text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
|---|---|
import sm
import aslam_backend as aopt
import aslam_cv as cv
import kalibr_camera_calibration as kcc
import numpy as np
import collections
import igraph
import itertools
import sys
import pylab as pl
try:
from PIL import Image # Modern
except ImportError:
import Image # Old import (backward compatibility)
im... | {"hexsha": "c4b60a817ee95890fc95d9c828aa20849a54d935", "size": 13258, "ext": "py", "lang": "Python", "max_stars_repo_path": "aslam_offline_calibration/kalibr/python/kalibr_camera_calibration/MulticamGraph.py", "max_stars_repo_name": "chengfzy/kalibr", "max_stars_repo_head_hexsha": "fe9705b380b160dc939607135f7d30efa64ea... |
#Circular view
from dna_features_viewer import BiopythonTranslator, CircularGraphicRecord
import matplotlib.pyplot as plt
from dna_features_viewer import BiopythonTranslator
from Bio import SeqIO
import numpy as np
from svglib.svglib import svg2rlg
from reportlab.graphics import renderPM
#Class that only labels regul... | {"hexsha": "b7dc239e6e2c1a53915fa79d837d4b53b99ee3c2", "size": 1653, "ext": "py", "lang": "Python", "max_stars_repo_path": "Archive/CircularView.py", "max_stars_repo_name": "DrValkaryon/BIOT-670-Spring2020-GenBank", "max_stars_repo_head_hexsha": "ab76a30e272f6647128e89657a39037000cd069e", "max_stars_repo_licenses": ["M... |
include("..\\libs\\FunctionsRobot.jl")
function putmarker!(robot::CoordsRobot)
x, y = get_xy(get_coords(robot))
if x - y <= 0
putmarker!(get_robot(robot))
end
end
function lestnizaWithPartitions!(r::Robot)
back_path = BackPath(r)
R = CoordsRobot(r)
marks!(R)
BackPath(R)
back!(... | {"hexsha": "b731096f1853d68c5a5f3f11f88ec93747057a9f", "size": 337, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "task_17/task_17.jl", "max_stars_repo_name": "Droideka501/mirea-progs", "max_stars_repo_head_hexsha": "5f96fda66e296f33b1cd9018a11467e4c568c709", "max_stars_repo_licenses": ["BSD-2-Clause"], "max_sta... |
import networkx as nx
import pandas as pd
from matplotlib import pyplot as plt
from networkx.generators.ego import ego_graph
from pyvis.network import Network
from sklearn.decomposition import PCA
def plot_network_with_edge_weights(G, figsize=(10, 10)):
elarge = [(u, v) for (u, v, d) in G.edges(data=True) if (d["... | {"hexsha": "6d09009b3ae72bf84b969eb05bf19b445dd19c05", "size": 3867, "ext": "py", "lang": "Python", "max_stars_repo_path": "vis/visualize.py", "max_stars_repo_name": "ryankarlos/networks_algos", "max_stars_repo_head_hexsha": "170f796635b7ff6a7ead07d767d8f5ba27ff7237", "max_stars_repo_licenses": ["FTL"], "max_stars_coun... |
"""
TODO: This really needs a rewrite, this was copied of working jupyter notebooks to get a working implementation of the recommender
"""
import sqlite3
import pickle
import torch
import numpy as np
import pandas as pd
from functools import partial
from glob import glob
from fastai.collab import *
from fastai.tabul... | {"hexsha": "f2265a0994e46b1ef759063c3364cd977429c322", "size": 7663, "ext": "py", "lang": "Python", "max_stars_repo_path": "server/recommender.py", "max_stars_repo_name": "KshitijKarthick/animewreck", "max_stars_repo_head_hexsha": "494ac6ae3eb21c6c7641a51e368dc72b5d1279c5", "max_stars_repo_licenses": ["MIT"], "max_star... |
from ..visualization.Viewer import Viewer
import numpy as np
import copy
from ..utils import Observer, Subject, IO, ObservableArray
class PointCloud(Observer, Subject):
"""
This class represent a Point Cloud.
Parameters:
vertices (np.array nx3): vertices of the point cloud
"""
... | {"hexsha": "7a13102585421e4f27c4c94af58062ef7a1cd3f9", "size": 1354, "ext": "py", "lang": "Python", "max_stars_repo_path": "Py3DViewer/structures/Pointcloud.py", "max_stars_repo_name": "alexus98/py3DViewer", "max_stars_repo_head_hexsha": "693d39db8956530aa89cea5bbf271d9b6a92bd79", "max_stars_repo_licenses": ["MIT"], "m... |
[STATEMENT]
lemma no_loose_bvar_subst_bvs1'_unchanged: "\<not> loose_bvar t lev \<Longrightarrow> subst_bvs1' t lev args = t"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<not> loose_bvar t lev \<Longrightarrow> subst_bvs1' t lev args = t
[PROOF STEP]
by (induction t lev args rule: subst_bvs1'.induct) auto | {"llama_tokens": 122, "file": "Metalogic_ProofChecker_BetaNorm", "length": 1} |
from functional import seq
import numpy as np
import torch
from safe_explorer.core.config import Config
from safe_explorer.env.ballnd import BallND
from safe_explorer.env.spaceship import Spaceship
from safe_explorer.ddpg.actor import Actor
from safe_explorer.ddpg.critic import Critic
from safe_explorer.ddpg.ddpg impo... | {"hexsha": "5876df33e9755b4d2808c15f74b06ccbd1a092ea", "size": 2480, "ext": "py", "lang": "Python", "max_stars_repo_path": "safe_explorer/main.py", "max_stars_repo_name": "ahalev/beta_mapping", "max_stars_repo_head_hexsha": "ebb2130ade2a2b8e288235e87e3112bea691b9e0", "max_stars_repo_licenses": ["Apache-2.0"], "max_star... |
# coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | {"hexsha": "4395b954b32b36d492d210242c9e4c28f10e26c0", "size": 8843, "ext": "py", "lang": "Python", "max_stars_repo_path": "aloe/aloe/fuzz/main_varlen.py", "max_stars_repo_name": "muell-monster/google-research", "max_stars_repo_head_hexsha": "04d2024f4723bc4be3d639a668c19fb1f6a31478", "max_stars_repo_licenses": ["Apach... |
MU Bus Area Phone #1 on the Campus Payphones node
Phone Number: (530) 7569903
Location: This phone sits in the bus stop area of the Memorial Union.
Description: This beautiful Britishstyle phone sits surrounded by a cozy patch of grass. Buses whirl by, taking students to and from Campus as you chat away. Perfec... | {"hexsha": "205971da3162a2bab9df654c6569914d084e7705", "size": 1321, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/MU_Bus_Phone_1.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
\paragraph{Communities of Skin}
The limit of the database, as performative, spectral skin, allows for a community to emerge between the human and the nonhuman. This means that the agency locus of the database needs to be placed precisely on its skin. In other words, given that this skin is available to the perception o... | {"hexsha": "f16a0f2e08471fd27deb62ef90403074497c18a8", "size": 2631, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "content/part-3/section-6/sub/limits.tex", "max_stars_repo_name": "fdch/database_music", "max_stars_repo_head_hexsha": "a42332d3551d42856bf102a00ea84bb4c924a86b", "max_stars_repo_licenses": ["FSFAP"]... |
import unittest
import numpy as np
from neuroga.fitness_function import FitnessFunction, FitnessFunctionType
from neuroga.genome import Genome
from neuroga.nsga_ii import NSGAII
from neuroga.subgenomes.real_number import RealNumber
from neuroga.subgenomes.real_number_sequence import RealNumberSequence
from neuroga.su... | {"hexsha": "972b70a11d0361b93a0a7c725a78ca9bebac19da", "size": 2547, "ext": "py", "lang": "Python", "max_stars_repo_path": "neuroga/tests/test_subegnome_crash.py", "max_stars_repo_name": "mnjirjak/NeuroGA", "max_stars_repo_head_hexsha": "98159fc9cadf6f49bc760e0bbac8530779e7659b", "max_stars_repo_licenses": ["Apache-2.0... |
import numpy as np
from sklearn.impute import SimpleImputer
from sklearn.linear_model import LogisticRegressionCV as Classifier
from sklearn.pipeline import make_union, make_pipeline
from suricate.preutils.functionclassifier import FunctionClassifier
from suricate.dftransformers import VectorizerConnector, ExactConnec... | {"hexsha": "8589b47c70667c284879a461b17ec5a5f460d48b", "size": 3556, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/pipeindexer/test_DfModel.py", "max_stars_repo_name": "ogierpaul/suricate", "max_stars_repo_head_hexsha": "fd43627e5d2a92fe4bf7b562f65ab89ec07ee49c", "max_stars_repo_licenses": ["MIT"], "max_... |
# -*- coding: utf-8 -*-
#
# Copyright (c) 2017, the cclib development team
#
# This file is part of cclib (http://cclib.github.io) and is distributed under
# the terms of the BSD 3-Clause License.
"""Parser for Q-Chem output files"""
from __future__ import division
from __future__ import print_function
import iterto... | {"hexsha": "13af72c55ceb5f89d6b008c92ec7eed01698d81f", "size": 77891, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/cclib/parser/qchemparser.py", "max_stars_repo_name": "maxscheurer/cclib", "max_stars_repo_head_hexsha": "722a8b534686465d4e3ae57b8dd285a56f197e4a", "max_stars_repo_licenses": ["BSD-3-Clause"]... |
import numpy as np
import matplotlib.pyplot as plt
import scipy as sp
import pandas as pd
from active_learning_cfd.cfd_regressor import load_regression_history_repetitions
from active_learning_cfd.error_measures import calculate_error, mean_relative_error
case_name = "mixer"
reference_filename = "reference_solution.... | {"hexsha": "2a0c0676ee7ef0d6e1661c4184fdd1bbecd419ca", "size": 3958, "ext": "py", "lang": "Python", "max_stars_repo_path": "cases/mixer3D/mixer_error_table.py", "max_stars_repo_name": "ImperialCollegeLondon/al_cfd_benchmark", "max_stars_repo_head_hexsha": "03b51d7e7d4def804e2ac18084deee8401636851", "max_stars_repo_lice... |
[STATEMENT]
lemma ma_is_rat: "is_rat (real_of x) = ma_is_rat x"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. is_rat (real_of x) = ma_is_rat x
[PROOF STEP]
proof (transfer, unfold is_rat_def, clarsimp)
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. \<And>p q ba. q = 0 \<or> ba \<in> sqrt_irrat \<Longrightarrow> ... | {"llama_tokens": 3316, "file": "Real_Impl_Real_Impl", "length": 30} |
-- ---------------------------------------------------------------------
-- Ejercicio. Demostrar que
-- (P → Q) ↔ ¬ P ∨ Q
-- ----------------------------------------------------------------------
import tactic
open_locale classical
-- 1ª demostración
-- ===============
example
(P Q : Prop)
: (P → Q) ↔ ¬ P... | {"author": "jaalonso", "repo": "Matematicas_en_Lean", "sha": "c44e23d87665cb4aa00c813c6bfb3c41ebc83aa8", "save_path": "github-repos/lean/jaalonso-Matematicas_en_Lean", "path": "github-repos/lean/jaalonso-Matematicas_en_Lean/Matematicas_en_Lean-c44e23d87665cb4aa00c813c6bfb3c41ebc83aa8/src/Logica/Implicacion_mediante_dis... |
!-------------------------------------------------------------------------------
!> module ATMOSPHERE / Physics Cloud Microphysics / SDM
!!
!! @par Description
!! Covert super-droplets to fluid variables
!!
!! - Reference
!! - Shima et al., 2009:
!! The super-droplet method for the numerical simulation of ... | {"hexsha": "9796e865c65d6c2034daa9bc06836fd85ca104b5", "size": 20996, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "contrib/SDM/sdm_sd2fluid.f90", "max_stars_repo_name": "Shima-Lab/SCALE-SDM_BOMEX_Sato2018", "max_stars_repo_head_hexsha": "6d7f66f36d00b64df0b93088eba8fe38a1bb1926", "max_stars_repo_licenses": ... |
# This file defines the 7 tetrominoes
# I O J L S Z T
#
# Shapes: https://tetris.fandom.com/wiki/SRS
import copy
import abc
import numpy as np
_SHAPES_I = np.array([
[(1, 0), (1, 1), (1, 2), (1, 3)],
[(0, 2), (1, 2), (2, 2), (3, 2)],
[(2, 0), (2, 1), (2, 2), (2, 3)],
[(0, 1), (1, 1), (2, 1), (3, 1)],
], dty... | {"hexsha": "a467e8353b647de9aed8aab7b01553b8ef930376", "size": 6324, "ext": "py", "lang": "Python", "max_stars_repo_path": "shape.py", "max_stars_repo_name": "wenlianglaw/Tetris-in-Python", "max_stars_repo_head_hexsha": "d4f0a22c4827e7eeb44c55def3f024e0c6932ebe", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1... |
[STATEMENT]
lemma Im_sgn [simp]: "Im(sgn z) = Im(z)/cmod z"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. Im (sgn z) = Im z / cmod z
[PROOF STEP]
by (simp add: complex_sgn_def divide_inverse) | {"llama_tokens": 91, "file": null, "length": 1} |
[STATEMENT]
lemma dg_prod_2_is_arrI'[dg_prod_cs_intros]:
assumes "gf = [g, f]\<^sub>\<circ>"
and "ab = [a, b]\<^sub>\<circ>"
and "cd = [c, d]\<^sub>\<circ>"
and "g : a \<mapsto>\<^bsub>\<AA>\<^esub> c"
and "f : b \<mapsto>\<^bsub>\<BB>\<^esub> d"
shows "gf : ab \<mapsto>\<^bsub>\<AA> \<times>\<^sub... | {"llama_tokens": 473, "file": "CZH_Foundations_czh_digraphs_CZH_DG_PDigraph", "length": 3} |
import math
import numpy as np
import tensorflow as tf
def msra_stddev(x, k_h, k_w):
return 1/math.sqrt(0.5*k_w*k_h*x.get_shape().as_list()[-1])
def mse_ignore_nans(preds, targets, **kwargs):
#Computes mse, ignores targets which are NANs
# replace nans in the target with corresponding preds, so tha... | {"hexsha": "e88d59aff820801d9b98c4ec7a6ebde020571f5b", "size": 2896, "ext": "py", "lang": "Python", "max_stars_repo_path": "DFP/tf_ops.py", "max_stars_repo_name": "Andres-c-Diaz/DirectFuturePrediction", "max_stars_repo_head_hexsha": "85430fbd4ec64970d2ab71e33680a91dea396263", "max_stars_repo_licenses": ["MIT"], "max_st... |
#! /usr/bin/env python
from numpy import random
import os
import argparse
class options():
def __init__(self):
parser = argparse.ArgumentParser(description='writes a file consisting of distance measurements with a gaussian distributed erro')
parser.add_argument('--distance', '-d', dest='distance', ... | {"hexsha": "b28b7c2c2a613d9480c7fd0a96768c0251addf4a", "size": 2733, "ext": "py", "lang": "Python", "max_stars_repo_path": "inputDataCreationTool/inputDistanceCreationTool.py", "max_stars_repo_name": "cwma86/KalmanFilter", "max_stars_repo_head_hexsha": "d2db8184d4d3f3ea45889d35128e225061d167dc", "max_stars_repo_license... |
# -*- coding:utf-8 -*-
from __future__ import division
import random
import cv2
import os
import re
import numpy as np
import pandas as pd
from nltk.corpus import stopwords
import keras.backend as K
from scipy import interp
from time import sleep
from matplotlib import pyplot as plt
from sklearn.metrics import accuracy... | {"hexsha": "c79e2c6a127e185071914fbded1ea29e20ec45a1", "size": 16381, "ext": "py", "lang": "Python", "max_stars_repo_path": "text_classification_keras.py", "max_stars_repo_name": "ohquai/Text_duplicate_abcnn", "max_stars_repo_head_hexsha": "abab90aa9bc30ac709df4ae383deac6ab1c5abb4", "max_stars_repo_licenses": ["MIT"], ... |
import properties
import numpy as np
from ... import survey
from ...utils.code_utils import deprecate_class
class Point(survey.BaseRx):
"""
Magnetic point receiver class for integral formulation
:param numpy.ndarray locs: receiver locations index (ie. :code:`np.c_[ind_1, ind_2, ...]`)
:param string c... | {"hexsha": "4af4c14df141a28d7cd9a3c6e21c2157fcbf75ed", "size": 1815, "ext": "py", "lang": "Python", "max_stars_repo_path": "SimPEG/potential_fields/magnetics/receivers.py", "max_stars_repo_name": "Prithwijit-Chak/simpeg", "max_stars_repo_head_hexsha": "d93145d768b5512621cdd75566b4a8175fee9ed3", "max_stars_repo_licenses... |
import numpy as np
import pandas as pd
from candidate_handler import candidates_update
#interdependent modules, it has to be imported like below,otherwise it wont work
import solver as solver
from cells_seen import cells_seen
import itertools
#%% Simple Colouring (Singles Chains)
# finds and returns conjugate pairs (s... | {"hexsha": "253f576fa0691a25f8f65c5cb9929be8e3a16bcd", "size": 9687, "ext": "py", "lang": "Python", "max_stars_repo_path": "singles_chains.py", "max_stars_repo_name": "shariarriday/Sudoku-Solver-Thesis", "max_stars_repo_head_hexsha": "8e9fad163daf50d1e96a82c5bd831b639d7bfac6", "max_stars_repo_licenses": ["MIT"], "max_s... |
\section{Conclusions}
