.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/run_tiled_ome_zarr.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_run_tiled_ome_zarr.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_run_tiled_ome_zarr.py:


Tiled OME-Zarr
==============

This script shows how to create a tiled single-resolution OME-Zarr dataset,
make a tiles grid, and write data.

.. GENERATED FROM PYTHON SOURCE LINES 10-17

.. code-block:: Python

    import os
    from tempfile import TemporaryDirectory

    import numpy as np

    from iohub.ngff import open_ome_zarr








.. GENERATED FROM PYTHON SOURCE LINES 18-19

Set storage path

.. GENERATED FROM PYTHON SOURCE LINES 19-23

.. code-block:: Python

    tmp_dir = TemporaryDirectory()
    store_path = os.path.join(tmp_dir.name, "tiled.zarr")
    print("Zarr store path", store_path)





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

 .. code-block:: none

    Zarr store path /tmp/tmpqih40eag/tiled.zarr




.. GENERATED FROM PYTHON SOURCE LINES 24-25

Write 5D data to a new Zarr store

.. GENERATED FROM PYTHON SOURCE LINES 25-46

.. code-block:: Python


    # define grid (rows, columns)
    grid_shape = (2, 3)
    # define tile shape (5D array)
    tile_shape = (5, 2, 3, 32, 32)


    with open_ome_zarr(
        store_path, layout="tiled", mode="a", channel_names=["DAPI", "GFP"]
    ) as dataset:
        dtype = np.uint16
        tiles = dataset.make_tiles(
            "tiled_raw", grid_shape=grid_shape, tile_shape=tile_shape, dtype=dtype
        )
        for row in range(grid_shape[0]):
            for column in range(grid_shape[1]):
                # each tile will be filled with different constant values
                data = np.zeros(shape=tile_shape, dtype=dtype) + row + column
                tiles.write_tile(data, row, column)









.. GENERATED FROM PYTHON SOURCE LINES 47-48

Load the dataset

.. GENERATED FROM PYTHON SOURCE LINES 48-59

.. code-block:: Python


    with open_ome_zarr(store_path, layout="tiled", mode="r") as dataset:
        # data store structure
        dataset.print_tree()
        # get tiled image array
        tiled = dataset["tiled_raw"]
        # check grid and tile shapes
        print(tiled.tiles, tiled.tile_shape)
        # read a tile
        tile_1_2 = tiled.get_tile(1, 2)





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

 .. code-block:: none

    /
     └── tiled_raw (5, 2, 3, 64, 96) uint16
    (2, 3) (1, 1, 1, 32, 32)




.. GENERATED FROM PYTHON SOURCE LINES 60-61

Try viewing the images with napari-ome-zarr

.. GENERATED FROM PYTHON SOURCE LINES 63-64

Clean up

.. GENERATED FROM PYTHON SOURCE LINES 64-65

.. code-block:: Python

    tmp_dir.cleanup()








.. _sphx_glr_download_auto_examples_run_tiled_ome_zarr.py:

.. only:: html

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

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

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

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

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