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# Jake Vanderplas jakevdp

Created Jun 13, 2011
ARPACK memory error
View AR_crash.py
 import numpy as np from scipy.sparse.linalg import eigs N = 6 k = 2 # with this random seed, I get a memory error on the third iteration below np.random.seed(2301) A = np.random.random((N,N))
Created Sep 29, 2011
test code & dataset for scikit-learn issue #365
View README
 code demonstrating the problem seen in issue #365 to run the example: tar -zxvf data.tgz python test.py
Created Dec 23, 2011
Benchmarks for eigenvalue decomposition
View banded_tools.py
 from time import time import numpy as np from scipy.sparse import spdiags, issparse, dia_matrix from scipy.sparse.linalg import factorized from scipy import linalg as splinalg class BandedMatrix(object): def __init__(self, data, lu=None): if issparse(data): if lu:
Created Dec 29, 2011
GMM BIC/AIC test
View README.rst

This includes a test of the new GMM routines in https://github.com/bthirion/scikit-learn/tree/gmm-fixes

By changing the line

GMM = mixture.GMM

at the top of the file, we can plot the BIC and AIC for each variant of GMM. Standard GMM works beautifully: it settles in on 3 components, which are a good description of the data. DPGMM and VBGMM produce some unexpected results.

Created Jan 5, 2012
General Distance Metrics for BallTree
View README.rst

This is the outline of a framework that will allow general distance metrics to be incorporated into scikit-learn BallTree. The idea is that we need a fast way to compute the distance between two points under a given metric. In the basic framework here, this involves creating an object which exposes C-pointers to a function and a parameter structure so that the distance function can be called from either python or directly from cython with no python overhead.

Created Jan 18, 2012
Example of sphinx image copy
View Makefile
 SPHINXBUILD = sphinx-build BUILDDIR = _build SPHINXOPTS = -d \$(BUILDDIR)/doctrees . all: html html: \$(SPHINXBUILD) -b html \$(SPHINXOPTS) \$(BUILDDIR)/html @echo @echo "Build finished. The HTML pages are in \$(BUILDDIR)/html."
Created Jan 23, 2012
Showing memory error in BallTree
View kneighbors_test.py
 import warnings from sklearn import datasets from sklearn.neighbors import NearestNeighbors import numpy as np n_points = 1000 n_neighbors = 10 out_dim = 2 n_trials = 100
Created Sep 30, 2012
Scikit-learn Documentation Template
View sklearn_doc.py
 """ This file has an example function, with a documentation string which should serve as a template for scikit-learn docstrings. """ def sklearn_template(X, y, a=1, flag=True, f=None, **kwargs): """This is where a short one-line description goes This is where a longer, multi-line description goes. It's not required, but might be helpful if more information is needed.
Created Oct 6, 2012
Demo for GIF animations
View basic_animation.py
 import numpy as np from matplotlib import pyplot as plt from matplotlib import animation # First set up the figure, the axis, and the plot element we want to animate fig = plt.figure() ax = fig.add_subplot(111, xlim=(0, 2), ylim=(-2, 2)) line, = ax.plot([], [], lw=2) # initialization function: plot the background of each frame
Last active Mar 15, 2021
Numba Ball Tree example
View README.md

# Numba Ball Tree

This is a quick attempt at writing a ball tree for nearest neighbor searches using numba. I've included a pure python version, and a version with numba jit decorators. Because class support in numba is not yet complete, all the code is factored out to stand-alone functions in the numba version. The resulting code produced by numba is about ~10 times slower than the cython ball tree in scikit-learn. My guess is that part of this stems from lack of inlining in numba, while the rest is due to some sort of overhead