def test_pollination_bad_cross_table_headers(self):
"""Pollination: ensure detection of missing headers in one table."""
from natcap.invest import pollination
temp_path = tempfile.mkdtemp(dir=self.workspace_dir)
bad_biophysical_table_path = os.path.join(temp_path,
'bad_biophysical_table.csv')
# one table has only spring the other has only fall.
with open(bad_biophysical_table_path, 'wb') as bad_biophysical_table:
bad_biophysical_table.write(
'lucode,nesting_cavity_availability_index,nesting_ground_index,floral_resources_spring_index\n'
'1,0.3,0.2,0.2\n')
bad_guild_table_path = os.path.join(temp_path, 'bad_guild_table.csv')
with open(bad_guild_table_path, 'wb') as bad_guild_table:
bad_guild_table.write(
'species,nesting_suitability_cavity_index,'
'foraging_activity_fall_index,alpha,relative_abundance\n')
bad_guild_table.write('apis,0.2,0.5,400,1.0\n')
bad_guild_table.write('bee,0.9,0.5,1400,0.5\n')
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
bad_guild_table_path,
'landcover_biophysical_table_path':
bad_biophysical_table_path,
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'farms.shp'),
}
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_bad_guild_headers(self):
"""Pollination: testing that model detects bad guild headers."""
from natcap.invest import pollination
temp_path = tempfile.mkdtemp(dir=self.workspace_dir)
bad_guild_table_path = os.path.join(temp_path, 'bad_guild_table.csv')
with open(bad_guild_table_path, 'wb') as bad_guild_table:
bad_guild_table.write(
'species,nesting_suitability_cavity_index,alpha,'
'relative_abundance\n')
bad_guild_table.write('apis,0.2,400,1.0\n')
bad_guild_table.write('bee,0.9,1400,0.1\n')
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
bad_guild_table_path,
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table.csv'),
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'farms.shp'),
}
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_bad_biophysical_headers(self):
"""Pollination: testing that model detects bad biophysical headers."""
from natcap.invest import pollination
temp_path = tempfile.mkdtemp(dir=self.workspace_dir)
bad_biophysical_table_path = os.path.join(temp_path,
'bad_biophysical_table.csv')
with open(bad_biophysical_table_path, 'wb') as bad_biophysical_table:
bad_biophysical_table.write(
'lucode,nesting_cavity_availability_index,nesting_ground_index\n'
'1,0.3,0.2\n')
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table.csv'),
'landcover_biophysical_table_path':
bad_biophysical_table_path,
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'farms.shp'),
}
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_no_farm_regression(self):
"""Pollination: regression testing sample data with no farms."""
from natcap.invest import pollination
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table.csv')
}
pollination.execute(args)
result_raster_path = os.path.join(
self.workspace_dir, 'pollinator_abundance_apis_spring.tif')
result_sum = numpy.float32(0.0)
for _, data_block in pygeoprocessing.iterblocks(
(result_raster_path, 1)):
result_sum += numpy.sum(data_block)
# the number below is just what the sum rounded to two decimal places
# when I manually inspected a run that appeared to be correct.
self.assertAlmostEqual(result_sum, 58.669518, places=2)
def test_pollination_regression(self):
"""Pollination: regression testing sample data."""
from natcap.invest import pollination
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input',
'pollination_example_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table_simple.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table_simple.csv'),
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'blueberry_ridge_farm.shp'),
}
# make empty result files to get coverage for removing if necessary
result_files = [
'farm_results.shp', 'total_pollinator_yield.tif',
'wild_pollinator_yield.tif'
]
for file_name in result_files:
f = open(os.path.join(self.workspace_dir, file_name), 'w')
f.close()
pollination.execute(args)
expected_farm_yields = {
'blueberry': {
'y_tot': 0.44934792607,
'y_wild': 0.09934792607
},
}
result_vector = ogr.Open(
os.path.join(self.workspace_dir, 'farm_results.shp'))
result_layer = result_vector.GetLayer()
try:
self.assertEqual(result_layer.GetFeatureCount(),
len(expected_farm_yields))
for feature in result_layer:
expected_yields = expected_farm_yields[feature.GetField(
'crop_type')]
for yield_type in expected_yields:
self.assertAlmostEqual(expected_yields[yield_type],
feature.GetField(yield_type),
places=2)
finally:
# make sure vector is closed before removing the workspace
result_layer = None
result_vector = None
PollinationTests._test_same_files(
os.path.join(REGRESSION_DATA, 'expected_file_list_regression.txt'),
self.workspace_dir)
def test_pollination_bad_farm_type(self):
"""Pollination: ensure detection of bad farm geometry type."""
