[2356] | 1 | import numpy |
---|
[2367] | 2 | from asap import rcParams |
---|
[2356] | 3 | from asap.scantable import scantable |
---|
[2367] | 4 | from asap.selector import selector |
---|
[2593] | 5 | from asap._asap import stgrid, stgrid2 |
---|
[2356] | 6 | import pylab as pl |
---|
[2367] | 7 | from logging import asaplog |
---|
[2356] | 8 | |
---|
[2680] | 9 | class asapgrid_base(object): |
---|
| 10 | def __init__( self ): |
---|
[2356] | 11 | self.outfile = None |
---|
[2367] | 12 | self.ifno = None |
---|
[2680] | 13 | self.gridder = None |
---|
| 14 | self.infile = None |
---|
| 15 | self.scantab = None |
---|
[2356] | 16 | |
---|
| 17 | def setData( self, infile ): |
---|
[2680] | 18 | raise NotImplementedError('setData is not implemented') |
---|
| 19 | |
---|
[2362] | 20 | def setIF( self, ifno ): |
---|
[2391] | 21 | """ |
---|
| 22 | Set IFNO to be processed. Currently, asapgrid allows to process |
---|
| 23 | only one IFNO for one gridding run even if the data contains |
---|
| 24 | multiple IFs. If you didn't specify IFNO, default value, which |
---|
| 25 | is IFNO in the first spectrum, will be processed. |
---|
| 26 | |
---|
| 27 | ifno -- IFNO to be processed. |
---|
| 28 | """ |
---|
[2367] | 29 | self.ifno = ifno |
---|
| 30 | self.gridder._setif( self.ifno ) |
---|
[2680] | 31 | |
---|
[2360] | 32 | def setPolList( self, pollist ): |
---|
[2391] | 33 | """ |
---|
| 34 | Set list of polarization components you want to process. |
---|
| 35 | If not specified, all POLNOs will be processed. |
---|
| 36 | |
---|
| 37 | pollist -- list of POLNOs. |
---|
| 38 | """ |
---|
[2360] | 39 | self.gridder._setpollist( pollist ) |
---|
| 40 | |
---|
[2364] | 41 | def setScanList( self, scanlist ): |
---|
[2391] | 42 | """ |
---|
| 43 | Set list of scans you want to process. If not specified, all |
---|
| 44 | scans will be processed. |
---|
| 45 | |
---|
| 46 | scanlist -- list of SCANNOs. |
---|
| 47 | """ |
---|
[2364] | 48 | self.gridder._setscanlist( scanlist ) |
---|
| 49 | |
---|
[2356] | 50 | def defineImage( self, nx=-1, ny=-1, cellx='', celly='', center='' ): |
---|
[2391] | 51 | """ |
---|
| 52 | Define spatial grid. |
---|
| 53 | |
---|
| 54 | First two parameters, nx and ny, define number of pixels of |
---|
| 55 | the grid. If which of those is not specified, it will be set |
---|
| 56 | to the same value as the other. If none of them are specified, |
---|
| 57 | it will be determined from map extent and cell size. |
---|
| 58 | |
---|
| 59 | Next two parameters, cellx and celly, define size of pixel. |
---|
| 60 | You should set those parameters as string, which is constructed |
---|
| 61 | numerical value and unit, e.g. '0.5arcmin', or numerical value. |
---|
| 62 | If those values are specified as numerical value, their units |
---|
[2421] | 63 | will be assumed to 'arcsec'. If which of those is not specified, |
---|
[2391] | 64 | it will be set to the same value as the other. If none of them |
---|
| 65 | are specified, it will be determined from map extent and number |
---|
| 66 | of pixels, or set to '1arcmin' if neither nx nor ny is set. |
---|
| 67 | |
---|
| 68 | The last parameter, center, define the central coordinate of |
---|
| 69 | the grid. You should specify its value as a string, like, |
---|
| 70 | |
---|
| 71 | 'J2000 05h08m50s -16d23m30s' |
---|
| 72 | |
---|
| 73 | or |
---|
| 74 | |
---|
| 75 | 'J2000 05:08:50 -16.23.30' |
---|
| 76 | |
---|
| 77 | You can omit equinox when you specify center coordinate. In that |
---|
| 78 | case, J2000 is assumed. If center is not specified, it will be |
---|
| 79 | determined from the observed positions of input data. |
---|
| 80 | |
---|
| 81 | nx -- number of pixels along x (R.A.) direction. |
---|
| 82 | ny -- number of pixels along y (Dec.) direction. |
---|
| 83 | cellx -- size of pixel in x (R.A.) direction. |
---|
| 84 | celly -- size of pixel in y (Dec.) direction. |
---|
| 85 | center -- central position of the grid. |
---|
| 86 | """ |
---|
| 87 | if not isinstance( cellx, str ): |
---|
[2421] | 88 | cellx = '%sarcsec'%(cellx) |
---|
[2391] | 89 | if not isinstance( celly, str ): |
---|
[2421] | 90 | celly = '%sarcsec'%(celly) |
---|
[2356] | 91 | self.gridder._defineimage( nx, ny, cellx, celly, center ) |
---|
| 92 | |
---|
[2678] | 93 | def setFunc( self, func='box', convsupport=-1, truncate="-1", gwidth="-1", jwidth="-1" ): |
---|
[2391] | 94 | """ |
---|
| 95 | Set convolution function. Possible options are 'box' (Box-car, |
---|
[2679] | 96 | default), 'sf' (prolate spheroidal), 'gauss' (Gaussian), and |
---|
| 97 | 'gjinc' (Gaussian * Jinc). |
---|
| 98 | Width of convolution function can be set using several parameters. |
---|
| 99 | For 'box' and 'sf', we have one parameter, convsupport, that |
---|
| 100 | specifies a cut-off radius of the convlolution function. By default |
---|
| 101 | (-1), convsupport is automatically set depending on each convolution |
---|
| 102 | function. Default values for convsupport are: |
---|
[2391] | 103 | |
---|
| 104 | 'box': 1 pixel |
---|
| 105 | 'sf': 3 pixels |
---|
| 106 | |
---|
[2679] | 107 | For 'gauss', we have two parameters for convolution function, |
---|
| 108 | truncate and gwidth. The truncate is similar to convsupport |
---|
| 109 | except that truncate allows to specify its value as float or |
---|
| 110 | string consisting of numeric and unit (e.g. '10arcsec' or |
---|
| 111 | '3pixel'). Available units are angular units ('arcsec', 'arcmin', |
---|
| 112 | 'deg', etc.) and 'pixel'. Default unit is 'pixel' so that if |
---|
| 113 | you specify numerical value or string without unit to gwidth, |
---|
| 114 | the value will be interpreted as 'pixel'. gwidth is an HWHM of |
---|
| 115 | gaussian. It also allows string value. Interpretation of the |
---|
| 116 | value for gwidth is same as truncate. Default value for 'gauss' |
---|
| 117 | is |
---|
| 118 | |
---|
| 119 | gwidth: '-1' ---> sqrt(log(2.0)) pixel |
---|
| 120 | truncate: '-1' ---> 3*gwidth pixel |
---|
| 121 | |
---|
| 122 | For 'gjinc', there is an additional parameter jwidth that |
---|
| 123 | specifies a width of the jinc function whose functional form is |
---|
| 124 | |
---|
| 125 | jinc(x) = J_1(pi*x/jwidth) / (pi*x/jwidth) |
---|
| 126 | |
---|
| 127 | Default values for 'gjinc' is |
---|
| 128 | |
---|
| 129 | gwidth: '-1' ---> 2.52*sqrt(log(2.0)) pixel |
---|
| 130 | jwidth: '-1' ---> 1.55 |
---|
