1 | import _asap
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2 | from asap import rcParams
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3 |
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4 | class fitter:
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5 | """
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6 | The fitting class for ASAP.
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7 | """
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8 | def _verbose(self, *args):
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9 | """
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10 | Set stdout output.
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11 | """
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12 | if type(args[0]) is bool:
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13 | self._vb = args[0]
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14 | return
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15 | elif len(args) == 0:
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16 | return self._vb
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17 |
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18 | def __init__(self):
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19 | """
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20 | Create a fitter object. No state is set.
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21 | """
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22 | self.fitter = _asap.fitter()
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23 | self.x = None
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24 | self.y = None
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25 | self.mask = None
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26 | self.fitfunc = None
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27 | self.fitfuncs = None
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28 | self.fitted = False
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29 | self.data = None
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30 | self.components = 0
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31 | self._fittedrow = 0
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32 | self._p = None
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33 | self._vb = True
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34 | self._selection = None
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35 |
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36 | def set_data(self, xdat, ydat, mask=None):
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37 | """
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38 | Set the absissa and ordinate for the fit. Also set the mask
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39 | indicationg valid points.
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40 | This can be used for data vectors retrieved from a scantable.
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41 | For scantable fitting use 'fitter.set_scan(scan, mask)'.
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42 | Parameters:
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43 | xdat: the abcissa values
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44 | ydat: the ordinate values
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45 | mask: an optional mask
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46 |
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47 | """
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48 | self.fitted = False
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49 | self.x = xdat
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50 | self.y = ydat
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51 | if mask == None:
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52 | from numarray import ones
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53 | self.mask = ones(len(xdat))
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54 | else:
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55 | self.mask = mask
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56 | return
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57 |
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58 | def set_scan(self, thescan=None, mask=None):
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59 | """
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60 | Set the 'data' (a scantable) of the fitter.
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61 | Parameters:
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62 | thescan: a scantable
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63 | mask: a msk retireved from the scantable
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64 | """
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65 | if not thescan:
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66 | print "Please give a correct scan"
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67 | self.fitted = False
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68 | self.data = thescan
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69 | if mask is None:
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70 | from numarray import ones
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71 | self.mask = ones(self.data.nchan())
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72 | else:
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73 | self.mask = mask
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74 | return
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75 |
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76 | def set_function(self, **kwargs):
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77 | """
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78 | Set the function to be fit.
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79 | Parameters:
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80 | poly: use a polynomial of the order given
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81 | gauss: fit the number of gaussian specified
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82 | Example:
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83 | fitter.set_function(gauss=2) # will fit two gaussians
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84 | fitter.set_function(poly=3) # will fit a 3rd order polynomial
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85 | """
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86 | #default poly order 0
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87 | n=0
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88 | if kwargs.has_key('poly'):
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89 | self.fitfunc = 'poly'
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90 | n = kwargs.get('poly')
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91 | self.components = [n]
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92 | elif kwargs.has_key('gauss'):
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93 | n = kwargs.get('gauss')
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94 | self.fitfunc = 'gauss'
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95 | self.fitfuncs = [ 'gauss' for i in range(n) ]
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96 | self.components = [ 3 for i in range(n) ]
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97 | else:
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98 | print "Invalid function type."
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99 | return
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100 | self.fitter.setexpression(self.fitfunc,n)
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101 | return
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102 |
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103 | def fit(self, row=0):
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104 | """
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105 | Execute the actual fitting process. All the state has to be set.
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106 | Parameters:
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107 | row: specify the row in the scantable
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108 | Example:
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109 | s = scantable('myscan.asap')
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110 | s.set_cursor(thepol=1) # select second pol
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111 | f = fitter()
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112 | f.set_scan(s)
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113 | f.set_function(poly=0)
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114 | f.fit(row=0) # fit first row
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115 | """
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116 | if ((self.x is None or self.y is None) and self.data is None) \
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117 | or self.fitfunc is None:
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118 | print "Fitter not yet initialised. Please set data & fit function"
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119 | return
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120 | else:
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121 | if self.data is not None:
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122 | self.x = self.data._getabcissa(row)
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123 | self.y = self.data._getspectrum(row)
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124 | print "Fitting:"
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125 | vb = self.data._vb
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126 | self.data._vb = True
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127 | self.selection = self.data.get_cursor()
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128 | self.data._vb = vb
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129 | self.fitter.setdata(self.x, self.y, self.mask)
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130 | if self.fitfunc == 'gauss':
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131 | ps = self.fitter.getparameters()
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132 | if len(ps) == 0:
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133 | self.fitter.estimate()
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134 | self.fitter.fit()
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135 | self._fittedrow = row
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136 | self.fitted = True
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137 | return
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138 |
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139 | def store_fit(self):
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140 | """
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141 | Store the fit parameters in the scantable.
