| 1 | import _asap |
|---|
| 2 | from asap import rcParams |
|---|
| 3 | from asap import print_log |
|---|
| 4 | from asap import _n_bools |
|---|
| 5 | |
|---|
| 6 | class fitter: |
|---|
| 7 | """ |
|---|
| 8 | The fitting class for ASAP. |
|---|
| 9 | """ |
|---|
| 10 | |
|---|
| 11 | def __init__(self): |
|---|
| 12 | """ |
|---|
| 13 | Create a fitter object. No state is set. |
|---|
| 14 | """ |
|---|
| 15 | self.fitter = _asap.fitter() |
|---|
| 16 | self.x = None |
|---|
| 17 | self.y = None |
|---|
| 18 | self.mask = None |
|---|
| 19 | self.fitfunc = None |
|---|
| 20 | self.fitfuncs = None |
|---|
| 21 | self.fitted = False |
|---|
| 22 | self.data = None |
|---|
| 23 | self.components = 0 |
|---|
| 24 | self._fittedrow = 0 |
|---|
| 25 | self._p = None |
|---|
| 26 | self._selection = None |
|---|
| 27 | self.uselinear = False |
|---|
| 28 | |
|---|
| 29 | def set_data(self, xdat, ydat, mask=None): |
|---|
| 30 | """ |
|---|
| 31 | Set the absissa and ordinate for the fit. Also set the mask |
|---|
| 32 | indicationg valid points. |
|---|
| 33 | This can be used for data vectors retrieved from a scantable. |
|---|
| 34 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
|---|
| 35 | Parameters: |
|---|
| 36 | xdat: the abcissa values |
|---|
| 37 | ydat: the ordinate values |
|---|
| 38 | mask: an optional mask |
|---|
| 39 | |
|---|
| 40 | """ |
|---|
| 41 | self.fitted = False |
|---|
| 42 | self.x = xdat |
|---|
| 43 | self.y = ydat |
|---|
| 44 | if mask == None: |
|---|
| 45 | self.mask = _n_bools(len(xdat), True) |
|---|
| 46 | else: |
|---|
| 47 | self.mask = mask |
|---|
| 48 | return |
|---|
| 49 | |
|---|
| 50 | def set_scan(self, thescan=None, mask=None): |
|---|
| 51 | """ |
|---|
| 52 | Set the 'data' (a scantable) of the fitter. |
|---|
| 53 | Parameters: |
|---|
| 54 | thescan: a scantable |
|---|
| 55 | mask: a msk retrieved from the scantable |
|---|
| 56 | """ |
|---|
| 57 | if not thescan: |
|---|
| 58 | msg = "Please give a correct scan" |
|---|
| 59 | if rcParams['verbose']: |
|---|
| 60 | print msg |
|---|
| 61 | return |
|---|
| 62 | else: |
|---|
| 63 | raise TypeError(msg) |
|---|
| 64 | self.fitted = False |
|---|
| 65 | self.data = thescan |
|---|
| 66 | self.mask = None |
|---|
| 67 | if mask is None: |
|---|
| 68 | self.mask = _n_bools(self.data.nchan(), True) |
|---|
| 69 | else: |
|---|
| 70 | self.mask = mask |
|---|
| 71 | return |
|---|
| 72 | |
|---|
| 73 | def set_function(self, **kwargs): |
|---|
| 74 | """ |
|---|
| 75 | Set the function to be fit. |
|---|
| 76 | Parameters: |
|---|
| 77 | poly: use a polynomial of the order given with nonlinear least squares fit |
|---|
| 78 | lpoly: use polynomial of the order given with linear least squares fit |
|---|
| 79 | gauss: fit the number of gaussian specified |
|---|
| 80 | Example: |
|---|
| 81 | fitter.set_function(gauss=2) # will fit two gaussians |
|---|
| 82 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method |
|---|
