.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples\01_data_in\plot_02_simpleitk.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_01_data_in_plot_02_simpleitk.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_01_data_in_plot_02_simpleitk.py:


Load from SimpleITK
===================

**Background.** Many imaging scripts already hold images as SimpleITK
objects. HABIT can wrap those objects directly, keeping their spacing,
origin and direction, so no files have to be rearranged.

**Purpose.** You get a :class:`~habit.contracts.Cohort` built from
SimpleITK images, plus a quick one-step habitat map on one patient to
show the cohort is usable.

**When to use.** Use this when your code already calls
``sitk.ReadImage`` or produces SimpleITK images; if your files follow the
HABIT folder layout, :doc:`/auto_examples/01_data_in/plot_01_directory`
is shorter.

**Key terms.**

* **cohort / subject / ROI** -- see
  :doc:`/auto_examples/01_data_in/plot_01_directory`.
* **one-step habitats** -- habitats clustered inside one subject only; see
  :doc:`/auto_examples/04_designs/plot_02_inside_each_subject`.

Read an image file and a mask file with SimpleITK, then put the volumes on
a :class:`~habit.contracts.Subject`. ``modality=`` is the series or ROI
name. One person and several people are each a
:class:`~habit.contracts.Cohort`.

.. GENERATED FROM PYTHON SOURCE LINES 32-33

One person. Change the two paths to your files.

.. GENERATED FROM PYTHON SOURCE LINES 33-58

.. code-block:: Python

    from pathlib import Path

    import matplotlib.pyplot as plt
    import SimpleITK as sitk

    from habit.contracts import Cohort, ImageVolume, MaskVolume, Subject
    from habit.datasets import fetch_demo
    from habit.recipes import one_step_habitat
    from habit.viz import plot_habitat_overlay, plot_simpleitk_ingest

    DATA = fetch_demo()
    IMAGE = DATA / "images" / "subj001" / "LAP" / "WATER__WATER__Ax_Dyn_LAVA_Flex+C_Series0009.nrrd"
    MASK = DATA / "masks" / "subj001" / "LAP" / "WATER__BH_Ax_LAVA_Flex_10min_Series0017_mask.nrrd"
    # from_sitk keeps spacing / origin / direction, so voxel sizes stay physical.
    volume = ImageVolume.from_sitk(sitk.ReadImage(str(IMAGE)), modality="LAP")
    roi = MaskVolume.from_sitk(sitk.ReadImage(str(MASK)), modality="LAP")
    # Dictionary keys are the names later stages use (modalities=..., roi=...).
    subject = Subject(
        subject_id="subj001",
        images={"LAP": volume},
        masks={"LAP": roi},
    )
    one = Cohort([subject], name="one")
    print(one)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    HABIT demo data (cached)
    DATA (preprocessed root): C:\Users\dongm\.habit_data\demo-data-v1\preprocessed

    On-disk inventory of this folder:
      subjects (5): subj001, subj002, subj003, subj004, subj005
      image series: LAP, PVP, delay_3min, pre_contrast
      mask keys:    LAP, PVP, delay_3min, pre_contrast
      example image: images/subj001/delay_3min/WATER__BH_Ax_LAVA_Flex_3min_Series0012.nrrd
      example mask:  masks/subj001/delay_3min/WATER__BH_Ax_LAVA_Flex_10min_Series0017_mask.nrrd

    Your own data must use the same folder tree (change IDs / series names):

      DATA/
        images/<subject_id>/<modality>/<one image file>
        masks/<subject_id>/<roi>/<one mask file>

    Then load it with the same call the demos use:

      cohort = cohort_from_directory(DATA, modalities=("LAP",), roi="LAP")

    Swap DATA / modalities / roi to match your tree. Mask key is often the
    same as one image series (here LAP).
    Cohort(1 subjects [subj001], name='one')




.. GENERATED FROM PYTHON SOURCE LINES 59-61

One-step habitats on this one person, then overlay. This only proves the
cohort works end to end; habitat stages are explained in section 2.

