# ndfind
[![pypi](https://img.shields.io/pypi/v/ndfind.svg)](https://pypi.python.org/pypi/ndfind)
[![python](https://img.shields.io/pypi/pyversions/ndfind.svg)](https://pypi.org/project/ndfind/)
![pytest](https://github.com/axil/ndfind/actions/workflows/python-package.yml/badge.svg)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![License](https://img.shields.io/pypi/l/ndfind)](https://pypi.org/project/ndfind/)
A collection of three cython-optimized search functions for NumPy. When the required value is found,
they return immediately, without scanning the whole array. It can result in 1000x or larger speedups for
huge arrays if the value is located close to the the beginning of the array.
## Installation:
pip install ndfind
## Contents
Basic usage:
- `find(a, v)` finds v in a, returns index of the first match or -1 if not found
- `first_above(a, v)` finds first element in a that is strictly greater than `v`,
returns its index or -1 if not found
- `first_nonzero(a)` finds the first nonzero element in a,
returns its index or -1 if not found
Advanced usage:
- `find(a, v, rtol=1e-05, atol=1e-08, sorted=False, missing=-1, raises=False)`
Returns the index of the first element in `a` equal to `v`.
If either a or v (or both) is of floating type, the parameters
`atol` (absolute tolerance) and `rtol` (relative tolerance)
are used for comparison (see `np.isclose()` for details).
Otherwise, returns the `missing` value (-1 by default)
or raises a `ValueError` if `raises=True`.
For example,
```python
>>> find([3, 1, 4, 1, 5], 4)
2
>>> find([1, 2, 3], 7)
-1
>>> find([1.1, 1.2, 1.3], 1.2)
1
>>> find(np.arange(0, 1, 0.1), 0.3)
3
>>> find([[3, 8, 4], [5, 2, 7]], 7)
(1, 2)
>>> find([[3, 8, 4], [5, 2, 7]], 9)
-1
>>> find([999980., 999990., 1e6], 1e6)
1
>>> find([999980., 999990., 1e6], 1e6, rtol=1e-9)
2
```
- `first_above(a, v, sorted=False, missing=-1, raises=False)`
Returns the index of the first element in `a` strictly greater than `v`.
If either a or v (or both) is of floating type, the parameters
`atol` (absolute tolerance) and `rtol` (relative tolerance)
are used for comparison (see `np.isclose()` for details).
In 2D and above the the values in `a` are always tested and returned in
row-major, C-style order.
If there is no value in `a` greater than `v`, returns the `default` value
(-1 by default) or raises a `ValueError` if `raises=True`.
`sorted`, use binary search to speed things up (works only if the array is sorted)
For example,
```python
>>> first_above([4, 5, 8, 2, 7], 6)
2
>>> first_above([[4, 5, 8], [2, 7, 3]], 6)
(0, 2)
>>> first_above([5, 6, 7], 9)
3
```
- `first_nonzero(a, missing=-1, raises=False)`
Returns the index of the first nonzero element in `a`.
In 2D and above the the values in `a` are always tested and returned in
row-major, C-style order.
For example,
```python
>>> first_nonzero([0, 0, 7, 0, 5])
2
>>> first_nonzero([False, True, False, False, True])
1
>>> first_nonzero([[0, 0, 0, 0], [0, 0, 5, 3]])
(1, 2)
```
## Testing
Run `pytest` in the project root.
Raw data
{
"_id": null,
"home_page": "https://github.com/axil/ndfind",
"name": "ndfind",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "find,first_above,first_nonzero,numpy,python",
"author": "Lev Maximov",
"author_email": "lev.maximov@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/fb/94/b483cdde885621c1bc8619b7e56d8cc530202be96983da930b11e1260d5e/ndfind-0.4.1.tar.gz",
"platform": null,
"description": "\ufeff# ndfind\n\n[![pypi](https://img.shields.io/pypi/v/ndfind.svg)](https://pypi.python.org/pypi/ndfind)\n[![python](https://img.shields.io/pypi/pyversions/ndfind.svg)](https://pypi.org/project/ndfind/)\n![pytest](https://github.com/axil/ndfind/actions/workflows/python-package.yml/badge.svg)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![License](https://img.shields.io/pypi/l/ndfind)](https://pypi.org/project/ndfind/)\n\nA collection of three cython-optimized search functions for NumPy. When the required value is found,\nthey return immediately, without scanning the whole array. It can result in 1000x or larger speedups for \nhuge arrays if the value is located close to the the beginning of the array.\n\n## Installation: \n\n pip install ndfind\n\n## Contents\n\nBasic usage: \n- `find(a, v)` finds v in a, returns index of the first match or -1 if not found\n- `first_above(a, v)` finds first element in a that is strictly greater than `v`, \nreturns its index or -1 if not found \n- `first_nonzero(a)` finds the first nonzero element in a, \nreturns its index or -1 if not found\n\nAdvanced usage:\n- `find(a, v, rtol=1e-05, atol=1e-08, sorted=False, missing=-1, raises=False)`\n Returns the index of the first element in `a` equal to `v`.\n If either a or v (or both) is of floating type, the parameters\n `atol` (absolute tolerance) and `rtol` (relative tolerance) \n are used for comparison (see `np.isclose()` for details).\n \n Otherwise, returns the `missing` value (-1 by default)\n or raises a `ValueError` if `raises=True`.\n\n For example,\n\n```python\n >>> find([3, 1, 4, 1, 5], 4)\n 2\n >>> find([1, 2, 3], 7)\n -1\n >>> find([1.1, 1.2, 1.3], 1.2)\n 1\n >>> find(np.arange(0, 1, 0.1), 0.3) \n 3\n >>> find([[3, 8, 4], [5, 2, 7]], 7)\n (1, 2)\n >>> find([[3, 8, 4], [5, 2, 7]], 9)\n -1\n >>> find([999980., 999990., 1e6], 1e6)\n 1\n >>> find([999980., 999990., 1e6], 1e6, rtol=1e-9)\n 2\n```\n\n- `first_above(a, v, sorted=False, missing=-1, raises=False)`\n Returns the index of the first element in `a` strictly greater than `v`.\n If either a or v (or both) is of floating type, the parameters\n `atol` (absolute tolerance) and `rtol` (relative tolerance) \n are used for comparison (see `np.isclose()` for details).\n\n In 2D and above the the values in `a` are always tested and returned in\n row-major, C-style order.\n\n If there is no value in `a` greater than `v`, returns the `default` value \n (-1 by default) or raises a `ValueError` if `raises=True`.\n\n `sorted`, use binary search to speed things up (works only if the array is sorted)\n\n \n For example,\n\n```python\n >>> first_above([4, 5, 8, 2, 7], 6)\n 2 \n >>> first_above([[4, 5, 8], [2, 7, 3]], 6)\n (0, 2) \n >>> first_above([5, 6, 7], 9)\n 3 \n```\n\n- `first_nonzero(a, missing=-1, raises=False)`\n Returns the index of the first nonzero element in `a`.\n\n In 2D and above the the values in `a` are always tested and returned in\n row-major, C-style order.\n\n For example,\n\n```python\n>>> first_nonzero([0, 0, 7, 0, 5])\n2\n>>> first_nonzero([False, True, False, False, True])\n1\n>>> first_nonzero([[0, 0, 0, 0], [0, 0, 5, 3]])\n(1, 2)\n```\n\n## Testing\n\nRun `pytest` in the project root.\n",
"bugtrack_url": null,
"license": "MIT License",
"summary": "A collection of cython-optimized search functions for NumPy",
"version": "0.4.1",
"project_urls": {
"Homepage": "https://github.com/axil/ndfind"
},
"split_keywords": [
"find",
"first_above",
"first_nonzero",
"numpy",
"python"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "8b1535bdefbe637e8f4b72b6e8ccae087bc3efbd44f9e68296d9b284f08ab04a",
"md5": "b1c64cad0389ae1736c612edbd6395e4",
"sha256": "737f352dace32c61e49d2eecdfa4c54ed2c0eff8195e52686509e8a88fa66067"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "b1c64cad0389ae1736c612edbd6395e4",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.7",
