1 | #!/usr/bin/python |
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2 | |
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3 | # fitDialog.py |
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4 | |
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5 | import wx |
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6 | from PlotPanel import PlotPanel |
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7 | from plottables import Theory1D |
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8 | import math,pylab,fittings |
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9 | import transform |
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10 | |
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11 | |
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12 | class LinearFit(wx.Dialog): |
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13 | #def __init__(self, parent, id, title): |
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14 | def __init__(self, parent, plottable, push_data,transform, id, title): |
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15 | wx.Dialog.__init__(self, parent, id, title, size=(450, 300)) |
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16 | """ |
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17 | for the fit window |
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18 | """ |
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19 | self.parent = parent |
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20 | self.transform = transform |
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21 | #dialog panel self call function to plot the fitting function |
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22 | self.push_data = push_data |
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23 | #dialog self plottable |
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24 | self.plottable = plottable |
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25 | |
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26 | #Dialog interface |
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27 | panel = wx.Panel(self, -1, style=wx.SIMPLE_BORDER) |
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28 | vbox = wx.BoxSizer(wx.VERTICAL) |
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29 | sizer = wx.GridBagSizer(5,5) |
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30 | |
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31 | vbox.Add(panel, 1, wx.EXPAND | wx.ALL) |
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32 | |
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33 | self.tcA = wx.TextCtrl(panel, -1,size=(120,20),style=wx.SIMPLE_BORDER) |
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34 | self.tcErrA = wx.TextCtrl(panel, -1,size=(120,20),style=wx.SIMPLE_BORDER) |
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35 | self.tcB = wx.TextCtrl(panel, -1,size=(120,20),style=wx.SIMPLE_BORDER) |
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36 | self.tcErrB = wx.TextCtrl(panel, -1,size=(120,20),style=wx.SIMPLE_BORDER) |
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37 | self.tcChi = wx.TextCtrl(panel, -1,size=(120,20),style=wx.SIMPLE_BORDER) |
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38 | self.FXmin = wx.TextCtrl(panel,-1,size=(120,20),style=wx.SIMPLE_BORDER) |
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39 | self.FXmax = wx.TextCtrl(panel,-1,size=(120,20),style=wx.SIMPLE_BORDER) |
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40 | self.PXmin = wx.TextCtrl(panel,-1,size=(120,20),style=wx.SIMPLE_BORDER) |
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41 | self.PXmax = wx.TextCtrl(panel,-1,size=(120,20),style=wx.SIMPLE_BORDER) |
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42 | self.btFit =wx.Button(panel,-1,'Fit',size=(120, 30)) |
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43 | self.btClose =wx.Button(panel, wx.ID_CANCEL,'Close',size=(90, 30) ) |
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44 | self.static_line_1 = wx.StaticLine(panel, -1) |
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45 | ix = 0 |
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46 | iy = 1 |
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47 | |
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48 | sizer.Add(wx.StaticText(panel, -1, 'y = Ax +B'),(iy, ix),(1,1),\ |
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49 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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50 | |
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51 | iy+=1 |
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52 | sizer.Add(wx.StaticText(panel, -1, 'Param A'),(iy, ix),\ |
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53 | (1,1), wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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54 | ix += 1 |
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55 | sizer.Add(self.tcA,(iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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56 | ix += 1 |
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57 | sizer.Add(wx.StaticText(panel, -1, '+/-'),(iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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58 | ix += 1 |
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59 | sizer.Add(self.tcErrA, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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60 | |
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61 | iy += 1 |
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62 | ix = 0 |
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63 | sizer.Add(wx.StaticText(panel, -1, 'Param B'),(iy, ix),(1,1),\ |
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64 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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65 | ix += 1 |
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66 | sizer.Add(self.tcB, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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67 | ix += 1 |
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68 | sizer.Add(wx.StaticText(panel, -1, '+/-'),(iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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69 | ix += 1 |
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70 | sizer.Add(self.tcErrB, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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71 | iy += 1 |
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72 | ix = 0 |
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73 | sizer.Add(wx.StaticText(panel, -1, 'Chi ^{2}'),(iy, ix),(1,1),\ |
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74 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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75 | ix += 1 |
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76 | sizer.Add(self.tcChi, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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77 | iy += 1 |
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78 | ix = 1 |
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79 | sizer.Add(wx.StaticText(panel, -1, 'Xmin'),(iy, ix),(1,1),\ |
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80 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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81 | ix += 2 |
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82 | sizer.Add(wx.StaticText(panel, -1, 'Xmax'),(iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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83 | iy += 1 |
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84 | ix = 0 |
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85 | sizer.Add(wx.StaticText(panel, -1, 'Plotted Range'),(iy, ix),(1,1),\ |
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86 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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87 | ix +=1 |
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88 | sizer.Add(self.PXmin, (iy, ix),(1,1),\ |
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89 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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90 | ix += 2 |
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91 | sizer.Add(self.PXmax, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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92 | iy += 1 |
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93 | ix = 0 |
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94 | sizer.Add(wx.StaticText(panel, -1, 'Fit Range'),(iy, ix),(1,1),\ |
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95 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 15) |
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96 | ix += 1 |
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97 | sizer.Add(self.FXmin, (iy, ix),(1,1),\ |
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98 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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99 | ix += 2 |
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100 | sizer.Add(self.FXmax, (iy, ix),(1,1), wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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101 | iy += 1 |
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102 | ix = 1 |
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103 | |
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104 | sizer.Add(self.btFit, (iy, ix),(1,1), wx.LEFT|wx.ADJUST_MINSIZE, 0) |
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105 | self.btFit.Bind(wx.EVT_BUTTON, self._onFit) |
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106 | ix += 2 |
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107 | sizer.Add(self.btClose, (iy, ix),(1,1),\ |
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108 | wx.LEFT|wx.EXPAND|wx.ADJUST_MINSIZE, 0) |
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109 | |
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110 | |
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111 | panel.SetSizer(sizer) |
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112 | self.SetSizer(vbox) |
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113 | self.Centre() |
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114 | # Receives the type of model for the fitting |
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115 | from LineModel import LineModel |
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116 | self.model = LineModel() |
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117 | |
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118 | |
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119 | #Display the fittings values |
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120 | self.default_A = self.model.getParam('A') |
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121 | self.default_B = self.model.getParam('B') |
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122 | self.cstA = fittings.Parameter(self.model, 'A', self.default_A) |
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123 | self.cstB = fittings.Parameter(self.model, 'B', self.default_B) |
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124 | |
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125 | # Set default value of parameter in fit dialog |
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126 | self.tcA.SetLabel(str(self.default_A)) |
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127 | self.tcB.SetLabel(str(self.default_B)) |
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128 | self.tcErrA.SetLabel(str(0.0)) |
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129 | self.tcErrB.SetLabel(str(0.0)) |
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130 | self.tcChi.SetLabel(str(0.0)) |
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131 | if self.plottable.x !=[]: |
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132 | self.mini =min(self.plottable.x) |
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133 | self.maxi =max(self.plottable.x) |
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134 | self.FXmin.SetLabel(str(self.mini)) |
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135 | self.FXmax.SetLabel(str(self.maxi)) |
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136 | |
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137 | self.PXmin.SetValue(str(self.mini)) |
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138 | self.PXmax.SetValue(str(self.maxi)) |
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139 | self.PXmin.Disable() |
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140 | self.PXmax.Disable() |
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141 | |
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142 | |
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143 | # new data for the fit |
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144 | self.file_data1 = Theory1D(x=[], y=[], dy=None) |
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145 | self.file_data1.name = "Fit" |
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146 | |
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147 | def _onFit(self ,event): |
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148 | """ |
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149 | Performs the fit. Receive an event when clicking on the button Fit.Computes chisqr , |
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150 | A and B parameters of the best linear fit y=Ax +B |
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151 | Push a plottable to |
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152 | """ |
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153 | |
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154 | tempx=[] |
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155 | tempy=[] |
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156 | tempdy = [] |
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157 | |
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158 | #Check if the field of Fit Dialog contain values and use the x max and min of the user |
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159 | xmin,xmax = self._checkVal(self.FXmin.GetValue(),self.FXmax.GetValue()) |
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160 | |
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161 | #store the values of View in x,y, dx,dy |
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162 | x,y,dx,dy=self.plottable.returnValuesOfView() |
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163 | # Receive transformations of x and y |
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164 | self.xtrans,self.ytrans= self.transform() |
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165 | |
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166 | # Check if View contains a x array .we online fit when x exits |
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167 | # makes transformation for y as a line to fit |
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168 | if x != []: |
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169 | |
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170 | xminView=self.floatTransform(xmin) |
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171 | xmaxView=self.floatTransform(xmax) |
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172 | |
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173 | # Store the transformed values of view x, y,dy in variables before the fit |
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174 | if self.ytrans.lower() == "log10(y)": |
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175 | for y_i in y: |
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176 | tempy.append(math.log10(y_i)) |
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177 | else: |
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178 | tempy = y |
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179 | if self.xtrans.lower() == "log10(x)": |
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180 | for x_i in x: |
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181 | tempx.append(math.log10(x_i)) |
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182 | else: |
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183 | tempx = x |
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184 | |
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185 | for y_i in y: |
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186 | dy = 1/y_i |
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187 | if dy >= y_i: |
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188 | dy = 0.9*y_i |
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189 | tempdy.append(dy) |
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190 | |
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191 | #Find the fitting parameters |
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192 | print "X", tempx |
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193 | print "Y", tempy |
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194 | chisqr, out, cov = fittings.sansfit(self.model, |
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195 | [self.cstA, self.cstB],tempx, tempy,tempdy,xminView,xmaxView) |
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196 | |
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197 | #Check that cov and out are iterable before displaying them |
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198 | if cov ==None: |
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199 | errA =0.0 |
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200 | errB =0.0 |
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201 | else: |
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202 | errA= math.sqrt(cov[0][0]) |
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203 | errB= math.sqrt(cov[1][1]) |
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204 | if out==None: |
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205 | cstA=0.0 |
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206 | cstB=0.0 |
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207 | else: |
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208 | cstA=out[0] |
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209 | cstB=out[1] |
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210 | # Reset model with the right values of A and B |
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211 | self.model.setParam('A', float(cstA)) |
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212 | self.model.setParam('B', float(cstB)) |
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213 | print "this is constant A:",float(cstA) |
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214 | tempx = [] |
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215 | tempy = [] |
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216 | y_model = 0.0 |
