How To Draw In The Same Figure Each Loop

How to update a plot on same figure during the loop?

Nosotros tin use matplotlib to update a plot on every iteration during the loop. With the help of matplotlib.pyplot.describe() office we tin can update the plot on the same effigy during the loop.

Using matplotlib.pyplot.draw(): It is used to update a figure that has been changed. It volition redraw the current figure.

Syntax: figure.canvas.draw()

Before this nosotros use figure.ion() function to run a GUI event loop. Without using figure.ion() we may not be able to come across the GUI plot.

Approach:

In the given instance firstly nosotros are importing all the necessary libraries that we are going to employ. And then creating X and Y. X holds the values from 0 to 10 which evenly spaced into 100 values. due east.g. we are creating values from 2 to 3 with evenly spaced 5 values (np.linspace(2, three, v)) It should output like these five values from 2 to 3 evenly spaced array([two , 2.25, two.five , 2.75, 3 ]). Afterward that we are initializing GUI using plt.ion() function, now we take to create a subplot, then we can plot Ten and Y values. After that we are running a for loop up to some iterations and creating a new_y values which concord our updating value then we are updating the values of X and Y using set_xdata() and set_ydata(). And canvass.draw() volition plot the updated values and canvas.flush_events() holds the GUI upshot till the UI events have been candy. This will run till the loop ends and values will be updated continuously.

Code:

Python3

                import                numpy as np              
                import                time              
                import                matplotlib.pyplot as plt              
                x                                =                np.linspace(                0                ,                                10                ,                                100                )              
                y                                =                np.sin(x)              
                plt.ion()              
                figure, ax                                =                plt.subplots(figsize                =                (                10                ,                                viii                ))              
                line1,                                =                ax.plot(x, y)              
                plt.championship(                "Geeks For Geeks"                , fontsize                =                xx                )              
                plt.xlabel(                "X-centrality"                )              
                plt.ylabel(                "Y-centrality"                )              
                for                _                                in                range                (                50                ):              
                                new_y                                =                np.sin(x                -                0.v                *                _)              
                                line1.set_xdata(x)              
                                line1.set_ydata(new_y)              
                                figure.sail.draw()              
                                figure.canvass.flush_events()              
                                time.sleep(                0.1                )              

Output:

Updating plot

Here, figure.sail.flush_events() is used to clear the former figure before plotting the updated figure.

Example 2: In this example lawmaking, nosotros are updating the value of y in a loop using set_xdata() and redrawing the figure every fourth dimension using canvas.draw().

Python3

                from                math                                import                pi              
                import                matplotlib.pyplot as plt              
                import                numpy equally np              
                import                time              
                x                                =                np.linspace(                1                ,                                thousand                ,                                5000                )              
                y                                =                np.random.randint(                one                ,                                1000                ,                                5000                )              
                plt.ion()              
                fig                                =                plt.figure()              
                ax                                =                fig.add_subplot(                111                )              
                line1,                                =                ax.plot(x, y)              
                plt.xlabel(                "X-axis"                )              
                plt.ylabel(                "Y-axis"                )              
                plt.title(                "Updating plot..."                )              
                for                _                                in                range                (                fifty                ):              
                                line1.set_xdata(ten                *                _)              
                                line1.set_ydata(y)              
                                fig.canvass.draw()              
                                fig.canvass.flush_events()              
                                time.sleep(                0.1                )              