1 | """This module defines the scantable class.""" |
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2 | |
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3 | import os |
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4 | try: |
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5 | from functools import wraps as wraps_dec |
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6 | except ImportError: |
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7 | from asap.compatibility import wraps as wraps_dec |
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8 | |
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9 | from asap.env import is_casapy |
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10 | from asap._asap import Scantable |
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11 | from asap._asap import filler |
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12 | from asap.parameters import rcParams |
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13 | from asap.logging import asaplog, asaplog_post_dec |
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14 | from asap.selector import selector |
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15 | from asap.linecatalog import linecatalog |
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16 | from asap.coordinate import coordinate |
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17 | from asap.utils import _n_bools, mask_not, mask_and, mask_or, page |
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18 | from asap.asapfitter import fitter |
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19 | |
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20 | |
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21 | def preserve_selection(func): |
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22 | @wraps_dec(func) |
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23 | def wrap(obj, *args, **kw): |
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24 | basesel = obj.get_selection() |
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25 | try: |
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26 | val = func(obj, *args, **kw) |
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27 | finally: |
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28 | obj.set_selection(basesel) |
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29 | return val |
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30 | return wrap |
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31 | |
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32 | def is_scantable(filename): |
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33 | """Is the given file a scantable? |
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34 | |
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35 | Parameters: |
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36 | |
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37 | filename: the name of the file/directory to test |
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38 | |
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39 | """ |
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40 | if ( os.path.isdir(filename) |
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41 | and os.path.exists(filename+'/table.info') |
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42 | and os.path.exists(filename+'/table.dat') ): |
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43 | f=open(filename+'/table.info') |
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44 | l=f.readline() |
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45 | f.close() |
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46 | #if ( l.find('Scantable') != -1 ): |
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47 | if ( l.find('Measurement Set') == -1 ): |
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48 | return True |
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49 | else: |
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50 | return False |
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51 | else: |
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52 | return False |
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53 | ## return (os.path.isdir(filename) |
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54 | ## and not os.path.exists(filename+'/table.f1') |
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55 | ## and os.path.exists(filename+'/table.info')) |
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56 | |
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57 | def is_ms(filename): |
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58 | """Is the given file a MeasurementSet? |
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59 | |
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60 | Parameters: |
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61 | |
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62 | filename: the name of the file/directory to test |
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63 | |
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64 | """ |
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65 | if ( os.path.isdir(filename) |
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66 | and os.path.exists(filename+'/table.info') |
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67 | and os.path.exists(filename+'/table.dat') ): |
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68 | f=open(filename+'/table.info') |
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69 | l=f.readline() |
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70 | f.close() |
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71 | if ( l.find('Measurement Set') != -1 ): |
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72 | return True |
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73 | else: |
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74 | return False |
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75 | else: |
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76 | return False |
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77 | |
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78 | class scantable(Scantable): |
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79 | """\ |
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80 | The ASAP container for scans (single-dish data). |
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81 | """ |
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82 | |
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83 | @asaplog_post_dec |
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84 | #def __init__(self, filename, average=None, unit=None, getpt=None, |
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85 | # antenna=None, parallactify=None): |
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86 | def __init__(self, filename, average=None, unit=None, parallactify=None, **args): |
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87 | """\ |
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88 | Create a scantable from a saved one or make a reference |
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89 | |
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90 | Parameters: |
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91 | |
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92 | filename: the name of an asap table on disk |
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93 | or |
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94 | the name of a rpfits/sdfits/ms file |
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95 | (integrations within scans are auto averaged |
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96 | and the whole file is read) or |
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97 | [advanced] a reference to an existing scantable |
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98 | |
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99 | average: average all integrations withinb a scan on read. |
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100 | The default (True) is taken from .asaprc. |
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101 | |
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102 | unit: brightness unit; must be consistent with K or Jy. |
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103 | Over-rides the default selected by the filler |
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104 | (input rpfits/sdfits/ms) or replaces the value |
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105 | in existing scantables |
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106 | |
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107 | getpt: for MeasurementSet input data only: |
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108 | If True, all pointing data are filled. |
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109 | The deafult is False, which makes time to load |
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110 | the MS data faster in some cases. |
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111 | |
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112 | antenna: for MeasurementSet input data only: |
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113 | Antenna selection. integer (id) or string (name or id). |
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114 | |
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115 | parallactify: Indicate that the data had been parallatified. Default |
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116 | is taken from rc file. |
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117 | |
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118 | """ |
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119 | if average is None: |
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120 | average = rcParams['scantable.autoaverage'] |
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121 | #if getpt is None: |
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122 | # getpt = True |
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123 | #if antenna is not None: |
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124 | # asaplog.push("Antenna selection currently unsupported." |
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125 | # "Using ''") |
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126 | # asaplog.post('WARN') |
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127 | #if antenna is None: |
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128 | # antenna = '' |
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129 | #elif type(antenna) == int: |
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130 | # antenna = '%s' % antenna |
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131 | #elif type(antenna) == list: |
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132 | # tmpstr = '' |
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133 | # for i in range( len(antenna) ): |
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134 | # if type(antenna[i]) == int: |
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135 | # tmpstr = tmpstr + ('%s,'%(antenna[i])) |
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136 | # elif type(antenna[i]) == str: |
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137 | # tmpstr=tmpstr+antenna[i]+',' |
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138 | # else: |
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139 | # raise TypeError('Bad antenna selection.') |
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140 | # antenna = tmpstr.rstrip(',') |
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141 | parallactify = parallactify or rcParams['scantable.parallactify'] |
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142 | varlist = vars() |
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143 | from asap._asap import stmath |
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144 | self._math = stmath( rcParams['insitu'] ) |
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145 | if isinstance(filename, Scantable): |
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146 | Scantable.__init__(self, filename) |
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147 | else: |
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148 | if isinstance(filename, str): |
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149 | filename = os.path.expandvars(filename) |
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150 | filename = os.path.expanduser(filename) |
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151 | if not os.path.exists(filename): |
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152 | s = "File '%s' not found." % (filename) |
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153 | raise IOError(s) |
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154 | if is_scantable(filename): |
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155 | ondisk = rcParams['scantable.storage'] == 'disk' |
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156 | Scantable.__init__(self, filename, ondisk) |
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157 | if unit is not None: |
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158 | self.set_fluxunit(unit) |
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159 | # do not reset to the default freqframe |
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160 | #self.set_freqframe(rcParams['scantable.freqframe']) |
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161 | #elif os.path.isdir(filename) \ |
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162 | # and not os.path.exists(filename+'/table.f1'): |
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163 | elif is_ms(filename): |
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164 | # Measurement Set |
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165 | opts={'ms': {}} |
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166 | mskeys=['getpt','antenna'] |
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167 | for key in mskeys: |
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168 | if key in args.keys(): |
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169 | opts['ms'][key] = args[key] |
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170 | #self._fill([filename], unit, average, getpt, antenna) |
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171 | self._fill([filename], unit, average, opts) |
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172 | elif os.path.isfile(filename): |
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173 | #self._fill([filename], unit, average, getpt, antenna) |
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174 | self._fill([filename], unit, average) |
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175 | else: |
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176 | msg = "The given file '%s'is not a valid " \ |
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177 | "asap table." % (filename) |
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178 | raise IOError(msg) |
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179 | elif (isinstance(filename, list) or isinstance(filename, tuple)) \ |
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180 | and isinstance(filename[-1], str): |
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181 | #self._fill(filename, unit, average, getpt, antenna) |
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182 | self._fill(filename, unit, average) |
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183 | self.parallactify(parallactify) |
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184 | self._add_history("scantable", varlist) |
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185 | |
