def _choose_peak_ids(peaks, n_peaks_to_index):
"""Choose `n_peaks_to_index` indices from `peaks`.
This implementation sorts by angle and then picks every
len(peaks)/n_peaks_to_index element to get an even distribution of angles.
Parameters
----------
peaks : array_like
Array of peak positions.
n_peaks_to_index : int
Number of indices to return.
Returns
-------
peak_ids : numpy.array
Array of indices of the chosen peaks.
"""
r, angles = _cart2polar(peaks[:, 0], peaks[:, 1])
return angles.argsort()[
np.linspace(0, angles.shape[0] - 1, n_peaks_to_index, dtype=np.int)
]
def test_cart2polar(x, y, r, theta):
rc, thetac = _cart2polar(x=x, y=y)
np.testing.assert_almost_equal(rc, r)
np.testing.assert_almost_equal(thetac, theta)
