def main2():
seims_cfg = ParseSEIMSConfig()
seims_cfg.db_name = 'youwuzhen10m_longterm_model'
thresholds = {18: [18, 72, 288, 0.1, -0.1]}
fuzzyslppos_fnames = [(1, 'summit', 'rdgInf'), (4, 'backslope', 'bksInf'),
(16, 'valley', 'vlyInf')]
outfname = 'SLPPOS_UNITS_10121314'
hillslp_data = DelinateSlopePositionByThreshold(seims_cfg, thresholds,
fuzzyslppos_fnames,
outfname)
print(hillslp_data)
def __init__(self, cf, method='nsga2'):
# type: (ConfigParser, str) -> None
"""Initialization."""
# 1. SEIMS model related
self.model = ParseSEIMSConfig(cf)
# 2. Common settings of auto-calibration
if 'CALI_Settings' not in cf.sections():
raise ValueError("[CALI_Settings] section MUST be existed in *.ini file.")
self.param_range_def = 'cali_param_rng.def'
if cf.has_option('CALI_Settings', 'paramrngdef'):
self.param_range_def = cf.get('CALI_Settings', 'paramrngdef')
self.param_range_def = self.model.model_dir + os.path.sep + self.param_range_def
if not FileClass.is_file_exists(self.param_range_def):
raise IOError('Ranges of parameters MUST be provided!')
# UTCTIME of calibration and validation (optional) periods
if not (cf.has_option('CALI_Settings', 'cali_time_start') and
cf.has_option('CALI_Settings', 'cali_time_end')):
raise ValueError("Start and end time of Calibration "
"MUST be specified in [CALI_Settings].")
self.cali_stime = parse_datetime_from_ini(cf, 'CALI_Settings', 'cali_time_start')
self.cali_etime = parse_datetime_from_ini(cf, 'CALI_Settings', 'cali_time_end')
self.vali_stime = parse_datetime_from_ini(cf, 'CALI_Settings', 'vali_time_start')
self.vali_etime = parse_datetime_from_ini(cf, 'CALI_Settings', 'vali_time_end')
self.calc_validation = True if self.vali_stime and self.vali_etime else False
if self.cali_stime >= self.cali_etime or (self.calc_validation and
self.vali_stime >= self.vali_etime):
raise ValueError("Wrong time settings in [CALI_Settings]!")
# 3. Parameters settings for specific optimization algorithm
self.opt_mtd = method
self.opt = None
if self.opt_mtd == 'nsga2':
self.opt = ParseNSGA2Config(cf, self.model.model_dir, 'CALI_NSGA2_Gen_%d_Pop_%d')
def __init__(self, cf, method='morris'):
"""Initialization."""
self.method = method
# 1. SEIMS model related
self.model = ParseSEIMSConfig(cf)
# 2. Common settings of parameters sensitivity analysis
if 'PSA_Settings' not in cf.sections():
raise ValueError(
"[PSA_Settings] section MUST be existed in *.ini file.")
self.evaluate_params = list()
if cf.has_option('PSA_Settings', 'evaluateparam'):
eva_str = cf.get('PSA_Settings', 'evaluateparam')
self.evaluate_params = StringClass.split_string(eva_str, ',')
else:
self.evaluate_params = ['Q'] # Default
self.param_range_def = 'morris_param_rng.def' # Default
if cf.has_option('PSA_Settings', 'paramrngdef'):
self.param_range_def = cf.get('PSA_Settings', 'paramrngdef')
self.param_range_def = self.model.model_dir + os.path.sep + self.param_range_def
if not FileClass.is_file_exists(self.param_range_def):
raise IOError('Ranges of parameters MUST be provided!')
if not (cf.has_option('PSA_Settings', 'psa_time_start')
and cf.has_option('PSA_Settings', 'psa_time_end')):
raise ValueError(
"Start and end time of PSA MUST be specified in [PSA_Settings]."
)
try:
# UTCTIME
tstart = cf.get('PSA_Settings', 'psa_time_start')
tend = cf.get('PSA_Settings', 'psa_time_end')
self.psa_stime = StringClass.get_datetime(tstart)
self.psa_etime = StringClass.get_datetime(tend)
except ValueError:
raise ValueError('The time format MUST be"YYYY-MM-DD HH:MM:SS".')
if self.psa_stime >= self.psa_etime:
raise ValueError("Wrong time settings in [PSA_Settings]!")