| 83 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method |
|---|
| 84 | """ |
|---|
| 85 | #default poly order 0 |
|---|
| 86 | n=0 |
|---|
| 87 | if kwargs.has_key('poly'): |
|---|
| 88 | self.fitfunc = 'poly' |
|---|
| 89 | n = kwargs.get('poly') |
|---|
| 90 | self.components = [n] |
|---|
| 91 | self.uselinear = False |
|---|
| 92 | elif kwargs.has_key('lpoly'): |
|---|
| 93 | self.fitfunc = 'poly' |
|---|
| 94 | n = kwargs.get('lpoly') |
|---|
| 95 | self.components = [n] |
|---|
| 96 | self.uselinear = True |
|---|
| 97 | elif kwargs.has_key('gauss'): |
|---|
| 98 | n = kwargs.get('gauss') |
|---|
| 99 | self.fitfunc = 'gauss' |
|---|
| 100 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
|---|
| 101 | self.components = [ 3 for i in range(n) ] |
|---|
| 102 | self.uselinear = False |
|---|
| 103 | else: |
|---|
| 104 | msg = "Invalid function type." |
|---|
| 105 | if rcParams['verbose']: |
|---|
| 106 | print msg |
|---|
| 107 | return |
|---|
| 108 | else: |
|---|
| 109 | raise TypeError(msg) |
|---|
| 110 | |
|---|
| 111 | self.fitter.setexpression(self.fitfunc,n) |
|---|
| 112 | self.fitted = False |
|---|
| 113 | return |
|---|
| 114 | |
|---|
| 115 | def fit(self, row=0, estimate=False): |
|---|
| 116 | """ |
|---|
| 117 | Execute the actual fitting process. All the state has to be set. |
|---|
| 118 | Parameters: |
|---|
| 119 | row: specify the row in the scantable |
|---|
| 120 | estimate: auto-compute an initial parameter set (default False) |
|---|
| 121 | This can be used to compute estimates even if fit was |
|---|
| 122 | called before. |
|---|
| 123 | Example: |
|---|
| 124 | s = scantable('myscan.asap') |
|---|
| 125 | s.set_cursor(thepol=1) # select second pol |
|---|
| 126 | f = fitter() |
|---|
| 127 | f.set_scan(s) |
|---|
| 128 | f.set_function(poly=0) |
|---|
| 129 | f.fit(row=0) # fit first row |
|---|
| 130 | """ |
|---|
| 131 | if ((self.x is None or self.y is None) and self.data is None) \ |
|---|
| 132 | or self.fitfunc is None: |
|---|
| 133 | msg = "Fitter not yet initialised. Please set data & fit function" |
|---|
| 134 | if rcParams['verbose']: |
|---|
| 135 | print msg |
|---|
| 136 | return |
|---|
| 137 | else: |
|---|
| 138 | raise RuntimeError(msg) |
|---|
| 139 | |
|---|
| 140 | else: |
|---|
| 141 | if self.data is not None: |
|---|
| 142 | self.x = self.data._getabcissa(row) |
|---|
| 143 | self.y = self.data._getspectrum(row) |
|---|
| 144 | from asap import asaplog |
|---|
| 145 | asaplog.push("Fitting:") |
|---|
| 146 | i = row |
|---|
| 147 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i),self.data.getbeam(i),self.data.getif(i),self.data.getpol(i), self.data.getcycle(i)) |
|---|
| 148 | asaplog.push(out,False) |
|---|
| 149 | self.fitter.setdata(self.x, self.y, self.mask) |
|---|
| 150 | if self.fitfunc == 'gauss': |
|---|
| 151 | ps = self.fitter.getparameters() |
|---|
| 152 | if len(ps) == 0 or estimate: |
|---|
| 153 | self.fitter.estimate() |
|---|
| 154 | try: |
|---|
| 155 | fxdpar = list(self.fitter.getfixedparameters()) |
