Include a scenario graph in the report.

cara/apps/calculator/report_generator.py

@@ -1,7 +1,12 @@
+import base64
 from datetime import datetime
+import io
 from pathlib import Path
 
 import jinja2
+import matplotlib
+matplotlib.use('agg')
+import matplotlib.pyplot as plt
 import numpy as np
 
 from cara import models
@@ -10,13 +15,19 @@ from .model_generator import FormData
 
 def calculate_report_data(model: models.Model):
     resolution = 600
-    times = list(np.linspace(0, 10, resolution))
+
+    # TODO: Have this for exposed not infected.
+    t_start = model.infected.presence.boundaries()[0][0]
+    t_end = model.infected.presence.boundaries()[-1][1]
+
+    times = list(np.linspace(t_start, t_end, resolution))
     concentrations = [model.concentration(time) for time in times]
     highest_const = max(concentrations)
     prob = model.infection_probability()
     er = model.infected.emission_rate(0.1)
     exposed_occupants = model.exposed_occupants
     r0 = prob * exposed_occupants / 100
+
     return {
         "times": times,
         "concentrations": concentrations,
@@ -25,14 +36,46 @@ def calculate_report_data(model: models.Model):
         "emission_rate": er,
         "exposed_occupants": exposed_occupants,
         "R0": r0,
+        "scenario_plot_src": embed_figure(plot(times, concentrations)),
     }
 
+
+def embed_figure(figure) -> str:
+    # Draw the scenario graph.
+    img_data = io.BytesIO()
+
+    figure.savefig(img_data, format='png', bbox_inches="tight")
+    plt.close()
+    img_data.seek(0)
+    pic_hash = base64.b64encode(img_data.read()).decode('ascii')
+    # A src suitable for a tag such as f'<img id="scenario_concentration_plot" src="{result}">.
+    return f'data:image/png;base64,{pic_hash}'
+
+
+def plot(times, concentrations):
+    fig = plt.figure()
+    ax = fig.add_subplot(1, 1, 1)
+    ax.plot(times, concentrations)
+    ax.spines['right'].set_visible(False)
+    ax.spines['top'].set_visible(False)
+
+    ax.set_xlabel('Hours from start of event')
+    ax.set_ylabel('Concentration ($q/m^3$)')
+    ax.set_title('Concentration of infectious quanta aerosols')
+
+    # top = max([0.75, max(concentrations)])
+    # print(max(concentrations))
+    # ax.set_ylim(bottom=1e-4, top=top)
+    return fig
+
+
 def build_report(model: models.Model, form: FormData):
     now = datetime.now()
     time = now.strftime("%d/%m/%Y %H:%M:%S")
     request = {"the": "form", "request": "data"}
+
     context = {
-        'model': model, 
+        'model': model,
         'request': request, 
         'creation_date': time, 
         'model_version': 'Beta v1.0.0', 
@@ -65,8 +108,6 @@ def build_report(model: models.Model, form: FormData):
         'coffee_duration': form.coffee_duration, 
         'coffee_times': [['00:00','00:00'], ['00:00','00:00'], ['00:00','00:00'], ['00:00','00:00']], 
         'mask_wearing': form.mask_wearing, 
-        'infection_probability': round(model.infection_probability(), 2), 
-        'reproduction_rate': 2
     }
 
     context.update(calculate_report_data(model))

cara/apps/calculator/templates/report.html.j2

@@ -121,8 +121,11 @@
 	</ul>
 
 	<p class="result_title">Results:</p>
-		<p class="data_text"> In this scenario, the estimated probability of one exposed occupant getting infected P(i) is {{ infection_probability }} % and the estimated basic reproduction rate (R0) is {{ reproduction_rate }}.<p>
+		<p class="data_text">
+		In this scenario, the estimated probability of one exposed occupant getting infected P(i) is {{ "{:#.2g}".format(prob_inf) }}% and the estimated basic reproduction rate (R0) is {{ "{:#.2g}".format(R0) }}.
+		<p>
 	<p class="data_title">Exposure graph:</p>
+	<img id="scenario_concentration_plot" src="{{ scenario_plot_src }}">
 
 	<br><br><br><br><br><br><br>
 	<div style="border: 2px solid black; padding: 15px;">