%Answer to the final question:
The whole chapter focused on building a list of requirements, designing a system, implementing it and validating the work done. All to answer the question: \textit{"Is it possible to build a feasible architectural design, by using such a tool, to implement all th... | {"hexsha": "263f4c5e3d6da88dc5eea88a54d2d97b93df5428", "size": 2056, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "Documents/prototype/prototypeconclusion.tex", "max_stars_repo_name": "coletiv/supplychain-composer-thesis", "max_stars_repo_head_hexsha": "a212134246e6d5c3ea578f5633c0ce04af4c1069", "max_stars_repo_... |
(* Title: HOL/ex/Adhoc_Overloading_Examples.thy
Author: Christian Sternagel
*)
section \<open>Ad Hoc Overloading\<close>
theory Adhoc_Overloading_Examples
imports
Main
"~~/src/HOL/Library/Infinite_Set"
"~~/src/Tools/Adhoc_Overloading"
begin
text \<open>Adhoc overloading allows to overload a const... | {"author": "SEL4PROJ", "repo": "jormungand", "sha": "bad97f9817b4034cd705cd295a1f86af880a7631", "save_path": "github-repos/isabelle/SEL4PROJ-jormungand", "path": "github-repos/isabelle/SEL4PROJ-jormungand/jormungand-bad97f9817b4034cd705cd295a1f86af880a7631/case_study/isabelle/src/HOL/ex/Adhoc_Overloading_Examples.thy"} |
module SSPS
using Gen
using GLMNet
using ArgParse
using JSON
export julia_main
include("dbn_preprocess.jl")
include("dbn_models.jl")
include("dbn_proposals.jl")
include("mcmc_inference.jl")
include("state_updates.jl")
@load_generated_functions()
"""
Given the results of a previous run, recover the
state of the ... | {"hexsha": "17b4aed8757c775cb1de1ffcdc5b25165a8b7be7", "size": 7462, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "SSPS/src/SSPS.jl", "max_stars_repo_name": "gitter-lab/ssps", "max_stars_repo_head_hexsha": "8557cb1961bcd951c5f78102070925e945567600", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 14, "ma... |
import argparse
import json
import logging
import os
from itertools import islice
import numpy as np
from sklearn.metrics import ndcg_score
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument(
'--predict-result',
help='The predict result for the evaluating data.'... | {"hexsha": "cb547296230925cccb5bdc08506683eb6f0ce1f4", "size": 2408, "ext": "py", "lang": "Python", "max_stars_repo_path": "azureml/components/evaluate/evaluate.py", "max_stars_repo_name": "ltxtech/lightgbm-transform", "max_stars_repo_head_hexsha": "ca3bdaae4e594c1bf74503c5ec151f2b794f855c", "max_stars_repo_licenses": ... |
# -*- coding: utf-8 -*-
"""
Copyright 2020 DR ROBIN RAFFE PRYCE JONES
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 re... | {"hexsha": "2277e8f52a95ab90cf89cc3d1ecd0e137f996890", "size": 2878, "ext": "py", "lang": "Python", "max_stars_repo_path": "CustomLib/Funcs.py", "max_stars_repo_name": "rxj879/Box_Up_Surface", "max_stars_repo_head_hexsha": "15f508df4394f1d2c26cdfb3c5924cfa8cc50161", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
[STATEMENT]
lemma bound_of_const[simp, intro]:
"bound_of (\<lambda>x. c) = (c::real)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. bound_of (\<lambda>x. c) = c
[PROOF STEP]
unfolding bound_of_def
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (SUP x. c) = c
[PROOF STEP]
by(intro antisym cSup_least cSup_upper ... | {"llama_tokens": 159, "file": "pGCL_Expectations", "length": 2} |
# -*- coding: utf-8 -*-
import os
import json
import re
import logging
import numpy as np
logging.basicConfig(level=logging.INFO) # ,format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def get_voacb(file_path):
w_freq = {}
with open(file_path, 'r', encoding='ut... | {"hexsha": "d965b4d5fbcded249b1998a0f5712cacf7019cbc", "size": 1994, "ext": "py", "lang": "Python", "max_stars_repo_path": "data_processing/collect_intents.py", "max_stars_repo_name": "luckyRookies/slot_filling_and_intent_detection_of_SLU", "max_stars_repo_head_hexsha": "b68f5a79ae627521ca940689c5f898844d976f5d", "max_... |
\subsection*{Code Listings}
\addcontentsline{toc}{subsection}{Code Listings}
The code listings have not been included to save printing. However, the full source code may be found attached, or alternatively is freely available under the MIT software license at \url{https://github.com/sprusr/taxicoin/}.
%\subsubsection... | {"hexsha": "ddc0f4e253246da62df99d5c93ecd576d34d6e50", "size": 661, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "docs/tex/appendix/code-listings.tex", "max_stars_repo_name": "sprusr/taxicoin", "max_stars_repo_head_hexsha": "3f0fd26841992aa47d5e4f6fce56de4b56452f30", "max_stars_repo_licenses": ["MIT"], "max_star... |
#MERCURY 1
import logging
import pandas as pd
import sys
import numpy as np
from ta import *
from feature_selector import FeatureSelector
from sklearn.preprocessing import StandardScaler, OneHotEncoder
from sklearn.model_selection import train_test_split
logging.basicConfig(level=logging.DEBUG,format='%(asctime)s-%(pr... | {"hexsha": "2be40ff4b74e889b35589bb7d66313ed9e2c13b0", "size": 7395, "ext": "py", "lang": "Python", "max_stars_repo_path": "data_loader/data_loader.py", "max_stars_repo_name": "tinkermachine/Mercury", "max_stars_repo_head_hexsha": "16c4b1ae2c3568e9d54d91d4308c5e4d33a36e0c", "max_stars_repo_licenses": ["Apache-2.0"], "m... |
# Implementation of the show function for Model, Kpoints, PlaneWaveBasis
# to avoid clutter in their respective files. For "shorter" files
# (e.g. elements.jl, Energies.jl) the preference is still to keep
# show in the same file to avoid forgetting to add a print statement
# for an added field.
function Base.show(io::... | {"hexsha": "befbeeb7e2dd53a71fa84125547e3dba93f2bd5f", "size": 3022, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/show.jl", "max_stars_repo_name": "chemicalfiend/DFTK.jl", "max_stars_repo_head_hexsha": "757122b9e23ddefda9dae59c175a4260c81c8836", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "ma... |
#include <boost/mpl/aux_/preprocessed/msvc60/greater.hpp>
| {"hexsha": "9eeedd2d6b07e12db6ebf9e6e648ab29cf6ef1b9", "size": 58, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/boost_mpl_aux__preprocessed_msvc60_greater.hpp", "max_stars_repo_name": "miathedev/BoostForArduino", "max_stars_repo_head_hexsha": "919621dcd0c157094bed4df752b583ba6ea6409e", "max_stars_repo_licen... |
import os, pickle
import matplotlib.pyplot as pl
import matplotlib.dates as mdates
import scipy as sp
import mpl_toolkits.basemap as bm
dsetname='merra'
varname='SLP'
indname='nao'
path=os.environ['NOBACKUP']+'/verification/'+dsetname
indfile=path+'/data/'+varname+'_'+indname+'.dat'
indpic=path+'/pics/'+varname+'_'+in... | {"hexsha": "e086ee0135d1265b34c22b9c77629d9010aa3f30", "size": 1837, "ext": "py", "lang": "Python", "max_stars_repo_path": "GEOS_Util/coupled_diagnostics/verification/merra/nao_plots.py", "max_stars_repo_name": "GEOS-ESM/GMAO_Shared", "max_stars_repo_head_hexsha": "022af23abbc7883891006b57379be96d9a50df23", "max_stars_... |
#if !defined(BOOST_PP_IS_ITERATING)
///// header body
#ifndef BOOST_MPL_APPLY_WRAP_HPP_INCLUDED
#define BOOST_MPL_APPLY_WRAP_HPP_INCLUDED
// Copyright Aleksey Gurtovoy 2000-2004
//
// Distributed under the Boost Software License, Version 1.0.
