我使用matplotlib.pyplot制作带有几个子图的图。这就是我最终想要的:一个2x2阵列的"主要"地块。每个曲线在图中都有两条曲线,每条曲线使用不同的y轴。另外,我希望每一个都有一个较小的插图。
到目前为止,我已经使用了这个工作示例代码获得了第一部分:
import matplotlib.pyplot as plt
import numpy as np
import os
import shutil
import time
import sys
#Simplest working example of tight_layout and plots problem
def two_scales(ax1, time, data1, data2, c1, c2, xlabel, y1label, y2label):
ax2 = ax1.twinx()
ax1.plot(time, data1, color=c1)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(y1label)
ax2.plot(time, data2, color=c2)
ax2.set_ylabel(y2label)
return ax1, ax2
# Change color of each axis
def color_y_axis(ax, color):
"""Color your axes."""
for t in ax.get_yticklabels():
t.set_color(color)
return None
def insetPlots():
t = np.arange(0.01, 10.0, 0.01)
#Figure stuff
fig, baseAxes = plt.subplots(2,2,figsize=(10, 6))
baseAxesFlattened = baseAxes.flatten()
for i, dat in enumerate(baseAxesFlattened):
s1 = np.exp((i+1)*t)
s2 = .3*np.sin((i+1)*.2 * np.pi * t)
#Plotting them together
tempAx1, tempAx2 = two_scales(baseAxesFlattened[i], t, s1, s2, 'b', 'r','heyheyhey','yayaya','woopwoop')
#Changing the color of the axes
color_y_axis(tempAx1, 'b')
color_y_axis(tempAx2, 'r')
plt.tight_layout()
#plt.figure(figsize=(6, 8))
picname="/mypath/testtesttest.png"
plt.savefig(picname)
insetPlots()
到目前为止产生了这个,很好:
现在我想添加插图。我可以很容易地做到这一点:
import matplotlib.pyplot as plt
import numpy as np
import os
import shutil
import time
import sys
#Simplest working example of tight_layout and plots problem
def two_scales(ax1, time, data1, data2, c1, c2, xlabel, y1label, y2label):
ax2 = ax1.twinx()
ax1.plot(time, data1, color=c1)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(y1label)
ax2.plot(time, data2, color=c2)
ax2.set_ylabel(y2label)
return ax1, ax2
# Change color of each axis
def color_y_axis(ax, color):
"""Color your axes."""
for t in ax.get_yticklabels():
t.set_color(color)
return None
def insetPlots():
t = np.arange(0.01, 10.0, 0.01)
#Figure stuff
fig, baseAxes = plt.subplots(2,2,figsize=(10, 6))
baseAxesFlattened = baseAxes.flatten()
for i, dat in enumerate(baseAxesFlattened):
s1 = np.exp((i+1)*t)
s2 = .3*np.sin((i+1)*.2 * np.pi * t)
#Plotting them together
tempAx1, tempAx2 = two_scales(baseAxesFlattened[i], t, s1, s2, 'b', 'r','heyheyhey','yayaya','woopwoop')
#Changing the color of the axes
color_y_axis(tempAx1, 'b')
color_y_axis(tempAx2, 'r')
pos = tempAx1.get_position()
#print(pos)
posString = str(pos)
x0Ind, y0Ind, x1Ind, y1Ind = posString.find('x0'),posString.find('y0'),posString.find('x1'),posString.find('y1')
#print(x0Ind, y0Ind, x1Ind, y1Ind)
x0, y0, x1, y1 = float(posString[x0Ind+3:y0Ind-2]), float(posString[y0Ind+3:x1Ind-2]), float(posString[x1Ind+3:y1Ind-2]), float(posString[y1Ind+3:-1])
#print(x0, y0, x1, y1)
mainPlotW = x1 - x0
mainPlotH = y1 - y0
w, h = 0.3*mainPlotW, 0.25*mainPlotH
left, bottom, width, height = [x0 + .15*mainPlotW, y0 + .7*mainPlotH, w, h]
insetAx = fig.add_axes([left, bottom, width, height])
#insetAx.plot(range(6)[::-1], color='green')
s3 = np.sin(.2 * np.pi * t/(i+1))
insetAx.plot(t,s3, color='green')
#plt.tight_layout()
#plt.figure(figsize=(6, 8))
picname="/mypath/testtesttest.png"
plt.savefig(picname)
insetPlots()
请注意,我在这里注释了tight_layout()。这产生了这个,它在我想要的位置有插图:
因此,这个插图位于正确的位置,但由于tight_layout()消失,主要图的轴标签重叠。如果我有tight_layout()(那么,与上面的代码完全相同,但是该行没有注释),我得到了这个:
主要情节'轴不再重叠,但插图现在处于错误的位置。我运行代码时也会收到此警告:
/usr/local/lib/python3.6/dist-packages/matplotlib/figure.py:2022: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.