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186 | @asaplog_post_dec |
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187 | def save(self, name=None, format=None, overwrite=False): |
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188 | """\ |
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189 | Store the scantable on disk. This can be an asap (aips++) Table, |
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190 | SDFITS or MS2 format. |
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191 | |
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192 | Parameters: |
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193 | |
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194 | name: the name of the outputfile. For format "ASCII" |
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195 | this is the root file name (data in 'name'.txt |
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196 | and header in 'name'_header.txt) |
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197 | |
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198 | format: an optional file format. Default is ASAP. |
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199 | Allowed are: |
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200 | |
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201 | * 'ASAP' (save as ASAP [aips++] Table), |
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202 | * 'SDFITS' (save as SDFITS file) |
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203 | * 'ASCII' (saves as ascii text file) |
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204 | * 'MS2' (saves as an casacore MeasurementSet V2) |
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205 | * 'FITS' (save as image FITS - not readable by class) |
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206 | * 'CLASS' (save as FITS readable by CLASS) |
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207 | |
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208 | overwrite: If the file should be overwritten if it exists. |
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209 | The default False is to return with warning |
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210 | without writing the output. USE WITH CARE. |
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211 | |
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212 | Example:: |
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213 | |
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214 | scan.save('myscan.asap') |
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215 | scan.save('myscan.sdfits', 'SDFITS') |
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216 | |
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217 | """ |
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218 | from os import path |
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219 | format = format or rcParams['scantable.save'] |
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220 | suffix = '.'+format.lower() |
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221 | if name is None or name == "": |
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222 | name = 'scantable'+suffix |
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223 | msg = "No filename given. Using default name %s..." % name |
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224 | asaplog.push(msg) |
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225 | name = path.expandvars(name) |
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226 | if path.isfile(name) or path.isdir(name): |
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227 | if not overwrite: |
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228 | msg = "File %s exists." % name |
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229 | raise IOError(msg) |
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230 | format2 = format.upper() |
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231 | if format2 == 'ASAP': |
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232 | self._save(name) |
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233 | else: |
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234 | from asap._asap import stwriter as stw |
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235 | writer = stw(format2) |
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236 | writer.write(self, name) |
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237 | return |
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238 | |
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239 | def copy(self): |
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240 | """Return a copy of this scantable. |
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241 | |
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242 | *Note*: |
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243 | |
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244 | This makes a full (deep) copy. scan2 = scan1 makes a reference. |
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245 | |
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246 | Example:: |
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247 | |
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248 | copiedscan = scan.copy() |
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249 | |
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250 | """ |
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251 | sd = scantable(Scantable._copy(self)) |
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252 | return sd |
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253 | |
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254 | def drop_scan(self, scanid=None): |
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255 | """\ |
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256 | Return a new scantable where the specified scan number(s) has(have) |
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257 | been dropped. |
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258 | |
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259 | Parameters: |
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260 | |
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261 | scanid: a (list of) scan number(s) |
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262 | |
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263 | """ |
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264 | from asap import _is_sequence_or_number as _is_valid |
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265 | from asap import _to_list |
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266 | from asap import unique |
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267 | if not _is_valid(scanid): |
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268 | raise RuntimeError( 'Please specify a scanno to drop from the scantable' ) |
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269 | scanid = _to_list(scanid) |
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270 | allscans = unique([ self.getscan(i) for i in range(self.nrow())]) |
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271 | for sid in scanid: allscans.remove(sid) |
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272 | if len(allscans) == 0: |
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273 | raise ValueError("Can't remove all scans") |
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274 | sel = selector(scans=allscans) |
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275 | return self._select_copy(sel) |
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276 | |
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277 | def _select_copy(self, selection): |
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278 | orig = self.get_selection() |
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279 | self.set_selection(orig+selection) |
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280 | cp = self.copy() |
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281 | self.set_selection(orig) |
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282 | return cp |
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283 | |
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284 | def get_scan(self, scanid=None): |
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285 | """\ |
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286 | Return a specific scan (by scanno) or collection of scans (by |
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287 | source name) in a new scantable. |
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288 | |
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289 | *Note*: |
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290 | |
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291 | See scantable.drop_scan() for the inverse operation. |
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292 | |
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293 | Parameters: |
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294 | |
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295 | scanid: a (list of) scanno or a source name, unix-style |
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296 | patterns are accepted for source name matching, e.g. |
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297 | '*_R' gets all 'ref scans |
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298 | |
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299 | Example:: |
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300 | |
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301 | # get all scans containing the source '323p459' |
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302 | newscan = scan.get_scan('323p459') |
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303 | # get all 'off' scans |
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304 | refscans = scan.get_scan('*_R') |
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305 | # get a susbset of scans by scanno (as listed in scan.summary()) |
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306 | newscan = scan.get_scan([0, 2, 7, 10]) |
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307 | |
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308 | """ |
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309 | if scanid is None: |
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310 | raise RuntimeError( 'Please specify a scan no or name to ' |
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311 | 'retrieve from the scantable' ) |
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312 | try: |
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313 | bsel = self.get_selection() |
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314 | sel = selector() |
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315 | if type(scanid) is str: |
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316 | sel.set_name(scanid) |
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317 | return self._select_copy(sel) |
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318 | elif type(scanid) is int: |
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319 | sel.set_scans([scanid]) |
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320 | return self._select_copy(sel) |
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321 | elif type(scanid) is list: |
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322 | sel.set_scans(scanid) |
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323 | return self._select_copy(sel) |
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324 | else: |
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325 | msg = "Illegal scanid type, use 'int' or 'list' if ints." |
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326 | raise TypeError(msg) |
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327 | except RuntimeError: |
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328 | raise |
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329 | |
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330 | def __str__(self): |
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331 | return Scantable._summary(self, True) |
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332 | |
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333 | def summary(self, filename=None): |
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334 | """\ |
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335 | Print a summary of the contents of this scantable. |
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336 | |
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337 | Parameters: |
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338 | |
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339 | filename: the name of a file to write the putput to |
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340 | Default - no file output |
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341 | |
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342 | """ |
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343 | info = Scantable._summary(self, True) |
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344 | if filename is not None: |
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345 | if filename is "": |
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346 | filename = 'scantable_summary.txt' |
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347 | from os.path import expandvars, isdir |
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348 | filename = expandvars(filename) |
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349 | if not isdir(filename): |
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350 | data = open(filename, 'w') |
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351 | data.write(info) |
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352 | data.close() |
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353 | else: |
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354 | msg = "Illegal file name '%s'." % (filename) |
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355 | raise IOError(msg) |
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356 | return page(info) |
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357 | |
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358 | def get_spectrum(self, rowno): |
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359 | """Return the spectrum for the current row in the scantable as a list. |
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360 | |
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361 | Parameters: |
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362 | |
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363 | rowno: the row number to retrieve the spectrum from |
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364 | |
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365 | """ |
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366 | return self._getspectrum(rowno) |
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367 | |
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368 | def get_mask(self, rowno): |
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369 | """Return the mask for the current row in the scantable as a list. |
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370 | |
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371 | Parameters: |
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372 | |
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373 | rowno: the row number to retrieve the mask from |
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374 | |
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375 | """ |
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376 | return self._getmask(rowno) |
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377 | |
