[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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| 112 | antenna: Antenna selection. integer (id) or string (name or id). |
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| 113 | |
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| 114 | parallactify: Indicate that the data had been parallatified. Default |
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| 115 | is taken from rc file. |
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| 116 | |
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[710] | 117 | """ |
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[976] | 118 | if average is None: |
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[710] | 119 | average = rcParams['scantable.autoaverage'] |
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[1916] | 120 | #if getpt is None: |
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| 121 | # getpt = True |
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| 122 | #if antenna is not None: |
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| 123 | # asaplog.push("Antenna selection currently unsupported." |
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| 124 | # "Using ''") |
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| 125 | # asaplog.post('WARN') |
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| 126 | #if antenna is None: |
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| 127 | # antenna = '' |
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| 128 | #elif type(antenna) == int: |
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| 129 | # antenna = '%s' % antenna |
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| 130 | #elif type(antenna) == list: |
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| 131 | # tmpstr = '' |
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| 132 | # for i in range( len(antenna) ): |
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| 133 | # if type(antenna[i]) == int: |
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| 134 | # tmpstr = tmpstr + ('%s,'%(antenna[i])) |
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| 135 | # elif type(antenna[i]) == str: |
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| 136 | # tmpstr=tmpstr+antenna[i]+',' |
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| 137 | # else: |
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| 138 | # raise TypeError('Bad antenna selection.') |
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| 139 | # antenna = tmpstr.rstrip(',') |
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[1593] | 140 | parallactify = parallactify or rcParams['scantable.parallactify'] |
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[1259] | 141 | varlist = vars() |
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[876] | 142 | from asap._asap import stmath |
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[1819] | 143 | self._math = stmath( rcParams['insitu'] ) |
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[876] | 144 | if isinstance(filename, Scantable): |
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| 145 | Scantable.__init__(self, filename) |
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[181] | 146 | else: |
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[1697] | 147 | if isinstance(filename, str): |
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[976] | 148 | filename = os.path.expandvars(filename) |
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| 149 | filename = os.path.expanduser(filename) |
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| 150 | if not os.path.exists(filename): |
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| 151 | s = "File '%s' not found." % (filename) |
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| 152 | raise IOError(s) |
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[1697] | 153 | if is_scantable(filename): |
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| 154 | ondisk = rcParams['scantable.storage'] == 'disk' |
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| 155 | Scantable.__init__(self, filename, ondisk) |
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| 156 | if unit is not None: |
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| 157 | self.set_fluxunit(unit) |
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[1819] | 158 | # do not reset to the default freqframe |
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| 159 | #self.set_freqframe(rcParams['scantable.freqframe']) |
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[1883] | 160 | #elif os.path.isdir(filename) \ |
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| 161 | # and not os.path.exists(filename+'/table.f1'): |
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| 162 | elif is_ms(filename): |
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[1916] | 163 | # Measurement Set |
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| 164 | opts={'ms': {}} |
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| 165 | mskeys=['getpt','antenna'] |
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| 166 | for key in mskeys: |
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| 167 | if key in args.keys(): |
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| 168 | opts['ms'][key] = args[key] |
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| 169 | #self._fill([filename], unit, average, getpt, antenna) |
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| 170 | self._fill([filename], unit, average, opts) |
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[1893] | 171 | elif os.path.isfile(filename): |
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[1916] | 172 | #self._fill([filename], unit, average, getpt, antenna) |
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| 173 | self._fill([filename], unit, average) |
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[1883] | 174 | else: |
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[1819] | 175 | msg = "The given file '%s'is not a valid " \ |
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| 176 | "asap table." % (filename) |
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[1859] | 177 | raise IOError(msg) |
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[1118] | 178 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
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[976] | 179 | and isinstance(filename[-1], str): |
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[1916] | 180 | #self._fill(filename, unit, average, getpt, antenna) |
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| 181 | self._fill(filename, unit, average) |
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[1586] | 182 | self.parallactify(parallactify) |
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[1259] | 183 | self._add_history("scantable", varlist) |
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[102] | 184 | |
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[1862] | 185 | @asaplog_post_dec |
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[876] | 186 | def save(self, name=None, format=None, overwrite=False): |
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[1846] | 187 | """\ |
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[1280] | 188 | Store the scantable on disk. This can be an asap (aips++) Table, |
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| 189 | SDFITS or MS2 format. |
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[1846] | 190 | |
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[116] | 191 | Parameters: |
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[1846] | 192 | |
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[1093] | 193 | name: the name of the outputfile. For format "ASCII" |
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| 194 | this is the root file name (data in 'name'.txt |
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[497] | 195 | and header in 'name'_header.txt) |
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[1855] | 196 | |
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[116] | 197 | format: an optional file format. Default is ASAP. |
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[1855] | 198 | Allowed are: |
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| 199 | |
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| 200 | * 'ASAP' (save as ASAP [aips++] Table), |
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| 201 | * 'SDFITS' (save as SDFITS file) |
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| 202 | * 'ASCII' (saves as ascii text file) |
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| 203 | * 'MS2' (saves as an casacore MeasurementSet V2) |
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| 204 | * 'FITS' (save as image FITS - not readable by class) |
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| 205 | * 'CLASS' (save as FITS readable by CLASS) |
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| 206 | |
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[411] | 207 | overwrite: If the file should be overwritten if it exists. |
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[256] | 208 | The default False is to return with warning |
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[411] | 209 | without writing the output. USE WITH CARE. |
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[1855] | 210 | |
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[1846] | 211 | Example:: |
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| 212 | |
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[116] | 213 | scan.save('myscan.asap') |
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[1118] | 214 | scan.save('myscan.sdfits', 'SDFITS') |
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[1846] | 215 | |
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[116] | 216 | """ |
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[411] | 217 | from os import path |
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[1593] | 218 | format = format or rcParams['scantable.save'] |
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[256] | 219 | suffix = '.'+format.lower() |
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[1118] | 220 | if name is None or name == "": |
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[256] | 221 | name = 'scantable'+suffix |
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[718] | 222 | msg = "No filename given. Using default name %s..." % name |
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| 223 | asaplog.push(msg) |
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[411] | 224 | name = path.expandvars(name) |
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[256] | 225 | if path.isfile(name) or path.isdir(name): |
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| 226 | if not overwrite: |
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[718] | 227 | msg = "File %s exists." % name |
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[1859] | 228 | raise IOError(msg) |
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[451] | 229 | format2 = format.upper() |
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| 230 | if format2 == 'ASAP': |
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[116] | 231 | self._save(name) |
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| 232 | else: |
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[989] | 233 | from asap._asap import stwriter as stw |
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[1118] | 234 | writer = stw(format2) |
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| 235 | writer.write(self, name) |
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[116] | 236 | return |
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| 237 | |
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[102] | 238 | def copy(self): |
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[1846] | 239 | """Return a copy of this scantable. |
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| 240 | |
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| 241 | *Note*: |
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| 242 | |
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[1348] | 243 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
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[1846] | 244 | |
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| 245 | Example:: |
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| 246 | |
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[102] | 247 | copiedscan = scan.copy() |
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[1846] | 248 | |
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[102] | 249 | """ |
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[876] | 250 | sd = scantable(Scantable._copy(self)) |
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[113] | 251 | return sd |
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| 252 | |
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[1093] | 253 | def drop_scan(self, scanid=None): |
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[1846] | 254 | """\ |
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[1093] | 255 | Return a new scantable where the specified scan number(s) has(have) |
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| 256 | been dropped. |
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[1846] | 257 | |
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[1093] | 258 | Parameters: |
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[1846] | 259 | |
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[1093] | 260 | scanid: a (list of) scan number(s) |
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[1846] | 261 | |
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[1093] | 262 | """ |
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| 263 | from asap import _is_sequence_or_number as _is_valid |
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| 264 | from asap import _to_list |
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| 265 | from asap import unique |
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| 266 | if not _is_valid(scanid): |
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[1859] | 267 | raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) |
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| 268 | scanid = _to_list(scanid) |
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| 269 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
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| 270 | for sid in scanid: allscans.remove(sid) |
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| 271 | if len(allscans) == 0: |
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| 272 | raise ValueError("Can't remove all scans") |
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| 273 | sel = selector(scans=allscans) |
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| 274 | return self._select_copy(sel) |
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[1093] | 275 | |
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[1594] | 276 | def _select_copy(self, selection): |
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| 277 | orig = self.get_selection() |
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| 278 | self.set_selection(orig+selection) |
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| 279 | cp = self.copy() |
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| 280 | self.set_selection(orig) |
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| 281 | return cp |
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| 282 | |
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[102] | 283 | def get_scan(self, scanid=None): |
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[1855] | 284 | """\ |
