timeseries.curve_geometry

This Cython module contains the core algorithms for the geometry of curves.

If a function requires its own explicit iterator in a loop, probably it should go here. Anything that is just a vectorized operation in NumPy or Pandas can go in plain python elsewhere.

See http://docs.cython.org/src/tutorial/np.html for ideas on writing efficient code in Cython.

This module is compiled by either of these commands

• python setup.py install (as called by pip for standard installation and use)
• python setup.py build_ext --inplace (as run by developers for code testing)

Notes

Automatically-generated online documentation will never see the C-only functions that are defined with cdef in Cython, as shown in http://cython.readthedocs.io/en/latest/src/reference/extension_types.html Because of the limitations of Sphinx, you’ll have to simply view the sourcecode for further information. For this module, these C-only functions include

• homology.dim0.root()
• homology.dim0.connected()
• homology.dim0.merge()

Copyright

• This file is part of https://github.com/geomdata/gda-public/
• 2015, 2016, 2017 by Geometric Data Analytics, Inc. (http://geomdata.com)
• AGPL license. See LICENSE or https://github.com/geomdata/gda-public/blob/master/LICENSE

Functions

cdist(XA, XB[, metric, p, V, VI, w])	Computes distance between each pair of the two collections of inputs.
cleanup(ndarray time, ndarray position, …)	Throw out bad points by speed comparison.
contour_crossings(x[, contour])	Take a one dimensional array and find the positions where the array crosses (or touches) a contour.
euclidean(u, v)	Computes the Euclidean distance between two 1-D arrays.
frenet_frame(velocity, acceleration)	Find the Frenet frame using QR-decomposition at each time step.
frenet_kappa_tau(ndarray velocity, …)	Compute KAPPA curvature and TAU torsion for a curve
mollifier(time, position[, refinement, width])	Smooth function in a way that retains shape by adding new graph values via the linear interpolate and smoothing via convolution with the Friedrichs’ mollifier.
mollifier_uneven(time, position[, …])	Smooth function in a way that retains shape by adding new graph values via the linear interpolate and smoothing via convolution with the Friedrichs’ mollifier.
secant_arclength(ndarray position)	Compute the cumulative arc-length sample-by-sample.
secant_derivative(ndarray time, …)	Compute the secant derivatives using points equally spaced BY INDEX.
secant_jump(ndarray position)	Compute the secant displacement sample-by-sample.
similarity_matrix(a, b[, func])	similarity_matrix computes the similarity matrix of two iterables given a specified metric, defaulting to a euclidean metric.
tangent_arclength(ndarray time, ndarray velocity)	Compute the cumulative arc-length by integrating speed.