[113] | 1 | import _asap |
---|
[259] | 2 | from asap import rcParams |
---|
[723] | 3 | from asap import print_log |
---|
[1295] | 4 | from asap import _n_bools |
---|
[1603] | 5 | from asap import mask_and |
---|
[1614] | 6 | from asap import asaplog |
---|
[113] | 7 | |
---|
| 8 | class fitter: |
---|
| 9 | """ |
---|
| 10 | The fitting class for ASAP. |
---|
| 11 | """ |
---|
[723] | 12 | |
---|
[113] | 13 | def __init__(self): |
---|
| 14 | """ |
---|
| 15 | Create a fitter object. No state is set. |
---|
| 16 | """ |
---|
| 17 | self.fitter = _asap.fitter() |
---|
| 18 | self.x = None |
---|
| 19 | self.y = None |
---|
| 20 | self.mask = None |
---|
| 21 | self.fitfunc = None |
---|
[515] | 22 | self.fitfuncs = None |
---|
[113] | 23 | self.fitted = False |
---|
| 24 | self.data = None |
---|
[515] | 25 | self.components = 0 |
---|
| 26 | self._fittedrow = 0 |
---|
[113] | 27 | self._p = None |
---|
[515] | 28 | self._selection = None |
---|
[1389] | 29 | self.uselinear = False |
---|
[113] | 30 | |
---|
| 31 | def set_data(self, xdat, ydat, mask=None): |
---|
| 32 | """ |
---|
[158] | 33 | Set the absissa and ordinate for the fit. Also set the mask |
---|
[113] | 34 | indicationg valid points. |
---|
| 35 | This can be used for data vectors retrieved from a scantable. |
---|
| 36 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
---|
| 37 | Parameters: |
---|
[158] | 38 | xdat: the abcissa values |
---|
[113] | 39 | ydat: the ordinate values |
---|
| 40 | mask: an optional mask |
---|
[723] | 41 | |
---|
[113] | 42 | """ |
---|
| 43 | self.fitted = False |
---|
| 44 | self.x = xdat |
---|
| 45 | self.y = ydat |
---|
| 46 | if mask == None: |
---|
[1295] | 47 | self.mask = _n_bools(len(xdat), True) |
---|
[113] | 48 | else: |
---|
| 49 | self.mask = mask |
---|
| 50 | return |
---|
| 51 | |
---|
| 52 | def set_scan(self, thescan=None, mask=None): |
---|
| 53 | """ |
---|
| 54 | Set the 'data' (a scantable) of the fitter. |
---|
| 55 | Parameters: |
---|
| 56 | thescan: a scantable |
---|
[1603] | 57 | mask: a msk retrieved from the scantable |
---|
[113] | 58 | """ |
---|
| 59 | if not thescan: |
---|
[723] | 60 | msg = "Please give a correct scan" |
---|
| 61 | if rcParams['verbose']: |
---|
[1612] | 62 | #print msg |
---|
[1614] | 63 | asaplog.push(msg) |
---|
| 64 | print_log('ERROR') |
---|
[723] | 65 | return |
---|
| 66 | else: |
---|
| 67 | raise TypeError(msg) |
---|
[113] | 68 | self.fitted = False |
---|
| 69 | self.data = thescan |
---|
[1075] | 70 | self.mask = None |
---|
[113] | 71 | if mask is None: |
---|
[1295] | 72 | self.mask = _n_bools(self.data.nchan(), True) |
---|
[113] | 73 | else: |
---|
| 74 | self.mask = mask |
---|
| 75 | return |
---|
| 76 | |
---|
| 77 | def set_function(self, **kwargs): |
---|
| 78 | """ |
---|
| 79 | Set the function to be fit. |
---|
| 80 | Parameters: |
---|
[1389] | 81 | poly: use a polynomial of the order given with nonlinear least squares fit |
---|
| 82 | lpoly: use polynomial of the order given with linear least squares fit |
---|
[113] | 83 | gauss: fit the number of gaussian specified |
---|
| 84 | Example: |
---|
| 85 | fitter.set_function(gauss=2) # will fit two gaussians |
---|
[1389] | 86 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method |
---|
| 87 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method |
---|
[113] | 88 | """ |
---|
[723] | 89 | #default poly order 0 |
---|
[515] | 90 | n=0 |
---|
[113] | 91 | if kwargs.has_key('poly'): |
