[1846] | 1 | """This module defines the scantable class.""" |
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| 2 | |
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[1697] | 3 | import os |
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[1691] | 4 | try: |
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| 5 | from functools import wraps as wraps_dec |
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| 6 | except ImportError: |
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| 7 | from asap.compatibility import wraps as wraps_dec |
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| 8 | |
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[1824] | 9 | from asap.env import is_casapy |
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[876] | 10 | from asap._asap import Scantable |
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[1843] | 11 | from asap._asap import filler |
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[1824] | 12 | from asap.parameters import rcParams |
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[1862] | 13 | from asap.logging import asaplog, asaplog_post_dec |
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[1824] | 14 | from asap.selector import selector |
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| 15 | from asap.linecatalog import linecatalog |
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[1600] | 16 | from asap.coordinate import coordinate |
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[1859] | 17 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page |
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[1907] | 18 | from asap.asapfitter import fitter |
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[102] | 19 | |
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[1689] | 20 | |
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| 21 | def preserve_selection(func): |
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[1691] | 22 | @wraps_dec(func) |
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[1689] | 23 | def wrap(obj, *args, **kw): |
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| 24 | basesel = obj.get_selection() |
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[1857] | 25 | try: |
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| 26 | val = func(obj, *args, **kw) |
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| 27 | finally: |
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| 28 | obj.set_selection(basesel) |
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[1689] | 29 | return val |
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| 30 | return wrap |
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| 31 | |
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[1846] | 32 | def is_scantable(filename): |
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| 33 | """Is the given file a scantable? |
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[1689] | 34 | |
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[1846] | 35 | Parameters: |
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| 36 | |
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| 37 | filename: the name of the file/directory to test |
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| 38 | |
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| 39 | """ |
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[1883] | 40 | if ( os.path.isdir(filename) |
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| 41 | and os.path.exists(filename+'/table.info') |
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| 42 | and os.path.exists(filename+'/table.dat') ): |
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| 43 | f=open(filename+'/table.info') |
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| 44 | l=f.readline() |
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| 45 | f.close() |
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| 46 | #if ( l.find('Scantable') != -1 ): |
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| 47 | if ( l.find('Measurement Set') == -1 ): |
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| 48 | return True |
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| 49 | else: |
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| 50 | return False |
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| 51 | else: |
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| 52 | return False |
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| 53 | ## return (os.path.isdir(filename) |
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| 54 | ## and not os.path.exists(filename+'/table.f1') |
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| 55 | ## and os.path.exists(filename+'/table.info')) |
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[1697] | 56 | |
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[1883] | 57 | def is_ms(filename): |
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| 58 | """Is the given file a MeasurementSet? |
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[1697] | 59 | |
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[1883] | 60 | Parameters: |
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| 61 | |
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| 62 | filename: the name of the file/directory to test |
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| 63 | |
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| 64 | """ |
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| 65 | if ( os.path.isdir(filename) |
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| 66 | and os.path.exists(filename+'/table.info') |
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| 67 | and os.path.exists(filename+'/table.dat') ): |
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| 68 | f=open(filename+'/table.info') |
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| 69 | l=f.readline() |
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| 70 | f.close() |
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| 71 | if ( l.find('Measurement Set') != -1 ): |
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| 72 | return True |
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| 73 | else: |
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| 74 | return False |
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| 75 | else: |
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| 76 | return False |
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| 77 | |
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[876] | 78 | class scantable(Scantable): |
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[1846] | 79 | """\ |
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| 80 | The ASAP container for scans (single-dish data). |
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[102] | 81 | """ |
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[1819] | 82 | |
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[1862] | 83 | @asaplog_post_dec |
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[1916] | 84 | #def __init__(self, filename, average=None, unit=None, getpt=None, |
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| 85 | # antenna=None, parallactify=None): |
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| 86 | def __init__(self, filename, average=None, unit=None, parallactify=None, **args): |
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[1846] | 87 | """\ |
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[102] | 88 | Create a scantable from a saved one or make a reference |
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[1846] | 89 | |
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[102] | 90 | Parameters: |
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[1846] | 91 | |
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| 92 | filename: the name of an asap table on disk |
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| 93 | or |
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| 94 | the name of a rpfits/sdfits/ms file |
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| 95 | (integrations within scans are auto averaged |
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| 96 | and the whole file is read) or |
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| 97 | [advanced] a reference to an existing scantable |
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| 98 | |
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| 99 | average: average all integrations withinb a scan on read. |
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| 100 | The default (True) is taken from .asaprc. |
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| 101 | |
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[484] | 102 | unit: brightness unit; must be consistent with K or Jy. |
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[1846] | 103 | Over-rides the default selected by the filler |
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| 104 | (input rpfits/sdfits/ms) or replaces the value |
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| 105 | in existing scantables |
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| 106 | |
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| 107 | getpt: for MeasurementSet input data only: |
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| 108 | If True, all pointing data are filled. |
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| 109 | The deafult is False, which makes time to load |
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| 110 | the MS data faster in some cases. |
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| 111 | |
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[1920] | 112 | antenna: for MeasurementSet input data only: |
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| 113 | Antenna selection. integer (id) or string (name or id). |
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[1846] | 114 | |
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| 115 | parallactify: Indicate that the data had been parallatified. Default |
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| 116 | is taken from rc file. |
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| 117 | |
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[710] | 118 | """ |
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[976] | 119 | if average is None: |
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[710] | 120 | average = rcParams['scantable.autoaverage'] |
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[1916] | 121 | #if getpt is None: |
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| 122 | # getpt = True |
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| 123 | #if antenna is not None: |
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| 124 | # asaplog.push("Antenna selection currently unsupported." |
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| 125 | # "Using ''") |
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| 126 | # asaplog.post('WARN') |
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| 127 | #if antenna is None: |
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| 128 | # antenna = '' |
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| 129 | #elif type(antenna) == int: |
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| 130 | # antenna = '%s' % antenna |
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| 131 | #elif type(antenna) == list: |
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| 132 | # tmpstr = '' |
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| 133 | # for i in range( len(antenna) ): |
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| 134 | # if type(antenna[i]) == int: |
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| 135 | # tmpstr = tmpstr + ('%s,'%(antenna[i])) |
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| 136 | # elif type(antenna[i]) == str: |
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| 137 | # tmpstr=tmpstr+antenna[i]+',' |
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| 138 | # else: |
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| 139 | # raise TypeError('Bad antenna selection.') |
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| 140 | # antenna = tmpstr.rstrip(',') |
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[1593] | 141 | parallactify = parallactify or rcParams['scantable.parallactify'] |
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[1259] | 142 | varlist = vars() |
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[876] | 143 | from asap._asap import stmath |
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[1819] | 144 | self._math = stmath( rcParams['insitu'] ) |
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[876] | 145 | if isinstance(filename, Scantable): |
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| 146 | Scantable.__init__(self, filename) |
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[181] | 147 | else: |
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[1697] | 148 | if isinstance(filename, str): |
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[976] | 149 | filename = os.path.expandvars(filename) |
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| 150 | filename = os.path.expanduser(filename) |
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| 151 | if not os.path.exists(filename): |
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| 152 | s = "File '%s' not found." % (filename) |
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| 153 | raise IOError(s) |
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[1697] | 154 | if is_scantable(filename): |
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| 155 | ondisk = rcParams['scantable.storage'] == 'disk' |
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| 156 | Scantable.__init__(self, filename, ondisk) |
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| 157 | if unit is not None: |
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| 158 | self.set_fluxunit(unit) |
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[1819] | 159 | # do not reset to the default freqframe |
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| 160 | #self.set_freqframe(rcParams['scantable.freqframe']) |
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[1883] | 161 | #elif os.path.isdir(filename) \ |
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| 162 | # and not os.path.exists(filename+'/table.f1'): |
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| 163 | elif is_ms(filename): |
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[1916] | 164 | # Measurement Set |
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| 165 | opts={'ms': {}} |
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| 166 | mskeys=['getpt','antenna'] |
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| 167 | for key in mskeys: |
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| 168 | if key in args.keys(): |
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| 169 | opts['ms'][key] = args[key] |
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| 170 | #self._fill([filename], unit, average, getpt, antenna) |
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| 171 | self._fill([filename], unit, average, opts) |
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[1893] | 172 | elif os.path.isfile(filename): |
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[1916] | 173 | #self._fill([filename], unit, average, getpt, antenna) |
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| 174 | self._fill([filename], unit, average) |
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[1883] | 175 | else: |
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[1819] | 176 | msg = "The given file '%s'is not a valid " \ |
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| 177 | "asap table." % (filename) |
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[1859] | 178 | raise IOError(msg) |
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[1118] | 179 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
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[976] | 180 | and isinstance(filename[-1], str): |
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[1916] | 181 | #self._fill(filename, unit, average, getpt, antenna) |
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| 182 | self._fill(filename, unit, average) |
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[1586] | 183 | self.parallactify(parallactify) |
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[1259] | 184 | self._add_history("scantable", varlist) |
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[102] | 185 | |
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[1862] | 186 | @asaplog_post_dec |
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[876] | 187 | def save(self, name=None, format=None, overwrite=False): |
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[1846] | 188 | """\ |
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[1280] | 189 | Store the scantable on disk. This can be an asap (aips++) Table, |
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| 190 | SDFITS or MS2 format. |
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[1846] | 191 | |
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[116] | 192 | Parameters: |
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[1846] | 193 | |
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[1093] | 194 | name: the name of the outputfile. For format "ASCII" |
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| 195 | this is the root file name (data in 'name'.txt |
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[497] | 196 | and header in 'name'_header.txt) |
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[1855] | 197 | |
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[116] | 198 | format: an optional file format. Default is ASAP. |
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[1855] | 199 | Allowed are: |
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| 200 | |
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| 201 | * 'ASAP' (save as ASAP [aips++] Table), |
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| 202 | * 'SDFITS' (save as SDFITS file) |
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| 203 | * 'ASCII' (saves as ascii text file) |
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| 204 | * 'MS2' (saves as an casacore MeasurementSet V2) |
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| 205 | * 'FITS' (save as image FITS - not readable by class) |
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| 206 | * 'CLASS' (save as FITS readable by CLASS) |
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| 207 | |
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[411] | 208 | overwrite: If the file should be overwritten if it exists. |
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[256] | 209 | The default False is to return with warning |
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[411] | 210 | without writing the output. USE WITH CARE. |
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[1855] | 211 | |
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[1846] | 212 | Example:: |
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| 213 | |
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[116] | 214 | scan.save('myscan.asap') |
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[1118] | 215 | scan.save('myscan.sdfits', 'SDFITS') |
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[1846] | 216 | |
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[116] | 217 | """ |
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[411] | 218 | from os import path |
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[1593] | 219 | format = format or rcParams['scantable.save'] |
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[256] | 220 | suffix = '.'+format.lower() |
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[1118] | 221 | if name is None or name == "": |
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[256] | 222 | name = 'scantable'+suffix |
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[718] | 223 | msg = "No filename given. Using default name %s..." % name |
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| 224 | asaplog.push(msg) |
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[411] | 225 | name = path.expandvars(name) |
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[256] | 226 | if path.isfile(name) or path.isdir(name): |
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| 227 | if not overwrite: |
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[718] | 228 | msg = "File %s exists." % name |
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[1859] | 229 | raise IOError(msg) |
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[451] | 230 | format2 = format.upper() |
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| 231 | if format2 == 'ASAP': |
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[116] | 232 | self._save(name) |
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| 233 | else: |
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[989] | 234 | from asap._asap import stwriter as stw |
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[1118] | 235 | writer = stw(format2) |
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| 236 | writer.write(self, name) |
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[116] | 237 | return |
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| 238 | |
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[102] | 239 | def copy(self): |
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[1846] | 240 | """Return a copy of this scantable. |
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| 241 | |
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| 242 | *Note*: |
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| 243 | |
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[1348] | 244 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
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[1846] | 245 | |
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| 246 | Example:: |
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| 247 | |
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[102] | 248 | copiedscan = scan.copy() |
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[1846] | 249 | |
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[102] | 250 | """ |
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[876] | 251 | sd = scantable(Scantable._copy(self)) |
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[113] | 252 | return sd |
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| 253 | |
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[1093] | 254 | def drop_scan(self, scanid=None): |
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[1846] | 255 | """\ |
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[1093] | 256 | Return a new scantable where the specified scan number(s) has(have) |
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| 257 | been dropped. |
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[1846] | 258 | |
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[1093] | 259 | Parameters: |
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[1846] | 260 | |
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[1093] | 261 | scanid: a (list of) scan number(s) |
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[1846] | 262 | |
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[1093] | 263 | """ |
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| 264 | from asap import _is_sequence_or_number as _is_valid |
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| 265 | from asap import _to_list |
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| 266 | from asap import unique |
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| 267 | if not _is_valid(scanid): |
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[1859] | 268 | raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) |
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| 269 | scanid = _to_list(scanid) |
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| 270 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
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| 271 | for sid in scanid: allscans.remove(sid) |
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| 272 | if len(allscans) == 0: |
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| 273 | raise ValueError("Can't remove all scans") |
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| 274 | sel = selector(scans=allscans) |
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| 275 | return self._select_copy(sel) |
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[1093] | 276 | |
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[1594] | 277 | def _select_copy(self, selection): |
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| 278 | orig = self.get_selection() |
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| 279 | self.set_selection(orig+selection) |
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| 280 | cp = self.copy() |
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| 281 | self.set_selection(orig) |
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| 282 | return cp |
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| 283 | |
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[102] | 284 | def get_scan(self, scanid=None): |
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[1855] | 285 | """\ |
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[102] | 286 | Return a specific scan (by scanno) or collection of scans (by |
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| 287 | source name) in a new scantable. |
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[1846] | 288 | |
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| 289 | *Note*: |
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| 290 | |
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[1348] | 291 | See scantable.drop_scan() for the inverse operation. |
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[1846] | 292 | |
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[102] | 293 | Parameters: |
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[1846] | 294 | |
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[513] | 295 | scanid: a (list of) scanno or a source name, unix-style |
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| 296 | patterns are accepted for source name matching, e.g. |
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| 297 | '*_R' gets all 'ref scans |
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[1846] | 298 | |
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| 299 | Example:: |
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| 300 | |
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[513] | 301 | # get all scans containing the source '323p459' |
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| 302 | newscan = scan.get_scan('323p459') |
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| 303 | # get all 'off' scans |
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| 304 | refscans = scan.get_scan('*_R') |
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| 305 | # get a susbset of scans by scanno (as listed in scan.summary()) |
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[1118] | 306 | newscan = scan.get_scan([0, 2, 7, 10]) |
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[1846] | 307 | |
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[102] | 308 | """ |
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| 309 | if scanid is None: |
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[1859] | 310 | raise RuntimeError( 'Please specify a scan no or name to ' |
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| 311 | 'retrieve from the scantable' ) |
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[102] | 312 | try: |
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[946] | 313 | bsel = self.get_selection() |
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| 314 | sel = selector() |
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[102] | 315 | if type(scanid) is str: |
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[946] | 316 | sel.set_name(scanid) |
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[1594] | 317 | return self._select_copy(sel) |
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[102] | 318 | elif type(scanid) is int: |
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[946] | 319 | sel.set_scans([scanid]) |
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[1594] | 320 | return self._select_copy(sel) |
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[381] | 321 | elif type(scanid) is list: |
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[946] | 322 | sel.set_scans(scanid) |
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[1594] | 323 | return self._select_copy(sel) |
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[381] | 324 | else: |
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[718] | 325 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
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[1859] | 326 | raise TypeError(msg) |
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[102] | 327 | except RuntimeError: |
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[1859] | 328 | raise |
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[102] | 329 | |
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| 330 | def __str__(self): |
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[1118] | 331 | return Scantable._summary(self, True) |
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[102] | 332 | |
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[976] | 333 | def summary(self, filename=None): |
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[1846] | 334 | """\ |
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[102] | 335 | Print a summary of the contents of this scantable. |
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[1846] | 336 | |
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[102] | 337 | Parameters: |
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[1846] | 338 | |
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[102] | 339 | filename: the name of a file to write the putput to |
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| 340 | Default - no file output |
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[1846] | 341 | |
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[102] | 342 | """ |
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[976] | 343 | info = Scantable._summary(self, True) |
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[102] | 344 | if filename is not None: |
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[256] | 345 | if filename is "": |
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| 346 | filename = 'scantable_summary.txt' |
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[415] | 347 | from os.path import expandvars, isdir |
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[411] | 348 | filename = expandvars(filename) |
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[415] | 349 | if not isdir(filename): |
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[413] | 350 | data = open(filename, 'w') |
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| 351 | data.write(info) |
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| 352 | data.close() |
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| 353 | else: |
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[718] | 354 | msg = "Illegal file name '%s'." % (filename) |
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[1859] | 355 | raise IOError(msg) |
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| 356 | return page(info) |
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[710] | 357 | |
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[1512] | 358 | def get_spectrum(self, rowno): |
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[1471] | 359 | """Return the spectrum for the current row in the scantable as a list. |
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[1846] | 360 | |
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[1471] | 361 | Parameters: |
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[1846] | 362 | |
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[1573] | 363 | rowno: the row number to retrieve the spectrum from |
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[1846] | 364 | |
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[1471] | 365 | """ |
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| 366 | return self._getspectrum(rowno) |
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[946] | 367 | |
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[1471] | 368 | def get_mask(self, rowno): |
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| 369 | """Return the mask for the current row in the scantable as a list. |
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[1846] | 370 | |
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[1471] | 371 | Parameters: |
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[1846] | 372 | |
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[1573] | 373 | rowno: the row number to retrieve the mask from |
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[1846] | 374 | |
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[1471] | 375 | """ |
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| 376 | return self._getmask(rowno) |
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| 377 | |
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| 378 | def set_spectrum(self, spec, rowno): |
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| 379 | """Return the spectrum for the current row in the scantable as a list. |
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[1846] | 380 | |
