-Python- | 链家网深圳所有租房信息爬取 -

https://docs.python.org/3/library/math.html

The math module consists mostly of thin wrappers around the platform C math library functions.

While python itself can only execute a single instruction at a time, a low level c function that is called by python does not have this limitation.
So it's not python that is using multiple cores but your system's well optimized math library that is wrapped by python's math module.

That basically answers both your questions.

Regarding the usefulness of multiprocessing: It is still useful for those cases, where you're trying to parallelize pure python code or code that does not call libraries that already use multiple cores. However, it comes with inter process communication (IPC) overhead that may or may not be larger than the performance gain that you get from using multiple cores. Tuning IPC is therefore often crucial for multiprocessing in python.

This is an error in Arelle, which shows up for Python 3.6 and later. There is a pull request for it , but that is still open (since July 2017). Given that Python 3.6 has been out for quite a while, I don't know why this hasn't been fixed.

You are using the lxml branch, which has been stale for 10 years. So perhaps this error has actually been fixed (even if the pull request is still open) on the master brach, but not on the lxml branch. Try installing from master first, if that is an option for you.

You have to calculate the movement per frame depending on the frame rate.

pygame.time.Clock.tick returns the number of milliseconds since the last call. When you call it in the application loop, this is the number of milliseconds that have passed since the last frame. When you call it without a parameter (framerate=0), the FPS are unlimited.

Define the distance in pixels that the player should move per second (move_per_second). Then compute the distance per frame in the application loop:

It seems that there is a bug in readline (which is used by Homebrew to install Python)

Short answer:

We can try findall then explode

You will have to vendor the dependency. The easiest way to do that is to include the dependency inside your python package, not outside.

setuptools requires you to include a MANIFEST.in file to include non-package, non-python files in your distribution.

See this project for an example of how to do that.

Your project structure should look something like this:

Using answer of @Charles Duffy you can make older versions run on M1s. However Python versions before 3.8 will NOT be officially supported on M1 because they were not in bug-fix phase when M1 chips were released. It is stated clearly here as:

">Are there plans to backport PR 22855 to any branches older than 3.9?

The plan is to also support 3.8 on Big Sur and Apple Silicon as 3.8 is still in bugfix mode. There are no plans to backport support to 3.7 and 3.6 which are in the security-fix-only phase of their release cycles."

in this python bug tracker.

So I don't think there is any way to get them working on M1 unless someone tweaks python on their own.

Go to the main section of the GitHub repository: https://github.com/codingforentrepreneurs/OpenCV-Python-Series

1. Press the code button and then download as zip.
2. Unzip the file in your downloads.
3. Navigate to src/recognisers and the file face-trainner.yml should be there.
4. Use that file how you want in your project (discard of the rest if you have no need for it).

Also make sure that you have typed the correct file name in your program with the two 'n's (face-trainner.yml not face-trainer.yml)

Restating the problem - My understanding given the different comments and your updates is the following:

• someone other than you is in possession of data, which as it happens is 2D data, i.e. an Nx2 matrix;
• using the covariance matrix, they are effectively saying something about the joint distribution of these two dimensions, specifically about the variance;
• if they assume a Gaussian distribution, as is implied by your comment regarding 68%, 95% and 99.7% for 1sigma, 2sigma and 3sigma, they can draw ellipses which represent the 2D-normal distribution: these are in fact some of the contour lines associated with the 3D "bell" surface;
• you have obtained the contour lines in a graph and are trying to obtain the covariance matrix (not the original data...);
• you are concerned about the complexity of having to extract the information from each ellipsis.

Partial answer:

• It is impossible to recover the original data, I hope you are already aware of that, but in case you are not let's just note that the covariance matrix is a summary statistic of the data, much like the average, and although it says something about the data many different datasets could happen to have the same summary statistic (the same way many different sets of numbers can give you an average of 10).
• It is possible to somewhat recover the covariance matrix, i.e. the 3 numbers a, b and c in the matrix [a,b;b,c], though the error in doing so will likely be large because of how imprecise the pixel representation is. Essentially, you will be looking for the dimensions of the two axes, for the variances, as well as the angle of one of the axes, for the covariance.
• Unless I am mistaken, under the Gaussian assumption above, you only need to measure this for one of the three ellipses, and then factor by whatever number of sigmas that contour represents. Here you might want to either use the best-defined ellipse, or attempt to use the largest one, which will provide the maximum precision for your measurements (cf. pixelization).
• Also, the problem of finding the axes and angle for the ellipse need not be as complex as what it seems like in your first trials: instead of trying to find the contour of the ellipses, find the bounding rectangle.
• In order to further simplify this process, if your images are color-coded the way you show, then a filter on blue pixels might be enough in terms of image processing. Then simply take the minimum and maximum (x,y) coordinates in order to obtain the bounding rectangle.
• Once the bounding rectangle is obtained, find the equation to your ellipse (that's a question for a math group, but you could start here for example).

Happy filtering!