| 1 | import _asap |
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| 2 | from asap import rcParams |
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| 3 | |
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| 4 | class fitter: |
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| 5 | """ |
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| 6 | The fitting class for ASAP. |
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| 7 | """ |
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| 8 | def _verbose(self, *args): |
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| 9 | """ |
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| 10 | Set stdout output. |
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| 11 | """ |
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| 12 | if type(args[0]) is bool: |
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| 13 | self._vb = args[0] |
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| 14 | return |
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| 15 | elif len(args) == 0: |
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| 16 | return self._vb |
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| 17 | |
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| 18 | def __init__(self): |
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| 19 | """ |
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| 20 | Create a fitter object. No state is set. |
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| 21 | """ |
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| 22 | self.fitter = _asap.fitter() |
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| 23 | self.x = None |
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| 24 | self.y = None |
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| 25 | self.mask = None |
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| 26 | self.fitfunc = None |
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| 27 | self.fitfuncs = None |
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| 28 | self.fitted = False |
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| 29 | self.data = None |
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| 30 | self.components = 0 |
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| 31 | self._fittedrow = 0 |
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| 32 | self._p = None |
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| 33 | self._vb = True |
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| 34 | self._selection = None |
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| 35 | |
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| 36 | def set_data(self, xdat, ydat, mask=None): |
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| 37 | """ |
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| 38 | Set the absissa and ordinate for the fit. Also set the mask |
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| 39 | indicationg valid points. |
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| 40 | This can be used for data vectors retrieved from a scantable. |
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| 41 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
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| 42 | Parameters: |
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| 43 | xdat: the abcissa values |
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| 44 | ydat: the ordinate values |
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| 45 | mask: an optional mask |
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| 46 | |
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| 47 | """ |
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| 48 | self.fitted = False |
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| 49 | self.x = xdat |
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| 50 | self.y = ydat |
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| 51 | if mask == None: |
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| 52 | from numarray import ones |
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| 53 | self.mask = ones(len(xdat)) |
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| 54 | else: |
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| 55 | self.mask = mask |
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| 56 | return |
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| 57 | |
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| 58 | def set_scan(self, thescan=None, mask=None): |
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| 59 | """ |
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| 60 | Set the 'data' (a scantable) of the fitter. |
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| 61 | Parameters: |
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| 62 | thescan: a scantable |
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| 63 | mask: a msk retireved from the scantable |
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| 64 | """ |
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| 65 | if not thescan: |
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| 66 | print "Please give a correct scan" |
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| 67 | self.fitted = False |
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| 68 | self.data = thescan |
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| 69 | if mask is None: |
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| 70 | from numarray import ones |
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| 71 | self.mask = ones(self.data.nchan()) |
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| 72 | else: |
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| 73 | self.mask = mask |
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| 74 | return |
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| 75 | |
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| 76 | def set_function(self, **kwargs): |
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| 77 | """ |
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| 78 | Set the function to be fit. |
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| 79 | Parameters: |
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| 80 | poly: use a polynomial of the order given |
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| 81 | gauss: fit the number of gaussian specified |
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| 82 | Example: |
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| 83 | fitter.set_function(gauss=2) # will fit two gaussians |
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| 84 | fitter.set_function(poly=3) # will fit a 3rd order polynomial |
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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 | elif kwargs.has_key('gauss'): |
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| 93 | n = kwargs.get('gauss') |
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| 94 | self.fitfunc = 'gauss' |
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| 95 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
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| 96 | self.components = [ 3 for i in range(n) ] |
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| 97 | else: |
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| 98 | print "Invalid function type." |
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| 99 | return |
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| 100 | self.fitter.setexpression(self.fitfunc,n) |
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| 101 | return |
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| 102 | |
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| 103 | def fit(self, row=0): |
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| 104 | """ |
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| 105 | Execute the actual fitting process. All the state has to be set. |
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| 106 | Parameters: |
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| 107 | row: specify the row in the scantable |
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| 108 | Example: |
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| 109 | s = scantable('myscan.asap') |
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| 110 | s.set_cursor(thepol=1) # select second pol |
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| 111 | f = fitter() |
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| 112 | f.set_scan(s) |
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| 113 | f.set_function(poly=0) |
