text: /**
  * @license Apache-2.0
  *
  * Copyright (c) 2020 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 floor = require( '@stdlib/math/base/special/floor' );
  var sqrt = require( '@stdlib/math/base/special/sqrt' );
  var abs = require( '@stdlib/math/base/special/abs' );
  var isnan = require( '@stdlib/math/base/assert/is-nan' );
  var Float64Array = require( '@stdlib/array/float64' );
  var EPS = require( '@stdlib/constants/math/float64-eps' );
  var dsem = require( './../lib/ndarray.js' );
  
  
  // TESTS //
  
  tape( 'main export is a function', function test( t ) {
  	t.ok( true, __filename );
  	t.strictEqual( typeof dsem, 'function', 'main export is a function' );
  	t.end();
  });
  
  tape( 'the function has an arity of 5', function test( t ) {
  	t.strictEqual( dsem.length, 5, 'has expected arity' );
  	t.end();
  });
  
  tape( 'the function calculates the standard error of the mean for a strided array (population)', function test( t ) {
  	var expected;
  	var delta;
  	var tol;
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
  	v = dsem( x.length, 0, x, 1, 0 );
  	expected = sqrt( 53.5/x.length ) / sqrt( x.length );
  
  	delta = abs( v - expected );
  	tol = 1.0 * EPS * abs( expected );
  	t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+v+'. E: '+expected+'. tol: '+tol+'. Δ: '+delta+'.' );
  
  	x = new Float64Array( [ -4.0, -4.0 ] );
  	v = dsem( x.length, 0, x, 1, 0 );
  	t.strictEqual( v, 0.0, 'returns expected value' );
  
  	x = new Float64Array( [ NaN, 4.0 ] );
  	v = dsem( x.length, 0, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'the function calculates the standard error of the mean for a strided array (sample)', function test( t ) {
  	var expected;
  	var delta;
  	var tol;
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
  	v = dsem( x.length, 1, x, 1, 0 );
  	expected = sqrt( 53.5/(x.length-1) ) / sqrt( x.length );
  
  	delta = abs( v - expected );
  	tol = 1.0 * EPS * abs( expected );
  	t.strictEqual( delta <= tol, true, 'within tolerance. Actual: '+v+'. E: '+expected+'. tol: '+tol+'. Δ: '+delta+'.' );
  
  	x = new Float64Array( [ -4.0, -4.0 ] );
  	v = dsem( x.length, 1, x, 1, 0 );
  	t.strictEqual( v, 0.0, 'returns expected value' );
  
  	x = new Float64Array( [ NaN, 4.0 ] );
  	v = dsem( x.length, 1, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
  
  	v = dsem( 0, 1, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	v = dsem( -1, 1, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'if provided an `N` parameter equal to `1`, the function returns a standard error of the mean of `0` (population)', function test( t ) {
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
  
  	v = dsem( 1, 0, x, 1, 0 );
  	t.strictEqual( v, 0.0, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'if provided a `correction` parameter yielding `N-correction` less than or equal to `0`, the function returns `NaN`', function test( t ) {
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
  
  	v = dsem( x.length, x.length, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	v = dsem( x.length, x.length+1, x, 1, 0 );
  	t.strictEqual( isnan( v ), true, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'the function supports a `stride` parameter', function test( t ) {
  	var N;
  	var x;
  	var v;
  
  	x = new Float64Array([
  		1.0,  // 0
  		2.0,
  		2.0,  // 1
  		-7.0,
  		-2.0, // 2
  		3.0,
  		4.0,  // 3
  		2.0
  	]);
  
  	N = floor( x.length / 2 );
  	v = dsem( N, 1, x, 2, 0 );
  
  	t.strictEqual( v, 1.25, 'returns expected value' );
  	t.end();
  });
  
  tape( 'the function supports a negative `stride` parameter', function test( t ) {
  	var N;
  	var x;
  	var v;
  
  	x = new Float64Array([
  		1.0,  // 3
  		2.0,
  		2.0,  // 2
  		-7.0,
  		-2.0, // 1
  		3.0,
  		4.0,  // 0
  		2.0
  	]);
  
  	N = floor( x.length / 2 );
  	v = dsem( N, 1, x, -2, 6 );
  
  	t.strictEqual( v, 1.25, 'returns expected value' );
  	t.end();
  });
  
  tape( 'if provided a `stride` parameter equal to `0`, the function returns `0`', function test( t ) {
  	var x;
  	var v;
  
  	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
  
  	v = dsem( x.length, 1, x, 0, 0 );
  	t.strictEqual( v, 0.0, 'returns expected value' );
  
  	t.end();
  });
  
  tape( 'the function supports an `offset` parameter', function test( t ) {
  	var N;
  	var x;
  	var v;
  
  	x = new Float64Array([
  		2.0,
  		1.0,  // 0
  		2.0,
  		-2.0, // 1
  		-2.0,
  		2.0,  // 2
  		3.0,
  		4.0   // 3
  	]);
  	N = floor( x.length / 2 );
  
  	v = dsem( N, 1, x, 2, 1 );
  	t.strictEqual( v, 1.25, 'returns expected value' );
  
  	t.end();
  });
  