def __init__(self, link):
super(TrackingView, self).__init__()
self.link = link
self.link.add_callback(MSG_TRACKING_SNRS, self.tracking_snrs_callback)
# ======= Line Plot =======
self.plot_data = ArrayPlotData(t=[0.0])
self.plot = Plot(self.plot_data, auto_colors=colours_list)
self.plot.value_range.tight_bounds = False
self.plot.value_range.low_setting = 0.0
for n in range(TRACK_N_CHANNELS):
self.plot_data.set_data('ch'+str(n), [0.0])
self.plot.plot(('t', 'ch'+str(n)), type='line', color='auto')
# ======= Bar Plot =======
idxs = ArrayDataSource(range(1, len(self.snrs)+1))
self.vals = ArrayDataSource(self.snrs, sort_order='none')
# Create the index range
index_range = DataRange1D(idxs, low=0.4, high=TRACK_N_CHANNELS+0.6)
index_mapper = LinearMapper(range=index_range)
# Create the value range
value_range = DataRange1D(low=0.0, high=25.0)
value_mapper = LinearMapper(range=value_range)
plot = BarPlot(index=idxs, value=self.vals,
index_mapper=index_mapper, value_mapper=value_mapper,
line_color='blue', fill_color='blue', bar_width=0.8)
container = OverlayPlotContainer(bgcolor = "white")
plot.padding = 10
plot.padding_left = 30
plot.padding_bottom = 30
container.add(plot)
left_axis = PlotAxis(plot, orientation='left')
bottom_axis = LabelAxis(plot, orientation='bottom',
labels = map(str, range(1, TRACK_N_CHANNELS+1)),
positions = range(1, TRACK_N_CHANNELS+1),
small_haxis_style=True)
plot.underlays.append(left_axis)
plot.underlays.append(bottom_axis)
self.snr_bars = container
self.python_console_cmds = {
'track': self
}
def _create_plot(self):
# count data
if len(self.df) > 0:
self.indexes = np.arange(len(self.df.date_time))
time_ds = ArrayDataSource(self.indexes)
vol_ds = ArrayDataSource(self.df.volumn.values, sort_order="none")
xmapper = LinearMapper(range=DataRange1D(time_ds))
vol_mapper = LinearMapper(range=DataRange1D(vol_ds))
####################################################################
# create volumn plot
vol_plot = BarPlot(index=time_ds, value=vol_ds,
index_mapper=xmapper,
value_mapper=vol_mapper,
line_color="transparent",
fill_color="blue",
bar_width=0.6,
antialias=False,
height=100,
resizable="h",
origin="bottom left",
bgcolor="white",
border_visible=True
)
vol_plot.padding = 30
vol_plot.padding_left = 40
vol_plot.tools.append(
PanTool(vol_plot, constrain=True, constrain_direction="x"))
add_default_grids(vol_plot)
add_default_axes(vol_plot)
#print vol_plot.index_mapper.range.high
#print vol_plot.value_mapper.range.low, vol_plot.value_mapper.range.high
self.vol_plot = vol_plot
self.container.add(vol_plot)
####################################################################
## Create price plot
sorted_vals = np.vstack(
(self.df.open, self.df.high, self.df.low, self.df.close))
sorted_vals.sort(0)
__bool = self.df.close.values - self.df.open.values
self.up_boolean = __bool >= 0
self.down_boolean = np.invert(self.up_boolean)
pd = ArrayPlotData(
up_index=self.indexes[self.up_boolean],
up_min=sorted_vals[0][self.up_boolean],
up_bar_min=sorted_vals[1][self.up_boolean],
up_bar_max=sorted_vals[2][self.up_boolean],
up_max=sorted_vals[3][self.up_boolean],
down_index=self.indexes[self.down_boolean],
down_min=sorted_vals[0][self.down_boolean],
down_bar_min=sorted_vals[1][self.down_boolean],
down_bar_max=sorted_vals[2][self.down_boolean],
down_max=sorted_vals[3][self.down_boolean],
volumn=self.df.volumn.values,
index=self.indexes
)
price_plot = Plot(pd)
up_plot = price_plot.candle_plot(
("up_index", "up_min", "up_bar_min", "up_bar_max", "up_max"),
color=color_red,
bgcolor="azure",
bar_line_color="black",
stem_color="black",
end_cap=False)[0]
