| [113] | 1 | import _asap
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| [259] | 2 | from asap import rcParams
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| [1757] | 3 | from asap import print_log, print_log_dec
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| [1295] | 4 | from asap import _n_bools
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| [1603] | 5 | from asap import mask_and
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| [1614] | 6 | from asap import asaplog
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| [113] | 7 |
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| 8 | class fitter:
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| 9 | """
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| 10 | The fitting class for ASAP.
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| 11 | """
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| [723] | 12 |
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| [113] | 13 | def __init__(self):
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| 14 | """
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| 15 | Create a fitter object. No state is set.
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| 16 | """
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| 17 | self.fitter = _asap.fitter()
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| 18 | self.x = None
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| 19 | self.y = None
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| 20 | self.mask = None
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| 21 | self.fitfunc = None
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| [515] | 22 | self.fitfuncs = None
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| [113] | 23 | self.fitted = False
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| 24 | self.data = None
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| [515] | 25 | self.components = 0
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| 26 | self._fittedrow = 0
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| [113] | 27 | self._p = None
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| [515] | 28 | self._selection = None
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| [1389] | 29 | self.uselinear = False
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| [113] | 30 |
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| 31 | def set_data(self, xdat, ydat, mask=None):
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| 32 | """
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| [158] | 33 | Set the absissa and ordinate for the fit. Also set the mask
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| [113] | 34 | indicationg valid points.
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| 35 | This can be used for data vectors retrieved from a scantable.
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| 36 | For scantable fitting use 'fitter.set_scan(scan, mask)'.
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| 37 | Parameters:
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| [158] | 38 | xdat: the abcissa values
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| [113] | 39 | ydat: the ordinate values
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| 40 | mask: an optional mask
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| [723] | 41 |
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| [113] | 42 | """
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| 43 | self.fitted = False
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| 44 | self.x = xdat
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| 45 | self.y = ydat
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| 46 | if mask == None:
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| [1295] | 47 | self.mask = _n_bools(len(xdat), True)
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| [113] | 48 | else:
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| 49 | self.mask = mask
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| 50 | return
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| 51 |
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| 52 | def set_scan(self, thescan=None, mask=None):
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| 53 | """
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| 54 | Set the 'data' (a scantable) of the fitter.
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| 55 | Parameters:
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| 56 | thescan: a scantable
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| [1603] | 57 | mask: a msk retrieved from the scantable
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| [113] | 58 | """
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| 59 | if not thescan:
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| [723] | 60 | msg = "Please give a correct scan"
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| 61 | if rcParams['verbose']:
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| [1612] | 62 | #print msg
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| [1614] | 63 | asaplog.push(msg)
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| 64 | print_log('ERROR')
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| [723] | 65 | return
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| 66 | else:
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| 67 | raise TypeError(msg)
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| [113] | 68 | self.fitted = False
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| 69 | self.data = thescan
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| [1075] | 70 | self.mask = None
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| [113] | 71 | if mask is None:
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| [1295] | 72 | self.mask = _n_bools(self.data.nchan(), True)
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| [113] | 73 | else:
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| 74 | self.mask = mask
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| 75 | return
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| 76 |
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| 77 | def set_function(self, **kwargs):
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| 78 | """
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| 79 | Set the function to be fit.
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| 80 | Parameters:
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| [1757] | 81 | poly: use a polynomial of the order given with nonlinear least squares fit
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| [1389] | 82 | lpoly: use polynomial of the order given with linear least squares fit
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| [113] | 83 | gauss: fit the number of gaussian specified
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| [1701] | 84 | lorentz: fit the number of lorentzian specified
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| [113] | 85 | Example:
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| [1389] | 86 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method
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| 87 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method
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| [1701] | 88 | fitter.set_function(gauss=2) # will fit two gaussians
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| 89 | fitter.set_function(lorentz=2) # will fit two lorentzians
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| [113] | 90 | """
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| [723] | 91 | #default poly order 0
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| [515] | 92 | n=0
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| [113] | 93 | if kwargs.has_key('poly'):
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| 94 | self.fitfunc = 'poly'
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| 95 | n = kwargs.get('poly')
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| [515] | 96 | self.components = [n]
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| [1757] | 97 | self.uselinear = False
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| [1389] | 98 | elif kwargs.has_key('lpoly'):
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| 99 | self.fitfunc = 'poly'
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| 100 | n = kwargs.get('lpoly')
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| 101 | self.components = [n]
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| 102 | self.uselinear = True
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| [113] | 103 | elif kwargs.has_key('gauss'):
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| 104 | n = kwargs.get('gauss')
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| 105 | self.fitfunc = 'gauss'
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| [515] | 106 | self.fitfuncs = [ 'gauss' for i in range(n) ]
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| 107 | self.components = [ 3 for i in range(n) ]
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| [1757] | 108 | self.uselinear = False
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| [1701] | 109 | elif kwargs.has_key('lorentz'):
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| 110 | n = kwargs.get('lorentz')
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| 111 | self.fitfunc = 'lorentz'
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| 112 | self.fitfuncs = [ 'lorentz' for i in range(n) ]
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| 113 | self.components = [ 3 for i in range(n) ]
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| [1757] | 114 | self.uselinear = False
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| [515] | 115 | else:
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| [723] | 116 | msg = "Invalid function type."
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| 117 | if rcParams['verbose']:
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| [1612] | 118 | #print msg
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| [1614] | 119 | asaplog.push(msg)
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| 120 | print_log('ERROR')
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| [723] | 121 | return
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| 122 | else:
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| 123 | raise TypeError(msg)
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| 124 |
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| [113] | 125 | self.fitter.setexpression(self.fitfunc,n)
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| [1232] | 126 | self.fitted = False
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| [113] | 127 | return
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| [723] | 128 |
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| [1798] | 129 | @print_log_dec
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| [1075] | 130 | def fit(self, row=0, estimate=False):
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| [113] | 131 | """
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| 132 | Execute the actual fitting process. All the state has to be set.
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| 133 | Parameters:
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| [1075] | 134 | row: specify the row in the scantable
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| 135 | estimate: auto-compute an initial parameter set (default False)
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| 136 | This can be used to compute estimates even if fit was
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| 137 | called before.
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| [113] | 138 | Example:
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| [515] | 139 | s = scantable('myscan.asap')
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| 140 | s.set_cursor(thepol=1) # select second pol
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| [113] | 141 | f = fitter()
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| 142 | f.set_scan(s)
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| 143 | f.set_function(poly=0)
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| [723] | 144 | f.fit(row=0) # fit first row
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| [113] | 145 | """
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| 146 | if ((self.x is None or self.y is None) and self.data is None) \
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| 147 | or self.fitfunc is None:
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| [723] | 148 | msg = "Fitter not yet initialised. Please set data & fit function"
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| 149 | if rcParams['verbose']:
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| [1612] | 150 | #print msg
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| [1614] | 151 | asaplog.push(msg)
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| 152 | print_log('ERROR')
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| [723] | 153 | return
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| 154 | else:
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| 155 | raise RuntimeError(msg)
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| 156 |
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| [113] | 157 | else:
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| 158 | if self.data is not None:
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| [515] | 159 | self.x = self.data._getabcissa(row)
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| 160 | self.y = self.data._getspectrum(row)
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| [1603] | 161 | self.mask = mask_and(self.mask, self.data._getmask(row))
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| [723] | 162 | asaplog.push("Fitting:")
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| [943] | 163 | i = row
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| [1603] | 164 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i),
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| 165 | self.data.getbeam(i),
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| 166 | self.data.getif(i),
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| [1757] | 167 | self.data.getpol(i),
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| [1603] | 168 | self.data.getcycle(i))
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| [1075] | 169 | asaplog.push(out,False)
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| [515] | 170 | self.fitter.setdata(self.x, self.y, self.mask)
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| [1701] | 171 | if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
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| [113] | 172 | ps = self.fitter.getparameters()
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| [1075] | 173 | if len(ps) == 0 or estimate:
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| [113] | 174 | self.fitter.estimate()
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| [1628] | 175 | try:
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| 176 | fxdpar = list(self.fitter.getfixedparameters())
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| [1232] | 177 | if len(fxdpar) and fxdpar.count(0) == 0:
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| 178 | raise RuntimeError,"No point fitting, if all parameters are fixed."
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| [1389] | 179 | if self.uselinear:
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| 180 | converged = self.fitter.lfit()
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| 181 | else:
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| 182 | converged = self.fitter.fit()
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| [1075] | 183 | if not converged:
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| 184 | raise RuntimeError,"Fit didn't converge."
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| [626] | 185 | except RuntimeError, msg:
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| [723] | 186 | if rcParams['verbose']:
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| [1612] | 187 | #print msg
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| [1614] | 188 | print_log()
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| [1676] | 189 | asaplog.push(str(msg))
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| [1614] | 190 | print_log('ERROR')
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| [723] | 191 | else:
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| 192 | raise
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| [515] | 193 | self._fittedrow = row
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| [113] | 194 | self.fitted = True
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| [723] | 195 | print_log()
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| [113] | 196 | return
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| 197 |
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| [1232] | 198 | def store_fit(self, filename=None):
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| [526] | 199 | """
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| [1232] | 200 | Save the fit parameters.
