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GaelVaroquaux / Discussion
Created February 27, 2014 14:38
Temporary. Only for discussion purposes
This gist is only meant for discussion.
@GaelVaroquaux
GaelVaroquaux / bench_dbscan.py
Last active December 20, 2015 10:19
Benchmarking scikit_learn 0.14.X release
import numpy as np
import time
from sklearn import cluster
from sklearn import datasets
lfw = datasets.fetch_lfw_people()
X_lfw = lfw.data[:, :5]
eps = 8. # This choice of EPS gives 44 clusters
@GaelVaroquaux
GaelVaroquaux / map_wrapper.pyx
Created October 17, 2012 10:31
Wrapping CPP map container to a dict-like Python object
"""
Uses C++ map containers for fast dict-like behavior with keys being
integers, and values float.
"""
# Author: Gael Varoquaux
# License: BSD
# XXX: this needs Cython 17.1 or later. Elsewhere you will get a C++ compilation error.
import numpy as np
@GaelVaroquaux
GaelVaroquaux / lasso.py
Created October 5, 2012 07:12 — forked from aweinstein/lasso.py
scikitlearn lasso path fat vs thin X matrix
import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import Lasso, lars_path
np.random.seed(42)
def gen_data(n, m, k):
X = np.random.randn(n, m)
w = np.zeros((m, 1))
i = np.arange(0, m)
@GaelVaroquaux
GaelVaroquaux / sklearn_EN_example.py
Created September 29, 2012 16:16 — forked from arokem/sklearn_EN_example.py
Demonstrate that ElasticNet doesn't fit all the way, even for rather strict convergence criteria
import numpy as np
import sklearn.linear_model as lm
X = np.array([[ -2.18252949e-01, -8.21949578e-02, -4.64055457e-02,
-1.78405908e-01, -1.93863740e-01, 5.30667625e-02,
1.83851107e-01, 1.23426449e-01, 1.97396315e-01,
-2.12615837e-01, 7.06452283e-02, -1.94509405e-01,
-9.77929516e-02, 2.07135018e-01, -3.40368338e-02,
2.02970673e-01, -2.28669466e-01, 4.17398420e-02,
1.80163132e-01, 3.24254938e-02, -2.41198452e-03,
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GaelVaroquaux / bench_elastic_net.py
Created September 24, 2012 13:08
Benchmark of elastic net on a very sparse system
# Licence : BSD
# Author: Gael Varoquaux
from time import time
import numpy as np
import pylab as pl
from scipy import linalg, ndimage
from sklearn import linear_model
@GaelVaroquaux
GaelVaroquaux / bench.py
Created August 6, 2012 13:29
Benching neurimaging I/O
"""
Benching I/O with joblib and other libraries. Comment and
un-comment what you are interested in.
Warning: this is slow, and the benchs are easily offset by other disk
activity.
"""
import os
import time
import shutil
@GaelVaroquaux
GaelVaroquaux / bench.py
Created January 2, 2012 16:15
Benching I/O speed with numpy, joblib, NiBabel and pytables
"""
Benching I/O with joblib and other libraries. Comment and
un-comment what you are interested in.
Warning: this is slow, and the benchs are easily offset by other disk
activity.
"""
import os
import time
import shutil
@GaelVaroquaux
GaelVaroquaux / lighting_talk.rst
Created December 5, 2011 10:29
Bootstrapping a SciPy-related community project

Bootstrapping a SciPy-related community project

This document is a lightning talk: it only gives pointers, you need to Google and read references

Goal

@GaelVaroquaux
GaelVaroquaux / 00README.rst
Last active September 15, 2023 03:58
Copy-less bindings of C-generated arrays with Cython

Cython example of exposing C-computed arrays in Python without data copies

The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.

The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy