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.buildinfo

@@ -0,0 +1,4 @@
+# Sphinx build info version 1
+# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
+config: 99142181445c475509bfbaf515a4c708
+tags: 645f666f9bcd5a90fca523b33c5a78b7

_downloads/01eacccaa3110e4f8317ee6d3f576cce/example_kdtree.ipynb

@@ -1,16 +1,5 @@
 {
   "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "collapsed": false
-      },
-      "outputs": [],
-      "source": [
-        "%matplotlib inline"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -82,7 +71,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.8.5"
+      "version": "3.9.20"
     }
   },
   "nbformat": 4,

_downloads/05fae4bb5ea585ab61e284fb627d1f1c/example_hinge_gyri.ipynb

@@ -1,16 +1,5 @@
 {
   "cells": [
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "collapsed": false
-      },
-      "outputs": [],
-      "source": [
-        "%matplotlib inline"
-      ]
-    },
     {
       "cell_type": "markdown",
       "metadata": {},
@@ -26,7 +15,14 @@
       },
       "outputs": [],
       "source": [
-        "# Authors: Julien Lefevre <[email protected]>\n\n# License: BSD (3-clause)\n# sphinx_gallery_thumbnail_number = 2"
+        "# Authors: Julien Lefevre <[email protected]>\n\n# License: MIT\n# sphinx_gallery_thumbnail_number = 2"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "NOTE: there is no visualization tool in slam, but we provide at the\n end of this script exemplare code to do the visualization with\n an external solution\n##############################################################################\n\n"
       ]
     },
     {
@@ -44,7 +40,7 @@
       },
       "outputs": [],
       "source": [
-        "import slam.plot as splt\nimport slam.curvature as scurv\nimport slam.generate_parametric_surfaces as sgps"
+        "import slam.curvature as scurv\nimport slam.generate_parametric_surfaces as sgps"
       ]
     },
     {
@@ -62,7 +58,14 @@
       },
       "outputs": [],
       "source": [
-        "hinge_mesh = sgps.generate_hinge(n_hinge=4)\nmesh_curvatures = scurv.curvatures_and_derivatives(hinge_mesh)\nmean_curvature = 1 / 2 * mesh_curvatures[0].sum(axis=0)\n\nvisb_sc = splt.visbrain_plot(\n    mesh=hinge_mesh, tex=mean_curvature, caption=\"hinge\", cblabel=\"mean curvature\"\n)\n\nvisb_sc.preview()"
+        "hinge_mesh = sgps.generate_hinge(n_hinge=4)\nmesh_curvatures = scurv.curvatures_and_derivatives(hinge_mesh)\nmean_curvature = 1 / 2 * mesh_curvatures[0].sum(axis=0)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## VISUALIZATION USING EXTERNAL TOOLS\n# Visualization with visbrain\nvisb_sc = splt.visbrain_plot(\n    mesh=hinge_mesh,\n    tex=mean_curvature,\n    caption=\"hinge\",\n    cblabel=\"mean curvature\"\n)\nvisb_sc.preview()\n\n"
       ]
     }
   ],
@@ -82,7 +85,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.8.5"
+      "version": "3.9.20"
     }
   },
   "nbformat": 4,

_downloads/1103ea032737d8c0a99f16d45774fa2a/example_surface_profiling.py

@@ -8,21 +8,24 @@
 
 # Authors: Tianqi SONG <[email protected]>
 
-# License: BSD (3-clause)
+# License: MIT
 # sphinx_gallery_thumbnail_number = 2
 
+###############################################################################
+# NOTE: there is no visualization tool in slam, but we provide at the
+# end of this script exemplare code to do the visualization with
+# an external solution
+###############################################################################
 
 ###############################################################################
 # importation of slam modules
 import numpy as np
-import trimesh.visual.color
-
 import slam.surface_profiling as surfpf
 import slam.io as sio
 
 ###############################################################################
 # loading an example mesh
-mesh = sio.load_mesh("data/example_mesh.gii")
+mesh = sio.load_mesh("../examples/data/example_mesh.gii")
 
 ###############################################################################
 # Select a vertex and get the coordinate and normal.
@@ -45,43 +48,46 @@
     vert0, norm0, init_rot_dir, rot_angle, r_step, max_samples, mesh
 )
 
