def _rebuild_plot(self):
container = self.plot
value_range = DataRange1D(low=-1, high=1.0)
index_range = DataRange1D(self.index_ds, high="track", tracking_amount=24 * 3600 * 365)
color_mapper = cmap(range=value_range)
# Remove old plots
container.remove(*container.components)
for val, row in zip(self.value_ds, self.rows):
horizon = HorizonPlot(
index=self.index_ds,
value=val,
index_mapper=LinearMapper(range=index_range, stretch_data=False),
value_mapper=BandedMapper(range=DataRange1D(val)),
color_mapper=cmap(range=DataRange1D(val)), # color_mapper,
negative_bands=False,
)
horizon.tools.append(PanTool(horizon, constrain=True, constrain_direction="x"))
horizon.overlays.append(
PlotLabel(component=horizon, hjustify="right", text=row, overlay_position="outside left")
)
container.add(horizon)
bottom_axis = PlotAxis(
horizon, orientation="bottom", tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem())
)
container.overlays = [bottom_axis]
container.request_redraw()
def _rebuild_plot(self):
container = self.plot
value_range = DataRange1D(low=-1, high=1.)
index_range = DataRange1D(self.index_ds,
high='track',
tracking_amount=24 * 3600 * 365)
color_mapper = cmap(range=value_range)
# Remove old plots
container.remove(*container.components)
for val, row in zip(self.value_ds, self.rows):
horizon = HorizonPlot(
index=self.index_ds,
value=val,
index_mapper=LinearMapper(range=index_range,
stretch_data=False),
value_mapper=BandedMapper(range=DataRange1D(val)),
color_mapper=cmap(range=DataRange1D(val)), #color_mapper,
negative_bands=False,
)
horizon.tools.append(
PanTool(horizon, constrain=True, constrain_direction="x"))
horizon.overlays.append(
PlotLabel(component=horizon,
hjustify='right',
text=row,
overlay_position='outside left'))
container.add(horizon)
bottom_axis = PlotAxis(
horizon,
orientation="bottom",
tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
container.overlays = [bottom_axis]
container.request_redraw()
def _corr_plot_default(self):
diag = self.covar.diagonal()
corr = self.covar / np.sqrt(np.outer(diag, diag))
N = len(diag)
value_range = DataRange1D(low=-1, high=1)
color_mapper = cmap(range=value_range)
index = GridDataSource()
value = ImageData()
mapper = GridMapper(range=DataRange2D(index),
y_low_pos=1.0,
y_high_pos=0.0)
index.set_data(xdata=np.arange(-0.5, N), ydata=np.arange(-0.5, N))
value.set_data(np.flipud(corr))
self.corr_data = value
cmap_plot = CMapImagePlot(index=index,
index_mapper=mapper,
value=value,
value_mapper=color_mapper,
padding=(40, 40, 100, 40))
yaxis = PlotAxis(
cmap_plot,
orientation='left',
tick_interval=1,
tick_label_formatter=lambda x: self.header[int(N - 1 - x)],
tick_generator=ShowAllTickGenerator(positions=np.arange(N)))
xaxis = PlotAxis(
cmap_plot,
orientation='top',
tick_interval=1,
tick_label_formatter=lambda x: self.header[int(x)],
tick_label_alignment='edge',
tick_generator=ShowAllTickGenerator(positions=np.arange(N)))
cmap_plot.overlays.append(yaxis)
cmap_plot.overlays.append(xaxis)
colorbar = ColorBar(
index_mapper=LinearMapper(range=cmap_plot.value_range),
plot=cmap_plot,
orientation='v',
resizable='v',
width=10,
padding=(40, 5, 100, 40))
container = HPlotContainer(bgcolor='transparent')
container.add(cmap_plot)
container.add(colorbar)
return container
def _create_plot_components():
# Create the data and datasource objects
# In order for the date axis to work, the index data points need to
# be in units of seconds since the epoch. This is because we are using
# the CalendarScaleSystem, whose formatters interpret the numerical values
# as seconds since the epoch.
high = 1.
numpoints = 5000
random.seed(1000)
index = create_dates(numpoints)
price = 100 * cumprod(random.lognormal(0.0, 0.04, size=numpoints))
changes = price / price[0] - 1.