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[1471] | 381 | Parameters: |
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[1846] | 382 | |
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[1855] | 383 | spec: the new spectrum |
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[1846] | 384 | |
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[1855] | 385 | rowno: the row number to set the spectrum for |
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| 386 | |
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[1471] | 387 | """ |
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| 388 | assert(len(spec) == self.nchan()) |
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| 389 | return self._setspectrum(spec, rowno) |
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| 390 | |
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[1600] | 391 | def get_coordinate(self, rowno): |
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| 392 | """Return the (spectral) coordinate for a a given 'rowno'. |
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[1846] | 393 | |
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| 394 | *Note*: |
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| 395 | |
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[1600] | 396 | * This coordinate is only valid until a scantable method modifies |
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| 397 | the frequency axis. |
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| 398 | * This coordinate does contain the original frequency set-up |
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| 399 | NOT the new frame. The conversions however are done using the user |
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| 400 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
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| 401 | use scantable.freq_align first. Without it there is no closure, |
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[1846] | 402 | i.e.:: |
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[1600] | 403 | |
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[1846] | 404 | c = myscan.get_coordinate(0) |
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| 405 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
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| 406 | |
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[1600] | 407 | Parameters: |
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[1846] | 408 | |
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[1600] | 409 | rowno: the row number for the spectral coordinate |
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| 410 | |
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| 411 | """ |
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| 412 | return coordinate(Scantable.get_coordinate(self, rowno)) |
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| 413 | |
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[946] | 414 | def get_selection(self): |
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[1846] | 415 | """\ |
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[1005] | 416 | Get the selection object currently set on this scantable. |
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[1846] | 417 | |
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| 418 | Example:: |
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| 419 | |
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[1005] | 420 | sel = scan.get_selection() |
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| 421 | sel.set_ifs(0) # select IF 0 |
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| 422 | scan.set_selection(sel) # apply modified selection |
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[1846] | 423 | |
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[946] | 424 | """ |
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| 425 | return selector(self._getselection()) |
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| 426 | |
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[1576] | 427 | def set_selection(self, selection=None, **kw): |
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[1846] | 428 | """\ |
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[1005] | 429 | Select a subset of the data. All following operations on this scantable |
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| 430 | are only applied to thi selection. |
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[1846] | 431 | |
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[1005] | 432 | Parameters: |
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[1697] | 433 | |
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[1846] | 434 | selection: a selector object (default unset the selection), or |
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| 435 | any combination of "pols", "ifs", "beams", "scans", |
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| 436 | "cycles", "name", "query" |
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[1697] | 437 | |
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[1846] | 438 | Examples:: |
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[1697] | 439 | |
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[1005] | 440 | sel = selector() # create a selection object |
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[1118] | 441 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
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[1005] | 442 | scan.set_selection(sel) # set the selection |
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| 443 | scan.summary() # will only print summary of scanno 0 an 3 |
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| 444 | scan.set_selection() # unset the selection |
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[1697] | 445 | # or the equivalent |
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| 446 | scan.set_selection(scans=[0,3]) |
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| 447 | scan.summary() # will only print summary of scanno 0 an 3 |
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| 448 | scan.set_selection() # unset the selection |
---|
[1846] | 449 | |
---|
[946] | 450 | """ |
---|
[1576] | 451 | if selection is None: |
---|
| 452 | # reset |
---|
| 453 | if len(kw) == 0: |
---|
| 454 | selection = selector() |
---|
| 455 | else: |
---|
| 456 | # try keywords |
---|
| 457 | for k in kw: |
---|
| 458 | if k not in selector.fields: |
---|
| 459 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
| 460 | selection = selector(**kw) |
---|
[946] | 461 | self._setselection(selection) |
---|
| 462 | |
---|
[1819] | 463 | def get_row(self, row=0, insitu=None): |
---|
[1846] | 464 | """\ |
---|
[1819] | 465 | Select a row in the scantable. |
---|
| 466 | Return a scantable with single row. |
---|
[1846] | 467 | |
---|
[1819] | 468 | Parameters: |
---|
[1846] | 469 | |
---|
| 470 | row: row no of integration, default is 0. |
---|
| 471 | insitu: if False a new scantable is returned. Otherwise, the |
---|
| 472 | scaling is done in-situ. The default is taken from .asaprc |
---|
| 473 | (False) |
---|
| 474 | |
---|
[1819] | 475 | """ |
---|
| 476 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 477 | if not insitu: |
---|
| 478 | workscan = self.copy() |
---|
| 479 | else: |
---|
| 480 | workscan = self |
---|
| 481 | # Select a row |
---|
| 482 | sel=selector() |
---|
| 483 | sel.set_scans([workscan.getscan(row)]) |
---|
| 484 | sel.set_cycles([workscan.getcycle(row)]) |
---|
| 485 | sel.set_beams([workscan.getbeam(row)]) |
---|
| 486 | sel.set_ifs([workscan.getif(row)]) |
---|
| 487 | sel.set_polarisations([workscan.getpol(row)]) |
---|
| 488 | sel.set_name(workscan._getsourcename(row)) |
---|
| 489 | workscan.set_selection(sel) |
---|
| 490 | if not workscan.nrow() == 1: |
---|
| 491 | msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) |
---|
| 492 | raise RuntimeError(msg) |
---|
| 493 | del sel |
---|
| 494 | if insitu: |
---|
| 495 | self._assign(workscan) |
---|
| 496 | else: |
---|
| 497 | return workscan |
---|
| 498 | |
---|
[1862] | 499 | @asaplog_post_dec |
---|
[1907] | 500 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
---|
[1846] | 501 | """\ |
---|
[135] | 502 | Determine the specified statistic of the current beam/if/pol |
---|
[102] | 503 | Takes a 'mask' as an optional parameter to specify which |
---|
| 504 | channels should be excluded. |
---|
[1846] | 505 | |
---|
[102] | 506 | Parameters: |
---|
[1846] | 507 | |
---|
[1819] | 508 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
---|
| 509 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
---|
[1855] | 510 | |
---|
[135] | 511 | mask: an optional mask specifying where the statistic |
---|
[102] | 512 | should be determined. |
---|
[1855] | 513 | |
---|
[1819] | 514 | form: format string to print statistic values |
---|
[1846] | 515 | |
---|
[1907] | 516 | row: row number of spectrum to process. |
---|
| 517 | (default is None: for all rows) |
---|
[1846] | 518 | |
---|
[1907] | 519 | Example: |
---|
[113] | 520 | scan.set_unit('channel') |
---|
[1118] | 521 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 522 | scan.stats(stat='mean', mask=m) |
---|
[1846] | 523 | |
---|
[102] | 524 | """ |
---|
[1593] | 525 | mask = mask or [] |
---|
[876] | 526 | if not self._check_ifs(): |
---|
[1118] | 527 | raise ValueError("Cannot apply mask as the IFs have different " |
---|
| 528 | "number of channels. Please use setselection() " |
---|
| 529 | "to select individual IFs") |
---|
[1819] | 530 | rtnabc = False |
---|
| 531 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
| 532 | getchan = False |
---|
| 533 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
| 534 | chan = self._math._minmaxchan(self, mask, stat) |
---|
| 535 | getchan = True |
---|
| 536 | statvals = [] |
---|
[1907] | 537 | if not rtnabc: |
---|
| 538 | if row == None: |
---|
| 539 | statvals = self._math._stats(self, mask, stat) |
---|
| 540 | else: |
---|
| 541 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
[256] | 542 | |
---|
[1819] | 543 | #def cb(i): |
---|
| 544 | # return statvals[i] |
---|
[256] | 545 | |
---|
[1819] | 546 | #return self._row_callback(cb, stat) |
---|
[102] | 547 | |
---|
[1819] | 548 | label=stat |
---|
| 549 | #callback=cb |
---|
| 550 | out = "" |
---|
| 551 | #outvec = [] |
---|
| 552 | sep = '-'*50 |
---|
[1907] | 553 | |
---|
| 554 | if row == None: |
---|
| 555 | rows = xrange(self.nrow()) |
---|
| 556 | elif isinstance(row, int): |
---|
| 557 | rows = [ row ] |
---|
| 558 | |
---|
| 559 | for i in rows: |
---|
[1819] | 560 | refstr = '' |
---|
| 561 | statunit= '' |
---|
| 562 | if getchan: |
---|
| 563 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
| 564 | if rtnabc: |
---|
| 565 | statvals.append(qx['value']) |
---|
| 566 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
| 567 | statunit= '['+qx['unit']+']' |
---|
| 568 | else: |
---|
| 569 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
| 570 | |
---|
| 571 | tm = self._gettime(i) |
---|
| 572 | src = self._getsourcename(i) |
---|
| 573 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
| 574 | out += 'Time[%s]:\n' % (tm) |
---|
[1907] | 575 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 576 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 577 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[1819] | 578 | #outvec.append(callback(i)) |
---|
[1907] | 579 | if len(rows) > 1: |
---|
| 580 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
| 581 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
| 582 | else: |
---|
| 583 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
| 584 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
[1819] | 585 | out += sep+"\n" |
---|
| 586 | |
---|
[1859] | 587 | import os |
---|
| 588 | if os.environ.has_key( 'USER' ): |
---|
| 589 | usr = os.environ['USER'] |
---|
| 590 | else: |
---|
| 591 | import commands |
---|
| 592 | usr = commands.getoutput( 'whoami' ) |
---|
| 593 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
| 594 | f = open(tmpfile,'w') |
---|
| 595 | print >> f, sep |
---|
| 596 | print >> f, ' %s %s' % (label, statunit) |
---|
| 597 | print >> f, sep |
---|
| 598 | print >> f, out |
---|
| 599 | f.close() |
---|
| 600 | f = open(tmpfile,'r') |
---|
| 601 | x = f.readlines() |
---|
| 602 | f.close() |
---|
| 603 | asaplog.push(''.join(x), False) |
---|
| 604 | |
---|
[1819] | 605 | return statvals |
---|
| 606 | |
---|
| 607 | def chan2data(self, rowno=0, chan=0): |
---|
[1846] | 608 | """\ |
---|
[1819] | 609 | Returns channel/frequency/velocity and spectral value |
---|
| 610 | at an arbitrary row and channel in the scantable. |
---|
[1846] | 611 | |
---|
[1819] | 612 | Parameters: |
---|
[1846] | 613 | |
---|
[1819] | 614 | rowno: a row number in the scantable. Default is the |
---|
| 615 | first row, i.e. rowno=0 |
---|
[1855] | 616 | |
---|
[1819] | 617 | chan: a channel in the scantable. Default is the first |
---|
| 618 | channel, i.e. pos=0 |
---|
[1846] | 619 | |
---|
[1819] | 620 | """ |
---|
| 621 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
| 622 | qx = {'unit': self.get_unit(), |
---|
| 623 | 'value': self._getabcissa(rowno)[chan]} |
---|
| 624 | qy = {'unit': self.get_fluxunit(), |
---|
| 625 | 'value': self._getspectrum(rowno)[chan]} |
---|
| 626 | return qx, qy |
---|
| 627 | |
---|
[1118] | 628 | def stddev(self, mask=None): |
---|
[1846] | 629 | """\ |
---|
[135] | 630 | Determine the standard deviation of the current beam/if/pol |
---|
| 631 | Takes a 'mask' as an optional parameter to specify which |
---|
| 632 | channels should be excluded. |
---|
[1846] | 633 | |
---|
[135] | 634 | Parameters: |
---|
[1846] | 635 | |
---|
[135] | 636 | mask: an optional mask specifying where the standard |
---|
| 637 | deviation should be determined. |
---|
| 638 | |
---|
[1846] | 639 | Example:: |
---|
| 640 | |
---|
[135] | 641 | scan.set_unit('channel') |
---|
[1118] | 642 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 643 | scan.stddev(mask=m) |
---|
[1846] | 644 | |
---|
[135] | 645 | """ |
---|
[1118] | 646 | return self.stats(stat='stddev', mask=mask); |
---|
[135] | 647 | |
---|
[1003] | 648 | |
---|
[1259] | 649 | def get_column_names(self): |
---|
[1846] | 650 | """\ |
---|
[1003] | 651 | Return a list of column names, which can be used for selection. |
---|
| 652 | """ |
---|
[1259] | 653 | return list(Scantable.get_column_names(self)) |
---|
[1003] | 654 | |
---|
[1730] | 655 | def get_tsys(self, row=-1): |
---|
[1846] | 656 | """\ |
---|
[113] | 657 | Return the System temperatures. |
---|
[1846] | 658 | |
---|
| 659 | Parameters: |
---|
| 660 | |
---|
| 661 | row: the rowno to get the information for. (default all rows) |
---|
| 662 | |
---|
[113] | 663 | Returns: |
---|
[1846] | 664 | |
---|
[876] | 665 | a list of Tsys values for the current selection |
---|
[1846] | 666 | |
---|
[113] | 667 | """ |
---|
[1730] | 668 | if row > -1: |
---|
| 669 | return self._get_column(self._gettsys, row) |
---|
[876] | 670 | return self._row_callback(self._gettsys, "Tsys") |
---|
[256] | 671 | |
---|
[1730] | 672 | |
---|
| 673 | def get_weather(self, row=-1): |
---|
[1846] | 674 | """\ |
---|
| 675 | Return the weather informations. |
---|
| 676 | |
---|
| 677 | Parameters: |
---|
| 678 | |
---|
| 679 | row: the rowno to get the information for. (default all rows) |
---|
| 680 | |
---|
| 681 | Returns: |
---|
| 682 | |
---|
| 683 | a dict or list of of dicts of values for the current selection |
---|
| 684 | |
---|
| 685 | """ |
---|
| 686 | |
---|
[1730] | 687 | values = self._get_column(self._get_weather, row) |
---|
| 688 | if row > -1: |
---|
| 689 | return {'temperature': values[0], |
---|
| 690 | 'pressure': values[1], 'humidity' : values[2], |
---|
| 691 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
| 692 | } |
---|
| 693 | else: |
---|
| 694 | out = [] |
---|
| 695 | for r in values: |
---|
| 696 | |
---|
| 697 | out.append({'temperature': r[0], |
---|
| 698 | 'pressure': r[1], 'humidity' : r[2], |
---|
| 699 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
| 700 | }) |
---|
| 701 | return out |
---|
| 702 | |
---|
[876] | 703 | def _row_callback(self, callback, label): |
---|
| 704 | out = "" |
---|
[1118] | 705 | outvec = [] |
---|
[1590] | 706 | sep = '-'*50 |
---|
[876] | 707 | for i in range(self.nrow()): |
---|
| 708 | tm = self._gettime(i) |
---|
| 709 | src = self._getsourcename(i) |
---|
[1590] | 710 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
[876] | 711 | out += 'Time[%s]:\n' % (tm) |
---|
[1590] | 712 | if self.nbeam(-1) > 1: |
---|
| 713 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 714 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 715 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[876] | 716 | outvec.append(callback(i)) |
---|
| 717 | out += '= %3.3f\n' % (outvec[i]) |
---|
[1590] | 718 | out += sep+'\n' |
---|
[1859] | 719 | |
---|
| 720 | asaplog.push(sep) |
---|
| 721 | asaplog.push(" %s" % (label)) |
---|
| 722 | asaplog.push(sep) |
---|
| 723 | asaplog.push(out) |
---|
[1861] | 724 | asaplog.post() |
