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Fix casting warnings #1400

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merged 3 commits into from
Jul 19, 2023
Merged

Fix casting warnings #1400

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3a18c03
Casting fields directly to float32 on reading, to fix numpy RuntimeWa…
erikvansebille Jul 19, 2023
1c39751
Fixing nan dtypes in particlefile zarr array extending
erikvansebille Jul 19, 2023
501d5cd
Removing debug-code line
erikvansebille Jul 19, 2023
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1 change: 1 addition & 0 deletions parcels/field.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1449,6 +1449,7 @@ def computeTimeChunk(self, data, tindex):
interp_method=self.interp_method,
data_full_zdim=self.data_full_zdim,
chunksize=self.chunksize,
cast_data_dtype=self.cast_data_dtype,
rechunk_callback_fields=rechunk_callback_fields,
chunkdims_name_map=self.netcdf_chunkdims_name_map,
netcdf_decodewarning=self.netcdf_decodewarning)
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5 changes: 3 additions & 2 deletions parcels/fieldfilebuffer.py
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Expand Up @@ -22,6 +22,7 @@ def __init__(self, filename, dimensions, indices, timestamp=None,
self.indices = indices
self.dataset = None
self.timestamp = timestamp
self.cast_data_dtype = kwargs.pop('cast_data_dtype', np.float32)
self.ti = None
self.interp_method = interp_method
self.data_full_zdim = data_full_zdim
Expand Down Expand Up @@ -207,7 +208,7 @@ def data_access(self):
data = self.dataset[self.name]
ti = range(data.shape[0]) if self.ti is None else self.ti
data = self._apply_indices(data, ti)
return np.array(data)
return np.array(data, dtype=self.cast_data_dtype)

@property
def time(self):
Expand Down Expand Up @@ -740,7 +741,7 @@ def data_access(self):
self.rechunk_callback_fields()
self.chunking_finalized = True

return data
return data.astype(self.cast_data_dtype)


class DeferredDaskFileBuffer(DaskFileBuffer):
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10 changes: 5 additions & 5 deletions parcels/particlefile/baseparticlefile.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,16 +201,16 @@

def _extend_zarr_dims(self, Z, store, dtype, axis):
if axis == 1:
a = np.full((Z.shape[0], self.chunks[1]), np.nan, dtype=dtype)
a = np.full((Z.shape[0], self.chunks[1]), self.fill_value_map[dtype], dtype=dtype)
obs = zarr.group(store=store, overwrite=False)["obs"]
if len(obs) == Z.shape[1]:
obs.append(np.arange(self.chunks[1])+obs[-1]+1)
else:
extra_trajs = max(self.maxids - Z.shape[0], self.chunks[0])
if len(Z.shape) == 2:
a = np.full((extra_trajs, Z.shape[1]), np.nan, dtype=dtype)
a = np.full((extra_trajs, Z.shape[1]), self.fill_value_map[dtype], dtype=dtype)

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else:
a = np.full((extra_trajs,), np.nan, dtype=dtype)
a = np.full((extra_trajs,), self.fill_value_map[dtype], dtype=dtype)

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Z.append(a, axis=axis)
zarr.consolidate_metadata(store)

Expand Down Expand Up @@ -281,11 +281,11 @@
varout = self._convert_varout_name(var)
if varout not in ['trajectory']: # because 'trajectory' is written as coordinate
if self.write_once(var):
data = np.full((arrsize[0],), np.nan, dtype=self.vars_to_write[var])
data = np.full((arrsize[0],), self.fill_value_map[self.vars_to_write[var]], dtype=self.vars_to_write[var])

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data[ids_once] = pset.collection.getvardata(var, indices_to_write_once)
dims = ["trajectory"]
else:
data = np.full(arrsize, np.nan, dtype=self.vars_to_write[var])
data = np.full(arrsize, self.fill_value_map[self.vars_to_write[var]], dtype=self.vars_to_write[var])
data[ids, 0] = pset.collection.getvardata(var, indices_to_write)
dims = ["trajectory", "obs"]
ds[varout] = xr.DataArray(data=data, dims=dims, attrs=attrs[varout])
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