[113] | 1 | import _asap |
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[259] | 2 | from asap import rcParams |
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[1589] | 3 | from asap import print_log_dec |
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[1295] | 4 | from asap import _n_bools |
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[1536] | 5 | from asap import mask_and |
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[113] | 6 | |
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| 7 | class fitter: |
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| 8 | """ |
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| 9 | The fitting class for ASAP. |
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| 10 | """ |
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[723] | 11 | |
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[113] | 12 | def __init__(self): |
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| 13 | """ |
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| 14 | Create a fitter object. No state is set. |
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| 15 | """ |
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| 16 | self.fitter = _asap.fitter() |
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| 17 | self.x = None |
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| 18 | self.y = None |
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| 19 | self.mask = None |
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| 20 | self.fitfunc = None |
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[515] | 21 | self.fitfuncs = None |
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[113] | 22 | self.fitted = False |
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| 23 | self.data = None |
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[515] | 24 | self.components = 0 |
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| 25 | self._fittedrow = 0 |
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[113] | 26 | self._p = None |
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[515] | 27 | self._selection = None |
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[1391] | 28 | self.uselinear = False |
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[113] | 29 | |
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| 30 | def set_data(self, xdat, ydat, mask=None): |
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| 31 | """ |
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[158] | 32 | Set the absissa and ordinate for the fit. Also set the mask |
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[113] | 33 | indicationg valid points. |
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| 34 | This can be used for data vectors retrieved from a scantable. |
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| 35 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
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| 36 | Parameters: |
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[158] | 37 | xdat: the abcissa values |
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[113] | 38 | ydat: the ordinate values |
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| 39 | mask: an optional mask |
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[723] | 40 | |
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[113] | 41 | """ |
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| 42 | self.fitted = False |
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| 43 | self.x = xdat |
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| 44 | self.y = ydat |
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| 45 | if mask == None: |
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[1295] | 46 | self.mask = _n_bools(len(xdat), True) |
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[113] | 47 | else: |
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| 48 | self.mask = mask |
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| 49 | return |
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| 50 | |
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| 51 | def set_scan(self, thescan=None, mask=None): |
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| 52 | """ |
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| 53 | Set the 'data' (a scantable) of the fitter. |
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| 54 | Parameters: |
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| 55 | thescan: a scantable |
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[1420] | 56 | mask: a msk retrieved from the scantable |
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[113] | 57 | """ |
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| 58 | if not thescan: |
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[723] | 59 | msg = "Please give a correct scan" |
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| 60 | if rcParams['verbose']: |
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| 61 | print msg |
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| 62 | return |
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| 63 | else: |
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| 64 | raise TypeError(msg) |
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[113] | 65 | self.fitted = False |
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| 66 | self.data = thescan |
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[1075] | 67 | self.mask = None |
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[113] | 68 | if mask is None: |
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[1295] | 69 | self.mask = _n_bools(self.data.nchan(), True) |
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[113] | 70 | else: |
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| 71 | self.mask = mask |
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| 72 | return |
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| 73 | |
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| 74 | def set_function(self, **kwargs): |
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| 75 | """ |
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| 76 | Set the function to be fit. |
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| 77 | Parameters: |
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[1589] | 78 | poly: use a polynomial of the order given with nonlinear least squares fit |
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[1391] | 79 | lpoly: use polynomial of the order given with linear least squares fit |
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[113] | 80 | gauss: fit the number of gaussian specified |
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| 81 | Example: |
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| 82 | fitter.set_function(gauss=2) # will fit two gaussians |
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[1391] | 83 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method |
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| 84 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method |
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[113] | 85 | """ |
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[723] | 86 | #default poly order 0 |
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[515] | 87 | n=0 |
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[113] | 88 | if kwargs.has_key('poly'): |
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| 89 | self.fitfunc = 'poly' |
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| 90 | n = kwargs.get('poly') |
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[515] | 91 | self.components = [n] |
