[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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[2315] | 4 | import tempfile |
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[1948] | 5 | import numpy |
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[1691] | 6 | try: |
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| 7 | from functools import wraps as wraps_dec |
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| 8 | except ImportError: |
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| 9 | from asap.compatibility import wraps as wraps_dec |
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| 10 | |
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[1824] | 11 | from asap.env import is_casapy |
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[876] | 12 | from asap._asap import Scantable |
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[2004] | 13 | from asap._asap import filler, msfiller |
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[1824] | 14 | from asap.parameters import rcParams |
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[1862] | 15 | from asap.logging import asaplog, asaplog_post_dec |
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[1824] | 16 | from asap.selector import selector |
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| 17 | from asap.linecatalog import linecatalog |
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[1600] | 18 | from asap.coordinate import coordinate |
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[1859] | 19 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page |
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[1907] | 20 | from asap.asapfitter import fitter |
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[102] | 21 | |
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[1689] | 22 | |
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| 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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| 48 | #if ( l.find('Scantable') != -1 ): |
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| 49 | if ( l.find('Measurement Set') == -1 ): |
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| 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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[876] | 176 | class scantable(Scantable): |
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[1846] | 177 | """\ |
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| 178 | The ASAP container for scans (single-dish data). |
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[102] | 179 | """ |
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[1819] | 180 | |
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[1862] | 181 | @asaplog_post_dec |
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[2315] | 182 | def __init__(self, filename, average=None, unit=None, parallactify=None, |
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| 183 | **args): |
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[1846] | 184 | """\ |
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[102] | 185 | Create a scantable from a saved one or make a reference |
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[1846] | 186 | |
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[102] | 187 | Parameters: |
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[1846] | 188 | |
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| 189 | filename: the name of an asap table on disk |
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| 190 | or |
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| 191 | the name of a rpfits/sdfits/ms file |
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| 192 | (integrations within scans are auto averaged |
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| 193 | and the whole file is read) or |
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| 194 | [advanced] a reference to an existing scantable |
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| 195 | |
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| 196 | average: average all integrations withinb a scan on read. |
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| 197 | The default (True) is taken from .asaprc. |
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| 198 | |
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[484] | 199 | unit: brightness unit; must be consistent with K or Jy. |
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[1846] | 200 | Over-rides the default selected by the filler |
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| 201 | (input rpfits/sdfits/ms) or replaces the value |
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| 202 | in existing scantables |
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| 203 | |
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[1920] | 204 | antenna: for MeasurementSet input data only: |
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[2349] | 205 | Antenna selection. integer (id) or string |
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| 206 | (name or id). |
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[1846] | 207 | |
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[2349] | 208 | parallactify: Indicate that the data had been parallactified. |
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| 209 | Default (false) is taken from rc file. |
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[1846] | 210 | |
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[710] | 211 | """ |
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[976] | 212 | if average is None: |
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[710] | 213 | average = rcParams['scantable.autoaverage'] |
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[1593] | 214 | parallactify = parallactify or rcParams['scantable.parallactify'] |
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[1259] | 215 | varlist = vars() |
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[876] | 216 | from asap._asap import stmath |
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[1819] | 217 | self._math = stmath( rcParams['insitu'] ) |
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[876] | 218 | if isinstance(filename, Scantable): |
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| 219 | Scantable.__init__(self, filename) |
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[181] | 220 | else: |
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[1697] | 221 | if isinstance(filename, str): |
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[976] | 222 | filename = os.path.expandvars(filename) |
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| 223 | filename = os.path.expanduser(filename) |
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| 224 | if not os.path.exists(filename): |
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| 225 | s = "File '%s' not found." % (filename) |
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| 226 | raise IOError(s) |
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[1697] | 227 | if is_scantable(filename): |
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| 228 | ondisk = rcParams['scantable.storage'] == 'disk' |
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| 229 | Scantable.__init__(self, filename, ondisk) |
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| 230 | if unit is not None: |
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| 231 | self.set_fluxunit(unit) |
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[2008] | 232 | if average: |
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| 233 | self._assign( self.average_time( scanav=True ) ) |
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[1819] | 234 | # do not reset to the default freqframe |
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| 235 | #self.set_freqframe(rcParams['scantable.freqframe']) |
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[1883] | 236 | elif is_ms(filename): |
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[1916] | 237 | # Measurement Set |
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| 238 | opts={'ms': {}} |
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| 239 | mskeys=['getpt','antenna'] |
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| 240 | for key in mskeys: |
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| 241 | if key in args.keys(): |
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| 242 | opts['ms'][key] = args[key] |
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| 243 | self._fill([filename], unit, average, opts) |
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[1893] | 244 | elif os.path.isfile(filename): |
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[1916] | 245 | self._fill([filename], unit, average) |
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[2350] | 246 | # only apply to new data not "copy constructor" |
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| 247 | self.parallactify(parallactify) |
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[1883] | 248 | else: |
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[1819] | 249 | msg = "The given file '%s'is not a valid " \ |
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| 250 | "asap table." % (filename) |
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[1859] | 251 | raise IOError(msg) |
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[1118] | 252 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
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[976] | 253 | and isinstance(filename[-1], str): |
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[1916] | 254 | self._fill(filename, unit, average) |
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[1586] | 255 | self.parallactify(parallactify) |
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[1259] | 256 | self._add_history("scantable", varlist) |
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[102] | 257 | |
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[1862] | 258 | @asaplog_post_dec |
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[876] | 259 | def save(self, name=None, format=None, overwrite=False): |
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[1846] | 260 | """\ |
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[1280] | 261 | Store the scantable on disk. This can be an asap (aips++) Table, |
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| 262 | SDFITS or MS2 format. |
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[1846] | 263 | |
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[116] | 264 | Parameters: |
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[1846] | 265 | |
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[1093] | 266 | name: the name of the outputfile. For format "ASCII" |
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| 267 | this is the root file name (data in 'name'.txt |
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[497] | 268 | and header in 'name'_header.txt) |
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[1855] | 269 | |
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[116] | 270 | format: an optional file format. Default is ASAP. |
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[1855] | 271 | Allowed are: |
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| 272 | |
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| 273 | * 'ASAP' (save as ASAP [aips++] Table), |
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| 274 | * 'SDFITS' (save as SDFITS file) |
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| 275 | * 'ASCII' (saves as ascii text file) |
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| 276 | * 'MS2' (saves as an casacore MeasurementSet V2) |
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[2315] | 277 | * 'FITS' (save as image FITS - not readable by |
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| 278 | class) |
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[1855] | 279 | * 'CLASS' (save as FITS readable by CLASS) |
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| 280 | |
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[411] | 281 | overwrite: If the file should be overwritten if it exists. |
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[256] | 282 | The default False is to return with warning |
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[411] | 283 | without writing the output. USE WITH CARE. |
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[1855] | 284 | |
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[1846] | 285 | Example:: |
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| 286 | |
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[116] | 287 | scan.save('myscan.asap') |
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[1118] | 288 | scan.save('myscan.sdfits', 'SDFITS') |
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[1846] | 289 | |
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[116] | 290 | """ |
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[411] | 291 | from os import path |
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[1593] | 292 | format = format or rcParams['scantable.save'] |
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[256] | 293 | suffix = '.'+format.lower() |
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[1118] | 294 | if name is None or name == "": |
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[256] | 295 | name = 'scantable'+suffix |
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[718] | 296 | msg = "No filename given. Using default name %s..." % name |
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| 297 | asaplog.push(msg) |
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[411] | 298 | name = path.expandvars(name) |
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[256] | 299 | if path.isfile(name) or path.isdir(name): |
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| 300 | if not overwrite: |
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[718] | 301 | msg = "File %s exists." % name |
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[1859] | 302 | raise IOError(msg) |
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[451] | 303 | format2 = format.upper() |
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| 304 | if format2 == 'ASAP': |
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[116] | 305 | self._save(name) |
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[2029] | 306 | elif format2 == 'MS2': |
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| 307 | msopt = {'ms': {'overwrite': overwrite } } |
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| 308 | from asap._asap import mswriter |
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| 309 | writer = mswriter( self ) |
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| 310 | writer.write( name, msopt ) |
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[116] | 311 | else: |
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[989] | 312 | from asap._asap import stwriter as stw |
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[1118] | 313 | writer = stw(format2) |
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| 314 | writer.write(self, name) |
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[116] | 315 | return |
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| 316 | |
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[102] | 317 | def copy(self): |
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[1846] | 318 | """Return a copy of this scantable. |
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| 319 | |
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| 320 | *Note*: |
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| 321 | |
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[1348] | 322 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
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[1846] | 323 | |
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| 324 | Example:: |
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| 325 | |
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[102] | 326 | copiedscan = scan.copy() |
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[1846] | 327 | |
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[102] | 328 | """ |
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[876] | 329 | sd = scantable(Scantable._copy(self)) |
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[113] | 330 | return sd |
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| 331 | |
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[1093] | 332 | def drop_scan(self, scanid=None): |
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[1846] | 333 | """\ |
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[1093] | 334 | Return a new scantable where the specified scan number(s) has(have) |
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| 335 | been dropped. |
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[1846] | 336 | |
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[1093] | 337 | Parameters: |
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[1846] | 338 | |
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[1093] | 339 | scanid: a (list of) scan number(s) |
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[1846] | 340 | |
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[1093] | 341 | """ |
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| 342 | from asap import _is_sequence_or_number as _is_valid |
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| 343 | from asap import _to_list |
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| 344 | from asap import unique |
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| 345 | if not _is_valid(scanid): |
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[2315] | 346 | raise RuntimeError( 'Please specify a scanno to drop from the' |
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| 347 | ' scantable' ) |
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[1859] | 348 | scanid = _to_list(scanid) |
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| 349 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
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| 350 | for sid in scanid: allscans.remove(sid) |
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| 351 | if len(allscans) == 0: |
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| 352 | raise ValueError("Can't remove all scans") |
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| 353 | sel = selector(scans=allscans) |
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| 354 | return self._select_copy(sel) |
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[1093] | 355 | |
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[1594] | 356 | def _select_copy(self, selection): |
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| 357 | orig = self.get_selection() |
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| 358 | self.set_selection(orig+selection) |
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| 359 | cp = self.copy() |
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| 360 | self.set_selection(orig) |
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| 361 | return cp |
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| 362 | |
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[102] | 363 | def get_scan(self, scanid=None): |
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[1855] | 364 | """\ |
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[102] | 365 | Return a specific scan (by scanno) or collection of scans (by |
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| 366 | source name) in a new scantable. |
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[1846] | 367 | |
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| 368 | *Note*: |
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| 369 | |
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[1348] | 370 | See scantable.drop_scan() for the inverse operation. |
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[1846] | 371 | |
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[102] | 372 | Parameters: |
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[1846] | 373 | |
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[513] | 374 | scanid: a (list of) scanno or a source name, unix-style |
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| 375 | patterns are accepted for source name matching, e.g. |
