def test_lokta_volterra(self):
"""Test that LV is calculating correctly.
WARNING: lokta_volterra function is being tested less rigorously than
other functions because hand calculating the answers for many steps
would be prohibitively time consuming. The function is being tested
by seeing if it agrees with the downloaded code from the scipy tutorial
and by testing if it correctly evaluates fixed or stable points.
scipy tutorial available at:
http://www.scipy.org/Cookbook/LoktaVolterraTutorial."""
# from the scipy tutorial
a = 1.0
b = 0.1
c = 1.5
d = 0.75
def dX_dt(X, t=0):
""" Return the growth rate of fox and rabbit populations. """
return array([a * X[0] - b * X[0] * X[1], -c * X[1] + d * b * X[0] * X[1]])
t = linspace(0, 15, 1000)
X0 = array([10, 5])
exp = integrate.odeint(dX_dt, X0, t)
# calculate with our function
C = array([[1.0, 0, -0.1], [-1.5, 0.075, 0]])
f = dX_dt_template(C)
Y = lokta_volterra(f, array([10, 5]), 0, 15, 1000)
assert_array_almost_equal(exp, Y.T)
def test_lokta_volterra(self):
'''Test that LV is calculating correctly.
WARNING: lokta_volterra function is being tested less rigorously than
other functions because hand calculating the answers for many steps
would be prohibitively time consuming. The function is being tested
by seeing if it agrees with the downloaded code from the scipy tutorial
and by testing if it correctly evaluates fixed or stable points.
scipy tutorial available at:
http://www.scipy.org/Cookbook/LoktaVolterraTutorial.'''
# from the scipy tutorial
a = 1.
b = 0.1
c = 1.5
d = 0.75
def dX_dt(X, t=0):
""" Return the growth rate of fox and rabbit populations. """
return array([ a*X[0] - b*X[0]*X[1] ,
-c*X[1] + d*b*X[0]*X[1] ])
t = linspace(0, 15, 1000)
X0 = array([10, 5])
exp = integrate.odeint(dX_dt, X0, t)
# calculate with our function
C = array([[1., 0, -.1],
[-1.5, 0.075, 0]])
f = dX_dt_template(C)
Y = lokta_volterra(f, array([10,5]), 0, 15, 1000)
assert_array_almost_equal(exp, Y.T)
def test_dX_dt_template(self):
"""Test that the function returned by dX_dt_template evals correctly."""
C = array([[0.5, 0.6, 0.7], [0.1, 0.2, 1.5]])
X = array([10, 20])
exp = array([205, 642])
obs = dX_dt_template(C)(X)
assert_array_almost_equal(obs, exp)
def test_dX_dt_template(self):
'''Test that the function returned by dX_dt_template evals correctly.'''
C = array([[.5, .6, .7],
[.1, .2, 1.5]])
X = array([10,20])
exp = array([205,642])
obs = dX_dt_template(C)(X)
assert_array_almost_equal(obs, exp)
