Extrap multi-parameter support for modeling and visualization

[marcusritter1]

UPDATES:

• added a check for .cali file type to reader_dispatch() so no value error is raised when other file types, folders are in the provided dir
• refactored the code in produce_models() so it can deal with measurement repetitions
• added visualization for 2 parameter models
• added additional visualization options to plots, like min/max, error bars, optimal scaling curves, etc.
• added Extra-P data aggregation support for measurement repetitions, choose between mean/median for model creation
• added exception class for extra-p thicket dataframe conversion to let the user know if a measurement can not be used for modeling and why
• visualization type is now automatically chosen by the number of detected model parameters
• added type checking and hints to code
• updated test cases for new modeling capabilities
• added multi-parameter support for componentize function
• added new function complexity_statsframe() to analyze the asymptotic complexity of the models in the dataframe and rank them according to their growth trends