| 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 | from plottables import Theory1D |
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| 15 | #from plottables import Data1D |
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| 16 | #TODO: make the plottables interactive |
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| 17 | |
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| 18 | from plottables import Graph |
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| 19 | #(FuncFitEvent, EVT_FUNC_FIT) = wx.lib.newevent.NewEvent() |
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| 20 | import math,pylab |
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| 21 | def show_tree(obj,d=0): |
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| 22 | """Handy function for displaying a tree of graph objects""" |
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| 23 | print "%s%s" % ("-"*d,obj.__class__.__name__) |
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| 24 | if 'get_children' in dir(obj): |
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| 25 | for a in obj.get_children(): show_tree(a,d+1) |
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| 26 | def _rescale(lo,hi,step,pt=None,bal=None,scale='linear'): |
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| 27 | """ |
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| 28 | Rescale (lo,hi) by step, returning the new (lo,hi) |
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| 29 | The scaling is centered on pt, with positive values of step |
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| 30 | driving lo/hi away from pt and negative values pulling them in. |
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| 31 | If bal is given instead of point, it is already in [0,1] coordinates. |
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| 32 | |
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| 33 | This is a helper function for step-based zooming. |
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| 34 | """ |
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| 35 | # Convert values into the correct scale for a linear transformation |
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| 36 | # TODO: use proper scale transformers |
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| 37 | loprev = lo |
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| 38 | hiprev = hi |
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| 39 | ptprev = pt |
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| 40 | if scale=='log': |
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| 41 | #assert lo >0 |
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| 42 | if lo > 0 : |
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| 43 | lo = math.log10(lo) |
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| 44 | if hi > 0 : |
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| 45 | hi = math.log10(hi) |
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| 46 | if pt is not None: pt = math.log10(pt) |
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| 47 | |
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| 48 | # Compute delta from axis range * %, or 1-% if persent is negative |
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| 49 | if step > 0: |
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| 50 | delta = float(hi-lo)*step/100 |
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| 51 | else: |
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| 52 | delta = float(hi-lo)*step/(100-step) |
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| 53 | |
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| 54 | # Add scale factor proportionally to the lo and hi values, preserving the |
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| 55 | # point under the mouse |
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| 56 | if bal is None: |
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| 57 | bal = float(pt-lo)/(hi-lo) |
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| 58 | lo = lo - bal*delta |
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| 59 | hi = hi + (1-bal)*delta |
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| 60 | |
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| 61 | # Convert transformed values back to the original scale |
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| 62 | if scale=='log': |
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| 63 | #if (lo <= -300) and (hi >= 300): |
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| 64 | if (lo > 0) and (math.log(lo) <= -300): |
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| 65 | lo=loprev |
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| 66 | hi=hiprev |
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| 67 | print "Not possible to scale" |
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| 68 | if (lo == 0) or (lo <= -300): |
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| 69 | lo=loprev |
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| 70 | hi=hiprev |
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| 71 | print "Not possible to scale" |
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| 72 | else: |
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| 73 | lo,hi = math.pow(10.,lo),math.pow(10.,hi) |
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| 74 | #assert lo >0,"lo = %g"%lo |
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| 75 | print "possible to scale" |
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| 76 | |
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| 77 | print "these are low and high",lo,hi |
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| 78 | |
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| 79 | return (lo,hi) |
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| 80 | |
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| 81 | |
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| 82 | class PlotPanel(wx.Panel): |
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| 83 | """ |
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| 84 | The PlotPanel has a Figure and a Canvas. OnSize events simply set a |
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| 85 | flag, and the actually redrawing of the |
