| [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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| [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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| [1295] | 44 | self.mask = _n_bools(len(xdat), True)
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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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| [1295] | 67 | self.mask = _n_bools(self.data.nchan(), True)
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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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| [1232] | 102 | self.fitted = False
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| [113] | 103 | return
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| [723] | 104 |
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| [1075] | 105 | def fit(self, row=0, estimate=False):
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| [113] | 106 | """
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| 107 | Execute the actual fitting process. All the state has to be set.
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| 108 | Parameters:
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| [1075] | 109 | row: specify the row in the scantable
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| 110 | estimate: auto-compute an initial parameter set (default False)
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| 111 | This can be used to compute estimates even if fit was
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| 112 | called before.
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| [113] | 113 | Example:
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| [515] | 114 | s = scantable('myscan.asap')
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| 115 | s.set_cursor(thepol=1) # select second pol
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| [113] | 116 | f = fitter()
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| 117 | f.set_scan(s)
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| 118 | f.set_function(poly=0)
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| [723] | 119 | f.fit(row=0) # fit first row
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| [113] | 120 | """
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| 121 | if ((self.x is None or self.y is None) and self.data is None) \
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| 122 | or self.fitfunc is None:
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| [723] | 123 | msg = "Fitter not yet initialised. Please set data & fit function"
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| 124 | if rcParams['verbose']:
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| 125 | print msg
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| 126 | return
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| 127 | else:
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| 128 | raise RuntimeError(msg)
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| 129 |
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| [113] | 130 | else:
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| 131 | if self.data is not None:
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| [515] | 132 | self.x = self.data._getabcissa(row)
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| 133 | self.y = self.data._getspectrum(row)
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| [723] | 134 | from asap import asaplog
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| 135 | asaplog.push("Fitting:")
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| [943] | 136 | i = row
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| 137 | 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] | 138 | asaplog.push(out,False)
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| [515] | 139 | self.fitter.setdata(self.x, self.y, self.mask)
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| [113] | 140 | if self.fitfunc == 'gauss':
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| 141 | ps = self.fitter.getparameters()
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| [1075] | 142 | if len(ps) == 0 or estimate:
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| [113] | 143 | self.fitter.estimate()
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| [626] | 144 | try:
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| [1232] | 145 | fxdpar = list(self.fitter.getfixedparameters())
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| 146 | if len(fxdpar) and fxdpar.count(0) == 0:
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| 147 | raise RuntimeError,"No point fitting, if all parameters are fixed."
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| [1075] | 148 | converged = self.fitter.fit()
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| 149 | if not converged:
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| 150 | raise RuntimeError,"Fit didn't converge."
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| [626] | 151 | except RuntimeError, msg:
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| [723] | 152 | if rcParams['verbose']:
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| 153 | print msg
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| 154 | else:
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| 155 | raise
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| [515] | 156 | self._fittedrow = row
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| [113] | 157 | self.fitted = True
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| [723] | 158 | print_log()
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| [113] | 159 | return
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| 160 |
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| [1232] | 161 | def store_fit(self, filename=None):
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| [526] | 162 | """
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| [1232] | 163 | Save the fit parameters.
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| 164 | Parameters:
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| 165 | filename: if specified save as an ASCII file, if None (default)
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| 166 | store it in the scnatable
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| [526] | 167 | """
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| [515] | 168 | if self.fitted and self.data is not None:
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| 169 | pars = list(self.fitter.getparameters())
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| 170 | fixed = list(self.fitter.getfixedparameters())
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| [975] | 171 | from asap.asapfit import asapfit
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| 172 | fit = asapfit()
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| 173 | fit.setparameters(pars)
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| 174 | fit.setfixedparameters(fixed)
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| 175 | fit.setfunctions(self.fitfuncs)
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| 176 | fit.setcomponents(self.components)
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| 177 | fit.setframeinfo(self.data._getcoordinfo())
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| [1232] | 178 | if filename is not None:
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| 179 | import os
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| 180 | filename = os.path.expandvars(os.path.expanduser(filename))
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| 181 | if os.path.exists(filename):
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| 182 | raise IOError("File '%s' exists." % filename)
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| 183 | fit.save(filename)
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| 184 | else:
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| 185 | self.data._addfit(fit,self._fittedrow)
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| [515] | 186 |
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| [1017] | 187 | #def set_parameters(self, params, fixed=None, component=None):
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| 188 | def set_parameters(self,*args,**kwargs):
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| [526] | 189 | """
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| 190 | Set the parameters to be fitted.
