automatically cleans up data before generating the graph

.nova/Publishing/Phlaym.json

@@ -1,5 +1,8 @@
 {
   "identifier" : "65C0B698-D114-41B3-8F58-13D74F7D3E93",
+  "ignoredFilePatterns" : [
+    "data.csv"
+  ],
   "remotePath" : "\/home\/phlaym\/jwst-plotter",
   "server" : "Phlaym",
   "usesPublishing" : true

.nova/Tasks/Graph.json

@@ -6,5 +6,5 @@
     }
   },
   "identifier" : "EADBCF2F-F2FC-418C-9C08-EBAE9F98C8BD",
-  "openLogOnRun" : "fail"
+  "openLogOnRun" : "start"
 }

graph.py

@@ -13,8 +13,41 @@ FILTER_DEPLOYMENTS = True
 
 plt.rcParams["figure.autolayout"] = True
 plt.rcParams['figure.figsize'] = (16, 10)
+
 data_frame = pd.read_csv("data.csv", delimiter=';')
 
+# Filter rows, so that only the following will be kept:
+# First and last rows,
+# rows which have a different temperature than the one before,
+# and rows which have a different temperature than the one after.
+#
+# Basically: If the temperatures don't change for a few rows, keep only the first
+# and last of that run
+last_row = None
+timestamps_to_keep = []
+for row in data_frame.iterrows():
+    # row is actually a tuple with index at 0 and the row data at 1. We care only about the row data
+    row = row[1]
+    # First row: Always keep it
+    if last_row is None:
+        last_row = row
+        timestamps_to_keep.append(row['timestamp'])
+        continue
+    # Any temp changed?
+    keep_row = (last_row['tempWarmSide1C'] != row['tempWarmSide1C'] or
+                last_row['tempWarmSide2C'] != row['tempWarmSide2C'] or
+                last_row['tempCoolSide1C'] != row['tempCoolSide1C'] or
+                last_row['tempCoolSide2C'] != row['tempCoolSide2C'])
+    # Keep this and the previous row
+    if keep_row:
+        timestamps_to_keep.append(last_row['timestamp'])
+        timestamps_to_keep.append(row['timestamp'])
+    last_row = row
+# Always keep the last row
+timestamps_to_keep.append(data_frame.iloc[-1:]['timestamp'])
+# Filter rows by the timestamps we just saved
+data_frame = data_frame[data_frame.timestamp.isin(timestamps_to_keep)]
+
 # Subplot, to move legend next to plot
 # 1 row, 1 col, index: 1
 plt.subplot(1, 1, 1)