diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md b/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md
index eb6a46aed57a..171e5820b7f9 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/README.md
@@ -98,9 +98,9 @@ The use of the term `n-1` is commonly referred to as Bessel's correction. Note,
var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' );
```
-#### snanvariancepn( N, correction, x, stride )
+#### snanvariancepn( N, correction, x, strideX )
-Computes the [variance][variance] of a single-precision floating-point strided array `x` ignoring `NaN` values and using a two-pass algorithm.
+Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm.
```javascript
var Float32Array = require( '@stdlib/array/float32' );
@@ -116,39 +116,36 @@ The function has the following parameters:
- **N**: number of indexed elements.
- **correction**: degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
- **x**: input [`Float32Array`][@stdlib/array/float32].
-- **stride**: index increment for `x`.
+- **strideX**: stride length for `x`.
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [variance][variance] of every other element in `x`,
+
+<!-- eslint-disable max-len -->
```javascript
var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
-var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] );
-var N = floor( x.length / 2 );
+var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN, NaN ] );
-var v = snanvariancepn( N, 1, x, 2 );
+var v = snanvariancepn( 5, 1, x, 2 );
// returns 6.25
```
Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
-<!-- eslint-disable stdlib/capitalized-comments -->
+<!-- eslint-disable stdlib/capitalized-comments, max-len -->
```javascript
var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
-var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
+var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-var N = floor( x0.length / 2 );
-
-var v = snanvariancepn( N, 1, x1, 2 );
+var v = snanvariancepn( 5, 1, x1, 2 );
// returns 6.25
```
-#### snanvariancepn.ndarray( N, correction, x, stride, offset )
+#### snanvariancepn.ndarray( N, correction, x, strideX, offsetX )
Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics.
@@ -163,18 +160,18 @@ var v = snanvariancepn.ndarray( x.length, 1, x, 1, 0 );
The function has the following additional parameters:
-- **offset**: starting index for `x`.
+- **offsetX**: starting index for `x`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other element in `x` starting from the second element
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [variance][variance] for every other value in `x` starting from the second value
+<!-- eslint-disable max-len -->
```javascript
var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
-var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
+var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
-var v = snanvariancepn.ndarray( N, 1, x, 2, 1 );
+var v = snanvariancepn.ndarray( 5, 1, x, 2, 1 );
// returns 6.25
```
@@ -200,18 +197,19 @@ var v = snanvariancepn.ndarray( N, 1, x, 2, 1 );
<!-- eslint no-undef: "error" -->
```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' );
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
- x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
+ }
+ return uniform( -50.0, 50.0 );
}
+
+var x = filledarrayBy( 10, 'float32', rand );
console.log( x );
var v = snanvariancepn( x.length, 1, x, 1 );
@@ -222,6 +220,125 @@ console.log( v );
<!-- /.examples -->
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/snanvariancepn.h"
+```
+
+#### stdlib_strided_snanvariancepn( N, correction, \*X, strideX )
+
+Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm.
+
+```c
+const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };
+
+float v = stdlib_strided_snanvariancepn( 4, 1.0f, x, 1 );
+// returns ~4.3333f
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
+- **X**: `[in] float*` input array.
+- **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_snanvariancepn( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_snanvariancepn_ndarray( N, correction, \*X, strideX, offsetX )
+
+Computes the [variance][variance] of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics.
+
+```c
+const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };
+
+float v = stdlib_strided_snanvariancepn_ndarray( 4, 1.0f, x, 1, 0 );
+// returns ~4.3333f
+```
+
+The function accepts the following arguments:
+
+- **N**: `[in] CBLAS_INT` number of indexed elements.
+- **correction**: `[in] float` degrees of freedom adjustment. Setting this parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the [variance][variance] according to `n-c` where `c` corresponds to the provided degrees of freedom adjustment and `n` corresponds to the number of non-`NaN` indexed elements. When computing the [variance][variance] of a population, setting this parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the unbiased sample [variance][variance], setting this parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
+- **X**: `[in] float*` input array.
+- **strideX**: `[in] CBLAS_INT` stride length for `X`.
+- **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_snanvariancepn_ndarray( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/snanvariancepn.h"
+#include <stdio.h>
+
+int main( void ) {
+ // Create a strided array:
+ const float x[] = { 1.0f, 2.0f, 0.0f/0.0f, 3.0f, 0.0f/0.0f, 4.0f, 5.0f, 6.0f, 0.0f/0.0f, 7.0f, 8.0f, 0.0f/0.0f };
+
+ // Specify the number of elements:
+ const int N = 6;
+
+ // Specify the stride length:
+ const int strideX = 2;
+
+ // Compute the variance:
+ float v = stdlib_strided_snanvariancepn( N, 1.0f, x, strideX );
+
+ // Print the result:
+ printf( "sample variance: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
* * *
<section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js
index 836a588556c5..9f2122f34287 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.js
@@ -21,16 +21,30 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
var pkg = require( './../package.json' ).name;
var snanvariancepn = require( './../lib/snanvariancepn.js' );
// FUNCTIONS //
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
+ }
+ return uniform( -10.0, 10.0 );
+}
+
/**
* Creates a benchmark function.
*
@@ -39,17 +53,7 @@ var snanvariancepn = require( './../lib/snanvariancepn.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = new Float32Array( len );
- for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = ( randu()*20.0 ) - 10.0;
- }
- }
+ var x = filledarrayBy( len, 'float32', rand );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js
index 03c1f751db0b..8f7fa8621f6c 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.native.js
@@ -22,10 +22,11 @@
var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;
@@ -40,6 +41,19 @@ var opts = {
// FUNCTIONS //
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
+ }
+ return uniform( -10.0, 10.0 );
+}
+
/**
* Creates a benchmark function.
*
@@ -48,17 +62,7 @@ var opts = {
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = new Float32Array( len );
- for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = ( randu()*20.0 ) - 10.0;
- }
- }
+ var x = filledarrayBy( len, 'float32', rand );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js
index a42e8965bde5..2e2d6644ff88 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.js
@@ -21,16 +21,30 @@
// MODULES //
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
var pkg = require( './../package.json' ).name;
var snanvariancepn = require( './../lib/ndarray.js' );
// FUNCTIONS //
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
+ }
+ return uniform( -10.0, 10.0 );
+}
+
/**
* Creates a benchmark function.
*
@@ -39,17 +53,7 @@ var snanvariancepn = require( './../lib/ndarray.js' );
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = new Float32Array( len );
- for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = ( randu()*20.0 ) - 10.0;
- }
- }
+ var x = filledarrayBy( len, 'float32', rand );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js
index 2e5e254b1cdc..56ce8a4f843b 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/benchmark.ndarray.native.js
@@ -22,10 +22,11 @@
var resolve = require( 'path' ).resolve;
var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
var tryRequire = require( '@stdlib/utils/try-require' );
var pkg = require( './../package.json' ).name;
@@ -40,6 +41,19 @@ var opts = {
// FUNCTIONS //
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
+ }
+ return uniform( -10.0, 10.0 );
+}
+
/**
* Creates a benchmark function.
*
@@ -48,17 +62,7 @@ var opts = {
* @returns {Function} benchmark function
*/
function createBenchmark( len ) {
- var x;
- var i;
-
- x = new Float32Array( len );
- for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = ( randu()*20.0 ) - 10.0;
- }
- }
+ var x = filledarrayBy( len, 'float32', rand );
return benchmark;
function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c
index de403cac8195..445fa95b5fda 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
* @param len array length
* @return elapsed time in seconds
*/
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
double elapsed;
float x[ len ];
float v;
@@ -102,11 +102,16 @@ static double benchmark( int iterations, int len ) {
int i;
for ( i = 0; i < len; i++ ) {
- x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+ if ( rand_float() < 0.2 ) {
+ x[ i ] = 0.0f / 0.0f; // NaN
+ } else {
+ x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+ }
}
v = 0.0f;
t = tic();
for ( i = 0; i < iterations; i++ ) {
+ // cppcheck-suppress uninitvar
v = stdlib_strided_snanvariancepn( len, 1.0f, x, 1 );
if ( v != v ) {
printf( "should not return NaN\n" );
@@ -120,6 +125,44 @@ static double benchmark( int iterations, int len ) {
return elapsed;
}
+/**
+* Runs a benchmark.
+*
+* @param iterations number of iterations
+* @param len array length
+* @return elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+ double elapsed;
+ float x[ len ];
+ float v;
+ double t;
+ int i;
+
+ for ( i = 0; i < len; i++ ) {
+ if ( rand_float() < 0.2 ) {
+ x[ i ] = 0.0f / 0.0f; // NaN
+ } else {
+ x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+ }
+ }
+ v = 0.0f;
+ t = tic();
+ for ( i = 0; i < iterations; i++ ) {
+ // cppcheck-suppress uninitvar
+ v = stdlib_strided_snanvariancepn_ndarray( len, 1.0f, x, 1, 0 );
+ if ( v != v ) {
+ printf( "should not return NaN\n" );
+ break;
+ }
+ }
+ elapsed = tic() - t;
+ if ( v != v ) {
+ printf( "should not return NaN\n" );
+ }
+ return elapsed;
+}
+
/**
* Main execution sequence.
*/
@@ -142,7 +185,18 @@ int main( void ) {
for ( j = 0; j < REPEATS; j++ ) {
count += 1;
printf( "# c::%s:len=%d\n", NAME, len );
- elapsed = benchmark( iter, len );
+ elapsed = benchmark1( iter, len );
+ print_results( iter, elapsed );
+ printf( "ok %d benchmark finished\n", count );
+ }
+ }
+ for ( i = MIN; i <= MAX; i++ ) {
+ len = pow( 10, i );
+ iter = ITERATIONS / pow( 10, i-1 );
+ for ( j = 0; j < REPEATS; j++ ) {
+ count += 1;
+ printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+ elapsed = benchmark2( iter, len );
print_results( iter, elapsed );
printf( "ok %d benchmark finished\n", count );
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt
index 28f293820f68..60bae8809e43 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/repl.txt
@@ -1,10 +1,10 @@
-{{alias}}( N, correction, x, stride )
+{{alias}}( N, correction, x, strideX )
Computes the variance of a single-precision floating-point strided array
ignoring `NaN` values and using a two-pass algorithm.
