# 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.