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| 86 | figure is triggered by an Idle event. |
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| 87 | """ |
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| 88 | def __init__(self, parent, id = -1, color = None,\ |
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| 89 | dpi = None, **kwargs): |
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| 90 | wx.Panel.__init__(self, parent, id = id, **kwargs) |
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| 91 | self.parent = parent |
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| 92 | self.figure = Figure(None, dpi) |
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| 93 | #self.figure = pylab.Figure(None, dpi) |
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| 94 | #self.canvas = NoRepaintCanvas(self, -1, self.figure) |
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| 95 | self.canvas = FigureCanvas(self, -1, self.figure) |
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| 96 | self.SetColor(color) |
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| 97 | #self.Bind(wx.EVT_IDLE, self._onIdle) |
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| 98 | #self.Bind(wx.EVT_SIZE, self._onSize) |
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| 99 | self._resizeflag = True |
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| 100 | self._SetSize() |
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| 101 | self.subplot = self.figure.add_subplot(111) |
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| 102 | self.figure.subplots_adjust(left=.2, bottom=.2) |
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| 103 | self.yscale = 'linear' |
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| 104 | self.xscale = 'linear' |
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| 105 | sizer = wx.BoxSizer(wx.VERTICAL) |
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| 106 | sizer.Add(self.canvas,1,wx.EXPAND) |
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| 107 | self.SetSizer(sizer) |
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| 108 | |
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| 109 | # Graph object to manage the plottables |
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| 110 | self.graph = Graph() |
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| 111 | #self.Bind(EVT_FUNC_FIT, self.onFitRange) |
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| 112 | self.Bind(wx.EVT_CONTEXT_MENU, self.onContextMenu) |
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| 113 | #self.Bind(EVT_PROPERTY, self._onEVT_FUNC_PROPERTY) |
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| 114 | # Define some constants |
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| 115 | self.colorlist = ['b','g','r','c','m','y'] |
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| 116 | self.symbollist = ['o','x','^','v','<','>','+','s','d','D','h','H','p'] |
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| 117 | #User scale |
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| 118 | self.xLabel ="x" |
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| 119 | self.yLabel ="log10(y)" |
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| 120 | self.viewModel ="--" |
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| 121 | # keep track if the previous transformation of x and y in Property dialog |
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| 122 | self.prevXtrans =" " |
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| 123 | self.prevYtrans =" " |
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| 124 | self.canvas.mpl_connect('scroll_event',self.onWheel) |
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| 125 | self.axes = [self.subplot] |
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| 126 | # new data for the fit |
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| 127 | self.fit_result = Theory1D(x=[], y=[], dy=None) |
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| 128 | #self.fit_result = Data1D(x=[], y=[],dx=None, dy=None) |
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| 129 | self.fit_result.name = "Fit" |
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| 130 | # For fit Dialog initial display |
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| 131 | self.xmin=0.0 |
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| 132 | self.xmax=0.0 |
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| 133 | self.xminView=0.0 |
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| 134 | self.xmaxView=0.0 |
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| 135 | self.Avalue=None |
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| 136 | self.Bvalue=None |
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| 137 | self.ErrAvalue=None |
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| 138 | self.ErrBvalue=None |
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| 139 | self.Chivalue=None |
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| 140 | def resetFitView(self): |
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| 141 | """ |
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| 142 | For fit Dialog initial display |
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| 143 | """ |
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| 144 | self.xmin=0.0 |
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| 145 | self.xmax=0.0 |
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| 146 | self.xminView=0.0 |
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| 147 | self.xmaxView=0.0 |
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| 148 | self.Avalue=None |
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| 149 | self.Bvalue=None |
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| 150 | self.ErrAvalue=None |
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| 151 | self.ErrBvalue=None |
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| 152 | self.Chivalue=None |
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| 153 | def onWheel(self, event): |
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| 154 | """ |
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| 155 | Process mouse wheel as zoom events |
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| 156 | """ |
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| 157 | ax = event.inaxes |
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| 158 | step = event.step |
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| 159 | |
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| 160 | if ax != None: |
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| 161 | # Event occurred inside a plotting area |
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| 162 | lo,hi = ax.get_xlim() |
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| 163 | lo,hi = _rescale(lo,hi,step,pt=event.xdata) |
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| 164 | ax.set_xlim((lo,hi)) |
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| 165 | |
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| 166 | lo,hi = ax.get_ylim() |
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| 167 | lo,hi = _rescale(lo,hi,step,pt=event.ydata) |
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| 168 | ax.set_ylim((lo,hi)) |
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| 169 | else: |
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| 170 | # Check if zoom happens in the axes |
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| 171 | xdata,ydata = None,None |
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| 172 | x,y = event.x,event.y |
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| 173 | |
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| 174 | for ax in self.axes: |
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| 175 | insidex,_ = ax.xaxis.contains(event) |
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| 176 | if insidex: |
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| 177 | xdata,_ = ax.transAxes.inverse_xy_tup((x,y)) |
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| 178 | print "xaxis",x,"->",xdata |
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| 179 | insidey,_ = ax.yaxis.contains(event) |
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| 180 | if insidey: |
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| 181 | _,ydata = ax.transAxes.inverse_xy_tup((x,y)) |
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| 182 | print "yaxis",y,"->",ydata |
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| 183 | if xdata is not None: |
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| 184 | lo,hi = ax.get_xlim() |
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| 185 | lo,hi = _rescale(lo,hi,step,bal=xdata,scale=ax.get_xscale()) |
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| 186 | ax.set_xlim((lo,hi)) |
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| 187 | if ydata is not None: |
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| 188 | lo,hi = ax.get_ylim() |
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| 189 | lo,hi = _rescale(lo,hi,step,bal=ydata,scale=ax.get_yscale()) |
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| 190 | ax.set_ylim((lo,hi)) |
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| 191 | |
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| 192 | self.canvas.draw_idle() |
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| 193 | |
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| 194 | |
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| 195 | def returnTrans(self): |
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| 196 | """ |
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| 197 | Return values and labels used by Fit Dialog |
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| 198 | """ |
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| 199 | return self.xLabel,self.yLabel, self.Avalue, self.Bvalue,\ |
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| 200 | self.ErrAvalue,self.ErrBvalue,self.Chivalue |
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| 201 | |
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| 202 | def setTrans(self,xtrans,ytrans): |
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| 203 | """ |
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| 204 | @param xtrans: set x transformation on Property dialog |
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| 205 | @param ytrans: set y transformation on Property dialog |
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| 206 | """ |
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| 207 | self.prevXtrans =xtrans |
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| 208 | self.prevYtrans =ytrans |
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| 209 | |
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| 210 | def onFitting(self, event): |
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| 211 | """ |
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| 212 | when clicking on linear Fit on context menu , display Fitting Dialog |
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| 213 | """ |
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| 214 | list =[] |
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| 215 | list = self.graph.returnPlottable() |
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| 216 | from fitDialog import LinearFit |
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| 217 | |
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| 218 | if len(list.keys())>0: |
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| 219 | first_item = list.keys()[0] |
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| 220 | dlg = LinearFit( None, first_item, self.onFitDisplay,self.returnTrans, -1, 'Fitting') |
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| 221 | |
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| 222 | if (self.xmin !=0.0 )and ( self.xmax !=0.0)\ |
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| 223 | and(self.xminView !=0.0 )and ( self.xmaxView !=0.0): |
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| 224 | dlg.setFitRange(self.xminView,self.xmaxView,self.xmin,self.xmax) |
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| 225 | dlg.ShowModal() |
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| 226 | |
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| 227 | def _onProperties(self, event): |
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| 228 | """ |
