| [1085] | 1 | from asap.scantable import scantable
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| [258] | 2 | from asap import rcParams
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| [1757] | 3 | from asap import print_log, print_log_dec
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| [1389] | 4 | from asap import selector
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| [1614] | 5 | from asap import asaplog
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| [1631] | 6 | from asap import asaplotgui
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| [101] | 7 |
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| [1798] | 8 | @print_log_dec
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| [143] | 9 | def average_time(*args, **kwargs):
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| [101] | 10 | """
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| [113] | 11 | Return the (time) average of a scan or list of scans. [in channels only]
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| [305] | 12 | The cursor of the output scan is set to 0
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| [113] | 13 | Parameters:
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| [1361] | 14 | one scan or comma separated scans or a list of scans
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| [143] | 15 | mask: an optional mask (only used for 'var' and 'tsys' weighting)
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| [558] | 16 | scanav: True averages each scan separately.
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| 17 | False (default) averages all scans together,
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| [1232] | 18 | weight: Weighting scheme.
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| 19 | 'none' (mean no weight)
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| 20 | 'var' (1/var(spec) weighted)
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| 21 | 'tsys' (1/Tsys**2 weighted)
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| 22 | 'tint' (integration time weighted)
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| 23 | 'tintsys' (Tint/Tsys**2)
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| 24 | 'median' ( median averaging)
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| [930] | 25 | align: align the spectra in velocity before averaging. It takes
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| 26 | the time of the first spectrum in the first scantable
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| 27 | as reference time.
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| [113] | 28 | Example:
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| 29 | # return a time averaged scan from scana and scanb
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| 30 | # without using a mask
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| [129] | 31 | scanav = average_time(scana,scanb)
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| [1757] | 32 | # or equivalent
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| 33 | # scanav = average_time([scana, scanb])
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| [113] | 34 | # return the (time) averaged scan, i.e. the average of
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| 35 | # all correlator cycles
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| [558] | 36 | scanav = average_time(scan, scanav=True)
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| [101] | 37 | """
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| [930] | 38 | scanav = False
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| [143] | 39 | if kwargs.has_key('scanav'):
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| [930] | 40 | scanav = kwargs.get('scanav')
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| [524] | 41 | weight = 'tint'
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| [143] | 42 | if kwargs.has_key('weight'):
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| 43 | weight = kwargs.get('weight')
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| 44 | mask = ()
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| 45 | if kwargs.has_key('mask'):
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| 46 | mask = kwargs.get('mask')
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| [930] | 47 | align = False
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| 48 | if kwargs.has_key('align'):
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| 49 | align = kwargs.get('align')
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| [1446] | 50 | compel = False
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| 51 | if kwargs.has_key('compel'):
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| 52 | compel = kwargs.get('compel')
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| [489] | 53 | varlist = vars()
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| [665] | 54 | if isinstance(args[0],list):
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| [981] | 55 | lst = args[0]
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| [665] | 56 | elif isinstance(args[0],tuple):
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| [981] | 57 | lst = list(args[0])
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| [665] | 58 | else:
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| [981] | 59 | lst = list(args)
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| [720] | 60 |
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| [489] | 61 | del varlist["kwargs"]
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| 62 | varlist["args"] = "%d scantables" % len(lst)
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| [981] | 63 | # need special formatting here for history...
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| [720] | 64 |
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| [876] | 65 | from asap._asap import stmath
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| 66 | stm = stmath()
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| [113] | 67 | for s in lst:
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| [101] | 68 | if not isinstance(s,scantable):
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| [720] | 69 | msg = "Please give a list of scantables"
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| 70 | if rcParams['verbose']:
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| [1612] | 71 | #print msg
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| [1614] | 72 | asaplog.push(msg)
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| 73 | print_log('ERROR')
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| [720] | 74 | return
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| 75 | else:
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| 76 | raise TypeError(msg)
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| [945] | 77 | if scanav: scanav = "SCAN"
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| 78 | else: scanav = "NONE"
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| [981] | 79 | alignedlst = []
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| 80 | if align:
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| 81 | refepoch = lst[0].get_time(0)
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| 82 | for scan in lst:
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| 83 | alignedlst.append(scan.freq_align(refepoch,insitu=False))
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| 84 | else:
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| [1059] | 85 | alignedlst = lst
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| [1232] | 86 | if weight.upper() == 'MEDIAN':
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| 87 | # median doesn't support list of scantables - merge first
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| 88 | merged = None
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| 89 | if len(alignedlst) > 1:
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| 90 | merged = merge(alignedlst)
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| 91 | else:
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| 92 | merged = alignedlst[0]
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| 93 | s = scantable(stm._averagechannel(merged, 'MEDIAN', scanav))
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| 94 | del merged
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| 95 | else:
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| [1446] | 96 | #s = scantable(stm._average(alignedlst, mask, weight.upper(), scanav))
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| 97 | s = scantable(stm._new_average(alignedlst, compel, mask, weight.upper(), scanav))
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| [489] | 98 | s._add_history("average_time",varlist)
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| [720] | 99 | print_log()
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| [489] | 100 | return s
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| [101] | 101 |
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| [1074] | 102 | def quotient(source, reference, preserve=True):
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| 103 | """
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| 104 | Return the quotient of a 'source' (signal) scan and a 'reference' scan.
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| 105 | The reference can have just one scan, even if the signal has many. Otherwise
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| 106 | they must have the same number of scans.
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| 107 | The cursor of the output scan is set to 0
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| 108 | Parameters:
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| 109 | source: the 'on' scan
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| 110 | reference: the 'off' scan
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| 111 | preserve: you can preserve (default) the continuum or
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| 112 | remove it. The equations used are
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| 113 | preserve: Output = Toff * (on/off) - Toff
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| 114 | remove: Output = Toff * (on/off) - Ton
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| 115 | """
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| 116 | varlist = vars()
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| 117 | from asap._asap import stmath
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| 118 | stm = stmath()
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| 119 | stm._setinsitu(False)
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| 120 | s = scantable(stm._quotient(source, reference, preserve))
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| 121 | s._add_history("quotient",varlist)
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| 122 | print_log()
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| 123 | return s
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| [101] | 124 |
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| [1798] | 125 | @print_log_dec
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| [1389] | 126 | def dototalpower(calon, caloff, tcalval=0.0):
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| 127 | """
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| 128 | Do calibration for CAL on,off signals.
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| 129 | Adopted from GBTIDL dototalpower
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| 130 | Parameters:
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| 131 | calon: the 'cal on' subintegration
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| 132 | caloff: the 'cal off' subintegration
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| 133 | tcalval: user supplied Tcal value
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| 134 | """
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| 135 | varlist = vars()
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| 136 | from asap._asap import stmath
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| 137 | stm = stmath()
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| 138 | stm._setinsitu(False)
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| 139 | s = scantable(stm._dototalpower(calon, caloff, tcalval))
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| 140 | s._add_history("dototalpower",varlist)
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| 141 | print_log()
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| 142 | return s
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| 143 |
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| [1798] | 144 | @print_log_dec
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| [1389] | 145 | def dosigref(sig, ref, smooth, tsysval=0.0, tauval=0.0):
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| 146 | """
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| 147 | Calculate a quotient (sig-ref/ref * Tsys)
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| 148 | Adopted from GBTIDL dosigref
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| 149 | Parameters:
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| 150 | sig: on source data
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| 151 | ref: reference data
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| 152 | smooth: width of box car smoothing for reference
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| 153 | tsysval: user specified Tsys (scalar only)
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| 154 | tauval: user specified Tau (required if tsysval is set)
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| 155 | """
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| 156 | varlist = vars()
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| 157 | from asap._asap import stmath
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| 158 | stm = stmath()
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| 159 | stm._setinsitu(False)
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| 160 | s = scantable(stm._dosigref(sig, ref, smooth, tsysval, tauval))
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| 161 | s._add_history("dosigref",varlist)
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| 162 | print_log()
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| 163 | return s
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| 164 |
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| [1798] | 165 | @print_log_dec
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| [1631] | 166 | def calps(scantab, scannos, smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
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| [1389] | 167 | """
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| 168 | Calibrate GBT position switched data
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| 169 | Adopted from GBTIDL getps
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| 170 | Currently calps identify the scans as position switched data if they
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| 171 | contain '_ps' in the source name. The data must contains 'CAL' signal
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| 172 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
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| 173 | need to be present in the source name field.
