1 | import wx.lib.newevent |
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2 | import matplotlib |
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3 | matplotlib.interactive(False) |
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4 | #Use the WxAgg back end. The Wx one takes too long to render |
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5 | matplotlib.use('WXAgg') |
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6 | from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg |
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7 | from matplotlib.figure import Figure |
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8 | import os |
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9 | import fittings |
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10 | import transform |
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11 | from canvas import FigureCanvas |
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12 | from matplotlib.widgets import RectangleSelector |
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13 | from pylab import gca, gcf |
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14 | |
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15 | #TODO: make the plottables interactive |
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16 | |
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17 | from plottables import Graph |
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18 | #(FuncFitEvent, EVT_FUNC_FIT) = wx.lib.newevent.NewEvent() |
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19 | import math,pylab |
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20 | def show_tree(obj,d=0): |
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21 | """Handy function for displaying a tree of graph objects""" |
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22 | print "%s%s" % ("-"*d,obj.__class__.__name__) |
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23 | if 'get_children' in dir(obj): |
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24 | for a in obj.get_children(): show_tree(a,d+1) |
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25 | |
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26 | |
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27 | |
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28 | class PlotPanel(wx.Panel): |
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29 | """ |
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30 | The PlotPanel has a Figure and a Canvas. OnSize events simply set a |
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31 | flag, and the actually redrawing of the |
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32 | figure is triggered by an Idle event. |
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33 | """ |
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34 | def __init__(self, parent, id = -1, color = None,\ |
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35 | dpi = None, **kwargs): |
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36 | wx.Panel.__init__(self, parent, id = id, **kwargs) |
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37 | self.parent = parent |
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38 | self.figure = Figure(None, dpi) |
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39 | #self.figure = pylab.Figure(None, dpi) |
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40 | #self.canvas = NoRepaintCanvas(self, -1, self.figure) |
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41 | self.canvas = FigureCanvas(self, -1, self.figure) |
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42 | self.SetColor(color) |
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43 | #self.Bind(wx.EVT_IDLE, self._onIdle) |
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44 | #self.Bind(wx.EVT_SIZE, self._onSize) |
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45 | self._resizeflag = True |
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46 | self._SetSize() |
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47 | self.subplot = self.figure.add_subplot(111) |
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48 | self.figure.subplots_adjust(left=.2, bottom=.2) |
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49 | self.yscale = 'linear' |
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50 | self.xscale = 'linear' |
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51 | sizer = wx.BoxSizer(wx.VERTICAL) |
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52 | sizer.Add(self.canvas,1,wx.EXPAND) |
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53 | self.SetSizer(sizer) |
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54 | |
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55 | # Graph object to manage the plottables |
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56 | self.graph = Graph() |
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57 | #self.Bind(EVT_FUNC_FIT, self.onFitRange) |
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58 | self.Bind(wx.EVT_CONTEXT_MENU, self.onContextMenu) |
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59 | #self.Bind(EVT_PROPERTY, self._onEVT_FUNC_PROPERTY) |
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60 | # Define some constants |
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61 | self.colorlist = ['b','g','r','c','m','y'] |
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62 | self.symbollist = ['o','x','^','v','<','>','+','s','d','D','h','H','p'] |
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63 | #User scale |
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64 | self.xscales ="x" |
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65 | self.yscales ="log10(y)" |
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66 | self.viewModel ="--" |
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67 | # keep track if the previous transformation of x and y in Property dialog |
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68 | self.prevXtrans =" " |
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69 | |
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70 | self.prevYtrans =" " |
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71 | |
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72 | def returnTrans(self): |
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73 | return self.xscales,self.yscales |
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74 | |
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75 | def setTrans(self,xtrans,ytrans): |
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76 | """ |
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77 | @param xtrans: set x transformation on Property dialog |
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78 | @param ytrans: set y transformation on Property dialog |
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79 | """ |
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80 | self.prevXtrans =xtrans |
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81 | self.prevYtrans =ytrans |
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82 | |
