def test_regular_lattice(self):
# 4x4 regular lattice with the exterior
known = [P00, P10]
bounds = (0, 0, 3, 3)
lattice = self.spaghetti.regular_lattice(bounds, 2, nv=2, exterior=True)
observed = lattice[0].vertices
self.assertEqual(observed, known)
# 5x5 regular lattice without the exterior
known = [P33, P34]
bounds = (0, 0, 4, 4)
lattice = self.spaghetti.regular_lattice(bounds, 3, exterior=False)
observed = lattice[-1].vertices
self.assertEqual(observed, known)
# 7x9 regular lattice from shapefile bounds
known_vertices = [
(723414.3683108028, 875929.0396895551),
(724286.1381211297, 875929.0396895551),
]
shp = io.open(STREETS)
lattice = self.spaghetti.regular_lattice(shp.bbox, 5, nv=7, exterior=True)
observed_vertices = lattice[0].vertices
for observed, known in zip(observed_vertices, known_vertices):
self.assertEqual((observed[0], observed[1]), known)
# test for Type Error
with self.assertRaises(TypeError):
self.spaghetti.regular_lattice(bounds, [[4]])
# test for Runtime Error
with self.assertRaises(RuntimeError):
self.spaghetti.regular_lattice((0, 0, 1), 1)
def setUp(self):
data_path = ps.examples.get_path("GData_utm.csv")
data = io.open(data_path)
self.coords = list(zip(data.by_col('X'), data.by_col('Y')))
self.y = np.array(data.by_col('PctBach')).reshape((-1, 1))
rural = np.array(data.by_col('PctRural')).reshape((-1, 1))
pov = np.array(data.by_col('PctPov')).reshape((-1, 1))
black = np.array(data.by_col('PctBlack')).reshape((-1, 1))
fb = np.array(data.by_col('PctFB')).reshape((-1, 1))
self.X = np.hstack([rural, pov, black])
self.mgwr_X = np.hstack([fb, black, rural])
def setUp(self):
data_path = os.path.join(os.path.dirname(__file__),'georgia/GData_utm.csv')
#data = libpysal.open(data_path)
data = io.open(data_path)
self.coords = list(zip(data.by_col('X'), data.by_col('Y')))
self.y = np.array(data.by_col('PctBach')).reshape((-1,1))
rural = np.array(data.by_col('PctRural')).reshape((-1,1))
pov = np.array(data.by_col('PctPov')).reshape((-1,1))
black = np.array(data.by_col('PctBlack')).reshape((-1,1))
fb = np.array(data.by_col('PctFB')).reshape((-1,1))
self.X = np.hstack([rural, pov, black])
self.mgwr_X = np.hstack([fb, black, rural])
def setUp(self):
data_path = os.path.join(os.path.dirname(__file__),
'tokyo/Tokyomortality.csv')
data = io.open(data_path, mode='Ur')
self.coords = list(
zip(data.by_col('X_CENTROID'), data.by_col('Y_CENTROID')))
self.y = np.array(data.by_col('db2564')).reshape((-1, 1))
self.off = np.array(data.by_col('eb2564')).reshape((-1, 1))
OCC = np.array(data.by_col('OCC_TEC')).reshape((-1, 1))
OWN = np.array(data.by_col('OWNH')).reshape((-1, 1))
POP = np.array(data.by_col('POP65')).reshape((-1, 1))
UNEMP = np.array(data.by_col('UNEMP')).reshape((-1, 1))
self.X = np.hstack([OCC, OWN, POP, UNEMP])
