将x轴拆分为两个以上的部分（Python）

我想把我的x轴分成5个部分。关于如何将其分为两个部分，有很多答案，因此我遵循了相同的策略，但不适用于超过两个部分。 有人曾经成功地将一个轴分成两部分以上吗

import numpy as np
from pylab import *
import matplotlib.pyplot as plt

fig,(ax,ax2,ax3,ax4,ax5) = plt.subplots(1,2,sharey=True)
ax.plot(wvln0,alb0,linestyle='-', marker='o', color='r',linewidth=1.0,label='Haze = 0T')
ax2.plot(wvln0,alb0,linestyle='-', marker='o', color='r',linewidth=1.0,label='Haze = 0T')
ax3.plot(wvln0,alb0,linestyle='-', marker='o', color='r',linewidth=1.0,label='Haze = 0T')
ax4.plot(wvln0,alb0,linestyle='-', marker='o', color='r',linewidth=1.0,label='Haze = 0T')
ax5.plot(wvln0,alb0,linestyle='-', marker='o', color='r',linewidth=1.0,label='Haze = 0T')
ax.set_xlim(0.15,1.10)
ax2.set_xlim(1.15,2.25)
ax3.set_xlim(1.20,1.30)
ax4.set_xlim(1.55,1.65)
ax5.set_xlim(1.95,2.15)

ax.spines['right'].set_visible(False)
ax2.spines['left'].set_visible(False)
ax.yaxis.tick_left()
ax.tick_params(labeltop='off') # don't put tick labels at the top
ax2.yaxis.tick_right()
plt.subplots_adjust(wspace=0.1)

axes = plt.gca()
axes.set_ylim([0.0,0.72])
plt.show()

返回

Traceback (most recent call last):
  File "/Users/jadecheclair/Documents/NASA Ames Research/NASA Codes/Wavlengths_Rages/wvln_alb.py", line 37, in <module>
fig,(ax,ax2,ax3,ax4,ax5) = plt.subplots(1,2,sharey=True)
ValueError: need more than 2 values to unpack

它回来了

Traceback (most recent call last):
  File "/Users/jadecheclair/Documents/NASA Ames Research/NASA Codes/Wavlengths_Rages/wvln_alb.py", line 37, in <module>
fig,(ax,ax2,ax3,ax4,ax5) = plt.subplots(1,2,3,4,5,sharey=True)
TypeError: subplots() got multiple values for keyword argument 'sharey'

问题1 您没有正确调用plt.subplot。这里是默认用法

子地块行=1，ncols=1，sharex=False，sharey=False，挤压=True，子地块宽度=None，gridspec宽度=None，**图宽度

看起来您希望一行中有5个子批次，所以将nrows=1，ncols=5

问题2 您需要正确设置脊椎-您只希望最左侧和最右侧的脊椎可见。使用以下功能可以轻松完成此任务：

def multi_spine_adj( axs):
    axs[0].spines['right'].set_visible(False)
    axs[0].yaxis.tick_left()
    for ax in axs[1:-1]:
        ax.spines['right'].set_visible(False)
        ax.spines['left'].set_visible(False)
    axs[-1].spines['left'].set_visible(False)
    axs[-1].yaxis.tick_right()

#wvln0 = np.linspace( 0,5,50) # make some fake data
#alb0 =  np.random.random(50) #make some fake data 

opts = {'linestyle':'-', 'marker':'o', 'color':'r','linewidth':1,'label':'Haze = 0T'}

fig,axs = plt.subplots(1,5,sharey=True)

xlims = [(0.15,1.10),
        (1.15,2.25),
        (1.20,1.30),
        (1.55,1.65),
        (1.95,2.15)]

for i,ax in enumerate(axs):
    x1,x2 = xlims[i]
    ax.plot(wvln0,alb0,**opts)
    ax.set_xlim(x1,x2)

multi_spine_adj(axs)    
plt.show()

提示 请注意，您可以轻松地在axs上进行迭代，这将使您的代码更干净，如果您想添加更多中断，则更易于修改，例如问题1 您没有正确调用plt.subplot。这里是默认用法

子地块行=1，ncols=1，sharex=False，sharey=False，挤压=True，子地块宽度=None，gridspec宽度=None，**图宽度

看起来您希望一行中有5个子批次，所以将nrows=1，ncols=5

问题2 您需要正确设置脊椎-您只希望最左侧和最右侧的脊椎可见。使用以下功能可以轻松完成此任务：

def multi_spine_adj( axs):
    axs[0].spines['right'].set_visible(False)
    axs[0].yaxis.tick_left()
    for ax in axs[1:-1]:
        ax.spines['right'].set_visible(False)
        ax.spines['left'].set_visible(False)
    axs[-1].spines['left'].set_visible(False)
    axs[-1].yaxis.tick_right()

