empir | open source PHP Windows/Unix tool | Compression library

I have a 3d point cloud. I used matplotlib to draw a scatterplot representing the point cloud viewed from above. The point cloud is stored as a list of coordinates in meters. The output of matplotlib.pyplot.scatter is a png image.

In addition to saving the image, I want to save the correspondence pixels <-> meters. How to do that?

Here the code I use to make my image with matplotlib. I use a dataframe to manipulate the point cloud.

I have data that looks like this:

I am trying to show both cumulative and non-cumulative distributions on the same plot.

Following is a kind of data set I am working on it:

I am looking to make a autocomplete based on index, so each argument has its own autocomplete for example

PROMPT> use stackoverflow

therefore use would have its own autocomplete and so would stackoverflow I know this is possible as empire did it and ive tried things like readline, prompt_toolkit and suggestions?

I currently encounter huge overhead because of NumPy's transpose function. I found this function virtually always run in single-threaded, whatever how large the transposed matrix/array is. I probably need to avoid this huge time cost.

To my understanding, other functions like np.dot or vector increment would run in parallel, if numpy array is large enough. Some element-wise operations seems to be better parallelized in package numexpr, but numexpr probably couldn't handle transpose.

I wish to learn what is the better way to resolve problem. To state this problem in detail,

• Sometimes NumPy runs transpose ultrafast (like B = A.T) because the transposed tensor is not used in calculation or be dumped, and there is no need to really transpose data at this stage. When calling B[:] = A.T, that really do transpose of data.
• I think a parallelized transpose function should be a resolution. The problem is how to implement it.
• Hope the solution does not require packages other than NumPy. ctype binding is acceptable. And hope code is not too difficult to use nor too complicated.
• Tensor transpose is a plus. Though techniques to transpose a matrix could be also utilized in specific tensor transpose problem, I think it could be difficult to write a universal API for tensor transpose. I actually also need to handle tensor transpose, but handling tensors could complicate this stackoverflow problem.
• And if there's possibility to implement parallelized transpose in future, or there's a plan exists? Then there would be no need to implement transpose by myself ;)

Thanks in advance for any suggestions!

Handling a model transpose problem (size of A is ~763MB) on my personal computer in Linux with 4-cores available (400% CPU in total).

I know that this is a relatively simple question, I just can't figure it out. I have three tables: people, presentations, and people_presentations. people and presentations both have ID columns, and people_presentations that has foreign keys to each of people and presentations.

For example:

people:

I have the following empirical equation (engineering):

I need to remove the right icons that are the up and down arrows from a Material UI TextField that I modified from the Material UI documentations (https://material-ui.com/components/autocomplete/#autocomplete) Highlights section.

I tried some solutions from stack overflow like (Remove the arrow and cross that appears for TextField type=“time” material-ui React) and (Remove the arrow and cross that appears for TextField type=“time” material-ui React) but they didn't work and, I ended up with the following code:

App.js: