def test_analyze(self):
ws = resource_filename('tidegates.testing', 'analyze')
testdir = 'tidegates.testing.analyze'
test_dem = resource_filename(testdir, 'dem.tif')
test_zones = resource_filename(testdir, 'zones.shp')
test_wetlands = resource_filename(testdir, 'wetlands.shp')
test_buidlings = resource_filename(testdir, 'buildings.shp')
output = resource_filename(testdir, 'flooding.shp')
topo_array, zones_array, template = tidegates.process_dem_and_zones(
dem=test_dem,
zones=test_zones,
ID_column="GeoID",
cleanup=True,
verbose=False
)
with utils.WorkSpace(ws), utils.OverwriteState(True):
flood, wetland, building = self.tbx.analyze(
topo_array=topo_array,
zones_array=zones_array,
template=template,
elev=self.elev,
slr=self.slr,
surge=self.surge,
num=None,
flood_output=output,
dem=test_dem,
zones=test_zones,
ID_column='GeoID',
wetlands=test_wetlands,
buildings=test_buidlings,
)
nt.assert_true(isinstance(flood, arcpy.mapping.Layer))
nt.assert_equal(flood.dataSource, resource_filename(testdir, self.flood_output))
nt.assert_true(isinstance(wetland, arcpy.mapping.Layer))
nt.assert_true(isinstance(building, arcpy.mapping.Layer))
tgtest.assert_shapefiles_are_close(
resource_filename(testdir, self.flood_output),
resource_filename(testdir, self.known_flood_output)
)
def test_analyze(self):
ws = resource_filename('tidegates.testing', 'analyze')
testdir = 'tidegates.testing.analyze'
test_dem = resource_filename(testdir, 'dem.tif')
test_zones = resource_filename(testdir, 'zones.shp')
test_wetlands = resource_filename(testdir, 'wetlands.shp')
test_buidlings = resource_filename(testdir, 'buildings.shp')
output = resource_filename(testdir, 'flooding.shp')
topo_array, zones_array, template = tidegates.process_dem_and_zones(
dem=test_dem,
zones=test_zones,
ID_column="GeoID",
cleanup=True,
verbose=False)
with utils.WorkSpace(ws), utils.OverwriteState(True):
flood, wetland, building = self.tbx.analyze(
topo_array=topo_array,
zones_array=zones_array,
template=template,
elev=self.elev,
slr=self.slr,
surge=self.surge,
num=None,
flood_output=output,
dem=test_dem,
zones=test_zones,
ID_column='GeoID',
wetlands=test_wetlands,
buildings=test_buidlings,
)
nt.assert_true(isinstance(flood, arcpy.mapping.Layer))
nt.assert_equal(flood.dataSource,
resource_filename(testdir, self.flood_output))
nt.assert_true(isinstance(wetland, arcpy.mapping.Layer))
nt.assert_true(isinstance(building, arcpy.mapping.Layer))
tgtest.assert_shapefiles_are_close(
resource_filename(testdir, self.flood_output),
resource_filename(testdir, self.known_flood_output))
def test_process_dem_and_zones():
known_topo = numpy.array([
[-999.0, 0.305, 0.610, 0.914, 1.219, 1.524, 1.829, 2.134,],
[ 0.305, 0.610, 0.914, 1.219, 1.524, 1.829, 2.134, 2.438,],
[ 0.610, 0.914, 1.219, 1.524, 1.829, 2.134, 2.438, 2.743,],
[ 0.914, 1.219, 1.524, 1.829, 2.134, 2.438, 2.743, 3.048,],
[ 1.219, 1.524, 1.829, 2.134, 2.438, 2.743, 3.048, 3.353,],
[ 1.524, 1.829, 2.134, 2.438, 2.743, 3.048, 3.353, 3.658,],
])
known_zones = numpy.array([
[-999, 2, 2, 2, 2, 2, 2, -999],
[-999, 2, 2, 2, -999, 2, 2, -999],
[ 1, 1, 1, 1, -999, 2, 2, -999],
[ 1, 1, 1, 1, -999, 2, 2, -999],
[ 1, -999, 1, 1, 2, 2, 2, 2],
[-999, -999, 1, 1, 2, 2, 2, 2]
])
known_cell_size = 8
known_X, known_Y = 4, 22
ws = resource_filename('tidegates.testing', 'process_dem_and_zones')
with utils.WorkSpace(ws), utils.OverwriteState(True):
ta, za, template = tidegates.process_dem_and_zones(
dem='topo.tif',
zones='zones.shp',
ID_column='GeoID',
cleanup=True,
verbose=False
)
nptest.assert_array_almost_equal(ta, known_topo, decimal=3)
nptest.assert_array_almost_equal(za, known_zones, decimal=3)
nt.assert_equal(template.meanCellWidth, known_cell_size)
nt.assert_equal(template.meanCellHeight, known_cell_size)
nt.assert_equal(template.extent.lowerLeft.X, known_X)
nt.assert_equal(template.extent.lowerLeft.Y, known_Y)
def main_execute(self, **params):
""" Performs the flood-impact analysis on multiple flood
elevations.
