Matplotlib python hold on

Matplotlib python hold on

Matplotlib.pyplot.hold () is ‘3.1.2’, which is the default setting of hold on,

Then,
module ‘matplotlib.pyplot’ has no attribute ‘hold’
It becomes.
How do I hold off without changing the version?

Hold machinery
Setting or unsetting hold (deprecated in version 2.0) has now been completely removed.Matplotlib now always behaves as if hold = True. To clear an axes you can manually use cla (), or to clear an entire figure use clf ().

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matplotlib.pyplot.hold with it’s examples

In this post, we will learn about matplotlib.pyplot.hold but before going right to it let’s understand briefly what matplot is.

The Matplotlib library allows you to plot data in two dimensions. Matplotlib allows users to plot graphs easily, a low-level Python library. . We can use it freely from online sources. Matplotlib is mostly used in python along with c and c++ but only to some extent. Easy things become easy with Matplotlib, and hard things become possible with Matplotlib.

Installation of Matplotlib:

Follow the below-given command to install Matplotlib in your system if you already have python and pip installed.

Importing Matplotlib:

After installing matplotlib you can import your code by using the import command below:

Matplotlib is now ready for our use.

pyplot:

Matplotlib is a library that has pyplot as its submodule and most services of Matplotlib lie under it. But how will you import it? Follow the given code:

import matplotlib.pyplot as plt # Henceforth, Pyplot will be called plt.

Example:

import matplotlib.pyplot as plt import numpy as np x_coordiantes = np.array([0, 10]) y_coordinates = np.array([0, 200]) plt.plot(x_coordinates, y_coordinates) plt.show()

Output:

matplotlib.pyplot.hold:

Now, what is .hold? The hold function behaves the same way as in matplotlib and pyplot. A plot command set to ‘on’ will display a new plot on top of the existing plot without clearing the current one. In this way, incremental plotting is possible.

hold() # toggle hold hold(True) # hold is on hold(False) # hold is off

Example:

lines = plot(linestyle='-', color='red') lines = plot(linestyle='-', color='blue', hold='on')

Python version 3.0 deprecates the .hold mechanism. The behavior will remain consistent with the long-time default value of True. The current plot axes will be added to subsequent plot commands when .hold is True. When you then plot the next command, the figure and current axis will be cleared if the hold was set to false.

Do you want to learn how we plot a line graph from a NumPy array? Follow this tutorial: Plotting of line graph from NumPy array

Know more about Numpy from this tutorial: How does NumPy.histogram2d works in Python

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How to hold plot figures in Python

You have to keep explicit handle to matplotlib figure and/or set to in config. Some graphs are generated inside a loop, and these are plotted separately from and : Solution 1: Just call at the end: Solution 2: You can use the following: Solution 3: The feature is switched on by default in .

How to hold plot figures in Python

I have this code, where c_X,c_Y,c_Z,X,Y,Z X_2,Y_2,Z_2,X_4,Y_4,Z_4, are lists of points (my data).

import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D for i in range (2): fig = plt.figure(i) ax = fig.add_subplot(111, projection='3d') ax.scatter(c_X,c_Y,c_Z, color = 'midnightblue') ax.scatter(X, Y, Z, color = 'mediumaquamarine') ax.scatter(X_2,Y_2,Z_2, color = 'cadetblue') ax.scatter(X_4,Y_4,Z_4, color = 'cadetblue') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.draw() 

How can i hold or get the 3 plots, in 3 different figures, in the end ?

Modify your code as suggested in the comments to your question.

import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D for i in range (2): fig = plt.figure(i) ax = fig.add_subplot(111, projection='3d') ax.scatter(c_X,c_Y,c_Z, color = 'midnightblue') ax.scatter(X, Y, Z, color = 'mediumaquamarine') ax.scatter(X_2,Y_2,Z_2, color = 'cadetblue') ax.scatter(X_4,Y_4,Z_4, color = 'cadetblue') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.show() 

I think this does what you want.