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378 | def set_spectrum(self, spec, rowno): |
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379 | """Set the spectrum for the current row in the scantable. |
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380 | |
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381 | Parameters: |
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382 | |
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383 | spec: the new spectrum |
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384 | |
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385 | rowno: the row number to set the spectrum for |
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386 | |
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387 | """ |
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388 | assert(len(spec) == self.nchan()) |
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389 | return self._setspectrum(spec, rowno) |
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390 | |
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391 | def get_coordinate(self, rowno): |
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392 | """Return the (spectral) coordinate for a a given 'rowno'. |
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393 | |
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394 | *Note*: |
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395 | |
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396 | * This coordinate is only valid until a scantable method modifies |
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397 | the frequency axis. |
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398 | * This coordinate does contain the original frequency set-up |
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399 | NOT the new frame. The conversions however are done using the user |
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400 | specified frame (e.g. LSRK/TOPO). To get the 'real' coordinate, |
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401 | use scantable.freq_align first. Without it there is no closure, |
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402 | i.e.:: |
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403 | |
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404 | c = myscan.get_coordinate(0) |
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405 | c.to_frequency(c.get_reference_pixel()) != c.get_reference_value() |
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406 | |
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407 | Parameters: |
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408 | |
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409 | rowno: the row number for the spectral coordinate |
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410 | |
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411 | """ |
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412 | return coordinate(Scantable.get_coordinate(self, rowno)) |
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413 | |
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414 | def get_selection(self): |
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415 | """\ |
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416 | Get the selection object currently set on this scantable. |
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417 | |
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418 | Example:: |
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419 | |
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420 | sel = scan.get_selection() |
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421 | sel.set_ifs(0) # select IF 0 |
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422 | scan.set_selection(sel) # apply modified selection |
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423 | |
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424 | """ |
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425 | return selector(self._getselection()) |
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426 | |
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427 | def set_selection(self, selection=None, **kw): |
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428 | """\ |
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429 | Select a subset of the data. All following operations on this scantable |
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430 | are only applied to thi selection. |
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431 | |
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432 | Parameters: |
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433 | |
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434 | selection: a selector object (default unset the selection), or |
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435 | any combination of "pols", "ifs", "beams", "scans", |
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436 | "cycles", "name", "query" |
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437 | |
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438 | Examples:: |
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439 | |
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440 | sel = selector() # create a selection object |
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441 | self.set_scans([0, 3]) # select SCANNO 0 and 3 |
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442 | scan.set_selection(sel) # set the selection |
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443 | scan.summary() # will only print summary of scanno 0 an 3 |
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444 | scan.set_selection() # unset the selection |
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445 | # or the equivalent |
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446 | scan.set_selection(scans=[0,3]) |
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447 | scan.summary() # will only print summary of scanno 0 an 3 |
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448 | scan.set_selection() # unset the selection |
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449 | |
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450 | """ |
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451 | if selection is None: |
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452 | # reset |
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453 | if len(kw) == 0: |
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454 | selection = selector() |
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455 | else: |
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456 | # try keywords |
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457 | for k in kw: |
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458 | if k not in selector.fields: |
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459 | raise KeyError("Invalid selection key '%s', valid keys are %s" % (k, selector.fields)) |
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460 | selection = selector(**kw) |
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461 | self._setselection(selection) |
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462 | |
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463 | def get_row(self, row=0, insitu=None): |
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464 | """\ |
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465 | Select a row in the scantable. |
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466 | Return a scantable with single row. |
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467 | |
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468 | Parameters: |
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469 | |
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470 | row: row no of integration, default is 0. |
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471 | insitu: if False a new scantable is returned. Otherwise, the |
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472 | scaling is done in-situ. The default is taken from .asaprc |
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473 | (False) |
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474 | |
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475 | """ |
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476 | if insitu is None: insitu = rcParams['insitu'] |
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477 | if not insitu: |
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478 | workscan = self.copy() |
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479 | else: |
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480 | workscan = self |
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481 | # Select a row |
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482 | sel=selector() |
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483 | sel.set_scans([workscan.getscan(row)]) |
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484 | sel.set_cycles([workscan.getcycle(row)]) |
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485 | sel.set_beams([workscan.getbeam(row)]) |
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486 | sel.set_ifs([workscan.getif(row)]) |
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487 | sel.set_polarisations([workscan.getpol(row)]) |
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488 | sel.set_name(workscan._getsourcename(row)) |
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489 | workscan.set_selection(sel) |
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490 | if not workscan.nrow() == 1: |
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491 | msg = "Cloud not identify single row. %d rows selected."%(workscan.nrow()) |
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492 | raise RuntimeError(msg) |
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493 | del sel |
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494 | if insitu: |
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495 | self._assign(workscan) |
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496 | else: |
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497 | return workscan |
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498 | |
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499 | @asaplog_post_dec |
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500 | def stats(self, stat='stddev', mask=None, form='3.3f', row=None): |
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501 | """\ |
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502 | Determine the specified statistic of the current beam/if/pol |
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503 | Takes a 'mask' as an optional parameter to specify which |
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504 | channels should be excluded. |
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505 | |
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506 | Parameters: |
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507 | |
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508 | stat: 'min', 'max', 'min_abc', 'max_abc', 'sumsq', 'sum', |
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509 | 'mean', 'var', 'stddev', 'avdev', 'rms', 'median' |
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510 | |
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511 | mask: an optional mask specifying where the statistic |
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512 | should be determined. |
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513 | |
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514 | form: format string to print statistic values |
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515 | |
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516 | row: row number of spectrum to process. |
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517 | (default is None: for all rows) |
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518 | |
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519 | Example: |
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520 | scan.set_unit('channel') |
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521 | msk = scan.create_mask([100, 200], [500, 600]) |
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522 | scan.stats(stat='mean', mask=m) |
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523 | |
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524 | """ |
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525 | mask = mask or [] |
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526 | if not self._check_ifs(): |
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527 | raise ValueError("Cannot apply mask as the IFs have different " |
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528 | "number of channels. Please use setselection() " |
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529 | "to select individual IFs") |
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530 | rtnabc = False |
---|
531 | if stat.lower().endswith('_abc'): rtnabc = True |
---|
532 | getchan = False |
---|
533 | if stat.lower().startswith('min') or stat.lower().startswith('max'): |
---|
534 | chan = self._math._minmaxchan(self, mask, stat) |
---|
535 | getchan = True |
---|
536 | statvals = [] |
---|
537 | if not rtnabc: |
---|
538 | if row == None: |
---|
539 | statvals = self._math._stats(self, mask, stat) |
---|
540 | else: |
---|
541 | statvals = self._math._statsrow(self, mask, stat, int(row)) |
---|
542 | |
---|
543 | #def cb(i): |
---|
544 | # return statvals[i] |
---|
545 | |
---|
546 | #return self._row_callback(cb, stat) |
---|
547 | |
---|
548 | label=stat |
---|
549 | #callback=cb |
---|
550 | out = "" |
---|
551 | #outvec = [] |
---|
552 | sep = '-'*50 |
---|
553 | |
---|
554 | if row == None: |
---|
555 | rows = xrange(self.nrow()) |
---|
556 | elif isinstance(row, int): |
---|
557 | rows = [ row ] |
---|
558 | |
---|
559 | for i in rows: |
---|
560 | refstr = '' |
---|
561 | statunit= '' |
---|
562 | if getchan: |
---|
563 | qx, qy = self.chan2data(rowno=i, chan=chan[i]) |
---|
564 | if rtnabc: |
---|
565 | statvals.append(qx['value']) |
---|
566 | refstr = ('(value: %'+form) % (qy['value'])+' ['+qy['unit']+'])' |
---|
567 | statunit= '['+qx['unit']+']' |
---|
568 | else: |
---|
569 | refstr = ('(@ %'+form) % (qx['value'])+' ['+qx['unit']+'])' |
---|
570 | |
---|
571 | tm = self._gettime(i) |
---|
572 | src = self._getsourcename(i) |
---|
573 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
574 | out += 'Time[%s]:\n' % (tm) |
---|
575 | if self.nbeam(-1) > 1: out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
576 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
577 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
578 | #outvec.append(callback(i)) |
---|
579 | if len(rows) > 1: |
---|
580 | # out += ('= %'+form) % (outvec[i]) +' '+refstr+'\n' |
---|
581 | out += ('= %'+form) % (statvals[i]) +' '+refstr+'\n' |
---|
582 | else: |
---|
583 | # out += ('= %'+form) % (outvec[0]) +' '+refstr+'\n' |
---|
584 | out += ('= %'+form) % (statvals[0]) +' '+refstr+'\n' |
---|
585 | out += sep+"\n" |
---|
586 | |
---|
587 | import os |
---|
588 | if os.environ.has_key( 'USER' ): |
---|
589 | usr = os.environ['USER'] |
---|
590 | else: |
---|
591 | import commands |
---|
592 | usr = commands.getoutput( 'whoami' ) |
---|
593 | tmpfile = '/tmp/tmp_'+usr+'_casapy_asap_scantable_stats' |
---|
594 | f = open(tmpfile,'w') |
---|
595 | print >> f, sep |
---|
596 | print >> f, ' %s %s' % (label, statunit) |
---|
597 | print >> f, sep |
---|
598 | print >> f, out |
---|
599 | f.close() |
---|
600 | f = open(tmpfile,'r') |
---|
601 | x = f.readlines() |
---|
602 | f.close() |
---|
603 | asaplog.push(''.join(x), False) |
---|
604 | |
---|
605 | return statvals |
---|
606 | |
---|
607 | def chan2data(self, rowno=0, chan=0): |
---|
608 | """\ |
---|
609 | Returns channel/frequency/velocity and spectral value |
