1 | """Prototype plottable object support. |
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2 | |
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3 | The main point of this prototype is to provide a clean separation between |
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4 | the style (plotter details: color, grids, widgets, etc.) and substance |
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5 | (application details: which information to plot). Programmers should not be |
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6 | dictating line colours and plotting symbols. |
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7 | |
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8 | Unlike the problem of style in CSS or Word, where most paragraphs look |
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9 | the same, each line on a graph has to be distinguishable from its neighbours. |
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10 | Our solution is to provide parametric styles, in which a number of |
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11 | different classes of object (e.g., reflectometry data, reflectometry |
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12 | theory) representing multiple graph primitives cycle through a colour |
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13 | palette provided by the underlying plotter. |
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14 | |
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15 | A full treatment would provide perceptual dimensions of prominence and |
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16 | distinctiveness rather than a simple colour number. |
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17 | """ |
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18 | |
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19 | # Design question: who owns the color? |
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20 | # Is it a property of the plottable? |
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21 | # Or of the plottable as it exists on the graph? |
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22 | # Or if the graph? |
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23 | # If a plottable can appear on multiple graphs, in some case the |
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24 | # color should be the same on each graph in which it appears, and |
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25 | # in other cases (where multiple plottables from different graphs |
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26 | # coexist), the color should be assigned by the graph. In any case |
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27 | # once a plottable is placed on the graph its color should not |
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28 | # depend on the other plottables on the graph. Furthermore, if |
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29 | # a plottable is added and removed from a graph and added again, |
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30 | # it may be nice, but not necessary, to have the color persist. |
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31 | # |
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32 | # The safest approach seems to be to give ownership of color |
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33 | # to the graph, which will allocate the colors along with the |
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34 | # plottable. The plottable will need to return the number of |
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35 | # colors that are needed. |
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36 | # |
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37 | # The situation is less clear for symbols. It is less clear |
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38 | # how much the application requires that symbols be unique across |
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39 | # all plots on the graph. |
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40 | |
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41 | # Support for ancient python versions |
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42 | if 'any' not in dir(__builtins__): |
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43 | def any(L): |
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44 | for cond in L: |
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45 | if cond: return True |
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46 | return False |
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47 | def all(L): |
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48 | for cond in L: |
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49 | if not cond: return False |
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50 | return True |
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51 | |
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52 | # Graph structure for holding multiple plottables |
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53 | class Graph: |
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54 | """ |
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55 | Generic plottables graph structure. |
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56 | |
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57 | Plot styles are based on color/symbol lists. The user gets to select |
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58 | the list of colors/symbols/sizes to choose from, not the application |
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59 | developer. The programmer only gets to add/remove lines from the |
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60 | plot and move to the next symbol/color. |
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61 | |
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62 | Another dimension is prominence, which refers to line sizes/point sizes. |
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63 | |
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64 | Axis transformations allow the user to select the coordinate view |
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65 | which provides clarity to the data. There is no way we can provide |
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66 | every possible transformation for every application generically, so |
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67 | the plottable objects themselves will need to provide the transformations. |
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68 | Here are some examples from reflectometry: |
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69 | independent: x -> f(x) |
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70 | monitor scaling: y -> M*y |
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71 | log: y -> log(y if y > min else min) |
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72 | cos: y -> cos(y*pi/180) |
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73 | dependent: x -> f(x,y) |
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74 | Q4: y -> y*x^4 |
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75 | fresnel: y -> y*fresnel(x) |
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76 | coordinated: x,y = f(x,y) |
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77 | Q: x -> 2*pi/L (cos(x*pi/180) - cos(y*pi/180)) |
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78 | y -> 2*pi/L (sin(x*pi/180) + sin(y*pi/180)) |
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79 | reducing: x,y = f(x1,x2,y1,y2) |
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80 | spin asymmetry: x -> x1, y -> (y1 - y2)/(y1 + y2) |
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81 | vector net: x -> x1, y -> y1*cos(y2*pi/180) |
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82 | Multiple transformations are possible, such as Q4 spin asymmetry |
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83 | |
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84 | Axes have further complications in that the units of what are being |
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85 | plotted should correspond to the units on the axes. Plotting multiple |
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86 | types on the same graph should be handled gracefully, e.g., by creating |
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87 | a separate tab for each available axis type, breaking into subplots, |
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88 | showing multiple axes on the same plot, or generating inset plots. |
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89 | Ultimately the decision should be left to the user. |
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90 | |
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91 | Graph properties such as grids/crosshairs should be under user control, |
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92 | as should the sizes of items such as axis fonts, etc. No direct |
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93 | access will be provided to the application. |
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94 | |
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95 | Axis limits are mostly under user control. If the user has zoomed or |
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96 | panned then those limits are preserved even if new data is plotted. |
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97 | The exception is when, e.g., scanning through a set of related lines |
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98 | in which the user may want to fix the limits so that user can compare |
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99 | the values directly. Another exception is when creating multiple |
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100 | graphs sharing the same limits, though this case may be important |
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101 | enough that it is handled by the graph widget itself. Axis limits |
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102 | will of course have to understand the effects of axis transformations. |
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103 | |
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104 | High level plottable objects may be composed of low level primitives. |
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105 | Operations such as legend/hide/show copy/paste, etc. need to operate |
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106 | on these primitives as a group. E.g., allowing the user to have a |
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107 | working canvas where they can drag lines they want to save and annotate |
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108 | them. |
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109 | |
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110 | Graphs need to be printable. A page layout program for entire plots |
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111 | would be nice. |
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112 | """ |
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113 | def xaxis(self,name,units): |
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114 | """Properties of the x axis. |
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115 | """ |
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116 | if self.prop["xunit"] and units != self.prop["xunit"]: |
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117 | pass |
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118 | #print "Plottable: how do we handle non-commensurate units" |
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119 | self.prop["xlabel"] = "%s (%s)"%(name,units) |
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120 | self.prop["xunit"] = units |
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121 | |
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122 | def yaxis(self,name,units): |
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123 | """Properties of the y axis. |
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124 | """ |
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125 | if self.prop["yunit"] and units != self.prop["yunit"]: |
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126 | pass |
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127 | #print "Plottable: how do we handle non-commensurate units" |
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128 | self.prop["ylabel"] = "%s (%s)"%(name,units) |
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129 | self.prop["yunit"] = units |
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130 | |
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131 | def title(self,name): |
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132 | """Graph title |
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133 | """ |
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134 | self.prop["title"] = name |
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135 | |
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136 | def get(self,key): |
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137 | """Get the graph properties""" |
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138 | if key=="color": |
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139 | return self.color |
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140 | elif key == "symbol": |
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141 | return self.symbol |
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142 | else: |
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143 | return self.prop[key] |
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144 | |
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145 | def set(self,**kw): |
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146 | """Set the graph properties""" |
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147 | for key in kw: |
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148 | if key == "color": |
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149 | self.color = kw[key]%len(self.colorlist) |
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150 | elif key == "symbol": |
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151 | self.symbol = kw[key]%len(self.symbollist) |
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152 | else: |
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153 | self.prop[key] = kw[key] |
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154 | |
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155 | def isPlotted(self, plottable): |
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156 | """Return True is the plottable is already on the graph""" |
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157 | if plottable in self.plottables: |
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158 | return True |
