text stringlengths 0 27.1M | meta dict |
|---|---|
% Make the command for organizing stories
% \story{name}{title}{story}{pronouns}{major}{year}
\newcommand{\story}[6]{
\section*{\uppercase{\textbf{#1}}: #2}
#3 \\
\textit{-#4} \\
\textit{-#5, #6}
}
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FUNCTION PS_TOTL ( t850, td850, t500 )
C************************************************************************
C* PS_TOTL *
C* *
C* This function computes the total totals index: *
C* *
C* TOTL = ( T850 - T500 ) + ( TD850 - T500 ) *
C* *
C* REAL PS_TOTL ( T850, TD850, T500 )... | {
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[STATEMENT]
lemma charpoly_eq: "charpoly A = Cayley_Hamilton.charpoly (from_vec A)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. Cayley_Hamilton_Compatible.charpoly A = Cayley_Hamilton.charpoly (from_vec A)
[PROOF STEP]
unfolding charpoly_def Cayley_Hamilton.charpoly_def det_sq_matrix_eq[symmetric] X_def C_def
[PR... | {
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# (c) Tom Gaimann, 2020
# Zusammensetzung eines frequenzmodulierten Signals
# Ref: https://gist.github.com/fedden/d06cd490fcceab83952619311556044a
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({'font.size': 22})
f_modulator = 4 # Frequenz der Nachrichten Welle
f_carrier = 40 # Frequenz der ... | {
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from ale_python_interface import ALEInterface
import pygame
from pygame.locals import *
import numpy as np
import os
import scipy.ndimage as ndimage
class AtariEnvironment:
"""
Environment for playing Atari games using ALE Interface
"""
def __init__(self, game_filename, **kwargs):
"""
Create an environmen... | {
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#define BOOST_TEST_MODULE URL
#include <boost/test/unit_test.hpp>
#include "odil/webservices/URL.h"
BOOST_AUTO_TEST_CASE(Equal)
{
auto const url = odil::webservices::URL::parse(
"foo://example.com:8042/over/there?name=ferret#nose");
BOOST_REQUIRE(url == url);
BOOST_REQUIRE(!(url != url));
}
BOOST... | {
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"""
struct GridPortion{Dc,Dp,G} <: Grid{Dc,Dp}
parent_grid::G
cell_to_parent_cell::Vector{Int32}
node_to_parent_node::Vector{Int32}
end
"""
struct GridPortion{Dc,Dp,G} <: Grid{Dc,Dp}
parent_grid::G
cell_to_parent_cell::Vector{Int32}
node_to_parent_node::Vector{Int32}
cell_to_nodes::Ta... | {
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/*
* Server.h
*
* Created on: 19 нояб. 2017 г.
* Author: snork
*/
#ifndef SERVER_HPP_
#define SERVER_HPP_
#include <queue>
#include <boost/asio/io_service.hpp>
#include <boost/asio/strand.hpp>
#include <boost/asio/ip/v6_only.hpp>
#include <boost/asio/ip/tcp.hpp>
#include <boost/asio/write.hpp>
#include "... | {
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import subprocess
import os
import datetime
import time
import numpy as np
"""
'Logger' intended for real-time logging from inside executors to hdfs. May be slow, so use sparingly!
Looks at CONFIG["LOGS"]["hdfs_logfile"] for hdfs logfile path. Example (note the *3* fwd slashes) might be:
hdfs:///tmp/logfile.txt
Can... | {
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## Demo de for Loops
## Prof. James Hunter
## from: https://rstudio.cloud/project/1181172
## 28 de maio de 2020
## Baseado em Cap. 21 de Grolemund & Wickham, R for Data Science (O'Reilly)
set.seed(42)
df <- tibble(
a = rnorm(10),
b = rnorm(10),
c = rnorm(10),
d = rnorm(10)
)
glimpse(df)
s... | {
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@testset "Testing CHSF Descriptor for dc Si" begin
@info("Testing CHSF Descriptor for dc Si.")
using DescriptorZoo, JuLIP, Test
at = bulk(:Si, cubic=true)
desc = chsf(at, 6.5, n=2, l=2)
chsf_ref = [10.3698237,1.4503467,-8.2118063,51.6882200,-53.0113716,69.8233316] #n=2,l=2 case
chsf_now = vcat(desc[1,:]...)
println(@t... | {
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from pytest_check import check
import fdm
import jax
from jax.config import config
import jax.numpy as np
import fenics
import fenics_adjoint as fa
import ufl
from jaxfenics_adjoint import build_jax_fem_eval
config.update("jax_enable_x64", True)
fenics.parameters["std_out_all_processes"] = False
fenics.set_log_level... | {
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2019.4.30
# @Author : FrankEl
# @File : Feature_selection_demo_rt.py
import matplotlib.pyplot as plt
import numpy as np
import scipy.io as scio
from sklearn.cross_decomposition import PLSRegression
from sklearn.model_selection import train_test_split
from... | {
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double precision function deter3(r)
implicit none
double precision r(3,3)
c
c return the determinant of a 3x3 matrix
c
deter3 =
$ r(1,1)*(r(2,2)*r(3,3)-r(2,3)*r(3,2)) -
$ r(1,2)*(r(2,1)*r(3,3)-r(2,3)*r(3,1)) +
$ r(1,3)*(r(2,1)*r(3,2)-r(2,2)*r(3,1))
c
end
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# -*- coding: utf-8 -*-
# Copyright (C) 2015-2017 by Brendt Wohlberg <brendt@ieee.org>
# All rights reserved. BSD 3-clause License.
# This file is part of the SPORCO package. Details of the copyright
# and user license can be found in the 'LICENSE.txt' file distributed
# with the package.
"""Utility functions"""
from... | {
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## Main function: header_analysis(text)
## input file: readme files text data
## output file: json files with categories extracted using header analysis; other text data cannot be extracted
import os
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import re
import string
import colle... | {
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module Accounting
using Compat
import Compat: String
import Currencies: currency
using Currencies
using DataStructures
import Base.push!
include("debitcredit.jl")
include("accounts.jl")
include("entries.jl")
include("ledger.jl")
include("reports.jl")
export Split, Entry, Ledger
export Asset, Liability, Equity, Reve... | {
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import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import pandas as pd
data = pd.read_csv('mobile_cleaned.csv')
data.head()
ax = sns.scatterplot(x="stand_by_time", y="battery_capacity", data=data)
plt.show()
ax = sns.scatterplot(x = "stand_by_time", y = "battery_capacity", hue="thickness", dat... | {
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# coding=utf-8
# coding=utf-8
# Copyright 2019 The RecSim Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | {
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[STATEMENT]
lemma mult_L_omega_below:
"(x * L)\<^sup>\<omega> \<le> x * L"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (x * L)\<^sup>\<omega> \<le> x * L
[PROOF STEP]
by (metis mult_right_isotone n_L_below_L omega_slide) | {
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#include <iostream>
#include <stdexcept>
#include <boost/lexical_cast.hpp>
#include "Tudat/Astrodynamics/BasicAstrodynamics/physicalConstants.h"
#include "Tudat/Astrodynamics/BasicAstrodynamics/timeConversions.h"
#include "Tudat/External/SpiceInterface/spiceInterface.h"
#include "Tudat/External/SpiceInterface... | {
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#!/usr/bin/env python3
"""
Fast approximations for various trig functions
"""
from approx.cheby import cheby_poly, cheby_fit
from utils import utils
import math
from matplotlib import pyplot as plt
import numpy as np
from typing import Callable, Union, Optional, Tuple
PI = math.pi
HALF_PI = 0.5 * P... | {
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[STATEMENT]
lemma map2set_finite[relator_props]:
assumes "finite_map_rel (\<langle>Rk,Id\<rangle>R)"
shows "finite_set_rel (\<langle>Rk\<rangle>map2set_rel R)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. finite_set_rel (\<langle>Rk\<rangle>map2set_rel R)
[PROOF STEP]
using assms
[PROOF STATE]
proof (prove)
us... | {
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"""
Copyright (c) 2016 Jet Propulsion Laboratory,
California Institute of Technology. All rights reserved
"""
import sys
import traceback
from datetime import datetime, timedelta
from multiprocessing.dummy import Pool, Manager
from shapely.geometry import box
import numpy as np
import pytz
from nexustiles.nexustiles ... | {
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import numpy as np
from scipy.stats.distributions import norm
def generate_logistic():
# Number of clusters
nclust = 100
# Regression coefficients
beta = np.array([1, -2, 1], dtype=np.float64)
# Covariate correlations
r = 0.4
# Cluster effects of covariates
rx = 0.5
# Within-c... | {
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## Automatically adapted for numpy.oldnumeric Jul 23, 2007 by
#############################################################################
#
# Author: Alex T. GILLET
#
# Copyright: A. Gillet TSRI 2003
#
#############################################################################
#
# $Header: /opt/cvs/DejaVu2/Arrows... | {
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import http.client
import json
import numpy
from pymongo import MongoClient
import datetime
import pprint
from bson.objectid import ObjectId
client = MongoClient('mongodb://trading:secret@127.0.0.1:27017/')
trading_db = client['trading-db']
api_response_collection = trading_db['api-response-collection']
# post_id = t... | {
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# FIXME: Import order causes error:
# ImportError: dlopen: cannot load any more object with static TL
# https://github.com/pytorch/pytorch/issues/2083
import torch
import numpy as np
import skimage.data
from torchfcn.models.fcn32s import get_upsampling_weight
def test_get_upsampling_weight():
src = skimage.data... | {
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program test1
integer I
real X(100)
C AND expression
DO 100 I =1,N
IF ((I.LT.1).AND.(I.LE.50)) THEN
ELSE
X(I) = 1
ENDIF
100 CONTINUE
C OR expression
DO 200 I =1,N
IF ((1.LE.I).OR.(I.LE.50)) TH... | {
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# -*- coding: utf-8 -*-
"""
Test of the population propagator
"""
from aloe import step
from aloe import world
import numpy
from quantarhei.testing.feature import FeatureFileGenerator
from quantarhei.testing.feature import match_number
from quantarhei import TimeAxis
from quantarhei import PopulationPr... | {
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import torch
import torch.nn as nn
import torch.nn.quantized as nnq
from torch.quantization import QuantStub, DeQuantStub
import torchvision
import unittest
import os
from neural_compressor.adaptor import FRAMEWORKS
from neural_compressor.model import MODELS
from neural_compressor.adaptor.pytorch import PyTorchVersion... | {
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import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
from mpl_toolkits.mplot3d.axes3d import Axes3D
def load_data(filename):
'''
读取数据，将其转换为np.array的形式，将x和y以元组形式返回，解包获取数据
'''
column1 = list()
column2 = list()
... | {
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#ifndef BEAST_TEST_STRING_ISTREAM_HPP
#define BEAST_TEST_STRING_ISTREAM_HPP
#include <beast/core/async_result.hpp>
#include <beast/core/bind_handler.hpp>
#include <beast/core/error.hpp>
#include <beast/websocket/teardown.hpp>
#include <boost/asio/buffer.hpp>
#include <boost/asio/io_service.hpp>
#include <boost/throw_... | {
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[STATEMENT]
lemma row_empty:"row [] i = []"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. row [] i = []
[PROOF STEP]
unfolding row_def
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. map (\<lambda>w. w ! i) [] = []
[PROOF STEP]
by auto | {
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#%%
import tensorflow as tf
import numpy as np
t = tf.constant([0,1,2,1])
# %%
tf.equal(t, 1)
# %%
tf.cast(tf.equal(t, 1), tf.int32)
# %%t
indices = tf.where(tf.not_equal(t, 1)) | {
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#!/usr/bin/env python3
# coding=utf-8
import matplotlib.pyplot as plt
import numpy as np
def f(x, y):
# the height function
return (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)
n = 100
x = np.linspace(-3, 3, n)
y = np.linspace(-3, 3, n)
X, Y = np.meshgrid(x, y)
# use plt.contourf to filling con... | {
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[STATEMENT]
lemma locally_empty [iff]: "locally P {}"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. locally P {}
[PROOF STEP]
by (simp add: locally_def openin_subtopology) | {
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# Copyright 2018 Google LLC
#
# 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 agreed to in writing, s... | {
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[STATEMENT]
lemma kc_8x7_hd: "hd kc8x7 = (1,1)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. hd kc8x7 = (1, 1)
[PROOF STEP]
by eval | {
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import numpy as np
import itertools
from affordable.affordable import Affordable, get_action
ACTIONS = ('np', 'up', 'dn', 'lf', 'rt', 'rs')
class Shaman(Affordable):
def __init__(self, ctx, name, width, height):
super(Shaman, self).__init__(ctx, name)
self.width = width
self.height = he... | {
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module SurfaceCouplingTests
using Test
using Gridap
import Gridap: ∇
using LinearAlgebra: tr, ⋅
# Analytical functions
u(x) = VectorValue( x[1]^2 + 2*x[2]^2, -x[1]^2 )
∇u(x) = TensorValue( 2*x[1], 4*x[2], -2*x[1], zero(x[1]) )
Δu(x) = VectorValue( 6, -2 )
p(x) = x[1] + 3*x[2]
∇p(x) = VectorValue(1,3)
s(x) = -Δu(x)... | {
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In Chestnut Park there is a roundhouse that serves as a mini community center for the neighborhood. Sadly it is often the target of vandalism.
