Plots now export bin file for later visualization 📈

Author: davidgur

tools/at_home_plot.py

@@ -8,6 +8,7 @@
 
 import os
 import sys
+import pickle as pl
 import pandas as pd
 import numpy as np
 import matplotlib.pyplot as plt
@@ -39,15 +40,18 @@
             at_home_data.append([sum(x) for x in zip(data['G9A'], data['G10A'], data['G11A'], data['G12A'])])
 
 # Plot the at_home_data with low opacity
+fig = plt.figure(figsize=(18.5, 10.5))
+ax = fig.gca()
+
 for data in at_home_data:
-    plt.plot(np.linspace(0, len(data) * 15 // (24 * 60), len(data)), data, alpha=0.1)
+    ax.plot(np.linspace(0, len(data) * 15 // (24 * 60), len(data)), data, alpha=0.1)
 
 # Get the "average" at home plot
 avg_data = savgol_filter([np.nanmedian(data_at_y) for data_at_y in itertools.zip_longest(*at_home_data, fillvalue=0)], 89, 3)
-plt.plot(np.linspace(0, len(avg_data) * 15 // (24*60), len(avg_data)), avg_data)
+ax.plot(np.linspace(0, len(avg_data) * 15 // (24*60), len(avg_data)), avg_data)
 
-plt.title("Number of people absent from school due to measles infection")
 plt.xlabel("Time (days)")
 plt.ylabel("# of people")
 
-plt.show()
+# Pickle
+pl.dump(fig, open(sys.argv[2], 'wb+'))

tools/infected_visualization.py

@@ -10,6 +10,7 @@
 import sys
 import pandas as pd
 import numpy as np
+import pickle as pl
 import matplotlib.pyplot as plt
 
 import itertools
@@ -45,9 +46,10 @@
 # Get the "average" at home plot
 avg_data = savgol_filter([np.nanmedian(data_at_y) for data_at_y in itertools.zip_longest(*infected_data, fillvalue=0)], 89, 3)
 plt.plot(np.linspace(0, len(avg_data) * 15 // (24*60), len(avg_data)), avg_data)
-
-plt.title("Number of people infected with measles due to measles outbreak")
 plt.xlabel("Time (days)")
 plt.ylabel("# of people")
 
-plt.show()
+fig = plt.gcf()
+
+# Pickle
+pl.dump(fig, open(sys.argv[2], 'wb+'))

tools/plot_population.py

@@ -9,6 +9,7 @@
 import sys
 import itertools
 import pandas as pd
+import pickle as pl
 import numpy as np
 import matplotlib.pyplot as plt
 
@@ -65,7 +66,7 @@
 vacc_rate = 100 * (by_grade_data[9]['V'][0][0] / (by_grade_data[9]['S'][0][0] + by_grade_data[9]['V'][0][0] + 1))
 a = 0.02 # Alpha
 
-fig = plt.figure()
+fig = plt.figure(figsize=(20,10), dpi=100)
 grade9_ax  = fig.add_subplot(221)
 grade10_ax = fig.add_subplot(222)
 grade11_ax = fig.add_subplot(223)
@@ -131,5 +132,7 @@
 
 fig.suptitle(
     'Compartmentalization of students in different grades within a secondary school during a measles outbreak\n (Vaccination rate: ' + str(round(vacc_rate, 2)) + '%)')
-    
-plt.show()
+
+
+# Pickle
+pl.dump(fig, open(sys.argv[2], 'wb+'))