[samples] Update samples

samples/python/reactors/combustor.py

@@ -11,7 +11,7 @@
 enclosing scope. Also shows the use of a PressureController to create a constant
 pressure reactor with a fixed volume.
 
-Requires: cantera >= 2.5.0, matplotlib >= 2.0
+Requires: cantera >= 3.0, matplotlib >= 2.0
 Keywords: combustion, reactor network, well-stirred reactor, plotting
 """
 
@@ -54,11 +54,11 @@ def mdot(t):
 
 inlet_mfc = ct.MassFlowController(inlet, combustor, mdot=mdot)
 
-# A PressureController has a baseline mass flow rate matching the 'master'
+# A PressureController has a baseline mass flow rate matching the 'primary'
 # MassFlowController, with an additional pressure-dependent term. By explicitly
 # including the upstream mass flow rate, the pressure is kept constant without
 # needing to use a large value for 'K', which can introduce undesired stiffness.
-outlet_mfc = ct.PressureController(combustor, exhaust, master=inlet_mfc, K=0.01)
+outlet_mfc = ct.PressureController(combustor, exhaust, primary=inlet_mfc, K=0.01)
 
 # the simulation only contains one reactor
 sim = ct.ReactorNet([combustor])
@@ -69,7 +69,7 @@ def mdot(t):
 
 residence_time = 0.1  # starting residence time
 while combustor.T > 500:
-    sim.set_initial_time(0.0)  # reset the integrator
+    sim.initial_time = 0.0  # reset the integrator
     sim.advance_to_steady_state()
     print('tres = {:.2e}; T = {:.1f}'.format(residence_time, combustor.T))
     states.append(combustor.thermo.state, tres=residence_time)

samples/python/reactors/custom2.py

@@ -14,7 +14,7 @@
 determined by integrating the equation of motion. This requires adding a new
 variable to the reactor's state vector which represents the wall velocity.
 
-Requires: cantera >= 2.6.0, matplotlib >= 2.0
+Requires: cantera >= 3.0, matplotlib >= 2.0
 Keywords: combustion, reactor network, user-defined model, plotting
 """
 
@@ -47,7 +47,7 @@ def after_update_state(self, y):
         # This method is used to set the state of the Reactor and Wall objects
         # based on the new values for the state vector provided by the ODE solver
         self.v_wall = y[self.i_wall]
-        self.walls[0].set_velocity(self.v_wall)
+        self.walls[0].velocity = self.v_wall
 
     def after_eval(self, t, LHS, RHS):
         # Calculate the time derivative for the additional equation

samples/python/reactors/ic_engine.py

@@ -1,12 +1,11 @@
-# -*- coding: utf-8 -*-
 """
 Simulation of a (gaseous) Diesel-type internal combustion engine.
 
 The simulation uses n-Dodecane as fuel, which is injected close to top dead
 center. Note that this example uses numerous simplifying assumptions and
 thus serves for illustration purposes only.
 
-Requires: cantera >= 2.5.0, scipy >= 0.19, matplotlib >= 2.0
+Requires: cantera >= 3.0, scipy >= 0.19, matplotlib >= 2.0
 Keywords: combustion, thermodynamics, internal combustion engine,
           thermodynamic cycle, reactor network, plotting, pollutant formation
 """
@@ -110,7 +109,7 @@ def piston_speed(t):
 inlet_valve = ct.Valve(inlet, cyl)
 inlet_delta = np.mod(inlet_close - inlet_open, 4 * np.pi)
 inlet_valve.valve_coeff = inlet_valve_coeff
-inlet_valve.set_time_function(
+inlet_valve.time_function = (
     lambda t: np.mod(crank_angle(t) - inlet_open, 4 * np.pi) < inlet_delta)
 
 # define injector state (gaseous!)
@@ -122,7 +121,7 @@ def piston_speed(t):
 injector_delta = np.mod(injector_close - injector_open, 4 * np.pi)
 injector_t_open = (injector_close - injector_open) / 2. / np.pi / f
 injector_mfc.mass_flow_coeff = injector_mass / injector_t_open
-injector_mfc.set_time_function(
+injector_mfc.time_function = (
     lambda t: np.mod(crank_angle(t) - injector_open, 4 * np.pi) < injector_delta)
 
 # define outlet pressure (temperature and composition don't matter)
@@ -133,7 +132,7 @@ def piston_speed(t):
 outlet_valve = ct.Valve(cyl, outlet)
 outlet_delta = np.mod(outlet_close - outlet_open, 4 * np.pi)
 outlet_valve.valve_coeff = outlet_valve_coeff
-outlet_valve.set_time_function(
+outlet_valve.time_function = (
     lambda t: np.mod(crank_angle(t) - outlet_open, 4 * np.pi) < outlet_delta)
 
 # define ambient pressure (temperature and composition don't matter)
@@ -143,7 +142,7 @@ def piston_speed(t):
 # piston is modeled as a moving wall
 piston = ct.Wall(ambient_air, cyl)
 piston.area = A_piston
-piston.set_velocity(piston_speed)
+piston.velocity = piston_speed
 
 # create a reactor network containing the cylinder and limit advance step
 sim = ct.ReactorNet([cyl])

samples/python/reactors/pfr.py

@@ -1,10 +1,9 @@
-# -*- coding: utf-8 -*-
 """
 This example solves a plug-flow reactor problem of hydrogen-oxygen combustion.
 The PFR is computed by two approaches: The simulation of a Lagrangian fluid
 particle, and the simulation of a chain of reactors.
 
-Requires: cantera >= 2.5.0, matplotlib >= 2.0
+Requires: cantera >= 3.0, matplotlib >= 2.0
 Keywords: combustion, reactor network, plug flow reactor
 """
 
@@ -109,7 +108,7 @@
 # We need an outlet to the downstream reservoir. This will determine the
 # pressure in the reactor. The value of K will only affect the transient
 # pressure difference.
-v = ct.PressureController(r2, downstream, master=m, K=1e-5)
+v = ct.PressureController(r2, downstream, primary=m, K=1e-5)
 
 sim2 = ct.ReactorNet([r2])
 

samples/python/reactors/surf_pfr_chain.py

@@ -5,7 +5,7 @@
 DAE system, the PFR is approximated as a chain of successive WSRs. See surf_pfr.py
 for a more advanced implementation that solves the DAE system directly.
 
-Requires: cantera >= 2.5.0
+Requires: cantera >= 3.0
 Keywords: catalysis, reactor network, surface chemistry, plug flow reactor,
           packed bed reactor
 """
@@ -95,7 +95,7 @@
 # We need an outlet to the downstream reservoir. This will determine the
 # pressure in the reactor. The value of K will only affect the transient
 # pressure difference.
-v = ct.PressureController(r, downstream, master=m, K=1e-5)
+v = ct.PressureController(r, downstream, primary=m, K=1e-5)
 
 sim = ct.ReactorNet([r])