def test_region_model_repository(self):
id_list = [1225]
epsg_id = 32632
# parameters can be loaded from yaml_config Model parameters..
pt_params = api.PriestleyTaylorParameter() # *params["priestley_taylor"])
gs_params = api.GammaSnowParameter() # *params["gamma_snow"])
ss_params = api.SkaugenParameter()
ae_params = api.ActualEvapotranspirationParameter() # *params["act_evap"])
k_params = api.KirchnerParameter() # *params["kirchner"])
p_params = api.PrecipitationCorrectionParameter() # TODO; default 1.0, is it used ??
ptgsk_rm_params = api.pt_gs_k.PTGSKParameter(pt_params, gs_params, ae_params, k_params, p_params)
ptssk_rm_params = api.pt_ss_k.PTSSKParameter(pt_params, ss_params, ae_params, k_params, p_params)
# create the description for 4 models of tistel,ptgsk, ptssk, full and optimized
tistel_grid_spec = GridSpecification(epsg_id=epsg_id, x0=362000.0, y0=6765000.0, dx=1000, dy=1000, nx=8,
ny=8)
cfg_list = [
RegionModelConfig("tistel-ptgsk", PTGSKModel, ptgsk_rm_params, tistel_grid_spec, "unregulated", "FELTNR", id_list),
RegionModelConfig("tistel-ptgsk-opt", PTGSKOptModel, ptgsk_rm_params, tistel_grid_spec, "unregulated", "FELTNR", id_list),
RegionModelConfig("tistel-ptssk", PTSSKModel, ptssk_rm_params, tistel_grid_spec, "unregulated", "FELTNR", id_list)
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rmr = GisRegionModelRepository(rm_cfg_dict) # ok, now we have a Gis RegionModelRepository that can handle all named entities we pass.
cm1 = rmr.get_region_model("tistel-ptgsk") # pull out a PTGSKModel for tistel
cm2 = rmr.get_region_model("tistel-ptgsk-opt")
# Does not work, fail on ct. model:
cm3 = rmr.get_region_model("tistel-ptssk") # pull out a PTGSKModel for tistel
# cm4= rmr.get_region_model("tistel-ptssk",PTSSKOptModel)
self.assertIsNotNone(cm3)
self.assertIsNotNone(cm1)
self.assertIsNotNone(cm2)
self.assertIsNotNone(
cm2.catchment_id_map) # This one is needed in order to properly map catchment-id to internal id
self.assertEqual(cm2.catchment_id_map[0], id_list[0])
def test_region_model_nea_nidelv(self):
nea_nidelv_grid_spec = GridSpecification(epsg_id=32633,
x0=270000.0,
y0=7035000.0,
dx=1000,
dy=1000,
nx=105,
ny=75)
catch_ids = [
1228, 1308, 1394, 1443, 1726, 1867, 1996, 2041, 2129, 2195,
2198, 2277, 2402, 2446, 2465, 2545, 2640, 2718, 3002, 3536,
3630
] # , 1000010, 1000011]
ptgsk_params = self.std_ptgsk_parameters
cfg_list = [
RegionModelConfig("nea-nidelv-ptgsk", PTGSKModel, ptgsk_params,
nea_nidelv_grid_spec, "regulated",
"CATCH_ID", catch_ids)
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rmr = GisRegionModelRepository(rm_cfg_dict)
nea_nidelv = rmr.get_region_model("nea-nidelv-ptgsk")
self.assertIsNotNone(nea_nidelv)
self.assertEqual(len(nea_nidelv.catchment_id_map), len(catch_ids))
print("nea-nidelv:{0}".format(nea_nidelv.catchment_id_map))
def test_region_model_repository(self):
id_list = [1225]
epsg_id = 32632
# parameters can be loaded from yaml_config Model parameters..
pt_params = api.PriestleyTaylorParameter(
) # *params["priestley_taylor"])
gs_params = api.GammaSnowParameter() # *params["gamma_snow"])
ss_params = api.SkaugenParameter()
ae_params = api.ActualEvapotranspirationParameter(
) # *params["act_evap"])
k_params = api.KirchnerParameter() # *params["kirchner"])
p_params = api.PrecipitationCorrectionParameter(
) # TODO; default 1.0, is it used ??