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| 174 | (GBT MS data reading process to scantable automatically append these
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| 175 | id names to the source names)
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| 176 |
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| 177 | Parameters:
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| 178 | scantab: scantable
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| 179 | scannos: list of scan numbers
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| 180 | smooth: optional box smoothing order for the reference
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| 181 | (default is 1 = no smoothing)
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| 182 | tsysval: optional user specified Tsys (default is 0.0,
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| 183 | use Tsys in the data)
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| 184 | tauval: optional user specified Tau
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| 185 | tcalval: optional user specified Tcal (default is 0.0,
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| 186 | use Tcal value in the data)
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| 187 | """
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| 188 | varlist = vars()
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| 189 | # check for the appropriate data
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| [1693] | 190 | ## s = scantab.get_scan('*_ps*')
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| 191 | ## if s is None:
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| 192 | ## msg = "The input data appear to contain no position-switch mode data."
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| 193 | ## if rcParams['verbose']:
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| 194 | ## #print msg
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| 195 | ## asaplog.push(msg)
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| 196 | ## print_log('ERROR')
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| 197 | ## return
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| 198 | ## else:
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| 199 | ## raise TypeError(msg)
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| 200 | s = scantab.copy()
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| 201 | from asap._asap import srctype
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| 202 | sel = selector()
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| 203 | sel.set_types( srctype.pson )
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| 204 | try:
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| 205 | scantab.set_selection( sel )
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| 206 | except Exception, e:
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| [1389] | 207 | msg = "The input data appear to contain no position-switch mode data."
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| 208 | if rcParams['verbose']:
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| [1612] | 209 | #print msg
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| [1614] | 210 | asaplog.push(msg)
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| 211 | print_log('ERROR')
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| [1389] | 212 | return
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| 213 | else:
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| 214 | raise TypeError(msg)
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| [1693] | 215 | s.set_selection()
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| 216 | sel.reset()
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| [1389] | 217 | ssub = s.get_scan(scannos)
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| 218 | if ssub is None:
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| 219 | msg = "No data was found with given scan numbers!"
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| 220 | if rcParams['verbose']:
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| [1612] | 221 | #print msg
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| [1614] | 222 | asaplog.push(msg)
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| 223 | print_log('ERROR')
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| [1389] | 224 | return
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| 225 | else:
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| 226 | raise TypeError(msg)
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| [1693] | 227 | #ssubon = ssub.get_scan('*calon')
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| 228 | #ssuboff = ssub.get_scan('*[^calon]')
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| 229 | sel.set_types( [srctype.poncal,srctype.poffcal] )
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| 230 | ssub.set_selection( sel )
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| 231 | ssubon = ssub.copy()
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| 232 | ssub.set_selection()
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| 233 | sel.reset()
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| 234 | sel.set_types( [srctype.pson,srctype.psoff] )
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| 235 | ssub.set_selection( sel )
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| 236 | ssuboff = ssub.copy()
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| 237 | ssub.set_selection()
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| 238 | sel.reset()
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| [1389] | 239 | if ssubon.nrow() != ssuboff.nrow():
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| 240 | msg = "mismatch in numbers of CAL on/off scans. Cannot calibrate. Check the scan numbers."
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| 241 | if rcParams['verbose']:
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| [1612] | 242 | #print msg
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| [1614] | 243 | asaplog.push(msg)
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| 244 | print_log('ERROR')
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| [1389] | 245 | return
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| 246 | else:
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| 247 | raise TypeError(msg)
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| 248 | cals = dototalpower(ssubon, ssuboff, tcalval)
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| [1693] | 249 | #sig = cals.get_scan('*ps')
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| 250 | #ref = cals.get_scan('*psr')
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| 251 | sel.set_types( srctype.pson )
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| 252 | cals.set_selection( sel )
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| 253 | sig = cals.copy()
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| 254 | cals.set_selection()
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| 255 | sel.reset()
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| 256 | sel.set_types( srctype.psoff )
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| 257 | cals.set_selection( sel )
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| 258 | ref = cals.copy()
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| 259 | cals.set_selection()
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| 260 | sel.reset()
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| [1389] | 261 | if sig.nscan() != ref.nscan():
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| 262 | msg = "mismatch in numbers of on/off scans. Cannot calibrate. Check the scan numbers."
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| 263 | if rcParams['verbose']:
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| [1612] | 264 | #print msg
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| [1614] | 265 | asaplog.push(msg)
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| 266 | print_log('ERROR')
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| [1389] | 267 | return
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| 268 | else:
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| 269 | raise TypeError(msg)
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| 270 |
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| 271 | #for user supplied Tsys
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| 272 | if tsysval>0.0:
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| 273 | if tauval<=0.0:
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| 274 | msg = "Need to supply a valid tau to use the supplied Tsys"
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| 275 | if rcParams['verbose']:
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| [1612] | 276 | #print msg
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| [1614] | 277 | asaplog.push(msg)
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| 278 | print_log('ERROR')
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| [1389] | 279 | return
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| 280 | else:
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| 281 | raise TypeError(msg)
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| 282 | else:
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| 283 | sig.recalc_azel()
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| 284 | ref.recalc_azel()
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| 285 | #msg = "Use of user specified Tsys is not fully implemented yet."
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| 286 | #if rcParams['verbose']:
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| 287 | # print msg
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| 288 | # return
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| 289 | #else:
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| 290 | # raise TypeError(msg)
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| 291 | # use get_elevation to get elevation and
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| 292 | # calculate a scaling factor using the formula
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| 293 | # -> tsys use to dosigref
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| 294 |
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| 295 | #ress = dosigref(sig, ref, smooth, tsysval)
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| 296 | ress = dosigref(sig, ref, smooth, tsysval, tauval)
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| [1631] | 297 | ###
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| 298 | if verify:
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| 299 | # get data
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| 300 | import numpy
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| 301 | precal={}
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| 302 | postcal=[]
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| 303 | keys=['ps','ps_calon','psr','psr_calon']
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| [1693] | 304 | types=[srctype.pson,srctype.poncal,srctype.psoff,srctype.poffcal]
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| [1631] | 305 | ifnos=list(ssub.getifnos())
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| 306 | polnos=list(ssub.getpolnos())
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| 307 | sel=selector()
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| 308 | for i in range(2):
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| [1693] | 309 | #ss=ssuboff.get_scan('*'+keys[2*i])
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| [1631] | 310 | ll=[]
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| 311 | for j in range(len(ifnos)):
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| 312 | for k in range(len(polnos)):
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| 313 | sel.set_ifs(ifnos[j])
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| 314 | sel.set_polarizations(polnos[k])
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| [1693] | 315 | sel.set_types(types[2*i])
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| [1631] | 316 | try:
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| [1693] | 317 | #ss.set_selection(sel)
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| 318 | ssuboff.set_selection(sel)
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| [1631] | 319 | except:
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| 320 | continue
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| [1693] | 321 | #ll.append(numpy.array(ss._getspectrum(0)))
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| 322 | ll.append(numpy.array(ssuboff._getspectrum(0)))
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| [1631] | 323 | sel.reset()
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| [1693] | 324 | ssuboff.set_selection()
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| [1631] | 325 | precal[keys[2*i]]=ll
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| [1693] | 326 | #del ss
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| 327 | #ss=ssubon.get_scan('*'+keys[2*i+1])
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| [1631] | 328 | ll=[]
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| 329 | for j in range(len(ifnos)):
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| 330 | for k in range(len(polnos)):
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| 331 | sel.set_ifs(ifnos[j])
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| 332 | sel.set_polarizations(polnos[k])
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| [1693] | 333 | sel.set_types(types[2*i+1])
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| [1631] | 334 | try:
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| [1693] | 335 | #ss.set_selection(sel)
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| 336 | ssubon.set_selection(sel)
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| [1631] | 337 | except:
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| 338 | continue
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| [1693] | 339 | #ll.append(numpy.array(ss._getspectrum(0)))
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| 340 | ll.append(numpy.array(ssubon._getspectrum(0)))
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| [1631] | 341 | sel.reset()
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| [1693] | 342 | ssubon.set_selection()
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| [1631] | 343 | precal[keys[2*i+1]]=ll
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| [1693] | 344 | #del ss
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| [1631] | 345 | for j in range(len(ifnos)):
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| 346 | for k in range(len(polnos)):
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| 347 | sel.set_ifs(ifnos[j])
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| 348 | sel.set_polarizations(polnos[k])
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| 349 | try:
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| 350 | ress.set_selection(sel)
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| 351 | except:
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| 352 | continue
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| 353 | postcal.append(numpy.array(ress._getspectrum(0)))
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| 354 | sel.reset()
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| 355 | ress.set_selection()
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| 356 | del sel
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| 357 | # plot
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| 358 | print_log()
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| 359 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
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| 360 | print_log('WARN')
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| 361 | p=asaplotgui.asaplotgui()
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| 362 | #nr=min(6,len(ifnos)*len(polnos))
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| 363 | nr=len(ifnos)*len(polnos)
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| 364 | titles=[]
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| 365 | btics=[]
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| 366 | if nr<4:
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| 367 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
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| 368 | for i in range(2*nr):
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| 369 | b=False
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| 370 | if i >= 2*nr-2:
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| 371 | b=True
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| 372 | btics.append(b)
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| 373 | elif nr==4:
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| 374 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
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| 375 | for i in range(2*nr):
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| 376 | b=False
|
|---|
| 377 | if i >= 2*nr-4:
|
|---|
| 378 | b=True
|
|---|
| 379 | btics.append(b)
|
|---|
| 380 | elif nr<7:
|
|---|
| 381 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 382 | for i in range(2*nr):
|
|---|
| 383 | if i >= 2*nr-4:
|
|---|
| 384 | b=True
|
|---|
| 385 | btics.append(b)
|
|---|
| 386 | else:
|
|---|
| 387 | print_log()
|
|---|
| 388 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
|
|---|
| 389 | print_log('WARN')
|
|---|
| 390 | nr=6
|
|---|
| 391 | for i in range(2*nr):
|
|---|
| 392 | b=False
|
|---|
| 393 | if i >= 2*nr-4:
|
|---|
| 394 | b=True
|
|---|
| 395 | btics.append(b)
|
|---|
| 396 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 397 | for i in range(nr):
|
|---|
| 398 | p.subplot(2*i)
|
|---|
| 399 | p.color=0
|
|---|
| 400 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 401 | titles.append(title)
|
|---|
| 402 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 403 | ymin=1.0e100
|
|---|
| 404 | ymax=-1.0e100
|
|---|
| 405 | nchan=s.nchan()
|
|---|
| 406 | edge=int(nchan*0.01)
|
|---|
| 407 | for j in range(4):
|
|---|
| 408 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 409 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 410 | ymin=min(ymin,spmin)
|
|---|
| 411 | ymax=max(ymax,spmax)
|
|---|
| 412 | for j in range(4):
|
|---|
| 413 | if i==0:
|
|---|
| 414 | p.set_line(label=keys[j])
|
|---|
| 415 | else:
|
|---|
| 416 | p.legend()
|
|---|
| 417 | p.plot(precal[keys[j]][i])
|
|---|
| 418 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 419 | if not btics[2*i]:
|
|---|
| 420 | p.axes.set_xticks([])
|
|---|
| 421 | p.subplot(2*i+1)
|
|---|
| 422 | p.color=0
|
|---|
| 423 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 424 | titles.append(title)
|
|---|
| 425 | #p.set_axes('title',title)
|
|---|
| 426 | p.legend()
|
|---|
| 427 | ymin=postcal[i][edge:nchan-edge].min()
|
|---|
| 428 | ymax=postcal[i][edge:nchan-edge].max()
|
|---|
| 429 | p.plot(postcal[i])
|
|---|
| 430 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 431 | if not btics[2*i+1]:
|
|---|
| 432 | p.axes.set_xticks([])
|
|---|
| 433 | for i in range(2*nr):
|
|---|
| 434 | p.subplot(i)
|
|---|
| 435 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 436 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 437 | if x.upper() == 'N':
|
|---|
| 438 | p.unmap()
|
|---|
| 439 | del p
|
|---|
| 440 | return scabtab
|
|---|
| 441 | p.unmap()
|
|---|
| 442 | del p
|
|---|
| 443 | ###
|
|---|
| [1389] | 444 | ress._add_history("calps", varlist)
|
|---|
| 445 | print_log()
|
|---|
| 446 | return ress
|
|---|
| 447 |
|
|---|
| [1798] | 448 | @print_log_dec
|
|---|
| [1631] | 449 | def calnod(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
|---|
| [1389] | 450 | """
|
|---|
| 451 | Do full (but a pair of scans at time) processing of GBT Nod data
|
|---|
| 452 | calibration.
|
|---|
| 453 | Adopted from GBTIDL's getnod
|
|---|
| 454 | Parameters:
|
|---|
| 455 | scantab: scantable
|
|---|
| 456 | scannos: a pair of scan numbers, or the first scan number of the pair
|
|---|
| 457 | smooth: box car smoothing order
|
|---|
| 458 | tsysval: optional user specified Tsys value
|
|---|
| 459 | tauval: optional user specified tau value (not implemented yet)
|
|---|
| 460 | tcalval: optional user specified Tcal value
|
|---|
| 461 | """
|
|---|
| 462 | varlist = vars()
|
|---|
| 463 | from asap._asap import stmath
|
|---|
| [1693] | 464 | from asap._asap import srctype
|
|---|
| [1389] | 465 | stm = stmath()
|
|---|
| 466 | stm._setinsitu(False)
|
|---|
| 467 |
|
|---|
| 468 | # check for the appropriate data
|
|---|
| [1693] | 469 | ## s = scantab.get_scan('*_nod*')
|
|---|
| 470 | ## if s is None:
|
|---|
| 471 | ## msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 472 | ## if rcParams['verbose']:
|
|---|
| 473 | ## #print msg
|
|---|
| 474 | ## asaplog.push(msg)
|
|---|
| 475 | ## print_log('ERROR')
|
|---|
| 476 | ## return
|
|---|
| 477 | ## else:
|
|---|
| 478 | ## raise TypeError(msg)
|
|---|
| 479 | s = scantab.copy()
|
|---|
| 480 | sel = selector()
|
|---|
| 481 | sel.set_types( srctype.nod )
|
|---|
| 482 | try:
|
|---|
| 483 | s.set_selection( sel )
|
|---|
| 484 | except Exception, e:
|
|---|
| [1389] | 485 | msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 486 | if rcParams['verbose']:
|
|---|
| [1612] | 487 | #print msg
|
|---|
| [1614] | 488 | asaplog.push(msg)
|
|---|
| 489 | print_log('ERROR')
|
|---|
| [1389] | 490 | return
|
|---|
| 491 | else:
|
|---|
| 492 | raise TypeError(msg)
|
|---|
| [1693] | 493 | sel.reset()
|
|---|
| 494 | del sel
|
|---|
| 495 | del s
|
|---|
| [1389] | 496 |
|
|---|
| 497 | # need check correspondance of each beam with sig-ref ...
