I want to get the wrapped func source file location correctly. Can anyone help? The folder structure look like this, and all the functions in test.py have keyword decorator on it. lib |— keyword.py main |— test.py Keyword.py from functools import wraps def keyword(name=None, tags=(), types=()): def _method_wrapper(func): @wraps(func) def _passargs(self, *args, **kwargs): .. some ..

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I have a even grid with data containing Nans, I want to fill this data with Nan by interpolated values. Before interpolation, I mask out the positions with Nans. The resulted interpolated data still has Nans. How to fix this issue? I use cubic interpolation z data: enter image description here x=np.linspace(0,xmax,num=np.shape(z)[0]) y=np.linspace(0,ymax,num=np.shape(z)[1]) xgrid,ygrid=np.meshgrid(x,y) zphas ..

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I’ve been trying to sort a top-5 leaderboard which includes the score and the username of the account that got the score. Here is my current code: g = open("scores.txt", "r") score1 = g.readline().strip() score2 = g.readline().strip() score3 = g.readline().strip() score4 = g.readline().strip() score5 = g.readline().strip() print(score1,score2,score3,score4,score5) print(sorted([score1,score2,score3,score4,score5], reverse = True)) g.close() It seems to ..

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For the data set x y 1 80 4 40 16 20 64 10 256 5 LibreOffice Calc gives me the following (polynomial, degree 3, Trend Line) but scipy.interpolate.interp1d called with kind=’cubic’ yields this: I’ve tried playing with interp1d‘s arguments and also tried spline interpolation and scipy.optimize.curve_fit but neither gave me something similar to what ..

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I plan to use GEKKO to solve a dynamic production scheduling problem involving a supply, process, consume process flow with hold-up (storage) between some steps. I want to maximise some objective over the horizon. However, at some timesteps there may be pre-defined limitations on processing capacities of some unit operations. While I can use the ..

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I tried to crypt a password using a blowfish hashing algorithm by the next line: c_word = crypt.crypt(password, insalt) Actually, insalt including the next format: $hashing_algo$salt$. For example: here the password is 123456 and the insalt is $2y$04$aaaabbbbccccddddeeee$ According https://www.dcode.fr/crypt-hasing-function that’s the right insalt, in contrast to the common format $hashing_algo$salt$hashed$ by https://www.cyberciti.biz/faq/understanding-etcshadow-file/. After that ..

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I have a large Python 3.6 system where multiple processes and threads interact with each other and the user. Simplified, there is a Scheduler instance (subclasses threading.Thread) and a Worker instance (subclasses multiprocessing.Process). Both objects run for the entire duration of the program. The user interacts with the Scheduler by adding Task instances and the ..

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