text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
|---|---|
import plotly.express as px
from dash import dcc, html, Dash
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output, State
import pandas as pd
import numpy as np
import os
import dash
### FIGURES ###
from .plotlyfunctions import *
# Build App
def init_dashboard(server):
... | {"hexsha": "bca4aea5a257f302fd3172d28d482f8470a5553d", "size": 2984, "ext": "py", "lang": "Python", "max_stars_repo_path": "apps/dashboards/forecast/train.py", "max_stars_repo_name": "wesleybeckner/truffletopia", "max_stars_repo_head_hexsha": "574caf24b41126d3d71c45b49cfd44820c42fa7e", "max_stars_repo_licenses": ["MIT"... |
import time
import os
import tensorflow as tf
import numpy as np
from keras.optimizers import Adam
from keras.layers import Input
import Model
import Util
class DeRed():
def __init__(self,orientation):
self.orientation = orientation
self.filter = 32
self.data_path = '../Data/'
se... | {"hexsha": "24bbc8e9ca44afa29210e56525ba5740fcdbd6af", "size": 3081, "ext": "py", "lang": "Python", "max_stars_repo_path": "Code/DeRed.py", "max_stars_repo_name": "DezhengTian/DeRed-Harmonization", "max_stars_repo_head_hexsha": "5c22d874ec61643d5dee0a43ffe817db5cae18b5", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
/* -*- Mode: C++; tab-width: 4; indent-tabs-mode: t; c-basic-offset: 4 -*- vim:set ts=4 sw=4 sts=4 noet: */
#ifdef HAVE_CONFIG_H
#include "config.h"
#endif
#include "load/var.h"
#include <boost/uuid/uuid_io.hpp>
#include "bc/pack.h"
#include "cellml.h"
#include "database.h"
#include "lo.pb.h"
#include "phml.h"
#incl... | {"hexsha": "81d854ea74a241feb005bb3b775da0aff0199185", "size": 3884, "ext": "cc", "lang": "C++", "max_stars_repo_path": "test/load/test_var.cc", "max_stars_repo_name": "Abhisheknishant/Flint", "max_stars_repo_head_hexsha": "441beab56d21e4069b858ae6588fa0fa3084d722", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
REBOL [
Title: "Testing library"
File: %spec.r
Author: "Kirill Temnov"
Date: 15/11/2015
]
test-suite: context [
name: ""
total: ""
errors: 0
fails: 0
assert: func [
block
][
if error?
try [
r: do block
either do block [
... | {"hexsha": "b7181b5c446e1dfe4cf938592d36b5c12c1bb0be", "size": 876, "ext": "r", "lang": "R", "max_stars_repo_path": "tests/spec.r", "max_stars_repo_name": "KirillTemnov/stack-vm", "max_stars_repo_head_hexsha": "b3b5ddcc6da7e454d0433c22ad7d7ba78c279597", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 2, "max_sta... |
#ifndef N_BODY_PHYSICAL_HPP
#define N_BODY_PHYSICAL_HPP
#include "communication.hpp"
#include "config.hpp"
#include "data.hpp"
#include "logging.hpp"
#include "space.hpp"
#include "tree.hpp"
#include <boost/archive/xml_oarchive.hpp>
#include <boost/mpi.hpp>
#include <cmath>
#include <cstddef>
namespace n_body::physic... | {"hexsha": "1677364b618111ee7d20ad04b0faacb007c4ff55", "size": 6233, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/physical.hpp", "max_stars_repo_name": "linyinfeng/n-body", "max_stars_repo_head_hexsha": "e40c859689d76a3f36cd08e072d7ee24685e8be4", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1.0, "... |
\documentclass[10pt]{sigplanconf}
\usepackage[compact]{titlesec}
\usepackage[utf8]{inputenc}
\usepackage{amsmath}
\usepackage{amssymb}
\usepackage{url}
\usepackage{color}
\usepackage{multirow}
\setlength{\textfloatsep}{8pt}
\newcommand{\Value}{\mathbf{value}}
\newcommand{\Any}{\mathbf{any}}
\newcommand{\Nil}{\mathbf... | {"hexsha": "da65a1761927c2f74d3233bb34ca2f0633969750", "size": 82737, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "doc/papers/dls15/paper.tex", "max_stars_repo_name": "andremm/typedlua", "max_stars_repo_head_hexsha": "2ff68c56668da62b0fa8e7256f70f3ca1475586a", "max_stars_repo_licenses": ["MIT", "Unlicense"], "m... |
\section{Partition function}
Theories with an action can be quantized using a path integral.
The partition function in Euclidean signature is defined as
% \footnote{
% Wick rotation analytically continues time to imaginary (Euclidean) time, $t\rightarrow -i t_E$,
% then the oscillatory exponential becomes decaying. }
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import os
import numpy as np
import pandas as pd
from time import time, sleep
from datetime import timedelta
from torch.utils.tensorboard import SummaryWriter
from tensorboard.backend.event_processing import event_accumulator
from tqdm import tqdm
from .algo.base import Algorithm
from .env import NormalizedE... | {"hexsha": "943401f914012a4379580df049f55bbdc68727cd", "size": 4385, "ext": "py", "lang": "Python", "max_stars_repo_path": "cail/trainer.py", "max_stars_repo_name": "Stanford-ILIAD/Confidence-Aware-Imitation-Learning", "max_stars_repo_head_hexsha": "1d8af0e4ab87a025885133a2384d5a937329b2f5", "max_stars_repo_licenses": ... |
#ifndef UNIT_TESTS_JSON_EQUAL
#define UNIT_TESTS_JSON_EQUAL
#include <boost/test/unit_test.hpp>
#include "osrm/json_container.hpp"
#include "util/json_deep_compare.hpp"
inline boost::test_tools::predicate_result compareJSON(const osrm::util::json::Value &reference,
... | {"hexsha": "1453086e0dec6448a76a8f89c922844516369ebe", "size": 721, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "unit_tests/library/equal_json.hpp", "max_stars_repo_name": "jhermsmeier/osrm-backend", "max_stars_repo_head_hexsha": "7b11cd3a11c939c957eeff71af7feddaa86e7f82", "max_stars_repo_licenses": ["BSD-2-Cla... |
#!/usr/local/bin/python
"""
***********************************************
- PROGRAM: matrix2tab.py
- CONTACT: Bryan lajoie (bryan.lajoie@umassmed.edu)
***********************************************
"""
from __future__ import print_function
from __future__ import division
import numpy as np
import scipy as sp
impor... | {"hexsha": "e060efb3b5ae045ae97d60ab195831989417a867", "size": 14297, "ext": "py", "lang": "Python", "max_stars_repo_path": "scripts/python/matrix2tab.py", "max_stars_repo_name": "sergpolly/cworld-dekker", "max_stars_repo_head_hexsha": "7557bbe873e623e9059482722922faca4e784ad0", "max_stars_repo_licenses": ["Apache-2.0"... |
