516, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/runtests.jl", "max_stars_repo_name": "jonas-schulze/GameOfLife.jl", "max_stars_repo_head_hexsha": "6d81b0486feba5f16b04fad42842dee9b9c8ecdc", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
#!/usr/bin/env python
# -*- coding: UTF-8 -*-
"""
author: sanja7s
---------------
plot the distribution
"""
import os
import datetime as dt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib
from collections import defaultdict
from matplotlib import colors
from mpl_toolkits.axes... | {"hexsha": "7c7f203a4aad419a8f776bf814ec1932c9d2454d", "size": 3676, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/distributions/job_steps_distribution.py", "max_stars_repo_name": "sanja7s/EEDC", "max_stars_repo_head_hexsha": "6a9aabf61bc857ad9b54d07b256610e766a0d88d", "max_stars_repo_licenses": ["Apache-2... |
""" Solution for Project Euler's problem #1 """
import os
import time
from datetime import timedelta
import jax.numpy as jnp
from jax import jit
from gante_project_euler.math.prime import is_multiple
@jit
def get_solution():
""" Solves the problem and returns the answer.
"""
integers = jnp.arange(1000)... | {"hexsha": "773b25dd73bdd4df76b579be838ed9a6a874b34a", "size": 1071, "ext": "py", "lang": "Python", "max_stars_repo_path": "gante_project_euler/solutions/problem_001.py", "max_stars_repo_name": "gante/project_euler", "max_stars_repo_head_hexsha": "9b5e780259e28d4f4d66cb4c954623f81aeaa5af", "max_stars_repo_licenses": ["... |
#include <iostream>
#include <string>
#include <vector>
#include <atomic>
#include <condition_variable>
#include <deque>
#include <mutex>
#include <thread>
#include <unordered_map>
#include <unordered_set>
#include <boost/property_tree/ptree.hpp>
#include <boost/property_tree/json_parser.hpp>
#include <networking/s... | {"hexsha": "2dbaa31b6893672104f5183f431281a0b614c9f2", "size": 4019, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "server/server/src/server.cpp", "max_stars_repo_name": "dzagar/AndroidMessenger", "max_stars_repo_head_hexsha": "2a43c2144145b02496c5cab9e59c6827a3d43ec5", "max_stars_repo_licenses": ["MIT"], "max_st... |
#== # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
#
# Description
#
# Tests related to TLE parser.
#
# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ==#
# Macros tle_str and tlenc_str
# ============================
@testset "Macros tle_str and tlenc_str" beg... | {"hexsha": "3dca5047590a6fb2cab76cdeeab1aeb62fc48cf7", "size": 4703, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/submodules/SatelliteToolboxTLE/tle.jl", "max_stars_repo_name": "UnofficialJuliaMirrorSnapshots/SatelliteToolbox.jl-6ac157d9-b43d-51bb-8fab-48bf53814f4a", "max_stars_repo_head_hexsha": "7337476... |
#!/usr/bin/env python
#
# featdesign.py - The FEATFSFDesign class, and a few other things.
#
# Author: Paul McCarthy <pauldmccarthy@gmail.com>
#
"""This module provides the :class:`FEATFSFDesign` class, which encapsulates
a FEAT design matrix.
The :class:`FEATFSFDesign` class is intended to be used to access the desi... | {"hexsha": "ce5b41f592609b5dbd6bc8b987e04016567a761c", "size": 25901, "ext": "py", "lang": "Python", "max_stars_repo_path": "fsl/data/featdesign.py", "max_stars_repo_name": "physimals/fslpy", "max_stars_repo_head_hexsha": "10dd3f996c79d402c65cf0af724b8b00082d5176", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_... |
import sys
import yaml
import math
import time
import random
import traceback
import xarray as xr
import numpy as np
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
import scipy.sparse
from scipy.ndimage import gaussian_filter
from tqdm.auto import tqdm
import numpy.fft as FFT
from... | {"hexsha": "b7cce1083e20fa136bd5ea1396ec3a8af9dfef6a", "size": 7493, "ext": "py", "lang": "Python", "max_stars_repo_path": "echo/examples/keras/model.py", "max_stars_repo_name": "NCAR/echo-opt", "max_stars_repo_head_hexsha": "a5bd69cce36da90fec7eed4fe3b240243fcf53b0", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
module Day22
export get_inputs, get_solution1, get_solution2
## Input getting
function get_inputs()
test_input1 = test_input2 = read_input(joinpath(@__DIR__, "test_input1.txt"))
test_output1 = 306
test_output2 = 291
data = read_input(joinpath(@__DIR__, "input.txt"))
return (; test_input1, test_in... | {"hexsha": "4df3c36c4eb10ecdbc60b1d930320122c57675d9", "size": 1670, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "scripts/Day22/code.jl", "max_stars_repo_name": "jonniedie/Advent2020", "max_stars_repo_head_hexsha": "3af73d728f6f9827fa5a1124354ebebc77eec69d", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#module mido for working with midi files
from mido import MidiFile, Message
import os
import numpy as np
from tensorflow.keras.models import load_model
from tensorflow.keras.layers import *
#load midi file
data = []
pattern = MidiFile("musics/Hot N Cold - Chorus.mid")
a = []
#get all messages from pattern... | {"hexsha": "65ccadce9e283f874d6349b4c76cb51f923a923e", "size": 2176, "ext": "py", "lang": "Python", "max_stars_repo_path": "generate.py", "max_stars_repo_name": "durman53/tensorflow-keras-music-generation", "max_stars_repo_head_hexsha": "02086a2f5afdde32c2a271b60a55ffef2f393061", "max_stars_repo_licenses": ["MIT"], "ma... |
if nprocs() < 2
id_me = myid()
id_other = addprocs(1)[1]
using MessageUtils
using Base.Test
end
c = channel()
put!(c, 1; timeout=10.0)
put!(c, "Hello")
put!(c, 5.0)
@test isready(c) == true
@test fetch(c) == 1
@test fetch(c) == 1 # Should not have been popped previously
@test take!(c) == 1
@test... | {"hexsha": "381675c9b3e12f55c68d239a298fcf487eb3516a", "size": 1115, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/test_channel.jl", "max_stars_repo_name": "JuliaPackageMirrors/MessageUtils.jl", "max_stars_repo_head_hexsha": "dbe01a3578b25ed348ee8c36bc393ce86be2016b", "max_stars_repo_licenses": ["MIT"], "m... |
#
# (c) 2015-2018, ETH Zurich, Institut fuer Theoretische Physik
# Author: Dominik Gresch <greschd@gmx.ch>
"""Tests for joining two models together."""
