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Kalman-and-Bayesian-Filters-in-Python
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styleguide
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Set Code Style to "Google Python Style Guide"
Hey, looking for a way to change the default PEP-8 code style to the one of Google. I see that I can set it manually or import the settings, but I've been unable to find a settings file (other than this one for Vim). I also haven't been able to find examples of what a PyCharm-supported settings file would be formatted like, so I can write one myself.
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Google C++ Style Guide Example
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I'm kinda new to Java, and it feels like I'm screaming at a coffee cup every time there's an error.
I use intellij and import Googlecodestyles, modify it a bit to my liking and save that setting. I believe they have one for eclipse also. I believe this it is https://github.com/google/styleguide/blob/gh-pages/eclipse-java-google-style.xml
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How does Apache ShardingSphere standardize and format code? We use Spotless
For latest rules of ShardingSphere, see [shardingsphereeclipseformatter.xml](https://github.com/apache/shardingsphere/blob/master/src/resources/shardingsphere_eclipse_formatter.xml). For references, check the [eclipse-java-google-style.xml](https://github.com/google/styleguide/blob/gh-pages/eclipse-java-google-style.xml) file.
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Would it be possible to get IDE level formatting capabilities? I am not exactly looking for IDEL level customisability. I just need a way to figure out how to use Google Style Guides to format codes while editing.
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Zero Config Code Formatter?
You just need to have the desired Format rules, like https://github.com/google/styleguide/blob/gh-pages/intellij-java-google-style.xml
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NaturalDocs: Plain English Code Documentation
Since it's been around since 2003, I'm curious to know how many projects out there are using it. Would be great if there are some open source examples available as well. I mostly stick to Python, so I'm most familiar with the Google docstring format[1], but seeing as there are other ones[2] as well aren't those usable for other languages too? Seems to be the case of yet another "standard", though since this is such an old project I may out of my depth in saying that.
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[1]: https://github.com/google/styleguide/blob/gh-pages/pyguide.m...
[2]: https://stackoverflow.com/a/24385103
Kalman-and-Bayesian-Filters-in-Python
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The Kalman Filter
A fantastic interactive introduction to Kalman filters can be found on the following repo:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
It explains them from first principles and provides the intuitive rationale for them but doesn't shy away from the math when it feels the student should be ready for it.
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Kalman Filter Explained Simply
No thread on Kalman Filters is complete without a link to this excellent learning resource, a book written as a set of Jupyter notebooks:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
That book mentions alpha-beta filters as sort of a younger sibling to full-blown Kalman filters. I recently had need of something like this at work, and started doing a bunch of reading. Eventually I realized that alpha-beta filters (and the whole Kalman family) is very focused on predicting the near future, whereas what I really needed was just a way to smooth historical data.
So I started reading in that direction, came across "double exponential smoothing" which seemed perfect for my use-case, and as I went into it I realized... it's just the alpha-beta filter again, but now with different names for all the variables :(
I can't help feeling like this entire neighborhood of math rests on a few common fundamental theories, but because different disciplines arrived at the same systems via different approaches, they end up sounding a little different and the commonality is obscured. Something about power series, Euler's number, gradient descent, filters, feedback systems, general system theory... it feels to me like there's a relatively small kernel of intuitive understanding at the heart of all that stuff, which could end up making glorious sense of a lot of mathematics if I could only grasp it.
Somebody help me out, here!
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Recommendations for undergrad to learn optimal state estimation
This provides an excellent intro that jumps right into code. https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python
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A Non-Mathematical Introduction to Kalman Filters for Programmers
If you know a bit of Python and you find it sometimes tough to grind through a textbook, take a look here:
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
Interactive examples programmed in Jupyter notebooks.
- Looking for a study partner to learn kalman filter
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Kalman Filter for Beginners
Thank you, very good resource! Timely too, as I am revising this topic.
My work is mostly in python. I found this interactive book using Jupyter that explains Kalman filters from first principles.
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...
- Starting out with Kalman Filter.
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want to learn kalman filter
Try this book
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kalman filter & c++
https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python And on robotics in general
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Do you use particle/Kalman filters at work?
- Kalman and Bayesian Filters in Python
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