#wvln0 = np.linspace( 0,5,50) # make some fake data
#alb0 =  np.random.random(50) #make some fake data 

opts = {'linestyle':'-', 'marker':'o', 'color':'r','linewidth':1,'label':'Haze = 0T'}

fig,axs = plt.subplots(1,5,sharey=True)

xlims = [(0.15,1.10),
        (1.15,2.25),
        (1.20,1.30),
        (1.55,1.65),
        (1.95,2.15)]

for i,ax in enumerate(axs):
    x1,x2 = xlims[i]
    ax.plot(wvln0,alb0,**opts)
    ax.set_xlim(x1,x2)

multi_spine_adj(axs)    
plt.show()

提示

---

请注意，您可以轻松地在axs上进行迭代，这使您的代码更干净，如果您想添加更多的中断，则更易于修改。例如，这是一个示例，显示了我如何通过在图形中手动放置三个轴来完成此操作

from __future__ import division, unicode_literals
import matplotlib.pyplot as plt
import numpy as np

plt.close('all')

# ----- PREPARE DATA ----

t = np.arange(0, 7 * 10**5, 10)
x = np.abs(np.sin(t/10.**2)) * 300

# ----- FIG CREATION ----

fig = plt.figure(figsize=(8, 5), facecolor='white')

# Margins (dimensions are in inches):
left_margin = 0.6 / fig.get_figwidth()
right_margin = 0.25 / fig.get_figwidth()
bottom_margin = 0.75 / fig.get_figheight()
top_margin = 0.25 / fig.get_figwidth()
mid_margin = 0.1 / fig.get_figwidth()  # horizontal space between subplots

# ----- DEFINE PARAMETERS FOR EACH AXE ----

# Proportion of the figure's width taken by each axe (the sum must == 1):
f = [0.5, 0.3, 0.2]

xmin = [200, 50, 0]     # xaxis minimum values for each axe
xmax = [8200, 200, 50]  # xaxis maximum values for each axe
xscl = [2000, 50, 10]   # xaxis scale for each axe

ymin, ymax = 0, 320  # yaxis minimum and maximum values

colors = ['green', 'blue', 'red']  # colors of each plot
labels = ['label1', 'label2', 'label3']  # labels of each plot for the legend

Naxes = len(f)  # Total number of axes to add to the figure.

x0, y0 = left_margin, bottom_margin   # origin point of the axe
h = 1 - (bottom_margin + top_margin)  # height of the axe

# total width of the axes:
wtot = 1 - (left_margin + right_margin + (Naxes-1)*mid_margin)

lines = []  # to store handles for generating the legend later on
for i in range(Naxes):

    # ----- AXES CREATION ----

    w = wtot*f[i]  # width of the current axe
    ax = fig.add_axes([x0, y0, w, h], frameon=True, axisbg='none')

    if i == 0:  # First axe to the left
        ax.spines['right'].set_visible(False)
        ax.tick_params(right='off', labelright='off')

    elif i == Naxes-1:  # Last axe to the right
        ax.spines['left'].set_visible(False)
        ax.tick_params(left='off', labelleft='off',
                       right='off', labelright='off')
    else:
        ax.spines['left'].set_visible(False)
        ax.spines['right'].set_visible(False)
        ax.tick_params(left='off', labelleft='off',
                       right='off', labelright='off')

    # origin point of the next axe to be added to the figure:
    x0 += w + mid_margin

    # ----- SETUP XTICKS ----

    if i == Naxes-1:
        xticks = np.arange(xmin[i], xmax[i] + xscl[i]/2, xscl[i])
    else:
        xticks = np.arange(xmin[i]+xscl[i], xmax[i] + xscl[i]/2, xscl[i])
    ax.set_xticks(xticks)
    ax.xaxis.set_ticks_position('bottom')
    ax.tick_params(axis='x', direction='out', labelsize=8)

    xticks_minor = np.arange(xmin[i], xmax[i] + xscl[i]/5., xscl[i] / 5.)
    ax.set_xticks(xticks_minor, minor=True)
    ax.tick_params(axis='x', which='minor', direction='out')

    # ----- PLOT DATA ----

    line, = ax.plot(t, x, color=colors[i])
    lines.append(line)  # for plotting the legend

    ax.axis([xmin[i], xmax[i], ymin, ymax])
    ax.invert_xaxis()

# ---- SET XAXIS LABEL ----

fig.axes[0].set_xlabel('Time (years)', fontsize=12, va='bottom', ha='center')
fig.axes[0].xaxis.set_label_coords(0.5, 0.05, transform=fig.transFigure)

# -----  LEGEND ----

fig.axes[0].legend(lines, labels, loc=(0.1, 0.1), ncol=1, fancybox=True,
                   fontsize=12)

# ----- SHOW FIG ----

fig.savefig('SingleAxeThreeScale.png')
plt.show()

其结果是：

---

这是一个示例，显示了我如何通过在图形中手动放置三个轴来完成此操作

from __future__ import division, unicode_literals
import matplotlib.pyplot as plt
import numpy as np

plt.close('all')

# ----- PREPARE DATA ----

t = np.arange(0, 7 * 10**5, 10)
x = np.abs(np.sin(t/10.**2)) * 300

# ----- FIG CREATION ----

fig = plt.figure(figsize=(8, 5), facecolor='white')

# Margins (dimensions are in inches):
left_margin = 0.6 / fig.get_figwidth()
right_margin = 0.25 / fig.get_figwidth()
bottom_margin = 0.75 / fig.get_figheight()
top_margin = 0.25 / fig.get_figwidth()
mid_margin = 0.1 / fig.get_figwidth()  # horizontal space between subplots

# ----- DEFINE PARAMETERS FOR EACH AXE ----

# Proportion of the figure's width taken by each axe (the sum must == 1):
f = [0.5, 0.3, 0.2]

xmin = [200, 50, 0]     # xaxis minimum values for each axe
xmax = [8200, 200, 50]  # xaxis maximum values for each axe
xscl = [2000, 50, 10]   # xaxis scale for each axe

ymin, ymax = 0, 320  # yaxis minimum and maximum values

colors = ['green', 'blue', 'red']  # colors of each plot
labels = ['label1', 'label2', 'label3']  # labels of each plot for the legend

Naxes = len(f)  # Total number of axes to add to the figure.

x0, y0 = left_margin, bottom_margin   # origin point of the axe
h = 1 - (bottom_margin + top_margin)  # height of the axe

# total width of the axes:
wtot = 1 - (left_margin + right_margin + (Naxes-1)*mid_margin)

lines = []  # to store handles for generating the legend later on
for i in range(Naxes):

    # ----- AXES CREATION ----

    w = wtot*f[i]  # width of the current axe
    ax = fig.add_axes([x0, y0, w, h], frameon=True, axisbg='none')

    if i == 0:  # First axe to the left
        ax.spines['right'].set_visible(False)
        ax.tick_params(right='off', labelright='off')

    elif i == Naxes-1:  # Last axe to the right
        ax.spines['left'].set_visible(False)
        ax.tick_params(left='off', labelleft='off',
                       right='off', labelright='off')
    else:
        ax.spines['left'].set_visible(False)
        ax.spines['right'].set_visible(False)
        ax.tick_params(left='off', labelleft='off',
                       right='off', labelright='off')

    # origin point of the next axe to be added to the figure:
    x0 += w + mid_margin

    # ----- SETUP XTICKS ----

    if i == Naxes-1:
        xticks = np.arange(xmin[i], xmax[i] + xscl[i]/2, xscl[i])
    else:
        xticks = np.arange(xmin[i]+xscl[i], xmax[i] + xscl[i]/2, xscl[i])
    ax.set_xticks(xticks)
    ax.xaxis.set_ticks_position('bottom')
    ax.tick_params(axis='x', direction='out', labelsize=8)

    xticks_minor = np.arange(xmin[i], xmax[i] + xscl[i]/5., xscl[i] / 5.)
    ax.set_xticks(xticks_minor, minor=True)
    ax.tick_params(axis='x', which='minor', direction='out')

    # ----- PLOT DATA ----

    line, = ax.plot(t, x, color=colors[i])
    lines.append(line)  # for plotting the legend

    ax.axis([xmin[i], xmax[i], ymin, ymax])
    ax.invert_xaxis()

# ---- SET XAXIS LABEL ----

fig.axes[0].set_xlabel('Time (years)', fontsize=12, va='bottom', ha='center')
fig.axes[0].xaxis.set_label_coords(0.5, 0.05, transform=fig.transFigure)

# -----  LEGEND ----

fig.axes[0].legend(lines, labels, loc=(0.1, 0.1), ncol=1, fancybox=True,
                   fontsize=12)

# ----- SHOW FIG ----

fig.savefig('SingleAxeThreeScale.png')
plt.show()

其结果是：

---

我建议编辑以添加matplotlib标记。希望您能通过这种方式获得更多相关的视图。查看plt.subplot的文档-您给它行、列作为轴。试试fig，ax，ax2，ax3，ax4，ax5=plt。子批1,5，sharey=True。我建议编辑以添加matplotlib标记。希望您能通过这种方式获得更多相关的视图。查看plt.subplot的文档-您给它行、列作为轴。尝试fig，ax，ax2，ax3，ax4，ax5=plt。子批1,5，sharey=True。