| 1 | import numpy |
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| 2 | from asap.scantable import scantable |
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| 3 | from asap._asap import stgrid |
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| 4 | import pylab as pl |
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| 5 | |
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| 6 | class asapgrid: |
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| 7 | def __init__( self, infile ): |
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| 8 | self.infile = infile |
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| 9 | self.outfile = None |
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| 10 | self.gridder = stgrid( self.infile ) |
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| 11 | |
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| 12 | def setData( self, infile ): |
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| 13 | self.gridder._setin( infile ) |
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| 14 | |
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| 15 | def defineImage( self, nx=-1, ny=-1, cellx='', celly='', center='' ): |
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| 16 | self.gridder._defineimage( nx, ny, cellx, celly, center ) |
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| 17 | |
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| 18 | def setOption( self, convType='box', convSupport=-1 ): |
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| 19 | self.gridder._setoption( convType, convSupport ) |
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| 20 | |
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| 21 | def grid( self ): |
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| 22 | self.gridder._grid() |
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| 23 | |
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| 24 | def save( self, outfile='' ): |
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| 25 | self.outfile = self.gridder._save( outfile ) |
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| 26 | |
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| 27 | def plot( self, plotchan=-1 ): |
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| 28 | plotter = _SDGridPlotter( self.infile, self.outfile ) |
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| 29 | plotter.plot( chan=plotchan ) |
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| 30 | |
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| 31 | class _SDGridPlotter: |
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| 32 | def __init__( self, infile, outfile=None ): |
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| 33 | self.infile = infile |
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| 34 | self.outfile = outfile |
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| 35 | if self.outfile is None: |
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| 36 | self.outfile = self.infile.rstrip('/')+'.grid' |
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| 37 | self.grid = None |
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| 38 | self.pointing = None |
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| 39 | self.data = None |
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| 40 | self.nx = -1 |
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| 41 | self.ny = -1 |
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| 42 | self.nchan = 0 |
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| 43 | self.cellx = 0.0 |
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| 44 | self.celly = 0.0 |
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| 45 | self.center = [0.0,0.0] |
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| 46 | self.nonzero = [[0.0],[0.0]] |
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| 47 | self.get() |
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| 48 | |
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| 49 | def get( self ): |
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| 50 | s = scantable( self.infile, average=False ) |
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| 51 | self.pointing = numpy.array( s.get_directionval() ).transpose() |
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| 52 | spectra = [] |
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| 53 | for i in xrange(s.nrow()): |
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| 54 | spectra.append( s._getspectrum( i ) ) |
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| 55 | spectra = numpy.array( spectra ).transpose() |
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| 56 | self.nchan = spectra.shape[0] |
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| 57 | del s |
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| 58 | |
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| 59 | idx = spectra.nonzero()[1] |
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| 60 | #self.nonzero = self.pointing.take( idx, axis=1 ) |
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| 61 | |
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| 62 | s = scantable( self.outfile, average=False ) |
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| 63 | self.grid = numpy.array( s.get_directionval() ).transpose() |
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| 64 | dirstring = s.get_direction() |
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| 65 | nrow = s.nrow() |
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| 66 | spectra = [] |
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| 67 | for i in xrange(nrow): |
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| 68 | spectra.append( s._getspectrum( i ) ) |
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| 69 | spectra = numpy.array( spectra ).transpose() |
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| 70 | |
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| 71 | idx = 0 |
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| 72 | d0 = dirstring[0].split()[-1] |
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| 73 | while ( dirstring[idx].split()[-1] == d0 ): |
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| 74 | idx += 1 |
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| 75 | |
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| 76 | self.ny = idx |
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| 77 | self.nx = nrow / idx |
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| 78 | |
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| 79 | self.cellx = abs( self.grid[0][0] - self.grid[0][1] ) |
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| 80 | self.celly = abs( self.grid[1][0] - self.grid[1][self.ny] ) |
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| 81 | |
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| 82 | self.data = spectra.reshape( (self.nchan,self.nx,self.ny) ) |
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| 83 | |
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| 84 | def plot( self, chan=-1 ): |
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| 85 | if chan < 0: |
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| 86 | data = self.data.mean(axis=0) |
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| 87 | title = 'Gridded Image (averaged over channel)' |
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| 88 | else: |
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| 89 | data = self.data[chan] |
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| 90 | title = 'Gridded Image (channel %s)'%(chan) |
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| 91 | pl.figure(10) |
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| 92 | pl.clf() |
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| 93 | pl.plot(self.grid[0],self.grid[1],'.',color='blue') |
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| 94 | pl.plot(self.pointing[0],self.pointing[1],'.',color='red') |
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| 95 | #pl.plot(self.nonzero[0],self.nonzero[1],'o',color='green') |
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| 96 | extent=[self.grid[0].min()-0.5*self.cellx, |
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| 97 | self.grid[0].max()+0.5*self.cellx, |
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| 98 | self.grid[1].min()-0.5*self.celly, |
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| 99 | self.grid[1].max()+0.5*self.celly] |
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| 100 | pl.imshow(data,extent=extent,origin='lower',interpolation='nearest') |
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| 101 | pl.colorbar() |
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| 102 | pl.xlabel('R.A. [rad]') |
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| 103 | pl.ylabel('Dec. [rad]') |
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| 104 | pl.title( title ) |
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