---|
[1175] | 725 | return outvec |
---|
[256] | 726 | |
---|
[1070] | 727 | def _get_column(self, callback, row=-1): |
---|
| 728 | """ |
---|
| 729 | """ |
---|
| 730 | if row == -1: |
---|
| 731 | return [callback(i) for i in range(self.nrow())] |
---|
| 732 | else: |
---|
[1819] | 733 | if 0 <= row < self.nrow(): |
---|
[1070] | 734 | return callback(row) |
---|
[256] | 735 | |
---|
[1070] | 736 | |
---|
[1348] | 737 | def get_time(self, row=-1, asdatetime=False): |
---|
[1846] | 738 | """\ |
---|
[113] | 739 | Get a list of time stamps for the observations. |
---|
[1348] | 740 | Return a datetime object for each integration time stamp in the scantable. |
---|
[1846] | 741 | |
---|
[113] | 742 | Parameters: |
---|
[1846] | 743 | |
---|
[1348] | 744 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 745 | |
---|
[1348] | 746 | asdatetime: return values as datetime objects rather than strings |
---|
[1846] | 747 | |
---|
[113] | 748 | """ |
---|
[1175] | 749 | from time import strptime |
---|
| 750 | from datetime import datetime |
---|
[1392] | 751 | times = self._get_column(self._gettime, row) |
---|
[1348] | 752 | if not asdatetime: |
---|
[1392] | 753 | return times |
---|
[1175] | 754 | format = "%Y/%m/%d/%H:%M:%S" |
---|
| 755 | if isinstance(times, list): |
---|
| 756 | return [datetime(*strptime(i, format)[:6]) for i in times] |
---|
| 757 | else: |
---|
| 758 | return datetime(*strptime(times, format)[:6]) |
---|
[102] | 759 | |
---|
[1348] | 760 | |
---|
| 761 | def get_inttime(self, row=-1): |
---|
[1846] | 762 | """\ |
---|
[1348] | 763 | Get a list of integration times for the observations. |
---|
| 764 | Return a time in seconds for each integration in the scantable. |
---|
[1846] | 765 | |
---|
[1348] | 766 | Parameters: |
---|
[1846] | 767 | |
---|
[1348] | 768 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 769 | |
---|
[1348] | 770 | """ |
---|
[1573] | 771 | return self._get_column(self._getinttime, row) |
---|
[1348] | 772 | |
---|
[1573] | 773 | |
---|
[714] | 774 | def get_sourcename(self, row=-1): |
---|
[1846] | 775 | """\ |
---|
[794] | 776 | Get a list source names for the observations. |
---|
[714] | 777 | Return a string for each integration in the scantable. |
---|
| 778 | Parameters: |
---|
[1846] | 779 | |
---|
[1348] | 780 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 781 | |
---|
[714] | 782 | """ |
---|
[1070] | 783 | return self._get_column(self._getsourcename, row) |
---|
[714] | 784 | |
---|
[794] | 785 | def get_elevation(self, row=-1): |
---|
[1846] | 786 | """\ |
---|
[794] | 787 | Get a list of elevations for the observations. |
---|
| 788 | Return a float for each integration in the scantable. |
---|
[1846] | 789 | |
---|
[794] | 790 | Parameters: |
---|
[1846] | 791 | |
---|
[1348] | 792 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 793 | |
---|
[794] | 794 | """ |
---|
[1070] | 795 | return self._get_column(self._getelevation, row) |
---|
[794] | 796 | |
---|
| 797 | def get_azimuth(self, row=-1): |
---|
[1846] | 798 | """\ |
---|
[794] | 799 | Get a list of azimuths for the observations. |
---|
| 800 | Return a float for each integration in the scantable. |
---|
[1846] | 801 | |
---|
[794] | 802 | Parameters: |
---|
[1348] | 803 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 804 | |
---|
[794] | 805 | """ |
---|
[1070] | 806 | return self._get_column(self._getazimuth, row) |
---|
[794] | 807 | |
---|
| 808 | def get_parangle(self, row=-1): |
---|
[1846] | 809 | """\ |
---|
[794] | 810 | Get a list of parallactic angles for the observations. |
---|
| 811 | Return a float for each integration in the scantable. |
---|
[1846] | 812 | |
---|
[794] | 813 | Parameters: |
---|
[1846] | 814 | |
---|
[1348] | 815 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 816 | |
---|
[794] | 817 | """ |
---|
[1070] | 818 | return self._get_column(self._getparangle, row) |
---|
[794] | 819 | |
---|
[1070] | 820 | def get_direction(self, row=-1): |
---|
| 821 | """ |
---|
| 822 | Get a list of Positions on the sky (direction) for the observations. |
---|
[1594] | 823 | Return a string for each integration in the scantable. |
---|
[1855] | 824 | |
---|
[1070] | 825 | Parameters: |
---|
[1855] | 826 | |
---|
[1070] | 827 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 828 | |
---|
[1070] | 829 | """ |
---|
| 830 | return self._get_column(self._getdirection, row) |
---|
| 831 | |
---|
[1391] | 832 | def get_directionval(self, row=-1): |
---|
[1846] | 833 | """\ |
---|
[1391] | 834 | Get a list of Positions on the sky (direction) for the observations. |
---|
| 835 | Return a float for each integration in the scantable. |
---|
[1846] | 836 | |
---|
[1391] | 837 | Parameters: |
---|
[1846] | 838 | |
---|
[1391] | 839 | row: row no of integration. Default -1 return all rows |
---|
[1846] | 840 | |
---|
[1391] | 841 | """ |
---|
| 842 | return self._get_column(self._getdirectionvec, row) |
---|
| 843 | |
---|
[1862] | 844 | @asaplog_post_dec |
---|
[102] | 845 | def set_unit(self, unit='channel'): |
---|
[1846] | 846 | """\ |
---|
[102] | 847 | Set the unit for all following operations on this scantable |
---|
[1846] | 848 | |
---|
[102] | 849 | Parameters: |
---|
[1846] | 850 | |
---|
| 851 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
| 852 | 'km/s', 'channel' or equivalent '' |
---|
| 853 | |
---|
[102] | 854 | """ |
---|
[484] | 855 | varlist = vars() |
---|
[1118] | 856 | if unit in ['', 'pixel', 'channel']: |
---|
[113] | 857 | unit = '' |
---|
| 858 | inf = list(self._getcoordinfo()) |
---|
| 859 | inf[0] = unit |
---|
| 860 | self._setcoordinfo(inf) |
---|
[1118] | 861 | self._add_history("set_unit", varlist) |
---|
[113] | 862 | |
---|
[1862] | 863 | @asaplog_post_dec |
---|
[484] | 864 | def set_instrument(self, instr): |
---|
[1846] | 865 | """\ |
---|
[1348] | 866 | Set the instrument for subsequent processing. |
---|
[1846] | 867 | |
---|
[358] | 868 | Parameters: |
---|
[1846] | 869 | |
---|
[710] | 870 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
[407] | 871 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
[1846] | 872 | |
---|
[358] | 873 | """ |
---|
| 874 | self._setInstrument(instr) |
---|
[1118] | 875 | self._add_history("set_instument", vars()) |
---|
[358] | 876 | |
---|
[1862] | 877 | @asaplog_post_dec |
---|
[1190] | 878 | def set_feedtype(self, feedtype): |
---|
[1846] | 879 | """\ |
---|
[1190] | 880 | Overwrite the feed type, which might not be set correctly. |
---|
[1846] | 881 | |
---|
[1190] | 882 | Parameters: |
---|
[1846] | 883 | |
---|
[1190] | 884 | feedtype: 'linear' or 'circular' |
---|
[1846] | 885 | |
---|
[1190] | 886 | """ |
---|
| 887 | self._setfeedtype(feedtype) |
---|
| 888 | self._add_history("set_feedtype", vars()) |
---|
| 889 | |
---|
[1862] | 890 | @asaplog_post_dec |
---|
[276] | 891 | def set_doppler(self, doppler='RADIO'): |
---|
[1846] | 892 | """\ |
---|
[276] | 893 | Set the doppler for all following operations on this scantable. |
---|
[1846] | 894 | |
---|
[276] | 895 | Parameters: |
---|
[1846] | 896 | |
---|
[276] | 897 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
[1846] | 898 | |
---|
[276] | 899 | """ |
---|
[484] | 900 | varlist = vars() |
---|
[276] | 901 | inf = list(self._getcoordinfo()) |
---|
| 902 | inf[2] = doppler |
---|
| 903 | self._setcoordinfo(inf) |
---|
[1118] | 904 | self._add_history("set_doppler", vars()) |
---|
[710] | 905 | |
---|
[1862] | 906 | @asaplog_post_dec |
---|
[226] | 907 | def set_freqframe(self, frame=None): |
---|
[1846] | 908 | """\ |
---|
[113] | 909 | Set the frame type of the Spectral Axis. |
---|
[1846] | 910 | |
---|
[113] | 911 | Parameters: |
---|
[1846] | 912 | |
---|
[591] | 913 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
[1819] | 914 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
[1118] | 915 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
[1846] | 916 | |
---|
| 917 | Example:: |
---|
| 918 | |
---|
[113] | 919 | scan.set_freqframe('BARY') |
---|
[1846] | 920 | |
---|
[113] | 921 | """ |
---|
[1593] | 922 | frame = frame or rcParams['scantable.freqframe'] |
---|
[484] | 923 | varlist = vars() |
---|
[1819] | 924 | # "REST" is not implemented in casacore |
---|
| 925 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
| 926 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
| 927 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
[1118] | 928 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
[591] | 929 | |
---|
[989] | 930 | if frame in valid: |
---|
[113] | 931 | inf = list(self._getcoordinfo()) |
---|
| 932 | inf[1] = frame |
---|
| 933 | self._setcoordinfo(inf) |
---|
[1118] | 934 | self._add_history("set_freqframe", varlist) |
---|
[102] | 935 | else: |
---|
[1118] | 936 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
[1859] | 937 | raise TypeError(msg) |
---|
[710] | 938 | |
---|
[1862] | 939 | @asaplog_post_dec |
---|
[989] | 940 | def set_dirframe(self, frame=""): |
---|
[1846] | 941 | """\ |
---|
[989] | 942 | Set the frame type of the Direction on the sky. |
---|
[1846] | 943 | |
---|
[989] | 944 | Parameters: |
---|
[1846] | 945 | |
---|
[989] | 946 | frame: an optional frame type, default ''. Valid frames are: |
---|
| 947 | 'J2000', 'B1950', 'GALACTIC' |
---|
[1846] | 948 | |
---|
| 949 | Example: |
---|
| 950 | |
---|
[989] | 951 | scan.set_dirframe('GALACTIC') |
---|
[1846] | 952 | |
---|
[989] | 953 | """ |
---|
| 954 | varlist = vars() |
---|
[1859] | 955 | Scantable.set_dirframe(self, frame) |
---|
[1118] | 956 | self._add_history("set_dirframe", varlist) |
---|
[989] | 957 | |
---|
[113] | 958 | def get_unit(self): |
---|
[1846] | 959 | """\ |
---|
[113] | 960 | Get the default unit set in this scantable |
---|
[1846] | 961 | |
---|
[113] | 962 | Returns: |
---|
[1846] | 963 | |
---|
[113] | 964 | A unit string |
---|
[1846] | 965 | |
---|
[113] | 966 | """ |
---|
| 967 | inf = self._getcoordinfo() |
---|
| 968 | unit = inf[0] |
---|
| 969 | if unit == '': unit = 'channel' |
---|
| 970 | return unit |
---|
[102] | 971 | |
---|
[1862] | 972 | @asaplog_post_dec |
---|
[158] | 973 | def get_abcissa(self, rowno=0): |
---|
[1846] | 974 | """\ |
---|
[158] | 975 | Get the abcissa in the current coordinate setup for the currently |
---|
[113] | 976 | selected Beam/IF/Pol |
---|
[1846] | 977 | |
---|
[113] | 978 | Parameters: |
---|
[1846] | 979 | |
---|
[226] | 980 | rowno: an optional row number in the scantable. Default is the |
---|
| 981 | first row, i.e. rowno=0 |
---|
[1846] | 982 | |
---|
[113] | 983 | Returns: |
---|
[1846] | 984 | |
---|
[1348] | 985 | The abcissa values and the format string (as a dictionary) |
---|
[1846] | 986 | |
---|
[113] | 987 | """ |
---|
[256] | 988 | abc = self._getabcissa(rowno) |
---|
[710] | 989 | lbl = self._getabcissalabel(rowno) |
---|
[158] | 990 | return abc, lbl |
---|
[113] | 991 | |
---|
[1862] | 992 | @asaplog_post_dec |
---|
[1819] | 993 | def flag(self, mask=None, unflag=False): |
---|
[1846] | 994 | """\ |
---|
[1001] | 995 | Flag the selected data using an optional channel mask. |
---|
[1846] | 996 | |
---|
[1001] | 997 | Parameters: |
---|
[1846] | 998 | |
---|
[1001] | 999 | mask: an optional channel mask, created with create_mask. Default |
---|
| 1000 | (no mask) is all channels. |
---|
[1855] | 1001 | |
---|
[1819] | 1002 | unflag: if True, unflag the data |
---|
[1846] | 1003 | |
---|
[1001] | 1004 | """ |
---|
| 1005 | varlist = vars() |
---|
[1593] | 1006 | mask = mask or [] |
---|
[1859] | 1007 | self._flag(mask, unflag) |
---|
[1001] | 1008 | self._add_history("flag", varlist) |
---|
| 1009 | |
---|
[1862] | 1010 | @asaplog_post_dec |
---|
[1819] | 1011 | def flag_row(self, rows=[], unflag=False): |
---|
[1846] | 1012 | """\ |
---|
[1819] | 1013 | Flag the selected data in row-based manner. |
---|
[1846] | 1014 | |
---|
[1819] | 1015 | Parameters: |
---|
[1846] | 1016 | |
---|
[1843] | 1017 | rows: list of row numbers to be flagged. Default is no row |
---|
| 1018 | (must be explicitly specified to execute row-based flagging). |
---|
[1855] | 1019 | |
---|
[1819] | 1020 | unflag: if True, unflag the data. |
---|
[1846] | 1021 | |
---|
[1819] | 1022 | """ |
---|
| 1023 | varlist = vars() |
---|
[1859] | 1024 | self._flag_row(rows, unflag) |
---|
[1819] | 1025 | self._add_history("flag_row", varlist) |
---|
| 1026 | |
---|
[1862] | 1027 | @asaplog_post_dec |
---|
[1819] | 1028 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
[1846] | 1029 | """\ |
---|
[1819] | 1030 | Flag the selected data outside a specified range (in channel-base) |
---|
[1846] | 1031 | |
---|
[1819] | 1032 | Parameters: |
---|
[1846] | 1033 | |
---|
[1819] | 1034 | uthres: upper threshold. |
---|
[1855] | 1035 | |
---|
[1819] | 1036 | dthres: lower threshold |
---|
[1846] | 1037 | |
---|
[1819] | 1038 | clipoutside: True for flagging data outside the range [dthres:uthres]. |
---|
| 1039 | False for glagging data inside the range. |
---|
[1855] | 1040 | |
---|
[1846] | 1041 | unflag: if True, unflag the data. |
---|
| 1042 | |
---|
[1819] | 1043 | """ |
---|
| 1044 | varlist = vars() |
---|
[1859] | 1045 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
[1819] | 1046 | self._add_history("clip", varlist) |
---|
| 1047 | |
---|
[1862] | 1048 | @asaplog_post_dec |
---|
[1584] | 1049 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
[1846] | 1050 | """\ |
---|
[1192] | 1051 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
[1584] | 1052 | Flagged data in the scantable gets interpolated over the region. |
---|
[1192] | 1053 | No taper is applied. |
---|
[1846] | 1054 | |
---|
[1192] | 1055 | Parameters: |
---|
[1846] | 1056 | |
---|
[1579] | 1057 | start: the start frequency (really a period within the |
---|
| 1058 | bandwidth) or period to remove |
---|
[1855] | 1059 | |
---|
[1579] | 1060 | end: the end frequency or period to remove |
---|
[1855] | 1061 | |
---|
[1584] | 1062 | unit: the frequency unit (default "MHz") or "" for |
---|
[1579] | 1063 | explicit lag channels |
---|
[1846] | 1064 | |
---|
| 1065 | *Notes*: |
---|
| 1066 | |
---|
[1579] | 1067 | It is recommended to flag edges of the band or strong |
---|
[1348] | 1068 | signals beforehand. |
---|
[1846] | 1069 | |
---|
[1192] | 1070 | """ |
---|
| 1071 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 1072 | self._math._setinsitu(insitu) |
---|
| 1073 | varlist = vars() |
---|
[1579] | 1074 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
| 1075 | if not (unit == "" or base.has_key(unit)): |
---|
[1192] | 1076 | raise ValueError("%s is not a valid unit." % unit) |
---|
[1859] | 1077 | if unit == "": |
---|
| 1078 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
| 1079 | else: |
---|
| 1080 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
| 1081 | end*base[unit], "frequency")) |
---|
[1192] | 1082 | s._add_history("lag_flag", varlist) |
---|
| 1083 | if insitu: |
---|
| 1084 | self._assign(s) |
---|
| 1085 | else: |
---|
| 1086 | return s |
---|
[1001] | 1087 | |
---|
[1862] | 1088 | @asaplog_post_dec |
---|
[113] | 1089 | def create_mask(self, *args, **kwargs): |
---|
[1846] | 1090 | """\ |
---|
[1118] | 1091 | Compute and return a mask based on [min, max] windows. |
---|
[189] | 1092 | The specified windows are to be INCLUDED, when the mask is |
---|
[113] | 1093 | applied. |
---|
[1846] | 1094 | |
---|
[102] | 1095 | Parameters: |
---|
[1846] | 1096 | |
---|
[1118] | 1097 | [min, max], [min2, max2], ... |
---|
[1024] | 1098 | Pairs of start/end points (inclusive)specifying the regions |
---|
[102] | 1099 | to be masked |
---|
[1855] | 1100 | |
---|
[189] | 1101 | invert: optional argument. If specified as True, |
---|
| 1102 | return an inverted mask, i.e. the regions |
---|
| 1103 | specified are EXCLUDED |
---|
[1855] | 1104 | |
---|
[513] | 1105 | row: create the mask using the specified row for |
---|
| 1106 | unit conversions, default is row=0 |
---|
| 1107 | only necessary if frequency varies over rows. |
---|
[1846] | 1108 | |
---|
| 1109 | Examples:: |
---|
| 1110 | |
---|
[113] | 1111 | scan.set_unit('channel') |
---|
[1846] | 1112 | # a) |
---|
[1118] | 1113 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
[189] | 1114 | # masks everything outside 400 and 500 |
---|
[113] | 1115 | # and 800 and 900 in the unit 'channel' |
---|
| 1116 | |
---|
[1846] | 1117 | # b) |
---|
[1118] | 1118 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
[189] | 1119 | # masks the regions between 400 and 500 |
---|
[113] | 1120 | # and 800 and 900 in the unit 'channel' |
---|
[1846] | 1121 | |
---|
| 1122 | # c) |
---|
| 1123 | #mask only channel 400 |
---|
[1554] | 1124 | msk = scan.create_mask([400]) |
---|
[1846] | 1125 | |
---|
[102] | 1126 | """ |
---|
[1554] | 1127 | row = kwargs.get("row", 0) |
---|
[513] | 1128 | data = self._getabcissa(row) |
---|
[113] | 1129 | u = self._getcoordinfo()[0] |
---|
[1859] | 1130 | if u == "": |
---|
| 1131 | u = "channel" |
---|
| 1132 | msg = "The current mask window unit is %s" % u |
---|
| 1133 | i = self._check_ifs() |
---|
| 1134 | if not i: |
---|
| 1135 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1136 | asaplog.push(msg) |
---|
[102] | 1137 | n = self.nchan() |
---|
[1295] | 1138 | msk = _n_bools(n, False) |
---|