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| 191 | Parameters:
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| 192 | params: a vector of parameters
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| 193 | fixed: a vector of which parameters are to be held fixed
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| 194 | (default is none)
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| 195 | component: in case of multiple gaussians, the index of the
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| 196 | component
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| [1017] | 197 | """
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| 198 | component = None
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| 199 | fixed = None
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| 200 | params = None
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| [1031] | 201 |
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| [1017] | 202 | if len(args) and isinstance(args[0],dict):
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| 203 | kwargs = args[0]
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| 204 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
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| 205 | if kwargs.has_key("params"): params = kwargs["params"]
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| 206 | if len(args) == 2 and isinstance(args[1], int):
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| 207 | component = args[1]
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| [515] | 208 | if self.fitfunc is None:
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| [723] | 209 | msg = "Please specify a fitting function first."
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| 210 | if rcParams['verbose']:
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| 211 | print msg
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| 212 | return
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| 213 | else:
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| 214 | raise RuntimeError(msg)
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| [515] | 215 | if self.fitfunc == "gauss" and component is not None:
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| [1017] | 216 | if not self.fitted and sum(self.fitter.getparameters()) == 0:
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| [1295] | 217 | pars = _n_bools(len(self.components)*3, False)
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| 218 | fxd = _n_bools(len(pars), False)
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| [515] | 219 | else:
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| [723] | 220 | pars = list(self.fitter.getparameters())
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| [515] | 221 | fxd = list(self.fitter.getfixedparameters())
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| 222 | i = 3*component
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| 223 | pars[i:i+3] = params
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| 224 | fxd[i:i+3] = fixed
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| 225 | params = pars
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| [723] | 226 | fixed = fxd
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| [113] | 227 | self.fitter.setparameters(params)
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| 228 | if fixed is not None:
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| 229 | self.fitter.setfixedparameters(fixed)
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| [723] | 230 | print_log()
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| [113] | 231 | return
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| [515] | 232 |
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| [1217] | 233 | def set_gauss_parameters(self, peak, centre, fwhm,
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| [1017] | 234 | peakfixed=0, centerfixed=0,
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| [1217] | 235 | fwhmfixed=0,
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| [515] | 236 | component=0):
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| [113] | 237 | """
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| [515] | 238 | Set the Parameters of a 'Gaussian' component, set with set_function.
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| 239 | Parameters:
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| [1232] | 240 | peak, centre, fwhm: The gaussian parameters
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| [515] | 241 | peakfixed,
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| 242 | centerfixed,
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| [1217] | 243 | fwhmfixed: Optional parameters to indicate if
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| [515] | 244 | the paramters should be held fixed during
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| 245 | the fitting process. The default is to keep
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| 246 | all parameters flexible.
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| [526] | 247 | component: The number of the component (Default is the
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| 248 | component 0)
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| [515] | 249 | """
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| 250 | if self.fitfunc != "gauss":
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| [723] | 251 | msg = "Function only operates on Gaussian components."
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| 252 | if rcParams['verbose']:
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| 253 | print msg
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| 254 | return
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| 255 | else:
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| 256 | raise ValueError(msg)
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| [515] | 257 | if 0 <= component < len(self.components):
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| [1217] | 258 | d = {'params':[peak, centre, fwhm],
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| 259 | 'fixed':[peakfixed, centerfixed, fwhmfixed]}
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| [1017] | 260 | self.set_parameters(d, component)
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| [515] | 261 | else:
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| [723] | 262 | msg = "Please select a valid component."
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| 263 | if rcParams['verbose']:
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| 264 | print msg
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| 265 | return
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| 266 | else:
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| 267 | raise ValueError(msg)
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| 268 |
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| [975] | 269 | def get_area(self, component=None):
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| 270 | """
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| 271 | Return the area under the fitted gaussian component.
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| 272 | Parameters:
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| 273 | component: the gaussian component selection,
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| 274 | default (None) is the sum of all components
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| 275 | Note:
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| 276 | This will only work for gaussian fits.
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| 277 | """
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| 278 | if not self.fitted: return
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| 279 | if self.fitfunc == "gauss":
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| 280 | pars = list(self.fitter.getparameters())
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| 281 | from math import log,pi,sqrt
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| 282 | fac = sqrt(pi/log(16.0))
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| 283 | areas = []
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| 284 | for i in range(len(self.components)):
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| 285 | j = i*3
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| 286 | cpars = pars[j:j+3]
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| 287 | areas.append(fac * cpars[0] * cpars[2])
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| 288 | else:
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| 289 | return None
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| 290 | if component is not None:
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| 291 | return areas[component]
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| 292 | else:
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| 293 | return sum(areas)
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| 294 |
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| [1075] | 295 | def get_errors(self, component=None):
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| [515] | 296 | """
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| [1075] | 297 | Return the errors in the parameters.
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| 298 | Parameters:
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| 299 | component: get the errors for the specified component
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| 300 | only, default is all components
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| 301 | """
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| 302 | if not self.fitted:
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| 303 | msg = "Not yet fitted."
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| 304 | if rcParams['verbose']:
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| 305 | print msg
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| 306 | return
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| 307 | else:
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| 308 | raise RuntimeError(msg)
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| 309 | errs = list(self.fitter.geterrors())
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| 310 | cerrs = errs
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| 311 | if component is not None:
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| 312 | if self.fitfunc == "gauss":
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| 313 | i = 3*component
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| 314 | if i < len(errs):
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| 315 | cerrs = errs[i:i+3]
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| 316 | return cerrs
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| 317 |
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| 318 | def get_parameters(self, component=None, errors=False):
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| 319 | """
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| [113] | 320 | Return the fit paramters.
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| [526] | 321 | Parameters:
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| 322 | component: get the parameters for the specified component
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| 323 | only, default is all components
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| [113] | 324 | """
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| 325 | if not self.fitted:
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| [723] | 326 | msg = "Not yet fitted."
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| 327 | if rcParams['verbose']:
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| 328 | print msg
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| 329 | return
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| 330 | else:
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| 331 | raise RuntimeError(msg)
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| [113] | 332 | pars = list(self.fitter.getparameters())
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| 333 | fixed = list(self.fitter.getfixedparameters())
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| [1075] | 334 | errs = list(self.fitter.geterrors())
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| [1039] | 335 | area = []
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| [723] | 336 | if component is not None:
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| [515] | 337 | if self.fitfunc == "gauss":
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| 338 | i = 3*component
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| 339 | cpars = pars[i:i+3]
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| 340 | cfixed = fixed[i:i+3]
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| [1075] | 341 | cerrs = errs[i:i+3]
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| [1039] | 342 | a = self.get_area(component)
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| 343 | area = [a for i in range(3)]
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| [515] | 344 | else:
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| 345 | cpars = pars
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| [723] | 346 | cfixed = fixed