If you have only 4 figures you can just use:

fig = plt.figure() ax = Axes3D(fig) ax.scatter(c_X,c_Y,c_Z, color = 'midnightblue') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.show() fig = plt.figure() ax = Axes3D(fig) ax.scatter(X, Y, Z, color = 'mediumaquamarine') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.show() fig = plt.figure() ax = Axes3D(fig) ax.scatter(X_2,Y_2,Z_2, color = 'cadetblue') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.show() fig = plt.figure() ax = Axes3D(fig) ax.scatter(X_4,Y_4,Z_4, color = 'cadetblue') ax.set_xlabel('x') ax.set_ylabel('y') ax.set_zlabel('z') plt.show() 

Or you can merge your arrays into one for X, one for Y and one for Z. Create a list for the color and use a loop:

c = ['color1', 'color2', etc] for i in range(k): plt.figure() ax = Axes3D(fig) ax.scatter(X[i], Y[i], Z[i], color=c[i]) plt.show() 

Multiple plots in one figure in Python, you can make different sizes in one figure as well, use slices in that case: gs = gridspec.GridSpec (3, 3) ax1 = plt.subplot (gs [0,:]) # row 0 (top) spans all (3) columns. consult the docs for more help and examples. This little bit i typed up for myself once, and is very much based/copied from the docs as well.

Python equivalent to ‘hold on’ in Matlab

Is there an explicit equivalent command in Python’s matplotlib for Matlab’s hold on ? I’m trying to plot all my graphs on the same axes. Some graphs are generated inside a for loop, and these are plotted separately from su and sl :

import numpy as np import matplotlib.pyplot as plt for i in np.arange(1,5): z = 68 + 4 * np.random.randn(50) zm = np.cumsum(z) / range(1,len(z)+1) plt.plot(zm) plt.axis([0,50,60,80]) plt.show() n = np.arange(1,51) su = 68 + 4 / np.sqrt(n) sl = 68 - 4 / np.sqrt(n) plt.plot(n,su,n,sl) plt.axis([0,50,60,80]) plt.show() 

Just call plt.show() at the end:

import numpy as np import matplotlib.pyplot as plt plt.axis([0,50,60,80]) for i in np.arange(1,5): z = 68 + 4 * np.random.randn(50) zm = np.cumsum(z) / range(1,len(z)+1) plt.plot(zm) n = np.arange(1,51) su = 68 + 4 / np.sqrt(n) sl = 68 - 4 / np.sqrt(n) plt.plot(n,su,n,sl) plt.show() 

You can use the following:

The hold on feature is switched on by default in matplotlib.pyplot . So each time you evoke plt.plot() before plt.show() a drawing is added to the plot. Launching plt.plot() after the function plt.show() leads to redrawing the whole picture.

check pyplot docs. For completeness,

import numpy as np import matplotlib.pyplot as plt #evenly sampled time at 200ms intervals t = np.arange(0., 5., 0.2) # red dashes, blue squares and green triangles plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^') plt.show() 

Graph Plotting in Python, Following steps were followed: Define the x-axis and corresponding y-axis values as lists. Plot them on canvas using .plot () function. Give a name to x-axis and y-axis using .xlabel () and .ylabel () functions. Give a title to your plot using .title () function. Finally, to view your plot, we use .show () function.

Python 3 pyplot.hold is deprecated

I would like to use the pyplot.hold(True) since I want to draw a contour plot on a scatter plot. When I use the below code, it has the warning that pyplot.hold is deprecated . Is there any other option in Python 3 or I just ignore the warning? Thank you very much.

plt.scatter(X[:, 0], X[:, 1], s=150, c='b', marker='x', linewidths=1) plt.hold(True) plt.contour(X1, X2, Z, np.power(10,(np.arange(-20, 0.1, 3)).T)) plt.hold(False) 

Matplotlib does not erase any content from a figure by itself. The concept of hold is hence not necessary in matplotlib and will be removed.

Your code should therefore look like

Possibly followed by plt.savefig(..) or plt.show() .

Python — Is there a way to detach matplotlib plots so that, import matplotlib.pyplot as plt #code generating the plot in a loop or function #saving the plot plt.savefig(var+’_plot.png’,bbox_inches=’tight’, dpi=250) #you can allways reopen the plot using os.system(var+’_plot.png’) # unfortunately .png allows no interaction. #the following avoids plot blocking the execution …

Hold is not working for pyplot

I have a problem using pyplot. I am new to Python so sorry if I am doing some obvious mistake.

After I have plotted something using pyplot it shows the graph, but when I then try and add e.g. ylabel it will not update the current graph. It results in a new graph with only the ylabel, not previously entered information. So to me it seems to be a problem with recognizing the current graph/axis, but the ishold delivers a True statement.

My setup is Python 2.7 in Python(x,y). The problem occurs both in the Spyder IDE and the IPython Qt Console. It does however not occur in the regular IPython console (which, by constrast, is not interactive, but everything is included when using show(). When I turn off interactive in Spyder/Qt console it does not show anything after using the show() command).

import matplotlib.pyplot as plt plt.plot([1,2,3,4]) Out[2]: []  plt.ylabel('test') Out[3]:  plt.ishold() Out[4]: True matplotlib.get_backend() Out[6]: 'module://IPython.kernel.zmq.pylab.backend_inline' 

Hope any of you have some input. Thanks.

This is one of the things were InlineBackend have to behave differently from other backend or you would have sort of a memory leak. You have to keep explicit handle to matplotlib figure and/or set close_figure to False in config. Usually pyplot is a compatibility layer for matlab for convenience, try to learn to do using the Object Oriented way.

fig,ax = subplots() ax.plot(range(4)) ax.set_ylabel('my label') . 

Python — Keep a figure «on hold» after running a script, Keep a figure «on hold» after running a script. from pylab import * from numpy import * time=linspace (-pi,pi,10000) ycos=cos (time) ysin=sin (time) plot (time,ycos) plot (time,ysin) show () If I do all these steps via an Ipython terminal, I can keep the figure open and interact with it.

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[python] Python equivalent to ‘hold on’ in Matlab

Is there an explicit equivalent command in Python’s matplotlib for Matlab’s hold on ? I’m trying to plot all my graphs on the same axes. Some graphs are generated inside a for loop, and these are plotted separately from su and sl :

import numpy as np import matplotlib.pyplot as plt for i in np.arange(1,5): z = 68 + 4 * np.random.randn(50) zm = np.cumsum(z) / range(1,len(z)+1) plt.plot(zm) plt.axis([0,50,60,80]) plt.show() n = np.arange(1,51) su = 68 + 4 / np.sqrt(n) sl = 68 - 4 / np.sqrt(n) plt.plot(n,su,n,sl) plt.axis([0,50,60,80]) plt.show() 

The answer is

Just call plt.show() at the end:

import numpy as np import matplotlib.pyplot as plt plt.axis([0,50,60,80]) for i in np.arange(1,5): z = 68 + 4 * np.random.randn(50) zm = np.cumsum(z) / range(1,len(z)+1) plt.plot(zm) n = np.arange(1,51) su = 68 + 4 / np.sqrt(n) sl = 68 - 4 / np.sqrt(n) plt.plot(n,su,n,sl) plt.show() 

You can use the following:

The hold on feature is switched on by default in matplotlib.pyplot . So each time you evoke plt.plot() before plt.show() a drawing is added to the plot. Launching plt.plot() after the function plt.show() leads to redrawing the whole picture.

check pyplot docs. For completeness,

import numpy as np import matplotlib.pyplot as plt #evenly sampled time at 200ms intervals t = np.arange(0., 5., 0.2) # red dashes, blue squares and green triangles plt.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^') plt.show() 

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