hots.node

Provide actions specific to nodes (plot nodes data, build dictionnary for node IDs, compute different statistic measures …)

hots.node.build_dict_id_nodes(df_host)[source]

Build dictionnary for corresponding IDs and indexes.

Parameters:

df_host (pd.DataFrame) – _description_

Returns:

_description_

Return type:

Dict

hots.node.check_capacities(df_host, df_host_meta)[source]

Check if node capacities are satisfied at a given time.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • df_host_meta (pd.DataFrame) – _description_

Returns:

_description_

Return type:

List

hots.node.get_list_mean(df_host, total_time)[source]

Return list of mean for each metric in each node.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

Returns:

_description_

Return type:

Tuple[Dict, Dict]

hots.node.get_list_var(df_host, total_time)[source]

Return list of variance for each metric in each node.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

Returns:

_description_

Return type:

Tuple[Dict, Dict]

hots.node.get_list_vmr(df_host, total_time)[source]

Compute VMR (Variance-to-mean ratio) for each metric in each node.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

Returns:

_description_

Return type:

Tuple[Dict, Dict]

hots.node.get_mean_consumption(df_host)[source]

Compute mean consumption for each metric in each node and globally.

Parameters:

df_host (pd.DataFrame) – _description_

hots.node.get_mean_consumption_node(df_host, node_id)[source]

Get mean consumption of node_id.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • node_id (str) – _description_

Returns:

_description_

Return type:

float

hots.node.get_nodes_load_info(df_host, df_host_meta)[source]

Get all wanted node information in a dataframe.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • df_host_meta (pd.DataFrame) – _description_

Returns:

_description_

Return type:

pd.DataFrame

hots.node.get_nodes_variance(df_host, total_time, part)[source]

Compute the Variance for each metric in each node and return the results in two numpy arrays.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

  • part (int) – _description_

Returns:

_description_

Return type:

Tuple[np.array, np.array]

hots.node.get_variance_consumption(df_host)[source]

Compute the variance and standard deviation consumption for each metric in each node and globally.

Parameters:

df_host (pd.DataFrame) – _description_

hots.node.plot_all_data_all_nodes(df_host)[source]

Plot all metrics node consumption.

Parameters:

df_host (pd.DataFrame) – _description_

hots.node.plot_all_data_all_nodes_end(df_host, total_time)[source]

Plot all metrics consumption for all nodes.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

hots.node.plot_data_all_nodes(df_host, metric, max_cap, sep_time)[source]

Plot specific metric consumption for all nodes.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • metric (str) – _description_

  • max_cap (float) – _description_

  • sep_time (int) – _description_

Returns:

_description_

Return type:

plt.Figure

hots.node.plot_total_usage(df_host, title='Total conso on all nodes')[source]

Plot the global resources consumption and return the global maximum usage for each metric.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • title (str, optional) – _description_, defaults to ‘Total conso on all nodes’

Returns:

_description_

Return type:

Tuple[float, float]

hots.node.print_vmr(df_host, total_time, part)[source]

Compute VMR (Variance-to-mean ratio) for each metric in each node.

Parameters:
  • df_host (pd.DataFrame) – _description_

  • total_time (int) – _description_

  • part (int) – _description_