如何检查对象是否为“matplotlib.collectives.PolyCollection”类型

gt0wga4j  于 2023-08-06  发布在  其他
关注(0)|答案(1)|浏览(83)

对于一个特定的任务（Link），我想检查一个对象是否是：

matplotlib.collections.PolyCollection

字符串
或a：

matplotlib.lines.Line2D

型
对象。
我把它累成这样：

if isinstance(handle, matplotlib.collections.PolyCollection):

型
但这并不奏效。如果要测试两个变量h和句柄是否属于同一类型，我如何检查它们是否都是 matplotlib.collections.PolyCollection 或 matplotlib.lines.Line2D 对象？

编辑1

下面是有问题的代码，它适应了上面链接中的解决方案：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
import math

def is_inlist(handle, handles):
    for h in handles:
        if h.get_color() == handle.get_color() and \
            h.get_linestyle() == handle.get_linestyle() and \
            h.get_marker() == handle.get_marker():
            return True
    return False

lines=[]
labels=[]
legend_properties = {'weight':'bold','size':10}  
# Example data

mu = 0
mu2 = 5
variance = 1
variance2 = 2
sigma = math.sqrt(variance)
sigma2 = math.sqrt(variance2)
x = np.linspace(mu-3*variance,mu+3*variance, 100)
x2 = np.linspace(mu2-3*variance2,mu2+3*variance2, 100)

nrows = 4
# Plot

fig, axis = plt.subplots(nrows, sharex=True, sharey=False, figsize=(5, 8))
fig.subplots_adjust(hspace=0.0001)
#fig.suptitle("Stacked Plots with global Legend which contains to little elements",fontsize=14,weight='bold')

axis[0].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[0].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[0].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[0].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[0].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[1].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[1].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[1].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[1].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[1].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='yellow',alpha=0.5,label="PEAK5", interpolate=True)
axis[1].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[2].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[2].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[2].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK3", interpolate=True)
axis[2].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[2].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[3].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[3].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[3].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[3].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[3].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK5", interpolate=True)
axis[3].fill_between(x+5.5,0,mlab.normpdf(x, mu, sigma), color='violet',alpha=0.5,label="PEAK6", interpolate=True)
axis[3].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)





for i in range(nrows):
    h, l = axis[i].get_legend_handles_labels()
    for hi, li in zip(h,l):
        if not is_inlist(hi, lines):
            lines.append(hi)
            labels.append(li)
           



#x for x in item if x not in Z







            
# only 3 Legend entrys Label1 , Label2 and Label3 are visible .. Differences in cloors and markers are ignored
plt.legend(handles=lines, labels=labels,bbox_to_anchor=(0., nrows+.02, 1., .102), loc=3,ncol=3, prop=legend_properties,mode="expand", borderaxespad=0.,frameon=False,framealpha=0.0) 

plt.show()

型
不幸的是，它给了我错误：

Traceback (most recent call last):
      File "PATH..../.py", line 76, in <module>
        if not is_inlist(hi, lines):
      File "PATH..../.py", line 9, in is_inlist
        if h.get_color() == handle.get_color() and \
    AttributeError: 'PolyCollection' object has no attribute 'get_color'

型
有人建议我为每种类型的matplotlib对象做一个案例分析。这就是我奋斗的地方。我想改变“is_inlist”函数，以适应不同的情况。但案例分析本身还不起作用：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
import math

def is_inlist(handle, handles):
    for h in handles:
        if isinstance(handle, matplotlib.collections.PolyCollection) and isinstance(h, matplotlib.collections.PolyCollection):
            if h.get_color() == handle.get_color() and \
                h.get_linestyle() == handle.get_linestyle() and \
                h.get_marker() == handle.get_marker():
                return True
        if isinstance(handle, matplotlib.lines.Line2D) and isinstance(h, matplotlib.lines.Line2D):
            if h.get_color() == handle.get_color() and \
                h.get_linestyle() == handle.get_linestyle() and \
                h.get_marker() == handle.get_marker():
                return True        
                
                
    return False

lines=[]
labels=[]
legend_properties = {'weight':'bold','size':10}  
# Example data

mu = 0
mu2 = 5
variance = 1
variance2 = 2
sigma = math.sqrt(variance)
sigma2 = math.sqrt(variance2)
x = np.linspace(mu-3*variance,mu+3*variance, 100)
x2 = np.linspace(mu2-3*variance2,mu2+3*variance2, 100)

