Merge pull request #1168 from developmentseed/ab/add-sel-by-datetime-to-xarray

Add datetime to _cast_to_type

Author: abarciauskas-bgse

CHANGES.md

@@ -2,6 +2,10 @@
 
 ## Unreleased
 
+### titiler.xarray
+
+* use dimension's `dtype` to cast user *selection*
+
 ## 0.22.2 (2025-06-02)
 
 ### titiler.application

src/titiler/xarray/tests/test_io_tools.py

@@ -67,11 +67,6 @@ def test_get_variable():
     assert da["time"][0] == numpy.datetime64("2022-01-01")
     assert da["time"][1] == numpy.datetime64("2023-01-01")
 
-    da = get_variable(ds, "dataset", sel=["time=1st of January 2023"])
-    assert da.rio.crs
-    assert da.dims == ("y", "x")
-    assert da["time"] == numpy.datetime64("2023-01-01")
-
     # Select the Nearest Time
     da = get_variable(ds, "dataset", sel=["time=2024-01-01T01:00:00"], method="nearest")
     assert da.rio.crs
@@ -169,6 +164,46 @@ def test_get_variable():
         da = get_variable(ds, "dataset")
 
 
+def test_get_variable_datetime_tz():
+    """test io.get_variable with datetime and timezones."""
+    arr = numpy.arange(0, 33 * 35 * 2).reshape(2, 33, 35)
+    data = xarray.DataArray(
+        arr,
+        dims=("time", "y", "x"),
+        coords={
+            "x": numpy.arange(-170, 180, 10),
+            "y": numpy.arange(-80, 85, 5),
+            "time": [
+                datetime(2022, 1, 1),
+                datetime(2023, 1, 1),
+            ],
+        },
+    )
+    data.attrs.update({"valid_min": arr.min(), "valid_max": arr.max()})
+    assert not data.rio.crs
+    assert data.dims == ("time", "y", "x")
+    ds = data.to_dataset(name="dataset")
+
+    da = get_variable(ds, "dataset", sel=["time=2023-01-01T00:00:00"], method="nearest")
+    assert da.rio.crs
+    assert da.dims == ("y", "x")
+    assert da["time"] == numpy.datetime64("2023-01-01")
+
+    da = get_variable(
+        ds, "dataset", sel=["time=2023-01-01T00:00:00Z"], method="nearest"
+    )
+    assert da.rio.crs
+    assert da.dims == ("y", "x")
+    assert da["time"] == numpy.datetime64("2023-01-01")
+
+    da = get_variable(
+        ds, "dataset", sel=["time=2023-01-01T00:00:00+03:00"], method="nearest"
+    )
+    assert da.rio.crs
+    assert da.dims == ("y", "x")
+    assert da["time"] == numpy.datetime64("2023-01-01")
+
+
 @pytest.mark.parametrize(
     "protocol,filename",
     [

src/titiler/xarray/titiler/xarray/io.py

@@ -4,8 +4,6 @@
 from urllib.parse import urlparse
 
 import attr
-import numpy
-import pandas
 import xarray
 from morecantile import TileMatrixSet
 from rio_tiler.constants import WEB_MERCATOR_TMS
@@ -133,19 +131,6 @@ def _arrange_dims(da: xarray.DataArray) -> xarray.DataArray:
     return da
 
 
-def _cast_to_type(value, dtype: Any) -> Any:
-    if "timedelta" in str(dtype):
-        value = pandas.to_timedelta(value)
-
-    elif numpy.issubdtype(dtype, numpy.integer):
-        value = int(value)
-
-    elif numpy.issubdtype(dtype, numpy.floating):
-        value = float(value)
-
-    return value
-
-
 def get_variable(
     ds: xarray.Dataset,
     variable: str,
@@ -171,7 +156,10 @@ def get_variable(
         for s in sel:
             val: Union[str, slice]
             dim, val = s.split("=")
-            val = _cast_to_type(val, da[dim].dtype)
+
+            # cast string to dtype of the dimension
+            if da[dim].dtype != "O":
+                val = da[dim].dtype.type(val)
 
             if dim in _idx:
                 _idx[dim].append(val)