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)