/* harmony default export */

/* harmony export (binding) */

/* harmony import */

/*#__PURE__*/

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

/**
	* Evaluates the cumulative distribution function (CDF) for a uniform distribution.
	*
	* @private
	* @param {number} x - input value
	* @returns {Probability} evaluated CDF
	*
	* @example
	* var y = cdf( 2.0 );
	* // returns <number>
	*/

/**
	* Evaluates the probability density function (PDF) for a uniform distribution.
	*
	* @private
	* @param {number} x - input value
	* @returns {number} evaluated PDF
	*
	* @example
	* var y = pdf( 2.0 );
	* // returns <number>
	*/

/**
 * Iterates through children that are "valid elements".
 *
 * The provided forEachFunc(child, index) will be called for each
 * leaf child with the index reflecting the position relative to "valid components".
 */

/**
 * Iterates through children that are typically specified as `props.children`,
 * but only maps over children that are "valid elements".
 *
 * The mapFunction provided index will be normalised to the components mapped,
 * so an invalid component would not increase the index.
 *
 */

/**
* @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.
*/

/**
* 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
*/

/**
* Evaluates the cumulative distribution function (CDF) for a uniform distribution with minimum support `a` and maximum support `b` at a value `x`.
*
* @param {number} x - input value
* @param {number} a - minimum support
* @param {number} b - maximum support
* @returns {Probability} evaluated CDF
*
* @example
* var y = cdf( 9.0, 0.0, 10.0 );
* // returns 0.9
*
* @example
* var y = cdf( 0.5, 0.0, 2.0 );
* // returns 0.25
*
* @example
* var y = cdf( +Infinity, 2.0, 4.0 );
* // returns 1.0
*
* @example
* var y = cdf( -Infinity, 2.0, 4.0 );
* // returns 0.0
*
* @example
* var y = cdf( NaN, 0.0, 1.0 );
* // returns NaN
*
* @example
* var y = cdf( 0.0, NaN, 1.0 );
* // returns NaN
*
* @example
* var y = cdf( 0.0, 0.0, NaN );
* // returns NaN
*
* @example
* var y = cdf( 2.0, 1.0, 0.0 );
* // returns NaN
*/

/**
* Evaluates the probability density function (PDF) for a uniform distribution with minimum support `a` and maximum support `b` at a value `x`.
*
* @param {number} x - input value
* @param {number} a - minimum support
* @param {number} b - maximum support
* @returns {number} evaluated PDF
*
* @example
* var y = pdf( 2.0, 0.0, 4.0 );
* // returns 0.25
*
* @example
* var y = pdf( 5.0, 0.0, 4.0 );
* // returns 0.0
*
* @example
* var y = pdf( 0.25, 0.0, 1.0 );
* // returns 1.0
*
* @example
* var y = pdf( NaN, 0.0, 1.0 );
* // returns NaN
*
* @example
* var y = pdf( 0.0, NaN, 1.0 );
* // returns NaN
*
* @example
* var y = pdf( 0.0, 0.0, NaN );
* // returns NaN
*
* @example
* var y = pdf( 2.0, 3.0, 1.0 );
* // returns NaN
*/

/**
* Returns a function for evaluating the cumulative distribution function (CDF) for a uniform distribution with minimum support `a` and maximum support `b`.
*
* @param {number} a - minimum support
* @param {number} b - maximum support
* @returns {Function} CDF
*
* @example
* var cdf = factory( 0.0, 10.0 );
* var y = cdf( 0.5 );
* // returns 0.05
*
* y = cdf( 8.0 );
* // returns 0.8
*/

/**
* Returns a function for evaluating the probability density function (PDF) for a uniform distribution with minimum support `a` and maximum support `b`.
*
* @param {number} a - minimum support
* @param {number} b - maximum support
* @returns {Function} PDF
*
* @example
* var pdf = factory( 0.0, 10.0 );
* var y = pdf( 2.0 );
* // returns 0.1
*
* y = pdf( 12.0 );
* // returns 0.0
*/

/**
* Uniform distribution cumulative distribution function (CDF).
*
* @module @stdlib/stats/base/dists/uniform/cdf
*
* @example
* var cdf = require( '@stdlib/stats/base/dists/uniform/cdf' );
*
* var y = cdf( 5.0, 0.0, 4.0 );
* // returns 1.0
*
* var mycdf = cdf.factory( 0.0, 10.0 );
* y = mycdf( 0.5 );
* // returns 0.05
*
* y = mycdf( 8.0 );
* // returns 0.8
*/

/**
* Uniform distribution probability density function (PDF).
*
* @module @stdlib/stats/base/dists/uniform/pdf
*
* @example
* var pdf = require( '@stdlib/stats/base/dists/uniform/pdf' );
*
* var y = pdf( 3.0, 2.0, 6.0 );
* // returns 0.25
*
* var myPDF = pdf.factory( 6.0, 7.0 );
* y = myPDF( 7.0 );
* // returns 1.0
*
* y = myPDF( 5.0 );
* // returns 0.0
*/

/***/

// EXPORTS //

// MAIN //

// MODULES //

// Need to define the default "as" during prop destructuring to be compatible with styled-components github.com/react-bootstrap/react-bootstrap/issues/3595

// PROPERTIES //

// VARIABLES //

// We provide an empty the TabContext so `<Nav>`s in `<TabPane>`s don't

// conflict with the top level one.
