feat: finding nearby points of interest (POIs) for location-based ser…#34
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Mankavelda wants to merge 1 commit into
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feat: finding nearby points of interest (POIs) for location-based ser…#34Mankavelda wants to merge 1 commit into
Mankavelda wants to merge 1 commit into
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patricoferris
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Thanks @Mankavelda -- you will need to add a dune file to build main.ml. You should be able to use the tests as a basis to do that.
| open Rtree | ||
| open Printf | ||
| (* Sample Point of Interest data structure *) | ||
| type poi = { |
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How about making this it's own module:
module Poi = struct
type t = {...}
end| let ic = open_in filename in | ||
| let csv = Csv.of_channel ~has_header:true ic in | ||
| let pois = ref [] in | ||
| Csv.iter |
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To make this more functional I think we should use fold_left instead of iter + mutable state :))
| (* Load geospatial data from external csv file *) | ||
| let csv = | ||
| List.map (fun name -> name, Csv.load name) | ||
| [ "example/pois.csv"] |
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Not valid OCaml as we need an in afterwards.
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Ok @patricoferris , I will have to check and correct that
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…vices.
This PR makes the following changes
*closes issue #33
Real world example: finding nearby points of interest (POIs) for location-based services.
description
This pull request introduces a code example that shows the application of the R-tree library to solve a real-world challenge: finding nearby points of interest (POIs) for location-based services. The example demonstrates how the R-tree data structure efficiently organizes and queries geospatial data, which is vital for applications such as navigation, mapping, and location-based recommendations.
Key Components
Sample Data: The code example defines a custom data structure, poi, to represent points of interest. Each poi object includes attributes like name, latitude, and longitude, which are typical of geospatial data.
Integration with R-tree Library: The code demonstrates the seamless integration of the OCaml R-tree library. The library's functionalities, including creating an R-tree, inserting data, and performing spatial queries, are used in the example.
Data Insertion: The code inserts a list of sample POIs into the R-tree. This operation organizes the POIs spatially within the tree structure, which is essential for efficient spatial queries.
Spatial Query: To illustrate the R-tree's capabilities, the code performs a spatial query to find nearby POIs within a specified radius of a given location. The R-tree's range query functionality is employed, optimizing the process of identifying relevant points of interest.