| [113] | 1 | import _asap
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| [1826] | 2 | from asap.parameters import rcParams
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| [1862] | 3 | from asap.logging import asaplog, asaplog_post_dec
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| [1826] | 4 | from asap.utils import _n_bools, mask_and
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| [2666] | 5 | from numpy import ndarray
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| [113] | 6 |
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| 7 | class fitter:
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| 8 | """
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| 9 | The fitting class for ASAP.
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| 10 | """
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| 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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| [1391] | 27 | self.uselinear = False
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| [2666] | 28 | self._constraints = []
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| [113] | 29 |
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| 30 | def set_data(self, xdat, ydat, mask=None):
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| 31 | """
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| [158] | 32 | Set the absissa and ordinate for the fit. Also set the mask
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| [2153] | 33 | indicating valid points.
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| [113] | 34 | This can be used for data vectors retrieved from a scantable.
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| 35 | For scantable fitting use 'fitter.set_scan(scan, mask)'.
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| 36 | Parameters:
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| [158] | 37 | xdat: the abcissa values
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| [113] | 38 | ydat: the ordinate values
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| 39 | mask: an optional mask
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| [723] | 40 |
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| [113] | 41 | """
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| 42 | self.fitted = False
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| 43 | self.x = xdat
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| 44 | self.y = ydat
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| 45 | if mask == None:
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| [1295] | 46 | self.mask = _n_bools(len(xdat), True)
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| [113] | 47 | else:
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| 48 | self.mask = mask
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| 49 | return
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| 50 |
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| [1862] | 51 | @asaplog_post_dec
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| [113] | 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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| [1420] | 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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| [1859] | 61 | raise TypeError(msg)
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| [113] | 62 | self.fitted = False
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| 63 | self.data = thescan
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| [1075] | 64 | self.mask = None
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| [113] | 65 | if mask is None:
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| [1295] | 66 | self.mask = _n_bools(self.data.nchan(), True)
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| [113] | 67 | else:
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| 68 | self.mask = mask
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| 69 | return
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| 70 |
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| [1862] | 71 | @asaplog_post_dec
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| [113] | 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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| [2666] | 76 | poly: use a polynomial of the order given with nonlinear
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| 77 | least squares fit
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| 78 | lpoly: use polynomial of the order given with linear least
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| 79 | squares fit
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| [2047] | 80 | gauss: fit the number of gaussian specified
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| 81 | lorentz: fit the number of lorentzian specified
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| 82 | sinusoid: fit the number of sinusoid specified
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| [113] | 83 | Example:
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| [2666] | 84 | fitter.set_function(poly=3) # will fit a 3rd order polynomial
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| 85 | # via nonlinear method
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| 86 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial
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| 87 | # via linear method
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| [1819] | 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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| [2047] | 90 | fitter.set_function(sinusoid=3) # will fit three sinusoids
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| [113] | 91 | """
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| [723] | 92 | #default poly order 0
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| [515] | 93 | n=0
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| [113] | 94 | if kwargs.has_key('poly'):
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| 95 | self.fitfunc = 'poly'
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| [1938] | 96 | self.fitfuncs = ['poly']
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| [113] | 97 | n = kwargs.get('poly')
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| [1938] | 98 | self.components = [n+1]
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| [1589] | 99 | self.uselinear = False
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| [1391] | 100 | elif kwargs.has_key('lpoly'):
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| 101 | self.fitfunc = 'poly'
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| [1938] | 102 | self.fitfuncs = ['lpoly']
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| [1391] | 103 | n = kwargs.get('lpoly')
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| [1938] | 104 | self.components = [n+1]
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| [1391] | 105 | self.uselinear = True
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| [113] | 106 | elif kwargs.has_key('gauss'):
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| 107 | n = kwargs.get('gauss')
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| 108 | self.fitfunc = 'gauss'
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| [515] | 109 | self.fitfuncs = [ 'gauss' for i in range(n) ]
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| 110 | self.components = [ 3 for i in range(n) ]
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| [1589] | 111 | self.uselinear = False
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| [1819] | 112 | elif kwargs.has_key('lorentz'):
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| 113 | n = kwargs.get('lorentz')
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| 114 | self.fitfunc = 'lorentz'
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| 115 | self.fitfuncs = [ 'lorentz' for i in range(n) ]
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| 116 | self.components = [ 3 for i in range(n) ]
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| 117 | self.uselinear = False
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| [2047] | 118 | elif kwargs.has_key('sinusoid'):
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| 119 | n = kwargs.get('sinusoid')
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| 120 | self.fitfunc = 'sinusoid'
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| 121 | self.fitfuncs = [ 'sinusoid' for i in range(n) ]
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| 122 | self.components = [ 3 for i in range(n) ]
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| 123 | self.uselinear = False
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| [2666] | 124 | elif kwargs.has_key('expression'):
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| 125 | self.uselinear = False
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| 126 | raise RuntimeError("Not yet implemented")
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| [515] | 127 | else:
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| [723] | 128 | msg = "Invalid function type."