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| 201 | Parameters:
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| 202 | filename: if specified save as an ASCII file, if None (default)
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| 203 | store it in the scnatable
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| [526] | 204 | """
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| [515] | 205 | if self.fitted and self.data is not None:
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| 206 | pars = list(self.fitter.getparameters())
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| 207 | fixed = list(self.fitter.getfixedparameters())
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| [975] | 208 | from asap.asapfit import asapfit
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| 209 | fit = asapfit()
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| 210 | fit.setparameters(pars)
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| 211 | fit.setfixedparameters(fixed)
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| 212 | fit.setfunctions(self.fitfuncs)
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| 213 | fit.setcomponents(self.components)
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| 214 | fit.setframeinfo(self.data._getcoordinfo())
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| [1232] | 215 | if filename is not None:
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| 216 | import os
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| 217 | filename = os.path.expandvars(os.path.expanduser(filename))
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| 218 | if os.path.exists(filename):
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| 219 | raise IOError("File '%s' exists." % filename)
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| 220 | fit.save(filename)
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| 221 | else:
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| 222 | self.data._addfit(fit,self._fittedrow)
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| [515] | 223 |
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| [1798] | 224 | @print_log_dec
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| [1017] | 225 | def set_parameters(self,*args,**kwargs):
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| [526] | 226 | """
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| 227 | Set the parameters to be fitted.
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| 228 | Parameters:
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| 229 | params: a vector of parameters
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| 230 | fixed: a vector of which parameters are to be held fixed
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| 231 | (default is none)
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| 232 | component: in case of multiple gaussians, the index of the
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| 233 | component
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| [1017] | 234 | """
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| 235 | component = None
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| 236 | fixed = None
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| 237 | params = None
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| [1031] | 238 |
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| [1017] | 239 | if len(args) and isinstance(args[0],dict):
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| 240 | kwargs = args[0]
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| 241 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
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| 242 | if kwargs.has_key("params"): params = kwargs["params"]
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| 243 | if len(args) == 2 and isinstance(args[1], int):
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| 244 | component = args[1]
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| [515] | 245 | if self.fitfunc is None:
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| [723] | 246 | msg = "Please specify a fitting function first."
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| 247 | if rcParams['verbose']:
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| [1612] | 248 | #print msg
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| [1614] | 249 | asaplog.push(msg)
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| 250 | print_log('ERROR')
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| [723] | 251 | return
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| 252 | else:
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| 253 | raise RuntimeError(msg)
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| [1701] | 254 | if (self.fitfunc == "gauss" or self.fitfunc == 'lorentz') and component is not None:
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| [1017] | 255 | if not self.fitted and sum(self.fitter.getparameters()) == 0:
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| [1295] | 256 | pars = _n_bools(len(self.components)*3, False)
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| 257 | fxd = _n_bools(len(pars), False)
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| [515] | 258 | else:
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| [723] | 259 | pars = list(self.fitter.getparameters())
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| [515] | 260 | fxd = list(self.fitter.getfixedparameters())
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| 261 | i = 3*component
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| 262 | pars[i:i+3] = params
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| 263 | fxd[i:i+3] = fixed
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| 264 | params = pars
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| [723] | 265 | fixed = fxd
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| [113] | 266 | self.fitter.setparameters(params)
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| 267 | if fixed is not None:
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| 268 | self.fitter.setfixedparameters(fixed)
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| [723] | 269 | print_log()
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| [113] | 270 | return
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| [515] | 271 |
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| [1217] | 272 | def set_gauss_parameters(self, peak, centre, fwhm,
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| [1603] | 273 | peakfixed=0, centrefixed=0,
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| [1217] | 274 | fwhmfixed=0,
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| [515] | 275 | component=0):
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| [113] | 276 | """
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| [515] | 277 | Set the Parameters of a 'Gaussian' component, set with set_function.
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| 278 | Parameters:
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| [1232] | 279 | peak, centre, fwhm: The gaussian parameters
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| [515] | 280 | peakfixed,
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| [1603] | 281 | centrefixed,
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| [1217] | 282 | fwhmfixed: Optional parameters to indicate if
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| [515] | 283 | the paramters should be held fixed during
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| 284 | the fitting process. The default is to keep
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| 285 | all parameters flexible.
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| [526] | 286 | component: The number of the component (Default is the
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| 287 | component 0)
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| [515] | 288 | """
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| 289 | if self.fitfunc != "gauss":
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| [723] | 290 | msg = "Function only operates on Gaussian components."
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| 291 | if rcParams['verbose']:
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| [1612] | 292 | #print msg
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| [1614] | 293 | asaplog.push(msg)
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| 294 | print_log('ERROR')
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| [723] | 295 | return
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| 296 | else:
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| 297 | raise ValueError(msg)
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| [515] | 298 | if 0 <= component < len(self.components):
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| [1217] | 299 | d = {'params':[peak, centre, fwhm],
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| [1603] | 300 | 'fixed':[peakfixed, centrefixed, fwhmfixed]}
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| [1017] | 301 | self.set_parameters(d, component)
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| [515] | 302 | else:
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| [723] | 303 | msg = "Please select a valid component."
