refactor: precompute constant

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Author: Planeshifter

lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/lib/main.js

@@ -21,8 +21,11 @@
 // MODULES //
 
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var SQRT3 = require( '@stdlib/constants/float64/sqrt-three' );
-var PI = require( '@stdlib/constants/float64/pi' );
+
+
+// VARIABLES //
+
+var PI_OVER_SQRT_THREE = 1.8137993642342178; // π divided by the square root of 3
 
 
 // MAIN //
@@ -62,7 +65,7 @@ function stdev( mu, s ) {
 	) {
 		return NaN;
 	}
-	return s * PI / SQRT3;
+	return s * PI_OVER_SQRT_THREE;
 }
 
 

lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/src/main.c

@@ -21,6 +21,8 @@
 #include "stdlib/constants/float64/pi.h"
 #include "stdlib/constants/float64/sqrt_three.h"
 
+static const double PI_OVER_SQRT_THREE = 1.8137993642342178; // π divided by the square root of 3
+
 /**
 * Returns the standard deviation for a logistic distribution with location `mu` and scale `s`.
 *
@@ -40,5 +42,5 @@ double stdlib_base_dists_logistic_stdev( const double mu, const double s ) {
 	) {
 		return 0.0/0.0; // NaN
 	}
-	return s * STDLIB_CONSTANT_FLOAT64_PI / STDLIB_CONSTANT_FLOAT64_SQRT3;
+	return s * PI_OVER_SQRT_THREE;
 }

lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/test/test.js

@@ -96,7 +96,7 @@ tape( 'the function returns the standard deviation of a logistic distribution',
 				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
 			} else {
 				delta = abs( y - expected[ i ] );
-				tol = 2.0 * EPS * abs( expected[ i ] );
+				tol = 1.0 * EPS * abs( expected[ i ] );
 				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 			}
 		}

lib/node_modules/@stdlib/stats/base/dists/logistic/stdev/test/test.native.js

@@ -105,7 +105,7 @@ tape( 'the function returns the standard deviation of a logistic distribution',
 				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
 			} else {
 				delta = abs( y - expected[ i ] );
-				tol = 2.0 * EPS * abs( expected[ i ] );
+				tol = 1.0 * EPS * abs( expected[ i ] );
 				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
 			}
 		}