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I've seen this algorithm described, and I'd rather not reinvent the wheel if a standard implementation exists. I've also learned that if there is a scipy/numpy implementation, it is usually much faster than anything I can roll myself in python.
I have a large number of points on the plane (several million). Starting with a large box that encompasses all the points, I'd like to continuously subdivide the box into equal area sub-boxes. The subdivision continues recursively while there are at least 1,000 points in the sub-box. The algorithm returns a tree that describes the subdivisions and the mapping of the points to each leaf node of the tree.
What is the name of this algorithm (something like divide and conquer?), and is there a standard method of doing it when given a 2D numpy array of points?
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NumPy, stands for Numerical Python, is used for the manipulation of elements of numerical array data. SciPy, stands for Scientific Python, is used for numerical computations in Python. Both these packages provide extended functionality to work with Python.
SciPy builds on NumPy. All the numerical code resides in SciPy. The SciPy module consists of all the NumPy functions. It is however better to use the fast processing NumPy.
What is the difference between NumPy and SciPy? In an ideal world, NumPy would contain nothing but the array data type and the most basic operations: indexing, sorting, reshaping, basic elementwise functions, etc. All numerical code would reside in SciPy.
SciPy is a collection of mathematical algorithms and convenience functions built on the NumPy extension of Python. It adds significant power to the interactive Python session by providing the user with high-level commands and classes for manipulating and visualizing data.
It's called a quadtree partition. As far as Python code, see this thread.
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