def getAxis(self,X,Y):
"""
return the proper axis limits for the plots
"""
out = []
mM = [(min(X),max(X)),(min(Y),max(Y))]
for i,j in mM:
#YJC: checking if values are negative, if yes, return 0 and break
if j <0 or i <0:
return 0
log_i = scipy.log10(i)
d, I = scipy.modf(log_i)
if log_i < 0:
add = 0.5 *(scipy.absolute(d)<0.5)
else:
add = 0.5 *(scipy.absolute(d)>0.5)
m = scipy.floor(log_i) + add
out.append(10**m)
log_j = scipy.log10(j)
d, I = scipy.modf(log_j)
if log_j < 0:
add = - 0.5 *(scipy.absolute(d)>0.5)
else:
add = - 0.5 *(scipy.absolute(d)<0.5)
m = scipy.ceil(log_j) + add
out.append(10**m)
return tuple(out)
def integrate(self,u,lambd):
dt = self.dt
Dt = self.Dt
dx = self.dx
alpha, steps = scipy.modf(Dt/dt)
# we assume that u is the logarithm of the density
# print "in integrate"
# print "u: ", u
# print "+++"
y=scipy.exp(u)
# print "y: ", y
# print "+++"
for i in range(int(steps)):
rhs=self.rhs(y,lambd)
y=y+rhs*dt
rhs=self.rhs(y,lambd)
y_new=y+rhs*dt
y_Dt = alpha*y_new+(1-alpha)*y
# print "y_Dt: ", y_Dt
# print '++++'
# print sum(y_Dt)
# print "+++"
u_Dt = scipy.log(y_Dt)
# print "u_Dt: ", u_Dt
# print "-------"
return u_Dt
def integrate(self, u, lambd):
dt = self.dt
Dt = self.Dt
dx = self.dx
alpha, steps = scipy.modf(Dt / dt)
y = scipy.array(u)
# we assume that u is the logarithm of the density
# print "in integrate"
# print "u: ", u
# print "+++"
for i in range(int(steps)):
rhs = self.rhs(y, lambd)
y = y + rhs * dt
rhs = self.rhs(y, lambd)
y_new = y + rhs * dt
y_Dt = alpha * y_new + (1 - alpha) * y
# print '++++'
u_Dt = scipy.array(y_Dt)
# print sum(u_Dt)
# print "+++"
# print "u_Dt: ", u_Dt
# print "-------"
return u_Dt