text stringlengths 0 27.1M | meta dict |
|---|---|
import tactic.basic
import tactic.omega
import .ch11_imp
open imp
/-
Open Scope imp_scope.
Fixpoint ceval_step2 (st : state) (c : com) (i : nat) : state :=
match i with
| O ⇒ empty_st
| S i' ⇒
match c with
| SKIP ⇒
st
| l ::= a1 ⇒
(l !-> aeval st a1 ; st)
| c1 ;; c2 ⇒
... | {
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/-
Copyright (c) 2022 Damiano Testa. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Damiano Testa
-/
import data.polynomial.algebra_map
import ring_theory.localization.basic
/-! # Laurent polynomials
We introduce Laurent polynomials over a semiring `R`. Mathematic... | {
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from collections import OrderedDict
from enum import Enum, unique
import numpy as np
from typing import Dict, Union, Iterator, Type, Tuple
from meio.gsm.dag_gsm import GuaranteedServiceModelDAG
from meio.gsm.tree_gsm import Stage, GuaranteedServiceModelTree, GuaranteedServiceModel
def create_supply_chain_network_fro... | {
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[STATEMENT]
lemma eventually_nhds_top:
fixes P :: "'a :: {order_top,linorder_topology} \<Rightarrow> bool"
and b :: 'a
assumes "b < top"
shows "eventually P (nhds top) \<longleftrightarrow> (\<exists>b<top. (\<forall>z. b < z \<longrightarrow> P z))"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. eventuall... | {
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import numpy as np
import pytest
from sklearn.utils._readonly_array_wrapper import ReadonlyArrayWrapper, _test_sum
from sklearn.utils._testing import create_memmap_backed_data
def _readonly_array_copy(x):
"""Return a copy of x with flag writeable set to False."""
y = x.copy()
y.flags["WRITEABLE"] = Fals... | {
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module Variables
include("./constants.jl")
using JuMP
using .Constants
export init_variables
function init_variables(m)
#Dimensions of box
@variable(m, lob_length_of_box[i=1:length(boxes)] == boxes[i][1])
@variable(m, wob_width_of_box[i=1:length(boxes)] == boxes[i][2])
@variable(m, hob_height_of... | {
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"""
json 불러와서 캡션 붙이는 것
"""
import json
import pandas as pd
path = './datasets/vqa/v2_OpenEnded_mscoco_train2014_questions.json'
with open(path) as question:
question = json.load(question)
# question['questions'][0]
# question['questions'][1]
# question['questions'][2]
df = pd.DataFrame(question['questions'])
d... | {
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# script to convert the newly generated Relative Humidity
def convert_to_hur( tas_arr, vap_arr ):
import numpy as np
with np.errstate( over='ignore' ):
esa_arr = 6.112 * np.exp( 17.62 * tas_arr/ (243.12 + tas_arr) )
# esa_arr = 6.112 * np.exp( 22.46 * tas_arr / (272.62 + tas_arr) )
return vap_arr/esa_arr * 100... | {
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[STATEMENT]
lemma closed_Union [continuous_intros, intro]: "finite S \<Longrightarrow> \<forall>T\<in>S. closed T \<Longrightarrow> closed (\<Union>S)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<lbrakk>finite S; \<forall>T\<in>S. closed T\<rbrakk> \<Longrightarrow> closed (\<Union> S)
[PROOF STEP]
by (induct s... | {
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subroutine qqb_ttw_v(p,msqv)
************************************************************************
* Author: R. K. Ellis *
* March, 2012. *
* ... | {
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# coding: utf-8
from scipy import stats
import numpy as np
from itertools import chain
from scipy.stats import chi2_contingency
import jpegio as jio
import collections
img = jio.read('00576.jpg')
g = img.coef_arrays[0]
g = g.reshape(g.shape[0]*g.shape[1])
for ind in range(30):
g1 = g[0.03*len(g)*i:0.03*len(g)*(... | {
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\documentclass{article}
\usepackage{bm}
\usepackage{amsmath}
\usepackage{graphicx}
\usepackage{mdwlist}
\usepackage[colorlinks=true]{hyperref}
\usepackage{geometry}
\geometry{margin=1in}
\geometry{headheight=2in}
\geometry{top=1in}
\usepackage{palatino}
\usepackage{listings}
\usepackage{color}
\definecolor{codegreen}... | {
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# -*- coding: utf-8 -*-
# Copyright (c) 2018 The HERA Collaboration
# Licensed under the MIT License
from __future__ import print_function, division, absolute_import
import numpy as np
from six.moves import range
from scipy.signal import windows
from warnings import warn
from scipy.optimize import leastsq, lsq_linear... | {
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import collections
import itertools
import numpy as np
from operator import itemgetter
from scipy.spatial import distance
import re
DEBUG = False
"""Vector stuff"""
def v_same_orientation(v1, v2):
return np.dot(v1, v2) > 0
"""Division by zero problem!"""
