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