---|
| 92 | self.fitfunc = 'poly' |
---|
| 93 | n = kwargs.get('poly') |
---|
[515] | 94 | self.components = [n] |
---|
[1389] | 95 | self.uselinear = False |
---|
| 96 | elif kwargs.has_key('lpoly'): |
---|
| 97 | self.fitfunc = 'poly' |
---|
| 98 | n = kwargs.get('lpoly') |
---|
| 99 | self.components = [n] |
---|
| 100 | self.uselinear = True |
---|
[113] | 101 | elif kwargs.has_key('gauss'): |
---|
| 102 | n = kwargs.get('gauss') |
---|
| 103 | self.fitfunc = 'gauss' |
---|
[515] | 104 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
---|
| 105 | self.components = [ 3 for i in range(n) ] |
---|
[1389] | 106 | self.uselinear = False |
---|
[515] | 107 | else: |
---|
[723] | 108 | msg = "Invalid function type." |
---|
| 109 | if rcParams['verbose']: |
---|
[1612] | 110 | #print msg |
---|
[1614] | 111 | asaplog.push(msg) |
---|
| 112 | print_log('ERROR') |
---|
[723] | 113 | return |
---|
| 114 | else: |
---|
| 115 | raise TypeError(msg) |
---|
| 116 | |
---|
[113] | 117 | self.fitter.setexpression(self.fitfunc,n) |
---|
[1232] | 118 | self.fitted = False |
---|
[113] | 119 | return |
---|
[723] | 120 | |
---|
[1075] | 121 | def fit(self, row=0, estimate=False): |
---|
[113] | 122 | """ |
---|
| 123 | Execute the actual fitting process. All the state has to be set. |
---|
| 124 | Parameters: |
---|
[1075] | 125 | row: specify the row in the scantable |
---|
| 126 | estimate: auto-compute an initial parameter set (default False) |
---|
| 127 | This can be used to compute estimates even if fit was |
---|
| 128 | called before. |
---|
[113] | 129 | Example: |
---|
[515] | 130 | s = scantable('myscan.asap') |
---|
| 131 | s.set_cursor(thepol=1) # select second pol |
---|
[113] | 132 | f = fitter() |
---|
| 133 | f.set_scan(s) |
---|
| 134 | f.set_function(poly=0) |
---|
[723] | 135 | f.fit(row=0) # fit first row |
---|
[113] | 136 | """ |
---|
| 137 | if ((self.x is None or self.y is None) and self.data is None) \ |
---|
| 138 | or self.fitfunc is None: |
---|
[723] | 139 | msg = "Fitter not yet initialised. Please set data & fit function" |
---|
| 140 | if rcParams['verbose']: |
---|
[1612] | 141 | #print msg |
---|
[1614] | 142 | asaplog.push(msg) |
---|
| 143 | print_log('ERROR') |
---|
[723] | 144 | return |
---|
| 145 | else: |
---|
| 146 | raise RuntimeError(msg) |
---|
| 147 | |
---|
[113] | 148 | else: |
---|
| 149 | if self.data is not None: |
---|
[515] | 150 | self.x = self.data._getabcissa(row) |
---|
| 151 | self.y = self.data._getspectrum(row) |
---|
[1603] | 152 | self.mask = mask_and(self.mask, self.data._getmask(row)) |
---|
[723] | 153 | from asap import asaplog |
---|
| 154 | asaplog.push("Fitting:") |
---|
[943] | 155 | i = row |
---|
[1603] | 156 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i), |
---|
| 157 | self.data.getbeam(i), |
---|
| 158 | self.data.getif(i), |
---|
| 159 | self.data.getpol(i), |
---|
| 160 | self.data.getcycle(i)) |
---|
[1075] | 161 | asaplog.push(out,False) |
---|
[515] | 162 | self.fitter.setdata(self.x, self.y, self.mask) |
---|
[113] | 163 | if self.fitfunc == 'gauss': |
---|
| 164 | ps = self.fitter.getparameters() |
---|
[1075] | 165 | if len(ps) == 0 or estimate: |
---|
[113] | 166 | self.fitter.estimate() |
---|
[1628] | 167 | try: |
---|
| 168 | fxdpar = list(self.fitter.getfixedparameters()) |
---|
[1232] | 169 | if len(fxdpar) and fxdpar.count(0) == 0: |
---|
| 170 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
---|