nrows = 4
# Plot

fig, axis = plt.subplots(nrows, sharex=True, sharey=False, figsize=(5, 8))
fig.subplots_adjust(hspace=0.0001)
#fig.suptitle("Stacked Plots with global Legend which contains to little elements",fontsize=14,weight='bold')

axis[0].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[0].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[0].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[0].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[0].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[1].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[1].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[1].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[1].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[1].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='yellow',alpha=0.5,label="PEAK5", interpolate=True)
axis[1].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[2].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[2].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[2].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK3", interpolate=True)
axis[2].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[2].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[3].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[3].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[3].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[3].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[3].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK5", interpolate=True)
axis[3].fill_between(x+5.5,0,mlab.normpdf(x, mu, sigma), color='violet',alpha=0.5,label="PEAK6", interpolate=True)
axis[3].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)


for i in range(nrows):
    h, l = axis[i].get_legend_handles_labels()
    for hi, li in zip(h,l):
        if not is_inlist(hi, lines):
            lines.append(hi)
            labels.append(li)
           



# only 3 Legend entrys Label1 , Label2 and Label3 are visible .. Differences in cloors and markers are ignored
plt.legend(handles=lines, labels=labels,bbox_to_anchor=(0., nrows+.02, 1., .102), loc=3,ncol=3, prop=legend_properties,mode="expand", borderaxespad=0.,frameon=False,framealpha=0.0) 

plt.show()

型
我得到的错误是：

Traceback (most recent call last):
      File "Path/.. .py", line 84, in <module>
        if not is_inlist(hi, lines):
      File "Path/.. .py", line 9, in is_inlist
        if isinstance(handle, matplotlib.collections.PolyCollection) and isinstance(handle, matplotlib.collections.PolyCollection):
    NameError: global name 'matplotlib' is not defined

型

编辑2

我补充道：

import matplotlib.collections

型
正如我所建议的

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
import math
import matplotlib.collections

def is_inlist(handle, handles):
    for h in handles:
        if isinstance(handle, matplotlib.collections.PolyCollection) and isinstance(h, matplotlib.collections.PolyCollection):
            if h.get_facecolor() == handle.get_facecolor() and \
                h.get_linestyle() == handle.get_linestyle() and \
                h.get_alpha() == handle.get_alpha():
                return True
        if isinstance(handle, matplotlib.lines.Line2D) and isinstance(h, matplotlib.lines.Line2D):
            if h.get_color() == handle.get_color() and \
                h.get_linestyle() == handle.get_linestyle() and \
                h.get_marker() == handle.get_marker():
                return True        
                
                
    return False

lines=[]
labels=[]
legend_properties = {'weight':'bold','size':10}  
# Example data

mu = 0
mu2 = 5
variance = 1
variance2 = 2
sigma = math.sqrt(variance)
sigma2 = math.sqrt(variance2)
x = np.linspace(mu-3*variance,mu+3*variance, 100)
x2 = np.linspace(mu2-3*variance2,mu2+3*variance2, 100)

nrows = 4
# Plot

fig, axis = plt.subplots(nrows, sharex=True, sharey=False, figsize=(5, 8))
fig.subplots_adjust(hspace=0.0001)
#fig.suptitle("Stacked Plots with global Legend which contains to little elements",fontsize=14,weight='bold')

axis[0].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[0].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[0].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[0].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[0].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[1].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[1].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[1].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[1].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[1].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='yellow',alpha=0.5,label="PEAK5", interpolate=True)
axis[1].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[2].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[2].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[2].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK3", interpolate=True)
axis[2].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[2].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[3].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[3].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[3].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[3].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[3].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK5", interpolate=True)
axis[3].fill_between(x+5.5,0,mlab.normpdf(x, mu, sigma), color='violet',alpha=0.5,label="PEAK6", interpolate=True)
axis[3].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)


for i in range(nrows):
    h, l = axis[i].get_legend_handles_labels()
    for hi, li in zip(h,l):
        if not is_inlist(hi, lines):
            lines.append(hi)
            labels.append(li)
           



# only 3 Legend entrys Label1 , Label2 and Label3 are visible .. Differences in cloors and markers are ignored
plt.legend(handles=lines, labels=labels,bbox_to_anchor=(0., nrows-1+.02, 1., .102), loc=3,ncol=3, prop=legend_properties,mode="expand", borderaxespad=0.,frameon=False,framealpha=0.0) 

plt.show()

型
我现在得到的错误是：

Traceback (most recent call last):
      File "Path/.. .py", line 80, in <module>
        if not is_inlist(hi, lines):
      File "Dath/.. .py", line 10, in is_inlist
        if h.get_facecolor() == handle.get_facecolor() and \
    ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