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| [1075] | 347 | cerrs = errs
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| [515] | 348 | else:
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| 349 | cpars = pars
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| 350 | cfixed = fixed
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| [1075] | 351 | cerrs = errs
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| [1039] | 352 | if self.fitfunc == "gauss":
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| 353 | for c in range(len(self.components)):
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| 354 | a = self.get_area(c)
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| 355 | area += [a for i in range(3)]
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| [1088] | 356 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
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| [723] | 357 | if rcParams['verbose']:
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| [515] | 358 | print fpars
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| [1075] | 359 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
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| 360 | 'errors':cerrs}
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| [723] | 361 |
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| [1075] | 362 | def _format_pars(self, pars, fixed, errors, area):
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| [113] | 363 | out = ''
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| 364 | if self.fitfunc == 'poly':
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| 365 | c = 0
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| [515] | 366 | for i in range(len(pars)):
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| 367 | fix = ""
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| [1232] | 368 | if len(fixed) and fixed[i]: fix = "(fixed)"
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| [1088] | 369 | if errors :
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| 370 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])
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| 371 | else:
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| 372 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
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| [113] | 373 | c+=1
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| [515] | 374 | out = out[:-1] # remove trailing ','
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| [113] | 375 | elif self.fitfunc == 'gauss':
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| 376 | i = 0
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| 377 | c = 0
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| [515] | 378 | aunit = ''
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| 379 | ounit = ''
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| [113] | 380 | if self.data:
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| [515] | 381 | aunit = self.data.get_unit()
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| 382 | ounit = self.data.get_fluxunit()
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| [113] | 383 | while i < len(pars):
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| [1039] | 384 | if len(area):
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| 385 | 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] | 386 | else:
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| 387 | 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] | 388 | c+=1
|
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| 389 | i+=3
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| 390 | return out
|
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| [723] | 391 |
|
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| [113] | 392 | def get_estimate(self):
|
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| 393 | """
|
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| [515] | 394 | Return the parameter estimates (for non-linear functions).
|
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| [113] | 395 | """
|
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| 396 | pars = self.fitter.getestimate()
|
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| [943] | 397 | fixed = self.fitter.getfixedparameters()
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| [723] | 398 | if rcParams['verbose']:
|
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| [1017] | 399 | print self._format_pars(pars,fixed,None)
|
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| [113] | 400 | return pars
|
|---|
| 401 |
|
|---|
| 402 | def get_residual(self):
|
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| 403 | """
|
|---|
| 404 | Return the residual of the fit.
|
|---|
| 405 | """
|
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| 406 | if not self.fitted:
|
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| [723] | 407 | msg = "Not yet fitted."
|
|---|
| 408 | if rcParams['verbose']:
|
|---|
| 409 | print msg
|
|---|
| 410 | return
|
|---|
| 411 | else:
|
|---|
| 412 | raise RuntimeError(msg)
|
|---|
| [113] | 413 | return self.fitter.getresidual()
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|---|
| 414 |
|
|---|
| 415 | def get_chi2(self):
|
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| 416 | """
|
|---|
| 417 | Return chi^2.
|
|---|
| 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 | ch2 = self.fitter.getchi2()
|
|---|
| [723] | 427 | if rcParams['verbose']:
|
|---|
| [113] | 428 | print 'Chi^2 = %3.3f' % (ch2)
|
|---|
| [723] | 429 | return ch2
|
|---|
| [113] | 430 |
|
|---|
| 431 | def get_fit(self):
|
|---|
| 432 | """
|
|---|
| 433 | Return the fitted ordinate values.
|
|---|
| 434 | """
|
|---|
| 435 | if not self.fitted:
|
|---|
| [723] | 436 | msg = "Not yet fitted."
|
|---|
| 437 | if rcParams['verbose']:
|
|---|
| 438 | print msg
|
|---|
| 439 | return
|
|---|
| 440 | else:
|
|---|
| 441 | raise RuntimeError(msg)
|
|---|
| [113] | 442 | return self.fitter.getfit()
|
|---|
| 443 |
|
|---|
| 444 | def commit(self):
|
|---|
| 445 | """
|
|---|
| [526] | 446 | Return a new scan where the fits have been commited (subtracted)
|
|---|
| [113] | 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)
|
|---|
| [975] | 455 | from asap import scantable
|
|---|
| 456 | if not isinstance(self.data, scantable):
|
|---|
| [723] | 457 | msg = "Not a scantable"
|
|---|
| 458 | if rcParams['verbose']:
|
|---|
| 459 | print msg
|
|---|
| 460 | return
|
|---|
| 461 | else:
|
|---|
| 462 | raise TypeError(msg)
|
|---|
| [113] | 463 | scan = self.data.copy()
|
|---|
| [259] | 464 | scan._setspectrum(self.fitter.getresidual())
|
|---|
| [723] | 465 | print_log()
|
|---|
| [1092] | 466 | return scan
|
|---|
| [113] | 467 |
|
|---|
| [723] | 468 | def plot(self, residual=False, components=None, plotparms=False, filename=None):
|
|---|
| [113] | 469 | """
|
|---|
| 470 | Plot the last fit.