[710] | 1139 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
| 1140 | |
---|
[1118] | 1141 | ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ |
---|
| 1142 | and args or args[0] |
---|
[710] | 1143 | for window in ws: |
---|
[1554] | 1144 | if len(window) == 1: |
---|
| 1145 | window = [window[0], window[0]] |
---|
| 1146 | if len(window) == 0 or len(window) > 2: |
---|
| 1147 | raise ValueError("A window needs to be defined as [start(, end)]") |
---|
[1545] | 1148 | if window[0] > window[1]: |
---|
| 1149 | tmp = window[0] |
---|
| 1150 | window[0] = window[1] |
---|
| 1151 | window[1] = tmp |
---|
[102] | 1152 | for i in range(n): |
---|
[1024] | 1153 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
[1295] | 1154 | msk[i] = True |
---|
[113] | 1155 | if kwargs.has_key('invert'): |
---|
| 1156 | if kwargs.get('invert'): |
---|
[1295] | 1157 | msk = mask_not(msk) |
---|
[102] | 1158 | return msk |
---|
[710] | 1159 | |
---|
[1924] | 1160 | def get_masklist(self, mask=None, row=0, silent=False): |
---|
[1846] | 1161 | """\ |
---|
[1819] | 1162 | Compute and return a list of mask windows, [min, max]. |
---|
[1846] | 1163 | |
---|
[1819] | 1164 | Parameters: |
---|
[1846] | 1165 | |
---|
[1819] | 1166 | mask: channel mask, created with create_mask. |
---|
[1855] | 1167 | |
---|
[1819] | 1168 | row: calcutate the masklist using the specified row |
---|
| 1169 | for unit conversions, default is row=0 |
---|
| 1170 | only necessary if frequency varies over rows. |
---|
[1846] | 1171 | |
---|
[1819] | 1172 | Returns: |
---|
[1846] | 1173 | |
---|
[1819] | 1174 | [min, max], [min2, max2], ... |
---|
| 1175 | Pairs of start/end points (inclusive)specifying |
---|
| 1176 | the masked regions |
---|
[1846] | 1177 | |
---|
[1819] | 1178 | """ |
---|
| 1179 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1180 | raise TypeError("The mask should be list or tuple.") |
---|
| 1181 | if len(mask) < 2: |
---|
| 1182 | raise TypeError("The mask elements should be > 1") |
---|
| 1183 | if self.nchan() != len(mask): |
---|
| 1184 | msg = "Number of channels in scantable != number of mask elements" |
---|
| 1185 | raise TypeError(msg) |
---|
| 1186 | data = self._getabcissa(row) |
---|
| 1187 | u = self._getcoordinfo()[0] |
---|
[1859] | 1188 | if u == "": |
---|
| 1189 | u = "channel" |
---|
| 1190 | msg = "The current mask window unit is %s" % u |
---|
| 1191 | i = self._check_ifs() |
---|
| 1192 | if not i: |
---|
| 1193 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
[1924] | 1194 | if not silent: |
---|
| 1195 | asaplog.push(msg) |
---|
[1819] | 1196 | masklist=[] |
---|
| 1197 | ist, ien = None, None |
---|
| 1198 | ist, ien=self.get_mask_indices(mask) |
---|
| 1199 | if ist is not None and ien is not None: |
---|
| 1200 | for i in xrange(len(ist)): |
---|
| 1201 | range=[data[ist[i]],data[ien[i]]] |
---|
| 1202 | range.sort() |
---|
| 1203 | masklist.append([range[0],range[1]]) |
---|
| 1204 | return masklist |
---|
| 1205 | |
---|
| 1206 | def get_mask_indices(self, mask=None): |
---|
[1846] | 1207 | """\ |
---|
[1819] | 1208 | Compute and Return lists of mask start indices and mask end indices. |
---|
[1855] | 1209 | |
---|
| 1210 | Parameters: |
---|
| 1211 | |
---|
[1819] | 1212 | mask: channel mask, created with create_mask. |
---|
[1846] | 1213 | |
---|
[1819] | 1214 | Returns: |
---|
[1846] | 1215 | |
---|
[1819] | 1216 | List of mask start indices and that of mask end indices, |
---|
| 1217 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
[1846] | 1218 | |
---|
[1819] | 1219 | """ |
---|
| 1220 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1221 | raise TypeError("The mask should be list or tuple.") |
---|
| 1222 | if len(mask) < 2: |
---|
| 1223 | raise TypeError("The mask elements should be > 1") |
---|
| 1224 | istart=[] |
---|
| 1225 | iend=[] |
---|
| 1226 | if mask[0]: istart.append(0) |
---|
| 1227 | for i in range(len(mask)-1): |
---|
| 1228 | if not mask[i] and mask[i+1]: |
---|
| 1229 | istart.append(i+1) |
---|
| 1230 | elif mask[i] and not mask[i+1]: |
---|
| 1231 | iend.append(i) |
---|
| 1232 | if mask[len(mask)-1]: iend.append(len(mask)-1) |
---|
| 1233 | if len(istart) != len(iend): |
---|
| 1234 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
| 1235 | for i in range(len(istart)): |
---|
| 1236 | if istart[i] > iend[i]: |
---|
| 1237 | raise RuntimeError("Mask start index > mask end index") |
---|
| 1238 | break |
---|
| 1239 | return istart,iend |
---|
| 1240 | |
---|
| 1241 | # def get_restfreqs(self): |
---|
| 1242 | # """ |
---|
| 1243 | # Get the restfrequency(s) stored in this scantable. |
---|
| 1244 | # The return value(s) are always of unit 'Hz' |
---|
| 1245 | # Parameters: |
---|
| 1246 | # none |
---|
| 1247 | # Returns: |
---|
| 1248 | # a list of doubles |
---|
| 1249 | # """ |
---|
| 1250 | # return list(self._getrestfreqs()) |
---|
| 1251 | |
---|
| 1252 | def get_restfreqs(self, ids=None): |
---|
[1846] | 1253 | """\ |
---|
[256] | 1254 | Get the restfrequency(s) stored in this scantable. |
---|
| 1255 | The return value(s) are always of unit 'Hz' |
---|
[1846] | 1256 | |
---|
[256] | 1257 | Parameters: |
---|
[1846] | 1258 | |
---|
[1819] | 1259 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
| 1260 | be retrieved |
---|
[1846] | 1261 | |
---|
[256] | 1262 | Returns: |
---|
[1846] | 1263 | |
---|
[1819] | 1264 | dictionary containing ids and a list of doubles for each id |
---|
[1846] | 1265 | |
---|
[256] | 1266 | """ |
---|
[1819] | 1267 | if ids is None: |
---|
| 1268 | rfreqs={} |
---|
| 1269 | idlist = self.getmolnos() |
---|
| 1270 | for i in idlist: |
---|
| 1271 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1272 | return rfreqs |
---|
| 1273 | else: |
---|
| 1274 | if type(ids)==list or type(ids)==tuple: |
---|
| 1275 | rfreqs={} |
---|
| 1276 | for i in ids: |
---|
| 1277 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1278 | return rfreqs |
---|
| 1279 | else: |
---|
| 1280 | return list(self._getrestfreqs(ids)) |
---|
| 1281 | #return list(self._getrestfreqs(ids)) |
---|
[102] | 1282 | |
---|
[931] | 1283 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
[1846] | 1284 | """\ |
---|
[931] | 1285 | Set or replace the restfrequency specified and |
---|
| 1286 | If the 'freqs' argument holds a scalar, |
---|
| 1287 | then that rest frequency will be applied to all the selected |
---|
| 1288 | data. If the 'freqs' argument holds |
---|
| 1289 | a vector, then it MUST be of equal or smaller length than |
---|
| 1290 | the number of IFs (and the available restfrequencies will be |
---|
| 1291 | replaced by this vector). In this case, *all* data have |
---|
| 1292 | the restfrequency set per IF according |
---|
| 1293 | to the corresponding value you give in the 'freqs' vector. |
---|
[1118] | 1294 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
[931] | 1295 | IF 1 gets restfreq 2e9. |
---|
[1846] | 1296 | |
---|
[1395] | 1297 | You can also specify the frequencies via a linecatalog. |
---|
[1153] | 1298 | |
---|
[931] | 1299 | Parameters: |
---|
[1846] | 1300 | |
---|
[931] | 1301 | freqs: list of rest frequency values or string idenitfiers |
---|
[1855] | 1302 | |
---|
[931] | 1303 | unit: unit for rest frequency (default 'Hz') |
---|
[402] | 1304 | |
---|
[1846] | 1305 | |
---|
| 1306 | Example:: |
---|
| 1307 | |
---|
[1819] | 1308 | # set the given restfrequency for the all currently selected IFs |
---|
[931] | 1309 | scan.set_restfreqs(freqs=1.4e9) |
---|
[1845] | 1310 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
| 1311 | # list, i.e |
---|
| 1312 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
| 1313 | # len(list_of_restfreqs) == nIF |
---|
| 1314 | # for nIF == 1 the following will set multiple restfrequency for |
---|
| 1315 | # that IF |
---|
[1819] | 1316 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
[1845] | 1317 | # set multiple restfrequencies per IF. as a list of lists where |
---|
| 1318 | # the outer list has nIF elements, the inner s arbitrary |
---|
| 1319 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
[391] | 1320 | |
---|
[1846] | 1321 | *Note*: |
---|
[1845] | 1322 | |
---|
[931] | 1323 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
| 1324 | source and IF basis, use scantable.set_selection() before using |
---|
[1846] | 1325 | this function:: |
---|
[931] | 1326 | |
---|
[1846] | 1327 | # provided your scantable is called scan |
---|
| 1328 | selection = selector() |
---|
| 1329 | selection.set_name("ORION*") |
---|
| 1330 | selection.set_ifs([1]) |
---|
| 1331 | scan.set_selection(selection) |
---|
| 1332 | scan.set_restfreqs(freqs=86.6e9) |
---|
| 1333 | |
---|
[931] | 1334 | """ |
---|
| 1335 | varlist = vars() |
---|
[1157] | 1336 | from asap import linecatalog |
---|
| 1337 | # simple value |
---|
[1118] | 1338 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
[1845] | 1339 | self._setrestfreqs([freqs], [""], unit) |
---|
[1157] | 1340 | # list of values |
---|
[1118] | 1341 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
[1157] | 1342 | # list values are scalars |
---|
[1118] | 1343 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
[1845] | 1344 | if len(freqs) == 1: |
---|
| 1345 | self._setrestfreqs(freqs, [""], unit) |
---|
| 1346 | else: |
---|
| 1347 | # allow the 'old' mode of setting mulitple IFs |
---|
| 1348 | sel = selector() |
---|
| 1349 | savesel = self._getselection() |
---|
| 1350 | iflist = self.getifnos() |
---|
| 1351 | if len(freqs)>len(iflist): |
---|
| 1352 | raise ValueError("number of elements in list of list " |
---|
| 1353 | "exeeds the current IF selections") |
---|
| 1354 | iflist = self.getifnos() |
---|
| 1355 | for i, fval in enumerate(freqs): |
---|
| 1356 | sel.set_ifs(iflist[i]) |
---|
| 1357 | self._setselection(sel) |
---|
| 1358 | self._setrestfreqs([fval], [""], unit) |
---|
| 1359 | self._setselection(savesel) |
---|
| 1360 | |
---|
| 1361 | # list values are dict, {'value'=, 'name'=) |
---|
[1157] | 1362 | elif isinstance(freqs[-1], dict): |
---|
[1845] | 1363 | values = [] |
---|
| 1364 | names = [] |
---|
| 1365 | for d in freqs: |
---|
| 1366 | values.append(d["value"]) |
---|
| 1367 | names.append(d["name"]) |
---|
| 1368 | self._setrestfreqs(values, names, unit) |
---|
[1819] | 1369 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
[1157] | 1370 | sel = selector() |
---|
| 1371 | savesel = self._getselection() |
---|
[1322] | 1372 | iflist = self.getifnos() |
---|
[1819] | 1373 | if len(freqs)>len(iflist): |
---|
[1845] | 1374 | raise ValueError("number of elements in list of list exeeds" |
---|
| 1375 | " the current IF selections") |
---|
| 1376 | for i, fval in enumerate(freqs): |
---|
[1322] | 1377 | sel.set_ifs(iflist[i]) |
---|
[1259] | 1378 | self._setselection(sel) |
---|
[1845] | 1379 | self._setrestfreqs(fval, [""], unit) |
---|
[1157] | 1380 | self._setselection(savesel) |
---|
| 1381 | # freqs are to be taken from a linecatalog |
---|
[1153] | 1382 | elif isinstance(freqs, linecatalog): |
---|
| 1383 | sel = selector() |
---|
| 1384 | savesel = self._getselection() |
---|
| 1385 | for i in xrange(freqs.nrow()): |
---|
[1322] | 1386 | sel.set_ifs(iflist[i]) |
---|
[1153] | 1387 | self._setselection(sel) |
---|
[1845] | 1388 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
| 1389 | [freqs.get_name(i)], "MHz") |
---|
[1153] | 1390 | # ensure that we are not iterating past nIF |
---|
| 1391 | if i == self.nif()-1: break |
---|
| 1392 | self._setselection(savesel) |
---|
[931] | 1393 | else: |
---|
| 1394 | return |
---|
| 1395 | self._add_history("set_restfreqs", varlist) |
---|
| 1396 | |
---|
[1360] | 1397 | def shift_refpix(self, delta): |
---|
[1846] | 1398 | """\ |
---|
[1589] | 1399 | Shift the reference pixel of the Spectra Coordinate by an |
---|
| 1400 | integer amount. |
---|
[1846] | 1401 | |
---|
[1589] | 1402 | Parameters: |
---|
[1846] | 1403 | |
---|
[1589] | 1404 | delta: the amount to shift by |
---|
[1846] | 1405 | |
---|
| 1406 | *Note*: |
---|
| 1407 | |
---|
[1589] | 1408 | Be careful using this with broadband data. |
---|
[1846] | 1409 | |
---|
[1360] | 1410 | """ |
---|
[1731] | 1411 | Scantable.shift_refpix(self, delta) |
---|
[931] | 1412 | |
---|
[1862] | 1413 | @asaplog_post_dec |
---|
[1259] | 1414 | def history(self, filename=None): |
---|
[1846] | 1415 | """\ |
---|
[1259] | 1416 | Print the history. Optionally to a file. |
---|
[1846] | 1417 | |
---|
[1348] | 1418 | Parameters: |
---|
[1846] | 1419 | |
---|
[1348] | 1420 | filename: The name of the file to save the history to. |
---|
[1846] | 1421 | |
---|
[1259] | 1422 | """ |
---|
[484] | 1423 | hist = list(self._gethistory()) |
---|
[794] | 1424 | out = "-"*80 |
---|
[484] | 1425 | for h in hist: |
---|
[489] | 1426 | if h.startswith("---"): |
---|
[1857] | 1427 | out = "\n".join([out, h]) |
---|
[489] | 1428 | else: |
---|
| 1429 | items = h.split("##") |
---|
| 1430 | date = items[0] |
---|
| 1431 | func = items[1] |
---|
| 1432 | items = items[2:] |
---|
[794] | 1433 | out += "\n"+date+"\n" |
---|
| 1434 | out += "Function: %s\n Parameters:" % (func) |
---|
[489] | 1435 | for i in items: |
---|
| 1436 | s = i.split("=") |
---|
[1118] | 1437 | out += "\n %s = %s" % (s[0], s[1]) |
---|
[1857] | 1438 | out = "\n".join([out, "-"*80]) |
---|
[1259] | 1439 | if filename is not None: |
---|
| 1440 | if filename is "": |
---|
| 1441 | filename = 'scantable_history.txt' |
---|
| 1442 | import os |
---|
| 1443 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 1444 | if not os.path.isdir(filename): |
---|
| 1445 | data = open(filename, 'w') |
---|
| 1446 | data.write(out) |
---|
| 1447 | data.close() |
---|
| 1448 | else: |
---|
| 1449 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 1450 | raise IOError(msg) |
---|
| 1451 | return page(out) |
---|
[513] | 1452 | # |
---|
| 1453 | # Maths business |
---|
| 1454 | # |
---|
[1862] | 1455 | @asaplog_post_dec |
---|
[931] | 1456 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
[1846] | 1457 | """\ |
---|
[1070] | 1458 | Return the (time) weighted average of a scan. |
---|
[1846] | 1459 | |
---|
| 1460 | *Note*: |
---|
| 1461 | |
---|
[1070] | 1462 | in channels only - align if necessary |
---|
[1846] | 1463 | |
---|
[513] | 1464 | Parameters: |
---|
[1846] | 1465 | |
---|
[513] | 1466 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
| 1467 | weighting) |
---|
[1855] | 1468 | |
---|
[558] | 1469 | scanav: True averages each scan separately |
---|
| 1470 | False (default) averages all scans together, |
---|
[1855] | 1471 | |
---|
[1099] | 1472 | weight: Weighting scheme. |
---|
| 1473 | 'none' (mean no weight) |
---|
| 1474 | 'var' (1/var(spec) weighted) |
---|
| 1475 | 'tsys' (1/Tsys**2 weighted) |
---|
| 1476 | 'tint' (integration time weighted) |
---|
| 1477 | 'tintsys' (Tint/Tsys**2) |
---|
| 1478 | 'median' ( median averaging) |
---|
[535] | 1479 | The default is 'tint' |
---|
[1855] | 1480 | |
---|
[931] | 1481 | align: align the spectra in velocity before averaging. It takes |
---|
| 1482 | the time of the first spectrum as reference time. |
---|
[1846] | 1483 | |
---|
| 1484 | Example:: |
---|
| 1485 | |
---|
[513] | 1486 | # time average the scantable without using a mask |
---|
[710] | 1487 | newscan = scan.average_time() |
---|
[1846] | 1488 | |
---|
[513] | 1489 | """ |
---|
| 1490 | varlist = vars() |
---|
[1593] | 1491 | weight = weight or 'TINT' |
---|
| 1492 | mask = mask or () |
---|
| 1493 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
[1118] | 1494 | scan = (self, ) |
---|
[1859] | 1495 | |
---|
| 1496 | if align: |
---|
| 1497 | scan = (self.freq_align(insitu=False), ) |
---|
| 1498 | s = None |
---|
| 1499 | if weight.upper() == 'MEDIAN': |
---|
| 1500 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
| 1501 | scanav)) |
---|
| 1502 | else: |
---|
| 1503 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
| 1504 | scanav)) |
---|
[1099] | 1505 | s._add_history("average_time", varlist) |
---|
[513] | 1506 | return s |
---|
[710] | 1507 | |
---|
[1862] | 1508 | @asaplog_post_dec |
---|
[876] | 1509 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
[1846] | 1510 | """\ |
---|
[513] | 1511 | Return a scan where all spectra are converted to either |
---|
| 1512 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
| 1513 | By default the function tries to look the values up internally. |
---|
| 1514 | If it can't find them (or if you want to over-ride), you must |
---|
| 1515 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
| 1516 | also if you don't set it). jyperk takes precedence if you set both. |
---|
[1846] | 1517 | |
---|
[513] | 1518 | Parameters: |
---|
[1846] | 1519 | |
---|
[513] | 1520 | jyperk: the Jy / K conversion factor |
---|
[1855] | 1521 | |
---|
[513] | 1522 | eta: the aperture efficiency |
---|
[1855] | 1523 | |
---|
[513] | 1524 | d: the geomtric diameter (metres) |
---|
[1855] | 1525 | |
---|
[513] | 1526 | insitu: if False a new scantable is returned. |
---|
| 1527 | Otherwise, the scaling is done in-situ |
---|
| 1528 | The default is taken from .asaprc (False) |
---|
[1846] | 1529 | |
---|
[513] | 1530 | """ |
---|
| 1531 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1532 | self._math._setinsitu(insitu) |
---|
[513] | 1533 | varlist = vars() |
---|
[1593] | 1534 | jyperk = jyperk or -1.0 |
---|
| 1535 | d = d or -1.0 |
---|
| 1536 | eta = eta or -1.0 |
---|
[876] | 1537 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
| 1538 | s._add_history("convert_flux", varlist) |
---|
| 1539 | if insitu: self._assign(s) |
---|
| 1540 | else: return s |
---|
[513] | 1541 | |
---|
[1862] | 1542 | @asaplog_post_dec |
---|
[876] | 1543 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
[1846] | 1544 | """\ |
---|
[513] | 1545 | Return a scan after applying a gain-elevation correction. |
---|
| 1546 | The correction can be made via either a polynomial or a |
---|
| 1547 | table-based interpolation (and extrapolation if necessary). |
---|
| 1548 | You specify polynomial coefficients, an ascii table or neither. |
---|
| 1549 | If you specify neither, then a polynomial correction will be made |
---|
| 1550 | with built in coefficients known for certain telescopes (an error |
---|
| 1551 | will occur if the instrument is not known). |
---|
| 1552 | The data and Tsys are *divided* by the scaling factors. |
---|
[1846] | 1553 | |
---|
[513] | 1554 | Parameters: |
---|
[1846] | 1555 | |
---|
[513] | 1556 | poly: Polynomial coefficients (default None) to compute a |
---|
| 1557 | gain-elevation correction as a function of |
---|
| 1558 | elevation (in degrees). |
---|
[1855] | 1559 | |
---|
[513] | 1560 | filename: The name of an ascii file holding correction factors. |
---|
| 1561 | The first row of the ascii file must give the column |
---|
| 1562 | names and these MUST include columns |
---|
| 1563 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
| 1564 | by this) somewhere. |
---|
| 1565 | The second row must give the data type of the |
---|
| 1566 | column. Use 'R' for Real and 'I' for Integer. |
---|
| 1567 | An example file would be |
---|
| 1568 | (actual factors are arbitrary) : |
---|
| 1569 | |
---|
| 1570 | TIME ELEVATION FACTOR |
---|
| 1571 | R R R |
---|
| 1572 | 0.1 0 0.8 |
---|
| 1573 | 0.2 20 0.85 |
---|
| 1574 | 0.3 40 0.9 |
---|
| 1575 | 0.4 60 0.85 |
---|
| 1576 | 0.5 80 0.8 |
---|
| 1577 | 0.6 90 0.75 |
---|
[1855] | 1578 | |
---|
[513] | 1579 | method: Interpolation method when correcting from a table. |
---|
| 1580 | Values are "nearest", "linear" (default), "cubic" |
---|
| 1581 | and "spline" |
---|
[1855] | 1582 | |
---|
[513] | 1583 | insitu: if False a new scantable is returned. |
---|
| 1584 | Otherwise, the scaling is done in-situ |
---|
| 1585 | The default is taken from .asaprc (False) |
---|
[1846] | 1586 | |
---|
[513] | 1587 | """ |
---|
| 1588 | |
---|
| 1589 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1590 | self._math._setinsitu(insitu) |
---|
[513] | 1591 | varlist = vars() |
---|
[1593] | 1592 | poly = poly or () |
---|
[513] | 1593 | from os.path import expandvars |
---|
| 1594 | filename = expandvars(filename) |
---|
[876] | 1595 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
| 1596 | s._add_history("gain_el", varlist) |
---|
[1593] | 1597 | if insitu: |
---|
| 1598 | self._assign(s) |
---|
| 1599 | else: |
---|
| 1600 | return s |
---|
[710] | 1601 | |
---|
[1862] | 1602 | @asaplog_post_dec |
---|
[931] | 1603 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
[1846] | 1604 | """\ |
---|
[513] | 1605 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
| 1606 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
| 1607 | set_freqframe. |
---|
[1846] | 1608 | |
---|
[513] | 1609 | Parameters: |
---|
[1855] | 1610 | |
---|
[513] | 1611 | reftime: reference time to align at. By default, the time of |
---|
| 1612 | the first row of data is used. |
---|
[1855] | 1613 | |
---|
[513] | 1614 | method: Interpolation method for regridding the spectra. |
---|
| 1615 | Choose from "nearest", "linear", "cubic" (default) |
---|
| 1616 | and "spline" |
---|
[1855] | 1617 | |
---|
[513] | 1618 | insitu: if False a new scantable is returned. |
---|
| 1619 | Otherwise, the scaling is done in-situ |
---|
| 1620 | The default is taken from .asaprc (False) |
---|
[1846] | 1621 | |
---|
[513] | 1622 | """ |
---|
[931] | 1623 | if insitu is None: insitu = rcParams["insitu"] |
---|
[876] | 1624 | self._math._setinsitu(insitu) |
---|
[513] | 1625 | varlist = vars() |
---|
[1593] | 1626 | reftime = reftime or "" |
---|
[931] | 1627 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
[876] | 1628 | s._add_history("freq_align", varlist) |
---|
| 1629 | if insitu: self._assign(s) |
---|
| 1630 | else: return s |
---|
[513] | 1631 | |
---|
[1862] | 1632 | @asaplog_post_dec |
---|
[1725] | 1633 | def opacity(self, tau=None, insitu=None): |
---|
[1846] | 1634 | """\ |
---|
[513] | 1635 | Apply an opacity correction. The data |
---|
| 1636 | and Tsys are multiplied by the correction factor. |
---|
[1846] | 1637 | |
---|
[513] | 1638 | Parameters: |
---|
[1855] | 1639 | |
---|
[1689] | 1640 | tau: (list of) opacity from which the correction factor is |
---|
[513] | 1641 | exp(tau*ZD) |
---|
[1689] | 1642 | where ZD is the zenith-distance. |
---|
| 1643 | If a list is provided, it has to be of length nIF, |
---|
| 1644 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
| 1645 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
[1725] | 1646 | if tau is `None` the opacities are determined from a |
---|
| 1647 | model. |
---|
[1855] | 1648 | |
---|
[513] | 1649 | insitu: if False a new scantable is returned. |
---|
| 1650 | Otherwise, the scaling is done in-situ |
---|
| 1651 | The default is taken from .asaprc (False) |
---|
[1846] | 1652 | |
---|
[513] | 1653 | """ |
---|
| 1654 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1655 | self._math._setinsitu(insitu) |
---|
[513] | 1656 | varlist = vars() |
---|
[1689] | 1657 | if not hasattr(tau, "__len__"): |
---|
| 1658 | tau = [tau] |
---|
[876] | 1659 | s = scantable(self._math._opacity(self, tau)) |
---|
| 1660 | s._add_history("opacity", varlist) |
---|
| 1661 | if insitu: self._assign(s) |
---|
| 1662 | else: return s |
---|
[513] | 1663 | |
---|
[1862] | 1664 | @asaplog_post_dec |
---|
[513] | 1665 | def bin(self, width=5, insitu=None): |
---|
[1846] | 1666 | """\ |
---|
[513] | 1667 | Return a scan where all spectra have been binned up. |
---|
[1846] | 1668 | |
---|
[1348] | 1669 | Parameters: |
---|
[1846] | 1670 | |
---|
[513] | 1671 | width: The bin width (default=5) in pixels |
---|
[1855] | 1672 | |
---|
[513] | 1673 | insitu: if False a new scantable is returned. |
---|
| 1674 | Otherwise, the scaling is done in-situ |
---|
| 1675 | The default is taken from .asaprc (False) |
---|
[1846] | 1676 | |
---|
[513] | 1677 | """ |
---|
| 1678 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1679 | self._math._setinsitu(insitu) |
---|
[513] | 1680 | varlist = vars() |
---|
[876] | 1681 | s = scantable(self._math._bin(self, width)) |
---|
[1118] | 1682 | s._add_history("bin", varlist) |
---|
[1589] | 1683 | if insitu: |
---|
| 1684 | self._assign(s) |
---|
| 1685 | else: |
---|
| 1686 | return s |
---|
[513] | 1687 | |
---|
[1862] | 1688 | @asaplog_post_dec |
---|
[513] | 1689 | def resample(self, width=5, method='cubic', insitu=None): |
---|
[1846] | 1690 | """\ |
---|
[1348] | 1691 | Return a scan where all spectra have been binned up. |
---|
[1573] | 1692 | |
---|
[1348] | 1693 | Parameters: |
---|
[1846] | 1694 | |
---|
[513] | 1695 | width: The bin width (default=5) in pixels |
---|
[1855] | 1696 | |
---|
[513] | 1697 | method: Interpolation method when correcting from a table. |
---|
| 1698 | Values are "nearest", "linear", "cubic" (default) |
---|
| 1699 | and "spline" |
---|
[1855] | 1700 | |
---|
[513] | 1701 | insitu: if False a new scantable is returned. |
---|
| 1702 | Otherwise, the scaling is done in-situ |
---|
| 1703 | The default is taken from .asaprc (False) |
---|
[1846] | 1704 | |
---|
[513] | 1705 | """ |
---|
| 1706 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1707 | self._math._setinsitu(insitu) |
---|
[513] | 1708 | varlist = vars() |
---|
[876] | 1709 | s = scantable(self._math._resample(self, method, width)) |
---|
[1118] | 1710 | s._add_history("resample", varlist) |
---|
[876] | 1711 | if insitu: self._assign(s) |
---|
| 1712 | else: return s |
---|
[513] | 1713 | |
---|
[1862] | 1714 | @asaplog_post_dec |
---|
[946] | 1715 | def average_pol(self, mask=None, weight='none'): |
---|
[1846] | 1716 | """\ |
---|
[946] | 1717 | Average the Polarisations together. |
---|
[1846] | 1718 | |
---|
[946] | 1719 | Parameters: |
---|
[1846] | 1720 | |
---|
[946] | 1721 | mask: An optional mask defining the region, where the |
---|
| 1722 | averaging will be applied. The output will have all |
---|
| 1723 | specified points masked. |
---|
[1855] | 1724 | |
---|
[946] | 1725 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 1726 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 1727 | |
---|
[946] | 1728 | """ |
---|
| 1729 | varlist = vars() |
---|
[1593] | 1730 | mask = mask or () |
---|
[1010] | 1731 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
[1118] | 1732 | s._add_history("average_pol", varlist) |
---|
[992] | 1733 | return s |
---|
[513] | 1734 | |
---|
[1862] | 1735 | @asaplog_post_dec |
---|
[1145] | 1736 | def average_beam(self, mask=None, weight='none'): |
---|
[1846] | 1737 | """\ |
---|
[1145] | 1738 | Average the Beams together. |
---|
[1846] | 1739 | |
---|
[1145] | 1740 | Parameters: |
---|
| 1741 | mask: An optional mask defining the region, where the |
---|
| 1742 | averaging will be applied. The output will have all |
---|
| 1743 | specified points masked. |
---|
[1855] | 1744 | |
---|
[1145] | 1745 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 1746 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 1747 | |
---|
[1145] | 1748 | """ |
---|
| 1749 | varlist = vars() |
---|
[1593] | 1750 | mask = mask or () |
---|
[1145] | 1751 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
| 1752 | s._add_history("average_beam", varlist) |
---|
| 1753 | return s |
---|
| 1754 | |
---|
[1586] | 1755 | def parallactify(self, pflag): |
---|
[1846] | 1756 | """\ |
---|
[1843] | 1757 | Set a flag to indicate whether this data should be treated as having |
---|
[1617] | 1758 | been 'parallactified' (total phase == 0.0) |
---|
[1846] | 1759 | |
---|
[1617] | 1760 | Parameters: |
---|
[1855] | 1761 | |
---|
[1843] | 1762 | pflag: Bool indicating whether to turn this on (True) or |
---|
[1617] | 1763 | off (False) |
---|
[1846] | 1764 | |
---|
[1617] | 1765 | """ |
---|
[1586] | 1766 | varlist = vars() |
---|
| 1767 | self._parallactify(pflag) |
---|
| 1768 | self._add_history("parallactify", varlist) |
---|
| 1769 | |
---|
[1862] | 1770 | @asaplog_post_dec |
---|
[992] | 1771 | def convert_pol(self, poltype=None): |
---|
[1846] | 1772 | """\ |
---|
[992] | 1773 | Convert the data to a different polarisation type. |
---|
[1565] | 1774 | Note that you will need cross-polarisation terms for most conversions. |
---|
[1846] | 1775 | |
---|
[992] | 1776 | Parameters: |
---|
[1855] | 1777 | |
---|
[992] | 1778 | poltype: The new polarisation type. Valid types are: |
---|
[1565] | 1779 | "linear", "circular", "stokes" and "linpol" |
---|
[1846] | 1780 | |
---|
[992] | 1781 | """ |
---|
| 1782 | varlist = vars() |
---|
[1859] | 1783 | s = scantable(self._math._convertpol(self, poltype)) |
---|
[1118] | 1784 | s._add_history("convert_pol", varlist) |
---|
[992] | 1785 | return s |
---|
| 1786 | |
---|
[1862] | 1787 | @asaplog_post_dec |
---|
[1819] | 1788 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): |
---|
[1846] | 1789 | """\ |
---|
[513] | 1790 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
[1846] | 1791 | |
---|
[513] | 1792 | Parameters: |
---|
[1846] | 1793 | |
---|
[513] | 1794 | kernel: The type of smoothing kernel. Select from |
---|
[1574] | 1795 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
| 1796 | or 'poly' |
---|
[1855] | 1797 | |
---|
[513] | 1798 | width: The width of the kernel in pixels. For hanning this is |
---|
| 1799 | ignored otherwise it defauls to 5 pixels. |
---|
| 1800 | For 'gaussian' it is the Full Width Half |
---|
| 1801 | Maximum. For 'boxcar' it is the full width. |
---|
[1574] | 1802 | For 'rmedian' and 'poly' it is the half width. |
---|
[1855] | 1803 | |
---|
[1574] | 1804 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
| 1805 | specify the order of the polnomial. Ignored by all other |
---|
| 1806 | kernels. |
---|
[1855] | 1807 | |
---|
[1819] | 1808 | plot: plot the original and the smoothed spectra. |
---|
| 1809 | In this each indivual fit has to be approved, by |
---|
| 1810 | typing 'y' or 'n' |
---|
[1855] | 1811 | |
---|
[513] | 1812 | insitu: if False a new scantable is returned. |
---|
| 1813 | Otherwise, the scaling is done in-situ |
---|
| 1814 | The default is taken from .asaprc (False) |
---|
[1846] | 1815 | |
---|
[513] | 1816 | """ |
---|
| 1817 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1818 | self._math._setinsitu(insitu) |
---|
[513] | 1819 | varlist = vars() |
---|
[1819] | 1820 | |
---|
| 1821 | if plot: orgscan = self.copy() |
---|
| 1822 | |
---|
[1574] | 1823 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
[876] | 1824 | s._add_history("smooth", varlist) |
---|
[1819] | 1825 | |
---|
| 1826 | if plot: |
---|
| 1827 | if rcParams['plotter.gui']: |
---|
| 1828 | from asap.asaplotgui import asaplotgui as asaplot |
---|
| 1829 | else: |
---|
| 1830 | from asap.asaplot import asaplot |
---|
| 1831 | self._p=asaplot() |
---|
| 1832 | self._p.set_panels() |
---|
| 1833 | ylab=s._get_ordinate_label() |
---|
| 1834 | #self._p.palette(0,["#777777","red"]) |
---|
| 1835 | for r in xrange(s.nrow()): |
---|
| 1836 | xsm=s._getabcissa(r) |
---|
| 1837 | ysm=s._getspectrum(r) |
---|
| 1838 | xorg=orgscan._getabcissa(r) |
---|
| 1839 | yorg=orgscan._getspectrum(r) |
---|
| 1840 | self._p.clear() |
---|
| 1841 | self._p.hold() |
---|
| 1842 | self._p.set_axes('ylabel',ylab) |
---|
| 1843 | self._p.set_axes('xlabel',s._getabcissalabel(r)) |
---|
| 1844 | self._p.set_axes('title',s._getsourcename(r)) |
---|
| 1845 | self._p.set_line(label='Original',color="#777777") |
---|
| 1846 | self._p.plot(xorg,yorg) |
---|
| 1847 | self._p.set_line(label='Smoothed',color="red") |
---|
| 1848 | self._p.plot(xsm,ysm) |
---|
| 1849 | ### Ugly part for legend |
---|
| 1850 | for i in [0,1]: |
---|
| 1851 | self._p.subplots[0]['lines'].append([self._p.subplots[0]['axes'].lines[i]]) |
---|
| 1852 | self._p.release() |
---|
| 1853 | ### Ugly part for legend |
---|
| 1854 | self._p.subplots[0]['lines']=[] |
---|
| 1855 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
| 1856 | if res.upper() == 'N': |
---|
| 1857 | s._setspectrum(yorg, r) |
---|
| 1858 | self._p.unmap() |
---|
| 1859 | self._p = None |
---|
| 1860 | del orgscan |
---|
| 1861 | |
---|
[876] | 1862 | if insitu: self._assign(s) |
---|
| 1863 | else: return s |
---|
[513] | 1864 | |
---|
[1862] | 1865 | @asaplog_post_dec |
---|
[1907] | 1866 | def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None): |
---|
[1846] | 1867 | """\ |
---|
[513] | 1868 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[1907] | 1869 | |
---|
[513] | 1870 | Parameters: |
---|
[1846] | 1871 | |
---|
[794] | 1872 | mask: an optional mask |
---|
[1855] | 1873 | |
---|
[794] | 1874 | order: the order of the polynomial (default is 0) |
---|
[1855] | 1875 | |
---|
[1061] | 1876 | plot: plot the fit and the residual. In this each |
---|
| 1877 | indivual fit has to be approved, by typing 'y' |
---|
| 1878 | or 'n' |
---|
[1855] | 1879 | |
---|
[1391] | 1880 | uselin: use linear polynomial fit |
---|
[1855] | 1881 | |
---|
[794] | 1882 | insitu: if False a new scantable is returned. |
---|
| 1883 | Otherwise, the scaling is done in-situ |
---|
| 1884 | The default is taken from .asaprc (False) |
---|
[1846] | 1885 | |
---|
[1907] | 1886 | rows: row numbers of spectra to be processed. |
---|
| 1887 | (default is None: for all rows) |
---|
| 1888 | |
---|
| 1889 | Example: |
---|
[513] | 1890 | # return a scan baselined by a third order polynomial, |
---|
| 1891 | # not using a mask |
---|
| 1892 | bscan = scan.poly_baseline(order=3) |
---|
[1846] | 1893 | |
---|
[579] | 1894 | """ |
---|
[513] | 1895 | if insitu is None: insitu = rcParams['insitu'] |
---|
[1819] | 1896 | if not insitu: |
---|
| 1897 | workscan = self.copy() |
---|
| 1898 | else: |
---|
| 1899 | workscan = self |
---|
[513] | 1900 | varlist = vars() |
---|
| 1901 | if mask is None: |
---|
[1907] | 1902 | mask = [True for i in xrange(self.nchan())] |
---|
[1819] | 1903 | |
---|
[1217] | 1904 | try: |
---|
| 1905 | f = fitter() |
---|
[1391] | 1906 | if uselin: |
---|
| 1907 | f.set_function(lpoly=order) |
---|
| 1908 | else: |
---|
| 1909 | f.set_function(poly=order) |
---|
[1819] | 1910 | |
---|
[1907] | 1911 | if rows == None: |
---|
| 1912 | rows = xrange(workscan.nrow()) |
---|
| 1913 | elif isinstance(rows, int): |
---|
| 1914 | rows = [ rows ] |
---|
| 1915 | |
---|
[1819] | 1916 | if len(rows) > 0: |
---|
| 1917 | self.blpars = [] |
---|
[1907] | 1918 | self.masklists = [] |
---|
| 1919 | self.actualmask = [] |
---|
| 1920 | |
---|
[1819] | 1921 | for r in rows: |
---|
| 1922 | f.x = workscan._getabcissa(r) |
---|
| 1923 | f.y = workscan._getspectrum(r) |
---|