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83 | def onFitting(self, event): |
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84 | """ |
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85 | when clicking on linear Fit on context menu , display Fitting Dialog |
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86 | """ |
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87 | list =[] |
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88 | list = self.graph.returnPlottable() |
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89 | from fitDialog import LinearFit |
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90 | |
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91 | if len(list.keys())>0: |
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92 | first_item = list.keys()[0] |
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93 | dlg = LinearFit( None, first_item, self.onFitDisplay,self.returnTrans, -1, 'Fitting') |
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94 | dlg.ShowModal() |
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95 | |
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96 | def _onProperties(self, event): |
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97 | """ |
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98 | when clicking on Properties on context menu ,The Property dialog is displayed |
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99 | The user selects a transformation for x or y value and a new plot is displayed |
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100 | """ |
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101 | from PropertyDialog import Properties |
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102 | dial = Properties(self, -1, 'Properties') |
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103 | dial.setValues( self.prevXtrans, self.prevYtrans,self.viewModel ) |
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104 | if dial.ShowModal() == wx.ID_OK: |
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105 | self.xscales, self.yscales,self.viewModel = dial.getValues() |
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106 | if self.viewModel =="Guinier lny vs x^(2)": |
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107 | self.xscales="x^(2)" |
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108 | self.yscales="ln(y)" |
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109 | self.viewModel = "--" |
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110 | dial.setValues( self.xscales, self.yscales,self.viewModel ) |
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111 | self._onEVT_FUNC_PROPERTY() |
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112 | dial.Destroy() |
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113 | |
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114 | def set_yscale(self, scale='linear'): |
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115 | """ |
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116 | Set the scale on Y-axis |
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117 | @param scale: the scale of y-axis |
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118 | """ |
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119 | self.subplot.set_yscale(scale) |
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120 | self.yscale = scale |
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121 | |
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122 | def get_yscale(self): |
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123 | """ |
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124 | @return: Y-axis scale |
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125 | """ |
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126 | return self.yscale |
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127 | |
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128 | def set_xscale(self, scale='linear'): |
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129 | """ |
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130 | Set the scale on x-axis |
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131 | @param scale: the scale of x-axis |
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132 | """ |
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133 | self.subplot.set_xscale(scale) |
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134 | self.xscale = scale |
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135 | |
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136 | def get_xscale(self): |
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137 | """ |
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138 | @return: x-axis scale |
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139 | """ |
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140 | return self.xscale |
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141 | |
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142 | def SetColor(self, rgbtuple): |
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143 | """Set figure and canvas colours to be the same""" |
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144 | if not rgbtuple: |
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145 | rgbtuple = wx.SystemSettings.GetColour(wx.SYS_COLOUR_BTNFACE).Get() |
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146 | col = [c/255.0 for c in rgbtuple] |
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147 | self.figure.set_facecolor(col) |
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148 | self.figure.set_edgecolor(col) |
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149 | self.canvas.SetBackgroundColour(wx.Colour(*rgbtuple)) |
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150 | |
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151 | def _onSize(self, event): |
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152 | self._resizeflag = True |
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153 | |
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154 | def _onIdle(self, evt): |
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155 | if self._resizeflag: |
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156 | self._resizeflag = False |
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157 | self._SetSize() |
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158 | self.draw() |
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159 | |
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160 | def _SetSize(self, pixels = None): |
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161 | """ |
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162 | This method can be called to force the Plot to be a desired size, which defaults to |
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163 | the ClientSize of the panel |
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164 | """ |
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165 | if not pixels: |
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166 | pixels = self.GetClientSize() |
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167 | self.canvas.SetSize(pixels) |