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[102] | 285 | Return a specific scan (by scanno) or collection of scans (by |
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| 286 | source name) in a new scantable. |
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[1846] | 287 | |
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| 288 | *Note*: |
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| 289 | |
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[1348] | 290 | See scantable.drop_scan() for the inverse operation. |
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[1846] | 291 | |
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[102] | 292 | Parameters: |
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[1846] | 293 | |
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[513] | 294 | scanid: a (list of) scanno or a source name, unix-style |
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| 295 | patterns are accepted for source name matching, e.g. |
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| 296 | '*_R' gets all 'ref scans |
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[1846] | 297 | |
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| 298 | Example:: |
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| 299 | |
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[513] | 300 | # get all scans containing the source '323p459' |
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| 301 | newscan = scan.get_scan('323p459') |
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| 302 | # get all 'off' scans |
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| 303 | refscans = scan.get_scan('*_R') |
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| 304 | # get a susbset of scans by scanno (as listed in scan.summary()) |
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[1118] | 305 | newscan = scan.get_scan([0, 2, 7, 10]) |
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[1846] | 306 | |
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[102] | 307 | """ |
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| 308 | if scanid is None: |
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[1859] | 309 | raise RuntimeError( 'Please specify a scan no or name to ' |
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| 310 | 'retrieve from the scantable' ) |
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[102] | 311 | try: |
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[946] | 312 | bsel = self.get_selection() |
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| 313 | sel = selector() |
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[102] | 314 | if type(scanid) is str: |
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[946] | 315 | sel.set_name(scanid) |
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[1594] | 316 | return self._select_copy(sel) |
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[102] | 317 | elif type(scanid) is int: |
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[946] | 318 | sel.set_scans([scanid]) |
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[1594] | 319 | return self._select_copy(sel) |
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[381] | 320 | elif type(scanid) is list: |
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[946] | 321 | sel.set_scans(scanid) |
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[1594] | 322 | return self._select_copy(sel) |
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[381] | 323 | else: |
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[718] | 324 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
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[1859] | 325 | raise TypeError(msg) |
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[102] | 326 | except RuntimeError: |
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[1859] | 327 | raise |
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[102] | 328 | |
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| 329 | def __str__(self): |
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[1118] | 330 | return Scantable._summary(self, True) |
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[102] | 331 | |
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[976] | 332 | def summary(self, filename=None): |
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[1846] | 333 | """\ |
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[102] | 334 | Print a summary of the contents of this scantable. |
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[1846] | 335 | |
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[102] | 336 | Parameters: |
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[1846] | 337 | |
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[102] | 338 | filename: the name of a file to write the putput to |
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| 339 | Default - no file output |
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[1846] | 340 | |
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[102] | 341 | """ |
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[976] | 342 | info = Scantable._summary(self, True) |
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[102] | 343 | if filename is not None: |
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[256] | 344 | if filename is "": |
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| 345 | filename = 'scantable_summary.txt' |
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[415] | 346 | from os.path import expandvars, isdir |
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[411] | 347 | filename = expandvars(filename) |
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[415] | 348 | if not isdir(filename): |
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[413] | 349 | data = open(filename, 'w') |
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| 350 | data.write(info) |
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| 351 | data.close() |
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| 352 | else: |
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[718] | 353 | msg = "Illegal file name '%s'." % (filename) |
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[1859] | 354 | raise IOError(msg) |
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| 355 | return page(info) |
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[710] | 356 | |
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[1512] | 357 | def get_spectrum(self, rowno): |
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[1471] | 358 | """Return the spectrum for the current row in the scantable as a list. |
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[1846] | 359 | |
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[1471] | 360 | Parameters: |
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[1846] | 361 | |
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[1573] | 362 | rowno: the row number to retrieve the spectrum from |
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[1846] | 363 | |
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[1471] | 364 | """ |
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| 365 | return self._getspectrum(rowno) |
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[946] | 366 | |
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[1471] | 367 | def get_mask(self, rowno): |
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| 368 | """Return the mask for the current row in the scantable as a list. |
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[1846] | 369 | |
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[1471] | 370 | Parameters: |
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[1846] | 371 | |
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[1573] | 372 | rowno: the row number to retrieve the mask from |
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[1846] | 373 | |
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[1471] | 374 | """ |
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| 375 | return self._getmask(rowno) |
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| 376 | |
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| 377 | def set_spectrum(self, spec, rowno): |
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| 378 | """Return the spectrum for the current row in the scantable as a list. |
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[1846] | 379 | |
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[1471] | 380 | Parameters: |
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[1846] | 381 | |
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[1855] | 382 | spec: the new spectrum |
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[1846] | 383 | |
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[1855] | 384 | rowno: the row number to set the spectrum for |
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| 385 | |
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[1471] | 386 | """ |
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| 387 | assert(len(spec) == self.nchan()) |
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| 388 | return self._setspectrum(spec, rowno) |
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| 389 | |
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[1600] | 390 | def get_coordinate(self, rowno): |
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| 391 | """Return the (spectral) coordinate for a a given 'rowno'. |
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[1846] | 392 | |
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| 393 | *Note*: |
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| 394 | |
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[1600] | 395 | * This coordinate is only valid until a scantable method modifies |
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| 396 | the frequency axis. |
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| 397 | * This coordinate does contain the original frequency set-up |
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| 398 | NOT the new frame. The conversions however are done using the user |
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| 399 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
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| 400 | use scantable.freq_align first. Without it there is no closure, |
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[1846] | 401 | i.e.:: |
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[1600] | 402 | |
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[1846] | 403 | c = myscan.get_coordinate(0) |
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| 404 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
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| 405 | |
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[1600] | 406 | Parameters: |
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[1846] | 407 | |
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[1600] | 408 | rowno: the row number for the spectral coordinate |
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| 409 | |
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| 410 | """ |
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| 411 | return coordinate(Scantable.get_coordinate(self, rowno)) |
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| 412 | |
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[946] | 413 | def get_selection(self): |
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[1846] | 414 | """\ |
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[1005] | 415 | Get the selection object currently set on this scantable. |
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[1846] | 416 | |
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| 417 | Example:: |
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| 418 | |
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[1005] | 419 | sel = scan.get_selection() |
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| 420 | sel.set_ifs(0) # select IF 0 |
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| 421 | scan.set_selection(sel) # apply modified selection |
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[1846] | 422 | |
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[946] | 423 | """ |
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| 424 | return selector(self._getselection()) |
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| 425 | |
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[1576] | 426 | def set_selection(self, selection=None, **kw): |
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[1846] | 427 | """\ |
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[1005] | 428 | Select a subset of the data. All following operations on this scantable |
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| 429 | are only applied to thi selection. |
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[1846] | 430 | |
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[1005] | 431 | Parameters: |
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[1697] | 432 | |
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[1846] | 433 | selection: a selector object (default unset the selection), or |
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| 434 | any combination of "pols", "ifs", "beams", "scans", |
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| 435 | "cycles", "name", "query" |
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[1697] | 436 | |
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[1846] | 437 | Examples:: |
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[1697] | 438 | |
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[1005] | 439 | sel = selector() # create a selection object |
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[1118] | 440 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
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[1005] | 441 | scan.set_selection(sel) # set the selection |
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| 442 | scan.summary() # will only print summary of scanno 0 an 3 |
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| 443 | scan.set_selection() # unset the selection |
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[1697] | 444 | # or the equivalent |
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| 445 | scan.set_selection(scans=[0,3]) |
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| 446 | scan.summary() # will only print summary of scanno 0 an 3 |
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| 447 | scan.set_selection() # unset the selection |
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[1846] | 448 | |
---|
[946] | 449 | """ |
---|
[1576] | 450 | if selection is None: |
---|
| 451 | # reset |
---|
| 452 | if len(kw) == 0: |
---|
| 453 | selection = selector() |
---|
| 454 | else: |
---|
| 455 | # try keywords |
---|
| 456 | for k in kw: |
---|
| 457 | if k not in selector.fields: |
---|
| 458 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
| 459 | selection = selector(**kw) |
---|
[946] | 460 | self._setselection(selection) |
---|
| 461 | |
---|
[1819] | 462 | def get_row(self, row=0, insitu=None): |
---|
[1846] | 463 | """\ |
---|
[1819] | 464 | Select a row in the scantable. |
---|
| 465 | Return a scantable with single row. |
---|
[1846] | 466 | |
---|
[1819] | 467 | Parameters: |
---|
[1846] | 468 | |
---|
| 469 | row: row no of integration, default is 0. |
---|
| 470 | insitu: if False a new scantable is returned. Otherwise, the |
---|
| 471 | scaling is done in-situ. The default is taken from .asaprc |
---|
| 472 | (False) |
---|
| 473 | |
---|
[1819] | 474 | """ |
---|
| 475 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 476 | if not insitu: |
---|
| 477 | workscan = self.copy() |
---|
| 478 | else: |
---|
| 479 | workscan = self |
---|
| 480 | # Select a row |
---|
| 481 | sel=selector() |
---|
| 482 | sel.set_scans([workscan.getscan(row)]) |
---|
| 483 | sel.set_cycles([workscan.getcycle(row)]) |
---|
| 484 | sel.set_beams([workscan.getbeam(row)]) |
---|
| 485 | sel.set_ifs([workscan.getif(row)]) |
---|
| 486 | sel.set_polarisations([workscan.getpol(row)]) |
---|
| 487 | sel.set_name(workscan._getsourcename(row)) |
---|
| 488 | workscan.set_selection(sel) |
---|
| 489 | if not workscan.nrow() == 1: |
---|
| 490 | msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) |
---|
| 491 | raise RuntimeError(msg) |
---|
| 492 | del sel |
---|
| 493 | if insitu: |
---|
| 494 | self._assign(workscan) |
---|
| 495 | else: |
---|
| 496 | return workscan |
---|
| 497 | |
---|
[1862] | 498 | @asaplog_post_dec |
---|
[1907] | 499 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
---|
[1846] | 500 | """\ |
---|
[135] | 501 | Determine the specified statistic of the current beam/if/pol |
---|
[102] | 502 | Takes a 'mask' as an optional parameter to specify which |
---|
| 503 | channels should be excluded. |
---|
[1846] | 504 | |
---|
[102] | 505 | Parameters: |
---|
[1846] | 506 | |
---|
[1819] | 507 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
---|
| 508 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
---|
[1855] | 509 | |
---|
[135] | 510 | mask: an optional mask specifying where the statistic |
---|
[102] | 511 | should be determined. |
---|
[1855] | 512 | |
---|
[1819] | 513 | form: format string to print statistic values |
---|
[1846] | 514 | |
---|
[1907] | 515 | row: row number of spectrum to process. |
---|
| 516 | (default is None: for all rows) |
---|
[1846] | 517 | |
---|
[1907] | 518 | Example: |
---|
[113] | 519 | scan.set_unit('channel') |
---|
[1118] | 520 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 521 | scan.stats(stat='mean', mask=m) |
---|
[1846] | 522 | |
---|
[102] | 523 | """ |
---|
[1593] | 524 | mask = mask or [] |
---|
[876] | 525 | if not self._check_ifs(): |
---|
[1118] | 526 | raise ValueError("Cannot apply mask as the IFs have different " |
---|
| 527 | "number of channels. Please use setselection() " |
---|
| 528 | "to select individual IFs") |
---|
[1819] | 529 | rtnabc = False |
---|
| 530 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
| 531 | getchan = False |
---|
| 532 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
| 533 | chan = self._math._minmaxchan(self, mask, stat) |
---|
| 534 | getchan = True |
---|
| 535 | statvals = [] |
---|
[1907] | 536 | if not rtnabc: |
---|
| 537 | if row == None: |
---|
| 538 | statvals = self._math._stats(self, mask, stat) |
---|
| 539 | else: |
---|
| 540 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
[256] | 541 | |
---|
[1819] | 542 | #def cb(i): |
---|
| 543 | # return statvals[i] |
---|
[256] | 544 | |
---|
[1819] | 545 | #return self._row_callback(cb, stat) |
---|
[102] | 546 | |
---|
[1819] | 547 | label=stat |
---|
| 548 | #callback=cb |
---|
| 549 | out = "" |
---|
| 550 | #outvec = [] |
---|
| 551 | sep = '-'*50 |
---|
[1907] | 552 | |
---|
| 553 | if row == None: |
---|
| 554 | rows = xrange(self.nrow()) |
---|
| 555 | elif isinstance(row, int): |
---|
| 556 | rows = [ row ] |
---|
| 557 | |
---|
| 558 | for i in rows: |
---|
[1819] | 559 | refstr = '' |
---|
| 560 | statunit= '' |
---|
| 561 | if getchan: |
---|
| 562 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
| 563 | if rtnabc: |
---|
| 564 | statvals.append(qx['value']) |
---|
| 565 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
| 566 | statunit= '['+qx['unit']+']' |
---|
| 567 | else: |
---|
| 568 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
| 569 | |
---|
| 570 | tm = self._gettime(i) |
---|
| 571 | src = self._getsourcename(i) |
---|
| 572 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
| 573 | out += 'Time[%s]:\n' % (tm) |
---|
[1907] | 574 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 575 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 576 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[1819] | 577 | #outvec.append(callback(i)) |
---|
[1907] | 578 | if len(rows) > 1: |
---|
| 579 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
| 580 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
| 581 | else: |
---|
| 582 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
| 583 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
[1819] | 584 | out += sep+"\n" |
---|
| 585 | |
---|
[1859] | 586 | import os |
---|
| 587 | if os.environ.has_key( 'USER' ): |
---|
| 588 | usr = os.environ['USER'] |
---|
| 589 | else: |
---|
| 590 | import commands |
---|
| 591 | usr = commands.getoutput( 'whoami' ) |
---|
| 592 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
| 593 | f = open(tmpfile,'w') |
---|
| 594 | print >> f, sep |
---|
| 595 | print >> f, ' %s %s' % (label, statunit) |
---|
| 596 | print >> f, sep |
---|
| 597 | print >> f, out |
---|
| 598 | f.close() |
---|
| 599 | f = open(tmpfile,'r') |
---|
| 600 | x = f.readlines() |
---|
| 601 | f.close() |
---|
| 602 | asaplog.push(''.join(x), False) |
---|
| 603 | |
---|
[1819] | 604 | return statvals |
---|
| 605 | |
---|
| 606 | def chan2data(self, rowno=0, chan=0): |
---|
[1846] | 607 | """\ |
---|
[1819] | 608 | Returns channel/frequency/velocity and spectral value |
---|
| 609 | at an arbitrary row and channel in the scantable. |
---|
[1846] | 610 | |
---|
[1819] | 611 | Parameters: |
---|
[1846] | 612 | |
---|
[1819] | 613 | rowno: a row number in the scantable. Default is the |
---|
| 614 | first row, i.e. rowno=0 |
---|
[1855] | 615 | |
---|
[1819] | 616 | chan: a channel in the scantable. Default is the first |
---|
| 617 | channel, i.e. pos=0 |
---|
[1846] | 618 | |
---|
[1819] | 619 | """ |
---|
| 620 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
| 621 | qx = {'unit': self.get_unit(), |
---|
| 622 | 'value': self._getabcissa(rowno)[chan]} |
---|
| 623 | qy = {'unit': self.get_fluxunit(), |
---|
| 624 | 'value': self._getspectrum(rowno)[chan]} |
---|
| 625 | return qx, qy |
---|
| 626 | |
---|
[1118] | 627 | def stddev(self, mask=None): |
---|
[1846] | 628 | """\ |
---|
[135] | 629 | Determine the standard deviation of the current beam/if/pol |
---|
| 630 | Takes a 'mask' as an optional parameter to specify which |
---|
| 631 | channels should be excluded. |
---|
[1846] | 632 | |
---|
[135] | 633 | Parameters: |
---|
[1846] | 634 | |
---|
[135] | 635 | mask: an optional mask specifying where the standard |
---|
| 636 | deviation should be determined. |
---|
| 637 | |
---|
[1846] | 638 | Example:: |
---|
| 639 | |
---|
[135] | 640 | scan.set_unit('channel') |
---|
[1118] | 641 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 642 | scan.stddev(mask=m) |
---|
[1846] | 643 | |
---|
[135] | 644 | """ |
---|
[1118] | 645 | return self.stats(stat='stddev', mask=mask); |
---|
[135] | 646 | |
---|
[1003] | 647 | |
---|
[1259] | 648 | def get_column_names(self): |
---|
[1846] | 649 | """\ |
---|
[1003] | 650 | Return a list of column names, which can be used for selection. |
---|
| 651 | """ |
---|
[1259] | 652 | return list(Scantable.get_column_names(self)) |
---|
[1003] | 653 | |
---|
[1730] | 654 | def get_tsys(self, row=-1): |
---|
[1846] | 655 | """\ |
---|
[113] | 656 | Return the System temperatures. |
---|
[1846] | 657 | |
---|
| 658 | Parameters: |
---|
| 659 | |
---|
| 660 | row: the rowno to get the information for. (default all rows) |
---|
| 661 | |
---|
[113] | 662 | Returns: |
---|
[1846] | 663 | |
---|
[876] | 664 | a list of Tsys values for the current selection |
---|
[1846] | 665 | |
---|
[113] | 666 | """ |
---|
[1730] | 667 | if row > -1: |
---|
| 668 | return self._get_column(self._gettsys, row) |
---|
[876] | 669 | return self._row_callback(self._gettsys, "Tsys") |
---|
[256] | 670 | |
---|
[1730] | 671 | |
---|
| 672 | def get_weather(self, row=-1): |
---|
[1846] | 673 | """\ |
---|
| 674 | Return the weather informations. |
---|
| 675 | |
---|
| 676 | Parameters: |
---|
| 677 | |
---|
| 678 | row: the rowno to get the information for. (default all rows) |
---|
| 679 | |
---|
| 680 | Returns: |
---|
| 681 | |
---|
| 682 | a dict or list of of dicts of values for the current selection |
---|
| 683 | |
---|
| 684 | """ |
---|
| 685 | |
---|
[1730] | 686 | values = self._get_column(self._get_weather, row) |
---|
| 687 | if row > -1: |
---|
| 688 | return {'temperature': values[0], |
---|
| 689 | 'pressure': values[1], 'humidity' : values[2], |
---|
| 690 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
| 691 | } |
---|
| 692 | else: |
---|
| 693 | out = [] |
---|
| 694 | for r in values: |
---|
| 695 | |
---|
| 696 | out.append({'temperature': r[0], |
---|
| 697 | 'pressure': r[1], 'humidity' : r[2], |
---|
| 698 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
| 699 | }) |
---|
| 700 | return out |
---|
| 701 | |
---|
[876] | 702 | def _row_callback(self, callback, label): |
---|
| 703 | out = "" |
---|
[1118] | 704 | outvec = [] |
---|
[1590] | 705 | sep = '-'*50 |
---|
[876] | 706 | for i in range(self.nrow()): |
---|
| 707 | tm = self._gettime(i) |
---|
| 708 | src = self._getsourcename(i) |
---|
[1590] | 709 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
[876] | 710 | out += 'Time[%s]:\n' % (tm) |
---|
[1590] | 711 | if self.nbeam(-1) > 1: |
---|
| 712 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 713 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 714 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[876] | 715 | outvec.append(callback(i)) |
---|
| 716 | out += '= %3.3f\n' % (outvec[i]) |
---|
[1590] | 717 | out += sep+'\n' |
---|
[1859] | 718 | |
---|
| 719 | asaplog.push(sep) |
---|
| 720 | asaplog.push(" %s" % (label)) |
---|
| 721 | asaplog.push(sep) |
---|
| 722 | asaplog.push(out) |
---|
[1861] | 723 | asaplog.post() |
---|
[1175] | 724 | return outvec |
---|
[256] | 725 | |
---|
[1070] | 726 | def _get_column(self, callback, row=-1): |
---|
| 727 | """ |
---|
| 728 | """ |
---|
| 729 | if row == -1: |
---|
| 730 | return [callback(i) for i in range(self.nrow())] |
---|
| 731 | else: |
---|
[1819] | 732 | if 0 <= row < self.nrow(): |
---|
[1070] | 733 | return callback(row) |
---|
[256] | 734 | |
---|
[1070] | 735 | |
---|
[1348] | 736 | def get_time(self, row=-1, asdatetime=False): |
---|
[1846] | 737 | """\ |
---|
[113] | 738 | Get a list of time stamps for the observations. |
---|
[1348] | 739 | Return a datetime object for each integration time stamp in the scantable. |
---|
[1846] | 740 | |
---|
[113] | 741 | Parameters: |
---|
[1846] | 742 | |
---|
[1348] | 743 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 744 | |
---|
[1348] | 745 | asdatetime: return values as datetime objects rather than strings |
---|
[1846] | 746 | |
---|
[113] | 747 | """ |
---|
[1175] | 748 | from time import strptime |
---|
| 749 | from datetime import datetime |
---|
[1392] | 750 | times = self._get_column(self._gettime, row) |
---|
[1348] | 751 | if not asdatetime: |
---|
[1392] | 752 | return times |
---|
[1175] | 753 | format = "%Y/%m/%d/%H:%M:%S" |
---|
| 754 | if isinstance(times, list): |
---|
| 755 | return [datetime(*strptime(i, format)[:6]) for i in times] |
---|
| 756 | else: |
---|
| 757 | return datetime(*strptime(times, format)[:6]) |
---|
[102] | 758 | |
---|
[1348] | 759 | |
---|
| 760 | def get_inttime(self, row=-1): |
---|
[1846] | 761 | """\ |
---|
[1348] | 762 | Get a list of integration times for the observations. |
---|
| 763 | Return a time in seconds for each integration in the scantable. |
---|
[1846] | 764 | |
---|
[1348] | 765 | Parameters: |
---|
[1846] | 766 | |
---|
[1348] | 767 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 768 | |
---|
[1348] | 769 | """ |
---|
[1573] | 770 | return self._get_column(self._getinttime, row) |
---|
[1348] | 771 | |
---|
[1573] | 772 | |
---|
[714] | 773 | def get_sourcename(self, row=-1): |
---|
[1846] | 774 | """\ |
---|
[794] | 775 | Get a list source names for the observations. |
---|
[714] | 776 | Return a string for each integration in the scantable. |
---|
| 777 | Parameters: |
---|
[1846] | 778 | |
---|
[1348] | 779 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 780 | |
---|
[714] | 781 | """ |
---|
[1070] | 782 | return self._get_column(self._getsourcename, row) |
---|
[714] | 783 | |
---|
[794] | 784 | def get_elevation(self, row=-1): |
---|
[1846] | 785 | """\ |
---|
[794] | 786 | Get a list of elevations for the observations. |
---|
| 787 | Return a float for each integration in the scantable. |
---|
[1846] | 788 | |
---|
[794] | 789 | Parameters: |
---|
[1846] | 790 | |
---|
[1348] | 791 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 792 | |
---|
[794] | 793 | """ |
---|
[1070] | 794 | return self._get_column(self._getelevation, row) |
---|
[794] | 795 | |
---|
| 796 | def get_azimuth(self, row=-1): |
---|
[1846] | 797 | """\ |
---|
[794] | 798 | Get a list of azimuths for the observations. |
---|
| 799 | Return a float for each integration in the scantable. |
---|
[1846] | 800 | |
---|
[794] | 801 | Parameters: |
---|
[1348] | 802 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 803 | |
---|
[794] | 804 | """ |
---|
[1070] | 805 | return self._get_column(self._getazimuth, row) |
---|
[794] | 806 | |
---|
| 807 | def get_parangle(self, row=-1): |
---|
[1846] | 808 | """\ |
---|
[794] | 809 | Get a list of parallactic angles for the observations. |
---|
| 810 | Return a float for each integration in the scantable. |
---|
[1846] | 811 | |
---|
[794] | 812 | Parameters: |
---|
[1846] | 813 | |
---|
[1348] | 814 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 815 | |
---|
[794] | 816 | """ |
---|
[1070] | 817 | return self._get_column(self._getparangle, row) |
---|
[794] | 818 | |
---|
[1070] | 819 | def get_direction(self, row=-1): |
---|
| 820 | """ |
---|
| 821 | Get a list of Positions on the sky (direction) for the observations. |
---|
[1594] | 822 | Return a string for each integration in the scantable. |
---|
[1855] | 823 | |
---|
[1070] | 824 | Parameters: |
---|
[1855] | 825 | |
---|
[1070] | 826 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 827 | |
---|
[1070] | 828 | """ |
---|
| 829 | return self._get_column(self._getdirection, row) |
---|
| 830 | |
---|
[1391] | 831 | def get_directionval(self, row=-1): |
---|
[1846] | 832 | """\ |
---|
[1391] | 833 | Get a list of Positions on the sky (direction) for the observations. |
---|
| 834 | Return a float for each integration in the scantable. |
---|
[1846] | 835 | |
---|
[1391] | 836 | Parameters: |
---|
[1846] | 837 | |
---|
[1391] | 838 | row: row no of integration. Default -1 return all rows |
---|
[1846] | 839 | |
---|
[1391] | 840 | """ |
---|
| 841 | return self._get_column(self._getdirectionvec, row) |
---|
| 842 | |
---|
[1862] | 843 | @asaplog_post_dec |
---|
[102] | 844 | def set_unit(self, unit='channel'): |
---|
[1846] | 845 | """\ |
---|
[102] | 846 | Set the unit for all following operations on this scantable |
---|
[1846] | 847 | |
---|
[102] | 848 | Parameters: |
---|
[1846] | 849 | |
---|
| 850 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
| 851 | 'km/s', 'channel' or equivalent '' |
---|
| 852 | |
---|
[102] | 853 | """ |
---|
[484] | 854 | varlist = vars() |
---|
[1118] | 855 | if unit in ['', 'pixel', 'channel']: |
---|
[113] | 856 | unit = '' |
---|
| 857 | inf = list(self._getcoordinfo()) |
---|
| 858 | inf[0] = unit |
---|
| 859 | self._setcoordinfo(inf) |
---|
[1118] | 860 | self._add_history("set_unit", varlist) |
---|
[113] | 861 | |
---|
[1862] | 862 | @asaplog_post_dec |
---|
[484] | 863 | def set_instrument(self, instr): |
---|
[1846] | 864 | """\ |
---|
[1348] | 865 | Set the instrument for subsequent processing. |
---|
[1846] | 866 | |
---|
[358] | 867 | Parameters: |
---|
[1846] | 868 | |
---|
[710] | 869 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
[407] | 870 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
[1846] | 871 | |
---|
[358] | 872 | """ |
---|
| 873 | self._setInstrument(instr) |
---|
[1118] | 874 | self._add_history("set_instument", vars()) |
---|
[358] | 875 | |
---|
[1862] | 876 | @asaplog_post_dec |
---|
[1190] | 877 | def set_feedtype(self, feedtype): |
---|
[1846] | 878 | """\ |
---|
[1190] | 879 | Overwrite the feed type, which might not be set correctly. |
---|
[1846] | 880 | |
---|
[1190] | 881 | Parameters: |
---|
[1846] | 882 | |
---|
[1190] | 883 | feedtype: 'linear' or 'circular' |
---|
[1846] | 884 | |
---|
[1190] | 885 | """ |
---|
| 886 | self._setfeedtype(feedtype) |
---|
| 887 | self._add_history("set_feedtype", vars()) |
---|
| 888 | |
---|
[1862] | 889 | @asaplog_post_dec |
---|
[276] | 890 | def set_doppler(self, doppler='RADIO'): |
---|
[1846] | 891 | """\ |
---|
[276] | 892 | Set the doppler for all following operations on this scantable. |
---|
[1846] | 893 | |
---|
[276] | 894 | Parameters: |
---|
[1846] | 895 | |
---|
[276] | 896 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
[1846] | 897 | |
---|
[276] | 898 | """ |
---|
[484] | 899 | varlist = vars() |
---|
[276] | 900 | inf = list(self._getcoordinfo()) |
---|
| 901 | inf[2] = doppler |
---|
| 902 | self._setcoordinfo(inf) |
---|
[1118] | 903 | self._add_history("set_doppler", vars()) |
---|
[710] | 904 | |
---|
[1862] | 905 | @asaplog_post_dec |
---|
[226] | 906 | def set_freqframe(self, frame=None): |
---|
[1846] | 907 | """\ |
---|
[113] | 908 | Set the frame type of the Spectral Axis. |
---|
[1846] | 909 | |
---|
[113] | 910 | Parameters: |
---|
[1846] | 911 | |
---|
[591] | 912 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
[1819] | 913 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
[1118] | 914 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
[1846] | 915 | |
---|
| 916 | Example:: |
---|
| 917 | |
---|
[113] | 918 | scan.set_freqframe('BARY') |
---|
[1846] | 919 | |
---|
[113] | 920 | """ |
---|
[1593] | 921 | frame = frame or rcParams['scantable.freqframe'] |
---|
[484] | 922 | varlist = vars() |
---|
[1819] | 923 | # "REST" is not implemented in casacore |
---|
| 924 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
| 925 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
| 926 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
[1118] | 927 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
[591] | 928 | |
---|
[989] | 929 | if frame in valid: |
---|
[113] | 930 | inf = list(self._getcoordinfo()) |
---|
| 931 | inf[1] = frame |
---|
| 932 | self._setcoordinfo(inf) |
---|
[1118] | 933 | self._add_history("set_freqframe", varlist) |
---|
[102] | 934 | else: |
---|
[1118] | 935 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
[1859] | 936 | raise TypeError(msg) |
---|
[710] | 937 | |
---|
[1862] | 938 | @asaplog_post_dec |
---|
[989] | 939 | def set_dirframe(self, frame=""): |
---|
[1846] | 940 | """\ |
---|
[989] | 941 | Set the frame type of the Direction on the sky. |
---|
[1846] | 942 | |
---|
[989] | 943 | Parameters: |
---|
[1846] | 944 | |
---|
[989] | 945 | frame: an optional frame type, default ''. Valid frames are: |
---|
| 946 | 'J2000', 'B1950', 'GALACTIC' |
---|
[1846] | 947 | |
---|
| 948 | Example: |
---|
| 949 | |
---|
[989] | 950 | scan.set_dirframe('GALACTIC') |
---|
[1846] | 951 | |
---|
[989] | 952 | """ |
---|
| 953 | varlist = vars() |
---|
[1859] | 954 | Scantable.set_dirframe(self, frame) |
---|
[1118] | 955 | self._add_history("set_dirframe", varlist) |
---|
[989] | 956 | |
---|
[113] | 957 | def get_unit(self): |
---|
[1846] | 958 | """\ |
---|
[113] | 959 | Get the default unit set in this scantable |
---|
[1846] | 960 | |
---|
[113] | 961 | Returns: |
---|
[1846] | 962 | |
---|
[113] | 963 | A unit string |
---|
[1846] | 964 | |
---|
[113] | 965 | """ |
---|
| 966 | inf = self._getcoordinfo() |
---|
| 967 | unit = inf[0] |
---|
| 968 | if unit == '': unit = 'channel' |
---|
| 969 | return unit |
---|
[102] | 970 | |
---|
[1862] | 971 | @asaplog_post_dec |
---|
[158] | 972 | def get_abcissa(self, rowno=0): |
---|
[1846] | 973 | """\ |
---|
[158] | 974 | Get the abcissa in the current coordinate setup for the currently |
---|
[113] | 975 | selected Beam/IF/Pol |
---|
[1846] | 976 | |
---|
[113] | 977 | Parameters: |
---|
[1846] | 978 | |
---|
[226] | 979 | rowno: an optional row number in the scantable. Default is the |
---|
| 980 | first row, i.e. rowno=0 |
---|
[1846] | 981 | |
---|
[113] | 982 | Returns: |
---|
[1846] | 983 | |
---|
[1348] | 984 | The abcissa values and the format string (as a dictionary) |
---|
[1846] | 985 | |
---|
[113] | 986 | """ |
---|
[256] | 987 | abc = self._getabcissa(rowno) |
---|
[710] | 988 | lbl = self._getabcissalabel(rowno) |
---|
[158] | 989 | return abc, lbl |
---|
[113] | 990 | |
---|
[1862] | 991 | @asaplog_post_dec |
---|
[1819] | 992 | def flag(self, mask=None, unflag=False): |
---|
[1846] | 993 | """\ |
---|
[1001] | 994 | Flag the selected data using an optional channel mask. |
---|
[1846] | 995 | |
---|
[1001] | 996 | Parameters: |
---|
[1846] | 997 | |
---|
[1001] | 998 | mask: an optional channel mask, created with create_mask. Default |
---|
| 999 | (no mask) is all channels. |
---|
[1855] | 1000 | |
---|
[1819] | 1001 | unflag: if True, unflag the data |
---|
[1846] | 1002 | |
---|
[1001] | 1003 | """ |
---|
| 1004 | varlist = vars() |
---|
[1593] | 1005 | mask = mask or [] |
---|
[1859] | 1006 | self._flag(mask, unflag) |
---|
[1001] | 1007 | self._add_history("flag", varlist) |
---|
| 1008 | |
---|
[1862] | 1009 | @asaplog_post_dec |
---|
[1819] | 1010 | def flag_row(self, rows=[], unflag=False): |
---|
[1846] | 1011 | """\ |
---|
[1819] | 1012 | Flag the selected data in row-based manner. |
---|
[1846] | 1013 | |
---|
[1819] | 1014 | Parameters: |
---|
[1846] | 1015 | |
---|
[1843] | 1016 | rows: list of row numbers to be flagged. Default is no row |
---|
| 1017 | (must be explicitly specified to execute row-based flagging). |
---|
[1855] | 1018 | |
---|
[1819] | 1019 | unflag: if True, unflag the data. |
---|
[1846] | 1020 | |
---|
[1819] | 1021 | """ |
---|
| 1022 | varlist = vars() |
---|
[1859] | 1023 | self._flag_row(rows, unflag) |
---|
[1819] | 1024 | self._add_history("flag_row", varlist) |
---|
| 1025 | |
---|
[1862] | 1026 | @asaplog_post_dec |
---|
[1819] | 1027 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
[1846] | 1028 | """\ |
---|
[1819] | 1029 | Flag the selected data outside a specified range (in channel-base) |
---|
[1846] | 1030 | |
---|
[1819] | 1031 | Parameters: |
---|
[1846] | 1032 | |
---|
[1819] | 1033 | uthres: upper threshold. |
---|
[1855] | 1034 | |
---|
[1819] | 1035 | dthres: lower threshold |
---|
[1846] | 1036 | |
---|
[1819] | 1037 | clipoutside: True for flagging data outside the range [dthres:uthres]. |
---|
| 1038 | False for glagging data inside the range. |
---|
[1855] | 1039 | |
---|
[1846] | 1040 | unflag: if True, unflag the data. |
---|
| 1041 | |
---|
[1819] | 1042 | """ |
---|
| 1043 | varlist = vars() |
---|
[1859] | 1044 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
[1819] | 1045 | self._add_history("clip", varlist) |
---|
| 1046 | |
---|
[1862] | 1047 | @asaplog_post_dec |
---|
[1584] | 1048 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
[1846] | 1049 | """\ |
---|
[1192] | 1050 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
[1584] | 1051 | Flagged data in the scantable gets interpolated over the region. |
---|
[1192] | 1052 | No taper is applied. |
---|
[1846] | 1053 | |
---|
[1192] | 1054 | Parameters: |
---|
[1846] | 1055 | |
---|
[1579] | 1056 | start: the start frequency (really a period within the |
---|
| 1057 | bandwidth) or period to remove |
---|
[1855] | 1058 | |
---|
[1579] | 1059 | end: the end frequency or period to remove |
---|
[1855] | 1060 | |
---|
[1584] | 1061 | unit: the frequency unit (default "MHz") or "" for |
---|
[1579] | 1062 | explicit lag channels |
---|
[1846] | 1063 | |
---|
| 1064 | *Notes*: |
---|
| 1065 | |
---|
[1579] | 1066 | It is recommended to flag edges of the band or strong |
---|
[1348] | 1067 | signals beforehand. |
---|
[1846] | 1068 | |
---|
[1192] | 1069 | """ |
---|
| 1070 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 1071 | self._math._setinsitu(insitu) |
---|
| 1072 | varlist = vars() |
---|
[1579] | 1073 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
| 1074 | if not (unit == "" or base.has_key(unit)): |
---|
[1192] | 1075 | raise ValueError("%s is not a valid unit." % unit) |
---|
[1859] | 1076 | if unit == "": |
---|
| 1077 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
| 1078 | else: |
---|
| 1079 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
| 1080 | end*base[unit], "frequency")) |
---|
[1192] | 1081 | s._add_history("lag_flag", varlist) |
---|
| 1082 | if insitu: |
---|
| 1083 | self._assign(s) |
---|
| 1084 | else: |
---|
| 1085 | return s |
---|
[1001] | 1086 | |
---|
[1862] | 1087 | @asaplog_post_dec |
---|
[113] | 1088 | def create_mask(self, *args, **kwargs): |
---|
[1846] | 1089 | """\ |
---|
[1118] | 1090 | Compute and return a mask based on [min, max] windows. |
---|
[189] | 1091 | The specified windows are to be INCLUDED, when the mask is |
---|
[113] | 1092 | applied. |
---|
[1846] | 1093 | |
---|
[102] | 1094 | Parameters: |
---|
[1846] | 1095 | |
---|
[1118] | 1096 | [min, max], [min2, max2], ... |
---|
[1024] | 1097 | Pairs of start/end points (inclusive)specifying the regions |
---|
[102] | 1098 | to be masked |
---|
[1855] | 1099 | |
---|
[189] | 1100 | invert: optional argument. If specified as True, |
---|
| 1101 | return an inverted mask, i.e. the regions |
---|
| 1102 | specified are EXCLUDED |
---|
[1855] | 1103 | |
---|
[513] | 1104 | row: create the mask using the specified row for |
---|
| 1105 | unit conversions, default is row=0 |
---|
| 1106 | only necessary if frequency varies over rows. |
---|
[1846] | 1107 | |
---|
| 1108 | Examples:: |
---|
| 1109 | |
---|
[113] | 1110 | scan.set_unit('channel') |
---|
[1846] | 1111 | # a) |
---|
[1118] | 1112 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
[189] | 1113 | # masks everything outside 400 and 500 |
---|
[113] | 1114 | # and 800 and 900 in the unit 'channel' |
---|
| 1115 | |
---|
[1846] | 1116 | # b) |
---|
[1118] | 1117 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
[189] | 1118 | # masks the regions between 400 and 500 |
---|
[113] | 1119 | # and 800 and 900 in the unit 'channel' |
---|
[1846] | 1120 | |
---|
| 1121 | # c) |
---|
| 1122 | #mask only channel 400 |
---|
[1554] | 1123 | msk = scan.create_mask([400]) |
---|
[1846] | 1124 | |
---|
[102] | 1125 | """ |
---|
[1554] | 1126 | row = kwargs.get("row", 0) |
---|
[513] | 1127 | data = self._getabcissa(row) |
---|
[113] | 1128 | u = self._getcoordinfo()[0] |
---|
[1859] | 1129 | if u == "": |
---|
| 1130 | u = "channel" |
---|
| 1131 | msg = "The current mask window unit is %s" % u |
---|
| 1132 | i = self._check_ifs() |
---|
| 1133 | if not i: |
---|
| 1134 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1135 | asaplog.push(msg) |
---|
[102] | 1136 | n = self.nchan() |
---|
[1295] | 1137 | msk = _n_bools(n, False) |
---|
[710] | 1138 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
| 1139 | |
---|
[1118] | 1140 | ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ |
---|
| 1141 | and args or args[0] |
---|
[710] | 1142 | for window in ws: |
---|
[1554] | 1143 | if len(window) == 1: |
---|
| 1144 | window = [window[0], window[0]] |
---|
| 1145 | if len(window) == 0 or len(window) > 2: |
---|
| 1146 | raise ValueError("A window needs to be defined as [start(, end)]") |
---|
[1545] | 1147 | if window[0] > window[1]: |
---|
| 1148 | tmp = window[0] |
---|
| 1149 | window[0] = window[1] |
---|
| 1150 | window[1] = tmp |
---|
[102] | 1151 | for i in range(n): |
---|
[1024] | 1152 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
[1295] | 1153 | msk[i] = True |
---|
[113] | 1154 | if kwargs.has_key('invert'): |
---|
| 1155 | if kwargs.get('invert'): |
---|
[1295] | 1156 | msk = mask_not(msk) |
---|
[102] | 1157 | return msk |
---|
[710] | 1158 | |
---|
[1819] | 1159 | def get_masklist(self, mask=None, row=0): |
---|
[1846] | 1160 | """\ |
---|
[1819] | 1161 | Compute and return a list of mask windows, [min, max]. |
---|
[1846] | 1162 | |
---|
[1819] | 1163 | Parameters: |
---|
[1846] | 1164 | |
---|
[1819] | 1165 | mask: channel mask, created with create_mask. |
---|
[1855] | 1166 | |
---|
[1819] | 1167 | row: calcutate the masklist using the specified row |
---|
| 1168 | for unit conversions, default is row=0 |
---|
| 1169 | only necessary if frequency varies over rows. |
---|
[1846] | 1170 | |
---|
[1819] | 1171 | Returns: |
---|
[1846] | 1172 | |
---|
[1819] | 1173 | [min, max], [min2, max2], ... |
---|
| 1174 | Pairs of start/end points (inclusive)specifying |
---|
| 1175 | the masked regions |
---|
[1846] | 1176 | |
---|
[1819] | 1177 | """ |
---|
| 1178 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1179 | raise TypeError("The mask should be list or tuple.") |
---|
| 1180 | if len(mask) < 2: |
---|
| 1181 | raise TypeError("The mask elements should be > 1") |
---|
| 1182 | if self.nchan() != len(mask): |
---|
| 1183 | msg = "Number of channels in scantable != number of mask elements" |
---|
| 1184 | raise TypeError(msg) |
---|
| 1185 | data = self._getabcissa(row) |
---|
| 1186 | u = self._getcoordinfo()[0] |
---|
[1859] | 1187 | if u == "": |
---|
| 1188 | u = "channel" |
---|
| 1189 | msg = "The current mask window unit is %s" % u |
---|
| 1190 | i = self._check_ifs() |
---|
| 1191 | if not i: |
---|
| 1192 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1193 | asaplog.push(msg) |
---|
[1819] | 1194 | masklist=[] |
---|
| 1195 | ist, ien = None, None |
---|
| 1196 | ist, ien=self.get_mask_indices(mask) |
---|
| 1197 | if ist is not None and ien is not None: |
---|
| 1198 | for i in xrange(len(ist)): |
---|
| 1199 | range=[data[ist[i]],data[ien[i]]] |
---|
| 1200 | range.sort() |
---|
| 1201 | masklist.append([range[0],range[1]]) |
---|
| 1202 | return masklist |
---|
| 1203 | |
---|
| 1204 | def get_mask_indices(self, mask=None): |
---|
[1846] | 1205 | """\ |
---|
[1819] | 1206 | Compute and Return lists of mask start indices and mask end indices. |
---|
[1855] | 1207 | |
---|
| 1208 | Parameters: |
---|
| 1209 | |
---|
[1819] | 1210 | mask: channel mask, created with create_mask. |
---|
[1846] | 1211 | |
---|
[1819] | 1212 | Returns: |
---|
[1846] | 1213 | |
---|
[1819] | 1214 | List of mask start indices and that of mask end indices, |
---|
| 1215 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
[1846] | 1216 | |
---|
[1819] | 1217 | """ |
---|
| 1218 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1219 | raise TypeError("The mask should be list or tuple.") |
---|
| 1220 | if len(mask) < 2: |
---|
| 1221 | raise TypeError("The mask elements should be > 1") |
---|
| 1222 | istart=[] |
---|
| 1223 | iend=[] |
---|
| 1224 | if mask[0]: istart.append(0) |
---|
| 1225 | for i in range(len(mask)-1): |
---|
| 1226 | if not mask[i] and mask[i+1]: |
---|
| 1227 | istart.append(i+1) |
---|
| 1228 | elif mask[i] and not mask[i+1]: |
---|
| 1229 | iend.append(i) |
---|
| 1230 | if mask[len(mask)-1]: iend.append(len(mask)-1) |
---|
| 1231 | if len(istart) != len(iend): |
---|
| 1232 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
| 1233 | for i in range(len(istart)): |
---|
| 1234 | if istart[i] > iend[i]: |
---|
| 1235 | raise RuntimeError("Mask start index > mask end index") |
---|
| 1236 | break |
---|
| 1237 | return istart,iend |
---|
| 1238 | |
---|
| 1239 | # def get_restfreqs(self): |
---|
| 1240 | # """ |
---|
| 1241 | # Get the restfrequency(s) stored in this scantable. |
---|
| 1242 | # The return value(s) are always of unit 'Hz' |
---|
| 1243 | # Parameters: |
---|
| 1244 | # none |
---|
| 1245 | # Returns: |
---|
| 1246 | # a list of doubles |
---|
| 1247 | # """ |
---|
| 1248 | # return list(self._getrestfreqs()) |
---|
| 1249 | |
---|
| 1250 | def get_restfreqs(self, ids=None): |
---|
[1846] | 1251 | """\ |
---|
[256] | 1252 | Get the restfrequency(s) stored in this scantable. |
---|
| 1253 | The return value(s) are always of unit 'Hz' |
---|
[1846] | 1254 | |
---|
[256] | 1255 | Parameters: |
---|
[1846] | 1256 | |
---|
[1819] | 1257 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
