visiontoolkit.constants.CONFIG_DEFAULTS

visiontoolkit.constants.CONFIG_DEFAULTS = {'cfp-cscale': 'plasma', 'cfp-input-general-config': {'legend': True, 'linewidth': 0.4, 'markersize': 5, 'title': 'Input: observational field (path, to be used for co-location, with its corresponding data, to be ignored)'}, 'cfp-input-levs-config': {}, 'cfp-input-track-only-config': {'colorbar': False, 'legend': True, 'linewidth': 0, 'markersize': 0.5, 'title': 'Input: flight track from observational field to co-locate model field onto'}, 'cfp-mapset-config': {}, 'cfp-output-general-config': {'legend': True, 'linewidth': 0.4, 'markersize': 5, 'title': 'Result: model co-located onto observational path'}, 'cfp-output-levs-config': {}, 'chosen-model-field': False, 'chosen-obs-field': False, 'halo-size': 1, 'history-message': 'Processed using the NCAS VISION Toolkit to colocate from model data to the observational data spatio-temporal location.', 'model-data-path': '.', 'obs-data-path': '.', 'orography': None, 'output-file-name': 'vision_toolkit_result_field.nc', 'outputs-dir': '.', 'plot-of-input-obs-track-only': True, 'plotname-start': 'vision_toolkit', 'preprocess-mode-model': None, 'preprocess-mode-obs': None, 'show-plot-of-input-obs': True, 'skip-all-plotting': False, 'source-axes': False, 'spatial-colocation-method': 'linear', 'start-time-override': False, 'verbose': 0, 'vertical-colocation-coord': 'air_pressure'}

dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s

(key, value) pairs

dict(iterable) -> new dictionary initialized as if via:

d = {} for k, v in iterable:

d[k] = v

dict(**kwargs) -> new dictionary initialized with the name=value pairs

in the keyword argument list. For example: dict(one=1, two=2)