measurementStopDate_1 returns the start date and time_difference is affected (tens of seconds). Indeed the SAR acquisition dates are recomputed after passing start date in every cell and after resampling.
here
|
ds["time"] = xr.DataArray( |
|
data=np.full(ds["lon"].shape, t), |
|
dims=("owiAzSize", "owiRaSize"), |
|
attrs={"long_name": "time", "standard_name": "time"}, |
|
) |
here
|
# FIXME astype unknown effect on bool or else |
and here
|
unique_time = np.unique(ds[meta.time_name]) |
unique_time = np.unique(ds[meta.time_name])
ds.attrs["measurementStartDate"] = str(np.nanmin(unique_time))
ds.attrs["measurementStopDate"] = str(np.nanmax(unique_time))
- solution : keep time_1 as a constant, remove it from variables and ensure that time attributes are kept
measurementStopDate_1 returns the start date and time_difference is affected (tens of seconds). Indeed the SAR acquisition dates are recomputed after passing start date in every cell and after resampling.
here
coloc_sat/coloc_sat/sar_meta.py
Lines 54 to 58 in d52a603
here
coloc_sat/coloc_sat/intersection.py
Line 900 in d52a603
and here
coloc_sat/coloc_sat/intersection.py
Line 1262 in d52a603