Bye, Bye, Bye (SciPy)

[mjonuschat]

Replace SciPy functionality with NumPy equivalents to escape dependency hell.

libatlas is a dependency for installing precompiled SciPy packages for python, but the latest Raspbian/Debian 13 no longer have that package. Instead of requiring the heavy SciPy dependency replace the functionality with direct NumPy calls / a little bit of wrapper code.

• refactor: Replace SciPy pearsonr correlation coefficent with NumPy functionality
• refactor: Use numpy for linear regression calculations
• refactor: Replace scipy.spectrogram with numpy fft
• refactor: Bump numpy version, remove scipy dependency
• refactor: Stop installing scipy sytem dependencies
• docs: Remove scipy from list of dependencies

Summary by Sourcery

Remove SciPy dependency by reimplementing correlation, regression, and spectrogram functionality with pure NumPy, update dependency versions and installation scripts, and clean up documentation accordingly

Enhancements:

• Replace Pearson correlation using SciPy with NumPy's corrcoef
• Replace linear regression using SciPy stats with NumPy polynomial fitting
• Implement FFT-based spectrogram using NumPy in a new helper module instead of SciPy signal
• Remove installation of SciPy and related system libraries (libatlas, libopenblas)

Build:

• Bump NumPy version constraints and drop SciPy from requirements.txt

Documentation:

• Remove SciPy from the list of dependencies in documentation

[sourcery-ai[bot]]

Reviewer's Guide

This PR removes the SciPy dependency by migrating spectral, regression, and correlation routines to NumPy-based implementations and streamlines dependency management by updating requirements, install scripts, and documentation.

Class diagram for updated spectrogram computation (NumPy-based)

classDiagram
    class SpectrogramHelper {
        +compute_spectrogram(data)
        +spectrogram(x, fs, window, nperseg, noverlap)
        +_fft_helper(x, window, nperseg, noverlap, nfft, sides)
        +_detrend_constant(data)
    }
    SpectrogramHelper <|-- compute_spectrogram
    SpectrogramHelper <|-- spectrogram
    SpectrogramHelper <|-- _fft_helper
    SpectrogramHelper <|-- _detrend_constant

Class diagram for updated linear regression direction calculation

classDiagram
    class AxesMapComputation {
        +_linear_regression_direction(position_x, position_y, position_z)
    }
    class Polynomial {
        +fit(time, position, 1)
        +convert()
    }
    AxesMapComputation --> Polynomial: uses

Class diagram for updated correlation calculation in BeltsComputation

classDiagram
    class BeltsComputation {
        +compute()
    }
    BeltsComputation --> numpy: uses corrcoef

File-Level Changes

Change	Details	Files
Migrate spectrogram generation from SciPy to a custom NumPy FFT–based implementation	Remove SciPy import and compute_spectrogram in common_func Introduce new helper module with _fft_helper, spectrogram, and compute_spectrogram functions using NumPy	shaketune/helpers/common_func.py shaketune/helpers/spectrogram.py
Replace SciPy linear regression with NumPy Polynomial.fit	Swap stats.linregress calls for Polynomial.fit.convert Update intercept and slope assignments from the fit result	shaketune/graph_creators/computations/axes_map_computation.py
Swap SciPy’s pearsonr with NumPy’s corrcoef for correlation computation	Replace pearsonr call with np.corrcoef Adjust similarity_factor calculation to use the corrcoef output	shaketune/graph_creators/computations/belts_computation.py
Remove SciPy from dependencies and clean up installation steps	Delete SciPy entries and add conditional NumPy version constraints in requirements.txt Remove system package installation logic in install.sh and update docs to exclude SciPy	requirements.txt install.sh docs/cli_usage.md

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[EricZimmerman]

@Frix-x when will this be accepted?

[schutztj]

Happy to test this on my machine if we think it's ready

[Frix-x]

Thank you so much @mjonuschat for this contribution! 🙏

As we discussed on Discord, I've created a hybrid solution merging your more generic approach with some low-RAM optimizations targeting Raspberry Pi (using a pre-allocated buffer approach instead of stride tricks for the spectrogram).

Your changes are now merged into the develop branch. Thanks again for the collaboration!