Merged charts to create more space.
This commit is contained in:
Jamie Cash
+89
-90
@@ -527,12 +527,8 @@ class GraphPanel(wx.Panel):
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# Super
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wx.Panel.__init__(self, parent)
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# 3 axis, 2 price data for calculate, 2 price data for last coefficient and coefficient history.
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# All will have axis labels and top and right boarders
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# removed
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self.__fig, self.__axes = plt.subplots(nrows=5, ncols=1)
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# Create the canvas
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# Fig & canvas
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self.__fig = plt.figure()
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self.__canvas = FigureCanvas(self, -1, self.__fig)
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# Date format for x axes
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@@ -551,8 +547,7 @@ class GraphPanel(wx.Panel):
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self.__axes = None
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self.__fig = None
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def draw(self, prices=None, ticks=None, history=None, symbols=None, divergence_threshold=None,
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monitor_inverse=False):
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def draw(self, prices, ticks, history, symbols, divergence_threshold=None, monitor_inverse=False):
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"""
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Plot the correlations.
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:param prices: Price data used to calculate base coefficient. List [Symbol1 Price Data, Symbol 2 Price Data]
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@@ -582,10 +577,6 @@ class GraphPanel(wx.Panel):
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times.append(hist['Date To'])
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coefficients.append(hist['Coefficient'])
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# Clear. We will need to redraw
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for ax in self.__axes:
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ax.clear()
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if symbols_selected:
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# Axis ranges
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if price_data_available:
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@@ -600,101 +591,109 @@ class GraphPanel(wx.Panel):
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else:
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tick_chart_date_range = [datetime.now() - timedelta(days=1/48), datetime.now()]
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# Chart config
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titles = [f"Base Coefficient Price Data for {symbols[0]}", f"Base Coefficient Price Data for {symbols[1]}",
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f"Coefficient Tick Data for {symbols[0]}", f"Coefficient Tick Data for {symbols[1]}",
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f"Coefficient History for {symbols[0]}:{symbols[1]}"]
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xlims = [price_chart_date_range, price_chart_date_range, tick_chart_date_range, tick_chart_date_range, None]
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ylims = [None, None, None, None, [-1, 1]]
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# First two charts. Data used to calculate base coefficient and data used to calculate latest coefficient.
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# Both charts will use 2 plots on a single axis and have different y ranges.
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titles = [f"Base Coefficient Price Data for {symbols[0]}:{symbols[1]}",
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f"Coefficient Tick Data for {symbols[0]}:{symbols[1]}"]
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xlims = [price_chart_date_range, tick_chart_date_range]
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# Axis labels
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xlabels = [None, None, None, None, None]
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ylabels = ['Price', 'Price', 'Price', 'Price', 'Coefficient']
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xdata = [[prices[0]['time'] if price_data_available else [],
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prices[1]['time'] if price_data_available else []],
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[ticks[0]['time'] if tick_data_available else [],
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ticks[1]['time'] if tick_data_available else []]]
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# Tick labels and formats
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tick_labels = [[],
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prices[1]['time'] if price_data_available else [],
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[],
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ticks[1]['time'] if tick_data_available else [],
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times[0].array if history_data_available else []]
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mtick_fmts = [None, self.__tick_fmt_date, None, self.__tick_fmt_time, self.__tick_fmt_time]
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mtick_rot = [0, 45, 0, 45, 45]
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ydata = [[prices[0]['close'] if price_data_available else [],
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prices[1]['close'] if price_data_available else []],
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[ticks[0]['ask'] if tick_data_available else [],
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ticks[1]['ask'] if tick_data_available else []]]
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# Chart data
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xdata = [prices[0]['time'] if price_data_available else [],
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prices[1]['time'] if price_data_available else [],
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ticks[0]['time'] if tick_data_available else [],
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ticks[1]['time'] if tick_data_available else [],
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times if history_data_available else []]
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tick_labels = [prices[1]['time'] if price_data_available else [],
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ticks[1]['time'] if tick_data_available else []]
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ydata = [prices[0]['close'] if price_data_available else [],
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prices[1]['close'] if price_data_available else [],
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ticks[0]['ask'] if tick_data_available else [],
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ticks[1]['ask'] if tick_data_available else [],
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coefficients if history_data_available else []]
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tick_formats = [self.__tick_fmt_date, self.__tick_fmt_time]
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# Chart types
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types = ['plot', 'plot', 'plot', 'plot', 'scatter']
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# Clear the figure then redraw the 2 charts
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self.__fig.clf()
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for i in range(0, 2):
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# 2 axis. One for each symbol
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s1ax = self.__fig.add_subplot(3, 1, i+1)
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s2ax = s1ax.twinx()
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# Legends
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legends = [None, None, None, None, [f"{Config().get('monitor.calculations.long.from')} Minutes",
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f"{Config().get('monitor.calculations.medium.from')} Minutes",
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f"{Config().get('monitor.calculations.short.from')} Minutes"]]
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# lines
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horiz_lines = [None, None, None, None, [divergence_threshold, divergence_threshold * -1
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if divergence_threshold is not None and monitor_inverse else None]]
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# Draw 5 charts
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for index in range(0, len(self.__axes)):
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# Titles and axis labels
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self.__axes[index].set_title(titles[index])
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self.__axes[index].set_xlabel(xlabels[index])
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self.__axes[index].set_ylabel(ylabels[index])
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s1ax.set_title(titles[i])
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s1ax.set_ylabel('Price')
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# Limits
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if xlims[index] is not None:
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self.__axes[index].set_xlim(xlims[index])
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# X Limits
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s1ax.set_xlim(xlims[i])
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if ylims[index] is not None:
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self.__axes[index].set_ylim(ylims[index])
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# Y Labels. Left for symbol1, right for symbol2
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colors = ['green', 'blue']
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s1ax.set_ylabel(f"{symbols[0]}", color=colors[0])
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s2ax.set_ylabel(f"{symbols[1]}", color=colors[1])
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# Remove typ and right boarders
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self.__axes[index].spines["top"].set_visible(False)
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self.__axes[index].spines["right"].set_visible(False)
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# Plot both lines
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s1ax.plot(xdata[i][0], ydata[i][0], color=colors[0])
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s2ax.plot(xdata[i][1], ydata[i][1], color=colors[1])
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# Plot. There may be more than one set of data or each chart. Convert single data to list, then loop
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xdata_list = xdata[index] if isinstance(xdata[index], list) else [xdata[index], ]
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ydata_list = ydata[index] if isinstance(ydata[index], list) else [ydata[index], ]
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for data_index in range(0, len(xdata_list)):
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if types[index] == 'plot':
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self.__axes[index].plot(xdata_list[data_index], ydata_list[data_index])
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elif types[index] == 'scatter':
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self.__axes[index].scatter(xdata_list[data_index], ydata_list[data_index], s=1)
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# Y tick colours
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s1ax.tick_params(axis='y', labelcolor=colors[0])
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s2ax.tick_params(axis='y', labelcolor=colors[1])
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# Ticks, labels and formats. Fixing xticks with FixedLocator but also using MaxNLocator to avoid
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# cramped x-labels
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if len(tick_labels[index]) > 0:
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self.__axes[index].xaxis.set_major_locator(mticker.MaxNLocator(10))
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ticks_loc = self.__axes[index].get_xticks().tolist()
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self.__axes[index].xaxis.set_major_locator(mticker.FixedLocator(ticks_loc))
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self.__axes[index].set_xticklabels(ticks_loc)
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if mtick_fmts[index] is not None:
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self.__axes[index].xaxis.set_major_formatter(mtick_fmts[index])
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plt.setp(self.__axes[index].xaxis.get_majorticklabels(), rotation=mtick_rot[index])
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if len(tick_labels[i]) > 0:
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s1ax.xaxis.set_major_locator(mticker.MaxNLocator(10))
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ticks_loc = s1ax.get_xticks().tolist()
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s1ax.xaxis.set_major_locator(mticker.FixedLocator(ticks_loc))
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s1ax.set_xticklabels(ticks_loc)
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if tick_formats[i] is not None:
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s1ax.xaxis.set_major_formatter(tick_formats[i])
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plt.setp(s1ax.xaxis.get_majorticklabels(), rotation=45)
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else:
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self.__axes[index].set_xticklabels([])
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s1ax.set_xticklabels([])
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# Lines
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if horiz_lines[index] is not None and isinstance(horiz_lines[index], list):
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for line_pos in horiz_lines[index]:
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if line_pos is not None:
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self.__axes[index].axhline(y=line_pos, color="red", label='_nolegend_', linewidth=1)
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# Third chart showing the coefficient history and the divergence threshold lines.
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ax = self.__fig.add_subplot(3, 1, 3)
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# Legends
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if legends[index] is not None:
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self.__axes[index].legend(legends[index])
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# Titles and axis labels
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ax.set_title(f"Coefficient History for {symbols[0]}:{symbols[1]}")
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ax.set_ylabel('Coefficient')
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# Y Limits. Coefficients range from -1 to 1
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ax.set_ylim([-1, 1])
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# Plot data if we have history data available
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if history_data_available:
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# Plot. There may be more than one set of data for chart. One for each coefficient date range. Convert
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# single data to list, then loop to plot
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xdata = times if isinstance(times, list) else [times, ]
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ydata = coefficients if isinstance(coefficients, list) else [coefficients, ]
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for i in range(0, len(xdata)):
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ax.scatter(xdata[i], ydata[i], s=1)
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# Ticks, labels and formats. Fixing xticks with FixedLocator but also using MaxNLocator to avoid
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# cramped x-labels
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if len(times[0].array) > 0:
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ax.xaxis.set_major_locator(mticker.MaxNLocator(10))
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ticks_loc = ax.get_xticks().tolist()
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ax.xaxis.set_major_locator(mticker.FixedLocator(ticks_loc))
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ax.set_xticklabels(ticks_loc)
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ax.xaxis.set_major_formatter(self.__tick_fmt_time)
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plt.setp(ax.xaxis.get_majorticklabels(), rotation=45)
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else:
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ax.set_xticklabels([])
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# Legend
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ax.legend([f"{Config().get('monitor.calculations.long.from')} Minutes",
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f"{Config().get('monitor.calculations.medium.from')} Minutes",
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f"{Config().get('monitor.calculations.short.from')} Minutes"])
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# Lines showing divergence threshold. 2 if we are monitoring inverse correlations.
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if divergence_threshold is not None:
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ax.axhline(y=divergence_threshold, color="red", label='_nolegend_', linewidth=1)
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if monitor_inverse:
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ax.axhline(y=divergence_threshold * -1, color="red", label='_nolegend_', linewidth=1)
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# Layout with padding between charts
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self.__fig.tight_layout(pad=0.5)
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