[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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[1948] | 4 | import numpy |
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[1691] | 5 | try: |
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| 6 | from functools import wraps as wraps_dec |
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| 7 | except ImportError: |
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| 8 | from asap.compatibility import wraps as wraps_dec |
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| 9 | |
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[1824] | 10 | from asap.env import is_casapy |
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[876] | 11 | from asap._asap import Scantable |
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[2004] | 12 | from asap._asap import filler, msfiller |
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[1824] | 13 | from asap.parameters import rcParams |
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[1862] | 14 | from asap.logging import asaplog, asaplog_post_dec |
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[1824] | 15 | from asap.selector import selector |
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| 16 | from asap.linecatalog import linecatalog |
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[1600] | 17 | from asap.coordinate import coordinate |
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[1859] | 18 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page |
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[1907] | 19 | from asap.asapfitter import fitter |
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[102] | 20 | |
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[1689] | 21 | |
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| 22 | def preserve_selection(func): |
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[1691] | 23 | @wraps_dec(func) |
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[1689] | 24 | def wrap(obj, *args, **kw): |
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| 25 | basesel = obj.get_selection() |
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[1857] | 26 | try: |
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| 27 | val = func(obj, *args, **kw) |
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| 28 | finally: |
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| 29 | obj.set_selection(basesel) |
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[1689] | 30 | return val |
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| 31 | return wrap |
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| 32 | |
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[1846] | 33 | def is_scantable(filename): |
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| 34 | """Is the given file a scantable? |
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[1689] | 35 | |
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[1846] | 36 | Parameters: |
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| 37 | |
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| 38 | filename: the name of the file/directory to test |
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| 39 | |
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| 40 | """ |
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[1883] | 41 | if ( os.path.isdir(filename) |
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| 42 | and os.path.exists(filename+'/table.info') |
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| 43 | and os.path.exists(filename+'/table.dat') ): |
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| 44 | f=open(filename+'/table.info') |
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| 45 | l=f.readline() |
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| 46 | f.close() |
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| 47 | #if ( l.find('Scantable') != -1 ): |
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| 48 | if ( l.find('Measurement Set') == -1 ): |
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| 49 | return True |
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| 50 | else: |
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| 51 | return False |
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| 52 | else: |
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| 53 | return False |
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| 54 | ## return (os.path.isdir(filename) |
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| 55 | ## and not os.path.exists(filename+'/table.f1') |
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| 56 | ## and os.path.exists(filename+'/table.info')) |
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[1697] | 57 | |
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[1883] | 58 | def is_ms(filename): |
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| 59 | """Is the given file a MeasurementSet? |
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[1697] | 60 | |
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[1883] | 61 | Parameters: |
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| 62 | |
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| 63 | filename: the name of the file/directory to test |
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| 64 | |
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| 65 | """ |
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| 66 | if ( os.path.isdir(filename) |
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| 67 | and os.path.exists(filename+'/table.info') |
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| 68 | and os.path.exists(filename+'/table.dat') ): |
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| 69 | f=open(filename+'/table.info') |
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| 70 | l=f.readline() |
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| 71 | f.close() |
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| 72 | if ( l.find('Measurement Set') != -1 ): |
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| 73 | return True |
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| 74 | else: |
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| 75 | return False |
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| 76 | else: |
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| 77 | return False |
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| 78 | |
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[876] | 79 | class scantable(Scantable): |
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[1846] | 80 | """\ |
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| 81 | The ASAP container for scans (single-dish data). |
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[102] | 82 | """ |
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[1819] | 83 | |
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[1862] | 84 | @asaplog_post_dec |
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[1916] | 85 | #def __init__(self, filename, average=None, unit=None, getpt=None, |
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| 86 | # antenna=None, parallactify=None): |
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| 87 | def __init__(self, filename, average=None, unit=None, parallactify=None, **args): |
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[1846] | 88 | """\ |
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[102] | 89 | Create a scantable from a saved one or make a reference |
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[1846] | 90 | |
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[102] | 91 | Parameters: |
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[1846] | 92 | |
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| 93 | filename: the name of an asap table on disk |
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| 94 | or |
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| 95 | the name of a rpfits/sdfits/ms file |
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| 96 | (integrations within scans are auto averaged |
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| 97 | and the whole file is read) or |
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| 98 | [advanced] a reference to an existing scantable |
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| 99 | |
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| 100 | average: average all integrations withinb a scan on read. |
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| 101 | The default (True) is taken from .asaprc. |
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| 102 | |
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[484] | 103 | unit: brightness unit; must be consistent with K or Jy. |
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[1846] | 104 | Over-rides the default selected by the filler |
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| 105 | (input rpfits/sdfits/ms) or replaces the value |
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| 106 | in existing scantables |
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| 107 | |
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| 108 | getpt: for MeasurementSet input data only: |
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| 109 | If True, all pointing data are filled. |
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| 110 | The deafult is False, which makes time to load |
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| 111 | the MS data faster in some cases. |
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| 112 | |
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[1920] | 113 | antenna: for MeasurementSet input data only: |
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| 114 | Antenna selection. integer (id) or string (name or id). |
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[1846] | 115 | |
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| 116 | parallactify: Indicate that the data had been parallatified. Default |
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| 117 | is taken from rc file. |
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| 118 | |
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[710] | 119 | """ |
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[976] | 120 | if average is None: |
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[710] | 121 | average = rcParams['scantable.autoaverage'] |
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[1916] | 122 | #if getpt is None: |
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| 123 | # getpt = True |
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| 124 | #if antenna is not None: |
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| 125 | # asaplog.push("Antenna selection currently unsupported." |
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| 126 | # "Using ''") |
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| 127 | # asaplog.post('WARN') |
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| 128 | #if antenna is None: |
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| 129 | # antenna = '' |
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| 130 | #elif type(antenna) == int: |
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| 131 | # antenna = '%s' % antenna |
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| 132 | #elif type(antenna) == list: |
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| 133 | # tmpstr = '' |
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| 134 | # for i in range( len(antenna) ): |
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| 135 | # if type(antenna[i]) == int: |
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| 136 | # tmpstr = tmpstr + ('%s,'%(antenna[i])) |
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| 137 | # elif type(antenna[i]) == str: |
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| 138 | # tmpstr=tmpstr+antenna[i]+',' |
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| 139 | # else: |
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| 140 | # raise TypeError('Bad antenna selection.') |
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| 141 | # antenna = tmpstr.rstrip(',') |
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[1593] | 142 | parallactify = parallactify or rcParams['scantable.parallactify'] |
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[1259] | 143 | varlist = vars() |
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[876] | 144 | from asap._asap import stmath |
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[1819] | 145 | self._math = stmath( rcParams['insitu'] ) |
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[876] | 146 | if isinstance(filename, Scantable): |
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| 147 | Scantable.__init__(self, filename) |
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[181] | 148 | else: |
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[1697] | 149 | if isinstance(filename, str): |
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[976] | 150 | filename = os.path.expandvars(filename) |
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| 151 | filename = os.path.expanduser(filename) |
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| 152 | if not os.path.exists(filename): |
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| 153 | s = "File '%s' not found." % (filename) |
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| 154 | raise IOError(s) |
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[1697] | 155 | if is_scantable(filename): |
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| 156 | ondisk = rcParams['scantable.storage'] == 'disk' |
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| 157 | Scantable.__init__(self, filename, ondisk) |
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| 158 | if unit is not None: |
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| 159 | self.set_fluxunit(unit) |
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[2008] | 160 | if average: |
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| 161 | self._assign( self.average_time( scanav=True ) ) |
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[1819] | 162 | # do not reset to the default freqframe |
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| 163 | #self.set_freqframe(rcParams['scantable.freqframe']) |
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[1883] | 164 | #elif os.path.isdir(filename) \ |
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| 165 | # and not os.path.exists(filename+'/table.f1'): |
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| 166 | elif is_ms(filename): |
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[1916] | 167 | # Measurement Set |
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| 168 | opts={'ms': {}} |
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| 169 | mskeys=['getpt','antenna'] |
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| 170 | for key in mskeys: |
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| 171 | if key in args.keys(): |
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| 172 | opts['ms'][key] = args[key] |
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| 173 | #self._fill([filename], unit, average, getpt, antenna) |
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| 174 | self._fill([filename], unit, average, opts) |
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[1893] | 175 | elif os.path.isfile(filename): |
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[1916] | 176 | #self._fill([filename], unit, average, getpt, antenna) |
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| 177 | self._fill([filename], unit, average) |
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[1883] | 178 | else: |
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[1819] | 179 | msg = "The given file '%s'is not a valid " \ |
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| 180 | "asap table." % (filename) |
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[1859] | 181 | raise IOError(msg) |
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[1118] | 182 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
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[976] | 183 | and isinstance(filename[-1], str): |
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[1916] | 184 | #self._fill(filename, unit, average, getpt, antenna) |
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| 185 | self._fill(filename, unit, average) |
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[1586] | 186 | self.parallactify(parallactify) |
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[1259] | 187 | self._add_history("scantable", varlist) |
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[102] | 188 | |
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[1862] | 189 | @asaplog_post_dec |
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[876] | 190 | def save(self, name=None, format=None, overwrite=False): |
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[1846] | 191 | """\ |
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[1280] | 192 | Store the scantable on disk. This can be an asap (aips++) Table, |
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| 193 | SDFITS or MS2 format. |
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[1846] | 194 | |
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[116] | 195 | Parameters: |
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[1846] | 196 | |
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[1093] | 197 | name: the name of the outputfile. For format "ASCII" |
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| 198 | this is the root file name (data in 'name'.txt |
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[497] | 199 | and header in 'name'_header.txt) |
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[1855] | 200 | |
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[116] | 201 | format: an optional file format. Default is ASAP. |
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[1855] | 202 | Allowed are: |
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| 203 | |
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| 204 | * 'ASAP' (save as ASAP [aips++] Table), |
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| 205 | * 'SDFITS' (save as SDFITS file) |
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| 206 | * 'ASCII' (saves as ascii text file) |
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| 207 | * 'MS2' (saves as an casacore MeasurementSet V2) |
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| 208 | * 'FITS' (save as image FITS - not readable by class) |
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| 209 | * 'CLASS' (save as FITS readable by CLASS) |
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| 210 | |
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[411] | 211 | overwrite: If the file should be overwritten if it exists. |
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[256] | 212 | The default False is to return with warning |
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[411] | 213 | without writing the output. USE WITH CARE. |
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[1855] | 214 | |
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[1846] | 215 | Example:: |
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| 216 | |
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[116] | 217 | scan.save('myscan.asap') |
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[1118] | 218 | scan.save('myscan.sdfits', 'SDFITS') |
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[1846] | 219 | |
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[116] | 220 | """ |
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[411] | 221 | from os import path |
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[1593] | 222 | format = format or rcParams['scantable.save'] |
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[256] | 223 | suffix = '.'+format.lower() |
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[1118] | 224 | if name is None or name == "": |
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[256] | 225 | name = 'scantable'+suffix |
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[718] | 226 | msg = "No filename given. Using default name %s..." % name |
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| 227 | asaplog.push(msg) |
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[411] | 228 | name = path.expandvars(name) |
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[256] | 229 | if path.isfile(name) or path.isdir(name): |
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| 230 | if not overwrite: |
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[718] | 231 | msg = "File %s exists." % name |
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[1859] | 232 | raise IOError(msg) |
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[451] | 233 | format2 = format.upper() |
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| 234 | if format2 == 'ASAP': |
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[116] | 235 | self._save(name) |
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[2029] | 236 | elif format2 == 'MS2': |
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| 237 | msopt = {'ms': {'overwrite': overwrite } } |
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| 238 | from asap._asap import mswriter |
