Improve landing page (#66)

* Improve landing page

- Simplify presentation
- Remove warning as first thing you see
- Tell people why we target bonsai

* Address some review comments

* Minor updates after merging

* Remove breadcrumb attribute

Co-authored-by: cjsha <cs@open-ephys.org>
Co-authored-by: bparks13 <bap@open-ephys.org>

docfx.json

@@ -59,7 +59,8 @@
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       "markdigExtensions": [
         "attributes",
-        "customcontainers"
+        "customcontainers",
+        "footnotes"
       ],
       "alerts": {
         "TODO": "alert alert-secondary"

index.md

@@ -1,33 +1,97 @@
 ---
 uid: index
 title: OpenEphys.Onix1
-_disableBreadcrumb: true
 ---
 
-> [!Warning]
-> These docs are under active development, feel free to contribute by either [raising an issue](https://github.com/bonsai-rx/docs/issues) or following the links saying **Edit this page**.
+`OpenEphys.Onix1` is a [Bonsai](https://bonsai-rx.org/) library that can be used to control the [ONIX PCIe Acquisition System](https://open-ephys.org/onix/oeps-9006), which provides:
 
-`OpenEphys.Onix1` is a library that can be used in [Bonsai](https://bonsai-rx.org/) to acquire data from ONIX devices, such as the [ONIX PCIe Acquisition System](https://open-ephys.org/onix/oeps-9006). For more details on the ONI specification, check out [this link](https://open-ephys.github.io/ONI/), and to learn more about ONIX devices and their implementation of ONI, click [here](https://open-ephys.github.io/onix-docs/).
+* Support for a variety of tools such as [Neuropixels (all
+  variants)](https://www.neuropixels.org/),
+  [Miniscopes](https://open-ephys.org/miniscope-v4/miniscope-v4), [Intan-based
+  headstages](https://open-ephys.org/onix/oeps-7741), and more
+* Automatic hardware synchronization of all data streams.
+* Torque-free commutation of ultra-thin (down to ~0.2mm diameter) tethers
+* High performance closed-loop control (100 usec feedback loop times)
 
-## Advantages
-
-While data can be acquired using programs other than Bonsai, there are a number of advantages that come from building `OpenEphys.Onix1` as a Bonsai library. A major advantage is that it maintains maximal compatibility with open source programs, including [OpenCV](https://opencv.org/), [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut), and many more.
+<br>
+<div class="quick-links">
 
-Other major advantages include:
-* Visual interface provided by building on top of Bonsai's foundation
-* Time-stamped synchronization across multiple devices
-* Combine data streams for real-time processing
+| <xref:getting-started> | [Operator Reference](xref:OpenEphys.Onix1) | <xref:tutorials> | [Hardware Guide](https://open-ephys.github.io/onix-docs/) |
+|:----:|:----:|:----:|:----:|
+| [![User Guide](images/running.svg){width=150}](xref:getting-started) | [![Operator Reference](images/books.svg){width=150}](xref:OpenEphys.Onix1) | [![Tutorials](images/beaker.svg){width=150}](xref:tutorials) |[![Tutorials](images/screwdriver.svg){width=150}](https://open-ephys.github.io/onix-docs/)|
 
