# By default loadFilter() will also turn on the application of the filter. You can set
# switchOnFilter to False when calling loadFilter to not activate the filter immediately,
# and also toggle the filters on and off with switchOffFilter() and switchOnFilter().
obs.switchOffFilter()
# With the filter off let's get the full spectrum of the selected pixel.
specDict = obs.getPixelSpectrum(row, col, firstSec=0, integrationTime= -1, weighted=True, fluxWeighted=True)
specWvlBinEdges = specDict['wvlBinEdges']
fullSpectrum = specDict['spectrum']
# Now let's switch the filter back on and overplot the filtered spectrum with the full
# spectrum.
obs.switchOnFilter()
filteredSpecDict = obs.getPixelSpectrum(row, col, firstSec=0, integrationTime= -1, weighted=True, fluxWeighted=True)
filteredSpecWvlBinEdges = filteredSpecDict['wvlBinEdges']
filteredSpectrum = filteredSpecDict['spectrum']
plt.step(specWvlBinEdges[:-1], fullSpectrum, where = 'post', label = 'Full ARCONS spectrum of single pixel')
plt.step(filteredSpecWvlBinEdges[:-1], filteredSpectrum, where = 'post', label = 'Filtered spectrum')
plt.xlabel('Angstroms')
plt.ylabel('Total counts (not counts/s/Angstrom)')
plt.ylim(0,1200000)
plt.legend()
plt.show()
# Synthetic filters also apply seamlessly to images. Let's create an image cube that's
# had a synthetic filter applied and step through the bins to show the filters are
# cutting the cube to appropriate levels.
