[113] | 1 | import _asap |
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[1826] | 2 | from asap.parameters import rcParams |
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[1862] | 3 | from asap.logging import asaplog, asaplog_post_dec |
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[1826] | 4 | from asap.utils import _n_bools, mask_and |
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[113] | 5 | |
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[1826] | 6 | |
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[113] | 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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| 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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[1391] | 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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[2153] | 32 | indicating valid points. |
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[113] | 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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[1862] | 50 | @asaplog_post_dec |
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[113] | 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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[1859] | 60 | raise TypeError(msg) |
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[113] | 61 | self.fitted = False |
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| 62 | self.data = thescan |
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[1075] | 63 | self.mask = None |
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[113] | 64 | if mask is None: |
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[1295] | 65 | self.mask = _n_bools(self.data.nchan(), True) |
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[113] | 66 | else: |
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| 67 | self.mask = mask |
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| 68 | return |
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| 69 | |
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[1862] | 70 | @asaplog_post_dec |
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[113] | 71 | def set_function(self, **kwargs): |
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| 72 | """ |
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| 73 | Set the function to be fit. |
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| 74 | Parameters: |
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[2047] | 75 | poly: use a polynomial of the order given with nonlinear least squares fit |
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| 76 | lpoly: use polynomial of the order given with linear least squares fit |
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| 77 | gauss: fit the number of gaussian specified |
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| 78 | lorentz: fit the number of lorentzian specified |
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| 79 | sinusoid: fit the number of sinusoid specified |
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[113] | 80 | Example: |
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[1391] | 81 | fitter.set_function(poly=3) # will fit a 3rd order polynomial via nonlinear method |
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| 82 | fitter.set_function(lpoly=3) # will fit a 3rd order polynomial via linear method |
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[1819] | 83 | fitter.set_function(gauss=2) # will fit two gaussians |
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| 84 | fitter.set_function(lorentz=2) # will fit two lorentzians |
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[2047] | 85 | fitter.set_function(sinusoid=3) # will fit three sinusoids |
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[113] | 86 | """ |
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[723] | 87 | #default poly order 0 |
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[515] | 88 | n=0 |
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[113] | 89 | if kwargs.has_key('poly'): |
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| 90 | self.fitfunc = 'poly' |
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[1938] | 91 | self.fitfuncs = ['poly'] |
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[113] | 92 | n = kwargs.get('poly') |
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[1938] | 93 | self.components = [n+1] |
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[1589] | 94 | self.uselinear = False |
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[1391] | 95 | elif kwargs.has_key('lpoly'): |
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| 96 | self.fitfunc = 'poly' |
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[1938] | 97 | self.fitfuncs = ['lpoly'] |
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[1391] | 98 | n = kwargs.get('lpoly') |
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[1938] | 99 | self.components = [n+1] |
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[1391] | 100 | self.uselinear = True |
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[113] | 101 | elif kwargs.has_key('gauss'): |
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| 102 | n = kwargs.get('gauss') |
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| 103 | self.fitfunc = 'gauss' |
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[515] | 104 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
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| 105 | self.components = [ 3 for i in range(n) ] |
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[1589] | 106 | self.uselinear = False |
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[1819] | 107 | elif kwargs.has_key('lorentz'): |
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| 108 | n = kwargs.get('lorentz') |
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| 109 | self.fitfunc = 'lorentz' |
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| 110 | self.fitfuncs = [ 'lorentz' for i in range(n) ] |
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| 111 | self.components = [ 3 for i in range(n) ] |