# pylint: disable=invalid-name
import pytest
import numpy as np
import tbmodels
@pytest.fixture
def model_dense(sample):
"""Fixture for a dense tight-binding m... | {"hexsha": "ab56d882433f712422d55f1c55d56fbabd934f7a", "size": 2662, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_join_models.py", "max_stars_repo_name": "Z2PackDev/TBModels", "max_stars_repo_head_hexsha": "1b0f07aa16000d3436ec30cc9e8132637fbfa4e6", "max_stars_repo_licenses": ["Apache-2.0"], "max_s... |
#!/usr/bin/env ipython
import os
from pylab import *
from numpy import *
import matplotlib.patches as patches
import matplotlib.transforms as transforms
import console_colors as ccl
import numpy as np
class gral:
def __init__(self):
self.name='name'
def makefig(mc, sh, TEXT, YLIMS, YLAB, fname_fig, ftex... | {"hexsha": "c55684bfc6b69183581ef99d1594335f06435e64", "size": 8405, "ext": "py", "lang": "Python", "max_stars_repo_path": "mixed.icmes/src/mix_funcs.py", "max_stars_repo_name": "jimsrc/seatos", "max_stars_repo_head_hexsha": "e775dba1a2a96ff44b837cf8d85101ccfef302b1", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
# -*- coding: utf-8 -*-
"""
Created on Wed Mar 28 15:34:18 2012
Author: Josef Perktold
"""
from statsmodels.compatnp.py3k import BytesIO, asbytes
import numpy as np
from numpy.testing import assert_almost_equal, assert_equal
from statsmodels.stats.libqsturng import qsturng
ss = '''\
43.9 1 1
39.0 1 2
4... | {"hexsha": "133ae06beaecb774e2090211a6aa886ea9129411", "size": 8684, "ext": "py", "lang": "Python", "max_stars_repo_path": "statsmodels/stats/tests/test_pairwise.py", "max_stars_repo_name": "toobaz/statsmodels", "max_stars_repo_head_hexsha": "5286dd713a809b0630232508bf9ad5104aae1980", "max_stars_repo_licenses": ["BSD-3... |
import pytest
import numpy as np
import pandas as pd
import sys
sys.path.insert(0, '../')
from mut.io import scrape_frontmatter
def test_scrape_frontmatter():
accept_dict = {'status': 'accept', 'reason': 'test reason'}
reject_dict = {'status': 'reject', 'reason': 'test reason'}
questionable_dict = {'statu... | {"hexsha": "63912330c217f17c357db7d2bae7216fd99ae2b6", "size": 1051, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_io.py", "max_stars_repo_name": "RPGroup-PBoC/mwc_mutants", "max_stars_repo_head_hexsha": "35581602c35793fc8ec42c8aff37b8305c5e54e1", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#!/usr/bin/env python3
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from matplotlib.patches import Wedge
import cv2
import numpy as np
from utils import helpers
class Render(object):
"""
"""
def __init__(self, fig_size=(7, 7)):
fig = plt.figure(figsize=fig_size)
self.plt_ax ... | {"hexsha": "eeb7254b7d609e265324acc5ac6fff42f36ac686", "size": 4961, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/old_code_feb_12/utils/display.py", "max_stars_repo_name": "suresh-guttikonda/sim-environment", "max_stars_repo_head_hexsha": "cc8faec17714d58c0e1f0227c8b7d4cf8817a136", "max_stars_repo_license... |
[STATEMENT]
lemma merge_G_simps [simp]:
"merge_G (G\<^sub>m x) (G\<^sub>m y) = map_option G\<^sub>m (merge_F (root_hash_T rha) (merge_T rha ma) rhb mb x y)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. local.merge_G (G\<^sub>m x) (G\<^sub>m y) = map_option G\<^sub>m (merge_F (root_hash_T rha) (merge_T rha ma) rh... | {"llama_tokens": 169, "file": "ADS_Functor_Generic_ADS_Construction", "length": 1} |
import numpy as np
import unittest
from fpmlib.projections import HalfSpace, Box, Ball
from fpmlib.nonexpansive import *
class TestIntersection(unittest.TestCase):
def test_1d(self):
# p := [-1, 1]
p = Intersection([HalfSpace(np.array([1]), 1), HalfSpace(np.array([-1]), 1)])
self.assertFal... | {"hexsha": "552c062b91880157feae8dcc371b4998f4913933", "size": 3946, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_nonexpansive.py", "max_stars_repo_name": "kazh98/fpmlib", "max_stars_repo_head_hexsha": "49533953ea3305f5db7b3afe978c323ddf4ede2a", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import, division
from future.utils import viewitems
import os
import numpy as np
import matplotlib
matplotlib.use('Agg') # Run in headless mode
import matplotlib.pyplot as plt
from ..api.model import Model
_srcdir = os.path.dirname(__file__)
_outdir = os.path.... | {"hexsha": "9dc9131733a5bd7c941302eb00f3983ae8ad31ee", "size": 4819, "ext": "py", "lang": "Python", "max_stars_repo_path": "test/test_plots.py", "max_stars_repo_name": "JLTastet/scalar_portal", "max_stars_repo_head_hexsha": "8d444d72e4c5d31b237a59621935757790c5a0e7", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
"""
Particular class of small traffic network
@author: Tianshu Chu
"""
import os, sys
sys.path.append(os.path.dirname(os.path.abspath(os.path.dirname(__file__))))
import configparser
import logging
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
import t... | {"hexsha": "543cf8708cc9768db68bde9107bc2611236e071f", "size": 4462, "ext": "py", "lang": "Python", "max_stars_repo_path": "envs/test_grid_env.py", "max_stars_repo_name": "Taek111/deeprl_signal_control", "max_stars_repo_head_hexsha": "24ee6d31c1600adb040a2e872e9200937bbdacf6", "max_stars_repo_licenses": ["MIT"], "max_s... |
[STATEMENT]
lemma lists_not_empty: "lists A \<noteq> {}"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. lists A \<noteq> {}
[PROOF STEP]
using Nil_in_lists
[PROOF STATE]
proof (prove)
using this:
[] \<in> lists ?A
goal (1 subgoal):
1. lists A \<noteq> {}
[PROOF STEP]
by blast | {"llama_tokens": 123, "file": null, "length": 2} |
import pytest
import numpy as np
from Animate.Movie import Movie
from Animate.Animation import Animation
import matplotlib as mpl
def test_ratio_2():
m = Movie(dt=1.0/14, height_ratio=2)
img = np.arange(100).reshape(4, 5, 5)
m.add_image(img, style='dark_img')
a = Animation(m)
a._init_draw()
as... | {"hexsha": "cecab4b3ea21cbc33cbe1e2bce5082320952ff13", "size": 5382, "ext": "py", "lang": "Python", "max_stars_repo_path": "test/test_Animation_init.py", "max_stars_repo_name": "toddrme2178/AnimateImages", "max_stars_repo_head_hexsha": "d7a944f04d008d7ce652cfa4e6dc29cbf950b5dd", "max_stars_repo_licenses": ["MIT"], "max... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
from __future__ import absolute_import, division, print_function, unicode_literals
import abc
import numpy as np
__all__ = ['MissingDataAssociationException',
'IncompatibleUncertaintiesException', 'NDUncertainty',
'StdDevUncertain... | {"hexsha": "1f1288898c2368794013eb1a52f39e089a72a464", "size": 11388, "ext": "py", "lang": "Python", "max_stars_repo_path": "astropy/nddata/nduncertainty.py", "max_stars_repo_name": "xiaomi1122/astropy", "max_stars_repo_head_hexsha": "8876e902f5efa02a3fc27d82fe15c16001d4df5e", "max_stars_repo_licenses": ["BSD-3-Clause"... |
INTEGER FUNCTION ICBFMS ( STR, LSTR )
C$$$ SUBPROGRAM DOCUMENTATION BLOCK
C
C SUBPROGRAM: ICBFMS
C PRGMMR: J. ATOR ORG: NP12 DATE: 2012-06-07
C
C ABSTRACT: THIS FUNCTION TESTS WHETHER THE INPUT CHARACTER STRING
C IS "MISSING" BY CHECKING IF ALL OF THE EQUIVALENT BITS ARE SET TO 1.
C IT IS SIM... | {"hexsha": "9fef9c658ea26d011515657a601697de13e004c9", "size": 2023, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "extlibs/ncepBUFR/v10.2.3/icbfms.f", "max_stars_repo_name": "oxelson/gempak", "max_stars_repo_head_hexsha": "e7c477814d7084c87d3313c94e192d13d8341fa1", "max_stars_repo_licenses": ["BSD-3-Clause"], ... |
import numpy as np
from gym import spaces
from gym_cellular_automata import Operator
from gym_cellular_automata.forest_fire.utils.neighbors import neighborhood_at
class ForestFire(Operator):
grid_dependant = True
action_dependant = False
context_dependant = True
deterministic = False
def __ini... | {"hexsha": "caf0f8bd1a7f8812095fd3d6d5b9c282b21f68a0", "size": 1859, "ext": "py", "lang": "Python", "max_stars_repo_path": "gym_cellular_automata/forest_fire/operators/ca_DrosselSchwabl.py", "max_stars_repo_name": "elbecerrasoto/gym-automata", "max_stars_repo_head_hexsha": "145e9549029fe8effa827979b3f90016a681fffa", "m... |
import os
os.environ["CUDA_VISIBLE_DEVICES"] = "-1"
from tensorflow.keras.models import load_model
import numpy as np
import LowLevel_NeuralNet as llnn
import numpy_reference
import time
import csv
if __name__ == "__main__":
layers = [
llnn.Conv2d("c1", 1, 8, 3),
llnn.ReLU(),
llnn.Conv2d(... | {"hexsha": "3e83e26b921a7e1ecd182c62b39e5bfd17819c7b", "size": 2200, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/speed.py", "max_stars_repo_name": "ArthurFDLR/LowLevel_NeuralNet", "max_stars_repo_head_hexsha": "90610d521bc0b4e6623b14784e4a00d9ba4a109f", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
#! /usr/bin/env python2.7
#Socket client example in python
from __future__ import print_function
import socket #for sockets
import sys #for exit
import numpy as np
import struct
#host = '10.0.1.3';
host = '127.0.0.1'; # IP address or host name
port = 5001;
bufsize = 1000000
# from https://stackoverflow.com/q... | {"hexsha": "da13d915040c09fc1d67686a84145c72ce5ad73e", "size": 3432, "ext": "py", "lang": "Python", "max_stars_repo_path": "VizServer/PythonVizServer/tango-sound-viz-testclient.py", "max_stars_repo_name": "drscotthawley/SoundFieldsForever", "max_stars_repo_head_hexsha": "1b3d28d38bd0eedfe422349f11da39ce597f484d", "max_... |
(*
File: Moebius_Mu.thy
Author: Manuel Eberl, TU München
*)
section \<open>The M\"{o}bius $\mu$ function\<close>
theory Moebius_Mu
imports
Main
"HOL-Number_Theory.Number_Theory"
"HOL-Computational_Algebra.Squarefree"
Dirichlet_Series
Dirichlet_Misc
begin
definition moebius_mu :: "nat \<Righta... | {"author": "isabelle-prover", "repo": "mirror-afp-devel", "sha": "c84055551f07621736c3eb6a1ef4fb7e8cc57dd1", "save_path": "github-repos/isabelle/isabelle-prover-mirror-afp-devel", "path": "github-repos/isabelle/isabelle-prover-mirror-afp-devel/mirror-afp-devel-c84055551f07621736c3eb6a1ef4fb7e8cc57dd1/thys/Dirichlet_Ser... |
#define WIN32_LEAN_AND_MEAN
#include "client.h"
#include <boost/beast/core.hpp>
#include <boost/beast/http.hpp>
#include <boost/beast/version.hpp>
#include <boost/asio/connect.hpp>
#include <boost/asio/ip/tcp.hpp>
#include <boost/asio/ssl/stream.hpp>
#include <boost/asio/ssl.hpp>
#include <regex>
#include <cstdlib>
#i... | {"hexsha": "796b93b344b1b52eef7da36f6bbaa3f538e3f3b0", "size": 8518, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "httpserver/client.cpp", "max_stars_repo_name": "d3roch4/httpserver", "max_stars_repo_head_hexsha": "74c76a7decd56e1e7f9b081aab9031251eea8683", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
import os
import scipy.io
import h5py
import numpy as np
from datetime import date
from scripts.processes.CreateLonLat import CreateLonLat
from scripts.processes.PsFiles import PsFiles
from scripts.utils.ArrayUtils import ArrayUtils
from tests.MetaTestCase import MetaTestCase
class TestPsFiles(MetaTestCase):
@cl... | {"hexsha": "023b76f3b5a81ba6a36630b922efb57890bc8111", "size": 6387, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/scripts/processes/test_psFiles.py", "max_stars_repo_name": "Vants/stampsreplacer", "max_stars_repo_head_hexsha": "a61d5174e1ee1d840a327ce6ec059a3a9f84a13b", "max_stars_repo_licenses": ["MIT"... |
// Copyright Oliver Kowalke 2009.
// 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)
#ifndef BOOST_TASKS_DETAIL_WORKER_H
#define BOOST_TASKS_DETAIL_WORKER_H
#include <cstddef>
#include <utili... | {"hexsha": "a0814c7dd8adbf2290be6eac3dda7b62de98e379", "size": 5114, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "libs/boost.task/boost/task/detail/worker.hpp", "max_stars_repo_name": "ghisguth/tasks", "max_stars_repo_head_hexsha": "ce04926dbee2ab1204ed34e50dbce53f0303bde1", "max_stars_repo_licenses": ["MIT"], ... |
\section{Data Samples}
%\label{sec:datasample} % uncomment if label used.
In this analysis, the full data collected at $\sqrt{s} = 13$ TeV with the ATLAS Detector in 2015 and 2018 are used, corresponding to an integrated luminosity of 139 ~\ifb.
All datasets have been produced using Athena release 21.
\begin{itemiz... | {"hexsha": "1765115d60027328c8785eca7d096db66863e50a", "size": 4798, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "include/datasamples.tex", "max_stars_repo_name": "krybacki/IntNote2", "max_stars_repo_head_hexsha": "45b1a7d88ca7b15f19ec25270b6fbbebd839fa0b", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_... |
import os
import rnnSMAP
from rnnSMAP import runTrainLSTM
import matplotlib.pyplot as plt
import numpy as np
import imp
imp.reload(rnnSMAP)
rnnSMAP.reload()
#################################################
# intervals temporal test
doOpt = []
# doOpt.append('train')
doOpt.append('test')
# doOpt.append('plotMap')
# d... | {"hexsha": "83bcddf6e0b1308b40eaa8b7bf1a5db402f0130f", "size": 4528, "ext": "py", "lang": "Python", "max_stars_repo_path": "app/sigma/int_spatial.py", "max_stars_repo_name": "fkwai/geolearn", "max_stars_repo_head_hexsha": "30cb4353d22af5020a48100d07ab04f465a315b0", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
The Veterans Affairs Office is for veterans, reservists or dependents of a disabled or deceased veteran. They will help qualified veterans apply and receive their Montgomery G.I. Bill benefits. Students must have copies of their DD240 ready to begin the process. Beginning 2009/2010 academic year, veterans can decid... | {"hexsha": "ca6d9e139aa29c7b03d7d5e338ffdb4de08b3fc5", "size": 1268, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/Veterans_Affairs_Office.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max_... |
// Licensed to the Apache Software Foundation (ASF) under one
// or more contributor license agreements. See the NOTICE file
// distributed with this work for additional information
// regarding copyright ownership. The ASF licenses this file
// to you under the Apache License, Version 2.0 (the
// "License"); you may... | {"hexsha": "332bf69e0733ce94cace06e27721db430a5ee088", "size": 96145, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "be/src/olap/olap_table.cpp", "max_stars_repo_name": "crazyleeyang/incubator-doris", "max_stars_repo_head_hexsha": "85b4619d54ca109a6c6d49dd10541d660ad8058c", "max_stars_repo_licenses": ["Apache-2.0... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu May 13 18:06:50 2021
@author: romainloirs
"""
# ---------------------------- ML -----------------------------------
def mean_closest(stop,road_id, adj_mat, n=5):
idx = list(adj_mat.index).index(stop)
l = list(adj_mat.iloc[idx,:])
... | {"hexsha": "b2a862cffa04a709306b83152cb19aa701e1ee76", "size": 6558, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/ML.py", "max_stars_repo_name": "Rathea0286/routiiens-app", "max_stars_repo_head_hexsha": "46e9f7f14ddbf5d15743673064591aae27b26a22", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count... |
\chapter*{Acknowledgements}
\markboth{Acknowledgements}{Acknowledgements}
\addcontentsline{toc}{chapter}{Acknowledgements}
\bigskip
% put your text here
\paragraph{}
First and foremost, I would like to address my wholehearted thanks to Professor Stephan Morgenthaler who accepted to be the supervisor of my master thesi... | {"hexsha": "d5c915d2f7a1f35a90ccf12bdc8d20c2855d154f", "size": 1624, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "report/head/acknowledgements.tex", "max_stars_repo_name": "CillianMH/pdmExtremeValueTheory", "max_stars_repo_head_hexsha": "f7a7504c2eca0c6be665bcfc3d98dfee6c02de41", "max_stars_repo_licenses": ["MI... |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%% calculation of the 'epsgg' matrix for circular holes using
%%% analytical expression; the matrix is symmetric, i.e E'=E
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... | {"author": "Sable", "repo": "mcbench-benchmarks", "sha": "ba13b2f0296ef49491b95e3f984c7c41fccdb6d8", "save_path": "github-repos/MATLAB/Sable-mcbench-benchmarks", "path": "github-repos/MATLAB/Sable-mcbench-benchmarks/mcbench-benchmarks-ba13b2f0296ef49491b95e3f984c7c41fccdb6d8/22808-eigenmodes-in-a-2d-photonic-crystal/ep... |
from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Generator
import numpy as np
class DataSetElement(ABC):
@abstractmethod
def get_image(self) -> np.ndarray:
pass
@abstractmethod
def get_image_path(self) -> str:
pass
@abstractmethod
def... | {"hexsha": "174c96798cd23a008814537df195437a050e039f", "size": 585, "ext": "py", "lang": "Python", "max_stars_repo_path": "onemetric/cv/loaders/base.py", "max_stars_repo_name": "SkalskiP/onemetric", "max_stars_repo_head_hexsha": "7beb04b1372adc93723ccc8ecaeb0fdf556a2261", "max_stars_repo_licenses": ["BSD-3-Clause"], "m... |
import numpy as np
import pytest
from eddington import FittingDataError, linear, random_data
A = np.array([1, 2])
def test_residuals_data_columns_names():
data = random_data(linear, a=A)
residuals_data = data.residuals(fit_func=linear, a=A)
assert (
data.x_column == residuals_data.x_column
)... | {"hexsha": "e66e939ab514fc1cc1c6b1b7284ac78d0fb5c1c1", "size": 3170, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/fitting_data/test_residuals_fitting_data.py", "max_stars_repo_name": "EddLabs/eddington_core", "max_stars_repo_head_hexsha": "0923fc7fdf1240181554b2612a97d5708d6244bf", "max_stars_repo_licen... |
import numpy as np
from Get_global_value import num_q
from Get_global_value import J_type
from Get_global_value import Ez
from Get_global_value import BB
from Get_global_value import m0
from Get_global_value import m
from Get_global_value import mass
from Get_global_value import inertia0
from Get_global_value import in... | {"hexsha": "04eca9f1de693f58ca06a2bb173be421c8a059fb", "size": 2335, "ext": "py", "lang": "Python", "max_stars_repo_path": "calc_vel.py", "max_stars_repo_name": "lirun-sat/spacerobot_dynamics", "max_stars_repo_head_hexsha": "aaefb578cff122c2bfdf506d6a999ded26a48aae", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
import numpy as np
import os
from tensorflow.keras.layers import Dense, Input
from tensorflow.keras.models import Model
import tensorflow as tf
from spektral.layers.pooling import global_pool
from spektral.transforms.normalize_adj import NormalizeAdj
from spektral.layers import ECCConv
class PhaseModel(Model):
d... | {"hexsha": "8b2976cf4d1ca5e4431fca3e5ea5460d99acabe8", "size": 4196, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/Top2Phase/model.py", "max_stars_repo_name": "moradza/Top2Phase", "max_stars_repo_head_hexsha": "faab7a91bd2fc3b2c03a7b25280c4f1a0b285109", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
# -*- coding: utf-8 -*-
# coding=utf-8
# Copyright 2019 The SGNMT 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-2.0
#
# Unless requir... | {"hexsha": "d9a4591fea4b335fde755e6b2804c36f6e097ec7", "size": 17492, "ext": "py", "lang": "Python", "max_stars_repo_path": "cam/sgnmt/output.py", "max_stars_repo_name": "cmeister747/sgnmt", "max_stars_repo_head_hexsha": "322e217ad0d3538bf2dde12d76ea2651e85352d3", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_c... |
'''
=========================
modelr.SeismicModel.py
=========================
Container for handling seismic models.
'''
from modelr.constants import WAVELETS, wavelet_duration,\
REFLECTION_MODELS
import numpy as np
from modelr.web.urlargparse import SendHelp, ArgumentError, \
URLArgumentParser
from agileg... | {"hexsha": "8f0ca681048b5939e00669544ddd6b2fdcb7f027", "size": 3275, "ext": "py", "lang": "Python", "max_stars_repo_path": "modelr/SeismicModel.py", "max_stars_repo_name": "ben-bougher/modelr", "max_stars_repo_head_hexsha": "2a3ad38285bad24f5aa05f3ecc4e976dd3147da9", "max_stars_repo_licenses": ["Apache-2.0"], "max_star... |
# -*- coding: utf-8 -*-
# BioSTEAM: The Biorefinery Simulation and Techno-Economic Analysis Modules
# Copyright (C) 2020-2021, Yoel Cortes-Pena <yoelcortes@gmail.com>
#
# This module is under the UIUC open-source license. See
# github.com/BioSTEAMDevelopmentGroup/biosteam/blob/master/LICENSE.txt
# for license details... | {"hexsha": "d5edbbd09afbf08597032a138c9ff2edfbeb5c5a", "size": 16583, "ext": "py", "lang": "Python", "max_stars_repo_path": "biosteam/evaluation/_state.py", "max_stars_repo_name": "BioSTEAMDevelopmentGroup/biosteam", "max_stars_repo_head_hexsha": "cc34afdb3b1f57c615c661a642f8f953dbeef744", "max_stars_repo_licenses": ["... |
import nevergrad as ng
import numpy as np
def optimize_params(optim_name, loss_func, num_params, init_values, max_iters, num_workers=1, bounds=None, popsize=None):
parametrization = ng.p.Array(init=init_values)
if bounds is not None:
parametrization.set_bounds(lower=bounds[:, 0], upper=bounds[:, 1])
... | {"hexsha": "2ae186babad5522c71d67cea4e7cbc8f97f2e99a", "size": 1428, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/grad_free_util.py", "max_stars_repo_name": "eanswer/DiffHand", "max_stars_repo_head_hexsha": "d7b9c068b7fa364935f3dc9d964d63e1e3a774c8", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
from flask import Flask, render_template, url_for, flash, redirect
from form import RegistrationForm, LoginForm, BookForm, UploadBook, Contact, DeleteBook
from recomm import recom
from flask_sqlalchemy import SQLAlchemy
from PIL import Image
import os
import pandas as pd
import numpy as np
from flask_table impo... | {"hexsha": "e36686e40bbc42d7213b5dd43cf50d25b18da7df", "size": 4569, "ext": "py", "lang": "Python", "max_stars_repo_path": "fl/main.py", "max_stars_repo_name": "SahilkK/Book_Recommender_System", "max_stars_repo_head_hexsha": "0471a43ca86d59b3cd373426b570172ddacd9a79", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
import numpy as np
import matplotlib.pyplot as plt
from pynwb.ophys import RoiResponseSeries, DfOverF, PlaneSegmentation, TwoPhotonSeries, ImageSegmentation
from pynwb.base import NWBDataInterface
from ndx_grayscalevolume import GrayscaleVolume
from .utils.cmaps import linear_transfer_function
from .utils.dynamictable ... | {"hexsha": "336a3d47ac1c65113f008cf4ff4ab40a0acf0995", "size": 7206, "ext": "py", "lang": "Python", "max_stars_repo_path": "nwbwidgets/ophys.py", "max_stars_repo_name": "d-sot/nwb-jupyter-widgets", "max_stars_repo_head_hexsha": "f9bf5c036c39f29e26b3cdb78198cccfa1b13cef", "max_stars_repo_licenses": ["BSD-3-Clause-LBNL"]... |
include 'fac.f'
c
program test
c
c Exercise A, section 11.
c Main program to test factorial function.
c
integer n, fac
10 continue
write(*,*) 'Give n: '
read (*,*) n
if (n.gt.0) then
write(*,*) n, ' factorial is', fac(n)
goto 10
endif
c End of ... | {"hexsha": "b920b3473804f81d0f7d9afd3ea243e33d94dc0a", "size": 347, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "test_fac.f", "max_stars_repo_name": "JONGHOKim-Raphael/fff", "max_stars_repo_head_hexsha": "bd0c3df4e7a5bcf072b5a28cb7ed46052b2dddd1", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "... |
# The following contains just abstract types regarding models and "virtual" method
#The most basic type, needed in order to support DifferentialEquations.jl
abstract type BaseProcess{T <: Number} end
# There will inherit from this type just processes, i.e. models that know what is a zeroCurve and a divided
abstract t... | {"hexsha": "592e27c9776fa4cae4a5f1cc21e9fcfc0249d520", "size": 3502, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/models/base_models.jl", "max_stars_repo_name": "rcalxrc08/FinancialMonteCarlo.jl", "max_stars_repo_head_hexsha": "3c7444414ea3a449d3aeb48c182d4c05b37c31b4", "max_stars_repo_licenses": ["MIT"], ... |
```python
from sympy import *
import numpy as np
from matplotlib import pyplot as plt
x = Symbol('x')
# Function
y = x**2
# First derivative with respect to x
yprime = y.diff(x)
# Initial sequence
theta = 2
theta2 = 0
# Initiale the step size
alpha = .001
iterations = 0
check = 0
precision = 1/100000
iterationsMa... | {"hexsha": "0361b23a28d37973896a1d899b465b06865f3814", "size": 16402, "ext": "ipynb", "lang": "Jupyter Notebook", "max_stars_repo_path": "NotesAndTutorials/Gradient_univ.ipynb", "max_stars_repo_name": "ChristopherDaigle/ConvexOptimizationWithPython", "max_stars_repo_head_hexsha": "b7a1b5126b076d06ec03e906b19930bf324272... |
import warnings
import numpy as np
import nengo
from nengo.dists import Choice, Uniform
from nengo.networks.ensemblearray import EnsembleArray
from nengo.solvers import NnlsL2nz
from nengo.utils.stdlib import nested
# connection weights from (Gurney, Prescott, & Redgrave, 2001)
class Weights(object):
mm = 1
... | {"hexsha": "0faadeb78d306c6e44410490ce8734d7a44a3b9a", "size": 6950, "ext": "py", "lang": "Python", "max_stars_repo_path": "nengo/networks/actionselection.py", "max_stars_repo_name": "hunse/nengo", "max_stars_repo_head_hexsha": "5fcd7b18aa9496e5c47c38c6408430cd9f68a720", "max_stars_repo_licenses": ["BSD-2-Clause"], "ma... |
import keras
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from keras import initializers
from keras.datasets import mnist
from utils import (
compile_model,
create_mlp_model,
get_activations,
grid_axes_it,
)
seed = 10
# Number of points to plot
n_train... | {"hexsha": "4ee71209fba925be373c8ae508bb1c0432d8dda5", "size": 2444, "ext": "py", "lang": "Python", "max_stars_repo_path": "articles/neural-network-initialization/plot-activation-layers.py", "max_stars_repo_name": "sangaline/intoli-article-materials", "max_stars_repo_head_hexsha": "b01010ddc769ac20ce492bce478ee49c859c5... |
[STATEMENT]
lemma execlass_leq_code: "class_leq (set cs) c1 c2 = execlass_leq cs c1 c2"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. class_leq (set cs) c1 c2 = execlass_leq cs c1 c2
[PROOF STEP]
by (simp add: class_leq_def class_les_def member_def) | {"llama_tokens": 109, "file": "Metalogic_ProofChecker_CheckerExe", "length": 1} |
# coding: utf-8
import numpy as np
import pandas as pd
# import matplotlib.pyplot as plt
## user
# 读取user -> feature选择 -> 缺失值填充 -> 对性别编码 -> 归一化
users = pd.read_csv('data/users.csv', sep=',')
user_features = ["RESPID","GENDER","AGE","Q1","Q2","Q3","Q4","Q5","Q6","Q7","Q8","Q9","Q10","Q11","Q12","Q13","Q14","Q15","Q16",... | {"hexsha": "9bffef5fe1703099d08485bf7b347861e75940a1", "size": 3552, "ext": "py", "lang": "Python", "max_stars_repo_path": "kaggle/EMI_music/main.py", "max_stars_repo_name": "JayMiao/MLAction", "max_stars_repo_head_hexsha": "fec1c08fa33ed1f5d9b0befecc6dac551cc02302", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
# Copyright (c) 2018 Pablo Moreno-Munoz
# Universidad Carlos III de Madrid and University of Sheffield
import sys
import numpy as np
import GPy
from GPy.inference.latent_function_inference import LatentFunctionInference
from GPy.inference.latent_function_inference.posterior import Posterior
from GPy.util import choles... | {"hexsha": "c5a1693228c6510b23ef3d6f2c2a790e36385c86", "size": 10160, "ext": "py", "lang": "Python", "max_stars_repo_path": "hetmogp/svmogp_inf.py", "max_stars_repo_name": "skitimoon/HetMOGP", "max_stars_repo_head_hexsha": "85307629a54b70026fbbbccd66c54c9d739173b4", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
import numpy as np
from numpy.testing import *
import skimage.graph.mcp as mcp
a = np.ones((8, 8), dtype=np.float32)
a[1:-1, 1] = 0
a[1, 1:-1] = 0
## array([[ 1., 1., 1., 1., 1., 1., 1., 1.],
## [ 1., 0., 0., 0., 0., 0., 0., 1.],
## [ 1., 0., 1., 1., 1., 1., 1., 1.],
## [ 1.... | {"hexsha": "e3fd45a0aef1a565bc105927a122e123a2a524fc", "size": 5853, "ext": "py", "lang": "Python", "max_stars_repo_path": "skimage/graph/tests/test_mcp.py", "max_stars_repo_name": "RKDSOne/scikit-image", "max_stars_repo_head_hexsha": "baa67eafcace9cde1b94ad2d467e2f2e0468e759", "max_stars_repo_licenses": ["BSD-3-Clause... |
// ====================================================================================
// Copyright (c) 2012, ioriiod0@gmail.com All rights reserved.
// File : timer.hpp
// Author : ioriiod0@gmail.com
// Last Change : 11/19/2012 04:15 PM
// Description :
// ============================================... | {"hexsha": "5968c518004144489df613fc9c4daf95c38c8cd8", "size": 1904, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "orchid/asio/timer.hpp", "max_stars_repo_name": "ioriiod0/orchid", "max_stars_repo_head_hexsha": "347cec6a2b882b8b9c34b83fda360db9dd60bc11", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 68.... |
/*
* Copyright (c) 2017 Cryptonomex, Inc., and contributors.
