[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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[1295] | 4 | from asap import _n_bools |
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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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[1389] | 27 | self.uselinear = False |
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[113] | 28 | |
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| 29 | def set_data(self, xdat, ydat, mask=None): |
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| 30 | """ |
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[158] | 31 | Set the absissa and ordinate for the fit. Also set the mask |
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[113] | 32 | indicationg valid points. |
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| 33 | This can be used for data vectors retrieved from a scantable. |
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| 34 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
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| 35 | Parameters: |
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[158] | 36 | xdat: the abcissa values |
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[113] | 37 | ydat: the ordinate values |
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| 38 | mask: an optional mask |
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[723] | 39 | |
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[113] | 40 | """ |
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| 41 | self.fitted = False |
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| 42 | self.x = xdat |
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| 43 | self.y = ydat |
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| 44 | if mask == None: |
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[1295] | 45 | self.mask = _n_bools(len(xdat), True) |
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[113] | 46 | else: |
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| 47 | self.mask = mask |
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| 48 | return |
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| 49 | |
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| 50 | def set_scan(self, thescan=None, mask=None): |
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| 51 | """ |
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| 52 | Set the 'data' (a scantable) of the fitter. |
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| 53 | Parameters: |
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| 54 | thescan: a scantable |
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| 55 | mask: a msk retireved from the scantable |
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| 56 | """ |
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| 57 | if not thescan: |
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[723] | 58 | msg = "Please give a correct scan" |
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| 59 | if rcParams['verbose']: |
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| 60 | print msg |
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| 61 | return |
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| 62 | else: |
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| 63 | raise TypeError(msg) |
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[113] | 64 | self.fitted = False |
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| 65 | self.data = thescan |
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[1075] | 66 | self.mask = None |
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[113] | 67 | if mask is None: |
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[1295] | 68 | self.mask = _n_bools(self.data.nchan(), True) |
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[113] | 69 | else: |
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| 70 | self.mask = mask |
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| 71 | return |
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| 72 | |
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| 73 | def set_function(self, **kwargs): |
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| 74 | """ |
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| 75 | Set the function to be fit. |
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| 76 | Parameters: |
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[1389] | 77 | poly: use a polynomial of the order given with nonlinear least squares fit |
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| 78 | lpoly: use polynomial of the order given with linear least squares fit |
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[113] | 79 | gauss: fit the number of gaussian specified |
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| 80 | Example: |
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| 81 | fitter.set_function(gauss=2) # will fit two gaussians |
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[1389] | 82 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method |
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| 83 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method |
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[113] | 84 | """ |
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[723] | 85 | #default poly order 0 |
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[515] | 86 | n=0 |
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[113] | 87 | if kwargs.has_key('poly'): |
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| 88 | self.fitfunc = 'poly' |
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| 89 | n = kwargs.get('poly') |
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[515] | 90 | self.components = [n] |
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[1389] | 91 | self.uselinear = False |
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| 92 | elif kwargs.has_key('lpoly'): |
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| 93 | self.fitfunc = 'poly' |
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| 94 | n = kwargs.get('lpoly') |
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| 95 | self.components = [n] |
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| 96 | self.uselinear = True |
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[113] | 97 | elif kwargs.has_key('gauss'): |
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| 98 | n = kwargs.get('gauss') |
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| 99 | self.fitfunc = 'gauss' |
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[515] | 100 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
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| 101 | self.components = [ 3 for i in range(n) ] |
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[1389] | 102 | self.uselinear = False |
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[515] | 103 | else: |
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[723] | 104 | msg = "Invalid function type." |
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| 105 | if rcParams['verbose']: |
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| 106 | print msg |