---|
610 | at an arbitrary row and channel in the scantable. |
---|
611 | |
---|
612 | Parameters: |
---|
613 | |
---|
614 | rowno: a row number in the scantable. Default is the |
---|
615 | first row, i.e. rowno=0 |
---|
616 | |
---|
617 | chan: a channel in the scantable. Default is the first |
---|
618 | channel, i.e. pos=0 |
---|
619 | |
---|
620 | """ |
---|
621 | if isinstance(rowno, int) and isinstance(chan, int): |
---|
622 | qx = {'unit': self.get_unit(), |
---|
623 | 'value': self._getabcissa(rowno)[chan]} |
---|
624 | qy = {'unit': self.get_fluxunit(), |
---|
625 | 'value': self._getspectrum(rowno)[chan]} |
---|
626 | return qx, qy |
---|
627 | |
---|
628 | def stddev(self, mask=None): |
---|
629 | """\ |
---|
630 | Determine the standard deviation of the current beam/if/pol |
---|
631 | Takes a 'mask' as an optional parameter to specify which |
---|
632 | channels should be excluded. |
---|
633 | |
---|
634 | Parameters: |
---|
635 | |
---|
636 | mask: an optional mask specifying where the standard |
---|
637 | deviation should be determined. |
---|
638 | |
---|
639 | Example:: |
---|
640 | |
---|
641 | scan.set_unit('channel') |
---|
642 | msk = scan.create_mask([100, 200], [500, 600]) |
---|
643 | scan.stddev(mask=m) |
---|
644 | |
---|
645 | """ |
---|
646 | return self.stats(stat='stddev', mask=mask); |
---|
647 | |
---|
648 | |
---|
649 | def get_column_names(self): |
---|
650 | """\ |
---|
651 | Return a list of column names, which can be used for selection. |
---|
652 | """ |
---|
653 | return list(Scantable.get_column_names(self)) |
---|
654 | |
---|
655 | def get_tsys(self, row=-1): |
---|
656 | """\ |
---|
657 | Return the System temperatures. |
---|
658 | |
---|
659 | Parameters: |
---|
660 | |
---|
661 | row: the rowno to get the information for. (default all rows) |
---|
662 | |
---|
663 | Returns: |
---|
664 | |
---|
665 | a list of Tsys values for the current selection |
---|
666 | |
---|
667 | """ |
---|
668 | if row > -1: |
---|
669 | return self._get_column(self._gettsys, row) |
---|
670 | return self._row_callback(self._gettsys, "Tsys") |
---|
671 | |
---|
672 | |
---|
673 | def get_weather(self, row=-1): |
---|
674 | """\ |
---|
675 | Return the weather informations. |
---|
676 | |
---|
677 | Parameters: |
---|
678 | |
---|
679 | row: the rowno to get the information for. (default all rows) |
---|
680 | |
---|
681 | Returns: |
---|
682 | |
---|
683 | a dict or list of of dicts of values for the current selection |
---|
684 | |
---|
685 | """ |
---|
686 | |
---|
687 | values = self._get_column(self._get_weather, row) |
---|
688 | if row > -1: |
---|
689 | return {'temperature': values[0], |
---|
690 | 'pressure': values[1], 'humidity' : values[2], |
---|
691 | 'windspeed' : values[3], 'windaz' : values[4] |
---|
692 | } |
---|
693 | else: |
---|
694 | out = [] |
---|
695 | for r in values: |
---|
696 | |
---|
697 | out.append({'temperature': r[0], |
---|
698 | 'pressure': r[1], 'humidity' : r[2], |
---|
699 | 'windspeed' : r[3], 'windaz' : r[4] |
---|
700 | }) |
---|
701 | return out |
---|
702 | |
---|
703 | def _row_callback(self, callback, label): |
---|
704 | out = "" |
---|
705 | outvec = [] |
---|
706 | sep = '-'*50 |
---|
707 | for i in range(self.nrow()): |
---|
708 | tm = self._gettime(i) |
---|
709 | src = self._getsourcename(i) |
---|
710 | out += 'Scan[%d] (%s) ' % (self.getscan(i), src) |
---|
711 | out += 'Time[%s]:\n' % (tm) |
---|
712 | if self.nbeam(-1) > 1: |
---|
713 | out += ' Beam[%d] ' % (self.getbeam(i)) |
---|
714 | if self.nif(-1) > 1: out += ' IF[%d] ' % (self.getif(i)) |
---|
715 | if self.npol(-1) > 1: out += ' Pol[%d] ' % (self.getpol(i)) |
---|
716 | outvec.append(callback(i)) |
---|
717 | out += '= %3.3f\n' % (outvec[i]) |
---|
718 | out += sep+'\n' |
---|
719 | |
---|
720 | asaplog.push(sep) |
---|
721 | asaplog.push(" %s" % (label)) |
---|
722 | asaplog.push(sep) |
---|
723 | asaplog.push(out) |
---|
724 | asaplog.post() |
---|
725 | return outvec |
---|
726 | |
---|
727 | def _get_column(self, callback, row=-1): |
---|
728 | """ |
---|
729 | """ |
---|
730 | if row == -1: |
---|
731 | return [callback(i) for i in range(self.nrow())] |
---|
732 | else: |
---|
733 | if 0 <= row < self.nrow(): |
---|
734 | return callback(row) |
---|
735 | |
---|
736 | |
---|
737 | def get_time(self, row=-1, asdatetime=False): |
---|
738 | """\ |
---|
739 | Get a list of time stamps for the observations. |
---|
740 | Return a datetime object or a string (default) for each |
---|
741 | integration time stamp in the scantable. |
---|
742 | |
---|
743 | Parameters: |
---|
744 | |
---|
745 | row: row no of integration. Default -1 return all rows |
---|
746 | |
---|
747 | asdatetime: return values as datetime objects rather than strings |
---|
748 | |
---|
749 | """ |
---|
750 | from time import strptime |
---|
751 | from datetime import datetime |
---|
752 | times = self._get_column(self._gettime, row) |
---|
753 | if not asdatetime: |
---|
754 | return times |
---|
755 | format = "%Y/%m/%d/%H:%M:%S" |
---|
756 | if isinstance(times, list): |
---|
757 | return [datetime(*strptime(i, format)[:6]) for i in times] |
---|
758 | else: |
---|
759 | return datetime(*strptime(times, format)[:6]) |
---|
760 | |
---|
761 | |
---|
762 | def get_inttime(self, row=-1): |
---|
763 | """\ |
---|
764 | Get a list of integration times for the observations. |
---|
765 | Return a time in seconds for each integration in the scantable. |
---|
766 | |
---|
767 | Parameters: |
---|
768 | |
---|
769 | row: row no of integration. Default -1 return all rows. |
---|
770 | |
---|
771 | """ |
---|
772 | return self._get_column(self._getinttime, row) |
---|
773 | |
---|
774 | |
---|
775 | def get_sourcename(self, row=-1): |
---|
776 | """\ |
---|
777 | Get a list source names for the observations. |
---|
778 | Return a string for each integration in the scantable. |
---|
779 | Parameters: |
---|
780 | |
---|
781 | row: row no of integration. Default -1 return all rows. |
---|
782 | |
---|
783 | """ |
---|
784 | return self._get_column(self._getsourcename, row) |
---|
785 | |
---|
786 | def get_elevation(self, row=-1): |
---|
787 | """\ |
---|
788 | Get a list of elevations for the observations. |
---|
789 | Return a float for each integration in the scantable. |
---|
790 | |
---|
791 | Parameters: |
---|
792 | |
---|
793 | row: row no of integration. Default -1 return all rows. |
---|
794 | |
---|
795 | """ |
---|
796 | return self._get_column(self._getelevation, row) |
---|
797 | |
---|
798 | def get_azimuth(self, row=-1): |
---|
799 | """\ |
---|
800 | Get a list of azimuths for the observations. |
---|
801 | Return a float for each integration in the scantable. |
---|
802 | |
---|
803 | Parameters: |
---|
804 | row: row no of integration. Default -1 return all rows. |
---|
805 | |
---|
806 | """ |
---|
807 | return self._get_column(self._getazimuth, row) |
---|
808 | |
---|
809 | def get_parangle(self, row=-1): |
---|
810 | """\ |
---|
811 | Get a list of parallactic angles for the observations. |
---|
812 | Return a float for each integration in the scantable. |
---|
813 | |
---|
814 | Parameters: |
---|
815 | |
---|
816 | row: row no of integration. Default -1 return all rows. |
---|
817 | |
---|
818 | """ |
---|
819 | return self._get_column(self._getparangle, row) |
---|
820 | |
---|
821 | def get_direction(self, row=-1): |
---|
822 | """ |
---|
823 | Get a list of Positions on the sky (direction) for the observations. |
---|
824 | Return a string for each integration in the scantable. |
---|
825 | |
---|
826 | Parameters: |
---|
827 | |
---|
828 | row: row no of integration. Default -1 return all rows |
---|
829 | |
---|
830 | """ |
---|
831 | return self._get_column(self._getdirection, row) |
---|
832 | |
---|
833 | def get_directionval(self, row=-1): |
---|
834 | """\ |
---|
835 | Get a list of Positions on the sky (direction) for the observations. |
---|
836 | Return a float for each integration in the scantable. |
---|
837 | |
---|
838 | Parameters: |
---|
839 | |
---|
840 | row: row no of integration. Default -1 return all rows |
---|
841 | |
---|
842 | """ |
---|
843 | return self._get_column(self._getdirectionvec, row) |
---|
844 | |
---|
845 | @asaplog_post_dec |
---|
846 | def set_unit(self, unit='channel'): |
---|
847 | """\ |
---|
848 | Set the unit for all following operations on this scantable |
---|
849 | |
---|
850 | Parameters: |
---|
851 | |
---|
852 | unit: optional unit, default is 'channel'. Use one of '*Hz', |
---|
853 | 'km/s', 'channel' or equivalent '' |
---|
854 | |
---|
855 | """ |
---|
856 | varlist = vars() |
---|
857 | if unit in ['', 'pixel', 'channel']: |
---|
858 | unit = '' |
---|
859 | inf = list(self._getcoordinfo()) |
---|
860 | inf[0] = unit |
---|
861 | self._setcoordinfo(inf) |
---|
862 | self._add_history("set_unit", varlist) |
---|
863 | |
---|
864 | @asaplog_post_dec |
---|
865 | def set_instrument(self, instr): |
---|
866 | """\ |
---|
867 | Set the instrument for subsequent processing. |
---|
868 | |
---|
869 | Parameters: |
---|
870 | |
---|
871 | instr: Select from 'ATPKSMB', 'ATPKSHOH', 'ATMOPRA', |
---|
872 | 'DSS-43' (Tid), 'CEDUNA', and 'HOBART' |
---|
873 | |
---|
874 | """ |
---|
875 | self._setInstrument(instr) |
---|
876 | self._add_history("set_instument", vars()) |
---|
877 | |
---|
878 | @asaplog_post_dec |
---|
879 | def set_feedtype(self, feedtype): |
---|
880 | """\ |
---|
881 | Overwrite the feed type, which might not be set correctly. |
---|
882 | |
---|
883 | Parameters: |
---|
884 | |
---|
885 | feedtype: 'linear' or 'circular' |
---|
886 | |
---|
887 | """ |
---|
888 | self._setfeedtype(feedtype) |
---|
889 | self._add_history("set_feedtype", vars()) |
---|
890 | |
---|
891 | @asaplog_post_dec |
---|
892 | def set_doppler(self, doppler='RADIO'): |
---|
893 | """\ |
---|
894 | Set the doppler for all following operations on this scantable. |
---|
895 | |
---|
896 | Parameters: |
---|
897 | |
---|
898 | doppler: One of 'RADIO', 'OPTICAL', 'Z', 'BETA', 'GAMMA' |
---|
899 | |
---|
900 | """ |
---|
901 | varlist = vars() |
---|
902 | inf = list(self._getcoordinfo()) |
---|
903 | inf[2] = doppler |
---|
904 | self._setcoordinfo(inf) |
---|
905 | self._add_history("set_doppler", vars()) |
---|
906 | |
---|
907 | @asaplog_post_dec |
---|
908 | def set_freqframe(self, frame=None): |
---|
909 | """\ |
---|
910 | Set the frame type of the Spectral Axis. |
---|
911 | |
---|
912 | Parameters: |
---|
913 | |
---|
914 | frame: an optional frame type, default 'LSRK'. Valid frames are: |
---|
915 | 'TOPO', 'LSRD', 'LSRK', 'BARY', |
---|
916 | 'GEO', 'GALACTO', 'LGROUP', 'CMB' |
---|
917 | |
---|
918 | Example:: |
---|
919 | |
---|
920 | scan.set_freqframe('BARY') |
---|
921 | |
---|
922 | """ |
---|
923 | frame = frame or rcParams['scantable.freqframe'] |
---|
924 | varlist = vars() |
---|
925 | # "REST" is not implemented in casacore |
---|
926 | #valid = ['REST', 'TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
927 | # 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
928 | valid = ['TOPO', 'LSRD', 'LSRK', 'BARY', \ |
---|
929 | 'GEO', 'GALACTO', 'LGROUP', 'CMB'] |
---|
930 | |
---|
931 | if frame in valid: |
---|
932 | inf = list(self._getcoordinfo()) |
---|
933 | inf[1] = frame |
---|
934 | self._setcoordinfo(inf) |
---|
935 | self._add_history("set_freqframe", varlist) |
---|
936 | else: |
---|
937 | msg = "Please specify a valid freq type. Valid types are:\n", valid |
---|
938 | raise TypeError(msg) |
---|
939 | |
---|
940 | @asaplog_post_dec |
---|
941 | def set_dirframe(self, frame=""): |
---|
942 | """\ |
---|
943 | Set the frame type of the Direction on the sky. |
---|
944 | |
---|
945 | Parameters: |
---|
946 | |
---|
947 | frame: an optional frame type, default ''. Valid frames are: |
---|
948 | 'J2000', 'B1950', 'GALACTIC' |
---|
949 | |
---|
950 | Example: |
---|
951 | |
---|
952 | scan.set_dirframe('GALACTIC') |
---|
953 | |
---|
954 | """ |
---|
955 | varlist = vars() |
---|
956 | Scantable.set_dirframe(self, frame) |
---|
957 | self._add_history("set_dirframe", varlist) |
---|
958 | |
---|
959 | def get_unit(self): |
---|
960 | """\ |
---|
961 | Get the default unit set in this scantable |
---|
962 | |
---|
963 | Returns: |
---|
964 | |
---|
965 | A unit string |
---|
966 | |
---|
967 | """ |
---|
968 | inf = self._getcoordinfo() |
---|
969 | unit = inf[0] |
---|
970 | if unit == '': unit = 'channel' |
---|
971 | return unit |
---|
972 | |
---|
973 | @asaplog_post_dec |
---|
974 | def get_abcissa(self, rowno=0): |
---|
975 | """\ |
---|
976 | Get the abcissa in the current coordinate setup for the currently |
---|
977 | selected Beam/IF/Pol |
---|
978 | |
---|
979 | Parameters: |
---|
980 | |
---|
981 | rowno: an optional row number in the scantable. Default is the |
---|
982 | first row, i.e. rowno=0 |
---|
983 | |
---|
984 | Returns: |
---|
985 | |
---|
986 | The abcissa values and the format string (as a dictionary) |
---|
987 | |
---|
988 | """ |
---|
989 | abc = self._getabcissa(rowno) |
---|
990 | lbl = self._getabcissalabel(rowno) |
---|
991 | return abc, lbl |
---|
992 | |
---|
993 | @asaplog_post_dec |
---|
994 | def flag(self, mask=None, unflag=False): |
---|
995 | """\ |
---|
996 | Flag the selected data using an optional channel mask. |
---|
997 | |
---|
998 | Parameters: |
---|
999 | |
---|
1000 | mask: an optional channel mask, created with create_mask. Default |
---|
1001 | (no mask) is all channels. |
---|
1002 | |
---|
1003 | unflag: if True, unflag the data |
---|
1004 | |
---|
1005 | """ |
---|
1006 | varlist = vars() |
---|
1007 | mask = mask or [] |
---|
1008 | self._flag(mask, unflag) |
---|
1009 | self._add_history("flag", varlist) |
---|
1010 | |
---|
1011 | @asaplog_post_dec |
---|
1012 | def flag_row(self, rows=[], unflag=False): |
---|
1013 | """\ |
---|
1014 | Flag the selected data in row-based manner. |
---|
1015 | |
---|
1016 | Parameters: |
---|
1017 | |
---|
1018 | rows: list of row numbers to be flagged. Default is no row |
---|
1019 | (must be explicitly specified to execute row-based flagging). |
---|
1020 | |
---|
1021 | unflag: if True, unflag the data. |
---|
1022 | |
---|
1023 | """ |
---|
1024 | varlist = vars() |
---|
1025 | self._flag_row(rows, unflag) |
---|
1026 | self._add_history("flag_row", varlist) |
---|
1027 | |
---|
1028 | @asaplog_post_dec |
---|
1029 | def clip(self, uthres=None, dthres=None, clipoutside=True, unflag=False): |
---|
1030 | """\ |
---|
1031 | Flag the selected data outside a specified range (in channel-base) |
---|
1032 | |
---|
1033 | Parameters: |
---|
1034 | |
---|
1035 | uthres: upper threshold. |
---|
1036 | |
---|
1037 | dthres: lower threshold |
---|
1038 | |
---|
1039 | clipoutside: True for flagging data outside the range [dthres:uthres]. |
---|
1040 | False for flagging data inside the range. |
---|
1041 | |
---|
1042 | unflag: if True, unflag the data. |
---|
1043 | |
---|
1044 | """ |
---|
1045 | varlist = vars() |
---|
1046 | self._clip(uthres, dthres, clipoutside, unflag) |
---|
1047 | self._add_history("clip", varlist) |
---|
1048 | |
---|
1049 | @asaplog_post_dec |
---|
1050 | def lag_flag(self, start, end, unit="MHz", insitu=None): |
---|
1051 | """\ |
---|
1052 | Flag the data in 'lag' space by providing a frequency to remove. |
---|
1053 | Flagged data in the scantable gets interpolated over the region. |
---|
1054 | No taper is applied. |
---|
1055 | |
---|
1056 | Parameters: |
---|
1057 | |
---|
1058 | start: the start frequency (really a period within the |
---|
1059 | bandwidth) or period to remove |
---|
1060 | |
---|
1061 | end: the end frequency or period to remove |
---|
1062 | |
---|
1063 | unit: the frequency unit (default "MHz") or "" for |
---|
1064 | explicit lag channels |
---|
1065 | |
---|
1066 | *Notes*: |
---|
1067 | |
---|
1068 | It is recommended to flag edges of the band or strong |
---|
1069 | signals beforehand. |
---|
1070 | |
---|
1071 | """ |
---|
1072 | if insitu is None: insitu = rcParams['insitu'] |
---|
1073 | self._math._setinsitu(insitu) |
---|
1074 | varlist = vars() |
---|
1075 | base = { "GHz": 1000000000., "MHz": 1000000., "kHz": 1000., "Hz": 1.} |
