| [1085] | 1 | from asap.scantable import scantable
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| [258] | 2 | from asap import rcParams
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| [720] | 3 | from asap import print_log
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| [1389] | 4 | from asap import selector
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| [101] | 5 |
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| [143] | 6 | def average_time(*args, **kwargs):
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| [101] | 7 | """
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| [113] | 8 | Return the (time) average of a scan or list of scans. [in channels only]
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| [305] | 9 | The cursor of the output scan is set to 0
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| [113] | 10 | Parameters:
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| [1361] | 11 | one scan or comma separated scans or a list of scans
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| [143] | 12 | mask: an optional mask (only used for 'var' and 'tsys' weighting)
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| [558] | 13 | scanav: True averages each scan separately.
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| 14 | False (default) averages all scans together,
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| [1232] | 15 | weight: Weighting scheme.
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| 16 | 'none' (mean no weight)
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| 17 | 'var' (1/var(spec) weighted)
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| 18 | 'tsys' (1/Tsys**2 weighted)
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| 19 | 'tint' (integration time weighted)
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| 20 | 'tintsys' (Tint/Tsys**2)
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| 21 | 'median' ( median averaging)
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| [930] | 22 | align: align the spectra in velocity before averaging. It takes
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| 23 | the time of the first spectrum in the first scantable
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| 24 | as reference time.
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| [113] | 25 | Example:
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| 26 | # return a time averaged scan from scana and scanb
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| 27 | # without using a mask
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| [129] | 28 | scanav = average_time(scana,scanb)
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| [1361] | 29 | # or equivalent
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| 30 | # scanav = average_time([scana, scanb])
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| [113] | 31 | # return the (time) averaged scan, i.e. the average of
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| 32 | # all correlator cycles
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| [558] | 33 | scanav = average_time(scan, scanav=True)
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| [101] | 34 | """
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| [930] | 35 | scanav = False
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| [143] | 36 | if kwargs.has_key('scanav'):
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| [930] | 37 | scanav = kwargs.get('scanav')
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| [524] | 38 | weight = 'tint'
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| [143] | 39 | if kwargs.has_key('weight'):
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| 40 | weight = kwargs.get('weight')
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| 41 | mask = ()
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| 42 | if kwargs.has_key('mask'):
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| 43 | mask = kwargs.get('mask')
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| [930] | 44 | align = False
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| 45 | if kwargs.has_key('align'):
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| 46 | align = kwargs.get('align')
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| [1446] | 47 | compel = False
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| 48 | if kwargs.has_key('compel'):
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| 49 | compel = kwargs.get('compel')
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| [489] | 50 | varlist = vars()
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| [665] | 51 | if isinstance(args[0],list):
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| [981] | 52 | lst = args[0]
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| [665] | 53 | elif isinstance(args[0],tuple):
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| [981] | 54 | lst = list(args[0])
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| [665] | 55 | else:
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| [981] | 56 | lst = list(args)
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| [720] | 57 |
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| [489] | 58 | del varlist["kwargs"]
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| 59 | varlist["args"] = "%d scantables" % len(lst)
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| [981] | 60 | # need special formatting here for history...
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| [720] | 61 |
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| [876] | 62 | from asap._asap import stmath
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| 63 | stm = stmath()
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| [113] | 64 | for s in lst:
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| [101] | 65 | if not isinstance(s,scantable):
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| [720] | 66 | msg = "Please give a list of scantables"
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| 67 | if rcParams['verbose']:
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| 68 | print msg
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| 69 | return
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| 70 | else:
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| 71 | raise TypeError(msg)
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| [945] | 72 | if scanav: scanav = "SCAN"
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| 73 | else: scanav = "NONE"
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| [981] | 74 | alignedlst = []
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| 75 | if align:
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| 76 | refepoch = lst[0].get_time(0)
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| 77 | for scan in lst:
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| 78 | alignedlst.append(scan.freq_align(refepoch,insitu=False))
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| 79 | else:
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| [1059] | 80 | alignedlst = lst
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| [1232] | 81 | if weight.upper() == 'MEDIAN':
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| 82 | # median doesn't support list of scantables - merge first
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| 83 | merged = None
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| 84 | if len(alignedlst) > 1:
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| 85 | merged = merge(alignedlst)
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| 86 | else:
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| 87 | merged = alignedlst[0]
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| 88 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav))
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| 89 | del merged
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| 90 | else:
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| [1446] | 91 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
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| 92 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav))
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| [489] | 93 | s._add_history("average_time",varlist)
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| [720] | 94 | print_log()
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| [489] | 95 | return s
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| [101] | 96 |
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| [1074] | 97 | def quotient(source, reference, preserve=True):
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| 98 | """
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| 99 | Return the quotient of a 'source' (signal) scan and a 'reference' scan.