|---|
| 156 | if len(fxdpar) and fxdpar.count(0) == 0: |
|---|
| 157 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
|---|
| 158 | if self.uselinear: |
|---|
| 159 | converged = self.fitter.lfit() |
|---|
| 160 | else: |
|---|
| 161 | converged = self.fitter.fit() |
|---|
| 162 | if not converged: |
|---|
| 163 | raise RuntimeError,"Fit didn't converge." |
|---|
| 164 | except RuntimeError, msg: |
|---|
| 165 | if rcParams['verbose']: |
|---|
| 166 | print msg |
|---|
| 167 | else: |
|---|
| 168 | raise |
|---|
| 169 | self._fittedrow = row |
|---|
| 170 | self.fitted = True |
|---|
| 171 | print_log() |
|---|
| 172 | return |
|---|
| 173 | |
|---|
| 174 | def store_fit(self, filename=None): |
|---|
| 175 | """ |
|---|
| 176 | Save the fit parameters. |
|---|
| 177 | Parameters: |
|---|
| 178 | filename: if specified save as an ASCII file, if None (default) |
|---|
| 179 | store it in the scnatable |
|---|
| 180 | """ |
|---|
| 181 | if self.fitted and self.data is not None: |
|---|
| 182 | pars = list(self.fitter.getparameters()) |
|---|
| 183 | fixed = list(self.fitter.getfixedparameters()) |
|---|
| 184 | from asap.asapfit import asapfit |
|---|
| 185 | fit = asapfit() |
|---|
| 186 | fit.setparameters(pars) |
|---|
| 187 | fit.setfixedparameters(fixed) |
|---|
| 188 | fit.setfunctions(self.fitfuncs) |
|---|
| 189 | fit.setcomponents(self.components) |
|---|
| 190 | fit.setframeinfo(self.data._getcoordinfo()) |
|---|
| 191 | if filename is not None: |
|---|
| 192 | import os |
|---|
| 193 | filename = os.path.expandvars(os.path.expanduser(filename)) |
|---|
| 194 | if os.path.exists(filename): |
|---|
| 195 | raise IOError("File '%s' exists." % filename) |
|---|
| 196 | fit.save(filename) |
|---|
| 197 | else: |
|---|
| 198 | self.data._addfit(fit,self._fittedrow) |
|---|
| 199 | |
|---|
| 200 | #def set_parameters(self, params, fixed=None, component=None): |
|---|
| 201 | def set_parameters(self,*args,**kwargs): |
|---|
| 202 | """ |
|---|
| 203 | Set the parameters to be fitted. |
|---|
| 204 | Parameters: |
|---|
| 205 | params: a vector of parameters |
|---|
| 206 | fixed: a vector of which parameters are to be held fixed |
|---|
| 207 | (default is none) |
|---|
| 208 | component: in case of multiple gaussians, the index of the |
|---|
| 209 | component |
|---|
| 210 | """ |
|---|
| 211 | component = None |
|---|
| 212 | fixed = None |
|---|
| 213 | params = None |
|---|
| 214 | |
|---|
| 215 | if len(args) and isinstance(args[0],dict): |
|---|
| 216 | kwargs = args[0] |
|---|
| 217 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
|---|
| 218 | if kwargs.has_key("params"): params = kwargs["params"] |
|---|
| 219 | if len(args) == 2 and isinstance(args[1], int): |
|---|
| 220 | component = args[1] |
|---|
| 221 | if self.fitfunc is None: |
|---|
| 222 | msg = "Please specify a fitting function first." |
|---|
| 223 | if rcParams['verbose']: |
|---|
| 224 | print msg |
|---|
| 225 | return |
|---|
| 226 | else: |
|---|
