text stringlengths 0 1.25M | meta stringlengths 47 1.89k |
|---|---|
[STATEMENT]
lemma dynmethd_access_prop:
assumes statM: "methd G statC sig = Some statM" and
stat_acc: "G\<turnstile>Methd sig statM of statC accessible_from accC" and
dynM: "dynmethd G statC dynC sig = Some dynM" and
wf: "wf_prog G"
shows "G\<turnstile>Methd sig dynM in dynC dyn_acce... | {"llama_tokens": 8157, "file": null, "length": 76} |
[STATEMENT]
lemma set_MkIde_elem_of_img:
assumes "A \<subseteq> S.Univ" and "S.ide (S.MkIde (elem_of ` A))"
shows "S.set (S.MkIde (elem_of ` A)) = A"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. S.set (S.MkIde (elem_of ` A)) = A
[PROOF STEP]
proof -
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. S.set (... | {"llama_tokens": 1100, "file": "Category3_SetCat", "length": 12} |
#!/usr/bin/env python
from __future__ import print_function
import sys
import itertools
from copy import deepcopy
version_help = "Python 2.7 or 3.4+ required."
if sys.version_info[0] == 2:
assert sys.version_info[1] == 7, version_help
elif sys.version_info[0] == 3:
assert sys.version_info[1] >= 4, version_hel... | {"hexsha": "f67d9c39b1d02e6a13c1e16ba2b0e547cd6e27ec", "size": 28826, "ext": "py", "lang": "Python", "max_stars_repo_path": "dmppl/experiments/treebalance/treebalance.py", "max_stars_repo_name": "DaveMcEwan/dmppl", "max_stars_repo_head_hexsha": "68e8a121d4591360080cd40121add1796ae48a1b", "max_stars_repo_licenses": ["MI... |
"""
======================================
Decision Tree Regression with AdaBoost
======================================
A decision tree is boosted using the AdaBoost.R2 [1]_ algorithm on a 1D
sinusoidal dataset with a small amount of Gaussian noise.
299 boosts (300 decision trees) is compared with a single decision t... | {"hexsha": "659a2a5944ea6864a9923b7df5d6abf615262db1", "size": 1531, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/ensemble/plot_adaboost_regression.py", "max_stars_repo_name": "talahajeer/scikit-learn", "max_stars_repo_head_hexsha": "d66b42708a5912039740cd08f747229433e579b5", "max_stars_repo_licenses... |
import matplotlib.pyplot as plt
import numpy as np
from numpy.linalg import inv
import matplotlib.colors as colors
from matplotlib import cm
from matplotlib import rc
from matplotlib import rcParams
__author__ = 'ernesto'
# if use latex or mathtext
rc('text', usetex=True)
rcParams['text.latex.preamble']=[r"\usepack... | {"hexsha": "826b13ca1296450ec18ccbae97e762cefc9e596d", "size": 6150, "ext": "py", "lang": "Python", "max_stars_repo_path": "figuras/PycharmKayStatisticalReport/example_13_4_graphs.py", "max_stars_repo_name": "bor9/estudiando_el_kay", "max_stars_repo_head_hexsha": "6e07908b8b0b5a5166dadce30001e6100e8304c3", "max_stars_r... |
# Code by Denis Zahariev(DeniBademi) 2021
# Made with <3 and python
# Email: denis.zaharievv@gmail.com
from numpy import sin, cos
import numpy as np
import matplotlib.pyplot as plt
import scipy.integrate as integrate
import matplotlib.animation as animation
import math
from scipy.integrate import quad
delay = 10
cla... | {"hexsha": "e7b1074cb5e521eee44ad94f78a72ed201ceab3a", "size": 2079, "ext": "py", "lang": "Python", "max_stars_repo_path": "basicAnimation.py", "max_stars_repo_name": "DeniBademi/Fourier-Series-drawing-replicator", "max_stars_repo_head_hexsha": "78605d2fd263d36a7f03b5f00110f1ad372e1400", "max_stars_repo_licenses": ["MI... |
import argparse
import cv2
import numpy as np
import math
import os
import copy
# Minimum number of matches that have to be found
# to consider the recognition valid
MIN_MATCHES = 8
class OBJ:
def __init__(self, filename, swapyz=False):
"""Loads a Wavefront OBJ file. """
self.vertices = []
... | {"hexsha": "53192bd9cf4fd50379892a23fa1b3a5f8ed411e1", "size": 10126, "ext": "py", "lang": "Python", "max_stars_repo_path": "Part4.py", "max_stars_repo_name": "ankit-1517/Augmented-Reality-based-Car-race", "max_stars_repo_head_hexsha": "548ef56c3a6bfdc785c94858aae44a6941800784", "max_stars_repo_licenses": ["MIT"], "max... |
import itertools
import pandas as pd
import numpy as np
# all permutations are already reverse-deleted
# all sequences are represented in binary
nucleotides = {'A':0,'C':1,'G':2,'T':3}
numtonuc = {0:'A',1:'C',2:'G',3:'T'}
complement = {0:3,3:0,1:2,2:1}
def window(fseq, window_size):
for i in range(len(fseq) - wi... | {"hexsha": "41126b58b023d692d489620dd861a44c6d619f54", "size": 3563, "ext": "py", "lang": "Python", "max_stars_repo_path": "generate_prediction/bio.py", "max_stars_repo_name": "yangyxt/QBiC-Pred", "max_stars_repo_head_hexsha": "fc4a7ca042fc89ee9b726dc99c981be11030e29c", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
"""
FeasibilityEvaluator{T} <: AbstractNLPEvaluator
TODO
"""
mutable struct FeasibilityEvaluator{Evaluator<:AbstractNLPEvaluator, T, VT} <: AbstractNLPEvaluator
inner::Evaluator
x_min::VT
x_max::VT
cons::VT
end
function FeasibilityEvaluator(nlp::AbstractNLPEvaluator)
if !is_constrained(nlp)
... | {"hexsha": "1f8c6074d12542ae56ad20ed7fa82c6a80322852", "size": 2966, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/Evaluators/feasibility_evaluator.jl", "max_stars_repo_name": "exanauts/ExaPF.jl", "max_stars_repo_head_hexsha": "cd1bcb8a0782fe448d46a10816f82c5d28c3854e", "max_stars_repo_licenses": ["MIT"], "... |
#=
Copyright (c) 2015, Intel Corporation
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 list of conditions and the following disclaime... | {"hexsha": "23e938ece02690a09debd085b5af0ce0e74d9fc0", "size": 2156, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/correctness/knob-test1.jl", "max_stars_repo_name": "IntelLabs/Sparso", "max_stars_repo_head_hexsha": "570e7a18a96045e490f4ebf27ea948592e0bfa0b", "max_stars_repo_licenses": ["BSD-3-Clause"], "m... |
#= Sigmoid.jl
a quick script to perform a sigmoid transformation using the equation:
σ(X) = 1 /(1 + ℯ ^ vX)
function:
sigmoid(signal;v)
where signal is the input timeseries and the parameter v determines the how shallow /
steep the sigmoid curve will be. Smaller values of v flatten the curve
From França... | {"hexsha": "bfefa1af0e8d8829dfc2a62341f48d84195eb200", "size": 1192, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "sigmoid.jl", "max_stars_repo_name": "tehrandavis/data_management_tools", "max_stars_repo_head_hexsha": "3c531c78f85f4de3be20dc4ac35696721fe77290", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
"""
.. _ref_mapdl_math_basic:
PyMAPDL APDLMath Basic Operations
---------------------------------
This tutorial shows how you can use pymapdl to use APDL math for basic
operations on APDLMath vectors and matrices in the APDL memory
workspace.
The `ansys.mapdl.math` submodule gives access to APDLMath features
inside ... | {"hexsha": "69c83566c1c827526e4a6b4b76b85cd7cab41137", "size": 5665, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/01-apdlmath-examples/basic_operations.py", "max_stars_repo_name": "Miiicah/pymapdl", "max_stars_repo_head_hexsha": "ce85393ca82db7556a5d05883ca3fd9296444cba", "max_stars_repo_licenses": [... |
from datascientist.model.regression.skl.linear_model.sgd import _sgd
import numpy as np
def test_sgd():
x_train = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
y_train = np.dot(x_train, np.array([1, 2])) + 3
x_test = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
y_test = np.dot(x_test, np.array([1, 2])) + ... | {"hexsha": "c81296018a8de1556aac605b4bbc713c90a0d96d", "size": 1235, "ext": "py", "lang": "Python", "max_stars_repo_path": "datascientist/model/regression/skl/linear_model/tests/test_sgd.py", "max_stars_repo_name": "kritikaparmar-programmer/DataScientist", "max_stars_repo_head_hexsha": "b70f25b4afe28a2862a4ebfba163d162... |
using SymbolicML
using Test
using Statistics
using StatsBase
include("functions/runtests_summary.jl")
| {"hexsha": "7387c7c282a3c2da1c52ad63fe879cab06faf03b", "size": 104, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "test/runtests.jl", "max_stars_repo_name": "gspina140/SymbolicML.jl", "max_stars_repo_head_hexsha": "a89d19cbfeeb32ad6ead9944f7d87e86788c6a90", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
import datetime
import os
import subprocess
import numpy
from scipy.stats import norm
from . import romannumerals
# ToDo: Bring back scale bar
# ToDo: Add option for solid fill of vectors
def roundto(num, nearest):
"""
Rounds :param:`num` to the nearest increment of :param:`nearest`
"""
return int... | {"hexsha": "5c12f2b89c78d1e0bd28229f8856e698d7e7c93e", "size": 10014, "ext": "py", "lang": "Python", "max_stars_repo_path": "pygbrowse/utilities.py", "max_stars_repo_name": "phageghost/python-genome-browser", "max_stars_repo_head_hexsha": "c052bb72ca89664f48d1248b5a4500482c823ee7", "max_stars_repo_licenses": ["MIT"], "... |
!> CHEASE Output Reader
!!
!! A module to read in datafiles from CHEASE.
!!
!! Written by Edmund Highcock
!! edmundhighcock@sourceforge.net
!!
!!
!! Available quantities are:
!!
!! Zero D:
!! r0exp_chease,b0exp_chease
!! One D:
!! rgeom_chease,ageom_chease,q_chease,dqdpsi_chease,
!! d2qdpsi2_chease,p_chease,dpdpsi_che... | {"hexsha": "faa7e25d1ed5c7969e3438fd153fda8edcae896d", "size": 14123, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "geo/read_chease.f90", "max_stars_repo_name": "nicolaschristen/gs2_ndc_git", "max_stars_repo_head_hexsha": "ec0295f0726d7e2f372a02cadad0e375f7cd1c31", "max_stars_repo_licenses": ["MIT"], "max_st... |
/**********************************************************************
* Copyright (c) 2008-2014, Alliance for Sustainable Energy.
* All rights reserved.
*
* This library is free software; you can redistribute it and/or
* modify it under the terms of the GNU Lesser General Public
* License as publishe... | {"hexsha": "a65edd6770215b12090137fddf2988abf68b4059", "size": 10161, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "openstudiocore/src/osversion/VersionTranslator.hpp", "max_stars_repo_name": "ORNL-BTRIC/OpenStudio", "max_stars_repo_head_hexsha": "878f94bebf6f025445d1373e8b2304ececac16d8", "max_stars_repo_licens... |
function get_devices(sys::PowerSystems.PowerSystem,category::Type{PowerSystems.ThermalGen})
return sys.generators.thermal
end
function get_devices(sys::PowerSystems.PowerSystem,category::Type{PowerSystems.RenewableGen})
return sys.generators.renewable
end
function get_devices(sys::PowerSystems.PowerSystem,cate... | {"hexsha": "bbaf5ee401fdc88ddf14c30360ed16a4887b157b", "size": 1390, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/component_constructors/services_constructor.jl", "max_stars_repo_name": "gitter-badger/PowerSimulations.jl", "max_stars_repo_head_hexsha": "608671297c4b813505aef4073932eae3d8875af6", "max_stars... |
#import string
import multiprocessing
from functools import partial
import sys
import numpy as np
import pandas as pd
from sqlalchemy import create_engine
from sqlalchemy_utils import database_exists
import pickle
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
from sklearn.... | {"hexsha": "c4aa4bb94794b0601be0ff27d7cf962e237ba023", "size": 5932, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/train_classifier.py", "max_stars_repo_name": "baky0905/disaster-response-pipeline", "max_stars_repo_head_hexsha": "09ff91230037c21fea69a101c7057b30accb56fd", "max_stars_repo_licenses": ["MI... |
#!/usr/bin/env python3
import numpy as np
from vchamtools.vcham import vcham
from itertools import combinations
# TODO:
# load and save H from disk
# add mode numbers to H class
# enables also better plotting! make plotting package for H
def op_parameter_section(H, states=None):
"""states list in... | {"hexsha": "6df92e0e21793824058bc1e4878f377a1dc4bbd7", "size": 14191, "ext": "py", "lang": "Python", "max_stars_repo_path": "vchamtools/vcham/mctdh.py", "max_stars_repo_name": "oh-fv/vchamtools", "max_stars_repo_head_hexsha": "80ca39931b47db00cb9ed70e04687fabade20610", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
# Decision Lens API
#
# No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen)
#
# OpenAPI spec version: 1.0
#
# Generated by: https://github.com/swagger-api/swagger-codegen.git
#' AddUserRequest Class
#'
#' @field user
#' @field message
#'
#' @importFrom R6 R6Class
#... | {"hexsha": "66057c26cf518d47c72555c692bb004eed8131a4", "size": 2051, "ext": "r", "lang": "R", "max_stars_repo_path": "R/R/AddUserRequest.r", "max_stars_repo_name": "dlens/dlxapi", "max_stars_repo_head_hexsha": "189a6519240ce625d7a9cdb89e305a335d2aa045", "max_stars_repo_licenses": ["MIT"], "max_stars_count": null, "max_... |
import streamlit as st
import pandas as pd
import numpy as np
st.title('Weekly Deaths from Pneumonia, Influenza, or COVID-19')
DATA_SOURCE = './NCHSData47.csv'
YEAR = 'year'
WEEK = 'week'
OTHER_DEATHS = 'other deaths'
PNEUMONIA_DEATHS = 'pneumonia deaths'
INFLUENZA_DEATHS = 'influenza deaths'
COVID19_DEATHS = 'covid-... | {"hexsha": "978fd72854d712b21c2e4acd655f29d85d42b9d4", "size": 981, "ext": "py", "lang": "Python", "max_stars_repo_path": "main.py", "max_stars_repo_name": "greenfructose/PICDeathVisualizationUS", "max_stars_repo_head_hexsha": "d6aa631cd7916c6e20f123bb1b5c36f615d55e0f", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
record Foo (param : Nat) where
constructor MkFoo
num : Int
implementation Show (Foo n) where
show f = show (param_param f) ++ ", " ++ show (num f)
main : IO ()
main = do let x = MkFoo {param=10} 20
putStrLn (show (record { param_param = 42 } x))
putStrLn (show (record { num = 42 } x))
| {"hexsha": "8795f7bc2bd82c98ad1a47e5ec9441956bf67c84", "size": 315, "ext": "idr", "lang": "Idris", "max_stars_repo_path": "test/idris-dev/records002/record002.idr", "max_stars_repo_name": "grin-compiler/idris-grin", "max_stars_repo_head_hexsha": "0514e4d41933143223cb685e23f450dcbf3d5593", "max_stars_repo_licenses": ["B... |
""" Example of ordinary Monte Carlo with rejection sampling integrating circle area """
import numpy as np
import scipy.stats
from matplotlib.colors import Normalize
from pylab import *; ion()
import probayes as pb
# PARAMETERS
radius = 1.
steps = 10000
# SETUP CIRCLE FUNCTION AND RVs
def inside(x, y):
return np.a... | {"hexsha": "3c984a0b7efd3122e8314a1d6202a905e5f9e29c", "size": 1931, "ext": "py", "lang": "Python", "max_stars_repo_path": "examples/omc/omc_rejection_sp_circle.py", "max_stars_repo_name": "Bhumbra/probayes", "max_stars_repo_head_hexsha": "e5ac193076e4188b9b38c0e18466223ab4d041f7", "max_stars_repo_licenses": ["BSD-3-Cl... |
"""
$(SIGNATURES)
Write, to the current working directory, a .tex file with the parmater list for the NIPA dataset and parameter values for the TableID parameter.
Arguments
---------
* `b` -- a [`Bea`](@ref) connection
"""
function nipa_metadata_tex(b::Bea)
url = b.url
key = b.key
bea_dataset = b.dataset... | {"hexsha": "becd5bf87224b4d116df6588915b90775012bca1", "size": 2812, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/nipa_metadata_tex.jl", "max_stars_repo_name": "JuliaPackageMirrors/BeaData.jl", "max_stars_repo_head_hexsha": "dc0e9bef0d59b9110f22c0828a90a28a3c0b5926", "max_stars_repo_licenses": ["MIT"], "ma... |
[STATEMENT]
lemma evaluate_iff:
"evaluate True env st e r \<longleftrightarrow> (r = eval env e st)"
"evaluate_list True env st es r' \<longleftrightarrow> (r' = eval_list env es st)"
"evaluate_match True env st v pes v' r \<longleftrightarrow> (r = eval_match env v pes v' st)"
[PROOF STATE]
proof (prove)
goal (1... | {"llama_tokens": 205, "file": "CakeML_Big_Step_Fun_Equiv", "length": 1} |
import os
import shutil
import torch
import logging
import numpy as np
from scipy.ndimage import gaussian_filter1d
from scipy.signal.windows import triang
class AverageMeter(object):
def __init__(self, name, fmt=':f'):
self.name = name
self.fmt = fmt
self.reset()
def reset(self):
... | {"hexsha": "f79db7f406a5a81d8c50d2c49617123bb0be1d6f", "size": 4223, "ext": "py", "lang": "Python", "max_stars_repo_path": "imdb-wiki-dir/utils.py", "max_stars_repo_name": "jiawei-ren/BalancedMSE", "max_stars_repo_head_hexsha": "4e1f44fe4cc2518159b1c67159abe3d2b0cea014", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
```python
import numpy as np
import matplotlib.pylab as plt
from numpy.lib.stride_tricks import sliding_window_view
```
## Implementing a Function to Compute the Local Binary Pattern
Local Binary Pattern (LBP) is a simple yet very efficient texture feature commonly used in image processing.
\begin{align}
LBP(p) =... | {"hexsha": "65a48e00caada21038013b87b38aa97d72cb5e19", "size": 4471, "ext": "ipynb", "lang": "Jupyter Notebook", "max_stars_repo_path": "Submissions/lbp_compiled.ipynb", "max_stars_repo_name": "yash30147101/ENEL645", "max_stars_repo_head_hexsha": "15b54b0188be3aa214295d5dd37bb51b39a31e58", "max_stars_repo_licenses": ["... |
# -*- coding: utf-8 -*-
import cv2
import sys
import numpy as np
import argparse
imagePath = "img.png"
sx = sy = None
previewImage = None
if len(sys.argv) < 3:
print("""
Usage:
python mouseInteractive -i img.png
""")
sys.exit(-1)
if sys.argv[1]=="-i":
imagePath = sys.argv[2]
def cre... | {"hexsha": "11bb268e235390ce4ed73761c89b12c27bab8ebc", "size": 1343, "ext": "py", "lang": "Python", "max_stars_repo_path": "mouseInteractive.py", "max_stars_repo_name": "wwwins/OpenCV-Samples", "max_stars_repo_head_hexsha": "6a88c411064d5a8d012fbc2299a6d85b4526785e", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
#!/usr/bin/env python
"""
Implements Dozier type algorihms for estimating fire size/temperature.
This software is hereby placed in the public domain.
Arlindo.daSilva@nasa.gov
"""
import sys
from mxd14 import *
from planck import *
from math import pi
from pylab import pcolor, plot, col... | {"hexsha": "ab82436aae6e350b4ddc59557f029393090a38fe", "size": 22321, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/Components/qfed/qfed/dozier.py", "max_stars_repo_name": "GEOS-ESM/AeroApps", "max_stars_repo_head_hexsha": "874dad6f34420c014d98eccbe81a061bdc0110cf", "max_stars_repo_licenses": ["NASA-1.3", ... |
import dolfin as df
import itertools
import numpy as np
def as_tuple(maybe):
'''Tuple of numbers'''
if isinstance(maybe, (int, float)):
return (maybe, )
return tuple(maybe)
def subdomain_bbox(subdomains, label=None):
'''
Draw a bounding box around subdomain defined by entities in `subdom... | {"hexsha": "8d64d39eadcc393f1874bebf563379c0422f161b", "size": 4527, "ext": "py", "lang": "Python", "max_stars_repo_path": "neuronmi/simulators/solver/aux.py", "max_stars_repo_name": "MiroK/nEuronMI", "max_stars_repo_head_hexsha": "227b26598fa2cde5aabec68db898f308fb44aa31", "max_stars_repo_licenses": ["Apache-2.0"], "m... |
# -*- coding: utf-8 -*-
"""
Data conversion between space/time vector and space/time grid formats
Created on Sat Jun 27 11:40:16 2015
@author: hdragon689
"""
from six.moves import range
import numpy as np
import pandas as pd
def valstv2stg(ch, z, cMS=None, tME=None):
'''
Converts the values of a space/time var... | {"hexsha": "9e2887bb71d5bfd163c17351b422f223f8364bb9", "size": 4982, "ext": "py", "lang": "Python", "max_stars_repo_path": "stamps/general/valstvgx.py", "max_stars_repo_name": "stemlab689/stamps", "max_stars_repo_head_hexsha": "5494d4e86ad005082c677d9a07f71e1606338ba0", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
#!/usr/bin/env python3
import random
import time
import json
# import pprint
import sys
import numpy as np
from datetime import datetime
from signal import signal, SIGPIPE, SIG_DFL
if __name__ == '__main__':
if len(sys.argv) < 6:
sys.stderr.write("arguments:\n")
sys.stderr.write("\t$1 filenam... | {"hexsha": "9552a8d8e4ea7b572e9f699ba2c830927e46267e", "size": 4715, "ext": "py", "lang": "Python", "max_stars_repo_path": "bin/mobility.py", "max_stars_repo_name": "sarub0b0/hashmot-deltahq", "max_stars_repo_head_hexsha": "8ef0b5d138ae8922e1ba1b649cee4ef05dd04849", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
module FluorescentSeries
using AxisArrays, ImageAxes
include("core.jl")
include("algorithms.jl")
export
FluorescentSerie,
deltaFF
end # module
| {"hexsha": "064cdf729136f53a5bea06193ba108b8996eec1b", "size": 146, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/FluorescentSeries.jl", "max_stars_repo_name": "UnofficialJuliaMirror/FluorescentSeries.jl-68ab7a74-b89c-58c4-90e0-a4e17bbb69bc", "max_stars_repo_head_hexsha": "0161604726d4d653e529f3e74172be751b... |
\documentclass{article}
\usepackage{graphicx}
\usepackage{epsfig}
\usepackage{amssymb,amsmath}
\usepackage{array}
\graphicspath{ {./assignment_2/} }
\singlespace
\setlength{\parindent}{0pt}
\title{CTA200 2020 Assignment 2 Summary}
\author{SURP Student Ethan Sun}
\date{May 10th, 2020}
\begin{document}
\maketitle
\se... | {"hexsha": "3bcddfeff114cfab3ba47740b121186e2777b4d0", "size": 4708, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "assignment_2/Question_3.tex", "max_stars_repo_name": "ethan-sun-010/CTA200", "max_stars_repo_head_hexsha": "c7f4948501977ce3a7580e0809adbe3011cc086b", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
function [model, L] = ppcaVb(X, q, prior)
% Perform variatioanl Bayeisan inference for probabilistic PCA model.
% Input:
% X: d x n data matrix
% q: dimension of target space
% Output:
% model: trained model structure
% L: variantional lower bound
% Reference:
% Pattern Recognition and Machine Learning by C... | {"author": "PRML", "repo": "PRMLT", "sha": "baac49f643db6b39e75307d3b21307b32b29a7a9", "save_path": "github-repos/MATLAB/PRML-PRMLT", "path": "github-repos/MATLAB/PRML-PRMLT/PRMLT-baac49f643db6b39e75307d3b21307b32b29a7a9/chapter12/ppcaVb.m"} |
import torch
from torch import nn
from torch.nn import functional as F
import numpy as np
torch.set_default_tensor_type("torch.cuda.FloatTensor")
class Generator(nn.Module):
def __init__(self):
super().__init__()
self.conv_1 = nn.ConvTranspose2d(100, 512, kernel_size=4, stride=1)
self.batc_1 = nn.BatchNorm2d... | {"hexsha": "b2f7ddbcf49d32beb9ea18e125cad3ae981ece9a", "size": 1969, "ext": "py", "lang": "Python", "max_stars_repo_path": "models/dcgan.py", "max_stars_repo_name": "hexhowells/Neural-Network-Implementations", "max_stars_repo_head_hexsha": "3b163e721c62e53aa54a4e1d6ce971bd68b1461b", "max_stars_repo_licenses": ["MIT"], ... |
% !TEX root = Main.tex
\section{Non-Negative Matrix Factorization}
$\mathbf{X} \in \mathbb{Z}^{N \times M}_{\geq 0}$, NMF: $\mathbf{X} \approx \mathbf{U^\top V}, x_{ij}=\sum_z{u_{zi}v_{zj}}=\langle\mathbf{u}_i \mathbf{v}_j\rangle$
Decompose object into features: topics, face parts, etc.. $\mathbf{u}$ weights on parts, ... | {"hexsha": "083833fa0e797ee3270f8390a9dc09da5cb627ef", "size": 2722, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "NMF.tex", "max_stars_repo_name": "vscherer/eth-cil-exam-cheatsheet", "max_stars_repo_head_hexsha": "9ae156bcf5e2797e65b5495ff520649b43860cdd", "max_stars_repo_licenses": ["CC0-1.0"], "max_stars_coun... |
Products and Services
Special event shoots (Formals, Philanthropies, Bid Days, etc.)
Indoor and outdoor photo shoots
Headshots and Portraits
Greek Composites
Senior Portraits
Bands
Background
Devon Latzen has been photographing people and events for almost ten years. He began shooting for the school newspa... | {"hexsha": "27a3ae4da2baab20db9151c1af14766022bfb5a0", "size": 1155, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "lab/davisWiki/Devon_Latzen_Photography.f", "max_stars_repo_name": "voflo/Search", "max_stars_repo_head_hexsha": "55088b2fe6a9d6c90590f090542e0c0e3c188c7d", "max_stars_repo_licenses": ["MIT"], "max... |
from corvus.structures import Handler, Exchange, Loop, Update
import corvutils.pyparsing as pp
import os, sys, subprocess, shutil #, resource
import re
# Debug: FDV
import pprint
import numpy as np
pp_debug = pprint.PrettyPrinter(indent=4)
# Define dictionary of implemented calculations
implemented = {}
strlistkey = l... | {"hexsha": "52610f8bfa50d48885edcf6c40e146c8185c0506", "size": 12453, "ext": "py", "lang": "Python", "max_stars_repo_path": "corvus/ocean.py", "max_stars_repo_name": "times-software/Corvus", "max_stars_repo_head_hexsha": "d220e2db28743ecb6748e2a245eb3992daa554c1", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_stars... |
\section{Process' Perspective}
\subsection{Team}
To organize our team, we make a weekly plan each Tuesday. The plan depends on the current hangups of the project and the new tasks of the week. \newline
We split up the team in subgroups, depending on the complexity of the task we are taking on.
Each subgroup starts the... | {"hexsha": "a4c527b726b10da30058729843f906f539b02474", "size": 9544, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "report/sections/process_perspective.tex", "max_stars_repo_name": "salsitu/minitwit_thesvindler", "max_stars_repo_head_hexsha": "1b8ee619c763bafbc6cc0b19424e834741bd1809", "max_stars_repo_licenses": ... |
import numpy as np
from model.rng.RNG import RNG
class GaussianRNG(RNG):
def __init__(self, density):
super().__init__(density)
self.mu, self.sigma = 0, self.get_mapped_sigma(density)
def get_next(self):
return np.random.normal(self.mu, self.sigma)
@staticmethod
def get_mapp... | {"hexsha": "dbdb41d91506852e4fb5e5b1e926b9312de27ffe", "size": 409, "ext": "py", "lang": "Python", "max_stars_repo_path": "model/rng/GaussianRNG.py", "max_stars_repo_name": "rieder91/som-cluster-generator", "max_stars_repo_head_hexsha": "a828e168e0fee4d5d9ac4e7206de89a2fc736b85", "max_stars_repo_licenses": ["MIT"], "ma... |
// extending_return_type_traits.cpp -- The Boost Lambda Library --------
//
// Copyright (C) 2000-2003 Jaakko Jarvi (jaakko.jarvi@cs.utu.fi)
// Copyright (C) 2000-2003 Gary Powell (powellg@amazon.com)
//
// Distributed under the Boost Software License, Version 1.0. (See
// accompanying file LICENSE_1_0.txt or copy at... | {"hexsha": "731379a9c125f178a00be79517047d33d40d7a70", "size": 9031, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "console/src/boost_1_78_0/libs/lambda/test/extending_rt_traits.cpp", "max_stars_repo_name": "vany152/FilesHash", "max_stars_repo_head_hexsha": "39f282807b7f1abc56dac389e8259ee3bb557a8d", "max_stars_r... |
SUBROUTINE GDPUVP ( gvect, u, v, y, npts, wind, winpos, filtfc,
+ windxn, windyn, refvec, iret )
C************************************************************************
C* GDPUVP *
C* *
C* This subroutine draws a wind profile in GDPROF. *
C* *
C* GDPUVP ( GVECT, U, ... | {"hexsha": "73dc5344b36a9c2f177d08a4867f25ec68b0e5e7", "size": 4601, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "gempak/source/programs/gd/gdprof/gdpuvp.f", "max_stars_repo_name": "oxelson/gempak", "max_stars_repo_head_hexsha": "e7c477814d7084c87d3313c94e192d13d8341fa1", "max_stars_repo_licenses": ["BSD-3-Cl... |
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# 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 law or a... | {"hexsha": "c48f1c56a18dda7f0f423f1a34b3b14aeb52ef2f", "size": 14356, "ext": "py", "lang": "Python", "max_stars_repo_path": "mars/serialization/serializables/field_type.py", "max_stars_repo_name": "yuyiming/mars", "max_stars_repo_head_hexsha": "5e6990d1ea022444dd646c56697e596ef5d7e747", "max_stars_repo_licenses": ["Apa... |
#include "MergeTreeDataMergerMutator.h"
#include <Storages/MergeTree/MergeTreeSequentialSource.h>
#include <Storages/MergeTree/MergedBlockOutputStream.h>
#include <Storages/MergeTree/MergedColumnOnlyOutputStream.h>
#include <Storages/MergeTree/SimpleMergeSelector.h>
#include <Storages/MergeTree/AllMergeSelector.h>
#in... | {"hexsha": "f596828ed059c3a85946b2103b201edaa784d43f", "size": 25350, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/Storages/MergeTree/MergeTreeDataMergerMutator.cpp", "max_stars_repo_name": "zzachimed/ClickHouse", "max_stars_repo_head_hexsha": "a403f1cd1b2655a60ca196d209ef443ef6d91b39", "max_stars_repo_lice... |
import discord
from discord.ui import Button, View
from .pytari2600.pytari2600 import new_atari
from PIL import Image
from io import BytesIO
import pygame
import numpy
K_A = 0
K_UP = 1
K_DOWN = 2
K_LEFT = 3
K_RIGHT = 4
async def get_acceptable_url(file, channel):
message = await channel.send(file=file)
ret... | {"hexsha": "47ba6aeeea52dfd399273fff3cef54a1424f04bf", "size": 3933, "ext": "py", "lang": "Python", "max_stars_repo_path": "modules/emulator/atari.py", "max_stars_repo_name": "5space/nesbot", "max_stars_repo_head_hexsha": "38a9e8cadf0cbe41ee25e0850c244e2834a6e12c", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
# MINLP written by GAMS Convert at 04/21/18 13:55:19
#
# Equation counts
# Total E G L N X C B
# 202 96 36 70 0 0 0 0
#
# Variable counts
# x b i s1s s2s sc ... | {"hexsha": "e86483df48cf327292c2324ab1350f1c4fe15786", "size": 64971, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/examples/minlplib/watersym2.py", "max_stars_repo_name": "ouyang-w-19/decogo", "max_stars_repo_head_hexsha": "52546480e49776251d4d27856e18a46f40c824a1", "max_stars_repo_licenses": ["MIT"], "... |
#####################################################################
# #
# /functions.py #
# #
# Copyright 2013, Monash University ... | {"hexsha": "829c3a02bf13610649d01f63417bd8c50959a79a", "size": 8895, "ext": "py", "lang": "Python", "max_stars_repo_path": "labscript/functions.py", "max_stars_repo_name": "restelli/labscript", "max_stars_repo_head_hexsha": "4d263442a4381eec1ff0c628467aa59486681df6", "max_stars_repo_licenses": ["BSD-2-Clause"], "max_st... |
import time
import datetime
import urllib
import pandas
from pytz import timezone
import numpy
import pyopencl as cl
import pyopencl.array as cl_array
import json
from kafka import KafkaProducer
def google_finance_data_reader(symbol, interval_seconds, num_days):
url_string = "http://www.google.com/finance/getpri... | {"hexsha": "65cfb81d5a02b7ba20142ca876679ff4105213c8", "size": 2647, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/main/python/google_finance_predictions.py", "max_stars_repo_name": "Sapphirine/201605-45", "max_stars_repo_head_hexsha": "4af4d6934f7abbf3b89383a9946f5b76b0fe29b4", "max_stars_repo_licenses": ... |
import numpy as np
class UncertaintyModel(object):
def __init__(self, ratingMatrix):
self.ratingMatrix = ratingMatrix
def reset(self, seed=None):
# Reset the weights as if no training was done
pass
def save(self, fileName):
# Save the model
return fileName
def... | {"hexsha": "2e1b306029397c938587bf8483e6af06e1ee0552", "size": 793, "ext": "py", "lang": "Python", "max_stars_repo_path": "sclrecommender/bandit/model/uncertaintyModel.py", "max_stars_repo_name": "wezteoh/Bandit_Recommendation", "max_stars_repo_head_hexsha": "a326e4d1d082e1a2113fe739bc343fb45b0b8a4a", "max_stars_repo_l... |
"""
postprocessing.py
Postprocessing of CDIP files and QC logs.