warnings.warn("This figure includes Axes that are not compatible "
我怎样才能让它们都起作用?我怀疑我做了一些简单的错误,比如以错误的方式放置插图。
编辑:我找到了一个解决方案,但它很难看,我希望不是"正确的"这样做的方式。我怀疑tight_layout()正在移动东西,因此插入图的位置(取决于主要图块的位置)相对于tight_layout()之后的主要图形变得混乱。所以我通过绘制主要情节,进行严格布局,然后添加插图来解决问题:import matplotlib.pyplot as plt
import numpy as np
import os
import shutil
import time
import sys
#Simplest working example of tight_layout and plots problem
def two_scales(ax1, time, data1, data2, c1, c2, xlabel, y1label, y2label):
ax2 = ax1.twinx()
ax1.plot(time, data1, color=c1)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(y1label)
ax2.plot(time, data2, color=c2)
ax2.set_ylabel(y2label)
return ax1, ax2
# Change color of each axis
def color_y_axis(ax, color):
"""Color your axes."""
for t in ax.get_yticklabels():
t.set_color(color)
return None
def insetPlots():
t = np.arange(0.01, 10.0, 0.01)
#Figure stuff
fig, baseAxes = plt.subplots(2,2,figsize=(10, 6))
baseAxesFlattened = baseAxes.flatten()
majorAxes = []
for i, dat in enumerate(baseAxesFlattened):
s1 = np.exp((i+1)*t)
s2 = .3*np.sin((i+1)*.2 * np.pi * t)
#Plotting them together
tempAx1, tempAx2 = two_scales(baseAxesFlattened[i], t, s1, s2, 'b', 'r','heyheyhey','yayaya','woopwoop')
majorAxes.append(tempAx1)
#Changing the color of the axes
color_y_axis(tempAx1, 'b')
color_y_axis(tempAx2, 'r')
plt.tight_layout()
for i, dat in enumerate(baseAxesFlattened):
tempAx1 = majorAxes[i]
pos = tempAx1.get_position()
#print(pos)
posString = str(pos)
x0Ind, y0Ind, x1Ind, y1Ind = posString.find('x0'),posString.find('y0'),posString.find('x1'),posString.find('y1')
#print(x0Ind, y0Ind, x1Ind, y1Ind)
x0, y0, x1, y1 = float(posString[x0Ind+3:y0Ind-2]), float(posString[y0Ind+3:x1Ind-2]), float(posString[x1Ind+3:y1Ind-2]), float(posString[y1Ind+3:-1])
#print(x0, y0, x1, y1)
mainPlotW = x1 - x0
mainPlotH = y1 - y0
w, h = 0.3*mainPlotW, 0.25*mainPlotH
left, bottom, width, height = [x0 + .15*mainPlotW, y0 + .7*mainPlotH, w, h]
insetAx = fig.add_axes([left, bottom, width, height])
#insetAx.plot(range(6)[::-1], color='green')
s3 = np.sin(.2 * np.pi * t/(i+1))
insetAx.plot(t,s3, color='green')
#plt.tight_layout()
#plt.figure(figsize=(6, 8))
picname="/mypath/testtesttest.png"
plt.savefig(picname)
insetPlots()
有更简洁的方法吗?
