def compose(
rfile,
gfile,
bfile,
source_r,
source_g,
source_b,
scales=(1.0, 1.0, 1.0),
Q=1.0,
alpha=1.0,
masklevel=None,
saturation="color",
offset=0.0,
backsub=False,
vb=False,
outfile="color.png",
):
"""
Compose RGB color image.
"""
# -------------------------------------------------------------------
if vb:
print(
"HumVI: Making color composite image of data in following files:",
rfile,
gfile,
bfile,
)
print("HumVI: Output will be written to", outfile)
if masklevel is not None:
print("HumVI: Masking stretched pixel values less than", masklevel)
# Read in images, calibrated into flux units:
band3 = humvi.channel(rfile, source_r)
band2 = humvi.channel(gfile, source_g)
band1 = humvi.channel(bfile, source_b)
# Check shapes are equal:
humvi.check_image_shapes(band1.image, band2.image, band3.image)
# Subtract backgrounds (median, optional):
if backsub:
band1.subtract_background()
band2.subtract_background()
band3.subtract_background()
# -------------------------------------------------------------------
# BUG: as it stands, this code assumes one file one channel, whereas
# in practice we might like to be able to make composites based on
# N bands. Need to overload + operator for channels? Calib etc will
# need altering as well as image.
red = band3
green = band2
blue = band1
# -------------------------------------------------------------------
# Set scales determining color balance in composite:
rscale, gscale, bscale = humvi.normalize_scales(scales)
red.set_scale(manually=rscale)
green.set_scale(manually=gscale)
blue.set_scale(manually=bscale)
if vb:
print("HumVI: Scales normalized to:", red.scale, green.scale, blue.scale)
# Scale images - only do once:
red.apply_scale()
green.apply_scale()
blue.apply_scale()
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Stretch images to cope with high dynamic range:
if vb:
print("HumVI: Stretch parameters Q,alpha:", Q, alpha)
print(
"HumVI: At low surface brightness levels, the channel images are further rescaled by alpha"
)
print(
"HumVI: Nonlinearity sets in at about 1/Q*alpha in the scaled intensity image:",
1.0 / (Q * alpha),
)
# Compute total intensity image and the arcsinh of it:
I = humvi.lupton_intensity(red.image, green.image, blue.image, type="sum")
stretch = humvi.lupton_stretch(I, Q, alpha)
# Apply stretch to channel images:
r = stretch * red.image
g = stretch * green.image
b = stretch * blue.image
if masklevel is not None:
# Mask problem areas - exact zeros or very negative patches should
# be set to zero.
# BUG: this should have been done after scaling but before conversion
# to channels, as its the individual images that have problems...
r, g, b = humvi.pjm_mask(r, g, b, masklevel)
# Offset the stretched images to make zero level appear dark gray.
# Negative offset makes background more black...
r, g, b = humvi.pjm_offset(r, g, b, offset)
if saturation == "color":
# Saturate to colour at some level - might as well be 1, since
# Q redefines scale?:
threshold = 1.0
r, g, b = humvi.lupton_saturate(r, g, b, threshold)
# Otherwise, saturate to white.
# Package into a python Image, and write out to file:
image = humvi.pack_up(r, g, b)
# image.save(outfile)
if vb:
print("HumVI: Image saved to:", outfile)
return image
print compose.__doc__
return
# Parse nonlinearity parameters:
Qs,alphas = pars.split(',')
Q = float(Qs)
alpha = float(alphas)
# Parse channel colour scales:
x,y,z = scales.split(',')
rscale,gscale,bscale = float(x),float(y),float(z)
# -------------------------------------------------------------------
# Read in images, calibrated into flux units:
band3 = humvi.channel(rfile)
band2 = humvi.channel(gfile)
band1 = humvi.channel(bfile)
# Check shapes are equal:
humvi.check_image_shapes(band1.image,band2.image,band3.image)
# Subtract backgrounds (median, optional):
if backsub:
band1.subtract_background()
band2.subtract_background()
band3.subtract_background()
# -------------------------------------------------------------------
# BUG: as it stands, this code assumes one file one channel, whereas
def compose(rfile, gfile, bfile, scales=(1.0,1.0,1.0), Q=1.0, alpha=1.0, \
masklevel=None, saturation='color', offset=0.0, backsub=False, \
vb=False, outfile='color.png'):
"""
Compose RGB color image.
