Pycewise
Installation
pip install pycewise
Optional installation requirements
The main functionnality of this package (computing a segmented linear regression) can be used without any third-party code.
For additional features, the following packages should be installed (pip install <package_name>):
- numpy
- statsmodels
- jupyter
- matplotlib
- graphviz
- coverage
- mock
- palettable
Usage
Basic example:
from pycewise import *
import pandas
df = pandas.read_csv('test_data/memcpy_small.csv')
reg = compute_regression(df['size'], df['duration'], mode='log')
print(reg)
For more advanced usage, see the notebooks.
1 maintainer
Metadata
1 maintainer
Release files for pycewise 0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pycewise-0.1.4-py3-none-any.whl | Python 3 | none | any | Details for pycewise-0.1.4-py3-none-any.whl |
Release files / pycewise-0.1.4-py3-none-any.whl
| Download URL | pycewise-0.1.4-py3-none-any.whl |
|---|---|
| Size | 13.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6ba554e397e0c4283899f8632ddba9f6ceee2f79b6893467e376938a84bc88c8
|
|
BLAKE2b-256 checksum How to use checksums |
6c046249487560d3d85beafe26ee41c8865948c2f803534fc9e6e799b1ada5f2
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.3.0 pkginfo/1.7.0 requests/2.25.1 setuptools/53.0.0 requests-toolbelt/0.9.1 tqdm/4.58.0 CPython/3.9.2
|
Security for pycewise 0.1.4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
