{ "cells": [ { "cell_type": "markdown", "id": "73bd968b-d970-4a05-94ef-4e7abf990827", "metadata": {}, "source": [ "Chapter 04\n", "\n", "# diag() 函数\n", "Book_4《矩阵力量》 | 鸢尾花书:从加减乘除到机器学习 (第二版)" ] }, { "cell_type": "markdown", "id": "53c03812-0303-4691-9961-f87c9059705c", "metadata": {}, "source": [ "\n", "\n", "该代码首先定义了一个 $3 \\times 3$ 的矩阵 $A$:\n", "\n", "$$\n", "A = \\begin{bmatrix} 1 & 2 & 3 \\\\ 4 & 5 & 6 \\\\ 7 & 8 & 9 \\end{bmatrix}\n", "$$\n", "\n", "然后,代码使用 `np.diag` 提取矩阵 $A$ 的对角元素,得到向量 $a = [1, 5, 9]$。接下来,通过向量 $a$ 构建了一个新的对角矩阵 $A_{\\text{diag}}$,其形式为:\n", "\n", "$$\n", "A_{\\text{diag}} = \\begin{bmatrix} 1 & 0 & 0 \\\\ 0 & 5 & 0 \\\\ 0 & 0 & 9 \\end{bmatrix}\n", "$$\n", "\n", "此过程展示了从一个矩阵中提取对角线元素并利用这些元素构造新的对角矩阵的操作。" ] }, { "cell_type": "markdown", "id": "ccb1e0a3-d0ed-4996-9880-b08ba4918993", "metadata": {}, "source": [ "## 导入所需库" ] }, { "cell_type": "code", "execution_count": 1, "id": "e1227d8c-7f70-48b9-af13-a17776aa8152", "metadata": {}, "outputs": [], "source": [ "import numpy as np # 导入NumPy库,用于数值计算" ] }, { "cell_type": "markdown", "id": "49b8f8e3-3955-48f6-ab9c-de1db5afbe2a", "metadata": {}, "source": [ "## 定义矩阵" ] }, { "cell_type": "code", "execution_count": 2, "id": "c6358766-e0e7-480c-814e-c1ccfbae8e24", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "matrix([[1, 2, 3],\n", " [4, 5, 6],\n", " [7, 8, 9]])" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A = np.matrix([[1, 2, 3], # 定义矩阵A\n", " [4, 5, 6],\n", " [7, 8, 9]])\n", "A " ] }, { "cell_type": "markdown", "id": "3a682155-7c02-4961-acb9-ab7a3c1b17e8", "metadata": {}, "source": [ "## 提取对角元素" ] }, { "cell_type": "code", "execution_count": 3, "id": "7b2ea9e5-48fa-4b8f-ad4c-6b040817a15d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([1, 5, 9])" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "a = np.diag(A) # 提取矩阵A的对角元素\n", "a" ] }, { "cell_type": "markdown", "id": "f4e2f66a-370e-410a-ab12-c1f071662dc9", "metadata": {}, "source": [ "## 构造对角矩阵" ] }, { "cell_type": "code", "execution_count": 4, "id": "eea76f59-4071-47b4-b852-740f3df7045c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([[1, 0, 0],\n", " [0, 5, 0],\n", " [0, 0, 9]])" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "A_diag = np.diag(a) # 使用对角元素a构造对角矩阵A_diag\n", "A_diag" ] }, { "cell_type": "code", "execution_count": null, "id": "85a80909-2aac-49ed-bb7a-f8cc6b80ee7d", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "ecd322f4-f919-4be2-adc3-69d28ef25e69", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.12.7" } }, "nbformat": 4, "nbformat_minor": 5 }