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| 304 | if rcParams['verbose']:
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| [1612] | 305 | #print msg
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| [1614] | 306 | asaplog.push(msg)
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| 307 | print_log('ERROR')
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| [723] | 308 | return
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| 309 | else:
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| 310 | raise ValueError(msg)
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| 311 |
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| [1701] | 312 | def set_lorentz_parameters(self, peak, centre, fwhm,
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| 313 | peakfixed=0, centrefixed=0,
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| 314 | fwhmfixed=0,
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| 315 | component=0):
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| 316 | """
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| 317 | Set the Parameters of a 'Lorentzian' component, set with set_function.
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| 318 | Parameters:
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| 319 | peak, centre, fwhm: The gaussian parameters
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| 320 | peakfixed,
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| 321 | centrefixed,
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| 322 | fwhmfixed: Optional parameters to indicate if
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| 323 | the paramters should be held fixed during
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| 324 | the fitting process. The default is to keep
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| 325 | all parameters flexible.
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| 326 | component: The number of the component (Default is the
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| 327 | component 0)
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| 328 | """
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| 329 | if self.fitfunc != "lorentz":
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| 330 | msg = "Function only operates on Lorentzian components."
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| 331 | if rcParams['verbose']:
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| 332 | #print msg
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| 333 | asaplog.push(msg)
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| 334 | print_log('ERROR')
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| 335 | return
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| 336 | else:
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| 337 | raise ValueError(msg)
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| 338 | if 0 <= component < len(self.components):
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| 339 | d = {'params':[peak, centre, fwhm],
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| 340 | 'fixed':[peakfixed, centrefixed, fwhmfixed]}
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| 341 | self.set_parameters(d, component)
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| 342 | else:
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| 343 | msg = "Please select a valid component."
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| 344 | if rcParams['verbose']:
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| 345 | #print msg
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| 346 | asaplog.push(msg)
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| 347 | print_log('ERROR')
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| 348 | return
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| 349 | else:
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| 350 | raise ValueError(msg)
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| 351 |
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| [975] | 352 | def get_area(self, component=None):
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| 353 | """
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| [1701] | 354 | Return the area under the fitted gaussian/lorentzian component.
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| [975] | 355 | Parameters:
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| [1701] | 356 | component: the gaussian/lorentzian component selection,
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| [975] | 357 | default (None) is the sum of all components
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| 358 | Note:
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| [1701] | 359 | This will only work for gaussian/lorentzian fits.
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| [975] | 360 | """
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| 361 | if not self.fitted: return
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| [1701] | 362 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
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| [975] | 363 | pars = list(self.fitter.getparameters())
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| 364 | from math import log,pi,sqrt
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| [1701] | 365 | if self.fitfunc == "gauss":
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| 366 | fac = sqrt(pi/log(16.0))
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| 367 | elif self.fitfunc == "lorentz":
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| 368 | fac = pi/2.0
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| [975] | 369 | areas = []
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| 370 | for i in range(len(self.components)):
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| 371 | j = i*3
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| 372 | cpars = pars[j:j+3]
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| 373 | areas.append(fac * cpars[0] * cpars[2])
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| 374 | else:
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| 375 | return None
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| 376 | if component is not None:
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| 377 | return areas[component]
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| 378 | else:
|
|---|
| 379 | return sum(areas)
|
|---|
| 380 |
|
|---|
| [1075] | 381 | def get_errors(self, component=None):
|
|---|
| [515] | 382 | """
|
|---|
| [1075] | 383 | Return the errors in the parameters.
|
|---|
| 384 | Parameters:
|
|---|
| 385 | component: get the errors for the specified component
|
|---|
| 386 | only, default is all components
|
|---|
| 387 | """
|
|---|
| 388 | if not self.fitted:
|
|---|
| 389 | msg = "Not yet fitted."
|
|---|
| 390 | if rcParams['verbose']:
|
|---|
| [1612] | 391 | #print msg
|
|---|
| [1614] | 392 | asaplog.push(msg)
|
|---|
| 393 | print_log('ERROR')
|
|---|
| [1075] | 394 | return
|
|---|
| 395 | else:
|
|---|
| 396 | raise RuntimeError(msg)
|
|---|
| 397 | errs = list(self.fitter.geterrors())
|
|---|
| 398 | cerrs = errs
|
|---|
| 399 | if component is not None:
|
|---|
| [1701] | 400 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| [1075] | 401 | i = 3*component
|
|---|
| 402 | if i < len(errs):
|
|---|
| 403 | cerrs = errs[i:i+3]
|
|---|
| 404 | return cerrs
|
|---|
| 405 |
|
|---|
| 406 | def get_parameters(self, component=None, errors=False):
|
|---|
| 407 | """
|
|---|
| [113] | 408 | Return the fit paramters.
