plot done with zoomed section

examples/coevolution/plots.py

@@ -1,3 +1,4 @@
+from cProfile import label
 from email import header
 import os
 import numpy as np
@@ -1416,7 +1417,7 @@ def plot_lt_foraging_gentic(ip=0.85, time=1000):
     plt.close(fig)
 
 
-def plot_lt_foraging_gentic_baseline_foraging(ip=0.85, time=10000):
+def plot_foraging_baseline(ip=0.85, time=10000):
     fig = plt.figure(figsize=(8,6), dpi=200)
     # data = np.mean(np.squeeze(read_data_n_agent_perturbations_all(
     #     n=100, iter=12000, threshold=7, time=time, iprob=0.85,
@@ -1434,13 +1435,6 @@ def plot_lt_foraging_gentic_baseline_foraging(ip=0.85, time=10000):
     xvalues = np.array(list(range(12002)))
     # mask = xvalues % 500 == 0
     mask = [True] * len(xvalues)
-    # ax1.plot(xvalues[mask], data[1,:][mask], 'o-', label='Lateral Transfer Rate')
-    # ax1.plot(xvalues[mask], data[2,:][mask], 'o-', label='Genetic Step Rate')
-    # ax1.legend(fontsize="small", loc="upper left", title='Metric')
-    # ax1.set_xlabel('Evolution Steps')
-    # ax1.set_ylabel('Rate per step')
-    # ax1.set_yticks(range(0, 50, 10))
-
     ax1.plot(xvalues[mask], q2[0,:][mask], '-', label='Foraging', color='green')
     ax1.fill_between(
                 xvalues[mask], q1[0,:][mask], q3[0,:][mask], color='seagreen', alpha=0.3)
@@ -1457,14 +1451,67 @@ def plot_lt_foraging_gentic_baseline_foraging(ip=0.85, time=10000):
     plt.title('Baseline')
     plt.tight_layout()
     maindir = '/tmp/swarm/data/experiments/'
+    fig.savefig(
+        maindir + 'baselineallplot'+ '.png')
+    plt.close(fig)
+
+
+def plot_foraging_baseline_trap(ip=0.85, time=1000):
+    fig = plt.figure(figsize=(8,6), dpi=200)
+    basedata = np.squeeze(read_data_n_agent_perturbations_all(
+        n=100, iter=12000, threshold=7, time=10000, iprob=0.85,
+        no_objects=1, radius=5, idx=[2,4]))
+
+    baseq2 = np.median(basedata, axis=1)
+    baseq1 = np.quantile(basedata, axis=1, q=0.25)
+    baseq3 = np.quantile(basedata, axis=1, q=0.75)
+    ax1 = fig.add_subplot(1, 1, 1)
+    xvalues = np.array(list(range(12002)))
+    mask = xvalues % 500 == 0
+    # mask = [True] * len(xvalues)
+    ax1.plot(xvalues[mask], baseq2[0,:][mask], '-', label='Baseline Foraging', color='green')
+    ax1.fill_between(
+                xvalues[mask], baseq1[0,:][mask], baseq3[0,:][mask], color='seagreen', alpha=0.3)
+
+    ax_zoom = ax1.inset_axes([0.05,0.5,0.47,0.47])
+    data = np.squeeze(read_data_n_agent_perturbations_all(
+        n=100, iter=12000, threshold=7, time=time, iprob=0.85, addobject='Traps',
+        no_objects=1, radius=10, idx=[2,4]))
+
+    q2 = np.median(data, axis=1)
+    q1 = np.quantile(data, axis=1, q=0.25)
+    q3 = np.quantile(data, axis=1, q=0.75)
+    xvalues = np.array(list(range(12002)))
+    mask = [True] * len(xvalues)
+    ax1.plot(xvalues[mask], q2[0,:][mask], '-', label='Foraging with Trap', color='red')
+    ax1.fill_between(
+                xvalues[mask], q1[0,:][mask], q3[0,:][mask], color='salmon', alpha=0.3)
+
+    ax_zoom.plot(xvalues[mask], q2[0,:][mask], '-', label='Trap', color='red')
+    ax_zoom.plot(xvalues[mask], baseq2[0,:][mask], '-', label='Baseline', color='green')
+    ax_zoom.set_xlim(1000,2000)
+    ax_zoom.set_ylim(0,8)
+    ax1.indicate_inset_zoom(ax_zoom, edgecolor="black", label="Zoomed", alpha=0.5)
+
+    ax1.legend(fontsize="small", loc="lower right", title="Learning Efficiency")
+    ax1.set_xlabel('Evolution Steps')
+    ax1.set_ylabel('Foraging (%)')
+    ax1.set_yticks(range(0, 105, 20))
+    ax2 = ax1.twinx()
+    ax2.set_yticks(range(0, 105, 20))
+
+    plt.title('Trap Added at 1000 Step')
+    plt.tight_layout()
+    maindir = '/tmp/swarm/data/experiments/'
     # fname = 'agentsitecomp' + agent
     # nadir = os.path.join(maindir, str(100))
 
     fig.savefig(
-        maindir + 'baselineallplot'+ '.png')
+        maindir + 'baseline_trap_zoom_'+ str(time)+ '.png')
     plt.close(fig)
 
 
+
 def obstacle_introduced_compare():
     timings = range(7000, 11001, 1000)
     # data50 = [read_data_n_agent_perturbations(
@@ -1523,7 +1570,9 @@ def main():
     # obstacle_introduced_compare()
     # for t in range(1000,11001,1000):
     #    plot_lt_foraging_gentic(time=t)
-    plot_lt_foraging_gentic_baseline_foraging()
+    # plot_foraging_baseline()
+    # plot_foraging_baseline_obstacle()
+    plot_foraging_baseline_trap()
 
 
 if __name__ == '__main__':

requirements.txt

@@ -1,3 +1,3 @@
 numpy
 psycopg2-binary
-joblib
+joblib