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| 229 | when clicking on Properties on context menu ,The Property dialog is displayed |
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| 230 | The user selects a transformation for x or y value and a new plot is displayed |
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| 231 | """ |
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| 232 | list =[] |
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| 233 | list = self.graph.returnPlottable() |
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| 234 | if len(list.keys())>0: |
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| 235 | first_item = list.keys()[0] |
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| 236 | if first_item.x !=[]: |
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| 237 | from PropertyDialog import Properties |
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| 238 | dial = Properties(self, -1, 'Properties') |
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| 239 | dial.setValues( self.prevXtrans, self.prevYtrans,self.viewModel ) |
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| 240 | if dial.ShowModal() == wx.ID_OK: |
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| 241 | self.xLabel, self.yLabel,self.viewModel = dial.getValues() |
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| 242 | if self.viewModel =="Guinier lny vs x^(2)": |
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| 243 | self.xLabel="x^(2)" |
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| 244 | self.yLabel="ln(y)" |
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| 245 | self.viewModel = "--" |
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| 246 | dial.setValues( self.xLabel, self.yLabel,self.viewModel ) |
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| 247 | self._onEVT_FUNC_PROPERTY() |
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| 248 | dial.Destroy() |
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| 249 | |
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| 250 | |
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| 251 | def set_yscale(self, scale='linear'): |
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| 252 | """ |
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| 253 | Set the scale on Y-axis |
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| 254 | @param scale: the scale of y-axis |
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| 255 | """ |
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| 256 | self.subplot.set_yscale(scale) |
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| 257 | self.yscale = scale |
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| 258 | |
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| 259 | def get_yscale(self): |
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| 260 | """ |
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| 261 | @return: Y-axis scale |
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| 262 | """ |
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| 263 | return self.yscale |
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| 264 | |
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| 265 | def set_xscale(self, scale='linear'): |
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| 266 | """ |
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| 267 | Set the scale on x-axis |
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| 268 | @param scale: the scale of x-axis |
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| 269 | """ |
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| 270 | self.subplot.set_xscale(scale) |
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| 271 | self.xscale = scale |
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| 272 | |
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| 273 | def get_xscale(self): |
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| 274 | """ |
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| 275 | @return: x-axis scale |
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| 276 | """ |
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| 277 | return self.xscale |
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| 278 | |
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| 279 | def SetColor(self, rgbtuple): |
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| 280 | """Set figure and canvas colours to be the same""" |
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| 281 | if not rgbtuple: |
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| 282 | rgbtuple = wx.SystemSettings.GetColour(wx.SYS_COLOUR_BTNFACE).Get() |
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| 283 | col = [c/255.0 for c in rgbtuple] |
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| 284 | self.figure.set_facecolor(col) |
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| 285 | self.figure.set_edgecolor(col) |
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| 286 | self.canvas.SetBackgroundColour(wx.Colour(*rgbtuple)) |
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| 287 | |
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| 288 | def _onSize(self, event): |
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| 289 | self._resizeflag = True |
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| 290 | |
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| 291 | def _onIdle(self, evt): |
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| 292 | if self._resizeflag: |
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| 293 | self._resizeflag = False |
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| 294 | self._SetSize() |
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| 295 | self.draw() |
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| 296 | |
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| 297 | def _SetSize(self, pixels = None): |
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| 298 | """ |
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| 299 | This method can be called to force the Plot to be a desired size, which defaults to |
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| 300 | the ClientSize of the panel |
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| 301 | """ |
