Initial commit
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MIT License
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Copyright (c) 2023 Jan-Lukas Else
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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# Cell Location Map using Mozilla Location Service
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This repository provides code to display the cell locations using the Mozilla Location Service. The code extracts cell data from a CSV export file and generates an interactive map with markers representing the cell locations.
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## Prerequisites
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- Go programming language
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- Access to a [cell export file from the Mozilla Location Service](https://location.services.mozilla.com/downloads)
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## Installation
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1. Clone the repository:
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```shell
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git clone https://git.jlel.se/jlelse/mls.git
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```
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2. Change to the project directory:
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```shell
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cd mls
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```
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## Usage
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### Step 1: Filter Cell Data
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To filter the cell data and generate an output file, run the following command:
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```shell
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go run ./filter/main.go <input CSV file> <output CSV file> <radio> <mcc> <network> <min samples> <output columns>
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```
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- `<input CSV file>`: Path to the input CSV file containing the cell data.
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- `<output CSV file>`: Path to the output CSV file where the filtered data will be saved.
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- `<radio>`: The desired radio type (e.g., LTE).
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- `<mcc>`: The desired Mobile Country Code (e.g., 262 for Germany).
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- `<network>`: The desired network code (e.g., 3 for o2-de).
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- `<min samples>`: The minimum number of samples required for a cell to be included.
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- `<output columns>`: Space-separated list of columns to include in the output.
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Example:
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```shell
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go run ./filter/main.go ./MLS-full-cell-export.csv ./output.csv LTE 262 3 100 lon lat created updated cell
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```
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### Step 2: Generate Map
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To generate an HTML map with the filtered cell data, run the following command:
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```shell
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go run ./web/main.go <input CSV file> <output HTML file>
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```
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- `<input CSV file>`: Path to the input CSV file containing the filtered cell data with the columns lon,lat,created,updated,cell.
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- `<output HTML file>`: Path to the output HTML file where the map will be saved.
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Example:
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```shell
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go run ./web/main.go ./output.csv ./map.html
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```
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## Acknowledgments
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The code in this repository is based on the [Mozilla Location Service](https://location.services.mozilla.com/) and leverages the following open-source libraries:
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- [Leaflet](https://leafletjs.com/) (version 1.9.4): An open-source JavaScript library for interactive maps.
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- [Leaflet.markercluster](https://github.com/Leaflet/Leaflet.markercluster) (version 1.4.1): A plugin for Leaflet that provides clustering functionality for markers.
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The idea for this project was inspired by the [CellInspector Map](https://mls.maxomagier.de/map.html).
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## License
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This project is licensed under the [MIT License](LICENSE).
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package main
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import (
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"encoding/csv"
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"fmt"
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"io"
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"os"
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)
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func main() {
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// Check if the correct number of command-line arguments is provided
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if len(os.Args) < 6 {
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fmt.Println("Usage: go run main.go <input CSV file> <output CSV file> <radio> <mcc> <network> <min samples> <output columns>")
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return
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}
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// Get the command-line arguments
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inputFile := os.Args[1]
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outputFile := os.Args[2]
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desiredRadio := os.Args[3]
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desiredMCC := os.Args[4]
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desiredNetwork := os.Args[5]
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desiredMinSamples := os.Args[6]
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desiredColumns := os.Args[7:]
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// Open the input CSV file
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input, err := os.Open(inputFile)
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if err != nil {
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fmt.Println("Error opening the input file:", err)
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return
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}
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defer input.Close()
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// Create the output CSV file
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output, err := os.Create(outputFile)
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if err != nil {
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fmt.Println("Error creating the output file:", err)
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return
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}
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defer output.Close()
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// CSV reader and writer initialization
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reader := csv.NewReader(input)
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writer := csv.NewWriter(output)
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// Read the header row to get the column indices
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header, err := reader.Read()
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if err != nil {
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fmt.Println("Error reading CSV header:", err)
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return
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}
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radioIndex := findColumnIndex(header, "radio")
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mccIndex := findColumnIndex(header, "mcc")
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netIndex := findColumnIndex(header, "net")
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samplesIndex := findColumnIndex(header, "samples")
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// Find the indices of the desired columns
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desiredIndices := make([]int, len(desiredColumns))
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for i, column := range desiredColumns {
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desiredIndices[i] = findColumnIndex(header, column)
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if desiredIndices[i] == -1 {
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fmt.Println("Column not found:", column)
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return
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}
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}
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// Write the header row to the output file
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err = writer.Write(desiredColumns)
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if err != nil {
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fmt.Println("Error writing the header row:", err)
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return
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}
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// Read the CSV data line by line
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for {
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row, err := reader.Read()
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if err == io.EOF {
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break
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} else if err != nil {
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fmt.Println("Error reading CSV data:", err)
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return
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}
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// Check the filter criteria
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radio := row[radioIndex]
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mcc := row[mccIndex]
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net := row[netIndex]
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samples := row[samplesIndex]
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if radio == desiredRadio && mcc == desiredMCC && net == desiredNetwork && samples >= desiredMinSamples {
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// Extract the desired columns based on indices
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filteredRow := make([]string, len(desiredIndices))
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for i, index := range desiredIndices {
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filteredRow[i] = row[index]
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}
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// Write the row to the output file
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err := writer.Write(filteredRow)
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if err != nil {
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fmt.Println("Error writing the row:", err)
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return
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}
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}
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}
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// Write CSV writer data to the file
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writer.Flush()
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if err := writer.Error(); err != nil {
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fmt.Println("Error writing the output file:", err)
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return
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}
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fmt.Println("Filtering completed.")
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}
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// Helper function to find the index of a column name in the header row
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func findColumnIndex(header []string, columnName string) int {
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for i, name := range header {
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if name == columnName {
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return i
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}
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}
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return -1
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}
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package main
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import (
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"encoding/csv"
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"fmt"
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"log"
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"os"
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"strconv"
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"strings"
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"time"
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)
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const (
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leafletVersion = "1.9.4"
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markerClusterVersion = "1.4.1"
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htmlTemplateStart = `<!DOCTYPE html>
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<html>
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<head>
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<title>Location Map</title>
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<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@%s/dist/leaflet.css" />
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<link rel="stylesheet" href="https://unpkg.com/leaflet.markercluster@%s/dist/MarkerCluster.css" />
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<link rel="stylesheet" href="https://unpkg.com/leaflet.markercluster@%s/dist/MarkerCluster.Default.css" />
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<style>
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#map {
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height: 800px;
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}
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</style>
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</head>
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<body>
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<div id="map"></div>
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<script src="https://cdn.jsdelivr.net/npm/leaflet@%s/dist/leaflet.js"></script>
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<script src="https://unpkg.com/leaflet.markercluster@%s/dist/leaflet.markercluster.js"></script>
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<script>
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var map = L.map('map').setView([0, 0], 2);
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L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', {
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attribution: 'Map data © <a href="https://www.openstreetmap.org/">OpenStreetMap</a> contributors',
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maxZoom: 18,
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}).addTo(map);
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var markers = L.markerClusterGroup();
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`
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htmlTemplateEnd = `
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map.addLayer(markers);
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</script>
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</body>
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</html>`
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)
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func main() {
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if len(os.Args) != 3 {
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fmt.Println("Usage: go run main.go <input CSV file (needs lon,lat,created,updated,cell)> <output HTML file>")
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return
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}
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inputFile := os.Args[1]
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outputFile := os.Args[2]
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// Open the CSV file
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file, err := os.Open(inputFile)
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if err != nil {
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log.Fatal(err)
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}
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defer file.Close()
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// Read the CSV records
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reader := csv.NewReader(file)
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records, err := readCSVRecords(reader)
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if err != nil {
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log.Fatal(err)
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}
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// Generate the HTML
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html := generateHTML(records)
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// Save the HTML to a file
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err = writeHTMLToFile(outputFile, html)
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if err != nil {
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log.Fatal(err)
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}
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fmt.Printf("Map generated successfully and saved to %s.\n", outputFile)
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}
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func readCSVRecords(reader *csv.Reader) ([][]string, error) {
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reader.Comma = ',' // Set the delimiter to comma explicitly
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records, err := reader.ReadAll()
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if err != nil {
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return nil, err
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}
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// Remove the header row
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if len(records) > 0 {
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records = records[1:]
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}
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return records, nil
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}
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func generateHTML(records [][]string) string {
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var htmlBuilder strings.Builder
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htmlBuilder.WriteString(fmt.Sprintf(htmlTemplateStart, leafletVersion, markerClusterVersion, markerClusterVersion, leafletVersion, markerClusterVersion))
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for _, record := range records {
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// Parse longitude and latitude
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lon, err := strconv.ParseFloat(record[0], 64)
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if err != nil {
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log.Fatalf("Error parsing longitude: %v\nLongitude value: %s\n", err, record[0])
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}
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lat, err := strconv.ParseFloat(record[1], 64)
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if err != nil {
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log.Fatalf("Error parsing latitude: %v\nLatitude value: %s\n", err, record[1])
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}
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// Get created and updated timestamps
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created := record[2]
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updated := record[3]
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cell := record[4]
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htmlBuilder.WriteString(fmt.Sprintf(`
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var marker = L.marker([%f, %f]);
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marker.bindTooltip("Created: %s<br />Updated: %s<br />Cell: %s");
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markers.addLayer(marker);
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`, lat, lon, formatTimestamp(created), formatTimestamp(updated), cell))
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}
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htmlBuilder.WriteString(htmlTemplateEnd)
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return htmlBuilder.String()
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}
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func formatTimestamp(timestamp string) string {
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// Parse the Unix timestamp string to an integer
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unixTime, err := strconv.ParseInt(timestamp, 10, 64)
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if err != nil {
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return "" // Return an empty string if parsing fails
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}
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// Convert the Unix timestamp to a time.Time value
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timeValue := time.Unix(unixTime, 0)
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// Format the time
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isoFormatted := timeValue.Format(time.RFC3339)
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return isoFormatted
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}
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func writeHTMLToFile(filename string, html string) error {
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file, err := os.Create(filename)
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if err != nil {
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return err
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}
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defer file.Close()
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_, err = file.WriteString(html)
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if err != nil {
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return err
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}
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return nil
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}
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