Merge f95d7e2 into 1eee9ca

doc/tutorial.rst

@@ -482,10 +482,10 @@ you are using iPython, you can press tab twice after "m.mymodel" to
 tab complete and see all the possible options). 
 
 
-Now, we will import the *PyLab* and PySB integrator module. Enter
+Now, we will import the *PyLab* and PySB simulator module. Enter
 the commands as shown below::
 
-   >>> from pysb.integrate import odesolve
+   >>> from pysb.simulator.scipy import ScipyOdeSolver
    >>> import pylab as pl
 
 We have now loaded the integration engine and the graph engine into
@@ -523,7 +523,7 @@ These are the points at which we will get data for each ODE from the
 integrator. With this, we can now run our simulation. Enter the
 following commands to run the simulation::
 
-   >>> yout = odesolve(m.model, t)
+   >>> yout = ScipyOdeSolver.execute(m.model, tspan=t)
 
 To verify that the simulation run you can see the content of the
 *yout* object. For example, check for the content of the *Bid*

pysb/core.py

@@ -505,11 +505,12 @@ def is_equivalent_to(self, other):
         #   so some sort of canonicalization of that numbering is necessary.
         if not isinstance(other, ComplexPattern):
             raise Exception("Can only compare ComplexPattern to another ComplexPattern")
+        mp_order = lambda mp: (mp[0], mp[1].keys(), mp[2])
         return (self.compartment == other.compartment and
-                sorted((repr(mp.monomer), mp.site_conditions, mp.compartment)
-                       for mp in self.monomer_patterns) ==
-                sorted((repr(mp.monomer), mp.site_conditions, mp.compartment)
-                       for mp in other.monomer_patterns))
+                sorted([(repr(mp.monomer), mp.site_conditions, mp.compartment)
+                       for mp in self.monomer_patterns], key=mp_order) ==
+                sorted([(repr(mp.monomer), mp.site_conditions, mp.compartment)
+                       for mp in other.monomer_patterns], key=mp_order))
 
     def copy(self):
         """

pysb/examples/hello_pysb.py

@@ -30,12 +30,12 @@
 
 if __name__ == '__main__':
     from pylab import linspace, plot, xlabel, ylabel, show
-    from pysb.integrate import odesolve
+    from pysb.simulator import ScipyOdeSimulator
     print(__doc__)
     # Simulate the model through 40 seconds
     time = linspace(0, 40, 100)
     print("Simulating...")
-    x = odesolve(model, time)
+    x = ScipyOdeSimulator.execute(model, tspan=time)
     # Plot the trajectory of LR
     plot(time, x['LR'])
     xlabel('Time (seconds)')

pysb/examples/run_bax_pore.py

@@ -3,14 +3,14 @@
 
 from __future__ import print_function
 from pylab import *
-from pysb.integrate import odesolve
+from pysb.simulator.scipy import ScipyOdeSimulator
 
 from bax_pore import model
 
 
 t = linspace(0, 100)
 print("Simulating...")
-x = odesolve(model, t)
+x = ScipyOdeSimulator.execute(model, tspan=t)
 
 p = plot(t, c_[x['BAX4'], x['BAX4_inh']])
 figlegend(p, ['BAX4', 'BAX4_inh'], 'upper left')

pysb/examples/run_bax_pore_sequential.py

@@ -3,7 +3,7 @@
 
 from __future__ import print_function
 from pylab import *
-from pysb.integrate import odesolve
+from pysb.simulator.scipy import ScipyOdeSimulator
 
 from bax_pore_sequential import model, max_size
 
@@ -12,7 +12,7 @@
 # vector of time points happens to help with the integration
 t = logspace(-3, 5) # 1e-3 to 1e5
 print("Simulating...")
-x = odesolve(model, t)
+x = ScipyOdeSimulator.execute(model, tspan=t)
 
 # Plot trajectory of each pore
 for i in range(1, max_size + 1):

pysb/examples/run_earm_1_0.py

@@ -3,7 +3,7 @@
 al. 2008)."""
 
 from __future__ import print_function
-from pysb.integrate import odesolve
+from pysb.simulator import ScipyOdeSimulator
 from pylab import *
 
 from earm_1_0 import model
@@ -41,7 +41,7 @@ def fig_4a():
         model.parameters['L_0'].value = Ls[i]
 
         print("  L_0 = %g" % Ls[i])
-        x = odesolve(model, t)
+        x = ScipyOdeSimulator.execute(model, tspan=t)
 
         fs[i] = (x['PARP_unbound'][0] - x['PARP_unbound'][-1]) / x['PARP_unbound'][0]
         dP = 60 * (x['PARP_unbound'][:-1] - x['PARP_unbound'][1:]) / (dt * x['PARP_unbound'][0])  # in minutes
@@ -67,7 +67,7 @@ def fig_4b():
     print("Simulating model for figure 4B...")
 
     t = linspace(0, 6*3600, 6*60+1)  # 6 hours
-    x = odesolve(model, t)
+    x = ScipyOdeSimulator.execute(model, tspan=t)
 
     x_norm = c_[x['Bid_unbound'], x['PARP_unbound'], x['mSmac_unbound']]
     x_norm = 1 - x_norm / x_norm[0, :]  # gets away without max() since first values are largest

pysb/examples/run_kinase_cascade.py

@@ -1,15 +1,15 @@
 #!/usr/bin/env python
 
 from __future__ import print_function
-from pysb.integrate import odesolve
+from pysb.simulator import ScipyOdeSimulator
 from pylab import linspace, plot, legend, show
 
 from kinase_cascade import model
 
 
 tspan = linspace(0, 1200)
 print("Simulating...")
-yfull = odesolve(model, tspan)
+yfull = ScipyOdeSimulator.execute(model, tspan=tspan)
 plot(tspan, yfull['ppMEK'], label='ppMEK')
 plot(tspan, yfull['ppERK'], label='ppERK')
 legend(loc='upper left')

pysb/examples/run_robertson.py

@@ -5,15 +5,16 @@
 
 from __future__ import print_function
 from pylab import *
-from pysb.integrate import odesolve
+from pysb.simulator import ScipyOdeSimulator
 
 from robertson import model
 
 # We will integrate from t=0 to t=40
 t = linspace(0, 40)
 # Simulate the model
 print("Simulating...")
-y = odesolve(model, t, rtol=1e-4, atol=[1e-8, 1e-14, 1e-6])
+y = ScipyOdeSimulator.execute(model, tspan=t, rtol=1e-4,
+                              atol=[1e-8, 1e-14, 1e-6])
 # Gather the observables of interest into a matrix
 yobs = array([y[obs] for obs in ('A_total', 'B_total', 'C_total')]).T
 # Plot normalized trajectories

pysb/examples/run_tyson_oscillator.py

@@ -1,10 +1,10 @@
 from pysb.examples.tyson_oscillator import model
-from pysb.integrate import odesolve
 import numpy as np
+from pysb.simulator import ScipyOdeSimulator
 import matplotlib.pyplot as plt
 
 t = np.linspace(0, 100, 10001)
-x = odesolve(model, t)
+x = ScipyOdeSimulator.execute(model, tspan=t)
 
 plt.plot(t, x['CT'],  lw=2, label='CT')  # Good validation of mass balance for cdc2, should be constant at 1
 plt.plot(t, x['YT'], lw=2, label='YT')