def summarize(gt, agg):
"""Scatterplot matrix of aggregated phenotypes vs genotypes."""
for i, ai in enumerate(agg.dtype.names):
for j, gj in enumerate(gt.dtype.names):
spij(len(agg.dtype.names), len(gt.dtype.names), i, j)
plt.plot(gt[gj], agg[ai], 'o')
xmin, xmax, ymin, ymax = plt.axis()
ypad = 0.1 * (ymax - ymin)
plt.axis([xmin - 0.5, xmax + 0.5, -ypad, ymax + ypad])
plt.axis()
if i == len(agg.dtype) - 1:
plt.xlabel(gj)
if j == 0:
plt.ylabel(ai)
tweak_legend()
title("Variable gap protocol, I_CaL")
### List of models
def model(name):
def result():
plt.title(name)
axis("off")
return result
mod = [model(i)
for i in "Hodgkin-Huxley FitzHugh-Nagumo Luo-Rudy Bondarenko".split()]
exp = [exp_pace, exp_p1p2, exp_vargap]
vis = [vis_ap, vis_ct, vis_p1p2, vis_vargap]
panels = mod, exp, vis
m = max([len(i) for i in panels])
n = len(panels)
plt.figure()
for j, panelj in enumerate(panels):
for i, panelij in enumerate(panelj):
# spij(m, n, i, j)
spij(n, m, j, i)
panelij()
plt.show()