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| [1859] | 129 | raise TypeError(msg)
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| [723] | 130 |
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| [113] | 131 | self.fitter.setexpression(self.fitfunc,n)
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| [2666] | 132 | self._constraints = []
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| [1232] | 133 | self.fitted = False
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| [113] | 134 | return
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| [723] | 135 |
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| [1862] | 136 | @asaplog_post_dec
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| [1075] | 137 | def fit(self, row=0, estimate=False):
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| [113] | 138 | """
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| 139 | Execute the actual fitting process. All the state has to be set.
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| 140 | Parameters:
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| [1075] | 141 | row: specify the row in the scantable
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| 142 | estimate: auto-compute an initial parameter set (default False)
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| 143 | This can be used to compute estimates even if fit was
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| 144 | called before.
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| [113] | 145 | Example:
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| [515] | 146 | s = scantable('myscan.asap')
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| 147 | s.set_cursor(thepol=1) # select second pol
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| [113] | 148 | f = fitter()
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| 149 | f.set_scan(s)
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| 150 | f.set_function(poly=0)
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| [723] | 151 | f.fit(row=0) # fit first row
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| [113] | 152 | """
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| 153 | if ((self.x is None or self.y is None) and self.data is None) \
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| 154 | or self.fitfunc is None:
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| [723] | 155 | msg = "Fitter not yet initialised. Please set data & fit function"
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| [1859] | 156 | raise RuntimeError(msg)
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| [723] | 157 |
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| [2666] | 158 | if self.data is not None:
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| [2961] | 159 | if self.data._getflagrow(row):
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| 160 | raise RuntimeError,"Can not fit flagged row."
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| [2666] | 161 | self.x = self.data._getabcissa(row)
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| 162 | self.y = self.data._getspectrum(row)
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| 163 | #self.mask = mask_and(self.mask, self.data._getmask(row))
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| 164 | if len(self.x) == len(self.mask):
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| 165 | self.mask = mask_and(self.mask, self.data._getmask(row))
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| 166 | else:
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| 167 | asaplog.push('lengths of data and mask are not the same. '
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| 168 | 'preset mask will be ignored')
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| 169 | asaplog.post('WARN','asapfit.fit')
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| 170 | self.mask=self.data._getmask(row)
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| 171 | asaplog.push("Fitting:")
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| 172 | i = row
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| 173 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
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| 174 | self.data.getscan(i),
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| 175 | self.data.getbeam(i),
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| 176 | self.data.getif(i),
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| 177 | self.data.getpol(i),
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| 178 | self.data.getcycle(i))
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| 179 |
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| 180 | asaplog.push(out, False)
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| 181 |
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| [515] | 182 | self.fitter.setdata(self.x, self.y, self.mask)
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| [1819] | 183 | if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz':
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| [113] | 184 | ps = self.fitter.getparameters()
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| [1075] | 185 | if len(ps) == 0 or estimate:
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| [113] | 186 | self.fitter.estimate()
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| [1859] | 187 | fxdpar = list(self.fitter.getfixedparameters())
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| 188 | if len(fxdpar) and fxdpar.count(0) == 0:
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| 189 | raise RuntimeError,"No point fitting, if all parameters are fixed."
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| [2666] | 190 | if self._constraints:
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| 191 | for c in self._constraints:
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| 192 | self.fitter.addconstraint(c[0]+[c[-1]])
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| [1859] | 193 | if self.uselinear:
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| 194 | converged = self.fitter.lfit()
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| 195 | else:
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| 196 | converged = self.fitter.fit()
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| 197 | if not converged:
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| 198 | raise RuntimeError,"Fit didn't converge."
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| [515] | 199 | self._fittedrow = row
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| [113] | 200 | self.fitted = True
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| 201 | return
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| 202 |
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| [1232] | 203 | def store_fit(self, filename=None):
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| [526] | 204 | """
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| [1232] | 205 | Save the fit parameters.