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| 376 | '*_R' gets all 'ref scans |
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[1846] | 377 | |
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| 378 | Example:: |
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| 379 | |
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[513] | 380 | # get all scans containing the source '323p459' |
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| 381 | newscan = scan.get_scan('323p459') |
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| 382 | # get all 'off' scans |
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| 383 | refscans = scan.get_scan('*_R') |
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| 384 | # get a susbset of scans by scanno (as listed in scan.summary()) |
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[1118] | 385 | newscan = scan.get_scan([0, 2, 7, 10]) |
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[1846] | 386 | |
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[102] | 387 | """ |
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| 388 | if scanid is None: |
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[1859] | 389 | raise RuntimeError( 'Please specify a scan no or name to ' |
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| 390 | 'retrieve from the scantable' ) |
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[102] | 391 | try: |
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[946] | 392 | bsel = self.get_selection() |
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| 393 | sel = selector() |
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[102] | 394 | if type(scanid) is str: |
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[946] | 395 | sel.set_name(scanid) |
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[1594] | 396 | return self._select_copy(sel) |
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[102] | 397 | elif type(scanid) is int: |
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[946] | 398 | sel.set_scans([scanid]) |
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[1594] | 399 | return self._select_copy(sel) |
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[381] | 400 | elif type(scanid) is list: |
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[946] | 401 | sel.set_scans(scanid) |
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[1594] | 402 | return self._select_copy(sel) |
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[381] | 403 | else: |
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[718] | 404 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
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[1859] | 405 | raise TypeError(msg) |
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[102] | 406 | except RuntimeError: |
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[1859] | 407 | raise |
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[102] | 408 | |
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| 409 | def __str__(self): |
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[2315] | 410 | tempFile = tempfile.NamedTemporaryFile() |
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| 411 | Scantable._summary(self, tempFile.name) |
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| 412 | tempFile.seek(0) |
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| 413 | asaplog.clear() |
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| 414 | return tempFile.file.read() |
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[102] | 415 | |
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[2315] | 416 | @asaplog_post_dec |
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[976] | 417 | def summary(self, filename=None): |
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[1846] | 418 | """\ |
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[102] | 419 | Print a summary of the contents of this scantable. |
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[1846] | 420 | |
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[102] | 421 | Parameters: |
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[1846] | 422 | |
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[1931] | 423 | filename: the name of a file to write the putput to |
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[102] | 424 | Default - no file output |
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[1846] | 425 | |
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[102] | 426 | """ |
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[2286] | 427 | # info = Scantable._summary(self) |
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[102] | 428 | if filename is not None: |
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[256] | 429 | if filename is "": |
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| 430 | filename = 'scantable_summary.txt' |
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[415] | 431 | from os.path import expandvars, isdir |
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[411] | 432 | filename = expandvars(filename) |
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[2286] | 433 | # if not isdir(filename): |
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| 434 | # data = open(filename, 'w') |
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| 435 | # data.write(info) |
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| 436 | # data.close() |
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| 437 | # else: |
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| 438 | if isdir(filename): |
---|
[718] | 439 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 440 | raise IOError(msg) |
---|
[2286] | 441 | else: |
---|
| 442 | filename = "" |
---|
| 443 | Scantable._summary(self, filename) |
---|
[2290] | 444 | # info = Scantable._summary(self, filename) |
---|
[2286] | 445 | # return page(info) |
---|
[710] | 446 | |
---|
[1512] | 447 | def get_spectrum(self, rowno): |
---|
[1471] | 448 | """Return the spectrum for the current row in the scantable as a list. |
---|
[1846] | 449 | |
---|
[1471] | 450 | Parameters: |
---|
[1846] | 451 | |
---|
[1573] | 452 | rowno: the row number to retrieve the spectrum from |
---|
[1846] | 453 | |
---|
[1471] | 454 | """ |
---|
| 455 | return self._getspectrum(rowno) |
---|
[946] | 456 | |
---|
[1471] | 457 | def get_mask(self, rowno): |
---|
| 458 | """Return the mask for the current row in the scantable as a list. |
---|
[1846] | 459 | |
---|
[1471] | 460 | Parameters: |
---|
[1846] | 461 | |
---|
[1573] | 462 | rowno: the row number to retrieve the mask from |
---|
[1846] | 463 | |
---|
[1471] | 464 | """ |
---|
| 465 | return self._getmask(rowno) |
---|
| 466 | |
---|
| 467 | def set_spectrum(self, spec, rowno): |
---|
[1938] | 468 | """Set the spectrum for the current row in the scantable. |
---|
[1846] | 469 | |
---|
[1471] | 470 | Parameters: |
---|
[1846] | 471 | |
---|
[1855] | 472 | spec: the new spectrum |
---|
[1846] | 473 | |
---|
[1855] | 474 | rowno: the row number to set the spectrum for |
---|
| 475 | |
---|
[1471] | 476 | """ |
---|
[2348] | 477 | assert(len(spec) == self.nchan(self.getif(rowno))) |
---|
[1471] | 478 | return self._setspectrum(spec, rowno) |
---|
| 479 | |
---|
[1600] | 480 | def get_coordinate(self, rowno): |
---|
| 481 | """Return the (spectral) coordinate for a a given 'rowno'. |
---|
[1846] | 482 | |
---|
| 483 | *Note*: |
---|
| 484 | |
---|
[1600] | 485 | * This coordinate is only valid until a scantable method modifies |
---|
| 486 | the frequency axis. |
---|
| 487 | * This coordinate does contain the original frequency set-up |
---|
| 488 | NOT the new frame. The conversions however are done using the user |
---|
| 489 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
---|
| 490 | use scantable.freq_align first. Without it there is no closure, |
---|
[1846] | 491 | i.e.:: |
---|
[1600] | 492 | |
---|
[1846] | 493 | c = myscan.get_coordinate(0) |
---|
| 494 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
---|
| 495 | |
---|
[1600] | 496 | Parameters: |
---|
[1846] | 497 | |
---|
[1600] | 498 | rowno: the row number for the spectral coordinate |
---|
| 499 | |
---|
| 500 | """ |
---|
| 501 | return coordinate(Scantable.get_coordinate(self, rowno)) |
---|
| 502 | |
---|
[946] | 503 | def get_selection(self): |
---|
[1846] | 504 | """\ |
---|
[1005] | 505 | Get the selection object currently set on this scantable. |
---|
[1846] | 506 | |
---|
| 507 | Example:: |
---|
| 508 | |
---|
[1005] | 509 | sel = scan.get_selection() |
---|
| 510 | sel.set_ifs(0) # select IF 0 |
---|
| 511 | scan.set_selection(sel) # apply modified selection |
---|
[1846] | 512 | |
---|
[946] | 513 | """ |
---|
| 514 | return selector(self._getselection()) |
---|
| 515 | |
---|
[1576] | 516 | def set_selection(self, selection=None, **kw): |
---|
[1846] | 517 | """\ |
---|
[1005] | 518 | Select a subset of the data. All following operations on this scantable |
---|
| 519 | are only applied to thi selection. |
---|
[1846] | 520 | |
---|
[1005] | 521 | Parameters: |
---|
[1697] | 522 | |
---|
[1846] | 523 | selection: a selector object (default unset the selection), or |
---|
| 524 | any combination of "pols", "ifs", "beams", "scans", |
---|
| 525 | "cycles", "name", "query" |
---|
[1697] | 526 | |
---|
[1846] | 527 | Examples:: |
---|
[1697] | 528 | |
---|
[1005] | 529 | sel = selector() # create a selection object |
---|
[1118] | 530 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
---|
[1005] | 531 | scan.set_selection(sel) # set the selection |
---|
| 532 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 533 | scan.set_selection() # unset the selection |
---|
[1697] | 534 | # or the equivalent |
---|
| 535 | scan.set_selection(scans=[0,3]) |
---|
| 536 | scan.summary() # will only print summary of scanno 0 an 3 |
---|
| 537 | scan.set_selection() # unset the selection |
---|
[1846] | 538 | |
---|
[946] | 539 | """ |
---|
[1576] | 540 | if selection is None: |
---|
| 541 | # reset |
---|
| 542 | if len(kw) == 0: |
---|
| 543 | selection = selector() |
---|
| 544 | else: |
---|
| 545 | # try keywords |
---|
| 546 | for k in kw: |
---|
| 547 | if k not in selector.fields: |
---|
[2320] | 548 | raise KeyError("Invalid selection key '%s', " |
---|
| 549 | "valid keys are %s" % (k, |
---|
| 550 | selector.fields)) |
---|
[1576] | 551 | selection = selector(**kw) |
---|
[946] | 552 | self._setselection(selection) |
---|
| 553 | |
---|
[1819] | 554 | def get_row(self, row=0, insitu=None): |
---|
[1846] | 555 | """\ |
---|
[1819] | 556 | Select a row in the scantable. |
---|
| 557 | Return a scantable with single row. |
---|
[1846] | 558 | |
---|
[1819] | 559 | Parameters: |
---|
[1846] | 560 | |
---|
| 561 | row: row no of integration, default is 0. |
---|
| 562 | insitu: if False a new scantable is returned. Otherwise, the |
---|
| 563 | scaling is done in-situ. The default is taken from .asaprc |
---|
| 564 | (False) |
---|
| 565 | |
---|
[1819] | 566 | """ |
---|
[2349] | 567 | if insitu is None: |
---|
| 568 | insitu = rcParams['insitu'] |
---|
[1819] | 569 | if not insitu: |
---|
| 570 | workscan = self.copy() |
---|
| 571 | else: |
---|
| 572 | workscan = self |
---|
| 573 | # Select a row |
---|
[2349] | 574 | sel = selector() |
---|
[1992] | 575 | sel.set_rows([row]) |
---|
[1819] | 576 | workscan.set_selection(sel) |
---|
| 577 | if not workscan.nrow() == 1: |
---|
[2349] | 578 | msg = "Could not identify single row. %d rows selected." \ |
---|
| 579 | % (workscan.nrow()) |
---|
[1819] | 580 | raise RuntimeError(msg) |
---|
| 581 | if insitu: |
---|
| 582 | self._assign(workscan) |
---|
| 583 | else: |
---|
| 584 | return workscan |
---|
| 585 | |
---|
[1862] | 586 | @asaplog_post_dec |
---|
[1907] | 587 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
---|
[1846] | 588 | """\ |
---|
[135] | 589 | Determine the specified statistic of the current beam/if/pol |
---|
[102] | 590 | Takes a 'mask' as an optional parameter to specify which |
---|
| 591 | channels should be excluded. |
---|
[1846] | 592 | |
---|
[102] | 593 | Parameters: |
---|
[1846] | 594 | |
---|
[1819] | 595 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
---|
| 596 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
---|
[1855] | 597 | |
---|
[135] | 598 | mask: an optional mask specifying where the statistic |
---|
[102] | 599 | should be determined. |
---|
[1855] | 600 | |
---|
[1819] | 601 | form: format string to print statistic values |
---|
[1846] | 602 | |
---|
[1907] | 603 | row: row number of spectrum to process. |
---|
| 604 | (default is None: for all rows) |
---|
[1846] | 605 | |
---|
[1907] | 606 | Example: |
---|
[113] | 607 | scan.set_unit('channel') |
---|
[1118] | 608 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 609 | scan.stats(stat='mean', mask=m) |
---|
[1846] | 610 | |
---|
[102] | 611 | """ |
---|
[1593] | 612 | mask = mask or [] |
---|
[876] | 613 | if not self._check_ifs(): |
---|
[1118] | 614 | raise ValueError("Cannot apply mask as the IFs have different " |
---|
| 615 | "number of channels. Please use setselection() " |
---|
| 616 | "to select individual IFs") |
---|
[1819] | 617 | rtnabc = False |
---|
| 618 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
| 619 | getchan = False |
---|
| 620 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
| 621 | chan = self._math._minmaxchan(self, mask, stat) |
---|
| 622 | getchan = True |
---|
| 623 | statvals = [] |
---|
[1907] | 624 | if not rtnabc: |
---|
| 625 | if row == None: |
---|
| 626 | statvals = self._math._stats(self, mask, stat) |
---|
| 627 | else: |
---|
| 628 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
[256] | 629 | |
---|
[1819] | 630 | #def cb(i): |
---|
| 631 | # return statvals[i] |
---|
[256] | 632 | |
---|
[1819] | 633 | #return self._row_callback(cb, stat) |
---|
[102] | 634 | |
---|
[1819] | 635 | label=stat |
---|
| 636 | #callback=cb |
---|
| 637 | out = "" |
---|
| 638 | #outvec = [] |
---|
| 639 | sep = '-'*50 |
---|
[1907] | 640 | |
---|
| 641 | if row == None: |
---|
| 642 | rows = xrange(self.nrow()) |
---|
| 643 | elif isinstance(row, int): |
---|
| 644 | rows = [ row ] |
---|
| 645 | |
---|
| 646 | for i in rows: |
---|
[1819] | 647 | refstr = '' |
---|
| 648 | statunit= '' |
---|
| 649 | if getchan: |
---|
| 650 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
| 651 | if rtnabc: |
---|
| 652 | statvals.append(qx['value']) |
---|
| 653 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
| 654 | statunit= '['+qx['unit']+']' |
---|
| 655 | else: |
---|
| 656 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
| 657 | |
---|
| 658 | tm = self._gettime(i) |
---|
| 659 | src = self._getsourcename(i) |
---|
| 660 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
| 661 | out += 'Time[%s]:\n' % (tm) |
---|
[1907] | 662 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 663 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 664 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[1819] | 665 | #outvec.append(callback(i)) |
---|
[1907] | 666 | if len(rows) > 1: |
---|
| 667 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
| 668 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
| 669 | else: |
---|
| 670 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
| 671 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
[1819] | 672 | out += sep+"\n" |
---|
| 673 | |
---|
[1859] | 674 | import os |
---|
| 675 | if os.environ.has_key( 'USER' ): |
---|
| 676 | usr = os.environ['USER'] |
---|
| 677 | else: |
---|
| 678 | import commands |
---|
| 679 | usr = commands.getoutput( 'whoami' ) |
---|
| 680 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
| 681 | f = open(tmpfile,'w') |
---|
| 682 | print >> f, sep |
---|
| 683 | print >> f, ' %s %s' % (label, statunit) |
---|
| 684 | print >> f, sep |
---|
| 685 | print >> f, out |
---|
| 686 | f.close() |
---|
| 687 | f = open(tmpfile,'r') |
---|
| 688 | x = f.readlines() |
---|
| 689 | f.close() |
---|
| 690 | asaplog.push(''.join(x), False) |
---|
| 691 | |
---|
[1819] | 692 | return statvals |
---|
| 693 | |
---|
| 694 | def chan2data(self, rowno=0, chan=0): |
---|
[1846] | 695 | """\ |
---|
[1819] | 696 | Returns channel/frequency/velocity and spectral value |
---|
| 697 | at an arbitrary row and channel in the scantable. |
---|
[1846] | 698 | |
---|
[1819] | 699 | Parameters: |
---|
[1846] | 700 | |
---|
[1819] | 701 | rowno: a row number in the scantable. Default is the |
---|
| 702 | first row, i.e. rowno=0 |
---|
[1855] | 703 | |
---|
[1819] | 704 | chan: a channel in the scantable. Default is the first |
---|
| 705 | channel, i.e. pos=0 |
---|
[1846] | 706 | |
---|
[1819] | 707 | """ |
---|
| 708 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
| 709 | qx = {'unit': self.get_unit(), |
---|
| 710 | 'value': self._getabcissa(rowno)[chan]} |
---|
| 711 | qy = {'unit': self.get_fluxunit(), |
---|
| 712 | 'value': self._getspectrum(rowno)[chan]} |
---|
| 713 | return qx, qy |
---|
| 714 | |
---|
[1118] | 715 | def stddev(self, mask=None): |
---|
[1846] | 716 | """\ |
---|
[135] | 717 | Determine the standard deviation of the current beam/if/pol |
---|
| 718 | Takes a 'mask' as an optional parameter to specify which |
---|
| 719 | channels should be excluded. |
---|
[1846] | 720 | |
---|
[135] | 721 | Parameters: |
---|
[1846] | 722 | |
---|
[135] | 723 | mask: an optional mask specifying where the standard |
---|
| 724 | deviation should be determined. |
---|
| 725 | |
---|
[1846] | 726 | Example:: |
---|
| 727 | |
---|
[135] | 728 | scan.set_unit('channel') |
---|
[1118] | 729 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
[135] | 730 | scan.stddev(mask=m) |
---|
[1846] | 731 | |
---|
[135] | 732 | """ |
---|
[1118] | 733 | return self.stats(stat='stddev', mask=mask); |
---|
[135] | 734 | |
---|
[1003] | 735 | |
---|
[1259] | 736 | def get_column_names(self): |
---|
[1846] | 737 | """\ |
---|
[1003] | 738 | Return a list of column names, which can be used for selection. |
---|
| 739 | """ |
---|
[1259] | 740 | return list(Scantable.get_column_names(self)) |
---|
[1003] | 741 | |
---|
[1730] | 742 | def get_tsys(self, row=-1): |
---|
[1846] | 743 | """\ |
---|
[113] | 744 | Return the System temperatures. |
---|
[1846] | 745 | |
---|
| 746 | Parameters: |
---|
| 747 | |
---|
| 748 | row: the rowno to get the information for. (default all rows) |
---|
| 749 | |
---|
[113] | 750 | Returns: |
---|
[1846] | 751 | |
---|
[876] | 752 | a list of Tsys values for the current selection |
---|
[1846] | 753 | |
---|
[113] | 754 | """ |
---|
[1730] | 755 | if row > -1: |
---|
| 756 | return self._get_column(self._gettsys, row) |
---|
[876] | 757 | return self._row_callback(self._gettsys, "Tsys") |
---|
[256] | 758 | |
---|
[1730] | 759 | |
---|
| 760 | def get_weather(self, row=-1): |
---|
[1846] | 761 | """\ |
---|
| 762 | Return the weather informations. |
---|
| 763 | |
---|
| 764 | Parameters: |
---|
| 765 | |
---|
| 766 | row: the rowno to get the information for. (default all rows) |
---|
| 767 | |
---|
| 768 | Returns: |
---|
| 769 | |
---|
| 770 | a dict or list of of dicts of values for the current selection |
---|
| 771 | |
---|
| 772 | """ |
---|
| 773 | |
---|
[1730] | 774 | values = self._get_column(self._get_weather, row) |
---|
| 775 | if row > -1: |
---|
| 776 | return {'temperature': values[0], |
---|
| 777 | 'pressure': values[1], 'humidity' : values[2], |
---|
| 778 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
| 779 | } |
---|
| 780 | else: |
---|
| 781 | out = [] |
---|
| 782 | for r in values: |
---|
| 783 | |
---|
| 784 | out.append({'temperature': r[0], |
---|
| 785 | 'pressure': r[1], 'humidity' : r[2], |
---|
| 786 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
| 787 | }) |
---|
| 788 | return out |
---|
| 789 | |
---|
[876] | 790 | def _row_callback(self, callback, label): |
---|
| 791 | out = "" |
---|
[1118] | 792 | outvec = [] |
---|
[1590] | 793 | sep = '-'*50 |
---|
[876] | 794 | for i in range(self.nrow()): |
---|
| 795 | tm = self._gettime(i) |
---|
| 796 | src = self._getsourcename(i) |
---|
[1590] | 797 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
[876] | 798 | out += 'Time[%s]:\n' % (tm) |
---|
[1590] | 799 | if self.nbeam(-1) > 1: |
---|
| 800 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
| 801 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
| 802 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
[876] | 803 | outvec.append(callback(i)) |
---|
| 804 | out += '= %3.3f\n' % (outvec[i]) |
---|
[1590] | 805 | out += sep+'\n' |
---|
[1859] | 806 | |
---|
| 807 | asaplog.push(sep) |
---|
| 808 | asaplog.push(" %s" % (label)) |
---|
| 809 | asaplog.push(sep) |
---|
| 810 | asaplog.push(out) |
---|
[1861] | 811 | asaplog.post() |
---|
