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