{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# 记录数组" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "记录数组(`record array`)与结构数组类似:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "质点类型:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ "partical_dtype = np.dtype([('mass', 'float'), \n", " ('velocity', 'float')])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "生成记录数组要使用 `numpy.rec` 里的 `fromrecords` 方法:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from numpy import rec\n", "\n", "particals_rec = rec.fromrecords([(1,1), (1,2), (2,1), (1,3)], \n", " dtype = partical_dtype)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "rec.array([(1.0, 1.0), (1.0, 2.0), (2.0, 1.0), (1.0, 3.0)], \n", " dtype=[('mass', '