splinecloud-scipy

A Python client for SplineCloud API

The client library is based on SciPy and allows to load data and curves from SplineCloud into your code. Once loaded spline curves can be easily evaluated.

Installation

pip install splinecloud-scipy

Example of loading spline curve

from splinecloud_scipy import load_spline

curve_id = 'spl_K5t56P5bormJ' # take curve ID from the 'API link' dropdown at SplineCloud
spline = load_spline(curve_id)

Evaluating spline curve for a range of x values

import numpy as np
import matplotlib.pyplot as plt

X = np.linspace(0, 20, 100)
Y = [spline.eval(x) for x in X]

plt.plot(X,Y)
plt.grid()
plt.show()

Load data fitted by spline and evaluate fit accuracy

columns, table = spline.load_data()
x_data, y_data = table.T

plt.plot(X,Y)
plt.plot(x_data, y_data, 'o', color="grey")
plt.grid()
plt.xlabel(columns[0])
plt.ylabel(columns[1])
plt.show()

RMSE = spline.fit_accuracy(table, method="RMSE")
print(RMSE)

0.011307453345329156

Example of loading data in your code

from splinecloud_scipy import load_subset
subset_id = 'sbt_nDO4XmmYqeGI' # subset id can be taken from the SplineCloud
columns, table = load_subset(subset_id)

>>> columns

['Throttle (%)',
 'Load Currency (A)',
 'Pull (g)',
 'Power (W)',
 'Efficiency (g/W)']

>>> table

array([[5.0000e-01, 6.7600e+00, 3.8500e+02, 1.0871e+02, 3.5420e+00],
       [6.0000e-01, 1.0200e+01, 4.9500e+02, 1.6249e+02, 3.0460e+00],
       [7.0000e-01, 1.3580e+01, 6.0600e+02, 2.1768e+02, 2.7840e+00],
       [8.0000e-01, 1.7390e+01, 6.8700e+02, 2.7140e+02, 2.5510e+00],
       [9.0000e-01, 2.1030e+01, 7.4700e+02, 3.2813e+02, 2.2770e+00],
       [1.0000e+00, 2.5060e+01, 8.0700e+02, 3.8555e+02, 2.0930e+00]])

These examples are available as notebooks in the project's 'examples' folder.

Important

This library supports BSpline geometry but does not support weighted BSplines (NURBS). If you adjust the weights of the curve control points use another client, that supports NURBS (a link will be provided here soon).