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| 206 | Parameters:
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| 207 | filename: if specified save as an ASCII file, if None (default)
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| 208 | store it in the scnatable
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| [526] | 209 | """
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| [515] | 210 | if self.fitted and self.data is not None:
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| 211 | pars = list(self.fitter.getparameters())
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| 212 | fixed = list(self.fitter.getfixedparameters())
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| [975] | 213 | from asap.asapfit import asapfit
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| 214 | fit = asapfit()
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| 215 | fit.setparameters(pars)
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| 216 | fit.setfixedparameters(fixed)
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| 217 | fit.setfunctions(self.fitfuncs)
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| 218 | fit.setcomponents(self.components)
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| 219 | fit.setframeinfo(self.data._getcoordinfo())
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| [1232] | 220 | if filename is not None:
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| 221 | import os
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| 222 | filename = os.path.expandvars(os.path.expanduser(filename))
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| 223 | if os.path.exists(filename):
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| 224 | raise IOError("File '%s' exists." % filename)
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| 225 | fit.save(filename)
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| 226 | else:
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| 227 | self.data._addfit(fit,self._fittedrow)
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| [515] | 228 |
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| [1862] | 229 | @asaplog_post_dec
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| [1017] | 230 | def set_parameters(self,*args,**kwargs):
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| [526] | 231 | """
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| 232 | Set the parameters to be fitted.
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| 233 | Parameters:
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| 234 | params: a vector of parameters
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| 235 | fixed: a vector of which parameters are to be held fixed
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| 236 | (default is none)
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| [2047] | 237 | component: in case of multiple gaussians/lorentzians/sinusoidals,
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| 238 | the index of the target component
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| [1017] | 239 | """
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| 240 | component = None
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| 241 | fixed = None
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| 242 | params = None
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| [1031] | 243 |
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| [1017] | 244 | if len(args) and isinstance(args[0],dict):
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| 245 | kwargs = args[0]
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| 246 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"]
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| 247 | if kwargs.has_key("params"): params = kwargs["params"]
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| 248 | if len(args) == 2 and isinstance(args[1], int):
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| 249 | component = args[1]
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| [515] | 250 | if self.fitfunc is None:
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| [723] | 251 | msg = "Please specify a fitting function first."
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| [1859] | 252 | raise RuntimeError(msg)
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| [2666] | 253 | if (self.fitfunc == "gauss" or self.fitfunc == "lorentz"
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| 254 | or self.fitfunc == "sinusoid") 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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| [2047] | 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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| [2047] | 260 | fxd = list(self.fitter.getfixedparameters())
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| [515] | 261 | i = 3*component
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| 262 | pars[i:i+3] = params
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| [2047] | 263 | fxd[i:i+3] = fixed
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| [515] | 264 | params = pars
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| [2047] | 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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| 269 | return
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| [515] | 270 |
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| [1862] | 271 | @asaplog_post_dec
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| [1217] | 272 | def set_gauss_parameters(self, peak, centre, fwhm,
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| [1409] | 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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| [1409] | 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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| [1859] | 291 | raise ValueError(msg)
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| [515] | 292 | if 0 <= component < len(self.components):
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| [1217] | 293 | d = {'params':[peak, centre, fwhm],
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| [1409] | 294 | 'fixed':[peakfixed, centrefixed, fwhmfixed]}
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| [1017] | 295 | self.set_parameters(d, component)
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| [515] | 296 | else:
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| [723] | 297 | msg = "Please select a valid component."
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| [1859] | 298 | raise ValueError(msg)
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| [723] | 299 |
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| [1862] | 300 | @asaplog_post_dec
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| [1819] | 301 | def set_lorentz_parameters(self, peak, centre, fwhm,
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| 302 | peakfixed=0, centrefixed=0,
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| 303 | fwhmfixed=0,
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| 304 | component=0):
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| 305 | """
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| 306 | Set the Parameters of a 'Lorentzian' component, set with set_function.
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| 307 | Parameters:
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| [1927] | 308 | peak, centre, fwhm: The lorentzian parameters
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| [1819] | 309 | peakfixed,
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| 310 | centrefixed,
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| 311 | fwhmfixed: Optional parameters to indicate if
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| 312 | the paramters should be held fixed during
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| 313 | the fitting process. The default is to keep
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| 314 | all parameters flexible.
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| 315 | component: The number of the component (Default is the
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| 316 | component 0)
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| 317 | """
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| 318 | if self.fitfunc != "lorentz":
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| 319 | msg = "Function only operates on Lorentzian components."
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| [1859] | 320 | raise ValueError(msg)
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| [1819] | 321 | if 0 <= component < len(self.components):
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| 322 | d = {'params':[peak, centre, fwhm],
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| 323 | 'fixed':[peakfixed, centrefixed, fwhmfixed]}
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| 324 | self.set_parameters(d, component)
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| 325 | else:
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| 326 | msg = "Please select a valid component."
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| [1859] | 327 | raise ValueError(msg)
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| [1819] | 328 |
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| [2047] | 329 | @asaplog_post_dec
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| 330 | def set_sinusoid_parameters(self, ampl, period, x0,
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| 331 | amplfixed=0, periodfixed=0,
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| 332 | x0fixed=0,
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| 333 | component=0):
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| 334 | """
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| 335 | Set the Parameters of a 'Sinusoidal' component, set with set_function.
