| 1 | from scantable import scantable
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| 2 | from asap import rcParams
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| 3 |
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| 4 | def average_time(*args, **kwargs):
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| 5 | """
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| 6 | Return the (time) average of a scan or list of scans. [in channels only]
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| 7 | The cursor of the output scan is set to 0
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| 8 | Parameters:
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| 9 | one scan or comma separated scans
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| 10 | mask: an optional mask (only used for 'var' and 'tsys' weighting)
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| 11 | scanav: True averages each scan separately.
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| 12 | False (default) averages all scans together,
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| 13 | weight: Weighting scheme. 'none, 'var' (1/var(spec)
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| 14 | weighted), 'tsys' (1/Tsys**2 weighted), 'tint'
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| 15 | (integration time weighted) or 'tintsys' (Tsys
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| 16 | and tint). The default is 'tint'
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| 17 | Example:
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| 18 | # return a time averaged scan from scana and scanb
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| 19 | # without using a mask
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| 20 | scanav = average_time(scana,scanb)
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| 21 | # return the (time) averaged scan, i.e. the average of
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| 22 | # all correlator cycles
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| 23 | scanav = average_time(scan, scanav=True)
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| 24 |
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| 25 | """
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| 26 | scanAv = False
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| 27 | if kwargs.has_key('scanav'):
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| 28 | scanAv = kwargs.get('scanav')
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| 29 | weight = 'tint'
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| 30 | if kwargs.has_key('weight'):
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| 31 | weight = kwargs.get('weight')
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| 32 | mask = ()
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| 33 | if kwargs.has_key('mask'):
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| 34 | mask = kwargs.get('mask')
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| 35 | varlist = vars()
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| 36 | lst = tuple(args)
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| 37 | del varlist["kwargs"]
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| 38 | varlist["args"] = "%d scantables" % len(lst)
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| 39 | # need special formatting her for history...
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| 40 |
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| 41 | from asap._asap import average as _av
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| 42 | for s in lst:
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| 43 | if not isinstance(s,scantable):
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| 44 | print "Please give a list of scantables"
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| 45 | return
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| 46 | s = scantable(_av(lst, mask, scanAv, weight))
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| 47 | s._add_history("average_time",varlist)
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| 48 | return s
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| 49 |
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| 50 | def quotient(source, reference, preserve=True):
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| 51 | """
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| 52 | Return the quotient of a 'source' (signal) scan and a 'reference' scan.
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| 53 | The reference can have just one row, even if the signal has many. Otherwise
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| 54 | they must have the same number of rows.
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| 55 | The cursor of the output scan is set to 0
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| 56 | Parameters:
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| 57 | source: the 'on' scan
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| 58 | reference: the 'off' scan
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| 59 | preserve: you can preserve (default) the continuum or
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| 60 | remove it. The equations used are
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| 61 | preserve: Output = Toff * (on/off) - Toff
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| 62 | remove: Output = Toff * (on/off) - Ton
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| 63 | """
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| 64 | varlist = vars()
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| 65 | from asap._asap import quotient as _quot
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| 66 | s = scantable(_quot(source, reference, preserve))
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| 67 | s._add_history("quotient",varlist)
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| 68 | return s
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| 69 |
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| 70 | def simple_math(left, right, op='add', tsys=True):
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| 71 | """
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| 72 | Apply simple mathematical binary operations to two
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| 73 | scan tables, returning the result in a new scan table.
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| 74 | The operation is applied to both the correlations and the TSys data
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| 75 | The cursor of the output scan is set to 0
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| 76 | Parameters:
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| 77 | left: the 'left' scan
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| 78 | right: the 'right' scan
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| 79 | op: the operation: 'add' (default), 'sub', 'mul', 'div'
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| 80 | tsys: if True (default) then apply the operation to Tsys
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| 81 | as well as the data
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| 82 | """
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| 83 | varlist = vars()
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| 84 | if not isinstance(left,scantable) and not isinstance(right,scantable):
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| 85 | print "Please provide two scantables as input"
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| 86 | return
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| 87 | from asap._asap import b_operate as _bop
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| 88 | s = scantable(_bop(left, right, op, tsys))
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| 89 | s._add_history("simple_math", varlist)
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| 90 | return s
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