| [113] | 1 | import _asap
|
|---|
| [259] | 2 | from asap import rcParams
|
|---|
| [723] | 3 | from asap import print_log
|
|---|
| [113] | 4 |
|
|---|
| 5 | class fitter:
|
|---|
| 6 | """
|
|---|
| 7 | The fitting class for ASAP.
|
|---|
| 8 | """
|
|---|
| [723] | 9 |
|
|---|
| [113] | 10 | def __init__(self):
|
|---|
| 11 | """
|
|---|
| 12 | Create a fitter object. No state is set.
|
|---|
| 13 | """
|
|---|
| 14 | self.fitter = _asap.fitter()
|
|---|
| 15 | self.x = None
|
|---|
| 16 | self.y = None
|
|---|
| 17 | self.mask = None
|
|---|
| 18 | self.fitfunc = None
|
|---|
| [515] | 19 | self.fitfuncs = None
|
|---|
| [113] | 20 | self.fitted = False
|
|---|
| 21 | self.data = None
|
|---|
| [515] | 22 | self.components = 0
|
|---|
| 23 | self._fittedrow = 0
|
|---|
| [113] | 24 | self._p = None
|
|---|
| [515] | 25 | self._selection = None
|
|---|
| [113] | 26 |
|
|---|
| 27 | def set_data(self, xdat, ydat, mask=None):
|
|---|
| 28 | """
|
|---|
| [158] | 29 | Set the absissa and ordinate for the fit. Also set the mask
|
|---|
| [113] | 30 | indicationg valid points.
|
|---|
| 31 | This can be used for data vectors retrieved from a scantable.
|
|---|
| 32 | For scantable fitting use 'fitter.set_scan(scan, mask)'.
|
|---|
| 33 | Parameters:
|
|---|
| [158] | 34 | xdat: the abcissa values
|
|---|
| [113] | 35 | ydat: the ordinate values
|
|---|
| 36 | mask: an optional mask
|
|---|
| [723] | 37 |
|
|---|
| [113] | 38 | """
|
|---|
| 39 | self.fitted = False
|
|---|
| 40 | self.x = xdat
|
|---|
| 41 | self.y = ydat
|
|---|
| 42 | if mask == None:
|
|---|
| 43 | from numarray import ones
|
|---|
| 44 | self.mask = ones(len(xdat))
|
|---|
| 45 | else:
|
|---|
| 46 | self.mask = mask
|
|---|
| 47 | return
|
|---|
| 48 |
|
|---|
| 49 | def set_scan(self, thescan=None, mask=None):
|
|---|
| 50 | """
|
|---|
| 51 | Set the 'data' (a scantable) of the fitter.
|
|---|
| 52 | Parameters:
|
|---|
| 53 | thescan: a scantable
|
|---|
| 54 | mask: a msk retireved from the scantable
|
|---|
| 55 | """
|
|---|
| 56 | if not thescan:
|
|---|
| [723] | 57 | msg = "Please give a correct scan"
|
|---|
| 58 | if rcParams['verbose']:
|
|---|
| 59 | print msg
|
|---|
| 60 | return
|
|---|
| 61 | else:
|
|---|
| 62 | raise TypeError(msg)
|
|---|
| [113] | 63 | self.fitted = False
|
|---|
| 64 | self.data = thescan
|
|---|
| 65 | if mask is None:
|
|---|
| 66 | from numarray import ones
|
|---|
| 67 | self.mask = ones(self.data.nchan())
|
|---|
| 68 | else:
|
|---|
| 69 | self.mask = mask
|
|---|
| 70 | return
|
|---|
| 71 |
|
|---|
| 72 | def set_function(self, **kwargs):
|
|---|
| 73 | """
|
|---|
| 74 | Set the function to be fit.
