Functionalities

The Jarkus Analysis Toolbox provides many functionalities. Here, all available modules are explained per category.

Geometric functions

Provides basic geometric functions that execute calculations based on the coastal profile.

JAT.Geometric_functions.find_intersections(elevation, crossshore, y_value)

Find cross-shore location of intersection between profile and horizontal line at a fixed elevation.

Parameters:

elevation (np.array) – np.array containing the elevation of the coastal profile in meters.
crossshore (np.array) – np.array containing the crossshore location in meters.
y_value (float) – Elevation of the horizontal line in meters.

Returns:

intersection_x: Cross-shore location of the intersection between the coastal profile and horizontal line.

Return type:

int

JAT.Geometric_functions.get_gradient(elevation, seaward_x, landward_x)

Find gradient of a profile between two points

The gradient of a coastal profile is determined by finding the slope of the line of best fit along the elevation between a landward and seaward boundary.

Parameters:

elevation (np.array) – np.array containing the elevation of the coastal profile in meters
seaward_x (float or int) – Cross-shore seaward boundary
landward_x (float or int) – Cross-shore landward boundary

Returns:

gradient: slope of the best fit line

Return type:

float

JAT.Geometric_functions.get_volume(elevation, seaward_x, landward_x)

Determine volume under coastal profile between two two points

The volume of the coastal profile between a landward and seaward boundary is determined by integrating over the surface beneath the coastal profile between those two points.

Parameters:

elevation (np.array) – np.array containing the elevation of the coastal profile in meters
seaward_x (float or int) – Cross-shore seaward boundary
landward_x (float or int) – Cross-shore landward boundary

Returns:

volume: surface under the graph in m^2. Can be interpreted as m^3 by assuming the profile is 1 m wide.

Return type:

float

Jarkus Analysis Toolbox

Loading and plotting transects.

This class provides the functionalities to retrieve the jarkus dataset and filter out the years and locations requested by the user. This includes determining whether the user defined request is available. Additionally, the elevation of each requested transect can be saved and plotted to provide easy access for analysis, and the conversion of the transect number to the alongshore kilometer is provided.

Extracting characteristic parameters from coastal profiles.

This class provides the functionalities to extract the characteristic parameters requested by the user from transects of the jarkus dataset. Additionally, it provides functions to post-process the outcome of the extraction.

Filtering functions

Provides functions that allow filtering of the extracted characteristic parameters.

JAT.Filtering_functions.availability_locations_filter(config, dimension)

Filter out transects based on data availability.

Filter out transects that have a data availability that is lower than the user-defined threshold.

Parameters:

config (dict) – configuration file that includes the user defined availability threshold in percentage (filter2, locations)
dimension (pd.dataframe) – dataframe containing the values of a characteristic parameter through time and more multiple transect locations.

Returns:

dimension_filt: dataframe containing the values of a characteristic parameter where filtered transects have been removed.

Return type:

pd.dataframe

JAT.Filtering_functions.availability_years_filter(config, dimension)

Filter out years based on data availability.

Filter out years that have a data availability that is lower than the user-defined threshold.

Parameters:

config (dict) – configuration file that includes the user defined availability threshold in percentage (filter2, years)
dimension (pd.dataframe) – dataframe containing the values of a characteristic parameter through time and for multiple transect locations.

Returns:

dimension_filt: dataframe containing the values of a characteristic parameter where filtered years have been removed.

Return type:

pd.dataframe

JAT.Filtering_functions.locations_filter(dimension, filter_file)

Filter out user-defined transects.

Filter out locations that are specified by the user from a dataframe of a characteristic parameter. Default settings filter out locations like the Hondsbossche Dunes and Maasvlakte, redundant transects at the outer edges of the Wadden Islands, and dams in Zeeland.

Parameters:

dimension (pd.dataframe) – dataframe containing the values of a characteristic parameter through time and more multiple transect locations.
filter_file (dict) – Includes a numbered list of sections that should be excluded. The first transect number represents the start of the section, the second transect number the end.

Returns:

dimension_filt: dataframe containing the values of a characteristic parameter where filtered transects have been removed.

Return type:

pd.dataframe

JAT.Filtering_functions.nourishment_filter(config, dimension)

Split characteristic parameter values into nourished and not nourished transects.

Parameters:

config (dict) – configuration file that includes the directory where the nourishment database is stored.
dimension (pd.dataframe) – dataframe containing the values of a characteristic parameter through time and more multiple transect locations.

Returns:

pd.dataframe – nourished_dataframe: dataframe containing the values of a characteristic parameter of only transect that have been nourished.
pd.dataframe – not_nourished_dataframe: dataframe containing the values of a characteristic parameter of only transect that have not been nourished.

JAT.Filtering_functions.yrs_filter(dimension, begin_year, end_year)

Filter out user-defined years.

Filter values of a characteristic parameter that are associated with a range of years that is specified by the user.

Parameters:

dimension (pd.dataframe) – dataframe containing the values of a characteristic parameter through time and more multiple transect locations.
begin_yr (int) – Start year of the range that should be filtered
end_yr (int) – End year of the range that should be filtered

Returns:

dimension_filt: dataframe containing the values of a characteristic parameter where filtered years have been removed.

Return type:

pd.dataframe