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| 107 | return |
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| 108 | else: |
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| 109 | raise TypeError(msg) |
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| 110 | |
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[113] | 111 | self.fitter.setexpression(self.fitfunc,n) |
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[1232] | 112 | self.fitted = False |
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[113] | 113 | return |
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[723] | 114 | |
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[1075] | 115 | def fit(self, row=0, estimate=False): |
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[113] | 116 | """ |
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| 117 | Execute the actual fitting process. All the state has to be set. |
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| 118 | Parameters: |
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[1075] | 119 | row: specify the row in the scantable |
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| 120 | estimate: auto-compute an initial parameter set (default False) |
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| 121 | This can be used to compute estimates even if fit was |
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| 122 | called before. |
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[113] | 123 | Example: |
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[515] | 124 | s = scantable('myscan.asap') |
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| 125 | s.set_cursor(thepol=1) # select second pol |
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[113] | 126 | f = fitter() |
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| 127 | f.set_scan(s) |
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| 128 | f.set_function(poly=0) |
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[723] | 129 | f.fit(row=0) # fit first row |
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[113] | 130 | """ |
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| 131 | if ((self.x is None or self.y is None) and self.data is None) \ |
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| 132 | or self.fitfunc is None: |
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[723] | 133 | msg = "Fitter not yet initialised. Please set data & fit function" |
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| 134 | if rcParams['verbose']: |
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| 135 | print msg |
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| 136 | return |
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| 137 | else: |
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| 138 | raise RuntimeError(msg) |
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| 139 | |
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[113] | 140 | else: |
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| 141 | if self.data is not None: |
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[515] | 142 | self.x = self.data._getabcissa(row) |
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| 143 | self.y = self.data._getspectrum(row) |
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[723] | 144 | from asap import asaplog |
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| 145 | asaplog.push("Fitting:") |
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[943] | 146 | i = row |
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| 147 | 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] | 148 | asaplog.push(out,False) |
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[515] | 149 | self.fitter.setdata(self.x, self.y, self.mask) |
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[113] | 150 | if self.fitfunc == 'gauss': |
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| 151 | ps = self.fitter.getparameters() |
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[1075] | 152 | if len(ps) == 0 or estimate: |
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[113] | 153 | self.fitter.estimate() |
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[626] | 154 | try: |
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[1232] | 155 | fxdpar = list(self.fitter.getfixedparameters()) |
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| 156 | if len(fxdpar) and fxdpar.count(0) == 0: |
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| 157 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
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[1389] | 158 | if self.uselinear: |
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| 159 | converged = self.fitter.lfit() |
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| 160 | else: |
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| 161 | converged = self.fitter.fit() |
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[1075] | 162 | if not converged: |
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| 163 | raise RuntimeError,"Fit didn't converge." |
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[626] | 164 | except RuntimeError, msg: |
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[723] | 165 | if rcParams['verbose']: |
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| 166 | print msg |
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| 167 | else: |
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| 168 | raise |
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[515] | 169 | self._fittedrow = row |
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[113] | 170 | self.fitted = True |
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[723] | 171 | print_log() |
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[113] | 172 | return |
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| 173 | |
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[1232] | 174 | def store_fit(self, filename=None): |
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[526] | 175 | """ |
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[1232] | 176 | Save the fit parameters. |
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| 177 | Parameters: |
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| 178 | filename: if specified save as an ASCII file, if None (default) |
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| 179 | store it in the scnatable |
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[526] | 180 | """ |
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[515] | 181 | if self.fitted and self.data is not None: |
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| 182 | pars = list(self.fitter.getparameters()) |
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| 183 | fixed = list(self.fitter.getfixedparameters()) |
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[975] | 184 | from asap.asapfit import asapfit |
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| 185 | fit = asapfit() |
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| 186 | fit.setparameters(pars) |
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| 187 | fit.setfixedparameters(fixed) |