|
|---|
| 75 | Parameters:
|
|---|
| 76 | poly: use a polynomial of the order given
|
|---|
| 77 | gauss: fit the number of gaussian specified
|
|---|
| 78 | Example:
|
|---|
| 79 | fitter.set_function(gauss=2) # will fit two gaussians
|
|---|
| 80 | fitter.set_function(poly=3) # will fit a 3rd order polynomial
|
|---|
| 81 | """
|
|---|
| [723] | 82 | #default poly order 0
|
|---|
| [515] | 83 | n=0
|
|---|
| [113] | 84 | if kwargs.has_key('poly'):
|
|---|
| 85 | self.fitfunc = 'poly'
|
|---|
| 86 | n = kwargs.get('poly')
|
|---|
| [515] | 87 | self.components = [n]
|
|---|
| [113] | 88 | elif kwargs.has_key('gauss'):
|
|---|
| 89 | n = kwargs.get('gauss')
|
|---|
| 90 | self.fitfunc = 'gauss'
|
|---|
| [515] | 91 | self.fitfuncs = [ 'gauss' for i in range(n) ]
|
|---|
| 92 | self.components = [ 3 for i in range(n) ]
|
|---|
| 93 | else:
|
|---|
| [723] | 94 | msg = "Invalid function type."
|
|---|
| 95 | if rcParams['verbose']:
|
|---|
| 96 | print msg
|
|---|
| 97 | return
|
|---|
| 98 | else:
|
|---|
| 99 | raise TypeError(msg)
|
|---|
| 100 |
|
|---|
| [113] | 101 | self.fitter.setexpression(self.fitfunc,n)
|
|---|
| 102 | return
|
|---|
| [723] | 103 |
|
|---|
| [515] | 104 | def fit(self, row=0):
|
|---|
| [113] | 105 | """
|
|---|
| 106 | Execute the actual fitting process. All the state has to be set.
|
|---|
| 107 | Parameters:
|
|---|
| [526] | 108 | row: specify the row in the scantable
|
|---|
| [113] | 109 | Example:
|
|---|
| [515] | 110 | s = scantable('myscan.asap')
|
|---|
| 111 | s.set_cursor(thepol=1) # select second pol
|
|---|
| [113] | 112 | f = fitter()
|
|---|
| 113 | f.set_scan(s)
|
|---|
| 114 | f.set_function(poly=0)
|
|---|
| [723] | 115 | f.fit(row=0) # fit first row
|
|---|
| [113] | 116 | """
|
|---|
| 117 | if ((self.x is None or self.y is None) and self.data is None) \
|
|---|
| 118 | or self.fitfunc is None:
|
|---|
| [723] | 119 | msg = "Fitter not yet initialised. Please set data & fit function"
|
|---|
| 120 | if rcParams['verbose']:
|
|---|
| 121 | print msg
|
|---|
| 122 | return
|
|---|
| 123 | else:
|
|---|
| 124 | raise RuntimeError(msg)
|
|---|
| 125 |
|
|---|
| [113] | 126 | else:
|
|---|
| 127 | if self.data is not None:
|
|---|
| [515] | 128 | self.x = self.data._getabcissa(row)
|
|---|
| 129 | self.y = self.data._getspectrum(row)
|
|---|
| [723] | 130 | from asap import asaplog
|
|---|
| 131 | asaplog.push("Fitting:")
|
|---|
| [515] | 132 | self.selection = self.data.get_cursor()
|
|---|
| 133 | self.fitter.setdata(self.x, self.y, self.mask)
|
|---|
| [113] | 134 | if self.fitfunc == 'gauss':
|
|---|
| 135 | ps = self.fitter.getparameters()
|
|---|
| 136 | if len(ps) == 0:
|
|---|
| 137 | self.fitter.estimate()
|
|---|
| [626] | 138 | try:
|
|---|
| 139 | self.fitter.fit()
|
|---|
| 140 | except RuntimeError, msg:
|
|---|
| [723] | 141 | if rcParams['verbose']:
|
|---|
| 142 | print msg
|
|---|
| 143 | else:
|
|---|
| 144 | raise
|
|---|
| [515] | 145 | self._fittedrow = row
|
|---|
| [113] | 146 | self.fitted = True
|
|---|
| [723] | 147 | print_log()
|
|---|
| [113] | 148 | return
|
|---|
| 149 |
|
|---|
| [515] | 150 | def store_fit(self):
|
|---|
| [526] | 151 | """
|
|---|
| 152 | Store the fit parameters in the scantable.