[1389] | 171 | if self.uselinear: |
---|
| 172 | converged = self.fitter.lfit() |
---|
| 173 | else: |
---|
| 174 | converged = self.fitter.fit() |
---|
[1075] | 175 | if not converged: |
---|
| 176 | raise RuntimeError,"Fit didn't converge." |
---|
[626] | 177 | except RuntimeError, msg: |
---|
[723] | 178 | if rcParams['verbose']: |
---|
[1612] | 179 | #print msg |
---|
[1614] | 180 | print_log() |
---|
[1627] | 181 | asaplog.push(msg.message) |
---|
[1614] | 182 | print_log('ERROR') |
---|
[723] | 183 | else: |
---|
| 184 | raise |
---|
[515] | 185 | self._fittedrow = row |
---|
[113] | 186 | self.fitted = True |
---|
[723] | 187 | print_log() |
---|
[113] | 188 | return |
---|
| 189 | |
---|
[1232] | 190 | def store_fit(self, filename=None): |
---|
[526] | 191 | """ |
---|
[1232] | 192 | Save the fit parameters. |
---|
| 193 | Parameters: |
---|
| 194 | filename: if specified save as an ASCII file, if None (default) |
---|
| 195 | store it in the scnatable |
---|
[526] | 196 | """ |
---|
[515] | 197 | if self.fitted and self.data is not None: |
---|
| 198 | pars = list(self.fitter.getparameters()) |
---|
| 199 | fixed = list(self.fitter.getfixedparameters()) |
---|
[975] | 200 | from asap.asapfit import asapfit |
---|
| 201 | fit = asapfit() |
---|
| 202 | fit.setparameters(pars) |
---|
| 203 | fit.setfixedparameters(fixed) |
---|
| 204 | fit.setfunctions(self.fitfuncs) |
---|
| 205 | fit.setcomponents(self.components) |
---|
| 206 | fit.setframeinfo(self.data._getcoordinfo()) |
---|
[1232] | 207 | if filename is not None: |
---|
| 208 | import os |
---|
| 209 | filename = os.path.expandvars(os.path.expanduser(filename)) |
---|
| 210 | if os.path.exists(filename): |
---|
| 211 | raise IOError("File '%s' exists." % filename) |
---|
| 212 | fit.save(filename) |
---|
| 213 | else: |
---|
| 214 | self.data._addfit(fit,self._fittedrow) |
---|
[515] | 215 | |
---|
[1017] | 216 | #def set_parameters(self, params, fixed=None, component=None): |
---|
| 217 | def set_parameters(self,*args,**kwargs): |
---|
[526] | 218 | """ |
---|
| 219 | Set the parameters to be fitted. |
---|
| 220 | Parameters: |
---|
| 221 | params: a vector of parameters |
---|
| 222 | fixed: a vector of which parameters are to be held fixed |
---|
| 223 | (default is none) |
---|
| 224 | component: in case of multiple gaussians, the index of the |
---|
| 225 | component |
---|
[1017] | 226 | """ |
---|
| 227 | component = None |
---|
| 228 | fixed = None |
---|
| 229 | params = None |
---|
[1031] | 230 | |
---|
[1017] | 231 | if len(args) and isinstance(args[0],dict): |
---|
| 232 | kwargs = args[0] |
---|
| 233 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
---|
| 234 | if kwargs.has_key("params"): params = kwargs["params"] |
---|
| 235 | if len(args) == 2 and isinstance(args[1], int): |
---|
| 236 | component = args[1] |
---|
[515] | 237 | if self.fitfunc is None: |
---|
[723] | 238 | msg = "Please specify a fitting function first." |
---|
| 239 | if rcParams['verbose']: |
---|
[1612] | 240 | #print msg |
---|
[1614] | 241 | asaplog.push(msg) |
---|
| 242 | print_log('ERROR') |
---|
[723] | 243 | return |
---|
| 244 | else: |
---|
| 245 | raise RuntimeError(msg) |
---|
[515] | 246 | if self.fitfunc == "gauss" and component is not None: |
---|
[1017] | 247 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
---|
[1295] | 248 | pars = _n_bools(len(self.components)*3, False) |
---|
| 249 | fxd = _n_bools(len(pars), False) |
---|
[515] | 250 | else: |
---|
