Multiple plots from function Matplotlib

Question

(Adjusted to suggestions) I already have a function that performs some plot:

def plot_i(Y, ax = None): if ax == None: ax = plt.gca() fig = plt.figure() ax.plot(Y) plt.close(fig) return fig

And I wish to use this to plot in a grid for n arrays. Let's assume the grid is (n // 2, 2) for simplicity and that n is even. At the moment, I came up with this:

def multi_plot(Y_arr, function): n = len(Y_arr) fig, ax = plt.subplots(n // 2, 2) for i in range(n): # assign to one axis a call of the function = plot_i that draws a plot plt.close(fig) return fig

Unfortunately, what I get if I do something like:

# inside the loop plot_i(Y[:, i], ax = ax[k,j])

Is correct but I need to close figures each time at the end, otherwise I keep on adding figures to plt. Is there any way I can avoid calling each time plt.close(fig)?

Not sure I understand what exactly you are looking for. But matplotlib has here a good example of how to distribute N subplots in an n x m grid. — Mr. T
– Mr. T, Commented Dec 27, 2021 at 20:17
@Mr.T I already have a way to distribute the plots, this one is easier and I will implement it. However, checking the link, what id done for each ax is ax.plot. I wish to call my personal plotting function for each ax. Doing so, I would be able to call this multi_plot for different functions. — simonegiancola09
– simonegiancola09, Commented Dec 27, 2021 at 20:20
Pass plot_i an ax parameter and switch to the object-oriented interface within it. — BigBen
– BigBen, Commented Dec 27, 2021 at 20:20
@BigBen I tried, but still do not understand how to do this, could you explain with an example? I tried setting ax = None as parameter in plot_i, which if None get the current axis with plt.gca(). In the multi_plot function, I then pass the axis parameter as the axis of interest, but yet it prints each single plot and does not return a fig object that contains all of them. Will edit the question accordingly. — simonegiancola09
– simonegiancola09, Commented Dec 27, 2021 at 20:29
@BigBen I actually solved the first issue, thank you for the clarification!!! — simonegiancola09
– simonegiancola09, Commented Dec 27, 2021 at 20:42

azelcer · Accepted Answer · 2021-12-28 19:11:24Z

If I understand correctly, you are looking for something like this:

import numpy as np import matplotlib.pyplot as plt def plot_i(Y, ax=None): if ax == None: ax = plt.gca() ax.plot(Y) return def multi_plot(Y_arr, function, n_cols=2): n = Y_arr.shape[1] fig, ax = plt.subplots(n // n_cols + (1 if n % n_cols else 0), n_cols) for i in range(n): # assign to one axis a call of the function = plot_i that draws a plot function(Y_arr[:, i], ax = ax[i//n_cols, i%n_cols]) return fig if __name__ == '__main__': x = np.linspace(0,12.6, 100) # let's create some fake data data = np.exp(-np.linspace(0,.5, 14)[np.newaxis, :] * x[:, np.newaxis]) * np.sin(x[:, np.newaxis]) fig = multi_plot(data, plot_i, 3)

Be careful when using gca(): it will create a new figure if there is no figure active.

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