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new bf5b9b9 SDAP-312: Improved UTM reprojection speed (#129)
bf5b9b9 is described below
commit bf5b9b9bbf1ad7ca8b750a7c91ead8582ac7e281
Author: Stepheny Perez <[email protected]>
AuthorDate: Thu May 20 14:17:21 2021 -0700
SDAP-312: Improved UTM reprojection speed (#129)
---
analysis/webservice/algorithms_spark/Matchup.py | 9 ++++-----
1 file changed, 4 insertions(+), 5 deletions(-)
diff --git a/analysis/webservice/algorithms_spark/Matchup.py
b/analysis/webservice/algorithms_spark/Matchup.py
index 0734965..a5277b3 100644
--- a/analysis/webservice/algorithms_spark/Matchup.py
+++ b/analysis/webservice/algorithms_spark/Matchup.py
@@ -552,7 +552,6 @@ def match_satellite_to_insitu(tile_ids, primary_b,
matchup_b, parameter_b, tt_b,
# Find the centroid of the matchup bounding box and initialize the
projections
matchup_center = box(matchup_min_lon, matchup_min_lat, matchup_max_lon,
matchup_max_lat).centroid.coords[0]
aeqd_proj = pyproj.Proj(proj='aeqd', lon_0=matchup_center[0],
lat_0=matchup_center[1])
- lonlat_proj = pyproj.Proj(proj='lonlat')
# Increase temporal extents by the time tolerance
matchup_min_time = tiles_min_time - tt_b.value
@@ -592,7 +591,7 @@ def match_satellite_to_insitu(tile_ids, primary_b,
matchup_b, parameter_b, tt_b,
except ValueError:
y, x = Point(*[float(c) for c in
edge_point['point'].split(',')]).coords[0]
- matchup_points[n][0], matchup_points[n][1] =
pyproj.transform(p1=lonlat_proj, p2=aeqd_proj, x=x, y=y)
+ matchup_points[n][0], matchup_points[n][1] = aeqd_proj(x, y)
print("%s Time to convert match points for partition %s to %s" % (
str(datetime.now() - the_time), tile_ids[0], tile_ids[-1]))
@@ -603,14 +602,14 @@ def match_satellite_to_insitu(tile_ids, primary_b,
matchup_b, parameter_b, tt_b,
# The actual matching happens in the generator. This is so that we only
load 1 tile into memory at a time
match_generators = [match_tile_to_point_generator(tile_service, tile_id,
m_tree, edge_results, bounding_wkt_b.value,
- parameter_b.value,
rt_b.value, lonlat_proj, aeqd_proj) for tile_id
+ parameter_b.value,
rt_b.value, aeqd_proj) for tile_id
in tile_ids]
return chain(*match_generators)
def match_tile_to_point_generator(tile_service, tile_id, m_tree, edge_results,
search_domain_bounding_wkt,
- search_parameter, radius_tolerance,
lonlat_proj, aeqd_proj):
+ search_parameter, radius_tolerance,
aeqd_proj):
from nexustiles.model.nexusmodel import NexusPoint
from webservice.algorithms_spark.Matchup import DomsPoint # Must import
DomsPoint or Spark complains
@@ -630,7 +629,7 @@ def match_tile_to_point_generator(tile_service, tile_id,
m_tree, edge_results, s
# Get list of indices of valid values
valid_indices = tile.get_indices()
primary_points = np.array(
- [pyproj.transform(p1=lonlat_proj, p2=aeqd_proj,
x=tile.longitudes[aslice[2]], y=tile.latitudes[aslice[1]]) for
+ [aeqd_proj(tile.longitudes[aslice[2]], tile.latitudes[aslice[1]]) for
aslice in valid_indices])
print("%s Time to convert primary points for tile %s" %
(str(datetime.now() - the_time), tile_id))
