Polar | Audio engine for CUDA processing | GPU library

by sgmackie C++ Version: Current License: No License

X-Ray Key Features Code Snippets(2)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Polar Summary

Polar is a C++ library typically used in Hardware, GPU applications. Polar has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Audio engine for CUDA processing (Windows/Linux)

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Quality

Security

License

Reuse

Support

Polar has a low active ecosystem.

It has 7 star(s) with 2 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

Polar has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Polar is current.

Quality

Polar has no bugs reported.

Security

Polar has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Polar does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Polar releases are not available. You will need to build from source code and install.

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Polar Key Features

No Key Features are available at this moment for Polar.

Polar Examples and Code Snippets

title: Convert function to variadic tags: function,array expertise: intermediate cover: blog_images/polar-bear.jpg firstSeen: 2017-12-22T05:08:36+02:00 lastUpdated: 2021-06-13T13:50:25+03:00

npm

Lines of Code : 6

License : No License

Copy

const collectInto = fn => (...args) => fn(args);


const Pall = collectInto(Promise.all.bind(Promise));
let p1 = Promise.resolve(1);
let p2 = Promise.resolve(2);
let p3 = new Promise(resolve => setTimeout(resolve, 2000, 3));
Pall(p1, p2, p3)

Return polar force vectors .

python

Lines of Code : 21

License : Permissive (MIT License)

Copy

def polar_force(
    magnitude: float, angle: float, radian_mode: bool = False
) -> list[float]:
    """
    Resolves force along rectangular components.
    (force, angle) => (force_x, force_y)
    >>> import math
    >>> for

Community Discussions

Trending Discussions on Polar

Circular histogram with fitted Von Mises Distribution

Apply function to all columns of a Polars-DataFrame

Why changing where statement to a variable cause query to be 4 times slower

Arrow IPC vs Feather

How to zoom into a specific latitude in cartopy.crs.Orthographic?

Strange problem with multiple polar plots in matplotlib

(ValueError: Columns must be same length as key) from sentiment analysis

Python Plotly Polar Chart Slice Alignment

recomend the way to write a monitor in UVM with defferent event polarity

Rounding to three decimals in Python

QUESTION

Circular histogram with fitted Von Mises Distribution

Asked 2021-Jun-13 at 15:13

For the past days I've been trying to plot circular data with python, by constructing a circular histogram ranging from 0 to 2pi and fitting a Von Mises Distribution. What I really want to achieve is this:

Directional data with fitted Von-Mises Distribution. This plot was constructed with Matplotlib, Scipy and Numpy and can be found at: http://jpktd.blogspot.com/2012/11/polar-histogram.html

This plot was produced using R, but gives the idea of what I want to plot. It can be found here: https://www.zeileis.org/news/circtree/

WHAT I HAVE DONE SO FAR:

...

ANSWER

Answered 2021-Apr-27 at 15:36

This is what I achieved:

I'm not entirely sure if you wanted x to range from [-pi,pi] or [0,2pi]. If you want the range [0,2pi] instead, just comment out the lines ax.set_xlim and ax.set_xticks.

Source https://stackoverflow.com/questions/67282865

QUESTION

Apply function to all columns of a Polars-DataFrame

Asked 2021-Jun-11 at 09:30

I know how to apply a function to all columns present in a Pandas-DataFrame. However, I have not figured out yet how to achieve this when using a Polars-DataFrame.

I checked the section from the Polars User Guide devoted to this topic, but I have not find the answer. Here I attach a code snippet with my unsuccessful attempts.

...

ANSWER

Answered 2021-Jun-11 at 09:30

You can use the expression syntax to select all columns with pl.col("*") and then map the numpy np.log2(..) function over the columns.