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| 239 | writer = mswriter( self ) |
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| 240 | writer.write( name, msopt ) |
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[116] | 241 | else: |
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[989] | 242 | from asap._asap import stwriter as stw |
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[1118] | 243 | writer = stw(format2) |
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| 244 | writer.write(self, name) |
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[116] | 245 | return |
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| 246 | |
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[102] | 247 | def copy(self): |
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[1846] | 248 | """Return a copy of this scantable. |
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| 249 | |
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| 250 | *Note*: |
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| 251 | |
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[1348] | 252 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
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[1846] | 253 | |
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| 254 | Example:: |
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| 255 | |
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[102] | 256 | copiedscan = scan.copy() |
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[1846] | 257 | |
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[102] | 258 | """ |
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[876] | 259 | sd = scantable(Scantable._copy(self)) |
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[113] | 260 | return sd |
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| 261 | |
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[1093] | 262 | def drop_scan(self, scanid=None): |
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[1846] | 263 | """\ |
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[1093] | 264 | Return a new scantable where the specified scan number(s) has(have) |
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| 265 | been dropped. |
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[1846] | 266 | |
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[1093] | 267 | Parameters: |
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[1846] | 268 | |
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[1093] | 269 | scanid: a (list of) scan number(s) |
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[1846] | 270 | |
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[1093] | 271 | """ |
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| 272 | from asap import _is_sequence_or_number as _is_valid |
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| 273 | from asap import _to_list |
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| 274 | from asap import unique |
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| 275 | if not _is_valid(scanid): |
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[1859] | 276 | raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) |
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| 277 | scanid = _to_list(scanid) |
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| 278 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
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| 279 | for sid in scanid: allscans.remove(sid) |
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| 280 | if len(allscans) == 0: |
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| 281 | raise ValueError("Can't remove all scans") |
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| 282 | sel = selector(scans=allscans) |
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| 283 | return self._select_copy(sel) |
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[1093] | 284 | |
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[1594] | 285 | def _select_copy(self, selection): |
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| 286 | orig = self.get_selection() |
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| 287 | self.set_selection(orig+selection) |
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| 288 | cp = self.copy() |
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| 289 | self.set_selection(orig) |
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| 290 | return cp |
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| 291 | |
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[102] | 292 | def get_scan(self, scanid=None): |
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[1855] | 293 | """\ |
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[102] | 294 | Return a specific scan (by scanno) or collection of scans (by |
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| 295 | source name) in a new scantable. |
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[1846] | 296 | |
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| 297 | *Note*: |
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| 298 | |
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[1348] | 299 | See scantable.drop_scan() for the inverse operation. |
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[1846] | 300 | |
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[102] | 301 | Parameters: |
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[1846] | 302 | |
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[513] | 303 | scanid: a (list of) scanno or a source name, unix-style |
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| 304 | patterns are accepted for source name matching, e.g. |
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| 305 | '*_R' gets all 'ref scans |
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[1846] | 306 | |
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| 307 | Example:: |
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| 308 | |
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[513] | 309 | # get all scans containing the source '323p459' |
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| 310 | newscan = scan.get_scan('323p459') |
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| 311 | # get all 'off' scans |
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| 312 | refscans = scan.get_scan('*_R') |
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| 313 | # get a susbset of scans by scanno (as listed in scan.summary()) |
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[1118] | 314 | newscan = scan.get_scan([0, 2, 7, 10]) |
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[1846] | 315 | |
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[102] | 316 | """ |
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| 317 | if scanid is None: |
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[1859] | 318 | raise RuntimeError( 'Please specify a scan no or name to ' |
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| 319 | 'retrieve from the scantable' ) |
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[102] | 320 | try: |
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[946] | 321 | bsel = self.get_selection() |
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| 322 | sel = selector() |
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[102] | 323 | if type(scanid) is str: |
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[946] | 324 | sel.set_name(scanid) |
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[1594] | 325 | return self._select_copy(sel) |
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[102] | 326 | elif type(scanid) is int: |
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[946] | 327 | sel.set_scans([scanid]) |
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[1594] | 328 | return self._select_copy(sel) |
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[381] | 329 | elif type(scanid) is list: |
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[946] | 330 | sel.set_scans(scanid) |
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[1594] | 331 | return self._select_copy(sel) |
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[381] | 332 | else: |
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[718] | 333 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
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[1859] | 334 | raise TypeError(msg) |
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[102] | 335 | except RuntimeError: |
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[1859] | 336 | raise |
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[102] | 337 | |
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| 338 | def __str__(self): |
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[2178] | 339 | return Scantable._summary(self) |
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[102] | 340 | |
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[976] | 341 | def summary(self, filename=None): |
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[1846] | 342 | """\ |
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[102] | 343 | Print a summary of the contents of this scantable. |
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[1846] | 344 | |
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[102] | 345 | Parameters: |
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[1846] | 346 | |
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[1931] | 347 | filename: the name of a file to write the putput to |
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[102] | 348 | Default - no file output |
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[1846] | 349 | |
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[102] | 350 | """ |
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[2178] | 351 | info = Scantable._summary(self) |
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[102] | 352 | if filename is not None: |
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[256] | 353 | if filename is "": |
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| 354 | filename = 'scantable_summary.txt' |
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[415] | 355 | from os.path import expandvars, isdir |
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[411] | 356 | filename = expandvars(filename) |
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[415] | 357 | if not isdir(filename): |
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[413] | 358 | data = open(filename, 'w') |
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| 359 | data.write(info) |
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| 360 | data.close() |
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| 361 | else: |
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[718] | 362 | msg = "Illegal file name '%s'." % (filename) |
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[1859] | 363 | raise IOError(msg) |
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| 364 | return page(info) |
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[710] | 365 | |
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[1512] | 366 | def get_spectrum(self, rowno): |
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[1471] | 367 | """Return the spectrum for the current row in the scantable as a list. |
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[1846] | 368 | |
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[1471] | 369 | Parameters: |
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[1846] | 370 | |
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[1573] | 371 | rowno: the row number to retrieve the spectrum from |
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[1846] | 372 | |
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[1471] | 373 | """ |
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| 374 | return self._getspectrum(rowno) |
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[946] | 375 | |
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[1471] | 376 | def get_mask(self, rowno): |
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| 377 | """Return the mask for the current row in the scantable as a list. |
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[1846] | 378 | |
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[1471] | 379 | Parameters: |
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[1846] | 380 | |
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[1573] | 381 | rowno: the row number to retrieve the mask from |
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[1846] | 382 | |
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[1471] | 383 | """ |
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| 384 | return self._getmask(rowno) |
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| 385 | |
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| 386 | def set_spectrum(self, spec, rowno): |
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[1938] | 387 | """Set the spectrum for the current row in the scantable. |
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[1846] | 388 | |
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[1471] | 389 | Parameters: |
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[1846] | 390 | |
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[1855] | 391 | spec: the new spectrum |
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[1846] | 392 | |
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[1855] | 393 | rowno: the row number to set the spectrum for |
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| 394 | |
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[1471] | 395 | """ |
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| 396 | assert(len(spec) == self.nchan()) |
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| 397 | return self._setspectrum(spec, rowno) |
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| 398 | |
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[1600] | 399 | def get_coordinate(self, rowno): |
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| 400 | """Return the (spectral) coordinate for a a given 'rowno'. |
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[1846] | 401 | |
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| 402 | *Note*: |
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| 403 | |
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[1600] | 404 | * This coordinate is only valid until a scantable method modifies |
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| 405 | the frequency axis. |
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| 406 | * This coordinate does contain the original frequency set-up |
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| 407 | NOT the new frame. The conversions however are done using the user |
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| 408 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
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| 409 | use scantable.freq_align first. Without it there is no closure, |
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[1846] | 410 | i.e.:: |
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[1600] | 411 | |
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[1846] | 412 | c = myscan.get_coordinate(0) |
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| 413 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
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| 414 | |
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[1600] | 415 | Parameters: |
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[1846] | 416 | |
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[1600] | 417 | rowno: the row number for the spectral coordinate |
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| 418 | |
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| 419 | """ |
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| 420 | return coordinate(Scantable.get_coordinate(self, rowno)) |
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| 421 | |
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[946] | 422 | def get_selection(self): |
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[1846] | 423 | """\ |
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[1005] | 424 | Get the selection object currently set on this scantable. |
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[1846] | 425 | |
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| 426 | Example:: |
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| 427 | |
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[1005] | 428 | sel = scan.get_selection() |
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| 429 | sel.set_ifs(0) # select IF 0 |
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| 430 | scan.set_selection(sel) # apply modified selection |
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[1846] | 431 | |
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[946] | 432 | """ |
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| 433 | return selector(self._getselection()) |
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| 434 | |
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[1576] | 435 | def set_selection(self, selection=None, **kw): |
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[1846] | 436 | """\ |
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[1005] | 437 | Select a subset of the data. All following operations on this scantable |
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| 438 | are only applied to thi selection. |
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[1846] | 439 | |
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[1005] | 440 | Parameters: |
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[1697] | 441 | |
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[1846] | 442 | selection: a selector object (default unset the selection), or |
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| 443 | any combination of "pols", "ifs", "beams", "scans", |
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| 444 | "cycles", "name", "query" |
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[1697] | 445 | |
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[1846] | 446 | Examples:: |
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[1697] | 447 | |
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[1005] | 448 | sel = selector() # create a selection object |
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[1118] | 449 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
---|
[1005] | 450 | scan.set_selection(sel) # set the selection |
---|
| 451 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 452 | scan.set_selection() # unset the selection |
---|
[1697] | 453 | # or the equivalent |
---|
| 454 | scan.set_selection(scans=[0,3]) |
---|
| 455 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 456 | scan.set_selection() # unset the selection |
---|
[1846] | 457 | |
---|
[946] | 458 | """ |
---|
[1576] | 459 | if selection is None: |
---|
| 460 | # reset |
---|
| 461 | if len(kw) == 0: |
---|
| 462 | selection = selector() |
---|
| 463 | else: |
---|
| 464 | # try keywords |
---|
| 465 | for k in kw: |
---|
| 466 | if k not in selector.fields: |
---|
| 467 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
---|
| 468 | selection = selector(**kw) |
---|
[946] | 469 | self._setselection(selection) |
---|
| 470 | |
---|
[1819] | 471 | def get_row(self, row=0, insitu=None): |
---|
[1846] | 472 | """\ |
---|
[1819] | 473 | Select a row in the scantable. |
---|
| 474 | Return a scantable with single row. |
---|
[1846] | 475 | |
---|
[1819] | 476 | Parameters: |
---|
[1846] | 477 | |
---|
| 478 | row: row no of integration, default is 0. |
---|
| 479 | insitu: if False a new scantable is returned. Otherwise, the |
---|
| 480 | scaling is done in-situ. The default is taken from .asaprc |
---|
| 481 | (False) |
---|
| 482 | |
---|
[1819] | 483 | """ |
---|
| 484 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 485 | if not insitu: |
---|
| 486 | workscan = self.copy() |
---|
| 487 | else: |
---|
| 488 | workscan = self |
---|
| 489 | # Select a row |
---|
| 490 | sel=selector() |
---|
[1992] | 491 | sel.set_rows([row]) |
---|
| 492 | #sel.set_scans([workscan.getscan(row)]) |
---|
| 493 | #sel.set_cycles([workscan.getcycle(row)]) |
---|
| 494 | #sel.set_beams([workscan.getbeam(row)]) |
---|
| 495 | #sel.set_ifs([workscan.getif(row)]) |
---|
| 496 | #sel.set_polarisations([workscan.getpol(row)]) |
---|
| 497 | #sel.set_name(workscan._getsourcename(row)) |
---|
[1819] | 498 | workscan.set_selection(sel) |
---|
| 499 | if not workscan.nrow() == 1: |
---|
| 500 | msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) |
---|
| 501 | raise RuntimeError(msg) |
---|
| 502 | del sel |
---|
| 503 | if insitu: |
---|
| 504 | self._assign(workscan) |
---|
| 505 | else: |
---|
| 506 | return workscan |
---|
| 507 | |
---|
[1862] | 508 | @asaplog_post_dec |
---|
[1907] | 509 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
---|
[1846] | 510 | """\ |
---|
[135] | 511 | Determine the specified statistic of the current beam/if/pol |
---|
[102] | 512 | Takes a 'mask' as an optional parameter to specify which |
---|
| 513 | channels should be excluded. |
---|
[1846] | 514 | |
---|
[102] | 515 | Parameters: |
---|
[1846] | 516 | |
---|
[1819] | 517 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
---|
| 518 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
---|
[1855] | 519 | |
---|
