Apply url and typo fixes code review

Co-authored-by: Chang Huan Lo <[email protected]>

README.md

@@ -22,7 +22,7 @@ Python tools for analysing body movements across space and time, to aid the stud
 
 ## Overview
 
-Pose estimation tools, such as [DeepLabCut](http://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) are now commonplace when processing video data of animal behaviour. There is not yet a standardised, easy to use way to process the pose tracks produced from these software packages.
+Pose estimation tools, such as [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) are now commonplace when processing video data of animal behaviour. There is not yet a standardised, easy-to-use way to process the pose tracks produced from these software packages.
 
 movement aims to provide a consistent modular interface to analyse pose tracks, allowing steps such as data cleaning, visualisation and motion quantification.
 We aim to support a range of pose estimation packages, along with 2D or 3D tracking of single or multiple animals.

docs/source/community/mission-scope.md

@@ -7,11 +7,11 @@
 
 ## Scope
 
-At its core, movement handles trajectories of *keypoints*, which are specific body parts of an *individual*. An individual's posture or *pose* is represented by a set of keypoint coordinates, given in 2D (x,y) or 3D (x,y,z). The sequential collection of poses over time forms *pose tracks*. In neuroscience, these tracks are typically extracted from video data using software like [DeepLabCut](http://www.mackenziemathislab.org/deeplabcut) or [SLEAP](https://sleap.ai/).
+At its core, movement handles trajectories of *keypoints*, which are specific body parts of an *individual*. An individual's posture or *pose* is represented by a set of keypoint coordinates, given in 2D (x,y) or 3D (x,y,z). The sequential collection of poses over time forms *pose tracks*. In neuroscience, these tracks are typically extracted from video data using software like [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut) or [SLEAP](https://sleap.ai/).
 
 With movement, our vision is to present a **consistent interface for pose tracks** and to **analyze them using modular and accessible tools**. We aim to accommodate data from a range of pose estimation packages, in **2D or 3D**, tracking **single or multiple individuals**. The focus will be on providing functionalities for data cleaning, visualisation and motion quantification (see the [Roadmap](target-roadmap) for details).
 
-While movement isn't designed for behaviour classification or action segmentation, it may extract features useful for these tasks. We are planning to develop separate packages for this purpose, which will be compatible with movement and the existing ecosystem of related tools.
+While movement is not designed for behaviour classification or action segmentation, it may extract features useful for these tasks. We are planning to develop separate packages for this purpose, which will be compatible with movement and the existing ecosystem of related tools.
 
 ## Design principles
 
@@ -24,4 +24,4 @@ movement is committed to:
 - __Performance and responsiveness__, especially for large datasets, using parallel processing where appropriate.
 - __Modularity and flexibility__. We envision movement as a platform for new tools and analyses, offering users the building blocks to craft their own workflows.
 
-Some of these principles are shared with, and were inspired by, napari's [Mission and Values](https://napari.org/mission.html) statement.
+Some of these principles are shared with, and were inspired by, napari's [Mission and Values](https://napari.org/stable/community/mission_and_values.html) statement.

docs/source/community/roadmap.md

@@ -3,7 +3,7 @@
 
 The roadmap outlines **current development priorities** and aims to **guide core developers** and to **encourage community contributions**. It is a living document and will be updated as the project evolves.
 
-The roadmap is **not meant to limit** movement features, as we're open to suggestions and contributions. Join our [Zulip chat](https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement/topic/Welcome!) to share your ideas. We'll take community demand and feedback into account when planning future releases.
+The roadmap is **not meant to limit** movement features, as we are open to suggestions and contributions. Join our [Zulip chat](https://neuroinformatics.zulipchat.com/#narrow/stream/406001-Movement/topic/Welcome!) to share your ideas. We will take community demand and feedback into account when planning future releases.
 
 ## Long-term vision
 The following features are being considered for the first stable version `v1.0`.
@@ -19,7 +19,7 @@ The following features are being considered for the first stable version `v1.0`.
 ## Short-term milestone - `v0.1`
 We plan to release version `v0.1` of movement in early 2024, providing a minimal set of features to demonstrate the project's potential and to gather feedback from users. At minimum, it should include the following features:
 
-- Importing pose tracks from [DeepLabCut](http://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) into a common `xarray.Dataset` structure. This has been largely accomplished, but some remaining work is required to handle special cases.
+- Importing pose tracks from [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) into a common `xarray.Dataset` structure. This has been largely accomplished, but some remaining work is required to handle special cases.
 - Visualisation of pose tracks using [napari](https://napari.org/). We aim to represent pose tracks via the [napari tracks layer](https://napari.org/stable/howtos/layers/tracks.html) and overlay them on a video frame. This should be accompanied by a minimal GUI widget to allow selection of a subset of the tracks to plot. This line of work is still in a pilot phase. We may decide to use a different visualisation framework if we encounter roadblocks.
 - At least one function for cleaning the pose tracks. Once the first one is in place, it can serve as a template for others.
 - Computing velocity and acceleration from pose tracks. Again, this should serve as a template for other kinematic variables.

docs/source/index.md

@@ -29,7 +29,7 @@ Get in touch and contribute.
 
 ## Overview
 
-Pose estimation tools, such as [DeepLabCut](http://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) are now commonplace when processing video data of animal behaviour. There is not yet a standardised, easy to use way to process the *pose tracks* produced from these software packages.
+Pose estimation tools, such as [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut) and [SLEAP](https://sleap.ai/) are now commonplace when processing video data of animal behaviour. There is not yet a standardised, easy-to-use way to process the *pose tracks* produced from these software packages.
 
 movement aims to provide a consistent modular interface to analyse pose tracks, allowing steps such as data cleaning, visualisation and motion quantification.
 We aim to support a range of pose estimation packages, along with 2D or 3D tracking of single or multiple animals.

docs/source/snippets/status-warning.md

@@ -1,6 +1,6 @@
 :::{admonition} Status
 :class: warning
 - 🏗️ The package is currently in early development. Stay tuned ⌛
-- It is not sufficiently tested to be used for scientific analysis
-- The interface is subject to changes
+- It is not sufficiently tested to be used for scientific analysis.
+- The interface is subject to changes.
 :::