"""
import os
import json
import numpy as np
import tqdm
from .constants import QC_EXTREME_WAVE_LOG_THRESHOLD
def plot_qc(qcfile, outdir, exclude_flags=tuple('cefg'), plot_extreme=True):
"""Write plots of QC records from given log file to output ... | {"hexsha": "49c8f407ed9044a391939533cea3c885bd2ee55d", "size": 5971, "ext": "py", "lang": "Python", "max_stars_repo_path": "fowd/postprocessing.py", "max_stars_repo_name": "dionhaefner/FOWD", "max_stars_repo_head_hexsha": "29fd9a6c822c7e01d6e44056e05bcc5dc8d8f53a", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
#!/usr/bin/env python2
#
# Copyright 2018 Obodroid Corporation by Lertlove
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | {"hexsha": "288e48f9c1424820fe202a2ba5e3fecdaa66bf35", "size": 8444, "ext": "py", "lang": "Python", "max_stars_repo_path": "demos/clustering.py", "max_stars_repo_name": "obodroid/openface", "max_stars_repo_head_hexsha": "39866481103fd405fa59bd47488f4a56070b0eac", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_co... |
import tensorflow as tf
import numpy as np
from vizdoom import DoomGame
import random
import time
from skimage import transform
from collections import deque
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
def create_environment():
game = DoomGame()
game.load_config("basic.cfg")
game.set_doom_scenari... | {"hexsha": "428ceb94fb3f902a9c40eab1da6d8fcde6c7f38b", "size": 13009, "ext": "py", "lang": "Python", "max_stars_repo_path": "DQN/Doom/DQN_Doom.py", "max_stars_repo_name": "Urinx/ReinforcementLearning", "max_stars_repo_head_hexsha": "40c00b8297503e127c6c8134a8becffb81b676e4", "max_stars_repo_licenses": ["Apache-2.0"], "... |
module DryRun
using Mocking
export @dryer
include("dryer.jl")
# Create the initial definition of `activated` which defaults DryRun to be disabled
activated() = false
"""
DryRun.activate()
Enable `@mock` call sites to allow for calling patches instead of the original function.
"""
function activate()
# Avo... | {"hexsha": "81dca054df0262ad0f0e04201b71d6d6d916e162", "size": 1254, "ext": "jl", "lang": "Julia", "max_stars_repo_path": "src/DryRun.jl", "max_stars_repo_name": "samuel-massinon/DryRun.jl", "max_stars_repo_head_hexsha": "1d6435dd609f9331ad3a9f34bde1734f007a7958", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
import seaborn as sns
import time
import datetime
plt.style.use("seaborn-colorblind")
data4 = pd.read_csv("C:/Users/VARUN/De... | {"hexsha": "c53b7bacc1c18f1804d10413c2675b375eba7d2d", "size": 3386, "ext": "py", "lang": "Python", "max_stars_repo_path": "Air-Pollution-Levels-Exploratory-Data-Analysis-master/Test.py", "max_stars_repo_name": "varuntotakura/AirPollutionAnalysis", "max_stars_repo_head_hexsha": "ec8a1df747c018b13856a346c8236adc8268c6bb... |
import string
import operator as op
from functools import reduce
import numpy as np
from . import nodal_corrections as nc
class BaseConstituent(object):
xdo_int = {
'A': 1, 'B': 2, 'C': 3, 'D': 4, 'E': 5, 'F': 6, 'G': 7, 'H': 8, 'I': 9,
'J': 10, 'K': 11, 'L': 12, 'M': 13, 'N': 14, 'O': 15, 'P': 16, 'Q': 17,
'R... | {"hexsha": "37e7274b06f65f4c44d14501457c9363744cdefd", "size": 6351, "ext": "py", "lang": "Python", "max_stars_repo_path": "pytides/constituent.py", "max_stars_repo_name": "yudevan/pytides", "max_stars_repo_head_hexsha": "507f2bc5d19fa5e427045cc2bf9ed724daf67f0c", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
import numpy as np
import math
import time
from .base import try_gpu, Timer, Accumulator
from .figure import set_figsize, plt, Animator
from .data import data_iter_consecutive, data_iter_random
from .model import linreg
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from... | {"hexsha": "070d94176a01972f335ba956f04be70a63318d70", "size": 16714, "ext": "py", "lang": "Python", "max_stars_repo_path": "d2l/train.py", "max_stars_repo_name": "cingtiye/d2l-pytorch", "max_stars_repo_head_hexsha": "9152fa5309fd48ac06b85e961ca13d44a425a647", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_count... |
/*
Copyright 2014-2015 Glen Joseph Fernandes
(glenjofe@gmail.com)
Distributed under the Boost Software License, Version 1.0.
(http://www.boost.org/LICENSE_1_0.txt)
*/
#include <boost/align/alignment_of.hpp>
#include <boost/align/is_aligned.hpp>
#include <boost/core/lightweight_test.hpp>
#include <boost/confi... | {"hexsha": "13d330f5a9ecb3d9e26c6d8cbad2612e5e2fcb51", "size": 1472, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "REDSI_1160929_1161573/boost_1_67_0/libs/align/test/is_aligned_test.cpp", "max_stars_repo_name": "Wultyc/ISEP_1718_2A2S_REDSI_TrabalhoGrupo", "max_stars_repo_head_hexsha": "eb0f7ef64e188fe871f47c2ef9... |
tmpdir/fdpic-shared.so: file format elf32-(little|big)arm
DYNAMIC RELOCATION RECORDS
OFFSET TYPE VALUE
.* R_ARM_FUNCDESC_VALUE my_shared_func3
| {"hexsha": "22b755e51b61c14f8d164cb42375545f852c5ec3", "size": 168, "ext": "r", "lang": "R", "max_stars_repo_path": "contrib/gnu/gdb/dist/ld/testsuite/ld-arm/fdpic-shared.r", "max_stars_repo_name": "TheSledgeHammer/2.11BSD", "max_stars_repo_head_hexsha": "fe61f0b9aaa273783cd027c7b5ec77e95ead2153", "max_stars_repo_licen... |
import torch
import numpy as np
from sklearn.metrics import precision_recall_fscore_support
from torch import nn, Tensor, optim
from typing import Tuple, Optional
from src.tasks import OmniTask
from src.utils.data import OmniDataset
from argparse import Namespace
class ClassificationTask(OmniTask):
def __init__(
... | {"hexsha": "bcc50c11a4499ad89fc1b7b22aa7b1b6ecf30232", "size": 4778, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/tasks/classification.py", "max_stars_repo_name": "andompesta/omnitext", "max_stars_repo_head_hexsha": "da6467b6cd9086b2278f7a1560596261f125800e", "max_stars_repo_licenses": ["MIT"], "max_stars... |
C$Procedure LBUPD ( Line buffer, update )
SUBROUTINE LBUPD_1 ( NLINE, NCOM, PTRS )
IMPLICIT NONE
C$ Abstract
C
C Update internal information in a line buffer.
C
C$ Disclaimer
C
C THIS SOFTWARE AND ANY RELATED MATERIALS WERE CREATED BY THE
C CALIFORNIA INSTITUTE OF TECHNOLOGY (CALTECH) UNDE... | {"hexsha": "a7d19fe737d25c09a7fb4e62a2a206df665e3388", "size": 4385, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "source/nasa_f/lbupd_1.f", "max_stars_repo_name": "agforero/FTFramework", "max_stars_repo_head_hexsha": "6caf0bc7bae8dc54a62da62df37e852625f0427d", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
"""
An implementation of a general zero-knowledge proof protocl for claims in NP
WARNING::
DO NOT USE THIS IN ANY SECURITY-CRITICAL CODE. This code has not been tested
and probably has many security vulnerabilities. In particular, it use sage's
default random number generator, which probably is not suitabl... | {"hexsha": "d34dc2648d16b7ccecd48a0324c806fdf030f2dc", "size": 5595, "ext": "py", "lang": "Python", "max_stars_repo_path": "zero_knowledge.py", "max_stars_repo_name": "itaibn/zero-knowledge", "max_stars_repo_head_hexsha": "4a270ebb9baf1163006eaef104799072aaec7d84", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_star... |
# coding=utf-8
import cv2
import numpy as np
import pygame
import time
import trigger_email
#if you get error while importing the google how to install <Package Name> in python 3.6
THRESHOLD = 40
camera = cv2.VideoCapture(0)
es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,4))
kernel = np.ones((5,5), np.uint8)
... | {"hexsha": "293637e8d9c302076ba4f81fa0c4c5a573ea2a98", "size": 2321, "ext": "py", "lang": "Python", "max_stars_repo_path": "PythonCode/Windows.py", "max_stars_repo_name": "omkaryadav/UltimateSecurityCam", "max_stars_repo_head_hexsha": "7241c4c568bc3f2d530f79fd6b0f25f5920606ae", "max_stars_repo_licenses": ["MIT"], "max_... |
from df_compare import df_compare
import pandas as pd
import numpy as np
import datetime
import pytest
import warnings
import logging
logging.basicConfig(level=logging.WARNING)
warnings.filterwarnings(action='ignore', category=pd.core.common.SettingWithCopyWarning)
@pytest.fixture(scope='session')
def base_dict():
... | {"hexsha": "ed56c54d41aa57ef9a62aaf98de26a9a0c71897e", "size": 5959, "ext": "py", "lang": "Python", "max_stars_repo_path": "test/test_core.py", "max_stars_repo_name": "caseyclements/df_compare", "max_stars_repo_head_hexsha": "4ece5c4d1c78c25b629c7b748fea610d39be0843", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_s... |
# -*- coding: utf-8 -*-
"""
Optimization of hyper parameters.
