72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
#!/bin/python
|
|
|
|
import matplotlib.pyplot as plt
|
|
import numpy as np
|
|
from hexplot import plot_hexagon
|
|
|
|
def plot_alive_ants_vs_time(model, title=None):
|
|
y = model.datacollector.get_model_vars_dataframe()["alive_ants"]
|
|
plt.figure(figsize=(10,10), dpi=600)
|
|
plt.plot(y)
|
|
plt.xlabel("time step")
|
|
plt.ylabel("alive agents")
|
|
if title is None:
|
|
plt.savefig("alive_agents_over_time.eps")
|
|
else:
|
|
plt.savefig(f"{title}.png")
|
|
|
|
|
|
def plot_connectivity_vs_time(model, title=None):
|
|
y = model.datacollector.get_model_vars_dataframe()["connectivity"]
|
|
plt.figure(figsize=(10,10), dpi=600)
|
|
plt.plot(y)
|
|
plt.xlabel("time step")
|
|
plt.ylabel("No. of food sources connected to the nest")
|
|
if title is None:
|
|
plt.savefig("connectivity_over_time.eps")
|
|
else:
|
|
plt.savefig(f"{title}.png")
|
|
|
|
|
|
def dead_ants_vs_time(model, title=None):
|
|
y = np.cumsum(model.datacollector.get_model_vars_dataframe()["dying_ants"])
|
|
plt.figure(figsize=(10,10), dpi=600)
|
|
plt.plot(y)
|
|
plt.xlabel("time step")
|
|
plt.ylabel("dead agents")
|
|
if title is None:
|
|
plt.savefig("dead_agents_over_time.eps")
|
|
else:
|
|
plt.savefig(f"{title}.png")
|
|
|
|
|
|
def cum_successful_ants_vs_time(model, title=None):
|
|
y = model.datacollector.get_model_vars_dataframe()["successful_walkers"]
|
|
plt.figure(figsize=(10,10), dpi=600)
|
|
plt.plot(y)
|
|
plt.xlabel("time step")
|
|
plt.ylabel("cummulative successful agents")
|
|
if title is None:
|
|
plt.savefig("cumsum_successful_agents_over_time.eps")
|
|
else:
|
|
plt.savefig(f"{title}.png")
|
|
|
|
|
|
def plot_heatmap(model, low=10, high=200):
|
|
for time in np.arange(0, model.max_steps + 1, 1000):
|
|
pheromone_concentration = model.datacollector.get_model_vars_dataframe()["pheromone_a"][time]
|
|
a = pheromone_concentration
|
|
#plot_hexagon(a)
|
|
pheromone_concentration = model.datacollector.get_model_vars_dataframe()["pheromone_b"][time]
|
|
b = pheromone_concentration
|
|
#plot_hexagon(b)
|
|
c = np.max([a,b], axis=0)
|
|
c = a + b
|
|
c = np.clip(c, 1, 1000000000)
|
|
c = np.log(c)
|
|
c = c/np.max(c)
|
|
food_locations = np.nonzero(model.grid.fields['food'])
|
|
x_food = [ food[0] for food in food_locations ]
|
|
y_food = [ food[1] for food in food_locations ]
|
|
plot_hexagon(c, title=f"cummulative pheromone density at timestep {time}")
|