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