# 3. Parameters settings for specific sensitivity analysis methods
self.morris = None
self.fast = None
if self.method == 'fast':
self.fast = FASTConfig(cf)
self.psa_outpath = '%s/PSA_FAST_N%dM%d' % (
self.model.model_dir, self.fast.N, self.fast.M)
elif self.method == 'morris':
self.morris = MorrisConfig(cf)
self.psa_outpath = '%s/PSA_Morris_N%dL%d' % (
self.model.model_dir, self.morris.N, self.morris.num_levels)
# 4. (Optional) Plot settings for matplotlib
self.plot_cfg = PlotConfig(cf)
# Do not remove psa_outpath if already existed
UtilClass.mkdir(self.psa_outpath)
self.outfiles = PSAOutputs(self.psa_outpath)
def write_runmodel_config_file(mpaths, org_file_name):
org_cfg_file = mpaths.cfg_dir + os.path.sep + org_file_name
runmodel_cfg_file = mpaths.workspace + os.path.sep + org_file_name
cfg_items = list()
with open(org_cfg_file, 'r', encoding='utf-8') as f:
for line in f.readlines():
cfg_items.append(line.strip())
cfg_items.append('MODEL_DIR = %s' % mpaths.model_dir)
cfg_items.append('BIN_DIR = %s' % mpaths.bin_dir)
with open(runmodel_cfg_file, 'w', encoding='utf-8') as f:
for item in cfg_items:
f.write('%s\n' % item)
cf = ConfigParser()
cf.read(runmodel_cfg_file)
return ParseSEIMSConfig(cf)
def __init__(self, cf, method='nsga2'):
"""Initialization."""
# 1. SEIMS model related
self.model = ParseSEIMSConfig(cf)
# 2. Common settings of auto-calibration
if 'CALI_Settings' not in cf.sections():
raise ValueError(
"[CALI_Settings] section MUST be existed in *.ini file.")
self.param_range_def = 'cali_param_rng.def'
if cf.has_option('CALI_Settings', 'paramrngdef'):
self.param_range_def = cf.get('CALI_Settings', 'paramrngdef')
self.param_range_def = self.model.model_dir + os.path.sep + self.param_range_def
if not FileClass.is_file_exists(self.param_range_def):
raise IOError('Ranges of parameters MUST be provided!')
if not (cf.has_option('CALI_Settings', 'cali_time_start')
and cf.has_option('CALI_Settings', 'cali_time_end')):
raise ValueError("Start and end time of Calibration "
"MUST be specified in [CALI_Settings].")
try: # UTCTIME
tstart = cf.get('CALI_Settings', 'cali_time_start')
tend = cf.get('CALI_Settings', 'cali_time_end')
self.cali_stime = StringClass.get_datetime(tstart)
self.cali_etime = StringClass.get_datetime(tend)
self.calc_validation = False
if cf.has_option('CALI_Settings', 'vali_time_start') and \
cf.has_option('CALI_Settings', 'vali_time_end'):
tstart = cf.get('CALI_Settings', 'vali_time_start')
tend = cf.get('CALI_Settings', 'vali_time_end')
self.vali_stime = StringClass.get_datetime(tstart)
self.vali_etime = StringClass.get_datetime(tend)
self.calc_validation = True
except ValueError:
raise ValueError(
'The time format MUST be "YYYY-MM-DD" or "YYYY-MM-DD HH:MM:SS".'
)
if self.cali_stime >= self.cali_etime or (
self.calc_validation and self.vali_stime >= self.vali_etime):
raise ValueError("Wrong time setted in [CALI_Settings]!")
# 3. Parameters settings for specific optimization algorithm
self.opt_mtd = method
self.opt = None
if self.opt_mtd == 'nsga2':
self.opt = ParseNSGA2Config(cf, self.model.model_dir)
def __init__(self, cf):
"""Initialization."""
# 1. SEIMS model related
self.model_cfg = ParseSEIMSConfig(cf)
# 2. Parameters
self.plt_subbsnid = -1
self.plt_vars = list()
if 'PARAMETERS' in cf.sections():
self.plt_subbsnid = cf.getint('PARAMETERS', 'plot_subbasinid')
plt_vars_str = cf.get('PARAMETERS', 'plot_variables')
else:
raise ValueError(
"[PARAMETERS] section MUST be existed in *.ini file.")
if self.plt_subbsnid < 0:
raise ValueError(
"PLOT_SUBBASINID must be greater or equal than 0.")
if plt_vars_str != '':
self.plt_vars = StringClass.split_string(plt_vars_str)
else:
raise ValueError("PLOT_VARIABLES illegal defined in [PARAMETERS]!")
# 3. Optional_Parameters
if 'OPTIONAL_PARAMETERS' not in cf.sections():
raise ValueError(
"[OPTIONAL_PARAMETERS] section MUST be existed in *.ini file.")
# UTCTIME
self.cali_stime = parse_datetime_from_ini(cf, 'OPTIONAL_PARAMETERS',
'cali_time_start')
self.cali_etime = parse_datetime_from_ini(cf, 'OPTIONAL_PARAMETERS',
'cali_time_end')
self.vali_stime = parse_datetime_from_ini(cf, 'OPTIONAL_PARAMETERS',
'vali_time_start')
self.vali_etime = parse_datetime_from_ini(cf, 'OPTIONAL_PARAMETERS',
'vali_time_end')
if not self.cali_stime or not self.cali_etime or self.cali_stime >= self.cali_etime:
raise ValueError(
"Wrong time settings of calibration in [OPTIONAL_PARAMETERS]!")
if self.vali_stime and self.vali_etime and self.vali_stime >= self.vali_etime:
raise ValueError(
"Wrong time settings of validation in [OPTIONAL_PARAMETERS]!")
# 4. Switches
self.lang_cn = False
if 'SWITCH' in cf.sections():
self.lang_cn = cf.getboolean('SWITCH', 'lang_cn')
def __init__(self, cf, method='nsga2'):
# type: (ConfigParser, str) -> None
"""Initialization."""
# 1. SEIMS model related
self.model = ParseSEIMSConfig(cf) # type: ParseSEIMSConfig
# 2. Common settings of BMPs scenario
self.eval_stime = None # type: Optional[datetime]
self.eval_etime = None # type: Optional[datetime]
self.worst_econ = 0.
self.worst_env = 0.
self.runtime_years = 0.
self.export_sce_txt = False
self.export_sce_tif = False
if 'Scenario_Common' not in cf.sections():
raise ValueError(
'[Scenario_Common] section MUST be existed in *.ini file.')
self.eval_stime = parse_datetime_from_ini(cf, 'Scenario_Common',
'eval_time_start')
self.eval_etime = parse_datetime_from_ini(cf, 'Scenario_Common',
'eval_time_end')
self.worst_econ = cf.getfloat('Scenario_Common', 'worst_economy')
self.worst_env = cf.getfloat('Scenario_Common', 'worst_environment')
self.runtime_years = cf.getfloat('Scenario_Common', 'runtime_years')
if cf.has_option('Scenario_Common', 'export_scenario_txt'):
self.export_sce_txt = cf.getboolean('Scenario_Common',
'export_scenario_txt')
if cf.has_option('Scenario_Common', 'export_scenario_tif'):
self.export_sce_tif = cf.getboolean('Scenario_Common',
'export_scenario_tif')
# 3. Application specific setting section [BMPs]
# Selected BMPs, the key is BMPID, and value is the BMP information dict
self.bmps_info = dict(
) # type: Dict[int, Dict[AnyStr, Union[int, float, AnyStr, List[Union[int, float, AnyStr]]]]]
# BMPs to be constant for generated scenarios during optimization, same format with bmps_info
self.bmps_retain = dict(
) # type: Dict[int, Dict[AnyStr, Union[int, float, AnyStr, List[Union[int, float, AnyStr]]]]]
self.eval_info = dict(
) # type: Dict[AnyStr, Union[int, float, AnyStr]]
self.bmps_cfg_unit = 'CONNFIELD' # type: AnyStr
self.bmps_cfg_method = 'RAND' # type: AnyStr
if 'BMPs' not in cf.sections():
raise ValueError(
'[BMPs] section MUST be existed for specific scenario analysis.'
