Measurements handling

Measurement datasets are a central part in model validation and therefore we designed the Dataset class that offer a number of useful methods to deal with them.

A typical workflow consists in casting your measurement data into dymoval Signal objects and then use the created Signals to instantiate a Dataset object.

Signals

Dymoval Signal are used to represent real-world signals.

Dymoval Signals are Typeddict with the following keys

Keys

Functions

Dymoval offers few function for dealing with Signals:

Dataset class

The Dataset class is used to store and manipulate measurement datasets.

Since to validate a model you need some measurement datasets, objects of this class are used also to instantiate ValidationSession objects, and the passed Dataset object becomes an attribute of the newly created ValidationSession object.

A Dataset object can be instantiated in two ways:

1. Through a list of dymoval Signals (see validate_signals() )

2. Through a pandas DataFrame with a specific structure (see validate_dataframe())

Constructor

Attributes

Manipulation methods

Plotting methods

Other methods