nais package¶
nais.checker module¶
- nais.checker.startNaisChecker(dataset_path, bounding_boxes_path)¶
Manually check a NAIS dataset and draw bounding boxes around bad data
- Parameters:
- data_filestr
Name of NAIS netcdf data file including path
- boundary_filestr
Name of file where to save the coordinates of bad data bounding boxes.
nais.processor module¶
- nais.processor.make_config_template(file_name)¶
Make a configuration file template
- Parameters:
- file_namestr
full path to configuration file
For example /home/user/config.yml
- nais.processor.nais_processor(config_file)¶
Processes NAIS data
- Parameters:
- config_filestr
full path to configuration file
nais.utils module¶
- nais.utils.combine_data(source_dir, date_range, time_reso, flag_sensitivity=0.5)¶
- Parameters:
- source_dirstr
Directory for NAIS datafiles
- date_rangepandas.DatetimeIndex
Range of dates for combining data
- time_resostr
A pandas date frequency string
See for all options here: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
- flag_sensitivityfloat
fraction of time flag needs to be present in resampling
- Returns:
- xarray.Dataset or None
Combined dataset, None if no data in the date range
- nais.utils.combine_databases(database_list, combined_database)¶
Combine JSON databases
- Parameters:
- database_listlist of str
List of full paths to databases that should be combined
First database should have the earliest data, second database the second earliest and so on
- combined_databasestr
full path to combined database
- nais.utils.remove_flagged_rows(ds, flag)¶
- Parameters:
- dsxarray.Dataset
NAIS dataset
- flagstr
Flag to be removed
- Returns:
- xarray.Dataset
NAIS dataset with flag rows set to NaN