From 3aba5dbac57073160d09d4d92a8e0102d11ae83a Mon Sep 17 00:00:00 2001
From: Jesse Mapel <jmapel@usgs.gov>
Date: Thu, 2 Jan 2020 10:27:47 -0700
Subject: [PATCH] Added check for repeated fields in protobuf
---
plio/io/io_controlnetwork.py | 9 ++++++++-
plio/io/tests/test_io_controlnetwork.py | 6 +++---
2 files changed, 11 insertions(+), 4 deletions(-)
diff --git a/plio/io/io_controlnetwork.py b/plio/io/io_controlnetwork.py
index 57774f9..13ddfd5 100644
--- a/plio/io/io_controlnetwork.py
+++ b/plio/io/io_controlnetwork.py
@@ -270,6 +270,9 @@ class IsisStore(object):
arr = arr.ravel().tolist()
point_spec.aprioriCovar.extend(arr)
+ # If field is repeated you must extend instead of assign
+ elif cnf._CONTROLPOINTFILEENTRYV0002.fields_by_name[attr].label == 3:
+ getattr(point_spec, attr).extend(g.iloc[0][df_attr])
else:
setattr(point_spec, attr, attrtype(g.iloc[0][df_attr]))
@@ -284,7 +287,11 @@ class IsisStore(object):
# Un-mangle common attribute names between points and measures
df_attr = self.measure_field_map.get(attr, attr)
if df_attr in g.columns:
- setattr(measure_spec, attr, attrtype(m[df_attr]))
+ # If field is repeated you must extend instead of assign
+ if cnf._CONTROLPOINTFILEENTRYV0002_MEASURE.fields_by_name[attr].label == 3:
+ getattr(measure_spec, attr).extend(m[df_attr])
+ else:
+ setattr(measure_spec, attr, attrtype(m[df_attr]))
# ISIS pixels are centered on (0.5, 0.5). NDArrays are (0,0) based.
measure_spec.sample = m['sample'] + 0.5
measure_spec.line = m['line'] + 0.5
diff --git a/plio/io/tests/test_io_controlnetwork.py b/plio/io/tests/test_io_controlnetwork.py
index 9d13793..8b628ce 100644
--- a/plio/io/tests/test_io_controlnetwork.py
+++ b/plio/io/tests/test_io_controlnetwork.py
@@ -39,12 +39,12 @@ class TestWriteIsisControlNetwork(unittest.TestCase):
serial_times = {295: '1971-07-31T01:24:11.754',
296: '1971-07-31T01:24:36.970'}
cls.serials = {i:'APOLLO15/METRIC/{}'.format(j) for i, j in enumerate(serial_times.values())}
- columns = ['id', 'pointType', 'serialnumber', 'measureType', 'sample', 'line', 'image_index']
+ columns = ['id', 'pointType', 'serialnumber', 'measureType', 'sample', 'line', 'image_index', 'pointLog', 'measureLog']
data = []
for i in range(cls.npts):
- data.append((i, 2, cls.serials[0], 2, 0, 0, 0))
- data.append((i, 2, cls.serials[1], 2, 0, 0, 1))
+ data.append((i, 2, cls.serials[0], 2, 0, 0, 0, [], []))
+ data.append((i, 2, cls.serials[1], 2, 0, 0, 1, [], []))
df = pd.DataFrame(data, columns=columns)
--
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