def test_missing_aoi(self):
"""Forest carbon edge: ensure missing AOI causes exception."""
from natcap.invest import forest_carbon_edge_effect
args = {
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'no_forest_edge_carbon_lu_table_bad_pool_value.csv'),
'compute_forest_edge_effects':
False,
'lulc_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'small_lulc.tif'),
'n_nearest_model_points':
1,
'pools_to_calculate':
'all',
'results_suffix':
'small_no_edge_effect',
'tropical_forest_edge_carbon_model_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
'n_workers':
-1
}
args['aoi_vector_path'] = os.path.join('path', 'to', 'nonexistant',
'aoi.shp')
with self.assertRaises(ValueError) as cm:
forest_carbon_edge_effect.execute(args)
expected_message = 'Unable to open aoi at:'
actual_message = str(cm.exception)
self.assertTrue(expected_message in actual_message, actual_message)
def test_carbon_nodata_lulc(self):
"""Forest Carbon Edge: ensure nodata lulc raster cause exception"""
from natcap.invest import forest_carbon_edge_effect
args = {
'aoi_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'small_aoi.shp'),
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'forest_edge_carbon_lu_table.csv'),
'compute_forest_edge_effects':
True,
'lulc_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'nodata_lulc.tif'),
'n_nearest_model_points':
10,
'pools_to_calculate':
'all',
'tropical_forest_edge_carbon_model_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
'n_workers':
-1
}
with self.assertRaises(ValueError) as cm:
forest_carbon_edge_effect.execute(args)
expected_message = 'The landcover raster '
actual_message = str(cm.exception)
self.assertTrue(expected_message in actual_message, actual_message)
def test_carbon_bad_pool_value(self):
"""Forest Carbon Edge: test with bad carbon pool value."""
from natcap.invest import forest_carbon_edge_effect
args = {
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'no_forest_edge_carbon_lu_table_bad_pool_value.csv'),
'compute_forest_edge_effects':
False,
'lulc_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'small_lulc.tif'),
'n_nearest_model_points':
1,
'pools_to_calculate':
'all',
'results_suffix':
'small_no_edge_effect',
'tropical_forest_edge_carbon_model_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
'n_workers':
-1
}
with self.assertRaises(ValueError) as cm:
forest_carbon_edge_effect.execute(args)
expected_message = 'Could not interpret carbon pool value'
actual_message = str(cm.exception)
self.assertTrue(expected_message in actual_message, actual_message)
def test_carbon_small_dup_output(self):
"""Forest Carbon Edge: small test for existing output overlap."""
from natcap.invest import forest_carbon_edge_effect
args = {
'aoi_uri':
os.path.join(REGRESSION_DATA, 'small_aoi.shp'),
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_uri':
os.path.join(SAMPLE_DATA, 'forest_edge_carbon_lu_table.csv'),
'compute_forest_edge_effects':
True,
'lulc_uri':
os.path.join(REGRESSION_DATA, 'small_lulc.tif'),
'n_nearest_model_points':
'1',
'pools_to_calculate':
'above_ground',
'results_suffix':
'small',
'tropical_forest_edge_carbon_model_shape_uri':
os.path.join(SAMPLE_DATA, 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
}
# explictily testing that invoking twice doesn't cause the model to
# crash because of exising outputs
forest_carbon_edge_effect.execute(args)
forest_carbon_edge_effect.execute(args)
self.assertTrue(True) # explict pass of the model
def test_carbon_small_bad_pool_value(self):
"""Forest Carbon Edge: small test with bad carbon pool value."""
from natcap.invest import forest_carbon_edge_effect
args = {
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_uri':
os.path.join(REGRESSION_DATA,
'no_forest_edge_carbon_lu_table_bad_pool_value.csv'),
'compute_forest_edge_effects':
False,
'lulc_uri':
os.path.join(REGRESSION_DATA, 'small_lulc.tif'),
'n_nearest_model_points':
'1',
'pools_to_calculate':
'all',
'results_suffix':
'small_no_edge_effect',
'tropical_forest_edge_carbon_model_shape_uri':
os.path.join(SAMPLE_DATA, 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
}
with self.assertRaises(ValueError):
forest_carbon_edge_effect.execute(args)
def test_carbon_small_no_forest_edge(self):
"""Forest Carbon Edge: small test for no forest edge effects."""
