122 lines
3.5 KiB
Plaintext
122 lines
3.5 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"import numpy as np"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "markdown",
|
|
"metadata": {},
|
|
"source": [
|
|
"# 数据拼接\n",
|
|
"\n",
|
|
"1. np.concatenate 是numpy中对array进行拼接的函数\n",
|
|
"axis参数为指定按照哪个维度进行拼接"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"[[ 2.62434536 0.38824359 0.47182825 -0.07296862]\n",
|
|
" [ 1.86540763 -1.3015387 2.74481176 0.2387931 ]\n",
|
|
" [ 1.3190391 0.75062962 2.46210794 -1.06014071]\n",
|
|
" [ 0.6775828 0.61594565 2.13376944 -0.09989127]\n",
|
|
" [ 0.82757179 0.12214158 1.04221375 1.58281521]] \n",
|
|
" (5, 4) \n",
|
|
"\n",
|
|
"[[-0.10061918 2.14472371 1.90159072 1.50249434]\n",
|
|
" [ 1.90085595 0.31627214 0.87710977 0.06423057]\n",
|
|
" [ 0.73211192 1.53035547 0.30833925 0.60324647]] \n",
|
|
" (3, 4) \n",
|
|
"\n",
|
|
"[[ 0.3128273 0.15479436]\n",
|
|
" [ 0.32875387 0.9873354 ]\n",
|
|
" [-0.11731035 1.2344157 ]\n",
|
|
" [ 2.65980218 1.74204416]\n",
|
|
" [ 0.80816445 0.11237104]] \n",
|
|
" (5, 2) \n",
|
|
"\n",
|
|
"[[ 2.62434536 0.38824359 0.47182825 -0.07296862]\n",
|
|
" [ 1.86540763 -1.3015387 2.74481176 0.2387931 ]\n",
|
|
" [ 1.3190391 0.75062962 2.46210794 -1.06014071]\n",
|
|
" [ 0.6775828 0.61594565 2.13376944 -0.09989127]\n",
|
|
" [ 0.82757179 0.12214158 1.04221375 1.58281521]\n",
|
|
" [-0.10061918 2.14472371 1.90159072 1.50249434]\n",
|
|
" [ 1.90085595 0.31627214 0.87710977 0.06423057]\n",
|
|
" [ 0.73211192 1.53035547 0.30833925 0.60324647]] \n",
|
|
" (8, 4) \n",
|
|
"\n",
|
|
"[[ 2.62434536 0.38824359 0.47182825 -0.07296862 0.3128273 0.15479436]\n",
|
|
" [ 1.86540763 -1.3015387 2.74481176 0.2387931 0.32875387 0.9873354 ]\n",
|
|
" [ 1.3190391 0.75062962 2.46210794 -1.06014071 -0.11731035 1.2344157 ]\n",
|
|
" [ 0.6775828 0.61594565 2.13376944 -0.09989127 2.65980218 1.74204416]\n",
|
|
" [ 0.82757179 0.12214158 1.04221375 1.58281521 0.80816445 0.11237104]] \n",
|
|
" (5, 6) \n",
|
|
"\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"rdm = np.random.RandomState(1)\n",
|
|
"x1 = rdm.normal(1,1,(5,4))\n",
|
|
"x2 = rdm.normal(1,1,(3,4))\n",
|
|
"x3 = rdm.normal(1,1,(5,2))\n",
|
|
"print(x1,\"\\n\",x1.shape,\"\\n\")\n",
|
|
"print(x2,\"\\n\",x2.shape,\"\\n\")\n",
|
|
"print(x3,\"\\n\",x3.shape,\"\\n\")\n",
|
|
"\n",
|
|
"con1 = np.concatenate([x1,x2],axis=0)\n",
|
|
"print(con1,\"\\n\",con1.shape,\"\\n\")\n",
|
|
"\n",
|
|
"con2 = np.concatenate([x1,x3],axis=1)\n",
|
|
"print(con2,\"\\n\",con2.shape,\"\\n\")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3.9.13 ('gym')",
|
|
"language": "python",
|
|
"name": "python3"
|
|
},
|
|
"language_info": {
|
|
"codemirror_mode": {
|
|
"name": "ipython",
|
|
"version": 3
|
|
},
|
|
"file_extension": ".py",
|
|
"mimetype": "text/x-python",
|
|
"name": "python",
|
|
"nbconvert_exporter": "python",
|
|
"pygments_lexer": "ipython3",
|
|
"version": "3.9.13"
|
|
},
|
|
"orig_nbformat": 4,
|
|
"vscode": {
|
|
"interpreter": {
|
|
"hash": "eb62451c918ef6a4174992a3510c06ea27ba0bc2fc5ee7a9f470b6f52b0b170f"
|
|
}
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|