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#!/usr/bin/env julia
#
# @license Apache-2.0
#
# Copyright (c) 2018 The Stdlib Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import Distributions: logpdf, NegativeBinomial
import JSON
"""
gen( x, r, p, name )
Generate fixture data and write to file.
# Arguments
* `x`: input value
* `r`: number of successes until experiment is stopped
* `p`: success probability
* `name::AbstractString`: output filename
# Examples
``` julia
julia> x = rand( 1000 ) .* 15;
julia> r = round.( rand( 1000 ) .* 20 );
julia> p = rand( 1000 );
julia> gen( x, r, p, "data.json" );
```
"""
function gen( x, r, p, name )
z = Array{Float64}( undef, length(x) );
for i in eachindex(x)
z[ i ] = logpdf( NegativeBinomial( r[i], p[i] ), x[i] );
end
# Store data to be written to file as a collection:
data = Dict([
("x", x),
("r", r),
("p", p),
("expected", z)
]);
# Based on the script directory, create an output filepath:
filepath = joinpath( dir, name );
# Write the data to the output filepath as JSON:
outfile = open( filepath, "w" );
write( outfile, JSON.json(data) );
close( outfile );
end
# Get the filename:
file = @__FILE__;
# Extract the directory in which this file resides:
dir = dirname( file );
# Random (small r, small p):
x = round.( rand( 1000 ) .* 15 );
r = round.( ( rand( 1000 ) .* 20 ) .+ 0.5 );
p = rand( 1000 ) .* 0.2;
gen( x, r, p, "small_small.json" );
# Random (small r, high p):
x = round.( rand( 1000 ) .* 15 );
r = round.( ( rand( 1000 ) .* 20 ) .+ 0.5 );
p = ( rand( 1000 ) .* 0.25 ) .+ 0.75;
gen( x, r, p, "small_high.json" );
# Random (high r, high p):
x = round.( rand( 1000 ) .* 80 );
r = round.( ( rand( 1000 ) .* 100 ) .+ 0.5 );
p = ( rand( 1000 ) .* 0.25 ) .+ 0.75;
gen( x, r, p, "high_high.json" );
# Random (high r, small p):
x = round.( rand( 1000 ) .* 40 );
r = round.( ( rand( 1000 ) .* 100 ) .+ 0.5 );
p = rand( 1000 ) .* 0.2;
gen( x, r, p, "high_small.json" );
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