content stringlengths 6 1.03M | input_ids listlengths 4 535k | ratio_char_token float64 0.68 8.61 | token_count int64 4 535k |
|---|---|---|---|
for testscen in 1:2
valdir, scenario, use_permafrost, use_seaice = get_scenario(testscen)
println(scenario)
m = test_page_model()
include("../src/components/RCPSSPScenario.jl")
include("../src/components/CH4emissions.jl")
scenario = addrcpsspscenario(m, scenario)
ch4emit = add_comp!(m, ch4... | [
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3... | 2.470414 | 338 |
using AutoML
using Base.Test
# write your own tests here
@test 1 == 1
include("evaluation/mlogloss.jl")
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push!(LOAD_PATH, "/Users/czhang/Desktop/Projects/dw_/julialib/")
import DimmWitted
DimmWitted.set_libpath("/Users/czhang/Desktop/Projects/dw_/libdw_julia")
######################################
# The following piece of code creates a
# synthetic data set:
# - Data type is Cdouble
# - Modle type is Array{Cdoubl... | [
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<filename>src/generic/state.jl
"Generic PDDL state description."
mutable struct GenericState <: State
types::Set{Compound} # Object type declarations
facts::Set{Term} # Boolean-valued fluents
values::Dict{Symbol,Any} # All other fluents
end
GenericState(types) = GenericState(types, Set{Term}(), Dict{Symbol... | [
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<reponame>jmmshn/LeetCode.jl
# ---
# title: 675. Cut Off Trees for Golf Event
# id: problem675
# author: <NAME>
# date: 2020-10-31
# difficulty: Hard
# categories: Breadth-first Search
# link: <https://leetcode.com/problems/cut-off-trees-for-golf-event/description/>
# hidden: true
# ---
#
# You are asked to cut off al... | [
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<gh_stars>1-10
function kerker_mix(res, mixOpts::kerkerMixOptions)
#The Kerker mixing, following the parameter setup of elliptic
#preconditioner.
#
#<NAME>
#Last revision: 5/6/2012
return kerker_mix(res, mixOpts.KerkerB, mixOpts.kmult,
mixOpts.YukawaK, mixOpts.epsil0)
end
function kerker_mi... | [
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mutable struct WishartStatXMLElement <: MyXMLElement
el::XMLOrNothing
traitLikelihood_el::TraitLikelihoodXMLElement
rm_el::Union{Nothing, RepeatedMeasuresXMLElement}
mbd_el::Union{Nothing, MBDXMLElement}
function WishartStatXMLElement(like_el::TraitLikelihoodXMLElement,
mbd_el::MBDX... | [
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2538,... | 2.132413 | 1,956 |
<reponame>dataScienceToolKit/NextGP.jl<filename>src/runTime.jl
using StatsModels: AbstractTerm
struct RandTerm <: AbstractTerm
var::Char
data::Char
end
ran(s::Char, d::Char) = RandTerm(s, d)
struct PartRegTerm <: AbstractTerm
mat::Char
regSize::Int
path::String
end
PR(s::Char, d::Int, p::String)... | [
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<filename>src/02_commands/03_Navigation/02_Get_Current_URL.jl
# Command: Get Current URL
"""
current_url(session::Session)::String
Get Current URL.
"""
function current_url(session::Session)::String
@unpack addr, id = session
response = HTTP.get("$addr/session/$id/url", [("Content-Type" => "application/json")... | [
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# Copyright (c) 2017: <NAME> and contributors
# Copyright (c) 2017: Google Inc.
#
# Use of this source code is governed by an MIT-style license that can be found
# in the LICENSE.md file or at https://opensource.org/licenses/MIT.
using Test
# This file gets called first. It it doesn't crash, all is well.
include("iss... | [
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<filename>src/findfonts.jl
if Sys.isapple()
function _font_paths()
[
"/Library/Fonts", # Additional fonts that can be used by all users. This is generally where fonts go if they are to be used by other applications.
joinpath(homedir(), "Library/Fonts"), # Fonts specific to each user... | [
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220,... | 2.155866 | 1,790 |
<gh_stars>0
include("config.jl")
println("evalon=$evalon")
include("gtest1.jl")
abc()
| [
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<reponame>davidanthoff/SASLib.jl<filename>src/tables.jl<gh_stars>0
Tables.istable(::Type{<:ResultSet}) = true
Tables.rowaccess(::Type{<:ResultSet}) = true
Tables.columnaccess(::Type{<:ResultSet}) = true
Tables.rows(rs::ResultSet) = rs
Tables.columns(rs::ResultSet) = rs
Tables.schema(rs::ResultSet) = Tables.Schema(na... | [
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<filename>src/partitioning/variable.jl