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| 336 | Parameters:
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| 337 | ampl, period, x0: The sinusoidal parameters
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| 338 | amplfixed,
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| 339 | periodfixed,
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| 340 | x0fixed: Optional parameters to indicate if
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| 341 | the paramters should be held fixed during
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| 342 | the fitting process. The default is to keep
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| 343 | all parameters flexible.
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| 344 | component: The number of the component (Default is the
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| 345 | component 0)
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| 346 | """
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| 347 | if self.fitfunc != "sinusoid":
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| 348 | msg = "Function only operates on Sinusoidal components."
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| 349 | raise ValueError(msg)
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| 350 | if 0 <= component < len(self.components):
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| 351 | d = {'params':[ampl, period, x0],
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| 352 | 'fixed': [amplfixed, periodfixed, x0fixed]}
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| 353 | self.set_parameters(d, component)
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| 354 | else:
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| 355 | msg = "Please select a valid component."
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| 356 | raise ValueError(msg)
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| 357 |
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| [2666] | 358 |
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| 359 | def add_constraint(self, xpar, y):
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| 360 | """Add parameter constraints to the fit. This is done by setting up
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| 361 | linear equations for the related parameters.
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| 362 |
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| 363 | For example a two component gaussian fit where the amplitudes are
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| [2681] | 364 | constraint by amp1 = 2*amp2 and paramaters for the two components
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| 365 | in the order [amp1,peakv1,sigma1,amp2,peakv2,sigma2]
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| 366 | needs a constraint
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| [2666] | 367 |
|
|---|
| [2681] | 368 | add_constraint([1, 0, 0, -2, 0, 0], 0)
|
|---|
| [2666] | 369 |
|
|---|
| [2681] | 370 | as the linear equation is
|
|---|
| 371 |
|
|---|
| 372 | 1*amp1 + 0*peakv1 + 0*sigma1 -2*amp2 + 0*peakv2 + 0*sigma2 = 0
|
|---|
| 373 |
|
|---|
| 374 | and similarly for a velocity difference of v2-v1=17
|
|---|
| [2666] | 375 |
|
|---|
| 376 | add_constraint([0.,-1.,0.,0.,1.,0.], 17.)
|
|---|
| 377 |
|
|---|
| 378 | """
|
|---|
| 379 | self._constraints.append((xpar, y))
|
|---|
| 380 |
|
|---|
| 381 |
|
|---|
| [975] | 382 | def get_area(self, component=None):
|
|---|
| 383 | """
|
|---|
| [1819] | 384 | Return the area under the fitted gaussian/lorentzian component.
|
|---|
| [975] | 385 | Parameters:
|
|---|
| [1819] | 386 | component: the gaussian/lorentzian component selection,
|
|---|
| [975] | 387 | default (None) is the sum of all components
|
|---|
| 388 | Note:
|
|---|
| [1819] | 389 | This will only work for gaussian/lorentzian fits.
|
|---|
| [975] | 390 | """
|
|---|
| 391 | if not self.fitted: return
|
|---|
| [1819] | 392 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| [975] | 393 | pars = list(self.fitter.getparameters())
|
|---|
| 394 | from math import log,pi,sqrt
|
|---|
| [1819] | 395 | if self.fitfunc == "gauss":
|
|---|
| 396 | fac = sqrt(pi/log(16.0))
|
|---|
| 397 | elif self.fitfunc == "lorentz":
|
|---|
| 398 | fac = pi/2.0
|
|---|
| [975] | 399 | areas = []
|
|---|
| 400 | for i in range(len(self.components)):
|
|---|
| 401 | j = i*3
|
|---|
| 402 | cpars = pars[j:j+3]
|
|---|
| 403 | areas.append(fac * cpars[0] * cpars[2])
|
|---|
| 404 | else:
|
|---|
| 405 | return None
|
|---|
| 406 | if component is not None:
|
|---|
| 407 | return areas[component]
|
|---|
| 408 | else:
|
|---|
| 409 | return sum(areas)
|
|---|
| 410 |
|
|---|
| [1862] | 411 | @asaplog_post_dec
|
|---|
| [1075] | 412 | def get_errors(self, component=None):
|
|---|
| [515] | 413 | """
|
|---|
| [1075] | 414 | Return the errors in the parameters.
|
|---|
| 415 | Parameters:
|
|---|
| 416 | component: get the errors for the specified component
|
|---|
| 417 | only, default is all components
|
|---|
| 418 | """
|
|---|
| 419 | if not self.fitted:
|
|---|
| 420 | msg = "Not yet fitted."
