Python core.read_layer函数代码示例

    def test_run(self):
        """TestVolcanoPointPopulationFunction: Test running the IF."""
        merapi_point_path = test_data_path('hazard', 'volcano_point.shp')
        population_path = test_data_path(
            'exposure', 'pop_binary_raster_20_20.asc')

        merapi_point_layer = read_layer(merapi_point_path)
        population_layer = read_layer(population_path)

        impact_function = VolcanoPointPopulationFunction.instance()

        # Run merapi point
        impact_function.hazard = merapi_point_layer
        impact_function.exposure = population_layer
        impact_function.run()
        impact_layer = impact_function.impact
        # Check the question
        expected_question = (
            'In the event of a volcano point how many '
            'people might be impacted')
        message = 'The question should be %s, but it returns %s' % (
            expected_question, impact_function.question)
        self.assertEqual(expected_question, impact_function.question, message)
        # Count by hand
        expected_affected_population = 200
        result = numpy.nansum(impact_layer.get_data())
        message = 'Expecting %s, but it returns %s' % (
            expected_affected_population, result)
        self.assertEqual(expected_affected_population, result, message)

    def test_run(self):
        function = FloodEvacuationRasterHazardFunction.instance()

        hazard_path = test_data_path('hazard', 'continuous_flood_20_20.asc')
        exposure_path = test_data_path(
            'exposure', 'pop_binary_raster_20_20.asc')
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        function.hazard = hazard_layer
        function.exposure = exposure_layer
        function.run()
        impact = function.impact

        # Count of flooded objects is calculated "by the hands"
        # print "keywords", keywords
        keywords = impact.get_keywords()
        evacuated = float(keywords['evacuated'])
        total_needs_full = keywords['total_needs']
        total_needs_weekly = OrderedDict([
            [x['table name'], x['amount']] for x in
            total_needs_full['weekly']
        ])
        total_needs_single = OrderedDict([
            [x['table name'], x['amount']] for x in
            total_needs_full['single']
        ])

        expected_evacuated = 100
        self.assertEqual(evacuated, expected_evacuated)
        self.assertEqual(total_needs_weekly['Rice [kg]'], 280)
        self.assertEqual(total_needs_weekly['Family Kits'], 20)
        self.assertEqual(total_needs_weekly['Drinking Water [l]'], 1750)
        self.assertEqual(total_needs_weekly['Clean Water [l]'], 6700)
        self.assertEqual(total_needs_single['Toilets'], 5)

    def test_flood_raster_building_impact_function(self):
        """Flood raster building impact function works

        This test also exercises interpolation of hazard level (raster) to
        building locations (vector data).
        """
        for haz_filename in ['Flood_Current_Depth_Jakarta_geographic.asc',
                             'Flood_Design_Depth_Jakarta_geographic.asc']:
            # Name file names for hazard level and exposure
            hazard_filename = '%s/%s' % (HAZDATA, haz_filename)
            exposure_filename = ('%s/OSM_building_polygons_20110905.shp'
                                 % TESTDATA)

            # Calculate impact using API
            hazard_layer = read_layer(hazard_filename)
            exposure_layer = read_layer(exposure_filename)

            plugin_name = 'FloodRasterBuildingImpactFunction'
            impact_function = get_plugin(plugin_name)

            impact_vector = calculate_impact(
                layers=[hazard_layer, exposure_layer],
                impact_fcn=impact_function)

            # Extract calculated result
            icoordinates = impact_vector.get_geometry()
            iattributes = impact_vector.get_data()

            # Check
            assert len(icoordinates) == 34960
            assert len(iattributes) == 34960

    def test_run(self):
        impact_function = TsunamiRasterBuildingFunction.instance()

        hazard_path = test_data_path("hazard", "continuous_flood_20_20.asc")
        exposure_path = test_data_path("exposure", "buildings.shp")
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        impact_function.hazard = SafeLayer(hazard_layer)
        impact_function.exposure = SafeLayer(exposure_layer)
        impact_function.run()
        impact_layer = impact_function.impact

        # Extract calculated result
        impact_data = impact_layer.get_data()
        self.assertEqual(len(impact_data), 181)

