Results in Location

In this example we will demonstrate how to: Extend core API methods using a user-defined Python function. Retrieve internal forces for a specific member and loading at any location along the member. Use NumPy to perform linear interpolation between available results. Work with data as Pandas DataFrames for filtering and manipulation.

Python

from dlubal.api import rfem
import numpy

def get_member_internal_force(member_no: int, loading: str = 'LC1', force: str = 'm_y', location: float = 0) -> float:
    df = rfem_app.get_results(
        results_type=rfem.results.STATIC_ANALYSIS_MEMBERS_INTERNAL_FORCES,
        filters=[
            rfem.results.ResultsFilter(
                column_id="member_no",
                filter_expression=str(member_no)
            ),
            # rfem.results.ResultsFilter(
            #     column_id="loading",
            #     filter_expression=str(loading)
            # ),
        ]
    ).data

    # Filter by loading
    df_loading = df[df['loading'] == loading]

    # Get locations and forces as arrays
    locations = df_loading['location_x'].to_numpy(dtype=float)
    forces = df_loading[force].to_numpy(dtype=float)

    # Check range
    if not (locations[0] <= location <= locations[-1]):
        print('Location is out of range')
        return 0

    # Linear interpolation
    return float(numpy.interp(location, locations, forces))



with rfem.Application() as rfem_app:

    # --- Retriev results from the active model (already calculated) ---

    v_z = get_member_internal_force(member_no=46, loading = 'CO2', force = 'v_z', location = 0.4)
    print(v_z)