[1907] | 1924 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
[1819] | 1925 | f.data = None |
---|
| 1926 | f.fit() |
---|
| 1927 | if plot: |
---|
| 1928 | f.plot(residual=True) |
---|
| 1929 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
| 1930 | if x.upper() == 'N': |
---|
| 1931 | self.blpars.append(None) |
---|
[1907] | 1932 | self.masklists.append(None) |
---|
| 1933 | self.actualmask.append(None) |
---|
[1819] | 1934 | continue |
---|
| 1935 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
| 1936 | self.blpars.append(f.get_parameters()) |
---|
[1924] | 1937 | self.masklists.append(workscan.get_masklist(f.mask, row=r, silent=True)) |
---|
[1907] | 1938 | self.actualmask.append(f.mask) |
---|
[1819] | 1939 | |
---|
| 1940 | if plot: |
---|
| 1941 | f._p.unmap() |
---|
| 1942 | f._p = None |
---|
| 1943 | workscan._add_history("poly_baseline", varlist) |
---|
[1856] | 1944 | if insitu: |
---|
| 1945 | self._assign(workscan) |
---|
| 1946 | else: |
---|
| 1947 | return workscan |
---|
[1217] | 1948 | except RuntimeError: |
---|
| 1949 | msg = "The fit failed, possibly because it didn't converge." |
---|
[1859] | 1950 | raise RuntimeError(msg) |
---|
[513] | 1951 | |
---|
[1924] | 1952 | @asaplog_post_dec |
---|
| 1953 | def poly_baseline(self, mask=None, order=0, plot=False, batch=False, |
---|
| 1954 | insitu=None, rows=None): |
---|
[1907] | 1955 | """\ |
---|
| 1956 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 1957 | Parameters: |
---|
| 1958 | mask: an optional mask |
---|
| 1959 | order: the order of the polynomial (default is 0) |
---|
| 1960 | plot: plot the fit and the residual. In this each |
---|
| 1961 | indivual fit has to be approved, by typing 'y' |
---|
| 1962 | or 'n'. Ignored if batch = True. |
---|
| 1963 | batch: if True a faster algorithm is used and logs |
---|
| 1964 | including the fit results are not output |
---|
| 1965 | (default is False) |
---|
| 1966 | insitu: if False a new scantable is returned. |
---|
| 1967 | Otherwise, the scaling is done in-situ |
---|
| 1968 | The default is taken from .asaprc (False) |
---|
| 1969 | rows: row numbers of spectra to be processed. |
---|
| 1970 | (default is None: for all rows) |
---|
| 1971 | Example: |
---|
| 1972 | # return a scan baselined by a third order polynomial, |
---|
| 1973 | # not using a mask |
---|
| 1974 | bscan = scan.poly_baseline(order=3) |
---|
| 1975 | """ |
---|
| 1976 | if insitu is None: insitu = rcParams["insitu"] |
---|
[1924] | 1977 | varlist = vars() |
---|
[1907] | 1978 | if insitu: |
---|
| 1979 | workscan = self |
---|
| 1980 | else: |
---|
| 1981 | workscan = self.copy() |
---|
| 1982 | |
---|
| 1983 | nchan = workscan.nchan() |
---|
| 1984 | |
---|
| 1985 | if mask is None: |
---|
| 1986 | mask = [True for i in xrange(nchan)] |
---|
| 1987 | |
---|
| 1988 | try: |
---|
| 1989 | if rows == None: |
---|
| 1990 | rows = xrange(workscan.nrow()) |
---|
| 1991 | elif isinstance(rows, int): |
---|
| 1992 | rows = [ rows ] |
---|
| 1993 | |
---|
| 1994 | if len(rows) > 0: |
---|
[1924] | 1995 | workscan.blpars = [] |
---|
| 1996 | workscan.masklists = [] |
---|
| 1997 | workscan.actualmask = [] |
---|
[1907] | 1998 | |
---|
| 1999 | if batch: |
---|
[1924] | 2000 | workscan._poly_baseline_batch(mask, order) |
---|
[1907] | 2001 | elif plot: |
---|
| 2002 | f = fitter() |
---|
| 2003 | f.set_function(lpoly=order) |
---|
| 2004 | for r in rows: |
---|
| 2005 | f.x = workscan._getabcissa(r) |
---|
| 2006 | f.y = workscan._getspectrum(r) |
---|
| 2007 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2008 | f.data = None |
---|
| 2009 | f.fit() |
---|
| 2010 | |
---|
| 2011 | f.plot(residual=True) |
---|
| 2012 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2013 | if accept_fit.upper() == "N": |
---|
| 2014 | self.blpars.append(None) |
---|
| 2015 | self.masklists.append(None) |
---|
| 2016 | self.actualmask.append(None) |
---|
| 2017 | continue |
---|
| 2018 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
[1924] | 2019 | workscan.blpars.append(f.get_parameters()) |
---|
| 2020 | workscan.masklists.append(workscan.get_masklist(f.mask, row=r)) |
---|
| 2021 | workscan.actualmask.append(f.mask) |
---|
[1907] | 2022 | |
---|
| 2023 | f._p.unmap() |
---|
| 2024 | f._p = None |
---|
| 2025 | else: |
---|
| 2026 | for r in rows: |
---|
[1924] | 2027 | fitparams = workscan._poly_baseline(mask, order, r) |
---|
| 2028 | params = fitparams.getparameters() |
---|
| 2029 | fmtd = ", ".join(["p%d = %3.6f" % (i, v) for i, v in enumerate(params)]) |
---|
| 2030 | errors = fitparams.geterrors() |
---|
| 2031 | fmask = mask_and(mask, workscan._getmask(r)) |
---|
| 2032 | |
---|
| 2033 | workscan.blpars.append({"params":params, |
---|
| 2034 | "fixed": fitparams.getfixedparameters(), |
---|
| 2035 | "formatted":fmtd, "errors":errors}) |
---|
| 2036 | workscan.masklists.append(workscan.get_masklist(fmask, r, silent=True)) |
---|
| 2037 | workscan.actualmask.append(fmask) |
---|
[1907] | 2038 | |
---|
[1924] | 2039 | asaplog.push(fmtd) |
---|
[1907] | 2040 | |
---|
| 2041 | workscan._add_history("poly_baseline", varlist) |
---|
| 2042 | |
---|
| 2043 | if insitu: |
---|
| 2044 | self._assign(workscan) |
---|
| 2045 | else: |
---|
| 2046 | return workscan |
---|
| 2047 | |
---|
[1919] | 2048 | except RuntimeError, e: |
---|
[1907] | 2049 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2050 | if rcParams["verbose"]: |
---|
[1919] | 2051 | asaplog.push(str(e)) |
---|
[1907] | 2052 | asaplog.push(str(msg)) |
---|
| 2053 | return |
---|
| 2054 | else: |
---|
[1919] | 2055 | raise RuntimeError(str(e)+'\n'+msg) |
---|
[1907] | 2056 | |
---|
| 2057 | |
---|
| 2058 | def auto_poly_baseline(self, mask=None, edge=(0, 0), order=0, |
---|
[1280] | 2059 | threshold=3, chan_avg_limit=1, plot=False, |
---|
[1907] | 2060 | insitu=None, rows=None): |
---|
[1846] | 2061 | """\ |
---|
[880] | 2062 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 2063 | Spectral lines are detected first using linefinder and masked out |
---|
| 2064 | to avoid them affecting the baseline solution. |
---|
| 2065 | |
---|
| 2066 | Parameters: |
---|
[1846] | 2067 | |
---|
[880] | 2068 | mask: an optional mask retreived from scantable |
---|
[1846] | 2069 | |
---|
| 2070 | edge: an optional number of channel to drop at the edge of |
---|
| 2071 | spectrum. If only one value is |
---|
[880] | 2072 | specified, the same number will be dropped from |
---|
| 2073 | both sides of the spectrum. Default is to keep |
---|
[907] | 2074 | all channels. Nested tuples represent individual |
---|
[976] | 2075 | edge selection for different IFs (a number of spectral |
---|
| 2076 | channels can be different) |
---|
[1846] | 2077 | |
---|
[880] | 2078 | order: the order of the polynomial (default is 0) |
---|
[1846] | 2079 | |
---|
[880] | 2080 | threshold: the threshold used by line finder. It is better to |
---|
| 2081 | keep it large as only strong lines affect the |
---|
| 2082 | baseline solution. |
---|
[1846] | 2083 | |
---|
[1280] | 2084 | chan_avg_limit: |
---|
| 2085 | a maximum number of consequtive spectral channels to |
---|
| 2086 | average during the search of weak and broad lines. |
---|
| 2087 | The default is no averaging (and no search for weak |
---|
| 2088 | lines). If such lines can affect the fitted baseline |
---|
| 2089 | (e.g. a high order polynomial is fitted), increase this |
---|
| 2090 | parameter (usually values up to 8 are reasonable). Most |
---|
| 2091 | users of this method should find the default value |
---|
| 2092 | sufficient. |
---|
[1846] | 2093 | |
---|
[1061] | 2094 | plot: plot the fit and the residual. In this each |
---|
| 2095 | indivual fit has to be approved, by typing 'y' |
---|
| 2096 | or 'n' |
---|
[1846] | 2097 | |
---|
[880] | 2098 | insitu: if False a new scantable is returned. |
---|
| 2099 | Otherwise, the scaling is done in-situ |
---|
| 2100 | The default is taken from .asaprc (False) |
---|
[1907] | 2101 | rows: row numbers of spectra to be processed. |
---|
| 2102 | (default is None: for all rows) |
---|
[880] | 2103 | |
---|
[1846] | 2104 | |
---|
| 2105 | Example:: |
---|
| 2106 | |
---|
| 2107 | scan2 = scan.auto_poly_baseline(order=7, insitu=False) |
---|
| 2108 | |
---|
[880] | 2109 | """ |
---|
| 2110 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2111 | varlist = vars() |
---|
| 2112 | from asap.asaplinefind import linefinder |
---|
| 2113 | from asap import _is_sequence_or_number as _is_valid |
---|
| 2114 | |
---|
[976] | 2115 | # check whether edge is set up for each IF individually |
---|
[1118] | 2116 | individualedge = False; |
---|
| 2117 | if len(edge) > 1: |
---|
| 2118 | if isinstance(edge[0], list) or isinstance(edge[0], tuple): |
---|
| 2119 | individualedge = True; |
---|
[907] | 2120 | |
---|
[1118] | 2121 | if not _is_valid(edge, int) and not individualedge: |
---|
[909] | 2122 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
[907] | 2123 | pair of integers specified as a tuple. Nested tuples are allowed \ |
---|
| 2124 | to make individual selection for different IFs." |
---|
[919] | 2125 | |
---|
[1118] | 2126 | curedge = (0, 0) |
---|
| 2127 | if individualedge: |
---|
| 2128 | for edgepar in edge: |
---|
| 2129 | if not _is_valid(edgepar, int): |
---|
| 2130 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 2131 | to be a pair of integers or an integer." |
---|
[907] | 2132 | else: |
---|
[1118] | 2133 | curedge = edge; |
---|
[880] | 2134 | |
---|
[1907] | 2135 | if not insitu: |
---|
| 2136 | workscan = self.copy() |
---|
| 2137 | else: |
---|
| 2138 | workscan = self |
---|
| 2139 | |
---|
[880] | 2140 | # setup fitter |
---|
| 2141 | f = fitter() |
---|
[1907] | 2142 | f.set_function(lpoly=order) |
---|
[880] | 2143 | |
---|
| 2144 | # setup line finder |
---|
[1118] | 2145 | fl = linefinder() |
---|
[1268] | 2146 | fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) |
---|
[880] | 2147 | |
---|
[907] | 2148 | fl.set_scan(workscan) |
---|
| 2149 | |
---|
[1907] | 2150 | if mask is None: |
---|
| 2151 | mask = _n_bools(workscan.nchan(), True) |
---|
| 2152 | |
---|
| 2153 | if rows is None: |
---|
| 2154 | rows = xrange(workscan.nrow()) |
---|
| 2155 | elif isinstance(rows, int): |
---|
| 2156 | rows = [ rows ] |
---|
| 2157 | |
---|
[1819] | 2158 | # Save parameters of baseline fits & masklists as a class attribute. |
---|
| 2159 | # NOTICE: It does not reflect changes in scantable! |
---|
| 2160 | if len(rows) > 0: |
---|
| 2161 | self.blpars=[] |
---|
| 2162 | self.masklists=[] |
---|
[1907] | 2163 | self.actualmask=[] |
---|
[880] | 2164 | asaplog.push("Processing:") |
---|
| 2165 | for r in rows: |
---|
[1118] | 2166 | msg = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % \ |
---|
| 2167 | (workscan.getscan(r), workscan.getbeam(r), workscan.getif(r), \ |
---|
| 2168 | workscan.getpol(r), workscan.getcycle(r)) |
---|
[880] | 2169 | asaplog.push(msg, False) |
---|
[907] | 2170 | |
---|
[976] | 2171 | # figure out edge parameter |
---|
[1118] | 2172 | if individualedge: |
---|
| 2173 | if len(edge) >= workscan.getif(r): |
---|
| 2174 | raise RuntimeError, "Number of edge elements appear to " \ |
---|
| 2175 | "be less than the number of IFs" |
---|
| 2176 | curedge = edge[workscan.getif(r)] |
---|
[919] | 2177 | |
---|
[1907] | 2178 | actualmask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
[1819] | 2179 | |
---|
[976] | 2180 | # setup line finder |
---|
[1819] | 2181 | fl.find_lines(r, actualmask, curedge) |
---|
[1907] | 2182 | |
---|
[1819] | 2183 | f.x = workscan._getabcissa(r) |
---|
| 2184 | f.y = workscan._getspectrum(r) |
---|
[1907] | 2185 | f.mask = fl.get_mask() |
---|
[1819] | 2186 | f.data = None |
---|
[880] | 2187 | f.fit() |
---|
[1819] | 2188 | |
---|
| 2189 | # Show mask list |
---|
[1924] | 2190 | masklist=workscan.get_masklist(f.mask, row=r, silent=True) |
---|
[1819] | 2191 | msg = "mask range: "+str(masklist) |
---|
| 2192 | asaplog.push(msg, False) |
---|
| 2193 | |
---|
[1061] | 2194 | if plot: |
---|
| 2195 | f.plot(residual=True) |
---|
| 2196 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2197 | if x.upper() == 'N': |
---|
[1819] | 2198 | self.blpars.append(None) |
---|
| 2199 | self.masklists.append(None) |
---|
[1907] | 2200 | self.actualmask.append(None) |
---|
[1061] | 2201 | continue |
---|
[1819] | 2202 | |
---|
[880] | 2203 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
[1819] | 2204 | self.blpars.append(f.get_parameters()) |
---|
| 2205 | self.masklists.append(masklist) |
---|
[1907] | 2206 | self.actualmask.append(f.mask) |
---|
[1061] | 2207 | if plot: |
---|
| 2208 | f._p.unmap() |
---|
| 2209 | f._p = None |
---|
| 2210 | workscan._add_history("auto_poly_baseline", varlist) |
---|
[880] | 2211 | if insitu: |
---|
| 2212 | self._assign(workscan) |
---|
| 2213 | else: |
---|
| 2214 | return workscan |
---|
| 2215 | |
---|
[1862] | 2216 | @asaplog_post_dec |
---|
[914] | 2217 | def rotate_linpolphase(self, angle): |
---|
[1846] | 2218 | """\ |
---|
[914] | 2219 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
| 2220 | This is always done in situ in the raw data. So if you call this |
---|
| 2221 | function more than once then each call rotates the phase further. |
---|
[1846] | 2222 | |
---|
[914] | 2223 | Parameters: |
---|
[1846] | 2224 | |
---|
[914] | 2225 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2226 | |
---|
| 2227 | Example:: |
---|
| 2228 | |
---|
[914] | 2229 | scan.rotate_linpolphase(2.3) |
---|
[1846] | 2230 | |
---|
[914] | 2231 | """ |
---|
| 2232 | varlist = vars() |
---|
[936] | 2233 | self._math._rotate_linpolphase(self, angle) |
---|
[914] | 2234 | self._add_history("rotate_linpolphase", varlist) |
---|
| 2235 | return |
---|
[710] | 2236 | |
---|
[1862] | 2237 | @asaplog_post_dec |
---|
[914] | 2238 | def rotate_xyphase(self, angle): |
---|
[1846] | 2239 | """\ |
---|
[914] | 2240 | Rotate the phase of the XY correlation. This is always done in situ |
---|
| 2241 | in the data. So if you call this function more than once |
---|
| 2242 | then each call rotates the phase further. |
---|
[1846] | 2243 | |
---|
[914] | 2244 | Parameters: |
---|
[1846] | 2245 | |
---|
[914] | 2246 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2247 | |
---|
| 2248 | Example:: |
---|
| 2249 | |
---|
[914] | 2250 | scan.rotate_xyphase(2.3) |
---|
[1846] | 2251 | |
---|
[914] | 2252 | """ |
---|
| 2253 | varlist = vars() |
---|
[936] | 2254 | self._math._rotate_xyphase(self, angle) |
---|
[914] | 2255 | self._add_history("rotate_xyphase", varlist) |
---|
| 2256 | return |
---|
| 2257 | |
---|
[1862] | 2258 | @asaplog_post_dec |
---|
[914] | 2259 | def swap_linears(self): |
---|
[1846] | 2260 | """\ |
---|
[1573] | 2261 | Swap the linear polarisations XX and YY, or better the first two |
---|
[1348] | 2262 | polarisations as this also works for ciculars. |
---|
[914] | 2263 | """ |
---|
| 2264 | varlist = vars() |
---|
[936] | 2265 | self._math._swap_linears(self) |
---|
[914] | 2266 | self._add_history("swap_linears", varlist) |
---|
| 2267 | return |
---|
| 2268 | |
---|
[1862] | 2269 | @asaplog_post_dec |
---|
[914] | 2270 | def invert_phase(self): |
---|
[1846] | 2271 | """\ |
---|
[914] | 2272 | Invert the phase of the complex polarisation |
---|
| 2273 | """ |
---|
| 2274 | varlist = vars() |
---|
[936] | 2275 | self._math._invert_phase(self) |
---|
[914] | 2276 | self._add_history("invert_phase", varlist) |
---|
| 2277 | return |
---|
| 2278 | |
---|
[1862] | 2279 | @asaplog_post_dec |
---|
[876] | 2280 | def add(self, offset, insitu=None): |
---|
[1846] | 2281 | """\ |
---|
[513] | 2282 | Return a scan where all spectra have the offset added |
---|
[1846] | 2283 | |
---|
[513] | 2284 | Parameters: |
---|
[1846] | 2285 | |
---|
[513] | 2286 | offset: the offset |
---|
[1855] | 2287 | |
---|
[513] | 2288 | insitu: if False a new scantable is returned. |
---|
| 2289 | Otherwise, the scaling is done in-situ |
---|
| 2290 | The default is taken from .asaprc (False) |
---|
[1846] | 2291 | |
---|
[513] | 2292 | """ |
---|
| 2293 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2294 | self._math._setinsitu(insitu) |
---|
[513] | 2295 | varlist = vars() |
---|
[876] | 2296 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
[1118] | 2297 | s._add_history("add", varlist) |
---|
[876] | 2298 | if insitu: |
---|
| 2299 | self._assign(s) |
---|
| 2300 | else: |
---|
[513] | 2301 | return s |
---|
| 2302 | |
---|
[1862] | 2303 | @asaplog_post_dec |
---|
[1308] | 2304 | def scale(self, factor, tsys=True, insitu=None): |
---|
[1846] | 2305 | """\ |
---|
| 2306 | |
---|
[513] | 2307 | Return a scan where all spectra are scaled by the give 'factor' |
---|
[1846] | 2308 | |
---|
[513] | 2309 | Parameters: |
---|
[1846] | 2310 | |
---|
[1819] | 2311 | factor: the scaling factor (float or 1D float list) |
---|
[1855] | 2312 | |
---|
[513] | 2313 | insitu: if False a new scantable is returned. |
---|
| 2314 | Otherwise, the scaling is done in-situ |
---|
| 2315 | The default is taken from .asaprc (False) |
---|
[1855] | 2316 | |
---|
[513] | 2317 | tsys: if True (default) then apply the operation to Tsys |
---|
| 2318 | as well as the data |
---|
[1846] | 2319 | |
---|
[513] | 2320 | """ |
---|