down_plot = price_plot.candle_plot(
("down_index", "down_min", "down_bar_min",
"down_bar_max", "down_max"),
color=color_green,
bar_line_color="black",
stem_color="black",
end_cap=False)[0]
price_plot.fill_padding = True
price_plot.padding = 30
price_plot.padding_left = 40
price_plot.tools.append(ZoomTool(component=price_plot, tool_mode="box", zoom_factor=1.2, always_on=False))
price_plot.tools.append(PanTool(price_plot, drag_button="left"))
price_plot.tools.append(
XYTool(price_plot, callback=self._update_ohlc)) # get data
self._add_line_tool(up_plot)
self._add_line_tool(down_plot)
price_plot.range2d = self._compute_range2d()
price_plot.index_mapper = vol_plot.index_mapper # maper vol_plot and price_plot
self.price_plot = price_plot
self.container.add(price_plot)
def _create_plot(self):
# count data
if len(self.df) > 0:
self.indexes = np.arange(len(self.df.date_time))
time_ds = ArrayDataSource(self.indexes)
vol_ds = ArrayDataSource(self.df.volumn.values, sort_order="none")
xmapper = LinearMapper(range=DataRange1D(time_ds))
vol_mapper = LinearMapper(range=DataRange1D(vol_ds))
####################################################################
# create volumn plot
vol_plot = BarPlot(
index=time_ds,
value=vol_ds,
index_mapper=xmapper,
value_mapper=vol_mapper,
line_color="transparent",
fill_color="blue",
bar_width=0.6,
antialias=False,
height=100,
resizable="h",
origin="bottom left",
bgcolor="white",
border_visible=True,
)
vol_plot.padding = 30
vol_plot.padding_left = 40
vol_plot.tools.append(PanTool(vol_plot, constrain=True, constrain_direction="x"))
add_default_grids(vol_plot)
add_default_axes(vol_plot)
# print vol_plot.index_mapper.range.high
# print vol_plot.value_mapper.range.low, vol_plot.value_mapper.range.high
self.vol_plot = vol_plot
self.container.add(vol_plot)
####################################################################
## Create price plot
sorted_vals = np.vstack((self.df.open, self.df.high, self.df.low, self.df.close))
sorted_vals.sort(0)
__bool = self.df.close.values - self.df.open.values
self.up_boolean = __bool >= 0
self.down_boolean = np.invert(self.up_boolean)
pd = ArrayPlotData(
up_index=self.indexes[self.up_boolean],
up_min=sorted_vals[0][self.up_boolean],
up_bar_min=sorted_vals[1][self.up_boolean],
up_bar_max=sorted_vals[2][self.up_boolean],
up_max=sorted_vals[3][self.up_boolean],
down_index=self.indexes[self.down_boolean],
down_min=sorted_vals[0][self.down_boolean],
down_bar_min=sorted_vals[1][self.down_boolean],
down_bar_max=sorted_vals[2][self.down_boolean],
down_max=sorted_vals[3][self.down_boolean],
volumn=self.df.volumn.values,
index=self.indexes,
)
price_plot = Plot(pd)
up_plot = price_plot.candle_plot(
("up_index", "up_min", "up_bar_min", "up_bar_max", "up_max"),
color=color_red,
bgcolor="azure",
bar_line_color="black",
stem_color="black",
end_cap=False,
)[0]
down_plot = price_plot.candle_plot(
("down_index", "down_min", "down_bar_min", "down_bar_max", "down_max"),
color=color_green,
bar_line_color="black",
stem_color="black",
end_cap=False,
)[0]
price_plot.fill_padding = True
price_plot.padding = 30
price_plot.padding_left = 40
price_plot.tools.append(ZoomTool(component=price_plot, tool_mode="box", zoom_factor=1.2, always_on=False))
price_plot.tools.append(PanTool(price_plot, drag_button="left"))
price_plot.tools.append(XYTool(price_plot, callback=self._update_ohlc)) # get data
self._add_line_tool(up_plot)
self._add_line_tool(down_plot)
price_plot.range2d = self._compute_range2d()
price_plot.index_mapper = vol_plot.index_mapper # maper vol_plot and price_plot
self.price_plot = price_plot
self.container.add(price_plot)