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168 | self.figure.set_size_inches(pixels[0]/self.figure.get_dpi(), |
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169 | pixels[1]/self.figure.get_dpi()) |
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170 | |
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171 | def draw(self): |
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172 | """Where the actual drawing happens""" |
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173 | self.figure.canvas.draw_idle() |
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174 | |
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175 | |
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176 | |
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177 | |
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178 | def onselect(self,event1, event2): |
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179 | print"went here" |
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180 | from matplotlib.widgets import RectangleSelector |
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181 | from pylab import show, gca, gcf |
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182 | |
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183 | 'event1 and event2 are the press and release events' |
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184 | x1, y1 = event1.xdata, event1.ydata |
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185 | x2, y2 = event2.xdata, event2.ydata |
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186 | print "(%3.2f, %3.2f) --> (%3.2f, %3.2f)"%(x1,y1,x2,y2) |
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187 | print " The button you used were: ",event1.button, event2.button |
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188 | gca().set_xlim([x1,x2]) |
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189 | gca().set_ylim([y1,y2]) |
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190 | gcf().canvas.draw_idle() |
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191 | |
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192 | # drawtype is 'box' or 'line' or 'none' |
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193 | LS = RectangleSelector(self.subplot, onselect,drawtype='box',useblit=True) |
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194 | show() |
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195 | |
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196 | |
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197 | |
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198 | |
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199 | def onSaveImage(self, evt): |
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200 | #figure.savefig |
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201 | #print "Save image not implemented" |
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202 | path = None |
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203 | dlg = wx.FileDialog(self, "Choose a file", os.getcwd(), "", "*.png", wx.SAVE) |
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204 | if dlg.ShowModal() == wx.ID_OK: |
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205 | path = dlg.GetPath() |
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206 | mypath = os.path.basename(path) |
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207 | print path |
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208 | dlg.Destroy() |
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209 | if not path == None: |
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210 | self.subplot.figure.savefig(path,dpi=300, facecolor='w', edgecolor='w', |
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211 | orentation='portrait', papertype=None, format='png') |
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212 | |
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213 | def onContextMenu(self, event): |
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214 | """ |
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215 | Default context menu for a plot panel |
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216 | """ |
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217 | # Slicer plot popup menu |
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218 | slicerpop = wx.Menu() |
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219 | slicerpop.Append(313,'&Save image', 'Save image as PNG') |
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220 | wx.EVT_MENU(self, 313, self.onSaveImage) |
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221 | |
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222 | slicerpop.Append(316, '&Load 1D data file') |
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223 | wx.EVT_MENU(self, 316, self._onLoad1DData) |
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224 | |
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225 | slicerpop.AppendSeparator() |
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226 | slicerpop.Append(315, '&Properties') |
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227 | wx.EVT_MENU(self, 315, self._onProperties) |
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228 | |
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229 | slicerpop.AppendSeparator() |
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230 | slicerpop.Append(317, '&Linear Fit') |
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231 | wx.EVT_MENU(self, 317, self.onFitting) |
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232 | |
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233 | pos = event.GetPosition() |
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234 | pos = self.ScreenToClient(pos) |
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235 | self.PopupMenu(slicerpop, pos) |
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236 | |
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237 | ## The following is plottable functionality |
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238 | |
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239 | |
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240 | def properties(self,prop): |
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241 | """Set some properties of the graph. |
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242 | |
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243 | The set of properties is not yet determined. |
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244 | """ |
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245 | # The particulars of how they are stored and manipulated (e.g., do |
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246 | # we want an inventory internally) is not settled. I've used a |
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247 | # property dictionary for now. |
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248 | # |
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249 | # How these properties interact with a user defined style file is |
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250 | # even less clear. |
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251 | |
