content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
<filename>scripts/code_replica_experiment.jl
using DrWatson, GPUAcceleratedTracking, CUDA, Tracking, GNSSSignals, StructArrays, ProgressMeter;
import Tracking: Hz, ms;
@quickactivate "GPUAcceleratedTracking"
N = 2048:32:262_144
err_rel = zeros(length(N))
@showprogress 0.5 for (idx, num_samples) in enumerate(N)
# ... | [
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<filename>src/uncore/pmu.jl
abstract type PMUType end
pmutype(::T) where {T} = error("`pmutype` not defined for arguments of type $T")
# Defaults
_unitstatus(x::PMUType, i...) = error("`unitstatus` undefined for $(typeof(x))")
_unitcontrol(x::PMUType, i...) = error("`unitcontrol` undefined for $(typeof(x))")
_counter... | [
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7... | 2.561219 | 2,001 |
# Helper functions to read Harwell-Boeing and Rutherford-Boeing data.
function decode_int_fmt(fmt :: AbstractString)
if fmt[1] == '('
fmt = uppercase(fmt[2:end-1])
end
return map(s -> isempty(s) ? 1 : parse(Int, s), split(fmt, 'I'))
end
function decode_real_fmt(fmt :: AbstractString)
fmt = join(split(fmt... | [
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7... | 2.201117 | 1,432 |
<reponame>UnofficialJuliaMirrorSnapshots/POMDPModels.jl-355abbd5-f08e-5560-ac9e-8b5f2592a0ca<filename>test/crying.jl<gh_stars>0
using Test
using POMDPModels
# using POMDPSimulators
using POMDPTesting
using POMDPs
using POMDPModelTools
using BeliefUpdaters
using Random
let
problem = BabyPOMDP()
# starve polic... | [
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6... | 2.291045 | 536 |
<reponame>darwinproject/CBIOMES-Processing.jl
# byproducts.jl
"""
StartWorkers(nwrkrs::Int)
Start workers if needed.
"""
function StartWorkers(nwrkrs::Int)
set_workers = nwrkrs
nworkers() < set_workers ? addprocs(set_workers) : nothing
nworkers()
end
"""
TaskDriver(indx,fn)
Broacast / distribute ta... | [
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198... | 1.958962 | 1,657 |
#
# Example of a medium-scale graphene calculation. Only suitable for running
# on a cluster or machine with large memory.
#src tags: long
#
using DFTK
kgrid = [12, 12, 4]
Tsmear = 0.0009500431544769484
Ecut = 15
lattice = [4.659533614391621 -2.3297668071958104 0.0;
0.0 4.035274479829987 0.0;
0... | [
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2... | 2.153846 | 364 |
<gh_stars>0
#!/usr/bin/env julia
#load path to qjulia home directory
push!(LOAD_PATH, joinpath(@__DIR__, "..", "core"))
push!(LOAD_PATH, joinpath(@__DIR__, "..", "libs/quda-routines"))
push!(LOAD_PATH, joinpath(@__DIR__, "..", "libs/scidac-routines"))
push!(LOAD_PATH, joinpath(@__DIR__, "..", "main/fields"))
import Q... | [
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11,
366,
... | 2.104389 | 4,215 |
<reponame>cscherrer/Mitosis.jl
logpdf0(x, P) = logdensity(Gaussian{(:Σ,)}(P), x)
struct Message{T,S}
q0::S
q::T
end
message(q0, q) = Message(q0, q)
message() = nothing
function backward(::BF, k::Union{AffineGaussianKernel,LinearGaussianKernel}, q::Gaussian{(:μ,:Σ)})
ν, Σ = q.μ, q.Σ
B, β, Q = params(k)... | [
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9... | 1.764564 | 3,313 |
using NumericalMethodsforEngineers, DataFrames, Plots
pyplot(size=(700,700))
ProjDir = dirname(@__FILE__)
cd(ProjDir) #do
x = [1.0, 3.0, 6.0, 5.0]
y = [1.0, 5.0, 10.0, 9.0]
xi = [2.0, 4.5]
(dfin, dfxi) = lagrangianpolynomial(length(x), x, y, xi)
xint = 1:0.1:5
(dfin, dfxint) = lagrangianpolynomial(le... | [
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73,
3527... | 2.103261 | 368 |
function check(i, j)
id, im = div(i, 9), mod(i, 9)
jd, jm = div(j, 9), mod(j, 9)
jd == id && return true
jm == im && return true
div(id, 3) == div(jd, 3) &&
div(jm, 3) == div(im, 3)
end
const lookup = zeros(Bool, 81, 81)
for i in 1:81
for j in 1:81
lookup[i,j] = check(i-1, j-1)
... | [
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8,
... | 1.548096 | 998 |
using Distributions
using PyPlot
using LsqFit
using CSV, DataFrames, DataFramesMeta
using StatsBase
""" Functions for results of Fig. 2E """
# Run:
# mean_thrs_delay_1, mean_thrs_delay_3 = SinergiafMRI_datafit.get_state_visits_bootstrapped()
function get_state_visits_bootstrapped(;
... | [
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329,
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286,
12138,
13,
362,
36,
37227,
198,
2,
5660,... | 2.041609 | 6,537 |
<gh_stars>10-100
export JITEventListener, GDBRegistrationListener, IntelJITEventListener,
OProfileJITEventListener, PerfJITEventListener
@checked struct JITEventListener
ref::API.LLVMJITEventListenerRef
end
Base.unsafe_convert(::Type{API.LLVMJITEventListenerRef}, listener::JITEventListener) = listener.ref
... | [
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220,
220,
220,
220,
440,
37046,
41,
2043,
9237,
33252,
11,
2448,
69,
41,
... | 2.935622 | 233 |
"""
hubbard_dispersion(k)
Dispersion relation for [`HubbardMom1D`](@ref). Returns `-2cos(k)`.
See also [`continuum_dispersion`](@ref).
"""
hubbard_dispersion(k) = -2cos(k)
"""
continuum_dispersion(k)
Dispersion relation for [`HubbardMom1D`](@ref). Returns `k^2`.
See also [`hubbard_dispersion`](@ref).
"""
con... | [
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6... | 2.239726 | 3,504 |
<reponame>jagot/AtomicLevels.jl<gh_stars>1-10
module AtomicLevels
using UnicodeFun
using Formatting
using Parameters
using BlockBandedMatrices
using WignerSymbols
using HalfIntegers
using Combinatorics
include("common.jl")
include("unicode.jl")
include("parity.jl")
include("orbitals.jl")
include("relativistic_orbital... | [
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40117,
198,
3500,
9726,
... | 2.780303 | 264 |
module ARCSolver
export main, simple
using Reexport
include("grids.jl")
@reexport using .Grids
include("render.jl")
@reexport using .Render
include("solve.jl")
@reexport using .Solve
include("diff.jl")
@reexport using .Diff
using Images, ImageView
function main()
tasks = load_tasks()
# warmstart
pri... | [
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31... | 2.280788 | 406 |
# Model
include_model("hopper")
mb = 3.0 # body mass
ml = 0.3 # leg mass
Jb = 0.75 # body inertia
Jl = 0.075 # leg inertia
model = Hopper{Discrete, FixedTime}(n, m, d,
mb, ml, Jb, Jl,
0.25, g,
qL, qU,
uL, uU,
nq,
nu,
nc,
nf,
nb,
ns,
... | [
2,
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... | 1.831924 | 4,611 |
function makealltrans(N,n,Ω,basis="Hermite")
dim=length(N)
if dim==1
Nx = N[1]
ωx = Ω[1]
#n-field transforms for PGPE
x,wx,Tx = nfieldtrans(Nx,n,ω=ωx,basis=basis)
return x,wx,Tx
elseif dim==2
Nx,Ny = N
ωx,ωy = Ω
#n-field transforms for PGPE
x,wx,Tx = nfieldtrans(Nx,n,ω=ωx,basis=basis)
y,wy,Ty = nfie... | [
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220,
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7377,... | 1.773109 | 357 |
import Distributions: logpdf, pdf
struct SDT{T1,T2} <: ContinuousUnivariateDistribution
d::T1
c::T2
end
logpdf(d::SDT, data::Vector{Int64}) = logpdf(d, data...)
logpdf(d::SDT, data::Tuple{Vararg{Int64}}) = logpdf(d, data...)
function logpdf(d::SDT, hits, fas, Nd)
@unpack d,c = d
θhit = cdf(Normal(0,... | [
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4... | 2.048327 | 269 |
# This code is based on the gridap hyperelasticity demo: https://gridap.github.io/Tutorials/dev/pages/t005_hyperelasticity/
# Here I expanded it to 3D and added Makie based model visualisation.
# Note this code currently requires: ] add Makie@0.15.2 GLMakie@0.4.6
using Gridap
using Gridap.Visualization
using Gridap... | [
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62,
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14,
198,
2,
3423,
... | 2.127701 | 3,101 |
{"score": 8.04, "timestamp": 1580207216.0, "score_count": 256261}
{"score": 8.06, "timestamp": 1567156859.0, "score_count": 246192}
{"score": 8.06, "timestamp": 1566888606.0, "score_count": 245781}
{"score": 8.06, "timestamp": 1565672254.0, "score_count": 244871}
{"score": 8.06, "timestamp": 1565469084.0, "score_count"... | [
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131... | 2.360307 | 7,044 |
import UUIDs
# This function is based off of a similar function here:
# https://github.com/JuliaRegistries/RegistryCI.jl/blob/master/src/RegistryCI.jl
function gather_stdlib_uuids()
return Set{UUIDs.UUID}(x for x in keys(Pkg.Types.stdlib()))
end
| [
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1... | 2.728261 | 92 |
<filename>src/Backends/Hive.jl
module HiveLoader
# https://github.com/JuliaDatabases/Hive.jl v0.3.0
using Hive # HiveSession HiveAuth
using Octo.Repo: ExecuteResult
const current = Dict{Symbol, Any}(
:sess => nothing,
)
current_sess() = current[:sess]
# db_connect
function db_connect(; host::String="localhost",... | [
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1303... | 2.715719 | 598 |
function _permute_front(t::AbstractTensorMap) # make TensorMap{S,N₁+N₂-1,1}
I = TensorKit.allind(t) # = (1:N₁+N₂...,)
if BraidingStyle(sectortype(t)) isa SymmetricBraiding
permute(t, Base.front(I), (I[end],))
else
levels = I
braid(t, levels, Base.front(I), (I[end],))
end
end
func... | [
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20827,... | 1.839974 | 1,531 |
<reponame>gcleroux/SnakeAI.jl
function train!(agent::AbstractAgent, game::SnakeAI.Game)
# Get the current step
old_state = SnakeAI.get_state(game)
# Get the predicted move for the state
move = get_action(agent, old_state)
SnakeAI.send_inputs!(game, move)
# Play the step
reward, done, score... | [
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... | 2.324274 | 1,619 |
using VLConstraintBasedModelGenerationUtilities
# setup path to protein sequence file -
path_to_vff_file = "/Users/jeffreyvarner/Desktop/julia_work/VLConstraintBasedModelGenerationUtilities.jl/test/data/Test.vff"
path_to_system_model_file = "/Users/jeffreyvarner/Desktop/julia_work/VLConstraintBasedModelGenerationUtili... | [
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1... | 2.917582 | 364 |
using Printf
using BenchmarkTools
function heat()
N = 1001
T0 = Matrix{Float64}(undef,N,N)
T1 = Matrix{Float64}(undef,N,N)
x = Matrix{Float64}(undef,N,N)
y = Matrix{Float64}(undef,N,N)
a = 0
b = π;
dx = (b-a)/(N-1)
for j=1:N
for i=1:N
x[i,j] = (i-1)... | [
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8,
201... | 1.486057 | 4,339 |
<reponame>henrystoldt/fvCFD
######################### Global Time Stepping ###########################
function forwardEuler(mesh::Mesh, fluxResidualFn, sln::SolutionState, boundaryConditions, fluid::Fluid, dt)
sln.fluxResiduals = fluxResidualFn(mesh, sln, boundaryConditions, fluid)
@fastmath sln.cellState .+= ... | [
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... | 2.517808 | 1,825 |
################################################################################
#
# AlgAssRelOrd
#
################################################################################
# S is the element type of the base field of the algebra, T the fractional ideal
# type of this field
mutable struct AlgAssRelOrd{S, T, U... | [
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2... | 2.262766 | 2,017 |
"
Iterating over an AbstractGroup is the same as iterating over the set.
"
abstract type AbstractGroup end
# TODO: convert `Set` to `AbstractSet` where possible to support OrderedSets et al
"""
Stucture consisting of a set and a binary operation. No constraints are put on either expression.
