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Tag: numba

Python numba returned data types when calculating MSE

I am using numba to calculate MSE. The input are images which are ready as numpy arrays of uint8. Each element is 0-255. When calculating the squared difference between two images the python function returns (expectedly) a uint8 result, but the same function when using numba returns int64. What’s unclear to me is why the python-only code preserves the data-type

how to use mask using numba @jit

I would like to do simple division and average using jit function where nopython = True. my jit function goes however this throws me an error, what would be the workaround for this? I am trying to do this without the loop, any lights would be appreiciate. Answer numba doesn’t support some arguments for some of numpy modules (e.g. np.mean()

Numba: indexing a vector is giving an error

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 have the same values. This is

Correct usage of numpy.vstack with python’s numba

I am currently trying to speed up some python code using numba. According to the documentation of numba, numpy.meshgrid is not supported but numpy.vstack is. So I replaced the meshgrid call by vstack which works fine when not using numba. It does not work, however, when using numba. Here is the code: And here is the error message: It sounds

Create np.array filled with zero arrays

I’m trying to initialize an “empty” array with each elements containing t_list a 8×8 np.zeros array : t_list = np.zeros((8,8), dtype=np.float32) I would now want to have a np.array with multiple t_list at each indexes: result = np.array((t_list, t_list, …., tlist)) I would like to be able to control the number of time t_list is in result. I know that

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