1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
|
from typing import Any, Dict, Optional
import xarray as xr
from . import esa_safe
def to_group_zarr(
product_path: esa_safe.PathType,
output_store: Any,
groups: Optional[Dict[str, str]] = None,
**kwargs: Any,
) -> None:
root = xr.open_dataset(product_path, engine="sentinel-1")
root.to_zarr(output_store, mode="w", **kwargs)
if groups is None:
groups = {g: g for g in root.attrs["subgroups"]}
for group_out, group_in in groups.items():
try:
group_ds = xr.open_dataset(
product_path, engine="sentinel-1", group=group_in
)
group_ds.to_zarr(output_store, mode="a", group=group_out, **kwargs)
except FileNotFoundError:
pass
# Apparently there is no way to save SLC images because "netcdf4" doesn't support complex data
# and "h5netcdf" crashes on an issue related to dimension names
def to_group_netcdf(
product_path: esa_safe.PathType,
output_store: str,
groups: Optional[Dict[str, str]] = None,
**kwargs: Any,
) -> None:
root = xr.open_dataset(product_path, engine="sentinel-1")
root.to_netcdf(output_store, mode="w", **kwargs)
if groups is None:
groups = {g: g for g in root.attrs["subgroups"]}
for group_out, group_in in groups.items():
try:
group_ds = xr.open_dataset(
product_path, engine="sentinel-1", group=group_in
)
group_ds.to_netcdf(output_store, mode="a", group=group_out, **kwargs)
except FileNotFoundError:
pass
|