---|
1076 | if not (unit == "" or base.has_key(unit)): |
---|
1077 | raise ValueError("%s is not a valid unit." % unit) |
---|
1078 | if unit == "": |
---|
1079 | s = scantable(self._math._lag_flag(self, start, end, "lags")) |
---|
1080 | else: |
---|
1081 | s = scantable(self._math._lag_flag(self, start*base[unit], |
---|
1082 | end*base[unit], "frequency")) |
---|
1083 | s._add_history("lag_flag", varlist) |
---|
1084 | if insitu: |
---|
1085 | self._assign(s) |
---|
1086 | else: |
---|
1087 | return s |
---|
1088 | |
---|
1089 | @asaplog_post_dec |
---|
1090 | def create_mask(self, *args, **kwargs): |
---|
1091 | """\ |
---|
1092 | Compute and return a mask based on [min, max] windows. |
---|
1093 | The specified windows are to be INCLUDED, when the mask is |
---|
1094 | applied. |
---|
1095 | |
---|
1096 | Parameters: |
---|
1097 | |
---|
1098 | [min, max], [min2, max2], ... |
---|
1099 | Pairs of start/end points (inclusive)specifying the regions |
---|
1100 | to be masked |
---|
1101 | |
---|
1102 | invert: optional argument. If specified as True, |
---|
1103 | return an inverted mask, i.e. the regions |
---|
1104 | specified are EXCLUDED |
---|
1105 | |
---|
1106 | row: create the mask using the specified row for |
---|
1107 | unit conversions, default is row=0 |
---|
1108 | only necessary if frequency varies over rows. |
---|
1109 | |
---|
1110 | Examples:: |
---|
1111 | |
---|
1112 | scan.set_unit('channel') |
---|
1113 | # a) |
---|
1114 | msk = scan.create_mask([400, 500], [800, 900]) |
---|
1115 | # masks everything outside 400 and 500 |
---|
1116 | # and 800 and 900 in the unit 'channel' |
---|
1117 | |
---|
1118 | # b) |
---|
1119 | msk = scan.create_mask([400, 500], [800, 900], invert=True) |
---|
1120 | # masks the regions between 400 and 500 |
---|
1121 | # and 800 and 900 in the unit 'channel' |
---|
1122 | |
---|
1123 | # c) |
---|
1124 | #mask only channel 400 |
---|
1125 | msk = scan.create_mask([400]) |
---|
1126 | |
---|
1127 | """ |
---|
1128 | row = kwargs.get("row", 0) |
---|
1129 | data = self._getabcissa(row) |
---|
1130 | u = self._getcoordinfo()[0] |
---|
1131 | if u == "": |
---|
1132 | u = "channel" |
---|
1133 | msg = "The current mask window unit is %s" % u |
---|
1134 | i = self._check_ifs() |
---|
1135 | if not i: |
---|
1136 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
1137 | asaplog.push(msg) |
---|
1138 | n = self.nchan() |
---|
1139 | msk = _n_bools(n, False) |
---|
1140 | # test if args is a 'list' or a 'normal *args - UGLY!!! |
---|
1141 | |
---|
1142 | ws = (isinstance(args[-1][-1], int) or isinstance(args[-1][-1], float)) \ |
---|
1143 | and args or args[0] |
---|
1144 | for window in ws: |
---|
1145 | if len(window) == 1: |
---|
1146 | window = [window[0], window[0]] |
---|
1147 | if len(window) == 0 or len(window) > 2: |
---|
1148 | raise ValueError("A window needs to be defined as [start(, end)]") |
---|
1149 | if window[0] > window[1]: |
---|
1150 | tmp = window[0] |
---|
1151 | window[0] = window[1] |
---|
1152 | window[1] = tmp |
---|
1153 | for i in range(n): |
---|
1154 | if data[i] >= window[0] and data[i] <= window[1]: |
---|
1155 | msk[i] = True |
---|
1156 | if kwargs.has_key('invert'): |
---|
1157 | if kwargs.get('invert'): |
---|
1158 | msk = mask_not(msk) |
---|
1159 | return msk |
---|
1160 | |
---|
1161 | def get_masklist(self, mask=None, row=0, silent=False): |
---|
1162 | """\ |
---|
1163 | Compute and return a list of mask windows, [min, max]. |
---|
1164 | |
---|
1165 | Parameters: |
---|
1166 | |
---|
1167 | mask: channel mask, created with create_mask. |
---|
1168 | |
---|
1169 | row: calcutate the masklist using the specified row |
---|
1170 | for unit conversions, default is row=0 |
---|
1171 | only necessary if frequency varies over rows. |
---|
1172 | |
---|
1173 | Returns: |
---|
1174 | |
---|
1175 | [min, max], [min2, max2], ... |
---|
1176 | Pairs of start/end points (inclusive)specifying |
---|
1177 | the masked regions |
---|
1178 | |
---|
1179 | """ |
---|
1180 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
1181 | raise TypeError("The mask should be list or tuple.") |
---|
1182 | if len(mask) < 2: |
---|
1183 | raise TypeError("The mask elements should be > 1") |
---|
1184 | if self.nchan() != len(mask): |
---|
1185 | msg = "Number of channels in scantable != number of mask elements" |
---|
1186 | raise TypeError(msg) |
---|
1187 | data = self._getabcissa(row) |
---|
1188 | u = self._getcoordinfo()[0] |
---|
1189 | if u == "": |
---|
1190 | u = "channel" |
---|
1191 | msg = "The current mask window unit is %s" % u |
---|
1192 | i = self._check_ifs() |
---|
1193 | if not i: |
---|
1194 | msg += "\nThis mask is only valid for IF=%d" % (self.getif(i)) |
---|
1195 | if not silent: |
---|
1196 | asaplog.push(msg) |
---|
1197 | masklist=[] |
---|
1198 | ist, ien = None, None |
---|
1199 | ist, ien=self.get_mask_indices(mask) |
---|
1200 | if ist is not None and ien is not None: |
---|
1201 | for i in xrange(len(ist)): |
---|
1202 | range=[data[ist[i]],data[ien[i]]] |
---|
1203 | range.sort() |
---|
1204 | masklist.append([range[0],range[1]]) |
---|
1205 | return masklist |
---|
1206 | |
---|
1207 | def get_mask_indices(self, mask=None): |
---|
1208 | """\ |
---|
1209 | Compute and Return lists of mask start indices and mask end indices. |
---|
1210 | |
---|
1211 | Parameters: |
---|
1212 | |
---|
1213 | mask: channel mask, created with create_mask. |
---|
1214 | |
---|
1215 | Returns: |
---|
1216 | |
---|
1217 | List of mask start indices and that of mask end indices, |
---|
1218 | i.e., [istart1,istart2,....], [iend1,iend2,....]. |
---|
1219 | |
---|
1220 | """ |
---|
1221 | if not (isinstance(mask,list) or isinstance(mask, tuple)): |
---|
1222 | raise TypeError("The mask should be list or tuple.") |
---|
1223 | if len(mask) < 2: |
---|
1224 | raise TypeError("The mask elements should be > 1") |
---|
1225 | istart=[] |
---|
1226 | iend=[] |
---|
1227 | if mask[0]: istart.append(0) |
---|
1228 | for i in range(len(mask)-1): |
---|
1229 | if not mask[i] and mask[i+1]: |
---|
1230 | istart.append(i+1) |
---|
1231 | elif mask[i] and not mask[i+1]: |
---|
1232 | iend.append(i) |
---|
1233 | if mask[len(mask)-1]: iend.append(len(mask)-1) |
---|
1234 | if len(istart) != len(iend): |
---|
1235 | raise RuntimeError("Numbers of mask start != mask end.") |
---|
1236 | for i in range(len(istart)): |
---|
1237 | if istart[i] > iend[i]: |
---|
1238 | raise RuntimeError("Mask start index > mask end index") |
---|
1239 | break |
---|
1240 | return istart,iend |
---|
1241 | |
---|
1242 | # def get_restfreqs(self): |
---|
1243 | # """ |
---|
1244 | # Get the restfrequency(s) stored in this scantable. |
---|
1245 | # The return value(s) are always of unit 'Hz' |
---|
1246 | # Parameters: |
---|
1247 | # none |
---|
1248 | # Returns: |
---|
1249 | # a list of doubles |
---|
1250 | # """ |
---|
1251 | # return list(self._getrestfreqs()) |
---|
1252 | |
---|
1253 | def get_restfreqs(self, ids=None): |
---|
1254 | """\ |
---|
1255 | Get the restfrequency(s) stored in this scantable. |
---|
1256 | The return value(s) are always of unit 'Hz' |
---|
1257 | |
---|
1258 | Parameters: |
---|
1259 | |
---|
1260 | ids: (optional) a list of MOLECULE_ID for that restfrequency(s) to |
---|
1261 | be retrieved |
---|
1262 | |
---|
1263 | Returns: |
---|
1264 | |
---|
1265 | dictionary containing ids and a list of doubles for each id |
---|
1266 | |
---|
1267 | """ |
---|
1268 | if ids is None: |
---|
1269 | rfreqs={} |
---|
1270 | idlist = self.getmolnos() |
---|
1271 | for i in idlist: |
---|
1272 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
1273 | return rfreqs |
---|
1274 | else: |
---|
1275 | if type(ids)==list or type(ids)==tuple: |
---|
1276 | rfreqs={} |
---|
1277 | for i in ids: |
---|
1278 | rfreqs[i]=list(self._getrestfreqs(i)) |
---|
1279 | return rfreqs |
---|
1280 | else: |
---|
1281 | return list(self._getrestfreqs(ids)) |
---|
1282 | #return list(self._getrestfreqs(ids)) |
---|
1283 | |
---|
1284 | def set_restfreqs(self, freqs=None, unit='Hz'): |
---|
1285 | """\ |
---|
1286 | Set or replace the restfrequency specified and |
---|
1287 | if the 'freqs' argument holds a scalar, |
---|
1288 | then that rest frequency will be applied to all the selected |
---|
1289 | data. If the 'freqs' argument holds |
---|
1290 | a vector, then it MUST be of equal or smaller length than |
---|
1291 | the number of IFs (and the available restfrequencies will be |
---|
1292 | replaced by this vector). In this case, *all* data have |
---|
1293 | the restfrequency set per IF according |
---|
1294 | to the corresponding value you give in the 'freqs' vector. |
---|
1295 | E.g. 'freqs=[1e9, 2e9]' would mean IF 0 gets restfreq 1e9 and |
---|
1296 | IF 1 gets restfreq 2e9. |
---|
1297 | |
---|
1298 | You can also specify the frequencies via a linecatalog. |
---|
1299 | |
---|
1300 | Parameters: |
---|
1301 | |
---|
1302 | freqs: list of rest frequency values or string idenitfiers |
---|
1303 | |
---|
1304 | unit: unit for rest frequency (default 'Hz') |
---|
1305 | |
---|
1306 | |
---|
1307 | Example:: |
---|
1308 | |
---|
1309 | # set the given restfrequency for the all currently selected IFs |
---|
1310 | scan.set_restfreqs(freqs=1.4e9) |
---|
1311 | # set restfrequencies for the n IFs (n > 1) in the order of the |
---|
1312 | # list, i.e |
---|
1313 | # IF0 -> 1.4e9, IF1 -> 1.41e9, IF3 -> 1.42e9 |
---|
1314 | # len(list_of_restfreqs) == nIF |
---|
1315 | # for nIF == 1 the following will set multiple restfrequency for |
---|
1316 | # that IF |
---|
1317 | scan.set_restfreqs(freqs=[1.4e9, 1.41e9, 1.42e9]) |
---|
1318 | # set multiple restfrequencies per IF. as a list of lists where |
---|
1319 | # the outer list has nIF elements, the inner s arbitrary |
---|
1320 | scan.set_restfreqs(freqs=[[1.4e9, 1.41e9], [1.67e9]]) |
---|
1321 | |
---|
1322 | *Note*: |
---|
1323 | |
---|
1324 | To do more sophisticate Restfrequency setting, e.g. on a |
---|
1325 | source and IF basis, use scantable.set_selection() before using |
---|
1326 | this function:: |
---|
1327 | |
---|
1328 | # provided your scantable is called scan |
---|
1329 | selection = selector() |
---|
1330 | selection.set_name("ORION*") |
---|
1331 | selection.set_ifs([1]) |
---|
1332 | scan.set_selection(selection) |
---|
1333 | scan.set_restfreqs(freqs=86.6e9) |
---|
1334 | |
---|
1335 | """ |
---|
1336 | varlist = vars() |
---|
1337 | from asap import linecatalog |
---|
1338 | # simple value |
---|
1339 | if isinstance(freqs, int) or isinstance(freqs, float): |
---|
1340 | self._setrestfreqs([freqs], [""], unit) |
---|
1341 | # list of values |
---|
1342 | elif isinstance(freqs, list) or isinstance(freqs, tuple): |
---|
1343 | # list values are scalars |
---|
1344 | if isinstance(freqs[-1], int) or isinstance(freqs[-1], float): |
---|
1345 | if len(freqs) == 1: |
---|
1346 | self._setrestfreqs(freqs, [""], unit) |
---|
1347 | else: |
---|
1348 | # allow the 'old' mode of setting mulitple IFs |
---|
1349 | sel = selector() |
---|
1350 | savesel = self._getselection() |
---|
1351 | iflist = self.getifnos() |
---|
1352 | if len(freqs)>len(iflist): |
---|
1353 | raise ValueError("number of elements in list of list " |
---|
1354 | "exeeds the current IF selections") |
---|
1355 | iflist = self.getifnos() |
---|
1356 | for i, fval in enumerate(freqs): |
---|
1357 | sel.set_ifs(iflist[i]) |
---|
1358 | self._setselection(sel) |
---|
1359 | self._setrestfreqs([fval], [""], unit) |
---|
1360 | self._setselection(savesel) |
---|
1361 | |
---|
1362 | # list values are dict, {'value'=, 'name'=) |
---|
1363 | elif isinstance(freqs[-1], dict): |
---|
1364 | values = [] |
---|
1365 | names = [] |
---|
1366 | for d in freqs: |
---|
1367 | values.append(d["value"]) |
---|
1368 | names.append(d["name"]) |
---|
1369 | self._setrestfreqs(values, names, unit) |
---|
1370 | elif isinstance(freqs[-1], list) or isinstance(freqs[-1], tuple): |
---|
1371 | sel = selector() |
---|
1372 | savesel = self._getselection() |
---|
1373 | iflist = self.getifnos() |
---|
1374 | if len(freqs)>len(iflist): |
---|
1375 | raise ValueError("number of elements in list of list exeeds" |
---|
1376 | " the current IF selections") |
---|
1377 | for i, fval in enumerate(freqs): |
---|
1378 | sel.set_ifs(iflist[i]) |
---|
1379 | self._setselection(sel) |
---|
1380 | self._setrestfreqs(fval, [""], unit) |
---|
1381 | self._setselection(savesel) |
---|
1382 | # freqs are to be taken from a linecatalog |
---|
1383 | elif isinstance(freqs, linecatalog): |
---|
1384 | sel = selector() |
---|
1385 | savesel = self._getselection() |
---|
1386 | for i in xrange(freqs.nrow()): |
---|
1387 | sel.set_ifs(iflist[i]) |
---|
1388 | self._setselection(sel) |
---|
1389 | self._setrestfreqs([freqs.get_frequency(i)], |
---|
1390 | [freqs.get_name(i)], "MHz") |
---|
1391 | # ensure that we are not iterating past nIF |
---|
1392 | if i == self.nif()-1: break |
---|
1393 | self._setselection(savesel) |
---|
1394 | else: |
---|
1395 | return |
---|
1396 | self._add_history("set_restfreqs", varlist) |
---|
1397 | |
---|
1398 | def shift_refpix(self, delta): |
---|
1399 | """\ |
---|
1400 | Shift the reference pixel of the Spectra Coordinate by an |
---|
1401 | integer amount. |
---|
1402 | |
---|
1403 | Parameters: |
---|
1404 | |
---|
1405 | delta: the amount to shift by |
---|
1406 | |
---|
1407 | *Note*: |
---|
1408 | |
---|
1409 | Be careful using this with broadband data. |
---|
1410 | |
---|
1411 | """ |
---|
1412 | Scantable.shift_refpix(self, delta) |
---|
1413 | |
---|
1414 | @asaplog_post_dec |
---|
1415 | def history(self, filename=None): |
---|
1416 | """\ |
---|
1417 | Print the history. Optionally to a file. |
---|
1418 | |
---|
1419 | Parameters: |
---|
1420 | |
---|
1421 | filename: The name of the file to save the history to. |
---|
1422 | |
---|
1423 | """ |
---|
1424 | hist = list(self._gethistory()) |
---|
1425 | out = "-"*80 |
---|
1426 | for h in hist: |
---|
1427 | if h.startswith("---"): |
---|
1428 | out = "\n".join([out, h]) |
---|
1429 | else: |
---|
1430 | items = h.split("##") |
---|
1431 | date = items[0] |
---|
1432 | func = items[1] |
---|
1433 | items = items[2:] |
---|
1434 | out += "\n"+date+"\n" |
---|
1435 | out += "Function: %s\n Parameters:" % (func) |
---|
1436 | for i in items: |
---|
1437 | if i == '': |
---|
1438 | continue |
---|
1439 | s = i.split("=") |
---|
1440 | out += "\n %s = %s" % (s[0], s[1]) |
---|
1441 | out = "\n".join([out, "-"*80]) |
---|
1442 | if filename is not None: |
---|
1443 | if filename is "": |
---|
1444 | filename = 'scantable_history.txt' |
---|
1445 | import os |
---|
1446 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
1447 | if not os.path.isdir(filename): |
---|
1448 | data = open(filename, 'w') |
---|
1449 | data.write(out) |
---|
1450 | data.close() |
---|
1451 | else: |
---|
1452 | msg = "Illegal file name '%s'." % (filename) |
---|
1453 | raise IOError(msg) |
---|
1454 | return page(out) |
---|
1455 | # |
---|
1456 | # Maths business |
---|
1457 | # |
---|
1458 | @asaplog_post_dec |
---|
1459 | def average_time(self, mask=None, scanav=False, weight='tint', align=False): |
---|
1460 | """\ |
---|
1461 | Return the (time) weighted average of a scan. |
---|
1462 | |
---|
1463 | *Note*: |
---|
1464 | |
---|
1465 | in channels only - align if necessary |
---|
1466 | |
---|
1467 | Parameters: |
---|
1468 | |
---|
1469 | mask: an optional mask (only used for 'var' and 'tsys' |
---|
1470 | weighting) |
---|
1471 | |
---|
1472 | scanav: True averages each scan separately |
---|
1473 | False (default) averages all scans together, |
---|
1474 | |
---|
1475 | weight: Weighting scheme. |
---|
1476 | 'none' (mean no weight) |
---|
1477 | 'var' (1/var(spec) weighted) |
---|
1478 | 'tsys' (1/Tsys**2 weighted) |
---|
1479 | 'tint' (integration time weighted) |
---|
1480 | 'tintsys' (Tint/Tsys**2) |
---|
1481 | 'median' ( median averaging) |
---|
1482 | The default is 'tint' |
---|
1483 | |
---|
1484 | align: align the spectra in velocity before averaging. It takes |
---|
1485 | the time of the first spectrum as reference time. |
---|
1486 | |
---|
1487 | Example:: |
