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imager.apparentsens - Function

2.3.1 Calculate rms sensitivity directly from weights


Description

This function calculates the point source sensitivity for the data selected by im.selectvis(...), and according to the imaging weighting parameters specified in im.weight(...) and im.defineimage(...). The calculation is performed solely using the weight information stored in the MS WEIGHT column (WEIGHT_SPECTRUM tbd), and as adjusted by the net imaging weighting function (natural, uniform, robust, taper, etc.). Therefore, it is assumed that the MS WEIGHTs have been properly initialized and calibrated along with the visibility data. As long as the WEIGHTs are in the inverse square units of the visibilities (i.e., inverse variance weights), the calculation should yield the real theoretical imaging sensitivity for data at any stage of the calibration (though data at early and intermediate stages of calibration may not be sufficiently coherent for imaging at high–or even modest–fidelity).

Two values are reported in the logger and returned (see example below). First, the apparent sensitivity (in the units implied by the WEIGHTs’ units), for the specified imaging weighting scheme. Second, a unitless factor describing the ratio of the apparent sensitivity to that obtained with pure ’natural’ weighting (the nominal peak sensitivity). When ’natural’ weighting is selected, this ratio factor will be 1.0; all other weighting choices will yield an apparent sensitivity ratio greater than 1.0.

Currently, this function reports only the continuum sensitivity for the selected data, and in particular, for the aggregate bandwidth indicated by the spectral window selection. The calculation further assumes that the visibility samples are each entirely independent (i.e., no redundant samples such as would occur for overlapping spectral windows).

A future version of this function will support reporting a sensitivity spectrum for the spectral line case (including support for WEIGHT_SPECTRUM). For now, spectral line sensitivity may be reasonably estimated by dividing the reported sensitivity by the square root of the fractional bandwidth of a single image channel, or by selecting a bandwidth matching the width of a single image channel.

Arguments





Outputs

pointsource

Calculated apparent point source sensitivity (in units implied by the MS weights)

allowed:

double

Default:

relative

Ratio of apparent sensitivity relative to natural weighting

allowed:

double

Default:

Inputs

async

Run asynchronously in the background

allowed:

bool

Default:

false

Returns
bool

Example

 
 
# open and set up selection and image plane parameters  
im.open(’mydata.ms’)  
im.selectvis(field=’2’,spw=’0’)  
im.defineimage(mode=’mfs’,spw=0,stokes=’I’,cellx=’15arcsec’,celly=’15arcsec’,nx=256,ny=256)  
 
# report natural weighting sensitivity  
im.weight(type=’natural’)  
nat=im.apparentsens();  
print ’Natural Sensitivity =’, nat[1];  
print ’Relative to Natural Weighting = ’, nat[2];  
 
# switch to uniform weighting  
im.weight(type=’uniform’)  
uni=im.apparentsens();  
print ’Uniform Sensitivity =’, uni[1];  
print ’Relative to Natural Weighting = ’, uni[2];  
 
# switch to briggs weighting  
im.weight(type=’briggs’,robust=0.0)  
rob=im.apparentsens();  
print ’Briggs Sensitivity =’, rob[1];  
print ’Relative to Natural Weighting = ’, rob[2];  
 
im.close()  
 

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