"""
struct Groupoi... | [
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2383... | 2.477052 | 5,142 |
<gh_stars>0
# Ospa dist
function ospa_dist(pca1::Vector{Pointcloud},
pca2::Vector{Pointcloud},
c::S
) where {S <: Real}
#dmat = Matrix{Float64}(length(pca1), length(pca2))
dmat = Matrix{Float64}(undef, length(pca1), length(pca2))
for i=1:length(pca1)
... | [
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220,
220,
220,
220,
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220,
220,
... | 1.778561 | 709 |
<reponame>mkg33/Catalyst.jl<gh_stars>0
using Catalyst
rn = @reaction_network begin
α, S + I --> 2I
β, I --> R
S^2, R --> 0
end α β
# check can make a graph
gr = Graph(rn)
# check can save a graph
fname = Base.Filesystem.tempname()
savegraph(gr, fname, "png")
| [
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40,
... | 2.382609 | 115 |
<filename>src/plot_recipes/recipes_populations.jl
import ..UncertainValues: UncertainScalarPopulation
using RecipesBase
#@recipe f(::Type{UncertainScalarPopulation{T}}, x::UncertainScalarPopulation{T}) where {T} =
# rand(x, 10000)
@recipe function f(p::UncertainScalarPopulation{T}) where T
@series begin
... | [
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2,
31,
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431,
2... | 2.448598 | 214 |
export pointwise_log_likelihoods
const ARRAY_DIMS_WARNING = "The supplied array of mcmc samples indicates you have more
parameters than mcmc samples.This is possible, but highly unusual. Please check that your
array of mcmc samples has the following dimensions: [n_samples,n_parms,n_chains]."
"""
pointwise_log_li... | [
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621,
285,
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66,
8405,... | 2.595041 | 847 |
<reponame>n-kishaloy/FinanceLib.jl
import FinanceLib
import Dates
@testset "FinanceLib " begin
@testset "tv" begin
@test FinanceLib.yearFrac(Dates.Date(2027,2,12), Dates.Date(2018,2,12)) ≈ -8.999315537303216
@test FinanceLib.invYearFrac(Dates.Date(2027,2,12),... | [
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220,
220,
220,
220,
... | 1.925748 | 3,744 |
<filename>src/lib/broadcast.jl<gh_stars>0
# .-'''-. _..._
# ' _ \ _______ .-'_..._''.
# /| / /` '. \ \ ___ `'. .' .' '.\
# || . | \ ' ' |--.\ \ / .'
# ... | [
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... | 1.835768 | 1,985 |
<filename>src/categorical_algebra/FinSets.jl
""" The category of finite sets and functions, and its skeleton.
"""
module FinSets
export FinSet, FinFunction, FinDomFunction, TabularSet, TabularLimit,
force, is_indexed, preimage,
JoinAlgorithm, SmartJoin, NestedLoopJoin, SortMergeJoin, HashJoin,
SubFinSet, SubOpBoo... | [
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... | 2.538146 | 18,272 |
<gh_stars>1-10
"""
ForceDirectedLayout
The fields are, in order:
- `move`, a tuple to specify whether moves on the x and y axes are allowed
- `k`, a tuple (kₐ,kᵣ) giving the strength of attraction and repulsion
- `exponents`, a tuple (a,b,c,d) giving the exponents for the attraction and
repulsion functions
- `g... | [
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1771,
6100,
319,
262,
2124,
290,
... | 2.39918 | 2,683 |
<reponame>tawheeler/AutoDrivers.jl
type GMR{M<:MvNormal}
# μ₁₋₂ = μ₁ + Σ₁₂ * Σ₂₂⁻¹ * (x₂ - μ₂) = A*x₂ + b
vec_A::Vector{Matrix{Float64}} # [n_components [ntargets×nindicators]]
vec_b::Vector{Vector{Float64}} # [n_components [ntargets]]
# pdf(p), all pre-computed. Used to compute βⱼ(p)
mixture_Obs:... | [
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224,
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18919,
... | 1.930055 | 2,888 |
import Base: position
using FFTW
"""
PositionBasis(xmin, xmax, Npoints)
PositionBasis(b::MomentumBasis)
Basis for a particle in real space.
For simplicity periodic boundaries are assumed which means that
the rightmost point defined by `xmax` is not included in the basis
but is defined to be the same as `xmin... | [
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298,
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15522,
2... | 2.07227 | 9,506 |
#Constant mean function
"""
MeanConst <: Mean
Constant mean function
```math
m(x) = β
```
with constant ``β``.
"""
mutable struct MeanConst <: Mean
"Constant"
β::Float64
"Priors for mean parameters"
priors::Array
"""
MeanConst(β::Float64)
Create `MeanConst` with constant `β`.
... | [
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26638,
1... | 2.494444 | 360 |
# __BEGIN_LICENSE__
#
# ThreeDeconv.jl
#
# Copyright (c) 2018, Stanford University
#
# All rights reserved.
#
# Redistribution and use in source and binary forms for academic and other
# non-commercial purposes with or without modification, are permitted provided
# that the following conditions are met:
#
# * Redistrib... | [
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... | 2.277254 | 3,394 |
<filename>backend/anime_data/snapshots_8676.jl
{"score": 7.47, "score_count": 105041, "timestamp": 1567156691.0}
{"score": 7.47, "score_count": 104512, "timestamp": 1565255920.0}
{"score": 7.48, "score_count": 103497, "timestamp": 1560521897.0}
{"score": 7.48, "score_count": 103335, "timestamp": 1559873532.0}
{"score":... | [
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1298,
1315,
3134,
1314,
2791,
6... | 2.346216 | 1,242 |
@testset "isconvex" begin
m = JuMP.Model()
JuMP.@variables m begin
x
y
z
end
# AffExpr
@test MultilinearOpt.isconvex(x + y)
@test MultilinearOpt.isconvex(x - z - 3)
# QuadExpr
@test MultilinearOpt.isconvex(x^2)
@test MultilinearOpt.isconvex(x^2 + 0 * z^2) # test posi... | [
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285,
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198,
220,
220,
220,
220,
220,
220,
2124,
198,
220,
220,... | 2.048433 | 702 |
module FullRegisterGate
export expandGateToFullRegister
# expandGateToFullRegister expands the given gate with optional control qubits to entire quantum register with the given size.
function expandGateToFullRegister(register_size::Integer,
gate::AbstractMatrix{Complex{Float64}},
gate_lowest_index::Integer,
contro... | [
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... | 2.738128 | 737 |
<gh_stars>0
# ---
# layout: post
# title: "π day"
# date: 2019-03-13 00:00:00 +0000
# categories: blog
# mathjax: true
# ---
# >In the UK we have started to celebrate π day (the 3rd month's 14th day) every year, even though we don't use the USA's date formatting convention of `monthnumber` followed by `daynumber`. But... | [
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2,
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25,
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198,
2,
10688,... | 2.88238 | 4,370 |
typealias ReComp Union{Real,Complex}
immutable Dual{T<:ReComp} <: Number
value::T
epsilon::T
end
Dual{S<:ReComp,T<:ReComp}(x::S, y::T) = Dual(promote(x,y)...)
Dual(x::ReComp) = Dual(x, zero(x))
const ɛ = Dual(false, true)
const imɛ = Dual(Complex(false, false), Complex(false, true))
typealias Dual128 Dual{Fl... | [
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43... | 1.935233 | 4,879 |
<reponame>hessammehr/Chain.jl<gh_stars>0
using Plots
using MCMCChain
n_iter = 500
n_name = 3
n_chain = 2
val = randn(n_iter, n_name, n_chain) .+ [1, 2, 3]'
val = hcat(val, rand(1:2, n_iter, 1, n_chain))
chn = Chains(val)
# plotting singe plotting types
ps_trace = plot(chn, :trace)
ps_mean = plot(chn, :mean)
ps_dens... | [
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513,
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62,
... | 2.342412 | 257 |
<reponame>kfgarrity/TightlyBound.jl
using Test
using TightlyBound
using Suppressor
#include("../includes_laguerre.jl")
#include("../Ewald.jl")
TESTDIR=TightlyBound.TESTDIR
function loaddata(dirs; scf=true)
tbc_list = []
dft_list = []
for t in dirs
# println(t*"/qe.save")
... | [
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414,
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306,
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306,
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198,
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198,
198,
2,
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7203,
40720,
42813,
62,
75,
11433,
263,
260,
13,
20362,
494... | 1.920926 | 3,111 |
struct Match
rule::AbstractRule
# the rhs pattern to instantiate
pat_to_inst::Union{Nothing,Pattern}
# the substitution
sub::Sub
# the id the matched the lhs
id::EClassId
end
const MatchesBuf = Vector{Match}
function cached_ids(g::EGraph, p::Pattern)# ::Vector{Int64}
collect(keys(... | [
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220,
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284,
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220,
220,
220,
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62,
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62,
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3712,
38176,
90,
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11,
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92,
198,
220,
220,... | 2.135194 | 1,827 |
<reponame>AndrewSerra/Knet.jl<filename>src/ops20_gpu/rnn.jl
import Knet.Ops20: rnnforw
using Knet.Ops20: RNN
using Knet.KnetArrays: DevArray, KnetArray, Cptr
using CUDA: CuArray, CUDNN, CU_NULL
using AutoGrad: AutoGrad, @primitive1, value, recording, Param, Value
"RNN descriptor"
mutable struct RD; ptr; end
"Dropout ... | [
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20471,
13,
20362,
198,
11748,
509,
3262,
13,
41472,
1238,
25,
374,
20471,
1640,
86,
198,
3500,
509,
3262,
... | 2.143205 | 7,395 |
"""
critic(decisionMat, fns)
Apply CRITIC (Combined Compromise Solution) method for a given matrix and criteria types.
# Arguments:
- `decisionMat::DataFrame`: n × m matrix of objective values for n alternatives and m criteria
- `fns::Array{Function, 1}`: m-vector of functions to be applied on the columns.... | [
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8,
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257,
1813,
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290,
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198,
198,... | 2.341997 | 1,462 |
using InfrastructureSystems
using PowerSystems
using InteractiveUtils
const IS = InfrastructureSystems
const PSY = PowerSystems
IS.strip_module_name
function _check_exception(T, exceptions::Vector)
for type_exception in exceptions
if T <: type_exception
return true
end
end
retu... | [
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198,
198,
1797,
13,
36311,
62,
21412,
62,
3672,
198,
198,
8818,
4808... | 1.971566 | 2,075 |
# create Vec
@testset "Vec{$ST}" begin
vtype = PETSc.C.VECMPI
vec = PETSc.Vec(ST, vtype)
resize!(vec, 4)
@test_throws ArgumentError resize!(vec)
len_ret = length(vec)
@test length(vec) == 4
@test size(vec) == (4,)
@test lengthlocal(vec) == 4
@test sizelocal(vec) == (4,)
@test PETSc.gettype(vec) == ... | [
2,
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7,
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8,
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... | 1.88146 | 5,205 |
export SymbolContext, ContextualSymbol, show
import Base.show, Base.show_unquoted
import Crayons: CrayonStack, Crayon
"""
SymbolContext(syms, function [,display_expression])
A symbol context is a special function, evaluating symbols within the body of
the function within the context of a single argument. Gene... | [
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... | 2.682948 | 1,126 |
<reponame>aviks/Logging.jl
using Logging
function log_test()
debug("debug message")
info("info message")
warn("warning message")
err("error message")
critical("critical message")
end
println("Setting level=DEBUG")
Logging.configure(level=DEBUG)
log_test()
println()
println("Setting level=INFO")
L... | [
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4943,
198,
... | 2.938679 | 212 |
#######################################################################
#
# An example of creating an Excel charts with a date axis using
# XlsxWriter.
#
# Original Python Copyright 2013-2016, <NAME>, <EMAIL>
# https://github.com/jmcnamara/XlsxWriter
using Dates
using XlsxWriter
function test()
wb = Workbook("chart... | [
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... | 2.434851 | 637 |
<filename>src/julia_sets.jl<gh_stars>0
module julia_sets
using PyPlot
export gen_jset,show_jset
function gen_jset{T<:Real,U<:Real}(R::Function,x::Array{T,1},y::Array{T,1},n_iter::Int64,escape_tol::U)
A = zeros(length(x),length(y));
for i=1:length(x)
for j=1:length(y)
z = Complex(x[i],y[j])
for k... | [
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7... | 1.762463 | 341 |
<reponame>zsunberg/ContinuousPOMDPTreeSearchExperiments.jl
using DataFrames
using CSV
data = CSV.read("data/multilane_Saturday_28_Apr_16_17.csv")
means = by(data, :solver) do df
n = size(df, 1)
return DataFrame(reward=mean(df[:reward]),
reward_sem=std(df[:reward])/sqrt(n)
... | [
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13,
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7203,
7890,
14,
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346,
1531,
62,
19844... | 2.047337 | 169 |
# Routines related to fragmenting CAD entities in gmsh, while preserving physical groups
function process_material_hierarchy!(
new_physical_groups::Dict{String, Vector{Tuple{Int32,Int32}}},
material_hierarchy::Vector{String})
# Get the material groups and the entities in each group
groups = co... | [
2,
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7,
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220,
220,
220,
220,
220,
220,
220,
649,
62,
42854,
62,
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3712,... | 2.352891 | 3,511 |
using Test;
using AdalmPluto;
@testset "libIIO/scan.jl" begin
# disable the assertions
toggleNoAssertions(true);
C_iio_has_backend("usb") || (@error "Library doesn't have the USB backend available. Skipping tests."; return;)
@testset "Scan context" begin
# C_iio_create_scan_context
@t... | [
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19846,
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507,... | 1.997143 | 1,400 |
<reponame>mjirik/LarSurf.jl<gh_stars>1-10
# check speed of new and old sparse filter
using Revise
using LarSurf
using LinearAlgebraicRepresentation
Lar = LinearAlgebraicRepresentation
using Plasm, SparseArrays
using Pandas
using Seaborn
using Dates
using Logging
using Profile
using ProfileView
b3, something = LarSu... | [
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786,
198,
3500,
25577,
14214,
69,
198... | 2.194631 | 447 |
<reponame>zyth0s/PySCF.jl
module PySCF
using PyCall: pyimport
pyscf = pyimport("pyscf")
mp = pyimport("pyscf.mp") # Had to import mp alone ??!
