hots.init

Provide stuff for initialization step (load DataFrames, global variables)

hots.init.build_df_from_containers(df_indiv)[source]

Build the df_host from containers df.

Parameters:

df_indiv (pd.DataFrame) – _description_

Returns:

_description_

Return type:

pd.DataFrame

hots.init.define_globals(p_path, config)[source]

Define the fields, as global variables, from config.

Parameters:
  • p_path (Path) – _description_

  • config (Dict) – _description_

hots.init.df_from_csv(file)[source]

Load DataFrame from CSV file.

Parameters:

file (Path) – _description_

Returns:

_description_

Return type:

pd.DataFrame

hots.init.init_dfs(data)[source]

Perform CSV files reading in data folder.

Parameters:

data (str) – _description_

Returns:

_description_

Return type:

Tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]

hots.init.read_params(path, k, tau, method, cluster_method, param, output_path)[source]

Get parameters from file and build the Dict config object.

Parameters:
  • path (str) – _description_

  • k (int) – _description_

  • tau (int) – _description_

  • method (str) – _description_

  • cluster_method (str) – _description_

  • param (str) – _description_

  • output_path (str) – _description_

Raises:
  • ValueError – _description_

  • ValueError – _description_

Returns:

_description_

Return type:

Dict

hots.init.set_loop_results()[source]

Create the dataframe for loop results.

Returns:

_description_

Return type:

pd.DataFrame

hots.init.set_times_df()[source]

Create the dataframe for times info.

Returns:

_description_

Return type:

pd.DataFrame