#!/bin/python
# This script will ...
#
#
#
# TO DO: annotation paths are hard coded and if two-sided or one-sided p-values are also hard coded
#
#
# Abin Abraham
# created on: 2020-01-05 08:20:56
import os
import sys
import numpy as np
import pandas as pd
import pickle
from .helper_general import safe_mkdir
f... | {"hexsha": "7804716456647ec213df03a29488ce0f81fe474b", "size": 2158, "ext": "py", "lang": "Python", "max_stars_repo_path": "gsel_vec/scripts/helper_calc_genome_distribution_of_annotations.py", "max_stars_repo_name": "abraham-abin13/gsel_vec", "max_stars_repo_head_hexsha": "486baa867f95f1d9d106e59a00e408d14ac42271", "ma... |
[STATEMENT]
lemma reduce_system_matrix_signs_helper_aux_R:
fixes p:: "real poly"
fixes qs :: "real poly list"
fixes subsets :: "(nat list*nat list) list"
fixes signs :: "rat list list"
fixes S:: "nat list"
assumes well_def_h: "\<forall>x. List.member S x \<longrightarrow> x < length signs"
assumes nonz... | {"llama_tokens": 9144, "file": "BenOr_Kozen_Reif_Renegar_Proofs", "length": 66} |
theory Semantics
imports Main
begin
section {* The Language *}
subsection {* Variables and Values *}
type_synonym vname = string -- "names for variables"
datatype val
= Bool bool -- "Boolean value"
| Intg int -- "integer value"
abbreviation "true == Bool True"
abbreviation "false == Bool False"
... | {"author": "Josh-Tilles", "repo": "AFP", "sha": "f4bf1d502bde2a3469d482b62c531f1c3af3e881", "save_path": "github-repos/isabelle/Josh-Tilles-AFP", "path": "github-repos/isabelle/Josh-Tilles-AFP/AFP-f4bf1d502bde2a3469d482b62c531f1c3af3e881/thys/VolpanoSmith/Semantics.thy"} |
# !/usr/bin/env python
# -*- coding:utf-8 -*-
import argparse
import cv2
import numpy as np
def color_encode(color):
if color == 'red':
return (0,0,255)
elif color == 'blue':
return (255,0,0)
elif color == 'green':
return (0,255,0)
elif color == 'yellow':
return (0,255,... | {"hexsha": "07a623233d7a564c021bf57899ac2574810de382", "size": 2253, "ext": "py", "lang": "Python", "max_stars_repo_path": "others/change_bg_color.py", "max_stars_repo_name": "daishoui/ex", "max_stars_repo_head_hexsha": "fd75f6a907cabb6c60036136b6a182a7d025d4b3", "max_stars_repo_licenses": ["MIT"], "max_stars_count": n... |
import os
from operator import add
import numpy as np
import torch
from PIL import Image
from torchvision.datasets import CocoDetection
from transforms import ToImgaug, ImgaugToTensor
class CocoMask(CocoDetection):
def __init__(self, root, annFile, transform=None, target_transform=None, transforms=None, use_mas... | {"hexsha": "88cb95bfbf43fff29cdd5e21e133c70fe7027323", "size": 2181, "ext": "py", "lang": "Python", "max_stars_repo_path": "datasets.py", "max_stars_repo_name": "danmalowany/trains-model-zoo", "max_stars_repo_head_hexsha": "2091100057afae9593b18ddcefd81b7d46724a96", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
% Time-Variable Input
In earlier versions of MODFLOW, most stress-boundary packages read input on a stress period-by-stress period basis, and those values were held constant during the stress period. In \programname{}, many stress values can be specified with a higher degree of time resolution (from time step to time ... | {"hexsha": "f2aaa4c05e7b2439f7b8b00bae2465172d429a24", "size": 19456, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "doc/mf6io/gwf/tsi.tex", "max_stars_repo_name": "scharlton2/modflow6", "max_stars_repo_head_hexsha": "83ac72ee3b6f580aaffef6352cf15c1697d3ce66", "max_stars_repo_licenses": ["CC0-1.0"], "max_stars_co... |
import sys
import socket
import binascii
import networkx as nx
import matplotlib.pyplot as plt
from pcapng import FileScanner
from pcapng import blocks
def get_pcap_packet_blocks(filename):
packet_blocks = []
with open(filename, 'rb') as fp:
scanner = FileScanner(fp)
for block in scanner:
... | {"hexsha": "8bed8c14d8a6636cd350221f7b321433568c4f52", "size": 3116, "ext": "py", "lang": "Python", "max_stars_repo_path": "simple-pcapng-visualizer.py", "max_stars_repo_name": "heyi1999/simple-pcapng-visualizer", "max_stars_repo_head_hexsha": "785102efd2408e7526c0aebecbe2da057b697bf9", "max_stars_repo_licenses": ["Apa... |
#pragma GCC diagnostic push
#pragma GCC diagnostic ignored "-Wsign-compare"
#include <boost/test/unit_test.hpp>
#pragma GCC diagnostic pop
#include <eosio/chain/exceptions.hpp>
#include <eosio/chain/resource_limits.hpp>
#include <eosio/testing/tester.hpp>
#include <fc/exception/exception.hpp>
#include <fc/variant_obj... | {"hexsha": "3e9a9318229930f1204f021821da0e305dc1652d", "size": 5162, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "unittests/rem_account_price_test.cpp", "max_stars_repo_name": "Remmeauth/core", "max_stars_repo_head_hexsha": "578996ce408ca0adbe6a6b895177199017ee907b", "max_stars_repo_licenses": ["MIT"], "max_sta... |
modelMatrix = function(x,
interactions = FALSE, intercept = FALSE){
#' Create a sparse design matrix from data frame
#'
#' \code{modelMatrix} takes in a data.frame and encodes it as a sparse model.Matrix object.
#' Factors use treatment ("one-hot") encoding, creating indicator variables from categorical
#'... | {"hexsha": "00a3e7e5ef29bfc4e15df8eeeb91e7ff4ba9e1e6", "size": 1639, "ext": "r", "lang": "R", "max_stars_repo_path": "R/modelMatrix.r", "max_stars_repo_name": "dhelkey/babymonitor", "max_stars_repo_head_hexsha": "591dbfa43678ee25be1ea0d9601da78735be0639", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "ma... |
from constants import Directions
import numpy as np
import matplotlib.pyplot as plt
import time
def simple_run(pool, direction):
def forward(f_pool):
node_to_run = f_pool[0]
f_pool = f_pool[1:]
node_to_run.forward()
f_pool.extend(list(filter(lambda ol: ol.can_forward, node_to_run.g... | {"hexsha": "3ee64c083d495c404d372936a352e5fecd4ac9cb", "size": 4311, "ext": "py", "lang": "Python", "max_stars_repo_path": "session.py", "max_stars_repo_name": "WallFacer5/ArtifIdiot", "max_stars_repo_head_hexsha": "698aac564901f64138b1e6287ab1996792a8f2fa", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, ... |
```python
import numpy as np
from pycalphad import Model, Database, calculate, equilibrium
import pycalphad.variables as v
#dbf = Database('2016-08-10-AlGdMgand18RLPSO-for 3d plot.tdb')
dbf = Database('alfe_sei.TDB')
models = {key: Model(dbf, ['AL', 'FE', 'VA'], key) for key in dbf.phases.keys()}
```
```python
#Set ... | {"hexsha": "9b9edb92a41123cdf5c658be1aaf878ab40cdfde", "size": 806655, "ext": "ipynb", "lang": "Jupyter Notebook", "max_stars_repo_path": "EqPerformance-solveq.ipynb", "max_stars_repo_name": "richardotis/pycalphad-sandbox", "max_stars_repo_head_hexsha": "43d8786eee8f279266497e9c5f4630d19c893092", "max_stars_repo_licens... |
import matplotlib.pyplot as plt
import numpy as np
from typing import List
def bits_to_int_list(bits: str) -> List[int]:
"""
Ex:
1010100 -> [1, 0, 1, 0, 1, 0, 0]
"""
bits = list(map(int, bits))
return bits
def make_graph(signal: List[int], bits: List[int], title: str) -> None:
"""Use... | {"hexsha": "945432d729e002edb16c7d46be99ec4d9f1c4ac5", "size": 4701, "ext": "py", "lang": "Python", "max_stars_repo_path": "bits_to_plot.py", "max_stars_repo_name": "renan-cunha/signal_encoding", "max_stars_repo_head_hexsha": "16ae675fb6575f13219f44dc15c2eb1c84069632", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
module TestPatterns
using Test
using ReTest: and, or, not, interpolated, reachable, depth, pass, fail, iter
import ReTest
struct MockTestset
id
marks
parent
iter
MockTestset() = new(rand(1:typemax(Int)), ReTest.Marks(), nothing, 1)
end
ReTest.tsdepth(::MockTestset) = 1
const basic_patterns = [a... | {"hexsha": "dc7cc65bf92f4deda0706c2353117b0dfe7f70c6", "size": 2595, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/test_patterns.jl", "max_stars_repo_name": "danielsoutar/ReTest.jl", "max_stars_repo_head_hexsha": "4831b0fc23f2897bbeb999de9bdd14e968653199", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
program t
integer::ierr,i
character(5)::s
100 format (i0)
open(unit=77,file='infile',status='old',iostat=ierr)
read(77,fmt='(a)',iostat=ierr) s
print 100,ierr
print '(a)',s
close(77,iostat=ierr)
end program t
| {"hexsha": "fdb1879ff0f73c9226e85d66f2cffb282e7c744a", "size": 223, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "tests/t0180r/t.f90", "max_stars_repo_name": "maddenp/ppp", "max_stars_repo_head_hexsha": "81956c0fc66ff742531817ac9028c4df940cc13e", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count": ... |
import numpy as np
import fastfilters as ff
import vigra
import time
class Timer(object):
def __enter__(self):
self.a = time.clock()
return self
def __exit__(self, *args):
self.b = time.clock()
self.delta = self.b - self.a
a = np.zeros((5000,5000)).astype(np.float32)
for order in [0,1,2]:
for sigma in [... | {"hexsha": "914c2c5928fe6cc64f0b23915b391e57e2e59696", "size": 4099, "ext": "py", "lang": "Python", "max_stars_repo_path": "benchmark/bench_vigra.py", "max_stars_repo_name": "k-dominik/fastfilters", "max_stars_repo_head_hexsha": "715281e8ee20e15080e416b60e13e1d33984908f", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
"""
@author: Torben Gräber
"""
# Imports
import numpy as np
import matplotlib.pyplot as plt
import GPyOpt
# Keras and Tensorflow Imports
from keras.callbacks import ModelCheckpoint
# Custom Imports
from .HelperFunctions import ensure_dir, get_color_setup
from .HelperFunctions import save_pickle_file, l... | {"hexsha": "eec7e32853f342902f242cf18daaf26e829c4565", "size": 22932, "ext": "py", "lang": "Python", "max_stars_repo_path": "StatePerception/Trainer.py", "max_stars_repo_name": "graebe/StatePerception", "max_stars_repo_head_hexsha": "bba6743ef95ba5f1d693ba9d409188e37b0d95ec", "max_stars_repo_licenses": ["BSD-3-Clause"]... |
import deepmatcher as dm
import numpy as np
np.random.seed(42)
import random
random.seed(42)
if __name__ == "__main__":
data_dir = "/home/zz/Work/data/deepmatcher_toy/sample_data/itunes-amazon"
train, validation, test = \
dm.data.process(path=data_dir,
check_cached_data=False,
... | {"hexsha": "cacd15bd541f6934f979688a2423f230987cd12b", "size": 2017, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/sandbox/dm_test.py", "max_stars_repo_name": "ziqizhang/wop_matching", "max_stars_repo_head_hexsha": "dd1beb12284c1dd43889c09b4935b8fe20f7c36c", "max_stars_repo_licenses": ["BSD-3-Clause"], "ma... |
import pickle
import numpy as np
from scipy.stats import entropy
from create_edgelist import read_network
from collections import Counter
G, mapping = read_network(network_type='directed')
scratch_base = '/scratch/larock.t/shipping/results/interpolated_paths/'
#scratch_base = '../results/interpolated_paths/'
data = d... | {"hexsha": "1d750f2c6f3ea3b8578c49c2699ccda8b7f97255", "size": 1978, "ext": "py", "lang": "Python", "max_stars_repo_path": "code/degreeseq_vs_routeseq.py", "max_stars_repo_name": "tlarock/shipping", "max_stars_repo_head_hexsha": "9d8e608e98824281126248d726783eda8ddf80f5", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '0'
from numpy.random import randn, randint
from decimal import Decimal
from tqdm import tqdm
import pickle
from tensorflow.keras.utils import plot_model
from cDCGAN.Discriminator import make_discriminator
from cDCGAN.Generator import make_generator
import tensorf... | {"hexsha": "f3eead6a15850b160fdbbecd28d6381ab9d0348e", "size": 6840, "ext": "py", "lang": "Python", "max_stars_repo_path": "cDCGAN/cdcgan.py", "max_stars_repo_name": "Laende/Bacheloroppgave-droneteknologi", "max_stars_repo_head_hexsha": "15d9b2cd0eeba47fd2e9615fb01d598516826194", "max_stars_repo_licenses": ["MIT"], "ma... |
[STATEMENT]
lemma nn_integral_count_space_reindex:
"inj_on f A \<Longrightarrow>(\<integral>\<^sup>+ y. g y \<partial>count_space (f ` A)) = (\<integral>\<^sup>+ x. g (f x) \<partial>count_space A)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. inj_on f A \<Longrightarrow> integral\<^sup>N (count_space (f ` A)) g... | {"llama_tokens": 190, "file": "MFMC_Countable_MFMC_Misc", "length": 1} |
"""
SubgradientMaster
Implementation of projected subgradient method
"""
mutable struct SubgradientMaster <: AbstractLagrangeMaster
num_vars::Int
num_functions::Int
eval_f::Union{Nothing,Function}
iter::Int # current iteration count
maxiter::Int
obj_limit::Float64
f::Float64
best_... | {"hexsha": "e95599ce178e18658f47883c746b08abd02e4c51", "size": 4085, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/LagrangeMaster/SubgradientMethod.jl", "max_stars_repo_name": "kibaekkim/JuDD.jl", "max_stars_repo_head_hexsha": "de25e24f1475e3aaa5908335ba6749e88125c953", "max_stars_repo_licenses": ["MIT"], "... |
from collections.abc import Sequence
import numbers
import numpy as np
from brian2.core.variables import Variables, get_dtype
from brian2.groups.group import Group, CodeRunner
from brian2.utils.logger import get_logger
from brian2.units.fundamentalunits import Quantity
from brian2.units.allunits import second
__all_... | {"hexsha": "d49af0a604ad2883c342c42bf534df3ffde428c6", "size": 16296, "ext": "py", "lang": "Python", "max_stars_repo_path": "brian2/monitors/statemonitor.py", "max_stars_repo_name": "adriangb/brian2", "max_stars_repo_head_hexsha": "eef588f9b258af82dc5f8f06599ecf11bcaae53e", "max_stars_repo_licenses": ["BSD-2-Clause"], ... |
#!/usr/bin/env python3
import numpy as np
from numpy import sin, cos
from numpy.linalg import eig
from scipy.integrate import solve_ivp
import matplotlib.pyplot as plt
def system(t, x):
plant = np.array([ [ 0.0, 1.0],
[-1, -0.1] ])
desired_point = np.array([1.0,0.0])
error = desire... | {"hexsha": "a74279f16b58d376348508ec74252ef64ea75e71", "size": 675, "ext": "py", "lang": "Python", "max_stars_repo_path": "autopilot/proof.py", "max_stars_repo_name": "FunRoss7/sailing", "max_stars_repo_head_hexsha": "f4c931ea65b5c12ae3d6c4f533cd864da97f908c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
'''Test utilities in xroms'''
import xroms
import xarray as xr
import numpy as np
import cartopy
grid = xr.open_dataset('tests/input/grid.nc')
ds = xr.open_dataset('tests/input/ocean_his_0001.nc')
# combine the two:
ds = ds.merge(grid, overwrite_vars=True, compat='override')
def test_argsel2d():
'''Check that ... | {"hexsha": "84a28285e3e5efeb5ca960ea11194b94d9db6c39", "size": 3745, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_utils.py", "max_stars_repo_name": "ocefpaf/xroms", "max_stars_repo_head_hexsha": "763d6e678e28fe074e0aaab26fecd2b74e51a8b0", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 4, "m... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from time import time
import random
import networkx as nx
def random_walk(G, path_length, alpha=0, rand=random.Random(), start=None):
""" Returns a truncated random walk.
path_length: Length of the random walk.
alpha: probability of restarts.
... | {"hexsha": "717f95e3d665d5f13a206e5e7ee7834966e49bc1", "size": 1189, "ext": "py", "lang": "Python", "max_stars_repo_path": "algorithms/deepwalk/graph.py", "max_stars_repo_name": "mpoiitis/GraphM-framework", "max_stars_repo_head_hexsha": "82904b9940b029579b86c359e17312cfa7ef1692", "max_stars_repo_licenses": ["MIT"], "ma... |
/*
* Copyright (c) 2019 Opticks Team. All Rights Reserved.
*
* This file is part of Opticks
* (see https://bitbucket.org/simoncblyth/opticks).
*
* 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 ... | {"hexsha": "f475b6f03dd0afb6d673aee5f8f7fe6826a7e3ee", "size": 12497, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "npy/NGeoTestConfig.cpp", "max_stars_repo_name": "hanswenzel/opticks", "max_stars_repo_head_hexsha": "b75b5929b6cf36a5eedeffb3031af2920f75f9f0", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars... |
#!/usr/bin/env python3
import pandas as pd
import numpy as np
import math
import os
import sys
from datetime import datetime, timedelta
import matplotlib.pyplot as plt
import matplotlib.ticker as mticker
from jmaloc import MapRegion
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import cartopy.io.shapere... | {"hexsha": "8c430323502e90f07e8d2d29b372183a8cf06560", "size": 9540, "ext": "py", "lang": "Python", "max_stars_repo_path": "jma_ame_nrt/cartopy_jma_cumrain.py", "max_stars_repo_name": "yyousuke/jma_draw", "max_stars_repo_head_hexsha": "e8e24521e494ec7ae26be211bfc8ddc62bb73899", "max_stars_repo_licenses": ["MIT"], "max_... |
#redirect Institute of Transportation Studies
| {"hexsha": "7d7f54ec4509a0541569f04d7411f6d012d0ddea", "size": 46, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/Institute_for_Transportation_Studies.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["M... |
/-
Copyright (c) 2020 Johan Commelin. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Johan Commelin
-/
import ring_theory.witt_vector.basic
/-!
# Teichmüller lifts
This file defines `witt_vector.teichmuller`, a monoid hom `R →* 𝕎 R`, which embeds `r : R` as the
`0`... | {"author": "leanprover-community", "repo": "mathlib", "sha": "5e526d18cea33550268dcbbddcb822d5cde40654", "save_path": "github-repos/lean/leanprover-community-mathlib", "path": "github-repos/lean/leanprover-community-mathlib/mathlib-5e526d18cea33550268dcbbddcb822d5cde40654/src/ring_theory/witt_vector/teichmuller.lean"} |
[STATEMENT]
lemma dense_accessible_frontier_points:
fixes S :: "'a::{complete_space,real_normed_vector} set"
assumes "open S" and opeSV: "openin (top_of_set (frontier S)) V" and "V \<noteq> {}"
obtains g where "arc g" "g ` {0..<1} \<subseteq> S" "pathstart g \<in> S" "pathfinish g \<in> V"
[PROOF STATE]
proof (pr... | {"llama_tokens": 10377, "file": null, "length": 114} |
import numpy as np
import scipy as sp
import scipy.spatial.distance
import matplotlib.pyplot as plt
from keras import backend as K
from ViewMNIST import PlotResult
def GetFeature(x, functor, saveIdx, normalize=False):
embedding = None
try:
layer_outs = functor([x, 0.])
embedding = layer_outs[... | {"hexsha": "6cb8c3fccaf0a289c26128905937527c1d3f7bf6", "size": 1780, "ext": "py", "lang": "Python", "max_stars_repo_path": "ReIDHelpers.py", "max_stars_repo_name": "psiva7/MNISTTriplet", "max_stars_repo_head_hexsha": "695897b5229387a092b69b5de17dbd996ca2d899", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null... |
import matplotlib.pyplot as plt
import numpy as np
from scipy.stats import norm
from functools import reduce
import sys
import subprocess
import argparse
import pandas as pd
from statistics import mean, variance, stdev, median_grouped
# ref. https://qiita.com/qsnsr123/items/325d21621cfe9e553c17
plt.rcParams['font.fa... | {"hexsha": "4f1eab1c3cc220b768892c9f8150bd1767358d7c", "size": 15604, "ext": "py", "lang": "Python", "max_stars_repo_path": "calc_e2e.py", "max_stars_repo_name": "mu-mu-mu/ros1_analysis", "max_stars_repo_head_hexsha": "48f69e337cee9a992904fa6b5394251f8876cdc0", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_coun... |
C
C $Id: kurv1.f,v 1.5 2008-07-27 03:10:11 haley Exp $
C
C Copyright (C) 2000
C University Corporation for Atmospheric Research
C All Rights Reserved
C
C The use of this Software is governed by a License Agreemen... | {"hexsha": "c659c950ded7fa10e14c12ee73761e15a77d20c5", "size": 6071, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "ngmath/src/lib/gridpack/fitgrid/kurv1.f", "max_stars_repo_name": "tenomoto/ncl", "max_stars_repo_head_hexsha": "a87114a689a1566e9aa03d85bcf6dc7325b47633", "max_stars_repo_licenses": ["Apache-2.0"]... |
import numpy as np
import fabio
import configparser
from fabio.edfimage import edfimage
from fabio.tifimage import tifimage
### This function save the calibrant image as edf extension ###
### root_save: path of the folder where the image will be saved
### save_img_name: name of the image
### extension: format... | {"hexsha": "477ecb619cb11c6c1f784ced6d35c64a291e4375", "size": 637, "ext": "py", "lang": "Python", "max_stars_repo_path": "easistrain/func_save_edf_image.py", "max_stars_repo_name": "woutdenolf/easistrain", "max_stars_repo_head_hexsha": "0484168e33e548af01a5cc649abf815c45b182f1", "max_stars_repo_licenses": ["MIT"], "ma... |
import torch
import os
import gc
import pandas as pd
import numpy as np
from BengaliDataset import BengaliDataset
from Resnet import ResNet
from Utils import seed_everything
# Constants
# Setting
SEED = 222
BATCH_SIZE = 64
HEIGHT = 137
WIDTH = 236
device = "cuda" if torch.cuda.is_available() else "cpu"
seed_everythin... | {"hexsha": "21928405de2a90801cea41fca354009a06452e87", "size": 2525, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/CreateTestCsv.py", "max_stars_repo_name": "jaswged/bengali-handwritten-ai", "max_stars_repo_head_hexsha": "aef86c495255cf9ec671f46f1c919a7f97d35762", "max_stars_repo_licenses": ["MIT"], "max_s... |
import numpy as np
import scipy.sparse as sp
from ...common_files.common_infos import CommonInfos
import multiprocessing as mp
from ...solvers.solvers_scipy.solver_sp import SolverSp
from ...solvers.solvers_trilinos.solvers_tril import solverTril
import time
class masterNeumanNonNested:
def __init__(self, data_i... | {"hexsha": "4493bf3c587db86f991807366822c87413283ba8", "size": 14055, "ext": "py", "lang": "Python", "max_stars_repo_path": "packs/adm/non_uniform/paralel_neuman_new0.py", "max_stars_repo_name": "CiceroAraujo/SB", "max_stars_repo_head_hexsha": "637cc4bc63c952f058c316b2b1fbfbb5cd6250c8", "max_stars_repo_licenses": ["MIT... |
[STATEMENT]
theorem mk_alt_consistency_subset: \<open>C \<subseteq> mk_alt_consistency C\<close>
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. C \<subseteq> mk_alt_consistency C
[PROOF STEP]
unfolding mk_alt_consistency_def
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. C \<subseteq> {S. \<exists>f. psubst f ` S... | {"llama_tokens": 980, "file": "FOL-Fitting_FOL_Fitting", "length": 14} |
import argparse
import os
import numpy as np
from PIL import Image
from matplotlib import pyplot as plt
# --------------- Arguments ---------------
parser = argparse.ArgumentParser(description='Colorpalette')
parser.add_argument('--img', type=str, required=True)
args = parser.parse_args()
def get_dom... | {"hexsha": "843893c11a0e2b8a707dfbaeb77ee59f82a21883", "size": 2363, "ext": "py", "lang": "Python", "max_stars_repo_path": "ColorpaletteFromImage.py", "max_stars_repo_name": "flow-dev/ColorpaletteFromImage", "max_stars_repo_head_hexsha": "5763942a7a5f6cf2d975e51a738a6e7df3c73538", "max_stars_repo_licenses": ["MIT"], "m... |
#!/usr/bin/env python3
"""
This python scripts visualizes and plots the 3D
voxels based on their confidence score and produces a heatmap.
"""
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
import numpy as np
from pylab import *
import time
import torch
def visualizeVoxels(voxelGrids, frameRa... | {"hexsha": "c432df790ebd4bac4da093ac02ceaeb3645102cc", "size": 2182, "ext": "py", "lang": "Python", "max_stars_repo_path": "tools/plotvoxel.py", "max_stars_repo_name": "prithusuresh/semantic-point-generation", "max_stars_repo_head_hexsha": "e9dd107b86e6068bd1de38b6dc177108a54deee1", "max_stars_repo_licenses": ["Apache-... |
library(rhdf5)
library(qvalue)
library(dplyr)
##Settings
baseFolder <- "C:/OnlineFolders/BitSync/Current_Work/EBI_HipSci/T/"
#################
##Read files.
setwd(baseFolder)
observedFeatures <- 0
results <- NULL
snpAnnotation <- NULL
featureAnnotation <- NULL
filesToRead <- list.files(".",pattern = ".h... | {"hexsha": "9a40818524c8bf9e23bd58f148d88e66af3c7dd3", "size": 911, "ext": "r", "lang": "R", "max_stars_repo_path": "Limix_QTL/post_processing/scripts/R/GettingPermQTLsFromH5.r", "max_stars_repo_name": "Bonder-MJ/limix_qtl", "max_stars_repo_head_hexsha": "71f18f4e39cdba0f0e6dc59713b83701599bc86f", "max_stars_repo_licen... |
import cv2
import numpy as np
from lib.dataset import resize
def find_circle(image, kernel=33):
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
image_gray = resize(image, 512, size_is_min=True)
image_gray = cv2.medianBlur(image_gray, kernel)
height, width = image_gray.shape
min_dim = min(height, ... | {"hexsha": "c3c522ad299cd3ee08543d4003637c00af986cb8", "size": 2042, "ext": "py", "lang": "Python", "max_stars_repo_path": "preprocessing/image_ops.py", "max_stars_repo_name": "wonderit/aptos-retinopathy-detection", "max_stars_repo_head_hexsha": "8402ce798fa0419627fb878788fa771849e34516", "max_stars_repo_licenses": ["M... |
From SyDPaCC.Tree Require Import
Skeletons Closure BTree.
