def _create_plot_component(): # Create some data index, sorted_vals = _create_data(200) # Create a plot data obect and give it this data pd = ArrayPlotData(index = index, min = sorted_vals[0], bar_min = sorted_vals[1], average = sorted_vals[2], bar_max = sorted_vals[3], max = sorted_vals[4]) # Create the plot plot = Plot(pd) plot.candle_plot(("index", "min", "bar_min", "average", "bar_max", "max"), color = "lightgray", bar_line_color = "black", stem_color = "blue", center_color = "red", center_width = 2) # Tweak some of the plot properties plot.title = "Candlestick 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(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)