neurots.preprocess.validity_checkers¶
Functions to check that the given parameters and distributions will not break the algorithm.
The functions for validity checkers should have the signature: check_something(params, distrs).
These functions should be very generic and should not depend on any context in which the related
grower is used.
The checkers should be registered to be executed in the preprocess step using the
@register_validator decorator if they are applied per grow_type and growth_method, or with
@register_global_validator if they need the entire data.
Functions
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Check consistency between parameters and persistence diagram. |
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Check that the 'radius' parameter is not present or raise a warning. |
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Check consistency between diameter parameters and distributions values. |
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Check consistency between metric parameters and distributions values. |
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Check that params contains a 'num_seg' entry. |
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Validate distributions. |
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Validate parameters. |
- neurots.preprocess.validity_checkers.check_bar_length(params, distrs)¶
Check consistency between parameters and persistence diagram.
- neurots.preprocess.validity_checkers.check_deprecated_radius(params, distrs)¶
Check that the ‘radius’ parameter is not present or raise a warning.
- neurots.preprocess.validity_checkers.check_diameter_consistency(params, distrs)¶
Check consistency between diameter parameters and distributions values.
- neurots.preprocess.validity_checkers.check_metric_consistency(params, distrs)¶
Check consistency between metric parameters and distributions values.
- neurots.preprocess.validity_checkers.check_num_seg(params, distrs)¶
Check that params contains a ‘num_seg’ entry.
- neurots.preprocess.validity_checkers.validate_distributions(_, distrs)¶
Validate distributions.
- neurots.preprocess.validity_checkers.validate_parameters(params, _)¶
Validate parameters.