butsugiri

# -*- coding: utf-8 -*-
"""
Parse iTunes Library and Generate Word Cloud
"""
"""
Copy "iTunes Music Library.xml" to the same directory as Python script
"""
import matplotlib.pyplot as plt
from lxml import etree
from collections import defaultdict

butsugiri

<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<a:fontScheme xmlns:a="http://schemas.openxmlformats.org/drawingml/2006/main" name="ヒラギノ角ゴ+Avenir"><a:majorFont><a:latin typeface="Avenir Next"/><a:ea typeface="Hiragino Kaku Gothic ProN W3"/><a:cs typeface=""/></a:majorFont><a:minorFont><a:latin typeface="Avenir Next"/><a:ea typeface="Hiragino Kaku Gothic ProN W3"/><a:cs typeface=""/></a:minorFont></a:fontScheme>

butsugiri

# -*- coding: utf-8 -*-
"""
"""
import numpy as np

def sigmoid(x):
    return 1./(1.+np.exp(-x))

def sigmoid_deriv(x):
    return x * (1.0 - x)

butsugiri

# -*- coding: utf-8 -*-
"""
お手製のニューラルネットワーク
トレーニング編
"""
import sys
import numpy as np
from collections import defaultdict

def create_features(line, ids):

butsugiri

butsugiri

# -*- coding: utf-8 -*-
"""
Chainerを用いた多層パーセプトロンの実装
多分に参考にしました: https://github.com/ichiroex/xor-mlp-chainer
"""
import sys
import numpy as np
import chainer
from chainer import cuda, Function, gradient_check, Variable, optimizers, serializers, utils
from chainer import Link, Chain, ChainList

butsugiri

# -*- coding: utf-8 -*-
"""
docomoの言語解析API(固有表現抽出)を叩くサンプルコード
"""
import requests
import json

BASEURL = "https://api.apigw.smt.docomo.ne.jp/gooLanguageAnalysis/v1/entity?APIKEY="
APIKEY = "YOUR APIKEY" #ここにAPIKEYを入力

butsugiri

butsugiri

text = open("00001.dict", encoding="shift-jis").read()
tree = etree.fromstring(text.encode("shift-jis"))
print(etree.tostring(tree, encoding="utf-8", xml_declaration=True, doctype="<!DOCTYPE gda>").decode("utf8")) 

butsugiri

# -*- coding: utf-8 -*-
from nltk.tree import Tree
from nltk.tree import ParentedTree
from nltk.tree import ImmutableParentedTree


def main():
    tree = ImmutableParentedTree.fromstring("(ROOT (S (NP (NNP Dog)) (VP (VBZ likes) (NP (NN cat))) (. .)))")
    t = tree.leaf_treeposition(1)
    x = tree.leaf_treeposition(2)