clusterzeug


Nameclusterzeug JSON
Version 0.10 PyPI version JSON
download
home_pagehttps://github.com/hansalemaos/clusterzeug
SummarySome functions for clustering
upload_time2023-10-28 22:29:48
maintainer
docs_urlNone
authorJohannes Fischer
requires_python
licenseMIT
keywords clustering data
VCS
bugtrack_url
requirements numexpr numpy scikit_learn
Travis-CI No Travis.
coveralls test coverage No coveralls.
            
# Some functions for clustering 

## Tested against Windows / Python 3.11 / Anaconda

## pip install clusterzeug

```python


from clusterzeug import (
    birchcluster,
    gaussianmixture,
    opticscluster,
    hdbscancluster,
    dbscan,
    agglomerativeclustering,
    spectralclustering,
    kmeanscluster,
    minibatchkmeanscluster,
    afinity_propagation,
    mean_shift,
)
import numpy as np
import random
data = np.array(
    [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(100)],
    dtype=np.int64,
)
a1 = birchcluster(data, n_clusters=10)
a2 = gaussianmixture(data, n_components=5)
a3 = opticscluster(data, min_samples=5)
a4 = hdbscancluster(data, min_cluster_size=5)
a5 = dbscan(data, eps=0.5, min_samples=5)
a6 = agglomerativeclustering(data, n_clusters=10)
a7 = spectralclustering(data, n_clusters=10)
res = kmeanscluster(data, n_clusters=10)
print(res)
res2 = minibatchkmeanscluster(data, n_clusters=10)
print(res2)
aff = afinity_propagation(data, damping=0.5, preference=-10)
print(aff)
ms = mean_shift(data,bandwidth=2.0)
print(ms)

```

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/hansalemaos/clusterzeug",
    "name": "clusterzeug",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "clustering,data",
    "author": "Johannes Fischer",
    "author_email": "aulasparticularesdealemaosp@gmail.com",
    "download_url": "https://files.pythonhosted.org/packages/bf/ea/e76ebb8e944c8fb3fda280e2110bbd84ea693e6104bf3eb368724efec8ce/clusterzeug-0.10.tar.gz",
    "platform": null,
    "description": "\r\n# Some functions for clustering \r\n\r\n## Tested against Windows / Python 3.11 / Anaconda\r\n\r\n## pip install clusterzeug\r\n\r\n```python\r\n\r\n\r\nfrom clusterzeug import (\r\n    birchcluster,\r\n    gaussianmixture,\r\n    opticscluster,\r\n    hdbscancluster,\r\n    dbscan,\r\n    agglomerativeclustering,\r\n    spectralclustering,\r\n    kmeanscluster,\r\n    minibatchkmeanscluster,\r\n    afinity_propagation,\r\n    mean_shift,\r\n)\r\nimport numpy as np\r\nimport random\r\ndata = np.array(\r\n    [[random.randint(1, 1000), random.randint(1, 1000)] for _ in range(100)],\r\n    dtype=np.int64,\r\n)\r\na1 = birchcluster(data, n_clusters=10)\r\na2 = gaussianmixture(data, n_components=5)\r\na3 = opticscluster(data, min_samples=5)\r\na4 = hdbscancluster(data, min_cluster_size=5)\r\na5 = dbscan(data, eps=0.5, min_samples=5)\r\na6 = agglomerativeclustering(data, n_clusters=10)\r\na7 = spectralclustering(data, n_clusters=10)\r\nres = kmeanscluster(data, n_clusters=10)\r\nprint(res)\r\nres2 = minibatchkmeanscluster(data, n_clusters=10)\r\nprint(res2)\r\naff = afinity_propagation(data, damping=0.5, preference=-10)\r\nprint(aff)\r\nms = mean_shift(data,bandwidth=2.0)\r\nprint(ms)\r\n\r\n```\r\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Some functions for clustering",
    "version": "0.10",
    "project_urls": {
        "Homepage": "https://github.com/hansalemaos/clusterzeug"
    },
    "split_keywords": [
        "clustering",
        "data"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "4a4f2047de8e050a02fa3eb97b2d674e902045413aaed3d84822757a725e335a",
                "md5": "e5cc39b6877a34caf0ecf9f6dfec3041",
                "sha256": "c16824e37716a622be488df741fe08531aa1cbfadcec5b9e56f2998ef3fd7042"
            },
            "downloads": -1,
            "filename": "clusterzeug-0.10-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "e5cc39b6877a34caf0ecf9f6dfec3041",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 21991,
            "upload_time": "2023-10-28T22:29:46",
            "upload_time_iso_8601": "2023-10-28T22:29:46.652334Z",
            "url": "https://files.pythonhosted.org/packages/4a/4f/2047de8e050a02fa3eb97b2d674e902045413aaed3d84822757a725e335a/clusterzeug-0.10-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "bfeae76ebb8e944c8fb3fda280e2110bbd84ea693e6104bf3eb368724efec8ce",
                "md5": "ebc9d4dda8bc329f6c3fbea02b06619c",
                "sha256": "358c62f02d152995ffa8173c3293818333941e80fffd59f562755da2bc5a6112"
            },
            "downloads": -1,
            "filename": "clusterzeug-0.10.tar.gz",
            "has_sig": false,
            "md5_digest": "ebc9d4dda8bc329f6c3fbea02b06619c",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 21495,
            "upload_time": "2023-10-28T22:29:48",
            "upload_time_iso_8601": "2023-10-28T22:29:48.477483Z",
            "url": "https://files.pythonhosted.org/packages/bf/ea/e76ebb8e944c8fb3fda280e2110bbd84ea693e6104bf3eb368724efec8ce/clusterzeug-0.10.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-10-28 22:29:48",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "hansalemaos",
    "github_project": "clusterzeug",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "requirements": [
        {
            "name": "numexpr",
            "specs": []
        },
        {
            "name": "numpy",
            "specs": []
        },
        {
            "name": "scikit_learn",
            "specs": []
        }
    ],
    "lcname": "clusterzeug"
}
        
Elapsed time: 0.32123s