Both grid search and random search using the ``hyperopt`` library are
supported.
The hyper parameter specification of a reconstructor class, optionally
including default options for optimization, are specified in the class
attribute :attr:`~dival.Reconstru... | {"hexsha": "88df9d4018c89be81542a3a02938f800a834f5c8", "size": 12096, "ext": "py", "lang": "Python", "max_stars_repo_path": "dival/hyper_param_search.py", "max_stars_repo_name": "MBaltz/dival", "max_stars_repo_head_hexsha": "b7c10ed471d05242312a7d4916900c92e0c36cdb", "max_stars_repo_licenses": ["MIT"], "max_stars_count... |
%%
%% Automatically generated file from DocOnce source
%% (https://github.com/hplgit/doconce/)
%%
%%
% #ifdef PTEX2TEX_EXPLANATION
%%
%% The file follows the ptex2tex extended LaTeX format, see
%% ptex2tex: http://code.google.com/p/ptex2tex/
%%
%% Run
%% ptex2tex myfile
%% or
%% doconce ptex2tex myfile
%%
%% ... | {"hexsha": "a9b0ca13676b060169d8e633d63c7ec3eac70da7", "size": 17464, "ext": "tex", "lang": "TeX", "max_stars_repo_path": "doc/Projects/2017/Project1/pdf/Project1.p.tex", "max_stars_repo_name": "kimrojas/ComputationalPhysicsMSU", "max_stars_repo_head_hexsha": "a47cfc18b3ad6adb23045b3f49fab18c0333f556", "max_stars_repo_... |
import pandas as pd
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Input
from keras.layers import LSTM
from keras.layers import GRU
from keras.layers import Dropout
from keras.layers import TimeDistributed
from keras.callbacks import EarlyStopping
from keras.layers import Conv1D... | {"hexsha": "764e7a07a05046acdae791908724a66fdb279789", "size": 1457, "ext": "py", "lang": "Python", "max_stars_repo_path": "hw3/CNN_predict.py", "max_stars_repo_name": "thtang/ML2017FALL", "max_stars_repo_head_hexsha": "9060a11c29600c835286ee0866e15ede25850182", "max_stars_repo_licenses": ["Apache-2.0"], "max_stars_cou... |
// Copyright (c) 2012-2018, The CryptoNote developers, The Bytecoin developers, [ ] developers.
// Licensed under the GNU Lesser General Public License. See LICENSE for details.
#include "DBsqlite3.hpp"
#include <boost/lexical_cast.hpp>
#include <iostream>
#include "PathTools.hpp"
#include "common/string.hpp"
... | {"hexsha": "a7ef4dec69e43c1950a6786e059fafc197fcc529", "size": 14169, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "src/platform/DBsqlite3.cpp", "max_stars_repo_name": "VaultB/vaultb", "max_stars_repo_head_hexsha": "de41b954ea4d8a4f54a5ab95adf14af85809f55e", "max_stars_repo_licenses": ["MIT"], "max_stars_count":... |
// Distributed under the MIT License.
// See LICENSE.txt for details.
#include "Framework/TestingFramework.hpp"
#include <boost/functional/hash.hpp>
#include <cstddef>
#include <deque>
#include <memory>
#include <utility>
#include "DataStructures/DataBox/DataBox.hpp"
#include "DataStructures/DataBox/PrefixHelpers.hp... | {"hexsha": "8116fa3b50d806ea90a633d39694880631dbf29c", "size": 18549, "ext": "cpp", "lang": "C++", "max_stars_repo_path": "tests/Unit/Evolution/DgSubcell/Actions/Test_TciAndRollback.cpp", "max_stars_repo_name": "kidder/spectre", "max_stars_repo_head_hexsha": "97ae95f72320f9f67895d3303824e64de6fd9077", "max_stars_repo_l... |
------------------------------------------------------------------------------
-- Properties of the alter list
------------------------------------------------------------------------------
{-# OPTIONS --exact-split #-}
{-# OPTIONS --no-sized-types #-}
{-# OPTIONS --no-universe-polymorphism #-}
... | {"hexsha": "fa987bc1b8031c011466d09dd17b0db29d4f4258", "size": 1655, "ext": "agda", "lang": "Agda", "max_stars_repo_path": "notes/FOT/FOTC/UnguardedCorecursion/Alter/PropertiesATP.agda", "max_stars_repo_name": "asr/fotc", "max_stars_repo_head_hexsha": "2fc9f2b81052a2e0822669f02036c5750371b72d", "max_stars_repo_licenses... |
'''
Comparison of Continuous No-Regret Algorithms
@date: May 26, 2015
'''
# Set up infrastructure and basic problem parameters
import matplotlib as mpl
mpl.use('Agg') # this is needed when running on a linux server over terminal
import multiprocessing as mp
import numpy as np
import datetime, os
import pickle
from Co... | {"hexsha": "3710c3ace455c228c08f89d4d372abe219427b14", "size": 3675, "ext": "py", "lang": "Python", "max_stars_repo_path": "vs_example.py", "max_stars_repo_name": "anonymouscontributor/cnr", "max_stars_repo_head_hexsha": "f0c793baddf67b8540ea90617e82d27269d367b9", "max_stars_repo_licenses": ["MIT"], "max_stars_count": ... |
[STATEMENT]
lemma cut_off_after_match_any: "simple_fw (cut_off_after_match_any rs) p = simple_fw rs p"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. simple_fw (cut_off_after_match_any rs) p = simple_fw rs p
[PROOF STEP]
apply(induction rs p rule: simple_fw.induct)
[PROOF STATE]
proof (prove)
goal (3 subgoals):
1. ... | {"llama_tokens": 353, "file": "Simple_Firewall_SimpleFw_Semantics", "length": 2} |
# -*- coding: utf-8 -*-
"""
Created on Fri Jan 04 13:23:27 2013
@author: Joey
"""
import numpy as np
import spectroscopy.Spacetime as Spacetime
import spectroscopy.ElectronicOperator as ElectronicOperator
import spectroscopy.NuclearWavefunction as NuclearWavefunction
import spectroscopy.NuclearOperator as ... | {"hexsha": "35f4ae08d0402a378ba10452eeba70b13f997334", "size": 4709, "ext": "py", "lang": "Python", "max_stars_repo_path": "systems/Juergen/one_fast_mode_monomer.py", "max_stars_repo_name": "jgoodknight/spectroscopy", "max_stars_repo_head_hexsha": "5c41852dff8d02fe49395ecc5cd36902ec867033", "max_stars_repo_licenses": [... |
from __future__ import annotations
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
Iterable,
List,
Optional,
Set,
Tuple,
Union,
cast,
)
import networkx as nx
import strictyaml as yaml
from dcp.utils.common import md5_hash, remove_dupes
from loguru import logger
fro... | {"hexsha": "d85a466770286f91f3683b91be777406023ff679", "size": 8621, "ext": "py", "lang": "Python", "max_stars_repo_path": "snapflow/core/graph.py", "max_stars_repo_name": "icedevml/snapflow", "max_stars_repo_head_hexsha": "329dae3f8eaa70d3a26d38a505faeb45d8eecb57", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_sta... |
#ifndef OPTIONS_HPP_
#define OPTIONS_HPP_
#include <boost/program_options.hpp>
#include <string>
#include <vector>
#include "lvr2/config/BaseOption.hpp"
namespace viewer
{
using boost::program_options::options_description;
using boost::program_options::positional_options_description;
using boost::program_options::va... | {"hexsha": "e200ea04c171ec12b99d6e488f0745bb60bc9fde", "size": 1224, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "src/tools/lvr2_viewer/app/Options.hpp", "max_stars_repo_name": "uos/lvr", "max_stars_repo_head_hexsha": "9bb03a30441b027c39db967318877e03725112d5", "max_stars_repo_licenses": ["BSD-3-Clause"], "max_... |
import numpy as np
import matplotlib.pyplot as plt
import h5py as h5
def plot_traj(x,name,label=""):
fig_traj = plt.figure(1)
ax_traj = fig_traj.add_subplot(111)
ax_traj.plot(x[:,:,0],x[:,:,1],label=label)
ax_traj.set_aspect('equal')
ax_traj.legend()
fig_xztraj = plt.figure(2)
ax_xztraj =... | {"hexsha": "6f191c961bbd9d24e1cd18ed8847a1240d72f6d9", "size": 2428, "ext": "py", "lang": "Python", "max_stars_repo_path": "tools/plotting.py", "max_stars_repo_name": "Krissmedt/relativistic_sdc", "max_stars_repo_head_hexsha": "7b294a9ab5d75a1540f192393ad0b4a570bfddb5", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
import numpy
import pandas
scoreData = pandas.DataFrame({'Y': ['A', 'A', 'A', 'A', 'A', 'A', 'A', 'B', 'B', 'B', 'B', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C', 'C'],
'P_A': [0.47, 0.13, 0.33, 0.47, 0.37, 0.47, 0.5, 0.47, 0.33, 0, 0.47, 0.47, 0.33, 0.47, 0.47, 0, 0.47, 0, 0.47, 0.47],
... | {"hexsha": "b2c5f0c7437782a3d6e4ccac6510aac15db89353", "size": 3767, "ext": "py", "lang": "Python", "max_stars_repo_path": "Kolmogorov-Smirnov Curve/Target Metric.py", "max_stars_repo_name": "eyobghiday/machine-learning", "max_stars_repo_head_hexsha": "d7165f2b64df6fb780ad30aae55b3b827382bede", "max_stars_repo_licenses... |
c ============================================
subroutine b4step2(maxmx,maxmy,mbc,mx,my,meqn,q,
& xlower,ylower,dx,dy,t,dt,maux,aux)
c ============================================
c
c # called from claw2 before each call to step2.