|
|---|
| [526] | 409 | Parameters:
|
|---|
| 410 | component: get the parameters for the specified component
|
|---|
| 411 | only, default is all components
|
|---|
| [113] | 412 | """
|
|---|
| 413 | if not self.fitted:
|
|---|
| [723] | 414 | msg = "Not yet fitted."
|
|---|
| 415 | if rcParams['verbose']:
|
|---|
| [1612] | 416 | #print msg
|
|---|
| [1614] | 417 | asaplog.push(msg)
|
|---|
| 418 | print_log('ERROR')
|
|---|
| [723] | 419 | return
|
|---|
| 420 | else:
|
|---|
| 421 | raise RuntimeError(msg)
|
|---|
| [113] | 422 | pars = list(self.fitter.getparameters())
|
|---|
| 423 | fixed = list(self.fitter.getfixedparameters())
|
|---|
| [1075] | 424 | errs = list(self.fitter.geterrors())
|
|---|
| [1039] | 425 | area = []
|
|---|
| [723] | 426 | if component is not None:
|
|---|
| [1701] | 427 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| [515] | 428 | i = 3*component
|
|---|
| 429 | cpars = pars[i:i+3]
|
|---|
| 430 | cfixed = fixed[i:i+3]
|
|---|
| [1075] | 431 | cerrs = errs[i:i+3]
|
|---|
| [1039] | 432 | a = self.get_area(component)
|
|---|
| 433 | area = [a for i in range(3)]
|
|---|
| [515] | 434 | else:
|
|---|
| 435 | cpars = pars
|
|---|
| [723] | 436 | cfixed = fixed
|
|---|
| [1075] | 437 | cerrs = errs
|
|---|
| [515] | 438 | else:
|
|---|
| 439 | cpars = pars
|
|---|
| 440 | cfixed = fixed
|
|---|
| [1075] | 441 | cerrs = errs
|
|---|
| [1701] | 442 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| [1039] | 443 | for c in range(len(self.components)):
|
|---|
| 444 | a = self.get_area(c)
|
|---|
| 445 | area += [a for i in range(3)]
|
|---|
| [1088] | 446 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
|
|---|
| [723] | 447 | if rcParams['verbose']:
|
|---|
| [1612] | 448 | #print fpars
|
|---|
| [1614] | 449 | asaplog.push(fpars)
|
|---|
| 450 | print_log()
|
|---|
| [1075] | 451 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
|
|---|
| 452 | 'errors':cerrs}
|
|---|
| [723] | 453 |
|
|---|
| [1075] | 454 | def _format_pars(self, pars, fixed, errors, area):
|
|---|
| [113] | 455 | out = ''
|
|---|
| 456 | if self.fitfunc == 'poly':
|
|---|
| 457 | c = 0
|
|---|
| [515] | 458 | for i in range(len(pars)):
|
|---|
| 459 | fix = ""
|
|---|
| [1232] | 460 | if len(fixed) and fixed[i]: fix = "(fixed)"
|
|---|
| [1088] | 461 | if errors :
|
|---|
| 462 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i])
|
|---|
| 463 | else:
|
|---|
| 464 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i])
|
|---|
| [113] | 465 | c+=1
|
|---|
| [515] | 466 | out = out[:-1] # remove trailing ','
|
|---|
| [1701] | 467 | elif self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
|
|---|
| [113] | 468 | i = 0
|
|---|
| 469 | c = 0
|
|---|
| [515] | 470 | aunit = ''
|
|---|
| 471 | ounit = ''
|
|---|
| [113] | 472 | if self.data:
|
|---|
| [515] | 473 | aunit = self.data.get_unit()
|
|---|
| 474 | ounit = self.data.get_fluxunit()
|
|---|
| [113] | 475 | while i < len(pars):
|
|---|
| [1039] | 476 | if len(area):
|
|---|
| 477 | 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] | 478 | else:
|
|---|
| 479 | 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] | 480 | c+=1
|
|---|
| 481 | i+=3
|
|---|
| 482 | return out
|
|---|
| [723] | 483 |
|
|---|
| [113] | 484 | def get_estimate(self):
|
|---|
| 485 | """
|
|---|
| [515] | 486 | Return the parameter estimates (for non-linear functions).
