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add function to normalize all time coord units #732

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merged 4 commits into from
Jan 16, 2025
Merged

add function to normalize all time coord units #732

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210acc5
add function to normalize all time coord units
jtmims Jan 13, 2025
5a42bda
add logic for all time unit types
jtmims Jan 16, 2025
715bbf2
re-add whitespace
jtmims Jan 16, 2025
d3cd927
typo
jtmims Jan 16, 2025
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34 changes: 31 additions & 3 deletions src/preprocessor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -886,7 +886,11 @@ def crop_date_range(self, case_date_range: util.DateRange, xr_ds, time_coord) ->
decode_times=True,
use_cftime=True # use cftime instead of np.datetime6
)
cal = xr_ds[time_coord.name].attrs.get('calendar', 'noleap')
cal = 'noleap'
if 'calendar' in xr_ds[time_coord.name].attrs:
cal = xr_ds[time_coord.name].attrs['calendar']
elif 'calendar' in xr_ds[time_coord.name].encoding:
cal = xr_ds[time_coord.name].encoding['calendar']

ds_date_time = xr_ds[time_coord.name].values
ds_start_time = ds_date_time[0]
Expand Down Expand Up @@ -914,7 +918,6 @@ def crop_date_range(self, case_date_range: util.DateRange, xr_ds, time_coord) ->
ds_end = self.cast_to_cftime(ds_end_time, cal)
date_range_cf_start = self.cast_to_cftime(case_date_range.start.lower, cal)
date_range_cf_end = self.cast_to_cftime(case_date_range.end.lower, cal)

if ds_start < date_range_cf_start and ds_end < date_range_cf_start or \
ds_end > date_range_cf_end and ds_start > date_range_cf_end:
new_xr_ds = None
Expand All @@ -931,7 +934,6 @@ def crop_date_range(self, case_date_range: util.DateRange, xr_ds, time_coord) ->
# dataset contains all of requested date range
elif date_range_cf_start>=ds_start and date_range_cf_end<=ds_end:
new_xr_ds = xr_ds.sel({time_coord.name: slice(date_range_cf_start, date_range_cf_end)})

return new_xr_ds

def check_group_daterange(self, df: pd.DataFrame, date_range: util.DateRange,
Expand Down Expand Up @@ -1012,6 +1014,31 @@ def check_group_daterange(self, df: pd.DataFrame, date_range: util.DateRange,
# hit an exception; return empty DataFrame to signify failure
return pd.DataFrame(columns=group_df.columns)

def normalize_time_units(self, subset_dict: dict, log=_log) -> dict:
"""
Some datasets will have the time units defined based on each individual file.
This function updates each time unit to rely on the earliest year grabbed
in the query stage.
"""
time_units = [subset_dict[f].time.units for f in list(subset_dict)]

if len(set(time_units)) > 1:
if all(["days since " in u for u in time_units]):
#assumes "days since ????" unit format
start = np.sort([int(u.replace("days since ", "")[:4]) for u in time_units])[0]
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@jtmims This should accommodate cases where units are leap seconds (not common, but that doesn't mean we won't see it).

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I have pushed new commits which adds logic to handle multiple types of time units

new_unit = f"days since {start}-01-01 00:00:00"
for f in list(subset_dict):
current = int(subset_dict[f].time.units.replace("days since ", "")[:4])
if current > start:
subset_dict[f].coords['time'] = subset_dict[f].time.assign_attrs(
units=new_unit
)
for i, v in enumerate(subset_dict[f].time.values):
subset_dict[f].coords['time'].values[i] = v + 365*(current-start) + 1
else:
raise AttributeError("Different units were found for time coord in each file. "
"We were unable to normalize due to the units not being in 'days since ' format")
return subset_dict

def query_catalog(self,
case_dict: dict,
Expand Down Expand Up @@ -1124,6 +1151,7 @@ def query_catalog(self,
# tl;dr hic sunt dracones
var_xr = []
if not var.is_static:
cat_subset_dict = self.normalize_time_units(cat_subset_dict)
time_sort_dict = {f: cat_subset_dict[f].time.values[0]
for f in list(cat_subset_dict)}
time_sort_dict = dict(sorted(time_sort_dict.items(), key=lambda item: item[1]))
Expand Down
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