|
|---|
| 471 | Parameters:
|
|---|
| 472 | residual: an optional parameter indicating if the residual
|
|---|
| 473 | should be plotted (default 'False')
|
|---|
| [526] | 474 | components: a list of components to plot, e.g [0,1],
|
|---|
| 475 | -1 plots the total fit. Default is to only
|
|---|
| 476 | plot the total fit.
|
|---|
| 477 | plotparms: Inidicates if the parameter values should be present
|
|---|
| 478 | on the plot
|
|---|
| [113] | 479 | """
|
|---|
| 480 | if not self.fitted:
|
|---|
| 481 | return
|
|---|
| [723] | 482 | if not self._p or self._p.is_dead:
|
|---|
| 483 | if rcParams['plotter.gui']:
|
|---|
| 484 | from asap.asaplotgui import asaplotgui as asaplot
|
|---|
| 485 | else:
|
|---|
| 486 | from asap.asaplot import asaplot
|
|---|
| 487 | self._p = asaplot()
|
|---|
| 488 | self._p.hold()
|
|---|
| [113] | 489 | self._p.clear()
|
|---|
| [515] | 490 | self._p.set_panels()
|
|---|
| [652] | 491 | self._p.palette(0)
|
|---|
| [113] | 492 | tlab = 'Spectrum'
|
|---|
| [723] | 493 | xlab = 'Abcissa'
|
|---|
| [1017] | 494 | ylab = 'Ordinate'
|
|---|
| [1273] | 495 | from matplotlib.numerix import ma,logical_not,logical_and,array
|
|---|
| 496 | m = self.mask
|
|---|
| [113] | 497 | if self.data:
|
|---|
| [515] | 498 | tlab = self.data._getsourcename(self._fittedrow)
|
|---|
| 499 | xlab = self.data._getabcissalabel(self._fittedrow)
|
|---|
| [1273] | 500 | m = logical_and(self.mask,
|
|---|
| 501 | array(self.data._getmask(self._fittedrow)),
|
|---|
| 502 | copy=False)
|
|---|
| 503 |
|
|---|
| [626] | 504 | ylab = self.data._get_ordinate_label()
|
|---|
| [515] | 505 |
|
|---|
| [1075] | 506 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
|
|---|
| [652] | 507 | self._p.palette(0,colours)
|
|---|
| [515] | 508 | self._p.set_line(label='Spectrum')
|
|---|
| [1273] | 509 | y = ma.masked_array(self.y,mask=logical_not(m))
|
|---|
| [1088] | 510 | self._p.plot(self.x, y)
|
|---|
| [113] | 511 | if residual:
|
|---|
| [652] | 512 | self._p.palette(1)
|
|---|
| [515] | 513 | self._p.set_line(label='Residual')
|
|---|
| [1116] | 514 | y = ma.masked_array(self.get_residual(),
|
|---|
| [1273] | 515 | mask=logical_not(m))
|
|---|
| [1088] | 516 | self._p.plot(self.x, y)
|
|---|
| [652] | 517 | self._p.palette(2)
|
|---|
| [515] | 518 | if components is not None:
|
|---|
| 519 | cs = components
|
|---|
| 520 | if isinstance(components,int): cs = [components]
|
|---|
| [526] | 521 | if plotparms:
|
|---|
| [1031] | 522 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
|
|---|
| [515] | 523 | n = len(self.components)
|
|---|
| [652] | 524 | self._p.palette(3)
|
|---|
| [515] | 525 | for c in cs:
|
|---|
| 526 | if 0 <= c < n:
|
|---|
| 527 | lab = self.fitfuncs[c]+str(c)
|
|---|
| 528 | self._p.set_line(label=lab)
|
|---|
| [1116] | 529 | y = ma.masked_array(self.fitter.evaluate(c),
|