index_ds = ArrayDataSource(index)
value_ds = ArrayDataSource(changes, sort_order="none")
value_range = DataRange1D(value_ds, low=-high, high=high)
index_mapper = LinearMapper(range=DataRange1D(index_ds),
stretch_data=False)
horizon = HorizonPlot(
bands=4,
index=index_ds,
value=value_ds,
index_mapper=index_mapper,
value_mapper=BandedMapper(range=DataRange1D(low=0, high=high)),
color_mapper=cmap(range=value_range),
)
horizon.tools.append(
PanTool(horizon, constrain=True, constrain_direction="x"))
axis = PlotAxis(mapper=horizon.value_mapper,
component=horizon,
orientation="left",
tick_label_position="outside")
horizon.overlays.append(axis)
bottom_axis = PlotAxis(
horizon,
orientation="bottom",
tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
horizon.overlays.append(bottom_axis)
filled = FilledLinePlot(
index=index_ds,
value=value_ds,
index_mapper=index_mapper,
value_mapper=LinearMapper(range=value_range, stretch_data=False),
fill_color=(0.81960784, 0.89803922, 0.94117647),
edge_color='transparent',
)
filled.tools.append(
PanTool(filled, constrain=True, constrain_direction="x"))
axis = PlotAxis(mapper=filled.value_mapper,
component=filled,
orientation="left",
tick_label_position="outside")
filled.overlays.append(axis)
grid = PlotGrid(
mapper=filled.value_mapper,
component=filled,
orientation='horizontal',
line_color='lightgray',
line_style="dot",
)
filled.underlays.append(grid)
colormap = horizon.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
orientation='v',
resizable='v',
width=20,
padding=20)
padding = (40, 20, 0, 0)
over1 = HPlotContainer(use_backbuffer=True,
padding=padding,
padding_top=20)
over1.add(filled)
over1.add(colorbar)
over2 = OverlayPlotContainer(padding=padding, padding_bottom=40)
over2.add(horizon)
return over1, over2
def _create_plot_components():
# Create the data and datasource objects
# In order for the date axis to work, the index data points need to
# be in units of seconds since the epoch. This is because we are using
# the CalendarScaleSystem, whose formatters interpret the numerical values
# as seconds since the epoch.
high = 1.
numpoints = 5000
random.seed(1000)
index = create_dates(numpoints)
price = 100*cumprod(random.lognormal(0.0, 0.04, size=numpoints))
changes = price/price[0] - 1.
index_ds = ArrayDataSource(index)
value_ds = ArrayDataSource(changes, sort_order="none")
value_range = DataRange1D(value_ds, low=-high, high=high)
index_mapper = LinearMapper(range=DataRange1D(index_ds), stretch_data=False)
horizon = HorizonPlot(
bands = 4,
index = index_ds,
value = value_ds,
index_mapper = index_mapper,
value_mapper = BandedMapper(range=DataRange1D(low=0, high=high)),
color_mapper = cmap(range=value_range),
)
horizon.tools.append(PanTool(horizon, constrain=True, constrain_direction="x"))
axis = PlotAxis(mapper = horizon.value_mapper, component=horizon, orientation="left",
tick_label_position="outside")
horizon.overlays.append(axis)
bottom_axis = PlotAxis(horizon, orientation="bottom",
tick_generator=ScalesTickGenerator(scale=CalendarScaleSystem()))
horizon.overlays.append(bottom_axis)
filled = FilledLinePlot(
index = index_ds,
value = value_ds,
index_mapper = index_mapper,
value_mapper = LinearMapper(range=value_range, stretch_data=False),
fill_color = (0.81960784, 0.89803922, 0.94117647),
edge_color = 'transparent',
)
filled.tools.append(PanTool(filled, constrain=True, constrain_direction="x"))
axis = PlotAxis(mapper = filled.value_mapper, component=filled, orientation="left",
tick_label_position="outside")
filled.overlays.append(axis)
grid = PlotGrid(mapper = filled.value_mapper, component=filled, orientation='horizontal',
line_color='lightgray', line_style="dot",)
filled.underlays.append(grid)
colormap = horizon.color_mapper
colorbar = ColorBar(index_mapper=LinearMapper(range=colormap.range),
color_mapper=colormap,
orientation='v',
resizable='v',
width=20,
padding=20)
padding = (40, 20, 0, 0)
over1 = HPlotContainer(use_backbuffer=True, padding=padding, padding_top=20)
over1.add(filled)
over1.add(colorbar)
over2 = OverlayPlotContainer(padding = padding, padding_bottom=40)
over2.add(horizon)
return over1, over2
