[113] | 1 | import _asap |
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[259] | 2 | from asap import rcParams |
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[723] | 3 | from asap import print_log |
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[1134] | 4 | from asap import NUM |
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[113] | 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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[723] | 10 | |
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[113] | 11 | def __init__(self): |
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| 12 | """ |
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| 13 | Create a fitter object. No state is set. |
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| 14 | """ |
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| 15 | self.fitter = _asap.fitter() |
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| 16 | self.x = None |
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| 17 | self.y = None |
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| 18 | self.mask = None |
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| 19 | self.fitfunc = None |
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[515] | 20 | self.fitfuncs = None |
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[113] | 21 | self.fitted = False |
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| 22 | self.data = None |
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[515] | 23 | self.components = 0 |
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| 24 | self._fittedrow = 0 |
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[113] | 25 | self._p = None |
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[515] | 26 | self._selection = None |
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[113] | 27 | |
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| 28 | def set_data(self, xdat, ydat, mask=None): |
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| 29 | """ |
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[158] | 30 | Set the absissa and ordinate for the fit. Also set the mask |
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[113] | 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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[158] | 35 | xdat: the abcissa values |
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[113] | 36 | ydat: the ordinate values |
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| 37 | mask: an optional mask |
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[723] | 38 | |
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[113] | 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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[1134] | 44 | self.mask = NUM.ones(len(xdat)) |
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[113] | 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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[723] | 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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[113] | 63 | self.fitted = False |
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| 64 | self.data = thescan |
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[1075] | 65 | self.mask = None |
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[113] | 66 | if mask is None: |
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[1134] | 67 | self.mask = NUM.ones(self.data.nchan()) |
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[113] | 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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[723] | 82 | #default poly order 0 |
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[515] | 83 | n=0 |
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[113] | 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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[515] | 87 | self.components = [n] |
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[113] | 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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[515] | 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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[723] | 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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[113] | 101 | self.fitter.setexpression(self.fitfunc,n) |
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| 102 | return |
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[723] | 103 | |
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[1075] | 104 | def fit(self, row=0, estimate=False): |
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[113] | 105 | """ |
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| 106 | Execute the actual fitting process. All the state has to be set. |
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| 107 | Parameters: |
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[1075] | 108 | row: specify the row in the scantable |
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| 109 | estimate: auto-compute an initial parameter set (default False) |
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| 110 | This can be used to compute estimates even if fit was |
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| 111 | called before. |
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[113] | 112 | Example: |
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[515] | 113 | s = scantable('myscan.asap') |
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| 114 | s.set_cursor(thepol=1) # select second pol |
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[113] | 115 | f = fitter() |
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| 116 | f.set_scan(s) |
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| 117 | f.set_function(poly=0) |
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[723] | 118 | f.fit(row=0) # fit first row |
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[113] | 119 | """ |
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| 120 | if ((self.x is None or self.y is None) and self.data is None) \ |
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| 121 | or self.fitfunc is None: |
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[723] | 122 | msg = "Fitter not yet initialised. Please set data & fit function" |
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| 123 | if rcParams['verbose']: |
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| 124 | print msg |
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| 125 | return |
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| 126 | else: |
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| 127 | raise RuntimeError(msg) |
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| 128 | |
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[113] | 129 | else: |
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| 130 | if self.data is not None: |
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[515] | 131 | self.x = self.data._getabcissa(row) |
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| 132 | self.y = self.data._getspectrum(row) |
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[723] | 133 | from asap import asaplog |
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| 134 | asaplog.push("Fitting:") |
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[943] | 135 | i = row |
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| 136 | 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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[1075] | 137 | asaplog.push(out,False) |
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[515] | 138 | self.fitter.setdata(self.x, self.y, self.mask) |
