General utilities

Toolkit for system-agnostic functionality.

The Boulder Opal Toolkits are currently in beta phase of development. Breaking changes may be introduced.

Graph nodes

Graph nodes to define common operations. You can access them from the utils namespace of a Graph object. For example, to use complex_optimizable_pwc_signal:

qctrl = Qctrl()
graph = qctrl.create_graph()
graph.utils.complex_optimizable_pwc_signal(...)

Following is a list of graph nodes in the utils toolkit:

`complex_optimizable_pwc_signal`	Create a complex optimizable piecewise-constant signal.
`filter_and_resample_pwc`	Filter a piecewise-constant function with a sinc filter and resample it again.
`real_optimizable_pwc_signal`	Create a real optimizable piecewise-constant signal.

Functions

Methods to perform common tasks. You can access them from the utils namespace of the Qctrl object. For example, to use confidence_ellipse_matrix:

qctrl = Qctrl()
qctrl.utils.confidence_ellipse_matrix(...)

Following is a list of functions in the utils toolkit:

`confidence_ellipse_matrix`	Calculate a matrix that you can use to represent the confidence region of parameters that you estimated.
`extract_filter_function_arrays`	Convert the output samples of a filter function calculation into NumPy arrays.
`pwc_arrays_to_pairs`	Create a list of dictionaries with "value" and "duration" keys representing a piecewise-constant function from arrays containing the durations and values.
`pwc_pairs_to_arrays`	Extract arrays with the durations and values representing a piecewise-constant function from a list of dictionaries with "value" and "duration" keys.