我们从Python开源项目中，提取了以下3个代码示例，用于说明如何使用mpl_toolkits.axes_grid1.host_subplot()。
def summarizePerformance(self, test_data_set): """ This function is called at every PERIOD_BTW_SUMMARY_PERFS. Parameters ----------- test_data_set """ print ("Summary Perf") observations = test_data_set.observations() prices = observations[0][100:200] invest = observations[1][100:200] steps=np.arange(len(prices)) steps_long=np.arange(len(prices)*10)/10. #print steps,invest,prices host = host_subplot(111, axes_class=AA.Axes) plt.subplots_adjust(right=0.9, left=0.1) par1 = host.twinx() host.set_xlabel("Time") host.set_ylabel("Price") par1.set_ylabel("Investment") p1, = host.plot(steps_long, np.repeat(prices,10), lw=3, c = 'b', alpha=0.8, ls='-', label = 'Price') p2, = par1.plot(steps, invest, marker='o', lw=3, c = 'g', alpha=0.5, ls='-', label = 'Investment') par1.set_ylim(-0.09, 1.09) host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) plt.savefig("plot.png") print ("A plot of the policy obtained has been saved under the name plot.png")
def plot_machine(self): class_instance = file_handler(self.filename) class_instance.file_iteration() data_sets = class_instance.data_conversion() names = getattr(class_instance, "substances") if len(names) > 2: host = host_subplot(111, axes_class = AA.Axes) plt.subplots_adjust(right = 0.75) par1 = host.twinx() par2 = host.twinx() host.set_yscale("log") par1.set_yscale("log") par2.set_yscale("log") offset = 60 new_fixed_axis = par2.get_grid_helper().new_fixed_axis par2.axis["right"] = new_fixed_axis(loc="right", axes=par2, offset=(offset, 0)) par2.axis["right"].toggle(all = True) host.set_xlabel(data_sets[0]["x_unit"]) plotty_things = [host, par1, par2] for data_set, name, things in zip(data_sets, names, plotty_things): x_val = data_set["data"][0] y_val = data_set["data"][1] x_unit = data_set["x_unit"] y_unit = data_set["y_unit"] things.set_ylabel(y_unit) things.plot(x_val, y_val, label = data_set["sample element"]) plt.legend() plt.show() else: data_set = data_sets[0] x_val = data_set["data"][0] y_val = data_set["data"][1] x_val = x_val.copy(order = "C") x_unit = data_set["x_unit"] y_unit = data_set["y_unit"] plt.semilogy(x_val, y_val, label = data_set["sample info"][2], nonposy = "clip") plt.xlabel(x_unit) plt.ylabel(y_unit) plt.legend() plt.show()
def plot_machine(self): class_instance = file_handler(self.filename) class_instance.file_iteration() data_sets = class_instance.data_conversion() names = getattr(class_instance, "substances") if len(names) > 2: host = host_subplot(111, axes_class = AA.Axes) plt.subplots_adjust(right = 0.75) par1 = host.twinx() par2 = host.twinx() host.set_yscale("log") par1.set_yscale("log") par2.set_yscale("log") offset = 60 new_fixed_axis = par2.get_grid_helper().new_fixed_axis par2.axis["right"] = new_fixed_axis(loc="right", axes=par2, offset=(offset, 0)) par2.axis["right"].toggle(all = True) host.set_xlabel(data_sets[0]["x_unit"]) plotty_things = [host, par1, par2] for data_set, name, things in zip(data_sets, names, plotty_things): x_val = data_set["data"]["x"] y_val = data_set["data"]["y"] x_unit = data_set["x_unit"] y_unit = data_set["y_unit"] things.set_ylabel(y_unit) things.plot(x_val, y_val, label = data_set["sample element"]) plt.legend() plt.show() else: data_set = data_sets[0] x_val = data_set["data"][0] y_val = data_set["data"][1] x_val = x_val.copy(order = "C") x_unit = data_set["x_unit"] y_unit = data_set["y_unit"] plt.semilogy(x_val, y_val, label = data_set["sample info"][2], nonposy = "clip") plt.xlabel(x_unit) plt.ylabel(y_unit) plt.legend() plt.show()