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[113] | 139 | if self.fitfunc == 'gauss': |
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| 140 | ps = self.fitter.getparameters() |
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[1075] | 141 | if len(ps) == 0 or estimate: |
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[113] | 142 | self.fitter.estimate() |
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[626] | 143 | try: |
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[1075] | 144 | converged = self.fitter.fit() |
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| 145 | if not converged: |
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| 146 | raise RuntimeError,"Fit didn't converge." |
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[626] | 147 | except RuntimeError, msg: |
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[723] | 148 | if rcParams['verbose']: |
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| 149 | print msg |
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| 150 | else: |
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| 151 | raise |
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[515] | 152 | self._fittedrow = row |
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[113] | 153 | self.fitted = True |
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[723] | 154 | print_log() |
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[113] | 155 | return |
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| 156 | |
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[515] | 157 | def store_fit(self): |
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[526] | 158 | """ |
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| 159 | Store the fit parameters in the scantable. |
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| 160 | """ |
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[515] | 161 | if self.fitted and self.data is not None: |
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| 162 | pars = list(self.fitter.getparameters()) |
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| 163 | fixed = list(self.fitter.getfixedparameters()) |
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[975] | 164 | from asap.asapfit import asapfit |
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| 165 | fit = asapfit() |
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| 166 | fit.setparameters(pars) |
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| 167 | fit.setfixedparameters(fixed) |
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| 168 | fit.setfunctions(self.fitfuncs) |
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| 169 | fit.setcomponents(self.components) |
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| 170 | fit.setframeinfo(self.data._getcoordinfo()) |
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| 171 | self.data._addfit(fit,self._fittedrow) |
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[515] | 172 | |
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[1017] | 173 | #def set_parameters(self, params, fixed=None, component=None): |
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| 174 | def set_parameters(self,*args,**kwargs): |
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[526] | 175 | """ |
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| 176 | Set the parameters to be fitted. |
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| 177 | Parameters: |
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| 178 | params: a vector of parameters |
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| 179 | fixed: a vector of which parameters are to be held fixed |
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| 180 | (default is none) |
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| 181 | component: in case of multiple gaussians, the index of the |
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| 182 | component |
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[1017] | 183 | """ |
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| 184 | component = None |
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| 185 | fixed = None |
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| 186 | params = None |
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[1031] | 187 | |
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[1017] | 188 | if len(args) and isinstance(args[0],dict): |
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| 189 | kwargs = args[0] |
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| 190 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
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| 191 | if kwargs.has_key("params"): params = kwargs["params"] |
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| 192 | if len(args) == 2 and isinstance(args[1], int): |
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| 193 | component = args[1] |
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[515] | 194 | if self.fitfunc is None: |
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[723] | 195 | msg = "Please specify a fitting function first." |
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| 196 | if rcParams['verbose']: |
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| 197 | print msg |
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| 198 | return |
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| 199 | else: |
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| 200 | raise RuntimeError(msg) |
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[515] | 201 | if self.fitfunc == "gauss" and component is not None: |
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[1017] | 202 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
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[1134] | 203 | pars = list(NUM.zeros(len(self.components)*3)) |
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| 204 | fxd = list(NUM.zeros(len(pars))) |
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[515] | 205 | else: |
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[723] | 206 | pars = list(self.fitter.getparameters()) |
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[515] | 207 | fxd = list(self.fitter.getfixedparameters()) |
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| 208 | i = 3*component |
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| 209 | pars[i:i+3] = params |
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| 210 | fxd[i:i+3] = fixed |
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| 211 | params = pars |
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[723] | 212 | fixed = fxd |
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[113] | 213 | self.fitter.setparameters(params) |
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| 214 | if fixed is not None: |
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| 215 | self.fitter.setfixedparameters(fixed) |
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[723] | 216 | print_log() |
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[113] | 217 | return |
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[515] | 218 | |
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| 219 | def set_gauss_parameters(self, peak, centre, fhwm, |
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[1017] | 220 | peakfixed=0, centerfixed=0, |
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| 221 | fhwmfixed=0, |
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[515] | 222 | component=0): |
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[113] | 223 | """ |
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[515] | 224 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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| 225 | Parameters: |