答案 0 :(得分:0)
tight_layout()
只是大多数常见情节的有用工具,但不能处理所有情况。
在您的特定情况下,我认为您最好在创建嵌入轴之前调用tight_layout()
,并使用生成的轴位置为您的插图找到正确的坐标
import matplotlib.pyplot as plt
import numpy as np
import os
import shutil
import time
import sys
#Simplest working example of tight_layout and plots problem
def two_scales(ax1, time, data1, data2, c1, c2, xlabel, y1label, y2label):
ax2 = ax1.twinx()
ax1.plot(time, data1, color=c1)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(y1label)
ax2.plot(time, data2, color=c2)
ax2.set_ylabel(y2label)
return ax1, ax2
# Change color of each axis
def color_y_axis(ax, color):
"""Color your axes."""
for t in ax.get_yticklabels():
t.set_color(color)
return None
def insetPlots():
t = np.arange(0.01, 10.0, 0.01)
#Figure stuff
fig, baseAxes = plt.subplots(2,2,figsize=(10, 6))
baseAxesFlattened = baseAxes.flatten()
for i, ax in enumerate(baseAxesFlattened):
s1 = np.exp((i+1)*t)
s2 = .3*np.sin((i+1)*.2 * np.pi * t)
#Plotting them together
tempAx1, tempAx2 = two_scales(ax, t, s1, s2, 'b', 'r','heyheyhey','yayaya','woopwoop')
#Changing the color of the axes
color_y_axis(tempAx1, 'b')
color_y_axis(tempAx2, 'r')
fig.tight_layout()
for i, ax in enumerate(baseAxesFlattened):
pos = ax.get_position()
#print(pos)
mainPlotW = pos.x1 - pos.x0
mainPlotH = pos.y1 - pos.y0
w, h = 0.3*mainPlotW, 0.25*mainPlotH
left, bottom, width, height = [pos.x0 + .15*mainPlotW, pos.y0 + .7*mainPlotH, w, h]
insetAx = fig.add_axes([left, bottom, width, height])
insetAx.plot(range(6)[::-1], color='green')
s3 = np.sin(.2 * np.pi * t/(i+1))
insetAx.plot(t,s3, color='green')
insetPlots()
PS 您使用pos
变量做了一些非常奇怪的事情,在将其转换回str
之前将其转换为float
。我在代码中的第二个循环中简化了代码
答案 1 :(得分:0)
我建议使用mpl_toolkits.axes_grid1.inset_locator.InsetPosition
来定位插图。这简化了很多事情,不需要将绘图大小与任何东西相乘。
然后您可以选择在创建插图之前或之后调用fig.tight_layout()
,结果绘图不会更改(尽管在发出警告后调用它,在这种情况下您可以忽略)。
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1.inset_locator import InsetPosition
import numpy as np
def two_scales(ax1, time, data1, data2, c1, c2, xlabel, y1label, y2label):
ax2 = ax1.twinx()
ax1.plot(time, data1, color=c1)
ax1.set_xlabel(xlabel)
ax1.set_ylabel(y1label)
ax2.plot(time, data2, color=c2)
ax2.set_ylabel(y2label)
return ax1, ax2
# Change color of each axis
def color_y_axis(ax, color):
"""Color your axes."""
for t in ax.get_yticklabels():
t.set_color(color)
return None
def insetPlots():
t = np.arange(0.01, 10.0, 0.01)
#Figure stuff
fig, baseAxes = plt.subplots(2,2,figsize=(10, 6))
baseAxesFlattened = baseAxes.flatten()
for i, ax in enumerate(baseAxesFlattened):
s1 = np.exp((i+1)*t)
s2 = .3*np.sin((i+1)*.2 * np.pi * t)
#Plotting them together
tempAx1, tempAx2 = two_scales(ax, t, s1, s2, 'b', 'r',
'heyheyhey','yayaya','woopwoop')
#Changing the color of the axes
color_y_axis(tempAx1, 'b')
color_y_axis(tempAx2, 'r')
fig.tight_layout()
for i, ax in enumerate(baseAxesFlattened):
insetAx = fig.add_axes([0, 0, 1, 1], label="{}".format(i))
ip = InsetPosition(ax, [.15, 0.7, 0.3, 0.25]) #posx, posy, width, height
insetAx.set_axes_locator(ip)
insetAx.plot(range(6)[::-1], color='green')
s3 = np.sin(.2 * np.pi * t/(i+1))
insetAx.plot(t,s3, color='green')
# putting tight_layout here will produce a warning,
# yet the resulting plot is the same
# fig.tight_layout()
insetPlots()
plt.show()