text stringlengths 0 27.1M | meta dict |
|---|---|
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-2, 2)
plt.subplots(2, 2, sharex = True)
plt.subplot(2, 2, 1)
plt.ylabel("y")
plt.xlabel("x")
plt.yticks([1, 0, -1])
plt.plot(x, np.sin(4*x), color="red", label="sin(4x)")
plt.legend(loc = "center right")
plt.subplot(2, 2, 2)
plt.xlabel("x")
plt.yti... | {
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from flask import Flask, request, jsonify
app = Flask(__name__)
import pickle
with open('../models/digitizer.pickle', 'rb') as fd:
methods = pickle.load(fd)
scale = methods['scale']
model = methods['model']
import numpy as np
from json import loads
@app.route('/', methods=['POST'])
def index():
data = l... | {
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import requests
import json
import sys
import time
import argparse
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument('--datatransformer_provider', help='URL of the Data Transformer Provider')
#parser.add_argument('--resource_type', help='Type of resource')
parser.add_argument('--num_test', help=... | {
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[STATEMENT]
lemma preal_add_less_cancel_left [simp]: "(t + (r::preal) < t + s) \<longleftrightarrow> (r < s)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (t + r < t + s) = (r < s)
[PROOF STEP]
by (blast intro: preal_add_less2_mono2 preal_add_left_less_cancel) | {
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\chapter{Overview}
\noindent
\CmdStan is the command-line interface for Stan. The next two
chapters describe tools that are built as part of \CmdStan
installation: \code{stanc} and \code{stansummary}. The process of building a
\CmdStan executable from a Stan program is as follows:
%
\begin{enumerate}
\item A Stan pr... | {
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# Copyright 2019 AIST
#
# 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, softwar... | {
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```python
import sympy as sp
```
```python
s = sp.Symbol('s')
```
```python
V = sp.Symbol('V')
```
```python
top = (2*V*s)*(1/s+2*s/(4*s**2+1)) - 0
```
```python
bottom = (1/s+(6*s+3)/(3*s+1))*(1/s+2*s/(4*s**2+1)) - (1/s)**2
```
```python
sp.simplify(top/bottom)
```
2*V*s*(18*s**3 + 6*s**2 + 3*s + 1)/... | {
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import os, argparse, torch, time
import torch.optim as optim
import torchvision.models as models
import torch.nn.functional as F
import torch.nn as nn
import torch.utils.data as torchdata
import numpy as np
import torch.backends.cudnn as cudnn
from torch.utils.data import DataLoader
import torchvision.transforms as tra... | {
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# -*- coding: UTF-8 -*-
import numpy as np
import math
from faceemo.utils import FACIAL_LANDMARKS_68_IDXS
def _distance_x(l1, l2):
return (l2[0] - l1[0])
def _distance_y(l1, l2):
return (l2[1] - l1[1])
def _distance_allpairs_xy(landmarks):
allpairsX = []
allpairsY = []
for i in range(len(land... | {
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#include <iostream>
#include <functional>
#include <armadillo>
#include <string>
// include code from b.cc (except main function)
#define NO_MAIN
#include "b.cc"
#undef NO_MAIN
using namespace std;
using namespace arma;
const std::string CHECK_MARK = "✓";
const std::string BALLOT_X = "✗";
struct test { std::functio... | {
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from sklearn.utils.class_weight import compute_class_weight
from sklearn import metrics as skmetrics
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import inspect
def calc_metrics(metrics: list,
y_true: np.array,
y_pred: np.array or None = None,
... | {
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\chapter{Conclusion}
Conclusion
| {
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MODULE grid
! Based on grid of femswe, with additional variables of other files
IMPLICIT NONE
! COUNTING
! Number of grids in multigrid hierarchy
INTEGER :: ngrids
! nface Number of faces on each grid
! nedge Number of edges on each grid
! nvert Number of vertices on each edge
INTEGER, ALLOCA... | {
