1 | import numpy |
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2 | from asap import rcParams |
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3 | from asap.scantable import scantable |
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4 | from asap.selector import selector |
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5 | from asap._asap import stgrid |
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6 | import pylab as pl |
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7 | from logging import asaplog |
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8 | |
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9 | class asapgrid: |
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10 | """ |
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11 | The asapgrid class is defined to convolve data onto regular |
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12 | spatial grid. Typical usage is as follows: |
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13 | |
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14 | # create asapgrid instance with two input data |
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15 | g = asapgrid( ['testimage1.asap','testimage2.asap'] ) |
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16 | # set IFNO if necessary |
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17 | g.setIF( 0 ) |
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18 | # set POLNOs if necessary |
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19 | g.setPolList( [0,1] ) |
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20 | # set SCANNOs if necessary |
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21 | g.setScanList( [22,23,24] ) |
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22 | # define image with full specification |
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23 | # you can skip some parameters (see help for defineImage) |
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24 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
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25 | center='J2000 10h10m10s -5d05m05s' ) |
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26 | # set convolution function |
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27 | g.setFunc( func='sf', width=3 ) |
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28 | # enable min/max clipping |
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29 | g.enableClip() |
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30 | # or, disable min/max clipping |
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31 | #g.disableClip() |
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32 | # actual gridding |
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33 | g.grid() |
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34 | # save result |
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35 | g.save( outfile='grid.asap' ) |
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36 | # plot result |
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37 | g.plot( plotchan=1246, plotpol=-1, plotgrid=True, plotobs=True ) |
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38 | """ |
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39 | def __init__( self, infile ): |
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40 | """ |
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41 | Create asapgrid instance. |
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42 | |
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43 | infile -- input data as a string or string list if you want |
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44 | to grid more than one data at once. |
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45 | """ |
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46 | self.outfile = None |
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47 | self.ifno = None |
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48 | self.gridder = stgrid() |
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49 | self.setData( infile ) |
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50 | |
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51 | def setData( self, infile ): |
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52 | """ |
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53 | Set data to be processed. |
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54 | |
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55 | infile -- input data as a string or string list if you want |
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56 | to grid more than one data at once. |
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57 | """ |
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58 | if isinstance( infile, str ): |
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59 | self.gridder._setin( infile ) |
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60 | else: |
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61 | self.gridder._setfiles( infile ) |
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62 | self.infile = infile |
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63 | |
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64 | def setIF( self, ifno ): |
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65 | """ |
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66 | Set IFNO to be processed. Currently, asapgrid allows to process |
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67 | only one IFNO for one gridding run even if the data contains |
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68 | multiple IFs. If you didn't specify IFNO, default value, which |
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69 | is IFNO in the first spectrum, will be processed. |
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70 | |
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71 | ifno -- IFNO to be processed. |
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72 | """ |
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73 | self.ifno = ifno |
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74 | self.gridder._setif( self.ifno ) |
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75 | |
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76 | def setPolList( self, pollist ): |
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77 | """ |
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78 | Set list of polarization components you want to process. |
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79 | If not specified, all POLNOs will be processed. |
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80 | |
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81 | pollist -- list of POLNOs. |
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82 | """ |
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83 | self.gridder._setpollist( pollist ) |
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84 | |
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85 | def setScanList( self, scanlist ): |
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86 | """ |
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87 | Set list of scans you want to process. If not specified, all |
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88 | scans will be processed. |
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89 | |
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90 | scanlist -- list of SCANNOs. |
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91 | """ |
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92 | self.gridder._setscanlist( scanlist ) |
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93 | |
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94 | def defineImage( self, nx=-1, ny=-1, cellx='', celly='', center='' ): |
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95 | """ |
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96 | Define spatial grid. |
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97 | |
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98 | First two parameters, nx and ny, define number of pixels of |
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99 | the grid. If which of those is not specified, it will be set |
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100 | to the same value as the other. If none of them are specified, |
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101 | it will be determined from map extent and cell size. |
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102 | |
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103 | Next two parameters, cellx and celly, define size of pixel. |
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104 | You should set those parameters as string, which is constructed |
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105 | numerical value and unit, e.g. '0.5arcmin', or numerical value. |
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106 | If those values are specified as numerical value, their units |
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107 | will be assumed to 'arcsec'. If which of those is not specified, |
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108 | it will be set to the same value as the other. If none of them |
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109 | are specified, it will be determined from map extent and number |
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110 | of pixels, or set to '1arcmin' if neither nx nor ny is set. |
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111 | |
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112 | The last parameter, center, define the central coordinate of |
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113 | the grid. You should specify its value as a string, like, |
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114 | |
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115 | 'J2000 05h08m50s -16d23m30s' |
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116 | |
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117 | or |
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118 | |
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119 | 'J2000 05:08:50 -16.23.30' |
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120 | |
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121 | You can omit equinox when you specify center coordinate. In that |
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122 | case, J2000 is assumed. If center is not specified, it will be |
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123 | determined from the observed positions of input data. |
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124 | |
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125 | nx -- number of pixels along x (R.A.) direction. |
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126 | ny -- number of pixels along y (Dec.) direction. |
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127 | cellx -- size of pixel in x (R.A.) direction. |
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128 | celly -- size of pixel in y (Dec.) direction. |
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129 | center -- central position of the grid. |
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130 | """ |
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131 | if not isinstance( cellx, str ): |
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132 | cellx = '%sarcsec'%(cellx) |
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133 | if not isinstance( celly, str ): |
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134 | celly = '%sarcsec'%(celly) |
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135 | self.gridder._defineimage( nx, ny, cellx, celly, center ) |
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136 | |
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137 | def setFunc( self, func='box', width=-1 ): |
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138 | """ |
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139 | Set convolution function. Possible options are 'box' (Box-car, |
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140 | default), 'sf' (prolate spheroidal), and 'gauss' (Gaussian). |
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141 | Width of convolution function can be set using width parameter. |
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142 | By default (-1), width is automatically set depending on each |
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143 | convolution function. Default values for width are: |
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144 | |
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145 | 'box': 1 pixel |
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146 | 'sf': 3 pixels |
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147 | 'gauss': 1 pixel (width is used as HWHM) |
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148 | |
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149 | func -- Function type ('box', 'sf', 'gauss'). |
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150 | width -- Width of convolution function. Default (-1) is to |
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151 | choose pre-defined value for each convolution function. |
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152 | """ |
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153 | self.gridder._setfunc( func, width ) |
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154 | |
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155 | def setWeight( self, weightType='uniform' ): |
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156 | """ |
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157 | Set weight type. Possible options are 'uniform' (default), |
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158 | 'tint' (weight by integration time), 'tsys' (weight by |
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159 | Tsys: 1/Tsys**2), and 'tintsys' (weight by integration time |
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160 | as well as Tsys: tint/Tsys**2). |
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161 | |
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162 | weightType -- weight type ('uniform', 'tint', 'tsys', 'tintsys') |
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163 | """ |
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164 | self.gridder._setweight( weightType ) |
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165 | |
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166 | def enableClip( self ): |
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167 | """ |
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168 | Enable min/max clipping. |
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169 | |
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170 | By default, min/max clipping is disabled so that you should |
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171 | call this method before actual gridding if you want to do |
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172 | clipping. |
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173 | """ |
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174 | self.gridder._enableclip() |
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175 | |
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176 | def disableClip( self ): |
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177 | """ |
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178 | Disable min/max clipping. |
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179 | """ |
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180 | self.gridder._disableclip() |
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181 | |
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182 | def grid( self ): |
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183 | """ |
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184 | Actual gridding which will be done based on several user inputs. |
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185 | """ |
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186 | self.gridder._grid() |
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187 | |
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188 | def save( self, outfile='' ): |
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189 | """ |
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190 | Save result. By default, output data name will be constructed |
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191 | from first element of input data name list (e.g. 'input.asap.grid'). |
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192 | |
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193 | outfile -- output data name. |
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194 | """ |
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195 | self.outfile = self.gridder._save( outfile ) |
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196 | |
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197 | def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ): |
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198 | """ |
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199 | Plot gridded data. |
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200 | |
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201 | plotchan -- Which channel you want to plot. Default (-1) is |
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202 | to average all the channels. |
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203 | plotpol -- Which polarization component you want to plot. |
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204 | Default (-1) is to average all the polarization |
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205 | components. |
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206 | plotobs -- Also plot observed position if True. Default |
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207 | is False. Setting True for large amount of spectra |
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208 | might be time consuming. |
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209 | plotgrid -- Also plot grid center if True. Default is False. |
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210 | Setting True for large number of grids might be |
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211 | time consuming. |
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212 | """ |
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213 | import time |
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214 | t0=time.time() |
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215 | # to load scantable on disk |
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216 | storg = rcParams['scantable.storage'] |
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217 | rcParams['scantable.storage'] = 'disk' |
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218 | plotter = _SDGridPlotter( self.infile, self.outfile, self.ifno ) |
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219 | plotter.plot( chan=plotchan, pol=plotpol, plotobs=plotobs, plotgrid=plotgrid ) |
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220 | # back to original setup |
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221 | rcParams['scantable.storage'] = storg |
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222 | t1=time.time() |
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223 | asaplog.push('plot: elapsed time %s sec'%(t1-t0)) |
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224 | asaplog.post('DEBUG','asapgrid.plot') |
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225 | |
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226 | class _SDGridPlotter: |
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227 | def __init__( self, infile, outfile=None, ifno=-1 ): |
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228 | if isinstance( infile, str ): |
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229 | self.infile = [infile] |
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230 | else: |
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231 | self.infile = infile |
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232 | self.outfile = outfile |
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233 | if self.outfile is None: |
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234 | self.outfile = self.infile[0].rstrip('/')+'.grid' |
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235 | self.nx = -1 |
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236 | self.ny = -1 |
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237 | self.nchan = 0 |
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238 | self.npol = 0 |
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239 | self.pollist = [] |
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240 | self.cellx = 0.0 |
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241 | self.celly = 0.0 |
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242 | self.center = [0.0,0.0] |
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243 | self.nonzero = [[0.0],[0.0]] |
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244 | self.ifno = ifno |
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245 | self.tablein = None |
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246 | self.nrow = 0 |
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247 | self.blc = None |
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248 | self.trc = None |
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249 | self.get() |
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250 | |
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251 | def get( self ): |
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252 | s = scantable( self.outfile, average=False ) |
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253 | self.nchan = len(s._getspectrum(0)) |
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254 | nrow = s.nrow() |
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255 | pols = numpy.ones( nrow, dtype=int ) |
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256 | for i in xrange(nrow): |
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257 | pols[i] = s.getpol(i) |
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258 | self.pollist, indices = numpy.unique( pols, return_inverse=True ) |
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259 | self.npol = len(self.pollist) |
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260 | self.pollist = self.pollist[indices[:self.npol]] |
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261 | #print 'pollist=',self.pollist |
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262 | #print 'npol=',self.npol |
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263 | #print 'nrow=',nrow |
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264 | |
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265 | idx = 0 |
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266 | d0 = s.get_direction( 0 ).split()[-1] |
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267 | while ( s.get_direction(self.npol*idx) is not None \ |
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268 | and s.get_direction(self.npol*idx).split()[-1] == d0 ): |
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269 | idx += 1 |
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270 | |
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271 | self.nx = idx |
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272 | self.ny = nrow / (self.npol * idx ) |
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273 | #print 'nx,ny=',self.nx,self.ny |
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274 | |
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275 | self.blc = s.get_directionval( 0 ) |
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276 | self.trc = s.get_directionval( nrow-self.npol ) |
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277 | #print self.blc |
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278 | #print self.trc |
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279 | if nrow > 1: |
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280 | incrx = s.get_directionval( self.npol ) |
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281 | incry = s.get_directionval( self.nx*self.npol ) |
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282 | else: |
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283 | incrx = [0.0,0.0] |
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284 | incry = [0.0,0.0] |
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285 | self.cellx = abs( self.blc[0] - incrx[0] ) |
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286 | self.celly = abs( self.blc[1] - incry[1] ) |
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287 | #print 'cellx,celly=',self.cellx,self.celly |
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288 | |
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289 | def plot( self, chan=-1, pol=-1, plotobs=False, plotgrid=False ): |
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290 | if pol < 0: |
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291 | opt = 'averaged over pol' |
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292 | else: |
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293 | opt = 'pol %s'%(pol) |
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294 | if type(chan) is list: |
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295 | opt += ', averaged over channel %s-%s'%(chan[0],chan[1]) |
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296 | elif chan < 0: |
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297 | opt += ', averaged over channel' |
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298 | else: |
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299 | opt += ', channel %s'%(chan) |
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300 | data = self.getData( chan, pol ) |
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301 | data = numpy.fliplr( data ) |
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302 | title = 'Gridded Image (%s)'%(opt) |
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303 | pl.figure(10) |
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304 | pl.clf() |
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305 | # plot grid position |
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306 | if plotgrid: |
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307 | x = numpy.arange(self.blc[0],self.trc[0]+0.5*self.cellx,self.cellx,dtype=float) |
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308 | #print 'len(x)=',len(x) |
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309 | #print 'x=',x |
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310 | ybase = numpy.ones(self.nx,dtype=float)*self.blc[1] |
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311 | #print 'len(ybase)=',len(ybase) |
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312 | incr = self.celly |
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313 | for iy in xrange(self.ny): |
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314 | y = ybase + iy * incr |
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315 | #print y |
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316 | pl.plot(x,y,',',color='blue') |
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317 | # plot observed position |
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318 | if plotobs: |
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319 | for i in xrange(len(self.infile)): |
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320 | self.createTableIn( self.infile[i] ) |
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321 | irow = 0 |
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322 | while ( irow < self.nrow ): |
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323 | chunk = self.getPointingChunk( irow ) |
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324 | #print chunk |
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325 | pl.plot(chunk[0],chunk[1],',',color='green') |
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326 | irow += chunk.shape[1] |
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327 | #print irow |
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328 | # show image |
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329 | extent=[self.trc[0]+0.5*self.cellx, |
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330 | self.blc[0]-0.5*self.cellx, |
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331 | self.blc[1]-0.5*self.celly, |
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332 | self.trc[1]+0.5*self.celly] |
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333 | deccorr = 1.0/numpy.cos(0.5*(self.blc[1]+self.trc[1])) |
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334 | pl.imshow(data,extent=extent,origin='lower',interpolation='nearest') |
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335 | pl.colorbar() |
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336 | pl.xlabel('R.A. [rad]') |
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337 | pl.ylabel('Dec. [rad]') |
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338 | ax = pl.axes() |
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339 | ax.set_aspect(deccorr) |
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340 | pl.title( title ) |
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341 | |
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342 | def createTableIn( self, tab ): |
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343 | del self.tablein |
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344 | self.tablein = scantable( tab, average=False ) |
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345 | if self.ifno < 0: |
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346 | ifno = self.tablein.getif(0) |
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347 | print 'ifno=',ifno |
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348 | else: |
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349 | ifno = self.ifno |
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350 | sel = selector() |
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351 | sel.set_ifs( ifno ) |
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352 | self.tablein.set_selection( sel ) |
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353 | self.nchan = len(self.tablein._getspectrum(0)) |
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354 | self.nrow = self.tablein.nrow() |
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355 | del sel |
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356 | |
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357 | |
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358 | def getPointingChunk( self, irow ): |
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359 | numchunk = 1000 |
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360 | nrow = min( self.nrow-irow, numchunk ) |
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361 | #print 'nrow=',nrow |
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362 | v = numpy.zeros( (2,nrow), dtype=float ) |
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363 | idx = 0 |
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364 | for i in xrange(irow,irow+nrow): |
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365 | d = self.tablein.get_directionval( i ) |
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366 | v[0,idx] = d[0] |
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367 | v[1,idx] = d[1] |
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368 | idx += 1 |
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369 | return v |
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370 | |
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371 | def getData( self, chan=-1, pol=-1 ): |
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372 | if type(chan) == list: |
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373 | spectra = self.__chanAverage(start=chan[0],end=chan[1]) |
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374 | elif chan == -1: |
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375 | spectra = self.__chanAverage() |
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376 | else: |
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377 | spectra = self.__chanIndex( chan ) |
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378 | data = spectra.reshape( (self.npol,self.ny,self.nx) ) |
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379 | if pol == -1: |
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380 | retval = data.mean(axis=0) |
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381 | else: |
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382 | retval = data[pol] |
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383 | return retval |
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384 | |
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385 | def __chanAverage( self, start=-1, end=-1 ): |
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386 | s = scantable( self.outfile, average=False ) |
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387 | nrow = s.nrow() |
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388 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
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389 | irow = 0 |
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390 | sp = [0 for i in xrange(self.nchan)] |
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391 | if start < 0: |
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392 | start = 0 |
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393 | if end < 0: |
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394 | end = self.nchan |
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395 | for i in xrange(nrow/self.npol): |
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396 | for ip in xrange(self.npol): |
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397 | sp = s._getspectrum( irow )[start:end] |
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398 | spectra[ip,i] = numpy.mean( sp ) |
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399 | irow += 1 |
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400 | |
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401 | return spectra |
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402 | |
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403 | def __chanIndex( self, idx ): |
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404 | s = scantable( self.outfile, average=False ) |
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405 | nrow = s.nrow() |
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406 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
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407 | irow = 0 |
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408 | sp = [0 for i in xrange(self.nchan)] |
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409 | for i in xrange(nrow/self.npol): |
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410 | for ip in xrange(self.npol): |
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411 | sp = s._getspectrum( irow ) |
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412 | spectra[ip,i] = sp[idx] |
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413 | irow += 1 |
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414 | return spectra |
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415 | |
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416 | |
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