Lotta's master's thesis 2020:

Files to run the inverse model of my Master's thesis of modelling cosmogenic nuclides to detect past glaciations.

all_functions_original.py

Contains all the functions used.

• forward calculates the nuclide concentrations with depth
• find_times chooses randomly times that are tested as a possible solution
• inverse tests if the tested model fits to the reference forward model

example.py

Contains an example how to run the code.

"test1.txt" and "test2.txt" have an example output from the example.py

Liisa's master's thesis 2026:

Files to run the improved cosmogenic inverse model introduced in my master's thesis.

all_functions.py

Contains all the functions needed for running the inverse model.

• 'forward' calculates the concentration profiles
• 'synthetic_data' creates a synthetic data set given input values for the model parameters defining the exposure history
• 'MCinverse' executes one iteration of uniform Monte Carlo (random sampling) inversion, calls 'find_times' and 'rand_erosion' to find random parameter values
• 'NAinverse' executes the inversion with Neighbourhood Algorithm sampling
• 'MCMCinverse' executes the inversion with Markov Chain Monte Carlo sampling
• 'inverse' calculates the misfit of a sampled set of model parameters, called by 'NAinverse' and 'MCMCinverse'

Synthetic_data_creation.py

An example of how to create synthetic data

Inversion_test.py

An example of how to run the inverse model

Additional examples of plotting a summary of the results

• Misfit_plot.py : an example of how to create a box plot showing the minimum (=best model) misfit values for different inversions
• Best_params_plot.py : an example of how to create box plots showing the best model parameter values (one subfigure for each inverted parameter) for different inversions