AstroGeoFit Python Library¶

Execution of the Library¶

The AstroGeoFit library provides a wide range of functions designed to help users both obtain and visualize the results produced by the tool. To improve readability and usability, these functions are organized by functionality through the use of specific prefixes that indicate their purpose.

AstroGeoFit_tool class¶

This class represents the main core of the tool, which will recieve all the necessary parameters to obtain the results of the different sections (fitting, MCMC, Weight Computation and Significance Test). This class contains the function run() which will execute the tool itself. Find the detailed guide in: AstroGeoFit_tool class.

plt_fit_ functions¶

The functions with this prefix generate plots from the results obtained after fitting our genetic algorithm and predicting our new data with it. Find the detailed guide in: plt_fit_ detailed function guide.

The functions that we find on this category are:

plt_fit_summary_of_the_results

plt_fit_metric_per_number_of_knots

plt_fit_aics_bics_per_number_knots

plt_fit_aics_r2_per_number_knots

plt_fit_sedimentation_rate_per_depth

plt_fit_sedimentation_rate_depth_with_uncertainty

plt_fit_spectrum_plot

plt_fit_time_series

plt_fit_ETP_signals_from_model

plt_fit_eccentricity_mswd_plot

plt_fit_correlation_eccentricity_and_solution

Note: Some of these functions require another function from the data_ category to be executed.

plt_significance_ function¶

The function with this prefix generates a plot using the results of the significance test. Find the detailed guide in: plt_significance_ detailed function guide.

The function that we find on this category is:

plt_significance_test_results

plt_mcmc_ functions¶

The functions that have this prefix use the results of the mcmc and the weight calcula (if executed) to obtain different types of plots. Find the detailed guide in: plt_mcmc_ detailed function guide.

The functions that we find on this category are:

plt_mcmc_SR_per_num_knots

plt_mcmc_aic_and_r2_per_number_knots

plt_mcmc_eccentricity_correlation_with_solution

plt_mcmc_summary_of_results

plt_mcmc_prior_frequencies_distributions

plt_mcmc_phase_of_frequencies

Note: Some of these functions require another function from the data_ category to be executed.

data_ functions¶

Functions with this prefix are related to obtaining data required for specific plots. Plots that depend on a preceding function will be marked with the Pre-Requisite. Find the detailed guide in: data_ detailed function guide.

The functions that we find on this category are:

data_calculate_eccentricity_parameters

data_obtain_mcmc_results_per_a_number_of_knots

data_obtain_analysis_file_and_result_files

data_obtain_age_depth_values

Configuration Handling¶

The library functions can be run independently or configured through the .yml configuration file parser provided.

We recommend using the configuration loader to prepare the configuration file before calling plotting or execution functions.

Example Usage¶

This example shows how to obtain the results of the fitting part, and plot the summary of those results. The path of the fitting results file is taken from the configuration file by not introducing the parameters output_folder and output_file on the data_obtain_analysis_file_and_result_files function.

from astrogeofit import plt_fit_summary_of_the_results

configuration_file_path = "path/to/your/configuration_file.yaml"
number_of_knots_to_explore = 54
types_of_saving = ["pdf"]
output_path = "output/results/path"
x_axis_limits = None
invSR_plot_y_limits = [y_min,y_max]
age_plot_y_limits = [y_min,y_max]
fitted_data_plot_y_limits = [y_min,y_max]
correlation_plot_y_limits = [y_min,y_max]
# Load optimization results, prediction function, and data...
plt_fit_summary_of_the_results(
    configuration_file_path = configuration_file_path,
    number_of_knots_to_explore = number_of_knots_to_explore,
    types_of_saving = types_of_saving,
    output_path = output_path,
    x_axis_limits = x_axis_limits,
    invSR_plot_y_limits = invSR_plot_y_limits
    age_plot_y_limits = age_plot_y_limits
    fitted_data_plot_y_limits = fitted_data_plot_y_limits
    correlation_plot_y_limits = correlation_plot_y_limits
)

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