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252 | # Properties defined by plot |
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253 | self.subplot.set_xlabel(r"$%s$" % prop["xlabel"]) |
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254 | self.subplot.set_ylabel(r"$%s$" % prop["ylabel"]) |
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255 | self.subplot.set_title(prop["title"]) |
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256 | |
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257 | # Properties defined by user |
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258 | #self.axes.grid(True) |
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259 | |
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260 | def clear(self): |
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261 | """Reset the plot""" |
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262 | |
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263 | # TODO: Redraw is brutal. Render to a backing store and swap in |
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264 | # TODO: rather than redrawing on the fly. |
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265 | self.subplot.clear() |
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266 | self.subplot.hold(True) |
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267 | |
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268 | def render(self): |
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269 | """Commit the plot after all objects are drawn""" |
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270 | # TODO: this is when the backing store should be swapped in. |
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271 | from matplotlib.font_manager import FontProperties |
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272 | self.subplot.legend(prop=FontProperties(size=10)) |
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273 | #self.subplot.legend() |
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274 | pass |
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275 | |
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276 | def xaxis(self,label,units): |
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277 | """xaxis label and units. |
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278 | |
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279 | Axis labels know about units. |
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280 | |
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281 | We need to do this so that we can detect when axes are not |
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282 | commesurate. Currently this is ignored other than for formatting |
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283 | purposes. |
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284 | """ |
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285 | if units != "": label = label + " (" + units + ")" |
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286 | self.subplot.set_xlabel(label) |
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287 | pass |
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288 | |
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289 | def yaxis(self,label,units): |
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290 | """yaxis label and units.""" |
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291 | if units != "": label = label + " (" + units + ")" |
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292 | self.subplot.set_ylabel(label) |
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293 | pass |
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294 | |
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295 | def _connect_to_xlim(self,callback): |
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296 | """Bind the xlim change notification to the callback""" |
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297 | def process_xlim(axes): |
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298 | lo,hi = subplot.get_xlim() |
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299 | callback(lo,hi) |
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300 | self.subplot.callbacks.connect('xlim_changed',process_xlim) |
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301 | |
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302 | #def connect(self,trigger,callback): |
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303 | # print "PlotPanel.connect???" |
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304 | # if trigger == 'xlim': self._connect_to_xlim(callback) |
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305 | |
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306 | def points(self,x,y,dx=None,dy=None,color=0,symbol=0,label=None): |
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307 | """Draw markers with error bars""" |
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308 | self.subplot.set_yscale('linear') |
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309 | self.subplot.set_xscale('linear') |
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310 | # Convert tuple (lo,hi) to array [(x-lo),(hi-x)] |
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311 | if dx != None and type(dx) == type(()): |
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312 | dx = nx.vstack((x-dx[0],dx[1]-x)).transpose() |
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313 | if dy != None and type(dy) == type(()): |
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314 | dy = nx.vstack((y-dy[0],dy[1]-y)).transpose() |
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315 | |
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316 | if dx==None and dy==None: |
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317 | h = self.subplot.plot(x,y,color=self._color(color), |
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318 | marker=self._symbol(symbol),linestyle='',label=label) |
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319 | else: |
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320 | self.subplot.errorbar(x, y, yerr=dy, xerr=None, |
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321 | ecolor=self._color(color), capsize=2,linestyle='', barsabove=False, |
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322 | marker=self._symbol(symbol), |
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323 | lolims=False, uplims=False, |
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324 | xlolims=False, xuplims=False,label=label) |
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325 | |
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326 | self.subplot.set_yscale(self.yscale) |
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327 | self.subplot.set_xscale(self.xscale) |
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328 | |
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329 | def curve(self,x,y,dy=None,color=0,symbol=0,label=None): |
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330 | """Draw a line on a graph, possibly with confidence intervals.""" |
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331 | c = self._color(color) |