型

解决方案基于ImportanceOfBeingErnest的解释：

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
import math
import matplotlib.collections

def is_inlist(handle, handles):
    for h in handles:
        if isinstance(handle, matplotlib.collections.PolyCollection) and isinstance(h, matplotlib.collections.PolyCollection): 
            if np.all(h.get_facecolor() == handle.get_facecolor()) and \
                np.all(h.get_linestyle() == handle.get_linestyle()) and \
                np.all(h.get_alpha() == handle.get_alpha()):
                return True
        elif isinstance(handle, matplotlib.lines.Line2D) and isinstance(h, matplotlib.lines.Line2D):
            if h.get_color() == handle.get_color() and \
                h.get_linestyle() == handle.get_linestyle() and \
                h.get_marker() == handle.get_marker():
                return True        
                
                
    return False

lines=[]
labels=[]
legend_properties = {'weight':'bold','size':10}  
# Example data

mu = 0
mu2 = 5
variance = 1
variance2 = 2
sigma = math.sqrt(variance)
sigma2 = math.sqrt(variance2)
x = np.linspace(mu-3*variance,mu+3*variance, 100)
x2 = np.linspace(mu2-3*variance2,mu2+3*variance2, 100)

nrows = 4
# Plot

fig, axis = plt.subplots(nrows, sharex=True, sharey=False, figsize=(5, 8))
fig.subplots_adjust(hspace=0.0001)
#fig.suptitle("Stacked Plots with global Legend which contains to little elements",fontsize=14,weight='bold')

axis[0].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[0].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[0].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[0].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[0].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[1].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[1].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[1].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[1].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[1].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='yellow',alpha=0.5,label="PEAK5", interpolate=True)
axis[1].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[2].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[2].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='orange',alpha=0.5,label="PEAK2", interpolate=True)
axis[2].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK3", interpolate=True)
axis[2].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[2].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)

axis[3].fill_between(x+6,0,mlab.normpdf(x, mu, sigma), color='green',alpha=0.5,label="PEAK1", interpolate=True)
axis[3].fill_between(x+4,0,mlab.normpdf(x, mu, sigma), color='purple',alpha=0.5,label="PEAK2", interpolate=True)
axis[3].fill_between(x+3,0,mlab.normpdf(x, mu, sigma), color='blue',alpha=0.5,label="PEAK3", interpolate=True)
axis[3].fill_between(x+7,0,mlab.normpdf(x, mu, sigma), color='red',alpha=0.5,label="PEAK4", interpolate=True)
axis[3].fill_between(x+6.5,0,mlab.normpdf(x, mu, sigma), color='#73d216',alpha=0.5,label="PEAK5", interpolate=True)
axis[3].fill_between(x+5.5,0,mlab.normpdf(x, mu, sigma), color='violet',alpha=0.5,label="PEAK6", interpolate=True)
axis[3].plot(x2,2.5*mlab.normpdf(x2, mu2, sigma2),color='black',linestyle="",label="Exp", marker="o", markersize=4)


for i in range(nrows):
    h, l = axis[i].get_legend_handles_labels()
    for hi, li in zip(h,l):
        if not is_inlist(hi, lines):
            lines.append(hi)
            labels.append(li)
           



# only 3 Legend entrys Label1 , Label2 and Label3 are visible .. Differences in cloors and markers are ignored
plt.legend(handles=lines, labels=labels,bbox_to_anchor=(0., nrows-1+.02, 1., .102), loc=3,ncol=3, prop=legend_properties,mode="expand", borderaxespad=0.,frameon=False,framealpha=0.0) 

plt.show()

型

matplotlib

1条答案

按热度按时间
wgx48brx

wgx48brx1#

最初问题的解决方案是实际导入为比较提供类的模块。
你只是缺少import matplotlib.collections。
下一个错误其实是不言自明的。它说不可能比较两个数组。
所以我们假设
h的面颜色为[[ 0., 0.50196078, 0., 0.5]]，并且
handle的面色为[[ 1., 0.64705882, 0., 0.5]]，则
h.get_facecolor() == handle.get_facecolor()的结果为[[False False True True]]
现在，两次假和两次真是真还是假？谁也不知道。因此，您需要使用any()或all()来决定是要知道是否有任何元素为True，还是所有元素都为True。
在这里，您可能希望检查是否有相同的颜色，因此使用all：

np.all(h.get_facecolor() == handle.get_facecolor())

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