fdasrsf

library2.6.9pypypi✓ verified 89d ago

A Python library for functional data analysis (FDA) using the Square Root Slope Framework (SRSF). It provides elastic registration, alignment, principal component analysis, and classification of functional data. Current version 2.6.9, with regular releases.

data ai-ml

pip install fdasrsf

github ↗package ↗homepage ↗docs ↗

INSTALL

IMPORT

SIG · FDASRSF

fdasrsf

datapythonv2.6.9

harness data pending

Install & Compatibility

Where this runs

No compatibility data collected yet for this library.

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

fdasrsf

✓ import fdasrsf

✗ from fdasrsf import ...

Most common pattern: use `import fdasrsf` then access functions via `fdasrsf.function_name`. Submodules like `fdasrsf.fdaclassification` are often imported explicitly.

fdasrsf.time_warping

✓ from fdasrsf import time_warping

For warping functions; no common mistake.

Basic example of aligning functional data using fdasrsf.

import fdasrsf import numpy as np # Generate example functional data: 10 time series of 100 points N, M = 10, 100 t = np.linspace(0, 1, M) f = np.random.randn(N, M) # Align functions using elastic registration # Note: The main alignment function is `elastic_regression`, but for alignment use `time_warping`. aligned = fdasrsf.time_warping.align_fPCA(f, t) print(aligned['fPCA'])

fdasrsf --version

Debug

Known issues

breakingIn version 2.x, the `fdasrsf` package moved from `fdasrsf` (no subpackage) to a structure with submodules. Old code using `from fdasrsf import align_fPCA` no longer works.

fix

Use `from fdasrsf.time_warping import align_fPCA` instead.

affects: >=2.0.0

deprecatedThe function `fdasrsf.fdaclassification.classification()` was deprecated in favor of `fdasrsf.classification.classify()`.

fix

Replace `fdasrsf.fdaclassification.classification` with `fdasrsf.classification.classify`

affects: >=2.4.0

gotchaThe input data is expected as a 2D array of shape (N, M) where N=number of functions, M=number of time points. Many users pass (M, N) and get bizarre results.

fix

Ensure your data matrix is (N, M), not (M, N). Transpose with `.T` if needed.

affects: all

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'fdasrsf'

The package is not installed or installed in a different Python environment.

fix

Run `pip install fdasrsf` in the correct environment (Python >=3.10).

AttributeError: module 'fdasrsf' has no attribute 'align_fPCA'

In version 2.x, submodules are not automatically imported. `fdasrsf` no longer has top-level functions.

fix

Use `from fdasrsf.time_warping import align_fPCA` or `import fdasrsf.time_warping` then `fdasrsf.time_warping.align_fPCA()`.

Upgrade

Version history

2.6.9latest on PyPI · released Mar 28, 2026

Audit

Dependencies

numpyrequiredcore array operations

scipyrequiredoptimization and interpolation

matplotliboptionalplotting

Agent activity

14 hits · last 30 days

node

Amazon

OpenAI (training)

Resources

githubhttps://github.com/jdtuck/fdasrsf_python ↗

packagehttps://pypi.org/project/fdasrsf/ ↗

homepagehttp://research.tetonedge.net ↗

docshttps://fdasrsf-python.readthedocs.io/en/latest/ ↗