fixed the failing test by reusing the hiopy's assumption of time attribute to exist

apps/hiopy/_distribute_work.py

@@ -2,11 +2,8 @@
 
 import logging
 from math import ceil, prod
-
 import numpy as np
 
-from ._zarr_utils import get_time_axis
-
 logger = logging.getLogger(__name__)
 
 
@@ -49,9 +46,8 @@ def _estimate_size(*data_vars):
     """
     size = 0.0
     for dv in data_vars:
-        time_axis = get_time_axis(dv)
-        if time_axis is not None:
-            dt = time_axis[1] - time_axis[0]
+        if dv.time is not None:
+            dt = dv.time[1] - dv.time[0]
             size += prod(dv.shape[1:]) * dv.dtype.itemsize / dt
     return size
 

apps/hiopy/tests/test_distribute_work.py

@@ -18,7 +18,9 @@ def _create_test_vars():
     time.attrs["units"] = "seconds since 2000-01-01"
 
     var1 = zarr.zeros(shape=[10, 10], path="var1", store=store, chunks=(2, 5))
+    var1.time = time
     var2 = zarr.zeros(shape=[10, 10], path="var2", store=store, chunks=(2, 5))
+    var2.time = time
     for v in (var1, var2):
         v.attrs["_ARRAY_DIMENSIONS"] = ("time", "cell")
 

apps/hiopy/worker.py

@@ -146,14 +146,14 @@ def main():
         def_grid(coyote, data_vars[0], chunk_slice)
 
         for v in data_vars:
-            dt = v["time"][1] - v["time"][0]
+            dt = v.time[1] - v.time[0]
             # compute time start index
             t0 = (
                 np.datetime64(start_datetime())
-                - np.datetime64(v["time"].attrs["units"][len("seconds since ") :])
+                - np.datetime64(v.time.attrs["units"][len("seconds since ") :])
             ) / np.timedelta64(1, "s") + dt
-            t0_idx = np.searchsorted(v["time"], t0)
-            assert v["time"][t0_idx] == t0, "start_datetime not found in time axis"
+            t0_idx = np.searchsorted(v.time, t0)
+            assert v.time[t0_idx] == t0, "start_datetime not found in time axis"
 
             # see YAC_REDUCTION_TIME_NONE etc. (TODO: pass constants through coyote)
             time_methods2yac = {"point": 0, "sum": 1, "mean": 2, "min": 3, "max": 4}