{"id":69254,"date":"2018-08-22T15:47:41","date_gmt":"2018-08-22T06:47:41","guid":{"rendered":"https:\/\/www.sejuku.net\/blog\/?p=69254"},"modified":"2024-05-06T11:51:10","modified_gmt":"2024-05-06T02:51:10","slug":"%e3%80%90numpy%e5%85%a5%e9%96%80-np-reshape%e3%80%91","status":"publish","type":"post","link":"https:\/\/www.sejuku.net\/blog\/69254","title":{"rendered":"\u3010NumPy\u5165\u9580 np.reshape\u3011\u914d\u5217\u306e\u5f62\u3092\u5909\u3048\u308b\u65b9\u6cd5 flatten\u306e\u4ee3\u7528\u306b\u3082\uff01"},"content":{"rendered":"

\u884c\u5217\u8a08\u7b97\u3067\u306f\u3001\u914d\u5217\u306eshape\uff08\u5f62\uff09\u304c\u975e\u5e38\u306b\u91cd\u8981\u306b\u306a\u308a\u307e\u3059\u3002numpy.array\uff08\u914d\u5217\uff09\u306eshape\u3092\u5909\u3048\u308b\u65b9\u6cd5\u306f\u3044\u308d\u3044\u308d\u3042\u308a\u307e\u3059\u304c\u3001np.reshape\u304c\u6700\u3082\u67d4\u8edf\u3067\u7c21\u5358\u306a\u95a2\u6570\u3067\u3059\u3002<\/p>\n

\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u305d\u3093\u306anp.reshape\u306e\u4f7f\u3044\u65b9\u3092\u89e3\u8aac\u3057\u307e\u3059\u3002<\/p>\n

np.reshape\u306e\u5f15\u6570\u3068\u8fd4\u308a\u5024<\/h2>\n

np.reshape\u306e\u4e3b\u306a\u5f15\u6570\u3068\u8fd4\u308a\u5024\u306e\u89e3\u8aac\u3067\u3059\u3002<\/p>\n

\u53c2\u8003\uff1aSciPy.org<\/a><\/p>\n

numpy.<\/code>reshape<\/code>(<\/span>a<\/em>, newshape<\/em>, order=’C’<\/em>)<\/span><\/p>\n

\u30c7\u30fc\u30bf\uff08\u914d\u5217\u306e\u8981\u7d20\uff09\u306f\u5909\u66f4\u305b\u305a\u306b\u3001\u914d\u5217\u3092\u65b0\u3057\u3044\u5f62\u72b6\u306b\u3057\u307e\u3059\u3002<\/p>\n\n\n\n<\/colgroup>\n\n\n\n
Parameters:<\/th>\n\n
\n
a :<\/span> array_like<\/span><\/dt>\n
\n

\u5f62\u3092\u5909\u3048\u305f\u3044\u914d\u5217<\/p>\n<\/dd>\n

newshape :<\/span> int or tuple of ints<\/span><\/dt>\n
\n

\u914d\u5217\u306e\u65b0\u3057\u3044\u5f62\u72b6\u3001int\u578b\u304btuple\u578b\u3067\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n<\/dd>\n

order :<\/span> {\u2018C\u2019, \u2018F\u2019, \u2018A\u2019}, optional<\/span><\/dt>\n<\/dl>\n<\/td>\n<\/tr>\n
Returns:<\/th>\n\n
\n
reshaped_array :<\/span> ndarray<\/span><\/dt>\n
\n

\u53ef\u80fd\u3067\u3042\u308c\u3070\u65b0\u3057\u3044view object\u3001\u7121\u7406\u306a\u3089\u3070\u914d\u5217\u306e\u30b3\u30d4\u30fc\u3002<\/p>\n<\/dd>\n<\/dl>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n

\u4f7f\u3044\u65b9<\/h2>\n

\u3053\u3053\u304b\u3089\u5148\u306e\u30b5\u30f3\u30d7\u30eb\u30b3\u30fc\u30c9\u306f\u3001\u5168\u3066Jupyter\u306e\u4e0a\u3067\u8a66\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n

In\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u306fJupyter\u306e\u30bb\u30eb\u306b\u66f8\u304f\u30b3\u30fc\u30c9\u3067\u3001Out\u4ee5\u4e0b\u306f\u76f4\u524d\u306eIn\u306b\u66f8\u304b\u308c\u305f\u30b3\u30fc\u30c9\u306e\u51fa\u529b\u7d50\u679c\u3067\u3059\u3002<\/p>\n

\u307e\u305a\u306fnumpy\u3092import\u3057\u307e\u3059\u3002<\/p>\n

In\u00a0[1]:<\/p>\n

\n
\n
\n
\n
\n
import numpy as np<\/pre>\n
\u305d\u3057\u3066\u914d\u5217\u306e\u60c5\u5831\u3092\u78ba\u8a8d\u3059\u308b\u305f\u3081\u306e\u95a2\u6570\u3092\u7528\u610f\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[2]:<\/div>\n
\n
\n
\n
def array_info(x):\r\n    print(\"\u914d\u5217\u306eshape\", x.shape)\r\n    print(\"\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b\", x.dtype)\r\n    print(\"\u914d\u5217\u306e\u4e2d\u8eabn\",x)<\/pre>\n
\u3067\u306f\u307e\u305a\u3001reshape\u5bfe\u8c61\u306e\u914d\u5217\u3092\u7528\u610f\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[3]:<\/div>\n
\n
\n
\n
x = np.arange(0,12) \r\narray_info(x)<\/pre>\n
Out:<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\u914d\u5217\u306eshape (12,)\r\n\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b int64\r\n\u914d\u5217\u306e\u4e2d\u8eab\r\n [ 0  1  2  3  4  5  6  7  8  9 10 11]\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\u57fa\u672c\u7684\u306a\u4f7f\u3044\u65b9<\/h3>\n
np.reshape\u306e\u7b2c\u4e8c\u5f15\u6570\u3068\u3057\u3066\u4f7f\u3048\u308bshape(\u914d\u5217\u306e\u5f62\uff09\u306f\u3001\u65b0\u3057\u3044shape\u306e\u7a4d\u304c\u5143\u306eshape\u306e\u7a4d\u3068\u540c\u3058\u5024\u306b\u306a\u308b\u3088\u3046\u306b\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n
\u4f8b\u3048\u3070\u3001\u3053\u3053\u3067\u3001x\u3092\u5225\u306e\u5f62\u306b\u5909\u3048\u3088\u3046\u3068\u601d\u3063\u305f\u6642\u3001<\/p>\n
\u524d\u306e\u914d\u5217\u306eshape\u306e\u7a4d = \u65b0\u3057\u3044\u914d\u5217\u306eshape\u306e\u7a4d\r\n(12,) = (3, 4)\r\n12 = 3 \u00d7 4<\/pre>\n
\u3068\u306a\u3063\u3066\u3044\u308c\u3070OK\u3067\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
\n
In [4]:\r\n\r\nx2 = np.reshape(x, (3,4))\r\narray_info(x2)\r\n\r\nOut:\r\n\u914d\u5217\u306eshape (3, 4)\r\n\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b int64\r\n\u914d\u5217\u306e\u4e2d\u8eab\r\n [[ 0  1  2  3]\r\n [ 4  5  6  7]\r\n [ 8  9 10 11]]\r\n\r\nIn [5]:\r\n\r\nx3 = np.reshape(x2, (2,2,3))\r\narray_info(x3)\r\n\r\nOut:\r\n\u914d\u5217\u306eshape (2, 2, 3)\r\n\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b int64\r\n\u914d\u5217\u306e\u4e2d\u8eab\r\n [[[ 0  1  2]\r\n  [ 3  4  5]]\r\n\r\n [[ 6  7  8]\r\n  [ 9 10 11]]]<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
flatten\u95a2\u6570\u306e\u3088\u3046\u306b\u3001\u591a\u6b21\u5143\u914d\u5217\u3092\u4e00\u6b21\u5143\u914d\u5217\u306b\u5c55\u958b\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[6]:<\/div>\n
\n
\n
\n
size = np.prod(x3.shape)\r\nx4 = np.reshape(x3, size)\r\n\r\nprint(x3.shape, \"->\", size)\r\narray_info(x4)<\/pre>\n
Out:<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
(2, 2, 3) -> 12\r\n\u914d\u5217\u306eshape (12,)\r\n\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b int64\r\n\u914d\u5217\u306e\u4e2d\u8eab\r\n [ 0  1  2  3  4  5  6  7  8  9 10 11]\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
flatten, ravel\u3068\u306e\u901f\u5ea6\u6bd4\u8f03<\/h3>\n
flatten\u3084ravel\u3068\u3044\u3046\u95a2\u6570\u306f\u3001\u591a\u6b21\u5143\u914d\u5217\u3092\u4e00\u6b21\u5143\u914d\u5217\u306b\u5c55\u958b\u3059\u308b\u6a5f\u80fd\u3092\u6301\u3061\u307e\u3059\u3002<\/p>\n
\u3053\u308c\u3089\u3068reshape\u3068\u306e\u901f\u5ea6\u6bd4\u8f03\u3092\u3057\u3066\u307f\u307e\u3057\u3087\u3046jupyter\u3067\u306fcell\u306e\u5148\u982d\u306b%%timeit\u3092\u3064\u3051\u308b\u3053\u3068\u3067\u8a08\u7b97\u6642\u9593\u3092\u8a08\u6e2c\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[7]:<\/div>\n
\n
\n
\n
%%timeit\r\n\r\nsize = np.prod(x3.shape)\r\nx4 = np.reshape(x3, size)<\/pre>\n
[\u8a08\u7b97\u6642\u9593]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
