/**
* @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.
*/

'use strict';

// MODULES //

var tape = require( 'tape' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var abs = require( '@stdlib/math/base/special/abs' );
var NINF = require( '@stdlib/constants/float64/ninf' );
var PINF = require( '@stdlib/constants/float64/pinf' );
var EPS = require( '@stdlib/constants/float64/eps' );
var factory = require( './../lib/factory.js' );


// FIXTURES //

var smallMean = require( './fixtures/julia/small_mean.json' );
var mediumMean = require( './fixtures/julia/medium_mean.json' );
var largeMean = require( './fixtures/julia/large_mean.json' );


// TESTS //

tape( 'main export is a function', function test( t ) {
	t.ok( true, __filename );
	t.equal( typeof factory, 'function', 'main export is a function' );
	t.end();
});

tape( 'the function returns a function', function test( t ) {
	var logpmf = factory( 0.5 );
	t.equal( typeof logpmf, 'function', 'returns a function' );
	t.end();
});

tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( 0.5 );
	y = logpmf( NaN );
	t.equal( isnan( y ), true, 'returns NaN' );

	logpmf = factory( NaN );
	y = logpmf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	t.end();
});

tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided `Infinity` for `x`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( 1.0 );
	y = logpmf( PINF );
	t.equal( y, NINF, 'returns -Infinity' );

	t.end();
});

tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided a negative integer for `x`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( 0.4 );
	y = logpmf( -4.0 );
	t.equal( y, NINF, 'returns -Infinity' );

	y = logpmf( -1.0 );
	t.equal( y, NINF, 'returns -Infinity' );

	t.end();
});

tape( 'if provided a finite `lambda`, the function returns a function which returns `0` when provided a non-integer for `x`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( 0.4 );
	y = logpmf( 1.3 );
	t.equal( y, NINF, 'returns -Infinity' );

	y = logpmf( 1.4 );
	t.equal( y, NINF, 'returns -Infinity' );

	y = logpmf( 3.2 );
	t.equal( y, NINF, 'returns -Infinity' );

	y = logpmf( 4.8 );
	t.equal( y, NINF, 'returns -Infinity' );

	y = logpmf( -1.2 );
	t.equal( y, NINF, 'returns -Infinity' );

	t.end();
});

tape( 'if provided a negative `lambda`, the created function always returns `NaN`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( -1.0 );

	y = logpmf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	y = logpmf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	t.end();
});

tape( 'if provided `lambda` equals `0`, the created function evaluates a degenerate distribution centered at `0`', function test( t ) {
	var logpmf;
	var y;

	logpmf = factory( 0.0 );
	y = logpmf( 0.0 );
	t.equal( y, 0.0, 'returns 0 for x equal to 0' );

	y = logpmf( 3.0 );
	t.equal( y, NINF, 'returns -Infinity for x greater than 0' );

	y = logpmf( -1.0 );
	t.equal( y, NINF, 'returns -Infinity for x smaller than 0' );

	t.end();
});

tape( 'the created function evaluates the logpmf for `x` given small `lambda`', function test( t ) {
	var expected;
	var logpmf;
	var lambda;
	var delta;
	var tol;
	var i;
	var x;
	var y;

	expected = smallMean.expected;
	x = smallMean.x;
	lambda = smallMean.lambda;
	for ( i = 0; i < x.length; i++ ) {
		logpmf = factory( lambda[i] );
		y = logpmf( x[i] );
		if ( y === expected[i] ) {
			t.equal( y, expected[i], 'x: '+x[i]+'. lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
		} else {
			delta = abs( y - expected[ i ] );
			tol = 20.0 * EPS * abs( expected[ i ] );
			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
		}
	}
	t.end();
});

tape( 'the function evaluates the logpmf for `x` given medium `lambda`', function test( t ) {
	var expected;
	var lambda;
	var logpmf;
	var delta;
	var tol;
	var i;
	var x;
	var y;

	expected = mediumMean.expected;
	x = mediumMean.x;
	lambda = mediumMean.lambda;
	for ( i = 0; i < x.length; i++ ) {
		logpmf = factory( lambda[i] );
		y = logpmf( x[i] );
		if ( y === expected[i] ) {
			t.equal( y, expected[i], 'x: '+x[i]+'. lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
		} else {
			delta = abs( y - expected[ i ] );
			tol = 30.0 * EPS * abs( expected[ i ] );
			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
		}
	}
	t.end();
});

tape( 'the function evaluates the logpmf for `x` given large `lambda`', function test( t ) {
	var expected;
	var lambda;
	var logpmf;
	var delta;
	var tol;
	var i;
	var x;
	var y;

	expected = largeMean.expected;
	x = largeMean.x;
	lambda = largeMean.lambda;
	for ( i = 0; i < x.length; i++ ) {
		logpmf = factory( lambda[i] );
		y = logpmf( x[i] );
		if ( y === expected[i] ) {
			t.equal( y, expected[i], 'x: '+x[i]+'. lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
		} else {
			delta = abs( y - expected[ i ] );
			tol = 80.0 * EPS * abs( expected[ i ] );
			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
		}
	}
	t.end();
});