[723] | 251 | pars = list(self.fitter.getparameters()) |
---|
[515] | 252 | fxd = list(self.fitter.getfixedparameters()) |
---|
| 253 | i = 3*component |
---|
| 254 | pars[i:i+3] = params |
---|
| 255 | fxd[i:i+3] = fixed |
---|
| 256 | params = pars |
---|
[723] | 257 | fixed = fxd |
---|
[113] | 258 | self.fitter.setparameters(params) |
---|
| 259 | if fixed is not None: |
---|
| 260 | self.fitter.setfixedparameters(fixed) |
---|
[723] | 261 | print_log() |
---|
[113] | 262 | return |
---|
[515] | 263 | |
---|
[1217] | 264 | def set_gauss_parameters(self, peak, centre, fwhm, |
---|
[1603] | 265 | peakfixed=0, centrefixed=0, |
---|
[1217] | 266 | fwhmfixed=0, |
---|
[515] | 267 | component=0): |
---|
[113] | 268 | """ |
---|
[515] | 269 | Set the Parameters of a 'Gaussian' component, set with set_function. |
---|
| 270 | Parameters: |
---|
[1232] | 271 | peak, centre, fwhm: The gaussian parameters |
---|
[515] | 272 | peakfixed, |
---|
[1603] | 273 | centrefixed, |
---|
[1217] | 274 | fwhmfixed: Optional parameters to indicate if |
---|
[515] | 275 | the paramters should be held fixed during |
---|
| 276 | the fitting process. The default is to keep |
---|
| 277 | all parameters flexible. |
---|
[526] | 278 | component: The number of the component (Default is the |
---|
| 279 | component 0) |
---|
[515] | 280 | """ |
---|
| 281 | if self.fitfunc != "gauss": |
---|
[723] | 282 | msg = "Function only operates on Gaussian components." |
---|
| 283 | if rcParams['verbose']: |
---|
[1612] | 284 | #print msg |
---|
[1614] | 285 | asaplog.push(msg) |
---|
| 286 | print_log('ERROR') |
---|
[723] | 287 | return |
---|
| 288 | else: |
---|
| 289 | raise ValueError(msg) |
---|
[515] | 290 | if 0 <= component < len(self.components): |
---|
[1217] | 291 | d = {'params':[peak, centre, fwhm], |
---|
[1603] | 292 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
---|
[1017] | 293 | self.set_parameters(d, component) |
---|
[515] | 294 | else: |
---|
[723] | 295 | msg = "Please select a valid component." |
---|
| 296 | if rcParams['verbose']: |
---|
[1612] | 297 | #print msg |
---|
[1614] | 298 | asaplog.push(msg) |
---|
| 299 | print_log('ERROR') |
---|
[723] | 300 | return |
---|
| 301 | else: |
---|
| 302 | raise ValueError(msg) |
---|
| 303 | |
---|
[975] | 304 | def get_area(self, component=None): |
---|
| 305 | """ |
---|
| 306 | Return the area under the fitted gaussian component. |
---|
| 307 | Parameters: |
---|
| 308 | component: the gaussian component selection, |
---|
| 309 | default (None) is the sum of all components |
---|
| 310 | Note: |
---|
| 311 | This will only work for gaussian fits. |
---|
| 312 | """ |
---|
| 313 | if not self.fitted: return |
---|
| 314 | if self.fitfunc == "gauss": |
---|
| 315 | pars = list(self.fitter.getparameters()) |
---|
| 316 | from math import log,pi,sqrt |
---|
| 317 | fac = sqrt(pi/log(16.0)) |
---|
| 318 | areas = [] |
---|
| 319 | for i in range(len(self.components)): |
---|
| 320 | j = i*3 |
---|
| 321 | cpars = pars[j:j+3] |
---|
| 322 | areas.append(fac * cpars[0] * cpars[2]) |
---|
| 323 | else: |
---|
| 324 | return None |
---|
| 325 | if component is not None: |
---|
| 326 | return areas[component] |
---|
| 327 | else: |
---|
| 328 | return sum(areas) |
---|
| 329 | |
---|
[1075] | 330 | def get_errors(self, component=None): |
---|
[515] | 331 | """ |
---|
[1075] | 332 | Return the errors in the parameters. |
---|
| 333 | Parameters: |
---|
