Multiple Plots In A Single Matplotlib Figure

In a Python script, I have a set of 2D NumPy float arrays, let say n1, n2, n3 and n4. For each such array I have two integer values offset_i_x and offset_i_y (replace i by 1, 2, 3

Solution 1:

You may want to consider the add_axes function of matplotlib.pyplot.

Below is a dirty example, based on what you want to achieve. Note that I have chosen values of offsets so the example works. You will have to figure out how to convert the values of the offsets you have for each images in fraction of the figure.

import numpy as np
import matplotlib.pyplot as plt

def make_img_from_data(data, offset_xy, fig_number=1):
    fig.add_axes([0+offset_xy[0], 0+offset_xy[1], 0.5, 0.5])
    plt.imshow(data)

# creation of a dictionary with of 4 2D numpy array# and corresponding offsets (x, y)# offsets for the 4 2D numpy arrays
offset_a_x = 0
offset_a_y = 0
offset_b_x = 0.5
offset_b_y = 0
offset_c_x = 0
offset_c_y = 0.5
offset_d_x = 0.5
offset_d_y = 0.5

data_list = ['a', 'b', 'c', 'd']
offsets_list = [[offset_a_x, offset_a_y], [offset_b_x, offset_b_y],
                [offset_c_x, offset_c_y], [offset_d_x, offset_d_y]]

# dictionary of the data and offsets
data_dict = {f: [np.random.rand(12, 12), values] for f,values in zip(data_list, offsets_list)}

fig = plt.figure(1, figsize=(6,6))

for n in data_dict:
    make_img_from_data(data_dict[n][0], data_dict[n][1])

plt.show()

which produces:

Solution 2:

If I understand correctly, you seem to be looking for subplots. Have a look at the thumbnail gallery for examples.