| 227 | raise RuntimeError(msg) |
|---|
| 228 | if self.fitfunc == "gauss" and component is not None: |
|---|
| 229 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
|---|
| 230 | pars = _n_bools(len(self.components)*3, False) |
|---|
| 231 | fxd = _n_bools(len(pars), False) |
|---|
| 232 | else: |
|---|
| 233 | pars = list(self.fitter.getparameters()) |
|---|
| 234 | fxd = list(self.fitter.getfixedparameters()) |
|---|
| 235 | i = 3*component |
|---|
| 236 | pars[i:i+3] = params |
|---|
| 237 | fxd[i:i+3] = fixed |
|---|
| 238 | params = pars |
|---|
| 239 | fixed = fxd |
|---|
| 240 | self.fitter.setparameters(params) |
|---|
| 241 | if fixed is not None: |
|---|
| 242 | self.fitter.setfixedparameters(fixed) |
|---|
| 243 | print_log() |
|---|
| 244 | return |
|---|
| 245 | |
|---|
| 246 | def set_gauss_parameters(self, peak, centre, fwhm, |
|---|
| 247 | peakfixed=0, centrefixed=0, |
|---|
| 248 | fwhmfixed=0, |
|---|
| 249 | component=0): |
|---|
| 250 | """ |
|---|
| 251 | Set the Parameters of a 'Gaussian' component, set with set_function. |
|---|
| 252 | Parameters: |
|---|
| 253 | peak, centre, fwhm: The gaussian parameters |
|---|
| 254 | peakfixed, |
|---|
| 255 | centrefixed, |
|---|
| 256 | fwhmfixed: Optional parameters to indicate if |
|---|
| 257 | the paramters should be held fixed during |
|---|
| 258 | the fitting process. The default is to keep |
|---|
| 259 | all parameters flexible. |
|---|
| 260 | component: The number of the component (Default is the |
|---|
| 261 | component 0) |
|---|
| 262 | """ |
|---|
| 263 | if self.fitfunc != "gauss": |
|---|
| 264 | msg = "Function only operates on Gaussian components." |
|---|
| 265 | if rcParams['verbose']: |
|---|
| 266 | print msg |
|---|
| 267 | return |
|---|
| 268 | else: |
|---|
| 269 | raise ValueError(msg) |
|---|
| 270 | if 0 <= component < len(self.components): |
|---|
| 271 | d = {'params':[peak, centre, fwhm], |
|---|
| 272 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
|---|
| 273 | self.set_parameters(d, component) |
|---|
| 274 | else: |
|---|
| 275 | msg = "Please select a valid component." |
|---|
| 276 | if rcParams['verbose']: |
|---|
| 277 | print msg |
|---|
| 278 | return |
|---|
| 279 | else: |
|---|
| 280 | raise ValueError(msg) |
|---|
| 281 | |
|---|
| 282 | def get_area(self, component=None): |
|---|
| 283 | """ |
|---|
| 284 | Return the area under the fitted gaussian component. |
|---|
| 285 | Parameters: |
|---|
| 286 | component: the gaussian component selection, |
|---|
| 287 | default (None) is the sum of all components |
|---|
| 288 | Note: |
|---|
| 289 | This will only work for gaussian fits. |
|---|
| 290 | """ |
|---|
| 291 | if not self.fitted: return |
|---|
| 292 | if self.fitfunc == "gauss": |
|---|
| 293 | pars = list(self.fitter.getparameters()) |
|---|
| 294 | from math import log,pi,sqrt |
|---|
| 295 | fac = sqrt(pi/log(16.0)) |
|---|
| 296 | areas = [] |
|---|
| 297 | for i in range(len(self.components)): |
|---|
| 298 | j = i*3 |
|---|
| 299 | cpars = pars[j:j+3] |
|---|
| 300 | areas.append(fac * cpars[0] * cpars[2]) |
|---|
| 301 | else: |
|---|
| 302 | return None |
|---|
| 303 | if component is not None: |
|---|
| 304 | return areas[component] |
|---|
| 305 | else: |
|---|
| 306 | return sum(areas) |
|---|
| 307 | |
|---|
| 308 | def get_errors(self, component=None): |
|---|
| 309 | """ |
|---|
| 310 | Return the errors in the parameters. |
|---|
| 311 | Parameters: |
|---|
| 312 | component: get the errors for the specified component |
|---|
| 313 | only, default is all components |
|---|
| 314 | """ |
|---|
| 315 | if not self.fitted: |
|---|
| 316 | msg = "Not yet fitted." |
|---|
| 317 | if rcParams['verbose']: |
|---|
| 318 | print msg |
|---|
| 319 | return |
|---|
| 320 | else: |
|---|
| 321 | raise RuntimeError(msg) |
|---|
| 322 | errs = list(self.fitter.geterrors()) |
|---|
| 323 | cerrs = errs |
|---|
| 324 | if component is not None: |
|---|
| 325 | if self.fitfunc == "gauss": |
|---|
| 326 | i = 3*component |
|---|
| 327 | if i < len(errs): |
|---|
| 328 | cerrs = errs[i:i+3] |
|---|
| 329 | return cerrs |
|---|
| 330 | |
|---|
| 331 | def get_parameters(self, component=None, errors=False): |
|---|
| 332 | """ |
|---|
| 333 | Return the fit paramters. |
|---|
| 334 | Parameters: |
|---|
| 335 | component: get the parameters for the specified component |
|---|
| 336 | only, default is all components |
|---|
| 337 | """ |
|---|
| 338 | if not self.fitted: |
|---|
| 339 | msg = "Not yet fitted." |
|---|
| 340 | if rcParams['verbose']: |
|---|
| 341 | print msg |
|---|
| 342 | return |
|---|
| 343 | else: |
|---|
| 344 | raise RuntimeError(msg) |
|---|
| 345 | pars = list(self.fitter.getparameters()) |
|---|
| 346 | fixed = list(self.fitter.getfixedparameters()) |
|---|
| 347 | errs = list(self.fitter.geterrors()) |
|---|
| 348 | area = [] |
|---|
| 349 | if component is not None: |
|---|
| 350 | if self.fitfunc == "gauss": |
|---|
| 351 | i = 3*component |
|---|
| 352 | cpars = pars[i:i+3] |
|---|
| 353 | cfixed = fixed[i:i+3] |
|---|
| 354 | cerrs = errs[i:i+3] |
|---|
| 355 | a = self.get_area(component) |
|---|
| 356 | area = [a for i in range(3)] |
|---|
| 357 | else: |
|---|
| 358 | cpars = pars |
|---|
| 359 | cfixed = fixed |
|---|
| 360 | cerrs = errs |
|---|
| 361 | else: |
|---|
| 362 | cpars = pars |
|---|
| 363 | cfixed = fixed |
|---|
| 364 | cerrs = errs |
|---|
| 365 | if self.fitfunc == "gauss": |
|---|
| 366 | for c in range(len(self.components)): |
|---|
| 367 | a = self.get_area(c) |
|---|
| 368 | area += [a for i in range(3)] |
|---|
| 369 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
|---|
| 370 | if rcParams['verbose']: |
|---|
| 371 | print fpars |
|---|
| 372 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
|---|
| 373 | 'errors':cerrs} |
|---|
| 374 | |
|---|
| 375 | def _format_pars(self, pars, fixed, errors, area): |
|---|
| 376 | out = '' |
|---|
| 377 | if self.fitfunc == 'poly': |
|---|
| 378 | c = 0 |
|---|
| 379 | for i in range(len(pars)): |
