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.github/workflows/convert.sh

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echo "Converting all .md tutorials to .py files..."
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TUTS_DIR="$( cd -- "$(dirname "$0")" >/dev/null 2>&1 ; pwd -P )/../../docs/tutorials"
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pushd ${TUTS_DIR}
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for file in *.md; do
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if [ "$file" != "index.md" ] && [ "$file" != "livestream.md" ]; then
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jupytext --to py $file
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fi
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for subdir in */; do
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pushd $subdir
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for file in *.md; do
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if [ "$file" != "index.md" ] && [ "$file" != "livestream.md" ]; then
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jupytext --to py $file
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fi
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done
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popd
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done
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popd
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echo "Done."

docs/examples/livestream_napari.py

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"""
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This script will livestream data to the [napari viewer](https://napari.org/stable/). You may also utilize the `Acquire` napari plugin, which is provided in the `acquire-imaging` package on PyPI upon install. You can access the plugin in the napari plugins menu once `Acquire` is installed. You can review the [plugin code here](https://github.com/acquire-project/acquire-python/blob/main/python/acquire/__init__.py).
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This script will livestream data to the [napari viewer](https://napari.org/stable/). You may also utilize the `Acquire` napari plugin, which is provided in the `acquire-imaging` package on PyPI upon install. You can access the plugin in the napari plugins menu once `Acquire` is installed. You can review the [plugin code in `acquire-imaging`](https://github.com/acquire-project/acquire-python/blob/main/python/acquire/__init__.py).
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"""
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import acquire

docs/index.md

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- [FLIR Blackfly USB3 (BFLY-U3-23S6M-C)](https://www.flir.com/products/blackfly-usb3/?model=BFLY-U3-23S6M-C&vertical=machine+vision&segment=iis)
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- [FLIR Oryx 10GigE (ORX-10GS-51S5M-C)](https://www.flir.com/products/oryx-10gige/?model=ORX-10GS-51S5M-C&vertical=machine+vision&segment=iis)
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For testing and demonstration purposes, Acquire also provides a few simulated video sources. For more information on supported cameras and video sources, check out [this tutorial](./tutorials/drivers.md).
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For testing and demonstration purposes, Acquire also provides a few simulated video sources. For more information on supported cameras and video sources, check out [this tutorial](./tutorials/setup_acquisition/drivers.md).
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Acquire supports the following output file formats:
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- [Tiff](https://en.wikipedia.org/wiki/TIFF)
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- [OME-Zarr](https://ngff.openmicroscopy.org/latest/) for [Zarr v2](https://zarr.readthedocs.io/en/stable/spec/v2.html)
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- [Zarr v3](https://zarr.readthedocs.io/en/stable/spec/v3.html)
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Acquire also supports raw and trash storage devices. For more information on supported file formats and storage devices, check out [this tutorial](./tutorials/storage.md).
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Acquire also supports raw and trash storage devices. For more information on supported file formats and storage devices, check out the [Storage Device Selection tutorial](./tutorials/setup_acquisition/storage.md).
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## Citing Acquire
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~~~
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## Acquire License
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`Acquire` is provided under an [Apache 2.0 license](https://github.com/acquire-project/acquire-python/blob/main/LICENSE). You can learn more about the Apache license in the [documentation here](https://www.apache.org/licenses/LICENSE-2.0).
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`Acquire` is provided under an [Apache 2.0 license](https://github.com/acquire-project/acquire-python/blob/main/LICENSE). [Learn more about the Apache license](https://www.apache.org/licenses/LICENSE-2.0).
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# Data
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These tutorials will help you learn how to access data during acquisition.
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Please [submit an issue on GitHub](https://github.com/acquire-project/acquire-docs/issues/new)
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if you'd like to request a tutorial. If you are also interested in contributing
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to this documentation, please visit our
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[contribution guide](https://acquire-project.github.io/acquire-docs/dev/for_contributors/).
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# Livestream to napari
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The below script can be used to livestream data to the [napari viewer](https://napari.org/stable/). You may also utilize the `Acquire` napari plugin, which is provided in the package upon install. You can access the plugin in the napari plugins menu once `Acquire` is installed. You can review the [plugin code in the `acquire-imaging` repository](https://github.com/acquire-project/acquire-python/blob/d4a927079830dd9b61289e19e68dafdff4e8e643/python/acquire/__init__.py#L134). You may also stream using other packages such at `matplotlib`.
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~~~python
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{% include "../../examples/livestream_napari.py" %}
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~~~
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[Download this tutorial as a Python script](../../examples/livestream_napari.py){ .md-button .md-button-center }

