content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
<reponame>timmyfaraday/MultiStateSystems.jl
################################################################################
# Copyright 2020, <NAME> #
################################################################################
# MultiStateSystems.jl ... | [
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<filename>src/graphnodefeaturization.jl
import ChemistryFeaturization: encode, encodable_elements, decode, output_shape, features
using ChemistryFeaturization.Data
using ChemistryFeaturization.ElementFeature
using DataFrames
const default_nbins = 10
"""
GraphNodeFeaturization(atom_features, codecs)
GraphNode... | [
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... | 2.604685 | 2,092 |
<filename>test/ITensorNetworks/models.jl
using ITensors
using ITensorNetworkAD
using ITensorNetworkAD.ITensorNetworks: Models
@testset "test local hamiltonian builder" begin
Nx = 2
Ny = 3
sites = siteinds("S=1/2", Ny, Nx)
H = Models.mpo(Models.Model("tfim"), sites; h=1.0)
H_local = Models.localham(Models.Mod... | [
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2... | 2.522843 | 197 |
<reponame>JuliaDiffEq/ArrayInterface.jl
using ArrayInterface
using ArrayInterfaceOffsetArrays
using OffsetArrays
using Static
using Test
A = zeros(3, 4, 5);
O = OffsetArray(A, 3, 7, 10);
Op = PermutedDimsArray(O,(3,1,2));
@test @inferred(ArrayInterface.offsets(O)) === (4, 8, 11)
@test @inferred(ArrayInterface.offsets... | [
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... | 2.549068 | 805 |
"""
Provides the [`render`](@ref) methods to write the documentation as HTML files
(`MIME"text/html"`).
# Page outline
The [`HTMLWriter`](@ref) makes use of the page outline that is determined by the
headings. It is assumed that if the very first block of a page is a level 1 heading,
then it is intended as the page t... | [
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... | 2.480597 | 9,586 |
<reponame>adelinehillier/LearnConvection
using LearnConvection
using Plots
default_modify_predictor_fn(x, 𝒟, time_index) = x
modify_pred_fns = [
default_modify_predictor_fn,
append_tke,
partial_temp_profile(1:16),
partial_temp_profile(17:32),
]
f = append_tke
problems = [
Slack("KPP"; ... | [
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25... | 2.15545 | 1,679 |
# epsxc only version
function XC_c_pw_E( Rhoe )
third = 1.0/3.0
pi34 = 0.6203504908994
rs = pi34/Rhoe^third
a = 0.031091
a1 = 0.21370
b1 = 7.5957
b2 = 3.5876
b3 = 1.6382
b4 = 0.49294
# interpolation formula
rs12 = sqrt(rs)
rs32 = rs * rs12
rs2 = rs^2
om = ... | [
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292... | 1.774809 | 262 |
<reponame>phaverty/RleVectors.jl
module TestUtils
using Test
using RLEVectors
@testset begin
# rep
@test RLEVectors.rep([4, 5, 6], each = 2) == [4, 4, 5, 5, 6, 6]
@test RLEVectors.rep([4, 5, 6], times = 2) == [4, 5, 6, 4, 5, 6]
@test RLEVectors.rep([4, 5, 6], each = 3, times = 2) ==
[4, 4, ... | [
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198... | 1.918981 | 864 |
<gh_stars>1-10
export headtohead
using DataFrames, Chain, DataFrameMacros
using Cascadia: nodeText
using TableScraper: scrape_tables
# using Infiltrator
using Tables
function headtohead(name1, name2; verbose=true)
# get the front page
front_page_url = "https://www.goratings.org/en/"
front_page = scrape_ta... | [
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... | 2.213467 | 698 |
<reponame>pitmonticone/Impute.jl
"""
KNN(; kwargs...)
Imputation using k-Nearest Neighbor algorithm.
# Keyword Arguments
* `k::Int`: number of nearest neighbors
* `dist::MinkowskiMetric`: distance metric suppports by `NearestNeighbors.jl` (Euclidean, Chebyshev, Minkowski and Cityblock)
* `threshold::AbstractFloat... | [
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... | 2.649083 | 1,308 |
<filename>examples/sprites/arrows3d.jl
using GLVisualize, GeometryTypes, Reactive, GLAbstraction
if !isdefined(:runtests)
window = glscreen()
timesignal = loop(linspace(0f0, 1f0, 360))
end
description = """
Efficiently animated 3D unicode arrow field
"""
