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
host.axis["right"].set_visible(False)
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)
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 = HostAxes(fig, [0.1, 0.1, 0.8, 0.8])
par1 = ParasiteAxes(host, sharex=host)
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("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())
ax_wear.set_ylabel('Wear')
load_axisline = ax_load.get_grid_helper().new_fixed_axis
cp_axisline = ax_cp.get_grid_helper().new_fixed_axis
wear_axisline = ax_wear.get_grid_helper().new_fixed_axis
ax_load.axis['right2'] = load_axisline(loc='right',
axes=ax_load,
offset=(40, 0))
ax_cp.axis['right3'] = cp_axisline(loc='right', axes=ax_cp, offset=(80, 0))
ax_wear.axis['right4'] = wear_axisline(loc='right',
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)
host.axis["right"].set_visible(False)
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)
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()
#elif i == 2 :
#elif i < len(values) - 1 :
#p1, = par1.plot(values[i], zcs[i], label= os.path.splitext(os.path.basename(filenames[i + 1]))[0])
# p1, = par1.plot(values[i], zcs[i], label= "RDI")
elif i == 3:
host.plot(values[i],
zcs[i],
label="L-Architect PAD",
linewidth=0.8,
color=palettes["L-Architect"])
#par1.set_ylim(0, 16)
#par2.set_ylim(1, 65)
host.set_ylim(0, 16)
host.set_xlim(0, MAX_X)
host.legend()
#p1
#maxPoints =
if max(values[2]) < 3:
par1.set_xlim(0, 8)
#remove decima if it is integer
#pointsXlabels = par1.get_xticks().tolist()
#pointsTicklabels = []
#for lab in pointsXlabels:
# newtick = float(lab)
# newtickstring = str(float(newtick))
# if newtick.is_integer() :
# newtickstring = str(int(newtick))
par1.set_ylabel('功率(P)(kW)', color="red")
>>>>>>> f5b55f5735c94ec9573668b5d56b78a8eef2e8f7
par1.axis['right'].major_ticklabels.set_visible(True)
par1.axis['right'].label.set_visible(True)
<<<<<<< HEAD
par2.set_ylabel('扬程')
=======
par2.set_ylabel('效率(E)(%)', color="blue")
>>>>>>> f5b55f5735c94ec9573668b5d56b78a8eef2e8f7
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, fm + 1)
<<<<<<< HEAD
host.set_ylim(0, hm + 5)
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)
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()
for i in range (0, len(zcs)):
zcs[i] -= minZ
maxZ = maxZ - minZ + 2
#minZ = minEffZ
host = HostAxes(fig, [0.15, 0.1, 0.65, 0.8])
par1 = ParasiteAxes(host, sharey=host)
par2 = ParasiteAxes(host, sharey=host)
host.parasites.append(par1)
host.parasites.append(par2)
host.set_xlabel("PAD ($m^2.m^{-3}$)")
host.set_ylabel("Height (m)")
host.set_xlim(0, MAX_PAD)
par1.set_xlabel("Average number of returns per 10cm cube voxel")
#par1.set_xlabel("RDI")
par2.set_xlabel("Occusion (%)")
host.axis["top"].set_visible(False)
par1.axis["top"].set_visible(True)
par1.axis["top"].major_ticklabels.set_visible(True)
par1.axis["top"].label.set_visible(True)
#par2.axis["top"].label.set_visible(True)
par1.set_xlim(0,maxVal[2]/maxVal[1]*MAX_PAD)
offset = (0, 40)
new_axisline = par2._grid_helper.new_fixed_axis
par2.axis["top2"] = new_axisline(loc="top", axes=par2, offset=offset)
#host.parasites.append(par2)
#host.set_ylabel("F1 score")
#host.set_xlabel("# Filter size")
host.axis["right"].set_visible(False)
#plt.xticks([])
host.axis["top"].major_ticks.set_color('white')
par1.axis["right"].set_visible(True)
#par1.set_ylabel("Runtime")
par1.axis["right"].major_ticklabels.set_visible(True)
par1.axis["right"].label.set_visible(True)
#par2.set_ylabel("Velocity")
#offset = (60, 0)
#new_axisline = par2.get_grid_helper().new_fixed_axis
#par2.axis["right2"] = new_axisline(loc="right", axes=par2, offset=offset)
fig.add_axes(host)
host.set_xlim(0, 80)
host.set_ylim(0.6, 0.8)
host.set_xlabel("Number of filter size")
host.set_ylabel("F1 score")
par1.set_ylabel("Runtime")
#p1, = host.plot([1, 5, 10, 15, 20, 25, 30, 35, 40,50,60,70,80,90,100], [0.66, 0.736, 0.764, 0.778, 0.786, 0.814, 0.786, 0.783, 0.787,0.791,0.789,0.785,0.790,0.792,0.786], 'o-',label="F1 score", linewidth=2.2, color="#59604C")
#p2, = par1.plot([1, 5, 10, 15, 20, 25, 30, 35, 40,50,60,70,80,90,100], [3.52, 3.68, 3.71, 3.72, 3.84, 3.85, 3.87, 3.96, 3.86,3.876,3.83,3.83,3.89,3.97,4.04], '*--', label="Runtime", linewidth=2.2, color="#A35638")
p1, = host.plot([1, 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80], [
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], [
fig.savefig(path_fig, dpi=300, transparent=True, bbox_inches='tight')
fig1 = plt.figure(1, figsize=(2.5, 1.2))
host = HostAxes(fig1, [0.15, 0.1, 0.65, 0.8])
par1 = ParasiteAxes(host, sharex=host)
host.parasites.append(par1)
host.axis["right"].set_visible(False)
par1.axis["right"].set_visible(True)
par1.axis["right"].major_ticklabels.set_visible(True)
par1.axis["right"].label.set_visible(True)
fig1.add_axes(host)
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,
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()
#ax_wear.set_ylabel('Wear')
load_axisline = ax_load.get_grid_helper().new_fixed_axis
#cp_axisline = ax_cp.get_grid_helper().new_fixed_axis
#wear_axisline = ax_wear.get_grid_helper().new_fixed_axis
ax_load.axis['right2'] = load_axisline(loc='right',
axes=ax_load,
offset=(70, 0))
#ax_cp.axis['right3'] = cp_axisline(loc='right', axes=ax_cp, offset=(80,0))
#ax_wear.axis['right4'] = wear_axisline(loc='right', axes=ax_wear, offset=(120,0))
fig.add_axes(ax_cof)
#set limit of x, y
ax_cof.set_xlim(-3, 21)
ax_cof.set_ylim(0, 200)
curve_cof = ax_cof.plot(data[0],
data[1],
's-',
label="Compress Strength",
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],
