chore: minor clean-up

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Author: Planeshifter

lib/node_modules/@stdlib/math/base/special/cceil/benchmark/c/benchmark.c

@@ -104,7 +104,7 @@ static double benchmark( void ) {
 
 	t = tic();
 	for ( i = 0; i < ITERATIONS; i++ ) {
-		x = v[ i % 100 ]  + v[ i % 100 ] *I;
+		x = v[ i % 100 ] + v[ i % 100 ] *I;
 		y = stdlib_base_ceil( creal( x ) ) + stdlib_base_ceil( cimag( x ) )*I;
 		if ( creal( y ) != creal( y ) ) {
 			printf( "unexpected result\n" );

lib/node_modules/@stdlib/math/base/special/kernel-log1p/lib/main.js

@@ -74,7 +74,7 @@ var polyvalQ = require( './polyval_q.js' );
 *     We use a special Reme algorithm on \\(\[0,0.1716]\\) to generate a polynomial of degree \\(14\\) to approximate \\(R\\). The maximum error of this polynomial approximation is bounded by \\(2^{-58.45}\\). In other words,
 *
 *     ```tex
-*     R(z) ~ L_{g1} s^2 + L_{g2} s^4 + L_{g3} s^6 + L_{g4} s^8 + L_{g5} s^{10}  + L_{g6} s^{12}  + L_{g7} s^{14}
+*     R(z) ~ L_{g1} s^2 + L_{g2} s^4 + L_{g3} s^6 + L_{g4} s^8 + L_{g5} s^{10} + L_{g6} s^{12} + L_{g7} s^{14}
 *     ```
 *
 *     where the values of \\(L_{g1}\\) to \\(L_{g7}\\) are the polynomial coefficients used in the program below and

lib/node_modules/@stdlib/math/base/special/kernel-log1p/src/main.c

@@ -111,7 +111,7 @@ static double polyval_q( const double x ) {
 *     We use a special Reme algorithm on \\(\[0,0.1716]\\) to generate a polynomial of degree \\(14\\) to approximate \\(R\\). The maximum error of this polynomial approximation is bounded by \\(2^{-58.45}\\). In other words,
 *
 *     ```tex
-*     R(z) ~ L_{g1} s^2 + L_{g2} s^4 + L_{g3} s^6 + L_{g4} s^8 + L_{g5} s^{10}  + L_{g6} s^{12}  + L_{g7} s^{14}
+*     R(z) ~ L_{g1} s^2 + L_{g2} s^4 + L_{g3} s^6 + L_{g4} s^8 + L_{g5} s^{10} + L_{g6} s^{12} + L_{g7} s^{14}
 *     ```
 *
 *     where the values of \\(L_{g1}\\) to \\(L_{g7}\\) are the polynomial coefficients used in the program below and

lib/node_modules/@stdlib/stats/base/dists/exponential/logcdf/benchmark/c/benchmark.c

@@ -38,7 +38,7 @@ static void print_version( void ) {
 /**
 * Prints the TAP summary.
 *
-* @param total	  total number of tests
+* @param total    total number of tests
 * @param passing  total number of passing tests
 */
 static void print_summary( int total, int passing ) {

lib/node_modules/@stdlib/stats/base/dists/geometric/pmf/README.md

@@ -204,7 +204,6 @@ double stdlib_base_dists_geometric_pmf( const double x, const double p );
 #include "stdlib/math/base/special/round.h"
 #include <stdlib.h>
 #include <stdio.h>
-#include <math.h>
 
 static double random_uniform( const double min, const double max ) {
     double v = (double)rand() / ( (double)RAND_MAX + 1.0 );

lib/node_modules/@stdlib/stats/base/dists/geometric/pmf/binding.gyp

@@ -167,4 +167,4 @@
       ], # end actions
     }, # end target copy_addon
   ], # end targets
-}
+}

lib/node_modules/@stdlib/stats/base/dists/geometric/pmf/examples/c/example.c

@@ -20,7 +20,6 @@
 #include "stdlib/math/base/special/round.h"
 #include <stdlib.h>
 #include <stdio.h>
-#include <math.h>
 
 static double random_uniform( const double min, const double max ) {
 	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );

lib/node_modules/@stdlib/stats/base/dists/geometric/pmf/src/main.c

@@ -24,9 +24,9 @@
 /**
 * Returns the probability mass function of a geometric distribution.
 *
-* @param x	input value
-* @param p	success probability
-* @return 	evaluated PMF
+* @param x   input value
+* @param p   success probability
+* @return    evaluated PMF
 *
 * @example
 * double y = stdlib_base_dists_geometric_pmf( 4.0, 0.3 );

lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/README.md

@@ -145,7 +145,7 @@ for ( i = 0; i < 10; i++ ) {
     x = randu() * 10.0;
     sigma = randu() * 10.0;
     y = logpdf( x, sigma );
-    console.log( 'x: %d, σ: %d, f(x;σ): %d', x.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) );
+    console.log( 'x: %d, σ: %d, ln(f(x;σ)): %d', x.toFixed( 4 ), sigma.toFixed( 4 ), y.toFixed( 4 ) );
 }
 ```
 

lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/benchmark/benchmark.js

@@ -43,7 +43,7 @@ bench( pkg, function benchmark( b ) {
 	x = new Float64Array( len );
 	sigma = new Float64Array( len );
 	for ( i = 0; i < len; i++ ) {
-		x[ i ] = ( randu() * 100.0 ) - 100.0;
+		x[ i ] = randu() * 100.0;
 		sigma[ i ] = ( randu() * 20.0 ) + EPS;
 	}
 	for ( i = 0; i < b.iterations; i++ ) {