# let the visualization rotate later on
rotation = map... | [
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... | 2.858621 | 290 |
module ControlBenchmarks
################################################################################
# Main exports from this package
#
# The individual benchmarks are exported at the top of their respective files.
################################################################################
export controlbenc... | [
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... | 4.030242 | 496 |
<filename>test/base.jl
@testset "Base Extensions" begin
bins = 0:0.1:1.0
@test nextpow2(bins) == 0:0.1:1.6
@test allequal([false]) # assume equality for length 1 arrays
@test allequal([0.00, 0, 0im])# check for equivilancy across types
end
| [
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13... | 2.525773 | 97 |
#!/usr/bin/julia
function err()
println("Usage: please input a number")
end
function even_odd(n)
if (n % 2 == 0 )
return "Even"
else
return "Odd"
end
end
try
println(even_odd(parse(Int, ARGS[1])))
catch e
err()
end
| [
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... | 2.15 | 120 |
<reponame>irhum/CUDA.jl
module APIUtils
using ..CUDA
using Libdl
# helpers that facilitate working with CUDA APIs
include("call.jl")
include("enum.jl")
end
| [
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<reponame>CiaranOMara/BigBed.jl
# BigBed Overlap
# ==============
struct OverlapIterator
reader::Reader
chromid::UInt32
chromstart::UInt32
chromend::UInt32
end
function Base.eltype(::Type{OverlapIterator})
return Record
end
function Base.IteratorSize(::Type{OverlapIterator})
return Base.SizeU... | [
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220... | 2.49955 | 1,111 |
import GreyDecision.GreyNumbers: GreyNumber
import GreyDecision.Utility: makeminmax
import GreyDecision.Electre: electre
@testset "Electre with white numbers" begin
tol = 0.00001
w = [0.110, 0.035, 0.379, 0.384, 0.002, 0.002, 0.010, 0.077]
Amat = [
100 92 10 2 80 70 95 80
8... | [
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260... | 1.946012 | 815 |
# ENV["PYCALL_JL_RUNTIME_PYTHON"] = Sys.which("python") or ''
#using PyCall
using ElectronicStructure: Atom, Geometry, MolecularSpec,
InteractionOperator, MolecularData
# using ElectronicStructurePySCF: PySCF
using QuantumOps: FermiSum
"""
qiskit_geometry_to_Geometry(geometry::Matrix)
Convert a geometry sp... | [
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... | 2.454842 | 919 |
<filename>test/GridapTests/StokesTaylorHoodTests.jl<gh_stars>0
module StokesTaylorHoodTests
using Test
using Gridap
import Gridap: ∇
using LinearAlgebra: tr, ⋅
# Using automatic differentiation
u(x) = VectorValue( x[1]^2 + 2*x[2]^2, -x[1]^2 )
p(x) = x[1] + 3*x[2]
f(x) = -Δ(u)(x) + ∇(p)(x)
g(x) = (∇⋅u)(x)
∇u(x) = ∇(u... | [
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<gh_stars>0
module LIFNeuron
export LIFStates, LIFParams, evolve, update_dc
using ...Signals
using Printf
mutable struct LIFStates{T <: AbstractFloat}
v::T
t_refractory::T
dc::T
v_equilibrium::T
end
function gen_v_eqlbrm(dc::T, tau_refractory::T, v_steady::T) where {T <: AbstractFloat}
dc * tau_re... | [
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... | 2.005489 | 1,093 |
<reponame>JuliaTagBot/SampleDistributions.jl<gh_stars>0
using Distributions
using SampleDistributions
using BenchmarkTools
d = SampleDistribution(['a', 'a', 'b', 'c'])
d2 = SampleDistribution([1, 1, 2, 3])
v = rand(Char['a', 'b', 'c', 'd'], 1000)
D = SampleDistribution(v)
| [
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<gh_stars>0
using POMDPs
using POMCPOWRAVE
using ProfileView
using POMDPModels
#=
using Gallium
breakpoint(Pkg.dir("POMCPOWRAVE", "src", "solver.jl"), 40)
=#
solver = POMCPOWRAVESolver(tree_queries=50_000,
eps=0.01,
c=10.0,
enable_action_pw=false,
... | [
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... | 1.971429 | 315 |
# Macro for checking arguments
macro check_args(K, param, cond, desc=string(cond))
quote
if !($(esc(cond)))
throw(ArgumentError(string(
$(string(K)), ": ", $(string(param)), " = ", $(esc(param)), " does not ",
"satisfy the constraint ", $(string(desc)), ".")))
... | [
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220,
220,
220,
220,
220,
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7,
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7,
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... | 2.206128 | 359 |
"""
Zeros(::Type{T}, shape...) where T
return an all-zero-elements-array of type T which has shape `shape...`
# Example
julia> Zeros(Array{Float64}, 2, 5)
2×5 Array{Float64,2}:
0.0 0.0 0.0 0.0 0.0
0.0 0.0 0.0 0.0 0.0
"""
function Zeros(::Type{T}, shape...) where T
return fill!(T(unde... | [
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22... | 2.111632 | 3,198 |
using Tools
using Documenter
DocMeta.setdocmeta!(Tools, :DocTestSetup, :(using Tools); recursive=true)
makedocs(;
modules=[Tools],
authors="KronosTheLate",
repo="https://github.com/KronosTheLate/Tools.jl/blob/{commit}{path}#{line}",
sitename="Tools.jl",
format=Documenter.HTML(;
prettyurls=... | [
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220... | 2.271318 | 258 |
# OpenCV.jl tests (demos)
#################################################################################################
export run_demo
demos = [ "CreateImage",
# "ImageConversion",
# "Thresholding",
# "LiveVideo",
# "setVideoProperties",
# "LiveVideoWithTrackbars... | [
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3... | 2.341538 | 325 |
<reponame>kdayday/SIIPExamples.jl<gh_stars>0
# # Simulations with TAMU data and [PowerSimulations.jl](https://github.com/NREL/PowerSimulations.jl)
# **Originally Contributed by**: <NAME>
# ## Introduction
# This is a basic simulation example using the [TAMU Cases](https://electricgrids.engr.tamu.edu/).
# ## Depende... | [
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... | 2.919126 | 915 |
<filename>test/options.jl
@testset "Options" begin
cbc_optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
@test_logs (:error, r"Possible values are") Model(optimizer_with_attributes(
CS.Optimizer,
"lp_optimizer" => cbc_optimizer,
"logging" => [],
"traverse_stra... | [
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49... | 2.217949 | 156 |
<filename>src/api/model_IoK8sApiBatchV1beta1CronJob.jl
# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
mutable struct IoK8sApiBatchV1beta1CronJob <: SwaggerModel
apiVersion::Any # spec type: Union{ Nothing, String } # spe... | [
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13... | 2.521495 | 1,070 |
<filename>src/fs_expansion.jl
"""
fs_expansion(x, u, v, L, T, n = i -> 2^-(1 + i/2))
Global recursion: find the value of the process on the dyadic points given by the first L Levels,
`x` is a vector containing coordinates `u`,`v` initial and final point
`T` length of the basis
`n` is the normalization function... | [
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16... | 1.89653 | 1,585 |
#=
surface_test:
- Julia version: 1.1.0
- Author: Jirik
- Date: 2019-03-19
=#
# using Revise
using Test
using Logging
using SparseArrays
using Distributed
if nprocs() == 1
addprocs(3)
end
@everywhere using LarSurf
# using Plasm
# using LinearAlgebraicRepresentation
# Lar = LinearAlgebraicRepresentation
@testset "... | [
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... | 2.419954 | 431 |
3 #run
reload("IBFS")
Sim = IBFS.Simulation()
Sim.configure()
Sim.setup() | [
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] | 2.34375 | 32 |
<filename>hysynth/pwld/julia_bridge/plot_results.jl<gh_stars>1-10
using Plots, Polyhedra
using LazySets: center, HalfSpace
include("simplify_set.jl")
include("analyze_sequence.jl")
include("sample.jl")
function create_plot(; layout=1)
return plot(aspect_ratio=1, layout=layout)
end
function plot_results(x0::Abstr... | [
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50,
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25,
... | 1.927918 | 1,859 |
# Copyright (c) 2021 <NAME>
# Copyright (c) 2000 <NAME>
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later versi... | [
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... | 2.656566 | 693 |
<filename>src/filters.jl<gh_stars>0
using DSP
"""
highlow_butterworth_filter(data,sampling_rate; low_pass=30, high_pass=1, bw_n_pole=5, offset=true)
Applies a high and low-pass filter of butterworth design (n pole 5). For altering the
threshold values for filters, change add keyword arguments low_pass for low pas... | [
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62... | 2.650924 | 974 |
struct Animal
name::String
end
sayname(a::Animal) = print("My name is $(a.name).")
mydog = Animal("Tom")
sayname(mydog)
| [
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1... | 2.54 | 50 |
<filename>test/runtests.jl
using ChainRulesCore
using FiniteDifferences
using LinearAlgebra
using Printf
using Random
using StaticArrays
using Test
# Test struct for `rand_tangent` and `difference`.
struct Foo
a::Float64
b::Int
c::Any
end
@testset "FiniteDifferences" begin
include("rand_tangent.jl")
... | [
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6208... | 2.678571 | 168 |
const USE_GPU = false
const VISUALIZE = true
const BENCHMARK = false
include("elastic_wave_3D.jl")
elastic_wave_3D(128, 10.0) | [
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... | 2.52 | 50 |
using NetworkModels
using Documenter
DocMeta.setdocmeta!(NetworkModels, :DocTestSetup, :(using NetworkModels); recursive=true)
makedocs(;
modules=[NetworkModels],
authors="<NAME>, University of Namur",
repo="https://github.com/csimal/NetworkModels.jl/blob/{commit}{path}#{line}",
sitename="NetworkModel... | [
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8,
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42... | 2.400749 | 267 |
include("./imports.jl")
@testset ExtendedTestSet "Normalize" begin
@testset ExtendedTestSet "normalize" begin
image = rand(Float32, 10, 10, 3)
means = SVector{3}(rand(Float32, 1, 1, 3))
stds = SVector{3}(rand(Float32, 1, 1, 3))
@test denormalize(normalize(copy(image), means, stds)... | [
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2... | 2.258946 | 1,537 |
using Pkg.Artifacts
import ONNXNaiveNASflux.BaseOnnx: readproto, TensorProto
import ONNXNaiveNASflux: CompGraphBuilder, extract
using Downloads
using Downloads: download
const last_dl_time = Dict()
function prepare_node_test(name, ninputs, noutputs)
ahash = get_node_artifact(name, ninputs=ninputs, noutputs=noutp... | [
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... | 2.282943 | 1,237 |
using CSV, StateSpaceModels, Plots, Dates
# Load the Nile annual flow dataset
nile = CSV.read("Nile.csv")
# Convert data to an array of Float64
flow = Float64.(nile.Flow)
# Plot the data
p1 = plot(nile.Year, flow, label = "Annual flow", legend = :topright, color = :black)
# Specify the state-space model
model = loc... | [
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7177,
286,... | 2.627389 | 314 |
function step!(x,bkhs)
nε = size(bkhs.D)[2]
ε = rand(Normal(),nε)
x .= bkhs.C*x + bkhs.D*ε
return x
end
function timeseries(bkhs,n)
m = size(bkhs.C)[1] # number of equations
x = zeros(m)
ts = zeros(n,m)
for τ in 1:n
ts[τ,:] = step!(x,bkhs)
... | [
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... | 1.570755 | 424 |
<filename>src/tierra/organism/organism.jl
using DataStructures: CircularBuffer
using SHA
mutable struct TierrianOrganism
key::UInt64
a::UInt16
b::UInt16
c::UInt16
d::UInt16
stack::CircularBuffer{UInt16}
ip::UInt16
error_flag::Bool
start_address::UInt16
length::UInt16
... | [
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... | 2.48 | 350 |
<reponame>jonathanBieler/JuliaWordsUtils.jl
using JuliaWordsUtils
using Test
tostring(s,ij) = s[ij[1]:ij[2]]
# write your own tests here
@testset "select_word_backward" begin
@test select_word_backward(3,"1234") == (1,3)
@test select_word_backward(3,"1234",true) == (1,3)
@test select_word_backward(10,"se... | [
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597... | 2.197269 | 659 |
abstract type PointTriangulationPartition{D, T} <: AbstractTriangulationPartition{D, T} end
abstract type PointTriangulationPartitionFull{D, T} <: AbstractTriangulationPartitionFull{D, T} end
abstract type MutablePointTriangulationPartition{D, T} <: AbstractMutableTriangulationPartition{D, T} end
abstract type Mutable... | [
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... | 2.892473 | 837 |
<gh_stars>0
#=
Transforms.jl:
Author: <NAME> (<EMAIL>)
Acknowledgements-
Original source -
https://github.com/fastai/fastai2/blob/master/fastai2/data/transforms.py
Original documentation-
https://github.com/fastai/fastai2/blob/master/nbs/05_data.transforms.ipynb
Helper functions for processing data and basi... | [
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13,
... | 2.545691 | 6,161 |
m = Model(GLPK.Optimizer)
@variable(m, x ≥ 0)
lista = []
push!(lista,@expression(m, x-1))
push!(lista,@expression(m, x-2))
push!(lista,@expression(m, x-3))
| [
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#!/usr/bin/env julia
using RobotOS
@rosimport geometry_msgs.msg: Point, Pose, Pose2D, PoseStamped, Vector3, Twist
@rosimport std_srvs.srv: Empty, SetBool
@rosimport nav_msgs.srv.GetPlan
@rosimport gazebo_msgs.msg: ModelState, ModelStates
@rosimport gazebo_msgs.srv: SetModelState, GetModelState, GetWorldProperties
rost... | [
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31,
495... | 2.567682 | 1,411 |
module TestEduction
using Test
using Transducers
@testset "composition" begin
ed1 = eduction(Map(sin), 1:2)
ed2 = eduction(Map(cos), ed1)
ed3 = eduction(Map(tan), ed2)
@test Transducer(ed1) === Map(sin)
@test Transducer(ed2) === opcompose(Map(sin), Map(cos))
@test Transducer(ed3) === opcompose... | [
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... | 2.28 | 250 |
<gh_stars>1-10
#### Deprecate on 0.5 (to be removed on 0.6)
function dim(d::MultivariateDistribution)
Base.depwarn("dim(d::MultivariateDistribution) is deprecated. Please use length(d).", :dim)
return length(d)
end
function binaryentropy(d::UnivariateDistribution)
Base.depwarn("binaryentropy is deprecat... | [
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... | 2.707581 | 277 |
const FIG_DIR = joinpath(WATERFALL_DIR,"fig")
# Dimensions
WIDTH = 800
HEIGHT = 400
BORDER = 10
TOP_BORDER = 20
BOTTOM_BORDER = 30
LEFT_BORDER = 70
RIGHT_BORDER = 20
SEP = 10
FONTSIZE = 18
VMAX = 22.5
VMIN = 16
# Names
const SAMPLE_COL = :Sample
const VALUE_COL = :Value
# Colors
const HEX_LOSS = parse(Luxor.Coloran... | [
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12532... | 1.978745 | 988 |
<reponame>johnnychen94/FixedPointNumbers.jl
import Base.@deprecate_binding
function floattype(::Type{T}) where {T <: Real}
Base.depwarn("""
In a future release, the fallback definition of `floattype` will throw a MethodError if it cannot return a type `<:AbstractFloat`.
See the documentation on `fl... | [
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<reponame>JuliaBinaryWrappers/GR_jll.jl<filename>src/GR_jll.jl<gh_stars>1-10
# Use baremodule to shave off a few KB from the serialized `.ji` file
baremodule GR_jll
using Base
using Base: UUID
import JLLWrappers
JLLWrappers.@generate_main_file_header("GR")
JLLWrappers.@generate_main_file("GR", UUID("d2c73de3-f751-5644... | [
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... | 2.388158 | 152 |
"""
load(fpath::String; gamma::Union{Nothing,Float64}=nothing)
Read a `.png` image from file at `fpath`. `gamma` can be used to override the automatic gamma
correction, a value of 1.0 means no gamma correction.
Returns a matrix.
The result will be an 8 bit (N0f8) image if the source bit depth is <= 8 bits, 16 bit... | [
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261... | 2.199252 | 6,153 |
<gh_stars>100-1000
name = "LLVM"
llvm_full_version = v"9.0.1+4"
libllvm_version = v"9.0.1+5"
# Include common LLVM stuff
include("../common.jl")
build_tarballs(ARGS, configure_extraction(ARGS, llvm_full_version, name, libllvm_version)...; skip_audit=true)
| [
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16... | 2.401869 | 107 |
<gh_stars>0
# (a<1) & (a>0)
# (β<1) & (β>0)
# -a+β < 0
using NLopt
using Revise
function func(x, p)
# simple linear func
x*p[1] + p[2]
end
function cost(p, xvec, actual)
# predicted
pred = func.(xvec, (p,))
# cost
sum((pred .- actual).^2)
end
function constraint1(p)
p[1] - p[2]
end
fun... | [
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5... | 2.173494 | 415 |
<reponame>jalving/ModelGraphSolvers.jl<filename>src/DualDecomposition/optimizer.jl
mutable struct DDOptimizer <: AbstractGraphOptimizer
dd_model::DDModel
end
function DDOptimizer()
end
JuMP.optimize!(graph::ModelGraph,optimizer::DDOptimizer) = dual_decomposition_solve(graph,optimizer.args...;optimizer.kwargs...)... | [
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<reponame>RvSpectML/NeidSolarScripts.jl<gh_stars>0
### A Pluto.jl notebook ###
# v0.14.5
using Markdown
using InteractiveUtils
# ╔═╡ 723b4419-4413-431a-9a2b-5a501cbd2607
begin
import Pkg;
Pkg.activate(joinpath(homedir(),"Code","RvSpectMLEcoSystem","NeidSolarScripts"))