Parameters
----------
workspace : str
The folder or geodatabase where the analysis will be
executed.
dem : str
Filename of the digital elevation model (topography data)
to be used in determinging the inundated areas.
zones : str
Name of zones of influence layer.
ID_column : str
Name of the field in ``zones`` that uniquely identifies
each zone of influence.
elevation : list, optional
List of (custom) flood elevations to be analyzed. If this is
not provided, *all* of the standard scenarios will be
evaluated.
flood_output : str
Filename where the extent of flooding and damage will be
saved.
wetlands, buildings : str, optional
Names of the wetland and building footprint layers.
wetland_output, building_output : str, optional
Filenames where the flooded wetlands and building footprints
will be saved.
Returns
-------
None
"""
wetlands = params.get('wetlands', None)
buildings = params.get('buildings', None)
all_floods = []
all_wetlands = []
all_buildings = []
with utils.WorkSpace(params['workspace']), utils.OverwriteState(True):
topo_array, zones_array, template = tidegates.process_dem_and_zones(
dem=params['dem'],
zones=params['zones'],
ID_column=params['ID_column']
)
for num, scenario in enumerate(self.make_scenarios(**params)):
fldlyr, wtlndlyr, blgdlyr = self.analyze(
topo_array=topo_array,
zones_array=zones_array,
template=template,
elev=scenario['elev'],
surge=scenario['surge_name'],
slr=scenario['slr'],
num=num,
**params
)
all_floods.append(fldlyr.dataSource)
if wetlands is not None:
all_wetlands.append(wtlndlyr.dataSource)
if buildings is not None:
all_buildings.append(blgdlyr.dataSource)
self.finish_results(
params['flood_output'],
all_floods,
msg="Merging and cleaning up all flood results",
verbose=True,
asMessage=True,
)
if wetlands is not None:
wtld_output = params.get(
'wetland_output',
utils.create_temp_filename(params['wetlands'], prefix='output_', filetype='shape')
)
self.finish_results(
wtld_output,
all_wetlands,
sourcename=params['wetlands'],
msg="Merging and cleaning up all wetlands results",
verbose=True,
asMessage=True,
)
if buildings is not None:
bldg_output = params.get(
'building_output',
utils.create_temp_filename(params['buildings'], prefix='output_', filetype='shape')
)
self.finish_results(
bldg_output,
all_buildings,
sourcename=params['buildings'],
msg="Merging and cleaning up all buildings results",
verbose=True,
asMessage=True,
)
def main_execute(self, **params):
""" Performs the flood-impact analysis on multiple flood
elevations.
Parameters
----------
workspace : str
The folder or geodatabase where the analysis will be
executed.
dem : str
Filename of the digital elevation model (topography data)
to be used in determinging the inundated areas.
zones : str
Name of zones of influence layer.
