| [113] | 1 | import _asap
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| [259] | 2 | from asap import rcParams
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| [723] | 3 | from asap import print_log
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| [1134] | 4 | from asap import NUM
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| [113] | 5 |
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| 6 | class fitter:
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| 7 | """
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| 8 | The fitting class for ASAP.
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| 9 | """
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| [723] | 10 |
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| [113] | 11 | def __init__(self):
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| 12 | """
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| 13 | Create a fitter object. No state is set.
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| 14 | """
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| 15 | self.fitter = _asap.fitter()
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| 16 | self.x = None
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| 17 | self.y = None
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| 18 | self.mask = None
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| 19 | self.fitfunc = None
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| [515] | 20 | self.fitfuncs = None
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| [113] | 21 | self.fitted = False
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| 22 | self.data = None
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| [515] | 23 | self.components = 0
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| 24 | self._fittedrow = 0
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| [113] | 25 | self._p = None
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| [515] | 26 | self._selection = None
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| [113] | 27 |
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| 28 | def set_data(self, xdat, ydat, mask=None):
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| 29 | """
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| [158] | 30 | Set the absissa and ordinate for the fit. Also set the mask
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| [113] | 31 | indicationg valid points.
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| 32 | This can be used for data vectors retrieved from a scantable.
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| 33 | For scantable fitting use 'fitter.set_scan(scan, mask)'.
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| 34 | Parameters:
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| [158] | 35 | xdat: the abcissa values
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| [113] | 36 | ydat: the ordinate values
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| 37 | mask: an optional mask
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| [723] | 38 |
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| [113] | 39 | """
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| 40 | self.fitted = False
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| 41 | self.x = xdat
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| 42 | self.y = ydat
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| 43 | if mask == None:
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| [1134] | 44 | self.mask = NUM.ones(len(xdat))
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| [113] | 45 | else:
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| 46 | self.mask = mask
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| 47 | return
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| 48 |
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| 49 | def set_scan(self, thescan=None, mask=None):
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| 50 | """
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| 51 | Set the 'data' (a scantable) of the fitter.
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| 52 | Parameters:
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| 53 | thescan: a scantable
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| 54 | mask: a msk retireved from the scantable
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| 55 | """
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| 56 | if not thescan:
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| [723] | 57 | msg = "Please give a correct scan"
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| 58 | if rcParams['verbose']:
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| 59 | print msg
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| 60 | return
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| 61 | else:
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| 62 | raise TypeError(msg)
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| [113] | 63 | self.fitted = False
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| 64 | self.data = thescan
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| [1075] | 65 | self.mask = None
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| [113] | 66 | if mask is None:
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| [1134] | 67 | self.mask = NUM.ones(self.data.nchan())
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| [113] | 68 | else:
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| 69 | self.mask = mask
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| 70 | return
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| 71 |
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| 72 | def set_function(self, **kwargs):
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| 73 | """
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| 74 | Set the function to be fit.
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| 75 | Parameters:
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| 76 | poly: use a polynomial of the order given
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| 77 | gauss: fit the number of gaussian specified
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| 78 | Example:
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| 79 | fitter.set_function(gauss=2) # will fit two gaussians
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| 80 | fitter.set_function(poly=3) # will fit a 3rd order polynomial
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| 81 | """
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| [723] | 82 | #default poly order 0
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| [515] | 83 | n=0
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| [113] | 84 | if kwargs.has_key('poly'):
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| 85 | self.fitfunc = 'poly'
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| 86 | n = kwargs.get('poly')
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| [515] | 87 | self.components = [n]
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| [113] | 88 | elif kwargs.has_key('gauss'):
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| 89 | n = kwargs.get('gauss')
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| 90 | self.fitfunc = 'gauss'
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| [515] | 91 | self.fitfuncs = [ 'gauss' for i in range(n) ]
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| 92 | self.components = [ 3 for i in range(n) ]
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| 93 | else:
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| [723] | 94 | msg = "Invalid function type."