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159 | return False |
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160 | |
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161 | def add(self,plottable): |
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162 | """Add a new plottable to the graph""" |
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163 | # record the colour associated with the plottable |
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164 | if not plottable in self.plottables: |
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165 | self.plottables[plottable]=self.color |
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166 | self.color += plottable.colors() |
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167 | |
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168 | def changed(self): |
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169 | """Detect if any graphed plottables have changed""" |
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170 | return any([p.changed() for p in self.plottables]) |
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171 | |
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172 | def delete(self,plottable): |
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173 | """Remove an existing plottable from the graph""" |
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174 | if plottable in self.plottables: |
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175 | del self.plottables[plottable] |
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176 | if self.color > 0: |
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177 | self.color = self.color -1 |
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178 | else: |
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179 | self.color =0 |
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180 | |
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181 | def reset(self): |
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182 | """Reset the graph.""" |
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183 | self.color = 0 |
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184 | self.symbol = 0 |
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185 | self.prop = {"xlabel":"", "xunit":None, |
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186 | "ylabel":"","yunit":None, |
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187 | "title":""} |
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188 | self.plottables = {} |
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189 | |
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190 | def _make_labels(self): |
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191 | # Find groups of related plottables |
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192 | sets = {} |
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193 | for p in self.plottables: |
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194 | if p.__class__ in sets: |
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195 | sets[p.__class__].append(p) |
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196 | else: |
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197 | sets[p.__class__] = [p] |
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198 | |
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199 | # Ask each plottable class for a set of unique labels |
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200 | labels = {} |
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201 | for c in sets: |
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202 | labels.update(c.labels(sets[c])) |
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203 | |
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204 | return labels |
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205 | |
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206 | def returnPlottable(self): |
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207 | return self.plottables |
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208 | |
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209 | def render(self,plot): |
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210 | """Redraw the graph""" |
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211 | plot.clear() |
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212 | plot.properties(self.prop) |
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213 | labels = self._make_labels() |
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214 | for p in self.plottables: |
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215 | p.render(plot,color=self.plottables[p],symbol=0,label=labels[p]) |
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216 | plot.render() |
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217 | |
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218 | def __init__(self,**kw): |
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219 | self.reset() |
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220 | self.set(**kw) |
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221 | |
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222 | |
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223 | # Transform interface definition |
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224 | # No need to inherit from this class, just need to provide |
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225 | # the same methods. |
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226 | class Transform: |
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227 | """Define a transform plugin to the plottable architecture. |
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228 | |
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229 | Transforms operate on axes. The plottable defines the |
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230 | set of transforms available for it, and the axes on which |
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231 | they operate. These transforms can operate on the x axis |
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232 | only, the y axis only or on the x and y axes together. |
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233 | |
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234 | This infrastructure is not able to support transformations |
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235 | such as log and polar plots as these require full control |
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236 | over the drawing of axes and grids. |
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237 | |
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238 | A transform has a number of attributes. |
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239 | |
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240 | name: user visible name for the transform. This will |
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241 | appear in the context menu for the axis and the transform |
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242 | menu for the graph. |
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243 | type: operational axis. This determines whether the |
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244 | transform should appear on x,y or z axis context |
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245 | menus, or if it should appear in the context menu for |
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246 | the graph. |
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247 | inventory: (not implemented) |
