1 | import _asap |
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2 | from asap import rcParams |
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3 | from asap import print_log |
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4 | |
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5 | class fitter: |
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6 | """ |
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7 | The fitting class for ASAP. |
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8 | """ |
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9 | |
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10 | def __init__(self): |
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11 | """ |
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12 | Create a fitter object. No state is set. |
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13 | """ |
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14 | self.fitter = _asap.fitter() |
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15 | self.x = None |
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16 | self.y = None |
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17 | self.mask = None |
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18 | self.fitfunc = None |
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19 | self.fitfuncs = None |
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20 | self.fitted = False |
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21 | self.data = None |
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22 | self.components = 0 |
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23 | self._fittedrow = 0 |
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24 | self._p = None |
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25 | self._selection = None |
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26 | |
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27 | def set_data(self, xdat, ydat, mask=None): |
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28 | """ |
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29 | Set the absissa and ordinate for the fit. Also set the mask |
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30 | indicationg valid points. |
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31 | This can be used for data vectors retrieved from a scantable. |
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32 | For scantable fitting use 'fitter.set_scan(scan, mask)'. |
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33 | Parameters: |
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34 | xdat: the abcissa values |
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35 | ydat: the ordinate values |
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36 | mask: an optional mask |
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37 | |
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38 | """ |
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39 | self.fitted = False |
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40 | self.x = xdat |
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41 | self.y = ydat |
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42 | if mask == None: |
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43 | from numarray import ones |
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44 | self.mask = ones(len(xdat)) |
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45 | else: |
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46 | self.mask = mask |
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47 | return |
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48 | |
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49 | def set_scan(self, thescan=None, mask=None): |
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50 | """ |
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51 | Set the 'data' (a scantable) of the fitter. |
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52 | Parameters: |
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53 | thescan: a scantable |
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54 | mask: a msk retireved from the scantable |
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55 | """ |
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56 | if not thescan: |
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57 | msg = "Please give a correct scan" |
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58 | if rcParams['verbose']: |
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59 | print msg |
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60 | return |
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61 | else: |
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62 | raise TypeError(msg) |
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63 | self.fitted = False |
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64 | self.data = thescan |
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65 | if mask is None: |
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66 | from numarray import ones |
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67 | self.mask = ones(self.data.nchan()) |
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68 | else: |
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69 | self.mask = mask |
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70 | return |
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71 | |
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72 | def set_function(self, **kwargs): |
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73 | """ |
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74 | Set the function to be fit. |
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75 | Parameters: |
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76 | poly: use a polynomial of the order given |
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77 | gauss: fit the number of gaussian specified |
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78 | Example: |
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79 | fitter.set_function(gauss=2) # will fit two gaussians |
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80 | fitter.set_function(poly=3) # will fit a 3rd order polynomial |
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81 | """ |
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82 | #default poly order 0 |
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83 | n=0 |
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84 | if kwargs.has_key('poly'): |
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85 | self.fitfunc = 'poly' |
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86 | n = kwargs.get('poly') |
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87 | self.components = [n] |
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88 | elif kwargs.has_key('gauss'): |
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89 | n = kwargs.get('gauss') |
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90 | self.fitfunc = 'gauss' |
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91 | self.fitfuncs = [ 'gauss' for i in range(n) ] |
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92 | self.components = [ 3 for i in range(n) ] |
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93 | else: |
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94 | msg = "Invalid function type." |
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95 | if rcParams['verbose']: |
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96 | print msg |
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97 | return |
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98 | else: |
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99 | raise TypeError(msg) |
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100 | |
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101 | self.fitter.setexpression(self.fitfunc,n) |
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102 | return |
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103 | |
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104 | def fit(self, row=0): |
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105 | """ |
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106 | Execute the actual fitting process. All the state has to be set. |
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107 | Parameters: |
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108 | row: specify the row in the scantable |
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109 | Example: |
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110 | s = scantable('myscan.asap') |
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111 | s.set_cursor(thepol=1) # select second pol |
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112 | f = fitter() |
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113 | f.set_scan(s) |
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114 | f.set_function(poly=0) |
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115 | f.fit(row=0) # fit first row |
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116 | """ |
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117 | if ((self.x is None or self.y is None) and self.data is None) \ |
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118 | or self.fitfunc is None: |
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119 | msg = "Fitter not yet initialised. Please set data & fit function" |
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120 | if rcParams['verbose']: |
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121 | print msg |
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122 | return |
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123 | else: |
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124 | raise RuntimeError(msg) |
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125 | |
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126 | else: |