|
|---|
| [1859] | 421 | raise RuntimeError(msg)
|
|---|
| [1075] | 422 | errs = list(self.fitter.geterrors())
|
|---|
| 423 | cerrs = errs
|
|---|
| 424 | if component is not None:
|
|---|
| [2666] | 425 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz" \
|
|---|
| 426 | or self.fitfunc == "sinusoid":
|
|---|
| [1075] | 427 | i = 3*component
|
|---|
| 428 | if i < len(errs):
|
|---|
| 429 | cerrs = errs[i:i+3]
|
|---|
| 430 | return cerrs
|
|---|
| 431 |
|
|---|
| [1859] | 432 |
|
|---|
| [1862] | 433 | @asaplog_post_dec
|
|---|
| [1075] | 434 | def get_parameters(self, component=None, errors=False):
|
|---|
| 435 | """
|
|---|
| [113] | 436 | Return the fit paramters.
|
|---|
| [526] | 437 | Parameters:
|
|---|
| 438 | component: get the parameters for the specified component
|
|---|
| 439 | only, default is all components
|
|---|
| [113] | 440 | """
|
|---|
| 441 | if not self.fitted:
|
|---|
| [723] | 442 | msg = "Not yet fitted."
|
|---|
| [1859] | 443 | raise RuntimeError(msg)
|
|---|
| [113] | 444 | pars = list(self.fitter.getparameters())
|
|---|
| 445 | fixed = list(self.fitter.getfixedparameters())
|
|---|
| [1075] | 446 | errs = list(self.fitter.geterrors())
|
|---|
| [1039] | 447 | area = []
|
|---|
| [723] | 448 | if component is not None:
|
|---|
| [2047] | 449 | if self.fitfunc == "poly" or self.fitfunc == "lpoly":
|
|---|
| 450 | cpars = pars
|
|---|
| 451 | cfixed = fixed
|
|---|
| 452 | cerrs = errs
|
|---|
| 453 | else:
|
|---|
| [515] | 454 | i = 3*component
|
|---|
| 455 | cpars = pars[i:i+3]
|
|---|
| 456 | cfixed = fixed[i:i+3]
|
|---|
| [1075] | 457 | cerrs = errs[i:i+3]
|
|---|
| [2047] | 458 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| 459 | a = self.get_area(component)
|
|---|
| 460 | area = [a for i in range(3)]
|
|---|
| [515] | 461 | else:
|
|---|
| 462 | cpars = pars
|
|---|
| 463 | cfixed = fixed
|
|---|
| [1075] | 464 | cerrs = errs
|
|---|
| [1819] | 465 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| [1039] | 466 | for c in range(len(self.components)):
|
|---|
| [2047] | 467 | a = self.get_area(c)
|
|---|
| 468 | area += [a for i in range(3)]
|
|---|
| [1088] | 469 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area)
|
|---|
| [1859] | 470 | asaplog.push(fpars)
|
|---|
| [1075] | 471 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars,
|
|---|
| 472 | 'errors':cerrs}
|
|---|
| [723] | 473 |
|
|---|
| [1075] | 474 | def _format_pars(self, pars, fixed, errors, area):
|
|---|
| [113] | 475 | out = ''
|
|---|
| [2047] | 476 | if self.fitfunc == "poly" or self.fitfunc == "lpoly":
|
|---|
| [113] | 477 | c = 0
|
|---|
| [515] | 478 | for i in range(len(pars)):
|
|---|
| 479 | fix = ""
|
|---|
| [1232] | 480 | if len(fixed) and fixed[i]: fix = "(fixed)"
|
|---|
| [2047] | 481 | out += " p%d%s= %3.6f" % (c, fix, pars[i])
|
|---|
| 482 | if errors : out += " (%1.6f)" % errors[i]
|
|---|
| 483 | out += ","
|
|---|
| [113] | 484 | c+=1
|
|---|
| [515] | 485 | out = out[:-1] # remove trailing ','
|
|---|
| [2047] | 486 | else:
|
|---|
| [113] | 487 | i = 0
|
|---|
| 488 | c = 0
|
|---|
| [2047] | 489 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz":
|
|---|
| 490 | pnam = ["peak", "centre", "FWHM"]
|
|---|
| 491 | elif self.fitfunc == "sinusoid":
|
|---|
| 492 | pnam = ["amplitude", "period", "x0"]
|
|---|
| 493 | aunit = ""
|
|---|
| 494 | ounit = ""
|
|---|
| [113] | 495 | if self.data:
|
|---|
| [515] | 496 | aunit = self.data.get_unit()
|
|---|
| 497 | ounit = self.data.get_fluxunit()
|
|---|
| [113] | 498 | while i < len(pars):
|
|---|
| [2047] | 499 | fix0 = fix1 = fix2 = ""
|
|---|
| 500 | if i < len(fixed)-2:
|
|---|
| 501 | if fixed[i]: fix0 = "(fixed)"
|
|---|
| 502 | if fixed[i+1]: fix1 = "(fixed)"
|
|---|
| 503 | if fixed[i+2]: fix2 = "(fixed)"
|
|---|
| 504 | out += " %2d: " % c
|
|---|
| 505 | out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit)
|
|---|
| 506 | out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit)
|
|---|
| 507 | out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit)
|
|---|
| [2666] | 508 | if len(area): out += " area = %3.3f %s %s\n" % (area[i],
|
|---|
| 509 | ounit,
|
|---|
| 510 | aunit)
|
|---|
| [113] | 511 | c+=1
|
|---|
| 512 | i+=3
|
|---|
| 513 | return out
|
|---|
| [723] | 514 |
|
|---|
| [1859] | 515 |
|
|---|
| [1862] | 516 | @asaplog_post_dec
|
|---|
| [113] | 517 | def get_estimate(self):
|
|---|
| 518 | """
|
|---|
| [515] | 519 | Return the parameter estimates (for non-linear functions).