|---|
| 380 | fix = "" |
|---|
| 381 | if len(fixed) and fixed[i]: fix = "(fixed)" |
|---|
| 382 | if errors : |
|---|
| 383 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i]) |
|---|
| 384 | else: |
|---|
| 385 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i]) |
|---|
| 386 | c+=1 |
|---|
| 387 | out = out[:-1] # remove trailing ',' |
|---|
| 388 | elif self.fitfunc == 'gauss': |
|---|
| 389 | i = 0 |
|---|
| 390 | c = 0 |
|---|
| 391 | aunit = '' |
|---|
| 392 | ounit = '' |
|---|
| 393 | if self.data: |
|---|
| 394 | aunit = self.data.get_unit() |
|---|
| 395 | ounit = self.data.get_fluxunit() |
|---|
| 396 | while i < len(pars): |
|---|
| 397 | if len(area): |
|---|
| 398 | out += ' %2d: peak = %3.3f %s , centre = %3.3f %s, FWHM = %3.3f %s\n area = %3.3f %s %s\n' % (c,pars[i],ounit,pars[i+1],aunit,pars[i+2],aunit, area[i],ounit,aunit) |
|---|
| 399 | else: |
|---|
| 400 | out += ' %2d: 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,ounit,aunit) |
|---|
| 401 | c+=1 |
|---|
| 402 | i+=3 |
|---|
| 403 | return out |
|---|
| 404 | |
|---|
| 405 | def get_estimate(self): |
|---|
| 406 | """ |
|---|
| 407 | Return the parameter estimates (for non-linear functions). |
|---|
| 408 | """ |
|---|
| 409 | pars = self.fitter.getestimate() |
|---|
| 410 | fixed = self.fitter.getfixedparameters() |
|---|
| 411 | if rcParams['verbose']: |
|---|
| 412 | print self._format_pars(pars,fixed,None) |
|---|
| 413 | return pars |
|---|
| 414 | |
|---|
| 415 | def get_residual(self): |
|---|
| 416 | """ |
|---|
| 417 | Return the residual of the fit. |
|---|
| 418 | """ |
|---|
| 419 | if not self.fitted: |
|---|
| 420 | msg = "Not yet fitted." |
|---|
| 421 | if rcParams['verbose']: |
|---|
| 422 | print msg |
|---|
| 423 | return |
|---|
| 424 | else: |
|---|
| 425 | raise RuntimeError(msg) |
|---|
| 426 | return self.fitter.getresidual() |
|---|
| 427 | |
|---|
| 428 | def get_chi2(self): |
|---|
| 429 | """ |
|---|
| 430 | Return chi^2. |
|---|
| 431 | """ |
|---|
| 432 | if not self.fitted: |
|---|
| 433 | msg = "Not yet fitted." |
|---|
| 434 | if rcParams['verbose']: |
|---|
| 435 | print msg |
|---|
| 436 | return |
|---|
| 437 | else: |
|---|
| 438 | raise RuntimeError(msg) |
|---|
| 439 | ch2 = self.fitter.getchi2() |
|---|
| 440 | if rcParams['verbose']: |
|---|
| 441 | print 'Chi^2 = %3.3f' % (ch2) |
|---|
| 442 | return ch2 |
|---|
| 443 | |
|---|
| 444 | def get_fit(self): |
|---|
| 445 | """ |
|---|
| 446 | Return the fitted ordinate values. |
|---|
| 447 | """ |
|---|
| 448 | if not self.fitted: |
|---|
| 449 | msg = "Not yet fitted." |
|---|
| 450 | if rcParams['verbose']: |
|---|
| 451 | print msg |
|---|
| 452 | return |
|---|
| 453 | else: |
|---|
| 454 | raise RuntimeError(msg) |
|---|
| 455 | return self.fitter.getfit() |
|---|
| 456 | |
|---|
| 457 | def commit(self): |
|---|
| 458 | """ |
|---|
| 459 | Return a new scan where the fits have been commited (subtracted) |
|---|
| 460 | """ |
|---|
| 461 | if not self.fitted: |