begin
using CSV, JLD2, FileIO
using Data... | [
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... | 1.793837 | 6,393 |
# This file is a part of JuliaFEM.
# License is MIT: see https://github.com/JuliaFEM/JuliaFEM.jl/blob/master/LICENSE.md
include("vonmises.jl")
# Elasticity problems
abstract ElasticPlasticProblem <: AbstractProblem
abstract PlaneStressElasticPlasticProblem <: ElasticPlasticProblem
function get_unknown_fie... | [
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... | 1.904125 | 4,339 |
<reponame>benandow/UiRef
module disambig
export adagramDisambig
using AdaGram
GC.enable(false)
vm, dict = load_model("model/model_output_full.out");
function adagramDisambig(target_word, context)
counter = 0
maxval = 0.0
maxcnt = 0
arr = disambiguate(vm, dict, target_word, split(context))
for w in arr
coun... | [
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8,
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3440... | 2.432749 | 171 |
<reponame>maccam912/adventofcode2018<gh_stars>0
using LightGraphs, SimpleWeightedGraphs
const Y_INC = 16807
const X_INC = 48271
const DEPTH = 8103
const TARGET_X = 9
const TARGET_Y = 758
const WIDTH = TARGET_X*20
const HEIGHT = TARGET_Y+40
mutable struct Rescuer
x::Int64
y::Int64
tool::String... | [
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36928... | 1.64951 | 3,264 |
"""
# Description
Predict profile across all time steps for the true check.
- if the problem is sequential, predict profiles from start to finish without the training, using only the initial profile as the initial condition.
- if the problem is residual, predict profiles at each timestep using model-predicted ... | [
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... | 2.153261 | 4,078 |
module Testing
import ..NodalDG
using Test
@test_throws AssertionError NodalDG.Mesh1D([0, 1, 2],
[[1 2]; [2 3]; [3 4]])
@test_throws AssertionError NodalDG.Mesh1D([0, 1, 2],
[[0 1]; [1 2]])
let mesh = NodalDG.Mesh1D([0, 1, 2, 3],... | [
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2... | 1.71517 | 323 |
<gh_stars>1-10
module OutlierDetectionNeighbors
using OutlierDetectionInterface
using OutlierDetectionInterface:SCORE_UNSUPERVISED
const OD = OutlierDetectionInterface
import NearestNeighbors
const NN = NearestNeighbors
import Distances
const DI = Distances
include("utils.jl")
inc... | [
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4033... | 2.073986 | 419 |
# ---
# title: 1467. Probability of a Two Boxes Having The Same Number of Distinct Balls
# id: problem1467
# author: <NAME>
# date: 2020-10-31
# difficulty: Hard
# categories: Math, Backtracking
# link: <https://leetcode.com/problems/probability-of-a-two-boxes-having-the-same-number-of-distinct-balls/description/>
# hi... | [
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1... | 2.585593 | 1,291 |
<filename>docs/make.jl
using Documenter
using Unfold
using DocStringExtensions
using Plots
gr()
#unicodeplots()
makedocs(sitename="Unfold.jl",
root = joinpath(dirname(pathof(Unfold)), "..", "docs"),
prettyurls = get(ENV, "CI", nothing) == "true",
pages = [
"index.md",
"L... | [
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82,... | 2.149378 | 241 |
<reponame>mamta-borle/Respository_Mamta
const WEAT_WORD_SETS =
(
science_arts=(
S=("science","technology","physics","chemistry","einstein","nasa","experiment","astronomy"),
T=("poetry","art","shakespeare","dance","literature","novel","symphony","drama"),
A=("male","man","boy","brother","he","him","his","son"),
B=("fema... | [
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1404,
62,
54,
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62,
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50,
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198,
7,
198,
16801,
62,
5889,
16193,
198,
50,
28,
7203,
16801,
2430,
45503,... | 2.913907 | 453 |
@testset "Ewald Summation" begin
function test_ewald_NaCl()
lat_vecs = [1.0 0 0;
0 1.0 0;
0 0 1.0]
b_vecs = [zeros(3)]
latsize = [2, 2, 2]
lattice = Sunny.Lattice(lat_vecs, b_vecs, latsize)
sys = ChargeSystem(lattice)
sys.sites .= reshape([1, -1, -1, 1, -... | [
31,
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366,
36,
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76,
341,
1,
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62,
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1940,
62,
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2601,
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685,
16,
13,
15,
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220,
220,
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26,
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220,
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220,
220,
... | 1.943005 | 3,088 |
facts("is_square_stochastic with sparse transition") do
@fact is_square_stochastic(speye(10)) => true
@fact is_square_stochastic([ speye(10) for _ = 1:3 ]) => true
@fact is_square_stochastic([ 2*speye(10) for _ = 1:3 ]) => false
end
facts("square stochastic with Int transition") do
@fact is_square_stoc... | [
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... | 2.265577 | 979 |
using GitHub, JSON, HTTP, MbedTLS
using Dates, Test, Base64
using GitHub: Branch, name
using GitHub.Checks
include("ghtype_tests.jl")
include("event_tests.jl")
include("read_only_api_tests.jl")
include("auth_tests.jl")
@testset "SSH keygen" begin
pubkey, privkey = GitHub.genkeys(keycomment="GitHub.jl")
@test ... | [
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... | 2.619048 | 147 |
<gh_stars>1-10
#all kernel functions are normalized such that their support radius is h
@fastmath function pos(x::Float64)::Float64
return (x > 0.0 ? x : 0.0)
end
"""
spline23(h::Float64, r::Float64)::Float64
Returns ``w(r)``, the value of a 2d cubic spline ``w`` with support radius `h`.
