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4 changes: 2 additions & 2 deletions docs/migration-guides/numpy/README.md
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Expand Up @@ -35,10 +35,10 @@ limitations under the License.
| Broadcast a scalar to a specified shape | `np.broadcast_to(np.array(scalar), shape)` | [`broadcastScalar(scalar, shape)`][@stdlib/ndarray/broadcast-scalar] |
| Copy an array | `np.copy(x)` | [`copy(x)`][@stdlib/ndarray/copy] |
| Count the number of falsy values in an array | `x.size-np.count_nonzero(x)` | [`countFalsy(x)`][@stdlib/ndarray/count-falsy] |
| Count the number of truthy values in an array | `np.count_nonzeros(x)` | [`countTruthy(x)`][@stdlib/ndarray/count-truthy] |
| Count the number of truthy values in an array | `np.count_nonzero(x)` | [`countTruthy(x)`][@stdlib/ndarray/count-truthy] |
| Test whether an array includes a specific value | `np.any(np.equal(x,v))` | [`includes(x,v)`][@stdlib/ndarray/includes] |
| Reverse the elements along a dimension | `np.flip(x, axis=dim)` | [`reverseDimension(x, dim)`][@stdlib/ndarray/reverse-dimension] |
| Prepend a a specified number of singleton dimensions | `np.reshape(x, (1,)*n + x.shape)` | [`prependSingletonDimensions(x, n)`][@stdlib/ndarray/prepend-singleton-dimensions] |
| Prepend a specified number of singleton dimensions | `np.reshape(x, (1,)*n + x.shape)` | [`prependSingletonDimensions(x, n)`][@stdlib/ndarray/prepend-singleton-dimensions] |
| Test whether an array contains at least `n` truthy values | `np.count_nonzero(x) >= n` | [`some(x, n)`][@stdlib/ndarray/some] |

<!-- lint enable table-pipe-alignment -->
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Expand Up @@ -120,6 +120,8 @@ static double benchmark1( int iterations, int len ) {
if ( y[ len-1 ] != y[ len-1 ] ) {
printf( "should not return NaN\n" );
}
free( x );
free( y );
return elapsed;
}

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2 changes: 1 addition & 1 deletion lib/node_modules/@stdlib/blas/ext/base/sdiff/README.md
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Expand Up @@ -68,7 +68,7 @@ The function has the following parameters:
- **workspace**: workspace [`Float32Array`][@stdlib/array/float32]. Must have `N + N1 + N2 - 1` elements.
- **strideW**: stride length for `workspace`.

The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to differences of every other element:
The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute differences of every other element:

```javascript
var Float32Array = require( '@stdlib/array/float32' );
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Expand Up @@ -16,8 +16,6 @@
* limitations under the License.
*/

/* eslint-disable space-in-parens */

import zeros = require( '@stdlib/ndarray/base/zeros' );
import reinterpretBoolean = require( './index' );

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