def show_all(): fig = plt.figure() host = HostAxes(fig, [0.15, 0.1, 0.65, 0.8]) par1 = ParasiteAxes(host, sharex=host) par2 = ParasiteAxes(host, sharex=host) host.parasites.append(par1) host.parasites.append(par2) host.set_ylabel("Temperature") host.set_xlabel("Datetime") host.axis["right"].set_visible(False) host.set_ylim(25, 35) par1.set_ylabel("eCO2") par1.axis["right"].set_visible(True) par1.axis["right"].major_ticklabels.set_visible(True) par1.axis["right"].label.set_visible(True) par1.set_ylim(400, 2000) par2.set_ylabel("TVOC") new_axisline = par2.get_grid_helper().new_fixed_axis par2.axis["right2"] = new_axisline(loc="right", axes=par2, offset=(60, 0)) par2.set_ylim(0, 1000) fig.add_axes(host) p1, = host.plot(temperatures, label="Temperature") p2, = par1.plot(eCO2s, label="eCO2") p3, = par2.plot(TVOCs, label="TVOC") host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) par2.axis["right2"].label.set_color(p3.get_color()) plt.show()
par1.axis["right"].label.set_visible(True) par2.set_ylabel("Velocity") offset = (60, 0) new_axisline = par2._grid_helper.new_fixed_axis par2.axis["right2"] = new_axisline(loc="right", axes=par2, offset=offset) fig.add_axes(host) host.set_xlim(0, 2) host.set_ylim(0, 2) host.set_xlabel("Distance") host.set_ylabel("Density") par1.set_ylabel("Temperature") p1, = host.plot([0, 1, 2], [0, 1, 2], label="Density") p2, = par1.plot([0, 1, 2], [0, 3, 2], label="Temperature") p3, = par2.plot([0, 1, 2], [50, 30, 15], label="Velocity") par1.set_ylim(0, 4) par2.set_ylim(1, 65) host.legend() host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) par2.axis["right2"].label.set_color(p3.get_color()) plt.show()
def plot_vel_acc_rdis(vel, acc, rdis): title_font_dict = { 'family': 'Times New Roman', 'color': 'black', 'weight': 'normal', 'fontsize': 15 } axis_font_dict = { 'family': 'Times New Roman', 'color': 'black', 'weight': 'normal', 'fontsize': 30 } legend_font = { 'family': 'Times New Roman', 'weight': 'normal', 'size': 10, } vel_x = np.array(vel)[:, 0] / 10. vel_y = np.array(vel)[:, 1] acc_x = np.array(acc)[:, 0] / 10. acc_y = np.array(acc)[:, 1] rdis_x = np.array(rdis)[:, 0] / 10. rdis_y = np.array(rdis)[:, 1] fig = plt.figure(figsize=(10, 3.5), dpi=200) vel_axes = HostAxes(fig, [0.05, 0.1, 0.8, 0.8]) acc_axes = ParasiteAxes(vel_axes, sharex=vel_axes) rdis_axes = ParasiteAxes(vel_axes, sharex=vel_axes) vel_axes.parasites.append(acc_axes) vel_axes.parasites.append(rdis_axes) vel_axes.set_ylabel('Velocity (m/s)') vel_axes.set_xlabel('Time (s)') vel_axes.axis['right'].set_visible(False) acc_axes.axis['right'].set_visible(True) acc_axes.set_ylabel('Acceleration (m/s^2)') acc_axes.axis['right'].major_ticklabels.set_visible(True) acc_axes.axis['right'].label.set_visible(True) rdis_axes.set_ylabel('Relative distance (m)') offset = (60, 0) new_axisline = rdis_axes._grid_helper.new_fixed_axis rdis_axes.axis['right2'] = new_axisline(loc='right', axes=rdis_axes, offset=offset) fig.add_axes(vel_axes) p1, = vel_axes.plot(vel_x, vel_y, label="Vel", linewidth=2) p2, = acc_axes.plot(acc_x, acc_y, label="Acc", linewidth=2) p3, = rdis_axes.plot(rdis_x, rdis_y, label="RD", linewidth=2) vel_axes.legend(prop=legend_font) vel_axes.set_ylim(0, np.max(vel_y) + 