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| 95 | if rcParams['verbose']:
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| 96 | print msg
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| 97 | return
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| 98 | else:
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| 99 | raise TypeError(msg)
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| 100 |
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| [113] | 101 | self.fitter.setexpression(self.fitfunc,n)
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| 102 | return
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| [723] | 103 |
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| [1075] | 104 | def fit(self, row=0, estimate=False):
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| [113] | 105 | """
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| 106 | Execute the actual fitting process. All the state has to be set.
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| 107 | Parameters:
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| [1075] | 108 | row: specify the row in the scantable
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| 109 | estimate: auto-compute an initial parameter set (default False)
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| 110 | This can be used to compute estimates even if fit was
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| 111 | called before.
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| [113] | 112 | Example:
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| [515] | 113 | s = scantable('myscan.asap')
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| 114 | s.set_cursor(thepol=1) # select second pol
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| [113] | 115 | f = fitter()
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| 116 | f.set_scan(s)
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| 117 | f.set_function(poly=0)
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| [723] | 118 | f.fit(row=0) # fit first row
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| [113] | 119 | """
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| 120 | if ((self.x is None or self.y is None) and self.data is None) \
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| 121 | or self.fitfunc is None:
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| [723] | 122 | msg = "Fitter not yet initialised. Please set data & fit function"
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| 123 | if rcParams['verbose']:
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| 124 | print msg
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| 125 | return
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| 126 | else:
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| 127 | raise RuntimeError(msg)
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| 128 |
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| [113] | 129 | else:
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| 130 | if self.data is not None:
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| [515] | 131 | self.x = self.data._getabcissa(row)
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| 132 | self.y = self.data._getspectrum(row)
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| [723] | 133 | from asap import asaplog
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| 134 | asaplog.push("Fitting:")
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| [943] | 135 | i = row
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| 136 | 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))
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| [1075] | 137 | asaplog.push(out,False)
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| [515] | 138 | self.fitter.setdata(self.x, self.y, self.mask)
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| [113] | 139 | if self.fitfunc == 'gauss':
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| 140 | ps = self.fitter.getparameters()
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| [1075] | 141 | if len(ps) == 0 or estimate:
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| [113] | 142 | self.fitter.estimate()
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| [626] | 143 | try:
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| [1075] | 144 | converged = self.fitter.fit()
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| 145 | if not converged:
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| 146 | raise RuntimeError,"Fit didn't converge."
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| [626] | 147 | except RuntimeError, msg:
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| [723] | 148 | if rcParams['verbose']:
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| 149 | print msg
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| 150 | else:
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| 151 | raise
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| [515] | 152 | self._fittedrow = row
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| [113] | 153 | self.fitted = True
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| [723] | 154 | print_log()
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| [113] | 155 | return
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| 156 |
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| [515] | 157 | def store_fit(self):
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| [526] | 158 | """
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| 159 | Store the fit parameters in the scantable.
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| 160 | """
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| [515] | 161 | if self.fitted and self.data is not None:
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| 162 | pars = list(self.fitter.getparameters())
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| 163 | fixed = list(self.fitter.getfixedparameters())
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| [975] | 164 | from asap.asapfit import asapfit
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| 165 | fit = asapfit()
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| 166 | fit.setparameters(pars)
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| 167 | fit.setfixedparameters(fixed)
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| 168 | fit.setfunctions(self.fitfuncs)
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| 169 | fit.setcomponents(self.components)
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| 170 | fit.setframeinfo(self.data._getcoordinfo())
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| 171 | self.data._addfit(fit,self._fittedrow)
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| [515] | 172 |
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| [1017] | 173 | #def set_parameters(self, params, fixed=None, component=None):
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| 174 | def set_parameters(self,*args,**kwargs):
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| [526] | 175 | """
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| 176 | Set the parameters to be fitted.
