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uni-m.cds-num-met/week5/ex1.py

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Python
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#!/usr/bin/env python3
"""Ordinary Differential Equations"""
import numpy as np
# Integrations Schemes #
########################
# Single Step
#------------
def mk_phi_euler(f):
""" Return a Phi computed for the Euler Method. """
def phi_euler(x, y, h):
return f(x[-1], y[-1])
return phi_euler
def mk_phi_euler_mod(f):
""" Return a Phi computed for the Modified Euler (Collatz) Method. """
def phi_euler_mod(x, y, h):
return f(x[-1] + 0.5*h, y[-1] + 0.5*h*f(x[-1], y[-1]))
return phi_euler_mod
def mk_phi_heun(f):
""" Return a Phi computed for the Heun Method. """
def phi_heun(x, y, h):
return (f(x[-1], y[-1]) + f(x[-1] + h, y[-1] + h * f(x[-1], y[-1])))/2
return phi_heun
def mk_phi_rk4(f):
""" Return a Phi computed for the 4th order Runge-Kutta Method. """
def phi_rk4(x, y, h):
k1 = f(x[-1], y[-1])
k2 = f(x[-1] + 0.5*h, y[-1] + 0.5*k1)
k3 = f(x[-1] + 0.5*h, y[-1] + 0.5*h*k2)
k4 = f(x[-1] + h, y[-1] + h*k3)
return (k1 + 2*k2 + 2*k3 + k4)/6
return phi_rk4
# Multi Step
#-----------
def mk_phi_AB3(f, phi_short = None):
steps = 3
def phi_AB3(x, y, h):
if len(x) < steps:
if phi_short is None:
raise ValueError("This function needs at least {} steps, {} given.".format(steps, len(x)))
else:
return phi_short(x, y, h)
else:
return ( 23*f(x[-1], y[-1]) - 16*f(x[-2], y[-2]) + 5*f(x[-3], y[-3]) )/12
return phi_AB3
def mk_phi_AB4(f, phi_short = None):
steps = 4
def phi_AB4(x, y, h):
if len(x) < steps:
if phi_short is None:
raise ValueError("This function needs at least {} steps, {} given.".format(steps, len(x)))
else:
return phi_short(x, y, h)
else:
return ( 55*f(x[-1], y[-1]) - 59*f(x[-2], y[-2]) + 37*f(x[-3], y[-3]) -9*f(x[-4],y[-4]))/24
return phi_AB4
# Integrator #
##############
def integrator(x, y_0, phi, y_i = None ):
x = np.asarray(x)
if isinstance(y_0, (list,np.ndarray)):
y_0 = np.asarray(y_0)
else:
y_0 = np.array([ y_0 ])
N = len(x)
M = len(y_0)
y = np.zeros((N,M), dtype=np.float64)
y[0] = y_0
j = 0
if y_i is not None:
for i, _ in enumerate(y_i):
y[i+1] = y_i[i]
j = i
h = x[1]-x[0]
for i in range(j+1, N):
y[i] = y[i-1] + h*phi(x[:i], y[:i], h)
return y
# Math Test Functions #
#######################
def ODEF(x, y):
return y - x**2 + 1
def ODEF_sol(x):
return (x+1)**2 - 0.5*np.exp(x)
# Testing #
###########
def test_integrator_singlestep():
test_func = ODEF
exact_sol = ODEF_sol
N = 2e1
# Domain on which to do the integration
x = np.linspace(0, 1, N)
# Generate Initial Value
y_0 = 0.5
schemes = [
["Euler", mk_phi_euler],
["Collatz", mk_phi_euler_mod],
["Heun", mk_phi_heun],
["RK4", mk_phi_rk4],
]
# Show Plot
from matplotlib import pyplot
pyplot.subplots()
for name, func in schemes:
pyplot.plot(x, integrator(x, y_0, func(test_func)), '--o', label=name)
pyplot.plot(x, exact_sol(x), '-', label="Exact Solution")
pyplot.xlabel("x")
pyplot.ylabel("y")
pyplot.legend()
pyplot.show()
def test_integrator_multistep():
test_func = ODEF
exact_sol = ODEF_sol
N = 2e1
# Domain on which to do the integration
x = np.linspace(0, 1, N)
# Calculate Initial Values using RK4
y_0 = 0.5
y_init = integrator(x[:4], y_0, mk_phi_rk4(test_func))
#Name, func, steps
multi_schemes = [
["AB3", mk_phi_AB3, 3],
["AB4", mk_phi_AB4, 4],
]
# Show Plot
from matplotlib import pyplot
pyplot.subplots()
# Exact Solution
pyplot.plot(x, exact_sol(x), '-', label="Exact Solution")
# Plot the schemes
for name, func, steps in multi_schemes:
try:
pyplot.plot(x, integrator(x, y_0, func(test_func), y_init[:steps]), '--o', label=name)
except Exception as e:
print(e)
pass
pyplot.xlabel("x")
pyplot.ylabel("y")
pyplot.legend()
pyplot.show()
def plot_integration_errors():
test_func = ODEF
exact_sol = ODEF_sol
# Domain on which to do the integration
x = np.arange(0, 2.001, step=0.02)
# Calculate Initial Values using RK4
y_0 = 0.5
y_init = integrator(x[:4], y_0, mk_phi_rk4(test_func))
single_schemes = [
["Euler", mk_phi_euler],
["Collatz", mk_phi_euler_mod],
["Heun", mk_phi_heun],
["RK4", mk_phi_rk4],
]
multi_schemes = [
["AB3", mk_phi_AB3, 3],
["AB4", mk_phi_AB4, 4],
]
# Show Plot
from matplotlib import pyplot
pyplot.subplots()
# Pre calculate the exact solution
exact = exact_sol(x)
exact = np.reshape(exact, (-1,1))
# Plot Single Step Schemes
for name, func in single_schemes:
try:
pyplot.plot(x, np.abs(exact - integrator(x, y_0, func(test_func))), '--o', label=name)
except Exception as e:
print(e)
pass
# Plot Multi Step Schemes
for name, func, steps in multi_schemes:
try:
pyplot.plot(x, np.abs(exact - integrator(x, y_0, func(test_func), y_init[:steps])), '--o', label=name)
except Exception as e:
print(e)
pass
pyplot.xlabel("x")
pyplot.ylabel("absolute error $|\\bar{y} - y|$")
pyplot.legend()
pyplot.show()
if __name__ == "__main__":
np.random.seed(0)
#test_integrator_singlestep()
#test_integrator_multistep()
plot_integration_errors()