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