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| 302 | if not pixels: |
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| 303 | pixels = self.GetClientSize() |
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| 304 | self.canvas.SetSize(pixels) |
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| 305 | self.figure.set_size_inches(pixels[0]/self.figure.get_dpi(), |
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| 306 | pixels[1]/self.figure.get_dpi()) |
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| 307 | |
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| 308 | def draw(self): |
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| 309 | """Where the actual drawing happens""" |
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| 310 | self.figure.canvas.draw_idle() |
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| 311 | |
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| 312 | |
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| 313 | |
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| 314 | |
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| 315 | |
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| 316 | def onSaveImage(self, evt): |
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| 317 | #figure.savefig |
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| 318 | #print "Save image not implemented" |
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| 319 | path = None |
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| 320 | dlg = wx.FileDialog(self, "Choose a file", os.getcwd(), "", "*.png", wx.SAVE) |
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| 321 | if dlg.ShowModal() == wx.ID_OK: |
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| 322 | path = dlg.GetPath() |
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| 323 | mypath = os.path.basename(path) |
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| 324 | print path |
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| 325 | dlg.Destroy() |
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| 326 | if not path == None: |
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| 327 | self.subplot.figure.savefig(path,dpi=300, facecolor='w', edgecolor='w', |
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| 328 | orentation='portrait', papertype=None, format='png') |
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| 329 | |
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| 330 | def onContextMenu(self, event): |
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| 331 | """ |
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| 332 | Default context menu for a plot panel |
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| 333 | """ |
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| 334 | # Slicer plot popup menu |
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| 335 | slicerpop = wx.Menu() |
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| 336 | slicerpop.Append(313,'&Save image', 'Save image as PNG') |
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| 337 | wx.EVT_MENU(self, 313, self.onSaveImage) |
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| 338 | |
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| 339 | slicerpop.Append(316, '&Load 1D data file') |
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| 340 | wx.EVT_MENU(self, 316, self._onLoad1DData) |
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| 341 | |
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| 342 | slicerpop.AppendSeparator() |
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| 343 | slicerpop.Append(315, '&Properties') |
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| 344 | wx.EVT_MENU(self, 315, self._onProperties) |
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| 345 | |
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| 346 | slicerpop.AppendSeparator() |
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| 347 | slicerpop.Append(317, '&Linear Fit') |
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| 348 | wx.EVT_MENU(self, 317, self.onFitting) |
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| 349 | |
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| 350 | slicerpop.AppendSeparator() |
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| 351 | slicerpop.Append(318, '&Reset Graph') |
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| 352 | wx.EVT_MENU(self, 318, self.onResetGraph) |
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| 353 | |
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| 354 | pos = event.GetPosition() |
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| 355 | pos = self.ScreenToClient(pos) |
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| 356 | self.PopupMenu(slicerpop, pos) |
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| 357 | |
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| 358 | ## The following is plottable functionality |
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| 359 | |
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| 360 | |
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| 361 | def properties(self,prop): |
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| 362 | """Set some properties of the graph. |
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| 363 | |
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| 364 | The set of properties is not yet determined. |
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| 365 | """ |
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| 366 | # The particulars of how they are stored and manipulated (e.g., do |
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| 367 | # we want an inventory internally) is not settled. I've used a |
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| 368 | # property dictionary for now. |
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| 369 | # |
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| 370 | # How these properties interact with a user defined style file is |
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| 371 | # even less clear. |
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| 372 | |
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| 373 | # Properties defined by plot |
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| 374 | self.subplot.set_xlabel(r"$%s$" % prop["xlabel"]) |