[1175] | 812 | return outvec |
---|
[256] | 813 | |
---|
[1947] | 814 | def _get_column(self, callback, row=-1, *args): |
---|
[1070] | 815 | """ |
---|
| 816 | """ |
---|
| 817 | if row == -1: |
---|
[1947] | 818 | return [callback(i, *args) for i in range(self.nrow())] |
---|
[1070] | 819 | else: |
---|
[1819] | 820 | if 0 <= row < self.nrow(): |
---|
[1947] | 821 | return callback(row, *args) |
---|
[256] | 822 | |
---|
[1070] | 823 | |
---|
[1948] | 824 | def get_time(self, row=-1, asdatetime=False, prec=-1): |
---|
[1846] | 825 | """\ |
---|
[113] | 826 | Get a list of time stamps for the observations. |
---|
[1938] | 827 | Return a datetime object or a string (default) for each |
---|
| 828 | integration time stamp in the scantable. |
---|
[1846] | 829 | |
---|
[113] | 830 | Parameters: |
---|
[1846] | 831 | |
---|
[1348] | 832 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 833 | |
---|
[1348] | 834 | asdatetime: return values as datetime objects rather than strings |
---|
[1846] | 835 | |
---|
[2349] | 836 | prec: number of digits shown. Default -1 to automatic |
---|
| 837 | calculation. |
---|
[1948] | 838 | Note this number is equals to the digits of MVTime, |
---|
| 839 | i.e., 0<prec<3: dates with hh:: only, |
---|
| 840 | <5: with hh:mm:, <7 or 0: with hh:mm:ss, |
---|
[1947] | 841 | and 6> : with hh:mm:ss.tt... (prec-6 t's added) |
---|
| 842 | |
---|
[113] | 843 | """ |
---|
[1175] | 844 | from datetime import datetime |
---|
[1948] | 845 | if prec < 0: |
---|
| 846 | # automagically set necessary precision +1 |
---|
[2349] | 847 | prec = 7 - \ |
---|
| 848 | numpy.floor(numpy.log10(numpy.min(self.get_inttime(row)))) |
---|
[1948] | 849 | prec = max(6, int(prec)) |
---|
| 850 | else: |
---|
| 851 | prec = max(0, prec) |
---|
| 852 | if asdatetime: |
---|
| 853 | #precision can be 1 millisecond at max |
---|
| 854 | prec = min(12, prec) |
---|
| 855 | |
---|
[1947] | 856 | times = self._get_column(self._gettime, row, prec) |
---|
[1348] | 857 | if not asdatetime: |
---|
[1392] | 858 | return times |
---|
[1947] | 859 | format = "%Y/%m/%d/%H:%M:%S.%f" |
---|
| 860 | if prec < 7: |
---|
| 861 | nsub = 1 + (((6-prec)/2) % 3) |
---|
| 862 | substr = [".%f","%S","%M"] |
---|
| 863 | for i in range(nsub): |
---|
| 864 | format = format.replace(substr[i],"") |
---|
[1175] | 865 | if isinstance(times, list): |
---|
[1947] | 866 | return [datetime.strptime(i, format) for i in times] |
---|
[1175] | 867 | else: |
---|
[1947] | 868 | return datetime.strptime(times, format) |
---|
[102] | 869 | |
---|
[1348] | 870 | |
---|
| 871 | def get_inttime(self, row=-1): |
---|
[1846] | 872 | """\ |
---|
[1348] | 873 | Get a list of integration times for the observations. |
---|
| 874 | Return a time in seconds for each integration in the scantable. |
---|
[1846] | 875 | |
---|
[1348] | 876 | Parameters: |
---|
[1846] | 877 | |
---|
[1348] | 878 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 879 | |
---|
[1348] | 880 | """ |
---|
[1573] | 881 | return self._get_column(self._getinttime, row) |
---|
[1348] | 882 | |
---|
[1573] | 883 | |
---|
[714] | 884 | def get_sourcename(self, row=-1): |
---|
[1846] | 885 | """\ |
---|
[794] | 886 | Get a list source names for the observations. |
---|
[714] | 887 | Return a string for each integration in the scantable. |
---|
| 888 | Parameters: |
---|
[1846] | 889 | |
---|
[1348] | 890 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 891 | |
---|
[714] | 892 | """ |
---|
[1070] | 893 | return self._get_column(self._getsourcename, row) |
---|
[714] | 894 | |
---|
[794] | 895 | def get_elevation(self, row=-1): |
---|
[1846] | 896 | """\ |
---|
[794] | 897 | Get a list of elevations for the observations. |
---|
| 898 | Return a float for each integration in the scantable. |
---|
[1846] | 899 | |
---|
[794] | 900 | Parameters: |
---|
[1846] | 901 | |
---|
[1348] | 902 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 903 | |
---|
[794] | 904 | """ |
---|
[1070] | 905 | return self._get_column(self._getelevation, row) |
---|
[794] | 906 | |
---|
| 907 | def get_azimuth(self, row=-1): |
---|
[1846] | 908 | """\ |
---|
[794] | 909 | Get a list of azimuths for the observations. |
---|
| 910 | Return a float for each integration in the scantable. |
---|
[1846] | 911 | |
---|
[794] | 912 | Parameters: |
---|
[1348] | 913 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 914 | |
---|
[794] | 915 | """ |
---|
[1070] | 916 | return self._get_column(self._getazimuth, row) |
---|
[794] | 917 | |
---|
| 918 | def get_parangle(self, row=-1): |
---|
[1846] | 919 | """\ |
---|
[794] | 920 | Get a list of parallactic angles for the observations. |
---|
| 921 | Return a float for each integration in the scantable. |
---|
[1846] | 922 | |
---|
[794] | 923 | Parameters: |
---|
[1846] | 924 | |
---|
[1348] | 925 | row: row no of integration. Default -1 return all rows. |
---|
[1846] | 926 | |
---|
[794] | 927 | """ |
---|
[1070] | 928 | return self._get_column(self._getparangle, row) |
---|
[794] | 929 | |
---|
[1070] | 930 | def get_direction(self, row=-1): |
---|
| 931 | """ |
---|
| 932 | Get a list of Positions on the sky (direction) for the observations. |
---|
[1594] | 933 | Return a string for each integration in the scantable. |
---|
[1855] | 934 | |
---|
[1070] | 935 | Parameters: |
---|
[1855] | 936 | |
---|
[1070] | 937 | row: row no of integration. Default -1 return all rows |
---|
[1855] | 938 | |
---|
[1070] | 939 | """ |
---|
| 940 | return self._get_column(self._getdirection, row) |
---|
| 941 | |
---|
[1391] | 942 | def get_directionval(self, row=-1): |
---|
[1846] | 943 | """\ |
---|
[1391] | 944 | Get a list of Positions on the sky (direction) for the observations. |
---|
| 945 | Return a float for each integration in the scantable. |
---|
[1846] | 946 | |
---|
[1391] | 947 | Parameters: |
---|
[1846] | 948 | |
---|
[1391] | 949 | row: row no of integration. Default -1 return all rows |
---|
[1846] | 950 | |
---|
[1391] | 951 | """ |
---|
| 952 | return self._get_column(self._getdirectionvec, row) |
---|
| 953 | |
---|
[1862] | 954 | @asaplog_post_dec |
---|
[102] | 955 | def set_unit(self, unit='channel'): |
---|
[1846] | 956 | """\ |
---|
[102] | 957 | Set the unit for all following operations on this scantable |
---|
[1846] | 958 | |
---|
[102] | 959 | Parameters: |
---|
[1846] | 960 | |
---|
| 961 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
| 962 | 'km/s', 'channel' or equivalent '' |
---|
| 963 | |
---|
[102] | 964 | """ |
---|
[484] | 965 | varlist = vars() |
---|
[1118] | 966 | if unit in ['', 'pixel', 'channel']: |
---|
[113] | 967 | unit = '' |
---|
| 968 | inf = list(self._getcoordinfo()) |
---|
| 969 | inf[0] = unit |
---|
| 970 | self._setcoordinfo(inf) |
---|
[1118] | 971 | self._add_history("set_unit", varlist) |
---|
[113] | 972 | |
---|
[1862] | 973 | @asaplog_post_dec |
---|
[484] | 974 | def set_instrument(self, instr): |
---|
[1846] | 975 | """\ |
---|
[1348] | 976 | Set the instrument for subsequent processing. |
---|
[1846] | 977 | |
---|
[358] | 978 | Parameters: |
---|
[1846] | 979 | |
---|
[710] | 980 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
[407] | 981 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
[1846] | 982 | |
---|
[358] | 983 | """ |
---|
| 984 | self._setInstrument(instr) |
---|
[1118] | 985 | self._add_history("set_instument", vars()) |
---|
[358] | 986 | |
---|
[1862] | 987 | @asaplog_post_dec |
---|
[1190] | 988 | def set_feedtype(self, feedtype): |
---|
[1846] | 989 | """\ |
---|
[1190] | 990 | Overwrite the feed type, which might not be set correctly. |
---|
[1846] | 991 | |
---|
[1190] | 992 | Parameters: |
---|
[1846] | 993 | |
---|
[1190] | 994 | feedtype: 'linear' or 'circular' |
---|
[1846] | 995 | |
---|
[1190] | 996 | """ |
---|
| 997 | self._setfeedtype(feedtype) |
---|
| 998 | self._add_history("set_feedtype", vars()) |
---|
| 999 | |
---|
[1862] | 1000 | @asaplog_post_dec |
---|
[276] | 1001 | def set_doppler(self, doppler='RADIO'): |
---|
[1846] | 1002 | """\ |
---|
[276] | 1003 | Set the doppler for all following operations on this scantable. |
---|
[1846] | 1004 | |
---|
[276] | 1005 | Parameters: |
---|
[1846] | 1006 | |
---|
[276] | 1007 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
[1846] | 1008 | |
---|
[276] | 1009 | """ |
---|
[484] | 1010 | varlist = vars() |
---|
[276] | 1011 | inf = list(self._getcoordinfo()) |
---|
| 1012 | inf[2] = doppler |
---|
| 1013 | self._setcoordinfo(inf) |
---|
[1118] | 1014 | self._add_history("set_doppler", vars()) |
---|
[710] | 1015 | |
---|
[1862] | 1016 | @asaplog_post_dec |
---|
[226] | 1017 | def set_freqframe(self, frame=None): |
---|
[1846] | 1018 | """\ |
---|
[113] | 1019 | Set the frame type of the Spectral Axis. |
---|
[1846] | 1020 | |
---|
[113] | 1021 | Parameters: |
---|
[1846] | 1022 | |
---|
[591] | 1023 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
[1819] | 1024 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
[1118] | 1025 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
[1846] | 1026 | |
---|
| 1027 | Example:: |
---|
| 1028 | |
---|
[113] | 1029 | scan.set_freqframe('BARY') |
---|
[1846] | 1030 | |
---|
[113] | 1031 | """ |
---|
[1593] | 1032 | frame = frame or rcParams['scantable.freqframe'] |
---|
[484] | 1033 | varlist = vars() |
---|
[1819] | 1034 | # "REST" is not implemented in casacore |
---|
| 1035 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
| 1036 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
| 1037 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
[1118] | 1038 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
[591] | 1039 | |
---|
[989] | 1040 | if frame in valid: |
---|
[113] | 1041 | inf = list(self._getcoordinfo()) |
---|
| 1042 | inf[1] = frame |
---|
| 1043 | self._setcoordinfo(inf) |
---|
[1118] | 1044 | self._add_history("set_freqframe", varlist) |
---|
[102] | 1045 | else: |
---|
[1118] | 1046 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
[1859] | 1047 | raise TypeError(msg) |
---|
[710] | 1048 | |
---|
[1862] | 1049 | @asaplog_post_dec |
---|
[989] | 1050 | def set_dirframe(self, frame=""): |
---|
[1846] | 1051 | """\ |
---|
[989] | 1052 | Set the frame type of the Direction on the sky. |
---|
[1846] | 1053 | |
---|
[989] | 1054 | Parameters: |
---|
[1846] | 1055 | |
---|
[989] | 1056 | frame: an optional frame type, default ''. Valid frames are: |
---|
| 1057 | 'J2000', 'B1950', 'GALACTIC' |
---|
[1846] | 1058 | |
---|
| 1059 | Example: |
---|
| 1060 | |
---|
[989] | 1061 | scan.set_dirframe('GALACTIC') |
---|
[1846] | 1062 | |
---|
[989] | 1063 | """ |
---|
| 1064 | varlist = vars() |
---|
[1859] | 1065 | Scantable.set_dirframe(self, frame) |
---|
[1118] | 1066 | self._add_history("set_dirframe", varlist) |
---|
[989] | 1067 | |
---|
[113] | 1068 | def get_unit(self): |
---|
[1846] | 1069 | """\ |
---|
[113] | 1070 | Get the default unit set in this scantable |
---|
[1846] | 1071 | |
---|
[113] | 1072 | Returns: |
---|
[1846] | 1073 | |
---|
[113] | 1074 | A unit string |
---|
[1846] | 1075 | |
---|
[113] | 1076 | """ |
---|
| 1077 | inf = self._getcoordinfo() |
---|
| 1078 | unit = inf[0] |
---|
| 1079 | if unit == '': unit = 'channel' |
---|
| 1080 | return unit |
---|
[102] | 1081 | |
---|
[1862] | 1082 | @asaplog_post_dec |
---|
[158] | 1083 | def get_abcissa(self, rowno=0): |
---|
[1846] | 1084 | """\ |
---|
[158] | 1085 | Get the abcissa in the current coordinate setup for the currently |
---|
[113] | 1086 | selected Beam/IF/Pol |
---|
[1846] | 1087 | |
---|
[113] | 1088 | Parameters: |
---|
[1846] | 1089 | |
---|
[226] | 1090 | rowno: an optional row number in the scantable. Default is the |
---|
| 1091 | first row, i.e. rowno=0 |
---|
[1846] | 1092 | |
---|
[113] | 1093 | Returns: |
---|
[1846] | 1094 | |
---|
[1348] | 1095 | The abcissa values and the format string (as a dictionary) |
---|
[1846] | 1096 | |
---|
[113] | 1097 | """ |
---|
[256] | 1098 | abc = self._getabcissa(rowno) |
---|
[710] | 1099 | lbl = self._getabcissalabel(rowno) |
---|
[158] | 1100 | return abc, lbl |
---|
[113] | 1101 | |
---|
[1862] | 1102 | @asaplog_post_dec |
---|
[2322] | 1103 | def flag(self, mask=None, unflag=False, row=-1): |
---|
[1846] | 1104 | """\ |
---|
[1001] | 1105 | Flag the selected data using an optional channel mask. |
---|
[1846] | 1106 | |
---|
[1001] | 1107 | Parameters: |
---|
[1846] | 1108 | |
---|
[1001] | 1109 | mask: an optional channel mask, created with create_mask. Default |
---|
| 1110 | (no mask) is all channels. |
---|
[1855] | 1111 | |
---|
[1819] | 1112 | unflag: if True, unflag the data |
---|
[1846] | 1113 | |
---|
[2322] | 1114 | row: an optional row number in the scantable. |
---|
| 1115 | Default -1 flags all rows |
---|
| 1116 | |
---|
[1001] | 1117 | """ |
---|
| 1118 | varlist = vars() |
---|
[1593] | 1119 | mask = mask or [] |
---|
[1994] | 1120 | self._flag(row, mask, unflag) |
---|
[1001] | 1121 | self._add_history("flag", varlist) |
---|
| 1122 | |
---|
[1862] | 1123 | @asaplog_post_dec |
---|
[2322] | 1124 | def flag_row(self, rows=None, unflag=False): |
---|
[1846] | 1125 | """\ |
---|
[1819] | 1126 | Flag the selected data in row-based manner. |
---|
[1846] | 1127 | |
---|
[1819] | 1128 | Parameters: |
---|
[1846] | 1129 | |
---|
[1843] | 1130 | rows: list of row numbers to be flagged. Default is no row |
---|
[2322] | 1131 | (must be explicitly specified to execute row-based |
---|
| 1132 | flagging). |
---|
[1855] | 1133 | |
---|
[1819] | 1134 | unflag: if True, unflag the data. |
---|
[1846] | 1135 | |
---|
[1819] | 1136 | """ |
---|
| 1137 | varlist = vars() |
---|
[2322] | 1138 | if rows is None: |
---|
| 1139 | rows = [] |
---|
[1859] | 1140 | self._flag_row(rows, unflag) |
---|
[1819] | 1141 | self._add_history("flag_row", varlist) |
---|
| 1142 | |
---|
[1862] | 1143 | @asaplog_post_dec |
---|
[1819] | 1144 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
[1846] | 1145 | """\ |
---|
[1819] | 1146 | Flag the selected data outside a specified range (in channel-base) |
---|
[1846] | 1147 | |
---|
[1819] | 1148 | Parameters: |
---|
[1846] | 1149 | |
---|
[1819] | 1150 | uthres: upper threshold. |
---|
[1855] | 1151 | |
---|
[1819] | 1152 | dthres: lower threshold |
---|
[1846] | 1153 | |
---|
[2322] | 1154 | clipoutside: True for flagging data outside the range |
---|
| 1155 | [dthres:uthres]. |
---|
[1928] | 1156 | False for flagging data inside the range. |
---|
[1855] | 1157 | |
---|
[1846] | 1158 | unflag: if True, unflag the data. |
---|
| 1159 | |
---|
[1819] | 1160 | """ |
---|
| 1161 | varlist = vars() |
---|
[1859] | 1162 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
[1819] | 1163 | self._add_history("clip", varlist) |
---|
| 1164 | |
---|
[1862] | 1165 | @asaplog_post_dec |
---|
[1584] | 1166 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
[1846] | 1167 | """\ |
---|
[1192] | 1168 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
[2177] | 1169 | Flagged data in the scantable get interpolated over the region. |
---|
[1192] | 1170 | No taper is applied. |
---|
[1846] | 1171 | |
---|
[1192] | 1172 | Parameters: |
---|
[1846] | 1173 | |
---|
[1579] | 1174 | start: the start frequency (really a period within the |
---|
| 1175 | bandwidth) or period to remove |
---|
[1855] | 1176 | |
---|
[1579] | 1177 | end: the end frequency or period to remove |
---|
[1855] | 1178 | |
---|
[1584] | 1179 | unit: the frequency unit (default "MHz") or "" for |
---|
[1579] | 1180 | explicit lag channels |
---|
[1846] | 1181 | |
---|
| 1182 | *Notes*: |
---|
| 1183 | |
---|
[1579] | 1184 | It is recommended to flag edges of the band or strong |
---|
[1348] | 1185 | signals beforehand. |
---|
[1846] | 1186 | |
---|
[1192] | 1187 | """ |
---|
| 1188 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 1189 | self._math._setinsitu(insitu) |
---|
| 1190 | varlist = vars() |
---|
[1579] | 1191 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
| 1192 | if not (unit == "" or base.has_key(unit)): |
---|
[1192] | 1193 | raise ValueError("%s is not a valid unit." % unit) |
---|
[1859] | 1194 | if unit == "": |
---|
| 1195 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
| 1196 | else: |
---|
| 1197 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
| 1198 | end*base[unit], "frequency")) |
---|
[1192] | 1199 | s._add_history("lag_flag", varlist) |
---|
| 1200 | if insitu: |
---|
| 1201 | self._assign(s) |
---|
| 1202 | else: |
---|
| 1203 | return s |
---|
[1001] | 1204 | |
---|
[1862] | 1205 | @asaplog_post_dec |
---|
[2349] | 1206 | def fft(self, rowno=None, mask=None, getrealimag=False): |
---|
[2177] | 1207 | """\ |
---|
| 1208 | Apply FFT to the spectra. |
---|
| 1209 | Flagged data in the scantable get interpolated over the region. |
---|
| 1210 | |
---|
| 1211 | Parameters: |
---|
[2186] | 1212 | |
---|
| 1213 | rowno: The row number(s) to be processed. int, list |
---|
[2349] | 1214 | and tuple are accepted. By default (None), FFT |
---|
[2186] | 1215 | is applied to the whole data. |
---|
| 1216 | |
---|
| 1217 | mask: Auxiliary channel mask(s). Given as a boolean |
---|
| 1218 | list, it is applied to all specified rows. |
---|
| 1219 | A list of boolean lists can also be used to |
---|
| 1220 | apply different masks. In the latter case, the |
---|
| 1221 | length of 'mask' must be the same as that of |
---|
[2349] | 1222 | 'rowno'. The default is None. |
---|
[2177] | 1223 | |
---|
| 1224 | getrealimag: If True, returns the real and imaginary part |
---|
| 1225 | values of the complex results. |
---|
| 1226 | If False (the default), returns the amplitude |
---|
| 1227 | (absolute value) normalised with Ndata/2 and |
---|
| 1228 | phase (argument, in unit of radian). |
---|
| 1229 | |
---|
| 1230 | Returns: |
---|
| 1231 | |
---|
[2186] | 1232 | A list of dictionaries containing the results for each spectrum. |
---|
| 1233 | Each dictionary contains two values, the real and the imaginary |
---|
| 1234 | parts when getrealimag = True, or the amplitude(absolute value) |
---|
| 1235 | and the phase(argument) when getrealimag = False. The key for |
---|
| 1236 | these values are 'real' and 'imag', or 'ampl' and 'phase', |
---|
[2177] | 1237 | respectively. |
---|
| 1238 | """ |
---|
[2349] | 1239 | if rowno is None: |
---|
| 1240 | rowno = [] |
---|
| 1241 | if mask is None: |
---|
| 1242 | mask = [] |
---|
[2177] | 1243 | if isinstance(rowno, int): |
---|
| 1244 | rowno = [rowno] |
---|
| 1245 | elif not (isinstance(rowno, list) or isinstance(rowno, tuple)): |
---|
[2186] | 1246 | raise TypeError("The row number(s) must be int, list or tuple.") |
---|
| 1247 | |
---|
| 1248 | if len(rowno) == 0: rowno = [i for i in xrange(self.nrow())] |
---|
| 1249 | |
---|
| 1250 | if not (isinstance(mask, list) or isinstance(mask, tuple)): |
---|
[2349] | 1251 | raise TypeError("The mask must be a boolean list or a list of " |
---|
| 1252 | "boolean list.") |
---|
[2186] | 1253 | if len(mask) == 0: mask = [True for i in xrange(self.nchan())] |
---|
| 1254 | if isinstance(mask[0], bool): mask = [mask] |
---|
| 1255 | elif not (isinstance(mask[0], list) or isinstance(mask[0], tuple)): |
---|
[2349] | 1256 | raise TypeError("The mask must be a boolean list or a list of " |
---|
| 1257 | "boolean list.") |
---|
[2186] | 1258 | |
---|
| 1259 | usecommonmask = (len(mask) == 1) |
---|
| 1260 | if not usecommonmask: |
---|
| 1261 | if len(mask) != len(rowno): |
---|
[2349] | 1262 | raise ValueError("When specifying masks for each spectrum, " |
---|
| 1263 | "the numbers of them must be identical.") |
---|
[2186] | 1264 | for amask in mask: |
---|
| 1265 | if len(amask) != self.nchan(): |
---|
[2349] | 1266 | raise ValueError("The spectra and the mask have different " |
---|
| 1267 | "length.") |
---|
[2177] | 1268 | |
---|
[2186] | 1269 | res = [] |
---|
| 1270 | |
---|
| 1271 | imask = 0 |
---|
| 1272 | for whichrow in rowno: |
---|
| 1273 | fspec = self._fft(whichrow, mask[imask], getrealimag) |
---|
| 1274 | nspec = len(fspec) |
---|
[2177] | 1275 | |
---|
[2349] | 1276 | i = 0 |
---|
| 1277 | v1 = [] |
---|
| 1278 | v2 = [] |
---|
| 1279 | reselem = {"real":[],"imag":[]} if getrealimag \ |
---|
| 1280 | else {"ampl":[],"phase":[]} |
---|
[2177] | 1281 | |
---|
[2186] | 1282 | while (i < nspec): |
---|
| 1283 | v1.append(fspec[i]) |
---|
| 1284 | v2.append(fspec[i+1]) |
---|
[2349] | 1285 | i += 2 |
---|
[2186] | 1286 | |
---|
[2177] | 1287 | if getrealimag: |
---|
[2186] | 1288 | reselem["real"] += v1 |
---|
| 1289 | reselem["imag"] += v2 |
---|
[2177] | 1290 | else: |
---|
[2186] | 1291 | reselem["ampl"] += v1 |
---|
| 1292 | reselem["phase"] += v2 |
---|
[2177] | 1293 | |
---|
[2186] | 1294 | res.append(reselem) |
---|
| 1295 | |
---|
[2349] | 1296 | if not usecommonmask: |
---|
| 1297 | imask += 1 |
---|
[2186] | 1298 | |
---|
[2177] | 1299 | return res |
---|
| 1300 | |
---|
