Violin Plot Generation

class SAES.plots.violin.Violin(data: DataFrame, metrics: DataFrame, metric: str)

Bases: object

Class to generate violin plots for the performance results of different algorithms across multiple instances.

Attributes:

data (pd.DataFrame):

A pandas DataFrame containing the performance results of different algorithms across multiple instances.

metric (str):

The metric to be used for comparison.

algorithms (np.ndarray):

An array containing the names of the algorithms.

instances (np.ndarray):

An array containing the names of the instances.

logger (Logger):

A logger object to record and display log messages.

Methods:

__init__(data: pd.DataFrame, metrics: pd.DataFrame, metric: str):

Initializes the violin object with the given data, metrics, and metric.

save_instance(instance: str, output_path: str):

Generates a violin for the specified instance and saves it to the specified output path.

save_all_instances(output_path: str):

Generates a violin for all instances and saves it to the specified output path.

show_instance(instance: str):

Generates a violin for the specified instance and displays it.

show_all_instances():

Generates a violin for all instances and displays it.

save_all_instances(output_path: str, file_name: str = None, width: int = 30) → None

Generates a violin for all instances and saves it to the specified output path.

Args:

output_path (str):

The path where the violin image will be saved.

file_name (str):

The name of the file to be saved. If None, a default name will be used.

width (int):

The width of the violin image.

Returns:

None

Example:

>>> frtom SAES.plots.violin import Violin
>>> import os
>>> 
>>> data = pd.read_csv("data.csv")
>>> metrics = pd.read_csv("metrics.csv")
>>> metric = "HV"
>>> violin = Violin(data, metrics, metric)
>>> violin.save_all_instances(os.getcwd())

save_instance(instance: str, output_path: str, file_name: str = None, width: int = 8) → None

Generates a violin for the specified instance and saves it to the specified output path.

Args:

instance (str):

The name of the instance for which the violin is to be generated.

output_path (str):

The path where the violin image will be saved.

file_name (str):

The name of the file to be saved. If None, a default name will be used.

width (int):

The width of the violin image.

returns:

None

Example:

>>> frtom SAES.plots.violin import Violin
>>> import os
>>> 
>>> data = pd.read_csv("data.csv")
>>> metrics = pd.read_csv("metrics.csv")
>>> metric = "HV"
>>> violin = Violin(data, metrics, metric)
>>> violin.save_instance("ZDT1", os.getcwd())

show_all_instances(width: int = 30) → None

Generates a violin for all instances and displays it.

Args:

width (int):

The width of the violin image.

Returns:

None

Example:

>>> frtom SAES.plots.violin import Violin
>>> import os
>>> 
>>> data = pd.read_csv("data.csv")
>>> metrics = pd.read_csv("metrics.csv")
>>> metric = "HV"
>>> violin = Violin(data, metrics, metric)
>>> violin.show_all_instances()

show_instance(instance: str, width: int = 8) → None

Generates a violin for the specified instance and displays it.

Args:

instance (str):

The name of the instance for which the violin is to be generated.

width (int):

The width of the violin image.

returns:

None

Example:

>>> frtom SAES.plots.violin import Violin
>>> import os
>>> 
>>> data = pd.read_csv("data.csv")
>>> metrics = pd.read_csv("metrics.csv")
>>> metric = "HV"
>>> violin = Violin(data, metrics, metric)
>>> violin.show_instance("ZDT1")