frankinspace commented on a change in pull request #132:
URL:
https://github.com/apache/incubator-sdap-nexus/pull/132#discussion_r709661092
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File path: data-access/nexustiles/model/nexusmodel.py
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@@ -100,6 +136,8 @@ def nexus_point_generator(self, include_nan=False):
def get_indices(self, include_nan=False):
if include_nan:
return list(np.ndindex(self.data.shape))
+ if self.is_multi:
+ return np.argwhere(self.data[0])
Review comment:
I may not totally understand your concern but, I don't think that's
exactly what he meant. For two variables in the same collection, if they came
from different instruments and/or have different quality attributes to them it
is possible that there is a measurement at index i,j for variable 1 but not at
index i,j for variable 2.
The "mask" is already part of the data (in the form of fill values). When
read by numpy they get turned into masked arrays where the mask is part of the
data array itself. So you don't need to look up a mask based on the variable
being read, it's just part of the data
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