PostGIS
Mobile
QGIS
MapBender
GeoServer
GeoNode
GeoNetwork
Novella
Solutions
94 lines
2.4 KiB
Markdown
94 lines
2.4 KiB
Markdown
# Hot Spot Time Series Worker
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Processes hot spot time series analysis jobs to analyze temporal patterns in hot spots.
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## Overview
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The hot spot time series worker performs hot spot analysis across multiple time periods to identify temporal patterns in spatial clustering.
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## Job Type
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`hotspot_timeseries`
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## Input Parameters
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```json
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{
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"dataset_id": 123,
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"value_field": "population",
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"time_field": "date",
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"time_periods": ["2020", "2021", "2022"],
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"neighbor_type": "distance",
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"distance": 1000
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}
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```
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### Parameters
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- `dataset_id` (required): Source dataset ID
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- `value_field` (required): Numeric field to analyze
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- `time_field` (required): Field containing time period identifiers
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- `time_periods` (required): Array of time period values to analyze
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- `neighbor_type` (optional): "distance" or "knn" (default: "distance")
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- `distance` (required if neighbor_type="distance"): Distance threshold
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- `k_neighbors` (required if neighbor_type="knn"): Number of nearest neighbors
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## Output
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Creates a new dataset with time series hot spot results:
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- Hot spot analysis for each time period
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- Temporal patterns in clustering
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- Time period identifiers
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- Gi* z-scores and p-values for each period
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## Algorithm
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The worker:
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1. Filters data by time period
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2. Performs hot spot analysis for each period
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3. Combines results with time period information
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4. Stores results in output table
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## Example
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```bash
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# Enqueue a hot spot time series job via API
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curl -X POST "https://example.com/api/hotspot_timeseries_run.php" \
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-H "Content-Type: application/json" \
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-d '{
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"dataset_id": 123,
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"value_field": "population",
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"time_field": "year",
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"time_periods": ["2020", "2021", "2022"],
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"neighbor_type": "distance",
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"distance": 1000
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}'
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```
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## Background Jobs
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This analysis runs as a background job. The worker:
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1. Fetches queued `hotspot_timeseries` jobs
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2. Validates input parameters
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3. Performs hot spot analysis for each time period
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4. Combines results
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5. Creates output dataset
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6. Marks job as completed
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## Performance Considerations
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- Processing time depends on dataset size and number of time periods
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- Each time period requires separate hot spot analysis
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- Consider limiting number of time periods for large datasets
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- Results can be large for many time periods
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## Related Documentation
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- [Hot Spot Analysis Tool](../analysis-tools/hotspot.md)
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- [Analysis API](../api/analysis.md)
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- [Workers Overview](index.md)
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