1 | import _asap |
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2 | from asap.parameters import rcParams |
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3 | from asap.logging import asaplog, asaplog_post_dec |
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4 | from asap.utils import _n_bools, mask_and |
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5 | |
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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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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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20 | self.fitfuncs = None |
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21 | self.fitted = False |
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22 | self.data = None |
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23 | self.components = 0 |
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24 | self._fittedrow = 0 |
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25 | self._p = None |
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26 | self._selection = None |
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27 | self.uselinear = False |
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28 | |
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29 | def set_data(self, xdat, ydat, mask=None): |
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30 | """ |
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31 | Set the absissa and ordinate for the fit. Also set the mask |
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32 | indicationg valid points. |
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33 | This can be used for data vectors retrieved from a scantable. |
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34 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
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35 | Parameters: |
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36 | xdat: the abcissa values |
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37 | ydat: the ordinate values |
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38 | mask: an optional mask |
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39 | |
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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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45 | self.mask = _n_bools(len(xdat), True) |
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46 | else: |
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47 | self.mask = mask |
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48 | return |
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49 | |
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50 | @asaplog_post_dec |
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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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56 | mask: a msk retrieved from the scantable |
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57 | """ |
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58 | if not thescan: |
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59 | msg = "Please give a correct scan" |
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60 | raise TypeError(msg) |
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61 | self.fitted = False |
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62 | self.data = thescan |
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63 | self.mask = None |
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64 | if mask is None: |
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65 | self.mask = _n_bools(self.data.nchan(), True) |
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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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70 | @asaplog_post_dec |
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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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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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80 | Example: |
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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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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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85 | fitter.set_function(sinusoid=3) # will fit three sinusoids |
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86 | """ |
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87 | #default poly order 0 |
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88 | n=0 |
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89 | if kwargs.has_key('poly'): |
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90 | self.fitfunc = 'poly' |
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91 | self.fitfuncs = ['poly'] |
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92 | n = kwargs.get('poly') |
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93 | self.components = [n+1] |
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94 | self.uselinear = False |
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95 | elif kwargs.has_key('lpoly'): |
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96 | self.fitfunc = 'poly' |
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97 | self.fitfuncs = ['lpoly'] |
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98 | n = kwargs.get('lpoly') |
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99 | self.components = [n+1] |
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100 | self.uselinear = True |
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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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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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106 | self.uselinear = False |
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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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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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119 | else: |
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120 | msg = "Invalid function type." |
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121 | raise TypeError(msg) |
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122 | |
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123 | self.fitter.setexpression(self.fitfunc,n) |
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124 | self.fitted = False |
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125 | return |
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126 | |
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127 | @asaplog_post_dec |
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128 | def fit(self, row=0, estimate=False): |