| 1301 | @asaplog_post_dec |
---|
[113] | 1302 | def create_mask(self, *args, **kwargs): |
---|
[1846] | 1303 | """\ |
---|
[1118] | 1304 | Compute and return a mask based on [min, max] windows. |
---|
[189] | 1305 | The specified windows are to be INCLUDED, when the mask is |
---|
[113] | 1306 | applied. |
---|
[1846] | 1307 | |
---|
[102] | 1308 | Parameters: |
---|
[1846] | 1309 | |
---|
[1118] | 1310 | [min, max], [min2, max2], ... |
---|
[1024] | 1311 | Pairs of start/end points (inclusive)specifying the regions |
---|
[102] | 1312 | to be masked |
---|
[1855] | 1313 | |
---|
[189] | 1314 | invert: optional argument. If specified as True, |
---|
| 1315 | return an inverted mask, i.e. the regions |
---|
| 1316 | specified are EXCLUDED |
---|
[1855] | 1317 | |
---|
[513] | 1318 | row: create the mask using the specified row for |
---|
| 1319 | unit conversions, default is row=0 |
---|
| 1320 | only necessary if frequency varies over rows. |
---|
[1846] | 1321 | |
---|
| 1322 | Examples:: |
---|
| 1323 | |
---|
[113] | 1324 | scan.set_unit('channel') |
---|
[1846] | 1325 | # a) |
---|
[1118] | 1326 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
[189] | 1327 | # masks everything outside 400 and 500 |
---|
[113] | 1328 | # and 800 and 900 in the unit 'channel' |
---|
| 1329 | |
---|
[1846] | 1330 | # b) |
---|
[1118] | 1331 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
[189] | 1332 | # masks the regions between 400 and 500 |
---|
[113] | 1333 | # and 800 and 900 in the unit 'channel' |
---|
[1846] | 1334 | |
---|
| 1335 | # c) |
---|
| 1336 | #mask only channel 400 |
---|
[1554] | 1337 | msk = scan.create_mask([400]) |
---|
[1846] | 1338 | |
---|
[102] | 1339 | """ |
---|
[1554] | 1340 | row = kwargs.get("row", 0) |
---|
[513] | 1341 | data = self._getabcissa(row) |
---|
[113] | 1342 | u = self._getcoordinfo()[0] |
---|
[1859] | 1343 | if u == "": |
---|
| 1344 | u = "channel" |
---|
| 1345 | msg = "The current mask window unit is %s" % u |
---|
| 1346 | i = self._check_ifs() |
---|
| 1347 | if not i: |
---|
| 1348 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
| 1349 | asaplog.push(msg) |
---|
[2348] | 1350 | n = len(data) |
---|
[1295] | 1351 | msk = _n_bools(n, False) |
---|
[710] | 1352 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
| 1353 | |
---|
[2349] | 1354 | ws = (isinstance(args[-1][-1], int) |
---|
| 1355 | or isinstance(args[-1][-1], float)) and args or args[0] |
---|
[710] | 1356 | for window in ws: |
---|
[1554] | 1357 | if len(window) == 1: |
---|
| 1358 | window = [window[0], window[0]] |
---|
| 1359 | if len(window) == 0 or len(window) > 2: |
---|
[2349] | 1360 | raise ValueError("A window needs to be defined as " |
---|
| 1361 | "[start(, end)]") |
---|
[1545] | 1362 | if window[0] > window[1]: |
---|
| 1363 | tmp = window[0] |
---|
| 1364 | window[0] = window[1] |
---|
| 1365 | window[1] = tmp |
---|
[102] | 1366 | for i in range(n): |
---|
[1024] | 1367 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
[1295] | 1368 | msk[i] = True |
---|
[113] | 1369 | if kwargs.has_key('invert'): |
---|
| 1370 | if kwargs.get('invert'): |
---|
[1295] | 1371 | msk = mask_not(msk) |
---|
[102] | 1372 | return msk |
---|
[710] | 1373 | |
---|
[1931] | 1374 | def get_masklist(self, mask=None, row=0, silent=False): |
---|
[1846] | 1375 | """\ |
---|
[1819] | 1376 | Compute and return a list of mask windows, [min, max]. |
---|
[1846] | 1377 | |
---|
[1819] | 1378 | Parameters: |
---|
[1846] | 1379 | |
---|
[1819] | 1380 | mask: channel mask, created with create_mask. |
---|
[1855] | 1381 | |
---|
[1819] | 1382 | row: calcutate the masklist using the specified row |
---|
| 1383 | for unit conversions, default is row=0 |
---|
| 1384 | only necessary if frequency varies over rows. |
---|
[1846] | 1385 | |
---|
[1819] | 1386 | Returns: |
---|
[1846] | 1387 | |
---|
[1819] | 1388 | [min, max], [min2, max2], ... |
---|
| 1389 | Pairs of start/end points (inclusive)specifying |
---|
| 1390 | the masked regions |
---|
[1846] | 1391 | |
---|
[1819] | 1392 | """ |
---|
| 1393 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1394 | raise TypeError("The mask should be list or tuple.") |
---|
| 1395 | if len(mask) < 2: |
---|
| 1396 | raise TypeError("The mask elements should be > 1") |
---|
[2348] | 1397 | data = self._getabcissa(row) |
---|
| 1398 | if len(data) != len(mask): |
---|
[1819] | 1399 | msg = "Number of channels in scantable != number of mask elements" |
---|
| 1400 | raise TypeError(msg) |
---|
| 1401 | u = self._getcoordinfo()[0] |
---|
[1859] | 1402 | if u == "": |
---|
| 1403 | u = "channel" |
---|
| 1404 | msg = "The current mask window unit is %s" % u |
---|
| 1405 | i = self._check_ifs() |
---|
| 1406 | if not i: |
---|
| 1407 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
[1931] | 1408 | if not silent: |
---|
| 1409 | asaplog.push(msg) |
---|
[2349] | 1410 | masklist = [] |
---|
[1819] | 1411 | ist, ien = None, None |
---|
| 1412 | ist, ien=self.get_mask_indices(mask) |
---|
| 1413 | if ist is not None and ien is not None: |
---|
| 1414 | for i in xrange(len(ist)): |
---|
| 1415 | range=[data[ist[i]],data[ien[i]]] |
---|
| 1416 | range.sort() |
---|
| 1417 | masklist.append([range[0],range[1]]) |
---|
| 1418 | return masklist |
---|
| 1419 | |
---|
| 1420 | def get_mask_indices(self, mask=None): |
---|
[1846] | 1421 | """\ |
---|
[1819] | 1422 | Compute and Return lists of mask start indices and mask end indices. |
---|
[1855] | 1423 | |
---|
| 1424 | Parameters: |
---|
| 1425 | |
---|
[1819] | 1426 | mask: channel mask, created with create_mask. |
---|
[1846] | 1427 | |
---|
[1819] | 1428 | Returns: |
---|
[1846] | 1429 | |
---|
[1819] | 1430 | List of mask start indices and that of mask end indices, |
---|
| 1431 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
[1846] | 1432 | |
---|
[1819] | 1433 | """ |
---|
| 1434 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
| 1435 | raise TypeError("The mask should be list or tuple.") |
---|
| 1436 | if len(mask) < 2: |
---|
| 1437 | raise TypeError("The mask elements should be > 1") |
---|
[2349] | 1438 | istart = [] |
---|
| 1439 | iend = [] |
---|
| 1440 | if mask[0]: |
---|
| 1441 | istart.append(0) |
---|
[1819] | 1442 | for i in range(len(mask)-1): |
---|
| 1443 | if not mask[i] and mask[i+1]: |
---|
| 1444 | istart.append(i+1) |
---|
| 1445 | elif mask[i] and not mask[i+1]: |
---|
| 1446 | iend.append(i) |
---|
[2349] | 1447 | if mask[len(mask)-1]: |
---|
| 1448 | iend.append(len(mask)-1) |
---|
[1819] | 1449 | if len(istart) != len(iend): |
---|
| 1450 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
| 1451 | for i in range(len(istart)): |
---|
| 1452 | if istart[i] > iend[i]: |
---|
| 1453 | raise RuntimeError("Mask start index > mask end index") |
---|
| 1454 | break |
---|
| 1455 | return istart,iend |
---|
| 1456 | |
---|
[2013] | 1457 | @asaplog_post_dec |
---|
[2349] | 1458 | def parse_maskexpr(self, maskstring): |
---|
[2013] | 1459 | """ |
---|
| 1460 | Parse CASA type mask selection syntax (IF dependent). |
---|
| 1461 | |
---|
| 1462 | Parameters: |
---|
| 1463 | maskstring : A string mask selection expression. |
---|
| 1464 | A comma separated selections mean different IF - |
---|
| 1465 | channel combinations. IFs and channel selections |
---|
| 1466 | are partitioned by a colon, ':'. |
---|
| 1467 | examples: |
---|
[2015] | 1468 | '' = all IFs (all channels) |
---|
[2013] | 1469 | '<2,4~6,9' = IFs 0,1,4,5,6,9 (all channels) |
---|
| 1470 | '3:3~45;60' = channels 3 to 45 and 60 in IF 3 |
---|
| 1471 | '0~1:2~6,8' = channels 2 to 6 in IFs 0,1, and |
---|
| 1472 | all channels in IF8 |
---|
| 1473 | Returns: |
---|
| 1474 | A dictionary of selected (valid) IF and masklist pairs, |
---|
| 1475 | e.g. {'0': [[50,250],[350,462]], '2': [[100,400],[550,974]]} |
---|
| 1476 | """ |
---|
| 1477 | if not isinstance(maskstring,str): |
---|
| 1478 | asaplog.post() |
---|
| 1479 | asaplog.push("Invalid mask expression") |
---|
| 1480 | asaplog.post("ERROR") |
---|
| 1481 | |
---|
| 1482 | valid_ifs = self.getifnos() |
---|
| 1483 | frequnit = self.get_unit() |
---|
| 1484 | seldict = {} |
---|
[2015] | 1485 | if maskstring == "": |
---|
| 1486 | maskstring = str(valid_ifs)[1:-1] |
---|
[2013] | 1487 | ## split each selection |
---|
| 1488 | sellist = maskstring.split(',') |
---|
| 1489 | for currselstr in sellist: |
---|
| 1490 | selset = currselstr.split(':') |
---|
| 1491 | # spw and mask string (may include ~, < or >) |
---|
[2349] | 1492 | spwmasklist = self._parse_selection(selset[0], typestr='integer', |
---|
| 1493 | offset=1, minval=min(valid_ifs), |
---|
| 1494 | maxval=max(valid_ifs)) |
---|
[2013] | 1495 | for spwlist in spwmasklist: |
---|
| 1496 | selspws = [] |
---|
| 1497 | for ispw in range(spwlist[0],spwlist[1]+1): |
---|
| 1498 | # Put into the list only if ispw exists |
---|
| 1499 | if valid_ifs.count(ispw): |
---|
| 1500 | selspws.append(ispw) |
---|
| 1501 | del spwmasklist, spwlist |
---|
| 1502 | |
---|
| 1503 | # parse frequency mask list |
---|
| 1504 | if len(selset) > 1: |
---|
[2349] | 1505 | freqmasklist = self._parse_selection(selset[1], typestr='float', |
---|
| 1506 | offset=0.) |
---|
[2013] | 1507 | else: |
---|
| 1508 | # want to select the whole spectrum |
---|
| 1509 | freqmasklist = [None] |
---|
| 1510 | |
---|
| 1511 | ## define a dictionary of spw - masklist combination |
---|
| 1512 | for ispw in selspws: |
---|
| 1513 | #print "working on", ispw |
---|
| 1514 | spwstr = str(ispw) |
---|
| 1515 | if len(selspws) == 0: |
---|
| 1516 | # empty spw |
---|
| 1517 | continue |
---|
| 1518 | else: |
---|
| 1519 | ## want to get min and max of the spw and |
---|
| 1520 | ## offset to set for '<' and '>' |
---|
| 1521 | if frequnit == 'channel': |
---|
| 1522 | minfreq = 0 |
---|
| 1523 | maxfreq = self.nchan(ifno=ispw) |
---|
| 1524 | offset = 0.5 |
---|
| 1525 | else: |
---|
| 1526 | ## This is ugly part. need improvement |
---|
| 1527 | for ifrow in xrange(self.nrow()): |
---|
| 1528 | if self.getif(ifrow) == ispw: |
---|
| 1529 | #print "IF",ispw,"found in row =",ifrow |
---|
| 1530 | break |
---|
| 1531 | freqcoord = self.get_coordinate(ifrow) |
---|
| 1532 | freqs = self._getabcissa(ifrow) |
---|
| 1533 | minfreq = min(freqs) |
---|
| 1534 | maxfreq = max(freqs) |
---|
| 1535 | if len(freqs) == 1: |
---|
| 1536 | offset = 0.5 |
---|
| 1537 | elif frequnit.find('Hz') > 0: |
---|
[2349] | 1538 | offset = abs(freqcoord.to_frequency(1, |
---|
| 1539 | unit=frequnit) |
---|
| 1540 | -freqcoord.to_frequency(0, |
---|
| 1541 | unit=frequnit) |
---|
| 1542 | )*0.5 |
---|
[2013] | 1543 | elif frequnit.find('m/s') > 0: |
---|
[2349] | 1544 | offset = abs(freqcoord.to_velocity(1, |
---|
| 1545 | unit=frequnit) |
---|
| 1546 | -freqcoord.to_velocity(0, |
---|
| 1547 | unit=frequnit) |
---|
| 1548 | )*0.5 |
---|
[2013] | 1549 | else: |
---|
| 1550 | asaplog.post() |
---|
| 1551 | asaplog.push("Invalid frequency unit") |
---|
| 1552 | asaplog.post("ERROR") |
---|
| 1553 | del freqs, freqcoord, ifrow |
---|
| 1554 | for freq in freqmasklist: |
---|
| 1555 | selmask = freq or [minfreq, maxfreq] |
---|
| 1556 | if selmask[0] == None: |
---|
| 1557 | ## selection was "<freq[1]". |
---|
| 1558 | if selmask[1] < minfreq: |
---|
| 1559 | ## avoid adding region selection |
---|
| 1560 | selmask = None |
---|
| 1561 | else: |
---|
| 1562 | selmask = [minfreq,selmask[1]-offset] |
---|
| 1563 | elif selmask[1] == None: |
---|
| 1564 | ## selection was ">freq[0]" |
---|
| 1565 | if selmask[0] > maxfreq: |
---|
| 1566 | ## avoid adding region selection |
---|
| 1567 | selmask = None |
---|
| 1568 | else: |
---|
| 1569 | selmask = [selmask[0]+offset,maxfreq] |
---|
| 1570 | if selmask: |
---|
| 1571 | if not seldict.has_key(spwstr): |
---|
| 1572 | # new spw selection |
---|
| 1573 | seldict[spwstr] = [] |
---|
| 1574 | seldict[spwstr] += [selmask] |
---|
| 1575 | del minfreq,maxfreq,offset,freq,selmask |
---|
| 1576 | del spwstr |
---|
| 1577 | del freqmasklist |
---|
| 1578 | del valid_ifs |
---|
| 1579 | if len(seldict) == 0: |
---|
| 1580 | asaplog.post() |
---|
[2349] | 1581 | asaplog.push("No valid selection in the mask expression: " |
---|
| 1582 | +maskstring) |
---|
[2013] | 1583 | asaplog.post("WARN") |
---|
| 1584 | return None |
---|
| 1585 | msg = "Selected masklist:\n" |
---|
| 1586 | for sif, lmask in seldict.iteritems(): |
---|
| 1587 | msg += " IF"+sif+" - "+str(lmask)+"\n" |
---|
| 1588 | asaplog.push(msg) |
---|
| 1589 | return seldict |
---|
| 1590 | |
---|
[2349] | 1591 | def _parse_selection(self, selstr, typestr='float', offset=0., |
---|
[2351] | 1592 | minval=None, maxval=None): |
---|
[2013] | 1593 | """ |
---|
| 1594 | Parameters: |
---|
| 1595 | selstr : The Selection string, e.g., '<3;5~7;100~103;9' |
---|
| 1596 | typestr : The type of the values in returned list |
---|
| 1597 | ('integer' or 'float') |
---|
| 1598 | offset : The offset value to subtract from or add to |
---|
| 1599 | the boundary value if the selection string |
---|
| 1600 | includes '<' or '>' |
---|
| 1601 | minval, maxval : The minimum/maximum values to set if the |
---|
| 1602 | selection string includes '<' or '>'. |
---|
| 1603 | The list element is filled with None by default. |
---|
| 1604 | Returns: |
---|
| 1605 | A list of min/max pair of selections. |
---|
| 1606 | Example: |
---|
| 1607 | _parseSelection('<3;5~7;9',typestr='int',offset=1,minval=0) |
---|
| 1608 | returns [[0,2],[5,7],[9,9]] |
---|
| 1609 | """ |
---|
| 1610 | selgroups = selstr.split(';') |
---|
| 1611 | sellists = [] |
---|
| 1612 | if typestr.lower().startswith('int'): |
---|
| 1613 | formatfunc = int |
---|
| 1614 | else: |
---|
| 1615 | formatfunc = float |
---|
| 1616 | |
---|
| 1617 | for currsel in selgroups: |
---|
| 1618 | if currsel.find('~') > 0: |
---|
| 1619 | minsel = formatfunc(currsel.split('~')[0].strip()) |
---|
| 1620 | maxsel = formatfunc(currsel.split('~')[1].strip()) |
---|
| 1621 | elif currsel.strip().startswith('<'): |
---|
| 1622 | minsel = minval |
---|
| 1623 | maxsel = formatfunc(currsel.split('<')[1].strip()) \ |
---|
| 1624 | - formatfunc(offset) |
---|
| 1625 | elif currsel.strip().startswith('>'): |
---|
| 1626 | minsel = formatfunc(currsel.split('>')[1].strip()) \ |
---|
| 1627 | + formatfunc(offset) |
---|
| 1628 | maxsel = maxval |
---|
| 1629 | else: |
---|
| 1630 | minsel = formatfunc(currsel) |
---|
| 1631 | maxsel = formatfunc(currsel) |
---|
| 1632 | sellists.append([minsel,maxsel]) |
---|
| 1633 | return sellists |
---|
| 1634 | |
---|
[1819] | 1635 | # def get_restfreqs(self): |
---|
| 1636 | # """ |
---|
| 1637 | # Get the restfrequency(s) stored in this scantable. |
---|
| 1638 | # The return value(s) are always of unit 'Hz' |
---|
| 1639 | # Parameters: |
---|
| 1640 | # none |
---|
| 1641 | # Returns: |
---|
| 1642 | # a list of doubles |
---|
| 1643 | # """ |
---|
| 1644 | # return list(self._getrestfreqs()) |
---|
| 1645 | |
---|
| 1646 | def get_restfreqs(self, ids=None): |
---|
[1846] | 1647 | """\ |
---|
[256] | 1648 | Get the restfrequency(s) stored in this scantable. |
---|
| 1649 | The return value(s) are always of unit 'Hz' |
---|
[1846] | 1650 | |
---|
[256] | 1651 | Parameters: |
---|
[1846] | 1652 | |
---|
[1819] | 1653 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
| 1654 | be retrieved |
---|
[1846] | 1655 | |
---|
[256] | 1656 | Returns: |
---|
[1846] | 1657 | |
---|
[1819] | 1658 | dictionary containing ids and a list of doubles for each id |
---|
[1846] | 1659 | |
---|
[256] | 1660 | """ |
---|
[1819] | 1661 | if ids is None: |
---|
[2349] | 1662 | rfreqs = {} |
---|
[1819] | 1663 | idlist = self.getmolnos() |
---|
| 1664 | for i in idlist: |
---|
[2349] | 1665 | rfreqs[i] = list(self._getrestfreqs(i)) |
---|
[1819] | 1666 | return rfreqs |
---|
| 1667 | else: |
---|
[2349] | 1668 | if type(ids) == list or type(ids) == tuple: |
---|
| 1669 | rfreqs = {} |
---|
[1819] | 1670 | for i in ids: |
---|
[2349] | 1671 | rfreqs[i] = list(self._getrestfreqs(i)) |
---|
[1819] | 1672 | return rfreqs |
---|
| 1673 | else: |
---|
| 1674 | return list(self._getrestfreqs(ids)) |
---|
[102] | 1675 | |
---|
[2349] | 1676 | @asaplog_post_dec |
---|
[931] | 1677 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
[1846] | 1678 | """\ |
---|
[931] | 1679 | Set or replace the restfrequency specified and |
---|
[1938] | 1680 | if the 'freqs' argument holds a scalar, |
---|
[931] | 1681 | then that rest frequency will be applied to all the selected |
---|
| 1682 | data. If the 'freqs' argument holds |
---|
| 1683 | a vector, then it MUST be of equal or smaller length than |
---|
| 1684 | the number of IFs (and the available restfrequencies will be |
---|
| 1685 | replaced by this vector). In this case, *all* data have |
---|
| 1686 | the restfrequency set per IF according |
---|
| 1687 | to the corresponding value you give in the 'freqs' vector. |
---|
[1118] | 1688 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
[931] | 1689 | IF 1 gets restfreq 2e9. |
---|
[1846] | 1690 | |
---|
[1395] | 1691 | You can also specify the frequencies via a linecatalog. |
---|
[1153] | 1692 | |
---|
[931] | 1693 | Parameters: |
---|
[1846] | 1694 | |
---|
[931] | 1695 | freqs: list of rest frequency values or string idenitfiers |
---|
[1855] | 1696 | |
---|
[931] | 1697 | unit: unit for rest frequency (default 'Hz') |
---|
[402] | 1698 | |
---|
[1846] | 1699 | |
---|
| 1700 | Example:: |
---|
| 1701 | |
---|
[1819] | 1702 | # set the given restfrequency for the all currently selected IFs |
---|
[931] | 1703 | scan.set_restfreqs(freqs=1.4e9) |
---|
[1845] | 1704 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
| 1705 | # list, i.e |
---|
| 1706 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
| 1707 | # len(list_of_restfreqs) == nIF |
---|
| 1708 | # for nIF == 1 the following will set multiple restfrequency for |
---|
| 1709 | # that IF |
---|
[1819] | 1710 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
[1845] | 1711 | # set multiple restfrequencies per IF. as a list of lists where |
---|
| 1712 | # the outer list has nIF elements, the inner s arbitrary |
---|
| 1713 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
[391] | 1714 | |
---|
[1846] | 1715 | *Note*: |
---|
[1845] | 1716 | |
---|
[931] | 1717 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
| 1718 | source and IF basis, use scantable.set_selection() before using |
---|
[1846] | 1719 | this function:: |
---|
[931] | 1720 | |
---|
[1846] | 1721 | # provided your scantable is called scan |
---|
| 1722 | selection = selector() |
---|
| 1723 | selection.set_name("ORION*") |
---|
| 1724 | selection.set_ifs([1]) |
---|
| 1725 | scan.set_selection(selection) |
---|
| 1726 | scan.set_restfreqs(freqs=86.6e9) |
---|
| 1727 | |
---|
[931] | 1728 | """ |
---|
| 1729 | varlist = vars() |
---|
[1157] | 1730 | from asap import linecatalog |
---|
| 1731 | # simple value |
---|
[1118] | 1732 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
[1845] | 1733 | self._setrestfreqs([freqs], [""], unit) |
---|
[1157] | 1734 | # list of values |
---|
[1118] | 1735 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
[1157] | 1736 | # list values are scalars |
---|
[1118] | 1737 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
[1845] | 1738 | if len(freqs) == 1: |
---|
| 1739 | self._setrestfreqs(freqs, [""], unit) |
---|
| 1740 | else: |
---|
| 1741 | # allow the 'old' mode of setting mulitple IFs |
---|
| 1742 | sel = selector() |
---|
| 1743 | savesel = self._getselection() |
---|
| 1744 | iflist = self.getifnos() |
---|
| 1745 | if len(freqs)>len(iflist): |
---|
| 1746 | raise ValueError("number of elements in list of list " |
---|
| 1747 | "exeeds the current IF selections") |
---|
| 1748 | iflist = self.getifnos() |
---|
| 1749 | for i, fval in enumerate(freqs): |
---|
| 1750 | sel.set_ifs(iflist[i]) |
---|
| 1751 | self._setselection(sel) |
---|
| 1752 | self._setrestfreqs([fval], [""], unit) |
---|
| 1753 | self._setselection(savesel) |
---|
| 1754 | |
---|
| 1755 | # list values are dict, {'value'=, 'name'=) |
---|
[1157] | 1756 | elif isinstance(freqs[-1], dict): |
---|
[1845] | 1757 | values = [] |
---|
| 1758 | names = [] |
---|
| 1759 | for d in freqs: |
---|
| 1760 | values.append(d["value"]) |
---|
| 1761 | names.append(d["name"]) |
---|
| 1762 | self._setrestfreqs(values, names, unit) |
---|
[1819] | 1763 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
[1157] | 1764 | sel = selector() |
---|
| 1765 | savesel = self._getselection() |
---|
[1322] | 1766 | iflist = self.getifnos() |
---|
[1819] | 1767 | if len(freqs)>len(iflist): |
---|
[1845] | 1768 | raise ValueError("number of elements in list of list exeeds" |
---|
| 1769 | " the current IF selections") |
---|
| 1770 | for i, fval in enumerate(freqs): |
---|
[1322] | 1771 | sel.set_ifs(iflist[i]) |
---|
[1259] | 1772 | self._setselection(sel) |
---|
[1845] | 1773 | self._setrestfreqs(fval, [""], unit) |
---|
[1157] | 1774 | self._setselection(savesel) |
---|
| 1775 | # freqs are to be taken from a linecatalog |
---|
[1153] | 1776 | elif isinstance(freqs, linecatalog): |
---|
| 1777 | sel = selector() |
---|
| 1778 | savesel = self._getselection() |
---|
| 1779 | for i in xrange(freqs.nrow()): |
---|
[1322] | 1780 | sel.set_ifs(iflist[i]) |
---|
[1153] | 1781 | self._setselection(sel) |
---|
[1845] | 1782 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
| 1783 | [freqs.get_name(i)], "MHz") |
---|
[1153] | 1784 | # ensure that we are not iterating past nIF |
---|
| 1785 | if i == self.nif()-1: break |
---|
| 1786 | self._setselection(savesel) |
---|
[931] | 1787 | else: |
---|
| 1788 | return |
---|
| 1789 | self._add_history("set_restfreqs", varlist) |
---|
| 1790 | |
---|
[2349] | 1791 | @asaplog_post_dec |
---|
[1360] | 1792 | def shift_refpix(self, delta): |
---|
[1846] | 1793 | """\ |
---|
[1589] | 1794 | Shift the reference pixel of the Spectra Coordinate by an |
---|
| 1795 | integer amount. |
---|
[1846] | 1796 | |
---|
[1589] | 1797 | Parameters: |
---|
[1846] | 1798 | |
---|
[1589] | 1799 | delta: the amount to shift by |
---|
[1846] | 1800 | |
---|
| 1801 | *Note*: |
---|
| 1802 | |
---|
[1589] | 1803 | Be careful using this with broadband data. |
---|
[1846] | 1804 | |
---|
[1360] | 1805 | """ |
---|
[2349] | 1806 | varlist = vars() |
---|
[1731] | 1807 | Scantable.shift_refpix(self, delta) |
---|
[2349] | 1808 | s._add_history("shift_refpix", varlist) |
---|
[931] | 1809 | |
---|
[1862] | 1810 | @asaplog_post_dec |
---|
[1259] | 1811 | def history(self, filename=None): |
---|
[1846] | 1812 | """\ |
---|
[1259] | 1813 | Print the history. Optionally to a file. |
---|
[1846] | 1814 | |
---|
[1348] | 1815 | Parameters: |
---|
[1846] | 1816 | |
---|
[1928] | 1817 | filename: The name of the file to save the history to. |
---|
[1846] | 1818 | |
---|
[1259] | 1819 | """ |
---|
[484] | 1820 | hist = list(self._gethistory()) |
---|
[794] | 1821 | out = "-"*80 |
---|
[484] | 1822 | for h in hist: |
---|
[489] | 1823 | if h.startswith("---"): |
---|
[1857] | 1824 | out = "\n".join([out, h]) |
---|
[489] | 1825 | else: |
---|
| 1826 | items = h.split("##") |
---|
| 1827 | date = items[0] |
---|
| 1828 | func = items[1] |
---|
| 1829 | items = items[2:] |
---|
[794] | 1830 | out += "\n"+date+"\n" |
---|
| 1831 | out += "Function: %s\n Parameters:" % (func) |
---|
[489] | 1832 | for i in items: |
---|
[1938] | 1833 | if i == '': |
---|
| 1834 | continue |
---|
[489] | 1835 | s = i.split("=") |
---|
[1118] | 1836 | out += "\n %s = %s" % (s[0], s[1]) |
---|
[1857] | 1837 | out = "\n".join([out, "-"*80]) |
---|
[1259] | 1838 | if filename is not None: |
---|
| 1839 | if filename is "": |
---|
| 1840 | filename = 'scantable_history.txt' |
---|
| 1841 | import os |
---|
| 1842 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 1843 | if not os.path.isdir(filename): |
---|
| 1844 | data = open(filename, 'w') |
---|
| 1845 | data.write(out) |
---|
| 1846 | data.close() |
---|
| 1847 | else: |
---|
| 1848 | msg = "Illegal file name '%s'." % (filename) |
---|
[1859] | 1849 | raise IOError(msg) |
---|
| 1850 | return page(out) |
---|
[2349] | 1851 | |
---|
[513] | 1852 | # |
---|
| 1853 | # Maths business |
---|
| 1854 | # |
---|
[1862] | 1855 | @asaplog_post_dec |
---|
[931] | 1856 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
[1846] | 1857 | """\ |
---|
[2349] | 1858 | Return the (time) weighted average of a scan. Scans will be averaged |
---|
| 1859 | only if the source direction (RA/DEC) is within 1' otherwise |
---|
[1846] | 1860 | |
---|
| 1861 | *Note*: |
---|
| 1862 | |
---|
[1070] | 1863 | in channels only - align if necessary |
---|
[1846] | 1864 | |
---|
[513] | 1865 | Parameters: |
---|
[1846] | 1866 | |
---|
[513] | 1867 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
| 1868 | weighting) |
---|
[1855] | 1869 | |
---|
[558] | 1870 | scanav: True averages each scan separately |
---|
| 1871 | False (default) averages all scans together, |
---|
[1855] | 1872 | |
---|
[1099] | 1873 | weight: Weighting scheme. |
---|
| 1874 | 'none' (mean no weight) |
---|
| 1875 | 'var' (1/var(spec) weighted) |
---|
| 1876 | 'tsys' (1/Tsys**2 weighted) |
---|
| 1877 | 'tint' (integration time weighted) |
---|
| 1878 | 'tintsys' (Tint/Tsys**2) |
---|
| 1879 | 'median' ( median averaging) |
---|
[535] | 1880 | The default is 'tint' |
---|
[1855] | 1881 | |
---|
[931] | 1882 | align: align the spectra in velocity before averaging. It takes |
---|
| 1883 | the time of the first spectrum as reference time. |
---|
[1846] | 1884 | |
---|
| 1885 | Example:: |
---|
| 1886 | |
---|
[513] | 1887 | # time average the scantable without using a mask |
---|
[710] | 1888 | newscan = scan.average_time() |
---|
[1846] | 1889 | |
---|
[513] | 1890 | """ |
---|
| 1891 | varlist = vars() |
---|
[1593] | 1892 | weight = weight or 'TINT' |
---|
| 1893 | mask = mask or () |
---|
| 1894 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
[1118] | 1895 | scan = (self, ) |
---|
[1859] | 1896 | |
---|
| 1897 | if align: |
---|
| 1898 | scan = (self.freq_align(insitu=False), ) |
---|
| 1899 | s = None |
---|
| 1900 | if weight.upper() == 'MEDIAN': |
---|
| 1901 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
| 1902 | scanav)) |
---|
| 1903 | else: |
---|
| 1904 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
| 1905 | scanav)) |
---|
[1099] | 1906 | s._add_history("average_time", varlist) |
---|
[513] | 1907 | return s |
---|
[710] | 1908 | |
---|
[1862] | 1909 | @asaplog_post_dec |
---|
[876] | 1910 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
[1846] | 1911 | """\ |
---|
[513] | 1912 | Return a scan where all spectra are converted to either |
---|
| 1913 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
| 1914 | By default the function tries to look the values up internally. |
---|
| 1915 | If it can't find them (or if you want to over-ride), you must |
---|
| 1916 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
| 1917 | also if you don't set it). jyperk takes precedence if you set both. |
---|
[1846] | 1918 | |
---|
[513] | 1919 | Parameters: |
---|
[1846] | 1920 | |
---|
[513] | 1921 | jyperk: the Jy / K conversion factor |
---|
[1855] | 1922 | |
---|
[513] | 1923 | eta: the aperture efficiency |
---|
[1855] | 1924 | |
---|
[1928] | 1925 | d: the geometric diameter (metres) |
---|
[1855] | 1926 | |
---|
[513] | 1927 | insitu: if False a new scantable is returned. |
---|
| 1928 | Otherwise, the scaling is done in-situ |
---|
| 1929 | The default is taken from .asaprc (False) |
---|
[1846] | 1930 | |
---|
[513] | 1931 | """ |
---|
| 1932 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1933 | self._math._setinsitu(insitu) |
---|
[513] | 1934 | varlist = vars() |
---|
[1593] | 1935 | jyperk = jyperk or -1.0 |
---|
| 1936 | d = d or -1.0 |
---|
| 1937 | eta = eta or -1.0 |
---|
[876] | 1938 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
| 1939 | s._add_history("convert_flux", varlist) |
---|
| 1940 | if insitu: self._assign(s) |
---|
| 1941 | else: return s |
---|
[513] | 1942 | |
---|
[1862] | 1943 | @asaplog_post_dec |
---|
[876] | 1944 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
[1846] | 1945 | """\ |
---|
[513] | 1946 | Return a scan after applying a gain-elevation correction. |
---|
| 1947 | The correction can be made via either a polynomial or a |
---|
| 1948 | table-based interpolation (and extrapolation if necessary). |
---|
| 1949 | You specify polynomial coefficients, an ascii table or neither. |
---|
| 1950 | If you specify neither, then a polynomial correction will be made |
---|
| 1951 | with built in coefficients known for certain telescopes (an error |
---|
| 1952 | will occur if the instrument is not known). |
---|
| 1953 | The data and Tsys are *divided* by the scaling factors. |
---|
[1846] | 1954 | |
---|
[513] | 1955 | Parameters: |
---|
[1846] | 1956 | |
---|
[513] | 1957 | poly: Polynomial coefficients (default None) to compute a |
---|
| 1958 | gain-elevation correction as a function of |
---|
| 1959 | elevation (in degrees). |
---|
[1855] | 1960 | |
---|
[513] | 1961 | filename: The name of an ascii file holding correction factors. |
---|
| 1962 | The first row of the ascii file must give the column |
---|
| 1963 | names and these MUST include columns |
---|
| 1964 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
| 1965 | by this) somewhere. |
---|
| 1966 | The second row must give the data type of the |
---|
| 1967 | column. Use 'R' for Real and 'I' for Integer. |
---|
| 1968 | An example file would be |
---|
| 1969 | (actual factors are arbitrary) : |
---|
| 1970 | |
---|
| 1971 | TIME ELEVATION FACTOR |
---|
| 1972 | R R R |
---|
| 1973 | 0.1 0 0.8 |
---|
| 1974 | 0.2 20 0.85 |
---|
| 1975 | 0.3 40 0.9 |
---|
| 1976 | 0.4 60 0.85 |
---|
| 1977 | 0.5 80 0.8 |
---|
| 1978 | 0.6 90 0.75 |
---|
[1855] | 1979 | |
---|
[513] | 1980 | method: Interpolation method when correcting from a table. |
---|
| 1981 | Values are "nearest", "linear" (default), "cubic" |
---|
| 1982 | and "spline" |
---|
[1855] | 1983 | |
---|
[513] | 1984 | insitu: if False a new scantable is returned. |
---|
| 1985 | Otherwise, the scaling is done in-situ |
---|
| 1986 | The default is taken from .asaprc (False) |
---|
[1846] | 1987 | |
---|
[513] | 1988 | """ |
---|
| 1989 | |
---|
| 1990 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 1991 | self._math._setinsitu(insitu) |
---|
[513] | 1992 | varlist = vars() |
---|
[1593] | 1993 | poly = poly or () |
---|
[513] | 1994 | from os.path import expandvars |
---|
| 1995 | filename = expandvars(filename) |
---|
[876] | 1996 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
| 1997 | s._add_history("gain_el", varlist) |
---|
[1593] | 1998 | if insitu: |
---|
| 1999 | self._assign(s) |
---|
| 2000 | else: |
---|
| 2001 | return s |
---|
[710] | 2002 | |
---|
[1862] | 2003 | @asaplog_post_dec |
---|
[931] | 2004 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
[1846] | 2005 | """\ |
---|
[513] | 2006 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
| 2007 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
| 2008 | set_freqframe. |
---|
[1846] | 2009 | |
---|
[513] | 2010 | Parameters: |
---|
[1855] | 2011 | |
---|
[513] | 2012 | reftime: reference time to align at. By default, the time of |
---|
| 2013 | the first row of data is used. |
---|
[1855] | 2014 | |
---|
[513] | 2015 | method: Interpolation method for regridding the spectra. |
---|
| 2016 | Choose from "nearest", "linear", "cubic" (default) |
---|
| 2017 | and "spline" |
---|
[1855] | 2018 | |
---|
[513] | 2019 | insitu: if False a new scantable is returned. |
---|
| 2020 | Otherwise, the scaling is done in-situ |
---|
| 2021 | The default is taken from .asaprc (False) |
---|
[1846] | 2022 | |
---|
[513] | 2023 | """ |
---|
[931] | 2024 | if insitu is None: insitu = rcParams["insitu"] |
---|
[876] | 2025 | self._math._setinsitu(insitu) |
---|
[513] | 2026 | varlist = vars() |
---|
[1593] | 2027 | reftime = reftime or "" |
---|
[931] | 2028 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
[876] | 2029 | s._add_history("freq_align", varlist) |
---|
[2349] | 2030 | if insitu: |
---|
| 2031 | self._assign(s) |
---|
| 2032 | else: |
---|
| 2033 | return s |
---|
[513] | 2034 | |
---|
[1862] | 2035 | @asaplog_post_dec |
---|
[1725] | 2036 | def opacity(self, tau=None, insitu=None): |
---|
[1846] | 2037 | """\ |
---|
[513] | 2038 | Apply an opacity correction. The data |
---|
| 2039 | and Tsys are multiplied by the correction factor. |
---|
[1846] | 2040 | |
---|
[513] | 2041 | Parameters: |
---|
[1855] | 2042 | |
---|
[1689] | 2043 | tau: (list of) opacity from which the correction factor is |
---|
[513] | 2044 | exp(tau*ZD) |
---|
[1689] | 2045 | where ZD is the zenith-distance. |
---|
| 2046 | If a list is provided, it has to be of length nIF, |
---|
| 2047 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
| 2048 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
[1725] | 2049 | if tau is `None` the opacities are determined from a |
---|
| 2050 | model. |
---|
[1855] | 2051 | |
---|
[513] | 2052 | insitu: if False a new scantable is returned. |
---|
| 2053 | Otherwise, the scaling is done in-situ |
---|
| 2054 | The default is taken from .asaprc (False) |
---|
[1846] | 2055 | |
---|
[513] | 2056 | """ |
---|
[2349] | 2057 | if insitu is None: |
---|
| 2058 | insitu = rcParams['insitu'] |
---|
[876] | 2059 | self._math._setinsitu(insitu) |
---|
[513] | 2060 | varlist = vars() |
---|
[1689] | 2061 | if not hasattr(tau, "__len__"): |
---|
| 2062 | tau = [tau] |
---|
[876] | 2063 | s = scantable(self._math._opacity(self, tau)) |
---|
| 2064 | s._add_history("opacity", varlist) |
---|
[2349] | 2065 | if insitu: |
---|
| 2066 | self._assign(s) |
---|
| 2067 | else: |
---|
| 2068 | return s |
---|
[513] | 2069 | |
---|
[1862] | 2070 | @asaplog_post_dec |
---|
[513] | 2071 | def bin(self, width=5, insitu=None): |
---|
[1846] | 2072 | """\ |
---|
[513] | 2073 | Return a scan where all spectra have been binned up. |
---|
[1846] | 2074 | |
---|
[1348] | 2075 | Parameters: |
---|
[1846] | 2076 | |
---|
[513] | 2077 | width: The bin width (default=5) in pixels |
---|
[1855] | 2078 | |
---|
[513] | 2079 | insitu: if False a new scantable is returned. |
---|
| 2080 | Otherwise, the scaling is done in-situ |
---|
| 2081 | The default is taken from .asaprc (False) |
---|
[1846] | 2082 | |
---|
[513] | 2083 | """ |
---|
[2349] | 2084 | if insitu is None: |
---|
| 2085 | insitu = rcParams['insitu'] |
---|
[876] | 2086 | self._math._setinsitu(insitu) |
---|
[513] | 2087 | varlist = vars() |
---|
[876] | 2088 | s = scantable(self._math._bin(self, width)) |
---|
[1118] | 2089 | s._add_history("bin", varlist) |
---|
[1589] | 2090 | if insitu: |
---|
| 2091 | self._assign(s) |
---|
| 2092 | else: |
---|
| 2093 | return s |
---|
[513] | 2094 | |
---|
[1862] | 2095 | @asaplog_post_dec |
---|
[513] | 2096 | def resample(self, width=5, method='cubic', insitu=None): |
---|
[1846] | 2097 | """\ |
---|
[1348] | 2098 | Return a scan where all spectra have been binned up. |
---|
[1573] | 2099 | |
---|
[1348] | 2100 | Parameters: |
---|
[1846] | 2101 | |
---|
[513] | 2102 | width: The bin width (default=5) in pixels |
---|
[1855] | 2103 | |
---|
[513] | 2104 | method: Interpolation method when correcting from a table. |
---|
| 2105 | Values are "nearest", "linear", "cubic" (default) |
---|
| 2106 | and "spline" |
---|
[1855] | 2107 | |
---|
[513] | 2108 | insitu: if False a new scantable is returned. |
---|
| 2109 | Otherwise, the scaling is done in-situ |
---|
| 2110 | The default is taken from .asaprc (False) |
---|
[1846] | 2111 | |
---|
[513] | 2112 | """ |
---|
[2349] | 2113 | if insitu is None: |
---|
| 2114 | insitu = rcParams['insitu'] |
---|
[876] | 2115 | self._math._setinsitu(insitu) |
---|
[513] | 2116 | varlist = vars() |
---|
[876] | 2117 | s = scantable(self._math._resample(self, method, width)) |
---|
[1118] | 2118 | s._add_history("resample", varlist) |
---|
[2349] | 2119 | if insitu: |
---|
| 2120 | self._assign(s) |
---|
| 2121 | else: |
---|
| 2122 | return s |
---|
[513] | 2123 | |
---|
[1862] | 2124 | @asaplog_post_dec |
---|
[946] | 2125 | def average_pol(self, mask=None, weight='none'): |
---|
[1846] | 2126 | """\ |
---|
[946] | 2127 | Average the Polarisations together. |
---|
[1846] | 2128 | |
---|
[946] | 2129 | Parameters: |
---|
[1846] | 2130 | |
---|
[946] | 2131 | mask: An optional mask defining the region, where the |
---|
| 2132 | averaging will be applied. The output will have all |
---|
| 2133 | specified points masked. |
---|
[1855] | 2134 | |
---|
[946] | 2135 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 2136 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 2137 | |
---|
[946] | 2138 | """ |
---|
| 2139 | varlist = vars() |
---|
[1593] | 2140 | mask = mask or () |
---|
[1010] | 2141 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
[1118] | 2142 | s._add_history("average_pol", varlist) |
---|
[992] | 2143 | return s |
---|
[513] | 2144 | |
---|
[1862] | 2145 | @asaplog_post_dec |
---|
[1145] | 2146 | def average_beam(self, mask=None, weight='none'): |
---|
[1846] | 2147 | """\ |
---|
[1145] | 2148 | Average the Beams together. |
---|
[1846] | 2149 | |
---|
[1145] | 2150 | Parameters: |
---|
| 2151 | mask: An optional mask defining the region, where the |
---|
| 2152 | averaging will be applied. The output will have all |
---|
| 2153 | specified points masked. |
---|
[1855] | 2154 | |
---|
[1145] | 2155 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
| 2156 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
[1846] | 2157 | |
---|
[1145] | 2158 | """ |
---|
| 2159 | varlist = vars() |
---|
[1593] | 2160 | mask = mask or () |
---|
[1145] | 2161 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
| 2162 | s._add_history("average_beam", varlist) |
---|
| 2163 | return s |
---|
| 2164 | |
---|
[1586] | 2165 | def parallactify(self, pflag): |
---|
[1846] | 2166 | """\ |
---|
[1843] | 2167 | Set a flag to indicate whether this data should be treated as having |
---|
[1617] | 2168 | been 'parallactified' (total phase == 0.0) |
---|
[1846] | 2169 | |
---|
[1617] | 2170 | Parameters: |
---|
[1855] | 2171 | |
---|
[1843] | 2172 | pflag: Bool indicating whether to turn this on (True) or |
---|
[1617] | 2173 | off (False) |
---|
[1846] | 2174 | |
---|
[1617] | 2175 | """ |
---|
[1586] | 2176 | varlist = vars() |
---|
| 2177 | self._parallactify(pflag) |
---|
| 2178 | self._add_history("parallactify", varlist) |
---|
| 2179 | |
---|
[1862] | 2180 | @asaplog_post_dec |
---|
[992] | 2181 | def convert_pol(self, poltype=None): |
---|
[1846] | 2182 | """\ |
---|
[992] | 2183 | Convert the data to a different polarisation type. |
---|
[1565] | 2184 | Note that you will need cross-polarisation terms for most conversions. |
---|
[1846] | 2185 | |
---|
[992] | 2186 | Parameters: |
---|
[1855] | 2187 | |
---|
[992] | 2188 | poltype: The new polarisation type. Valid types are: |
---|
[1565] | 2189 | "linear", "circular", "stokes" and "linpol" |
---|
[1846] | 2190 | |
---|
[992] | 2191 | """ |
---|
| 2192 | varlist = vars() |
---|
[1859] | 2193 | s = scantable(self._math._convertpol(self, poltype)) |
---|
[1118] | 2194 | s._add_history("convert_pol", varlist) |
---|
[992] | 2195 | return s |
---|
| 2196 | |
---|
[1862] | 2197 | @asaplog_post_dec |
---|
[2269] | 2198 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, |
---|
| 2199 | insitu=None): |
---|
[1846] | 2200 | """\ |
---|
[513] | 2201 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
[1846] | 2202 | |
---|
[513] | 2203 | Parameters: |
---|
[1846] | 2204 | |
---|
[513] | 2205 | kernel: The type of smoothing kernel. Select from |
---|
[1574] | 2206 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
| 2207 | or 'poly' |
---|
[1855] | 2208 | |
---|
[513] | 2209 | width: The width of the kernel in pixels. For hanning this is |
---|
| 2210 | ignored otherwise it defauls to 5 pixels. |
---|
| 2211 | For 'gaussian' it is the Full Width Half |
---|
| 2212 | Maximum. For 'boxcar' it is the full width. |
---|
[1574] | 2213 | For 'rmedian' and 'poly' it is the half width. |
---|
[1855] | 2214 | |
---|
[1574] | 2215 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
| 2216 | specify the order of the polnomial. Ignored by all other |
---|
| 2217 | kernels. |
---|
[1855] | 2218 | |
---|
[1819] | 2219 | plot: plot the original and the smoothed spectra. |
---|
| 2220 | In this each indivual fit has to be approved, by |
---|
| 2221 | typing 'y' or 'n' |
---|
[1855] | 2222 | |
---|
[513] | 2223 | insitu: if False a new scantable is returned. |
---|
| 2224 | Otherwise, the scaling is done in-situ |
---|
| 2225 | The default is taken from .asaprc (False) |
---|
[1846] | 2226 | |
---|
[513] | 2227 | """ |
---|
| 2228 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 2229 | self._math._setinsitu(insitu) |
---|
[513] | 2230 | varlist = vars() |
---|
[1819] | 2231 | |
---|
| 2232 | if plot: orgscan = self.copy() |
---|
| 2233 | |
---|
[1574] | 2234 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
[876] | 2235 | s._add_history("smooth", varlist) |
---|
[1819] | 2236 | |
---|
| 2237 | if plot: |
---|
[2150] | 2238 | from asap.asapplotter import new_asaplot |
---|
| 2239 | theplot = new_asaplot(rcParams['plotter.gui']) |
---|
| 2240 | theplot.set_panels() |
---|
[1819] | 2241 | ylab=s._get_ordinate_label() |
---|
[2150] | 2242 | #theplot.palette(0,["#777777","red"]) |
---|
[1819] | 2243 | for r in xrange(s.nrow()): |
---|
| 2244 | xsm=s._getabcissa(r) |
---|
| 2245 | ysm=s._getspectrum(r) |
---|
| 2246 | xorg=orgscan._getabcissa(r) |
---|
| 2247 | yorg=orgscan._getspectrum(r) |
---|
