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Allow missing/empty cycle time files in timeseries (#211)
## Description - Added support for missing/empty cycle time files when running in timeseries mode - Adding requirements that work on discover milan nodes ## Demonstration Comparing two time series of different lengths: ![time_series_omb](https://github.com/user-attachments/assets/0b91a062-28a3-4bb2-ae0d-6aa8d919abfe) Timeseries with a missing cycle time: ![time_series_omb](https://github.com/user-attachments/assets/d97dd883-7f62-410d-a8f7-31e30edc4eb5)
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setuptools>=59.4.0 | ||
pyyaml>=6.0 | ||
pycodestyle>=2.8.0 | ||
netCDF4 | ||
matplotlib | ||
cartopy>=0.21.1 | ||
scipy>=1.9.3 | ||
xarray>=2022.3.0 | ||
pandas>=1.4.0 | ||
numpy==1.22.3 | ||
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# Not explicitly part of eva but dependcies of eva dependencies already in spack-stack | ||
# versions need to be set to avoid other versions being picked | ||
pyproj | ||
importlib-metadata==4.8.2 | ||
contourpy==1.0.7 | ||
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# Additional packages | ||
git+https://github.com/NOAA-EMC/emcpy.git@f7b863d9508b921a78d7ff0e53de0b95e9a176f7#egg=emcpy | ||
scikit-learn | ||
seaborn | ||
hvplot | ||
nbconvert | ||
bokeh | ||
geopandas | ||
geoviews |
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setuptools>=59.4.0 | ||
pyyaml>=6.0 | ||
pycodestyle>=2.8.0 | ||
netCDF4 | ||
matplotlib | ||
cartopy>=0.21.1 | ||
scipy>=1.9.3 | ||
xarray>=2022.3.0 | ||
pandas>=1.4.0 | ||
numpy==1.22.3 | ||
attrs==21.4.0 | ||
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# Not explicitly part of eva but dependcies of eva dependencies already in spack-stack | ||
# versions need to be set to avoid other versions being picked | ||
pyproj | ||
importlib_metadata==7.1.0 | ||
contourpy==1.0.7 | ||
msgpack>=1.0.0 | ||
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# Additional packages | ||
git+https://github.com/NOAA-EMC/emcpy.git@f7b863d9508b921a78d7ff0e53de0b95e9a176f7#egg=emcpy | ||
scikit-learn | ||
seaborn | ||
hvplot | ||
nbconvert | ||
bokeh | ||
geopandas | ||
geoviews |
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import os | ||
import numpy as np | ||
import xarray as xr | ||
from eva.data.data_driver import data_driver | ||
from eva.data.data_collections import DataCollections | ||
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filename_retrieval = { | ||
"IodaObsSpace": lambda dataset_config: dataset_config["filenames"][0], | ||
"JediVariationalBiasCorrection": lambda dataset_config: dataset_config["bias_file"], | ||
} | ||
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def get_filename(dataset_config, logger): | ||
""" Retrieve filename using given type """ | ||
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dataset_type = dataset_config["type"] | ||
logger.assert_abort(dataset_type in filename_retrieval, | ||
f'Unknown dataset_type {dataset_type}') | ||
filename = filename_retrieval[dataset_type](dataset_config) | ||
return filename | ||
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def check_file(filename, logger): | ||
""" Check if first file exists and is nonzero """ | ||
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if not os.path.isfile(filename): | ||
logger.abort('First file provided to timeseries must exist.') | ||
elif os.stat(filename).st_size == 0: | ||
logger.abort('First file provided to timeseries must be nonzero.') | ||
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def create_empty_data(timeseries_config, dataset_config, timing, logger): | ||
""" Creating an empty data collection to use for missing cycle times """ | ||
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dc_tmp = DataCollections() | ||
collection = timeseries_config["collection"] | ||
data_driver(dataset_config, dc_tmp, timing, logger) | ||
dataset = dc_tmp.get_data_collection(collection) | ||
empty_data = xr.full_like(dataset, np.nan) | ||
dc = DataCollections() | ||
dc.create_or_add_to_collection(collection, empty_data) | ||
return dc |
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