[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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[2751] | 4 | import re
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[2315] | 5 | import tempfile
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[1948] | 6 | import numpy
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[1691] | 7 | try:
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| 8 | from functools import wraps as wraps_dec
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| 9 | except ImportError:
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| 10 | from asap.compatibility import wraps as wraps_dec
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| 11 |
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[1824] | 12 | from asap.env import is_casapy
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[876] | 13 | from asap._asap import Scantable
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[2004] | 14 | from asap._asap import filler, msfiller
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[1824] | 15 | from asap.parameters import rcParams
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[1862] | 16 | from asap.logging import asaplog, asaplog_post_dec
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[1824] | 17 | from asap.selector import selector
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| 18 | from asap.linecatalog import linecatalog
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[1600] | 19 | from asap.coordinate import coordinate
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[1859] | 20 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page
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[1907] | 21 | from asap.asapfitter import fitter
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[102] | 22 |
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[1689] | 23 | def preserve_selection(func):
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[1691] | 24 | @wraps_dec(func)
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[1689] | 25 | def wrap(obj, *args, **kw):
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| 26 | basesel = obj.get_selection()
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[1857] | 27 | try:
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| 28 | val = func(obj, *args, **kw)
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| 29 | finally:
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| 30 | obj.set_selection(basesel)
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[1689] | 31 | return val
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| 32 | return wrap
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| 33 |
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[1846] | 34 | def is_scantable(filename):
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| 35 | """Is the given file a scantable?
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[1689] | 36 |
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[1846] | 37 | Parameters:
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| 38 |
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| 39 | filename: the name of the file/directory to test
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| 40 |
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| 41 | """
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[1883] | 42 | if ( os.path.isdir(filename)
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| 43 | and os.path.exists(filename+'/table.info')
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| 44 | and os.path.exists(filename+'/table.dat') ):
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| 45 | f=open(filename+'/table.info')
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| 46 | l=f.readline()
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| 47 | f.close()
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[2753] | 48 | match_pattern = '^Type = (Scantable)? *$'
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[2751] | 49 | if re.match(match_pattern,l):
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[1883] | 50 | return True
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| 51 | else:
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| 52 | return False
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| 53 | else:
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| 54 | return False
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| 55 | ## return (os.path.isdir(filename)
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| 56 | ## and not os.path.exists(filename+'/table.f1')
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| 57 | ## and os.path.exists(filename+'/table.info'))
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[1697] | 58 |
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[1883] | 59 | def is_ms(filename):
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| 60 | """Is the given file a MeasurementSet?
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[1697] | 61 |
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[1883] | 62 | Parameters:
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| 63 |
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| 64 | filename: the name of the file/directory to test
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| 65 |
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| 66 | """
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| 67 | if ( os.path.isdir(filename)
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| 68 | and os.path.exists(filename+'/table.info')
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| 69 | and os.path.exists(filename+'/table.dat') ):
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| 70 | f=open(filename+'/table.info')
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| 71 | l=f.readline()
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| 72 | f.close()
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| 73 | if ( l.find('Measurement Set') != -1 ):
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| 74 | return True
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| 75 | else:
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| 76 | return False
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| 77 | else:
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| 78 | return False
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[2186] | 79 |
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| 80 | def normalise_edge_param(edge):
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| 81 | """\
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| 82 | Convert a given edge value to a one-dimensional array that can be
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| 83 | given to baseline-fitting/subtraction functions.
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| 84 | The length of the output value will be an even because values for
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| 85 | the both sides of spectra are to be contained for each IF. When
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| 86 | the length is 2, the values will be applied to all IFs. If the length
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| 87 | is larger than 2, it will be 2*ifnos().
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| 88 | Accepted format of edge include:
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| 89 | * an integer - will be used for both sides of spectra of all IFs.
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| 90 | e.g. 10 is converted to [10,10]
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[2277] | 91 | * an empty list/tuple [] - converted to [0, 0] and used for all IFs.
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[2186] | 92 | * a list/tuple containing an integer - same as the above case.
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| 93 | e.g. [10] is converted to [10,10]
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| 94 | * a list/tuple containing two integers - will be used for all IFs.
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| 95 | e.g. [5,10] is output as it is. no need to convert.
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| 96 | * a list/tuple of lists/tuples containing TWO integers -
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| 97 | each element of edge will be used for each IF.
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[2277] | 98 | e.g. [[5,10],[15,20]] - [5,10] for IF[0] and [15,20] for IF[1].
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| 99 |
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| 100 | If an element contains the same integer values, the input 'edge'
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| 101 | parameter can be given in a simpler shape in the following cases:
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[2186] | 102 | ** when len(edge)!=2
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[2277] | 103 | any elements containing the same values can be replaced
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| 104 | to single integers.
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| 105 | e.g. [[15,15]] can be simplified to [15] (or [15,15] or 15 also).
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| 106 | e.g. [[1,1],[2,2],[3,3]] can be simplified to [1,2,3].
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[2186] | 107 | ** when len(edge)=2
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| 108 | care is needed for this case: ONLY ONE of the
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| 109 | elements can be a single integer,
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| 110 | e.g. [[5,5],[10,10]] can be simplified to [5,[10,10]]
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[2277] | 111 | or [[5,5],10], but can NOT be simplified to [5,10].
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[2186] | 112 | when [5,10] given, it is interpreted as
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[2277] | 113 | [[5,10],[5,10],[5,10],...] instead, as shown before.
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[2186] | 114 | """
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| 115 | from asap import _is_sequence_or_number as _is_valid
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| 116 | if isinstance(edge, list) or isinstance(edge, tuple):
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| 117 | for edgepar in edge:
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| 118 | if not _is_valid(edgepar, int):
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| 119 | raise ValueError, "Each element of the 'edge' tuple has \
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| 120 | to be a pair of integers or an integer."
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| 121 | if isinstance(edgepar, list) or isinstance(edgepar, tuple):
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| 122 | if len(edgepar) != 2:
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| 123 | raise ValueError, "Each element of the 'edge' tuple has \
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| 124 | to be a pair of integers or an integer."
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| 125 | else:
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| 126 | if not _is_valid(edge, int):
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| 127 | raise ValueError, "Parameter 'edge' has to be an integer or a \
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| 128 | pair of integers specified as a tuple. \
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| 129 | Nested tuples are allowed \
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| 130 | to make individual selection for different IFs."
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| 131 |
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| 132 |
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| 133 | if isinstance(edge, int):
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| 134 | edge = [ edge, edge ] # e.g. 3 => [3,3]
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| 135 | elif isinstance(edge, list) or isinstance(edge, tuple):
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| 136 | if len(edge) == 0:
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| 137 | edge = [0, 0] # e.g. [] => [0,0]
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| 138 | elif len(edge) == 1:
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| 139 | if isinstance(edge[0], int):
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| 140 | edge = [ edge[0], edge[0] ] # e.g. [1] => [1,1]
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| 141 |
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| 142 | commonedge = True
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| 143 | if len(edge) > 2: commonedge = False
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| 144 | else:
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| 145 | for edgepar in edge:
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| 146 | if isinstance(edgepar, list) or isinstance(edgepar, tuple):
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| 147 | commonedge = False
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| 148 | break
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| 149 |
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| 150 | if commonedge:
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| 151 | if len(edge) > 1:
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| 152 | norm_edge = edge
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| 153 | else:
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| 154 | norm_edge = edge + edge
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| 155 | else:
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| 156 | norm_edge = []
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| 157 | for edgepar in edge:
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| 158 | if isinstance(edgepar, int):
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| 159 | norm_edge += [edgepar, edgepar]
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| 160 | else:
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| 161 | norm_edge += edgepar
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| 162 |
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| 163 | return norm_edge
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| 164 |
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| 165 | def raise_fitting_failure_exception(e):
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| 166 | msg = "The fit failed, possibly because it didn't converge."
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| 167 | if rcParams["verbose"]:
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| 168 | asaplog.push(str(e))
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| 169 | asaplog.push(str(msg))
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| 170 | else:
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| 171 | raise RuntimeError(str(e)+'\n'+msg)
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| 172 |
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[2189] | 173 | def pack_progress_params(showprogress, minnrow):
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| 174 | return str(showprogress).lower() + ',' + str(minnrow)
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| 175 |
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[2767] | 176 | def pack_blinfo(blinfo, maxirow):
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| 177 | """\
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| 178 | convert a dictionary or a list of dictionaries of baseline info
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| 179 | into a list of comma-separated strings.
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| 180 | """
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| 181 | if isinstance(blinfo, dict):
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| 182 | res = do_pack_blinfo(blinfo, maxirow)
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| 183 | return [res] if res != '' else []
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| 184 | elif isinstance(blinfo, list) or isinstance(blinfo, tuple):
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| 185 | res = []
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| 186 | for i in xrange(len(blinfo)):
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| 187 | resi = do_pack_blinfo(blinfo[i], maxirow)
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| 188 | if resi != '':
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| 189 | res.append(resi)
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| 190 | return res
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| 191 |
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| 192 | def do_pack_blinfo(blinfo, maxirow):
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| 193 | """\
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| 194 | convert a dictionary of baseline info for a spectrum into
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| 195 | a comma-separated string.
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| 196 | """
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| 197 | dinfo = {}
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| 198 | for key in ['row', 'blfunc', 'masklist']:
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| 199 | if blinfo.has_key(key):
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| 200 | val = blinfo[key]
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| 201 | if key == 'row':
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| 202 | irow = val
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| 203 | if isinstance(val, list) or isinstance(val, tuple):
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| 204 | slval = []
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| 205 | for i in xrange(len(val)):
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| 206 | if isinstance(val[i], list) or isinstance(val[i], tuple):
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| 207 | for j in xrange(len(val[i])):
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| 208 | slval.append(str(val[i][j]))
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| 209 | else:
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| 210 | slval.append(str(val[i]))
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| 211 | sval = ",".join(slval)
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| 212 | else:
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| 213 | sval = str(val)
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| 214 |
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| 215 | dinfo[key] = sval
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| 216 | else:
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| 217 | raise ValueError("'"+key+"' is missing in blinfo.")
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| 218 |
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| 219 | if irow >= maxirow: return ''
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| 220 |
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| 221 | for key in ['order', 'npiece', 'nwave']:
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| 222 | if blinfo.has_key(key):
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| 223 | val = blinfo[key]
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| 224 | if isinstance(val, list) or isinstance(val, tuple):
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| 225 | slval = []
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| 226 | for i in xrange(len(val)):
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| 227 | slval.append(str(val[i]))
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| 228 | sval = ",".join(slval)
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| 229 | else:
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| 230 | sval = str(val)
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| 231 | dinfo[key] = sval
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| 232 |
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| 233 | fspec_keys = {'poly': 'order', 'chebyshev': 'order', 'cspline': 'npiece', 'sinusoid': 'nwave'}
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| 234 |
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[2984] | 235 | fspec_key = fspec_keys[dinfo['blfunc']]
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[2767] | 236 | if not blinfo.has_key(fspec_key):
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| 237 | raise ValueError("'"+fspec_key+"' is missing in blinfo.")
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| 238 |
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| 239 | clip_params_n = 0
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| 240 | for key in ['clipthresh', 'clipniter']:
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| 241 | if blinfo.has_key(key):
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| 242 | clip_params_n += 1
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| 243 | dinfo[key] = str(blinfo[key])
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| 244 |
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| 245 | if clip_params_n == 0:
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| 246 | dinfo['clipthresh'] = '0.0'
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| 247 | dinfo['clipniter'] = '0'
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| 248 | elif clip_params_n != 2:
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| 249 | raise ValueError("both 'clipthresh' and 'clipniter' must be given for n-sigma clipping.")
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| 250 |
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| 251 | lf_params_n = 0
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| 252 | for key in ['thresh', 'edge', 'chan_avg_limit']:
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| 253 | if blinfo.has_key(key):
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| 254 | lf_params_n += 1
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| 255 | val = blinfo[key]
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| 256 | if isinstance(val, list) or isinstance(val, tuple):
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| 257 | slval = []
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| 258 | for i in xrange(len(val)):
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| 259 | slval.append(str(val[i]))
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| 260 | sval = ",".join(slval)
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| 261 | else:
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| 262 | sval = str(val)
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| 263 | dinfo[key] = sval
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| 264 |
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| 265 | if lf_params_n == 3:
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| 266 | dinfo['use_linefinder'] = 'true'
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[2810] | 267 | elif lf_params_n == 0:
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[2767] | 268 | dinfo['use_linefinder'] = 'false'
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| 269 | dinfo['thresh'] = ''
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| 270 | dinfo['edge'] = ''
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| 271 | dinfo['chan_avg_limit'] = ''
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| 272 | else:
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| 273 | raise ValueError("all of 'thresh', 'edge' and 'chan_avg_limit' must be given to use linefinder.")
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| 274 |
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[2984] | 275 | slblinfo = [dinfo['row'], dinfo['blfunc'], dinfo[fspec_key], dinfo['masklist'], \
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[2767] | 276 | dinfo['clipthresh'], dinfo['clipniter'], \
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| 277 | dinfo['use_linefinder'], dinfo['thresh'], dinfo['edge'], dinfo['chan_avg_limit']]
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| 278 |
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| 279 | return ":".join(slblinfo)
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| 280 |
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| 281 | def parse_fitresult(sres):
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| 282 | """\
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| 283 | Parse the returned value of apply_bltable() or sub_baseline() and
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| 284 | extract row number, the best-fit coefficients and rms, then pack
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| 285 | them into a dictionary.
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| 286 | The input value is generated by Scantable::packFittingResults() and
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| 287 | formatted as 'row:coeff[0],coeff[1],..,coeff[n-1]:rms'.
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| 288 | """
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| 289 | res = []
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| 290 | for i in xrange(len(sres)):
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| 291 | (srow, scoeff, srms) = sres[i].split(":")
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| 292 | row = int(srow)
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| 293 | rms = float(srms)
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| 294 | lscoeff = scoeff.split(",")
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| 295 | coeff = []
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| 296 | for j in xrange(len(lscoeff)):
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| 297 | coeff.append(float(lscoeff[j]))
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| 298 | res.append({'row': row, 'coeff': coeff, 'rms': rms})
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| 299 |
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| 300 | return res
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| 301 |
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[2882] | 302 | def is_number(s):
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| 303 | s = s.strip()
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| 304 | res = True
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| 305 | try:
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| 306 | a = float(s)
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| 307 | res = True
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| 308 | except:
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| 309 | res = False
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| 310 | finally:
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| 311 | return res
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| 312 |
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| 313 | def is_frequency(s):
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| 314 | s = s.strip()
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| 315 | return (s[-2:].lower() == "hz")
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| 316 |
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[2884] | 317 | def get_freq_by_string(s1, s2):
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| 318 | if not (is_number(s1) and is_frequency(s2)):
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[2882] | 319 | raise RuntimeError("Invalid input string.")
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| 320 |
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| 321 | prefix_list = ["a", "f", "p", "n", "u", "m", ".", "k", "M", "G", "T", "P", "E"]
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| 322 | factor_list = [1e-18, 1e-15, 1e-12, 1e-9, 1e-6, 1e-3, 1.0, 1e+3, 1e+6, 1e+9, 1e+12, 1e+15, 1e+18]
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| 323 |
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[2884] | 324 | s1 = s1.strip()
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| 325 | s2 = s2.strip()
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[2882] | 326 |
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[2884] | 327 | prefix = s2[-3:-2]
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[2882] | 328 | if is_number(prefix):
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[2884] | 329 | res1 = float(s1)
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| 330 | res2 = float(s2[:-2])
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[2882] | 331 | else:
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[2884] | 332 | factor = factor_list[prefix_list.index(prefix)]
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| 333 | res1 = float(s1) * factor
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| 334 | res2 = float(s2[:-3]) * factor
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[2882] | 335 |
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[2884] | 336 | return (res1, res2)
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[2882] | 337 |
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| 338 | def is_velocity(s):
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| 339 | s = s.strip()
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| 340 | return (s[-3:].lower() == "m/s")
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| 341 |
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[2884] | 342 | def get_velocity_by_string(s1, s2):
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| 343 | if not (is_number(s1) and is_velocity(s2)):
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[2882] | 344 | raise RuntimeError("Invalid input string.")
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| 345 |
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[2884] | 346 | # note that the default velocity unit is km/s
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[2882] | 347 | prefix_list = [".", "k"]
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| 348 | factor_list = [1e-3, 1.0]
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| 349 |
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[2884] | 350 | s1 = s1.strip()
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| 351 | s2 = s2.strip()
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[2882] | 352 |
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[2884] | 353 | prefix = s2[-4:-3]
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| 354 | if is_number(prefix): # in case velocity unit m/s
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| 355 | res1 = float(s1) * 1e-3
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| 356 | res2 = float(s2[:-3]) * 1e-3
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[2882] | 357 | else:
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[2884] | 358 | factor = factor_list[prefix_list.index(prefix)]
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| 359 | res1 = float(s1) * factor
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| 360 | res2 = float(s2[:-4]) * factor
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[2882] | 361 |
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[2884] | 362 | return (res1, res2)
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[2882] | 363 |
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[2889] | 364 | def get_frequency_by_velocity(restfreq, vel, doppler):
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[2882] | 365 | # vel is in unit of km/s
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| 366 |
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| 367 | # speed of light
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| 368 | vel_c = 299792.458
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| 369 |
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| 370 | import math
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| 371 | r = vel / vel_c
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| 372 |
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[2889] | 373 | if doppler.lower() == 'radio':
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| 374 | return restfreq * (1.0 - r)
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| 375 | if doppler.lower() == 'optical':
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| 376 | return restfreq / (1.0 + r)
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| 377 | else:
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| 378 | return restfreq * math.sqrt((1.0 - r) / (1.0 + r))
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[2882] | 379 |
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[2891] | 380 | def get_restfreq_in_Hz(s_restfreq):
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| 381 | value = 0.0
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| 382 | unit = ""
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| 383 | s = s_restfreq.replace(" ","")
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[2889] | 384 |
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[2891] | 385 | for i in range(len(s))[::-1]:
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| 386 | if s[i].isalpha():
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| 387 | unit = s[i] + unit
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| 388 | else:
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| 389 | value = float(s[0:i+1])
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| 390 | break
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| 391 |
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| 392 | if (unit == "") or (unit.lower() == "hz"):
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| 393 | return value
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| 394 | elif (len(unit) == 3) and (unit[1:3].lower() == "hz"):
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| 395 | unitprefix = unit[0]
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| 396 | factor = 1.0
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| 397 |
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| 398 | prefix_list = ["a", "f", "p", "n", "u", "m", ".", "k", "M", "G", "T", "P", "E"]
|
---|
| 399 | factor_list = [1e-18, 1e-15, 1e-12, 1e-9, 1e-6, 1e-3, 1.0, 1e+3, 1e+6, 1e+9, 1e+12, 1e+15, 1e+18]
|
---|
| 400 | factor = factor_list[prefix_list.index(unitprefix)]
|
---|
| 401 | """
|
---|
| 402 | if (unitprefix == 'a'):
|
---|
| 403 | factor = 1.0e-18
|
---|
| 404 | elif (unitprefix == 'f'):
|
---|
| 405 | factor = 1.0e-15
|
---|
| 406 | elif (unitprefix == 'p'):
|
---|
| 407 | factor = 1.0e-12
|
---|
| 408 | elif (unitprefix == 'n'):
|
---|
| 409 | factor = 1.0e-9
|
---|
| 410 | elif (unitprefix == 'u'):
|
---|
| 411 | factor = 1.0e-6
|
---|
| 412 | elif (unitprefix == 'm'):
|
---|
| 413 | factor = 1.0e-3
|
---|
| 414 | elif (unitprefix == 'k'):
|
---|
| 415 | factor = 1.0e+3
|
---|
| 416 | elif (unitprefix == 'M'):
|
---|
| 417 | factor = 1.0e+6
|
---|
| 418 | elif (unitprefix == 'G'):
|
---|
| 419 | factor = 1.0e+9
|
---|
| 420 | elif (unitprefix == 'T'):
|
---|
| 421 | factor = 1.0e+12
|
---|
| 422 | elif (unitprefix == 'P'):
|
---|
| 423 | factor = 1.0e+15
|
---|
| 424 | elif (unitprefix == 'E'):
|
---|
| 425 | factor = 1.0e+18
|
---|
| 426 | """
|
---|
| 427 | return value*factor
|
---|
| 428 | else:
|
---|
| 429 | mesg = "wrong unit of restfreq."
|
---|
| 430 | raise Exception, mesg
|
---|
| 431 |
|
---|
| 432 | def normalise_restfreq(in_restfreq):
|
---|
| 433 | if isinstance(in_restfreq, float):
|
---|
| 434 | return in_restfreq
|
---|
| 435 | elif isinstance(in_restfreq, int) or isinstance(in_restfreq, long):
|
---|
| 436 | return float(in_restfreq)
|
---|
| 437 | elif isinstance(in_restfreq, str):
|
---|
| 438 | return get_restfreq_in_Hz(in_restfreq)
|
---|
| 439 | elif isinstance(in_restfreq, list) or isinstance(in_restfreq, numpy.ndarray):
|
---|
| 440 | if isinstance(in_restfreq, numpy.ndarray):
|
---|
| 441 | if len(in_restfreq.shape) > 1:
|
---|
| 442 | mesg = "given in numpy.ndarray, in_restfreq must be 1-D."
|
---|
| 443 | raise Exception, mesg
|
---|
| 444 |
|
---|
| 445 | res = []
|
---|
| 446 | for i in xrange(len(in_restfreq)):
|
---|
| 447 | elem = in_restfreq[i]
|
---|
| 448 | if isinstance(elem, float):
|
---|
| 449 | res.append(elem)
|
---|
| 450 | elif isinstance(elem, int) or isinstance(elem, long):
|
---|
| 451 | res.append(float(elem))
|
---|
| 452 | elif isinstance(elem, str):
|
---|
| 453 | res.append(get_restfreq_in_Hz(elem))
|
---|
| 454 | elif isinstance(elem, dict):
|
---|
| 455 | if isinstance(elem["value"], float):
|
---|
| 456 | res.append(elem)
|
---|
| 457 | elif isinstance(elem["value"], int):
|
---|
| 458 | dictelem = {}
|
---|
| 459 | dictelem["name"] = elem["name"]
|
---|
| 460 | dictelem["value"] = float(elem["value"])
|
---|
| 461 | res.append(dictelem)
|
---|
| 462 | elif isinstance(elem["value"], str):
|
---|
| 463 | dictelem = {}
|
---|
| 464 | dictelem["name"] = elem["name"]
|
---|
| 465 | dictelem["value"] = get_restfreq_in_Hz(elem["value"])
|
---|
| 466 | res.append(dictelem)
|
---|
| 467 | else:
|
---|
| 468 | mesg = "restfreq elements must be float, int, or string."
|
---|
| 469 | raise Exception, mesg
|
---|
| 470 | return res
|
---|
| 471 | else:
|
---|
| 472 | mesg = "wrong type of restfreq given."
|
---|
| 473 | raise Exception, mesg
|
---|
| 474 |
|
---|
| 475 | def set_restfreq(s, restfreq):
|
---|
| 476 | rfset = (restfreq != '') and (restfreq != [])
|
---|
| 477 | if rfset:
|
---|
| 478 | s.set_restfreqs(normalise_restfreq(restfreq))
|
---|
| 479 |
|
---|
[876] | 480 | class scantable(Scantable):
|
---|
[1846] | 481 | """\
|
---|
| 482 | The ASAP container for scans (single-dish data).
|
---|
[102] | 483 | """
|
---|
[1819] | 484 |
|
---|
[1862] | 485 | @asaplog_post_dec
|
---|
[2315] | 486 | def __init__(self, filename, average=None, unit=None, parallactify=None,
|
---|
| 487 | **args):
|
---|
[1846] | 488 | """\
|
---|
[102] | 489 | Create a scantable from a saved one or make a reference
|
---|
[1846] | 490 |
|
---|
[102] | 491 | Parameters:
|
---|
[1846] | 492 |
|
---|
| 493 | filename: the name of an asap table on disk
|
---|
| 494 | or
|
---|
| 495 | the name of a rpfits/sdfits/ms file
|
---|
| 496 | (integrations within scans are auto averaged
|
---|
| 497 | and the whole file is read) or
|
---|
| 498 | [advanced] a reference to an existing scantable
|
---|
| 499 |
|
---|
| 500 | average: average all integrations withinb a scan on read.
|
---|
| 501 | The default (True) is taken from .asaprc.
|
---|
| 502 |
|
---|
[484] | 503 | unit: brightness unit; must be consistent with K or Jy.
|
---|
[1846] | 504 | Over-rides the default selected by the filler
|
---|
| 505 | (input rpfits/sdfits/ms) or replaces the value
|
---|
| 506 | in existing scantables
|
---|
| 507 |
|
---|
[1920] | 508 | antenna: for MeasurementSet input data only:
|
---|
[2349] | 509 | Antenna selection. integer (id) or string
|
---|
| 510 | (name or id).
|
---|
[1846] | 511 |
|
---|
[2349] | 512 | parallactify: Indicate that the data had been parallactified.
|
---|
| 513 | Default (false) is taken from rc file.
|
---|
[1846] | 514 |
|
---|
[2754] | 515 | getpt: Whether to import direction from MS/POINTING
|
---|
| 516 | table properly or not.
|
---|
| 517 | This is effective only when filename is MS.
|
---|
| 518 | The default (True) is to import direction
|
---|
| 519 | from MS/POINTING.
|
---|
[710] | 520 | """
|
---|
[976] | 521 | if average is None:
|
---|
[710] | 522 | average = rcParams['scantable.autoaverage']
|
---|
[1593] | 523 | parallactify = parallactify or rcParams['scantable.parallactify']
|
---|
[1259] | 524 | varlist = vars()
|
---|
[876] | 525 | from asap._asap import stmath
|
---|
[1819] | 526 | self._math = stmath( rcParams['insitu'] )
|
---|
[876] | 527 | if isinstance(filename, Scantable):
|
---|
| 528 | Scantable.__init__(self, filename)
|
---|
[181] | 529 | else:
|
---|
[1697] | 530 | if isinstance(filename, str):
|
---|
[976] | 531 | filename = os.path.expandvars(filename)
|
---|
| 532 | filename = os.path.expanduser(filename)
|
---|
| 533 | if not os.path.exists(filename):
|
---|
| 534 | s = "File '%s' not found." % (filename)
|
---|
| 535 | raise IOError(s)
|
---|
[1697] | 536 | if is_scantable(filename):
|
---|
| 537 | ondisk = rcParams['scantable.storage'] == 'disk'
|
---|
| 538 | Scantable.__init__(self, filename, ondisk)
|
---|
| 539 | if unit is not None:
|
---|
| 540 | self.set_fluxunit(unit)
|
---|
[2008] | 541 | if average:
|
---|
| 542 | self._assign( self.average_time( scanav=True ) )
|
---|
[1819] | 543 | # do not reset to the default freqframe
|
---|
| 544 | #self.set_freqframe(rcParams['scantable.freqframe'])
|
---|
[1883] | 545 | elif is_ms(filename):
|
---|
[1916] | 546 | # Measurement Set
|
---|
| 547 | opts={'ms': {}}
|
---|
[2844] | 548 | mskeys=['getpt','antenna']
|
---|
[1916] | 549 | for key in mskeys:
|
---|
| 550 | if key in args.keys():
|
---|
| 551 | opts['ms'][key] = args[key]
|
---|
| 552 | self._fill([filename], unit, average, opts)
|
---|
[1893] | 553 | elif os.path.isfile(filename):
|
---|
[2761] | 554 | opts={'nro': {}}
|
---|
| 555 | nrokeys=['freqref']
|
---|
| 556 | for key in nrokeys:
|
---|
| 557 | if key in args.keys():
|
---|
| 558 | opts['nro'][key] = args[key]
|
---|
| 559 | self._fill([filename], unit, average, opts)
|
---|
[2350] | 560 | # only apply to new data not "copy constructor"
|
---|
| 561 | self.parallactify(parallactify)
|
---|
[1883] | 562 | else:
|
---|
[1819] | 563 | msg = "The given file '%s'is not a valid " \
|
---|
| 564 | "asap table." % (filename)
|
---|
[1859] | 565 | raise IOError(msg)
|
---|
[1118] | 566 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \
|
---|
[976] | 567 | and isinstance(filename[-1], str):
|
---|
[1916] | 568 | self._fill(filename, unit, average)
|
---|
[1586] | 569 | self.parallactify(parallactify)
|
---|
[1259] | 570 | self._add_history("scantable", varlist)
|
---|
[102] | 571 |
|
---|
[1862] | 572 | @asaplog_post_dec
|
---|
[876] | 573 | def save(self, name=None, format=None, overwrite=False):
|
---|
[1846] | 574 | """\
|
---|
[1280] | 575 | Store the scantable on disk. This can be an asap (aips++) Table,
|
---|
| 576 | SDFITS or MS2 format.
|
---|
[1846] | 577 |
|
---|
[116] | 578 | Parameters:
|
---|
[1846] | 579 |
|
---|
[2431] | 580 | name: the name of the outputfile. For format 'ASCII'
|
---|
[1093] | 581 | this is the root file name (data in 'name'.txt
|
---|
[497] | 582 | and header in 'name'_header.txt)
|
---|
[1855] | 583 |
|
---|
[116] | 584 | format: an optional file format. Default is ASAP.
|
---|
[1855] | 585 | Allowed are:
|
---|
| 586 |
|
---|
| 587 | * 'ASAP' (save as ASAP [aips++] Table),
|
---|
| 588 | * 'SDFITS' (save as SDFITS file)
|
---|
| 589 | * 'ASCII' (saves as ascii text file)
|
---|
| 590 | * 'MS2' (saves as an casacore MeasurementSet V2)
|
---|
[2315] | 591 | * 'FITS' (save as image FITS - not readable by
|
---|
| 592 | class)
|
---|
[1855] | 593 | * 'CLASS' (save as FITS readable by CLASS)
|
---|
| 594 |
|
---|
[411] | 595 | overwrite: If the file should be overwritten if it exists.
|
---|
[256] | 596 | The default False is to return with warning
|
---|
[411] | 597 | without writing the output. USE WITH CARE.
|
---|
[1855] | 598 |
|
---|
[1846] | 599 | Example::
|
---|
| 600 |
|
---|
[116] | 601 | scan.save('myscan.asap')
|
---|
[1118] | 602 | scan.save('myscan.sdfits', 'SDFITS')
|
---|
[1846] | 603 |
|
---|
[116] | 604 | """
|
---|
[411] | 605 | from os import path
|
---|
[1593] | 606 | format = format or rcParams['scantable.save']
|
---|
[256] | 607 | suffix = '.'+format.lower()
|
---|
[1118] | 608 | if name is None or name == "":
|
---|
[256] | 609 | name = 'scantable'+suffix
|
---|
[718] | 610 | msg = "No filename given. Using default name %s..." % name
|
---|
| 611 | asaplog.push(msg)
|
---|
[411] | 612 | name = path.expandvars(name)
|
---|
[256] | 613 | if path.isfile(name) or path.isdir(name):
|
---|
| 614 | if not overwrite:
|
---|
[718] | 615 | msg = "File %s exists." % name
|
---|
[1859] | 616 | raise IOError(msg)
|
---|
[451] | 617 | format2 = format.upper()
|
---|
| 618 | if format2 == 'ASAP':
|
---|
[116] | 619 | self._save(name)
|
---|
[2029] | 620 | elif format2 == 'MS2':
|
---|
| 621 | msopt = {'ms': {'overwrite': overwrite } }
|
---|
| 622 | from asap._asap import mswriter
|
---|
| 623 | writer = mswriter( self )
|
---|
| 624 | writer.write( name, msopt )
|
---|
[116] | 625 | else:
|
---|
[989] | 626 | from asap._asap import stwriter as stw
|
---|
[1118] | 627 | writer = stw(format2)
|
---|
| 628 | writer.write(self, name)
|
---|
[116] | 629 | return
|
---|
| 630 |
|
---|
[102] | 631 | def copy(self):
|
---|
[1846] | 632 | """Return a copy of this scantable.
|
---|
| 633 |
|
---|
| 634 | *Note*:
|
---|
| 635 |
|
---|
[1348] | 636 | This makes a full (deep) copy. scan2 = scan1 makes a reference.
|
---|
[1846] | 637 |
|
---|
| 638 | Example::
|
---|
| 639 |
|
---|
[102] | 640 | copiedscan = scan.copy()
|
---|
[1846] | 641 |
|
---|
[102] | 642 | """
|
---|
[876] | 643 | sd = scantable(Scantable._copy(self))
|
---|
[113] | 644 | return sd
|
---|
| 645 |
|
---|
[1093] | 646 | def drop_scan(self, scanid=None):
|
---|
[1846] | 647 | """\
|
---|
[1093] | 648 | Return a new scantable where the specified scan number(s) has(have)
|
---|
| 649 | been dropped.
|
---|
[1846] | 650 |
|
---|
[1093] | 651 | Parameters:
|
---|
[1846] | 652 |
|
---|
[1093] | 653 | scanid: a (list of) scan number(s)
|
---|
[1846] | 654 |
|
---|
[1093] | 655 | """
|
---|
| 656 | from asap import _is_sequence_or_number as _is_valid
|
---|
| 657 | from asap import _to_list
|
---|
| 658 | from asap import unique
|
---|
| 659 | if not _is_valid(scanid):
|
---|
[2315] | 660 | raise RuntimeError( 'Please specify a scanno to drop from the'
|
---|
| 661 | ' scantable' )
|
---|
[1859] | 662 | scanid = _to_list(scanid)
|
---|
| 663 | allscans = unique([ self.getscan(i) for i in range(self.nrow())])
|
---|
| 664 | for sid in scanid: allscans.remove(sid)
|
---|
| 665 | if len(allscans) == 0:
|
---|
| 666 | raise ValueError("Can't remove all scans")
|
---|
| 667 | sel = selector(scans=allscans)
|
---|
| 668 | return self._select_copy(sel)
|
---|
[1093] | 669 |
|
---|
[1594] | 670 | def _select_copy(self, selection):
|
---|
| 671 | orig = self.get_selection()
|
---|
| 672 | self.set_selection(orig+selection)
|
---|
| 673 | cp = self.copy()
|
---|
| 674 | self.set_selection(orig)
|
---|
| 675 | return cp
|
---|
| 676 |
|
---|
[102] | 677 | def get_scan(self, scanid=None):
|
---|
[1855] | 678 | """\
|
---|
[102] | 679 | Return a specific scan (by scanno) or collection of scans (by
|
---|
| 680 | source name) in a new scantable.
|
---|
[1846] | 681 |
|
---|
| 682 | *Note*:
|
---|
| 683 |
|
---|
[1348] | 684 | See scantable.drop_scan() for the inverse operation.
|
---|
[1846] | 685 |
|
---|
[102] | 686 | Parameters:
|
---|
[1846] | 687 |
|
---|
[513] | 688 | scanid: a (list of) scanno or a source name, unix-style
|
---|
| 689 | patterns are accepted for source name matching, e.g.
|
---|
| 690 | '*_R' gets all 'ref scans
|
---|
[1846] | 691 |
|
---|
| 692 | Example::
|
---|
| 693 |
|
---|
[513] | 694 | # get all scans containing the source '323p459'
|
---|
| 695 | newscan = scan.get_scan('323p459')
|
---|
| 696 | # get all 'off' scans
|
---|
| 697 | refscans = scan.get_scan('*_R')
|
---|
| 698 | # get a susbset of scans by scanno (as listed in scan.summary())
|
---|
[1118] | 699 | newscan = scan.get_scan([0, 2, 7, 10])
|
---|
[1846] | 700 |
|
---|
[102] | 701 | """
|
---|
| 702 | if scanid is None:
|
---|
[1859] | 703 | raise RuntimeError( 'Please specify a scan no or name to '
|
---|
| 704 | 'retrieve from the scantable' )
|
---|
[102] | 705 | try:
|
---|
[946] | 706 | bsel = self.get_selection()
|
---|
| 707 | sel = selector()
|
---|
[102] | 708 | if type(scanid) is str:
|
---|
[946] | 709 | sel.set_name(scanid)
|
---|
[1594] | 710 | return self._select_copy(sel)
|
---|
[102] | 711 | elif type(scanid) is int:
|
---|
[946] | 712 | sel.set_scans([scanid])
|
---|
[1594] | 713 | return self._select_copy(sel)
|
---|
[381] | 714 | elif type(scanid) is list:
|
---|
[946] | 715 | sel.set_scans(scanid)
|
---|
[1594] | 716 | return self._select_copy(sel)
|
---|
[381] | 717 | else:
|
---|
[718] | 718 | msg = "Illegal scanid type, use 'int' or 'list' if ints."
|
---|
[1859] | 719 | raise TypeError(msg)
|
---|
[102] | 720 | except RuntimeError:
|
---|
[1859] | 721 | raise
|
---|
[102] | 722 |
|
---|
| 723 | def __str__(self):
|
---|
[2315] | 724 | tempFile = tempfile.NamedTemporaryFile()
|
---|
| 725 | Scantable._summary(self, tempFile.name)
|
---|
| 726 | tempFile.seek(0)
|
---|
| 727 | asaplog.clear()
|
---|
| 728 | return tempFile.file.read()
|
---|
[102] | 729 |
|
---|
[2315] | 730 | @asaplog_post_dec
|
---|
[976] | 731 | def summary(self, filename=None):
|
---|
[1846] | 732 | """\
|
---|
[102] | 733 | Print a summary of the contents of this scantable.
|
---|
[1846] | 734 |
|
---|
[102] | 735 | Parameters:
|
---|
[1846] | 736 |
|
---|
[1931] | 737 | filename: the name of a file to write the putput to
|
---|
[102] | 738 | Default - no file output
|
---|
[1846] | 739 |
|
---|
[102] | 740 | """
|
---|
| 741 | if filename is not None:
|
---|
[256] | 742 | if filename is "":
|
---|
| 743 | filename = 'scantable_summary.txt'
|
---|
[415] | 744 | from os.path import expandvars, isdir
|
---|
[411] | 745 | filename = expandvars(filename)
|
---|
[2286] | 746 | if isdir(filename):
|
---|
[718] | 747 | msg = "Illegal file name '%s'." % (filename)
|
---|
[1859] | 748 | raise IOError(msg)
|
---|
[2286] | 749 | else:
|
---|
| 750 | filename = ""
|
---|
| 751 | Scantable._summary(self, filename)
|
---|
[710] | 752 |
|
---|
[1512] | 753 | def get_spectrum(self, rowno):
|
---|
[1471] | 754 | """Return the spectrum for the current row in the scantable as a list.
|
---|
[1846] | 755 |
|
---|
[1471] | 756 | Parameters:
|
---|
[1846] | 757 |
|
---|
[1573] | 758 | rowno: the row number to retrieve the spectrum from
|
---|
[1846] | 759 |
|
---|
[1471] | 760 | """
|
---|
| 761 | return self._getspectrum(rowno)
|
---|
[946] | 762 |
|
---|
[1471] | 763 | def get_mask(self, rowno):
|
---|
| 764 | """Return the mask for the current row in the scantable as a list.
|
---|
[1846] | 765 |
|
---|
[1471] | 766 | Parameters:
|
---|
[1846] | 767 |
|
---|
[1573] | 768 | rowno: the row number to retrieve the mask from
|
---|
[1846] | 769 |
|
---|
[1471] | 770 | """
|
---|
| 771 | return self._getmask(rowno)
|
---|
| 772 |
|
---|
| 773 | def set_spectrum(self, spec, rowno):
|
---|
[1938] | 774 | """Set the spectrum for the current row in the scantable.
|
---|
[1846] | 775 |
|
---|
[1471] | 776 | Parameters:
|
---|
[1846] | 777 |
|
---|
[1855] | 778 | spec: the new spectrum
|
---|
[1846] | 779 |
|
---|
[1855] | 780 | rowno: the row number to set the spectrum for
|
---|
| 781 |
|
---|
[1471] | 782 | """
|
---|
[2348] | 783 | assert(len(spec) == self.nchan(self.getif(rowno)))
|
---|
[1471] | 784 | return self._setspectrum(spec, rowno)
|
---|
| 785 |
|
---|
[1600] | 786 | def get_coordinate(self, rowno):
|
---|
| 787 | """Return the (spectral) coordinate for a a given 'rowno'.
|
---|
[1846] | 788 |
|
---|
| 789 | *Note*:
|
---|
| 790 |
|
---|
[1600] | 791 | * This coordinate is only valid until a scantable method modifies
|
---|
| 792 | the frequency axis.
|
---|
| 793 | * This coordinate does contain the original frequency set-up
|
---|
| 794 | NOT the new frame. The conversions however are done using the user
|
---|
| 795 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate,
|
---|
| 796 | use scantable.freq_align first. Without it there is no closure,
|
---|
[1846] | 797 | i.e.::
|
---|
[1600] | 798 |
|
---|
[1846] | 799 | c = myscan.get_coordinate(0)
|
---|
| 800 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value()
|
---|
| 801 |
|
---|
[1600] | 802 | Parameters:
|
---|
[1846] | 803 |
|
---|
[1600] | 804 | rowno: the row number for the spectral coordinate
|
---|
| 805 |
|
---|
| 806 | """
|
---|
| 807 | return coordinate(Scantable.get_coordinate(self, rowno))
|
---|
| 808 |
|
---|
[946] | 809 | def get_selection(self):
|
---|
[1846] | 810 | """\
|
---|
[1005] | 811 | Get the selection object currently set on this scantable.
|
---|
[1846] | 812 |
|
---|
| 813 | Example::
|
---|
| 814 |
|
---|
[1005] | 815 | sel = scan.get_selection()
|
---|
| 816 | sel.set_ifs(0) # select IF 0
|
---|
| 817 | scan.set_selection(sel) # apply modified selection
|
---|
[1846] | 818 |
|
---|
[946] | 819 | """
|
---|
| 820 | return selector(self._getselection())
|
---|
| 821 |
|
---|
[1576] | 822 | def set_selection(self, selection=None, **kw):
|
---|
[1846] | 823 | """\
|
---|
[1005] | 824 | Select a subset of the data. All following operations on this scantable
|
---|
| 825 | are only applied to thi selection.
|
---|
[1846] | 826 |
|
---|
[1005] | 827 | Parameters:
|
---|
[1697] | 828 |
|
---|
[1846] | 829 | selection: a selector object (default unset the selection), or
|
---|
[2431] | 830 | any combination of 'pols', 'ifs', 'beams', 'scans',
|
---|
| 831 | 'cycles', 'name', 'query'
|
---|
[1697] | 832 |
|
---|
[1846] | 833 | Examples::
|
---|
[1697] | 834 |
|
---|
[1005] | 835 | sel = selector() # create a selection object
|
---|
[1118] | 836 | self.set_scans([0, 3]) # select SCANNO 0 and 3
|
---|
[1005] | 837 | scan.set_selection(sel) # set the selection
|
---|
| 838 | scan.summary() # will only print summary of scanno 0 an 3
|
---|
| 839 | scan.set_selection() # unset the selection
|
---|
[1697] | 840 | # or the equivalent
|
---|
| 841 | scan.set_selection(scans=[0,3])
|
---|
| 842 | scan.summary() # will only print summary of scanno 0 an 3
|
---|
| 843 | scan.set_selection() # unset the selection
|
---|
[1846] | 844 |
|
---|
[946] | 845 | """
|
---|
[1576] | 846 | if selection is None:
|
---|
| 847 | # reset
|
---|
| 848 | if len(kw) == 0:
|
---|
| 849 | selection = selector()
|
---|
| 850 | else:
|
---|
| 851 | # try keywords
|
---|
| 852 | for k in kw:
|
---|
| 853 | if k not in selector.fields:
|
---|
[2320] | 854 | raise KeyError("Invalid selection key '%s', "
|
---|
| 855 | "valid keys are %s" % (k,
|
---|
| 856 | selector.fields))
|
---|
[1576] | 857 | selection = selector(**kw)
|
---|
[946] | 858 | self._setselection(selection)
|
---|
| 859 |
|
---|
[1819] | 860 | def get_row(self, row=0, insitu=None):
|
---|
[1846] | 861 | """\
|
---|
[1819] | 862 | Select a row in the scantable.
|
---|
| 863 | Return a scantable with single row.
|
---|
[1846] | 864 |
|
---|
[1819] | 865 | Parameters:
|
---|
[1846] | 866 |
|
---|
| 867 | row: row no of integration, default is 0.
|
---|
| 868 | insitu: if False a new scantable is returned. Otherwise, the
|
---|
| 869 | scaling is done in-situ. The default is taken from .asaprc
|
---|
| 870 | (False)
|
---|
| 871 |
|
---|
[1819] | 872 | """
|
---|
[2349] | 873 | if insitu is None:
|
---|
| 874 | insitu = rcParams['insitu']
|
---|
[1819] | 875 | if not insitu:
|
---|
| 876 | workscan = self.copy()
|
---|
| 877 | else:
|
---|
| 878 | workscan = self
|
---|
| 879 | # Select a row
|
---|
[2349] | 880 | sel = selector()
|
---|
[1992] | 881 | sel.set_rows([row])
|
---|
[1819] | 882 | workscan.set_selection(sel)
|
---|
| 883 | if not workscan.nrow() == 1:
|
---|
[2349] | 884 | msg = "Could not identify single row. %d rows selected." \
|
---|
| 885 | % (workscan.nrow())
|
---|
[1819] | 886 | raise RuntimeError(msg)
|
---|
| 887 | if insitu:
|
---|
| 888 | self._assign(workscan)
|
---|
| 889 | else:
|
---|
| 890 | return workscan
|
---|
| 891 |
|
---|
[1862] | 892 | @asaplog_post_dec
|
---|
[2957] | 893 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None, skip_flaggedrow=False):
|
---|
[1846] | 894 | """\
|
---|
[135] | 895 | Determine the specified statistic of the current beam/if/pol
|
---|
[102] | 896 | Takes a 'mask' as an optional parameter to specify which
|
---|
| 897 | channels should be excluded.
|
---|
[1846] | 898 |
|
---|
[102] | 899 | Parameters:
|
---|
[1846] | 900 |
|
---|
[1819] | 901 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum',
|
---|
| 902 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median'
|
---|
[1855] | 903 |
|
---|
[135] | 904 | mask: an optional mask specifying where the statistic
|
---|
[102] | 905 | should be determined.
|
---|
[1855] | 906 |
|
---|
[1819] | 907 | form: format string to print statistic values
|
---|
[1846] | 908 |
|
---|
[1907] | 909 | row: row number of spectrum to process.
|
---|
| 910 | (default is None: for all rows)
|
---|
[1846] | 911 |
|
---|
[2957] | 912 | skip_flaggedrow: if True, skip outputting text for flagged
|
---|
| 913 | spectra. default is False.
|
---|
| 914 |
|
---|
[1907] | 915 | Example:
|
---|
[113] | 916 | scan.set_unit('channel')
|
---|
[1118] | 917 | msk = scan.create_mask([100, 200], [500, 600])
|
---|
[135] | 918 | scan.stats(stat='mean', mask=m)
|
---|
[1846] | 919 |
|
---|
[102] | 920 | """
|
---|
[1593] | 921 | mask = mask or []
|
---|
[876] | 922 | if not self._check_ifs():
|
---|
[1118] | 923 | raise ValueError("Cannot apply mask as the IFs have different "
|
---|
| 924 | "number of channels. Please use setselection() "
|
---|
| 925 | "to select individual IFs")
|
---|
[1819] | 926 | getchan = False
|
---|
| 927 | if stat.lower().startswith('min') or stat.lower().startswith('max'):
|
---|
| 928 | chan = self._math._minmaxchan(self, mask, stat)
|
---|
| 929 | getchan = True
|
---|
| 930 | statvals = []
|
---|
[2957] | 931 |
|
---|
| 932 | rtnabc = False
|
---|
| 933 | if stat.lower().endswith('_abc'):
|
---|
| 934 | rtnabc = True
|
---|
| 935 | else:
|
---|
[1907] | 936 | if row == None:
|
---|
| 937 | statvals = self._math._stats(self, mask, stat)
|
---|
| 938 | else:
|
---|
| 939 | statvals = self._math._statsrow(self, mask, stat, int(row))
|
---|
[256] | 940 |
|
---|
[1819] | 941 | #def cb(i):
|
---|
| 942 | # return statvals[i]
|
---|
[256] | 943 |
|
---|
[1819] | 944 | #return self._row_callback(cb, stat)
|
---|
[102] | 945 |
|
---|
[1819] | 946 | label=stat
|
---|
| 947 | #callback=cb
|
---|
| 948 | out = ""
|
---|
| 949 | #outvec = []
|
---|
| 950 | sep = '-'*50
|
---|
[1907] | 951 |
|
---|
| 952 | if row == None:
|
---|
| 953 | rows = xrange(self.nrow())
|
---|
| 954 | elif isinstance(row, int):
|
---|
| 955 | rows = [ row ]
|
---|
| 956 |
|
---|
| 957 | for i in rows:
|
---|
[1819] | 958 | refstr = ''
|
---|
| 959 | statunit= ''
|
---|
| 960 | if getchan:
|
---|
| 961 | qx, qy = self.chan2data(rowno=i, chan=chan[i])
|
---|
| 962 | if rtnabc:
|
---|
| 963 | statvals.append(qx['value'])
|
---|
| 964 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])'
|
---|
| 965 | statunit= '['+qx['unit']+']'
|
---|
| 966 | else:
|
---|
| 967 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])'
|
---|
| 968 |
|
---|
[2973] | 969 | if skip_flaggedrow and self._getflagrow(i):
|
---|
| 970 | statvals[i] = None
|
---|
| 971 | continue
|
---|
[2957] | 972 |
|
---|
[1819] | 973 | tm = self._gettime(i)
|
---|
| 974 | src = self._getsourcename(i)
|
---|
| 975 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src)
|
---|
| 976 | out += 'Time[%s]:\n' % (tm)
|
---|
[1907] | 977 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i))
|
---|
| 978 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i))
|
---|
| 979 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i))
|
---|
[1819] | 980 | #outvec.append(callback(i))
|
---|
[1907] | 981 | if len(rows) > 1:
|
---|
| 982 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n'
|
---|
| 983 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n'
|
---|
| 984 | else:
|
---|
| 985 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n'
|
---|
| 986 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n'
|
---|
[1819] | 987 | out += sep+"\n"
|
---|
| 988 |
|
---|
[1859] | 989 | import os
|
---|
| 990 | if os.environ.has_key( 'USER' ):
|
---|
| 991 | usr = os.environ['USER']
|
---|
| 992 | else:
|
---|
| 993 | import commands
|
---|
| 994 | usr = commands.getoutput( 'whoami' )
|
---|
| 995 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats'
|
---|
| 996 | f = open(tmpfile,'w')
|
---|
| 997 | print >> f, sep
|
---|
| 998 | print >> f, ' %s %s' % (label, statunit)
|
---|
| 999 | print >> f, sep
|
---|
| 1000 | print >> f, out
|
---|
| 1001 | f.close()
|
---|
| 1002 | f = open(tmpfile,'r')
|
---|
| 1003 | x = f.readlines()
|
---|
| 1004 | f.close()
|
---|
| 1005 | asaplog.push(''.join(x), False)
|
---|
| 1006 |
|
---|
[1819] | 1007 | return statvals
|
---|
| 1008 |
|
---|
| 1009 | def chan2data(self, rowno=0, chan=0):
|
---|
[1846] | 1010 | """\
|
---|
[1819] | 1011 | Returns channel/frequency/velocity and spectral value
|
---|
| 1012 | at an arbitrary row and channel in the scantable.
|
---|
[1846] | 1013 |
|
---|
[1819] | 1014 | Parameters:
|
---|
[1846] | 1015 |
|
---|
[1819] | 1016 | rowno: a row number in the scantable. Default is the
|
---|
| 1017 | first row, i.e. rowno=0
|
---|
[1855] | 1018 |
|
---|
[1819] | 1019 | chan: a channel in the scantable. Default is the first
|
---|
| 1020 | channel, i.e. pos=0
|
---|
[1846] | 1021 |
|
---|
[1819] | 1022 | """
|
---|
| 1023 | if isinstance(rowno, int) and isinstance(chan, int):
|
---|
| 1024 | qx = {'unit': self.get_unit(),
|
---|
| 1025 | 'value': self._getabcissa(rowno)[chan]}
|
---|
| 1026 | qy = {'unit': self.get_fluxunit(),
|
---|
| 1027 | 'value': self._getspectrum(rowno)[chan]}
|
---|
| 1028 | return qx, qy
|
---|
| 1029 |
|
---|
[1118] | 1030 | def stddev(self, mask=None):
|
---|
[1846] | 1031 | """\
|
---|
[135] | 1032 | Determine the standard deviation of the current beam/if/pol
|
---|
| 1033 | Takes a 'mask' as an optional parameter to specify which
|
---|
| 1034 | channels should be excluded.
|
---|
[1846] | 1035 |
|
---|
[135] | 1036 | Parameters:
|
---|
[1846] | 1037 |
|
---|
[135] | 1038 | mask: an optional mask specifying where the standard
|
---|
| 1039 | deviation should be determined.
|
---|
| 1040 |
|
---|
[1846] | 1041 | Example::
|
---|
| 1042 |
|
---|
[135] | 1043 | scan.set_unit('channel')
|
---|
[1118] | 1044 | msk = scan.create_mask([100, 200], [500, 600])
|
---|
[135] | 1045 | scan.stddev(mask=m)
|
---|
[1846] | 1046 |
|
---|
[135] | 1047 | """
|
---|
[1118] | 1048 | return self.stats(stat='stddev', mask=mask);
|
---|
[135] | 1049 |
|
---|
[1003] | 1050 |
|
---|
[1259] | 1051 | def get_column_names(self):
|
---|
[1846] | 1052 | """\
|
---|
[1003] | 1053 | Return a list of column names, which can be used for selection.
|
---|
| 1054 | """
|
---|
[1259] | 1055 | return list(Scantable.get_column_names(self))
|
---|
[1003] | 1056 |
|
---|
[1730] | 1057 | def get_tsys(self, row=-1):
|
---|
[1846] | 1058 | """\
|
---|
[113] | 1059 | Return the System temperatures.
|
---|
[1846] | 1060 |
|
---|
| 1061 | Parameters:
|
---|
| 1062 |
|
---|
| 1063 | row: the rowno to get the information for. (default all rows)
|
---|
| 1064 |
|
---|
[113] | 1065 | Returns:
|
---|
[1846] | 1066 |
|
---|
[876] | 1067 | a list of Tsys values for the current selection
|
---|
[1846] | 1068 |
|
---|
[113] | 1069 | """
|
---|
[1730] | 1070 | if row > -1:
|
---|
| 1071 | return self._get_column(self._gettsys, row)
|
---|
[876] | 1072 | return self._row_callback(self._gettsys, "Tsys")
|
---|
[256] | 1073 |
|
---|
[2406] | 1074 | def get_tsysspectrum(self, row=-1):
|
---|
| 1075 | """\
|
---|
| 1076 | Return the channel dependent system temperatures.
|
---|
[1730] | 1077 |
|
---|
[2406] | 1078 | Parameters:
|
---|
| 1079 |
|
---|
| 1080 | row: the rowno to get the information for. (default all rows)
|
---|
| 1081 |
|
---|
| 1082 | Returns:
|
---|
| 1083 |
|
---|
| 1084 | a list of Tsys values for the current selection
|
---|
| 1085 |
|
---|
| 1086 | """
|
---|
| 1087 | return self._get_column( self._gettsysspectrum, row )
|
---|
| 1088 |
|
---|
[2791] | 1089 | def set_tsys(self, values, row=-1):
|
---|
| 1090 | """\
|
---|
| 1091 | Set the Tsys value(s) of the given 'row' or the whole scantable
|
---|
| 1092 | (selection).
|
---|
| 1093 |
|
---|
| 1094 | Parameters:
|
---|
| 1095 |
|
---|
| 1096 | values: a scalar or list (if Tsys is a vector) of Tsys value(s)
|
---|
| 1097 | row: the row number to apply Tsys values to.
|
---|
| 1098 | (default all rows)
|
---|
| 1099 |
|
---|
| 1100 | """
|
---|
| 1101 |
|
---|
| 1102 | if not hasattr(values, "__len__"):
|
---|
| 1103 | values = [values]
|
---|
| 1104 | self._settsys(values, row)
|
---|
| 1105 |
|
---|
[1730] | 1106 | def get_weather(self, row=-1):
|
---|
[1846] | 1107 | """\
|
---|
[2930] | 1108 | Return the weather information.
|
---|
[1846] | 1109 |
|
---|
| 1110 | Parameters:
|
---|
| 1111 |
|
---|
| 1112 | row: the rowno to get the information for. (default all rows)
|
---|
| 1113 |
|
---|
| 1114 | Returns:
|
---|
| 1115 |
|
---|
| 1116 | a dict or list of of dicts of values for the current selection
|
---|
| 1117 |
|
---|
| 1118 | """
|
---|
[2930] | 1119 | if row >= len(self):
|
---|
| 1120 | raise IndexError("row out of range")
|
---|
[1730] | 1121 | values = self._get_column(self._get_weather, row)
|
---|
| 1122 | if row > -1:
|
---|
| 1123 | return {'temperature': values[0],
|
---|
| 1124 | 'pressure': values[1], 'humidity' : values[2],
|
---|
| 1125 | 'windspeed' : values[3], 'windaz' : values[4]
|
---|
| 1126 | }
|
---|
| 1127 | else:
|
---|
| 1128 | out = []
|
---|
| 1129 | for r in values:
|
---|
| 1130 | out.append({'temperature': r[0],
|
---|
| 1131 | 'pressure': r[1], 'humidity' : r[2],
|
---|
| 1132 | 'windspeed' : r[3], 'windaz' : r[4]
|
---|
| 1133 | })
|
---|
| 1134 | return out
|
---|
| 1135 |
|
---|
[876] | 1136 | def _row_callback(self, callback, label):
|
---|
| 1137 | out = ""
|
---|
[1118] | 1138 | outvec = []
|
---|
[1590] | 1139 | sep = '-'*50
|
---|
[876] | 1140 | for i in range(self.nrow()):
|
---|
| 1141 | tm = self._gettime(i)
|
---|
| 1142 | src = self._getsourcename(i)
|
---|
[1590] | 1143 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src)
|
---|
[876] | 1144 | out += 'Time[%s]:\n' % (tm)
|
---|
[1590] | 1145 | if self.nbeam(-1) > 1:
|
---|
| 1146 | out += ' Beam[%d] ' % (self.getbeam(i))
|
---|
| 1147 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i))
|
---|
| 1148 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i))
|
---|
[876] | 1149 | outvec.append(callback(i))
|
---|
| 1150 | out += '= %3.3f\n' % (outvec[i])
|
---|
[1590] | 1151 | out += sep+'\n'
|
---|
[1859] | 1152 |
|
---|
| 1153 | asaplog.push(sep)
|
---|
| 1154 | asaplog.push(" %s" % (label))
|
---|
| 1155 | asaplog.push(sep)
|
---|
| 1156 | asaplog.push(out)
|
---|
[1861] | 1157 | asaplog.post()
|
---|
[1175] | 1158 | return outvec
|
---|
[256] | 1159 |
|
---|
[1947] | 1160 | def _get_column(self, callback, row=-1, *args):
|
---|
[1070] | 1161 | """
|
---|
| 1162 | """
|
---|
| 1163 | if row == -1:
|
---|
[1947] | 1164 | return [callback(i, *args) for i in range(self.nrow())]
|
---|
[1070] | 1165 | else:
|
---|
[1819] | 1166 | if 0 <= row < self.nrow():
|
---|
[1947] | 1167 | return callback(row, *args)
|
---|
[256] | 1168 |
|
---|
[1070] | 1169 |
|
---|
[1948] | 1170 | def get_time(self, row=-1, asdatetime=False, prec=-1):
|
---|
[1846] | 1171 | """\
|
---|
[113] | 1172 | Get a list of time stamps for the observations.
|
---|
[1938] | 1173 | Return a datetime object or a string (default) for each
|
---|
| 1174 | integration time stamp in the scantable.
|
---|
[1846] | 1175 |
|
---|
[113] | 1176 | Parameters:
|
---|
[1846] | 1177 |
|
---|
[1348] | 1178 | row: row no of integration. Default -1 return all rows
|
---|
[1855] | 1179 |
|
---|
[1348] | 1180 | asdatetime: return values as datetime objects rather than strings
|
---|
[1846] | 1181 |
|
---|
[2349] | 1182 | prec: number of digits shown. Default -1 to automatic
|
---|
| 1183 | calculation.
|
---|
[1948] | 1184 | Note this number is equals to the digits of MVTime,
|
---|
| 1185 | i.e., 0<prec<3: dates with hh:: only,
|
---|
| 1186 | <5: with hh:mm:, <7 or 0: with hh:mm:ss,
|
---|
[1947] | 1187 | and 6> : with hh:mm:ss.tt... (prec-6 t's added)
|
---|
| 1188 |
|
---|
[113] | 1189 | """
|
---|
[1175] | 1190 | from datetime import datetime
|
---|
[1948] | 1191 | if prec < 0:
|
---|
| 1192 | # automagically set necessary precision +1
|
---|
[2349] | 1193 | prec = 7 - \
|
---|
| 1194 | numpy.floor(numpy.log10(numpy.min(self.get_inttime(row))))
|
---|
[1948] | 1195 | prec = max(6, int(prec))
|
---|
| 1196 | else:
|
---|
| 1197 | prec = max(0, prec)
|
---|
| 1198 | if asdatetime:
|
---|
| 1199 | #precision can be 1 millisecond at max
|
---|
| 1200 | prec = min(12, prec)
|
---|
| 1201 |
|
---|
[1947] | 1202 | times = self._get_column(self._gettime, row, prec)
|
---|
[1348] | 1203 | if not asdatetime:
|
---|
[1392] | 1204 | return times
|
---|
[1947] | 1205 | format = "%Y/%m/%d/%H:%M:%S.%f"
|
---|
| 1206 | if prec < 7:
|
---|
| 1207 | nsub = 1 + (((6-prec)/2) % 3)
|
---|
| 1208 | substr = [".%f","%S","%M"]
|
---|
| 1209 | for i in range(nsub):
|
---|
| 1210 | format = format.replace(substr[i],"")
|
---|
[1175] | 1211 | if isinstance(times, list):
|
---|
[1947] | 1212 | return [datetime.strptime(i, format) for i in times]
|
---|
[1175] | 1213 | else:
|
---|
[1947] | 1214 | return datetime.strptime(times, format)
|
---|
[102] | 1215 |
|
---|
[1348] | 1216 |
|
---|
| 1217 | def get_inttime(self, row=-1):
|
---|
[1846] | 1218 | """\
|
---|
[1348] | 1219 | Get a list of integration times for the observations.
|
---|
| 1220 | Return a time in seconds for each integration in the scantable.
|
---|
[1846] | 1221 |
|
---|
[1348] | 1222 | Parameters:
|
---|
[1846] | 1223 |
|
---|
[1348] | 1224 | row: row no of integration. Default -1 return all rows.
|
---|
[1846] | 1225 |
|
---|
[1348] | 1226 | """
|
---|
[1573] | 1227 | return self._get_column(self._getinttime, row)
|
---|
[1348] | 1228 |
|
---|
[1573] | 1229 |
|
---|
[714] | 1230 | def get_sourcename(self, row=-1):
|
---|
[1846] | 1231 | """\
|
---|
[794] | 1232 | Get a list source names for the observations.
|
---|
[714] | 1233 | Return a string for each integration in the scantable.
|
---|
| 1234 | Parameters:
|
---|
[1846] | 1235 |
|
---|
[1348] | 1236 | row: row no of integration. Default -1 return all rows.
|
---|
[1846] | 1237 |
|
---|
[714] | 1238 | """
|
---|
[1070] | 1239 | return self._get_column(self._getsourcename, row)
|
---|
[714] | 1240 |
|
---|
[794] | 1241 | def get_elevation(self, row=-1):
|
---|
[1846] | 1242 | """\
|
---|
[794] | 1243 | Get a list of elevations for the observations.
|
---|
| 1244 | Return a float for each integration in the scantable.
|
---|
[1846] | 1245 |
|
---|
[794] | 1246 | Parameters:
|
---|
[1846] | 1247 |
|
---|
[1348] | 1248 | row: row no of integration. Default -1 return all rows.
|
---|
[1846] | 1249 |
|
---|
[794] | 1250 | """
|
---|
[1070] | 1251 | return self._get_column(self._getelevation, row)
|
---|
[794] | 1252 |
|
---|
| 1253 | def get_azimuth(self, row=-1):
|
---|
[1846] | 1254 | """\
|
---|
[794] | 1255 | Get a list of azimuths for the observations.
|
---|
| 1256 | Return a float for each integration in the scantable.
|
---|
[1846] | 1257 |
|
---|
[794] | 1258 | Parameters:
|
---|
[1348] | 1259 | row: row no of integration. Default -1 return all rows.
|
---|
[1846] | 1260 |
|
---|
[794] | 1261 | """
|
---|
[1070] | 1262 | return self._get_column(self._getazimuth, row)
|
---|
[794] | 1263 |
|
---|
| 1264 | def get_parangle(self, row=-1):
|
---|
[1846] | 1265 | """\
|
---|
[794] | 1266 | Get a list of parallactic angles for the observations.
|
---|
| 1267 | Return a float for each integration in the scantable.
|
---|
[1846] | 1268 |
|
---|
[794] | 1269 | Parameters:
|
---|
[1846] | 1270 |
|
---|
[1348] | 1271 | row: row no of integration. Default -1 return all rows.
|
---|
[1846] | 1272 |
|
---|
[794] | 1273 | """
|
---|
[1070] | 1274 | return self._get_column(self._getparangle, row)
|
---|
[794] | 1275 |
|
---|
[1070] | 1276 | def get_direction(self, row=-1):
|
---|
| 1277 | """
|
---|
| 1278 | Get a list of Positions on the sky (direction) for the observations.
|
---|
[1594] | 1279 | Return a string for each integration in the scantable.
|
---|
[1855] | 1280 |
|
---|
[1070] | 1281 | Parameters:
|
---|
[1855] | 1282 |
|
---|
[1070] | 1283 | row: row no of integration. Default -1 return all rows
|
---|
[1855] | 1284 |
|
---|
[1070] | 1285 | """
|
---|
| 1286 | return self._get_column(self._getdirection, row)
|
---|
| 1287 |
|
---|
[1391] | 1288 | def get_directionval(self, row=-1):
|
---|
[1846] | 1289 | """\
|
---|
[1391] | 1290 | Get a list of Positions on the sky (direction) for the observations.
|
---|
| 1291 | Return a float for each integration in the scantable.
|
---|
[1846] | 1292 |
|
---|
[1391] | 1293 | Parameters:
|
---|
[1846] | 1294 |
|
---|
[1391] | 1295 | row: row no of integration. Default -1 return all rows
|
---|
[1846] | 1296 |
|
---|
[1391] | 1297 | """
|
---|
| 1298 | return self._get_column(self._getdirectionvec, row)
|
---|
| 1299 |
|
---|
[1862] | 1300 | @asaplog_post_dec
|
---|
[102] | 1301 | def set_unit(self, unit='channel'):
|
---|
[1846] | 1302 | """\
|
---|
[102] | 1303 | Set the unit for all following operations on this scantable
|
---|
[1846] | 1304 |
|
---|
[102] | 1305 | Parameters:
|
---|
[1846] | 1306 |
|
---|
| 1307 | unit: optional unit, default is 'channel'. Use one of '*Hz',
|
---|
| 1308 | 'km/s', 'channel' or equivalent ''
|
---|
| 1309 |
|
---|
[102] | 1310 | """
|
---|
[484] | 1311 | varlist = vars()
|
---|
[1118] | 1312 | if unit in ['', 'pixel', 'channel']:
|
---|
[113] | 1313 | unit = ''
|
---|
| 1314 | inf = list(self._getcoordinfo())
|
---|
| 1315 | inf[0] = unit
|
---|
| 1316 | self._setcoordinfo(inf)
|
---|
[1118] | 1317 | self._add_history("set_unit", varlist)
|
---|
[113] | 1318 |
|
---|
[1862] | 1319 | @asaplog_post_dec
|
---|
[484] | 1320 | def set_instrument(self, instr):
|
---|
[1846] | 1321 | """\
|
---|
[1348] | 1322 | Set the instrument for subsequent processing.
|
---|
[1846] | 1323 |
|
---|
[358] | 1324 | Parameters:
|
---|
[1846] | 1325 |
|
---|
[710] | 1326 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA',
|
---|
[407] | 1327 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART'
|
---|
[1846] | 1328 |
|
---|
[358] | 1329 | """
|
---|
| 1330 | self._setInstrument(instr)
|
---|
[1118] | 1331 | self._add_history("set_instument", vars())
|
---|
[358] | 1332 |
|
---|
[1862] | 1333 | @asaplog_post_dec
|
---|
[1190] | 1334 | def set_feedtype(self, feedtype):
|
---|
[1846] | 1335 | """\
|
---|
[1190] | 1336 | Overwrite the feed type, which might not be set correctly.
|
---|
[1846] | 1337 |
|
---|
[1190] | 1338 | Parameters:
|
---|
[1846] | 1339 |
|
---|
[1190] | 1340 | feedtype: 'linear' or 'circular'
|
---|
[1846] | 1341 |
|
---|
[1190] | 1342 | """
|
---|
| 1343 | self._setfeedtype(feedtype)
|
---|
| 1344 | self._add_history("set_feedtype", vars())
|
---|
| 1345 |
|
---|
[1862] | 1346 | @asaplog_post_dec
|
---|
[2897] | 1347 | def get_doppler(self):
|
---|
| 1348 | """\
|
---|
| 1349 | Get the doppler.
|
---|
| 1350 | """
|
---|
| 1351 | return self._getcoordinfo()[2]
|
---|
| 1352 |
|
---|
| 1353 | @asaplog_post_dec
|
---|
[276] | 1354 | def set_doppler(self, doppler='RADIO'):
|
---|
[1846] | 1355 | """\
|
---|
[276] | 1356 | Set the doppler for all following operations on this scantable.
|
---|
[1846] | 1357 |
|
---|
[276] | 1358 | Parameters:
|
---|
[1846] | 1359 |
|
---|
[276] | 1360 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA'
|
---|
[1846] | 1361 |
|
---|
[276] | 1362 | """
|
---|
[484] | 1363 | varlist = vars()
|
---|
[276] | 1364 | inf = list(self._getcoordinfo())
|
---|
| 1365 | inf[2] = doppler
|
---|
| 1366 | self._setcoordinfo(inf)
|
---|
[1118] | 1367 | self._add_history("set_doppler", vars())
|
---|
[710] | 1368 |
|
---|
[1862] | 1369 | @asaplog_post_dec
|
---|
[226] | 1370 | def set_freqframe(self, frame=None):
|
---|
[1846] | 1371 | """\
|
---|
[113] | 1372 | Set the frame type of the Spectral Axis.
|
---|
[1846] | 1373 |
|
---|
[113] | 1374 | Parameters:
|
---|
[1846] | 1375 |
|
---|
[591] | 1376 | frame: an optional frame type, default 'LSRK'. Valid frames are:
|
---|
[1819] | 1377 | 'TOPO', 'LSRD', 'LSRK', 'BARY',
|
---|
[1118] | 1378 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'
|
---|
[1846] | 1379 |
|
---|
| 1380 | Example::
|
---|
| 1381 |
|
---|
[113] | 1382 | scan.set_freqframe('BARY')
|
---|
[1846] | 1383 |
|
---|
[113] | 1384 | """
|
---|
[1593] | 1385 | frame = frame or rcParams['scantable.freqframe']
|
---|
[484] | 1386 | varlist = vars()
|
---|
[1819] | 1387 | # "REST" is not implemented in casacore
|
---|
| 1388 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \
|
---|
| 1389 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB']
|
---|
| 1390 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \
|
---|
[1118] | 1391 | 'GEO', 'GALACTO', 'LGROUP', 'CMB']
|
---|
[591] | 1392 |
|
---|
[989] | 1393 | if frame in valid:
|
---|
[113] | 1394 | inf = list(self._getcoordinfo())
|
---|
| 1395 | inf[1] = frame
|
---|
| 1396 | self._setcoordinfo(inf)
|
---|
[1118] | 1397 | self._add_history("set_freqframe", varlist)
|
---|
[102] | 1398 | else:
|
---|
[1118] | 1399 | msg = "Please specify a valid freq type. Valid types are:\n", valid
|
---|
[1859] | 1400 | raise TypeError(msg)
|
---|
[710] | 1401 |
|
---|
[1862] | 1402 | @asaplog_post_dec
|
---|
[989] | 1403 | def set_dirframe(self, frame=""):
|
---|
[1846] | 1404 | """\
|
---|
[989] | 1405 | Set the frame type of the Direction on the sky.