---|
1488 | |
---|
1489 | # time average the scantable without using a mask |
---|
1490 | newscan = scan.average_time() |
---|
1491 | |
---|
1492 | """ |
---|
1493 | varlist = vars() |
---|
1494 | weight = weight or 'TINT' |
---|
1495 | mask = mask or () |
---|
1496 | scanav = (scanav and 'SCAN') or 'NONE' |
---|
1497 | scan = (self, ) |
---|
1498 | |
---|
1499 | if align: |
---|
1500 | scan = (self.freq_align(insitu=False), ) |
---|
1501 | s = None |
---|
1502 | if weight.upper() == 'MEDIAN': |
---|
1503 | s = scantable(self._math._averagechannel(scan[0], 'MEDIAN', |
---|
1504 | scanav)) |
---|
1505 | else: |
---|
1506 | s = scantable(self._math._average(scan, mask, weight.upper(), |
---|
1507 | scanav)) |
---|
1508 | s._add_history("average_time", varlist) |
---|
1509 | return s |
---|
1510 | |
---|
1511 | @asaplog_post_dec |
---|
1512 | def convert_flux(self, jyperk=None, eta=None, d=None, insitu=None): |
---|
1513 | """\ |
---|
1514 | Return a scan where all spectra are converted to either |
---|
1515 | Jansky or Kelvin depending upon the flux units of the scan table. |
---|
1516 | By default the function tries to look the values up internally. |
---|
1517 | If it can't find them (or if you want to over-ride), you must |
---|
1518 | specify EITHER jyperk OR eta (and D which it will try to look up |
---|
1519 | also if you don't set it). jyperk takes precedence if you set both. |
---|
1520 | |
---|
1521 | Parameters: |
---|
1522 | |
---|
1523 | jyperk: the Jy / K conversion factor |
---|
1524 | |
---|
1525 | eta: the aperture efficiency |
---|
1526 | |
---|
1527 | d: the geometric diameter (metres) |
---|
1528 | |
---|
1529 | insitu: if False a new scantable is returned. |
---|
1530 | Otherwise, the scaling is done in-situ |
---|
1531 | The default is taken from .asaprc (False) |
---|
1532 | |
---|
1533 | """ |
---|
1534 | if insitu is None: insitu = rcParams['insitu'] |
---|
1535 | self._math._setinsitu(insitu) |
---|
1536 | varlist = vars() |
---|
1537 | jyperk = jyperk or -1.0 |
---|
1538 | d = d or -1.0 |
---|
1539 | eta = eta or -1.0 |
---|
1540 | s = scantable(self._math._convertflux(self, d, eta, jyperk)) |
---|
1541 | s._add_history("convert_flux", varlist) |
---|
1542 | if insitu: self._assign(s) |
---|
1543 | else: return s |
---|
1544 | |
---|
1545 | @asaplog_post_dec |
---|
1546 | def gain_el(self, poly=None, filename="", method="linear", insitu=None): |
---|
1547 | """\ |
---|
1548 | Return a scan after applying a gain-elevation correction. |
---|
1549 | The correction can be made via either a polynomial or a |
---|
1550 | table-based interpolation (and extrapolation if necessary). |
---|
1551 | You specify polynomial coefficients, an ascii table or neither. |
---|
1552 | If you specify neither, then a polynomial correction will be made |
---|
1553 | with built in coefficients known for certain telescopes (an error |
---|
1554 | will occur if the instrument is not known). |
---|
1555 | The data and Tsys are *divided* by the scaling factors. |
---|
1556 | |
---|
1557 | Parameters: |
---|
1558 | |
---|
1559 | poly: Polynomial coefficients (default None) to compute a |
---|
1560 | gain-elevation correction as a function of |
---|
1561 | elevation (in degrees). |
---|
1562 | |
---|
1563 | filename: The name of an ascii file holding correction factors. |
---|
1564 | The first row of the ascii file must give the column |
---|
1565 | names and these MUST include columns |
---|
1566 | "ELEVATION" (degrees) and "FACTOR" (multiply data |
---|
1567 | by this) somewhere. |
---|
1568 | The second row must give the data type of the |
---|
1569 | column. Use 'R' for Real and 'I' for Integer. |
---|
1570 | An example file would be |
---|
1571 | (actual factors are arbitrary) : |
---|
1572 | |
---|
1573 | TIME ELEVATION FACTOR |
---|
1574 | R R R |
---|
1575 | 0.1 0 0.8 |
---|
1576 | 0.2 20 0.85 |
---|
1577 | 0.3 40 0.9 |
---|
1578 | 0.4 60 0.85 |
---|
1579 | 0.5 80 0.8 |
---|
1580 | 0.6 90 0.75 |
---|
1581 | |
---|
1582 | method: Interpolation method when correcting from a table. |
---|
1583 | Values are "nearest", "linear" (default), "cubic" |
---|
1584 | and "spline" |
---|
1585 | |
---|
1586 | insitu: if False a new scantable is returned. |
---|
1587 | Otherwise, the scaling is done in-situ |
---|
1588 | The default is taken from .asaprc (False) |
---|
1589 | |
---|
1590 | """ |
---|
1591 | |
---|
1592 | if insitu is None: insitu = rcParams['insitu'] |
---|
1593 | self._math._setinsitu(insitu) |
---|
1594 | varlist = vars() |
---|
1595 | poly = poly or () |
---|
1596 | from os.path import expandvars |
---|
1597 | filename = expandvars(filename) |
---|
1598 | s = scantable(self._math._gainel(self, poly, filename, method)) |
---|
1599 | s._add_history("gain_el", varlist) |
---|
1600 | if insitu: |
---|
1601 | self._assign(s) |
---|
1602 | else: |
---|
1603 | return s |
---|
1604 | |
---|
1605 | @asaplog_post_dec |
---|
1606 | def freq_align(self, reftime=None, method='cubic', insitu=None): |
---|
1607 | """\ |
---|
1608 | Return a scan where all rows have been aligned in frequency/velocity. |
---|
1609 | The alignment frequency frame (e.g. LSRK) is that set by function |
---|
1610 | set_freqframe. |
---|
1611 | |
---|
1612 | Parameters: |
---|
1613 | |
---|
1614 | reftime: reference time to align at. By default, the time of |
---|
1615 | the first row of data is used. |
---|
1616 | |
---|
1617 | method: Interpolation method for regridding the spectra. |
---|
1618 | Choose from "nearest", "linear", "cubic" (default) |
---|
1619 | and "spline" |
---|
1620 | |
---|
1621 | insitu: if False a new scantable is returned. |
---|
1622 | Otherwise, the scaling is done in-situ |
---|
1623 | The default is taken from .asaprc (False) |
---|
1624 | |
---|
1625 | """ |
---|
1626 | if insitu is None: insitu = rcParams["insitu"] |
---|
1627 | self._math._setinsitu(insitu) |
---|
1628 | varlist = vars() |
---|
1629 | reftime = reftime or "" |
---|
1630 | s = scantable(self._math._freq_align(self, reftime, method)) |
---|
1631 | s._add_history("freq_align", varlist) |
---|
1632 | if insitu: self._assign(s) |
---|
1633 | else: return s |
---|
1634 | |
---|
1635 | @asaplog_post_dec |
---|
1636 | def opacity(self, tau=None, insitu=None): |
---|
1637 | """\ |
---|
1638 | Apply an opacity correction. The data |
---|
1639 | and Tsys are multiplied by the correction factor. |
---|
1640 | |
---|
1641 | Parameters: |
---|
1642 | |
---|
1643 | tau: (list of) opacity from which the correction factor is |
---|
1644 | exp(tau*ZD) |
---|
1645 | where ZD is the zenith-distance. |
---|
1646 | If a list is provided, it has to be of length nIF, |
---|
1647 | nIF*nPol or 1 and in order of IF/POL, e.g. |
---|
1648 | [opif0pol0, opif0pol1, opif1pol0 ...] |
---|
1649 | if tau is `None` the opacities are determined from a |
---|
1650 | model. |
---|
1651 | |
---|
1652 | insitu: if False a new scantable is returned. |
---|
1653 | Otherwise, the scaling is done in-situ |
---|
1654 | The default is taken from .asaprc (False) |
---|
1655 | |
---|
1656 | """ |
---|
1657 | if insitu is None: insitu = rcParams['insitu'] |
---|
1658 | self._math._setinsitu(insitu) |
---|
1659 | varlist = vars() |
---|
1660 | if not hasattr(tau, "__len__"): |
---|
1661 | tau = [tau] |
---|
1662 | s = scantable(self._math._opacity(self, tau)) |
---|
1663 | s._add_history("opacity", varlist) |
---|
1664 | if insitu: self._assign(s) |
---|
1665 | else: return s |
---|
1666 | |
---|
1667 | @asaplog_post_dec |
---|
1668 | def bin(self, width=5, insitu=None): |
---|
1669 | """\ |
---|
1670 | Return a scan where all spectra have been binned up. |
---|
1671 | |
---|
1672 | Parameters: |
---|
1673 | |
---|
1674 | width: The bin width (default=5) in pixels |
---|
1675 | |
---|
1676 | insitu: if False a new scantable is returned. |
---|
1677 | Otherwise, the scaling is done in-situ |
---|
1678 | The default is taken from .asaprc (False) |
---|
1679 | |
---|
1680 | """ |
---|
1681 | if insitu is None: insitu = rcParams['insitu'] |
---|
1682 | self._math._setinsitu(insitu) |
---|
1683 | varlist = vars() |
---|
1684 | s = scantable(self._math._bin(self, width)) |
---|
1685 | s._add_history("bin", varlist) |
---|
1686 | if insitu: |
---|
1687 | self._assign(s) |
---|
1688 | else: |
---|
1689 | return s |
---|
1690 | |
---|
1691 | @asaplog_post_dec |
---|
1692 | def resample(self, width=5, method='cubic', insitu=None): |
---|
1693 | """\ |
---|
1694 | Return a scan where all spectra have been binned up. |
---|
1695 | |
---|
1696 | Parameters: |
---|
1697 | |
---|
1698 | width: The bin width (default=5) in pixels |
---|
1699 | |
---|
1700 | method: Interpolation method when correcting from a table. |
---|
1701 | Values are "nearest", "linear", "cubic" (default) |
---|
1702 | and "spline" |
---|
1703 | |
---|
1704 | insitu: if False a new scantable is returned. |
---|
1705 | Otherwise, the scaling is done in-situ |
---|
1706 | The default is taken from .asaprc (False) |
---|
1707 | |
---|
1708 | """ |
---|
1709 | if insitu is None: insitu = rcParams['insitu'] |
---|
1710 | self._math._setinsitu(insitu) |
---|
1711 | varlist = vars() |
---|
1712 | s = scantable(self._math._resample(self, method, width)) |
---|
1713 | s._add_history("resample", varlist) |
---|
1714 | if insitu: self._assign(s) |
---|
1715 | else: return s |
---|
1716 | |
---|
1717 | @asaplog_post_dec |
---|
1718 | def average_pol(self, mask=None, weight='none'): |
---|
1719 | """\ |
---|
1720 | Average the Polarisations together. |
---|
1721 | |
---|
1722 | Parameters: |
---|
1723 | |
---|
1724 | mask: An optional mask defining the region, where the |
---|
1725 | averaging will be applied. The output will have all |
---|
1726 | specified points masked. |
---|
1727 | |
---|
1728 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
1729 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
1730 | |
---|
1731 | """ |
---|
1732 | varlist = vars() |
---|
1733 | mask = mask or () |
---|
1734 | s = scantable(self._math._averagepol(self, mask, weight.upper())) |
---|
1735 | s._add_history("average_pol", varlist) |
---|
1736 | return s |
---|
1737 | |
---|
1738 | @asaplog_post_dec |
---|
1739 | def average_beam(self, mask=None, weight='none'): |
---|
1740 | """\ |
---|
1741 | Average the Beams together. |
---|
1742 | |
---|
1743 | Parameters: |
---|
1744 | mask: An optional mask defining the region, where the |
---|
1745 | averaging will be applied. The output will have all |
---|
1746 | specified points masked. |
---|
1747 | |
---|
1748 | weight: Weighting scheme. 'none' (default), 'var' (1/var(spec) |
---|
1749 | weighted), or 'tsys' (1/Tsys**2 weighted) |
---|
1750 | |
---|
1751 | """ |
---|
1752 | varlist = vars() |
---|
1753 | mask = mask or () |
---|
1754 | s = scantable(self._math._averagebeams(self, mask, weight.upper())) |
---|
1755 | s._add_history("average_beam", varlist) |
---|
1756 | return s |
---|
1757 | |
---|
1758 | def parallactify(self, pflag): |
---|
1759 | """\ |
---|
1760 | Set a flag to indicate whether this data should be treated as having |
---|
1761 | been 'parallactified' (total phase == 0.0) |
---|
1762 | |
---|
1763 | Parameters: |
---|
1764 | |
---|
1765 | pflag: Bool indicating whether to turn this on (True) or |
---|
1766 | off (False) |
---|
1767 | |
---|
1768 | """ |
---|
1769 | varlist = vars() |
---|
1770 | self._parallactify(pflag) |
---|
1771 | self._add_history("parallactify", varlist) |
---|
1772 | |
---|
1773 | @asaplog_post_dec |
---|
1774 | def convert_pol(self, poltype=None): |
---|
1775 | """\ |
---|
1776 | Convert the data to a different polarisation type. |
---|
1777 | Note that you will need cross-polarisation terms for most conversions. |
---|
1778 | |
---|
1779 | Parameters: |
---|
1780 | |
---|
1781 | poltype: The new polarisation type. Valid types are: |
---|
1782 | "linear", "circular", "stokes" and "linpol" |
---|
1783 | |
---|
1784 | """ |
---|
1785 | varlist = vars() |
---|
1786 | s = scantable(self._math._convertpol(self, poltype)) |
---|
1787 | s._add_history("convert_pol", varlist) |
---|
1788 | return s |
---|
1789 | |
---|
1790 | @asaplog_post_dec |
---|
1791 | def smooth(self, kernel="hanning", width=5.0, order=2, plot=False, insitu=None): |
---|
1792 | """\ |
---|
1793 | Smooth the spectrum by the specified kernel (conserving flux). |
---|
1794 | |
---|
1795 | Parameters: |
---|
1796 | |
---|
1797 | kernel: The type of smoothing kernel. Select from |
---|
1798 | 'hanning' (default), 'gaussian', 'boxcar', 'rmedian' |
---|
1799 | or 'poly' |
---|
1800 | |
---|
1801 | width: The width of the kernel in pixels. For hanning this is |
---|
1802 | ignored otherwise it defauls to 5 pixels. |
---|
1803 | For 'gaussian' it is the Full Width Half |
---|
1804 | Maximum. For 'boxcar' it is the full width. |
---|
1805 | For 'rmedian' and 'poly' it is the half width. |
---|
1806 | |
---|
1807 | order: Optional parameter for 'poly' kernel (default is 2), to |
---|
1808 | specify the order of the polnomial. Ignored by all other |
---|
1809 | kernels. |
---|
1810 | |
---|
1811 | plot: plot the original and the smoothed spectra. |
---|
1812 | In this each indivual fit has to be approved, by |
---|
1813 | typing 'y' or 'n' |
---|
1814 | |
---|
1815 | insitu: if False a new scantable is returned. |
---|
1816 | Otherwise, the scaling is done in-situ |
---|
1817 | The default is taken from .asaprc (False) |
---|
1818 | |
---|
1819 | """ |
---|
1820 | if insitu is None: insitu = rcParams['insitu'] |
---|
1821 | self._math._setinsitu(insitu) |
---|
1822 | varlist = vars() |
---|
1823 | |
---|
1824 | if plot: orgscan = self.copy() |
---|
1825 | |
---|
1826 | s = scantable(self._math._smooth(self, kernel.lower(), width, order)) |
---|
1827 | s._add_history("smooth", varlist) |
---|
1828 | |
---|
1829 | if plot: |
---|
1830 | if rcParams['plotter.gui']: |
---|
1831 | from asap.asaplotgui import asaplotgui as asaplot |
---|
1832 | else: |
---|
1833 | from asap.asaplot import asaplot |
---|
1834 | self._p=asaplot() |
---|
1835 | self._p.set_panels() |
---|
1836 | ylab=s._get_ordinate_label() |
---|
1837 | #self._p.palette(0,["#777777","red"]) |
---|
1838 | for r in xrange(s.nrow()): |
---|
1839 | xsm=s._getabcissa(r) |
---|
1840 | ysm=s._getspectrum(r) |
---|
1841 | xorg=orgscan._getabcissa(r) |
---|
1842 | yorg=orgscan._getspectrum(r) |
---|
1843 | self._p.clear() |
---|
1844 | self._p.hold() |
---|
1845 | self._p.set_axes('ylabel',ylab) |
---|
1846 | self._p.set_axes('xlabel',s._getabcissalabel(r)) |
---|
1847 | self._p.set_axes('title',s._getsourcename(r)) |
---|
1848 | self._p.set_line(label='Original',color="#777777") |
---|
1849 | self._p.plot(xorg,yorg) |
---|
1850 | self._p.set_line(label='Smoothed',color="red") |
---|
1851 | self._p.plot(xsm,ysm) |
---|
1852 | ### Ugly part for legend |
---|
1853 | for i in [0,1]: |
---|
1854 | self._p.subplots[0]['lines'].append([self._p.subplots[0]['axes'].lines[i]]) |
---|
1855 | self._p.release() |
---|
1856 | ### Ugly part for legend |
---|
1857 | self._p.subplots[0]['lines']=[] |
---|
1858 | res = raw_input("Accept smoothing ([y]/n): ") |
---|
1859 | if res.upper() == 'N': |
---|
1860 | s._setspectrum(yorg, r) |
---|
1861 | self._p.unmap() |
---|
1862 | self._p = None |
---|
1863 | del orgscan |
---|
1864 | |
---|
1865 | if insitu: self._assign(s) |
---|
1866 | else: return s |
---|
1867 | |
---|
1868 | @asaplog_post_dec |
---|
1869 | def old_poly_baseline(self, mask=None, order=0, plot=False, uselin=False, insitu=None, rows=None): |
---|
1870 | """\ |
---|
1871 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
1872 | |
---|
1873 | Parameters: |
---|
1874 | |
---|
1875 | mask: an optional mask |
---|
1876 | |
---|
1877 | order: the order of the polynomial (default is 0) |
---|
1878 | |
---|
1879 | plot: plot the fit and the residual. In this each |
---|
1880 | indivual fit has to be approved, by typing 'y' |
---|
1881 | or 'n' |
---|
1882 | |
---|
1883 | uselin: use linear polynomial fit |
---|
1884 | |
---|
1885 | insitu: if False a new scantable is returned. |
---|
1886 | Otherwise, the scaling is done in-situ |
---|
1887 | The default is taken from .asaprc (False) |
---|
1888 | |
---|