ID_column : str
Name of the field in ``zones`` that uniquely identifies
each zone of influence.
elevation : list, optional
List of (custom) flood elevations to be analyzed. If this is
not provided, *all* of the standard scenarios will be
evaluated.
flood_output : str
Filename where the extent of flooding and damage will be
saved.
wetlands, buildings : str, optional
Names of the wetland and building footprint layers.
wetland_output, building_output : str, optional
Filenames where the flooded wetlands and building footprints
will be saved.
Returns
-------
None
"""
wetlands = params.get('wetlands', None)
buildings = params.get('buildings', None)
all_floods = []
all_wetlands = []
all_buildings = []
with utils.WorkSpace(params['workspace']), utils.OverwriteState(True):
topo_array, zones_array, template = tidegates.process_dem_and_zones(
dem=params['dem'],
zones=params['zones'],
ID_column=params['ID_column']
)
for scenario in self.make_scenarios(**params):
fldlyr, wtlndlyr, blgdlyr = self.analyze(
topo_array=topo_array,
zones_array=zones_array,
template=template,
elev=scenario['elev'],
surge=scenario['surge_name'],
slr=scenario['slr'],
**params
)
all_floods.append(fldlyr.dataSource)
if wetlands is not None:
all_wetlands.append(wtlndlyr.dataSource)
if buildings is not None:
all_buildings.append(blgdlyr.dataSource)
self.finish_results(
params['flood_output'],
all_floods,
msg="Merging and cleaning up all flood results",
verbose=True,
asMessage=True,
)
if wetlands is not None:
wtld_output = params.get(
'wetland_output',
utils.create_temp_filename(params['wetlands'], prefix='output_', filetype='shape')
)
self.finish_results(
wtld_output,
all_wetlands,
sourcename=params['wetlands'],
msg="Merging and cleaning up all wetlands results",
verbose=True,
asMessage=True,
)
if buildings is not None:
bldg_output = params.get(
'building_output',
utils.create_temp_filename(params['buildings'], prefix='output_', filetype='shape')
)
self.finish_results(
bldg_output,
all_buildings,
sourcename=params['buildings'],
msg="Merging and cleaning up all buildings results",
verbose=True,
asMessage=True,
)
def test_process_dem_and_zones():
known_topo = numpy.array([
[
-999.0,
0.305,
0.610,
0.914,
1.219,
1.524,
1.829,
2.134,
],
[
0.305,
0.610,
0.914,
1.219,
1.524,
1.829,
2.134,
2.438,
],
[
0.610,
0.914,
1.219,
1.524,
1.829,
2.134,
2.438,
2.743,
],
[
0.914,
1.219,
1.524,
1.829,
2.134,
2.438,
2.743,
3.048,
],
[
1.219,
1.524,
1.829,
2.134,
2.438,
2.743,
3.048,
3.353,
],
[
1.524,
1.829,
2.134,
2.438,
2.743,
3.048,
3.353,
3.658,
],
])
known_zones = numpy.array([[-999, 2, 2, 2, 2, 2, 2, -999],
[-999, 2, 2, 2, -999, 2, 2, -999],
[1, 1, 1, 1, -999, 2, 2, -999],
[1, 1, 1, 1, -999, 2, 2, -999],
[1, -999, 1, 1, 2, 2, 2, 2],
[-999, -999, 1, 1, 2, 2, 2, 2]])
known_cell_size = 8
known_X, known_Y = 4, 22
ws = resource_filename('tidegates.testing', 'process_dem_and_zones')
with utils.WorkSpace(ws), utils.OverwriteState(True):
ta, za, template = tidegates.process_dem_and_zones(dem='topo.tif',
zones='zones.shp',
ID_column='GeoID',
cleanup=True,
verbose=False)
nptest.assert_array_almost_equal(ta, known_topo, decimal=3)
nptest.assert_array_almost_equal(za, known_zones, decimal=3)
nt.assert_equal(template.meanCellWidth, known_cell_size)
nt.assert_equal(template.meanCellHeight, known_cell_size)
nt.assert_equal(template.extent.lowerLeft.X, known_X)
nt.assert_equal(template.extent.lowerLeft.Y, known_Y)
