Ejemplo n.º 1
0
def test_serialization():
    """A test to ensure that data sets are JSON serializable."""

    data_set = PhysicalPropertyDataSet()
    data_set.add_properties(create_dummy_property(Density))

    data_set_json = data_set.json()

    parsed_data_set = PhysicalPropertyDataSet.parse_json(data_set_json)
    assert len(data_set) == len(parsed_data_set)

    parsed_data_set_json = parsed_data_set.json()
    assert parsed_data_set_json == data_set_json
def main():

    # Set up logging
    logging.basicConfig(level=logging.INFO)

    output_directory = "training_sets"
    os.makedirs(output_directory, exist_ok=True)

    rho_pure_h_vap = PhysicalPropertyDataSet.from_json(
        "../../../pure_optimisation/data_set_generation/expanded_set/training_set.json"
    )

    rho_pure = PhysicalPropertyDataSet.from_json(
        "../../../pure_optimisation/data_set_generation/expanded_set/training_set.json"
    )
    rho_pure.filter_by_property_types("Density")

    h_mix_rho_x = PhysicalPropertyDataSet.from_json(
        "../../../mixture_optimisation/data_set_generation/"
        "expanded_set/training_sets/h_mix_rho_x_training_set.json")

    h_mix_rho_x_rho_pure = PhysicalPropertyDataSet()
    h_mix_rho_x_rho_pure.merge(rho_pure)
    h_mix_rho_x_rho_pure.merge(h_mix_rho_x)
    h_mix_rho_x_rho_pure.json(
        os.path.join(output_directory, "h_mix_rho_x_rho_pure.json"))
    h_mix_rho_x_rho_pure.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_rho_x_rho_pure.csv"))

    h_mix_rho_x_rho_pure_h_vap = PhysicalPropertyDataSet()
    h_mix_rho_x_rho_pure_h_vap.merge(rho_pure_h_vap)
    h_mix_rho_x_rho_pure_h_vap.merge(h_mix_rho_x)
    h_mix_rho_x_rho_pure_h_vap.json(
        os.path.join(output_directory, "h_mix_rho_x_rho_pure_h_vap.json"))
    h_mix_rho_x_rho_pure_h_vap.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_rho_x_rho_pure_h_vap.csv"))
Ejemplo n.º 3
0
def main():

    training_set_smiles = [
        "CCO",
        "CC(=O)O",
        "COC=O",
        "CC(C)(C)O",
        "CC(C)O",
        "CO",
        "CCOC(C)=O",
        "CCOC(=O)CC(=O)OCC",
        "CC(C)CO",
        "CCCCO",
        "CCCCOC(C)=O",
        "CCCOC(C)=O",
    ]

    # Ensure the smiles patterns are standardized.
    smiles = [Component(x).smiles for x in training_set_smiles]

    # Load in the Hvap data
    h_vap_data_frame = pandas.read_csv(
        os.path.join(
            "..",
            "..",
            "..",
            "data_availability",
            "sourced_h_vap_data",
            "enthalpy_of_vaporization_pure.csv",
        ))
    h_vap_data_frame = filter_by_smiles(h_vap_data_frame,
                                        smiles_to_include=smiles,
                                        smiles_to_exclude=None)

    h_vap_data_set = data_set_from_data_frame(h_vap_data_frame)

    # # Load in the density data
    density_data_frame = pandas.read_csv(
        os.path.join(
            "..",
            "..",
            "..",
            "data_availability",
            "data_by_environments",
            "alcohol_ester",
            "all_data",
            "density_pure.csv",
        ))
    density_data_frame = filter_by_smiles(density_data_frame,
                                          smiles_to_include=smiles,
                                          smiles_to_exclude=None)

    density_data_set = data_set_from_data_frame(density_data_frame)

