| 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 | plotter = _SDGridPlotter( self.infile, self.outfile, self.ifno ) |
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| 309 | plotter.plot( chan=plotchan, pol=plotpol, plotobs=plotobs, plotgrid=plotgrid ) |
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| 310 | # back to original setup |
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| 311 | rcParams['scantable.storage'] = storg |
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| 312 | t1=time.time() |
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| 313 | asaplog.push('plot: elapsed time %s sec'%(t1-t0)) |
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| 314 | asaplog.post('DEBUG','asapgrid.plot') |
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| 315 | |
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| 316 | class asapgrid2(asapgrid_base): |
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| 317 | """ |
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| 318 | The asapgrid class is defined to convolve data onto regular |
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| 319 | spatial grid. Typical usage is as follows: |
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| 320 | |
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| 321 | # create asapgrid instance with input scantable |
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| 322 | s = scantable( 'testimage1.asap', average=False ) |
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| 323 | g = asapgrid( s ) |
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| 324 | # set IFNO if necessary |
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| 325 | g.setIF( 0 ) |
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| 326 | # set POLNOs if necessary |
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| 327 | g.setPolList( [0,1] ) |
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| 328 | # set SCANNOs if necessary |
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| 329 | g.setScanList( [22,23,24] ) |
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| 330 | # define image with full specification |
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| 331 | # you can skip some parameters (see help for defineImage) |
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| 332 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
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| 333 | center='J2000 10h10m10s -5d05m05s' ) |
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| 334 | # set convolution function |
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| 335 | g.setFunc( func='sf', width=3 ) |
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| 336 | # enable min/max clipping |
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| 337 | g.enableClip() |
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| 338 | # or, disable min/max clipping |
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| 339 | #g.disableClip() |
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| 340 | # actual gridding |
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| 341 | g.grid() |
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| 342 | # get result as scantable |
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| 343 | sg = g.getResult() |
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| 344 | """ |
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| 345 | def __init__( self, scantab ): |
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| 346 | """ |
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| 347 | Create asapgrid instance. |
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| 348 | |
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| 349 | scantab -- input data as a scantable or a list of scantables |
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| 350 | to grid more than one data at once. |
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| 351 | """ |
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| 352 | super(asapgrid2,self).__init__() |
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| 353 | self.gridder = stgrid2() |
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| 354 | self.scantab = scantab |
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| 355 | self.setData( scantab ) |
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| 356 | |
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| 357 | def setData( self, scantab ): |
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| 358 | """ |
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| 359 | Set data to be processed. |
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| 360 | |
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| 361 | scantab -- input data as a scantable or a list of scantables |
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| 362 | to grid more than one data at once. |
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| 363 | """ |
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| 364 | if isinstance( scantab, scantable ): |
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| 365 | self.gridder._setin( scantab ) |
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| 366 | else: |
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| 367 | self.gridder._setfiles( scantab ) |
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| 368 | self.scantab = scantab |
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| 369 | |
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| 370 | def getResult( self ): |
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| 371 | """ |
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| 372 | Return gridded data as a scantable. |
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| 373 | """ |
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| 374 | tp = 0 if rcParams['scantable.storage']=='memory' else 1 |
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| 375 | return scantable( self.gridder._get( tp ), average=False ) |
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| 376 | |
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| 377 | class _SDGridPlotter: |
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| 378 | def __init__( self, infile, outfile=None, ifno=-1 ): |
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| 379 | if isinstance( infile, str ): |
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| 380 | self.infile = [infile] |
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| 381 | else: |
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| 382 | self.infile = infile |
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| 383 | self.outfile = outfile |
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| 384 | if self.outfile is None: |
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| 385 | self.outfile = self.infile[0].rstrip('/')+'.grid' |
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| 386 | self.nx = -1 |
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| 387 | self.ny = -1 |
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| 388 | self.nchan = 0 |
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| 389 | self.npol = 0 |
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| 390 | self.pollist = [] |
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| 391 | self.cellx = 0.0 |
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| 392 | self.celly = 0.0 |
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| 393 | self.center = [0.0,0.0] |
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| 394 | self.nonzero = [[0.0],[0.0]] |
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| 395 | self.ifno = ifno |
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| 396 | self.tablein = None |
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| 397 | self.nrow = 0 |
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| 398 | self.blc = None |
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| 399 | self.trc = None |
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| 400 | self.get() |
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| 401 | |
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| 402 | def get( self ): |
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| 403 | s = scantable( self.outfile, average=False ) |
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| 404 | self.nchan = len(s._getspectrum(0)) |
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| 405 | nrow = s.nrow() |
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| 406 | pols = numpy.ones( nrow, dtype=int ) |
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| 407 | for i in xrange(nrow): |
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| 408 | pols[i] = s.getpol(i) |
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| 409 | self.pollist, indices = numpy.unique( pols, return_inverse=True ) |
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| 410 | self.npol = len(self.pollist) |
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| 411 | self.pollist = self.pollist[indices[:self.npol]] |
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| 412 | #print 'pollist=',self.pollist |
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| 413 | #print 'npol=',self.npol |
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| 414 | #print 'nrow=',nrow |
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| 415 | |
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| 416 | idx = 1 |
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| 417 | d0 = s.get_direction( 0 ).split()[-2] |
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| 418 | d = s.get_direction(self.npol*idx) |
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| 419 | while( d is not None \ |
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| 420 | and d.split()[-2] != d0): |
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| 421 | idx += 1 |
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| 422 | d = s.get_direction(self.npol*idx) |
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| 423 | |
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| 424 | self.nx = idx |
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| 425 | self.ny = nrow / (self.npol * idx ) |
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| 426 | #print 'nx,ny=',self.nx,self.ny |
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| 427 | |
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| 428 | self.blc = s.get_directionval( 0 ) |
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| 429 | self.trc = s.get_directionval( nrow-self.npol ) |
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| 430 | #print self.blc |
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| 431 | #print self.trc |
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| 432 | if nrow > 1: |
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| 433 | incrx = s.get_directionval( self.npol ) |
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| 434 | incry = s.get_directionval( self.nx*self.npol ) |
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| 435 | else: |
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| 436 | incrx = [0.0,0.0] |
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| 437 | incry = [0.0,0.0] |
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| 438 | self.cellx = abs( self.blc[0] - incrx[0] ) |
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| 439 | self.celly = abs( self.blc[1] - incry[1] ) |
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| 440 | #print 'cellx,celly=',self.cellx,self.celly |
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| 441 | |
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| 442 | def plot( self, chan=-1, pol=-1, plotobs=False, plotgrid=False ): |
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| 443 | if pol < 0: |
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| 444 | opt = 'averaged over pol' |
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| 445 | else: |
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| 446 | opt = 'pol %s'%(pol) |
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| 447 | if type(chan) is list: |
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| 448 | opt += ', averaged over channel %s-%s'%(chan[0],chan[1]) |
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| 449 | elif chan < 0: |
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| 450 | opt += ', averaged over channel' |
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| 451 | else: |
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| 452 | opt += ', channel %s'%(chan) |
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| 453 | data = self.getData( chan, pol ) |
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| 454 | #data = numpy.fliplr( data ) |
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| 455 | title = 'Gridded Image (%s)'%(opt) |
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| 456 | pl.figure(10) |
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| 457 | pl.clf() |
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| 458 | # plot grid position |
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| 459 | if plotgrid: |
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| 460 | x = numpy.arange(self.blc[0],self.trc[0]+0.5*self.cellx,self.cellx,dtype=float) |
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| 461 | #print 'len(x)=',len(x) |
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| 462 | #print 'x=',x |
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| 463 | ybase = numpy.ones(self.nx,dtype=float)*self.blc[1] |
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| 464 | #print 'len(ybase)=',len(ybase) |
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| 465 | incr = self.celly |
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| 466 | for iy in xrange(self.ny): |
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| 467 | y = ybase + iy * incr |
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| 468 | #print y |
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| 469 | pl.plot(x,y,',',color='blue') |
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| 470 | # plot observed position |
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| 471 | if plotobs: |
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| 472 | for i in xrange(len(self.infile)): |
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| 473 | self.createTableIn( self.infile[i] ) |
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| 474 | irow = 0 |
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| 475 | while ( irow < self.nrow ): |
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| 476 | chunk = self.getPointingChunk( irow ) |
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| 477 | #print chunk |
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| 478 | pl.plot(chunk[0],chunk[1],',',color='green') |
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| 479 | irow += chunk.shape[1] |
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| 480 | #print irow |
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| 481 | # show image |
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| 482 | extent=[self.trc[0]+0.5*self.cellx, |
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| 483 | self.blc[0]-0.5*self.cellx, |
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| 484 | self.blc[1]-0.5*self.celly, |
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| 485 | self.trc[1]+0.5*self.celly] |
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| 486 | deccorr = 1.0/numpy.cos(0.5*(self.blc[1]+self.trc[1])) |
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| 487 | pl.imshow(data,extent=extent,origin='lower',interpolation='nearest') |
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| 488 | pl.colorbar() |
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| 489 | pl.xlabel('R.A. [rad]') |
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| 490 | pl.ylabel('Dec. [rad]') |
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| 491 | ax = pl.axes() |
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| 492 | ax.set_aspect(deccorr) |
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| 493 | pl.title( title ) |
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| 494 | |
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| 495 | def createTableIn( self, tab ): |
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| 496 | del self.tablein |
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| 497 | self.tablein = scantable( tab, average=False ) |
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| 498 | if self.ifno < 0: |
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| 499 | ifno = self.tablein.getif(0) |
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| 500 | #print 'ifno=',ifno |
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| 501 | else: |
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| 502 | ifno = self.ifno |
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| 503 | sel = selector() |
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| 504 | sel.set_ifs( ifno ) |
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| 505 | self.tablein.set_selection( sel ) |
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| 506 | self.nchan = len(self.tablein._getspectrum(0)) |
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| 507 | self.nrow = self.tablein.nrow() |
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| 508 | del sel |
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| 509 | |
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| 510 | |
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| 511 | def getPointingChunk( self, irow ): |
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| 512 | numchunk = 1000 |
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| 513 | nrow = min( self.nrow-irow, numchunk ) |
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| 514 | #print 'nrow=',nrow |
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| 515 | v = numpy.zeros( (2,nrow), dtype=float ) |
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| 516 | idx = 0 |
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| 517 | for i in xrange(irow,irow+nrow): |
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| 518 | d = self.tablein.get_directionval( i ) |
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| 519 | v[0,idx] = d[0] |
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| 520 | v[1,idx] = d[1] |
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| 521 | idx += 1 |
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| 522 | return v |
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| 523 | |
|---|
| 524 | def getData( self, chan=-1, pol=-1 ): |
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| 525 | if type(chan) == list: |
|---|
| 526 | spectra = self.__chanAverage(start=chan[0],end=chan[1]) |
|---|
| 527 | elif chan == -1: |
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| 528 | spectra = self.__chanAverage() |
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| 529 | else: |
|---|
| 530 | spectra = self.__chanIndex( chan ) |
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| 531 | data = spectra.reshape( (self.npol,self.ny,self.nx) ) |
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| 532 | if pol == -1: |
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| 533 | retval = data.mean(axis=0) |
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| 534 | else: |
|---|
| 535 | retval = data[pol] |
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| 536 | return retval |
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| 537 | |
|---|
| 538 | def __chanAverage( self, start=-1, end=-1 ): |
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| 539 | s = scantable( self.outfile, average=False ) |
|---|
| 540 | nrow = s.nrow() |
|---|
| 541 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
|---|
| 542 | irow = 0 |
|---|
| 543 | sp = [0 for i in xrange(self.nchan)] |
|---|
| 544 | if start < 0: |
|---|
| 545 | start = 0 |
|---|
| 546 | if end < 0: |
|---|
| 547 | end = self.nchan |
|---|
| 548 | for i in xrange(nrow/self.npol): |
|---|
| 549 | for ip in xrange(self.npol): |
|---|
| 550 | sp = s._getspectrum( irow )[start:end] |
|---|
| 551 | spectra[ip,i] = numpy.mean( sp ) |
|---|
| 552 | irow += 1 |
|---|
| 553 | |
|---|
| 554 | return spectra |
|---|
| 555 | |
|---|
| 556 | def __chanIndex( self, idx ): |
|---|
| 557 | s = scantable( self.outfile, average=False ) |
|---|
| 558 | nrow = s.nrow() |
|---|
| 559 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
|---|
| 560 | irow = 0 |
|---|
| 561 | sp = [0 for i in xrange(self.nchan)] |
|---|
| 562 | for i in xrange(nrow/self.npol): |
|---|
| 563 | for ip in xrange(self.npol): |
|---|
| 564 | sp = s._getspectrum( irow ) |
|---|
| 565 | spectra[ip,i] = sp[idx] |
|---|
| 566 | irow += 1 |
|---|
| 567 | return spectra |
|---|
| 568 | |
|---|
| 569 | |
|---|
