How to check if object is of type “matplotlib.coll

问题:

For a specific task ( Link ) i want to check if an object is a :

matplotlib.collections.PolyCollection

or a:

matplotlib.lines.Line2D

object.

I tired it like this:

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

but this did not work. If would want to test if two variables h and handles are of the same type how would i check them both to bei either matplotlib.collections.PolyCollection or matplotlib.lines.Line2D objects?

Edit1

Here is the code in question wich adapts the solution in the above link:

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 wich 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()

unfortunately it gives me the error :

    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'

I was suggested to do a case analysis for each type of matplotlib object. this is where i struggle. I wanted to change the "is_inlist" function and to work for different cases. but the case analysis itself does not work yet:

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 wich 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()

The error i get is:

    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

Edit2

I added :

import matplotlib.collections

as i was suggested

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 wich 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()

The error i get now is:

    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()

solution based on the explanation of ImportanceOfBeingErnest:

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 wich 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()

回答1:

The solution to the initial problem is to actually import the module which provides the class for comparisson.

You simply lack import matplotlib.collections.

The next error is actually pretty self-explanatory. It says that it's impossible to compare two arrays.

So let's say the
facecolor of h is [[ 0., 0.50196078, 0., 0.5]] and the
facecolor of handle is [[ 1., 0.64705882, 0., 0.5]], then
h.get_facecolor() == handle.get_facecolor() results in [[False False True True]]

Now, is two times false and two times true true or false? One cannot know. Therefore you need to use either any() or all() to decide if you want to know if any of the elements is True or if all of the elements are True.

Here you would want to check for the same color, thus use all:

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