# ------------------------------------------------------------------
# Licensed under the MIT License. See LICENSE in the project root.
# ------------------------------------------------------------------
"""
VariablePartition(var)
A method for partitioning spatial data into... | [
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... | 3.256 | 375 |
<reponame>McCannLab/spatial_fingerprints<filename>inst/julia/main2.jl
include("scripts.jl")
function scr_ml(ARGS)
# PARSING ARGUMENTS
id_scr = parse(Int32, ARGS[1])
# number of biotracers
n_bio = parse(Int64, ARGS[2])
# number of indiv used for building distribution
n_distr = parse(Int64, ARG... | [
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8... | 2.009721 | 823 |
<reponame>jmboehm/Douglass.jl
# douglass.jl
# Todo implement for first version:
#
# @gen is probably suffering from type instability
# @egen is still really crap. It should expect a type (e.g. `egen Float64 :x = ...`)
# Nice to have, but not necessary for first version:
# assert <condition>
# collapse (<statistic>) <... | [
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... | 3.03551 | 873 |
<filename>src/stepsize_controllers.jl
function stepsize_controller!(integrator::SDDEIntegrator, controller::PIController, alg)
integrator.q11 = DiffEqBase.value(DiffEqBase.fastpow(integrator.EEst,controller.beta1))
integrator.q = DiffEqBase.value(integrator.q11/DiffEqBase.fastpow(integrator.qold,controller.beta2))... | [
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const branin = let res_init=zeros(2), jac_init=zeros(2,2), x_init=[2.0, 0.0]
function res(x, r)
r[1] = 4.0 * (x[1] + x[2])
r[2] = r[1] + (x[1] - x[2]) * ((x[1] - 2.0) ^ 2 + x[2] ^ 2 - 1.0)
return r
end
function jac(x, jac)
jac[1, 1] = 4.0
jac[1, 2] = 4.0
jac... | [
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87... | 1.45611 | 581 |
<gh_stars>1-10
# This file is a part of NeighborhoodApproximationIndex.jl
using Test, SimilaritySearch, InvertedFiles, LinearAlgebra, UnicodePlots
function runtest(; dim, n, m,
numcenters=5ceil(Int, sqrt(n)), k=10, centersrecall=0.95, kbuild=1, ksearch=1,
parallel_block=1000, ordering=DistanceOrdering(), minr... | [
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17... | 2.621764 | 1,893 |
<reponame>UnofficialJuliaMirrorSnapshots/CircularList.jl-e1d4a2be-69cc-597c-a2ea-cc5d6f241fff<gh_stars>1-10
using CircularList
using Test
@testset "CircularList.jl" begin
# general/peek
CL = circularlist(0)
@test length(CL) == 1
@test current(CL) == previous(CL)
@test current(CL) == next(CL)
... | [
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<filename>test/test_model_structure.jl
module TestModelStructure
# tests the framework of components and connections
using Test
using Mimi
import Mimi:
connect_param!, unconnected_params, set_dimension!, build,
get_connections, internal_param_conns, dim_count, dim_names,
modeldef, modelinstance, compde... | [
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2... | 2.455603 | 1,633 |
# This file is auto-generated by AWSMetadata.jl
using AWS
using AWS.AWSServices: amplifyuibuilder
using AWS.Compat
using AWS.UUIDs
"""
create_component(app_id, component_to_create, environment_name)
create_component(app_id, component_to_create, environment_name, params::Dict{String,<:Any})
Creates a new compo... | [
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... | 2.493786 | 7,242 |
export subalgebra, decompose, radical, is_central, is_simple
_base_ring(A::AbsAlgAss) = base_ring(A)
################################################################################
#
# Morphism types
#
################################################################################
morphism_type(::Type{T}, ::Type{... | [
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2... | 2.221879 | 17,469 |
function test_cat()
ϵ = eps(Float64)
rtol = sqrt(ϵ)
@testset ExtendedTestSet "Concatenation" begin
A = simple_sparse_matrix(Float64, 100, 100)
B = simple_matrix(Float64, 100, 10)
C = simple_matrix(Float64, 100, 90)
D = [A B C]
Ao = LinearOperator(A)
Bo = LinearOperator(B)
Co = LinearOp... | [
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# # How to Make a bar plot
# See [How to set up plots](3.0_set_up_plots.md) to get started
# ```julia
# using PowerGraphics
# const PG = PowerGraphics
# ```
# ### Make bar plots of results
# ```julia
# bar_plot(results)
# ```
# 
#  2020, UChicago Argonne, LLC. All rights reserved.
# Released under the modified BSD license. See COPYING.md for more details.
using UnitCommitment, Test, LinearAlgebra
import UnitCommitment: _Violation, _offer, _query
@... | [
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739,... | 2.440644 | 497 |
# Borrowed from Zygote tests
function ngradient(f, xs::AbstractArray...)
grads = zero.(xs)
for (x, Δ) in zip(xs, grads), i = 1:length(x)
δ = sqrt(eps())
tmp = x[i]
x[i] = tmp - δ / 2
y1 = f(xs...)
x[i] = tmp + δ / 2
y2 = f(xs...)
x[i] = tmp
Δ[i] = ... | [
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37455,
8,
287,... | 1.919255 | 322 |
using Documenter, CSV
makedocs(modules = [CSV], sitename = "CSV.jl", format = Documenter.HTML(canonical = "https://juliadata.github.io/CSV.jl/stable/"))
deploydocs(repo = "github.com/JuliaData/CSV.jl.git")
