CadetCareerProblem – Data Visualizations Methods

display_data_graph(p_dict={}, printing=None)

This method plots different aspects of the fixed parameters of the problem instance.

Source code in afccp/main.py

def display_data_graph(self, p_dict={}, printing=None):
    """
    This method plots different aspects of the fixed parameters of the problem instance.
    """

    # Print statement
    if printing is None:
        printing = self.printing

    # Adjust instance plot parameters
    self._reset_functional_parameters(p_dict)
    self.mdl_p = afccp.data.support.determine_afsc_plot_details(self)

    # Initialize the AFSC Chart object
    afsc_chart = afccp.visualizations.charts.AFSCsChart(self)

    # Construct the specific chart
    return afsc_chart.build(printing=printing)

display_all_data_graphs(p_dict={}, printing=None)

This method runs through all the different versions of graphs we have and saves them to the corresponding folder.

Source code in afccp/main.py

def display_all_data_graphs(self, p_dict={}, printing=None):
    """
    This method runs through all the different versions of graphs we have and saves
    them to the corresponding folder.
    """
    if printing is None:
        printing = self.printing

    if printing:
        print("Saving all data graphs to the corresponding folder...")

    # Regular Charts
    charts = []
    for graph in ["Average Utility", "USAFA Proportion", "Average Merit", "AFOCD Data", "Eligible Quota"]:
        p_dict["data_graph"] = graph
        charts.append(self.display_data_graph(p_dict, printing=printing))

    # Cadet Preference Analysis Charts
    p_dict["data_graph"] = "Cadet Preference Analysis"
    for version in range(1, 8):
        p_dict["version"] = str(version)
        charts.append(self.display_data_graph(p_dict, printing=printing))

    return charts

show_value_function(p_dict={}, printing=None)

This method plots a specific AFSC objective value function

Source code in afccp/main.py

def show_value_function(self, p_dict={}, printing=None):
    """
    This method plots a specific AFSC objective value function
    """

    if printing is None:
        printing = self.printing

    # Shorthand
    p, vp = self.parameters, self.value_parameters

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)
    self.mdl_p = afccp.data.support.determine_afsc_plot_details(self)
    ip = self.mdl_p  # More shorthand

    if printing:
        print('Creating value function chart for objective ' + ip['objective'] + ' for AFSC ' + ip['afsc'])

    # Determine AFSC and objective shown in this chart
    j, k = np.where(p["afscs"] == ip["afsc"])[0][0], np.where(vp["objectives"] == ip["objective"])[0][0]

    # ValueFunctionChart specific parameters
    vfc = ip['ValueFunctionChart']
    vfc['x_label'] = afccp.globals.obj_label_dict[ip['objective']]  # Get x label for this objective

    # Value Function specific coordinates to plot
    if vfc['x_pt'] is not None:
        vfc['y_pt'] = afccp.solutions.handling.value_function(vp['a'][j][k], vp['f^hat'][j][k], vp['r'][j][k],
                                                              vfc["x_pt"])

    # Determine x and y arrays
    if ip['smooth_value_function']:
        x_arr = (np.arange(1001) / 1000) * vp['a'][j][k][vp['r'][j][k] - 1]
        y_arr = np.array([afccp.solutions.handling.value_function(
            vp['a'][j][k], vp['f^hat'][j][k], vp['r'][j][k], x) for x in x_arr])
    else:
        x_arr, y_arr = vp['a'][j][k], vp['f^hat'][j][k]

    # Title and filepath for this value function!
    vfc['title'] = ip['afsc'] + ' ' + ip['objective'] + ' Value Function'
    vfc['filepath'] = self.export_paths['Analysis & Results'] + \
                      'Value Functions/' + self.data_name + ' ' + vfc['title'] + ' (' + self.vp_name + ').png'

    # Create and return the chart
    return afccp.visualizations.charts.ValueFunctionChart(x_arr, y_arr, vfc)

display_weight_function(p_dict={}, printing=None)

This method plots the weight function used for either cadets or AFSCs

Source code in afccp/main.py

def display_weight_function(self, p_dict={}, printing=None):
    """
    This method plots the weight function used for either cadets or AFSCs
    """

    if printing is None:
        printing = self.printing

    # Reset instance model parameters
    self._reset_functional_parameters(p_dict)
    self.mdl_p = afccp.data.support.determine_afsc_plot_details(self)

    # Make the folder
    if 'Value Parameters' not in os.listdir(self.export_paths['Analysis & Results']):
        os.mkdir(self.export_paths['Analysis & Results'] + 'Value Parameters')

    if printing:
        if self.mdl_p["cadets_graph"]:
            print("Creating cadet weight chart...")
        else:
            print("Creating AFSC weight chart...")

    # Build the chart
    chart = afccp.visualizations.charts.individual_weight_graph(self)

    if printing:
        chart.show()

    return chart