Merge pull request #28 from CovertLab/noform

Removed support for alternate forms, rearranging tests to allow for profiling

.gitignore

@@ -5,6 +5,7 @@ __pycache__
 MANIFEST
 build/
 dist/
+profile
 
 arrow.egg-info/
 stochastic_arrow.egg-info/

arrow/arrow.py

@@ -9,23 +9,23 @@ def choose(n, k):
     return np.rint(product)
 
 
-def propensity(stoichiometric_matrix, state, form):
-    reactants = np.where(stoichiometric_matrix < 0)
+def propensity(stoichiometry, state):
+    reactants = np.where(stoichiometry < 0)
     terms = [
-        form(state[reactant], -stoichiometric_matrix[reactant])
+        choose(state[reactant], -stoichiometry[reactant])
         for reactant in reactants[0]]
 
     return np.array(terms).prod()
 
-def step(stoichiometric_matrix, rates, state, forms, propensities=[], update_reactions=()):
+
+def step(stoichiometric_matrix, rates, state, propensities=[], update_reactions=()):
     if len(update_reactions):
         for update in update_reactions:
             stoichiometry = stoichiometric_matrix[:, update]
-            form = forms if callable(forms) else forms[update]
-            propensities[update] = propensity(stoichiometry, state, form)
+            propensities[update] = propensity(stoichiometry, state)
     else:
         propensities = np.array([
-            propensity(stoichiometry, state, forms if callable(forms) else forms[index])
+            propensity(stoichiometry, state)
             for index, stoichiometry in enumerate(stoichiometric_matrix.T)])
 
     distribution = (rates * propensities)
@@ -52,7 +52,7 @@ def step(stoichiometric_matrix, rates, state, forms, propensities=[], update_rea
     return time_to_next, outcome, choice, propensities
 
 
-def evolve(stoichiometric_matrix, rates, state, duration, forms=choose):
+def evolve(stoichiometric_matrix, rates, state, duration):
     time_current = 0
     time = [0]
     counts = [state]
@@ -61,18 +61,14 @@ def evolve(stoichiometric_matrix, rates, state, duration, forms=choose):
     events = np.zeros(rates.shape)
 
     dependencies = [
-        np.where(np.any(stoichiometric_matrix[
-            stoichiometry != 0
-            ] < 0, 0))[0]
-        for stoichiometry in stoichiometric_matrix.T
-        ]
+        np.where(np.any(stoichiometric_matrix[stoichiometry != 0] < 0, 0))[0]
+        for stoichiometry in stoichiometric_matrix.T]
 
     while True:
         time_to_next, state, choice, propensities = step(
             stoichiometric_matrix,
             rates,
             state,
-            forms,
             propensities,
             update_reactions)
 
@@ -94,13 +90,12 @@ def evolve(stoichiometric_matrix, rates, state, duration, forms=choose):
 
 
 class StochasticSystem(object):
-    def __init__(self, stoichiometric_matrix, rates, forms=None):
+    def __init__(self, stoichiometric_matrix, rates):
         self.stoichiometric_matrix = stoichiometric_matrix
         self.rates = rates
-        self.forms = forms or choose
 
     def step(self, state):
-        return step(self.stoichiometric_matrix, self.rates, state, forms=self.forms)
+        return step(self.stoichiometric_matrix, self.rates, state)
 
     def evolve(self, state, duration):
-        return evolve(self.stoichiometric_matrix, self.rates, state, duration, forms=self.forms)
+        return evolve(self.stoichiometric_matrix, self.rates, state, duration)

arrow/test/test_arrow.py

@@ -14,14 +14,14 @@
 
 import numpy as np
 import json
+import argparse
 
 from arrow import evolve, StochasticSystem
 
 def test_equilibration():
     stoichiometric_matrix = np.array([
         [-1, +1,  0],
-        [+1, -1, -1],
-        ])
+        [+1, -1, -1]])
 
     rates = np.array([10, 10, 0.1])
     system = StochasticSystem(stoichiometric_matrix, rates)
@@ -42,8 +42,7 @@ def test_dimerization():
         [-1, -2, +1],
         [-1,  0, +1],
         [+1,  0, -1],
-        [ 0, +1,  0]
-        ])
+        [ 0, +1,  0]])
 
     rates = np.array([3, 1, 1]) * 0.01
     system = StochasticSystem(stoichiometric_matrix, rates)
@@ -110,43 +109,53 @@ def load_state(filename):
     return (time, counts, events)
 
 if __name__ == '__main__':
-    from itertools import izip
-
-    import matplotlib.pyplot as plt
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--plot', action='store_true')
+    parser.add_argument('--complexation', action='store_true')
+    parser.add_argument('--runs', type=int, default=1)
+    args = parser.parse_args()
 
-    from arrow.analysis.plotting import plot_full_history
+    from itertools import izip
 
     systems = (
         test_equilibration,
         test_dimerization,
-        test_complexation,
-        )
+        test_complexation)
+
+    if not args.plot:
+        if args.complexation:
+            for run in xrange(args.runs):
+                test_complexation()
+        else:
+            for system in systems:
+                system()
+    else:
+        import matplotlib.pyplot as plt
+        from arrow.analysis.plotting import plot_full_history
 
-    n_systems = len(systems)
+        n_systems = len(systems)
 
-    ncols = int(np.ceil(np.sqrt(n_systems)))
-    nrows = int(np.ceil(n_systems / ncols))
+        ncols = int(np.ceil(np.sqrt(n_systems)))
+        nrows = int(np.ceil(n_systems / ncols))
 
-    margins = 1
-    axes_size = 3
+        margins = 1
+        axes_size = 3
 
-    figsize = (
-        margins + axes_size*ncols,
-        margins + axes_size*nrows
-        )
+        figsize = (
+            margins + axes_size*ncols,
+            margins + axes_size*nrows)
 
-    (fig, all_axes) = plt.subplots(
-        figsize = figsize,
-        nrows = nrows, ncols = ncols,
-        constrained_layout = True
-        )
+        (fig, all_axes) = plt.subplots(
+            figsize = figsize,
+            nrows = nrows, ncols = ncols,
+            constrained_layout = True)
 
-    all_axes = np.asarray(all_axes)
+        all_axes = np.asarray(all_axes)
 
-    for (axes, system) in izip(all_axes.flatten(), systems):
-        axes.set_title(system.func_name)
+        for (axes, system) in izip(all_axes.flatten(), systems):
+            axes.set_title(system.func_name)
 
-        time, counts, events = system()
-        plot_full_history(axes, time, counts)
+            time, counts, events = system()
+            plot_full_history(axes, time, counts)
 
-    fig.savefig('test_systems.png')
+        fig.savefig('test_systems.png')

setup.py

@@ -6,7 +6,7 @@
 
 setup(
 	name='stochastic-arrow',
-	version='0.0.4',
+	version='0.0.8',
 	packages=['arrow'],
 	author='Ryan Spangler',
 	author_email='[email protected]',