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| 114 | f.fit(row=0) # fit first row |
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| 115 | """ |
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| 116 | if ((self.x is None or self.y is None) and self.data is None) \ |
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| 117 | or self.fitfunc is None: |
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| 118 | print "Fitter not yet initialised. Please set data & fit function" |
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| 119 | return |
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| 120 | else: |
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| 121 | if self.data is not None: |
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| 122 | self.x = self.data._getabcissa(row) |
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| 123 | self.y = self.data._getspectrum(row) |
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| 124 | print "Fitting:" |
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| 125 | vb = self.data._vb |
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| 126 | self.data._vb = True |
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| 127 | self.selection = self.data.get_cursor() |
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| 128 | self.data._vb = vb |
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| 129 | self.fitter.setdata(self.x, self.y, self.mask) |
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| 130 | if self.fitfunc == 'gauss': |
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| 131 | ps = self.fitter.getparameters() |
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| 132 | if len(ps) == 0: |
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| 133 | self.fitter.estimate() |
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| 134 | try: |
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| 135 | self.fitter.fit() |
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| 136 | except RuntimeError, msg: |
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| 137 | print msg |
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| 138 | self._fittedrow = row |
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| 139 | self.fitted = True |
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| 140 | return |
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| 141 | |
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| 142 | def store_fit(self): |
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| 143 | """ |
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| 144 | Store the fit parameters in the scantable. |
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| 145 | """ |
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| 146 | if self.fitted and self.data is not None: |
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| 147 | pars = list(self.fitter.getparameters()) |
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| 148 | fixed = list(self.fitter.getfixedparameters()) |
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| 149 | self.data._addfit(self._fittedrow, pars, fixed, |
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| 150 | self.fitfuncs, self.components) |
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| 151 | |
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| 152 | def set_parameters(self, params, fixed=None, component=None): |
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| 153 | """ |
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| 154 | Set the parameters to be fitted. |
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| 155 | Parameters: |
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| 156 | params: a vector of parameters |
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| 157 | fixed: a vector of which parameters are to be held fixed |
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| 158 | (default is none) |
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| 159 | component: in case of multiple gaussians, the index of the |
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| 160 | component |
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| 161 | """ |
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| 162 | if self.fitfunc is None: |
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| 163 | print "Please specify a fitting function first." |
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| 164 | return |
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| 165 | if self.fitfunc == "gauss" and component is not None: |
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| 166 | if not self.fitted: |
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| 167 | from numarray import zeros |
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| 168 | pars = list(zeros(len(self.components)*3)) |
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| 169 | fxd = list(zeros(len(pars))) |
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| 170 | else: |
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| 171 | pars = list(self.fitter.getparameters()) |
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| 172 | fxd = list(self.fitter.getfixedparameters()) |
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| 173 | i = 3*component |
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| 174 | pars[i:i+3] = params |
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| 175 | fxd[i:i+3] = fixed |
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| 176 | params = pars |
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| 177 | fixed = fxd |
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| 178 | self.fitter.setparameters(params) |
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| 179 | if fixed is not None: |
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| 180 | self.fitter.setfixedparameters(fixed) |
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| 181 | return |
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| 182 | |
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| 183 | def set_gauss_parameters(self, peak, centre, fhwm, |
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| 184 | peakfixed=False, centerfixed=False, |
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| 185 | fhwmfixed=False, |
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| 186 | component=0): |
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| 187 | """ |
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| 188 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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| 189 | Parameters: |
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| 190 | peak, centre, fhwm: The gaussian parameters |
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| 191 | peakfixed, |
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| 192 | centerfixed, |
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| 193 | fhwmfixed: Optional parameters to indicate if |
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| 194 | the paramters should be held fixed during |
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| 195 | the fitting process. The default is to keep |
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| 196 | all parameters flexible. |
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| 197 | component: The number of the component (Default is the |
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| 198 | component 0) |
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| 199 | """ |
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| 200 | if self.fitfunc != "gauss": |
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| 201 | print "Function only operates on Gaussian components." |
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| 202 | return |
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| 203 | if 0 <= component < len(self.components): |
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| 204 | self.set_parameters([peak, centre, fhwm], |
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| 205 | [peakfixed, centerfixed, fhwmfixed], |
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| 206 | component) |
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| 207 | else: |
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| 208 | print "Please select a valid component." |
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| 209 | return |
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| 210 | |
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| 211 | def get_parameters(self, component=None): |