"size": 431402,
"upload_time": "2023-05-08T06:03:22",
"upload_time_iso_8601": "2023-05-08T06:03:22.450570Z",
"url": "https://files.pythonhosted.org/packages/8b/15/35bdefbe637e8f4b72b6e8ccae087bc3efbd44f9e68296d9b284f08ab04a/ndfind-0.4.1-cp310-cp310-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "abe0d8ab4d5d73da5723aa58f6513c454b9b7cbabc68226f19ee0291a29df712",
"md5": "fc22391ad876ccbfb58df8d864c9006c",
"sha256": "fc255c699223165b539722ec978155a77c3540400677170525febb2022dc1580"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "fc22391ad876ccbfb58df8d864c9006c",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.7",
"size": 2514563,
"upload_time": "2023-05-08T06:00:46",
"upload_time_iso_8601": "2023-05-08T06:00:46.469552Z",
"url": "https://files.pythonhosted.org/packages/ab/e0/d8ab4d5d73da5723aa58f6513c454b9b7cbabc68226f19ee0291a29df712/ndfind-0.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "46e5c1d611d392ad4628f5087d41a53abf1d8b41abf439c4b8274d90cc731b5a",
"md5": "b665f8bddac75c0c5dde31abbab6227a",
"sha256": "096b5019533471efe2c5309972f999e857a045dd2bf9eced8b0f1c6c4c845726"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp310-cp310-win_amd64.whl",
"has_sig": false,
"md5_digest": "b665f8bddac75c0c5dde31abbab6227a",
"packagetype": "bdist_wheel",
"python_version": "cp310",
"requires_python": ">=3.7",
"size": 282996,
"upload_time": "2023-05-08T06:02:41",
"upload_time_iso_8601": "2023-05-08T06:02:41.435570Z",
"url": "https://files.pythonhosted.org/packages/46/e5/c1d611d392ad4628f5087d41a53abf1d8b41abf439c4b8274d90cc731b5a/ndfind-0.4.1-cp310-cp310-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "78a44fd4bdff71dd7ff4689226372fea137ad7dd66ce24c0d634aee2670a638c",
"md5": "46bd28d535f79f633c0bfed161387476",
"sha256": "8dbdccfc5b60c9fc41f50ea7bc34ff1c749b545808163f6598baa2c782ad6dff"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "46bd28d535f79f633c0bfed161387476",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.7",
"size": 429057,
"upload_time": "2023-05-08T06:03:25",
"upload_time_iso_8601": "2023-05-08T06:03:25.030746Z",
"url": "https://files.pythonhosted.org/packages/78/a4/4fd4bdff71dd7ff4689226372fea137ad7dd66ce24c0d634aee2670a638c/ndfind-0.4.1-cp311-cp311-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "d3dfb8153fbd5169b33fd8ca40c92df3675813a8005e111c320d7db3e0dbb17d",
"md5": "341d34a225c3a2ef9c199ae2e89aa137",
"sha256": "fc41a5105bc41aa979f47bdd616f06d9f2252c4814c1a168ec8c9ebe6041b72a"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "341d34a225c3a2ef9c199ae2e89aa137",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.7",
"size": 2731031,
"upload_time": "2023-05-08T06:00:48",
"upload_time_iso_8601": "2023-05-08T06:00:48.792618Z",
"url": "https://files.pythonhosted.org/packages/d3/df/b8153fbd5169b33fd8ca40c92df3675813a8005e111c320d7db3e0dbb17d/ndfind-0.4.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "bcf6f637befbddc985423ffee01ef4cf075d9ceb661841d1ca47f52cf0315458",
"md5": "77e2da63d901a23056333c5c3e6e7692",
"sha256": "29f822c294bcb24a9802aa8616109ccda521b89874343eb890fc61f8b1e8522f"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp311-cp311-win_amd64.whl",
"has_sig": false,
"md5_digest": "77e2da63d901a23056333c5c3e6e7692",
"packagetype": "bdist_wheel",
"python_version": "cp311",
"requires_python": ">=3.7",
"size": 284017,
"upload_time": "2023-05-08T06:02:43",
"upload_time_iso_8601": "2023-05-08T06:02:43.551312Z",
"url": "https://files.pythonhosted.org/packages/bc/f6/f637befbddc985423ffee01ef4cf075d9ceb661841d1ca47f52cf0315458/ndfind-0.4.1-cp311-cp311-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "a79e7af2ef64be3b5d43ca0ac38ae1584bef9351c94b694e59d87d4ce22b0392",
"md5": "cfbb899cf36484ddbc761e1a1a8040ec",
"sha256": "4997a5c811487783256392a47d99408f725e6912a4f791ae6b4c9506f72c2e83"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp38-cp38-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "cfbb899cf36484ddbc761e1a1a8040ec",
"packagetype": "bdist_wheel",
"python_version": "cp38",
"requires_python": ">=3.7",
"size": 420591,
"upload_time": "2023-05-08T06:03:27",
"upload_time_iso_8601": "2023-05-08T06:03:27.090048Z",
"url": "https://files.pythonhosted.org/packages/a7/9e/7af2ef64be3b5d43ca0ac38ae1584bef9351c94b694e59d87d4ce22b0392/ndfind-0.4.1-cp38-cp38-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "17f7276b350f94eeae7f081189dda9dd87026bba3c1039bc54666149abcec2c4",