// (See accompanying file LICENSE_1_0.txt or copy at
// htt... | {"hexsha": "ede272a116dcc1ad83a77d7aeae57cb09732b2e0", "size": 5508, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "windows/include/boost/mpl/apply_wrap.hpp", "max_stars_repo_name": "jaredhoberock/gotham", "max_stars_repo_head_hexsha": "e3551cc355646530574d086d7cc2b82e41e8f798", "max_stars_repo_licenses": ["Apach... |
# Copyright (C) 2016-2021 Alibaba Group Holding Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable l... | {"hexsha": "98400e35df23fa18c3230bd4b2ee6ce3cf4030e0", "size": 3308, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/hyperml/data_utils.py", "max_stars_repo_name": "jiakai0419/Curvature-Learning-Framework", "max_stars_repo_head_hexsha": "f90165660ff321172bd7ab7da0e7fe2b3abcb70e", "max_stars_repo_license... |
//
// Least-recently used (LRU) queue device
// Clients and workers are shown here in-process
//
// NOTICE: increase file open limitation
// if increasing clients or workers.
#include <functional>
#include <iostream>
#include <memory>
#include <queue>
#include <string>
#include <vector>
#include <boost/asi... | {"hexsha": "81278c6863adc638ad82b9b3222efcf36928f627", "size": 7124, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "example/lbbroker.cpp", "max_stars_repo_name": "yayj/asio-zmq", "max_stars_repo_head_hexsha": "ec161333e26ce53ea0ea75cce74388997cdb43b3", "max_stars_repo_licenses": ["BSD-2-Clause"], "max_stars_count... |
import os
from pathlib import Path
import tweepy
import csv
import numpy as np
import pandas as pd
import io
def lambda_handler(event, context):
url = 'https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv'
df = pd.read_csv(url, usecols=['total_vaccinations', 'to... | {"hexsha": "563b19ede8ff5693d084a3cb6035bcb539f12191", "size": 1173, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/lambda_function.py", "max_stars_repo_name": "lastnameswayne/twittervaccinebot", "max_stars_repo_head_hexsha": "a9725f1a13d9a6fbd8023d0da853c4eda690f9ea", "max_stars_repo_licenses": ["MIT"], "m... |
from pysabr import hagan_2002_lognormal_sabr as sabr
import pytest
import numpy as np
def test_lognormal_beta_05():
s = 3 / 100
k = 3.02715567337258000 / 100
f = 2.52715567337258000 / 100
t = 10.00000000000000000
alpha = 0.0252982247897366000
beta = 0.5000000000000000000
rho = ... | {"hexsha": "14767b8513227ebde62061f206d039f01feb0b06", "size": 1799, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/hagan_2002_lognormal_sabr/test_interpolation.py", "max_stars_repo_name": "v-tsepelev/pysabr", "max_stars_repo_head_hexsha": "be22436625f4c0b605f362444b7aafeecda15959", "max_stars_repo_licens... |
from pathlib import Path
import shutil
import numpy as np
from ibllib.dsp.voltage import decompress_destripe_cbin
from ibllib.ephys import neuropixel
from ibllib.io import spikeglx
from ibllib.dsp.voltage import destripe
from ibllib.dsp.utils import rms
import detect.detector
from detect.run import run
APPLY_NN = F... | {"hexsha": "4deb6015e14fc507a05c597ab6865db6a8dfe5d2", "size": 2657, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/ibl_np1/00_detection.py", "max_stars_repo_name": "int-brain-lab/spikes", "max_stars_repo_head_hexsha": "bc557fa5024e8eedc60b7369dba12121df56d3be", "max_stars_repo_licenses": ["MIT"], "max... |
let S = ZZ{BigInt}, P = S[:x], x = P([0, 1])
@testset "construction of quotient ring" begin
ideal = x^2 + 1
@test P / ideal <: Quotient{P}
@test P / (x^3+1) <: Quotient{P}
Q = P / ideal
Qp = P / (x^3+1)
@test basetype(Q) == P
@test depth(Q) == 3
@test P / ideal != nothing
p = 4x +... | {"hexsha": "ba26fc1d23508d89b865e19424dde2b24ebd4f18", "size": 1418, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/quotient.jl", "max_stars_repo_name": "KlausC/CommutativeRings.jl", "max_stars_repo_head_hexsha": "2b6027c126b90f61bbad4ea230a34367522c3e52", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
import numpy as np
from ._skimage import *
from ._linalg import hessian_eigval
__all__ = ["binary_erosion",
"erosion"
"binary_dilation",
"dilation",
"binary_opening",
"opening",
"binary_closing",
"closing",
"gaussian... | {"hexsha": "52310e040c2547c4cafb1ab163ab6325cf6379ae", "size": 5171, "ext": "py", "lang": "Python", "max_stars_repo_path": "impy/arrays/utils/_filters.py", "max_stars_repo_name": "hanjinliu/impy", "max_stars_repo_head_hexsha": "d35b21be7739c3073ae87486673af68b1cdb2853", "max_stars_repo_licenses": ["BSD-3-Clause"], "max... |
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 28 08:48:41 2018
@author: mrestrepo
"""
import os
import time
import math
import pickle
import tensorflow as tf
import cv2
import numpy as np
from hashlib import md5
# import architectures as arch
from tensorflow.contrib.layers import flatten, variance_scaling_initial... | {"hexsha": "8b1d31e2e64315cd084c4af673b6bd4ecb090adf", "size": 15962, "ext": "py", "lang": "Python", "max_stars_repo_path": "ros/src/tl_detector/light_classification/helpers.py", "max_stars_repo_name": "cuckookernel/CarND-Final-Project", "max_stars_repo_head_hexsha": "37399514dfbe2a97c784013645394f3cbbb51408", "max_sta... |
from unittest import TestCase
import numpy as np
import pandas as pd
from pandas_ml_utils.model.features_and_labels.features_and_labels import FeaturesAndLabels
from pandas_ml_utils.model.features_and_labels.features_and_labels_extractor import FeatureTargetLabelExtractor
DF = pd.DataFrame({"a": [1,2,3,4,5],
... | {"hexsha": "6cdea700992c8ec913a43896aa348abc18d1ec41", "size": 2386, "ext": "py", "lang": "Python", "max_stars_repo_path": "test/unit_tests/model/test__features_and_labels_extraction.py", "max_stars_repo_name": "KIC/pandas_utils", "max_stars_repo_head_hexsha": "76b764e2f87c2e9bcee9a62cfe0b54e7fb046034", "max_stars_repo... |
import pandas as pd
import numpy as np
from scipy.stats import pearsonr, spearmanr
'''这两个暂时不管'''
def BANCHMARKINDEXCLOSE():
return np.nan
def BANCHMARKINDEXOPEN():
return np.nan
#RET,DTM和DBM我就直接在ipython notebook中定义过了
'''
def RET_func(CLOSE):
#here I first use forwardfill then backfill to fill the NAN value... | {"hexsha": "20cfcbd5d484be74fcc42c2eb385077e73cbe816", "size": 8494, "ext": "py", "lang": "Python", "max_stars_repo_path": "BTC_Alpha_func.py", "max_stars_repo_name": "chenhq/Data-Mining-on-BTC-Trading-Statistics", "max_stars_repo_head_hexsha": "f221e72a0551c77b3ab2dcb6c4448d0c743b54cc", "max_stars_repo_licenses": ["MI... |
! -*- f90 -*-
!###############################################################
!! SUBROUTINE TO COMPUTE THE KURTOSIS OF AN ARRAY
!###############################################################
subroutine kurtosis(a,nx,ny,nz,krt)
integer, intent(in) :: nx, ny, nz
double precision, intent(out):: krt
double p... | {"hexsha": "6e698a94093f385f13b12cc900584528a1bb93d3", "size": 2816, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "Analysis/Simulations/OLLibs/F90/kurtosis.f90", "max_stars_repo_name": "ahmadryan/TurbAn", "max_stars_repo_head_hexsha": "b8866d103a2ca2f5fbad73bcd4416f19299f22b2", "max_stars_repo_licenses": ["B... |
# Copyright (C) Huangying Zhan 2019. All rights reserved.
import copy
from matplotlib import pyplot as plt
import numpy as np
import os
from glob import glob
def scale_lse_solver(X, Y):
"""Least-sqaure-error solver
Compute optimal scaling factor so that s(X)-Y is minimum
Args:
X (KxN array): curr... | {"hexsha": "35dad7a66908f42460619dc543887cdb943f6eb6", "size": 23065, "ext": "py", "lang": "Python", "max_stars_repo_path": "kitti_odometry.py", "max_stars_repo_name": "nikola3794/kitti-odom-eval", "max_stars_repo_head_hexsha": "c808874dc18db3b60b8c711e55546f09af553659", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
C LAST UPDATE 27/01/97
C+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
C
SUBROUTINE FIBGEN(DMIN,DMAX)
IMPLICIT NONE
C
C Purpose: Generates Bragg-sampling points for fibre patterns.
C
C Calls 2: DRAGON , RECTOFF
C Called by: GUIFIX
C
C-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+... | {"hexsha": "6e8b03e3cd08f0cec201c2d3807f8035e69d742f", "size": 3441, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "software/guifix/FIBGEN.f", "max_stars_repo_name": "scattering-central/CCP13", "max_stars_repo_head_hexsha": "e78440d34d0ac80d2294b131ca17dddcf7505b01", "max_stars_repo_licenses": ["BSD-3-Clause"],... |
import sys,re
import numpy
from bisect import bisect_left
def MAF_chunks(source,ref,species=[]):
def var_parse(line):
d = {}
for m in re.finditer(r'(\S+)=(\S+)',line):
k,v = m.groups()
d[k] = v
return d
maf_dict = {}
comments = []
class MAFBloc... | {"hexsha": "d4b1486106234b83f7ea625ba658ea7f1d6597e3", "size": 7096, "ext": "py", "lang": "Python", "max_stars_repo_path": "io/maf.py", "max_stars_repo_name": "rajewsky-lab/byo", "max_stars_repo_head_hexsha": "188e7e24ddfb9d00370338c0a011391d90a6eaf2", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "max_star... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Aug 4 13:59:02 2019
@author: TempestGuerra
"""
import math as mt
import numpy as np
import bottleneck as bn
# This approach blends by maximum residuals on each variable
def computeResidualViscCoeffs(RES, QM, VFLW, DX, DZ, DXD, DZD, DX2, DZ2):
... | {"hexsha": "4fc9dd396fe3b8d56ced459667532203c4742b8b", "size": 1642, "ext": "py", "lang": "Python", "max_stars_repo_path": "computeResidualViscCoeffs.py", "max_stars_repo_name": "jeguerra/nonlinearMtnWavesSolver", "max_stars_repo_head_hexsha": "e2fe83d1f7c3c57cbe9ba0299a1b9179cf4b5869", "max_stars_repo_licenses": ["MIT... |
from pathlib import Path as path
base = str(path(__file__).resolve().parent.parent)
def area(aux_catalog_fname, dest="../data/output/"):
"""Computes the area of the SeaFlux grid cells"""
import xarray as xr
from fetch_data import read_catalog
from ..area import get_area_from_dataset
from .util... | {"hexsha": "ace0f2d6aba15e13fd05bdfe27c040ddd951bb45", "size": 6928, "ext": "py", "lang": "Python", "max_stars_repo_path": "pyseaflux/data/aux_vars.py", "max_stars_repo_name": "sckw/pySeaFlux", "max_stars_repo_head_hexsha": "ab125f72f8f0fb2d1b627b4dd229f8744e916120", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Jun 30 13:16:49 2017
@author: mmrosek
"""
import matplotlib.patches as mpatches
import numpy as np
import matplotlib.pyplot as plt
from sklearn.preprocessing import normalize, scale
from matplotlib.backends.backend_pdf import PdfPages
import operator
fr... | {"hexsha": "aefeab2cdd11dc61e723cf39511535c20b9a9bfc", "size": 7035, "ext": "py", "lang": "Python", "max_stars_repo_path": "Miscellaneous/plot_frag_collapse_ranks.py", "max_stars_repo_name": "mmrosek/Listeria-Mitochondria-Fragmentation", "max_stars_repo_head_hexsha": "d0702f202bf4abe90aa8d3b5b7fd66bf71d3ae7b", "max_sta... |
#!/usr/bin/env python
# encoding: utf-8
"""
=================================================
The python version implementation
"Combining Sketch and Tone for Pencil Drawing Production"
Cewu Lu, Li Xu, Jiaya Jia
International Symposium on Non-Photorealistic Animation and Rendering
(NPAR 2012), June, 2012
===========... | {"hexsha": "07b3d6d8264bdb912010d16dd80702c8af983d5e", "size": 7687, "ext": "py", "lang": "Python", "max_stars_repo_path": "pencil.py", "max_stars_repo_name": "duduainankai/pencil-python", "max_stars_repo_head_hexsha": "88fd04c80d1725acec891850adb81367ce6d2bcf", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 12... |
% BEGIN LICENSE BLOCK
% Version: CMPL 1.1
%
% The contents of this file are subject to the Cisco-style Mozilla Public
% License Version 1.1 (the "License"); you may not use this file except
% in compliance with the License. You may obtain a copy of the License
% at www.eclipse-clp.org/license.
%
% Software distribute... | {"hexsha": "63fc9902615ec4fb3519f43809bb2e177c955b54", "size": 9144, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "usr/eclipseclp/documents/libman/eplexdiff.tex", "max_stars_repo_name": "lambdaxymox/barrelfish", "max_stars_repo_head_hexsha": "06a9f54721a8d96874a8939d8973178a562c342f", "max_stars_repo_licenses": ... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#HW3 for EECS 598 Motion Planning
import time
import openravepy
import userdefined as us
import numpy as np
import kdtree
import transformationFunction as tf
from random import randrange
#### YOUR IMPORTS GO HERE ####
handles = [];
#### END OF YOUR IMPORTS ####
if no... | {"hexsha": "042d638eda0cefefccfb9e7e82e9896bfff4eb72", "size": 5213, "ext": "py", "lang": "Python", "max_stars_repo_path": "paperVersion/TestUpdateFunction.py", "max_stars_repo_name": "willsirius/DualTreeRRTStartMotionPlanning", "max_stars_repo_head_hexsha": "d3e6d2ec0cd7c38379d5b0ff42924b7216bd29cd", "max_stars_repo_l... |
! THIS VERSION: GALAHAD 2.1 - 22/03/2007 AT 09:00 GMT.
PROGRAM GALAHAD_WCP_test_deck
USE GALAHAD_QPT_double
USE GALAHAD_WCP_double ! double precision version
IMPLICIT NONE
INTEGER, PARAMETER :: wp = KIND( 1.0D+0 ) ! set precision
REAL ( KIND = wp ), PARAMETER :: infty = 10.0_wp *... | {"hexsha": "9db132862648f2e56469456b894d4f42e25bb85b", "size": 20889, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "legacy_fortran/galahad-2.3/src/wcp/wcpt.f90", "max_stars_repo_name": "dynamics-of-stellar-systems/dynamite_release", "max_stars_repo_head_hexsha": "a921d8a1bde98f48daeea78213fb17b3edb223bb", "m... |
# --------------
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
# code starts here
df=pd.read_csv(path)
print(df.head(10))
p_a=len(df[df['fico']>700])/len(df)
p_b=len(df[df['purpose']=='debt_consolidation'])/len(df)
df1=df[df['purpose']=='debt_consolidation']
print(df1)
p_a_b=len(df1[df1['fico'... | {"hexsha": "7a63267042b400df021c4f68b956eccc5f629c77", "size": 1129, "ext": "py", "lang": "Python", "max_stars_repo_path": "Probability-of-the-Loan-Defaulters/code.py", "max_stars_repo_name": "acharya221b/ga-learner-dsmp-repo", "max_stars_repo_head_hexsha": "9b493aff25cf861fa8b757d7f2e926e1dcbe6061", "max_stars_repo_li... |
import torch
import torch.optim as optim
import torch.nn as nn
import model
import adversarial1 as ad
import numpy as np
import argparse
import os
import torch.nn.functional as F
import scipy.io
from tqdm import tqdm
import json
torch.set_num_threads(1)
torch.manual_seed(1)
parser = argparse.ArgumentParser(descripti... | {"hexsha": "60850affeb65e0e21987e79e1639e8cdc081c1ce", "size": 14082, "ext": "py", "lang": "Python", "max_stars_repo_path": "BSP_voting/train_voting.py", "max_stars_repo_name": "comprehensiveMap/EI328-project", "max_stars_repo_head_hexsha": "145495454487c7a4496751ce3621873f6cd80872", "max_stars_repo_licenses": ["MIT"],... |
[STATEMENT]
lemma e2xs_xs [simp]:
"e2xs (encode_config ((f, xs, ls) # ss, rv)) = list_encode xs"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. e2xs (encode_config ((f, xs, ls) # ss, rv)) = Partial_Recursive.list_encode xs
[PROOF STEP]
using e2xs_def e2frame_frame encode_frame
[PROOF STATE]
proof (prove)
using thi... | {"llama_tokens": 283, "file": "Inductive_Inference_Universal", "length": 2} |
%% LyX 2.3.6.2 created this file. For more info, see http://www.lyx.org/.
%% Do not edit unless you really know what you are doing.