[135] | 520 | mask: an optional mask specifying where the statistic |
---|
[102] | 521 | should be determined. |
---|
[1855] | 522 | |
---|
[1819] | 523 | form: format string to print statistic values |
---|
[1846] | 524 | |
---|
[1907] | 525 | row: row number of spectrum to process. |
---|
| 526 | (default is None: for all rows) |
---|
[1846] | 527 | |
---|
[1907] | 528 | Example: |
---|
[113] | 529 | scan.set_unit('channel') |
---|
[1118] | 530 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 531 | scan.stats(stat='mean', mask=m) |
---|
[1846] | 532 | |
---|
[102] | 533 | """ |
---|
[1593] | 534 | mask = mask or [] |
---|
[876] | 535 | if not self._check_ifs(): |
---|
[1118] | 536 | raise ValueError("Cannot apply mask as the IFs have different " |
---|
| 537 | "number of channels. Please use setselection() " |
---|
| 538 | "to select individual IFs") |
---|
[1819] | 539 | rtnabc = False |
---|
| 540 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
| 541 | getchan = False |
---|
| 542 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
| 543 | chan = self._math._minmaxchan(self, mask, stat) |
---|
| 544 | getchan = True |
---|
| 545 | statvals = [] |
---|
[1907] | 546 | if not rtnabc: |
---|
| 547 | if row == None: |
---|
| 548 | statvals = self._math._stats(self, mask, stat) |
---|
| 549 | else: |
---|
| 550 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
[256] | 551 | |
---|
[1819] | 552 | #def cb(i): |
---|
| 553 | # return statvals[i] |
---|
[256] | 554 | |
---|
[1819] | 555 | #return self._row_callback(cb, stat) |
---|
[102] | 556 | |
---|
[1819] | 557 | label=stat |
---|
| 558 | #callback=cb |
---|
| 559 | out = "" |
---|
| 560 | #outvec = [] |
---|
| 561 | sep = '-'*50 |
---|
[1907] | 562 | |
---|
| 563 | if row == None: |
---|
| 564 | rows = xrange(self.nrow()) |
---|
| 565 | elif isinstance(row, int): |
---|
| 566 | rows = [ row ] |
---|
| 567 | |
---|
| 568 | for i in rows: |
---|
[1819] | 569 | refstr = '' |
---|
| 570 | statunit= '' |
---|
| 571 | if getchan: |
---|
| 572 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
| 573 | if rtnabc: |
---|
| 574 | statvals.append(qx['value']) |
---|
| 575 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
| 576 | statunit= '['+qx['unit']+']' |
---|
| 577 | else: |
---|
| 578 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
| 579 | |
---|
| 580 | tm = self._gettime(i) |
---|
| 581 | src = self._getsourcename(i) |
---|
| 582 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
| 583 | out += 'Time[%s]:\n' % (tm) |
---|
[1907] | 584 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 585 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 586 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[1819] | 587 | #outvec.append(callback(i)) |
---|
[1907] | 588 | if len(rows) > 1: |
---|
| 589 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
| 590 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
| 591 | else: |
---|
| 592 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
| 593 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
[1819] | 594 | out += sep+"\n" |
---|
| 595 | |
---|
[1859] | 596 | import os |
---|
| 597 | if os.environ.has_key( 'USER' ): |
---|
| 598 | usr = os.environ['USER'] |
---|
| 599 | else: |
---|
| 600 | import commands |
---|
| 601 | usr = commands.getoutput( 'whoami' ) |
---|
| 602 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
| 603 | f = open(tmpfile,'w') |
---|
| 604 | print >> f, sep |
---|
| 605 | print >> f, ' %s %s' % (label, statunit) |
---|
| 606 | print >> f, sep |
---|
| 607 | print >> f, out |
---|
| 608 | f.close() |
---|
| 609 | f = open(tmpfile,'r') |
---|
| 610 | x = f.readlines() |
---|
| 611 | f.close() |
---|
| 612 | asaplog.push(''.join(x), False) |
---|
| 613 | |
---|
[1819] | 614 | return statvals |
---|
| 615 | |
---|
| 616 | def chan2data(self, rowno=0, chan=0): |
---|
[1846] | 617 | """\ |
---|
[1819] | 618 | Returns channel/frequency/velocity and spectral value |
---|
| 619 | at an arbitrary row and channel in the scantable. |
---|
[1846] | 620 | |
---|
[1819] | 621 | Parameters: |
---|
[1846] | 622 | |
---|
[1819] | 623 | rowno: a row number in the scantable. Default is the |
---|
| 624 | first row, i.e. rowno=0 |
---|
[1855] | 625 | |
---|
[1819] | 626 | chan: a channel in the scantable. Default is the first |
---|
| 627 | channel, i.e. pos=0 |
---|
[1846] | 628 | |
---|
[1819] | 629 | """ |
---|
| 630 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
| 631 | qx = {'unit': self.get_unit(), |
---|
| 632 | 'value': self._getabcissa(rowno)[chan]} |
---|
| 633 | qy = {'unit': self.get_fluxunit(), |
---|
| 634 | 'value': self._getspectrum(rowno)[chan]} |
---|
| 635 | return qx, qy |
---|
| 636 | |
---|
[1118] | 637 | def stddev(self, mask=None): |
---|
[1846] | 638 | """\ |
---|
[135] | 639 | Determine the standard deviation of the current beam/if/pol |
---|
| 640 | Takes a 'mask' as an optional parameter to specify which |
---|
| 641 | channels should be excluded. |
---|
[1846] | 642 | |
---|
[135] | 643 | Parameters: |
---|
[1846] | 644 | |
---|
[135] | 645 | mask: an optional mask specifying where the standard |
---|
| 646 | deviation should be determined. |
---|
| 647 | |
---|
[1846] | 648 | Example:: |
---|
| 649 | |
---|
[135] | 650 | scan.set_unit('channel') |
---|
[1118] | 651 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 652 | scan.stddev(mask=m) |
---|
[1846] | 653 | |
---|
[135] | 654 | """ |
---|
[1118] | 655 | return self.stats(stat='stddev', mask=mask); |
---|
[135] | 656 | |
---|
[1003] | 657 | |
---|
[1259] | 658 | def get_column_names(self): |
---|
[1846] | 659 | """\ |
---|
[1003] | 660 | Return a list of column names, which can be used for selection. |
---|
| 661 | """ |
---|
[1259] | 662 | return list(Scantable.get_column_names(self)) |
---|
[1003] | 663 | |
---|
[1730] | 664 | def get_tsys(self, row=-1): |
---|
[1846] | 665 | """\ |
---|
[113] | 666 | Return the System temperatures. |
---|
[1846] | 667 | |
---|
| 668 | Parameters: |
---|
| 669 | |
---|
| 670 | row: the rowno to get the information for. (default all rows) |
---|
| 671 | |
---|
[113] | 672 | Returns: |
---|
[1846] | 673 | |
---|
[876] | 674 | a list of Tsys values for the current selection |
---|
[1846] | 675 | |
---|
[113] | 676 | """ |
---|
[1730] | 677 | if row > -1: |
---|
| 678 | return self._get_column(self._gettsys, row) |
---|
[876] | 679 | return self._row_callback(self._gettsys, "Tsys") |
---|
[256] | 680 | |
---|
[1730] | 681 | |
---|
| 682 | def get_weather(self, row=-1): |
---|
[1846] | 683 | """\ |
---|
| 684 | Return the weather informations. |
---|
| 685 | |
---|
| 686 | Parameters: |
---|
| 687 | |
---|
| 688 | row: the rowno to get the information for. (default all rows) |
---|
| 689 | |
---|
| 690 | Returns: |
---|
| 691 | |
---|
| 692 | a dict or list of of dicts of values for the current selection |
---|
| 693 | |
---|
| 694 | """ |
---|
| 695 | |
---|
[1730] | 696 | values = self._get_column(self._get_weather, row) |
---|
| 697 | if row > -1: |
---|
| 698 | return {'temperature': values[0], |
---|
| 699 | 'pressure': values[1], 'humidity' : values[2], |
---|
| 700 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
| 701 | } |
---|
| 702 | else: |
---|
| 703 | out = [] |
---|
| 704 | for r in values: |
---|
| 705 | |
---|
| 706 | out.append({'temperature': r[0], |
---|
| 707 | 'pressure': r[1], 'humidity' : r[2], |
---|
| 708 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
| 709 | }) |
---|
| 710 | return out |
---|
| 711 | |
---|
[876] | 712 | def _row_callback(self, callback, label): |
---|
| 713 | out = "" |
---|
[1118] | 714 | outvec = [] |
---|
[1590] | 715 | sep = '-'*50 |
---|
[876] | 716 | for i in range(self.nrow()): |
---|
| 717 | tm = self._gettime(i) |
---|
| 718 | src = self._getsourcename(i) |
---|
[1590] | 719 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
[876] | 720 | out += 'Time[%s]:\n' % (tm) |
---|
[1590] | 721 | if self.nbeam(-1) > 1: |
---|
| 722 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 723 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 724 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[876] | 725 | outvec.append(callback(i)) |
---|
| 726 | out += '= %3.3f\n' % (outvec[i]) |
---|
[1590] | 727 | out += sep+'\n' |
---|
[1859] | 728 | |
---|
| 729 | asaplog.push(sep) |
---|
| 730 | asaplog.push(" %s" % (label)) |
---|
| 731 | asaplog.push(sep) |
---|
| 732 | asaplog.push(out) |
---|
[1861] | 733 | asaplog.post() |
---|
[1175] | 734 | return outvec |
---|
[256] | 735 | |
---|
[1947] | 736 | def _get_column(self, callback, row=-1, *args): |
---|
[1070] | 737 | """ |
---|
| 738 | """ |
---|
| 739 | if row == -1: |
---|
[1947] | 740 | return [callback(i, *args) for i in range(self.nrow())] |
---|
[1070] | 741 | else: |
---|
[1819] | 742 | if 0 <= row < self.nrow(): |
---|
[1947] | 743 | return callback(row, *args) |
---|
[256] | 744 | |
---|
[1070] | 745 | |
---|
[1948] | 746 | def get_time(self, row=-1, asdatetime=False, prec=-1): |
---|
[1846] | 747 | """\ |
---|
[113] | 748 | Get a list of time stamps for the observations. |
---|
[1938] | 749 | Return a datetime object or a string (default) for each |
---|
| 750 | integration time stamp in the scantable. |
---|
[1846] | 751 | |
---|
[113] | 752 | Parameters: |
---|
[1846] | 753 | |
---|
[1348] | 754 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 755 | |
---|
[1348] | 756 | asdatetime: return values as datetime objects rather than strings |
---|
[1846] | 757 | |
---|
[1948] | 758 | prec: number of digits shown. Default -1 to automatic calculation. |
---|
| 759 | Note this number is equals to the digits of MVTime, |
---|
| 760 | i.e., 0<prec<3: dates with hh:: only, |
---|
| 761 | <5: with hh:mm:, <7 or 0: with hh:mm:ss, |
---|
[1947] | 762 | and 6> : with hh:mm:ss.tt... (prec-6 t's added) |
---|
| 763 | |
---|
[113] | 764 | """ |
---|
[1175] | 765 | from datetime import datetime |
---|
[1948] | 766 | if prec < 0: |
---|
| 767 | # automagically set necessary precision +1 |
---|
[1950] | 768 | prec = 7 - numpy.floor(numpy.log10(numpy.min(self.get_inttime(row)))) |
---|
[1948] | 769 | prec = max(6, int(prec)) |
---|
| 770 | else: |
---|
| 771 | prec = max(0, prec) |
---|
| 772 | if asdatetime: |
---|
| 773 | #precision can be 1 millisecond at max |
---|
| 774 | prec = min(12, prec) |
---|
| 775 | |
---|
[1947] | 776 | times = self._get_column(self._gettime, row, prec) |
---|
[1348] | 777 | if not asdatetime: |
---|
[1392] | 778 | return times |
---|
[1947] | 779 | format = "%Y/%m/%d/%H:%M:%S.%f" |
---|
| 780 | if prec < 7: |
---|
| 781 | nsub = 1 + (((6-prec)/2) % 3) |
---|
| 782 | substr = [".%f","%S","%M"] |
---|
| 783 | for i in range(nsub): |
---|
| 784 | format = format.replace(substr[i],"") |
---|
[1175] | 785 | if isinstance(times, list): |
---|
[1947] | 786 | return [datetime.strptime(i, format) for i in times] |
---|
[1175] | 787 | else: |
---|
[1947] | 788 | return datetime.strptime(times, format) |
---|
[102] | 789 | |
---|
[1348] | 790 | |
---|
| 791 | def get_inttime(self, row=-1): |
---|
[1846] | 792 | """\ |
---|
[1348] | 793 | Get a list of integration times for the observations. |
---|
| 794 | Return a time in seconds for each integration in the scantable. |
---|
[1846] | 795 | |
---|
[1348] | 796 | Parameters: |
---|
[1846] | 797 | |
---|
[1348] | 798 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 799 | |
---|
[1348] | 800 | """ |
---|
[1573] | 801 | return self._get_column(self._getinttime, row) |
---|
[1348] | 802 | |
---|
[1573] | 803 | |
---|
[714] | 804 | def get_sourcename(self, row=-1): |
---|
[1846] | 805 | """\ |
---|
[794] | 806 | Get a list source names for the observations. |
---|
[714] | 807 | Return a string for each integration in the scantable. |
---|
| 808 | Parameters: |
---|
[1846] | 809 | |
---|
[1348] | 810 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 811 | |
---|
[714] | 812 | """ |
---|
[1070] | 813 | return self._get_column(self._getsourcename, row) |
---|
[714] | 814 | |
---|
[794] | 815 | def get_elevation(self, row=-1): |
---|
[1846] | 816 | """\ |
---|
[794] | 817 | Get a list of elevations for the observations. |
---|
| 818 | Return a float for each integration in the scantable. |
---|
[1846] | 819 | |
---|
[794] | 820 | Parameters: |
---|
[1846] | 821 | |
---|
[1348] | 822 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 823 | |
---|
[794] | 824 | """ |
---|
[1070] | 825 | return self._get_column(self._getelevation, row) |
---|
[794] | 826 | |
---|
| 827 | def get_azimuth(self, row=-1): |
---|
[1846] | 828 | """\ |
---|
[794] | 829 | Get a list of azimuths for the observations. |
---|
| 830 | Return a float for each integration in the scantable. |
---|
[1846] | 831 | |
---|
[794] | 832 | Parameters: |
---|
[1348] | 833 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 834 | |
---|
[794] | 835 | """ |
---|
[1070] | 836 | return self._get_column(self._getazimuth, row) |
---|
[794] | 837 | |
---|
| 838 | def get_parangle(self, row=-1): |
---|
[1846] | 839 | """\ |
---|
[794] | 840 | Get a list of parallactic angles for the observations. |
---|
| 841 | Return a float for each integration in the scantable. |
---|
[1846] | 842 | |
---|
[794] | 843 | Parameters: |
---|
[1846] | 844 | |
---|
[1348] | 845 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 846 | |
---|
[794] | 847 | """ |
---|
[1070] | 848 | return self._get_column(self._getparangle, row) |
---|
[794] | 849 | |
---|
[1070] | 850 | def get_direction(self, row=-1): |
---|
| 851 | """ |
---|
| 852 | Get a list of Positions on the sky (direction) for the observations. |
---|
[1594] | 853 | Return a string for each integration in the scantable. |
---|
[1855] | 854 | |
---|
[1070] | 855 | Parameters: |
---|
[1855] | 856 | |
---|
[1070] | 857 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 858 | |
---|
[1070] | 859 | """ |
---|
| 860 | return self._get_column(self._getdirection, row) |
---|
| 861 | |
---|
[1391] | 862 | def get_directionval(self, row=-1): |
---|
[1846] | 863 | """\ |
---|
[1391] | 864 | Get a list of Positions on the sky (direction) for the observations. |
---|
| 865 | Return a float for each integration in the scantable. |
---|
[1846] | 866 | |
---|
[1391] | 867 | Parameters: |
---|
[1846] | 868 | |
---|
[1391] | 869 | row: row no of integration. Default -1 return all rows |
---|
[1846] | 870 | |
---|
[1391] | 871 | """ |
---|
| 872 | return self._get_column(self._getdirectionvec, row) |
---|
| 873 | |
---|
[1862] | 874 | @asaplog_post_dec |
---|
[102] | 875 | def set_unit(self, unit='channel'): |
---|
[1846] | 876 | """\ |
---|
[102] | 877 | Set the unit for all following operations on this scantable |
---|
[1846] | 878 | |
---|
[102] | 879 | Parameters: |
---|
[1846] | 880 | |
---|
| 881 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
| 882 | 'km/s', 'channel' or equivalent '' |
---|
| 883 | |
---|
[102] | 884 | """ |
---|
[484] | 885 | varlist = vars() |
---|
[1118] | 886 | if unit in ['', 'pixel', 'channel']: |
---|
[113] | 887 | unit = '' |
---|
| 888 | inf = list(self._getcoordinfo()) |
---|
| 889 | inf[0] = unit |
---|
| 890 | self._setcoordinfo(inf) |
---|
[1118] | 891 | self._add_history("set_unit", varlist) |
---|
[113] | 892 | |
---|
[1862] | 893 | @asaplog_post_dec |
---|
[484] | 894 | def set_instrument(self, instr): |
---|
[1846] | 895 | """\ |
---|
[1348] | 896 | Set the instrument for subsequent processing. |
---|
[1846] | 897 | |
---|
[358] | 898 | Parameters: |
---|
[1846] | 899 | |
---|
[710] | 900 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
[407] | 901 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
[1846] | 902 | |
---|
[358] | 903 | """ |
---|
| 904 | self._setInstrument(instr) |
---|
[1118] | 905 | self._add_history("set_instument", vars()) |
---|
[358] | 906 | |
---|
[1862] | 907 | @asaplog_post_dec |
---|
[1190] | 908 | def set_feedtype(self, feedtype): |
---|
[1846] | 909 | """\ |
---|
[1190] | 910 | Overwrite the feed type, which might not be set correctly. |
---|
[1846] | 911 | |
---|
[1190] | 912 | Parameters: |
---|
[1846] | 913 | |
---|
[1190] | 914 | feedtype: 'linear' or 'circular' |
---|
[1846] | 915 | |
---|
[1190] | 916 | """ |
---|
| 917 | self._setfeedtype(feedtype) |
---|
| 918 | self._add_history("set_feedtype", vars()) |
---|
| 919 | |
---|
[1862] | 920 | @asaplog_post_dec |
---|
[276] | 921 | def set_doppler(self, doppler='RADIO'): |
---|
[1846] | 922 | """\ |
---|
[276] | 923 | Set the doppler for all following operations on this scantable. |
---|
[1846] | 924 | |
---|
[276] | 925 | Parameters: |
---|
[1846] | 926 | |
---|
[276] | 927 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
[1846] | 928 | |
---|
[276] | 929 | """ |
---|
[484] | 930 | varlist = vars() |
---|
[276] | 931 | inf = list(self._getcoordinfo()) |
---|
| 932 | inf[2] = doppler |
---|
| 933 | self._setcoordinfo(inf) |
---|
[1118] | 934 | self._add_history("set_doppler", vars()) |
---|
[710] | 935 | |
---|
[1862] | 936 | @asaplog_post_dec |
---|
[226] | 937 | def set_freqframe(self, frame=None): |
---|
[1846] | 938 | """\ |
---|
[113] | 939 | Set the frame type of the Spectral Axis. |
---|
[1846] | 940 | |
---|
[113] | 941 | Parameters: |
---|
[1846] | 942 | |
---|
[591] | 943 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
[1819] | 944 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
[1118] | 945 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
[1846] | 946 | |
---|
| 947 | Example:: |
---|
| 948 | |
---|
[113] | 949 | scan.set_freqframe('BARY') |
---|
[1846] | 950 | |
---|
[113] | 951 | """ |
---|
[1593] | 952 | frame = frame or rcParams['scantable.freqframe'] |
---|
[484] | 953 | varlist = vars() |
---|
[1819] | 954 | # "REST" is not implemented in casacore |
---|
| 955 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
| 956 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
| 957 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
[1118] | 958 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
[591] | 959 | |
---|
[989] | 960 | if frame in valid: |
---|
[113] | 961 | inf = list(self._getcoordinfo()) |
---|
| 962 | inf[1] = frame |
---|
| 963 | self._setcoordinfo(inf) |
---|
[1118] | 964 | self._add_history("set_freqframe", varlist) |
---|
[102] | 965 | else: |
---|
[1118] | 966 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
[1859] | 967 | raise TypeError(msg) |
---|
[710] | 968 | |
---|
[1862] | 969 | @asaplog_post_dec |
---|
[989] | 970 | def set_dirframe(self, frame=""): |
---|
[1846] | 971 | """\ |
---|
[989] | 972 | Set the frame type of the Direction on the sky. |
---|
[1846] | 973 | |
---|
[989] | 974 | Parameters: |
---|
[1846] | 975 | |
---|
[989] | 976 | frame: an optional frame type, default ''. Valid frames are: |
---|
| 977 | 'J2000', 'B1950', 'GALACTIC' |
---|
[1846] | 978 | |
---|
| 979 | Example: |
---|
| 980 | |
---|
[989] | 981 | scan.set_dirframe('GALACTIC') |
---|
[1846] | 982 | |
---|
[989] | 983 | """ |
---|
| 984 | varlist = vars() |
---|
[1859] | 985 | Scantable.set_dirframe(self, frame) |
---|
[1118] | 986 | self._add_history("set_dirframe", varlist) |
---|
[989] | 987 | |
---|
[113] | 988 | def get_unit(self): |
---|
[1846] | 989 | """\ |
---|
[113] | 990 | Get the default unit set in this scantable |
---|
[1846] | 991 | |
---|
[113] | 992 | Returns: |
---|
[1846] | 993 | |
---|
[113] | 994 | A unit string |
---|
[1846] | 995 | |
---|
[113] | 996 | """ |
---|
| 997 | inf = self._getcoordinfo() |
---|
| 998 | unit = inf[0] |
---|
| 999 | if unit == '': unit = 'channel' |
---|
| 1000 | return unit |
---|
[102] | 1001 | |
---|
[1862] | 1002 | @asaplog_post_dec |
---|
[158] | 1003 | def get_abcissa(self, rowno=0): |
---|
[1846] | 1004 | """\ |
---|
[158] | 1005 | Get the abcissa in the current coordinate setup for the currently |
---|
[113] | 1006 | selected Beam/IF/Pol |
---|
[1846] | 1007 | |
---|
[113] | 1008 | Parameters: |
---|
[1846] | 1009 | |
---|
[226] | 1010 | rowno: an optional row number in the scantable. Default is the |
---|
| 1011 | first row, i.e. rowno=0 |
---|
[1846] | 1012 | |
---|
[113] | 1013 | Returns: |
---|
[1846] | 1014 | |
---|
[1348] | 1015 | The abcissa values and the format string (as a dictionary) |
---|
[1846] | 1016 | |
---|
[113] | 1017 | """ |
---|
[256] | 1018 | abc = self._getabcissa(rowno) |
---|
[710] | 1019 | lbl = self._getabcissalabel(rowno) |
---|
[158] | 1020 | return abc, lbl |
---|
[113] | 1021 | |
---|
[1862] | 1022 | @asaplog_post_dec |
---|
[1994] | 1023 | def flag(self, row=-1, mask=None, unflag=False): |
---|
[1846] | 1024 | """\ |
---|
[1001] | 1025 | Flag the selected data using an optional channel mask. |
---|
[1846] | 1026 | |
---|
[1001] | 1027 | Parameters: |
---|
[1846] | 1028 | |
---|
[1994] | 1029 | row: an optional row number in the scantable. |
---|
| 1030 | Default -1 flags all rows |
---|
| 1031 | |
---|
[1001] | 1032 | mask: an optional channel mask, created with create_mask. Default |
---|
| 1033 | (no mask) is all channels. |
---|
[1855] | 1034 | |
---|
[1819] | 1035 | unflag: if True, unflag the data |
---|
[1846] | 1036 | |
---|
[1001] | 1037 | """ |
---|
| 1038 | varlist = vars() |
---|
[1593] | 1039 | mask = mask or [] |
---|
[1994] | 1040 | self._flag(row, mask, unflag) |
---|
[1001] | 1041 | self._add_history("flag", varlist) |
---|
| 1042 | |
---|
[1862] | 1043 | @asaplog_post_dec |
---|
[1819] | 1044 | def flag_row(self, rows=[], unflag=False): |
---|
[1846] | 1045 | """\ |
---|
[1819] | 1046 | Flag the selected data in row-based manner. |
---|
[1846] | 1047 | |
---|
[1819] | 1048 | Parameters: |
---|
[1846] | 1049 | |
---|
[1843] | 1050 | rows: list of row numbers to be flagged. Default is no row |
---|
| 1051 | (must be explicitly specified to execute row-based flagging). |
---|
[1855] | 1052 | |
---|
[1819] | 1053 | unflag: if True, unflag the data. |
---|
[1846] | 1054 | |
---|
[1819] | 1055 | """ |
---|
| 1056 | varlist = vars() |
---|
[1859] | 1057 | self._flag_row(rows, unflag) |
---|
[1819] | 1058 | self._add_history("flag_row", varlist) |
---|
| 1059 | |
---|
[1862] | 1060 | @asaplog_post_dec |
---|
[1819] | 1061 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
[1846] | 1062 | """\ |
---|
[1819] | 1063 | Flag the selected data outside a specified range (in channel-base) |
---|
[1846] | 1064 | |
---|
[1819] | 1065 | Parameters: |
---|
[1846] | 1066 | |
---|
[1819] | 1067 | uthres: upper threshold. |
---|
[1855] | 1068 | |
---|
[1819] | 1069 | dthres: lower threshold |
---|
[1846] | 1070 | |
---|
[1819] | 1071 | clipoutside: True for flagging data outside the range [dthres:uthres]. |
---|
[1928] | 1072 | False for flagging data inside the range. |
---|
[1855] | 1073 | |
---|
[1846] | 1074 | unflag: if True, unflag the data. |
---|
| 1075 | |
---|
[1819] | 1076 | """ |
---|
| 1077 | varlist = vars() |
---|
[1859] | 1078 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
[1819] | 1079 | self._add_history("clip", varlist) |
---|
| 1080 | |
---|
[1862] | 1081 | @asaplog_post_dec |
---|
[1584] | 1082 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
[1846] | 1083 | """\ |
---|
[1192] | 1084 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
[2177] | 1085 | Flagged data in the scantable get interpolated over the region. |
---|
[1192] | 1086 | No taper is applied. |
---|
[1846] | 1087 | |
---|
[1192] | 1088 | Parameters: |
---|
[1846] | 1089 | |
---|
[1579] | 1090 | start: the start frequency (really a period within the |
---|
| 1091 | bandwidth) or period to remove |
---|
[1855] | 1092 | |
---|
[1579] | 1093 | end: the end frequency or period to remove |
---|
[1855] | 1094 | |
---|
[1584] | 1095 | unit: the frequency unit (default "MHz") or "" for |
---|
[1579] | 1096 | explicit lag channels |
---|
[1846] | 1097 | |
---|
| 1098 | *Notes*: |
---|
| 1099 | |
---|
[1579] | 1100 | It is recommended to flag edges of the band or strong |
---|
[1348] | 1101 | signals beforehand. |
---|
[1846] | 1102 | |
---|
[1192] | 1103 | """ |
---|
| 1104 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 1105 | self._math._setinsitu(insitu) |
---|
| 1106 | varlist = vars() |
---|
[1579] | 1107 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
| 1108 | if not (unit == "" or base.has_key(unit)): |
---|
[1192] | 1109 | raise ValueError("%s is not a valid unit." % unit) |
---|
[1859] | 1110 | if unit == "": |
---|
| 1111 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
| 1112 | else: |
---|
| 1113 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
| 1114 | end*base[unit], "frequency")) |
---|
[1192] | 1115 | s._add_history("lag_flag", varlist) |
---|
| 1116 | if insitu: |
---|
| 1117 | self._assign(s) |
---|
| 1118 | else: |
---|
| 1119 | return s |
---|
[1001] | 1120 | |
---|
[1862] | 1121 | @asaplog_post_dec |
---|
[2177] | 1122 | def fft(self, getrealimag=False, rowno=[]): |
---|
| 1123 | """\ |
---|
| 1124 | Apply FFT to the spectra. |
---|
| 1125 | Flagged data in the scantable get interpolated over the region. |
---|
| 1126 | |
---|
| 1127 | Parameters: |
---|
| 1128 | |
---|
| 1129 | getrealimag: If True, returns the real and imaginary part |
---|
| 1130 | values of the complex results. |
---|
| 1131 | If False (the default), returns the amplitude |
---|
| 1132 | (absolute value) normalised with Ndata/2 and |
---|
| 1133 | phase (argument, in unit of radian). |
---|
| 1134 | |
---|
| 1135 | rowno: The row number(s) to be processed. int, list |
---|
| 1136 | and tuple are accepted. By default ([]), FFT |
---|
| 1137 | is applied to the whole data. |
---|
| 1138 | |
---|
| 1139 | Returns: |
---|
| 1140 | |
---|
| 1141 | A dictionary containing two keys, i.e., 'real' and 'imag' for |
---|
| 1142 | getrealimag = True, or 'ampl' and 'phase' for getrealimag = False, |
---|
| 1143 | respectively. |
---|
| 1144 | The value for each key is a list of lists containing the FFT |
---|
| 1145 | results from each spectrum. |
---|
| 1146 | |
---|
| 1147 | """ |
---|
| 1148 | if getrealimag: |
---|
| 1149 | res = {"real":[], "imag":[]} # return real and imaginary values |
---|
| 1150 | else: |
---|
| 1151 | res = {"ampl":[], "phase":[]} # return amplitude and phase(argument) |
---|
| 1152 | |
---|
| 1153 | if isinstance(rowno, int): |
---|
| 1154 | rowno = [rowno] |
---|
| 1155 | elif not (isinstance(rowno, list) or isinstance(rowno, tuple)): |
---|
| 1156 | raise TypeError("The row number(s) should be int, list or tuple.") |
---|
| 1157 | |
---|
| 1158 | nrow = len(rowno) |
---|
| 1159 | if nrow == 0: nrow = self.nrow() # by default, calculate for all rows. |
---|
| 1160 | |
---|
| 1161 | fspec = self._math._fft(self, rowno, getrealimag) |
---|
| 1162 | nspec = len(fspec)/nrow |
---|
| 1163 | |
---|
| 1164 | i = 0 |
---|
| 1165 | while (i < nrow): |
---|
| 1166 | v1 = [] |
---|
| 1167 | v2 = [] |
---|
| 1168 | |
---|
| 1169 | j = 0 |
---|
| 1170 | while (j < nspec): |
---|
| 1171 | k = i*nspec + j |
---|
| 1172 | v1.append(fspec[k]) |
---|
| 1173 | v2.append(fspec[k+1]) |
---|
| 1174 | j += 2 |
---|
| 1175 | |
---|
| 1176 | if getrealimag: |
---|
| 1177 | res["real"].append(v1) |
---|
| 1178 | res["imag"].append(v2) |
---|
| 1179 | else: |
---|
| 1180 | res["ampl"].append(v1) |
---|
| 1181 | res["phase"].append(v2) |
---|
| 1182 | |
---|
| 1183 | i += 1 |
---|
| 1184 | |
---|
| 1185 | return res |
---|
| 1186 | |
---|
| 1187 | @asaplog_post_dec |
---|
[113] | 1188 | def create_mask(self, *args, **kwargs): |
---|
[1846] | 1189 | """\ |
---|
[1118] | 1190 | Compute and return a mask based on [min, max] windows. |
---|
[189] | 1191 | The specified windows are to be INCLUDED, when the mask is |
---|
[113] | 1192 | applied. |
---|
[1846] | 1193 | |
---|
[102] | 1194 | Parameters: |
---|
[1846] | 1195 | |
---|
[1118] | 1196 | [min, max], [min2, max2], ... |
---|
[1024] | 1197 | Pairs of start/end points (inclusive)specifying the regions |
---|
[102] | 1198 | to be masked |
---|
[1855] | 1199 | |
---|
[189] | 1200 | invert: optional argument. If specified as True, |
---|
| 1201 | return an inverted mask, i.e. the regions |
---|
| 1202 | specified are EXCLUDED |
---|
[1855] | 1203 | |
---|
[513] | 1204 | row: create the mask using the specified row for |
---|
| 1205 | unit conversions, default is row=0 |
---|
| 1206 | only necessary if frequency varies over rows. |
---|
[1846] | 1207 | |
---|
| 1208 | Examples:: |
---|
| 1209 | |
---|
[113] | 1210 | scan.set_unit('channel') |
---|
[1846] | 1211 | # a) |
---|
[1118] | 1212 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
[189] | 1213 | # masks everything outside 400 and 500 |
---|
[113] | 1214 | # and 800 and 900 in the unit 'channel' |
---|
| 1215 | |
---|
[1846] | 1216 | # b) |
---|
[1118] | 1217 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
[189] | 1218 | # masks the regions between 400 and 500 |
---|
[113] | 1219 | # and 800 and 900 in the unit 'channel' |
---|
[1846] | 1220 | |
---|
| 1221 | # c) |
---|
| 1222 | #mask only channel 400 |
---|
[1554] | 1223 | msk = scan.create_mask([400]) |
---|
[1846] | 1224 | |
---|
[102] | 1225 | """ |
---|
[1554] | 1226 | row = kwargs.get("row", 0) |
---|
[513] | 1227 | data = self._getabcissa(row) |
---|
[113] | 1228 | u = self._getcoordinfo()[0] |
---|
[1859] | 1229 | if u == "": |
---|
| 1230 | u = "channel" |
---|
| 1231 | msg = "The current mask window unit is %s" % u |
---|
| 1232 | i = self._check_ifs() |
---|
| 1233 | if not i: |
---|
| 1234 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1235 | asaplog.push(msg) |
---|
[102] | 1236 | n = self.nchan() |
---|
[1295] | 1237 | msk = _n_bools(n, False) |
---|
[710] | 1238 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
| 1239 | |
---|
[1118] | 1240 | ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ |
---|
| 1241 | and args or args[0] |
---|
[710] | 1242 | for window in ws: |
---|
[1554] | 1243 | if len(window) == 1: |
---|
| 1244 | window = [window[0], window[0]] |
---|
| 1245 | if len(window) == 0 or len(window) > 2: |
---|
| 1246 | raise ValueError("A window needs to be defined as [start(, end)]") |
---|
[1545] | 1247 | if window[0] > window[1]: |
---|
| 1248 | tmp = window[0] |
---|
| 1249 | window[0] = window[1] |
---|
| 1250 | window[1] = tmp |
---|
[102] | 1251 | for i in range(n): |
---|
[1024] | 1252 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
[1295] | 1253 | msk[i] = True |
---|
[113] | 1254 | if kwargs.has_key('invert'): |
---|
| 1255 | if kwargs.get('invert'): |
---|
[1295] | 1256 | msk = mask_not(msk) |
---|
[102] | 1257 | return msk |
---|
[710] | 1258 | |
---|
[1931] | 1259 | def get_masklist(self, mask=None, row=0, silent=False): |
---|
[1846] | 1260 | """\ |
---|
[1819] | 1261 | Compute and return a list of mask windows, [min, max]. |
---|
[1846] | 1262 | |
---|
[1819] | 1263 | Parameters: |
---|
[1846] | 1264 | |
---|
[1819] | 1265 | mask: channel mask, created with create_mask. |
---|
[1855] | 1266 | |
---|
[1819] | 1267 | row: calcutate the masklist using the specified row |
---|
| 1268 | for unit conversions, default is row=0 |
---|
| 1269 | only necessary if frequency varies over rows. |
---|
[1846] | 1270 | |
---|
[1819] | 1271 | Returns: |
---|
[1846] | 1272 | |
---|
[1819] | 1273 | [min, max], [min2, max2], ... |
---|
| 1274 | Pairs of start/end points (inclusive)specifying |
---|
| 1275 | the masked regions |
---|
[1846] | 1276 | |
---|
[1819] | 1277 | """ |
---|
| 1278 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1279 | raise TypeError("The mask should be list or tuple.") |
---|
| 1280 | if len(mask) < 2: |
---|
| 1281 | raise TypeError("The mask elements should be > 1") |
---|
| 1282 | if self.nchan() != len(mask): |
---|
| 1283 | msg = "Number of channels in scantable != number of mask elements" |
---|
| 1284 | raise TypeError(msg) |
---|
| 1285 | data = self._getabcissa(row) |
---|
| 1286 | u = self._getcoordinfo()[0] |
---|
[1859] | 1287 | if u == "": |
---|
| 1288 | u = "channel" |
---|
| 1289 | msg = "The current mask window unit is %s" % u |
---|
| 1290 | i = self._check_ifs() |
---|
| 1291 | if not i: |
---|
| 1292 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
[1931] | 1293 | if not silent: |
---|
| 1294 | asaplog.push(msg) |
---|
[1819] | 1295 | masklist=[] |
---|
| 1296 | ist, ien = None, None |
---|
| 1297 | ist, ien=self.get_mask_indices(mask) |
---|
| 1298 | if ist is not None and ien is not None: |
---|
| 1299 | for i in xrange(len(ist)): |
---|
| 1300 | range=[data[ist[i]],data[ien[i]]] |
---|
| 1301 | range.sort() |
---|
| 1302 | masklist.append([range[0],range[1]]) |
---|
| 1303 | return masklist |
---|
| 1304 | |
---|
| 1305 | def get_mask_indices(self, mask=None): |
---|
[1846] | 1306 | """\ |
---|
[1819] | 1307 | Compute and Return lists of mask start indices and mask end indices. |
---|
[1855] | 1308 | |
---|
| 1309 | Parameters: |
---|
| 1310 | |
---|
[1819] | 1311 | mask: channel mask, created with create_mask. |
---|
[1846] | 1312 | |
---|
[1819] | 1313 | Returns: |
---|
[1846] | 1314 | |
---|
[1819] | 1315 | List of mask start indices and that of mask end indices, |
---|
| 1316 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
[1846] | 1317 | |
---|
[1819] | 1318 | """ |
---|
| 1319 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1320 | raise TypeError("The mask should be list or tuple.") |
---|
| 1321 | if len(mask) < 2: |
---|
| 1322 | raise TypeError("The mask elements should be > 1") |
---|
| 1323 | istart=[] |
---|
| 1324 | iend=[] |
---|
| 1325 | if mask[0]: istart.append(0) |
---|
| 1326 | for i in range(len(mask)-1): |
---|
| 1327 | if not mask[i] and mask[i+1]: |
---|
| 1328 | istart.append(i+1) |
---|
| 1329 | elif mask[i] and not mask[i+1]: |
---|
| 1330 | iend.append(i) |
---|
| 1331 | if mask[len(mask)-1]: iend.append(len(mask)-1) |
---|
| 1332 | if len(istart) != len(iend): |
---|
| 1333 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
| 1334 | for i in range(len(istart)): |
---|
| 1335 | if istart[i] > iend[i]: |
---|
| 1336 | raise RuntimeError("Mask start index > mask end index") |
---|
| 1337 | break |
---|
| 1338 | return istart,iend |
---|
| 1339 | |
---|
[2013] | 1340 | @asaplog_post_dec |
---|
| 1341 | def parse_maskexpr(self,maskstring): |
---|
| 1342 | """ |
---|
| 1343 | Parse CASA type mask selection syntax (IF dependent). |
---|
| 1344 | |
---|
| 1345 | Parameters: |
---|
| 1346 | maskstring : A string mask selection expression. |
---|
| 1347 | A comma separated selections mean different IF - |
---|
| 1348 | channel combinations. IFs and channel selections |
---|
| 1349 | are partitioned by a colon, ':'. |
---|
| 1350 | examples: |
---|
[2015] | 1351 | '' = all IFs (all channels) |
---|
[2013] | 1352 | '<2,4~6,9' = IFs 0,1,4,5,6,9 (all channels) |
---|
| 1353 | '3:3~45;60' = channels 3 to 45 and 60 in IF 3 |
---|
| 1354 | '0~1:2~6,8' = channels 2 to 6 in IFs 0,1, and |
---|
| 1355 | all channels in IF8 |
---|
| 1356 | Returns: |
---|
| 1357 | A dictionary of selected (valid) IF and masklist pairs, |
---|
| 1358 | e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]} |
---|
| 1359 | """ |
---|
| 1360 | if not isinstance(maskstring,str): |
---|
| 1361 | asaplog.post() |
---|
| 1362 | asaplog.push("Invalid mask expression") |
---|
| 1363 | asaplog.post("ERROR") |
---|
| 1364 | |
---|
| 1365 | valid_ifs = self.getifnos() |
---|
| 1366 | frequnit = self.get_unit() |
---|
| 1367 | seldict = {} |
---|
[2015] | 1368 | if maskstring == "": |
---|
| 1369 | maskstring = str(valid_ifs)[1:-1] |
---|
[2013] | 1370 | ## split each selection |
---|
| 1371 | sellist = maskstring.split(',') |
---|
| 1372 | for currselstr in sellist: |
---|
| 1373 | selset = currselstr.split(':') |
---|
| 1374 | # spw and mask string (may include ~, < or >) |
---|
| 1375 | spwmasklist = self._parse_selection(selset[0],typestr='integer', |
---|
| 1376 | offset=1,minval=min(valid_ifs), |
---|
| 1377 | maxval=max(valid_ifs)) |
---|
| 1378 | for spwlist in spwmasklist: |
---|
| 1379 | selspws = [] |
---|
| 1380 | for ispw in range(spwlist[0],spwlist[1]+1): |
---|
| 1381 | # Put into the list only if ispw exists |
---|
| 1382 | if valid_ifs.count(ispw): |
---|
| 1383 | selspws.append(ispw) |
---|
| 1384 | del spwmasklist, spwlist |
---|
| 1385 | |
---|
| 1386 | # parse frequency mask list |
---|
| 1387 | if len(selset) > 1: |
---|
| 1388 | freqmasklist = self._parse_selection(selset[1],typestr='float', |
---|
| 1389 | offset=0.) |
---|
| 1390 | else: |
---|
| 1391 | # want to select the whole spectrum |
---|
| 1392 | freqmasklist = [None] |
---|
| 1393 | |
---|
| 1394 | ## define a dictionary of spw - masklist combination |
---|
| 1395 | for ispw in selspws: |
---|
| 1396 | #print "working on", ispw |
---|
| 1397 | spwstr = str(ispw) |
---|
| 1398 | if len(selspws) == 0: |
---|
| 1399 | # empty spw |
---|
| 1400 | continue |
---|
| 1401 | else: |
---|
| 1402 | ## want to get min and max of the spw and |
---|
| 1403 | ## offset to set for '<' and '>' |
---|
| 1404 | if frequnit == 'channel': |
---|
| 1405 | minfreq = 0 |
---|
| 1406 | maxfreq = self.nchan(ifno=ispw) |
---|
| 1407 | offset = 0.5 |
---|
| 1408 | else: |
---|
| 1409 | ## This is ugly part. need improvement |
---|
| 1410 | for ifrow in xrange(self.nrow()): |
---|
| 1411 | if self.getif(ifrow) == ispw: |
---|
| 1412 | #print "IF",ispw,"found in row =",ifrow |
---|
| 1413 | break |
---|
| 1414 | freqcoord = self.get_coordinate(ifrow) |
---|
| 1415 | freqs = self._getabcissa(ifrow) |
---|
| 1416 | minfreq = min(freqs) |
---|
| 1417 | maxfreq = max(freqs) |
---|
| 1418 | if len(freqs) == 1: |
---|
| 1419 | offset = 0.5 |
---|
| 1420 | elif frequnit.find('Hz') > 0: |
---|
| 1421 | offset = abs(freqcoord.to_frequency(1,unit=frequnit) |
---|
| 1422 | -freqcoord.to_frequency(0,unit=frequnit))*0.5 |
---|
| 1423 | elif frequnit.find('m/s') > 0: |
---|
| 1424 | offset = abs(freqcoord.to_velocity(1,unit=frequnit) |
---|
| 1425 | -freqcoord.to_velocity(0,unit=frequnit))*0.5 |
---|
| 1426 | else: |
---|
| 1427 | asaplog.post() |
---|
| 1428 | asaplog.push("Invalid frequency unit") |
---|
| 1429 | asaplog.post("ERROR") |
---|
| 1430 | del freqs, freqcoord, ifrow |
---|
| 1431 | for freq in freqmasklist: |
---|
| 1432 | selmask = freq or [minfreq, maxfreq] |
---|
| 1433 | if selmask[0] == None: |
---|
| 1434 | ## selection was "<freq[1]". |
---|
| 1435 | if selmask[1] < minfreq: |
---|
| 1436 | ## avoid adding region selection |
---|
| 1437 | selmask = None |
---|
| 1438 | else: |
---|
| 1439 | selmask = [minfreq,selmask[1]-offset] |
---|
| 1440 | elif selmask[1] == None: |
---|
| 1441 | ## selection was ">freq[0]" |
---|
| 1442 | if selmask[0] > maxfreq: |
---|
| 1443 | ## avoid adding region selection |
---|
| 1444 | selmask = None |
---|
| 1445 | else: |
---|
| 1446 | selmask = [selmask[0]+offset,maxfreq] |
---|
| 1447 | if selmask: |
---|
| 1448 | if not seldict.has_key(spwstr): |
---|
| 1449 | # new spw selection |
---|
| 1450 | seldict[spwstr] = [] |
---|
| 1451 | seldict[spwstr] += [selmask] |
---|
| 1452 | del minfreq,maxfreq,offset,freq,selmask |
---|
| 1453 | del spwstr |
---|
| 1454 | del freqmasklist |
---|
| 1455 | del valid_ifs |
---|
| 1456 | if len(seldict) == 0: |
---|
| 1457 | asaplog.post() |
---|
| 1458 | asaplog.push("No valid selection in the mask expression: "+maskstring) |
---|
| 1459 | asaplog.post("WARN") |
---|
| 1460 | return None |
---|
| 1461 | msg = "Selected masklist:\n" |
---|
| 1462 | for sif, lmask in seldict.iteritems(): |
---|
| 1463 | msg += " IF"+sif+" - "+str(lmask)+"\n" |
---|
| 1464 | asaplog.push(msg) |
---|
| 1465 | return seldict |
---|
| 1466 | |
---|
| 1467 | def _parse_selection(self,selstr,typestr='float',offset=0.,minval=None,maxval=None): |
---|
| 1468 | """ |
---|
| 1469 | Parameters: |
---|
| 1470 | selstr : The Selection string, e.g., '<3;5~7;100~103;9' |
---|
| 1471 | typestr : The type of the values in returned list |
---|
| 1472 | ('integer' or 'float') |
---|
| 1473 | offset : The offset value to subtract from or add to |
---|
| 1474 | the boundary value if the selection string |
---|
| 1475 | includes '<' or '>' |
---|
| 1476 | minval, maxval : The minimum/maximum values to set if the |
---|
| 1477 | selection string includes '<' or '>'. |
---|
| 1478 | The list element is filled with None by default. |
---|
| 1479 | Returns: |
---|
| 1480 | A list of min/max pair of selections. |
---|
| 1481 | Example: |
---|
| 1482 | _parseSelection('<3;5~7;9',typestr='int',offset=1,minval=0) |
---|
| 1483 | returns [[0,2],[5,7],[9,9]] |
---|
| 1484 | """ |
---|
| 1485 | selgroups = selstr.split(';') |
---|
| 1486 | sellists = [] |
---|
| 1487 | if typestr.lower().startswith('int'): |
---|
| 1488 | formatfunc = int |
---|
| 1489 | else: |
---|
| 1490 | formatfunc = float |
---|
| 1491 | |
---|
| 1492 | for currsel in selgroups: |
---|
| 1493 | if currsel.find('~') > 0: |
---|
| 1494 | minsel = formatfunc(currsel.split('~')[0].strip()) |
---|
| 1495 | maxsel = formatfunc(currsel.split('~')[1].strip()) |
---|
| 1496 | elif currsel.strip().startswith('<'): |
---|
| 1497 | minsel = minval |
---|
| 1498 | maxsel = formatfunc(currsel.split('<')[1].strip()) \ |
---|
| 1499 | - formatfunc(offset) |
---|
| 1500 | elif currsel.strip().startswith('>'): |
---|
| 1501 | minsel = formatfunc(currsel.split('>')[1].strip()) \ |
---|
| 1502 | + formatfunc(offset) |
---|
| 1503 | maxsel = maxval |
---|
| 1504 | else: |
---|
| 1505 | minsel = formatfunc(currsel) |
---|
| 1506 | maxsel = formatfunc(currsel) |
---|
| 1507 | sellists.append([minsel,maxsel]) |
---|
| 1508 | return sellists |
---|
| 1509 | |
---|
[1819] | 1510 | # def get_restfreqs(self): |
---|
| 1511 | # """ |
---|
| 1512 | # Get the restfrequency(s) stored in this scantable. |
---|
| 1513 | # The return value(s) are always of unit 'Hz' |
---|
| 1514 | # Parameters: |
---|
| 1515 | # none |
---|
| 1516 | # Returns: |
---|
| 1517 | # a list of doubles |
---|
| 1518 | # """ |
---|
| 1519 | # return list(self._getrestfreqs()) |
---|
| 1520 | |
---|
| 1521 | def get_restfreqs(self, ids=None): |
---|
[1846] | 1522 | """\ |
---|
[256] | 1523 | Get the restfrequency(s) stored in this scantable. |
---|
| 1524 | The return value(s) are always of unit 'Hz' |
---|
[1846] | 1525 | |
---|
[256] | 1526 | Parameters: |
---|
[1846] | 1527 | |
---|
[1819] | 1528 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
| 1529 | be retrieved |
---|
[1846] | 1530 | |
---|
[256] | 1531 | Returns: |
---|
[1846] | 1532 | |
---|
[1819] | 1533 | dictionary containing ids and a list of doubles for each id |
---|
[1846] | 1534 | |
---|
[256] | 1535 | """ |
---|
[1819] | 1536 | if ids is None: |
---|
| 1537 | rfreqs={} |
---|
| 1538 | idlist = self.getmolnos() |
---|
| 1539 | for i in idlist: |
---|
| 1540 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1541 | return rfreqs |
---|
| 1542 | else: |
---|
| 1543 | if type(ids)==list or type(ids)==tuple: |
---|
| 1544 | rfreqs={} |
---|
| 1545 | for i in ids: |
---|
| 1546 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
| 1547 | return rfreqs |
---|
| 1548 | else: |
---|
| 1549 | return list(self._getrestfreqs(ids)) |
---|
| 1550 | #return list(self._getrestfreqs(ids)) |
---|
[102] | 1551 | |
---|
[931] | 1552 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
[1846] | 1553 | """\ |
---|
[931] | 1554 | Set or replace the restfrequency specified and |
---|
[1938] | 1555 | if the 'freqs' argument holds a scalar, |
---|
[931] | 1556 | then that rest frequency will be applied to all the selected |
---|
| 1557 | data. If the 'freqs' argument holds |
---|
| 1558 | a vector, then it MUST be of equal or smaller length than |
---|
| 1559 | the number of IFs (and the available restfrequencies will be |
---|
| 1560 | replaced by this vector). In this case, *all* data have |
---|
| 1561 | the restfrequency set per IF according |