|
|---|
| 498 | # check for timestamps, scan numbers, subscan id (not available in
|
|---|
| 499 | # ASAP data format...). Assume 1st scan of the pair (beam 0 - sig
|
|---|
| 500 | # and beam 1 - ref...)
|
|---|
| 501 | # First scan number of paired scans or list of pairs of
|
|---|
| 502 | # scan numbers (has to have even number of pairs.)
|
|---|
| 503 |
|
|---|
| 504 | #data splitting
|
|---|
| 505 | scan1no = scan2no = 0
|
|---|
| 506 |
|
|---|
| 507 | if len(scannos)==1:
|
|---|
| 508 | scan1no = scannos[0]
|
|---|
| 509 | scan2no = scannos[0]+1
|
|---|
| 510 | pairScans = [scan1no, scan2no]
|
|---|
| 511 | else:
|
|---|
| 512 | #if len(scannos)>2:
|
|---|
| 513 | # msg = "calnod can only process a pair of nod scans at time."
|
|---|
| 514 | # if rcParams['verbose']:
|
|---|
| 515 | # print msg
|
|---|
| 516 | # return
|
|---|
| 517 | # else:
|
|---|
| 518 | # raise TypeError(msg)
|
|---|
| 519 | #
|
|---|
| 520 | #if len(scannos)==2:
|
|---|
| 521 | # scan1no = scannos[0]
|
|---|
| 522 | # scan2no = scannos[1]
|
|---|
| 523 | pairScans = list(scannos)
|
|---|
| 524 |
|
|---|
| 525 | if tsysval>0.0:
|
|---|
| 526 | if tauval<=0.0:
|
|---|
| 527 | msg = "Need to supply a valid tau to use the supplied Tsys"
|
|---|
| 528 | if rcParams['verbose']:
|
|---|
| [1612] | 529 | #print msg
|
|---|
| [1614] | 530 | asaplog.push(msg)
|
|---|
| 531 | print_log('ERROR')
|
|---|
| [1389] | 532 | return
|
|---|
| 533 | else:
|
|---|
| 534 | raise TypeError(msg)
|
|---|
| 535 | else:
|
|---|
| 536 | scantab.recalc_azel()
|
|---|
| 537 | resspec = scantable(stm._donod(scantab, pairScans, smooth, tsysval,tauval,tcalval))
|
|---|
| [1631] | 538 | ###
|
|---|
| 539 | if verify:
|
|---|
| 540 | # get data
|
|---|
| 541 | import numpy
|
|---|
| 542 | precal={}
|
|---|
| 543 | postcal=[]
|
|---|
| [1693] | 544 | keys=['','_calon']
|
|---|
| 545 | types=[srctype.nod,srctype.nodcal]
|
|---|
| [1631] | 546 | ifnos=list(scantab.getifnos())
|
|---|
| 547 | polnos=list(scantab.getpolnos())
|
|---|
| 548 | sel=selector()
|
|---|
| [1693] | 549 | ss = scantab.copy()
|
|---|
| [1631] | 550 | for i in range(2):
|
|---|
| [1693] | 551 | #ss=scantab.get_scan('*'+keys[i])
|
|---|
| [1631] | 552 | ll=[]
|
|---|
| 553 | ll2=[]
|
|---|
| 554 | for j in range(len(ifnos)):
|
|---|
| 555 | for k in range(len(polnos)):
|
|---|
| 556 | sel.set_ifs(ifnos[j])
|
|---|
| 557 | sel.set_polarizations(polnos[k])
|
|---|
| 558 | sel.set_scans(pairScans[0])
|
|---|
| [1693] | 559 | sel.set_types(types[i])
|
|---|
| [1631] | 560 | try:
|
|---|
| 561 | ss.set_selection(sel)
|
|---|
| 562 | except:
|
|---|
| 563 | continue
|
|---|
| 564 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 565 | sel.reset()
|
|---|
| 566 | ss.set_selection()
|
|---|
| 567 | sel.set_ifs(ifnos[j])
|
|---|
| 568 | sel.set_polarizations(polnos[k])
|
|---|
| 569 | sel.set_scans(pairScans[1])
|
|---|
| [1693] | 570 | sel.set_types(types[i])
|
|---|
| [1631] | 571 | try:
|
|---|
| 572 | ss.set_selection(sel)
|
|---|
| 573 | except:
|
|---|
| 574 | ll.pop()
|
|---|
| 575 | continue
|
|---|
| 576 | ll2.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 577 | sel.reset()
|
|---|
| 578 | ss.set_selection()
|
|---|
| [1693] | 579 | key='%s%s' %(pairScans[0],keys[i])
|
|---|
| [1631] | 580 | precal[key]=ll
|
|---|
| [1693] | 581 | key='%s%s' %(pairScans[1],keys[i])
|
|---|
| [1631] | 582 | precal[key]=ll2
|
|---|
| [1693] | 583 | #del ss
|
|---|
| [1631] | 584 | keys=precal.keys()
|
|---|
| 585 | for j in range(len(ifnos)):
|
|---|
| 586 | for k in range(len(polnos)):
|
|---|
| 587 | sel.set_ifs(ifnos[j])
|
|---|
| 588 | sel.set_polarizations(polnos[k])
|
|---|
| 589 | sel.set_scans(pairScans[0])
|
|---|
| 590 | try:
|
|---|
| 591 | resspec.set_selection(sel)
|
|---|
| 592 | except:
|
|---|
| 593 | continue
|
|---|
| 594 | postcal.append(numpy.array(resspec._getspectrum(0)))
|
|---|
| 595 | sel.reset()
|
|---|
| 596 | resspec.set_selection()
|
|---|
| 597 | del sel
|
|---|
| 598 | # plot
|
|---|
| 599 | print_log()
|
|---|
| 600 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
|---|
| 601 | print_log('WARN')
|
|---|
| 602 | p=asaplotgui.asaplotgui()
|
|---|
| 603 | #nr=min(6,len(ifnos)*len(polnos))
|
|---|
| 604 | nr=len(ifnos)*len(polnos)
|
|---|
| 605 | titles=[]
|
|---|
| 606 | btics=[]
|
|---|
| 607 | if nr<4:
|
|---|
| 608 | p.set_panels(rows=nr,cols=2,nplots=2*nr,ganged=False)
|
|---|
| 609 | for i in range(2*nr):
|
|---|
| 610 | b=False
|
|---|
| 611 | if i >= 2*nr-2:
|
|---|
| 612 | b=True
|
|---|
| 613 | btics.append(b)
|
|---|
| 614 | elif nr==4:
|
|---|
| 615 | p.set_panels(rows=2,cols=4,nplots=8,ganged=False)
|
|---|
| 616 | for i in range(2*nr):
|
|---|
| 617 | b=False
|
|---|
| 618 | if i >= 2*nr-4:
|
|---|
| 619 | b=True
|
|---|
| 620 | btics.append(b)
|
|---|
| 621 | elif nr<7:
|
|---|
| 622 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 623 | for i in range(2*nr):
|
|---|
| 624 | if i >= 2*nr-4:
|
|---|
| 625 | b=True
|
|---|
| 626 | btics.append(b)
|
|---|
| 627 | else:
|
|---|
| 628 | print_log()
|
|---|
| 629 | asaplog.push('Only first 6 [if,pol] pairs are plotted.')