| 131 | truncate: '-1' ---> automatically truncate at first null |
---|
| 132 | |
---|
| 133 | Default values for gwidth and jwidth are taken from Mangum et al. |
---|
| 134 | (2007). |
---|
| 135 | |
---|
| 136 | func -- Function type ('box', 'sf', 'gauss', 'gjinc'). |
---|
| 137 | convsupport -- Width of convolution function. Default (-1) is |
---|
| 138 | to choose pre-defined value for each convolution |
---|
| 139 | function. Effective only for 'box' and 'sf'. |
---|
| 140 | truncate -- Truncation radius of the convolution function. |
---|
| 141 | Acceptable value is an integer or a float in units of |
---|
| 142 | pixel, or a string consisting of numeric plus unit. |
---|
| 143 | Default unit for the string is 'pixel'. Default (-1) |
---|
| 144 | is to choose pre-defined value for each convolution |
---|
| 145 | function. Effective only for 'gauss' and 'gjinc'. |
---|
| 146 | gwidth -- The HWHM of the gaussian. Acceptable value is an integer |
---|
| 147 | or a float in units of pixel, or a string consisting of |
---|
| 148 | numeric plus unit. Default unit for the string is 'pixel'. |
---|
| 149 | Default (-1) is to choose pre-defined value for each |
---|
| 150 | convolution function. Effective only for 'gauss' and |
---|
| 151 | 'gjinc'. |
---|
| 152 | jwidth -- The width of the jinc function. Acceptable value is an |
---|
| 153 | integer or a float in units of pixel, or a string |
---|
| 154 | consisting of numeric plus unit. Default unit for the |
---|
| 155 | string is 'pixel'. Default (-1) is to choose pre-defined |
---|
| 156 | value for each convolution function. Effective only for |
---|
| 157 | 'gjinc'. |
---|
[2391] | 158 | """ |
---|
[2678] | 159 | self.gridder._setfunc(func, |
---|
| 160 | convsupport=convsupport, |
---|
| 161 | truncate=truncate, |
---|
| 162 | gwidth=gwidth, |
---|
| 163 | jwidth=jwidth) |
---|
[2356] | 164 | |
---|
[2361] | 165 | def setWeight( self, weightType='uniform' ): |
---|
[2391] | 166 | """ |
---|
| 167 | Set weight type. Possible options are 'uniform' (default), |
---|
| 168 | 'tint' (weight by integration time), 'tsys' (weight by |
---|
| 169 | Tsys: 1/Tsys**2), and 'tintsys' (weight by integration time |
---|
| 170 | as well as Tsys: tint/Tsys**2). |
---|
| 171 | |
---|
| 172 | weightType -- weight type ('uniform', 'tint', 'tsys', 'tintsys') |
---|
| 173 | """ |
---|
[2396] | 174 | self.gridder._setweight( weightType ) |
---|
[2361] | 175 | |
---|
[2396] | 176 | def enableClip( self ): |
---|
| 177 | """ |
---|
| 178 | Enable min/max clipping. |
---|
| 179 | |
---|
| 180 | By default, min/max clipping is disabled so that you should |
---|
| 181 | call this method before actual gridding if you want to do |
---|
| 182 | clipping. |
---|
| 183 | """ |
---|
| 184 | self.gridder._enableclip() |
---|
| 185 | |
---|
| 186 | def disableClip( self ): |
---|
| 187 | """ |
---|
| 188 | Disable min/max clipping. |
---|
| 189 | """ |
---|
| 190 | self.gridder._disableclip() |
---|
| 191 | |
---|
[2356] | 192 | def grid( self ): |
---|
[2391] | 193 | """ |
---|
| 194 | Actual gridding which will be done based on several user inputs. |
---|
| 195 | """ |
---|
[2356] | 196 | self.gridder._grid() |
---|
[2680] | 197 | |
---|
| 198 | def plotFunc(self, clear=True): |
---|
