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Improvements to forceatlas2 algorithm #488

Merged
merged 7 commits into from
Oct 14, 2017
Merged

Improvements to forceatlas2 algorithm #488

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7742086
Replace constants with parameters
jbcrail Oct 4, 2017
336a7a2
Check for loops
jbcrail Oct 4, 2017
cb649ad
Ignore weights during layout
jbcrail Oct 5, 2017
b9bf9d2
Fix typo
jbcrail Oct 5, 2017
c021b6b
Changed confusing parameter name
jbednar Oct 5, 2017
e6d1db8
Refactor how weights are ignored
jbcrail Oct 13, 2017
dbdabd6
Simplify edge iteration
jbcrail Oct 13, 2017
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28 changes: 21 additions & 7 deletions datashader/layout.py
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Original file line number Diff line number Diff line change
Expand Up @@ -90,22 +90,22 @@ def __call__(self, nodes, edges, **params):
return df


def _extract_points_from_nodes(nodes):
def _extract_points_from_nodes(nodes, params, dtype=None):
if 'x' in nodes.columns and 'y' in nodes.columns:
points = np.asarray(nodes[['x', 'y']])
else:
points = np.asarray(np.random.random((len(nodes), 2)))
points = np.asarray(np.random.random((len(nodes), params.dim)), dtype=dtype)
return points


def _convert_graph_to_sparse_matrix(nodes, edges, dtype=None, format='csr'):
def _convert_graph_to_sparse_matrix(nodes, edges, params, dtype=None, format='csr'):
nlen = len(nodes)
if 'id' in nodes:
index = dict(zip(nodes['id'].values, range(nlen)))
else:
index = dict(zip(nodes.index.values, range(nlen)))

if 'weight' not in edges:
if params.ignore_weights or 'weight' not in edges:
edges = edges.copy()
edges['weight'] = np.ones(len(edges))
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This seems like a very expensive step, and doesn't seem feasible as an approach in general, but I guess we can merge and come back to that later.


Expand All @@ -115,11 +115,22 @@ def _convert_graph_to_sparse_matrix(nodes, edges, dtype=None, format='csr'):
for src, dst, weight in [tuple(edge) for edge in edge_values]
if src in index and dst in index))

# symmetrize matrix
# Symmetrize matrix
d = data + data
r = rows + cols
c = cols + rows

# Check for nodes pointing to themselves
loops = edges[edges['source'] == edges['target']]
if len(loops):
loop_values = loops[['source', 'target', 'weight']].values
diag_index, diag_data = zip(*((index[src], -weight)
for src, dst, weight in [tuple(edge) for edge in loop_values]
if src in index and dst in index))
d += diag_data
r += diag_index
c += diag_index

M = scipy.sparse.coo_matrix((d, (r, c)), shape=(nlen, nlen), dtype=dtype)
return M.asformat(format)

Expand Down Expand Up @@ -206,14 +217,17 @@ class forceatlas2_layout(LayoutAlgorithm):
Random seed used to initialize the pseudo-random number
generator.""")

ignore_weights = param.Boolean(False, doc="""
Whether to use weights during layout""")

def __call__(self, nodes, edges, **params):
p = param.ParamOverrides(self, params)

np.random.seed(p.seed)

# Convert graph into sparse adjacency matrix and array of points
points = _extract_points_from_nodes(nodes)
matrix = _convert_graph_to_sparse_matrix(nodes, edges)
points = _extract_points_from_nodes(nodes, p, dtype='f')
matrix = _convert_graph_to_sparse_matrix(nodes, edges, p, dtype='f')

if p.k is None:
p.k = np.sqrt(1.0 / len(points))
Expand Down