As I needed something similar for my work, I put some effort into automating the process of grouping plots into figures depending on the display medium. At first I had the idea to do each plot only once and just add the subplots to the figures to be saved in the pdf, but sadly, according to a comment in this answer, this is not possible, so everything needs to be re-plotted. The code shows the general idea of how this can be automated using PdfPages:
from matplotlib import pyplot as plt
import numpy as np
from matplotlib.backends.backend_pdf import PdfPages
def niter(iterable, n):
"""
Function that returns an n-element iterator, i.e.
sub-lists of a list that are max. n elements long.
"""
pos = 0
while pos < len(iterable):
yield iterable[pos:pos+n]
pos += n
def plot_funcs(x, functions, funcnames, max_col, max_row):
"""
Function that plots all given functions over the given x-range,
max_col*max_row at a time, creating all needed figures while doing
so.
"""
##amount of functions to put in one plot
N = max_col*max_row
##created figures go here
figs = []
##plotted-on axes go here
used_axes = []
##looping through functions N at a time:
for funcs, names in zip(niter(functions, N), niter(funcnames,N)):
##figure and subplots
fig, axes = plt.subplots(max_col, max_row)
##plotting functions
for name,func,ax in zip(names, funcs, axes.reshape(-1)):
ax.plot(x, func(x))
ax.set_title(name)
used_axes.append(ax)
##removing empty axes:
for ax in axes.reshape(-1):
if ax not in used_axes:
ax.remove()
fig.tight_layout()
figs.append(fig)
return figs
##some functions to display
functions = [
lambda x: x, lambda x: 1-x, lambda x: x*x, lambda x: 1/x, #4
np.exp, np.sqrt, np.log, np.sin, np.cos, #5
]
funcnames = ['x','1-x', 'x$^2$', '1/x', 'exp', 'sqrt', 'log', 'sin','cos']
##layout for display on the screen
disp_max_col = 3
disp_max_row = 2
##layout for pdf
pdf_max_col = 2
pdf_max_row = 4
##displaying on the screen:
x = np.linspace(0,1,100)
figs = plot_funcs(x, functions, funcnames, disp_max_row, disp_max_col)
plt.show()
##saving to pdf if user wants to:
answer = input('Do you want to save the figures to pdf?')
if answer in ('y', 'Y', 'yes', ''):
##change number of subplots
N = disp_max_col*disp_max_row
figs = plot_funcs(x, functions, funcnames, pdf_max_row, pdf_max_col)
##from https://matplotlib.org/examples/pylab_examples/multipage_pdf.html
with PdfPages('multipage_pdf.pdf') as pdf:
for fig in figs:
plt.figure(fig.number)
pdf.savefig()
The core function, plot_funcs takes max_col and max_row keywords and then creates figures with the according amount of subplots. It then loops through a given list of functions to be plotted, each on its own subplot. Unused subplots are removed. Finally a list of all figures is returned.
In my example, I have 9 different functions, which I first show on the screen in a 2x3 layout (making a total of two figures, one with 6 subplots and one with 3 subplots). If the user is happy, the plots are redone in a 2x4 layout (again two figures, but this time one with 8 subplots and 1 with 1 subplot) and then saved to a file called multipage_pdf.pdf, following the example in the documentation.
Tested on python 3.5