---|
| 1562 | to the corresponding value you give in the 'freqs' vector. |
---|
[1118] | 1563 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
[931] | 1564 | IF 1 gets restfreq 2e9. |
---|
[1846] | 1565 | |
---|
[1395] | 1566 | You can also specify the frequencies via a linecatalog. |
---|
[1153] | 1567 | |
---|
[931] | 1568 | Parameters: |
---|
[1846] | 1569 | |
---|
[931] | 1570 | freqs: list of rest frequency values or string idenitfiers |
---|
[1855] | 1571 | |
---|
[931] | 1572 | unit: unit for rest frequency (default 'Hz') |
---|
[402] | 1573 | |
---|
[1846] | 1574 | |
---|
| 1575 | Example:: |
---|
| 1576 | |
---|
[1819] | 1577 | # set the given restfrequency for the all currently selected IFs |
---|
[931] | 1578 | scan.set_restfreqs(freqs=1.4e9) |
---|
[1845] | 1579 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
| 1580 | # list, i.e |
---|
| 1581 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
| 1582 | # len(list_of_restfreqs) == nIF |
---|
| 1583 | # for nIF == 1 the following will set multiple restfrequency for |
---|
| 1584 | # that IF |
---|
[1819] | 1585 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
[1845] | 1586 | # set multiple restfrequencies per IF. as a list of lists where |
---|
| 1587 | # the outer list has nIF elements, the inner s arbitrary |
---|
| 1588 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
[391] | 1589 | |
---|
[1846] | 1590 | *Note*: |
---|
[1845] | 1591 | |
---|
[931] | 1592 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
| 1593 | source and IF basis, use scantable.set_selection() before using |
---|
[1846] | 1594 | this function:: |
---|
[931] | 1595 | |
---|
[1846] | 1596 | # provided your scantable is called scan |
---|
| 1597 | selection = selector() |
---|
| 1598 | selection.set_name("ORION*") |
---|
| 1599 | selection.set_ifs([1]) |
---|
| 1600 | scan.set_selection(selection) |
---|
| 1601 | scan.set_restfreqs(freqs=86.6e9) |
---|
| 1602 | |
---|
[931] | 1603 | """ |
---|
| 1604 | varlist = vars() |
---|
[1157] | 1605 | from asap import linecatalog |
---|
| 1606 | # simple value |
---|
[1118] | 1607 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
[1845] | 1608 | self._setrestfreqs([freqs], [""], unit) |
---|
[1157] | 1609 | # list of values |
---|
[1118] | 1610 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
[1157] | 1611 | # list values are scalars |
---|
[1118] | 1612 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
[1845] | 1613 | if len(freqs) == 1: |
---|
| 1614 | self._setrestfreqs(freqs, [""], unit) |
---|
| 1615 | else: |
---|
| 1616 | # allow the 'old' mode of setting mulitple IFs |
---|
| 1617 | sel = selector() |
---|
| 1618 | savesel = self._getselection() |
---|
| 1619 | iflist = self.getifnos() |
---|
| 1620 | if len(freqs)>len(iflist): |
---|
| 1621 | raise ValueError("number of elements in list of list " |
---|
| 1622 | "exeeds the current IF selections") |
---|
| 1623 | iflist = self.getifnos() |
---|
| 1624 | for i, fval in enumerate(freqs): |
---|
| 1625 | sel.set_ifs(iflist[i]) |
---|
| 1626 | self._setselection(sel) |
---|
| 1627 | self._setrestfreqs([fval], [""], unit) |
---|
| 1628 | self._setselection(savesel) |
---|
| 1629 | |
---|
| 1630 | # list values are dict, {'value'=, 'name'=) |
---|
[1157] | 1631 | elif isinstance(freqs[-1], dict): |
---|
[1845] | 1632 | values = [] |
---|
| 1633 | names = [] |
---|
| 1634 | for d in freqs: |
---|
| 1635 | values.append(d["value"]) |
---|
| 1636 | names.append(d["name"]) |
---|
| 1637 | self._setrestfreqs(values, names, unit) |
---|
[1819] | 1638 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
[1157] | 1639 | sel = selector() |
---|
| 1640 | savesel = self._getselection() |
---|
[1322] | 1641 | iflist = self.getifnos() |
---|
[1819] | 1642 | if len(freqs)>len(iflist): |
---|
[1845] | 1643 | raise ValueError("number of elements in list of list exeeds" |
---|
| 1644 | " the current IF selections") |
---|
| 1645 | for i, fval in enumerate(freqs): |
---|
[1322] | 1646 | sel.set_ifs(iflist[i]) |
---|
[1259] | 1647 | self._setselection(sel) |
---|
[1845] | 1648 | self._setrestfreqs(fval, [""], unit) |
---|
[1157] | 1649 | self._setselection(savesel) |
---|
| 1650 | # freqs are to be taken from a linecatalog |
---|
[1153] | 1651 | elif isinstance(freqs, linecatalog): |
---|
| 1652 | sel = selector() |
---|
| 1653 | savesel = self._getselection() |
---|
| 1654 | for i in xrange(freqs.nrow()): |
---|
[1322] | 1655 | sel.set_ifs(iflist[i]) |
---|
[1153] | 1656 | self._setselection(sel) |
---|
[1845] | 1657 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
| 1658 | [freqs.get_name(i)], "MHz") |
---|
[1153] | 1659 | # ensure that we are not iterating past nIF |
---|
| 1660 | if i == self.nif()-1: break |
---|
| 1661 | self._setselection(savesel) |
---|
[931] | 1662 | else: |
---|
| 1663 | return |
---|
| 1664 | self._add_history("set_restfreqs", varlist) |
---|
| 1665 | |
---|
[1360] | 1666 | def shift_refpix(self, delta): |
---|
[1846] | 1667 | """\ |
---|
[1589] | 1668 | Shift the reference pixel of the Spectra Coordinate by an |
---|
| 1669 | integer amount. |
---|
[1846] | 1670 | |
---|
[1589] | 1671 | Parameters: |
---|
[1846] | 1672 | |
---|
[1589] | 1673 | delta: the amount to shift by |
---|
[1846] | 1674 | |
---|
| 1675 | *Note*: |
---|
| 1676 | |
---|
[1589] | 1677 | Be careful using this with broadband data. |
---|
[1846] | 1678 | |
---|
[1360] | 1679 | """ |
---|
[1731] | 1680 | Scantable.shift_refpix(self, delta) |
---|
[931] | 1681 | |
---|
[1862] | 1682 | @asaplog_post_dec |
---|
[1259] | 1683 | def history(self, filename=None): |
---|
[1846] | 1684 | """\ |
---|
[1259] | 1685 | Print the history. Optionally to a file. |
---|
[1846] | 1686 | |
---|
[1348] | 1687 | Parameters: |
---|
[1846] | 1688 | |
---|
[1928] | 1689 | filename: The name of the file to save the history to. |
---|
[1846] | 1690 | |
---|
[1259] | 1691 | """ |
---|
[484] | 1692 | hist = list(self._gethistory()) |
---|
[794] | 1693 | out = "-"*80 |
---|
[484] | 1694 | for h in hist: |
---|
[489] | 1695 | if h.startswith("---"): |
---|
[1857] | 1696 | out = "\n".join([out, h]) |
---|
[489] | 1697 | else: |
---|
| 1698 | items = h.split("##") |
---|
| 1699 | date = items[0] |
---|
| 1700 | func = items[1] |
---|
| 1701 | items = items[2:] |
---|
[794] | 1702 | out += "\n"+date+"\n" |
---|
| 1703 | out += "Function: %s\n Parameters:" % (func) |
---|
[489] | 1704 | for i in items: |
---|
[1938] | 1705 | if i == '': |
---|
| 1706 | continue |
---|
[489] | 1707 | s = i.split("=") |
---|
[1118] | 1708 | out += "\n %s = %s" % (s[0], s[1]) |
---|
[1857] | 1709 | out = "\n".join([out, "-"*80]) |
---|
[1259] | 1710 | if filename is not None: |
---|
| 1711 | if filename is "": |
---|
| 1712 | filename = 'scantable_history.txt' |
---|
| 1713 | import os |
---|
| 1714 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 1715 | if not os.path.isdir(filename): |
---|
| 1716 | data = open(filename, 'w') |
---|
| 1717 | data.write(out) |
---|
| 1718 | data.close() |
---|
| 1719 | else: |
---|
| 1720 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 1721 | raise IOError(msg) |
---|
| 1722 | return page(out) |
---|
[513] | 1723 | # |
---|
| 1724 | # Maths business |
---|
| 1725 | # |
---|
[1862] | 1726 | @asaplog_post_dec |
---|
[931] | 1727 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
[1846] | 1728 | """\ |
---|
[1070] | 1729 | Return the (time) weighted average of a scan. |
---|
[1846] | 1730 | |
---|
| 1731 | *Note*: |
---|
| 1732 | |
---|
[1070] | 1733 | in channels only - align if necessary |
---|
[1846] | 1734 | |
---|
[513] | 1735 | Parameters: |
---|
[1846] | 1736 | |
---|
[513] | 1737 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
| 1738 | weighting) |
---|
[1855] | 1739 | |
---|
[558] | 1740 | scanav: True averages each scan separately |
---|
| 1741 | False (default) averages all scans together, |
---|
[1855] | 1742 | |
---|
[1099] | 1743 | weight: Weighting scheme. |
---|
| 1744 | 'none' (mean no weight) |
---|
| 1745 | 'var' (1/var(spec) weighted) |
---|
| 1746 | 'tsys' (1/Tsys**2 weighted) |
---|
| 1747 | 'tint' (integration time weighted) |
---|
| 1748 | 'tintsys' (Tint/Tsys**2) |
---|
| 1749 | 'median' ( median averaging) |
---|
[535] | 1750 | The default is 'tint' |
---|
[1855] | 1751 | |
---|
[931] | 1752 | align: align the spectra in velocity before averaging. It takes |
---|
| 1753 | the time of the first spectrum as reference time. |
---|
[1846] | 1754 | |
---|
| 1755 | Example:: |
---|
| 1756 | |
---|
[513] | 1757 | # time average the scantable without using a mask |
---|
[710] | 1758 | newscan = scan.average_time() |
---|
[1846] | 1759 | |
---|
[513] | 1760 | """ |
---|
| 1761 | varlist = vars() |
---|
[1593] | 1762 | weight = weight or 'TINT' |
---|
| 1763 | mask = mask or () |
---|
| 1764 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
[1118] | 1765 | scan = (self, ) |
---|
[1859] | 1766 | |
---|
| 1767 | if align: |
---|
| 1768 | scan = (self.freq_align(insitu=False), ) |
---|
| 1769 | s = None |
---|
| 1770 | if weight.upper() == 'MEDIAN': |
---|
| 1771 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
| 1772 | scanav)) |
---|
| 1773 | else: |
---|
| 1774 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
| 1775 | scanav)) |
---|
[1099] | 1776 | s._add_history("average_time", varlist) |
---|
[513] | 1777 | return s |
---|
[710] | 1778 | |
---|
[1862] | 1779 | @asaplog_post_dec |
---|
[876] | 1780 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
[1846] | 1781 | """\ |
---|
[513] | 1782 | Return a scan where all spectra are converted to either |
---|
| 1783 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
| 1784 | By default the function tries to look the values up internally. |
---|
| 1785 | If it can't find them (or if you want to over-ride), you must |
---|
| 1786 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
| 1787 | also if you don't set it). jyperk takes precedence if you set both. |
---|
[1846] | 1788 | |
---|
[513] | 1789 | Parameters: |
---|
[1846] | 1790 | |
---|
[513] | 1791 | jyperk: the Jy / K conversion factor |
---|
[1855] | 1792 | |
---|
[513] | 1793 | eta: the aperture efficiency |
---|
[1855] | 1794 | |
---|
[1928] | 1795 | d: the geometric diameter (metres) |
---|
[1855] | 1796 | |
---|
[513] | 1797 | insitu: if False a new scantable is returned. |
---|
| 1798 | Otherwise, the scaling is done in-situ |
---|
| 1799 | The default is taken from .asaprc (False) |
---|
[1846] | 1800 | |
---|
[513] | 1801 | """ |
---|
| 1802 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1803 | self._math._setinsitu(insitu) |
---|
[513] | 1804 | varlist = vars() |
---|
[1593] | 1805 | jyperk = jyperk or -1.0 |
---|
| 1806 | d = d or -1.0 |
---|
| 1807 | eta = eta or -1.0 |
---|
[876] | 1808 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
| 1809 | s._add_history("convert_flux", varlist) |
---|
| 1810 | if insitu: self._assign(s) |
---|
| 1811 | else: return s |
---|
[513] | 1812 | |
---|
[1862] | 1813 | @asaplog_post_dec |
---|
[876] | 1814 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
[1846] | 1815 | """\ |
---|
[513] | 1816 | Return a scan after applying a gain-elevation correction. |
---|
| 1817 | The correction can be made via either a polynomial or a |
---|
| 1818 | table-based interpolation (and extrapolation if necessary). |
---|
| 1819 | You specify polynomial coefficients, an ascii table or neither. |
---|
| 1820 | If you specify neither, then a polynomial correction will be made |
---|
| 1821 | with built in coefficients known for certain telescopes (an error |
---|
| 1822 | will occur if the instrument is not known). |
---|
| 1823 | The data and Tsys are *divided* by the scaling factors. |
---|
[1846] | 1824 | |
---|
[513] | 1825 | Parameters: |
---|
[1846] | 1826 | |
---|
[513] | 1827 | poly: Polynomial coefficients (default None) to compute a |
---|
| 1828 | gain-elevation correction as a function of |
---|
| 1829 | elevation (in degrees). |
---|
[1855] | 1830 | |
---|
[513] | 1831 | filename: The name of an ascii file holding correction factors. |
---|
| 1832 | The first row of the ascii file must give the column |
---|
| 1833 | names and these MUST include columns |
---|
| 1834 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
| 1835 | by this) somewhere. |
---|
| 1836 | The second row must give the data type of the |
---|
| 1837 | column. Use 'R' for Real and 'I' for Integer. |
---|
| 1838 | An example file would be |
---|
| 1839 | (actual factors are arbitrary) : |
---|
| 1840 | |
---|
| 1841 | TIME ELEVATION FACTOR |
---|
| 1842 | R R R |
---|
| 1843 | 0.1 0 0.8 |
---|
| 1844 | 0.2 20 0.85 |
---|
| 1845 | 0.3 40 0.9 |
---|
| 1846 | 0.4 60 0.85 |
---|
| 1847 | 0.5 80 0.8 |
---|
| 1848 | 0.6 90 0.75 |
---|
[1855] | 1849 | |
---|
[513] | 1850 | method: Interpolation method when correcting from a table. |
---|
| 1851 | Values are "nearest", "linear" (default), "cubic" |
---|
| 1852 | and "spline" |
---|
[1855] | 1853 | |
---|
[513] | 1854 | insitu: if False a new scantable is returned. |
---|
| 1855 | Otherwise, the scaling is done in-situ |
---|
| 1856 | The default is taken from .asaprc (False) |
---|
[1846] | 1857 | |
---|
[513] | 1858 | """ |
---|
| 1859 | |
---|
| 1860 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1861 | self._math._setinsitu(insitu) |
---|
[513] | 1862 | varlist = vars() |
---|
[1593] | 1863 | poly = poly or () |
---|
[513] | 1864 | from os.path import expandvars |
---|
| 1865 | filename = expandvars(filename) |
---|
[876] | 1866 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
| 1867 | s._add_history("gain_el", varlist) |
---|
[1593] | 1868 | if insitu: |
---|
| 1869 | self._assign(s) |
---|
| 1870 | else: |
---|
| 1871 | return s |
---|
[710] | 1872 | |
---|
[1862] | 1873 | @asaplog_post_dec |
---|
[931] | 1874 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
[1846] | 1875 | """\ |
---|
[513] | 1876 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
| 1877 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
| 1878 | set_freqframe. |
---|
[1846] | 1879 | |
---|
[513] | 1880 | Parameters: |
---|
[1855] | 1881 | |
---|
[513] | 1882 | reftime: reference time to align at. By default, the time of |
---|
| 1883 | the first row of data is used. |
---|
[1855] | 1884 | |
---|
[513] | 1885 | method: Interpolation method for regridding the spectra. |
---|
| 1886 | Choose from "nearest", "linear", "cubic" (default) |
---|
| 1887 | and "spline" |
---|
[1855] | 1888 | |
---|
[513] | 1889 | insitu: if False a new scantable is returned. |
---|
| 1890 | Otherwise, the scaling is done in-situ |
---|
| 1891 | The default is taken from .asaprc (False) |
---|
[1846] | 1892 | |
---|
[513] | 1893 | """ |
---|
[931] | 1894 | if insitu is None: insitu = rcParams["insitu"] |
---|
[876] | 1895 | self._math._setinsitu(insitu) |
---|
[513] | 1896 | varlist = vars() |
---|
[1593] | 1897 | reftime = reftime or "" |
---|
[931] | 1898 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
[876] | 1899 | s._add_history("freq_align", varlist) |
---|
| 1900 | if insitu: self._assign(s) |
---|
| 1901 | else: return s |
---|
[513] | 1902 | |
---|
[1862] | 1903 | @asaplog_post_dec |
---|
[1725] | 1904 | def opacity(self, tau=None, insitu=None): |
---|
[1846] | 1905 | """\ |
---|
[513] | 1906 | Apply an opacity correction. The data |
---|
| 1907 | and Tsys are multiplied by the correction factor. |
---|
[1846] | 1908 | |
---|
[513] | 1909 | Parameters: |
---|
[1855] | 1910 | |
---|
[1689] | 1911 | tau: (list of) opacity from which the correction factor is |
---|
[513] | 1912 | exp(tau*ZD) |
---|
[1689] | 1913 | where ZD is the zenith-distance. |
---|
| 1914 | If a list is provided, it has to be of length nIF, |
---|
| 1915 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
| 1916 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
[1725] | 1917 | if tau is `None` the opacities are determined from a |
---|
| 1918 | model. |
---|
[1855] | 1919 | |
---|
[513] | 1920 | insitu: if False a new scantable is returned. |
---|
| 1921 | Otherwise, the scaling is done in-situ |
---|
| 1922 | The default is taken from .asaprc (False) |
---|
[1846] | 1923 | |
---|
[513] | 1924 | """ |
---|
| 1925 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1926 | self._math._setinsitu(insitu) |
---|
[513] | 1927 | varlist = vars() |
---|
[1689] | 1928 | if not hasattr(tau, "__len__"): |
---|
| 1929 | tau = [tau] |
---|
[876] | 1930 | s = scantable(self._math._opacity(self, tau)) |
---|
| 1931 | s._add_history("opacity", varlist) |
---|
| 1932 | if insitu: self._assign(s) |
---|
| 1933 | else: return s |
---|
[513] | 1934 | |
---|
[1862] | 1935 | @asaplog_post_dec |
---|
[513] | 1936 | def bin(self, width=5, insitu=None): |
---|
[1846] | 1937 | """\ |
---|
[513] | 1938 | Return a scan where all spectra have been binned up. |
---|
[1846] | 1939 | |
---|
[1348] | 1940 | Parameters: |
---|
[1846] | 1941 | |
---|
[513] | 1942 | width: The bin width (default=5) in pixels |
---|
[1855] | 1943 | |
---|
[513] | 1944 | insitu: if False a new scantable is returned. |
---|
| 1945 | Otherwise, the scaling is done in-situ |
---|
| 1946 | The default is taken from .asaprc (False) |
---|
[1846] | 1947 | |
---|
[513] | 1948 | """ |
---|
| 1949 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1950 | self._math._setinsitu(insitu) |
---|
[513] | 1951 | varlist = vars() |
---|
[876] | 1952 | s = scantable(self._math._bin(self, width)) |
---|
[1118] | 1953 | s._add_history("bin", varlist) |
---|
[1589] | 1954 | if insitu: |
---|
| 1955 | self._assign(s) |
---|
| 1956 | else: |
---|
| 1957 | return s |
---|
[513] | 1958 | |
---|
[1862] | 1959 | @asaplog_post_dec |
---|
[513] | 1960 | def resample(self, width=5, method='cubic', insitu=None): |
---|
[1846] | 1961 | """\ |
---|
[1348] | 1962 | Return a scan where all spectra have been binned up. |
---|
[1573] | 1963 | |
---|
[1348] | 1964 | Parameters: |
---|
[1846] | 1965 | |
---|
[513] | 1966 | width: The bin width (default=5) in pixels |
---|
[1855] | 1967 | |
---|
[513] | 1968 | method: Interpolation method when correcting from a table. |
---|
| 1969 | Values are "nearest", "linear", "cubic" (default) |
---|
| 1970 | and "spline" |
---|
[1855] | 1971 | |
---|
[513] | 1972 | insitu: if False a new scantable is returned. |
---|
| 1973 | Otherwise, the scaling is done in-situ |
---|
| 1974 | The default is taken from .asaprc (False) |
---|
[1846] | 1975 | |
---|
[513] | 1976 | """ |
---|
| 1977 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1978 | self._math._setinsitu(insitu) |
---|
[513] | 1979 | varlist = vars() |
---|
[876] | 1980 | s = scantable(self._math._resample(self, method, width)) |
---|
[1118] | 1981 | s._add_history("resample", varlist) |
---|
[876] | 1982 | if insitu: self._assign(s) |
---|
| 1983 | else: return s |
---|
[513] | 1984 | |
---|
[1862] | 1985 | @asaplog_post_dec |
---|
[946] | 1986 | def average_pol(self, mask=None, weight='none'): |
---|
[1846] | 1987 | """\ |
---|
[946] | 1988 | Average the Polarisations together. |
---|
[1846] | 1989 | |
---|
[946] | 1990 | Parameters: |
---|
[1846] | 1991 | |
---|
[946] | 1992 | mask: An optional mask defining the region, where the |
---|
| 1993 | averaging will be applied. The output will have all |
---|
| 1994 | specified points masked. |
---|
[1855] | 1995 | |
---|
[946] | 1996 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 1997 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 1998 | |
---|
[946] | 1999 | """ |
---|
| 2000 | varlist = vars() |
---|
[1593] | 2001 | mask = mask or () |
---|
[1010] | 2002 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
[1118] | 2003 | s._add_history("average_pol", varlist) |
---|
[992] | 2004 | return s |
---|
[513] | 2005 | |
---|
[1862] | 2006 | @asaplog_post_dec |
---|
[1145] | 2007 | def average_beam(self, mask=None, weight='none'): |
---|
[1846] | 2008 | """\ |
---|
[1145] | 2009 | Average the Beams together. |
---|
[1846] | 2010 | |
---|
[1145] | 2011 | Parameters: |
---|
| 2012 | mask: An optional mask defining the region, where the |
---|
| 2013 | averaging will be applied. The output will have all |
---|
| 2014 | specified points masked. |
---|
[1855] | 2015 | |
---|
[1145] | 2016 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 2017 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 2018 | |
---|
[1145] | 2019 | """ |
---|
| 2020 | varlist = vars() |
---|
[1593] | 2021 | mask = mask or () |
---|
[1145] | 2022 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
| 2023 | s._add_history("average_beam", varlist) |
---|
| 2024 | return s |
---|
| 2025 | |
---|
[1586] | 2026 | def parallactify(self, pflag): |
---|
[1846] | 2027 | """\ |
---|
[1843] | 2028 | Set a flag to indicate whether this data should be treated as having |
---|
[1617] | 2029 | been 'parallactified' (total phase == 0.0) |
---|
[1846] | 2030 | |
---|
[1617] | 2031 | Parameters: |
---|
[1855] | 2032 | |
---|
[1843] | 2033 | pflag: Bool indicating whether to turn this on (True) or |
---|
[1617] | 2034 | off (False) |
---|
[1846] | 2035 | |
---|
[1617] | 2036 | """ |
---|
[1586] | 2037 | varlist = vars() |
---|
| 2038 | self._parallactify(pflag) |
---|
| 2039 | self._add_history("parallactify", varlist) |
---|
| 2040 | |
---|
[1862] | 2041 | @asaplog_post_dec |
---|
[992] | 2042 | def convert_pol(self, poltype=None): |
---|
[1846] | 2043 | """\ |
---|
[992] | 2044 | Convert the data to a different polarisation type. |
---|
[1565] | 2045 | Note that you will need cross-polarisation terms for most conversions. |
---|
[1846] | 2046 | |
---|
[992] | 2047 | Parameters: |
---|
[1855] | 2048 | |
---|
[992] | 2049 | poltype: The new polarisation type. Valid types are: |
---|
[1565] | 2050 | "linear", "circular", "stokes" and "linpol" |
---|
[1846] | 2051 | |
---|
[992] | 2052 | """ |
