bayeso.utils.utils_plotting

It is utilities for plotting figures.

bayeso.utils.utils_plotting._save_figure(path_save: str, str_postfix: str, str_prefix: str = '') → None

It saves a figure.

Parameters:

  • path_save (str.) – path for saving a figure.

  • str_postfix (str.) – the name of postfix.

  • str_prefix (str., optional) – the name of prefix.

Returns:

None.

Return type:

NoneType

bayeso.utils.utils_plotting._set_ax_config(ax: matplotlib.axes._subplots.AxesSubplot, str_x_axis: str, str_y_axis: str, size_labels: int = 32, size_ticks: int = 22, xlim_min: float | None = None, xlim_max: float | None = None, draw_box: bool = True, draw_zero_axis: bool = False, draw_grid: bool = True) → None

It sets an axis configuration.

Parameters:

  • ax (matplotlib.axes._subplots.AxesSubplot) – inputs for acquisition function. Shape: (n, d).

  • str_x_axis (str.) – the name of x axis.

  • str_y_axis (str.) – the name of y axis.

  • size_labels (int., optional) – label size.

  • size_ticks (int., optional) – tick size.

  • xlim_min (NoneType or float, optional) – None, or minimum for x limit.

  • xlim_max (NoneType or float, optional) – None, or maximum for x limit.

  • draw_box (bool., optional) – flag for drawing a box.

  • draw_zero_axis (bool., optional) – flag for drawing a zero axis.

  • draw_grid (bool., optional) – flag for drawing grids.

Returns:

None.

Return type:

NoneType

bayeso.utils.utils_plotting._set_font_config(use_tex: bool) → None

It sets a font configuration.

Parameters:

use_tex (bool.) – flag for using latex.

Returns:

None.

Return type:

NoneType

bayeso.utils.utils_plotting._show_figure(pause_figure: bool, time_pause: int | float) → None

It shows a figure.

Parameters:

  • pause_figure (bool.) – flag for pausing before closing a figure.

  • time_pause (int. or float) – pausing time.

Returns:

None.

Return type:

NoneType

bayeso.utils.utils_plotting.plot_bo_step(X_train: ndarray, Y_train: ndarray, X_test: ndarray, Y_test: ndarray, mean_test: ndarray, std_test: ndarray, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'x', str_y_axis: str = 'y', num_init: int | None = None, use_tex: bool = False, draw_zero_axis: bool = False, pause_figure: bool = True, time_pause: int | float = 2.0, range_shade: float = 1.96) → None

It is for plotting Bayesian optimization results step by step.

Parameters:

  • X_train (numpy.ndarray) – training inputs. Shape: (n, 1).

  • Y_train (numpy.ndarray) – training outputs. Shape: (n, 1).

  • X_test (numpy.ndarray) – test inputs. Shape: (m, 1).

  • Y_test (numpy.ndarray) – true test outputs. Shape: (m, 1).

  • mean_test (numpy.ndarray) – posterior predictive mean function values over X_test. Shape: (m, 1).

  • std_test (numpy.ndarray) – posterior predictive standard deviation function values over X_test. Shape: (m, 1).

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • num_init (NoneType or int., optional) – None, or the number of initial examples.

  • use_tex (bool., optional) – flag for using latex.

  • draw_zero_axis (bool., optional) – flag for drawing a zero axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • range_shade (float, optional) – shade range for standard deviation.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError

bayeso.utils.utils_plotting.plot_bo_step_with_acq(X_train: ndarray, Y_train: ndarray, X_test: ndarray, Y_test: ndarray, mean_test: ndarray, std_test: ndarray, acq_test: ndarray, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'x', str_y_axis: str = 'y', str_acq_axis: str = 'acq.', num_init: int | None = None, use_tex: bool = False, draw_zero_axis: bool = False, pause_figure: bool = True, time_pause: int | float = 2.0, range_shade: float = 1.96) → None

It is for plotting Bayesian optimization results step by step.

Parameters:

  • X_train (numpy.ndarray) – training inputs. Shape: (n, 1).

  • Y_train (numpy.ndarray) – training outputs. Shape: (n, 1).

  • X_test (numpy.ndarray) – test inputs. Shape: (m, 1).

  • Y_test (numpy.ndarray) – true test outputs. Shape: (m, 1).

  • mean_test (numpy.ndarray) – posterior predictive mean function values over X_test. Shape: (m, 1).

  • std_test (numpy.ndarray) – posterior predictive standard deviation function values over X_test. Shape: (m, 1).

  • acq_test (numpy.ndarray) – acquisition funcion values over X_test. Shape: (m, 1).

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • str_acq_axis (str., optional) – the name of acquisition function axis.

  • num_init (NoneType or int., optional) – None, or the number of initial examples.

  • use_tex (bool., optional) – flag for using latex.

  • draw_zero_axis (bool., optional) – flag for drawing a zero axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • range_shade (float, optional) – shade range for standard deviation.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError

bayeso.utils.utils_plotting.plot_gp_via_distribution(X_train: ndarray, Y_train: ndarray, X_test: ndarray, mean_test: ndarray, std_test: ndarray, Y_test: ndarray | None = None, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'x', str_y_axis: str = 'y', use_tex: bool = False, draw_zero_axis: bool = False, pause_figure: bool = True, time_pause: int | float = 2.0, range_shade: float = 1.96, colors: ndarray = array(['red', 'green', 'blue', 'orange', 'olive', 'purple', 'darkred', 'limegreen', 'deepskyblue', 'lightsalmon', 'aquamarine', 'navy', 'rosybrown', 'darkkhaki', 'darkslategray'], dtype='<U13')) → None

It is for plotting Gaussian process regression.

Parameters:

  • X_train (numpy.ndarray) – training inputs. Shape: (n, 1).

