import csvimport jsondef loaddata(): file = open(r'thesis.csv', 'r') # 读入论文信息文件 fileopen = csv.reader(file) header = next(fileopen) #存储第一作者的信息 first_author = [] #存储最终的学者信息 scholar = [] for row in fileopen: if row[0] not in first_author: # 第一作者统计 first_author.append(row[0]) # 由于所有的第一、第二作者加起来太多，我们只统计第一作者 scholar = first_author print("data loaded") return scholarloaddata函数用于初始化数据，载入csv文件，将所有的筛选出来的第一作者赋给scholar数组def updatelink(scholar): file1 = open(r'thesis.csv', 'r') # 再次打开论文信息文件 fileopen1 = csv.reader(file1) header1 = next(fileopen1) # 第一作者之间互相合作的次数统计的二维矩阵 link = [[0 for j in range(len(scholar))] for i in range(len(scholar))] for row in fileopen1: if row[0] in scholar: cowoker = row[2].split(';') for woker in cowoker: if woker in scholar: link[scholar.index(row[0])][scholar.index(woker)] += 1 for i in range(len(scholar)): link[i][i] = 0 print("link updated") return linkupdatelink函数用于生成一个二维数组link[][]来存储每两个学者之间的合作信息def authorinfo(scholar,link): data = [] # 用来统计每个第一作者和其他人一共合作的次数 times = [0] * len(scholar) for i in range(len(scholar)): times[i] += sum(link[i]) for j in range(len(scholar)): times[i] += link[j][i] for i in range(len(scholar)): # 统计每两个人之间的合作次数 for j in range(i + 1, len(scholar)): temp = link[i][j] + link[j][i] link[i][j], link[j][i] = temp, temp # 用来生成每个学者、每个节点的信息，适应echart所需要的格式 for i in range(len(scholar)): if times[i] != 0: person = {} person["name"] = scholar[i] person["symbolSize"] = times[i] * 5 person["category"] = i % 5 person["draggable"] = "true" person["value"] = times[i] data.append(person) print("author") return dataauthorinfo函数用于将学者的信息进行整理，获得echart所需要的节点信息，这里我们会进一步筛选掉一部分学者def linksinfo(scholar,link): links = [] for i in range(len(scholar)): # 生成每条边的信息 for j in range(i + 1, len(scholar)): if link[i][j] != 0: links.append({"source": scholar[i], "target": scholar[j], "value": link[i][j]}) print("links") return linkslinksinfo函数用于生成边的信息。if __name__=='__main__': scholar = loaddata() link = updatelink(scholar) data = authorinfo(scholar,link) links = linksinfo(scholar,link) output = {} output['data'] = data # 生成json格式的文件 output['links'] = links with open("C:\wamp64\www\project\data.json", "w") as f: # 将数据写入json文件中 json.dump(output, f, sort_keys=True, indent=4, separators=(',', ':')) print("finished")<!DOCTYPE html><html style="width: 100%;height:100%;"><head> <meta charset="utf-8"> <title>ECharts</title> <!-- 引入 echarts.js --> <script src="echarts.js"></script> <script src="http://libs.baidu.com/jquery/1.9.1/jquery.min.js"></script> <script src="dataTool.js"></script> </head><body style="width: 100%;height:100%;"> <!-- 为ECharts准备一个具备大小（宽高）的Dom --> <div id="main" style="width: 100%;height:100%;"></div> <script type="text/javascript"> // 基于准备好的dom，初始化echarts实例 var myChart = echarts.init(document.getElementById('main')); // 加载同目录下json文件中的json数据 $.getJSON("./data.json", function(linedata) { var option = { //设置整个页面的背景颜色 backgroundColor: new echarts.graphic.RadialGradient(0.3, 0.3, 0.8, [{ offset: 0, color: '#f7f8fa' }, { offset: 1, color: '#cdd0d5' }]), //设置标题 title: { text: "学者合作信息图", top: "top", left: "center" }, tooltip: {}, legend: [{ formatter: function(name) { return echarts.format.truncateText(name, 40, '14px Microsoft Yahei', '…'); }, tooltip: { show: true }, selectedMode: 'false', bottom: 20, }], //右上角的三个工具按钮 toolbox: { show: true, feature: { // magicType: { // show: true, // type: ['force', 'chord'] // }, dataView: { show: true, readOnly: true }, restore: { show: true }, saveAsImage: { show: true } } }, animationDuration: 3000, animationEasingUpdate: 'quinticInOut', //图片的形式 series: [{ name: 'scholar', type: 'graph', layout: 'force', force: { repulsion: 1000 }, //设置节点信息和边的信息 data: linedata.data, links: linedata.links, categories: [{ 'name': '分类1' }, { 'name': '分类2' }, { 'name': '分类3' }, { 'name': '分类4' }, { 'name': '分类5' }], focusNodeAdjacency: true, roam: true, label: { normal: { show: true, position: 'top', } }, //边的格式 lineStyle: { normal: { opacity: 1, width: 1, curveness: 0.1 } } }] }; myChart.setOption(option)}) </script></body></html> 