| 1258 | be retrieved |
---|
[1846] | 1259 | |
---|
[256] | 1260 | Returns: |
---|
[1846] | 1261 | |
---|
[1819] | 1262 | dictionary containing ids and a list of doubles for each id |
---|
[1846] | 1263 | |
---|
[256] | 1264 | """ |
---|
[1819] | 1265 | if ids is None: |
---|
| 1266 | rfreqs={} |
---|
| 1267 | idlist = self.getmolnos() |
---|
| 1268 | for i in idlist: |
---|
| 1269 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1270 | return rfreqs |
---|
| 1271 | else: |
---|
| 1272 | if type(ids)==list or type(ids)==tuple: |
---|
| 1273 | rfreqs={} |
---|
| 1274 | for i in ids: |
---|
| 1275 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1276 | return rfreqs |
---|
| 1277 | else: |
---|
| 1278 | return list(self._getrestfreqs(ids)) |
---|
| 1279 | #return list(self._getrestfreqs(ids)) |
---|
[102] | 1280 | |
---|
[931] | 1281 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
[1846] | 1282 | """\ |
---|
[931] | 1283 | Set or replace the restfrequency specified and |
---|
| 1284 | If the 'freqs' argument holds a scalar, |
---|
| 1285 | then that rest frequency will be applied to all the selected |
---|
| 1286 | data. If the 'freqs' argument holds |
---|
| 1287 | a vector, then it MUST be of equal or smaller length than |
---|
| 1288 | the number of IFs (and the available restfrequencies will be |
---|
| 1289 | replaced by this vector). In this case, *all* data have |
---|
| 1290 | the restfrequency set per IF according |
---|
| 1291 | to the corresponding value you give in the 'freqs' vector. |
---|
[1118] | 1292 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
[931] | 1293 | IF 1 gets restfreq 2e9. |
---|
[1846] | 1294 | |
---|
[1395] | 1295 | You can also specify the frequencies via a linecatalog. |
---|
[1153] | 1296 | |
---|
[931] | 1297 | Parameters: |
---|
[1846] | 1298 | |
---|
[931] | 1299 | freqs: list of rest frequency values or string idenitfiers |
---|
[1855] | 1300 | |
---|
[931] | 1301 | unit: unit for rest frequency (default 'Hz') |
---|
[402] | 1302 | |
---|
[1846] | 1303 | |
---|
| 1304 | Example:: |
---|
| 1305 | |
---|
[1819] | 1306 | # set the given restfrequency for the all currently selected IFs |
---|
[931] | 1307 | scan.set_restfreqs(freqs=1.4e9) |
---|
[1845] | 1308 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
| 1309 | # list, i.e |
---|
| 1310 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
| 1311 | # len(list_of_restfreqs) == nIF |
---|
| 1312 | # for nIF == 1 the following will set multiple restfrequency for |
---|
| 1313 | # that IF |
---|
[1819] | 1314 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
[1845] | 1315 | # set multiple restfrequencies per IF. as a list of lists where |
---|
| 1316 | # the outer list has nIF elements, the inner s arbitrary |
---|
| 1317 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
[391] | 1318 | |
---|
[1846] | 1319 | *Note*: |
---|
[1845] | 1320 | |
---|
[931] | 1321 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
| 1322 | source and IF basis, use scantable.set_selection() before using |
---|
[1846] | 1323 | this function:: |
---|
[931] | 1324 | |
---|
[1846] | 1325 | # provided your scantable is called scan |
---|
| 1326 | selection = selector() |
---|
| 1327 | selection.set_name("ORION*") |
---|
| 1328 | selection.set_ifs([1]) |
---|
| 1329 | scan.set_selection(selection) |
---|
| 1330 | scan.set_restfreqs(freqs=86.6e9) |
---|
| 1331 | |
---|
[931] | 1332 | """ |
---|
| 1333 | varlist = vars() |
---|
[1157] | 1334 | from asap import linecatalog |
---|
| 1335 | # simple value |
---|
[1118] | 1336 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
[1845] | 1337 | self._setrestfreqs([freqs], [""], unit) |
---|
[1157] | 1338 | # list of values |
---|
[1118] | 1339 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
[1157] | 1340 | # list values are scalars |
---|
[1118] | 1341 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
[1845] | 1342 | if len(freqs) == 1: |
---|
| 1343 | self._setrestfreqs(freqs, [""], unit) |
---|
| 1344 | else: |
---|
| 1345 | # allow the 'old' mode of setting mulitple IFs |
---|
| 1346 | sel = selector() |
---|
| 1347 | savesel = self._getselection() |
---|
| 1348 | iflist = self.getifnos() |
---|
| 1349 | if len(freqs)>len(iflist): |
---|
| 1350 | raise ValueError("number of elements in list of list " |
---|
| 1351 | "exeeds the current IF selections") |
---|
| 1352 | iflist = self.getifnos() |
---|
| 1353 | for i, fval in enumerate(freqs): |
---|
| 1354 | sel.set_ifs(iflist[i]) |
---|
| 1355 | self._setselection(sel) |
---|
| 1356 | self._setrestfreqs([fval], [""], unit) |
---|
| 1357 | self._setselection(savesel) |
---|
| 1358 | |
---|
| 1359 | # list values are dict, {'value'=, 'name'=) |
---|
[1157] | 1360 | elif isinstance(freqs[-1], dict): |
---|
[1845] | 1361 | values = [] |
---|
| 1362 | names = [] |
---|
| 1363 | for d in freqs: |
---|
| 1364 | values.append(d["value"]) |
---|
| 1365 | names.append(d["name"]) |
---|
| 1366 | self._setrestfreqs(values, names, unit) |
---|
[1819] | 1367 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
[1157] | 1368 | sel = selector() |
---|
| 1369 | savesel = self._getselection() |
---|
[1322] | 1370 | iflist = self.getifnos() |
---|
[1819] | 1371 | if len(freqs)>len(iflist): |
---|
[1845] | 1372 | raise ValueError("number of elements in list of list exeeds" |
---|
| 1373 | " the current IF selections") |
---|
| 1374 | for i, fval in enumerate(freqs): |
---|
[1322] | 1375 | sel.set_ifs(iflist[i]) |
---|
[1259] | 1376 | self._setselection(sel) |
---|
[1845] | 1377 | self._setrestfreqs(fval, [""], unit) |
---|
[1157] | 1378 | self._setselection(savesel) |
---|
| 1379 | # freqs are to be taken from a linecatalog |
---|
[1153] | 1380 | elif isinstance(freqs, linecatalog): |
---|
| 1381 | sel = selector() |
---|
| 1382 | savesel = self._getselection() |
---|
| 1383 | for i in xrange(freqs.nrow()): |
---|
[1322] | 1384 | sel.set_ifs(iflist[i]) |
---|
[1153] | 1385 | self._setselection(sel) |
---|
[1845] | 1386 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
| 1387 | [freqs.get_name(i)], "MHz") |
---|
[1153] | 1388 | # ensure that we are not iterating past nIF |
---|
| 1389 | if i == self.nif()-1: break |
---|
| 1390 | self._setselection(savesel) |
---|
[931] | 1391 | else: |
---|
| 1392 | return |
---|
| 1393 | self._add_history("set_restfreqs", varlist) |
---|
| 1394 | |
---|
[1360] | 1395 | def shift_refpix(self, delta): |
---|
[1846] | 1396 | """\ |
---|
[1589] | 1397 | Shift the reference pixel of the Spectra Coordinate by an |
---|
| 1398 | integer amount. |
---|
[1846] | 1399 | |
---|
[1589] | 1400 | Parameters: |
---|
[1846] | 1401 | |
---|
[1589] | 1402 | delta: the amount to shift by |
---|
[1846] | 1403 | |
---|
| 1404 | *Note*: |
---|
| 1405 | |
---|
[1589] | 1406 | Be careful using this with broadband data. |
---|
[1846] | 1407 | |
---|
[1360] | 1408 | """ |
---|
[1731] | 1409 | Scantable.shift_refpix(self, delta) |
---|
[931] | 1410 | |
---|
[1862] | 1411 | @asaplog_post_dec |
---|
[1259] | 1412 | def history(self, filename=None): |
---|
[1846] | 1413 | """\ |
---|
[1259] | 1414 | Print the history. Optionally to a file. |
---|
[1846] | 1415 | |
---|
[1348] | 1416 | Parameters: |
---|
[1846] | 1417 | |
---|
[1348] | 1418 | filename: The name of the file to save the history to. |
---|
[1846] | 1419 | |
---|
[1259] | 1420 | """ |
---|
[484] | 1421 | hist = list(self._gethistory()) |
---|
[794] | 1422 | out = "-"*80 |
---|
[484] | 1423 | for h in hist: |
---|
[489] | 1424 | if h.startswith("---"): |
---|
[1857] | 1425 | out = "\n".join([out, h]) |
---|
[489] | 1426 | else: |
---|
| 1427 | items = h.split("##") |
---|
| 1428 | date = items[0] |
---|
| 1429 | func = items[1] |
---|
| 1430 | items = items[2:] |
---|
[794] | 1431 | out += "\n"+date+"\n" |
---|
| 1432 | out += "Function: %s\n Parameters:" % (func) |
---|
[489] | 1433 | for i in items: |
---|
| 1434 | s = i.split("=") |
---|
[1118] | 1435 | out += "\n %s = %s" % (s[0], s[1]) |
---|
[1857] | 1436 | out = "\n".join([out, "-"*80]) |
---|
[1259] | 1437 | if filename is not None: |
---|
| 1438 | if filename is "": |
---|
| 1439 | filename = 'scantable_history.txt' |
---|
| 1440 | import os |
---|
| 1441 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 1442 | if not os.path.isdir(filename): |
---|
| 1443 | data = open(filename, 'w') |
---|
| 1444 | data.write(out) |
---|
| 1445 | data.close() |
---|
| 1446 | else: |
---|
| 1447 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 1448 | raise IOError(msg) |
---|
| 1449 | return page(out) |
---|
[513] | 1450 | # |
---|
| 1451 | # Maths business |
---|
| 1452 | # |
---|
[1862] | 1453 | @asaplog_post_dec |
---|
[931] | 1454 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
[1846] | 1455 | """\ |
---|
[1070] | 1456 | Return the (time) weighted average of a scan. |
---|
[1846] | 1457 | |
---|
| 1458 | *Note*: |
---|
| 1459 | |
---|
[1070] | 1460 | in channels only - align if necessary |
---|
[1846] | 1461 | |
---|
[513] | 1462 | Parameters: |
---|
[1846] | 1463 | |
---|
[513] | 1464 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
| 1465 | weighting) |
---|
[1855] | 1466 | |
---|
[558] | 1467 | scanav: True averages each scan separately |
---|
| 1468 | False (default) averages all scans together, |
---|
[1855] | 1469 | |
---|
[1099] | 1470 | weight: Weighting scheme. |
---|
| 1471 | 'none' (mean no weight) |
---|
| 1472 | 'var' (1/var(spec) weighted) |
---|
| 1473 | 'tsys' (1/Tsys**2 weighted) |
---|
| 1474 | 'tint' (integration time weighted) |
---|
| 1475 | 'tintsys' (Tint/Tsys**2) |
---|
| 1476 | 'median' ( median averaging) |
---|
[535] | 1477 | The default is 'tint' |
---|
[1855] | 1478 | |
---|
[931] | 1479 | align: align the spectra in velocity before averaging. It takes |
---|
| 1480 | the time of the first spectrum as reference time. |
---|
[1846] | 1481 | |
---|
| 1482 | Example:: |
---|
| 1483 | |
---|
[513] | 1484 | # time average the scantable without using a mask |
---|
[710] | 1485 | newscan = scan.average_time() |
---|
[1846] | 1486 | |
---|
[513] | 1487 | """ |
---|
| 1488 | varlist = vars() |
---|
[1593] | 1489 | weight = weight or 'TINT' |
---|
| 1490 | mask = mask or () |
---|
| 1491 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
[1118] | 1492 | scan = (self, ) |
---|
[1859] | 1493 | |
---|
| 1494 | if align: |
---|
| 1495 | scan = (self.freq_align(insitu=False), ) |
---|
| 1496 | s = None |
---|
| 1497 | if weight.upper() == 'MEDIAN': |
---|
| 1498 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
| 1499 | scanav)) |
---|
| 1500 | else: |
---|
| 1501 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
| 1502 | scanav)) |
---|
[1099] | 1503 | s._add_history("average_time", varlist) |
---|
[513] | 1504 | return s |
---|
[710] | 1505 | |
---|
[1862] | 1506 | @asaplog_post_dec |
---|
[876] | 1507 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
[1846] | 1508 | """\ |
---|
[513] | 1509 | Return a scan where all spectra are converted to either |
---|
| 1510 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
| 1511 | By default the function tries to look the values up internally. |
---|
| 1512 | If it can't find them (or if you want to over-ride), you must |
---|
| 1513 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
| 1514 | also if you don't set it). jyperk takes precedence if you set both. |
---|
[1846] | 1515 | |
---|
[513] | 1516 | Parameters: |
---|
[1846] | 1517 | |
---|
[513] | 1518 | jyperk: the Jy / K conversion factor |
---|
[1855] | 1519 | |
---|
[513] | 1520 | eta: the aperture efficiency |
---|
[1855] | 1521 | |
---|
[513] | 1522 | d: the geomtric diameter (metres) |
---|
[1855] | 1523 | |
---|
[513] | 1524 | insitu: if False a new scantable is returned. |
---|
| 1525 | Otherwise, the scaling is done in-situ |
---|
| 1526 | The default is taken from .asaprc (False) |
---|
[1846] | 1527 | |
---|
[513] | 1528 | """ |
---|
| 1529 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1530 | self._math._setinsitu(insitu) |
---|
[513] | 1531 | varlist = vars() |
---|
[1593] | 1532 | jyperk = jyperk or -1.0 |
---|
| 1533 | d = d or -1.0 |
---|
| 1534 | eta = eta or -1.0 |
---|
[876] | 1535 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
| 1536 | s._add_history("convert_flux", varlist) |
---|
| 1537 | if insitu: self._assign(s) |
---|
| 1538 | else: return s |
---|
[513] | 1539 | |
---|
[1862] | 1540 | @asaplog_post_dec |
---|
[876] | 1541 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
[1846] | 1542 | """\ |
---|
[513] | 1543 | Return a scan after applying a gain-elevation correction. |
---|
| 1544 | The correction can be made via either a polynomial or a |
---|
| 1545 | table-based interpolation (and extrapolation if necessary). |
---|
| 1546 | You specify polynomial coefficients, an ascii table or neither. |
---|
| 1547 | If you specify neither, then a polynomial correction will be made |
---|
| 1548 | with built in coefficients known for certain telescopes (an error |
---|
| 1549 | will occur if the instrument is not known). |
---|
| 1550 | The data and Tsys are *divided* by the scaling factors. |
---|
[1846] | 1551 | |
---|
[513] | 1552 | Parameters: |
---|
[1846] | 1553 | |
---|
[513] | 1554 | poly: Polynomial coefficients (default None) to compute a |
---|
| 1555 | gain-elevation correction as a function of |
---|
| 1556 | elevation (in degrees). |
---|
[1855] | 1557 | |
---|
[513] | 1558 | filename: The name of an ascii file holding correction factors. |
---|
| 1559 | The first row of the ascii file must give the column |
---|
| 1560 | names and these MUST include columns |
---|
| 1561 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
| 1562 | by this) somewhere. |
---|
| 1563 | The second row must give the data type of the |
---|
| 1564 | column. Use 'R' for Real and 'I' for Integer. |
---|
| 1565 | An example file would be |
---|
| 1566 | (actual factors are arbitrary) : |
---|
| 1567 | |
---|
| 1568 | TIME ELEVATION FACTOR |
---|
| 1569 | R R R |
---|
| 1570 | 0.1 0 0.8 |
---|
| 1571 | 0.2 20 0.85 |
---|
| 1572 | 0.3 40 0.9 |
---|
| 1573 | 0.4 60 0.85 |
---|
| 1574 | 0.5 80 0.8 |
---|
| 1575 | 0.6 90 0.75 |
---|
[1855] | 1576 | |
---|
[513] | 1577 | method: Interpolation method when correcting from a table. |
---|
| 1578 | Values are "nearest", "linear" (default), "cubic" |
---|
| 1579 | and "spline" |
---|
[1855] | 1580 | |
---|
[513] | 1581 | insitu: if False a new scantable is returned. |
---|
| 1582 | Otherwise, the scaling is done in-situ |
---|
| 1583 | The default is taken from .asaprc (False) |
---|
[1846] | 1584 | |
---|
[513] | 1585 | """ |
---|
| 1586 | |
---|
| 1587 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1588 | self._math._setinsitu(insitu) |
---|
[513] | 1589 | varlist = vars() |
---|
[1593] | 1590 | poly = poly or () |
---|
[513] | 1591 | from os.path import expandvars |
---|
| 1592 | filename = expandvars(filename) |
---|
[876] | 1593 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
| 1594 | s._add_history("gain_el", varlist) |
---|
[1593] | 1595 | if insitu: |
---|
| 1596 | self._assign(s) |
---|
| 1597 | else: |
---|
| 1598 | return s |
---|
[710] | 1599 | |
---|
[1862] | 1600 | @asaplog_post_dec |
---|
[931] | 1601 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
[1846] | 1602 | """\ |
---|
[513] | 1603 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
| 1604 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
| 1605 | set_freqframe. |
---|
[1846] | 1606 | |
---|
[513] | 1607 | Parameters: |
---|
[1855] | 1608 | |
---|
[513] | 1609 | reftime: reference time to align at. By default, the time of |
---|
| 1610 | the first row of data is used. |
---|
[1855] | 1611 | |
---|
[513] | 1612 | method: Interpolation method for regridding the spectra. |
---|
| 1613 | Choose from "nearest", "linear", "cubic" (default) |
---|
| 1614 | and "spline" |
---|
[1855] | 1615 | |
---|
[513] | 1616 | insitu: if False a new scantable is returned. |
---|
| 1617 | Otherwise, the scaling is done in-situ |
---|
| 1618 | The default is taken from .asaprc (False) |
---|
[1846] | 1619 | |
---|
