def test_open_hmdataarray():
# os.chdir('test/release')
modeltime = hm.set_modeltime(
datetime.datetime(2003,6,1),
datetime.datetime(2003,6,30),
datetime.timedelta(days=1)
)
domain = hm.set_domain(
'test_data/qrparm.soil_HWSD_cont_cosbyNew.nc',
modeltime,
'field342',
is_1d=True,
xy_dimname='land'
)
# domain.mask
# domain.starttime
# domain.endtime
# domain.n_timestep
# domain.dt
da = hm.open_hmdataarray(
'test_data/SWdown_WFDEI_land_200306.nc',
'SWdown',
domain,
True,
'land'
)
da = da.select(
time=slice(
datetime.datetime(2003,6,1),
datetime.datetime(2003,6,10)
)
)
def test_open_hmdataarray():
modeltime = hm.set_modeltime(datetime.datetime(2003, 6, 1, 0, 0),
datetime.datetime(2003, 6, 10, 0, 0),
datetime.timedelta(days=1))
domain = hm.set_domain('test_data/ghana_landmask_0pt25degree.tif',
modeltime)
da = hm.open_hmdataarray('test_data/AgMERRA_2003_tavg.nc4', 'tavg', domain)
da.select(time=pd.Timestamp(2003, 6, 1), method='nearest')
def test_set_domain():
modeltime = hm.set_modeltime(
datetime.datetime(2003,6,1),
datetime.datetime(2003,6,30),
datetime.timedelta(days=1)
)
hm.set_domain(
'test_data/qrparm.soil_HWSD_cont_cosbyNew.nc',
modeltime,
'field342',
is_1d=True,
xy_dimname='land'
)
def preprocessor(debug, outputdir, deterministic, montecarlo, kalmanfilter, config):
configuration = AquaCropConfiguration(
config,
outputdir,
debug,
deterministic=deterministic,
montecarlo=montecarlo,
kalmanfilter=kalmanfilter
)
modeltime = set_modeltime(
pd.Timestamp(configuration.CLOCK['start_time']),
pd.Timestamp(configuration.CLOCK['end_time']),
pd.Timedelta('1 day')
)
z_coords = get_z_coords(configuration)
domain = set_domain(
configuration.MODEL_GRID['mask'],
modeltime,
configuration.MODEL_GRID['mask_varname'],
configuration.MODEL_GRID['area_varname'],
configuration.MODEL_GRID['is_1d'],
configuration.MODEL_GRID['xy_dimname'],
z_coords,
configuration.PSEUDO_COORDS
)
# decide whether to preprocess etref
# would this be better as an option?
if configuration.ETREF['preprocess']:
initial_state = None
etref_method = configuration.ETREF['method']
if 'PenmanMonteith' in etref_method:
etref_fn = run_etref(PenmanMonteith, configuration,
modeltime, domain, initial_state)
if 'Hargreaves' in etref_method:
etref_fn = run_etref(Hargreaves, configuration,
modeltime, domain, initial_state)
if 'PriestleyTaylor' in etref_method:
etref_fn = run_etref(PriestleyTaylor, configuration,
modeltime, domain, initial_state)
# Update configuration
configuration.ETREF['filename'] = etref_fn
configuration.ETREF['varname'] = 'etref'
if domain.is_1d:
configuration.ETREF['is_1d'] = True
configuration.ETREF['xy_dimname'] = 'space'
clear_cache()
return configuration, modeltime, domain
def cli(debug, outputdir, config):
# load configuration
configuration = ETRefConfiguration(config, outputdir, debug)
# create modeltime object
print(type(configuration.CLOCK['start_time']))
modeltime = set_modeltime(pd.Timestamp(configuration.CLOCK['start_time']),
pd.Timestamp(configuration.CLOCK['end_time']),
pd.Timedelta('1 day'))
# set model domain
domain = set_domain(
configuration.MODEL_GRID['mask'],
modeltime,
configuration.MODEL_GRID['mask_varname'],
configuration.MODEL_GRID['area_varname'],
configuration.MODEL_GRID['is_1d'],
configuration.MODEL_GRID['xy_dimname'] # ,
# z_coords=None,
# pseudo_coords=configuration.PSEUDO_COORDS
)
def create_dynamic_model(method):
return HmDynamicModel(method, configuration, modeltime, domain,
variable_list, initial_state)
initial_state = None