| 199 | """ |
---|
| 200 | Support function to see the shape of current grid function. |
---|
[2356] | 201 | |
---|
[2680] | 202 | clear -- clear panel if True. Default is True. |
---|
| 203 | """ |
---|
| 204 | pl.figure(11) |
---|
| 205 | if clear: |
---|
| 206 | pl.clf() |
---|
| 207 | f = self.gridder._getfunc() |
---|
| 208 | convsampling = 100 |
---|
| 209 | a = numpy.arange(0,len(f)/convsampling,1./convsampling,dtype=float) |
---|
| 210 | pl.plot(a,f,'.-') |
---|
| 211 | pl.xlabel('pixel') |
---|
| 212 | pl.ylabel('convFunc') |
---|
| 213 | |
---|
[2356] | 214 | def save( self, outfile='' ): |
---|
[2680] | 215 | raise NotImplementedError('save is not implemented') |
---|
| 216 | |
---|
| 217 | def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ): |
---|
| 218 | raise NotImplementedError('plot is not implemented') |
---|
| 219 | |
---|
| 220 | def getResult( self ): |
---|
| 221 | raise NotImplementedError('getResult is not implemented') |
---|
| 222 | |
---|
| 223 | class asapgrid(asapgrid_base): |
---|
| 224 | """ |
---|
| 225 | The asapgrid class is defined to convolve data onto regular |
---|
| 226 | spatial grid. Typical usage is as follows: |
---|
| 227 | |
---|
| 228 | # create asapgrid instance with two input data |
---|
| 229 | g = asapgrid( ['testimage1.asap','testimage2.asap'] ) |
---|
| 230 | # set IFNO if necessary |
---|
| 231 | g.setIF( 0 ) |
---|
| 232 | # set POLNOs if necessary |
---|
| 233 | g.setPolList( [0,1] ) |
---|
| 234 | # set SCANNOs if necessary |
---|
| 235 | g.setScanList( [22,23,24] ) |
---|
| 236 | # define image with full specification |
---|
| 237 | # you can skip some parameters (see help for defineImage) |
---|
| 238 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
---|
| 239 | center='J2000 10h10m10s -5d05m05s' ) |
---|
| 240 | # set convolution function |
---|
| 241 | g.setFunc( func='sf', convsupport=3 ) |
---|
| 242 | # enable min/max clipping |
---|
| 243 | g.enableClip() |
---|
| 244 | # or, disable min/max clipping |
---|
| 245 | #g.disableClip() |
---|
| 246 | # actual gridding |
---|
| 247 | g.grid() |
---|
| 248 | # save result |
---|
| 249 | g.save( outfile='grid.asap' ) |
---|
| 250 | # plot result |
---|
| 251 | g.plot( plotchan=1246, plotpol=-1, plotgrid=True, plotobs=True ) |
---|
| 252 | """ |
---|
| 253 | def __init__( self, infile ): |
---|
[2391] | 254 | """ |
---|
[2680] | 255 | Create asapgrid instance. |
---|
| 256 | |
---|
| 257 | infile -- input data as a string or string list if you want |
---|
| 258 | to grid more than one data at once. |
---|
| 259 | """ |
---|
| 260 | super(asapgrid,self).__init__() |
---|
| 261 | self.gridder = stgrid() |
---|
| 262 | self.infile=infile |
---|
| 263 | self.setData(infile) |
---|
| 264 | |
---|
| 265 | def setData( self, infile ): |
---|
| 266 | """ |
---|
| 267 | Set data to be processed. |
---|
| 268 | |
---|
| 269 | infile -- input data as a string or string list if you want |
---|
| 270 | to grid more than one data at once. |
---|
| 271 | """ |
---|
| 272 | if isinstance( infile, str ): |
---|
| 273 | self.gridder._setin( infile ) |
---|
| 274 | else: |
---|
| 275 | self.gridder._setfiles( infile ) |
---|
| 276 | self.infile = infile |
---|
| 277 | |
---|