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| 188 | fit.setfunctions(self.fitfuncs) |
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| 189 | fit.setcomponents(self.components) |
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| 190 | fit.setframeinfo(self.data._getcoordinfo()) |
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[1232] | 191 | if filename is not None: |
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| 192 | import os |
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| 193 | filename = os.path.expandvars(os.path.expanduser(filename)) |
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| 194 | if os.path.exists(filename): |
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| 195 | raise IOError("File '%s' exists." % filename) |
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| 196 | fit.save(filename) |
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| 197 | else: |
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| 198 | self.data._addfit(fit,self._fittedrow) |
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[515] | 199 | |
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[1017] | 200 | #def set_parameters(self, params, fixed=None, component=None): |
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| 201 | def set_parameters(self,*args,**kwargs): |
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[526] | 202 | """ |
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| 203 | Set the parameters to be fitted. |
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| 204 | Parameters: |
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| 205 | params: a vector of parameters |
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| 206 | fixed: a vector of which parameters are to be held fixed |
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| 207 | (default is none) |
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| 208 | component: in case of multiple gaussians, the index of the |
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| 209 | component |
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[1017] | 210 | """ |
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| 211 | component = None |
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| 212 | fixed = None |
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| 213 | params = None |
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[1031] | 214 | |
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[1017] | 215 | if len(args) and isinstance(args[0],dict): |
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| 216 | kwargs = args[0] |
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| 217 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
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| 218 | if kwargs.has_key("params"): params = kwargs["params"] |
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| 219 | if len(args) == 2 and isinstance(args[1], int): |
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| 220 | component = args[1] |
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[515] | 221 | if self.fitfunc is None: |
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[723] | 222 | msg = "Please specify a fitting function first." |
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| 223 | if rcParams['verbose']: |
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| 224 | print msg |
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| 225 | return |
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| 226 | else: |
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| 227 | raise RuntimeError(msg) |
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[515] | 228 | if self.fitfunc == "gauss" and component is not None: |
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[1017] | 229 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
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[1295] | 230 | pars = _n_bools(len(self.components)*3, False) |
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| 231 | fxd = _n_bools(len(pars), False) |
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[515] | 232 | else: |
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[723] | 233 | pars = list(self.fitter.getparameters()) |
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[515] | 234 | fxd = list(self.fitter.getfixedparameters()) |
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| 235 | i = 3*component |
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| 236 | pars[i:i+3] = params |
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| 237 | fxd[i:i+3] = fixed |
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| 238 | params = pars |
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[723] | 239 | fixed = fxd |
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[113] | 240 | self.fitter.setparameters(params) |
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| 241 | if fixed is not None: |
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| 242 | self.fitter.setfixedparameters(fixed) |
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[723] | 243 | print_log() |
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[113] | 244 | return |
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[515] | 245 | |
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[1217] | 246 | def set_gauss_parameters(self, peak, centre, fwhm, |
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[1017] | 247 | peakfixed=0, centerfixed=0, |
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[1217] | 248 | fwhmfixed=0, |
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[515] | 249 | component=0): |
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[113] | 250 | """ |
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[515] | 251 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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| 252 | Parameters: |
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[1232] | 253 | peak, centre, fwhm: The gaussian parameters |
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[515] | 254 | peakfixed, |
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| 255 | centerfixed, |
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[1217] | 256 | fwhmfixed: Optional parameters to indicate if |
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[515] | 257 | the paramters should be held fixed during |
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| 258 | the fitting process. The default is to keep |
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| 259 | all parameters flexible. |
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[526] | 260 | component: The number of the component (Default is the |
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| 261 | component 0) |
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[515] | 262 | """ |
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| 263 | if self.fitfunc != "gauss": |
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[723] | 264 | msg = "Function only operates on Gaussian components." |
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| 265 | if rcParams['verbose']: |
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| 266 | print msg |
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| 267 | return |
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| 268 | else: |
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| 269 | raise ValueError(msg) |
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[515] | 270 | if 0 <= component < len(self.components): |
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[1217] | 271 | d = {'params':[peak, centre, fwhm], |
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| 272 | 'fixed':[peakfixed, centerfixed, fwhmfixed]} |
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[1017] | 273 | self.set_parameters(d, component) |
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[515] | 274 | else: |
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[723] | 275 | msg = "Please select a valid component." |
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| 276 | if rcParams['verbose']: |
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| 277 | print msg |
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| 278 | return |
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| 279 | else: |
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| 280 | raise ValueError(msg) |
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| 281 | |
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[975] | 282 | def get_area(self, component=None): |
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| 283 | """ |
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| 284 | Return the area under the fitted gaussian component. |
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| 285 | Parameters: |
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| 286 | component: the gaussian component selection, |
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| 287 | default (None) is the sum of all components |
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| 288 | Note: |
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| 289 | This will only work for gaussian fits. |
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| 290 | """ |
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| 291 | if not self.fitted: return |
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| 292 | if self.fitfunc == "gauss": |
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| 293 | pars = list(self.fitter.getparameters()) |
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| 294 | from math import log,pi,sqrt |
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| 295 | fac = sqrt(pi/log(16.0)) |
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| 296 | areas = [] |
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| 297 | for i in range(len(self.components)): |
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| 298 | j = i*3 |
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| 299 | cpars = pars[j:j+3] |
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| 300 | areas.append(fac * cpars[0] * cpars[2]) |
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| 301 | else: |
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| 302 | return None |
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| 303 | if component is not None: |
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| 304 | return areas[component] |
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| 305 | else: |
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| 306 | return sum(areas) |
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| 307 | |
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[1075] | 308 | def get_errors(self, component=None): |
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[515] | 309 | """ |
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[1075] | 310 | Return the errors in the parameters. |
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| 311 | Parameters: |
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| 312 | component: get the errors for the specified component |
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| 313 | only, default is all components |
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| 314 | """ |
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| 315 | if not self.fitted: |
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| 316 | msg = "Not yet fitted." |
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| 317 | if rcParams['verbose']: |
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| 318 | print msg |
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| 319 | return |
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| 320 | else: |
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| 321 | raise RuntimeError(msg) |
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| 322 | errs = list(self.fitter.geterrors()) |
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| 323 | cerrs = errs |
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| 324 | if component is not None: |
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| 325 | if self.fitfunc == "gauss": |
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| 326 | i = 3*component |
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| 327 | if i < len(errs): |
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| 328 | cerrs = errs[i:i+3] |
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| 329 | return cerrs |
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| 330 | |
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| 331 | def get_parameters(self, component=None, errors=False): |
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| 332 | """ |
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[113] | 333 | Return the fit paramters. |
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[526] | 334 | Parameters: |
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| 335 | component: get the parameters for the specified component |
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| 336 | only, default is all components |
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[113] | 337 | """ |
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| 338 | if not self.fitted: |
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[723] | 339 | msg = "Not yet fitted." |
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| 340 | if rcParams['verbose']: |
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| 341 | print msg |
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| 342 | return |
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| 343 | else: |
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| 344 | raise RuntimeError(msg) |
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[113] | 345 | pars = list(self.fitter.getparameters()) |
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| 346 | fixed = list(self.fitter.getfixedparameters()) |
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[1075] | 347 | errs = list(self.fitter.geterrors()) |
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[1039] | 348 | area = [] |
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[723] | 349 | if component is not None: |
