update of docstrings for optimizer_tool
@@ -18,7 +18,7 @@ framework_path = str(framework_path.parent)
def importClass(class_name, module_name, module_path):
"""
- Function to import a class runtime based on its module and name
+ Import a class runtime based on its module and name
:param class_name: name of the class
:type class_name: str
@@ -42,7 +42,7 @@ def importClass(class_name, module_name, module_path):
def load_model(optimization_object):
"""
- Function used to load the topic model for the resume_optimization
+ Load the topic model for the resume of the optimization
:param optimization_object: dictionary of optimization attributes saved in the jaon file
:type optimization_object: dict
@@ -66,7 +66,7 @@ def load_model(optimization_object):
def select_metric(metric_parameters, metric_name):
"""
- Function to select the metric for the resume of the optimization
+ Select the metric for the resume of the optimization
:param metric_parameters: metric parameters
:type metric_parameters: list
@@ -86,7 +86,7 @@ def select_metric(metric_parameters, metric_name):
def choose_optimizer(params):
"""
- Function to choose a surrogate model for Bayesian Optimization
+ Choose a surrogate model for Bayesian Optimization
:param params: list of setting of the BO experiment
:type params: object
@@ -185,7 +185,7 @@ def early_condition(values, n_stop, n_random):
def plot_model_runs(model_runs, current_call, name_plot):
"""
- Function to save a boxplot of the data (Works only when optimization_runs is 1).
+ Save a boxplot of the data (Works only when optimization_runs is 1).
:param model_runs: dictionary of all the model runs.
:type model_runs: dict
@@ -209,7 +209,7 @@ def plot_model_runs(model_runs, current_call, name_plot):
def plot_bayesian_optimization(values, name_plot,
log_scale=False, conv_max=True):
"""
- Function to save a convergence plot of the result of a Bayesian_optimization.
+ Save a convergence plot of the result of a Bayesian_optimization.
:param values: List of objective function values
:type values: list
@@ -270,7 +270,7 @@ def convert_type(obj):
def check_instance(obj):
"""
- Function to check if a specific object con be inserted in the json file.
+ Check if a specific object con be inserted in the json file.
:param obj: an object of the optimization to be saved
:type obj: [str,float, int, bool, etc.]
@@ -288,7 +288,7 @@ def check_instance(obj):
def save_search_space(search_space):
"""
- Function to save the search space in the json file
+ Save the search space in the json file
:param search_space: dictionary of the search space (scikit-optimize object)
:type search_space: dict
@@ -311,7 +311,7 @@ def save_search_space(search_space):
def load_search_space(search_space):
"""
- Function to load the search space from the json file
+ Load the search space from the json file
:param search_space: dictionary of the search space (insertable in a json file)
:type dict:
@@ -449,7 +449,7 @@ class BestEvaluation:
def save_to_csv(self, name_file):
"""
- Function to save the results of BO to a csv file
+ Save results for Bayesian Optimization to a csv file
:param name_file: name of the file
:type name_file: str
@@ -490,7 +490,7 @@ class BestEvaluation:
def load(self, name):
"""
- Load the results of optimization
+ Load the results for Bayesian Optimization
:param name: name of the json file
:type name: str