*
* The 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, including without limitation the... | {"hexsha": "8b0f0c591b14373a6be73ab2cceb43ce94c81ff3", "size": 97456, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "libraries/app/database_api.cpp", "max_stars_repo_name": "citshares/citshares", "max_stars_repo_head_hexsha": "5fa121d9c6b582158cc043fda93862440515c925", "max_stars_repo_licenses": ["MIT"], "max_sta... |
#include <iostream>
#include <vector>
#include <map>
#include <numeric>
#include <Eigen/Dense>
using HouseProperties = std::map<std::string, double>;
struct House
{
double price;
HouseProperties properties;
};
struct Model
{
double constant;
std::map<std::string, double> coefs;
Model() : const... | {"hexsha": "4d74bad09e29651950e1fe62cbc95c02385396c3", "size": 8990, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "LinearRegression/main.cpp", "max_stars_repo_name": "alxbilger/machinelearningeducation", "max_stars_repo_head_hexsha": "38107124a77506ef5232f054660b1249795807d0", "max_stars_repo_licenses": ["MIT"],... |
from pathlib import Path, PurePosixPath
import networkx
import pytest
from fsspec.implementations.http import HTTPFileSystem
from fsspec.implementations.local import LocalFileSystem
from gcsfs import GCSFileSystem
from s3fs.core import S3FileSystem
from kedro.extras.datasets.networkx import GraphMLDataSet
from kedro.... | {"hexsha": "226f92f4f11c8fe7869026ff51b08bcfca5492bf", "size": 7369, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/extras/datasets/networkx/test_graphml_dataset.py", "max_stars_repo_name": "Mu-L/kedro", "max_stars_repo_head_hexsha": "a925fd59187a642e124527f0f1097e92ea8d1819", "max_stars_repo_licenses": [... |
import os, re
import numpy as np
import pandas as pd
from metrics import MetricsAccumulator
class Disaggregator():
def __init__(self,
EVALUATION_DATA_PATH,
TARGET_APPLIANCE,
ON_POWER_THRESHOLD,
MAX_TARGET_POWER,
disagg_func,
... | {"hexsha": "6a80c1c1c9555e5a9357ed150ab777c987d053e7", "size": 10194, "ext": "py", "lang": "Python", "max_stars_repo_path": "disaggregator.py", "max_stars_repo_name": "KaibinBao/neuralnilm-pytorch", "max_stars_repo_head_hexsha": "017b85fc921f0638f93a0e16f615028f60b7d279", "max_stars_repo_licenses": ["Apache-2.0"], "max... |
# generate toy events
# generate 1D gaussians for input features
# we also test event number functionality needed for ATLAS reweighting
import csv
import numpy as np
def make_sample(mu=0.,sigma=1.,nevents=1000,start_eventnumber=1):
s = np.random.normal(mu, sigma, nevents)
# toy event index:
enum = np.aran... | {"hexsha": "79b9c8015165a67a9347c92d4d15ffc6151ab22f", "size": 1405, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/inputs/generate_inputs.py", "max_stars_repo_name": "lmijovic/carl-torch", "max_stars_repo_head_hexsha": "bd4e483b3c6a3685a874ba9c33d4dd5be524627d", "max_stars_repo_licenses": ["MIT"], "max_s... |
import numpy as np
from icdar21_mapseg_eval.point_detection import eval_pt_detect
radius_limit = 118
ground_truth = np.float32([
[5710, 1170], # A
[8080, 1170], # B
[3330, 3530], # C
[5710, 3550], # D
[8085, 3540], # E
[3327, 5922], # F
[5715, 5940], # G
[8085, 5942]]) # H
pre... | {"hexsha": "7938d82847077878d032fd158efb67a9258cdf3a", "size": 3230, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_point_detection.py", "max_stars_repo_name": "soduco/icdar21-mapseg-eval", "max_stars_repo_head_hexsha": "4186395828b5cf16a136f2cea2f946984d062791", "max_stars_repo_licenses": ["MIT"], "... |
import os
import numpy as np
import mujoco_py
import matplotlib as mpl
mpl.use('Qt4Agg')
import matplotlib.pyplot as plt
model_path = os.path.join('..','gym_kuka_mujoco','envs','assets', 'full_kuka_mesh_collision.xml')
model = mujoco_py.load_model_from_path(model_path)
# model.integrator = 0
sim = mujoco_py.MjSim(mode... | {"hexsha": "d6a0ae43b0ee02a9bf6d9d1ecb06054302917331", "size": 2405, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/attic/kuka_model_pd_controller.py", "max_stars_repo_name": "leonmkim/gym-kuka-mujoco", "max_stars_repo_head_hexsha": "ed45ae74d10e69f4e51439de2d1d0c0811623b6b", "max_stars_repo_licenses":... |
export Freeflyer
# Parameters from:
# asl_free_flyer/free_flyer_node/param/robots/enterprise.yaml
# asl_free_flyer/free_flyer_control/src/waypoint_py_controller/parameters.py
# tribal knowledge
mutable struct Freeflyer{T<:AbstractFloat} <: Robot
mass_ff_min::T
mass_ff_max::T
mass_ff::T
J_ff::T
J_ff_inv::T
... | {"hexsha": "cc617e4e1a3d6502774dbf636dba297bb0edf6b1", "size": 1927, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/robot/freeflyer.jl", "max_stars_repo_name": "schoelst/GuSTO.jl", "max_stars_repo_head_hexsha": "b5753959c2e232c4e91be3e73ec4a81470c703b1", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
using Pkg
Pkg.add("StatsBase")
Pkg.add("HDF5")
Pkg.add("DataStructures")
Pkg.add("NearestNeighbors")
Pkg.add("JSON")
Pkg.add("Serialization")
Pkg.add("CSV")
Pkg.add("DataFrames")
| {"hexsha": "1711964215d4d066751f977bd11048dc1dfc5639", "size": 180, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "traj_er/t2vec_experience/pkg-install.jl", "max_stars_repo_name": "lzzppp/DERT", "max_stars_repo_head_hexsha": "e1f9ee2489f76e2ed741d6637fd2b1e8bb225fb6", "max_stars_repo_licenses": ["MIT"], "max_sta... |
# fig_ggn_hyperpolarization.py ---
# Author: Subhasis Ray
# Created: Tue Feb 12 14:53:34 2019 (-0500)
# Last-Updated: Tue Feb 12 15:37:32 2019 (-0500)
# By: Subhasis Ray
# Version: $Id$
# Code:
"""Supplementary figures showing GGN hyperpolarization when PN->KC
connection is not clustered"""
from __futur... | {"hexsha": "2912310c29d7b17be3b5efa38a4c2837ab1ebdf2", "size": 2237, "ext": "py", "lang": "Python", "max_stars_repo_path": "analysis/fig_ggn_hyperpolarization.py", "max_stars_repo_name": "subhacom/mbnet", "max_stars_repo_head_hexsha": "b0ab55079ed31614f923ee15ed65defae156332b", "max_stars_repo_licenses": ["Unlicense"],... |
# This file is a part of BAT.jl, licensed under the MIT License (MIT).
# TODO: add plot without Int for overview?
function plothistogram(h::StatsBase.Histogram, swap::Bool)
if swap
return h.weights, h.edges[1][1:end-1]
else
return h.edges[1][1:end-1], h.weights
end
end
@recipe function f... | {"hexsha": "1a0c4820cee016cc364806d4ed45a6918f86574b", "size": 3906, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/plotting/recipes_MarginalDist_1D.jl", "max_stars_repo_name": "Micki-D/BAT.jl", "max_stars_repo_head_hexsha": "15e470654de300eb99f5b9f5a864764f59ac74db", "max_stars_repo_licenses": ["MIT"], "max... |
import numpy as np
from optimizer import Optimizer
class Dfp(Optimizer):
"""
Davidon–Fletcher–Powell algorithm. See
https://arxiv.org/pdf/2004.14866.pdf
for a convergence proof and see
https://en.wikipedia.org/wiki/Davidon-Fletcher-Powell_formula
for a general description.