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| 375 | self.subplot.set_ylabel(r"$%s$" % prop["ylabel"]) |
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| 376 | self.subplot.set_title(prop["title"]) |
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| 377 | |
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| 378 | # Properties defined by user |
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| 379 | #self.axes.grid(True) |
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| 380 | |
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| 381 | def clear(self): |
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| 382 | """Reset the plot""" |
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| 383 | |
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| 384 | # TODO: Redraw is brutal. Render to a backing store and swap in |
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| 385 | # TODO: rather than redrawing on the fly. |
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| 386 | self.subplot.clear() |
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| 387 | self.subplot.hold(True) |
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| 388 | |
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| 389 | def render(self): |
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| 390 | """Commit the plot after all objects are drawn""" |
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| 391 | # TODO: this is when the backing store should be swapped in. |
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| 392 | from matplotlib.font_manager import FontProperties |
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| 393 | self.subplot.legend(prop=FontProperties(size=10)) |
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| 394 | #self.subplot.legend() |
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| 395 | pass |
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| 396 | |
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| 397 | def xaxis(self,label,units): |
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| 398 | """xaxis label and units. |
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| 399 | |
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| 400 | Axis labels know about units. |
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| 401 | |
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| 402 | We need to do this so that we can detect when axes are not |
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| 403 | commesurate. Currently this is ignored other than for formatting |
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| 404 | purposes. |
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| 405 | """ |
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| 406 | if units != "": label = label + " (" + units + ")" |
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| 407 | self.subplot.set_xlabel(label) |
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| 408 | pass |
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| 409 | |
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| 410 | def yaxis(self,label,units): |
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| 411 | """yaxis label and units.""" |
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| 412 | if units != "": label = label + " (" + units + ")" |
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| 413 | self.subplot.set_ylabel(label) |
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| 414 | pass |
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| 415 | |
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| 416 | def _connect_to_xlim(self,callback): |
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| 417 | """Bind the xlim change notification to the callback""" |
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| 418 | def process_xlim(axes): |
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| 419 | lo,hi = subplot.get_xlim() |
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| 420 | callback(lo,hi) |
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| 421 | self.subplot.callbacks.connect('xlim_changed',process_xlim) |
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| 422 | |
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| 423 | #def connect(self,trigger,callback): |
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| 424 | # print "PlotPanel.connect???" |
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| 425 | # if trigger == 'xlim': self._connect_to_xlim(callback) |
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| 426 | |
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| 427 | def points(self,x,y,dx=None,dy=None,color=0,symbol=0,label=None): |
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| 428 | """Draw markers with error bars""" |
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| 429 | self.subplot.set_yscale('linear') |
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| 430 | self.subplot.set_xscale('linear') |
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| 431 | # Convert tuple (lo,hi) to array [(x-lo),(hi-x)] |
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| 432 | if dx != None and type(dx) == type(()): |
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| 433 | dx = nx.vstack((x-dx[0],dx[1]-x)).transpose() |
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| 434 | if dy != None and type(dy) == type(()): |
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| 435 | dy = nx.vstack((y-dy[0],dy[1]-y)).transpose() |
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| 436 | |
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| 437 | if dx==None and dy==None: |
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| 438 | h = self.subplot.plot(x,y,color=self._color(color), |
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| 439 | marker=self._symbol(symbol),linestyle='',label=label) |
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| 440 | else: |
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| 441 | self.subplot.errorbar(x, y, yerr=dy, xerr=None, |
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| 442 | ecolor=self._color(color), capsize=2,linestyle='', barsabove=False, |
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| 443 | marker=self._symbol(symbol), |
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| 444 | lolims=False, uplims=False, |
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| 445 | xlolims=False, xuplims=False,label=label) |
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| 446 | |
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| 447 | self.subplot.set_yscale(self.yscale) |
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| 448 | self.subplot.set_xscale(self.xscale) |
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| 449 | |
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| 450 | def curve(self,x,y,dy=None,color=0,symbol=0,label=None): |
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| 451 | """Draw a line on a graph, possibly with confidence intervals.""" |
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| 452 | c = self._color(color) |
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| 453 | self.subplot.set_yscale('linear') |
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| 454 | self.subplot.set_xscale('linear') |
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| 455 | |
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| 456 | hlist = self.subplot.plot(x,y,color=c,marker='',linestyle='-',label=label) |
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| 457 | |
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| 458 | self.subplot.set_yscale(self.yscale) |
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| 459 | self.subplot.set_xscale(self.xscale) |
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| 460 | |
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| 461 | def _color(self,c): |
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| 462 | """Return a particular colour""" |
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| 463 | return self.colorlist[c%len(self.colorlist)] |
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| 464 | |
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| 465 | def _symbol(self,s): |
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| 466 | """Return a particular symbol""" |
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| 467 | return self.symbollist[s%len(self.symbollist)] |
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| 468 | |
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| 469 | def _onEVT_FUNC_PROPERTY(self): |
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| 470 | """ |
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| 471 | Receive the x and y transformation from myDialog,Transforms x and y in View |
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| 472 | and set the scale |
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| 473 | """ |
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| 474 | list =[] |
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| 475 | list = self.graph.returnPlottable() |
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| 476 | self.fit_result.x =[] |
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| 477 | self.fit_result.y =[] |
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| 478 | self.fit_result.dx=None |
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| 479 | self.fit_result.dy=None |
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| 480 | |
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| 481 | for item in list: |
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| 482 | item.setLabel(self.xLabel,self.yLabel) |
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| 483 | if ( self.xLabel=="x" ): |
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| 484 | item.transformX(transform.toX,transform.errToX) |
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| 485 | self.set_xscale("linear") |
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| 486 | name, units = item.get_xaxis() |
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| 487 | self.graph.xaxis("%s" % name, "%s^{-1}" % units) |
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| 488 | |
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| 489 | if ( self.xLabel=="x^(2)" ): |
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| 490 | item.transformX(transform.toX2,transform.errToX2) |
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| 491 | self.set_xscale('linear') |
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| 492 | name, units = item.get_xaxis() |
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| 493 | self.graph.xaxis("%s^{2}" % name, "%s^{-2}" % units) |
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| 494 | |
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| 495 | if (self.xLabel=="log10(x)" ): |
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| 496 | item.transformX(transform.toX,transform.errToX) |
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| 497 | self.set_xscale("log") |
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| 498 | name, units = item.get_xaxis() |
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| 499 | self.graph.xaxis("\log_{10}\ \ %s" % name, "%s^{-1}" % units) |
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| 500 | |
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| 501 | if ( self.yLabel=="ln(y)" ): |
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| 502 | item.transformY(transform.toLogX,transform.errToLogX) |
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| 503 | self.set_yscale("linear") |
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| 504 | name, units = item.get_yaxis() |
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| 505 | self.graph.yaxis("log\ \ %s" % name, "%s^{-1}" % units) |
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| 506 | |
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| 507 | if ( self.yLabel=="y" ): |
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| 508 | item.transformY(transform.toX,transform.errToX) |
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| 509 | self.set_yscale("linear") |
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| 510 | name, units = item.get_yaxis() |
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| 511 | self.graph.yaxis("%s" % name, "%s^{-1}" % units) |
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| 512 | |
|---|
| 513 | if ( self.yLabel=="log10(y)" ): |