Source https://stackoverflow.com/questions/67834912

QUESTION

Why changing where statement to a variable cause query to be 4 times slower

Asked 2021-Jun-10 at 02:20

I am inserting data from one table "Tags" from "Recovery" database into another table "Tags" in "R3" database

they all live in my laptop similar SQL Server instance

I have built the insert query and because Recovery..Tags table is around 180M records I decided to break it into smaller sebsets. ( 1 million recs at the time)

Here is my query (Let's call Query A)

...

ANSWER

Answered 2021-Jun-10 at 00:06

The reason the first query is so much faster is it went parallel. This means the cardinality estimator knew enough about the data it had to handle, and the query was large enough to tip the threshold for parallel execution. Then, the engine passed chunks of data for different processors to handle individually, then report back and repartition the streams.

With the value as a variable, it effectively becomes a scalar function evaluation, and a query cannot go parallel with a scalar function, because the value has to determined before the cardinality estimator can figure out what to do with it. Therefore, it runs in a single thread, and is slower.

Some sort of looping mechanism might help. Create the included indexes to assist the engine in handling this request. You can probably find a better looping mechanism, since you are familiar with the identity ranges you care about, but this should get you in the right direction. Adjust for your needs.

With a loop like this, it commits the changes with each loop, so you aren't locking the table indefinitely.

Source https://stackoverflow.com/questions/67912454

QUESTION

Arrow IPC vs Feather

Asked 2021-Jun-09 at 20:52

What is the difference between Arrow IPC and Feather?

The official documentation says:

Version 2 (V2), the default version, which is exactly represented as the Arrow IPC file format on disk. V2 files support storing all Arrow data types as well as compression with LZ4 or ZSTD. V2 was first made available in Apache Arrow 0.17.0.

While vaex, a pandas alternative, has two different functions, one for Arrow IPC and one for Feather. polars, another pandas alternative, indicate that Arrow IPC and Feather are the same.

...

ANSWER

Answered 2021-Jun-09 at 20:18

TL;DR There is no difference between the Arrow IPC file format and Feather V2.

There's some confusion because of the two versions of Feather, and because of the Arrow IPC file format vs the Arrow IPC stream format.

For the two versions of Feather, see the FAQ entry:

What about the “Feather” file format?

The Feather v1 format was a simplified custom container for writing a subset of the Arrow format to disk prior to the development of the Arrow IPC file format. “Feather version 2” is now exactly the Arrow IPC file format and we have retained the “Feather” name and APIs for backwards compatibility.

So IPC == Feather(V2). Some places refer to Feather mean Feather(V1) which is different from the IPC file format. However, that doesn't seem to be the issue here: Polars and Vaex appear to use Feather to mean Feather(V2) (though Vaex slightly misleadingly says "Feather is exactly represented as the Arrow IPC file format on disk, but also support compression").

Vaex exposes both export_arrow and export_feather. This relates to another point of Arrow, as it defines both an IPC stream format and an IPC file format. They differ in that the file format has a magic string (for file identification) and a footer (to support random access reads) (documentation).

export_feather always writes the IPC file format (==FeatherV2), while export_arrow lets you choose between the IPC file format and the IPC stream format. Looking at where export_feather was added I think the confusion might stem from the PyArrow APIs making it obvious how to enable compression with the Feather API methods (which are a user-friendly convenience) but not with the IPC file writer (which is what export_arrow uses). But ultimately, the format being written is the same.

Source https://stackoverflow.com/questions/67910612

QUESTION

How to zoom into a specific latitude in cartopy.crs.Orthographic?

Asked 2021-Jun-08 at 11:56

I'm unsure if this is possible, but I'm essentially trying to isolate the Arctic circle latitude (60N) in an orthographic map AND maintain the ellipsoid, not have the zoomed in image be a rectangle/square.

Here is what I have:

...

ANSWER

Answered 2021-Jun-08 at 11:56

To get a zoom-in and square extent of an orthographic map, You need to plot some control points (with .scatter, for example) or specify correct extent in projection coordinates (more difficult). Here is the code to try.

Source https://stackoverflow.com/questions/67877552

QUESTION

Strange problem with multiple polar plots in matplotlib

Asked 2021-Jun-07 at 21:04

I've run into a strange issue plotting two ellipses on a single polar plot with matplotlib. Here's my Python code:

...

ANSWER

Answered 2021-Jun-07 at 21:04

I have matplotlib version 3.4.1 and this is my output. Try to update matplotlib

Source https://stackoverflow.com/questions/67878607

QUESTION

(ValueError: Columns must be same length as key) from sentiment analysis

Asked 2021-Jun-06 at 20:52

I have been executing a sentiment analysis, and have returned the positive and negative outcomes to my pd.DataFrame in the following manner.

author Text Sentiment 12323 this is text (0.25, 0.35)

However, when I want to split the sentiment column (which consists of Polarity and Subjectivity), I get the following error:

ValueError: Columns must be same length as key

I have tried multiple approaches:

str.split
str.extract
rounding

With the rounding approach I get an error mentioning the float NaN's could not be multiplied. So I suppose that there is a NaN in there somewhere. However, when I look for NaN's I get this answer:

...

ANSWER

Answered 2021-Jun-06 at 20:52

Edit: changed case from df['sentiment'] to df['Sentiment']

The string methods won't work because it's not a string but a set stored in the cell.

You can do this to create a new column:

Source https://stackoverflow.com/questions/67833669

QUESTION

Python Plotly Polar Chart Slice Alignment

Asked 2021-Jun-03 at 20:43

So what I'm trying to do is create a polar chart using plotly. However, it needs to look similar to a pie chart, where each label is given a slice of the circle. Currently the polar chart works fine, if I divide the circle into equal slices. But, when I try to give them a slice corresponding to the weights it doesn't work out too well, as it tends to overlap or leave spaces between each slice. This is mainly due to the Theta.

Can someone please explain where I've gone wrong?

Ratings - Max value is 5, Min value is 1. This is used to determine the length of the slice in the polar chart.

Weights - Max value is 100, Min value is 1. This is used to determine the width of the slice in the polar chart.

Labels - To identify each slice.

When equally splitting the circle ...

ANSWER

Answered 2021-Jun-03 at 20:43

I think you are assuming that theta sets the location of one edge of a radial sector when it is in fact the center of that radial sector. Here is your code but with a calculation of theta that accounts for this difference:

Source https://stackoverflow.com/questions/67804152

QUESTION

recomend the way to write a monitor in UVM with defferent event polarity

Asked 2021-Jun-03 at 11:14

I am trying to implement a monitor for VDU(Video display unit) and the way the VDU can be programmed says that sync signals have controllable polarity. This means than according to VDU settings monitor should react on @posedge or @negedge event. Is there any way to pass the type (means posesge or negedge) via configuration data base or do something like this. Instead of write if(truth) @posedge else @negedge. And assertion also needs to be controlled this way but assertion at list designed to take event type as an argument but I am no sure config data base calls are allowed inside interface.

...

ANSWER

Answered 2021-Jun-01 at 03:15

You should write your code assuming positive polarity, but feed them through an xor operator.

Source https://stackoverflow.com/questions/67769794

QUESTION

Rounding to three decimals in Python

Asked 2021-May-29 at 03:50

I have an answer to my code question that asks me to round

Part 1: Write a line of code in the cell below that will display the lexicon-based sentiment polarity score for the following sentence: 'Hiking in the mountains is fun and very relaxing.'

Part 2: What is the lexicon-based sentiment polarity score for the sentence 'Hiking in the mountains is fun and very relaxing.' ? Report your answer using three decimals of precision (e.g., 0.321).**

How do I add a rounding function to this in the snippet of code?

...

ANSWER

Answered 2021-May-29 at 03:50

2 ways here:

1: assign the result of get_lexicon_polarity to a variable, then pass the variable to np.round

Source https://stackoverflow.com/questions/67747545

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Polar

You can download it from GitHub.

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