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142 | """
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143 | if self.fitted and self.data is not None:
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144 | pars = list(self.fitter.getparameters())
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145 | fixed = list(self.fitter.getfixedparameters())
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146 | self.data._addfit(self._fittedrow, pars, fixed,
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147 | self.fitfuncs, self.components)
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148 |
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149 | def set_parameters(self, params, fixed=None, component=None):
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150 | """
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151 | Set the parameters to be fitted.
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152 | Parameters:
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153 | params: a vector of parameters
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154 | fixed: a vector of which parameters are to be held fixed
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155 | (default is none)
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156 | component: in case of multiple gaussians, the index of the
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157 | component
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158 | """
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159 | if self.fitfunc is None:
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160 | print "Please specify a fitting function first."
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161 | return
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162 | if self.fitfunc == "gauss" and component is not None:
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163 | if not self.fitted:
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164 | from numarray import zeros
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165 | pars = list(zeros(len(self.components)*3))
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166 | fxd = list(zeros(len(pars)))
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167 | else:
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168 | pars = list(self.fitter.getparameters())
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169 | fxd = list(self.fitter.getfixedparameters())
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170 | i = 3*component
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171 | pars[i:i+3] = params
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172 | fxd[i:i+3] = fixed
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173 | params = pars
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174 | fixed = fxd
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175 | self.fitter.setparameters(params)
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176 | if fixed is not None:
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177 | self.fitter.setfixedparameters(fixed)
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178 | return
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179 |
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180 | def set_gauss_parameters(self, peak, centre, fhwm,
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181 | peakfixed=False, centerfixed=False,
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182 | fhwmfixed=False,
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183 | component=0):
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184 | """
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185 | Set the Parameters of a 'Gaussian' component, set with set_function.
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186 | Parameters:
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187 | peak, centre, fhwm: The gaussian parameters
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188 | peakfixed,
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189 | centerfixed,
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190 | fhwmfixed: Optional parameters to indicate if
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191 | the paramters should be held fixed during
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192 | the fitting process. The default is to keep
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193 | all parameters flexible.
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194 | component: The number of the component (Default is the
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195 | component 0)
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196 | """
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197 | if self.fitfunc != "gauss":
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198 | print "Function only operates on Gaussian components."
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199 | return
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200 | if 0 <= component < len(self.components):
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201 | self.set_parameters([peak, centre, fhwm],
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202 | [peakfixed, centerfixed, fhwmfixed],
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203 | component)
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204 | else:
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205 | print "Please select a valid component."
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206 | return
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207 |
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208 | def get_parameters(self, component=None):
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209 | """
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210 | Return the fit paramters.
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211 | Parameters:
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212 | component: get the parameters for the specified component
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213 | only, default is all components
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214 | """
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215 | if not self.fitted:
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216 | print "Not yet fitted."
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217 | pars = list(self.fitter.getparameters())
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218 | fixed = list(self.fitter.getfixedparameters())
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219 | if component is not None:
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220 | if self.fitfunc == "gauss":
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221 | i = 3*component
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222 | cpars = pars[i:i+3]
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223 | cfixed = fixed[i:i+3]
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224 | else:
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225 | cpars = pars
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226 | cfixed = fixed
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227 | else:
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228 | cpars = pars
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229 | cfixed = fixed
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230 | fpars = self._format_pars(cpars, cfixed)
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231 | if self._vb:
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232 | print fpars
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233 | return cpars, cfixed, fpars
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234 |
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235 | def _format_pars(self, pars, fixed):
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236 | out = ''
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237 | if self.fitfunc == 'poly':
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238 | c = 0
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239 | for i in range(len(pars)):
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240 | fix = ""
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241 | if fixed[i]: fix = "(fixed)"
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242 | out += ' p%d%s= %3.3f,' % (c,fix,pars[i])
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243 | c+=1
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244 | out = out[:-1] # remove trailing ','
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245 | elif self.fitfunc == 'gauss':
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246 | i = 0
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247 | c = 0
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248 | aunit = ''
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249 | ounit = ''
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250 | if self.data:
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251 | aunit = self.data.get_unit()
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252 | ounit = self.data.get_fluxunit()
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253 | while i < len(pars):
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254 | out += ' %d: peak = %3.3f %s , centre = %3.3f %s, FWHM = %3.3f %s \n' % (c,pars[i],ounit,pars[i+1],aunit,pars[i+2],aunit)
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255 | c+=1
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256 | i+=3
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257 | return out
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258 |
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259 | def get_estimate(self):
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260 | """
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261 | Return the parameter estimates (for non-linear functions).
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262 | """
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263 | pars = self.fitter.getestimate()
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264 | if self._vb:
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265 | print self._format_pars(pars)
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266 | return pars
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267 |
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268 |
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269 | def get_residual(self):
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270 | """
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271 | Return the residual of the fit.
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272 | """
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273 | if not self.fitted:
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274 | print "Not yet fitted."
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275 | return self.fitter.getresidual()
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276 |
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277 | def get_chi2(self):
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278 | """
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279 | Return chi^2.
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280 | """
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281 | if not self.fitted:
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282 | print "Not yet fitted."