\documentclass[12pt,a4paper,fleqn,american,parskip=half-,svgnames]{scrartcl}
\usepackage[T1]{fontenc}
\usepackage[utf8]{inputenc}
\usepackage{amsmath}
\makeatletter
%%%%%%%%%%%%%%%%%%%%... | {"hexsha": "068bf187c4faf589aa380439f15febeb1fc38a5b", "size": 8146, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "reports/Phase_field_modeling_exercise.tex", "max_stars_repo_name": "pzimbrod/ML-for-PhaseField", "max_stars_repo_head_hexsha": "22f7d8ac292f6f02e520f75c61078449453ed244", "max_stars_repo_licenses": ... |
import os
import tensorflow as tf
import numpy as np
'''Routines for reading the CIFAR-10 python batch files.'''
# Global constants describing the CIFAR-10 data set.
NUM_CLASSES = 10
NUM_EXAMPLES_PER_EPOCH_FOR_TRAIN = 50000
DEFALFT_DATASET_DIR = '/datasets/cifar-10-batches-py'
def _load_cifar10(path=DEFALFT_DATAS... | {"hexsha": "cef25097601dc69b290921b47864ec65610468e3", "size": 3668, "ext": "py", "lang": "Python", "max_stars_repo_path": "alexnet_cifar10/input.py", "max_stars_repo_name": "zhangjunpeng9354/Learning-Tensorflow-by-Models", "max_stars_repo_head_hexsha": "9e6ab4da4ec66fb6e7934d129c57110c85e3d7da", "max_stars_repo_licens... |
#!/usr/bin/env python3
"""===============================================================================
FILE: money.py
USAGE: ./money.py
DESCRIPTION:
OPTIONS: ---
REQUIREMENTS: ---
BUGS: ---
NOTES: ---
AUTHOR: Alex Leontiev (alozz1991@gmail.com)
ORGANIZATION:
VERSI... | {"hexsha": "1fd1de2c2106930fd7d9e55ae45b8feded41f7c7", "size": 7000, "ext": "py", "lang": "Python", "max_stars_repo_path": "money.py", "max_stars_repo_name": "nailbiter/pyassistantbot2", "max_stars_repo_head_hexsha": "00a4171e8359ad4d61fea0bf7e84241ba79708d6", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
[STATEMENT]
lemma pp_increasing:
"x \<le> --x"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. x \<le> - - x
[PROOF STEP]
using inf_p pseudo_complement
[PROOF STATE]
proof (prove)
using this:
?x \<sqinter> - ?x = bot
(?x \<sqinter> ?y = bot) = (?x \<le> - ?y)
goal (1 subgoal):
1. x \<le> - - x
[PROOF STEP]
by bla... | {"llama_tokens": 152, "file": "Stone_Algebras_P_Algebras", "length": 2} |
import matplotlib
matplotlib.use('Pdf')
import matplotlib.pyplot as plt
import numpy as np
import os.path as osp
import rllab.misc.logger as logger
import rllab.plotter as plotter
import tensorflow as tf
import time
from rllab.algos.base import RLAlgorithm
from sandbox.rocky.tf.policies.base import Policy
from sandbo... | {"hexsha": "276ffa5d88e6e142aff2db7afc573888f80f7ef7", "size": 15914, "ext": "py", "lang": "Python", "max_stars_repo_path": "sandbox/rocky/tf/algos/batch_bmaml_polopt.py", "max_stars_repo_name": "jsikyoon/bmaml_rl", "max_stars_repo_head_hexsha": "2b34ef343723f06570bb06f7ee538b5ed16b0126", "max_stars_repo_licenses": ["M... |
from multiprocessing import Pool
import glob
import cv2
import os
import json
import re
import functools
import numpy as np
import matplotlib.pyplot as plt
from ...util.histogram import get_histogram_min_max_with_percentile
def extract_lab_and_boundary(file_name):
"""Computes the Lab space of the image and the ... | {"hexsha": "95a5cf55f89b176bec7b3ca639edada1b26405d6", "size": 10771, "ext": "py", "lang": "Python", "max_stars_repo_path": "livius/video/processing/vault/multiprocessing_test.py", "max_stars_repo_name": "papar22/livius", "max_stars_repo_head_hexsha": "a28929ef27f9737a598bbae36360ebe7b55a3f41", "max_stars_repo_licenses... |
# 2019-11-15 00:35:39(JST)
import collections
import sys
# import math
# from string import ascii_lowercase, ascii_uppercase, digits
# from bisect import bisect_left as bi_l, bisect_right as bi_r
# import itertools
# from functools import reduce
# import operator as op
# from scipy.misc import comb # float
... | {"hexsha": "5afe075068edfd4443d994fe5cdc74b560fdae21", "size": 635, "ext": "py", "lang": "Python", "max_stars_repo_path": "jp.atcoder/abc132/abc132_a/8436068.py", "max_stars_repo_name": "kagemeka/atcoder-submissions", "max_stars_repo_head_hexsha": "91d8ad37411ea2ec582b10ba41b1e3cae01d4d6e", "max_stars_repo_licenses": [... |
from sympy import ( symbols, solve, diff, integrate, exp, lambdify, pprint )
import matplotlib.pyplot as plt
import numpy as np
# The life (in months) of a certain electronic computer part has a probability density function defined by F,
# Find the probability that a randomly selected component will last the followin... | {"hexsha": "e0f7e088ecdb9ac8993aeeaa2a806b5c9246ed38", "size": 1332, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/Classes/MSDS400/Module 9/life_span.py", "max_stars_repo_name": "bmoretz/Python-Playground", "max_stars_repo_head_hexsha": "a367ec7659b85c24363c21b5c0ac25db08ffa1f6", "max_stars_repo_licenses":... |
"""ASE interface for MST module implemented in MuST package available at
https://github.com/mstsuite/MuST"""
import numpy as np
from ase.calculators.calculator import FileIOCalculator, SCFError
import os
import subprocess
import glob
from ase.units import Bohr, Rydberg
from default_params import defaults
from ase.dat... | {"hexsha": "1a16cc63e3571cbfa0c26b1773b2b7df7993b856", "size": 13809, "ext": "py", "lang": "Python", "max_stars_repo_path": "ase_must/must.py", "max_stars_repo_name": "ramntczcu/MuST", "max_stars_repo_head_hexsha": "06371c5b4a4f15349a84b712911da9dd241a40a0", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars_count... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 30 21:24:34 2020
@author: antoine
"""
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Oct 22 17:21:12 2019
@author: antoine
Code pour devernay avec rapport isopérimétrique
"""
import os
import numpy as np
import cv2
from skima... | {"hexsha": "3a35516e2e2a9eedb26fd92b4dd0ef6a143422a9", "size": 13788, "ext": "py", "lang": "Python", "max_stars_repo_path": "iso_th_devernay.py", "max_stars_repo_name": "anttad/SubpixelCircleDetection", "max_stars_repo_head_hexsha": "912252d4a305d71f800ed39b3ce87946251cb675", "max_stars_repo_licenses": ["MIT"], "max_st... |
from __future__ import print_function
from __future__ import division
import os
import numpy as np
import collections
import json
import h5py
import random
from tqdm import tqdm
import torch
import torch.nn as nn
from torch.autograd import Variable
import torch.nn.functional as F
import framework.configbase
import f... | {"hexsha": "fa9fd17d09b364cc812547aeff0d29dcfc8a67e8", "size": 6366, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/transformer.py", "max_stars_repo_name": "riokt/video-paragraph", "max_stars_repo_head_hexsha": "2da3298819e73809af495457db2cf1dfffad712f", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
import numpy as np
from sympy import *
import matplotlib.pyplot as plt
import time
import math
def actual_result(func, val):
dfunc = diff(func,'x')
x = val
return eval(str(dfunc))
def two_point(func, x, h):
funcx = eval(str(func))
x = x + h
funcxh = eval(str(func))
return (funcxh - funcx... | {"hexsha": "29e34f9f3b77de0307ad18a3e825e2a78a5a3bf4", "size": 1076, "ext": "py", "lang": "Python", "max_stars_repo_path": "twoPoint.py", "max_stars_repo_name": "nguyenvu2589/Numerical", "max_stars_repo_head_hexsha": "23eee7d31a8871d5d53871ebc9950866cf11ad23", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
# Copyright (C) 2018-2022 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
import os
import sys
import numpy as np
import paddle
#print numpy array like C structure
def print_alike(arr):
shape = arr.shape
rank = len(shape)
#print("shape: ", shape, "rank: %d" %(rank))
#for idx, value in np.nde... | {"hexsha": "d5cdc71e4d4ea50f3a49f4afa400a56abccde836", "size": 3706, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/core/tests/frontend/paddle/test_models/gen_scripts/save_model.py", "max_stars_repo_name": "ryanloney/openvino-1", "max_stars_repo_head_hexsha": "4e0a740eb3ee31062ba0df88fcf438564f67edb7", "max... |
using StaticModules, Test
using StaticModules
@staticmodule Foo begin
x = 1
f(y) = x^2 + 2y
end
@test :x ∈ propertynames(Foo)
@test :f ∈ propertynames(Foo)
@test Foo.x == 1
@test @with Foo begin
f(1) == 3x
end
@test @with (;f = x -> x + 1, x = 2) begin
f(1) == x
end
struct Bar
a
b
end
... | {"hexsha": "7a0a74aece278a9fad37c7562c8b2f8803db29e9", "size": 835, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/runtests.jl", "max_stars_repo_name": "MasonProtter/StaticModules.jl", "max_stars_repo_head_hexsha": "3cbc42382dd5f075748a79132b1a35a8f7846bbc", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jul 21 16:03:24 2021
@author: loic
"""
import os
import geopy
import numpy as np
import geopy.distance
import scipy.io as sio
from scipy import signal
from zipfile import ZipFile
import matplotlib.pyplot as plt
from scipy.interpolate import griddata
f... | {"hexsha": "a79e3d74e0b4a52c3d19ddfc282086d34e2865f5", "size": 20001, "ext": "py", "lang": "Python", "max_stars_repo_path": "Codes/Reproduce_Fig_4_Noise.py", "max_stars_repo_name": "lviens/2020_Autocorrelations", "max_stars_repo_head_hexsha": "1f5797e83b0b3aad1f9443e2b754dd6fd3fe0f63", "max_stars_repo_licenses": ["MIT"... |
""" Helper functions for the Access Control Queuing problem
This script contains object definitions and herlper functions for the Access Control
Queuing problem, which are useful for the q-learning implementation.