docs/tutorials/index.md

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request a tutorial, or if you are also interested in contributing to a tutorial
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to this documentation please visit our
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[contribution guide](../for_contributors/index.md).
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<div class="cards">
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<div class="card">
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<h4>Setup acquisition</h4>
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<p>Learn how to configure and run an acquisition</p>
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<a href="setup_acquisition" class="button">Setup acquisition</a>
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</div>
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<div class="card">
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<h4>Using JSON</h4>
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<p>Learn how to save and retrieve acquisition settings</p>
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<a href="using_json" class="button">Using JSON</a>
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</div>
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<div class="card">
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<h4>Data</h4>
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<p>Learn how to access data during acquisition</p>
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<a href="access_data" class="button">Data</a>
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</div>
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<div class="card">
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<h4>Zarr</h4>
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<p>Learn about using OME-Zarr with Acquire</p>
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<a href="zarr" class="button">Zarr</a>
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</div>
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</div>

docs/tutorials/livestream.md

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docs/tutorials/configure.md renamed to docs/tutorials/setup_acquisition/configure.md

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## Configure `Camera`
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`Camera` class objects have 2 attributes, `settings`, a `CameraProperties` object, and an optional attribute `identifier`, which is a `DeviceIdentifier` object.
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`CameraProperties` has 5 attributes that are numbers and specify the exposure time and line interval in microseconds, how many pixels, if any, to bin (set to 1 by default to disable), and tuples for the image size and location on the camera chip. The other attributes are all instances of different classes. The `pixel_type` attribute is a `SampleType` object which indicates the data type of the pixel values in the image, such as Uint8. The `readout_direction` attribute is a `Direction` object specifying whether the data is read forwards or backwards from the camera. The `input_triggers` attribute is an `InputTriggers` object that details the characteristics of any input triggers in the system. The `output_triggers` attribute is an `OutputTriggers` object that details the characteristics of any output triggers in the system. All of the attributes of `InputTriggers` and `OutputTriggers` objects are instances of the `Trigger` class. The `Trigger` class is described in [this tutorial](https://acquire-project.github.io/acquire-docs/tutorials/trig_json/).
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`CameraProperties` has 5 attributes that are numbers and specify the exposure time and line interval in microseconds, how many pixels, if any, to bin (set to 1 by default to disable), and tuples for the image size and location on the camera chip. The other attributes are all instances of different classes. The `pixel_type` attribute is a `SampleType` object which indicates the data type of the pixel values in the image, such as Uint8. The `readout_direction` attribute is a `Direction` object specifying whether the data is read forwards or backwards from the camera. The `input_triggers` attribute is an `InputTriggers` object that details the characteristics of any input triggers in the system. The `output_triggers` attribute is an `OutputTriggers` object that details the characteristics of any output triggers in the system. All of the attributes of `InputTriggers` and `OutputTriggers` objects are instances of the `Trigger` class. The `Trigger` class is described in [Triggers from a JSON file](../using_json/trig_json.md).
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## Configure `Storage`
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`Storage` objects have 2 attributes, `settings`, a `StorageProperties` object, and an optional attribute `identifier`, which is an instance of the `DeviceIdentifier` class described above.
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`StorageProperties` has 2 attributes `external_metadata_json` and `filename` which are strings of the filename or filetree of the output metadata in JSON format and image data in whatever format corresponds to the selected storage device, respectively. `first_frame_id` is an integer ID that corresponds to the first frame of the current acquisition and is typically 0. `pixel_scale_um` is the camera pixel size in microns. `enable_multiscale` is a boolean used to specify if the data should be saved as an image pyramid. See the [multiscale tutorial](multiscale.md) for more information. The `chunking` attribute is an instance of the `ChunkingProperties` class, used for Zarr storage. See the [chunking tutorial](multiscale.md) for more information.
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`StorageProperties` has 2 attributes `external_metadata_json` and `filename` which are strings of the filename or filetree of the output metadata in JSON format and image data in whatever format corresponds to the selected storage device, respectively. `first_frame_id` is an integer ID that corresponds to the first frame of the current acquisition and is typically 0. `pixel_scale_um` is the camera pixel size in microns. `enable_multiscale` is a boolean used to specify if the data should be saved as an image pyramid. See [Multiscale Data Acqusition](../zarr/multiscale.md) for more information. The `chunking` attribute is an instance of the `ChunkingProperties` class, used for Zarr storage. See [Chunking Data for Zarr Storage](../zarr/chunked.md) for more information.
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We'll specify the name of the output image file below.
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