Why does NumPy drastically slow down when I *decrease* the size of an array?
I have a 2D NumPy array, where the entries are random floats clustered tightly around 1.0, e.g. 1.015, 0.989, etc. The number of rows is n_rows = 10^4, and the number of columns is 2^13: