gpt4 book ai didi

python - 在子图中显示两个数据集 `ax2.set_xticklabels`

转载 作者:太空宇宙 更新时间:2023-11-04 04:41:31 28 4
gpt4 key购买 nike

我的上部子图显示了两个数据集:orangegreen

以下代码显示了绿色数据集的xtick标签,

在上部子图的ax2轴(图中标记为X2的轴):

ind_pos_Pd3 = [0, 4, 8, 12, 16]
axarr[0].set_xticks(X1_green[ind_pos_Pd3])
ax2.set_xticks(X1_green[ind_pos_Pd3])
ax2.set_xticklabels(["%.2f" % i for i in X2_green[ind_pos_Pd3]])

enter image description here

相反,下面的代码显示了orange数据集的xtick标签,

在上部子图的ax2轴(图中标记为X2的轴):

ind_pos_Bd3 = [0, 4, 8, 12, 16, 20, 24, 28, 32]
axarr[0].set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticklabels(["%.2f" % i for i in X2_orange[ind_pos_Bd3]])

enter image description here

有没有办法“混合”这两种方案并实现一个分为两个面板的 ax2 轴:“下面板”填充绿色数据集的标签,“上面板” panel"填充了来自橙色数据集的标签?

类似于:

enter image description here

我在想这个伪代码:

ind_pos_Bd3 = [0, 4, 8, 12, 16, 20, 24, 28, 32]
ind_pos_Pd3 = [0, 4, 8, 12, 16]

axarr[0].set_xticks(X1_orange[ind_pos_Bd3])
axarr[0].set_xticks(X1_green[ind_pos_Pd3])

ax2.set_xticks(X1_green[ind_pos_Pd3])

ax2.set_xticklabels(["%.2f \n %.2f" % i for i in zip(X2_orange[ind_pos_Bd3], X1_green[ind_pos_Pd3]])

但是,"%.2f\n %.2f" 方案不起作用。

最小工作示例:

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick

X1_orange = np.array([ 10., 30.1, 50.2, 70.3, 90.4, 110.51, 130.61, 150.71, 170.81,
190.91, 211.01, 231.11, 251.21, 271.31, 291.41, 311.52, 331.62, 351.72,
371.82, 391.92, 412.02, 432.12, 452.22, 472.32, 492.42, 512.53, 532.63,
552.73, 572.83, 592.93, 613.03, 633.13, 653.23])

X2_orange = np.array([ 2.56691976, 2.5781089 , 2.59624855, 2.62275805, 2.64568568, 2.66607658,
2.6959714 , 2.7231501 , 2.75529391, 2.78894345, 2.81573712, 2.84711104,
2.88437499, 2.9191375 , 2.95033337, 2.99340594, 3.02206115, 3.06383265,
3.08649135, 3.12707204, 3.18500195, 3.24240915, 3.25965166, 3.36137181,
3.35468811, 3.42661704, 3.46254097, 3.61136855, 3.65505401, 3.89043407,
3.80421353, 3.79380128, 4.01570509])

X1_green = np.array([ 10. , 30.1 , 50.2 , 70.3 , 90.4 , 110.51, 130.61, 150.71, 170.81,
190.91, 211.01, 231.11, 251.21, 271.31, 291.41, 311.52, 331.62])

X2_green = np.array([ 1.9894731 , 2.00259207, 2.01875725, 2.04333825, 2.07700656, 2.09629866,
2.14727031, 2.17488234, 2.2499103 , 2.2698862 , 2.31607409, 2.41452705,
2.50847008, 2.61117044, 2.70657103, 3.25283819, 3.31585812])

Y0_orange = np.array([-1.87483583, -1.82358431, -1.78627169, -1.75242213, -1.7299256 , -1.69363695,
-1.64623615, -1.59656948, -1.56967972, -1.55058869, -1.51874314, -1.45673839,
-1.40554361, -1.39904184, -1.35322104, -1.33906865, -1.30865871, -1.28099683,
-1.24897269, -1.19802619, -1.17268543, -1.13523614, -1.09290541, -1.05642197,
-1.00189406, -0.95390527, -0.90890049, -0.82522042, -0.76334378, -0.64504498,
-0.62782754, -0.47358849, -0.49772039])

Y0_green = np.array([-1.97113854, -1.92908192, -1.84404067, -1.75333855, -1.67575628, -1.58010168,
-1.48746063, -1.40770641, -1.31802444, -1.2302243 , -1.14927205, -1.04251178,
-0.91661452, -0.82924669, -0.65075739, -0.37715382, -0.21349827])

##### THREE SUBPLOTS::

###### Y0 plot:
f, axarr = plt.subplots(3, sharex=True, figsize=(11,5))
axarr[0].plot(X1_orange, Y0_orange, linestyle='--', marker="o", markersize=6, color='orange')
axarr[0].plot(X1_green, Y0_green, linestyle='--', marker="o", markersize=6, color='green')
axarr[0].set_ylabel('Y0', fontsize=15)

# Create a new axis:
axarr[0].grid()
ax2 = axarr[0].twiny()

# Make the ax1-ticks and ax1-tick-labels match the line color (blue):
axarr[0].tick_params('x', colors='blue')

# Make the ax2-ticks and ax2-tick-labels match the red color:
# this only controls the font and color of label
ax2.set_xlabel('x2', fontsize=14, color='red')
# this also adds the numbers on top of the tics,
# but sets the colors of the tics
ax2.tick_params('x', colors='orange')

# Set xlimits of ax2 the same as ax1
ax2.set_xlim(axarr[0].get_xlim())

# Set ticks at desired position
ind_pos_Bd3 = [0, 4, 8, 12, 16, 20, 24, 28, 32]
axarr[0].set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticklabels(["%.2f" % i for i in X2_orange[ind_pos_Bd3]])

