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##### table.calc - Function

3.2.1 TaQL expression with calc to calculate an expression on a table

Description

Get the result from the calculation of an expression on a table

The expression can be any expression that can be given in the WHERE clause of a SELECT expression (thus including subqueries). The given expression determines if the result is a scalar, a vector, or a record containing arrays. See the examples below.

Arguments

 Inputs expr Expression string allowed: string Default: prefix TaQL prefix for style and ordering etc ...check TaQL note 199 for usage allowed: string Default: using style base0, endincl, fortranorder showtaql Show the full taql command used allowed: bool Default: false
Returns
anyvariant

Example

tb.calc(’[select from ngc5921.ms  giving [mean(abs(DATA))]]’)

find the mean of the abs of each row of the  DATA column of the MeasurementSet ngc5921.ms

returns a (potentially enormous) record where a field contains the
value of the expression for the row with that number. Note that it
returns a record because for each row the expression results in an array.
It should be clear that this example is useless. However, something
like this could be useful for a column with (very) small arrays.

tb.calc(’[select from ngc5921.ms.contsub giving  [ntrue(FLAG)]]’)

returns for each row the number of flags set. The result is a vector,
because for each row the expression results in a scalar.

tb.calc(’sum([select from ngc5921.ms.contsub giving  [ntrue(FLAG)]])’)

returns the total number of flags set in the table (in a single
scalar).

using subrow array
tb.calc(’median([select from ngc5921.ms where ANTENNA1==3 && ANTENNA2==5 giving [abs(DATA[0,31])]])’)

The above will find the median channel 31 and 0th pol of the requested  baseline formed with antennas 3 and 5.
Note that the that the default casa order of arrays is fortran order ...pol axis is before channel axis

tb.calc(’median([select from ngc5921.ms where ANTENNA1==3 && ANTENNA2==5 giving [abs(DATA[31, 0])]])’, prefix=’using style python’)

Now the same is as the above but using the python style of axis ordering access

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