From SyDPaCC.Bsml Require Import Model.Core Model.Pid Skeletons.StdLib.
From SyDPaCC.Core Require Import Bmf Parallelization.
Require Import Lia NArith.
Open Scope N_scope.
Module Make (Import Bsml : SyDPaCC.Bsml.Model.Core.BSML).
Module Pid := Pid.Mak... | {"author": "SyDPaCC", "repo": "sydpacc", "sha": "640f0f74f21524ee203b192255ecfa9e456fb7d1", "save_path": "github-repos/coq/SyDPaCC-sydpacc", "path": "github-repos/coq/SyDPaCC-sydpacc/sydpacc-640f0f74f21524ee203b192255ecfa9e456fb7d1/Tree/Applications/MapOne.v"} |
"""Some custom helper types to make type hints and type checking easier.
For user facing type declarations, please see :py:func:`biopsykit.utils.datatype_helper`.
"""
from pathlib import Path
from typing import Hashable, Sequence, TypeVar, Union
import numpy as np
import pandas as pd
_Hashable = Union[Hashable, str... | {"hexsha": "5b1fddc4d202f434e11819bad248ea09142a7926", "size": 578, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/biopsykit/utils/_types.py", "max_stars_repo_name": "Zwitscherle/BioPsyKit", "max_stars_repo_head_hexsha": "7200c5f1be75c20f53e1eb4c991aca1c89e3dd88", "max_stars_repo_licenses": ["MIT"], "max_st... |
import gym
import tensorflow as tf
import numpy as np
from collections import deque
from stable_baselines import logger
from stable_baselines.ppo2 import PPO2
from stable_baselines.ppo2.ppo2 import swap_and_flatten
from stable_baselines.common.callbacks import BaseCallback, CallbackList
from stable_baselines.asil.cal... | {"hexsha": "9db9bdb39d0160dcc69b594c9e88680a48d24e2f", "size": 19073, "ext": "py", "lang": "Python", "max_stars_repo_path": "stable_baselines/asil/asil.py", "max_stars_repo_name": "philippaltmann/ASIL", "max_stars_repo_head_hexsha": "d01d782e6fe0dd21ad2aadcb02f0f380732f81d7", "max_stars_repo_licenses": ["MIT"], "max_st... |
import slicer
import math
import numpy as np
from fMRSICore import MatLibraryClass as matLibraryClass
from fMRSICore import UnitClass as unitClass
class SpectrumClass(object):
""" properties """
""" % constantes """
STATUS_OK = 0;
FILE_ERROR = -1;
status = STATUS_OK ;
#figureArrang... | {"hexsha": "70d1fdc4a84bb3eb572135774b83dea3ac30951d", "size": 10177, "ext": "py", "lang": "Python", "max_stars_repo_path": "PFileParser/fMRSICore/SpectrumClass.py", "max_stars_repo_name": "fmarcano/SlicerFMRSI", "max_stars_repo_head_hexsha": "e6c538938275fd6d917f2287fb0da49b67dcf6ef", "max_stars_repo_licenses": ["Apac... |
#define BOOST_TEST_DYN_LINK
#ifdef STAND_ALONE
#define BOOST_TEST_MODULE Main
#endif
#include <boost/test/unit_test.hpp>
#include "time_helper.h"
#include <iostream>
namespace r = reinforcement_learning;
BOOST_AUTO_TEST_CASE(time_usage) {
r::clock_time_provider ctp;
const uint16_t NUM_ITER = 1000;
for (int i = ... | {"hexsha": "cfe77c25d39163c9c0970dd2f2fc04c84334ab90", "size": 1290, "ext": "cc", "lang": "C++", "max_stars_repo_path": "unit_test/time_tests.cc", "max_stars_repo_name": "yannstad/reinforcement_learning", "max_stars_repo_head_hexsha": "29e5a4f786ed81ed2c9bc64ae6b14bdbf18b99e4", "max_stars_repo_licenses": ["MIT"], "max_... |
! Copyright 2020 Free Software Foundation, Inc.
! This program is free software; you can redistribute it and/or modify
! it under the terms of the GNU General Public License as published by
! the Free Software Foundation; either version 3 of the License, or
! (at your option) any later version.
!
! This program is dis... | {"hexsha": "b72cd1bb2bccb4fd80c2d38bd85c799e75cdafa2", "size": 901, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "contrib/gnu/gdb/dist/gdb/testsuite/gdb.fortran/array-bounds-high.f90", "max_stars_repo_name": "TheSledgeHammer/2.11BSD", "max_stars_repo_head_hexsha": "fe61f0b9aaa273783cd027c7b5ec77e95ead2153", ... |
import quantum_circuit.gates
from quantum_circuit.gates import State
import quantum_circuit.gates_library as g_lib
import numpy as np
import math
from tests.testcase import BaseTestCase
class TestShor(BaseTestCase):
def test_shor(self):
# run test and see if errors are thrown
main()
def main():... | {"hexsha": "3f0f8a8cabcedcc694a1f1d2e808183a1e6c21ae", "size": 1390, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_grover.py", "max_stars_repo_name": "mathisgerdes/Quantum_Computing_Project", "max_stars_repo_head_hexsha": "d83855003da7b45b0ea90e9b214d78c6d452379b", "max_stars_repo_licenses": ["MIT"]... |
subroutine furlea(
i spavac,time1,time0,
m ii)
c
c + + + PURPOSE + + +
c This subprogram allows for lower end advance during the depletion
c and recession phases.
c
c Called from FURREC
c Author(s): E. R. Kottwitz
c Reference in U... | {"hexsha": "f59150ff0b4d8505897e0add5e69381bb211a701", "size": 4261, "ext": "for", "lang": "FORTRAN", "max_stars_repo_path": "src/wepp2010.1/furlea.for", "max_stars_repo_name": "jarad/dep", "max_stars_repo_head_hexsha": "fe73982f4c70039e1a31b9e8e2d9aac31502f803", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1... |
theory Mg_Prod
imports "../Pord" "../Mergeable" "../Bump"
begin
(* For product types, we impose an ordering that requires that _all_ components of
* product a be less than or equal to their corresponding components of b,
* in order for a <[ b to hold.