#ind_pos_Pd3 = [0, 4, 8, 12, 16]
#axarr[0].set_xticks(X1_green[ind_pos_Pd3])
#ax2.set_xticks(X1_green[ind_pos_Pd3])
#ax2.set_xticklabels(["%.2f" % i for i in X2_green[ind_pos_Pd3]])


# Just to align the Delta_V ylabel to the other 3 ylabel's
labelx = -0.075 # very close to the plot
axarr[0].yaxis.set_label_coords(labelx, 0.5, transform=None)


##### Y1 plot:
#f, axarr = plt.subplots(3, sharex=True)
axarr[1].set_ylabel('Y1', fontsize=15)

# Create a new axis:
axarr[1].grid()
ax2 = axarr[1].twiny()

# Make the ax1-ticks and ax1-tick-labels match the line color (blue):
axarr[1].tick_params('x', colors='blue')

# Make the ax2-ticks and ax2-tick-labels match the red color:
ax2.tick_params('x', colors='red')
ax2.set_xticklabels([]) # disable the tic labels

# Set xlimits of ax2 the same as ax1
ax2.set_xlim(axarr[1].get_xlim())

# Set ticks at desired position
ind_pos_Bd3 = [0, 4, 8, 12, 16, 20, 24, 28, 32]
axarr[1].set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticks(X1_orange[ind_pos_Bd3])

# Label ticks of ax2 with values from X2
#ax2.set_xticklabels(["%.2f" % i for i in P])
axarr[1].yaxis.set_major_formatter(mtick.FormatStrFormatter('%1.e'))

#### Y2 plot:
axarr[2].set_ylabel('Y2', fontsize=15)

# Create a new axis:
axarr[2].grid()
ax2 = axarr[2].twiny()

# Make the ax1-ticks and ax1-tick-labels match the line color (blue):
axarr[2].tick_params('x', colors='blue')

# Make the ax2-ticks and ax2-tick-labels match the red color:
axarr[2].set_xlabel('X1', fontsize=14, color='blue')
# this also adds the numbers on top of the tics,
# but sets the colors of the tics
axarr[2].tick_params('x', colors='blue')

# Make the ax2-ticks and ax2-tick-labels match the red color:
ax2.tick_params('x', colors='red')
ax2.set_xticklabels([]) # disable the tic labels

# Set xlimits of ax2 the same as ax1
ax2.set_xlim(axarr[2].get_xlim())

# Set ticks at desired position
ind_pos_Bd3 = [0, 4, 8, 12, 16, 20, 24, 28, 32]
axarr[2].set_xticks(X1_orange[ind_pos_Bd3])
ax2.set_xticks(X1_orange[ind_pos_Bd3])

# Label ticks of ax2 with values from X2
axarr[2].yaxis.set_major_formatter(mtick.FormatStrFormatter('%1.e'))


plt.show()

最佳答案

诀窍是为您想要的每行刻度标签添加一个新的双轴。

然后您可以在 tick_params 中设置 pad 参数来正确定位它们。

请允许我将您的示例缩小一点以便于理解

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick

fig, ax = plt.subplots(figsize=(12,2))

np.random.seed(42)
x0 = np.arange(50)
y0 = np.random.rand(50)
x1 = np.arange(30)
y1 = np.random.rand(30) + 0.7

ax.plot(x0, y0, ls='--', marker='o', ms=6, color='orange')
ax.grid(True)
ax.tick_params('x', colors='blue')
ax.set_xlabel('x1', fontsize=14, color='blue')
ax.set_ylabel('y', fontsize=14)

tax1 = ax.twiny()
tax1.set_xlim(ax.get_xlim())
tax1.tick_params('x', colors='orange', pad=14)
tax1.set_xlabel('x2', fontsize=14, color='red', labelpad=6)

tax2 = ax.twiny()
tax2.set_xlim(ax.get_xlim())
tax2.plot(x1, y1, ls='--', marker='o', ms=6, color='green')
tax2.tick_params('x', colors='green')
tax2.set_xticks([0, 10, 20, 30])

fig.savefig('img.png', pad_inches=0, bbox_inches='tight')

enter image description here

正如您在评论中指出的那样,该图的一个问题是您得到了绿色和橙色的刻度线,并且您希望它们像 x2 标签一样显示为红色。

您可以在 tick_params 中设置 length=0 隐藏绿色刻度线,先用红色绘制橙色刻度线,然后将标签颜色设置为橙色。

修改后的代码

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as mtick

fig, ax = plt.subplots(figsize=(12,2))

np.random.seed(42)
x0 = np.arange(50)
y0 = np.random.rand(50)
x1 = np.arange(30)
y1 = np.random.rand(30) + 0.7

ax.plot(x0, y0, ls='--', marker='o', ms=6, color='orange')
ax.grid(True)
ax.tick_params('x', colors='blue')
ax.set_xlabel('x1', fontsize=14, color='blue')
ax.set_ylabel('y', fontsize=14)

tax1 = ax.twiny()
tax1.set_xlim(ax.get_xlim())
tax1.tick_params('x', colors='red', pad=14)
tax1.set_xlabel('x2', fontsize=14, color='red', labelpad=6)
[x.set_color("orange") for x in tax1.get_xticklabels()]

tax2 = ax.twiny()
tax2.set_xlim(ax.get_xlim())
tax2.plot(x1, y1, ls='--', marker='o', ms=6, color='green')
tax2.tick_params('x', colors='green', pad=6, length=0)
tax2.set_xticks([0, 10, 20, 30])

fig.savefig('img2.png', pad_inches=0, bbox_inches='tight')

enter image description here

关于python - 在子图中显示两个数据集 `ax2.set_xticklabels`,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/50517103/

28 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com