def get_spectra(self):
import util
xpeaks = self.__find_peaks()
image_length = self.image_data.shape[1]
start_pixel = 1000
yvalues_at_start = xpeaks[start_pixel]
self.num_spectra = len(yvalues_at_start)
xthreshold = 5
ythreshold = 2
cur_num_spectra = 0
# Going from right to left
for num, y in enumerate(yvalues_at_start):
cur_y = y
s = Spectrum([], [], self)
cur_x = start_pixel
for next_spec_x in range(start_pixel + 1, image_length):
check_y = xpeaks[next_spec_x]
# Check for xpixels to see if there exists a y pixel that's less
# than some value away.
spec_indices = np.where(abs(cur_y - check_y) <= ythreshold)[0]
if len(spec_indices) > 0:
next_ind = spec_indices[0]
nexty = check_y[next_ind]
s.add_peak(next_spec_x, nexty)
cur_x = next_spec_x
cur_y = nexty
if abs(next_spec_x - cur_x) >= xthreshold:
break
cur_x = start_pixel
cur_y = y
for prev_spec_x in range(start_pixel - 1, 0, -1):
check_y = xpeaks[prev_spec_x]
spec_indices = np.where(abs(cur_y - check_y) <= ythreshold)[0]
if len(spec_indices) > 0:
prev_ind = spec_indices[0]
prevy = check_y[prev_ind]
s.add_peak(prev_spec_x, prevy)
cur_x = prev_spec_x
cur_y = prevy
if abs(prev_spec_x - cur_x) >= xthreshold:
break
build_prep_success = s.build_prepare()
if build_prep_success:
cur_num_spectra += 1
self.spectra.append(s)
print("Spectrum %d/%d ready for building..." %
(cur_num_spectra, self.num_spectra))
else:
self.num_spectra -= 1
self.__fit_overlap_boundary_parabola()
self.__update_spectral_boundaries()
built_spectra = []
cur_num_spectra = 0
for spectrum in self.spectra:
build_success = spectrum.build()
if build_success:
cur_num_spectra += 1
built_spectra.append(spectrum)
print("Building spectrum %d/%d" %
(cur_num_spectra, self.num_spectra))
print("Min x:", spectrum.xvalues[0], "\nMax x:",
spectrum.xvalues[-1])
else:
self.num_spectra -= 1
self.spectra = built_spectra