| {
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... |
# -*- coding: utf-8 -*-
# This file as well as the whole tsfresh package are licenced under the MIT licence (see the LICENCE.txt)
# Maximilian Christ (maximilianchrist.com), Blue Yonder Gmbh, 2016
"""
This module contains the main function to interact with tsfresh: extract features
"""
from __future__ import absolute_... | {
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"""
Copyright (c) 2019 Intel Corporation
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 agreed to in writin... | {
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//
// lager - library for functional interactive c++ programs
// Copyright (C) 2017 Juan Pedro Bolivar Puente
//
// This file is part of lager.
//
// lager is free software: you can redistribute it and/or modify
// it under the terms of the MIT License, as detailed in the LICENSE
// file located at the root of this sou... | {
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export TimeDelay, ps2μm!, μm2ps!
ps2μm(t::Real) = round(149.896225 * t)
μm2ps(d::Real) = d / 149.896225
for f in (:ps2μm, :μm2ps)
@eval begin
function $(Symbol(f, !))(arr::VecI)
@simd for i in eachindex(arr)
@inbounds arr[i] = $f(arr[i])
end
return nothi... | {
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from __future__ import print_function, division
import os
from PIL import Image
import numpy as np
from torch.utils.data import Dataset
from mypath import Path
from torchvision import transforms
from dataloaders import custom_transforms as tr
import pandas as pd
class LiverSegmentation(Dataset):
"""
LITS datas... | {
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[STATEMENT]
lemma inv_2 :
"(\<tau> \<Turnstile> Person .allInstances@pre()->includes\<^sub>S\<^sub>e\<^sub>t(self)) \<Longrightarrow>
(\<tau> \<Turnstile> inv\<^sub>P\<^sub>e\<^sub>r\<^sub>s\<^sub>o\<^sub>n\<^sub>_\<^sub>l\<^sub>a\<^sub>b\<^sub>e\<^sub>l\<^sub>A\<^sub>T\<^sub>p\<^sub>r\<^sub>e(self)) = ((\<tau> \... | {
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import sys
import argparse
from time import time
import pandas as pd
import numpy as np
from sqlalchemy import create_engine
import re
from scipy import stats
from nltk.tokenize import word_tokenize
from nltk.stem.wordnet import WordNetLemmatizer
from nltk.corpus import stopwords
import spacy
import en_core_web_sm
... | {
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from __future__ import division
import numpy as np
from skimage.color import rgb2gray
from skimage import transform
from skimage import segmentation
from skimage import morphology
from skimage import transform
from scipy.interpolate import interp1d
from scipy import stats
from scipy import sparse
from scipy.misc import... | {
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import numpy as np
import tensorflow as tf
import tensorflow_probability as tfp
import Nn
from utils.sth import sth
from utils.tf2_utils import get_TensorSpecs, gaussian_clip_rsample, gaussian_likelihood_sum, gaussian_entropy
from Algorithms.tf2algos.base.on_policy import On_Policy
class PG(On_Policy):
def __init... | {
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'''
Author: Tobi and Gundram
'''
from __future__ import print_function
import tensorflow as tf
from tensorflow.python.ops import ctc_ops as ctc
from tensorflow.python.ops import rnn_cell
from tensorflow.python.ops.rnn import bidirectional_rnn
from util.LoaderUtil import read_image_list, get_list_vals
from random impo... | {
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# Coefficients calculated with https://github.com/simonbyrne/Remez.jl
@inline function approx_sin8(x::Union{T,Vec{<:Any,T},VecUnroll{<:Any,<:Any,T}}) where {T <: Real}
# poly(x) ≈ (xʳ = sqrt(x); sin((xʳ*π)/2)/xʳ)
x² = x * x
c0 = T(2.2214414690791831235079404853520399592349401067725149122047990692096659312188... | {
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import re
from collections import OrderedDict
import pytest
import numpy as np
from tests.test_commons.base import mixin_suite
import plums.commons.data as data
import plums.commons.data.mixin
from plums.commons.data.taxonomy import Label, Taxonomy
@pytest.fixture(params=('ordered-dict', 'tile-collection'))
def til... | {
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from sklearn.model_selection import learning_curve
from sklearn.model_selection import ShuffleSplit
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.metrics import accuracy_score, recall_score, precision_score
from emissions.data import load_data, clean_data
def scoring_table(search... | {
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"""
Created on Sun Apr 15 00:39:35 2018
@author: Hrid
Source: https://github.com/hridkamolbiswas/Principal-Component-Analysis-PCA-on-image-dataset/blob/master/pca.py
"""
import numpy as np
from numpy import linalg as LA
import os, os.path
# np.set_printoptions(threshold=np.nan)
# import cv2
from matplotlib.image impor... | {
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"""Implements ETL processing for COVID-19 datasets.
It performs the following actions:
1. pull updated datasets from https://github.com/datadista/datasets
1.1. SOURCE environment variable points to a local repository path
2. read .csv data files into pandas dataframes
3. export data to JSONStat format
4. push JSON f... | {
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[STATEMENT]
lemma oth_class_taut_3_g[PLM]:
"[(\<phi> \<^bold>\<equiv> \<psi>) \<^bold>\<equiv> (\<psi> \<^bold>\<equiv> \<phi>) in v]"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. [\<phi> \<^bold>\<equiv> \<psi> \<^bold>\<equiv> (\<psi> \<^bold>\<equiv> \<phi>) in v]
[PROOF STEP]
by PLM_solver | {
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[STATEMENT]
lemma ad_equiv_list_comm: "ad_equiv_list X xs ys \<Longrightarrow> ad_equiv_list X ys xs"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. ad_equiv_list X xs ys \<Longrightarrow> ad_equiv_list X ys xs
[PROOF STEP]
by (auto simp: ad_equiv_list_def) (smt (verit, del_insts) ad_equiv_pair_comm in_set_zip prod.... | {
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# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/060_callback.core.ipynb (unless otherwise specified).