| 334 | component: get the errors for the specified component |
---|
| 335 | only, default is all components |
---|
| 336 | """ |
---|
| 337 | if not self.fitted: |
---|
| 338 | msg = "Not yet fitted." |
---|
| 339 | if rcParams['verbose']: |
---|
[1612] | 340 | #print msg |
---|
[1614] | 341 | asaplog.push(msg) |
---|
| 342 | print_log('ERROR') |
---|
[1075] | 343 | return |
---|
| 344 | else: |
---|
| 345 | raise RuntimeError(msg) |
---|
| 346 | errs = list(self.fitter.geterrors()) |
---|
| 347 | cerrs = errs |
---|
| 348 | if component is not None: |
---|
| 349 | if self.fitfunc == "gauss": |
---|
| 350 | i = 3*component |
---|
| 351 | if i < len(errs): |
---|
| 352 | cerrs = errs[i:i+3] |
---|
| 353 | return cerrs |
---|
| 354 | |
---|
| 355 | def get_parameters(self, component=None, errors=False): |
---|
| 356 | """ |
---|
[113] | 357 | Return the fit paramters. |
---|
[526] | 358 | Parameters: |
---|
| 359 | component: get the parameters for the specified component |
---|
| 360 | only, default is all components |
---|
[113] | 361 | """ |
---|
| 362 | if not self.fitted: |
---|
[723] | 363 | msg = "Not yet fitted." |
---|
| 364 | if rcParams['verbose']: |
---|
[1612] | 365 | #print msg |
---|
[1614] | 366 | asaplog.push(msg) |
---|
| 367 | print_log('ERROR') |
---|
[723] | 368 | return |
---|
| 369 | else: |
---|
| 370 | raise RuntimeError(msg) |
---|
[113] | 371 | pars = list(self.fitter.getparameters()) |
---|
| 372 | fixed = list(self.fitter.getfixedparameters()) |
---|
[1075] | 373 | errs = list(self.fitter.geterrors()) |
---|
[1039] | 374 | area = [] |
---|
[723] | 375 | if component is not None: |
---|
[515] | 376 | if self.fitfunc == "gauss": |
---|
| 377 | i = 3*component |
---|
| 378 | cpars = pars[i:i+3] |
---|
| 379 | cfixed = fixed[i:i+3] |
---|
[1075] | 380 | cerrs = errs[i:i+3] |
---|
[1039] | 381 | a = self.get_area(component) |
---|
| 382 | area = [a for i in range(3)] |
---|
[515] | 383 | else: |
---|
| 384 | cpars = pars |
---|
[723] | 385 | cfixed = fixed |
---|
[1075] | 386 | cerrs = errs |
---|
[515] | 387 | else: |
---|
| 388 | cpars = pars |
---|
| 389 | cfixed = fixed |
---|
[1075] | 390 | cerrs = errs |
---|
[1039] | 391 | if self.fitfunc == "gauss": |
---|
| 392 | for c in range(len(self.components)): |
---|
| 393 | a = self.get_area(c) |
---|
| 394 | area += [a for i in range(3)] |
---|
[1088] | 395 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
---|
[723] | 396 | if rcParams['verbose']: |
---|
[1612] | 397 | #print fpars |
---|
[1614] | 398 | asaplog.push(fpars) |
---|
| 399 | print_log() |
---|
[1075] | 400 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
---|
| 401 | 'errors':cerrs} |
---|
[723] | 402 | |
---|
[1075] | 403 | def _format_pars(self, pars, fixed, errors, area): |
---|
[113] | 404 | out = '' |
---|
| 405 | if self.fitfunc == 'poly': |
---|
| 406 | c = 0 |
---|
[515] | 407 | for i in range(len(pars)): |
---|
| 408 | fix = "" |
---|
[1232] | 409 | if len(fixed) and fixed[i]: fix = "(fixed)" |
---|
[1088] | 410 | if errors : |
---|
| 411 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i]) |
---|
| 412 | else: |
---|
| 413 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i]) |
---|
[113] | 414 | c+=1 |
---|
[515] | 415 | out = out[:-1] # remove trailing ',' |
---|
[113] | 416 | elif self.fitfunc == 'gauss': |
---|
| 417 | i = 0 |
---|
| 418 | c = 0 |
---|
[515] | 419 | aunit = '' |
---|
| 420 | ounit = '' |
---|
[113] | 421 | if self.data: |
---|
[515] | 422 | aunit = self.data.get_unit() |