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| 226 | peak, centre, fhwm: The gaussian parameters |
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| 227 | peakfixed, |
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| 228 | centerfixed, |
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| 229 | fhwmfixed: Optional parameters to indicate if |
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| 230 | the paramters should be held fixed during |
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| 231 | the fitting process. The default is to keep |
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| 232 | all parameters flexible. |
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[526] | 233 | component: The number of the component (Default is the |
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| 234 | component 0) |
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[515] | 235 | """ |
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| 236 | if self.fitfunc != "gauss": |
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[723] | 237 | msg = "Function only operates on Gaussian components." |
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| 238 | if rcParams['verbose']: |
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| 239 | print msg |
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| 240 | return |
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| 241 | else: |
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| 242 | raise ValueError(msg) |
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[515] | 243 | if 0 <= component < len(self.components): |
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[1017] | 244 | d = {'params':[peak, centre, fhwm], |
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| 245 | 'fixed':[peakfixed, centerfixed, fhwmfixed]} |
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| 246 | self.set_parameters(d, component) |
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[515] | 247 | else: |
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[723] | 248 | msg = "Please select a valid component." |
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| 249 | if rcParams['verbose']: |
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| 250 | print msg |
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| 251 | return |
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| 252 | else: |
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| 253 | raise ValueError(msg) |
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| 254 | |
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[975] | 255 | def get_area(self, component=None): |
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| 256 | """ |
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| 257 | Return the area under the fitted gaussian component. |
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| 258 | Parameters: |
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| 259 | component: the gaussian component selection, |
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| 260 | default (None) is the sum of all components |
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| 261 | Note: |
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| 262 | This will only work for gaussian fits. |
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| 263 | """ |
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| 264 | if not self.fitted: return |
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| 265 | if self.fitfunc == "gauss": |
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| 266 | pars = list(self.fitter.getparameters()) |
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| 267 | from math import log,pi,sqrt |
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| 268 | fac = sqrt(pi/log(16.0)) |
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| 269 | areas = [] |
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| 270 | for i in range(len(self.components)): |
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| 271 | j = i*3 |
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| 272 | cpars = pars[j:j+3] |
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| 273 | areas.append(fac * cpars[0] * cpars[2]) |
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| 274 | else: |
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| 275 | return None |
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| 276 | if component is not None: |
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| 277 | return areas[component] |
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| 278 | else: |
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| 279 | return sum(areas) |
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| 280 | |
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[1075] | 281 | def get_errors(self, component=None): |
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[515] | 282 | """ |
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[1075] | 283 | Return the errors in the parameters. |
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| 284 | Parameters: |
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| 285 | component: get the errors for the specified component |
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| 286 | only, default is all components |
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| 287 | """ |
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| 288 | if not self.fitted: |
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| 289 | msg = "Not yet fitted." |
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| 290 | if rcParams['verbose']: |
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| 291 | print msg |
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| 292 | return |
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| 293 | else: |
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| 294 | raise RuntimeError(msg) |
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| 295 | errs = list(self.fitter.geterrors()) |
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| 296 | cerrs = errs |
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| 297 | if component is not None: |
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| 298 | if self.fitfunc == "gauss": |
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| 299 | i = 3*component |
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| 300 | if i < len(errs): |
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| 301 | cerrs = errs[i:i+3] |
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| 302 | return cerrs |
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| 303 | |
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| 304 | def get_parameters(self, component=None, errors=False): |
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| 305 | """ |
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[113] | 306 | Return the fit paramters. |
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[526] | 307 | Parameters: |
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| 308 | component: get the parameters for the specified component |
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| 309 | only, default is all components |
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[113] | 310 | """ |
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| 311 | if not self.fitted: |
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[723] | 312 | msg = "Not yet fitted." |
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| 313 | if rcParams['verbose']: |
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| 314 | print msg |
