def r_igraph_scan1(g, save_fn=None):
"""
Compute the scan statistic 1 of graph g and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a scan1 attribute to all nodes and returns.
@return: The graph with the scan1 attribute appended
"""
scanstat1 = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::local_scan(g)
}
""")
ss1vector = scanstat1(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(os.path.abspath(save_fn),
ss1vector) # TODO: Clean input for programmatic access
print "Scan Statistic saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(
g, "scan1", ss1vector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_clust_coeff(g, save_fn=None):
"""
Compute clustering coefficient/transitivity of graph g
and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a clustcoeff attribute to all nodes and returns.
@return: the graph with the clustcoeff attribute appended
"""
clustcoeff = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::transitivity(g, "local")
}
""")
ccvector = clustcoeff(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn, ccvector) # TODO: Clean input for programmatic access
print "Clustering Coefficient saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(g, "clustcoeff", ccvector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_triangles(g, save_fn=None):
"""
Compute local triangle count of graph g and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a tri count attribute to all nodes and returns.
@return: The graph with the tri vertex attribute appended
"""
triangles = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::adjacent.triangles(g)
}
""")
trivector = triangles(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn,
trivector) # TODO: Clean input for programmatic access
print "Triangle Count saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(
g, "tri", trivector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_triangles(g, save_fn=None):
"""
Compute local triangle count of graph g and save as necessary
Positional arguments
====================
g - The igraph loaded via Rpy2 so an R object
Optional arguments
==================
save_fn - the filename you want to use to save it. If not provided
the graph adds a tri count attribute to all nodes and returns.
"""
triangles = robjects.r("""
require(igraph)
fn <- function(g){
igraph::adjacent.triangles(g)
}
""")
trivector = triangles(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn, trivector) # TODO: Clean input for programmatic access
print "Triangle Count saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(g, "tri", trivector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_clust_coeff(g, save_fn=None):
"""
Compute clustering coefficient/transitivity of graph g
and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a clustcoeff attribute to all nodes and returns.
@return: the graph with the clustcoeff attribute appended
"""
clustcoeff = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::transitivity(g, "local")
}
""")
ccvector = clustcoeff(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn,
ccvector) # TODO: Clean input for programmatic access
print "Clustering Coefficient saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(
g, "clustcoeff", ccvector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_degree(g, mode="total", save_fn=None):
"""
Compute degree of graph g and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param mode: the type of degree. Default is an undirected i.e. in-degree + out degree
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a degree attribute to all nodes and returns.
@return: the graph with the degree attribute set.
"""
deg = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::degree(g, mode="%s")
}
""" % mode)
degvector = deg(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn,
degvector) # TODO: Clean input for programmatic access
print "Degree saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(
g, "degree", degvector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_degree(g, save_fn=None):
"""
Compute degree of graph g and save as necessary
Positional arguments
====================
g - The igraph loaded via Rpy2 so an R object
Optional arguments
==================
save_fn - the filename you want to use to save it. If not provided
the graph adds a degree attribute to all nodes and returns.
"""
deg = robjects.r("""
require(igraph)
fn <- function(g){
igraph::degree(g, mode="total")
}
""")
degvector = deg(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn, degvector) # TODO: Clean input for programmatic access
print "Degree saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(g, "degree", degvector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_degree(g, mode="total", save_fn=None):
"""
Compute degree of graph g and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param mode: the type of degree. Default is an undirected i.e. in-degree + out degree
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a degree attribute to all nodes and returns.
@return: the graph with the degree attribute set.
"""
deg = robjects.r(
"""
suppressMessages(require(igraph))
fn <- function(g){
igraph::degree(g, mode="%s")
}
"""
% mode
)
degvector = deg(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn, degvector) # TODO: Clean input for programmatic access
print "Degree saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(g, "degree", degvector) # Attribute name may need to change
return g # return so we can use for other attributes
def r_igraph_scan1(g, save_fn=None):
"""
Compute the scan statistic 1 of graph g and save as necessary
@param g: The igraph loaded via Rpy2 so an R object
@param save_fn: the filename you want to use to save it. If not provided
the graph adds a scan1 attribute to all nodes and returns.
