Merge pull request #84 from melissawm/fix-links

Make all links internal

docs/examples/livestream_napari.py

@@ -1,5 +1,5 @@
 """
-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).
+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).
 """
 
 import acquire

docs/index.md

@@ -58,7 +58,7 @@ Acquire supports the following output file formats:
 - [OME-Zarr](https://ngff.openmicroscopy.org/latest/) for [Zarr v2](https://zarr.readthedocs.io/en/stable/spec/v2.html)
 - [Zarr v3](https://zarr.readthedocs.io/en/stable/spec/v3.html)
 
-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).
+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/storage.md).
 
 ## Citing Acquire
 
@@ -67,4 +67,4 @@ Acquire also supports raw and trash storage devices. For more information on sup
 ~~~
 
 ## Acquire License
-`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).
+`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).

docs/tutorials/chunked.md

@@ -2,7 +2,7 @@
 
 This tutorial will provide an example of writing chunked data to a Zarr storage device.
 
-Zarr has additional capabilities relative to the basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. To enable _chunking_, set the attributes in an instance of the `ChunkingProperties` class. You can learn more about the Zarr capabilities in `Acquire` [here](https://github.com/acquire-project/acquire-driver-zarr).
+Zarr has additional capabilities relative to the basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. To enable _chunking_, set the attributes in an instance of the `ChunkingProperties` class. You can learn more about the Zarr capabilities in `Acquire` in [the Acquire Zarr documentation](https://github.com/acquire-project/acquire-driver-zarr/blob/main/README.md).
 
 ## Configure `Runtime`
 To start, we'll create a `Runtime` object and configure the streaming process, selecting `Zarr` as the storage device to enable chunking the data.

docs/tutorials/compressed.md

@@ -3,7 +3,7 @@
 This tutorial will provide an example of writing compressed data to a Zarr file.
 
 `Acquire` supports streaming compressed data to the `ZarrBlosc1*` storage devices. Compression is done via [Blosc](https://www.blosc.org/pages/blosc-in-depth/).
-Supported codecs are _lz4_ and _zstd_, available with **ZarrBlosc1Lz4ByteShuffle** and **ZarrBlosc1ZstdByteShuffle** devices, respectively. For a comparison of these codecs, please refer to the [Blosc docs](https://www.blosc.org/). You can learn more about the Zarr capabilities in `Acquire` [here](https://github.com/acquire-project/acquire-driver-zarr).
+Supported codecs are _lz4_ and _zstd_, available with **ZarrBlosc1Lz4ByteShuffle** and **ZarrBlosc1ZstdByteShuffle** devices, respectively. For a comparison of these codecs, please refer to the [Blosc docs](https://www.blosc.org/). You can learn more about the Zarr capabilities in `Acquire` in [the Acquire Zarr documentation](https://github.com/acquire-project/acquire-driver-zarr/blob/main/README.md).
 
 ## Configure `Runtime`
 
@@ -62,7 +62,7 @@ import zarr
 compressed = zarr.open(config.video[0].storage.settings.filename)
 ```
 
-We'll print some of the data properties to illustrate how the data was compressed. Since we have not enabled [multiscale](https://acquire-project.github.io/acquire-docs/tutorials/multiscale/) output, `out.zarr` will only have one top level array`"0"`.
+We'll print some of the data properties to illustrate how the data was compressed. Since we have not enabled [multiscale](multiscale.md) output, `out.zarr` will only have one top level array`"0"`.
 
 
 ```python

docs/tutorials/configure.md

@@ -47,7 +47,7 @@ config.video[0].max_frame_count = 100
 ## Configure `Camera`
 `Camera` class objects have 2 attributes, `settings`, a `CameraProperties` object, and an optional attribute `identifier`, which is a `DeviceIdentifier` object.
 
-`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/).
+`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](trig_json.md).
 
 We'll configure some camera settings below.
 
@@ -65,7 +65,7 @@ config.video[0].camera.settings.pixel_type = acquire.SampleType.U32
 ## Configure `Storage`
 `Storage` objects have 2 attributes, `settings`, a `StorageProperties` object, and an optional attribute `identifier`, which is an instance of the `DeviceIdentifier` class described above.
 
-`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.
+`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](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](chunked.md) for more information.
 
 We'll specify the name of the output image file below.
 

docs/tutorials/livestream.md

@@ -1,6 +1,6 @@
 # Livestream to napari
 
-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 here](https://github.com/acquire-project/acquire-python/blob/main/python/acquire/__init__.py#L131). You may also stream using other packages such at `matplotlib`.
+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`.
 
 ~~~python
 {% include "../examples/livestream_napari.py" %}

docs/tutorials/multiscale.md

@@ -2,7 +2,7 @@
 
 This tutorial will provide an example of writing multiscale data to a Zarr file.
 
-Zarr has additional capabilities relative to Acquire's basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. To enable _chunking_ and _multiscale storage_, set those attributes in instances of the `ChunkingProperties` and `StorageProperties` classes, respectively. You can learn more about the Zarr capabilities in `Acquire` [here](https://github.com/acquire-project/acquire-driver-zarr).
+Zarr has additional capabilities relative to Acquire's basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. To enable _chunking_ and _multiscale storage_, set those attributes in instances of the `ChunkingProperties` and `StorageProperties` classes, respectively. You can learn more about the Zarr capabilities in `Acquire` in [the Acquire Zarr documentation](https://github.com/acquire-project/acquire-driver-zarr/blob/main/README.md).
 
 ## Configure `Runtime`
 To start, we'll create a `Runtime` object and begin to configure the streaming process, selecting `Zarr` as the storage device so that writing multiscale data is possible.

docs/tutorials/props_json.md

@@ -20,7 +20,7 @@ All camera settings are captured by an instance of the `Properties` class, which
 config = runtime.get_configuration()
 ```
 
-You can update any of the settings in this instance of `Properties`. To save any updated settings, use the `set_configuration` method.  For this tutorial, we'll simply specify a camera, and then save these new settings. Note that more settings must be provided before this `Properties` object could be used for an acquistion. Check out [this tutorial](configure.md) for more information on configuring an acquisition.
+You can update any of the settings in this instance of `Properties`. To save any updated settings, use the `set_configuration` method.  For this tutorial, we'll simply specify a camera, and then save these new settings. Note that more settings must be provided before this `Properties` object could be used for an acquistion. Check out [Configure an Acquisition](configure.md) for more information on configuring an acquisition.
 
 ```python
 # set the radial sine simulated camera as the first video stream

docs/tutorials/setup.md

@@ -1,6 +1,6 @@
 # Utilizing the Setup Method
 
-This tutorial will provide an example of utilizing the [setup method](https://github.com/acquire-project/acquire-python/blob/ce0764e86bf1d10eb3a447eb670c28808ab3da3b/python/acquire/__init__.py#L41) to configure `Runtime` and specify some basic properties.
+This tutorial will provide an example of utilizing the [setup method][acquire.setup] to configure `Runtime` and specify some basic properties.
 
 ## Setup Function Definition
 

docs/tutorials/start_stop.md

@@ -4,7 +4,7 @@ This tutorial will provide an example of starting, stopping, and restarting acqu
 
