Fix broken links?

docs/source/blog/version1/core_and_napari_merge.md

@@ -17,7 +17,7 @@ As such;
 - [`cellfinder-core`](https://github.com/brainglobe/cellfinder-core) and [`cellfinder-napari`](https://github.com/brainglobe/cellfinder-napari) will be deprecated.
 - [A _package_ called `cellfinder`](https://github.com/brainglobe/cellfinder) will become available as a replacement for this functionality. Note that this will re-use the old "cellfinder" name that the command-line-interface had, [prior to its migration](./cellfinder_migration_live.md).
 - The `cellfinder-napari` plugin is now simply called "cellfinder" internally, and when loaded up in napari.
-- The "cellfinder" name for the whole-brain registration and analysis workflow provided by [`brainglobe-workflows`](documentation/brainglobe-workflows/index) will be deprecated to avoid confusion. This workflow will now be available as "`brainmapper`".
+- The "cellfinder" name for the whole-brain registration and analysis workflow provided by [`brainglobe-workflows`](/documentation/brainglobe-workflows/index.md) will be deprecated to avoid confusion. This workflow will now be available as "`brainmapper`".
 
 From a user perspective, this is just a restructuring and reorganisation of existing functionality, and the renaming of the cellfinder command-line tool to `brainmapper`.
 If you were using the `cellfinder-core` backend, or the `cellfinder-napari` plugins, you'll need to uninstall those packages and install version `1.0.0` (or later) of the [`cellfinder` _package_](https://pypi.org/project/cellfinder/).

