def compare_benchmarks(first_benchmark: dict,
second_benchmark: dict,
output_path: str,
filename: str) -> dict:
"""
It compares the results of two benchmark runs.
It uses an 8th-order Lagrange interpolator to compare the state (or the dependent variable, depending on what is
given as input) history. The difference is returned in form of a dictionary and, if desired, written to a file named
filename and placed in the directory output_path.
Parameters
----------
first_benchmark : dict
State (or dependent variable history) from the first benchmark.
second_benchmark : dict
State (or dependent variable history) from the second benchmark.
output_path : str
If and where to save the benchmark results (if None, results are NOT written).
filename : str
Name of the output file.
Returns
-------
benchmark_difference : dict
Interpolated difference between the two benchmarks' state (or dependent variable) history.
"""
# Create 8th-order Lagrange interpolator for first benchmark
benchmark_interpolator = interpolators.create_one_dimensional_interpolator(first_benchmark,
interpolators.lagrange_interpolation(8))
# Calculate the difference between the benchmarks
print('Calculating benchmark differences...')
# Initialize difference dictionaries
benchmark_difference = dict()
# Calculate the difference between the states and dependent variables in an iterative manner
for second_epoch in second_benchmark.keys():
benchmark_difference[second_epoch] = benchmark_interpolator.interpolate(second_epoch) - \
second_benchmark[second_epoch]
# Write results to files
if output_path is not None:
save2txt(benchmark_difference,
filename,
output_path)
# Return the interpolator
return benchmark_difference
# Create mass rate model
mass_rate_settings_on_vehicle = {
'Vehicle': [propagation_setup.mass.from_thrust()]
}
# Create mass propagator settings (same for all propagations)
mass_propagator_settings = propagation_setup.propagator.mass(
bodies_to_propagate, mass_rate_settings_on_vehicle,
np.array([vehicle_mass]), termination_settings)
###########################################################################
# IF DESIRED, GENERATE BENCHMARK ##########################################
###########################################################################
if use_benchmark:
# Define benchmark interpolator settings to make a comparison between the two benchmarks
benchmark_interpolator_settings = interpolators.lagrange_interpolation(8)
# Create propagation settings for the benchmark
translational_propagator_settings = propagation_setup.propagator.translational(
central_bodies,
acceleration_settings,
bodies_to_propagate,
initial_state,
termination_settings,
output_variables=dependent_variables_to_save)
# Note, the following line is needed to properly use the accelerations, and modify them in the Problem class
translational_propagator_settings.recreate_state_derivative_models(bodies)
# Create multi-type propagation settings list
propagator_settings_list = [
translational_propagator_settings, mass_propagator_settings