Modules.ContourBoxplot package
Submodules
Modules.ContourBoxplot.contour_boxplot module
- Modules.ContourBoxplot.contour_boxplot.contour_boxplot(binary_images, method='contour_bd', binary_images_depths=None, percentil=95, ax=None, show_median=True, show_outliers=True)[source]
Plot the contour boxplot including the band depth area between the top and bottom contours along with the median contour.
Parameters:
- binary_imagesnp.ndarray
3D array of shape (N, H, W) where N is the number of binary images and H, W are the height and width of each image.
- methodstr, optional
The method to use for plotting. Options are ‘contour_bd’. Default is ‘contour_bd’.
- binary_images_depthsnp.ndarray, optional
1D array of band depths of shape (N,). If None, it will be computed.
- percentilfloat, optional
Percentile for the band depth calculation. Default is 100.
- axmatplotlib.axes.Axes, optional
Matplotlib Axes object to plot on. If None, a new figure and axes will be created.
- show_medianbool, optional
Whether to plot the median contour. Default is True.
- show_outliersbool, optional
Whether to plot the outlier contours. Default is True.
Returns:
- axmatplotlib.axes.Axes
The Axes object with the plot.
Usage Example:
Modules.ContourBoxplot.contour_boxplot_mesh module
- Modules.ContourBoxplot.contour_boxplot_mesh.countour_binary_image(binary_images, depths, outlier_percentile=95, show_non_outliers=True, show_iqr=True, show_firstquartile=True)[source]
Create a contour boxplot mesh from binary images and their depths.
Parameters:
- binary_imagesnp.ndarray
3D array of shape (n_images, height, width) containing binary images (0s and 1s)
- depthsnp.ndarray
1D array of precomputed depth scores for each image. If None, depths will be computed.
- outlier_percentilefloat, optional
Percentile threshold to define outliers. Default is 95.
- show_non_outliersbool, optional
If True, highlights non-outlier regions in light gray. Default is True.
- show_iqrbool, optional
If True, highlights the interquartile range (IQR) in gray. Default is True.
- show_firstquartilebool, optional
If True, highlights the first quartile region in a different shade of gray. Default is True.
Returns:
- result_imagenp.ndarray
2D array representing the contour boxplot mesh.
- top_contournp.ndarray
2D array representing the top contour of the mesh.
- outliersnp.ndarray
3D array containing the outlier images.
Modules.ContourBoxplot.contour_boxplot_stats module
Modules.ContourBoxplot.contour_boxplot_vis module
- Modules.ContourBoxplot.contour_boxplot_vis.matplotlib_contour_vis(result_image, median=None, outliers=None, ax=None)[source]
Plot the contour boxplot with median and outliers.
Parameters:
- result_imagenp.ndarray
2D array representing the contour boxplot image.
- mediannp.ndarray, optional
2D binary array representing the median contour. Default is None.
- outlierslist of np.ndarray, optional
List of 2D binary arrays representing outlier contours. Default is None.
- axmatplotlib.axes.Axes, optional
Matplotlib Axes object to plot on. If None, a new figure and axes will be created.
Returns:
- axmatplotlib.axes.Axes
Matplotlib Axes object with the plotted contour boxplot.
Module contents
ContourBoxplot Module
This module provides contour-based boxplot functionality for uncertainty visualization.