Preparing differently sized plot panels, labelled with proper genetics nomenclature, using matplotlib.

plotDemo.py

import matplotlib as mp
import matplotlib.pyplot as plt
import numpy as np
import string

# Set font for figure according to journal specs
mp.rcParams['font.family'] = "Arial"

# Gene deletion names read from file might not necessarily be in lower case
gnames=["EXO1","RAD9","TMA20"]

# Convert to standard genetics nomenclature: lowercase with delta (set italics below)
stdgens=[gname.lower()+r"$\Delta$" for gname in gnames]

# Varying plot sizes
plotsizes=[[6,12],[6,6],[6,6]]

# Different colours
cmap=plt.get_cmap("Paired") # http://matplotlib.org/examples/color/colormaps_reference.html
colors = [cmap(i) for i in np.linspace(0, 1, len(gnames))]

for i,(plotsize,gname) in enumerate(zip(plotsizes,stdgens)):
    # Generate some fake data to plot
    t=np.random.normal(0,1,100)
    x=np.random.normal(0,1,100)

    plt.figure(figsize=plotsize)
    plt.scatter(t,x,edgecolors="face",c=colors[i])
    plt.xlim(-5,5)
    plt.ylim(-5,5)
    plt.xlabel("t",fontsize=24)
    plt.ylabel("x(t)",fontsize=24)
    plt.tick_params(axis="both",size=12,labelsize=16)
    plt.title(gname,fontsize=24,style="italic") # Specify font style here
    panel_label=string.ascii_uppercase[i]
    plt.savefig("plotDemo{}.pdf".format(panel_label))