|
|---|
| 153 | """
|
|---|
| [515] | 154 | if self.fitted and self.data is not None:
|
|---|
| 155 | pars = list(self.fitter.getparameters())
|
|---|
| 156 | fixed = list(self.fitter.getfixedparameters())
|
|---|
| 157 | self.data._addfit(self._fittedrow, pars, fixed,
|
|---|
| 158 | self.fitfuncs, self.components)
|
|---|
| 159 |
|
|---|
| 160 | def set_parameters(self, params, fixed=None, component=None):
|
|---|
| [526] | 161 | """
|
|---|
| 162 | Set the parameters to be fitted.
|
|---|
| 163 | Parameters:
|
|---|
| 164 | params: a vector of parameters
|
|---|
| 165 | fixed: a vector of which parameters are to be held fixed
|
|---|
| 166 | (default is none)
|
|---|
| 167 | component: in case of multiple gaussians, the index of the
|
|---|
| 168 | component
|
|---|
| 169 | """
|
|---|
| [515] | 170 | if self.fitfunc is None:
|
|---|
| [723] | 171 | msg = "Please specify a fitting function first."
|
|---|
| 172 | if rcParams['verbose']:
|
|---|
| 173 | print msg
|
|---|
| 174 | return
|
|---|
| 175 | else:
|
|---|
| 176 | raise RuntimeError(msg)
|
|---|
| [515] | 177 | if self.fitfunc == "gauss" and component is not None:
|
|---|
| 178 | if not self.fitted:
|
|---|
| 179 | from numarray import zeros
|
|---|
| 180 | pars = list(zeros(len(self.components)*3))
|
|---|
| 181 | fxd = list(zeros(len(pars)))
|
|---|
| 182 | else:
|
|---|
| [723] | 183 | pars = list(self.fitter.getparameters())
|
|---|
| [515] | 184 | fxd = list(self.fitter.getfixedparameters())
|
|---|
| 185 | i = 3*component
|
|---|
| 186 | pars[i:i+3] = params
|
|---|
| 187 | fxd[i:i+3] = fixed
|
|---|
| 188 | params = pars
|
|---|
| [723] | 189 | fixed = fxd
|
|---|
| [113] | 190 | self.fitter.setparameters(params)
|
|---|
| 191 | if fixed is not None:
|
|---|
| 192 | self.fitter.setfixedparameters(fixed)
|
|---|
| [723] | 193 | print_log()
|
|---|
| [113] | 194 | return
|
|---|
| [515] | 195 |
|
|---|
| 196 | def set_gauss_parameters(self, peak, centre, fhwm,
|
|---|
| 197 | peakfixed=False, centerfixed=False,
|
|---|
| 198 | fhwmfixed=False,
|
|---|
| 199 | component=0):
|
|---|
| [113] | 200 | """
|
|---|
| [515] | 201 | Set the Parameters of a 'Gaussian' component, set with set_function.
|
|---|
| 202 | Parameters:
|
|---|
| 203 | peak, centre, fhwm: The gaussian parameters
|
|---|
| 204 | peakfixed,
|
|---|
| 205 | centerfixed,
|
|---|
| 206 | fhwmfixed: Optional parameters to indicate if
|
|---|
| 207 | the paramters should be held fixed during
|
|---|
| 208 | the fitting process. The default is to keep
|
|---|
| 209 | all parameters flexible.
|
|---|
| [526] | 210 | component: The number of the component (Default is the
|
|---|
| 211 | component 0)
|
|---|
| [515] | 212 | """
|
|---|
| 213 | if self.fitfunc != "gauss":
|
|---|
| [723] | 214 | msg = "Function only operates on Gaussian components."