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127 | if self.data is not None: |
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128 | self.x = self.data._getabcissa(row) |
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129 | self.y = self.data._getspectrum(row) |
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130 | from asap import asaplog |
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131 | asaplog.push("Fitting:") |
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132 | self.selection = self.data.get_cursor() |
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133 | self.fitter.setdata(self.x, self.y, self.mask) |
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134 | if self.fitfunc == 'gauss': |
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135 | ps = self.fitter.getparameters() |
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136 | if len(ps) == 0: |
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137 | self.fitter.estimate() |
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138 | try: |
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139 | self.fitter.fit() |
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140 | except RuntimeError, msg: |
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141 | if rcParams['verbose']: |
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142 | print msg |
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143 | else: |
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144 | raise |
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145 | self._fittedrow = row |
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146 | self.fitted = True |
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147 | print_log() |
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148 | return |
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149 | |
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150 | def store_fit(self): |
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151 | """ |
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152 | Store the fit parameters in the scantable. |
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153 | """ |
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154 | if self.fitted and self.data is not None: |
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155 | pars = list(self.fitter.getparameters()) |
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156 | fixed = list(self.fitter.getfixedparameters()) |
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157 | self.data._addfit(self._fittedrow, pars, fixed, |
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158 | self.fitfuncs, self.components) |
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159 | |
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160 | def set_parameters(self, params, fixed=None, component=None): |
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161 | """ |
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162 | Set the parameters to be fitted. |
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163 | Parameters: |
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164 | params: a vector of parameters |
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165 | fixed: a vector of which parameters are to be held fixed |
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166 | (default is none) |
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167 | component: in case of multiple gaussians, the index of the |
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168 | component |
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169 | """ |
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170 | if self.fitfunc is None: |
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171 | msg = "Please specify a fitting function first." |
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172 | if rcParams['verbose']: |
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173 | print msg |
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174 | return |
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175 | else: |
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176 | raise RuntimeError(msg) |
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177 | if self.fitfunc == "gauss" and component is not None: |
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178 | if not self.fitted: |
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179 | from numarray import zeros |
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180 | pars = list(zeros(len(self.components)*3)) |
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181 | fxd = list(zeros(len(pars))) |
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182 | else: |
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183 | pars = list(self.fitter.getparameters()) |
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184 | fxd = list(self.fitter.getfixedparameters()) |
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185 | i = 3*component |
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186 | pars[i:i+3] = params |
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187 | fxd[i:i+3] = fixed |
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188 | params = pars |
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189 | fixed = fxd |
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190 | self.fitter.setparameters(params) |
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191 | if fixed is not None: |
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192 | self.fitter.setfixedparameters(fixed) |
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193 | print_log() |
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194 | return |
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195 | |
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196 | def set_gauss_parameters(self, peak, centre, fhwm, |
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197 | peakfixed=False, centerfixed=False, |
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198 | fhwmfixed=False, |
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199 | component=0): |
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200 | """ |
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201 | Set the Parameters of a 'Gaussian' component, set with set_function. |
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202 | Parameters: |
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203 | peak, centre, fhwm: The gaussian parameters |
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204 | peakfixed, |
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205 | centerfixed, |
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206 | fhwmfixed: Optional parameters to indicate if |
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207 | the paramters should be held fixed during |
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208 | the fitting process. The default is to keep |
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209 | all parameters flexible. |
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210 | component: The number of the component (Default is the |
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211 | component 0) |
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212 | """ |
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213 | if self.fitfunc != "gauss": |
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214 | msg = "Function only operates on Gaussian components." |
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215 | if rcParams['verbose']: |
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216 | print msg |
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217 | return |
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218 | else: |
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219 | raise ValueError(msg) |
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220 | if 0 <= component < len(self.components): |
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221 | self.set_parameters([peak, centre, fhwm], |
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222 | [peakfixed, centerfixed, fhwmfixed], |
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223 | component) |
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224 | else: |
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225 | msg = "Please select a valid component." |
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226 | if rcParams['verbose']: |
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227 | print msg |
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228 | return |
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229 | else: |
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230 | raise ValueError(msg) |
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231 | |
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232 | def get_parameters(self, component=None): |
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233 | """ |
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234 | Return the fit paramters. |
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235 | Parameters: |
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236 | component: get the parameters for the specified component |
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237 | only, default is all components |
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238 | """ |
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239 | if not self.fitted: |
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240 | msg = "Not yet fitted." |
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241 | if rcParams['verbose']: |
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242 | print msg |
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243 | return |
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244 | else: |
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245 | raise RuntimeError(msg) |
