As discussed in the discord. lb-in^2 is the common imperial MOI unit,
e.g. Onshape uses it.
Also, improved the Java docstring for `KilogramMetersSquaredPerSecond`
to explain what it represents.
---------
Co-authored-by: Benjamin Hall <bhall@ctr-electronics.com>
The initial build file generation for robotpy projects was relatively
naive and purpose built to get `allwpilib` compiling, without supporting
all the available features.
This modifies the generation scripts to be able to support multiple
embedded libraries, which will be necessary for #8858, since `mrclib.so`
will need to be bundled along with the hal libraries. In addition some
cleanup was done to get the wheels looking more like what is in pypi.
This lets us remove the unmaintained StackWalker library and its hacky
upstream_utils script.
@Gold856 reported that StackWalker gives blank stacktraces:
https://discord.com/channels/176186766946992128/368993897495527424/1261940029287301150.
They also reported an earlier version of this PR giving the following
stacktrace instead:
```
D:\allwpilib\developerRobot\src\main\native\cpp\Robot.cpp(18): developerRobotCpp!Robot::RobotInit+0xB6
D:\allwpilib\wpilibc\src\main\native\cpp\TimedRobot.cpp(22): wpilibcd!frc::TimedRobot::StartCompetition+0x4F
D:\allwpilib\wpilibc\src\main\native\include\frc\RobotBase.h(36): developerRobotCpp!frc::impl::RunRobot<Robot>+0xC8
D:\allwpilib\wpilibc\src\main\native\include\frc\RobotBase.h(106): developerRobotCpp!frc::StartRobot<Robot>+0x17E
D:\allwpilib\developerRobot\src\main\native\cpp\Robot.cpp(60): developerRobotCpp!main+0xB
D:\a\_work\1\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl(79): developerRobotCpp!invoke_main+0x39
D:\a\_work\1\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl(288): developerRobotCpp!__scrt_common_main_seh+0x132
D:\a\_work\1\s\src\vctools\crt\vcstartup\src\startup\exe_common.inl(331): developerRobotCpp!__scrt_common_main+0xE
D:\a\_work\1\s\src\vctools\crt\vcstartup\src\startup\exe_main.cpp(17): developerRobotCpp!mainCRTStartup+0xE
KERNEL32!BaseThreadInitThunk+0x1D
ntdll!RtlUserThreadStart+0x28
```
People generally have expressed a dislike for the Hungarian notation
used in member variables, especially in examples/templates, and our
styleguide shouldn't be forced on downstream consumers, so this removes
all Hungarian notation from the examples/templates.
There are _some_ benefits to Hungarian for private member variables
(like knowing what's a member vs. local in a PR review) so we'll keep
private member variables the same for now, but public variables should
no longer use Hungarian notation, since it looks much worse. A new PMD
XPath rule has been added to accomplish this goal. Some other
non-compliant variables were fixed for the new rule.
There were complaints about no patch files being created from CI when
the examples pre-gen fails for people who don't build with bazel. This
adds a new action step to run just the non-robotpy pregen.
I also added an argument to the diff tests to make it a unified diff,
which might make it easier to hand fix.
Part of the `semiwrap` process that hasn't been ported over yet is
generating pyi stubs. It is possible to not have your semiwrap setup
correctly and "leak" native types into the generated python docstrings,
which causes the process to
[fail](https://github.com/pjreiniger/mostrobotpy/actions/runs/24618640845/job/71985311682#step:12:3652).
semiwrap also has a tool you can run, 'create-imports' that will read
the symbols from a build pybind library and automatically create and
sort the imports in the `__init__.py` file. This step is not enforced by
CI, which is why it hasn't been failing in `mostrobotpy` land.
This PR fixes the stubgen problems and runs reorganizes the imports. I
will have a follow up PR that can bring these automatically into the
build system after this lands. I'd do a fancy new `gh stack` but I can't
figure out if it works on forks.
Originally started with just swerve, but expanded to diff and mecanum
(docs only) for parity across the drivetrains. Return value checks are
applied when possible to make migration easier and to error loudly if
people forget.
---------
Co-authored-by: Joseph Eng <91924258+KangarooKoala@users.noreply.github.com>
Jackson is a very heavy library; it supports loads of features that we
don't need, and historically has caused issues due to long class loading
times (a little over 2 seconds to load AprilTagFieldLayout). This often
manifests as a help request in the form of "my robot disables when I do
X, but doesn't disable when doing X in subsequent attempts until code
restart." While SC has brought down Jackson loading times significantly,
with AprilTagFieldLayout loads taking only 330 milliseconds, that's
still a rather long delay, and while libraries should handle any JSON
loading ahead of time to prevent delays in auto/teleop, it would still
be good to make the worst case better to reduce user frustration.
Benchmarks indicate using [Avaje
Jsonb](https://github.com/avaje/avaje-jsonb) to load AprilTagFieldLayout
only takes ~70 ms, a fair chunk of which isn't actually in Avaje Jsonb
(~4 ms is spent on using getResourceAsStream to retrieve the JSON file,
~8 ms is spent on just loading the AprilTag class and its dependencies).
Note that all times listed are end-to-end, meaning nothing else was done
except for the operation being benchmarked, and doing arithmetic on them
can be flawed due to some classes being loaded twice, i.e.,
getResourceAsStream and `new AprilTag()` likely load some of the same
JDK classes and so subtracting both from the Avaje Jsonb load time is
likely slightly incorrect because class loading is being double counted.
For our purposes, it's likely accurate enough and is mostly just for
contextualization.
Benchmarks were run on a Raspberry Pi CM5 with 2 GB of RAM. Source code
for the
[results](https://github.com/user-attachments/files/26471452/benchmark.txt)
can be found in the "Fastjson2" commit
(2456d15ca8ebd17635e607cd40bf8816e77869a1).
Avaje Jsonb uses code generation via annotation processors to generate
the classes needed to do JSON serde and uses service providers to find
them, which will require downstream changes in robot projects, as the
different service providers in each library must be merged together for
Avaje Jsonb to function. We will use the Gradle shadow plugin, as its
already used by the installer and therefore adds zero additional
dependencies.
There's changes to the diagnostic output and a performance improvement
for autodiff setup. I also updated Java's Options docs to more closely
match upstream.
The wrapper includes reverse mode autodiff, the Problem DSL, and the
optimal control problem API. I wrote it by directly translating the
upstream
[API](https://github.com/SleipnirGroup/Sleipnir/tree/main/include/sleipnir)
and [tests](https://github.com/SleipnirGroup/Sleipnir/tree/main/test) to
Java (i.e., copy-paste-modify).
I replaced the ArmFeedforward and Ellipse2d JNIs with implementations
using the Sleipnir Java bindings. Switching dev binary JNIs to release
by default sped up wpimath test runs from several minutes to 7 seconds.
- Remove status return from HAL level (clock getting should never fail)
- Remove 32-bit timestamp expand function
- Make monotonic_clock.hpp (formerly fpga_clock.hpp) header-only and
move to root hal include directory
I left "free speed" alone since that's the technical term for it. In
general, velocity is a vector quantity, and speed is a magnitude (i.e.,
a strictly positive value).
This PR also replaces the speed verbiage in MotorController with duty
cycle.
Fixes#8423.
This hooks up the bazel build to the robotpyExamples. It can use the
(formly pyfrc or whatever) automatic unit tests for an example, as well
as exposing the ability to run the example in simulation, with or
without `halsim_gui` with a command such as `bazel run
//robotpyExamples:AddressableLED-sim`
This required building and using wheels instead of just a normal
`py_library`, so that things like `ENTRY_POINTS` can be used. I took a
bare bones approach to building and naming the wheels (for example the
native ones don't have the OS info or python version in them, so they
wouldn't be suitable publish to pypi, but that can always be updated
later.
Avoids boxing to reduce allocations, combines for loops as an
optimization, and removes massive switch statement because Java's
generics are type erased, so the different type parameters make no
difference.
Also fixes the google compile-testing library to 0.23.0 (the latest
available at time of writing) instead of a wildcard
Jackson versions were inconsistent across projects; most were on 2.19.2,
but the fields subproject was on 2.15.2. All projects are now on 2.19.2
for consistency
In C++, we use a diagonal matrix to avoid an expensive matrix
multiplication. EJML doesn't have a diagonal matrix type, so in Java, we
use a double array and implement the multiplication manually.
Add a simple tap counting filter for boolean streams.
The filter activates when the input has risen (transitioned from false
to true, like when a button is tapped) the required number of times
within the time window after the first rising edge. Once activated, the
output remains true as long as the input is true. The tap count resets
when the time window expires or when the input goes false after
activation.
Example usage:
```java
xbox.a()
.multiPress(2, 0.2) // Detect a double tap within 0.2 seconds
.onTrue(Commands.print("Double tapped A button"));
xbox.y()
.multiPress(2, 0.5) // Detect a double tap within 0.5 seconds
.whileTrue(Commands.print("Y held after tap").repeatedly());
```
This is not a noise reduction and/or input smoothing filter, but it is
similar in usage to debounce, so I believe it could be considered a
filter, but am open to a better location.
I believe this would be a useful addition, as double/triple tapping a
button is a common control option in games, yet is not often utilized by
newer FRC teams. I believe adding it to WPILib in a standard way will
allow more teams to make the most out of their controls.
Documents the extrinsic vs intrinsic semantics of `plus()` and
`minus()`. (`rotateBy()` was documented in [a previous
PR](https://github.com/wpilibsuite/allwpilib/pull/5508))
Fixes usage of `plus()` and `minus()` in `Rotation3d.interpolate()`.
(Fixes#8523)
Fixes incorrect usages of `plus()`, `minus()`, and `rotateBy()`
throughout `Odometry3d`.
Adds explanatory comments for some `plus()`, `minus()`, and `rotateBy()`
operations.
Fixes `TimeInterpolatableBuffer` not using twists for `Pose3d` (this was
just because I happened to notice it, it isn't really related to the PR)
To check all of our usages of `plus()`, `minus()`, and `rotateBy()`, I
marked them as deprecated, checked compile errors from `./gradlew
compileJava`, and then undeprecated them. You can see all of the spots
that showed up (at least on the Java side) by viewing the diff for
241109c.
I wanted to present this alternative to #8526 because the change has its
own quirks, there's little time before kickoff, and there would be no
code-side warning to teams (and mentors) already used to the current
behavior.
Used Gemini to convert the C++ tests in wpimath/.../kinematics to
pytest. For ease of use required a better constructor for
`MecanumDriveWheelPositions`
I did this conversion months ago (before robotpy landed and before the
reorg), so new tests might be missing. At least its better than nothing
🤷
Broke the huge pr that does almost everything into parts so its easier
to review.
---------
Co-authored-by: David Vo <auscompgeek@users.noreply.github.com>
