pwtools.num.order_similar

pwtools.num.order_similar(arr, repeat=1, order=2)

Band ordering algorithm. Uses up to quadradic extrapolation. Handles crossing points.

This can be used to order dispersion plots, for instance.

Parameters:

• arr (2d array (npoints, ndim)) – ndim 1d data streams with npoints each.

• repeat (int) – 1: run 1 time, N: run recursively N times

• order (int) – Order of extrapolation: 0 = next similar point, 1 = linear using the two last points, 2 = quadratic using the 3 last points

Returns:

arr2 – Array with ordered data series.

Return type:

like arr

Notes

The more points, the better. The first 1-2 steps should start smoothly or the algo will get confused. If you don’t get all crossing points resolved, try repeat > 1. But if the algo placed points from different data streams into one, you are lost. Then you can only use more points to make the extrapolation more precise.

Examples

>>> import numpy as np
>>> from pwtools import mpl, num
>>> plt = mpl.plt
>>> x = np.linspace(0,10,200)
>>> a = np.array([np.sin(0.5*x),
...               1.2*np.cos(2*x),
...               np.sin(2.5*(x-1.5)),
...               0.2*np.sin(x-1.1),
...               0.3*np.sin(x-1.1),
...               ]).T
>>> for ai in a:
...     np.random.shuffle(ai)
>>> plt.figure(); plt.plot(a); plt.title('raw data')
>>> aa = num.order_similar(a, repeat=1, order=2)
>>> plt.figure(); plt.plot(aa); plt.title('sorted, repeat=1, order=2')
>>> aa = num.order_similar(a, repeat=2, order=1)
>>> plt.figure(); plt.plot(aa); plt.title('sorted, repeat=2, order=1')
>>> plt.show()