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| 177 | Parameters:
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| 178 | params: a vector of parameters
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| 179 | fixed: a vector of which parameters are to be held fixed
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| 180 | (default is none)
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| 181 | component: in case of multiple gaussians, the index of the
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| 182 | component
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| [1017] | 183 | """
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| 184 | component = None
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| 185 | fixed = None
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| 186 | params = None
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| [1031] | 187 |
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| [1017] | 188 | if len(args) and isinstance(args[0],dict):
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| 189 | kwargs = args[0]
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| 190 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
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| 191 | if kwargs.has_key("params"): params = kwargs["params"]
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| 192 | if len(args) == 2 and isinstance(args[1], int):
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| 193 | component = args[1]
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| [515] | 194 | if self.fitfunc is None:
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| [723] | 195 | msg = "Please specify a fitting function first."
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| 196 | if rcParams['verbose']:
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| 197 | print msg
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| 198 | return
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| 199 | else:
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| 200 | raise RuntimeError(msg)
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| [515] | 201 | if self.fitfunc == "gauss" and component is not None:
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| [1017] | 202 | if not self.fitted and sum(self.fitter.getparameters()) == 0:
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| [1134] | 203 | pars = list(NUM.zeros(len(self.components)*3))
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| 204 | fxd = list(NUM.zeros(len(pars)))
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| [515] | 205 | else:
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| [723] | 206 | pars = list(self.fitter.getparameters())
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| [515] | 207 | fxd = list(self.fitter.getfixedparameters())
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| 208 | i = 3*component
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| 209 | pars[i:i+3] = params
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| 210 | fxd[i:i+3] = fixed
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| 211 | params = pars
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| [723] | 212 | fixed = fxd
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| [113] | 213 | self.fitter.setparameters(params)
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| 214 | if fixed is not None:
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| 215 | self.fitter.setfixedparameters(fixed)
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| [723] | 216 | print_log()
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| [113] | 217 | return
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| [515] | 218 |
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| 219 | def set_gauss_parameters(self, peak, centre, fhwm,
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| [1017] | 220 | peakfixed=0, centerfixed=0,
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| 221 | fhwmfixed=0,
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| [515] | 222 | component=0):
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| [113] | 223 | """
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| [515] | 224 | Set the Parameters of a 'Gaussian' component, set with set_function.
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| 225 | Parameters:
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| 226 | peak, centre, fhwm: The gaussian parameters
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| 227 | peakfixed,
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| 228 | centerfixed,
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| 229 | fhwmfixed: Optional parameters to indicate if
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| 230 | the paramters should be held fixed during
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| 231 | the fitting process. The default is to keep
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| 232 | all parameters flexible.
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| [526] | 233 | component: The number of the component (Default is the
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| 234 | component 0)
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| [515] | 235 | """
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| 236 | if self.fitfunc != "gauss":
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| [723] | 237 | msg = "Function only operates on Gaussian components."
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| 238 | if rcParams['verbose']:
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| 239 | print msg
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| 240 | return
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| 241 | else:
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| 242 | raise ValueError(msg)
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| [515] | 243 | if 0 <= component < len(self.components):
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| [1017] | 244 | d = {'params':[peak, centre, fhwm],
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| 245 | 'fixed':[peakfixed, centerfixed, fhwmfixed]}
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| 246 | self.set_parameters(d, component)
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| [515] | 247 | else:
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| [723] | 248 | msg = "Please select a valid component."
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| 249 | if rcParams['verbose']:
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| 250 | print msg
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| 251 | return
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| 252 | else:
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| 253 | raise ValueError(msg)
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| 254 |
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| [975] | 255 | def get_area(self, component=None):
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| 256 | """
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| 257 | Return the area under the fitted gaussian component.
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| 258 | Parameters:
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| 259 | component: the gaussian component selection,
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| 260 | default (None) is the sum of all components
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| 261 | Note:
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| 262 | This will only work for gaussian fits.
