def test_constructor(self): # Create a Voxel object v = pystospa.Voxel([10], 1.0) # Check that the Voxel attributes are as expected self.assertEqual(len(v.get_molecules()), 1) self.assertEqual(v.get_molecules()[0], 10) self.assertEqual(v.get_voxel_size(), 1.0)
def test_constructor(self): # Create a Simulator object v = pystospa.Voxel([10], 1.0) v.add_reaction(pystospa.Reaction(1.5, lambda x, y: x[0], [-1])) s = pystospa.Simulator([v]) # Check that the Simulator attributes are as expected self.assertEqual(s.get_time(), 0.0) self.assertEqual(s.get_voxels()[0].get_molecules()[0], 10)
def test_member_functions(self): # Create a Voxel object v = pystospa.Voxel([10], 1.0) r = pystospa.Reaction(1.5, lambda x, y: x[0], [-1]) # Check that a Reaction object has been added correctly v.add_reaction(r) rs = v.get_reactions() self.assertEqual(len(rs), 1) self.assertEqual(rs[0].get_rate(), 1.5) self.assertEqual(v.get_total_propensity(), 15)
def test_member_functions(self): # Create a Simulator object v = pystospa.Voxel([10], 1.0) v.add_reaction(pystospa.Reaction(1.5, lambda x, y: x[0], [-1])) s = pystospa.Simulator([v]) # Check setting seed for generating random number s.set_seed(153) self.assertEqual(s.get_seed(), 153) # Check a single step in SSA works s.step() self.assertGreater(s.get_time(), 0) self.assertEqual(s.get_voxels()[0].get_molecules()[0], 9) # Check that getting to specific time point works s.advance(1.0) self.assertGreater(s.get_time(), 1.0)
#!/usr/bin/env python import matplotlib.pyplot as plt import numpy as np import pystospa as ss # Create voxel object. Arguments: vector of number of molecules, size of the voxel initial_num = [100] # number of molecules of species A domain_size = 10.0 # size of the domain in cm v = ss.Voxel(initial_num, domain_size) # Create reaction object. # Arguments: reaction rate, propensity func, stoichiometry vector k = 1.0 propensity = lambda num_mols, area: num_mols[0] stoch = [-1] r = ss.Reaction(k, propensity, stoch) # Add a reaction to a voxel v.add_reaction(r) # Pass the voxel with the reaction(s) to the simulator object s = ss.Simulator([v]) # Run the simulation. Arguments: path to output file, time step, number of steps s.run("cme_example.dat", 0.01, 500) # Read the file containing the data data = np.loadtxt("cme_example.dat") time = data[:, 0] # Time points num_A = data[:, 1] # Number of molecules of A
#!/usr/bin/env python import matplotlib.pyplot as plt import numpy as np import pystospa as ss # Create a vector of voxel objects. Voxel arguments: vector of number of molecules, size of the voxel initial_num = [10000] voxel_size = 1.0 domain = [ss.Voxel(initial_num, voxel_size)] # We add nine voxels with no molecules for i in range(9): domain.append(ss.Voxel([0], voxel_size)) # Create and add the reaction objects d = 1.0 # diffusion rate k = 1.0 # decay rate propensity = lambda num_mols, length : num_mols[0] stoch = [-1] for i, vox in enumerate(domain): # Add diffusion jump to the right from voxel i to voxel i+1 (if one exists) if i < len(domain)-1: vox.add_reaction(ss.Reaction(d, propensity, stoch, i+1)) # Add diffusion jump to the left from voxel i+1 to voxel i (if one exists) if i > 0: vox.add_reaction(ss.Reaction(d, propensity, stoch, i-1)) vox.add_reaction(ss.Reaction(k, propensity, stoch)) # Pass the voxels with the reaction(s) to the simulator object s = ss.Simulator(domain) # Run the simulation. Arguments: path to output file, time step, number of steps s.run("rdme_example_2.dat", 0.01, 200)