|
|---|
| [113] | 520 | """
|
|---|
| 521 | pars = self.fitter.getestimate()
|
|---|
| [943] | 522 | fixed = self.fitter.getfixedparameters()
|
|---|
| [1927] | 523 | asaplog.push(self._format_pars(pars,fixed,None,None))
|
|---|
| [113] | 524 | return pars
|
|---|
| 525 |
|
|---|
| [1862] | 526 | @asaplog_post_dec
|
|---|
| [113] | 527 | def get_residual(self):
|
|---|
| 528 | """
|
|---|
| 529 | Return the residual of the fit.
|
|---|
| 530 | """
|
|---|
| 531 | if not self.fitted:
|
|---|
| [723] | 532 | msg = "Not yet fitted."
|
|---|
| [1859] | 533 | raise RuntimeError(msg)
|
|---|
| [113] | 534 | return self.fitter.getresidual()
|
|---|
| 535 |
|
|---|
| [1862] | 536 | @asaplog_post_dec
|
|---|
| [113] | 537 | def get_chi2(self):
|
|---|
| 538 | """
|
|---|
| 539 | Return chi^2.
|
|---|
| 540 | """
|
|---|
| 541 | if not self.fitted:
|
|---|
| [723] | 542 | msg = "Not yet fitted."
|
|---|
| [1859] | 543 | raise RuntimeError(msg)
|
|---|
| [113] | 544 | ch2 = self.fitter.getchi2()
|
|---|
| [1859] | 545 | asaplog.push( 'Chi^2 = %3.3f' % (ch2) )
|
|---|
| [723] | 546 | return ch2
|
|---|
| [113] | 547 |
|
|---|
| [1862] | 548 | @asaplog_post_dec
|
|---|
| [113] | 549 | def get_fit(self):
|
|---|
| 550 | """
|
|---|
| 551 | Return the fitted ordinate values.
|
|---|
| 552 | """
|
|---|
| 553 | if not self.fitted:
|
|---|
| [723] | 554 | msg = "Not yet fitted."
|
|---|
| [1859] | 555 | raise RuntimeError(msg)
|
|---|
| [113] | 556 | return self.fitter.getfit()
|
|---|
| 557 |
|
|---|
| [1862] | 558 | @asaplog_post_dec
|
|---|
| [113] | 559 | def commit(self):
|
|---|
| 560 | """
|
|---|
| [526] | 561 | Return a new scan where the fits have been commited (subtracted)
|
|---|
| [113] | 562 | """
|
|---|
| 563 | if not self.fitted:
|
|---|
| [723] | 564 | msg = "Not yet fitted."
|
|---|
| [1859] | 565 | raise RuntimeError(msg)
|
|---|
| [975] | 566 | from asap import scantable
|
|---|
| 567 | if not isinstance(self.data, scantable):
|
|---|
| [723] | 568 | msg = "Not a scantable"
|
|---|
| [1859] | 569 | raise TypeError(msg)
|
|---|
| [113] | 570 | scan = self.data.copy()
|
|---|
| [259] | 571 | scan._setspectrum(self.fitter.getresidual())
|
|---|
| [1092] | 572 | return scan
|
|---|
| [113] | 573 |
|
|---|
| [1862] | 574 | @asaplog_post_dec
|
|---|
| [1689] | 575 | def plot(self, residual=False, components=None, plotparms=False,
|
|---|
| 576 | filename=None):
|
|---|
| [113] | 577 | """
|
|---|
| 578 | Plot the last fit.
|
|---|
| 579 | Parameters:
|
|---|
| 580 | residual: an optional parameter indicating if the residual
|
|---|
| 581 | should be plotted (default 'False')
|
|---|
| [526] | 582 | components: a list of components to plot, e.g [0,1],
|
|---|
| 583 | -1 plots the total fit. Default is to only
|
|---|
| 584 | plot the total fit.