def v_angle(v1, v2):
length_v1 = np.linalg.norm(v... | {
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/*#ifndef MODEL_MARKET_H
#define MODEL_MARKET_H
#endif // MODEL_MARKET_H
*/
#pragma once
#include <graphene/chain/protocol/operations.hpp>
#include <graphene/db/generic_index.hpp>
#include <boost/multi_index/composite_key.hpp>
#include <vector>
namespace graphene
{
namespace chain
{
using namespace s... | {
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MODULE in_out_manager
!!======================================================================
!! *** MODULE in_out_manager ***
!! I/O manager utilities : Defines run parameters together with logical units
!!=====================================================================
... | {
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[STATEMENT]
lemma R_therm_dyn:
assumes "a > 0" and "0 \<le> \<tau>" and "0 < Tmin" and "Tmax < L"
shows "rel_R \<lceil>\<lambda>s. I Tmin Tmax s \<and> s$2 = 0 \<and> s$3 = s$1\<rceil> \<lceil>I Tmin Tmax\<rceil> \<ge>
(IF (\<lambda>s. s$4 = 0) THEN
(x\<acute>= (\<lambda>t. f a 0) & G Tmin Tmax a 0 on (\<la... | {
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import keras
import numpy as np
import os
from keras.preprocessing.image import ImageDataGenerator , array_to_img, img_to_array, load_img
from Tkinter import Tk
from tkFileDialog import askdirectory
import GetFilePathFromDir as getfdir
Tk().withdraw()
PathMana = getfdir.GetFileinDir()
datagen = ImageDataGenerator(... | {
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Require Import bedrock2.Syntax.
Require Import bedrock2.NotationsCustomEntry.
Require Import bedrock2.FE310CSemantics.
Require Import coqutil.Z.Lia.
From bedrock2 Require Import BasicC64Semantics ProgramLogic.
From bedrock2 Require Import Array Scalars Separation.
From coqutil Require Import Word.Interface Map.Interfa... | {
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import os
import numpy as np
import skimage.data
from skimage.io import imsave, imread
from skimage import transform
from skimage.color import rgb2gray
import matplotlib.pyplot as plt
img_w = 128
img_h = 128
PATH_NEW_IMGS_FOLDER = 'Resized_images'
def load_imgs():
CONDITIONS = lambda img_name: Fal... | {
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import numpy as np
import os
from scanorama import *
from scipy.sparse import vstack
from sklearn.preprocessing import LabelEncoder, scale
from experiments import *
from process import load_names
from utils import *
NAMESPACE = 'mono_macro'
METHOD = 'svd'
DIMRED = 100
data_names = [
'data/macrophage/monocytes_1'... | {
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"""-------------------------------------------------------
Licensed under The MIT License [see LICENSE for details]
Written by Kyungjun Lee
-------------------------------------------------------"""
import subprocess as sp
import numpy as np
# global variables
ACCEPTABLE_AVAILABLE_MEMORY = 10000
# https://github.com/... | {
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include("1.jl")
include("11.jl")
include("14.jl")
function mark_allzicper(r::Robot)
angleofsquare1111(r::Robot)
putmarker!(r)
snake11per(r)
if (isborder(r,Ost))
putmarkholeper(r,West)
else
putmarkholeper(r,inverse(West))
end
end
function snake11per(r::Robo... | {
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from .version import __version__
from .sr import (
pysr,
PySRRegressor,
best,
best_tex,
best_callable,
best_row,
)
from .julia_helpers import install
from .feynman_problems import Problem, FeynmanProblem
from .export_jax import sympy2jax
from .export_torch import sympy2torch
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Hills Drive is located in West Davis and leads into the parking lot for the Western Center for Agricultural Equipment. It is a Davis Isnt Flat very confused street. Image(hills.jpg, thumbnail, 500, right)
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using ZStd
using Base.Test
@testset "helpers" begin
