TomDLT

from functools import wraps
import time

import numpy as np
import scipy.sparse as sp

from sklearn.utils.testing import assert_array_equal


class ContextDecorator(object):

TomDLT

from functools import wraps
import time

import numpy as np
import scipy.sparse as sp

from sklearn.utils.testing import assert_array_equal


class ContextDecorator(object):

TomDLT

import numpy as np

import matplotlib.pyplot as plt
from matplotlib import rcParams
from matplotlib.ticker import LinearLocator

# use default Latex font for math even with matplotlib 2.0
rcParams['mathtext.fontset'] = 'cm'

fig = plt.figure()

TomDLT

import cProfile


def profile_this(fn):
    def profiled_fn(*args, **kwargs):
        filename = fn.__name__ + '.profile'
        prof = cProfile.Profile()
        ret = prof.runcall(fn, *args, **kwargs)
        prof.dump_stats(filename)
        return ret

TomDLT

import numpy as np
import matplotlib.pyplot as plt

from mne.preprocessing.peak_finder import peak_finder


def test_peak_finder(signal, thresh=None):
    plt.plot(signal)

    # find the maxima

TomDLT

from __future__ import print_function
import sys
import time


# copy from MNE-Python
class ProgressBar():
    """Class for generating a command-line progressbar
    Parameters
    ----------

TomDLT

import re
import os

# find existing links
matches = []
with open('whats_new.rst', 'r') as f:
    for line in f.readlines():
        m = re.search('`[A-Za-z üéö@.ä-]*`_', line)
        if m is not None:
            matches.append(m.group(0))

TomDLT

from __future__ import print_function
import warnings

import numpy as np
import neo.io
from mne.io.array import RawArray
from mne import create_info


def _smr(filename):

TomDLT

from sklearn.datasets import fetch_olivetti_faces
from sklearn.decomposition.nmf import NMF
from sklearn.externals.joblib import Parallel, delayed


def fit(X):
    nmf.fit(X)


def nmf_test(n_jobs=-1, backend='multiprocessing'):

TomDLT

import warnings
import neo.io

def smr2sig(filename, smr_nums=[0]):
    """
    read signal from .smr file (Spike2)

    parameters
    ----------
    filename    : name of file