procurve 0.0.2

Principal curve for spherical data using splines.

ProCurve

What is ProCurve?

It is a robust principal curve package focused on fitting data that lies in a sphere. Splines are the estimators used for the principal curves.

How to install

The package can be installed via pip using:

pip install procurve

Example:

Run the load base case as:

from src.procurve.principal_curve import PrincipalCurve
from src.procurve.utils import create_dataset
from src.procurve.plotting import plot_3d, segments
import numpy as np
from mpl_toolkits.mplot3d.art3d import Line3DCollection

X = create_dataset(source="snake")
spline_params = {"degree": 4,
                 "low_angle_deg": -40,
                 "high_angle_deg": 180,
                 "radius": 1.0}
pc = PrincipalCurve()
X, s, f_spline = pc.fit(X, init_fn="curve", param_fun=spline_params)
s_high_res = np.linspace(0, 1, 1000)
f_s = f_spline(s_high_res)

#%% Plot data
ax = plot_3d(X, plot_wireframe=True)
ax.plot(f_s[:,0], f_s[:,1],  f_s[:,2], color="C3", linewidth=0.5, label="Principal curve")
line_collections_fit = segments(pc.last_iteration_log["data_sorted"],
                                pc.last_iteration_log["p_orthogonal"])
lc_fit = Line3DCollection(line_collections_fit, colors="C1", linewidths=0.4, label="Orthogonal projection")
ax.add_collection(lc_fit)
ax.legend(fontsize="small")

Reading and citations:

The pseudo-algorithm and mathematical formulation can be found here.

How to contact us

Any questions, suggestions or collaborations contact Mauricio Salazar at <[e-mail]>