etref_method = configuration.ET_METHOD['method']
if 'PenmanMonteith' in etref_method:
dynamic_model = create_dynamic_model(PenmanMonteith)
# dynamic_model = HmDynamicModel(
# PenmanMonteith,
# configuration,
# modeltime,
# domain,
# variable_list,
# initial_state
# )
if 'Hargreaves' in etref_method:
dynamic_model = create_dynamic_model(Hargreaves)
if 'PriestleyTaylor' in etref_method:
dynamic_model = create_dynamic_model(PriestleyTaylor)
# run model
dynamic_framework = HmDynamicFramework(dynamic_model, len(modeltime) + 1)
dynamic_framework.setQuiet(True)
dynamic_framework.run()
def main(argv):
disclaimer.print_disclaimer()
# get the full path of the config file provided as system argument
config_filename = os.path.abspath(argv[0])
# determine whether to run the model in debug mode
debug_mode = False
if len(argv) > 2:
if (argv[1] == "debug"):
debug_mode = True
# load configuration
configuration = AquaCropConfiguration(config_filename, debug_mode)
# create modeltime object
modeltime = set_modeltime(pd.Timestamp(configuration.CLOCK['startTime']),
pd.Timestamp(configuration.CLOCK['endTime']),
pd.Timedelta(configuration.CLOCK['timeDelta']))
# retrieve z coordinate information from config
dz_lyr = configuration.SOIL_PROFILE['dzLayer']
z_lyr_bot = np.cumsum(dz_lyr)
z_lyr_top = z_lyr_bot - dz_lyr
z_lyr_mid = (z_lyr_top + z_lyr_bot) / 2
dz_comp = configuration.SOIL_PROFILE['dzComp']
z_comp_bot = np.cumsum(dz_comp)
z_comp_top = z_comp_bot - dz_comp
z_comp_mid = (z_comp_top + z_comp_bot) / 2
z_coords = {'layer': z_lyr_mid, 'depth': z_comp_mid}
# set model domain
domain = set_domain(configuration.MODEL_GRID['mask'], modeltime,
configuration.MODEL_GRID['mask_varname'],
configuration.MODEL_GRID['area_varname'],
configuration.MODEL_GRID['is_1d'],
configuration.MODEL_GRID['xy_dimname'], z_coords,
configuration.PSEUDO_COORDS)
# create dynamic model object
initial_state = None
dynamic_model = HmDynamicModel(AquaCrop, configuration, modeltime, domain,
variable_list, initial_state)
# run model
dynamic_framework = HmDynamicFramework(dynamic_model, len(modeltime) + 1)
dynamic_framework.setQuiet(True)
dynamic_framework.run()
def test_set_domain():
modeltime = hm.set_modeltime(datetime.datetime(2003, 6, 1),
datetime.datetime(2003, 6, 30),
datetime.timedelta(days=1))
hm.set_domain('test_data/ghana_landmask_0pt25degree.tif', modeltime)
import datetime
import hm.api as hm
import xarray as xr
# import pytest
import pandas as pd
import numpy as np
ds = xr.open_dataset(
'~/dev/aquacrop/test/example/Ch7_Ex1a_Tunis_Wheat_1979/Input/annual_co2_conc_aos_ch7_ex1a_tunis_wheat.nc'
)
da = ds['co2']
da.sel({'time': pd.Timestamp('1979-10-15 00:00:00')}, method='nearest')
os.chdir("test/release")
modeltime = hm.set_modeltime(datetime.datetime(2003, 6, 1, 0, 0),
datetime.datetime(2003, 6, 10, 0, 0),
datetime.timedelta(days=1))
# domain = hm.set_domain(
# 'test_data/ghana_landmask_0pt25degree.tif',
# modeltime,
# pseudo_coords={'crop':np.array([0,1,2,3,4])}
# )
# da = hm.open_hmdataarray(
# 'test_data/AgMERRA_2003_tavg.nc4',
# 'tavg',
# domain
# )
# x = da.select(time=pd.Timestamp(2003,6,4), method='nearest')
# x = da.select(time=slice(pd.Timestamp(2003,6,4), pd.Timestamp(2003,6,6)))
def cli(debug, outputdir, deterministic, montecarlo, kalmanfilter, config):
"""Example script"""
if sum([deterministic, montecarlo, kalmanfilter]) != 1:
raise click.UsageError(
"Exactly one of 'deterministic', 'monte-carlo', and 'enkf'"
" must be specified.")
