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[286,286,100,25,25,100,4,4,100,286,286,100,"27824a1f3c90218cfe5f3be923f8f879d98ed9dc","2024-12-16 21:09:13 -0500"]
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<span class="cline-any cline-neutral">&nbsp;</span></td><td class="text"><pre class="prettyprint lang-js">/**
* @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.
*/
&nbsp;
'use strict';
&nbsp;
// MODULES //
&nbsp;
var constantFunction = require( '@stdlib/utils/constant-function' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
&nbsp;
&nbsp;
// MAIN //
&nbsp;
/**
* 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
*/
function factory( a, b ) {
if (
isnan( a ) ||
isnan( b ) ||
a &gt;= b
) {
return constantFunction( NaN );
}
return pdf;
&nbsp;
/**
* 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 &lt;number&gt;
*/
function pdf( x ) {
if ( isnan( x ) ) {
return NaN;
}
if ( x &lt; a || x &gt; b ) {
return 0.0;
}
return 1.0 / ( b - a );
}
}
&nbsp;
&nbsp;
// EXPORTS //
&nbsp;
module.exports = factory;
&nbsp;</pre></td></tr></table></pre>

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