    # Retain the density measurements which were made closest to 298.15K and 1 atm.
    target_state_point = StatePoint(
        temperature=298.15 * unit.kelvin,
        pressure=1.0 * unit.atmosphere,
        mole_fractions=(1.0, ),
    )

    final_data_set = PhysicalPropertyDataSet()

    for substance in density_data_set.substances:

        properties_per_state = defaultdict(list)

        # Refactor the properties into more convenient data structures.
        for physical_property in density_data_set.properties_by_substance(
                substance):

            state_point = StatePoint.from_physical_property(physical_property)
            properties_per_state[state_point].append(physical_property)

        # Sort the state points based on their distance to the target state.
        sorted_states_points = list(
            sorted(
                properties_per_state.keys(),
                key=functools.partial(StatePoint.individual_distances,
                                      target_state_point),
            ))

        final_data_set.add_properties(
            properties_per_state[sorted_states_points[0]][0])

    final_data_set.merge(h_vap_data_set)

    final_data_set.json("training_set.json", format=True)
    final_data_set.to_pandas().to_csv("training_set.csv", index=False)
Ejemplo n.º 4
0
def main():

    # Set up logging
    logging.basicConfig(level=logging.INFO)

    output_directory = "training_sets"
    os.makedirs(output_directory, exist_ok=True)

    pure_density_h_vap = PhysicalPropertyDataSet.from_json(
        "../../pure_optimisation/data_set_generation/training_set.json"
    )

    pure_density = PhysicalPropertyDataSet.from_json(
        "../../pure_optimisation/data_set_generation/training_set.json"
    )
    pure_density.filter_by_property_types("Density")

    h_mix_v_excess = PhysicalPropertyDataSet.from_json(
        "../../mixture_optimisation/data_set_generation/"
        "training_sets/h_mix_v_excess_training_set.json"
    )
    h_mix_binary_density = PhysicalPropertyDataSet.from_json(
        "../../mixture_optimisation/data_set_generation/"
        "training_sets/h_mix_density_training_set.json"
    )

    h_mix_binary_density_pure_density = PhysicalPropertyDataSet()
    h_mix_binary_density_pure_density.merge(pure_density)
    h_mix_binary_density_pure_density.merge(h_mix_binary_density)
    h_mix_binary_density_pure_density.json(
        os.path.join(output_directory, "h_mix_binary_density_pure_density.json")
    )
    h_mix_binary_density_pure_density.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_binary_density_pure_density.csv")
    )

    h_mix_v_excess_pure_density = PhysicalPropertyDataSet()
    h_mix_v_excess_pure_density.merge(pure_density)
    h_mix_v_excess_pure_density.merge(h_mix_v_excess)
    h_mix_v_excess_pure_density.json(
        os.path.join(output_directory, "h_mix_v_excess_pure_density.json")
    )
    h_mix_v_excess_pure_density.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_v_excess_pure_density.csv")
    )

    h_mix_binary_density_pure_density_h_vap = PhysicalPropertyDataSet()
    h_mix_binary_density_pure_density_h_vap.merge(pure_density_h_vap)
    h_mix_binary_density_pure_density_h_vap.merge(h_mix_binary_density)
    h_mix_binary_density_pure_density_h_vap.json(
        os.path.join(output_directory, "h_mix_binary_density_pure_density_h_vap.json")
    )
    h_mix_binary_density_pure_density_h_vap.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_binary_density_pure_density_h_vap.csv")
    )

    h_mix_v_excess_pure_density_h_vap = PhysicalPropertyDataSet()
    h_mix_v_excess_pure_density_h_vap.merge(pure_density_h_vap)
    h_mix_v_excess_pure_density_h_vap.merge(h_mix_v_excess)
    h_mix_v_excess_pure_density_h_vap.json(
        os.path.join(output_directory, "h_mix_v_excess_pure_density_h_vap.json")
    )
    h_mix_v_excess_pure_density_h_vap.to_pandas().to_csv(
        os.path.join(output_directory, "h_mix_v_excess_pure_density_h_vap.csv")
    )