1) vel_axes.set_xlim(0, np.max(vel_x)) rdis_axes.set_ylim(0, np.max(rdis_y) + 1) # plt.plot(vel_x, vel_y, color="green", label="Velocity", linewidth=2) # plt.ylabel('Velocity (m/s)', fontdict=axis_font_dict) # # plt.plot(acc_x, acc_y, color="orange", label="Acceleration", linewidth=2, secondary_y=True) # plt.ylabel('Acceleration (m/s^2)', fontdict=axis_font_dict) # plt.title('Kinematic information of host vehicle', fontdict=title_font_dict) # plt.xlabel('Time (s)', fontdict=axis_font_dict) # plt.ylabel('Likelihood', fontdict=axis_font_dict) # plt.tick_params(labelsize=20) plt.legend(prop=legend_font) # plt.ylim(0., 1.) # left, right = plt.xlim() # plt.xlim(0., right) plt.show() pass
axes=ax_wear, offset=(120, 0)) fig.add_axes(ax_cof) ''' #set limit of x, y ax_cof.set_xlim(0,2) ax_cof.set_ylim(0,3) ''' curve_cof, = ax_cof.plot([0, 1, 2], [0, 1, 2], label="CoF", color='black') curve_temp, = ax_temp.plot([0, 1, 2], [0, 3, 2], label="Temp", color='red') curve_load, = ax_load.plot([0, 1, 2], [1, 2, 3], label="Load", color='green') curve_cp, = ax_cp.plot([0, 1, 2], [0, 40, 25], label="CP", color='pink') curve_wear, = ax_wear.plot([0, 1, 2], [25, 18, 9], label="Wear", color='blue') ax_temp.set_ylim(0, 4) ax_load.set_ylim(0, 4) ax_cp.set_ylim(0, 50) ax_wear.set_ylim(0, 30) ax_cof.legend() #轴名称,刻度值的颜色 #ax_cof.axis['left'].label.set_color(ax_cof.get_color()) ax_temp.axis['right'].label.set_color('red') ax_load.axis['right2'].label.set_color('green') ax_cp.axis['right3'].label.set_color('pink') ax_wear.axis['right4'].label.set_color('blue') ax_temp.axis['right'].major_ticks.set_color('red') ax_load.axis['right2'].major_ticks.set_color('green')
host.set_ylabel("Density") host.set_xlabel("Distance") host.axis["right"].set_visible(True) par1.axis["right"].set_visible(True) par1.set_ylabel("Temperature") par1.axis["right"].major_ticklabels.set_visible(True) par1.axis["right"].label.set_visible(True) fig.add_axes(host) host.set_xlim(1975, 2010) host.set_ylim(0, 100) host.set_xlabel("GDP and Success rate") host.set_ylabel("GDP per five years (*2*10^10") par1.set_ylabel("Success Rate (%)") p1, = host.plot(names, gdp_values, label="GDP") p2, = par1.plot(names, edu_values, label="Success Rate") par1.set_ylim(0, 100) host.legend() host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) plt.show()
par2.set_ylabel("Velocity") offset = (60, 0) new_axisline = par2._grid_helper.new_fixed_axis par2.axis["right2"] = new_axisline(loc="right", axes=par2, offset=offset) fig.add_axes(host) host.set_xlim(0, 2) host.set_ylim(0, 2) host.set_xlabel("Distance") host.set_ylabel("Density") par1.set_ylabel("Temperature") p1, = host.plot([0, 1, 2], [0, 1, 2], label="Density") p2, = par1.plot([0, 1, 2], [0, 3, 2], label="Temperature") p3, = par2.plot([0, 1, 2], [50, 30, 15], label="Velocity") par1.set_ylim(0, 4) par2.set_ylim(1, 65) host.legend() host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) par2.axis["right2"].label.set_color(p3.get_color()) plt.draw() plt.show()