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| 212 | """ |
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| 213 | Return the fit paramters. |
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| 214 | Parameters: |
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| 215 | component: get the parameters for the specified component |
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| 216 | only, default is all components |
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| 217 | """ |
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| 218 | if not self.fitted: |
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| 219 | print "Not yet fitted." |
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| 220 | pars = list(self.fitter.getparameters()) |
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| 221 | fixed = list(self.fitter.getfixedparameters()) |
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| 222 | if component is not None: |
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| 223 | if self.fitfunc == "gauss": |
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| 224 | i = 3*component |
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| 225 | cpars = pars[i:i+3] |
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| 226 | cfixed = fixed[i:i+3] |
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| 227 | else: |
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| 228 | cpars = pars |
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| 229 | cfixed = fixed |
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| 230 | else: |
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| 231 | cpars = pars |
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| 232 | cfixed = fixed |
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| 233 | fpars = self._format_pars(cpars, cfixed) |
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| 234 | if self._vb: |
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| 235 | print fpars |
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| 236 | return cpars, cfixed, fpars |
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| 237 | |
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| 238 | def _format_pars(self, pars, fixed): |
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| 239 | out = '' |
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| 240 | if self.fitfunc == 'poly': |
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| 241 | c = 0 |
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| 242 | for i in range(len(pars)): |
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| 243 | fix = "" |
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| 244 | if fixed[i]: fix = "(fixed)" |
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| 245 | out += ' p%d%s= %3.3f,' % (c,fix,pars[i]) |
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| 246 | c+=1 |
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| 247 | out = out[:-1] # remove trailing ',' |
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| 248 | elif self.fitfunc == 'gauss': |
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| 249 | i = 0 |
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| 250 | c = 0 |
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| 251 | aunit = '' |
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| 252 | ounit = '' |
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| 253 | if self.data: |
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| 254 | aunit = self.data.get_unit() |
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| 255 | ounit = self.data.get_fluxunit() |
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| 256 | while i < len(pars): |
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| 257 | out += ' %d: 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) |
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| 258 | c+=1 |
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| 259 | i+=3 |
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| 260 | return out |
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| 261 | |
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| 262 | def get_estimate(self): |
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| 263 | """ |
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| 264 | Return the parameter estimates (for non-linear functions). |
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| 265 | """ |
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| 266 | pars = self.fitter.getestimate() |
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| 267 | if self._vb: |
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| 268 | print self._format_pars(pars) |
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| 269 | return pars |
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| 270 | |
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| 271 | |
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| 272 | def get_residual(self): |
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| 273 | """ |
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| 274 | Return the residual of the fit. |
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| 275 | """ |
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| 276 | if not self.fitted: |
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| 277 | print "Not yet fitted." |
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| 278 | return self.fitter.getresidual() |
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| 279 | |
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| 280 | def get_chi2(self): |
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| 281 | """ |
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| 282 | Return chi^2. |
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| 283 | """ |
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| 284 | if not self.fitted: |
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| 285 | print "Not yet fitted." |
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| 286 | ch2 = self.fitter.getchi2() |
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| 287 | if self._vb: |
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| 288 | print 'Chi^2 = %3.3f' % (ch2) |
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| 289 | return ch2 |
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| 290 | |
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| 291 | def get_fit(self): |
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| 292 | """ |
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| 293 | Return the fitted ordinate values. |
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| 294 | """ |
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| 295 | if not self.fitted: |
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| 296 | print "Not yet fitted." |
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| 297 | return self.fitter.getfit() |
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| 298 | |
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| 299 | def commit(self): |
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| 300 | """ |
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| 301 | Return a new scan where the fits have been commited (subtracted) |
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| 302 | """ |
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| 303 | if not self.fitted: |
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| 304 | print "Not yet fitted." |
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| 305 | if self.data is not scantable: |
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| 306 | print "Only works with scantables" |
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| 307 | return |
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| 308 | scan = self.data.copy() |
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| 309 | scan._setspectrum(self.fitter.getresidual()) |
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| 310 | |
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| 311 | def plot(self, residual=False, components=None, plotparms=False): |
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| 312 | """ |
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| 313 | Plot the last fit. |
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| 314 | Parameters: |
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| 315 | residual: an optional parameter indicating if the residual |
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| 316 | should be plotted (default 'False') |
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| 317 | components: a list of components to plot, e.g [0,1], |
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| 318 | -1 plots the total fit. Default is to only |
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| 319 | plot the total fit. |
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| 320 | plotparms: Inidicates if the parameter values should be present |
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| 321 | on the plot |
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| 322 | """ |
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| 323 | if not self.fitted: |
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| 324 | return |
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| 325 | if not self._p: |
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| 326 | from asap.asaplot import ASAPlot |
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| 327 | self._p = ASAPlot() |
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| 328 | if self._p.is_dead: |
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| 329 | from asap.asaplot import ASAPlot |
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| 330 | self._p = ASAPlot() |
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| 331 | self._p.clear() |
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| 332 | self._p.set_panels() |
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| 333 | self._p.palette(0) |
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| 334 | tlab = 'Spectrum' |
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| 335 | xlab = 'Abcissa' |
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| 336 | m = () |
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| 337 | if self.data: |
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| 338 | tlab = self.data._getsourcename(self._fittedrow) |
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| 339 | xlab = self.data._getabcissalabel(self._fittedrow) |
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| 340 | m = self.data._getmask(self._fittedrow) |
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| 341 | ylab = self.data._get_ordinate_label() |
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| 342 | |
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| 343 | colours = ["grey60","grey80","red","orange","purple","green","magenta", "cyan"] |
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| 344 | self._p.palette(0,colours) |
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| 345 | self._p.set_line(label='Spectrum') |
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| 346 | self._p.plot(self.x, self.y, m) |
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| 347 | if residual: |
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| 348 | self._p.palette(1) |
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| 349 | self._p.set_line(label='Residual') |
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| 350 | self._p.plot(self.x, self.get_residual(), m) |
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| 351 | self._p.palette(2) |
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| 352 | if components is not None: |
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| 353 | cs = components |
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| 354 | if isinstance(components,int): cs = [components] |
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| 355 | if plotparms: |
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| 356 | self._p.text(0.15,0.15,str(self.get_parameters()[2]),size=8) |
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| 357 | n = len(self.components) |
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| 358 | self._p.palette(3) |
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| 359 | for c in cs: |
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| 360 | if 0 <= c < n: |
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| 361 | lab = self.fitfuncs[c]+str(c) |
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| 362 | self._p.set_line(label=lab) |
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| 363 | self._p.plot(self.x, self.fitter.evaluate(c), m) |
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| 364 | elif c == -1: |
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| 365 | self._p.palette(2) |
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| 366 | self._p.set_line(label="Total Fit") |
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| 367 | self._p.plot(self.x, self.get_fit(), m) |
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| 368 | else: |
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| 369 | self._p.palette(2) |
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| 370 | self._p.set_line(label='Fit') |
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| 371 | self._p.plot(self.x, self.get_fit(), m) |
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| 372 | self._p.set_axes('xlabel',xlab) |
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| 373 | self._p.set_axes('ylabel',ylab) |
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| 374 | self._p.set_axes('title',tlab) |
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| 375 | self._p.release() |
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| 376 | |
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| 377 | def auto_fit(self, insitu=None): |
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| 378 | """ |
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| 379 | Return a scan where the function is applied to all rows for |
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| 380 | all Beams/IFs/Pols. |
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| 381 | |
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| 382 | """ |
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| 383 | from asap import scantable |
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| 384 | if not isinstance(self.data, scantable) : |
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| 385 | print "Only works with scantables" |
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| 386 | return |
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| 387 | if insitu is None: insitu = rcParams['insitu'] |
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| 388 | if not insitu: |
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| 389 | scan = self.data.copy() |
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| 390 | else: |
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| 391 | scan = self.data |
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| 392 | vb = scan._vb |
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| 393 | scan._vb = False |
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| 394 | sel = scan.get_cursor() |
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| 395 | rows = range(scan.nrow()) |
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| 396 | for i in range(scan.nbeam()): |
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| 397 | scan.setbeam(i) |
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| 398 | for j in range(scan.nif()): |
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| 399 | scan.setif(j) |
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| 400 | for k in range(scan.npol()): |
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| 401 | scan.setpol(k) |
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| 402 | if self._vb: |
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| 403 | print "Fitting:" |
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| 404 | print 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k) |
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| 405 | for iRow in rows: |
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| 406 | self.x = scan._getabcissa(iRow) |
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| 407 | self.y = scan._getspectrum(iRow) |
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| 408 | self.data = None |
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| 409 | self.fit() |
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| 410 | x = self.get_parameters() |
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| 411 | scan._setspectrum(self.fitter.getresidual(),iRow) |
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| 412 | scan.set_cursor(sel[0],sel[1],sel[2]) |
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| 413 | scan._vb = vb |
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| 414 | if not insitu: |
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| 415 | return scan |
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