loop over 2d subplot as if it's a 1-D

Question

I'm trying to plot many data using subplots and I'm NOT in trouble but I'm wondering if there is a convenience method to do this.

below is the sample code.

import numpy as np    
import math 
import matplotlib.pyplot as plt

quantities=["sam_mvir","mvir","rvir","rs","vrms","vmax"
,"jx","jy","jz","spin","m200b","m200c","m500c","m2500c"
,"xoff","voff","btoc","ctoa","ax","ay","az"]

# len(quantities) = 21, just to make the second loop expression 
# shorter in this post.

ncol = 5
nrow = math.ceil(21 / ncol)

fig, axes = plt.subplots(nrows = nrow, ncols=ncol, figsize=(8,6))

for i in range(nrow):
    for j in range(((21-i*5)>5)*5 + ((21-i*5)<5)*(21%5)):
        axes[i, j].plot(tree[quantities[i*ncol + j]]) 
        axes[i, j].set_title(quantities[i*ncol + j])

This code loops over a 2D array of subplots and stops at the 21st plot leaving 4 panels empty. My question is that, is there any built-in method to do this task? For example, make 2D subplot array and "flatten" the array into 1D then loop over 1D array through 0 to 20.

The expression in the second range() is very ugly. I don't think I'm going to use this code. I think the trivial way is to count the number of plots and break if count > 21. But I just wonder if there is a better (or fancy) way.

Answer 1

subplots returns an ndarray of axes objects, you can just flatten or ravel it:

fig, axes = plt.subplots(nrows = nrow, ncols=ncol, figsize=(8,6))
for ax in axes.flatten()[:20]:
    # do stuff to ax