import numpy
from asap import rcParams
from asap.scantable import scantable
from asap.selector import selector
from asap._asap import stgrid
import pylab as pl
from logging import asaplog

class asapgrid:
    """
    The asapgrid class is defined to convolve data onto regular
    spatial grid. Typical usage is as follows:

       # create asapgrid instance with two input data
       g = asapgrid( ['testimage1.asap','testimage2.asap'] )
       # set IFNO if necessary
       g.setIF( 0 )
       # set POLNOs if necessary
       g.setPolList( [0,1] )
       # set SCANNOs if necessary
       g.setScanList( [22,23,24] )
       # define image with full specification
       # you can skip some parameters (see help for defineImage)
       g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec',
                      center='J2000 10h10m10s -5d05m05s' )
       # set convolution function
       g.setFunc( func='sf', width=3 )
       # enable min/max clipping
       g.enableClip()
       # or, disable min/max clipping
       #g.disableClip()
       # actual gridding
       g.grid()
       # save result
       g.save( outfile='grid.asap' )
       # plot result
       g.plot( plotchan=1246, plotpol=-1, plotgrid=True, plotobs=True )
    """
    def __init__( self, infile ):
        """
        Create asapgrid instance.

        infile -- input data as a string or string list if you want
                  to grid more than one data at once.  
        """
        self.outfile = None
        self.ifno = None
        self.gridder = stgrid()
        self.setData( infile )

    def setData( self, infile ):
        """
        Set data to be processed.

        infile -- input data as a string or string list if you want
                  to grid more than one data at once.  
        """
        if isinstance( infile, str ):
            self.gridder._setin( infile )
        else:
            self.gridder._setfiles( infile )
        self.infile = infile 

    def setIF( self, ifno ):
        """
        Set IFNO to be processed. Currently, asapgrid allows to process
        only one IFNO for one gridding run even if the data contains
        multiple IFs. If you didn't specify IFNO, default value, which
        is IFNO in the first spectrum, will be processed.

        ifno -- IFNO to be processed.
        """
        self.ifno = ifno
        self.gridder._setif( self.ifno )

    def setPolList( self, pollist ):
        """
        Set list of polarization components you want to process.
        If not specified, all POLNOs will be processed.

        pollist -- list of POLNOs.
        """
        self.gridder._setpollist( pollist )

    def setScanList( self, scanlist ):
        """
        Set list of scans you want to process. If not specified, all
        scans will be processed.

        scanlist -- list of SCANNOs.
        """
        self.gridder._setscanlist( scanlist )

    def defineImage( self, nx=-1, ny=-1, cellx='', celly='', center='' ):
        """
        Define spatial grid.

        First two parameters, nx and ny, define number of pixels of
        the grid. If which of those is not specified, it will be set
        to the same value as the other. If none of them are specified,
        it will be determined from map extent and cell size.

        Next two parameters, cellx and celly, define size of pixel.
        You should set those parameters as string, which is constructed
        numerical value and unit, e.g. '0.5arcmin', or numerical value.
        If those values are specified as numerical value, their units
        will be assumed to 'arcsec'. If which of those is not specified,
        it will be set to the same value as the other. If none of them
        are specified, it will be determined from map extent and number
        of pixels, or set to '1arcmin' if neither nx nor ny is set.

        The last parameter, center, define the central coordinate of
        the grid. You should specify its value as a string, like,

           'J2000 05h08m50s -16d23m30s'

        or 

           'J2000 05:08:50 -16.23.30'

        You can omit equinox when you specify center coordinate. In that
        case, J2000 is assumed. If center is not specified, it will be
        determined from the observed positions of input data.

        nx -- number of pixels along x (R.A.) direction.
        ny -- number of pixels along y (Dec.) direction.
        cellx -- size of pixel in x (R.A.) direction.
        celly -- size of pixel in y (Dec.) direction.
        center -- central position of the grid.
        """
        if not isinstance( cellx, str ):
            cellx = '%sarcsec'%(cellx)
        if not isinstance( celly, str ):
            celly = '%sarcsec'%(celly)
        self.gridder._defineimage( nx, ny, cellx, celly, center )

    def setFunc( self, func='box', width=-1 ):
        """
        Set convolution function. Possible options are 'box' (Box-car,
        default), 'sf' (prolate spheroidal), and 'gauss' (Gaussian).
        Width of convolution function can be set using width parameter.
        By default (-1), width is automatically set depending on each
        convolution function. Default values for width are:

           'box': 1 pixel
           'sf': 3 pixels
           'gauss': 3 pixels (width is used as HWHM)

        func -- Function type ('box', 'sf', 'gauss').
        width -- Width of convolution function. Default (-1) is to
                 choose pre-defined value for each convolution function.
        """
        self.gridder._setfunc( func, width )

    def setWeight( self, weightType='uniform' ):
        """
        Set weight type. Possible options are 'uniform' (default),
        'tint' (weight by integration time), 'tsys' (weight by
        Tsys: 1/Tsys**2), and 'tintsys' (weight by integration time
        as well as Tsys: tint/Tsys**2).

        weightType -- weight type ('uniform', 'tint', 'tsys', 'tintsys')
        """
        self.gridder._setweight( weightType )

    def enableClip( self ):
        """
        Enable min/max clipping.

        By default, min/max clipping is disabled so that you should
        call this method before actual gridding if you want to do
        clipping.
        """
        self.gridder._enableclip()

    def disableClip( self ):
        """
        Disable min/max clipping.
        """
        self.gridder._disableclip()

    def grid( self ):
        """
        Actual gridding which will be done based on several user inputs. 
        """
        self.gridder._grid()

    def save( self, outfile='' ):
        """
        Save result. By default, output data name will be constructed
        from first element of input data name list (e.g. 'input.asap.grid').

        outfile -- output data name. 
        """
        self.outfile = self.gridder._save( outfile ) 

    def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ):
        """
        Plot gridded data.

        plotchan -- Which channel you want to plot. Default (-1) is
                    to average all the channels.
        plotpol -- Which polarization component you want to plot.
                   Default (-1) is to average all the polarization
                   components.
        plotobs -- Also plot observed position if True. Default
                   is False. Setting True for large amount of spectra
                   might be time consuming.
        plotgrid -- Also plot grid center if True. Default is False.
                    Setting True for large number of grids might be
                    time consuming.
        """
        import time
        t0=time.time()
        # to load scantable on disk
        storg = rcParams['scantable.storage']
        rcParams['scantable.storage'] = 'disk'
        plotter = _SDGridPlotter( self.infile, self.outfile, self.ifno )
        plotter.plot( chan=plotchan, pol=plotpol, plotobs=plotobs, plotgrid=plotgrid )
        # back to original setup
        rcParams['scantable.storage'] = storg
        t1=time.time()
        asaplog.push('plot: elapsed time %s sec'%(t1-t0))
        asaplog.post('DEBUG','asapgrid.plot')
        
class _SDGridPlotter:
    def __init__( self, infile, outfile=None, ifno=-1 ):
        if isinstance( infile, str ):
            self.infile = [infile]
        else:
            self.infile = infile
        self.outfile = outfile
        if self.outfile is None:
            self.outfile = self.infile[0].rstrip('/')+'.grid'
        self.nx = -1
        self.ny = -1
        self.nchan = 0
        self.npol = 0
        self.pollist = []
        self.cellx = 0.0
        self.celly = 0.0
        self.center = [0.0,0.0]
        self.nonzero = [[0.0],[0.0]]
        self.ifno = ifno
        self.tablein = None
        self.nrow = 0
        self.blc = None
        self.trc = None
        self.get()

    def get( self ):
        s = scantable( self.outfile, average=False )
        self.nchan = len(s._getspectrum(0))
        nrow = s.nrow()
        pols = numpy.ones( nrow, dtype=int )
        for i in xrange(nrow):
            pols[i] = s.getpol(i)
        self.pollist, indices = numpy.unique( pols, return_inverse=True )
        self.npol = len(self.pollist)
        self.pollist = self.pollist[indices[:self.npol]]
        #print 'pollist=',self.pollist
        #print 'npol=',self.npol
        #print 'nrow=',nrow

        idx = 0
        d0 = s.get_direction( 0 ).split()[-1]
        while ( s.get_direction(self.npol*idx) is not None \
                and s.get_direction(self.npol*idx).split()[-1] == d0 ):
            idx += 1
        
        self.nx = idx
        self.ny = nrow / (self.npol * idx )
        #print 'nx,ny=',self.nx,self.ny

        self.blc = s.get_directionval( 0 )
        self.trc = s.get_directionval( nrow-self.npol )
        #print self.blc
        #print self.trc
        if nrow > 1:
            incrx = s.get_directionval( self.npol )
            incry = s.get_directionval( self.nx*self.npol )
        else:
            incrx = [0.0,0.0]
            incry = [0.0,0.0]
        self.cellx = abs( self.blc[0] - incrx[0] )
        self.celly = abs( self.blc[1] - incry[1] )
        #print 'cellx,celly=',self.cellx,self.celly

    def plot( self, chan=-1, pol=-1, plotobs=False, plotgrid=False ):
        if pol < 0:
            opt = 'averaged over pol'
        else:
            opt = 'pol %s'%(pol)
        if type(chan) is list:
            opt += ', averaged over channel %s-%s'%(chan[0],chan[1])
        elif chan < 0:
            opt += ', averaged over channel'
        else:
            opt += ', channel %s'%(chan)
        data = self.getData( chan, pol )
        data = numpy.fliplr( data )
        title = 'Gridded Image (%s)'%(opt)
        pl.figure(10)
        pl.clf()
        # plot grid position
        if plotgrid:
            x = numpy.arange(self.blc[0],self.trc[0]+0.5*self.cellx,self.cellx,dtype=float)
            #print 'len(x)=',len(x)
            #print 'x=',x
            ybase = numpy.ones(self.nx,dtype=float)*self.blc[1]
            #print 'len(ybase)=',len(ybase)
            incr = self.celly 
            for iy in xrange(self.ny):
                y = ybase + iy * incr
                #print y
                pl.plot(x,y,',',color='blue')
        # plot observed position
        if plotobs:
            for i in xrange(len(self.infile)):
                self.createTableIn( self.infile[i] )
                irow = 0 
                while ( irow < self.nrow ):
                    chunk = self.getPointingChunk( irow )
                    #print chunk
                    pl.plot(chunk[0],chunk[1],',',color='green')
                    irow += chunk.shape[1]
                    #print irow
        # show image
        extent=[self.trc[0]+0.5*self.cellx,
                self.blc[0]-0.5*self.cellx,
                self.blc[1]-0.5*self.celly,
                self.trc[1]+0.5*self.celly]
        deccorr = 1.0/numpy.cos(0.5*(self.blc[1]+self.trc[1]))
        pl.imshow(data,extent=extent,origin='lower',interpolation='nearest')
        pl.colorbar()
        pl.xlabel('R.A. [rad]')
        pl.ylabel('Dec. [rad]')
        ax = pl.axes()
        ax.set_aspect(deccorr)
        pl.title( title )

    def createTableIn( self, tab ):
        del self.tablein
        self.tablein = scantable( tab, average=False )
        if self.ifno < 0:
            ifno = self.tablein.getif(0)
            print 'ifno=',ifno
        else:
            ifno = self.ifno
        sel = selector()
        sel.set_ifs( ifno )
        self.tablein.set_selection( sel )
        self.nchan = len(self.tablein._getspectrum(0))
        self.nrow = self.tablein.nrow()
        del sel
        

    def getPointingChunk( self, irow ):
        numchunk = 1000
        nrow = min( self.nrow-irow, numchunk )
        #print 'nrow=',nrow
        v = numpy.zeros( (2,nrow), dtype=float )
        idx = 0
        for i in xrange(irow,irow+nrow):
            d = self.tablein.get_directionval( i )
            v[0,idx] = d[0]
            v[1,idx] = d[1]
            idx += 1
        return v

    def getData( self, chan=-1, pol=-1 ):
        if type(chan) == list:
            spectra = self.__chanAverage(start=chan[0],end=chan[1])
        elif chan == -1:
            spectra = self.__chanAverage()
        else:
            spectra = self.__chanIndex( chan )
        data = spectra.reshape( (self.npol,self.ny,self.nx) )
        if pol == -1:
            retval = data.mean(axis=0)
        else:
            retval = data[pol]
        return retval

    def __chanAverage( self, start=-1, end=-1 ):
        s = scantable( self.outfile, average=False )
        nrow = s.nrow() 
        spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float )
        irow = 0
        sp = [0 for i in xrange(self.nchan)]
        if start < 0:
            start = 0
        if end < 0:
            end = self.nchan
        for i in xrange(nrow/self.npol):
            for ip in xrange(self.npol):
                sp = s._getspectrum( irow )[start:end]
                spectra[ip,i] = numpy.mean( sp )
                irow += 1
            
        return spectra

    def __chanIndex( self, idx ):
        s = scantable( self.outfile, average=False )
        nrow = s.nrow()
        spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float )
        irow = 0
        sp = [0 for i in xrange(self.nchan)]
        for i in xrange(nrow/self.npol):
            for ip in xrange(self.npol):
                sp = s._getspectrum( irow )
                spectra[ip,i] = sp[idx]
                irow += 1
        return spectra
        
            