|
|---|
| 215 | if rcParams['verbose']:
|
|---|
| 216 | print msg
|
|---|
| 217 | return
|
|---|
| 218 | else:
|
|---|
| 219 | raise ValueError(msg)
|
|---|
| [515] | 220 | if 0 <= component < len(self.components):
|
|---|
| 221 | self.set_parameters([peak, centre, fhwm],
|
|---|
| 222 | [peakfixed, centerfixed, fhwmfixed],
|
|---|
| 223 | component)
|
|---|
| 224 | else:
|
|---|
| [723] | 225 | msg = "Please select a valid component."
|
|---|
| 226 | if rcParams['verbose']:
|
|---|
| 227 | print msg
|
|---|
| 228 | return
|
|---|
| 229 | else:
|
|---|
| 230 | raise ValueError(msg)
|
|---|
| 231 |
|
|---|
| [515] | 232 | def get_parameters(self, component=None):
|
|---|
| 233 | """
|
|---|
| [113] | 234 | Return the fit paramters.
|
|---|
| [526] | 235 | Parameters:
|
|---|
| 236 | component: get the parameters for the specified component
|
|---|
| 237 | only, default is all components
|
|---|
| [113] | 238 | """
|
|---|
| 239 | if not self.fitted:
|
|---|
| [723] | 240 | msg = "Not yet fitted."
|
|---|
| 241 | if rcParams['verbose']:
|
|---|
| 242 | print msg
|
|---|
| 243 | return
|
|---|
| 244 | else:
|
|---|
| 245 | raise RuntimeError(msg)
|
|---|
| [113] | 246 | pars = list(self.fitter.getparameters())
|
|---|
| 247 | fixed = list(self.fitter.getfixedparameters())
|
|---|
| [723] | 248 | if component is not None:
|
|---|
| [515] | 249 | if self.fitfunc == "gauss":
|
|---|
| 250 | i = 3*component
|
|---|
| 251 | cpars = pars[i:i+3]
|
|---|
| 252 | cfixed = fixed[i:i+3]
|
|---|
| 253 | else:
|
|---|
| 254 | cpars = pars
|
|---|
| [723] | 255 | cfixed = fixed
|
|---|
| [515] | 256 | else:
|
|---|
| 257 | cpars = pars
|
|---|
| 258 | cfixed = fixed
|
|---|
| 259 | fpars = self._format_pars(cpars, cfixed)
|
|---|
| [723] | 260 | if rcParams['verbose']:
|
|---|
| [515] | 261 | print fpars
|
|---|
| 262 | return cpars, cfixed, fpars
|
|---|
| [723] | 263 |
|
|---|
| [515] | 264 | def _format_pars(self, pars, fixed):
|
|---|
| [113] | 265 | out = ''
|
|---|
| 266 | if self.fitfunc == 'poly':
|
|---|
| 267 | c = 0
|
|---|
| [515] | 268 | for i in range(len(pars)):
|
|---|
| 269 | fix = ""
|
|---|
| 270 | if fixed[i]: fix = "(fixed)"
|
|---|
| 271 | out += ' p%d%s= %3.3f,' % (c,fix,pars[i])
|
|---|
| [113] | 272 | c+=1
|
|---|
| [515] | 273 | out = out[:-1] # remove trailing ','
|
|---|
| [113] | 274 | elif self.fitfunc == 'gauss':
|
|---|
| 275 | i = 0
|
|---|
| 276 | c = 0
|
|---|
| [515] | 277 | aunit = ''
|
|---|
| 278 | ounit = ''
|
|---|
| [113] | 279 | if self.data:
|
|---|
| [515] | 280 | aunit = self.data.get_unit()
|
|---|
| 281 | ounit = self.data.get_fluxunit()
|
|---|
| [113] | 282 | while i < len(pars):
|
|---|
| [515] | 283 | out += ' %d: peak = %3.3f %s , centre = %3.3f %s, FWHM = %3.3f %s \n' % (c,pars[i],ounit,pars[i+1],aunit,pars[i+2],aunit)
|
|---|
| [113] | 284 | c+=1
|
|---|
| 285 | i+=3
|
|---|
| 286 | return out
|
|---|
| [723] | 287 |
|
|---|
| [113] | 288 | def get_estimate(self):
|
|---|
| 289 | """
|
|---|
| [515] | 290 | Return the parameter estimates (for non-linear functions).
