def make_plot(self, orientation):
# make some data points
x = arange(3)
x = ArrayDataSource(x, sort_order="ascending")
y = array([2, 0, 1])
# Plot the data
pd = ArrayPlotData(x=x, y=y)
plot = Plot(pd, orientation=orientation)
line_plot = plot.plot(("x", "y"))[0]
# Construct a fake screen space for the plots
# otherwise would need to actually display the plots to get this
index_mapper = LinearMapper(data_range=DataRange1D(low=0, high=2),
high_pos=380,
low_pos=20)
value_mapper = LinearMapper(data_range=DataRange1D(low=0, high=2),
high_pos=380,
low_pos=20)
plot.index_mapper = index_mapper
plot.value_mapper = value_mapper
line_plot.index_mapper = index_mapper
line_plot.value_mapper = value_mapper
return plot, line_plot
def make_plot(self, orientation):
# make some data points
x = arange(3)
x = ArrayDataSource(x, sort_order="ascending")
y = array([2,0,1])
# Plot the data
pd = ArrayPlotData(x=x, y=y)
plot = Plot(pd, orientation=orientation)
line_plot = plot.plot(("x", "y"))[0]
# Construct a fake screen space for the plots
# otherwise would need to actually display the plots to get this
index_mapper = LinearMapper(data_range=DataRange1D(low=0,high=2),
high_pos=380, low_pos=20)
value_mapper = LinearMapper(data_range=DataRange1D(low=0,high=2),
high_pos=380, low_pos=20)
plot.index_mapper = index_mapper
plot.value_mapper = value_mapper
line_plot.index_mapper = index_mapper
line_plot.value_mapper = value_mapper
return plot, line_plot
def _create_1D1_plot(self):
index = 0
plot0 = Plot(self.plotdata, padding=0)
plot0.padding_left = 5
plot0.padding_bottom = 5
Container = OverlayPlotContainer(padding = 50, fill_padding = True, bgcolor = "lightgray", use_backbuffer=True)
y1 = range(len(self.PCAData.batchs[0].prescores))
points = []
for batch in self.PCAData.batchs:
if (self.active_scores_combobox == "Post Scores"):
x1 = self.PCAData.batchs[index].postscores
else:
x1 = self.PCAData.batchs[index].prescores
if (self.Shape == self.phenotypes[0]):
a = 1
elif (self.Shape == self.phenotypes[1]):
a = batch.number
elif (self.Shape == self.phenotypes[2]):
a = batch.type
else:
a = 0
if (self.Color == self.phenotypes[0]):
b = 0
elif(self.Color == self.phenotypes[1]):
b = batch.number
elif(self.Color == self.phenotypes[2]):
b = batch.type
else:
b = 0
tmarker = shapes[a]
bcolor = self.colors[b]
for i in range(len(x1)):
points.append((x1[i],y1[i]))
plot0 = create_scatter_plot((x1,y1), marker = tmarker, color=getColor(bcolor))
if batch.isSelected:
plot0.alpha = 1
else:
plot0.alpha = 0.2
plot0.bgcolor = "white"
plot0.border_visible = True
if index == 0:
value_mapper = plot0.value_mapper
index_mapper = plot0.index_mapper
add_default_grids(plot0)
add_default_axes(plot0, vtitle='PCA Indices', htitle='PCA Scores')
plot0.index_range.tight_bounds = False
plot0.index_range.refresh()
plot0.value_range.tight_bounds = False
plot0.value_range.refresh()
plot0.tools.append(PanTool(plot0))
zoom = ZoomTool(plot0, tool_mode="box", always_on=False, maintain_aspect_ratio=False)
plot0.overlays.append(zoom)
dragzoom = DragZoom(plot0, drag_button="right", maintain_aspect_ratio=False)
plot0.tools.append(dragzoom)
else:
plot0.value_mapper = value_mapper
value_mapper.range.add(plot0.value)
plot0.index_mapper = index_mapper
index_mapper.range.add(plot0.index)
Container.add(plot0)
index = index +1
self.RightPlot = Container
def _create_1D1_plot(self):
index = 0
plot0 = Plot(self.plotdata, padding=0)
plot0.padding_left = 5
plot0.padding_bottom = 5
Container = OverlayPlotContainer(padding=50,
fill_padding=True,
bgcolor="lightgray",
use_backbuffer=True)
y1 = range(len(self.PCAData.batchs[0].prescores))
points = []
for batch in self.PCAData.batchs:
if (self.active_scores_combobox == "Post Scores"):
x1 = self.PCAData.batchs[index].postscores
else:
x1 = self.PCAData.batchs[index].prescores
'''if (self.Shape == self.phenotypes[0]):
a = 1
elif (self.Shape == self.phenotypes[1]):
a = batch.number
elif (self.Shape == self.phenotypes[2]):
a = batch.type
else:
a = 0
if (self.Color == self.phenotypes[0]):
b = 0
elif(self.Color == self.phenotypes[1]):
b = batch.number
elif(self.Color == self.phenotypes[2]):
b = batch.type
else:
b = 0 '''
a = batch.type
b = batch.number
tmarker = shapes[a]
bcolor = self.colors[b]
for i in range(len(x1)):
points.append((x1[i], y1[i]))
plot0 = create_scatter_plot((x1, y1),
marker=tmarker,
color=getColor(bcolor))
if batch.isSelected:
plot0.alpha = 1
plot0.alpha = 1
else:
plot0.fill_alpha = 0.2
plot0.edge_alpha = 0.2
plot0.bgcolor = "white"
plot0.border_visible = True
if index == 0:
value_mapper = plot0.value_mapper
index_mapper = plot0.index_mapper
add_default_grids(plot0)
add_default_axes(plot0,
vtitle='PCA Indices',
htitle='PCA Scores')
plot0.index_range.tight_bounds = False
plot0.index_range.refresh()
plot0.value_range.tight_bounds = False
plot0.value_range.refresh()
plot0.tools.append(PanTool(plot0))
zoom = ZoomTool(plot0,
tool_mode="box",
always_on=False,
maintain_aspect_ratio=False)
plot0.overlays.append(zoom)
dragzoom = DragZoom(plot0,
drag_button="right",
maintain_aspect_ratio=False)
plot0.tools.append(dragzoom)
else:
plot0.value_mapper = value_mapper
value_mapper.range.add(plot0.value)
plot0.index_mapper = index_mapper
index_mapper.range.add(plot0.index)
if batch.isSelected:
Container.add(plot0)
index = index + 1
self.RightPlot = Container