.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/04_locations/000_employing_locations_of_interest.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_04_locations_000_employing_locations_of_interest.py: Utilizing locations of interest ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ `siibra` provides common locations of interests on reference spaces as objects. These location objects can be used to query features or assignment to the maps, see :ref:`sphx_glr_examples_05_anatomical_assignment_001_coordinates.py` and :ref:`sphx_glr_examples_05_anatomical_assignment_002_activation_maps.py`. The conversion of these locations to other spaces are done in the background but one can also be invoked when needed. .. GENERATED FROM PYTHON SOURCE LINES 29-33 .. code-block:: Python import siibra from nilearn import plotting import numpy as np .. GENERATED FROM PYTHON SOURCE LINES 34-36 The simplest location type is a point. It can have a uncertainty variable or can be exact. .. GENERATED FROM PYTHON SOURCE LINES 36-40 .. code-block:: Python point = siibra.Point((27.75, -32.0, 63.725), space='mni152') point_uncertain = siibra.Point((27.75, -32.0, 63.725), space='mni152', sigma_mm=3.) point_uncertain .. rst-class:: sphx-glr-script-out .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 41-42 We can create a PointCloud from several points or a set of coordinates. .. GENERATED FROM PYTHON SOURCE LINES 42-48 .. code-block:: Python siibra.PointCloud( [(27.75, -32.0, 63.725), (27.75, -32.0, 63.725)], space='mni152', sigma_mm=[0.0, 3.] ) .. rst-class:: sphx-glr-script-out .. code-block:: none ", ""]), space='minds/core/referencespace/v1.0.0/dafcffc5-4826-4bf1-8ff6-46b8a31ff8e2'> .. GENERATED FROM PYTHON SOURCE LINES 49-52 There are several helper properties and methods for locations, some specific to the location type. For example, we can warp the points to another space (currently limited only between MNI152, COLIN27, and BigBrain). .. GENERATED FROM PYTHON SOURCE LINES 52-55 .. code-block:: Python print(point.warp('bigbrain')) print(point.warp('colin27')) .. rst-class:: sphx-glr-script-out .. code-block:: none Point in BigBrain microscopic template (histology) [13.141,-5.65729,41.6915] Point in MNI Colin 27 [26.5659,-40.0247,64.2493] .. GENERATED FROM PYTHON SOURCE LINES 56-57 To explore further, let us first create a random pointcloud .. GENERATED FROM PYTHON SOURCE LINES 57-66 .. code-block:: Python ptset = siibra.PointCloud( np.array([ np.random.randn(10000) * 3 - 27.75, np.random.randn(10000) * 3 - 32.0, np.random.randn(10000) * 3 + 63.725 ]).T, space='mni152' ) .. GENERATED FROM PYTHON SOURCE LINES 67-68 We can display these points as a kernel density estimated volume .. GENERATED FROM PYTHON SOURCE LINES 68-71 .. code-block:: Python kde_volume = siibra.volumes.from_pointcloud(ptset) plotting.view_img(kde_volume.fetch()) .. rst-class:: sphx-glr-script-out .. code-block:: none /actions-runner/_work/_tool/Python/3.11.15/x64/lib/python3.11/site-packages/numpy/_core/fromnumeric.py:840: UserWarning: Warning: 'partition' will ignore the 'mask' of the MaskedArray. a.partition(kth, axis=axis, kind=kind, order=order) .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 72-76 Moreover, a location object can be used to query features. While we can also, query with the pointcloud, let us use the bounding box that encloses these points. We will query for image features and print the assignment of the anatomical anchors to our BoundingBox .. GENERATED FROM PYTHON SOURCE LINES 76-81 .. code-block:: Python bbox = ptset.boundingbox features_of_interest = siibra.features.get(bbox, 'image') for f in features_of_interest: print(f.last_match_description) .. rst-class:: sphx-glr-script-out .. code-block:: none 'Bounding box from (-86.55,-91.19,-61.17)mm to (22.83,85.56,75.21)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-13.97,-58.79)mm to (68.44,-13.95,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-13.13,-58.79)mm to (68.44,-13.11,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-12.11,-58.79)mm to (68.44,-12.09,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-10.91,-58.79)mm to (68.43,-10.89,62.10)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-10.05,-58.79)mm to (68.43,-10.03,62.10)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-9.13,-58.79)mm to (68.44,-9.11,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-8.11,-58.79)mm to (68.44,-8.09,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-7.11,-58.79)mm to (68.44,-7.09,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-6.11,-58.79)mm to (68.44,-6.09,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-4.95,-58.79)mm to (68.44,-4.93,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-3.93,-58.79)mm to (68.44,-3.91,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-3.07,-58.79)mm to (68.44,-3.05,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-1.89,-58.79)mm to (68.44,-1.87,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-0.87,-58.79)mm to (68.44,-0.85,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,-0.03,-58.79)mm to (68.44,-0.01,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,1.09,-58.79)mm to (68.44,1.11,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,1.99,-58.79)mm to (68.44,2.01,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,2.87,-58.79)mm to (68.44,2.89,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,3.93,-58.79)mm to (68.44,3.95,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-70.68,4.97,-58.79)mm to (68.44,4.99,62.11)mm in BigBrain microscopic template (histology) space' overlaps with 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-96.10,-132.10,-78.10)mm to (96.90,96.90,114.90)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' contains 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-96.10,-132.10,-78.10)mm to (96.90,96.90,114.90)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' contains 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-95.98,-131.98,-77.98)mm to (96.92,96.92,114.92)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' contains 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' 'Bounding box from (-96.10,-132.10,-78.10)mm to (96.90,96.90,114.90)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' contains 'Bounding box from (-39.38,-43.05,53.30)mm to (-15.40,-20.91,75.85)mm in MNI 152 ICBM 2009c Nonlinear Asymmetric space' .. GENERATED FROM PYTHON SOURCE LINES 82-83 And now let us simply select the features that overlaps with our BoundingBox .. GENERATED FROM PYTHON SOURCE LINES 83-91 .. code-block:: Python selected_features = [ f for f in features_of_interest if "overlaps" in str(f.last_match_result[0].qualification) ] for f in selected_features: print(f.name) .. rst-class:: sphx-glr-script-out .. code-block:: none The Enriched Connectome - Block face images of full sagittal human brain sections (blockface) #2803: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #2845: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #2896: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #2956: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #2999: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3045: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3096: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3146: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3196: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3254: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3305: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3348: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3407: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3458: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3500: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3556: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3601: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3645: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3698: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) #3750: selected 1 micron scans of BigBrain histological sections (v1.0) (cell body staining) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 22.395 seconds) **Estimated memory usage:** 370 MB .. _sphx_glr_download_examples_04_locations_000_employing_locations_of_interest.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: 000_employing_locations_of_interest.ipynb <000_employing_locations_of_interest.ipynb>` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: 000_employing_locations_of_interest.py <000_employing_locations_of_interest.py>` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: 000_employing_locations_of_interest.zip <000_employing_locations_of_interest.zip>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_