use pandas.to_timedelta function instead of invoking deprecated ctor …

…arg (#918)

* use pandas.to_timedelta function instead of invoking deprecated ctor (unit argument will be gone)

* handle all old units

* pin pandas >=1.5

* Update weldx/tags/time/timedeltaindex.py

Co-authored-by: Çağtay Fabry <cagtay.fabry@bam.de>

CHANGELOG.md

@@ -1,10 +1,20 @@
 # Release Notes
 
+## 0.6.8 (unreleased)
+
+### Changes
+
+- use pandas.to_timedelta function to pass units to the TimeDeltaIndex object \[{pull}`918`\].
+
+### Dependencies
+
+- unpin nbval testing dependency.
+
 ## 0.6.7 (2023.08.24)
 
 ### Added
 
-- added `weldx.exceptions` module with `WeldxException` \[{pull}`871`\] .
+- added `weldx.exceptions` module with `WeldxException` \[{pull}`871`\].
 
 ### Fixes
 

pyproject.toml

@@ -37,7 +37,7 @@ requires-python = ">=3.9"
 dependencies = [
     "numpy >=1.20",
     "asdf >=2.15.1",
-    "pandas >=1.0",
+    "pandas >=1.5",
     "xarray >=2022.9.0",
     "scipy >=1.6.2",
     "sympy >=1.6",
@@ -64,7 +64,7 @@ test = [
     "pytest >=6",
     "pytest-cov",
     "pytest-xdist",
-    "nbval <0.10",
+    "nbval",
 ]
 vis = [
     "weldx_widgets >=0.2",
@@ -125,6 +125,7 @@ filterwarnings = [
     "ignore::DeprecationWarning:traittypes.*:",
     "ignore:Passing method to :FutureWarning:xarray.*:",
     "error::pint.UnitStrippedWarning",
+    #"error::FutureWarning",  # todo: we want to enable this, as it notifies us about upcoming failures due to upstream changes.
 ]
 
 [tool.coverage.run]

weldx/schemas/weldx.bam.de/weldx/time/time-0.1.0.yaml

@@ -34,7 +34,7 @@ examples:
         values: !<asdf://weldx.bam.de/weldx/tags/time/datetimeindex-0.1.0>
           start: !<asdf://weldx.bam.de/weldx/tags/time/timestamp-0.1.0> '2021-01-01T00:00:00'
           end: !<asdf://weldx.bam.de/weldx/tags/time/timestamp-0.1.0> '2021-01-01T00:00:02'
-          freq: S
+          freq: s
           min: !<asdf://weldx.bam.de/weldx/tags/time/timestamp-0.1.0> '2021-01-01T00:00:00'
           max: !<asdf://weldx.bam.de/weldx/tags/time/timestamp-0.1.0> '2021-01-01T00:00:02'
         reference_time: !<asdf://weldx.bam.de/weldx/tags/time/timestamp-0.1.0> '2021-01-01T00:00:00'

weldx/schemas/weldx.bam.de/weldx/time/timedeltaindex-0.1.0.yaml

@@ -13,7 +13,7 @@ examples:
       !<asdf://weldx.bam.de/weldx/tags/time/timedeltaindex-0.1.0>
         start: !<asdf://weldx.bam.de/weldx/tags/time/timedelta-0.1.0> P0DT0H0M0S
         end: !<asdf://weldx.bam.de/weldx/tags/time/timedelta-0.1.0> P0DT0H0M10S
-        freq: 2S
+        freq: 2s
         min: !<asdf://weldx.bam.de/weldx/tags/time/timedelta-0.1.0> P0DT0H0M0S
         max: !<asdf://weldx.bam.de/weldx/tags/time/timedelta-0.1.0> P0DT0H0M10S
   -

weldx/tags/time/timedeltaindex.py

@@ -8,6 +8,14 @@
 
 __all__ = ["TimedeltaIndexConverter"]
 
+PANDAS_OLD_UNIT_SUFFIXES = dict(H="h", T="min", S="s", L="ms", U="us", N="ns")
+
+
+def _handle_converted_pd_tdi_units(node: TaggedDict):
+    """Convert changed units in Pandas.Datetimeindex to valid values."""
+    for suf in PANDAS_OLD_UNIT_SUFFIXES:
+        node["freq"] = node["freq"].replace(suf, PANDAS_OLD_UNIT_SUFFIXES[suf])
+
 
 class TimedeltaIndexConverter(WeldxConverter):
     """A simple implementation of serializing pandas TimedeltaIndex."""
@@ -33,6 +41,7 @@ def to_yaml_tree(self, obj: pd.TimedeltaIndex, tag: str, ctx) -> dict:
     def from_yaml_tree(self, node: dict, tag: str, ctx):
         """Construct TimedeltaIndex from tree."""
         if "freq" in node:
+            _handle_converted_pd_tdi_units(node)
             return pd.timedelta_range(
                 start=node["start"], end=node["end"], freq=node["freq"]
             )
@@ -43,6 +52,7 @@ def from_yaml_tree(self, node: dict, tag: str, ctx):
     def shape_from_tagged(node: TaggedDict) -> list[int]:
         """Calculate the shape from static tagged tree instance."""
         if "freq" in node:
+            _handle_converted_pd_tdi_units(node)
             tdi_temp = pd.timedelta_range(
                 start=str(node["start"]),  # can't handle TaggedString directly
                 end=str(node["end"]),

weldx/tests/asdf_tests/test_asdf_core.py

@@ -424,12 +424,12 @@ def test_coordinate_system_manager_time_dependencies(
         lcs_tdp_1_time_ref = pd.Timestamp("2000-03-17")
     lcs_tdp_1 = tf.LocalCoordinateSystem(
         coordinates=Q_([[1, 2, 3], [4, 5, 6]], "mm"),
-        time=pd.TimedeltaIndex([1, 2], "D"),
+        time=pd.to_timedelta([1, 2], "D"),
         time_ref=lcs_tdp_1_time_ref,
     )
     lcs_tdp_2 = tf.LocalCoordinateSystem(
         coordinates=Q_([[3, 7, 3], [9, 5, 8]], "mm"),
-        time=pd.TimedeltaIndex([1, 2], "D"),
+        time=pd.to_timedelta([1, 2], "D"),
         time_ref=pd.Timestamp("2000-03-21"),
     )
 

weldx/tests/test_core.py

@@ -227,10 +227,9 @@ class TestTimeSeries:
 
     ME = MathematicalExpression
     DTI = pd.DatetimeIndex
-    TDI = pd.TimedeltaIndex
     TS = TimeSeries
 