---|
| 423 | ounit = self.data.get_fluxunit() |
---|
[113] | 424 | while i < len(pars): |
---|
[1039] | 425 | if len(area): |
---|
| 426 | 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) |
---|
[1017] | 427 | else: |
---|
| 428 | 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) |
---|
[113] | 429 | c+=1 |
---|
| 430 | i+=3 |
---|
| 431 | return out |
---|
[723] | 432 | |
---|
[113] | 433 | def get_estimate(self): |
---|
| 434 | """ |
---|
[515] | 435 | Return the parameter estimates (for non-linear functions). |
---|
[113] | 436 | """ |
---|
| 437 | pars = self.fitter.getestimate() |
---|
[943] | 438 | fixed = self.fitter.getfixedparameters() |
---|
[723] | 439 | if rcParams['verbose']: |
---|
[1612] | 440 | #print self._format_pars(pars,fixed,None) |
---|
[1614] | 441 | asaplog.push(self._format_pars(pars,fixed,None)) |
---|
| 442 | print_log() |
---|
[113] | 443 | return pars |
---|
| 444 | |
---|
| 445 | def get_residual(self): |
---|
| 446 | """ |
---|
| 447 | Return the residual of the fit. |
---|
| 448 | """ |
---|
| 449 | if not self.fitted: |
---|
[723] | 450 | msg = "Not yet fitted." |
---|
| 451 | if rcParams['verbose']: |
---|
[1612] | 452 | #print msg |
---|
[1614] | 453 | asaplog.push(msg) |
---|
| 454 | print_log('ERROR') |
---|
[723] | 455 | return |
---|
| 456 | else: |
---|
| 457 | raise RuntimeError(msg) |
---|
[113] | 458 | return self.fitter.getresidual() |
---|
| 459 | |
---|
| 460 | def get_chi2(self): |
---|
| 461 | """ |
---|
| 462 | Return chi^2. |
---|
| 463 | """ |
---|
| 464 | if not self.fitted: |
---|
[723] | 465 | msg = "Not yet fitted." |
---|
| 466 | if rcParams['verbose']: |
---|
[1612] | 467 | #print msg |
---|
[1614] | 468 | asaplog.push(msg) |
---|
| 469 | print_log('ERROR') |
---|
[723] | 470 | return |
---|
| 471 | else: |
---|
| 472 | raise RuntimeError(msg) |
---|
[113] | 473 | ch2 = self.fitter.getchi2() |
---|
[723] | 474 | if rcParams['verbose']: |
---|
[1612] | 475 | #print 'Chi^2 = %3.3f' % (ch2) |
---|
[1614] | 476 | asaplog.push( 'Chi^2 = %3.3f' % (ch2) ) |
---|
| 477 | print_log() |
---|
[723] | 478 | return ch2 |
---|
[113] | 479 | |
---|
| 480 | def get_fit(self): |
---|
| 481 | """ |
---|
| 482 | Return the fitted ordinate values. |
---|
| 483 | """ |
---|
| 484 | if not self.fitted: |
---|
[723] | 485 | msg = "Not yet fitted." |
---|
| 486 | if rcParams['verbose']: |
---|
[1612] | 487 | #print msg |
---|
[1614] | 488 | asaplog.push(msg) |
---|
| 489 | print_log('ERROR') |
---|
[723] | 490 | return |
---|
| 491 | else: |
---|
| 492 | raise RuntimeError(msg) |
---|
[113] | 493 | return self.fitter.getfit() |
---|
| 494 | |
---|
| 495 | def commit(self): |
---|
| 496 | """ |
---|
[526] | 497 | Return a new scan where the fits have been commited (subtracted) |
---|
[113] | 498 | """ |
---|
| 499 | if not self.fitted: |
---|
[723] | 500 | msg = "Not yet fitted." |
---|
| 501 | if rcParams['verbose']: |
---|
[1612] | 502 | #print msg |
---|
[1614] | 503 | asaplog.push(msg) |
---|
| 504 | print_log('ERROR') |
---|
[723] | 505 | return |
---|
| 506 | else: |
---|
| 507 | raise RuntimeError(msg) |
---|
[975] | 508 | from asap import scantable |
---|
| 509 | if not isinstance(self.data, scantable): |
---|
[723] | 510 | msg = "Not a scantable" |
---|
| 511 | if rcParams['verbose']: |
---|
[1612] | 512 | #print msg |
---|
[1614] | 513 | asaplog.push(msg) |
---|
| 514 | print_log('ERROR') |
---|
[723] | 515 | return |
---|
| 516 | else: |
---|