        # 1 = inundated, 2 = wet, 3 = dry
        expected_result = {0: 1, 1: 116, 2: 64, 3: 0, 4: 0}

        result = {0: 0, 1: 0, 2: 0, 3: 0, 4: 0}
        for feature in impact_data:
            inundated_status = feature[impact_function.target_field]
            result[inundated_status] += 1

        message = "Expecting %s, but it returns %s" % (expected_result, result)
        self.assertEqual(expected_result, result, message)

    def test_volcano_circle_population_impact(self):
        """Volcano function runs circular evacuation zone."""
        # Name file names for hazard level, exposure and expected fatalities
        hazard_filename = '%s/Merapi_alert.shp' % TESTDATA
        exposure_filename = ('%s/glp10ag.asc' % EXPDATA)

        # Calculate impact using API
        hazard_layer = read_layer(hazard_filename)
        exposure_layer = read_layer(exposure_filename)

        plugin_name = 'Volcano Polygon Hazard Population'
        impact_function = get_plugin(plugin_name)

        impact_layer = calculate_impact(
            layers=[hazard_layer, exposure_layer], impact_fcn=impact_function)
        impact_filename = impact_layer.get_filename()

        impact_layer = read_layer(impact_filename)
        keywords = impact_layer.get_keywords()
        print keywords
        # This is the expected number of people affected
        # Distance [km]	Total	Cumulative
        # 3	     15.800	15.800
        # 5	     17.300	33.100
        # 10	125.000	158.000
        message = 'Result not as expected'
        impact_summary = keywords['impact_summary']
        self.assertTrue(format_int(15800) in impact_summary, message)
        self.assertTrue(format_int(17300) in impact_summary, message)
        self.assertTrue(format_int(125000) in impact_summary, message)

    def test_run(self):
        function = AshRasterPopulationFunction.instance()

        hazard_path = standard_data_path('hazard', 'ash_raster_wgs84.tif')
        exposure_path = standard_data_path(
            'exposure', 'pop_binary_raster_20_20.asc')
        # We need clipping for both layers to be in the same dimension
        clipped_hazard, clipped_exposure = clip_layers(
            hazard_path, exposure_path)

        hazard_layer = read_layer(clipped_hazard.source())
        exposure_layer = read_layer(clipped_exposure.source())

        # Let's set the extent to the hazard extent
        function.hazard = SafeLayer(hazard_layer)
        function.exposure = SafeLayer(exposure_layer)
        function.run()
        impact = function.impact
        expected = [
            [u'Population in very low hazard zone', 0],
            [u'Population in medium hazard zone', 1374],
            [u'Population in high hazard zone', 20],
            [u'Population in very high hazard zone', 0],
            [u'Population in low hazard zone', 8443],
            [u'Total affected population', 9837],
            [u'Unaffected population', 0],
            [u'Total population', 9837],
            [u'Population needing evacuation <sup>1</sup>', 9837]
        ]
        self.assertListEqual(
            expected, impact.impact_data['impact summary']['fields'])

    def test_run(self):
        function = ContinuousHazardPopulationFunction.instance()

        hazard_path = test_data_path(
            'hazard', 'continuous_flood_20_20.asc')
        exposure_path = test_data_path(
            'exposure', 'pop_binary_raster_20_20.asc')
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        function.hazard = SafeLayer(hazard_layer)
        function.exposure = SafeLayer(exposure_layer)
        function.run()
        impact = function.impact

        # print "keywords", keywords
        keywords = impact.get_keywords()
        total_needs_full = keywords['total_needs']
        total_needs_weekly = OrderedDict([
            [x['table name'], x['amount']] for x in
            total_needs_full['weekly']
        ])
        total_needs_single = OrderedDict([
            [x['table name'], x['amount']] for x in
            total_needs_full['single']
        ])

        self.assertEqual(total_needs_weekly['Rice [kg]'], 336)
        self.assertEqual(total_needs_weekly['Drinking Water [l]'], 2100)
        self.assertEqual(total_needs_weekly['Clean Water [l]'], 8040)
        self.assertEqual(total_needs_weekly['Family Kits'], 24)
        self.assertEqual(total_needs_single['Toilets'], 6)

    def test_run(self):
        impact_function = FloodRasterBuildingFunction.instance()

        hazard_path = test_data_path('hazard', 'continuous_flood_20_20.asc')
        exposure_path = test_data_path('exposure', 'buildings.shp')
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        impact_function.hazard = hazard_layer
        impact_function.exposure = exposure_layer
        impact_function.run()
        impact_layer = impact_function.impact