*
* In other words, this is _not_ a lexicographic ordering. L... | {"author": "mmalvarez", "repo": "Gazelle", "sha": "0a80144107b3ec7487725bd88d658843beb6cb82", "save_path": "github-repos/isabelle/mmalvarez-Gazelle", "path": "github-repos/isabelle/mmalvarez-Gazelle/Gazelle-0a80144107b3ec7487725bd88d658843beb6cb82/Mergeable/Instances/Mg_Prod.thy"} |
import os
import nltk
nltk.download('punkt')
nltk.download('wordnet')
import numpy
from tensorflow import keras
import random
import json
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.stem.snowball import SnowballStemmer
scriptpath = os.path.abspath(__file__)
scriptdir = os.path.dirname(scriptpath)
INTENTS... | {"hexsha": "b72ea6f06961554705caa4d0eb7f8d5a4c4a9ce0", "size": 3789, "ext": "py", "lang": "Python", "max_stars_repo_path": "api/bot/chatbot-deployment/ChatbotFunctions.py", "max_stars_repo_name": "Ammar-Raneez/SDGP-MEDIC-IN-ONE", "max_stars_repo_head_hexsha": "bffcc424a1cde4eaad012cfba6fbeeb4b12e75d3", "max_stars_repo_... |
using LinearAlgebra
function sigmoid(a)
return 1.0 / (1 + exp(-a))
end
function fit(x, t; alpha = 0.01, tau_max = 1000)
function CEE(w, x, t)
grad = zeros(size(w))
for i in 1:length(t)
ti = (t[i] > 0) ? 1 : 0
h = sigmoid(dot(w, x[i, :]))
grad += ((h - ti) * x[... | {"hexsha": "c6443455c31facba90bdd0c9c8840972cd0a27f9", "size": 1304, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/Classification/OVR.jl", "max_stars_repo_name": "QGMW22/Horse.jl", "max_stars_repo_head_hexsha": "77be589dbf047a029615dde7773360ebcb5d99b6", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
# Imports
import torch
from torch.utils.data import DataLoader, Dataset
from torchvision import datasets
import os
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import warnings
from skimage.transform import resize as sk_resize
from skimage import exposure
warnings.filterwarnings('ign... | {"hexsha": "13f5bc52ea78ae2144c6893a9d35d976fc3228c3", "size": 4819, "ext": "py", "lang": "Python", "max_stars_repo_path": "emotion_detection/fer_data_utils.py", "max_stars_repo_name": "anmol-sinha-coder/DEmoClassi", "max_stars_repo_head_hexsha": "476e8ffe95312b302f02dd44d238d5c447e5b054", "max_stars_repo_licenses": ["... |
section \<open>Static data dependence\<close>
theory DataDependence imports "../Basic/DynDataDependence" begin
context CFG_wf begin
definition data_dependence :: "'node \<Rightarrow> 'var \<Rightarrow> 'node \<Rightarrow> bool"
("_ influences _ in _" [51,0])
where data_dependences_eq:"n influences V in n' \<equi... | {"author": "data61", "repo": "PSL", "sha": "2a71eac0db39ad490fe4921a5ce1e4344dc43b12", "save_path": "github-repos/isabelle/data61-PSL", "path": "github-repos/isabelle/data61-PSL/PSL-2a71eac0db39ad490fe4921a5ce1e4344dc43b12/SeLFiE/Example/afp-2020-05-16/thys/Slicing/StaticIntra/DataDependence.thy"} |
-makelib xcelium_lib/xilinx_vip -sv \
"D:/Xilinx/Vivado/2018.2/data/xilinx_vip/hdl/axi4stream_vip_axi4streampc.sv" \
"D:/Xilinx/Vivado/2018.2/data/xilinx_vip/hdl/axi_vip_axi4pc.sv" \
"D:/Xilinx/Vivado/2018.2/data/xilinx_vip/hdl/xil_common_vip_pkg.sv" \
"D:/Xilinx/Vivado/2018.2/data/xilinx_vip/hdl/axi4stream_vip... | {"hexsha": "90622289a116c061894fca534214b052592b645c", "size": 28687, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "project_1/project_1.ip_user_files/sim_scripts/design_1/xcelium/run.f", "max_stars_repo_name": "qxynju2017/Nexys-Video-Microblaze-OV5640-HDMI-", "max_stars_repo_head_hexsha": "64392396aab6c6b92c05... |
import mylib
import ctypes
import numpy as np
print("Try test_empty:")
mylib.test_empty()
print("\nTry test_add:")
print(mylib.test_add(34.55, 23))
print("\nTry test_add_double:")
print(mylib.test_add_double(34.55, 43.0))
# Create a 25 elements array
numel = 25
data = (ctypes.c_int * numel)(*[x for x in range(nume... | {"hexsha": "33e0d55fe93cbffac3dd7206c100f592d0b16798", "size": 1911, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/C++/Core/Python/test_mylib.py", "max_stars_repo_name": "cesmix-mit/MDP", "max_stars_repo_head_hexsha": "746e4f4aead5911ddeda77b0d2c117e3b70cc5c4", "max_stars_repo_licenses": ["MIT"], "max_star... |
\chapter*{Abstract}
Maximising the economic effectiveness of a wind farm is essential in making wind a more economic source of energy. This effectiveness can be increased through the reduction of operation and maintenance costs, which can be achieved through continuously monitoring the condition of wind turbines. An a... | {"hexsha": "bfb8a902622f582374fd84e422ad3694c9022d16", "size": 2051, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "docs/abstract.tex", "max_stars_repo_name": "nmstreethran/WindTurbineClassification", "max_stars_repo_head_hexsha": "b0ea6de909ccd5bb425cee291ca3c252c11df4eb", "max_stars_repo_licenses": ["MIT"], "ma... |
struct NNStatistics
units::String
arealUnits::String
area::Polygon
observedMeanDistance::Real
expectedMeanDistance::Real
nearestNeighbourIndex::Real
pointsCount::Real
zScore::Real
end
"""
analysis(data::F, area::Union{P, Nothing}=nothing, units::String="kilometers") ... | {"hexsha": "56ad33b06abaf0f062476104c172569abfc07146", "size": 2794, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/lib/NearestNeighbour.jl", "max_stars_repo_name": "visr/Turf.jl", "max_stars_repo_head_hexsha": "fe3a61fabe6d5b9e7f0197bf1820be25432c467d", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Implements a simple high/low pass filter for audio source separation
"""
from __future__ import division
import numpy as np
import scipy.signal
import mask_separation_base
from ideal_mask import IdealMask
class HighLowPassFilter(mask_separation_base.MaskSeparationB... | {"hexsha": "e0136bb10914166b84c838e0666b9a3f3e5fa2c4", "size": 4524, "ext": "py", "lang": "Python", "max_stars_repo_path": "build/lib/nussl/separation/high_low_pass_filter.py", "max_stars_repo_name": "KingStorm/nussl", "max_stars_repo_head_hexsha": "78edfdaad16845fc705cefb336a7e6e5923fbcd4", "max_stars_repo_licenses": ... |
import os
import sys
import numpy as np
from PIL import Image
num=1
path ="/Users/pection/Documents/mn_furniture/AddwatermarkProgram/Lastday/"
#we shall store all the file names in this list
filelist=[]
for root, dirs, files in os.walk(path):
for file in files:
if(file.endswith(".jpg")):
filelis... | {"hexsha": "dd7f9dbcfe5bd13ce56beb5ae807d4bb63f3c4df", "size": 1609, "ext": "py", "lang": "Python", "max_stars_repo_path": "Program_python/Extractfolderimage.py", "max_stars_repo_name": "pection/MN-furniture", "max_stars_repo_head_hexsha": "4c796f072662c15b2a263272ef2637e221c42cab", "max_stars_repo_licenses": ["MIT"], ... |
from __future__ import print_function
import numpy as np
import tensorflow as tf
import sklearn.metrics
# Import MNIST data
from tensorflow.examples.tutorials.mnist import input_data
def readData(filename):
with open(filename, 'r') as f:
string = [line.strip().split('\t') for line in f.readlin... | {"hexsha": "b342df6655d48103222dd408514e69bb3613f130", "size": 2589, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/knn/knn.py", "max_stars_repo_name": "ZhengtianXu/Gene_Chip", "max_stars_repo_head_hexsha": "f7b8e84bdaf8963923de16443fac22ce11df5714", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 17... |
[STATEMENT]
lemma PsiInv_alpha1: "\<turnstile> alpha1 \<and> $PsiInv \<longrightarrow> PsiInv$"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<turnstile> alpha1 \<and> $PsiInv \<longrightarrow> PsiInv$
[PROOF STEP]
by (auto simp: alpha1_def PsiInv_defs) | {"llama_tokens": 103, "file": null, "length": 1} |
[STATEMENT]
lemma [code abstract]:
"integer_of_natural (m - n) = max 0 (integer_of_natural m - integer_of_natural n)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. integer_of_natural (m - n) = max 0 (integer_of_natural m - integer_of_natural n)
[PROOF STEP]
by transfer simp | {"llama_tokens": 107, "file": null, "length": 1} |
using Test
using JSON3
using Pinecone
APIKEY = ENV["PINECONE_API_KEY"]
CLOUDENV="us-west1-gcp"
context = Pinecone.init(APIKEY, CLOUDENV)
INDEX = "filter-example"
NAMESPACE = "mynamespace"
index = Pinecone.Index(INDEX);
@testset verbose = true "Create/Delete" begin
testindexname = "unittestindex"
@testset ... | {"hexsha": "af6b951ba6def5978beab9bd842468fded56664a", "size": 2286, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/testcreatedelete.jl", "max_stars_repo_name": "tullytim/Pinecone.jl", "max_stars_repo_head_hexsha": "1846a919bd1ba337e8c3f161d7f95469cdd2d252", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import pytest
import numpy as np
from context import Runner, ExecutionType, get_configs, docker_available
class MockContext():
def __init__(self):
self.obj = {}
@pytest.mark.skipif(not docker_available(), reason='Docker is not available')
def test_runner_langermann():
internal_conf = get_configs('c... | {"hexsha": "efbcd20984caeb62b715ba75dbe7a42ac7515b65", "size": 685, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/test_runner.py", "max_stars_repo_name": "d53dave/cgopt", "max_stars_repo_head_hexsha": "a655d87a8577d18a7a714431f4237e4c9ebbf7e8", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 1, "m... |
# -*- coding: utf-8 -*-
from distutils.version import LooseVersion
import numpy
from aiida.orm import Dict, TrajectoryData
from qe_tools import CONSTANTS
from .base import Parser
from .parse_raw.cp import parse_cp_raw_output, parse_cp_traj_stanzas
class CpParser(Parser):
"""This class is the implementation of t... | {"hexsha": "143030d7b7b4c832b03c3fdc365597fe2ddd2f5f", "size": 16514, "ext": "py", "lang": "Python", "max_stars_repo_path": "aiida_quantumespresso/parsers/cp.py", "max_stars_repo_name": "ramirezfranciscof/aiida-quantumespresso", "max_stars_repo_head_hexsha": "cb32be5361afa05bad617f00f8b187c96eb365ec", "max_stars_repo_l... |
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
This module provides tools for calculating total error arrays.
