def test_expression_ICs(self):
"""Test math expression as IC"""
test_net = net.copy()
test_net.set_initial_var_value('x', 'A + 1.5*B')
traj = test_net.integrate(np.linspace(0, 5, 5))
ICx = traj.getVariableTrajectory('x')[0]
self.assertAlmostEqual(ICx, 4.0, 6, 'Failed on changing parameter IC')
def test_parameter_ics(self):
"""Test parameters as ICs"""
test_net = net.copy()
test_net.set_initial_var_value('x', 'A')
traj = test_net.integrate(np.linspace(0, 5, 5))
ICx = traj.getVariableTrajectory('x')[0]
self.assertAlmostEqual(ICx, 1.0, 6, 'Failed on parameter IC')
def test_resetting_initial_conditions(self):
"""Test resetting of ICs"""
test_net = net.copy()
test_net.set_initial_var_value('x', 0.5)
traj = test_net.integrate(np.linspace(0, 5, 5))
ICx = traj.getVariableTrajectory('x')[0]
self.assertAlmostEqual(ICx, 0.5, 6, 'Failed on resetting IC')
def test_resetting_parameter(self):
"""Test changing parameters as ICs"""
test_net = net.copy()
test_net.set_initial_var_value('x', 'A')
test_net.set_initial_var_value('A', 0.9)
traj = test_net.integrate(np.linspace(0, 5, 5))
ICx = traj.getVariableTrajectory('x')[0]
self.assertAlmostEqual(ICx, 0.9, 6, 'Failed on changing parameter IC')
def test_default_initial_conditions(self):
"""Test that default ICs are handled correctly"""
test_net = net.copy()
traj = test_net.integrate(np.linspace(0, 5, 5))
ICx = traj.getVariableTrajectory('x')[0]
ICy = traj.getVariableTrajectory('y')[0]
self.assertAlmostEqual(ICx, 1.0, 6, 'Failed on default IC')
self.assertAlmostEqual(ICy, 2.0, 6, 'Failed on default IC')
from __future__ import absolute_import
from __future__ import division
from past.utils import old_div
import unittest
import scipy
import numpy as np
from SloppyCell.ReactionNetworks import *
from TestNetwork import net
net = net.copy()
net.setInitialVariableValue('A', 1.0)
net.setInitialVariableValue('B', 2.0)
net.addParameter('xIC', 4.0)
net.setInitialVariableValue('x', '2.0*exp(xIC)')
net.compile()
class test_TimeDerivs(unittest.TestCase):
def test_TimeDerivs(self):
"""Test time derivatives of the trajectory and the sensitivity
trajectory """
net.add_int_times = False
# need really finely spaced time points for the finite differencing to
# work
times = np.linspace(0.0, .001, 1000)
Traj = Dynamics.integrate(net, times, return_derivs=True)
sensTraj = Dynamics.integrate_sensitivity(net,
times,
return_derivs=True)