cc = pyimport("pyscf.cc") # Had to import mp alone ??!
# Utilities
function pyscf_atom_from_xyz(fpath::String)
join(split(read(open(fpath),String),"\n")[3:end],"\n")
en... | [
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796,
12972,
11748,
7203,
79,
893,
12993,
4943,
198,
... | 2.554779 | 429 |
<filename>src/profiling.jl
# Code used for latency profiling
using StatsBase, Statistics, Dates
struct ProfilerInput
worker::Int
θ::Float64
q::Float64
timestamp::Time
comp_delay::Float64
comm_delay::Float64
end
struct ProfilerOutput
worker::Int # worker index
θ::Float64... | [
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220,
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220,
220,
220,
7377,
... | 2.24776 | 3,237 |
<filename>src/dracula.jl<gh_stars>100-1000
# Names follow:
# https://draculatheme.com/contribute#color-palette
dracula_palette = [
colorant"#8be9fd" # Cyan
colorant"#ff79c6" # Pink
colorant"#50fa7b" # Green
colorant"#bd93f9" # Purple
colorant"#ffb86c" # Orange
colorant"#ff5555" # Red
coloran... | [
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1326,
13,
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14,
3642,
4163,
2,
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12,
18596,
5857,
198,
7109,... | 2.113695 | 387 |
<reponame>briochemc/AIBECS.jl<gh_stars>10-100
# Reexport SinkingParticles as they are useful outside too
#@reexport module SinkingParticles
using Unitful
using LinearAlgebra, SparseArrays
using OceanGrids
"""
PFDO(grd; w_top)
Builds the particle-flux-divergence operator `PFDO` for a given particle sinking speed... | [
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31,
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... | 2.196544 | 2,951 |
<reponame>BlancaCC/TFG-Estudio-de-las-redes-neuronales
@testset "Nodes initialization algorithm n=3 entry = 3 output = 2" begin
M = 1 # Constante para la función rampa
# Bien definido para tamaño n = 2 y salida de dimensión 1
f_regression(x,y,z)=[x*y-z,x]
data_set_size = 6
entry_dimension = 3
... | [
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513,
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796,
362... | 2.215415 | 506 |
<reponame>szarnyasg/SuiteSparseGraphBLAS.jl<gh_stars>0
@testset "operations.jl" begin
@testset "ewise" begin
m = GBMatrix([[1,2,3] [4,5,6]])
n = GBMatrix([1,2,3,2], [1,2,2,1], [1,2,3,4])
#eadd correctness
@test eadd(m, n) == GBMatrix([1,1,2,2,3,3], [1,2,1,2,1,2], [2,4,6,7,3,9])
... | [
27,
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602,
13,
20362,
1,
2221,
198,
220,
220,
220,
2488,
9288,
2617... | 1.780639 | 1,942 |
using SimpleTest
using YAML
println("Enter two numbers")
num1 = parse(Float64, readline())
num2 = parse(Float64, readline())
result = simple_operation(num1, num2)
println("The sum is ", result)
sep = "/"
working_path = pwd()
settings_path = joinpath(working_path, "settings.yml")
testpath = joinpath(pwd(), "src")
push!(... | [
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575,
2390,
43,
198,
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16,
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17,
796,
21136,
7,
43879,
2414,
11,
1100,
1370,
28955,
198,
20274,
... | 2.901235 | 162 |
@testset "fsm_active_close.jl" begin
base_seq = WrappingInt32(1 << 31)
DEFAULT_CAPACITY = 64000
TIMEOUT_DFLT = 1000
@testset "start in TIME_WAIT, timeout" begin
conn = TCPConnection()
#Listen will do nothing
expect_state(conn, JLSponge.LISTEN)
tick!(conn, 1)
... | [
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220,
220,
220,
5550,
38865,
62,
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2246,
9050,
796,
5598,
83... | 1.97035 | 371 |
using Test
@testset "config" begin
include("config.jl")
end
@testset "fileio" begin
include("fileio.jl")
end
@testset "json" begin
include("json.jl")
end | [
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... | 2.507463 | 67 |
<gh_stars>1-10
module LifeContingencies
using ActuaryUtilities
using MortalityTables
using Transducers
using Dates
using Yields
const mt = MortalityTables
export LifeContingency,
Insurance, AnnuityDue, AnnuityImmediate,
APV,
SingleLife, Frasier, JointLife,
LastSurvivor,
survival,
reserve_... | [
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198,
3500,
44712,
198,
3500,
575,
1164,
82,
198,
220,
220,
22... | 2.723 | 6,213 |
<filename>test/all.jl
include("orderbook.jl")
include("blotter.jl")
include("trades.jl")
include("portfolio.jl")
include("account.jl")
include("utilities.jl")
| [
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198,
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7203,
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1... | 2.789474 | 57 |
using StanSample, DataFrames
model = "
data {
int<lower=0> N;
int<lower=0,upper=1> y[N];
}
parameters {
real<lower=0,upper=1> theta;
}
model {
theta ~ beta(1,1);
y ~ bernoulli(theta);
}
";
sm = SampleModel("bernoulli", model);
data = Dict("N" => 10, "y" => [0, 1, 0, 1, 0, 0, 0, 0, 0, 1]);
rc = stan_... | [
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28,
15,
29,
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26,
220,
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220,
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28,
15,
11,
45828,
28,
16,
29,
331,
58,
45,
11208,
198,
92,
220,
... | 2.135678 | 199 |
###Define functions to be used in testing below
###Test functions for TargetModel
function targetsin!(r::Vector,t::AbstractVector,paras::Vector)
for i=1:length(t)
r[i] = sin(paras[1]*t[i])
end
r
end
targetsin(t::AbstractVector,paras::Vector) = targetsin!(zeros(eltype(t),length(t)),t,paras)
###Tes... | [
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23839,
38469,
11,
1845,
292,
3712,
38469,
8,
198,
220,
220,
220,
329... | 2.779294 | 1,246 |
<reponame>JakeGrainger/WhittleLikelihoodInference.jl
using Plots
@testset "plotting" begin
@testset "plotsdf" begin
@test_throws ArgumentError plotsdf(1.0)
@test_throws ArgumentError plotsdf(OU,1:2)
@test_throws ArgumentError plotsdf(1.0,1:2)
@test_throws ArgumentError plotsdf(OU(1.0... | [
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198,
31,
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366,
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889,
1,
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198,
220,
220,
220,
2488,
9288,
2617,
366,
489,
1747,
7568,
1,
2221... | 1.947084 | 926 |
# Visualization
function plot_state_city(state)
qiskit.visualization.plot_state_city(state)
end
function plot_histogram(data)
qiskit.visualization.plot_histogram(data)
end
| [
2,
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7110,
62,
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62,
19205,
7,
5219,
8,
198,
220,
220,
220,
10662,
1984,
270,
13,
41464,
1634,
13,
29487,
62,
5219,
62,
19205,
7,
5219,
8,
198,
437,
198,
198,
8818,
7110,
62,
10034,
21857,
7,
7890,
... | 2.757576 | 66 |
# AbstractBandedMatrix must implement
# A BlockBandedMatrix is a BlockMatrix, but is not a BandedMatrix
abstract type AbstractBlockBandedMatrix{T} <: AbstractBlockMatrix{T} end
"""
blockbandwidths(A)
Returns a tuple containing the upper and lower blockbandwidth of `A`.
"""
blockbandwidths(A::AbstractMatrix) = (... | [
2,
27741,
33,
12249,
46912,
1276,
3494,
198,
198,
2,
317,
9726,
33,
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318,
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11,
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33,
12249,
46912,
90,
51,
92,
1279,
25,
27741,
1... | 2.656969 | 1,478 |
<gh_stars>1-10
function [D,J,JInv,X]=JacobiSphere(ksi,F,Grid)
Rad=Grid.Rad;
X1=Grid.Nodes(F.N(1)).P(1)...
+(Grid.Nodes(F.N(2)).P(1)-Grid.Nodes(F.N(1)).P(1))*ksi(1)...
+(Grid.Nodes(F.N(4)).P(1)-Grid.Nodes(F.N(1)).P(1))*ksi(2)...
+(Grid.Nodes(F.N(3)).P(1)-Grid.Nodes(F.N(4)).P(1)-Grid.Nodes(F.N(2)).P(1)+Grid.Nodes(F... | [
27,
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29,
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41,
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8,
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28,
41339,
13,
15546,
26,
198,
55,
16,
28,
41339,
13,
45,
4147,
... | 1.445545 | 1,919 |
<gh_stars>1-10
module JungleHelperSpiderBoss
using ..Ahorn, Maple
@mapdef Entity "JungleHelper/SpiderBoss" SpiderBoss(x::Integer, y::Integer, color::String="Blue", sprite::String="", webSprite::String="", flag::String="")
const bossColors = String["Blue", "Purple", "Red"]
const bossSprites = Dict{String, String}(
... | [
27,
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62,
30783,
29,
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198,
21412,
26411,
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11,
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31,
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366,
41,
13687,
47429,
14,
41294,
37310,
1,
12648,
37310,
7,
87,
3712,
46541,... | 2.633735 | 415 |
<gh_stars>1-10
import ONNXRunTime
function onnxruntime_infer(f, inputs...)
reversedims(a::AbstractArray{T,N}) where {T, N} = permutedims(a, N:-1:1)
mktempdir() do dir
modelfile = joinpath(dir, "model.onnx")
save(modelfile, f, size.(inputs)...)
model = ONNXRunTime.load_inference(modelfile)
return model(Di... | [
27,
456,
62,
30783,
29,
16,
12,
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198,
198,
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440,
6144,
55,
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319,
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87,
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62,
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7,
69,
11,
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628,
197,
260,
690,
276,
12078,
7,
64,
3712,
23839,
19182,
90,
51,
11,
45,
... | 2.379888 | 179 |
#Load the Distributions package. Use `Pkg.install("Distributions")` to install first time.
using Distributions: TDist, ccdf
type regress_results
coefs
yhat
res
vcv
tstat
pval
end
# Keyword arguments are placed after semicolon.
# Symbols start with colon, e.g. `:symbol`.
function ols(y, X; corr... | [
2,
8912,
262,
46567,
507,
5301,
13,
5765,
4600,
47,
10025,
13,
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2455,
507,
4943,
63,
284,
2721,
717,
640,
13,
198,
3500,
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507,
25,
13320,
396,
11,
36624,
7568,
198,
198,
4906,
50252,
62,
43420,
198,
220,
220... | 1.852048 | 1,514 |
<reponame>stevengj/GMT.jl<filename>src/grd2kml.jl
"""
grd2kml(cmd0::String="", arg1=nothing, kwargs...)
Reads a 2-D grid file and makes a quadtree of PNG images and KML wrappers for Google Earth
using the selected tile size [256x256 pixels].
Full option list at [`grd2kml`]($(GMTdoc)grd2kml.html)
Parameters
--------... | [
27,
7856,
261,
480,
29,
4169,
574,
70,
73,
14,
49424,
13,
20362,
27,
34345,
29,
10677,
14,
2164,
67,
17,
74,
4029,
13,
20362,
198,
37811,
198,
197,
2164,
67,
17,
74,
4029,
7,
28758,
15,
3712,
10100,
2625,
1600,
1822,
16,
28,
223... | 2.532591 | 1,258 |
using SimLynx
using Test
@testset "SimLynx.jl" begin
@test greet() == "Hello World!"