|---|
| 514 | item.transformY(transform.toX,transform.errToX) |
|---|
| 515 | self.set_yscale("log") |
|---|
| 516 | name, units = item.get_yaxis() |
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| 517 | self.graph.yaxis("\log_{10}\ \ %s" % name, "%s^{-1}" % units) |
|---|
| 518 | |
|---|
| 519 | if ( self.yLabel=="y^(2)" ): |
|---|
| 520 | item.transformY( transform.toX2,transform.errToX2 ) |
|---|
| 521 | self.set_yscale("linear") |
|---|
| 522 | name, units = item.get_yaxis() |
|---|
| 523 | self.graph.yaxis("%s^{2}" % name, "%s^{-2}" % units) |
|---|
| 524 | |
|---|
| 525 | if ( self.yLabel =="1/y"): |
|---|
| 526 | item.transformY(transform.toOneOverX,transform.errOneOverX ) |
|---|
| 527 | self.set_yscale("linear") |
|---|
| 528 | name, units = item.get_yaxis() |
|---|
| 529 | self.graph.yaxis("%s" % name, "\ \%s" % units) |
|---|
| 530 | |
|---|
| 531 | if ( self.yLabel =="1/sqrt(y)" ): |
|---|
| 532 | item.transformY(transform.toOneOverSqrtX,transform.errOneOverSqrtX ) |
|---|
| 533 | self.set_yscale("linear") |
|---|
| 534 | name, units = item.get_yaxis() |
|---|
| 535 | self.graph.yaxis("\sqrt{%s}" %name, "%s" % units) |
|---|
| 536 | |
|---|
| 537 | if ( self.yLabel =="ln(y*x)"): |
|---|
| 538 | item.transformY( transform.toLogXY,transform.errToLogXY) |
|---|
| 539 | self.set_yscale("linear") |
|---|
| 540 | yname, yunits = item.get_yaxis() |
|---|
| 541 | xname, xunits = item.get_xaxis() |
|---|
| 542 | self.graph.yaxis("log\ %s %s" % (yname,xname), "%s^{-1}%s^{-1}" % (yunits,xunits)) |
|---|
| 543 | |
|---|
| 544 | if ( self.yLabel =="ln(y*x^(2))"): |
|---|
| 545 | item.transformY( transform.toLogYX2,transform.errToLogYX2) |
|---|
| 546 | self.set_yscale("linear") |
|---|
| 547 | yname, yunits = item.get_yaxis() |
|---|
| 548 | xname, xunits = item.get_xaxis() |
|---|
| 549 | self.graph.yaxis("Log %s%s^{2}" % (yname,xname), "%s^{-1}%s^{-2}" % (yunits,xunits)) |
|---|
| 550 | |
|---|
| 551 | if ( self.yLabel =="ln(y*x^(4))"): |
|---|
| 552 | item.transformY(transform.toLogYX4,transform.errToLogYX4) |
|---|
| 553 | self.set_yscale("linear") |
|---|
| 554 | yname, yunits = item.get_yaxis() |
|---|
| 555 | xname, xunits = item.get_xaxis() |
|---|
| 556 | self.graph.yaxis("Log %s%s^{4}" % (yname,xname), "%s^{-1}%s^{-4}" % (yunits,xunits)) |
|---|
| 557 | |
|---|
| 558 | if ( self.viewModel == "Guinier lny vs x^(2)"): |
|---|
| 559 | |
|---|
| 560 | item.transformX(transform.toX2,transform.errToX2) |
|---|
| 561 | self.set_xscale('linear') |
|---|
| 562 | name, units = item.get_xaxis() |
|---|
| 563 | self.graph.xaxis("%s^{2}" % name, "%s^{-2}" % units) |
|---|
| 564 | |
|---|
| 565 | item.transformY(transform.toLogX,transform.errToLogX ) |
|---|
| 566 | self.set_yscale("linear") |
|---|
| 567 | name, units = item.get_yaxis() |
|---|
| 568 | self.graph.yaxis("$Log %s$" % name, "%s^{-1}" % units) |
|---|
| 569 | |
|---|
| 570 | item.transformView() |
|---|
| 571 | |
|---|
| 572 | #item.name = self.yLabel+" vs " +self.xLabel |
|---|
| 573 | self.resetFitView() |
|---|
| 574 | self.prevXtrans = self.xLabel |
|---|
| 575 | self.prevYtrans = self.yLabel |
|---|
| 576 | self.graph.render(self) |
|---|
| 577 | self.subplot.figure.canvas.draw_idle() |
|---|
| 578 | |
|---|
| 579 | def onFitDisplay(self, tempx,tempy,xminView,xmaxView,xmin,xmax,func): |
|---|
| 580 | """ |
|---|
| 581 | Add a new plottable into the graph .In this case this plottable will be used |
|---|
| 582 | to fit some data |
|---|
| 583 | @param tempx: The x data of fit line |
|---|
| 584 | @param tempy: The y data of fit line |
|---|
| 585 | @param xminView: the lower bound of fitting range |
|---|
| 586 | @param xminView: the upper bound of fitting range |
|---|
| 587 | @param xmin: the lowest value of data to fit to the line |
|---|
| 588 | @param xmax: the highest value of data to fit to the line |
|---|
| 589 | """ |
|---|
| 590 | # Saving value to redisplay in Fit Dialog when it is opened again |
|---|
| 591 | self.Avalue,self.Bvalue,self.ErrAvalue,self.ErrBvalue,self.Chivalue=func |
|---|
| 592 | self.xminView=xminView |
|---|
| 593 | self.xmaxView=xmaxView |
|---|
| 594 | self.xmin= xmin |
|---|
| 595 | self.xmax= xmax |
|---|
| 596 | #In case need to change the range of data plotted |
|---|
| 597 | list =[] |
|---|
| 598 | list = self.graph.returnPlottable() |
|---|
| 599 | for item in list: |
|---|
| 600 | #item.onFitRange(xminView,xmaxView) |
|---|
| 601 | item.onFitRange(None,None) |
|---|
| 602 | |
|---|
| 603 | # Create new data plottable with result |
|---|
| 604 | self.fit_result.x =[] |
|---|
| 605 | self.fit_result.y =[] |
|---|
| 606 | self.fit_result.x =tempx |
|---|
| 607 | self.fit_result.y =tempy |
|---|
| 608 | self.fit_result.dx=None |
|---|
| 609 | self.fit_result.dy=None |
|---|
| 610 | #Load the view with the new values |
|---|
| 611 | self.fit_result.reset_view() |
|---|
| 612 | # Add the new plottable to the graph |
|---|
| 613 | self.graph.add(self.fit_result) |
|---|
| 614 | self.graph.render(self) |
|---|
| 615 | self.subplot.figure.canvas.draw_idle() |
|---|
| 616 | |
|---|
| 617 | |
|---|
| 618 | def onResetGraph(self,event): |
|---|
| 619 | """ |
|---|
| 620 | Reset the graph by plotting the full range of data |
|---|
| 621 | """ |
|---|
| 622 | list =[] |
|---|
| 623 | list = self.graph.returnPlottable() |
|---|
| 624 | for item in list: |
|---|
| 625 | item.onReset() |
|---|
| 626 | self.graph.render(self) |
|---|
| 627 | self.subplot.figure.canvas.draw_idle() |
|---|
| 628 | |
|---|
| 629 | class NoRepaintCanvas(FigureCanvasWxAgg): |
|---|
| 630 | """We subclass FigureCanvasWxAgg, overriding the _onPaint method, so that |
|---|
| 631 | the draw method is only called for the first two paint events. After that, |
|---|
| 632 | the canvas will only be redrawn when it is resized. |
|---|
| 633 | """ |
|---|
| 634 | def __init__(self, *args, **kwargs): |
|---|
| 635 | FigureCanvasWxAgg.__init__(self, *args, **kwargs) |
|---|
| 636 | self._drawn = 0 |
|---|
| 637 | |
|---|
| 638 | def _onPaint(self, evt): |
|---|
| 639 | """ |
|---|
| 640 | Called when wxPaintEvt is generated |
|---|
| 641 | """ |
|---|
| 642 | if not self._isRealized: |
|---|
| 643 | self.realize() |
|---|
| 644 | if self._drawn < 2: |
|---|
| 645 | self.draw(repaint = False) |
|---|
| 646 | self._drawn += 1 |
|---|
| 647 | self.gui_repaint(drawDC=wx.PaintDC(self)) |
|---|
| 648 | |
|---|
