122 lines
54 KiB
Text
122 lines
54 KiB
Text
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 人工智能与机器学习-实验1"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Part.III Matplotlib绘图练习\n",
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"\n",
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"|学号 |姓名 |\n",
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"|----------|--------|\n",
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"|***REMOVED***|***REMOVED***|\n",
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"|2020113874|何一涛|"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1. 曲线\n",
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"\n",
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"* 用蓝线绘制函数$𝑓(𝑥) = 𝑥^2−2𝑥+3$的图表,并在坐标(1,2)位置处标上一个红色的点\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import numpy as np\n",
|
||
"x = np.linspace(-1, 3, 50)\n",
|
||
"y = x**2 - 2*x + 3\n",
|
||
"plt.plot(x, y, color='blue', linewidth=1.0)\n",
|
||
"plt.scatter(1, 2, color='red')\n",
|
||
"plt.show()\n"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"metadata": {},
|
||
"source": [
|
||
"### 2. x-y图\n",
|
||
"\n",
|
||
"* 使用`np.linspace()`函数生成$t\\in [0, 2\\pi]$。\n",
|
||
"* 给定$𝑥=16*sin(𝑡)^3$和$𝑦=13*cos(𝑡)−5*cos(2𝑡)−2*cos(3𝑡)−cos(4𝑡)$,画出x-y图表,\n",
|
||
"* 并给图标添加一个题目:Heart"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 5,
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 640x480 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
}
|
||
],
|
||
"source": [
|
||
"import matplotlib.pyplot as plt\n",
|
||
"import numpy as np\n",
|
||
"t = np.linspace(0, 2*np.pi, 1000)\n",
|
||
"x = 16*np.sin(t)**3\n",
|
||
"y = 13*np.cos(t) - 5*np.cos(2*t) - 2*np.cos(3*t) - np.cos(4*t)\n",
|
||
"plt.plot(x, y, color='red', linewidth=1.0)\n",
|
||
"plt.title('Heart')\n",
|
||
"plt.show()"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "Python 3.10.7 ('.venv': venv)",
|
||
"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": "3.10.7"
|
||
},
|
||
"vscode": {
|
||
"interpreter": {
|
||
"hash": "1f0d395e06aa83586067b19165efc9b683889967164248deef4bbf1fa27cfb00"
|
||
}
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 2
|
||
}
|