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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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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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136 | Example: |
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137 | s = scantable('myscan.asap') |
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138 | s.set_cursor(thepol=1) # select second pol |
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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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142 | f.fit(row=0) # fit first row |
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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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146 | msg = "Fitter not yet initialised. Please set data & fit function" |
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147 | raise RuntimeError(msg) |
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148 | |
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149 | else: |
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150 | if self.data is not None: |
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151 | self.x = self.data._getabcissa(row) |
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152 | self.y = self.data._getspectrum(row) |
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153 | self.mask = mask_and(self.mask, self.data._getmask(row)) |
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154 | asaplog.push("Fitting:") |
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155 | i = row |
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156 | out = "Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (self.data.getscan(i), |
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157 | self.data.getbeam(i), |
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158 | self.data.getif(i), |
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159 | self.data.getpol(i), |
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160 | self.data.getcycle(i)) |
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161 | asaplog.push(out,False) |
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162 | self.fitter.setdata(self.x, self.y, self.mask) |
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163 | if self.fitfunc == 'gauss' or self.fitfunc == 'lorentz': |
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164 | ps = self.fitter.getparameters() |
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165 | if len(ps) == 0 or estimate: |
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166 | self.fitter.estimate() |
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167 | fxdpar = list(self.fitter.getfixedparameters()) |
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168 | if len(fxdpar) and fxdpar.count(0) == 0: |
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169 | raise RuntimeError,"No point fitting, if all parameters are fixed." |
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170 | if self.uselinear: |
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171 | converged = self.fitter.lfit() |
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172 | else: |
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173 | converged = self.fitter.fit() |
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174 | if not converged: |
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175 | raise RuntimeError,"Fit didn't converge." |
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176 | self._fittedrow = row |
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177 | self.fitted = True |
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178 | return |
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179 | |
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180 | def store_fit(self, filename=None): |
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181 | """ |
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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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186 | """ |
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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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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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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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205 | |
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206 | @asaplog_post_dec |
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207 | def set_parameters(self,*args,**kwargs): |
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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/lorentzians/sinusoidals, |
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215 | the index of the target component |
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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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220 | |
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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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227 | if self.fitfunc is None: |
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228 | msg = "Please specify a fitting function first." |
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229 | raise RuntimeError(msg) |
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230 | if (self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid") and component is not None: |
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231 | if not self.fitted and sum(self.fitter.getparameters()) == 0: |
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232 | pars = _n_bools(len(self.components)*3, False) |
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233 | fxd = _n_bools(len(pars), False) |
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234 | else: |
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235 | pars = list(self.fitter.getparameters()) |
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236 | fxd = list(self.fitter.getfixedparameters()) |
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237 | i = 3*component |
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238 | pars[i:i+3] = params |
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239 | fxd[i:i+3] = fixed |
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240 | params = pars |
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241 | fixed = fxd |
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242 | self.fitter.setparameters(params) |
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243 | if fixed is not None: |
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244 | self.fitter.setfixedparameters(fixed) |
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245 | return |
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246 | |
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247 | @asaplog_post_dec |