|
|---|
| [113] | 487 | """
|
|---|
| 488 | pars = self.fitter.getestimate()
|
|---|
| [943] | 489 | fixed = self.fitter.getfixedparameters()
|
|---|
| [723] | 490 | if rcParams['verbose']:
|
|---|
| [1612] | 491 | #print self._format_pars(pars,fixed,None)
|
|---|
| [1614] | 492 | asaplog.push(self._format_pars(pars,fixed,None))
|
|---|
| 493 | print_log()
|
|---|
| [113] | 494 | return pars
|
|---|
| 495 |
|
|---|
| 496 | def get_residual(self):
|
|---|
| 497 | """
|
|---|
| 498 | Return the residual of the fit.
|
|---|
| 499 | """
|
|---|
| 500 | if not self.fitted:
|
|---|
| [723] | 501 | msg = "Not yet fitted."
|
|---|
| 502 | if rcParams['verbose']:
|
|---|
| [1612] | 503 | #print msg
|
|---|
| [1614] | 504 | asaplog.push(msg)
|
|---|
| 505 | print_log('ERROR')
|
|---|
| [723] | 506 | return
|
|---|
| 507 | else:
|
|---|
| 508 | raise RuntimeError(msg)
|
|---|
| [113] | 509 | return self.fitter.getresidual()
|
|---|
| 510 |
|
|---|
| 511 | def get_chi2(self):
|
|---|
| 512 | """
|
|---|
| 513 | Return chi^2.
|
|---|
| 514 | """
|
|---|
| 515 | if not self.fitted:
|
|---|
| [723] | 516 | msg = "Not yet fitted."
|
|---|
| 517 | if rcParams['verbose']:
|
|---|
| [1612] | 518 | #print msg
|
|---|
| [1614] | 519 | asaplog.push(msg)
|
|---|
| 520 | print_log('ERROR')
|
|---|
| [723] | 521 | return
|
|---|
| 522 | else:
|
|---|
| 523 | raise RuntimeError(msg)
|
|---|
| [113] | 524 | ch2 = self.fitter.getchi2()
|
|---|
| [723] | 525 | if rcParams['verbose']:
|
|---|
| [1612] | 526 | #print 'Chi^2 = %3.3f' % (ch2)
|
|---|
| [1614] | 527 | asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
|
|---|
| 528 | print_log()
|
|---|
| [723] | 529 | return ch2
|
|---|
| [113] | 530 |
|
|---|
| 531 | def get_fit(self):
|
|---|
| 532 | """
|
|---|
| 533 | Return the fitted ordinate values.
|
|---|
| 534 | """
|
|---|
| 535 | if not self.fitted:
|
|---|
| [723] | 536 | msg = "Not yet fitted."
|
|---|
| 537 | if rcParams['verbose']:
|
|---|
| [1612] | 538 | #print msg
|
|---|
| [1614] | 539 | asaplog.push(msg)
|
|---|
| 540 | print_log('ERROR')
|
|---|
| [723] | 541 | return
|
|---|
| 542 | else:
|
|---|
| 543 | raise RuntimeError(msg)
|
|---|
| [113] | 544 | return self.fitter.getfit()
|
|---|
| 545 |
|
|---|
| [1798] | 546 | @print_log_dec
|
|---|
| [113] | 547 | def commit(self):
|
|---|
| 548 | """
|
|---|
| [526] | 549 | Return a new scan where the fits have been commited (subtracted)
|
|---|
| [113] | 550 | """
|
|---|
| 551 | if not self.fitted:
|
|---|
| [723] | 552 | msg = "Not yet fitted."
|
|---|
| 553 | if rcParams['verbose']:
|
|---|
| [1612] | 554 | #print msg
|
|---|
| [1614] | 555 | asaplog.push(msg)
|
|---|
| 556 | print_log('ERROR')
|
|---|
| [723] | 557 | return
|
|---|
| 558 | else:
|
|---|
| 559 | raise RuntimeError(msg)
|
|---|
| [975] | 560 | from asap import scantable
|
|---|
| 561 | if not isinstance(self.data, scantable):
|
|---|
| [723] | 562 | msg = "Not a scantable"
|
|---|
| 563 | if rcParams['verbose']:
|
|---|
| [1612] | 564 | #print msg
|
|---|
| [1614] | 565 | asaplog.push(msg)
|
|---|
| 566 | print_log('ERROR')
|
|---|
| [723] | 567 | return
|
|---|
| 568 | else:
|
|---|
| 569 | raise TypeError(msg)
|
|---|
| [113] | 570 | scan = self.data.copy()
|
|---|
| [259] | 571 | scan._setspectrum(self.fitter.getresidual())
|
|---|
| [723] | 572 | print_log()
|
|---|
| [1092] | 573 | return scan
|
|---|
| [113] | 574 |
|
|---|
| [1798] | 575 | @print_log_dec
|
|---|
| [1757] | 576 | def plot(self, residual=False, components=None, plotparms=False,
|
|---|
| 577 | filename=None):
|
|---|
| [113] | 578 | """
|
|---|
| 579 | Plot the last fit.
