oxc | The first C compiler written in Rust .. | Compiler library
kandi X-RAY | oxc Summary
kandi X-RAY | oxc Summary
A C compiler written in Rust for experimentation and understanding compilers. Should be easy to fork from and work with. Everything is handwritten and the compiler uses no third-party libraries. Please keep in mind, the compiler is currently EXPERIMENTAL, and is NOT PRODUCTION READY. The compiler is roughly following this article.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of oxc
oxc Key Features
oxc Examples and Code Snippets
Lines of Code : 140License : Permissive (MIT)
Copy$ cargo build
...
$ .\target\debug\oxc.exe .\test\stage_7\valid\consecutive_declarations.c
.\test\stage_7\valid\consecutive_declarations.c:
int main() {
int a = 0;
{
int b = 1;
a = b;
}
{
int b = 2;
a = Community Discussions
Trending Discussions on oxc
QUESTION
I am currently trying to deploy my Spring Boot backend on Heroku using the free dyno. I have also connected the backend to MongoDB Atlas for my DB.
During start up of the Spring Boot server I create 2 Java threads to populate 2 different collections within the database simultaneously. This all works locally and I can get the application started on Heroku and can access REST endpoints but I am getting the below error regarding my threads.
2020-11-23T23:03:11.942515+00:00 app[web.1]: [7.521s][warning][os,thread] Failed to start thread - pthread_create failed (EAGAIN) for attributes: stacksize: 512k, guardsize: 0k, detached.
Here is the full Heroku log as well:
...ANSWER
Answered 2020-Nov-24 at 17:58@BeppeC pointed out that this link to Heroku's help forum had an answer for this. Originally I did not have a Procfile, so I added one and it ended up looking like this:
web: java -Dserver.port=$PORT $JAVA_OPTS -Xss2m -jar build/libs/.jar
The command to pay attention to was -Xss2m. This sets the stack size and the default value on the Free, Hobby, or Standard-1X dyno's is 512k, which is lower than the default JVM size of 1MB.
I ended up increasing it to 2MB and this solved my issues with the threads taking up too many resources.
QUESTION
Can I as how to reproduce a plot indicated below using the following code in ggplot2 or any other ploting method? How can I show the data points/samples to reflect group variable and the expression level of the gene "OXC"? Thank you!
...ANSWER
Answered 2020-Sep-20 at 17:13Do you mean something like this? I have used the data you shared. The key is to use the shape aesthetic element in your aes(). It will create shapes instead of common points. After that if you want additional customization, you can use scale_shape_manual() in order to define different shapes. Here somo options for you. The numeric color scale can be also added with color or fill aesthetic elements. Here the code:
QUESTION
Dear fellow stackoverflow users,
I'm a computational chemist and I have a geometry problem. I have a bunch of coordinates that define a molecular surface and I would like to derive the outward normal vectors of this surface. It seems that the surface approximates the properties of a manifold when I look at it, though the coordinate points were not derived using this framework explicitly. I have to make it clear also that in the general case, molecular surfaces are not always convex hull and can have some degree of concavity. What they do not have is discontinuities, the surfaces are smooth by construction. But since I don't know what to do of these mathematical specifications, I tried to devise an algorithm for the general problem.
As a preliminary remark, for each point of the surface, I can determine the position of the nearest atom. So, for each point, I have these xyz coordinates available as well. The algorithm takes the following form:
1. Computing the distance matrix between each of the available points (which scales, unavoidably, to the square of the number of points but it remains reasonable for my cases using numpy)
2. Extracting the two nearest neighbors of each point
3. Use this triplet of points to generate two vectors centered on each point
4. Get the normal vector based on the cross product of these two vectors followed by its normalization
5. Calculate the vector between the point and its underlying atom
6. If this vector makes an angle below 90° with the normal vector, this vector is inwards pointing and thus it is replaced by its opposite
The result of this full procedure is somewhat okay, but there are still various vectors that, when I visually check the result using matplotlib, are somewhat parallel to the surface. Here is the matplotlib result for the water molecule: Here is the molecular surface of water for comparison (where you can find the underlying atoms). Ignore the color coding of the surface, it is color coded by surface charge, which is irrelevant for the present discussion.
This surface is obtained by a third party software from which I have no access to the code. I can only visualize it, and I cannot have access to the smoothing procedures used within it for final rendering.
As the image suggests it, the surface is very smooth and thus I expect the normal vectors to account for this "smoothness", which they do imperfectly. I need the normal vectors to actually reflect the smoothness of the surface because the roughness of the surface depicted by the present normal vectors has a noticeable impact on the quality of my subsequent computations based on these normal vectors. Does anyone has any idea about what I could do, under a reasonable computational time, to fix this issue?
Here is a working code that will reproduce my first figure:
...ANSWER
Answered 2018-Nov-30 at 16:37The "standard" procedure to estimate the normals is, for every point, to find the k nearest neighbors, where k is a small number (ten ?). Then to compute a best plane fit through these points, and to use the normal to the plane.
Unfortunately, a difficulty arises in that the sign of the normal is indeterminate and you need to implement a normal coherence enforcement process. Maybe in your case this is easier as all normals seem to be pointing away from some center point.
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Rust is installed and managed by the rustup tool. Rust has a 6-week rapid release process and supports a great number of platforms, so there are many builds of Rust available at any time. Please refer rust-lang.org for more information.
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