I have a set of RGB
Images and I made a RGB
fits image with aplpy
and I also overlaid some contours on the image but I would like to cut the image and make small fits images where I would see the peaks of contour.
import aplpy
import atpy
from pyavm import AVM
import asciitable
import matplotlib
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm,BoundaryNorm
import montage_wrapper
from astropy.io import fits
import pyfits
from astropy import wcs
fitsfile = 'rgb.fits'
fitsfile_2d = 'rgb_2d.fits'
pngfile = 'rgb_arcsinh_contour.png'
figfile = 'rgb.png'
w = wcs.WCS(naxis=2)
# Set up an "Airy's zenithal" projection
# Vector properties may be set with Python lists, or Numpy arrays
w.wcs.crpix = [5.70000000E+03, 3.05000000E+03]
w.wcs.cdelt = np.array([-6.611111263E-05, 6.611111263E-05])
w.wcs.crval = [23.166667, -7.666667]
w.wcs.ctype = ["RA---TAN", "DEC--TAN"]
w.wcs.cunit =["deg","deg"]
# Print out all of the contents of the WCS object
w.wcs.print_contents()
# Some pixel coordinates of interest.
pixcrd = np.array([[0,0],[24,38],[45,98]], np.float_)
# Convert pixel coordinates to world coordinates
world = w.wcs_pix2world(pixcrd, 1)
print world
# Convert the same coordinates back to pixel coordinates.
pixcrd2 = w.wcs_world2pix(world, 1)
print pixcrd2
# These should be the same as the original pixel coordinates, modulo
# some floating-point error.
assert np.max(np.abs(pixcrd - pixcrd2)) < 1e-6
# Now, write out the WCS object as a FITS header
header = w.to_header()
hdu = pyfits.open(fitsfile)
# header is an astropy.io.fits.Header object. We can use it to create a new
# PrimaryHDU and write it to a file.
hdu = fits.PrimaryHDU(header=header)
# make rgb image
aplpy.make_rgb_image(fitsfile, pngfile,
vmin_r=-0.005, vmax_r=0.2,
vmin_g=-0.02, vmax_g=0.1,
vmin_b=-0.02,vmax_b=0.04,
embed_avm_tags=False)
# make a figure
img = aplpy.FITSFigure(fitsfile_2d)
img.show_rgb(pngfile)
img.set_nan_color('white')
standard_setup(img)
How could I produce subplots from given coordinates of the image with a given size ?
According to the APLpy documentation, you can make subplots:
By default, FITSFigure creates a figure with a single subplot that occupies the entire figure. However, APLpy can be used to place a subplot in an existing matplotlib figure instance. To do this, FITSFigure should be called with the figure= argument as follows:
import aplpy import matplotlib.pyplot as mpl fig = mpl.figure() f = aplpy.FITSFigure('some_image.fits', figure=fig)
and recenter your figures:
The figure can be interactively explored by zooming and panning. To recenter on a specific region programmatically, use the following method, specifying either a radius:
fig.recenter(33.23, 55.33, radius=0.3) # degrees
or a separate width and height:
fig.recenter(33.23, 55.33, width=0.3, height=0.2) # degrees
I have tested it because I also use APLpy and it works nice for me.
HTH,
Germán.