| 278 | def save( self, outfile='' ): |
---|
| 279 | """ |
---|
[2391] | 280 | Save result. By default, output data name will be constructed |
---|
| 281 | from first element of input data name list (e.g. 'input.asap.grid'). |
---|
| 282 | |
---|
| 283 | outfile -- output data name. |
---|
| 284 | """ |
---|
[2356] | 285 | self.outfile = self.gridder._save( outfile ) |
---|
| 286 | |
---|
[2375] | 287 | def plot( self, plotchan=-1, plotpol=-1, plotobs=False, plotgrid=False ): |
---|
[2391] | 288 | """ |
---|
| 289 | Plot gridded data. |
---|
| 290 | |
---|
| 291 | plotchan -- Which channel you want to plot. Default (-1) is |
---|
| 292 | to average all the channels. |
---|
| 293 | plotpol -- Which polarization component you want to plot. |
---|
| 294 | Default (-1) is to average all the polarization |
---|
| 295 | components. |
---|
| 296 | plotobs -- Also plot observed position if True. Default |
---|
| 297 | is False. Setting True for large amount of spectra |
---|
| 298 | might be time consuming. |
---|
| 299 | plotgrid -- Also plot grid center if True. Default is False. |
---|
| 300 | Setting True for large number of grids might be |
---|
| 301 | time consuming. |
---|
| 302 | """ |
---|
[2367] | 303 | import time |
---|
| 304 | t0=time.time() |
---|
| 305 | # to load scantable on disk |
---|
| 306 | storg = rcParams['scantable.storage'] |
---|
| 307 | rcParams['scantable.storage'] = 'disk' |
---|
[2686] | 308 | [nx,ny] = self.gridder._get_resultant_map_size() |
---|
| 309 | [cellx,celly] = self.gridder._get_resultant_cell_size() |
---|
| 310 | plotter = _SDGridPlotter( self.infile, self.outfile, self.ifno, |
---|
| 311 | nx=nx, ny=ny, cellx=cellx, celly=celly ) |
---|
[2375] | 312 | plotter.plot( chan=plotchan, pol=plotpol, plotobs=plotobs, plotgrid=plotgrid ) |
---|
[2367] | 313 | # back to original setup |
---|
| 314 | rcParams['scantable.storage'] = storg |
---|
| 315 | t1=time.time() |
---|
| 316 | asaplog.push('plot: elapsed time %s sec'%(t1-t0)) |
---|
| 317 | asaplog.post('DEBUG','asapgrid.plot') |
---|
[2356] | 318 | |
---|
[2680] | 319 | class asapgrid2(asapgrid_base): |
---|
[2593] | 320 | """ |
---|
| 321 | The asapgrid class is defined to convolve data onto regular |
---|
| 322 | spatial grid. Typical usage is as follows: |
---|
| 323 | |
---|
| 324 | # create asapgrid instance with input scantable |
---|
| 325 | s = scantable( 'testimage1.asap', average=False ) |
---|
| 326 | g = asapgrid( s ) |
---|
| 327 | # set IFNO if necessary |
---|
| 328 | g.setIF( 0 ) |
---|
| 329 | # set POLNOs if necessary |
---|
| 330 | g.setPolList( [0,1] ) |
---|
| 331 | # set SCANNOs if necessary |
---|
| 332 | g.setScanList( [22,23,24] ) |
---|
| 333 | # define image with full specification |
---|
| 334 | # you can skip some parameters (see help for defineImage) |
---|
| 335 | g.defineImage( nx=12, ny=12, cellx='10arcsec', celly='10arcsec', |
---|
| 336 | center='J2000 10h10m10s -5d05m05s' ) |
---|
| 337 | # set convolution function |
---|
| 338 | g.setFunc( func='sf', width=3 ) |
---|
| 339 | # enable min/max clipping |
---|
| 340 | g.enableClip() |
---|
| 341 | # or, disable min/max clipping |
---|
| 342 | #g.disableClip() |
---|
| 343 | # actual gridding |
---|
| 344 | g.grid() |
