/*
* Adapted from MIT-licensed code.
*
* Copyright (c) 2014. Athan Reines.
*
* @source https://github.com/compute-io/mean
*/

/* This is a generated file. Do not edit directly. */

/* harmony default export */

/* harmony import */

/*#__PURE__*/

/**
	* Constant function.
	*
	* @private
	* @returns {*} constant value
	*/

/**
* @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.
*
*
* ## Notice
*
* The following copyright and license were part of the original implementation available as part of [FreeBSD]{@link https://svnweb.freebsd.org/base/release/9.3.0/lib/msun/src/e_log.c}. The implementation follows the original, but has been modified for JavaScript.
*
* ```text
* Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
*
* Developed at SunPro, a Sun Microsystems, Inc. business.
* Permission to use, copy, modify, and distribute this
* software is freely granted, provided that this notice
* is preserved.
* ```
*/

/**
* @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.
*/

/**
* A learning component illustrating coverage of confidence intervals for the mean of a binomial distribution.
*
* @property {(string|node)} intro - overrides default (interactive) intro text
* @property {boolean} quartileNotation - controls whether to use quartile notation in intro text
* @property {boolean} sampleStats - controls whether one should be able to switch between using the sample proportion or the known population success probability when calculating the standard error
*/

/**
* Computes the arithmetic mean of a numeric array.
*
* @param {Array} arr - input array
* @returns {(number|null)} arithmetic mean or null
*/

/**
* Create a constant function.
*
* @module @stdlib/utils/constant-function
*
* @example
* var constantFunction = require( '@stdlib/utils/constant-function' );
*
* var fcn = constantFunction( 3.14 );
*
* var v = fcn();
* // returns 3.14
*
* v = fcn();
* // returns 3.14
*
* v = fcn();
* // returns 3.14
*/

/**
* Creates a function which always returns the same value.
*
* @param {*} [value] - value to always return
* @returns {Function} constant function
*
* @example
* var fcn = wrap( 3.14 );
*
* var v = fcn();
* // returns 3.14
*
* v = fcn();
* // returns 3.14
*
* v = fcn();
* // returns 3.14
*/

/**
* Evaluate the natural logarithm.
*
* @module @stdlib/math/base/special/ln
*
* @example
* var ln = require( '@stdlib/math/base/special/ln' );
*
* var v = ln( 4.0 );
* // returns ~1.386
*
* v = ln( 0.0 );
* // returns -Infinity
*
* v = ln( Infinity );
* // returns Infinity
*
* v = ln( NaN );
* // returns NaN
*
* v = ln( -4.0 );
* // returns NaN
*/

/**
* Evaluates a polynomial.
*
* ## Notes
*
* -   The implementation uses [Horner's rule][horners-method] for efficient computation.
*
* [horners-method]: https://en.wikipedia.org/wiki/Horner%27s_method
*
*
* @private
* @param {number} x - value at which to evaluate the polynomial
* @returns {number} evaluated polynomial
*/

/**
* Evaluates the natural logarithm.
*
* @param {NonNegativeNumber} x - input value
* @returns {number} function value
*
* @example
* var v = ln( 4.0 );
* // returns ~1.386
*
* @example
* var v = ln( 0.0 );
* // returns -Infinity
*
* @example
* var v = ln( Infinity );
* // returns Infinity
*
* @example
* var v = ln( NaN );
* // returns NaN
*
* @example
* var v = ln( -4.0 );
* // returns NaN
*/

/***/

// Case: -2**-20 <= f < 2**-20

// Case: 0 < x < 2**-1022

// EXPORTS //

// Exports

// MAIN //

// MODULES //

// Module

// Normalize `x` or `x/2`...

// PROPERTIES //

// Subnormal number, scale up `x`:

// VARIABLES //

// asm type annotation
