updating demo docs

demos/animation_demo/README.md

@@ -1,19 +1,19 @@
 # Animating Network Automata
 
-Network Automata can be animated with the Netomaton `animate` function.
+Network Automata can be animated with the Netomaton `animate_activities` function.
 
 For example, the evolution of a 2D 60x60 Cellular Automaton can be
 visualized using:
 ```python
-ntm.animate(activities, shape=(60, 60), interval=150)
+ntm.animate_activities(trajectory, shape=(60, 60), interval=150)
 ```
 <img src="../../resources/animation2D.gif" width="40%"/>
 
 The evolution of a 1D Celluar Automaton with 200 cells can be visualized
 using:
 ```python
 # note that the shape specified is a tuple containing only a single value
-ntm.animate(activities, shape=(200,))
+ntm.animate_activities(trajectory, shape=(200,))
 ```
 <img src="../../resources/animation1D.gif" width="40%"/>
 
@@ -22,7 +22,7 @@ timestep, that vector can be reshaped and visualized however desired.
 For example, the evolution of a 1D Cellular Automaton with 225 cells
 can be visualized as if it were a 2D Cellular Automation, using:
 ```python
-ntm.animate(activities, shape=(15, 15))
+ntm.animate_activities(trajectory, shape=(15, 15), interval=100)
 ```
 <img src="../../resources/animation1Db.gif" width="40%"/>
 

demos/asynchronous_automata/README.md

@@ -22,19 +22,21 @@ automaton from Wolfram's NKS Notes on Chapter 9, section 10:
 ```python
 import netomaton as ntm
 
-adjacency_matrix = ntm.topology.adjacency.cellular_automaton(n=21)
+network = ntm.topology.cellular_automaton(n=21)
 
 initial_conditions =[0]*10 + [1] + [0]*10
 
 r = ntm.AsynchronousRule(activity_rule=ntm.rules.nks_ca_rule(60),
                          update_order=range(1, 20))
 
-activities, adjacencies = ntm.evolve(initial_conditions, adjacency_matrix, timesteps=19*20,
-                                     activity_rule=r)
+trajectory = ntm.evolve(initial_conditions=initial_conditions, network=network,
+                        timesteps=19*20, activity_rule=r)
 
 # plot every 19th row, including the first, as a cycle is completed every 19 rows
+activities = ntm.get_activities_over_time_as_list(trajectory)
 ntm.plot_grid(activities[::19])
 ```
+
 <img src="../../resources/rule60async.png" width="40%"/>
 
 The full source code for this example can be found [here](asynchronous_automata_demo.py).

demos/ca_density_classification/README.md

@@ -21,7 +21,7 @@ import netomaton as ntm
 import numpy as np
 
 # set r to 3, for a neighbourhood size of 7
-adjacency_matrix = ntm.topology.adjacency.cellular_automaton(149, r=3)
+network = ntm.topology.cellular_automaton(149, r=3)
 
 initial_conditions = np.random.randint(0, 2, 149)
 
@@ -30,11 +30,12 @@ rule_number = 6667021275756174439087127638698866559
 
 print("density of 1s: %s" % (np.count_nonzero(initial_conditions) / 149))
 
-activities, adjacencies = ntm.evolve(initial_conditions, adjacency_matrix, timesteps=149,
-                                     activity_rule=ntm.rules.binary_ca_rule(rule_number))
+trajectory = ntm.evolve(initial_conditions=initial_conditions, network=network,
+                        activity_rule=ntm.rules.binary_ca_rule(rule_number), timesteps=149)
 
-ntm.plot_grid(activities)
+ntm.plot_activities(trajectory)
 ```
+
 <img src="../../resources/density_classification.png" width="50%"/>
 
 The full source code for this example can be found [here](ca_density_classification_demo.py).

demos/continuous_automata/README.md

@@ -10,22 +10,23 @@ from Wolfram's NKS book, found on page 157:
 import math
 import netomaton as ntm
 
-adjacency_matrix = ntm.topology.adjacency.cellular_automaton(n=200)
+network = ntm.topology.cellular_automaton(n=200)
 
 initial_conditions = [0.0]*100 + [1.0] + [0.0]*99
 
-# NKS page 157
+ # NKS page 157
 def activity_rule(ctx):
-    activities = ctx.activities
+    activities = ctx.neighbourhood_activities
     result = (sum(activities) / len(activities)) * (3 / 2)
     frac, whole = math.modf(result)
     return frac
 
-activities, adjacencies = ntm.evolve(initial_conditions, adjacency_matrix, timesteps=150,
-                                     activity_rule=activity_rule)
+trajectory = ntm.evolve(initial_conditions=initial_conditions, network=network,
+                        activity_rule=activity_rule, timesteps=150)
 
-ntm.plot_grid(activities)
+ntm.plot_activities(trajectory)
 ```
+
 <img src="../../resources/continuous_ca.png" width="40%"/>
 
 The full source code for this example can be found [here](continuous_automata_demo.py).