Added deployment stages

graph.py

@@ -6,6 +6,8 @@ import pandas as pd
 from matplotlib import pyplot as plt
 import matplotlib.dates as md
 
+SHOW_DEPLOYMENTS = True
+
 plt.rcParams["figure.autolayout"] = True
 
 data_frame = pd.read_csv("data.csv", delimiter=';')
@@ -45,5 +47,54 @@ for i, j in zip(datenums, data_frame.tempCoolSide2C):
 
 plt.axhline(y=-223, color='darkblue', linestyle=':', label='Operating temperature')
 
+launch_date = datetime.datetime.fromisoformat('2021-12-25T12:20+00:00')
+deployment_names = [
+    'Sunshield Pallet',
+    'DTA Deployment',
+    'Sunshield Covers Release',
+    'Sunshield Mid-Boom',
+    'Sunshield Layer Tensioning Ongoing',
+    'Sunshield Tensioning Complete',
+    'Secondary Mirror Deployment',
+    'Aft Deployed Instrument Radiator',
+    'Port Primary Mirror Wing',
+    'WEBB IS FULLY DEPLOYED!',
+    'Individual Mirror Segment Movements',
+    'L2 Insertion Burn',
+    'WEBB IS ORBITING L2'
+]
+
+# deployment dates, based on "+ X days"
+deployment_dates = [md.date2num(launch_date + datetime.timedelta(days=x)) for x in [
+    3,
+    4,
+    5,
+    6,
+    9,
+    10,
+    11,
+    12,
+    13,
+    14,
+    15,
+    26,
+    29.5]
+]
+
+latest_available_temp_date = max(datenums)
+earliest_available_temp_date = min(datenums)
+
+deployments_data = zip(deployment_names, deployment_dates)
+filtered_deployments_data = filter(lambda tup:
+                                   tup[1] >= earliest_available_temp_date and
+                                   tup[1] <= latest_available_temp_date, deployments_data)
+
+max_temp = max(max(data_frame.tempWarmSide1C), max(data_frame.tempWarmSide2C))
+
+if SHOW_DEPLOYMENTS:
+    for label, date in filtered_deployments_data:
+        plt.axvline(x=date, color='gray', linestyle=':')
+        plt.text(x=date, y=max_temp+30, s=label, rotation=25)
+
 plt.legend(bbox_to_anchor=(1, 1), loc="upper left")
 plt.show()