/* 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, license, and long comment 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_exp.c}. The implementation follows the original, but has been modified for JavaScript.
*
* ```text
* Copyright (C) 2004 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 for calculating probabilities of a exponential distribution.
*
* @property {boolean} hideCDF - controls whether to hide the CDF plots
* @property {number} step - step size of the scroll input
* @property {Object} style - CSS inline styles
*/

/**
* Computes \\(e^{r} 2^k\\) where \\(r = \mathrm{hi} - \mathrm{lo}\\) and \\(|r| \leq \ln(2)/2\\).
*
* @private
* @param {number} hi - upper bound
* @param {number} lo - lower bound
* @param {integer} k - power of 2
* @returns {number} function value
*/

/**
* 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 exponential function.
*
* @module @stdlib/math/base/special/exp
*
* @example
* var exp = require( '@stdlib/math/base/special/exp' );
*
* var v = exp( 4.0 );
* // returns ~54.5982
*
* v = exp( -9.0 );
* // returns ~1.234e-4
*
* v = exp( 0.0 );
* // returns 1.0
*
* v = exp( NaN );
* // 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 exponential function.
*
* ## Method
*
* 1.  We reduce \\( x \\) to an \\( r \\) so that \\( |r| \leq 0.5 \cdot \ln(2) \approx 0.34658 \\). Given \\( x \\), we find an \\( r \\) and integer \\( k \\) such that
*
*     ```tex
*     \begin{align*}
*     x &= k \cdot \ln(2) + r \\
*     |r| &\leq 0.5 \cdot \ln(2)
*     \end{align*}
*     ```
*
*     <!-- <note> -->
*
*     \\( r \\) can be represented as \\( r = \mathrm{hi} - \mathrm{lo} \\) for better accuracy.
*
*     <!-- </note> -->
*
* 2.  We approximate of \\( e^{r} \\) by a special rational function on the interval \\(\[0,0.34658]\\):
*
*     ```tex
*     \begin{align*}
*     R\left(r^2\right) &= r \cdot \frac{ e^{r}+1 }{ e^{r}-1 } \\
*     &= 2 + \frac{r^2}{6} - \frac{r^4}{360} + \ldots
*     \end{align*}
*     ```
*
*     We use a special Remes algorithm on \\(\[0,0.34658]\\) to generate a polynomial of degree \\(5\\) to approximate \\(R\\). The maximum error of this polynomial approximation is bounded by \\(2^{-59}\\). In other words,
*
*     ```tex
*     R(z) \sim 2 + P_1 z + P_2 z^2 + P_3 z^3 + P_4 z^4 + P_5 z^5
*     ```
*
*     where \\( z = r^2 \\) and
*
*     ```tex
*     \left|  2 + P_1 z + \ldots + P_5 z^5  - R(z) \right| \leq 2^{-59}
*     ```
*
*     <!-- <note> -->
*
*     The values of \\( P_1 \\) to \\( P_5 \\) are listed in the source code.
*
*     <!-- </note> -->
*
*     The computation of \\( e^{r} \\) thus becomes
*
*     ```tex
*     \begin{align*}
*     e^{r} &= 1 + \frac{2r}{R-r} \\
*           &= 1 + r + \frac{r \cdot R_1(r)}{2 - R_1(r)}\ \text{for better accuracy}
*     \end{align*}
*     ```
*
*     where
*
*     ```tex
*     R_1(r) = r - P_1\ r^2 + P_2\ r^4 + \ldots + P_5\ r^{10}
*     ```
*
* 3.  We scale back to obtain \\( e^{x} \\). From step 1, we have
*
*     ```tex
*     e^{x} = 2^k e^{r}
*     ```
*
*
* ## Special Cases
*
* ```tex
* \begin{align*}
* e^\infty &= \infty \\
* e^{-\infty} &= 0 \\
* e^{\mathrm{NaN}} &= \mathrm{NaN} \\
* e^0 &= 1\ \mathrm{is\ exact\ for\ finite\ argument\ only}
* \end{align*}
* ```
*
* ## Notes
*
* -   According to an error analysis, the error is always less than \\(1\\) ulp (unit in the last place).
*
* -   For an IEEE double,
*
*     -   if \\(x > 7.09782712893383973096\mbox{e+}02\\), then \\(e^{x}\\) overflows
*     -   if \\(x < -7.45133219101941108420\mbox{e+}02\\), then \\(e^{x}\\) underflows
*
* -   The hexadecimal values included in the source code are the intended ones for the used constants. Decimal values may be used, provided that the compiler will convert from decimal to binary accurately enough to produce the intended hexadecimal values.
*
*
* @param {number} x - input value
* @returns {number} function value
*
* @example
* var v = exp( 4.0 );
* // returns ~54.5982
*
* @example
* var v = exp( -9.0 );
* // returns ~1.234e-4
*
* @example
* var v = exp( 0.0 );
* // returns 1.0
*
* @example
* var v = exp( NaN );
* // returns NaN
*/

/**
* Round a numeric value toward zero.
*
* @module @stdlib/math/base/special/trunc
*
* @example
* var trunc = require( '@stdlib/math/base/special/trunc' );
*
* var v = trunc( -4.2 );
* // returns -4.0
*
* v = trunc( 9.99999 );
* // returns 9.0
*
* v = trunc( 0.0 );
* // returns 0.0
*
* v = trunc( -0.0 );
* // returns -0.0
*
* v = trunc( NaN );
* // returns NaN
*
* v = trunc( Infinity );
* // returns Infinity
*
* v = trunc( -Infinity );
* // returns -Infinity
*/

/**
* Rounds a numeric value toward zero.
*
* @param {number} x - input value
* @returns {number} rounded value
*
* @example
* var v = trunc( -4.2 );
* // returns -4.0
*
* @example
* var v = trunc( 9.99999 );
* // returns 9.0
*
* @example
* var v = trunc( 0.0 );
* // returns 0.0
*
* @example
* var v = trunc( -0.0 );
* // returns -0.0
*
* @example
* var v = trunc( NaN );
* // returns NaN
*
* @example
* var v = trunc( Infinity );
* // returns Infinity
*
* @example
* var v = trunc( -Infinity );
* // returns -Infinity
*/

/***/

// EXPORTS //

// MAIN //

// MODULES //

// PROPERTIES //

// Reduce and compute `r = hi - lo` for extra precision.

// VARIABLES //