Ar... | {"hexsha": "275b21590b0c98385da8fc77a380cbdf95eb8a6d", "size": 2063, "ext": "py", "lang": "Python", "max_stars_repo_path": "quasi_newton/dfp.py", "max_stars_repo_name": "konstmish/opt_methods", "max_stars_repo_head_hexsha": "ae73d9bd89ae5c463e70328d73cbd190175df98c", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import unicode_literals, print_function
from math import log10
from time import time
import networkx as nx
from config import DATA_PATH
from util import dump_json, read_json
def make_edge_trace():
edge_trace = {
"x": [],
"y": [],
... | {"hexsha": "05334acf9a2f63cc22121fac477481e000fb9a55", "size": 3758, "ext": "py", "lang": "Python", "max_stars_repo_path": "genre_dag/plot.py", "max_stars_repo_name": "ribbas/music-genre-nw", "max_stars_repo_head_hexsha": "fb6aea2d8cff59d32525b2b4434caf77b6b60079", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
# by Lazaro Alonso
using CairoMakie
let
x = 0:0.05:4π
fig = Figure(resolution = (600,400), font = "CMU Serif") # probably you need to install this font in your system
ax = Axis(fig, xlabel = L"x", ylabel = L"f (x)", ylabelsize = 22,
xlabelsize= 22, xgridstyle=:dash, ygridstyle=:dash, xtickalign =... | {"hexsha": "eec0b43463372a02c6a4d0b1dc924cff93170d3a", "size": 909, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "_assets/scripts/latexSample/latexSample.jl", "max_stars_repo_name": "MisterBiggs/BeautifulMakie", "max_stars_repo_head_hexsha": "5e43819d1f2af8b80bf45895bc117cd55197d972", "max_stars_repo_licenses":... |
[STATEMENT]
lemma rel_spmf_eqI [simp]: "rel_spmf (=) x x"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. rel_spmf (=) x x
[PROOF STEP]
by(simp add: option.rel_eq) | {"llama_tokens": 81, "file": "CryptHOL_Misc_CryptHOL", "length": 1} |
/-
Copyright (c) 2017 Microsoft Corporation. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johannes Hölzl, Mario Carneiro, Oliver Nash
-/
import data.finset.basic
/-!
# Finsets in product types
This file defines finset constructions on the product type `α × β`. Bewa... | {"author": "jjaassoonn", "repo": "projective_space", "sha": "11fe19fe9d7991a272e7a40be4b6ad9b0c10c7ce", "save_path": "github-repos/lean/jjaassoonn-projective_space", "path": "github-repos/lean/jjaassoonn-projective_space/projective_space-11fe19fe9d7991a272e7a40be4b6ad9b0c10c7ce/src/data/finset/prod.lean"} |
[STATEMENT]
lemma NE_intT_forget: "NE (intT \<sigma>)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<exists>a. intT \<sigma> a
[PROOF STEP]
proof-
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. \<exists>a. intT \<sigma> a
[PROOF STEP]
obtain b where b: "eintT \<sigma> b"
[PROOF STATE]
proof (prove)
goal (1 sub... | {"llama_tokens": 6418, "file": "Sort_Encodings_T", "length": 76} |
## Conversion
"""
Convert a domain object to a domain object with the given element type `T`.
"""
convert_domain(::Type{T}, d::Domain{T}) where {T} = d
convert_domain(::Type{T}, d::Domain{S}) where {S,T} = convert(Domain{T}, d)
convert_domain(::Type{T}, d) where {T} = _convert_domain(T, d, eltype(d))
_convert_domain... | {"hexsha": "5575e7fe497a4f3747a36084aff7c5c5695a5d9e", "size": 1360, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/generic/promotion.jl", "max_stars_repo_name": "UnofficialJuliaMirrorSnapshots/DomainSets.jl-5b8099bc-c8ec-5219-889f-1d9e522a28bf", "max_stars_repo_head_hexsha": "8caa1870145e15e07abeda96ffe8408... |
"""
Source: https://github.com/JBlumstein/NYCParking/blob/master/NYC_Parking_Violations_Mapping_Example.ipynb
NYC parking ticket violations
Usage:
mpiexec -n [cores] python nyc-parking.py
Data for 2016 and 2017 is in S3 bucket (s3://bodo-examples-data/nyc-parking-tickets)
or you can get data from https://www.k... | {"hexsha": "8f432f656684d4dd82b36b737471d84aeec65606", "size": 6153, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/nyc-parking/nyc-parking.py", "max_stars_repo_name": "prutskov/Bodo-examples", "max_stars_repo_head_hexsha": "7c96e89f3ac9062eb598b99da2729718007b8e4d", "max_stars_repo_licenses": ["Apache... |
"""Utilities for BERT trainer."""
import functools
from typing import Any, Dict, Tuple, Optional, Mapping, Union, List
from absl import logging
from clu import metric_writers
import flax
from flax import jax_utils
import flax.linen as nn
import jax
import jax.numpy as jnp
import jax.profiler
import ml_collections
imp... | {"hexsha": "7ffccb9ba5dc2de61cd0dab29d8b8be83d2195b5", "size": 13605, "ext": "py", "lang": "Python", "max_stars_repo_path": "scenic/projects/baselines/bert/train_utils.py", "max_stars_repo_name": "techthiyanes/scenic", "max_stars_repo_head_hexsha": "05585b1189364e29d82413b9d4a50ffa8c246f0c", "max_stars_repo_licenses": ... |
\section{Evalutation}
This final sections acts as an evaluation of the success of the Taxicoin project, both as a protocol and an implementation.
\subsection{Completeness of Requirements}
While Taxicoin does have defined behaviour for all perceived \enquote{normal} behaviours of drivers and riders, it is difficult t... | {"hexsha": "adf3381315534d01e1c228a7b16d6782351f8de5", "size": 7767, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "docs/tex/evaluation.tex", "max_stars_repo_name": "sprusr/taxicoin", "max_stars_repo_head_hexsha": "3f0fd26841992aa47d5e4f6fce56de4b56452f30", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 3... |
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""
Detection Training Script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is made to train standard models in detectron2.
In order to let one script support training of many models,
this s... | {"hexsha": "dee7a9ba203c3650d26b4671873fedc246ae734a", "size": 35651, "ext": "py", "lang": "Python", "max_stars_repo_path": "tools/train_net.py", "max_stars_repo_name": "quangvy2703/ABCNet-ESRGAN-SRTEXT", "max_stars_repo_head_hexsha": "952c3c3b4df9f974ddc09ec6d613c302d66a3a57", "max_stars_repo_licenses": ["BSD-2-Clause... |
record R : Set₁ where
field
⟨_+_⟩ : Set
open R
-- Name parts coming from projections can not be used as part of
-- variables.
F : Set → Set
F + = +
| {"hexsha": "6b5d74906bf1525e78827d4e05267f9309f25f5f", "size": 157, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "test/Fail/Issue3400-3.agda", "max_stars_repo_name": "cruhland/agda", "max_stars_repo_head_hexsha": "7f58030124fa99dfbf8db376659416f3ad8384de", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
"""
This is a script to convert the predictions to regions
-------------------------------------
Author: Sushanth Kathirvelu
"""
import json
import matplotlib.pyplot as plt
from numpy import array, zeros
import numpy as np
from scipy.misc import imread, imsave
from PIL import Image
mask = Image.open('../../training_ma... | {"hexsha": "e4450edfc9b1370d383981f5201879e14eefe613", "size": 685, "ext": "py", "lang": "Python", "max_stars_repo_path": "exploration/regions.py", "max_stars_repo_name": "dsp-uga/team-coombs", "max_stars_repo_head_hexsha": "bcf875e03b2b8986a6361cb9606059e75af3df51", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
"""
Python code for rank aggregation, for both full and partial lists. For methods/algorithms
I have followed the paper
"Rank aggregation methods for the web" (2001) C. Dwork, R. Kumar, M. Naor, D. Sivakumar.
Proceedings of the 10th international conference on World Wide Web.
Created May 22, 2015
@author: Kevin S. ... | {"hexsha": "36ace85d3d41b200a1274c63f01915d0638e1b32", "size": 24386, "ext": "py", "lang": "Python", "max_stars_repo_path": "rankagg.py", "max_stars_repo_name": "thelahunginjeet/pyrankagg", "max_stars_repo_head_hexsha": "8eb68eda46059c3ae1780e5672d198731889c547", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_... |
import csv
import os.path
import numpy as np
import pandas as pd
COLUMNS = {
'txNomeParlamentar': 'congressperson_name',
'ideCadastro': 'congressperson_id',
'nuCarteiraParlamentar': 'congressperson_document',
'nuLegislatura': 'term',
'sgUF': 'state',
'sgPartido': 'party',
'codLegislatura'... | {"hexsha": "4eae6d504385c22917a5dd630396d7e12b7f5d00", "size": 5324, "ext": "py", "lang": "Python", "max_stars_repo_path": "serenata_toolbox/chamber_of_deputies/reimbursements_cleaner.py", "max_stars_repo_name": "luizfzs/serenata-toolbox", "max_stars_repo_head_hexsha": "73efa9401cb562be2b8f7df74b49aee25727e181", "max_s... |
/*
* FieldManagerLIst.cpp
*
* Created on: Oct 26, 2012
* Author: "James C. Sutherland"
*
* Copyright (c) 2012-2017 The University of Utah
*
* 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 ... | {"hexsha": "8e48676e5ef6028aaed036cda96596035910f8a1", "size": 4538, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "expression/FieldManagerList.cpp", "max_stars_repo_name": "MaxZZG/ExprLib", "max_stars_repo_head_hexsha": "c35e361ef6af365e7cd6afca6548595693bd149a", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
using Combinatorics
# Part 1
# Load input
expenses = open("day01_input.txt") do f
[parse(Int32, line) for line in eachline(f)]
end
# See which pair sum to 2020 and multiply them
for (value1, value2) in combinations(expenses, 2)
if value1 + value2 == 2020
println("Product of $value1 and $value2: $(valu... | {"hexsha": "d86f8f89acc869659f57bedc47afea10847f3a5b", "size": 529, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "2020/day01.jl", "max_stars_repo_name": "ericgreveson/adventofcode", "max_stars_repo_head_hexsha": "6671ef8c16a837f697bb3fb91004d1bd892814ba", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_co... |
import logging
import multiprocessing
import pickle
import warnings
from abc import ABCMeta, abstractmethod
from concurrent.futures.process import ProcessPoolExecutor
from dataclasses import asdict, dataclass, is_dataclass
from itertools import chain
from math import isclose
from pathlib import Path
from typing import ... | {"hexsha": "e03eb4476f08f0c0c1fa69c10bb6b4ef700aaadb", "size": 30871, "ext": "py", "lang": "Python", "max_stars_repo_path": "lhotse/features/base.py", "max_stars_repo_name": "jtrmal/lhotse", "max_stars_repo_head_hexsha": "db9f42bd9171616f92c41f4d9a56b29998c9dedf", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_c... |
[STATEMENT]
lemma path_connected_Iio[simp]: "path_connected {..<a}" for a :: real
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. path_connected {..<a}
[PROOF STEP]
by (simp add: convex_imp_path_connected) | {"llama_tokens": 82, "file": null, "length": 1} |
module trigd
implicit none
contains
function sind(x)
real*4 sind, x, pi180_sp
pi180_sp=2.0e0 * asin(1.0e0) / 180.0e0
sind = sin(pi180_sp * x)
end function sind
function dsind(x)
real*8 dsind, x, pi180_dp
pi180_dp=2.0d0 * asin(1.0d0) / 180.... | {"hexsha": "6bc3f16b51619653673d7175dbd41b22376049ef", "size": 1472, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "bin/db/dbmoment/DREGERS_MTPACKAGE/mtmanip_module.f", "max_stars_repo_name": "jreyes1108/antelope_contrib", "max_stars_repo_head_hexsha": "be2354605d8463d6067029eb16464a0bf432a41b", "max_stars_repo... |
[STATEMENT]
lemma (in Module) gen_mHom_eq:"\<lbrakk>R module N; generator R M H; f \<in> mHom R M N;
g \<in> mHom R M N; \<forall>h\<in>H. f h = g h \<rbrakk> \<Longrightarrow> f = g"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>R module N; generator R M H; f \<in> mHom R M N; g \<in> mHom R M N; \... | {"llama_tokens": 9110, "file": "Group-Ring-Module_Algebra8", "length": 22} |
from cdlib import BiNodeClustering
import networkx as nx
from cdlib.utils import convert_graph_formats
__all__ = ['bimlpa']
def bimlpa(g, theta=0.3, lambd=7):
"""
BiMLPA is designed to detect the many-to-many correspondence community in bipartite networks using multi-label propagation algorithm.
:para... | {"hexsha": "c18728b590cc4429d58b1d764269cc2385b21294", "size": 1310, "ext": "py", "lang": "Python", "max_stars_repo_path": "cdlib/algorithms/biparitte_clustering.py", "max_stars_repo_name": "deklanw/cdlib", "max_stars_repo_head_hexsha": "cc2d5da032842882e530ac1b9038db07d1293526", "max_stars_repo_licenses": ["BSD-2-Clau... |
import re
import torch
from torch import nn
import os
from .ELMoForManyLangs import elmo
from .postprocessing import _run_word_segmentation_with_dictionary, construct_dictionary
import numpy as np
import math
import json
def sort_list(li, piv=2,unsort_ind=None):
ind = []
if unsort_ind == None:
... | {"hexsha": "261bc6faf444146641834446828696e9c4ed232d", "size": 11559, "ext": "py", "lang": "Python", "max_stars_repo_path": "pywordseg/pywordseg.py", "max_stars_repo_name": "berzi/pywordseg", "max_stars_repo_head_hexsha": "df8e0dc76ddfcca46ce416ae377009a95df9c27f", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
import numpy as np
import torch
from scipy.integrate import quad
from scipy.stats import norm, lognorm
from abc import ABC, abstractmethod
def bs_binary_aon(spot, strike, expiry, r, sigma):
"""Computes the true value of a binary asset-or-nothing option under Black-Scholes assumptions
:param spot: float
... | {"hexsha": "5226c6c4a211ecbdcf7360a1fee7bb9e40128bfd", "size": 7188, "ext": "py", "lang": "Python", "max_stars_repo_path": "sde_mc/options.py", "max_stars_repo_name": "Piers14/sde_mc", "max_stars_repo_head_hexsha": "0bdab1fe39667b36516d5543d0d7099466ba90b9", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "ma... |
from __future__ import print_function
from __future__ import division
import numpy as np
from matplotlib import pyplot as plt
def vote_peaks(signal, filter_size=1,passes=2,threshold=.8):
"""
Input:
signal : dictionary, contains two_theta, d_spacings, and input_vector arrays
p... | {"hexsha": "980004880a73b14320d0b904c2fb328ff2eec44b", "size": 3839, "ext": "py", "lang": "Python", "max_stars_repo_path": "PeakFinding.py", "max_stars_repo_name": "MatthewGong/DiffractionClassification", "max_stars_repo_head_hexsha": "68be6cf3960f09388253c79bab13cbd9dc07edbb", "max_stars_repo_licenses": ["MIT"], "max_... |
!
! Copyright (C) 2013, Northwestern University and Argonne National Laboratory
! See COPYRIGHT notice in top-level directory.
!
! This is part of the PnetCDF package.
!
! $Id: f90tst_parallel3.f90 2512 2016-09-29 01:29:37Z wkliao $
! This program tests PnetCDF parallel I/O from
! fortran. It creates... | {"hexsha": "8d622a69e67eefac933eb48be9484714ab02bee5", "size": 7295, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "tests/libs/pnetcdf/tests/f90tst_parallel3.f90", "max_stars_repo_name": "utdsimmons/ohpc", "max_stars_repo_head_hexsha": "70dc728926a835ba049ddd3f4627ef08db7c95a0", "max_stars_repo_licenses": ["A... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.