|---|
| [1273] | 530 | mask=logical_not(m))
|
|---|
| [1088] | 531 |
|
|---|
| 532 | self._p.plot(self.x, y)
|
|---|
| [515] | 533 | elif c == -1:
|
|---|
| [652] | 534 | self._p.palette(2)
|
|---|
| [515] | 535 | self._p.set_line(label="Total Fit")
|
|---|
| [1116] | 536 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| [1273] | 537 | mask=logical_not(m))
|
|---|
| [1088] | 538 | self._p.plot(self.x, y)
|
|---|
| [515] | 539 | else:
|
|---|
| [652] | 540 | self._p.palette(2)
|
|---|
| [515] | 541 | self._p.set_line(label='Fit')
|
|---|
| [1116] | 542 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| [1273] | 543 | mask=logical_not(m))
|
|---|
| [1088] | 544 | self._p.plot(self.x, y)
|
|---|
| [723] | 545 | xlim=[min(self.x),max(self.x)]
|
|---|
| 546 | self._p.axes.set_xlim(xlim)
|
|---|
| [113] | 547 | self._p.set_axes('xlabel',xlab)
|
|---|
| 548 | self._p.set_axes('ylabel',ylab)
|
|---|
| 549 | self._p.set_axes('title',tlab)
|
|---|
| 550 | self._p.release()
|
|---|
| [723] | 551 | if (not rcParams['plotter.gui']):
|
|---|
| 552 | self._p.save(filename)
|
|---|
| 553 | print_log()
|
|---|
| [113] | 554 |
|
|---|
| [1061] | 555 | def auto_fit(self, insitu=None, plot=False):
|
|---|
| [113] | 556 | """
|
|---|
| [515] | 557 | Return a scan where the function is applied to all rows for
|
|---|
| 558 | all Beams/IFs/Pols.
|
|---|
| [723] | 559 |
|
|---|
| [113] | 560 | """
|
|---|
| 561 | from asap import scantable
|
|---|
| [515] | 562 | if not isinstance(self.data, scantable) :
|
|---|
| [723] | 563 | msg = "Data is not a scantable"
|
|---|
| 564 | if rcParams['verbose']:
|
|---|
| 565 | print msg
|
|---|
| 566 | return
|
|---|
| 567 | else:
|
|---|
| 568 | raise TypeError(msg)
|
|---|
| [259] | 569 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 570 | if not insitu:
|
|---|
| 571 | scan = self.data.copy()
|
|---|
| 572 | else:
|
|---|
| 573 | scan = self.data
|
|---|
| [880] | 574 | rows = xrange(scan.nrow())
|
|---|
| [723] | 575 | from asap import asaplog
|
|---|
| [876] | 576 | asaplog.push("Fitting:")
|
|---|
| 577 | for r in rows:
|
|---|
| [1031] | 578 | 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] | 579 | asaplog.push(out, False)
|
|---|
| [876] | 580 | self.x = scan._getabcissa(r)
|
|---|
| 581 | self.y = scan._getspectrum(r)
|
|---|
| 582 | self.data = None
|
|---|
| 583 | self.fit()
|
|---|
| 584 | x = self.get_parameters()
|
|---|
| [1061] | 585 | if plot:
|
|---|
| 586 | self.plot(residual=True)
|
|---|
| 587 | x = raw_input("Accept fit ([y]/n): ")
|
|---|
| 588 | if x.upper() == 'N':
|
|---|
| 589 | continue
|
|---|
| [880] | 590 | scan._setspectrum(self.fitter.getresidual(), r)
|
|---|
| [1061] | 591 | if plot:
|
|---|
| 592 | self._p.unmap()
|
|---|
| 593 | self._p = None
|
|---|
| [876] | 594 | print_log()
|
|---|
| 595 | return scan
|
|---|
| [794] | 596 |
|
|---|