|
|---|
| 630 | print_log('WARN')
|
|---|
| 631 | nr=6
|
|---|
| 632 | for i in range(2*nr):
|
|---|
| 633 | b=False
|
|---|
| 634 | if i >= 2*nr-4:
|
|---|
| 635 | b=True
|
|---|
| 636 | btics.append(b)
|
|---|
| 637 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False)
|
|---|
| 638 | for i in range(nr):
|
|---|
| 639 | p.subplot(2*i)
|
|---|
| 640 | p.color=0
|
|---|
| 641 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 642 | titles.append(title)
|
|---|
| 643 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 644 | ymin=1.0e100
|
|---|
| 645 | ymax=-1.0e100
|
|---|
| 646 | nchan=scantab.nchan()
|
|---|
| 647 | edge=int(nchan*0.01)
|
|---|
| 648 | for j in range(4):
|
|---|
| 649 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 650 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 651 | ymin=min(ymin,spmin)
|
|---|
| 652 | ymax=max(ymax,spmax)
|
|---|
| 653 | for j in range(4):
|
|---|
| 654 | if i==0:
|
|---|
| 655 | p.set_line(label=keys[j])
|
|---|
| 656 | else:
|
|---|
| 657 | p.legend()
|
|---|
| 658 | p.plot(precal[keys[j]][i])
|
|---|
| 659 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 660 | if not btics[2*i]:
|
|---|
| 661 | p.axes.set_xticks([])
|
|---|
| 662 | p.subplot(2*i+1)
|
|---|
| 663 | p.color=0
|
|---|
| 664 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 665 | titles.append(title)
|
|---|
| 666 | #p.set_axes('title',title)
|
|---|
| 667 | p.legend()
|
|---|
| 668 | ymin=postcal[i][edge:nchan-edge].min()
|
|---|
| 669 | ymax=postcal[i][edge:nchan-edge].max()
|
|---|
| 670 | p.plot(postcal[i])
|
|---|
| 671 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 672 | if not btics[2*i+1]:
|
|---|
| 673 | p.axes.set_xticks([])
|
|---|
| 674 | for i in range(2*nr):
|
|---|
| 675 | p.subplot(i)
|
|---|
| 676 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 677 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 678 | if x.upper() == 'N':
|
|---|
| 679 | p.unmap()
|
|---|
| 680 | del p
|
|---|
| 681 | return scabtab
|
|---|
| 682 | p.unmap()
|
|---|
| 683 | del p
|
|---|
| 684 | ###
|
|---|
| [1389] | 685 | resspec._add_history("calnod",varlist)
|
|---|
| 686 | print_log()
|
|---|
| 687 | return resspec
|
|---|
| 688 |
|
|---|
| [1798] | 689 | @print_log_dec
|
|---|
| [1631] | 690 | def calfs(scantab, scannos=[], smooth=1, tsysval=0.0, tauval=0.0, tcalval=0.0, verify=False):
|
|---|
| [1389] | 691 | """
|
|---|
| 692 | Calibrate GBT frequency switched data.
|
|---|
| 693 | Adopted from GBTIDL getfs.
|
|---|
| 694 | Currently calfs identify the scans as frequency switched data if they
|
|---|
| 695 | contain '_fs' in the source name. The data must contains 'CAL' signal
|
|---|
| 696 | on/off in each integration. To identify 'CAL' on state, the word, 'calon'
|
|---|
| 697 | need to be present in the source name field.
|
|---|
| 698 | (GBT MS data reading via scantable automatically append these
|
|---|
| 699 | id names to the source names)
|
|---|
| 700 |
|
|---|
| 701 | Parameters:
|
|---|
| 702 | scantab: scantable
|
|---|
| 703 | scannos: list of scan numbers
|
|---|
| 704 | smooth: optional box smoothing order for the reference
|
|---|
| 705 | (default is 1 = no smoothing)
|
|---|
| 706 | tsysval: optional user specified Tsys (default is 0.0,
|
|---|
| 707 | use Tsys in the data)
|
|---|
| 708 | tauval: optional user specified Tau
|
|---|
| 709 | """
|
|---|
| 710 | varlist = vars()
|
|---|
| 711 | from asap._asap import stmath
|
|---|
| [1693] | 712 | from asap._asap import srctype
|
|---|
| [1389] | 713 | stm = stmath()
|
|---|
| 714 | stm._setinsitu(False)
|
|---|
| 715 |
|
|---|
| 716 | # check = scantab.get_scan('*_fs*')
|
|---|
| 717 | # if check is None:
|
|---|
| 718 | # msg = "The input data appear to contain no Nod observing mode data."
|
|---|
| 719 | # if rcParams['verbose']:
|
|---|
| 720 | # print msg
|
|---|
| 721 | # return
|
|---|
| 722 | # else:
|
|---|
| 723 | # raise TypeError(msg)
|
|---|
| 724 | s = scantab.get_scan(scannos)
|
|---|
| 725 | del scantab
|
|---|
| 726 |
|
|---|
| 727 | resspec = scantable(stm._dofs(s, scannos, smooth, tsysval,tauval,tcalval))
|
|---|
| [1631] | 728 | ###
|
|---|
| 729 | if verify:
|
|---|
| 730 | # get data
|
|---|
| 731 | ssub = s.get_scan(scannos)
|
|---|
| [1693] | 732 | #ssubon = ssub.get_scan('*calon')
|
|---|
| 733 | #ssuboff = ssub.get_scan('*[^calon]')
|
|---|
| 734 | sel = selector()
|
|---|
| 735 | sel.set_types( [srctype.foncal,srctype.foffcal] )
|
|---|
| 736 | ssub.set_selection( sel )
|
|---|
| 737 | ssubon = ssub.copy()
|
|---|
| 738 | ssub.set_selection()
|
|---|
| 739 | sel.reset()
|
|---|
| 740 | sel.set_types( [srctype.fson,srctype.fsoff] )
|
|---|
| 741 | ssub.set_selection( sel )
|
|---|
| 742 | ssuboff = ssub.copy()
|
|---|
| 743 | ssub.set_selection()
|
|---|
| 744 | sel.reset()
|
|---|
| [1631] | 745 | import numpy
|
|---|
| 746 | precal={}
|
|---|
| 747 | postcal=[]
|
|---|
| 748 | keys=['fs','fs_calon','fsr','fsr_calon']
|
|---|
| [1693] | 749 | types=[srctype.fson,srctype.foncal,srctype.fsoff,srctype.foffcal]
|
|---|
| [1631] | 750 | ifnos=list(ssub.getifnos())
|
|---|
| 751 | polnos=list(ssub.getpolnos())
|
|---|
| 752 | for i in range(2):
|
|---|
| [1693] | 753 | #ss=ssuboff.get_scan('*'+keys[2*i])
|
|---|
| [1631] | 754 | ll=[]
|
|---|
| 755 | for j in range(len(ifnos)):
|
|---|
| 756 | for k in range(len(polnos)):
|
|---|
| 757 | sel.set_ifs(ifnos[j])
|
|---|
| 758 | sel.set_polarizations(polnos[k])
|
|---|
| [1693] | 759 | sel.set_types(types[2*i])
|
|---|
| [1631] | 760 | try:
|
|---|
| [1693] | 761 | #ss.set_selection(sel)
|
|---|
| 762 | ssuboff.set_selection(sel)
|
|---|
| [1631] | 763 | except:
|
|---|