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#include <stdio.h>
#include <gsl/gsl_linalg.h>
double A[] =
{
-1.0, 0.0, 2.0, 1.0,
0.0, -1.0, 3.0, 2.0,
1.0, 2.0, 3.0, 0.0,
-3.0, 1.0, 4.0, 2.0
};
double y[] = { 0.0, 1.0, 2.0, 1.0 };
int main() {
gsl_matrix_view m = gsl_matrix_view_array(A, 4, 4);
gsl_vector_view b = gsl_vector_view_array(y, 4);
gsl_v... | {
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c
subroutine newtil(tilseq,ntill,iplane,oldind)
c
c on the first day of simulation and at the end of a tilage day
c the next tilage date is found
integer tilseq, ntill,iplane,oldind
include 'pmxpln.inc'
include 'pmxtil.inc'
include 'pmxtls.inc'
c
include 'cupdate.inc'
c
c ol... | {
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using Weave
nkwds = (out_path = "notebooks/", jupyter_path = "$(homedir())/.julia/conda/3/bin/jupyter", nbconvert_options = "--allow-errors")
skwds = (out_path = "sheets/", jupyter_path = "$(homedir())/.julia/conda/3/bin/jupyter", nbconvert_options = "--allow-errors")
##
# notes
##
notebook("src/Julia.jmd"; nkwds.... | {
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r"""
Bijection classes for type `A_{2n}^{(2)\dagger}`
Part of the (internal) classes which runs the bijection between rigged
configurations and KR tableaux of type `A_{2n}^{(2)\dagger}`.
AUTHORS:
- Travis Scrimshaw (2012-12-21): Initial version
TESTS::
sage: KRT = crystals.TensorProductOfKirillovReshetikhinTab... | {
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#pragma once
#include <memory>
#include <boost/serialization/access.hpp>
#include <boost/serialization/base_object.hpp>
#include "Layer.hpp"
#include "../optimizer/NeuralNetworkOptimizer.hpp"
#include "NoNeuronLayer.hpp"
namespace snn::internal
{
class MaxPooling2D final : public NoNeuronLayer
{
private:
... | {
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[STATEMENT]
lemma rGamma_complex_of_real: "rGamma (complex_of_real x) = complex_of_real (rGamma x)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. rGamma (complex_of_real x) = complex_of_real (rGamma x)
[PROOF STEP]
unfolding rGamma_real_def
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. rGamma (complex_of_real x... | {
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"""
"""
import numpy as np
from jax import random as jran
from ..utils.galmatch import calculate_indx_correspondence
def inherit_host_centric_posvel(
ran_key,
is_sat_source,
is_sat_target,
logmh_host_source,
logmh_host_target,
pos_host_source,
pos_host_target,
vel_host_source,
vel_... | {
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_make_left_env(ψ::CuMPS, k::Int) = CUDA.ones(eltype(ψ), 1, 1, k)
_make_left_env_new(ψ::CuMPS, k::Int) = CUDA.ones(eltype(ψ), 1, k)
_make_LL(ψ::CuMPS, b::Int, k::Int, d::Int) = CUDA.zeros(eltype(ψ), b, b, k, d)
_make_LL_new(ψ::CuMPS, b::Int, k::Int, d::Int) = CUDA.zeros(eltype(ψ), b, k, d)
function CuMPS(ig::MetaGraph,... | {
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%\input{/Users/joshyv/Research/misc/latex_paper.tex}
\documentclass{article}
\usepackage{amsmath}
\usepackage{graphicx}
\usepackage{amsfonts}
\usepackage{amssymb}
\usepackage{amsthm}
%\usepackage{cite}
\usepackage{algorithm}
\usepackage{algorithmic}
% \usepackage{times}
\usepackage{fancyhdr}
\usepackage{graphicx}
\usep... | {
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import numpy as np
from examples.example_utils import make_chainer_a3c
from dacbench.benchmarks import CMAESBenchmark
# Helper method to flatten observation space
def flatten(li):
return [value for sublist in li for value in sublist]
# Make CMA-ES environment
# We use the configuration from the "Learning to O... | {
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#!/usr/bin/env python
from __future__ import print_function
import gzip
import os
import pickle
import time
import gym
import numpy as np
from util import DATA_DIR, DATA_FILE
def key_press(key, mod):
global human_agent_action, human_wants_restart, human_wants_exit, human_sets_pause, acceleration
if key == ... | {
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""" Bifurcation point classes. Each class locates and processes bifurcation points.
* _BranchPointFold is a version based on BranchPoint location algorithms
* BranchPoint: Branch process is broken (can't find alternate branch -- see MATCONT notes)
Drew LaMar, March 2006
"""
from __future__ import absolu... | {
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import networkx as nx
from cStringIO import StringIO
from Bio import Phylo
import matplotlib.pyplot as plt
import random
import logging
from tqdm import tqdm
logger = logging.getLogger()
logger.setLevel(logging.INFO)
import numpy as np
import trees
from trees.ddt import DirichletDiffusionTree, Inverse, GaussianLikeliho... | {
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[STATEMENT]
lemma singular_simplex_empty:
"topspace X = {} \<Longrightarrow> \<not> singular_simplex p X f"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. topspace X = {} \<Longrightarrow> \<not> singular_simplex p X f
[PROOF STEP]
by (simp add: singular_simplex_def continuous_map nonempty_standard_simplex) | {
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'''
This file contains my implementation of the method to determine
Stain Vector using SVD as outlined in the following paper:-
Macenko, Marc, et al. "A method for normalizing histology slides for quantitative analysis."
Biomedical Imaging: From Nano to Macro, 2009.
ISBI'09. IEEE International Symposium on. IEEE, 2009.... | {
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library(ggplot2)
library(dplyr)
library(shiny)
library(lubridate)
library(stringr)
library(gridExtra)
library(RCurl)
library(scales)
shinyServer(function(input, output) {
########LOAD SONAR#######
load("data/sonar.rda")
########GET REALTIME#####
load("data/rt_dat.rda")
########TEST FISH########
load("d... | {
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using Test
using Plots
function test_backwardpass_sqrt!(res::SolverIterResults,solver::Solver,bp::BackwardPass)
# Get problem sizes
res = results2
n,m,N = get_sizes(solver)
m̄,mm = get_num_controls(solver)
n̄,nn = get_num_states(solver)
# Objective
costfun = solver.obj.cost
dt = solver... | {
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# Cython compile instructions
from setuptools import setup
from setuptools import Extension, find_packages
import numpy
import os
import glob
from sys import platform
import sys
import sysconfig
# py_modules = ['alphaimpute2']
# py_modules += [os.path.join('src','General', 'InputOutput')]
# py_modules += [os.path.jo... | {
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/*
Copyright (c) 2014, Project OSRM contributors
All rights reserved.
Redistribution and use in source and binary forms, with or without modification,
are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list
of conditions and the f... | {
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#!/bin/python
import numpy as np
def binary_step(x):
return np.where(x < 0, 0, 1)
def binary_step_(x):
return np.where(x != 0, 0, np.inf)
def linear(x, a=1):
return a * x
def linear_(x, a=1):
return a
def sigmoid(x):
return 1 / (1 + np.exp(-x))
def sigmoid_(x):
return sigmoid(x) * (1-... | {
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"""sfh dataset."""
import os
import glob
from astropy.table import Table, vstack
import tensorflow as tf
import tensorflow_datasets as tfds
import numpy as np
# TODO(sfh): Markdown description that will appear on the catalog page.
_DESCRIPTION = """
# SFH Dataset
Dataset for generative models. Data is extracted fr... | {
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import train_synth.config as config
from src.utils.data_manipulation import generate_target_others, denormalize_mean_variance
from train_synth.dataloader import DataLoaderEval
from src.utils.parallel import DataParallelModel
from src.utils.utils import generate_word_bbox, get_weighted_character_target, calculate_fscore... | {
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Address(Decatur Court) is a residential Culdesacs culdesac in South Davis.
Intersecting Streets
Concord Avenue
| {
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# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# 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 applica... | {
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import numpy as np
import tensorflow as tf
from sklearn.neighbors import NearestNeighbors
import matplotlib.pyplot as plt
from keras.preprocessing.image import load_img, img_to_array
from keras.applications.vgg16 import preprocess_input
def cosim(x,y):
# a=np.sum(x*y.T)
# b=np.sqrt(np.sum(x*x.T))*np.sqrt(np.s... | {
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#! /usr/bin/python3
TCP_IP = "localhost"
TCP_PORT = 6100
from pyspark import SparkContext
from pyspark.sql.session import SparkSession
from pyspark.streaming import StreamingContext
from sparknlp.annotator import *
from sparknlp.base import *
import json
from pyspark.sql.functions import *
from pyspark.sql.types impo... | {
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# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
import sys
import os
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(BASE_DIR)
ROOT_DIR = os.path.di... | {
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#include "InetAddress.h"
#include <strings.h> // bzero
#include <netinet/in.h>
#include <arpa/inet.h>
#include <boost/static_assert.hpp>
using namespace Reactor;
static const in_addr_t kInaddrAny = INADDR_ANY;
InetAddress::InetAddress(uint16_t port)
{
bzero(&addr_, sizeof addr_);
addr_.sin_family = AF_INET;
... | {
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import mediapipe as mp
import cv2
import numpy as np
import uuid
import os
mp_drawing = mp.solutions.drawing_utils
mp_hands = mp.solutions.hands
cap = cv2.VideoCapture(0)
with mp_hands.Hands(min_detection_confidence=0.8, min_tracking_confidence=0.5) as hands:
while cap.isOpened():
ret, frame = cap.read()
... | {
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import numpy as np
import subprocess, sys, os.path
from itertools import *
import pandas as pd
import logging
from .pstreader import PstReader
def _default_empty_creator(count):
return np.empty([count or 0, 0],dtype=str)
def _default_empty_creator_val(row_count,col_count):
return np.empty([row_count,col_coun... | {
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# -*- coding: utf-8 -*-
#
#
# This source file is part of the FabSim software toolkit, which is
# distributed under the BSD 3-Clause license.
# Please refer to LICENSE for detailed information regarding the
# licensing.
#
# fab.py contains general-purpose FabSim routines.
import threading
import base.AsyncThreadingPool... | {
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(* *********************************************************************)
(* *)
(* The Compcert verified compiler *)
(* *)
(* Xavier Leroy... | {
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[STATEMENT]
lemma normal_ordinal_rec:
assumes s: "\<forall>p x. x < s p x"
shows "normal (ordinal_rec z s)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. normal (ordinal_rec z s)
[PROOF STEP]
apply (rule normalI)
[PROOF STATE]
proof (prove)
goal (2 subgoals):
1. \<And>f. OrdinalInduct.strict_mono f \<Longrightarro... | {
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import cv2 as cv
import numpy as np
import Module as m
import time
import dlib
# variables
COUNTER = 0
TOTAL_BLINK = 0
fonts = cv.FONT_HERSHEY_PLAIN
frameCounter = 0
capID = 0
EyesClosedFrame = 3
# objects
camera = cv.VideoCapture(capID)
# Define the codec and create VideoWriter object
fourcc = cv.VideoWriter_fourcc(... | {
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@testset "Appender Error" begin
db = DBInterface.connect(DuckDB.DB)
con = DBInterface.connect(db)
@test_throws DuckDB.QueryException DuckDB.Appender(db, "nonexistanttable")
@test_throws DuckDB.QueryException DuckDB.Appender(con, "t")
end
@testset "Appender Usage" begin
db = DBInterface.connect(Du... | {
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from __future__ import print_function, division
import numpy as np
import os
import cv2
from PIL import Image
import random
from functools import partial
import tensorflow as tf
from keras.models import Model, Sequential, load_model
from keras.layers.merge import _Merge
from keras.layers import Input, Conv2D, MaxPooli... | {
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import numpy as np
import pandas as pd
import argparse
import os
from pandas.tseries.holiday import USFederalHolidayCalendar as calendar
def prepare_data(data_path):
"""Returns dataframe with features."""
# Get data
df = pd.read_csv(data_path)
# Remove NaNs
df = df.dropna()
# Convert date ... | {
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Load LFindLoad.
Load LFindLoad.
From adtind Require Import goal80.
From lfind Require Import LFind.
Lemma lfind_state (y:lst):@eq lst y (append y Nil).
Admitted.
From QuickChick Require Import QuickChick.
