[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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[1782] | 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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[1782] | 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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[1782] | 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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[1782] | 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 |
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| 377 | if i >= 2*nr-4: |
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| 378 | b=True |
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| 379 | btics.append(b) |
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| 380 | elif nr<7: |
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| 381 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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| 382 | for i in range(2*nr): |
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| 383 | if i >= 2*nr-4: |
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| 384 | b=True |
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| 385 | btics.append(b) |
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| 386 | else: |
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| 387 | print_log() |
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| 388 | asaplog.push('Only first 6 [if,pol] pairs are plotted.') |
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| 389 | print_log('WARN') |
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| 390 | nr=6 |
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| 391 | for i in range(2*nr): |
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| 392 | b=False |
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| 393 | if i >= 2*nr-4: |
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| 394 | b=True |
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| 395 | btics.append(b) |
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| 396 | p.set_panels(rows=3,cols=4,nplots=2*nr,ganged=False) |
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| 397 | for i in range(nr): |
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| 398 | p.subplot(2*i) |
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| 399 | p.color=0 |
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| 400 | title='raw data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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| 401 | titles.append(title) |
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| 402 | #p.set_axes('title',title,fontsize=40) |
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| 403 | ymin=1.0e100 |
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| 404 | ymax=-1.0e100 |
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| 405 | nchan=s.nchan() |
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| 406 | edge=int(nchan*0.01) |
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| 407 | for j in range(4): |
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| 408 | spmin=min(precal[keys[j]][i][edge:nchan-edge]) |
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| 409 | spmax=max(precal[keys[j]][i][edge:nchan-edge]) |
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| 410 | ymin=min(ymin,spmin) |
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| 411 | ymax=max(ymax,spmax) |
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| 412 | for j in range(4): |
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| 413 | if i==0: |
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| 414 | p.set_line(label=keys[j]) |
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| 415 | else: |
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| 416 | p.legend() |
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| 417 | p.plot(precal[keys[j]][i]) |
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| 418 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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| 419 | if not btics[2*i]: |
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| 420 | p.axes.set_xticks([]) |
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| 421 | p.subplot(2*i+1) |
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| 422 | p.color=0 |
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| 423 | title='cal data IF%s POL%s' % (ifnos[int(i/len(polnos))],polnos[i%len(polnos)]) |
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| 424 | titles.append(title) |
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| 425 | #p.set_axes('title',title) |
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| 426 | p.legend() |
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| 427 | ymin=postcal[i][edge:nchan-edge].min() |
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| 428 | ymax=postcal[i][edge:nchan-edge].max() |
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| 429 | p.plot(postcal[i]) |
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| 430 | p.axes.set_ylim(ymin-0.1*abs(ymin),ymax+0.1*abs(ymax)) |
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| 431 | if not btics[2*i+1]: |
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| 432 | p.axes.set_xticks([]) |
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| 433 | for i in range(2*nr): |
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| 434 | p.subplot(i) |
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| 435 | p.set_axes('title',titles[i],fontsize='medium') |
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| 436 | x=raw_input('Accept calibration ([y]/n): ' ) |
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| 437 | if x.upper() == 'N': |
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| 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 | |
---|
[1782] | 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 | |
---|
[1782] | 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 | |
---|
[1782] | 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 | |
---|