def _create_plot(self, data, name, type="line"):
p = Plot(self.plot_data)
p.plot(data, name=name, title=name, type=type)
p.tools.append(PanTool(p))
zoom = ZoomTool(component=p, tool_mode="box", always_on=False)
p.overlays.append(zoom)
p.title = name
p.index_scale = "log"
return p
def _create_plot(self, data, name, type="line"):
p = Plot(self.plot_data)
p.plot(data, name=name, title=name, type=type)
p.tools.append(PanTool(p))
zoom = ZoomTool(component=p, tool_mode="box", always_on=False)
p.overlays.append(zoom)
p.title = name
p.index_scale = "log"
return p
def __init__(self, **kw):
super(CorrelationData, self).__init__(**kw)
plot = Plot(self.plotdata)
plot2 = Plot(self.plotdata)
plot.plot(("time", "cr"), type="line", color="blue")
plot2.plot(("lag", "corr"), type="line", color="green")
plot2.plot(("lag", "avg"), type="line", color="red")
plot2.index_scale = 'log'
self.cr_plot = plot
self.corr_plot = plot2
def stairstep_plot(energy, data, data_name):
# Munge the data into a plotable form
x, y = stair_step(energy, data)
# Create a plot data obect and give it this data
pd = ArrayPlotData()
pd.set_data("index", x)
pd.set_data("value", y)
# Create the plot
plot = Plot(pd)
plot.plot(("index", "value"),
type="line",
marker="circle",
index_sort="ascending",
color="red",
marker_size=3,
bgcolor="white")
# Tweak some of the plot properties
plot.title = data_name
plot.line_width = 0.5
plot.padding = 100
plot.x_axis.title = "Energy [MeV]"
plot.x_axis.title_font = "Roman 16"
plot.x_axis.tick_label_font = "Roman 12"
plot.y_axis.title = "Data"
plot.y_axis.title_font = "Roman 16"
plot.y_axis.tick_label_font = "Roman 12"
plot.index_scale = 'log'
plot.value_scale = 'log'
# Attach some tools to the plot
plot.tools.append(PanTool(plot))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
