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‎.gitignore‎

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# Git #
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#######
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.worktrees
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# Visual Studio #
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#################
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‎docs/migration-guides/numpy/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2026 The Stdlib Authors.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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-->
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<!-- lint disable expected-html-sections -->
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# NumPy
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> Migration guide for NumPy.
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## Common Operations
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<!-- lint disable table-pipe-alignment -->
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| Description | NumPy | stdlib |
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| ----------- | ----- | ------ |
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| Append a zero-filled array of the same shape along a specified dimension | `np.concat((x, np.zeros_like(x)), axis=dim)` | [`concat([x, zerosLike(x)], {dim: dim})`][@stdlib/ndarray/concat] |
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| Broadcast an array to a specified shape | `np.broadcast_to(x, shape)` | [`broadcastArray(x, shape)`][@stdlib/ndarray/broadcast-array] |
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| Broadcast a scalar to a specified shape | `np.broadcast_to(np.array(scalar), shape)` | [`broadcastScalar(scalar, shape)`][@stdlib/ndarray/broadcast-scalar] |
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| Compute the maximum absolute value | `np.max(np.abs(x))` | [`maxabs(x)`][@stdlib/stats/maxabs] |
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| Compute the minimum absolute value | `np.min(np.abs(x))` | [`minabs(x)`][@stdlib/stats/minabs] |
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| Concatenate a list of arrays along the second-to-last dimension | `np.concat(arrays, axis=-2)` | [`vconcat(arrays)`][@stdlib/ndarray/vconcat] |
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| Concatenate a list of arrays along the last dimension | `np.concat(arrays, axis=-1)` | [`hconcat(arrays)`][@stdlib/ndarray/hconcat] |
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| Concatenate a list of one-dimensional arrays as columns | `np.column_stack(arrays)` | [`colcat(arrays)`][@stdlib/ndarray/colcat] |
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| Concatenate a list of one-dimensional arrays as rows | `np.vstack(arrays)` | [`rowcat(arrays)`][@stdlib/ndarray/rowcat] |
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| Copy an array | `np.copy(x)` | [`copy(x)`][@stdlib/ndarray/copy] |
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| Count the number of falsy values in an array | `x.size-np.count_nonzero(x)` | [`countFalsy(x)`][@stdlib/ndarray/count-falsy] |
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| Count the number of truthy values in an array | `np.count_nonzero(x)` | [`countTruthy(x)`][@stdlib/ndarray/count-truthy] |
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| Create a sorted copy of an array | `np.sort(x)` | [`toSorted(x)`][@stdlib/blas/ext/to-sorted] |
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| Create an array containing evenly spaced numbers over a specified interval and having a desired shape | `np.reshape(np.linspace(start, stop), shape)` | [`linspace(shape, start, stop)`][@stdlib/blas/ext/linspace] |
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| Create an array of uniformly distributed pseudorandom numbers | `np.random.default_rng().uniform(low,high,shape)` | [`uniform(shape,low,high)`][@stdlib/random/uniform] |
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| Filter an array according to a predicate function | `x[np.vectorize(predicate)(x)]` | [`filter(x, predicate)`][@stdlib/ndarray/filter] |
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| Find the index of the first element which equals a specified value | `np.argmax(x == v, axis=dim)` | [`indexOf(x, v, {dim: dim})`][@stdlib/blas/ext/index-of] |
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| Find the index of the last element which equals a specified value | `x.shape[dim]-1-np.argmax(np.flip(x, axis=dim) == v, axis=dim)` | [`lastIndexOf(x, v, {dim: dim})`][@stdlib/blas/ext/last-index-of] |
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| Flatten an array to a desired depth | `np.reshape(x, newshape)` | [`flatten(x, {depth: depth})`][@stdlib/ndarray/flatten] |
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| Flatten an array starting from a specific dimension | `np.reshape(x, x.shape[:dim] + (-1,))` | [`flattenFrom(x, dim)`][@stdlib/ndarray/flatten-from] |
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| Prepend a specified number of singleton dimensions | `np.reshape(x, (1,)*n + x.shape)` | [`prependSingletonDimensions(x, n)`][@stdlib/ndarray/prepend-singleton-dimensions] |
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| Prepend a zero-filled array of the same shape along a specified dimension | `np.concat((np.zeros_like(x), x), axis=dim)` | [`concat([zerosLike(x), x], {dim: dim})`][@stdlib/ndarray/concat] |
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| Remove singleton dimensions | `np.squeeze(x)` | [`removeSingletonDimensions(x)`][@stdlib/ndarray/remove-singleton-dimensions] |
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| Reverse the elements along a dimension | `np.flip(x, axis=dim)` | [`reverseDimension(x, dim)`][@stdlib/ndarray/reverse-dimension] |
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| Rotate an array by 90 degrees in a specified plane | `np.rot90(x, axes=dims)` | [`rot90(x, {dims: dims})`][@stdlib/ndarray/rot90] |
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| Rotate an array by 180 degrees in a specified plane | `np.rot90(x, k=2, axes=dims)` | [`rot180(x, {dims: dims})`][@stdlib/ndarray/rot180] |
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| Sort an array in-place | `x[:] = np.sort(x)` | [`sort(x)`][@stdlib/blas/ext/sort] |
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| Test whether an array contains at least `n` truthy values | `np.count_nonzero(x) >= n` | [`some(x, n)`][@stdlib/ndarray/some] |
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| Test whether an array contains truthy values | `np.any(x)` | [`any(x)`][@stdlib/ndarray/any] |
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| Test whether an array includes a specific value | `np.any(x == v)` | [`includes(x,v)`][@stdlib/ndarray/includes] |
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<!-- lint enable table-pipe-alignment -->
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## Function Reference
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{{table}}
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<section class="links">
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[@stdlib/blas/ext/index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/index-of
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[@stdlib/blas/ext/last-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/last-index-of
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[@stdlib/blas/ext/linspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/linspace
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[@stdlib/blas/ext/sort]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/sort
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[@stdlib/blas/ext/to-sorted]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/to-sorted
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[@stdlib/ndarray/any]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/any
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[@stdlib/ndarray/broadcast-array]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/broadcast-array
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[@stdlib/ndarray/broadcast-scalar]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/broadcast-scalar
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[@stdlib/ndarray/colcat]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/colcat
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[@stdlib/ndarray/concat]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/concat
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[@stdlib/ndarray/copy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/copy
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[@stdlib/ndarray/count-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/count-falsy
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[@stdlib/ndarray/count-truthy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/count-truthy
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[@stdlib/ndarray/filter]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/filter
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[@stdlib/ndarray/flatten]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/flatten
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[@stdlib/ndarray/flatten-from]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/flatten-from
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[@stdlib/ndarray/hconcat]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/hconcat
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[@stdlib/ndarray/includes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/includes
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[@stdlib/ndarray/prepend-singleton-dimensions]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/prepend-singleton-dimensions
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[@stdlib/ndarray/remove-singleton-dimensions]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/remove-singleton-dimensions
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[@stdlib/ndarray/reverse-dimension]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/reverse-dimension
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[@stdlib/ndarray/rot90]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/rot90
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[@stdlib/ndarray/rot180]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/rot180
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[@stdlib/ndarray/rowcat]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/rowcat
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[@stdlib/ndarray/some]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/some
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[@stdlib/ndarray/vconcat]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/vconcat
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[@stdlib/random/uniform]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/random/uniform
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[@stdlib/stats/maxabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/maxabs
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[@stdlib/stats/minabs]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/minabs
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</section>
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<!-- /.links -->

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