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, stgrid2 |
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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_base(object): |
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10 | def __init__( self ): |
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11 | self.outfile = None |
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12 | self.ifno = None |
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13 | self.gridder = None |
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14 | self.infile = None |
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15 | self.scantab = None |
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16 | |
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17 | def setData( self, infile ): |
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18 | raise NotImplementedError('setData is not implemented') |
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19 | |
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20 | def setIF( self, ifno ): |
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21 | """ |
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22 | Set IFNO to be processed. Currently, asapgrid allows to process |
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23 | only one IFNO for one gridding run even if the data contains |
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24 | multiple IFs. If you didn't specify IFNO, default value, which |
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25 | is IFNO in the first spectrum, will be processed. |
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26 | |
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27 | ifno -- IFNO to be processed. |
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28 | """ |
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29 | self.ifno = ifno |
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30 | self.gridder._setif( self.ifno ) |
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31 | |
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32 | def setPolList( self, pollist ): |
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33 | """ |
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34 | Set list of polarization components you want to process. |
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35 | If not specified, all POLNOs will be processed. |
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36 | |
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37 | pollist -- list of POLNOs. |
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38 | """ |
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39 | self.gridder._setpollist( pollist ) |
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40 | |
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41 | def setScanList( self, scanlist ): |
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42 | """ |
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43 | Set list of scans you want to process. If not specified, all |
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44 | scans will be processed. |
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45 | |
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46 | scanlist -- list of SCANNOs. |
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47 | """ |
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48 | self.gridder._setscanlist( scanlist ) |
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49 | |
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50 | def defineImage( self, nx=-1, ny=-1, cellx='', celly='', center='' ): |
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51 | """ |
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52 | Define spatial grid. |
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53 | |
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54 | First two parameters, nx and ny, define number of pixels of |
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55 | the grid. If which of those is not specified, it will be set |
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56 | to the same value as the other. If none of them are specified, |
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57 | it will be determined from map extent and cell size. |
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58 | |
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59 | Next two parameters, cellx and celly, define size of pixel. |
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60 | You should set those parameters as string, which is constructed |
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61 | numerical value and unit, e.g. '0.5arcmin', or numerical value. |
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62 | If those values are specified as numerical value, their units |
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63 | will be assumed to 'arcsec'. If which of those is not specified, |
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64 | it will be set to the same value as the other. If none of them |
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65 | are specified, it will be determined from map extent and number |
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66 | of pixels, or set to '1arcmin' if neither nx nor ny is set. |
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67 | |
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68 | The last parameter, center, define the central coordinate of |
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69 | the grid. You should specify its value as a string, like, |
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70 | |
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71 | 'J2000 05h08m50s -16d23m30s' |
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72 | |
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73 | or |
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74 | |
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75 | 'J2000 05:08:50 -16.23.30' |
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76 | |
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77 | You can omit equinox when you specify center coordinate. In that |
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78 | case, J2000 is assumed. If center is not specified, it will be |
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79 | determined from the observed positions of input data. |
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80 | |
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81 | nx -- number of pixels along x (R.A.) direction. |
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82 | ny -- number of pixels along y (Dec.) direction. |
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83 | cellx -- size of pixel in x (R.A.) direction. |
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84 | celly -- size of pixel in y (Dec.) direction. |
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85 | center -- central position of the grid. |
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86 | """ |
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87 | if not isinstance( cellx, str ): |
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88 | cellx = '%sarcsec'%(cellx) |
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89 | if not isinstance( celly, str ): |
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90 | celly = '%sarcsec'%(celly) |
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91 | self.gridder._defineimage( nx, ny, cellx, celly, center ) |
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92 | |
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93 | def setFunc( self, func='box', convsupport=-1, truncate="-1", gwidth="-1", jwidth="-1" ): |