---|
| 2053 | varlist = vars() |
---|
[1859] | 2054 | s = scantable(self._math._convertpol(self, poltype)) |
---|
[1118] | 2055 | s._add_history("convert_pol", varlist) |
---|
[992] | 2056 | return s |
---|
| 2057 | |
---|
[1862] | 2058 | @asaplog_post_dec |
---|
[1819] | 2059 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): |
---|
[1846] | 2060 | """\ |
---|
[513] | 2061 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
[1846] | 2062 | |
---|
[513] | 2063 | Parameters: |
---|
[1846] | 2064 | |
---|
[513] | 2065 | kernel: The type of smoothing kernel. Select from |
---|
[1574] | 2066 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
| 2067 | or 'poly' |
---|
[1855] | 2068 | |
---|
[513] | 2069 | width: The width of the kernel in pixels. For hanning this is |
---|
| 2070 | ignored otherwise it defauls to 5 pixels. |
---|
| 2071 | For 'gaussian' it is the Full Width Half |
---|
| 2072 | Maximum. For 'boxcar' it is the full width. |
---|
[1574] | 2073 | For 'rmedian' and 'poly' it is the half width. |
---|
[1855] | 2074 | |
---|
[1574] | 2075 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
| 2076 | specify the order of the polnomial. Ignored by all other |
---|
| 2077 | kernels. |
---|
[1855] | 2078 | |
---|
[1819] | 2079 | plot: plot the original and the smoothed spectra. |
---|
| 2080 | In this each indivual fit has to be approved, by |
---|
| 2081 | typing 'y' or 'n' |
---|
[1855] | 2082 | |
---|
[513] | 2083 | insitu: if False a new scantable is returned. |
---|
| 2084 | Otherwise, the scaling is done in-situ |
---|
| 2085 | The default is taken from .asaprc (False) |
---|
[1846] | 2086 | |
---|
[513] | 2087 | """ |
---|
| 2088 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2089 | self._math._setinsitu(insitu) |
---|
[513] | 2090 | varlist = vars() |
---|
[1819] | 2091 | |
---|
| 2092 | if plot: orgscan = self.copy() |
---|
| 2093 | |
---|
[1574] | 2094 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
[876] | 2095 | s._add_history("smooth", varlist) |
---|
[1819] | 2096 | |
---|
| 2097 | if plot: |
---|
[2150] | 2098 | from asap.asapplotter import new_asaplot |
---|
| 2099 | theplot = new_asaplot(rcParams['plotter.gui']) |
---|
| 2100 | theplot.set_panels() |
---|
[1819] | 2101 | ylab=s._get_ordinate_label() |
---|
[2150] | 2102 | #theplot.palette(0,["#777777","red"]) |
---|
[1819] | 2103 | for r in xrange(s.nrow()): |
---|
| 2104 | xsm=s._getabcissa(r) |
---|
| 2105 | ysm=s._getspectrum(r) |
---|
| 2106 | xorg=orgscan._getabcissa(r) |
---|
| 2107 | yorg=orgscan._getspectrum(r) |
---|
[2150] | 2108 | theplot.clear() |
---|
| 2109 | theplot.hold() |
---|
| 2110 | theplot.set_axes('ylabel',ylab) |
---|
| 2111 | theplot.set_axes('xlabel',s._getabcissalabel(r)) |
---|
| 2112 | theplot.set_axes('title',s._getsourcename(r)) |
---|
| 2113 | theplot.set_line(label='Original',color="#777777") |
---|
| 2114 | theplot.plot(xorg,yorg) |
---|
| 2115 | theplot.set_line(label='Smoothed',color="red") |
---|
| 2116 | theplot.plot(xsm,ysm) |
---|
[1819] | 2117 | ### Ugly part for legend |
---|
| 2118 | for i in [0,1]: |
---|
[2150] | 2119 | theplot.subplots[0]['lines'].append([theplot.subplots[0]['axes'].lines[i]]) |
---|
| 2120 | theplot.release() |
---|
[1819] | 2121 | ### Ugly part for legend |
---|
[2150] | 2122 | theplot.subplots[0]['lines']=[] |
---|
[1819] | 2123 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
| 2124 | if res.upper() == 'N': |
---|
| 2125 | s._setspectrum(yorg, r) |
---|
[2150] | 2126 | theplot.quit() |
---|
| 2127 | del theplot |
---|
[1819] | 2128 | del orgscan |
---|
| 2129 | |
---|
[876] | 2130 | if insitu: self._assign(s) |
---|
| 2131 | else: return s |
---|
[513] | 2132 | |
---|
[2012] | 2133 | |
---|
[1862] | 2134 | @asaplog_post_dec |
---|
[2081] | 2135 | def sinusoid_baseline(self, insitu=None, mask=None, nwave=None, maxwavelength=None, |
---|
| 2136 | clipthresh=None, clipniter=None, plot=None, getresidual=None, outlog=None, blfile=None): |
---|
[2047] | 2137 | """\ |
---|
[2094] | 2138 | Return a scan which has been baselined (all rows) with sinusoidal functions. |
---|
[2047] | 2139 | Parameters: |
---|
[2081] | 2140 | insitu: If False a new scantable is returned. |
---|
| 2141 | Otherwise, the scaling is done in-situ |
---|
| 2142 | The default is taken from .asaprc (False) |
---|
| 2143 | mask: An optional mask |
---|
| 2144 | nwave: the maximum wave number of sinusoids within |
---|
| 2145 | maxwavelength * (spectral range). |
---|
| 2146 | The default is 3 (i.e., sinusoids with wave |
---|
| 2147 | number of 0(=constant), 1, 2, and 3 are |
---|
| 2148 | used for fitting). Also it is possible to |
---|
| 2149 | explicitly specify all the wave numbers to |
---|
| 2150 | be used, by giving a list including them |
---|
| 2151 | (e.g. [0,1,2,15,16]). |
---|
| 2152 | maxwavelength: the longest sinusoidal wavelength. The |
---|
| 2153 | default is 1.0 (unit: spectral range). |
---|
| 2154 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2129] | 2155 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
[2081] | 2156 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2157 | plot the fit and the residual. In this each |
---|
| 2158 | indivual fit has to be approved, by typing 'y' |
---|
| 2159 | or 'n' |
---|
| 2160 | getresidual: if False, returns best-fit values instead of |
---|
| 2161 | residual. (default is True) |
---|
| 2162 | outlog: Output the coefficients of the best-fit |
---|
| 2163 | function to logger (default is False) |
---|
| 2164 | blfile: Name of a text file in which the best-fit |
---|
| 2165 | parameter values to be written |
---|
| 2166 | (default is "": no file/logger output) |
---|
[2047] | 2167 | |
---|
| 2168 | Example: |
---|
| 2169 | # return a scan baselined by a combination of sinusoidal curves having |
---|
[2081] | 2170 | # wave numbers in spectral window up to 10, |
---|
[2047] | 2171 | # also with 3-sigma clipping, iteration up to 4 times |
---|
[2081] | 2172 | bscan = scan.sinusoid_baseline(nwave=10,clipthresh=3.0,clipniter=4) |
---|
| 2173 | |
---|
| 2174 | Note: |
---|
| 2175 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2176 | based on specunit of 'channel'. |
---|
[2047] | 2177 | """ |
---|
| 2178 | |
---|
| 2179 | varlist = vars() |
---|
| 2180 | |
---|
| 2181 | if insitu is None: insitu = rcParams["insitu"] |
---|
| 2182 | if insitu: |
---|
| 2183 | workscan = self |
---|
| 2184 | else: |
---|
| 2185 | workscan = self.copy() |
---|
| 2186 | |
---|
| 2187 | nchan = workscan.nchan() |
---|
| 2188 | |
---|
[2081] | 2189 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2190 | if nwave is None: nwave = 3 |
---|
| 2191 | if maxwavelength is None: maxwavelength = 1.0 |
---|
| 2192 | if clipthresh is None: clipthresh = 3.0 |
---|
[2129] | 2193 | if clipniter is None: clipniter = 0 |
---|
[2081] | 2194 | if plot is None: plot = False |
---|
| 2195 | if getresidual is None: getresidual = True |
---|
| 2196 | if outlog is None: outlog = False |
---|
| 2197 | if blfile is None: blfile = "" |
---|
[2047] | 2198 | |
---|
[2081] | 2199 | if isinstance(nwave, int): |
---|
| 2200 | in_nwave = nwave |
---|
| 2201 | nwave = [] |
---|
| 2202 | for i in xrange(in_nwave+1): nwave.append(i) |
---|
| 2203 | |
---|
[2047] | 2204 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2205 | |
---|
| 2206 | try: |
---|
[2081] | 2207 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
| 2208 | workscan._sinusoid_baseline(mask, nwave, maxwavelength, clipthresh, clipniter, getresidual, outlog, blfile) |
---|
[2047] | 2209 | |
---|
| 2210 | workscan._add_history("sinusoid_baseline", varlist) |
---|
| 2211 | |
---|
| 2212 | if insitu: |
---|
| 2213 | self._assign(workscan) |
---|
| 2214 | else: |
---|
| 2215 | return workscan |
---|
| 2216 | |
---|
| 2217 | except RuntimeError, e: |
---|
| 2218 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2219 | if rcParams["verbose"]: |
---|
| 2220 | asaplog.push(str(e)) |
---|
| 2221 | asaplog.push(str(msg)) |
---|
| 2222 | return |
---|
| 2223 | else: |
---|
| 2224 | raise RuntimeError(str(e)+'\n'+msg) |
---|
| 2225 | |
---|
| 2226 | |
---|
[2081] | 2227 | def auto_sinusoid_baseline(self, insitu=None, mask=None, nwave=None, maxwavelength=None, |
---|
[2047] | 2228 | clipthresh=None, clipniter=None, edge=None, threshold=None, |
---|
[2081] | 2229 | chan_avg_limit=None, plot=None, getresidual=None, outlog=None, blfile=None): |
---|
[2047] | 2230 | """\ |
---|
[2094] | 2231 | Return a scan which has been baselined (all rows) with sinusoidal functions. |
---|
[2047] | 2232 | Spectral lines are detected first using linefinder and masked out |
---|
| 2233 | to avoid them affecting the baseline solution. |
---|
| 2234 | |
---|
| 2235 | Parameters: |
---|
[2081] | 2236 | insitu: if False a new scantable is returned. |
---|
| 2237 | Otherwise, the scaling is done in-situ |
---|
| 2238 | The default is taken from .asaprc (False) |
---|
| 2239 | mask: an optional mask retreived from scantable |
---|
| 2240 | nwave: the maximum wave number of sinusoids within |
---|
| 2241 | maxwavelength * (spectral range). |
---|
| 2242 | The default is 3 (i.e., sinusoids with wave |
---|
| 2243 | number of 0(=constant), 1, 2, and 3 are |
---|
| 2244 | used for fitting). Also it is possible to |
---|
| 2245 | explicitly specify all the wave numbers to |
---|
| 2246 | be used, by giving a list including them |
---|
| 2247 | (e.g. [0,1,2,15,16]). |
---|
| 2248 | maxwavelength: the longest sinusoidal wavelength. The |
---|
| 2249 | default is 1.0 (unit: spectral range). |
---|
| 2250 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2129] | 2251 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
[2081] | 2252 | edge: an optional number of channel to drop at |
---|
| 2253 | the edge of spectrum. If only one value is |
---|
| 2254 | specified, the same number will be dropped |
---|
| 2255 | from both sides of the spectrum. Default |
---|
| 2256 | is to keep all channels. Nested tuples |
---|
| 2257 | represent individual edge selection for |
---|
| 2258 | different IFs (a number of spectral channels |
---|
| 2259 | can be different) |
---|
| 2260 | threshold: the threshold used by line finder. It is |
---|
| 2261 | better to keep it large as only strong lines |
---|
| 2262 | affect the baseline solution. |
---|
| 2263 | chan_avg_limit:a maximum number of consequtive spectral |
---|
| 2264 | channels to average during the search of |
---|
| 2265 | weak and broad lines. The default is no |
---|
| 2266 | averaging (and no search for weak lines). |
---|
| 2267 | If such lines can affect the fitted baseline |
---|
| 2268 | (e.g. a high order polynomial is fitted), |
---|
| 2269 | increase this parameter (usually values up |
---|
| 2270 | to 8 are reasonable). Most users of this |
---|
| 2271 | method should find the default value sufficient. |
---|
| 2272 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2273 | plot the fit and the residual. In this each |
---|
| 2274 | indivual fit has to be approved, by typing 'y' |
---|
| 2275 | or 'n' |
---|
| 2276 | getresidual: if False, returns best-fit values instead of |
---|
| 2277 | residual. (default is True) |
---|
| 2278 | outlog: Output the coefficients of the best-fit |
---|
| 2279 | function to logger (default is False) |
---|
| 2280 | blfile: Name of a text file in which the best-fit |
---|
| 2281 | parameter values to be written |
---|
| 2282 | (default is "": no file/logger output) |
---|
[2047] | 2283 | |
---|
| 2284 | Example: |
---|
[2081] | 2285 | bscan = scan.auto_sinusoid_baseline(nwave=10, insitu=False) |
---|
| 2286 | |
---|
| 2287 | Note: |
---|
| 2288 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2289 | based on specunit of 'channel'. |
---|
[2047] | 2290 | """ |
---|
| 2291 | |
---|
| 2292 | varlist = vars() |
---|
| 2293 | |
---|
| 2294 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2295 | if insitu: |
---|
| 2296 | workscan = self |
---|
| 2297 | else: |
---|
| 2298 | workscan = self.copy() |
---|
| 2299 | |
---|
| 2300 | nchan = workscan.nchan() |
---|
| 2301 | |
---|
[2081] | 2302 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2303 | if nwave is None: nwave = 3 |
---|
| 2304 | if maxwavelength is None: maxwavelength = 1.0 |
---|
| 2305 | if clipthresh is None: clipthresh = 3.0 |
---|
[2129] | 2306 | if clipniter is None: clipniter = 0 |
---|
[2081] | 2307 | if edge is None: edge = (0,0) |
---|
| 2308 | if threshold is None: threshold = 3 |
---|
[2047] | 2309 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
[2081] | 2310 | if plot is None: plot = False |
---|
| 2311 | if getresidual is None: getresidual = True |
---|
| 2312 | if outlog is None: outlog = False |
---|
| 2313 | if blfile is None: blfile = "" |
---|
[2047] | 2314 | |
---|
| 2315 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2316 | |
---|
| 2317 | from asap.asaplinefind import linefinder |
---|
| 2318 | from asap import _is_sequence_or_number as _is_valid |
---|
| 2319 | |
---|
[2081] | 2320 | if isinstance(nwave, int): |
---|
| 2321 | in_nwave = nwave |
---|
| 2322 | nwave = [] |
---|
| 2323 | for i in xrange(in_nwave+1): nwave.append(i) |
---|
| 2324 | |
---|
[2047] | 2325 | if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ] |
---|
| 2326 | individualedge = False; |
---|
| 2327 | if len(edge) > 1: individualedge = isinstance(edge[0], list) or isinstance(edge[0], tuple) |
---|
| 2328 | |
---|
| 2329 | if individualedge: |
---|
| 2330 | for edgepar in edge: |
---|
| 2331 | if not _is_valid(edgepar, int): |
---|
| 2332 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 2333 | to be a pair of integers or an integer." |
---|
| 2334 | else: |
---|
| 2335 | if not _is_valid(edge, int): |
---|
| 2336 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
| 2337 | pair of integers specified as a tuple. \ |
---|
| 2338 | Nested tuples are allowed \ |
---|
| 2339 | to make individual selection for different IFs." |
---|
| 2340 | |
---|
| 2341 | if len(edge) > 1: |
---|
| 2342 | curedge = edge |
---|
| 2343 | else: |
---|
| 2344 | curedge = edge + edge |
---|
| 2345 | |
---|
| 2346 | try: |
---|
[2081] | 2347 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
[2047] | 2348 | if individualedge: |
---|
| 2349 | curedge = [] |
---|
| 2350 | for i in xrange(len(edge)): |
---|
| 2351 | curedge += edge[i] |
---|
| 2352 | |
---|
[2081] | 2353 | workscan._auto_sinusoid_baseline(mask, nwave, maxwavelength, clipthresh, clipniter, curedge, threshold, chan_avg_limit, getresidual, outlog, blfile) |
---|
[2047] | 2354 | |
---|
| 2355 | workscan._add_history("auto_sinusoid_baseline", varlist) |
---|
| 2356 | |
---|
| 2357 | if insitu: |
---|
| 2358 | self._assign(workscan) |
---|
| 2359 | else: |
---|
| 2360 | return workscan |
---|
| 2361 | |
---|
| 2362 | except RuntimeError, e: |
---|
| 2363 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2364 | if rcParams["verbose"]: |
---|
| 2365 | asaplog.push(str(e)) |
---|
| 2366 | asaplog.push(str(msg)) |
---|
| 2367 | return |
---|
| 2368 | else: |
---|
| 2369 | raise RuntimeError(str(e)+'\n'+msg) |
---|
| 2370 | |
---|
| 2371 | |
---|
| 2372 | @asaplog_post_dec |
---|
[2094] | 2373 | def cspline_baseline(self, insitu=None, mask=None, npiece=None, |
---|
| 2374 | clipthresh=None, clipniter=None, plot=None, getresidual=None, outlog=None, blfile=None): |
---|
[1846] | 2375 | """\ |
---|
[2012] | 2376 | Return a scan which has been baselined (all rows) by cubic spline function (piecewise cubic polynomial). |
---|
[513] | 2377 | Parameters: |
---|
[2012] | 2378 | insitu: If False a new scantable is returned. |
---|
| 2379 | Otherwise, the scaling is done in-situ |
---|
| 2380 | The default is taken from .asaprc (False) |
---|
| 2381 | mask: An optional mask |
---|
| 2382 | npiece: Number of pieces. (default is 2) |
---|
| 2383 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2129] | 2384 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
[2012] | 2385 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2386 | plot the fit and the residual. In this each |
---|
| 2387 | indivual fit has to be approved, by typing 'y' |
---|
| 2388 | or 'n' |
---|
[2094] | 2389 | getresidual:if False, returns best-fit values instead of |
---|
| 2390 | residual. (default is True) |
---|
[2012] | 2391 | outlog: Output the coefficients of the best-fit |
---|
| 2392 | function to logger (default is False) |
---|
| 2393 | blfile: Name of a text file in which the best-fit |
---|
| 2394 | parameter values to be written |
---|
| 2395 | (default is "": no file/logger output) |
---|
[1846] | 2396 | |
---|
[2012] | 2397 | Example: |
---|
| 2398 | # return a scan baselined by a cubic spline consisting of 2 pieces (i.e., 1 internal knot), |
---|
| 2399 | # also with 3-sigma clipping, iteration up to 4 times |
---|
| 2400 | bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4) |
---|
[2081] | 2401 | |
---|
| 2402 | Note: |
---|
| 2403 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2404 | based on specunit of 'channel'. |
---|
[2012] | 2405 | """ |
---|
| 2406 | |
---|
| 2407 | varlist = vars() |
---|
| 2408 | |
---|
| 2409 | if insitu is None: insitu = rcParams["insitu"] |
---|
| 2410 | if insitu: |
---|
| 2411 | workscan = self |
---|
| 2412 | else: |
---|
| 2413 | workscan = self.copy() |
---|
[1855] | 2414 | |
---|
[2012] | 2415 | nchan = workscan.nchan() |
---|
| 2416 | |
---|
[2094] | 2417 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2418 | if npiece is None: npiece = 2 |
---|
| 2419 | if clipthresh is None: clipthresh = 3.0 |
---|
[2129] | 2420 | if clipniter is None: clipniter = 0 |
---|
[2094] | 2421 | if plot is None: plot = False |
---|
| 2422 | if getresidual is None: getresidual = True |
---|
| 2423 | if outlog is None: outlog = False |
---|
| 2424 | if blfile is None: blfile = "" |
---|
[1855] | 2425 | |
---|
[2012] | 2426 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2427 | |
---|
| 2428 | try: |
---|
| 2429 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
[2094] | 2430 | workscan._cspline_baseline(mask, npiece, clipthresh, clipniter, getresidual, outlog, blfile) |
---|
[2012] | 2431 | |
---|
| 2432 | workscan._add_history("cspline_baseline", varlist) |
---|
| 2433 | |
---|
| 2434 | if insitu: |
---|
| 2435 | self._assign(workscan) |
---|
| 2436 | else: |
---|
| 2437 | return workscan |
---|
| 2438 | |
---|
| 2439 | except RuntimeError, e: |
---|
| 2440 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2441 | if rcParams["verbose"]: |
---|
| 2442 | asaplog.push(str(e)) |
---|
| 2443 | asaplog.push(str(msg)) |
---|
| 2444 | return |
---|
| 2445 | else: |
---|
| 2446 | raise RuntimeError(str(e)+'\n'+msg) |
---|
[1855] | 2447 | |
---|
| 2448 | |
---|
[2012] | 2449 | def auto_cspline_baseline(self, insitu=None, mask=None, npiece=None, clipthresh=None, |
---|
| 2450 | clipniter=None, edge=None, threshold=None, |
---|
[2094] | 2451 | chan_avg_limit=None, getresidual=None, plot=None, outlog=None, blfile=None): |
---|
[2012] | 2452 | """\ |
---|
| 2453 | Return a scan which has been baselined (all rows) by cubic spline |
---|
| 2454 | function (piecewise cubic polynomial). |
---|
| 2455 | Spectral lines are detected first using linefinder and masked out |
---|
| 2456 | to avoid them affecting the baseline solution. |
---|
| 2457 | |
---|
| 2458 | Parameters: |
---|
[794] | 2459 | insitu: if False a new scantable is returned. |
---|
| 2460 | Otherwise, the scaling is done in-situ |
---|
| 2461 | The default is taken from .asaprc (False) |
---|
[2012] | 2462 | mask: an optional mask retreived from scantable |
---|
| 2463 | npiece: Number of pieces. (default is 2) |
---|
| 2464 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2129] | 2465 | clipniter: maximum number of iteration of 'clipthresh'-sigma clipping (default is 0) |
---|
[2012] | 2466 | edge: an optional number of channel to drop at |
---|
| 2467 | the edge of spectrum. If only one value is |
---|
| 2468 | specified, the same number will be dropped |
---|
| 2469 | from both sides of the spectrum. Default |
---|
| 2470 | is to keep all channels. Nested tuples |
---|
| 2471 | represent individual edge selection for |
---|
| 2472 | different IFs (a number of spectral channels |
---|
| 2473 | can be different) |
---|
| 2474 | threshold: the threshold used by line finder. It is |
---|
| 2475 | better to keep it large as only strong lines |
---|
| 2476 | affect the baseline solution. |
---|
| 2477 | chan_avg_limit: |
---|
| 2478 | a maximum number of consequtive spectral |
---|
| 2479 | channels to average during the search of |
---|
| 2480 | weak and broad lines. The default is no |
---|
| 2481 | averaging (and no search for weak lines). |
---|
| 2482 | If such lines can affect the fitted baseline |
---|
| 2483 | (e.g. a high order polynomial is fitted), |
---|
| 2484 | increase this parameter (usually values up |
---|
| 2485 | to 8 are reasonable). Most users of this |
---|
| 2486 | method should find the default value sufficient. |
---|
| 2487 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2488 | plot the fit and the residual. In this each |
---|
| 2489 | indivual fit has to be approved, by typing 'y' |
---|
| 2490 | or 'n' |
---|
[2094] | 2491 | getresidual:if False, returns best-fit values instead of |
---|
| 2492 | residual. (default is True) |
---|
[2012] | 2493 | outlog: Output the coefficients of the best-fit |
---|
| 2494 | function to logger (default is False) |
---|
| 2495 | blfile: Name of a text file in which the best-fit |
---|
| 2496 | parameter values to be written |
---|
| 2497 | (default is "": no file/logger output) |
---|
[1846] | 2498 | |
---|
[1907] | 2499 | Example: |
---|
[2012] | 2500 | bscan = scan.auto_cspline_baseline(npiece=3, insitu=False) |
---|
[2081] | 2501 | |
---|
| 2502 | Note: |
---|
| 2503 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2504 | based on specunit of 'channel'. |
