poutyface

githubへ登録
===========
git remote add origin [email protected]:<username>/<application_name>.git
git push origin master


初期設定
=======
git config --global user.name "Foo Bar"
git config --global user.email "[email protected]"

luispedro

# UPDATE IN 2020
# You almost always will want to use the version at
# https://github.com/luispedro/imread, which is
# up-to-date and works with Python 3





# Copyright: Luis Pedro Coelho <[email protected]>, 2012

coela

from numpy.random import *
import pickle
import numpy

pixnum = 784
pixnum2 = 100

alpha = 0.1
numIterations = 500

TakuTsuzuki

import numpy
import argparse
import cPickle as pickle

import utils

class Autoencoder3(object):
    def __init__(self, n_visible = 784, n_hidden1 = 784,
        n_hidden2 = 784, n_hidden3 = 784,
        n_hidden4 = 784, n_hidden5 = 784,

denis-bz

N-dimensional test functions for optimization, in Python.

These are the n-dim Matlab functions by A. Hedar (2005), translated to Python-numpy.
http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO.htm
ackley dp griew levy mich perm powell power rast rosen schw sphere sum2 trid zakh .m + ellipse nesterov powellsincos

http://imgur.com/Iu9H0jk is a plot of 3 no-derivative algorithms, NLOpt LN_BOBYQA LN_PRAXIS LN_SBPLX,

TakuTsuzuki

import numpy as np

def entropy(X):
    #caluculate Entropy of 1D-list
    X = np.array(X,dtype='f')
    p = X/np.sum(X)
    p = np.array([x for x in p if x>0])
    
    H = np.sum(-p*np.log2(p))
    

mikelane

import click
import difflib
import numpy as np
import random
import sys
import time

from os import name, system
from scipy.ndimage import convolve