def run_simulation(json_dict, **kwargs):
r"""
Starts MVS tool simulation from an input json file
Parameters
-----------
json_dict: dict
json from http request
Other Parameters
----------------
pdf_report: bool, optional
Can generate an automatic pdf report of the simulation's results (True) or not (False)
Default: False.
display_output : str, optional
Sets the level of displayed logging messages.
Options: "debug", "info", "warning", "error". Default: "info".
lp_file_output : bool, optional
Specifies whether linear equation system generated is saved as lp file.
Default: False.
"""
welcome_text = (
"\n \n Multi-Vector Simulation Tool (MVS) V" + version_num + " " +
"\n Version: " + version_date + " " +
'\n Part of the toolbox of H2020 project "E-LAND", ' +
"Integrated multi-vector management system for Energy isLANDs" +
"\n Coded at: Reiner Lemoine Institute (Berlin) " +
"\n Contributors: Martha M. Hoffmann \n \n ")
logging.info(welcome_text)
logging.debug("Accessing script: B0_data_input_json")
dict_values = data_input.convert_from_json_to_special_types(json_dict)
print("")
logging.debug("Accessing script: C0_data_processing")
data_processing.all(dict_values)
print("")
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = modelling.run_oemof(dict_values)
print("")
logging.debug("Accessing script: E0_evaluation")
evaluation.evaluate_dict(dict_values, results_main, results_meta)
logging.debug("Convert results to json")
epa_dict_values = data_parser.convert_mvs_params_to_epa(dict_values)
output_processing.select_essential_results(epa_dict_values)
json_values = output_processing.store_as_json(epa_dict_values)
return json.loads(json_values)
def test_parse_pandas_series_provided_longer_time_index(self, caplog):
pd_series = B0.convert_from_json_to_special_types(
self.test_dict_series, time_index=self.ti_long)
# collect warning message
log_msg = caplog.record_tuples[0]
# check it is a warning
assert log_msg[1] == 30
assert (
"The time index inferred from simulation_settings is shorter as the timeserie under the field series"
in log_msg[2])
assert (pd_series["series"].values == self.test_result_series.values
).all()
def test_parse_pandas_series_provided_time_index(self):
pd_series = B0.convert_from_json_to_special_types(
self.test_dict_series, time_index=self.ti)
assert (pd_series["series"] == self.test_result_series).all()
def run_simulation(json_dict, epa_format=True, **kwargs):
r"""
Starts MVS tool simulation from an input json file
Parameters
-----------
json_dict: dict
json from http request
epa_format: bool, optional
Specifies whether the output is formatted for EPA standards
Default: True
Other Parameters
----------------
pdf_report: bool, optional
Can generate an automatic pdf report of the simulation's results (True) or not (False)
Default: False.
display_output : str, optional
Sets the level of displayed logging messages.
Options: "debug", "info", "warning", "error". Default: "info".
lp_file_output : bool, optional
Specifies whether linear equation system generated is saved as lp file.
Default: False.
"""
display_output = kwargs.get("display_output", None)
if display_output == "debug":
screen_level = logging.DEBUG
elif display_output == "info":
screen_level = logging.INFO
elif display_output == "warning":
screen_level = logging.WARNING
elif display_output == "error":
screen_level = logging.ERROR
else:
screen_level = logging.INFO
# Define logging settings and path for saving log
logger.define_logging(screen_level=screen_level)
welcome_text = (
"\n \n Multi-Vector Simulation Tool (MVS) V" + version_num + " " +
"\n Version: " + version_date + " " +
'\n Part of the toolbox of H2020 project "E-LAND", ' +
"Integrated multi-vector management system for Energy isLANDs" +
"\n Coded at: Reiner Lemoine Institute (Berlin) " +
"\n Reference: https://zenodo.org/record/4610237 \n \n ")
logging.info(welcome_text)
logging.debug("Accessing script: B0_data_input_json")
dict_values = B0.convert_from_json_to_special_types(json_dict)
print("")
logging.debug("Accessing script: C0_data_processing")
C0.all(dict_values)
print("")
logging.debug("Accessing script: D0_modelling_and_optimization")
results_meta, results_main = D0.run_oemof(dict_values)
print("")
logging.debug("Accessing script: E0_evaluation")
E0.evaluate_dict(dict_values, results_main, results_meta)
logging.debug("Convert results to json")
if epa_format is True:
epa_dict_values = data_parser.convert_mvs_params_to_epa(dict_values)
json_values = F0.store_as_json(epa_dict_values)
answer = json.loads(json_values)
else:
answer = dict_values
return answer