projection

问题 I'm using OpenJPA with QueryDSL, I try to avoid manipulating Tuple objects by using the bean projections features of QueryDSL. I have for example these two Entity, with a @ManyToOne relation. @Entity public class Folder { private Long id; private String name; private String path; @ManyToOne @JoinColumn(name = "FK_FILE_ID") private File file; } @Entity public class File { private Long id; private String fileName; } When I'm executing this query : List<Folder> listFolders = query.from(folder)

问题 I'm using OpenJPA with QueryDSL, I try to avoid manipulating Tuple objects by using the bean projections features of QueryDSL. I have for example these two Entity, with a @ManyToOne relation. @Entity public class Folder { private Long id; private String name; private String path; @ManyToOne @JoinColumn(name = "FK_FILE_ID") private File file; } @Entity public class File { private Long id; private String fileName; } When I'm executing this query : List<Folder> listFolders = query.from(folder)

问题 I am trying to find a way to calculate a 2d Power Diagram in Python. For this I want to make use of the fact that a 2d power diagram can be interpreted as the intersection of a regular 3d voronoi diagram with a plane. With the SciPy Voronoi module I can calculate a 3d Voronoi diagram - is there a possibility to intersect it with a plane and convert it to a 2d diagram? 回答1: There isn't yet a power diagram capability inside of SciPy. Converting a 3D Voronoi diagram into a 2D power diagram is

问题 Problem statement I am trying to reproject 2D points to their original 3D coordinates, assuming I know the distance at which each point is. Following the OpenCV documentation, I managed to get it to work with zero-distortions. However, when there are distortions, the result is not correct. Current approach So, the idea is to reverse the following: into the following: By: Geting rid of any distortions using cv::undistortPoints Use intrinsics to get back to the normalized camera coordinates by

问题 I have coordinates, all of which should be located in DC, but I cannot figure out how to convert them from NAD 83 to latitude and longitude in R. I'm using the spTransform() function in the rgdal package and get an error about non-conformant data. library(rgdal) nad83_coords <- data.frame(x=c(396842.6, 397886.9, 398315.5, 398154.3, 398010.3), y=c(140887.1, 139847.0, 138743.9, 139534.5, 138697.3)) coordinates(nad83_coords) <- c('x', 'y') proj4string(nad83_coords) <- CRS("+init=epsg:4269")

问题 I have coordinates, all of which should be located in DC, but I cannot figure out how to convert them from NAD 83 to latitude and longitude in R. I'm using the spTransform() function in the rgdal package and get an error about non-conformant data. library(rgdal) nad83_coords <- data.frame(x=c(396842.6, 397886.9, 398315.5, 398154.3, 398010.3), y=c(140887.1, 139847.0, 138743.9, 139534.5, 138697.3)) coordinates(nad83_coords) <- c('x', 'y') proj4string(nad83_coords) <- CRS("+init=epsg:4269")

问题 I have an IQueryable whose Entity Framework 4 objects I would like to project to their DTO equivalents. One such object 'Person' is an EF4 class, and the corresponding POCO PersonP is a class I've defined. I am using Automapper to map between them. However, when I try the following code: IQueryable<Person> originalModel = _repo.QueryAll(); IQueryable<PersonP> projection = originalModel.Select(e => Mapper.Map<Person, PersonP>(e)); The projection generates this error at runtime: LINQ to

问题 I have a JPA tree structure @Entity public class Document { @Id @GeneratedValue(strategy = GenerationType.AUTO) private int id; private String text; @ManyToOne @JoinColumn(name = "parent") Document parent; @OneToMany(mappedBy = "parent", fetch = FetchType.EAGER) Set<Document> children; (getters and setters) } and a projection @Projection(name = "all", types = Document.class) public interface AllDocumentsProjection { int getId(); String getText(); Set<Document> getChildren(); } When I make a

问题 I have a 3D point cloud (XYZ) where the Z can be position or energy. I want to project them on a 2D surface in a n -by- m grid (in my problem n = m ) in a manner that each grid cell has a value of the maximum difference of Z , in case of Z being position, or a value of summation over Z , in case of Z being energy. For example, in a range of 0 <= (x,y) <= 20 , there are 500 points. Let's say the xy-plane has n -by- m partitions, e.g. 4 -by- 4 ; by which I mean in both x and y directions we

问题 Normally the definition of a projection matrix P is the 3x4 matrix which projects point from world coordinates to image/pixel coordinates. The projection matrix can be split up into: K : a 3x4 camera matrix K with the intrinsic parameters T : a 4x4 transformation matrix with the extrinsic parameters The projection matrix is then P = K * T . What are the clear definitions of the following input to OpenCV's stereoRectify: cameraMatrix1 – First camera matrix (I assume it is the instrinsic K part