sacfpy
sacfpy is a small scientific Python package for reproducing two diagnostics
associated with the sample autocorrelation identity discussed by Hassani (2009):
- The sum of the sample autocorrelations over all positive lags.
- The raw periodogram / sample spectral density at frequency zero.
The implementation uses the same fixed-divisor sample autocovariance convention described in the paper.
Installation for development
python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
pip install -e ".[test]"
On Windows PowerShell, activate the environment with:
.venv\Scripts\Activate.ps1
Example
from sacfpy import analyze
x = [1, 2, 3, 5, 4, 7]
result = analyze(x)
print(result)
Typical output contains:
acf_sum: approximately -0.5
periodogram_zero: approximately 0.0
Main functions
sample_acf(x, max_lag=None)sample_acf_sum(x)periodogram_zero(x)analyze(x)
Run tests
pytest
Build the package
python -m pip install build
python -m build
The wheel and source distribution will be created in dist/.
Reference
Hassani, H. (2009). Sum of the sample autocorrelation function. Random Operators / Stochastic Equations, 17, 125–130.
Metadata
Release files for Hassani.SACF 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hassani_sacf-0.1.0.tar.gz | 3.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hassani_sacf-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.4 kB
Release files / hassani_sacf-0.1.0.tar.gz
| Download URL | hassani_sacf-0.1.0.tar.gz |
|---|---|
| Size | 3.0 kB |
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Release files / hassani_sacf-0.1.0-py3-none-any.whl
| Download URL | hassani_sacf-0.1.0-py3-none-any.whl |
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| Size | 3.4 kB |
| Tags | Python 3 |
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