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94 | """ |
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95 | Set convolution function. Possible options are 'box' (Box-car, |
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96 | default), 'sf' (prolate spheroidal), 'gauss' (Gaussian), and |
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97 | 'gjinc' (Gaussian * Jinc). |
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98 | Width of convolution function can be set using several parameters. |
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99 | For 'box' and 'sf', we have one parameter, convsupport, that |
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100 | specifies a cut-off radius of the convlolution function. By default |
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101 | (-1), convsupport is automatically set depending on each convolution |
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102 | function. Default values for convsupport are: |
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103 | |
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104 | 'box': 1 pixel |
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105 | 'sf': 3 pixels |
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106 | |
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107 | For 'gauss', we have two parameters for convolution function, |
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108 | truncate and gwidth. The truncate is similar to convsupport |
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109 | except that truncate allows to specify its value as float or |
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110 | string consisting of numeric and unit (e.g. '10arcsec' or |
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111 | '3pixel'). Available units are angular units ('arcsec', 'arcmin', |
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112 | 'deg', etc.) and 'pixel'. Default unit is 'pixel' so that if |
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113 | you specify numerical value or string without unit to gwidth, |
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114 | the value will be interpreted as 'pixel'. gwidth is an HWHM of |
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115 | gaussian. It also allows string value. Interpretation of the |
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116 | value for gwidth is same as truncate. Default value for 'gauss' |
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117 | is |
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118 | |
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119 | gwidth: '-1' ---> sqrt(log(2.0)) pixel |
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120 | truncate: '-1' ---> 3*gwidth pixel |
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121 | |
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122 | For 'gjinc', there is an additional parameter jwidth that |
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123 | specifies a width of the jinc function whose functional form is |
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124 | |
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125 | jinc(x) = J_1(pi*x/jwidth) / (pi*x/jwidth) |
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126 | |
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127 | Default values for 'gjinc' is |
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128 | |
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129 | gwidth: '-1' ---> 2.52*sqrt(log(2.0)) pixel |
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130 | jwidth: '-1' ---> 1.55 |
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131 | truncate: '-1' ---> automatically truncate at first null |
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132 | |
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133 | Default values for gwidth and jwidth are taken from Mangum et al. |
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134 | (2007). |
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135 | |
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136 | func -- Function type ('box', 'sf', 'gauss', 'gjinc'). |
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137 | convsupport -- Width of convolution function. Default (-1) is |
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138 | to choose pre-defined value for each convolution |
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139 | function. Effective only for 'box' and 'sf'. |
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140 | truncate -- Truncation radius of the convolution function. |
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141 | Acceptable value is an integer or a float in units of |
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142 | pixel, or a string consisting of numeric plus unit. |
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143 | Default unit for the string is 'pixel'. Default (-1) |
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144 | is to choose pre-defined value for each convolution |
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145 | function. Effective only for 'gauss' and 'gjinc'. |
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146 | gwidth -- The HWHM of the gaussian. Acceptable value is an integer |
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147 | or a float in units of pixel, or a string consisting of |
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148 | numeric plus unit. Default unit for the string is 'pixel'. |
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149 | Default (-1) is to choose pre-defined value for each |
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150 | convolution function. Effective only for 'gauss' and |
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151 | 'gjinc'. |
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152 | jwidth -- The width of the jinc function. Acceptable value is an |
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153 | integer or a float in units of pixel, or a string |
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154 | consisting of numeric plus unit. Default unit for the |
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155 | string is 'pixel'. Default (-1) is to choose pre-defined |
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156 | value for each convolution function. Effective only for |
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157 | 'gjinc'. |
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158 | """ |
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159 | self.gridder._setfunc(func, |
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160 | convsupport=convsupport, |
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161 | truncate=truncate, |
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162 | gwidth=gwidth, |
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163 | jwidth=jwidth) |
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164 | |
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165 | def setWeight( self, weightType='uniform' ): |
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166 | """ |
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167 | Set weight type. Possible options are 'uniform' (default), |
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168 | 'tint' (weight by integration time), 'tsys' (weight by |
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169 | Tsys: 1/Tsys**2), and 'tintsys' (weight by integration time |
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170 | as well as Tsys: tint/Tsys**2). |
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171 | |
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172 | weightType -- weight type ('uniform', 'tint', 'tsys', 'tintsys') |
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173 | """ |
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174 | self.gridder._setweight( weightType ) |
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175 | |
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176 | def enableClip( self ): |
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177 | """ |
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178 | Enable min/max clipping. |
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179 | |
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180 | By default, min/max clipping is disabled so that you should |
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181 | call this method before actual gridding if you want to do |
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182 | clipping. |
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183 | """ |
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184 | self.gridder._enableclip() |
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185 | |
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186 | def disableClip( self ): |
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187 | """ |
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188 | Disable min/max clipping. |
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189 | """ |
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190 | self.gridder._disableclip() |
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191 | |
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192 | def grid( self ): |
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193 | """ |
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194 | Actual gridding which will be done based on several user inputs. |
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195 | """ |
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196 | self.gridder._grid() |
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197 | |
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198 | def plotFunc(self, clear=True): |
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199 | """ |
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200 | Support function to see the shape of current grid function. |
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201 | |
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202 | clear -- clear panel if True. Default is True. |
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203 | """ |
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204 | pl.figure(11) |
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205 | if clear: |
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206 | pl.clf() |
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207 | f = self.gridder._getfunc() |
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208 | convsampling = 100 |
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209 | a = numpy.arange(0,len(f)/convsampling,1./convsampling,dtype=float) |
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210 | pl.plot(a,f,'.-') |
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211 | pl.xlabel('pixel') |
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212 | pl.ylabel('convFunc') |
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213 | |
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214 | def save( self, outfile='' ): |
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215 | raise NotImplementedError('save is not implemented') |
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216 | |
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217 | def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ): |
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218 | raise NotImplementedError('plot is not implemented') |
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219 | |
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220 | def getResult( self ): |
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221 | raise NotImplementedError('getResult is not implemented') |
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222 | |
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223 | class asapgrid(asapgrid_base): |
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224 | """ |
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225 | The asapgrid class is defined to convolve data onto regular |
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226 | spatial grid. Typical usage is as follows: |
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227 | |
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228 | # create asapgrid instance with two input data |
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229 | g = asapgrid( ['testimage1.asap','testimage2.asap'] ) |
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230 | # set IFNO if necessary |
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231 | g.setIF( 0 ) |
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232 | # set POLNOs if necessary |
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233 | g.setPolList( [0,1] ) |
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234 | # set SCANNOs if necessary |
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235 | g.setScanList( [22,23,24] ) |
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236 | # define image with full specification |
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237 | # you can skip some parameters (see help for defineImage) |
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238 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
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239 | center='J2000 10h10m10s -5d05m05s' ) |
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240 | # set convolution function |
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241 | g.setFunc( func='sf', convsupport=3 ) |
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242 | # enable min/max clipping |
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243 | g.enableClip() |
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244 | # or, disable min/max clipping |
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245 | #g.disableClip() |
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246 | # actual gridding |
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247 | g.grid() |
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248 | # save result |
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249 | g.save( outfile='grid.asap' ) |
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250 | # plot result |
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251 | g.plot( plotchan=1246, plotpol=-1, plotgrid=True, plotobs=True ) |
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252 | """ |
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253 | def __init__( self, infile ): |
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254 | """ |
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255 | Create asapgrid instance. |
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256 | |
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257 | infile -- input data as a string or string list if you want |
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258 | to grid more than one data at once. |
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259 | """ |
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260 | super(asapgrid,self).__init__() |
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261 | self.gridder = stgrid() |
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262 | self.infile=infile |
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263 | self.setData(infile) |
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264 | |
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265 | def setData( self, infile ): |