configuration = AquaCropConfiguration(config,
outputdir,
debug,
deterministic=deterministic,
montecarlo=montecarlo,
kalmanfilter=kalmanfilter)
modeltime = set_modeltime(pd.Timestamp(configuration.CLOCK['start_time']),
pd.Timestamp(configuration.CLOCK['end_time']),
pd.Timedelta('1 day'))
# retrieve z coordinate information from config
dz_lyr = configuration.SOIL_PROFILE['dzLayer']
z_lyr_bot = np.cumsum(dz_lyr)
z_lyr_top = z_lyr_bot - dz_lyr
z_lyr_mid = (z_lyr_top + z_lyr_bot) / 2
dz_comp = configuration.SOIL_PROFILE['dzComp']
z_comp_bot = np.cumsum(dz_comp)
z_comp_top = z_comp_bot - dz_comp
z_comp_mid = (z_comp_top + z_comp_bot) / 2
z_coords = {'layer': z_lyr_mid, 'depth': z_comp_mid}
# set model domain
# settings_dir = os.path.split(os.path.abspath(config))[0]
domain = set_domain(
# os.path.join(workdir, configuration.MODEL_GRID['mask']),
configuration.MODEL_GRID['mask'],
modeltime,
configuration.MODEL_GRID['mask_varname'],
configuration.MODEL_GRID['area_varname'],
configuration.MODEL_GRID['is_1d'],
configuration.MODEL_GRID['xy_dimname'],
z_coords,
configuration.PSEUDO_COORDS)
# decide whether to preprocess etref
# would this be better as an option?
if configuration.ETREF['preprocess']:
initial_state = None
etref_method = configuration.ETREF['method']
if 'PenmanMonteith' in etref_method:
etref_fn = run_etref(PenmanMonteith, configuration, modeltime,
domain, initial_state)
if 'Hargreaves' in etref_method:
etref_fn = run_etref(Hargreaves, configuration, modeltime, domain,
initial_state)
if 'PriestleyTaylor' in etref_method:
etref_fn = run_etref(PriestleyTaylor, configuration, modeltime,
domain, initial_state)
# Update configuration
configuration.ETREF['filename'] = etref_fn
configuration.ETREF['varname'] = 'etref'
if domain.is_1d:
configuration.ETREF['is_1d'] = True
configuration.ETREF['xy_dimname'] = 'space'
clear_cache()
# run model using user-specified model framework
initial_state = None
modeltime.reset()
if deterministic:
dynamic_model = HmDynamicModel(AquaCrop, configuration, modeltime,
domain, variable_list_crop,
initial_state)
dynamic_framework = HmDynamicFramework(dynamic_model,
lastTimeStep=len(modeltime) + 1,
firstTimestep=1)
dynamic_framework.setQuiet(True)
dynamic_framework.run()
elif montecarlo:
dynamic_model = HmMonteCarloModel(AquaCrop, configuration, modeltime,
domain, variable_list_crop,
initial_state)
dynamic_framework = HmDynamicFramework(dynamic_model,
lastTimeStep=len(modeltime) + 1,
firstTimestep=1)
dynamic_framework.setQuiet(True)
mc_framework = HmMonteCarloFramework(
dynamic_framework,
nrSamples=int(configuration.MONTE_CARLO['num_samples']))
mc_framework.run()
elif kalmanfilter:
dynamic_model = AqEnKfModel(AquaCrop, configuration, modeltime, domain,
variable_list_crop, initial_state)
dynamic_framework = HmDynamicFramework(dynamic_model,
lastTimeStep=len(modeltime) + 1,
firstTimestep=1)
dynamic_framework.setQuiet(True)
mc_framework = HmMonteCarloFramework(
dynamic_framework,
nrSamples=int(configuration.MONTE_CARLO['num_samples']))
enkf_framework = HmEnsKalmanFilterFramework(mc_framework)
enkf_framework.setFilterTimesteps(
configuration.KALMAN_FILTER['filter_timesteps'])
enkf_framework.run()
def test_set_modeltime():
hm.set_modeltime(
datetime.datetime(2003,6,1),
datetime.datetime(2003,6,30),
datetime.timedelta(days=1)
)