"md5": "fdce2e60569e640070e3c7d03d815572",
"sha256": "1db561592983361aca85c88d35fc4f7a75e2d0ad5273ebe9a32cc40e23a2ef6e"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "fdce2e60569e640070e3c7d03d815572",
"packagetype": "bdist_wheel",
"python_version": "cp38",
"requires_python": ">=3.7",
"size": 2655262,
"upload_time": "2023-05-08T06:00:51",
"upload_time_iso_8601": "2023-05-08T06:00:51.076376Z",
"url": "https://files.pythonhosted.org/packages/17/f7/276b350f94eeae7f081189dda9dd87026bba3c1039bc54666149abcec2c4/ndfind-0.4.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "7135f4378432ede8d9569e4f5bf2a24484af3843dc52dff76c0ce3d2a7cdc5ed",
"md5": "26b7587d20c3d6f6de9ba40fe9923f27",
"sha256": "b0e621d4c6ad857d548a36970e2d9ddd2cd77a5d8094adb76f56483f0df54f89"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp38-cp38-win_amd64.whl",
"has_sig": false,
"md5_digest": "26b7587d20c3d6f6de9ba40fe9923f27",
"packagetype": "bdist_wheel",
"python_version": "cp38",
"requires_python": ">=3.7",
"size": 294638,
"upload_time": "2023-05-08T06:02:45",
"upload_time_iso_8601": "2023-05-08T06:02:45.510973Z",
"url": "https://files.pythonhosted.org/packages/71/35/f4378432ede8d9569e4f5bf2a24484af3843dc52dff76c0ce3d2a7cdc5ed/ndfind-0.4.1-cp38-cp38-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "38f67127d6492e18a2b6be41992dfaa18f3f7bc2cd382e8fb6e5d07a418520b0",
"md5": "748ec5818db47da22b37a2bcecf4fd9e",
"sha256": "8a0df0f7b2cc110034484194638eeef860f7d450f9e53599bbf12eed190512eb"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp39-cp39-macosx_10_9_x86_64.whl",
"has_sig": false,
"md5_digest": "748ec5818db47da22b37a2bcecf4fd9e",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.7",
"size": 439528,
"upload_time": "2023-05-08T06:03:28",
"upload_time_iso_8601": "2023-05-08T06:03:28.846397Z",
"url": "https://files.pythonhosted.org/packages/38/f6/7127d6492e18a2b6be41992dfaa18f3f7bc2cd382e8fb6e5d07a418520b0/ndfind-0.4.1-cp39-cp39-macosx_10_9_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "ebfde9846bcbf89a227cf60d4fb358a4db1843b821dc4002a0d32d2b6bffe88c",
"md5": "6723c6869d77adf869f8117147450ded",
"sha256": "889e47047c275d972017460a0ce9f4975b4663fb88fb23ac76180e07687f1c0f"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"has_sig": false,
"md5_digest": "6723c6869d77adf869f8117147450ded",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.7",
"size": 2562167,
"upload_time": "2023-05-08T06:00:53",
"upload_time_iso_8601": "2023-05-08T06:00:53.536854Z",
"url": "https://files.pythonhosted.org/packages/eb/fd/e9846bcbf89a227cf60d4fb358a4db1843b821dc4002a0d32d2b6bffe88c/ndfind-0.4.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "e8406e49ba5aaf17a09b75b6db2e07f479de852653c5c60fe2753cbc32948533",
"md5": "e3ae756a803cc4527ca7925af9590814",
"sha256": "a415580b43c305c61c9ed35b849a5e1727edc206ab8ea168fb67b75177c60f93"
},
"downloads": -1,
"filename": "ndfind-0.4.1-cp39-cp39-win_amd64.whl",
"has_sig": false,
"md5_digest": "e3ae756a803cc4527ca7925af9590814",
"packagetype": "bdist_wheel",
"python_version": "cp39",
"requires_python": ">=3.7",
"size": 290663,
"upload_time": "2023-05-08T06:02:47",
"upload_time_iso_8601": "2023-05-08T06:02:47.060073Z",
"url": "https://files.pythonhosted.org/packages/e8/40/6e49ba5aaf17a09b75b6db2e07f479de852653c5c60fe2753cbc32948533/ndfind-0.4.1-cp39-cp39-win_amd64.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "fb94b483cdde885621c1bc8619b7e56d8cc530202be96983da930b11e1260d5e",
"md5": "25e1764c1979c875becd5a7d5219f7d2",
"sha256": "db3ec9bbfca1a027a31d47ed8c449371e0c2e876da7a51f032e49639e91d3f49"
},
"downloads": -1,
"filename": "ndfind-0.4.1.tar.gz",
"has_sig": false,
"md5_digest": "25e1764c1979c875becd5a7d5219f7d2",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 300776,
"upload_time": "2023-05-08T05:56:20",
"upload_time_iso_8601": "2023-05-08T05:56:20.872128Z",
"url": "https://files.pythonhosted.org/packages/fb/94/b483cdde885621c1bc8619b7e56d8cc530202be96983da930b11e1260d5e/ndfind-0.4.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-05-08 05:56:20",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "axil",
"github_project": "ndfind",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [],
"lcname": "ndfind"
}