|
|---|
| 585 | plotparms: Inidicates if the parameter values should be present
|
|---|
| 586 | on the plot
|
|---|
| [113] | 587 | """
|
|---|
| [2538] | 588 | from matplotlib import rc as rcp
|
|---|
| [113] | 589 | if not self.fitted:
|
|---|
| 590 | return
|
|---|
| [2541] | 591 | #if not self._p or self._p.is_dead:
|
|---|
| 592 | if not (self._p and self._p._alive()):
|
|---|
| [2150] | 593 | from asap.asapplotter import new_asaplot
|
|---|
| [2451] | 594 | del self._p
|
|---|
| [2150] | 595 | self._p = new_asaplot(rcParams['plotter.gui'])
|
|---|
| [723] | 596 | self._p.hold()
|
|---|
| [113] | 597 | self._p.clear()
|
|---|
| [2535] | 598 | rcp('lines', linewidth=1)
|
|---|
| [515] | 599 | self._p.set_panels()
|
|---|
| [652] | 600 | self._p.palette(0)
|
|---|
| [113] | 601 | tlab = 'Spectrum'
|
|---|
| [723] | 602 | xlab = 'Abcissa'
|
|---|
| [1017] | 603 | ylab = 'Ordinate'
|
|---|
| [1739] | 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)
|
|---|
| [2153] | 609 | if self.data._getflagrow(self._fittedrow):
|
|---|
| 610 | m = [False]
|
|---|
| 611 | else:
|
|---|
| 612 | m = logical_and(self.mask,
|
|---|
| 613 | array(self.data._getmask(self._fittedrow),
|
|---|
| 614 | copy=False))
|
|---|
| [1589] | 615 |
|
|---|
| [626] | 616 | ylab = self.data._get_ordinate_label()
|
|---|
| [515] | 617 |
|
|---|
| [2666] | 618 | colours = ["#777777","#dddddd","red","orange","purple","green",
|
|---|
| 619 | "magenta", "cyan"]
|
|---|
| [1819] | 620 | nomask=True
|
|---|
| 621 | for i in range(len(m)):
|
|---|
| 622 | nomask = nomask and m[i]
|
|---|
| [2153] | 623 | if len(m) == 1:
|
|---|
| 624 | m = m[0]
|
|---|
| 625 | invm = (not m)
|
|---|
| 626 | else:
|
|---|
| 627 | invm = logical_not(m)
|
|---|
| [1819] | 628 | label0='Masked Region'
|
|---|
| 629 | label1='Spectrum'
|
|---|
| 630 | if ( nomask ):
|
|---|
| 631 | label0=label1
|
|---|
| 632 | else:
|
|---|
| 633 | y = ma.masked_array( self.y, mask = m )
|
|---|
| 634 | self._p.palette(1,colours)
|
|---|
| 635 | self._p.set_line( label = label1 )
|
|---|
| 636 | self._p.plot( self.x, y )
|
|---|
| [652] | 637 | self._p.palette(0,colours)
|
|---|
| [1819] | 638 | self._p.set_line(label=label0)
|
|---|
| [2153] | 639 | y = ma.masked_array(self.y,mask=invm)
|
|---|
| [1088] | 640 | self._p.plot(self.x, y)
|
|---|
| [113] | 641 | if residual:
|
|---|
| [1819] | 642 | self._p.palette(7)
|
|---|
| [515] | 643 | self._p.set_line(label='Residual')
|
|---|
| [1116] | 644 | y = ma.masked_array(self.get_residual(),
|
|---|
| [2153] | 645 | mask=invm)
|
|---|
| [1088] | 646 | self._p.plot(self.x, y)
|
|---|
| [652] | 647 | self._p.palette(2)
|
|---|
| [515] | 648 | if components is not None:
|
|---|
| 649 | cs = components
|
|---|
| 650 | if isinstance(components,int): cs = [components]
|
|---|
| [526] | 651 | if plotparms:
|
|---|
| [2666] | 652 | self._p.text(0.15,0.15,
|
|---|
| 653 | str(self.get_parameters()['formatted']),size=8)
|
|---|
| [515] | 654 | n = len(self.components)
|
|---|
| [652] | 655 | self._p.palette(3)
|
|---|
| [515] | 656 | for c in cs:
|
|---|
| 657 | if 0 <= c < n:
|
|---|
| 658 | lab = self.fitfuncs[c]+str(c)
|
|---|
| 659 | self._p.set_line(label=lab)
|
|---|
| [2153] | 660 | y = ma.masked_array(self.fitter.evaluate(c), mask=invm)
|
|---|
| [1088] | 661 |
|
|---|
| 662 | self._p.plot(self.x, y)
|
|---|
| [515] | 663 | elif c == -1:
|
|---|
| [652] | 664 | self._p.palette(2)
|
|---|
| [515] | 665 | self._p.set_line(label="Total Fit")
|
