def OrnsteinUhlenbeck(x, mu, sigma, tau):
'''
An Ornstein-Uhlenbeck process.
mu = mean
sigma = standard deviation
tau = time constant
x = name of the variable
Returns an Equations() object
'''
return Equations('dx/dt=(mu-x)*invtau+sigma*((2.*invtau)**.5)*xi : unit', \
x=x, mu=mu, sigma=sigma, invtau=1. / tau, unit=get_unit(mu))
def OrnsteinUhlenbeck(x, mu, sigma, tau):
'''
An Ornstein-Uhlenbeck process.
mu = mean
sigma = standard deviation
tau = time constant
x = name of the variable
Returns an Equations() object
'''
return Equations('dx/dt=(mu-x)*invtau+sigma*((2.*invtau)**.5)*xi : unit', \
x=x, mu=mu, sigma=sigma, invtau=1. / tau, unit=get_unit(mu))
def __init__(self, f, xmin, xmax, n):
self.xmin = xmin
self.xmax = xmax
self.dx = (xmax - xmin) / float(n)
self.invdx = 1 / self.dx
self.unit = get_unit(f(xmin))
# Tabulation at midpoints
x = xmin + (.5 + arange(n)) * self.dx
try:
self.f = f(x)
except:
# If it fails we try passing the values one by one
self.f = zeros(n) * f(xmin) # for the unit
for i in xrange(n):
self.f[i] = f(x[i])
def __init__(self, f, xmin, xmax, n):
self.xmin = xmin
self.xmax = xmax
self.dx = (xmax - xmin) / float(n)
self.invdx = 1 / self.dx
self.unit = get_unit(f(xmin))
# Tabulation at midpoints
x = xmin + (.5 + arange(n)) * self.dx
try:
self.f = f(x)
except:
# If it fails we try passing the values one by one
self.f = zeros(n) * f(xmin) # for the unit
for i in xrange(n):
self.f[i] = f(x[i])
def __init__(self, f, xmin, xmax, n):
self.xmin = xmin
self.xmax = xmax
self.dx = (xmax - xmin) / float(n - 1)
self.invdx = 1 / self.dx
# Not at midpoints here
x = xmin + arange(n) * self.dx
self.unit = get_unit(f(xmin))
try:
self.f = f(x)
except:
# If it fails we try passing the values one by one
self.f = zeros(n) * f(xmin) # for the unit
for i in xrange(n):
self.f[i] = f(x[i])
self.f = array(self.f)
self.df = (self.f[range(1, n)] - self.f[range(n - 1)]) * float(self.invdx)
def __init__(self, f, xmin, xmax, n):
self.xmin = xmin
self.xmax = xmax
self.dx = (xmax - xmin) / float(n - 1)
self.invdx = 1 / self.dx
# Not at midpoints here
x = xmin + arange(n) * self.dx
self.unit = get_unit(f(xmin))
try:
self.f = f(x)
except:
# If it fails we try passing the values one by one
self.f = zeros(n) * f(xmin) # for the unit
for i in xrange(n):
self.f[i] = f(x[i])
self.f = array(self.f)
self.df = (self.f[range(1, n)] - self.f[range(n - 1)]) * float(
self.invdx)