| 764 | continue
|
|---|
| 765 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 766 | sel.reset()
|
|---|
| [1693] | 767 | #ss.set_selection()
|
|---|
| 768 | ssuboff.set_selection()
|
|---|
| [1631] | 769 | precal[keys[2*i]]=ll
|
|---|
| [1693] | 770 | #del ss
|
|---|
| 771 | #ss=ssubon.get_scan('*'+keys[2*i+1])
|
|---|
| [1631] | 772 | ll=[]
|
|---|
| 773 | for j in range(len(ifnos)):
|
|---|
| 774 | for k in range(len(polnos)):
|
|---|
| 775 | sel.set_ifs(ifnos[j])
|
|---|
| 776 | sel.set_polarizations(polnos[k])
|
|---|
| [1693] | 777 | sel.set_types(types[2*i+1])
|
|---|
| [1631] | 778 | try:
|
|---|
| [1693] | 779 | #ss.set_selection(sel)
|
|---|
| 780 | ssubon.set_selection(sel)
|
|---|
| [1631] | 781 | except:
|
|---|
| 782 | continue
|
|---|
| 783 | ll.append(numpy.array(ss._getspectrum(0)))
|
|---|
| 784 | sel.reset()
|
|---|
| [1693] | 785 | #ss.set_selection()
|
|---|
| 786 | ssubon.set_selection()
|
|---|
| [1631] | 787 | precal[keys[2*i+1]]=ll
|
|---|
| [1693] | 788 | #del ss
|
|---|
| 789 | #sig=resspec.get_scan('*_fs')
|
|---|
| 790 | #ref=resspec.get_scan('*_fsr')
|
|---|
| 791 | sel.set_types( srctype.fson )
|
|---|
| 792 | resspec.set_selection( sel )
|
|---|
| 793 | sig=resspec.copy()
|
|---|
| 794 | resspec.set_selection()
|
|---|
| 795 | sel.reset()
|
|---|
| 796 | sel.set_type( srctype.fsoff )
|
|---|
| 797 | resspec.set_selection( sel )
|
|---|
| 798 | ref=resspec.copy()
|
|---|
| 799 | resspec.set_selection()
|
|---|
| 800 | sel.reset()
|
|---|
| [1631] | 801 | for k in range(len(polnos)):
|
|---|
| 802 | for j in range(len(ifnos)):
|
|---|
| 803 | sel.set_ifs(ifnos[j])
|
|---|
| 804 | sel.set_polarizations(polnos[k])
|
|---|
| 805 | try:
|
|---|
| 806 | sig.set_selection(sel)
|
|---|
| 807 | postcal.append(numpy.array(sig._getspectrum(0)))
|
|---|
| 808 | except:
|
|---|
| 809 | ref.set_selection(sel)
|
|---|
| 810 | postcal.append(numpy.array(ref._getspectrum(0)))
|
|---|
| 811 | sel.reset()
|
|---|
| 812 | resspec.set_selection()
|
|---|
| 813 | del sel
|
|---|
| 814 | # plot
|
|---|
| 815 | print_log()
|
|---|
| 816 | asaplog.push('Plot only first spectrum for each [if,pol] pairs to verify calibration.')
|
|---|
| 817 | print_log('WARN')
|
|---|
| 818 | p=asaplotgui.asaplotgui()
|
|---|
| 819 | #nr=min(6,len(ifnos)*len(polnos))
|
|---|
| 820 | nr=len(ifnos)/2*len(polnos)
|
|---|
| 821 | titles=[]
|
|---|
| 822 | btics=[]
|
|---|
| 823 | if nr>3:
|
|---|
| 824 | print_log()
|
|---|
| 825 | asaplog.push('Only first 3 [if,pol] pairs are plotted.')
|
|---|
| 826 | print_log('WARN')
|
|---|
| 827 | nr=3
|
|---|
| 828 | p.set_panels(rows=nr,cols=3,nplots=3*nr,ganged=False)
|
|---|
| 829 | for i in range(3*nr):
|
|---|
| 830 | b=False
|
|---|
| 831 | if i >= 3*nr-3:
|
|---|
| 832 | b=True
|
|---|
| 833 | btics.append(b)
|
|---|
| 834 | for i in range(nr):
|
|---|
| 835 | p.subplot(3*i)
|
|---|
| 836 | p.color=0
|
|---|
| 837 | title='raw data IF%s,%s POL%s' % (ifnos[2*int(i/len(polnos))],ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
|---|
| 838 | titles.append(title)
|
|---|
| 839 | #p.set_axes('title',title,fontsize=40)
|
|---|
| 840 | ymin=1.0e100
|
|---|
| 841 | ymax=-1.0e100
|
|---|
| 842 | nchan=s.nchan()
|
|---|
| 843 | edge=int(nchan*0.01)
|
|---|
| 844 | for j in range(4):
|
|---|
| 845 | spmin=min(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 846 | spmax=max(precal[keys[j]][i][edge:nchan-edge])
|
|---|
| 847 | ymin=min(ymin,spmin)
|
|---|
| 848 | ymax=max(ymax,spmax)
|
|---|
| 849 | for j in range(4):
|
|---|
| 850 | if i==0:
|
|---|
| 851 | p.set_line(label=keys[j])
|
|---|
| 852 | else:
|
|---|
| 853 | p.legend()
|
|---|
| 854 | p.plot(precal[keys[j]][i])
|
|---|
| 855 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 856 | if not btics[3*i]:
|
|---|
| 857 | p.axes.set_xticks([])
|
|---|
| 858 | p.subplot(3*i+1)
|
|---|
| 859 | p.color=0
|
|---|
| 860 | title='sig data IF%s POL%s' % (ifnos[2*int(i/len(polnos))],polnos[i%len(polnos)])
|
|---|
| 861 | titles.append(title)
|
|---|
| 862 | #p.set_axes('title',title)
|
|---|
| 863 | p.legend()
|
|---|
| 864 | ymin=postcal[2*i][edge:nchan-edge].min()
|
|---|
| 865 | ymax=postcal[2*i][edge:nchan-edge].max()
|
|---|
| 866 | p.plot(postcal[2*i])
|
|---|
| 867 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 868 | if not btics[3*i+1]:
|
|---|
| 869 | p.axes.set_xticks([])
|
|---|
| 870 | p.subplot(3*i+2)
|
|---|
| 871 | p.color=0
|
|---|
| 872 | title='ref data IF%s POL%s' % (ifnos[2*int(i/len(polnos))+1],polnos[i%len(polnos)])
|
|---|
| 873 | titles.append(title)
|
|---|
| 874 | #p.set_axes('title',title)
|
|---|
| 875 | p.legend()
|
|---|
| 876 | ymin=postcal[2*i+1][edge:nchan-edge].min()
|
|---|
| 877 | ymax=postcal[2*i+1][edge:nchan-edge].max()
|
|---|
| 878 | p.plot(postcal[2*i+1])
|
|---|
| 879 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax))
|
|---|
| 880 | if not btics[3*i+2]:
|
|---|
| 881 | p.axes.set_xticks([])
|
|---|
| 882 | for i in range(3*nr):
|
|---|
| 883 | p.subplot(i)
|
|---|
| 884 | p.set_axes('title',titles[i],fontsize='medium')
|
|---|
| 885 | x=raw_input('Accept calibration ([y]/n): ' )
|
|---|
| 886 | if x.upper() == 'N':
|
|---|
| 887 | p.unmap()
|
|---|
| 888 | del p
|
|---|
| 889 | return scabtab
|
|---|
| 890 | p.unmap()
|
|---|
| 891 | del p
|
|---|
| 892 | ###
|
|---|
| [1389] | 893 | resspec._add_history("calfs",varlist)
|
|---|
| 894 | print_log()
|
|---|
| 895 | return resspec
|
|---|
| 896 |
|
|---|
| [1798] | 897 | @print_log_dec
|
|---|
| [918] | 898 | def merge(*args):
|
|---|
| [945] | 899 | """
|
|---|
| [1362] | 900 | Merge a list of scanatables, or comma-sperated scantables into one
|
|---|
| 901 | scnatble.
|
|---|
| 902 | Parameters:
|
|---|
| 903 | A list [scan1, scan2] or scan1, scan2.
|
|---|
| 904 | Example:
|
|---|
| 905 | myscans = [scan1, scan2]
|
|---|
| [1757] | 906 | allscans = merge(myscans)
|
|---|
| 907 | # or equivalent
|
|---|
| 908 | sameallscans = merge(scan1, scan2)
|
|---|
| [945] | 909 | """
|
|---|
| [918] | 910 | varlist = vars()
|
|---|
| 911 | if isinstance(args[0],list):
|
|---|
| 912 | lst = tuple(args[0])
|
|---|
| 913 | elif isinstance(args[0],tuple):
|
|---|
| 914 | lst = args[0]
|
|---|
| 915 | else:
|
|---|
| 916 | lst = tuple(args)
|
|---|
| 917 | varlist["args"] = "%d scantables" % len(lst)
|
|---|
| 918 | # need special formatting her for history...
|
|---|
| 919 | from asap._asap import stmath
|
|---|
| 920 | stm = stmath()
|
|---|
| 921 | for s in lst:
|
|---|
| 922 | if not isinstance(s,scantable):
|
|---|
| 923 | msg = "Please give a list of scantables"
|
|---|
| 924 | if rcParams['verbose']:
|
|---|
| [1612] | 925 | #print msg
|
|---|
| [1614] | 926 | asaplog.push(msg)
|
|---|
| 927 | print_log('ERROR')
|
|---|
| [918] | 928 | return
|
|---|
| 929 | else:
|
|---|
| 930 | raise TypeError(msg)
|
|---|
| 931 | s = scantable(stm._merge(lst))
|
|---|
| 932 | s._add_history("merge", varlist)
|
|---|
| 933 | print_log()
|
|---|
| 934 | return s
|
|---|
| [1074] | 935 |
|
|---|
| [1633] | 936 | def calibrate( scantab, scannos=[], calmode='none', verify=None ):
|
|---|
| 937 | """
|
|---|
| 938 | Calibrate data.
|
|---|
| [1631] | 939 |
|
|---|
| [1633] | 940 | Parameters:
|
|---|
| 941 | scantab: scantable
|
|---|
| 942 | scannos: list of scan number
|
|---|
| 943 | calmode: calibration mode
|
|---|
| 944 | verify: verify calibration
|
|---|
| 945 | """
|
|---|
| 946 | antname = scantab.get_antennaname()
|
|---|
| 947 | if ( calmode == 'nod' ):
|
|---|
| 948 | asaplog.push( 'Calibrating nod data.' )
|
|---|
| 949 | print_log()
|
|---|
| 950 | scal = calnod( scantab, scannos=scannos, verify=verify )
|
|---|
| 951 | elif ( calmode == 'quotient' ):
|
|---|
| 952 | asaplog.push( 'Calibrating using quotient.' )
|
|---|
| 953 | print_log()
|
|---|
| 954 | scal = scantab.auto_quotient( verify=verify )
|
|---|
| 955 | elif ( calmode == 'ps' ):
|
|---|
| 956 | asaplog.push( 'Calibrating %s position-switched data.' % antname )
|
|---|
| 957 | print_log()
|
|---|
| [1673] | 958 | if ( antname.find( 'APEX' ) != -1 ):
|
|---|
| 959 | scal = apexcal( scantab, scannos, calmode, verify )
|
|---|
| 960 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ):
|
|---|
| [1633] | 961 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 962 | else:
|
|---|
| 963 | scal = calps( scantab, scannos=scannos, verify=verify )
|
|---|
| 964 | elif ( calmode == 'fs' or calmode == 'fsotf' ):
|
|---|
| 965 | asaplog.push( 'Calibrating %s frequency-switched data.' % antname )
|
|---|
| 966 | print_log()
|
|---|
| [1673] | 967 | if ( antname.find( 'APEX' ) != -1 ):
|
|---|
| 968 | scal = apexcal( scantab, scannos, calmode, verify )
|
|---|
| 969 | elif ( antname.find( 'ALMA' ) != -1 or antname.find( 'OSF' ) != -1 ):
|
|---|
| [1633] | 970 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 971 | else:
|
|---|
| 972 | scal = calfs( scantab, scannos=scannos, verify=verify )
|
|---|
| 973 | elif ( calmode == 'otf' ):
|
|---|
| 974 | asaplog.push( 'Calibrating %s On-The-Fly data.' % antname )
|
|---|
| 975 | print_log()
|
|---|
| 976 | scal = almacal( scantab, scannos, calmode, verify )
|
|---|
| 977 | else:
|
|---|
| 978 | asaplog.push( 'No calibration.' )
|
|---|
| 979 | scal = scantab.copy()
|
|---|
| 980 |
|
|---|
| 981 | return scal
|
|---|
| 982 |
|
|---|
| [1673] | 983 | def apexcal( scantab, scannos=[], calmode='none', verify=False ):
|
|---|
| [1633] | 984 | """
|
|---|
| [1673] | 985 | Calibrate APEX data
|
|---|
| [1633] | 986 |
|
|---|
| 987 | Parameters:
|
|---|
| 988 | scantab: scantable
|
|---|
| 989 | scannos: list of scan number
|
|---|
| 990 | calmode: calibration mode
|
|---|
| [1650] | 991 |
|
|---|
| [1633] | 992 | verify: verify calibration
|
|---|
| 993 | """
|
|---|
| 994 | from asap._asap import stmath
|
|---|
| 995 | stm = stmath()
|
|---|
| 996 | antname = scantab.get_antennaname()
|
|---|
| 997 | ssub = scantab.get_scan( scannos )
|
|---|
| 998 | scal = scantable( stm.cwcal( ssub, calmode, antname ) )
|
|---|
| 999 | return scal
|
|---|
| [1650] | 1000 |
|
|---|
| [1673] | 1001 | def almacal( scantab, scannos=[], calmode='none', verify=False ):
|
|---|
| 1002 | """
|
|---|
| 1003 | Calibrate ALMA data
|
|---|
| 1004 |
|
|---|
| 1005 | Parameters:
|
|---|
| 1006 | scantab: scantable
|
|---|
| 1007 | scannos: list of scan number
|
|---|
| 1008 | calmode: calibration mode
|
|---|
| 1009 |
|
|---|
| 1010 | verify: verify calibration
|
|---|
| 1011 | """
|
|---|
| 1012 | from asap._asap import stmath
|
|---|
| 1013 | stm = stmath()
|
|---|
| 1014 | ssub = scantab.get_scan( scannos )
|
|---|
| 1015 | scal = scantable( stm.almacal( ssub, calmode ) )
|
|---|
| 1016 | return scal
|
|---|
| 1017 |
|
|---|
| [1650] | 1018 | def splitant(filename, outprefix='',overwrite=False):
|
|---|
| 1019 | """
|
|---|
| 1020 | Split Measurement set by antenna name, save data as a scantables,
|
|---|
| 1021 | and return a list of filename.
|
|---|
| 1022 | Notice this method can only be available from CASA.
|
|---|
| 1023 | Prameter
|
|---|
| 1024 | filename: the name of Measurement set to be read.
|
|---|
| 1025 | outprefix: the prefix of output scantable name.
