Multiprocess Plotting In Matplotlib

How can one visualize data using matplotlib by a function in parallel? I.e. I want to create figures in parallel processes and then display them in the main process. Here is an exa

Solution 1:

The linked question's answer hides the start of the code in a if __name__ == "__main__": clause. Hence the following should work here.

import pandas as pd
import matplotlib.pyplot as plt

import multiprocessing
#multiprocessing.freeze_support() # <- may be required on windows

df = pd.DataFrame(data={'i':['A','A','B','B'],
                       'x':[1.,2.,3.,4.],
                       'y':[1.,2.,3.,4.]})
df.set_index('i', inplace=True)
df.sort_index(inplace=True)

# function which creates a figure from the data
def Draw(df, i):
    fig, ax  = plt.subplots()
    df = df.loc[i,:]
    ax.scatter(df['x'], df['y'])
    plt.show()

# creating figures in parallel
args = [(df,'A'), (df,'B')]

def multiP():
    for a in args:
        p = multiprocessing.Process(target=Draw, args=a)
        p.start()

if __name__ == "__main__":         
    multiP()