I am working on a project in which I need to put together a plot grid of 10 rows and 3 columns. Although I have been able to make the plots and arrange the subplots, I was not able to produce a nice plot without white space such as this one below from gridspec documentatation.
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I am trying to implement a large number of matrix-matrix multiplications in Python. Initially, I assumed that NumPy would use automatically my threaded BLAS libraries since I built it against those libraries. However, when I look at top or something else it seems like the code does not use threading at all.
How do you save/load a scipy sparse csr_matrix in a portable format? The scipy sparse matrix is created on Python 3 (Windows 64-bit) to run on Python 2 (Linux 64-bit). Initially, I used pickle (with protocol=2 and fix_imports=True) but this didn’t work going from Python 3.2.2 (Windows 64-bit) to Python 2.7.2 (Windows 32-bit) and got the error:
I need a python method to open and import TIFF images into numpy arrays so I can analyze and modify the pixel data and then save them as TIFFs again. (They are basically light intensity maps in greyscale, representing the respective values per pixel)
I used fft function in numpy which resulted in a complex array. How to get the exact frequency values?
If x doesn’t implement an __iadd__ method then the x += y statement is just a shorthand for x = x + y. This would be the case if x was something like an int.
I’m trying to use dot products, matrix inversion and other basic linear algebra operations that are available in numpy from Cython. Functions like numpy.linalg.inv (inversion), numpy.dot (dot product), X.t (transpose of matrix/array). There’s a large overhead to calling numpy.* from Cython functions and the rest of the function is written in Cython, so I’d like to avoid this.
I have such Python code:
I have the following array
How can I get get the position (indices) of the largest value in a multi-dimensional NumPy array?