-    time_discrete = pd.TimedeltaIndex([0, 1, 2, 3, 4], unit="s")
+    time_discrete = pd.to_timedelta([0, 1, 2, 3, 4], "s")
     value_constant = Q_(1, "m")
     values_discrete = Q_(np.array([10, 11, 12, 14, 16]), "mm")
     me_expr_str = "a*t + b"
@@ -251,7 +250,7 @@ class TestTimeSeries:
         "data, time, interpolation, shape_exp",
         [
             (Q_(1, "m"), None, None, (1,)),
-            (Q_([3, 7, 1], "m"), TDI([0, 1, 2], unit="s"), "step", (3,)),
+            (Q_([3, 7, 1], "m"), pd.to_timedelta([0, 1, 2], unit="s"), "step", (3,)),
             (Q_([3, 7, 1], ""), Q_([0, 1, 2], "s"), "step", (3,)),
             (Q_([3, 7, 1], ""), DTI(["2010", "2011", "2012"]), "step", (3,)),
         ],
@@ -329,12 +328,17 @@ def test_construction_expression(data, shape_exp, unit_exp):
     @pytest.mark.parametrize(
         "data, dims, coords, exception_type",
         [
-            (Q_([1, 2, 3], "m"), "time", dict(time=TDI([1, 2, 3])), None),
-            (Q_([1, 2, 3], "m"), "a", dict(a=TDI([1, 2, 3])), KeyError),
-            (Q_([[1, 2]], "m"), ("a", "time"), dict(a=[2], time=TDI([1, 2])), None),
+            (Q_([1, 2, 3], "m"), "time", dict(time=pd.to_timedelta([1, 2, 3])), None),
+            (Q_([1, 2, 3], "m"), "a", dict(a=pd.to_timedelta([1, 2, 3])), KeyError),
+            (
+                Q_([[1, 2]], "m"),
+                ("a", "time"),
+                dict(a=[2], time=pd.to_timedelta([1, 2])),
+                None,
+            ),
             (Q_([1, 2, 3], "m"), "time", None, KeyError),
             (Q_([1, 2, 3], "m"), "time", dict(time=[1, 2, 3]), TypeError),
-            ([1, 2, 3], "time", dict(time=TDI([1, 2, 3])), TypeError),
+            ([1, 2, 3], "time", dict(time=pd.to_timedelta([1, 2, 3])), TypeError),
         ],
     )
     @pytest.mark.parametrize("reference_time", [None, "2000-01-01"])
@@ -382,7 +386,7 @@ def test_construction_exceptions(
 
     # test_comparison -------------------------------------
 
-    time_wrong_values = TDI([0, 1, 2, 3, 5], unit="s")
+    time_wrong_values = pd.to_timedelta([0, 1, 2, 3, 5], "s")
     values_discrete_wrong = Q_(np.array([10, 11, 12, 15, 16]), "mm")
     values_unit_wrong = Q_(np.array([10, 11, 12, 14, 16]), "s")
     values_unit_prefix_wrong = Q_(np.array([10, 11, 12, 14, 16]), "m")
@@ -426,9 +430,9 @@ def test_comparison(ts, ts_other, result_exp):
 
     # test_interp_time -----------------------------------------------------------------
 
-    time_single = pd.TimedeltaIndex([2.1], "s")
+    time_single = pd.to_timedelta([2.1], "s")
     time_single_q = Q_(2.1, "s")
-    time_mul = pd.TimedeltaIndex([-3, 0.7, 1.1, 1.9, 2.5, 3, 4, 7], "s")
+    time_mul = pd.to_timedelta([-3, 0.7, 1.1, 1.9, 2.5, 3, 4, 7], "s")
     time_mul_q = Q_([-3, 0.7, 1.1, 1.9, 2.5, 3, 4, 7], "s")
     results_exp_vec = [
         [-8, 3, -3],

weldx/tests/test_time.py

@@ -7,7 +7,6 @@
 import xarray as xr
 from pandas import DatetimeIndex as DTI
 from pandas import Timedelta, Timestamp, date_range
-from pandas import TimedeltaIndex as TDI
 from pint import DimensionalityError
 
 from weldx.constants import Q_
@@ -77,7 +76,7 @@ def _initialize_time_type(
 
 def _is_timedelta(cls_type):
     """Return ``True`` if the passed type is a timedelta type."""
-    return cls_type in [TDI, Timedelta, np.timedelta64] or (
+    return cls_type in [pd.to_timedelta, Timedelta, np.timedelta64] or (
         cls_type is Time and not Time.is_absolute
     )
 
@@ -143,7 +142,9 @@ def _get_init_exp_values(
             val = [v + offset for v in delta_val]
 
         val = val[0] if data_was_scalar else val
-        exp_timedelta = Timedelta(val, "s") if data_was_scalar else TDI(val, "s")
+        exp_timedelta = (
+            Timedelta(val, "s") if data_was_scalar else pd.to_timedelta(val, "s")
+        )
 