from natcap.invest import pollination
# make some fake farm points
point_geom = [shapely.geometry.Point(20, -20)]
farm_shape_path = os.path.join(self.workspace_dir, 'point_farm.shp')
# Create the point shapefile
srs = osr.SpatialReference()
srs.ImportFromEPSG(3157)
projection_wkt = srs.ExportToWkt()
fields = {
'crop_type': ogr.OFTString,
'half_sat': ogr.OFTReal,
'p_managed': ogr.OFTReal
}
attrs = [{'crop_type': 'test', 'half_sat': 0.5, 'p_managed': 0.5}]
pygeoprocessing.shapely_geometry_to_vector(point_geom,
farm_shape_path,
projection_wkt,
'ESRI Shapefile',
fields=fields,
attribute_list=attrs,
ogr_geom_type=ogr.wkbPoint)
args = {
'results_suffix':
'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table.csv'),
'farm_vector_path':
farm_shape_path,
}
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_bad_farm_type(self):
"""Pollination: ensure detection of bad farm geometry type."""
from natcap.invest import pollination
# make some fake farm points
point_geom = [shapely.geometry.Point(20, -20)]
farm_shape_path = os.path.join(self.workspace_dir, 'point_farm.shp')
# Create the point shapefile
srs = sampledata.SRS_WILLAMETTE
fields = {
'crop_type': 'string',
'half_sat': 'real',
'p_managed': 'real'
}
attrs = [{'crop_type': 'test', 'half_sat': 0.5, 'p_managed': 0.5}]
pygeoprocessing.testing.create_vector_on_disk(
point_geom,
srs.projection,
fields,
attrs,
vector_format='ESRI Shapefile',
filename=farm_shape_path)
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table.csv'),
'farm_vector_path':
farm_shape_path,
}
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_missing_guild_header(self):
"""Pollination: regression testing missing guild headers."""
from natcap.invest import pollination
args = {
'results_suffix':
u'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input',
'pollination_example_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input',
'missing_guild_table_header.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table_simple.csv'),
}
# should error when not finding an expected farm header
with self.assertRaises(ValueError):
pollination.execute(args)
def test_pollination_missing_lulc_values(self):
"""Pollination: testing that model detects missing lulc values."""
from natcap.invest import pollination
import pandas
temp_path = tempfile.mkdtemp(dir=self.workspace_dir)
args = {
'results_suffix':
'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input', 'clipped_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table.csv'),
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input', 'farms.shp'),
}
bad_biophysical_table_path = os.path.join(temp_path,
'bad_biophysical_table.csv')
bio_df = pandas.read_csv(args['landcover_biophysical_table_path'])
bio_df = bio_df[bio_df['lucode'] != 1]
bio_df.to_csv(bad_biophysical_table_path)
bio_df = None
args['landcover_biophysical_table_path'] = bad_biophysical_table_path
with self.assertRaises(ValueError) as cm:
pollination.execute(args)
self.assertTrue(
"The missing values found in the LULC raster but not the table"
" are: [1]" in str(cm.exception))
def test_pollination_too_many_farm_seasons(self):
"""Pollination: regression testing too many seasons in farm."""
from natcap.invest import pollination
args = {
'results_suffix':
'',
'workspace_dir':
self.workspace_dir,
'landcover_raster_path':
os.path.join(REGRESSION_DATA, 'input',
'pollination_example_landcover.tif'),
'guild_table_path':
os.path.join(REGRESSION_DATA, 'input', 'guild_table_simple.csv'),
'landcover_biophysical_table_path':
os.path.join(REGRESSION_DATA, 'input',
'landcover_biophysical_table_simple.csv'),
'farm_vector_path':
os.path.join(REGRESSION_DATA, 'input',
'too_many_seasons_farm.shp'),
}
# should error when not finding an expected farm header
with self.assertRaises(ValueError):
pollination.execute(args)