"""
import astropy.units as u
from astropy.utils.misc import isiterable
import numpy as np
__all__ = ['calc_total_error']
def calc_total_error(data, bkg_error, effective_gain):
"""
... | {"hexsha": "67e969f13b71b077283c91eeb3346832c2d32774", "size": 7791, "ext": "py", "lang": "Python", "max_stars_repo_path": "photutils/utils/errors.py", "max_stars_repo_name": "pllim/photutils", "max_stars_repo_head_hexsha": "ff78b6dd97a9fa890b6c77b51f207d4c2ff28889", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_st... |
[STATEMENT]
lemma up_injective:
"\<up>x = \<up>y \<Longrightarrow> x = y"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<up>x = \<up>y \<Longrightarrow> x = y
[PROOF STEP]
using order.antisym
[PROOF STATE]
proof (prove)
using this:
\<lbrakk>?a \<le> ?b; ?b \<le> ?a\<rbrakk> \<Longrightarrow> ?a = ?b
goal (1 sub... | {"llama_tokens": 172, "file": "Stone_Algebras_Filters", "length": 2} |
"""
check https://github.com/thautwarm/MLStyle.jl/blob/master/matrix_benchmark.jl
"""
include("matrix-benchmark/sampler.jl")
include("matrix-benchmark/utils.jl")
export ArbitrarySampler
export Utils
versus_items = ("datatype", "misc", "tuple", "array", "structfields", "vs-match")
function run_all()
for item in v... | {"hexsha": "bed74abf1a55f53e09cf9b9fff5ceb6ab1e73c12", "size": 531, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "benchmark.jl", "max_stars_repo_name": "caseykneale/MLStyle.jl", "max_stars_repo_head_hexsha": "866e3bf3fcd21329bdc8cf3bd0d8d576fe33b666", "max_stars_repo_licenses": ["MIT"], "max_stars_count": 309, ... |
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
Unit tests for KinwaveImplicitOverlandFlowModel.
Created on Sat Apr 1 10:49:33 2017
@author: gtucker
"""
from numpy.testing import assert_allclose, assert_raises
from landlab import RasterModelGrid
from landlab.components import LinearDiffusionOverlandFlowRouter
... | {"hexsha": "f8a4616e592559a9ac6ff3141c3be3df862a44ba", "size": 2136, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/components/overland_flow/test_linear_diffusion_overland_flow.py", "max_stars_repo_name": "clebouteiller/landlab", "max_stars_repo_head_hexsha": "e6f47db76ea0814c4c5a24e695bbafb74c722ff7", "m... |
import logging
import uuid
import numpy as np
from sklearn.datasets import load_diabetes
import pandas as pd
import os
from commons.utils.singleton import Singleton
class Metadata:
id = None
filename = None
features = None
features_min = None
features_max = None
target_min = None
target_m... | {"hexsha": "755c2f37f3588d625a196b2711a03dcf726867a1", "size": 6699, "ext": "py", "lang": "Python", "max_stars_repo_path": "commons/data/data_loader.py", "max_stars_repo_name": "DeltaML/commons", "max_stars_repo_head_hexsha": "5f75783e8e63972bc906fac9f63eb4d1469cad4a", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
[STATEMENT]
lemma en_eq_3[PLM]:
"[\<^bold>\<diamond>\<lbrace>x,F\<rbrace> \<^bold>\<equiv> \<lbrace>x,F\<rbrace> in v]"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. [\<^bold>\<diamond>\<lbrace>x,F\<rbrace> \<^bold>\<equiv> \<lbrace>x,F\<rbrace> in v]
[PROOF STEP]
using encoding[axiom_instance] derived_S5_rules... | {"llama_tokens": 444, "file": "PLM_TAO_9_PLM", "length": 2} |
[STATEMENT]
lemma alphaAbs_qAbs_imp_alphaAbs_all_qFresh:
assumes "qGood X" and "qAbs xs x X $= qAbs xs' x' X'"
shows "alphaAbs_all_qFresh xs x X xs' x' X'"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. alphaAbs_all_qFresh xs x X xs' x' X'
[PROOF STEP]
proof-
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. alphaAb... | {"llama_tokens": 1751, "file": "Binding_Syntax_Theory_QuasiTerms_PickFresh_Alpha", "length": 16} |
MODULE wlGridModule
USE wlKindModule, ONLY: dp
IMPLICIT NONE
PRIVATE
TYPE, PUBLIC :: GridType
CHARACTER(LEN=32) :: Name
CHARACTER(LEN=32) :: Unit
INTEGER :: nPoints
INTEGER :: LogInterp
REAL(dp) :: minValue
REAL(dp) :: maxValue
REAL(dp), DIMENSION(:), ALLOCATABLE :: Values
END... | {"hexsha": "995c9f91777dc0034476b34a5c388a34e2c0bed9", "size": 3044, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "Distributions/Library/wlGridModule.f90", "max_stars_repo_name": "srichers/weaklib", "max_stars_repo_head_hexsha": "4a26ff17d3224d8fe90b922cb55ea9d865200154", "max_stars_repo_licenses": ["BSD-3-C... |
#!/usr/bin/env python
import rospy
import numpy as np
from geometry_msgs.msg import Point
from std_msgs.msg import Int64
import time
import math
from Adafruit_MotorHAT import Adafruit_MotorHAT
class gazebo_car_control_node(object):
def __init__(self):
self.node_name = "gazebo_car_control_node"
self.active = Tr... | {"hexsha": "258a2d48560b1ec21f684475acb740739ffc103d", "size": 2229, "ext": "py", "lang": "Python", "max_stars_repo_path": "catkin_ws/src/arg_nctu/kaku/duckietown_kaku/src/gazebo_car_control_node.py", "max_stars_repo_name": "eric565648/duckietown-pi2", "max_stars_repo_head_hexsha": "33af7985a857a323e15d20e6572bc07530a1... |
import os.path as osp
from PIL import Image
from torch.utils.data import Dataset
from torchvision import transforms
import os
import numpy as np
class MiniImageNet(Dataset):
def __init__(self, setname, args, return_path=False):
IMAGE_PATH = os.path.join(args.data_dir, 'miniimagenet/images')
SPLIT... | {"hexsha": "8ab819d07f24d03a67d3ed1fcde2941dffd6b502", "size": 2349, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/dataloader/mini_imagenet.py", "max_stars_repo_name": "TJUdyk/Matrix_RENet", "max_stars_repo_head_hexsha": "5d066e4e08e412b1f880c63743edfdb72bdc7138", "max_stars_repo_licenses": ["MIT"], "ma... |
\section{Summary and Conclusions}
\label{sec:conclusions}
We have developed a realizability-preserving DG-IMEX scheme for a two-moment model of fermion transport.