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[1589] | 92 | self.uselinear = False |
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[1391] | 93 | elif kwargs.has_key('lpoly'): |
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| 94 | self.fitfunc = 'poly' |
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| 95 | n = kwargs.get('lpoly') |
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| 96 | self.components = [n] |
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| 97 | self.uselinear = True |
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[113] | 98 | elif kwargs.has_key('gauss'): |
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| 99 | n = kwargs.get('gauss') |
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| 100 | self.fitfunc = 'gauss' |
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[515] | 101 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
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| 102 | self.components = [ 3 for i in range(n) ] |
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[1589] | 103 | self.uselinear = False |
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[515] | 104 | else: |
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[723] | 105 | msg = "Invalid function type." |
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| 106 | if rcParams['verbose']: |
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| 107 | print msg |
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| 108 | return |
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| 109 | else: |
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| 110 | raise TypeError(msg) |
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| 111 | |
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[113] | 112 | self.fitter.setexpression(self.fitfunc,n) |
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[1232] | 113 | self.fitted = False |
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[113] | 114 | return |
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[723] | 115 | |
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[1589] | 116 | @print_log_dec |
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[1075] | 117 | def fit(self, row=0, estimate=False): |
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[113] | 118 | """ |
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| 119 | Execute the actual fitting process. All the state has to be set. |
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| 120 | Parameters: |
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[1075] | 121 | row: specify the row in the scantable |
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| 122 | estimate: auto-compute an initial parameter set (default False) |
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| 123 | This can be used to compute estimates even if fit was |
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| 124 | called before. |
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[113] | 125 | Example: |
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[515] | 126 | s = scantable('myscan.asap') |
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| 127 | s.set_cursor(thepol=1) # select second pol |
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[113] | 128 | f = fitter() |
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| 129 | f.set_scan(s) |
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| 130 | f.set_function(poly=0) |
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[723] | 131 | f.fit(row=0) # fit first row |
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[113] | 132 | """ |
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| 133 | if ((self.x is None or self.y is None) and self.data is None) \ |
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| 134 | or self.fitfunc is None: |
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[723] | 135 | msg = "Fitter not yet initialised. Please set data & fit function" |
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| 136 | if rcParams['verbose']: |
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| 137 | print msg |
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| 138 | return |
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| 139 | else: |
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| 140 | raise RuntimeError(msg) |
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| 141 | |
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[113] | 142 | else: |
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| 143 | if self.data is not None: |
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[515] | 144 | self.x = self.data._getabcissa(row) |
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| 145 | self.y = self.data._getspectrum(row) |
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[1536] | 146 | self.mask = mask_and(self.mask, self.data._getmask(row)) |
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[723] | 147 | from asap import asaplog |
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| 148 | asaplog.push("Fitting:") |
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[943] | 149 | i = row |
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[1536] | 150 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i), |
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| 151 | self.data.getbeam(i), |
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| 152 | self.data.getif(i), |
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[1589] | 153 | self.data.getpol(i), |
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[1536] | 154 | self.data.getcycle(i)) |
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[1075] | 155 | asaplog.push(out,False) |
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[515] | 156 | self.fitter.setdata(self.x, self.y, self.mask) |
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[113] | 157 | if self.fitfunc == 'gauss': |
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| 158 | ps = self.fitter.getparameters() |
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[1075] | 159 | if len(ps) == 0 or estimate: |
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[113] | 160 | self.fitter.estimate() |
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[626] | 161 | try: |
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[1232] | 162 | fxdpar = list(self.fitter.getfixedparameters()) |
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| 163 | if len(fxdpar) and fxdpar.count(0) == 0: |
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| 164 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
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[1391] | 165 | if self.uselinear: |
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| 166 | converged = self.fitter.lfit() |
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| 167 | else: |
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| 168 | converged = self.fitter.fit() |
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[1075] | 169 | if not converged: |
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| 170 | raise RuntimeError,"Fit didn't converge." |
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[626] | 171 | except RuntimeError, msg: |
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[723] | 172 | if rcParams['verbose']: |
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| 173 | print msg |
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| 174 | else: |
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| 175 | raise |
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[515] | 176 | self._fittedrow = row |
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[113] | 177 | self.fitted = True |
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| 178 | return |
