Use the DM Mask for Existed Masks

[teweitsai]

Use the DM mask instead of numpy.ndarray(dtype=int) for existed masks. The followings are the example code by Robert:

import matplotlib.pyplot as plt

%matplotlib ipympl
plt.rcParams['figure.figsize'] = [7, 6]

import lsst.afw.image as afwImage
import lsst.afw.display as afwDisplay

afwDisplay.setDefaultBackend("matplotlib")

# Add a new mask plane called "AOS" to all Masks in this session
AOS = 1 << afwImage.Mask.addMaskPlane("AOS")
afwDisplay.setDefaultMaskPlaneColor("AOS", afwDisplay.CYAN)  # actually most color names are accepted

# create a MaskedImage with an image, a mask, and a variance plane
mi = afwImage.MaskedImageF(11, 21)
#
# Set some pixels in the image and mask.   I could do this "natively", but in the case
# I'm using the numpy interface (the .array)
mi.image.array[5:15, 5:6] = 10
mi.mask.array[10, 5] |= AOS
mi.mask.array[0:3, :] |= afwImage.Mask.getPlaneBitMask("BAD")
mi.mask.array[1, 1] |= afwImage.Mask.getPlaneBitMask("DETECTED")
#
# Make use of that mask;  I could have used np.where instead
#
mi.image.array[(mi.mask.array & AOS) != 0] = 20
#
# And display the result.
#
if False:
    fig = 1; plt.close(fig); fig = plt.figure(fig)
    disp = afwDisplay.Display(fig)
else:
    disp = afwDisplay.Display(1, reopenPlot=True)

disp.setImageColormap('gray')
disp.scale('linear', 'minmax')
disp.mtv(mi, title="Using a Mask")