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