The examples below show how to use the radiopadre machinery. The initialization block below (between "####") is mandatory.
You must select "Cell|Run All" from the above menu to re-run the notebook , and wait for it to finish running.
This particular notebook is built for the example results directory that can be downloaded from Dropbox, use this link to download example-reduction-dir from Dropbox: https://www.dropbox.com/sh/hde4azjdscsw20c/AAB2M0w3Ttm4ioPI0bccOPE-a?dl=0
Then do "cd example-reduction-dir; run-radiopadre.sh" inside your copy of the results directory to start the notebook server and point your browser to the port indicated by the script.
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### MANDATORY INIT ###
%matplotlib inline
from radiopadre import DirList
dirs = DirList()
######################
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# dirs is a directory list object
# By default displays all directories under your results directory
# dirs.show() will have the same effect
dirs
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dirs[0].files
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dirs[0].fits.summary() # gives list of FITS files in directory #0 above
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# displays thumbnails for all FITS files in directory #0
dirs[0].fits.thumbs()
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dirs[0].fits.thumbs(zoom=2,vmin=0,vmax=1)
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# gives list of FITS files matching the pattern
dirs[0].fits("*s7*")
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dirs[0].fits("*s7*").show()
dirs[0].fits("*s7*").thumbs()
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# list of images (PNG, JPG, etc.) in directory #3
dirs[3].images.show(ncol=2)
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# clickable thumbnails of same
dirs[3].images.thumbs(ncol=6)
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# first FITS file in directory #0. Stokes axis is unrolled by default, but this can be controlled by
# invoking dirs[0].fits[0].show() with some extra arguments
dirs[0].fits[0].show(vmin=-5e-5,vmax=5e-5)
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# and this shows how to invoke show() with some explicit arguments to control the rendering
dirs[0].fits[0].show(unroll=None,vmin=-5e-5,vmax=5e-5,zoom=4)
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# just some info about the given file
dirs[0].fits[0].info()
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# A more elaborate rendering of the same file using aplpy. Note that .fullpath gives you the path to the file.
# aplpy is quite slow so we don't use it by default for all files, but this example shows you how to do
# a proper rendering
import aplpy
fig = aplpy.FITSFigure(dirs[0].fits[0].fullpath,slices=[0,0])
fig.show_colorscale(cmap='gist_heat',vmin=-5e-5,vmax=5e-5)
fig.add_colorbar()