weights = 1e4 / sw.plot_size * (dx/4) * np.ones(meas.shape)
plt.hist(meas, bins=N/4, weights=weights,
histtype='stepfilled', color='0.5', edgecolor='0.5', label='aspen meas')
plt.plot(aw.x, naw[j], '-r', label='aspen', linewidth=2)
plt.legend(loc='best')
plt.xlabel('dbh (mm)')
plt.ylabel('stems per hectare')
plt.savefig('plots/proj_%s_%d.png' % (plotname, t))
plt.close()
psw = [ sw.population(nsw[j]) for j in range(len(T)) ]
paw = [ aw.population(naw[j]) for j in range(len(T)) ]
psw[0] = sum(nsw[0])
paw[0] = sum(naw[0])
# Tmeas = [ t for t in sw.meas['SW'] ]
Tmeas = sw.years
pswmeas = np.asarray([ len(sw.meas['SW'][t]) for t in Tmeas ]) / sw.plot_size * 1e4
pawmeas = np.asarray([ len(aw.meas['AW'][t]) for t in Tmeas ]) / aw.plot_size * 1e4
plt.figure()
plt.plot(T[1:], psw[1:], 'ob', label='spruce')
plt.plot(T[1:], paw[1:], 'or', label='aspen')
plt.plot(Tmeas, pswmeas, 'sc', label='spruce (meas)')
plt.plot(Tmeas, pawmeas, 'sm', label='aspen (meas)')
plt.legend(loc='best')
k.setup(MidPoint(), N)
mrates = []
for j in range(1, nsw.shape[0] - 1):
mr = sw.population(nsw[j + 1]) / sw.population(nsw[j])
mrates.append(mr)
mrates = np.asarray(mrates)
print name, np.mean(mrates), np.var(mrates)
# plt.figure()
# for j, t in enumerate(T):
# plt.plot(sw.x, nsw[j], '-b')
# plt.plot(aw.x, naw[j], '-r')
psw = np.asarray([sw.population(nsw[j]) for j in range(len(T))])
paw = np.asarray([aw.population(naw[j]) for j in range(len(T))])
psw[0] = sum(nsw[0])
paw[0] = sum(naw[0])
sage = np.asarray(T[1:]) + 20
sph[0].plot(sage, psw[1:], label=plotname, **pens[plotname])
sph[1].plot(sage, paw[1:], label=plotname, **pens[plotname])
sph[2].plot(sage, psw[1:] + paw[1:], label=plotname, **pens[plotname])
basal_area = lambda k, s: np.pi * np.dot(k.method.P, s * (k.x / 2) ** 2) / 1e6
swba = np.asarray([basal_area(sw, nsw[j]) for j in range(len(T))])
awba = np.asarray([basal_area(aw, naw[j]) for j in range(len(T))])
ba[0].plot(sage, swba[1:], label=plotname, **pens[plotname])