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| 263 | """
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| 264 | if not self.fitted: return
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| 265 | if self.fitfunc == "gauss":
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| 266 | pars = list(self.fitter.getparameters())
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| 267 | from math import log,pi,sqrt
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| 268 | fac = sqrt(pi/log(16.0))
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| 269 | areas = []
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| 270 | for i in range(len(self.components)):
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| 271 | j = i*3
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| 272 | cpars = pars[j:j+3]
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| 273 | areas.append(fac * cpars[0] * cpars[2])
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| 274 | else:
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| 275 | return None
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| 276 | if component is not None:
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| 277 | return areas[component]
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| 278 | else:
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| 279 | return sum(areas)
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| 280 |
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| [1075] | 281 | def get_errors(self, component=None):
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| [515] | 282 | """
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| [1075] | 283 | Return the errors in the parameters.
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| 284 | Parameters:
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| 285 | component: get the errors for the specified component
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| 286 | only, default is all components
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| 287 | """
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| 288 | if not self.fitted:
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| 289 | msg = "Not yet fitted."
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| 290 | if rcParams['verbose']:
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| 291 | print msg
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| 292 | return
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| 293 | else:
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| 294 | raise RuntimeError(msg)
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| 295 | errs = list(self.fitter.geterrors())
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| 296 | cerrs = errs
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| 297 | if component is not None:
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| 298 | if self.fitfunc == "gauss":
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| 299 | i = 3*component
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| 300 | if i < len(errs):
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| 301 | cerrs = errs[i:i+3]
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| 302 | return cerrs
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| 303 |
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| 304 | def get_parameters(self, component=None, errors=False):
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| 305 | """
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| [113] | 306 | Return the fit paramters.
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| [526] | 307 | Parameters:
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| 308 | component: get the parameters for the specified component
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| 309 | only, default is all components
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| [113] | 310 | """
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| 311 | if not self.fitted:
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| [723] | 312 | msg = "Not yet fitted."
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| 313 | if rcParams['verbose']:
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| 314 | print msg
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| 315 | return
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| 316 | else:
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| 317 | raise RuntimeError(msg)
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| [113] | 318 | pars = list(self.fitter.getparameters())
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| 319 | fixed = list(self.fitter.getfixedparameters())
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| [1075] | 320 | errs = list(self.fitter.geterrors())
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| [1039] | 321 | area = []
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| [723] | 322 | if component is not None:
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| [515] | 323 | if self.fitfunc == "gauss":
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| 324 | i = 3*component
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| 325 | cpars = pars[i:i+3]
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| 326 | cfixed = fixed[i:i+3]
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| [1075] | 327 | cerrs = errs[i:i+3]
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| [1039] | 328 | a = self.get_area(component)
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| 329 | area = [a for i in range(3)]
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| [515] | 330 | else:
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| 331 | cpars = pars
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| [723] | 332 | cfixed = fixed
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| [1075] | 333 | cerrs = errs
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| [515] | 334 | else:
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| 335 | cpars = pars
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| 336 | cfixed = fixed
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| [1075] | 337 | cerrs = errs
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| [1039] | 338 | if self.fitfunc == "gauss":
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| 339 | for c in range(len(self.components)):
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| 340 | a = self.get_area(c)
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| 341 | area += [a for i in range(3)]
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| [1088] | 342 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
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| [723] | 343 | if rcParams['verbose']:
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| [515] | 344 | print fpars
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| [1075] | 345 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
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| 346 | 'errors':cerrs}
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| [723] | 347 |
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| [1075] | 348 | def _format_pars(self, pars, fixed, errors, area):
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| [113] | 349 | out = ''
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| 350 | if self.fitfunc == 'poly':
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| 351 | c = 0
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| [515] | 352 | for i in range(len(pars)):
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| 353 | fix = ""
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| 354 | if fixed[i]: fix = "(fixed)"
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| [1088] | 355 | if errors :
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| 356 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])
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| 357 | else:
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| 358 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
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| [113] | 359 | c+=1
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| [515] | 360 | out = out[:-1] # remove trailing ','
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| [113] | 361 | elif self.fitfunc == 'gauss':
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| 362 | i = 0
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| 363 | c = 0
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| [515] | 364 | aunit = ''
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| 365 | ounit = ''
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| [113] | 366 | if self.data:
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| [515] | 367 | aunit = self.data.get_unit()
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| 368 | ounit = self.data.get_fluxunit()
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| [113] | 369 | while i < len(pars):
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| [1039] | 370 | if len(area):
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| 371 | 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)
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| [1017] | 372 | else:
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| 373 | 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)
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| [113] | 374 | c+=1
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| 375 | i+=3
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| 376 | return out
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| [723] | 377 |
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| [113] | 378 | def get_estimate(self):
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| 379 | """
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| [515] | 380 | Return the parameter estimates (for non-linear functions).
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| [113] | 381 | """
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| 382 | pars = self.fitter.getestimate()
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| [943] | 383 | fixed = self.fitter.getfixedparameters()
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| [723] | 384 | if rcParams['verbose']:
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| [1017] | 385 | print self._format_pars(pars,fixed,None)
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| [113] | 386 | return pars
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| 387 |
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| 388 | def get_residual(self):
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| 389 | """
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| 390 | Return the residual of the fit.
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| 391 | """
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| 392 | if not self.fitted:
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| [723] | 393 | msg = "Not yet fitted."
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| 394 | if rcParams['verbose']:
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| 395 | print msg
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| 396 | return
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| 397 | else:
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| 398 | raise RuntimeError(msg)
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| [113] | 399 | return self.fitter.getresidual()
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| 400 |
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| 401 | def get_chi2(self):
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| 402 | """
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| 403 | Return chi^2.
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| 404 | """
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| 405 | if not self.fitted:
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| [723] | 406 | msg = "Not yet fitted."
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| 407 | if rcParams['verbose']:
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| 408 | print msg
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| 409 | return
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| 410 | else:
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| 411 | raise RuntimeError(msg)
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| [113] | 412 | ch2 = self.fitter.getchi2()
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| [723] | 413 | if rcParams['verbose']:
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| [113] | 414 | print 'Chi^2 = %3.3f' % (ch2)
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| [723] | 415 | return ch2
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| [113] | 416 |
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| 417 | def get_fit(self):
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| 418 | """
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| 419 | Return the fitted ordinate values.
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| 420 | """
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| 421 | if not self.fitted:
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| [723] | 422 | msg = "Not yet fitted."
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| 423 | if rcParams['verbose']:
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| 424 | print msg
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| 425 | return
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| 426 | else:
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| 427 | raise RuntimeError(msg)
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| [113] | 428 | return self.fitter.getfit()
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| 429 |
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| 430 | def commit(self):
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| 431 | """
|
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| [526] | 432 | Return a new scan where the fits have been commited (subtracted)
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| [113] | 433 | """
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| 434 | if not self.fitted:
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| [723] | 435 | msg = "Not yet fitted."
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| 436 | if rcParams['verbose']:
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| 437 | print msg
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| 438 | return
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| 439 | else:
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| 440 | raise RuntimeError(msg)
|
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| [975] | 441 | from asap import scantable
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| 442 | if not isinstance(self.data, scantable):
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| [723] | 443 | msg = "Not a scantable"
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| 444 | if rcParams['verbose']:
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| 445 | print msg
|
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| 446 | return
|
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| 447 | else:
|
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| 448 | raise TypeError(msg)
|
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| [113] | 449 | scan = self.data.copy()
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| [259] | 450 | scan._setspectrum(self.fitter.getresidual())
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| [723] | 451 | print_log()
|
|---|
| [1092] | 452 | return scan
|
|---|
| [113] | 453 |
|
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| [723] | 454 | def plot(self, residual=False, components=None, plotparms=False, filename=None):
|
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| [113] | 455 | """
|
|---|
| 456 | Plot the last fit.
