How does numpy.histogram() work?
While reading up on numpy, I encountered the function numpy.histogram().
numpy
How to plot line (polygonal chain) with numpy/scipy/matplotlib with minimal smoothing
I am trying to plot a line in matplotlib.. I am searching for the right type of interpolation.. I want something like this
Iterating over Numpy matrix rows to apply a function each?
I want to be able to iterate over the matrix to apply a function to each row. How can I do it for a Numpy matrix ?
Generating movie from python without saving individual frames to files
I would like to create an h264 or divx movie from frames that I generate in a python script in matplotlib. There are about 100k frames in this movie.
more efficient way to calculate distance in numpy?
i have a question on how to calculate distances in numpy as fast as it can,
NaNs as key in dictionaries
Can anyone explain the following behaviour to me?
how do I calculate a rolling idxmax
consider the pd.Series s
Efficiently detect sign-changes in python
I want to do exactly what this guy did:
Matplotlib: how to make imshow read x,y coordinates from other numpy arrays?
When you want to plot a numpy array with imshow, this is what you normally do:
Fastest save and load options for a numpy array
I have a script that generates two-dimensional numpy arrays with dtype=float and shape on the order of (1e3, 1e6). Right now I’m using np.save and np.load to perform IO operations with the arrays. However, these functions take several seconds for each array. Are there faster methods for saving and loading the entire arrays (i.e., without making assumptions about their contents and reducing them)? I’m open to converting the arrays to another type before saving as long as the data are retained exactly.