def test_geo_cell_data_vector(self):
gcdv = api.GeoCellDataVector()
for i in range(5):
p = api.GeoPoint(100, 200, 300)
ltf = api.LandTypeFractions()
ltf.set_fractions(glacier=0.1, lake=0.1, reservoir=0.1, forest=0.1)
gcd = api.GeoCellData(p, 1000000.0, i, 0.9, ltf)
gcdv.append(gcd)
self.assertEqual(len(gcdv), 5)
for i in range(5):
self.assertEqual(gcdv[i].catchment_id(), i)
def test_geo_cell_data_vector(self):
gcdv = api.GeoCellDataVector()
for i in range(5):
p = api.GeoPoint(100, 200, 300)
ltf = api.LandTypeFractions()
ltf.set_fractions(glacier=0.1, lake=0.1, reservoir=0.1, forest=0.1)
gcd = api.GeoCellData(p, 1000000.0, i, 0.9, ltf)
gcdv.append(gcd)
self.assertEqual(len(gcdv), 5)
for i in range(5):
self.assertEqual(gcdv[i].catchment_id(), i)
g2 = api.GeoCellDataVector(gcdv) # copy construct a new
self.assertTrue(g2 == gcdv)
g2[0].set_catchment_id(10)
self.assertTrue(g2 != gcdv)
# serialize
gcdv_s= gcdv.serialize()
self.assertGreater(len(gcdv_s),2)
gcdv_deserialized = api.GeoCellDataVector.deserialize(gcdv_s)
self.assertIsNotNone(gcdv_deserialized)
self.assertTrue(gcdv_deserialized == gcdv)
def build_model(model_t, parameter_t, model_size, num_catchments=1):
cell_area = 1000 * 1000
region_parameter = parameter_t()
gcds = api.GeoCellDataVector() # creating models from geo_cell-data is easier and more flexible
for i in range(model_size):
gp = api.GeoPoint(500+ 1000.0*i,500.0, 500.0*i/model_size)
cid = 0
if num_catchments > 1:
cid = random.randint(1, num_catchments + 1)
geo_cell_data = api.GeoCellData(gp, cell_area, cid, 0.9, api.LandTypeFractions(0.01, 0.05, 0.19, 0.3, 0.45))
geo_cell_data.land_type_fractions_info().set_fractions(glacier=0.01, lake=0.05, reservoir=0.19, forest=0.3)
gcds.append(geo_cell_data)
return model_t(gcds, region_parameter)
# using a scatter plot of the cells
fig, ax = plt.subplots(figsize=(15, 5))
cm = plt.cm.get_cmap('rainbow')
elv_col = ax.scatter(x, y, c=z, marker='.', s=40, lw=0, cmap=cm)
# cm = plt.cm.get_cmap('gist_gray')
# cid_col = ax.scatter(x, y, c=cid, marker='.', s=40, lw=0, alpha=0.4, cmap=cm)
plt.colorbar(elv_col).set_label('catchment elevation [m]')
# plt.colorbar(cid_col).set_label('catchment indices [id]')
plt.title('Nea Nidelva Catchment')
plt.show()
# print(set(cid))
print(cell_data.variables.keys())
# let's first create a container that will hold all of our module domain cells
cell_data_vector = api.GeoCellDataVector()
# get dimensions from netcdf file
num_cells = cell_data.dimensions['cell'].size
for i in range(num_cells):
gp = api.GeoPoint(x[i], y[i], z[i])
cid = cell_data.variables['catchment_id'][i]
cell_area = cell_data.variables['area'][i]
glac = cell_data.variables['glacier-fraction'][i]
lake = cell_data.variables['lake-fraction'][i]
rsvr = cell_data.variables['reservoir-fraction'][i]
frst = cell_data.variables['forest-fraction'][i]
unsp = 1 - (glac + lake + rsvr + frst)