|
---|
[1846] | 1406 |
|
---|
[989] | 1407 | Parameters:
|
---|
[1846] | 1408 |
|
---|
[989] | 1409 | frame: an optional frame type, default ''. Valid frames are:
|
---|
| 1410 | 'J2000', 'B1950', 'GALACTIC'
|
---|
[1846] | 1411 |
|
---|
| 1412 | Example:
|
---|
| 1413 |
|
---|
[989] | 1414 | scan.set_dirframe('GALACTIC')
|
---|
[1846] | 1415 |
|
---|
[989] | 1416 | """
|
---|
| 1417 | varlist = vars()
|
---|
[1859] | 1418 | Scantable.set_dirframe(self, frame)
|
---|
[1118] | 1419 | self._add_history("set_dirframe", varlist)
|
---|
[989] | 1420 |
|
---|
[113] | 1421 | def get_unit(self):
|
---|
[1846] | 1422 | """\
|
---|
[113] | 1423 | Get the default unit set in this scantable
|
---|
[1846] | 1424 |
|
---|
[113] | 1425 | Returns:
|
---|
[1846] | 1426 |
|
---|
[113] | 1427 | A unit string
|
---|
[1846] | 1428 |
|
---|
[113] | 1429 | """
|
---|
| 1430 | inf = self._getcoordinfo()
|
---|
| 1431 | unit = inf[0]
|
---|
| 1432 | if unit == '': unit = 'channel'
|
---|
| 1433 | return unit
|
---|
[102] | 1434 |
|
---|
[1862] | 1435 | @asaplog_post_dec
|
---|
[158] | 1436 | def get_abcissa(self, rowno=0):
|
---|
[1846] | 1437 | """\
|
---|
[158] | 1438 | Get the abcissa in the current coordinate setup for the currently
|
---|
[113] | 1439 | selected Beam/IF/Pol
|
---|
[1846] | 1440 |
|
---|
[113] | 1441 | Parameters:
|
---|
[1846] | 1442 |
|
---|
[226] | 1443 | rowno: an optional row number in the scantable. Default is the
|
---|
| 1444 | first row, i.e. rowno=0
|
---|
[1846] | 1445 |
|
---|
[113] | 1446 | Returns:
|
---|
[1846] | 1447 |
|
---|
[1348] | 1448 | The abcissa values and the format string (as a dictionary)
|
---|
[1846] | 1449 |
|
---|
[113] | 1450 | """
|
---|
[256] | 1451 | abc = self._getabcissa(rowno)
|
---|
[710] | 1452 | lbl = self._getabcissalabel(rowno)
|
---|
[158] | 1453 | return abc, lbl
|
---|
[113] | 1454 |
|
---|
[1862] | 1455 | @asaplog_post_dec
|
---|
[2322] | 1456 | def flag(self, mask=None, unflag=False, row=-1):
|
---|
[1846] | 1457 | """\
|
---|
[1001] | 1458 | Flag the selected data using an optional channel mask.
|
---|
[1846] | 1459 |
|
---|
[1001] | 1460 | Parameters:
|
---|
[1846] | 1461 |
|
---|
[1001] | 1462 | mask: an optional channel mask, created with create_mask. Default
|
---|
| 1463 | (no mask) is all channels.
|
---|
[1855] | 1464 |
|
---|
[1819] | 1465 | unflag: if True, unflag the data
|
---|
[1846] | 1466 |
|
---|
[2322] | 1467 | row: an optional row number in the scantable.
|
---|
| 1468 | Default -1 flags all rows
|
---|
| 1469 |
|
---|
[1001] | 1470 | """
|
---|
| 1471 | varlist = vars()
|
---|
[1593] | 1472 | mask = mask or []
|
---|
[1994] | 1473 | self._flag(row, mask, unflag)
|
---|
[1001] | 1474 | self._add_history("flag", varlist)
|
---|
| 1475 |
|
---|
[1862] | 1476 | @asaplog_post_dec
|
---|
[2322] | 1477 | def flag_row(self, rows=None, unflag=False):
|
---|
[1846] | 1478 | """\
|
---|
[1819] | 1479 | Flag the selected data in row-based manner.
|
---|
[1846] | 1480 |
|
---|
[1819] | 1481 | Parameters:
|
---|
[1846] | 1482 |
|
---|
[1843] | 1483 | rows: list of row numbers to be flagged. Default is no row
|
---|
[2322] | 1484 | (must be explicitly specified to execute row-based
|
---|
| 1485 | flagging).
|
---|
[1855] | 1486 |
|
---|
[1819] | 1487 | unflag: if True, unflag the data.
|
---|
[1846] | 1488 |
|
---|
[1819] | 1489 | """
|
---|
| 1490 | varlist = vars()
|
---|
[2322] | 1491 | if rows is None:
|
---|
| 1492 | rows = []
|
---|
[1859] | 1493 | self._flag_row(rows, unflag)
|
---|
[1819] | 1494 | self._add_history("flag_row", varlist)
|
---|
| 1495 |
|
---|
[1862] | 1496 | @asaplog_post_dec
|
---|
[1819] | 1497 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False):
|
---|
[1846] | 1498 | """\
|
---|
[1819] | 1499 | Flag the selected data outside a specified range (in channel-base)
|
---|
[1846] | 1500 |
|
---|
[1819] | 1501 | Parameters:
|
---|
[1846] | 1502 |
|
---|
[1819] | 1503 | uthres: upper threshold.
|
---|
[1855] | 1504 |
|
---|
[1819] | 1505 | dthres: lower threshold
|
---|
[1846] | 1506 |
|
---|
[2322] | 1507 | clipoutside: True for flagging data outside the range
|
---|
| 1508 | [dthres:uthres].
|
---|
[1928] | 1509 | False for flagging data inside the range.
|
---|
[1855] | 1510 |
|
---|
[1846] | 1511 | unflag: if True, unflag the data.
|
---|
| 1512 |
|
---|
[1819] | 1513 | """
|
---|
| 1514 | varlist = vars()
|
---|
[1859] | 1515 | self._clip(uthres, dthres, clipoutside, unflag)
|
---|
[1819] | 1516 | self._add_history("clip", varlist)
|
---|
| 1517 |
|
---|
[1862] | 1518 | @asaplog_post_dec
|
---|
[1584] | 1519 | def lag_flag(self, start, end, unit="MHz", insitu=None):
|
---|
[1846] | 1520 | """\
|
---|
[1192] | 1521 | Flag the data in 'lag' space by providing a frequency to remove.
|
---|
[2177] | 1522 | Flagged data in the scantable get interpolated over the region.
|
---|
[1192] | 1523 | No taper is applied.
|
---|
[1846] | 1524 |
|
---|
[1192] | 1525 | Parameters:
|
---|
[1846] | 1526 |
|
---|
[1579] | 1527 | start: the start frequency (really a period within the
|
---|
| 1528 | bandwidth) or period to remove
|
---|
[1855] | 1529 |
|
---|
[1579] | 1530 | end: the end frequency or period to remove
|
---|
[1855] | 1531 |
|
---|
[2431] | 1532 | unit: the frequency unit (default 'MHz') or '' for
|
---|
[1579] | 1533 | explicit lag channels
|
---|
[1846] | 1534 |
|
---|
| 1535 | *Notes*:
|
---|
| 1536 |
|
---|
[1579] | 1537 | It is recommended to flag edges of the band or strong
|
---|
[1348] | 1538 | signals beforehand.
|
---|
[1846] | 1539 |
|
---|
[1192] | 1540 | """
|
---|
| 1541 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 1542 | self._math._setinsitu(insitu)
|
---|
| 1543 | varlist = vars()
|
---|
[1579] | 1544 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.}
|
---|
| 1545 | if not (unit == "" or base.has_key(unit)):
|
---|
[1192] | 1546 | raise ValueError("%s is not a valid unit." % unit)
|
---|
[1859] | 1547 | if unit == "":
|
---|
| 1548 | s = scantable(self._math._lag_flag(self, start, end, "lags"))
|
---|
| 1549 | else:
|
---|
| 1550 | s = scantable(self._math._lag_flag(self, start*base[unit],
|
---|
| 1551 | end*base[unit], "frequency"))
|
---|
[1192] | 1552 | s._add_history("lag_flag", varlist)
|
---|
| 1553 | if insitu:
|
---|
| 1554 | self._assign(s)
|
---|
| 1555 | else:
|
---|
| 1556 | return s
|
---|
[1001] | 1557 |
|
---|
[1862] | 1558 | @asaplog_post_dec
|
---|
[2349] | 1559 | def fft(self, rowno=None, mask=None, getrealimag=False):
|
---|
[2177] | 1560 | """\
|
---|
| 1561 | Apply FFT to the spectra.
|
---|
| 1562 | Flagged data in the scantable get interpolated over the region.
|
---|
| 1563 |
|
---|
| 1564 | Parameters:
|
---|
[2186] | 1565 |
|
---|
| 1566 | rowno: The row number(s) to be processed. int, list
|
---|
[2349] | 1567 | and tuple are accepted. By default (None), FFT
|
---|
[2186] | 1568 | is applied to the whole data.
|
---|
| 1569 |
|
---|
| 1570 | mask: Auxiliary channel mask(s). Given as a boolean
|
---|
| 1571 | list, it is applied to all specified rows.
|
---|
| 1572 | A list of boolean lists can also be used to
|
---|
| 1573 | apply different masks. In the latter case, the
|
---|
| 1574 | length of 'mask' must be the same as that of
|
---|
[2349] | 1575 | 'rowno'. The default is None.
|
---|
[2177] | 1576 |
|
---|
| 1577 | getrealimag: If True, returns the real and imaginary part
|
---|
| 1578 | values of the complex results.
|
---|
| 1579 | If False (the default), returns the amplitude
|
---|
| 1580 | (absolute value) normalised with Ndata/2 and
|
---|
| 1581 | phase (argument, in unit of radian).
|
---|
| 1582 |
|
---|
| 1583 | Returns:
|
---|
| 1584 |
|
---|
[2186] | 1585 | A list of dictionaries containing the results for each spectrum.
|
---|
| 1586 | Each dictionary contains two values, the real and the imaginary
|
---|
| 1587 | parts when getrealimag = True, or the amplitude(absolute value)
|
---|
| 1588 | and the phase(argument) when getrealimag = False. The key for
|
---|
| 1589 | these values are 'real' and 'imag', or 'ampl' and 'phase',
|
---|
[2177] | 1590 | respectively.
|
---|
| 1591 | """
|
---|
[2349] | 1592 | if rowno is None:
|
---|
| 1593 | rowno = []
|
---|
[2177] | 1594 | if isinstance(rowno, int):
|
---|
| 1595 | rowno = [rowno]
|
---|
| 1596 | elif not (isinstance(rowno, list) or isinstance(rowno, tuple)):
|
---|
[2186] | 1597 | raise TypeError("The row number(s) must be int, list or tuple.")
|
---|
| 1598 | if len(rowno) == 0: rowno = [i for i in xrange(self.nrow())]
|
---|
| 1599 |
|
---|
[2411] | 1600 | usecommonmask = True
|
---|
| 1601 |
|
---|
| 1602 | if mask is None:
|
---|
| 1603 | mask = []
|
---|
| 1604 | if isinstance(mask, list) or isinstance(mask, tuple):
|
---|
| 1605 | if len(mask) == 0:
|
---|
| 1606 | mask = [[]]
|
---|
| 1607 | else:
|
---|
| 1608 | if isinstance(mask[0], bool):
|
---|
| 1609 | if len(mask) != self.nchan(self.getif(rowno[0])):
|
---|
| 1610 | raise ValueError("The spectra and the mask have "
|
---|
| 1611 | "different length.")
|
---|
| 1612 | mask = [mask]
|
---|
| 1613 | elif isinstance(mask[0], list) or isinstance(mask[0], tuple):
|
---|
| 1614 | usecommonmask = False
|
---|
| 1615 | if len(mask) != len(rowno):
|
---|
| 1616 | raise ValueError("When specifying masks for each "
|
---|
| 1617 | "spectrum, the numbers of them "
|
---|
| 1618 | "must be identical.")
|
---|
| 1619 | for i in xrange(mask):
|
---|
| 1620 | if len(mask[i]) != self.nchan(self.getif(rowno[i])):
|
---|
| 1621 | raise ValueError("The spectra and the mask have "
|
---|
| 1622 | "different length.")
|
---|
| 1623 | else:
|
---|
| 1624 | raise TypeError("The mask must be a boolean list or "
|
---|
| 1625 | "a list of boolean list.")
|
---|
| 1626 | else:
|
---|
[2349] | 1627 | raise TypeError("The mask must be a boolean list or a list of "
|
---|
| 1628 | "boolean list.")
|
---|
[2186] | 1629 |
|
---|
| 1630 | res = []
|
---|
| 1631 |
|
---|
| 1632 | imask = 0
|
---|
| 1633 | for whichrow in rowno:
|
---|
| 1634 | fspec = self._fft(whichrow, mask[imask], getrealimag)
|
---|
| 1635 | nspec = len(fspec)
|
---|
[2177] | 1636 |
|
---|
[2349] | 1637 | i = 0
|
---|
| 1638 | v1 = []
|
---|
| 1639 | v2 = []
|
---|
| 1640 | reselem = {"real":[],"imag":[]} if getrealimag \
|
---|
| 1641 | else {"ampl":[],"phase":[]}
|
---|
[2177] | 1642 |
|
---|
[2186] | 1643 | while (i < nspec):
|
---|
| 1644 | v1.append(fspec[i])
|
---|
| 1645 | v2.append(fspec[i+1])
|
---|
[2349] | 1646 | i += 2
|
---|
[2186] | 1647 |
|
---|
[2177] | 1648 | if getrealimag:
|
---|
[2186] | 1649 | reselem["real"] += v1
|
---|
| 1650 | reselem["imag"] += v2
|
---|
[2177] | 1651 | else:
|
---|
[2186] | 1652 | reselem["ampl"] += v1
|
---|
| 1653 | reselem["phase"] += v2
|
---|
[2177] | 1654 |
|
---|
[2186] | 1655 | res.append(reselem)
|
---|
| 1656 |
|
---|
[2349] | 1657 | if not usecommonmask:
|
---|
| 1658 | imask += 1
|
---|
[2186] | 1659 |
|
---|
[2177] | 1660 | return res
|
---|
| 1661 |
|
---|
| 1662 | @asaplog_post_dec
|
---|
[113] | 1663 | def create_mask(self, *args, **kwargs):
|
---|
[1846] | 1664 | """\
|
---|
[1118] | 1665 | Compute and return a mask based on [min, max] windows.
|
---|
[189] | 1666 | The specified windows are to be INCLUDED, when the mask is
|
---|
[113] | 1667 | applied.
|
---|
[1846] | 1668 |
|
---|
[102] | 1669 | Parameters:
|
---|
[1846] | 1670 |
|
---|
[1118] | 1671 | [min, max], [min2, max2], ...
|
---|
[1024] | 1672 | Pairs of start/end points (inclusive)specifying the regions
|
---|
[102] | 1673 | to be masked
|
---|
[1855] | 1674 |
|
---|
[189] | 1675 | invert: optional argument. If specified as True,
|
---|
| 1676 | return an inverted mask, i.e. the regions
|
---|
| 1677 | specified are EXCLUDED
|
---|
[1855] | 1678 |
|
---|
[513] | 1679 | row: create the mask using the specified row for
|
---|
| 1680 | unit conversions, default is row=0
|
---|
| 1681 | only necessary if frequency varies over rows.
|
---|
[1846] | 1682 |
|
---|
| 1683 | Examples::
|
---|
| 1684 |
|
---|
[113] | 1685 | scan.set_unit('channel')
|
---|
[1846] | 1686 | # a)
|
---|
[1118] | 1687 | msk = scan.create_mask([400, 500], [800, 900])
|
---|
[189] | 1688 | # masks everything outside 400 and 500
|
---|
[113] | 1689 | # and 800 and 900 in the unit 'channel'
|
---|
| 1690 |
|
---|
[1846] | 1691 | # b)
|
---|
[1118] | 1692 | msk = scan.create_mask([400, 500], [800, 900], invert=True)
|
---|
[189] | 1693 | # masks the regions between 400 and 500
|
---|
[113] | 1694 | # and 800 and 900 in the unit 'channel'
|
---|
[1846] | 1695 |
|
---|
| 1696 | # c)
|
---|
| 1697 | #mask only channel 400
|
---|
[1554] | 1698 | msk = scan.create_mask([400])
|
---|
[1846] | 1699 |
|
---|
[102] | 1700 | """
|
---|
[1554] | 1701 | row = kwargs.get("row", 0)
|
---|
[513] | 1702 | data = self._getabcissa(row)
|
---|
[113] | 1703 | u = self._getcoordinfo()[0]
|
---|
[1859] | 1704 | if u == "":
|
---|
| 1705 | u = "channel"
|
---|
| 1706 | msg = "The current mask window unit is %s" % u
|
---|
| 1707 | i = self._check_ifs()
|
---|
| 1708 | if not i:
|
---|
| 1709 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i))
|
---|
| 1710 | asaplog.push(msg)
|
---|
[2348] | 1711 | n = len(data)
|
---|
[1295] | 1712 | msk = _n_bools(n, False)
|
---|
[710] | 1713 | # test if args is a 'list' or a 'normal *args - UGLY!!!
|
---|
| 1714 |
|
---|
[2349] | 1715 | ws = (isinstance(args[-1][-1], int)
|
---|
| 1716 | or isinstance(args[-1][-1], float)) and args or args[0]
|
---|
[710] | 1717 | for window in ws:
|
---|
[1554] | 1718 | if len(window) == 1:
|
---|
| 1719 | window = [window[0], window[0]]
|
---|
| 1720 | if len(window) == 0 or len(window) > 2:
|
---|
[2349] | 1721 | raise ValueError("A window needs to be defined as "
|
---|
| 1722 | "[start(, end)]")
|
---|
[1545] | 1723 | if window[0] > window[1]:
|
---|
| 1724 | tmp = window[0]
|
---|
| 1725 | window[0] = window[1]
|
---|
| 1726 | window[1] = tmp
|
---|
[102] | 1727 | for i in range(n):
|
---|
[1024] | 1728 | if data[i] >= window[0] and data[i] <= window[1]:
|
---|
[1295] | 1729 | msk[i] = True
|
---|
[113] | 1730 | if kwargs.has_key('invert'):
|
---|
| 1731 | if kwargs.get('invert'):
|
---|
[1295] | 1732 | msk = mask_not(msk)
|
---|
[102] | 1733 | return msk
|
---|
[710] | 1734 |
|
---|
[1931] | 1735 | def get_masklist(self, mask=None, row=0, silent=False):
|
---|
[1846] | 1736 | """\
|
---|
[1819] | 1737 | Compute and return a list of mask windows, [min, max].
|
---|
[1846] | 1738 |
|
---|
[1819] | 1739 | Parameters:
|
---|
[1846] | 1740 |
|
---|
[1819] | 1741 | mask: channel mask, created with create_mask.
|
---|
[1855] | 1742 |
|
---|
[1819] | 1743 | row: calcutate the masklist using the specified row
|
---|
| 1744 | for unit conversions, default is row=0
|
---|
| 1745 | only necessary if frequency varies over rows.
|
---|
[1846] | 1746 |
|
---|
[1819] | 1747 | Returns:
|
---|
[1846] | 1748 |
|
---|
[1819] | 1749 | [min, max], [min2, max2], ...
|
---|
| 1750 | Pairs of start/end points (inclusive)specifying
|
---|
| 1751 | the masked regions
|
---|
[1846] | 1752 |
|
---|
[1819] | 1753 | """
|
---|
| 1754 | if not (isinstance(mask,list) or isinstance(mask, tuple)):
|
---|
| 1755 | raise TypeError("The mask should be list or tuple.")
|
---|
[2427] | 1756 | if len(mask) <= 0:
|
---|
| 1757 | raise TypeError("The mask elements should be > 0")
|
---|
[2348] | 1758 | data = self._getabcissa(row)
|
---|
| 1759 | if len(data) != len(mask):
|
---|
[1819] | 1760 | msg = "Number of channels in scantable != number of mask elements"
|
---|
| 1761 | raise TypeError(msg)
|
---|
| 1762 | u = self._getcoordinfo()[0]
|
---|
[1859] | 1763 | if u == "":
|
---|
| 1764 | u = "channel"
|
---|
| 1765 | msg = "The current mask window unit is %s" % u
|
---|
| 1766 | i = self._check_ifs()
|
---|
| 1767 | if not i:
|
---|
| 1768 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i))
|
---|
[1931] | 1769 | if not silent:
|
---|
| 1770 | asaplog.push(msg)
|
---|
[2349] | 1771 | masklist = []
|
---|
[1819] | 1772 | ist, ien = None, None
|
---|
| 1773 | ist, ien=self.get_mask_indices(mask)
|
---|
| 1774 | if ist is not None and ien is not None:
|
---|
| 1775 | for i in xrange(len(ist)):
|
---|
| 1776 | range=[data[ist[i]],data[ien[i]]]
|
---|
| 1777 | range.sort()
|
---|
| 1778 | masklist.append([range[0],range[1]])
|
---|
| 1779 | return masklist
|
---|
| 1780 |
|
---|
| 1781 | def get_mask_indices(self, mask=None):
|
---|
[1846] | 1782 | """\
|
---|
[1819] | 1783 | Compute and Return lists of mask start indices and mask end indices.
|
---|
[1855] | 1784 |
|
---|
| 1785 | Parameters:
|
---|
| 1786 |
|
---|
[1819] | 1787 | mask: channel mask, created with create_mask.
|
---|
[1846] | 1788 |
|
---|
[1819] | 1789 | Returns:
|
---|
[1846] | 1790 |
|
---|
[1819] | 1791 | List of mask start indices and that of mask end indices,
|
---|
| 1792 | i.e., [istart1,istart2,....], [iend1,iend2,....].
|
---|
[1846] | 1793 |
|
---|
[1819] | 1794 | """
|
---|
| 1795 | if not (isinstance(mask,list) or isinstance(mask, tuple)):
|
---|
| 1796 | raise TypeError("The mask should be list or tuple.")
|
---|
[2427] | 1797 | if len(mask) <= 0:
|
---|
| 1798 | raise TypeError("The mask elements should be > 0")
|
---|
[2349] | 1799 | istart = []
|
---|
| 1800 | iend = []
|
---|
| 1801 | if mask[0]:
|
---|
| 1802 | istart.append(0)
|
---|
[1819] | 1803 | for i in range(len(mask)-1):
|
---|
| 1804 | if not mask[i] and mask[i+1]:
|
---|
| 1805 | istart.append(i+1)
|
---|
| 1806 | elif mask[i] and not mask[i+1]:
|
---|
| 1807 | iend.append(i)
|
---|
[2349] | 1808 | if mask[len(mask)-1]:
|
---|
| 1809 | iend.append(len(mask)-1)
|
---|
[1819] | 1810 | if len(istart) != len(iend):
|
---|
| 1811 | raise RuntimeError("Numbers of mask start != mask end.")
|
---|
| 1812 | for i in range(len(istart)):
|
---|
| 1813 | if istart[i] > iend[i]:
|
---|
| 1814 | raise RuntimeError("Mask start index > mask end index")
|
---|
| 1815 | break
|
---|
| 1816 | return istart,iend
|
---|
| 1817 |
|
---|
[2013] | 1818 | @asaplog_post_dec
|
---|
[2882] | 1819 | def parse_spw_selection(self, selectstring, restfreq=None, frame=None, doppler=None):
|
---|
| 1820 | """
|
---|
| 1821 | Parse MS type spw/channel selection syntax.
|
---|
| 1822 |
|
---|
| 1823 | Parameters:
|
---|
| 1824 | selectstring : A string expression of spw and channel selection.
|
---|
| 1825 | Comma-separated expressions mean different spw -
|
---|
| 1826 | channel combinations. Spws and channel selections
|
---|
| 1827 | are partitioned by a colon ':'. In a single
|
---|
| 1828 | selection expression, you can put multiple values
|
---|
| 1829 | separated by semicolons ';'. Both for spw and
|
---|
| 1830 | channel selection, allowed cases include single
|
---|
| 1831 | value, blank('') or asterisk('*') to specify all
|
---|
| 1832 | available values, two values connected with a
|
---|
| 1833 | tilde ('~') to specify an inclusive range. Unit
|
---|
| 1834 | strings for frequency or velocity can be added to
|
---|
| 1835 | the tilde-connected values. For channel selection
|
---|
| 1836 | expression, placing a '<' or a '>' is possible to
|
---|
| 1837 | specify a semi-infinite interval as well.
|
---|
| 1838 |
|
---|
| 1839 | examples:
|
---|
| 1840 | '' or '*' = all spws (all channels)
|
---|
| 1841 | '<2,4~6,9' = Spws 0,1,4,5,6,9 (all channels)
|
---|
| 1842 | '3:3~45;60' = channels 3 to 45 and 60 in spw 3
|
---|
| 1843 | '0~1:2~6,8' = channels 2 to 6 in spws 0,1, and
|
---|
| 1844 | all channels in spw8
|
---|
[2936] | 1845 | '1.3~1.5GHz' = all spws whose central frequency
|
---|
| 1846 | falls in frequency range between
|
---|
| 1847 | 1.3GHz and 1.5GHz.
|
---|
| 1848 | '1.3~1.5GHz:1.3~1.5GHz' = channels which fall
|
---|
[2884] | 1849 | between the specified
|
---|
| 1850 | frequency range in spws
|
---|
[2936] | 1851 | whose central frequency
|
---|
| 1852 | falls in the specified
|
---|
| 1853 | frequency range.
|
---|
[2884] | 1854 | '1:-200~250km/s' = channels that fall between the
|
---|
| 1855 | specified velocity range in
|
---|
| 1856 | spw 1.
|
---|
[2897] | 1857 | restfreq: the rest frequency.
|
---|
| 1858 | examples: '115.2712GHz', 115271201800.0
|
---|
| 1859 | frame: an optional frame type, default 'LSRK'. Valid frames are:
|
---|
| 1860 | 'TOPO', 'LSRD', 'LSRK', 'BARY',
|
---|
| 1861 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'
|
---|
| 1862 | doppler: one of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA'
|
---|
[2882] | 1863 | Returns:
|
---|
| 1864 | A dictionary of selected (valid) spw and masklist pairs,
|
---|
| 1865 | e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]}
|
---|
| 1866 | """
|
---|
| 1867 | if not isinstance(selectstring, str):
|
---|
| 1868 | asaplog.post()
|
---|
| 1869 | asaplog.push("Expression of spw/channel selection must be a string.")
|
---|
| 1870 | asaplog.post("ERROR")
|
---|
| 1871 |
|
---|
| 1872 | orig_unit = self.get_unit()
|
---|
| 1873 | self.set_unit('channel')
|
---|
| 1874 |
|
---|
[2891] | 1875 | if restfreq is not None:
|
---|
[2892] | 1876 | orig_molids = self._getmolidcol_list()
|
---|
| 1877 | set_restfreq(self, restfreq)
|
---|
[2882] | 1878 |
|
---|
[2897] | 1879 | orig_coord = self._getcoordinfo()
|
---|
[2892] | 1880 |
|
---|
| 1881 | if frame is not None:
|
---|
| 1882 | orig_frame = orig_coord[1]
|
---|
| 1883 | self.set_freqframe(frame)
|
---|
| 1884 |
|
---|
| 1885 | if doppler is not None:
|
---|
| 1886 | orig_doppler = orig_coord[2]
|
---|
| 1887 | self.set_doppler(doppler)
|
---|
[2882] | 1888 |
|
---|
| 1889 | valid_ifs = self.getifnos()
|
---|
| 1890 |
|
---|
| 1891 | comma_sep = selectstring.split(",")
|
---|
| 1892 | res = {}
|
---|
| 1893 |
|
---|
| 1894 | for cms_elem in comma_sep:
|
---|
| 1895 | colon_sep = cms_elem.split(":")
|
---|
| 1896 |
|
---|
| 1897 | if (len(colon_sep) > 2):
|
---|
| 1898 | raise RuntimeError("Invalid selection expression: more than two colons!")
|
---|
| 1899 |
|
---|
| 1900 | # parse spw expression and store result in spw_list.
|
---|
| 1901 | # allowed cases include '', '*', 'a', '<a', '>a', 'a~b',
|
---|
[2884] | 1902 | # 'a~b*Hz' (where * can be '', 'k', 'M', 'G' etc.),
|
---|
| 1903 | # 'a~b*m/s' (where * can be '' or 'k') and also
|
---|
[2882] | 1904 | # several of the above expressions connected with ';'.
|
---|
| 1905 |
|
---|
| 1906 | spw_list = []
|
---|
| 1907 |
|
---|
| 1908 | semicolon_sep = colon_sep[0].split(";")
|
---|
| 1909 |
|
---|
| 1910 | for scs_elem in semicolon_sep:
|
---|
| 1911 | scs_elem = scs_elem.strip()
|
---|
| 1912 |
|
---|
| 1913 | lt_sep = scs_elem.split("<")
|
---|
| 1914 | gt_sep = scs_elem.split(">")
|
---|
| 1915 | ti_sep = scs_elem.split("~")
|
---|
| 1916 |
|
---|
| 1917 | lt_sep_length = len(lt_sep)
|
---|
| 1918 | gt_sep_length = len(gt_sep)
|
---|
| 1919 | ti_sep_length = len(ti_sep)
|
---|
| 1920 |
|
---|
| 1921 | len_product = lt_sep_length * gt_sep_length * ti_sep_length
|
---|
| 1922 |
|
---|
| 1923 | if (len_product > 2):
|
---|
| 1924 | # '<', '>' and '~' must not coexist in a single spw expression
|
---|
| 1925 |
|
---|
| 1926 | raise RuntimeError("Invalid spw selection.")
|
---|
| 1927 |
|
---|
| 1928 | elif (len_product == 1):
|
---|
| 1929 | # '', '*', or single spw number.
|
---|
| 1930 |
|
---|
| 1931 | if (scs_elem == "") or (scs_elem == "*"):
|
---|
| 1932 | spw_list = valid_ifs[:] # deep copy
|
---|
| 1933 |
|
---|
| 1934 | else: # single number
|
---|
[2887] | 1935 | expr = int(scs_elem)
|
---|
| 1936 | spw_list.append(expr)
|
---|
| 1937 | if expr not in valid_ifs:
|
---|
| 1938 | asaplog.push("Invalid spw given. Ignored.")
|
---|
| 1939 |
|
---|
[2882] | 1940 | else: # (len_product == 2)
|
---|
[2887] | 1941 | # namely, one of '<', '>' or '~' appears just once.
|
---|
[2882] | 1942 |
|
---|
| 1943 | if (lt_sep_length == 2): # '<a'
|
---|
| 1944 | if is_number(lt_sep[1]):
|
---|
[2886] | 1945 | no_valid_spw = True
|
---|
[2882] | 1946 | for i in valid_ifs:
|
---|
| 1947 | if (i < float(lt_sep[1])):
|
---|
| 1948 | spw_list.append(i)
|
---|
[2886] | 1949 | no_valid_spw = False
|
---|
| 1950 |
|
---|
| 1951 | if no_valid_spw:
|
---|
| 1952 | raise ValueError("Invalid spw selection ('<" + str(lt_sep[1]) + "').")
|
---|
[2882] | 1953 |
|
---|
| 1954 | else:
|
---|
[2886] | 1955 | raise RuntimeError("Invalid spw selection.")
|
---|
[2882] | 1956 |
|
---|
| 1957 | elif (gt_sep_length == 2): # '>a'
|
---|
| 1958 | if is_number(gt_sep[1]):
|
---|
[2886] | 1959 | no_valid_spw = True
|
---|
[2882] | 1960 | for i in valid_ifs:
|
---|
| 1961 | if (i > float(gt_sep[1])):
|
---|
| 1962 | spw_list.append(i)
|
---|
[2886] | 1963 | no_valid_spw = False
|
---|
| 1964 |
|
---|
| 1965 | if no_valid_spw:
|
---|
| 1966 | raise ValueError("Invalid spw selection ('>" + str(gt_sep[1]) + "').")
|
---|
[2882] | 1967 |
|
---|
| 1968 | else:
|
---|
[2886] | 1969 | raise RuntimeError("Invalid spw selection.")
|
---|
[2882] | 1970 |
|
---|
| 1971 | else: # (ti_sep_length == 2) where both boundaries inclusive
|
---|
| 1972 | expr0 = ti_sep[0].strip()
|
---|
| 1973 | expr1 = ti_sep[1].strip()
|
---|
| 1974 |
|
---|
| 1975 | if is_number(expr0) and is_number(expr1):
|
---|
| 1976 | # 'a~b'
|
---|
| 1977 | expr_pmin = min(float(expr0), float(expr1))
|
---|
| 1978 | expr_pmax = max(float(expr0), float(expr1))
|
---|
[2887] | 1979 | has_invalid_spw = False
|
---|
[2886] | 1980 | no_valid_spw = True
|
---|
| 1981 |
|
---|
[2882] | 1982 | for i in valid_ifs:
|
---|
| 1983 | if (expr_pmin <= i) and (i <= expr_pmax):
|
---|
| 1984 | spw_list.append(i)
|
---|
[2886] | 1985 | no_valid_spw = False
|
---|
[2887] | 1986 | else:
|
---|
| 1987 | has_invalid_spw = True
|
---|
[2886] | 1988 |
|
---|
[2887] | 1989 | if has_invalid_spw:
|
---|
| 1990 | msg = "Invalid spw is given. Ignored."
|
---|
| 1991 | asaplog.push(msg)
|
---|
| 1992 | asaplog.post()
|
---|
| 1993 |
|
---|
[2886] | 1994 | if no_valid_spw:
|
---|
| 1995 | raise ValueError("No valid spw in range ('" + str(expr_pmin) + "~" + str(expr_pmax) + "').")
|
---|
[2887] | 1996 |
|
---|
[2884] | 1997 | elif is_number(expr0) and is_frequency(expr1):
|
---|
| 1998 | # 'a~b*Hz'
|
---|
| 1999 | (expr_f0, expr_f1) = get_freq_by_string(expr0, expr1)
|
---|
[2936] | 2000 | expr_fmin = min(expr_f0, expr_f1)
|
---|
| 2001 | expr_fmax = max(expr_f0, expr_f1)
|
---|
[2886] | 2002 | no_valid_spw = True
|
---|
| 2003 |
|
---|
[2882] | 2004 | for coord in self._get_coordinate_list():
|
---|
[2936] | 2005 | spw = coord['if']
|
---|
| 2006 |
|
---|
| 2007 | """
|
---|
[2882] | 2008 | expr_p0 = coord['coord'].to_pixel(expr_f0)
|
---|
| 2009 | expr_p1 = coord['coord'].to_pixel(expr_f1)
|
---|
| 2010 | expr_pmin = min(expr_p0, expr_p1)
|
---|
| 2011 | expr_pmax = max(expr_p0, expr_p1)
|
---|
| 2012 |
|
---|
| 2013 | pmin = 0.0
|
---|
| 2014 | pmax = float(self.nchan(spw) - 1)
|
---|
[2936] | 2015 |
|
---|
[2882] | 2016 | if ((expr_pmax - pmin)*(expr_pmin - pmax) <= 0.0):
|
---|
| 2017 | spw_list.append(spw)
|
---|
[2886] | 2018 | no_valid_spw = False
|
---|
[2936] | 2019 | """
|
---|
[2886] | 2020 |
|
---|
[2937] | 2021 | crd = coord['coord']
|
---|
| 2022 | fhead = crd.to_frequency(0)
|
---|
| 2023 | ftail = crd.to_frequency(self.nchan(spw) - 1)
|
---|
[2936] | 2024 | fcen = (fhead + ftail) / 2.0
|
---|
| 2025 |
|
---|
| 2026 | if ((expr_fmin <= fcen) and (fcen <= expr_fmax)):
|
---|
| 2027 | spw_list.append(spw)
|
---|
| 2028 | no_valid_spw = False
|
---|
| 2029 |
|
---|
[2886] | 2030 | if no_valid_spw:
|
---|
| 2031 | raise ValueError("No valid spw in range ('" + str(expr0) + "~" + str(expr1) + "').")
|
---|
[2882] | 2032 |
|
---|
[2884] | 2033 | elif is_number(expr0) and is_velocity(expr1):
|
---|
| 2034 | # 'a~b*m/s'
|
---|
| 2035 | (expr_v0, expr_v1) = get_velocity_by_string(expr0, expr1)
|
---|
[2882] | 2036 | expr_vmin = min(expr_v0, expr_v1)
|
---|
| 2037 | expr_vmax = max(expr_v0, expr_v1)
|
---|
[2886] | 2038 | no_valid_spw = True
|
---|
| 2039 |
|
---|
[2882] | 2040 | for coord in self._get_coordinate_list():
|
---|
| 2041 | spw = coord['if']
|
---|
[2936] | 2042 |
|
---|
| 2043 | """
|
---|
[2882] | 2044 | pmin = 0.0
|
---|
| 2045 | pmax = float(self.nchan(spw) - 1)
|
---|
| 2046 |
|
---|
| 2047 | vel0 = coord['coord'].to_velocity(pmin)
|
---|
| 2048 | vel1 = coord['coord'].to_velocity(pmax)
|
---|
| 2049 |
|
---|
| 2050 | vmin = min(vel0, vel1)
|
---|
| 2051 | vmax = max(vel0, vel1)
|
---|
| 2052 |
|
---|
| 2053 | if ((expr_vmax - vmin)*(expr_vmin - vmax) <= 0.0):
|
---|
| 2054 | spw_list.append(spw)
|
---|
[2886] | 2055 | no_valid_spw = False
|
---|
[2936] | 2056 | """
|
---|
[2886] | 2057 |
|
---|
[2937] | 2058 | crd = coord['coord']
|
---|
| 2059 | fhead = crd.to_frequency(0)
|
---|
| 2060 | ftail = crd.to_frequency(self.nchan(spw) - 1)
|
---|
| 2061 | fcen = (fhead + ftail) / 2.0
|
---|
| 2062 | vcen = crd.to_velocity(crd.to_pixel(fcen))
|
---|
[2936] | 2063 |
|
---|
| 2064 | if ((expr_vmin <= vcen) and (vcen <= expr_vmax)):
|
---|
| 2065 | spw_list.append(spw)
|
---|
| 2066 | no_valid_spw = False
|
---|
| 2067 |
|
---|
[2886] | 2068 | if no_valid_spw:
|
---|
| 2069 | raise ValueError("No valid spw in range ('" + str(expr0) + "~" + str(expr1) + "').")
