From c7434f7b80b95a3c9bf512a1ba363609eef91be5 Mon Sep 17 00:00:00 2001
From: Coda Phillips <cphillips@sean.ssec.wisc.edu>
Date: Thu, 18 Aug 2016 16:20:22 -0500
Subject: [PATCH] Document electronics_checks
---
electronic_checks.py | 18 ++++++++++++------
1 file changed, 12 insertions(+), 6 deletions(-)
diff --git a/electronic_checks.py b/electronic_checks.py
index 5bd1af4..b41d1f8 100644
--- a/electronic_checks.py
+++ b/electronic_checks.py
@@ -6,18 +6,19 @@ import itertools
electronic_checks = BaseCheckList()
def find_bb_outliers(frame, parameters, bb):
+ """
+ Find outliers in blackbody temperatures.
+ Annotate any problems, and set quality flags for each thermistor
+ """
window_length = parameters.get('window_length', 50)
if bb == 'HBB':
delta_thresh = .001
- bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
- bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
- bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
else:
delta_thresh = .01
- bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
- bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
- bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
+ bbb_outliers = np.array(list(_scan_for_outliers(frame, '{}bottomTemp'.format(bb), delta_thresh)))
+ bba_outliers = np.array(list(_scan_for_outliers(frame, '{}apexTemp'.format(bb), delta_thresh)))
+ bbt_outliers = np.array(list(_scan_for_outliers(frame, '{}topTemp'.format(bb), delta_thresh)))
variable_qcs = pd.DataFrame({
'qc_{}bottomTemp'.format(bb) : bbb_outliers * 1,
@@ -53,12 +54,17 @@ def _find_6sigma_outliers(frame, window_length, estimation_func=_compute_robust_
return estimation_func(frame, window_length) > 6
def _scan_for_outliers(frame, variable, delta_thresh):
+ """
+ Check for temperature changes exceeding the delta_thresh rate in degK / sec
+ """
last = None
for i, row in frame.iterrows():
+ # First row cannot be an outlier
if last is None:
yield False
last = row
else:
+ # Compare each row to previous non-outlier row
time_diff = (row.datetime - last.datetime).total_seconds()
variable_diff = row[variable] - last[variable]
if abs(variable_diff / time_diff) < delta_thresh:
--
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