  • Y_train (numpy.ndarray) – training outputs. Shape: (n, 1).

  • X_test (numpy.ndarray) – test inputs. Shape: (m, 1).

  • mean_test (numpy.ndarray) – posterior predictive mean function values over X_test. Shape: (m, 1).

  • std_test (numpy.ndarray) – posterior predictive standard deviation function values over X_test. Shape: (m, 1).

  • Y_test (NoneType or numpy.ndarray, optional) – None, or true test outputs. Shape: (m, 1).

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • use_tex (bool., optional) – flag for using latex.

  • draw_zero_axis (bool., optional) – flag for drawing a zero axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • range_shade (float, optional) – shade range for standard deviation.

  • colors (np.ndarray, optional) – array of colors.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError

bayeso.utils.utils_plotting.plot_gp_via_sample(X: ndarray, Ys: ndarray, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'x', str_y_axis: str = 'y', use_tex: bool = False, draw_zero_axis: bool = False, pause_figure: bool = True, time_pause: int | float = 2.0, colors: ndarray = array(['red', 'green', 'blue', 'orange', 'olive', 'purple', 'darkred', 'limegreen', 'deepskyblue', 'lightsalmon', 'aquamarine', 'navy', 'rosybrown', 'darkkhaki', 'darkslategray'], dtype='<U13')) → None

It is for plotting sampled functions from multivariate distributions.

Parameters:

  • X (numpy.ndarray) – training inputs. Shape: (n, 1).

  • Ys (numpy.ndarray) – training outputs. Shape: (m, n).

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • use_tex (bool., optional) – flag for using latex.

  • draw_zero_axis (bool., optional) – flag for drawing a zero axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • colors (np.ndarray, optional) – array of colors.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError

bayeso.utils.utils_plotting.plot_minimum_vs_iter(minima: ndarray, list_str_label: List[str], num_init: int, draw_std: bool, include_marker: bool = True, include_legend: bool = False, use_tex: bool = False, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'Iteration', str_y_axis: str = 'Minimum function value', pause_figure: bool = True, time_pause: int | float = 2.0, range_shade: float = 1.96, markers: ndarray = array(['.', 'x', '*', '+', '^', 'v', '<', '>', 'd', ',', '8', 'h', '1', '2', '3'], dtype='<U1'), colors: ndarray = array(['red', 'green', 'blue', 'orange', 'olive', 'purple', 'darkred', 'limegreen', 'deepskyblue', 'lightsalmon', 'aquamarine', 'navy', 'rosybrown', 'darkkhaki', 'darkslategray'], dtype='<U13')) → None

It is for plotting optimization results of Bayesian optimization, in terms of iterations.

Parameters:

  • minima (numpy.ndarray) – function values over acquired examples. Shape: (b, r, n) where b is the number of experiments, r is the number of rounds, and n is the number of iterations per round.

  • list_str_label (list) – list of label strings. Shape: (b, ).

  • num_init (int.) – the number of initial examples < n.

  • draw_std (bool.) – flag for drawing standard deviations.

  • include_marker (bool., optional) – flag for drawing markers.

  • include_legend (bool., optional) – flag for drawing a legend.

  • use_tex (bool., optional) – flag for using latex.

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • range_shade (float, optional) – shade range for standard deviation.

  • markers (np.ndarray, optional) – array of markers.

  • colors (np.ndarray, optional) – array of colors.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError

bayeso.utils.utils_plotting.plot_minimum_vs_time(times: ndarray, minima: ndarray, list_str_label: List[str], num_init: int, draw_std: bool, include_marker: bool = True, include_legend: bool = False, use_tex: bool = False, path_save: str | None = None, str_postfix: str | None = None, str_x_axis: str = 'Time (sec.)', str_y_axis: str = 'Minimum function value', pause_figure: bool = True, time_pause: int | float = 2.0, range_shade: float = 1.96, markers: ndarray = array(['.', 'x', '*', '+', '^', 'v', '<', '>', 'd', ',', '8', 'h', '1', '2', '3'], dtype='<U1'), colors: ndarray = array(['red', 'green', 'blue', 'orange', 'olive', 'purple', 'darkred', 'limegreen', 'deepskyblue', 'lightsalmon', 'aquamarine', 'navy', 'rosybrown', 'darkkhaki', 'darkslategray'], dtype='<U13')) → None

It is for plotting optimization results of Bayesian optimization, in terms of execution time.

Parameters:

  • times (numpy.ndarray) – execution times. Shape: (b, r, n), or (b, r, num_init + n) where b is the number of experiments, r is the number of rounds, and n is the number of iterations per round.

  • minima (numpy.ndarray) – function values over acquired examples. Shape: (b, r, num_init + n) where b is the number of experiments, r is the number of rounds, and n is the number of iterations per round.

  • list_str_label (list) – list of label strings. Shape: (b, ).

  • num_init (int.) – the number of initial examples.

  • draw_std (bool.) – flag for drawing standard deviations.

  • include_marker (bool., optional) – flag for drawing markers.

  • include_legend (bool., optional) – flag for drawing a legend.

  • use_tex (bool., optional) – flag for using latex.

  • path_save (NoneType or str., optional) – None, or path for saving a figure.

  • str_postfix (NoneType or str., optional) – None, or the name of postfix.

  • str_x_axis (str., optional) – the name of x axis.

  • str_y_axis (str., optional) – the name of y axis.

  • pause_figure (bool., optional) – flag for pausing before closing a figure.

  • time_pause (int. or float, optional) – pausing time.

  • range_shade (float, optional) – shade range for standard deviation.

  • markers (np.ndarray, optional) – array of markers.

  • colors (np.ndarray, optional) – array of colors.

Returns:

None.

Return type:

NoneType

Raises:

AssertionError