[2150] | 2248 | theplot.clear() |
---|
| 2249 | theplot.hold() |
---|
| 2250 | theplot.set_axes('ylabel',ylab) |
---|
| 2251 | theplot.set_axes('xlabel',s._getabcissalabel(r)) |
---|
| 2252 | theplot.set_axes('title',s._getsourcename(r)) |
---|
| 2253 | theplot.set_line(label='Original',color="#777777") |
---|
| 2254 | theplot.plot(xorg,yorg) |
---|
| 2255 | theplot.set_line(label='Smoothed',color="red") |
---|
| 2256 | theplot.plot(xsm,ysm) |
---|
[1819] | 2257 | ### Ugly part for legend |
---|
| 2258 | for i in [0,1]: |
---|
[2349] | 2259 | theplot.subplots[0]['lines'].append( |
---|
| 2260 | [theplot.subplots[0]['axes'].lines[i]] |
---|
| 2261 | ) |
---|
[2150] | 2262 | theplot.release() |
---|
[1819] | 2263 | ### Ugly part for legend |
---|
[2150] | 2264 | theplot.subplots[0]['lines']=[] |
---|
[1819] | 2265 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
| 2266 | if res.upper() == 'N': |
---|
| 2267 | s._setspectrum(yorg, r) |
---|
[2150] | 2268 | theplot.quit() |
---|
| 2269 | del theplot |
---|
[1819] | 2270 | del orgscan |
---|
| 2271 | |
---|
[876] | 2272 | if insitu: self._assign(s) |
---|
| 2273 | else: return s |
---|
[513] | 2274 | |
---|
[2186] | 2275 | @asaplog_post_dec |
---|
| 2276 | def _parse_wn(self, wn): |
---|
| 2277 | if isinstance(wn, list) or isinstance(wn, tuple): |
---|
| 2278 | return wn |
---|
| 2279 | elif isinstance(wn, int): |
---|
| 2280 | return [ wn ] |
---|
| 2281 | elif isinstance(wn, str): |
---|
[2277] | 2282 | if '-' in wn: # case 'a-b' : return [a,a+1,...,b-1,b] |
---|
[2186] | 2283 | val = wn.split('-') |
---|
| 2284 | val = [int(val[0]), int(val[1])] |
---|
| 2285 | val.sort() |
---|
| 2286 | res = [i for i in xrange(val[0], val[1]+1)] |
---|
[2277] | 2287 | elif wn[:2] == '<=' or wn[:2] == '=<': # cases '<=a','=<a' : return [0,1,...,a-1,a] |
---|
[2186] | 2288 | val = int(wn[2:])+1 |
---|
| 2289 | res = [i for i in xrange(val)] |
---|
[2277] | 2290 | elif wn[-2:] == '>=' or wn[-2:] == '=>': # cases 'a>=','a=>' : return [0,1,...,a-1,a] |
---|
[2186] | 2291 | val = int(wn[:-2])+1 |
---|
| 2292 | res = [i for i in xrange(val)] |
---|
[2277] | 2293 | elif wn[0] == '<': # case '<a' : return [0,1,...,a-2,a-1] |
---|
[2186] | 2294 | val = int(wn[1:]) |
---|
| 2295 | res = [i for i in xrange(val)] |
---|
[2277] | 2296 | elif wn[-1] == '>': # case 'a>' : return [0,1,...,a-2,a-1] |
---|
[2186] | 2297 | val = int(wn[:-1]) |
---|
| 2298 | res = [i for i in xrange(val)] |
---|
[2277] | 2299 | elif wn[:2] == '>=' or wn[:2] == '=>': # cases '>=a','=>a' : return [a,a+1,...,a_nyq] |
---|
[2186] | 2300 | val = int(wn[2:]) |
---|
| 2301 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
[2277] | 2302 | elif wn[-2:] == '<=' or wn[-2:] == '=<': # cases 'a<=','a=<' : return [a,a+1,...,a_nyq] |
---|
[2186] | 2303 | val = int(wn[:-2]) |
---|
| 2304 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
[2277] | 2305 | elif wn[0] == '>': # case '>a' : return [a+1,a+2,...,a_nyq] |
---|
[2186] | 2306 | val = int(wn[1:])+1 |
---|
| 2307 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
[2277] | 2308 | elif wn[-1] == '<': # case 'a<' : return [a+1,a+2,...,a_nyq] |
---|
[2186] | 2309 | val = int(wn[:-1])+1 |
---|
| 2310 | res = [i for i in xrange(val, self.nchan()/2+1)] |
---|
[2012] | 2311 | |
---|
[2186] | 2312 | return res |
---|
| 2313 | else: |
---|
| 2314 | msg = 'wrong value given for addwn/rejwn' |
---|
| 2315 | raise RuntimeError(msg) |
---|
| 2316 | |
---|
| 2317 | |
---|
[1862] | 2318 | @asaplog_post_dec |
---|
[2277] | 2319 | def sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, |
---|
[2269] | 2320 | fftmethod=None, fftthresh=None, |
---|
| 2321 | addwn=None, rejwn=None, clipthresh=None, |
---|
| 2322 | clipniter=None, plot=None, |
---|
| 2323 | getresidual=None, showprogress=None, |
---|
| 2324 | minnrow=None, outlog=None, blfile=None): |
---|
[2047] | 2325 | """\ |
---|
[2349] | 2326 | Return a scan which has been baselined (all rows) with sinusoidal |
---|
| 2327 | functions. |
---|
| 2328 | |
---|
[2047] | 2329 | Parameters: |
---|
[2186] | 2330 | insitu: if False a new scantable is returned. |
---|
[2081] | 2331 | Otherwise, the scaling is done in-situ |
---|
| 2332 | The default is taken from .asaprc (False) |
---|
[2186] | 2333 | mask: an optional mask |
---|
| 2334 | applyfft: if True use some method, such as FFT, to find |
---|
| 2335 | strongest sinusoidal components in the wavenumber |
---|
| 2336 | domain to be used for baseline fitting. |
---|
| 2337 | default is True. |
---|
| 2338 | fftmethod: method to find the strong sinusoidal components. |
---|
| 2339 | now only 'fft' is available and it is the default. |
---|
| 2340 | fftthresh: the threshold to select wave numbers to be used for |
---|
| 2341 | fitting from the distribution of amplitudes in the |
---|
| 2342 | wavenumber domain. |
---|
| 2343 | both float and string values accepted. |
---|
| 2344 | given a float value, the unit is set to sigma. |
---|
| 2345 | for string values, allowed formats include: |
---|
[2349] | 2346 | 'xsigma' or 'x' (= x-sigma level. e.g., |
---|
| 2347 | '3sigma'), or |
---|
[2186] | 2348 | 'topx' (= the x strongest ones, e.g. 'top5'). |
---|
| 2349 | default is 3.0 (unit: sigma). |
---|
| 2350 | addwn: the additional wave numbers to be used for fitting. |
---|
| 2351 | list or integer value is accepted to specify every |
---|
| 2352 | wave numbers. also string value can be used in case |
---|
| 2353 | you need to specify wave numbers in a certain range, |
---|
| 2354 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b), |
---|
| 2355 | '<a' (= 0,1,...,a-2,a-1), |
---|
| 2356 | '>=a' (= a, a+1, ... up to the maximum wave |
---|
| 2357 | number corresponding to the Nyquist |
---|
| 2358 | frequency for the case of FFT). |
---|
| 2359 | default is []. |
---|
| 2360 | rejwn: the wave numbers NOT to be used for fitting. |
---|
| 2361 | can be set just as addwn but has higher priority: |
---|
| 2362 | wave numbers which are specified both in addwn |
---|
| 2363 | and rejwn will NOT be used. default is []. |
---|
[2081] | 2364 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2349] | 2365 | clipniter: maximum number of iteration of 'clipthresh'-sigma |
---|
| 2366 | clipping (default is 0) |
---|
[2081] | 2367 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2368 | plot the fit and the residual. In this each |
---|
| 2369 | indivual fit has to be approved, by typing 'y' |
---|
| 2370 | or 'n' |
---|
| 2371 | getresidual: if False, returns best-fit values instead of |
---|
| 2372 | residual. (default is True) |
---|
[2189] | 2373 | showprogress: show progress status for large data. |
---|
| 2374 | default is True. |
---|
| 2375 | minnrow: minimum number of input spectra to show. |
---|
| 2376 | default is 1000. |
---|
[2081] | 2377 | outlog: Output the coefficients of the best-fit |
---|
| 2378 | function to logger (default is False) |
---|
| 2379 | blfile: Name of a text file in which the best-fit |
---|
| 2380 | parameter values to be written |
---|
[2186] | 2381 | (default is '': no file/logger output) |
---|
[2047] | 2382 | |
---|
| 2383 | Example: |
---|
[2349] | 2384 | # return a scan baselined by a combination of sinusoidal curves |
---|
| 2385 | # having wave numbers in spectral window up to 10, |
---|
[2047] | 2386 | # also with 3-sigma clipping, iteration up to 4 times |
---|
[2186] | 2387 | bscan = scan.sinusoid_baseline(addwn='<=10',clipthresh=3.0,clipniter=4) |
---|
[2081] | 2388 | |
---|
| 2389 | Note: |
---|
| 2390 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2391 | based on specunit of 'channel'. |
---|
[2047] | 2392 | """ |
---|
| 2393 | |
---|
[2186] | 2394 | try: |
---|
| 2395 | varlist = vars() |
---|
[2047] | 2396 | |
---|
[2186] | 2397 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2398 | if insitu: |
---|
| 2399 | workscan = self |
---|
| 2400 | else: |
---|
| 2401 | workscan = self.copy() |
---|
| 2402 | |
---|
[2277] | 2403 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
[2186] | 2404 | if applyfft is None: applyfft = True |
---|
| 2405 | if fftmethod is None: fftmethod = 'fft' |
---|
| 2406 | if fftthresh is None: fftthresh = 3.0 |
---|
| 2407 | if addwn is None: addwn = [] |
---|
| 2408 | if rejwn is None: rejwn = [] |
---|
| 2409 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2410 | if clipniter is None: clipniter = 0 |
---|
| 2411 | if plot is None: plot = False |
---|
| 2412 | if getresidual is None: getresidual = True |
---|
[2189] | 2413 | if showprogress is None: showprogress = True |
---|
| 2414 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2415 | if outlog is None: outlog = False |
---|
| 2416 | if blfile is None: blfile = '' |
---|
[2047] | 2417 | |
---|
[2081] | 2418 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
[2349] | 2419 | workscan._sinusoid_baseline(mask, applyfft, fftmethod.lower(), |
---|
| 2420 | str(fftthresh).lower(), |
---|
| 2421 | workscan._parse_wn(addwn), |
---|
| 2422 | workscan._parse_wn(rejwn), clipthresh, |
---|
| 2423 | clipniter, getresidual, |
---|
| 2424 | pack_progress_params(showprogress, |
---|
| 2425 | minnrow), outlog, |
---|
| 2426 | blfile) |
---|
[2186] | 2427 | workscan._add_history('sinusoid_baseline', varlist) |
---|
[2047] | 2428 | |
---|
| 2429 | if insitu: |
---|
| 2430 | self._assign(workscan) |
---|
| 2431 | else: |
---|
| 2432 | return workscan |
---|
| 2433 | |
---|
| 2434 | except RuntimeError, e: |
---|
[2186] | 2435 | raise_fitting_failure_exception(e) |
---|
[2047] | 2436 | |
---|
| 2437 | |
---|
[2186] | 2438 | @asaplog_post_dec |
---|
[2349] | 2439 | def auto_sinusoid_baseline(self, insitu=None, mask=None, applyfft=None, |
---|
| 2440 | fftmethod=None, fftthresh=None, |
---|
| 2441 | addwn=None, rejwn=None, clipthresh=None, |
---|
| 2442 | clipniter=None, edge=None, threshold=None, |
---|
| 2443 | chan_avg_limit=None, plot=None, |
---|
| 2444 | getresidual=None, showprogress=None, |
---|
| 2445 | minnrow=None, outlog=None, blfile=None): |
---|
[2047] | 2446 | """\ |
---|
[2349] | 2447 | Return a scan which has been baselined (all rows) with sinusoidal |
---|
| 2448 | functions. |
---|
[2047] | 2449 | Spectral lines are detected first using linefinder and masked out |
---|
| 2450 | to avoid them affecting the baseline solution. |
---|
| 2451 | |
---|
| 2452 | Parameters: |
---|
[2189] | 2453 | insitu: if False a new scantable is returned. |
---|
| 2454 | Otherwise, the scaling is done in-situ |
---|
| 2455 | The default is taken from .asaprc (False) |
---|
| 2456 | mask: an optional mask retreived from scantable |
---|
| 2457 | applyfft: if True use some method, such as FFT, to find |
---|
| 2458 | strongest sinusoidal components in the wavenumber |
---|
| 2459 | domain to be used for baseline fitting. |
---|
| 2460 | default is True. |
---|
| 2461 | fftmethod: method to find the strong sinusoidal components. |
---|
| 2462 | now only 'fft' is available and it is the default. |
---|
| 2463 | fftthresh: the threshold to select wave numbers to be used for |
---|
| 2464 | fitting from the distribution of amplitudes in the |
---|
| 2465 | wavenumber domain. |
---|
| 2466 | both float and string values accepted. |
---|
| 2467 | given a float value, the unit is set to sigma. |
---|
| 2468 | for string values, allowed formats include: |
---|
[2349] | 2469 | 'xsigma' or 'x' (= x-sigma level. e.g., |
---|
| 2470 | '3sigma'), or |
---|
[2189] | 2471 | 'topx' (= the x strongest ones, e.g. 'top5'). |
---|
| 2472 | default is 3.0 (unit: sigma). |
---|
| 2473 | addwn: the additional wave numbers to be used for fitting. |
---|
| 2474 | list or integer value is accepted to specify every |
---|
| 2475 | wave numbers. also string value can be used in case |
---|
| 2476 | you need to specify wave numbers in a certain range, |
---|
| 2477 | e.g., 'a-b' (= a, a+1, a+2, ..., b-1, b), |
---|
| 2478 | '<a' (= 0,1,...,a-2,a-1), |
---|
| 2479 | '>=a' (= a, a+1, ... up to the maximum wave |
---|
| 2480 | number corresponding to the Nyquist |
---|
| 2481 | frequency for the case of FFT). |
---|
| 2482 | default is []. |
---|
| 2483 | rejwn: the wave numbers NOT to be used for fitting. |
---|
| 2484 | can be set just as addwn but has higher priority: |
---|
| 2485 | wave numbers which are specified both in addwn |
---|
| 2486 | and rejwn will NOT be used. default is []. |
---|
| 2487 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2349] | 2488 | clipniter: maximum number of iteration of 'clipthresh'-sigma |
---|
| 2489 | clipping (default is 0) |
---|
[2189] | 2490 | edge: an optional number of channel to drop at |
---|
| 2491 | the edge of spectrum. If only one value is |
---|
| 2492 | specified, the same number will be dropped |
---|
| 2493 | from both sides of the spectrum. Default |
---|
| 2494 | is to keep all channels. Nested tuples |
---|
| 2495 | represent individual edge selection for |
---|
| 2496 | different IFs (a number of spectral channels |
---|
| 2497 | can be different) |
---|
| 2498 | threshold: the threshold used by line finder. It is |
---|
| 2499 | better to keep it large as only strong lines |
---|
| 2500 | affect the baseline solution. |
---|
| 2501 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2502 | channels to average during the search of |
---|
| 2503 | weak and broad lines. The default is no |
---|
| 2504 | averaging (and no search for weak lines). |
---|
| 2505 | If such lines can affect the fitted baseline |
---|
| 2506 | (e.g. a high order polynomial is fitted), |
---|
| 2507 | increase this parameter (usually values up |
---|
| 2508 | to 8 are reasonable). Most users of this |
---|
| 2509 | method should find the default value sufficient. |
---|
| 2510 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2511 | plot the fit and the residual. In this each |
---|
| 2512 | indivual fit has to be approved, by typing 'y' |
---|
| 2513 | or 'n' |
---|
| 2514 | getresidual: if False, returns best-fit values instead of |
---|
| 2515 | residual. (default is True) |
---|
| 2516 | showprogress: show progress status for large data. |
---|
| 2517 | default is True. |
---|
| 2518 | minnrow: minimum number of input spectra to show. |
---|
| 2519 | default is 1000. |
---|
| 2520 | outlog: Output the coefficients of the best-fit |
---|
| 2521 | function to logger (default is False) |
---|
| 2522 | blfile: Name of a text file in which the best-fit |
---|
| 2523 | parameter values to be written |
---|
| 2524 | (default is "": no file/logger output) |
---|
[2047] | 2525 | |
---|
| 2526 | Example: |
---|
[2186] | 2527 | bscan = scan.auto_sinusoid_baseline(addwn='<=10', insitu=False) |
---|
[2081] | 2528 | |
---|
| 2529 | Note: |
---|
| 2530 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2531 | based on specunit of 'channel'. |
---|
[2047] | 2532 | """ |
---|
| 2533 | |
---|
[2186] | 2534 | try: |
---|
| 2535 | varlist = vars() |
---|
[2047] | 2536 | |
---|
[2186] | 2537 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2538 | if insitu: |
---|
| 2539 | workscan = self |
---|
[2047] | 2540 | else: |
---|
[2186] | 2541 | workscan = self.copy() |
---|
| 2542 | |
---|
[2277] | 2543 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
[2186] | 2544 | if applyfft is None: applyfft = True |
---|
| 2545 | if fftmethod is None: fftmethod = 'fft' |
---|
| 2546 | if fftthresh is None: fftthresh = 3.0 |
---|
| 2547 | if addwn is None: addwn = [] |
---|
| 2548 | if rejwn is None: rejwn = [] |
---|
| 2549 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2550 | if clipniter is None: clipniter = 0 |
---|
| 2551 | if edge is None: edge = (0,0) |
---|
| 2552 | if threshold is None: threshold = 3 |
---|
| 2553 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2554 | if plot is None: plot = False |
---|
| 2555 | if getresidual is None: getresidual = True |
---|
[2189] | 2556 | if showprogress is None: showprogress = True |
---|
| 2557 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2558 | if outlog is None: outlog = False |
---|
| 2559 | if blfile is None: blfile = '' |
---|
[2047] | 2560 | |
---|
[2277] | 2561 | #CURRENTLY, PLOT=true is UNAVAILABLE UNTIL sinusoidal fitting is implemented as a fitter method. |
---|
[2349] | 2562 | workscan._auto_sinusoid_baseline(mask, applyfft, |
---|
| 2563 | fftmethod.lower(), |
---|
| 2564 | str(fftthresh).lower(), |
---|
| 2565 | workscan._parse_wn(addwn), |
---|
| 2566 | workscan._parse_wn(rejwn), |
---|
| 2567 | clipthresh, clipniter, |
---|
| 2568 | normalise_edge_param(edge), |
---|
| 2569 | threshold, chan_avg_limit, |
---|
| 2570 | getresidual, |
---|
| 2571 | pack_progress_params(showprogress, |
---|
| 2572 | minnrow), |
---|
| 2573 | outlog, blfile) |
---|
[2047] | 2574 | workscan._add_history("auto_sinusoid_baseline", varlist) |
---|
| 2575 | |
---|
| 2576 | if insitu: |
---|
| 2577 | self._assign(workscan) |
---|
| 2578 | else: |
---|
| 2579 | return workscan |
---|
| 2580 | |
---|
| 2581 | except RuntimeError, e: |
---|
[2186] | 2582 | raise_fitting_failure_exception(e) |
---|
[2047] | 2583 | |
---|
| 2584 | @asaplog_post_dec |
---|
[2349] | 2585 | def cspline_baseline(self, insitu=None, mask=None, npiece=None, |
---|
| 2586 | clipthresh=None, clipniter=None, plot=None, |
---|
| 2587 | getresidual=None, showprogress=None, minnrow=None, |
---|
| 2588 | outlog=None, blfile=None): |
---|
[1846] | 2589 | """\ |
---|
[2349] | 2590 | Return a scan which has been baselined (all rows) by cubic spline |
---|
| 2591 | function (piecewise cubic polynomial). |
---|
| 2592 | |
---|
[513] | 2593 | Parameters: |
---|
[2189] | 2594 | insitu: If False a new scantable is returned. |
---|
| 2595 | Otherwise, the scaling is done in-situ |
---|
| 2596 | The default is taken from .asaprc (False) |
---|
| 2597 | mask: An optional mask |
---|
| 2598 | npiece: Number of pieces. (default is 2) |
---|
| 2599 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2349] | 2600 | clipniter: maximum number of iteration of 'clipthresh'-sigma |
---|
| 2601 | clipping (default is 0) |
---|
[2189] | 2602 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2603 | plot the fit and the residual. In this each |
---|
| 2604 | indivual fit has to be approved, by typing 'y' |
---|
| 2605 | or 'n' |
---|
| 2606 | getresidual: if False, returns best-fit values instead of |
---|
| 2607 | residual. (default is True) |
---|
| 2608 | showprogress: show progress status for large data. |
---|
| 2609 | default is True. |
---|
| 2610 | minnrow: minimum number of input spectra to show. |
---|
| 2611 | default is 1000. |
---|
| 2612 | outlog: Output the coefficients of the best-fit |
---|
| 2613 | function to logger (default is False) |
---|
| 2614 | blfile: Name of a text file in which the best-fit |
---|
| 2615 | parameter values to be written |
---|
| 2616 | (default is "": no file/logger output) |
---|
[1846] | 2617 | |
---|
[2012] | 2618 | Example: |
---|
[2349] | 2619 | # return a scan baselined by a cubic spline consisting of 2 pieces |
---|
| 2620 | # (i.e., 1 internal knot), |
---|
[2012] | 2621 | # also with 3-sigma clipping, iteration up to 4 times |
---|
| 2622 | bscan = scan.cspline_baseline(npiece=2,clipthresh=3.0,clipniter=4) |
---|
[2081] | 2623 | |
---|
| 2624 | Note: |
---|
| 2625 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2626 | based on specunit of 'channel'. |
---|
[2012] | 2627 | """ |
---|
| 2628 | |
---|
[2186] | 2629 | try: |
---|
| 2630 | varlist = vars() |
---|
| 2631 | |
---|
| 2632 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2633 | if insitu: |
---|
| 2634 | workscan = self |
---|
| 2635 | else: |
---|
| 2636 | workscan = self.copy() |
---|
[1855] | 2637 | |
---|
[2277] | 2638 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
[2189] | 2639 | if npiece is None: npiece = 2 |
---|
| 2640 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2641 | if clipniter is None: clipniter = 0 |
---|
| 2642 | if plot is None: plot = False |
---|
| 2643 | if getresidual is None: getresidual = True |
---|
| 2644 | if showprogress is None: showprogress = True |
---|
| 2645 | if minnrow is None: minnrow = 1000 |
---|
| 2646 | if outlog is None: outlog = False |
---|
| 2647 | if blfile is None: blfile = '' |
---|
[1855] | 2648 | |
---|
[2012] | 2649 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
[2349] | 2650 | workscan._cspline_baseline(mask, npiece, clipthresh, clipniter, |
---|
| 2651 | getresidual, |
---|
| 2652 | pack_progress_params(showprogress, |
---|
| 2653 | minnrow), outlog, |
---|
| 2654 | blfile) |
---|
[2012] | 2655 | workscan._add_history("cspline_baseline", varlist) |
---|
| 2656 | |
---|
| 2657 | if insitu: |
---|
| 2658 | self._assign(workscan) |
---|
| 2659 | else: |
---|
| 2660 | return workscan |
---|
| 2661 | |
---|
| 2662 | except RuntimeError, e: |
---|
[2186] | 2663 | raise_fitting_failure_exception(e) |
---|
[1855] | 2664 | |
---|
[2186] | 2665 | @asaplog_post_dec |
---|