The scheme employs algebraic closures based on Fermi-Dirac statistics and combines a time step restriction (CFL condition), a realizability-enforcing limi... | {"hexsha": "8c39a14fd89c0b670f4610105fa48dbc1619739c", "size": 4881, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "Documents/M1/realizableFermionicM1/sections/conclusion.tex", "max_stars_repo_name": "srichers/thornado", "max_stars_repo_head_hexsha": "bc6666cbf9ae8b39b1ba5feffac80303c2b1f9a8", "max_stars_repo_lic... |
import cv2
import numpy as np
import time
import threading
import queue
from xavier_config import qsize
class VideoStream(threading.Thread):
def __init__(self, url, pos, frame_q, resolution=(360, 640), threaded=False):
super(VideoStream, self).__init__()
self.cam = cv2.VideoCapture(url)
se... | {"hexsha": "7c5dea8b3325b442440b8413ee23c1fce310ff90", "size": 7318, "ext": "py", "lang": "Python", "max_stars_repo_path": "xavier/streamutils.py", "max_stars_repo_name": "igarag/homesecurity", "max_stars_repo_head_hexsha": "35e9ea3b02fbeed771ad9d7c1bd474c36b8b64d3", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
# Main window and functions of the ephys analysis program
import sys
from PyQt5.QtCore import Qt, pyqtSlot, QEvent
from PyQt5.QtWidgets import QMainWindow, QAction, QLabel, QGridLayout, \
QPushButton, QButtonGroup, QRadioButton, QVBoxLayout, QHBoxLayout, \
QTextEdit, QWidget, QFileDialog, QApplication, QCheckBox,\... | {"hexsha": "3b46dce4d7de86b27484ba7d6ee28ee87923ada7", "size": 21906, "ext": "py", "lang": "Python", "max_stars_repo_path": "whole_cell_patch/main.py", "max_stars_repo_name": "11uc/whole_cell_patch", "max_stars_repo_head_hexsha": "84e11bbb904b363a6bb5af878d46e23d789c5be0", "max_stars_repo_licenses": ["MIT"], "max_stars... |
//initialization related to ros
#include "ros/ros.h"
#include "std_msgs/Byte.h"
//#include "std_msgs/String.h"
//#include "dynamixel_workbench_msgs/DynamixelCommand.h"
#include <darknet_ros_msgs/BoundingBoxes.h>
#include <gb_visual_detection_3d_msgs/BoundingBoxes3d.h>
#include <python2.7/Python.h>
//#include <thre... | {"hexsha": "33af2bc16b4882fdb78c551b323761e094e62c87", "size": 17098, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "final/rosi_controller/src/mobile_tolerance.cpp", "max_stars_repo_name": "songdaegeun/school-zone-enforcement-system", "max_stars_repo_head_hexsha": "b5680909fd5a348575563534428d2117f8dc2e3f", "max_... |
/**
* Copyright (c) 2018, University Osnabrück
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
* * Redistributions of source code must retain the above copyright
* notice, this li... | {"hexsha": "366e1a7c978857bf174af29a05486a15b63c781f", "size": 16761, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/tools/lvr2_reconstruct/Options.hpp", "max_stars_repo_name": "uos/lvr", "max_stars_repo_head_hexsha": "9bb03a30441b027c39db967318877e03725112d5", "max_stars_repo_licenses": ["BSD-3-Clause"], "ma... |
from typing import Dict, Union
import numpy as np
from scipy.optimize import linear_sum_assignment # type: ignore
from ..dist import iou_dist
from ..tracks import Tracks
def calculate_id_metrics(
ground_truth: Tracks, hypotheses: Tracks, dist_threshold: float = 0.5
) -> Dict[str, Union[float, int]]:
gts =... | {"hexsha": "a421ece6f5afcfca51e749653b86e5f8fd8da341", "size": 2290, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/evaldet/mot_metrics/identity.py", "max_stars_repo_name": "traffic-ai/EvalDeT", "max_stars_repo_head_hexsha": "3b52698e1b03fb9066e3203c2f36aebfa0030aba", "max_stars_repo_licenses": ["Apache-2.0... |
#' #This source code is provided under the BSD license and is provided AS IS with no warranty or guarantee of fit for purpose. See the project's LICENSE.txt for details.
#' #Copyright Thomson Reuters 2013. All rights reserved.
#' @param dates dates
#' @param seccodes seccodes
#' @param per.seccode per.seccode
#' ... | {"hexsha": "52a85b7f752650874f4b3e2ef083767a35c1db5b", "size": 1035, "ext": "r", "lang": "R", "max_stars_repo_path": "R/get.unadj.daily.close.r", "max_stars_repo_name": "thomsonreuters/oqad", "max_stars_repo_head_hexsha": "eeebc58aebdc514513d41f572ca89b170996ae8e", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_star... |
// Copyright (c) 2014-2021 The Bitcoin Core developers
// Distributed under the MIT software license, see the accompanying
// file COPYING or http://www.opensource.org/licenses/mit-license.php.
#include <chainparams.h>
#include <consensus/amount.h>
#include <net.h>
#include <signet.h>
#include <uint256.h>
#include <va... | {"hexsha": "a0871174c41fc75187990fec6284998c5b0c3863", "size": 8413, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/test/validation_tests.cpp", "max_stars_repo_name": "spaceexpanse/xaya", "max_stars_repo_head_hexsha": "49aee2d5abc0c36d6aee990e7acbc3aece2b7a82", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
from numpy.testing import assert_allclose, run_module_suite
from pyins import earth
def test_principal_radii():
lat = 0
re, rn = earth.principal_radii(lat)
assert_allclose(re, earth.R0, rtol=1e-10)
assert_allclose(rn, earth.R0 * (1 - earth.E2), rtol=1e-10)
lat = [0, 90]
re, rn = earth.princip... | {"hexsha": "3727a4f61e7d39e04465de369c8a44716b191e62", "size": 1546, "ext": "py", "lang": "Python", "max_stars_repo_path": "pyins/tests/test_earth.py", "max_stars_repo_name": "toniklenk/pyins", "max_stars_repo_head_hexsha": "db18a6083dbd7397315095d9a5096cd515f7e248", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
This module defines a class `PartitionExt` which extends the `Partition` class in SageMath with
methods related to the computation of the generalized core and quotient decomposition as described in [Pearce, 2020].
See the docstring of the `PartitionExt` class for a des... | {"hexsha": "f91a053fa833361787bd1251951cc18b6fa2c968", "size": 16822, "ext": "py", "lang": "Python", "max_stars_repo_path": "abacus_extension.py", "max_stars_repo_name": "edwardmpearce/pyparti", "max_stars_repo_head_hexsha": "951e78da7dfd6d4891a02b77ea67910e7435a17d", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
\documentclass[11pt]{article}
\usepackage[breakable]{tcolorbox}
\usepackage{parskip} % Stop auto-indenting (to mimic markdown behaviour)
\usepackage{iftex}
\ifPDFTeX
\usepackage[T1]{fontenc}
\usepackage{mathpazo}
\else
\usepackage{fontspec}
\fi
% Basic figure setup, for... | {"hexsha": "209eaeef869d361835bb4524311bbfa252241ce3", "size": 133309, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "03_tail/data_analyse.tex", "max_stars_repo_name": "eXpensia/Confined-Brownian-Motion", "max_stars_repo_head_hexsha": "bd0eb6dea929727ea081dae060a7d1aa32efafd1", "max_stars_repo_licenses": ["MIT"],... |
'''reorganizes full 20 year 100% timeseries into 25/50/100% 5/10/20 year ones. So less extensive sureys can be done.
2020-01-01T19:00:00.000 = 2458850.29166667 # start date
2025-01-01T19:00:00.000 = 2460677.29166667 # 5 years
2030-01-01T19:00:00.000 = 2462503.29166667 # 10 years
2040-01-01T19:00:00.000 = 2466155.291666... | {"hexsha": "5a9ee226009d063aba40a2ffcf19fa0b8499d9d8", "size": 4563, "ext": "py", "lang": "Python", "max_stars_repo_path": "truncate.py", "max_stars_repo_name": "pdn4kd/isochoric-expander", "max_stars_repo_head_hexsha": "56bfdc3c7efb3a242ff4ae4c556d70bb7f171e5f", "max_stars_repo_licenses": ["MIT"], "max_stars_count": n... |
from flask import Flask, request, jsonify
import json
import pickle
import pandas as pd
import numpy as np
import drmodel
app = Flask(__name__)
# Load the model
model = pickle.load(open('model.pkl','rb'))
labels ={
0: "versicolor",
1: "setosa",
2: "virginica"
}
@app.route('/api',methods=['POST'])
def predi... | {"hexsha": "cab58ea6954cc4d3d115ffbddea76b13100853a9", "size": 683, "ext": "py", "lang": "Python", "max_stars_repo_path": "server.py", "max_stars_repo_name": "datarobot-community/mlops-pipeline", "max_stars_repo_head_hexsha": "dbb717f9b805dda6933912daa80d427db350e1a5", "max_stars_repo_licenses": ["Apache-2.0"], "max_st... |
{-# OPTIONS --without-K --safe #-}
open import Algebra
module Data.FingerTree.View
{r m}
(ℳ : Monoid r m)
where
open import Level using (_⊔_)
open import Data.Product
open import Function
open import Data.List as List using (List; _∷_; [])
open import Data.FingerTree.Structures ℳ
open import Data.FingerTree.... | {"hexsha": "268576458d0b5e0e55137bd7bb8322ac23b1470c", "size": 4581, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "src/Data/FingerTree/View.agda", "max_stars_repo_name": "oisdk/agda-indexed-fingertree", "max_stars_repo_head_hexsha": "39c3d96937384b052b782ffddf4fdec68c5d139f", "max_stars_repo_licenses": ["MIT"]... |
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