Example figure creation

figure.py

# All sizes are in fraction of the figure size

figsize = (6, 7.5)
f = plt.figure(figsize=figsize)

# borders
top_edge = .03
bot_edge = .055
l_edge = .15
r_edge = .01

# gaps between panels
h_gap = .05
v0_gap = .05
v1_gap = .06

# confusion matrix and bottom panel
width_cm = .625
bot_height = .175
bot_width = 1. - l_edge - r_edge

# Make confusion matrix square
height_cm = width_cm * figsize[0] / figsize[1]

# Dendrogram axis
height_d = 1 - bot_edge - bot_height - v0_gap - height_cm - v1_gap - top_edge
r0_y = bot_edge + bot_height + v0_gap + height_cm + v1_gap
x0 = l_edge
ax0 = f.add_axes([x0, r0_y, width_cm, height_d])

width = 1 - l_edge - width_cm - h_gap - r_edge
# Distance plot
x1 = x0 + width_cm + h_gap
ax1 = f.add_axes([x1,  r0_y, width, height_d])

r1_y = bot_edge + bot_height + v1_gap
# Colorbar
x2 = x1 + width + h_gap
cax = f.add_axes([l_edge, r1_y - .45 * v1_gap, .075, .02])
# Confusion matrix
ax2 = f.add_axes([l_edge, r1_y, width_cm, height_cm])
# CV accuracies
width = 1 - l_edge - width_cm - h_gap - r_edge
ax3 = f.add_axes([l_edge + width_cm + h_gap, r1_y, width, height_cm])

# Correlations
ax4 = f.add_axes([l_edge, bot_edge, bot_width, bot_height])