1889 | rows: row numbers of spectra to be processed. |
---|
1890 | (default is None: for all rows) |
---|
1891 | |
---|
1892 | Example: |
---|
1893 | # return a scan baselined by a third order polynomial, |
---|
1894 | # not using a mask |
---|
1895 | bscan = scan.poly_baseline(order=3) |
---|
1896 | |
---|
1897 | """ |
---|
1898 | if insitu is None: insitu = rcParams['insitu'] |
---|
1899 | if not insitu: |
---|
1900 | workscan = self.copy() |
---|
1901 | else: |
---|
1902 | workscan = self |
---|
1903 | varlist = vars() |
---|
1904 | if mask is None: |
---|
1905 | mask = [True for i in xrange(self.nchan())] |
---|
1906 | |
---|
1907 | try: |
---|
1908 | f = fitter() |
---|
1909 | if uselin: |
---|
1910 | f.set_function(lpoly=order) |
---|
1911 | else: |
---|
1912 | f.set_function(poly=order) |
---|
1913 | |
---|
1914 | if rows == None: |
---|
1915 | rows = xrange(workscan.nrow()) |
---|
1916 | elif isinstance(rows, int): |
---|
1917 | rows = [ rows ] |
---|
1918 | |
---|
1919 | if len(rows) > 0: |
---|
1920 | self.blpars = [] |
---|
1921 | self.masklists = [] |
---|
1922 | self.actualmask = [] |
---|
1923 | |
---|
1924 | for r in rows: |
---|
1925 | f.x = workscan._getabcissa(r) |
---|
1926 | f.y = workscan._getspectrum(r) |
---|
1927 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
1928 | f.data = None |
---|
1929 | f.fit() |
---|
1930 | if plot: |
---|
1931 | f.plot(residual=True) |
---|
1932 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
1933 | if x.upper() == 'N': |
---|
1934 | self.blpars.append(None) |
---|
1935 | self.masklists.append(None) |
---|
1936 | self.actualmask.append(None) |
---|
1937 | continue |
---|
1938 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
1939 | self.blpars.append(f.get_parameters()) |
---|
1940 | self.masklists.append(workscan.get_masklist(f.mask, row=r, silent=True)) |
---|
1941 | self.actualmask.append(f.mask) |
---|
1942 | |
---|
1943 | if plot: |
---|
1944 | f._p.unmap() |
---|
1945 | f._p = None |
---|
1946 | workscan._add_history("poly_baseline", varlist) |
---|
1947 | if insitu: |
---|
1948 | self._assign(workscan) |
---|
1949 | else: |
---|
1950 | return workscan |
---|
1951 | except RuntimeError: |
---|
1952 | msg = "The fit failed, possibly because it didn't converge." |
---|
1953 | raise RuntimeError(msg) |
---|
1954 | |
---|
1955 | @asaplog_post_dec |
---|
1956 | def poly_baseline(self, mask=None, order=0, plot=False, batch=False, insitu=None, rows=None): |
---|
1957 | """\ |
---|
1958 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
1959 | Parameters: |
---|
1960 | mask: an optional mask |
---|
1961 | order: the order of the polynomial (default is 0) |
---|
1962 | plot: plot the fit and the residual. In this each |
---|
1963 | indivual fit has to be approved, by typing 'y' |
---|
1964 | or 'n'. Ignored if batch = True. |
---|
1965 | batch: if True a faster algorithm is used and logs |
---|
1966 | including the fit results are not output |
---|
1967 | (default is False) |
---|
1968 | insitu: if False a new scantable is returned. |
---|
1969 | Otherwise, the scaling is done in-situ |
---|
1970 | The default is taken from .asaprc (False) |
---|
1971 | rows: row numbers of spectra to be baselined. |
---|
1972 | (default is None: for all rows) |
---|
1973 | Example: |
---|
1974 | # return a scan baselined by a third order polynomial, |
---|
1975 | # not using a mask |
---|
1976 | bscan = scan.poly_baseline(order=3) |
---|
1977 | """ |
---|
1978 | |
---|
1979 | varlist = vars() |
---|
1980 | |
---|
1981 | if insitu is None: insitu = rcParams["insitu"] |
---|
1982 | if insitu: |
---|
1983 | workscan = self |
---|
1984 | else: |
---|
1985 | workscan = self.copy() |
---|
1986 | |
---|
1987 | nchan = workscan.nchan() |
---|
1988 | |
---|
1989 | if mask is None: |
---|
1990 | mask = [True for i in xrange(nchan)] |
---|
1991 | |
---|
1992 | try: |
---|
1993 | if rows == None: |
---|
1994 | rows = xrange(workscan.nrow()) |
---|
1995 | elif isinstance(rows, int): |
---|
1996 | rows = [ rows ] |
---|
1997 | |
---|
1998 | if len(rows) > 0: |
---|
1999 | workscan.blpars = [] |
---|
2000 | workscan.masklists = [] |
---|
2001 | workscan.actualmask = [] |
---|
2002 | |
---|
2003 | if batch: |
---|
2004 | workscan._poly_baseline_batch(mask, order) |
---|
2005 | elif plot: |
---|
2006 | f = fitter() |
---|
2007 | f.set_function(lpoly=order) |
---|
2008 | for r in rows: |
---|
2009 | f.x = workscan._getabcissa(r) |
---|
2010 | f.y = workscan._getspectrum(r) |
---|
2011 | f.mask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
2012 | f.data = None |
---|
2013 | f.fit() |
---|
2014 | |
---|
2015 | f.plot(residual=True) |
---|
2016 | accept_fit = raw_input("Accept fit ( [y]/n ): ") |
---|
2017 | if accept_fit.upper() == "N": |
---|
2018 | self.blpars.append(None) |
---|
2019 | self.masklists.append(None) |
---|
2020 | self.actualmask.append(None) |
---|
2021 | continue |
---|
2022 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
2023 | workscan.blpars.append(f.get_parameters()) |
---|
2024 | workscan.masklists.append(workscan.get_masklist(f.mask, row=r)) |
---|
2025 | workscan.actualmask.append(f.mask) |
---|
2026 | |
---|
2027 | f._p.unmap() |
---|
2028 | f._p = None |
---|
2029 | else: |
---|
2030 | for r in rows: |
---|
2031 | fitparams = workscan._poly_baseline(mask, order, r) |
---|
2032 | params = fitparams.getparameters() |
---|
2033 | fmtd = ", ".join(["p%d = %3.6f" % (i, v) for i, v in enumerate(params)]) |
---|
2034 | errors = fitparams.geterrors() |
---|
2035 | fmask = mask_and(mask, workscan._getmask(r)) |
---|
2036 | |
---|
2037 | workscan.blpars.append({"params":params, |
---|
2038 | "fixed": fitparams.getfixedparameters(), |
---|
2039 | "formatted":fmtd, "errors":errors}) |
---|
2040 | workscan.masklists.append(workscan.get_masklist(fmask, r, silent=True)) |
---|
2041 | workscan.actualmask.append(fmask) |
---|
2042 | |
---|
2043 | asaplog.push(fmtd) |
---|
2044 | |
---|
2045 | workscan._add_history("poly_baseline", varlist) |
---|
2046 | |
---|
2047 | if insitu: |
---|
2048 | self._assign(workscan) |
---|
2049 | else: |
---|
2050 | return workscan |
---|
2051 | |
---|
2052 | except RuntimeError, e: |
---|
2053 | msg = "The fit failed, possibly because it didn't converge." |
---|
2054 | if rcParams["verbose"]: |
---|
2055 | asaplog.push(str(e)) |
---|
2056 | asaplog.push(str(msg)) |
---|
2057 | return |
---|
2058 | else: |
---|
2059 | raise RuntimeError(str(e)+'\n'+msg) |
---|
2060 | |
---|
2061 | |
---|
2062 | def auto_poly_baseline(self, mask=None, edge=(0, 0), order=0, |
---|
2063 | threshold=3, chan_avg_limit=1, plot=False, |
---|
2064 | insitu=None, rows=None): |
---|
2065 | """\ |
---|
2066 | Return a scan which has been baselined (all rows) by a polynomial. |
---|
2067 | Spectral lines are detected first using linefinder and masked out |
---|
2068 | to avoid them affecting the baseline solution. |
---|
2069 | |
---|
2070 | Parameters: |
---|
2071 | |
---|
2072 | mask: an optional mask retreived from scantable |
---|
2073 | |
---|
2074 | edge: an optional number of channel to drop at the edge of |
---|
2075 | spectrum. If only one value is |
---|
2076 | specified, the same number will be dropped from |
---|
2077 | both sides of the spectrum. Default is to keep |
---|
2078 | all channels. Nested tuples represent individual |
---|
2079 | edge selection for different IFs (a number of spectral |
---|
2080 | channels can be different) |
---|
2081 | |
---|
2082 | order: the order of the polynomial (default is 0) |
---|
2083 | |
---|
2084 | threshold: the threshold used by line finder. It is better to |
---|
2085 | keep it large as only strong lines affect the |
---|
2086 | baseline solution. |
---|
2087 | |
---|
2088 | chan_avg_limit: |
---|
2089 | a maximum number of consequtive spectral channels to |
---|
2090 | average during the search of weak and broad lines. |
---|
2091 | The default is no averaging (and no search for weak |
---|
2092 | lines). If such lines can affect the fitted baseline |
---|
2093 | (e.g. a high order polynomial is fitted), increase this |
---|
2094 | parameter (usually values up to 8 are reasonable). Most |
---|
2095 | users of this method should find the default value |
---|
2096 | sufficient. |
---|
2097 | |
---|
2098 | plot: plot the fit and the residual. In this each |
---|
2099 | indivual fit has to be approved, by typing 'y' |
---|
2100 | or 'n' |
---|
2101 | |
---|
2102 | insitu: if False a new scantable is returned. |
---|
2103 | Otherwise, the scaling is done in-situ |
---|
2104 | The default is taken from .asaprc (False) |
---|
2105 | rows: row numbers of spectra to be processed. |
---|
2106 | (default is None: for all rows) |
---|
2107 | |
---|
2108 | |
---|
2109 | Example:: |
---|
2110 | |
---|
2111 | scan2 = scan.auto_poly_baseline(order=7, insitu=False) |
---|
2112 | |
---|
2113 | """ |
---|
2114 | if insitu is None: insitu = rcParams['insitu'] |
---|
2115 | varlist = vars() |
---|
2116 | from asap.asaplinefind import linefinder |
---|
2117 | from asap import _is_sequence_or_number as _is_valid |
---|
2118 | |
---|
2119 | # check whether edge is set up for each IF individually |
---|
2120 | individualedge = False; |
---|
2121 | if len(edge) > 1: |
---|
2122 | if isinstance(edge[0], list) or isinstance(edge[0], tuple): |
---|
2123 | individualedge = True; |
---|
2124 | |
---|
2125 | if not _is_valid(edge, int) and not individualedge: |
---|
2126 | raise ValueError, "Parameter 'edge' has to be an integer or a \ |
---|
2127 | pair of integers specified as a tuple. Nested tuples are allowed \ |
---|
2128 | to make individual selection for different IFs." |
---|
2129 | |
---|
2130 | curedge = (0, 0) |
---|
2131 | if individualedge: |
---|
2132 | for edgepar in edge: |
---|
2133 | if not _is_valid(edgepar, int): |
---|
2134 | raise ValueError, "Each element of the 'edge' tuple has \ |
---|
2135 | to be a pair of integers or an integer." |
---|
2136 | else: |
---|
2137 | curedge = edge; |
---|
2138 | |
---|
2139 | if not insitu: |
---|
2140 | workscan = self.copy() |
---|
2141 | else: |
---|
2142 | workscan = self |
---|
2143 | |
---|
2144 | # setup fitter |
---|
2145 | f = fitter() |
---|
2146 | f.set_function(lpoly=order) |
---|
2147 | |
---|
2148 | # setup line finder |
---|
2149 | fl = linefinder() |
---|
2150 | fl.set_options(threshold=threshold,avg_limit=chan_avg_limit) |
---|
2151 | |
---|
2152 | fl.set_scan(workscan) |
---|
2153 | |
---|
2154 | if mask is None: |
---|
2155 | mask = _n_bools(workscan.nchan(), True) |
---|
2156 | |
---|
2157 | if rows is None: |
---|
2158 | rows = xrange(workscan.nrow()) |
---|
2159 | elif isinstance(rows, int): |
---|
2160 | rows = [ rows ] |
---|
2161 | |
---|
2162 | # Save parameters of baseline fits & masklists as a class attribute. |
---|
2163 | # NOTICE: It does not reflect changes in scantable! |
---|
2164 | if len(rows) > 0: |
---|
2165 | self.blpars=[] |
---|
2166 | self.masklists=[] |
---|
2167 | self.actualmask=[] |
---|
2168 | asaplog.push("Processing:") |
---|
2169 | for r in rows: |
---|
2170 | msg = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % \ |
---|
2171 | (workscan.getscan(r), workscan.getbeam(r), workscan.getif(r), \ |
---|
2172 | workscan.getpol(r), workscan.getcycle(r)) |
---|
2173 | asaplog.push(msg, False) |
---|
2174 | |
---|
2175 | # figure out edge parameter |
---|
2176 | if individualedge: |
---|
2177 | if len(edge) >= workscan.getif(r): |
---|
2178 | raise RuntimeError, "Number of edge elements appear to " \ |
---|
2179 | "be less than the number of IFs" |
---|
2180 | curedge = edge[workscan.getif(r)] |
---|
2181 | |
---|
2182 | actualmask = mask_and(mask, workscan._getmask(r)) # (CAS-1434) |
---|
2183 | |
---|
2184 | # setup line finder |
---|
2185 | fl.find_lines(r, actualmask, curedge) |
---|
2186 | |
---|
2187 | f.x = workscan._getabcissa(r) |
---|
2188 | f.y = workscan._getspectrum(r) |
---|
2189 | f.mask = fl.get_mask() |
---|
2190 | f.data = None |
---|
2191 | f.fit() |
---|
2192 | |
---|
2193 | # Show mask list |
---|
2194 | masklist=workscan.get_masklist(f.mask, row=r, silent=True) |
---|
2195 | msg = "mask range: "+str(masklist) |
---|
2196 | asaplog.push(msg, False) |
---|
2197 | |
---|
2198 | if plot: |
---|
2199 | f.plot(residual=True) |
---|
2200 | x = raw_input("Accept fit ( [y]/n ): ") |
---|
2201 | if x.upper() == 'N': |
---|
2202 | self.blpars.append(None) |
---|
2203 | self.masklists.append(None) |
---|
2204 | self.actualmask.append(None) |
---|
2205 | continue |
---|
2206 | |
---|
2207 | workscan._setspectrum(f.fitter.getresidual(), r) |
---|
2208 | self.blpars.append(f.get_parameters()) |
---|
2209 | self.masklists.append(masklist) |
---|
2210 | self.actualmask.append(f.mask) |
---|
2211 | if plot: |
---|
2212 | f._p.unmap() |
---|
2213 | f._p = None |
---|
2214 | workscan._add_history("auto_poly_baseline", varlist) |
---|
2215 | if insitu: |
---|
2216 | self._assign(workscan) |
---|
2217 | else: |
---|
2218 | return workscan |
---|
2219 | |
---|
2220 | @asaplog_post_dec |
---|
2221 | def rotate_linpolphase(self, angle): |
---|
2222 | """\ |
---|
2223 | Rotate the phase of the complex polarization O=Q+iU correlation. |
---|
2224 | This is always done in situ in the raw data. So if you call this |
---|
2225 | function more than once then each call rotates the phase further. |
---|
2226 | |
---|
2227 | Parameters: |
---|
2228 | |
---|
2229 | angle: The angle (degrees) to rotate (add) by. |
---|
2230 | |
---|
2231 | Example:: |
---|
2232 | |
---|
2233 | scan.rotate_linpolphase(2.3) |
---|
2234 | |
---|
2235 | """ |
---|
2236 | varlist = vars() |
---|
2237 | self._math._rotate_linpolphase(self, angle) |
---|
2238 | self._add_history("rotate_linpolphase", varlist) |
---|
2239 | return |
---|
2240 | |
---|
2241 | @asaplog_post_dec |
---|
2242 | def rotate_xyphase(self, angle): |
---|
2243 | """\ |
---|
2244 | Rotate the phase of the XY correlation. This is always done in situ |
---|
2245 | in the data. So if you call this function more than once |
---|
2246 | then each call rotates the phase further. |
---|
2247 | |
---|
2248 | Parameters: |
---|
2249 | |
---|
2250 | angle: The angle (degrees) to rotate (add) by. |
---|
2251 | |
---|
2252 | Example:: |
---|
2253 | |
---|
2254 | scan.rotate_xyphase(2.3) |
---|
2255 | |
---|
2256 | """ |
---|
2257 | varlist = vars() |
---|
2258 | self._math._rotate_xyphase(self, angle) |
---|
2259 | self._add_history("rotate_xyphase", varlist) |
---|
2260 | return |
---|
2261 | |
---|
2262 | @asaplog_post_dec |
---|
2263 | def swap_linears(self): |
---|
2264 | """\ |
---|
2265 | Swap the linear polarisations XX and YY, or better the first two |
---|
2266 | polarisations as this also works for ciculars. |
---|
2267 | """ |
---|
2268 | varlist = vars() |
---|
2269 | self._math._swap_linears(self) |
---|
2270 | self._add_history("swap_linears", varlist) |
---|
2271 | return |
---|
2272 | |
---|
2273 | @asaplog_post_dec |
---|
2274 | def invert_phase(self): |
---|
2275 | """\ |
---|
2276 | Invert the phase of the complex polarisation |
---|
2277 | """ |
---|
2278 | varlist = vars() |
---|
2279 | self._math._invert_phase(self) |
---|
2280 | self._add_history("invert_phase", varlist) |
---|
2281 | return |
---|
2282 | |
---|
2283 | @asaplog_post_dec |
---|
2284 | def add(self, offset, insitu=None): |
---|
2285 | """\ |
---|
2286 | Return a scan where all spectra have the offset added |
---|
2287 | |
---|
2288 | Parameters: |
---|
2289 | |
---|
2290 | offset: the offset |
---|
2291 | |
---|
2292 | insitu: if False a new scantable is returned. |
---|
2293 | Otherwise, the scaling is done in-situ |
---|
2294 | The default is taken from .asaprc (False) |
---|
2295 | |
---|
2296 | """ |
---|
2297 | if insitu is None: insitu = rcParams['insitu'] |
---|
2298 | self._math._setinsitu(insitu) |
---|
2299 | varlist = vars() |
---|
2300 | s = scantable(self._math._unaryop(self, offset, "ADD", False)) |
---|
2301 | s._add_history("add", varlist) |
---|
2302 | if insitu: |
---|
2303 | self._assign(s) |
---|
2304 | else: |
---|
2305 | return s |
---|
2306 | |
---|
2307 | @asaplog_post_dec |
---|
2308 | def scale(self, factor, tsys=True, insitu=None): |
---|
2309 | """\ |
---|
2310 | |
