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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() |
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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) |
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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: |
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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") |
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$ 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'} |
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