ptgsk_rm_params = api.pt_gs_k.PTGSKParameter(
pt_params, gs_params, ae_params, k_params, p_params)
ptssk_rm_params = api.pt_ss_k.PTSSKParameter(
pt_params, ss_params, ae_params, k_params, p_params)
# create the description for 4 models of tistel,ptgsk, ptssk, full and optimized
tistel_grid_spec = GridSpecification(epsg_id=epsg_id,
x0=362000.0,
y0=6765000.0,
dx=1000,
dy=1000,
nx=8,
ny=8)
cfg_list = [
RegionModelConfig("tistel-ptgsk", PTGSKModel, ptgsk_rm_params,
tistel_grid_spec, "unregulated", "FELTNR",
id_list),
RegionModelConfig("tistel-ptgsk-opt", PTGSKOptModel,
ptgsk_rm_params, tistel_grid_spec,
"unregulated", "FELTNR", id_list),
RegionModelConfig("tistel-ptssk", PTSSKModel, ptssk_rm_params,
tistel_grid_spec, "unregulated", "FELTNR",
id_list)
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rmr = GisRegionModelRepository(
rm_cfg_dict
) # ok, now we have a Gis RegionModelRepository that can handle all named entities we pass.
cm1 = rmr.get_region_model(
"tistel-ptgsk") # pull out a PTGSKModel for tistel
cm2 = rmr.get_region_model("tistel-ptgsk-opt")
# Does not work, fail on ct. model:
cm3 = rmr.get_region_model(
"tistel-ptssk") # pull out a PTGSKModel for tistel
# cm4= rmr.get_region_model("tistel-ptssk",PTSSKOptModel)
self.assertIsNotNone(cm3)
self.assertIsNotNone(cm1)
self.assertIsNotNone(cm2)
self.assertIsNotNone(
cm2.catchment_id_map
) # This one is needed in order to properly map catchment-id to internal id
self.assertEqual(cm2.catchment_id_map[0], id_list[0])
def test_region_model_nea_nidelv(self):
nea_nidelv_grid_spec = GridSpecification(epsg_id=32633, x0=270000.0, y0=7035000.0, dx=1000, dy=1000, nx=105, ny=75)
catch_ids = [1228, 1308, 1394, 1443, 1726, 1867, 1996, 2041, 2129, 2195, 2198, 2277, 2402, 2446, 2465, 2545,
2640, 2718, 3002, 3536, 3630, 1000010, 1000011]
ptgsk_params = self.std_ptgsk_parameters
cfg_list = [
RegionModelConfig("nea-nidelv-ptgsk", PTGSKModel, ptgsk_params, nea_nidelv_grid_spec, "regulated", "CATCH_ID", catch_ids)
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rmr = GisRegionModelRepository(rm_cfg_dict)
nea_nidelv = rmr.get_region_model("nea-nidelv-ptgsk")
self.assertIsNotNone(nea_nidelv)
self.assertEqual(len(nea_nidelv.catchment_id_map), len(catch_ids))
print("nea-nidelv:{0}".format(nea_nidelv.catchment_id_map))
def region_model_repository(self):
"""
Returns
-------
- RegionModelRepository - configured with 'Tistel-ptgsk' etc.
"""
id_list = [1225]
# parameters can be loaded from yaml_config Model parameters..
pt_params = api.PriestleyTaylorParameter(
) # *params["priestley_taylor"])
gs_params = api.GammaSnowParameter() # *params["gamma_snow"])
ss_params = api.SkaugenParameter()
ae_params = api.ActualEvapotranspirationParameter(
) # *params["act_evap"])
k_params = api.KirchnerParameter() # *params["kirchner"])
p_params = api.PrecipitationCorrectionParameter(
) # TODO; default 1.0, is it used ??
