Advertisements I am getting errors trying to run numpy.dot with numba. It seems to be supported (eg: numpy: Faster np.dot/ multiply(element-wise multiplication) when one array is the same) but eg this code gives me the following error (it runs fine if I remove the njit part) Code: import numpy as np import numba @numba.njit() def… Read More Unable to use numpy.dot with numba
Advertisements I have a df and need to count how many adjacent columns have the same sign as other columns based on the sign of the first column, and multiply by the sign of the first column. What I need to speed up is the calc_df function, which runs like this on my computer: %timeit… Read More How can I speed up the computation of a specific function?
Advertisements I have the following situation: Supposing I have an array, and I want to subtract (absolute value) between the actual not null value and the previous not null values. [np.nan, np.nan, 10, np.nan, np.nan, 5, np.nan, 3, 6, np.nan, np.nan, 7] Expected output: [nan, nan, nan, nan, nan, 5, nan, 2, 3, nan, nan,… Read More numpy – Subtract array between actual value and previous value (only not null)
Advertisements How can I write import foo.bar in __init__.py so it will load the system-wide version of foo/bar.py when run from most places, but will load the local version of bar.py when run from within foo‘s source directory? # foo/__init__.py from foo.bar import baz baz() # foo/bar.py def baz: print(‘Hello") This will always load the… Read More Python imports in deployed/local packages
Advertisements I started using python and numba recently. My problem is: I have a matrix (n rows and m columns).In a for loop I have to change the values of specific columns. Without numba, the code is running fine. But when I use njit(), it just crashes. Note: In my real project, each row don’t… Read More Numba: indexing a vector is giving an error