[513] | 1620 | """ |
---|
[931] | 1621 | if insitu is None: insitu = rcParams["insitu"] |
---|
[876] | 1622 | self._math._setinsitu(insitu) |
---|
[513] | 1623 | varlist = vars() |
---|
[1593] | 1624 | reftime = reftime or "" |
---|
[931] | 1625 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
[876] | 1626 | s._add_history("freq_align", varlist) |
---|
| 1627 | if insitu: self._assign(s) |
---|
| 1628 | else: return s |
---|
[513] | 1629 | |
---|
[1862] | 1630 | @asaplog_post_dec |
---|
[1725] | 1631 | def opacity(self, tau=None, insitu=None): |
---|
[1846] | 1632 | """\ |
---|
[513] | 1633 | Apply an opacity correction. The data |
---|
| 1634 | and Tsys are multiplied by the correction factor. |
---|
[1846] | 1635 | |
---|
[513] | 1636 | Parameters: |
---|
[1855] | 1637 | |
---|
[1689] | 1638 | tau: (list of) opacity from which the correction factor is |
---|
[513] | 1639 | exp(tau*ZD) |
---|
[1689] | 1640 | where ZD is the zenith-distance. |
---|
| 1641 | If a list is provided, it has to be of length nIF, |
---|
| 1642 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
| 1643 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
[1725] | 1644 | if tau is `None` the opacities are determined from a |
---|
| 1645 | model. |
---|
[1855] | 1646 | |
---|
[513] | 1647 | insitu: if False a new scantable is returned. |
---|
| 1648 | Otherwise, the scaling is done in-situ |
---|
| 1649 | The default is taken from .asaprc (False) |
---|
[1846] | 1650 | |
---|
[513] | 1651 | """ |
---|
| 1652 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1653 | self._math._setinsitu(insitu) |
---|
[513] | 1654 | varlist = vars() |
---|
[1689] | 1655 | if not hasattr(tau, "__len__"): |
---|
| 1656 | tau = [tau] |
---|
[876] | 1657 | s = scantable(self._math._opacity(self, tau)) |
---|
| 1658 | s._add_history("opacity", varlist) |
---|
| 1659 | if insitu: self._assign(s) |
---|
| 1660 | else: return s |
---|
[513] | 1661 | |
---|
[1862] | 1662 | @asaplog_post_dec |
---|
[513] | 1663 | def bin(self, width=5, insitu=None): |
---|
[1846] | 1664 | """\ |
---|
[513] | 1665 | Return a scan where all spectra have been binned up. |
---|
[1846] | 1666 | |
---|
[1348] | 1667 | Parameters: |
---|
[1846] | 1668 | |
---|
[513] | 1669 | width: The bin width (default=5) in pixels |
---|
[1855] | 1670 | |
---|
[513] | 1671 | insitu: if False a new scantable is returned. |
---|
| 1672 | Otherwise, the scaling is done in-situ |
---|
| 1673 | The default is taken from .asaprc (False) |
---|
[1846] | 1674 | |
---|
[513] | 1675 | """ |
---|
| 1676 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1677 | self._math._setinsitu(insitu) |
---|
[513] | 1678 | varlist = vars() |
---|
[876] | 1679 | s = scantable(self._math._bin(self, width)) |
---|
[1118] | 1680 | s._add_history("bin", varlist) |
---|
[1589] | 1681 | if insitu: |
---|
| 1682 | self._assign(s) |
---|
| 1683 | else: |
---|
| 1684 | return s |
---|
[513] | 1685 | |
---|
[1862] | 1686 | @asaplog_post_dec |
---|
[513] | 1687 | def resample(self, width=5, method='cubic', insitu=None): |
---|
[1846] | 1688 | """\ |
---|
[1348] | 1689 | Return a scan where all spectra have been binned up. |
---|
[1573] | 1690 | |
---|
[1348] | 1691 | Parameters: |
---|
[1846] | 1692 | |
---|
[513] | 1693 | width: The bin width (default=5) in pixels |
---|
[1855] | 1694 | |
---|
[513] | 1695 | method: Interpolation method when correcting from a table. |
---|
| 1696 | Values are "nearest", "linear", "cubic" (default) |
---|
| 1697 | and "spline" |
---|
[1855] | 1698 | |
---|
[513] | 1699 | insitu: if False a new scantable is returned. |
---|
| 1700 | Otherwise, the scaling is done in-situ |
---|
| 1701 | The default is taken from .asaprc (False) |
---|
[1846] | 1702 | |
---|
[513] | 1703 | """ |
---|
| 1704 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1705 | self._math._setinsitu(insitu) |
---|
[513] | 1706 | varlist = vars() |
---|
[876] | 1707 | s = scantable(self._math._resample(self, method, width)) |
---|
[1118] | 1708 | s._add_history("resample", varlist) |
---|
[876] | 1709 | if insitu: self._assign(s) |
---|
| 1710 | else: return s |
---|
[513] | 1711 | |
---|
[1862] | 1712 | @asaplog_post_dec |
---|
[946] | 1713 | def average_pol(self, mask=None, weight='none'): |
---|
[1846] | 1714 | """\ |
---|
[946] | 1715 | Average the Polarisations together. |
---|
[1846] | 1716 | |
---|
[946] | 1717 | Parameters: |
---|
[1846] | 1718 | |
---|
[946] | 1719 | mask: An optional mask defining the region, where the |
---|
| 1720 | averaging will be applied. The output will have all |
---|
| 1721 | specified points masked. |
---|
[1855] | 1722 | |
---|
[946] | 1723 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 1724 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 1725 | |
---|
[946] | 1726 | """ |
---|
| 1727 | varlist = vars() |
---|
[1593] | 1728 | mask = mask or () |
---|
[1010] | 1729 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
[1118] | 1730 | s._add_history("average_pol", varlist) |
---|
[992] | 1731 | return s |
---|
[513] | 1732 | |
---|
[1862] | 1733 | @asaplog_post_dec |
---|
[1145] | 1734 | def average_beam(self, mask=None, weight='none'): |
---|
[1846] | 1735 | """\ |
---|
[1145] | 1736 | Average the Beams together. |
---|
[1846] | 1737 | |
---|
[1145] | 1738 | Parameters: |
---|
| 1739 | mask: An optional mask defining the region, where the |
---|
| 1740 | averaging will be applied. The output will have all |
---|
| 1741 | specified points masked. |
---|
[1855] | 1742 | |
---|
[1145] | 1743 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 1744 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 1745 | |
---|
[1145] | 1746 | """ |
---|
| 1747 | varlist = vars() |
---|
[1593] | 1748 | mask = mask or () |
---|
[1145] | 1749 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
| 1750 | s._add_history("average_beam", varlist) |
---|
| 1751 | return s |
---|
| 1752 | |
---|
[1586] | 1753 | def parallactify(self, pflag): |
---|
[1846] | 1754 | """\ |
---|
[1843] | 1755 | Set a flag to indicate whether this data should be treated as having |
---|
[1617] | 1756 | been 'parallactified' (total phase == 0.0) |
---|
[1846] | 1757 | |
---|
[1617] | 1758 | Parameters: |
---|
[1855] | 1759 | |
---|
[1843] | 1760 | pflag: Bool indicating whether to turn this on (True) or |
---|
[1617] | 1761 | off (False) |
---|
[1846] | 1762 | |
---|
[1617] | 1763 | """ |
---|
[1586] | 1764 | varlist = vars() |
---|
| 1765 | self._parallactify(pflag) |
---|
| 1766 | self._add_history("parallactify", varlist) |
---|
| 1767 | |
---|
[1862] | 1768 | @asaplog_post_dec |
---|
[992] | 1769 | def convert_pol(self, poltype=None): |
---|
[1846] | 1770 | """\ |
---|
[992] | 1771 | Convert the data to a different polarisation type. |
---|
[1565] | 1772 | Note that you will need cross-polarisation terms for most conversions. |
---|
[1846] | 1773 | |
---|
[992] | 1774 | Parameters: |
---|
[1855] | 1775 | |
---|
[992] | 1776 | poltype: The new polarisation type. Valid types are: |
---|
[1565] | 1777 | "linear", "circular", "stokes" and "linpol" |
---|
[1846] | 1778 | |
---|
[992] | 1779 | """ |
---|
| 1780 | varlist = vars() |
---|
[1859] | 1781 | s = scantable(self._math._convertpol(self, poltype)) |
---|
[1118] | 1782 | s._add_history("convert_pol", varlist) |
---|
[992] | 1783 | return s |
---|
| 1784 | |
---|
[1862] | 1785 | @asaplog_post_dec |
---|
[1819] | 1786 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): |
---|
[1846] | 1787 | """\ |
---|
[513] | 1788 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
[1846] | 1789 | |
---|
[513] | 1790 | Parameters: |
---|
[1846] | 1791 | |
---|
[513] | 1792 | kernel: The type of smoothing kernel. Select from |
---|
[1574] | 1793 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
| 1794 | or 'poly' |
---|
[1855] | 1795 | |
---|
[513] | 1796 | width: The width of the kernel in pixels. For hanning this is |
---|
| 1797 | ignored otherwise it defauls to 5 pixels. |
---|
| 1798 | For 'gaussian' it is the Full Width Half |
---|
| 1799 | Maximum. For 'boxcar' it is the full width. |
---|
[1574] | 1800 | For 'rmedian' and 'poly' it is the half width. |
---|
[1855] | 1801 | |
---|
[1574] | 1802 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
| 1803 | specify the order of the polnomial. Ignored by all other |
---|
| 1804 | kernels. |
---|
[1855] | 1805 | |
---|
[1819] | 1806 | plot: plot the original and the smoothed spectra. |
---|
| 1807 | In this each indivual fit has to be approved, by |
---|
| 1808 | typing 'y' or 'n' |
---|
[1855] | 1809 | |
---|
[513] | 1810 | insitu: if False a new scantable is returned. |
---|
| 1811 | Otherwise, the scaling is done in-situ |
---|
| 1812 | The default is taken from .asaprc (False) |
---|
[1846] | 1813 | |
---|
[513] | 1814 | """ |
---|
| 1815 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1816 | self._math._setinsitu(insitu) |
---|
[513] | 1817 | varlist = vars() |
---|
[1819] | 1818 | |
---|
| 1819 | if plot: orgscan = self.copy() |
---|
| 1820 | |
---|
[1574] | 1821 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
[876] | 1822 | s._add_history("smooth", varlist) |
---|
[1819] | 1823 | |
---|
| 1824 | if plot: |
---|
| 1825 | if rcParams['plotter.gui']: |
---|
| 1826 | from asap.asaplotgui import asaplotgui as asaplot |
---|
| 1827 | else: |
---|
| 1828 | from asap.asaplot import asaplot |
---|
| 1829 | self._p=asaplot() |
---|
| 1830 | self._p.set_panels() |
---|
| 1831 | ylab=s._get_ordinate_label() |
---|
| 1832 | #self._p.palette(0,["#777777","red"]) |
---|
| 1833 | for r in xrange(s.nrow()): |
---|
| 1834 | xsm=s._getabcissa(r) |
---|
| 1835 | ysm=s._getspectrum(r) |
---|
| 1836 | xorg=orgscan._getabcissa(r) |
---|
| 1837 | yorg=orgscan._getspectrum(r) |
---|
| 1838 | self._p.clear() |
---|
| 1839 | self._p.hold() |
---|
| 1840 | self._p.set_axes('ylabel',ylab) |
---|
| 1841 | self._p.set_axes('xlabel',s._getabcissalabel(r)) |
---|
| 1842 | self._p.set_axes('title',s._getsourcename(r)) |
---|
| 1843 | self._p.set_line(label='Original',color="#777777") |
---|
| 1844 | self._p.plot(xorg,yorg) |
---|
| 1845 | self._p.set_line(label='Smoothed',color="red") |
---|
| 1846 | self._p.plot(xsm,ysm) |
---|
| 1847 | ### Ugly part for legend |
---|
| 1848 | for i in [0,1]: |
---|
| 1849 | self._p.subplots[0]['lines'].append([self._p.subplots[0]['axes'].lines[i]]) |
---|
| 1850 | self._p.release() |
---|
| 1851 | ### Ugly part for legend |
---|
| 1852 | self._p.subplots[0]['lines']=[] |
---|
| 1853 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
| 1854 | if res.upper() == 'N': |
---|
| 1855 | s._setspectrum(yorg, r) |
---|
| 1856 | self._p.unmap() |
---|
| 1857 | self._p = None |
---|
| 1858 | del orgscan |
---|
| 1859 | |
---|
[876] | 1860 | if insitu: self._assign(s) |
---|
| 1861 | else: return s |
---|
[513] | 1862 | |
---|
[1862] | 1863 | @asaplog_post_dec |
---|
[1907] | 1864 | def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None): |
---|
[1846] | 1865 | """\ |
---|
[513] | 1866 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[1907] | 1867 | |
---|
[513] | 1868 | Parameters: |
---|
[1846] | 1869 | |
---|
[794] | 1870 | mask: an optional mask |
---|
[1855] | 1871 | |
---|
[794] | 1872 | order: the order of the polynomial (default is 0) |
---|
[1855] | 1873 | |
---|
[1061] | 1874 | plot: plot the fit and the residual. In this each |
---|
| 1875 | indivual fit has to be approved, by typing 'y' |
---|
| 1876 | or 'n' |
---|
[1855] | 1877 | |
---|
[1391] | 1878 | uselin: use linear polynomial fit |
---|
[1855] | 1879 | |
---|
[794] | 1880 | insitu: if False a new scantable is returned. |
---|
| 1881 | Otherwise, the scaling is done in-situ |
---|
| 1882 | The default is taken from .asaprc (False) |
---|
[1846] | 1883 | |
---|
[1907] | 1884 | rows: row numbers of spectra to be processed. |
---|
| 1885 | (default is None: for all rows) |
---|
| 1886 | |
---|
| 1887 | Example: |
---|
[513] | 1888 | # return a scan baselined by a third order polynomial, |
---|
| 1889 | # not using a mask |
---|
| 1890 | bscan = scan.poly_baseline(order=3) |
---|
[1846] | 1891 | |
---|
[579] | 1892 | """ |
---|
[513] | 1893 | if insitu is None: insitu = rcParams['insitu'] |
---|
[1819] | 1894 | if not insitu: |
---|
| 1895 | workscan = self.copy() |
---|
| 1896 | else: |
---|
| 1897 | workscan = self |
---|
[513] | 1898 | varlist = vars() |
---|
| 1899 | if mask is None: |
---|
[1907] | 1900 | mask = [True for i in xrange(self.nchan())] |
---|
[1819] | 1901 | |
---|
[1217] | 1902 | try: |
---|
| 1903 | f = fitter() |
---|
[1391] | 1904 | if uselin: |
---|
| 1905 | f.set_function(lpoly=order) |
---|
| 1906 | else: |
---|
| 1907 | f.set_function(poly=order) |
---|
[1819] | 1908 | |
---|
[1907] | 1909 | if rows == None: |
---|
| 1910 | rows = xrange(workscan.nrow()) |
---|
| 1911 | elif isinstance(rows, int): |
---|
| 1912 | rows = [ rows ] |
---|
| 1913 | |
---|
[1819] | 1914 | if len(rows) > 0: |
---|
| 1915 | self.blpars = [] |
---|
[1907] | 1916 | self.masklists = [] |
---|
| 1917 | self.actualmask = [] |
---|
| 1918 | |
---|
[1819] | 1919 | for r in rows: |
---|
| 1920 | f.x = workscan._getabcissa(r) |
---|
| 1921 | f.y = workscan._getspectrum(r) |
---|
[1907] | 1922 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
[1819] | 1923 | f.data = None |
---|
| 1924 | f.fit() |
---|
| 1925 | if plot: |
---|
| 1926 | f.plot(residual=True) |
---|
| 1927 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
| 1928 | if x.upper() == 'N': |
---|
| 1929 | self.blpars.append(None) |
---|
[1907] | 1930 | self.masklists.append(None) |
---|
| 1931 | self.actualmask.append(None) |
---|
[1819] | 1932 | continue |
---|
| 1933 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
| 1934 | self.blpars.append(f.get_parameters()) |
---|
[1907] | 1935 | self.masklists.append(workscan.get_masklist(f.mask, row=r)) |
---|
| 1936 | self.actualmask.append(f.mask) |
---|
[1819] | 1937 | |
---|
| 1938 | if plot: |
---|
| 1939 | f._p.unmap() |
---|
| 1940 | f._p = None |
---|
| 1941 | workscan._add_history("poly_baseline", varlist) |
---|
[1856] | 1942 | if insitu: |
---|
| 1943 | self._assign(workscan) |
---|
| 1944 | else: |
---|
| 1945 | return workscan |
---|
[1217] | 1946 | except RuntimeError: |
---|
| 1947 | msg = "The fit failed, possibly because it didn't converge." |
---|
[1859] | 1948 | raise RuntimeError(msg) |
---|
[513] | 1949 | |
---|
[1819] | 1950 | |
---|
[1907] | 1951 | def poly_baseline(self, mask=None, order=0, plot=False, batch=False, insitu=None, rows=None): |
---|
| 1952 | """\ |
---|
| 1953 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 1954 | Parameters: |
---|
| 1955 | mask: an optional mask |
---|
| 1956 | order: the order of the polynomial (default is 0) |
---|
| 1957 | plot: plot the fit and the residual. In this each |
---|
| 1958 | indivual fit has to be approved, by typing 'y' |
---|
| 1959 | or 'n'. Ignored if batch = True. |
---|
| 1960 | batch: if True a faster algorithm is used and logs |
---|
| 1961 | including the fit results are not output |
---|
| 1962 | (default is False) |
---|
| 1963 | insitu: if False a new scantable is returned. |
---|
| 1964 | Otherwise, the scaling is done in-situ |
---|
| 1965 | The default is taken from .asaprc (False) |
---|
| 1966 | rows: row numbers of spectra to be processed. |
---|
| 1967 | (default is None: for all rows) |
---|
| 1968 | Example: |
---|
| 1969 | # return a scan baselined by a third order polynomial, |
---|
| 1970 | # not using a mask |
---|
| 1971 | bscan = scan.poly_baseline(order=3) |
---|
| 1972 | """ |
---|
| 1973 | if insitu is None: insitu = rcParams["insitu"] |
---|
| 1974 | if insitu: |
---|
| 1975 | workscan = self |
---|
| 1976 | else: |
---|
| 1977 | workscan = self.copy() |
---|
| 1978 | |
---|
| 1979 | varlist = vars() |
---|
| 1980 | nchan = workscan.nchan() |
---|
| 1981 | |
---|
| 1982 | if mask is None: |
---|
| 1983 | mask = [True for i in xrange(nchan)] |
---|
| 1984 | |
---|
| 1985 | try: |
---|
| 1986 | if rows == None: |
---|
| 1987 | rows = xrange(workscan.nrow()) |
---|
| 1988 | elif isinstance(rows, int): |
---|
| 1989 | rows = [ rows ] |
---|
| 1990 | |
---|
| 1991 | if len(rows) > 0: |
---|
| 1992 | self.blpars = [] |
---|
| 1993 | self.masklists = [] |
---|
| 1994 | self.actualmask = [] |
---|
| 1995 | |
---|
| 1996 | if batch: |
---|
| 1997 | for r in rows: |
---|
[1908] | 1998 | workscan._poly_baseline_batch(mask, order, r) |
---|
[1907] | 1999 | elif plot: |
---|
| 2000 | f = fitter() |
---|
| 2001 | f.set_function(lpoly=order) |
---|
| 2002 | for r in rows: |
---|
| 2003 | f.x = workscan._getabcissa(r) |
---|
| 2004 | f.y = workscan._getspectrum(r) |
---|
| 2005 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2006 | f.data = None |
---|
| 2007 | f.fit() |
---|
| 2008 | |
---|
| 2009 | f.plot(residual=True) |
---|
| 2010 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2011 | if accept_fit.upper() == "N": |
---|
| 2012 | self.blpars.append(None) |
---|
| 2013 | self.masklists.append(None) |
---|
| 2014 | self.actualmask.append(None) |
---|
| 2015 | continue |
---|
| 2016 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
| 2017 | self.blpars.append(f.get_parameters()) |
---|
| 2018 | self.masklists.append(workscan.get_masklist(f.mask, row=r)) |
---|
| 2019 | self.actualmask.append(f.mask) |
---|
| 2020 | |
---|
| 2021 | f._p.unmap() |
---|
| 2022 | f._p = None |
---|
| 2023 | else: |
---|
| 2024 | import array |
---|
| 2025 | for r in rows: |
---|
| 2026 | pars = array.array("f", [0.0 for i in range(order+1)]) |
---|
| 2027 | pars_adr = pars.buffer_info()[0] |
---|
| 2028 | pars_len = pars.buffer_info()[1] |
---|
| 2029 | |
---|
| 2030 | errs = array.array("f", [0.0 for i in range(order+1)]) |
---|
| 2031 | errs_adr = errs.buffer_info()[0] |
---|
| 2032 | errs_len = errs.buffer_info()[1] |
---|
| 2033 | |
---|
| 2034 | fmsk = array.array("i", [1 for i in range(nchan)]) |
---|
| 2035 | fmsk_adr = fmsk.buffer_info()[0] |
---|
| 2036 | fmsk_len = fmsk.buffer_info()[1] |
---|
| 2037 | |
---|
| 2038 | workscan._poly_baseline(mask, order, r, pars_adr, pars_len, errs_adr, errs_len, fmsk_adr, fmsk_len) |
---|
| 2039 | |
---|
| 2040 | params = pars.tolist() |
---|
| 2041 | fmtd = "" |
---|
| 2042 | for i in xrange(len(params)): fmtd += " p%d= %3.6f," % (i, params[i]) |
---|
| 2043 | fmtd = fmtd[:-1] # remove trailing "," |
---|
| 2044 | errors = errs.tolist() |
---|
| 2045 | fmask = fmsk.tolist() |
---|
| 2046 | for i in xrange(len(fmask)): fmask[i] = (fmask[i] > 0) # transform (1/0) -> (True/False) |
---|
| 2047 | |
---|
| 2048 | self.blpars.append({"params":params, "fixed":[], "formatted":fmtd, "errors":errors}) |
---|
| 2049 | self.masklists.append(workscan.get_masklist(fmask, r)) |
---|
| 2050 | self.actualmask.append(fmask) |
---|
| 2051 | |
---|
| 2052 | asaplog.push(str(fmtd)) |
---|
| 2053 | |
---|
| 2054 | workscan._add_history("poly_baseline", varlist) |
---|
| 2055 | |
---|
| 2056 | if insitu: |
---|
| 2057 | self._assign(workscan) |
---|
| 2058 | else: |
---|
| 2059 | return workscan |
---|
| 2060 | |
---|
[1919] | 2061 | except RuntimeError, e: |
---|
[1907] | 2062 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2063 | if rcParams["verbose"]: |
---|
[1919] | 2064 | asaplog.push(str(e)) |
---|
[1907] | 2065 | asaplog.push(str(msg)) |
---|
| 2066 | return |
---|
| 2067 | else: |
---|
[1919] | 2068 | raise RuntimeError(str(e)+'\n'+msg) |
---|
[1907] | 2069 | |
---|
| 2070 | |
---|
| 2071 | def auto_poly_baseline(self, mask=None, edge=(0, 0), order=0, |
---|
[1280] | 2072 | threshold=3, chan_avg_limit=1, plot=False, |
---|
[1907] | 2073 | insitu=None, rows=None): |
---|
[1846] | 2074 | """\ |
---|
[880] | 2075 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 2076 | Spectral lines are detected first using linefinder and masked out |
---|
| 2077 | to avoid them affecting the baseline solution. |
---|
| 2078 | |
---|
| 2079 | Parameters: |
---|
[1846] | 2080 | |
---|
[880] | 2081 | mask: an optional mask retreived from scantable |
---|
[1846] | 2082 | |
---|
| 2083 | edge: an optional number of channel to drop at the edge of |
---|
| 2084 | spectrum. If only one value is |
---|
[880] | 2085 | specified, the same number will be dropped from |
---|
| 2086 | both sides of the spectrum. Default is to keep |
---|
[907] | 2087 | all channels. Nested tuples represent individual |
---|
[976] | 2088 | edge selection for different IFs (a number of spectral |
---|
| 2089 | channels can be different) |
---|
[1846] | 2090 | |
---|
[880] | 2091 | order: the order of the polynomial (default is 0) |
---|
[1846] | 2092 | |
---|
[880] | 2093 | threshold: the threshold used by line finder. It is better to |
---|
| 2094 | keep it large as only strong lines affect the |
---|
| 2095 | baseline solution. |
---|
[1846] | 2096 | |
---|
[1280] | 2097 | chan_avg_limit: |
---|
| 2098 | a maximum number of consequtive spectral channels to |
---|
| 2099 | average during the search of weak and broad lines. |
---|
| 2100 | The default is no averaging (and no search for weak |
---|
| 2101 | lines). If such lines can affect the fitted baseline |
---|
| 2102 | (e.g. a high order polynomial is fitted), increase this |
---|
| 2103 | parameter (usually values up to 8 are reasonable). Most |
---|
| 2104 | users of this method should find the default value |
---|
| 2105 | sufficient. |
---|
[1846] | 2106 | |
---|
[1061] | 2107 | plot: plot the fit and the residual. In this each |
---|
| 2108 | indivual fit has to be approved, by typing 'y' |
---|
| 2109 | or 'n' |
---|
[1846] | 2110 | |
---|
[880] | 2111 | insitu: if False a new scantable is returned. |
---|
| 2112 | Otherwise, the scaling is done in-situ |
---|
| 2113 | The default is taken from .asaprc (False) |
---|
[1907] | 2114 | rows: row numbers of spectra to be processed. |
---|
| 2115 | (default is None: for all rows) |
---|
[880] | 2116 | |
---|
[1846] | 2117 | |
---|
| 2118 | Example:: |
---|
| 2119 | |
---|
| 2120 | scan2 = scan.auto_poly_baseline(order=7, insitu=False) |
---|
| 2121 | |
---|
[880] | 2122 | """ |
---|
| 2123 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2124 | varlist = vars() |
---|
| 2125 | from asap.asaplinefind import linefinder |
---|
| 2126 | from asap import _is_sequence_or_number as _is_valid |
---|
| 2127 | |
---|
[976] | 2128 | # check whether edge is set up for each IF individually |
---|
[1118] | 2129 | individualedge = False; |
---|
| 2130 | if len(edge) > 1: |
---|
| 2131 | if isinstance(edge[0], list) or isinstance(edge[0], tuple): |
---|
| 2132 | individualedge = True; |
---|
[907] | 2133 | |
---|
[1118] | 2134 | if not _is_valid(edge, int) and not individualedge: |
---|
[909] | 2135 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
[907] | 2136 | pair of integers specified as a tuple. Nested tuples are allowed \ |
---|
| 2137 | to make individual selection for different IFs." |
---|
[919] | 2138 | |
---|
[1118] | 2139 | curedge = (0, 0) |
---|
| 2140 | if individualedge: |
---|
| 2141 | for edgepar in edge: |
---|
| 2142 | if not _is_valid(edgepar, int): |
---|
| 2143 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 2144 | to be a pair of integers or an integer." |
---|
[907] | 2145 | else: |
---|
[1118] | 2146 | curedge = edge; |
---|
[880] | 2147 | |
---|
[1907] | 2148 | if not insitu: |
---|
| 2149 | workscan = self.copy() |
---|
| 2150 | else: |
---|
| 2151 | workscan = self |
---|
| 2152 | |
---|
[880] | 2153 | # setup fitter |
---|
| 2154 | f = fitter() |
---|
[1907] | 2155 | f.set_function(lpoly=order) |
---|
[880] | 2156 | |
---|
| 2157 | # setup line finder |
---|
[1118] | 2158 | fl = linefinder() |
---|
[1268] | 2159 | fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) |
---|
[880] | 2160 | |
---|
[907] | 2161 | fl.set_scan(workscan) |
---|
| 2162 | |
---|
[1907] | 2163 | if mask is None: |
---|
| 2164 | mask = _n_bools(workscan.nchan(), True) |
---|
| 2165 | |
---|
| 2166 | if rows is None: |
---|
| 2167 | rows = xrange(workscan.nrow()) |
---|
| 2168 | elif isinstance(rows, int): |
---|
| 2169 | rows = [ rows ] |
---|
| 2170 | |
---|
[1819] | 2171 | # Save parameters of baseline fits & masklists as a class attribute. |
---|
| 2172 | # NOTICE: It does not reflect changes in scantable! |
---|
| 2173 | if len(rows) > 0: |
---|
| 2174 | self.blpars=[] |
---|
| 2175 | self.masklists=[] |
---|
[1907] | 2176 | self.actualmask=[] |
---|
[880] | 2177 | asaplog.push("Processing:") |
---|
| 2178 | for r in rows: |
---|
[1118] | 2179 | msg = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % \ |
---|
| 2180 | (workscan.getscan(r), workscan.getbeam(r), workscan.getif(r), \ |
---|
| 2181 | workscan.getpol(r), workscan.getcycle(r)) |
---|
[880] | 2182 | asaplog.push(msg, False) |
---|
[907] | 2183 | |
---|
[976] | 2184 | # figure out edge parameter |
---|
[1118] | 2185 | if individualedge: |
---|
| 2186 | if len(edge) >= workscan.getif(r): |
---|
| 2187 | raise RuntimeError, "Number of edge elements appear to " \ |
---|
| 2188 | "be less than the number of IFs" |
---|
| 2189 | curedge = edge[workscan.getif(r)] |
---|
[919] | 2190 | |
---|
[1907] | 2191 | actualmask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
[1819] | 2192 | |
---|
[976] | 2193 | # setup line finder |
---|
[1819] | 2194 | fl.find_lines(r, actualmask, curedge) |
---|
[1907] | 2195 | |
---|
[1819] | 2196 | f.x = workscan._getabcissa(r) |
---|
| 2197 | f.y = workscan._getspectrum(r) |
---|
[1907] | 2198 | f.mask = fl.get_mask() |
---|
[1819] | 2199 | f.data = None |
---|
[880] | 2200 | f.fit() |
---|
[1819] | 2201 | |
---|
| 2202 | # Show mask list |
---|
[1907] | 2203 | masklist=workscan.get_masklist(f.mask, row=r) |
---|
[1819] | 2204 | msg = "mask range: "+str(masklist) |
---|
| 2205 | asaplog.push(msg, False) |
---|
| 2206 | |
---|
[1061] | 2207 | if plot: |
---|
| 2208 | f.plot(residual=True) |
---|
| 2209 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2210 | if x.upper() == 'N': |
---|
[1819] | 2211 | self.blpars.append(None) |
---|
| 2212 | self.masklists.append(None) |
---|
[1907] | 2213 | self.actualmask.append(None) |
---|
[1061] | 2214 | continue |
---|
[1819] | 2215 | |
---|
[880] | 2216 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
[1819] | 2217 | self.blpars.append(f.get_parameters()) |
---|
| 2218 | self.masklists.append(masklist) |
---|
[1907] | 2219 | self.actualmask.append(f.mask) |
---|
[1061] | 2220 | if plot: |
---|
| 2221 | f._p.unmap() |
---|
| 2222 | f._p = None |
---|
| 2223 | workscan._add_history("auto_poly_baseline", varlist) |
---|
[880] | 2224 | if insitu: |
---|
| 2225 | self._assign(workscan) |
---|
| 2226 | else: |
---|
| 2227 | return workscan |
---|
| 2228 | |
---|
[1862] | 2229 | @asaplog_post_dec |
---|
[914] | 2230 | def rotate_linpolphase(self, angle): |
---|
[1846] | 2231 | """\ |
---|
[914] | 2232 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
| 2233 | This is always done in situ in the raw data. So if you call this |
---|
| 2234 | function more than once then each call rotates the phase further. |
---|
[1846] | 2235 | |
---|
[914] | 2236 | Parameters: |
---|
[1846] | 2237 | |
---|
[914] | 2238 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2239 | |
---|
| 2240 | Example:: |
---|
| 2241 | |
---|
[914] | 2242 | scan.rotate_linpolphase(2.3) |
---|
[1846] | 2243 | |
---|
[914] | 2244 | """ |
---|
| 2245 | varlist = vars() |
---|
[936] | 2246 | self._math._rotate_linpolphase(self, angle) |
---|
[914] | 2247 | self._add_history("rotate_linpolphase", varlist) |
---|
| 2248 | return |
---|
[710] | 2249 | |
---|
[1862] | 2250 | @asaplog_post_dec |
---|
[914] | 2251 | def rotate_xyphase(self, angle): |
---|
[1846] | 2252 | """\ |
---|
[914] | 2253 | Rotate the phase of the XY correlation. This is always done in situ |
---|
| 2254 | in the data. So if you call this function more than once |
---|
| 2255 | then each call rotates the phase further. |
---|
[1846] | 2256 | |
---|
[914] | 2257 | Parameters: |
---|
[1846] | 2258 | |
---|
[914] | 2259 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2260 | |
---|
| 2261 | Example:: |
---|
| 2262 | |
---|
[914] | 2263 | scan.rotate_xyphase(2.3) |
---|
[1846] | 2264 | |
---|
[914] | 2265 | """ |
---|
| 2266 | varlist = vars() |
---|
[936] | 2267 | self._math._rotate_xyphase(self, angle) |
---|
[914] | 2268 | self._add_history("rotate_xyphase", varlist) |
---|
| 2269 | return |
---|
| 2270 | |
---|
[1862] | 2271 | @asaplog_post_dec |
---|
[914] | 2272 | def swap_linears(self): |
---|
[1846] | 2273 | """\ |
---|
[1573] | 2274 | Swap the linear polarisations XX and YY, or better the first two |
---|
[1348] | 2275 | polarisations as this also works for ciculars. |
---|
[914] | 2276 | """ |
---|
| 2277 | varlist = vars() |
---|
[936] | 2278 | self._math._swap_linears(self) |
---|
[914] | 2279 | self._add_history("swap_linears", varlist) |
---|
| 2280 | return |
---|
| 2281 | |
---|
[1862] | 2282 | @asaplog_post_dec |
---|
[914] | 2283 | def invert_phase(self): |
---|
[1846] | 2284 | """\ |
---|
[914] | 2285 | Invert the phase of the complex polarisation |
---|
| 2286 | """ |
---|
| 2287 | varlist = vars() |
---|
[936] | 2288 | self._math._invert_phase(self) |
---|
[914] | 2289 | self._add_history("invert_phase", varlist) |
---|
| 2290 | return |
---|
| 2291 | |
---|
[1862] | 2292 | @asaplog_post_dec |
---|
[876] | 2293 | def add(self, offset, insitu=None): |
---|
[1846] | 2294 | """\ |
---|
[513] | 2295 | Return a scan where all spectra have the offset added |
---|
[1846] | 2296 | |
---|
[513] | 2297 | Parameters: |
---|
[1846] | 2298 | |
---|
[513] | 2299 | offset: the offset |
---|
[1855] | 2300 | |
---|
[513] | 2301 | insitu: if False a new scantable is returned. |
---|
| 2302 | Otherwise, the scaling is done in-situ |
---|
| 2303 | The default is taken from .asaprc (False) |
---|
[1846] | 2304 | |
---|
[513] | 2305 | """ |
---|
| 2306 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2307 | self._math._setinsitu(insitu) |
---|
[513] | 2308 | varlist = vars() |
---|
[876] | 2309 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
[1118] | 2310 | s._add_history("add", varlist) |
---|
[876] | 2311 | if insitu: |
---|
| 2312 | self._assign(s) |
---|
| 2313 | else: |
---|
[513] | 2314 | return s |
---|
| 2315 | |
---|
[1862] | 2316 | @asaplog_post_dec |
---|
[1308] | 2317 | def scale(self, factor, tsys=True, insitu=None): |
---|
[1846] | 2318 | """\ |
---|
| 2319 | |
---|
[513] | 2320 | Return a scan where all spectra are scaled by the give 'factor' |
---|
[1846] | 2321 | |
---|
[513] | 2322 | Parameters: |
---|
[1846] | 2323 | |
---|
[1819] | 2324 | factor: the scaling factor (float or 1D float list) |
---|
[1855] | 2325 | |
---|
[513] | 2326 | insitu: if False a new scantable is returned. |
---|
| 2327 | Otherwise, the scaling is done in-situ |
---|
| 2328 | The default is taken from .asaprc (False) |
---|
[1855] | 2329 | |
---|
[513] | 2330 | tsys: if True (default) then apply the operation to Tsys |
---|
| 2331 | as well as the data |
---|
[1846] | 2332 | |
---|
[513] | 2333 | """ |
---|
| 2334 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2335 | self._math._setinsitu(insitu) |
---|
[513] | 2336 | varlist = vars() |
---|
[1819] | 2337 | s = None |
---|
| 2338 | import numpy |
---|
| 2339 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
| 2340 | if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): |
---|
| 2341 | from asapmath import _array2dOp |
---|
| 2342 | s = _array2dOp( self.copy(), factor, "MUL", tsys ) |
---|
| 2343 | else: |
---|
| 2344 | s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) |
---|
| 2345 | else: |
---|
| 2346 | s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) |
---|
[1118] | 2347 | s._add_history("scale", varlist) |
---|
[876] | 2348 | if insitu: |
---|
| 2349 | self._assign(s) |
---|
| 2350 | else: |
---|
[513] | 2351 | return s |
---|
| 2352 | |
---|
[1504] | 2353 | def set_sourcetype(self, match, matchtype="pattern", |
---|
| 2354 | sourcetype="reference"): |
---|
[1846] | 2355 | """\ |
---|
[1502] | 2356 | Set the type of the source to be an source or reference scan |
---|
[1846] | 2357 | using the provided pattern. |
---|
| 2358 | |
---|
[1502] | 2359 | Parameters: |
---|
[1846] | 2360 | |
---|