c # use to set time-dependent aux arrays or perform... | {"hexsha": "513b1bb3eb63d8e7870ac89b4dbfaf8eed631173", "size": 592, "ext": "f", "lang": "FORTRAN", "max_stars_repo_path": "clawpack/2d/lib/b4step2.f", "max_stars_repo_name": "geoflows/geoclaw-4.x", "max_stars_repo_head_hexsha": "c8879d25405017b38392aa3b1ea422ff3e3604ea", "max_stars_repo_licenses": ["BSD-3-Clause"], "ma... |
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import torch
from flowbias.config import Config
from flowbias.utils.flow import compute_color
from flowbias.utils.meta_infrastructure import get_available_datasets
from flowbias.evaluations.edgeEval.area_filter import AreaFilter
from flowbias.uti... | {"hexsha": "b1586a043a532a1686917e104ec089acb68deff0", "size": 1788, "ext": "py", "lang": "Python", "max_stars_repo_path": "evaluations/edgeEval/display_area_filter.py", "max_stars_repo_name": "MoritzWillig/flowbias", "max_stars_repo_head_hexsha": "d08e1d8cd250ed147060d374f648e39a23ef16f5", "max_stars_repo_licenses": [... |
from __future__ import division
from typing import Union, Optional
import numpy as np # type: ignore
import cupy as cp # type: ignore
from gepapy.operations import Operations
class Job_Shop(Operations):
"""Job_Shop."""
def __init__(
self,
processing_time: Optional[Union[list, np.ndarray, c... | {"hexsha": "59697cdbb20799802aa707c4b5f127930871621d", "size": 3459, "ext": "py", "lang": "Python", "max_stars_repo_path": "gepapy/job_shop.py", "max_stars_repo_name": "mandalarotation/GenSchedulingCuda-GSC", "max_stars_repo_head_hexsha": "936d23d26b6a1db93096a849426a6f57089b8747", "max_stars_repo_licenses": ["MIT"], "... |
"""Use this script to generate fake CPT data."""
import os
import sys
from pathlib import Path
import numpy as np
import pandas as pd
from faker import Faker
fake = Faker()
fake.seed(0)
def usage(argv):
"""Give feedback on commandline usage."""
cmd = os.path.basename(argv[0])
print('usage: %s <file_pat... | {"hexsha": "6cca9663c0227afcd422115b1391e7a93ea57d73", "size": 2249, "ext": "py", "lang": "Python", "max_stars_repo_path": "Python/sql test/sql_test/scripts/generate_fake_data.py", "max_stars_repo_name": "Pietervanhalem/Pieters-Personal-Repository", "max_stars_repo_head_hexsha": "c31e3c86b1d42f29876455e8553f350d4d527ee... |
from Bio import SeqIO
import numpy as np
import timeit
import sys
from functools import lru_cache
from operator import itemgetter
from typing import List, Tuple
import random
from data.ExactWeightedMatching import ExactWeightedMatching
from lib.helperfunctions import preprocess, DNALA, fitness
def random_pairing(num... | {"hexsha": "37e36647bc5e66567b5364b7ea2582a031ed0aa2", "size": 1580, "ext": "py", "lang": "Python", "max_stars_repo_path": "ex1/main_DNALA_EXACT_RANDOM.py", "max_stars_repo_name": "tkauf15k/sos2020", "max_stars_repo_head_hexsha": "b75188097d095e4acaca32290ba4f49fa8cb6c0e", "max_stars_repo_licenses": ["Apache-2.0"], "ma... |
#!/usr/bin/env python
# > ./stream.py
# > ./stream.py --dev=help
import cv2 as cv
from umucv.stream import autoStream
from collections import deque
import numpy as np
frames = deque(maxlen=10)
for key, frame in autoStream():
aux = cv.resize(frame, (160,140))
frames.append(aux)
screen = np.hstack(frame... | {"hexsha": "e09191bbee7d1df971176a8c376065935b1a61ac", "size": 385, "ext": "py", "lang": "Python", "max_stars_repo_path": "2021-2022/stream_frame_queue.py", "max_stars_repo_name": "franciscomirasg/umucv", "max_stars_repo_head_hexsha": "703629d5152d55d00821aee02d30fbb3cca1b73e", "max_stars_repo_licenses": ["BSD-3-Clause... |
#ifndef NCURSES_STREAM_HPP
#define NCURSES_STREAM_HPP
#include <string>
#include <ncurses.h>
#include <boost//algorithm/string.hpp>
#include "Character.hpp"
#include "Maze.hpp"
#include "Cell.hpp"
class NCursesStream
{
/// \brief wrapper class around NCurses initialization and de-initialization methods
struc... | {"hexsha": "5c1f62da078d13a133d3952d5a44c369ee44167d", "size": 11396, "ext": "hpp", "lang": "C++", "max_stars_repo_path": "dungeon/NCursesStream.hpp", "max_stars_repo_name": "samsparks/climaze", "max_stars_repo_head_hexsha": "a49dc0a926f86311212a61e837ebb46e2a387fe2", "max_stars_repo_licenses": ["MIT"], "max_stars_coun... |
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# (C) British Crown Copyright 2017-2021 Met Office.
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions a... | {"hexsha": "e08301419ba4e3ea152d3f4c509d9025fef13bb4", "size": 24272, "ext": "py", "lang": "Python", "max_stars_repo_path": "improver_tests/ensemble_copula_coupling/test_utilities.py", "max_stars_repo_name": "bjwheltor/improver", "max_stars_repo_head_hexsha": "21b21106f2a7376ee32cd01f47ea81bb770f56a9", "max_stars_repo_... |
"""
OpenCV Canny Edge Detection :
Edge detection is term where identify the boundary of object in image.
"""
# importing module
import cv2
import numpy as np
# image path
img = cv2.imread("../images/1.jpeg")
# canny edge detection
edges = cv2.Canny(img, 100, 200)
# display the image
cv2.imshow("Edge detecti... | {"hexsha": "f7f926ed34066ddacdcd3afe5880a5e521b52bc1", "size": 480, "ext": "py", "lang": "Python", "max_stars_repo_path": "OpenCV2/Image_Processing/Canny_Edge_Detection.py", "max_stars_repo_name": "siddharth-143/Python", "max_stars_repo_head_hexsha": "293f4643a3a13e3b82d23fd8922db54dbb0f12bc", "max_stars_repo_licenses"... |
subroutine opandist (gsmObj, event, fisevent, nn)
! ======================================================================
!
! Accumulate distribution of fission fragments' opening angles.
! nn is total number of produced neutrons.
! bf12 contains the fragment velocity vectors.
!
! Written by K. K.... | {"hexsha": "cf384e0fbdfc2ce34f58196cb3f500de9b953022", "size": 3406, "ext": "f90", "lang": "FORTRAN", "max_stars_repo_path": "src/GeneralizedSpallation/tally/opandist.f90", "max_stars_repo_name": "lanl/generalized-spallation-model", "max_stars_repo_head_hexsha": "4a2f01a873d2e8f2304b8fd1474d43d1ce8d744d", "max_stars_re... |
function V = spm_vol(P)
% Get header information for images
% FORMAT V = spm_vol(P)
% P - a char or cell array of filenames
% V - a structure array containing image volume information
% The elements of the structures are:
% V.fname - the filename of the image.