__all__ = ['TransformScheduler', 'ShowGraph', 'ShowGraphCallback2', 'SaveModel', 'get_lds_kernel_window',
'prepare_LDS_weights', 'WeightedPerSampleLoss', 'BatchSubsampler']
# Cell
from fastai.callback.all ... | {
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#!/usr/bin/env python
# coding: utf-8
# In[1]:
get_ipython().run_line_magic('ls', '')
# In[2]:
import numpy as np
import matplotlib.pyplot as plt
# In[4]:
filen = 'feooh'
# In[5]:
data = np.loadtxt(filen+'.ASC')
# In[6]:
plt.plot(data[:,0], data[:,1])
# In[7]:
plt.plot(data[:,0], data[:,2])
# I... | {
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import numpy as np
from sklearn import __version__
from sklearn.utils import check_array
from sklearn.utils.validation import check_is_fitted
from .base import BaseFeatureLibrary
from .weak_pde_library import WeakPDELibrary
class GeneralizedLibrary(BaseFeatureLibrary):
"""Put multiple libraries into one library.... | {
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import time
import numpy as np
from matplotlib import rc
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})
rc('text', usetex=True)
from pydrake.all import PiecewisePolynomial
from qsim_old.simulator import QuasistaticSimulator
from qsim_old.problem_definition_pinch import problem_definition
from plo... | {
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import os
import subprocess
import shutil
import numpy as np
import pandas as pd
from d3m.primitives.schema_discovery import profiler
from d3m.primitives.data_transformation import column_parser, extract_columns_by_semantic_types, grouping_field_compose
from kf_d3m_primitives.ts_forecasting.nbeats.nbeats import NBEAT... | {
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import onnx
import numpy as np
from mqbench.utils.logger import logger
from .utils import ONNXGraph
FAKE_QUANTIZE_OP = ['FakeQuantizeLearnablePerchannelAffine', 'FixedPerChannelAffine', 'FakeQuantizeDSQPerchannel',
'LearnablePerTensorAffine', 'FixedPerTensorAffine', 'FakeQuantizeDSQPertensor']
... | {
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import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import sklearn
def prepare_country_stats(_bli, _gdp):
""" Prepare stats to be used in regression """
return print("yo")
def run_model():
""" Method to run linear model against BLI and GDP data """
# Stats grabbed from http://stats... | {
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import ctypes
import os
import numpy as np
'''
Author - Daniel J. Whiting
Date modified - 10/08/2017
'''
class HRMTimeAPI():
def __init__(self):
# Load DLL into memory
SENSL = r'C:\Program Files (x86)\sensL\HRM-TDC\HRM_TDC DRIVERS'
os.environ['PATH'] = ';'.join([SENSL, os.environ['PATH']])
self.dll = ctype... | {
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{-# OPTIONS --without-K --safe #-}
open import Relation.Binary.Core
module Definitions
{a ℓ} {A : Set a} -- The underlying set
(_≈_ : Rel A ℓ) -- The underlying equality
where
open import Algebra.Core
open import Data.Product
open import Algebra.Definitions
Alternativeˡ : Op₂ A → Set _
Alternativeˡ _∙_ ... | {
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import math
import re
from collections import namedtuple
from functools import lru_cache
import numpy as np
from m2cgen.ast import TOTAL_NUMBER_OF_EXPRESSIONS
CachedResult = namedtuple('CachedResult', ['var_name', 'expr_result'])
def get_file_content(path):
return path.read_text(encoding="utf-8")
@lru_cache(... | {
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using Revise
using DataFrames, CSV, JDF
using WeakRefStrings
a[!, :stringarr] = StringArray(rand(["a", "a", "b"], size(a,1)))
a[!, :cate] = categorical(a[!, :stringarr])
@time a = CSV.read("c:/data/feature_matrix_cleaned.csv");
@time savejdf("c:/data/feature_matrix_cleaned.csv.jdf", a)
a = nothing
@time... | {
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"""
Training/testing/inference script for COVID-Net CT models for COVID-19 detection in CT images.
"""
import math
import os
import sys
import time
import cv2
import json
import shutil
import numpy as np
from math import ceil
import tensorflow as tf
import matplotlib.pyplot as plt
from sklearn.metrics import confusion... | {
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import os.path
from optparse import OptionParser
import results
import pylab
import loader
import time
import torch
import numpy as np
from descriptors import raw_gray_descriptor, hardnet_descriptor, hog_descriptor
# parameters according to the paper --
class ... | {
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################################################
## STEP 4. Number of genes vs UMIs filter
#################################################
# This filter focuses on filter cells that are far from the behaviour of the relationship between the number of genes (it measures the number of
# genes in a cell that has at le... | {
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Load LFindLoad.
From lfind Require Import LFind.
From adtind Require Import goal11.
Require Import Extraction.
Extract Inductive nat => nat [ "(O)" "S" ].
Extract Inductive list => list [ "Nil" "Cons" ].
Definition lfind_example_1 := ( Cons (Succ (Succ Zero)) (Cons Zero Nil)).