|
|---|
| 1026 | the names of output scantable will be
|
|---|
| 1027 | outprefix.antenna1, outprefix.antenna2, ....
|
|---|
| [1651] | 1028 | If not specified, outprefix = filename is assumed.
|
|---|
| [1650] | 1029 | overwrite If the file should be overwritten if it exists.
|
|---|
| 1030 | The default False is to return with warning
|
|---|
| 1031 | without writing the output. USE WITH CARE.
|
|---|
| 1032 |
|
|---|
| 1033 | """
|
|---|
| 1034 | # Import the table toolkit from CASA
|
|---|
| 1035 | try:
|
|---|
| [1686] | 1036 | import casac
|
|---|
| [1650] | 1037 | except ImportError:
|
|---|
| [1686] | 1038 | if rcParams['verbose']:
|
|---|
| 1039 | #print "failed to load casa"
|
|---|
| 1040 | print_log()
|
|---|
| 1041 | asaplog.push("failed to load casa")
|
|---|
| 1042 | print_log('ERROR')
|
|---|
| 1043 | else: raise
|
|---|
| 1044 | return False
|
|---|
| [1650] | 1045 | try:
|
|---|
| [1686] | 1046 | tbtool = casac.homefinder.find_home_by_name('tableHome')
|
|---|
| 1047 | tb = tbtool.create()
|
|---|
| 1048 | tb2 = tbtool.create()
|
|---|
| [1650] | 1049 | except:
|
|---|
| [1686] | 1050 | if rcParams['verbose']:
|
|---|
| 1051 | #print "failed to load a table tool:\n", e
|
|---|
| 1052 | print_log()
|
|---|
| 1053 | asaplog.push("failed to load table tool")
|
|---|
| 1054 | print_log('ERROR')
|
|---|
| 1055 | else: raise
|
|---|
| 1056 | return False
|
|---|
| [1650] | 1057 | # Check the input filename
|
|---|
| 1058 | if isinstance(filename, str):
|
|---|
| 1059 | import os.path
|
|---|
| 1060 | filename = os.path.expandvars(filename)
|
|---|
| 1061 | filename = os.path.expanduser(filename)
|
|---|
| 1062 | if not os.path.exists(filename):
|
|---|
| 1063 | s = "File '%s' not found." % (filename)
|
|---|
| 1064 | if rcParams['verbose']:
|
|---|
| 1065 | print_log()
|
|---|
| 1066 | asaplog.push(s)
|
|---|
| 1067 | print_log('ERROR')
|
|---|
| 1068 | return
|
|---|
| 1069 | raise IOError(s)
|
|---|
| 1070 | # check if input file is MS
|
|---|
| 1071 | if not os.path.isdir(filename) \
|
|---|
| 1072 | or not os.path.exists(filename+'/ANTENNA') \
|
|---|
| 1073 | or not os.path.exists(filename+'/table.f1'):
|
|---|
| 1074 | s = "File '%s' is not a Measurement set." % (filename)
|
|---|
| 1075 | if rcParams['verbose']:
|
|---|
| 1076 | print_log()
|
|---|
| 1077 | asaplog.push(s)
|
|---|
| 1078 | print_log('ERROR')
|
|---|
| 1079 | return
|
|---|
| 1080 | raise IOError(s)
|
|---|
| 1081 | else:
|
|---|
| 1082 | s = "The filename should be string. "
|
|---|
| 1083 | if rcParams['verbose']:
|
|---|
| 1084 | print_log()
|
|---|
| 1085 | asaplog.push(s)
|
|---|
| 1086 | print_log('ERROR')
|
|---|
| 1087 | return
|
|---|
| 1088 | raise TypeError(s)
|
|---|
| 1089 | # Check out put file name
|
|---|
| 1090 | outname=''
|
|---|
| 1091 | if len(outprefix) > 0: prefix=outprefix+'.'
|
|---|
| [1651] | 1092 | else:
|
|---|
| [1686] | 1093 | prefix=filename.rstrip('/')
|
|---|
| [1650] | 1094 | # Now do the actual splitting.
|
|---|
| 1095 | outfiles=[]
|
|---|
| 1096 | tb.open(tablename=filename+'/ANTENNA',nomodify=True)
|
|---|
| 1097 | nant=tb.nrows()
|
|---|
| 1098 | antnames=tb.getcol('NAME',0,nant,1)
|
|---|
| 1099 | antpos=tb.getcol('POSITION',0,nant,1).transpose()
|
|---|
| 1100 | tb.close()
|
|---|
| 1101 | tb.open(tablename=filename,nomodify=True)
|
|---|
| 1102 | ant1=tb.getcol('ANTENNA1',0,-1,1)
|
|---|
| [1686] | 1103 | tb.close()
|
|---|
| [1650] | 1104 | for antid in set(ant1):
|
|---|
| [1686] | 1105 | scan=scantable(filename,average=False,getpt=True,antenna=int(antid))
|
|---|
| [1650] | 1106 | outname=prefix+antnames[antid]+'.asap'
|
|---|
| 1107 | scan.save(outname,format='ASAP',overwrite=overwrite)
|
|---|
| [1686] | 1108 | del scan
|
|---|
| [1650] | 1109 | outfiles.append(outname)
|
|---|
| 1110 | del tb, tb2
|
|---|
| 1111 | return outfiles
|
|---|
| [1679] | 1112 |
|
|---|
| 1113 | def _array2dOp( scan, value, mode="ADD", tsys=False ):
|
|---|
| 1114 | """
|
|---|
| 1115 | This function is workaround on the basic operation of scantable
|
|---|
| 1116 | with 2 dimensional float list.
|
|---|
| 1117 |
|
|---|
| 1118 | scan: scantable operand
|
|---|
| 1119 | value: float list operand
|
|---|
| 1120 | mode: operation mode (ADD, SUB, MUL, DIV)
|
|---|
| 1121 | tsys: if True, operate tsys as well
|
|---|
| 1122 | """
|
|---|
| 1123 | nrow = scan.nrow()
|
|---|
| 1124 | s = None
|
|---|
| [1682] | 1125 | if len( value ) == 1:
|
|---|
| 1126 | from asap._asap import stmath
|
|---|
| 1127 | stm = stmath()
|
|---|
| 1128 | s = scantable( stm._arrayop( scan.copy(), value[0], mode, tsys ) )
|
|---|
| 1129 | del stm
|
|---|
| 1130 | elif len( value ) != nrow:
|
|---|
| 1131 | asaplog.push( 'len(value) must be 1 or conform to scan.nrow()' )
|
|---|
| [1679] | 1132 | print_log( 'ERROR' )
|
|---|
| 1133 | else:
|
|---|
| 1134 | from asap._asap import stmath
|
|---|
| 1135 | stm = stmath()
|
|---|
| 1136 | # insitu must be True
|
|---|
| 1137 | stm._setinsitu( True )
|
|---|
| 1138 | s = scan.copy()
|
|---|
| 1139 | sel = selector()
|
|---|
| 1140 | for irow in range( nrow ):
|
|---|
| 1141 | sel.set_rows( irow )
|
|---|
| 1142 | s.set_selection( sel )
|
|---|
| 1143 | if len( value[irow] ) == 1:
|
|---|
| 1144 | stm._unaryop( s, value[irow][0], mode, tsys )
|
|---|
| 1145 | else:
|
|---|
| 1146 | stm._arrayop( s, value[irow], mode, tsys, 'channel' )
|
|---|
| 1147 | s.set_selection()
|
|---|
| 1148 | sel.reset()
|
|---|
| 1149 | del sel
|
|---|
| 1150 | del stm
|
|---|
| 1151 | return s
|
|---|
| 1152 |
|
|---|
| 1153 |
|
|---|
| 1154 |
|
|---|
