sdcpy 0.5.2

Scale Dependent Correlation in Python

sdcpy

Scale Dependent Correlation (SDC) analysis^{1, 2, 3} in Python.

• Free software: MIT license
• Documentation: https://sdcpy.readthedocs.io.

Installation

Install from PyPI:

pip install sdcpy

Or using uv:

uv pip install sdcpy

Usage

import numpy as np
import pandas as pd
from sdcpy import SDCAnalysis

# Synthetic signal with transient pattern between indices 63-169
def tc_signal(i):
    error = np.random.normal()
    if 63 <= i <= 169:
        return np.sin(2 * np.pi * (1 / 37) * i) + 0.6 * error
    return error

np.random.seed(42)
ts1 = pd.Series([tc_signal(i) for i in range(250)])
ts2 = pd.Series([tc_signal(i) for i in range(250)])

# Run SDC analysis
sdc = SDCAnalysis(ts1, ts2, fragment_size=50, n_permutations=99)

# Generate 2-way SDC combi plot
fig = sdc.combi_plot(xlabel="TS1", ylabel="TS2")
fig.savefig("sdc_plot.png", dpi=150, bbox_inches="tight")

See examples/basic_usage.py for a complete example with synthetic data showing transient correlations.

Development

To set up a local development environment:

# Install uv (if not already installed)
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and install
git clone https://github.com/AlFontal/sdcpy.git
cd sdcpy
uv sync --all-groups

# Run tests
uv run pytest

See CONTRIBUTING.md for more details.

References

1. Rodó, X. (2001). Reversal of three global atmospheric fields linking changes in SST anomalies in the Pacific, Atlantic and Indian oceans at tropical latitudes and midlatitudes. Climate Dynamics, 18:203-217. DOI: 10.1007/s003820100171.

2. Rodríguez, M.A. & Rodó, X. (2004). A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis. Oecologia, 138,485-504. DOI: 10.1007/s00442-003-1464-4.

3. Rodó, X. & M.A. Rodriguez-Arias. (2006). A new method to detect transitory signatures and local time/space variability structures in the climate system: the scale-dependent correlation analysis. Climate Dynamics, 27:441-458. DOI: 10.1007/s00382-005-0106-4.