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| 112 | self.uselinear = False |
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[2047] | 113 | elif kwargs.has_key('sinusoid'): |
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| 114 | n = kwargs.get('sinusoid') |
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| 115 | self.fitfunc = 'sinusoid' |
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| 116 | self.fitfuncs = [ 'sinusoid' for i in range(n) ] |
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| 117 | self.components = [ 3 for i in range(n) ] |
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| 118 | self.uselinear = False |
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[515] | 119 | else: |
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[723] | 120 | msg = "Invalid function type." |
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[1859] | 121 | raise TypeError(msg) |
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[723] | 122 | |
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[113] | 123 | self.fitter.setexpression(self.fitfunc,n) |
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[1232] | 124 | self.fitted = False |
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[113] | 125 | return |
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[723] | 126 | |
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[1862] | 127 | @asaplog_post_dec |
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[1075] | 128 | def fit(self, row=0, estimate=False): |
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[113] | 129 | """ |
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| 130 | Execute the actual fitting process. All the state has to be set. |
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| 131 | Parameters: |
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[1075] | 132 | row: specify the row in the scantable |
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| 133 | estimate: auto-compute an initial parameter set (default False) |
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| 134 | This can be used to compute estimates even if fit was |
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| 135 | called before. |
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[113] | 136 | Example: |
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[515] | 137 | s = scantable('myscan.asap') |
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| 138 | s.set_cursor(thepol=1) # select second pol |
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[113] | 139 | f = fitter() |
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| 140 | f.set_scan(s) |
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| 141 | f.set_function(poly=0) |
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[723] | 142 | f.fit(row=0) # fit first row |
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[113] | 143 | """ |
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| 144 | if ((self.x is None or self.y is None) and self.data is None) \ |
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| 145 | or self.fitfunc is None: |
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[723] | 146 | msg = "Fitter not yet initialised. Please set data & fit function" |
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[1859] | 147 | raise RuntimeError(msg) |
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[723] | 148 | |
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[113] | 149 | else: |
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| 150 | if self.data is not None: |
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[515] | 151 | self.x = self.data._getabcissa(row) |
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| 152 | self.y = self.data._getspectrum(row) |
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[2408] | 153 | #self.mask = mask_and(self.mask, self.data._getmask(row)) |
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| 154 | if len(self.x) == len(self.mask): |
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| 155 | self.mask = mask_and(self.mask, self.data._getmask(row)) |
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| 156 | else: |
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| 157 | asaplog.push('lengths of data and mask are not the same. preset mask will be ignored') |
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| 158 | asaplog.post('WARN','asapfit.fit') |
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[2409] | 159 | self.mask=self.data._getmask(row) |
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[723] | 160 | asaplog.push("Fitting:") |
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[943] | 161 | i = row |
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[1536] | 162 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i), |
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| 163 | self.data.getbeam(i), |
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| 164 | self.data.getif(i), |
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[1589] | 165 | self.data.getpol(i), |
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[1536] | 166 | self.data.getcycle(i)) |
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[1075] | 167 | asaplog.push(out,False) |
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[515] | 168 | self.fitter.setdata(self.x, self.y, self.mask) |
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[1819] | 169 | if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz': |
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[113] | 170 | ps = self.fitter.getparameters() |
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[1075] | 171 | if len(ps) == 0 or estimate: |
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[113] | 172 | self.fitter.estimate() |
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[1859] | 173 | fxdpar = list(self.fitter.getfixedparameters()) |
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| 174 | if len(fxdpar) and fxdpar.count(0) == 0: |
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| 175 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
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| 176 | if self.uselinear: |
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| 177 | converged = self.fitter.lfit() |
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| 178 | else: |
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| 179 | converged = self.fitter.fit() |
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| 180 | if not converged: |
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| 181 | raise RuntimeError,"Fit didn't converge." |
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[515] | 182 | self._fittedrow = row |
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[113] | 183 | self.fitted = True |
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| 184 | return |
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| 185 | |
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[1232] | 186 | def store_fit(self, filename=None): |
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[526] | 187 | """ |
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[1232] | 188 | Save the fit parameters. |
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| 189 | Parameters: |
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| 190 | filename: if specified save as an ASCII file, if None (default) |
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| 191 | store it in the scnatable |
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[526] | 192 | """ |
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[515] | 193 | if self.fitted and self.data is not None: |
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| 194 | pars = list(self.fitter.getparameters()) |
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| 195 | fixed = list(self.fitter.getfixedparameters()) |
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[975] | 196 | from asap.asapfit import asapfit |
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| 197 | fit = asapfit() |
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| 198 | fit.setparameters(pars) |
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| 199 | fit.setfixedparameters(fixed) |
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| 200 | fit.setfunctions(self.fitfuncs) |
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| 201 | fit.setcomponents(self.components) |
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| 202 | fit.setframeinfo(self.data._getcoordinfo()) |
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[1232] | 203 | if filename is not None: |
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| 204 | import os |
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| 205 | filename = os.path.expandvars(os.path.expanduser(filename)) |
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| 206 | if os.path.exists(filename): |
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| 207 | raise IOError("File '%s' exists." % filename) |
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| 208 | fit.save(filename) |
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| 209 | else: |
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| 210 | self.data._addfit(fit,self._fittedrow) |
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[515] | 211 | |
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[1862] | 212 | @asaplog_post_dec |
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[1017] | 213 | def set_parameters(self,*args,**kwargs): |
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[526] | 214 | """ |
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| 215 | Set the parameters to be fitted. |
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| 216 | Parameters: |
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| 217 | params: a vector of parameters |
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| 218 | fixed: a vector of which parameters are to be held fixed |
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| 219 | (default is none) |
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[2047] | 220 | component: in case of multiple gaussians/lorentzians/sinusoidals, |
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| 221 | the index of the target component |
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[1017] | 222 | """ |
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| 223 | component = None |
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| 224 | fixed = None |
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| 225 | params = None |
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[1031] | 226 | |
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[1017] | 227 | if len(args) and isinstance(args[0],dict): |
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| 228 | kwargs = args[0] |
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| 229 | if kwargs.has_key("fixed"): fixed = kwargs["fixed"] |
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| 230 | if kwargs.has_key("params"): params = kwargs["params"] |
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| 231 | if len(args) == 2 and isinstance(args[1], int): |
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| 232 | component = args[1] |
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[515] | 233 | if self.fitfunc is None: |
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[723] | 234 | msg = "Please specify a fitting function first." |
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[1859] | 235 | raise RuntimeError(msg) |
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[2047] | 236 | if (self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid") and component is not None: |
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[1017] | 237 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
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[1295] | 238 | pars = _n_bools(len(self.components)*3, False) |
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[2047] | 239 | fxd = _n_bools(len(pars), False) |
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[515] | 240 | else: |
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[723] | 241 | pars = list(self.fitter.getparameters()) |
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[2047] | 242 | fxd = list(self.fitter.getfixedparameters()) |
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[515] | 243 | i = 3*component |
