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#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
""" | |
Translated from a MATLAB script (which also includes C-weighting, octave | |
and one-third-octave digital filters). | |
Author: Christophe Couvreur, Faculte Polytechnique de Mons (Belgium) | |
couvreur@thor.fpms.ac.be | |
Last modification: Aug. 20, 1997, 10:00am. | |
BSD license |
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#!/usr/bin/env python2.7 | |
import scipy.ndimage as ndimage | |
import numpy | |
def local_maxima(array, min_distance = 1, periodic=False, edges_allowed=True): | |
"""Find all local maxima of the array, separated by at least min_distance.""" | |
array = numpy.asarray(array) | |
cval = 0 | |
if periodic: |
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# assume the following directory structure where contents of doc/ | |
# and source/ are already checked into repo., with the exception | |
# of the _build directory (i,e. you can check in _themes or _sources | |
# or whatever else). | |
# | |
# proj/ | |
# source/ | |
# doc/ | |
# remove doc/_build/html if present |
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git clone <repo-address> | |
git tag -l | |
git checkout <tag-name> | |
git branch -D master | |
git checkout -b master |
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class Color(object): | |
""" | |
utility to return ansi colored text. | |
""" | |
colors = { | |
'black': 30, | |
'red': 31, | |
'green': 32, | |
'yellow': 33, |
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import random | |
add = lambda a,b: a+b | |
sub = lambda a,b: a-b | |
mul = lambda a,b: a*b | |
div = lambda a,b: a/b if a % b == 0 else 0/0 | |
operations = [ (add, '+'), | |
(sub, '-'), | |
(mul, '*'), |
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from __future__ import print_function | |
import imageio | |
from PIL import Image | |
import numpy as np | |
import keras | |
from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation | |
from keras.models import Model | |
from keras.regularizers import l2 | |
from keras.optimizers import SGD |
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import tweepy | |
import csv | |
import pandas as pd | |
####input your credentials here | |
consumer_key = '' | |
consumer_secret = '' | |
access_token = '' | |
access_token_secret = '' | |
auth = tweepy.OAuthHandler(consumer_key, consumer_secret) |
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""" | |
Functions to identify TE-dependent and TE-independent components. | |
""" | |
import json | |
import logging | |
import pickle | |
from nilearn._utils import check_niimg | |
import numpy as np | |
from scipy import stats |
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