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