A new script for making animations

README.md

@@ -40,7 +40,9 @@ Fell free to use our code, and if you do so, please cite us!
 * `plots/` this directory doesn't exist in the repository, but after running the simulation (or a plotting function) it will be created and plots will be generated and saved here by default
 * `results/` this directory doesn't exist in the repository, but after running the simulation it will be created and results will be saved here by default
 * `scripts/` different scripts for custom tasks, mainly for running `main.py` many times with different parameters
+  * `animation.py` a script for making animations of the network showing how states/votes are changing
   * `binom_approx.py` this script requires to run `main.py` manually with the same parameters first, then on top of the results of the simulation plots a binomial approximation, where voters basically flip a coin to chose their state/vote
+  * `fit_planar_c.py` a script fitting the `planar_c` parameter value to the commuting data
   * `media_susceptibility.py` this script runs `main.py` for a range of different mass media influence and plots media susceptibility and other measures
   * `media_vs_zealots.py` this script runs `main.py` for a range of different numbers of zealots and different mass media influence and plots the results for cross-influenced system
   * `zealot_susceptibility.py` this script runs `main.py` for a range of different numbers of zealots and plots zealot susceptibility and other measures

scripts/animation.py

@@ -0,0 +1,78 @@
+"""
+A script running the simulation for a given configuration (you can provide a config file),
+saving plots of the graph on the way, and creating an animation at the end.
+This script doesn't have many options as it is meant to play around with it,
+so if you want to get some fancy plots etc. just modify the code.
+"""
+import os
+import sys
+import glob
+import inspect
+
+# path hack for imports to work when running this script from any location,
+# without the hack one has to manually edit PYTHONPATH every time
+currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
+parentdir = os.path.dirname(currentdir)
+sys.path.insert(0, parentdir)
+
+from configuration.parser import get_arguments
+from configuration.logging import log
+from tools import run_with_time, compute_edge_ratio
+from plotting import plot_traj, plot_network
+from net_generation.base import init_graph, add_zealots
+from simulation.base import run_simulation, run_thermalization
+
+
+NUM_FRAMES = 100  # the number of frames to save
+MC_STEP = 10  # the number of Monte Carlo steps of simulation between frames
+
+
+@run_with_time
+def make_animation(config):
+    os.makedirs('plots/animation', exist_ok=True)
+    os.chdir('plots/animation')
+
+    # initialize the graph
+    graph = init_graph(config.n, config.district_sizes, config.avg_deg, block_coords=config.district_coords,
+                        ratio=config.ratio, planar_const=config.planar_c, euclidean=config.euclidean,
+                        state_generator=config.initialize_states, random_dist=config.random_dist,
+                        initial_state=config.not_zealot_state, all_states=config.all_states)
+    graph = add_zealots(graph, config.n_zealots, zealot_state=config.zealot_state, **config.zealots_config)
+
+    link_fraction, link_ratio = compute_edge_ratio(graph)
+    log.info(f'There is {str(round(100.0 * link_fraction, 1))}% of inter-district connections')
+    log.info(f'Ratio of inter- to intra-district links is equal {str(round(link_ratio, 3))}')
+
+    # save the layout to use the same one in each frame
+    ll = graph.layout()
+
+    # show the first plot with colored districts so one can stop the script and rerun it, if the layout is not nice
+    plot_network(graph, config, mode='districts', ig_layout=ll)
+
+    if config.therm_time > 1:
+        graph, trajectory = run_thermalization(config, graph, config.epsilon, config.therm_time, n=config.n)
+        plot_traj(trajectory, config.suffix)
+    plot_network(graph, config, mode='states', ig_layout=ll, save_as=f'{0:05d}.png')
+
+    for i in range(NUM_FRAMES):
+        log.info(f'Running loop no. {i}')
+        graph = run_simulation(config, graph, config.epsilon, MC_STEP * config.n, n=config.n)
+        plot_network(graph, config, mode='states', ig_layout=ll, save_as=f'{i + 1:05d}.png')
+
+    # change the command in this line to create the animation with your preferred program and in the preferred format
+    # for example, you might also use 'convert -delay 10 -loop 0 %05d.png animation.gif' etc.
+    os.system('ffmpeg -framerate 10 -i %05d.png animation.mp4')
+
+    # don't remove .png files if you want to be able to play around
+    # with animation parameters (like speed) without having to run the whole simulation again
+    response = input('Do you want to remove the created .png files? [Y/N] ')
+    if response == 'Y':
+        log.info(f'Removing the .png files')
+        for f in glob.glob('[0-9]' * 5 + '.png'):
+            os.remove(f)
+
+
+if __name__ == '__main__':
+    os.chdir(parentdir)
+    cfg = get_arguments()
+    make_animation(cfg)

scripts/fit_planar_c.py

@@ -1,4 +1,11 @@
 # -*- coding: utf-8 -*-
+"""
+A script fitting the planar_c parameter of the main simulation to commuting data.
+The data must be provided as in the examples below in an array, where the first row
+contains commuting distances in km, and the second row provides a fraction of people
+commuting up to the distance given on the same position in the first row, but more
+than the previous distance. The second row must add up to 1.
+"""
 import numpy as np
 import matplotlib.pyplot as plt
 from scipy.optimize import minimize