def run_tr55(census, model_input):
"""
A thin Celery wrapper around our TR55 implementation.
"""
et_max = 0.207
precip = _get_precip_value(model_input)
if precip is None:
raise Exception('No precipitation value defined')
# TODO: These next two lines are just for
# demonstration purposes.
modifications = get_census_modifications(model_input)
census['modifications'] = modifications
def simulate_day(cell, cell_count):
soil_type, land_use = cell.lower().split(':')
et = et_max * lookup_ki(land_use)
return simulate_cell_day((precip, et), cell, cell_count)
model_output = simulate_modifications(census, fn=simulate_day)
return {
'inputmod_hash': model_input['inputmod_hash'],
'census': census,
'runoff': model_output,
'quality': format_quality(model_output)
}
def run_tr55(census, model_input):
"""
A thin Celery wrapper around our TR55 implementation.
"""
et_max = 0.207
precip = model_input['precip']
# TODO: These next two lines are just for
# demonstration purposes.
modifications = get_census_modifications(model_input)
census['modifications'] = modifications
print(census)
def simulate_day(cell, cell_count):
soil_type, land_use = cell.lower().split(':')
et = et_max * lookup_ki(land_use)
return simulate_cell_day((precip, et), cell, cell_count)
model_output = simulate_modifications(census, fn=simulate_day)
return {
'runoff': model_output,
'quality': format_quality(model_output)
}
def run_tr55(census, model_input):
"""
A thin Celery wrapper around our TR55 implementation.
"""
et_max = 0.207
precip = _get_precip_value(model_input)
if precip is None:
raise Exception('No precipitation value defined')
# TODO: These next two lines are just for
# demonstration purposes.
modifications = get_census_modifications(model_input)
census['modifications'] = modifications
def simulate_day(cell, cell_count):
soil_type, land_use = cell.lower().split(':')
et = et_max * lookup_ki(land_use)
return simulate_cell_day((precip, et), cell, cell_count)
model_output = simulate_modifications(census, fn=simulate_day)
return {
'inputmod_hash': model_input['inputmod_hash'],
'census': census,
'runoff': model_output,
'quality': format_quality(model_output)
}
'desert'
]
soil_types = ['a', 'b', 'c', 'd']
et_max = 0.207
pre_columbian = False
# For each input value, compute the model outputs for a
# single day and tile.
for precip, land_use, soil_type in product(precips,
land_uses,
soil_types):
cells = {
'cell_count': 1,
'distribution': {
'%s:%s' % (soil_type, land_use): {'cell_count': 1}
}
}
def fn(cell, cell_count):
(soil_type, land_use) = cell.lower().split(':')
et = et_max * lookup_ki(land_use)
return simulate_cell_day((precip, et), cell, cell_count)
model_out = (simulate_modifications(cells, fn=fn)
['unmodified']['distribution'].values()[0])
writer.writerow((precip, land_use,
soil_type, model_out['et'],
model_out['inf'], model_out['runoff']))