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217 | # load tempy with the minimum transformation |
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218 | |
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219 | if self.xtrans == "log10(x)": |
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220 | y_model = self.model.run(math.log10(xmin)) |
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221 | |
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222 | else: |
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223 | y_model = self.model.run(xminView) |
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224 | tempx.append(xmin) |
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225 | |
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226 | if self.ytrans == "log10(y)": |
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227 | tempy.append(math.pow(10,y_model)) |
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228 | else: |
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229 | tempy.append(y_model) |
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230 | #Load tempy with the value between xView min and xView max |
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231 | #for j in range(len(x)): |
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232 | # if (x[j] > xminView and x[j] < xmaxView): |
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233 | # if self.xtrans == "log10(x)": |
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234 | # y_model = self.model.run(math.log10(x[j])) |
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235 | # else: |
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236 | # y_model = self.model.run(x[j]) |
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237 | |
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238 | |
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239 | # if self.ytrans == "log10(y)": |
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240 | # tempy.append(math.pow(10,y_model)) |
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241 | # else: |
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242 | # tempy.append(y_model) |
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243 | # tempx.append(x[j]) |
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244 | |
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245 | # load tempy with the maximum transformation |
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246 | if self.xtrans == "log10(x)": |
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247 | y_model = self.model.run(math.log10(xmax)) |
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248 | |
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249 | else: |
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250 | y_model = self.model.run(xmaxView) |
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251 | tempx.append(xmax) |
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252 | |
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253 | if self.ytrans == "log10(y)": |
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254 | tempy.append(math.pow(10,y_model)) |
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255 | else: |
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256 | tempy.append(y_model) |
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257 | # Create new data plottable with result |
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258 | self.file_data1.x =[] |
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259 | self.file_data1.y =[] |
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260 | self.file_data1.x =tempx |
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261 | self.file_data1.y =tempy |
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262 | self.file_data1.dx=None |
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263 | self.file_data1.dy=None |
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264 | |
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265 | #Load the view with the new values |
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266 | self.file_data1.reset_view() |
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267 | |
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268 | #Send the data to display to the PlotPanel |
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269 | self.push_data(self.file_data1) |
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270 | |
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271 | # Display the fitting value on the Fit Dialog |
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272 | self._onsetValues(cstA, cstB, errA,errB,chisqr) |
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273 | |
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274 | def _onsetValues(self,cstA,cstB,errA,errB,Chi): |
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275 | """ |
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276 | Display the value on fit Dialog |
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277 | """ |
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278 | self.tcA.SetValue(str(cstA)) |
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279 | self.tcB.SetValue(str(cstB)) |
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280 | self.tcErrA.SetValue(str(errA)) |
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281 | self.tcErrB.SetValue(str(errB)) |
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282 | self.tcChi.SetValue(str(Chi)) |
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283 | |
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284 | def _returnPlottable(self): |
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285 | return self.file_data1 |
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286 | |
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287 | def _checkVal(self,usermin, usermax): |
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288 | """ |
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289 | Ensure that fields parameter contains a min and a max value |
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290 | within x min and x max range |
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291 | """ |
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292 | if float(usermin) < float(usermax): |
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293 | if float(usermin) >= float(self.mini) and float(usermin) < float(self.maxi): |
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294 | self.FXmin.SetValue(str(usermin)) |
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295 | else: |
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296 | self.FXmin.SetValue(str(self.mini)) |
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297 | |
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298 | if float(usermax) > float(self.mini) and float(usermax) <= float(self.maxi): |
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299 | self.FXmax.SetLabel(str(usermax)) |
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300 | else: |
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301 | self.FXmax.SetLabel(str(self.maxi)) |
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302 | |
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303 | mini =float(self.FXmin.GetValue()) |
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304 | maxi =float(self.FXmax.GetValue()) |
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305 | |
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306 | return mini, maxi |
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307 | def floatTransform(self,x): |
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308 | """ |
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309 | transform a float.It is use to determine the x.View min and x.View max for values |
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310 | not in x |
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311 | """ |
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312 | if ( self.xtrans=="x" ): |
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313 | return transform.toX(x) |
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314 | |
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315 | if ( self.xtrans=="x^(2)" ): |
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316 | return transform.toX2(x) |
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317 | |
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318 | if (self.xtrans=="log10(x)" ): |
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319 | if x >0: |
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320 | return math.log10(x) |
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321 | else: |
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322 | raise ValueError,"cannot compute log of a negative number" |
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323 | |
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324 | |
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325 | |
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326 | if __name__ == "__main__": |
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327 | app = wx.App() |
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328 | dialog=LinearFit(None, -1, 'Fitting') |
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329 | dialog.ShowModal() |
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330 | app.MainLoop() |
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331 | |
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332 | |
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