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246 | pars = list(self.fitter.getparameters()) |
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247 | fixed = list(self.fitter.getfixedparameters()) |
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248 | if component is not None: |
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249 | if self.fitfunc == "gauss": |
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250 | i = 3*component |
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251 | cpars = pars[i:i+3] |
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252 | cfixed = fixed[i:i+3] |
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253 | else: |
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254 | cpars = pars |
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255 | cfixed = fixed |
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256 | else: |
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257 | cpars = pars |
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258 | cfixed = fixed |
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259 | fpars = self._format_pars(cpars, cfixed) |
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260 | if rcParams['verbose']: |
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261 | print fpars |
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262 | return cpars, cfixed, fpars |
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263 | |
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264 | def _format_pars(self, pars, fixed): |
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265 | out = '' |
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266 | if self.fitfunc == 'poly': |
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267 | c = 0 |
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268 | for i in range(len(pars)): |
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269 | fix = "" |
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270 | if fixed[i]: fix = "(fixed)" |
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271 | out += ' p%d%s= %3.3f,' % (c,fix,pars[i]) |
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272 | c+=1 |
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273 | out = out[:-1] # remove trailing ',' |
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274 | elif self.fitfunc == 'gauss': |
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275 | i = 0 |
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276 | c = 0 |
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277 | aunit = '' |
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278 | ounit = '' |
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279 | if self.data: |
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280 | aunit = self.data.get_unit() |
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281 | ounit = self.data.get_fluxunit() |
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282 | while i < len(pars): |
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283 | 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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284 | c+=1 |
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285 | i+=3 |
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286 | return out |
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287 | |
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288 | def get_estimate(self): |
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289 | """ |
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290 | Return the parameter estimates (for non-linear functions). |
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291 | """ |
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292 | pars = self.fitter.getestimate() |
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293 | if rcParams['verbose']: |
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294 | print self._format_pars(pars) |
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295 | return pars |
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296 | |
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297 | def get_residual(self): |
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298 | """ |
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299 | Return the residual of the fit. |
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300 | """ |
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301 | if not self.fitted: |
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302 | msg = "Not yet fitted." |
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303 | if rcParams['verbose']: |
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304 | print msg |
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305 | return |
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306 | else: |
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307 | raise RuntimeError(msg) |
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308 | return self.fitter.getresidual() |
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309 | |
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310 | def get_chi2(self): |
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311 | """ |
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312 | Return chi^2. |
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313 | """ |
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314 | if not self.fitted: |
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315 | msg = "Not yet fitted." |
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316 | if rcParams['verbose']: |
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317 | print msg |
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318 | return |
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319 | else: |
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320 | raise RuntimeError(msg) |
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321 | ch2 = self.fitter.getchi2() |
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322 | if rcParams['verbose']: |
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323 | print 'Chi^2 = %3.3f' % (ch2) |
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324 | return ch2 |
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325 | |
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326 | def get_fit(self): |
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327 | """ |
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328 | Return the fitted ordinate values. |
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329 | """ |
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330 | if not self.fitted: |
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331 | msg = "Not yet fitted." |
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332 | if rcParams['verbose']: |
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333 | print msg |
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334 | return |
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335 | else: |
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336 | raise RuntimeError(msg) |
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337 | return self.fitter.getfit() |
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338 | |
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339 | def commit(self): |
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340 | """ |
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341 | Return a new scan where the fits have been commited (subtracted) |
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342 | """ |
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343 | if not self.fitted: |
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344 | print "Not yet fitted." |
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345 | msg = "Not yet fitted." |
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346 | if rcParams['verbose']: |
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347 | print msg |
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348 | return |
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349 | else: |
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350 | raise RuntimeError(msg) |
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351 | if self.data is not scantable: |
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352 | msg = "Not a scantable" |
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353 | if rcParams['verbose']: |
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354 | print msg |
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355 | return |
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356 | else: |
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357 | raise TypeError(msg) |
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358 | scan = self.data.copy() |
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359 | scan._setspectrum(self.fitter.getresidual()) |
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360 | print_log() |
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361 | |
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362 | def plot(self, residual=False, components=None, plotparms=False, filename=None): |
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363 | """ |
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364 | Plot the last fit. |
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365 | Parameters: |
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366 | residual: an optional parameter indicating if the residual |
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367 | should be plotted (default 'False') |
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368 | components: a list of components to plot, e.g [0,1], |
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369 | -1 plots the total fit. Default is to only |
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370 | plot the total fit. |