|
|---|
| 457 | Parameters:
|
|---|
| 458 | residual: an optional parameter indicating if the residual
|
|---|
| 459 | should be plotted (default 'False')
|
|---|
| [526] | 460 | components: a list of components to plot, e.g [0,1],
|
|---|
| 461 | -1 plots the total fit. Default is to only
|
|---|
| 462 | plot the total fit.
|
|---|
| 463 | plotparms: Inidicates if the parameter values should be present
|
|---|
| 464 | on the plot
|
|---|
| [113] | 465 | """
|
|---|
| 466 | if not self.fitted:
|
|---|
| 467 | return
|
|---|
| [723] | 468 | if not self._p or self._p.is_dead:
|
|---|
| 469 | if rcParams['plotter.gui']:
|
|---|
| 470 | from asap.asaplotgui import asaplotgui as asaplot
|
|---|
| 471 | else:
|
|---|
| 472 | from asap.asaplot import asaplot
|
|---|
| 473 | self._p = asaplot()
|
|---|
| 474 | self._p.hold()
|
|---|
| [113] | 475 | self._p.clear()
|
|---|
| [515] | 476 | self._p.set_panels()
|
|---|
| [652] | 477 | self._p.palette(0)
|
|---|
| [113] | 478 | tlab = 'Spectrum'
|
|---|
| [723] | 479 | xlab = 'Abcissa'
|
|---|
| [1017] | 480 | ylab = 'Ordinate'
|
|---|
| 481 | m = None
|
|---|
| [113] | 482 | if self.data:
|
|---|
| [515] | 483 | tlab = self.data._getsourcename(self._fittedrow)
|
|---|
| 484 | xlab = self.data._getabcissalabel(self._fittedrow)
|
|---|
| 485 | m = self.data._getmask(self._fittedrow)
|
|---|
| [626] | 486 | ylab = self.data._get_ordinate_label()
|
|---|
| [515] | 487 |
|
|---|
| [1075] | 488 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
|
|---|
| [652] | 489 | self._p.palette(0,colours)
|
|---|
| [515] | 490 | self._p.set_line(label='Spectrum')
|
|---|
| [1088] | 491 | from matplotlib.numerix import ma,logical_not,array
|
|---|
| [1116] | 492 | y = ma.masked_array(self.y,mask=logical_not(array(m,copy=False)))
|
|---|
| [1088] | 493 | self._p.plot(self.x, y)
|
|---|
| [113] | 494 | if residual:
|
|---|
| [652] | 495 | self._p.palette(1)
|
|---|
| [515] | 496 | self._p.set_line(label='Residual')
|
|---|
| [1116] | 497 | y = ma.masked_array(self.get_residual(),
|
|---|
| 498 | mask=logical_not(array(m,copy=False)))
|
|---|
| [1088] | 499 | self._p.plot(self.x, y)
|
|---|
| [652] | 500 | self._p.palette(2)
|
|---|
| [515] | 501 | if components is not None:
|
|---|
| 502 | cs = components
|
|---|
| 503 | if isinstance(components,int): cs = [components]
|
|---|
| [526] | 504 | if plotparms:
|
|---|
| [1031] | 505 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
|
|---|
| [515] | 506 | n = len(self.components)
|
|---|
| [652] | 507 | self._p.palette(3)
|
|---|
| [515] | 508 | for c in cs:
|
|---|
| 509 | if 0 <= c < n:
|
|---|
| 510 | lab = self.fitfuncs[c]+str(c)
|
|---|
| 511 | self._p.set_line(label=lab)
|
|---|
| [1116] | 512 | y = ma.masked_array(self.fitter.evaluate(c),
|
|---|
| 513 | mask=logical_not(array(m,copy=False)))
|
|---|