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| 244 | pars[i:i+3] = params |
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[2047] | 245 | fxd[i:i+3] = fixed |
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[515] | 246 | params = pars |
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[2047] | 247 | fixed = fxd |
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[113] | 248 | self.fitter.setparameters(params) |
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| 249 | if fixed is not None: |
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| 250 | self.fitter.setfixedparameters(fixed) |
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| 251 | return |
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[515] | 252 | |
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[1862] | 253 | @asaplog_post_dec |
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[1217] | 254 | def set_gauss_parameters(self, peak, centre, fwhm, |
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[1409] | 255 | peakfixed=0, centrefixed=0, |
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[1217] | 256 | fwhmfixed=0, |
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[515] | 257 | component=0): |
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[113] | 258 | """ |
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[515] | 259 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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| 260 | Parameters: |
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[1232] | 261 | peak, centre, fwhm: The gaussian parameters |
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[515] | 262 | peakfixed, |
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[1409] | 263 | centrefixed, |
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[1217] | 264 | fwhmfixed: Optional parameters to indicate if |
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[515] | 265 | the paramters should be held fixed during |
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| 266 | the fitting process. The default is to keep |
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| 267 | all parameters flexible. |
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[526] | 268 | component: The number of the component (Default is the |
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| 269 | component 0) |
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[515] | 270 | """ |
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| 271 | if self.fitfunc != "gauss": |
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[723] | 272 | msg = "Function only operates on Gaussian components." |
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[1859] | 273 | raise ValueError(msg) |
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[515] | 274 | if 0 <= component < len(self.components): |
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[1217] | 275 | d = {'params':[peak, centre, fwhm], |
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[1409] | 276 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
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[1017] | 277 | self.set_parameters(d, component) |
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[515] | 278 | else: |
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[723] | 279 | msg = "Please select a valid component." |
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[1859] | 280 | raise ValueError(msg) |
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[723] | 281 | |
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[1862] | 282 | @asaplog_post_dec |
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[1819] | 283 | def set_lorentz_parameters(self, peak, centre, fwhm, |
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| 284 | peakfixed=0, centrefixed=0, |
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| 285 | fwhmfixed=0, |
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| 286 | component=0): |
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| 287 | """ |
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| 288 | Set the Parameters of a 'Lorentzian' component, set with set_function. |
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| 289 | Parameters: |
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[1927] | 290 | peak, centre, fwhm: The lorentzian parameters |
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[1819] | 291 | peakfixed, |
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| 292 | centrefixed, |
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| 293 | fwhmfixed: Optional parameters to indicate if |
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| 294 | the paramters should be held fixed during |
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| 295 | the fitting process. The default is to keep |
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| 296 | all parameters flexible. |
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| 297 | component: The number of the component (Default is the |
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| 298 | component 0) |
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| 299 | """ |
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| 300 | if self.fitfunc != "lorentz": |
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| 301 | msg = "Function only operates on Lorentzian components." |
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[1859] | 302 | raise ValueError(msg) |
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[1819] | 303 | if 0 <= component < len(self.components): |
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| 304 | d = {'params':[peak, centre, fwhm], |
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| 305 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
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| 306 | self.set_parameters(d, component) |
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| 307 | else: |
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| 308 | msg = "Please select a valid component." |
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[1859] | 309 | raise ValueError(msg) |
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[1819] | 310 | |
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[2047] | 311 | @asaplog_post_dec |
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| 312 | def set_sinusoid_parameters(self, ampl, period, x0, |
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| 313 | amplfixed=0, periodfixed=0, |
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| 314 | x0fixed=0, |
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| 315 | component=0): |
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| 316 | """ |
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| 317 | Set the Parameters of a 'Sinusoidal' component, set with set_function. |
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| 318 | Parameters: |
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| 319 | ampl, period, x0: The sinusoidal parameters |
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| 320 | amplfixed, |
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| 321 | periodfixed, |
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| 322 | x0fixed: Optional parameters to indicate if |
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| 323 | the paramters should be held fixed during |
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| 324 | the fitting process. The default is to keep |
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| 325 | all parameters flexible. |
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| 326 | component: The number of the component (Default is the |
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| 327 | component 0) |
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| 328 | """ |
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| 329 | if self.fitfunc != "sinusoid": |
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| 330 | msg = "Function only operates on Sinusoidal components." |
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| 331 | raise ValueError(msg) |
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| 332 | if 0 <= component < len(self.components): |
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| 333 | d = {'params':[ampl, period, x0], |
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| 334 | 'fixed': [amplfixed, periodfixed, x0fixed]} |
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| 335 | self.set_parameters(d, component) |
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| 336 | else: |
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| 337 | msg = "Please select a valid component." |
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| 338 | raise ValueError(msg) |
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| 339 | |
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[975] | 340 | def get_area(self, component=None): |
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| 341 | """ |
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[1819] | 342 | Return the area under the fitted gaussian/lorentzian component. |
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[975] | 343 | Parameters: |
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[1819] | 344 | component: the gaussian/lorentzian component selection, |
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[975] | 345 | default (None) is the sum of all components |
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| 346 | Note: |
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[1819] | 347 | This will only work for gaussian/lorentzian fits. |
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[975] | 348 | """ |
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| 349 | if not self.fitted: return |
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[1819] | 350 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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[975] | 351 | pars = list(self.fitter.getparameters()) |
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| 352 | from math import log,pi,sqrt |
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[1819] | 353 | if self.fitfunc == "gauss": |
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| 354 | fac = sqrt(pi/log(16.0)) |
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| 355 | elif self.fitfunc == "lorentz": |
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| 356 | fac = pi/2.0 |
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[975] | 357 | areas = [] |
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| 358 | for i in range(len(self.components)): |
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| 359 | j = i*3 |
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| 360 | cpars = pars[j:j+3] |
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| 361 | areas.append(fac * cpars[0] * cpars[2]) |
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| 362 | else: |
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| 363 | return None |
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| 364 | if component is not None: |
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| 365 | return areas[component] |
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| 366 | else: |
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| 367 | return sum(areas) |
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| 368 | |
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[1862] | 369 | @asaplog_post_dec |
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[1075] | 370 | def get_errors(self, component=None): |
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[515] | 371 | """ |
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[1075] | 372 | Return the errors in the parameters. |
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| 373 | Parameters: |
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| 374 | component: get the errors for the specified component |
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| 375 | only, default is all components |
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| 376 | """ |
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| 377 | if not self.fitted: |
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| 378 | msg = "Not yet fitted." |
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[1859] | 379 | raise RuntimeError(msg) |
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[1075] | 380 | errs = list(self.fitter.geterrors()) |
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| 381 | cerrs = errs |
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| 382 | if component is not None: |
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[2047] | 383 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid": |
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[1075] | 384 | i = 3*component |
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| 385 | if i < len(errs): |
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| 386 | cerrs = errs[i:i+3] |
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| 387 | return cerrs |
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| 388 | |
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[1859] | 389 | |
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[1862] | 390 | @asaplog_post_dec |
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[1075] | 391 | def get_parameters(self, component=None, errors=False): |
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| 392 | """ |
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[113] | 393 | Return the fit paramters. |
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[526] | 394 | Parameters: |
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| 395 | component: get the parameters for the specified component |
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| 396 | only, default is all components |
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[113] | 397 | """ |
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| 398 | if not self.fitted: |
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[723] | 399 | msg = "Not yet fitted." |
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[1859] | 400 | raise RuntimeError(msg) |
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[113] | 401 | pars = list(self.fitter.getparameters()) |
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| 402 | fixed = list(self.fitter.getfixedparameters()) |
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[1075] | 403 | errs = list(self.fitter.geterrors()) |
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[1039] | 404 | area = [] |
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[723] | 405 | if component is not None: |
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[2047] | 406 | if self.fitfunc == "poly" or self.fitfunc == "lpoly": |
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| 407 | cpars = pars |
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| 408 | cfixed = fixed |
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| 409 | cerrs = errs |
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| 410 | else: |
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[515] | 411 | i = 3*component |
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| 412 | cpars = pars[i:i+3] |
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| 413 | cfixed = fixed[i:i+3] |
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[1075] | 414 | cerrs = errs[i:i+3] |
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[2047] | 415 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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| 416 | a = self.get_area(component) |
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| 417 | area = [a for i in range(3)] |
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[515] | 418 | else: |
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| 419 | cpars = pars |
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| 420 | cfixed = fixed |
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[1075] | 421 | cerrs = errs |
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[1819] | 422 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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[1039] | 423 | for c in range(len(self.components)): |
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[2047] | 424 | a = self.get_area(c) |
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| 425 | area += [a for i in range(3)] |
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[1088] | 426 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
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[1859] | 427 | asaplog.push(fpars) |
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[1075] | 428 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
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| 429 | 'errors':cerrs} |
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[723] | 430 | |
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[1075] | 431 | def _format_pars(self, pars, fixed, errors, area): |
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[113] | 432 | out = '' |
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[2047] | 433 | if self.fitfunc == "poly" or self.fitfunc == "lpoly": |
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[113] | 434 | c = 0 |
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[515] | 435 | for i in range(len(pars)): |
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| 436 | fix = "" |
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[1232] | 437 | if len(fixed) and fixed[i]: fix = "(fixed)" |
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[2047] | 438 | out += " p%d%s= %3.6f" % (c, fix, pars[i]) |
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| 439 | if errors : out += " (%1.6f)" % errors[i] |
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| 440 | out += "," |
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[113] | 441 | c+=1 |
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[515] | 442 | out = out[:-1] # remove trailing ',' |
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[2047] | 443 | else: |
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[113] | 444 | i = 0 |
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| 445 | c = 0 |
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[2047] | 446 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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| 447 | pnam = ["peak", "centre", "FWHM"] |
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| 448 | elif self.fitfunc == "sinusoid": |