def draw_point_fcst(t2m=None, u10m=None, v10m=None, rn=None, model=None, output_dir=None, points=None, extra_info=None): plt.rcParams['font.sans-serif'] = ['SimHei'] # 步骤一(替换sans-serif字体) plt.rcParams['axes.unicode_minus'] = False # 步骤二(解决坐标轴负数的负号显示问题) if (sys.platform[0:3] == 'lin'): locale.setlocale(locale.LC_CTYPE, 'zh_CN.utf8') if (sys.platform[0:3] == 'win'): locale.setlocale(locale.LC_CTYPE, 'chinese') initTime = pd.to_datetime(str( t2m['forecast_reference_time'].values)).replace( tzinfo=None).to_pydatetime() # draw figure fig = plt.figure(figsize=(16, 4.5)) ax_t2m = HostAxes(fig, [0.1, 0.28, .8, .62]) ax_rn = ParasiteAxes(ax_t2m, sharex=ax_t2m) #其他信息 #append axes ax_t2m.parasites.append(ax_rn) #invisible right axis of ax ax_t2m.axis['right'].set_visible(False) ax_t2m.axis['right'].set_visible(False) ax_rn.axis['right'].set_visible(True) ax_rn.axis['right'].major_ticklabels.set_visible(True) ax_rn.axis['right'].label.set_visible(True) #set label for axis ax_t2m.set_ylabel('温度($^\circ$C)', fontsize=100) ax_rn.set_ylabel('降水(mm)', fontsize=100) fig.add_axes(ax_t2m) # draw main figure #2米温度—————————————————————————————————————— if (model == '中央台指导'): model = '智能网格' utl.add_public_title_sta(title=model + '预报 ' + extra_info['point_name'] + ' [' + str(points['lon'][0]) + ',' + str(points['lat'][0]) + ']', initTime=initTime, fontsize=21) for ifhour in t2m['forecast_period'].values: if (ifhour == t2m['forecast_period'].values[0]): t2m_t = (initTime + timedelta(hours=ifhour)) else: t2m_t = np.append(t2m_t, (initTime + timedelta(hours=ifhour))) curve_t2m = ax_t2m.plot(t2m_t, np.squeeze(t2m['data'].values), c='#FF6600', linewidth=3, label='2m温度') ax_t2m.set_xlim(t2m_t[0], t2m_t[-1]) ax_t2m.set_ylim( math.floor(t2m['data'].values.min() / 5) * 5 - 2, math.ceil(t2m['data'].values.max() / 5) * 5) #降水—————————————————————————————————————— for ifhour in rn['forecast_period'].values: if (ifhour == rn['forecast_period'].values[0]): rn_t = (initTime + timedelta(hours=ifhour)) else: rn_t = np.append(rn_t, (initTime + timedelta(hours=ifhour))) mask = (rn['data'] < 999) rn = rn['data'].where(mask) ax_rn.bar(rn_t, np.squeeze(rn.values), width=0.1, color='#00008B', label=str( int(rn['forecast_period'].values[1] - rn['forecast_period'].values[0])) + '小时降水', alpha=0.5) #curve_rn=ax_rn.plot(rn_t, np.squeeze(rn['data'].values), c='#40C4FF',linewidth=3) ax_rn.set_ylim(0, np.nanmax(np.append(10, np.squeeze(rn.values)))) ### xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时 ax_t2m.xaxis.set_major_locator(xaxis_intaval) # add legend ax_t2m.legend(fontsize=15, loc='upper right') ax_t2m.tick_params(length=10) ax_t2m.tick_params(axis='y', labelsize=100) ax_t2m.set_xticklabels([' ']) miloc = mpl.dates.HourLocator(byhour=(8, 11, 14, 17, 20, 23, 2, 5)) #单位是小时 ax_t2m.xaxis.set_minor_locator(miloc) yminorLocator = MultipleLocator(1) #将此y轴次刻度标签设置为1的倍数 ax_t2m.yaxis.set_minor_locator(yminorLocator) ymajorLocator = MultipleLocator(5) #将此y轴次刻度标签设置为1的倍数 ax_t2m.yaxis.set_major_locator(ymajorLocator) ax_t2m.grid(axis='x', which='minor', ls='--') ax_t2m.axis['left'].label.set_fontsize(15) ax_t2m.axis['left'].major_ticklabels.set_fontsize(15) ax_rn.axis['right'].label.set_fontsize(15) ax_rn.axis['right'].major_ticklabels.set_fontsize(15) #10米风—————————————————————————————————————— ax_uv = plt.axes([0.1, 0.16, .8, .12]) for ifhour in u10m['forecast_period'].values: if (ifhour == u10m['forecast_period'].values[0]): uv_t = (initTime + timedelta(hours=ifhour)) else: uv_t = np.append(uv_t, (initTime + timedelta(hours=ifhour))) wsp = (u10m**2 + v10m**2)**0.5 #curve_uv=ax_uv.plot(uv_t, np.squeeze(wsp['data'].values), c='#696969',linewidth=3,label='10m风') ax_uv.barbs(uv_t, np.zeros(len(uv_t)), np.squeeze(u10m['data'].values), np.squeeze(v10m['data'].values), fill_empty=True, color='gray', barb_increments={ 'half': 2, 'full': 4, 'flag': 20 }, length=5.8, linewidth=1.5, zorder=100) ax_uv.set_ylim(-1, 1) ax_uv.set_xlim(uv_t[0], uv_t[-1]) #ax_uv.axis('off') ax_uv.set_yticklabels([' ']) #logo utl.add_logo_extra_in_axes(pos=[0.87, 0.00, .1, .1], which='nmc', size='Xlarge') #开启自适应 xaxis_intaval = mpl.dates.HourLocator(byhour=(8, 20)) #单位是小时 ax_uv.xaxis.set_major_locator(xaxis_intaval) ax_uv.tick_params(length=5, axis='x') ax_uv.tick_params(length=0, axis='y') miloc = mpl.dates.HourLocator(byhour=(8, 11, 14, 17, 20, 23, 2, 5)) #单位是小时 ax_uv.xaxis.set_minor_locator(miloc) ax_uv.grid(axis='x', which='both', ls='--') ax_uv.set_ylabel('10m风', fontsize=15) xstklbls = mpl.dates.DateFormatter('%m月%d日%H时') for label in ax_uv.get_xticklabels(): label.set_rotation(30) label.set_horizontalalignment('center') ax_uv.tick_params(axis='x', labelsize=15) #出图—————————————————————————————————————————————————————————— if (output_dir != None): isExists = os.path.exists(output_dir) if not isExists: os.makedirs(output_dir) output_dir2 = output_dir + model + '_起报时间_' + initTime.strftime( "%Y年%m月%d日%H时") + '/' if (os.path.exists(output_dir2) == False): os.makedirs(output_dir2) plt.savefig(output_dir2 + model + '_' + extra_info['point_name'] + '_' + extra_info['output_head_name'] + initTime.strftime("%Y%m%d%H") + '00' + extra_info['output_tail_name'] + '.jpg', dpi=200, bbox_inches='tight') else: plt.show()
def plot_multi_y(line_series_list, line_label_list, scatter_series_list, scatter_label_list): """ 第一条line做主轴,散点与主轴共用Y轴 :param line_series_list: :param line_label_list: :param scatter_series_list: :param scatter_label_list: :return: """ color_list = ['red', 'green', 'blue', 'yellow', 'pink', 'black', 'orange'] fig = plt.figure(1) host_axes = HostAxes(fig, [0.1, 0.1, 0.6, 0.8]) fig.add_axes(host_axes) host_axes.set_ylabel(line_label_list[0]) host_axes.axis['right'].set_visible(False) host_axes.set_ylim( min(line_series_list[0][1]) * 0.9, max(line_series_list[0][1]) * 1.1) host_axes.plot(line_series_list[0][0], line_series_list[0][1], label=line_label_list[0], color=color_list[0]) label_offset = 0 # line_axes = [] for i in range(len(line_series_list) - 1): axes = ParasiteAxes(host_axes, sharex=host_axes) axes.set_ylabel(line_label_list[i + 1]) axis_line = axes.get_grid_helper().new_fixed_axis axes.axis['right' + str(label_offset)] = axis_line( loc='right', axes=axes, offset=(label_offset, 0)) axes.axis['right' + str(label_offset)].label.set_color(color_list[i + 1]) axes.axis['right' + str(label_offset)].major_ticks.set_color( color_list[i + 1]) axes.axis['right' + str(label_offset)].major_ticklabels.set_color( color_list[i + 1]) axes.axis['right' + str(label_offset)].line.set_color(color_list[i + 1]) label_offset += 40 axes.set_ylim( min(line_series_list[i + 1][1]) * 0.9, max(line_series_list[i + 1][1]) * 1.1) axes.plot(line_series_list[i + 1][0], line_series_list[i + 1][1], label=line_label_list[i + 1], color=color_list[i + 1]) # line_axes.append(axes) host_axes.parasites.append(axes) # scatter_axes = [] for i in range(len(scatter_series_list)): # 与主轴共用Y轴 # axes = ParasiteAxes(host_axes, sharex=host_axes) # axes.set_ylabel(scatter_label_list[i]) # axis_line = axes.get_grid_helper().new_fixed_axis # axes.axis['right' + str(label_offset)] = axis_line(loc='right', axes=axes, offset=(label_offset, 0)) color_item = color_list[len(line_label_list) + i + 1] # axes.axis['right' + str(label_offset)].label.set_color(color_item) # axes.axis['right' + str(label_offset)].major_ticks.set_color(color_item) # axes.axis['right' + str(label_offset)].major_ticklabels.set_color(color_item) # axes.axis['right' + str(label_offset)].line.set_color(color_item) # label_offset += 40 # axes.set_ylim(min(scatter_series_list[i][1]), max(scatter_series_list[i][1])) host_axes.scatter(scatter_series_list[i][0], scatter_series_list[i][1], label=scatter_label_list[i], color=color_item) # scatter_axes.append(axes) # host_axes.parasites.append(axes) host_axes.legend() plt.show()
host.set_xlabel('流量') host.set_ylabel('功率') host.set_ylabel('效率') x = np.linspace(0, fm, 500) y = headparameters[0] * x ** 2 + headparameters[1] * x + headparameters[2] p1, = host.plot(x, y, label="HQ拟合曲线", color="black") host.scatter(flow1, head1, label="HQ离散数据") x1 = np.linspace(0, fm, 500) y1 = powerparameters[0] * x ** 2 + powerparameters[1] * x + powerparameters[2] p2, = par1.plot(x, y1, label="PQ拟合曲线", color="red") par1.scatter(flow1, power1, label="PQ离散数据") x2 = np.linspace(0, fm, 500) y2 = effectparameters[0] * x ** 2 + effectparameters[1] * x + effectparameters[2] p3, = par2.plot(x, y2, label="EQ拟合曲线", color="blue") par2.scatter(flow1, effect, label="EQ离散数据") par1.set_ylim(0, pm * 2) par2.set_ylim(0, nm + 5) host.legend() par2.axis['right2'].major_ticklabels.set_color(p3.get_color()) # 刻度值颜色 par2.axis['right2'].set_axisline_style('-|>', size=1.5) # 轴的形状色 ======= # plt.xticks(range(0, fm + 1, 1)) host.set_ylim(0, hm + 5) host.set_xlabel('流量(Q)(m3/h)') host.set_ylabel('功率(P)(kW)', color="red") host.set_ylabel('扬程(H)(m)', color="black") x = np.linspace(0, fm, 500) y = headparameters[0] * x ** 2 + headparameters[1] * x + headparameters[2] p1, = host.plot(x, y, label="HQ拟合曲线", color="black")
0.691, 0.693, 0.710, 0.715, 0.721, 0.727, 0.703, 0.704, 0.705, 0.695, 0.706, 0.687, 0.679 ], 'o-', label="F1 score", linewidth=2.2, color="#59604C") p2, = par1.plot([1, 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80], [ 5.13, 5.28, 5.33, 5.76, 5.99, 6.01, 6.54, 6.83, 6.99, 7.38, 7.85, 7.97, 8.42 ], '*--', label="Runtime(second)", linewidth=2.2, color="#A35638") #p1, = host.plot([1, 5, 10, 15, 20, 25, 30, 40,50,60,70,80], [0.589, 0.604, 0.614, 0.647, 0.634, 0.621, 0.612, 0.608, 0.531,0.546,0.448,0.486], 'o-',label="F1 score", linewidth=2.2, color="#59604C") #p2, = par1.plot([1, 5, 10, 15, 20, 25, 30, 40,50,60,70,80], [19.39, 17.82, 18.902, 18.904, 19.04, 19.509, 18.68, 19.53, 19.795,20.596,21.228,21.562], '*--', label="Runtime(second)", linewidth=2.2, color="#A35638") #p3, = par2.plot([0, 1, 2], [50, 30, 15], label="Velocity") par1.set_ylim(0, 30) #par1.set_ylim(0, 1) #par2.set_ylim(3.5, 4.2) host.legend(loc="upper left", fontsize=12) host.axis["left"].label.set_color(p1.get_color()) host.axis["left"].label.set_fontsize(14) host.axis["left"].label.fontweight = "bold" host.axis["bottom"].label.set_fontsize(14) par1.axis["right"].label.set_color(p2.get_color()) par1.axis["right"].label.set_fontsize(14) par1.axis["right"].label.fontweight = "bold" #par2.axis["right2"].label.set_color(p3.get_color()) plt.show()
label='utilization', color='#3366FF') plot_response, = axis_response.plot([250 for i in range(1000)], color='black', linestyle='--') # SLA violation定为250ms plot_response, = axis_response.plot(ansresponseList[botton], label='response time', color='#CC3333') plot_container, = axis_container.plot(anssupplypodList[botton], label='container', color='green') plot_throughput, = axis_throughput.plot(ansthroughputList[botton], label='throughput', color='orange') #通过范围限制调整数据在图中的位置(一个是调整上界,可以抬升;一个是调整占比比例,可以让其出现在想出现的区域) axis_cpu.set_ylim(0, 100) axis_response.set_ylim(-400, 400) axis_container.set_ylim(0, 40) axis_response.set_yticks([0, 100, 200, 300, 400, 500, 600]) #右侧轴线颜色与格式设置 axis_cpu.axis['right2'].set_axisline_style('-|>', size=1.5) #设置轴线样式 axis_cpu.axis['right2'].line.set_color(plot_cpu.get_color()) #轴线上色 axis_cpu.axis['right2'].major_ticklabels.set_color( plot_cpu.get_color()) #刻度值上色 axis_cpu.axis['right2'].label.set_color(plot_cpu.get_color()) axis_response.axis['right3'].set_axisline_style('-|>', size=1.5) #设置轴线样式 axis_response.axis['right3'].line.set_color( plot_response.get_color()) #轴线上色 axis_response.axis['right3'].major_ticklabels.set_color(
host.set_xlim(np.pi / 2, np.pi) host.set_ylim(0.29, 0.61) host.set_xticks([1.57, 1.8, 2.0, 2.2, 2.4, 2.6, 2.8, 3.0, 3.1415]) host.set_xticklabels( ['$\\pi/2$', '1.8', '2.0', '2.2', '2.4', '2.6', '2.8', '3.0', '$\\pi$']) host.set_xlabel("$\\theta_c$") host.set_ylabel("$\\theta_b^*$") par1.set_ylabel("min$_{\\theta_b} \\varepsilon$ $(\\times 10^{-3})$") p1, = host.plot(C[0, :], X[Z.argmin(axis=0), 0], label="$\\theta_b^*$", color='#1f77b4') p2, = par1.plot(C[0, :], Z.min(axis=0) * 1000, label="min$_{\\theta_b} \\varepsilon$", color='#e6550d') par1.set_ylim(0, 2.5) host.legend(loc='center left') host.grid(linestyle='--') host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) plt.show() path_fig1 = join(dirname(__file__), 'result//' + 'approximation2_2.pdf') fig1.savefig(path_fig1, dpi=300, transparent=True, bbox_inches='tight')
host.parasites.append(par1) host.set_ylabel("Density") host.set_xlabel("Distance") host.axis["right"].set_visible(True) par1.axis["right"].set_visible(True) par1.set_ylabel("Temperature") par1.axis["right"].major_ticklabels.set_visible(True) par1.axis["right"].label.set_visible(True) fig.add_axes(host) host.set_xlim(1975, 2010) host.set_ylim(0, 100) host.set_xlabel("Years Intervals") host.set_ylabel("Income") par1.set_ylabel("Pass Rate") p1, = host.plot(names, values1, label="Income") p2, = par1.plot(names, values2, label="Pass Rate") par1.set_ylim(56, 65) host.legend() host.axis["left"].label.set_color(p1.get_color()) par1.axis["right"].label.set_color(p2.get_color()) plt.show()
line_torque_multi_gear = ax_torque_multi_gear.plot( time[order], torque_multi_gear, linestyle=line_style[vehicle_number[order]], color=line_color[temperature_target[order]]) gear_max = max(gear_max, max(gear[order])) power_max = max(power_max, max(power)) lines_set = lines_set + line_power legend_set = [line.get_label() for line in lines_set] ax_power.legend(lines_set, legend_set, loc='upper left') ax_power.set_xlabel('Time(s)') ax_power.set_ylabel('Power(kw)') ax_power.set_ylim(-20, 2 * power_max) ax_power.set_yticks([i * 20 for i in range(0, int(power_max / 20 + 1))]) ax_gear.set_ylabel('Gear/Gear ratio') ax_gear.set_ylim(-gear_max, gear_max + 1) ax_gear.set_yticks([i for i in range(0, int(gear_max) + 1)]) if gear_max > 10: # if it is gear ratio, plot torque*gear ax_torque_multi_gear.set_ylabel('Torque*gear ratio(Nm)') ax_torque_multi_gear.set_ylim(-torque_mutil_gear_max - 50, torque_mutil_gear_max) ax_torque_multi_gear.set_yticks( [i * 500 for i in range(0, int(torque_mutil_gear_max / 500) + 2)]) ax_gear.set_ylim(0, 2 * gear_max) ax_power.legend(lines_set, legend_set, loc='upper right') plt.savefig(fig2_name + '.png', transparent=True) # plt.show()
def plot_line_(name, x, y1, y2, y3): #fig = plt.figure(figsize=(7,5)) #figsize默认为4,4(图像尺寸),facecolor="blue" fig = plt.figure(1) #figsize默认为4,4(图像尺寸),facecolor="blue" ax = HostAxes( fig, [0.15, 0.1, 0.7, 0.8 ]) #用[left, bottom, weight, height]的方式定义axes,0 <= l,b,w,h <= 1 ax_ndvi = ParasiteAxes(ax, sharex=ax) ax_t = ParasiteAxes(ax, sharex=ax) ax_p = ParasiteAxes(ax, sharex=ax) ax.parasites.append(ax_ndvi) ax.parasites.append(ax_p) ax.parasites.append(ax_t) ax.set_ylim(0.41, 0.75) ax.set_xlim(2004.5, 2015.5) ax.axis['right'].set_visible(False) ax.axis['top'].set_visible(False) # plt.tick_params(top = 'off', right = 'off') #ax_ndvi.axis['left1'] = new_axisline(loc='left', axes=ax_ndvi, offset=offset1) #ax.axis['left'].set_axisline_style('->',size=2) #轴的形状色 ax.axis['left'].line.set_linewidth(3) #轴宽 ax.axis['bottom'].line.set_linewidth(3) #轴宽 offset1 = (20, 0) offset2 = (60, 0) ax_t.set_ylim(10, 30) ax_p.set_ylim(500, 2500) new_axisline = ax_t._grid_helper.new_fixed_axis # "_grid_helper"与"get_grid_helper()"等价,可以代替 #new_axisline = par2.get_grid_helper().new_fixed_axis # 