- The `N` and `stride` parameters determine which elements in `x` are accessed
- at runtime.
+ The `N` and stride parameters determine which elements in the strided array
+ are accessed at runtime.
Indexing is relative to the first index. To introduce an offset, use a typed
array view.
@@ -34,8 +34,8 @@
x: Float32Array
Input array.
- stride: integer
- Index increment.
+ strideX: integer
+ Stride length.
Returns
-------
@@ -49,20 +49,19 @@
> {{alias}}( x.length, 1, x, 1 )
~4.3333
- // Using `N` and `stride` parameters:
- > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
- > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
- > {{alias}}( N, 1, x, 2 )
+ // Using `N` and stride parameters:
+ > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );
+ > {{alias}}( 4, 1, x, 2 )
~4.3333
// Using view offsets:
- > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
+ > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
> var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
- > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
- > {{alias}}( N, 1, x1, 2 )
+ > {{alias}}( 4, 1, x1, 2 )
~4.3333
-{{alias}}.ndarray( N, correction, x, stride, offset )
+
+{{alias}}.ndarray( N, correction, x, strideX, offsetX )
Computes the variance of a single-precision floating-point strided array
ignoring `NaN` values and using a two-pass algorithm and alternative
indexing semantics.
@@ -92,10 +91,10 @@
x: Float32Array
Input array.
- stride: integer
- Index increment.
+ strideX: integer
+ Stride length.
- offset: integer
+ offsetX: integer
Starting index.
Returns
@@ -111,9 +110,8 @@
~4.3333
// Using offset parameter:
- > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
- > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
- > {{alias}}.ndarray( N, 1, x, 2, 1 )
+ > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );
+ > {{alias}}.ndarray( 4, 1, x, 2, 1 )
~4.3333
See Also
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts
index 2828ff3b1201..43bea31e3c51 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/docs/types/index.d.ts
@@ -28,7 +28,7 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
- * @param stride - stride length
+ * @param strideX - stride length
* @returns variance
*
* @example
@@ -39,7 +39,7 @@ interface Routine {
* var v = snanvariancepn( x.length, 1, x, 1 );
* // returns ~4.3333
*/
- ( N: number, correction: number, x: Float32Array, stride: number ): number;
+ ( N: number, correction: number, x: Float32Array, strideX: number ): number;
/**
* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics.
@@ -47,8 +47,8 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
- * @param stride - stride length
- * @param offset - starting index
+ * @param strideX - stride length
+ * @param offsetX - starting index
* @returns variance
*
* @example
@@ -59,7 +59,7 @@ interface Routine {
* var v = snanvariancepn.ndarray( x.length, 1, x, 1, 0 );
* // returns ~4.3333
*/
- ndarray( N: number, correction: number, x: Float32Array, stride: number, offset: number ): number;
+ ndarray( N: number, correction: number, x: Float32Array, strideX: number, offsetX: number ): number;
}
/**
@@ -68,7 +68,7 @@ interface Routine {
* @param N - number of indexed elements
* @param correction - degrees of freedom adjustment
* @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
* @returns variance
*
* @example
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c
index 16fbdd6601d8..1aaf4a3635a0 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/c/example.c
@@ -17,21 +17,20 @@
*/
#include "stdlib/stats/base/snanvariancepn.h"
-#include <stdint.h>
#include <stdio.h>
int main( void ) {
// Create a strided array:
- float x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+ const float x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
// Specify the number of elements:
- int64_t N = 6;
+ const int N = 6;
// Specify the stride length:
- int64_t stride = 2;
+ const int strideX = 2;
// Compute the variance:
- float v = stdlib_strided_snanvariancepn( N, 1.0f, x, stride );
+ float v = stdlib_strided_snanvariancepn( N, 1.0f, x, strideX );
// Print the result:
printf( "sample variance: %f\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js
index 94f2cd4343a0..5de2baf9dd0f 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/examples/index.js
@@ -18,22 +18,19 @@
'use strict';
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
var snanvariancepn = require( './../lib' );
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
- if ( randu() < 0.2 ) {
- x[ i ] = NaN;
- } else {
- x[ i ] = round( (randu()*100.0) - 50.0 );
+function rand() {
+ if ( bernoulli( 0.8 ) < 1 ) {
+ return NaN;
}
+ return uniform( -50.0, 50.0 );
}
+
+var x = filledarrayBy( 10, 'float32', rand );
console.log( x );
var v = snanvariancepn( x.length, 1, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h b/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h
index 3b068f12175c..e2faea345c0c 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/include/stdlib/stats/base/snanvariancepn.h
@@ -19,7 +19,7 @@
#ifndef STDLIB_STATS_BASE_SNANVARIANCEPN_H
#define STDLIB_STATS_BASE_SNANVARIANCEPN_H
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
/*
* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
/**
* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm.
