From 46f067311b513c8302587adcfffe0b96e17ddc21 Mon Sep 17 00:00:00 2001
From: wroberts <wroberts4@wisc.edu>
Date: Wed, 4 Sep 2019 12:37:06 -0500
Subject: [PATCH] Make timestamp index when creating dataframe and add more
documentation
---
aosstower/level_00/influxdb.py | 12 +++++++++---
1 file changed, 9 insertions(+), 3 deletions(-)
diff --git a/aosstower/level_00/influxdb.py b/aosstower/level_00/influxdb.py
index d29faa4..4dee9a4 100644
--- a/aosstower/level_00/influxdb.py
+++ b/aosstower/level_00/influxdb.py
@@ -78,7 +78,13 @@ class Updater(object):
if self.data.get(key) is None:
self.data[key] = np.array([])
self.data[key] = np.append(self.data[key][time_mask], record[key])
- # Gets the seconds from the start of the current year. This makes any interval chronologically consistent.
+ # Gets the seconds from the start of the current year. This makes any interval equal to or smaller than a
+ # year an absolute interval (ie if the submit interval was 5 minutes, then data is submitted at 5, 10, 15,
+ # etc). For example: if "reference" used the start of the current minute and we wanted to submit anything in
+ # longer intervals than a minute, then the times that data is submitted would not be consistent. i.e. if the
+ # current minute was 13 and the submit interval was 5 minutes, then data would be submitted at 18, 23, 28,
+ # etc. If data collection went down and the next recorded current minute was 14, then data would be submitted
+ # at 19, 24, 29, etc (inconsistent).
reference = pd.datetime(record['timestamp'].year, 1, 1)
progress = (record['timestamp'] - reference).total_seconds() % self.submit_interval
# If data hits or will pass over a submit_interval interval, return data.
@@ -86,8 +92,8 @@ class Updater(object):
return self._calculate_averages()
def _calculate_averages(self):
- frame = pd.DataFrame(self.data)
- frame.set_index('timestamp', inplace=True)
+ index = self.data.pop('timestamp')
+ frame = pd.DataFrame(self.data, index=index)
frame.mask(frame == -99999., inplace=True)
# Add wind direction components so we can average wind direction properly.
frame['wind_east'], frame['wind_north'], _ = calc.wind_vector_components(frame['wind_speed'],
--
GitLab