| [
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11,
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198,
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76,
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796,
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7902,
53,
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263,
13,
28656,
7,
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605,
796,
366,
5450,
1378,
73,
32176,
14706,... | 2.536585 | 82 |
# This file is for Simulation object.
"""
Simulation(model; simdir=tempdir(), simname=string(uuid4()), simprefix="Simulation-", logger=SimpleLogger())
Constructs a `Simulation` object for the simulation of `model`. The `Simulation` object is used to monitor the state of the simulation of the `model`. `simdir` is ... | [
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985,
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12,
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49706... | 2.812912 | 1,518 |
<reponame>jonas-schulze/julia
# This file is a part of Julia. License is MIT: https://julialang.org/license
# script to generate tables of common symbols
# steps to rerun this:
# 1. empty the contents of common_symbols*.inc
# 2. build
# 3. cd src && ../julia --depwarn=no gen_sysimg_symtab.jl
import Base.Iterato... | [
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... | 1.836717 | 1,133 |
<reponame>qlete/markov-decision
export simulate, simulate_k, oneturn
include("traps.jl")
"""
simulate(list, dice, circular)
Returns the cost (number of dice throws) of a
a complete simulation of a Snakes and Ladders game, meaning
it starts at square 1, with a board disposition described
in `list`, a dice strateg... | [
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4943,
198,
198,
37811,
198,
220,
220,
220,
29308,
7,
4868,
11,... | 2.702335 | 1,028 |
<gh_stars>1-10
# This script checks sparse arrays can be used as caches for Γ₅, Γ₆, Λ_sss, and Σ_sss
using BenchmarkTools, RiskAdjustedLinearizations, Test
include(joinpath(dirname(@__FILE__), "..", "..", "examples", "rbc_cc", "rbc_cc.jl"))
include(joinpath(dirname(@__FILE__), "..", "..", "examples", "crw", "crw.jl"))
... | [
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19... | 2.019915 | 703 |
# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
@doc raw"""LimitRangeSpec defines a min/max usage limit for resources that match on kind.
IoK8sApiCoreV1LimitRangeSpec(;
limits=nothing,
)
- limits::Vector{... | [
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257,
949,
14... | 2.697531 | 648 |
<reponame>BradyPlanden/LiBRA<gh_stars>1-10
@inline function Phi_s(Cell,s,z,Def,ϕ_tf,D,res0)
"""
Solid Potential Transfer Function
Phi_s(Cell,s,z,Def)
"""
if Def == "Pos"
Electrode = Cell.Pos #Electrode Length
else
Electrode = Cell.Neg #Electrode Length
end
κ_eff = Cell.Const.κ*Electrode... | [
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11,
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62,
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11,
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... | 1.947214 | 1,023 |
import JuMP
import Ipopt
import Zygote
using JuMP: @variable, @constraint, @objective
using PartiallyObservedInverseGames.ForwardGame: IBRGameSolver, KKTGameSolver, solve_game
using PartiallyObservedInverseGames.InverseGames: InverseKKTConstraintSolver, solve_inverse_game
using PartiallyObservedInverseGames.Trajectory... | [
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3974... | 2.047469 | 2,865 |
<reponame>danielzhaotongliu/MALTrendsWeb
{"score_count": 205723, "timestamp": 1565469104.0, "score": 7.54}
{"score_count": 205461, "timestamp": 1564796520.0, "score": 7.54}
{"score_count": 205461, "timestamp": 1564455261.0, "score": 7.54}
{"score_count": 204221, "timestamp": 1562190541.0, "score": 7.54}
{"score_count":... | [
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1298,
1315,
39111,
3388,
13464,
13,
15,
11,
366,
26675,
1298... | 2.393187 | 6,165 |
include("try.jl")
# solvers_list = [:Mosek, :Ipopt, :Knitro_Ip, :Knitro_IpCG, :Knitro_AS, :Knitro_SQP, :Cvxopt]
solvers_list = [:Mosek]
tmpFloatDatatype = Float64
list= String[]
for i in 1:5
push!(list, "../PDFs/Data/gauss-$i")
end
size =[1,0.75,0.5,0.4]
list_instances=String[]
for l in 1:length(list)
for... | [
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270,
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62,
40,
79,
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11,
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25095,
270,... | 2.478261 | 368 |
<filename>src/diffusion.jl
"""
lp(s, x, t, y, P)
Log-transition density, shorthand for `logpdf(transitionprob(s,x,t,P),y)`.
"""
lp(s, x, t, y, P) = logpdf(transitionprob(s,x,t,P),y)
"""
llikelihood(X::SamplePath, P::ContinuousTimeProcess)
Log-likelihood of observations `X` using transition density `lp`.
""... | [
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653,
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11,
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329,
4600,
6404,
12315,
7,
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65... | 2.049201 | 1,565 |
export SimplexExact, transferoperator
"""
SimplexExact() <: TriangulationBasedTransferOperator
A transfer operator estimator using a triangulation partition and exact
simplex intersections[^Diego2019].
To use this estimator, the Simplices.jl
package must be brought into scope by doing `using Simplices` after ... | [
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257,
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1741,
... | 2.465731 | 1,211 |
<gh_stars>1-10
# src/crypto.jl
# Cryptocurrency Wallet Extras
export AbstractPublicKey,
keypairs,
privatekey,
AbstractDeterministicWallet,
rootkey,
mnemonic,
seed,
next_keypair!,
next_address!
"""```
AbstractPublicKey <: AbstractAddress
```
Public Keys for Wall... | [
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220,
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79,
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11,
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220,
220,
... | 3.209205 | 717 |
<gh_stars>0
function codegen end
include("utils.jl")
include("emulation.jl")
include("qasm.jl")
include("qobj.jl")
| [
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17256,
7203,
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13,
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... | 2.636364 | 44 |
module Docker
using AWS
using ..ECR
export login, pull, push, build
"""
login(registry_id::Union{AbstractString, Integer}="")
Gets the AWS ECR authorization token and runs the corresponding docker login command.