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| 449 | pnam = ["amplitude", "period", "x0"] |
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| 450 | aunit = "" |
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| 451 | ounit = "" |
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[113] | 452 | if self.data: |
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[515] | 453 | aunit = self.data.get_unit() |
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| 454 | ounit = self.data.get_fluxunit() |
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[113] | 455 | while i < len(pars): |
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[2047] | 456 | fix0 = fix1 = fix2 = "" |
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| 457 | if i < len(fixed)-2: |
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| 458 | if fixed[i]: fix0 = "(fixed)" |
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| 459 | if fixed[i+1]: fix1 = "(fixed)" |
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| 460 | if fixed[i+2]: fix2 = "(fixed)" |
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| 461 | out += " %2d: " % c |
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| 462 | out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit) |
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| 463 | out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit) |
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| 464 | out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit) |
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| 465 | if len(area): out += " area = %3.3f %s %s\n" % (area[i], ounit, aunit) |
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[113] | 466 | c+=1 |
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| 467 | i+=3 |
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| 468 | return out |
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[723] | 469 | |
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[1859] | 470 | |
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[1862] | 471 | @asaplog_post_dec |
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[113] | 472 | def get_estimate(self): |
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| 473 | """ |
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[515] | 474 | Return the parameter estimates (for non-linear functions). |
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[113] | 475 | """ |
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| 476 | pars = self.fitter.getestimate() |
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[943] | 477 | fixed = self.fitter.getfixedparameters() |
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[1927] | 478 | asaplog.push(self._format_pars(pars,fixed,None,None)) |
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[113] | 479 | return pars |
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| 480 | |
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[1862] | 481 | @asaplog_post_dec |
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[113] | 482 | def get_residual(self): |
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| 483 | """ |
---|
| 484 | Return the residual of the fit. |
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| 485 | """ |
---|
| 486 | if not self.fitted: |
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[723] | 487 | msg = "Not yet fitted." |
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[1859] | 488 | raise RuntimeError(msg) |
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[113] | 489 | return self.fitter.getresidual() |
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| 490 | |
---|
[1862] | 491 | @asaplog_post_dec |
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[113] | 492 | def get_chi2(self): |
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| 493 | """ |
---|
| 494 | Return chi^2. |
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| 495 | """ |
---|
| 496 | if not self.fitted: |
---|
[723] | 497 | msg = "Not yet fitted." |
---|
[1859] | 498 | raise RuntimeError(msg) |
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[113] | 499 | ch2 = self.fitter.getchi2() |
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[1859] | 500 | asaplog.push( 'Chi^2 = %3.3f' % (ch2) ) |
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[723] | 501 | return ch2 |
---|
[113] | 502 | |
---|
[1862] | 503 | @asaplog_post_dec |
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[113] | 504 | def get_fit(self): |
---|
| 505 | """ |
---|
| 506 | Return the fitted ordinate values. |
---|
| 507 | """ |
---|
| 508 | if not self.fitted: |
---|
[723] | 509 | msg = "Not yet fitted." |
---|
[1859] | 510 | raise RuntimeError(msg) |
---|
[113] | 511 | return self.fitter.getfit() |
---|
| 512 | |
---|
[1862] | 513 | @asaplog_post_dec |
---|
[113] | 514 | def commit(self): |
---|
| 515 | """ |
---|
[526] | 516 | Return a new scan where the fits have been commited (subtracted) |
---|
[113] | 517 | """ |
---|
| 518 | if not self.fitted: |
---|
[723] | 519 | msg = "Not yet fitted." |
---|
[1859] | 520 | raise RuntimeError(msg) |
---|
[975] | 521 | from asap import scantable |
---|
| 522 | if not isinstance(self.data, scantable): |
---|
[723] | 523 | msg = "Not a scantable" |
---|
[1859] | 524 | raise TypeError(msg) |
---|
[113] | 525 | scan = self.data.copy() |
---|
[259] | 526 | scan._setspectrum(self.fitter.getresidual()) |
---|
[1092] | 527 | return scan |
---|
[113] | 528 | |
---|
[1862] | 529 | @asaplog_post_dec |
---|
[1689] | 530 | def plot(self, residual=False, components=None, plotparms=False, |
---|
| 531 | filename=None): |
---|
[113] | 532 | """ |
---|
| 533 | Plot the last fit. |
---|
| 534 | Parameters: |
---|
| 535 | residual: an optional parameter indicating if the residual |
---|
| 536 | should be plotted (default 'False') |
---|
[526] | 537 | components: a list of components to plot, e.g [0,1], |
---|
| 538 | -1 plots the total fit. Default is to only |
---|
| 539 | plot the total fit. |
---|
| 540 | plotparms: Inidicates if the parameter values should be present |
---|
| 541 | on the plot |
---|
[113] | 542 | """ |
---|
| 543 | if not self.fitted: |
---|
| 544 | return |
---|
