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Sylvain Chevallier sylvchev

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@sylvchev
sylvchev / README
Last active August 29, 2015 14:10 — forked from leandrosilva/README
$ python xlogd.py sample.log
parsed: {'appname': 'test.app', 'timestamp': '2012-09-06 15:19:32', 'hostname': 'codezone.local', 'pid': '68898', 'priority': '132', 'message': 'bla bla bla warn'}
parsed: {'appname': 'test.app', 'timestamp': '2012-09-06 15:19:32', 'hostname': 'codezone.local', 'pid': '68902', 'priority': '131', 'message': 'bla bla bla error'}
parsed: {'appname': 'Dock', 'timestamp': '2012-09-06 15:19:32', 'hostname': 'codezone.local', 'pid': '154', 'priority': '11', 'message': 'CGSReleaseWindowList: called with 5 invalid window(s)'}
parsed: {'appname': 'WindowServer', 'timestamp': '2012-09-06 15:19:32', 'hostname': 'codezone.local', 'pid': '79', 'priority': '11', 'message': 'CGXSetWindowListAlpha: Invalid window 0'}
@sylvchev
sylvchev / sanity_check.ipynb
Last active August 29, 2015 14:24
Sanity check
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@sylvchev
sylvchev / scipy_benchmark.py
Last active November 29, 2015 00:07
Benchmarking scipy and numpy, to be measured with MKL, OpenBLAS and Netlib.
from __future__ import print_function
import sys
from numpy import array
from numpy.random import rand
from timeit import Timer
import pickle
from os import system
if len(sys.argv) is not 2:
print ("usage: numpy_benchmark.py whichpython")
@sylvchev
sylvchev / scipy_plot_benchmark.py
Last active November 30, 2015 13:48
Plotting a numpy/scipy benchmark between Canopy (MKL), Anaconda (Netlib) and my Gentoo python (OpenBLAS)
import matplotlib.pyplot as plt
import pickle
from numpy import arange
with open("scipy_canopy.pck", 'r') as f:
o = pickle.load(f)
canopy_dot = o['dot']
canopy_chol = o['chol']
canopy_svd = o['svd']
with open("scipy_anaconda.pck", 'r') as f:
@sylvchev
sylvchev / scatter_iris.py
Last active December 17, 2015 08:49
Scatter plot matrix for Iris dataset
from sklearn.datasets import load_iris
from numpy import array
from pandas import DataFrame
from pandas.tools.plotting import scatter_matrix
iris = load_iris()
df = DataFrame(iris.data, columns=iris.feature_names)
colors=array(50*['r']+50*['g']+50*['b'])
scatter_matrix(df, alpha=0.2, figsize=(10,10), color=colors)
@sylvchev
sylvchev / test_numpy_multiply_dot.py
Last active January 21, 2016 13:08
Testing numpy computation speed up for numpy.multiply vs numpy.dot in special case: for $V \in R^{n \times n}$ and $U \in R^n$, compare the speed up for numpy.dot(V, numpy.diag(U)) and numpy.multiply(V, U)
import numpy as np
from pyriemann.estimation import Covariances
from timeit import Timer
n, t = 1500, 3000
n_repeat = 100
X = np.random.rand(1, n, t)
U = np.random.rand(n)
cov = Covariances()
@sylvchev
sylvchev / EEG_covariance_example.ipynb
Created February 10, 2016 14:42
Some simple code to classify EEG BCI task based on their covariance matrix
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@sylvchev
sylvchev / covarianceSSVEPextraction.ipynb
Last active April 15, 2022 14:16
Building extended SSVEP covariance matrices for EEG-based cerebral interfaces
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@sylvchev
sylvchev / covarianceSSVEPclassification.ipynb
Last active November 21, 2020 22:49
Classifying SSVEP extended covariance matrices with MDM algorithm
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@sylvchev
sylvchev / plotCovarianceMNE.py
Created February 29, 2016 23:11
Opening and plotting coavriance matrices estimated from SSVEP dataset
import numpy as np
import mne
from sklearn.cross_validation import cross_val_score, KFold
from pyriemann.estimation import covariances
import matplotlib.pyplot as plt
tmin, tmax = 2., 5.
event_id = dict(resting=1, stim13=2, stim17=3, stim21=4)
data_path = './'
fname = 'subject12/record-[2014.03.10-19.17.37]'