|
|---|
| [113] | 291 | """
|
|---|
| 292 | pars = self.fitter.getestimate()
|
|---|
| [723] | 293 | if rcParams['verbose']:
|
|---|
| [113] | 294 | print self._format_pars(pars)
|
|---|
| 295 | return pars
|
|---|
| 296 |
|
|---|
| 297 | def get_residual(self):
|
|---|
| 298 | """
|
|---|
| 299 | Return the residual of the fit.
|
|---|
| 300 | """
|
|---|
| 301 | if not self.fitted:
|
|---|
| [723] | 302 | msg = "Not yet fitted."
|
|---|
| 303 | if rcParams['verbose']:
|
|---|
| 304 | print msg
|
|---|
| 305 | return
|
|---|
| 306 | else:
|
|---|
| 307 | raise RuntimeError(msg)
|
|---|
| [113] | 308 | return self.fitter.getresidual()
|
|---|
| 309 |
|
|---|
| 310 | def get_chi2(self):
|
|---|
| 311 | """
|
|---|
| 312 | Return chi^2.
|
|---|
| 313 | """
|
|---|
| 314 | if not self.fitted:
|
|---|
| [723] | 315 | msg = "Not yet fitted."
|
|---|
| 316 | if rcParams['verbose']:
|
|---|
| 317 | print msg
|
|---|
| 318 | return
|
|---|
| 319 | else:
|
|---|
| 320 | raise RuntimeError(msg)
|
|---|
| [113] | 321 | ch2 = self.fitter.getchi2()
|
|---|
| [723] | 322 | if rcParams['verbose']:
|
|---|
| [113] | 323 | print 'Chi^2 = %3.3f' % (ch2)
|
|---|
| [723] | 324 | return ch2
|
|---|
| [113] | 325 |
|
|---|
| 326 | def get_fit(self):
|
|---|
| 327 | """
|
|---|
| 328 | Return the fitted ordinate values.
|
|---|
| 329 | """
|
|---|
| 330 | if not self.fitted:
|
|---|
| [723] | 331 | msg = "Not yet fitted."
|
|---|
| 332 | if rcParams['verbose']:
|
|---|
| 333 | print msg
|
|---|
| 334 | return
|
|---|
| 335 | else:
|
|---|
| 336 | raise RuntimeError(msg)
|
|---|
| [113] | 337 | return self.fitter.getfit()
|
|---|
| 338 |
|
|---|
| 339 | def commit(self):
|
|---|
| 340 | """
|
|---|
| [526] | 341 | Return a new scan where the fits have been commited (subtracted)
|
|---|
| [113] | 342 | """
|
|---|
| 343 | if not self.fitted:
|
|---|
| 344 | print "Not yet fitted."
|
|---|
| [723] | 345 | msg = "Not yet fitted."
|
|---|
| 346 | if rcParams['verbose']:
|
|---|
| 347 | print msg
|
|---|
| 348 | return
|
|---|
| 349 | else:
|
|---|
| 350 | raise RuntimeError(msg)
|
|---|
| [113] | 351 | if self.data is not scantable:
|
|---|
| [723] | 352 | msg = "Not a scantable"
|
|---|
| 353 | if rcParams['verbose']:
|
|---|
| 354 | print msg
|
|---|
| 355 | return
|
|---|
| 356 | else:
|
|---|
| 357 | raise TypeError(msg)
|
|---|
| [113] | 358 | scan = self.data.copy()
|
|---|
| [259] | 359 | scan._setspectrum(self.fitter.getresidual())
|
|---|
| [723] | 360 | print_log()
|
|---|
| [113] | 361 |
|
|---|
| [723] | 362 | def plot(self, residual=False, components=None, plotparms=False, filename=None):
|
|---|
| [113] | 363 | """
|
|---|
| 364 | Plot the last fit.
|
|---|
| 365 | Parameters:
|
|---|
| 366 | residual: an optional parameter indicating if the residual
|
|---|
| 367 | should be plotted (default 'False')
|
|---|
| [526] | 368 | components: a list of components to plot, e.g [0,1],
|
|---|
| 369 | -1 plots the total fit. Default is to only
|
|---|
| 370 | plot the total fit.
|
|---|
| 371 | plotparms: Inidicates if the parameter values should be present
|
|---|
| 372 | on the plot
|
|---|
| [113] | 373 | """
|
|---|
| 374 | if not self.fitted:
|
|---|
| 375 | return
|
|---|
| [723] | 376 | if not self._p or self._p.is_dead:
|
|---|
| 377 | if rcParams['plotter.gui']:
|
|---|
| 378 | from asap.asaplotgui import asaplotgui as asaplot
|
|---|
| 379 | else:
|
|---|
| 380 | from asap.asaplot import asaplot
|
|---|
| 381 | self._p = asaplot()
|
|---|
| 382 | self._p.hold()
|
|---|
| [113] | 383 | self._p.clear()
|
|---|
| [515] | 384 | self._p.set_panels()
|
|---|
| [652] | 385 | self._p.palette(0)
|
|---|
| [113] | 386 | tlab = 'Spectrum'
|
|---|
| [723] | 387 | xlab = 'Abcissa'
|
|---|
| [515] | 388 | m = ()
|
|---|
| [113] | 389 | if self.data:
|
|---|
| [515] | 390 | tlab = self.data._getsourcename(self._fittedrow)
|
|---|
| 391 | xlab = self.data._getabcissalabel(self._fittedrow)
|
|---|
| 392 | m = self.data._getmask(self._fittedrow)
|
|---|
| [626] | 393 | ylab = self.data._get_ordinate_label()
|
|---|
| [515] | 394 |
|
|---|
| [668] | 395 | colours = ["#777777","#bbbbbb","red","orange","purple","green","magenta", "cyan"]
|
|---|
| [652] | 396 | self._p.palette(0,colours)
|
|---|
| [515] | 397 | self._p.set_line(label='Spectrum')
|
|---|
| [113] | 398 | self._p.plot(self.x, self.y, m)
|
|---|
| 399 | if residual:
|
|---|
| [652] | 400 | self._p.palette(1)
|
|---|
| [515] | 401 | self._p.set_line(label='Residual')
|
|---|
| [113] | 402 | self._p.plot(self.x, self.get_residual(), m)
|
|---|
| [652] | 403 | self._p.palette(2)
|
|---|
| [515] | 404 | if components is not None:
|
|---|
| 405 | cs = components
|
|---|
| 406 | if isinstance(components,int): cs = [components]
|
|---|
| [526] | 407 | if plotparms:
|
|---|
| 408 | self._p.text(0.15,0.15,str(self.get_parameters()[2]),size=8)
|
|---|
| [515] | 409 | n = len(self.components)
|
|---|
| [652] | 410 | self._p.palette(3)
|
|---|
| [515] | 411 | for c in cs:
|
|---|
| 412 | if 0 <= c < n:
|
|---|
| 413 | lab = self.fitfuncs[c]+str(c)
|
|---|
| 414 | self._p.set_line(label=lab)
|
|---|
| 415 | self._p.plot(self.x, self.fitter.evaluate(c), m)
|
|---|
| 416 | elif c == -1:
|
|---|
| [652] | 417 | self._p.palette(2)
|
|---|
| [515] | 418 | self._p.set_line(label="Total Fit")
|
|---|
| [723] | 419 | self._p.plot(self.x, self.get_fit(), m)
|
|---|
| [515] | 420 | else:
|
|---|
| [652] | 421 | self._p.palette(2)
|
|---|
| [515] | 422 | self._p.set_line(label='Fit')
|
|---|
| 423 | self._p.plot(self.x, self.get_fit(), m)
|
|---|
| [723] | 424 | xlim=[min(self.x),max(self.x)]
|
|---|
| 425 | self._p.axes.set_xlim(xlim)
|
|---|
| [113] | 426 | self._p.set_axes('xlabel',xlab)
|
|---|
| 427 | self._p.set_axes('ylabel',ylab)
|
|---|
| 428 | self._p.set_axes('title',tlab)
|
|---|
| 429 | self._p.release()
|
|---|
| [723] | 430 | if (not rcParams['plotter.gui']):
|
|---|
| 431 | self._p.save(filename)
|
|---|
| 432 | print_log()
|
|---|
| [113] | 433 |
|
|---|
| [786] | 434 | def auto_fit(self, insitu=None, allaxes=True):
|
|---|
| [113] | 435 | """
|
|---|
| [515] | 436 | Return a scan where the function is applied to all rows for
|
|---|
| 437 | all Beams/IFs/Pols.