[1504] | 2361 | match: a Unix style pattern, regular expression or selector |
---|
[1855] | 2362 | |
---|
[1504] | 2363 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
| 2364 | 'regex' regular expression |
---|
[1855] | 2365 | |
---|
[1502] | 2366 | sourcetype: the type of the source to use (source/reference) |
---|
[1846] | 2367 | |
---|
[1502] | 2368 | """ |
---|
| 2369 | varlist = vars() |
---|
| 2370 | basesel = self.get_selection() |
---|
| 2371 | stype = -1 |
---|
| 2372 | if sourcetype.lower().startswith("r"): |
---|
| 2373 | stype = 1 |
---|
| 2374 | elif sourcetype.lower().startswith("s"): |
---|
| 2375 | stype = 0 |
---|
[1504] | 2376 | else: |
---|
[1502] | 2377 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
[1504] | 2378 | if matchtype.lower().startswith("p"): |
---|
| 2379 | matchtype = "pattern" |
---|
| 2380 | elif matchtype.lower().startswith("r"): |
---|
| 2381 | matchtype = "regex" |
---|
| 2382 | else: |
---|
| 2383 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
[1502] | 2384 | sel = selector() |
---|
| 2385 | if isinstance(match, selector): |
---|
| 2386 | sel = match |
---|
| 2387 | else: |
---|
[1504] | 2388 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
[1502] | 2389 | self.set_selection(basesel+sel) |
---|
| 2390 | self._setsourcetype(stype) |
---|
| 2391 | self.set_selection(basesel) |
---|
[1573] | 2392 | self._add_history("set_sourcetype", varlist) |
---|
[1502] | 2393 | |
---|
[1862] | 2394 | @asaplog_post_dec |
---|
[1857] | 2395 | @preserve_selection |
---|
[1819] | 2396 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
[1846] | 2397 | """\ |
---|
[670] | 2398 | This function allows to build quotients automatically. |
---|
[1819] | 2399 | It assumes the observation to have the same number of |
---|
[670] | 2400 | "ons" and "offs" |
---|
[1846] | 2401 | |
---|
[670] | 2402 | Parameters: |
---|
[1846] | 2403 | |
---|
[710] | 2404 | preserve: you can preserve (default) the continuum or |
---|
| 2405 | remove it. The equations used are |
---|
[1857] | 2406 | |
---|
[670] | 2407 | preserve: Output = Toff * (on/off) - Toff |
---|
[1857] | 2408 | |
---|
[1070] | 2409 | remove: Output = Toff * (on/off) - Ton |
---|
[1855] | 2410 | |
---|
[1573] | 2411 | mode: the on/off detection mode |
---|
[1348] | 2412 | 'paired' (default) |
---|
| 2413 | identifies 'off' scans by the |
---|
| 2414 | trailing '_R' (Mopra/Parkes) or |
---|
| 2415 | '_e'/'_w' (Tid) and matches |
---|
| 2416 | on/off pairs from the observing pattern |
---|
[1502] | 2417 | 'time' |
---|
| 2418 | finds the closest off in time |
---|
[1348] | 2419 | |
---|
[1857] | 2420 | .. todo:: verify argument is not implemented |
---|
| 2421 | |
---|
[670] | 2422 | """ |
---|
[1857] | 2423 | varlist = vars() |
---|
[1348] | 2424 | modes = ["time", "paired"] |
---|
[670] | 2425 | if not mode in modes: |
---|
[876] | 2426 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
| 2427 | raise ValueError(msg) |
---|
[1348] | 2428 | s = None |
---|
| 2429 | if mode.lower() == "paired": |
---|
[1857] | 2430 | sel = self.get_selection() |
---|
[1875] | 2431 | sel.set_query("SRCTYPE==psoff") |
---|
[1356] | 2432 | self.set_selection(sel) |
---|
[1348] | 2433 | offs = self.copy() |
---|
[1875] | 2434 | sel.set_query("SRCTYPE==pson") |
---|
[1356] | 2435 | self.set_selection(sel) |
---|
[1348] | 2436 | ons = self.copy() |
---|
| 2437 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
| 2438 | elif mode.lower() == "time": |
---|
| 2439 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
[1118] | 2440 | s._add_history("auto_quotient", varlist) |
---|
[876] | 2441 | return s |
---|
[710] | 2442 | |
---|
[1862] | 2443 | @asaplog_post_dec |
---|
[1145] | 2444 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
[1846] | 2445 | """\ |
---|
[1143] | 2446 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
[1846] | 2447 | |
---|
[1143] | 2448 | Parameters: |
---|
[1846] | 2449 | |
---|
[1145] | 2450 | mask: an optional mask to be used when weight == 'stddev' |
---|
[1855] | 2451 | |
---|
[1143] | 2452 | weight: How to average the off beams. Default is 'median'. |
---|
[1855] | 2453 | |
---|
[1145] | 2454 | preserve: you can preserve (default) the continuum or |
---|
[1855] | 2455 | remove it. The equations used are: |
---|
[1846] | 2456 | |
---|
[1855] | 2457 | preserve: Output = Toff * (on/off) - Toff |
---|
| 2458 | |
---|
| 2459 | remove: Output = Toff * (on/off) - Ton |
---|
| 2460 | |
---|
[1217] | 2461 | """ |
---|
[1593] | 2462 | mask = mask or () |
---|
[1141] | 2463 | varlist = vars() |
---|
| 2464 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
[1143] | 2465 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
| 2466 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
[1217] | 2467 | from asapmath import quotient |
---|
[1145] | 2468 | q = quotient(on, off, preserve) |
---|
[1143] | 2469 | q._add_history("mx_quotient", varlist) |
---|
[1217] | 2470 | return q |
---|
[513] | 2471 | |
---|
[1862] | 2472 | @asaplog_post_dec |
---|
[718] | 2473 | def freq_switch(self, insitu=None): |
---|
[1846] | 2474 | """\ |
---|
[718] | 2475 | Apply frequency switching to the data. |
---|
[1846] | 2476 | |
---|
[718] | 2477 | Parameters: |
---|
[1846] | 2478 | |
---|
[718] | 2479 | insitu: if False a new scantable is returned. |
---|
| 2480 | Otherwise, the swictching is done in-situ |
---|
| 2481 | The default is taken from .asaprc (False) |
---|
[1846] | 2482 | |
---|
[718] | 2483 | """ |
---|
| 2484 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2485 | self._math._setinsitu(insitu) |
---|
[718] | 2486 | varlist = vars() |
---|
[876] | 2487 | s = scantable(self._math._freqswitch(self)) |
---|
[1118] | 2488 | s._add_history("freq_switch", varlist) |
---|
[1856] | 2489 | if insitu: |
---|
| 2490 | self._assign(s) |
---|
| 2491 | else: |
---|
| 2492 | return s |
---|
[718] | 2493 | |
---|
[1862] | 2494 | @asaplog_post_dec |
---|
[780] | 2495 | def recalc_azel(self): |
---|
[1846] | 2496 | """Recalculate the azimuth and elevation for each position.""" |
---|
[780] | 2497 | varlist = vars() |
---|
[876] | 2498 | self._recalcazel() |
---|
[780] | 2499 | self._add_history("recalc_azel", varlist) |
---|
| 2500 | return |
---|
| 2501 | |
---|
[1862] | 2502 | @asaplog_post_dec |
---|
[513] | 2503 | def __add__(self, other): |
---|
| 2504 | varlist = vars() |
---|
| 2505 | s = None |
---|
| 2506 | if isinstance(other, scantable): |
---|
[1573] | 2507 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
[513] | 2508 | elif isinstance(other, float): |
---|
[876] | 2509 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
[513] | 2510 | else: |
---|
[718] | 2511 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2512 | s._add_history("operator +", varlist) |
---|
| 2513 | return s |
---|
| 2514 | |
---|
[1862] | 2515 | @asaplog_post_dec |
---|
[513] | 2516 | def __sub__(self, other): |
---|
| 2517 | """ |
---|
| 2518 | implicit on all axes and on Tsys |
---|
| 2519 | """ |
---|
| 2520 | varlist = vars() |
---|
| 2521 | s = None |
---|
| 2522 | if isinstance(other, scantable): |
---|
[1588] | 2523 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
[513] | 2524 | elif isinstance(other, float): |
---|
[876] | 2525 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
[513] | 2526 | else: |
---|
[718] | 2527 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2528 | s._add_history("operator -", varlist) |
---|
| 2529 | return s |
---|
[710] | 2530 | |
---|
[1862] | 2531 | @asaplog_post_dec |
---|
[513] | 2532 | def __mul__(self, other): |
---|
| 2533 | """ |
---|
| 2534 | implicit on all axes and on Tsys |
---|
| 2535 | """ |
---|
| 2536 | varlist = vars() |
---|
| 2537 | s = None |
---|
| 2538 | if isinstance(other, scantable): |
---|
[1588] | 2539 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
[513] | 2540 | elif isinstance(other, float): |
---|
[876] | 2541 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
[513] | 2542 | else: |
---|
[718] | 2543 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2544 | s._add_history("operator *", varlist) |
---|
| 2545 | return s |
---|
| 2546 | |
---|
[710] | 2547 | |
---|
[1862] | 2548 | @asaplog_post_dec |
---|
[513] | 2549 | def __div__(self, other): |
---|
| 2550 | """ |
---|
| 2551 | implicit on all axes and on Tsys |
---|
| 2552 | """ |
---|
| 2553 | varlist = vars() |
---|
| 2554 | s = None |
---|
| 2555 | if isinstance(other, scantable): |
---|
[1589] | 2556 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
[513] | 2557 | elif isinstance(other, float): |
---|
| 2558 | if other == 0.0: |
---|
[718] | 2559 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
[876] | 2560 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
[513] | 2561 | else: |
---|
[718] | 2562 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 2563 | s._add_history("operator /", varlist) |
---|
| 2564 | return s |
---|
| 2565 | |
---|
[1862] | 2566 | @asaplog_post_dec |
---|
[530] | 2567 | def get_fit(self, row=0): |
---|
[1846] | 2568 | """\ |
---|
[530] | 2569 | Print or return the stored fits for a row in the scantable |
---|
[1846] | 2570 | |
---|
[530] | 2571 | Parameters: |
---|
[1846] | 2572 | |
---|
[530] | 2573 | row: the row which the fit has been applied to. |
---|
[1846] | 2574 | |
---|
[530] | 2575 | """ |
---|
| 2576 | if row > self.nrow(): |
---|
| 2577 | return |
---|
[976] | 2578 | from asap.asapfit import asapfit |
---|
[530] | 2579 | fit = asapfit(self._getfit(row)) |
---|
[1859] | 2580 | asaplog.push( '%s' %(fit) ) |
---|
| 2581 | return fit.as_dict() |
---|
[530] | 2582 | |
---|
[1483] | 2583 | def flag_nans(self): |
---|
[1846] | 2584 | """\ |
---|
[1483] | 2585 | Utility function to flag NaN values in the scantable. |
---|
| 2586 | """ |
---|
| 2587 | import numpy |
---|
| 2588 | basesel = self.get_selection() |
---|
| 2589 | for i in range(self.nrow()): |
---|
[1589] | 2590 | sel = self.get_row_selector(i) |
---|
| 2591 | self.set_selection(basesel+sel) |
---|
[1483] | 2592 | nans = numpy.isnan(self._getspectrum(0)) |
---|
| 2593 | if numpy.any(nans): |
---|
| 2594 | bnans = [ bool(v) for v in nans] |
---|
| 2595 | self.flag(bnans) |
---|
| 2596 | self.set_selection(basesel) |
---|
| 2597 | |
---|
[1588] | 2598 | def get_row_selector(self, rowno): |
---|
| 2599 | return selector(beams=self.getbeam(rowno), |
---|
| 2600 | ifs=self.getif(rowno), |
---|
| 2601 | pols=self.getpol(rowno), |
---|
| 2602 | scans=self.getscan(rowno), |
---|
| 2603 | cycles=self.getcycle(rowno)) |
---|
[1573] | 2604 | |
---|
[484] | 2605 | def _add_history(self, funcname, parameters): |
---|
[1435] | 2606 | if not rcParams['scantable.history']: |
---|
| 2607 | return |
---|
[484] | 2608 | # create date |
---|
| 2609 | sep = "##" |
---|
| 2610 | from datetime import datetime |
---|
| 2611 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
| 2612 | hist = dstr+sep |
---|
| 2613 | hist += funcname+sep#cdate+sep |
---|
| 2614 | if parameters.has_key('self'): del parameters['self'] |
---|
[1118] | 2615 | for k, v in parameters.iteritems(): |
---|
[484] | 2616 | if type(v) is dict: |
---|
[1118] | 2617 | for k2, v2 in v.iteritems(): |
---|
[484] | 2618 | hist += k2 |
---|
| 2619 | hist += "=" |
---|
[1118] | 2620 | if isinstance(v2, scantable): |
---|
[484] | 2621 | hist += 'scantable' |
---|
| 2622 | elif k2 == 'mask': |
---|
[1118] | 2623 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
[513] | 2624 | hist += str(self._zip_mask(v2)) |
---|
| 2625 | else: |
---|
| 2626 | hist += str(v2) |
---|
[484] | 2627 | else: |
---|
[513] | 2628 | hist += str(v2) |
---|
[484] | 2629 | else: |
---|
| 2630 | hist += k |
---|
| 2631 | hist += "=" |
---|
[1118] | 2632 | if isinstance(v, scantable): |
---|
[484] | 2633 | hist += 'scantable' |
---|
| 2634 | elif k == 'mask': |
---|
[1118] | 2635 | if isinstance(v, list) or isinstance(v, tuple): |
---|
[513] | 2636 | hist += str(self._zip_mask(v)) |
---|
| 2637 | else: |
---|
| 2638 | hist += str(v) |
---|
[484] | 2639 | else: |
---|
| 2640 | hist += str(v) |
---|
| 2641 | hist += sep |
---|
| 2642 | hist = hist[:-2] # remove trailing '##' |
---|
| 2643 | self._addhistory(hist) |
---|
| 2644 | |
---|
[710] | 2645 | |
---|
[484] | 2646 | def _zip_mask(self, mask): |
---|
| 2647 | mask = list(mask) |
---|
| 2648 | i = 0 |
---|
| 2649 | segments = [] |
---|
| 2650 | while mask[i:].count(1): |
---|
| 2651 | i += mask[i:].index(1) |
---|
| 2652 | if mask[i:].count(0): |
---|
| 2653 | j = i + mask[i:].index(0) |
---|
| 2654 | else: |
---|
[710] | 2655 | j = len(mask) |
---|
[1118] | 2656 | segments.append([i, j]) |
---|
[710] | 2657 | i = j |
---|
[484] | 2658 | return segments |
---|
[714] | 2659 | |
---|
[626] | 2660 | def _get_ordinate_label(self): |
---|
| 2661 | fu = "("+self.get_fluxunit()+")" |
---|
| 2662 | import re |
---|
| 2663 | lbl = "Intensity" |
---|
[1118] | 2664 | if re.match(".K.", fu): |
---|
[626] | 2665 | lbl = "Brightness Temperature "+ fu |
---|
[1118] | 2666 | elif re.match(".Jy.", fu): |
---|
[626] | 2667 | lbl = "Flux density "+ fu |
---|
| 2668 | return lbl |
---|
[710] | 2669 | |
---|
[876] | 2670 | def _check_ifs(self): |
---|
| 2671 | nchans = [self.nchan(i) for i in range(self.nif(-1))] |
---|
[889] | 2672 | nchans = filter(lambda t: t > 0, nchans) |
---|
[876] | 2673 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
[976] | 2674 | |
---|
[1862] | 2675 | @asaplog_post_dec |
---|
[1916] | 2676 | #def _fill(self, names, unit, average, getpt, antenna): |
---|
| 2677 | def _fill(self, names, unit, average, opts={}): |
---|
[976] | 2678 | first = True |
---|
| 2679 | fullnames = [] |
---|
| 2680 | for name in names: |
---|
| 2681 | name = os.path.expandvars(name) |
---|
| 2682 | name = os.path.expanduser(name) |
---|
| 2683 | if not os.path.exists(name): |
---|
| 2684 | msg = "File '%s' does not exists" % (name) |
---|
| 2685 | raise IOError(msg) |
---|
| 2686 | fullnames.append(name) |
---|
| 2687 | if average: |
---|
| 2688 | asaplog.push('Auto averaging integrations') |
---|
[1079] | 2689 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
[976] | 2690 | for name in fullnames: |
---|
[1073] | 2691 | tbl = Scantable(stype) |
---|
[1843] | 2692 | r = filler(tbl) |
---|
[1504] | 2693 | rx = rcParams['scantable.reference'] |
---|
[1843] | 2694 | r.setreferenceexpr(rx) |
---|
[976] | 2695 | msg = "Importing %s..." % (name) |
---|
[1118] | 2696 | asaplog.push(msg, False) |
---|
[1916] | 2697 | #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } |
---|
[1904] | 2698 | r.open(name, opts)# antenna, -1, -1, getpt) |
---|
[1843] | 2699 | r.fill() |
---|
[976] | 2700 | if average: |
---|
[1118] | 2701 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
[976] | 2702 | if not first: |
---|
| 2703 | tbl = self._math._merge([self, tbl]) |
---|
| 2704 | Scantable.__init__(self, tbl) |
---|
[1843] | 2705 | r.close() |
---|
[1118] | 2706 | del r, tbl |
---|
[976] | 2707 | first = False |
---|
[1861] | 2708 | #flush log |
---|
| 2709 | asaplog.post() |
---|
[976] | 2710 | if unit is not None: |
---|
| 2711 | self.set_fluxunit(unit) |
---|
[1824] | 2712 | if not is_casapy(): |
---|
| 2713 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[976] | 2714 | |
---|
[1402] | 2715 | def __getitem__(self, key): |
---|
| 2716 | if key < 0: |
---|
| 2717 | key += self.nrow() |
---|
| 2718 | if key >= self.nrow(): |
---|
| 2719 | raise IndexError("Row index out of range.") |
---|
| 2720 | return self._getspectrum(key) |
---|
| 2721 | |
---|
| 2722 | def __setitem__(self, key, value): |
---|
| 2723 | if key < 0: |
---|
| 2724 | key += self.nrow() |
---|
| 2725 | if key >= self.nrow(): |
---|
| 2726 | raise IndexError("Row index out of range.") |
---|
| 2727 | if not hasattr(value, "__len__") or \ |
---|
| 2728 | len(value) > self.nchan(self.getif(key)): |
---|
| 2729 | raise ValueError("Spectrum length doesn't match.") |
---|
| 2730 | return self._setspectrum(value, key) |
---|
| 2731 | |
---|
| 2732 | def __len__(self): |
---|
| 2733 | return self.nrow() |
---|
| 2734 | |
---|
| 2735 | def __iter__(self): |
---|
| 2736 | for i in range(len(self)): |
---|
| 2737 | yield self[i] |
---|