def _create_plot_component():
# Create some data
index, vals = _create_data(20)
# Create a plot data object and give it this data
pd = ArrayPlotData(index = index,
values = vals)
# Create the plot
plot = Plot(pd)
plot.stacked_bar_plot(("index", "values"),
color = ["red", "yellow", "green", "blue"],
outline_color = "lightgray",)
# Tweak some of the plot properties
plot.title = "Stacked Bar Plot"
plot.line_width = 0.5
plot.padding = 50
# Attach some tools to the plot
plot.tools.append(PanTool(plot, constrain_key="shift"))
zoom = ZoomTool(component=plot, tool_mode="box", always_on=False)
plot.overlays.append(zoom)
return plot
def _create_plot_component(self, recalc=False):
container = VPlotContainer()
### Assemble the scatter plot of the Efficient Frontier
x, y = self.get_stock_data()
if not hasattr(self, "efx") or recalc:
efx, efy, allocations = self.get_ef_data()
else:
efx = self.efx
efy = self.efy
p = self.portfolio
symbs = p.symbols
pd = ArrayPlotData(x=x, y=y, efx=efx, efy=efy, mp_x=[self.model_portfolio_x], mp_y=[self.model_portfolio_y])
# Create some plots of the data
plot = Plot(pd, title="Efficient Frontier")
# Create a scatter plot (and keep a handle on it)
stockplt = plot.plot(("x", "y"), color="transparent",
type="scatter",
marker="dot",
marker_line_color="transparent",
marker_color="transparent",
marker_size=1)[0]
efplt = plot.plot(("efx", "efy"), color=(0.0,0.5,0.0,0.25),
type="scatter",
marker="circle",
marker_size=6)[0]
efpltline = plot.plot(("efx", "efy"), color=(0.1,0.4,0.1,0.7),
type="line")[0]
# Create another one-point scatter for a model portfolio
mp_plot = plot.plot(("mp_x", "mp_y"), color=(1.0, 0.5, 0.5, 0.25),
type="scatter",
market="triangle",
market_size=7)[0]
for i in range(len(p.stocks)):
label = DataPointLabel(component=plot, data_point=(x[i], y[i]),
label_position="bottom right",
padding=4,
bgcolor="transparent",
border_visible=False,
text=self.symbols[i],
marker="circle",
marker_color=(0.0,0.0,0.5,0.25),
marker_line_color="lightgray",
marker_size=6,
arrow_size=8.0,
arrow_min_length=7.0,
font_size=14)
plot.overlays.append(label)
tool = DataLabelTool(label, drag_button="left", auto_arrow_root=True)
label.tools.append(tool)
stockplt.tools.append(ScatterInspector(stockplt, selection_mode="toggle",
persistent_hover=False))
scatinsp = ScatterInspectorOverlay(stockplt,
hover_color = "red",
hover_marker_size = 8,
hover_outline_color = (0.7, 0.7, 0.7, 0.5),
hover_line_width = 1)
stockplt.overlays.append(scatinsp)
# Tweak some of the plot properties
plot.padding = 50
stockplt.value_range.low=0.0
stockplt.value_range.high=0.1
stockplt.index_range.low=0.0
stockplt.index_range.high=0.1
# Attach some tools to the plot
plot.tools.append(PanTool(plot, drag_button="right"))
plot.overlays.append(ZoomTool(plot))
#### Assemble the "stacked area" plot
if not hasattr(self, "efx") or recalc:
a = self.get_ef_data()[2]
else:
a = self.allocations
rts = a.keys()
rts.sort()
rts = np.array(rts)
symbs = a[rts[0]].keys()
symbs.sort()
# "Transpose" symbols' weights to get vectors of weights for each symbol
symb_data = np.array([[a[rt][symb] for rt in rts] for symb in symbs])
self.symbols2 = [Symbol(symbol=symbs[i], color=COLORS[i]) for i in range(len(symbs))]
# Create a plot data object and give it this data
bpd = ArrayPlotData()
bpd.set_data("index", rts)
bpd.set_data("allocations", symb_data)
# Create a contour polygon plot of the data
bplot = Plot(bpd, title="Allocations")
bplot.stacked_bar_plot(("index", "allocations"),
color = COLORS,
outline_color = "gray")
bplot.padding = 50
#bplot.legend.visible = True
# Add a plot of the stocks
stock_obj_list = [p.stocks[symb] for symb in symbs]
#for itm in stock_obj_list:
#itm.print_traits()
#print "Has Cache?:", itm.stock_data_cache is not None
splot = StockPlot(stocks=[p.stocks[symb] for symb in symbs], colors=COLORS).plot
container.add(bplot)
container.add(plot)
container.add(splot)
return container