.. GENERATED FROM PYTHON SOURCE LINES 61-80

.. code-block:: Python

    sitk_result = one_step_habitat(
        modalities=("LAP",), n_habitats=3, random_seed=0, roi="LAP"
    ).fit_predict(one)
    Path("out").mkdir(exist_ok=True)

    # Visual summary of this route: SimpleITK image objects in, habitats out
    # (right panel zooms to the habitat bounding box).
    fig_ingest = plot_simpleitk_ingest(volume, sitk_result.habitat_maps[0])
    fig_ingest.savefig("out/data_from_sitk_ingest.png", dpi=150, bbox_inches="tight")
    plt.show()

    fig_sitk = plot_habitat_overlay(
        volume,
        sitk_result.habitat_maps[0],
        title="Habitats from SimpleITK",
    )
    fig_sitk.savefig("out/data_from_sitk_overlay.png", dpi=150, bbox_inches="tight")
    plt.show()




.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /auto_examples/01_data_in/images/sphx_glr_plot_02_simpleitk_001.png
         :alt: From SimpleITK to habitats, Habitats
         :srcset: /auto_examples/01_data_in/images/sphx_glr_plot_02_simpleitk_001.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /auto_examples/01_data_in/images/sphx_glr_plot_02_simpleitk_002.png
         :alt: Habitats from SimpleITK, Axis 0 (axial-like) @ 96, Axis 1 (coronal-like) @ 165, Axis 2 (sagittal-like) @ 71
         :srcset: /auto_examples/01_data_in/images/sphx_glr_plot_02_simpleitk_002.png
         :class: sphx-glr-multi-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    Cohort.map[_DefineAndLabelWithinSubject]:   0%|          | 0/1 [00:00<?, ?it/s]
    Cohort.map[_DefineAndLabelWithinSubject]: 100%|██████████| 1/1 [00:00<00:00,  1.35it/s]
    Cohort.map[_DefineAndLabelWithinSubject]: 100%|██████████| 1/1 [00:00<00:00,  1.35it/s]
    F:\work\habit_project\habit\viz\diagrams.py:245: UserWarning: Display geometry conflict: image/anatomy direction does not match mask/label direction. Using the mask/label direction so coronal/sagittal superior-up follows the labelled anatomy. Pass direction= to override.
      resolved_direction, resolved_spacing = resolve_display_geometry(
    F:\work\habit_project\habit\viz\habitat_overlay.py:806: UserWarning: Display geometry conflict: image/anatomy direction does not match mask/label direction. Using the mask/label direction so coronal/sagittal superior-up follows the labelled anatomy. Pass direction= to override.
      resolved_direction, resolved_spacing = resolve_display_geometry(




.. GENERATED FROM PYTHON SOURCE LINES 81-82

Several people. Same construction, one Subject per person.

.. GENERATED FROM PYTHON SOURCE LINES 82-93

.. code-block:: Python

    IMAGE_2 = DATA / "images" / "subj002" / "LAP" / "012_WATERWATERAxDynLAVAFlexC.nrrd"
    MASK_2 = DATA / "masks" / "subj002" / "LAP" / "016_WATERWATERBHAxLAVAFlex5min_mask.nrrd"
    volume_2 = ImageVolume.from_sitk(sitk.ReadImage(str(IMAGE_2)), modality="LAP")
    roi_2 = MaskVolume.from_sitk(sitk.ReadImage(str(MASK_2)), modality="LAP")
    subject_2 = Subject(
        subject_id="subj002",
        images={"LAP": volume_2},
        masks={"LAP": roi_2},
    )
    many = Cohort([subject, subject_2], name="many")
    print(many)




.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    Cohort(2 subjects [subj001, subj002], name='many')





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 3.021 seconds)


.. _sphx_glr_download_auto_examples_01_data_in_plot_02_simpleitk.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_02_simpleitk.ipynb <plot_02_simpleitk.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_02_simpleitk.py <plot_02_simpleitk.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_02_simpleitk.zip <plot_02_simpleitk.zip>`


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 .. rst-class:: sphx-glr-signature

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