*/
-float stdlib_strided_snanvariancepn( const int64_t N, const float correction, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_snanvariancepn)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
#ifdef __cplusplus
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js
index 48ff38fb8922..5b711544871c 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/index.js
@@ -34,13 +34,11 @@
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
* var snanvariancepn = require( '@stdlib/stats/base/snanvariancepn' );
*
* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
-* var N = floor( x.length / 2 );
*
-* var v = snanvariancepn.ndarray( N, 1, x, 2, 1 );
+* var v = snanvariancepn.ndarray( 5, 1, x, 2, 1 );
* // returns 6.25
*/
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js
index dd341090edb8..8cb371241ed5 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.js
@@ -46,21 +46,19 @@ var WORKSPACE = [ 0.0, 0 ];
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {Float32Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
* @returns {number} variance
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
*
* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
-* var N = floor( x.length / 2 );
*
-* var v = snanvariancepn( N, 1, x, 2, 1 );
+* var v = snanvariancepn( 5, 1, x, 2, 1 );
* // returns 6.25
*/
-function snanvariancepn( N, correction, x, stride, offset ) {
+function snanvariancepn( N, correction, x, strideX, offsetX ) {
var mu;
var ix;
var M2;
@@ -74,19 +72,19 @@ function snanvariancepn( N, correction, x, stride, offset ) {
if ( N <= 0 ) {
return NaN;
}
- if ( N === 1 || stride === 0 ) {
- v = x[ offset ];
+ if ( N === 1 || strideX === 0 ) {
+ v = x[ offsetX ];
if ( v === v && N-correction > 0.0 ) {
return 0.0;
}
return NaN;
}
- ix = offset;
+ ix = offsetX;
// Compute an estimate for the mean...
WORKSPACE[ 0 ] = 0.0;
WORKSPACE[ 1 ] = 0;
- snansumpw( N, WORKSPACE, x, stride, ix );
+ snansumpw( N, WORKSPACE, x, strideX, ix );
n = WORKSPACE[ 1 ];
nc = n - correction;
if ( nc <= 0.0 ) {
@@ -105,7 +103,7 @@ function snanvariancepn( N, correction, x, stride, offset ) {
M = float64ToFloat32( M + d );
n += 1;
}
- ix += stride;
+ ix += strideX;
}
return float64ToFloat32( float64ToFloat32(M2/nc) - float64ToFloat32(float64ToFloat32(M/n)*float64ToFloat32(M/nc)) ); // eslint-disable-line max-len
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js
index 7a2ca055b51e..8c4c2e0486a8 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/ndarray.native.js
@@ -20,8 +20,7 @@
// MODULES //
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './snanvariancepn.native.js' );
+var addon = require( './../src/addon.node' );
// MAIN //
@@ -32,27 +31,20 @@ var addon = require( './snanvariancepn.native.js' );
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {Float32Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
* @returns {number} variance
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
*
* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
-* var N = floor( x.length / 2 );
*
-* var v = snanvariancepn( N, 1, x, 2, 1 );
+* var v = snanvariancepn( 5, 1, x, 2, 1 );
* // returns 6.25
*/
-function snanvariancepn( N, correction, x, stride, offset ) {
- var view;
- if ( stride < 0 ) {
- offset += (N-1) * stride;
- }
- view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
- return addon( N, correction, view, stride );
+function snanvariancepn( N, correction, x, strideX, offsetX ) {
+ return addon.ndarray( N, correction, x, strideX, offsetX );
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js
index e09fce5b3698..fc8ba7b4b62c 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snansumpw.js
@@ -47,22 +47,20 @@ var BLOCKSIZE = 128;
* @param {PositiveInteger} N - number of indexed elements
* @param {NumericArray} out - two-element output array whose first element is the accumulated sum and whose second element is the accumulated number of summed values
* @param {Float32Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
* @returns {NumericArray} output array
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
*
* var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN, NaN ] );
-* var N = floor( x.length / 2 );
*
* var out = [ 0.0, 0 ];
-* var v = snansumpw( N, out, x, 2, 1 );
+* var v = snansumpw( 5, out, x, 2, 1 );
* // returns [ 5.0, 4 ]
*/
-function snansumpw( N, out, x, stride, offset ) {
+function snansumpw( N, out, x, strideX, offsetX ) {
var ix;
var s0;
var s1;
@@ -78,7 +76,7 @@ function snansumpw( N, out, x, stride, offset ) {
var v;
var i;
- ix = offset;
+ ix = offsetX;
if ( N < 8 ) {
// Use simple summation...
