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diff --git a/src/silx/gui/_glutils/utils.py b/src/silx/gui/_glutils/utils.py
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+# coding: utf-8
+# /*##########################################################################
+#
+# Copyright (c) 2014-2021 European Synchrotron Radiation Facility
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# ###########################################################################*/
+"""This module provides conversion functions between OpenGL and numpy types.
+"""
+
+__authors__ = ["T. Vincent"]
+__license__ = "MIT"
+__date__ = "10/01/2017"
+
+import numpy
+
+from OpenGL.constants import BYTE_SIZES as _BYTE_SIZES
+from OpenGL.constants import ARRAY_TO_GL_TYPE_MAPPING as _ARRAY_TO_GL_TYPE_MAPPING
+
+
+def sizeofGLType(type_):
+    """Returns the size in bytes of an element of type `type_`"""
+    return _BYTE_SIZES[type_]
+
+
+def isSupportedGLType(type_):
+    """Test if a numpy type or dtype can be converted to a GL type."""
+    return numpy.dtype(type_).char in _ARRAY_TO_GL_TYPE_MAPPING
+
+
+def numpyToGLType(type_):
+    """Returns the GL type corresponding the provided numpy type or dtype."""
+    return _ARRAY_TO_GL_TYPE_MAPPING[numpy.dtype(type_).char]
+
+
+def segmentTrianglesIntersection(segment, triangles):
+    """Check for segment/triangles intersection.
+
+    This is based on signed tetrahedron volume comparison.
+
+    See A. Kensler, A., Shirley, P.
+    Optimizing Ray-Triangle Intersection via Automated Search.
+    Symposium on Interactive Ray Tracing, vol. 0, p33-38 (2006)
+
+    :param numpy.ndarray segment:
+        Segment end points as a 2x3 array of coordinates
+    :param numpy.ndarray triangles:
+        Nx3x3 array of triangles
+    :return: (triangle indices, segment parameter, barycentric coord)
+        Indices of intersected triangles, "depth" along the segment
+        of the intersection point and barycentric coordinates of intersection
+        point in the triangle.
+    :rtype: List[numpy.ndarray]
+    """
+    # TODO triangles from vertices + indices
+    # TODO early rejection? e.g., check segment bbox vs triangle bbox
+    segment = numpy.asarray(segment)
+    assert segment.ndim == 2
+    assert segment.shape == (2, 3)
+
+    triangles = numpy.asarray(triangles)
+    assert triangles.ndim == 3
+    assert triangles.shape[1] == 3
+
+    # Test line/triangles intersection
+    d = segment[1] - segment[0]
+    t0s0 = segment[0] - triangles[:, 0, :]
+    edge01 = triangles[:, 1, :] - triangles[:, 0, :]
+    edge02 = triangles[:, 2, :] - triangles[:, 0, :]
+
+    dCrossEdge02 = numpy.cross(d, edge02)
+    t0s0CrossEdge01 = numpy.cross(t0s0, edge01)
+    volume = numpy.sum(dCrossEdge02 * edge01, axis=1)
+    del edge01
+    subVolumes = numpy.empty((len(triangles), 3), dtype=triangles.dtype)
+    subVolumes[:, 1] = numpy.sum(dCrossEdge02 * t0s0, axis=1)
+    del dCrossEdge02
+    subVolumes[:, 2] = numpy.sum(t0s0CrossEdge01 * d, axis=1)
+    subVolumes[:, 0] = volume - subVolumes[:, 1] - subVolumes[:, 2]
+    intersect = numpy.logical_or(
+        numpy.all(subVolumes >= 0., axis=1),  # All positive
+        numpy.all(subVolumes <= 0., axis=1))  # All negative
+    intersect = numpy.where(intersect)[0]  # Indices of intersected triangles
+
+    # Get barycentric coordinates
+    with numpy.errstate(invalid="ignore"):
+        barycentric = subVolumes[intersect] / volume[intersect].reshape(-1, 1)
+    del subVolumes
+
+    # Test segment/triangles intersection
+    volAlpha = numpy.sum(t0s0CrossEdge01[intersect] * edge02[intersect], axis=1)
+    with numpy.errstate(invalid="ignore"):
+        t = volAlpha / volume[intersect]  # segment parameter of intersected triangles
+    del t0s0CrossEdge01
+    del edge02
+    del volAlpha
+    del volume
+
+    inSegmentMask = numpy.logical_and(t >= 0., t <= 1.)
+    intersect = intersect[inSegmentMask]
+    t = t[inSegmentMask]
+    barycentric = barycentric[inSegmentMask]
+
+    # Sort intersecting triangles by t
+    indices = numpy.argsort(t)
+    return intersect[indices], t[indices], barycentric[indices]