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248 | a dictionary of user settable parameter names and |
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249 | their associated types. These should appear as keyword |
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250 | arguments to the transform call. For example, Fresnel |
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251 | reflectivity requires the substrate density: |
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252 | { 'rho': type.Value(10e-6/units.angstrom**2) } |
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253 | Supply reasonable defaults in the callback so that |
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254 | limited plotting clients work even though they cannot |
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255 | set the inventory. |
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256 | """ |
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257 | |
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258 | def __call__(self,plottable,**kwargs): |
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259 | """Transform the data. Whenever a plottable is added |
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260 | to the axes, the infrastructure will apply all required |
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261 | transforms. When the user selects a different representation |
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262 | for the axes (via menu, script, or context menu), all |
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263 | plottables on the axes will be transformed. The |
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264 | plottable should store the underlying data but set |
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265 | the standard x,dx,y,dy,z,dz attributes appropriately. |
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266 | |
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267 | If the call raises a NotImplemented error the dataline |
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268 | will not be plotted. The associated string will usually |
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269 | be 'Not a valid transform', though other strings are possible. |
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270 | The application may or may not display the message to the |
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271 | user, along with an indication of which plottable was at fault. |
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272 | """ |
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273 | raise NotImplemented,"Not a valid transform" |
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274 | |
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275 | # Related issues |
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276 | # ============== |
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277 | # |
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278 | # log scale: |
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279 | # All axes have implicit log/linear scaling options. |
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280 | # |
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281 | # normalization: |
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282 | # Want to display raw counts vs detector efficiency correction |
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283 | # Want to normalize by time/monitor/proton current/intensity. |
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284 | # Want to display by eg. counts per 3 sec or counts per 10000 monitor. |
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285 | # Want to divide by footprint (ab initio, fitted or measured). |
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286 | # Want to scale by attenuator values. |
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287 | # |
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288 | # compare/contrast: |
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289 | # Want to average all visible lines with the same tag, and |
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290 | # display difference from one particular line. Not a transform |
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291 | # issue? |
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292 | # |
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293 | # multiline graph: |
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294 | # How do we show/hide data parts. E.g., data or theory, or |
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295 | # different polarization cross sections? One way is with |
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296 | # tags: each plottable has a set of tags and the tags are |
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297 | # listed as check boxes above the plotting area. Click a |
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298 | # tag and all plottables with that tag are hidden on the |
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299 | # plot and on the legend. |
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300 | # |
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301 | # nonconformant y-axes: |
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302 | # What do we do with temperature vs. Q and reflectivity vs. Q |
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303 | # on the same graph? |
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304 | # |
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305 | # 2D -> 1D: |
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306 | # Want various slices through the data. Do transforms apply |
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307 | # to the sliced data as well? |
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308 | |
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309 | |
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310 | class Plottable: |
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311 | def xaxis(self, name, units): |
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312 | """ |
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313 | Set the name and unit of x_axis |
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314 | @param name: the name of x-axis |
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315 | @param units : the units of x_axis |
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316 | """ |
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317 | self._xaxis = name |
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318 | self._xunit = units |
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319 | |
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320 | def yaxis(self, name, units): |
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321 | """ |
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322 | Set the name and unit of y_axis |
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323 | @param name: the name of y-axis |
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324 | @param units : the units of y_axis |
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325 | """ |
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326 | self._yaxis = name |
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327 | self._yunit = units |
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328 | |
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329 | def get_xaxis(self): |
