API Reference
Toolkit for system-agnostic functionality.
The Boulder Opal Toolkits are currently in beta phase of development. Breaking changes may be introduced.
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:
Graph
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.
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() 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.