5.67 \u00b5s \u00b1 46.7 ns per loop (mean \u00b1 std. dev. of 7 runs, 100000 loops each)\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[8]:<\/div>\n
\n
\n
\n
%%timeit\r\n\r\nx4 = np.reshape(x3, size)<\/pre>\n
[\u8a08\u7b97\u6642\u9593]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
1.11 \u00b5s \u00b1 15.8 ns per loop (mean \u00b1 std. dev. of 7 runs, 1000000 loops each)\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[9]:<\/div>\n
\n
\n
\n
%%timeit\r\n\r\nx4 = x3.flatten()<\/pre>\n
[\u8a08\u7b97\u6642\u9593]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
555 ns \u00b1 11.2 ns per loop (mean \u00b1 std. dev. of 7 runs, 1000000 loops each)\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
In\u00a0[10]:<\/div>\n
\n
\n
\n
%%timeit\r\n\r\nx4 = x3.ravel()\r\n<\/pre>\n
[\u8a08\u7b97\u6642\u9593]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\n
165 ns \u00b1 2.21 ns per loop (mean \u00b1 std. dev. of 7 runs, 10000000 loops each)\r\n<\/pre>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
\u6b8b\u5ff5\u306a\u304c\u3089reshape\u304c\u4e00\u756a\u9045\u304f\u3001\u6b21\u306bflatten\u3001\u4e00\u756a\u65e9\u3044\u306e\u304cravel\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n<\/div>\n<\/div>\n<\/div>\n
\n
\n
\n
ravel\u306f\u5143\u306e\u914d\u5217\u3078\u306e\u53c2\u7167\u3092\u8fd4\u3057\u3066\u3044\u308b\u306e\u3067\u3001\u5f62\u3092\u5909\u3048\u305f\u65b9\u306e\u914d\u5217\u306e\u8981\u7d20\u3092\u5909\u66f4\u3059\u308b\u3068\u3001\u5143\u306e\u914d\u5217\u306e\u65b9\u3082\u5909\u66f4\u3055\u308c\u3066\u3057\u307e\u3046\u306e\u3067\u6ce8\u610f\u304c\u5fc5\u8981\u3067\u3059\u3002<\/p>\n
reshape(-1)\u3067\u914d\u5217\u306eshape\u3092\u81ea\u52d5\u8a2d\u5b9a<\/h3>\n
np.reshape\u306eshape\u306e\u8a08\u7b97\u3001\u697d\u3092\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002<\/p>\n
\u4f8b\u3048\u3070\u3001(12,)\u3092(2, 6)\u306b\u3057\u305f\u3044\u6642\u3002\u5909\u66f4\u5f8c\u306e\u914d\u5217\u306e\u5f62\u3001\u7247\u65b9\u3092\u8a2d\u5b9a\u3057\u3066\u4e0a\u3052\u308c\u3070\u6b8b\u308a\u306f-1\u3068\u66f8\u304f\u3060\u3051\u3067\u52dd\u624b\u306bshape\u3092\u6700\u9069\u306a\u3082\u306e\u306b\u3057\u3066\u304f\u308c\u307e\u3059\u3002\u5b9f\u969b\u306b\u898b\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
In [11]:<\/p>\n
x5 = np.reshape(x3, (2,-1))\r\narray_info(x5)<\/pre>\n
Out:<\/p>\n
\u914d\u5217\u306eshape (2, 6)\r\n\u914d\u5217\u306e\u8981\u7d20\u306e\u30c7\u30fc\u30bf\u578b int64\r\n\u914d\u5217\u306e\u4e2d\u8eab\r\n [[ 0  1  2  3  4  5]\r\n [ 6  7  8  9 10 11]]<\/pre>\n<\/div>\n<\/div>\n<\/div>\n
\u307e\u3068\u3081<\/h2>\n
\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001numpy.array\u306eshape\u3092\u5909\u3048\u308b\uff08\u914d\u5217\u306e\u5f62\u3092\u5909\u3048\u308b\uff09\u95a2\u6570\u3001np.reshape\u306b\u3064\u3044\u3066\u7d39\u4ecb\u3057\u307e\u3057\u305f\u3002\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306a\u3069\u306e\u8a08\u7b97\u3067\u306f\u3001\u914d\u5217\u306e\u5f62\u304c\u63c3\u3063\u3066\u3044\u306a\u3044\u3068\u8a08\u7b97\u304c\u3067\u304d\u306a\u3044\u3068\u3044\u3063\u305f\u3053\u3068\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\u305d\u3093\u306a\u3068\u304d\u306bnp.reshape\u306f\u975e\u5e38\u306b\u6709\u7528\u306a\u95a2\u6570\u3067\u3059\u3002\u3053\u306e\u8a18\u4e8b\u3067np.reshape\u306e\u4f7f\u3044\u65b9\u3092\u899a\u3048\u3066\u3001\u662f\u975e\u79d1\u5b66\u8a08\u7b97\u3084\u6a5f\u68b0\u5b66\u7fd2\u306e\u5b9f\u88c5\u306b\u5f79\u7acb\u3066\u3066\u304f\u3060\u3055\u3044\uff01<\/p>\n
\u4eca\u56de\u306e\u8a18\u4e8b\u306f\u4e0b\u8a18\u306e\u8a18\u4e8b\u3092\u53c2\u8003\u306b\u3057\u3066\u3044\u307e\u3059\u3002
\n\u53c2\u8003\u8a18\u4e8b\uff1a
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