spellcheck

Author: Tom-Willemsen

.github/workflows/documentation.yml

@@ -3,6 +3,19 @@ name: sphinx
 on: [push, pull_request, workflow_call]
 
 jobs:
+  spellcheck:
+    runs-on: "windows-latest"
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.13"
+      - name: install requirements
+        run: pip install -e .[dev]
+      - name: run spellcheck
+        run: sphinx-build -E -a -W --keep-going -b spelling doc _build
   call_sphinx_builder:
     uses: ISISComputingGroup/reusable-workflows/.github/workflows/sphinx.yml@main
     secrets: inherit

README.md

@@ -8,5 +8,5 @@ Core bluesky plan stubs & devices for use at ISIS.
 | [CI (nightly)](https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/lint-and-test-nightly.yml)                    | [<img src="https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/lint-and-test-nightly.yml/badge.svg">](https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/lint-and-test-nightly.yml) |
 | [CI (`bluesky` & `ophyd-async` main)](https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/test-against-main.yml) | [<img src="https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/test-against-main.yml/badge.svg">](https://github.com/ISISComputingGroup/ibex_bluesky_core/actions/workflows/test-against-main.yml)         |
 | [PyPI](https://pypi.org/project/ibex-bluesky-core/)                                                                                    | ![PyPI - Version](https://img.shields.io/pypi/v/ibex_bluesky_core)                                                                                                                                                               |
-| [Github](https://github.com/ISISComputingGroup/ibex_bluesky_core)                                                                      | ![GitHub Release](https://img.shields.io/github/v/release/IsisComputingGroup/ibex_bluesky_core)                                                                                                                                  |
+| [GitHub](https://github.com/ISISComputingGroup/ibex_bluesky_core)                                                                      | ![GitHub Release](https://img.shields.io/github/v/release/IsisComputingGroup/ibex_bluesky_core)                                                                                                                                  |
 | [License](https://github.com/ISISComputingGroup/ibex_bluesky_core/blob/main/LICENSE)                                                   | ![GitHub License](https://img.shields.io/github/license/ISISComputingGroup/ibex_bluesky_core)                                                                                                                                    |

doc/architectural_decisions/005-variance-addition.md

@@ -6,8 +6,8 @@ Current
 
 ## Context
 
-For counts data, the uncertainty on counts is typically defined by poisson counting statistics, i.e. the standard
-deviation on `N` counts is `sqrt(N)`.
+For counts data, the uncertainty on counts is typically defined by Poisson counting statistics, i.e. the standard
+deviation on {math}`N` counts is {math}`\sqrt{N}`.
 
 This can be problematic in cases where zero counts have been collected, as the standard deviation will then be zero,
 which will subsequently lead to "infinite" point weightings in downstream fitting routines for example.
@@ -24,17 +24,17 @@ Use a standard deviation of `NaN` for points with zero counts.
 
 ### Option C
 
-Define the standard deviation of `N` counts as `1` if counts are zero, otherwise `sqrt(N)`. This is one of the
+Define the standard deviation of {math}`N` counts as {math}`1` if counts are zero, otherwise {math}`\sqrt{N}`. This is one of the
 approaches [available in mantid](https://github.com/mantidproject/mantid/blob/bbbb86edc2c3fa554499770463aa25c2b46984e5/docs/source/algorithms/SetUncertainties-v1.rst#L16) for example.
 
 ### Option D
 
-Define the standard deviation of `N` counts as `sqrt(N+0.5)` unconditionally - on the basis that "half a count" is 
+Define the standard deviation of {math}`N` counts as {math}`\sqrt{N+0.5}` unconditionally - on the basis that "half a count" is 
 smaller than the smallest possible actual measurement which can be taken.
 
 ### Option E
 
-No special handling, calculate std. dev. as `sqrt(N)`.
+No special handling, calculate std. dev. as {math}`\sqrt{N}`.
 
 ---
 

doc/architectural_decisions/006-where-to-put-code.md

@@ -34,7 +34,7 @@ Examples of devices and where we would put them under this model:
 Examples of plans and where we would put them under this model:
 ### `ibex_bluesky_core` plans
 - Scanning one block against DAE with a common set of callbacks
-- Optimizing an axis against a readback (e.g. consituent parts of reflectometry auto-align)
+- Optimizing an axis against a readback (e.g. constituent parts of reflectometry auto-align)
 - Very common plans
   - `scan_motor_against_dae`:
     * Always assumes a "motor" - i.e. sets up a block with `use_completion_callback=True` and `use_global_moving_flag=True`

doc/architectural_decisions/008-centre-of-mass.md

@@ -20,4 +20,4 @@ We currently only need to support positive peaks, but in future a toggle could b
 
 This will mean that...
 - Our version of the callback will not be supported by Bluesky and may need changes as Bluesky updates.
-- We can have a version of the callback that is made bespokely for our use cases.
+- We can have a version of the callback that is made specifically for our use cases.

doc/callbacks/file_writing.md

@@ -56,7 +56,7 @@ Optional parameters, not shown above, include:
 The data is prepended on the first event with the names and units of each logged field, and then subsequently the data 
 for each scan separated by a newline. The data is separated by commas, though the metadata is not.
 
-The file also contains metadata such as the bluesky version, plan type, and rb number.
+The file also contains metadata such as the bluesky version, plan type, and RB number.
 
 ## Fit outputs
 

doc/callbacks/fitting/fitting.md

@@ -161,7 +161,7 @@ lf = LiveFit(fit_method, y="y_signal", x="x_signal", update_every=0.5)
 ```
 
 :::{note}
-The parameters returned from the guess function must allocate to the arguments to the model function, ignoring the independant variable e.g `x` in this case. Array-like structures are not allowed. See the {external+lmfit:doc}`parameters` for more information.
+The parameters returned from the guess function must allocate to the arguments to the model function, ignoring the independent variable e.g `x` in this case. Array-like structures are not allowed. See the {external+lmfit:doc}`parameters` for more information.
 :::
 
 Each {py:obj}`~ibex_bluesky_core.fitting.FitMethod` in {py:obj}`ibex_bluesky_core.fitting` has a `.model()` and `.guess()`, which make up their fitting method. These are publicly accessible class methods.
@@ -215,7 +215,7 @@ lf = LiveFit(fit_method, y="y_signal", x="x_signal", update_every=0.5)
 Or you can create a completely user-defined fitting method.
 
 :::{note}
-For fits that require arguments, you will need to pass values to their respecitive `.model` and `.guess` functions. E.g for {py:obj}`~ibex_bluesky_core.fitting.Polynomial` fitting:
+For fits that require arguments, you will need to pass values to their respective `.model` and `.guess` functions. E.g for {py:obj}`~ibex_bluesky_core.fitting.Polynomial` fitting:
 :::
 
 ```python

doc/callbacks/plotting.md

@@ -50,7 +50,7 @@ See [docs for `call_qt_aware`](../plan_stubs/matplotlib_helpers.md) for a descri
 `yield from call_qt_aware` rather than calling `matplotlib` functions directly.
 ```
 
-By providing a signal name to the `yerr` argument you can pass uncertainties to {py:obj}`~ibex_bluesky_core.callbacks.LivePlot`, by not providing anything for this argument means that no errorbars will be drawn. Errorbars are drawn after each point collected, displaying their standard deviation- uncertainty data is collected from Bluesky event documents and errorbars are updated after every new point added.
+By providing a signal name to the `yerr` argument you can pass uncertainties to {py:obj}`~ibex_bluesky_core.callbacks.LivePlot`, by not providing anything for this argument means that no error bars will be drawn. Error bars are drawn after each point collected, displaying their standard deviation - uncertainty data is collected from Bluesky event documents and error bars are updated after every new point added.
 
 The `plot_callback` object can then be subscribed to the run engine, using either:
 - An explicit callback when calling the run engine: `RE(some_plan(), plot_callback)`

doc/conf.py

@@ -80,6 +80,12 @@
 myst_heading_anchors = 7
 autodoc_preserve_defaults = True
 
+spelling_lang = "en_GB"
+spelling_filters = ["enchant.tokenize.MentionFilter"]
+spelling_warning = True
+spelling_show_suggestions = True
+spelling_suggestion_limit = 3
+
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3", None),
     "bluesky": ("https://blueskyproject.io/bluesky/main/", None),

doc/dev/create_a_release.md

@@ -12,10 +12,10 @@ git push origin tag <release.version.number>
 
 This will start a workflow that will check that all linters and tests pass, 
 and then publish a new release with the version number specified in the tag to 
-[Pypi](https://pypi.org/project/ibex-bluesky-core/0.0.1/) and github. The new 
+[PyPI](https://pypi.org/project/ibex-bluesky-core/0.0.1/) and github. The new 
 release can then be installed via `pip install ibex_bluesky_core`. 
 
 The workflow must be approved by someone in the ICP-Write group. To do this go 
 to the action (Actions -> the action on the tag) and approve it.
 
-Credentials for Pypi can be found in keeper.
+Credentials for PyPI can be found in keeper.