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@kenjisato
Last active August 29, 2015 14:21
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2015 経済動学 講義資料 (2015-05-18)
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import numpy as np
class System:
def __init__(self, f, dim):
self.f = f
self.dim = dim
def forward(self, x):
return self.f(x)
def simulate(s, *, start, steps):
x = np.array(start)
count = 0
while count < steps:
yield x
x = s.forward(x)
count += 1
def shoot(s, *, goal, steps):
for
if __name__ == "__main__":
def f(x):
A = np.array([[1.0, -0.5], [0.0, 1.0]])
return np.dot(A, x)
s = System(f, (2, 2))
path = simulate(s, start=[1., 1.], steps=10)
import numpy as np
class System:
def __init__(self, dim):
self.dim = dim
def forward(self, x):
pass
class Logistic(System):
def __init__(self, a):
self.a = a
super().__init__(dim=1)
# System.__init__(dim=1)
def forward(self, x):
return self.a * x * (1 - x)
class Tent(System):
def __init__(self, a):
self.a = a
super().__init__(dim=1)
def forward(self, x):
return self.a * min(x, 1 - x)
class Linear(System):
def __init__(self, A):
self.A = A
super().__init__(dim=A.shape[0])
def forward(self, x):
return np.dot(self.A, x)
class NoUse:
def forward(self, x):
return 2 * x
def run(system, x, steps):
for i in range(steps):
x1 = system.forward(x)
yield x
x = x1
# Generators
def logistic(x):
"""Logistic map"""
return 4 * x * (1 - x)
def logistic_path(x, length):
y = [x]
for _ in range(length - 1):
y.append(logistic(y[-1]))
return y
def logistic_gen(x, length):
for _ in range(length):
x1 = logistic(x)
yield x
x = x1
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