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330 | """ Return the units and name of x-axis""" |
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331 | return self._xaxis, self._xunit |
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332 | |
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333 | def get_yaxis(self): |
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334 | """ Return the units and name of y- axis""" |
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335 | return self._yaxis, self._yunit |
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336 | |
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337 | @classmethod |
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338 | def labels(cls,collection): |
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339 | """ |
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340 | Construct a set of unique labels for a collection of plottables of |
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341 | the same type. |
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342 | |
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343 | Returns a map from plottable to name. |
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344 | """ |
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345 | n = len(collection) |
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346 | map = {} |
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347 | if n > 0: |
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348 | basename = str(cls).split('.')[-1] |
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349 | if n == 1: |
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350 | map[collection[0]] = basename |
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351 | else: |
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352 | for i in xrange(len(collection)): |
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353 | map[collection[i]] = "%s %d"%(basename,i) |
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354 | return map |
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355 | ##Use the following if @classmethod doesn't work |
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356 | # labels = classmethod(labels) |
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357 | |
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358 | def __init__(self): |
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359 | self.view = View() |
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360 | self._xaxis = "" |
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361 | self._xunit = "" |
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362 | self._yaxis = "" |
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363 | self._yunit = "" |
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364 | |
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365 | def set_View(self,x,y): |
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366 | """ Load View """ |
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367 | self.x= x |
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368 | self.y = y |
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369 | self.reset_view() |
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370 | |
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371 | def reset_view(self): |
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372 | """ Reload view with new value to plot""" |
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373 | self.view = self.View(self.x, self.y, self.dx, self.dy) |
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374 | |
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375 | |
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376 | |
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377 | def render(self,plot): |
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378 | """The base class makes sure the correct units are being used for |
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379 | subsequent plottable. |
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380 | |
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381 | For now it is assumed that the graphs are commensurate, and if you |
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382 | put a Qx object on a Temperature graph then you had better hope |
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383 | that it makes sense. |
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384 | """ |
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385 | |
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386 | plot.xaxis(self._xaxis, self._xunit) |
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387 | plot.yaxis(self._yaxis, self._yunit) |
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388 | |
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389 | def colors(self): |
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390 | """Return the number of colors need to render the object""" |
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391 | return 1 |
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392 | |
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393 | def transform_x(self, func, errfunc): |
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394 | """ |
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395 | @param func: reference to x transformation function |
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396 | |
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397 | """ |
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398 | self.view.transform_x(func, errfunc, x=self.x, y=self.y, dx=self.dx, dy=self.dy) |
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399 | |
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400 | def transform_y(self, func, errfunc): |
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401 | """ |
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402 | @param func: reference to y transformation function |
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403 | |
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404 | """ |
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405 | self.view.transform_y(func, errfunc, self.y, self.x, self.dx, self.dy) |
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406 | |
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407 | |
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408 | def returnValuesOfView(self): |
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409 | |
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410 | return self.view.returnXview() |
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411 | |
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412 | |
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413 | class View: |
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414 | """ |
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415 | Representation of the data that might include a transformation |
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416 | """ |
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417 | x = None |
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418 | y = None |
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419 | dx = None |
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420 | dy = None |
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421 | |
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422 | def __init__(self, x=None, y=None, dx=None, dy=None): |
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423 | self.x = x |