|
---|
[2882] | 2070 |
|
---|
| 2071 | else:
|
---|
| 2072 | # cases such as 'aGHz~bkm/s' are not allowed now
|
---|
| 2073 | raise RuntimeError("Invalid spw selection.")
|
---|
| 2074 |
|
---|
[2887] | 2075 | # check spw list and remove invalid ones.
|
---|
| 2076 | # if no valid spw left, emit ValueError.
|
---|
| 2077 | if len(spw_list) == 0:
|
---|
| 2078 | raise ValueError("No valid spw in given range.")
|
---|
| 2079 |
|
---|
[2882] | 2080 | # parse channel expression and store the result in crange_list.
|
---|
| 2081 | # allowed cases include '', 'a~b', 'a*Hz~b*Hz' (where * can be
|
---|
| 2082 | # '', 'k', 'M', 'G' etc.), 'a*m/s~b*m/s' (where * can be '' or 'k')
|
---|
| 2083 | # and also several of the above expressions connected with ';'.
|
---|
| 2084 |
|
---|
| 2085 | for spw in spw_list:
|
---|
| 2086 | pmin = 0.0
|
---|
| 2087 | pmax = float(self.nchan(spw) - 1)
|
---|
[2909] | 2088 |
|
---|
| 2089 | molid = self._getmolidcol_list()[self.get_first_rowno_by_if(spw)]
|
---|
[2882] | 2090 |
|
---|
| 2091 | if (len(colon_sep) == 1):
|
---|
| 2092 | # no expression for channel selection,
|
---|
| 2093 | # which means all channels are to be selected.
|
---|
| 2094 | crange_list = [[pmin, pmax]]
|
---|
| 2095 |
|
---|
| 2096 | else: # (len(colon_sep) == 2)
|
---|
| 2097 | crange_list = []
|
---|
| 2098 |
|
---|
| 2099 | found = False
|
---|
| 2100 | for i in self._get_coordinate_list():
|
---|
| 2101 | if (i['if'] == spw):
|
---|
| 2102 | coord = i['coord']
|
---|
| 2103 | found = True
|
---|
| 2104 | break
|
---|
| 2105 |
|
---|
[2887] | 2106 | if found:
|
---|
| 2107 | semicolon_sep = colon_sep[1].split(";")
|
---|
| 2108 | for scs_elem in semicolon_sep:
|
---|
| 2109 | scs_elem = scs_elem.strip()
|
---|
[2882] | 2110 |
|
---|
[2887] | 2111 | ti_sep = scs_elem.split("~")
|
---|
| 2112 | ti_sep_length = len(ti_sep)
|
---|
[2882] | 2113 |
|
---|
[2887] | 2114 | if (ti_sep_length > 2):
|
---|
| 2115 | raise RuntimeError("Invalid channel selection.")
|
---|
[2882] | 2116 |
|
---|
[2887] | 2117 | elif (ti_sep_length == 1):
|
---|
| 2118 | if (scs_elem == "") or (scs_elem == "*"):
|
---|
| 2119 | # '' and '*' for all channels
|
---|
| 2120 | crange_list = [[pmin, pmax]]
|
---|
| 2121 | break
|
---|
| 2122 | elif (is_number(scs_elem)):
|
---|
| 2123 | # single channel given
|
---|
| 2124 | crange_list.append([float(scs_elem), float(scs_elem)])
|
---|
| 2125 | else:
|
---|
| 2126 | raise RuntimeError("Invalid channel selection.")
|
---|
[2882] | 2127 |
|
---|
[2887] | 2128 | else: #(ti_sep_length == 2)
|
---|
| 2129 | expr0 = ti_sep[0].strip()
|
---|
| 2130 | expr1 = ti_sep[1].strip()
|
---|
[2882] | 2131 |
|
---|
[2887] | 2132 | if is_number(expr0) and is_number(expr1):
|
---|
| 2133 | # 'a~b'
|
---|
| 2134 | expr_pmin = min(float(expr0), float(expr1))
|
---|
| 2135 | expr_pmax = max(float(expr0), float(expr1))
|
---|
[2882] | 2136 |
|
---|
[2887] | 2137 | elif is_number(expr0) and is_frequency(expr1):
|
---|
| 2138 | # 'a~b*Hz'
|
---|
| 2139 | (expr_f0, expr_f1) = get_freq_by_string(expr0, expr1)
|
---|
| 2140 | expr_p0 = coord.to_pixel(expr_f0)
|
---|
| 2141 | expr_p1 = coord.to_pixel(expr_f1)
|
---|
| 2142 | expr_pmin = min(expr_p0, expr_p1)
|
---|
| 2143 | expr_pmax = max(expr_p0, expr_p1)
|
---|
[2882] | 2144 |
|
---|
[2887] | 2145 | elif is_number(expr0) and is_velocity(expr1):
|
---|
| 2146 | # 'a~b*m/s'
|
---|
[2909] | 2147 | restf = self.get_restfreqs()[molid][0]
|
---|
[2887] | 2148 | (expr_v0, expr_v1) = get_velocity_by_string(expr0, expr1)
|
---|
[2897] | 2149 | dppl = self.get_doppler()
|
---|
| 2150 | expr_f0 = get_frequency_by_velocity(restf, expr_v0, dppl)
|
---|
| 2151 | expr_f1 = get_frequency_by_velocity(restf, expr_v1, dppl)
|
---|
[2887] | 2152 | expr_p0 = coord.to_pixel(expr_f0)
|
---|
| 2153 | expr_p1 = coord.to_pixel(expr_f1)
|
---|
| 2154 | expr_pmin = min(expr_p0, expr_p1)
|
---|
| 2155 | expr_pmax = max(expr_p0, expr_p1)
|
---|
[2882] | 2156 |
|
---|
[2887] | 2157 | else:
|
---|
| 2158 | # cases such as 'aGHz~bkm/s' are not allowed now
|
---|
| 2159 | raise RuntimeError("Invalid channel selection.")
|
---|
[2882] | 2160 |
|
---|
[2887] | 2161 | cmin = max(pmin, expr_pmin)
|
---|
| 2162 | cmax = min(pmax, expr_pmax)
|
---|
| 2163 | # if the given range of channel selection has overwrap with
|
---|
| 2164 | # that of current spw, output the overwrap area.
|
---|
| 2165 | if (cmin <= cmax):
|
---|
| 2166 | cmin = float(int(cmin + 0.5))
|
---|
| 2167 | cmax = float(int(cmax + 0.5))
|
---|
| 2168 | crange_list.append([cmin, cmax])
|
---|
[2882] | 2169 |
|
---|
| 2170 | if (len(crange_list) == 0):
|
---|
| 2171 | crange_list.append([])
|
---|
| 2172 |
|
---|
[2910] | 2173 | if (len(crange_list[0]) > 0):
|
---|
| 2174 | if res.has_key(spw):
|
---|
| 2175 | res[spw].extend(crange_list)
|
---|
| 2176 | else:
|
---|
| 2177 | res[spw] = crange_list
|
---|
[2882] | 2178 |
|
---|
[2887] | 2179 | for spw in res.keys():
|
---|
[2932] | 2180 | if spw in valid_ifs:
|
---|
[2933] | 2181 | # remove duplicated channel ranges
|
---|
[2932] | 2182 | for i in reversed(xrange(len(res[spw]))):
|
---|
| 2183 | for j in xrange(i):
|
---|
[2933] | 2184 | if ((res[spw][i][0]-res[spw][j][1])*(res[spw][i][1]-res[spw][j][0]) <= 0) or \
|
---|
| 2185 | (min(abs(res[spw][i][0]-res[spw][j][1]),abs(res[spw][j][0]-res[spw][i][1])) == 1):
|
---|
[2935] | 2186 | asaplog.post()
|
---|
| 2187 | merge_warn_mesg = "Spw " + str(spw) + ": overwrapping channel ranges are merged."
|
---|
| 2188 | asaplog.push(merge_warn_mesg)
|
---|
| 2189 | asaplog.post('WARN')
|
---|
[2932] | 2190 | res[spw][j][0] = min(res[spw][i][0], res[spw][j][0])
|
---|
| 2191 | res[spw][j][1] = max(res[spw][i][1], res[spw][j][1])
|
---|
| 2192 | res[spw].pop(i)
|
---|
| 2193 | break
|
---|
| 2194 | else:
|
---|
[2887] | 2195 | del res[spw]
|
---|
| 2196 |
|
---|
| 2197 | if len(res) == 0:
|
---|
| 2198 | raise RuntimeError("No valid spw.")
|
---|
| 2199 |
|
---|
[2882] | 2200 | # restore original values
|
---|
[2892] | 2201 | self.set_unit(orig_unit)
|
---|
[2891] | 2202 | if restfreq is not None:
|
---|
[2892] | 2203 | self._setmolidcol_list(orig_molids)
|
---|
| 2204 | if frame is not None:
|
---|
| 2205 | self.set_freqframe(orig_frame)
|
---|
| 2206 | if doppler is not None:
|
---|
| 2207 | self.set_doppler(orig_doppler)
|
---|
[2882] | 2208 |
|
---|
| 2209 | return res
|
---|
[2890] | 2210 |
|
---|
[2882] | 2211 | @asaplog_post_dec
|
---|
| 2212 | def get_first_rowno_by_if(self, ifno):
|
---|
| 2213 | found = False
|
---|
| 2214 | for irow in xrange(self.nrow()):
|
---|
| 2215 | if (self.getif(irow) == ifno):
|
---|
| 2216 | res = irow
|
---|
| 2217 | found = True
|
---|
| 2218 | break
|
---|
| 2219 |
|
---|
[2926] | 2220 | if not found: raise RuntimeError("No valid spw.")
|
---|
[2882] | 2221 |
|
---|
| 2222 | return res
|
---|
| 2223 |
|
---|
| 2224 | @asaplog_post_dec
|
---|
| 2225 | def _get_coordinate_list(self):
|
---|
| 2226 | res = []
|
---|
| 2227 | spws = self.getifnos()
|
---|
| 2228 | for spw in spws:
|
---|
| 2229 | elem = {}
|
---|
| 2230 | elem['if'] = spw
|
---|
| 2231 | elem['coord'] = self.get_coordinate(self.get_first_rowno_by_if(spw))
|
---|
| 2232 | res.append(elem)
|
---|
| 2233 |
|
---|
| 2234 | return res
|
---|
| 2235 |
|
---|
| 2236 | @asaplog_post_dec
|
---|
[2349] | 2237 | def parse_maskexpr(self, maskstring):
|
---|
[2013] | 2238 | """
|
---|
| 2239 | Parse CASA type mask selection syntax (IF dependent).
|
---|
| 2240 |
|
---|
| 2241 | Parameters:
|
---|
| 2242 | maskstring : A string mask selection expression.
|
---|
| 2243 | A comma separated selections mean different IF -
|
---|
| 2244 | channel combinations. IFs and channel selections
|
---|
| 2245 | are partitioned by a colon, ':'.
|
---|
| 2246 | examples:
|
---|
[2015] | 2247 | '' = all IFs (all channels)
|
---|
[2013] | 2248 | '<2,4~6,9' = IFs 0,1,4,5,6,9 (all channels)
|
---|
| 2249 | '3:3~45;60' = channels 3 to 45 and 60 in IF 3
|
---|
| 2250 | '0~1:2~6,8' = channels 2 to 6 in IFs 0,1, and
|
---|
| 2251 | all channels in IF8
|
---|
| 2252 | Returns:
|
---|
| 2253 | A dictionary of selected (valid) IF and masklist pairs,
|
---|
| 2254 | e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]}
|
---|
| 2255 | """
|
---|
| 2256 | if not isinstance(maskstring,str):
|
---|
| 2257 | asaplog.post()
|
---|
[2611] | 2258 | asaplog.push("Mask expression should be a string.")
|
---|
[2013] | 2259 | asaplog.post("ERROR")
|
---|
| 2260 |
|
---|
| 2261 | valid_ifs = self.getifnos()
|
---|
| 2262 | frequnit = self.get_unit()
|
---|
| 2263 | seldict = {}
|
---|
[2015] | 2264 | if maskstring == "":
|
---|
| 2265 | maskstring = str(valid_ifs)[1:-1]
|
---|
[2611] | 2266 | ## split each selection "IF range[:CHAN range]"
|
---|
[2867] | 2267 | # split maskstring by "<spaces>,<spaces>"
|
---|
| 2268 | comma_sep = re.compile('\s*,\s*')
|
---|
| 2269 | sellist = comma_sep.split(maskstring)
|
---|
| 2270 | # separator by "<spaces>:<spaces>"
|
---|
| 2271 | collon_sep = re.compile('\s*:\s*')
|
---|
[2013] | 2272 | for currselstr in sellist:
|
---|
[2867] | 2273 | selset = collon_sep.split(currselstr)
|
---|
[2013] | 2274 | # spw and mask string (may include ~, < or >)
|
---|
[2349] | 2275 | spwmasklist = self._parse_selection(selset[0], typestr='integer',
|
---|
[2611] | 2276 | minval=min(valid_ifs),
|
---|
[2349] | 2277 | maxval=max(valid_ifs))
|
---|
[2013] | 2278 | for spwlist in spwmasklist:
|
---|
| 2279 | selspws = []
|
---|
| 2280 | for ispw in range(spwlist[0],spwlist[1]+1):
|
---|
| 2281 | # Put into the list only if ispw exists
|
---|
| 2282 | if valid_ifs.count(ispw):
|
---|
| 2283 | selspws.append(ispw)
|
---|
| 2284 | del spwmasklist, spwlist
|
---|
| 2285 |
|
---|
| 2286 | # parse frequency mask list
|
---|
| 2287 | if len(selset) > 1:
|
---|
[2349] | 2288 | freqmasklist = self._parse_selection(selset[1], typestr='float',
|
---|
| 2289 | offset=0.)
|
---|
[2013] | 2290 | else:
|
---|
| 2291 | # want to select the whole spectrum
|
---|
| 2292 | freqmasklist = [None]
|
---|
| 2293 |
|
---|
| 2294 | ## define a dictionary of spw - masklist combination
|
---|
| 2295 | for ispw in selspws:
|
---|
| 2296 | #print "working on", ispw
|
---|
| 2297 | spwstr = str(ispw)
|
---|
| 2298 | if len(selspws) == 0:
|
---|
| 2299 | # empty spw
|
---|
| 2300 | continue
|
---|
| 2301 | else:
|
---|
| 2302 | ## want to get min and max of the spw and
|
---|
| 2303 | ## offset to set for '<' and '>'
|
---|
| 2304 | if frequnit == 'channel':
|
---|
| 2305 | minfreq = 0
|
---|
| 2306 | maxfreq = self.nchan(ifno=ispw)
|
---|
| 2307 | offset = 0.5
|
---|
| 2308 | else:
|
---|
| 2309 | ## This is ugly part. need improvement
|
---|
| 2310 | for ifrow in xrange(self.nrow()):
|
---|
| 2311 | if self.getif(ifrow) == ispw:
|
---|
| 2312 | #print "IF",ispw,"found in row =",ifrow
|
---|
| 2313 | break
|
---|
| 2314 | freqcoord = self.get_coordinate(ifrow)
|
---|
| 2315 | freqs = self._getabcissa(ifrow)
|
---|
| 2316 | minfreq = min(freqs)
|
---|
| 2317 | maxfreq = max(freqs)
|
---|
| 2318 | if len(freqs) == 1:
|
---|
| 2319 | offset = 0.5
|
---|
| 2320 | elif frequnit.find('Hz') > 0:
|
---|
[2349] | 2321 | offset = abs(freqcoord.to_frequency(1,
|
---|
| 2322 | unit=frequnit)
|
---|
| 2323 | -freqcoord.to_frequency(0,
|
---|
| 2324 | unit=frequnit)
|
---|
| 2325 | )*0.5
|
---|
[2013] | 2326 | elif frequnit.find('m/s') > 0:
|
---|
[2349] | 2327 | offset = abs(freqcoord.to_velocity(1,
|
---|
| 2328 | unit=frequnit)
|
---|
| 2329 | -freqcoord.to_velocity(0,
|
---|
| 2330 | unit=frequnit)
|
---|
| 2331 | )*0.5
|
---|
[2013] | 2332 | else:
|
---|
| 2333 | asaplog.post()
|
---|
| 2334 | asaplog.push("Invalid frequency unit")
|
---|
| 2335 | asaplog.post("ERROR")
|
---|
| 2336 | del freqs, freqcoord, ifrow
|
---|
| 2337 | for freq in freqmasklist:
|
---|
| 2338 | selmask = freq or [minfreq, maxfreq]
|
---|
| 2339 | if selmask[0] == None:
|
---|
| 2340 | ## selection was "<freq[1]".
|
---|
| 2341 | if selmask[1] < minfreq:
|
---|
| 2342 | ## avoid adding region selection
|
---|
| 2343 | selmask = None
|
---|
| 2344 | else:
|
---|
| 2345 | selmask = [minfreq,selmask[1]-offset]
|
---|
| 2346 | elif selmask[1] == None:
|
---|
| 2347 | ## selection was ">freq[0]"
|
---|
| 2348 | if selmask[0] > maxfreq:
|
---|
| 2349 | ## avoid adding region selection
|
---|
| 2350 | selmask = None
|
---|
| 2351 | else:
|
---|
| 2352 | selmask = [selmask[0]+offset,maxfreq]
|
---|
| 2353 | if selmask:
|
---|
| 2354 | if not seldict.has_key(spwstr):
|
---|
| 2355 | # new spw selection
|
---|
| 2356 | seldict[spwstr] = []
|
---|
| 2357 | seldict[spwstr] += [selmask]
|
---|
| 2358 | del minfreq,maxfreq,offset,freq,selmask
|
---|
| 2359 | del spwstr
|
---|
| 2360 | del freqmasklist
|
---|
| 2361 | del valid_ifs
|
---|
| 2362 | if len(seldict) == 0:
|
---|
| 2363 | asaplog.post()
|
---|
[2349] | 2364 | asaplog.push("No valid selection in the mask expression: "
|
---|
| 2365 | +maskstring)
|
---|
[2013] | 2366 | asaplog.post("WARN")
|
---|
| 2367 | return None
|
---|
| 2368 | msg = "Selected masklist:\n"
|
---|
| 2369 | for sif, lmask in seldict.iteritems():
|
---|
| 2370 | msg += " IF"+sif+" - "+str(lmask)+"\n"
|
---|
| 2371 | asaplog.push(msg)
|
---|
| 2372 | return seldict
|
---|
| 2373 |
|
---|
[2611] | 2374 | @asaplog_post_dec
|
---|
| 2375 | def parse_idx_selection(self, mode, selexpr):
|
---|
| 2376 | """
|
---|
| 2377 | Parse CASA type mask selection syntax of SCANNO, IFNO, POLNO,
|
---|
| 2378 | BEAMNO, and row number
|
---|
| 2379 |
|
---|
| 2380 | Parameters:
|
---|
| 2381 | mode : which column to select.
|
---|
| 2382 | ['scan',|'if'|'pol'|'beam'|'row']
|
---|
| 2383 | selexpr : A comma separated selection expression.
|
---|
| 2384 | examples:
|
---|
| 2385 | '' = all (returns [])
|
---|
| 2386 | '<2,4~6,9' = indices less than 2, 4 to 6 and 9
|
---|
| 2387 | (returns [0,1,4,5,6,9])
|
---|
| 2388 | Returns:
|
---|
| 2389 | A List of selected indices
|
---|
| 2390 | """
|
---|
| 2391 | if selexpr == "":
|
---|
| 2392 | return []
|
---|
| 2393 | valid_modes = {'s': 'scan', 'i': 'if', 'p': 'pol',
|
---|
| 2394 | 'b': 'beam', 'r': 'row'}
|
---|
| 2395 | smode = mode.lower()[0]
|
---|
| 2396 | if not (smode in valid_modes.keys()):
|
---|
| 2397 | msg = "Invalid mode '%s'. Valid modes are %s" %\
|
---|
| 2398 | (mode, str(valid_modes.values()))
|
---|
| 2399 | asaplog.post()
|
---|
| 2400 | asaplog.push(msg)
|
---|
| 2401 | asaplog.post("ERROR")
|
---|
| 2402 | mode = valid_modes[smode]
|
---|
| 2403 | minidx = None
|
---|
| 2404 | maxidx = None
|
---|
| 2405 | if smode == 'r':
|
---|
| 2406 | minidx = 0
|
---|
| 2407 | maxidx = self.nrow()
|
---|
| 2408 | else:
|
---|
| 2409 | idx = getattr(self,"get"+mode+"nos")()
|
---|
| 2410 | minidx = min(idx)
|
---|
| 2411 | maxidx = max(idx)
|
---|
| 2412 | del idx
|
---|
[2867] | 2413 | # split selexpr by "<spaces>,<spaces>"
|
---|
| 2414 | comma_sep = re.compile('\s*,\s*')
|
---|
| 2415 | sellist = comma_sep.split(selexpr)
|
---|
[2611] | 2416 | idxlist = []
|
---|
| 2417 | for currselstr in sellist:
|
---|
| 2418 | # single range (may include ~, < or >)
|
---|
| 2419 | currlist = self._parse_selection(currselstr, typestr='integer',
|
---|
| 2420 | minval=minidx,maxval=maxidx)
|
---|
| 2421 | for thelist in currlist:
|
---|
| 2422 | idxlist += range(thelist[0],thelist[1]+1)
|
---|
[2932] | 2423 | # remove duplicated elements after first ones
|
---|
| 2424 | for i in reversed(xrange(len(idxlist))):
|
---|
| 2425 | if idxlist.index(idxlist[i]) < i:
|
---|
| 2426 | idxlist.pop(i)
|
---|
[2611] | 2427 | msg = "Selected %s: %s" % (mode.upper()+"NO", str(idxlist))
|
---|
| 2428 | asaplog.push(msg)
|
---|
| 2429 | return idxlist
|
---|
| 2430 |
|
---|
[2349] | 2431 | def _parse_selection(self, selstr, typestr='float', offset=0.,
|
---|
[2351] | 2432 | minval=None, maxval=None):
|
---|
[2013] | 2433 | """
|
---|
| 2434 | Parameters:
|
---|
| 2435 | selstr : The Selection string, e.g., '<3;5~7;100~103;9'
|
---|
| 2436 | typestr : The type of the values in returned list
|
---|
| 2437 | ('integer' or 'float')
|
---|
| 2438 | offset : The offset value to subtract from or add to
|
---|
| 2439 | the boundary value if the selection string
|
---|
[2611] | 2440 | includes '<' or '>' [Valid only for typestr='float']
|
---|
[2013] | 2441 | minval, maxval : The minimum/maximum values to set if the
|
---|
| 2442 | selection string includes '<' or '>'.
|
---|
| 2443 | The list element is filled with None by default.
|
---|
| 2444 | Returns:
|
---|
| 2445 | A list of min/max pair of selections.
|
---|
| 2446 | Example:
|
---|
[2611] | 2447 | _parse_selection('<3;5~7;9',typestr='int',minval=0)
|
---|
| 2448 | --> returns [[0,2],[5,7],[9,9]]
|
---|
| 2449 | _parse_selection('<3;5~7;9',typestr='float',offset=0.5,minval=0)
|
---|
| 2450 | --> returns [[0.,2.5],[5.0,7.0],[9.,9.]]
|
---|
[2013] | 2451 | """
|
---|
[2867] | 2452 | # split selstr by '<spaces>;<spaces>'
|
---|
| 2453 | semi_sep = re.compile('\s*;\s*')
|
---|
| 2454 | selgroups = semi_sep.split(selstr)
|
---|
[2013] | 2455 | sellists = []
|
---|
| 2456 | if typestr.lower().startswith('int'):
|
---|
| 2457 | formatfunc = int
|
---|
[2611] | 2458 | offset = 1
|
---|
[2013] | 2459 | else:
|
---|
| 2460 | formatfunc = float
|
---|
| 2461 |
|
---|
| 2462 | for currsel in selgroups:
|
---|
[2867] | 2463 | if currsel.strip() == '*' or len(currsel.strip()) == 0:
|
---|
| 2464 | minsel = minval
|
---|
| 2465 | maxsel = maxval
|
---|
[2013] | 2466 | if currsel.find('~') > 0:
|
---|
[2611] | 2467 | # val0 <= x <= val1
|
---|
[2013] | 2468 | minsel = formatfunc(currsel.split('~')[0].strip())
|
---|
[2867] | 2469 | maxsel = formatfunc(currsel.split('~')[1].strip())
|
---|
[2611] | 2470 | elif currsel.strip().find('<=') > -1:
|
---|
| 2471 | bound = currsel.split('<=')
|
---|
| 2472 | try: # try "x <= val"
|
---|
| 2473 | minsel = minval
|
---|
| 2474 | maxsel = formatfunc(bound[1].strip())
|
---|
| 2475 | except ValueError: # now "val <= x"
|
---|
| 2476 | minsel = formatfunc(bound[0].strip())
|
---|
| 2477 | maxsel = maxval
|
---|
| 2478 | elif currsel.strip().find('>=') > -1:
|
---|
| 2479 | bound = currsel.split('>=')
|
---|
| 2480 | try: # try "x >= val"
|
---|
| 2481 | minsel = formatfunc(bound[1].strip())
|
---|
| 2482 | maxsel = maxval
|
---|
| 2483 | except ValueError: # now "val >= x"
|
---|
| 2484 | minsel = minval
|
---|
| 2485 | maxsel = formatfunc(bound[0].strip())
|
---|
| 2486 | elif currsel.strip().find('<') > -1:
|
---|
| 2487 | bound = currsel.split('<')
|
---|
| 2488 | try: # try "x < val"
|
---|
| 2489 | minsel = minval
|
---|
| 2490 | maxsel = formatfunc(bound[1].strip()) \
|
---|
| 2491 | - formatfunc(offset)
|
---|
| 2492 | except ValueError: # now "val < x"
|
---|
| 2493 | minsel = formatfunc(bound[0].strip()) \
|
---|
[2013] | 2494 | + formatfunc(offset)
|
---|
[2611] | 2495 | maxsel = maxval
|
---|
| 2496 | elif currsel.strip().find('>') > -1:
|
---|
| 2497 | bound = currsel.split('>')
|
---|
| 2498 | try: # try "x > val"
|
---|
| 2499 | minsel = formatfunc(bound[1].strip()) \
|
---|
| 2500 | + formatfunc(offset)
|
---|
| 2501 | maxsel = maxval
|
---|
| 2502 | except ValueError: # now "val > x"
|
---|
| 2503 | minsel = minval
|
---|
| 2504 | maxsel = formatfunc(bound[0].strip()) \
|
---|
| 2505 | - formatfunc(offset)
|
---|
[2013] | 2506 | else:
|
---|
| 2507 | minsel = formatfunc(currsel)
|
---|
| 2508 | maxsel = formatfunc(currsel)
|
---|
| 2509 | sellists.append([minsel,maxsel])
|
---|
| 2510 | return sellists
|
---|
| 2511 |
|
---|
[1819] | 2512 | # def get_restfreqs(self):
|
---|
| 2513 | # """
|
---|
| 2514 | # Get the restfrequency(s) stored in this scantable.
|
---|
| 2515 | # The return value(s) are always of unit 'Hz'
|
---|
| 2516 | # Parameters:
|
---|
| 2517 | # none
|
---|
| 2518 | # Returns:
|
---|
| 2519 | # a list of doubles
|
---|
| 2520 | # """
|
---|
| 2521 | # return list(self._getrestfreqs())
|
---|
| 2522 |
|
---|
| 2523 | def get_restfreqs(self, ids=None):
|
---|
[1846] | 2524 | """\
|
---|
[256] | 2525 | Get the restfrequency(s) stored in this scantable.
|
---|
| 2526 | The return value(s) are always of unit 'Hz'
|
---|
[1846] | 2527 |
|
---|
[256] | 2528 | Parameters:
|
---|
[1846] | 2529 |
|
---|
[1819] | 2530 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to
|
---|
| 2531 | be retrieved
|
---|
[1846] | 2532 |
|
---|
[256] | 2533 | Returns:
|
---|
[1846] | 2534 |
|
---|
[1819] | 2535 | dictionary containing ids and a list of doubles for each id
|
---|
[1846] | 2536 |
|
---|
[256] | 2537 | """
|
---|
[1819] | 2538 | if ids is None:
|
---|
[2349] | 2539 | rfreqs = {}
|
---|
[1819] | 2540 | idlist = self.getmolnos()
|
---|
| 2541 | for i in idlist:
|
---|
[2349] | 2542 | rfreqs[i] = list(self._getrestfreqs(i))
|
---|
[1819] | 2543 | return rfreqs
|
---|
| 2544 | else:
|
---|
[2349] | 2545 | if type(ids) == list or type(ids) == tuple:
|
---|
| 2546 | rfreqs = {}
|
---|
[1819] | 2547 | for i in ids:
|
---|
[2349] | 2548 | rfreqs[i] = list(self._getrestfreqs(i))
|
---|
[1819] | 2549 | return rfreqs
|
---|
| 2550 | else:
|
---|
| 2551 | return list(self._getrestfreqs(ids))
|
---|
[102] | 2552 |
|
---|
[2349] | 2553 | @asaplog_post_dec
|
---|
[931] | 2554 | def set_restfreqs(self, freqs=None, unit='Hz'):
|
---|
[1846] | 2555 | """\
|
---|
[931] | 2556 | Set or replace the restfrequency specified and
|
---|
[1938] | 2557 | if the 'freqs' argument holds a scalar,
|
---|
[931] | 2558 | then that rest frequency will be applied to all the selected
|
---|
| 2559 | data. If the 'freqs' argument holds
|
---|
| 2560 | a vector, then it MUST be of equal or smaller length than
|
---|
| 2561 | the number of IFs (and the available restfrequencies will be
|
---|
| 2562 | replaced by this vector). In this case, *all* data have
|
---|
| 2563 | the restfrequency set per IF according
|
---|
| 2564 | to the corresponding value you give in the 'freqs' vector.
|
---|
[1118] | 2565 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and
|
---|
[931] | 2566 | IF 1 gets restfreq 2e9.
|
---|
[1846] | 2567 |
|
---|
[1395] | 2568 | You can also specify the frequencies via a linecatalog.
|
---|
[1153] | 2569 |
|
---|
[931] | 2570 | Parameters:
|
---|
[1846] | 2571 |
|
---|
[931] | 2572 | freqs: list of rest frequency values or string idenitfiers
|
---|
[1855] | 2573 |
|
---|
[931] | 2574 | unit: unit for rest frequency (default 'Hz')
|
---|
[402] | 2575 |
|
---|
[1846] | 2576 |
|
---|
| 2577 | Example::
|
---|
| 2578 |
|
---|
[1819] | 2579 | # set the given restfrequency for the all currently selected IFs
|
---|
[931] | 2580 | scan.set_restfreqs(freqs=1.4e9)
|
---|
[1845] | 2581 | # set restfrequencies for the n IFs (n > 1) in the order of the
|
---|
| 2582 | # list, i.e
|
---|
| 2583 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9
|
---|
| 2584 | # len(list_of_restfreqs) == nIF
|
---|
| 2585 | # for nIF == 1 the following will set multiple restfrequency for
|
---|
| 2586 | # that IF
|
---|
[1819] | 2587 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9])
|
---|
[1845] | 2588 | # set multiple restfrequencies per IF. as a list of lists where
|
---|
| 2589 | # the outer list has nIF elements, the inner s arbitrary
|
---|
| 2590 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]])
|
---|
[391] | 2591 |
|
---|
[1846] | 2592 | *Note*:
|
---|
[1845] | 2593 |
|
---|
[931] | 2594 | To do more sophisticate Restfrequency setting, e.g. on a
|
---|
| 2595 | source and IF basis, use scantable.set_selection() before using
|
---|
[1846] | 2596 | this function::
|
---|
[931] | 2597 |
|
---|
[1846] | 2598 | # provided your scantable is called scan
|
---|
| 2599 | selection = selector()
|
---|
[2431] | 2600 | selection.set_name('ORION*')
|
---|
[1846] | 2601 | selection.set_ifs([1])
|
---|
| 2602 | scan.set_selection(selection)
|
---|
| 2603 | scan.set_restfreqs(freqs=86.6e9)
|
---|
| 2604 |
|
---|
[931] | 2605 | """
|
---|
| 2606 | varlist = vars()
|
---|
[1157] | 2607 | from asap import linecatalog
|
---|
| 2608 | # simple value
|
---|
[1118] | 2609 | if isinstance(freqs, int) or isinstance(freqs, float):
|
---|
[1845] | 2610 | self._setrestfreqs([freqs], [""], unit)
|
---|
[1157] | 2611 | # list of values
|
---|
[1118] | 2612 | elif isinstance(freqs, list) or isinstance(freqs, tuple):
|
---|
[1157] | 2613 | # list values are scalars
|
---|
[1118] | 2614 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float):
|
---|
[1845] | 2615 | if len(freqs) == 1:
|
---|
| 2616 | self._setrestfreqs(freqs, [""], unit)
|
---|
| 2617 | else:
|
---|
| 2618 | # allow the 'old' mode of setting mulitple IFs
|
---|
| 2619 | savesel = self._getselection()
|
---|
[2599] | 2620 | sel = self.get_selection()
|
---|
[1845] | 2621 | iflist = self.getifnos()
|
---|
| 2622 | if len(freqs)>len(iflist):
|
---|
| 2623 | raise ValueError("number of elements in list of list "
|
---|
| 2624 | "exeeds the current IF selections")
|
---|
| 2625 | iflist = self.getifnos()
|
---|
| 2626 | for i, fval in enumerate(freqs):
|
---|
| 2627 | sel.set_ifs(iflist[i])
|
---|
| 2628 | self._setselection(sel)
|
---|
| 2629 | self._setrestfreqs([fval], [""], unit)
|
---|
| 2630 | self._setselection(savesel)
|
---|
| 2631 |
|
---|
| 2632 | # list values are dict, {'value'=, 'name'=)
|
---|
[1157] | 2633 | elif isinstance(freqs[-1], dict):
|
---|
[1845] | 2634 | values = []
|
---|
| 2635 | names = []
|
---|
| 2636 | for d in freqs:
|
---|
| 2637 | values.append(d["value"])
|
---|
| 2638 | names.append(d["name"])
|
---|
| 2639 | self._setrestfreqs(values, names, unit)
|
---|
[1819] | 2640 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple):
|
---|
[1157] | 2641 | savesel = self._getselection()
|
---|
[2599] | 2642 | sel = self.get_selection()
|
---|
[1322] | 2643 | iflist = self.getifnos()
|
---|
[1819] | 2644 | if len(freqs)>len(iflist):
|
---|
[1845] | 2645 | raise ValueError("number of elements in list of list exeeds"
|
---|
| 2646 | " the current IF selections")
|
---|
| 2647 | for i, fval in enumerate(freqs):
|
---|
[1322] | 2648 | sel.set_ifs(iflist[i])
|
---|
[1259] | 2649 | self._setselection(sel)
|
---|
[1845] | 2650 | self._setrestfreqs(fval, [""], unit)
|
---|
[1157] | 2651 | self._setselection(savesel)
|
---|
| 2652 | # freqs are to be taken from a linecatalog
|
---|
[1153] | 2653 | elif isinstance(freqs, linecatalog):
|
---|
| 2654 | savesel = self._getselection()
|
---|
[2599] | 2655 | sel = self.get_selection()
|
---|
[1153] | 2656 | for i in xrange(freqs.nrow()):
|
---|
[1322] | 2657 | sel.set_ifs(iflist[i])
|
---|
[1153] | 2658 | self._setselection(sel)
|
---|
[1845] | 2659 | self._setrestfreqs([freqs.get_frequency(i)],
|
---|
| 2660 | [freqs.get_name(i)], "MHz")
|
---|
[1153] | 2661 | # ensure that we are not iterating past nIF
|
---|
| 2662 | if i == self.nif()-1: break
|
---|
| 2663 | self._setselection(savesel)
|
---|
[931] | 2664 | else:
|
---|
| 2665 | return
|
---|
| 2666 | self._add_history("set_restfreqs", varlist)
|
---|
| 2667 |
|
---|
[2349] | 2668 | @asaplog_post_dec
|
---|
[1360] | 2669 | def shift_refpix(self, delta):
|
---|
[1846] | 2670 | """\
|
---|
[1589] | 2671 | Shift the reference pixel of the Spectra Coordinate by an
|
---|
| 2672 | integer amount.