         # expected datetime
         exp_datetime = None
@@ -168,7 +169,7 @@ def _get_init_exp_values(
             (str, "timedelta"),
             (Time, "timedelta"),
             (Q_, "timedelta"),
-            TDI,
+            pd.to_timedelta,
             Timedelta,
             np.timedelta64,
             (str, "datetime"),
@@ -209,7 +210,7 @@ def test_init(
         # skip matrix cases that do not work --------------------
         if arr and input_type in [Timedelta, Timestamp]:
             return
-        if not arr and input_type in [DTI, TDI]:
+        if not arr and input_type in [DTI, pd.to_timedelta]:
             return
 
         # create input values -----------------------------------
@@ -247,7 +248,7 @@ def test_init(
             LocalCoordinateSystem(
                 coordinates=Q_(np.zeros((2, 3)), "mm"), time=["2000", "2001"]
             ),
-            TimeSeries(Q_([2, 4, 1], "m"), TDI([1, 2, 3], "s")),
+            TimeSeries(Q_([2, 4, 1], "m"), pd.to_timedelta([1, 2, 3], "s")),
             TimeSeries(Q_([2, 4, 1], "m"), ["2001", "2002", "2003"]),
         ],
     )
@@ -262,7 +263,7 @@ def test_init_from_time_dependent_types(time_dep_type):
     @pytest.mark.parametrize(
         "time, time_ref, raises",
         [
-            (TDI([3, 2, 1]), None, ValueError),
+            (pd.to_timedelta([3, 2, 1]), None, ValueError),
             (DTI(["2010", "2000"]), None, ValueError),
             (["2010", "2000"], None, ValueError),
             (Q_([3, 2, 1], "s"), None, ValueError),
@@ -290,7 +291,7 @@ def test_init_exception(time, time_ref, raises):
             (str, "timedelta"),
             (Time, "timedelta"),
             (Q_, "timedelta"),
-            TDI,
+            pd.to_timedelta,
             Timedelta,
             np.timedelta64,
             (str, "datetime"),
@@ -331,7 +332,7 @@ def test_add_timedelta(
         # skip array cases where the type does not support arrays
         if other_type in [Timedelta, Timestamp] and other_is_array:
             return
-        if not other_is_array and other_type in [DTI, TDI]:
+        if not other_is_array and other_type in [DTI, pd.to_timedelta]:
             return
 
         # skip __radd__ cases where we got conflicts with the other types' __add__
@@ -341,7 +342,7 @@ def test_add_timedelta(
             np.timedelta64,
             np.datetime64,
             DTI,
-            TDI,
+            pd.to_timedelta,
         ):
             return
 
@@ -392,7 +393,7 @@ def test_add_timedelta(
             str,
             Time,
             Q_,
-            TDI,
+            pd.to_timedelta,
             Timedelta,
             np.timedelta64,
         ],
@@ -421,11 +422,16 @@ def test_add_datetime(
         # skip array cases where the type does not support arrays
         if other_type in [Timedelta, Timestamp] and other_is_array:
             return
-        if not other_is_array and other_type in [DTI, TDI]:
+        if not other_is_array and other_type in [DTI, pd.to_timedelta]:
             return
 
         # skip __radd__ cases where we got conflicts with the other types' __add__
-        if not other_on_rhs and other_type in (Q_, np.ndarray, np.timedelta64, TDI):
+        if not other_on_rhs and other_type in (
+            Q_,
+            np.ndarray,
+            np.timedelta64,
+            pd.to_timedelta,
+        ):
             return
 
         # setup rhs
@@ -477,7 +483,7 @@ def _date_diff(date_1: str, date_2: str, unit: str) -> int:
             (str, "timedelta"),
             (Time, "timedelta"),
             (Q_, "timedelta"),
-            TDI,
+            pd.to_timedelta,
             Timedelta,
             np.timedelta64,
             (str, "datetime"),
@@ -532,7 +538,7 @@ def test_sub(
         # skip array cases where the type does not support arrays or scalars
         if other_type in [Timedelta, Timestamp] and other_is_array:
             return
-        if not other_is_array and other_type in [DTI, TDI]:
+        if not other_is_array and other_type in [DTI, pd.to_timedelta]:
             return
 
         # skip __rsub__ cases where we got conflicts with the other types' __sub__
@@ -542,7 +548,7 @@ def test_sub(
             np.timedelta64,
             np.datetime64,
             DTI,
-            TDI,
+            pd.to_timedelta,
         ):
             return
 
@@ -612,13 +618,16 @@ def test_sub(
         "arg, expected",
         [
             # timedeltas
-            (TDI([42], unit="ns"), TDI([42], unit="ns")),
+            (pd.to_timedelta([42], unit="ns"), pd.to_timedelta([42], unit="ns")),
             (pd.timedelta_range("0s", "20s", 10), pd.timedelta_range("0s", "20s", 10)),
-            (np.timedelta64(42), TDI([42], unit="ns")),
-            (np.array([-10, 0, 20]).astype("timedelta64[ns]"), TDI([-10, 0, 20], "ns")),
-            (Q_(42, "ns"), TDI([42], unit="ns")),
-            ("10s", TDI(["10s"])),
-            (["5ms", "10s", "2D"], TDI(["5 ms", "10s", "2D"])),
+            (np.timedelta64(42), pd.to_timedelta([42], unit="ns")),
+            (
+                np.array([-10, 0, 20]).astype("timedelta64[ns]"),
+                pd.to_timedelta([-10, 0, 20], "ns"),
+            ),
+            (Q_(42, "ns"), pd.to_timedelta([42], unit="ns")),
+            ("10s", pd.to_timedelta(["10s"])),
+            (["5ms", "10s", "2D"], pd.to_timedelta(["5 ms", "10s", "2D"])),
             # datetimes
             (np.datetime64(50, "Y"), DTI(["2020-01-01"])),
             ("2020-01-01", DTI(["2020-01-01"])),
@@ -647,10 +656,10 @@ def test_pandas_index(arg, expected):
             ("1s", "ms", 1000),
             ("1s", "us", 1000000),
             ("1s", "ns", 1000000000),
-            (TDI([1, 2, 3], "s"), "s", [1, 2, 3]),
-            (TDI([1, 2, 3], "s"), "ms", np.array([1, 2, 3]) * 1e3),
-            (TDI([1, 2, 3], "s"), "us", np.array([1, 2, 3]) * 1e6),
-            (TDI([1, 2, 3], "s"), "ns", np.array([1, 2, 3]) * 1e9),
+            (pd.to_timedelta([1, 2, 3], "s"), "s", [1, 2, 3]),
+            (pd.to_timedelta([1, 2, 3], "s"), "ms", np.array([1, 2, 3]) * 1e3),
+            (pd.to_timedelta([1, 2, 3], "s"), "us", np.array([1, 2, 3]) * 1e6),
+            (pd.to_timedelta([1, 2, 3], "s"), "ns", np.array([1, 2, 3]) * 1e9),
             ("2020-01-01", "s", 0),
         ],
     )
@@ -775,7 +784,14 @@ def test_resample_exceptions(values, number_or_interval, raises):
                 ],
                 date_range("2020-02-01", periods=8, freq="1D"),
             ),
-            ([TDI([1, 5]), TDI([2, 6, 7]), TDI([1, 3, 7])], TDI([1, 2, 3, 5, 6, 7])),
+            (
+                [
+                    pd.to_timedelta([1, 5]),
+                    pd.to_timedelta([2, 6, 7]),
+                    pd.to_timedelta([1, 3, 7]),
+                ],
+                pd.to_timedelta([1, 2, 3, 5, 6, 7]),
+            ),
         ],
     )
     @pytest.mark.parametrize("test_instance", [True, False])