text: /**
  * @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 ln = require( '@stdlib/math-base-special-ln' );
  var PINF = require( '@stdlib/constants-float64-pinf' );
  var NINF = require( '@stdlib/constants-float64-ninf' );
  var EPS = require( '@stdlib/constants-float64-eps' );
  var logpdf = require( './../lib' );
  
  
  // FIXTURES //
  
  var largeScale = require( './fixtures/julia/large_scale.json' );
  var largeShape = require( './fixtures/julia/large_shape.json' );
  var bothLarge = require( './fixtures/julia/both_large.json' );
  
  
  // TESTS //
  
  tape( 'main export is a function', function test( t ) {
  	t.ok( true, __filename );
  	t.equal( typeof logpdf, 'function', 'main export is a function' );
  	t.end();
  });
  
  tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
  	var y = logpdf( NaN, 1.0, 1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  	y = logpdf( 0.0, NaN, 1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  	y = logpdf( 0.0, 1.0, NaN );
  	t.equal( isnan( y ), true, 'returns NaN' );
  	t.end();
  });
  
  tape( 'if provided `+infinity` for `x` and a finite `lambda` and `k`, the function returns `-Infinity`', function test( t ) {
  	var y = logpdf( PINF, 1.0, 1.0 );
  	t.equal( y, NINF, 'returns -Infinity' );
  	t.end();
  });
  
  tape( 'if provided `-infinity` for `x` and a finite `lambda` and `k`, the function returns `-Infinity`', function test( t ) {
  	var y = logpdf( NINF, 1.0, 1.0 );
  	t.equal( y, NINF, 'returns -Infinity' );
  	t.end();
  });
  
  tape( 'if provided `lambda <= 0`, the function returns `NaN`', function test( t ) {
  	var y;
  
  	y = logpdf( 2.0, 2.0, 0.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, 2.0, -1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 0.0, 2.0, -1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, 2.0, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, PINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NaN, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	t.end();
  });
  
  tape( 'if provided `k <= 0`, the function returns `NaN`', function test( t ) {
  	var y;
  
  	y = logpdf( 2.0, 0.0, 2.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, -1.0, 2.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 0.0, -1.0, 2.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NINF, 2.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = logpdf( 2.0, NINF, NaN );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	t.end();
  });
  
  tape( 'if provided `0.0` for `x`, a positive `lambda` and `k` equal to one, the function returns `ln(k/lambda)`', function test( t ) {
  	var lambda;
  	var y;
  	var k;
  
  	k = 1.0;
  	lambda = 3.0;
  	y = logpdf( 0.0, k, lambda );
  	t.equal( y, ln(k/lambda), 'returns ln(k / lambda)' );
  	t.end();
  });
  
  tape( 'if provided `0.0` for `x`, a positive `lambda` and `k` not equal to one, the function returns `-Infinity`', function test( t ) {
  	var y = logpdf( 0.0, 2.0, 1.0 );
  	t.equal( y, NINF, 'returns -Infinity' );
  	t.end();
  });
  
  tape( 'the function evaluates the logpdf for `x` given large `lambda` and `k`', function test( t ) {
  	var expected;
  	var lambda;
  	var delta;
  	var tol;
  	var i;
  	var k;
  	var x;
  	var y;
  
  	expected = bothLarge.expected;
  	x = bothLarge.x;
  	lambda = bothLarge.lambda;
  	k = bothLarge.k;
  	for ( i = 0; i < x.length; i++ ) {
  		y = logpdf( x[i], k[i], lambda[i] );
  		if ( y === expected[i] ) {
  			t.equal( y, expected[i], 'x: '+x[i]+', k: '+k[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
  		} else {
  			delta = abs( y - expected[ i ] );
  			tol = 1.0 * EPS * abs( expected[ i ] );
  			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. k: '+k[i]+'. lambda: '+lambda[i]+'. y: '+y+'. Expected: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' );
  		}
  	}
  	t.end();
  });
  
  tape( 'the function evaluates the logpdf for `x` given large scale parameter `lambda`', function test( t ) {
  	var expected;
  	var lambda;
  	var delta;
  	var tol;
  	var i;
  	var k;
  	var x;
  	var y;
  
  	expected = largeScale.expected;
  	x = largeScale.x;
  	lambda = largeScale.lambda;
  	k = largeScale.k;
  	for ( i = 0; i < x.length; i++ ) {
  		y = logpdf( x[i], k[i], lambda[i] );
  		if ( y === expected[i] ) {
  			t.equal( y, expected[i], 'x: '+x[i]+', k: '+k[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
  		} else {
  			delta = abs( y - expected[ i ] );
  			tol = 1.0 * EPS * abs( expected[ i ] );
  			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. k: '+k[i]+'. lambda: '+lambda[i]+'. y: '+y+'. Expected: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' );
  		}
  	}
  	t.end();
  });
  
  tape( 'the function evaluates the logpdf for `x` given large shape parameter `k`', function test( t ) {
  	var expected;
  	var lambda;
  	var delta;
  	var tol;
  	var i;
  	var k;
  	var x;
  	var y;
  
  	expected = largeShape.expected;
  	x = largeShape.x;
  	lambda = largeShape.lambda;
  	k = largeShape.k;
  	for ( i = 0; i < x.length; i++ ) {
  		y = logpdf( x[i], k[i], lambda[i] );
  		if ( y === expected[i] ) {
  			t.equal( y, expected[i], 'x: '+x[i]+', k: '+k[i]+', lambda: '+lambda[i]+', y: '+y+', expected: '+expected[i] );
  		} else {
  			delta = abs( y - expected[ i ] );
  			tol = 1.0 * EPS * abs( expected[ i ] );
  			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. k: '+k[i]+'. lambda: '+lambda[i]+'. y: '+y+'. Expected: '+expected[i]+'. Δ: '+delta+'. tol: '+tol+'.' );
  		}
  	}
  	t.end();
  });
  