|
---|
[1846] | 2673 |
|
---|
[1589] | 2674 | Parameters:
|
---|
[1846] | 2675 |
|
---|
[1589] | 2676 | delta: the amount to shift by
|
---|
[1846] | 2677 |
|
---|
| 2678 | *Note*:
|
---|
| 2679 |
|
---|
[1589] | 2680 | Be careful using this with broadband data.
|
---|
[1846] | 2681 |
|
---|
[1360] | 2682 | """
|
---|
[2349] | 2683 | varlist = vars()
|
---|
[1731] | 2684 | Scantable.shift_refpix(self, delta)
|
---|
[2349] | 2685 | s._add_history("shift_refpix", varlist)
|
---|
[931] | 2686 |
|
---|
[1862] | 2687 | @asaplog_post_dec
|
---|
[2820] | 2688 | def history(self, filename=None, nrows=-1, start=0):
|
---|
[1846] | 2689 | """\
|
---|
[1259] | 2690 | Print the history. Optionally to a file.
|
---|
[1846] | 2691 |
|
---|
[1348] | 2692 | Parameters:
|
---|
[1846] | 2693 |
|
---|
[1928] | 2694 | filename: The name of the file to save the history to.
|
---|
[1846] | 2695 |
|
---|
[1259] | 2696 | """
|
---|
[2820] | 2697 | n = self._historylength()
|
---|
| 2698 | if nrows == -1:
|
---|
| 2699 | nrows = n
|
---|
| 2700 | if start+nrows > n:
|
---|
| 2701 | nrows = nrows-start
|
---|
| 2702 | if n > 1000 and nrows == n:
|
---|
| 2703 | nrows = 1000
|
---|
| 2704 | start = n-1000
|
---|
| 2705 | asaplog.push("Warning: History has {0} entries. Displaying last "
|
---|
| 2706 | "1000".format(n))
|
---|
| 2707 | hist = list(self._gethistory(nrows, start))
|
---|
[794] | 2708 | out = "-"*80
|
---|
[484] | 2709 | for h in hist:
|
---|
[2820] | 2710 | if not h.strip():
|
---|
| 2711 | continue
|
---|
| 2712 | if h.find("---") >-1:
|
---|
| 2713 | continue
|
---|
[489] | 2714 | else:
|
---|
| 2715 | items = h.split("##")
|
---|
| 2716 | date = items[0]
|
---|
| 2717 | func = items[1]
|
---|
| 2718 | items = items[2:]
|
---|
[794] | 2719 | out += "\n"+date+"\n"
|
---|
| 2720 | out += "Function: %s\n Parameters:" % (func)
|
---|
[489] | 2721 | for i in items:
|
---|
[1938] | 2722 | if i == '':
|
---|
| 2723 | continue
|
---|
[489] | 2724 | s = i.split("=")
|
---|
[1118] | 2725 | out += "\n %s = %s" % (s[0], s[1])
|
---|
[2820] | 2726 | out = "\n".join([out, "*"*80])
|
---|
[1259] | 2727 | if filename is not None:
|
---|
| 2728 | if filename is "":
|
---|
| 2729 | filename = 'scantable_history.txt'
|
---|
| 2730 | filename = os.path.expandvars(os.path.expanduser(filename))
|
---|
| 2731 | if not os.path.isdir(filename):
|
---|
| 2732 | data = open(filename, 'w')
|
---|
| 2733 | data.write(out)
|
---|
| 2734 | data.close()
|
---|
| 2735 | else:
|
---|
| 2736 | msg = "Illegal file name '%s'." % (filename)
|
---|
[1859] | 2737 | raise IOError(msg)
|
---|
| 2738 | return page(out)
|
---|
[2349] | 2739 |
|
---|
[513] | 2740 | #
|
---|
| 2741 | # Maths business
|
---|
| 2742 | #
|
---|
[1862] | 2743 | @asaplog_post_dec
|
---|
[2818] | 2744 | def average_time(self, mask=None, scanav=False, weight='tint', align=False,
|
---|
| 2745 | avmode="NONE"):
|
---|
[1846] | 2746 | """\
|
---|
[2349] | 2747 | Return the (time) weighted average of a scan. Scans will be averaged
|
---|
| 2748 | only if the source direction (RA/DEC) is within 1' otherwise
|
---|
[1846] | 2749 |
|
---|
| 2750 | *Note*:
|
---|
| 2751 |
|
---|
[1070] | 2752 | in channels only - align if necessary
|
---|
[1846] | 2753 |
|
---|
[513] | 2754 | Parameters:
|
---|
[1846] | 2755 |
|
---|
[513] | 2756 | mask: an optional mask (only used for 'var' and 'tsys'
|
---|
| 2757 | weighting)
|
---|
[1855] | 2758 |
|
---|
[558] | 2759 | scanav: True averages each scan separately
|
---|
| 2760 | False (default) averages all scans together,
|
---|
[1855] | 2761 |
|
---|
[1099] | 2762 | weight: Weighting scheme.
|
---|
| 2763 | 'none' (mean no weight)
|
---|
| 2764 | 'var' (1/var(spec) weighted)
|
---|
| 2765 | 'tsys' (1/Tsys**2 weighted)
|
---|
| 2766 | 'tint' (integration time weighted)
|
---|
| 2767 | 'tintsys' (Tint/Tsys**2)
|
---|
| 2768 | 'median' ( median averaging)
|
---|
[535] | 2769 | The default is 'tint'
|
---|
[1855] | 2770 |
|
---|
[931] | 2771 | align: align the spectra in velocity before averaging. It takes
|
---|
| 2772 | the time of the first spectrum as reference time.
|
---|
[2818] | 2773 | avmode: 'SOURCE' - also select by source name - or
|
---|
| 2774 | 'NONE' (default). Not applicable for scanav=True or
|
---|
| 2775 | weight=median
|
---|
[1846] | 2776 |
|
---|
| 2777 | Example::
|
---|
| 2778 |
|
---|
[513] | 2779 | # time average the scantable without using a mask
|
---|
[710] | 2780 | newscan = scan.average_time()
|
---|
[1846] | 2781 |
|
---|
[513] | 2782 | """
|
---|
| 2783 | varlist = vars()
|
---|
[1593] | 2784 | weight = weight or 'TINT'
|
---|
| 2785 | mask = mask or ()
|
---|
[2818] | 2786 | scanav = (scanav and 'SCAN') or avmode.upper()
|
---|
[1118] | 2787 | scan = (self, )
|
---|
[1859] | 2788 |
|
---|
| 2789 | if align:
|
---|
| 2790 | scan = (self.freq_align(insitu=False), )
|
---|
[2818] | 2791 | asaplog.push("Note: Alignment is don on a source-by-source basis")
|
---|
| 2792 | asaplog.push("Note: Averaging (by default) is not")
|
---|
| 2793 | # we need to set it to SOURCE averaging here
|
---|
[1859] | 2794 | s = None
|
---|
| 2795 | if weight.upper() == 'MEDIAN':
|
---|
| 2796 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN',
|
---|
| 2797 | scanav))
|
---|
| 2798 | else:
|
---|
| 2799 | s = scantable(self._math._average(scan, mask, weight.upper(),
|
---|
| 2800 | scanav))
|
---|
[1099] | 2801 | s._add_history("average_time", varlist)
|
---|
[513] | 2802 | return s
|
---|
[710] | 2803 |
|
---|
[1862] | 2804 | @asaplog_post_dec
|
---|
[876] | 2805 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None):
|
---|
[1846] | 2806 | """\
|
---|
[513] | 2807 | Return a scan where all spectra are converted to either
|
---|
| 2808 | Jansky or Kelvin depending upon the flux units of the scan table.
|
---|
| 2809 | By default the function tries to look the values up internally.
|
---|
| 2810 | If it can't find them (or if you want to over-ride), you must
|
---|
| 2811 | specify EITHER jyperk OR eta (and D which it will try to look up
|
---|
| 2812 | also if you don't set it). jyperk takes precedence if you set both.
|
---|
[1846] | 2813 |
|
---|
[513] | 2814 | Parameters:
|
---|
[1846] | 2815 |
|
---|
[513] | 2816 | jyperk: the Jy / K conversion factor
|
---|
[1855] | 2817 |
|
---|
[513] | 2818 | eta: the aperture efficiency
|
---|
[1855] | 2819 |
|
---|
[1928] | 2820 | d: the geometric diameter (metres)
|
---|
[1855] | 2821 |
|
---|
[513] | 2822 | insitu: if False a new scantable is returned.
|
---|
| 2823 | Otherwise, the scaling is done in-situ
|
---|
| 2824 | The default is taken from .asaprc (False)
|
---|
[1846] | 2825 |
|
---|
[513] | 2826 | """
|
---|
| 2827 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 2828 | self._math._setinsitu(insitu)
|
---|
[513] | 2829 | varlist = vars()
|
---|
[1593] | 2830 | jyperk = jyperk or -1.0
|
---|
| 2831 | d = d or -1.0
|
---|
| 2832 | eta = eta or -1.0
|
---|
[876] | 2833 | s = scantable(self._math._convertflux(self, d, eta, jyperk))
|
---|
| 2834 | s._add_history("convert_flux", varlist)
|
---|
| 2835 | if insitu: self._assign(s)
|
---|
| 2836 | else: return s
|
---|
[513] | 2837 |
|
---|
[1862] | 2838 | @asaplog_post_dec
|
---|
[876] | 2839 | def gain_el(self, poly=None, filename="", method="linear", insitu=None):
|
---|
[1846] | 2840 | """\
|
---|
[513] | 2841 | Return a scan after applying a gain-elevation correction.
|
---|
| 2842 | The correction can be made via either a polynomial or a
|
---|
| 2843 | table-based interpolation (and extrapolation if necessary).
|
---|
| 2844 | You specify polynomial coefficients, an ascii table or neither.
|
---|
| 2845 | If you specify neither, then a polynomial correction will be made
|
---|
| 2846 | with built in coefficients known for certain telescopes (an error
|
---|
| 2847 | will occur if the instrument is not known).
|
---|
| 2848 | The data and Tsys are *divided* by the scaling factors.
|
---|
[1846] | 2849 |
|
---|
[513] | 2850 | Parameters:
|
---|
[1846] | 2851 |
|
---|
[513] | 2852 | poly: Polynomial coefficients (default None) to compute a
|
---|
| 2853 | gain-elevation correction as a function of
|
---|
| 2854 | elevation (in degrees).
|
---|
[1855] | 2855 |
|
---|
[513] | 2856 | filename: The name of an ascii file holding correction factors.
|
---|
| 2857 | The first row of the ascii file must give the column
|
---|
| 2858 | names and these MUST include columns
|
---|
[2431] | 2859 | 'ELEVATION' (degrees) and 'FACTOR' (multiply data
|
---|
[513] | 2860 | by this) somewhere.
|
---|
| 2861 | The second row must give the data type of the
|
---|
| 2862 | column. Use 'R' for Real and 'I' for Integer.
|
---|
| 2863 | An example file would be
|
---|
| 2864 | (actual factors are arbitrary) :
|
---|
| 2865 |
|
---|
| 2866 | TIME ELEVATION FACTOR
|
---|
| 2867 | R R R
|
---|
| 2868 | 0.1 0 0.8
|
---|
| 2869 | 0.2 20 0.85
|
---|
| 2870 | 0.3 40 0.9
|
---|
| 2871 | 0.4 60 0.85
|
---|
| 2872 | 0.5 80 0.8
|
---|
| 2873 | 0.6 90 0.75
|
---|
[1855] | 2874 |
|
---|
[513] | 2875 | method: Interpolation method when correcting from a table.
|
---|
[2431] | 2876 | Values are 'nearest', 'linear' (default), 'cubic'
|
---|
| 2877 | and 'spline'
|
---|
[1855] | 2878 |
|
---|
[513] | 2879 | insitu: if False a new scantable is returned.
|
---|
| 2880 | Otherwise, the scaling is done in-situ
|
---|
| 2881 | The default is taken from .asaprc (False)
|
---|
[1846] | 2882 |
|
---|
[513] | 2883 | """
|
---|
| 2884 |
|
---|
| 2885 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 2886 | self._math._setinsitu(insitu)
|
---|
[513] | 2887 | varlist = vars()
|
---|
[1593] | 2888 | poly = poly or ()
|
---|
[513] | 2889 | from os.path import expandvars
|
---|
| 2890 | filename = expandvars(filename)
|
---|
[876] | 2891 | s = scantable(self._math._gainel(self, poly, filename, method))
|
---|
| 2892 | s._add_history("gain_el", varlist)
|
---|
[1593] | 2893 | if insitu:
|
---|
| 2894 | self._assign(s)
|
---|
| 2895 | else:
|
---|
| 2896 | return s
|
---|
[710] | 2897 |
|
---|
[1862] | 2898 | @asaplog_post_dec
|
---|
[931] | 2899 | def freq_align(self, reftime=None, method='cubic', insitu=None):
|
---|
[1846] | 2900 | """\
|
---|
[513] | 2901 | Return a scan where all rows have been aligned in frequency/velocity.
|
---|
| 2902 | The alignment frequency frame (e.g. LSRK) is that set by function
|
---|
| 2903 | set_freqframe.
|
---|
[1846] | 2904 |
|
---|
[513] | 2905 | Parameters:
|
---|
[1855] | 2906 |
|
---|
[513] | 2907 | reftime: reference time to align at. By default, the time of
|
---|
| 2908 | the first row of data is used.
|
---|
[1855] | 2909 |
|
---|
[513] | 2910 | method: Interpolation method for regridding the spectra.
|
---|
[2431] | 2911 | Choose from 'nearest', 'linear', 'cubic' (default)
|
---|
| 2912 | and 'spline'
|
---|
[1855] | 2913 |
|
---|
[513] | 2914 | insitu: if False a new scantable is returned.
|
---|
| 2915 | Otherwise, the scaling is done in-situ
|
---|
| 2916 | The default is taken from .asaprc (False)
|
---|
[1846] | 2917 |
|
---|
[513] | 2918 | """
|
---|
[931] | 2919 | if insitu is None: insitu = rcParams["insitu"]
|
---|
[2429] | 2920 | oldInsitu = self._math._insitu()
|
---|
[876] | 2921 | self._math._setinsitu(insitu)
|
---|
[513] | 2922 | varlist = vars()
|
---|
[1593] | 2923 | reftime = reftime or ""
|
---|
[931] | 2924 | s = scantable(self._math._freq_align(self, reftime, method))
|
---|
[876] | 2925 | s._add_history("freq_align", varlist)
|
---|
[2429] | 2926 | self._math._setinsitu(oldInsitu)
|
---|
[2349] | 2927 | if insitu:
|
---|
| 2928 | self._assign(s)
|
---|
| 2929 | else:
|
---|
| 2930 | return s
|
---|
[513] | 2931 |
|
---|
[1862] | 2932 | @asaplog_post_dec
|
---|
[1725] | 2933 | def opacity(self, tau=None, insitu=None):
|
---|
[1846] | 2934 | """\
|
---|
[513] | 2935 | Apply an opacity correction. The data
|
---|
| 2936 | and Tsys are multiplied by the correction factor.
|
---|
[1846] | 2937 |
|
---|
[513] | 2938 | Parameters:
|
---|
[1855] | 2939 |
|
---|
[1689] | 2940 | tau: (list of) opacity from which the correction factor is
|
---|
[513] | 2941 | exp(tau*ZD)
|
---|
[1689] | 2942 | where ZD is the zenith-distance.
|
---|
| 2943 | If a list is provided, it has to be of length nIF,
|
---|
| 2944 | nIF*nPol or 1 and in order of IF/POL, e.g.
|
---|
| 2945 | [opif0pol0, opif0pol1, opif1pol0 ...]
|
---|
[1725] | 2946 | if tau is `None` the opacities are determined from a
|
---|
| 2947 | model.
|
---|
[1855] | 2948 |
|
---|
[513] | 2949 | insitu: if False a new scantable is returned.
|
---|
| 2950 | Otherwise, the scaling is done in-situ
|
---|
| 2951 | The default is taken from .asaprc (False)
|
---|
[1846] | 2952 |
|
---|
[513] | 2953 | """
|
---|
[2349] | 2954 | if insitu is None:
|
---|
| 2955 | insitu = rcParams['insitu']
|
---|
[876] | 2956 | self._math._setinsitu(insitu)
|
---|
[513] | 2957 | varlist = vars()
|
---|
[1689] | 2958 | if not hasattr(tau, "__len__"):
|
---|
| 2959 | tau = [tau]
|
---|
[876] | 2960 | s = scantable(self._math._opacity(self, tau))
|
---|
| 2961 | s._add_history("opacity", varlist)
|
---|
[2349] | 2962 | if insitu:
|
---|
| 2963 | self._assign(s)
|
---|
| 2964 | else:
|
---|
| 2965 | return s
|
---|
[513] | 2966 |
|
---|
[1862] | 2967 | @asaplog_post_dec
|
---|
[513] | 2968 | def bin(self, width=5, insitu=None):
|
---|
[1846] | 2969 | """\
|
---|
[513] | 2970 | Return a scan where all spectra have been binned up.
|
---|
[1846] | 2971 |
|
---|
[1348] | 2972 | Parameters:
|
---|
[1846] | 2973 |
|
---|
[513] | 2974 | width: The bin width (default=5) in pixels
|
---|
[1855] | 2975 |
|
---|
[513] | 2976 | insitu: if False a new scantable is returned.
|
---|
| 2977 | Otherwise, the scaling is done in-situ
|
---|
| 2978 | The default is taken from .asaprc (False)
|
---|
[1846] | 2979 |
|
---|
[513] | 2980 | """
|
---|
[2349] | 2981 | if insitu is None:
|
---|
| 2982 | insitu = rcParams['insitu']
|
---|
[876] | 2983 | self._math._setinsitu(insitu)
|
---|
[513] | 2984 | varlist = vars()
|
---|
[876] | 2985 | s = scantable(self._math._bin(self, width))
|
---|
[1118] | 2986 | s._add_history("bin", varlist)
|
---|
[1589] | 2987 | if insitu:
|
---|
| 2988 | self._assign(s)
|
---|
| 2989 | else:
|
---|
| 2990 | return s
|
---|
[513] | 2991 |
|
---|
[1862] | 2992 | @asaplog_post_dec
|
---|
[2672] | 2993 | def reshape(self, first, last, insitu=None):
|
---|
| 2994 | """Resize the band by providing first and last channel.
|
---|
| 2995 | This will cut off all channels outside [first, last].
|
---|
| 2996 | """
|
---|
| 2997 | if insitu is None:
|
---|
| 2998 | insitu = rcParams['insitu']
|
---|
| 2999 | varlist = vars()
|
---|
| 3000 | if last < 0:
|
---|
| 3001 | last = self.nchan()-1 + last
|
---|
| 3002 | s = None
|
---|
| 3003 | if insitu:
|
---|
| 3004 | s = self
|
---|
| 3005 | else:
|
---|
| 3006 | s = self.copy()
|
---|
| 3007 | s._reshape(first,last)
|
---|
| 3008 | s._add_history("reshape", varlist)
|
---|
| 3009 | if not insitu:
|
---|
| 3010 | return s
|
---|
| 3011 |
|
---|
| 3012 | @asaplog_post_dec
|
---|
[513] | 3013 | def resample(self, width=5, method='cubic', insitu=None):
|
---|
[1846] | 3014 | """\
|
---|
[1348] | 3015 | Return a scan where all spectra have been binned up.
|
---|
[1573] | 3016 |
|
---|
[1348] | 3017 | Parameters:
|
---|
[1846] | 3018 |
|
---|
[513] | 3019 | width: The bin width (default=5) in pixels
|
---|
[1855] | 3020 |
|
---|
[513] | 3021 | method: Interpolation method when correcting from a table.
|
---|
[2431] | 3022 | Values are 'nearest', 'linear', 'cubic' (default)
|
---|
| 3023 | and 'spline'
|
---|
[1855] | 3024 |
|
---|
[513] | 3025 | insitu: if False a new scantable is returned.
|
---|
| 3026 | Otherwise, the scaling is done in-situ
|
---|
| 3027 | The default is taken from .asaprc (False)
|
---|
[1846] | 3028 |
|
---|
[513] | 3029 | """
|
---|
[2349] | 3030 | if insitu is None:
|
---|
| 3031 | insitu = rcParams['insitu']
|
---|
[876] | 3032 | self._math._setinsitu(insitu)
|
---|
[513] | 3033 | varlist = vars()
|
---|
[876] | 3034 | s = scantable(self._math._resample(self, method, width))
|
---|
[1118] | 3035 | s._add_history("resample", varlist)
|
---|
[2349] | 3036 | if insitu:
|
---|
| 3037 | self._assign(s)
|
---|
| 3038 | else:
|
---|
| 3039 | return s
|
---|
[513] | 3040 |
|
---|
[1862] | 3041 | @asaplog_post_dec
|
---|
[946] | 3042 | def average_pol(self, mask=None, weight='none'):
|
---|
[1846] | 3043 | """\
|
---|
[946] | 3044 | Average the Polarisations together.
|
---|
[1846] | 3045 |
|
---|
[946] | 3046 | Parameters:
|
---|
[1846] | 3047 |
|
---|
[946] | 3048 | mask: An optional mask defining the region, where the
|
---|
| 3049 | averaging will be applied. The output will have all
|
---|
| 3050 | specified points masked.
|
---|
[1855] | 3051 |
|
---|
[946] | 3052 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec)
|
---|
| 3053 | weighted), or 'tsys' (1/Tsys**2 weighted)
|
---|
[1846] | 3054 |
|
---|
[946] | 3055 | """
|
---|
| 3056 | varlist = vars()
|
---|
[1593] | 3057 | mask = mask or ()
|
---|
[1010] | 3058 | s = scantable(self._math._averagepol(self, mask, weight.upper()))
|
---|
[1118] | 3059 | s._add_history("average_pol", varlist)
|
---|
[992] | 3060 | return s
|
---|
[513] | 3061 |
|
---|
[1862] | 3062 | @asaplog_post_dec
|
---|
[1145] | 3063 | def average_beam(self, mask=None, weight='none'):
|
---|
[1846] | 3064 | """\
|
---|
[1145] | 3065 | Average the Beams together.
|
---|
[1846] | 3066 |
|
---|
[1145] | 3067 | Parameters:
|
---|
| 3068 | mask: An optional mask defining the region, where the
|
---|
| 3069 | averaging will be applied. The output will have all
|
---|
| 3070 | specified points masked.
|
---|
[1855] | 3071 |
|
---|
[1145] | 3072 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec)
|
---|
| 3073 | weighted), or 'tsys' (1/Tsys**2 weighted)
|
---|
[1846] | 3074 |
|
---|
[1145] | 3075 | """
|
---|
| 3076 | varlist = vars()
|
---|
[1593] | 3077 | mask = mask or ()
|
---|
[1145] | 3078 | s = scantable(self._math._averagebeams(self, mask, weight.upper()))
|
---|
| 3079 | s._add_history("average_beam", varlist)
|
---|
| 3080 | return s
|
---|
| 3081 |
|
---|
[1586] | 3082 | def parallactify(self, pflag):
|
---|
[1846] | 3083 | """\
|
---|
[1843] | 3084 | Set a flag to indicate whether this data should be treated as having
|
---|
[1617] | 3085 | been 'parallactified' (total phase == 0.0)
|
---|
[1846] | 3086 |
|
---|
[1617] | 3087 | Parameters:
|
---|
[1855] | 3088 |
|
---|
[1843] | 3089 | pflag: Bool indicating whether to turn this on (True) or
|
---|
[1617] | 3090 | off (False)
|
---|
[1846] | 3091 |
|
---|
[1617] | 3092 | """
|
---|
[1586] | 3093 | varlist = vars()
|
---|
| 3094 | self._parallactify(pflag)
|
---|
| 3095 | self._add_history("parallactify", varlist)
|
---|
| 3096 |
|
---|
[1862] | 3097 | @asaplog_post_dec
|
---|
[992] | 3098 | def convert_pol(self, poltype=None):
|
---|
[1846] | 3099 | """\
|
---|
[992] | 3100 | Convert the data to a different polarisation type.
|
---|
[1565] | 3101 | Note that you will need cross-polarisation terms for most conversions.
|
---|
[1846] | 3102 |
|
---|
[992] | 3103 | Parameters:
|
---|
[1855] | 3104 |
|
---|
[992] | 3105 | poltype: The new polarisation type. Valid types are:
|
---|
[2431] | 3106 | 'linear', 'circular', 'stokes' and 'linpol'
|
---|
[1846] | 3107 |
|
---|
[992] | 3108 | """
|
---|
| 3109 | varlist = vars()
|
---|
[1859] | 3110 | s = scantable(self._math._convertpol(self, poltype))
|
---|
[1118] | 3111 | s._add_history("convert_pol", varlist)
|
---|
[992] | 3112 | return s
|
---|
| 3113 |
|
---|
[1862] | 3114 | @asaplog_post_dec
|
---|
[2269] | 3115 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False,
|
---|
| 3116 | insitu=None):
|
---|
[1846] | 3117 | """\
|
---|
[513] | 3118 | Smooth the spectrum by the specified kernel (conserving flux).
|
---|
[1846] | 3119 |
|
---|
[513] | 3120 | Parameters:
|
---|
[1846] | 3121 |
|
---|
[513] | 3122 | kernel: The type of smoothing kernel. Select from
|
---|
[1574] | 3123 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian'
|
---|
| 3124 | or 'poly'
|
---|
[1855] | 3125 |
|
---|
[513] | 3126 | width: The width of the kernel in pixels. For hanning this is
|
---|
| 3127 | ignored otherwise it defauls to 5 pixels.
|
---|
| 3128 | For 'gaussian' it is the Full Width Half
|
---|
| 3129 | Maximum. For 'boxcar' it is the full width.
|
---|
[1574] | 3130 | For 'rmedian' and 'poly' it is the half width.
|
---|
[1855] | 3131 |
|
---|
[1574] | 3132 | order: Optional parameter for 'poly' kernel (default is 2), to
|
---|
| 3133 | specify the order of the polnomial. Ignored by all other
|
---|
| 3134 | kernels.
|
---|
[1855] | 3135 |
|
---|
[1819] | 3136 | plot: plot the original and the smoothed spectra.
|
---|
| 3137 | In this each indivual fit has to be approved, by
|
---|
| 3138 | typing 'y' or 'n'
|
---|
[1855] | 3139 |
|
---|
[513] | 3140 | insitu: if False a new scantable is returned.
|
---|
| 3141 | Otherwise, the scaling is done in-situ
|
---|
| 3142 | The default is taken from .asaprc (False)
|
---|
[1846] | 3143 |
|
---|
[513] | 3144 | """
|
---|
| 3145 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 3146 | self._math._setinsitu(insitu)
|
---|
[513] | 3147 | varlist = vars()
|
---|
[1819] | 3148 |
|
---|
| 3149 | if plot: orgscan = self.copy()
|
---|
| 3150 |
|
---|
[1574] | 3151 | s = scantable(self._math._smooth(self, kernel.lower(), width, order))
|
---|
[876] | 3152 | s._add_history("smooth", varlist)
|
---|
[1819] | 3153 |
|
---|
[2610] | 3154 | action = 'H'
|
---|
[1819] | 3155 | if plot:
|
---|
[2150] | 3156 | from asap.asapplotter import new_asaplot
|
---|
| 3157 | theplot = new_asaplot(rcParams['plotter.gui'])
|
---|
[2535] | 3158 | from matplotlib import rc as rcp
|
---|
| 3159 | rcp('lines', linewidth=1)
|
---|
[2150] | 3160 | theplot.set_panels()
|
---|
[1819] | 3161 | ylab=s._get_ordinate_label()
|
---|
[2150] | 3162 | #theplot.palette(0,["#777777","red"])
|
---|
[1819] | 3163 | for r in xrange(s.nrow()):
|
---|
| 3164 | xsm=s._getabcissa(r)
|
---|
| 3165 | ysm=s._getspectrum(r)
|
---|
| 3166 | xorg=orgscan._getabcissa(r)
|
---|
| 3167 | yorg=orgscan._getspectrum(r)
|
---|
[2610] | 3168 | if action != "N": #skip plotting if rejecting all
|
---|
| 3169 | theplot.clear()
|
---|
| 3170 | theplot.hold()
|
---|
| 3171 | theplot.set_axes('ylabel',ylab)
|
---|
| 3172 | theplot.set_axes('xlabel',s._getabcissalabel(r))
|
---|
| 3173 | theplot.set_axes('title',s._getsourcename(r))
|
---|
| 3174 | theplot.set_line(label='Original',color="#777777")
|
---|
| 3175 | theplot.plot(xorg,yorg)
|
---|
| 3176 | theplot.set_line(label='Smoothed',color="red")
|
---|
| 3177 | theplot.plot(xsm,ysm)
|
---|
| 3178 | ### Ugly part for legend
|
---|
| 3179 | for i in [0,1]:
|
---|
| 3180 | theplot.subplots[0]['lines'].append(
|
---|
| 3181 | [theplot.subplots[0]['axes'].lines[i]]
|
---|
| 3182 | )
|
---|
| 3183 | theplot.release()
|
---|
| 3184 | ### Ugly part for legend
|
---|
| 3185 | theplot.subplots[0]['lines']=[]
|
---|
| 3186 | res = self._get_verify_action("Accept smoothing?",action)
|
---|
| 3187 | #print "IF%d, POL%d: got result = %s" %(s.getif(r),s.getpol(r),res)
|
---|
| 3188 | if r == 0: action = None
|
---|
| 3189 | #res = raw_input("Accept smoothing ([y]/n): ")
|
---|
[1819] | 3190 | if res.upper() == 'N':
|
---|
[2610] | 3191 | # reject for the current rows
|
---|
[1819] | 3192 | s._setspectrum(yorg, r)
|
---|
[2610] | 3193 | elif res.upper() == 'R':
|
---|
| 3194 | # reject all the following rows
|
---|
| 3195 | action = "N"
|
---|
| 3196 | s._setspectrum(yorg, r)
|
---|
| 3197 | elif res.upper() == 'A':
|
---|
| 3198 | # accept all the following rows
|
---|
| 3199 | break
|
---|
[2150] | 3200 | theplot.quit()
|
---|
| 3201 | del theplot
|
---|
[1819] | 3202 | del orgscan
|
---|
| 3203 |
|
---|
[876] | 3204 | if insitu: self._assign(s)
|
---|
| 3205 | else: return s
|
---|
[513] | 3206 |
|
---|
[2186] | 3207 | @asaplog_post_dec
|
---|
[2435] | 3208 | def regrid_channel(self, width=5, plot=False, insitu=None):
|
---|
| 3209 | """\
|
---|
| 3210 | Regrid the spectra by the specified channel width
|
---|
| 3211 |
|
---|
| 3212 | Parameters:
|
---|
| 3213 |
|
---|
| 3214 | width: The channel width (float) of regridded spectra
|
---|
| 3215 | in the current spectral unit.
|
---|
| 3216 |
|
---|
| 3217 | plot: [NOT IMPLEMENTED YET]
|
---|
| 3218 | plot the original and the regridded spectra.
|
---|
| 3219 | In this each indivual fit has to be approved, by
|
---|
| 3220 | typing 'y' or 'n'
|
---|
| 3221 |
|
---|
| 3222 | insitu: if False a new scantable is returned.
|
---|
| 3223 | Otherwise, the scaling is done in-situ
|
---|
| 3224 | The default is taken from .asaprc (False)
|
---|
| 3225 |
|
---|
| 3226 | """
|
---|
| 3227 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3228 | varlist = vars()
|
---|
| 3229 |
|
---|
| 3230 | if plot:
|
---|
| 3231 | asaplog.post()
|
---|
| 3232 | asaplog.push("Verification plot is not implemtnetd yet.")
|
---|
| 3233 | asaplog.post("WARN")
|
---|
| 3234 |
|
---|
| 3235 | s = self.copy()
|
---|
| 3236 | s._regrid_specchan(width)
|
---|
| 3237 |
|
---|
| 3238 | s._add_history("regrid_channel", varlist)
|
---|
| 3239 |
|
---|
| 3240 | # if plot:
|
---|
| 3241 | # from asap.asapplotter import new_asaplot
|
---|
| 3242 | # theplot = new_asaplot(rcParams['plotter.gui'])
|
---|
[2535] | 3243 | # from matplotlib import rc as rcp
|
---|
| 3244 | # rcp('lines', linewidth=1)
|
---|
[2435] | 3245 | # theplot.set_panels()
|
---|
| 3246 | # ylab=s._get_ordinate_label()
|
---|
| 3247 | # #theplot.palette(0,["#777777","red"])
|
---|
| 3248 | # for r in xrange(s.nrow()):
|
---|
| 3249 | # xsm=s._getabcissa(r)
|
---|
| 3250 | # ysm=s._getspectrum(r)
|
---|
| 3251 | # xorg=orgscan._getabcissa(r)
|
---|
| 3252 | # yorg=orgscan._getspectrum(r)
|
---|
| 3253 | # theplot.clear()
|
---|
| 3254 | # theplot.hold()
|
---|
| 3255 | # theplot.set_axes('ylabel',ylab)
|
---|
| 3256 | # theplot.set_axes('xlabel',s._getabcissalabel(r))
|
---|
| 3257 | # theplot.set_axes('title',s._getsourcename(r))
|
---|
| 3258 | # theplot.set_line(label='Original',color="#777777")
|
---|
| 3259 | # theplot.plot(xorg,yorg)
|
---|
| 3260 | # theplot.set_line(label='Smoothed',color="red")
|
---|
| 3261 | # theplot.plot(xsm,ysm)
|
---|
| 3262 | # ### Ugly part for legend
|
---|
| 3263 | # for i in [0,1]:
|
---|
| 3264 | # theplot.subplots[0]['lines'].append(
|
---|
| 3265 | # [theplot.subplots[0]['axes'].lines[i]]
|
---|
| 3266 | # )
|
---|
| 3267 | # theplot.release()
|
---|
| 3268 | # ### Ugly part for legend
|
---|
| 3269 | # theplot.subplots[0]['lines']=[]
|
---|
| 3270 | # res = raw_input("Accept smoothing ([y]/n): ")
|
---|
| 3271 | # if res.upper() == 'N':
|
---|
| 3272 | # s._setspectrum(yorg, r)
|
---|
| 3273 | # theplot.quit()
|
---|
| 3274 | # del theplot
|
---|
| 3275 | # del orgscan
|
---|
| 3276 |
|
---|
| 3277 | if insitu: self._assign(s)
|
---|
| 3278 | else: return s
|
---|
| 3279 |
|
---|
| 3280 | @asaplog_post_dec
|
---|
[2186] | 3281 | def _parse_wn(self, wn):
|
---|
| 3282 | if isinstance(wn, list) or isinstance(wn, tuple):
|
---|
| 3283 | return wn
|
---|
| 3284 | elif isinstance(wn, int):
|
---|
| 3285 | return [ wn ]
|
---|
| 3286 | elif isinstance(wn, str):
|
---|
[2277] | 3287 | if '-' in wn: # case 'a-b' : return [a,a+1,...,b-1,b]
|
---|
[2186] | 3288 | val = wn.split('-')
|
---|
| 3289 | val = [int(val[0]), int(val[1])]
|
---|
| 3290 | val.sort()
|
---|
| 3291 | res = [i for i in xrange(val[0], val[1]+1)]
|
---|
[2277] | 3292 | elif wn[:2] == '<=' or wn[:2] == '=<': # cases '<=a','=<a' : return [0,1,...,a-1,a]
|
---|
[2186] | 3293 | val = int(wn[2:])+1
|
---|
| 3294 | res = [i for i in xrange(val)]
|
---|
[2277] | 3295 | elif wn[-2:] == '>=' or wn[-2:] == '=>': # cases 'a>=','a=>' : return [0,1,...,a-1,a]
|
---|
[2186] | 3296 | val = int(wn[:-2])+1
|
---|
| 3297 | res = [i for i in xrange(val)]
|
---|
[2277] | 3298 | elif wn[0] == '<': # case '<a' : return [0,1,...,a-2,a-1]
|
---|
[2186] | 3299 | val = int(wn[1:])
|
---|
| 3300 | res = [i for i in xrange(val)]
|
---|
[2277] | 3301 | elif wn[-1] == '>': # case 'a>' : return [0,1,...,a-2,a-1]
|
---|
[2186] | 3302 | val = int(wn[:-1])
|
---|
| 3303 | res = [i for i in xrange(val)]
|
---|
[2411] | 3304 | elif wn[:2] == '>=' or wn[:2] == '=>': # cases '>=a','=>a' : return [a,-999], which is
|
---|
| 3305 | # then interpreted in C++
|
---|
| 3306 | # side as [a,a+1,...,a_nyq]
|
---|
| 3307 | # (CAS-3759)
|
---|
[2186] | 3308 | val = int(wn[2:])
|
---|
[2411] | 3309 | res = [val, -999]
|
---|
| 3310 | #res = [i for i in xrange(val, self.nchan()/2+1)]
|
---|
| 3311 | elif wn[-2:] == '<=' or wn[-2:] == '=<': # cases 'a<=','a=<' : return [a,-999], which is
|
---|
| 3312 | # then interpreted in C++
|
---|
| 3313 | # side as [a,a+1,...,a_nyq]
|
---|
| 3314 | # (CAS-3759)
|
---|
[2186] | 3315 | val = int(wn[:-2])
|
---|
[2411] | 3316 | res = [val, -999]
|
---|
| 3317 | #res = [i for i in xrange(val, self.nchan()/2+1)]
|
---|
| 3318 | elif wn[0] == '>': # case '>a' : return [a+1,-999], which is
|
---|
| 3319 | # then interpreted in C++
|
---|
| 3320 | # side as [a+1,a+2,...,a_nyq]
|
---|
| 3321 | # (CAS-3759)
|
---|
[2186] | 3322 | val = int(wn[1:])+1
|
---|
[2411] | 3323 | res = [val, -999]
|
---|
| 3324 | #res = [i for i in xrange(val, self.nchan()/2+1)]
|
---|
| 3325 | elif wn[-1] == '<': # case 'a<' : return [a+1,-999], which is
|
---|
| 3326 | # then interpreted in C++
|
---|
| 3327 | # side as [a+1,a+2,...,a_nyq]
|
---|
| 3328 | # (CAS-3759)
|
---|
[2186] | 3329 | val = int(wn[:-1])+1
|
---|
[2411] | 3330 | res = [val, -999]
|
---|
| 3331 | #res = [i for i in xrange(val, self.nchan()/2+1)]
|
---|
[2012] | 3332 |
|
---|
[2186] | 3333 | return res
|
---|
| 3334 | else:
|
---|
| 3335 | msg = 'wrong value given for addwn/rejwn'
|
---|
| 3336 | raise RuntimeError(msg)
|
---|
| 3337 |
|
---|
[2713] | 3338 | @asaplog_post_dec
|
---|
[2810] | 3339 | def apply_bltable(self, insitu=None, retfitres=None, inbltable=None, outbltable=None, overwrite=None):
|
---|
[2767] | 3340 | """\
|
---|
| 3341 | Subtract baseline based on parameters written in Baseline Table.