@test typeof(ZStd.MAX_COMPRESSION) == Int
@test ZStd.MAX_COMPRESSION > 0
@test ZStd.check_zstd_error(UInt64(0)) == UInt64(0)
@test_throws ZStd.ZStdError ZStd.check_zstd_error(typemax(UInt64))
let
err = try
ZStd.check_zstd_err... | {
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#include <boost/mpl/aux_/preprocessed/dmc/equal_to.hpp>
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#!/usr/bin/python
import threading
import time
from Monsoon import HVPM
import struct
from datetime import datetime
import time
import math
from Monsoon.calibrationData import calibrationData
from Monsoon import Operations as ops
from copy import deepcopy
import numpy as np
import signal
import sys
import usb
import o... | {
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/*
* Copyright 2016 The Cartographer 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 applicable law... | {
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import numpy as np
from scipy.optimize import minimize_scalar
from astropy.modeling import models, fitting
from astropy.io import fits
from scipy.linalg import toeplitz, hankel
def kronDecomp (P,*args):
nargin = 1 + len(args)
if (nargin < 2):
print("Veuillez entrer le P et le Centre")
if (nar... | {
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import Playground.Data.BinaryTree.Basic
import Playground.Data.List.Is_Sorted
import Mathlib.Data.List.Perm
import Mathlib.Init.Algebra.Order
namespace Data.BinaryTree
section
variable {type} [LinearOrder type]
inductive IsBST : BinaryTree type → Prop
| nil : nil.IsBST
| node {value left right}
(left_IsB... | {
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\documentclass{article}
\title{Mystery Readme}
\date{\today}
\author{Paul Jones\\ Computer Architecture (01:198:211) \\ School of Arts and Sciences \\ Rutgers University}
\begin{document}
\maketitle
\section{My Process}
The way that I worked out what \texttt{mystery.s} does by first creating a \texttt{mystery.c}
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#coding:utf-8
import numpy as np
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.datasets import load_iris
import matplotlib.pyplot as plt
'''
author: heucoder
email: 812860165@qq.com
date: 2019.6.13
'''
def lda(data, target, n_dim):
'''
:param data: (n_samples, n_features)
... | {
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import numpy as np
def get_src_indices_by_row(row_idxs, shape, flat=True):
"""
Provide the src_indices when connecting a vectorized variable from an output to an input.
Indices are selected by choosing the first indices to be passed, corresponding to node
index in Dymos.
Parameters
---------... | {
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r"""
ISGCI: Information System on Graph Classes and their Inclusions
This module implements an interface to the `ISGCI <http://www.graphclasses.org/>`_ database in Sage.
This database gathers information on graph classes and their
inclusions in each other. It also contains information on the
complexity of several com... | {
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import argparse
import numpy as np
import glob
import os
import json
import sys
from tqdm import tqdm
from allennlp.commands.elmo import ElmoEmbedder
from allennlp.common.util import lazy_groups_of
from allennlp.data import vocabulary
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelp... | {
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# -*- coding: utf-8 -*-
"""
Created on Fri May 10 12:57:47 2019
@Title: FrontierLab exchange program - DBPS source code (for Bayesian Logistic Regression)
@Author: Chou I-Ping
@Reference: C. Sherlock and A. H. Thiery, “A discrete bouncy particle sampler,” 2017.
"""
import time
import numpy as np
import copy
def ess... | {
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\chapter{Reduction Recognition}
Figures~\ref{Tutorial:exampleReductionRecognition}
shows a translator which
finds the first loop of a main function and recognizes reduction operations
and variables within the loop.