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371 | plotparms: Inidicates if the parameter values should be present |
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372 | on the plot |
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373 | """ |
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374 | if not self.fitted: |
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375 | return |
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376 | if not self._p or self._p.is_dead: |
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377 | if rcParams['plotter.gui']: |
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378 | from asap.asaplotgui import asaplotgui as asaplot |
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379 | else: |
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380 | from asap.asaplot import asaplot |
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381 | self._p = asaplot() |
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382 | self._p.hold() |
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383 | self._p.clear() |
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384 | self._p.set_panels() |
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385 | self._p.palette(0) |
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386 | tlab = 'Spectrum' |
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387 | xlab = 'Abcissa' |
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388 | m = () |
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389 | if self.data: |
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390 | tlab = self.data._getsourcename(self._fittedrow) |
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391 | xlab = self.data._getabcissalabel(self._fittedrow) |
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392 | m = self.data._getmask(self._fittedrow) |
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393 | ylab = self.data._get_ordinate_label() |
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394 | |
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395 | colours = ["#777777","#bbbbbb","red","orange","purple","green","magenta", "cyan"] |
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396 | self._p.palette(0,colours) |
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397 | self._p.set_line(label='Spectrum') |
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398 | self._p.plot(self.x, self.y, m) |
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399 | if residual: |
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400 | self._p.palette(1) |
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401 | self._p.set_line(label='Residual') |
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402 | self._p.plot(self.x, self.get_residual(), m) |
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403 | self._p.palette(2) |
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404 | if components is not None: |
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405 | cs = components |
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406 | if isinstance(components,int): cs = [components] |
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407 | if plotparms: |
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408 | self._p.text(0.15,0.15,str(self.get_parameters()[2]),size=8) |
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409 | n = len(self.components) |
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410 | self._p.palette(3) |
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411 | for c in cs: |
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412 | if 0 <= c < n: |
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413 | lab = self.fitfuncs[c]+str(c) |
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414 | self._p.set_line(label=lab) |
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415 | self._p.plot(self.x, self.fitter.evaluate(c), m) |
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416 | elif c == -1: |
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417 | self._p.palette(2) |
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418 | self._p.set_line(label="Total Fit") |
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419 | self._p.plot(self.x, self.get_fit(), m) |
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420 | else: |
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421 | self._p.palette(2) |
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422 | self._p.set_line(label='Fit') |
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423 | self._p.plot(self.x, self.get_fit(), m) |
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424 | xlim=[min(self.x),max(self.x)] |
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425 | self._p.axes.set_xlim(xlim) |
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426 | self._p.set_axes('xlabel',xlab) |
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427 | self._p.set_axes('ylabel',ylab) |
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428 | self._p.set_axes('title',tlab) |
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429 | self._p.release() |
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430 | if (not rcParams['plotter.gui']): |
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431 | self._p.save(filename) |
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432 | print_log() |
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433 | |
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434 | def auto_fit(self, insitu=None, allaxes=True): |
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435 | """ |
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436 | Return a scan where the function is applied to all rows for |
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437 | all Beams/IFs/Pols. |
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438 | |
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439 | """ |
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440 | from asap import scantable |
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441 | if not isinstance(self.data, scantable) : |
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442 | msg = "Data is not a scantable" |
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443 | if rcParams['verbose']: |
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444 | print msg |
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445 | return |
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446 | else: |
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447 | raise TypeError(msg) |
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448 | if insitu is None: insitu = rcParams['insitu'] |
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449 | if not insitu: |
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450 | scan = self.data.copy() |
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451 | else: |
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452 | scan = self.data |
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453 | sel = scan.get_cursor() |
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454 | rows = range(scan.nrow()) |
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455 | from asap import asaplog |
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456 | if allaxes: |
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457 | for i in range(scan.nbeam()): |
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458 | scan.setbeam(i) |
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459 | for j in range(scan.nif()): |
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460 | scan.setif(j) |
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461 | for k in range(scan.npol()): |
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462 | scan.setpol(k) |
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463 | asaplog.push("Fitting:") |
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464 | out = 'Beam[%d], IF[%d], Pol[%d]' % (i,j,k) |
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465 | asaplog.push(out) |
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466 | for iRow in rows: |
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467 | self.x = scan._getabcissa(iRow) |
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468 | self.y = scan._getspectrum(iRow) |
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469 | self.data = None |
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470 | self.fit() |
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471 | x = self.get_parameters() |
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472 | scan._setspectrum(self.fitter.getresidual(),iRow) |
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473 | else: |
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474 | asaplog.push("Fitting:") |
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475 | out = 'Beam[%d], IF[%d], Pol[%d]' % sel |
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476 | asaplog.push(out) |
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477 | for iRow in rows: |
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478 | self.x = scan._getabcissa(iRow) |
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479 | self.y = scan._getspectrum(iRow) |
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480 | self.data = None |
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481 | self.fit() |
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482 | x = self.get_parameters() |
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483 | scan._setspectrum(self.fitter.getresidual(),iRow) |
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484 | |
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485 | scan.set_cursor(sel[0],sel[1],sel[2]) |
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486 | print_log() |
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487 | if not insitu: |
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488 | return scan |
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