├── .gitignore ├── Deep Learning ├── 005-邱锡鹏-神经网络与深度学习.pdf ├── LSTM │ ├── LSTM_Yao.html │ ├── LSTM_Yao.ipynb │ └── data │ │ └── MNIST │ │ └── processed │ │ └── test.pt └── LeNet │ ├── LeNet_Yao.html │ ├── LeNet_Yao.ipynb │ ├── stateparas │ ├── 0epoch_model_para.pth │ ├── 1epoch_model_para.pth │ ├── 2epoch_model_para.pth │ ├── 3epoch_model_para.pth │ ├── 4epoch_model_para.pth │ ├── 5epoch_model_para.pth │ ├── 6epoch_model_para.pth │ └── 7epoch_model_para.pth │ ├── torch.save.docx │ └── torch.save.pdf ├── FreewayTrafficModelingSurveillanceandContral ├── Answer2Homework1.pdf ├── Homework_LWR.py ├── 作业1.pdf ├── 密度三维时空图.png ├── 密度随时间变化折线图.png ├── 流量随时间变化折线图.png └── 速度三维时空图.png ├── GCN-Cora ├── GCN——一个结点是一个样本的情况（Cora数据集）.html ├── GCN——一个结点是一个样本的情况（Cora数据集）.ipynb └── Pytorch-geometric-notes-master │ ├── LICENSE │ ├── README.md │ └── costumed_graph_datasets.ipynb ├── GCN-ENZYMES ├── ENZYMES │ ├── processed │ │ ├── data.pt │ │ ├── pre_filter.pt │ │ └── pre_transform.pt │ └── raw │ │ ├── ENZYMES_A.txt │ │ ├── ENZYMES_graph_indicator.txt │ │ ├── ENZYMES_graph_labels.txt │ │ ├── ENZYMES_node_attributes.txt │ │ ├── ENZYMES_node_labels.txt │ │ └── README.txt ├── GCN.html ├── GCN.ipynb ├── GCN.zip ├── GCN │ ├── GCN.md │ └── output_13_0.png └── TUDataset A collection of benchmark datasets for learning with graphs.pdf ├── HappyTimes ├── ValentineDay │ ├── GiveHeartPit2Love.ipynb │ ├── readme.txt │ └── whitebackground.jpg └── 私家车出行特征Venism模型 │ ├── Current.vdf │ ├── 基于系统动力学的哈尔滨市私人小汽车出行特征建模分析_宋成举.pdf │ ├── 私人小汽车出行特征分析流图.2mdl │ └── 私人小汽车出行特征分析流图.mdl ├── Homework ├── Dijkstra.py └── README.md ├── LICENSE ├── README.md ├── TransBigData画图学习 ├── TransBigData.html ├── TransBigData.ipynb ├── hzpoi.txt ├── poi爬取_from师弟 │ ├── POI 爬虫.py │ └── amap_poicode.xlsx └── 以前的plot_map包 │ ├── plot_map.py │ ├── tileimg │ ├── 4-12-3415-1683-256.png │ ├── 4-12-3415-1684-256.png │ ├── 4-12-3415-1685-256.png │ ├── 4-12-3415-1686-256.png │ ├── 4-12-3415-1687-256.png │ ├── 4-12-3415-1688-256.png │ ├── 4-12-3416-1683-256.png │ ├── 4-12-3416-1684-256.png │ ├── 4-12-3416-1685-256.png │ ├── 4-12-3416-1686-256.png │ ├── 4-12-3416-1687-256.png │ ├── 4-12-3416-1688-256.png │ ├── 4-12-3417-1683-256.png │ ├── 4-12-3417-1684-256.png │ ├── 4-12-3417-1685-256.png │ ├── 4-12-3417-1686-256.png │ ├── 4-12-3417-1687-256.png │ └── 4-12-3417-1688-256.png │ ├── 点位图-500dpi.png │ ├── 点位图可视化.html │ ├── 点位图可视化.ipynb │ └── 说明.txt ├── python GTWR ├── Data_example.csv ├── GTWR.html ├── GTWR.ipynb ├── Geographical and Temporal Weighted Regression.pdf ├── MGWR A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity.pdf ├── gtwr-1.0.1.tar.gz ├── gtwr-1.0.1 │ ├── PKG-INFO │ ├── build │ │ └── lib │ │ │ └── gtwr │ │ │ ├── __init__.py │ │ │ ├── diagnosis.py │ │ │ ├── kernels.py │ │ │ ├── model.py │ │ │ ├── search.py │ │ │ ├── sel.py │ │ │ ├── setup.py │ │ │ └── testing.py │ ├── dist │ │ └── gtwr-1.0.1-py3.7.egg │ ├── gtwr.egg-info │ │ ├── PKG-INFO │ │ ├── SOURCES.txt │ │ ├── dependency_links.txt │ │ └── top_level.txt │ ├── gtwr │ │ ├── __init__.py │ │ ├── diagnosis.py │ │ ├── kernels.py │ │ ├── model.py │ │ ├── search.py │ │ ├── sel.py │ │ ├── setup.py │ │ └── testing.py │ ├── setup.cfg │ └── setup.py ├── mgtwr-1.0.4.tar.gz ├── mgtwr-1.0.4 │ ├── PKG-INFO │ ├── build │ │ └── lib │ │ │ └── mgtwr │ │ │ ├── __init__.py │ │ │ ├── diagnosis.py │ │ │ ├── gtwr.py │ │ │ ├── kernels.py │ │ │ ├── search.py │ │ │ ├── sel_bws.py │ │ │ └── setup.py │ ├── dist │ │ └── mgtwr-1.0.4-py3.7.egg │ ├── mgtwr.egg-info │ │ ├── PKG-INFO │ │ ├── SOURCES.txt │ │ ├── dependency_links.txt │ │ └── top_level.txt │ ├── new_mgtwr │ │ ├── __init__.py │ │ ├── __pycache__ │ │ │ ├── __init__.cpython-37.pyc │ │ │ ├── diagnosis.cpython-37.pyc │ │ │ ├── gtwr.cpython-37.pyc │ │ │ ├── kernels.cpython-37.pyc │ │ │ ├── new_gtwr.cpython-37.pyc │ │ │ ├── search.cpython-37.pyc │ │ │ └── sel_bws.cpython-37.pyc │ │ ├── diagnosis.py │ │ ├── gtwr.py │ │ ├── kernels.py │ │ ├── search.py │ │ ├── sel_bws.py │ │ └── setup.py │ ├── setup.cfg │ └── setup.py └── 毕业论文4.12.docx ├── python业务代码 ├── AHP层次分析法 │ ├── AHP.html │ └── AHP.ipynb ├── DynamicTimeWarping │ └── DTW.py ├── K-FoldCVNeutralNetwork │ ├── DealData.csv │ ├── neutralnetwork.py │ └── readme.txt ├── TOPSIS.ipynb ├── apriori.py ├── lda_experiment │ ├── LDA_Experiment.html │ ├── LDA_Experiment.ipynb │ └── LDA_Experiment.md ├── networkx-pagerank │ ├── networkx-pagerank.html │ └── networkx-pagerank.ipynb ├── pyecharts-geo │ └── pyecharts-geo │ │ ├── BMAP.json │ │ ├── Geovisua.html │ │ ├── Geovisua.ipynb │ │ ├── bmap_base.html │ │ ├── 不存在map_style时的情况.png │ │ ├── 存在map_style时的情况.png │ │ ├── 第一张图.png │ │ └── 销售数量可视化.html ├── python批量将csv导入mysql │ ├── importData.py │ └── readme.md ├── xgboost │ ├── TryXgboostForHappy.html │ ├── TryXgboostForHappy.ipynb │ ├── data │ │ ├── rf.py │ │ ├── test.csv │ │ ├── titanic.csv │ │ └── train.csv │ └── xgboost-0.90-cp35-cp35m-win_amd64.whl ├── 公交出行数据采集 │ ├── AMap_adcode_citycode.xlsx │ ├── __pycache__ │ │ └── basics.cpython-37.pyc │ ├── basics.py │ ├── data │ │ ├── bus_0.txt │ │ └── bus_1.txt │ ├── destination.txt │ ├── origin.txt │ ├── route │ │ ├── line_0.txt │ │ └── line_1.txt │ ├── 公交出行数据采集.html │ ├── 公交出行数据采集.ipynb │ └── 公交出行数据采集.md ├── 地图散点可视化 │ ├── 1 │ │ ├── Data.csv │ │ ├── MapVisualization.py │ │ ├── redult.html │ │ └── 数量.html │ ├── 2 │ │ ├── Data.xlsx │ │ ├── final_graph.html │ │ ├── plot_city_machine.py │ │ └── xxxx售出数量.html │ └── readme.txt ├── 粒子群算法geatpy │ ├── report.log │ ├── 粒子群算法.ipynb │ └── 粒子群算法.md ├── 经纬度计算距离.py ├── 遗传算法 │ ├── 遗传算法.html │ ├── 遗传算法.ipynb │ └── 遗传算法.md └── 验证性因子分析CFA │ ├── CFA.html │ ├── CFA.ipynb │ └── factor_analyzer-master.zip ├── python算法 ├── 01链表.py ├── 01链表.txt ├── 02无序链表中移除重复项.py ├── 03计算两个单链表所代表的数之和.py ├── 04对链表进行重新排序.py ├── 05如何找出单链表中的倒数第k个元素.py ├── 06如何将单链表向右旋转k个位置.py ├── 07如何检测一个较大的单链表是否有环.py ├── 08如何把链表相邻元素翻转.py ├── 09如何把链表以k个结点为一组进行翻转.py ├── 1.12方法1-如何展开链接列表.py ├── 1.12方法2-如何展开链接列表.py ├── 10如何合并两个有序链表.py ├── 11如何在只给定单链表中某个结点的指针的情况下删除该节点.py ├── 12如何判断两个单链表(无环)是否交叉.py ├── 2.10如何对数组中找出满足a+b=c+d的两个数对.py ├── 2.1如何实现栈(数组实现).py ├── 2.1如何实现栈(链表实现).py ├── 2.2如何实现队列(数组实现).py ├── 2.2如何实现队列(链表实现).py ├── 2.3如何翻转栈的所有元素.py ├── 2.4如何根据入栈序列判断可能的出栈序列.py ├── 2.5如何用O(1)的时间复杂度求栈中最小元素.py ├── 2.6如何用两个栈模拟队列操作.py ├── 2.7如何设计一个排序系统.py ├── 2.8如何实现URL缓存方案.py ├── 2.9如何从给定的车票中找出旅程.py ├── 3.10如何在二叉树中找出与输入整数相等的所有路径.py ├── 3.11如何对二叉树进行镜像反转.py ├── 3.12如何在二叉排序树中找出第一个大于中间值的结点.py ├── 3.13如何在二叉树中找出路径最大的和.py ├── 3.14如何实现反向DNS查找缓存.py ├── 3.2如何把一个有序整数数组放到二叉树中.py ├── 3.3如何从顶部开始逐层打印二叉树结点数据.py ├── 3.4如何求一棵二叉树的最大子树和.py ├── 3.5如何判断两棵二叉树是否相等.py ├── 3.6如何把二叉树转换为双向链表.py ├── 3.7如何判断一个数组是否是二元查找树后序遍历的序列.py ├── 3.8.2如何计算二叉树中两个结点的距离.py ├── 3.8如何找出排序二叉树上任意两个结点的最近共同父节点.py ├── 3.9如何复制二叉树.py ├── 4.1.2求数组中重复出现的自然序列.py ├── 4.10如何求数组连续最大和.py ├── 4.11如何找出数组中出现1次的数.py ├── 4.12如何对数组进行旋转.py ├── 4.13如何在不排序的情况下求数组中的中位数.py ├── 4.14如何求集合的所有子集.py ├── 4.15如何对数组进行循环位移.py ├── 4.16如何在有规律的二维数组中进行高效的数据查找.py ├── 4.17如何寻找最多的覆盖点.py ├── 4.18如何判断请求能否在给定的存储条件下完成.py ├── 4.19如何按照要求构造新的数组.py ├── 4.1如何找出数组中唯一的重复元素.py ├── 4.20如何获取最好的矩阵链相乘方法.py ├── 4.21如何求解迷宫问题.py ├── 4.22如何从三个有序数组中找出它们的公共元素.py ├── 4.23如何求两个有序集合的交集.py ├── 4.24如何对有大量重复的数字的数组排序.py ├── 4.25如何对任务进行调度.py ├── 4.26如何对磁盘进行分区.py ├── 4.2如何查找数组中元素的最大值和最小值.py ├── 4.3如何找出旋转数组的最小元素.py ├── 4.4如何找出数组中丢失的数.py ├── 4.5如何找出数组中出现奇数次的数.py ├── 4.6如何找出数组中第k小的数.py ├── 4.7如何求数组中两个元素的最小距离.py ├── 4.8如何求解最小三元组距离.py ├── 4.9如何求数组中绝对值最小的数.py ├── 5.10如何求字符串里的最长回文子串.py ├── 5.11如何按照给定的字母序列对字符数组排序.py ├── 5.12如何判断一个字符串是否包含重复字符.py ├── 5.13如何找到由其他单词组成的最长单词.py ├── 