This file should be imported as a module and contains the following functions:
* get_action - retu... | {"hexsha": "c84fbe3b8e6496ff717094a7f1c15698ef4522de", "size": 5043, "ext": "py", "lang": "Python", "max_stars_repo_path": "AccessQueues/utils_qleaning.py", "max_stars_repo_name": "nudging-SMDP/nudging-supplementary-material", "max_stars_repo_head_hexsha": "94795abf1e26abab07389436fc737029e6a2a566", "max_stars_repo_lic... |
// Warning! This file is autogenerated.
#include <boost/text/bidirectional.hpp>
#include "bidi_tests.hpp"
#include <gtest/gtest.h>
#include <algorithm>
std::vector<int> expected_levels;
std::vector<int> expected_reordered_indices;
TEST(bidi, bidi_444_000)
{
expected_levels = { 1, 0, -1, 1 };
expected_reo... | {"hexsha": "73cfdb895b2b41284ea76f90f6ed2e8f28492aad", "size": 818134, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "test/bidi_test_444.cpp", "max_stars_repo_name": "eightysquirrels/text", "max_stars_repo_head_hexsha": "d935545648777786dc196a75346cde8906da846a", "max_stars_repo_licenses": ["BSL-1.0"], "max_stars... |
import math
import itertools
from sklearn.cluster import DBSCAN
import numpy as np
import pysc2.agents.myAgent.myAgent_13_BIC_DQN.smart_actions as sa
from pysc2.agents.myAgent.myAgent_13_BIC_DQN.config import config
from pysc2.agents.myAgent.myAgent_13_BIC_DQN.tools import unit_list
from pysc2.lib import features
#... | {"hexsha": "8c8b814617187f278134394bc75988a6afa67299", "size": 15617, "ext": "py", "lang": "Python", "max_stars_repo_path": "pysc2/agents/myAgent/myAgent_13_BIC_DQN/tools/handcraft_function_for_level_2_attack_controller.py", "max_stars_repo_name": "Hotpotfish/pysc2", "max_stars_repo_head_hexsha": "3d7f7ffc01a50ab69d435... |
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Jan 6 08:43:46 2021
Compile CMIP6 simulations on a common grid within the NWES region into ensemble,
combining historical and SSP runs and averaging across variants per model.
@author: thermans
"""
import xarray as xr
import numpy as np
import os
im... | {"hexsha": "cac586b3757019fe0b70c10aa28ab08fb07d7883", "size": 5028, "ext": "py", "lang": "Python", "max_stars_repo_path": "cmip6_processing/compiling/compile_cmip6_models_variable_nwes_variantmean.py", "max_stars_repo_name": "Timh37/SeasonalDSLC_NWES", "max_stars_repo_head_hexsha": "9cbc155448dbd0ba07a5b95c5ce49dc3cb4... |
import gmi_misc
gmi_misc.print_header()
print("Calculate model's thickness map [lon lat km]")
import gmi_config
gmi_config.read_config()
import numpy as np
from scipy.interpolate import griddata
n_lon = int(abs(gmi_config.LON_MAX - gmi_config.WIDTH/2.0 - (gmi_config.LON_MIN + gmi_config.WIDTH/2.0)) / gmi_config.... | {"hexsha": "73d91457dfc319a0459cc18bfa4c33ea7320a304", "size": 1426, "ext": "py", "lang": "Python", "max_stars_repo_path": "gmi_model_thickness.py", "max_stars_repo_name": "eldarbaykiev/magtess-inversion-python", "max_stars_repo_head_hexsha": "e775fb0393c00eff9871cfa3e40c5784a89f3e5e", "max_stars_repo_licenses": ["BSD-... |
/* -*- mode: c++; tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 4 -*- */
/*
Copyright (C) 2006, 2007 Eric Ehlers
This file is part of QuantLib, a free-software/open-source library
for financial quantitative analysts and developers - http://quantlib.org/
QuantLib is free software: you can redistribute it a... | {"hexsha": "a5f0b6088582f3d2c9f1d5965a371540eba739a4", "size": 5013, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "ObjectHandler/ohxl/rangereference.hpp", "max_stars_repo_name": "txu2014/quantlib", "max_stars_repo_head_hexsha": "95c7d94906c30d0c3c4e0758a2ebfe2a62b075ec", "max_stars_repo_licenses": ["BSD-3-Clause... |
#!/usr/bin/env python
# File: demud.py
# Author: Kiri Wagstaff, 2/28/13; James Bedell, summer 2013
#
# Implementation of DEMUD (Discovery through Eigenbasis Modeling of
# Uninteresting Data). See Wagstaff et al., AAAI 2013.
#
# Copyright 2013-2015, by the California Institute of Technology. ALL
# RIGHTS RESERVED. Uni... | {"hexsha": "f5c411a45d1363a113d18f8b63b68e154abc4bcd", "size": 92208, "ext": "py", "lang": "Python", "max_stars_repo_path": "demud/demud.py", "max_stars_repo_name": "wkiri/DEMUD", "max_stars_repo_head_hexsha": "603e0a647e0da5fdc4bcaa2f3a0b21bd4155a41d", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": 49, ... |
from __future__ import absolute_import
import unittest
import numpy as np
from centrosome.otsu import otsu, entropy, otsu3, entropy3
class TestOtsu(unittest.TestCase):
def test_01_TwoValues(self):
"""Test Otsu of two values is between the two"""
x = otsu([0.2, 0.8])
self.assertTrue(x >= 0.... | {"hexsha": "8186941a98cfc10596e9392b787b54dd4be5f1a8", "size": 4783, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_otsu.py", "max_stars_repo_name": "DavidStirling/centrosome", "max_stars_repo_head_hexsha": "c1ea6629d510e376cd34d229ba3ba5079b3a7093", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_... |
[STATEMENT]
lemma Arr_Resid:
assumes "Con \<T> \<U>"
shows "Arr (\<T> \<lbrace>\\\<rbrace> \<U>)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (\<T> \<lbrace>\\<rbrace> \<U>) \<lbrace>\\<rbrace> (\<T> \<lbrace>\\<rbrace> \<U>) \<noteq> {}
[PROOF STEP]
by (metis Con_char N.Cong_class_memb_is_arr R.arrE N.re... | {"llama_tokens": 168, "file": "ResiduatedTransitionSystem_ResiduatedTransitionSystem", "length": 1} |
/*
Copyright 2017. All rights reserved.
Computer Vision Group, Visual Computing Institute
RWTH Aachen University, Germany
This file is part of the rwth_mot framework.