|
|---|
| [723] | 438 |
|
|---|
| [113] | 439 | """
|
|---|
| 440 | from asap import scantable
|
|---|
| [515] | 441 | if not isinstance(self.data, scantable) :
|
|---|
| [723] | 442 | msg = "Data is not a scantable"
|
|---|
| 443 | if rcParams['verbose']:
|
|---|
| 444 | print msg
|
|---|
| 445 | return
|
|---|
| 446 | else:
|
|---|
| 447 | raise TypeError(msg)
|
|---|
| [259] | 448 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 449 | if not insitu:
|
|---|
| 450 | scan = self.data.copy()
|
|---|
| 451 | else:
|
|---|
| 452 | scan = self.data
|
|---|
| 453 | sel = scan.get_cursor()
|
|---|
| [159] | 454 | rows = range(scan.nrow())
|
|---|
| [723] | 455 | from asap import asaplog
|
|---|
| [786] | 456 | if allaxes:
|
|---|
| 457 | for i in range(scan.nbeam()):
|
|---|
| 458 | scan.setbeam(i)
|
|---|
| 459 | for j in range(scan.nif()):
|
|---|
| 460 | scan.setif(j)
|
|---|
| 461 | for k in range(scan.npol()):
|
|---|
| 462 | scan.setpol(k)
|
|---|
| 463 | asaplog.push("Fitting:")
|
|---|
| 464 | out = 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k)
|
|---|
| 465 | asaplog.push(out)
|
|---|
| 466 | for iRow in rows:
|
|---|
| 467 | self.x = scan._getabcissa(iRow)
|
|---|
| 468 | self.y = scan._getspectrum(iRow)
|
|---|
| 469 | self.data = None
|
|---|
| 470 | self.fit()
|
|---|
| 471 | x = self.get_parameters()
|
|---|
| 472 | scan._setspectrum(self.fitter.getresidual(),iRow)
|
|---|
| 473 | else:
|
|---|
| 474 | asaplog.push("Fitting:")
|
|---|
| 475 | out = 'Beam[%d], IF[%d], Pol[%d]' % sel
|
|---|
| 476 | asaplog.push(out)
|
|---|
| 477 | for iRow in rows:
|
|---|
| 478 | self.x = scan._getabcissa(iRow)
|
|---|
| 479 | self.y = scan._getspectrum(iRow)
|
|---|
| 480 | self.data = None
|
|---|
| 481 | self.fit()
|
|---|
| 482 | x = self.get_parameters()
|
|---|
| 483 | scan._setspectrum(self.fitter.getresidual(),iRow)
|
|---|
| 484 |
|
|---|
| [259] | 485 | scan.set_cursor(sel[0],sel[1],sel[2])
|
|---|
| [723] | 486 | print_log()
|
|---|
| [259] | 487 | if not insitu:
|
|---|
| 488 | return scan
|
|---|