s = 0.0;
@@ -89,7 +87,7 @@ function snansumpw( N, out, x, stride, offset ) {
s = float64ToFloat32( s + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
}
out[ 0 ] = float64ToFloat32( out[ 0 ] + s );
out[ 1 ] += n;
@@ -114,49 +112,49 @@ function snansumpw( N, out, x, stride, offset ) {
s0 = float64ToFloat32( s0 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s1 = float64ToFloat32( s1 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s2 = float64ToFloat32( s2 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s3 = float64ToFloat32( s3 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s4 = float64ToFloat32( s4 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s5 = float64ToFloat32( s5 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s6 = float64ToFloat32( s6 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
v = x[ ix ];
if ( v === v ) {
s7 = float64ToFloat32( s7 + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
}
// Pairwise sum the accumulators:
s = float64ToFloat32( float64ToFloat32(float64ToFloat32(s0+s1) + float64ToFloat32(s2+s3)) + float64ToFloat32(float64ToFloat32(s4+s5) + float64ToFloat32(s6+s7)) ); // eslint-disable-line max-len
@@ -168,7 +166,7 @@ function snansumpw( N, out, x, stride, offset ) {
s = float64ToFloat32( s + v );
n += 1;
}
- ix += stride;
+ ix += strideX;
}
out[ 0 ] = float64ToFloat32( out[ 0 ] + s );
out[ 1 ] += n;
@@ -177,7 +175,7 @@ function snansumpw( N, out, x, stride, offset ) {
// Recurse by dividing by two, but avoiding non-multiples of unroll factor...
n = floor( N/2 );
n -= n % 8;
- return float64ToFloat32( snansumpw( n, out, x, stride, ix ) + snansumpw( N-n, out, x, stride, ix+(n*stride) ) ); // eslint-disable-line max-len
+ return float64ToFloat32( snansumpw( n, out, x, strideX, ix ) + snansumpw( N-n, out, x, strideX, ix+(n*strideX) ) ); // eslint-disable-line max-len
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js
index 4252fbec5e6e..6364de7bead4 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.js
@@ -20,13 +20,8 @@
// MODULES //
-var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
-var snansumpw = require( './snansumpw.js' );
-
-
-// VARIABLES //
-
-var WORKSPACE = [ 0.0, 0 ];
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
// MAIN //
@@ -46,69 +41,19 @@ var WORKSPACE = [ 0.0, 0 ];
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {Float32Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
* @returns {number} variance
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
*
* var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
*
-* var v = snanvariancepn( N, 1, x, 1 );
+* var v = snanvariancepn( x.length, 1, x, 1 );
* // returns ~4.3333
*/
-function snanvariancepn( N, correction, x, stride ) {
- var mu;
- var ix;
- var M2;
- var nc;
- var M;
- var d;
- var v;
- var n;
- var i;
-
- if ( N <= 0 ) {
- return NaN;
- }
- if ( N === 1 || stride === 0 ) {
- v = x[ 0 ];
- if ( v === v && N-correction > 0.0 ) {
- return 0.0;
- }
- return NaN;
- }
- if ( stride < 0 ) {
- ix = (1-N) * stride;
- } else {
- ix = 0;
- }
- // Compute an estimate for the mean...
- WORKSPACE[ 0 ] = 0.0;
- WORKSPACE[ 1 ] = 0;
- snansumpw( N, WORKSPACE, x, stride, ix );
- n = WORKSPACE[ 1 ];
- nc = n - correction;
- if ( nc <= 0.0 ) {
- return NaN;
- }
- mu = float64ToFloat32( WORKSPACE[ 0 ] / n );
-
- // Compute the variance...
- M2 = 0.0;
- M = 0.0;
- for ( i = 0; i < N; i++ ) {
- v = x[ ix ];
- if ( v === v ) {
- d = float64ToFloat32( v - mu );
- M2 = float64ToFloat32( M2 + float64ToFloat32( d*d ) );
- M = float64ToFloat32( M + d );
- n += 1;
- }
- ix += stride;
- }
- return float64ToFloat32( float64ToFloat32(M2/nc) - float64ToFloat32(float64ToFloat32(M/n)*float64ToFloat32(M/nc)) ); // eslint-disable-line max-len
+function snanvariancepn( N, correction, x, strideX ) {
+ return ndarray( N, correction, x, strideX, stride2offset( N, strideX ) );
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js
index 46b7e17eab5b..3cbe2d351c1d 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/lib/snanvariancepn.native.js
@@ -31,20 +31,19 @@ var addon = require( './../src/addon.node' );
* @param {PositiveInteger} N - number of indexed elements
* @param {number} correction - degrees of freedom adjustment
* @param {Float32Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
* @returns {number} variance
*
* @example
* var Float32Array = require( '@stdlib/array/float32' );
*
* var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
*
-* var v = snanvariancepn( N, 1, x, 1 );
+* var v = snanvariancepn( x.length, 1, x, 1 );
* // returns ~4.3333
*/
-function snanvariancepn( N, correction, x, stride ) {
- return addon( N, correction, x, stride );
+function snanvariancepn( N, correction, x, strideX ) {
+ return addon( N, correction, x, strideX );
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json
index 9e968d3aa6ae..d849b5d496d9 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/manifest.json
@@ -1,6 +1,7 @@
{
"options": {
- "task": "build"
+ "task": "build",
+ "wasm": false
},
"fields": [
{
@@ -27,17 +28,19 @@
"confs": [
{
"task": "build",
+ "wasm": false,
"src": [
- "./src/snanvariancepn.c"
+ "./src/main.c"
],
"include": [
"./include"
],
- "libraries": [
- "-lm"
- ],
+ "libraries": [],
"libpath": [],
"dependencies": [
+ "@stdlib/blas/base/shared",
+ "@stdlib/strided/base/stride2offset",