A reduction recognition algorithm (\lstinline{ReductionRecognition()}) is implemented in the SageInte... | {
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# import Pkg; Pkg.add(["FiniteDifferences", "Plots"])
using Faust, FiniteDifferences, Plots
process = compile("""
import("stdfaust.lib");
process = pm.ks(pm.f2l(ba.midikey2hz(60)), 0.1);
""")
function f(x)
init!(process, block_size=size(x, 1))
process.inputs = x
compute!(process)
end
x = randn(1024, 1)
... | {
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'''
This is the unittest for pinn module
'''
import unittest
import os
import sys
module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path:
sys.path.append(module_path)
import numpy as np
import tensorflow as tf
import prep_data
import Logger
import nn
dataset = '../data/single_action_2_... | {
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#include <appbase/application.hpp>
#include "chain_state_types.hpp"
#include "state_history.hpp"
#include <abieos.h>
#include <boost/beast/core/flat_buffer.hpp>
using namespace appbase;
using boost::beast::flat_buffer;
namespace chronicle {
// Channels published by receiver_plugin
namespace channels {
usin... | {
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# _
# | |
# __ _ _ _ __ _ _ __ ___ ___ _ __ | |_ ___ _ __
# / _` | | | |/ _` | '_ ` _ \ / _ \ '_ \| __/ _ \ '__|
# | (_| | |_| | (_| | | | | | | __/ | | | || __/ |
# \__,_|\__,_|\__, |_| |_| |_|\___|_| |_|\__\___|_|
# ... | {
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#include <vsim/env/environment.hpp>
#include <vsim/env/model.hpp>
#include <vsim/env/geometry.hpp>
#include <vsim/env/node.hpp>
#include <vsim/env/pose.hpp>
#include <vsim/env/drawable.hpp>
#include <vsim/util/format.hpp>
#include <vsim/util/filesystem.hpp>
#include <vsim/util/strings.hpp>
#include <pugixml/pugixml.h... | {
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import os
import cv2
import queue
import random
import threading
import face_recognition
import numpy as np
from sklearn import svm
import joblib
q = queue.Queue()
# 加载人脸图片并进行编码
def Encode():
print("Start Encoding")
image_path = 'C:\\Users\\Administrator\\Desktop\\face_recognition-master\\examples\\knn_exam... | {
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[STATEMENT]
lemma FINITE_states:
fixes X :: "'a set"
shows "finite X \<Longrightarrow> finite {(s :: 'a state). fmdom' s = X}"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. finite X \<Longrightarrow> finite {s. fmdom' s = X}
[PROOF STEP]
proof (induction rule: finite.induct)
[PROOF STATE]
proof (state)
goal (2... | {
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//
// Copyright (c) 2017-2019 Native Instruments GmbH, Berlin
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, cop... | {
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from collections import deque
import os
import cv2
from .wrapper_base import Wrapper, ObservationWrapper
import gym
import gym.spaces as spaces
import numpy as np
os.environ.setdefault("PATH", "")
cv2.ocl.setUseOpenCL(False)
class FrameStack(Wrapper):
def __init__(self, env, k):
"""Stack k last frames."... | {
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import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
import pandas as pd
from matplotlib import pyplot as plt
def training_plot(scores, folder_name, file_name):
plt.figure(figsize=(15,5))
plt.plot(range(len(scores["train"])), scores["train"], label=f'train {file_name}')
... | {
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#%%
import os
import pickle
import time
from pathlib import Path
import colorcet as cc
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.decomposition import PCA
from sklearn.feature_selection import VarianceThreshold
from sklearn.model_selection import train_tes... | {
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# -*- coding: utf-8 -*-
#
# Author: Taylor Smith <taylor.smith@alkaline-ml.com>
#
# Provide numpy compatibility and common variables. Since this
# is a relatively sparse script, I feel I must defend this design
# choice. See the docstring in the __init__: "Each sub-module is specifically
# designed not to make calls ou... | {
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import numpy as np
import matplotlib.pyplot as plt
import time
from xdesign_ming.material import XraylibMaterial, CustomMaterial
from xdesign_ming.geometry import *
from xdesign_ming.phantom import Phantom
from xdesign_ming.propagation import *
from xdesign_ming.plot import *
from xdesign_ming.acquisition import Simul... | {
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"""
This module contains tools to help in extracting training crops
from images, where a "crop" is a relatively small rectangular ROI from
within the bounds of an image.
