Export data

The simulator provides tools for exporting data automatically. An export section on the simulation file instructs which data is considered interesting, and should be thus exported with the selected sampling frequency. Data can be exported separately for each node, or can be aggregated on the fly using any univariate statistic function (e.g., mean, sum, product, percentile, median…). The treatment of missing or non-finite values can be specified as well. Results are exported in comma-separated values files, easily importable in a variety of data analysis tools.

Data export is realized by Exporters. Exporters are defined in the export section of the configuration, by specifying their type, their constructor parameters, and the data they should export. The elements under data must be instanceable implementations of Extractor.

Export data as CSV

Alchemist can export data to a custom comma-separated-values format. This is the classic way data is exported from the simulator, and relies on CSVExporter.

Examples

Export of the output of a Protelis program every 3 simulated seconds:
Click to show / hide code
```
incarnation: protelis
  export:
    - type: CSVExporter
      parameters:
        fileNameRoot: "test_export_interval"
        interval: 3.0
      data:
        - time
        - molecule: "default_module:default_program"
  
```
Export data to both a csv file and a MongoDB instance:
Click to show / hide code
```
incarnation: protelis
  export:
    - type: CSVExporter
      parameters:
        fileNameRoot: "test_exporters_loading"
        interval: 2.0
      data:
        - time
        - molecule: "default_module:default_program"
  
    - type: MongoDBExporter
      parameters:
        uri: "mongodb://localhost:27017/"
        dbName: "test"
        interval: 2.5
      data:
        - time
  
```
Export of the MeanSquaredError of some custom properties:
Click to show / hide code
```
incarnation: protelis
    export:
      - type: CSVExporter
        parameters: ["test-custom-export"]
        data:
          - type: MeanSquaredError
            parameters: [ "A", "A", product, "A", "A" ]
    
```

Export of the output of a Protelis program, values generated from nodes get accumulated into mean, max, min, variance, and median:

Click to show / hide code

incarnation: protelis
  variables:
    zoom: &zoom
      formula: 0.1
    image_name: { formula: "'chiaravalle.png'" }
    image_path: &image_path
      language: kotlin
      formula: >
        import java.io.File
        File("../..").walkTopDown().find { image_name in it.name }?.absolutePath ?: image_name      
    walking_speed: &walk-speed { default: 1.4, min: 1, max: 2, step: 0.1 }
    seed: &seed { default: 0, min: 0, max: 99, step: 1 }
    scenario_seed: &scenario_seed { formula: (seed + 31) * seed }
    people_count: &people_count
      type: GeometricVariable
      parameters: [300, 50, 500, 9]
  seeds: { simulation: *seed, scenario: *scenario_seed}
  export:
    - type: CSVExporter
      parameters:
        fileNameRoot: "00-testing_csv_export"
      data:
        - time
        - molecule: "default_module:default_program"
          aggregators: [ mean, max, min, variance, median ]
          value-filter: onlyfinite
    - type: CSVExporter
      parameters:
        fileNameRoot: "fixed-decimals"
      data:
        - type: Time
          parameters:
            precision: 2
        - molecule: "default_module:default_program"
          property: "self.nextRandomDouble()"
          precision: 2
          aggregators: [ mean, max, min, variance, median ]
          value-filter: onlyfinite
  environment: { type: ImageEnvironment, parameters: [*image_path, *zoom] }
  network-model: { type: ObstaclesBreakConnection, parameters: [5] }
  deployments:
    type: Rectangle
    parameters: [*people_count, 62, 15, 95, 200]
    programs:
      - time-distribution: 1
        program: >
          import protelis:coord:spreading
          let source = [110, 325]
          let vector = self.getCoordinates() - source
          let distance = hypot(vector.get(0), vector.get(1))
          distanceTo(distance < 50)        
      - program: send
      - { type: Event, time-distribution: 1, actions: { type: LevyWalk, parameters: [*walk-speed] } }
  
  terminate:
    - type: AfterTime
      parameters: 10

Export data to a MongoDB instance

Alchemist can send data directly to a pre-existing MongoDB instance through its MongoDBExporter.

Examples

Export data to both a csv file and a MongoDB instance:
Click to show / hide code
```
incarnation: protelis
  export:
    - type: CSVExporter
      parameters:
        fileNameRoot: "test_exporters_loading"
        interval: 2.0
      data:
        - time
        - molecule: "default_module:default_program"
  
    - type: MongoDBExporter
      parameters:
        uri: "mongodb://localhost:27017/"
        dbName: "test"
        interval: 2.5
      data:
        - time
  
```

Export of the output of a Protelis program, values generated from nodes get accumulated into mean, max, min, variance, and median:

Click to show / hide code