---|
[2012] | 2505 | """ |
---|
[1846] | 2506 | |
---|
[2012] | 2507 | varlist = vars() |
---|
| 2508 | |
---|
[513] | 2509 | if insitu is None: insitu = rcParams['insitu'] |
---|
[2012] | 2510 | if insitu: |
---|
| 2511 | workscan = self |
---|
| 2512 | else: |
---|
[1819] | 2513 | workscan = self.copy() |
---|
[2012] | 2514 | |
---|
| 2515 | nchan = workscan.nchan() |
---|
| 2516 | |
---|
[2094] | 2517 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2518 | if npiece is None: npiece = 2 |
---|
| 2519 | if clipthresh is None: clipthresh = 3.0 |
---|
[2129] | 2520 | if clipniter is None: clipniter = 0 |
---|
[2094] | 2521 | if edge is None: edge = (0, 0) |
---|
| 2522 | if threshold is None: threshold = 3 |
---|
[2012] | 2523 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
[2094] | 2524 | if plot is None: plot = False |
---|
| 2525 | if getresidual is None: getresidual = True |
---|
| 2526 | if outlog is None: outlog = False |
---|
| 2527 | if blfile is None: blfile = "" |
---|
[2012] | 2528 | |
---|
| 2529 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2530 | |
---|
| 2531 | from asap.asaplinefind import linefinder |
---|
| 2532 | from asap import _is_sequence_or_number as _is_valid |
---|
| 2533 | |
---|
| 2534 | if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ] |
---|
| 2535 | individualedge = False; |
---|
| 2536 | if len(edge) > 1: individualedge = isinstance(edge[0], list) or isinstance(edge[0], tuple) |
---|
| 2537 | |
---|
| 2538 | if individualedge: |
---|
| 2539 | for edgepar in edge: |
---|
| 2540 | if not _is_valid(edgepar, int): |
---|
| 2541 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 2542 | to be a pair of integers or an integer." |
---|
[1819] | 2543 | else: |
---|
[2012] | 2544 | if not _is_valid(edge, int): |
---|
| 2545 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
| 2546 | pair of integers specified as a tuple. \ |
---|
| 2547 | Nested tuples are allowed \ |
---|
| 2548 | to make individual selection for different IFs." |
---|
[1819] | 2549 | |
---|
[2012] | 2550 | if len(edge) > 1: |
---|
| 2551 | curedge = edge |
---|
[1391] | 2552 | else: |
---|
[2012] | 2553 | curedge = edge + edge |
---|
[1819] | 2554 | |
---|
[2012] | 2555 | try: |
---|
| 2556 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
| 2557 | if individualedge: |
---|
| 2558 | curedge = [] |
---|
| 2559 | for i in xrange(len(edge)): |
---|
| 2560 | curedge += edge[i] |
---|
| 2561 | |
---|
[2094] | 2562 | workscan._auto_cspline_baseline(mask, npiece, clipthresh, clipniter, curedge, threshold, chan_avg_limit, getresidual, outlog, blfile) |
---|
[2012] | 2563 | |
---|
| 2564 | workscan._add_history("auto_cspline_baseline", varlist) |
---|
[1907] | 2565 | |
---|
[1856] | 2566 | if insitu: |
---|
| 2567 | self._assign(workscan) |
---|
| 2568 | else: |
---|
| 2569 | return workscan |
---|
[2012] | 2570 | |
---|
| 2571 | except RuntimeError, e: |
---|
[1217] | 2572 | msg = "The fit failed, possibly because it didn't converge." |
---|
[2012] | 2573 | if rcParams["verbose"]: |
---|
| 2574 | asaplog.push(str(e)) |
---|
| 2575 | asaplog.push(str(msg)) |
---|
| 2576 | return |
---|
| 2577 | else: |
---|
| 2578 | raise RuntimeError(str(e)+'\n'+msg) |
---|
[513] | 2579 | |
---|
[2012] | 2580 | |
---|
[1931] | 2581 | @asaplog_post_dec |
---|
[2094] | 2582 | def poly_baseline(self, insitu=None, mask=None, order=None, plot=None, getresidual=None, outlog=None, blfile=None): |
---|
[1907] | 2583 | """\ |
---|
| 2584 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 2585 | Parameters: |
---|
[2012] | 2586 | insitu: if False a new scantable is returned. |
---|
| 2587 | Otherwise, the scaling is done in-situ |
---|
| 2588 | The default is taken from .asaprc (False) |
---|
[1907] | 2589 | mask: an optional mask |
---|
| 2590 | order: the order of the polynomial (default is 0) |
---|
| 2591 | plot: plot the fit and the residual. In this each |
---|
| 2592 | indivual fit has to be approved, by typing 'y' |
---|
[2012] | 2593 | or 'n' |
---|
[2094] | 2594 | getresidual:if False, returns best-fit values instead of |
---|
| 2595 | residual. (default is True) |
---|
[2012] | 2596 | outlog: Output the coefficients of the best-fit |
---|
| 2597 | function to logger (default is False) |
---|
| 2598 | blfile: Name of a text file in which the best-fit |
---|
| 2599 | parameter values to be written |
---|
| 2600 | (default is "": no file/logger output) |
---|
| 2601 | |
---|
[1907] | 2602 | Example: |
---|
| 2603 | # return a scan baselined by a third order polynomial, |
---|
| 2604 | # not using a mask |
---|
| 2605 | bscan = scan.poly_baseline(order=3) |
---|
| 2606 | """ |
---|
[1931] | 2607 | |
---|
| 2608 | varlist = vars() |
---|
| 2609 | |
---|
[1907] | 2610 | if insitu is None: insitu = rcParams["insitu"] |
---|
| 2611 | if insitu: |
---|
| 2612 | workscan = self |
---|
| 2613 | else: |
---|
| 2614 | workscan = self.copy() |
---|
| 2615 | |
---|
| 2616 | nchan = workscan.nchan() |
---|
| 2617 | |
---|
[2094] | 2618 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2619 | if order is None: order = 0 |
---|
| 2620 | if plot is None: plot = False |
---|
| 2621 | if getresidual is None: getresidual = True |
---|
| 2622 | if outlog is None: outlog = False |
---|
| 2623 | if blfile is None: blfile = "" |
---|
[1907] | 2624 | |
---|
[2012] | 2625 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2626 | |
---|
[1907] | 2627 | try: |
---|
[2012] | 2628 | rows = xrange(workscan.nrow()) |
---|
[1907] | 2629 | |
---|
[2012] | 2630 | #if len(rows) > 0: workscan._init_blinfo() |
---|
[1907] | 2631 | |
---|
[2012] | 2632 | if plot: |
---|
| 2633 | if outblfile: blf = open(blfile, "a") |
---|
| 2634 | |
---|
[1907] | 2635 | f = fitter() |
---|
| 2636 | f.set_function(lpoly=order) |
---|
| 2637 | for r in rows: |
---|
| 2638 | f.x = workscan._getabcissa(r) |
---|
| 2639 | f.y = workscan._getspectrum(r) |
---|
| 2640 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2641 | f.data = None |
---|
| 2642 | f.fit() |
---|
| 2643 | |
---|
| 2644 | f.plot(residual=True) |
---|
| 2645 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2646 | if accept_fit.upper() == "N": |
---|
[2012] | 2647 | #workscan._append_blinfo(None, None, None) |
---|
[1907] | 2648 | continue |
---|
[2012] | 2649 | |
---|
| 2650 | blpars = f.get_parameters() |
---|
| 2651 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 2652 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2094] | 2653 | workscan._setspectrum((f.fitter.getresidual() if getresidual else f.fitter.getfit()), r) |
---|
[1907] | 2654 | |
---|
[2012] | 2655 | if outblfile: |
---|
| 2656 | rms = workscan.get_rms(f.mask, r) |
---|
| 2657 | dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True) |
---|
| 2658 | blf.write(dataout) |
---|
| 2659 | |
---|
[1907] | 2660 | f._p.unmap() |
---|
| 2661 | f._p = None |
---|
[2012] | 2662 | |
---|
| 2663 | if outblfile: blf.close() |
---|
[1907] | 2664 | else: |
---|
[2094] | 2665 | workscan._poly_baseline(mask, order, getresidual, outlog, blfile) |
---|
[1907] | 2666 | |
---|
| 2667 | workscan._add_history("poly_baseline", varlist) |
---|
| 2668 | |
---|
| 2669 | if insitu: |
---|
| 2670 | self._assign(workscan) |
---|
| 2671 | else: |
---|
| 2672 | return workscan |
---|
| 2673 | |
---|
[1919] | 2674 | except RuntimeError, e: |
---|
[1907] | 2675 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2676 | if rcParams["verbose"]: |
---|
[1919] | 2677 | asaplog.push(str(e)) |
---|
[1907] | 2678 | asaplog.push(str(msg)) |
---|
| 2679 | return |
---|
| 2680 | else: |
---|
[1919] | 2681 | raise RuntimeError(str(e)+'\n'+msg) |
---|
[1907] | 2682 | |
---|
| 2683 | |
---|
[2012] | 2684 | def auto_poly_baseline(self, insitu=None, mask=None, order=None, edge=None, threshold=None, |
---|
[2094] | 2685 | chan_avg_limit=None, plot=None, getresidual=None, outlog=None, blfile=None): |
---|
[1846] | 2686 | """\ |
---|
[1931] | 2687 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[880] | 2688 | Spectral lines are detected first using linefinder and masked out |
---|
| 2689 | to avoid them affecting the baseline solution. |
---|
| 2690 | |
---|
| 2691 | Parameters: |
---|
[2012] | 2692 | insitu: if False a new scantable is returned. |
---|
| 2693 | Otherwise, the scaling is done in-situ |
---|
| 2694 | The default is taken from .asaprc (False) |
---|
[880] | 2695 | mask: an optional mask retreived from scantable |
---|
| 2696 | order: the order of the polynomial (default is 0) |
---|
[2012] | 2697 | edge: an optional number of channel to drop at |
---|
| 2698 | the edge of spectrum. If only one value is |
---|
| 2699 | specified, the same number will be dropped |
---|
| 2700 | from both sides of the spectrum. Default |
---|
| 2701 | is to keep all channels. Nested tuples |
---|
| 2702 | represent individual edge selection for |
---|
| 2703 | different IFs (a number of spectral channels |
---|
| 2704 | can be different) |
---|
| 2705 | threshold: the threshold used by line finder. It is |
---|
| 2706 | better to keep it large as only strong lines |
---|
| 2707 | affect the baseline solution. |
---|
[1280] | 2708 | chan_avg_limit: |
---|
[2012] | 2709 | a maximum number of consequtive spectral |
---|
| 2710 | channels to average during the search of |
---|
| 2711 | weak and broad lines. The default is no |
---|
| 2712 | averaging (and no search for weak lines). |
---|
| 2713 | If such lines can affect the fitted baseline |
---|
| 2714 | (e.g. a high order polynomial is fitted), |
---|
| 2715 | increase this parameter (usually values up |
---|
| 2716 | to 8 are reasonable). Most users of this |
---|
| 2717 | method should find the default value sufficient. |
---|
[1061] | 2718 | plot: plot the fit and the residual. In this each |
---|
| 2719 | indivual fit has to be approved, by typing 'y' |
---|
| 2720 | or 'n' |
---|
[2094] | 2721 | getresidual:if False, returns best-fit values instead of |
---|
| 2722 | residual. (default is True) |
---|
[2012] | 2723 | outlog: Output the coefficients of the best-fit |
---|
| 2724 | function to logger (default is False) |
---|
| 2725 | blfile: Name of a text file in which the best-fit |
---|
| 2726 | parameter values to be written |
---|
| 2727 | (default is "": no file/logger output) |
---|
[1846] | 2728 | |
---|
[2012] | 2729 | Example: |
---|
| 2730 | bscan = scan.auto_poly_baseline(order=7, insitu=False) |
---|
| 2731 | """ |
---|
[880] | 2732 | |
---|
[2012] | 2733 | varlist = vars() |
---|
[1846] | 2734 | |
---|
[2012] | 2735 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2736 | if insitu: |
---|
| 2737 | workscan = self |
---|
| 2738 | else: |
---|
| 2739 | workscan = self.copy() |
---|
[1846] | 2740 | |
---|
[2012] | 2741 | nchan = workscan.nchan() |
---|
| 2742 | |
---|
[2094] | 2743 | if mask is None: mask = [True for i in xrange(nchan)] |
---|
| 2744 | if order is None: order = 0 |
---|
| 2745 | if edge is None: edge = (0, 0) |
---|
| 2746 | if threshold is None: threshold = 3 |
---|
[2012] | 2747 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
[2094] | 2748 | if plot is None: plot = False |
---|
| 2749 | if getresidual is None: getresidual = True |
---|
| 2750 | if outlog is None: outlog = False |
---|
| 2751 | if blfile is None: blfile = "" |
---|
[1846] | 2752 | |
---|
[2012] | 2753 | outblfile = (blfile != "") and os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
| 2754 | |
---|
[880] | 2755 | from asap.asaplinefind import linefinder |
---|
| 2756 | from asap import _is_sequence_or_number as _is_valid |
---|
| 2757 | |
---|
[2012] | 2758 | if not (isinstance(edge, list) or isinstance(edge, tuple)): edge = [ edge ] |
---|
[1118] | 2759 | individualedge = False; |
---|
[2012] | 2760 | if len(edge) > 1: individualedge = isinstance(edge[0], list) or isinstance(edge[0], tuple) |
---|
[907] | 2761 | |
---|
[1118] | 2762 | if individualedge: |
---|
| 2763 | for edgepar in edge: |
---|
| 2764 | if not _is_valid(edgepar, int): |
---|
| 2765 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
| 2766 | to be a pair of integers or an integer." |
---|
[907] | 2767 | else: |
---|
[2012] | 2768 | if not _is_valid(edge, int): |
---|
| 2769 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
| 2770 | pair of integers specified as a tuple. \ |
---|
| 2771 | Nested tuples are allowed \ |
---|
| 2772 | to make individual selection for different IFs." |
---|
[880] | 2773 | |
---|
[2012] | 2774 | if len(edge) > 1: |
---|
| 2775 | curedge = edge |
---|
| 2776 | else: |
---|
| 2777 | curedge = edge + edge |
---|
[1907] | 2778 | |
---|
[2012] | 2779 | try: |
---|
| 2780 | rows = xrange(workscan.nrow()) |
---|
| 2781 | |
---|
| 2782 | #if len(rows) > 0: workscan._init_blinfo() |
---|
[880] | 2783 | |
---|
[2012] | 2784 | if plot: |
---|
| 2785 | if outblfile: blf = open(blfile, "a") |
---|
| 2786 | |
---|
| 2787 | fl = linefinder() |
---|
| 2788 | fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) |
---|
| 2789 | fl.set_scan(workscan) |
---|
| 2790 | f = fitter() |
---|
| 2791 | f.set_function(lpoly=order) |
---|
[880] | 2792 | |
---|
[2012] | 2793 | for r in rows: |
---|
| 2794 | if individualedge: |
---|
| 2795 | if len(edge) <= workscan.getif(r): |
---|
| 2796 | raise RuntimeError, "Number of edge elements appear to " \ |
---|
| 2797 | "be less than the number of IFs" |
---|
| 2798 | else: |
---|
| 2799 | curedge = edge[workscan.getif(r)] |
---|
[907] | 2800 | |
---|
[2012] | 2801 | fl.find_lines(r, mask_and(mask, workscan._getmask(r)), curedge) # (CAS-1434) |
---|
| 2802 | |
---|
| 2803 | f.x = workscan._getabcissa(r) |
---|
| 2804 | f.y = workscan._getspectrum(r) |
---|
| 2805 | f.mask = fl.get_mask() |
---|
| 2806 | f.data = None |
---|
| 2807 | f.fit() |
---|
| 2808 | |
---|
| 2809 | f.plot(residual=True) |
---|
| 2810 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2811 | if accept_fit.upper() == "N": |
---|
| 2812 | #workscan._append_blinfo(None, None, None) |
---|
| 2813 | continue |
---|
| 2814 | |
---|
| 2815 | blpars = f.get_parameters() |
---|
| 2816 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 2817 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2094] | 2818 | workscan._setspectrum((f.fitter.getresidual() if getresidual else f.fitter.getfit()), r) |
---|
[2012] | 2819 | |
---|
| 2820 | if outblfile: |
---|
| 2821 | rms = workscan.get_rms(f.mask, r) |
---|
| 2822 | dataout = workscan.format_blparams_row(blpars["params"], blpars["fixed"], rms, str(masklist), r, True) |
---|
| 2823 | blf.write(dataout) |
---|
| 2824 | |
---|
| 2825 | f._p.unmap() |
---|
| 2826 | f._p = None |
---|
| 2827 | |
---|
| 2828 | if outblfile: blf.close() |
---|
| 2829 | |
---|
| 2830 | else: |
---|
| 2831 | if individualedge: |
---|
| 2832 | curedge = [] |
---|
| 2833 | for i in xrange(len(edge)): |
---|
| 2834 | curedge += edge[i] |
---|
| 2835 | |
---|
[2094] | 2836 | workscan._auto_poly_baseline(mask, order, curedge, threshold, chan_avg_limit, getresidual, outlog, blfile) |
---|
[2012] | 2837 | |
---|
| 2838 | workscan._add_history("auto_poly_baseline", varlist) |
---|
| 2839 | |
---|
| 2840 | if insitu: |
---|
| 2841 | self._assign(workscan) |
---|
| 2842 | else: |
---|
| 2843 | return workscan |
---|
| 2844 | |
---|
| 2845 | except RuntimeError, e: |
---|
| 2846 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2847 | if rcParams["verbose"]: |
---|
| 2848 | asaplog.push(str(e)) |
---|
| 2849 | asaplog.push(str(msg)) |
---|
| 2850 | return |
---|
| 2851 | else: |
---|
| 2852 | raise RuntimeError(str(e)+'\n'+msg) |
---|
| 2853 | |
---|
| 2854 | |
---|
| 2855 | ### OBSOLETE ################################################################## |
---|
| 2856 | @asaplog_post_dec |
---|
| 2857 | def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None): |
---|
| 2858 | """ |
---|
| 2859 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[1907] | 2860 | |
---|
[2012] | 2861 | Parameters: |
---|
| 2862 | |
---|
| 2863 | mask: an optional mask |
---|
| 2864 | |
---|
| 2865 | order: the order of the polynomial (default is 0) |
---|
| 2866 | |
---|
| 2867 | plot: plot the fit and the residual. In this each |
---|
| 2868 | indivual fit has to be approved, by typing 'y' |
---|
| 2869 | or 'n' |
---|
| 2870 | |
---|
| 2871 | uselin: use linear polynomial fit |
---|
| 2872 | |
---|
| 2873 | insitu: if False a new scantable is returned. |
---|
| 2874 | Otherwise, the scaling is done in-situ |
---|
| 2875 | The default is taken from .asaprc (False) |
---|
| 2876 | |
---|
| 2877 | rows: row numbers of spectra to be processed. |
---|
| 2878 | (default is None: for all rows) |
---|
[1907] | 2879 | |
---|
[2012] | 2880 | Example: |
---|
| 2881 | # return a scan baselined by a third order polynomial, |
---|
| 2882 | # not using a mask |
---|
| 2883 | bscan = scan.poly_baseline(order=3) |
---|
[907] | 2884 | |
---|
[2012] | 2885 | """ |
---|
| 2886 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2887 | if not insitu: |
---|
| 2888 | workscan = self.copy() |
---|
| 2889 | else: |
---|
| 2890 | workscan = self |
---|
| 2891 | varlist = vars() |
---|
| 2892 | if mask is None: |
---|
| 2893 | mask = [True for i in xrange(self.nchan())] |
---|
[919] | 2894 | |
---|
[2012] | 2895 | try: |
---|
| 2896 | f = fitter() |
---|
| 2897 | if uselin: |
---|
| 2898 | f.set_function(lpoly=order) |
---|
| 2899 | else: |
---|
| 2900 | f.set_function(poly=order) |
---|
[1819] | 2901 | |
---|
[2012] | 2902 | if rows == None: |
---|
| 2903 | rows = xrange(workscan.nrow()) |
---|
| 2904 | elif isinstance(rows, int): |
---|
| 2905 | rows = [ rows ] |
---|
[1907] | 2906 | |
---|
[2012] | 2907 | if len(rows) > 0: |
---|
| 2908 | self.blpars = [] |
---|
| 2909 | self.masklists = [] |
---|
| 2910 | self.actualmask = [] |
---|
| 2911 | |
---|
| 2912 | for r in rows: |
---|
| 2913 | f.x = workscan._getabcissa(r) |
---|
| 2914 | f.y = workscan._getspectrum(r) |
---|
| 2915 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2916 | f.data = None |
---|
| 2917 | f.fit() |
---|
| 2918 | if plot: |
---|
| 2919 | f.plot(residual=True) |
---|
| 2920 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2921 | if x.upper() == 'N': |
---|
| 2922 | self.blpars.append(None) |
---|
| 2923 | self.masklists.append(None) |
---|
| 2924 | self.actualmask.append(None) |
---|
| 2925 | continue |
---|
| 2926 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
| 2927 | self.blpars.append(f.get_parameters()) |
---|
| 2928 | self.masklists.append(workscan.get_masklist(f.mask, row=r, silent=True)) |
---|
| 2929 | self.actualmask.append(f.mask) |
---|
[1819] | 2930 | |
---|
[1061] | 2931 | if plot: |
---|
[2012] | 2932 | f._p.unmap() |
---|
| 2933 | f._p = None |
---|
| 2934 | workscan._add_history("poly_baseline", varlist) |
---|
| 2935 | if insitu: |
---|
| 2936 | self._assign(workscan) |
---|
| 2937 | else: |
---|
| 2938 | return workscan |
---|
| 2939 | except RuntimeError: |
---|
| 2940 | msg = "The fit failed, possibly because it didn't converge." |
---|
| 2941 | raise RuntimeError(msg) |
---|
[1819] | 2942 | |
---|
[2012] | 2943 | def _init_blinfo(self): |
---|
| 2944 | """\ |
---|
| 2945 | Initialise the following three auxiliary members: |
---|
| 2946 | blpars : parameters of the best-fit baseline, |
---|
| 2947 | masklists : mask data (edge positions of masked channels) and |
---|
| 2948 | actualmask : mask data (in boolean list), |
---|
| 2949 | to keep for use later (including output to logger/text files). |
---|
| 2950 | Used by poly_baseline() and auto_poly_baseline() in case of |
---|
| 2951 | 'plot=True'. |
---|
| 2952 | """ |
---|
| 2953 | self.blpars = [] |
---|
| 2954 | self.masklists = [] |
---|
| 2955 | self.actualmask = [] |
---|
| 2956 | return |
---|
[880] | 2957 | |
---|
[2012] | 2958 | def _append_blinfo(self, data_blpars, data_masklists, data_actualmask): |
---|
| 2959 | """\ |
---|
| 2960 | Append baseline-fitting related info to blpars, masklist and |
---|
| 2961 | actualmask. |
---|
| 2962 | """ |
---|
| 2963 | self.blpars.append(data_blpars) |
---|
| 2964 | self.masklists.append(data_masklists) |
---|
| 2965 | self.actualmask.append(data_actualmask) |
---|
| 2966 | return |
---|
| 2967 | |
---|
[1862] | 2968 | @asaplog_post_dec |
---|
[914] | 2969 | def rotate_linpolphase(self, angle): |
---|
[1846] | 2970 | """\ |
---|
[914] | 2971 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
| 2972 | This is always done in situ in the raw data. So if you call this |
---|
| 2973 | function more than once then each call rotates the phase further. |
---|
[1846] | 2974 | |
---|
[914] | 2975 | Parameters: |
---|
[1846] | 2976 | |
---|
[914] | 2977 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2978 | |
---|
| 2979 | Example:: |
---|
| 2980 | |
---|
[914] | 2981 | scan.rotate_linpolphase(2.3) |
---|
[1846] | 2982 | |
---|
[914] | 2983 | """ |
---|
| 2984 | varlist = vars() |
---|
[936] | 2985 | self._math._rotate_linpolphase(self, angle) |
---|
[914] | 2986 | self._add_history("rotate_linpolphase", varlist) |
---|
| 2987 | return |
---|
[710] | 2988 | |
---|
[1862] | 2989 | @asaplog_post_dec |
---|
[914] | 2990 | def rotate_xyphase(self, angle): |
---|
[1846] | 2991 | """\ |
---|
[914] | 2992 | Rotate the phase of the XY correlation. This is always done in situ |
---|
| 2993 | in the data. So if you call this function more than once |
---|
| 2994 | then each call rotates the phase further. |
---|
[1846] | 2995 | |
---|
[914] | 2996 | Parameters: |
---|
[1846] | 2997 | |
---|
[914] | 2998 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 2999 | |
---|
| 3000 | Example:: |
---|
| 3001 | |
---|
[914] | 3002 | scan.rotate_xyphase(2.3) |
---|
[1846] | 3003 | |
---|
[914] | 3004 | """ |
---|
| 3005 | varlist = vars() |
---|
[936] | 3006 | self._math._rotate_xyphase(self, angle) |
---|