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248 | def set_gauss_parameters(self, peak, centre, fwhm, |
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249 | peakfixed=0, centrefixed=0, |
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250 | fwhmfixed=0, |
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251 | component=0): |
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252 | """ |
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253 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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254 | Parameters: |
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255 | peak, centre, fwhm: The gaussian parameters |
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256 | peakfixed, |
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257 | centrefixed, |
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258 | fwhmfixed: Optional parameters to indicate if |
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259 | the paramters should be held fixed during |
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260 | the fitting process. The default is to keep |
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261 | all parameters flexible. |
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262 | component: The number of the component (Default is the |
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263 | component 0) |
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264 | """ |
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265 | if self.fitfunc != "gauss": |
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266 | msg = "Function only operates on Gaussian components." |
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267 | raise ValueError(msg) |
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268 | if 0 <= component < len(self.components): |
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269 | d = {'params':[peak, centre, fwhm], |
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270 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
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271 | self.set_parameters(d, component) |
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272 | else: |
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273 | msg = "Please select a valid component." |
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274 | raise ValueError(msg) |
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275 | |
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276 | @asaplog_post_dec |
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277 | def set_lorentz_parameters(self, peak, centre, fwhm, |
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278 | peakfixed=0, centrefixed=0, |
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279 | fwhmfixed=0, |
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280 | component=0): |
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281 | """ |
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282 | Set the Parameters of a 'Lorentzian' component, set with set_function. |
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283 | Parameters: |
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284 | peak, centre, fwhm: The lorentzian parameters |
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285 | peakfixed, |
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286 | centrefixed, |
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287 | fwhmfixed: Optional parameters to indicate if |
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288 | the paramters should be held fixed during |
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289 | the fitting process. The default is to keep |
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290 | all parameters flexible. |
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291 | component: The number of the component (Default is the |
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292 | component 0) |
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293 | """ |
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294 | if self.fitfunc != "lorentz": |
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295 | msg = "Function only operates on Lorentzian components." |
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296 | raise ValueError(msg) |
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297 | if 0 <= component < len(self.components): |
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298 | d = {'params':[peak, centre, fwhm], |
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299 | 'fixed':[peakfixed, centrefixed, fwhmfixed]} |
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300 | self.set_parameters(d, component) |
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301 | else: |
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302 | msg = "Please select a valid component." |
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303 | raise ValueError(msg) |
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304 | |
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305 | @asaplog_post_dec |
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306 | def set_sinusoid_parameters(self, ampl, period, x0, |
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307 | amplfixed=0, periodfixed=0, |
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308 | x0fixed=0, |
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309 | component=0): |
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310 | """ |
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311 | Set the Parameters of a 'Sinusoidal' component, set with set_function. |
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312 | Parameters: |
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313 | ampl, period, x0: The sinusoidal parameters |
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314 | amplfixed, |
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315 | periodfixed, |
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316 | x0fixed: Optional parameters to indicate if |
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317 | the paramters should be held fixed during |
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318 | the fitting process. The default is to keep |
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319 | all parameters flexible. |
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320 | component: The number of the component (Default is the |
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321 | component 0) |
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322 | """ |
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323 | if self.fitfunc != "sinusoid": |
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324 | msg = "Function only operates on Sinusoidal components." |
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325 | raise ValueError(msg) |
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326 | if 0 <= component < len(self.components): |
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327 | d = {'params':[ampl, period, x0], |
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328 | 'fixed': [amplfixed, periodfixed, x0fixed]} |
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329 | self.set_parameters(d, component) |
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330 | else: |
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331 | msg = "Please select a valid component." |
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332 | raise ValueError(msg) |
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333 | |
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334 | def get_area(self, component=None): |
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335 | """ |
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336 | Return the area under the fitted gaussian/lorentzian component. |
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337 | Parameters: |
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338 | component: the gaussian/lorentzian component selection, |
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339 | default (None) is the sum of all components |
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340 | Note: |
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341 | This will only work for gaussian/lorentzian fits. |
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342 | """ |
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343 | if not self.fitted: return |
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344 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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345 | pars = list(self.fitter.getparameters()) |
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346 | from math import log,pi,sqrt |
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347 | if self.fitfunc == "gauss": |
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348 | fac = sqrt(pi/log(16.0)) |
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349 | elif self.fitfunc == "lorentz": |
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350 | fac = pi/2.0 |
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351 | areas = [] |
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352 | for i in range(len(self.components)): |
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353 | j = i*3 |
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354 | cpars = pars[j:j+3] |
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355 | areas.append(fac * cpars[0] * cpars[2]) |
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356 | else: |
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357 | return None |
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358 | if component is not None: |
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359 | return areas[component] |
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360 | else: |
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361 | return sum(areas) |
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362 | |
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363 | @asaplog_post_dec |
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364 | def get_errors(self, component=None): |
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365 | """ |
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366 | Return the errors in the parameters. |
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367 | Parameters: |
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368 | component: get the errors for the specified component |
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369 | only, default is all components |
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370 | """ |
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371 | if not self.fitted: |
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372 | msg = "Not yet fitted." |
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373 | raise RuntimeError(msg) |
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374 | errs = list(self.fitter.geterrors()) |
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375 | cerrs = errs |
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376 | if component is not None: |
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377 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz" or self.fitfunc == "sinusoid": |
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378 | i = 3*component |
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379 | if i < len(errs): |
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380 | cerrs = errs[i:i+3] |
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381 | return cerrs |
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382 | |
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383 | |
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384 | @asaplog_post_dec |
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385 | def get_parameters(self, component=None, errors=False): |
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386 | """ |
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387 | Return the fit paramters. |
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388 | Parameters: |
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389 | component: get the parameters for the specified component |
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390 | only, default is all components |
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391 | """ |
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392 | if not self.fitted: |
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393 | msg = "Not yet fitted." |
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394 | raise RuntimeError(msg) |
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395 | pars = list(self.fitter.getparameters()) |
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396 | fixed = list(self.fitter.getfixedparameters()) |
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397 | errs = list(self.fitter.geterrors()) |
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398 | area = [] |
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399 | if component is not None: |
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400 | if self.fitfunc == "poly" or self.fitfunc == "lpoly": |
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401 | cpars = pars |
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402 | cfixed = fixed |
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403 | cerrs = errs |
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404 | else: |
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405 | i = 3*component |
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406 | cpars = pars[i:i+3] |
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407 | cfixed = fixed[i:i+3] |
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408 | cerrs = errs[i:i+3] |
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409 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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410 | a = self.get_area(component) |
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411 | area = [a for i in range(3)] |
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412 | else: |
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413 | cpars = pars |
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414 | cfixed = fixed |
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415 | cerrs = errs |
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416 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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417 | for c in range(len(self.components)): |
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418 | a = self.get_area(c) |
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419 | area += [a for i in range(3)] |
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420 | fpars = self._format_pars(cpars, cfixed, errors and cerrs, area) |
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421 | asaplog.push(fpars) |
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422 | return {'params':cpars, 'fixed':cfixed, 'formatted': fpars, |
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423 | 'errors':cerrs} |
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424 | |
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425 | def _format_pars(self, pars, fixed, errors, area): |
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426 | out = '' |
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427 | if self.fitfunc == "poly" or self.fitfunc == "lpoly": |
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428 | c = 0 |
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429 | for i in range(len(pars)): |
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430 | fix = "" |
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431 | if len(fixed) and fixed[i]: fix = "(fixed)" |
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432 | out += " p%d%s= %3.6f" % (c, fix, pars[i]) |
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433 | if errors : out += " (%1.6f)" % errors[i] |
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434 | out += "," |
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435 | c+=1 |
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436 | out = out[:-1] # remove trailing ',' |
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437 | else: |
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438 | i = 0 |
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439 | c = 0 |
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440 | if self.fitfunc == "gauss" or self.fitfunc == "lorentz": |
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441 | pnam = ["peak", "centre", "FWHM"] |
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442 | elif self.fitfunc == "sinusoid": |
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443 | pnam = ["amplitude", "period", "x0"] |
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444 | aunit = "" |
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445 | ounit = "" |
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446 | if self.data: |
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447 | aunit = self.data.get_unit() |
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448 | ounit = self.data.get_fluxunit() |
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449 | while i < len(pars): |
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450 | fix0 = fix1 = fix2 = "" |
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451 | if i < len(fixed)-2: |
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452 | if fixed[i]: fix0 = "(fixed)" |
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453 | if fixed[i+1]: fix1 = "(fixed)" |
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454 | if fixed[i+2]: fix2 = "(fixed)" |
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455 | out += " %2d: " % c |
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456 | out += "%s%s = %3.3f %s, " % (pnam[0], fix0, pars[i], ounit) |
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457 | out += "%s%s = %3.3f %s, " % (pnam[1], fix1, pars[i+1], aunit) |
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458 | out += "%s%s = %3.3f %s\n" % (pnam[2], fix2, pars[i+2], aunit) |
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459 | if len(area): out += " area = %3.3f %s %s\n" % (area[i], ounit, aunit) |
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460 | c+=1 |
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461 | i+=3 |
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462 | return out |
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463 | |
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464 | |
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465 | @asaplog_post_dec |
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466 | def get_estimate(self): |
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467 | """ |
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468 | Return the parameter estimates (for non-linear functions). |
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469 | """ |
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470 | pars = self.fitter.getestimate() |
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471 | fixed = self.fitter.getfixedparameters() |
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472 | asaplog.push(self._format_pars(pars,fixed,None,None)) |
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473 | return pars |
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474 | |
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475 | @asaplog_post_dec |
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476 | def get_residual(self): |
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477 | """ |
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478 | Return the residual of the fit. |
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479 | """ |
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480 | if not self.fitted: |
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481 | msg = "Not yet fitted." |
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482 | raise RuntimeError(msg) |
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483 | return self.fitter.getresidual() |
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484 | |
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485 | @asaplog_post_dec |
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486 | def get_chi2(self): |
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487 | """ |
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488 | Return chi^2. |
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489 | """ |
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490 | if not self.fitted: |
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491 | msg = "Not yet fitted." |
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492 | raise RuntimeError(msg) |
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493 | ch2 = self.fitter.getchi2() |