Authors: Aljosa Osep (osep -at- vision.rwth-aachen.de)
rwth_mot framework is free software; you can redistribute it and/or modify it under the
terms of... | {"hexsha": "36ff7dfb1ecfd14ca82020ddff11d5b3e2992f69", "size": 15876, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/sun_utils/datasets_dirty_utils.cpp", "max_stars_repo_name": "OmranKaddah/Multi-Object-Tracking-in-The-Driving-Scene", "max_stars_repo_head_hexsha": "0a2e8092b7e8f4d6317b201be5442e62c4efd240", "... |
SUBROUTINE W3FI59(FIELD,NPTS,NBITS,NWORK,NPFLD,ISCALE,LEN,RMIN)
C$$$ SUBPROGRAM DOCUMENTATION BLOCK
C . . . .
C SUBPROGRAM: W3FI59 FORM AND PACK POSITIVE, SCALED DIFFERENCES
C PRGMMR: ALLARD, R. ORG: NMC41 DATE: 84-08-01
C
C ABSTR... | {"hexsha": "a05aa172ab2cad79c766295865f9c1857fc75f3a", "size": 4531, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "ungrib/src/ngl/w3/w3fi59.f", "max_stars_repo_name": "martinremy/wps", "max_stars_repo_head_hexsha": "8bddbdbb612a0e019ae110df481461d5d904053a", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
###################################################################
## Written by Eli Pugh and Ethan Shen ##
## {epugh}, {ezshen} @stanford.edu ##
## Translated from Matlab written by Jiantao Jiao ##
## https://github.com/EEthinker/Universal_direc... | {"hexsha": "cd3d185804840dabdf794cbd1f863fd091e00947", "size": 5750, "ext": "py", "lang": "Python", "max_stars_repo_path": "directed_information/compute_DI_MI.py", "max_stars_repo_name": "elipugh/directed_information", "max_stars_repo_head_hexsha": "d94172496a4d544c9e244c4a95acb8539017bb77", "max_stars_repo_licenses": ... |
import os, sys, argparse
import numpy as np
from dd_client import DD
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import random
random.seed(134124)
parser = argparse.ArgumentParser()
parser.add_argument("--image",help="path to image")
parser.add_argument("--nclasses",help="number of classes",type=... | {"hexsha": "502757bf0a67eeb39951a51bc3bddfd9c2def6ee", "size": 3302, "ext": "py", "lang": "Python", "max_stars_repo_path": "demo/segmentation/segment.py", "max_stars_repo_name": "dgtlmoon/deepdetect", "max_stars_repo_head_hexsha": "0b2f20be8211a95b1fea3a600f0d5ba17b8d339f", "max_stars_repo_licenses": ["Apache-2.0"], "m... |
#!/usr/bin/python
import lcm
import drc
from drc import reactive_recovery_debug_t
import sys
import time
from bot_lcmgl import lcmgl, GL_LINES
import numpy as np
def ppval(coefs, ts, t):
ti = np.where(ts < t)[-1]
if (len(ti) >= 1):
ti = ti[-1]
elif (len(ti) == 0):
ti = 0;
t_off = (t - ts[ti]);
out =... | {"hexsha": "3b47cc8fa55e8ba198b99c6eab05abfe4f406f41", "size": 1494, "ext": "py", "lang": "Python", "max_stars_repo_path": "software/control/src/reactive_recovery_debug_visualizer.py", "max_stars_repo_name": "liangfok/oh-distro", "max_stars_repo_head_hexsha": "eeee1d832164adce667e56667dafc64a8d7b8cee", "max_stars_repo_... |
import numpy as np
from aiida.manage.configuration import load_profile
from aiida.orm import Bool, Str, Code, Int, Float
from aiida.plugins import DataFactory, WorkflowFactory
from aiida.engine import submit
load_profile()
Dict = DataFactory('dict')
KpointsData = DataFactory("array.kpoints")
def launch_aiida_bulk_m... | {"hexsha": "91f78652ef71da1428345c3ac53a5b89f8202109", "size": 3862, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/submit.py", "max_stars_repo_name": "atztogo/aiida-vasp-bm", "max_stars_repo_head_hexsha": "46c6d53b2d1972960f64e2bc4327d999532eccc3", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
------------------------------------------------------------------------
-- The syntax of the untyped λ-calculus
------------------------------------------------------------------------
{-# OPTIONS --safe #-}
module Lambda.Simplified.Syntax where
open import Equality.Propositional
open import Prelude
open import Ve... | {"hexsha": "cd4123aa955e7d3e5a7f81f68c7b3e4dc1c8ecae", "size": 1449, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "src/Lambda/Simplified/Syntax.agda", "max_stars_repo_name": "nad/partiality-monad", "max_stars_repo_head_hexsha": "f69749280969f9093e5e13884c6feb0ad2506eae", "max_stars_repo_licenses": ["MIT"], "ma... |
# -*- coding: utf-8 -*-
# Standard library imports
import numpy as np
# Local applications imports
from mosqito.sq_metrics.loudness.loudness_zwst._main_loudness import _main_loudness
from mosqito.sq_metrics.loudness.loudness_zwst._calc_slopes import _calc_slopes
from mosqito.sq_metrics.loudness.loudness_zwtv._nonline... | {"hexsha": "0a53635ff83c80fb64fb581f8a692e84c35b9c6c", "size": 2518, "ext": "py", "lang": "Python", "max_stars_repo_path": "mosqito/sq_metrics/loudness/loudness_zwtv/loudness_zwtv.py", "max_stars_repo_name": "wantysal/MoSQITooo", "max_stars_repo_head_hexsha": "ef348c1d08a7831e673ac6c0819e2a74b07dc957", "max_stars_repo_... |
import co2_diag.graphics
from ccgcrv.ccg_filter import ccgFilter
from co2_diag import set_verbose
from co2_diag.data_source.models.cmip.cmip_collection import Collection as cmipCollection
from co2_diag.graphics.single_source_plots import plot_filter_components
from co2_diag.operations.time import ensure_dataset_datetim... | {"hexsha": "103ec2a904882bd0536e838318d8382ff02624ba", "size": 32509, "ext": "py", "lang": "Python", "max_stars_repo_path": "co2_diag/operations/Confrontation.py", "max_stars_repo_name": "dkauf42/gdess", "max_stars_repo_head_hexsha": "7945f4e7ea1c4a2e233c1ba8dd538743b6fb18b9", "max_stars_repo_licenses": ["BSD-3-Clause"... |
module QuantumControl
using Reexport
@reexport using QuantumPropagators
@reexport using QuantumControlBase
@reexport using Krotov
end
| {"hexsha": "8af28d1cabb31b1f5f09e2e6ec5a48ce55b55cd2", "size": 136, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/QuantumControl.jl", "max_stars_repo_name": "seba-car/QuantumControl.jl", "max_stars_repo_head_hexsha": "ff08d2e2d604c39fdd291634891c7925506eff0a", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
# much help from https://github.com/mnielsen/neural-networks-and-deep-learning
import random
import numpy as np
# z = Wx + b
def sigmoid_function(z):
return 1.0 / (1.0 + np.exp(-z))
def sigmoid_prime(z):
return sigmoid(z) * (1 - sigmoid(z))
class Network(object):
def __init__(self, sizes):
self.num_layers... | {"hexsha": "20893d4c4a39cfdf5770b72d84e6e2e8e5fcd38a", "size": 2209, "ext": "py", "lang": "Python", "max_stars_repo_path": "feed_forward_nn.py", "max_stars_repo_name": "shivam-singhal/nn_implementations", "max_stars_repo_head_hexsha": "962314e31a34fb386dc34a94e05d32ea68abad0b", "max_stars_repo_licenses": ["MIT"], "max_... |
macro inv(expr, cond)
cond isa Expr && cond.head == :if || throw(ArgumentError("$cond is not an if expression"))
cond.args[2] = expr
return cond
end
@inv println("Wow! Lucky Guess!") if true else println("Not!") end
| {"hexsha": "ac52de05c3de49a9c25ae15d413739458850bfaf", "size": 229, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "lang/Julia/inverted-syntax.jl", "max_stars_repo_name": "ethansaxenian/RosettaDecode", "max_stars_repo_head_hexsha": "8ea1a42a5f792280b50193ad47545d14ee371fb7", "max_stars_repo_licenses": ["MIT"], "m... |
#!/usr/bin/env python
"""UTILS.PY - Utility functions
"""
__authors__ = 'David Nidever <dnidever@montana.edu?'
__version__ = '20210928' # yyyymmdd
import os
import time
import numpy as np
from glob import glob
def datadir():
""" Return the data directory name."""
fil = os.path.abspath(__file__)
codedi... | {"hexsha": "299915a61a49b8567d15b6339f8ec3aae3e46b18", "size": 844, "ext": "py", "lang": "Python", "max_stars_repo_path": "chronos/utils.py", "max_stars_repo_name": "dnidever/chronos", "max_stars_repo_head_hexsha": "dc1c1b5b81f7969ec52ca7e685cb5bd08fe5fe97", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, ... |
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