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 PINF = require( '@stdlib/constants/float64/pinf' );
  var NINF = require( '@stdlib/constants/float64/ninf' );
  var EPS = require( '@stdlib/constants/float64/eps' );
  var skewness = require( './../lib' );
  
  
  // FIXTURES //
  
  var data = require( './fixtures/julia/data.json' );
  
  
  // TESTS //
  
  tape( 'main export is a function', function test( t ) {
  	t.ok( true, __filename );
  	t.equal( typeof skewness, 'function', 'main export is a function' );
  	t.end();
  });
  
  tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
  	var y = skewness( NaN, 1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  	y = skewness( 1.0, NaN );
  	t.equal( isnan( y ), true, 'returns NaN' );
  	t.end();
  });
  
  tape( 'if provided a nonpositive `s`, the function returns `NaN`', function test( t ) {
  	var y;
  
  	y = skewness( 2.0, 0.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( 2.0, -1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( 2.0, -1.0 );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( 1.0, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( PINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( NINF, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	y = skewness( NaN, NINF );
  	t.equal( isnan( y ), true, 'returns NaN' );
  
  	t.end();
  });
  
  tape( 'the function returns the skewness of a logistic distribution', function test( t ) {
  	var expected;
  	var delta;
  	var tol;
  	var mu;
  	var s;
  	var y;
  	var i;
  
  	expected = data.expected;
  	mu = data.mu;
  	s = data.s;
  	for ( i = 0; i < mu.length; i++ ) {
  		y = skewness( mu[i], s[i] );
  		if ( expected[i] !== null) {
  			if ( y === expected[i] ) {
  				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
  			} else {
  				delta = abs( y - expected[ i ] );
  				tol = 2.0 * EPS * abs( expected[ i ] );
  				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
  			}
  		}
  	}
  	t.end();
  });
  