% V.dim - the x, y and z dimensions of th... | {"author": "fieldtrip", "repo": "fieldtrip", "sha": "c2039be598a02d86b39aae76bfa7aaa720f9801c", "save_path": "github-repos/MATLAB/fieldtrip-fieldtrip", "path": "github-repos/MATLAB/fieldtrip-fieldtrip/fieldtrip-c2039be598a02d86b39aae76bfa7aaa720f9801c/external/spm12/spm_vol.m"} |
#!/usr/bin/env python
import fvm
import fvm.fvmbaseExt as fvmbaseExt
import fvm.importers as importers
import fvm.fvmparallel as fvmparallel
import sys, time
from numpy import *
from mpi4py import MPI
from FluentCase import FluentCase
#fvmbaseExt.enableDebug("cdtor")
fileBase = None
numIterations = 10
fileBase = "/... | {"hexsha": "58e507fa9e2942c5e6c4e824820878ca5baf4b79", "size": 6112, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/fvm/test/PARALLEL_TESTS/testMerger.py", "max_stars_repo_name": "drm42/fvm-drm", "max_stars_repo_head_hexsha": "c9b940e593034f1aa3020d63ff1e09ebef9c182a", "max_stars_repo_licenses": ["MIT"], "m... |
import cv2
import numpy as np
from imutils.video import FileVideoStream
vs=FileVideoStream('messi.webm').start()
ball=cv2.imread('ball.png')
Ball=ball.copy()
ball=cv2.cvtColor(ball,cv2.COLOR_BGR2GRAY)
ball=cv2.medianBlur(ball,5)
ball=cv2.adaptiveThreshold(ball,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY,3,5)
w... | {"hexsha": "af004acf49fe9dbb6556de71bdf574aed536601f", "size": 1038, "ext": "py", "lang": "Python", "max_stars_repo_path": "OpenCV/5.2.py", "max_stars_repo_name": "Nivedya-27/Autumn-of-Automation", "max_stars_repo_head_hexsha": "2f645b58d035d6277f7ee0ff77814be812815f6d", "max_stars_repo_licenses": ["MIT"], "max_stars_c... |
#!/usr/bin/python
#
# Copyright (c) PhaseSpace, Inc 2019
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL # PHASESPACE, INC BE LIABLE ... | {"hexsha": "621759eeb90331ee3fc4cb591f7c92bb30c7f722", "size": 3227, "ext": "py", "lang": "Python", "max_stars_repo_path": "plottest.py", "max_stars_repo_name": "jonathanzxu/mocap-roboticarm", "max_stars_repo_head_hexsha": "957f77249766c1b40b8416a9236a2c60c734e3cd", "max_stars_repo_licenses": ["MIT"], "max_stars_count"... |
classdef mme_xfmr3p_opf < mp.mme_xfmr3p
% MATPOWER
% Copyright (c) 2022, Power Systems Engineering Research Center (PSERC)
% by Ray Zimmerman, PSERC Cornell
%
% This file is part of MATPOWER.
% Covered by the 3-clause BSD License (see LICENSE file for details).
% See https://matpower.org for more info.
% ... | {"author": "MATPOWER", "repo": "matpower", "sha": "7da926d978824bf675a71e0a5cb91f8967f97007", "save_path": "github-repos/MATLAB/MATPOWER-matpower", "path": "github-repos/MATLAB/MATPOWER-matpower/matpower-7da926d978824bf675a71e0a5cb91f8967f97007/lib/+mp/mme_xfmr3p_opf.m"} |
"""
The :py:mod:`h2_fuel` module contains a class to read the required data and
a class to evaluate the power-to-fuel system.
"""
import os
import pandas as pd
import numpy as np
import pvlib
class ReadData:
"""
This class enables to read data from the data files.
Parameters
----------
filename... | {"hexsha": "0a94dee890f7756946beb4979301126f3782f582", "size": 19587, "ext": "py", "lang": "Python", "max_stars_repo_path": "rheia/CASES/H2_FUEL/h2_fuel.py", "max_stars_repo_name": "Tsiri/RHEIA", "max_stars_repo_head_hexsha": "a7bacd72e5515242e78ee413f9e8959ab4f1115d", "max_stars_repo_licenses": ["MIT"], "max_stars_cou... |
import numpy as np
from numpy.fft import fft2, ifft2, ifftshift
from scipy.sparse import spdiags, eye as speye
from scipy.sparse.linalg import spsolve
from menpofit.math.fft_utils import pad, crop
def mosse(X, y, l=0.01, boundary='constant', crop_filter=True):
r"""
Minimum Output Sum of Squared Errors (MOSSE... | {"hexsha": "2b80d9e1b419f80ff46311e072543bc34e8aa2a5", "size": 14354, "ext": "py", "lang": "Python", "max_stars_repo_path": "DeepAlignmentNetwork/menpofit/math/correlationfilter.py", "max_stars_repo_name": "chiawei-liu/DeepAlignmentNetwork", "max_stars_repo_head_hexsha": "52621cd2f697abe372b88c9ea0ee08f0d93b43d8", "max... |
import numpy as np
import torch
from torch import nn
class GaussianHeadWithStateIndependentCovariance(nn.Module):
"""Gaussian head with state-independent learned covariance.
This link is intended to be attached to a neural network that outputs
the mean of a Gaussian policy. The only learnable parameter t... | {"hexsha": "3faa32f5d73355e7535d488702b6391a6c98ea77", "size": 4099, "ext": "py", "lang": "Python", "max_stars_repo_path": "pfrl/policies/gaussian_policy.py", "max_stars_repo_name": "ummavi/pfrl-1", "max_stars_repo_head_hexsha": "e856a7cca30fcc3871024cdf7522d066006a5f0c", "max_stars_repo_licenses": ["MIT"], "max_stars_... |
"""Logic for alerting the user on possibly problematic patterns in the data (e.g. high number of zeros , constant
values, high correlations)."""
from enum import Enum, unique
from typing import List, Union
import warnings
from contextlib import suppress
import re
from dateutil.parser import parse
import numpy as np
f... | {"hexsha": "3be7ad25c4cdf519aad86fc074b3f9340f48588a", "size": 9688, "ext": "py", "lang": "Python", "max_stars_repo_path": "src/pandas_profiling_study/model/messages.py", "max_stars_repo_name": "lucasiscoviciMoon/pandas-profiling-study", "max_stars_repo_head_hexsha": "142d3b0f5e3139cdb531819f637a407682fa5684", "max_sta... |
import os
import sys
import numpy as np
from google.protobuf import text_format
from .layers import *
from .core import print_stderr
try:
import caffe
PYCAFFE_AVAILABLE = True
except ImportError:
import caffepb
PYCAFFE_AVAILABLE = False
print_stderr('WARNING: PyCaffe not found!')
print_stderr(... | {"hexsha": "7d01c64ee813bbbabc23d0c1c33c862e58182544", "size": 15245, "ext": "py", "lang": "Python", "max_stars_repo_path": "nn/kaffe/core.py", "max_stars_repo_name": "polltooh/FineGrainedAction", "max_stars_repo_head_hexsha": "4582b4179e643119448c7c20ab06044fb211163e", "max_stars_repo_licenses": ["MIT"], "max_stars_co... |
# -*- coding: utf-8 -*-
"""
comments
author: diqiuzhuanzhuan
email: diqiuzhuanzhuan@gmail.com
"""
import unittest
import numpy as np
import os
from .dataman import Sample
from .dataman import TrainingInstance
from .dataman import create_attention_mask
from .dataman import PreTrainingDataMan
class SampleTest(unittes... | {"hexsha": "5642196fbbc7407bd904daee56db7bf6c60c9bb1", "size": 7231, "ext": "py", "lang": "Python", "max_stars_repo_path": "poros/unilmv2/dataman_test.py", "max_stars_repo_name": "diqiuzhuanzhuan/poros", "max_stars_repo_head_hexsha": "b4f0ff4c5094aa9df12a9195e5b3edd85c3460f4", "max_stars_repo_licenses": ["MIT"], "max_s... |
import time,threading
import cv2,os,sys,socket,struct,pickle,psutil
import numpy as np
from tkinter import *
datalist=sorted(os.listdir('DATA/'))
datacounter=len(datalist)+1
for i in range(len(datalist)):
data=np.load("DATA/"+datalist[i],allow_pickle=True)
print("diving this",datalist[i])
np.save("DATA/dat... | {"hexsha": "d51679e901395e74c5420aa27ae0c129d1bfde8e", "size": 622, "ext": "py", "lang": "Python", "max_stars_repo_path": "tests/collecting_data/datadivider.py", "max_stars_repo_name": "gururajo/Self-Driving-Car", "max_stars_repo_head_hexsha": "fecde52396df6c17e6948cc77ab9d17a524150d3", "max_stars_repo_licenses": ["MIT... |
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