"""
# -------------------------------------------------------------------
if vb:
print "HumVI: Making color composite image of data in following files:",rfile,gfile,bfile
print "HumVI: Output will be written to",outfile
if masklevel is not None: print "HumVI: Masking stretched pixel values less than",masklevel
# Read in images, calibrated into flux units:
band3 = humvi.channel(rfile)
band2 = humvi.channel(gfile)
band1 = humvi.channel(bfile)
# Check shapes are equal:
humvi.check_image_shapes(band1.image,band2.image,band3.image)
# Subtract backgrounds (median, optional):
if backsub:
band1.subtract_background()
band2.subtract_background()
band3.subtract_background()
# -------------------------------------------------------------------
# BUG: as it stands, this code assumes one file one channel, whereas
# in practice we might like to be able to make composites based on
# N bands. Need to overload + operator for channels? Calib etc will
# need altering as well as image.
red = band3
green = band2
blue = band1
# -------------------------------------------------------------------
# Set scales determining color balance in composite:
rscale,gscale,bscale = humvi.normalize_scales(scales)
red.set_scale(manually=rscale)
green.set_scale(manually=gscale)
blue.set_scale(manually=bscale)
if vb: print 'HumVI: Scales normalized to:',red.scale,green.scale,blue.scale
# Scale images - only do once:
red.apply_scale()
green.apply_scale()
blue.apply_scale()
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# Stretch images to cope with high dynamic range:
if vb:
print "HumVI: Stretch parameters Q,alpha:",Q,alpha
print "HumVI: At low surface brightness levels, the channel images are further rescaled by alpha"
print "HumVI: Nonlinearity sets in at about 1/Q*alpha in the scaled intensity image:",1.0/(Q*alpha)
# Compute total intensity image and the arcsinh of it:
I = humvi.lupton_intensity(red.image,green.image,blue.image,type='sum')
stretch = humvi.lupton_stretch(I,Q,alpha)
# Apply stretch to channel images:
r = stretch * red.image
g = stretch * green.image
b = stretch * blue.image
if masklevel is not None:
# Mask problem areas - exact zeros or very negative patches should
# be set to zero.
# BUG: this should have been done after scaling but before conversion
# to channels, as its the individual images that have problems...
r,g,b = humvi.pjm_mask(r,g,b,masklevel)
# Offset the stretched images to make zero level appear dark gray.
# Negative offset makes background more black...
r,g,b = humvi.pjm_offset(r,g,b,offset)
if saturation == 'color':
# Saturate to colour at some level - might as well be 1, since
# Q redefines scale?:
threshold = 1.0
r,g,b = humvi.lupton_saturate(r,g,b,threshold)
# Otherwise, saturate to white.
# Package into a python Image, and write out to file:
image = humvi.pack_up(r,g,b)
image.save(outfile)
if vb: print "HumVI: Image saved to:",outfile
return
print compose.__doc__
return
# Parse nonlinearity parameters:
Qs,alphas = pars.split(',')
Q = float(Qs)
alpha = float(alphas)
# Parse channel colour scales:
x,y,z = scales.split(',')
rscale,gscale,bscale = float(x),float(y),float(z)
# -------------------------------------------------------------------
# Read in images, calibrated into flux units:
band3 = humvi.channel(rfile)
band2 = humvi.channel(gfile)
band1 = humvi.channel(bfile)
# Check shapes are equal:
humvi.check_image_shapes(band1.image,band2.image,band3.image)
# Subtract backgrounds (median, optional):
if backsub:
band1.subtract_background()
band2.subtract_background()
band3.subtract_background()
# -------------------------------------------------------------------
# BUG: as it stands, this code assumes one file one channel, whereas
else:
print compose.__doc__
return
## Parse nonlinearity parameters:
Qs,alphas = pars.split(',')
Q = float(Qs)
alpha = float(alphas)
## -------------------------------------------------------------------
## Read in images, set and apply scales etc:
# BUG: this code assumes one file one channel, whereas we would like
# to be able to make composites based on N bands.
red = humvi.channel(rfile)
green = humvi.channel(gfile)
blue = humvi.channel(bfile)
## Check shapes are equal:
humvi.check_image_shapes(red.image,green.image,blue.image)
# Subtract backgrounds (median, optional):
if backsub:
red.subtract_background()
green.subtract_background()
blue.subtract_background()
# Set scales:
# BUG: each image should be given a scale - need to work with
# image stacks, not red, green, blue. rgb can come after conversion to