I would like to write a program that makes extensive use of BLAS and LAPACK linear algebra functionalities. Since performance is an issue I did some benchmarking and would like know, if the approach I took is legitimate.
Let’s use, for example, numpy.sin()
Given a 3 times 3 numpy array
I have a large number of polygons (~100000) and try to find a smart way of calculating their intersecting area with a regular grid cells.
I’m using Python+Numpy (can maybe also use Scipy) and have three 2D points
How do I install SciPy on my system?
I am running a basic script that loops over a nested dictionary, grabs data from each record, and appends it to a Pandas DataFrame. The data looks something like this:
In Python generally, membership of a hashable collection is best tested via set. We know this because the use of hashing gives us O(1) lookup complexity versus O(n) for list or np.ndarray.
Are there any algorithms that will return the equation of a straight line from a set of 3D data points? I can find plenty of sources which will give the equation of a line from 2D data sets, but none in 3D.
I have a Numpy array of shape (6,2):