docs/source/community/releases/v1/cellfinder-core-and-plugin-merge.md

@@ -74,7 +74,7 @@ pip install brainglobe-workflows
 ```
 
 You will now have access to the `brainmapper` workflow from within your environment.
-This is the same as the old "cellfinder" workflow that you were using previously - but now it is [supplied by the `brainglobe-workflows` package](blog/version1/cellfinder_migration_live).
+This is the same as the old "cellfinder" workflow that you were using previously - but now it is [supplied by the `brainglobe-workflows` package](/blog/version1/cellfinder_migration_live.md).
 You will also have the latest version of the `cellfinder` package (`1.0.0` or later) installed;
 
 - `cellfinder-core` is included as a submodule, `cellfinder.core`.

docs/source/documentation/brainglobe-workflows/brainmapper/index.md

@@ -28,8 +28,8 @@ training/index
 
 ## Troubleshooting
 
-Since `brainmapper` uses `cellfinder`, you may encounter issues when using the command-line tool that are [documented on the `cellfinder` page](../cellfinder/troubleshooting/index.md).
-[Head there](../cellfinder/troubleshooting/index.md) for more information on some common issues and debugging tips.
+Since `brainmapper` uses `cellfinder`, you may encounter issues when using the command-line tool that are [documented on the `cellfinder` page](../../cellfinder/troubleshooting/index.md).
+[Head there](../../cellfinder/troubleshooting/index.md) for more information on some common issues and debugging tips.
 
 ## Notes
 

docs/source/documentation/brainglobe-workflows/brainmapper/visualisation.md

@@ -13,12 +13,12 @@ Assuming that your raw data is stored as `.tiff` files, drag these into napari (
 This should be whatever you passed to `brainmapper` originally, i.e., a single multipage tiff, or a directory of 2D tiffs.
 You can load as many channels as you like (e.g., the signal and the background channel).
 
-![Loading raw data into napari](/documentation/brainmapper/images/load_data.gif)
+![Loading raw data into napari](/documentation/brainglobe-workflows/brainmapper/images/load_data.gif)
 
 ## Visualising your results
 
 You can then drag and drop the `brainmapper` output directory (the one you specified with the `-o` flag) into the napari window.
 The plugin will then load your detected cells (in yellow) and the rejected cell candidates (in blue).
 If you carried out registration, then these results will be overlaid (similarly to the [brainreg plugin](/documentation/brainreg/user-guide/visualisation), but transformed to the coordinate space of your raw data).
 
-![Visualising `brainmapper` results. ](/documentation/`brainmapper`/images/load_results.gif)
+![Visualising `brainmapper` results](/documentation/brainglobe-workflows/brainmapper/images/load_results.gif)

docs/source/documentation/brainglobe-workflows/index.md

@@ -3,7 +3,7 @@
 brainglobe-workflows is a collection of common data analysis pipelines that utilise a combination of BrainGlobe tools.
 It currently provides:
 
-- `brainmapper`: Whole-brain cell detection and classification. [Read more about the command line interface here](/documentation/cellfinder/user-guide/command-line/index.md). This workflow was [previously called `cellfinder`](/blog/version1/core_and_napari_merge.md).
+- `brainmapper`: Whole-brain cell detection and classification. [Read more about the command line interface here](brainmapper/index.md). This workflow was [previously called `cellfinder`](/blog/version1/core_and_napari_merge.md).
 
 You can find more information on each of these tools by visiting the links below:
 

docs/source/documentation/brainrender/installation.md

@@ -26,9 +26,6 @@ others. You can safely ignore these.
 Note that some of `brainrender`'s more rarely used features may require the installation of additional packages. In particular, for exporting videos you will need to install [`ffmpeg`](https://ffmpeg.org/download.html).
 :::
 
-Once you have installed brainrender, dive right in with this 
-[getting started example notebook!](https://github.com/brainglobe/brainrender/blob/master/getting_started.ipynb)
-
 ## Advanced installation
 
 If you want the most recent version of `brainrender`'s code, perhaps to help developing it, you can either 

docs/source/tutorials/brainmapper/running-brainmapper.md

@@ -1,6 +1,6 @@
 # Running `brainmapper`
 
-`brainmapper` runs with a single command, with various arguments that are detailed in [Command line options](/documentation/brainglobe-workflows/brainmapper/user-guide/command-line/cli).
+`brainmapper` runs with a single command, with various arguments that are detailed in the [command line options](/documentation/brainglobe-workflows/brainmapper/cli).
 To analyse the example data, the flags we need are:
 
 - `-s` The primary **s**ignal channel: `test_brain/ch00`.
@@ -42,7 +42,7 @@ brainmapper -s test_brain/ch00 -b test_brain/ch01 -o test_brain/output -v 5 2 2
 
 :::{hint}
 If the cell classification step takes a (very) long time, it may not be using the GPU.
-If you have an NVIDIA GPU, see [Speeding up brainmapper](/documentation/brainglobe-workflows/brainmapper/troubleshooting/speed-up) to make sure that your GPU is set up properly.
+If you have an NVIDIA GPU, see [Speeding up brainmapper](/documentation/cellfinder/troubleshooting/speed-up) to make sure that your GPU is set up properly.
 :::
 
 Once `brainmapper` has run, you can go onto [Visualising the results](visualising-the-results).

docs/source/tutorials/brainmapper/setting-up.md

@@ -2,7 +2,7 @@
 
 ## Installation and download
 
-- First install the `brainmapper` command line tool, following the [Installation guide](/documentation/brainglobe-workflows/installation).
+- First install the `brainmapper` command line tool by installing the `brainglobe-workflows` package, following the [installation guide](/documentation/brainglobe-workflows/index.md#installation).
 - Download the data from [here](https://gin.g-node.org/cellfinder/data/raw/master/test\_brain\_SK\_AA\_71\_3.zip) (it will take a long time to download). Thanks to [Sepiedeh Keshavarzi](https://www.keshavarzilab.com/) for sharing the data.
 - Unzip the data to a directory of your choice (doesn't matter where). You should end up with a directory called `test_brain` with two directories, each containing 2800 images.
 - Open a terminal (Linux) or your command prompt (Windows).

docs/source/tutorials/brainmapper/visualising-the-results.md

@@ -5,7 +5,7 @@ description: How to inspect the results in napari
 # Visualising the results
 
 `brainmapper` comes with a plugin for [napari](https://napari.org/) for easily visualising the results.
-For more information, see [Visualisation](/documentation/brainglobe-workflows/brainmapper/user-guide/command-line/visualisation).
+For more information, see the [visualisation](/documentation/brainglobe-workflows/brainmapper/visualisation.md) section.
 To quickly view your data:
 
 - Open napari (type `napari` into a command window).

docs/source/tutorials/index.md

@@ -1,6 +1,7 @@
 # Tutorials
 
 ## Getting started
+
 ::::{grid} 1 2 2 3
 :gutter: 3
 
@@ -48,18 +49,17 @@ Retraining the cellfinder cell classification network in napari
 ::::
 
 ## Specific applications
+
 ::::{grid} 1 2 2 3
 :gutter: 3
 
-
 :::{grid-item-card} {fas}`brain;sd-text-primary` Probe segmentation
 :img-bottom: images/probes.png
 :link: silicon-probe-tracking
 :link-type: doc
 Analysis of silicon probe tracks (e.g. Neuropixels)
 :::
 
-
 :::{grid-item-card} {fas}`brain;sd-text-primary` Bulk tracing analysis
 :img-bottom: images/bulkaxons.png
 :link: tracing-tracking
@@ -69,7 +69,7 @@ Analyze and visualize bulk fluorescence tracing data
 
 :::{grid-item-card} {fas}`brain;sd-text-primary` Cell detection via brainmapper
 :img-bottom: images/cellfinder.png
-:link: brainmapper/index.md
+:link: brainmapper/index
 :link-type: doc
 Whole brain cell detection and registration
 :::
@@ -88,6 +88,5 @@ cellfinder-detection
 cellfinder-retraining
 silicon-probe-tracking
 tracing-tracking
-cellfinder-cli/index
-
+brainmapper/index
 ```