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