|---|
| [1116] | 666 | y = ma.masked_array(self.fitter.getfit(),
|
|---|
| [2153] | 667 | mask=invm)
|
|---|
| [1088] | 668 | self._p.plot(self.x, y)
|
|---|
| [515] | 669 | else:
|
|---|
| [652] | 670 | self._p.palette(2)
|
|---|
| [515] | 671 | self._p.set_line(label='Fit')
|
|---|
| [2153] | 672 | y = ma.masked_array(self.fitter.getfit(),mask=invm)
|
|---|
| [1088] | 673 | self._p.plot(self.x, y)
|
|---|
| [723] | 674 | xlim=[min(self.x),max(self.x)]
|
|---|
| 675 | self._p.axes.set_xlim(xlim)
|
|---|
| [113] | 676 | self._p.set_axes('xlabel',xlab)
|
|---|
| 677 | self._p.set_axes('ylabel',ylab)
|
|---|
| 678 | self._p.set_axes('title',tlab)
|
|---|
| 679 | self._p.release()
|
|---|
| [723] | 680 | if (not rcParams['plotter.gui']):
|
|---|
| 681 | self._p.save(filename)
|
|---|
| [113] | 682 |
|
|---|
| [1862] | 683 | @asaplog_post_dec
|
|---|
| [1061] | 684 | def auto_fit(self, insitu=None, plot=False):
|
|---|
| [113] | 685 | """
|
|---|
| [515] | 686 | Return a scan where the function is applied to all rows for
|
|---|
| 687 | all Beams/IFs/Pols.
|
|---|
| [723] | 688 |
|
|---|
| [113] | 689 | """
|
|---|
| 690 | from asap import scantable
|
|---|
| [515] | 691 | if not isinstance(self.data, scantable) :
|
|---|
| [723] | 692 | msg = "Data is not a scantable"
|
|---|
| [1859] | 693 | raise TypeError(msg)
|
|---|
| [259] | 694 | if insitu is None: insitu = rcParams['insitu']
|
|---|
| 695 | if not insitu:
|
|---|
| 696 | scan = self.data.copy()
|
|---|
| 697 | else:
|
|---|
| 698 | scan = self.data
|
|---|
| [880] | 699 | rows = xrange(scan.nrow())
|
|---|
| [1826] | 700 | # Save parameters of baseline fits as a class attribute.
|
|---|
| [1819] | 701 | # NOTICE: This does not reflect changes in scantable!
|
|---|
| 702 | if len(rows) > 0: self.blpars=[]
|
|---|
| [876] | 703 | asaplog.push("Fitting:")
|
|---|
| 704 | for r in rows:
|
|---|
| [2666] | 705 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (
|
|---|
| 706 | scan.getscan(r),
|
|---|
| 707 | scan.getbeam(r),
|
|---|
| 708 | scan.getif(r),
|
|---|
| 709 | scan.getpol(r),
|
|---|
| 710 | scan.getcycle(r)
|
|---|
| 711 | )
|
|---|
| [880] | 712 | asaplog.push(out, False)
|
|---|
| [876] | 713 | self.x = scan._getabcissa(r)
|
|---|
| 714 | self.y = scan._getspectrum(r)
|
|---|
| [2409] | 715 | #self.mask = mask_and(self.mask, scan._getmask(r))
|
|---|
| [2408] | 716 | if len(self.x) == len(self.mask):
|
|---|
| 717 | self.mask = mask_and(self.mask, self.data._getmask(row))
|
|---|
| 718 | else:
|
|---|
| [2666] | 719 | asaplog.push('lengths of data and mask are not the same. '
|
|---|
| 720 | 'preset mask will be ignored')
|
|---|
| [2408] | 721 | asaplog.post('WARN','asapfit.fit')
|
|---|
| [2409] | 722 | self.mask=self.data._getmask(row)
|
|---|
| [876] | 723 | self.data = None
|
|---|
| 724 | self.fit()
|
|---|
| 725 | x = self.get_parameters()
|
|---|
| [1819] | 726 | fpar = self.get_parameters()
|
|---|
| [1061] | 727 | if plot:
|
|---|
| 728 | self.plot(residual=True)
|
|---|
| 729 | x = raw_input("Accept fit ([y]/n): ")
|
|---|
| 730 | if x.upper() == 'N':
|
|---|
| [1819] | 731 | self.blpars.append(None)
|
|---|
| [1061] | 732 | continue
|
|---|
| [880] | 733 | scan._setspectrum(self.fitter.getresidual(), r)
|
|---|
| [1819] | 734 | self.blpars.append(fpar)
|
|---|
| [1061] | 735 | if plot:
|
|---|
| [2151] | 736 | self._p.quit()
|
|---|
| 737 | del self._p
|
|---|
| [1061] | 738 | self._p = None
|
|---|
| [876] | 739 | return scan
|
|---|