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[515] | 350 | if self.fitfunc == "gauss": |
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| 351 | i = 3*component |
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| 352 | cpars = pars[i:i+3] |
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| 353 | cfixed = fixed[i:i+3] |
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[1075] | 354 | cerrs = errs[i:i+3] |
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[1039] | 355 | a = self.get_area(component) |
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| 356 | area = [a for i in range(3)] |
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[515] | 357 | else: |
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| 358 | cpars = pars |
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[723] | 359 | cfixed = fixed |
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[1075] | 360 | cerrs = errs |
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[515] | 361 | else: |
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| 362 | cpars = pars |
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| 363 | cfixed = fixed |
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[1075] | 364 | cerrs = errs |
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[1039] | 365 | if self.fitfunc == "gauss": |
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| 366 | for c in range(len(self.components)): |
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| 367 | a = self.get_area(c) |
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| 368 | area += [a for i in range(3)] |
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[1088] | 369 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
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[723] | 370 | if rcParams['verbose']: |
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[515] | 371 | print fpars |
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[1075] | 372 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
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| 373 | 'errors':cerrs} |
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[723] | 374 | |
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[1075] | 375 | def _format_pars(self, pars, fixed, errors, area): |
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[113] | 376 | out = '' |
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| 377 | if self.fitfunc == 'poly': |
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| 378 | c = 0 |
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[515] | 379 | for i in range(len(pars)): |
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| 380 | fix = "" |
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[1232] | 381 | if len(fixed) and fixed[i]: fix = "(fixed)" |
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[1088] | 382 | if errors : |
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| 383 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i]) |
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| 384 | else: |
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| 385 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i]) |
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[113] | 386 | c+=1 |
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[515] | 387 | out = out[:-1] # remove trailing ',' |
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[113] | 388 | elif self.fitfunc == 'gauss': |
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| 389 | i = 0 |
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| 390 | c = 0 |
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[515] | 391 | aunit = '' |
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| 392 | ounit = '' |
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[113] | 393 | if self.data: |
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[515] | 394 | aunit = self.data.get_unit() |
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| 395 | ounit = self.data.get_fluxunit() |
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[113] | 396 | while i < len(pars): |
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[1039] | 397 | if len(area): |
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| 398 | 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] | 399 | else: |
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| 400 | 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] | 401 | c+=1 |
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| 402 | i+=3 |
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| 403 | return out |
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[723] | 404 | |
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[113] | 405 | def get_estimate(self): |
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| 406 | """ |
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[515] | 407 | Return the parameter estimates (for non-linear functions). |
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[113] | 408 | """ |
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| 409 | pars = self.fitter.getestimate() |
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[943] | 410 | fixed = self.fitter.getfixedparameters() |
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[723] | 411 | if rcParams['verbose']: |
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[1017] | 412 | print self._format_pars(pars,fixed,None) |
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[113] | 413 | return pars |
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| 414 | |
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| 415 | def get_residual(self): |
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| 416 | """ |
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| 417 | Return the residual of the fit. |
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| 418 | """ |
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| 419 | if not self.fitted: |
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[723] | 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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[113] | 426 | return self.fitter.getresidual() |
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| 427 | |
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| 428 | def get_chi2(self): |
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| 429 | """ |
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| 430 | Return chi^2. |
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| 431 | """ |
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| 432 | if not self.fitted: |
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[723] | 433 | msg = "Not yet fitted." |
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| 434 | if rcParams['verbose']: |
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| 435 | print msg |
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| 436 | return |
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| 437 | else: |
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| 438 | raise RuntimeError(msg) |
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[113] | 439 | ch2 = self.fitter.getchi2() |
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[723] | 440 | if rcParams['verbose']: |
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[113] | 441 | print 'Chi^2 = %3.3f' % (ch2) |
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[723] | 442 | return ch2 |
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[113] | 443 | |
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| 444 | def get_fit(self): |
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| 445 | """ |
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| 446 | Return the fitted ordinate values. |
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| 447 | """ |
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| 448 | if not self.fitted: |
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[723] | 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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[113] | 455 | return self.fitter.getfit() |
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| 456 | |
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| 457 | def commit(self): |
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| 458 | """ |
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[526] | 459 | Return a new scan where the fits have been commited (subtracted) |
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[113] | 460 | """ |
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| 461 | if not self.fitted: |
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[723] | 462 | msg = "Not yet fitted." |
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| 463 | if rcParams['verbose']: |
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| 464 | print msg |
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| 465 | return |
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| 466 | else: |
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| 467 | raise RuntimeError(msg) |
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[975] | 468 | from asap import scantable |
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| 469 | if not isinstance(self.data, scantable): |
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[723] | 470 | msg = "Not a scantable" |
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| 471 | if rcParams['verbose']: |
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| 472 | print msg |
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| 473 | return |
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| 474 | else: |
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| 475 | raise TypeError(msg) |
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[113] | 476 | scan = self.data.copy() |
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[259] | 477 | scan._setspectrum(self.fitter.getresidual()) |
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[723] | 478 | print_log() |
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[1092] | 479 | return scan |
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[113] | 480 | |
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[723] | 481 | def plot(self, residual=False, components=None, plotparms=False, filename=None): |
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[113] | 482 | """ |
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| 483 | Plot the last fit. |
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| 484 | Parameters: |
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| 485 | residual: an optional parameter indicating if the residual |
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| 486 | should be plotted (default 'False') |
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[526] | 487 | components: a list of components to plot, e.g [0,1], |
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| 488 | -1 plots the total fit. Default is to only |
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| 489 | plot the total fit. |
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| 490 | plotparms: Inidicates if the parameter values should be present |
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| 491 | on the plot |
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[113] | 492 | """ |
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| 493 | if not self.fitted: |
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| 494 | return |
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[723] | 495 | if not self._p or self._p.is_dead: |
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| 496 | if rcParams['plotter.gui']: |
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| 497 | from asap.asaplotgui import asaplotgui as asaplot |
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| 498 | else: |
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| 499 | from asap.asaplot import asaplot |
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| 500 | self._p = asaplot() |
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| 501 | self._p.hold() |
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[113] | 502 | self._p.clear() |
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[515] | 503 | self._p.set_panels() |
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[652] | 504 | self._p.palette(0) |
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[113] | 505 | tlab = 'Spectrum' |
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[723] | 506 | xlab = 'Abcissa' |
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[1017] | 507 | ylab = 'Ordinate' |
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[1273] | 508 | from matplotlib.numerix import ma,logical_not,logical_and,array |
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| 509 | m = self.mask |
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[113] | 510 | if self.data: |
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[515] | 511 | tlab = self.data._getsourcename(self._fittedrow) |
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| 512 | xlab = self.data._getabcissalabel(self._fittedrow) |
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[1273] | 513 | m = logical_and(self.mask, |
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[1306] | 514 | array(self.data._getmask(self._fittedrow), |
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| 515 | copy=False)) |
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[1389] | 516 | |
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[626] | 517 | ylab = self.data._get_ordinate_label() |
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[515] | 518 | |
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[1075] | 519 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
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[1461] | 520 | nomask=True |
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| 521 | for i in range(len(m)): |
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| 522 | nomask = nomask and m[i] |
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| 523 | label0='Masked Region' |
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| 524 | label1='Spectrum' |
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| 525 | if ( nomask ): |
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| 526 | label0=label1 |
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| 527 | else: |
