seaborn.distplot has been DEPRECATED in seaborn 0.11 and is replaced with the following: displot(), a figure-level function with a similar flexibility over the kind of plot to draw. This is a FacetGrid, and does not have the ax parameter, so it will not work with matplotlib.pyplot.subplots. histplot(), an axes-level function for plotting histograms, including with … Read more
ax.clear() clears the axes. That is, it removes all settings and data from the axes such that you are left with an axes, just as it had been just created. ax.axis(“off”) turns the axes off, such that all axes spines and ticklabels are hidden. ax.set_visible(False) turns the complete axes invisible, including the data that is … Read more
If you want to remove the axis spines, but not the other information (ticks, labels, etc.), you can do that like so: fig, ax = plt.subplots(7,1, sharex=True) t = np.arange(0, 1, 0.01) for i, a in enumerate(ax): a.plot(t, np.sin((i + 1) * 2 * np.pi * t)) a.spines[“top”].set_visible(False) a.spines[“right”].set_visible(False) a.spines[“bottom”].set_visible(False) or, more easily, using seaborn: … Read more
Look at the code and comments in it: import matplotlib.pyplot as plt import numpy as np from matplotlib import gridspec # Simple data to display in various forms x = np.linspace(0, 2 * np.pi, 400) y = np.sin(x ** 2) fig = plt.figure() # set height ratios for subplots gs = gridspec.GridSpec(2, 1, height_ratios=[2, 1]) … Read more
To display the multiple images use subplot() plt.figure() #subplot(r,c) provide the no. of rows and columns f, axarr = plt.subplots(4,1) # use the created array to output your multiple images. In this case I have stacked 4 images vertically axarr[0].imshow(v_slice[0]) axarr[1].imshow(v_slice[1]) axarr[2].imshow(v_slice[2]) axarr[3].imshow(v_slice[3])
Global title: In newer releases of matplotlib one can use Figure.suptitle() method of Figure: import matplotlib.pyplot as plt fig = plt.gcf() fig.suptitle(“Title centered above all subplots”, fontsize=14) Alternatively (based on @Steven C. Howell’s comment below (thank you!)), use the matplotlib.pyplot.suptitle() function: import matplotlib.pyplot as plt # plot stuff # … plt.suptitle(“Title centered above all subplots”, … Read more
The problem is the use of aspect=”equal”, which prevents the subplots from stretching to an arbitrary aspect ratio and filling up all the empty space. Normally, this would work: import matplotlib.pyplot as plt ax = [plt.subplot(2,2,i+1) for i in range(4)] for a in ax: a.set_xticklabels([]) a.set_yticklabels([]) plt.subplots_adjust(wspace=0, hspace=0) The result is this: However, with aspect=”equal”, … Read more
plt.subplot returns a subplot object which is a type of axes object. It has two methods for adding axis labels: set_xlabel and set_ylabel: ax = plt.subplot(‘111’) ax.set_xlabel(‘X Axis’) ax.set_ylabel(‘Y Axis’) You could also call plt.xlabel and plt.ylabel (like you did before) and specify the axes to which you want the label applied. ax = plt.subplot(‘111’) … Read more
Set the xlim and ylim properties on the Artist object by matplotlib.pyplot.setp() https://matplotlib.org/3.1.0/api/_as_gen/matplotlib.pyplot.setp.html # Importing matplotlib.pyplot package. import matplotlib.pyplot as plt # Assigning ‘fig’, ‘ax’ variables. fig, ax = plt.subplots(2, 2) # Defining custom ‘xlim’ and ‘ylim’ values. custom_xlim = (0, 100) custom_ylim = (-100, 100) # Setting the values for all axes. plt.setp(ax, xlim=custom_xlim, … Read more
Use plt.sca(ax) to set the current axes, where ax is the Axes object you’d like to become active.