end
| [
3500,
3184,
37207,
87,
198,
3500,
6208,
198,
198,
31,
9288,
2617,
366,
8890,
37207,
87,
13,
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1,
2221,
198,
220,
220,
220,
2488,
9288,
12589,
3419,
6624,
366,
15496,
2159,
2474,
198,
437,
198
] | 2.611111 | 36 |
# Note that this script can accept some limited command-line arguments, run
# `julia build_tarballs.jl --help` to see a usage message.
using BinaryBuilder
# Collection of sources required to build LCIOWrapBuilder
sources = [
"LCIOWrapBuilder"
]
# Bash recipe for building across all platforms
function getscript(ve... | [
2,
5740,
326,
428,
4226,
460,
2453,
617,
3614,
3141,
12,
1370,
7159,
11,
1057,
198,
2,
4600,
73,
43640,
1382,
62,
18870,
21591,
13,
20362,
1377,
16794,
63,
284,
766,
257,
8748,
3275,
13,
198,
3500,
45755,
32875,
198,
198,
2,
12251,
... | 2.652482 | 705 |
const CuDense{ElT,VecT} = Dense{ElT,VecT} where {VecT<:CuVector}
const CuDenseTensor{ElT,N,StoreT,IndsT} = Tensor{ElT,N,StoreT,IndsT} where {StoreT<:CuDense}
Dense{T, SA}(x::Dense{T, SB}) where {T<:Number, SA<:CuArray, SB<:Array} = Dense{T, SA}(CuArray(x))
Dense{T, SA}(x::Dense{T, SB}) where {T<:Number... | [
9979,
14496,
35,
1072,
90,
9527,
51,
11,
53,
721,
51,
92,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
796,
360,
1072,
90,
9527,
51,
11,
53,
721,
51,
92,
810,
1391,
53,
721,
51,
27,
25,
461... | 1.967434 | 6,909 |
<reponame>JuliaFEM/FEMBase.jl<filename>test/test_fields.jl
using FEMBase, Test
# From the beginning of a project we had a clear concept in our mind: "everything
# is a field". That is, everything can vary temporally and spatially. We think
# that constant is just a special case of field which does not vary in temporal... | [
27,
7856,
261,
480,
29,
16980,
544,
37,
3620,
14,
37,
3620,
14881,
13,
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27,
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29,
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14,
9288,
62,
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13,
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198,
3500,
376,
3620,
14881,
11,
6208,
198,
198,
2,
3574,
262,
3726,
286,
257,
1628,
356,
550,
257,... | 2.4506 | 3,249 |
<reponame>paveloom-j/Scats.jl
# This file contains a function
# to write input data to a file
"""
write(input::InputStruct, file::AbstractString)
Write input data from an instance of [`InputStruct`](@ref) to a file.
# Usage
```jldoctest; output = false
using Scats
s = Scats.API()
file, _ = mktemp()
s.Input.writ... | [
27,
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261,
480,
29,
8957,
626,
4207,
12,
73,
14,
3351,
1381,
13,
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198,
2,
770,
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4909,
257,
2163,
198,
2,
284,
3551,
5128,
1366,
284,
257,
2393,
198,
198,
37811,
198,
220,
220,
220,
3551,
7,
15414,
3712,
20560,
44909... | 2.304985 | 341 |
<gh_stars>1-10
module TreeTools
using FastaIO
using JSON
using Dates
## Includes
include("objects.jl")
include("objectsmethods.jl")
include("mutations.jl")
include("prunegraft.jl")
include("datamethods.jl")
include("reading.jl")
include("writing.jl")
include("misc.jl")
include("lbi.jl")
end
## Todo
# the child fiel... | [
27,
456,
62,
30783,
29,
16,
12,
940,
198,
21412,
12200,
33637,
628,
198,
3500,
12549,
64,
9399,
198,
3500,
19449,
198,
3500,
44712,
198,
2235,
29581,
198,
17256,
7203,
48205,
13,
20362,
4943,
198,
17256,
7203,
48205,
24396,
82,
13,
20... | 3.456522 | 184 |
<filename>src/maxpool.jl<gh_stars>0
function maxpool2x2relu!(B, A)
@avx for i₁ ∈ axes(B,1), i₂ ∈ axes(B,2), i₃ ∈ axes(B,3), i₄ ∈ axes(B,4)
A₁ = A[2i₁-1,2i₂-1,i₃,i₄]
A₂ = A[2i₁-1,2i₂ ,i₃,i₄]
A₃ = A[2i₁ ,2i₂-1,i₃,i₄]
A₄ = A[2i₁ ,2i₂ ,i₃,i₄]
B[i₁,i₂,i₃,i₄] = max(max(max(A₁, ... | [
27,
34345,
29,
10677,
14,
9806,
7742,
13,
20362,
27,
456,
62,
30783,
29,
15,
198,
8818,
3509,
7742,
17,
87,
17,
260,
2290,
0,
7,
33,
11,
317,
8,
198,
220,
220,
220,
2488,
615,
87,
329,
1312,
158,
224,
223,
18872,
230,
34197,
7... | 1.399521 | 2,921 |
<gh_stars>100-1000
# functions related to negative binomial distribution
# R implementations
using .RFunctions:
nbinompdf,
nbinomlogpdf,
nbinomcdf,
nbinomccdf,
nbinomlogcdf,
nbinomlogccdf,
nbinominvcdf,
nbinominvccdf,
nbinominvlogcdf,
nbinominvlogccdf
| [
27,
456,
62,
30783,
29,
3064,
12,
12825,
198,
2,
5499,
3519,
284,
4633,
9874,
49070,
6082,
198,
198,
2,
371,
25504,
198,
3500,
764,
49,
24629,
2733,
25,
198,
220,
220,
220,
299,
8800,
3361,
7568,
11,
198,
220,
220,
220,
299,
8800,... | 2.17037 | 135 |
<reponame>ven-k/RobustAndOptimalControl.jl
if haskey(ENV, "CI")
ENV["PLOTS_TEST"] = "true"
ENV["GKSwstype"] = "100" # gr segfault workaround
end
using Plots
using RobustAndOptimalControl
using LinearAlgebra
using Test
@testset "RobustAndOptimalControl.jl" begin
@testset "extendedstatespace" begin
... | [
27,
7856,
261,
480,
29,
574,
12,
74,
14,
14350,
436,
1870,
27871,
4402,
15988,
13,
20362,
198,
361,
468,
2539,
7,
1677,
53,
11,
366,
25690,
4943,
198,
220,
220,
220,
12964,
53,
14692,
6489,
33472,
62,
51,
6465,
8973,
796,
366,
794... | 2.237037 | 945 |
################################################################################
# Augmented Gradient Search ARS
################################################################################
using LinearAlgebra
using Statistics
import LinearAlgebra.normalize
import GeometryBasics.update
function train(env::Environ... | [
29113,
29113,
14468,
198,
2,
2447,
12061,
17701,
1153,
11140,
5923,
50,
198,
29113,
29113,
14468,
198,
3500,
44800,
2348,
29230,
198,
3500,
14370,
198,
198,
11748,
44800,
2348,
29230,
13,
11265,
1096,
198,
11748,
2269,
15748,
15522,
873,
... | 1.96544 | 1,331 |
<reponame>LudwigBoess/SpectralCRsUtility.jl<filename>src/io/io.jl
using GadgetUnits
using GadgetIO
function readSingleCRShockDataFromOutputFile(file::String)
# read file into memory
f = open(file)
lines = readlines(f)
close(f)
# filter only relevant lines. Output of every line... | [
27,
7856,
261,
480,
29,
43,
463,
28033,
16635,
408,
14,
49738,
1373,
9419,
82,
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879,
13,
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27,
34345,
29,
10677,
14,
952,
14,
952,
13,
20362,
198,
3500,
39266,
3118,
896,
198,
3500,
39266,
9399,
198,
198,
8818,
1100,
2800... | 1.88838 | 3,709 |
import Base.CoreLogging:
AbstractLogger,
LogLevel,
handle_message,
min_enabled_level,
shouldlog,
global_logger
struct BaseLogger <: AbstractLogger
min_level::LogLevel
end
min_enabled_level(logger::BaseLogger) = logger.min_level
shouldlog(logger::BaseLogger, args...) = true
function handle... | [
11748,
7308,
13,
14055,
11187,
2667,
25,
198,
220,
220,
220,
27741,
11187,
1362,
11,
198,
220,
220,
220,
5972,
4971,
11,
198,
220,
220,
220,
5412,
62,
20500,
11,
198,
220,
220,
220,
949,
62,
25616,
62,
5715,
11,
198,
220,
220,
220... | 2.723636 | 275 |
using CUDA
using MOCNeutronTransport
using BenchmarkTools
using Test
# Number of points to use in vectors
N = 2^20
println("Using Point arrays of length $N")
# Check num threads and give warning
nthreads = Threads.nthreads()
if nthreads === 1
@warn "Only using single-thread for cpu. Try restarting julia with 'jul... | [
3500,
29369,
5631,
198,
3500,
337,
4503,
8199,
315,
1313,
8291,
634,
198,
3500,
25187,
4102,
33637,
198,
3500,
6208,
198,
198,
2,
7913,
286,
2173,
284,
779,
287,
30104,
198,
45,
796,
362,
61,
1238,
198,
35235,
7203,
12814,
6252,
26515... | 2.181368 | 2,222 |
<reponame>JuliaTagBot/play
# Characters
const SUITCHAR=collect("CDHSN")
const CARDCHAR=collect("23456789TJQKA")
const HEXCHAR=collect("0123456789ABCDEF")
const PLAYERCHAR=collect("WNES")
hex2int(c::Char)=(c <= '9' ? c - '0' : c - '7')
int2hex(i::Integer)=HEXCHAR[i+1]
# Trump suits
const CLUBS=1
const DIAMONDS=2
const ... | [
27,
7856,
261,
480,
29,
16980,
544,
24835,
20630,
14,
1759,
198,
2,
26813,
198,
9979,
13558,
31949,
1503,
28,
33327,
7203,
8610,
7998,
45,
4943,
198,
9979,
48731,
38019,
28,
33327,
7203,
1954,
2231,
3134,
4531,
51,
41,
48,
25123,
4943... | 2.436975 | 476 |
<filename>src/providers/data.jl<gh_stars>1-10
using Dates
include("../structures.jl")
include("../util/util.jl")
include("../util/logger.jl")
function fetchData!(store::DataStore, attribute::DataAttribute)
throw("Unknown data provider $(typeof(attribute))")
end
include("sysstat.jl")
include("aws.jl")
| [
27,
34345,
29,
10677,
14,
15234,
4157,
14,
7890,
13,
20362,
27,
456,
62,
30783,
29,
16,
12,
940,
198,
3500,
44712,
198,
198,
17256,
7203,
40720,
7249,
942,
13,
20362,
4943,
198,
17256,
7203,
40720,
22602,
14,
22602,
13,
20362,
4943,
... | 2.952381 | 105 |
<reponame>MageekDM/Enigma
function get_perm(str::String)
p = Array(Int, length(str))
for (i,c) in enumerate(str)
p[i] = char2ind(c)
end
p
end
const ENIGMA_ROTORS = [
Rotor(get_perm("EKMFLGDQVZNTOWYHXUSPAIBRCJ"), Int[2]), #char2ind('Q')]), # I
Rotor(get_perm("AJDKSIRUXBLHWTMCQGZNPYFVOE")... | [
27,
7856,
261,
480,
29,
44,
496,
988,
23127,
14,
4834,
13495,
198,
8818,
651,
62,
16321,
7,
2536,
3712,
10100,
8,
198,
220,
220,
220,
279,
796,
15690,
7,
5317,
11,
4129,
7,
2536,
4008,
198,
220,
220,
220,
329,
357,
72,
11,
66,
... | 2.259754 | 1,871 |
<filename>src/optimizers/adam.jl
export Adam
"""
Adam
Adam Optimizer
# References
* <NAME> Ba, ["Adam: A Method for Stochastic Optimization"](http://arxiv.org/abs/1412.6980v8), ICLR 2015.
"""
mutable struct Adam
alpha::Float64
beta1::Float64
beta2::Float64
eps::Float64
states::IdDict
end
Ada... | [
27,
34345,
29,
10677,
14,
40085,
11341,
14,
324,
321,
13,
20362,
198,
39344,
7244,
198,
198,
37811,
198,
220,
220,
220,
7244,
198,
198,
23159,
30011,
7509,
198,
198,
2,
31458,
198,
9,
1279,
20608,
29,
8999,
11,
14631,
23159,
25,
317... | 2.057269 | 908 |
<reponame>UnofficialJuliaMirror/AWSSDK.jl-0d499d91-6ae5-5d63-9313-12987b87d5ad
#==============================================================================#
# Athena.jl
#
# This file is generated from:
# https://github.com/aws/aws-sdk-js/blob/master/apis/athena-2017-05-18.normal.json
#===============================... | [
27,
7856,
261,
480,
29,
3118,
16841,
16980,
544,
27453,
1472,
14,
12298,
5432,
48510,
13,
20362,
12,
15,
67,
28324,
67,
6420,
12,
21,
3609,
20,
12,
20,
67,
5066,
12,
6052,
1485,
12,
1065,
44183,
65,
5774,
67,
20,
324,
198,
2,
23... | 3.112891 | 5,368 |
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