+</div>
 <br>
 
-### Quick Links
-<br>
+### Why Bonsai?
+
+ONIX is built on the [ONI standard](https://open-ephys.github.io/ONI/), which is software
+agnostic. Bonsai is the first software target pursued by the Open Ephys team for
+ONIX hardware. There are three major reasons for this:
+
+1. **Performance.** ONIX is a universal interface for neural recording instruments. It can
+   capture data produced by neural probes, cameras, high-speed ADCs, etc. In
+   general terms, ONIX can capture data from arbitrary mixtures of
+   asynchronous[^1] data sources. Bonsai provides an extremely powerful,
+   open-source software platform for elegantly collecting, combining, and
+   processing data from essentially any data source regardless of its sample
+   rate, sample regularity, packet size, and bandwidth. Bonsai accomplishes this
+   task in a fundamental manner: it explicitly models each data source as an
+   ordered temporal sequence with a start and end called an
+   [Observable](https://reactivex.io/documentation/observable.html). This is
+   analogous to how, for instance,
+   [Numpy](https://numpy.org/doc/stable/index.html) explicitly models fixed-size
+   multi-dimensional arrays as
+   [ndarrays](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray).
+   And, just like Numpy offers an extensive linear algebra toolkit
+   to operate on these arrays, Bonsai offers an analogous
+   [toolkit](https://reactivex.io/documentation/operators.html)
+   for operating on temporal sequences of data. Because Bonsai was created around this core
+   data model and operator library, it makes capturing, processing, and combining data
+   sequences from different hardware sources natural in Bonsai, whereas it is
+   bug prone and difficult in other software options.
+1. **Code quality.** Open Ephys has been developing open source hardware and
+   software for the Neuroscience community for over a decade. In terms of code
+   quality, Bonsai is excellent. Bonsai uses a modern language and build system,
+   has integrated package management, and an extremely clean, featureful, and well
+   maintained API. Given that Bonsai's development model perfectly aligns with our
+   values, we are very proud to be able to contribute to its growth in the
+   Neuroscience community.
+1. **Third party integration.** Bonsai provides support for
+   hundreds of pieces of open- and closed-source hardware and software that are
+   used extensively in neuroscience research. For instance:
+
+    - The classic Open Ephys [acquisition system](https://open-ephys.org/acquisition-system)
+    - [Ucla Miniscope ecosystem](https://open-ephys.github.io/miniscope-docs/index.html)
+    - [National Instruments](https://bonsai-rx.org/daqmx/articles/intro.html) acquisition boards
+    - Virtually every machine-vision and sCMOS camera[^2]
+    - [Sanworks Bpod](https://sanworks.github.io/Bpod_Wiki/)
+    - [Harp](https://harp-tech.org/index.html)
+    - [Deeplabcut](https://github.com/bonsai-rx/deeplabcut) & [Sleap](https://github.com/bonsai-rx/sleap)
+    - And much more
+
+   By targeting Bonsai, ONIX can be used seamlessly with these third party tools.
+
+> [!NOTE]
+> We put a lot of effort into
+> making these docs useful for everyone. If you have suggestions for making
+> them even better, please contribute by either [raising an
+> issue](https://github.com/bonsai-rx/docs/issues) or following the links saying
+> **Edit this page**. We welcome all constructive feedback. As always, our goals
+> are better performing tools, less redundant development, and more reproducible
+> science.
+>
+> In addition to this library, we are currently developing ONIX support for the
+[Open Ephys GUI](https://open-ephys.org/gui/). 
 
-<div class="quick-links">
 
-| <xref:getting-started> | <xref:OpenEphys.Onix1> | <xref:tutorials> |
-|:--------------:|:-------------------:|:---------:|
-| [![User Guide](images/macbook.svg){width=200}](xref:getting-started) | [![Operator Guide](images/books.svg){width=200}](xref:OpenEphys.Onix1) | [![Tutorials](images/running.svg){width=200}](xref:tutorials) |
-| [New to Bonsai or <br>OpenEphys.Onix? Start here!](xref:getting-started) | [Operator references here](xref:OpenEphys.Onix1) | [Check out our tutorials <br>for useful workflows](xref:tutorials) |
+[^1]: Although physical data sources are asynchronous (e.g. a Neuropixels probe
+runs on a distinct clock and produces data at a distinct rate compared to the
+camera sensor on a Miniscope), all data is hardware-timestamped on a common
+clock. No post-hoc data alignment is required.
 
-</div>
+[^2]: [Flir](https://github.com/bonsai-rx/spinnaker), [Allied
+Vision](https://github.com/bonsai-rx/vimba),
+[Ximea](https://github.com/bonsai-rx/ximea),
+[Basler](https://github.com/bonsai-rx/pylon),
+[Excelitas](https://github.com/bonsai-rx/pco), etc.