 ## Configure Streaming
 
-To start, we'll create a `Runtime` object and configure the streaming process. To do this, we'll utilize the setup method. More information on that method is detailed in [this tutorial](https://acquire-project.github.io/acquire-docs/tutorials/setup).
+To start, we'll create a `Runtime` object and configure the streaming process. To do this, we'll utilize the setup method. More information on that method is detailed in [Utilizing the Setup Method](setup.md).
 
 ```python
 import acquire

docs/tutorials/storage.md

@@ -34,7 +34,7 @@ The output of that script will be:
 
 `Acquire` supports streaming data to [bigtiff](http://bigtiff.org/) and [Zarr V2](https://zarr.readthedocs.io/en/stable/spec/v2.html).
 
-Zarr has additional capabilities relative to the basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. You can learn more about the Zarr capabilities in `Acquire` [here](https://github.com/acquire-project/acquire-driver-zarr).
+Zarr has additional capabilities relative to the basic storage devices, namely _chunking_, _compression_, and _multiscale storage_. You can learn more about the Zarr capabilities in `Acquire` in [the Acquire Zarr documentation](https://github.com/acquire-project/acquire-driver-zarr/blob/main/README.md).
 
 - **raw** - Streams to a raw binary file.
 

docs/tutorials/trigger.md

@@ -15,7 +15,7 @@ runtime = acquire.Runtime()
 
 ## Configure Camera
 
-All camera settings can be captured by an instance of the `Properties` class, which will be associated with a given camera acquisition. The settings can be stored in a dictionary (e.g: `Properties.dict()`). These settings can be saved to a JSON file to be subsequently loaded, (e.g. `Properties(**json.load(open('acquire.json')))`), using the [json library](https://docs.python.org/3/library/json.html#). Check out [this tutorial](props_json.md) for a more detailed example, but in brief, you would use something like:
+All camera settings can be captured by an instance of the `Properties` class, which will be associated with a given camera acquisition. The settings can be stored in a dictionary (e.g: `Properties.dict()`). These settings can be saved to a JSON file to be subsequently loaded, (e.g. `Properties(**json.load(open('acquire.json')))`), using the [json library](https://docs.python.org/3/library/json.html#). Check out [Properties from a JSON file](props_json.md) for a more detailed example, but in brief, you would use something like:
 
 ```python
 config = runtime.get_configuration()
@@ -39,7 +39,7 @@ config.video[0].camera.identifier = runtime.device_manager().select(acquire.Devi
 
 Next we'll choose the settings for the Hamamatsu camera. The `CameraProperties` class describes the available settings, which include exposure time (in microseconds), binning, pixel data type (e.g. u16), and how many frames to acquire.
 
-Every property can be set using the following syntax, but in this example, we will only change a few of the available settings. [Check out this tutorial](configure.md) for an explanation of camera properties.
+Every property can be set using the following syntax, but in this example, we will only change a few of the available settings. Check out [Configure an Acquisition](configure.md) for an explanation of camera properties.
 
 ```python
 config.video[0].camera.settings.binning = 1 # no pixels will be combined
@@ -49,7 +49,7 @@ config.video[0].camera.settings.pixel_type = acquire.SampleType.U16 # sets the p
 config.video[0].max_frame_count = 10 # finite acquisition of 10 frames. Use 0 for infinite acquisition.
 ```
 
-Triggers can also be set in the `CameraProperties` object. The parameters can be stored in a dictionary (e.g: `Trigger.dict()`). You can construct a `Trigger` from a JSON file (e.g.  `acquire.Trigger(**json.loads(open('trigger.json')))` ), using the [json library](https://docs.python.org/3/library/json.html#). Check out [this tutorial](trig_json.md) for a more detailed example, but in brief, you would use something like:
+Triggers can also be set in the `CameraProperties` object. The parameters can be stored in a dictionary (e.g: `Trigger.dict()`). You can construct a `Trigger` from a JSON file (e.g.  `acquire.Trigger(**json.loads(open('trigger.json')))` ), using the [json library](https://docs.python.org/3/library/json.html#). Check out [Triggers from a JSON file](trig_json.md) for a more detailed example, but in brief, you would use something like:
 
 ```python
 trig = acquire.Trigger()
@@ -98,7 +98,7 @@ from rich.pretty import pprint
 pprint(config.dict())
 ```
 
-Check out [this tutorial](https://acquire-project.github.io/acquire-docs/tutorials/props_json/) for a more detailed example of saving `Properties`.
+Check out [Properties from a JSON file](props_json.md) for a more detailed example of saving `Properties`.
 
 ## Acquire data
 

mkdocs.yml

@@ -75,6 +75,7 @@ markdown_extensions:
   - toc:
       permalink: true
   - attr_list
+  - pymdownx.magiclink
 
 
 plugins: