ddg.optimize.ifs.utils module
- ddg.optimize.ifs.utils.log_history(f)[source]
Creates a log for the input of a given function.
- Parameters:
- fCallable
Function to use
- Returns:
- Callable
Wrapped function
- ddg.optimize.ifs.utils.attribute_helper(ifs, cell_type, name, boundary=[])[source]
Helper function for flatten wrappers extracting needed information about IndexedFaceSet attributes.
- Parameters:
- ifsIndexedFaceSet
- cell_typestr
Cell type of the attribute
- namestr
Name of the indexed faceset attribute to use
- boundaryIterable
Indices of cells to ignore
- Returns:
- arraynumpy.ndarray
Array of the attribute
- masknumpy.ndarray
Mask for non-boundary cells
- shape_igntuple of ints
Shape of attribute array used for flatten wrappers, when boundary values get ignored
- shape_remtuple of ints
Shape of attribute array used for flatten wrappers, when boundary values get removed
- ddg.optimize.ifs.utils.nflat_index(idx, n)[source]
Return indices for flattened (m,n)-dimensional arrays. The returned indices correspond to the indices of the entries of the rows given by idx after flattening the array.
- Parameters:
- idxIterable
Indices to convert to flattened indices
- nint
Dimension of target (m,n) array
- Returns:
- numpy.ndarray
Flat indices corresponding to idx
- ddg.optimize.ifs.utils.zero_columns(f, columns)[source]
Wraps sparse matrix valued function to zero columns.
- Parameters:
- f: Callable
Function to wrap
- columns: Iterable
Columns to zero
- Returns:
- Callable
wrapped function
- ddg.optimize.ifs.utils.remove_columns(f, columns)[source]
Wraps sparse matrix valued function to remove columns.
- Parameters:
- f: Callable
Function to wrap
- columns: Iterable
Columns to remove
- Returns:
- Callable
wrapped function
- ddg.optimize.ifs.utils.initial_guess(ifs, cell_type, name, boundary=[])[source]
Extracts attribute values for non-boundary cells.
- Parameters:
- ifsIndexedFaceSet
- cell_typestr
Cell type of the attribute
- namestr
Name of the indexed faceset attribute to use
- boundaryIterable
Indices of cells to ignore
- Returns:
- numpy.ndarray of shape (m,)
Values of attribute [name] on non-boundary cells in a flattened array