+ "@stdlib/math/base/assert/is-nanf",
"@stdlib/napi/export",
"@stdlib/napi/argv",
"@stdlib/napi/argv-int64",
@@ -48,31 +51,54 @@
},
{
"task": "benchmark",
+ "wasm": false,
"src": [
- "./src/snanvariancepn.c"
+ "./src/main.c"
],
"include": [
"./include"
],
- "libraries": [
- "-lm"
- ],
+ "libraries": [],
"libpath": [],
- "dependencies": []
+ "dependencies": [
+ "@stdlib/blas/base/shared",
+ "@stdlib/strided/base/stride2offset",
+ "@stdlib/math/base/assert/is-nanf"
+ ]
},
{
"task": "examples",
+ "wasm": false,
"src": [
- "./src/snanvariancepn.c"
+ "./src/main.c"
],
"include": [
"./include"
],
- "libraries": [
- "-lm"
+ "libraries": [],
+ "libpath": [],
+ "dependencies": [
+ "@stdlib/blas/base/shared",
+ "@stdlib/strided/base/stride2offset",
+ "@stdlib/math/base/assert/is-nanf"
+ ]
+ },
+ {
+ "task": "",
+ "wasm": true,
+ "src": [
+ "./src/main.c"
],
+ "include": [
+ "./include"
+ ],
+ "libraries": [],
"libpath": [],
- "dependencies": []
+ "dependencies": [
+ "@stdlib/blas/base/shared",
+ "@stdlib/strided/base/stride2offset",
+ "@stdlib/math/base/assert/is-nanf"
+ ]
}
]
}
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c
index 5d2c9e66be5b..6bd8b68d752a 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/addon.c
@@ -17,6 +17,7 @@
*/
#include "stdlib/stats/base/snanvariancepn.h"
+#include "stdlib/blas/base/shared.h"
#include "stdlib/napi/export.h"
#include "stdlib/napi/argv.h"
#include "stdlib/napi/argv_int64.h"
@@ -35,11 +36,29 @@
static napi_value addon( napi_env env, napi_callback_info info ) {
STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+ STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 );
STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
- STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
- STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
- STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancepn( N, correction, X, stride ), v );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 );
+ STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanvariancepn)( N, correction, X, strideX ), v );
return v;
}
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env environment under which the function is invoked
+* @param info callback data
+* @return Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+ STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+ STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+ STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 3 );
+ STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 4 );
+ STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+ STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 2 );
+ STDLIB_NAPI_CREATE_DOUBLE( env, (double)API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( N, correction, X, strideX, offsetX ), v );
+ return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/snanvariancepn.c b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c
similarity index 55%
rename from lib/node_modules/@stdlib/stats/base/snanvariancepn/src/snanvariancepn.c
rename to lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c
index a945022c2afb..526ddce88ecd 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/snanvariancepn.c
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/src/main.c
@@ -17,7 +17,9 @@
*/
#include "stdlib/stats/base/snanvariancepn.h"
-#include <stdint.h>
+#include "stdlib/strided/base/stride2offset.h"
+#include "stdlib/math/base/assert/is_nanf.h"
+#include "stdlib/blas/base/shared.h"
/**
* Computes the sum of single-precision floating-point strided array elements, ignoring `NaN` values and using pairwise summation.
@@ -30,20 +32,19 @@
*
* - Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." _SIAM Journal on Scientific Computing_ 14 (4): 783–99. doi:[10.1137/0914050](https://doi.org/10.1137/0914050).
*
-* @param N number of indexed elements
-* @param W two-element output array
-* @param X input array
-* @param stride stride length
-* @return output value
+* @param N number of indexed elements
+* @param X input array
+* @param strideX stride length
+* @param offsetX starting index
+* @param n pointer
+* @return output value
*/
-static void snansumpw( const int64_t N, double *W, const float *X, const int64_t stride ) {
- int64_t ix;
- float *xp1;
- float *xp2;
+static float snansumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, CBLAS_INT *n ) {
+ CBLAS_INT ix;
+ CBLAS_INT M;
+ CBLAS_INT m;
+ CBLAS_INT i;
float sum;
- int64_t M;
- int64_t n;
- int64_t i;
float s0;
float s1;
float s2;
@@ -54,26 +55,28 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t
float s7;
float v;
- if ( stride < 0 ) {
- ix = (1-N) * stride;
- } else {
- ix = 0;
+ sum = 0.0f;
+ ix = offsetX;
+ if ( strideX == 0 ) {
+ if ( stdlib_base_is_nanf( X[ ix ] ) ) {
+ return sum;
+ }
+ sum = X[ ix ] * N;
+ *n += N;
+ return sum;
}
if ( N < 8 ) {
// Use simple summation...
sum = 0.0f;
- n = 0;
for ( i = 0; i < N; i++ ) {
v = X[ ix ];
if ( v == v ) {
- sum += X[ ix ];
- n += 1;
+ sum += v;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
}
- W[ 0 ] += (double)sum;
- W[ 1 ] += (double)n;
- return;
+ return sum;
}
// Blocksize for pairwise summation: 128 (NOTE: decreasing the blocksize decreases rounding error as more pairs are summed, but also decreases performance. Because the inner loop is unrolled eight times, the blocksize is effectively `16`.)
if ( N <= 128 ) {
@@ -86,87 +89,76 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t
s5 = 0.0f;
s6 = 0.0f;
s7 = 0.0f;
- n = 0;
M = N % 8;
for ( i = 0; i < N-M; i += 8 ) {
v = X[ ix ];
if ( v == v ) {
s0 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s1 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s2 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s3 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s4 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s5 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s6 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
v = X[ ix ];
if ( v == v ) {
s7 += v;
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
}
// Pairwise sum the accumulators:
- sum = ((s0+s1) + (s2+s3)) + ((s4+s5) + (s6+s7));
+ sum = ( (s0+s1) + (s2+s3) ) + ( (s4+s5) + (s6+s7) );
// Clean-up loop...
for (; i < N; i++ ) {
v = X[ ix ];
if ( v == v ) {
sum += X[ ix ];
- n += 1;
+ *n += 1;
}
- ix += stride;
+ ix += strideX;
}
- W[ 0 ] += (double)sum;
- W[ 1 ] += (double)n;
- return;
+ return sum;
}
// Recurse by dividing by two, but avoiding non-multiples of unroll factor...
- n = N / 2;
- n -= n % 8;
- if ( stride < 0 ) {
- xp1 = (float *)X + ( (n-N)*stride );
- xp2 = (float *)X;
- } else {
- xp1 = (float *)X;
- xp2 = (float *)X + ( n*stride );
- }
- snansumpw( n, W, xp1, stride );
- snansumpw( N-n, W, xp2, stride );
+ m = N / 2;
+ m -= m % 8;
+ return snansumpw( m, X, strideX, ix, n ) + snansumpw( N-m, X, strideX, ix+(m*strideX), n );
}
/**
@@ -181,21 +173,46 @@ static void snansumpw( const int64_t N, double *W, const float *X, const int64_t
* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
*
-* @param N number of indexed elements
-* @param correction degrees of freedom adjustment
-* @param X input array
-* @param stride stride length
-* @return output value
+* @param N number of indexed elements
+* @param correction degrees of freedom adjustment
+* @param X input array
+* @param strideX stride length
+* @return output value
*/
-float stdlib_strided_snanvariancepn( const int64_t N, const float correction, const float *X, const int64_t stride ) {
- double W[] = { 0.0, 0.0 };
- int64_t ix;
- int64_t i;
+float API_SUFFIX(stdlib_strided_snanvariancepn)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX ) {
+ CBLAS_INT ox;
+ ox = stdlib_strided_stride2offset( N, strideX );
+ return API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( N, correction, X, strideX, ox );
+}
+
+/**
+* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm and alternative indexing semantics.
+*
+* ## Method
+*
+* - This implementation uses a two-pass approach, as suggested by Neely (1966).
+*
+* ## References
+*
+* - Neely, Peter M. 1966. "Comparison of Several Algorithms for Computation of Means, Standard Deviations and Correlation Coefficients." _Communications of the ACM_ 9 (7). Association for Computing Machinery: 496–99. doi:[10.1145/365719.365958](https://doi.org/10.1145/365719.365958).
+* - Schubert, Erich, and Michael Gertz. 2018. "Numerically Stable Parallel Computation of (Co-)Variance." In _Proceedings of the 30th International Conference on Scientific and Statistical Database Management_. New York, NY, USA: Association for Computing Machinery. doi:[10.1145/3221269.3223036](https://doi.org/10.1145/3221269.3223036).
+*
+* @param N number of indexed elements
+* @param correction degrees of freedom adjustment
+* @param X input array
+* @param strideX stride length
+* @param offsetX starting index
+* @return output value
+*/
+float API_SUFFIX(stdlib_strided_snanvariancepn_ndarray)( const CBLAS_INT N, const float correction, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+ CBLAS_INT ix;
+ CBLAS_INT i;
+ CBLAS_INT n;
double nc;
double dM;
- double n;
- float M2;
+ float sum;
float mu;
+ float M2;
float M;
float d;
float v;
@@ -203,26 +220,22 @@ float stdlib_strided_snanvariancepn( const int64_t N, const float correction, co
if ( N <= 0 ) {
return 0.0f / 0.0f; // NaN
}
- if ( N == 1 || stride == 0 ) {
- v = X[ 0 ];
+ if ( N == 1 || strideX == 0 ) {
+ v = X[ offsetX ];
if ( v == v && (double)N-(double)correction > 0.0 ) {
return 0.0f;
}
return 0.0f / 0.0f; // NaN
}
// Compute an estimate for the mean...
- snansumpw( N, W, X, stride );
- n = W[ 1 ];
+ n = 0;
+ sum = snansumpw( N, X, strideX, offsetX, &n );
nc = n - (double)correction;
if ( nc <= 0.0 ) {
return 0.0f / 0.0f; // NaN
}
- if ( stride < 0 ) {
- ix = (1-N) * stride;
- } else {
- ix = 0;
- }
- mu = (float)( W[ 0 ] / n );
+ ix = offsetX;
+ mu = (float)( (double)sum / (double)n );
// Compute the variance...