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332 | self.subplot.set_yscale('linear') |
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333 | self.subplot.set_xscale('linear') |
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334 | |
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335 | hlist = self.subplot.plot(x,y,color=c,marker='',linestyle='-',label=label) |
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336 | |
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337 | self.subplot.set_yscale(self.yscale) |
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338 | self.subplot.set_xscale(self.xscale) |
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339 | |
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340 | def _color(self,c): |
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341 | """Return a particular colour""" |
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342 | return self.colorlist[c%len(self.colorlist)] |
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343 | |
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344 | def _symbol(self,s): |
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345 | """Return a particular symbol""" |
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346 | return self.symbollist[s%len(self.symbollist)] |
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347 | |
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348 | def _onEVT_FUNC_PROPERTY(self): |
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349 | """ |
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350 | Receive the x and y transformation from myDialog,Transforms x and y in View |
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351 | and set the scale |
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352 | """ |
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353 | list =[] |
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354 | list = self.graph.returnPlottable() |
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355 | |
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356 | for item in list: |
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357 | item.getTransform(self.xscales,self.yscales) |
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358 | if ( self.xscales=="x" ): |
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359 | item.returnTransformationx(transform.toX,transform.errToX) |
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360 | |
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361 | self.set_xscale("linear") |
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362 | name, units = item.get_xaxis() |
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363 | self.graph.xaxis("%s" % name, "%s^{-1}" % units) |
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364 | |
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365 | if ( self.xscales=="x^(2)" ): |
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366 | item.returnTransformationx(transform.toX2,transform.errToX2) |
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367 | self.set_xscale('linear') |
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368 | name, units = item.get_xaxis() |
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369 | self.graph.xaxis("%s^{2}" % name, "%s^{-2}" % units) |
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370 | |
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371 | if (self.xscales=="log10(x)" ): |
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372 | item.returnTransformationx(transform.toX,transform.errToX) |
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373 | self.set_xscale("log") |
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374 | name, units = item.get_xaxis() |
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375 | self.graph.xaxis("Log10 %s" % name, "%s^{-1}" % units) |
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376 | |
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377 | if ( self.yscales=="ln(y)" ): |
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378 | item.returnTransformationy(transform.toLogX,transform.errToLogX) |
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379 | self.set_yscale("linear") |
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380 | name, units = item.get_yaxis() |
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381 | item.check_data_PlottableY() |
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382 | self.graph.yaxis("log %s" % name, "%s^{-1}" % units) |
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383 | |
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384 | if ( self.yscales=="y" ): |
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385 | item.returnTransformationy(transform.toX,transform.errToX) |
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386 | self.set_yscale("linear") |
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387 | name, units = item.get_yaxis() |
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388 | self.graph.yaxis("%s" % name, "%s^{-1}" % units) |
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389 | |
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390 | if ( self.yscales=="log10(y)" ): |
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391 | item.returnTransformationy(transform.toX,transform.errToX) |
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392 | item.check_data_PlottableY() |
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393 | self.set_yscale("log") |
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394 | name, units = item.get_yaxis() |
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395 | self.graph.yaxis("Log10 %s" % name, "%s^{-1}" % units) |
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396 | |
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397 | if ( self.yscales=="y^(2)" ): |
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398 | item.returnTransformationy( transform.toX2,transform.errToX2 ) |
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399 | self.set_yscale("linear") |
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400 | name, units = item.get_yaxis() |
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401 | self.graph.yaxis("%s^2" % name, "%s^{-2}" % units) |
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402 | |
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403 | if ( self.yscales =="1/y"): |
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404 | item.returnTransformationy(transform.toOneOverX,transform.errOneOverX ) |
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405 | self.set_yscale("linear") |
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406 | name, units = item.get_yaxis() |
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407 | self.graph.yaxis("%s" % name, "%s" % units) |
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408 | |
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409 | if ( self.yscales =="1/sqrt(y)" ): |
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410 | item.returnTransformationy(transform.toOneOverSqrtX,transform.errOneOverSqrtX ) |
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411 | self.set_yscale("linear") |