|---|
| 462 | msg = "Not yet fitted." |
|---|
| 463 | if rcParams['verbose']: |
|---|
| 464 | print msg |
|---|
| 465 | return |
|---|
| 466 | else: |
|---|
| 467 | raise RuntimeError(msg) |
|---|
| 468 | from asap import scantable |
|---|
| 469 | if not isinstance(self.data, scantable): |
|---|
| 470 | msg = "Not a scantable" |
|---|
| 471 | if rcParams['verbose']: |
|---|
| 472 | print msg |
|---|
| 473 | return |
|---|
| 474 | else: |
|---|
| 475 | raise TypeError(msg) |
|---|
| 476 | scan = self.data.copy() |
|---|
| 477 | scan._setspectrum(self.fitter.getresidual()) |
|---|
| 478 | print_log() |
|---|
| 479 | return scan |
|---|
| 480 | |
|---|
| 481 | def plot(self, residual=False, components=None, plotparms=False, filename=None): |
|---|
| 482 | """ |
|---|
| 483 | Plot the last fit. |
|---|
| 484 | Parameters: |
|---|
| 485 | residual: an optional parameter indicating if the residual |
|---|
| 486 | should be plotted (default 'False') |
|---|
| 487 | components: a list of components to plot, e.g [0,1], |
|---|
| 488 | -1 plots the total fit. Default is to only |
|---|
| 489 | plot the total fit. |
|---|
| 490 | plotparms: Inidicates if the parameter values should be present |
|---|
| 491 | on the plot |
|---|
| 492 | """ |
|---|
| 493 | if not self.fitted: |
|---|
| 494 | return |
|---|
| 495 | if not self._p or self._p.is_dead: |
|---|
| 496 | if rcParams['plotter.gui']: |
|---|
| 497 | from asap.asaplotgui import asaplotgui as asaplot |
|---|
| 498 | else: |
|---|
| 499 | from asap.asaplot import asaplot |
|---|
| 500 | self._p = asaplot() |
|---|
| 501 | self._p.hold() |
|---|
| 502 | self._p.clear() |
|---|
| 503 | self._p.set_panels() |
|---|
| 504 | self._p.palette(0) |
|---|
| 505 | tlab = 'Spectrum' |
|---|
| 506 | xlab = 'Abcissa' |
|---|
| 507 | ylab = 'Ordinate' |
|---|
| 508 | from matplotlib.numerix import ma,logical_not,logical_and,array |
|---|
| 509 | m = self.mask |
|---|
| 510 | if self.data: |
|---|
| 511 | tlab = self.data._getsourcename(self._fittedrow) |
|---|
| 512 | xlab = self.data._getabcissalabel(self._fittedrow) |
|---|
| 513 | m = logical_and(self.mask, |
|---|
| 514 | array(self.data._getmask(self._fittedrow), |
|---|
| 515 | copy=False)) |
|---|
| 516 | |
|---|
| 517 | ylab = self.data._get_ordinate_label() |
|---|
| 518 | |
|---|
| 519 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
|---|
| 520 | self._p.palette(0,colours) |
|---|
| 521 | self._p.set_line(label='Spectrum') |
|---|
| 522 | y = ma.masked_array(self.y,mask=logical_not(m)) |
|---|
| 523 | self._p.plot(self.x, y) |
|---|
| 524 | if residual: |
|---|
| 525 | self._p.palette(1) |
|---|
| 526 | self._p.set_line(label='Residual') |
|---|
| 527 | y = ma.masked_array(self.get_residual(), |
|---|
| 528 | mask=logical_not(m)) |
|---|
| 529 | self._p.plot(self.x, y) |
|---|
| 530 | self._p.palette(2) |
|---|
| 531 | if components is not None: |
|---|
| 532 | cs = components |
|---|
| 533 | if isinstance(components,int): cs = [components] |
|---|
| 534 | if plotparms: |
|---|
| 535 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
|---|
| 536 | n = len(self.components) |
|---|
| 537 | self._p.palette(3) |
|---|
| 538 | for c in cs: |
|---|
| 539 | if 0 <= c < n: |
|---|
| 540 | lab = self.fitfuncs[c]+str(c) |
|---|
| 541 | self._p.set_line(label=lab) |
|---|
| 542 | y = ma.masked_array(self.fitter.evaluate(c), |
|---|
| 543 | mask=logical_not(m)) |
|---|
| 544 | |
|---|
| 545 | self._p.plot(self.x, y) |
|---|
| 546 | elif c == -1: |
|---|
| 547 | self._p.palette(2) |
|---|
| 548 | self._p.set_line(label="Total Fit") |
|---|
| 549 | y = ma.masked_array(self.fitter.getfit(), |
|---|
| 550 | mask=logical_not(m)) |
|---|
| 551 | self._p.plot(self.x, y) |
|---|
| 552 | else: |
|---|
| 553 | self._p.palette(2) |
|---|
| 554 | self._p.set_line(label='Fit') |
|---|
| 555 | y = ma.masked_array(self.fitter.getfit(), |
|---|
| 556 | mask=logical_not(m)) |
|---|
| 557 | self._p.plot(self.x, y) |
|---|
| 558 | xlim=[min(self.x),max(self.x)] |
|---|
| 559 | self._p.axes.set_xlim(xlim) |
|---|
| 560 | self._p.set_axes('xlabel',xlab) |
|---|
| 561 | self._p.set_axes('ylabel',ylab) |
|---|
| 562 | self._p.set_axes('title',tlab) |
|---|
| 563 | self._p.release() |
|---|
| 564 | if (not rcParams['plotter.gui']): |
|---|
| 565 | self._p.save(filename) |
|---|
| 566 | print_log() |
|---|
| 567 | |
|---|
| 568 | def auto_fit(self, insitu=None, plot=False): |
|---|
| 569 | """ |
|---|
| 570 | Return a scan where the function is applied to all rows for |
|---|
| 571 | all Beams/IFs/Pols. |
|---|
| 572 | |
|---|
| 573 | """ |
|---|
| 574 | from asap import scantable |
|---|
| 575 | if not isinstance(self.data, scantable) : |
|---|
| 576 | msg = "Data is not a scantable" |
|---|
| 577 | if rcParams['verbose']: |
|---|
| 578 | print msg |
|---|
| 579 | return |
|---|
| 580 | else: |
|---|
| 581 | raise TypeError(msg) |
|---|
| 582 | if insitu is None: insitu = rcParams['insitu'] |
|---|
| 583 | if not insitu: |
|---|
| 584 | scan = self.data.copy() |
|---|
| 585 | else: |
|---|
| 586 | scan = self.data |
|---|
| 587 | rows = xrange(scan.nrow()) |
|---|
| 588 | from asap import asaplog |
|---|
| 589 | asaplog.push("Fitting:") |
|---|
| 590 | for r in rows: |
|---|
| 591 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),scan.getbeam(r),scan.getif(r),scan.getpol(r), scan.getcycle(r)) |
|---|
| 592 | asaplog.push(out, False) |
|---|
| 593 | self.x = scan._getabcissa(r) |
|---|
| 594 | self.y = scan._getspectrum(r) |
|---|
| 595 | self.data = None |
|---|
| 596 | self.fit() |
|---|
| 597 | x = self.get_parameters() |
|---|
| 598 | if plot: |
|---|
| 599 | self.plot(residual=True) |
|---|
| 600 | x = raw_input("Accept fit ([y]/n): ") |
|---|
| 601 | if x.upper() == 'N': |
|---|
| 602 | continue |
|---|
| 603 | scan._setspectrum(self.fitter.getresidual(), r) |
|---|
| 604 | if plot: |
|---|
| 605 | self._p.unmap() |
|---|
| 606 | self._p = None |
|---|
| 607 | print_log() |
|---|
| 608 | return scan |
|---|
| 609 | |
|---|