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| 315 | return |
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| 316 | else: |
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| 317 | raise RuntimeError(msg) |
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[113] | 318 | pars = list(self.fitter.getparameters()) |
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| 319 | fixed = list(self.fitter.getfixedparameters()) |
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[1075] | 320 | errs = list(self.fitter.geterrors()) |
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[1039] | 321 | area = [] |
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[723] | 322 | if component is not None: |
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[515] | 323 | if self.fitfunc == "gauss": |
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| 324 | i = 3*component |
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| 325 | cpars = pars[i:i+3] |
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| 326 | cfixed = fixed[i:i+3] |
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[1075] | 327 | cerrs = errs[i:i+3] |
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[1039] | 328 | a = self.get_area(component) |
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| 329 | area = [a for i in range(3)] |
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[515] | 330 | else: |
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| 331 | cpars = pars |
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[723] | 332 | cfixed = fixed |
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[1075] | 333 | cerrs = errs |
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[515] | 334 | else: |
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| 335 | cpars = pars |
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| 336 | cfixed = fixed |
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[1075] | 337 | cerrs = errs |
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[1039] | 338 | if self.fitfunc == "gauss": |
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| 339 | for c in range(len(self.components)): |
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| 340 | a = self.get_area(c) |
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| 341 | area += [a for i in range(3)] |
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[1088] | 342 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
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[723] | 343 | if rcParams['verbose']: |
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[515] | 344 | print fpars |
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[1075] | 345 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
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| 346 | 'errors':cerrs} |
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[723] | 347 | |
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[1075] | 348 | def _format_pars(self, pars, fixed, errors, area): |
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[113] | 349 | out = '' |
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| 350 | if self.fitfunc == 'poly': |
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| 351 | c = 0 |
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[515] | 352 | for i in range(len(pars)): |
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| 353 | fix = "" |
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| 354 | if fixed[i]: fix = "(fixed)" |
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[1088] | 355 | if errors : |
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| 356 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i]) |
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| 357 | else: |
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| 358 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i]) |
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[113] | 359 | c+=1 |
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[515] | 360 | out = out[:-1] # remove trailing ',' |
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[113] | 361 | elif self.fitfunc == 'gauss': |
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| 362 | i = 0 |
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| 363 | c = 0 |
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[515] | 364 | aunit = '' |
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| 365 | ounit = '' |
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[113] | 366 | if self.data: |
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[515] | 367 | aunit = self.data.get_unit() |
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| 368 | ounit = self.data.get_fluxunit() |
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[113] | 369 | while i < len(pars): |
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[1039] | 370 | if len(area): |
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| 371 | 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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[1017] | 372 | else: |
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| 373 | 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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[113] | 374 | c+=1 |
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| 375 | i+=3 |
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| 376 | return out |
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[723] | 377 | |
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[113] | 378 | def get_estimate(self): |
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| 379 | """ |
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[515] | 380 | Return the parameter estimates (for non-linear functions). |
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[113] | 381 | """ |
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| 382 | pars = self.fitter.getestimate() |
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[943] | 383 | fixed = self.fitter.getfixedparameters() |
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[723] | 384 | if rcParams['verbose']: |
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[1017] | 385 | print self._format_pars(pars,fixed,None) |
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[113] | 386 | return pars |
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| 387 | |
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| 388 | def get_residual(self): |
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| 389 | """ |
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| 390 | Return the residual of the fit. |
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| 391 | """ |
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| 392 | if not self.fitted: |
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[723] | 393 | msg = "Not yet fitted." |
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| 394 | if rcParams['verbose']: |
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| 395 | print msg |
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| 396 | return |
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| 397 | else: |
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| 398 | raise RuntimeError(msg) |
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[113] | 399 | return self.fitter.getresidual() |
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| 400 | |
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| 401 | def get_chi2(self): |
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| 402 | """ |
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| 403 | Return chi^2. |
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| 404 | """ |
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| 405 | if not self.fitted: |
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[723] | 406 | msg = "Not yet fitted." |
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| 407 | if rcParams['verbose']: |
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| 408 | print msg |
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| 409 | return |
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| 410 | else: |
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| 411 | raise RuntimeError(msg) |
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[113] | 412 | ch2 = self.fitter.getchi2() |
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[723] | 413 | if rcParams['verbose']: |
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[113] | 414 | print 'Chi^2 = %3.3f' % (ch2) |
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[723] | 415 | return ch2 |
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[113] | 416 | |
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| 417 | def get_fit(self): |
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| 418 | """ |
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| 419 | Return the fitted ordinate values. |
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| 420 | """ |
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| 421 | if not self.fitted: |
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[723] | 422 | msg = "Not yet fitted." |
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| 423 | if rcParams['verbose']: |
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| 424 | print msg |
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| 425 | return |
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| 426 | else: |
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| 427 | raise RuntimeError(msg) |
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[113] | 428 | return self.fitter.getfit() |
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| 429 | |
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| 430 | def commit(self): |
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| 431 | """ |
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[526] | 432 | Return a new scan where the fits have been commited (subtracted) |
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[113] | 433 | """ |
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| 434 | if not self.fitted: |
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[723] | 435 | msg = "Not yet fitted." |
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| 436 | if rcParams['verbose']: |
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| 437 | print msg |
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| 438 | return |
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| 439 | else: |
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| 440 | raise RuntimeError(msg) |
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[975] | 441 | from asap import scantable |
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| 442 | if not isinstance(self.data, scantable): |
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[723] | 443 | msg = "Not a scantable" |
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| 444 | if rcParams['verbose']: |
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| 445 | print msg |
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| 446 | return |
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| 447 | else: |
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| 448 | raise TypeError(msg) |
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[113] | 449 | scan = self.data.copy() |
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[259] | 450 | scan._setspectrum(self.fitter.getresidual()) |
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[723] | 451 | print_log() |
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[1092] | 452 | return scan |
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[113] | 453 | |
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[723] | 454 | def plot(self, residual=False, components=None, plotparms=False, filename=None): |
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[113] | 455 | """ |
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| 456 | Plot the last fit. |
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| 457 | Parameters: |
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| 458 | residual: an optional parameter indicating if the residual |
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| 459 | should be plotted (default 'False') |
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[526] | 460 | components: a list of components to plot, e.g [0,1], |
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| 461 | -1 plots the total fit. Default is to only |
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| 462 | plot the total fit. |
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| 463 | plotparms: Inidicates if the parameter values should be present |
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| 464 | on the plot |
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[113] | 465 | """ |
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| 466 | if not self.fitted: |
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| 467 | return |
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[723] | 468 | if not self._p or self._p.is_dead: |
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| 469 | if rcParams['plotter.gui']: |
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| 470 | from asap.asaplotgui import asaplotgui as asaplot |
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| 471 | else: |
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| 472 | from asap.asaplot import asaplot |
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| 473 | self._p = asaplot() |
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| 474 | self._p.hold() |
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[113] | 475 | self._p.clear() |
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[515] | 476 | self._p.set_panels() |
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[652] | 477 | self._p.palette(0) |
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[113] | 478 | tlab = 'Spectrum' |
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[723] | 479 | xlab = 'Abcissa' |
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[1017] | 480 | ylab = 'Ordinate' |
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| 481 | m = None |
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[113] | 482 | if self.data: |
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[515] | 483 | tlab = self.data._getsourcename(self._fittedrow) |
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| 484 | xlab = self.data._getabcissalabel(self._fittedrow) |
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| 485 | m = self.data._getmask(self._fittedrow) |
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[626] | 486 | ylab = self.data._get_ordinate_label() |
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[515] | 487 | |
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[1075] | 488 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
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[652] | 489 | self._p.palette(0,colours) |
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[515] | 490 | self._p.set_line(label='Spectrum') |
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[1088] | 491 | from matplotlib.numerix import ma,logical_not,array |
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[1116] | 492 | y = ma.masked_array(self.y,mask=logical_not(array(m,copy=False))) |
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[1088] | 493 | self._p.plot(self.x, y) |
