RFEM API 6.12.0002: Surface deformation u_z values returned as concatenated string (worked in 6.11)

Environment

  • RFEM: 6.12.0002 (works in 6.11.x)

Error

ValueError: could not convert string to float: '0.047897309064865110.047897309064865110.04789730906486511...'

Code that fails

# Get surface deformation results
surface_deflection_results = rfem_app.get_result_table(
    table=rfem.results.ResultTable.STATIC_ANALYSIS_SURFACES_LOCAL_DEFORMATIONS_GRID_POINTS_TABLE,
    loading=design_situation
).data

# Extract deflection results
def extract_deflection_results(surface_deflection_df: pd.DataFrame, footing_surface_id: int = 1) -> Dict[str, Any]:
    results = {}
    
    # Find max displacement_z (using u_z column name for RFEM6 API)
    max_z = surface_deflection_df['u_z'].max()  # FAILS HERE
    max_z_points = surface_deflection_df[surface_deflection_df['u_z'] == max_z]['grid_point'].unique().tolist()
    results["max_displacement_z"] = {
        "value": float(max_z * 1000),  # Convert to mm
        "grid_points": max_z_points
    }
    
    # Find min displacement_z (using u_z column name for RFEM6 API)
    min_z = surface_deflection_df['u_z'].min()  # FAILS HERE
    min_z_points = surface_deflection_df[surface_deflection_df['u_z'] == min_z]['grid_point'].unique().tolist()
    results["min_displacement_z"] = {
        "value": float(min_z * 1000),  # Convert to mm
        "grid_points": min_z_points
    }
    
    return results

Issue

In 6.12.0002, the u_z column contains concatenated strings like '0.047897309064865110.04789730906486511...' instead of numeric values. This worked fine in 6.11.

Question

Was there a change in 6.12.0002 to how STATIC_ANALYSIS_SURFACES_LOCAL_DEFORMATIONS_GRID_POINTS_TABLE returns the u_z column? How can I get numeric values instead of concatenated strings?

Or is this just a bug?

The results are present in the RFEM6 app UI.


VS Code recognises all the commands (I've noticed that previously when updating the names of certain api calls have changed, so thats the first thing I want to rule out).

I am a glass half full type of guy, so on the bright side at least the error creates quite a cool pattern.

Hi Samuel,

thx for sharing the issue - it seems to be a bug, that all the values in Pandas DataFrame are newly as string data type which is not correct.

We’ve already started working on the fix.

Let you know when it’s available.

Regards

2 Likes

Awesome thanks so much!

Hi Samuel,
let me share that in 6.12.0003 | 2.12.3 the issue with wrong column data types was fixed as works again as expected..
Looking forward for the feedback.
Regards

It’s working well now, thanks for the fix and update!

1 Like