Module enthought.​numerical_modeling.​numeric_context

Contents:
• Subpackages
• Submodules

Subpackages

• tests

Submodules

• a_numeric_context - Defines the abstract base class for all numeric context subclasses.
• a_numeric_filter - Abstract base class for all numeric context filters.
• a_numeric_item - Defines an abstract base class for accessing an item in a numeric context.
• aggregate_filter - Defines a filter which aggregates the results of several contained filters into a single composite filter
• api
• cached_context - Defines a termination numeric context which passes all of the data it receives from its upstream numeric context through unchanged, and also caches the values to avoid having to constantly recalculate upstream values.
• constants - Constants defined and used by the numeric context package.
• context_delegate - Delegate base class that can be used to customize various policies of a numeric context via subclassing.
• context_factory
• context_item - Defines an array value contained in the context.
• context_modified - An event object which describes what changes have occurred to a numeric context.
• deferred_context - Defines a concrete derived numeric context that defers propagation of all upstream context events to a future point in time
• derivative_context - Defines the abstract base class for all numeric contexts which connect to another numeric context.
• error - Defines various numeric context related exception classes.
• evaluated_item - Defines an array value whose value is determined by an expression evaluated on a context.
• event
• event_dict
• expression_filter - Defines a filter based on the result of evaluating a specified Python expression in a numeric context.
• extension_context - Defines the abstract base class for all numeric contexts which connect to another numeric context and behave as if they are the context base for the pipeline.
• filter_context - Defines an abstract base class for a derived numberic context which filter their data in some way.
• helper - Helper functions for constructing various types of common numeric context pipelines.
• index_filter - Creates a filter for all elements specified by a list of array indices (or its inverse: the elements not specified by a list of array indices).
• mapping_context - Defines a concrete class for a derived, filtered numeric context which reorders the data it receives from its upstream context via a numeric index array.
• mask_filter - Defines a filter specified by an explicit mask.
• nan_filter - Creates a filter for any element in all arrays of a context which are NaNs (or its inverse: the elements which do not contain a NaN for any of a context's arrays).
• numeric_context - Defines the root of a numeric context 'pipeline'.
• numeric_reference - A named reference to a single numeric context array value.
• reduction_context - Defines a concrete class for a derived, filtered numeric context which reduces the data it receives from its upstream context via a numeric boolean mask.
• selection_context - Defines a concrete class for a derived, filtered numeric context which passes the data it receives from its upstream context through unmodified, but provides a 'selection mask', which is a numeric boolean array that indicates which data items are in the selection.
• selection_reduction_context - Defines a termination numeric context which filters (i.e
• sort_filter - Creates a special sort filter which defines a sorting order for the elements of a context's arrays based on a specified Python expression
• sub_context_item - Defines an array value contained within a sub-context.
• termination_context - Defines an abstract base class for numeric contexts which can act as 'termination' points of numeric context pipelines
• trait_item - Defines an array value contained in an external object trait.
• traits_context - Defines a concrete termination class intended for use with Traits UI based user interfaces or other Traits-based clients connected to the numeric context