#

# plot an omori_x + poisson_tahir type figure

#

X=numpy.arange(0., 30., .1)

norm_fact = alpha+beta

alpha /= norm_fact

beta /= norm_fact

#

Y_omori_x = [omori_x(x) for x in X] #omori_x(X)

Y_poisson_x = [poisson_x(x) for x in X] # poisson_x(X)

#

YY = alpha*numpy.array(Y_omori_x) + beta*numpy.array(Y_poisson_x)

#

myplot=plt.loglog

#

plt.ion()

plt.figure(0)

plt.clf()

myplot(X, Y_omori_x, label='Aftershock Seismicity', lw=3)

myplot(X, Y_poisson_x, label='Largest Aftershock', lw=3)

myplot(X, YY, label = 'combined, $\\alpha = %.2f$, $\\beta = %.2f$' % (alpha, beta), lw=3)

#

plt.legend(loc=0, numpoints=1)

plt.xlabel('\'Normalized\' distance, $r/r_0$', size=16)

# do we have time to make a mini-bass and graph-viz it?

# just the branching...

#m=6.

#mc=3.

quakes = [[None, 0]] # like [[src, target]]

#

for quake in quakes:

N=nOmori(m=m-float(quake[1]), base=base)

parent = quake[1]

child = parent + 1

for i in range(int(N)):

quakes += [[parent, child]]

if len(quakes)>500:

print("breaking")

break

#

f=open(fout, 'w')

for rw in quakes:

f.write('%s -- %s\n' % (str(rw[0]), str(rw[1])))

f.close()

#