[2349] | 2666 | def auto_cspline_baseline(self, insitu=None, mask=None, npiece=None, |
---|
| 2667 | clipthresh=None, clipniter=None, |
---|
| 2668 | edge=None, threshold=None, chan_avg_limit=None, |
---|
| 2669 | getresidual=None, plot=None, |
---|
| 2670 | showprogress=None, minnrow=None, outlog=None, |
---|
| 2671 | blfile=None): |
---|
[2012] | 2672 | """\ |
---|
| 2673 | Return a scan which has been baselined (all rows) by cubic spline |
---|
| 2674 | function (piecewise cubic polynomial). |
---|
| 2675 | Spectral lines are detected first using linefinder and masked out |
---|
| 2676 | to avoid them affecting the baseline solution. |
---|
| 2677 | |
---|
| 2678 | Parameters: |
---|
[2189] | 2679 | insitu: if False a new scantable is returned. |
---|
| 2680 | Otherwise, the scaling is done in-situ |
---|
| 2681 | The default is taken from .asaprc (False) |
---|
| 2682 | mask: an optional mask retreived from scantable |
---|
| 2683 | npiece: Number of pieces. (default is 2) |
---|
| 2684 | clipthresh: Clipping threshold. (default is 3.0, unit: sigma) |
---|
[2349] | 2685 | clipniter: maximum number of iteration of 'clipthresh'-sigma |
---|
| 2686 | clipping (default is 0) |
---|
[2189] | 2687 | edge: an optional number of channel to drop at |
---|
| 2688 | the edge of spectrum. If only one value is |
---|
| 2689 | specified, the same number will be dropped |
---|
| 2690 | from both sides of the spectrum. Default |
---|
| 2691 | is to keep all channels. Nested tuples |
---|
| 2692 | represent individual edge selection for |
---|
| 2693 | different IFs (a number of spectral channels |
---|
| 2694 | can be different) |
---|
| 2695 | threshold: the threshold used by line finder. It is |
---|
| 2696 | better to keep it large as only strong lines |
---|
| 2697 | affect the baseline solution. |
---|
| 2698 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2699 | channels to average during the search of |
---|
| 2700 | weak and broad lines. The default is no |
---|
| 2701 | averaging (and no search for weak lines). |
---|
| 2702 | If such lines can affect the fitted baseline |
---|
| 2703 | (e.g. a high order polynomial is fitted), |
---|
| 2704 | increase this parameter (usually values up |
---|
| 2705 | to 8 are reasonable). Most users of this |
---|
| 2706 | method should find the default value sufficient. |
---|
| 2707 | plot: *** CURRENTLY UNAVAILABLE, ALWAYS FALSE *** |
---|
| 2708 | plot the fit and the residual. In this each |
---|
| 2709 | indivual fit has to be approved, by typing 'y' |
---|
| 2710 | or 'n' |
---|
| 2711 | getresidual: if False, returns best-fit values instead of |
---|
| 2712 | residual. (default is True) |
---|
| 2713 | showprogress: show progress status for large data. |
---|
| 2714 | default is True. |
---|
| 2715 | minnrow: minimum number of input spectra to show. |
---|
| 2716 | default is 1000. |
---|
| 2717 | outlog: Output the coefficients of the best-fit |
---|
| 2718 | function to logger (default is False) |
---|
| 2719 | blfile: Name of a text file in which the best-fit |
---|
| 2720 | parameter values to be written |
---|
| 2721 | (default is "": no file/logger output) |
---|
[1846] | 2722 | |
---|
[1907] | 2723 | Example: |
---|
[2012] | 2724 | bscan = scan.auto_cspline_baseline(npiece=3, insitu=False) |
---|
[2081] | 2725 | |
---|
| 2726 | Note: |
---|
| 2727 | The best-fit parameter values output in logger and/or blfile are now |
---|
| 2728 | based on specunit of 'channel'. |
---|
[2012] | 2729 | """ |
---|
[1846] | 2730 | |
---|
[2186] | 2731 | try: |
---|
| 2732 | varlist = vars() |
---|
[2012] | 2733 | |
---|
[2186] | 2734 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 2735 | if insitu: |
---|
| 2736 | workscan = self |
---|
[1391] | 2737 | else: |
---|
[2186] | 2738 | workscan = self.copy() |
---|
| 2739 | |
---|
[2277] | 2740 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
[2186] | 2741 | if npiece is None: npiece = 2 |
---|
| 2742 | if clipthresh is None: clipthresh = 3.0 |
---|
| 2743 | if clipniter is None: clipniter = 0 |
---|
| 2744 | if edge is None: edge = (0, 0) |
---|
| 2745 | if threshold is None: threshold = 3 |
---|
| 2746 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2747 | if plot is None: plot = False |
---|
| 2748 | if getresidual is None: getresidual = True |
---|
[2189] | 2749 | if showprogress is None: showprogress = True |
---|
| 2750 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2751 | if outlog is None: outlog = False |
---|
| 2752 | if blfile is None: blfile = '' |
---|
[1819] | 2753 | |
---|
[2277] | 2754 | #CURRENTLY, PLOT=true UNAVAILABLE UNTIL cubic spline fitting is implemented as a fitter method. |
---|
[2269] | 2755 | workscan._auto_cspline_baseline(mask, npiece, clipthresh, |
---|
| 2756 | clipniter, |
---|
| 2757 | normalise_edge_param(edge), |
---|
| 2758 | threshold, |
---|
| 2759 | chan_avg_limit, getresidual, |
---|
| 2760 | pack_progress_params(showprogress, |
---|
| 2761 | minnrow), |
---|
| 2762 | outlog, blfile) |
---|
[2012] | 2763 | workscan._add_history("auto_cspline_baseline", varlist) |
---|
[1907] | 2764 | |
---|
[1856] | 2765 | if insitu: |
---|
| 2766 | self._assign(workscan) |
---|
| 2767 | else: |
---|
| 2768 | return workscan |
---|
[2012] | 2769 | |
---|
| 2770 | except RuntimeError, e: |
---|
[2186] | 2771 | raise_fitting_failure_exception(e) |
---|
[513] | 2772 | |
---|
[1931] | 2773 | @asaplog_post_dec |
---|
[2269] | 2774 | def poly_baseline(self, mask=None, order=None, insitu=None, plot=None, |
---|
| 2775 | getresidual=None, showprogress=None, minnrow=None, |
---|
| 2776 | outlog=None, blfile=None): |
---|
[1907] | 2777 | """\ |
---|
| 2778 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
| 2779 | Parameters: |
---|
[2189] | 2780 | insitu: if False a new scantable is returned. |
---|
| 2781 | Otherwise, the scaling is done in-situ |
---|
| 2782 | The default is taken from .asaprc (False) |
---|
| 2783 | mask: an optional mask |
---|
| 2784 | order: the order of the polynomial (default is 0) |
---|
| 2785 | plot: plot the fit and the residual. In this each |
---|
| 2786 | indivual fit has to be approved, by typing 'y' |
---|
| 2787 | or 'n' |
---|
| 2788 | getresidual: if False, returns best-fit values instead of |
---|
| 2789 | residual. (default is True) |
---|
| 2790 | showprogress: show progress status for large data. |
---|
| 2791 | default is True. |
---|
| 2792 | minnrow: minimum number of input spectra to show. |
---|
| 2793 | default is 1000. |
---|
| 2794 | outlog: Output the coefficients of the best-fit |
---|
| 2795 | function to logger (default is False) |
---|
| 2796 | blfile: Name of a text file in which the best-fit |
---|
| 2797 | parameter values to be written |
---|
| 2798 | (default is "": no file/logger output) |
---|
[2012] | 2799 | |
---|
[1907] | 2800 | Example: |
---|
| 2801 | # return a scan baselined by a third order polynomial, |
---|
| 2802 | # not using a mask |
---|
| 2803 | bscan = scan.poly_baseline(order=3) |
---|
| 2804 | """ |
---|
[1931] | 2805 | |
---|
[2186] | 2806 | try: |
---|
| 2807 | varlist = vars() |
---|
[1931] | 2808 | |
---|
[2269] | 2809 | if insitu is None: |
---|
| 2810 | insitu = rcParams["insitu"] |
---|
[2186] | 2811 | if insitu: |
---|
| 2812 | workscan = self |
---|
| 2813 | else: |
---|
| 2814 | workscan = self.copy() |
---|
[1907] | 2815 | |
---|
[2277] | 2816 | if mask is None: mask = [True for i in \ |
---|
| 2817 | xrange(workscan.nchan())] |
---|
[2189] | 2818 | if order is None: order = 0 |
---|
| 2819 | if plot is None: plot = False |
---|
| 2820 | if getresidual is None: getresidual = True |
---|
| 2821 | if showprogress is None: showprogress = True |
---|
| 2822 | if minnrow is None: minnrow = 1000 |
---|
| 2823 | if outlog is None: outlog = False |
---|
| 2824 | if blfile is None: blfile = "" |
---|
[1907] | 2825 | |
---|
[2012] | 2826 | if plot: |
---|
[2269] | 2827 | outblfile = (blfile != "") and \ |
---|
[2349] | 2828 | os.path.exists(os.path.expanduser( |
---|
| 2829 | os.path.expandvars(blfile)) |
---|
| 2830 | ) |
---|
[2269] | 2831 | if outblfile: |
---|
| 2832 | blf = open(blfile, "a") |
---|
[2012] | 2833 | |
---|
[1907] | 2834 | f = fitter() |
---|
| 2835 | f.set_function(lpoly=order) |
---|
[2186] | 2836 | |
---|
| 2837 | rows = xrange(workscan.nrow()) |
---|
| 2838 | #if len(rows) > 0: workscan._init_blinfo() |
---|
| 2839 | |
---|
[1907] | 2840 | for r in rows: |
---|
| 2841 | f.x = workscan._getabcissa(r) |
---|
| 2842 | f.y = workscan._getspectrum(r) |
---|
| 2843 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
| 2844 | f.data = None |
---|
| 2845 | f.fit() |
---|
| 2846 | |
---|
| 2847 | f.plot(residual=True) |
---|
| 2848 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2849 | if accept_fit.upper() == "N": |
---|
[2012] | 2850 | #workscan._append_blinfo(None, None, None) |
---|
[1907] | 2851 | continue |
---|
[2012] | 2852 | |
---|
| 2853 | blpars = f.get_parameters() |
---|
| 2854 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 2855 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2269] | 2856 | workscan._setspectrum((f.fitter.getresidual() |
---|
| 2857 | if getresidual else f.fitter.getfit()), r) |
---|
[1907] | 2858 | |
---|
[2012] | 2859 | if outblfile: |
---|
| 2860 | rms = workscan.get_rms(f.mask, r) |
---|
[2269] | 2861 | dataout = \ |
---|
| 2862 | workscan.format_blparams_row(blpars["params"], |
---|
| 2863 | blpars["fixed"], |
---|
| 2864 | rms, str(masklist), |
---|
| 2865 | r, True) |
---|
[2012] | 2866 | blf.write(dataout) |
---|
| 2867 | |
---|
[1907] | 2868 | f._p.unmap() |
---|
| 2869 | f._p = None |
---|
[2012] | 2870 | |
---|
[2349] | 2871 | if outblfile: |
---|
| 2872 | blf.close() |
---|
[1907] | 2873 | else: |
---|
[2269] | 2874 | workscan._poly_baseline(mask, order, getresidual, |
---|
| 2875 | pack_progress_params(showprogress, |
---|
| 2876 | minnrow), |
---|
| 2877 | outlog, blfile) |
---|
[1907] | 2878 | |
---|
| 2879 | workscan._add_history("poly_baseline", varlist) |
---|
| 2880 | |
---|
| 2881 | if insitu: |
---|
| 2882 | self._assign(workscan) |
---|
| 2883 | else: |
---|
| 2884 | return workscan |
---|
| 2885 | |
---|
[1919] | 2886 | except RuntimeError, e: |
---|
[2186] | 2887 | raise_fitting_failure_exception(e) |
---|
[1907] | 2888 | |
---|
[2186] | 2889 | @asaplog_post_dec |
---|
[2269] | 2890 | def auto_poly_baseline(self, mask=None, order=None, edge=None, |
---|
| 2891 | threshold=None, chan_avg_limit=None, |
---|
| 2892 | plot=None, insitu=None, |
---|
| 2893 | getresidual=None, showprogress=None, |
---|
| 2894 | minnrow=None, outlog=None, blfile=None): |
---|
[1846] | 2895 | """\ |
---|
[1931] | 2896 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
[880] | 2897 | Spectral lines are detected first using linefinder and masked out |
---|
| 2898 | to avoid them affecting the baseline solution. |
---|
| 2899 | |
---|
| 2900 | Parameters: |
---|
[2189] | 2901 | insitu: if False a new scantable is returned. |
---|
| 2902 | Otherwise, the scaling is done in-situ |
---|
| 2903 | The default is taken from .asaprc (False) |
---|
| 2904 | mask: an optional mask retreived from scantable |
---|
| 2905 | order: the order of the polynomial (default is 0) |
---|
| 2906 | edge: an optional number of channel to drop at |
---|
| 2907 | the edge of spectrum. If only one value is |
---|
| 2908 | specified, the same number will be dropped |
---|
| 2909 | from both sides of the spectrum. Default |
---|
| 2910 | is to keep all channels. Nested tuples |
---|
| 2911 | represent individual edge selection for |
---|
| 2912 | different IFs (a number of spectral channels |
---|
| 2913 | can be different) |
---|
| 2914 | threshold: the threshold used by line finder. It is |
---|
| 2915 | better to keep it large as only strong lines |
---|
| 2916 | affect the baseline solution. |
---|
| 2917 | chan_avg_limit: a maximum number of consequtive spectral |
---|
| 2918 | channels to average during the search of |
---|
| 2919 | weak and broad lines. The default is no |
---|
| 2920 | averaging (and no search for weak lines). |
---|
| 2921 | If such lines can affect the fitted baseline |
---|
| 2922 | (e.g. a high order polynomial is fitted), |
---|
| 2923 | increase this parameter (usually values up |
---|
| 2924 | to 8 are reasonable). Most users of this |
---|
| 2925 | method should find the default value sufficient. |
---|
| 2926 | plot: plot the fit and the residual. In this each |
---|
| 2927 | indivual fit has to be approved, by typing 'y' |
---|
| 2928 | or 'n' |
---|
| 2929 | getresidual: if False, returns best-fit values instead of |
---|
| 2930 | residual. (default is True) |
---|
| 2931 | showprogress: show progress status for large data. |
---|
| 2932 | default is True. |
---|
| 2933 | minnrow: minimum number of input spectra to show. |
---|
| 2934 | default is 1000. |
---|
| 2935 | outlog: Output the coefficients of the best-fit |
---|
| 2936 | function to logger (default is False) |
---|
| 2937 | blfile: Name of a text file in which the best-fit |
---|
| 2938 | parameter values to be written |
---|
| 2939 | (default is "": no file/logger output) |
---|
[1846] | 2940 | |
---|
[2012] | 2941 | Example: |
---|
| 2942 | bscan = scan.auto_poly_baseline(order=7, insitu=False) |
---|
| 2943 | """ |
---|
[880] | 2944 | |
---|
[2186] | 2945 | try: |
---|
| 2946 | varlist = vars() |
---|
[1846] | 2947 | |
---|
[2269] | 2948 | if insitu is None: |
---|
| 2949 | insitu = rcParams['insitu'] |
---|
[2186] | 2950 | if insitu: |
---|
| 2951 | workscan = self |
---|
| 2952 | else: |
---|
| 2953 | workscan = self.copy() |
---|
[1846] | 2954 | |
---|
[2277] | 2955 | if mask is None: mask = [True for i in xrange(workscan.nchan())] |
---|
[2186] | 2956 | if order is None: order = 0 |
---|
| 2957 | if edge is None: edge = (0, 0) |
---|
| 2958 | if threshold is None: threshold = 3 |
---|
| 2959 | if chan_avg_limit is None: chan_avg_limit = 1 |
---|
| 2960 | if plot is None: plot = False |
---|
| 2961 | if getresidual is None: getresidual = True |
---|
[2189] | 2962 | if showprogress is None: showprogress = True |
---|
| 2963 | if minnrow is None: minnrow = 1000 |
---|
[2186] | 2964 | if outlog is None: outlog = False |
---|
| 2965 | if blfile is None: blfile = '' |
---|
[1846] | 2966 | |
---|
[2186] | 2967 | edge = normalise_edge_param(edge) |
---|
[880] | 2968 | |
---|
[2012] | 2969 | if plot: |
---|
[2269] | 2970 | outblfile = (blfile != "") and \ |
---|
| 2971 | os.path.exists(os.path.expanduser(os.path.expandvars(blfile))) |
---|
[2012] | 2972 | if outblfile: blf = open(blfile, "a") |
---|
| 2973 | |
---|
[2186] | 2974 | from asap.asaplinefind import linefinder |
---|
[2012] | 2975 | fl = linefinder() |
---|
[2269] | 2976 | fl.set_options(threshold=threshold, avg_limit=chan_avg_limit) |
---|
[2012] | 2977 | fl.set_scan(workscan) |
---|
[2186] | 2978 | |
---|
[2012] | 2979 | f = fitter() |
---|
| 2980 | f.set_function(lpoly=order) |
---|
[880] | 2981 | |
---|
[2186] | 2982 | rows = xrange(workscan.nrow()) |
---|
| 2983 | #if len(rows) > 0: workscan._init_blinfo() |
---|
| 2984 | |
---|
[2012] | 2985 | for r in rows: |
---|
[2186] | 2986 | idx = 2*workscan.getif(r) |
---|
[2269] | 2987 | fl.find_lines(r, mask_and(mask, workscan._getmask(r)), |
---|
| 2988 | edge[idx:idx+2]) # (CAS-1434) |
---|
[907] | 2989 | |
---|
[2012] | 2990 | f.x = workscan._getabcissa(r) |
---|
| 2991 | f.y = workscan._getspectrum(r) |
---|
| 2992 | f.mask = fl.get_mask() |
---|
| 2993 | f.data = None |
---|
| 2994 | f.fit() |
---|
| 2995 | |
---|
| 2996 | f.plot(residual=True) |
---|
| 2997 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
| 2998 | if accept_fit.upper() == "N": |
---|
| 2999 | #workscan._append_blinfo(None, None, None) |
---|
| 3000 | continue |
---|
| 3001 | |
---|
| 3002 | blpars = f.get_parameters() |
---|
| 3003 | masklist = workscan.get_masklist(f.mask, row=r, silent=True) |
---|
| 3004 | #workscan._append_blinfo(blpars, masklist, f.mask) |
---|
[2349] | 3005 | workscan._setspectrum( |
---|
| 3006 | (f.fitter.getresidual() if getresidual |
---|
| 3007 | else f.fitter.getfit()), r |
---|
| 3008 | ) |
---|
[2012] | 3009 | |
---|
| 3010 | if outblfile: |
---|
| 3011 | rms = workscan.get_rms(f.mask, r) |
---|
[2269] | 3012 | dataout = \ |
---|
| 3013 | workscan.format_blparams_row(blpars["params"], |
---|
| 3014 | blpars["fixed"], |
---|
| 3015 | rms, str(masklist), |
---|
| 3016 | r, True) |
---|
[2012] | 3017 | blf.write(dataout) |
---|
| 3018 | |
---|
| 3019 | f._p.unmap() |
---|
| 3020 | f._p = None |
---|
| 3021 | |
---|
| 3022 | if outblfile: blf.close() |
---|
| 3023 | else: |
---|
[2269] | 3024 | workscan._auto_poly_baseline(mask, order, edge, threshold, |
---|
| 3025 | chan_avg_limit, getresidual, |
---|
| 3026 | pack_progress_params(showprogress, |
---|
| 3027 | minnrow), |
---|
| 3028 | outlog, blfile) |
---|
[2012] | 3029 | |
---|
| 3030 | workscan._add_history("auto_poly_baseline", varlist) |
---|
| 3031 | |
---|
| 3032 | if insitu: |
---|
| 3033 | self._assign(workscan) |
---|
| 3034 | else: |
---|
| 3035 | return workscan |
---|
| 3036 | |
---|
| 3037 | except RuntimeError, e: |
---|
[2186] | 3038 | raise_fitting_failure_exception(e) |
---|
[2012] | 3039 | |
---|
| 3040 | def _init_blinfo(self): |
---|
| 3041 | """\ |
---|
| 3042 | Initialise the following three auxiliary members: |
---|
| 3043 | blpars : parameters of the best-fit baseline, |
---|
| 3044 | masklists : mask data (edge positions of masked channels) and |
---|
| 3045 | actualmask : mask data (in boolean list), |
---|
| 3046 | to keep for use later (including output to logger/text files). |
---|
| 3047 | Used by poly_baseline() and auto_poly_baseline() in case of |
---|
| 3048 | 'plot=True'. |
---|
| 3049 | """ |
---|
| 3050 | self.blpars = [] |
---|
| 3051 | self.masklists = [] |
---|
| 3052 | self.actualmask = [] |
---|
| 3053 | return |
---|
[880] | 3054 | |
---|
[2012] | 3055 | def _append_blinfo(self, data_blpars, data_masklists, data_actualmask): |
---|
| 3056 | """\ |
---|
| 3057 | Append baseline-fitting related info to blpars, masklist and |
---|
| 3058 | actualmask. |
---|
| 3059 | """ |
---|
| 3060 | self.blpars.append(data_blpars) |
---|
| 3061 | self.masklists.append(data_masklists) |
---|
| 3062 | self.actualmask.append(data_actualmask) |
---|
| 3063 | return |
---|
| 3064 | |
---|
[1862] | 3065 | @asaplog_post_dec |
---|
[914] | 3066 | def rotate_linpolphase(self, angle): |
---|
[1846] | 3067 | """\ |
---|
[914] | 3068 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
| 3069 | This is always done in situ in the raw data. So if you call this |
---|
| 3070 | function more than once then each call rotates the phase further. |
---|
[1846] | 3071 | |
---|
[914] | 3072 | Parameters: |
---|
[1846] | 3073 | |
---|
[914] | 3074 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 3075 | |
---|
| 3076 | Example:: |
---|
| 3077 | |
---|
[914] | 3078 | scan.rotate_linpolphase(2.3) |
---|
[1846] | 3079 | |
---|
[914] | 3080 | """ |
---|
| 3081 | varlist = vars() |
---|
[936] | 3082 | self._math._rotate_linpolphase(self, angle) |
---|
[914] | 3083 | self._add_history("rotate_linpolphase", varlist) |
---|
| 3084 | return |
---|
[710] | 3085 | |
---|
[1862] | 3086 | @asaplog_post_dec |
---|
[914] | 3087 | def rotate_xyphase(self, angle): |
---|
[1846] | 3088 | """\ |
---|
[914] | 3089 | Rotate the phase of the XY correlation. This is always done in situ |
---|
| 3090 | in the data. So if you call this function more than once |
---|
| 3091 | then each call rotates the phase further. |
---|
[1846] | 3092 | |
---|
[914] | 3093 | Parameters: |
---|
[1846] | 3094 | |
---|
[914] | 3095 | angle: The angle (degrees) to rotate (add) by. |
---|
[1846] | 3096 | |
---|
| 3097 | Example:: |
---|
| 3098 | |
---|
[914] | 3099 | scan.rotate_xyphase(2.3) |
---|
[1846] | 3100 | |
---|
[914] | 3101 | """ |
---|
| 3102 | varlist = vars() |
---|
[936] | 3103 | self._math._rotate_xyphase(self, angle) |
---|
[914] | 3104 | self._add_history("rotate_xyphase", varlist) |
---|
| 3105 | return |
---|
| 3106 | |
---|
[1862] | 3107 | @asaplog_post_dec |
---|
[914] | 3108 | def swap_linears(self): |
---|
[1846] | 3109 | """\ |
---|
[1573] | 3110 | Swap the linear polarisations XX and YY, or better the first two |
---|
[1348] | 3111 | polarisations as this also works for ciculars. |
---|
[914] | 3112 | """ |
---|
| 3113 | varlist = vars() |
---|
[936] | 3114 | self._math._swap_linears(self) |
---|
[914] | 3115 | self._add_history("swap_linears", varlist) |
---|
| 3116 | return |
---|
| 3117 | |
---|
[1862] | 3118 | @asaplog_post_dec |
---|
[914] | 3119 | def invert_phase(self): |
---|
[1846] | 3120 | """\ |
---|
[914] | 3121 | Invert the phase of the complex polarisation |
---|
| 3122 | """ |
---|
| 3123 | varlist = vars() |
---|
[936] | 3124 | self._math._invert_phase(self) |
---|
[914] | 3125 | self._add_history("invert_phase", varlist) |