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266 | """ |
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267 | Set data to be processed. |
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268 | |
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269 | infile -- input data as a string or string list if you want |
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270 | to grid more than one data at once. |
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271 | """ |
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272 | if isinstance( infile, str ): |
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273 | self.gridder._setin( infile ) |
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274 | else: |
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275 | self.gridder._setfiles( infile ) |
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276 | self.infile = infile |
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277 | |
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278 | def save( self, outfile='' ): |
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279 | """ |
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280 | Save result. By default, output data name will be constructed |
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281 | from first element of input data name list (e.g. 'input.asap.grid'). |
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282 | |
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283 | outfile -- output data name. |
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284 | """ |
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285 | self.outfile = self.gridder._save( outfile ) |
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286 | |
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287 | def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ): |
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288 | """ |
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289 | Plot gridded data. |
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290 | |
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291 | plotchan -- Which channel you want to plot. Default (-1) is |
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292 | to average all the channels. |
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293 | plotpol -- Which polarization component you want to plot. |
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294 | Default (-1) is to average all the polarization |
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295 | components. |
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296 | plotobs -- Also plot observed position if True. Default |
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297 | is False. Setting True for large amount of spectra |
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298 | might be time consuming. |
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299 | plotgrid -- Also plot grid center if True. Default is False. |
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300 | Setting True for large number of grids might be |
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301 | time consuming. |
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302 | """ |
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303 | import time |
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304 | t0=time.time() |
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305 | # to load scantable on disk |
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306 | storg = rcParams['scantable.storage'] |
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307 | rcParams['scantable.storage'] = 'disk' |
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308 | [nx,ny] = self.gridder._get_resultant_map_size() |
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309 | [cellx,celly] = self.gridder._get_resultant_cell_size() |
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310 | plotter = _SDGridPlotter( self.infile, self.outfile, self.ifno, |
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311 | nx=nx, ny=ny, cellx=cellx, celly=celly ) |
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312 | plotter.plot( chan=plotchan, pol=plotpol, plotobs=plotobs, plotgrid=plotgrid ) |
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313 | # back to original setup |
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314 | rcParams['scantable.storage'] = storg |
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315 | t1=time.time() |
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316 | asaplog.push('plot: elapsed time %s sec'%(t1-t0)) |
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317 | asaplog.post('DEBUG','asapgrid.plot') |
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318 | |
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319 | class asapgrid2(asapgrid_base): |
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320 | """ |
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321 | The asapgrid class is defined to convolve data onto regular |
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322 | spatial grid. Typical usage is as follows: |
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323 | |
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324 | # create asapgrid instance with input scantable |
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325 | s = scantable( 'testimage1.asap', average=False ) |
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326 | g = asapgrid( s ) |
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327 | # set IFNO if necessary |
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328 | g.setIF( 0 ) |
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329 | # set POLNOs if necessary |
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330 | g.setPolList( [0,1] ) |
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331 | # set SCANNOs if necessary |
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332 | g.setScanList( [22,23,24] ) |
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333 | # define image with full specification |
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334 | # you can skip some parameters (see help for defineImage) |
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335 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
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336 | center='J2000 10h10m10s -5d05m05s' ) |
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337 | # set convolution function |
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338 | g.setFunc( func='sf', width=3 ) |
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339 | # enable min/max clipping |
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340 | g.enableClip() |
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341 | # or, disable min/max clipping |
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342 | #g.disableClip() |
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343 | # actual gridding |
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344 | g.grid() |
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345 | # get result as scantable |
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346 | sg = g.getResult() |
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347 | """ |
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348 | def __init__( self, scantab ): |
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349 | """ |
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350 | Create asapgrid instance. |
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351 | |
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352 | scantab -- input data as a scantable or a list of scantables |
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353 | to grid more than one data at once. |
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354 | """ |
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355 | super(asapgrid2,self).__init__() |
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356 | self.gridder = stgrid2() |
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357 | self.scantab = scantab |
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358 | self.setData( scantab ) |
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359 | |
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360 | def setData( self, scantab ): |
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361 | """ |
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362 | Set data to be processed. |
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363 | |
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364 | scantab -- input data as a scantable or a list of scantables |
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365 | to grid more than one data at once. |
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366 | """ |
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367 | if isinstance( scantab, scantable ): |
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368 | self.gridder._setin( scantab ) |
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369 | else: |
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370 | self.gridder._setfiles( scantab ) |
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371 | self.scantab = scantab |
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372 | |
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373 | def getResult( self ): |
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374 | """ |
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375 | Return gridded data as a scantable. |
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376 | """ |
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377 | tp = 0 if rcParams['scantable.storage']=='memory' else 1 |
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378 | return scantable( self.gridder._get( tp ), average=False ) |
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379 | |
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380 | class _SDGridPlotter: |
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381 | def __init__( self, infile, outfile=None, ifno=-1, nx=-1, ny=-1, cellx=0.0, celly=0.0 ): |
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382 | if isinstance( infile, str ): |
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383 | self.infile = [infile] |
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384 | else: |
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385 | self.infile = infile |
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386 | self.outfile = outfile |
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387 | if self.outfile is None: |
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388 | self.outfile = self.infile[0].rstrip('/')+'.grid' |
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389 | self.nx = nx |
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390 | self.ny = ny if ny > 0 else nx |
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391 | self.nchan = 0 |
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392 | self.npol = 0 |
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393 | self.pollist = [] |
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394 | self.cellx = cellx |
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395 | self.celly = celly if celly > 0.0 else cellx |
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396 | self.center = [0.0,0.0] |
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397 | self.nonzero = [[0.0],[0.0]] |
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398 | self.ifno = ifno |
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399 | self.tablein = None |
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400 | self.nrow = 0 |
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401 | self.blc = None |
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402 | self.trc = None |
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403 | self.get() |
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404 | |
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405 | def get( self ): |
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406 | s = scantable( self.outfile, average=False ) |
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407 | self.nchan = len(s._getspectrum(0)) |
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408 | nrow = s.nrow() |
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409 | pols = numpy.ones( nrow, dtype=int ) |
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410 | for i in xrange(nrow): |
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411 | pols[i] = s.getpol(i) |
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412 | self.pollist, indices = numpy.unique( pols, return_inverse=True ) |
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413 | self.npol = len(self.pollist) |
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414 | self.pollist = self.pollist[indices[:self.npol]] |
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415 | #print 'pollist=',self.pollist |
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416 | #print 'npol=',self.npol |
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417 | #print 'nrow=',nrow |
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418 | |
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419 | if self.nx <= 0 or self.ny <= 0: |
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420 | idx = 1 |
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421 | d0 = s.get_direction( 0 ).split()[-2] |
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422 | d = s.get_direction(self.npol*idx) |
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423 | while( d is not None \ |
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424 | and d.split()[-2] != d0): |
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425 | idx += 1 |
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426 | d = s.get_direction(self.npol*idx) |
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427 | |
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428 | self.nx = idx |
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429 | self.ny = nrow / (self.npol * idx ) |
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430 | #print 'nx,ny=',self.nx,self.ny |
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431 | |
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432 | self.blc = s.get_directionval( 0 ) |
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433 | self.trc = s.get_directionval( nrow-self.npol ) |
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434 | #print self.blc |
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435 | #print self.trc |
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436 | |
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437 | if self.cellx <= 0.0 or self.celly <= 0.0: |
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438 | if nrow > 1: |
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439 | incrx = s.get_directionval( self.npol ) |
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440 | incry = s.get_directionval( self.nx*self.npol ) |
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441 | else: |
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442 | incrx = [0.0,0.0] |
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443 | incry = [0.0,0.0] |
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444 | self.cellx = abs( self.blc[0] - incrx[0] ) |
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445 | self.celly = abs( self.blc[1] - incry[1] ) |
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446 | #print 'cellx,celly=',self.cellx,self.celly |
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447 | |
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448 | def plot( self, chan=-1, pol=-1, plotobs=False, plotgrid=False ): |
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449 | if pol < 0: |
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450 | opt = 'averaged over pol' |
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451 | else: |
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452 | opt = 'pol %s'%(pol) |
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453 | if type(chan) is list: |
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454 | opt += ', averaged over channel %s-%s'%(chan[0],chan[1]) |
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455 | elif chan < 0: |
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456 | opt += ', averaged over channel' |
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457 | else: |
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458 | opt += ', channel %s'%(chan) |
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459 | data = self.getData( chan, pol ) |
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460 | #data = numpy.fliplr( data ) |
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461 | title = 'Gridded Image (%s)'%(opt) |
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462 | pl.figure(10) |
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463 | pl.clf() |
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464 | # plot grid position |
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465 | if plotgrid: |
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466 | x = numpy.arange(self.blc[0],self.trc[0]+0.5*self.cellx,self.cellx,dtype=float) |
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467 | #print 'len(x)=',len(x) |
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468 | #print 'x=',x |
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469 | ybase = numpy.ones(self.nx,dtype=float)*self.blc[1] |
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470 | #print 'len(ybase)=',len(ybase) |
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471 | incr = self.celly |
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472 | for iy in xrange(self.ny): |
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473 | y = ybase + iy * incr |
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474 | #print y |
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475 | pl.plot(x,y,',',color='blue') |
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476 | # plot observed position |
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477 | if plotobs: |
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478 | for i in xrange(len(self.infile)): |
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479 | self.createTableIn( self.infile[i] ) |
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480 | irow = 0 |
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481 | while ( irow < self.nrow ): |
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482 | chunk = self.getPointingChunk( irow ) |
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483 | #print chunk |
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484 | pl.plot(chunk[0],chunk[1],',',color='green') |
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485 | irow += chunk.shape[1] |
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486 | #print irow |
---|
487 | # show image |
---|
488 | extent=[self.trc[0]+0.5*self.cellx, |
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489 | self.blc[0]-0.5*self.cellx, |
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490 | self.blc[1]-0.5*self.celly, |
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491 | self.trc[1]+0.5*self.celly] |
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492 | deccorr = 1.0/numpy.cos(0.5*(self.blc[1]+self.trc[1])) |
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493 | pl.imshow(data,extent=extent,origin='lower',interpolation='nearest') |
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494 | pl.colorbar() |
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495 | pl.xlabel('R.A. [rad]') |
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496 | pl.ylabel('Dec. [rad]') |
---|
497 | ax = pl.axes() |
---|
498 | ax.set_aspect(deccorr) |
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499 | pl.title( title ) |
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500 | |
---|
501 | def createTableIn( self, tab ): |
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502 | del self.tablein |
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503 | self.tablein = scantable( tab, average=False ) |
---|
504 | if self.ifno < 0: |
---|
505 | ifno = self.tablein.getif(0) |
---|
506 | #print 'ifno=',ifno |
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507 | else: |
---|
508 | ifno = self.ifno |
---|
509 | sel = selector() |
---|
510 | sel.set_ifs( ifno ) |
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511 | self.tablein.set_selection( sel ) |
---|
512 | self.nchan = len(self.tablein._getspectrum(0)) |
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513 | self.nrow = self.tablein.nrow() |
---|
514 | del sel |
---|
515 | |
---|
516 | |
---|
517 | def getPointingChunk( self, irow ): |
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518 | numchunk = 1000 |
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519 | nrow = min( self.nrow-irow, numchunk ) |
---|
520 | #print 'nrow=',nrow |
---|
521 | v = numpy.zeros( (2,nrow), dtype=float ) |
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522 | idx = 0 |
---|
523 | for i in xrange(irow,irow+nrow): |
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524 | d = self.tablein.get_directionval( i ) |
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525 | v[0,idx] = d[0] |
---|
526 | v[1,idx] = d[1] |
---|
527 | idx += 1 |
---|
528 | return v |
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529 | |
---|
530 | def getData( self, chan=-1, pol=-1 ): |
---|
531 | if type(chan) == list: |
---|
532 | spectra = self.__chanAverage(start=chan[0],end=chan[1]) |
---|
533 | elif chan == -1: |
---|
534 | spectra = self.__chanAverage() |
---|
535 | else: |
---|
536 | spectra = self.__chanIndex( chan ) |
---|
537 | data = spectra.reshape( (self.npol,self.ny,self.nx) ) |
---|
538 | if pol == -1: |
---|
539 | retval = data.mean(axis=0) |
---|
540 | else: |
---|
541 | retval = data[pol] |
---|
542 | return retval |
---|
543 | |
---|
544 | def __chanAverage( self, start=-1, end=-1 ): |
---|
545 | s = scantable( self.outfile, average=False ) |
---|
546 | nrow = s.nrow() |
---|
547 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
---|
548 | irow = 0 |
---|
549 | sp = [0 for i in xrange(self.nchan)] |
---|
550 | if start < 0: |
---|
551 | start = 0 |
---|
552 | if end < 0: |
---|
553 | end = self.nchan |
---|
554 | for i in xrange(nrow/self.npol): |
---|
555 | for ip in xrange(self.npol): |
---|
556 | sp = s._getspectrum( irow )[start:end] |
---|
557 | spectra[ip,i] = numpy.mean( sp ) |
---|
558 | irow += 1 |
---|
559 | |
---|
560 | return spectra |
---|
561 | |
---|
562 | def __chanIndex( self, idx ): |
---|
563 | s = scantable( self.outfile, average=False ) |
---|
564 | nrow = s.nrow() |
---|
565 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
---|
566 | irow = 0 |
---|
567 | sp = [0 for i in xrange(self.nchan)] |
---|
568 | for i in xrange(nrow/self.npol): |
---|
569 | for ip in xrange(self.npol): |
---|
570 | sp = s._getspectrum( irow ) |
---|
571 | spectra[ip,i] = sp[idx] |
---|
572 | irow += 1 |
---|
573 | return spectra |
---|
574 | |
---|
575 | |
---|