希尔伯特曲线 适用于Java的实用程序 将沿N维希尔伯特曲线的距离变换为一个点并返回。 边界框（N维）查询支持（边界框映射到hilbert索引上用于单列查找的多个间隔） 特征 支持多种尺寸 方法链 二维渲染 与基准jmh 状态：部署到Maven的中央 Maven的包括 也见。 背景 甲是首先由大卫·希尔伯特在1891年描述的连续的分形空间填充曲线。 该库支持近似希尔伯特曲线。 H n中是第n个近似希尔伯特曲线，是一个长度为1的2 n -1个直线段的路径。 希尔伯特曲线可用于索引多个维度，并具有有用的局部性。 简而言之， 索引接近索引的点将接近与该索引对应的点。 图1. 2D希尔伯特具有1至6个比特曲线（H 1至H 6） HilbertCurveRenderer . renderToFile(bits, 200 , filename); 图2. 2D Hilbert曲

亚马逊上有一本中译本的书，鉴于大家普遍反映译者翻译的很差，共享下原版的电子版。 经典好书也需要能够理解其中内容的人才能体现其价值所在。给需要的童鞋提供资源。

网格-时空多维网格数据的信息学 Riley Hales开发了一个Python工具，用于从多维数据数组中提取时间序列子集，这是杨百翰大学土木与环境工程硕士学位论文的一部分。

Spatial_Data_Analysis_Theory_and_Practice_by_Robert_Haining Spatial Data Analysis: Theory and Practice provides a broad-ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy-related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modelling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master’s level students, but it also contains sufficient challenging material that it will be of interest to geographers, social scientists and economists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis.

spatial.rar

oracle.spatial的jar包，包括geometry、util等

Introduction Spatial Data Modeller, SDM, is a collection of tools for adding categorical maps with interval, ordinal, or ratio scale maps to produce a predictive map of where something of interest is likely to occur. This release of SDM has been modified to only work with ArcGIS 9.3. The SDM modifications in this version have to do with changes in Band Collection Statistics and intersection of points in rasters. These errors caused by changes in Band Collection Statistics and intersection of points in rasters can be subtle; tools such as Calculate Weights, Area Frequency, NN Input Files, MS Large and MS Small compute had to be modified. All of the tools have help files that include references to publications discussing the applications of the methods implemented in the tool. Several of the tools create output rasters, tables, or files that require the user to enter a name. Default values are provided in most cases to serve as suggestions of the style of naming that has been found useful. These names, following ArcGIS conventions, can be changed to meet the user’s needs. To make all of the features of SDM work properly it is required that several Environment parameters are set. See the discussion of Environment Settings below for the details. The Weights of Evidence, WofE, and Logistic Regression, LR, tools addresses area as the count of unit cells. It is assumed in the WofE and LR tools that the data has spatial units of meters. If your data has other spatial units, these WofE and LR tools may not work properly.

本文工作实现了两个模型： Spatial Dropout-GRU模型TextCNN模型，并分别测试了其情感分类效果。 开发环境：python3.6.5、tensorflow==1.12、keras==2.2.4 数据集： 1)训练集。包含2W条左右中文电影评论，其中正负向评论各1W条左右。 2)测试集。包含2w条左右中文电影评论，其中正负向评论各1W条左右。

空域金字塔完整的MATLAB代码，非常好用，结果很好

matlab精度检验代码场景分类的空间金字塔匹配 在MATLAB中实现 该项目针对计算机视觉和图像处理类CSE573完成，所有必需的说明均包含在说明pdf文件中。 该系统使用“词袋”方法及其“空间金字塔扩展”将给定图像分类为8种场景。 以下是一些关键点： 该系统已使用来自8个场景的1600幅图像进行了训练，这些场景分别是art_gallery，computer_room，garden，ice_scating，library，mountain，ocean，ocean_court。 在总共160张测试图像中，它具有48.125％的正确分类图像的总体准确度。 整个实现代码在MATLAB文件夹中。 测试和培训数据位于数据文件夹中。