| 1 | import _asap
|
|---|
| 2 |
|
|---|
| 3 | class fitter:
|
|---|
| 4 | """
|
|---|
| 5 | The fitting class for ASAP.
|
|---|
| 6 | """
|
|---|
| 7 | def _verbose(self, *args):
|
|---|
| 8 | """
|
|---|
| 9 | Set stdout output.
|
|---|
| 10 | """
|
|---|
| 11 | if type(args[0]) is bool:
|
|---|
| 12 | self._vb = args[0]
|
|---|
| 13 | return
|
|---|
| 14 | elif len(args) == 0:
|
|---|
| 15 | return self._vb
|
|---|
| 16 |
|
|---|
| 17 | def __init__(self):
|
|---|
| 18 | """
|
|---|
| 19 | Create a fitter object. No state is set.
|
|---|
| 20 | """
|
|---|
| 21 | self.fitter = _asap.fitter()
|
|---|
| 22 | self.x = None
|
|---|
| 23 | self.y = None
|
|---|
| 24 | self.mask = None
|
|---|
| 25 | self.fitfunc = None
|
|---|
| 26 | self.fitted = False
|
|---|
| 27 | self.data = None
|
|---|
| 28 | self._p = None
|
|---|
| 29 | self._vb = True
|
|---|
| 30 |
|
|---|
| 31 | def set_data(self, xdat, ydat, mask=None):
|
|---|
| 32 | """
|
|---|
| 33 | Set the absissa and ordinate for the fit. Also set the mask
|
|---|
| 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:
|
|---|
| 38 | xdat: the abcissa values
|
|---|
| 39 | ydat: the ordinate values
|
|---|
| 40 | mask: an optional mask
|
|---|
| 41 |
|
|---|
| 42 | """
|
|---|
| 43 | self.fitted = False
|
|---|
| 44 | self.x = xdat
|
|---|
| 45 | self.y = ydat
|
|---|
| 46 | if mask == None:
|
|---|
| 47 | from numarray import ones
|
|---|
| 48 | self.mask = ones(len(xdat))
|
|---|
| 49 | else:
|
|---|
| 50 | self.mask = mask
|
|---|
| 51 | return
|
|---|
| 52 |
|
|---|
| 53 | def set_scan(self, thescan=None, mask=None):
|
|---|
| 54 | """
|
|---|
| 55 | Set the 'data' (a scantable) of the fitter.
|
|---|
| 56 | Parameters:
|
|---|
| 57 | thescan: a scantable
|
|---|
| 58 | mask: a msk retireved from the scantable
|
|---|
| 59 | """
|
|---|
| 60 | if not thescan:
|
|---|
| 61 | print "Please give a correct scan"
|
|---|
| 62 | self.fitted = False
|
|---|
| 63 | self.data = thescan
|
|---|
| 64 | if mask is None:
|
|---|
| 65 | from numarray import ones
|
|---|
| 66 | self.mask = ones(self.data.nchan())
|
|---|
| 67 | else:
|
|---|
| 68 | self.mask = mask
|
|---|
| 69 | return
|
|---|
| 70 |
|
|---|
| 71 | def set_function(self, **kwargs):
|
|---|
| 72 | """
|
|---|
| 73 | Set the function to be fit.
|
|---|
| 74 | Parameters:
|
|---|
| 75 | poly: use a polynomial of the order given
|
|---|
| 76 | gauss: fit the number of gaussian specified
|
|---|
| 77 | Example:
|
|---|
| 78 | fitter.set_function(gauss=2) # will fit two gaussians
|
|---|
| 79 | fitter.set_function(poly=3) # will fit a 3rd order polynomial
|
|---|
| 80 | """
|
|---|
| 81 | #default poly order 0
|
|---|
| 82 | self.fitfunc = 'poly'
|
|---|
| 83 | n=0
|
|---|
| 84 | if kwargs.has_key('poly'):
|
|---|
| 85 | self.fitfunc = 'poly'
|
|---|
| 86 | n = kwargs.get('poly')
|
|---|
| 87 | elif kwargs.has_key('gauss'):
|
|---|
| 88 | n = kwargs.get('gauss')
|
|---|
| 89 | self.fitfunc = 'gauss'
|
|---|
| 90 |
|
|---|
| 91 | self.fitter.setexpression(self.fitfunc,n)
|
|---|
| 92 | return
|
|---|
| 93 |
|
|---|
| 94 | def fit(self):
|
|---|
| 95 | """
|
|---|
| 96 | Execute the actual fitting process. All the state has to be set.
|
|---|
| 97 | Parameters:
|
|---|
| 98 | none
|
|---|
| 99 | Example:
|
|---|
| 100 | s= scantable('myscan.asap')
|
|---|
| 101 | f = fitter()
|
|---|
| 102 | f.set_scan(s)
|
|---|
| 103 | f.set_function(poly=0)
|
|---|
| 104 | f.fit()
|
|---|
| 105 | """
|
|---|
| 106 | if ((self.x is None or self.y is None) and self.data is None) \
|
|---|
| 107 | or self.fitfunc is None:
|
|---|
| 108 | print "Fitter not yet initialised. Please set data & fit function"
|
|---|
| 109 | return
|
|---|
| 110 | else:
|
|---|
| 111 | if self.data is not None:
|
|---|
| 112 | self.x = self.data.getabcissa()
|
|---|
| 113 | self.y = self.data.getspectrum()
|
|---|
| 114 | print "Fitting:"
|
|---|
| 115 | vb = self.data._verbose
|
|---|
| 116 | self.data._verbose(True)
|
|---|
| 117 | s = self.data.get_selection()
|
|---|
| 118 | self.data._verbose(vb)
|
|---|
| 119 |
|
|---|
| 120 | self.fitter.setdata(self.x,self.y,self.mask)
|
|---|
| 121 | if self.fitfunc == 'gauss':
|
|---|
| 122 | ps = self.fitter.getparameters()
|
|---|
| 123 | if len(ps) == 0:
|
|---|
| 124 | self.fitter.estimate()
|
|---|
| 125 | self.fitter.fit()
|
|---|
| 126 | self.fitted = True
|
|---|
| 127 | return
|
|---|
| 128 |
|
|---|
| 129 | def set_parameters(self, params, fixed=None):
|
|---|
| 130 | self.fitter.setparameters(params)
|
|---|
| 131 | if fixed is not None:
|
|---|
| 132 | self.fitter.setfixedparameters(fixed)
|
|---|
| 133 | return
|
|---|
| 134 |
|
|---|
| 135 | def get_parameters(self):
|
|---|
| 136 | """
|
|---|
| 137 | Return the fit paramters.
|
|---|
| 138 |
|
|---|
| 139 | """
|
|---|
| 140 | if not self.fitted:
|
|---|
| 141 | print "Not yet fitted."
|
|---|
| 142 | pars = list(self.fitter.getparameters())
|
|---|
| 143 | fixed = list(self.fitter.getfixedparameters())
|
|---|
| 144 | if self._vb:
|
|---|
| 145 | print self._format_pars(pars)
|
|---|
| 146 | return pars,fixed
|
|---|
| 147 |
|
|---|
| 148 | def _format_pars(self, pars):
|
|---|
| 149 | out = ''
|
|---|
| 150 | if self.fitfunc == 'poly':
|
|---|
| 151 | c = 0
|
|---|
| 152 | for i in pars:
|
|---|
| 153 | out += ' p%d = %3.3f, ' % (c,i)
|
|---|
| 154 | c+=1
|
|---|
| 155 | elif self.fitfunc == 'gauss':
|
|---|
| 156 | i = 0
|
|---|
| 157 | c = 0
|
|---|
| 158 | unit = ''
|
|---|
| 159 | if self.data:
|
|---|
| 160 | unit = self.data.get_unit()
|
|---|
| 161 | while i < len(pars):
|
|---|
| 162 | out += ' %d: peak = %3.3f , centre = %3.3f %s, FWHM = %3.3f %s \n' % (c,pars[i],pars[i+1],unit,pars[i+2],unit)
|
|---|
| 163 | c+=1
|
|---|
| 164 | i+=3
|
|---|
| 165 | return out
|
|---|
| 166 |
|
|---|
| 167 | def get_estimate(self):
|
|---|
| 168 | """
|
|---|
| 169 | Return the paramter estimates (for non-linear functions).
|
|---|
| 170 | """
|
|---|
| 171 | pars = self.fitter.getestimate()
|
|---|
| 172 | if self._vb:
|
|---|
| 173 | print self._format_pars(pars)
|
|---|
| 174 | return pars
|
|---|
| 175 |
|
|---|
| 176 |
|
|---|
| 177 | def get_residual(self):
|
|---|
| 178 | """
|
|---|
| 179 | Return the residual of the fit.
|
|---|
| 180 | """
|
|---|
| 181 | if not self.fitted:
|
|---|
| 182 | print "Not yet fitted."
|
|---|
| 183 | return self.fitter.getresidual()
|
|---|
| 184 |
|
|---|
| 185 | def get_chi2(self):
|
|---|
| 186 | """
|
|---|
| 187 | Return chi^2.
|
|---|
| 188 | """
|
|---|
| 189 |
|
|---|
| 190 | if not self.fitted:
|
|---|
| 191 | print "Not yet fitted."
|
|---|
| 192 | ch2 = self.fitter.getchi2()
|
|---|
| 193 | if self._vb:
|
|---|
| 194 | print 'Chi^2 = %3.3f' % (ch2)
|
|---|
| 195 | return ch2
|
|---|
| 196 |
|
|---|
| 197 | def get_fit(self):
|
|---|
| 198 | """
|
|---|
| 199 | Return the fitted ordinate values.
|
|---|
| 200 | """
|
|---|
| 201 | if not self.fitted:
|
|---|
| 202 | print "Not yet fitted."
|
|---|
| 203 | return self.fitter.getfit()
|
|---|
| 204 |
|
|---|
| 205 | def commit(self):
|
|---|
| 206 | """
|
|---|
| 207 | Return a new scan where teh fits have been commited.
|
|---|
| 208 | """
|
|---|
| 209 | if not self.fitted:
|
|---|
| 210 | print "Not yet fitted."
|
|---|
| 211 | if self.data is not scantable:
|
|---|
| 212 | print "Only works with scantables"
|
|---|
| 213 | return
|
|---|
| 214 | scan = self.data.copy()
|
|---|
| 215 | scan.setspectrum(self.fitter.getresidual())
|
|---|
| 216 |
|
|---|
| 217 | def plot(self, residual=False):
|
|---|
| 218 | """
|
|---|
| 219 | Plot the last fit.
|
|---|
| 220 | Parameters:
|
|---|
| 221 | residual: an optional parameter indicating if the residual
|
|---|
| 222 | should be plotted (default 'False')
|
|---|
| 223 | """
|
|---|
| 224 | if not self.fitted:
|
|---|
| 225 | return
|
|---|
| 226 | if not self._p:
|
|---|
| 227 | from asap.asaplot import ASAPlot
|
|---|
| 228 | self._p = ASAPlot()
|
|---|
| 229 | if self._.is_dead:
|
|---|
| 230 | from asap.asaplot import ASAPlot
|
|---|
| 231 | self._p = ASAPlot()
|
|---|
| 232 | self._p.clear()
|
|---|
| 233 | tlab = 'Spectrum'
|
|---|
| 234 | xlab = 'Abcissa'
|
|---|
| 235 | if self.data:
|
|---|
| 236 | tlab = self.data._getsourcename(0)
|
|---|
| 237 | xlab = self.data.getabcissalabel(0)
|
|---|
| 238 | ylab = r'Flux'
|
|---|
| 239 | m = self.data.getmask(0)
|
|---|
| 240 | self._p.set_line(colour='blue',label='Spectrum')
|
|---|
| 241 | self._p.plot(self.x, self.y, m)
|
|---|
| 242 | if residual:
|
|---|
| 243 | self._p.set_line(colour='green',label='Residual')
|
|---|
| 244 | self._p.plot(self.x, self.get_residual(), m)
|
|---|
| 245 | self._p.set_line(colour='red',label='Fit')
|
|---|
| 246 | self._p.plot(self.x, self.get_fit(), m)
|
|---|
| 247 |
|
|---|
| 248 | self._p.set_axes('xlabel',xlab)
|
|---|
| 249 | self._p.set_axes('ylabel',ylab)
|
|---|
| 250 | self._p.set_axes('title',tlab)
|
|---|
| 251 | self._p.release()
|
|---|
| 252 |
|
|---|
| 253 |
|
|---|
| 254 | def auto_fit(self):
|
|---|
| 255 | """
|
|---|
| 256 | Return a scan where the function is applied to all rows for all Beams/IFs/Pols.
|
|---|
| 257 |
|
|---|
| 258 | """
|
|---|
| 259 | from asap import scantable
|
|---|
| 260 | if not isinstance(self.data,scantable) :
|
|---|
| 261 | print "Only works with scantables"
|
|---|
| 262 | return
|
|---|
| 263 | scan = self.data.copy()
|
|---|
| 264 | vb = scan._verbose
|
|---|
| 265 | scan._verbose(False)
|
|---|
| 266 | sel = scan.get_selection()
|
|---|
| 267 | rows = range(scan.nrow())
|
|---|
| 268 | for i in range(scan.nbeam()):
|
|---|
| 269 | scan.setbeam(i)
|
|---|
| 270 | for j in range(scan.nif()):
|
|---|
| 271 | scan.setif(j)
|
|---|
| 272 | for k in range(scan.npol()):
|
|---|
| 273 | scan.setpol(k)
|
|---|
| 274 | if self._vb:
|
|---|
| 275 | print "Fitting:"
|
|---|
| 276 | print 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k)
|
|---|
| 277 | for iRow in rows:
|
|---|
| 278 | self.x = scan.getabcissa(iRow)
|
|---|
| 279 | self.y = scan.getspectrum(iRow)
|
|---|
| 280 | self.data = None
|
|---|
| 281 | self.fit()
|
|---|
| 282 | x = self.get_parameters()
|
|---|
| 283 | scan.setspectrum(self.fitter.getresidual(),iRow)
|
|---|
| 284 | scan.set_selection(sel[0],sel[1],sel[2])
|
|---|
| 285 | scan._verbose(vb)
|
|---|
| 286 | return scan
|
|---|