M2 = 0.0f;
@@ -233,9 +246,8 @@ float stdlib_strided_snanvariancepn( const int64_t N, const float correction, co
d = v - mu;
M2 += d * d;
M += d;
- n += 1;
}
- ix += stride;
+ ix += strideX;
}
dM = (double)M;
return (float)((double)M2/nc) - ( (float)(dM/n) * (float)(dM/nc) );
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js
index 18a9eaf4be87..ee221ba51392 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.js
@@ -21,7 +21,6 @@
// MODULES //
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
var Float32Array = require( '@stdlib/array/float32' );
@@ -214,7 +213,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than
});
tape( 'the function supports a `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -231,15 +229,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
NaN
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2, 0 );
+ v = snanvariancepn( 5, 1, x, 2, 0 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', function test( t ) {
- var N;
var x;
var v;
var i;
@@ -256,9 +252,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
4.0, // 0
2.0
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, -2, 8 );
+ v = snanvariancepn( 5, 1, x, -2, 8 );
t.strictEqual( v, 6.25, 'returns expected value' );
x = new Float32Array( 1e3 );
@@ -294,7 +289,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p
});
tape( 'the function supports an `offset` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -310,9 +304,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
NaN,
NaN // 4
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2, 1 );
+ v = snanvariancepn( 5, 1, x, 2, 1 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js
index 506ec9192f9e..f3cd0e840545 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
var resolve = require( 'path' ).resolve;
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
var Float32Array = require( '@stdlib/array/float32' );
@@ -223,7 +222,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than
});
tape( 'the function supports a `stride` parameter', opts, function test( t ) {
- var N;
var x;
var v;
@@ -240,15 +238,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
NaN
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2, 0 );
+ v = snanvariancepn( 5, 1, x, 2, 0 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
- var N;
var x;
var v;
var i;
@@ -265,9 +261,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
4.0, // 0
2.0
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, -2, 8 );
+ v = snanvariancepn( 5, 1, x, -2, 8 );
t.strictEqual( v, 6.25, 'returns expected value' );
x = new Float32Array( 1e3 );
@@ -303,7 +298,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p
});
tape( 'the function supports an `offset` parameter', opts, function test( t ) {
- var N;
var x;
var v;
@@ -319,9 +313,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
NaN,
NaN // 4
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2, 1 );
+ v = snanvariancepn( 5, 1, x, 2, 1 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js
index 6b7588a79921..73ac03fc1657 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.js
@@ -21,7 +21,6 @@
// MODULES //
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
var Float32Array = require( '@stdlib/array/float32' );
@@ -214,7 +213,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than
});
tape( 'the function supports a `stride` parameter', function test( t ) {
- var N;
var x;
var v;
@@ -231,15 +229,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
NaN
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2 );
+ v = snanvariancepn( 5, 1, x, 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', function test( t ) {
- var N;
var x;
var v;
var i;
@@ -256,9 +252,8 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
4.0, // 0
2.0
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, -2 );
+ v = snanvariancepn( 5, 1, x, -2 );
t.strictEqual( v, 6.25, 'returns expected value' );
x = new Float32Array( 1e3 );
@@ -296,7 +291,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p
tape( 'the function supports view offsets', function test( t ) {
var x0;
var x1;
- var N;
var v;
x0 = new Float32Array([
@@ -314,9 +308,8 @@ tape( 'the function supports view offsets', function test( t ) {
]);
x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
- N = floor(x1.length / 2);
- v = snanvariancepn( N, 1, x1, 2 );
+ v = snanvariancepn( 5, 1, x1, 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js
index db52ef0db2d0..91fb98216d57 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancepn/test/test.snanvariancepn.native.js
@@ -22,7 +22,6 @@
var resolve = require( 'path' ).resolve;
var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
var Float32Array = require( '@stdlib/array/float32' );
@@ -223,7 +222,6 @@ tape( 'if provided a `correction` parameter yielding a correction term less than
});
tape( 'the function supports a `stride` parameter', opts, function test( t ) {
- var N;
var x;
var v;
@@ -240,15 +238,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
NaN
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, 2 );
+ v = snanvariancepn( 5, 1, x, 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();
});
tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
- var N;
var x;
var v;
var i;
@@ -265,9 +261,8 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
4.0, // 0
2.0
]);
- N = floor( x.length / 2 );
- v = snanvariancepn( N, 1, x, -2 );
+ v = snanvariancepn( 5, 1, x, -2 );
t.strictEqual( v, 6.25, 'returns expected value' );
x = new Float32Array( 1e3 );
@@ -305,7 +300,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p
tape( 'the function supports view offsets', opts, function test( t ) {
var x0;
var x1;
- var N;
var v;
x0 = new Float32Array([
@@ -323,9 +317,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
]);
x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
- N = floor(x1.length / 2);
- v = snanvariancepn( N, 1, x1, 2 );
+ v = snanvariancepn( 5, 1, x1, 2 );
t.strictEqual( v, 6.25, 'returns expected value' );
t.end();