[723] | 545 | if not self._p or self._p.is_dead: |
---|
[2150] | 546 | from asap.asapplotter import new_asaplot |
---|
[2451] | 547 | del self._p |
---|
[2150] | 548 | self._p = new_asaplot(rcParams['plotter.gui']) |
---|
[723] | 549 | self._p.hold() |
---|
[113] | 550 | self._p.clear() |
---|
[515] | 551 | self._p.set_panels() |
---|
[652] | 552 | self._p.palette(0) |
---|
[113] | 553 | tlab = 'Spectrum' |
---|
[723] | 554 | xlab = 'Abcissa' |
---|
[1017] | 555 | ylab = 'Ordinate' |
---|
[1739] | 556 | from numpy import ma,logical_not,logical_and,array |
---|
[1273] | 557 | m = self.mask |
---|
[113] | 558 | if self.data: |
---|
[515] | 559 | tlab = self.data._getsourcename(self._fittedrow) |
---|
| 560 | xlab = self.data._getabcissalabel(self._fittedrow) |
---|
[2153] | 561 | if self.data._getflagrow(self._fittedrow): |
---|
| 562 | m = [False] |
---|
| 563 | else: |
---|
| 564 | m = logical_and(self.mask, |
---|
| 565 | array(self.data._getmask(self._fittedrow), |
---|
| 566 | copy=False)) |
---|
[1589] | 567 | |
---|
[626] | 568 | ylab = self.data._get_ordinate_label() |
---|
[515] | 569 | |
---|
[1075] | 570 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
---|
[1819] | 571 | nomask=True |
---|
| 572 | for i in range(len(m)): |
---|
| 573 | nomask = nomask and m[i] |
---|
[2153] | 574 | if len(m) == 1: |
---|
| 575 | m = m[0] |
---|
| 576 | invm = (not m) |
---|
| 577 | else: |
---|
| 578 | invm = logical_not(m) |
---|
[1819] | 579 | label0='Masked Region' |
---|
| 580 | label1='Spectrum' |
---|
| 581 | if ( nomask ): |
---|
| 582 | label0=label1 |
---|
| 583 | else: |
---|
| 584 | y = ma.masked_array( self.y, mask = m ) |
---|
| 585 | self._p.palette(1,colours) |
---|
| 586 | self._p.set_line( label = label1 ) |
---|
| 587 | self._p.plot( self.x, y ) |
---|
[652] | 588 | self._p.palette(0,colours) |
---|
[1819] | 589 | self._p.set_line(label=label0) |
---|
[2153] | 590 | y = ma.masked_array(self.y,mask=invm) |
---|
[1088] | 591 | self._p.plot(self.x, y) |
---|
[113] | 592 | if residual: |
---|
[1819] | 593 | self._p.palette(7) |
---|
[515] | 594 | self._p.set_line(label='Residual') |
---|
[1116] | 595 | y = ma.masked_array(self.get_residual(), |
---|
[2153] | 596 | mask=invm) |
---|
[1088] | 597 | self._p.plot(self.x, y) |
---|
[652] | 598 | self._p.palette(2) |
---|
[515] | 599 | if components is not None: |
---|
| 600 | cs = components |
---|
| 601 | if isinstance(components,int): cs = [components] |
---|
[526] | 602 | if plotparms: |
---|
[1031] | 603 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
---|
[515] | 604 | n = len(self.components) |
---|
[652] | 605 | self._p.palette(3) |
---|
[515] | 606 | for c in cs: |
---|
| 607 | if 0 <= c < n: |
---|
| 608 | lab = self.fitfuncs[c]+str(c) |
---|
| 609 | self._p.set_line(label=lab) |
---|
[2153] | 610 | y = ma.masked_array(self.fitter.evaluate(c), mask=invm) |
---|
[1088] | 611 | |
---|
| 612 | self._p.plot(self.x, y) |
---|
[515] | 613 | elif c == -1: |
---|
[652] | 614 | self._p.palette(2) |
---|
[515] | 615 | self._p.set_line(label="Total Fit") |
---|
[1116] | 616 | y = ma.masked_array(self.fitter.getfit(), |
---|
[2153] | 617 | mask=invm) |
---|
[1088] | 618 | self._p.plot(self.x, y) |
---|
[515] | 619 | else: |
---|
[652] | 620 | self._p.palette(2) |
---|
[515] | 621 | self._p.set_line(label='Fit') |
---|
[2153] | 622 | y = ma.masked_array(self.fitter.getfit(),mask=invm) |
---|
[1088] | 623 | self._p.plot(self.x, y) |
---|
[723] | 624 | xlim=[min(self.x),max(self.x)] |
---|
| 625 | self._p.axes.set_xlim(xlim) |
---|
[113] | 626 | self._p.set_axes('xlabel',xlab) |
---|
| 627 | self._p.set_axes('ylabel',ylab) |
---|
| 628 | self._p.set_axes('title',tlab) |
---|
| 629 | self._p.release() |
---|
[723] | 630 | if (not rcParams['plotter.gui']): |
---|
| 631 | self._p.save(filename) |
---|
[113] | 632 | |
---|
[1862] | 633 | @asaplog_post_dec |
---|
[1061] | 634 | def auto_fit(self, insitu=None, plot=False): |
---|
[113] | 635 | """ |
---|
[515] | 636 | Return a scan where the function is applied to all rows for |
---|
| 637 | all Beams/IFs/Pols. |
---|
[723] | 638 | |
---|
[113] | 639 | """ |
---|
| 640 | from asap import scantable |
---|
[515] | 641 | if not isinstance(self.data, scantable) : |
---|
[723] | 642 | msg = "Data is not a scantable" |
---|
[1859] | 643 | raise TypeError(msg) |
---|
[259] | 644 | if insitu is None: insitu = rcParams['insitu'] |
---|
| 645 | if not insitu: |
---|
| 646 | scan = self.data.copy() |
---|
| 647 | else: |
---|
| 648 | scan = self.data |
---|
[880] | 649 | rows = xrange(scan.nrow()) |
---|
[1826] | 650 | # Save parameters of baseline fits as a class attribute. |
---|
[1819] | 651 | # NOTICE: This does not reflect changes in scantable! |
---|
| 652 | if len(rows) > 0: self.blpars=[] |
---|
[876] | 653 | asaplog.push("Fitting:") |
---|
| 654 | for r in rows: |
---|
[1536] | 655 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r), |
---|
| 656 | scan.getbeam(r), |
---|
| 657 | scan.getif(r), |
---|
[1589] | 658 | scan.getpol(r), |
---|
[1536] | 659 | scan.getcycle(r)) |
---|
[880] | 660 | asaplog.push(out, False) |
---|
[876] | 661 | self.x = scan._getabcissa(r) |
---|
| 662 | self.y = scan._getspectrum(r) |
---|
[2409] | 663 | #self.mask = mask_and(self.mask, scan._getmask(r)) |
---|
[2408] | 664 | if len(self.x) == len(self.mask): |
---|
| 665 | self.mask = mask_and(self.mask, self.data._getmask(row)) |
---|
| 666 | else: |
---|
| 667 | asaplog.push('lengths of data and mask are not the same. preset mask will be ignored') |
---|
| 668 | asaplog.post('WARN','asapfit.fit') |
---|
[2409] | 669 | self.mask=self.data._getmask(row) |
---|
[876] | 670 | self.data = None |
---|
| 671 | self.fit() |
---|
| 672 | x = self.get_parameters() |
---|
[1819] | 673 | fpar = self.get_parameters() |
---|
[1061] | 674 | if plot: |
---|
| 675 | self.plot(residual=True) |
---|
| 676 | x = raw_input("Accept fit ([y]/n): ") |
---|
| 677 | if x.upper() == 'N': |
---|
[1819] | 678 | self.blpars.append(None) |
---|
[1061] | 679 | continue |
---|
[880] | 680 | scan._setspectrum(self.fitter.getresidual(), r) |
---|
[1819] | 681 | self.blpars.append(fpar) |
---|
[1061] | 682 | if plot: |
---|
[2151] | 683 | self._p.quit() |
---|
| 684 | del self._p |
---|
[1061] | 685 | self._p = None |
---|
[876] | 686 | return scan |
---|