Integrates to unity.
"... | [
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25,
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198,
197,
7783,
357,
87,
1875,... | 2.123362 | 2,748 |
<gh_stars>0
using Pkg
if lowercase(get(ENV, "CI", "false")) == "true"
if Sys.islinux()
let basepython = get(ENV, "PYTHON", "python3")
envpath = joinpath(@__DIR__, "env")
run(`virtualenv --python=$basepython $envpath`)
# python = joinpath(envpath, "Scripts", "python.exe")
python =... | [
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220,
1... | 2.123894 | 226 |
module CreateTablePermissions
import SearchLight.Migrations: create_table, column, primary_key, add_index, drop_table
function up()
create_table(:permissions) do
[
primary_key()
column(:name, :string, limit = 100)
]
end
add_index(:permissions, :name)
end
function down()
drop_table(:permi... | [
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... | 2.696 | 125 |
# LibFTD2XX.jl
#
# Library installation script based on BinaryProvider LibFoo.jl example
using Libdl
using BinaryProvider
verbose = true
prefix = joinpath(@__DIR__, "usr")
if Sys.islinux()
libnames = ["libftd2xx", "libftd2xx.1.4.4", "libftd2xx.so.1.4.8"]
products = Product[LibraryProduct(joinpath(prefix, "r... | [
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40... | 2.000592 | 1,690 |
<gh_stars>0
using Distributed
addprocs(12, exeflags="--project") # create worker processes with current project activated
@everywhere include("parallel_setup.jl")
# simulated annealing parameters
T₀ = 0.5
N = 68
Ns = 36
Nt = 10
tol = 1.0
# bounds and step length
ub = repeat([1.0, repeat([0.5, 0.5, 1.0], 3)...], 6)... | [
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31,
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7203,
1845... | 2.168755 | 1,197 |
using Documenter, SparseRegression
makedocs(
format = Documenter.HTML(),
sitename = "SparseRegression.jl",
authors = "<NAME>",
clean = true,
pages = [
"index.md",
"usage.md",
"algorithms.md"
]
)
deploydocs(
repo = "github.com/joshday/SparseRegression.jl.git",
)
| [
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366,
50,
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8081,
2234,
13,
20362,
1600,
198,
220,... | 2.134228 | 149 |
#using Pkg
#Pkg.add("Flux")
using Flux
using Flux.Tracker
# executable math
f(x) = x^2+1
# f'(x) = 2x
df(x) = gradient(f,x,nest=true)[1] # df is a tuple, [1] gets the first coordinate
df(4)
# f''(x) = 2
ddf(x) = gradient(df,x,nest=true)[1]
ddf(0)
h(x) = -cos(x)^cos(x)
# h'(x) = tan(x)cos(x)^(cos(x)+1)(log... | [
198,
198,
2,
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350,
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16,
198,
198,
... | 2.288647 | 828 |
getDays(resource,subcal) = (x->x.date[1]).(filter(day ->day.date in subcal,resource.calendar.workdays))
function buildJd(timeslots,subcal)
timeslots |> @filter(_.dayID in keys(subcal) && !_.booked)|>@groupby(_.resourceID) |>@map((d = key(_),j = unique(map(x->x.dayID,_)))) |> NDSparse
end
function buildI(timeslot... | [
198,
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7,
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11,
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4008,
198,
198,
8818,
1382,
41,
6... | 2.474189 | 1,356 |
<filename>examples/ml-100k/convert.jl
using JLD
using SparseArrays
const n_user = 943
const n_item = 1682
R = spzeros(n_user, n_item)
open("ml-100k/u.data", "r") do f
for line in eachline(f)
l = split(line, "\t")
user, item, value = parse(Int, l[1]), parse(Int, l[2]), parse(Int, l[3])
R[u... | [
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198,
9979,
299,
62,
9186,
796,
1467,
6469,
198... | 2.065217 | 184 |
<gh_stars>1-10
using Test
using POMDPTesting
using FiniteHorizonPOMDPs
using POMDPs
using POMDPModelTools
import POMDPModels: SimpleGridWorld, BabyPOMDP
import POMDPPolicies: FunctionPolicy
import POMDPSimulators: stepthrough
@testset "interface" begin
@test HorizonLength(SimpleGridWorld()) == InfiniteHorizon()
... | [
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3500,
350,
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6322,
17633,
33637,
198,
11748,
35... | 2.907895 | 152 |
#############################
## The functions in this file may currently not work for some easy edge cases like K=constant.
## Use the monomial implementation in src/triVolterraMonomialKernel.jl for those cases instead
## and reserve this for non-trivial kernels.
#############################
## triVolterraEQ1FullKer... | [
14468,
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287,
428,
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937,
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287,
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14,
28461,
16598,
353,
430,
44,
6326,
498,... | 1.875241 | 3,631 |
<filename>CairoMakie/src/precompiles.jl
function get_obs(x::Attributes, visited, obs=Set())
if x in visited; return; else; push!(visited, x); end
union!(obs, values(x))
return obs
end
function get_obs(x::Union{AbstractVector, Tuple}, visited, obs=Set())
if x in visited; return; else; push!(visit... | [
27,
34345,
29,
34,
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44,
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87,
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201,
198,
220,
220,
220,
611,
2124,
287,
8672,
26,
1441,
26,
... | 2.24659 | 953 |
using ACE, LinearAlgebra, StaticArrays
using ACE: evaluate
using ACEtb
using Random: shuffle
# this should possibly go into the main ACEtb module, or possibly into
# the hamiltonian assembly code
function eval_bond(B, Rs, Zs, z0)
r̂ = Rs[1] / norm(Rs[1])
o = Rs[1]/2
Rr = map( r_ -> (r = r_ - o; o + r - 2*dot... | [
198,
3500,
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11,
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83,
65,
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198,
2,
428,
815,
5457,
467,
656,
262,
1388,
40488,
83,
65,
8265,
11,
393,
54... | 2.000902 | 1,109 |
<reponame>UnofficialJuliaMirrorSnapshots/GeneralizedMetropolisHastings.jl-e04668b6-ddf2-5c09-b17b-50da0d2d0da2<gh_stars>0
module GeneralizedMetropolisHastings
import PDMats
import Distributions
import Sundials
import Base: ==, size, length, eltype, show, display, time, similar, copy!, copy
import Base: mean, median, ... | [
27,
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261,
480,
29,
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12,
20,
66,
2931,
12,
65,
1558,
65,
12,
1120,
6814,
... | 2.844156 | 1,001 |
# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
mutable struct ContainerServiceProperties <: SwaggerModel
provisioningState::Any # spec type: Union{ Nothing, String } # spec name: provisioningState
orchestratorProfile:... | [
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2427,
13,
628,
198,
76,
18187,
2878,
43101,
16177,
2964,
18200,
1279,
25,
2451,
7928... | 3.6901 | 1,394 |
"""
Parse MTG section
# Arguments
- `f::IOStream`: A buffered IO stream to the mtg file, *e.g.* `f = open(file, "r")`
- `classes::Array`: The class section data as returned by `parse_section!`
- `description::Array`: The description section data as returned by `parse_section!`
- `features::Array`: The features sectio... | [
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198,
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325,
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2393,
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68,
13,
70,
15885,
4600,
69,
796,
1280,
7,
7... | 2.13264 | 5,677 |
<gh_stars>0
"""
`PersistentArray{T,N}` wraps an Array{Node, N} to
provide a versioned array interface. The Node type
maintains a history of each element, so the complexity
of each operation on the PersistentArray is dependent on
the corresponding Node operation in relation to the number
of stored versions.
"""
type Per... | [
27,
456,
62,
30783,
29,
15,
198,
37811,
198,
63,
30946,
7609,
19182,
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51,
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92,
63,
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281,
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485,
257,
2196,
276,
7177,
7071,
13,
383,
19081,
2099,
198,
76,
2913,
1299,
... | 2.75644 | 1,281 |
<reponame>vnikoofard/Agents.jl<filename>src/deprecations.jl
function ContinuousSpace(
extent,
spacing;
kwargs...,
)
@warn "Giving `spacing` as a positional argument to `ContinuousSpace` is "*
"deprecated, provide it as a keyword instead."
return ContinuousSpace(extend; spacing, kwargs...)
end
... | [
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261,
480,
29,
85,
77,
12125,
1659,
446,
14,
10262,
658,
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29,
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602,
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7,
198,
220,
220,
220,
6287,
11,
198,
220,
220,
220,
31050,
26,
198,
220,... | 2.693314 | 688 |
<filename>src/JuliaInXL.jl
#Copyright (c) 2015: Julia Computing Inc. All rights reserved.
module JuliaInXL
export xldate, parse_and_eval, jlsetvar
#import Base.include_from_node1; export include_from_node1
using Reexport
@reexport using JuliaWebAPI
using Logging
using Dates
using ZMQ
global const SECONDS_PER_MINUT... | [
27,
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29,
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32457,
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22300,
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32457,
198,
198,
39344,
2124,
335,
378,
11,
21136,
62,
392,
62,... | 2.704545 | 1,100 |
<reponame>Yoshinobu-Ishizaki/StatsWithJuliaBook
using Random, Distributions, KernelDensity, Plots, LaTeXStrings; pyplot()
Random.seed!(1)
function pval(mu0,mu,sig,n)
sample = rand(Normal(mu,sig),n)
xBar = mean(sample)
s = std(sample)
tStat = (xBar-mu0) / (s/sqrt(n))
ccdf(TDist(n-1), tStat)
... | [
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261,
480,
29,
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259,
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40,
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544,
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507,
11,
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35,
6377,
11,
1345,
1747,
11,
4689,
49568,
13290,
654,
26,
12972,
29487,
3419,... | 1.976277 | 548 |
# function query(key::AbstractString, fieldname="acronym")
# rq = HTTP.request("GET", "http://api.brain-map.org/api/v2/data/SectionDataSet/query.json?criteria=products[id\$eq1],genes[$fieldname\$eq'$key']&include=genes,section_images")
# end
const planedict = Dict("coronal"=>1, "sagittal"=>2)
function query_insit... | [
2,
2163,
12405,
7,
2539,
3712,
23839,
10100,
11,
2214,
3672,
2625,
330,
1313,
4948,
4943,
198,
2,
220,
220,
220,
220,
374,
80,
796,
14626,
13,
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7203,
18851,
1600,
366,
4023,
1378,
15042,
13,
27825,
12,
8899,
13,
2398,
14,
1504... | 2.144728 | 2,978 |
<filename>src/OldModelExploration.jl
module ModelExploration
export Explore, Dim, Free
using Catlab.CategoricalAlgebra
"""
A dimension implicitly specifies a metric space of structures, (or, think of it
as a preorder if we don't care about distances) ordered by "complexity" in some
context-dependent sense. We gener... | [
27,
34345,
29,
10677,
14,
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17633,
18438,
6944,
13,
20362,
198,
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41401,
11,
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11,
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198,
198,
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5181,
23912,
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34,
2397,
12409,
2348,
29230,
628,
198,
198,
37811,
198,
32,
15793,
... | 3.331169 | 616 |
<filename>examples/bez_multi_surf.jl
# ? activate Splines
import Pkg
Pkg.activate("Splines")
using PlotlyJS
using Revise
Revise.revise()
using Splines
@info "Computing"