        # Extract calculated result
        impact_data = impact_layer.get_data()
        self.assertEqual(len(impact_data), 181)

        # 1 = inundated, 2 = wet, 3 = dry
        expected_result = {
            1: 64,
            2: 117,
            3: 0
        }

        result = {
            1: 0,
            2: 0,
            3: 0
        }
        for feature in impact_data:
            inundated_status = feature['INUNDATED']
            result[inundated_status] += 1

        message = 'Expecting %s, but it returns %s' % (expected_result, result)
        self.assertEqual(expected_result, result, message)

    def test_run(self):
        function = ClassifiedRasterHazardBuildingFunction.instance()

        hazard_path = standard_data_path(
            'hazard', 'classified_hazard.tif')
        exposure_path = standard_data_path('exposure', 'small_building.shp')
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        function.hazard = SafeLayer(hazard_layer)
        function.exposure = SafeLayer(exposure_layer)
        function.run_analysis()
        impact_layer = function.impact
        impact_data = impact_layer.get_data()

        # Count
        expected_impact = {
            'Not affected': 5,
            'Low hazard zone': 2,
            'Medium hazard zone': 9,
            'High hazard zone': 5
        }

        result_impact = {}
        for impact_feature in impact_data:
            hazard_class = impact_feature[function.target_field]
            if hazard_class in result_impact:
                result_impact[hazard_class] += 1
            else:
                result_impact[hazard_class] = 1
        self.assertDictEqual(expected_impact, result_impact)

    def test_run(self):
        """TestVolcanoPolygonBuildingFunction: Test running the IF."""
        volcano_path = test_data_path('hazard', 'volcano_krb.shp')
        building_path = test_data_path('exposure', 'buildings.shp')

        hazard_layer = read_layer(volcano_path)
        exposure_layer = read_layer(building_path)

        impact_function = VolcanoPolygonBuildingFunction.instance()
        impact_function.hazard = hazard_layer
        impact_function.exposure = exposure_layer
        impact_function.run()
        impact_layer = impact_function.impact

        # Check the question
        expected_question = ('In the event of volcano krb how many buildings '
                             'might be affected')
        message = 'The question should be %s, but it returns %s' % (
            expected_question, impact_function.question)
        self.assertEqual(expected_question, impact_function.question, message)

        # The buildings should all be categorised into 5000 zone
        zone_sum = impact_layer.get_data(attribute='zone')
        krb3_zone_count = zone_sum.count('Kawasan Rawan Bencana III')
        krb2_zone_count = zone_sum.count('Kawasan Rawan Bencana II')
        # The result (counted by hand)
        expected_krb3_count = 11
        expected_krb2_count = 161
        message = 'Expecting %s for KRB III zone, but it returns %s' % (
            krb3_zone_count, expected_krb3_count)
        self.assertEqual(krb3_zone_count, expected_krb3_count, message)
        message = 'Expecting %s for KRB II zone, but it returns %s' % (
            krb2_zone_count, expected_krb2_count)
        self.assertEqual(krb2_zone_count, expected_krb2_count, message)

    def test_pager_earthquake_fatality_estimation(self):
        """Fatalities from ground shaking can be computed correctly
            using the Pager fatality model."""
        # Name file names for hazard level, exposure and expected fatalities
        hazard_filename = '%s/itb_test_mmi.asc' % TESTDATA
        exposure_filename = '%s/itb_test_pop.asc' % TESTDATA

        # Calculate impact using API
        hazard_layer = read_layer(hazard_filename)
        exposure_layer = read_layer(exposure_filename)
        plugin_name = 'PAG Fatality Function'
        impact_function = get_plugin(plugin_name)

        # Call calculation engine
        impact_layer = calculate_impact(
            layers=[hazard_layer, exposure_layer], impact_fcn=impact_function)
        impact_filename = impact_layer.get_filename()

        impact_layer = read_layer(impact_filename)
        keywords = impact_layer.get_keywords()
        population = keywords['total_population']
        fatalities = keywords['total_fatalities']

