hots.container

Provide actions specific to containers (plot containers data, build dictionnary for container IDs …)

hots.container.build_dict_id_containers(df_indiv)

Build dictionnary for corresponding IDs and indexes.

Parameters:

df_indiv (pd.DataFrame) – _description_

Returns:

_description_

Return type:

Dict

hots.container.build_var_delta_matrix(df_indiv, dict_id_c)

Build variance of deltas matrix.

Parameters:

• df_indiv (pd.DataFrame) – _description_

• dict_id_c (_type_) – _description_

Returns:

_description_

Return type:

np.array

hots.container.build_var_delta_matrix_cluster(df_clust, cluster_var_matrix, dict_id_c)

Build variance of deltas matrix from cluster.

Parameters:

• df_clust (pd.DataFrame) – _description_

• cluster_var_matrix (np.array) – _description_

• dict_id_c (Dict) – _description_

Returns:

_description_

Return type:

np.array

hots.container.build_vars_matrix_indivs(df_clust, vars_, dict_id_c)

Build containers matrix with clusters variance.

Parameters:

• df_clust (pd.DataFrame) – _description_

• vars (np.array) – _description_

• dict_id_c (Dict) – _description_

Returns:

_description_

Return type:

np.array

hots.container.plot_all_data_all_containers(df_indiv, sep_time, metrics=None)

Plot all metrics containers consumption.

Parameters:

• df_indiv (pd.DataFrame) – _description_

• sep_time (int) – _description_

• metrics (List[str], optional) – _description_, defaults to None

Returns:

_description_

Return type:

plt.Figure

hots.container.plot_data_all_containers(df_indiv, metric)

Plot a specific metric containers consumption.

Parameters:

• df_indiv (pd.DataFrame) – _description_

• metric (str) – _description_

hots.container.show_specific_containers(working_df_indiv, df_indiv_clust, my_instance, labels_)

Show specific (user input) containers.

Parameters:

• working_df_indiv (pd.DataFrame) – _description_

• df_indiv_clust (pd.DataFrame) – _description_

• my_instance (Instance) – _description_

• labels (List) – _description_