Definition lfi... | {
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import gym
import numpy as np
import cv2
import copy
class Env:
def __init__(self, vision=False):
self.vision = vision
self.W = 400
self.ACT_SCALE = 0.01
self.TL = 100
self.action_space = gym.spaces.Box(low=-1,high=1, shape=[3])
if not self.vision:
self.observation_space = gym.spaces.B... | {
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import numpy as np
from pprint import pprint
def __build_type1_(self,
labelmap_file,
label_col,
color_col,
file_col_sep):
# List of class names in CS dataset (ordered)
global CS_label_names
# Dict of CS labels such { 1: road, 2: .... | {
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import cv2
import os
import numpy as np
initialize = True
net = None
def get_output_layers(net):
layer_names = net.getLayerNames()
output_layers = [layer_names[i[0] - 1] for i in net.getUnconnectedOutLayers()]
return output_layers
def detect_common_objects(image, confidence=0.05, nms_thresh=0.05, model='yolov... | {
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[STATEMENT]
lemma jvm_one_step1[trans]:
"\<lbrakk> P \<turnstile> \<sigma> -jvm\<rightarrow>\<^sub>1 \<sigma>'; P \<turnstile> \<sigma>' -jvm\<rightarrow> \<sigma>'' \<rbrakk> \<Longrightarrow> P \<turnstile> \<sigma> -jvm\<rightarrow> \<sigma>''"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>P \<turnstil... | {
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using RandomFunctions
using Test
@testset "collatz.jl" begin
@test collatz_steps(10) == [5, 16, 8, 4, 2, 1]
@test collatz_steps_02(10) == [5, 16, 8, 4, 2, 1]
@test max_stop_time(10) == (19,9)
@test max_stop_time_02(10^7) == (8400511, 685)
@test max_stop_time_03(10^7) == (8400511, 685)
end
@testset... | {
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using BenchmarkTools
using Distributed
addprocs()
@everywhere using TrajectoryOptimization
@everywhere using SharedArrays
# Set up problem
model, obj0 = Dynamics.cartpole_analytical
n,m = model.n, model.m
obj = copy(obj0)
obj.x0 = [0;0;0;0.]
obj.xf = [0.5;pi;0;0]
obj.tf = 2.
u_bnd = 50
x_bnd = [0.6,Inf,Inf,Inf]
obj_c... | {
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import numpy as np
import os
from tools import *
def run_stochastic(dataset, name, R, c_0=3.0, L_0=1.0, x_axe_threshold=1000,
max_time=100, timestamps=[20, 20, 20, 20], show_legend=True,
inner_eps=1e-7, resid_eps=1e-6, M=1):
print('STOCHASTIC METHODS: \t %s, \t file: ... | {
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#!/usr/bin/env python
import os
import numpy as np
from PIL import Image
from matplotlib import pyplot as plt
from pyclowder.utils import CheckMessage
from pyclowder.files import upload_to_dataset
from pyclowder.datasets import download_metadata, upload_metadata, submit_extraction
from terrautils.extractors import Te... | {
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Inductive day : Type :=
| monday : day
| tuesday : day
| wednesday : day
| thursday : day
| friday : day
| saturday : day
| sunday : day.
Definition next_weekday (d:day) : day :=
match d with
| monday => tuesday
| tuesday => wednesday
| wednesday => thursday
| thursday => friday
| friday => monday
| saturday => mon... | {
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#!/usr/bin/env python3
"""A test file for matrixpng
The canonical source for this package is https://github.com/finitemobius/matrixpng-py"""
import matrixpng
import numpy as np
__author__ = "Finite Mobius, LLC"
__credits__ = ["Jason R. Miller"]
__license__ = "MIT"
__version__ = "alpha"
__maintainer__ = "Finite Mobiu... | {
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/*=============================================================================
Copyright (c) 2009 Hartmut Kaiser
Distributed under the Boost Software License, Version 1.0. (See accompanying
file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
==============================================... | {
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import pandas
import numpy
import random
DIMS96 = {'rows':8,'columns':12}
def create_constant_column_plate(dims: dict,sources: int):
"""
Generate a dataframe representing a 96-well plate that has one media
ingredient per column.
