import { describe, expect, it } from 'vitest'
import {
  bboxesEqual,
  isMunicipalityAreaName,
  isSelectionBoundedDataset,
  normalizeBboxFromCorners,
  parseBboxInput,
  productCoversZones,
  resultMetricLabel,
  selectedAreaCoverageZones,
  selectionAnalysisScale,
  selectionAreaSquareMetres,
  selectionDimensions,
  splitSelectionBbox,
} from './mapWorkspaceUtils'
import type { VectorSelectionBBox, VectorSelectionResponse } from '../../types'

describe('map workspace selection guards', () => {
  it('normalizes drag corners into an EPSG:4326 bbox', () => {
    expect(normalizeBboxFromCorners([5.2, 51.3], [4.8, 50.9])).toEqual({
      min_x: 4.8,
      min_y: 50.9,
      max_x: 5.2,
      max_y: 51.3,
      crs: 'EPSG:4326',
    })
  })

  it('rejects empty, inverted and degenerate manual selections', () => {
    expect(parseBboxInput({ min_x: '', min_y: '', max_x: '', max_y: '' })).toBeNull()
    expect(parseBboxInput({ min_x: '5', min_y: '51', max_x: '4', max_y: '52' })).toBeNull()
    expect(parseBboxInput({ min_x: '4', min_y: '51', max_x: '4', max_y: '52' })).toBeNull()
  })

  it('treats sub-nanodegree bbox drift as the same persisted selection', () => {
    const bbox = normalizeBboxFromCorners([4.98, 51.15], [5.02, 51.19])
    expect(bboxesEqual(bbox, { ...bbox, max_x: bbox.max_x + 1e-10 })).toBe(true)
    expect(bboxesEqual(bbox, { ...bbox, max_x: bbox.max_x + 1e-5 })).toBe(false)
  })

  it('computes a positive bounded selection area and renders governed metrics', () => {
    const bbox = normalizeBboxFromCorners([5.0, 51.0], [5.01, 51.01])
    expect(selectionAreaSquareMetres(bbox)).toBeGreaterThan(700_000)
    expect(selectionAreaSquareMetres(bbox)).toBeLessThan(900_000)

    const result = {
      feature_count: 12,
      truncated: false,
      summary: {
        metric_key: 'forest_area',
        metric_value: 14.236,
        metric_unit: 'ha',
      },
    } as unknown as VectorSelectionResponse
    expect(resultMetricLabel(result)).toBe('14,24 ha')
  })

  it('maps national work areas to regional provider zones without merging sources', () => {
    expect(selectedAreaCoverageZones('Belgium land')).toEqual([
      'belgium',
      'flanders',
      'wallonia',
      'brussels',
    ])
    expect(selectedAreaCoverageZones('RC Ardennes inland')).toEqual(['wallonia'])
    expect(selectedAreaCoverageZones('Brussels-Capital Region')).toEqual(['brussels'])
    expect(selectedAreaCoverageZones('Language boundary')).toEqual(['flanders', 'wallonia'])
    expect(productCoversZones(['wallonia'], ['flanders', 'wallonia'])).toBe(true)
    expect(productCoversZones(['brussels'], ['wallonia'])).toBe(false)
  })

  it('recognizes Dutch and release-golden municipality areas as local scope', () => {
    expect(isMunicipalityAreaName('Gemeente Mol')).toBe(true)
    expect(isMunicipalityAreaName('RC Golden - Mol municipality')).toBe(true)
    expect(isMunicipalityAreaName('Flanders')).toBe(false)
    expect(isMunicipalityAreaName('RC Golden - Kempen region')).toBe(false)
  })

  it('distinguishes selection-bounded acquisitions from reusable regional datasets', () => {
    expect(isSelectionBoundedDataset({
      geometry_clipped_to_selection: true,
      bbox_epsg4326: [4.55, 50.58, 4.56, 50.59],
    })).toBe(true)
    expect(isSelectionBoundedDataset({
      coverage_scope: 'bounded_selection',
      bbox_epsg4326: [5.1, 51.17, 5.11, 51.18],
    })).toBe(true)
    expect(isSelectionBoundedDataset({
      geometry_clipped_to_selection: false,
      bbox_epsg4326: [2.5, 49.5, 6.4, 51.6],
    })).toBe(false)
    expect(isSelectionBoundedDataset({
      geometry_clipped_to_selection: true,
    })).toBe(false)
  })

  it('classifies local, regional and overview selections before provider calls', () => {
    const bbox = (widthDegrees: number, heightDegrees: number): VectorSelectionBBox => ({
      min_x: 5,
      min_y: 51,
      max_x: 5 + widthDegrees,
      max_y: 51 + heightDegrees,
      crs: 'EPSG:4326',
    })
    expect(selectionAnalysisScale(bbox(0.1, 0.1))).toBe('detail')
    expect(selectionAnalysisScale(bbox(0.35, 0.25))).toBe('regional')
    expect(selectionAnalysisScale(bbox(1, 1))).toBe('overview')
  })

  it('splits regional selections into provider-safe tiles without changing the outer bounds', () => {
    const selection: VectorSelectionBBox = {
      min_x: 5,
      min_y: 51,
      max_x: 5.5,
      max_y: 51.35,
      crs: 'EPSG:4326',
    }
    const tiles = splitSelectionBbox(selection)
    expect(tiles.length).toBeGreaterThan(1)
    expect(Math.min(...tiles.map((tile) => tile.min_x))).toBe(selection.min_x)
    expect(Math.min(...tiles.map((tile) => tile.min_y))).toBe(selection.min_y)
    expect(Math.max(...tiles.map((tile) => tile.max_x))).toBe(selection.max_x)
    expect(Math.max(...tiles.map((tile) => tile.max_y))).toBe(selection.max_y)
    for (const tile of tiles) {
      const dimensions = selectionDimensions(tile)
      expect(dimensions.widthMetres).toBeLessThanOrEqual(18_100)
      expect(dimensions.heightMetres).toBeLessThanOrEqual(18_100)
    }
  })

  it('refuses an unbounded detail fan-out', () => {
    const selection: VectorSelectionBBox = {
      min_x: 4,
      min_y: 50,
      max_x: 6,
      max_y: 52,
      crs: 'EPSG:4326',
    }
    expect(() => splitSelectionBbox(selection)).toThrow('detailpartities')
  })
})