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Describe the bug
If one builds a l3 dataset for a time period that ends before the available ground tracks are exhausted, extending the dataset at a later stage results in skipping data of the month after the first l3 dataset ended.
This is because of a "dirty" convention to define the period that should be considered. The convention is to stop on the first day of the "end" time step if this is a month or a year. This results in some data in the month after the requested period being present - which, in turn, leads to that month being skipped if the datasets is being extended.
To Reproduce
Steps to reproduce the behavior:
l3.build_dataset("01-01", 2010, 2015)
l3.build_dataset("01-01", 2010, 2025, reprocess=False) # not sure about reprocess, but turning it of reproduces the behavior in any case
Expected behavior
There should never be data gaps that could even go unnoticed.
The text was updated successfully, but these errors were encountered:
Describe the bug
If one builds a l3 dataset for a time period that ends before the available ground tracks are exhausted, extending the dataset at a later stage results in skipping data of the month after the first l3 dataset ended.
This is because of a "dirty" convention to define the period that should be considered. The convention is to stop on the first day of the "end" time step if this is a month or a year. This results in some data in the month after the requested period being present - which, in turn, leads to that month being skipped if the datasets is being extended.
To Reproduce
Steps to reproduce the behavior:
Expected behavior
There should never be data gaps that could even go unnoticed.
The text was updated successfully, but these errors were encountered: