def _get_full_disjoint_col_matrix_cols(col_matrix):
"""
Find sets of disjoint columns in a column intersection matrix.
Parameters
----------
col_matrix : ndarray
Column intersection matrix
Returns
-------
list
List of lists of disjoint columns
"""
color_groups = []
_, ncols = col_matrix.shape
# -1 indicates that a column has not been colored
colors = np.full(ncols, -1, dtype=get_index_dtype(maxval=ncols))
for col in _order_by_ID(col_matrix):
neighbor_colors = set(colors[col_matrix[col]])
for color, grp in enumerate(color_groups):
if color not in neighbor_colors:
grp.append(col)
colors[col] = color
break
else:
colors[col] = len(color_groups)
color_groups.append([col])
return color_groups
def _get_full_disjoint_col_matrix_cols(col_matrix):
"""
Find sets of disjoint columns in a column intersection matrix.
Parameters
----------
col_matrix : ndarray
Column intersection matrix
Returns
-------
list
List of lists of disjoint columns
"""
color_groups = []
_, ncols = col_matrix.shape
# -1 indicates that a column has not been colored
colors = np.full(ncols, -1, dtype=get_index_dtype(maxval=ncols))
for col in _order_by_ID(col_matrix):
neighbor_colors = set(colors[col_matrix[col]])
for color, grp in enumerate(color_groups):
if color not in neighbor_colors:
grp.append(col)
colors[col] = color
break
else:
colors[col] = len(color_groups)
color_groups.append([col])
return color_groups
def _order_by_ID(col_matrix):
"""
Return columns in order of incidence degree (ID).
ID is the number of already colored neighbors (neighbors are dependent columns).
Parameters
----------
col_matrix : ndarray
Boolean array of column dependencies.
Yields
------
int
Column index.
"""
degrees = _count_nonzeros(col_matrix, axis=0)
ncols = degrees.size
if ncols == 0:
return
# use max degree column as a starting point instead of just choosing a random column
# since all have incidence degree of 0 when we start.
start = degrees.argmax()
yield start
colored_degrees = np.zeros(degrees.size,
dtype=get_index_dtype(maxval=degrees[start]))
colored_degrees[col_matrix[start]] += 1
colored_degrees[
start] = -ncols # ensure that this col will never have max degree again
for i in range(ncols - 1):
col = colored_degrees.argmax()
colored_degrees[col_matrix[col]] += 1
colored_degrees[
col] = -ncols # ensure that this col will never have max degree again
yield col
def _order_by_ID(col_matrix):
"""
Return columns in order of incidence degree (ID).
ID is the number of already colored neighbors (neighbors are dependent columns).
Parameters
----------
col_matrix : ndarray
Boolean array of column dependencies.
Yields
------
int
Column index.
"""
degrees = _count_nonzeros(col_matrix, axis=0)
ncols = degrees.size
if ncols == 0:
return
# use max degree column as a starting point instead of just choosing a random column
# since all have incidence degree of 0 when we start.
start = degrees.argmax()
yield start
colored_degrees = np.zeros(degrees.size, dtype=get_index_dtype(maxval=degrees[start]))
colored_degrees[col_matrix[start]] += 1
colored_degrees[start] = -ncols # ensure that this col will never have max degree again
for i in range(ncols - 1):
col = colored_degrees.argmax()
colored_degrees[col_matrix[col]] += 1
colored_degrees[col] = -ncols # ensure that this col will never have max degree again
yield col