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| 179 | |
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[1232] | 180 | def store_fit(self, filename=None): |
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[526] | 181 | """ |
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[1232] | 182 | Save the fit parameters. |
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| 183 | Parameters: |
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| 184 | filename: if specified save as an ASCII file, if None (default) |
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| 185 | store it in the scnatable |
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[526] | 186 | """ |
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[515] | 187 | if self.fitted and self.data is not None: |
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| 188 | pars = list(self.fitter.getparameters()) |
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| 189 | fixed = list(self.fitter.getfixedparameters()) |
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[975] | 190 | from asap.asapfit import asapfit |
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| 191 | fit = asapfit() |
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| 192 | fit.setparameters(pars) |
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| 193 | fit.setfixedparameters(fixed) |
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| 194 | fit.setfunctions(self.fitfuncs) |
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| 195 | fit.setcomponents(self.components) |
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| 196 | fit.setframeinfo(self.data._getcoordinfo()) |
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[1232] | 197 | if filename is not None: |
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| 198 | import os |
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| 199 | filename = os.path.expandvars(os.path.expanduser(filename)) |
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| 200 | if os.path.exists(filename): |
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| 201 | raise IOError("File '%s' exists." % filename) |
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| 202 | fit.save(filename) |
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| 203 | else: |
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| 204 | self.data._addfit(fit,self._fittedrow) |
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[515] | 205 | |
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[1589] | 206 | @print_log_dec |
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[1017] | 207 | def set_parameters(self,*args,**kwargs): |
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[526] | 208 | """ |
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| 209 | Set the parameters to be fitted. |
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| 210 | Parameters: |
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| 211 | params: a vector of parameters |
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| 212 | fixed: a vector of which parameters are to be held fixed |
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| 213 | (default is none) |
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| 214 | component: in case of multiple gaussians, the index of the |
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| 215 | component |
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[1017] | 216 | """ |
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| 217 | component = None |
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| 218 | fixed = None |
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| 219 | params = None |
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[1031] | 220 | |
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[1017] | 221 | if len(args) and isinstance(args[0],dict): |
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| 222 | kwargs = args[0] |
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| 223 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
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| 224 | if kwargs.has_key("params"): params = kwargs["params"] |
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| 225 | if len(args) == 2 and isinstance(args[1], int): |
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| 226 | component = args[1] |
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[515] | 227 | if self.fitfunc is None: |
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[723] | 228 | msg = "Please specify a fitting function first." |
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| 229 | if rcParams['verbose']: |
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| 230 | print msg |
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| 231 | return |
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| 232 | else: |
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| 233 | raise RuntimeError(msg) |
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[515] | 234 | if self.fitfunc == "gauss" and component is not None: |
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[1017] | 235 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
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[1295] | 236 | pars = _n_bools(len(self.components)*3, False) |
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| 237 | fxd = _n_bools(len(pars), False) |
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[515] | 238 | else: |
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[723] | 239 | pars = list(self.fitter.getparameters()) |
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[515] | 240 | fxd = list(self.fitter.getfixedparameters()) |
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| 241 | i = 3*component |
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| 242 | pars[i:i+3] = params |
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| 243 | fxd[i:i+3] = fixed |
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| 244 | params = pars |
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[723] | 245 | fixed = fxd |
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[113] | 246 | self.fitter.setparameters(params) |
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| 247 | if fixed is not None: |
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| 248 | self.fitter.setfixedparameters(fixed) |
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| 249 | return |
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[515] | 250 | |
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[1217] | 251 | def set_gauss_parameters(self, peak, centre, fwhm, |
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[1409] | 252 | peakfixed=0, centrefixed=0, |
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[1217] | 253 | fwhmfixed=0, |
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[515] | 254 | component=0): |
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[113] | 255 | """ |
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[515] | 256 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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| 257 | Parameters: |
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[1232] | 258 | peak, centre, fwhm: The gaussian parameters |
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[515] | 259 | peakfixed, |
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[1409] | 260 | centrefixed, |
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[1217] | 261 | fwhmfixed: Optional parameters to indicate if |
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[515] | 262 | the paramters should be held fixed during |
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| 263 | the fitting process. The default is to keep |
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| 264 | all parameters flexible. |
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[526] | 265 | component: The number of the component (Default is the |
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| 266 | component 0) |
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[515] | 267 | """ |
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| 268 | if self.fitfunc != "gauss": |
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[723] | 269 | msg = "Function only operates on Gaussian components." |
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| 270 | if rcParams['verbose']: |
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| 271 | print msg |
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| 272 | return |
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| 273 | else: |
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| 274 | raise ValueError(msg) |
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[515] | 275 | if 0 <= component < len(self.components): |
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[1217] | 276 | d = {'params':[peak, centre, fwhm], |
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[1409] | 277 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
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[1017] | 278 | self.set_parameters(d, component) |
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[515] | 279 | else: |
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[723] | 280 | msg = "Please select a valid component." |
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| 281 | if rcParams['verbose']: |
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| 282 | print msg |
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| 283 | return |
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| 284 | else: |
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| 285 | raise ValueError(msg) |
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| 286 | |
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[975] | 287 | def get_area(self, component=None): |
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| 288 | """ |
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| 289 | Return the area under the fitted gaussian component. |
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| 290 | Parameters: |
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| 291 | component: the gaussian component selection, |
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| 292 | default (None) is the sum of all components |
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| 293 | Note: |
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| 294 | This will only work for gaussian fits. |
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| 295 | """ |
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| 296 | if not self.fitted: return |
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| 297 | if self.fitfunc == "gauss": |
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| 298 | pars = list(self.fitter.getparameters()) |
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| 299 | from math import log,pi,sqrt |
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| 300 | fac = sqrt(pi/log(16.0)) |
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| 301 | areas = [] |
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| 302 | for i in range(len(self.components)): |
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| 303 | j = i*3 |
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| 304 | cpars = pars[j:j+3] |
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| 305 | areas.append(fac * cpars[0] * cpars[2]) |
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| 306 | else: |
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| 307 | return None |
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| 308 | if component is not None: |
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| 309 | return areas[component] |
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| 310 | else: |
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| 311 | return sum(areas) |
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| 312 | |
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[1075] | 313 | def get_errors(self, component=None): |
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[515] | 314 | """ |
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[1075] | 315 | Return the errors in the parameters. |
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| 316 | Parameters: |
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| 317 | component: get the errors for the specified component |
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| 318 | only, default is all components |
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| 319 | """ |
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| 320 | if not self.fitted: |
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| 321 | msg = "Not yet fitted." |
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| 322 | if rcParams['verbose']: |
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| 323 | print msg |
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| 324 | return |
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| 325 | else: |
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| 326 | raise RuntimeError(msg) |
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| 327 | errs = list(self.fitter.geterrors()) |
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| 328 | cerrs = errs |
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| 329 | if component is not None: |
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| 330 | if self.fitfunc == "gauss": |
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| 331 | i = 3*component |
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| 332 | if i < len(errs): |
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| 333 | cerrs = errs[i:i+3] |
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| 334 | return cerrs |
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| 335 | |
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| 336 | def get_parameters(self, component=None, errors=False): |
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| 337 | """ |
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[113] | 338 | Return the fit paramters. |
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[526] | 339 | Parameters: |
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| 340 | component: get the parameters for the specified component |
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| 341 | only, default is all components |
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[113] | 342 | """ |
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| 343 | if not self.fitted: |
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[723] | 344 | msg = "Not yet fitted." |
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| 345 | if rcParams['verbose']: |
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| 346 | print msg |
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| 347 | return |
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| 348 | else: |
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| 349 | raise RuntimeError(msg) |
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[113] | 350 | pars = list(self.fitter.getparameters()) |
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| 351 | fixed = list(self.fitter.getfixedparameters()) |
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[1075] | 352 | errs = list(self.fitter.geterrors()) |