---|
| 345 | # get result as scantable |
---|
| 346 | sg = g.getResult() |
---|
| 347 | """ |
---|
| 348 | def __init__( self, scantab ): |
---|
| 349 | """ |
---|
| 350 | Create asapgrid instance. |
---|
| 351 | |
---|
| 352 | scantab -- input data as a scantable or a list of scantables |
---|
| 353 | to grid more than one data at once. |
---|
| 354 | """ |
---|
[2680] | 355 | super(asapgrid2,self).__init__() |
---|
[2593] | 356 | self.gridder = stgrid2() |
---|
[2680] | 357 | self.scantab = scantab |
---|
[2593] | 358 | self.setData( scantab ) |
---|
| 359 | |
---|
| 360 | def setData( self, scantab ): |
---|
| 361 | """ |
---|
| 362 | Set data to be processed. |
---|
| 363 | |
---|
| 364 | scantab -- input data as a scantable or a list of scantables |
---|
| 365 | to grid more than one data at once. |
---|
| 366 | """ |
---|
| 367 | if isinstance( scantab, scantable ): |
---|
| 368 | self.gridder._setin( scantab ) |
---|
| 369 | else: |
---|
| 370 | self.gridder._setfiles( scantab ) |
---|
| 371 | self.scantab = scantab |
---|
| 372 | |
---|
| 373 | def getResult( self ): |
---|
| 374 | """ |
---|
| 375 | Return gridded data as a scantable. |
---|
| 376 | """ |
---|
[2594] | 377 | tp = 0 if rcParams['scantable.storage']=='memory' else 1 |
---|
[2680] | 378 | return scantable( self.gridder._get( tp ), average=False ) |
---|
[2593] | 379 | |
---|
[2356] | 380 | class _SDGridPlotter: |
---|
[2686] | 381 | def __init__( self, infile, outfile=None, ifno=-1, nx=-1, ny=-1, cellx=0.0, celly=0.0 ): |
---|
[2390] | 382 | if isinstance( infile, str ): |
---|
| 383 | self.infile = [infile] |
---|
| 384 | else: |
---|
| 385 | self.infile = infile |
---|
[2356] | 386 | self.outfile = outfile |
---|
| 387 | if self.outfile is None: |
---|
[2390] | 388 | self.outfile = self.infile[0].rstrip('/')+'.grid' |
---|
[2686] | 389 | self.nx = nx |
---|
| 390 | self.ny = ny if ny > 0 else nx |
---|
[2356] | 391 | self.nchan = 0 |
---|
[2360] | 392 | self.npol = 0 |
---|
| 393 | self.pollist = [] |
---|
[2686] | 394 | self.cellx = cellx |
---|
| 395 | self.celly = celly if celly > 0.0 else cellx |
---|
[2356] | 396 | self.center = [0.0,0.0] |
---|
| 397 | self.nonzero = [[0.0],[0.0]] |
---|
[2367] | 398 | self.ifno = ifno |
---|
[2372] | 399 | self.tablein = None |
---|
| 400 | self.nrow = 0 |
---|
| 401 | self.blc = None |
---|
| 402 | self.trc = None |
---|
[2356] | 403 | self.get() |
---|
| 404 | |
---|
| 405 | def get( self ): |
---|
| 406 | s = scantable( self.outfile, average=False ) |
---|
[2387] | 407 | self.nchan = len(s._getspectrum(0)) |
---|
[2356] | 408 | nrow = s.nrow() |
---|
[2360] | 409 | pols = numpy.ones( nrow, dtype=int ) |
---|
[2356] | 410 | for i in xrange(nrow): |
---|
[2360] | 411 | pols[i] = s.getpol(i) |
---|
| 412 | self.pollist, indices = numpy.unique( pols, return_inverse=True ) |
---|
| 413 | self.npol = len(self.pollist) |
---|
| 414 | self.pollist = self.pollist[indices[:self.npol]] |
---|
| 415 | #print 'pollist=',self.pollist |
---|
| 416 | #print 'npol=',self.npol |
---|
| 417 | #print 'nrow=',nrow |
---|
[2356] | 418 | |
---|
[2686] | 419 | if self.nx <= 0 or self.ny <= 0: |
---|
| 420 | idx = 1 |
---|
| 421 | d0 = s.get_direction( 0 ).split()[-2] |
---|
[2669] | 422 | d = s.get_direction(self.npol*idx) |
---|
[2686] | 423 | while( d is not None \ |
---|
| 424 | and d.split()[-2] != d0): |
---|
| 425 | idx += 1 |
---|
| 426 | d = s.get_direction(self.npol*idx) |
---|
[2367] | 427 | |
---|
[2686] | 428 | self.nx = idx |
---|
| 429 | self.ny = nrow / (self.npol * idx ) |
---|
| 430 | #print 'nx,ny=',self.nx,self.ny |
---|
[2372] | 431 | |
---|
| 432 | self.blc = s.get_directionval( 0 ) |
---|
| 433 | self.trc = s.get_directionval( nrow-self.npol ) |
---|
| 434 | #print self.blc |
---|
| 435 | #print self.trc |
---|
[2356] | 436 | |
---|
[2686] | 437 | if self.cellx <= 0.0 or self.celly <= 0.0: |
---|
| 438 | if nrow > 1: |
---|
| 439 | incrx = s.get_directionval( self.npol ) |
---|
| 440 | incry = s.get_directionval( self.nx*self.npol ) |
---|
| 441 | else: |
---|
| 442 | incrx = [0.0,0.0] |
---|
| 443 | incry = [0.0,0.0] |
---|
| 444 | self.cellx = abs( self.blc[0] - incrx[0] ) |
---|
| 445 | self.celly = abs( self.blc[1] - incry[1] ) |
---|
| 446 | #print 'cellx,celly=',self.cellx,self.celly |
---|
| 447 | |
---|
[2375] | 448 | def plot( self, chan=-1, pol=-1, plotobs=False, plotgrid=False ): |
---|
[2360] | 449 | if pol < 0: |
---|
| 450 | opt = 'averaged over pol' |
---|
[2356] | 451 | else: |
---|
[2360] | 452 | opt = 'pol %s'%(pol) |
---|
[2419] | 453 | if type(chan) is list: |
---|
| 454 | opt += ', averaged over channel %s-%s'%(chan[0],chan[1]) |
---|
| 455 | elif chan < 0: |
---|
[2360] | 456 | opt += ', averaged over channel' |
---|
| 457 | else: |
---|
| 458 | opt += ', channel %s'%(chan) |
---|
[2423] | 459 | data = self.getData( chan, pol ) |
---|
[2669] | 460 | #data = numpy.fliplr( data ) |
---|
[2360] | 461 | title = 'Gridded Image (%s)'%(opt) |
---|
[2356] | 462 | pl.figure(10) |
---|
| 463 | pl.clf() |
---|
[2372] | 464 | # plot grid position |
---|
[2375] | 465 | if plotgrid: |
---|
| 466 | x = numpy.arange(self.blc[0],self.trc[0]+0.5*self.cellx,self.cellx,dtype=float) |
---|
| 467 | #print 'len(x)=',len(x) |
---|
| 468 | #print 'x=',x |
---|
| 469 | ybase = numpy.ones(self.nx,dtype=float)*self.blc[1] |
---|
| 470 | #print 'len(ybase)=',len(ybase) |
---|
| 471 | incr = self.celly |
---|
| 472 | for iy in xrange(self.ny): |
---|
| 473 | y = ybase + iy * incr |
---|
| 474 | #print y |
---|
| 475 | pl.plot(x,y,',',color='blue') |
---|
[2372] | 476 | # plot observed position |
---|
[2375] | 477 | if plotobs: |
---|
[2390] | 478 | for i in xrange(len(self.infile)): |
---|
| 479 | self.createTableIn( self.infile[i] ) |
---|
| 480 | irow = 0 |
---|
| 481 | while ( irow < self.nrow ): |
---|
| 482 | chunk = self.getPointingChunk( irow ) |
---|
| 483 | #print chunk |
---|
| 484 | pl.plot(chunk[0],chunk[1],',',color='green') |
---|
| 485 | irow += chunk.shape[1] |
---|
| 486 | #print irow |
---|
[2372] | 487 | # show image |
---|
[2894] | 488 | extent=[self.blc[0]-0.5*self.cellx, |
---|
| 489 | self.trc[0]+0.5*self.cellx, |
---|
[2372] | 490 | self.blc[1]-0.5*self.celly, |
---|
| 491 | self.trc[1]+0.5*self.celly] |
---|
[2420] | 492 | deccorr = 1.0/numpy.cos(0.5*(self.blc[1]+self.trc[1])) |
---|
[2356] | 493 | pl.imshow(data,extent=extent,origin='lower',interpolation='nearest') |
---|
| 494 | pl.colorbar() |
---|