5.14如何统计字符串中连续的重复字符个数.py ├── 5.15如何求最长递增子序列的长度.py ├── 5.16求一个串中出现的第一个最长重复子串.py ├── 5.17如何求解字符串中字典序最大的子序列.py ├── 5.18如何判断一个字符串是否由另外一个字符串旋转得到.py ├── 5.19如何求字符串的编辑距离.py ├── 5.1如何求一个字符串的所有排列.py ├── 5.20如何在二维数组中寻找最短路线.py ├── 5.21如何截取包含中文的字符串.py ├── 5.22如何求相对路径.py ├── 5.23如何查找到达目标词的最短链长度.py ├── 5.2如何求两个字符串的最长公共子串.py ├── 5.3如何对字符串进行反转.py ├── 5.4如何判断两个字符串是否为换位字符串.py ├── 5.5如何判断两个字符串的包含关系.py ├── 5.6如何对由大小写字母组成的字符数组排序.py ├── 5.8如何判断字符串是否是整数.py ├── 5.9如何实现字符串的匹配.py ├── 6.10如何求二进制数中1的个数.py ├── 6.11如何找最小的不重复数.py ├── 6.12如何计算一个数的n次方.py ├── 6.13如何在不能使用库函数的条件下计算n的平方根.py ├── 6.14如何不使用^操作实现异或运算.py ├── 6.15如何不使用循环输出1到100.py ├── 6.1如何判断一个自然数是否是某个数的平方.py ├── 6.2如何判断一个数是否为2的n次方.py ├── 6.3如何不使用除法操作符实现两个正整数的除法.py ├── 6.4如何只使用+=操作符实现加减乘除运算.py ├── 6.5如何根据已知随机数生成函数计算新的随机数.py ├── 6.6如何判断1024!末尾有多少个0.py ├── 6.7如何按要求比较两个数的大小.py ├── 6.8如何求有序数列的第1500个数的值.py ├── 6.9如何把十进制数(long 型)分别以二进制和十六进制形式输出.py ├── 7.1如何求数字的组合.py ├── 7.2如何拿到最多金币.py ├── 7.3如何求正整数n所有可能的整数组合.py ├── 7.4如何用一个随机函数得到另外一个随机函数.py ├── 7.5如何等概率地从大小为n的数组中选取m个整数.py ├── 7.6如何组合1,2,5这三个数使其和为100.py ├── 7.7如何判断还有几盏灯泡亮着.py ├── 8.1如何进行选择排序.py ├── 8.2如何进行插入排序.py ├── 8.3如何进行冒泡排序.py ├── 8.4如何进行归并排序.py ├── 8.5如何进行快速排序.py ├── 8.6如何进行希尔排序.py ├── 8.7如何进行堆排序.py ├── 8.8如何进行基数排序.py ├── 9.10如何找出排名前500的数.py ├── 9.1如何从大量的url中找出相同的url.py ├── 9.2如何从大量数据中找出高频词.py ├── 9.3如何找出访问百度最多的IP.py ├── 9.4如何在大量的数据中找出不重复的整数.py ├── 9.5如何在大量的数据中判断一个数是否存在.py ├── 9.6如何查询最热门的查询串.py ├── 9.7如何统计不同电话号码的个数.py ├── 9.8如何从5亿个数中找出中位数.py ├── 9.9如何按照query的频度排序.py ├── readme.txt ├── 中位数.py ├── 恰饭.py ├── 恰饭和中位数题目.docx └── 讨论课ppt.pptx ├── rough set theory ├── A new version of the rule induction system LERS.pdf ├── 基于不完备决策表的属性约简及规则获取算法的研究_乔丽娟.caj └── 粗糙集理论与应用研究综述_王国胤.pdf ├── sklearn特征选择 ├── SVMand随机森林做特征选择.html └── SVMand随机森林做特征选择.ipynb ├── 兴趣面数据采集 ├── AMap_adcode_citycode.xlsx ├── basics.py ├── boundry.txt ├── boundry2.txt ├── browsermob-proxy-2.1.4-bin.zip ├── chromedriver_win32.zip ├── plot_map.py ├── 兴趣面采集与分析.html ├── 兴趣面采集与分析.ipynb ├── 杭州市公园POI.txt └── 杭州市行政规划 │ ├── 杭州市行政区划.cpg │ ├── 杭州市行政区划.dbf │ ├── 杭州市行政区划.shp │ └── 杭州市行政区划.shx ├── 电警点位分布folium ├── 点位分布可视化.html ├── 点位分布可视化.ipynb └── 输入说明.jpg ├── 空间计量学习 ├── 01数据整理及权重矩阵构建 │ ├── 01数据整理及权重矩阵构建.html │ ├── 01数据整理及权重矩阵构建.ipynb │ └── 01数据整理及权重矩阵构建.md ├── 02距离权重矩阵 │ ├── 02距离权重矩阵.html │ ├── 02距离权重矩阵.ipynb │ └── 02距离权重矩阵.zip └── 03空间计量模型实战 │ ├── 11_regression.html │ ├── 11_regression.ipynb │ ├── 11_regression.zip │ ├── neighbourhoods.geojson │ ├── regression_db.geojson │ ├── 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