csaps is a Python package for univariate, multivariate and n-dimensional grid data approximation using cubic smoothing splines. The package can be useful in practical engineering tasks for data approximation and smoothing.

Installing

Use pip for installing:

pip install -U csaps

or Poetry:

poetry add csaps

The module depends only on NumPy and SciPy. Python 3.10 or above is supported.

Simple Examples

Here is a couple of examples of smoothing data.

An univariate data smoothing:

import numpy as np
import matplotlib.pyplot as plt

from csaps import csaps

np.random.seed(1234)

x = np.linspace(-5., 5., 25)
y = np.exp(-(x/2.5)**2) + (np.random.rand(25) - 0.2) * 0.3
xs = np.linspace(x[0], x[-1], 150)

ys = csaps(x, y, xs, smooth=0.85)

plt.plot(x, y, 'o', xs, ys, '-')
plt.show()

A surface data smoothing:

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

from csaps import csaps

np.random.seed(1234)
xdata = [np.linspace(-3, 3, 41), np.linspace(-3.5, 3.5, 31)]
i, j = np.meshgrid(*xdata, indexing='ij')
ydata = (3 * (1 - j)**2. * np.exp(-(j**2) - (i + 1)**2)
         - 10 * (j / 5 - j**3 - i**5) * np.exp(-j**2 - i**2)
         - 1 / 3 * np.exp(-(j + 1)**2 - i**2))
ydata = ydata + (np.random.randn(*ydata.shape) * 0.75)

ydata_s = csaps(xdata, ydata, xdata, smooth=0.988)

fig = plt.figure(figsize=(7, 4.5))
ax = fig.add_subplot(111, projection='3d')
ax.set_facecolor('none')
c = [s['color'] for s in plt.rcParams['axes.prop_cycle']]
ax.plot_wireframe(j, i, ydata, linewidths=0.5, color=c[0], alpha=0.5)
ax.scatter(j, i, ydata, s=10, c=c[0], alpha=0.5)
ax.plot_surface(j, i, ydata_s, color=c[1], linewidth=0, alpha=1.0)
ax.view_init(elev=9., azim=290)

plt.show()

Documentation

More examples of usage and the full documentation can be found at https://csaps.readthedocs.io.

Development

We use Poetry to manage the project:

git clone https://github.com/espdev/csaps.git
cd csaps
poetry install -E docs

Also, install pre-commit hooks:

poetry run pre-commit install

Testing and Linting

We use pytest for testing and ruff/mypy for linting. Use poethepoet to run tests and linters:

poetry run poe test
poetry run poe check

Algorithm and Implementation

csaps Python package is inspired by MATLAB CSAPS function that is an implementation of Fortran routine SMOOTH from PGS (originally written by Carl de Boor).

Also, the algothithm implementation in other languages:

csaps-rs Rust ndarray/sprs based implementation
csaps-cpp C++11 Eigen based implementation (incomplete)

References

C. de Boor, A Practical Guide to Splines, Springer-Verlag, 1978.

License

MIT

Csaps

Install / Use

README