| 2321 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2322 | self._math._setinsitu(insitu) |
---|
[513] | 2323 | varlist = vars() |
---|
[1819] | 2324 | s = None |
---|
| 2325 | import numpy |
---|
| 2326 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
| 2327 | if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): |
---|
| 2328 | from asapmath import _array2dOp |
---|
| 2329 | s = _array2dOp( self.copy(), factor, "MUL", tsys ) |
---|
| 2330 | else: |
---|
| 2331 | s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) |
---|
| 2332 | else: |
---|
| 2333 | s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) |
---|
[1118] | 2334 | s._add_history("scale", varlist) |
---|
[876] | 2335 | if insitu: |
---|
| 2336 | self._assign(s) |
---|
| 2337 | else: |
---|
[513] | 2338 | return s |
---|
| 2339 | |
---|
[1504] | 2340 | def set_sourcetype(self, match, matchtype="pattern", |
---|
| 2341 | sourcetype="reference"): |
---|
[1846] | 2342 | """\ |
---|
[1502] | 2343 | Set the type of the source to be an source or reference scan |
---|
[1846] | 2344 | using the provided pattern. |
---|
| 2345 | |
---|
[1502] | 2346 | Parameters: |
---|
[1846] | 2347 | |
---|
[1504] | 2348 | match: a Unix style pattern, regular expression or selector |
---|
[1855] | 2349 | |
---|
[1504] | 2350 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
| 2351 | 'regex' regular expression |
---|
[1855] | 2352 | |
---|
[1502] | 2353 | sourcetype: the type of the source to use (source/reference) |
---|
[1846] | 2354 | |
---|
[1502] | 2355 | """ |
---|
| 2356 | varlist = vars() |
---|
| 2357 | basesel = self.get_selection() |
---|
| 2358 | stype = -1 |
---|
| 2359 | if sourcetype.lower().startswith("r"): |
---|
| 2360 | stype = 1 |
---|
| 2361 | elif sourcetype.lower().startswith("s"): |
---|
| 2362 | stype = 0 |
---|
[1504] | 2363 | else: |
---|
[1502] | 2364 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
[1504] | 2365 | if matchtype.lower().startswith("p"): |
---|
| 2366 | matchtype = "pattern" |
---|
| 2367 | elif matchtype.lower().startswith("r"): |
---|
| 2368 | matchtype = "regex" |
---|
| 2369 | else: |
---|
| 2370 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
[1502] | 2371 | sel = selector() |
---|
| 2372 | if isinstance(match, selector): |
---|
| 2373 | sel = match |
---|
| 2374 | else: |
---|
[1504] | 2375 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
[1502] | 2376 | self.set_selection(basesel+sel) |
---|
| 2377 | self._setsourcetype(stype) |
---|
| 2378 | self.set_selection(basesel) |
---|
[1573] | 2379 | self._add_history("set_sourcetype", varlist) |
---|
[1502] | 2380 | |
---|
[1862] | 2381 | @asaplog_post_dec |
---|
[1857] | 2382 | @preserve_selection |
---|
[1819] | 2383 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
[1846] | 2384 | """\ |
---|
[670] | 2385 | This function allows to build quotients automatically. |
---|
[1819] | 2386 | It assumes the observation to have the same number of |
---|
[670] | 2387 | "ons" and "offs" |
---|
[1846] | 2388 | |
---|
[670] | 2389 | Parameters: |
---|
[1846] | 2390 | |
---|
[710] | 2391 | preserve: you can preserve (default) the continuum or |
---|
| 2392 | remove it. The equations used are |
---|
[1857] | 2393 | |
---|
[670] | 2394 | preserve: Output = Toff * (on/off) - Toff |
---|
[1857] | 2395 | |
---|
[1070] | 2396 | remove: Output = Toff * (on/off) - Ton |
---|
[1855] | 2397 | |
---|
[1573] | 2398 | mode: the on/off detection mode |
---|
[1348] | 2399 | 'paired' (default) |
---|
| 2400 | identifies 'off' scans by the |
---|
| 2401 | trailing '_R' (Mopra/Parkes) or |
---|
| 2402 | '_e'/'_w' (Tid) and matches |
---|
| 2403 | on/off pairs from the observing pattern |
---|
[1502] | 2404 | 'time' |
---|
| 2405 | finds the closest off in time |
---|
[1348] | 2406 | |
---|
[1857] | 2407 | .. todo:: verify argument is not implemented |
---|
| 2408 | |
---|
[670] | 2409 | """ |
---|
[1857] | 2410 | varlist = vars() |
---|
[1348] | 2411 | modes = ["time", "paired"] |
---|
[670] | 2412 | if not mode in modes: |
---|
[876] | 2413 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
| 2414 | raise ValueError(msg) |
---|
[1348] | 2415 | s = None |
---|
| 2416 | if mode.lower() == "paired": |
---|
[1857] | 2417 | sel = self.get_selection() |
---|
[1875] | 2418 | sel.set_query("SRCTYPE==psoff") |
---|
[1356] | 2419 | self.set_selection(sel) |
---|
[1348] | 2420 | offs = self.copy() |
---|
[1875] | 2421 | sel.set_query("SRCTYPE==pson") |
---|
[1356] | 2422 | self.set_selection(sel) |
---|
[1348] | 2423 | ons = self.copy() |
---|
| 2424 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
| 2425 | elif mode.lower() == "time": |
---|
| 2426 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
[1118] | 2427 | s._add_history("auto_quotient", varlist) |
---|
[876] | 2428 | return s |
---|
[710] | 2429 | |
---|
[1862] | 2430 | @asaplog_post_dec |
---|
[1145] | 2431 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
[1846] | 2432 | """\ |
---|
[1143] | 2433 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
[1846] | 2434 | |
---|
[1143] | 2435 | Parameters: |
---|
[1846] | 2436 | |
---|
[1145] | 2437 | mask: an optional mask to be used when weight == 'stddev' |
---|
[1855] | 2438 | |
---|
[1143] | 2439 | weight: How to average the off beams. Default is 'median'. |
---|
[1855] | 2440 | |
---|
[1145] | 2441 | preserve: you can preserve (default) the continuum or |
---|
[1855] | 2442 | remove it. The equations used are: |
---|
[1846] | 2443 | |
---|
[1855] | 2444 | preserve: Output = Toff * (on/off) - Toff |
---|
| 2445 | |
---|
| 2446 | remove: Output = Toff * (on/off) - Ton |
---|
| 2447 | |
---|
[1217] | 2448 | """ |
---|
[1593] | 2449 | mask = mask or () |
---|
[1141] | 2450 | varlist = vars() |
---|
| 2451 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
[1143] | 2452 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
| 2453 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
[1217] | 2454 | from asapmath import quotient |
---|
[1145] | 2455 | q = quotient(on, off, preserve) |
---|
[1143] | 2456 | q._add_history("mx_quotient", varlist) |
---|
[1217] | 2457 | return q |
---|
[513] | 2458 | |
---|
[1862] | 2459 | @asaplog_post_dec |
---|
[718] | 2460 | def freq_switch(self, insitu=None): |
---|
[1846] | 2461 | """\ |
---|
[718] | 2462 | Apply frequency switching to the data. |
---|
[1846] | 2463 | |
---|
[718] | 2464 | Parameters: |
---|
[1846] | 2465 | |
---|
[718] | 2466 | insitu: if False a new scantable is returned. |
---|
| 2467 | Otherwise, the swictching is done in-situ |
---|
| 2468 | The default is taken from .asaprc (False) |
---|
[1846] | 2469 | |
---|
[718] | 2470 | """ |
---|
| 2471 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2472 | self._math._setinsitu(insitu) |
---|
[718] | 2473 | varlist = vars() |
---|
[876] | 2474 | s = scantable(self._math._freqswitch(self)) |
---|
[1118] | 2475 | s._add_history("freq_switch", varlist) |
---|
[1856] | 2476 | if insitu: |
---|
| 2477 | self._assign(s) |
---|
| 2478 | else: |
---|
| 2479 | return s |
---|
[718] | 2480 | |
---|
[1862] | 2481 | @asaplog_post_dec |
---|
[780] | 2482 | def recalc_azel(self): |
---|
[1846] | 2483 | """Recalculate the azimuth and elevation for each position.""" |
---|
[780] | 2484 | varlist = vars() |
---|
[876] | 2485 | self._recalcazel() |
---|
[780] | 2486 | self._add_history("recalc_azel", varlist) |
---|
| 2487 | return |
---|
| 2488 | |
---|
[1862] | 2489 | @asaplog_post_dec |
---|
[513] | 2490 | def __add__(self, other): |
---|
| 2491 | varlist = vars() |
---|
| 2492 | s = None |
---|
| 2493 | if isinstance(other, scantable): |
---|
[1573] | 2494 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
[513] | 2495 | elif isinstance(other, float): |
---|
[876] | 2496 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
[513] | 2497 | else: |
---|
[718] | 2498 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2499 | s._add_history("operator +", varlist) |
---|
| 2500 | return s |
---|
| 2501 | |
---|
[1862] | 2502 | @asaplog_post_dec |
---|
[513] | 2503 | def __sub__(self, other): |
---|
| 2504 | """ |
---|
| 2505 | implicit on all axes and on Tsys |
---|
| 2506 | """ |
---|
| 2507 | varlist = vars() |
---|
| 2508 | s = None |
---|
| 2509 | if isinstance(other, scantable): |
---|
[1588] | 2510 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
[513] | 2511 | elif isinstance(other, float): |
---|
[876] | 2512 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
[513] | 2513 | else: |
---|
[718] | 2514 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2515 | s._add_history("operator -", varlist) |
---|
| 2516 | return s |
---|
[710] | 2517 | |
---|
[1862] | 2518 | @asaplog_post_dec |
---|
[513] | 2519 | def __mul__(self, other): |
---|
| 2520 | """ |
---|
| 2521 | implicit on all axes and on Tsys |
---|
| 2522 | """ |
---|
| 2523 | varlist = vars() |
---|
| 2524 | s = None |
---|
| 2525 | if isinstance(other, scantable): |
---|
[1588] | 2526 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
[513] | 2527 | elif isinstance(other, float): |
---|
[876] | 2528 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
[513] | 2529 | else: |
---|
[718] | 2530 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2531 | s._add_history("operator *", varlist) |
---|
| 2532 | return s |
---|
| 2533 | |
---|
[710] | 2534 | |
---|
[1862] | 2535 | @asaplog_post_dec |
---|
[513] | 2536 | def __div__(self, other): |
---|
| 2537 | """ |
---|
| 2538 | implicit on all axes and on Tsys |
---|
| 2539 | """ |
---|
| 2540 | varlist = vars() |
---|
| 2541 | s = None |
---|
| 2542 | if isinstance(other, scantable): |
---|
[1589] | 2543 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
[513] | 2544 | elif isinstance(other, float): |
---|
| 2545 | if other == 0.0: |
---|
[718] | 2546 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
[876] | 2547 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
[513] | 2548 | else: |
---|
[718] | 2549 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2550 | s._add_history("operator /", varlist) |
---|
| 2551 | return s |
---|
| 2552 | |
---|
[1862] | 2553 | @asaplog_post_dec |
---|
[530] | 2554 | def get_fit(self, row=0): |
---|
[1846] | 2555 | """\ |
---|
[530] | 2556 | Print or return the stored fits for a row in the scantable |
---|
[1846] | 2557 | |
---|
[530] | 2558 | Parameters: |
---|
[1846] | 2559 | |
---|
[530] | 2560 | row: the row which the fit has been applied to. |
---|
[1846] | 2561 | |
---|
[530] | 2562 | """ |
---|
| 2563 | if row > self.nrow(): |
---|
| 2564 | return |
---|
[976] | 2565 | from asap.asapfit import asapfit |
---|
[530] | 2566 | fit = asapfit(self._getfit(row)) |
---|
[1859] | 2567 | asaplog.push( '%s' %(fit) ) |
---|
| 2568 | return fit.as_dict() |
---|
[530] | 2569 | |
---|
[1483] | 2570 | def flag_nans(self): |
---|
[1846] | 2571 | """\ |
---|
[1483] | 2572 | Utility function to flag NaN values in the scantable. |
---|
| 2573 | """ |
---|
| 2574 | import numpy |
---|
| 2575 | basesel = self.get_selection() |
---|
| 2576 | for i in range(self.nrow()): |
---|
[1589] | 2577 | sel = self.get_row_selector(i) |
---|
| 2578 | self.set_selection(basesel+sel) |
---|
[1483] | 2579 | nans = numpy.isnan(self._getspectrum(0)) |
---|
| 2580 | if numpy.any(nans): |
---|
| 2581 | bnans = [ bool(v) for v in nans] |
---|
| 2582 | self.flag(bnans) |
---|
| 2583 | self.set_selection(basesel) |
---|
| 2584 | |
---|
[1588] | 2585 | def get_row_selector(self, rowno): |
---|
| 2586 | return selector(beams=self.getbeam(rowno), |
---|
| 2587 | ifs=self.getif(rowno), |
---|
| 2588 | pols=self.getpol(rowno), |
---|
| 2589 | scans=self.getscan(rowno), |
---|
| 2590 | cycles=self.getcycle(rowno)) |
---|
[1573] | 2591 | |
---|
[484] | 2592 | def _add_history(self, funcname, parameters): |
---|
[1435] | 2593 | if not rcParams['scantable.history']: |
---|
| 2594 | return |
---|
[484] | 2595 | # create date |
---|
| 2596 | sep = "##" |
---|
| 2597 | from datetime import datetime |
---|
| 2598 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
| 2599 | hist = dstr+sep |
---|
| 2600 | hist += funcname+sep#cdate+sep |
---|
| 2601 | if parameters.has_key('self'): del parameters['self'] |
---|
[1118] | 2602 | for k, v in parameters.iteritems(): |
---|
[484] | 2603 | if type(v) is dict: |
---|
[1118] | 2604 | for k2, v2 in v.iteritems(): |
---|
[484] | 2605 | hist += k2 |
---|
| 2606 | hist += "=" |
---|
[1118] | 2607 | if isinstance(v2, scantable): |
---|
[484] | 2608 | hist += 'scantable' |
---|
| 2609 | elif k2 == 'mask': |
---|
[1118] | 2610 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
[513] | 2611 | hist += str(self._zip_mask(v2)) |
---|
| 2612 | else: |
---|
| 2613 | hist += str(v2) |
---|
[484] | 2614 | else: |
---|
[513] | 2615 | hist += str(v2) |
---|
[484] | 2616 | else: |
---|
| 2617 | hist += k |
---|
| 2618 | hist += "=" |
---|
[1118] | 2619 | if isinstance(v, scantable): |
---|
[484] | 2620 | hist += 'scantable' |
---|
| 2621 | elif k == 'mask': |
---|
[1118] | 2622 | if isinstance(v, list) or isinstance(v, tuple): |
---|
[513] | 2623 | hist += str(self._zip_mask(v)) |
---|
| 2624 | else: |
---|
| 2625 | hist += str(v) |
---|
[484] | 2626 | else: |
---|
| 2627 | hist += str(v) |
---|
| 2628 | hist += sep |
---|
| 2629 | hist = hist[:-2] # remove trailing '##' |
---|
| 2630 | self._addhistory(hist) |
---|
| 2631 | |
---|
[710] | 2632 | |
---|
[484] | 2633 | def _zip_mask(self, mask): |
---|
| 2634 | mask = list(mask) |
---|
| 2635 | i = 0 |
---|
| 2636 | segments = [] |
---|
| 2637 | while mask[i:].count(1): |
---|
| 2638 | i += mask[i:].index(1) |
---|
| 2639 | if mask[i:].count(0): |
---|
| 2640 | j = i + mask[i:].index(0) |
---|
| 2641 | else: |
---|
[710] | 2642 | j = len(mask) |
---|
[1118] | 2643 | segments.append([i, j]) |
---|
[710] | 2644 | i = j |
---|
[484] | 2645 | return segments |
---|
[714] | 2646 | |
---|
[626] | 2647 | def _get_ordinate_label(self): |
---|
| 2648 | fu = "("+self.get_fluxunit()+")" |
---|
| 2649 | import re |
---|
| 2650 | lbl = "Intensity" |
---|
[1118] | 2651 | if re.match(".K.", fu): |
---|
[626] | 2652 | lbl = "Brightness Temperature "+ fu |
---|
[1118] | 2653 | elif re.match(".Jy.", fu): |
---|
[626] | 2654 | lbl = "Flux density "+ fu |
---|
| 2655 | return lbl |
---|
[710] | 2656 | |
---|
[876] | 2657 | def _check_ifs(self): |
---|
| 2658 | nchans = [self.nchan(i) for i in range(self.nif(-1))] |
---|
[889] | 2659 | nchans = filter(lambda t: t > 0, nchans) |
---|
[876] | 2660 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
[976] | 2661 | |
---|
[1862] | 2662 | @asaplog_post_dec |
---|
[1916] | 2663 | #def _fill(self, names, unit, average, getpt, antenna): |
---|
| 2664 | def _fill(self, names, unit, average, opts={}): |
---|
[976] | 2665 | first = True |
---|
| 2666 | fullnames = [] |
---|
| 2667 | for name in names: |
---|
| 2668 | name = os.path.expandvars(name) |
---|
| 2669 | name = os.path.expanduser(name) |
---|
| 2670 | if not os.path.exists(name): |
---|
| 2671 | msg = "File '%s' does not exists" % (name) |
---|
| 2672 | raise IOError(msg) |
---|
| 2673 | fullnames.append(name) |
---|
| 2674 | if average: |
---|
| 2675 | asaplog.push('Auto averaging integrations') |
---|
[1079] | 2676 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
[976] | 2677 | for name in fullnames: |
---|
[1073] | 2678 | tbl = Scantable(stype) |
---|
[1843] | 2679 | r = filler(tbl) |
---|
[1504] | 2680 | rx = rcParams['scantable.reference'] |
---|
[1843] | 2681 | r.setreferenceexpr(rx) |
---|
[976] | 2682 | msg = "Importing %s..." % (name) |
---|
[1118] | 2683 | asaplog.push(msg, False) |
---|
[1916] | 2684 | #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } |
---|
[1904] | 2685 | r.open(name, opts)# antenna, -1, -1, getpt) |
---|
[1843] | 2686 | r.fill() |
---|
[976] | 2687 | if average: |
---|
[1118] | 2688 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
[976] | 2689 | if not first: |
---|
| 2690 | tbl = self._math._merge([self, tbl]) |
---|
| 2691 | Scantable.__init__(self, tbl) |
---|
[1843] | 2692 | r.close() |
---|
[1118] | 2693 | del r, tbl |
---|
[976] | 2694 | first = False |
---|
[1861] | 2695 | #flush log |
---|
| 2696 | asaplog.post() |
---|
[976] | 2697 | if unit is not None: |
---|
| 2698 | self.set_fluxunit(unit) |
---|
[1824] | 2699 | if not is_casapy(): |
---|
| 2700 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[976] | 2701 | |
---|
[1402] | 2702 | def __getitem__(self, key): |
---|
| 2703 | if key < 0: |
---|
| 2704 | key += self.nrow() |
---|
| 2705 | if key >= self.nrow(): |
---|
| 2706 | raise IndexError("Row index out of range.") |
---|
| 2707 | return self._getspectrum(key) |
---|
| 2708 | |
---|
| 2709 | def __setitem__(self, key, value): |
---|
| 2710 | if key < 0: |
---|
| 2711 | key += self.nrow() |
---|
| 2712 | if key >= self.nrow(): |
---|
| 2713 | raise IndexError("Row index out of range.") |
---|
| 2714 | if not hasattr(value, "__len__") or \ |
---|
| 2715 | len(value) > self.nchan(self.getif(key)): |
---|
| 2716 | raise ValueError("Spectrum length doesn't match.") |
---|
| 2717 | return self._setspectrum(value, key) |
---|
| 2718 | |
---|
| 2719 | def __len__(self): |
---|
| 2720 | return self.nrow() |
---|
| 2721 | |
---|
| 2722 | def __iter__(self): |
---|
| 2723 | for i in range(len(self)): |
---|
| 2724 | yield self[i] |
---|