---|
2311 | Return a scan where all spectra are scaled by the given 'factor' |
---|
2312 | |
---|
2313 | Parameters: |
---|
2314 | |
---|
2315 | factor: the scaling factor (float or 1D float list) |
---|
2316 | |
---|
2317 | insitu: if False a new scantable is returned. |
---|
2318 | Otherwise, the scaling is done in-situ |
---|
2319 | The default is taken from .asaprc (False) |
---|
2320 | |
---|
2321 | tsys: if True (default) then apply the operation to Tsys |
---|
2322 | as well as the data |
---|
2323 | |
---|
2324 | """ |
---|
2325 | if insitu is None: insitu = rcParams['insitu'] |
---|
2326 | self._math._setinsitu(insitu) |
---|
2327 | varlist = vars() |
---|
2328 | s = None |
---|
2329 | import numpy |
---|
2330 | if isinstance(factor, list) or isinstance(factor, numpy.ndarray): |
---|
2331 | if isinstance(factor[0], list) or isinstance(factor[0], numpy.ndarray): |
---|
2332 | from asapmath import _array2dOp |
---|
2333 | s = _array2dOp( self.copy(), factor, "MUL", tsys ) |
---|
2334 | else: |
---|
2335 | s = scantable( self._math._arrayop( self.copy(), factor, "MUL", tsys ) ) |
---|
2336 | else: |
---|
2337 | s = scantable(self._math._unaryop(self.copy(), factor, "MUL", tsys)) |
---|
2338 | s._add_history("scale", varlist) |
---|
2339 | if insitu: |
---|
2340 | self._assign(s) |
---|
2341 | else: |
---|
2342 | return s |
---|
2343 | |
---|
2344 | def set_sourcetype(self, match, matchtype="pattern", |
---|
2345 | sourcetype="reference"): |
---|
2346 | """\ |
---|
2347 | Set the type of the source to be an source or reference scan |
---|
2348 | using the provided pattern. |
---|
2349 | |
---|
2350 | Parameters: |
---|
2351 | |
---|
2352 | match: a Unix style pattern, regular expression or selector |
---|
2353 | |
---|
2354 | matchtype: 'pattern' (default) UNIX style pattern or |
---|
2355 | 'regex' regular expression |
---|
2356 | |
---|
2357 | sourcetype: the type of the source to use (source/reference) |
---|
2358 | |
---|
2359 | """ |
---|
2360 | varlist = vars() |
---|
2361 | basesel = self.get_selection() |
---|
2362 | stype = -1 |
---|
2363 | if sourcetype.lower().startswith("r"): |
---|
2364 | stype = 1 |
---|
2365 | elif sourcetype.lower().startswith("s"): |
---|
2366 | stype = 0 |
---|
2367 | else: |
---|
2368 | raise ValueError("Illegal sourcetype use s(ource) or r(eference)") |
---|
2369 | if matchtype.lower().startswith("p"): |
---|
2370 | matchtype = "pattern" |
---|
2371 | elif matchtype.lower().startswith("r"): |
---|
2372 | matchtype = "regex" |
---|
2373 | else: |
---|
2374 | raise ValueError("Illegal matchtype, use p(attern) or r(egex)") |
---|
2375 | sel = selector() |
---|
2376 | if isinstance(match, selector): |
---|
2377 | sel = match |
---|
2378 | else: |
---|
2379 | sel.set_query("SRCNAME == %s('%s')" % (matchtype, match)) |
---|
2380 | self.set_selection(basesel+sel) |
---|
2381 | self._setsourcetype(stype) |
---|
2382 | self.set_selection(basesel) |
---|
2383 | self._add_history("set_sourcetype", varlist) |
---|
2384 | |
---|
2385 | @asaplog_post_dec |
---|
2386 | @preserve_selection |
---|
2387 | def auto_quotient(self, preserve=True, mode='paired', verify=False): |
---|
2388 | """\ |
---|
2389 | This function allows to build quotients automatically. |
---|
2390 | It assumes the observation to have the same number of |
---|
2391 | "ons" and "offs" |
---|
2392 | |
---|
2393 | Parameters: |
---|
2394 | |
---|
2395 | preserve: you can preserve (default) the continuum or |
---|
2396 | remove it. The equations used are |
---|
2397 | |
---|
2398 | preserve: Output = Toff * (on/off) - Toff |
---|
2399 | |
---|
2400 | remove: Output = Toff * (on/off) - Ton |
---|
2401 | |
---|
2402 | mode: the on/off detection mode |
---|
2403 | 'paired' (default) |
---|
2404 | identifies 'off' scans by the |
---|
2405 | trailing '_R' (Mopra/Parkes) or |
---|
2406 | '_e'/'_w' (Tid) and matches |
---|
2407 | on/off pairs from the observing pattern |
---|
2408 | 'time' |
---|
2409 | finds the closest off in time |
---|
2410 | |
---|
2411 | .. todo:: verify argument is not implemented |
---|
2412 | |
---|
2413 | """ |
---|
2414 | varlist = vars() |
---|
2415 | modes = ["time", "paired"] |
---|
2416 | if not mode in modes: |
---|
2417 | msg = "please provide valid mode. Valid modes are %s" % (modes) |
---|
2418 | raise ValueError(msg) |
---|
2419 | s = None |
---|
2420 | if mode.lower() == "paired": |
---|
2421 | sel = self.get_selection() |
---|
2422 | sel.set_query("SRCTYPE==psoff") |
---|
2423 | self.set_selection(sel) |
---|
2424 | offs = self.copy() |
---|
2425 | sel.set_query("SRCTYPE==pson") |
---|
2426 | self.set_selection(sel) |
---|
2427 | ons = self.copy() |
---|
2428 | s = scantable(self._math._quotient(ons, offs, preserve)) |
---|
2429 | elif mode.lower() == "time": |
---|
2430 | s = scantable(self._math._auto_quotient(self, mode, preserve)) |
---|
2431 | s._add_history("auto_quotient", varlist) |
---|
2432 | return s |
---|
2433 | |
---|
2434 | @asaplog_post_dec |
---|
2435 | def mx_quotient(self, mask = None, weight='median', preserve=True): |
---|
2436 | """\ |
---|
2437 | Form a quotient using "off" beams when observing in "MX" mode. |
---|
2438 | |
---|
2439 | Parameters: |
---|
2440 | |
---|
2441 | mask: an optional mask to be used when weight == 'stddev' |
---|
2442 | |
---|
2443 | weight: How to average the off beams. Default is 'median'. |
---|
2444 | |
---|
2445 | preserve: you can preserve (default) the continuum or |
---|
2446 | remove it. The equations used are: |
---|
2447 | |
---|
2448 | preserve: Output = Toff * (on/off) - Toff |
---|
2449 | |
---|
2450 | remove: Output = Toff * (on/off) - Ton |
---|
2451 | |
---|
2452 | """ |
---|
2453 | mask = mask or () |
---|
2454 | varlist = vars() |
---|
2455 | on = scantable(self._math._mx_extract(self, 'on')) |
---|
2456 | preoff = scantable(self._math._mx_extract(self, 'off')) |
---|
2457 | off = preoff.average_time(mask=mask, weight=weight, scanav=False) |
---|
2458 | from asapmath import quotient |
---|
2459 | q = quotient(on, off, preserve) |
---|
2460 | q._add_history("mx_quotient", varlist) |
---|
2461 | return q |
---|
2462 | |
---|
2463 | @asaplog_post_dec |
---|
2464 | def freq_switch(self, insitu=None): |
---|
2465 | """\ |
---|
2466 | Apply frequency switching to the data. |
---|
2467 | |
---|
2468 | Parameters: |
---|
2469 | |
---|
2470 | insitu: if False a new scantable is returned. |
---|
2471 | Otherwise, the swictching is done in-situ |
---|
2472 | The default is taken from .asaprc (False) |
---|
2473 | |
---|
2474 | """ |
---|
2475 | if insitu is None: insitu = rcParams['insitu'] |
---|
2476 | self._math._setinsitu(insitu) |
---|
2477 | varlist = vars() |
---|
2478 | s = scantable(self._math._freqswitch(self)) |
---|
2479 | s._add_history("freq_switch", varlist) |
---|
2480 | if insitu: |
---|
2481 | self._assign(s) |
---|
2482 | else: |
---|
2483 | return s |
---|
2484 | |
---|
2485 | @asaplog_post_dec |
---|
2486 | def recalc_azel(self): |
---|
2487 | """Recalculate the azimuth and elevation for each position.""" |
---|
2488 | varlist = vars() |
---|
2489 | self._recalcazel() |
---|
2490 | self._add_history("recalc_azel", varlist) |
---|
2491 | return |
---|
2492 | |
---|
2493 | @asaplog_post_dec |
---|
2494 | def __add__(self, other): |
---|
2495 | varlist = vars() |
---|
2496 | s = None |
---|
2497 | if isinstance(other, scantable): |
---|
2498 | s = scantable(self._math._binaryop(self, other, "ADD")) |
---|
2499 | elif isinstance(other, float): |
---|
2500 | s = scantable(self._math._unaryop(self, other, "ADD", False)) |
---|
2501 | else: |
---|
2502 | raise TypeError("Other input is not a scantable or float value") |
---|
2503 | s._add_history("operator +", varlist) |
---|
2504 | return s |
---|
2505 | |
---|
2506 | @asaplog_post_dec |
---|
2507 | def __sub__(self, other): |
---|
2508 | """ |
---|
2509 | implicit on all axes and on Tsys |
---|
2510 | """ |
---|
2511 | varlist = vars() |
---|
2512 | s = None |
---|
2513 | if isinstance(other, scantable): |
---|
2514 | s = scantable(self._math._binaryop(self, other, "SUB")) |
---|
2515 | elif isinstance(other, float): |
---|
2516 | s = scantable(self._math._unaryop(self, other, "SUB", False)) |
---|
2517 | else: |
---|
2518 | raise TypeError("Other input is not a scantable or float value") |
---|
2519 | s._add_history("operator -", varlist) |
---|
2520 | return s |
---|
2521 | |
---|
2522 | @asaplog_post_dec |
---|
2523 | def __mul__(self, other): |
---|
2524 | """ |
---|
2525 | implicit on all axes and on Tsys |
---|
2526 | """ |
---|
2527 | varlist = vars() |
---|
2528 | s = None |
---|
2529 | if isinstance(other, scantable): |
---|
2530 | s = scantable(self._math._binaryop(self, other, "MUL")) |
---|
2531 | elif isinstance(other, float): |
---|
2532 | s = scantable(self._math._unaryop(self, other, "MUL", False)) |
---|
2533 | else: |
---|
2534 | raise TypeError("Other input is not a scantable or float value") |
---|
2535 | s._add_history("operator *", varlist) |
---|
2536 | return s |
---|
2537 | |
---|
2538 | |
---|
2539 | @asaplog_post_dec |
---|
2540 | def __div__(self, other): |
---|
2541 | """ |
---|
2542 | implicit on all axes and on Tsys |
---|
2543 | """ |
---|
2544 | varlist = vars() |
---|
2545 | s = None |
---|
2546 | if isinstance(other, scantable): |
---|
2547 | s = scantable(self._math._binaryop(self, other, "DIV")) |
---|
2548 | elif isinstance(other, float): |
---|
2549 | if other == 0.0: |
---|
2550 | raise ZeroDivisionError("Dividing by zero is not recommended") |
---|
2551 | s = scantable(self._math._unaryop(self, other, "DIV", False)) |
---|
2552 | else: |
---|
2553 | raise TypeError("Other input is not a scantable or float value") |
---|
2554 | s._add_history("operator /", varlist) |
---|
2555 | return s |
---|
2556 | |
---|
2557 | @asaplog_post_dec |
---|
2558 | def get_fit(self, row=0): |
---|
2559 | """\ |
---|
2560 | Print or return the stored fits for a row in the scantable |
---|
2561 | |
---|
2562 | Parameters: |
---|
2563 | |
---|
2564 | row: the row which the fit has been applied to. |
---|
2565 | |
---|
2566 | """ |
---|
2567 | if row > self.nrow(): |
---|
2568 | return |
---|
2569 | from asap.asapfit import asapfit |
---|
2570 | fit = asapfit(self._getfit(row)) |
---|
2571 | asaplog.push( '%s' %(fit) ) |
---|
2572 | return fit.as_dict() |
---|
2573 | |
---|
2574 | def flag_nans(self): |
---|
2575 | """\ |
---|
2576 | Utility function to flag NaN values in the scantable. |
---|
2577 | """ |
---|
2578 | import numpy |
---|
2579 | basesel = self.get_selection() |
---|
2580 | for i in range(self.nrow()): |
---|
2581 | sel = self.get_row_selector(i) |
---|
2582 | self.set_selection(basesel+sel) |
---|
2583 | nans = numpy.isnan(self._getspectrum(0)) |
---|
2584 | if numpy.any(nans): |
---|
2585 | bnans = [ bool(v) for v in nans] |
---|
2586 | self.flag(bnans) |
---|
2587 | self.set_selection(basesel) |
---|
2588 | |
---|
2589 | def get_row_selector(self, rowno): |
---|
2590 | return selector(beams=self.getbeam(rowno), |
---|
2591 | ifs=self.getif(rowno), |
---|
2592 | pols=self.getpol(rowno), |
---|
2593 | scans=self.getscan(rowno), |
---|
2594 | cycles=self.getcycle(rowno)) |
---|
2595 | |
---|
2596 | def _add_history(self, funcname, parameters): |
---|
2597 | if not rcParams['scantable.history']: |
---|
2598 | return |
---|
2599 | # create date |
---|
2600 | sep = "##" |
---|
2601 | from datetime import datetime |
---|
2602 | dstr = datetime.now().strftime('%Y/%m/%d %H:%M:%S') |
---|
2603 | hist = dstr+sep |
---|
2604 | hist += funcname+sep#cdate+sep |
---|
2605 | if parameters.has_key('self'): del parameters['self'] |
---|
2606 | for k, v in parameters.iteritems(): |
---|
2607 | if type(v) is dict: |
---|
2608 | for k2, v2 in v.iteritems(): |
---|
2609 | hist += k2 |
---|
2610 | hist += "=" |
---|
2611 | if isinstance(v2, scantable): |
---|
2612 | hist += 'scantable' |
---|
2613 | elif k2 == 'mask': |
---|
2614 | if isinstance(v2, list) or isinstance(v2, tuple): |
---|
2615 | hist += str(self._zip_mask(v2)) |
---|
2616 | else: |
---|
2617 | hist += str(v2) |
---|
2618 | else: |
---|
2619 | hist += str(v2) |
---|
2620 | else: |
---|
2621 | hist += k |
---|
2622 | hist += "=" |
---|
2623 | if isinstance(v, scantable): |
---|
2624 | hist += 'scantable' |
---|
2625 | elif k == 'mask': |
---|
2626 | if isinstance(v, list) or isinstance(v, tuple): |
---|
2627 | hist += str(self._zip_mask(v)) |
---|
2628 | else: |
---|
2629 | hist += str(v) |
---|
2630 | else: |
---|
2631 | hist += str(v) |
---|
2632 | hist += sep |
---|
2633 | hist = hist[:-2] # remove trailing '##' |
---|
2634 | self._addhistory(hist) |
---|
2635 | |
---|
2636 | |
---|
2637 | def _zip_mask(self, mask): |
---|
2638 | mask = list(mask) |
---|
2639 | i = 0 |
---|
2640 | segments = [] |
---|
2641 | while mask[i:].count(1): |
---|
2642 | i += mask[i:].index(1) |
---|
2643 | if mask[i:].count(0): |
---|
2644 | j = i + mask[i:].index(0) |
---|
2645 | else: |
---|
2646 | j = len(mask) |
---|
2647 | segments.append([i, j]) |
---|
2648 | i = j |
---|
2649 | return segments |
---|
2650 | |
---|
2651 | def _get_ordinate_label(self): |
---|
2652 | fu = "("+self.get_fluxunit()+")" |
---|
2653 | import re |
---|
2654 | lbl = "Intensity" |
---|
2655 | if re.match(".K.", fu): |
---|
2656 | lbl = "Brightness Temperature "+ fu |
---|
2657 | elif re.match(".Jy.", fu): |
---|
2658 | lbl = "Flux density "+ fu |
---|
2659 | return lbl |
---|
2660 | |
---|
2661 | def _check_ifs(self): |
---|
2662 | nchans = [self.nchan(i) for i in range(self.nif(-1))] |
---|
2663 | nchans = filter(lambda t: t > 0, nchans) |
---|
2664 | return (sum(nchans)/len(nchans) == nchans[0]) |
---|
2665 | |
---|
2666 | @asaplog_post_dec |
---|
2667 | #def _fill(self, names, unit, average, getpt, antenna): |
---|
2668 | def _fill(self, names, unit, average, opts={}): |
---|
2669 | first = True |
---|
2670 | fullnames = [] |
---|
2671 | for name in names: |
---|
2672 | name = os.path.expandvars(name) |
---|
2673 | name = os.path.expanduser(name) |
---|
2674 | if not os.path.exists(name): |
---|
2675 | msg = "File '%s' does not exists" % (name) |
---|
2676 | raise IOError(msg) |
---|
2677 | fullnames.append(name) |
---|
2678 | if average: |
---|
2679 | asaplog.push('Auto averaging integrations') |
---|
2680 | stype = int(rcParams['scantable.storage'].lower() == 'disk') |
---|
2681 | for name in fullnames: |
---|
2682 | tbl = Scantable(stype) |
---|
2683 | r = filler(tbl) |
---|
2684 | rx = rcParams['scantable.reference'] |
---|
2685 | r.setreferenceexpr(rx) |
---|
2686 | msg = "Importing %s..." % (name) |
---|
2687 | asaplog.push(msg, False) |
---|
2688 | #opts = {'ms': {'antenna' : antenna, 'getpt': getpt} } |
---|
2689 | r.open(name, opts)# antenna, -1, -1, getpt) |
---|
2690 | r.fill() |
---|
2691 | if average: |
---|
2692 | tbl = self._math._average((tbl, ), (), 'NONE', 'SCAN') |
---|
2693 | if not first: |
---|
2694 | tbl = self._math._merge([self, tbl]) |
---|
2695 | Scantable.__init__(self, tbl) |
---|
2696 | r.close() |
---|
2697 | del r, tbl |
---|
2698 | first = False |
---|
2699 | #flush log |
---|
2700 | asaplog.post() |
---|
2701 | if unit is not None: |
---|
2702 | self.set_fluxunit(unit) |
---|
2703 | if not is_casapy(): |
---|
2704 | self.set_freqframe(rcParams['scantable.freqframe']) |
---|
2705 | |
---|
2706 | def __getitem__(self, key): |
---|
2707 | if key < 0: |
---|
2708 | key += self.nrow() |
---|
2709 | if key >= self.nrow(): |
---|
2710 | raise IndexError("Row index out of range.") |
---|
2711 | return self._getspectrum(key) |
---|
2712 | |
---|
2713 | def __setitem__(self, key, value): |
---|
2714 | if key < 0: |
---|
2715 | key += self.nrow() |
---|
2716 | if key >= self.nrow(): |
---|
2717 | raise IndexError("Row index out of range.") |
---|
2718 | if not hasattr(value, "__len__") or \ |
---|
2719 | len(value) > self.nchan(self.getif(key)): |
---|
2720 | raise ValueError("Spectrum length doesn't match.") |
---|
2721 | return self._setspectrum(value, key) |
---|
2722 | |
---|
2723 | def __len__(self): |
---|
2724 | return self.nrow() |
---|
2725 | |
---|
2726 | def __iter__(self): |
---|
2727 | for i in range(len(self)): |
---|
2728 | yield self[i] |
---|