def read_focal_nodes(self, filename):
"""Loads list of focal nodes for arbitrary graph."""
focal_nodes = CSIO.load_graph(filename)
try:
if filename == self.options.habitat_file:#If graph was used as focal node file, then just want first two columns for focal_nodes.
focal_nodes = ComputeBase.deletecol(focal_nodes, 2)
focal_nodes = np.unique(np.asarray(focal_nodes))
except:
raise RuntimeError('Error processing focal node file. Please check file format')
return focal_nodes
def read_graph(self, filename):
"""Reads arbitrary graph from disk. Returns sparse adjacency matrix and node names ."""
graph_list = CSIO.load_graph(filename)
try:
zeros_in_resistance_graph = False
nodes = ComputeBase.deletecol(graph_list,2)
node_names = np.unique(np.asarray(nodes, dtype='int32'))
nodes[np.where(nodes>= 0)] = ComputeBase.relabel(nodes[np.where(nodes>= 0)], 0)
node1 = nodes[:,0]
node2 = nodes[:,1]
data = graph_list[:,2]
######################## Reclassification code
if self.options.use_reclass_table == True:
try:
reclass_table = CSIO.read_point_strengths(self.options.reclass_file)
except:
raise RuntimeError('Error reading reclass table. Please check file format.')
for i in range (0,reclass_table.shape[0]):
data = np.where(data==reclass_table[i,0], reclass_table[i,1],data)
Compute.logger.info('Reclassified landscape graph using %s'%(self.options.reclass_file,))
########################
if self.options.habitat_map_is_resistances == True:
zeros_in_resistance_graph = (np.where(data==0, 1, 0)).sum() > 0
conductances = 1/data
else:
conductances = data
numnodes = node_names.shape[0]
G = sparse.csr_matrix((conductances, (node1, node2)), shape = (numnodes, numnodes))
Gdense=G.todense()
g_graph = np.maximum(Gdense, Gdense.T) # To handle single or double entries for elements BHM 06/28/11
g_graph = sparse.csr_matrix(g_graph)
except:
raise RuntimeError('Error processing graph/network file. Please check file format')
if zeros_in_resistance_graph == True:
raise RuntimeError('Error: zero resistance values are not currently allowed in network/graph input file.')
return g_graph, node_names