QCInclude "/home/yousef/lemmafinder/benchmark/_lfind_clam_lf_goal80_theorem0_58_append_nil/".
QCInclude ".".
Extr... | {
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import copy
import os
import numpy as np
import random
import shutil
import sys
from src import trainer
from keras import backend as K
import tensorflow as tf
import argparse
from src.Logger import LOG
from keras.layers import Input,concatenate,GaussianNoise
from keras.models import load_model,Model
import shutil
os.en... | {
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##############written by fbb june 2011#####
########utility to bin and tophat smooth arrays of data.
########june 29 2011 so far it only works with oned array (e.g lighcurves!)
##########################################################################
#function: onedsmooth
# INPUT:
# arr: the imput array numpy a... | {
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'''
Brian Harder
5/24/2021
Description: This is a Python module that has 6 functions that I thought would be useful in my own life as a Choate student. There is are 6 math help functions, 2 standardized test simulation functions, a
function for stock prices, a fortunte teller game, a function for walking time bet... | {
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import matplotlib.pyplot as plt
from matplotlib import colors, gridspec
import matplotlib.ticker as mtick
from oas_erf.util.naming_conventions.var_info import get_fancy_var_name, get_fancy_unit_xr
from oas_erf.util.plot.plot_levlat import plot_levlat_diff, get_cbar_label, plot_levlat_abs, frelative, fdifference, \
... | {
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import os
import logging
import json
import genutil
import cdat_info
import cdutil
import MV2
import cdms2
import hashlib
import numpy
from collections import OrderedDict, Mapping
import pcmdi_metrics
import cdp.cdp_io
from pcmdi_metrics import LOG_LEVEL
import copy
import re
value = 0
cdms2.setNetcdfShuffleFlag(valu... | {
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import glob
import logging
import numpy as np
import os
import shlex
import shutil
import subprocess
import sys
from NPFitProduction.NPFitProduction.cross_sections import CrossSectionScan
from NPFit.NPFit.parameters import conversion
def annotate(args, config):
"""Annotate the output directory with a README
... | {
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Every Friday afternoon the Davis Korean Church offers bags of produce to the community for a $1 donation. The produce is seasonal, but may include corn, potatoes, tomatoes, yams, etc. These are standard grocerysize bags, onethird filled (about 10 pounds), and they all have the same items. Cant beat the living cheaply ... | {
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"include": null,
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"""
Andrin Jenal, 2017
ETH Zurich
"""
import os
import h5py
from zipfile import ZipFile
import numpy as np
from scipy import misc
class CelebDataset:
def __init__(self, dataset_destination_dir, image_size=64, channels=1):
self.dataset_dir = dataset_destination_dir
self.image_size = image_size
... | {
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import os
import sys
import logging
import time
import argparse
import numpy as np
from collections import OrderedDict
import options.options as option
import utils.util as util
from data.util import bgr2ycbcr, ImageSplitter, patchify_tensor, recompose_tensor
from data import create_dataset, create_dataloader
from mod... | {
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[STATEMENT]
lemma map_inv_map_inv [simp]:
assumes "inj_on f (dom f)"
shows "map_inv (map_inv f) = f"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. map_inv (map_inv f) = f
[PROOF STEP]
proof -
[PROOF STATE]
proof (state)
goal (1 subgoal):
1. map_inv (map_inv f) = f
[PROOF STEP]
from assms
[PROOF STATE]
proof (c... | {
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using CLBLAS
const clblas = CLBLAS
import OpenCL
using OpenCL: cl
function testDirectCall()
device, ctx, queue = clblas.get_next_compute_context()
A = rand(Float32, 1)
B = rand(Float32, 1)
C = rand(Float32, 1)
println(A, B, C)
a = cl.cl_float(6.6)
b = cl.cl_floa... | {
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import os, urllib
import mxnet as mx
import cv2
import numpy as np
import sys
def download(url,prefix=''):
filename = prefix+url.split("/")[-1]
if not os.path.exists(filename):
urllib.urlretrieve(url, filename)
def get_image(url, show=False):
filename = url.split("/")[-1]
urllib.urlretrieve(u... | {
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*DECK DBI
DOUBLE PRECISION FUNCTION DBI (X)
C***BEGIN PROLOGUE DBI
C***PURPOSE Evaluate the Bairy function (the Airy function of the
C second kind).