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412 | name, units = item.get_yaxis() |
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413 | item.check_data_PlottableY() |
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414 | self.graph.yaxis("%s" %name, "%s" % units) |
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415 | |
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416 | if ( self.yscales =="ln(y*x)"): |
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417 | item.returnTransformationy( transform.toLogXY,transform.errToLogXY) |
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418 | self.set_yscale("linear") |
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419 | yname, yunits = item.get_yaxis() |
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420 | xname, xunits = item.get_xaxis() |
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421 | self.graph.yaxis("Log %s%s" % (yname,xname), "%s^{-1}%s^{-1}" % (yunits,xunits)) |
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422 | |
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423 | if ( self.yscales =="ln(y*x^(2))"): |
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424 | item.returnTransformationy( transform.toLogYX2,transform.errToLogYX2) |
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425 | self.set_yscale("linear") |
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426 | yname, yunits = item.get_yaxis() |
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427 | xname, xunits = item.get_xaxis() |
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428 | item.check_data_PlottableY() |
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429 | self.graph.yaxis("Log %s%s^{2}" % (yname,xname), "%s^{-1}%s^{-2}" % (yunits,xunits)) |
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430 | |
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431 | if ( self.yscales =="ln(y*x^(4))"): |
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432 | item.returnTransformationy(transform.toLogYX4,transform.errToLogYX4) |
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433 | self.set_yscale("linear") |
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434 | yname, yunits = item.get_yaxis() |
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435 | xname, xunits = item.get_xaxis() |
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436 | self.graph.yaxis("Log %s%s^{4}" % (yname,xname), "%s^{-1}%s^{-4}" % (yunits,xunits)) |
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437 | |
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438 | if ( self.viewModel == "Guinier lny vs x^(2)"): |
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439 | item.returnTransformationx(transform.toX2,transform.errToX2) |
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440 | self.set_xscale('linear') |
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441 | name, units = item.get_xaxis() |
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442 | self.graph.xaxis("%s^{2}" % name, "%s^{-2}" % units) |
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443 | item.returnTransformationy(transform.toLogX,transform.errToLogX ) |
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444 | self.set_yscale("linear") |
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445 | name, units = item.get_yaxis() |
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446 | self.graph.yaxis("$Log %s$" % name, "%s^{-1}" % units) |
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447 | |
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448 | #item.name = self.yscales+" vs " +self.xscales |
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449 | self.prevXtrans = self.xscales |
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450 | self.prevYtrans = self.yscales |
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451 | item.transformView() |
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452 | self.graph.render(self) |
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453 | self.subplot.figure.canvas.draw_idle() |
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454 | |
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455 | def onFitDisplay(self, plottable): |
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456 | """ |
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457 | Add a new plottable into the graph .In this case this plottable will be used |
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458 | to fit some data |
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459 | @param plottable: the plottable to plot |
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460 | """ |
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461 | #Add the data to fit |
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462 | |
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463 | self.graph.add(plottable) |
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464 | self.graph.render(self) |
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465 | |
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466 | self.subplot.figure.canvas.draw_idle() |
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467 | self.graph.delete(plottable) |
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468 | |
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469 | |
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470 | |
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471 | class NoRepaintCanvas(FigureCanvasWxAgg): |
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472 | """We subclass FigureCanvasWxAgg, overriding the _onPaint method, so that |
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473 | the draw method is only called for the first two paint events. After that, |
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474 | the canvas will only be redrawn when it is resized. |
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475 | """ |
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476 | def __init__(self, *args, **kwargs): |
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477 | FigureCanvasWxAgg.__init__(self, *args, **kwargs) |
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478 | self._drawn = 0 |
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479 | |
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480 | def _onPaint(self, evt): |
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481 | """ |
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482 | Called when wxPaintEvt is generated |
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483 | """ |
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484 | if not self._isRealized: |
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485 | self.realize() |
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486 | if self._drawn < 2: |
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487 | self.draw(repaint = False) |
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488 | self._drawn += 1 |
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489 | self.gui_repaint(drawDC=wx.PaintDC(self)) |
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490 | |
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