Exporting of results

General overview

Results can be exported via the API using several methods:

• Exporting to results.h5

• Exporting via a user-defined python exporter

By default, exporting is disabled. Exporting is configured via the global settings, and is triggered by the export_results function.

# Uses whatever export options are specified in the model
session.export_results()

The following parameters affect the behavior of export_results:

• model.global_settings.export_target - Specifies exporter target type

• model.global_settings.export_directory_path - Directory to export to

• model.global_settings.export_settings - Specifies which data to export

The following property can be used to inject an exporter:

• model.exporter

Exporting to results.h5

First, a model must have been executed. Here is a basic example of that:

# Load and execute a model
mod = pyltm.LtmApiModule("my_session")
mod.load(filename=filename)
mod.write_model()
mod.execute_model()
model = mod.model

Once a model has been executed successfully, we can export to Hdf5 by specifying an export target, an export directory path, and then call the export function.

# export_target specifies which exporter to use
model.global_settings.export_target = pyltm.ExportTarget.Hdf5

# export_directory_path specifies which folder to export to
model.global_settings.export_directory_path = "./run_export"

# Export to results.h5
mod.export_results()

Exporting via a user-specified exporter

An exporter can be implemented in Python, and will receive the data to be exported. The exporter will only be used if the export target is set to User, and model.exporter has been specified.

Note that the exporter will be invoked several times with partial data.

class MyCustomExporter(pyltm.Exporter):
def __init__(self):
    self.db = MyBackendDb()

def export_data(self, exported: pyltm.ExportedData):
        # data is a wrapper that may contain one of several types of data

        # Which type it is can be determined with isinstance:
        if isinstance(exported.data, pyltm.WindData):
            self.export_wind_data(exported.data)
        elif isinstance(exported.data, pyltm.WaterValueData):
            self.export_water_value_data(exported.data)
        else:
            raise RuntimeError(f"Unknown data type: {repr(exported.data)}")

def export_wind_data(self, data: pyltm.WindData):
    # Wind data contgains one time series per busbar
    for data_per_busbar in data.busbar_tses:
        name = data_per_busbar.busbar_name
        txy = data_per_busbar.txy
        self.db.save_wind_data(name, txy)

def export_water_value_data(self, data: pyltm.WaterValueData):
    # Water values contains a N-dimensional array per busbar
    for data_per_busbar in data.busbar_water_values:
        name = data_per_busbar.busbar_name
        water_values = data_per_busbar.water_values
        self.db.save_water_value_data(name, water_values)

model.global_settings.export_target = pyltm.ExportTarget.User
model.global_settings.export_directory_path = "./run_export"
model.exporter = MyCustomExporter()

# Export to results.h5
mod.export_results()

Selective exporting

The export_settings property can be used to select what to export.

model.global_settings.export_settings.export_water_values = True
model.global_settings.export_settings.export_wind_data = False
mod.export_results()