---|
| 3126 | return |
---|
| 3127 | |
---|
[1862] | 3128 | @asaplog_post_dec |
---|
[876] | 3129 | def add(self, offset, insitu=None): |
---|
[1846] | 3130 | """\ |
---|
[513] | 3131 | Return a scan where all spectra have the offset added |
---|
[1846] | 3132 | |
---|
[513] | 3133 | Parameters: |
---|
[1846] | 3134 | |
---|
[513] | 3135 | offset: the offset |
---|
[1855] | 3136 | |
---|
[513] | 3137 | insitu: if False a new scantable is returned. |
---|
| 3138 | Otherwise, the scaling is done in-situ |
---|
| 3139 | The default is taken from .asaprc (False) |
---|
[1846] | 3140 | |
---|
[513] | 3141 | """ |
---|
| 3142 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3143 | self._math._setinsitu(insitu) |
---|
[513] | 3144 | varlist = vars() |
---|
[876] | 3145 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
[1118] | 3146 | s._add_history("add", varlist) |
---|
[876] | 3147 | if insitu: |
---|
| 3148 | self._assign(s) |
---|
| 3149 | else: |
---|
[513] | 3150 | return s |
---|
| 3151 | |
---|
[1862] | 3152 | @asaplog_post_dec |
---|
[1308] | 3153 | def scale(self, factor, tsys=True, insitu=None): |
---|
[1846] | 3154 | """\ |
---|
| 3155 | |
---|
[1938] | 3156 | Return a scan where all spectra are scaled by the given 'factor' |
---|
[1846] | 3157 | |
---|
[513] | 3158 | Parameters: |
---|
[1846] | 3159 | |
---|
[1819] | 3160 | factor: the scaling factor (float or 1D float list) |
---|
[1855] | 3161 | |
---|
[513] | 3162 | insitu: if False a new scantable is returned. |
---|
| 3163 | Otherwise, the scaling is done in-situ |
---|
| 3164 | The default is taken from .asaprc (False) |
---|
[1855] | 3165 | |
---|
[513] | 3166 | tsys: if True (default) then apply the operation to Tsys |
---|
| 3167 | as well as the data |
---|
[1846] | 3168 | |
---|
[513] | 3169 | """ |
---|
| 3170 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3171 | self._math._setinsitu(insitu) |
---|
[513] | 3172 | varlist = vars() |
---|
[1819] | 3173 | s = None |
---|
| 3174 | import numpy |
---|
| 3175 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
[2320] | 3176 | if isinstance(factor[0], list) or isinstance(factor[0], |
---|
| 3177 | numpy.ndarray): |
---|
[1819] | 3178 | from asapmath import _array2dOp |
---|
[2320] | 3179 | s = _array2dOp( self, factor, "MUL", tsys, insitu ) |
---|
[1819] | 3180 | else: |
---|
[2320] | 3181 | s = scantable( self._math._arrayop( self, factor, |
---|
| 3182 | "MUL", tsys ) ) |
---|
[1819] | 3183 | else: |
---|
[2320] | 3184 | s = scantable(self._math._unaryop(self, factor, "MUL", tsys)) |
---|
[1118] | 3185 | s._add_history("scale", varlist) |
---|
[876] | 3186 | if insitu: |
---|
| 3187 | self._assign(s) |
---|
| 3188 | else: |
---|
[513] | 3189 | return s |
---|
| 3190 | |
---|
[2349] | 3191 | @preserve_selection |
---|
| 3192 | def set_sourcetype(self, match, matchtype="pattern", |
---|
[1504] | 3193 | sourcetype="reference"): |
---|
[1846] | 3194 | """\ |
---|
[1502] | 3195 | Set the type of the source to be an source or reference scan |
---|
[1846] | 3196 | using the provided pattern. |
---|
| 3197 | |
---|
[1502] | 3198 | Parameters: |
---|
[1846] | 3199 | |
---|
[1504] | 3200 | match: a Unix style pattern, regular expression or selector |
---|
[1855] | 3201 | |
---|
[1504] | 3202 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
| 3203 | 'regex' regular expression |
---|
[1855] | 3204 | |
---|
[1502] | 3205 | sourcetype: the type of the source to use (source/reference) |
---|
[1846] | 3206 | |
---|
[1502] | 3207 | """ |
---|
| 3208 | varlist = vars() |
---|
| 3209 | basesel = self.get_selection() |
---|
| 3210 | stype = -1 |
---|
| 3211 | if sourcetype.lower().startswith("r"): |
---|
| 3212 | stype = 1 |
---|
| 3213 | elif sourcetype.lower().startswith("s"): |
---|
| 3214 | stype = 0 |
---|
[1504] | 3215 | else: |
---|
[1502] | 3216 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
[1504] | 3217 | if matchtype.lower().startswith("p"): |
---|
| 3218 | matchtype = "pattern" |
---|
| 3219 | elif matchtype.lower().startswith("r"): |
---|
| 3220 | matchtype = "regex" |
---|
| 3221 | else: |
---|
| 3222 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
[1502] | 3223 | sel = selector() |
---|
| 3224 | if isinstance(match, selector): |
---|
| 3225 | sel = match |
---|
| 3226 | else: |
---|
[1504] | 3227 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
[1502] | 3228 | self._setsourcetype(stype) |
---|
[1573] | 3229 | self._add_history("set_sourcetype", varlist) |
---|
[1502] | 3230 | |
---|
[1862] | 3231 | @asaplog_post_dec |
---|
[1857] | 3232 | @preserve_selection |
---|
[1819] | 3233 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
[1846] | 3234 | """\ |
---|
[670] | 3235 | This function allows to build quotients automatically. |
---|
[1819] | 3236 | It assumes the observation to have the same number of |
---|
[670] | 3237 | "ons" and "offs" |
---|
[1846] | 3238 | |
---|
[670] | 3239 | Parameters: |
---|
[1846] | 3240 | |
---|
[710] | 3241 | preserve: you can preserve (default) the continuum or |
---|
| 3242 | remove it. The equations used are |
---|
[1857] | 3243 | |
---|
[670] | 3244 | preserve: Output = Toff * (on/off) - Toff |
---|
[1857] | 3245 | |
---|
[1070] | 3246 | remove: Output = Toff * (on/off) - Ton |
---|
[1855] | 3247 | |
---|
[1573] | 3248 | mode: the on/off detection mode |
---|
[1348] | 3249 | 'paired' (default) |
---|
| 3250 | identifies 'off' scans by the |
---|
| 3251 | trailing '_R' (Mopra/Parkes) or |
---|
| 3252 | '_e'/'_w' (Tid) and matches |
---|
| 3253 | on/off pairs from the observing pattern |
---|
[1502] | 3254 | 'time' |
---|
| 3255 | finds the closest off in time |
---|
[1348] | 3256 | |
---|
[1857] | 3257 | .. todo:: verify argument is not implemented |
---|
| 3258 | |
---|
[670] | 3259 | """ |
---|
[1857] | 3260 | varlist = vars() |
---|
[1348] | 3261 | modes = ["time", "paired"] |
---|
[670] | 3262 | if not mode in modes: |
---|
[876] | 3263 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
| 3264 | raise ValueError(msg) |
---|
[1348] | 3265 | s = None |
---|
| 3266 | if mode.lower() == "paired": |
---|
[1857] | 3267 | sel = self.get_selection() |
---|
[1875] | 3268 | sel.set_query("SRCTYPE==psoff") |
---|
[1356] | 3269 | self.set_selection(sel) |
---|
[1348] | 3270 | offs = self.copy() |
---|
[1875] | 3271 | sel.set_query("SRCTYPE==pson") |
---|
[1356] | 3272 | self.set_selection(sel) |
---|
[1348] | 3273 | ons = self.copy() |
---|
| 3274 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
| 3275 | elif mode.lower() == "time": |
---|
| 3276 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
[1118] | 3277 | s._add_history("auto_quotient", varlist) |
---|
[876] | 3278 | return s |
---|
[710] | 3279 | |
---|
[1862] | 3280 | @asaplog_post_dec |
---|
[1145] | 3281 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
[1846] | 3282 | """\ |
---|
[1143] | 3283 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
[1846] | 3284 | |
---|
[1143] | 3285 | Parameters: |
---|
[1846] | 3286 | |
---|
[1145] | 3287 | mask: an optional mask to be used when weight == 'stddev' |
---|
[1855] | 3288 | |
---|
[1143] | 3289 | weight: How to average the off beams. Default is 'median'. |
---|
[1855] | 3290 | |
---|
[1145] | 3291 | preserve: you can preserve (default) the continuum or |
---|
[1855] | 3292 | remove it. The equations used are: |
---|
[1846] | 3293 | |
---|
[1855] | 3294 | preserve: Output = Toff * (on/off) - Toff |
---|
| 3295 | |
---|
| 3296 | remove: Output = Toff * (on/off) - Ton |
---|
| 3297 | |
---|
[1217] | 3298 | """ |
---|
[1593] | 3299 | mask = mask or () |
---|
[1141] | 3300 | varlist = vars() |
---|
| 3301 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
[1143] | 3302 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
| 3303 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
[1217] | 3304 | from asapmath import quotient |
---|
[1145] | 3305 | q = quotient(on, off, preserve) |
---|
[1143] | 3306 | q._add_history("mx_quotient", varlist) |
---|
[1217] | 3307 | return q |
---|
[513] | 3308 | |
---|
[1862] | 3309 | @asaplog_post_dec |
---|
[718] | 3310 | def freq_switch(self, insitu=None): |
---|
[1846] | 3311 | """\ |
---|
[718] | 3312 | Apply frequency switching to the data. |
---|
[1846] | 3313 | |
---|
[718] | 3314 | Parameters: |
---|
[1846] | 3315 | |
---|
[718] | 3316 | insitu: if False a new scantable is returned. |
---|
| 3317 | Otherwise, the swictching is done in-situ |
---|
| 3318 | The default is taken from .asaprc (False) |
---|
[1846] | 3319 | |
---|
[718] | 3320 | """ |
---|
| 3321 | if insitu is None: insitu = rcParams['insitu'] |
---|
[876] | 3322 | self._math._setinsitu(insitu) |
---|
[718] | 3323 | varlist = vars() |
---|
[876] | 3324 | s = scantable(self._math._freqswitch(self)) |
---|
[1118] | 3325 | s._add_history("freq_switch", varlist) |
---|
[1856] | 3326 | if insitu: |
---|
| 3327 | self._assign(s) |
---|
| 3328 | else: |
---|
| 3329 | return s |
---|
[718] | 3330 | |
---|
[1862] | 3331 | @asaplog_post_dec |
---|
[780] | 3332 | def recalc_azel(self): |
---|
[1846] | 3333 | """Recalculate the azimuth and elevation for each position.""" |
---|
[780] | 3334 | varlist = vars() |
---|
[876] | 3335 | self._recalcazel() |
---|
[780] | 3336 | self._add_history("recalc_azel", varlist) |
---|
| 3337 | return |
---|
| 3338 | |
---|
[1862] | 3339 | @asaplog_post_dec |
---|
[513] | 3340 | def __add__(self, other): |
---|
| 3341 | varlist = vars() |
---|
| 3342 | s = None |
---|
| 3343 | if isinstance(other, scantable): |
---|
[1573] | 3344 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
[513] | 3345 | elif isinstance(other, float): |
---|
[876] | 3346 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
[2144] | 3347 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
[2349] | 3348 | if isinstance(other[0], list) \ |
---|
| 3349 | or isinstance(other[0], numpy.ndarray): |
---|
[2144] | 3350 | from asapmath import _array2dOp |
---|
| 3351 | s = _array2dOp( self.copy(), other, "ADD", False ) |
---|
| 3352 | else: |
---|
[2349] | 3353 | s = scantable( self._math._arrayop( self.copy(), other, |
---|
| 3354 | "ADD", False ) ) |
---|
[513] | 3355 | else: |
---|
[718] | 3356 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3357 | s._add_history("operator +", varlist) |
---|
| 3358 | return s |
---|
| 3359 | |
---|
[1862] | 3360 | @asaplog_post_dec |
---|
[513] | 3361 | def __sub__(self, other): |
---|
| 3362 | """ |
---|
| 3363 | implicit on all axes and on Tsys |
---|
| 3364 | """ |
---|
| 3365 | varlist = vars() |
---|
| 3366 | s = None |
---|
| 3367 | if isinstance(other, scantable): |
---|
[1588] | 3368 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
[513] | 3369 | elif isinstance(other, float): |
---|
[876] | 3370 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
[2144] | 3371 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
[2349] | 3372 | if isinstance(other[0], list) \ |
---|
| 3373 | or isinstance(other[0], numpy.ndarray): |
---|
[2144] | 3374 | from asapmath import _array2dOp |
---|
| 3375 | s = _array2dOp( self.copy(), other, "SUB", False ) |
---|
| 3376 | else: |
---|
[2349] | 3377 | s = scantable( self._math._arrayop( self.copy(), other, |
---|
| 3378 | "SUB", False ) ) |
---|
[513] | 3379 | else: |
---|
[718] | 3380 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3381 | s._add_history("operator -", varlist) |
---|
| 3382 | return s |
---|
[710] | 3383 | |
---|
[1862] | 3384 | @asaplog_post_dec |
---|
[513] | 3385 | def __mul__(self, other): |
---|
| 3386 | """ |
---|
| 3387 | implicit on all axes and on Tsys |
---|
| 3388 | """ |
---|
| 3389 | varlist = vars() |
---|
| 3390 | s = None |
---|
| 3391 | if isinstance(other, scantable): |
---|
[1588] | 3392 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
[513] | 3393 | elif isinstance(other, float): |
---|
[876] | 3394 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
[2144] | 3395 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
[2349] | 3396 | if isinstance(other[0], list) \ |
---|
| 3397 | or isinstance(other[0], numpy.ndarray): |
---|
[2144] | 3398 | from asapmath import _array2dOp |
---|
| 3399 | s = _array2dOp( self.copy(), other, "MUL", False ) |
---|
| 3400 | else: |
---|
[2349] | 3401 | s = scantable( self._math._arrayop( self.copy(), other, |
---|
| 3402 | "MUL", False ) ) |
---|
[513] | 3403 | else: |
---|
[718] | 3404 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3405 | s._add_history("operator *", varlist) |
---|
| 3406 | return s |
---|
| 3407 | |
---|
[710] | 3408 | |
---|
[1862] | 3409 | @asaplog_post_dec |
---|
[513] | 3410 | def __div__(self, other): |
---|
| 3411 | """ |
---|
| 3412 | implicit on all axes and on Tsys |
---|
| 3413 | """ |
---|
| 3414 | varlist = vars() |
---|
| 3415 | s = None |
---|
| 3416 | if isinstance(other, scantable): |
---|
[1589] | 3417 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
[513] | 3418 | elif isinstance(other, float): |
---|
| 3419 | if other == 0.0: |
---|
[718] | 3420 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
[876] | 3421 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
[2144] | 3422 | elif isinstance(other, list) or isinstance(other, numpy.ndarray): |
---|
[2349] | 3423 | if isinstance(other[0], list) \ |
---|
| 3424 | or isinstance(other[0], numpy.ndarray): |
---|
[2144] | 3425 | from asapmath import _array2dOp |
---|
| 3426 | s = _array2dOp( self.copy(), other, "DIV", False ) |
---|
| 3427 | else: |
---|
[2349] | 3428 | s = scantable( self._math._arrayop( self.copy(), other, |
---|
| 3429 | "DIV", False ) ) |
---|
[513] | 3430 | else: |
---|
[718] | 3431 | raise TypeError("Other input is not a scantable or float value") |
---|
[513] | 3432 | s._add_history("operator /", varlist) |
---|
| 3433 | return s |
---|
| 3434 | |
---|
[1862] | 3435 | @asaplog_post_dec |
---|
[530] | 3436 | def get_fit(self, row=0): |
---|
[1846] | 3437 | """\ |
---|
[530] | 3438 | Print or return the stored fits for a row in the scantable |
---|
[1846] | 3439 | |
---|
[530] | 3440 | Parameters: |
---|
[1846] | 3441 | |
---|
[530] | 3442 | row: the row which the fit has been applied to. |
---|
[1846] | 3443 | |
---|
[530] | 3444 | """ |
---|
| 3445 | if row > self.nrow(): |
---|
| 3446 | return |
---|
[976] | 3447 | from asap.asapfit import asapfit |
---|
[530] | 3448 | fit = asapfit(self._getfit(row)) |
---|
[1859] | 3449 | asaplog.push( '%s' %(fit) ) |
---|
| 3450 | return fit.as_dict() |
---|
[530] | 3451 | |
---|
[2349] | 3452 | @preserve_selection |
---|
[1483] | 3453 | def flag_nans(self): |
---|
[1846] | 3454 | """\ |
---|
[1483] | 3455 | Utility function to flag NaN values in the scantable. |
---|
| 3456 | """ |
---|
| 3457 | import numpy |
---|
| 3458 | basesel = self.get_selection() |
---|
| 3459 | for i in range(self.nrow()): |
---|
[1589] | 3460 | sel = self.get_row_selector(i) |
---|
| 3461 | self.set_selection(basesel+sel) |
---|
[1483] | 3462 | nans = numpy.isnan(self._getspectrum(0)) |
---|
| 3463 | if numpy.any(nans): |
---|
| 3464 | bnans = [ bool(v) for v in nans] |
---|
| 3465 | self.flag(bnans) |
---|
| 3466 | |
---|
[1588] | 3467 | def get_row_selector(self, rowno): |
---|
[1992] | 3468 | return selector(rows=[rowno]) |
---|
[1573] | 3469 | |
---|
[484] | 3470 | def _add_history(self, funcname, parameters): |
---|
[1435] | 3471 | if not rcParams['scantable.history']: |
---|
| 3472 | return |
---|
[484] | 3473 | # create date |
---|
| 3474 | sep = "##" |
---|
| 3475 | from datetime import datetime |
---|
| 3476 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
| 3477 | hist = dstr+sep |
---|
| 3478 | hist += funcname+sep#cdate+sep |
---|
[2349] | 3479 | if parameters.has_key('self'): |
---|
| 3480 | del parameters['self'] |
---|
[1118] | 3481 | for k, v in parameters.iteritems(): |
---|
[484] | 3482 | if type(v) is dict: |
---|
[1118] | 3483 | for k2, v2 in v.iteritems(): |
---|
[484] | 3484 | hist += k2 |
---|
| 3485 | hist += "=" |
---|
[1118] | 3486 | if isinstance(v2, scantable): |
---|
[484] | 3487 | hist += 'scantable' |
---|
| 3488 | elif k2 == 'mask': |
---|
[1118] | 3489 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
[513] | 3490 | hist += str(self._zip_mask(v2)) |
---|
| 3491 | else: |
---|
| 3492 | hist += str(v2) |
---|
[484] | 3493 | else: |
---|
[513] | 3494 | hist += str(v2) |
---|
[484] | 3495 | else: |
---|
| 3496 | hist += k |
---|
| 3497 | hist += "=" |
---|
[1118] | 3498 | if isinstance(v, scantable): |
---|
[484] | 3499 | hist += 'scantable' |
---|
| 3500 | elif k == 'mask': |
---|
[1118] | 3501 | if isinstance(v, list) or isinstance(v, tuple): |
---|
[513] | 3502 | hist += str(self._zip_mask(v)) |
---|
| 3503 | else: |
---|
| 3504 | hist += str(v) |
---|
[484] | 3505 | else: |
---|
| 3506 | hist += str(v) |
---|
| 3507 | hist += sep |
---|
| 3508 | hist = hist[:-2] # remove trailing '##' |
---|
| 3509 | self._addhistory(hist) |
---|
| 3510 | |
---|
[710] | 3511 | |
---|
[484] | 3512 | def _zip_mask(self, mask): |
---|
| 3513 | mask = list(mask) |
---|
| 3514 | i = 0 |
---|
| 3515 | segments = [] |
---|
| 3516 | while mask[i:].count(1): |
---|
| 3517 | i += mask[i:].index(1) |
---|
| 3518 | if mask[i:].count(0): |
---|
| 3519 | j = i + mask[i:].index(0) |
---|
| 3520 | else: |
---|
[710] | 3521 | j = len(mask) |
---|
[1118] | 3522 | segments.append([i, j]) |
---|
[710] | 3523 | i = j |
---|
[484] | 3524 | return segments |
---|
[714] | 3525 | |
---|
[626] | 3526 | def _get_ordinate_label(self): |
---|
| 3527 | fu = "("+self.get_fluxunit()+")" |
---|
| 3528 | import re |
---|
| 3529 | lbl = "Intensity" |
---|
[1118] | 3530 | if re.match(".K.", fu): |
---|
[626] | 3531 | lbl = "Brightness Temperature "+ fu |
---|
[1118] | 3532 | elif re.match(".Jy.", fu): |
---|
[626] | 3533 | lbl = "Flux density "+ fu |
---|
| 3534 | return lbl |
---|
[710] | 3535 | |
---|
[876] | 3536 | def _check_ifs(self): |
---|
[2349] | 3537 | # return len(set([self.nchan(i) for i in self.getifnos()])) == 1 |
---|
[1986] | 3538 | nchans = [self.nchan(i) for i in self.getifnos()] |
---|
[2004] | 3539 | nchans = filter(lambda t: t > 0, nchans) |
---|
[876] | 3540 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
[976] | 3541 | |
---|
[1862] | 3542 | @asaplog_post_dec |
---|
[1916] | 3543 | def _fill(self, names, unit, average, opts={}): |
---|
[976] | 3544 | first = True |
---|
| 3545 | fullnames = [] |
---|
| 3546 | for name in names: |
---|
| 3547 | name = os.path.expandvars(name) |
---|
| 3548 | name = os.path.expanduser(name) |
---|
| 3549 | if not os.path.exists(name): |
---|
| 3550 | msg = "File '%s' does not exists" % (name) |
---|
| 3551 | raise IOError(msg) |
---|
| 3552 | fullnames.append(name) |
---|
| 3553 | if average: |
---|
| 3554 | asaplog.push('Auto averaging integrations') |
---|
[1079] | 3555 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
[976] | 3556 | for name in fullnames: |
---|
[1073] | 3557 | tbl = Scantable(stype) |
---|
[2004] | 3558 | if is_ms( name ): |
---|
| 3559 | r = msfiller( tbl ) |
---|
| 3560 | else: |
---|
| 3561 | r = filler( tbl ) |
---|
| 3562 | rx = rcParams['scantable.reference'] |
---|
| 3563 | r.setreferenceexpr(rx) |
---|
[976] | 3564 | msg = "Importing %s..." % (name) |
---|
[1118] | 3565 | asaplog.push(msg, False) |
---|
[2349] | 3566 | r.open(name, opts) |
---|
[1843] | 3567 | r.fill() |
---|
[976] | 3568 | if average: |
---|
[1118] | 3569 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
[976] | 3570 | if not first: |
---|
| 3571 | tbl = self._math._merge([self, tbl]) |
---|
| 3572 | Scantable.__init__(self, tbl) |
---|
[1843] | 3573 | r.close() |
---|
[1118] | 3574 | del r, tbl |
---|
[976] | 3575 | first = False |
---|
[1861] | 3576 | #flush log |
---|
| 3577 | asaplog.post() |
---|
[976] | 3578 | if unit is not None: |
---|
| 3579 | self.set_fluxunit(unit) |
---|
[1824] | 3580 | if not is_casapy(): |
---|
| 3581 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
[976] | 3582 | |
---|
[2012] | 3583 | |
---|
[1402] | 3584 | def __getitem__(self, key): |
---|
| 3585 | if key < 0: |
---|
| 3586 | key += self.nrow() |
---|
| 3587 | if key >= self.nrow(): |
---|
| 3588 | raise IndexError("Row index out of range.") |
---|
| 3589 | return self._getspectrum(key) |
---|
| 3590 | |
---|
| 3591 | def __setitem__(self, key, value): |
---|
| 3592 | if key < 0: |
---|
| 3593 | key += self.nrow() |
---|
| 3594 | if key >= self.nrow(): |
---|
| 3595 | raise IndexError("Row index out of range.") |
---|
| 3596 | if not hasattr(value, "__len__") or \ |
---|
| 3597 | len(value) > self.nchan(self.getif(key)): |
---|
| 3598 | raise ValueError("Spectrum length doesn't match.") |
---|
| 3599 | return self._setspectrum(value, key) |
---|
| 3600 | |
---|
| 3601 | def __len__(self): |
---|
| 3602 | return self.nrow() |
---|
| 3603 | |
---|
| 3604 | def __iter__(self): |
---|
| 3605 | for i in range(len(self)): |
---|
| 3606 | yield self[i] |
---|