|
---|
| 3342 |
|
---|
| 3343 | Parameters:
|
---|
[2809] | 3344 | insitu: if True, baseline fitting/subtraction is done
|
---|
[2810] | 3345 | in-situ. If False, a new scantable with
|
---|
| 3346 | baseline subtracted is returned. Actually,
|
---|
| 3347 | format of the returned value depends on both
|
---|
| 3348 | insitu and retfitres (see below).
|
---|
[2767] | 3349 | The default is taken from .asaprc (False)
|
---|
[2810] | 3350 | retfitres: if True, the results of baseline fitting (i.e.,
|
---|
| 3351 | coefficients and rms) are returned.
|
---|
| 3352 | default is False.
|
---|
| 3353 | The format of the returned value of this
|
---|
| 3354 | function varies as follows:
|
---|
| 3355 | (1) in case insitu=True and retfitres=True:
|
---|
| 3356 | fitting result.
|
---|
| 3357 | (2) in case insitu=True and retfitres=False:
|
---|
| 3358 | None.
|
---|
| 3359 | (3) in case insitu=False and retfitres=True:
|
---|
| 3360 | a dictionary containing a new scantable
|
---|
| 3361 | (with baseline subtracted) and the fitting
|
---|
| 3362 | results.
|
---|
| 3363 | (4) in case insitu=False and retfitres=False:
|
---|
| 3364 | a new scantable (with baseline subtracted).
|
---|
[2767] | 3365 | inbltable: name of input baseline table. The row number of
|
---|
| 3366 | scantable and that of inbltable must be
|
---|
| 3367 | identical.
|
---|
| 3368 | outbltable: name of output baseline table where baseline
|
---|
| 3369 | parameters and fitting results recorded.
|
---|
| 3370 | default is ''(no output).
|
---|
[2809] | 3371 | overwrite: if True when an existing baseline table is
|
---|
| 3372 | specified for outbltable, overwrites it.
|
---|
| 3373 | Otherwise there is no harm.
|
---|
[2767] | 3374 | default is False.
|
---|
| 3375 | """
|
---|
| 3376 |
|
---|
| 3377 | try:
|
---|
| 3378 | varlist = vars()
|
---|
[2810] | 3379 | if retfitres is None: retfitres = False
|
---|
[2767] | 3380 | if inbltable is None: raise ValueError("bltable missing.")
|
---|
| 3381 | if outbltable is None: outbltable = ''
|
---|
| 3382 | if overwrite is None: overwrite = False
|
---|
| 3383 |
|
---|
| 3384 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3385 | if insitu:
|
---|
| 3386 | workscan = self
|
---|
| 3387 | else:
|
---|
| 3388 | workscan = self.copy()
|
---|
| 3389 |
|
---|
| 3390 | sres = workscan._apply_bltable(inbltable,
|
---|
[2810] | 3391 | retfitres,
|
---|
[2767] | 3392 | outbltable,
|
---|
| 3393 | os.path.exists(outbltable),
|
---|
| 3394 | overwrite)
|
---|
[2810] | 3395 | if retfitres: res = parse_fitresult(sres)
|
---|
[2767] | 3396 |
|
---|
| 3397 | workscan._add_history('apply_bltable', varlist)
|
---|
| 3398 |
|
---|
| 3399 | if insitu:
|
---|
| 3400 | self._assign(workscan)
|
---|
[2810] | 3401 | if retfitres:
|
---|
| 3402 | return res
|
---|
| 3403 | else:
|
---|
| 3404 | return None
|
---|
[2767] | 3405 | else:
|
---|
[2810] | 3406 | if retfitres:
|
---|
| 3407 | return {'scantable': workscan, 'fitresults': res}
|
---|
| 3408 | else:
|
---|
| 3409 | return workscan
|
---|
[2767] | 3410 |
|
---|
| 3411 | except RuntimeError, e:
|
---|
| 3412 | raise_fitting_failure_exception(e)
|
---|
| 3413 |
|
---|
| 3414 | @asaplog_post_dec
|
---|
[2810] | 3415 | def sub_baseline(self, insitu=None, retfitres=None, blinfo=None, bltable=None, overwrite=None):
|
---|
[2767] | 3416 | """\
|
---|
| 3417 | Subtract baseline based on parameters written in the input list.
|
---|
| 3418 |
|
---|
| 3419 | Parameters:
|
---|
[2809] | 3420 | insitu: if True, baseline fitting/subtraction is done
|
---|
[2810] | 3421 | in-situ. If False, a new scantable with
|
---|
| 3422 | baseline subtracted is returned. Actually,
|
---|
| 3423 | format of the returned value depends on both
|
---|
| 3424 | insitu and retfitres (see below).
|
---|
[2767] | 3425 | The default is taken from .asaprc (False)
|
---|
[2810] | 3426 | retfitres: if True, the results of baseline fitting (i.e.,
|
---|
| 3427 | coefficients and rms) are returned.
|
---|
| 3428 | default is False.
|
---|
| 3429 | The format of the returned value of this
|
---|
| 3430 | function varies as follows:
|
---|
| 3431 | (1) in case insitu=True and retfitres=True:
|
---|
| 3432 | fitting result.
|
---|
| 3433 | (2) in case insitu=True and retfitres=False:
|
---|
| 3434 | None.
|
---|
| 3435 | (3) in case insitu=False and retfitres=True:
|
---|
| 3436 | a dictionary containing a new scantable
|
---|
| 3437 | (with baseline subtracted) and the fitting
|
---|
| 3438 | results.
|
---|
| 3439 | (4) in case insitu=False and retfitres=False:
|
---|
| 3440 | a new scantable (with baseline subtracted).
|
---|
[2767] | 3441 | blinfo: baseline parameter set stored in a dictionary
|
---|
| 3442 | or a list of dictionary. Each dictionary
|
---|
| 3443 | corresponds to each spectrum and must contain
|
---|
| 3444 | the following keys and values:
|
---|
| 3445 | 'row': row number,
|
---|
| 3446 | 'blfunc': function name. available ones include
|
---|
| 3447 | 'poly', 'chebyshev', 'cspline' and
|
---|
| 3448 | 'sinusoid',
|
---|
| 3449 | 'order': maximum order of polynomial. needed
|
---|
| 3450 | if blfunc='poly' or 'chebyshev',
|
---|
| 3451 | 'npiece': number or piecewise polynomial.
|
---|
| 3452 | needed if blfunc='cspline',
|
---|
| 3453 | 'nwave': a list of sinusoidal wave numbers.
|
---|
| 3454 | needed if blfunc='sinusoid', and
|
---|
| 3455 | 'masklist': min-max windows for channel mask.
|
---|
| 3456 | the specified ranges will be used
|
---|
| 3457 | for fitting.
|
---|
| 3458 | bltable: name of output baseline table where baseline
|
---|
| 3459 | parameters and fitting results recorded.
|
---|
| 3460 | default is ''(no output).
|
---|
[2809] | 3461 | overwrite: if True when an existing baseline table is
|
---|
| 3462 | specified for bltable, overwrites it.
|
---|
| 3463 | Otherwise there is no harm.
|
---|
[2767] | 3464 | default is False.
|
---|
| 3465 |
|
---|
| 3466 | Example:
|
---|
| 3467 | sub_baseline(blinfo=[{'row':0, 'blfunc':'poly', 'order':5,
|
---|
| 3468 | 'masklist':[[10,350],[352,510]]},
|
---|
| 3469 | {'row':1, 'blfunc':'cspline', 'npiece':3,
|
---|
| 3470 | 'masklist':[[3,16],[19,404],[407,511]]}
|
---|
| 3471 | ])
|
---|
| 3472 |
|
---|
| 3473 | the first spectrum (row=0) will be fitted with polynomial
|
---|
| 3474 | of order=5 and the next one (row=1) will be fitted with cubic
|
---|
| 3475 | spline consisting of 3 pieces.
|
---|
| 3476 | """
|
---|
| 3477 |
|
---|
| 3478 | try:
|
---|
| 3479 | varlist = vars()
|
---|
[2810] | 3480 | if retfitres is None: retfitres = False
|
---|
[2767] | 3481 | if blinfo is None: blinfo = []
|
---|
| 3482 | if bltable is None: bltable = ''
|
---|
| 3483 | if overwrite is None: overwrite = False
|
---|
| 3484 |
|
---|
| 3485 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3486 | if insitu:
|
---|
| 3487 | workscan = self
|
---|
| 3488 | else:
|
---|
| 3489 | workscan = self.copy()
|
---|
| 3490 |
|
---|
| 3491 | nrow = workscan.nrow()
|
---|
| 3492 |
|
---|
| 3493 | in_blinfo = pack_blinfo(blinfo=blinfo, maxirow=nrow)
|
---|
| 3494 |
|
---|
| 3495 | sres = workscan._sub_baseline(in_blinfo,
|
---|
[2810] | 3496 | retfitres,
|
---|
[2767] | 3497 | bltable,
|
---|
| 3498 | os.path.exists(bltable),
|
---|
| 3499 | overwrite)
|
---|
[2810] | 3500 | if retfitres: res = parse_fitresult(sres)
|
---|
[2767] | 3501 |
|
---|
| 3502 | workscan._add_history('sub_baseline', varlist)
|
---|
| 3503 |
|
---|
| 3504 | if insitu:
|
---|
| 3505 | self._assign(workscan)
|
---|
[2810] | 3506 | if retfitres:
|
---|
| 3507 | return res
|
---|
| 3508 | else:
|
---|
| 3509 | return None
|
---|
[2767] | 3510 | else:
|
---|
[2810] | 3511 | if retfitres:
|
---|
| 3512 | return {'scantable': workscan, 'fitresults': res}
|
---|
| 3513 | else:
|
---|
| 3514 | return workscan
|
---|
[2767] | 3515 |
|
---|
| 3516 | except RuntimeError, e:
|
---|
| 3517 | raise_fitting_failure_exception(e)
|
---|
| 3518 |
|
---|
| 3519 | @asaplog_post_dec
|
---|
[2713] | 3520 | def calc_aic(self, value=None, blfunc=None, order=None, mask=None,
|
---|
| 3521 | whichrow=None, uselinefinder=None, edge=None,
|
---|
| 3522 | threshold=None, chan_avg_limit=None):
|
---|
| 3523 | """\
|
---|
| 3524 | Calculates and returns model selection criteria for a specified
|
---|
| 3525 | baseline model and a given spectrum data.
|
---|
| 3526 | Available values include Akaike Information Criterion (AIC), the
|
---|
| 3527 | corrected Akaike Information Criterion (AICc) by Sugiura(1978),
|
---|
| 3528 | Bayesian Information Criterion (BIC) and the Generalised Cross
|
---|
| 3529 | Validation (GCV).
|
---|
[2186] | 3530 |
|
---|
[2713] | 3531 | Parameters:
|
---|
| 3532 | value: name of model selection criteria to calculate.
|
---|
| 3533 | available ones include 'aic', 'aicc', 'bic' and
|
---|
| 3534 | 'gcv'. default is 'aicc'.
|
---|
| 3535 | blfunc: baseline function name. available ones include
|
---|
| 3536 | 'chebyshev', 'cspline' and 'sinusoid'.
|
---|
| 3537 | default is 'chebyshev'.
|
---|
| 3538 | order: parameter for basline function. actually stands for
|
---|
| 3539 | order of polynomial (order) for 'chebyshev',
|
---|
| 3540 | number of spline pieces (npiece) for 'cspline' and
|
---|
| 3541 | maximum wave number for 'sinusoid', respectively.
|
---|
| 3542 | default is 5 (which is also the default order value
|
---|
| 3543 | for [auto_]chebyshev_baseline()).
|
---|
| 3544 | mask: an optional mask. default is [].
|
---|
| 3545 | whichrow: row number. default is 0 (the first row)
|
---|
| 3546 | uselinefinder: use sd.linefinder() to flag out line regions
|
---|
| 3547 | default is True.
|
---|
| 3548 | edge: an optional number of channel to drop at
|
---|
| 3549 | the edge of spectrum. If only one value is
|
---|
| 3550 | specified, the same number will be dropped
|
---|
| 3551 | from both sides of the spectrum. Default
|
---|
| 3552 | is to keep all channels. Nested tuples
|
---|
| 3553 | represent individual edge selection for
|
---|
| 3554 | different IFs (a number of spectral channels
|
---|
| 3555 | can be different)
|
---|
| 3556 | default is (0, 0).
|
---|
| 3557 | threshold: the threshold used by line finder. It is
|
---|
| 3558 | better to keep it large as only strong lines
|
---|
| 3559 | affect the baseline solution.
|
---|
| 3560 | default is 3.
|
---|
| 3561 | chan_avg_limit: a maximum number of consequtive spectral
|
---|
| 3562 | channels to average during the search of
|
---|
| 3563 | weak and broad lines. The default is no
|
---|
| 3564 | averaging (and no search for weak lines).
|
---|
| 3565 | If such lines can affect the fitted baseline
|
---|
| 3566 | (e.g. a high order polynomial is fitted),
|
---|
| 3567 | increase this parameter (usually values up
|
---|
| 3568 | to 8 are reasonable). Most users of this
|
---|
| 3569 | method should find the default value sufficient.
|
---|
| 3570 | default is 1.
|
---|
| 3571 |
|
---|
| 3572 | Example:
|
---|
| 3573 | aic = scan.calc_aic(blfunc='chebyshev', order=5, whichrow=0)
|
---|
| 3574 | """
|
---|
| 3575 |
|
---|
| 3576 | try:
|
---|
| 3577 | varlist = vars()
|
---|
| 3578 |
|
---|
| 3579 | if value is None: value = 'aicc'
|
---|
| 3580 | if blfunc is None: blfunc = 'chebyshev'
|
---|
| 3581 | if order is None: order = 5
|
---|
| 3582 | if mask is None: mask = []
|
---|
| 3583 | if whichrow is None: whichrow = 0
|
---|
| 3584 | if uselinefinder is None: uselinefinder = True
|
---|
| 3585 | if edge is None: edge = (0, 0)
|
---|
| 3586 | if threshold is None: threshold = 3
|
---|
| 3587 | if chan_avg_limit is None: chan_avg_limit = 1
|
---|
| 3588 |
|
---|
| 3589 | return self._calc_aic(value, blfunc, order, mask,
|
---|
| 3590 | whichrow, uselinefinder, edge,
|
---|
| 3591 | threshold, chan_avg_limit)
|
---|
| 3592 |
|
---|
| 3593 | except RuntimeError, e:
|
---|
| 3594 | raise_fitting_failure_exception(e)
|
---|
| 3595 |
|
---|
[1862] | 3596 | @asaplog_post_dec
|
---|
[2771] | 3597 | def sinusoid_baseline(self, mask=None, applyfft=None,
|
---|
[2269] | 3598 | fftmethod=None, fftthresh=None,
|
---|
[2771] | 3599 | addwn=None, rejwn=None,
|
---|
| 3600 | insitu=None,
|
---|
| 3601 | clipthresh=None, clipniter=None,
|
---|
| 3602 | plot=None,
|
---|
| 3603 | getresidual=None,
|
---|
| 3604 | showprogress=None, minnrow=None,
|
---|
| 3605 | outlog=None,
|
---|
[2767] | 3606 | blfile=None, csvformat=None,
|
---|
| 3607 | bltable=None):
|
---|
[2047] | 3608 | """\
|
---|
[2349] | 3609 | Return a scan which has been baselined (all rows) with sinusoidal
|
---|
| 3610 | functions.
|
---|
| 3611 |
|
---|
[2047] | 3612 | Parameters:
|
---|
[2186] | 3613 | mask: an optional mask
|
---|
| 3614 | applyfft: if True use some method, such as FFT, to find
|
---|
| 3615 | strongest sinusoidal components in the wavenumber
|
---|
| 3616 | domain to be used for baseline fitting.
|
---|
| 3617 | default is True.
|
---|
| 3618 | fftmethod: method to find the strong sinusoidal components.
|
---|
| 3619 | now only 'fft' is available and it is the default.
|
---|
| 3620 | fftthresh: the threshold to select wave numbers to be used for
|
---|
| 3621 | fitting from the distribution of amplitudes in the
|
---|
| 3622 | wavenumber domain.
|
---|
| 3623 | both float and string values accepted.
|
---|
| 3624 | given a float value, the unit is set to sigma.
|
---|
| 3625 | for string values, allowed formats include:
|
---|
[2349] | 3626 | 'xsigma' or 'x' (= x-sigma level. e.g.,
|
---|
| 3627 | '3sigma'), or
|
---|
[2186] | 3628 | 'topx' (= the x strongest ones, e.g. 'top5').
|
---|
| 3629 | default is 3.0 (unit: sigma).
|
---|
| 3630 | addwn: the additional wave numbers to be used for fitting.
|
---|
| 3631 | list or integer value is accepted to specify every
|
---|
| 3632 | wave numbers. also string value can be used in case
|
---|
| 3633 | you need to specify wave numbers in a certain range,
|
---|
| 3634 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b),
|
---|
| 3635 | '<a' (= 0,1,...,a-2,a-1),
|
---|
| 3636 | '>=a' (= a, a+1, ... up to the maximum wave
|
---|
| 3637 | number corresponding to the Nyquist
|
---|
| 3638 | frequency for the case of FFT).
|
---|
[2411] | 3639 | default is [0].
|
---|
[2186] | 3640 | rejwn: the wave numbers NOT to be used for fitting.
|
---|
| 3641 | can be set just as addwn but has higher priority:
|
---|
| 3642 | wave numbers which are specified both in addwn
|
---|
| 3643 | and rejwn will NOT be used. default is [].
|
---|
[2771] | 3644 | insitu: if False a new scantable is returned.
|
---|
| 3645 | Otherwise, the scaling is done in-situ
|
---|
| 3646 | The default is taken from .asaprc (False)
|
---|
[2081] | 3647 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
[2349] | 3648 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 3649 | clipping (default is 0)
|
---|
[2081] | 3650 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 3651 | plot the fit and the residual. In this each
|
---|
| 3652 | indivual fit has to be approved, by typing 'y'
|
---|
| 3653 | or 'n'
|
---|
| 3654 | getresidual: if False, returns best-fit values instead of
|
---|
| 3655 | residual. (default is True)
|
---|
[2189] | 3656 | showprogress: show progress status for large data.
|
---|
| 3657 | default is True.
|
---|
| 3658 | minnrow: minimum number of input spectra to show.
|
---|
| 3659 | default is 1000.
|
---|
[2081] | 3660 | outlog: Output the coefficients of the best-fit
|
---|
| 3661 | function to logger (default is False)
|
---|
| 3662 | blfile: Name of a text file in which the best-fit
|
---|
| 3663 | parameter values to be written
|
---|
[2186] | 3664 | (default is '': no file/logger output)
|
---|
[2641] | 3665 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 3666 | bltable: name of a baseline table where fitting results
|
---|
| 3667 | (coefficients, rms, etc.) are to be written.
|
---|
| 3668 | if given, fitting results will NOT be output to
|
---|
| 3669 | scantable (insitu=True) or None will be
|
---|
| 3670 | returned (insitu=False).
|
---|
| 3671 | (default is "": no table output)
|
---|
[2047] | 3672 |
|
---|
| 3673 | Example:
|
---|
[2349] | 3674 | # return a scan baselined by a combination of sinusoidal curves
|
---|
| 3675 | # having wave numbers in spectral window up to 10,
|
---|
[2047] | 3676 | # also with 3-sigma clipping, iteration up to 4 times
|
---|
[2186] | 3677 | bscan = scan.sinusoid_baseline(addwn='<=10',clipthresh=3.0,clipniter=4)
|
---|
[2081] | 3678 |
|
---|
| 3679 | Note:
|
---|
| 3680 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 3681 | based on specunit of 'channel'.
|
---|
[2047] | 3682 | """
|
---|
| 3683 |
|
---|
[2186] | 3684 | try:
|
---|
| 3685 | varlist = vars()
|
---|
[2047] | 3686 |
|
---|
[2186] | 3687 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3688 | if insitu:
|
---|
| 3689 | workscan = self
|
---|
| 3690 | else:
|
---|
| 3691 | workscan = self.copy()
|
---|
| 3692 |
|
---|
[2410] | 3693 | if mask is None: mask = []
|
---|
[2186] | 3694 | if applyfft is None: applyfft = True
|
---|
| 3695 | if fftmethod is None: fftmethod = 'fft'
|
---|
| 3696 | if fftthresh is None: fftthresh = 3.0
|
---|
[2411] | 3697 | if addwn is None: addwn = [0]
|
---|
[2186] | 3698 | if rejwn is None: rejwn = []
|
---|
| 3699 | if clipthresh is None: clipthresh = 3.0
|
---|
| 3700 | if clipniter is None: clipniter = 0
|
---|
| 3701 | if plot is None: plot = False
|
---|
| 3702 | if getresidual is None: getresidual = True
|
---|
[2189] | 3703 | if showprogress is None: showprogress = True
|
---|
| 3704 | if minnrow is None: minnrow = 1000
|
---|
[2186] | 3705 | if outlog is None: outlog = False
|
---|
| 3706 | if blfile is None: blfile = ''
|
---|
[2641] | 3707 | if csvformat is None: csvformat = False
|
---|
[2767] | 3708 | if bltable is None: bltable = ''
|
---|
[2047] | 3709 |
|
---|
[2767] | 3710 | sapplyfft = 'true' if applyfft else 'false'
|
---|
| 3711 | fftinfo = ','.join([sapplyfft, fftmethod.lower(), str(fftthresh).lower()])
|
---|
[2641] | 3712 |
|
---|
[2767] | 3713 | scsvformat = 'T' if csvformat else 'F'
|
---|
| 3714 |
|
---|
[2081] | 3715 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method.
|
---|
[2767] | 3716 | workscan._sinusoid_baseline(mask,
|
---|
| 3717 | fftinfo,
|
---|
| 3718 | #applyfft, fftmethod.lower(),
|
---|
| 3719 | #str(fftthresh).lower(),
|
---|
[2349] | 3720 | workscan._parse_wn(addwn),
|
---|
[2643] | 3721 | workscan._parse_wn(rejwn),
|
---|
| 3722 | clipthresh, clipniter,
|
---|
| 3723 | getresidual,
|
---|
[2349] | 3724 | pack_progress_params(showprogress,
|
---|
[2641] | 3725 | minnrow),
|
---|
[2767] | 3726 | outlog, scsvformat+blfile,
|
---|
| 3727 | bltable)
|
---|
[2186] | 3728 | workscan._add_history('sinusoid_baseline', varlist)
|
---|
[2767] | 3729 |
|
---|
| 3730 | if bltable == '':
|
---|
| 3731 | if insitu:
|
---|
| 3732 | self._assign(workscan)
|
---|
| 3733 | else:
|
---|
| 3734 | return workscan
|
---|
[2047] | 3735 | else:
|
---|
[2767] | 3736 | if not insitu:
|
---|
| 3737 | return None
|
---|
[2047] | 3738 |
|
---|
| 3739 | except RuntimeError, e:
|
---|
[2186] | 3740 | raise_fitting_failure_exception(e)
|
---|
[2047] | 3741 |
|
---|
| 3742 |
|
---|
[2186] | 3743 | @asaplog_post_dec
|
---|
[2771] | 3744 | def auto_sinusoid_baseline(self, mask=None, applyfft=None,
|
---|
[2349] | 3745 | fftmethod=None, fftthresh=None,
|
---|
[2771] | 3746 | addwn=None, rejwn=None,
|
---|
| 3747 | insitu=None,
|
---|
| 3748 | clipthresh=None, clipniter=None,
|
---|
| 3749 | edge=None, threshold=None, chan_avg_limit=None,
|
---|
| 3750 | plot=None,
|
---|
| 3751 | getresidual=None,
|
---|
| 3752 | showprogress=None, minnrow=None,
|
---|
| 3753 | outlog=None,
|
---|
[2767] | 3754 | blfile=None, csvformat=None,
|
---|
| 3755 | bltable=None):
|
---|
[2047] | 3756 | """\
|
---|
[2349] | 3757 | Return a scan which has been baselined (all rows) with sinusoidal
|
---|
| 3758 | functions.
|
---|
[2047] | 3759 | Spectral lines are detected first using linefinder and masked out
|
---|
| 3760 | to avoid them affecting the baseline solution.
|
---|
| 3761 |
|
---|
| 3762 | Parameters:
|
---|
[2189] | 3763 | mask: an optional mask retreived from scantable
|
---|
| 3764 | applyfft: if True use some method, such as FFT, to find
|
---|
| 3765 | strongest sinusoidal components in the wavenumber
|
---|
| 3766 | domain to be used for baseline fitting.
|
---|
| 3767 | default is True.
|
---|
| 3768 | fftmethod: method to find the strong sinusoidal components.
|
---|
| 3769 | now only 'fft' is available and it is the default.
|
---|
| 3770 | fftthresh: the threshold to select wave numbers to be used for
|
---|
| 3771 | fitting from the distribution of amplitudes in the
|
---|
| 3772 | wavenumber domain.
|
---|
| 3773 | both float and string values accepted.
|
---|
| 3774 | given a float value, the unit is set to sigma.
|
---|
| 3775 | for string values, allowed formats include:
|
---|
[2349] | 3776 | 'xsigma' or 'x' (= x-sigma level. e.g.,
|
---|
| 3777 | '3sigma'), or
|
---|
[2189] | 3778 | 'topx' (= the x strongest ones, e.g. 'top5').
|
---|
| 3779 | default is 3.0 (unit: sigma).
|
---|
| 3780 | addwn: the additional wave numbers to be used for fitting.
|
---|
| 3781 | list or integer value is accepted to specify every
|
---|
| 3782 | wave numbers. also string value can be used in case
|
---|
| 3783 | you need to specify wave numbers in a certain range,
|
---|
| 3784 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b),
|
---|
| 3785 | '<a' (= 0,1,...,a-2,a-1),
|
---|
| 3786 | '>=a' (= a, a+1, ... up to the maximum wave
|
---|
| 3787 | number corresponding to the Nyquist
|
---|
| 3788 | frequency for the case of FFT).
|
---|
[2411] | 3789 | default is [0].
|
---|
[2189] | 3790 | rejwn: the wave numbers NOT to be used for fitting.
|
---|
| 3791 | can be set just as addwn but has higher priority:
|
---|
| 3792 | wave numbers which are specified both in addwn
|
---|
| 3793 | and rejwn will NOT be used. default is [].
|
---|
[2771] | 3794 | insitu: if False a new scantable is returned.
|
---|
| 3795 | Otherwise, the scaling is done in-situ
|
---|
| 3796 | The default is taken from .asaprc (False)
|
---|
[2189] | 3797 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
[2349] | 3798 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 3799 | clipping (default is 0)
|
---|
[2189] | 3800 | edge: an optional number of channel to drop at
|
---|
| 3801 | the edge of spectrum. If only one value is
|
---|
| 3802 | specified, the same number will be dropped
|
---|
| 3803 | from both sides of the spectrum. Default
|
---|
| 3804 | is to keep all channels. Nested tuples
|
---|
| 3805 | represent individual edge selection for
|
---|
| 3806 | different IFs (a number of spectral channels
|
---|
| 3807 | can be different)
|
---|
| 3808 | threshold: the threshold used by line finder. It is
|
---|
| 3809 | better to keep it large as only strong lines
|
---|
| 3810 | affect the baseline solution.
|
---|
| 3811 | chan_avg_limit: a maximum number of consequtive spectral
|
---|
| 3812 | channels to average during the search of
|
---|
| 3813 | weak and broad lines. The default is no
|
---|
| 3814 | averaging (and no search for weak lines).
|
---|
| 3815 | If such lines can affect the fitted baseline
|
---|
| 3816 | (e.g. a high order polynomial is fitted),
|
---|
| 3817 | increase this parameter (usually values up
|
---|
| 3818 | to 8 are reasonable). Most users of this
|
---|
| 3819 | method should find the default value sufficient.
|
---|
| 3820 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 3821 | plot the fit and the residual. In this each
|
---|
| 3822 | indivual fit has to be approved, by typing 'y'
|
---|
| 3823 | or 'n'
|
---|
| 3824 | getresidual: if False, returns best-fit values instead of
|
---|
| 3825 | residual. (default is True)
|
---|
| 3826 | showprogress: show progress status for large data.
|
---|
| 3827 | default is True.
|
---|
| 3828 | minnrow: minimum number of input spectra to show.
|
---|
| 3829 | default is 1000.
|
---|
| 3830 | outlog: Output the coefficients of the best-fit
|
---|
| 3831 | function to logger (default is False)
|
---|
| 3832 | blfile: Name of a text file in which the best-fit
|
---|
| 3833 | parameter values to be written
|
---|
| 3834 | (default is "": no file/logger output)
|
---|
[2641] | 3835 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 3836 | bltable: name of a baseline table where fitting results
|
---|
| 3837 | (coefficients, rms, etc.) are to be written.
|
---|
| 3838 | if given, fitting results will NOT be output to
|
---|
| 3839 | scantable (insitu=True) or None will be
|
---|
| 3840 | returned (insitu=False).
|
---|
| 3841 | (default is "": no table output)
|
---|
[2047] | 3842 |
|
---|
| 3843 | Example:
|
---|
[2186] | 3844 | bscan = scan.auto_sinusoid_baseline(addwn='<=10', insitu=False)
|
---|
[2081] | 3845 |
|
---|
| 3846 | Note:
|
---|
| 3847 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 3848 | based on specunit of 'channel'.
|
---|
[2047] | 3849 | """
|
---|
| 3850 |
|
---|
[2186] | 3851 | try:
|
---|
| 3852 | varlist = vars()
|
---|
[2047] | 3853 |
|
---|
[2186] | 3854 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3855 | if insitu:
|
---|
| 3856 | workscan = self
|
---|
[2047] | 3857 | else:
|
---|
[2186] | 3858 | workscan = self.copy()
|
---|
| 3859 |
|
---|
[2410] | 3860 | if mask is None: mask = []
|
---|
[2186] | 3861 | if applyfft is None: applyfft = True
|
---|
| 3862 | if fftmethod is None: fftmethod = 'fft'
|
---|
| 3863 | if fftthresh is None: fftthresh = 3.0
|
---|
[2411] | 3864 | if addwn is None: addwn = [0]
|
---|
[2186] | 3865 | if rejwn is None: rejwn = []
|
---|
| 3866 | if clipthresh is None: clipthresh = 3.0
|
---|
| 3867 | if clipniter is None: clipniter = 0
|
---|
| 3868 | if edge is None: edge = (0,0)
|
---|
| 3869 | if threshold is None: threshold = 3
|
---|
| 3870 | if chan_avg_limit is None: chan_avg_limit = 1
|
---|
| 3871 | if plot is None: plot = False
|
---|
| 3872 | if getresidual is None: getresidual = True
|
---|
[2189] | 3873 | if showprogress is None: showprogress = True
|
---|
| 3874 | if minnrow is None: minnrow = 1000
|
---|
[2186] | 3875 | if outlog is None: outlog = False
|
---|
| 3876 | if blfile is None: blfile = ''
|
---|
[2641] | 3877 | if csvformat is None: csvformat = False
|
---|
[2767] | 3878 | if bltable is None: bltable = ''
|
---|
[2047] | 3879 |
|
---|
[2767] | 3880 | sapplyfft = 'true' if applyfft else 'false'
|
---|
| 3881 | fftinfo = ','.join([sapplyfft, fftmethod.lower(), str(fftthresh).lower()])
|
---|
[2641] | 3882 |
|
---|
[2767] | 3883 | scsvformat = 'T' if csvformat else 'F'
|
---|
| 3884 |
|
---|
[2277] | 3885 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method.
|
---|
[2767] | 3886 | workscan._auto_sinusoid_baseline(mask,
|
---|
| 3887 | fftinfo,
|
---|
[2349] | 3888 | workscan._parse_wn(addwn),
|
---|
| 3889 | workscan._parse_wn(rejwn),
|
---|
| 3890 | clipthresh, clipniter,
|
---|
| 3891 | normalise_edge_param(edge),
|
---|
| 3892 | threshold, chan_avg_limit,
|
---|
| 3893 | getresidual,
|
---|
| 3894 | pack_progress_params(showprogress,
|
---|
| 3895 | minnrow),
|
---|
[2767] | 3896 | outlog, scsvformat+blfile, bltable)
|
---|
[2047] | 3897 | workscan._add_history("auto_sinusoid_baseline", varlist)
|
---|
[2767] | 3898 |
|
---|
| 3899 | if bltable == '':
|
---|
| 3900 | if insitu:
|
---|
| 3901 | self._assign(workscan)
|
---|
| 3902 | else:
|
---|
| 3903 | return workscan
|
---|
[2047] | 3904 | else:
|
---|
[2767] | 3905 | if not insitu:
|
---|
| 3906 | return None
|
---|
[2047] | 3907 |
|
---|
| 3908 | except RuntimeError, e:
|
---|
[2186] | 3909 | raise_fitting_failure_exception(e)
|
---|
[2047] | 3910 |
|
---|
| 3911 | @asaplog_post_dec
|
---|
[2771] | 3912 | def cspline_baseline(self, mask=None, npiece=None, insitu=None,
|
---|
[2349] | 3913 | clipthresh=None, clipniter=None, plot=None,
|
---|
| 3914 | getresidual=None, showprogress=None, minnrow=None,
|
---|
[2767] | 3915 | outlog=None, blfile=None, csvformat=None,
|
---|
| 3916 | bltable=None):
|
---|
[1846] | 3917 | """\
|
---|
[2349] | 3918 | Return a scan which has been baselined (all rows) by cubic spline
|
---|
| 3919 | function (piecewise cubic polynomial).
|
---|
| 3920 |
|
---|
[513] | 3921 | Parameters:
|
---|
[2771] | 3922 | mask: An optional mask
|
---|
| 3923 | npiece: Number of pieces. (default is 2)
|
---|
[2189] | 3924 | insitu: If False a new scantable is returned.
|
---|
| 3925 | Otherwise, the scaling is done in-situ
|
---|
| 3926 | The default is taken from .asaprc (False)
|
---|
| 3927 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
[2349] | 3928 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 3929 | clipping (default is 0)
|
---|
[2189] | 3930 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 3931 | plot the fit and the residual. In this each
|
---|
| 3932 | indivual fit has to be approved, by typing 'y'
|
---|
| 3933 | or 'n'
|
---|
| 3934 | getresidual: if False, returns best-fit values instead of
|
---|
| 3935 | residual. (default is True)
|
---|
| 3936 | showprogress: show progress status for large data.
|
---|
| 3937 | default is True.
|
---|
| 3938 | minnrow: minimum number of input spectra to show.
|
---|
| 3939 | default is 1000.
|
---|
| 3940 | outlog: Output the coefficients of the best-fit
|
---|
| 3941 | function to logger (default is False)
|
---|
| 3942 | blfile: Name of a text file in which the best-fit
|
---|
| 3943 | parameter values to be written
|
---|
| 3944 | (default is "": no file/logger output)
|
---|
[2641] | 3945 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 3946 | bltable: name of a baseline table where fitting results
|
---|
| 3947 | (coefficients, rms, etc.) are to be written.
|
---|
| 3948 | if given, fitting results will NOT be output to
|
---|
| 3949 | scantable (insitu=True) or None will be
|
---|
| 3950 | returned (insitu=False).
|
---|
| 3951 | (default is "": no table output)
|
---|
[1846] | 3952 |
|
---|
[2012] | 3953 | Example:
|
---|
[2349] | 3954 | # return a scan baselined by a cubic spline consisting of 2 pieces
|
---|
| 3955 | # (i.e., 1 internal knot),
|
---|
[2012] | 3956 | # also with 3-sigma clipping, iteration up to 4 times
|
---|
| 3957 | bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4)
|
---|
[2081] | 3958 |
|
---|
| 3959 | Note:
|
---|
| 3960 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 3961 | based on specunit of 'channel'.
|
---|
[2012] | 3962 | """
|
---|
| 3963 |
|
---|
[2186] | 3964 | try:
|
---|
| 3965 | varlist = vars()
|
---|
| 3966 |
|
---|
| 3967 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 3968 | if insitu:
|
---|
| 3969 | workscan = self
|
---|
| 3970 | else:
|
---|
| 3971 | workscan = self.copy()
|
---|
[1855] | 3972 |
|
---|
[2410] | 3973 | if mask is None: mask = []
|
---|
[2189] | 3974 | if npiece is None: npiece = 2
|
---|
| 3975 | if clipthresh is None: clipthresh = 3.0
|
---|
| 3976 | if clipniter is None: clipniter = 0
|
---|
| 3977 | if plot is None: plot = False
|
---|
| 3978 | if getresidual is None: getresidual = True
|
---|
| 3979 | if showprogress is None: showprogress = True
|
---|
| 3980 | if minnrow is None: minnrow = 1000
|
---|
| 3981 | if outlog is None: outlog = False
|
---|
| 3982 | if blfile is None: blfile = ''
|
---|
[2767] | 3983 | if csvformat is None: csvformat = False
|
---|
| 3984 | if bltable is None: bltable = ''
|
---|
[1855] | 3985 |
|
---|
[2767] | 3986 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2641] | 3987 |
|
---|
[2012] | 3988 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method.
|
---|
[2767] | 3989 | workscan._cspline_baseline(mask, npiece,
|
---|
| 3990 | clipthresh, clipniter,
|
---|
[2349] | 3991 | getresidual,
|
---|
| 3992 | pack_progress_params(showprogress,
|
---|
[2641] | 3993 | minnrow),
|
---|
[2767] | 3994 | outlog, scsvformat+blfile,
|
---|
| 3995 | bltable)
|
---|
[2012] | 3996 | workscan._add_history("cspline_baseline", varlist)
|
---|
[2767] | 3997 |
|
---|
| 3998 | if bltable == '':
|
---|
| 3999 | if insitu:
|
---|
| 4000 | self._assign(workscan)
|
---|
| 4001 | else:
|
---|
| 4002 | return workscan
|
---|
[2012] | 4003 | else:
|
---|
[2767] | 4004 | if not insitu:
|
---|
| 4005 | return None
|
---|
[2012] | 4006 |
|
---|
| 4007 | except RuntimeError, e:
|
---|
[2186] | 4008 | raise_fitting_failure_exception(e)
|
---|
[1855] | 4009 |
|
---|
[2186] | 4010 | @asaplog_post_dec
|
---|
[2771] | 4011 | def auto_cspline_baseline(self, mask=None, npiece=None, insitu=None,
|
---|
[2349] | 4012 | clipthresh=None, clipniter=None,
|
---|
| 4013 | edge=None, threshold=None, chan_avg_limit=None,
|
---|
| 4014 | getresidual=None, plot=None,
|
---|
| 4015 | showprogress=None, minnrow=None, outlog=None,
|
---|
[2767] | 4016 | blfile=None, csvformat=None, bltable=None):
|
---|
[2012] | 4017 | """\
|
---|
| 4018 | Return a scan which has been baselined (all rows) by cubic spline
|
---|
| 4019 | function (piecewise cubic polynomial).
|
---|
| 4020 | Spectral lines are detected first using linefinder and masked out
|
---|
| 4021 | to avoid them affecting the baseline solution.
|
---|
| 4022 |
|
---|
| 4023 | Parameters:
|
---|
[2771] | 4024 | mask: an optional mask retreived from scantable
|
---|
| 4025 | npiece: Number of pieces. (default is 2)
|
---|
[2189] | 4026 | insitu: if False a new scantable is returned.
|
---|
| 4027 | Otherwise, the scaling is done in-situ
|
---|
| 4028 | The default is taken from .asaprc (False)
|
---|
| 4029 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
[2349] | 4030 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 4031 | clipping (default is 0)
|
---|
[2189] | 4032 | edge: an optional number of channel to drop at
|
---|
| 4033 | the edge of spectrum. If only one value is
|
---|
| 4034 | specified, the same number will be dropped
|
---|
| 4035 | from both sides of the spectrum. Default
|
---|
| 4036 | is to keep all channels. Nested tuples
|
---|
| 4037 | represent individual edge selection for
|
---|
| 4038 | different IFs (a number of spectral channels
|
---|
| 4039 | can be different)
|
---|
| 4040 | threshold: the threshold used by line finder. It is
|
---|
| 4041 | better to keep it large as only strong lines
|
---|
| 4042 | affect the baseline solution.
|
---|
| 4043 | chan_avg_limit: a maximum number of consequtive spectral
|
---|
| 4044 | channels to average during the search of
|
---|
| 4045 | weak and broad lines. The default is no
|
---|
| 4046 | averaging (and no search for weak lines).
|
---|
| 4047 | If such lines can affect the fitted baseline
|
---|
| 4048 | (e.g. a high order polynomial is fitted),
|
---|
| 4049 | increase this parameter (usually values up
|
---|
| 4050 | to 8 are reasonable). Most users of this
|
---|
| 4051 | method should find the default value sufficient.
|
---|
| 4052 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 4053 | plot the fit and the residual. In this each
|
---|
| 4054 | indivual fit has to be approved, by typing 'y'
|
---|
| 4055 | or 'n'
|
---|
| 4056 | getresidual: if False, returns best-fit values instead of
|
---|
| 4057 | residual. (default is True)
|
---|
| 4058 | showprogress: show progress status for large data.
|
---|
| 4059 | default is True.
|
---|
| 4060 | minnrow: minimum number of input spectra to show.
|
---|
| 4061 | default is 1000.
|
---|
| 4062 | outlog: Output the coefficients of the best-fit
|
---|
| 4063 | function to logger (default is False)
|
---|
| 4064 | blfile: Name of a text file in which the best-fit
|
---|
| 4065 | parameter values to be written
|
---|
| 4066 | (default is "": no file/logger output)
|
---|
[2641] | 4067 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 4068 | bltable: name of a baseline table where fitting results
|
---|
| 4069 | (coefficients, rms, etc.) are to be written.
|
---|
| 4070 | if given, fitting results will NOT be output to
|
---|
| 4071 | scantable (insitu=True) or None will be
|
---|
| 4072 | returned (insitu=False).
|
---|
| 4073 | (default is "": no table output)
|
---|
[1846] | 4074 |
|
---|
[1907] | 4075 | Example:
|
---|
[2012] | 4076 | bscan = scan.auto_cspline_baseline(npiece=3, insitu=False)
|
---|
[2081] | 4077 |
|
---|
| 4078 | Note:
|
---|
| 4079 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 4080 | based on specunit of 'channel'.
|
---|
[2012] | 4081 | """
|
---|
[1846] | 4082 |
|
---|
[2186] | 4083 | try:
|
---|
| 4084 | varlist = vars()
|
---|
[2012] | 4085 |
|
---|
[2186] | 4086 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 4087 | if insitu:
|
---|
| 4088 | workscan = self
|
---|
[1391] | 4089 | else:
|
---|
[2186] | 4090 | workscan = self.copy()
|
---|
| 4091 |
|
---|
[2410] | 4092 | #if mask is None: mask = [True for i in xrange(workscan.nchan())]
|
---|
| 4093 | if mask is None: mask = []
|
---|
[2186] | 4094 | if npiece is None: npiece = 2
|
---|
| 4095 | if clipthresh is None: clipthresh = 3.0
|
---|
| 4096 | if clipniter is None: clipniter = 0
|
---|
| 4097 | if edge is None: edge = (0, 0)
|
---|
| 4098 | if threshold is None: threshold = 3
|
---|
| 4099 | if chan_avg_limit is None: chan_avg_limit = 1
|
---|
| 4100 | if plot is None: plot = False
|
---|
| 4101 | if getresidual is None: getresidual = True
|
---|
[2189] | 4102 | if showprogress is None: showprogress = True
|
---|
| 4103 | if minnrow is None: minnrow = 1000
|
---|
[2186] | 4104 | if outlog is None: outlog = False
|
---|
| 4105 | if blfile is None: blfile = ''
|
---|
[2641] | 4106 | if csvformat is None: csvformat = False
|
---|
[2767] | 4107 | if bltable is None: bltable = ''
|
---|
[1819] | 4108 |
|
---|
[2767] | 4109 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2641] | 4110 |
|
---|
[2277] | 4111 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method.
|
---|
[2767] | 4112 | workscan._auto_cspline_baseline(mask, npiece,
|
---|
| 4113 | clipthresh, clipniter,
|
---|
[2269] | 4114 | normalise_edge_param(edge),
|
---|
| 4115 | threshold,
|
---|
| 4116 | chan_avg_limit, getresidual,
|
---|
| 4117 | pack_progress_params(showprogress,
|
---|
| 4118 | minnrow),
|
---|
[2767] | 4119 | outlog,
|
---|
| 4120 | scsvformat+blfile,
|
---|
| 4121 | bltable)
|
---|
[2012] | 4122 | workscan._add_history("auto_cspline_baseline", varlist)
|
---|
[2767] | 4123 |
|
---|
| 4124 | if bltable == '':
|
---|
| 4125 | if insitu:
|
---|
| 4126 | self._assign(workscan)
|
---|
| 4127 | else:
|
---|
| 4128 | return workscan
|
---|
[1856] | 4129 | else:
|
---|
[2767] | 4130 | if not insitu:
|
---|
| 4131 | return None
|
---|
[2012] | 4132 |
|
---|
| 4133 | except RuntimeError, e:
|
---|
[2186] | 4134 | raise_fitting_failure_exception(e)
|
---|
[513] | 4135 |
|
---|
[1931] | 4136 | @asaplog_post_dec
|
---|
[2771] | 4137 | def chebyshev_baseline(self, mask=None, order=None, insitu=None,
|
---|
[2645] | 4138 | clipthresh=None, clipniter=None, plot=None,
|
---|
| 4139 | getresidual=None, showprogress=None, minnrow=None,
|
---|
[2767] | 4140 | outlog=None, blfile=None, csvformat=None,
|
---|
| 4141 | bltable=None):
|
---|
[2645] | 4142 | """\
|
---|
| 4143 | Return a scan which has been baselined (all rows) by Chebyshev polynomials.
|
---|
| 4144 |
|
---|
| 4145 | Parameters:
|
---|
[2771] | 4146 | mask: An optional mask
|
---|
| 4147 | order: the maximum order of Chebyshev polynomial (default is 5)
|
---|
[2645] | 4148 | insitu: If False a new scantable is returned.
|
---|
| 4149 | Otherwise, the scaling is done in-situ
|
---|
| 4150 | The default is taken from .asaprc (False)
|
---|
| 4151 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
| 4152 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 4153 | clipping (default is 0)
|
---|
| 4154 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 4155 | plot the fit and the residual. In this each
|
---|
| 4156 | indivual fit has to be approved, by typing 'y'
|
---|
| 4157 | or 'n'
|
---|
| 4158 | getresidual: if False, returns best-fit values instead of
|
---|
| 4159 | residual. (default is True)
|
---|
| 4160 | showprogress: show progress status for large data.
|
---|
| 4161 | default is True.
|
---|
| 4162 | minnrow: minimum number of input spectra to show.
|
---|
| 4163 | default is 1000.
|
---|
| 4164 | outlog: Output the coefficients of the best-fit
|
---|
| 4165 | function to logger (default is False)
|
---|
| 4166 | blfile: Name of a text file in which the best-fit
|
---|
| 4167 | parameter values to be written
|
---|
| 4168 | (default is "": no file/logger output)
|
---|
| 4169 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 4170 | bltable: name of a baseline table where fitting results
|
---|
| 4171 | (coefficients, rms, etc.) are to be written.
|
---|
| 4172 | if given, fitting results will NOT be output to
|
---|
| 4173 | scantable (insitu=True) or None will be
|
---|
| 4174 | returned (insitu=False).
|
---|
| 4175 | (default is "": no table output)
|
---|
[2645] | 4176 |
|
---|
| 4177 | Example:
|
---|
| 4178 | # return a scan baselined by a cubic spline consisting of 2 pieces
|
---|
| 4179 | # (i.e., 1 internal knot),
|
---|
| 4180 | # also with 3-sigma clipping, iteration up to 4 times
|
---|
| 4181 | bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4)
|
---|
| 4182 |
|
---|
| 4183 | Note:
|
---|
| 4184 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 4185 | based on specunit of 'channel'.
|
---|
| 4186 | """
|
---|
| 4187 |
|
---|
| 4188 | try:
|
---|
| 4189 | varlist = vars()
|
---|
| 4190 |
|
---|
| 4191 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 4192 | if insitu:
|
---|
| 4193 | workscan = self
|
---|
| 4194 | else:
|
---|
| 4195 | workscan = self.copy()
|
---|
| 4196 |
|
---|
| 4197 | if mask is None: mask = []
|
---|
| 4198 | if order is None: order = 5
|
---|
| 4199 | if clipthresh is None: clipthresh = 3.0
|
---|
| 4200 | if clipniter is None: clipniter = 0
|
---|
| 4201 | if plot is None: plot = False
|
---|
| 4202 | if getresidual is None: getresidual = True
|
---|
| 4203 | if showprogress is None: showprogress = True
|
---|
| 4204 | if minnrow is None: minnrow = 1000
|
---|
| 4205 | if outlog is None: outlog = False
|
---|
| 4206 | if blfile is None: blfile = ''
|
---|
[2767] | 4207 | if csvformat is None: csvformat = False
|
---|
| 4208 | if bltable is None: bltable = ''
|
---|
[2645] | 4209 |
|
---|
[2767] | 4210 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2645] | 4211 |
|
---|
| 4212 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method.
|
---|
[2767] | 4213 | workscan._chebyshev_baseline(mask, order,
|
---|
| 4214 | clipthresh, clipniter,
|
---|
[2645] | 4215 | getresidual,
|
---|
| 4216 | pack_progress_params(showprogress,
|
---|
| 4217 | minnrow),
|
---|
[2767] | 4218 | outlog, scsvformat+blfile,
|
---|
| 4219 | bltable)
|
---|
[2645] | 4220 | workscan._add_history("chebyshev_baseline", varlist)
|
---|
[2767] | 4221 |
|
---|
| 4222 | if bltable == '':
|
---|
| 4223 | if insitu:
|
---|
| 4224 | self._assign(workscan)
|
---|
| 4225 | else:
|
---|
| 4226 | return workscan
|
---|
[2645] | 4227 | else:
|
---|
[2767] | 4228 | if not insitu:
|
---|
| 4229 | return None
|
---|
[2645] | 4230 |
|
---|
| 4231 | except RuntimeError, e:
|
---|
| 4232 | raise_fitting_failure_exception(e)
|
---|
| 4233 |
|
---|
| 4234 | @asaplog_post_dec
|
---|
[2771] | 4235 | def auto_chebyshev_baseline(self, mask=None, order=None, insitu=None,
|
---|
[2645] | 4236 | clipthresh=None, clipniter=None,
|
---|
| 4237 | edge=None, threshold=None, chan_avg_limit=None,
|
---|
| 4238 | getresidual=None, plot=None,
|
---|
| 4239 | showprogress=None, minnrow=None, outlog=None,
|
---|
[2767] | 4240 | blfile=None, csvformat=None, bltable=None):
|
---|
[2645] | 4241 | """\
|
---|
| 4242 | Return a scan which has been baselined (all rows) by Chebyshev polynomials.
|
---|
| 4243 | Spectral lines are detected first using linefinder and masked out
|
---|
| 4244 | to avoid them affecting the baseline solution.
|
---|
| 4245 |
|
---|
| 4246 | Parameters:
|
---|
[2771] | 4247 | mask: an optional mask retreived from scantable
|
---|
| 4248 | order: the maximum order of Chebyshev polynomial (default is 5)
|
---|
[2645] | 4249 | insitu: if False a new scantable is returned.
|
---|
| 4250 | Otherwise, the scaling is done in-situ
|
---|
| 4251 | The default is taken from .asaprc (False)
|
---|
| 4252 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
| 4253 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 4254 | clipping (default is 0)
|
---|
| 4255 | edge: an optional number of channel to drop at
|
---|
| 4256 | the edge of spectrum. If only one value is
|
---|
| 4257 | specified, the same number will be dropped
|
---|
| 4258 | from both sides of the spectrum. Default
|
---|
| 4259 | is to keep all channels. Nested tuples
|
---|
| 4260 | represent individual edge selection for
|
---|
| 4261 | different IFs (a number of spectral channels
|
---|
| 4262 | can be different)
|
---|
| 4263 | threshold: the threshold used by line finder. It is
|
---|
| 4264 | better to keep it large as only strong lines
|
---|
| 4265 | affect the baseline solution.
|
---|
| 4266 | chan_avg_limit: a maximum number of consequtive spectral
|
---|
| 4267 | channels to average during the search of
|
---|
| 4268 | weak and broad lines. The default is no
|
---|
| 4269 | averaging (and no search for weak lines).
|
---|
| 4270 | If such lines can affect the fitted baseline
|
---|
| 4271 | (e.g. a high order polynomial is fitted),
|
---|
| 4272 | increase this parameter (usually values up
|
---|
| 4273 | to 8 are reasonable). Most users of this
|
---|
| 4274 | method should find the default value sufficient.
|
---|
| 4275 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE ***
|
---|
| 4276 | plot the fit and the residual. In this each
|
---|
| 4277 | indivual fit has to be approved, by typing 'y'
|
---|
| 4278 | or 'n'
|
---|
| 4279 | getresidual: if False, returns best-fit values instead of
|
---|
| 4280 | residual. (default is True)
|
---|
| 4281 | showprogress: show progress status for large data.
|
---|
| 4282 | default is True.
|
---|
| 4283 | minnrow: minimum number of input spectra to show.
|
---|
| 4284 | default is 1000.
|
---|
| 4285 | outlog: Output the coefficients of the best-fit
|
---|
| 4286 | function to logger (default is False)
|
---|
| 4287 | blfile: Name of a text file in which the best-fit
|
---|
| 4288 | parameter values to be written
|
---|
| 4289 | (default is "": no file/logger output)
|
---|
| 4290 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 4291 | bltable: name of a baseline table where fitting results
|
---|
| 4292 | (coefficients, rms, etc.) are to be written.
|
---|
| 4293 | if given, fitting results will NOT be output to
|
---|
| 4294 | scantable (insitu=True) or None will be
|
---|
| 4295 | returned (insitu=False).
|
---|
| 4296 | (default is "": no table output)
|
---|
[2645] | 4297 |
|
---|
| 4298 | Example:
|
---|
| 4299 | bscan = scan.auto_cspline_baseline(npiece=3, insitu=False)
|
---|
| 4300 |
|
---|
| 4301 | Note:
|
---|
| 4302 | The best-fit parameter values output in logger and/or blfile are now
|
---|
| 4303 | based on specunit of 'channel'.
|
---|
| 4304 | """
|
---|
| 4305 |
|
---|
| 4306 | try:
|
---|
| 4307 | varlist = vars()
|
---|
| 4308 |
|
---|
| 4309 | if insitu is None: insitu = rcParams['insitu']
|
---|
| 4310 | if insitu:
|
---|
| 4311 | workscan = self
|
---|
| 4312 | else:
|
---|
| 4313 | workscan = self.copy()
|
---|
| 4314 |
|
---|
| 4315 | if mask is None: mask = []
|
---|
| 4316 | if order is None: order = 5
|
---|
| 4317 | if clipthresh is None: clipthresh = 3.0
|
---|
| 4318 | if clipniter is None: clipniter = 0
|
---|
| 4319 | if edge is None: edge = (0, 0)
|
---|
| 4320 | if threshold is None: threshold = 3
|
---|
| 4321 | if chan_avg_limit is None: chan_avg_limit = 1
|
---|
| 4322 | if plot is None: plot = False
|
---|
| 4323 | if getresidual is None: getresidual = True
|
---|
| 4324 | if showprogress is None: showprogress = True
|
---|
| 4325 | if minnrow is None: minnrow = 1000
|
---|
| 4326 | if outlog is None: outlog = False
|
---|
| 4327 | if blfile is None: blfile = ''
|
---|
| 4328 | if csvformat is None: csvformat = False
|
---|
[2767] | 4329 | if bltable is None: bltable = ''
|
---|
[2645] | 4330 |
|
---|
[2767] | 4331 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2645] | 4332 |
|
---|
| 4333 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method.
|
---|
[2767] | 4334 | workscan._auto_chebyshev_baseline(mask, order,
|
---|
| 4335 | clipthresh, clipniter,
|
---|
[2645] | 4336 | normalise_edge_param(edge),
|
---|
| 4337 | threshold,
|
---|
| 4338 | chan_avg_limit, getresidual,
|
---|
| 4339 | pack_progress_params(showprogress,
|
---|
| 4340 | minnrow),
|
---|
[2767] | 4341 | outlog, scsvformat+blfile,
|
---|
| 4342 | bltable)
|
---|
[2645] | 4343 | workscan._add_history("auto_chebyshev_baseline", varlist)
|
---|
[2767] | 4344 |
|
---|
| 4345 | if bltable == '':
|
---|
| 4346 | if insitu:
|
---|
| 4347 | self._assign(workscan)
|
---|
| 4348 | else:
|
---|
| 4349 | return workscan
|
---|
[2645] | 4350 | else:
|
---|
[2767] | 4351 | if not insitu:
|
---|
| 4352 | return None
|
---|
[2645] | 4353 |
|
---|
| 4354 | except RuntimeError, e:
|
---|
| 4355 | raise_fitting_failure_exception(e)
|
---|
| 4356 |
|
---|
| 4357 | @asaplog_post_dec
|
---|
[2771] | 4358 | def poly_baseline(self, mask=None, order=None, insitu=None,
|
---|
[2767] | 4359 | clipthresh=None, clipniter=None, plot=None,
|
---|
[2269] | 4360 | getresidual=None, showprogress=None, minnrow=None,
|
---|
[2767] | 4361 | outlog=None, blfile=None, csvformat=None,
|
---|
| 4362 | bltable=None):
|
---|
[1907] | 4363 | """\
|
---|
| 4364 | Return a scan which has been baselined (all rows) by a polynomial.
|
---|
| 4365 | Parameters:
|
---|
[2771] | 4366 | mask: an optional mask
|
---|
| 4367 | order: the order of the polynomial (default is 0)
|
---|
[2189] | 4368 | insitu: if False a new scantable is returned.
|
---|
| 4369 | Otherwise, the scaling is done in-situ
|
---|
| 4370 | The default is taken from .asaprc (False)
|
---|
[2767] | 4371 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
| 4372 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 4373 | clipping (default is 0)
|
---|
[2189] | 4374 | plot: plot the fit and the residual. In this each
|
---|
| 4375 | indivual fit has to be approved, by typing 'y'
|
---|
| 4376 | or 'n'
|
---|
| 4377 | getresidual: if False, returns best-fit values instead of
|
---|
| 4378 | residual. (default is True)
|
---|
| 4379 | showprogress: show progress status for large data.
|
---|
| 4380 | default is True.
|
---|
| 4381 | minnrow: minimum number of input spectra to show.
|
---|
| 4382 | default is 1000.
|
---|
| 4383 | outlog: Output the coefficients of the best-fit
|
---|
| 4384 | function to logger (default is False)
|
---|
| 4385 | blfile: Name of a text file in which the best-fit
|
---|
| 4386 | parameter values to be written
|
---|
| 4387 | (default is "": no file/logger output)
|
---|
[2641] | 4388 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 4389 | bltable: name of a baseline table where fitting results
|
---|
| 4390 | (coefficients, rms, etc.) are to be written.
|
---|
| 4391 | if given, fitting results will NOT be output to
|
---|
| 4392 | scantable (insitu=True) or None will be
|
---|
| 4393 | returned (insitu=False).
|
---|
| 4394 | (default is "": no table output)
|
---|
[2012] | 4395 |
|
---|
[1907] | 4396 | Example:
|
---|
| 4397 | # return a scan baselined by a third order polynomial,
|
---|
| 4398 | # not using a mask
|
---|
| 4399 | bscan = scan.poly_baseline(order=3)
|
---|
| 4400 | """
|
---|
[1931] | 4401 |
|
---|
[2186] | 4402 | try:
|
---|
| 4403 | varlist = vars()
|
---|
[1931] | 4404 |
|
---|
[2269] | 4405 | if insitu is None:
|
---|
| 4406 | insitu = rcParams["insitu"]
|
---|
[2186] | 4407 | if insitu:
|
---|
| 4408 | workscan = self
|
---|
| 4409 | else:
|
---|
| 4410 | workscan = self.copy()
|
---|
[1907] | 4411 |
|
---|
[2410] | 4412 | if mask is None: mask = []
|
---|
[2189] | 4413 | if order is None: order = 0
|
---|
[2767] | 4414 | if clipthresh is None: clipthresh = 3.0
|
---|
| 4415 | if clipniter is None: clipniter = 0
|
---|
[2189] | 4416 | if plot is None: plot = False
|
---|
| 4417 | if getresidual is None: getresidual = True
|
---|
| 4418 | if showprogress is None: showprogress = True
|
---|
| 4419 | if minnrow is None: minnrow = 1000
|
---|
| 4420 | if outlog is None: outlog = False
|
---|
[2767] | 4421 | if blfile is None: blfile = ''
|
---|
[2641] | 4422 | if csvformat is None: csvformat = False
|
---|
[2767] | 4423 | if bltable is None: bltable = ''
|
---|
[1907] | 4424 |
|
---|
[2767] | 4425 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2641] | 4426 |
|
---|
[2012] | 4427 | if plot:
|
---|
[2269] | 4428 | outblfile = (blfile != "") and \
|
---|
[2349] | 4429 | os.path.exists(os.path.expanduser(
|
---|
| 4430 | os.path.expandvars(blfile))
|
---|
| 4431 | )
|
---|
[2269] | 4432 | if outblfile:
|
---|
| 4433 | blf = open(blfile, "a")
|
---|
[2012] | 4434 |
|
---|
[1907] | 4435 | f = fitter()
|
---|
| 4436 | f.set_function(lpoly=order)
|
---|
[2186] | 4437 |
|
---|
| 4438 | rows = xrange(workscan.nrow())
|
---|
| 4439 | #if len(rows) > 0: workscan._init_blinfo()
|
---|
[2610] | 4440 |
|
---|
| 4441 | action = "H"
|
---|
[1907] | 4442 | for r in rows:
|
---|
| 4443 | f.x = workscan._getabcissa(r)
|
---|
| 4444 | f.y = workscan._getspectrum(r)
|
---|
[2541] | 4445 | if mask:
|
---|
| 4446 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434)
|
---|
| 4447 | else: # mask=None
|
---|
| 4448 | f.mask = workscan._getmask(r)
|
---|
| 4449 |
|
---|
[1907] | 4450 | f.data = None
|
---|
| 4451 | f.fit()
|
---|
[2541] | 4452 |
|
---|
[2610] | 4453 | if action != "Y": # skip plotting when accepting all
|
---|
| 4454 | f.plot(residual=True)
|
---|
| 4455 | #accept_fit = raw_input("Accept fit ( [y]/n ): ")
|
---|
| 4456 | #if accept_fit.upper() == "N":
|
---|
| 4457 | # #workscan._append_blinfo(None, None, None)
|
---|
| 4458 | # continue
|
---|
| 4459 | accept_fit = self._get_verify_action("Accept fit?",action)
|
---|
| 4460 | if r == 0: action = None
|
---|
[1907] | 4461 | if accept_fit.upper() == "N":
|
---|
| 4462 | continue
|
---|
[2610] | 4463 | elif accept_fit.upper() == "R":
|
---|
| 4464 | break
|
---|
| 4465 | elif accept_fit.upper() == "A":
|
---|
| 4466 | action = "Y"
|
---|
[2012] | 4467 |
|
---|
| 4468 | blpars = f.get_parameters()
|
---|
| 4469 | masklist = workscan.get_masklist(f.mask, row=r, silent=True)
|
---|
| 4470 | #workscan._append_blinfo(blpars, masklist, f.mask)
|
---|
[2269] | 4471 | workscan._setspectrum((f.fitter.getresidual()
|
---|
| 4472 | if getresidual else f.fitter.getfit()), r)
|
---|
[1907] | 4473 |
|
---|
[2012] | 4474 | if outblfile:
|
---|
| 4475 | rms = workscan.get_rms(f.mask, r)
|
---|
[2269] | 4476 | dataout = \
|
---|
| 4477 | workscan.format_blparams_row(blpars["params"],
|
---|
| 4478 | blpars["fixed"],
|
---|
| 4479 | rms, str(masklist),
|
---|
[2641] | 4480 | r, True, csvformat)
|
---|
[2012] | 4481 | blf.write(dataout)
|
---|
| 4482 |
|
---|
[1907] | 4483 | f._p.unmap()
|
---|
| 4484 | f._p = None
|
---|
[2012] | 4485 |
|
---|
[2349] | 4486 | if outblfile:
|
---|
| 4487 | blf.close()
|
---|
[1907] | 4488 | else:
|
---|
[2767] | 4489 | workscan._poly_baseline(mask, order,
|
---|
| 4490 | clipthresh, clipniter, #
|
---|
| 4491 | getresidual,
|
---|
[2269] | 4492 | pack_progress_params(showprogress,
|
---|
| 4493 | minnrow),
|
---|
[2767] | 4494 | outlog, scsvformat+blfile,
|
---|
| 4495 | bltable) #
|
---|
[1907] | 4496 |
|
---|
| 4497 | workscan._add_history("poly_baseline", varlist)
|
---|
| 4498 |
|
---|
| 4499 | if insitu:
|
---|
| 4500 | self._assign(workscan)
|
---|
| 4501 | else:
|
---|
| 4502 | return workscan
|
---|
| 4503 |
|
---|
[1919] | 4504 | except RuntimeError, e:
|
---|
[2186] | 4505 | raise_fitting_failure_exception(e)
|
---|
[1907] | 4506 |
|
---|
[2186] | 4507 | @asaplog_post_dec
|
---|
[2771] | 4508 | def auto_poly_baseline(self, mask=None, order=None, insitu=None,
|
---|
[2767] | 4509 | clipthresh=None, clipniter=None,
|
---|
| 4510 | edge=None, threshold=None, chan_avg_limit=None,
|
---|
| 4511 | getresidual=None, plot=None,
|
---|
| 4512 | showprogress=None, minnrow=None, outlog=None,
|
---|
| 4513 | blfile=None, csvformat=None, bltable=None):
|
---|
[1846] | 4514 | """\
|
---|
[1931] | 4515 | Return a scan which has been baselined (all rows) by a polynomial.
|
---|
[880] | 4516 | Spectral lines are detected first using linefinder and masked out
|
---|
| 4517 | to avoid them affecting the baseline solution.
|
---|
| 4518 |
|
---|
| 4519 | Parameters:
|
---|
[2771] | 4520 | mask: an optional mask retreived from scantable
|
---|
| 4521 | order: the order of the polynomial (default is 0)
|
---|
[2189] | 4522 | insitu: if False a new scantable is returned.
|
---|
| 4523 | Otherwise, the scaling is done in-situ
|
---|
| 4524 | The default is taken from .asaprc (False)
|
---|
[2767] | 4525 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma)
|
---|
| 4526 | clipniter: maximum number of iteration of 'clipthresh'-sigma
|
---|
| 4527 | clipping (default is 0)
|
---|
[2189] | 4528 | edge: an optional number of channel to drop at
|
---|
| 4529 | the edge of spectrum. If only one value is
|
---|
| 4530 | specified, the same number will be dropped
|
---|
| 4531 | from both sides of the spectrum. Default
|
---|
| 4532 | is to keep all channels. Nested tuples
|
---|
| 4533 | represent individual edge selection for
|
---|
| 4534 | different IFs (a number of spectral channels
|
---|
| 4535 | can be different)
|
---|
| 4536 | threshold: the threshold used by line finder. It is
|
---|
| 4537 | better to keep it large as only strong lines
|
---|
| 4538 | affect the baseline solution.
|
---|
| 4539 | chan_avg_limit: a maximum number of consequtive spectral
|
---|
| 4540 | channels to average during the search of
|
---|
| 4541 | weak and broad lines. The default is no
|
---|
| 4542 | averaging (and no search for weak lines).
|
---|
| 4543 | If such lines can affect the fitted baseline
|
---|
| 4544 | (e.g. a high order polynomial is fitted),
|
---|
| 4545 | increase this parameter (usually values up
|
---|
| 4546 | to 8 are reasonable). Most users of this
|
---|
| 4547 | method should find the default value sufficient.
|
---|
| 4548 | plot: plot the fit and the residual. In this each
|
---|
| 4549 | indivual fit has to be approved, by typing 'y'
|
---|
| 4550 | or 'n'
|
---|
| 4551 | getresidual: if False, returns best-fit values instead of
|
---|
| 4552 | residual. (default is True)
|
---|
| 4553 | showprogress: show progress status for large data.
|
---|
| 4554 | default is True.
|
---|
| 4555 | minnrow: minimum number of input spectra to show.
|
---|
| 4556 | default is 1000.
|
---|
| 4557 | outlog: Output the coefficients of the best-fit
|
---|
| 4558 | function to logger (default is False)
|
---|
| 4559 | blfile: Name of a text file in which the best-fit
|
---|
| 4560 | parameter values to be written
|
---|
| 4561 | (default is "": no file/logger output)
|
---|
[2641] | 4562 | csvformat: if True blfile is csv-formatted, default is False.
|
---|
[2767] | 4563 | bltable: name of a baseline table where fitting results
|
---|
| 4564 | (coefficients, rms, etc.) are to be written.
|
---|
| 4565 | if given, fitting results will NOT be output to
|
---|
| 4566 | scantable (insitu=True) or None will be
|
---|
| 4567 | returned (insitu=False).
