r-tree

In MiniGUi, I can see db.index . How do I set it to tree.spatial.rstarvariants.rstar.RStartTreeFactory via Java code? I have implemented: params.addParameter(AbstractDatabase.Parameterizer.INDEX_ID,tree.spatial.rstarvariants.rstar.RStarTreeFactory); For the second parameter of addParameter() function tree.spatial...RStarTreeFactory class not found // Setup parameters: ListParameterization params = new ListParameterization(); params.addParameter( FileBasedDatabaseConnection.Parameterizer.INPUT_ID, fileLocation); params.addParameter(AbstractDatabase.Parameterizer.INDEX_ID, RStarTreeFactory.class

How can R* Tree be implemented as a persistent (disk based) one? What is the architecture of the file for saving the R* Tree index or for saving leaf values? Notes: In addition how insert, update and delete operations can be performed in such a persistent R* Tree? Notes II: I have implemented an in-memory R-Tree with bulk load functionality. But I think that is totally irrelevant when we speak about disk-based ones. If you need to have an on-disk R-Tree index, I would suggest using Spatialite or Postgis . Spatialite is lightweight and easy to embed in a standalone application. Alternatively,

Why is this not returning a count of number of points in each neighbourhoods (bounding box)? import geopandas as gpd def radius(points_neighbour, points_center, new_field_name, r): """ :param points_neighbour: :param points_center: :param new_field_name: new field_name attached to points_center :param r: radius around points_center :return: """ sindex = points_neighbour.sindex pts_in_neighbour = [] for i, pt_center in points_center.iterrows(): nearest_index = list(sindex.intersection((pt_center.LATITUDE-r, pt_center.LONGITUDE-r, pt_center.LATITUDE+r, pt_center.LONGITUDE+r))) pts_in_this

I'm trying to understand how to implement an R-Tree which will be used for "selecting" a set of geometrical objects contained in a bounding rectangle. I checked out the article on Wikipedia, which shows an example of data layout as a B-Tree . I could write a B-Tree and use it to write an R-Tree, but these are two complicated data structures which I'd have to debug, test, etc. I would rather reuse an existing tree implementation (std::set/multiset) and provide the sorting operation. Assuming I have the following interface for my Shapes: class Shape { public: Shape(); virtual ~Shape(); const

I have a simplified map of a city that has streets in it as linestrings and addresses as points. I need to find closest path from each point to any street line. I have a working script that does this, but it runs in polynomial time as it has nested for loop. For 150 000 lines (shapely LineString) and 10 000 points (shapely Point), it takes 10 hours to finish on 8 GB Ram computer. The function looks like this (sorry for not making it entirely reproducible): import pandas as pd import shapely from shapely import Point, LineString def connect_nodes_to_closest_edges(edges_df , nodes_df, edges_geom

Possible Duplicate: Is there any documented free R-Tree implementation for .NET? Are there any R-Tree implementations in F#? Assumptions are: no need for insertion or deletion, fixed set of Geo-Fences (regions). Needs are: very fast search time. Thank you Daniel Here's a quick translation of this one in OCaml to F#. namespace RTree open System module Envelope = type t = float * float * float * float let ranges_intersect a b a' b' = a' <= b && a <= b' let intersects (x0, x1, y0, y1) (x0', x1', y0', y1') = (* For two envelopes to intersect, both of their ranges do. *) ranges_intersect x0 x1 x0'

I am having huge set of 2D line segments. So, I know; Line number, Begin (X,Y,Z) and End (x,Y,Z) of each line segment. I want to get proximity line segments for a given line segment. Likewise for all. To find the proximity I can apply this If I say my data it is as; So, at the end I want to get proximity lines as a vector for each line segment . I heard this type of vector of vector can be taken with r-tree data structures. I was searching it but still could not find the relevant one for me. Also I looked in opencv, there is a r-tree but it says something about classifier, and training phase..

I was searching the last few days for a stable implementation of the R-Tree with support of unlimited dimensions (20 or so would be enough). I only found this http://sourceforge.net/projects/jsi/ but they only support 2 dimensions. Another Option would be a multidimensional implementation of an interval-tree. Maybe I'm completly wrong with the idea of using an R-Tree or Intervall-Tree for my Problem so i state the Problem in short, that you can send me your thoughts about this. The Problem I need to solve is some kind of nearest-neighbour search. I have a set of Antennas and rooms and for each

I found some open source R-Tree implementations in C#, but none with documentation nor signs of being used by someone else than the developer. Jader Dias The NetTopologySuite is a JTS port to C# and it contains a STRtree class which is a read-only R-Tree I know of none, but I would point out that libraries like this tend to: Get written (normally with some bugs). Bugs get ironed out though use. All active bugs are fixed Optional 'Latent' bugs which could never happen due to previous semantics of the platform on which the library operates crop up if the platform changes in some way. Thus lack