"""
# initialize an array with one row for each well and one column for each
# med... | {
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// STD headers
#include <assert.h>
#include <limits>
#include <list>
#include <string>
#include <unordered_map>
#include <vector>
// Boost headers
#include <boost/program_options.hpp>
// Custom headers
#include "cache_base.hpp"
#include "cache_belady.hpp"
#include "cache_common.hpp"
#include "utils.hpp"
using namesp... | {
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[STATEMENT]
lemma errMOD_igSwapIGVarSTR:
fixes MOD :: "('index,'bindex,'varSort,'sort,'opSym,'var,'gTerm,'gAbs)model"
assumes "igVarIPresIGWls MOD" and "igSwapIGVar MOD"
shows "igSwapIGVar (errMOD MOD)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. igSwapIGVar (errMOD MOD)
[PROOF STEP]
using assms
[PROOF STATE]
pro... | {
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from __future__ import print_function, division
#
import sys,os
quspin_path = os.path.join(os.getcwd(),"../../")
sys.path.insert(0,quspin_path)
#
from quspin.operators import hamiltonian # Hamiltonians and operators
from quspin.basis import spin_basis_1d # Hilbert space spin basis
from quspin.tools.measurements import ... | {
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# encoding=utf-8
import random
import numpy as np
import torch
import torch.utils.data as data
from itertools import chain
import codecs
import json
import collections
import jieba
class MyDataset(data.Dataset):
def __init__(self, corp, config, mode='TRAIN'):
self.data_convs = []
self.data_labels ... | {
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abstract type AbstractMachine end
function filtrations end
function (m::AbstractMachine)(y₀)
forward, backward = filtrations(m, y₀)
return solve(y₀, m.W, m.σ, (forward, backward))
end
sum_dims(dims::Tuple) = prod(dims[1:end-2]) * sum(dims[end-1:end])
# glorot initialization, from https://github.com/FluxML/F... | {
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# Copyright (c) 2018-present, Royal Bank of Canada and other authors.
# See the AUTHORS.txt file for a list of contributors.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
from __future__ import absolute_import
from __f... | {
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import numpy as np
import matplotlib.pyplot as plt
X = np.linspace(-np.pi, np.pi, 256)
C = np.cos(X)
S = np.sin(X)
plt.plot(X, C)
plt.plot(X, S)
plt.show() | {
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__author__ = 'jlu96'
import causal_pipeline as cp
import sys
import pickle
import pandas as pd
import geneTSmunging as gtm
import os
import numpy as np
def get_parser():
# Parse arguments
import argparse
description = 'Given the baseline, per gene hyperparameter fit results, choose the best hyperparamet... | {
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"""
MatHeatDiffModule
Module for linear heat diffusion material models.
"""
module MatHeatDiffModule
using FinEtools.FTypesModule: FInt, FFlt, FCplxFlt, FFltVec, FIntVec, FFltMat, FIntMat, FMat, FVec, FDataDict
import FinEtools.MatModule: AbstractMat
using FinEtools.MatrixUtilityModule: mulCAB!
"""
MatHeatDi... | {
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import numpy as np
from scipy.interpolate import InterpolatedUnivariateSpline
from sklearn.mixture import GaussianMixture as GMM
from .utils import fix_dim_gmm, custom_KDE
class Likelihood(object):
"""A class for computation of the likelihood ratio.
Parameters
----------
model : instance of GPRegress... | {
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#!/usr/bin/env python3
#
# Copyright 2019 Peifeng Yu <peifeng@umich.edu>
#
# This file is part of Salus
# (see https://github.com/SymbioticLab/Salus).
#
# 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 L... | {
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# imports
import semseg_vaihingen.config as cfg
from . import model_generator
from . import data_io as dio
import numpy as np
from sklearn import metrics
import keras
import matplotlib as mpl
mpl.use('Agg')
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import os, re
import argparse
# l... | {
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%% DOS_DIR_TEST tests the DOS facility for issuing operating system commands.
%
% Discussion:
%
% DIR is a legal command on MS/DOS systems, and returns a list of the
% files in the current directory.
%
% Licensing:
%
% This code is distributed under the GNU LGPL license.
%
% Modified:
%
% 19 July 2006
%
... | {
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#! /usr/bin/env python
"""Tests for the ``preview_image`` module.
Authors
-------
- Johannes Sahlmann
Use
---
These tests can be run via the command line (omit the ``-s`` to
suppress verbose output to ``stdout``):
::
pytest -s test_preview_image.py
"""
import glob
import os
import pytes... | {
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