How can I tell if NumPy creates a view or a copy?
For a minimal working example, let’s digitize a 2D array. numpy.digitize requires a 1D array:
numpy
How to normalize a NumPy array to within a certain range?
After doing some processing on an audio or image array, it needs to be normalized within a range before it can be written back to a file. This can be done like so:
How do I catch a numpy warning like it’s an exception (not just for testing)?
I have to make a Lagrange polynomial in Python for a project I’m doing. I’m doing a barycentric style one to avoid using an explicit for-loop as opposed to a Newton’s divided difference style one. The problem I have is that I need to catch a division by zero, but Python (or maybe numpy) just makes it a warning instead of a normal exception.
Plotting a fast Fourier transform in Python
I have access to NumPy and SciPy and want to create a simple FFT of a data set. I have two lists, one that is y values and the other is timestamps for those y values.
A fast way to find the largest N elements in an numpy array
I know I can do it like the following:
How to save and load numpy.array() data properly?
I wonder, how to save and load numpy.array data properly. Currently I’m using the numpy.savetxt() method. For example, if I got an array markers, which looks like this:
Vectorized searchsorted numpy
Assume that I have two arrays A and B, where both A and B are m x n. My goal is now, for each row of A and B, to find where I should insert the elements of row i of A in the corresponding row of B. That is, I wish to apply np.digitize or np.searchsorted to each row of A and B.
Numpy – create matrix with rows of vector
I have a vector [x,y,z,q] and I want to create a matrix:
How to convert a NumPy array to PIL image applying matplotlib colormap
I have a simple problem, but I cannot find a good solution to it.