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283 | ch2 = self.fitter.getchi2()
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284 | if self._vb:
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285 | print 'Chi^2 = %3.3f' % (ch2)
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286 | return ch2
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287 |
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288 | def get_fit(self):
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289 | """
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290 | Return the fitted ordinate values.
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291 | """
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292 | if not self.fitted:
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293 | print "Not yet fitted."
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294 | return self.fitter.getfit()
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295 |
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296 | def commit(self):
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297 | """
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298 | Return a new scan where the fits have been commited (subtracted)
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299 | """
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300 | if not self.fitted:
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301 | print "Not yet fitted."
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302 | if self.data is not scantable:
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303 | print "Only works with scantables"
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304 | return
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305 | scan = self.data.copy()
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306 | scan._setspectrum(self.fitter.getresidual())
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307 |
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308 | def plot(self, residual=False, components=None, plotparms=False):
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309 | """
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310 | Plot the last fit.
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311 | Parameters:
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312 | residual: an optional parameter indicating if the residual
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313 | should be plotted (default 'False')
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314 | components: a list of components to plot, e.g [0,1],
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315 | -1 plots the total fit. Default is to only
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316 | plot the total fit.
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317 | plotparms: Inidicates if the parameter values should be present
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318 | on the plot
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319 | """
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320 | if not self.fitted:
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321 | return
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322 | if not self._p:
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323 | from asap.asaplot import ASAPlot
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324 | self._p = ASAPlot()
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325 | if self._p.is_dead:
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326 | from asap.asaplot import ASAPlot
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327 | self._p = ASAPlot()
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328 | self._p.clear()
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329 | self._p.set_panels()
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330 | self._p.palette(1)
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331 | tlab = 'Spectrum'
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332 | xlab = 'Abcissa'
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333 | m = ()
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334 | if self.data:
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335 | tlab = self.data._getsourcename(self._fittedrow)
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336 | xlab = self.data._getabcissalabel(self._fittedrow)
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337 | m = self.data._getmask(self._fittedrow)
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338 | ylab = r'Flux'
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339 |
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340 | colours = ["grey60","grey80","red","orange","purple","yellow","magenta", "cyan"]
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341 | self._p.palette(1,colours)
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342 | self._p.set_line(label='Spectrum')
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343 | self._p.plot(self.x, self.y, m)
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344 | if residual:
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345 | self._p.palette(2)
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346 | self._p.set_line(label='Residual')
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347 | self._p.plot(self.x, self.get_residual(), m)
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348 | self._p.palette(3)
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349 | if components is not None:
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350 | cs = components
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351 | if isinstance(components,int): cs = [components]
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352 | if plotparms:
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353 | self._p.text(0.15,0.15,str(self.get_parameters()[2]),size=8)
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354 | n = len(self.components)
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355 | self._p.palette(4)
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356 | for c in cs:
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357 | if 0 <= c < n:
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358 | lab = self.fitfuncs[c]+str(c)
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359 | self._p.set_line(label=lab)
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360 | self._p.plot(self.x, self.fitter.evaluate(c), m)
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361 | elif c == -1:
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362 | self._p.palette(3)
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363 | self._p.set_line(label="Total Fit")
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364 | self._p.plot(self.x, self.get_fit(), m)
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365 | else:
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366 | self._p.palette(3)
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367 | self._p.set_line(label='Fit')
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368 | self._p.plot(self.x, self.get_fit(), m)
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369 | self._p.set_axes('xlabel',xlab)
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370 | self._p.set_axes('ylabel',ylab)
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371 | self._p.set_axes('title',tlab)
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372 | self._p.release()
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373 |
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374 | def auto_fit(self, insitu=None):
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375 | """
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376 | Return a scan where the function is applied to all rows for
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377 | all Beams/IFs/Pols.
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378 |
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379 | """
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380 | from asap import scantable
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381 | if not isinstance(self.data, scantable) :
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382 | print "Only works with scantables"
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383 | return
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384 | if insitu is None: insitu = rcParams['insitu']
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385 | if not insitu:
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386 | scan = self.data.copy()
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387 | else:
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388 | scan = self.data
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389 | vb = scan._vb
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390 | scan._vb = False
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391 | sel = scan.get_cursor()
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392 | rows = range(scan.nrow())
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393 | for i in range(scan.nbeam()):
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394 | scan.setbeam(i)
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395 | for j in range(scan.nif()):
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396 | scan.setif(j)
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397 | for k in range(scan.npol()):
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398 | scan.setpol(k)
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399 | if self._vb:
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400 | print "Fitting:"
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401 | print 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k)
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402 | for iRow in rows:
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403 | self.x = scan._getabcissa(iRow)
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404 | self.y = scan._getspectrum(iRow)
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405 | self.data = None
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406 | self.fit()
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407 | x = self.get_parameters()
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408 | scan._setspectrum(self.fitter.getresidual(),iRow)
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409 | scan.set_cursor(sel[0],sel[1],sel[2])
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410 | scan._vb = vb
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411 | if not insitu:
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412 | return scan
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