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| 100 | The reference can have just one scan, even if the signal has many. Otherwise
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| 101 | they must have the same number of scans.
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| 102 | The cursor of the output scan is set to 0
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| 103 | Parameters:
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| 104 | source: the 'on' scan
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| 105 | reference: the 'off' scan
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| 106 | preserve: you can preserve (default) the continuum or
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| 107 | remove it. The equations used are
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| 108 | preserve: Output = Toff * (on/off) - Toff
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| 109 | remove: Output = Toff * (on/off) - Ton
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| 110 | """
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| 111 | varlist = vars()
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| 112 | from asap._asap import stmath
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| 113 | stm = stmath()
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| 114 | stm._setinsitu(False)
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| 115 | s = scantable(stm._quotient(source, reference, preserve))
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| 116 | s._add_history("quotient",varlist)
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| 117 | print_log()
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| 118 | return s
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| [101] | 119 |
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| [1389] | 120 | def dototalpower(calon, caloff, tcalval=0.0):
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| 121 | """
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| 122 | Do calibration for CAL on,off signals.
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| 123 | Adopted from GBTIDL dototalpower
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| 124 | Parameters:
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| 125 | calon: the 'cal on' subintegration
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| 126 | caloff: the 'cal off' subintegration
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| 127 | tcalval: user supplied Tcal value
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| 128 | """
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| 129 | varlist = vars()
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| 130 | from asap._asap import stmath
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| 131 | stm = stmath()
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| 132 | stm._setinsitu(False)
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| 133 | s = scantable(stm._dototalpower(calon, caloff, tcalval))
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| 134 | s._add_history("dototalpower",varlist)
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| 135 | print_log()
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| 136 | return s
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| 137 |
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| 138 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0):
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| 139 | """
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| 140 | Calculate a quotient (sig-ref/ref * Tsys)
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| 141 | Adopted from GBTIDL dosigref
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| 142 | Parameters:
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| 143 | sig: on source data
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| 144 | ref: reference data
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| 145 | smooth: width of box car smoothing for reference
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| 146 | tsysval: user specified Tsys (scalar only)
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| 147 | tauval: user specified Tau (required if tsysval is set)
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| 148 | """
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| 149 | varlist = vars()
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| 150 | from asap._asap import stmath
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| 151 | stm = stmath()
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| 152 | stm._setinsitu(False)
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| 153 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval))
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| 154 | s._add_history("dosigref",varlist)
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| 155 | print_log()
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| 156 | return s
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| 157 |
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| 158 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0):
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| 159 | """
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| 160 | Calibrate GBT position switched data
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| 161 | Adopted from GBTIDL getps
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| 162 | Currently calps identify the scans as position switched data if they
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| 163 | contain '_ps' in the source name. The data must contains 'CAL' signal
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| 164 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
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| 165 | need to be present in the source name field.
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| 166 | (GBT MS data reading process to scantable automatically append these
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| 167 | id names to the source names)
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| 168 |
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| 169 | Parameters:
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| 170 | scantab: scantable
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| 171 | scannos: list of scan numbers
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| 172 | smooth: optional box smoothing order for the reference
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| 173 | (default is 1 = no smoothing)
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| 174 | tsysval: optional user specified Tsys (default is 0.0,
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| 175 | use Tsys in the data)
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| 176 | tauval: optional user specified Tau
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| 177 | tcalval: optional user specified Tcal (default is 0.0,
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| 178 | use Tcal value in the data)
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| 179 | """
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| 180 | varlist = vars()
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| 181 | # check for the appropriate data
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| 182 | s = scantab.get_scan('*_ps*')
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| 183 | if s is None:
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| 184 | msg = "The input data appear to contain no position-switch mode data."
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| 185 | if rcParams['verbose']:
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| 186 | print msg
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| 187 | return
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| 188 | else:
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| 189 | raise TypeError(msg)
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| 190 | ssub = s.get_scan(scannos)
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| 191 | if ssub is None:
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| 192 | msg = "No data was found with given scan numbers!"
