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Speed up centroid function (remove interpolation) #179

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37 changes: 5 additions & 32 deletions lumispy/utils/signals.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,5 @@
import numpy as np
from hyperspy.axes import FunctionalDataAxis
from scipy.ndimage import center_of_mass
from scipy.interpolate import interp1d


def com(spectrum_intensities, signal_axis, **kwargs):
Expand All @@ -15,8 +13,6 @@ def com(spectrum_intensities, signal_axis, **kwargs):
signal_axis: hyperspy.axes.BaseDataAxis subclass
A HyperSpy signal axis class containing an array with the wavelength/
energy for each intensity/signal value.
kwargs : dictionary
For the scipy.interpolate.interp1d function.

Returns
-------
Expand All @@ -35,37 +31,13 @@ def com(spectrum_intensities, signal_axis, **kwargs):
>>> print(center_of_mass) # Outputs: [400.0]
"""

def _interpolate_signal(axis_array, index, **kwargs):
"""
Wrapper for `hs.axes.index2value` that linearly interpolates between
values should the index passed not be a integer. Using the kwargs, the
interpolation method can be changed.
"""
rem = index % 1
index = int(index // 1)
if rem == 0:
return axis_array[int(index)]
else:
y = [axis_array[index], axis_array[index + 1]]
x = [0, 1]
fx = interp1d(x, y, **kwargs)
return float(fx(rem))

# Find center of mass wrt array index
index_com = float(center_of_mass(spectrum_intensities)[0])

# Check for the type of hyperspy.axis
if type(signal_axis) == FunctionalDataAxis:
# Calculate value y from x[index_com]
x = _interpolate_signal(signal_axis.x.axis, index_com)
kwargs = {}
for kwarg in signal_axis.parameters_list:
kwargs[kwarg] = getattr(signal_axis, kwarg)
com_val = signal_axis._function(x, **kwargs)
xs = signal_axis.axis

elif hasattr(signal_axis, "axis"):
# Calculate value interpolating between index_com 0 and 1
com_val = _interpolate_signal(signal_axis.axis, index_com)
xs = signal_axis.axis

elif type(signal_axis) in (list, np.ndarray, tuple):
# Check for dimensionality
if len(spectrum_intensities) != len(signal_axis):
Expand All @@ -74,8 +46,9 @@ def _interpolate_signal(axis_array, index, **kwargs):
"the length of the wavelength array {len(signal_axis)}."
)
# Calculate value interpolating between index_com 0 and 1
com_val = _interpolate_signal(np.array(signal_axis), index_com)
xs = np.array(signal_axis)
else:
raise ValueError("The parmeter `signal_axis` must be a HyperSpy Axis object.")

com_val = np.sum(xs * spectrum_intensities) / np.sum(spectrum_intensities)
return com_val