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[1039] | 353 | area = [] |
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[723] | 354 | if component is not None: |
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[515] | 355 | if self.fitfunc == "gauss": |
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| 356 | i = 3*component |
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| 357 | cpars = pars[i:i+3] |
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| 358 | cfixed = fixed[i:i+3] |
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[1075] | 359 | cerrs = errs[i:i+3] |
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[1039] | 360 | a = self.get_area(component) |
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| 361 | area = [a for i in range(3)] |
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[515] | 362 | else: |
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| 363 | cpars = pars |
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[723] | 364 | cfixed = fixed |
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[1075] | 365 | cerrs = errs |
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[515] | 366 | else: |
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| 367 | cpars = pars |
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| 368 | cfixed = fixed |
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[1075] | 369 | cerrs = errs |
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[1039] | 370 | if self.fitfunc == "gauss": |
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| 371 | for c in range(len(self.components)): |
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| 372 | a = self.get_area(c) |
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| 373 | area += [a for i in range(3)] |
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[1088] | 374 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
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[723] | 375 | if rcParams['verbose']: |
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[515] | 376 | print fpars |
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[1075] | 377 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
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| 378 | 'errors':cerrs} |
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[723] | 379 | |
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[1075] | 380 | def _format_pars(self, pars, fixed, errors, area): |
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[113] | 381 | out = '' |
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| 382 | if self.fitfunc == 'poly': |
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| 383 | c = 0 |
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[515] | 384 | for i in range(len(pars)): |
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| 385 | fix = "" |
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[1232] | 386 | if len(fixed) and fixed[i]: fix = "(fixed)" |
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[1088] | 387 | if errors : |
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| 388 | out += ' p%d%s= %3.6f (%1.6f),' % (c,fix,pars[i], errors[i]) |
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| 389 | else: |
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| 390 | out += ' p%d%s= %3.6f,' % (c,fix,pars[i]) |
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[113] | 391 | c+=1 |
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[515] | 392 | out = out[:-1] # remove trailing ',' |
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[113] | 393 | elif self.fitfunc == 'gauss': |
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| 394 | i = 0 |
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| 395 | c = 0 |
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[515] | 396 | aunit = '' |
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| 397 | ounit = '' |
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[113] | 398 | if self.data: |
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[515] | 399 | aunit = self.data.get_unit() |
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| 400 | ounit = self.data.get_fluxunit() |
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[113] | 401 | while i < len(pars): |
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[1039] | 402 | if len(area): |
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| 403 | 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] | 404 | else: |
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| 405 | 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] | 406 | c+=1 |
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| 407 | i+=3 |
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| 408 | return out |
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[723] | 409 | |
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[113] | 410 | def get_estimate(self): |
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| 411 | """ |
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[515] | 412 | Return the parameter estimates (for non-linear functions). |
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[113] | 413 | """ |
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| 414 | pars = self.fitter.getestimate() |
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[943] | 415 | fixed = self.fitter.getfixedparameters() |
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[723] | 416 | if rcParams['verbose']: |
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[1017] | 417 | print self._format_pars(pars,fixed,None) |
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[113] | 418 | return pars |
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| 419 | |
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| 420 | def get_residual(self): |
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| 421 | """ |
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| 422 | Return the residual of the fit. |
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| 423 | """ |
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| 424 | if not self.fitted: |
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[723] | 425 | msg = "Not yet fitted." |
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| 426 | if rcParams['verbose']: |
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| 427 | print msg |
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| 428 | return |
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| 429 | else: |
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| 430 | raise RuntimeError(msg) |
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[113] | 431 | return self.fitter.getresidual() |
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| 432 | |
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| 433 | def get_chi2(self): |
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| 434 | """ |
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| 435 | Return chi^2. |
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| 436 | """ |
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| 437 | if not self.fitted: |
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[723] | 438 | msg = "Not yet fitted." |
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| 439 | if rcParams['verbose']: |
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| 440 | print msg |
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| 441 | return |
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| 442 | else: |
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| 443 | raise RuntimeError(msg) |
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[113] | 444 | ch2 = self.fitter.getchi2() |
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[723] | 445 | if rcParams['verbose']: |