ptgsk_rm_params = pt_gs_k.PTGSKParameter(pt_params, gs_params,
ae_params, k_params,
p_params)
ptssk_rm_params = pt_ss_k.PTSSKParameter(pt_params, ss_params,
ae_params, k_params,
p_params)
# create the description for 2 models of tistel,ptgsk, ptssk
tistel_grid_spec = self.grid_spec #
cfg_list = [
RegionModelConfig("Tistel-ptgsk", pt_gs_k.PTGSKModel,
ptgsk_rm_params, tistel_grid_spec,
"unregulated", "FELTNR", id_list),
RegionModelConfig("Tistel-ptssk", pt_ss_k.PTSSKModel,
ptssk_rm_params, tistel_grid_spec,
"unregulated", "FELTNR", id_list)
]
rm_cfg_dict = {x.name: x for x in cfg_list}
return GisRegionModelRepository(rm_cfg_dict)
def create_tistel_simulator(model, geo_ts_repository):
region_id = "Tistel-ptgsk"
interpolation_id = 0
cfg_list = [RegionModelConfig(region_id, model, tistel.pt_gs_k_parameters(),
tistel.grid_spec, tistel.gis_table_def[0],
tistel.gis_table_def[1], tistel.catchment_id_list)]
reg_model_repository = GisRegionModelRepository({x.name: x for x in cfg_list})
ptgsk = Simulator(region_id, interpolation_id, reg_model_repository,
geo_ts_repository,
tistel.interpolation_repository, None)
return ptgsk
def statkraft_region_model_repo_constructor(region_config, model_config,
region_model_id):
from shyft.repository.service.gis_region_model_repository import GisRegionModelRepository
from shyft.repository.service.gis_region_model_repository import RegionModelConfig
from shyft.repository.service.gis_region_model_repository import GridSpecification
from six import iteritems # This replaces dictionary.iteritems() on Python 2 and dictionary.items() on Python 3
repo_params = region_config.repository()['params']
d = region_config.domain()
grid_specification = GridSpecification(d['EPSG'], d['lower_left_x'],
d['lower_left_y'], d['step_x'],
d['step_y'], d['nx'], d['ny'])
region_model_type = model_config.model_type()
# Construct region parameter:
name_map = {
"gamma_snow": "gs",
"priestley_taylor": "pt",
"kirchner": "kirchner",
"actual_evapotranspiration": "ae",
"skaugen": "skaugen",
"hbv_snow": "snow"
}
region_parameter = region_model_type.parameter_t()
for p_type_name, value_ in iteritems(model_config.model_parameters()):
if p_type_name in name_map:
if hasattr(region_parameter, name_map[p_type_name]):
sub_param = getattr(region_parameter, name_map[p_type_name])
for p, v in iteritems(value_):
if hasattr(sub_param, p):
setattr(sub_param, p, v)
else:
raise ConfigError(
"Invalid parameter '{}' for parameter set '{}'".
format(p, p_type_name))
else:
raise ConfigError(
"Invalid parameter set '{}' for selected model '{}'".
format(p_type_name, region_model_type.__name__))
elif p_type_name == "p_corr_scale_factor":
region_parameter.p_corr.scale_factor = value_
else:
raise ConfigError("Unknown parameter set '{}'".format(p_type_name))
cfg_list = [
RegionModelConfig(region_model_id, region_model_type, region_parameter,
grid_specification,
repo_params['catchment_regulated_type'],
repo_params['service_id_field_name'],
region_config.catchments()),
]
rm_cfg_dict = {x.name: x for x in cfg_list}
return GisRegionModelRepository(rm_cfg_dict)
def test_serialize_and_deserialize(self):
rm_type = pt_gs_k.PTGSKModel
reg_param = rm_type.parameter_t()
epsg_id = 32633
catchment_type = 'regulated'
identifier = 'SUBCATCH_ID'
dxy = 1000.
