enh: function that calculates the new reference grid

sdcflows/utils/tools.py

@@ -23,6 +23,71 @@
 """Image processing tools."""
 
 
+def deoblique_and_zooms(in_reference, oblique, factor=4, padding=1):
+    """
+    Generate a sampling reference aligned with in_reference fully covering oblique.
+
+    Parameters
+    ----------
+    in_reference : :obj:`~nibabel.spatialimages.SpatialImage`
+        The sampling reference.
+    oblique : :obj:`~nibabel.spatialimages.SpatialImage`
+        The rotated coordinate system whose extent should be fully covered by the
+        generated reference.
+    factor : :obj:`int`
+        A factor to increase the resolution of the generated reference.
+    padding : :obj:`int`
+        Number of additional voxels around the most extreme positions of the projection of
+        oblique on to the reference.
+
+    """
+    from itertools import product
+    import numpy as np
+    from nibabel.affines import apply_affine, rescale_affine
+
+    # Reference space metadata
+    hdr = in_reference.header.copy()
+    affine = in_reference.affine
+    ref_shape = np.array(in_reference.shape[:3])
+    ref_zooms = np.array(hdr.get_zooms()[:3])
+    _, scode = in_reference.get_sform(coded=True)
+    _, qcode = in_reference.get_qform(coded=True)
+
+    # Calculate the 8 most extreme coordinates of oblique in in_reference space
+    extent = apply_affine(
+        oblique.affine,
+        np.array(list(product((0, 1), repeat=3))) * (ref_shape - 1),
+    )
+    extent_ijk = apply_affine(np.linalg.inv(affine), extent)
+
+    if isinstance(padding, int):
+        padding = tuple([padding] * 3)
+
+    underflow = min(extent_ijk.min(0) - padding, 0)
+    overflow = max(extent_ijk.max(0) + padding + 1 - ref_shape, 0)
+    if np.any(underflow > 0) or np.any(overflow > 0):
+        # Add under/overflow voxels
+        ref_shape += abs(underflow) + overflow
+        # Consistently update origin
+        affine[:-1, -1] = apply_affine(affine, underflow)
+
+    # Make grid denser
+    if abs(1.0 - factor) > 1e-5:
+        new_shape = np.rint(ref_shape * factor)
+        affine = rescale_affine(affine, ref_shape, ref_zooms / factor, new_shape)
+        ref_shape = new_shape
+
+    # Generate new reference
+    hdr.set_sform(affine, scode)
+    hdr.set_qform(affine, qcode)
+
+    return in_reference.__class__(
+        np.zeros(ref_shape.astype(int), dtype=hdr.get_data_dtype()),
+        affine,
+        hdr,
+    )
+
+
 def resample_to_zooms(in_file, zooms, order=3, prefilter=True):
     """Resample the input data to a new grid with the requested zooms."""
     from pathlib import Path