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[113] | 446 | print 'Chi^2 = %3.3f' % (ch2) |
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[723] | 447 | return ch2 |
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[113] | 448 | |
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| 449 | def get_fit(self): |
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| 450 | """ |
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| 451 | Return the fitted ordinate values. |
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| 452 | """ |
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| 453 | if not self.fitted: |
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[723] | 454 | msg = "Not yet fitted." |
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| 455 | if rcParams['verbose']: |
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| 456 | print msg |
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| 457 | return |
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| 458 | else: |
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| 459 | raise RuntimeError(msg) |
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[113] | 460 | return self.fitter.getfit() |
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| 461 | |
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[1589] | 462 | @print_log_dec |
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[113] | 463 | def commit(self): |
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| 464 | """ |
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[526] | 465 | Return a new scan where the fits have been commited (subtracted) |
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[113] | 466 | """ |
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| 467 | if not self.fitted: |
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[723] | 468 | msg = "Not yet fitted." |
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| 469 | if rcParams['verbose']: |
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| 470 | print msg |
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| 471 | return |
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| 472 | else: |
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| 473 | raise RuntimeError(msg) |
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[975] | 474 | from asap import scantable |
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| 475 | if not isinstance(self.data, scantable): |
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[723] | 476 | msg = "Not a scantable" |
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| 477 | if rcParams['verbose']: |
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| 478 | print msg |
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| 479 | return |
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| 480 | else: |
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| 481 | raise TypeError(msg) |
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[113] | 482 | scan = self.data.copy() |
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[259] | 483 | scan._setspectrum(self.fitter.getresidual()) |
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[1092] | 484 | return scan |
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[113] | 485 | |
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[1589] | 486 | @print_log_dec |
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[1689] | 487 | def plot(self, residual=False, components=None, plotparms=False, |
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| 488 | filename=None): |
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[113] | 489 | """ |
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| 490 | Plot the last fit. |
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| 491 | Parameters: |
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| 492 | residual: an optional parameter indicating if the residual |
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| 493 | should be plotted (default 'False') |
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[526] | 494 | components: a list of components to plot, e.g [0,1], |
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| 495 | -1 plots the total fit. Default is to only |
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| 496 | plot the total fit. |
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| 497 | plotparms: Inidicates if the parameter values should be present |
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| 498 | on the plot |
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[113] | 499 | """ |
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| 500 | if not self.fitted: |
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| 501 | return |
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[723] | 502 | if not self._p or self._p.is_dead: |
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| 503 | if rcParams['plotter.gui']: |
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| 504 | from asap.asaplotgui import asaplotgui as asaplot |
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| 505 | else: |
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| 506 | from asap.asaplot import asaplot |
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| 507 | self._p = asaplot() |
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| 508 | self._p.hold() |
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[113] | 509 | self._p.clear() |
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[515] | 510 | self._p.set_panels() |
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[652] | 511 | self._p.palette(0) |
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[113] | 512 | tlab = 'Spectrum' |
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[723] | 513 | xlab = 'Abcissa' |
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[1017] | 514 | ylab = 'Ordinate' |
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[1739] | 515 | from numpy import ma,logical_not,logical_and,array |
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[1273] | 516 | m = self.mask |
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[113] | 517 | if self.data: |
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[515] | 518 | tlab = self.data._getsourcename(self._fittedrow) |
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| 519 | xlab = self.data._getabcissalabel(self._fittedrow) |
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[1273] | 520 | m = logical_and(self.mask, |
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[1306] | 521 | array(self.data._getmask(self._fittedrow), |
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| 522 | copy=False)) |
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[1589] | 523 | |
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[626] | 524 | ylab = self.data._get_ordinate_label() |
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[515] | 525 | |
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[1075] | 526 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
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[652] | 527 | self._p.palette(0,colours) |
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[515] | 528 | self._p.set_line(label='Spectrum') |
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[1273] | 529 | y = ma.masked_array(self.y,mask=logical_not(m)) |
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[1088] | 530 | self._p.plot(self.x, y) |
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[113] | 531 | if residual: |
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[652] | 532 | self._p.palette(1) |
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[515] | 533 | self._p.set_line(label='Residual') |
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[1116] | 534 | y = ma.masked_array(self.get_residual(), |
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[1273] | 535 | mask=logical_not(m)) |
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[1088] | 536 | self._p.plot(self.x, y) |
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[652] | 537 | self._p.palette(2) |
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[515] | 538 | if components is not None: |
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| 539 | cs = components |
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| 540 | if isinstance(components,int): cs = [components] |
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[526] | 541 | if plotparms: |
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[1031] | 542 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
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[515] | 543 | n = len(self.components) |
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[652] | 544 | self._p.palette(3) |
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[515] | 545 | for c in cs: |
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| 546 | if 0 <= c < n: |
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| 547 | lab = self.fitfuncs[c]+str(c) |
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| 548 | self._p.set_line(label=lab) |
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[1116] | 549 | y = ma.masked_array(self.fitter.evaluate(c), |
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[1273] | 550 | mask=logical_not(m)) |
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[1088] | 551 | |
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| 552 | self._p.plot(self.x, y) |
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[515] | 553 | elif c == -1: |
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[652] | 554 | self._p.palette(2) |
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[515] | 555 | self._p.set_line(label="Total Fit") |
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[1116] | 556 | y = ma.masked_array(self.fitter.getfit(), |
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[1273] | 557 | mask=logical_not(m)) |
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[1088] | 558 | self._p.plot(self.x, y) |
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[515] | 559 | else: |
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[652] | 560 | self._p.palette(2) |
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[515] | 561 | self._p.set_line(label='Fit') |
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[1116] | 562 | y = ma.masked_array(self.fitter.getfit(), |
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[1273] | 563 | mask=logical_not(m)) |
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[1088] | 564 | self._p.plot(self.x, y) |
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[723] | 565 | xlim=[min(self.x),max(self.x)] |
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| 566 | self._p.axes.set_xlim(xlim) |
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[113] | 567 | self._p.set_axes('xlabel',xlab) |
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| 568 | self._p.set_axes('ylabel',ylab) |
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| 569 | self._p.set_axes('title',tlab) |
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| 570 | self._p.release() |
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[723] | 571 | if (not rcParams['plotter.gui']): |
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| 572 | self._p.save(filename) |
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[113] | 573 | |
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[1589] | 574 | @print_log_dec |
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[1061] | 575 | def auto_fit(self, insitu=None, plot=False): |
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[113] | 576 | """ |
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[515] | 577 | Return a scan where the function is applied to all rows for |
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| 578 | all Beams/IFs/Pols. |
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[723] | 579 | |
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[113] | 580 | """ |
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| 581 | from asap import scantable |
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[515] | 582 | if not isinstance(self.data, scantable) : |
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[723] | 583 | msg = "Data is not a scantable" |
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| 584 | if rcParams['verbose']: |
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| 585 | print msg |
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| 586 | return |
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| 587 | else: |
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| 588 | raise TypeError(msg) |
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[259] | 589 | if insitu is None: insitu = rcParams['insitu'] |
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| 590 | if not insitu: |
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| 591 | scan = self.data.copy() |
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| 592 | else: |
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| 593 | scan = self.data |
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[880] | 594 | rows = xrange(scan.nrow()) |
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[723] | 595 | from asap import asaplog |
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[876] | 596 | asaplog.push("Fitting:") |
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| 597 | for r in rows: |
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[1536] | 598 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r), |
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| 599 | scan.getbeam(r), |
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| 600 | scan.getif(r), |
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[1589] | 601 | scan.getpol(r), |
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[1536] | 602 | scan.getcycle(r)) |
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[880] | 603 | asaplog.push(out, False) |
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[876] | 604 | self.x = scan._getabcissa(r) |
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| 605 | self.y = scan._getspectrum(r) |
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[1536] | 606 | self.mask = mask_and(self.mask, scan._getmask(r)) |
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[876] | 607 | self.data = None |
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| 608 | self.fit() |
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| 609 | x = self.get_parameters() |
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[1061] | 610 | if plot: |
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| 611 | self.plot(residual=True) |
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| 612 | x = raw_input("Accept fit ([y]/n): ") |
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| 613 | if x.upper() == 'N': |
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| 614 | continue |
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[880] | 615 | scan._setspectrum(self.fitter.getresidual(), r) |
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[1061] | 616 | if plot: |
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| 617 | self._p.unmap() |
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| 618 | self._p = None |
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[876] | 619 | return scan |
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