Takes an optional AWS `config` keyword argument or uses the default.
"""
function login(
registr... | [
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198,
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49,
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198,
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7,
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62,
312,
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90,
23839,
10100,
11,
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92,
... | 2.938215 | 437 |
<filename>src/render.jl
# Open a URL in a browser
# function openurl(url::AbstractString)
# @static if is_apple() run(`open $url`) end
# @static if is_windows() run(`cmd /c start $url`) end
# @static if is_linux() run(`xdg-open $url`) end
# end
#
#Convenience method for getting Vega JSON
print(x::VegaVis... | [
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2,
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7,
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8,
198,
2,
220,
220,
220,
220,
2488,
12708,
611,
318,
62,
18040,
3419,
1057,
7,
63,
9654,... | 2.008273 | 967 |
## AbstractTrees interface
AbstractTrees.children(node::Node) = node.foldchildren ? typeof(node)[] : node.children
AbstractTrees.printnode(io::IO, node::Node) = print(io, node.foldchildren ? "+ " : " ", node.data)
| [
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7,
... | 3.056338 | 71 |
<reponame>JuliaAstrodynamics/Orekit.jl
module MomentWrapper
using JavaCall
const AbstractStorelessUnivariateStatistic = @jimport org.hipparchus.stat.descriptive.AbstractStorelessUnivariateStatistic
const AbstractUnivariateStatistic = @jimport org.hipparchus.stat.descriptive.AbstractUnivariateStatistic
const Aggregata... | [
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8... | 3.136216 | 925 |
<filename>src/Session/utils.jl
function get_stream(connection::HTTPConnection, stream_identifier::UInt32)
@assert stream_identifier != 0x0
for stream in connection.streams
if stream.stream_identifier == stream_identifier
return stream
end
end
stream = HTTPStream(stream_iden... | [
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87,
... | 2.666261 | 821 |
# Unit signalProcessing.jl, part of PosDefManifold Package for julia language
# v 0.3.5 - last update 6th of November 2019
#
# MIT License
# Copyright (c) 2019, <NAME>, CNRS, Grenobe, France:
# https://sites.google.com/site/marcocongedo/home
#
# DESCRIPTION
# This Unit implements Signal Processing m... | [
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198,
2,
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... | 2.233161 | 6,785 |
<reponame>ctrekker/PropositionalLogic.jl<gh_stars>1-10
export ¬, ∧, ∨, →, ⟷
export AbstractExpression, LogicalSymbol, LogicalExpression, istree, isnode, name, metadata, variables, operation, operations, arguments, parents, left, right, isassociative, iscommutative
export isunary, isbinary, argument_count
export @symbol... | [
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198,
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27741,
1... | 2.907614 | 6,278 |
<reponame>Mattriks/GeoStatsBase.jl
# ------------------------------------------------------------------
# Licensed under the MIT License. See LICENSE in the project root.
# ------------------------------------------------------------------
"""
RegularGrid(dims, origin, spacing)
A regular grid with dimensions `dim... | [
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220... | 2.565453 | 1,291 |
<filename>plotting/chunlok/plot_reproduce_state_visitation_heatmap.jl
using Plots
using Reproduce
using JLD2
using FileIO
using Statistics
using ProgressMeter
include("plot_utils.jl")
previous_GKSwstype = get(ENV, "GKSwstype", "")
ENV["GKSwstype"] = "100"
save_file = "plotting/chunlok/generated_plots/state_vistation... | [
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... | 2.443439 | 663 |
#=
Code for simulating, visualizing and manipulating *scalar* additive and
multiplicative functionals.
@authors: <NAME>
=#
using QuantEcon
"""
This type and method are written to transform a scalar additive functional
into a linear state space system.
"""
type AMF_LSS_VAR{TR<:Real}
A::TR
B::... | [
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19... | 1.981205 | 1,543 |
<gh_stars>10-100
include("Type/Type.jl") | [
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<filename>src/TimeModeling/Modeling/distributed.jl
_parallel_functions = [:time_modeling, :fwi_objective, :twri_objective, :extended_source_modeling, :lsrtm_objective]
# Shot and experiment parallelism
for func in _parallel_functions
@eval $func(args...; kwargs...) = task_distributed($func, _worker_pool(), args...;... | [
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1525... | 2.663236 | 3,109 |
<gh_stars>0
# This file was generated by the Julia Swagger Code Generator
# Do not modify this file directly. Modify the swagger specification instead.
mutable struct IoK8sApiCoreV1ServicePort <: SwaggerModel
name::Any # spec type: Union{ Nothing, String } # spec name: name
nodePort::Any # spec type: Union{ ... | [
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... | 2.719665 | 956 |
<gh_stars>100-1000
@inline function _colorediteration!(J,sparsity,rows_index,cols_index,vfx,colorvec,color_i,ncols)
@inbounds for i in 1:length(cols_index)
if colorvec[cols_index[i]] == color_i
J[rows_index[i],cols_index[i]] = vfx[rows_index[i]]
end
end
end
@inline function ... | [
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... | 1.704679 | 3,569 |
"""
Upper triangular and lower triangular matrices are the same views of the underlying data.
Upper triangular matrices are column major, and lower triangular row major.
As an implementation detail, indexing with @inbounds into the 0-triangle (ie, lower triangle of an Upper Triangular matrix) is undefined. This is bec... | [
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mutable struct KalmanFilter <: AbstractEstimator
belief_::MvNormal{Float64}
motion_noise_stds::Dict{String,Float64}
distance_dev_rate::Float64
direction_dev::Float64
pose_::Vector{Float64}
map_::Map
function KalmanFilter(
envmap::Map,
initial_pose::Vector{Float64},
mo... | [
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35,
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11,
4... | 1.810234 | 2,482 |
<reponame>andreasvarga/PeriodicSystems.jl<filename>test/test_psutils.jl
module Test_psutils
using PeriodicSystems
using DescriptorSystems
using Symbolics
using Test
using LinearAlgebra
using LinearAlgebra: BlasInt
using ApproxFun
#using BenchmarkTools
println("Test_psutils")
@testset "test_psutils" begin
# MB03BD... | [
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35... | 1.99958 | 14,284 |
# # RNN Character level
# In this example, we create a character-level recurrent neural network.
# A recurrent neural network (RNN) outputs a prediction and a hidden state at each step
# of the computation. The hidden state captures historical information of a sequence
# (i.e. the neural network has memory) and the... | [
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257,
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1123,
... | 3.015371 | 2,342 |
<reponame>UnofficialJuliaMirror/AIControl.jl-3868d828-178d-56af-83e1-d523478a73cd<gh_stars>10-100
using GZip
import Base: eof, close, position
export BamReader, close, value, eof, advance!, eachposition
mutable struct BamReader
bamStream
readOrientation #useReverseReads::Bool
done::Bool
position::Int6... | [
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... | 2.353069 | 1,385 |
function update!(cur_reactor::AbstractReactor)
if !cur_reactor.is_good
_NanizeReactor!(cur_reactor)
return cur_reactor
end
cur_reactor.sigma_v = calc_sigma_v(cur_reactor)
secondary_constraint = getfield(Fussy, Symbol("$(cur_reactor.constraint)_equation"))(cur_reactor)
cur_equation_set = EquationSe... | [
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220,
... | 2.199566 | 1,383 |
export TimeBasedSampleModel
import StatsBase: sample
"""
TimeBasedSampleModel(nactions::Int, κ::Float64 = 1e-4)
"""
mutable struct TimeBasedSampleModel <: AbstractEnvironmentModel
experiences::Dict{
Any,
Dict{Any,NamedTuple{(:reward, :terminal, :nextstate),Tuple{Float64,Bool,Any}}},
}
... | [
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19,
8,
198,
37811,... | 1.924628 | 942 |
<reponame>MasonProtter/ChainRules.jl
@testset "base" begin
@testset "Trig" begin
@testset "Basics" for x = (Float64(π)-0.01, Complex(π, π/2))
test_scalar(sec, x)
test_scalar(csc, x)
test_scalar(cot, x)
test_scalar(sinpi, x)
test_scalar(cospi, x)
... | [
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... | 1.64498 | 2,490 |
using Colors, Test
@test isempty(detect_ambiguities(Colors, Base, Core))
include("algorithms.jl")
include("conversion.jl")
include("colormaps.jl")
include("colordiff.jl")
include("din99.jl")
include("display.jl")
include("parse.jl")
include("utilities.jl")
| [
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... | 2.804348 | 92 |
<filename>test/test_utils.jl
using Test, WAVI
@testset "WAVI tests" begin
@testset "Pos Fraction" begin
@info "testing pos fraction"
z=[-1.0 -1.0 -1.0;-1.0 1.0 -1.0;-1.0 -1.0 -1.0]
pfh,pfu,pfv=WAVI.pos_fraction(z)
@test pfh == [0.0 0.0 0.0;0.0 0.5 0.0;0.0 0.0 0.0]
@test pfu ... | [
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1,
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198,
220,... | 1.833529 | 853 |
<filename>src/contamination/teff_chain2.jl
# Run a chain with:
# 1). T_1, T_2, f with the constraint T_1^4(1-f)+f T_2^4 = T_eff^4 within the uncertainties.
# 2). Fit these to the transit transmission data (assuming an achromatic atmosphere).
# 3). See how much this affects the Spitzer IRAC band inferred depths.
# ... | [
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19,
7,
16,
... | 2.167144 | 3,494 |
# ---
# title: Rotate
# cover: rotate.gif
# description: rotate image anticlockwise
# ---
# The type [`Rotate`](@ref) defines a generic anticlockwise rotation operation around the center
# of the image. It is also possible to pass some abstract vector to the constructor, in which case
# Augmentor will randomly sample ... | [
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... | 2.87037 | 540 |
"""
StaticSymbol
A statically typed `Symbol`.
"""
struct StaticSymbol{s}
StaticSymbol{s}() where {s} = new{s::Symbol}()
StaticSymbol(s::Symbol) = new{s}()
StaticSymbol(x::StaticSymbol) = x
StaticSymbol(x) = StaticSymbol(Symbol(x))
end
StaticSymbol(x, y) = StaticSymbol(Symbol(x, y))
StaticSymbol(x:... | [
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... | 2.372483 | 298 |
<reponame>a2ray/transD_GP<gh_stars>0
using transD_GP.GP, Random, PyPlot, Statistics, LinearAlgebra, PositiveFactorizations
##
Random.seed!(12)
f = 1.0/0.5
t = 0:(100*f)^-1:2/f
ntrain = 1
ntries = 4
λ = [0.1]
δ = 0.01
δtry = 5δ
p = 2
demean = true
findmin = true
switchflag = findmin ? -1. : 1.
knownvalue = NaN
acqfun = ... | [
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11,
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2235... | 1.959614 | 1,139 |
"""
pde_lin_test(n)
Test the linear operators.
"""
function pde_lin_test(n)
h = 1.0 / (n + 1)
x = collect(h:h:1.0-h)
fdata = fishinit(n)
z = rand(n, n)
L2d = Lap2d(n)
DX = Dx2d(n)
DY = Dy2d(n)
lapok = lap_test(n, x, z, L2d, fdata)
discok = disc_test(n, x, L2d, DX, DY, fdata)
lap... | [
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8... | 1.932921 | 969 |
# Note that this script can accept some limited command-line arguments, run
# `julia build_tarballs.jl --help` to see a usage message.
using BinaryBuilder
name = "Opus"
version = v"1.3.1"
# Collection of sources required to build Opus
sources = [
ArchiveSource("https://archive.mozilla.org/pub/opus/opus-$(version)... | [
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257,
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13,
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198,
198,
3672,
796,... | 2.816367 | 501 |
using Test
using ParticleInCell
@testset "ParticleMeshCoupling 2D" begin
n_cells = 10 # Number of cells
n_particles = 4 # Number of particles
spline_degree = 3 # Spline degree
xmin, xmax, nx = 0.0, 2.0, n_cells
ymin, ymax, ny = 0.0, 1.0, n_cells
mesh = TwoDGrid(xmin, xmax, nx, ymin, ymax, ny)... | [
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3... | 1.752448 | 2,145 |
<filename>test/AtomixTests/src/AtomixTests.jl
module AtomixTests
include("test_core.jl")
include("test_sugar.jl")
include("test_doctest.jl")
if VERSION >= v"1.7"
include("test_fallback.jl")
end
end # module AtomixTests
| [
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... | 2.389474 | 95 |
<gh_stars>1-10
module NamedAxesArrays
import Base: eltype, getindex, ndims, setindex!
immutable NamedAxesArray{T,N,A<:AbstractArray,axisnames<:(Symbol...)} <: AbstractArray{T,N}
data::A
end
NamedAxesArray{T,N}(A::AbstractArray{T,N}, axisnames::NTuple{N,Symbol}) = NamedAxes{T,N,typeof(A),axisnames}(A)
eltype{T... | [
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... | 2.209235 | 1,386 |
__precompile__(true)
module Baz
import Foo, Qux
this = "Baz"
end
| [
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1,
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198
] | 2.407407 | 27 |
function init_constraint_struct(com, ::GeqSetInternal, internals)
GeqSetConstraint(internals, internals.indices[1], internals.indices[2:end], [])
end
"""
init_constraint!(com::CS.CoM, constraint::GeqSetConstraint, fct::MOI.VectorOfVariables, set::GeqSetInternal)
Initialize the GeqSetConstraint by filling `sub... | [
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... | 2.370781 | 2,163 |
export Structure, Atom, Pseudo, DFTU
#Units exported
export Ang, e₀, kₑ, a₀, Eₕ, Ry
include("inputAPI.jl")
export DFInput
#Basic Interaction with DFInputs
export flag, setflags!, rmflags!, data, setdata!, setdataoption!, exec, execs,
setexecflags!, rmexecflags!, setexecdir!, runcommand, outputdata
#Extended I... | [
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... | 3.131799 | 478 |
<filename>src/models.jl<gh_stars>0
"""
A `RateModel` contains the parameters to calculate the contribution of a
growth or stress factor to the overall population growth rate.
A [`rate`](@ref) method corresponding to the model type must be defined specifying
the formulation, and optionally a [`condition`](@ref) method... | [
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2... | 3.21013 | 2,389 |
# - LOAD SYSTEM PACKAGES ------------------------------------------------------- #
using HTTP
# ------------------------------------------------------------------------------ #
# constants -
const path_to_package = dirname(pathof(@__MODULE__))
# - LOCAL FILES ----------------------------------------------------------... | [
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24212... | 5.316327 | 98 |
# Interval
# ========
#
# Base interval types and utilities.
#
# This file is a part of BioJulia.
# License is MIT: https://github.com/BioJulia/Bio.jl/blob/master/LICENSE.md
# Note, just to be clear: this shadows IntervalTrees.Interval
"A genomic interval specifies interval with some associated metadata"
struct Interv... | [
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12567,
13,
785,
14,
42787,
... | 2.613173 | 1,913 |
<reponame>Yoshinobu-Ishizaki/StatsWithJuliaBook
using Flux, MLDatasets, Statistics, Random, BSON
using Flux.Optimise: update!
using Flux: logitbinarycrossentropy
batchSize, latentDim = 500, 100
epochs = 40
etaD, etaG = 0.0002, 0.0002
images, _ = MLDatasets.MNIST.traindata(Float32)
imageTensor = reshape(@.(2f0 * image... | [
27,
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198,
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1610,
2821,
13,
27871,... | 2.025424 | 1,062 |
<reponame>bbejanov/StateSpaceEcon.jl
##################################################################################
# This file is part of StateSpaceEcon.jl
# BSD 3-Clause License
# Copyright (c) 2020-2022, Bank of Canada
# All rights reserved.
#######################################################################... | [
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682,
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... | 2.428517 | 2,602 |
<gh_stars>1-10
## ExoplanetsSysSim/src/mission_constants.jl
## (c) 2015 <NAME>
#module KeplerConstants
const num_channels = 84
const num_modules = 42
const num_quarters = 17 # QUERY: I'm favoring leaving out quarter 0, since that was engineering data. Agree?
const cdpp_durations = [1.5,2.,2.5,3.,3.5... | [
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29,
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29,
198,
198,
2,
21412,
40294,
34184,
1187,
198,
1500,
997,
... | 2.438267 | 1,223 |
using Pkg, DelimitedFiles, MPIReco
# Install required packages
for P in [:HTTP,:TensorDecompositions, :PyPlot]
try
@eval using $P
catch
Pkg.add(String(P))
@eval using $P
end
end
# Download data
include("downloadData.jl")
include("./utils/subsampling.jl")
include("./utils/FRTruncation.jl")
# load system... | [
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10707,
296,
1930,
1756,
11,
1058,
20519,
43328,
60,
198,
1949,
220,
198,
22... | 2.144888 | 1,477 |
<reponame>TartuQC/ClangARGH.jl
using Clang
using Clang.LibClang
using Test
@testset "typedef" begin
trans_unit = parse_header(joinpath(@__DIR__, "c", "typedef.h"))
ctx = DefaultContext()
push!(ctx.trans_units, trans_unit)
# get root cursor
root_cursor = getcursor(trans_unit)
cursors = children... | [
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198,
198,
31,
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2617,
366,
774,
9124,
891,
1,
2221,
198,
... | 2.304463 | 2,263 |
<reponame>KristofferC/FinEtools.jl
module NAFEMS_examples
using FinEtools
using FinEtools
using FinEtools.AlgoDeforLinearModule: ssit
function NAFEMS_FV32_algo()
println("""
FV32: Cantilevered tapered membrane
This is a test recommended by the National Agency for Finite Element Methods and
Standards (U... | [
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261,
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29,
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399,
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36,
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198,
3500,
4463,
36,
31391,
198,
3500,
4463,
36,
31391,
13,
2348,
2188,
7469,
273,
... | 2.156755 | 2,724 |
<filename>src/algorithms.jl
"""
```
normals{VT,FD,FT,FO}(vertices::Vector{Point{3, VT}},
faces::Vector{Face{FD,FT,FO}},
NT = Normal{3, VT})
```
Compute all vertex normals.
"""
function normals{VT,FD,FT,FO}(vertices::Vector{Point{3, VT}},
faces:... | [
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29,
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14,
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38469,
90,
12727,
90,
18,
11,
32751,
92,
5512,
198,
220,
220,
220... | 1.873418 | 474 |
using JuMP, EAGO
m = Model()
EAGO.register_eago_operators!(m)
@variable(m, -1 <= x[i=1:2] <= 1)
@variable(m, -2.8031108847289734 <= q <= 2.6473335630382056)
add_NL_constraint(m, :(sigmoid(-0.8475658981369358 + ... | [
3500,
12585,
7378,
11,
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4760,
46,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
285,
796,
9104,
3419,
628,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220,
220... | 1.54717 | 371 |
module ArtifactHelpers
using Pkg
using Pkg.Artifacts
using Pkg.PlatformEngines #Note: supplies unpack.
using Pkg.BinaryPlatforms
using SHA
using Downloads: download
using ZipFile
import Base: SHA1
export
File, AutoDownloadable, Zip, Processed,
build_artifact!, initialise_artifact, setup
const AUTODOWNLOADA... | [
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350,
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198,
3500,
350,
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13,
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198,
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350,
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13,
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7936,
1127,
1303,
6425,
25,
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555,
8002,
13,
198,
3500,
350,
10025,
13,
33,
3219,
37148,
82,
198,
35... | 2.757153 | 5,872 |
<filename>test/core.jl
function gen_dist(scl=5, nvars=2, nmix=nv)
Product([MixtureModel([Normal(scl*rand(), scl*rand()) for _ in 1:nmix]) for _ in 1:nvars])
end
| [
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44,
9602,
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26933,
26447,
7,
38528,
9,
25192,
... | 2.391304 | 69 |
<gh_stars>1-10
_scip = JuMP.optimizer_with_attributes(SCIP.Optimizer, "display/verblevel" => 0)
_glpk = GLPK.Optimizer
@testset "solve master problem: ground structure, discrete diameters" begin
# 7 9 even arc numbers for
# () - d2 - () reversed arcs
# /1 /3 /5
# s1 - () - d1
... | [
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14,
332,
903,
626,
1,
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657,
8,
198,
62,
4743,
79,
... | 1.889791 | 8,992 |
<gh_stars>1-10
import Base: @propagate_inbounds,getindex, setindex!,iterate,size,length,push!,
collect,view
export BodyList, getrange, numpts
struct BodyList
list :: Vector{Body}
end
BodyList() = BodyList(Body[])
@propagate_inbounds getindex(A::BodyList, i::Int) = A.list[i]
@propagate_inbounds set... | [
27,
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62,
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29,
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65,
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900,
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11,
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11,
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28265,
198,
220,
220,
220,
220,
220,
220,
220,
220,... | 2.527313 | 897 |
<reponame>terasakisatoshi/Gomagorithm.jl
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .jl
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.5.2
# kernelspec:
# display_name: Julia 1.5.0-rc2
# language: julia
# name: julia-1.5
# ---
"""
... | [
27,
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261,
480,
29,
353,
292,
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265,
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14,
38,
296,
363,
273,
342,
76,
13,
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198,
2,
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198,
2,
474,
929,
88,
353,
25,
198,
2,
220,
220,
474,
929,
88,
5239,
25,
198,
2,
220,
220,
220,
220,
2420,
62,
15... | 2.132159 | 908 |
<reponame>GediminasA/st16Sseqanalysis
function run()
out="Zymo1-2X-65C_S6_contigs.fasta"
ref="rRNA_ampl_1500Genomic.fasta"
mapf = "map"
#read names mapping
text=read(open(ref,"r"),String)
f=open(mapf,"r")
ct = 0
for l in readlines(mapf)
o,r = split(l)
text = replace(text,... | [
27,
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261,
480,
29,
38,
276,
320,
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32,
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220,
220,
220,
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78,
16,
12,
17,
55,
12,
2996,
34,
62,
50,
21,
62,
3642,
9235,
13,
7217,
64,
1,
... | 1.915493 | 213 |
<reponame>maeckha/Oceananigans.jl<filename>benchmark/benchmark_time_steppers.jl
push!(LOAD_PATH, joinpath(@__DIR__, ".."))
