Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

nilearn.plotting.img_comparison.plot_bland_altman

nilearn.plotting.img_comparison.plot_bland_altman(ref_img, src_img, masker=None, ref_label='reference image', src_label='source image', figure=None, title=None, cmap='inferno', colorbar=True, gridsize=100, lims=None, output_file=None)[source]

Create a Bland-Altman plot between 2 images.

Plot the the 2D distribution of voxel-wise differences as a function of the voxel-wise mean, along with an histogram for the distribution of each.

Note

Bland-Altman plots show the difference between the statistic values (y-axis) against the mean statistic value (x-axis) for all voxels.

The plots provide an assessment of the level of agreement between two images about the magnitude of the statistic value observed at each voxel.

If two images were in perfect agreement, all points on the Bland-Altman plot would lie on the x-axis, since the difference between the statistic values at each voxel would be zero.

The degree of disagreement is therefore evaluated by the perpendicular distance of points from the x-axis.

Parameters:
ref_img3D Niimg-like object or SurfaceImage

Reference image.

src_img3D Niimg-like object or SurfaceImage

Source image. Its type must match that of the ref_img. If the source image is Niimg-Like, it will be resampled to match that or the source image.

masker3D Niimg-like binary mask or NiftiMasker or binary SurfaceImage or or SurfaceMasker or None, default = None

Mask to be used on data. Its type must be compatible with that of the ref_img. If None is passed, an appropriate masker will be fitted on the reference image.

ref_labelstr, default=’reference image’

Name of reference image.

src_labelstr, default=’source image’

Name of source image.

figureint, or matplotlib.figure.Figure, or None, optional

Matplotlib figure used or its number. If None is given, a new figure is created.

titlestr, or None, default=None

The title displayed on the figure.

cmapmatplotlib.colors.Colormap, or str, optional

The colormap to use. Either a string which is a name of a matplotlib colormap, or a matplotlib colormap object. default=”inferno”

colorbarbool, optional

If True, display a colorbar on the right of the plots. default=True

gridsizeint or tuple of 2 int, default=100

Dimension of the grid on which to display the main plot. If a single value is passed, then the grid is square. If a tuple is passed, the first value corresponds to the length of the x axis, and the second value corresponds to the length of the y axis.

limsA list or tuple of 4 int or None, default=None

Determines the limit the central hexbin plot and the marginal histograms. Values in the list or tuple are: [-lim_x, lim_x, -lim_y, lim_y]. If None is passed values are determined based on the data.

output_filestr or pathlib.Path or None, optional

The name of an image file to export the plot to. Valid extensions are .png, .pdf, .svg. If output_file is not None, the plot is saved to a file, and the display is closed.

Notes

This function and the plot description was adapted from Bowring et al.[1] and its associated code base.

References