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| 528 | y = ma.masked_array( self.y, mask = m ) |
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| 529 | self._p.palette(1,colours) |
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| 530 | self._p.set_line( label = label1 ) |
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| 531 | self._p.plot( self.x, y ) |
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[652] | 532 | self._p.palette(0,colours) |
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[1461] | 533 | self._p.set_line(label=label0) |
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[1273] | 534 | y = ma.masked_array(self.y,mask=logical_not(m)) |
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[1088] | 535 | self._p.plot(self.x, y) |
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[113] | 536 | if residual: |
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[1461] | 537 | self._p.palette(7) |
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[515] | 538 | self._p.set_line(label='Residual') |
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[1116] | 539 | y = ma.masked_array(self.get_residual(), |
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[1273] | 540 | mask=logical_not(m)) |
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[1088] | 541 | self._p.plot(self.x, y) |
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[652] | 542 | self._p.palette(2) |
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[515] | 543 | if components is not None: |
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| 544 | cs = components |
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| 545 | if isinstance(components,int): cs = [components] |
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[526] | 546 | if plotparms: |
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[1031] | 547 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
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[515] | 548 | n = len(self.components) |
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[652] | 549 | self._p.palette(3) |
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[515] | 550 | for c in cs: |
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| 551 | if 0 <= c < n: |
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| 552 | lab = self.fitfuncs[c]+str(c) |
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| 553 | self._p.set_line(label=lab) |
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[1116] | 554 | y = ma.masked_array(self.fitter.evaluate(c), |
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[1273] | 555 | mask=logical_not(m)) |
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[1088] | 556 | |
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| 557 | self._p.plot(self.x, y) |
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[515] | 558 | elif c == -1: |
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[652] | 559 | self._p.palette(2) |
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[515] | 560 | self._p.set_line(label="Total Fit") |
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[1116] | 561 | y = ma.masked_array(self.fitter.getfit(), |
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[1273] | 562 | mask=logical_not(m)) |
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[1088] | 563 | self._p.plot(self.x, y) |
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[515] | 564 | else: |
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[652] | 565 | self._p.palette(2) |
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[515] | 566 | self._p.set_line(label='Fit') |
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[1116] | 567 | y = ma.masked_array(self.fitter.getfit(), |
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[1273] | 568 | mask=logical_not(m)) |
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[1088] | 569 | self._p.plot(self.x, y) |
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[723] | 570 | xlim=[min(self.x),max(self.x)] |
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| 571 | self._p.axes.set_xlim(xlim) |
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[113] | 572 | self._p.set_axes('xlabel',xlab) |
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| 573 | self._p.set_axes('ylabel',ylab) |
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| 574 | self._p.set_axes('title',tlab) |
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| 575 | self._p.release() |
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[723] | 576 | if (not rcParams['plotter.gui']): |
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| 577 | self._p.save(filename) |
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| 578 | print_log() |
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[113] | 579 | |
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[1061] | 580 | def auto_fit(self, insitu=None, plot=False): |
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[113] | 581 | """ |
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[515] | 582 | Return a scan where the function is applied to all rows for |
---|
| 583 | all Beams/IFs/Pols. |
---|
[723] | 584 | |
---|
[113] | 585 | """ |
---|
| 586 | from asap import scantable |
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[515] | 587 | if not isinstance(self.data, scantable) : |
---|
[723] | 588 | msg = "Data is not a scantable" |
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| 589 | if rcParams['verbose']: |
---|
| 590 | print msg |
---|
| 591 | return |
---|
| 592 | else: |
---|
| 593 | raise TypeError(msg) |
---|
[259] | 594 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 595 | if not insitu: |
---|
| 596 | scan = self.data.copy() |
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| 597 | else: |
---|
| 598 | scan = self.data |
---|
[880] | 599 | rows = xrange(scan.nrow()) |
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[1446] | 600 | # Save parameters of baseline fits as a class attribute. |
---|
| 601 | # NOTICE: This does not reflect changes in scantable! |
---|
| 602 | if len(rows) > 0: self.blpars=[] |
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[723] | 603 | from asap import asaplog |
---|
[876] | 604 | asaplog.push("Fitting:") |
---|
| 605 | for r in rows: |
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[1031] | 606 | 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] | 607 | asaplog.push(out, False) |
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[876] | 608 | self.x = scan._getabcissa(r) |
---|
| 609 | self.y = scan._getspectrum(r) |
---|
| 610 | self.data = None |
---|
| 611 | self.fit() |
---|
[1446] | 612 | fpar = self.get_parameters() |
---|
[1061] | 613 | if plot: |
---|
| 614 | self.plot(residual=True) |
---|
| 615 | x = raw_input("Accept fit ([y]/n): ") |
---|
| 616 | if x.upper() == 'N': |
---|
[1446] | 617 | self.blpars.append(None) |
---|
[1061] | 618 | continue |
---|
[880] | 619 | scan._setspectrum(self.fitter.getresidual(), r) |
---|
[1446] | 620 | self.blpars.append(fpar) |
---|
[1061] | 621 | if plot: |
---|
| 622 | self._p.unmap() |
---|
| 623 | self._p = None |
---|
[876] | 624 | print_log() |
---|
| 625 | return scan |
---|
[794] | 626 | |
---|