|
|---|
| 580 | Parameters:
|
|---|
| 581 | residual: an optional parameter indicating if the residual
|
|---|
| 582 | should be plotted (default 'False')
|
|---|
| [526] | 583 | components: a list of components to plot, e.g [0,1],
|
|---|
| 584 | -1 plots the total fit. Default is to only
|
|---|
| 585 | plot the total fit.
|
|---|
| 586 | plotparms: Inidicates if the parameter values should be present
|
|---|
| 587 | on the plot
|
|---|
| [113] | 588 | """
|
|---|
| 589 | if not self.fitted:
|
|---|
| 590 | return
|
|---|
| [723] | 591 | if not self._p or self._p.is_dead:
|
|---|
| 592 | if rcParams['plotter.gui']:
|
|---|
| 593 | from asap.asaplotgui import asaplotgui as asaplot
|
|---|
| 594 | else:
|
|---|
| 595 | from asap.asaplot import asaplot
|
|---|
| 596 | self._p = asaplot()
|
|---|
| 597 | self._p.hold()
|
|---|
| [113] | 598 | self._p.clear()
|
|---|
| [515] | 599 | self._p.set_panels()
|
|---|
| [652] | 600 | self._p.palette(0)
|
|---|
| [113] | 601 | tlab = 'Spectrum'
|
|---|
| [723] | 602 | xlab = 'Abcissa'
|
|---|
| [1017] | 603 | ylab = 'Ordinate'
|
|---|
| [1757] | 604 | from numpy import ma,logical_not,logical_and,array
|
|---|
| [1273] | 605 | m = self.mask
|
|---|
| [113] | 606 | if self.data:
|
|---|
| [515] | 607 | tlab = self.data._getsourcename(self._fittedrow)
|
|---|
| 608 | xlab = self.data._getabcissalabel(self._fittedrow)
|
|---|
| [1273] | 609 | m = logical_and(self.mask,
|
|---|
| [1306] | 610 | array(self.data._getmask(self._fittedrow),
|
|---|
| 611 | copy=False))
|
|---|
| [1757] | 612 |
|
|---|
| [626] | 613 | ylab = self.data._get_ordinate_label()
|
|---|
| [515] | 614 |
|
|---|
| [1075] | 615 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"]
|
|---|
| [1461] | 616 | nomask=True
|
|---|
| 617 | for i in range(len(m)):
|
|---|
| 618 | nomask = nomask and m[i]
|
|---|
| 619 | label0='Masked Region'
|
|---|
| 620 | label1='Spectrum'
|
|---|
| 621 | if ( nomask ):
|
|---|
| 622 | label0=label1
|
|---|
| 623 | else:
|
|---|
| 624 | y = ma.masked_array( self.y, mask = m )
|
|---|
| 625 | self._p.palette(1,colours)
|
|---|
| 626 | self._p.set_line( label = label1 )
|
|---|
| 627 | self._p.plot( self.x, y )
|
|---|
| [652] | 628 | self._p.palette(0,colours)
|
|---|
| [1461] | 629 | self._p.set_line(label=label0)
|
|---|
| [1273] | 630 | y = ma.masked_array(self.y,mask=logical_not(m))
|
|---|
| [1088] | 631 | self._p.plot(self.x, y)
|
|---|
| [113] | 632 | if residual:
|
|---|
| [1461] | 633 | self._p.palette(7)
|
|---|
| [515] | 634 | self._p.set_line(label='Residual')
|
|---|
| [1116] | 635 | y = ma.masked_array(self.get_residual(),
|
|---|
| [1273] | 636 | mask=logical_not(m))
|
|---|
| [1088] | 637 | self._p.plot(self.x, y)
|
|---|
| [652] | 638 | self._p.palette(2)
|
|---|
| [515] | 639 | if components is not None:
|
|---|
| 640 | cs = components
|
|---|
| 641 | if isinstance(components,int): cs = [components]
|
|---|
| [526] | 642 | if plotparms:
|
|---|
| [1031] | 643 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8)
|
|---|
| [515] | 644 | n = len(self.components)
|
|---|
| [652] | 645 | self._p.palette(3)
|
|---|
| [515] | 646 | for c in cs:
|
|---|
| 647 | if 0 <= c < n:
|
|---|
| 648 | lab = self.fitfuncs[c]+str(c)
|
|---|
| 649 | self._p.set_line(label=lab)
|
|---|
| [1116] | 650 | y = ma.masked_array(self.fitter.evaluate(c),
|
|---|
| [1273] | 651 | mask=logical_not(m))
|
|---|
| [1088] | 652 |
|
|---|
| 653 | self._p.plot(self.x, y)