|
---|
| 4568 | (default is "": no table output)
|
---|
[1846] | 4569 |
|
---|
[2012] | 4570 | Example:
|
---|
| 4571 | bscan = scan.auto_poly_baseline(order=7, insitu=False)
|
---|
| 4572 | """
|
---|
[880] | 4573 |
|
---|
[2186] | 4574 | try:
|
---|
| 4575 | varlist = vars()
|
---|
[1846] | 4576 |
|
---|
[2269] | 4577 | if insitu is None:
|
---|
| 4578 | insitu = rcParams['insitu']
|
---|
[2186] | 4579 | if insitu:
|
---|
| 4580 | workscan = self
|
---|
| 4581 | else:
|
---|
| 4582 | workscan = self.copy()
|
---|
[1846] | 4583 |
|
---|
[2410] | 4584 | if mask is None: mask = []
|
---|
[2186] | 4585 | if order is None: order = 0
|
---|
[2767] | 4586 | if clipthresh is None: clipthresh = 3.0
|
---|
| 4587 | if clipniter is None: clipniter = 0
|
---|
[2186] | 4588 | if edge is None: edge = (0, 0)
|
---|
| 4589 | if threshold is None: threshold = 3
|
---|
| 4590 | if chan_avg_limit is None: chan_avg_limit = 1
|
---|
| 4591 | if plot is None: plot = False
|
---|
| 4592 | if getresidual is None: getresidual = True
|
---|
[2189] | 4593 | if showprogress is None: showprogress = True
|
---|
| 4594 | if minnrow is None: minnrow = 1000
|
---|
[2186] | 4595 | if outlog is None: outlog = False
|
---|
| 4596 | if blfile is None: blfile = ''
|
---|
[2641] | 4597 | if csvformat is None: csvformat = False
|
---|
[2767] | 4598 | if bltable is None: bltable = ''
|
---|
[1846] | 4599 |
|
---|
[2767] | 4600 | scsvformat = 'T' if csvformat else 'F'
|
---|
[2641] | 4601 |
|
---|
[2186] | 4602 | edge = normalise_edge_param(edge)
|
---|
[880] | 4603 |
|
---|
[2012] | 4604 | if plot:
|
---|
[2269] | 4605 | outblfile = (blfile != "") and \
|
---|
| 4606 | os.path.exists(os.path.expanduser(os.path.expandvars(blfile)))
|
---|
[2012] | 4607 | if outblfile: blf = open(blfile, "a")
|
---|
| 4608 |
|
---|
[2186] | 4609 | from asap.asaplinefind import linefinder
|
---|
[2012] | 4610 | fl = linefinder()
|
---|
[2269] | 4611 | fl.set_options(threshold=threshold, avg_limit=chan_avg_limit)
|
---|
[2012] | 4612 | fl.set_scan(workscan)
|
---|
[2186] | 4613 |
|
---|
[2012] | 4614 | f = fitter()
|
---|
| 4615 | f.set_function(lpoly=order)
|
---|
[880] | 4616 |
|
---|
[2186] | 4617 | rows = xrange(workscan.nrow())
|
---|
| 4618 | #if len(rows) > 0: workscan._init_blinfo()
|
---|
[2610] | 4619 |
|
---|
| 4620 | action = "H"
|
---|
[2012] | 4621 | for r in rows:
|
---|
[2186] | 4622 | idx = 2*workscan.getif(r)
|
---|
[2541] | 4623 | if mask:
|
---|
| 4624 | msk = mask_and(mask, workscan._getmask(r)) # (CAS-1434)
|
---|
| 4625 | else: # mask=None
|
---|
| 4626 | msk = workscan._getmask(r)
|
---|
| 4627 | fl.find_lines(r, msk, edge[idx:idx+2])
|
---|
[907] | 4628 |
|
---|
[2012] | 4629 | f.x = workscan._getabcissa(r)
|
---|
| 4630 | f.y = workscan._getspectrum(r)
|
---|
| 4631 | f.mask = fl.get_mask()
|
---|
| 4632 | f.data = None
|
---|
| 4633 | f.fit()
|
---|
| 4634 |
|
---|
[2610] | 4635 | if action != "Y": # skip plotting when accepting all
|
---|
| 4636 | f.plot(residual=True)
|
---|
| 4637 | #accept_fit = raw_input("Accept fit ( [y]/n ): ")
|
---|
| 4638 | accept_fit = self._get_verify_action("Accept fit?",action)
|
---|
| 4639 | if r == 0: action = None
|
---|
[2012] | 4640 | if accept_fit.upper() == "N":
|
---|
| 4641 | #workscan._append_blinfo(None, None, None)
|
---|
| 4642 | continue
|
---|
[2610] | 4643 | elif accept_fit.upper() == "R":
|
---|
| 4644 | break
|
---|
| 4645 | elif accept_fit.upper() == "A":
|
---|
| 4646 | action = "Y"
|
---|
[2012] | 4647 |
|
---|
| 4648 | blpars = f.get_parameters()
|
---|
| 4649 | masklist = workscan.get_masklist(f.mask, row=r, silent=True)
|
---|
| 4650 | #workscan._append_blinfo(blpars, masklist, f.mask)
|
---|
[2349] | 4651 | workscan._setspectrum(
|
---|
| 4652 | (f.fitter.getresidual() if getresidual
|
---|
| 4653 | else f.fitter.getfit()), r
|
---|
| 4654 | )
|
---|
[2012] | 4655 |
|
---|
| 4656 | if outblfile:
|
---|
| 4657 | rms = workscan.get_rms(f.mask, r)
|
---|
[2269] | 4658 | dataout = \
|
---|
| 4659 | workscan.format_blparams_row(blpars["params"],
|
---|
| 4660 | blpars["fixed"],
|
---|
| 4661 | rms, str(masklist),
|
---|
[2641] | 4662 | r, True, csvformat)
|
---|
[2012] | 4663 | blf.write(dataout)
|
---|
| 4664 |
|
---|
| 4665 | f._p.unmap()
|
---|
| 4666 | f._p = None
|
---|
| 4667 |
|
---|
| 4668 | if outblfile: blf.close()
|
---|
| 4669 | else:
|
---|
[2767] | 4670 | workscan._auto_poly_baseline(mask, order,
|
---|
| 4671 | clipthresh, clipniter,
|
---|
| 4672 | edge, threshold,
|
---|
[2269] | 4673 | chan_avg_limit, getresidual,
|
---|
| 4674 | pack_progress_params(showprogress,
|
---|
| 4675 | minnrow),
|
---|
[2767] | 4676 | outlog, scsvformat+blfile,
|
---|
| 4677 | bltable)
|
---|
| 4678 | workscan._add_history("auto_poly_baseline", varlist)
|
---|
[2012] | 4679 |
|
---|
[2767] | 4680 | if bltable == '':
|
---|
| 4681 | if insitu:
|
---|
| 4682 | self._assign(workscan)
|
---|
| 4683 | else:
|
---|
| 4684 | return workscan
|
---|
[2012] | 4685 | else:
|
---|
[2767] | 4686 | if not insitu:
|
---|
| 4687 | return None
|
---|
[2012] | 4688 |
|
---|
| 4689 | except RuntimeError, e:
|
---|
[2186] | 4690 | raise_fitting_failure_exception(e)
|
---|
[2012] | 4691 |
|
---|
| 4692 | def _init_blinfo(self):
|
---|
| 4693 | """\
|
---|
| 4694 | Initialise the following three auxiliary members:
|
---|
| 4695 | blpars : parameters of the best-fit baseline,
|
---|
| 4696 | masklists : mask data (edge positions of masked channels) and
|
---|
| 4697 | actualmask : mask data (in boolean list),
|
---|
| 4698 | to keep for use later (including output to logger/text files).
|
---|
| 4699 | Used by poly_baseline() and auto_poly_baseline() in case of
|
---|
| 4700 | 'plot=True'.
|
---|
| 4701 | """
|
---|
| 4702 | self.blpars = []
|
---|
| 4703 | self.masklists = []
|
---|
| 4704 | self.actualmask = []
|
---|
| 4705 | return
|
---|
[880] | 4706 |
|
---|
[2012] | 4707 | def _append_blinfo(self, data_blpars, data_masklists, data_actualmask):
|
---|
| 4708 | """\
|
---|
| 4709 | Append baseline-fitting related info to blpars, masklist and
|
---|
| 4710 | actualmask.
|
---|
| 4711 | """
|
---|
| 4712 | self.blpars.append(data_blpars)
|
---|
| 4713 | self.masklists.append(data_masklists)
|
---|
| 4714 | self.actualmask.append(data_actualmask)
|
---|
| 4715 | return
|
---|
| 4716 |
|
---|
[1862] | 4717 | @asaplog_post_dec
|
---|
[914] | 4718 | def rotate_linpolphase(self, angle):
|
---|
[1846] | 4719 | """\
|
---|
[914] | 4720 | Rotate the phase of the complex polarization O=Q+iU correlation.
|
---|
| 4721 | This is always done in situ in the raw data. So if you call this
|
---|
| 4722 | function more than once then each call rotates the phase further.
|
---|
[1846] | 4723 |
|
---|
[914] | 4724 | Parameters:
|
---|
[1846] | 4725 |
|
---|
[914] | 4726 | angle: The angle (degrees) to rotate (add) by.
|
---|
[1846] | 4727 |
|
---|
| 4728 | Example::
|
---|
| 4729 |
|
---|
[914] | 4730 | scan.rotate_linpolphase(2.3)
|
---|
[1846] | 4731 |
|
---|
[914] | 4732 | """
|
---|
| 4733 | varlist = vars()
|
---|
[936] | 4734 | self._math._rotate_linpolphase(self, angle)
|
---|
[914] | 4735 | self._add_history("rotate_linpolphase", varlist)
|
---|
| 4736 | return
|
---|
[710] | 4737 |
|
---|
[1862] | 4738 | @asaplog_post_dec
|
---|
[914] | 4739 | def rotate_xyphase(self, angle):
|
---|
[1846] | 4740 | """\
|
---|
[914] | 4741 | Rotate the phase of the XY correlation. This is always done in situ
|
---|
| 4742 | in the data. So if you call this function more than once
|
---|
| 4743 | then each call rotates the phase further.
|
---|
[1846] | 4744 |
|
---|
[914] | 4745 | Parameters:
|
---|
[1846] | 4746 |
|
---|
[914] | 4747 | angle: The angle (degrees) to rotate (add) by.
|
---|
[1846] | 4748 |
|
---|
| 4749 | Example::
|
---|
| 4750 |
|
---|
[914] | 4751 | scan.rotate_xyphase(2.3)
|
---|
[1846] | 4752 |
|
---|
[914] | 4753 | """
|
---|
| 4754 | varlist = vars()
|
---|
[936] | 4755 | self._math._rotate_xyphase(self, angle)
|
---|
[914] | 4756 | self._add_history("rotate_xyphase", varlist)
|
---|
| 4757 | return
|
---|
| 4758 |
|
---|
[1862] | 4759 | @asaplog_post_dec
|
---|
[914] | 4760 | def swap_linears(self):
|
---|
[1846] | 4761 | """\
|
---|
[1573] | 4762 | Swap the linear polarisations XX and YY, or better the first two
|
---|
[1348] | 4763 | polarisations as this also works for ciculars.
|
---|
[914] | 4764 | """
|
---|
| 4765 | varlist = vars()
|
---|
[936] | 4766 | self._math._swap_linears(self)
|
---|
[914] | 4767 | self._add_history("swap_linears", varlist)
|
---|
| 4768 | return
|
---|
| 4769 |
|
---|
[1862] | 4770 | @asaplog_post_dec
|
---|
[914] | 4771 | def invert_phase(self):
|
---|
[1846] | 4772 | """\
|
---|
[914] | 4773 | Invert the phase of the complex polarisation
|
---|
| 4774 | """
|
---|
| 4775 | varlist = vars()
|
---|
[936] | 4776 | self._math._invert_phase(self)
|
---|
[914] | 4777 | self._add_history("invert_phase", varlist)
|
---|
| 4778 | return
|
---|
| 4779 |
|
---|
[1862] | 4780 | @asaplog_post_dec
|
---|
[876] | 4781 | def add(self, offset, insitu=None):
|
---|
[1846] | 4782 | """\
|
---|
[513] | 4783 | Return a scan where all spectra have the offset added
|
---|
[1846] | 4784 |
|
---|
[513] | 4785 | Parameters:
|
---|
[1846] | 4786 |
|
---|
[513] | 4787 | offset: the offset
|
---|
[1855] | 4788 |
|
---|
[513] | 4789 | insitu: if False a new scantable is returned.
|
---|
| 4790 | Otherwise, the scaling is done in-situ
|
---|
| 4791 | The default is taken from .asaprc (False)
|
---|
[1846] | 4792 |
|
---|
[513] | 4793 | """
|
---|
| 4794 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 4795 | self._math._setinsitu(insitu)
|
---|
[513] | 4796 | varlist = vars()
|
---|
[2954] | 4797 | s = scantable(self._math._unaryop(self, offset, "ADD", False, False))
|
---|
[1118] | 4798 | s._add_history("add", varlist)
|
---|
[876] | 4799 | if insitu:
|
---|
| 4800 | self._assign(s)
|
---|
| 4801 | else:
|
---|
[513] | 4802 | return s
|
---|
| 4803 |
|
---|
[1862] | 4804 | @asaplog_post_dec
|
---|
[2966] | 4805 | def scale(self, factor, tsys=True, insitu=None):
|
---|
[1846] | 4806 | """\
|
---|
| 4807 |
|
---|
[1938] | 4808 | Return a scan where all spectra are scaled by the given 'factor'
|
---|
[1846] | 4809 |
|
---|
[513] | 4810 | Parameters:
|
---|
[1846] | 4811 |
|
---|
[1819] | 4812 | factor: the scaling factor (float or 1D float list)
|
---|
[1855] | 4813 |
|
---|
[513] | 4814 | insitu: if False a new scantable is returned.
|
---|
| 4815 | Otherwise, the scaling is done in-situ
|
---|
| 4816 | The default is taken from .asaprc (False)
|
---|
[1855] | 4817 |
|
---|
[513] | 4818 | tsys: if True (default) then apply the operation to Tsys
|
---|
| 4819 | as well as the data
|
---|
| 4820 | """
|
---|
| 4821 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 4822 | self._math._setinsitu(insitu)
|
---|
[513] | 4823 | varlist = vars()
|
---|
[1819] | 4824 | s = None
|
---|
| 4825 | import numpy
|
---|
| 4826 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray):
|
---|
[2320] | 4827 | if isinstance(factor[0], list) or isinstance(factor[0],
|
---|
| 4828 | numpy.ndarray):
|
---|
[1819] | 4829 | from asapmath import _array2dOp
|
---|
[2966] | 4830 | s = _array2dOp( self, factor, "MUL", tsys, insitu, True )
|
---|
[1819] | 4831 | else:
|
---|
[2320] | 4832 | s = scantable( self._math._arrayop( self, factor,
|
---|
[2966] | 4833 | "MUL", tsys, True ) )
|
---|
[1819] | 4834 | else:
|
---|
[2966] | 4835 | s = scantable(self._math._unaryop(self, factor, "MUL", tsys, True ))
|
---|
[1118] | 4836 | s._add_history("scale", varlist)
|
---|
[876] | 4837 | if insitu:
|
---|
| 4838 | self._assign(s)
|
---|
| 4839 | else:
|
---|
[513] | 4840 | return s
|
---|
| 4841 |
|
---|
[2349] | 4842 | @preserve_selection
|
---|
| 4843 | def set_sourcetype(self, match, matchtype="pattern",
|
---|
[1504] | 4844 | sourcetype="reference"):
|
---|
[1846] | 4845 | """\
|
---|
[1502] | 4846 | Set the type of the source to be an source or reference scan
|
---|
[1846] | 4847 | using the provided pattern.
|
---|
| 4848 |
|
---|
[1502] | 4849 | Parameters:
|
---|
[1846] | 4850 |
|
---|
[1504] | 4851 | match: a Unix style pattern, regular expression or selector
|
---|
[1855] | 4852 |
|
---|
[1504] | 4853 | matchtype: 'pattern' (default) UNIX style pattern or
|
---|
| 4854 | 'regex' regular expression
|
---|
[1855] | 4855 |
|
---|
[1502] | 4856 | sourcetype: the type of the source to use (source/reference)
|
---|
[1846] | 4857 |
|
---|
[1502] | 4858 | """
|
---|
| 4859 | varlist = vars()
|
---|
| 4860 | stype = -1
|
---|
[2480] | 4861 | if sourcetype.lower().startswith("r") or sourcetype.lower() == "off":
|
---|
[1502] | 4862 | stype = 1
|
---|
[2480] | 4863 | elif sourcetype.lower().startswith("s") or sourcetype.lower() == "on":
|
---|
[1502] | 4864 | stype = 0
|
---|
[1504] | 4865 | else:
|
---|
[2480] | 4866 | raise ValueError("Illegal sourcetype use s(ource)/on or r(eference)/off")
|
---|
[1504] | 4867 | if matchtype.lower().startswith("p"):
|
---|
| 4868 | matchtype = "pattern"
|
---|
| 4869 | elif matchtype.lower().startswith("r"):
|
---|
| 4870 | matchtype = "regex"
|
---|
| 4871 | else:
|
---|
| 4872 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)")
|
---|
[1502] | 4873 | sel = selector()
|
---|
| 4874 | if isinstance(match, selector):
|
---|
| 4875 | sel = match
|
---|
| 4876 | else:
|
---|
[2480] | 4877 | sel.set_query("SRCNAME=%s('%s')" % (matchtype, match))
|
---|
| 4878 | self.set_selection(sel)
|
---|
[1502] | 4879 | self._setsourcetype(stype)
|
---|
[1573] | 4880 | self._add_history("set_sourcetype", varlist)
|
---|
[1502] | 4881 |
|
---|
[2818] | 4882 |
|
---|
| 4883 | def set_sourcename(self, name):
|
---|
| 4884 | varlist = vars()
|
---|
| 4885 | self._setsourcename(name)
|
---|
| 4886 | self._add_history("set_sourcename", varlist)
|
---|
| 4887 |
|
---|
[1862] | 4888 | @asaplog_post_dec
|
---|
[1857] | 4889 | @preserve_selection
|
---|
[1819] | 4890 | def auto_quotient(self, preserve=True, mode='paired', verify=False):
|
---|
[1846] | 4891 | """\
|
---|
[670] | 4892 | This function allows to build quotients automatically.
|
---|
[1819] | 4893 | It assumes the observation to have the same number of
|
---|
[670] | 4894 | "ons" and "offs"
|
---|
[1846] | 4895 |
|
---|
[670] | 4896 | Parameters:
|
---|
[1846] | 4897 |
|
---|
[710] | 4898 | preserve: you can preserve (default) the continuum or
|
---|
| 4899 | remove it. The equations used are
|
---|
[1857] | 4900 |
|
---|
[670] | 4901 | preserve: Output = Toff * (on/off) - Toff
|
---|
[1857] | 4902 |
|
---|
[1070] | 4903 | remove: Output = Toff * (on/off) - Ton
|
---|
[1855] | 4904 |
|
---|
[1573] | 4905 | mode: the on/off detection mode
|
---|
[1348] | 4906 | 'paired' (default)
|
---|
| 4907 | identifies 'off' scans by the
|
---|
| 4908 | trailing '_R' (Mopra/Parkes) or
|
---|
| 4909 | '_e'/'_w' (Tid) and matches
|
---|
| 4910 | on/off pairs from the observing pattern
|
---|
[1502] | 4911 | 'time'
|
---|
| 4912 | finds the closest off in time
|
---|
[1348] | 4913 |
|
---|
[1857] | 4914 | .. todo:: verify argument is not implemented
|
---|
| 4915 |
|
---|
[670] | 4916 | """
|
---|
[1857] | 4917 | varlist = vars()
|
---|
[1348] | 4918 | modes = ["time", "paired"]
|
---|
[670] | 4919 | if not mode in modes:
|
---|
[876] | 4920 | msg = "please provide valid mode. Valid modes are %s" % (modes)
|
---|
| 4921 | raise ValueError(msg)
|
---|
[1348] | 4922 | s = None
|
---|
| 4923 | if mode.lower() == "paired":
|
---|
[2840] | 4924 | from asap._asap import srctype
|
---|
[1857] | 4925 | sel = self.get_selection()
|
---|
[2840] | 4926 | #sel.set_query("SRCTYPE==psoff")
|
---|
| 4927 | sel.set_types(srctype.psoff)
|
---|
[1356] | 4928 | self.set_selection(sel)
|
---|
[1348] | 4929 | offs = self.copy()
|
---|
[2840] | 4930 | #sel.set_query("SRCTYPE==pson")
|
---|
| 4931 | sel.set_types(srctype.pson)
|
---|
[1356] | 4932 | self.set_selection(sel)
|
---|
[1348] | 4933 | ons = self.copy()
|
---|
| 4934 | s = scantable(self._math._quotient(ons, offs, preserve))
|
---|
| 4935 | elif mode.lower() == "time":
|
---|
| 4936 | s = scantable(self._math._auto_quotient(self, mode, preserve))
|
---|
[1118] | 4937 | s._add_history("auto_quotient", varlist)
|
---|
[876] | 4938 | return s
|
---|
[710] | 4939 |
|
---|
[1862] | 4940 | @asaplog_post_dec
|
---|
[1145] | 4941 | def mx_quotient(self, mask = None, weight='median', preserve=True):
|
---|
[1846] | 4942 | """\
|
---|
[1143] | 4943 | Form a quotient using "off" beams when observing in "MX" mode.
|
---|
[1846] | 4944 |
|
---|
[1143] | 4945 | Parameters:
|
---|
[1846] | 4946 |
|
---|
[1145] | 4947 | mask: an optional mask to be used when weight == 'stddev'
|
---|
[1855] | 4948 |
|
---|
[1143] | 4949 | weight: How to average the off beams. Default is 'median'.
|
---|
[1855] | 4950 |
|
---|
[1145] | 4951 | preserve: you can preserve (default) the continuum or
|
---|
[1855] | 4952 | remove it. The equations used are:
|
---|
[1846] | 4953 |
|
---|
[1855] | 4954 | preserve: Output = Toff * (on/off) - Toff
|
---|
| 4955 |
|
---|
| 4956 | remove: Output = Toff * (on/off) - Ton
|
---|
| 4957 |
|
---|
[1217] | 4958 | """
|
---|
[1593] | 4959 | mask = mask or ()
|
---|
[1141] | 4960 | varlist = vars()
|
---|
| 4961 | on = scantable(self._math._mx_extract(self, 'on'))
|
---|
[1143] | 4962 | preoff = scantable(self._math._mx_extract(self, 'off'))
|
---|
| 4963 | off = preoff.average_time(mask=mask, weight=weight, scanav=False)
|
---|
[1217] | 4964 | from asapmath import quotient
|
---|
[1145] | 4965 | q = quotient(on, off, preserve)
|
---|
[1143] | 4966 | q._add_history("mx_quotient", varlist)
|
---|
[1217] | 4967 | return q
|
---|
[513] | 4968 |
|
---|
[1862] | 4969 | @asaplog_post_dec
|
---|
[718] | 4970 | def freq_switch(self, insitu=None):
|
---|
[1846] | 4971 | """\
|
---|
[718] | 4972 | Apply frequency switching to the data.
|
---|
[1846] | 4973 |
|
---|
[718] | 4974 | Parameters:
|
---|
[1846] | 4975 |
|
---|
[718] | 4976 | insitu: if False a new scantable is returned.
|
---|
| 4977 | Otherwise, the swictching is done in-situ
|
---|
| 4978 | The default is taken from .asaprc (False)
|
---|
[1846] | 4979 |
|
---|
[718] | 4980 | """
|
---|
| 4981 | if insitu is None: insitu = rcParams['insitu']
|
---|
[876] | 4982 | self._math._setinsitu(insitu)
|
---|
[718] | 4983 | varlist = vars()
|
---|
[876] | 4984 | s = scantable(self._math._freqswitch(self))
|
---|
[1118] | 4985 | s._add_history("freq_switch", varlist)
|
---|
[1856] | 4986 | if insitu:
|
---|
| 4987 | self._assign(s)
|
---|
| 4988 | else:
|
---|
| 4989 | return s
|
---|
[718] | 4990 |
|
---|
[1862] | 4991 | @asaplog_post_dec
|
---|
[780] | 4992 | def recalc_azel(self):
|
---|
[1846] | 4993 | """Recalculate the azimuth and elevation for each position."""
|
---|
[780] | 4994 | varlist = vars()
|
---|
[876] | 4995 | self._recalcazel()
|
---|
[780] | 4996 | self._add_history("recalc_azel", varlist)
|
---|
| 4997 | return
|
---|
| 4998 |
|
---|
[1862] | 4999 | @asaplog_post_dec
|
---|
[513] | 5000 | def __add__(self, other):
|
---|
[2574] | 5001 | """
|
---|
| 5002 | implicit on all axes and on Tsys
|
---|
| 5003 | """
|
---|
[513] | 5004 | varlist = vars()
|
---|
[2574] | 5005 | s = self.__op( other, "ADD" )
|
---|
[513] | 5006 | s._add_history("operator +", varlist)
|
---|
| 5007 | return s
|
---|
| 5008 |
|
---|
[1862] | 5009 | @asaplog_post_dec
|
---|
[513] | 5010 | def __sub__(self, other):
|
---|
| 5011 | """
|
---|
| 5012 | implicit on all axes and on Tsys
|
---|
| 5013 | """
|
---|
| 5014 | varlist = vars()
|
---|
[2574] | 5015 | s = self.__op( other, "SUB" )
|
---|
[513] | 5016 | s._add_history("operator -", varlist)
|
---|
| 5017 | return s
|
---|
[710] | 5018 |
|
---|
[1862] | 5019 | @asaplog_post_dec
|
---|
[513] | 5020 | def __mul__(self, other):
|
---|
| 5021 | """
|
---|
| 5022 | implicit on all axes and on Tsys
|
---|
| 5023 | """
|
---|
| 5024 | varlist = vars()
|
---|
[2574] | 5025 | s = self.__op( other, "MUL" ) ;
|
---|
[513] | 5026 | s._add_history("operator *", varlist)
|
---|
| 5027 | return s
|
---|
| 5028 |
|
---|
[710] | 5029 |
|
---|
[1862] | 5030 | @asaplog_post_dec
|
---|
[513] | 5031 | def __div__(self, other):
|
---|
| 5032 | """
|
---|
| 5033 | implicit on all axes and on Tsys
|
---|
| 5034 | """
|
---|
| 5035 | varlist = vars()
|
---|
[2574] | 5036 | s = self.__op( other, "DIV" )
|
---|
| 5037 | s._add_history("operator /", varlist)
|
---|
| 5038 | return s
|
---|
| 5039 |
|
---|
| 5040 | @asaplog_post_dec
|
---|
| 5041 | def __op( self, other, mode ):
|
---|
[513] | 5042 | s = None
|
---|
| 5043 | if isinstance(other, scantable):
|
---|
[2574] | 5044 | s = scantable(self._math._binaryop(self, other, mode))
|
---|
[513] | 5045 | elif isinstance(other, float):
|
---|
| 5046 | if other == 0.0:
|
---|
[718] | 5047 | raise ZeroDivisionError("Dividing by zero is not recommended")
|
---|
[2954] | 5048 | s = scantable(self._math._unaryop(self, other, mode, False, False))
|
---|
[2144] | 5049 | elif isinstance(other, list) or isinstance(other, numpy.ndarray):
|
---|
[2349] | 5050 | if isinstance(other[0], list) \
|
---|
| 5051 | or isinstance(other[0], numpy.ndarray):
|
---|
[2144] | 5052 | from asapmath import _array2dOp
|
---|
[2574] | 5053 | s = _array2dOp( self, other, mode, False )
|
---|
[2144] | 5054 | else:
|
---|
[2574] | 5055 | s = scantable( self._math._arrayop( self, other,
|
---|
[2954] | 5056 | mode, False, False ) )
|
---|
[513] | 5057 | else:
|
---|
[718] | 5058 | raise TypeError("Other input is not a scantable or float value")
|
---|
[513] | 5059 | return s
|
---|
| 5060 |
|
---|
[1862] | 5061 | @asaplog_post_dec
|
---|
[530] | 5062 | def get_fit(self, row=0):
|
---|
[1846] | 5063 | """\
|
---|
[530] | 5064 | Print or return the stored fits for a row in the scantable
|
---|
[1846] | 5065 |
|
---|
[530] | 5066 | Parameters:
|
---|
[1846] | 5067 |
|
---|
[530] | 5068 | row: the row which the fit has been applied to.
|
---|
[1846] | 5069 |
|
---|
[530] | 5070 | """
|
---|
| 5071 | if row > self.nrow():
|
---|
| 5072 | return
|
---|
[976] | 5073 | from asap.asapfit import asapfit
|
---|
[530] | 5074 | fit = asapfit(self._getfit(row))
|
---|
[1859] | 5075 | asaplog.push( '%s' %(fit) )
|
---|
| 5076 | return fit.as_dict()
|
---|
[530] | 5077 |
|
---|
[2349] | 5078 | @preserve_selection
|
---|
[1483] | 5079 | def flag_nans(self):
|
---|
[1846] | 5080 | """\
|
---|
[1483] | 5081 | Utility function to flag NaN values in the scantable.
|
---|
| 5082 | """
|
---|
| 5083 | import numpy
|
---|
| 5084 | basesel = self.get_selection()
|
---|
| 5085 | for i in range(self.nrow()):
|
---|
[1589] | 5086 | sel = self.get_row_selector(i)
|
---|
| 5087 | self.set_selection(basesel+sel)
|
---|
[1483] | 5088 | nans = numpy.isnan(self._getspectrum(0))
|
---|
[2877] | 5089 | if numpy.any(nans):
|
---|
| 5090 | bnans = [ bool(v) for v in nans]
|
---|
| 5091 | self.flag(bnans)
|
---|
| 5092 |
|
---|
| 5093 | self.set_selection(basesel)
|
---|
[1483] | 5094 |
|
---|
[1588] | 5095 | def get_row_selector(self, rowno):
|
---|
[1992] | 5096 | return selector(rows=[rowno])
|
---|
[1573] | 5097 |
|
---|
[484] | 5098 | def _add_history(self, funcname, parameters):
|
---|
[1435] | 5099 | if not rcParams['scantable.history']:
|
---|
| 5100 | return
|
---|
[484] | 5101 | # create date
|
---|
| 5102 | sep = "##"
|
---|
| 5103 | from datetime import datetime
|
---|
| 5104 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S')
|
---|
| 5105 | hist = dstr+sep
|
---|
| 5106 | hist += funcname+sep#cdate+sep
|
---|
[2349] | 5107 | if parameters.has_key('self'):
|
---|
| 5108 | del parameters['self']
|
---|
[1118] | 5109 | for k, v in parameters.iteritems():
|
---|
[484] | 5110 | if type(v) is dict:
|
---|
[1118] | 5111 | for k2, v2 in v.iteritems():
|
---|
[484] | 5112 | hist += k2
|
---|
| 5113 | hist += "="
|
---|
[1118] | 5114 | if isinstance(v2, scantable):
|
---|
[484] | 5115 | hist += 'scantable'
|
---|
| 5116 | elif k2 == 'mask':
|
---|
[1118] | 5117 | if isinstance(v2, list) or isinstance(v2, tuple):
|
---|
[513] | 5118 | hist += str(self._zip_mask(v2))
|
---|
| 5119 | else:
|
---|
| 5120 | hist += str(v2)
|
---|
[484] | 5121 | else:
|
---|
[513] | 5122 | hist += str(v2)
|
---|
[484] | 5123 | else:
|
---|
| 5124 | hist += k
|
---|
| 5125 | hist += "="
|
---|
[1118] | 5126 | if isinstance(v, scantable):
|
---|
[484] | 5127 | hist += 'scantable'
|
---|
| 5128 | elif k == 'mask':
|
---|
[1118] | 5129 | if isinstance(v, list) or isinstance(v, tuple):
|
---|
[513] | 5130 | hist += str(self._zip_mask(v))
|
---|
| 5131 | else:
|
---|
| 5132 | hist += str(v)
|
---|
[484] | 5133 | else:
|
---|
| 5134 | hist += str(v)
|
---|
| 5135 | hist += sep
|
---|
| 5136 | hist = hist[:-2] # remove trailing '##'
|
---|
| 5137 | self._addhistory(hist)
|
---|
| 5138 |
|
---|
[710] | 5139 |
|
---|
[484] | 5140 | def _zip_mask(self, mask):
|
---|
| 5141 | mask = list(mask)
|
---|
| 5142 | i = 0
|
---|
| 5143 | segments = []
|
---|
| 5144 | while mask[i:].count(1):
|
---|
| 5145 | i += mask[i:].index(1)
|
---|
| 5146 | if mask[i:].count(0):
|
---|
| 5147 | j = i + mask[i:].index(0)
|
---|
| 5148 | else:
|
---|
[710] | 5149 | j = len(mask)
|
---|
[1118] | 5150 | segments.append([i, j])
|
---|
[710] | 5151 | i = j
|
---|
[484] | 5152 | return segments
|
---|
[714] | 5153 |
|
---|
[626] | 5154 | def _get_ordinate_label(self):
|
---|
| 5155 | fu = "("+self.get_fluxunit()+")"
|
---|
| 5156 | import re
|
---|
| 5157 | lbl = "Intensity"
|
---|
[1118] | 5158 | if re.match(".K.", fu):
|
---|
[626] | 5159 | lbl = "Brightness Temperature "+ fu
|
---|
[1118] | 5160 | elif re.match(".Jy.", fu):
|
---|
[626] | 5161 | lbl = "Flux density "+ fu
|
---|
| 5162 | return lbl
|
---|
[710] | 5163 |
|
---|
[876] | 5164 | def _check_ifs(self):
|
---|
[2349] | 5165 | # return len(set([self.nchan(i) for i in self.getifnos()])) == 1
|
---|
[1986] | 5166 | nchans = [self.nchan(i) for i in self.getifnos()]
|
---|
[2004] | 5167 | nchans = filter(lambda t: t > 0, nchans)
|
---|
[876] | 5168 | return (sum(nchans)/len(nchans) == nchans[0])
|
---|
[976] | 5169 |
|
---|
[1862] | 5170 | @asaplog_post_dec
|
---|
[1916] | 5171 | def _fill(self, names, unit, average, opts={}):
|
---|
[976] | 5172 | first = True
|
---|
| 5173 | fullnames = []
|
---|
| 5174 | for name in names:
|
---|
| 5175 | name = os.path.expandvars(name)
|
---|
| 5176 | name = os.path.expanduser(name)
|
---|
| 5177 | if not os.path.exists(name):
|
---|
| 5178 | msg = "File '%s' does not exists" % (name)
|
---|
| 5179 | raise IOError(msg)
|
---|
| 5180 | fullnames.append(name)
|
---|
| 5181 | if average:
|
---|
| 5182 | asaplog.push('Auto averaging integrations')
|
---|
[1079] | 5183 | stype = int(rcParams['scantable.storage'].lower() == 'disk')
|
---|
[976] | 5184 | for name in fullnames:
|
---|
[1073] | 5185 | tbl = Scantable(stype)
|
---|
[2004] | 5186 | if is_ms( name ):
|
---|
| 5187 | r = msfiller( tbl )
|
---|
| 5188 | else:
|
---|
| 5189 | r = filler( tbl )
|
---|
[976] | 5190 | msg = "Importing %s..." % (name)
|
---|
[1118] | 5191 | asaplog.push(msg, False)
|
---|
[2349] | 5192 | r.open(name, opts)
|
---|
[2480] | 5193 | rx = rcParams['scantable.reference']
|
---|
| 5194 | r.setreferenceexpr(rx)
|
---|
[1843] | 5195 | r.fill()
|
---|
[976] | 5196 | if average:
|
---|
[1118] | 5197 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN')
|
---|
[976] | 5198 | if not first:
|
---|
[2902] | 5199 | tbl = self._math._merge([self, tbl])
|
---|
[976] | 5200 | Scantable.__init__(self, tbl)
|
---|
[1843] | 5201 | r.close()
|
---|
[1118] | 5202 | del r, tbl
|
---|
[976] | 5203 | first = False
|
---|
[1861] | 5204 | #flush log
|
---|
| 5205 | asaplog.post()
|
---|
[976] | 5206 | if unit is not None:
|
---|
| 5207 | self.set_fluxunit(unit)
|
---|
[1824] | 5208 | if not is_casapy():
|
---|
| 5209 | self.set_freqframe(rcParams['scantable.freqframe'])
|
---|
[976] | 5210 |
|
---|
[2610] | 5211 | def _get_verify_action( self, msg, action=None ):
|
---|
| 5212 | valid_act = ['Y', 'N', 'A', 'R']
|
---|
| 5213 | if not action or not isinstance(action, str):
|
---|
| 5214 | action = raw_input("%s [Y/n/a/r] (h for help): " % msg)
|
---|
| 5215 | if action == '':
|
---|
| 5216 | return "Y"
|
---|
| 5217 | elif (action.upper()[0] in valid_act):
|
---|
| 5218 | return action.upper()[0]
|
---|
| 5219 | elif (action.upper()[0] in ['H','?']):
|
---|
| 5220 | print "Available actions of verification [Y|n|a|r]"
|
---|
| 5221 | print " Y : Yes for current data (default)"
|
---|
| 5222 | print " N : No for current data"
|
---|
| 5223 | print " A : Accept all in the following and exit from verification"
|
---|
| 5224 | print " R : Reject all in the following and exit from verification"
|
---|
| 5225 | print " H or ?: help (show this message)"
|
---|
| 5226 | return self._get_verify_action(msg)
|
---|
| 5227 | else:
|
---|
| 5228 | return 'Y'
|
---|
[2012] | 5229 |
|
---|
[1402] | 5230 | def __getitem__(self, key):
|
---|
| 5231 | if key < 0:
|
---|
| 5232 | key += self.nrow()
|
---|
| 5233 | if key >= self.nrow():
|
---|
| 5234 | raise IndexError("Row index out of range.")
|
---|
| 5235 | return self._getspectrum(key)
|
---|
| 5236 |
|
---|
| 5237 | def __setitem__(self, key, value):
|
---|
| 5238 | if key < 0:
|
---|
| 5239 | key += self.nrow()
|
---|
| 5240 | if key >= self.nrow():
|
---|
| 5241 | raise IndexError("Row index out of range.")
|
---|
| 5242 | if not hasattr(value, "__len__") or \
|
---|
| 5243 | len(value) > self.nchan(self.getif(key)):
|
---|
| 5244 | raise ValueError("Spectrum length doesn't match.")
|
---|
| 5245 | return self._setspectrum(value, key)
|
---|
| 5246 |
|
---|
| 5247 | def __len__(self):
|
---|
| 5248 | return self.nrow()
|
---|
| 5249 |
|
---|
| 5250 | def __iter__(self):
|
---|
| 5251 | for i in range(len(self)):
|
---|
| 5252 | yield self[i]
|
---|