pad = 5
# LTM5-Tya
id_list = [172, 174, 177, 185, 187, 190]
grid_specification = get_grid_spec_from_catch_poly(
id_list, catchment_type, identifier, epsg_id, dxy, pad)
# LTM5-Nea
id_list_1 = [180, 188, 191, 196]
grid_specification_1 = get_grid_spec_from_catch_poly(
id_list_1, catchment_type, identifier, epsg_id, dxy, pad)
cfg_list = [
RegionModelConfig('Tya', rm_type, reg_param,
grid_specification, catchment_type,
identifier, id_list),
RegionModelConfig('Nea', rm_type, reg_param,
grid_specification_1, catchment_type,
identifier, id_list_1),
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rm_repo = GisRegionModelRepository(rm_cfg_dict, use_cache=True)
# Start by removing existing cache file
GisRegionModelRepository.remove_cache(identifier,
grid_specification)
# Update cache with Nea cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier,
grid_specification_1,
id_list_1)
# Construct a region_model for Tya - this process should automatically append Tya cell_data to cache
rm = rm_repo.get_region_model('Tya')
cells_from_rm = rm.get_cells()
# Get Tya cell_data from the region_model
cell_data_from_region_model = cells_from_rm.geo_cell_data_vector(
cells_from_rm).to_numpy().reshape(-1, 11)
# Get Tya cell_data from auto generated cache
cell_data_from_auto_cache = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification, id_list)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier,
grid_specification)
# Update cache with Tya cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier,
grid_specification, id_list)
# Update cache with Nea cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier,
grid_specification_1,
id_list_1)
# Get Tya cell_data from updated cache
cell_data_from_updated_cache = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification, id_list)
# Get Nea cell_data from updated cache
cell_data_from_updated_cache_1 = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification_1, id_list_1)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier,
grid_specification)
# Get Nea cell_data from GIS
cell_data_from_gis_1 = GisRegionModelRepository.get_cell_data_from_gis(
catchment_type, identifier, grid_specification_1, id_list_1)
# Get Tya cell_data from GIS
cell_data_from_gis = GisRegionModelRepository.get_cell_data_from_gis(
catchment_type, identifier, grid_specification, id_list)
# Update cache with Tya cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier,
grid_specification, id_list)
# Construct a region_model for Nea - this process should automatically append Nea cell_data to cache')
rm_1 = rm_repo.get_region_model('Nea')
cells_from_rm_1 = rm_1.get_cells()
# Get Nea cell_data from the region_model
cell_data_from_region_model_1 = cells_from_rm_1.geo_cell_data_vector(
cells_from_rm_1).to_numpy().reshape(-1, 11)
# Get Nea cell_data from auto generated cache
cell_data_from_auto_cache_1 = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification_1, id_list_1)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier,
grid_specification)
# Comparing results...
# Arrays to compare
# Tya
# cell_data_from_region_model, cell_data_from_auto_cache, cell_data_from_updated_cache, cell_data_from_gis
atol = 1e-08
self.assertTrue(
np.allclose(cell_data_from_region_model,
cell_data_from_gis['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_auto_cache['geo_data'],
cell_data_from_gis['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_updated_cache['geo_data'],
cell_data_from_gis['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(rm.catchment_id_map,
cell_data_from_gis['cid_map'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_auto_cache['cid_map'],
cell_data_from_gis['cid_map'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_updated_cache['cid_map'],
cell_data_from_gis['cid_map'],
atol=atol))
# Nea
# cell_data_from_region_model_1, cell_data_from_auto_cache_1, cell_data_from_updated_cache_1, cell_data_from_gis_1
self.assertTrue(
np.allclose(cell_data_from_region_model_1,
cell_data_from_gis_1['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_auto_cache_1['geo_data'],
cell_data_from_gis_1['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_updated_cache_1['geo_data'],
cell_data_from_gis_1['geo_data'],
atol=atol))
self.assertTrue(
np.allclose(rm_1.catchment_id_map,
cell_data_from_gis_1['cid_map'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_auto_cache_1['cid_map'],
cell_data_from_gis_1['cid_map'],
atol=atol))
self.assertTrue(
np.allclose(cell_data_from_updated_cache_1['cid_map'],
cell_data_from_gis_1['cid_map'],
atol=atol))
def test_serialize_and_deserialize(self):
rm_type = pt_gs_k.PTGSKModel
reg_param = rm_type.parameter_t()
epsg_id = 32633
catchment_type = 'regulated'
identifier = 'SUBCATCH_ID'
dxy = 1000.