C***LIBRARY SLATEC (FNLIB)
C***CATEGORY C10D
C***TYPE DOUBLE PRECISION (BI-S, DBI-D)
C***KEYWORDS BAIRY FUNCTION, FNLIB, SPECIAL FUNCTIONS
C***... | {
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"""
==================
Animate Trajectory
==================
Animates a trajectory.
"""
print(__doc__)
import numpy as np
import pytransform3d.visualizer as pv
from pytransform3d.rotations import matrix_from_angle, R_id
from pytransform3d.transformations import transform_from, concat
def update_trajectory(step, n_... | {
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# Author: Igor Andreoni
# email: andreoni@caltech.edu
import glob
from astropy.io import fits
import numpy as np
import matplotlib.pyplot as plt
def str2bool(v):
if v.lower() in ('yes', 'true', 't', 'y', '1', 'Yes', 'True'):
return True
elif v.lower() in ('no', 'false', 'f', 'n', '0', 'No', 'False')... | {
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"""Methods for testing the subroutines in the grouptheory module."""
import unittest as ut
from phenum.grouptheory import ArrowPerm, RotPermList, OpList
import pytest
import numpy as np
gpath = "tests/grouptheory/"
def _read_fixOp_1D(fname):
import os
i = 1
growing = True
out = []
while growing:
... | {
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MODULE GreyVariables
!-----------------------------------------------------------------------
!
! File: GreyVariables
! Module: GreyVariables
! Type: Module
! Author: R. Chu, Dept of Physics, UTK
!
! Date: 8/21/16
!
! Purpose:
! Subroutines needed for GreyMomen... | {
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\chapter{Constructing an formula}
\label{chapter:constructingaformula}
The class \formulaClass represents SMT formulas, which are
defined according to the following abstract grammar
\[
\begin{array}{rccccccccccccc}
p &\quad ::=\quad & a & | & b & | & x & | & (p + p) & | & (p \cdot p) & | & (p^e) \\
v &\quad ::=\qu... | {
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# -*- coding: utf-8 -*-
"""
Created on Thu Dec 19 10:59:27 2019
@author: ykrempp
"""
import cv2
import numpy as np
from matplotlib import pyplot as plt
img_path = 'images\qupath_image.tif'
img = cv2.imread(img_path, 0)
scale_percent = 25 # percent of original size
width = int(img.shape[1] *... | {
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theory GabrielaLimonta2
imports Main "Repeat_Big_Step" "~~/src/HOL/IMP/Star"
begin
subsection "List setup"
text {*
In the following, we use the length of lists as integers
instead of natural numbers. Instead of converting @{typ nat}
to @{typ int} explicitly, we tell Isabelle to coerce @{typ nat}
automatical... | {
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed May 6 08:19:34 2020
@author: firo
"""
import sys
import argparse
import numpy as np
import networkx as nx
from joblib import Parallel, delayed
from wickingpnm.model import PNM
from wickingpnm.simulation import Simulation, Material
if __name__ == '_... | {
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[STATEMENT]
lemma remove_shadow_root_get_child_nodes_is_l_remove_shadow_root_get_child_nodes [instances]:
"l_remove_shadow_root_get_child_nodes get_child_nodes_locs remove_shadow_root_locs"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. l_remove_shadow_root_get_child_nodes Shadow_DOM.get_child_nodes_locs remove_sh... | {
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import random
import time
import os
import numpy as np
from . import preprocess
import torch
import torch.nn.functional as F
from torchvision.transforms.functional import hflip
import torch.utils.data as data
from PIL import Image
from scipy import sparse
from dsgn.utils.numpy_utils import *
from dsgn.utils.numba_ut... | {
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# src: https://github.com/facebookresearch/DrQA/blob/master/drqa/reader/data.py
import numpy as np
from torch.utils.data import Dataset
from torch.utils.data.sampler import Sampler
from .vector import vectorize
# ------------------------------------------------------------------------------
# PyTorch datase... | {
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cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
c Write res to IBIS file (out=res)
subroutine write_res(res,ids)
implicit none
c Inputs...
real res(2,202) !reseau locations
integer*4 ids(5) !frame,camera,filter,year,day
integer runit,ibis !VICAR and IBIS unit ... | {
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import pytest
import numpy as np
from scipy.special import zeta
from scipy.optimize import fsolve
from scipy.constants import speed_of_light
from options_tails.PowerLaw import PowerLaw
__author__ = "JNSFilipe"
__copyright__ = "JNSFilipe"
__license__ = "mit"
def test_PowerLaw():
## Create a Normal Random Distrib... | {
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module Mandrill
using Requests
using JSON
using Compat
if VERSION < v"0.4.0"
Base.split(str, spl; limit=0, keep=true) = split(str, spl, limit, keep)
end
global const api = "https://mandrillapp.com/api/1.0"
# package code goes here
function __init__()
global mandrill_key = get(ENV, "MANDRILL_KEY", "")
end
function... | {
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import numpy
from coopihc.inference.GoalInferenceWithUserPolicyGiven import (
GoalInferenceWithUserPolicyGiven,
)
from coopihc.policy.ELLDiscretePolicy import ELLDiscretePolicy
from coopihc.base.State import State
from coopihc.base.elements import discrete_array_element, array_element
# ----- needed before testing... | {
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# Adapted from https://github.com/sniklaus/pytorch-pwc/blob/master/run.py
import math
import os
import sys
import tempfile
import numpy as np
import torch
import sys
from tqdm import tqdm
arguments_strModel = 'default'
##########################################################
Backward_tensorGrid = {}
Backward_t... | {
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# import libraries
import pandas as pd
import numpy as np
from sqlalchemy import create_engine
from nltk.tokenize import word_tokenize
from nltk.stem import WordNetLemmatizer
import nltk
import pickle
from joblib import dump, load
nltk.download('punkt')
nltk.download('wordnet')
nltk.download('omw-1.4')
from sklearn.m... | {
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! @expect error
subroutine addfive(x)
implicit none
integer, intent(inout) :: x
x = x + 5
end subroutine addfive
program main
use smack
implicit none
integer :: x = 2
call addfive(x)
!print *, x == 7
call assert(x /= 7)
end program main
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import pandas as pd
import numpy as np
import gresearch_crypto
import xgboost as xgb
import traceback
import datetime
TRAIN_CSV = '/kaggle/input/g-research-crypto-forecasting/train.csv'
ASSET_DETAILS_CSV = '/kaggle/input/g-research-crypto-forecasting/asset_details.csv'
df = pd.read_csv(TRAIN_CSV)
df_asset_details = p... | {
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# Copyright 2016 James Hensman, Valentine Svensson, alexggmatthews, Mark van der Wilk
#
# 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... | {
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\documentclass[12pt]{article}
\newlength{\blackoutwidth}
\newcommand{\blackout}[1]
{%necessary comment
\settowidth{\blackoutwidth}{#1}%necessary comment
\rule[-0.3em]{\blackoutwidth}{1.125em}%necessary comment
}
\PassOptionsToPackage{usenames,dvipsnames}{xcolor}
\PassOptionsToPackage{colorlinks,linktoc=all}{hyper... | {
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[STATEMENT]
lemma solve_depressed_quartic_complex: "x \<in> set (solve_depressed_quartic_complex p q r)
\<longleftrightarrow> (x^4 + p * x^2 + q * x + r = 0)"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. (x \<in> set (solve_depressed_quartic_complex p q r)) = (x ^ 4 + p * x\<^sup>2 + q * x + r = 0)
[PROOF STEP]... | {
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... |
import pandas as pd
import numpy as np
def df_info(df: pd.DataFrame, return_info=False, shape=True, cols=True, info_prefix=''):
""" Print a string to describe a df.