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424 | self.y = y |
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425 | self.dx = dx |
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426 | self.dy = dy |
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427 | |
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428 | def transform_x(self, func, errfunc, x,y=None,dx=None, dy=None): |
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429 | """ |
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430 | Transforms the x and dx vectors and stores the output. |
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431 | |
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432 | @param func: function to apply to the data |
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433 | @param x: array of x values |
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434 | @param dx: array of error values |
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435 | @param errfunc: function to apply to errors |
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436 | """ |
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437 | import copy |
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438 | import numpy |
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439 | |
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440 | # Sanity check |
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441 | has_y = False |
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442 | if dx and not len(x)==len(dx): |
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443 | raise ValueError, "Plottable.View: Given x and dx are not of the same length" |
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444 | # Check length of y array |
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445 | if not y==None: |
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446 | if not len(y)==len(x): |
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447 | raise ValueError, "Plottable.View: Given y and x are not of the same length" |
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448 | else: |
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449 | has_y = True |
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450 | if dy and not len(y)==len(dy): |
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451 | raise ValueError, "Plottable.View: Given y and dy are not of the same length" |
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452 | |
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453 | self.x = numpy.zeros(len(x)) |
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454 | self.dx = numpy.zeros(len(x)) |
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455 | |
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456 | for i in range(len(x)): |
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457 | if has_y: |
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458 | self.x[i] = func(x[i],y[i]) |
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459 | if (dx!=None) and (dy !=None): |
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460 | self.dx[i] = errfunc(x[i], y[i], dx[i], dy[i]) |
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461 | elif (dx != None): |
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462 | self.dx[i] = errfunc(x[i], y[i], dx[i],0) |
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463 | elif (dy != None): |
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464 | self.dx[i] = errfunc(x[i], y[i],0,dy[i]) |
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465 | else: |
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466 | self.dx[i] = errfunc(x[i],y[i],0, 0) |
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467 | else: |
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468 | self.x[i] = func(x[i]) |
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469 | if (dx != None): |
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470 | self.dx[i] = errfunc(x[i], dx[i]) |
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471 | else: |
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472 | self.dx[i] = errfunc(x[i],None) |
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473 | |
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474 | |
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475 | def transform_y(self, func, errfunc, y, x=None,dx=None,dy=None): |
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476 | """ |
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477 | Transforms the y and dy vectors and stores the output. |
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478 | |
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479 | @param func: function to apply to the data y |
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480 | @param x: array of x values |
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481 | @param dx: array of error values |
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482 | @param y: array of y values |
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483 | @param dy: array of error values |
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484 | @param errfunc: function to apply to errors dy |
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485 | """ |
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486 | import copy |
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487 | import numpy |
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488 | # Sanity check |
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489 | has_x = False |
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490 | if dy and not len(y)==len(dy): |
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491 | raise ValueError, "Plottable.View: Given y and dy are not of the same length" |
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492 | # Check length of x array |
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493 | if not x==None: |
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494 | if not len(y)==len(x): |
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495 | raise ValueError, "Plottable.View: Given y and x are not of the same length" |
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496 | else: |
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497 | has_x = True |
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498 | if dx and not len(x)==len(dx): |
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499 | raise ValueError, "Plottable.View: Given x and dx are not of the same length" |
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500 | |
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501 | self.y = numpy.zeros(len(y)) |
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502 | self.dy = numpy.zeros(len(y)) |
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503 | |
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504 | for i in range(len(y)): |
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505 | |
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506 | if has_x: |
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507 | self.y[i] = func(y[i],x[i]) |
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508 | if (dx!=None) and (dy !=None): |
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509 | self.dy[i] = errfunc(y[i], x[i], dy[i], dx[i]) |
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510 | elif (dx != None): |
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511 | self.dy[i] = errfunc(y[i], x[i], 0, dx[i]) |