author: Stephen O'Hara
created: April 14, 2016
"""
import pyvision3 as pv3
import shapely.geometry as sg
import shapely.ops as so
import numpy as np
... | {
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%----------------------------------------------------------------------------
% Magic tutorial number 7
%----------------------------------------------------------------------------
\NeedsTeXFormat{LaTeX2e}[1994/12/01]
\documentclass[letterpaper,twoside,12pt]{article}
\usepackage{epsfig,times}
\setlength{\textwidth}{... | {
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\chapter{Soccer Simulation 2D}\label{chapter:ss2d}
In this chapter we explain the architecture of the Simulator itself. It is divided in 5 sections: about RoboCup Soccer Simulation Server (rcssserver), \cite{rcssserver}, explanation of the formation tactics and the formation editor, a section about the two major agents... | {
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"""
Classes for generating lists of detected events
"""
import numpy as np
from yt.funcs import issue_deprecation_warning
from pyxsim.utils import mylog
from yt.units.yt_array import YTQuantity, YTArray, uconcatenate
import astropy.io.fits as pyfits
import astropy.wcs as pywcs
import h5py
from pyxsim.utils import force... | {
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import os
import numpy as np
import cv2
import shutil
debug = False
numberToHandle = 500
def rotate(angle, center, landmark):
rad = angle * np.pi / 180.0
alpha = np.cos(rad)
beta = np.sin(rad)
M = np.zeros((2,3), dtype=np.float32)
M[0, 0] = alpha
M[0, 1] = beta
M[0, 2] = (1-alpha)*center[0... | {
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module PrimaryRecursive
# Write your package code here.
include("PRBase.jl")
include("arithmetic.jl")
export p1, p2, p3, PrimRec, succ, zro, Comb, Proj,
add, mult, pred, cosub, dff, sgn, nsgn, const1, remainder, ge,
ifel, square, floor_sqrt, traingle, pair, fib, fst, scd
end
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/-
Copyright (c) 2018 Kenny Lau. All rights reserved.
Released under Apache 2.0 license as described in the file LICENSE.
Authors: Kenny Lau, Yury Kudryashov
-/
import algebra.algebra.tower
/-!
# The `restrict_scalars` type alias
> THIS FILE IS SYNCHRONIZED WITH MATHLIB4.
> Any changes to this file require a corresp... | {
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import numpy as np
from future.cmorph import _dilate
rows = 1024
cols = 1024
srows = 64
scols = 64
image = np.random.randint(0, 255, rows * cols, dtype=np.uint8).reshape(
(rows, cols)
)
selem = np.random.randint(0, 1, srows * scols, dtype=np.uint8).reshape(
(srows, scols)
)
out = np.zeros((rows, cols), dtype=... | {
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import math
import time
import random
import numpy as np
from tqdm import tqdm, trange # 显示进度条
# 定义装饰器，监控运行时间
def timmer(func):
def wrapper(*args, **kwargs):
start_time = time.time()
res = func(*args, **kwargs)
stop_time = time.time()
print('func %s, run time: %s' % (f... | {
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# -*- coding: utf-8 -*-
"""Test for updater.ensemble module"""
import numpy as np
import datetime
from stonesoup.models.measurement.linear import LinearGaussian
from stonesoup.types.detection import Detection
from stonesoup.types.hypothesis import SingleHypothesis
from stonesoup.types.prediction import EnsembleStatePr... | {
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[STATEMENT]
lemma swing_pos_inv:"swing_pos w1 w2 \<Longrightarrow> (kauff_mat w1) = (kauff_mat w2)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. swing_pos w1 w2 \<Longrightarrow> kauff_mat w1 = kauff_mat w2
[PROOF STEP]
unfolding swing_pos_def
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. w1 = r_over_braid \<a... | {
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# rng
#random number generators
#Computers are not capable of generating true random numbers
#but can generate sequences with statistical randomness
# 1 Julia's implemented solution
rand(100)
# LCP psuedo solutions
function rng_Park_Miller1998(n;x1=3)
x=zeros(n)
x[1] = x1
u = zeros(n)
... | {
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# import itertools
import numpy as np
import matplotlib.pyplot as plt
from netCDF4 import Dataset
from postladim import ParticleFile
# ---------------
# User settings
# ---------------
# Files
particle_file = "station.nc"
# particle_file = "/home/bjorn/ladim/examples/station/station.nc"
grid_file = "../data/ocean_avg... | {
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module PyCMA
using PyCall
const cma = PyNULL()
function __init__()
copy!(cma, pyimport("cma"))
py"""
import numpy as np
"""
end
end # module
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#
# Copyright (c) 2014, Texas Water Development Board
# All rights reserved.
#
# This code is open-source. See LICENSE file for details.
#
""" View definitions for controlling layout of survey line editor task
Views are:
*BigView:
Example of use for overall layout with Controls on left and Plots on
right.
*P... | {
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// Licensed under the Apache License, Version 2.0.
// Author: Jin Qing (http://blog.csdn.net/jq0123)
// Worker command shared ptr.
#ifndef RPCZ_WORKER_CMD_PTR_HPP
#define RPCZ_WORKER_CMD_PTR_HPP
#include <boost/shared_ptr.hpp>
namespace rpcz {
namespace b2w {
struct worker_cmd;
struct handle_data_cmd;
} // namespac... | {
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"""
grd2cpt(cmd0::String="", arg1=[], kwargs...)
Make linear or histogram-equalized color palette table from grid
Full option list at [`grd2cpt`](http://gmt.soest.hawaii.edu/doc/latest/grd2cpt.html)
Parameters
----------
- **A** : **alpha** : **transparency** : -- Str --
Sets a constant level of transparency ... | {
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import numpy as np
import torch
import torch.nn.functional as F
def cutmix(images, labels, alpha=1.0, beta=1.0, num_classes=10):
"""
Apply CutMix to a batch of images.
Arguments:
image (torch.FloatTensor): images.
labels (torch.LongTensor): target labels.
alpha (float): parameter ... | {
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\chapter{Testing}
\index{testing}
Test jobs are generally contained in the source file of the
package that they are testing and are extracted using a
cradle composed of the package name appended by the letter T,
e.g. {\bf hbookt]} for HBOOK. The tests for {\bf KERNGEN}
are contained in a separate PAM file, KERNGENT.
... | {
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# coding: utf-8
import numpy as np
from scipy.sparse import diags
from functools import singledispatch
@singledispatch
def mm(n_param : int, constraint="inc", dim=0):
"""Creates the mapping matrix for the constraint P-splines as in
Fahrmeir, Regression p.436f, for the constraint.
Paramters:
--------... | {
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// Boost.Geometry (aka GGL, Generic Geometry Library)
// Copyright (c) 2007-2012 Barend Gehrels, Amsterdam, the Netherlands.
// This file was modified by Oracle on 2017.
// Modifications copyright (c) 2017 Oracle and/or its affiliates.
// Contributed and/or modified by Adam Wulkiewicz, on behalf of Oracle
// Use, m... | {
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'''
1. normalize by mean of each diagonal
- args: mat: numpy.ndarray
norm = normalizebydistance(mat)
2. calculate correlation between each column
corr = correlation(norm, method='pearson', center=True)
3. perform eigenvalue decomposition
- args: nc: number of eigenvectors returned
pc = decomposition(corr, method='eig... | {
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import os
import numpy as np
import pandas as pd
from collections import defaultdict
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
def tabulate_events(dpath):
summary_iterators = [EventAccumulator(os.path.join(dpath, dname)).Reload() for dname in os.listdir(dpath) if dname.sta... | {
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using MeshArrays, OceanStateEstimation, NetCDF
p=dirname(pathof(MeshArrays))
include(joinpath(p,"../examples/Demos.jl"))
"""
random_flow_field(;np=12,nq=18)
Set up a random flow field over a gridded domain of size np,nq
```
ϕ,u,v=random_flow_field()
```
"""
function random_flow_field(;np=12,nq=18)
Γ=simple_per... | {
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import argparse
import numpy as np
import os
import matplotlib.pyplot as plt
import matplotlib as mpl
import pandas
mpl.use('Agg')
"""IMPORTANT"""
# NOTE: this script assumes it is run in DReyeVR/Diagnostics/
assert("Diagnostics" in os.getcwd())
def plot_many_versus(data_x, data_ys, units="", name_x="X", name_y="Y",... | {
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import os
import numpy as np
import subprocess
import tempfile
from hqca.tools import *
from copy import deepcopy as copy
def purify(rdm,quantstore):
cdir = os.getcwd()
rdm.save(name=cdir+'/_temp',spin=quantstore.spin_rdm)
rdm.contract()
path_to_maple = quantstore.path_to_maple
print('Purifying 2-R... | {
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% !TeX spellcheck = en_GB
\documentclass[12pt]{beamer}
\usetheme[sectionpage=none, subsectionpage=progressbar, progressbar=foot, numbering=fraction]{metropolis}
\makeatletter
\setlength{\metropolis@frametitle@padding}{1.6ex}% <- default 2.2 ex
\setbeamertemplate{footline}{%
\begin{beamercolorbox}[wd=\textwidth, se... | {
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import matplotlib.pyplot as plt
import numpy as np
import os
def RAxisAngle(axis=[0, 1, 0], theta=0):
"""
Rotate an arbitrary point by an axis and an angle.
"""
cost = np.cos(theta)
sint = np.sin(theta)
return np.reshape(
[
cost + axis[0] * axis[0] * (1 - cost),
... | {
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import numpy as np
def KnuthSampling(total, m, left = -1):
'''
:param total: total
:param m: sample
:return:
'''
res = []
n = total
for i in range(total):
if i != left:
if np.random.random() < m / n:
res.append(i)
m -= 1
n -= 1
... | {
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Require Import Morphisms Coq.Floats.SpecFloat.
From FloatCohorts Require Import Option Arith FloatPair Cohorts Tactics.
Open Scope Z.
Section natural_normalization.
Fixpoint maximize_e' (m : positive) (e : Z) {struct m} : (positive * Z) :=
match m with
| (m'~0)%positive => maximize_e' m' (e + 1)
| _ ... | {
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from sentence_transformers import SentenceTransformer
import numpy as np
import re
from sklearn.metrics.pairwise import cosine_similarity
model = SentenceTransformer('roberta-large-nli-stsb-mean-tokens')
def get_similarity(question, target, evall):
question = re.sub('[\n\r]+', '', question)
target = re.sub('... | {
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module WaveformCommunications
using QuadGK, Statistics
export cosinepulse, halfsinepulse, rcpulse, srrcpulse, gaussianpulse,
Constellation, pam, qam, psk,
Pulse, pulseshaper, eyediag
include("pulses.jl")
include("constellations.jl")
include("utils.jl")
"""
pulseshaper(c, pulse, nsyms = 20)
Return... | {
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import pickle
import cv2
import numpy as np
from src.utils.image import crop_person_img
def load_gei(datapath, dim=None, crop_person=False, flatten=True):
with open(datapath, 'rb') as f:
data = pickle.load(f)
X = [data[idx]['sample'].astype('float64') for idx in range(len(data))]
if crop_perso... | {
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import re
from typing import Dict, List, Optional, Tuple
import numpy
import pandas
from nonbonded.library.models.datasets import DataSet, DataSetEntry
from nonbonded.library.models.projects import Benchmark
from nonbonded.library.models.results import BenchmarkResult, TargetResultType
from nonbonded.library.models.t... | {
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from matplotlib import pyplot
from ContrastBrightness import check
import unittest
import cv2
import sys
sys.path.insert(0, '../login_signup')
from detectors import age_model, gender_model, face_detect, crop
from mtcnn.mtcnn import MTCNN
import tensorflow as tf
import numpy as np
class Test(unittest.TestCase):
de... | {
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@testset "4.5.1.4 (d tan)^n (a+b sec)^m" begin
(a, b, c, d, e, f, m, n, x, ) = @variables a b c d e f m n x
#= ::Package:: =#
#= ::Title:: =#
#=Integrands*of*the*form*(d*tan(e+f*x))^n*(a+b*sec(e+f*x))^m=#
#= ::Section::Closed:: =#
#=Integrands*of*the*form*(d*tan(e+f*x))^n*(a+a*sec(e+f*x))^m=... | {
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from pandex import *
import pandas as pd
import numpy as np
import plotly_express as px
import dash_core_components as dcc
def rand_df(rows=5, cols=3, cumsum=True):
if cumsum == 'False':
return pd.DataFrame(np.random.randn(rows, cols))
return pd.DataFrame(np.random.randn(rows, cols)).cumsum()
dbaor... | {
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import numpy as np
import pandas as pd
import scipy
from sklearn import metrics
from FPMax import FPMax
from Apriori import Apriori
from MASPC import MASPC
import csv
from scipy.cluster.hierarchy import fcluster
from scipy.cluster.hierarchy import linkage
from optbinning import ContinuousOptimalBinning
# pd.set_option... | {
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using Flux
# ResidualBlock is used with `SkipConnection`
# using Parallel, first extract features, then combine them together
# separate filters
struct ResidualBlock
block
end
Flux.@functor ResidualBlock
(b::ResidualBlock)(x) = x |> b.block .|> leakyrelu
function basic_block()
layer = Chain(Conv((3, 3, 3), 1... | {
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[STATEMENT]
theorem exists_split: "(\<exists>x y. P x \<and> Q y) = ((\<exists>x. P x) \<and> (\<exists>y. Q y))"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (\<exists>x y. P x \<and> Q y) = ((\<exists>x. P x) \<and> (\<exists>y. Q y))
[PROOF STEP]
by simp | {
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//----------------------------------------------------------------------------
/// @file test_spinsort.cpp
/// @brief test program of the spinsort algorithm
///
/// @author Copyright (c) 2016 Francisco José Tapia (fjtapia@gmail.com )\n
/// Distributed under the Boost Software License, Version 1.0.\n
/// ... | {
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# coding:UTF-8
import numpy
import talib
import math
from sklearn.preprocessing import scale
from sklearn.preprocessing import minmax_scale
class ChartFeature(object):
def __init__(self, selector):
self.selector = selector
self.supported = {
"ROCP", "MACD", "RSI", "VROCP",... | {
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### Introduction to Random Variables and Statistical Distributions
```python
from scipy.stats import bernoulli, poisson, binom, norm, mvn
import numpy as np
from matplotlib import pyplot as plt
import matplotlib
%matplotlib inline
```
```python
headimg = plt.imread('../data/quarterheads.jpg')
tailimg = plt.imread('... | {
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# This file is a part of Julia. License is MIT: https://julialang.org/license
# ––––––––
# Emphasis
# ––––––––
mutable struct Italic
text
end
@trigger '*' ->
function asterisk_italic(stream::IO, md::MD)
result = parse_inline_wrapper(stream, "*")
return result === nothing ? nothing : Italic(parseinline(re... | {
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import ml_collections
from jaxdl.rl.networks.actor_nets import create_normal_dist_policy_fn
from jaxdl.rl.networks.critic_nets import create_double_critic_network_fn
def get_config():
config = ml_collections.ConfigDict()
config.algorithm = 'TD3'
config.critic_net_fn = create_double_critic_network_fn(
hidde... | {
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#include <string>
#include <sstream>
#include <map>
#include <memory>
#include <vector>
#include <gtest/gtest.h>
#include <boost/graph/adjacency_list.hpp>
#include "Alignment.hpp"
#include "AlnGraphBoost.hpp"
TEST(AlnGraphBoostTest, RawConsensus) {
std::string backbone = "ATATTAGGC";
AlnGraphBoost ag(backbone)... | {
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import numpy as np
import pandas as pd
import time
import sys
import emcee
from sklearn.model_selection import GridSearchCV
from sklearn.neighbors import KernelDensity
def get_all_bandwidths(h5_file,
thin_by=100,
data_path = '',
n_cores=8,
... | {
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import os
import numpy as np
import tempfile
import shutil
import pickle
import ntpath
import nipype.pipeline.engine as pe
import nipype.interfaces.utility as niu
from nipype.interfaces.base import (TraitedSpec, File, traits, InputMultiPath,
BaseInterface, OutputMultiPath, BaseInte... | {
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# This file was generated, do not modify it. # hide
using DelimitedFiles
using Plots
img = readdlm("/tmp/benchC.txt",',',Int)
M,N = img |> size
p=heatmap(1:N, 1:M, img, aspect_ratio=1, size=(400,400))
savefig(p, joinpath(@OUTPUT, "mandC.png")) #hide | {
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