| 495 | pl.xlabel('R.A. [rad]') |
---|
| 496 | pl.ylabel('Dec. [rad]') |
---|
[2420] | 497 | ax = pl.axes() |
---|
| 498 | ax.set_aspect(deccorr) |
---|
[2358] | 499 | pl.title( title ) |
---|
[2367] | 500 | |
---|
[2390] | 501 | def createTableIn( self, tab ): |
---|
| 502 | del self.tablein |
---|
| 503 | self.tablein = scantable( tab, average=False ) |
---|
[2387] | 504 | if self.ifno < 0: |
---|
| 505 | ifno = self.tablein.getif(0) |
---|
[2669] | 506 | #print 'ifno=',ifno |
---|
[2387] | 507 | else: |
---|
| 508 | ifno = self.ifno |
---|
| 509 | sel = selector() |
---|
| 510 | sel.set_ifs( ifno ) |
---|
[2390] | 511 | self.tablein.set_selection( sel ) |
---|
[2387] | 512 | self.nchan = len(self.tablein._getspectrum(0)) |
---|
[2390] | 513 | self.nrow = self.tablein.nrow() |
---|
[2387] | 514 | del sel |
---|
| 515 | |
---|
| 516 | |
---|
[2372] | 517 | def getPointingChunk( self, irow ): |
---|
| 518 | numchunk = 1000 |
---|
| 519 | nrow = min( self.nrow-irow, numchunk ) |
---|
| 520 | #print 'nrow=',nrow |
---|
| 521 | v = numpy.zeros( (2,nrow), dtype=float ) |
---|
| 522 | idx = 0 |
---|
| 523 | for i in xrange(irow,irow+nrow): |
---|
| 524 | d = self.tablein.get_directionval( i ) |
---|
| 525 | v[0,idx] = d[0] |
---|
| 526 | v[1,idx] = d[1] |
---|
| 527 | idx += 1 |
---|
| 528 | return v |
---|
| 529 | |
---|
[2367] | 530 | def getData( self, chan=-1, pol=-1 ): |
---|
[2419] | 531 | if type(chan) == list: |
---|
| 532 | spectra = self.__chanAverage(start=chan[0],end=chan[1]) |
---|
| 533 | elif chan == -1: |
---|
[2367] | 534 | spectra = self.__chanAverage() |
---|
| 535 | else: |
---|
| 536 | spectra = self.__chanIndex( chan ) |
---|
[2372] | 537 | data = spectra.reshape( (self.npol,self.ny,self.nx) ) |
---|
[2367] | 538 | if pol == -1: |
---|
| 539 | retval = data.mean(axis=0) |
---|
| 540 | else: |
---|
| 541 | retval = data[pol] |
---|
| 542 | return retval |
---|
| 543 | |
---|
[2419] | 544 | def __chanAverage( self, start=-1, end=-1 ): |
---|
[2367] | 545 | s = scantable( self.outfile, average=False ) |
---|
[2372] | 546 | nrow = s.nrow() |
---|
[2367] | 547 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
---|
| 548 | irow = 0 |
---|
| 549 | sp = [0 for i in xrange(self.nchan)] |
---|
[2419] | 550 | if start < 0: |
---|
| 551 | start = 0 |
---|
| 552 | if end < 0: |
---|
| 553 | end = self.nchan |
---|
[2367] | 554 | for i in xrange(nrow/self.npol): |
---|
| 555 | for ip in xrange(self.npol): |
---|
[2419] | 556 | sp = s._getspectrum( irow )[start:end] |
---|
[2367] | 557 | spectra[ip,i] = numpy.mean( sp ) |
---|
| 558 | irow += 1 |
---|
[2419] | 559 | |
---|
[2367] | 560 | return spectra |
---|
| 561 | |
---|
| 562 | def __chanIndex( self, idx ): |
---|
| 563 | s = scantable( self.outfile, average=False ) |
---|
[2372] | 564 | nrow = s.nrow() |
---|
[2367] | 565 | spectra = numpy.zeros( (self.npol,nrow/self.npol), dtype=float ) |
---|
| 566 | irow = 0 |
---|
| 567 | sp = [0 for i in xrange(self.nchan)] |
---|
| 568 | for i in xrange(nrow/self.npol): |
---|
| 569 | for ip in xrange(self.npol): |
---|
| 570 | sp = s._getspectrum( irow ) |
---|
| 571 | spectra[ip,i] = sp[idx] |
---|
| 572 | irow += 1 |
---|
| 573 | return spectra |
---|
| 574 | |
---|
| 575 | |
---|