| [1088] | 514 |
|
|---|
| 515 | self._p.plot(self.x, y)
|
|---|
| [515] | 516 | elif c == -1:
|
|---|
| [652] | 517 | self._p.palette(2)
|
|---|
| [515] | 518 | self._p.set_line(label="Total Fit")
|
|---|
| [1116] | 519 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| 520 | mask=logical_not(array(m,copy=False)))
|
|---|
| [1088] | 521 | self._p.plot(self.x, y)
|
|---|
| [515] | 522 | else:
|
|---|
| [652] | 523 | self._p.palette(2)
|
|---|
| [515] | 524 | self._p.set_line(label='Fit')
|
|---|
| [1116] | 525 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| 526 | mask=logical_not(array(m,copy=False)))
|
|---|
| [1088] | 527 | self._p.plot(self.x, y)
|
|---|
| [723] | 528 | xlim=[min(self.x),max(self.x)]
|
|---|
| 529 | self._p.axes.set_xlim(xlim)
|
|---|
| [113] | 530 | self._p.set_axes('xlabel',xlab)
|
|---|
| 531 | self._p.set_axes('ylabel',ylab)
|
|---|
| 532 | self._p.set_axes('title',tlab)
|
|---|
| 533 | self._p.release()
|
|---|
| [723] | 534 | if (not rcParams['plotter.gui']):
|
|---|
| 535 | self._p.save(filename)
|
|---|
| 536 | print_log()
|
|---|
| [113] | 537 |
|
|---|
| [1061] | 538 | def auto_fit(self, insitu=None, plot=False):
|
|---|
| [113] | 539 | """
|
|---|
| [515] | 540 | Return a scan where the function is applied to all rows for
|
|---|
| 541 | all Beams/IFs/Pols.
|
|---|
| [723] | 542 |
|
|---|
| [113] | 543 | """
|
|---|
| 544 | from asap import scantable
|
|---|
| [515] | 545 | if not isinstance(self.data, scantable) :
|
|---|
| [723] | 546 | msg = "Data is not a scantable"
|
|---|
| 547 | if rcParams['verbose']:
|
|---|
| 548 | print msg
|
|---|
| 549 | return
|
|---|
| 550 | else:
|
|---|
| 551 | raise TypeError(msg)
|
|---|
| [259] | 552 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 553 | if not insitu:
|
|---|
| 554 | scan = self.data.copy()
|
|---|
| 555 | else:
|
|---|
| 556 | scan = self.data
|
|---|
| [880] | 557 | rows = xrange(scan.nrow())
|
|---|
| [723] | 558 | from asap import asaplog
|
|---|
| [876] | 559 | asaplog.push("Fitting:")
|
|---|
| 560 | for r in rows:
|
|---|
| [1031] | 561 | 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))
|
|---|
| [880] | 562 | asaplog.push(out, False)
|
|---|
| [876] | 563 | self.x = scan._getabcissa(r)
|
|---|
| 564 | self.y = scan._getspectrum(r)
|
|---|
| 565 | self.data = None
|
|---|
| 566 | self.fit()
|
|---|
| 567 | x = self.get_parameters()
|
|---|
| [1061] | 568 | if plot:
|
|---|
| 569 | self.plot(residual=True)
|
|---|
| 570 | x = raw_input("Accept fit ([y]/n): ")
|
|---|
| 571 | if x.upper() == 'N':
|
|---|
| 572 | continue
|
|---|
| [880] | 573 | scan._setspectrum(self.fitter.getresidual(), r)
|
|---|
| [1061] | 574 | if plot:
|
|---|
| 575 | self._p.unmap()
|
|---|
| 576 | self._p = None
|
|---|
| [876] | 577 | print_log()
|
|---|
| 578 | return scan
|
|---|
| [794] | 579 |
|
|---|