用"get_grid_helper()"代替,结果一样,区别目前不清楚 new_axisline = ax_p._grid_helper.new_fixed_axis ax_t.axis['right2'] = new_axisline(loc='right', axes=ax_t, offset=offset1) #ax_t.axis['right2'].set_axisline_style('-|>',size=-1) #轴的形状色 ax_t.axis['right2'].line.set_linewidth(3) #轴宽 ax_t.axis['right2'].set_label( 'T') # ax_t.axis['right2'].set_axislabel_direction('-') ax_p.axis['right3'] = new_axisline(loc='right', axes=ax_p, offset=offset2) #ax_p.axis['right3'].set_axisline_style('->',size=-1) #轴的形状色 ax_p.axis['right3'].line.set_linewidth(3) #轴宽 ax_p.axis['right3'].set_label('P') ax_t.yaxis.set_major_locator(MultipleLocator(2)) ax_p.yaxis.set_major_locator(MultipleLocator(500)) ax.xaxis.set_major_locator( xmajorLocator ) #设置主刻度标签的位置,没有标签文本格式ax.xaxis.set_major_formatter(FormatStrFormatter('%5.1f')) ax.yaxis.set_major_locator(ymajorLocator) ax.xaxis.set_minor_locator(xminorLocator) #设置次刻度标签的位置,没有标签文本格式 ax.xaxis.set_minor_locator(xminorLocator) #打开网格 ax_ndvi.grid(which='minor', color='black', linestyle='--') #,lw=0.8, alpha=0.5) # grid setting) #绘制网格线 ax_t.grid(which='minor', color='black', linestyle='--') #,lw=0.8, alpha=0.5) # grid setting) #绘制网格线 ax.tick_params(axis='both', which='major', direction='in', width=2, length=lwidth, pad=tick_pad, labelsize=tick_labelsz, grid_linewidth=3) ax.set_ylabel('NDVI', font_properties=getChineseFont(80)) #ax.set_ylabel('NDVI',fontproperties=getChineseFont(100)) ax_t.tick_params(axis='both', which='both', direction='in', width=3, length=100, pad=18, labelsize=100, grid_linewidth=1) ax_p.tick_params(axis='both', which='both', direction='in', width=3, length=100, pad=18, labelsize=100, grid_linewidth=1) fig.add_axes(ax) ax.set_xlabel('Year') p1, = ax.plot(x, y1, label="NDVI", ls=linestyle, lw=lwidth, color=c1, marker=".", ms=16, mfc=c1) p2, = ax_t.plot(x, y3, label="Temperature", ls=linestyle, lw=lwidth, color=c2, marker="o", ms=marksize, mfc=c2) p3, = ax_p.plot(x, y2, label="Precipitation", ls=linestyle, lw=lwidth, color=c3, marker="o", ms=marksize, mfc=c3) #ax.set_xlabel('YEAR') #ax.set_ylabel('NDVI') plt.legend(loc=1, bbox_to_anchor=(0.9, 1.2), prop=getChineseFont(12), ncol=1, frameon=False, mode='expend') #plt.savefig(r'C:\Users\YeHui\Desktop\GGGGGGGGGGG.jpg')#, dpi=1000) plt.show()
color='black') # markerfacecolor='none 標記變成中空 curve_temp = ax_temp.plot(data[0], data[2], 'o-.', label='Porosity', color='red') curve_load = ax_load.plot(data[0], data[3], '^-', label="Coef. of Permeability", color='green') #curve_cp = ax_cp.plot(data[0], data[4], label="CP", color='pink') #curve_wear = ax_wear.plot(data[0], data[5], label="Wear", color='blue') ax_temp.set_ylim(0, 20) ax_load.set_ylim(0, 1) #ax_cp.set_ylim(0,0.5) #ax_wear.set_ylim(0,0.5) ax_cof.legend() #軸名稱,刻度值的顏色 #ax_cof.axis['left'].label.set_color(ax_cof.get_color()) ax_temp.axis['right'].label.set_color('red') ax_load.axis['right2'].label.set_color('green') #ax_cp.axis['right3'].label.set_color('pink') #ax_wear.axis['right4'].label.set_color('blue') ax_temp.axis['right'].major_ticks.set_color('red') ax_load.axis['right2'].major_ticks.set_color('green')