5e3cd5a9f1dfc0e320d3ff5a384505bf06904365,nilearn/plotting/displays.py,BaseSlicer,_map_show,#BaseSlicer#Any#Any#,423

Before Change

        xmin_, xmax_, ymin_, ymax_, zmin_, zmax_ = \
                                        xmin, xmax, ymin, ymax, zmin, zmax
        if hasattr(data, "mask") and isinstance(data.mask, np.ndarray):
            not_mask = np.logical_not(data.mask)
            xmin_, xmax_, ymin_, ymax_, zmin_, zmax_ = \
                    get_mask_bounds(nibabel.Nifti1Image(not_mask.astype(np.int),
                                    affine))
            if kwargs.get("vmin") is None or kwargs.get("vmax") is None:
                // Avoid dealing with masked arrays: they are slow
                if not np.any(not_mask):
                    // Everything is masked
                    vmin = vmax = 0
                else:
                    masked_map = np.asarray(data)[not_mask]
                    vmin = masked_map.min()
                    vmax = masked_map.max()
                if kwargs.get("vmin") is None:
                    kwargs["vmin"] = vmin
                if kwargs.get("vmax") is None:
                    kwargs["vmax"] = vmax
        else:
            if not "vmin" in kwargs:
                kwargs["vmin"] = data.min()
            if not "vmax" in kwargs:
                kwargs["vmax"] = data.max()

        bounding_box = (xmin_, xmax_), (ymin_, ymax_), (zmin_, zmax_)

        // For each ax, cut the data and plot it
        ims = []

After Change

        bounding_box = (xmin_, xmax_), (ymin_, ymax_), (zmin_, zmax_)

        ims = []
        to_iterate_over = itertools.izip(self.axes.itervalues(), data_2d_list)
        for display_ax, data_2d in to_iterate_over:
            if data_2d is not None:
                im = display_ax.draw_2d(data_2d, data_bounds, bounding_box,
                                        type=type, **kwargs)

Instances