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| 193 | if rcParams['verbose']:
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| 194 | print msg
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| 195 | return
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| 196 | else:
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| 197 | raise TypeError(msg)
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| 198 | ssubon = ssub.get_scan('*calon')
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| 199 | ssuboff = ssub.get_scan('*[^calon]')
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| 200 | if ssubon.nrow() != ssuboff.nrow():
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| 201 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers."
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| 202 | if rcParams['verbose']:
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| 203 | print msg
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| 204 | return
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| 205 | else:
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| 206 | raise TypeError(msg)
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| 207 | cals = dototalpower(ssubon, ssuboff, tcalval)
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| 208 | sig = cals.get_scan('*ps')
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| 209 | ref = cals.get_scan('*psr')
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| 210 | if sig.nscan() != ref.nscan():
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| 211 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers."
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| 212 | if rcParams['verbose']:
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| 213 | print msg
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| 214 | return
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| 215 | else:
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| 216 | raise TypeError(msg)
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| 217 |
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| 218 | #for user supplied Tsys
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| 219 | if tsysval>0.0:
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| 220 | if tauval<=0.0:
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| 221 | msg = "Need to supply a valid tau to use the supplied Tsys"
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| 222 | if rcParams['verbose']:
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| 223 | print msg
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| 224 | return
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| 225 | else:
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| 226 | raise TypeError(msg)
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| 227 | else:
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| 228 | sig.recalc_azel()
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| 229 | ref.recalc_azel()
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| 230 | #msg = "Use of user specified Tsys is not fully implemented yet."
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| 231 | #if rcParams['verbose']:
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| 232 | # print msg
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| 233 | # return
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| 234 | #else:
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| 235 | # raise TypeError(msg)
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| 236 | # use get_elevation to get elevation and
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| 237 | # calculate a scaling factor using the formula
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| 238 | # -> tsys use to dosigref
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| 239 |
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| 240 | #ress = dosigref(sig, ref, smooth, tsysval)
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| 241 | ress = dosigref(sig, ref, smooth, tsysval, tauval)
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| 242 | ress._add_history("calps", varlist)
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| 243 | print_log()
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| 244 | return ress
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| 245 |
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| 246 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0):
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| 247 | """
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| 248 | Do full (but a pair of scans at time) processing of GBT Nod data
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| 249 | calibration.
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| 250 | Adopted from GBTIDL's getnod
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| 251 | Parameters:
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| 252 | scantab: scantable
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| 253 | scannos: a pair of scan numbers, or the first scan number of the pair
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| 254 | smooth: box car smoothing order
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| 255 | tsysval: optional user specified Tsys value
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| 256 | tauval: optional user specified tau value (not implemented yet)
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| 257 | tcalval: optional user specified Tcal value
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| 258 | """
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| 259 | varlist = vars()
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| 260 | from asap._asap import stmath
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| 261 | stm = stmath()
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| 262 | stm._setinsitu(False)
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| 263 |
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| 264 | # check for the appropriate data
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| 265 | s = scantab.get_scan('*_nod*')
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| 266 | if s is None:
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| 267 | msg = "The input data appear to contain no Nod observing mode data."
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| 268 | if rcParams['verbose']:
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| 269 | print msg
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| 270 | return
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| 271 | else:
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| 272 | raise TypeError(msg)
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| 273 |
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| 274 | # need check correspondance of each beam with sig-ref ...
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| 275 | # check for timestamps, scan numbers, subscan id (not available in
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| 276 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig
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| 277 | # and beam 1 - ref...)
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| 278 | # First scan number of paired scans or list of pairs of
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| 279 | # scan numbers (has to have even number of pairs.)
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| 280 |
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| 281 | #data splitting
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| 282 | scan1no = scan2no = 0
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| 283 |
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| 284 | if len(scannos)==1:
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| 285 | scan1no = scannos[0]
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| 286 | scan2no = scannos[0]+1
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| 287 | pairScans = [scan1no, scan2no]
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| 288 | else:
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| 289 | #if len(scannos)>2:
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| 290 | # msg = "calnod can only process a pair of nod scans at time."