pad = 5
# LTM5-Tya
id_list = [172, 174, 177, 185, 187, 190]
grid_specification = get_grid_spec_from_catch_poly(id_list, catchment_type, identifier, epsg_id, dxy, pad)
# LTM5-Nea
id_list_1 = [180, 188, 191, 196]
grid_specification_1 = get_grid_spec_from_catch_poly(id_list_1, catchment_type, identifier, epsg_id, dxy, pad)
cfg_list = [
RegionModelConfig('Tya', rm_type, reg_param, grid_specification, catchment_type, identifier, id_list),
RegionModelConfig('Nea', rm_type, reg_param, grid_specification_1, catchment_type, identifier, id_list_1),
]
rm_cfg_dict = {x.name: x for x in cfg_list}
rm_repo = GisRegionModelRepository(rm_cfg_dict, use_cache=True)
# Start by removing existing cache file
GisRegionModelRepository.remove_cache(identifier, grid_specification)
# Update cache with Nea cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier, grid_specification_1, id_list_1)
# Construct a region_model for Tya - this process should automatically append Tya cell_data to cache
rm = rm_repo.get_region_model('Tya')
cells_from_rm = rm.get_cells()
# Get Tya cell_data from the region_model
cell_data_from_region_model = cells_from_rm.geo_cell_data_vector(cells_from_rm).to_numpy().reshape(-1, 11)
# Get Tya cell_data from auto generated cache
cell_data_from_auto_cache = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification, id_list)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier, grid_specification)
# Update cache with Tya cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier, grid_specification, id_list)
# Update cache with Nea cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier, grid_specification_1, id_list_1)
# Get Tya cell_data from updated cache
cell_data_from_updated_cache = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification, id_list)
# Get Nea cell_data from updated cache
cell_data_from_updated_cache_1 = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification_1, id_list_1)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier, grid_specification)
# Get Nea cell_data from GIS
cell_data_from_gis_1 = GisRegionModelRepository.get_cell_data_from_gis(
catchment_type, identifier, grid_specification_1, id_list_1)
# Get Tya cell_data from GIS
cell_data_from_gis = GisRegionModelRepository.get_cell_data_from_gis(
catchment_type, identifier, grid_specification, id_list)
# Update cache with Tya cell_data
GisRegionModelRepository.update_cache(catchment_type, identifier, grid_specification, id_list)
# Construct a region_model for Nea - this process should automatically append Nea cell_data to cache')
rm_1 = rm_repo.get_region_model('Nea')
cells_from_rm_1 = rm_1.get_cells()
# Get Nea cell_data from the region_model
cell_data_from_region_model_1 = cells_from_rm_1.geo_cell_data_vector(cells_from_rm_1).to_numpy().reshape(-1, 11)
# Get Nea cell_data from auto generated cache
cell_data_from_auto_cache_1 = GisRegionModelRepository.get_cell_data_from_cache(
identifier, grid_specification_1, id_list_1)
# Remove the cache file
GisRegionModelRepository.remove_cache(identifier, grid_specification)
# Comparing results...
# Arrays to compare
# Tya
# cell_data_from_region_model, cell_data_from_auto_cache, cell_data_from_updated_cache, cell_data_from_gis
atol = 1e-08
self.assertTrue(np.allclose(cell_data_from_region_model, cell_data_from_gis['geo_data'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_auto_cache['geo_data'], cell_data_from_gis['geo_data'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_updated_cache['geo_data'], cell_data_from_gis['geo_data'], atol=atol))
self.assertTrue(np.allclose(rm.catchment_id_map, cell_data_from_gis['cid_map'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_auto_cache['cid_map'], cell_data_from_gis['cid_map'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_updated_cache['cid_map'], cell_data_from_gis['cid_map'], atol=atol))
# Nea
# cell_data_from_region_model_1, cell_data_from_auto_cache_1, cell_data_from_updated_cache_1, cell_data_from_gis_1
self.assertTrue(np.allclose(cell_data_from_region_model_1, cell_data_from_gis_1['geo_data'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_auto_cache_1['geo_data'], cell_data_from_gis_1['geo_data'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_updated_cache_1['geo_data'], cell_data_from_gis_1['geo_data'], atol=atol))
self.assertTrue(np.allclose(rm_1.catchment_id_map, cell_data_from_gis_1['cid_map'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_auto_cache_1['cid_map'], cell_data_from_gis_1['cid_map'], atol=atol))
self.assertTrue(np.allclose(cell_data_from_updated_cache_1['cid_map'], cell_data_from_gis_1['cid_map'], atol=atol))