n, m = 8, 8
# cupula
N1 = [
cat([0:n-1 zeros(n) 4 .* sin.(range(0, stop=π, length=n))], dims=2)',
cat([zeros(m) 0:m-1 4 .* sin.(ra... | [
27,
34345,
29,
1069,
12629,
14,
1350,
89,
62,
41684,
62,
11793,
69,
13,
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198,
2,
5633,
15155,
13341,
1127,
198,
11748,
350,
10025,
198,
47,
10025,
13,
39022,
7203,
26568,
1127,
4943,
198,
198,
3500,
28114,
306,
20120,
198,
3500,... | 1.851738 | 978 |
# Portions translated from SLICOT-Reference distribution
# Copyright (c) 2002-2020 NICONET e.V.
function run_mb03wd(datfile, io=stdout)
NIN = 5
NOUT = 6
NMAX = 20
PMAX = 20
LDA1 = NMAX
LDA2 = NMAX
LDTAU = NMAX-1
LDZ1 = NMAX
LDZ2 = NMAX
LDZTA = NMAX
LDWORK = max( NMAX, NMAX + ... | [
2,
4347,
507,
14251,
422,
12419,
2149,
2394,
12,
26687,
6082,
198,
2,
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357,
66,
8,
6244,
12,
42334,
45593,
1340,
2767,
304,
13,
53,
13,
198,
8818,
1057,
62,
2022,
3070,
16993,
7,
19608,
7753,
11,
33245,
28,
19282,
448,
8,
19... | 1.75677 | 2,105 |
struct Node
x::Float64
y::Float64
id::String
end
mutable struct Way
id::String
visible::Bool
version::Int
changeset::String
timestamp::String
user::String
uid::String
nodes::Array{Node}
tags::Dict
Way() = new()
end
mutable struct Relation
id::String
visible:... | [
7249,
19081,
198,
220,
220,
220,
2124,
3712,
43879,
2414,
198,
220,
220,
220,
331,
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43879,
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198,
220,
220,
220,
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3712,
10100,
198,
437,
198,
198,
76,
18187,
2878,
6378,
198,
220,
220,
220,
4686,
3712,
10100,
198,
220,
... | 2.389163 | 203 |
<gh_stars>1-10
using LighthouseFlux
using Documenter
makedocs(; modules=[LighthouseFlux], sitename="LighthouseFlux",
authors="Beacon Biosignals and other contributors",
pages=["API Documentation" => "index.md"])
deploydocs(; repo="github.com/beacon-biosignals/LighthouseFlux.jl.git", devbranch="main"... | [
27,
456,
62,
30783,
29,
16,
12,
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3500,
406,
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37,
22564,
198,
3500,
16854,
263,
198,
198,
76,
4335,
420,
82,
7,
26,
13103,
41888,
43,
32303,
37,
22564,
4357,
1650,
12453,
2625,
43,
32303,
37,
22564,
1600,
198,
220,
2... | 2.661157 | 121 |
<gh_stars>0
function triangle_centrality1(A)
T = mul(A, A', Semirings.PLUS_TIMES[Float64], mask=A)
y = reduce(Monoids.PLUS_MONOID[Float64], T, dims=2)
k = reduce(Monoids.PLUS_MONOID[Float64], y)
return (3 * mul(A, y) - 2 * mul(T, y) .+ y) ./ k
end
function triangle_centrality2(A)
T = mul(A, A', Sem... | [
27,
456,
62,
30783,
29,
15,
198,
8818,
22950,
62,
31463,
414,
16,
7,
32,
8,
198,
220,
220,
220,
309,
796,
35971,
7,
32,
11,
317,
3256,
12449,
343,
654,
13,
6489,
2937,
62,
51,
3955,
1546,
58,
43879,
2414,
4357,
9335,
28,
32,
8... | 2.068966 | 290 |
<gh_stars>0
using LightGraphs, SimpleWeightedGraphs
function bfs_depth(input_data, start_position, go_condition, stop_condition=(x->false))
status = zeros(Int32, size(input_data)...)
queue::Array{NamedTuple{(:position, :depth),Tuple{CartesianIndex, Int32}},1} = []
if typeof(start_position) <: Tuple
start_pos... | [
27,
456,
62,
30783,
29,
15,
198,
3500,
4401,
37065,
82,
11,
17427,
25844,
276,
37065,
82,
198,
198,
8818,
275,
9501,
62,
18053,
7,
15414,
62,
7890,
11,
923,
62,
9150,
11,
467,
62,
31448,
11,
2245,
62,
31448,
16193,
87,
3784,
9562,... | 2.560193 | 623 |
import .MCMCChains: AbstractChains, ChainDataFrame, sections
using .DataFrames
export from_mcmcchains
const turing_key_map = Dict(
"acceptance_rate" => "mean_tree_accept",
"hamiltonian_energy" => "energy",
"hamiltonian_energy_error" => "energy_error",
"is_adapt" => "tune",
"max_hamiltonian_energy_... | [
11748,
764,
9655,
9655,
1925,
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25,
27741,
1925,
1299,
11,
21853,
6601,
19778,
11,
9004,
198,
3500,
764,
6601,
35439,
198,
198,
39344,
422,
62,
76,
11215,
66,
38861,
198,
198,
9979,
256,
870,
62,
2539,
62,
8899,
796,
360,
713,
7... | 2.441721 | 3,835 |
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