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| 291 | # if rcParams['verbose']:
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| 292 | # print msg
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| 293 | # return
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| 294 | # else:
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| 295 | # raise TypeError(msg)
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| 296 | #
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| 297 | #if len(scannos)==2:
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| 298 | # scan1no = scannos[0]
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| 299 | # scan2no = scannos[1]
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| 300 | pairScans = list(scannos)
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| 301 |
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| 302 | if tsysval>0.0:
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| 303 | if tauval<=0.0:
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| 304 | msg = "Need to supply a valid tau to use the supplied Tsys"
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| 305 | if rcParams['verbose']:
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| 306 | print msg
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| 307 | return
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| 308 | else:
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| 309 | raise TypeError(msg)
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| 310 | else:
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| 311 | scantab.recalc_azel()
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| 312 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval))
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| 313 | resspec._add_history("calnod",varlist)
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| 314 | print_log()
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| 315 | return resspec
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| 316 |
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| 317 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0):
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| 318 | """
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| 319 | Calibrate GBT frequency switched data.
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| 320 | Adopted from GBTIDL getfs.
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| 321 | Currently calfs identify the scans as frequency switched data if they
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| 322 | contain '_fs' in the source name. The data must contains 'CAL' signal
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| 323 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
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| 324 | need to be present in the source name field.
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| 325 | (GBT MS data reading via scantable automatically append these
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| 326 | id names to the source names)
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| 327 |
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| 328 | Parameters:
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| 329 | scantab: scantable
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| 330 | scannos: list of scan numbers
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| 331 | smooth: optional box smoothing order for the reference
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| 332 | (default is 1 = no smoothing)
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| 333 | tsysval: optional user specified Tsys (default is 0.0,
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| 334 | use Tsys in the data)
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| 335 | tauval: optional user specified Tau
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| 336 | """
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| 337 | varlist = vars()
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| 338 | from asap._asap import stmath
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| 339 | stm = stmath()
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| 340 | stm._setinsitu(False)
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| 341 |
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| 342 | # check = scantab.get_scan('*_fs*')
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| 343 | # if check is None:
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| 344 | # msg = "The input data appear to contain no Nod observing mode data."
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| 345 | # if rcParams['verbose']:
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| 346 | # print msg
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| 347 | # return
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| 348 | # else:
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| 349 | # raise TypeError(msg)
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| 350 | s = scantab.get_scan(scannos)
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| 351 | del scantab
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| 352 |
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| 353 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval))
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| 354 | resspec._add_history("calfs",varlist)
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| 355 | print_log()
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| 356 | return resspec
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| 357 |
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| [296] | 358 | def simple_math(left, right, op='add', tsys=True):
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| [242] | 359 | """
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| [720] | 360 | Apply simple mathematical binary operations to two
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| [242] | 361 | scan tables, returning the result in a new scan table.
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| 362 | The operation is applied to both the correlations and the TSys data
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| [305] | 363 | The cursor of the output scan is set to 0
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| [242] | 364 | Parameters:
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| 365 | left: the 'left' scan
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| 366 | right: the 'right' scan
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| 367 | op: the operation: 'add' (default), 'sub', 'mul', 'div'
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| [296] | 368 | tsys: if True (default) then apply the operation to Tsys
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| 369 | as well as the data
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| [242] | 370 | """
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| [1357] | 371 | print "simple_math is deprecated use +=/* instead."
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| [918] | 372 |
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| 373 | def merge(*args):
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| [945] | 374 | """
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| [1362] | 375 | Merge a list of scanatables, or comma-sperated scantables into one
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| 376 | scnatble.
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| 377 | Parameters:
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| 378 | A list [scan1, scan2] or scan1, scan2.
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| 379 | Example:
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| 380 | myscans = [scan1, scan2]
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| 381 | allscans = merge(myscans)
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| 382 | # or equivalent
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| 383 | sameallscans = merge(scan1, scan2)
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| [945] | 384 | """
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| [918] | 385 | varlist = vars()
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| 386 | if isinstance(args[0],list):
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| 387 | lst = tuple(args[0])
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| 388 | elif isinstance(args[0],tuple):
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| 389 | lst = args[0]
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| 390 | else:
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| 391 | lst = tuple(args)
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| 392 | varlist["args"] = "%d scantables" % len(lst)
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| 393 | # need special formatting her for history...
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| 394 | from asap._asap import stmath
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| 395 | stm = stmath()
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| 396 | for s in lst:
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| 397 | if not isinstance(s,scantable):
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| 398 | msg = "Please give a list of scantables"
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| 399 | if rcParams['verbose']:
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| 400 | print msg
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| 401 | return
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| 402 | else:
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| 403 | raise TypeError(msg)
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| 404 | s = scantable(stm._merge(lst))
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| 405 | s._add_history("merge", varlist)
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| 406 | print_log()
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| 407 | return s
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| [1074] | 408 |
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