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494 | asaplog.push( 'Chi^2 = %3.3f' % (ch2) ) |
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495 | return ch2 |
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496 | |
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497 | @asaplog_post_dec |
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498 | def get_fit(self): |
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499 | """ |
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500 | Return the fitted ordinate values. |
---|
501 | """ |
---|
502 | if not self.fitted: |
---|
503 | msg = "Not yet fitted." |
---|
504 | raise RuntimeError(msg) |
---|
505 | return self.fitter.getfit() |
---|
506 | |
---|
507 | @asaplog_post_dec |
---|
508 | def commit(self): |
---|
509 | """ |
---|
510 | Return a new scan where the fits have been commited (subtracted) |
---|
511 | """ |
---|
512 | if not self.fitted: |
---|
513 | msg = "Not yet fitted." |
---|
514 | raise RuntimeError(msg) |
---|
515 | from asap import scantable |
---|
516 | if not isinstance(self.data, scantable): |
---|
517 | msg = "Not a scantable" |
---|
518 | raise TypeError(msg) |
---|
519 | scan = self.data.copy() |
---|
520 | scan._setspectrum(self.fitter.getresidual()) |
---|
521 | return scan |
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522 | |
---|
523 | @asaplog_post_dec |
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524 | def plot(self, residual=False, components=None, plotparms=False, |
---|
525 | filename=None): |
---|
526 | """ |
---|
527 | Plot the last fit. |
---|
528 | Parameters: |
---|
529 | residual: an optional parameter indicating if the residual |
---|
530 | should be plotted (default 'False') |
---|
531 | components: a list of components to plot, e.g [0,1], |
---|
532 | -1 plots the total fit. Default is to only |
---|
533 | plot the total fit. |
---|
534 | plotparms: Inidicates if the parameter values should be present |
---|
535 | on the plot |
---|
536 | """ |
---|
537 | if not self.fitted: |
---|
538 | return |
---|
539 | if not self._p or self._p.is_dead: |
---|
540 | if rcParams['plotter.gui']: |
---|
541 | from asap.asaplotgui import asaplotgui as asaplot |
---|
542 | else: |
---|
543 | from asap.asaplot import asaplot |
---|
544 | self._p = asaplot() |
---|
545 | self._p.hold() |
---|
546 | self._p.clear() |
---|
547 | self._p.set_panels() |
---|
548 | self._p.palette(0) |
---|
549 | tlab = 'Spectrum' |
---|
550 | xlab = 'Abcissa' |
---|
551 | ylab = 'Ordinate' |
---|
552 | from numpy import ma,logical_not,logical_and,array |
---|
553 | m = self.mask |
---|
554 | if self.data: |
---|
555 | tlab = self.data._getsourcename(self._fittedrow) |
---|
556 | xlab = self.data._getabcissalabel(self._fittedrow) |
---|
557 | m = logical_and(self.mask, |
---|
558 | array(self.data._getmask(self._fittedrow), |
---|
559 | copy=False)) |
---|
560 | |
---|
561 | ylab = self.data._get_ordinate_label() |
---|
562 | |
---|
563 | colours = ["#777777","#dddddd","red","orange","purple","green","magenta", "cyan"] |
---|
564 | nomask=True |
---|
565 | for i in range(len(m)): |
---|
566 | nomask = nomask and m[i] |
---|
567 | label0='Masked Region' |
---|
568 | label1='Spectrum' |
---|
569 | if ( nomask ): |
---|
570 | label0=label1 |
---|
571 | else: |
---|
572 | y = ma.masked_array( self.y, mask = m ) |
---|
573 | self._p.palette(1,colours) |
---|
574 | self._p.set_line( label = label1 ) |
---|
575 | self._p.plot( self.x, y ) |
---|
576 | self._p.palette(0,colours) |
---|
577 | self._p.set_line(label=label0) |
---|
578 | y = ma.masked_array(self.y,mask=logical_not(m)) |
---|
579 | self._p.plot(self.x, y) |
---|
580 | if residual: |
---|
581 | self._p.palette(7) |
---|
582 | self._p.set_line(label='Residual') |
---|
583 | y = ma.masked_array(self.get_residual(), |
---|
584 | mask=logical_not(m)) |
---|
585 | self._p.plot(self.x, y) |
---|
586 | self._p.palette(2) |
---|
587 | if components is not None: |
---|
588 | cs = components |
---|
589 | if isinstance(components,int): cs = [components] |
---|
590 | if plotparms: |
---|
591 | self._p.text(0.15,0.15,str(self.get_parameters()['formatted']),size=8) |
---|
592 | n = len(self.components) |
---|
593 | self._p.palette(3) |
---|
594 | for c in cs: |
---|
595 | if 0 <= c < n: |
---|
596 | lab = self.fitfuncs[c]+str(c) |
---|
597 | self._p.set_line(label=lab) |
---|
598 | y = ma.masked_array(self.fitter.evaluate(c), |
---|
599 | mask=logical_not(m)) |
---|
600 | |
---|
601 | self._p.plot(self.x, y) |
---|
602 | elif c == -1: |
---|
603 | self._p.palette(2) |
---|
604 | self._p.set_line(label="Total Fit") |
---|
605 | y = ma.masked_array(self.fitter.getfit(), |
---|
606 | mask=logical_not(m)) |
---|
607 | self._p.plot(self.x, y) |
---|
608 | else: |
---|
609 | self._p.palette(2) |
---|
610 | self._p.set_line(label='Fit') |
---|
611 | y = ma.masked_array(self.fitter.getfit(), |
---|
612 | mask=logical_not(m)) |
---|
613 | self._p.plot(self.x, y) |
---|
614 | xlim=[min(self.x),max(self.x)] |
---|
615 | self._p.axes.set_xlim(xlim) |
---|
616 | self._p.set_axes('xlabel',xlab) |
---|
617 | self._p.set_axes('ylabel',ylab) |
---|
618 | self._p.set_axes('title',tlab) |
---|
619 | self._p.release() |
---|
620 | if (not rcParams['plotter.gui']): |
---|
621 | self._p.save(filename) |
---|
622 | |
---|
623 | @asaplog_post_dec |
---|
624 | def auto_fit(self, insitu=None, plot=False): |
---|
625 | """ |
---|
626 | Return a scan where the function is applied to all rows for |
---|
627 | all Beams/IFs/Pols. |
---|
628 | |
---|
629 | """ |
---|
630 | from asap import scantable |
---|
631 | if not isinstance(self.data, scantable) : |
---|
632 | msg = "Data is not a scantable" |
---|
633 | raise TypeError(msg) |
---|
634 | if insitu is None: insitu = rcParams['insitu'] |
---|
635 | if not insitu: |
---|
636 | scan = self.data.copy() |
---|
637 | else: |
---|
638 | scan = self.data |
---|
639 | rows = xrange(scan.nrow()) |
---|
640 | # Save parameters of baseline fits as a class attribute. |
---|
641 | # NOTICE: This does not reflect changes in scantable! |
---|
642 | if len(rows) > 0: self.blpars=[] |
---|
643 | asaplog.push("Fitting:") |
---|
644 | for r in rows: |
---|
645 | out = " Scan[%d] Beam[%d] IF[%d] Pol[%d] Cycle[%d]" % (scan.getscan(r), |
---|
646 | scan.getbeam(r), |
---|
647 | scan.getif(r), |
---|
648 | scan.getpol(r), |
---|
649 | scan.getcycle(r)) |
---|
650 | asaplog.push(out, False) |
---|
651 | self.x = scan._getabcissa(r) |
---|
652 | self.y = scan._getspectrum(r) |
---|
653 | self.mask = mask_and(self.mask, scan._getmask(r)) |
---|
654 | self.data = None |
---|
655 | self.fit() |
---|
656 | x = self.get_parameters() |
---|
657 | fpar = self.get_parameters() |
---|
658 | if plot: |
---|
659 | self.plot(residual=True) |
---|
660 | x = raw_input("Accept fit ([y]/n): ") |
---|
661 | if x.upper() == 'N': |
---|
662 | self.blpars.append(None) |
---|
663 | continue |
---|
664 | scan._setspectrum(self.fitter.getresidual(), r) |
---|
665 | self.blpars.append(fpar) |
---|
666 | if plot: |
---|
667 | self._p.unmap() |
---|
668 | self._p = None |
---|
669 | return scan |
---|