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Commit bc422734 authored by tomrink's avatar tomrink
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parent 52851844
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...@@ -19,7 +19,7 @@ class MyGenericException(Exception): ...@@ -19,7 +19,7 @@ class MyGenericException(Exception):
class LonLatGrid: class LonLatGrid:
# grd_lons, grd_lats: the longitude, latitude of each grid point (must be 2D grids), must have same shape # grd_lons, grd_lats: the longitude, latitude of each grid point (must be 2D grids), must have same shape
# Incoming longitude must be in range: 0 - 360 degrees # Incoming longitude must be in range: 0 - 360 degrees
# Can have NaN for off Earth grid points. # Can have NaN for off Earth grid points (these are handled internally).
def __init__(self, grd_lons, grd_lats): def __init__(self, grd_lons, grd_lats):
if grd_lons.shape != grd_lats.shape: if grd_lons.shape != grd_lats.shape:
raise MyGenericException('incoming lons,lats must have same shape') raise MyGenericException('incoming lons,lats must have same shape')
...@@ -50,9 +50,10 @@ class LonLatGrid: ...@@ -50,9 +50,10 @@ class LonLatGrid:
# locate nearest neighbor for incoming target in earth coordinates (Should not have NaNs) # locate nearest neighbor for incoming target in earth coordinates (Should not have NaNs)
# lons, lats can be flat or 2D # lons, lats can be flat or 2D
# closeness_threshold: if < distance of located_point to target, return off grid
# incoming longitude must be in range: 0 - 360 degrees # incoming longitude must be in range: 0 - 360 degrees
# returns NN indexes relative to the grid determined in the ctr. # returns NN indexes relative to the grid determined in the ctr.
def value_to_index(self, lons, lats): def value_to_index(self, lons, lats, closeness_threshold=2000):
if lons.shape != lats.shape: if lons.shape != lats.shape:
raise MyGenericException('incoming lons,lats must have same shape') raise MyGenericException('incoming lons,lats must have same shape')
...@@ -65,8 +66,9 @@ class LonLatGrid: ...@@ -65,8 +66,9 @@ class LonLatGrid:
xy = np.stack([lons, lats], axis=1) xy = np.stack([lons, lats], axis=1)
dist, indices = self.kd.query(np.deg2rad(xy)) dist, indices = self.kd.query(np.deg2rad(xy))
dist *= 6370000 # convert unit radius to meters
valid = indices < self.map_indexes.size valid = (indices < self.map_indexes.size) & (dist < closeness_threshold)
indices = indices[valid] indices = indices[valid]
return self.map_indexes[indices], indices return self.map_indexes[indices], indices
......
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