Get the data value(s) and/or mask value in an image.
The data point(s) to be retrieved are those found in the specified
region, which may be:
1. A region file from the viewer (region parameter)
2. A region specified by a set of rectangular
pixel coordinates, the channel ranges and/or the Stokes.
For directed output, run as
myoutput = imval()
Keyword arguments:
imagename -- Name of input image
Default: none; Example: imagename='ngc5921_task.im'
region -- region file or name.
Use the viewer, then region manager to select regions of
the image to process. Similar to box, but graphical
Or the name of a region stored with the image,
use rg.namesintable()
to retrieve the list of names.
Default: none
Example: region='myimage.im.rgn'
region='region1'
box -- A box region on the directional plane
Only pixel values acceptable at this time.
Default: '' (referencepixel values for the Directional coord);
Example: box='10,10,50,50'
box = '10,10,30,30,35,35,50,50' (two boxes)
box = '-1,-1' (all points)
chans -- channel numbers
Range of channel numbers to include in statistics
All spectral windows are included
Default:''= all; Example: chans='3~20';
chans='-1' (all channels)
stokes -- Stokes parameters to analyze.
Default: none (all); Example: stokes='IQUV';
stokes='I,Q'
stokes='-1' (all stokes values)
Options: 'I','Q','U','V','RR','RL','LR','LL','XX','YX','XY','YY', ...
General procedure:
1. Specify inputs, then
2. myoutput = imval()
or specify inputs directly in calling sequence to task
myoutput = imsval(imagename='image.im', etc)
3. myoutput['KEYS'] will contain the result associated with any
of the keys given below
KEYS CURRENTLY AVAILABLE
blc - absolute PIXEL coordinate of the bottom left corner of
the bounding box surrounding the selected region
trc - the absolute PIXEL coordinate of the top right corner
of the bounding box surrOunding the selected region
axes - List the data stored in each axis of the data block.
unit - unit of the returned data values.
data - data value(s) found in the given region
mask - mask value(s) found in the given region
NOTE: The data returned is in the same order as it is internally
stored, typically RA, DEC, spectral, stokes. Also both the data
and mask values are returned as Python Numpy arrays, for more
information on how to manipulate them see
http://numpy.scipy.org/#array_interface
Additional Examples
# The value and mask value at a single point (5,17,2,Q)
imval( 'myImage', box='5,5,17,17', chans=2, stokes='Q' )
# Select and report on two box regions
# box 1, bottom-left coord is 2,3 and top-right coord is 14,15
# box 2, bottom-left coord is 30,31 and top-right coord is 42,43
# Note that only the boxes for the
imval( 'myImage', box='2,3,14,15;30,31,42,43' )
# Select the same two box regions but only channels 4 and 5
imval( 'myImage', box='2,3,14,15;30,31,42,43', chan='4~5' )
# Select all channels greater the 20 as well as channel 0.
# Then the mean and standard deviation are printed
# Note that the data returned is a Python numpy array which
# has built in operations such as min, max, and means as
# demonstrated here.
results = imval( 'myImage', chans='>20;0' )
imval_data=results['data']
mask=results['mask']
# holds the absolute coordinates of the associated pixels in imval_data
coords = results['coords']
print "Data max: ", imval_data.max(), " mean is ", imval_data.mean()
swapped_data=imval_data.swapaxes(0,2)
swapped_mask=mask.swapaxes(0,2)
print "Data values for 21st channel: \n", swapped_data[0]
print "Mask values for 21st channel: \n", swapped_mask[0]
1.8.0