Release notes for sbmlutils 0.16.0

We are pleased to release the next version of sbmlutils including the following changes. Measured data drives a model: an interpolation of the data replaces quantities of an existing model in place, through a comp model which leaves the original untouched, or in a model definition (#16, #500).

New features

• Interpolation.drive drives a parameter, species or compartment of an existing model with the interpolated data, in place; x is the time or a quantity of the model, targets maps a column to the element it drives (#16, #500)
• Interpolation.drive_comp drives a model through a comp model which references the original, or embeds it with embed=True; flattened it simulates as the model driven in place (#16, #500)
• Interpolation.assignment_rules gives the interpolation as assignment rules of a model definition (#16, #500)

Breaking changes

• linear and cubic spline interpolation hold the first value before and the last value after the data, instead of 0.0 (#16, #500)
• data which cannot be interpolated raises a ValueError instead of a warning: fewer than 2 columns or data points (3 for the cubic spline), column names which are not strings or repeat, a first column which is not an SBML id, a column which is not numeric, a missing or infinite value, x which repeats (#16, #500)
• Interpolation.add_interpolator_to_model is removed, drive replaces it; Interpolation.create_interpolators is the property Interpolation.interpolators; the attributes doc and model of an Interpolation are removed (#16, #500)
• the standalone model of an interpolation is SBML L3V2 with a port on every interpolated parameter and on x, its notes name the data and the method (#16, #500)

Documentation

• the guide Interpolation covers driving a model in place, through comp and in a model definition, and its code is run by the tests; the example examples.interpolation.driving drives a model of glucose uptake with measured plasma glucose, examples.interpolation.pancreas drives a dose response (#16, #500)