using BenchmarkTools
using CUDA
using Oceananigans
using Benchmarks
# Benchmark function
function benchmark_time_stepper(Arch, N, TimeStepper)
grid = RegularRectilinearGrid(size=(N, N, N), e... | [
27,
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261,
480,
29,
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68,
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29,
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4102,
14,
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62,
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62,
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13,
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198,
14689,
0,
7,
35613,
62,
34219,
11,
4654,
6978,
7,
31,
834,
3472... | 2.722222 | 576 |
using ScikitLearn
@sk_import datasets: make_moons
@sk_import datasets: make_circles
@sk_import datasets: make_blobs
@sk_import datasets: make_s_curve
function generate_data_A(n_inlier = 300, n_outlier = 35)
inliers = make_moons(n_inlier, true, 0.1, random_state=seed)[1]'
out_tmp = make_blobs(n_outlier, n_feat... | [
3500,
10286,
15813,
20238,
198,
198,
31,
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62,
11748,
40522,
25,
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62,
5908,
684,
198,
31,
8135,
62,
11748,
40522,
25,
787,
62,
66,
343,
5427,
198,
31,
8135,
62,
11748,
40522,
25,
787,
62,
2436,
8158,
198,
31,
8135,
62,
117... | 2.286371 | 653 |
using Arblib
"""
parse_arbdoc(filename)
Parse a .rst file from the Arb documentation. Returns the title of the
document together with a list of sections with their titles and the
functions documented in them.
"""
function parse_arbdoc(filename)
return open(filename) do file
lines = readlines(file)
... | [
3500,
943,
2436,
571,
198,
198,
37811,
198,
220,
220,
220,
21136,
62,
38039,
15390,
7,
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8,
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325,
257,
764,
81,
301,
2393,
422,
262,
943,
65,
10314,
13,
16409,
262,
3670,
286,
262,
198,
22897,
1978,
351,
257,
1351,
... | 2.0953 | 3,851 |
using IL_simulations, PDBTools
top_dir = "/home/viniciusp/Documents/doutorado/ANALYSE/Repository/IL_simulations.jl/VSIL/ITP"
pdb_dir = "/home/viniciusp/Documents/doutorado/ANALYSE/Repository/IL_simulations.jl/VSIL/PDB"
input_dir = "/home/viniciusp/Documents/doutorado/ANALYSE/Repository/IL_simulations.jl/u... | [
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62,
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220,
220,
220,
220,
796,
220,
12813,
11195,
14,
7114,
291,
3754,
79,
14,
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14,
67,
448,
273,
4533,
14,
1565,
1847,
56,
5188,
14,
6207,
13264,
14,
... | 2.182438 | 1,321 |
# Note: none of the cross validation tests precise numbers. This is because
# random number generation can be different with Julia versions even if we
# set the seed. AKA I don't know any good way of ensuring continuous integration
@testset "Cross validation on SnpLinAlg, normal model" begin
#simulat data with k ... | [
2,
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25,
4844,
286,
262,
3272,
21201,
5254,
7141,
3146,
13,
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318,
780,
198,
2,
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1271,
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460,
307,
1180,
351,
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611,
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198,
2,
900,
262,
9403,
13,
15837,
32,
314,
836,
470,
760,
597,
922,
... | 2.330631 | 4,071 |
<reponame>harrymd/NonlinearEigenproblems.jl
using LinearAlgebra
export blocknewton
default_block_errmeasure(nep::NEP) = (S,X) -> opnorm(compute_MM(nep,S,X))
"""
(S,X)=blocknewton(nep [S,] [X,] [errmeasure,] [tol,] [maxit,] [armijo_factor,] [armijo_max,] [logger])
Applies the block Newton method to `nep::Abstrac... | [
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29127,
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29230,
198,
198,
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198,
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62,
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62,
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1326,
5015,
7,
77,
538,
3712,
45,
890... | 1.786835 | 4,208 |
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