-###############################################################################
-# Visualize result
-prof_points_mesh = profile_points.reshape(
-    profile_points.shape[0] * profile_points.shape[1], 3
-)
-prof_points_colors = np.zeros(prof_points_mesh.shape)
-points_mesh = trimesh.points.PointCloud(
-    prof_points_mesh, colors=np.array(prof_points_colors, dtype=np.uint8)
-)
-
-# set the points colors
-red, yellow, green, blue = [
-    [255, 0, 0, 255],
-    [255, 255, 0, 255],
-    [0, 255, 0, 255],
-    [0, 0, 255, 255],
-]
-color_i = np.zeros(4)
-for i in range(len(prof_points_mesh)):
-    degree = i / max_samples
-    num_profiles = int(360 / rot_angle)
-    segment_color = num_profiles / 3
-
-    if degree <= segment_color:
-        color_i = trimesh.visual.color.linear_color_map(
-            degree / segment_color, [red, yellow]
-        )
-    elif segment_color < degree <= segment_color * 2:
-        color_i = trimesh.visual.color.linear_color_map(
-            degree / segment_color - 1, [yellow, green]
-        )
-    elif segment_color * 2 < degree <= num_profiles:
-        color_i = trimesh.visual.color.linear_color_map(
-            degree / segment_color - 2, [green, blue]
-        )
-    points_mesh.colors[i] = np.array(color_i)
-
-# create a scene with the mesh and profiling points
-#scene = trimesh.Scene([points_mesh, mesh])
-#scene.show(smooth=False)
+#############################################################################
+# VISUALIZATION USING EXTERNAL TOOLS
+#############################################################################
+# import trimesh.visual.color
+# ###############################################################################
+# # Visualize result
+# prof_points_mesh = profile_points.reshape(
+#     profile_points.shape[0] * profile_points.shape[1], 3
+# )
+# prof_points_colors = np.zeros(prof_points_mesh.shape)
+# points_mesh = trimesh.points.PointCloud(
+#     prof_points_mesh, colors=np.array(prof_points_colors, dtype=np.uint8)
+# )
+# # set the points colors
+# red, yellow, green, blue = [
+#     [255, 0, 0, 255],
+#     [255, 255, 0, 255],
+#     [0, 255, 0, 255],
+#     [0, 0, 255, 255],
+# ]
+# color_i = np.zeros(4)
+# for i in range(len(prof_points_mesh)):
+#     degree = i / max_samples
+#     num_profiles = int(360 / rot_angle)
+#     segment_color = num_profiles / 3
+#
+#     if degree <= segment_color:
+#         color_i = trimesh.visual.color.linear_color_map(
+#             degree / segment_color, [red, yellow]
+#         )
+#     elif segment_color < degree <= segment_color * 2:
+#         color_i = trimesh.visual.color.linear_color_map(
+#             degree / segment_color - 1, [yellow, green]
+#         )
+#     elif segment_color * 2 < degree <= num_profiles:
+#         color_i = trimesh.visual.color.linear_color_map(
+#             degree / segment_color - 2, [green, blue]
+#         )
+#     points_mesh.colors[i] = np.array(color_i)
+#
+# # create a scene with the mesh and profiling points
+# scene = trimesh.Scene([points_mesh, mesh])
+# scene.show(smooth=False)

_downloads/1acd43dd845aadf007819a06a74ed2ef/example_hinge_gyri.py

@@ -8,26 +8,34 @@
 
 # Authors: Julien Lefevre <[email protected]>
 
-# License: BSD (3-clause)
+# License: MIT
 # sphinx_gallery_thumbnail_number = 2
 
+###############################################################################
+# NOTE: there is no visualization tool in slam, but we provide at the
+# end of this script exemplare code to do the visualization with
+# an external solution
+###############################################################################
 
 ###############################################################################
 # importation of slam modules
-import slam.plot as splt
 import slam.curvature as scurv
 import slam.generate_parametric_surfaces as sgps
 
-
 ###############################################################################
 # Creating an examplar 3-4-...n hinge mesh
-
 hinge_mesh = sgps.generate_hinge(n_hinge=4)
 mesh_curvatures = scurv.curvatures_and_derivatives(hinge_mesh)
 mean_curvature = 1 / 2 * mesh_curvatures[0].sum(axis=0)
 
-visb_sc = splt.visbrain_plot(
-    mesh=hinge_mesh, tex=mean_curvature, caption="hinge", cblabel="mean curvature"
-)
-
-visb_sc.preview()
+#############################################################################
+# VISUALIZATION USING EXTERNAL TOOLS
+# #############################################################################
+# # Visualization with visbrain
+# visb_sc = splt.visbrain_plot(
+#     mesh=hinge_mesh,
+#     tex=mean_curvature,
+#     caption="hinge",
+#     cblabel="mean curvature"
+# )
+# visb_sc.preview()

_downloads/1fe913e7437792218bfcc6e3f9023296/example_curvature_directions.py

@@ -8,67 +8,21 @@
 
 # Authors: Julien Lefevre <[email protected]>
 
-# License: BSD (3-clause)
+# License: MIT
 # sphinx_gallery_thumbnail_number = 2
 
-
 ###############################################################################
-# importation of slam modules
-import numpy as np
-import matplotlib.pyplot as plt
-from mpl_toolkits.mplot3d import Axes3D
+# NOTE: there is no visualization tool in slam, but we provide at the
+# end of this script exemplare code to do the visualization with
+# an external solution
+###############################################################################
 
+# importation of slam modules
 import slam.generate_parametric_surfaces as sgps
 import slam.curvature as scurv
 
-
-###############################################################################
-# Visualization of vector fields with matplotlib
-
-
-def visualize(mesh, vector_field, colors=None, params=None):
-    """
-    Visualize a mesh and a vector field over it
-    :param mesh: a mesh with n points
-    :param vector_field: (n,3) array
-    :param colors: (n,3) array
-    :param params: params[0] is the length of the quivers
-    :return:
-    """
-    n = mesh.vertices.shape[0]
-    if colors is None:
-        colors = np.zeros((n, 3))
-        colors[:, 0] = 1
-    if params is None:
-        params = []
-        params.append(0.1)
-
-    fig = plt.figure()
-    ax = Axes3D(fig)
-    ax.plot_trisurf(
-        mesh.vertices[:, 0],
-        mesh.vertices[:, 1],
-        mesh.vertices[:, 2],
-        triangles=mesh.faces,
-        shade=True,
-    )
-    plt.quiver(
-        mesh.vertices[:, 0],
-        mesh.vertices[:, 1],
-        mesh.vertices[:, 2],
-        vector_field[:, 0],
-        vector_field[:, 1],
-        vector_field[:, 2],
-        length=params[0],
-        colors=colors,
-    )
-
-    return fig
-
-
 ###############################################################################
 # Create quadric mesh
-
 nstep = 20
 equilateral = True
 
@@ -86,13 +40,56 @@ def visualize(mesh, vector_field, colors=None, params=None):
 
 ###############################################################################
 # Compute principal directions of curvature
-
-PrincipalCurvatures, PrincipalDir1, PrincipalDir2 = scurv.curvatures_and_derivatives(
-    quadric_mesh
-)
+PrincipalCurvatures, PrincipalDir1, PrincipalDir2 \
+    = scurv.curvatures_and_derivatives(quadric_mesh)
 
 ###############################################################################
-# Visualization
-
-visualize(quadric_mesh, PrincipalDir1)
-plt.show()
+# VISUALIZATION USING EXTERNAL TOOLS
+###############################################################################
+# import numpy as np
+# import matplotlib.pyplot as plt
+# from mpl_toolkits.mplot3d import Axes3D
+#
+# #############################################################################
+# # Visualization of vector fields with matplotlib
+# def visualize(mesh, vector_field, colors=None, params=None):
+#     """
+#     Visualize a mesh and a vector field over it
+#     :param mesh: a mesh with n points
+#     :param vector_field: (n,3) array
+#     :param colors: (n,3) array
+#     :param params: params[0] is the length of the quivers
+#     :return:
+#     """
+#     n = mesh.vertices.shape[0]
+#     if colors is None:
+#         colors = np.zeros((n, 3))
+#         colors[:, 0] = 1
+#     if params is None:
+#         params = []
+#         params.append(0.1)
+#
+#     fig = plt.figure()
+#     ax = Axes3D(fig)
+#     ax.plot_trisurf(
+#         mesh.vertices[:, 0],
+#         mesh.vertices[:, 1],
+#         mesh.vertices[:, 2],
+#         triangles=mesh.faces,
+#         shade=True,
+#     )
+#     plt.quiver(
+#         mesh.vertices[:, 0],
+#         mesh.vertices[:, 1],
+#         mesh.vertices[:, 2],
+#         vector_field[:, 0],
+#         vector_field[:, 1],
+#         vector_field[:, 2],
+#         length=params[0],
+#         colors=colors,
+#     )
+#
+#     return fig
+#
+# visualize(quadric_mesh, PrincipalDir1)
+# plt.show()