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512 | elif (dy != None): |
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513 | self.dy[i] = errfunc(y[i], x[i], dy[i], 0) |
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514 | else: |
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515 | self.dy[i] = errfunc(y[i], None) |
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516 | else: |
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517 | self.y[i] = func(y[i]) |
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518 | if (dy != None): |
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519 | self.dy[i] = errfunc( y[i],dy[i]) |
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520 | else: |
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521 | self.dy[i] = errfunc( y[i],None) |
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522 | |
---|
523 | |
---|
524 | def returnXview(self): |
---|
525 | return self.x,self.y,self.dx,self.dy |
---|
526 | |
---|
527 | |
---|
528 | class Data1D(Plottable): |
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529 | """Data plottable: scatter plot of x,y with errors in x and y. |
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530 | """ |
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531 | |
---|
532 | def __init__(self,x,y,dx=None,dy=None): |
---|
533 | """Draw points specified by x[i],y[i] in the current color/symbol. |
---|
534 | Uncertainty in x is given by dx[i], or by (xlo[i],xhi[i]) if the |
---|
535 | uncertainty is asymmetric. Similarly for y uncertainty. |
---|
536 | |
---|
537 | The title appears on the legend. |
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538 | The label, if it is different, appears on the status bar. |
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539 | """ |
---|
540 | self.name = "data" |
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541 | self.x = x |
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542 | self.y = y |
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543 | self.dx = dx |
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544 | self.dy = dy |
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545 | self.xaxis( 'q', 'A') |
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546 | self.yaxis( 'intensity', 'cm') |
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547 | self.view = self.View(self.x, self.y, self.dx, self.dy) |
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548 | |
---|
549 | def render(self,plot,**kw): |
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550 | plot.points(self.view.x,self.view.y,dx=self.view.dx,dy=self.view.dy,**kw) |
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551 | #plot.points(self.x,self.y,dx=self.dx,dy=self.dy,**kw) |
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552 | |
---|
553 | def changed(self): |
---|
554 | return False |
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555 | |
---|
556 | @classmethod |
---|
557 | def labels(cls, collection): |
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558 | """Build a label mostly unique within a collection""" |
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559 | map = {} |
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560 | for item in collection: |
---|
561 | #map[item] = label(item, collection) |
---|
562 | map[item] = r"$\rm{%s}$" % item.name |
---|
563 | return map |
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564 | |
---|
565 | class Theory1D(Plottable): |
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566 | """Theory plottable: line plot of x,y with confidence interval y. |
---|
567 | """ |
---|
568 | def __init__(self,x,y,dy=None): |
---|
569 | """Draw lines specified in x[i],y[i] in the current color/symbol. |
---|
570 | Confidence intervals in x are given by dx[i] or by (xlo[i],xhi[i]) |
---|
571 | if the limits are asymmetric. |
---|
572 | |
---|
573 | The title is the name that will show up on the legend. |
---|
574 | """ |
---|
575 | self.name= "theo" |
---|
576 | self.x = x |
---|
577 | self.y = y |
---|
578 | self.dy = dy |
---|
579 | |
---|
580 | self.view = self.View(self.x, self.y, None, self.dy) |
---|
581 | def render(self,plot,**kw): |
---|
582 | #plot.curve(self.x,self.y,dy=self.dy,**kw) |
---|
583 | plot.curve(self.view.x,self.view.y,dy=self.view.dy,**kw) |
---|
584 | |
---|
585 | def changed(self): |
---|
586 | return False |
---|
587 | @classmethod |
---|
588 | def labels(cls, collection): |
---|
589 | """Build a label mostly unique within a collection""" |
---|
590 | map = {} |
---|
591 | for item in collection: |
---|
592 | #map[item] = label(item, collection) |
---|
593 | map[item] = r"$\rm{%s}$" % item.name |
---|
594 | return map |
---|
595 | |
---|
596 | |
---|
597 | |
---|
598 | class Fit1D(Plottable): |
---|
599 | """Fit plottable: composed of a data line plus a theory line. This |
---|
600 | is treated like a single object from the perspective of the graph, |
---|
601 | except that it will have two legend entries, one for the data and |
---|
602 | one for the theory. |
---|
603 | |
---|
604 | The color of the data and theory will be shared.""" |
---|
605 | |
---|
606 | def __init__(self,data=None,theory=None): |
---|
607 | self.data=data |
---|
608 | self.theory=theory |
---|
609 | |
---|
610 | def render(self,plot,**kw): |
---|
611 | self.data.render(plot,**kw) |
---|
612 | self.theory.render(plot,**kw) |
---|
613 | |
---|
614 | def changed(self): |
---|
615 | return self.data.changed() or self.theory.changed() |
---|
616 | |
---|
617 | ###################################################### |
---|
618 | |
---|
619 | def sample_graph(): |
---|
620 | import numpy as nx |
---|
621 | |
---|
622 | # Construct a simple graph |
---|
623 | if False: |
---|
624 | x = nx.array([1,2,3,4,5,6],'d') |
---|
625 | y = nx.array([4,5,6,5,4,5],'d') |
---|
626 | dy = nx.array([0.2, 0.3, 0.1, 0.2, 0.9, 0.3]) |
---|
627 | else: |
---|
628 | x = nx.linspace(0,1.,10000) |
---|
629 | y = nx.sin(2*nx.pi*x*2.8) |
---|
630 | dy = nx.sqrt(100*nx.abs(y))/100 |
---|
631 | data = Data1D(x,y,dy=dy) |
---|
632 | data.xaxis('distance', 'm') |
---|
633 | data.yaxis('time', 's') |
---|
634 | graph = Graph() |
---|
635 | graph.title('Walking Results') |
---|
636 | graph.add(data) |
---|
637 | graph.add(Theory1D(x,y,dy=dy)) |
---|
638 | |
---|
639 | return graph |
---|
640 | |
---|
641 | def demo_plotter(graph): |
---|
642 | import wx |
---|
643 | #from pylab_plottables import Plotter |
---|
644 | from mplplotter import Plotter |
---|
645 | |
---|
646 | # Make a frame to show it |
---|
647 | app = wx.PySimpleApp() |
---|
648 | frame = wx.Frame(None,-1,'Plottables') |
---|
649 | plotter = Plotter(frame) |
---|
650 | frame.Show() |
---|
651 | |
---|
652 | # render the graph to the pylab plotter |
---|
653 | graph.render(plotter) |
---|
654 | |
---|
655 | class GraphUpdate: |
---|
656 | callnum=0 |
---|
657 | def __init__(self,graph,plotter): |
---|
658 | self.graph,self.plotter = graph,plotter |
---|
659 | def __call__(self): |
---|
660 | if self.graph.changed(): |
---|
661 | self.graph.render(self.plotter) |
---|
662 | return True |
---|
663 | return False |
---|
664 | def onIdle(self,event): |
---|
665 | #print "On Idle checker %d"%(self.callnum) |
---|
666 | self.callnum = self.callnum+1 |
---|
667 | if self.__call__(): |
---|
668 | pass # event.RequestMore() |
---|
669 | update = GraphUpdate(graph,plotter) |
---|
670 | frame.Bind(wx.EVT_IDLE,update.onIdle) |
---|
671 | app.MainLoop() |
---|
672 | |
---|
673 | import sys; print sys.version |
---|
674 | if __name__ == "__main__": |
---|
675 | demo_plotter(sample_graph()) |
---|
676 | |
---|