[914] | 3007 | self._add_history("rotate_xyphase", varlist) |
---|
| 3008 | return |
---|
| 3009 | |
---|
[1862] | 3010 | @asaplog_post_dec |
---|
[914] | 3011 | def swap_linears(self): |
---|
[1846] | 3012 | """\ |
---|
[1573] | 3013 | Swap the linear polarisations XX and YY, or better the first two |
---|
[1348] | 3014 | polarisations as this also works for ciculars. |
---|
[914] | 3015 | """ |
---|
| 3016 | varlist = vars() |
---|
[936] | 3017 | self._math._swap_linears(self) |
---|
[914] | 3018 | self._add_history("swap_linears", varlist) |
---|
| 3019 | return |
---|
| 3020 | |
---|
[1862] | 3021 | @asaplog_post_dec |
---|
[914] | 3022 | def invert_phase(self): |
---|
[1846] | 3023 | """\ |
---|
[914] | 3024 | Invert the phase of the complex polarisation |
---|
| 3025 | """ |
---|
| 3026 | varlist = vars() |
---|
[936] | 3027 | self._math._invert_phase(self) |
---|
[914] | 3028 | self._add_history("invert_phase", varlist) |
---|
| 3029 | return |
---|
| 3030 | |
---|
[1862] | 3031 | @asaplog_post_dec |
---|
[876] | 3032 | def add(self, offset, insitu=None): |
---|
[1846] | 3033 | """\ |
---|
[513] | 3034 | Return a scan where all spectra have the offset added |
---|
[1846] | 3035 | |
---|
[513] | 3036 | Parameters: |
---|
[1846] | 3037 | |
---|
[513] | 3038 | offset: the offset |
---|
[1855] | 3039 | |
---|
[513] | 3040 | insitu: if False a new scantable is returned. |
---|
| 3041 | Otherwise, the scaling is done in-situ |
---|
| 3042 | The default is taken from .asaprc (False) |
---|
[1846] | 3043 | |
---|
[513] | 3044 | """ |
---|
| 3045 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3046 | self._math._setinsitu(insitu) |
---|
[513] | 3047 | varlist = vars() |
---|
[876] | 3048 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
[1118] | 3049 | s._add_history("add", varlist) |
---|
[876] | 3050 | if insitu: |
---|
| 3051 | self._assign(s) |
---|
| 3052 | else: |
---|
[513] | 3053 | return s |
---|
| 3054 | |
---|
[1862] | 3055 | @asaplog_post_dec |
---|
[1308] | 3056 | def scale(self, factor, tsys=True, insitu=None): |
---|
[1846] | 3057 | """\ |
---|
| 3058 | |
---|
[1938] | 3059 | Return a scan where all spectra are scaled by the given 'factor' |
---|
[1846] | 3060 | |
---|
[513] | 3061 | Parameters: |
---|
[1846] | 3062 | |
---|
[1819] | 3063 | factor: the scaling factor (float or 1D float list) |
---|
[1855] | 3064 | |
---|
[513] | 3065 | insitu: if False a new scantable is returned. |
---|
| 3066 | Otherwise, the scaling is done in-situ |
---|
| 3067 | The default is taken from .asaprc (False) |
---|
[1855] | 3068 | |
---|
[513] | 3069 | tsys: if True (default) then apply the operation to Tsys |
---|
| 3070 | as well as the data |
---|
[1846] | 3071 | |
---|
[513] | 3072 | """ |
---|
| 3073 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3074 | self._math._setinsitu(insitu) |
---|
[513] | 3075 | varlist = vars() |
---|
[1819] | 3076 | s = None |
---|
| 3077 | import numpy |
---|
| 3078 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
| 3079 | if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): |
---|
| 3080 | from asapmath import _array2dOp |
---|
| 3081 | s = _array2dOp( self.copy(), factor, "MUL", tsys ) |
---|
| 3082 | else: |
---|
| 3083 | s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) |
---|
| 3084 | else: |
---|
| 3085 | s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) |
---|
[1118] | 3086 | s._add_history("scale", varlist) |
---|
[876] | 3087 | if insitu: |
---|
| 3088 | self._assign(s) |
---|
| 3089 | else: |
---|
[513] | 3090 | return s |
---|
| 3091 | |
---|
[1504] | 3092 | def set_sourcetype(self, match, matchtype="pattern", |
---|
| 3093 | sourcetype="reference"): |
---|
[1846] | 3094 | """\ |
---|
[1502] | 3095 | Set the type of the source to be an source or reference scan |
---|
[1846] | 3096 | using the provided pattern. |
---|
| 3097 | |
---|
[1502] | 3098 | Parameters: |
---|
[1846] | 3099 | |
---|
[1504] | 3100 | match: a Unix style pattern, regular expression or selector |
---|
[1855] | 3101 | |
---|
[1504] | 3102 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
| 3103 | 'regex' regular expression |
---|
[1855] | 3104 | |
---|
[1502] | 3105 | sourcetype: the type of the source to use (source/reference) |
---|
[1846] | 3106 | |
---|
[1502] | 3107 | """ |
---|
| 3108 | varlist = vars() |
---|
| 3109 | basesel = self.get_selection() |
---|
| 3110 | stype = -1 |
---|
| 3111 | if sourcetype.lower().startswith("r"): |
---|
| 3112 | stype = 1 |
---|
| 3113 | elif sourcetype.lower().startswith("s"): |
---|
| 3114 | stype = 0 |
---|
[1504] | 3115 | else: |
---|
[1502] | 3116 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
[1504] | 3117 | if matchtype.lower().startswith("p"): |
---|
| 3118 | matchtype = "pattern" |
---|
| 3119 | elif matchtype.lower().startswith("r"): |
---|
| 3120 | matchtype = "regex" |
---|
| 3121 | else: |
---|
| 3122 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
[1502] | 3123 | sel = selector() |
---|
| 3124 | if isinstance(match, selector): |
---|
| 3125 | sel = match |
---|
| 3126 | else: |
---|
[1504] | 3127 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
[1502] | 3128 | self.set_selection(basesel+sel) |
---|
| 3129 | self._setsourcetype(stype) |
---|
| 3130 | self.set_selection(basesel) |
---|
[1573] | 3131 | self._add_history("set_sourcetype", varlist) |
---|
[1502] | 3132 | |
---|
[1862] | 3133 | @asaplog_post_dec |
---|
[1857] | 3134 | @preserve_selection |
---|
[1819] | 3135 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
[1846] | 3136 | """\ |
---|
[670] | 3137 | This function allows to build quotients automatically. |
---|
[1819] | 3138 | It assumes the observation to have the same number of |
---|
[670] | 3139 | "ons" and "offs" |
---|
[1846] | 3140 | |
---|
[670] | 3141 | Parameters: |
---|
[1846] | 3142 | |
---|
[710] | 3143 | preserve: you can preserve (default) the continuum or |
---|
| 3144 | remove it. The equations used are |
---|
[1857] | 3145 | |
---|
[670] | 3146 | preserve: Output = Toff * (on/off) - Toff |
---|
[1857] | 3147 | |
---|
[1070] | 3148 | remove: Output = Toff * (on/off) - Ton |
---|
[1855] | 3149 | |
---|
[1573] | 3150 | mode: the on/off detection mode |
---|
[1348] | 3151 | 'paired' (default) |
---|
| 3152 | identifies 'off' scans by the |
---|
| 3153 | trailing '_R' (Mopra/Parkes) or |
---|
| 3154 | '_e'/'_w' (Tid) and matches |
---|
| 3155 | on/off pairs from the observing pattern |
---|
[1502] | 3156 | 'time' |
---|
| 3157 | finds the closest off in time |
---|
[1348] | 3158 | |
---|
[1857] | 3159 | .. todo:: verify argument is not implemented |
---|
| 3160 | |
---|
[670] | 3161 | """ |
---|
[1857] | 3162 | varlist = vars() |
---|
[1348] | 3163 | modes = ["time", "paired"] |
---|
[670] | 3164 | if not mode in modes: |
---|
[876] | 3165 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
| 3166 | raise ValueError(msg) |
---|
[1348] | 3167 | s = None |
---|
| 3168 | if mode.lower() == "paired": |
---|
[1857] | 3169 | sel = self.get_selection() |
---|
[1875] | 3170 | sel.set_query("SRCTYPE==psoff") |
---|
[1356] | 3171 | self.set_selection(sel) |
---|
[1348] | 3172 | offs = self.copy() |
---|
[1875] | 3173 | sel.set_query("SRCTYPE==pson") |
---|
[1356] | 3174 | self.set_selection(sel) |
---|
[1348] | 3175 | ons = self.copy() |
---|
| 3176 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
| 3177 | elif mode.lower() == "time": |
---|
| 3178 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
[1118] | 3179 | s._add_history("auto_quotient", varlist) |
---|
[876] | 3180 | return s |
---|
[710] | 3181 | |
---|
[1862] | 3182 | @asaplog_post_dec |
---|
[1145] | 3183 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
[1846] | 3184 | """\ |
---|
[1143] | 3185 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
[1846] | 3186 | |
---|
[1143] | 3187 | Parameters: |
---|
[1846] | 3188 | |
---|
[1145] | 3189 | mask: an optional mask to be used when weight == 'stddev' |
---|
[1855] | 3190 | |
---|
[1143] | 3191 | weight: How to average the off beams. Default is 'median'. |
---|
[1855] | 3192 | |
---|
[1145] | 3193 | preserve: you can preserve (default) the continuum or |
---|
[1855] | 3194 | remove it. The equations used are: |
---|
[1846] | 3195 | |
---|
[1855] | 3196 | preserve: Output = Toff * (on/off) - Toff |
---|
| 3197 | |
---|
| 3198 | remove: Output = Toff * (on/off) - Ton |
---|
| 3199 | |
---|
[1217] | 3200 | """ |
---|
[1593] | 3201 | mask = mask or () |
---|
[1141] | 3202 | varlist = vars() |
---|
| 3203 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
[1143] | 3204 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
| 3205 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
[1217] | 3206 | from asapmath import quotient |
---|
[1145] | 3207 | q = quotient(on, off, preserve) |
---|
[1143] | 3208 | q._add_history("mx_quotient", varlist) |
---|
[1217] | 3209 | return q |
---|
[513] | 3210 | |
---|
[1862] | 3211 | @asaplog_post_dec |
---|
[718] | 3212 | def freq_switch(self, insitu=None): |
---|
[1846] | 3213 | """\ |
---|
[718] | 3214 | Apply frequency switching to the data. |
---|
[1846] | 3215 | |
---|
[718] | 3216 | Parameters: |
---|
[1846] | 3217 | |
---|
[718] | 3218 | insitu: if False a new scantable is returned. |
---|
| 3219 | Otherwise, the swictching is done in-situ |
---|
| 3220 | The default is taken from .asaprc (False) |
---|
[1846] | 3221 | |
---|
[718] | 3222 | """ |
---|
| 3223 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3224 | self._math._setinsitu(insitu) |
---|
[718] | 3225 | varlist = vars() |
---|
[876] | 3226 | s = scantable(self._math._freqswitch(self)) |
---|
[1118] | 3227 | s._add_history("freq_switch", varlist) |
---|
[1856] | 3228 | if insitu: |
---|
| 3229 | self._assign(s) |
---|
| 3230 | else: |
---|
| 3231 | return s |
---|
[718] | 3232 | |
---|
[1862] | 3233 | @asaplog_post_dec |
---|
[780] | 3234 | def recalc_azel(self): |
---|
[1846] | 3235 | """Recalculate the azimuth and elevation for each position.""" |
---|
[780] | 3236 | varlist = vars() |
---|
[876] | 3237 | self._recalcazel() |
---|
[780] | 3238 | self._add_history("recalc_azel", varlist) |
---|
| 3239 | return |
---|
| 3240 | |
---|
[1862] | 3241 | @asaplog_post_dec |
---|
[513] | 3242 | def __add__(self, other): |
---|
| 3243 | varlist = vars() |
---|
| 3244 | s = None |
---|
| 3245 | if isinstance(other, scantable): |
---|
[1573] | 3246 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
[513] | 3247 | elif isinstance(other, float): |
---|
[876] | 3248 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
[2144] | 3249 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3250 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3251 | from asapmath import _array2dOp |
---|
| 3252 | s = _array2dOp( self.copy(), other, "ADD", False ) |
---|
| 3253 | else: |
---|
| 3254 | s = scantable( self._math._arrayop( self.copy(), other, "ADD", False ) ) |
---|
[513] | 3255 | else: |
---|
[718] | 3256 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3257 | s._add_history("operator +", varlist) |
---|
| 3258 | return s |
---|
| 3259 | |
---|
[1862] | 3260 | @asaplog_post_dec |
---|
[513] | 3261 | def __sub__(self, other): |
---|
| 3262 | """ |
---|
| 3263 | implicit on all axes and on Tsys |
---|
| 3264 | """ |
---|
| 3265 | varlist = vars() |
---|
| 3266 | s = None |
---|
| 3267 | if isinstance(other, scantable): |
---|
[1588] | 3268 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
[513] | 3269 | elif isinstance(other, float): |
---|
[876] | 3270 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
[2144] | 3271 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3272 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3273 | from asapmath import _array2dOp |
---|
| 3274 | s = _array2dOp( self.copy(), other, "SUB", False ) |
---|
| 3275 | else: |
---|
| 3276 | s = scantable( self._math._arrayop( self.copy(), other, "SUB", False ) ) |
---|
[513] | 3277 | else: |
---|
[718] | 3278 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3279 | s._add_history("operator -", varlist) |
---|
| 3280 | return s |
---|
[710] | 3281 | |
---|
[1862] | 3282 | @asaplog_post_dec |
---|
[513] | 3283 | def __mul__(self, other): |
---|
| 3284 | """ |
---|
| 3285 | implicit on all axes and on Tsys |
---|
| 3286 | """ |
---|
| 3287 | varlist = vars() |
---|
| 3288 | s = None |
---|
| 3289 | if isinstance(other, scantable): |
---|
[1588] | 3290 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
[513] | 3291 | elif isinstance(other, float): |
---|
[876] | 3292 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
[2144] | 3293 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3294 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3295 | from asapmath import _array2dOp |
---|
| 3296 | s = _array2dOp( self.copy(), other, "MUL", False ) |
---|
| 3297 | else: |
---|
| 3298 | s = scantable( self._math._arrayop( self.copy(), other, "MUL", False ) ) |
---|
[513] | 3299 | else: |
---|
[718] | 3300 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3301 | s._add_history("operator *", varlist) |
---|
| 3302 | return s |
---|
| 3303 | |
---|
[710] | 3304 | |
---|
[1862] | 3305 | @asaplog_post_dec |
---|
[513] | 3306 | def __div__(self, other): |
---|
| 3307 | """ |
---|
| 3308 | implicit on all axes and on Tsys |
---|
| 3309 | """ |
---|
| 3310 | varlist = vars() |
---|
| 3311 | s = None |
---|
| 3312 | if isinstance(other, scantable): |
---|
[1589] | 3313 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
[513] | 3314 | elif isinstance(other, float): |
---|
| 3315 | if other == 0.0: |
---|
[718] | 3316 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
[876] | 3317 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
[2144] | 3318 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
| 3319 | if isinstance(other[0], list) or isinstance(other[0], numpy.ndarray): |
---|
| 3320 | from asapmath import _array2dOp |
---|
| 3321 | s = _array2dOp( self.copy(), other, "DIV", False ) |
---|
| 3322 | else: |
---|
| 3323 | s = scantable( self._math._arrayop( self.copy(), other, "DIV", False ) ) |
---|
[513] | 3324 | else: |
---|
[718] | 3325 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3326 | s._add_history("operator /", varlist) |
---|
| 3327 | return s |
---|
| 3328 | |
---|
[1862] | 3329 | @asaplog_post_dec |
---|
[530] | 3330 | def get_fit(self, row=0): |
---|
[1846] | 3331 | """\ |
---|
[530] | 3332 | Print or return the stored fits for a row in the scantable |
---|
[1846] | 3333 | |
---|
[530] | 3334 | Parameters: |
---|
[1846] | 3335 | |
---|
[530] | 3336 | row: the row which the fit has been applied to. |
---|
[1846] | 3337 | |
---|
[530] | 3338 | """ |
---|
| 3339 | if row > self.nrow(): |
---|
| 3340 | return |
---|
[976] | 3341 | from asap.asapfit import asapfit |
---|
[530] | 3342 | fit = asapfit(self._getfit(row)) |
---|
[1859] | 3343 | asaplog.push( '%s' %(fit) ) |
---|
| 3344 | return fit.as_dict() |
---|
[530] | 3345 | |
---|
[1483] | 3346 | def flag_nans(self): |
---|
[1846] | 3347 | """\ |
---|
[1483] | 3348 | Utility function to flag NaN values in the scantable. |
---|
| 3349 | """ |
---|
| 3350 | import numpy |
---|
| 3351 | basesel = self.get_selection() |
---|
| 3352 | for i in range(self.nrow()): |
---|
[1589] | 3353 | sel = self.get_row_selector(i) |
---|
| 3354 | self.set_selection(basesel+sel) |
---|
[1483] | 3355 | nans = numpy.isnan(self._getspectrum(0)) |
---|
| 3356 | if numpy.any(nans): |
---|
| 3357 | bnans = [ bool(v) for v in nans] |
---|
| 3358 | self.flag(bnans) |
---|
| 3359 | self.set_selection(basesel) |
---|
| 3360 | |
---|
[1588] | 3361 | def get_row_selector(self, rowno): |
---|
[1992] | 3362 | #return selector(beams=self.getbeam(rowno), |
---|
| 3363 | # ifs=self.getif(rowno), |
---|
| 3364 | # pols=self.getpol(rowno), |
---|
| 3365 | # scans=self.getscan(rowno), |
---|
| 3366 | # cycles=self.getcycle(rowno)) |
---|
| 3367 | return selector(rows=[rowno]) |
---|
[1573] | 3368 | |
---|
[484] | 3369 | def _add_history(self, funcname, parameters): |
---|
[1435] | 3370 | if not rcParams['scantable.history']: |
---|
| 3371 | return |
---|
[484] | 3372 | # create date |
---|
| 3373 | sep = "##" |
---|
| 3374 | from datetime import datetime |
---|
| 3375 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
| 3376 | hist = dstr+sep |
---|
| 3377 | hist += funcname+sep#cdate+sep |
---|
| 3378 | if parameters.has_key('self'): del parameters['self'] |
---|
[1118] | 3379 | for k, v in parameters.iteritems(): |
---|
[484] | 3380 | if type(v) is dict: |
---|
[1118] | 3381 | for k2, v2 in v.iteritems(): |
---|
[484] | 3382 | hist += k2 |
---|
| 3383 | hist += "=" |
---|
[1118] | 3384 | if isinstance(v2, scantable): |
---|
[484] | 3385 | hist += 'scantable' |
---|
| 3386 | elif k2 == 'mask': |
---|
[1118] | 3387 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
[513] | 3388 | hist += str(self._zip_mask(v2)) |
---|
| 3389 | else: |
---|
| 3390 | hist += str(v2) |
---|
[484] | 3391 | else: |
---|
[513] | 3392 | hist += str(v2) |
---|
[484] | 3393 | else: |
---|
| 3394 | hist += k |
---|
| 3395 | hist += "=" |
---|
[1118] | 3396 | if isinstance(v, scantable): |
---|
[484] | 3397 | hist += 'scantable' |
---|
| 3398 | elif k == 'mask': |
---|
[1118] | 3399 | if isinstance(v, list) or isinstance(v, tuple): |
---|
[513] | 3400 | hist += str(self._zip_mask(v)) |
---|
| 3401 | else: |
---|
| 3402 | hist += str(v) |
---|
[484] | 3403 | else: |
---|
| 3404 | hist += str(v) |
---|
| 3405 | hist += sep |
---|
| 3406 | hist = hist[:-2] # remove trailing '##' |
---|
| 3407 | self._addhistory(hist) |
---|
| 3408 | |
---|
[710] | 3409 | |
---|
[484] | 3410 | def _zip_mask(self, mask): |
---|
| 3411 | mask = list(mask) |
---|
| 3412 | i = 0 |
---|
| 3413 | segments = [] |
---|
| 3414 | while mask[i:].count(1): |
---|
| 3415 | i += mask[i:].index(1) |
---|
| 3416 | if mask[i:].count(0): |
---|
| 3417 | j = i + mask[i:].index(0) |
---|
| 3418 | else: |
---|
[710] | 3419 | j = len(mask) |
---|
[1118] | 3420 | segments.append([i, j]) |
---|
[710] | 3421 | i = j |
---|
[484] | 3422 | return segments |
---|
[714] | 3423 | |
---|
[626] | 3424 | def _get_ordinate_label(self): |
---|
| 3425 | fu = "("+self.get_fluxunit()+")" |
---|
| 3426 | import re |
---|
| 3427 | lbl = "Intensity" |
---|
[1118] | 3428 | if re.match(".K.", fu): |
---|
[626] | 3429 | lbl = "Brightness Temperature "+ fu |
---|
[1118] | 3430 | elif re.match(".Jy.", fu): |
---|
[626] | 3431 | lbl = "Flux density "+ fu |
---|
| 3432 | return lbl |
---|
[710] | 3433 | |
---|
[876] | 3434 | def _check_ifs(self): |
---|
[1986] | 3435 | #nchans = [self.nchan(i) for i in range(self.nif(-1))] |
---|
| 3436 | nchans = [self.nchan(i) for i in self.getifnos()] |
---|
[2004] | 3437 | nchans = filter(lambda t: t > 0, nchans) |
---|
[876] | 3438 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
[976] | 3439 | |
---|
[1862] | 3440 | @asaplog_post_dec |
---|
[1916] | 3441 | #def _fill(self, names, unit, average, getpt, antenna): |
---|
| 3442 | def _fill(self, names, unit, average, opts={}): |
---|
[976] | 3443 | first = True |
---|
| 3444 | fullnames = [] |
---|
| 3445 | for name in names: |
---|
| 3446 | name = os.path.expandvars(name) |
---|
| 3447 | name = os.path.expanduser(name) |
---|
| 3448 | if not os.path.exists(name): |
---|
| 3449 | msg = "File '%s' does not exists" % (name) |
---|
| 3450 | raise IOError(msg) |
---|
| 3451 | fullnames.append(name) |
---|
| 3452 | if average: |
---|
| 3453 | asaplog.push('Auto averaging integrations') |
---|
[1079] | 3454 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
[976] | 3455 | for name in fullnames: |
---|
[1073] | 3456 | tbl = Scantable(stype) |
---|
[2004] | 3457 | if is_ms( name ): |
---|
| 3458 | r = msfiller( tbl ) |
---|
| 3459 | else: |
---|
| 3460 | r = filler( tbl ) |
---|
| 3461 | rx = rcParams['scantable.reference'] |
---|
| 3462 | r.setreferenceexpr(rx) |
---|
| 3463 | #r = filler(tbl) |
---|
| 3464 | #rx = rcParams['scantable.reference'] |
---|
| 3465 | #r.setreferenceexpr(rx) |
---|
[976] | 3466 | msg = "Importing %s..." % (name) |
---|
[1118] | 3467 | asaplog.push(msg, False) |
---|
[1916] | 3468 | #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } |
---|
[1904] | 3469 | r.open(name, opts)# antenna, -1, -1, getpt) |
---|
[1843] | 3470 | r.fill() |
---|
[976] | 3471 | if average: |
---|
[1118] | 3472 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
[976] | 3473 | if not first: |
---|
| 3474 | tbl = self._math._merge([self, tbl]) |
---|
| 3475 | Scantable.__init__(self, tbl) |
---|
[1843] | 3476 | r.close() |
---|
[1118] | 3477 | del r, tbl |
---|
[976] | 3478 | first = False |
---|
[1861] | 3479 | #flush log |
---|
| 3480 | asaplog.post() |
---|
[976] | 3481 | if unit is not None: |
---|
| 3482 | self.set_fluxunit(unit) |
---|
[1824] | 3483 | if not is_casapy(): |
---|
| 3484 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[976] | 3485 | |
---|
[2012] | 3486 | |
---|
[1402] | 3487 | def __getitem__(self, key): |
---|
| 3488 | if key < 0: |
---|
| 3489 | key += self.nrow() |
---|
| 3490 | if key >= self.nrow(): |
---|
| 3491 | raise IndexError("Row index out of range.") |
---|
| 3492 | return self._getspectrum(key) |
---|
| 3493 | |
---|
| 3494 | def __setitem__(self, key, value): |
---|
| 3495 | if key < 0: |
---|
| 3496 | key += self.nrow() |
---|
| 3497 | if key >= self.nrow(): |
---|
| 3498 | raise IndexError("Row index out of range.") |
---|
| 3499 | if not hasattr(value, "__len__") or \ |
---|
| 3500 | len(value) > self.nchan(self.getif(key)): |
---|
| 3501 | raise ValueError("Spectrum length doesn't match.") |
---|
| 3502 | return self._setspectrum(value, key) |
---|
| 3503 | |
---|
| 3504 | def __len__(self): |
---|
| 3505 | return self.nrow() |
---|
| 3506 | |
---|
| 3507 | def __iter__(self): |
---|
| 3508 | for i in range(len(self)): |
---|
| 3509 | yield self[i] |
---|