        # Check aggregated values
        expected_population = 85425000.0
        msg = ('Expected population was %f, I got %f'
               % (expected_population, population))
        self.assertEqual(population, expected_population, msg)

        expected_fatalities = 410000.0
        msg = ('Expected fatalities was %f, I got %f'
               % (expected_fatalities, fatalities))
        assert numpy.allclose(
            fatalities, expected_fatalities, rtol=1.0e-5), msg

    def test_flood_vector_building_impact_function(self):
        """Test flood building impact function works (flood is polygon)."""
        building = 'test_flood_building_impact_exposure.shp'
        flood_data = 'test_flood_building_impact_hazard.shp'
        plugin_name = 'FloodVectorBuildingImpactFunction'

        hazard_filename = os.path.join(TESTDATA, flood_data)
        exposure_filename = os.path.join(TESTDATA, building)

        # Calculate impact using API
        hazard_layer = read_layer(hazard_filename)
        exposure_layer = read_layer(exposure_filename)

        impact_function = get_plugin(plugin_name)

        # Call calculation engine
        impact_layer = calculate_impact(
            layers=[hazard_layer, exposure_layer], impact_fcn=impact_function)
        impact_filename = impact_layer.get_filename()
        impact_layer = read_layer(impact_filename)

        keywords = impact_layer.get_keywords()
        buildings_total = keywords['buildings_total']
        buildings_affected = keywords['buildings_affected']

        self.assertEqual(buildings_total, 67)
        self.assertEqual(buildings_affected, 41)

    def test_volcano_population_evacuation_impact(self):
        """Population impact from volcanic hazard is computed correctly."""
        # Name file names for hazard level, exposure and expected fatalities
        hazard_filename = '%s/donut.shp' % TESTDATA
        exposure_filename = ('%s/pop_merapi_clip.tif' % TESTDATA)

        # Calculate impact using API
        hazard_layer = read_layer(hazard_filename)
        exposure_layer = read_layer(exposure_filename)

        plugin_name = 'Volcano Polygon Hazard Population'
        impact_function = get_plugin(plugin_name)

        impact_layer = calculate_impact(
            layers=[hazard_layer, exposure_layer], impact_fcn=impact_function)
        impact_filename = impact_layer.get_filename()

        impact_layer = read_layer(impact_filename)

        keywords = impact_layer.get_keywords()

        # Check for expected results:
        for value in ['Merapi', 192055, 56514, 68568, 66971]:
            if isinstance(value, int):
                x = format_int(population_rounding(value))
            else:
                x = value
            summary = keywords['impact_summary']
            msg = ('Did not find expected value %s in summary %s'
                   % (x, summary))
            assert x in summary, msg

    def test_run(self):
        function = ClassifiedRasterHazardBuildingFunction.instance()

        hazard_path = test_data_path('hazard', 'classified_flood_20_20.asc')
        exposure_path = test_data_path('exposure', 'buildings.shp')
        hazard_layer = read_layer(hazard_path)
        exposure_layer = read_layer(exposure_path)

        function.hazard = hazard_layer
        function.exposure = exposure_layer
        function.run()
        impact_layer = function.impact
        impact_data = impact_layer.get_data()

        # Count
        expected_impact = {
            1.0: 67,
            2.0: 49,
            3.0: 64
        }

        result_impact = {
            1.0: 0,
            2.0: 0,
            3.0: 0
        }
        for impact_feature in impact_data:
            level = impact_feature['level']
            if not math.isnan(level):
                result_impact[level] += 1
        message = 'Expecting %s, but it returns %s' % (
            expected_impact, result_impact)
        self.assertEqual(expected_impact, result_impact, message)

    def test_aggregate(self):
        """Aggregation by boundaries works
        """

        # Name file names for hazard level and exposure
        boundary_filename = ('%s/kecamatan_jakarta_osm.shp' % TESTDATA)
        #data_filename = ('%s/Population_Jakarta_geographic.asc' % TESTDATA)

        # Get reference building impact data
        building_filename = ('%s/building_impact_scenario.shp' % TESTDATA)

        boundary_layer = read_layer(boundary_filename)
        building_layer = read_layer(building_filename)

        res = aggregate(data=building_layer,
                        boundaries=boundary_layer,
                        attribute_name='AFFECTED',
                        aggregation_function='count')

        #print res, len(res)
        #print boundary_layer, len(boundary_layer)
        msg = ('Number of aggregations %i should be the same as the '
               'number of specified boundaries %i' % (len(res),
                                                      len(boundary_layer)))
        assert len(res) == len(boundary_layer), msg