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import os
import matplotlib.pyplot as plt
import tqdm
from colour import SpectralShape, COLOURCHECKER_SDS, sd_to_XYZ
from otsu2018 import load_Otsu2018_spectra, Otsu2018Tree
if __name__ == '__main__':
print('Loading spectral data...')
sds = load_Otsu2018_spectra('CommonData/spectrum_m.csv', every_nth=100)
shape = SpectralShape(380, 730, 10)
print('Initializing the tree...')
tree = Otsu2018Tree(sds, shape)
print('Clustering...')
before = tree.total_reconstruction_error()
tree.optimise(progress_bar=tqdm.tqdm)
after = tree.total_reconstruction_error()
print('Error before: %g' % before)
print('Error after: %g' % after)
print('Saving the dataset...')
if not os.path.exists('datasets'):
os.makedirs('datasets')
data = tree.to_dataset()
data.to_file('datasets/otsu2018.npz')
data.to_Python_file('datasets/otsu2018.py')
print('Plotting...')
tree.visualise()
plt.figure()
examples = COLOURCHECKER_SDS['ColorChecker N Ohta'].items()
for i, (name, sd) in enumerate(examples):
plt.subplot(2, 3, 1 + i)
plt.title(name)
plt.plot(sd.wavelengths, sd.values, label='Original')
XYZ = sd_to_XYZ(sd) / 100
recovered_sd = tree.reconstruct(XYZ)
plt.plot(recovered_sd.wavelengths, recovered_sd.values,
label='Recovered')
plt.legend()
if i + 1 == 6:
break
plt.show()
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