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[113] | 494 | if residual: |
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[652] | 495 | self._p.palette(1) |
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[515] | 496 | self._p.set_line(label='Residual') |
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[1116] | 497 | y = ma.masked_array(self.get_residual(), |
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| 498 | mask=logical_not(array(m,copy=False))) |
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[1088] | 499 | self._p.plot(self.x, y) |
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[652] | 500 | self._p.palette(2) |
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[515] | 501 | if components is not None: |
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| 502 | cs = components |
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| 503 | if isinstance(components,int): cs = [components] |
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[526] | 504 | if plotparms: |
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[1031] | 505 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
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[515] | 506 | n = len(self.components) |
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[652] | 507 | self._p.palette(3) |
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[515] | 508 | for c in cs: |
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| 509 | if 0 <= c < n: |
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| 510 | lab = self.fitfuncs[c]+str(c) |
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| 511 | self._p.set_line(label=lab) |
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[1116] | 512 | y = ma.masked_array(self.fitter.evaluate(c), |
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| 513 | mask=logical_not(array(m,copy=False))) |
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[1088] | 514 | |
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| 515 | self._p.plot(self.x, y) |
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[515] | 516 | elif c == -1: |
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[652] | 517 | self._p.palette(2) |
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[515] | 518 | self._p.set_line(label="Total Fit") |
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[1116] | 519 | y = ma.masked_array(self.fitter.getfit(), |
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| 520 | mask=logical_not(array(m,copy=False))) |
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[1088] | 521 | self._p.plot(self.x, y) |
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[515] | 522 | else: |
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[652] | 523 | self._p.palette(2) |
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[515] | 524 | self._p.set_line(label='Fit') |
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[1116] | 525 | y = ma.masked_array(self.fitter.getfit(), |
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| 526 | mask=logical_not(array(m,copy=False))) |
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[1088] | 527 | self._p.plot(self.x, y) |
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[723] | 528 | xlim=[min(self.x),max(self.x)] |
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| 529 | self._p.axes.set_xlim(xlim) |
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[113] | 530 | self._p.set_axes('xlabel',xlab) |
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| 531 | self._p.set_axes('ylabel',ylab) |
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| 532 | self._p.set_axes('title',tlab) |
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| 533 | self._p.release() |
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[723] | 534 | if (not rcParams['plotter.gui']): |
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| 535 | self._p.save(filename) |
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| 536 | print_log() |
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[113] | 537 | |
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[1061] | 538 | def auto_fit(self, insitu=None, plot=False): |
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[113] | 539 | """ |
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[515] | 540 | Return a scan where the function is applied to all rows for |
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| 541 | all Beams/IFs/Pols. |
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[723] | 542 | |
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[113] | 543 | """ |
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| 544 | from asap import scantable |
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[515] | 545 | if not isinstance(self.data, scantable) : |
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[723] | 546 | msg = "Data is not a scantable" |
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| 547 | if rcParams['verbose']: |
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| 548 | print msg |
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| 549 | return |
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| 550 | else: |
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| 551 | raise TypeError(msg) |
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[259] | 552 | if insitu is None: insitu = rcParams['insitu'] |
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| 553 | if not insitu: |
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| 554 | scan = self.data.copy() |
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| 555 | else: |
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| 556 | scan = self.data |
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[880] | 557 | rows = xrange(scan.nrow()) |
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[723] | 558 | from asap import asaplog |
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[876] | 559 | asaplog.push("Fitting:") |
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| 560 | for r in rows: |
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[1031] | 561 | 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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[880] | 562 | asaplog.push(out, False) |
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[876] | 563 | self.x = scan._getabcissa(r) |
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| 564 | self.y = scan._getspectrum(r) |
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| 565 | self.data = None |
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| 566 | self.fit() |
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| 567 | x = self.get_parameters() |
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[1061] | 568 | if plot: |
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| 569 | self.plot(residual=True) |
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| 570 | x = raw_input("Accept fit ([y]/n): ") |
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| 571 | if x.upper() == 'N': |
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| 572 | continue |
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[880] | 573 | scan._setspectrum(self.fitter.getresidual(), r) |
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[1061] | 574 | if plot: |
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| 575 | self._p.unmap() |
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| 576 | self._p = None |
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[876] | 577 | print_log() |
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| 578 | return scan |
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[794] | 579 | |
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