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 resamples 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 complex_optimizable_pwc_signal:

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

Following is a list of functions in the utils toolkit:

complex_optimizable_pwc_signal

Create a complex optimizable piecewise-constant signal.

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.

real_optimizable_pwc_signal

Create a real optimizable piecewise-constant signal.