7. Visualisation Module#

This module contains the plot functions of BuckPy result files.

buckpy.buckpy_visualisation.assembly_dataframe_bend_sleeper_ilt(df)[source]#

Read the route bend data from the BuckPy input file and select the KP of the ‘Bend’, ‘Sleeper’, ‘RCM’ and ‘ILT’ from the ‘Route Type’ column.

Parameters:

df (pandas DataFrame) – DataFrame containing the data in the ‘Route’ tab.

Returns:

  • df1 (pandas DataFrame) – DataFrame containing the ‘Bend’ route type data.

  • df2 (pandas DataFrame) – DataFrame containing the ‘Sleeper’ route type data.

  • df3 (pandas DataFrame) – DataFrame containing the ‘RCM’ route type data.

  • df4 (pandas DataFrame) – DataFrame containing the ‘ILT’ route type data.

buckpy.buckpy_visualisation.assembly_dataframe_plot(df_sets, df_pps)[source]#

Assemble the dataframes on the probabilistic results and post-processing input data from BuckPy.

Parameters:

  • df_sets (pandas DataFrame) – DataFrame containing the output data in the ‘Sets’ tab.

  • df_pps (pandas DataFrame) – DataFrame containing the input data in the ‘Post-Processing’ tab.

Returns:

df – DataFrame containing the doubled rows of KP and results.

Return type:

pandas DataFrame

buckpy.buckpy_visualisation.assembly_double_rows(df)[source]#

Double each row of the dataframe based on KP.

Parameters:

df (pandas DataFrame) – DataFrame containing the KP and results.

Returns:

df – DataFrame containing the doubled rows of KP and results.

Return type:

pandas DataFrame

buckpy.buckpy_visualisation.plot_bend_sleeper_ilt(a1, df1, df2, df3, df4, y_max)[source]#

Plot route bend, sleeper and ILT.

Parameters:

  • a1 (Matplotlib plot) – Axis of the Matplotlib plot.

  • df1 (pandas DataFrame) – Dataframe containing the locations of the route bends.

  • df2 (pandas DataFrame) – Dataframe containing the locations of sleepers.

  • df3 (pandas DataFrame) – Dataframe containing the locations of RCMs.

  • df4 (pandas DataFrame) – Dataframe containing the locations of ILTs.

buckpy.buckpy_visualisation.plot_buckpy(work_dir, input_file_name, pipeline_id, scenario_no, bl_verbose=False)[source]#

Plot the probabilistic buckling results from BuckPy result files.

Parameters:

  • work_dir (str) – The working directory where the analysis files are located.

  • input_file_name (str) – The name of the input file.

  • pipeline_id (str) – Identifier of the pipeline.

  • scenario_no (int) – The scenario number.

buckpy.buckpy_visualisation.plot_results(file_name, df_no_buckles, df_force_profiles, df_bends, df_sleepers, df_rcms, df_ilts, df_set_pps)[source]#

Plot probabilistic results of BuckPy in 6 subplots: Row 1: unbuckled EAF, Number of Buckles, VAS; Row 2: buckled EAF, Probobality of Buckling, Friction.

Parameters:

  • file_name (str) – The name of the output image file.

  • df_no_buckles (pandas DataFrame) – DataFrame containing the data related to the number of buckles.

  • df_force_profiles (pandas DataFrame) – DataFrame containing the force profile data.

  • df_bends (pandas DataFrame) – DataFrame containing the ‘Bend’ route type data.

  • df_sleepers (pandas DataFrame) – DataFrame containing the ‘Sleeper’ route type data.

  • df_rcms (pandas DataFrame) – DataFrame containing the ‘RCM’ route type data.

  • df_ilts (pandas DataFrame) – DataFrame containing the ‘ILT’ route type data.

  • df_set_pps (pandas DataFrame) – DataFrame containing the doubled rows of KP and results from ‘Sets’ and ‘Post-Processing’ tabs.

buckpy.buckpy_visualisation.read_input(work_dir, input_file_name, pipeline_id, scenario_no)[source]#

Read the route bend and post-processing data from the BuckPy input file and select the data for the current scenario.

Parameters:

  • work_dir (str) – The working directory where the analysis files are located.

  • input_file_name (str) – The name of the input file.

  • pipeline_id (str) – Identifier of the pipeline.

  • scenario_no (int) – The scenario number.

Returns:

  • df_routes (pandas DataFrame) – DataFrame containing the data in the ‘Route’ tab.

  • df_pps (pandas DataFrame) – DataFrame containing the data in the ‘Post-Processing’ tab.

buckpy.buckpy_visualisation.read_output(output_file_name)[source]#

Read the data from the BuckPy result file.

Parameters:

output_file_name (string) – File path of the BuckPy result file.

Returns:

  • df_sets (pandas DataFrame) – DataFrame containing the data in the ‘Sets’ tab.

  • df_buckle (pandas DataFrame) – DataFrame containing the data related to the number of buckles.

  • df_force_prof (pandas DataFrame) – DataFrame containing the force profile data.