"""
info = info_prefix
if shape:
info = f'{info}Shape = {df.shape}'
if cols:
info = f'{info} , Cols = {df.columns.tol... | {
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\subsection{Implementing Small DB File IO in C} % (fold)
\label{sub:implementing_small_db_file_io_in_c}
\sref{sec:using_input_and_output} presented an altered version of the Small DB program from \cref{cha:dynamic_memory_allocation}. The changes introduced four new procedures used to save the programs data to file, an... | {
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import numpy as np
from modules.image_processor import ImageProcessor
from time import time,sleep
import random
import sys
sys.path.append(r"./sign_lane")
import sign as SN
import lane
import math
import cv2
import bird
from collections import Counter
# escape obstacle
OBSTACLE_RATIO = 2
CROSS_ANGLE = False
# fork ... | {
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SUBROUTINE CloseVariables
! By Allan P. Engsig-Karup.
USE GlobalVariables
USE MGlevels
IMPLICIT NONE
DEALLOCATE(Wavefield%E,Wavefield%W,Wavefield%P,FineGrid%h,tmp2D)
IF (FineGrid%Nx>1) THEN
DEALLOCATE(Wavefield%Ex,Wavefield%Exx,Wavefield%Px)
DEALLOCATE(FineGrid%hx,FineGrid%hxx)
! DEALLOCATE(FineGrid%DiffStencils%Sten... | {
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import open3d as o3d
import argparse
import os
import sys
import logging
import numpy
import numpy as np
import torch
import torch.utils.data
import torchvision
from torch.utils.data import DataLoader
from tqdm import tqdm
from sklearn.neighbors import NearestNeighbors
from scipy.spatial.distance import minkowski
impor... | {
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#!/usr/bin/env python
'''
File name: fetch_and_transform_data.py
Author: Varun Jampani
'''
# ---------------------------------------------------------------------------
# Video Propagation Networks
#----------------------------------------------------------------------------
# Copyright 2017 Max Planck Societ... | {
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SUBROUTINE W3FI82 (IFLD,FVAL1,FDIFF1,NPTS)
C$$$ SUBPROGRAM DOCUMENTATION BLOCK
C . . . .
C SUBPROGRAM: W3FI82 CONVERT TO SECOND DIFF ARRAY
C PRGMMR: CAVANAUGH ORG: NMC421 DATE:93-08-18
C
C ABSTRACT: ACCEPT AN INPUT ARRAY, CONVERT ... | {
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[STATEMENT]
lemma hRe_add: "\<And>x y. hRe (x + y) = hRe x + hRe y"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. \<And>x y. hRe (x + y) = hRe x + hRe y
[PROOF STEP]
by transfer simp | {
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[STATEMENT]
lemma pvar_trans_eval:
assumes "a \<in> carrier R"
assumes "b \<in> carrier (R\<^bsup>n\<^esup>)"
assumes "i < n"
shows "eval_at_point R b (pvar_trans n i a) = (b!i) \<ominus> a"
[PROOF STATE]
proof (prove)
goal (1 subgoal):
1. eval_at_point R b (pvar_trans n i a) = b ! i \<ominus> a
[PROOF STEP]
p... | {
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# -*- coding: utf-8 -*-
"""This example script demonstrates plotting echograms using fake data."""
import numpy as np
from matplotlib.pyplot import figure, show
from echolab2.processing import processed_data, line
from echolab2.plotting.matplotlib import echogram
test_data_pings = 100
test_data_samples = 1000
sample... | {
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#include <boost/spirit/home/classic/actor/swap_actor.hpp>
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using ..SymEngine
using ..SymEngine: @vars, Basic
export @vars, Basic, subs
include("register.jl")
include("instruct.jl")
include("blocks.jl")
include("patch.jl")
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function out = sampleInSeconds(stimList,ISI,varargin)
% out = sampleInSeconds(stimList,ISI,varargin)
% input: stimList, output: stimlist sampled in .1 seconds
% OR sampled at your specified frequency
scale = ceil(ISI*10);
if nargin > 2
scale = round(ISI/varargin{1});
end
numstim = size(s... | {
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Describe Users/kmitchell here.
Hi. Im nice, and I dont really know how to use this thing. YAY!
20080715 13:44:26 nbsp Welcome to the Wiki Howdy, Mr. or Ms. Mitchell, and Welcome to the Wiki! My names Evan, pleased to meet you. Everybody starts off not knowing how to use this thing, but being nice gets you plen... | {
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