| 517 | raise TypeError(msg) |
---|
[113] | 518 | scan = self.data.copy() |
---|
[259] | 519 | scan._setspectrum(self.fitter.getresidual()) |
---|
[723] | 520 | print_log() |
---|
[1092] | 521 | return scan |
---|
[113] | 522 | |
---|
[723] | 523 | def plot(self, residual=False, components=None, plotparms=False, filename=None): |
---|
[113] | 524 | """ |
---|
| 525 | Plot the last fit. |
---|
| 526 | Parameters: |
---|
| 527 | residual: an optional parameter indicating if the residual |
---|
| 528 | should be plotted (default 'False') |
---|
[526] | 529 | components: a list of components to plot, e.g [0,1], |
---|
| 530 | -1 plots the total fit. Default is to only |
---|
| 531 | plot the total fit. |
---|
| 532 | plotparms: Inidicates if the parameter values should be present |
---|
| 533 | on the plot |
---|
[113] | 534 | """ |
---|
| 535 | if not self.fitted: |
---|
| 536 | return |
---|
[723] | 537 | if not self._p or self._p.is_dead: |
---|
| 538 | if rcParams['plotter.gui']: |
---|
| 539 | from asap.asaplotgui import asaplotgui as asaplot |
---|
| 540 | else: |
---|
| 541 | from asap.asaplot import asaplot |
---|
| 542 | self._p = asaplot() |
---|
| 543 | self._p.hold() |
---|
[113] | 544 | self._p.clear() |
---|
[515] | 545 | self._p.set_panels() |
---|
[652] | 546 | self._p.palette(0) |
---|
[113] | 547 | tlab = 'Spectrum' |
---|
[723] | 548 | xlab = 'Abcissa' |
---|
[1017] | 549 | ylab = 'Ordinate' |
---|
[1273] | 550 | from matplotlib.numerix import ma,logical_not,logical_and,array |
---|
| 551 | m = self.mask |
---|
[113] | 552 | if self.data: |
---|
[515] | 553 | tlab = self.data._getsourcename(self._fittedrow) |
---|
| 554 | xlab = self.data._getabcissalabel(self._fittedrow) |
---|
[1273] | 555 | m = logical_and(self.mask, |
---|
[1306] | 556 | array(self.data._getmask(self._fittedrow), |
---|
| 557 | copy=False)) |
---|
[1389] | 558 | |
---|
[626] | 559 | ylab = self.data._get_ordinate_label() |
---|
[515] | 560 | |
---|
[1075] | 561 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
---|
[1461] | 562 | nomask=True |
---|
| 563 | for i in range(len(m)): |
---|
| 564 | nomask = nomask and m[i] |
---|
| 565 | label0='Masked Region' |
---|
| 566 | label1='Spectrum' |
---|
| 567 | if ( nomask ): |
---|
| 568 | label0=label1 |
---|
| 569 | else: |
---|
| 570 | y = ma.masked_array( self.y, mask = m ) |
---|
| 571 | self._p.palette(1,colours) |
---|
| 572 | self._p.set_line( label = label1 ) |
---|
| 573 | self._p.plot( self.x, y ) |
---|
[652] | 574 | self._p.palette(0,colours) |
---|
[1461] | 575 | self._p.set_line(label=label0) |
---|
[1273] | 576 | y = ma.masked_array(self.y,mask=logical_not(m)) |
---|
[1088] | 577 | self._p.plot(self.x, y) |
---|
[113] | 578 | if residual: |
---|
[1461] | 579 | self._p.palette(7) |
---|
[515] | 580 | self._p.set_line(label='Residual') |
---|
[1116] | 581 | y = ma.masked_array(self.get_residual(), |
---|
[1273] | 582 | mask=logical_not(m)) |
---|
[1088] | 583 | self._p.plot(self.x, y) |
---|
[652] | 584 | self._p.palette(2) |
---|
[515] | 585 | if components is not None: |
---|
| 586 | cs = components |
---|
| 587 | if isinstance(components,int): cs = [components] |
---|
[526] | 588 | if plotparms: |
---|
[1031] | 589 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
---|
[515] | 590 | n = len(self.components) |
---|
[652] | 591 | self._p.palette(3) |
---|
[515] | 592 | for c in cs: |
---|
| 593 | if 0 <= c < n: |
---|
| 594 | lab = self.fitfuncs[c]+str(c) |
---|
| 595 | self._p.set_line(label=lab) |
---|
[1116] | 596 | y = ma.masked_array(self.fitter.evaluate(c), |
---|
[1273] | 597 | mask=logical_not(m)) |
---|
[1088] | 598 | |
---|
| 599 | self._p.plot(self.x, y) |
---|
[515] | 600 | elif c == -1: |
---|
[652] | 601 | self._p.palette(2) |
---|
[515] | 602 | self._p.set_line(label="Total Fit") |
---|
[1116] | 603 | y = ma.masked_array(self.fitter.getfit(), |
---|
[1273] | 604 | mask=logical_not(m)) |
---|
[1088] | 605 | self._p.plot(self.x, y) |
---|
[515] | 606 | else: |
---|
[652] | 607 | self._p.palette(2) |
---|
[515] | 608 | self._p.set_line(label='Fit') |
---|
[1116] | 609 | y = ma.masked_array(self.fitter.getfit(), |
---|
[1273] | 610 | mask=logical_not(m)) |
---|
[1088] | 611 | self._p.plot(self.x, y) |
---|
[723] | 612 | xlim=[min(self.x),max(self.x)] |
---|
| 613 | self._p.axes.set_xlim(xlim) |
---|
[113] | 614 | self._p.set_axes('xlabel',xlab) |
---|
| 615 | self._p.set_axes('ylabel',ylab) |
---|
| 616 | self._p.set_axes('title',tlab) |
---|
| 617 | self._p.release() |
---|
[723] | 618 | if (not rcParams['plotter.gui']): |
---|
| 619 | self._p.save(filename) |
---|
| 620 | print_log() |
---|
[113] | 621 | |
---|
[1061] | 622 | def auto_fit(self, insitu=None, plot=False): |
---|
[113] | 623 | """ |
---|
[515] | 624 | Return a scan where the function is applied to all rows for |
---|
| 625 | all Beams/IFs/Pols. |
---|
[723] | 626 | |
---|
[113] | 627 | """ |
---|
| 628 | from asap import scantable |
---|
[515] | 629 | if not isinstance(self.data, scantable) : |
---|
[723] | 630 | msg = "Data is not a scantable" |
---|
| 631 | if rcParams['verbose']: |
---|
[1612] | 632 | #print msg |
---|
[1614] | 633 | asaplog.push(msg) |
---|
| 634 | print_log('ERROR') |
---|
[723] | 635 | return |
---|
| 636 | else: |
---|
| 637 | raise TypeError(msg) |
---|
[259] | 638 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 639 | if not insitu: |
---|
| 640 | scan = self.data.copy() |
---|
| 641 | else: |
---|
| 642 | scan = self.data |
---|
[880] | 643 | rows = xrange(scan.nrow()) |
---|
[1446] | 644 | # Save parameters of baseline fits as a class attribute. |
---|
| 645 | # NOTICE: This does not reflect changes in scantable! |
---|
| 646 | if len(rows) > 0: self.blpars=[] |
---|
[723] | 647 | from asap import asaplog |
---|
[876] | 648 | asaplog.push("Fitting:") |
---|
| 649 | for r in rows: |
---|
[1603] | 650 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r), |
---|
| 651 | scan.getbeam(r), |
---|
| 652 | scan.getif(r), |
---|
| 653 | scan.getpol(r), |
---|
| 654 | scan.getcycle(r)) |
---|
[880] | 655 | asaplog.push(out, False) |
---|
[876] | 656 | self.x = scan._getabcissa(r) |
---|
| 657 | self.y = scan._getspectrum(r) |
---|
[1603] | 658 | self.mask = mask_and(self.mask, scan._getmask(r)) |
---|
[876] | 659 | self.data = None |
---|
| 660 | self.fit() |
---|
[1603] | 661 | x = self.get_parameters() |
---|
[1446] | 662 | fpar = self.get_parameters() |
---|
[1061] | 663 | if plot: |
---|
| 664 | self.plot(residual=True) |
---|
| 665 | x = raw_input("Accept fit ([y]/n): ") |
---|
| 666 | if x.upper() == 'N': |
---|
[1446] | 667 | self.blpars.append(None) |
---|
[1061] | 668 | continue |
---|
[880] | 669 | scan._setspectrum(self.fitter.getresidual(), r) |
---|
[1446] | 670 | self.blpars.append(fpar) |
---|
[1061] | 671 | if plot: |
---|
| 672 | self._p.unmap() |
---|
| 673 | self._p = None |
---|
[876] | 674 | print_log() |
---|
| 675 | return scan |
---|
[794] | 676 | |
---|