from natcap.invest import forest_carbon_edge_effect
args = {
'aoi_uri':
os.path.join(REGRESSION_DATA, 'small_aoi.shp'),
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_uri':
os.path.join(REGRESSION_DATA,
'no_forest_edge_carbon_lu_table.csv'),
'compute_forest_edge_effects':
False,
'lulc_uri':
os.path.join(REGRESSION_DATA, 'small_lulc.tif'),
'n_nearest_model_points':
'1',
'pools_to_calculate':
'above_ground',
'results_suffix':
'small_no_edge_effect',
'tropical_forest_edge_carbon_model_shape_uri':
os.path.join(SAMPLE_DATA, 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
}
forest_carbon_edge_effect.execute(args)
ForestCarbonEdgeTests._test_same_files(
os.path.join(REGRESSION_DATA,
'file_list_small_no_edge_effect.txt'),
args['workspace_dir'])
ForestCarbonEdgeTests._assert_regression_results_eq(
args['workspace_dir'],
os.path.join(args['workspace_dir'],
'aggregated_carbon_stocks_small_no_edge_effect.shp'),
os.path.join(REGRESSION_DATA,
'agg_results_small_no_edge_effect.csv'))
def test_carbon_full(self):
"""Forest Carbon Edge: regression testing all functionality."""
from natcap.invest import forest_carbon_edge_effect
args = {
'aoi_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'small_aoi.shp'),
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'forest_edge_carbon_lu_table.csv'),
'compute_forest_edge_effects':
True,
'lulc_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'small_lulc.tif'),
'n_nearest_model_points':
10,
'pools_to_calculate':
'all',
'tropical_forest_edge_carbon_model_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
'n_workers':
-1
}
forest_carbon_edge_effect.execute(args)
ForestCarbonEdgeTests._test_same_files(
os.path.join(REGRESSION_DATA, 'file_list.txt'),
args['workspace_dir'])
self._assert_vector_results_close(
args['workspace_dir'], 'id', ['c_sum', 'c_ha_mean'],
os.path.join(args['workspace_dir'],
'aggregated_carbon_stocks.shp'),
os.path.join(REGRESSION_DATA, 'agg_results_base.shp'))
def test_carbon_full(self):
"""Forest Carbon Edge: regression testing all functionality."""
from natcap.invest import forest_carbon_edge_effect
args = {
'aoi_uri':
os.path.join(SAMPLE_DATA, 'forest_carbon_edge_demo_aoi.shp'),
'biomass_to_carbon_conversion_factor':
'0.47',
'biophysical_table_uri':
os.path.join(SAMPLE_DATA, 'forest_edge_carbon_lu_table.csv'),
'compute_forest_edge_effects':
True,
'lulc_uri':
os.path.join(SAMPLE_DATA, 'forest_carbon_edge_lulc_demo.tif'),
'n_nearest_model_points':
10,
'pools_to_calculate':
'all',
'tropical_forest_edge_carbon_model_shape_uri':
os.path.join(SAMPLE_DATA, 'core_data',
'forest_carbon_edge_regression_model_parameters.shp'),
'workspace_dir':
self.workspace_dir,
}
forest_carbon_edge_effect.execute(args)
ForestCarbonEdgeTests._test_same_files(
os.path.join(REGRESSION_DATA, 'file_list.txt'),
args['workspace_dir'])
ForestCarbonEdgeTests._assert_regression_results_eq(
args['workspace_dir'],
os.path.join(args['workspace_dir'],
'aggregated_carbon_stocks.shp'),
os.path.join(REGRESSION_DATA, 'agg_results_base.csv'))