|
|---|
| [515] | 654 | elif c == -1:
|
|---|
| [652] | 655 | self._p.palette(2)
|
|---|
| [515] | 656 | self._p.set_line(label="Total Fit")
|
|---|
| [1116] | 657 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| [1273] | 658 | mask=logical_not(m))
|
|---|
| [1088] | 659 | self._p.plot(self.x, y)
|
|---|
| [515] | 660 | else:
|
|---|
| [652] | 661 | self._p.palette(2)
|
|---|
| [515] | 662 | self._p.set_line(label='Fit')
|
|---|
| [1116] | 663 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| [1273] | 664 | mask=logical_not(m))
|
|---|
| [1088] | 665 | self._p.plot(self.x, y)
|
|---|
| [723] | 666 | xlim=[min(self.x),max(self.x)]
|
|---|
| 667 | self._p.axes.set_xlim(xlim)
|
|---|
| [113] | 668 | self._p.set_axes('xlabel',xlab)
|
|---|
| 669 | self._p.set_axes('ylabel',ylab)
|
|---|
| 670 | self._p.set_axes('title',tlab)
|
|---|
| 671 | self._p.release()
|
|---|
| [723] | 672 | if (not rcParams['plotter.gui']):
|
|---|
| 673 | self._p.save(filename)
|
|---|
| 674 | print_log()
|
|---|
| [113] | 675 |
|
|---|
| [1798] | 676 | @print_log_dec
|
|---|
| [1061] | 677 | def auto_fit(self, insitu=None, plot=False):
|
|---|
| [113] | 678 | """
|
|---|
| [515] | 679 | Return a scan where the function is applied to all rows for
|
|---|
| 680 | all Beams/IFs/Pols.
|
|---|
| [723] | 681 |
|
|---|
| [113] | 682 | """
|
|---|
| 683 | from asap import scantable
|
|---|
| [515] | 684 | if not isinstance(self.data, scantable) :
|
|---|
| [723] | 685 | msg = "Data is not a scantable"
|
|---|
| 686 | if rcParams['verbose']:
|
|---|
| [1612] | 687 | #print msg
|
|---|
| [1614] | 688 | asaplog.push(msg)
|
|---|
| 689 | print_log('ERROR')
|
|---|
| [723] | 690 | return
|
|---|
| 691 | else:
|
|---|
| 692 | raise TypeError(msg)
|
|---|
| [259] | 693 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 694 | if not insitu:
|
|---|
| 695 | scan = self.data.copy()
|
|---|
| 696 | else:
|
|---|
| 697 | scan = self.data
|
|---|
| [880] | 698 | rows = xrange(scan.nrow())
|
|---|
| [1446] | 699 | # Save parameters of baseline fits as a class attribute.
|
|---|
| 700 | # NOTICE: This does not reflect changes in scantable!
|
|---|
| 701 | if len(rows) > 0: self.blpars=[]
|
|---|
| [876] | 702 | asaplog.push("Fitting:")
|
|---|
| 703 | for r in rows:
|
|---|
| [1603] | 704 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r),
|
|---|
| 705 | scan.getbeam(r),
|
|---|
| 706 | scan.getif(r),
|
|---|
| [1757] | 707 | scan.getpol(r),
|
|---|
| [1603] | 708 | scan.getcycle(r))
|
|---|
| [880] | 709 | asaplog.push(out, False)
|
|---|
| [876] | 710 | self.x = scan._getabcissa(r)
|
|---|
| 711 | self.y = scan._getspectrum(r)
|
|---|
| [1603] | 712 | self.mask = mask_and(self.mask, scan._getmask(r))
|
|---|
| [876] | 713 | self.data = None
|
|---|
| 714 | self.fit()
|
|---|
| [1603] | 715 | x = self.get_parameters()
|
|---|
| [1446] | 716 | fpar = self.get_parameters()
|
|---|
| [1061] | 717 | if plot:
|
|---|
| 718 | self.plot(residual=True)
|
|---|
| 719 | x = raw_input("Accept fit ([y]/n): ")
|
|---|
| 720 | if x.upper() == 'N':
|
|---|
| [1446] | 721 | self.blpars.append(None)
|
|---|
| [1061] | 722 | continue
|
|---|
| [880] | 723 | scan._setspectrum(self.fitter.getresidual(), r)
|
|---|
| [1446] | 724 | self.blpars.append(fpar)
|
|---|
| [1061] | 725 | if plot:
|
|---|
| 726 | self._p.unmap()
|
|---|
| 727 | self._p = None
|
|---|
| [876] | 728 | print_log()
|
|---|
| 729 | return scan
|
|---|
