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fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2) for a 2 x 2 array. This is most useful for two subplots (e.g.: fig, (ax1, ax2) = plt.subplots(1, 2) or fig, (ax1, ax2) = plt.subplots(2, 1)). For more subplots, it's more efficient to flatten and iterate through the array of axes.
pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. For more advanced use cases you can use GridSpec for a more general subplot layout or Figure.add_subplot for adding subplots at arbitrary locations within the figure.
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.
subplots() is the recommended method to generate simple subplot arrangements: fig , ( ax1 , ax2 ) = plt . subplots ( 2 , 1 ) fig . suptitle ( 'A tale of 2 subplots' ) ax1 . plot ( x1 , y1 , 'o-' ) ax1 . set_ylabel ( 'Damped oscillation' ) ax2 . plot ( x2 , y2 , '.-' ) ax2 . set_xlabel ( 'time (s)' ) ax2 . set_ylabel ( 'Undamped' ) plt . show ()
# using the variable ax for single a Axes fig, ax = plt. subplots # using the variable axs for multiple Axes fig, axs = plt. subplots (2, 2) # using tuple unpacking for multiple Axes fig, (ax1, ax2) = plt. subplots (1, 2) fig, ((ax1, ax2), (ax3, ax4)) = plt. subplots (2, 2)
To go beyond a regular grid to subplots that span multiple rows and columns, plt.GridSpec() is the best tool. The plt.GridSpec() object does not create a plot by itself; it is simply a convenient interface that is recognized by the plt.subplot() command.
To go beyond a regular grid to subplots that span multiple rows and columns, plt.GridSpec is the best tool. plt.GridSpec does not create a plot by itself; it is rather a convenient interface...
