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Implemented stacked_sensitivity for adaptive number of wavelengths #116

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Implemented stacked_sensitivity for adaptive number of wavelengths #116

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33 changes: 19 additions & 14 deletions src/cedalion/imagereco/forward_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1094,9 +1094,9 @@ def compute_sensitivity(


# FIXME: better name for Adot * ext. coeffs
# FIXME: hardcoded for 2 chromophores (HbO and HbR) and wavelengths
# FIXME: hardcoded for 2 chromophores (HbO and HbR)
@staticmethod
def compute_stacked_sensitivity(sensitivity: xr.DataArray):
def compute_stacked_sensitivity(sensitivity: xr.DataArray, spectrum: str = "prahl"):
"""Compute stacked HbO and HbR sensitivity matrices from fluence.

Args:
Expand All @@ -1109,14 +1109,13 @@ def compute_stacked_sensitivity(sensitivity: xr.DataArray):

assert "wavelength" in sensitivity.dims
wavelengths = sensitivity.wavelength.values
assert len(wavelengths) == 2

if "units" in sensitivity.attrs:
units_sens = pint.Unit(sensitivity.attrs["units"])
else:
units_sens = pint.Unit("mm")

ec = cedalion.nirs.get_extinction_coefficients("prahl", wavelengths)
ec = cedalion.nirs.get_extinction_coefficients(spectrum, wavelengths)

units_ec = ec.pint.units
ec = ec.pint.dequantify()
Expand All @@ -1125,25 +1124,31 @@ def compute_stacked_sensitivity(sensitivity: xr.DataArray):

nchannel = sensitivity.sizes["channel"]
nvertices = sensitivity.sizes["vertex"]
A = np.zeros((2 * nchannel, 2 * nvertices))
nwavelengths = len(wavelengths)
A = np.zeros((nwavelengths * nchannel, 2 * nvertices))

wl1, wl2 = wavelengths
# fmt: off
A[:nchannel, :nvertices] = ec.sel(chromo="HbO", wavelength=wl1).values * sensitivity.sel(wavelength=wl1) # noqa: E501
A[:nchannel, nvertices:] = ec.sel(chromo="HbR", wavelength=wl1).values * sensitivity.sel(wavelength=wl1) # noqa: E501
A[nchannel:, :nvertices] = ec.sel(chromo="HbO", wavelength=wl2).values * sensitivity.sel(wavelength=wl2) # noqa: E501
A[nchannel:, nvertices:] = ec.sel(chromo="HbR", wavelength=wl2).values * sensitivity.sel(wavelength=wl2) # noqa: E501
for i, wl in enumerate(wavelengths):
for i, wl in enumerate(wavelengths):
A[i * nchannel : (i + 1) * nchannel, :nvertices] = (
ec.sel(chromo="HbO", wavelength=wl).values
* sensitivity.sel(wavelength=wl)
)
A[i * nchannel : (i + 1) * nchannel, nvertices:] = (
ec.sel(chromo="HbR", wavelength=wl).values
* sensitivity.sel(wavelength=wl)
)
# fmt: on

is_brain = np.hstack([sensitivity.is_brain, sensitivity.is_brain])
flat_chromo = ["HbO"] * nvertices + ["HbR"] * nvertices
flat_wavelength = [wl1] * nchannel + [wl2] * nchannel
flat_wavelength = [wl for wl in wavelengths for _ in range(nchannel)]
channel = sensitivity.channel.values
source = sensitivity.source.values
detector = sensitivity.detector.values
flat_channel = np.hstack((channel, channel))
flat_source = np.hstack((source, source))
flat_detector = np.hstack((detector, detector))
flat_channel = np.hstack([channel] * nwavelengths)
flat_source = np.hstack([source] * nwavelengths)
flat_detector = np.hstack([detector] * nwavelengths)
vertex = np.hstack([np.arange(nvertices), np.arange(nvertices)])

coords = {
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