)
bmpsinfostr = cf.get('BMPs', 'bmps_info')
self.bmps_info = UtilClass.decode_strs_in_dict(json.loads(bmpsinfostr))
if cf.has_option('BMPs', 'bmps_retain'):
bmpsretainstr = cf.get('BMPs', 'bmps_retain')
self.bmps_retain = json.loads(bmpsretainstr)
self.bmps_retain = UtilClass.decode_strs_in_dict(self.bmps_retain)
evalinfostr = cf.get('BMPs', 'eval_info')
self.eval_info = UtilClass.decode_strs_in_dict(json.loads(evalinfostr))
bmpscfgunitstr = cf.get('BMPs', 'bmps_cfg_units')
bmpscfgunitdict = UtilClass.decode_strs_in_dict(
json.loads(bmpscfgunitstr))
for unitname, unitcfg in viewitems(bmpscfgunitdict):
self.bmps_cfg_unit = unitname
if self.bmps_cfg_unit not in BMPS_CFG_UNITS:
raise ValueError('BMPs configuration unit MUST be '
'one of %s' % BMPS_CFG_UNITS.__str__())
if not isinstance(unitcfg, dict):
raise ValueError(
'The value of BMPs configuration unit MUST be dict value!')
for cfgname, cfgvalue in viewitems(unitcfg):
for bmpid, bmpdict in viewitems(self.bmps_info):
if cfgname in bmpdict:
continue
self.bmps_info[bmpid][cfgname] = cfgvalue
break
if cf.has_option('BMPs', 'bmps_cfg_method'):
self.bmps_cfg_method = cf.get('BMPs', 'bmps_cfg_method')
if self.bmps_cfg_method not in BMPS_CFG_METHODS:
print('BMPs configuration method MUST be one of %s' %
BMPS_CFG_METHODS.__str__())
self.bmps_cfg_method = 'RAND'
# Check the validation of configuration unit and method
if self.bmps_cfg_method not in BMPS_CFG_PAIR.get(self.bmps_cfg_unit):
raise ValueError('BMPs configuration method %s '
'is not supported on unit %s' %
(self.bmps_cfg_method, self.bmps_cfg_unit))
# Optimize boundary of BMP configuration unit
self.boundary_adaptive = False
self.boundary_adaptive_threshs = None
if cf.has_option('BMPs', 'bmps_cfg_units_opt'):
self.boundary_adaptive = cf.getboolean('BMPs',
'bmps_cfg_units_opt')
if cf.has_option('BMPs', 'boundary_adaptive_threshold'):
tstr = cf.get('BMPs', 'boundary_adaptive_threshold')
self.boundary_adaptive_threshs = StringClass.extract_numeric_values_from_string(
tstr)
if 0 not in self.boundary_adaptive_threshs:
self.boundary_adaptive_threshs.append(
0) # 0 means no adjustment of boundary
for tmp_thresh in self.boundary_adaptive_threshs:
if -1 * tmp_thresh not in self.boundary_adaptive_threshs:
self.boundary_adaptive_threshs.append(-1 * tmp_thresh)
# 4. Parameters settings for specific optimization algorithm
self.opt_mtd = method
self.opt = None # type: Union[ParseNSGA2Config, None]
if self.opt_mtd == 'nsga2':
self.opt = ParseNSGA2Config(
cf, self.model.model_dir,
'SA_NSGA2_%s_%s' % (self.bmps_cfg_unit, self.bmps_cfg_method))
# Using the existed population derived from previous scenario optimization
self.initial_byinput = cf.getboolean(self.opt_mtd.upper(), 'inputpopulation') if \
cf.has_option(self.opt_mtd.upper(), 'inputpopulation') else False
self.input_pareto_file = None
self.input_pareto_gen = -1
if cf.has_option(self.opt_mtd.upper(), 'paretofrontsfile'):
self.input_pareto_file = cf.get(self.opt_mtd.upper(),
'paretofrontsfile')
if cf.has_option(self.opt_mtd.upper(), 'generationselected'):
self.input_pareto_gen = cf.getint(self.opt_mtd.upper(),
'generationselected')
self.scenario_dir = self.opt.out_dir + os.path.sep + 'Scenarios'
UtilClass.rmmkdir(self.scenario_dir)
# 5. (Optional) Plot settings for matplotlib
self.plot_cfg = PlotConfig(cf)
def __init__(self, cf, method='nsga2'):
# type: (ConfigParser, str) -> None
"""Initialization."""
# 1. SEIMS model related
self.model = ParseSEIMSConfig(cf)
# 2. Common settings of BMPs scenario
self.eval_stime = None
self.eval_etime = None
self.worst_econ = 0.
self.worst_env = 0.
self.runtime_years = 0.
self.export_sce_txt = False
self.export_sce_tif = False
if 'Scenario_Common' not in cf.sections():
raise ValueError(
'[Scenario_Common] section MUST be existed in *.ini file.')
self.eval_stime = parse_datetime_from_ini(cf, 'Scenario_Common',
'eval_time_start')
self.eval_etime = parse_datetime_from_ini(cf, 'Scenario_Common',
'eval_time_end')
self.worst_econ = cf.getfloat('Scenario_Common', 'worst_economy')
self.worst_env = cf.getfloat('Scenario_Common', 'worst_environment')
self.runtime_years = cf.getfloat('Scenario_Common', 'runtime_years')
if cf.has_option('Scenario_Common', 'export_scenario_txt'):
self.export_sce_txt = cf.getboolean('Scenario_Common',
'export_scenario_txt')
if cf.has_option('Scenario_Common', 'export_scenario_tif'):
self.export_sce_tif = cf.getboolean('Scenario_Common',
'export_scenario_tif')
# 3. Application specific setting section [BMPs]
self.bmps_info = dict() # BMP to be evaluated, JSON format
self.bmps_retain = dict() # BMPs to be constant, JSON format
self.bmps_cfg_unit = 'SLPPOS'
self.bmps_cfg_method = 'RDM'
if 'BMPs' not in cf.sections():
raise ValueError(
'[BMPs] section MUST be existed for specific scenario analysis.'
)
bmpsinfostr = cf.get('BMPs', 'bmps_info')
self.bmps_info = UtilClass.decode_strs_in_dict(json.loads(bmpsinfostr))
if cf.has_option('BMPs', 'bmps_retain'):
bmpsretainstr = cf.get('BMPs', 'bmps_retain')
self.bmps_retain = json.loads(bmpsretainstr)
self.bmps_retain = UtilClass.decode_strs_in_dict(self.bmps_retain)
bmpscfgunitstr = cf.get('BMPs', 'bmps_cfg_units')
bmpscfgunitdict = UtilClass.decode_strs_in_dict(
json.loads(bmpscfgunitstr))
for unitname, unitcfg in viewitems(bmpscfgunitdict):
self.bmps_cfg_unit = unitname
if self.bmps_cfg_unit not in BMPS_CFG_UNITS:
raise ValueError('BMPs configuration unit MUST be '
'one of %s' % BMPS_CFG_UNITS.__str__())
if not isinstance(unitcfg, dict):
raise ValueError(
'The value of BMPs configuration unit MUST be dict value!')
for cfgname, cfgvalue in viewitems(unitcfg):
self.bmps_info[cfgname] = cfgvalue
break
if cf.has_option('BMPs', 'bmps_cfg_method'):
self.bmps_cfg_method = cf.get('BMPs', 'bmps_cfg_method')
if self.bmps_cfg_method not in BMPS_CFG_METHODS:
print('BMPs configuration method MUST be one of %s' %
BMPS_CFG_METHODS.__str__())
self.bmps_cfg_method = 'RDM'
# Check the validation of configuration unit and method
if self.bmps_cfg_method not in BMPS_CFG_PAIR.get(self.bmps_cfg_unit):
raise ValueError('BMPs configuration method %s '
'is not supported on unit %s' %
(self.bmps_cfg_method, self.bmps_cfg_unit))
# 4. Parameters settings for specific optimization algorithm
self.opt_mtd = method
self.opt = None # type: Union[ParseNSGA2Config]
if self.opt_mtd == 'nsga2':
self.opt = ParseNSGA2Config(
cf, self.model.model_dir,
'SA_NSGA2_%s_%s' % (self.bmps_cfg_unit, self.bmps_cfg_method))
self.scenario_dir = self.opt.out_dir + os.path.sep + 'Scenarios'
UtilClass.rmmkdir(self.scenario_dir)