@return: The graph with the scan1 attribute appended
"""
scanstat1 = robjects.r("""
suppressMessages(require(igraph))
fn <- function(g){
igraph::local_scan(g)
}
""")
ss1vector = scanstat1(g)
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(os.path.abspath(save_fn), ss1vector) # TODO: Clean input for programmatic access
print "Scan Statistic saved as %s ..." % save_fn
else:
g = r_igraph_set_vertex_attr(g, "scan1", ss1vector) # Attribute name may need to change
return g # return so we can use for other attributes
eigs = None
vcount = r_igraph_vcount(g, False)
nev = k if k < (vcount - 2) else (vcount-3)
try:
eigs = esd(g, nev, real, lcc)
except Exception, msg:
print msg
return g # *Note premature exit*
if return_eigs: return eigs # used for MAD
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn[0], eigs[0][0]) # eigenvalues
createSave(save_fn[1], eigs[0][1]) # eigenvectors
print "Eigenvalues saved as %s ..." % save_fn[0]
print "eigenvectors ssaved as %s ..." % save_fn[1]
else:
global gl_eigvects
gl_eigvects = eigs[0][1]
print "Setting eigenvalues as graph attr ..."
g = r_igraph_set_graph_attribute(g, "eigvals", "["+", ".join(map(cut, (eigs[0][0])))+"]") # Return a comma separated string
eig_idx = eigs[1]
print "Mapping eigenvectors ..."
eigvects = map(get_str_eigvects, [(idx, idx+nev) for idx in xrange(0, ((len(eigs[1]))*nev), nev)])
del eigs
def compute(inv_dict, save=True):
'''
@param inv_dict: is a dict optinally containing any of these:
- inv_dict['edge']: boolean for global edge count
- inv_dict['ver']: boolean for global vertex number
- inv_dict['tri']: boolean for local triangle count
- inv_dict['tri_fn']: the path of a precomputed triangle count (.npy)
- inv_dict['eig']: boolean for eigenvalues and eigenvectors
- inv_dict['eigvl_fn']: the path of a precomputed eigenvalues (.npy)
- inv_dict['eigvect_fn']: the path of a precomputed eigenvectors (.npy)
- inv_dict['deg']: boolean for local degree count
- inv_dict['deg_fn']: the path of a precomputed triangle count (.npy)
- inv_dict['ss1']: boolean for scan 1 statistic
- inv_dict['cc']: boolean for clustering coefficient
- inv_dict['mad']: boolean for maximum average degree
- inv_dict['save_dir']: the base path where all invariants will create sub-dirs & be should be saved
@param save: boolean for auto save or not. TODO: use this
'''
# Popualate inv_dict
inv_dict = populate_inv_dict(inv_dict)
if inv_dict['save_dir'] is None:
inv_dict['save_dir'] = os.path.dirname(inv_dict['graph_fn'])
if (inv_dict.has_key('G')):
if inv_dict['G'] is not None:
G = inv_dict['G']
elif (inv_dict['graphsize'] == 'b' or inv_dict['graphsize'] == 'big'):
G = loadAdjMat(inv_dict['graph_fn'], inv_dict['lcc_fn']) # TODO: test
# small graphs
else:
G = loadAnyMat(inv_dict['graph_fn'], inv_dict['data_elem'])
if isinstance(G, str):
print G
return G # Error message
num_nodes = G.shape[0] # number of nodes
# CC requires deg_fn and tri_fn. Load if available
if inv_dict['cc']:
# if either #tri or deg is undefined
if not inv_dict['tri_fn']:
inv_dict['tri'] = True
if not inv_dict['deg_fn']:
inv_dict['deg'] = True
cc_array = np.zeros(num_nodes)
# All invariants that require eigenvalues
if ((inv_dict['tri'] and not inv_dict['tri_fn'])
or (inv_dict['mad'])):
if not inv_dict['eigvl_fn']:
inv_dict['eig'] = True
# Only create arrays if the computation will be done
if inv_dict['tri']:
if inv_dict['tri_fn']:
tri_array = np.load(inv_dict['tri_fn']) # load if precomputed
else:
tri_array = np.zeros(num_nodes) # local triangle count
if inv_dict['deg'] or inv_dict['edge']: # edge is global number of edges
inv_dict['deg'] = True
if inv_dict['deg_fn']:
deg_array = np.load(inv_dict['deg_fn'])
else:
deg_array = np.zeros(num_nodes) # Vertex degrees of all vertices
if (inv_dict['ss1']):
ss1_array = np.zeros(num_nodes) # Induced subgraph edge number i.e scan statistic
if (not inv_dict['k'] or inv_dict['k'] > 100 or inv_dict['k'] > G.shape[0] - 2):
k = 100 if G.shape[0]-2 > 101 else G.shape[0] - 2 # Maximum of 100 eigenvalues
start = time()
# Calculate Eigenvalues & Eigen vectors
if inv_dict['eig']:
if not (inv_dict['eigvl_fn'] or inv_dict['eigvect_fn']):
l, u = arpack.eigs(G, k=k, which='LM') # LanczosMethod(A,0)
print 'Time taken to calc Eigenvalues: %f secs\n' % (time() - start)
else:
try:
l = np.load(inv_dict['eigvl_fn'])
u = l = np.load(inv_dict['eigvect_fn'])
except Exception:
return "[IOERROR: ]Eigenvalues failed to load"
# All other invariants
start = time()
#### For loop ####
if (inv_dict['cc'] or inv_dict['ss1'] or (inv_dict['tri'] and not inv_dict['tri_fn'])\
or (inv_dict['deg'] and not inv_dict['deg_fn']) ): # one of the others
for j in range(num_nodes):
# tri
if not inv_dict['tri_fn'] and inv_dict['tri']: # if this is still None we need to compute it
tri_array[j] = abs(round((sum( np.power(l.real,3) * (u[j][:].real**2)) ) / 6.0)) # Divide by six because we count locally
# ss1 & deg
if inv_dict['ss1'] or (not inv_dict['deg_fn'] and inv_dict['deg']):
nbors = G[:,j].nonzero()[0]
# deg
if (not inv_dict['deg_fn'] and inv_dict['deg']):
deg_array[j] = nbors.shape[0]
# ss1
if inv_dict['ss1']:
if (nbors.shape[0] > 0):
nbors_mat = G[:,nbors][nbors,:]
ss1_array[j] = nbors.shape[0] + (nbors_mat.nnz/2.0) # scan stat 1 # Divide by two because of symmetric matrix
else:
ss1_array[j] = 0 # zero neighbors hence zero cardinality enduced subgraph
# cc
if inv_dict['cc']:
if (deg_array[j] > 2):
cc_array[j] = (2.0 * tri_array[j]) / ( deg_array[j] * (deg_array[j] - 1) ) # Jari et al
else:
cc_array[j] = 0
print 'Time taken to compute loop dependent invariants: %f secs\n' % (time() - start)
### End For ###
# global edge
if inv_dict['edge']:
edge_count = deg_array.sum()
# global vertices is num_nodes
''' MAD '''
if (inv_dict['mad']):
max_ave_deg = np.max(l.real)
# Computation complete - handle the saving now ...
''' Top eigenvalues & eigenvectors '''
if not inv_dict['eigvl_fn'] and inv_dict['eig'] :
eigvDir = os.path.join(inv_dict['save_dir'], "Eigen") #if eigvDir is None else eigvDir
# Immediately write eigs to file
inv_dict['eigvl_fn'] = os.path.join(eigvDir, getBaseName(inv_dict['graph_fn']) + '_eigvl.npy')
inv_dict['eigvect_fn'] = os.path.join(eigvDir, getBaseName(inv_dict['graph_fn']) + '_eigvect.npy')
createSave(inv_dict['eigvl_fn'], l.real) # eigenvalues
createSave(inv_dict['eigvect_fn'], u) # eigenvectors
print 'Eigenvalues and eigenvectors saved ...'
''' Triangle count '''
if not inv_dict['tri_fn'] and inv_dict['tri']:
triDir = os.path.join(inv_dict['save_dir'], "Triangle") #if triDir is None else triDir
inv_dict['tri_fn'] = os.path.join(triDir, getBaseName(inv_dict['graph_fn']) + '_triangles.npy') # TODO HERE
createSave(inv_dict['tri_fn'], tri_array)
print 'Triangle Count saved ...'
''' Degree count'''
if not inv_dict['deg_fn'] and inv_dict['deg']:
degDir = os.path.join(inv_dict['save_dir'], "Degree") #if degDir is None else degDir
inv_dict['deg_fn'] = os.path.join(degDir, getBaseName(inv_dict['graph_fn']) + '_degree.npy')
createSave(inv_dict['deg_fn'], deg_array)
print 'Degree saved ...'
''' MAD '''
if inv_dict['mad']:
MADdir = os.path.join(inv_dict['save_dir'], "MAD") #if MADdir is None else MADdir
inv_dict['mad_fn'] = os.path.join(MADdir, getBaseName(inv_dict['graph_fn']) + '_mad.npy')
createSave(inv_dict['mad_fn'], max_ave_deg)
print 'Maximum average Degree saved ...'
''' Scan Statistic 1'''
if inv_dict['ss1']:
ss1Dir = os.path.join(inv_dict['save_dir'], "SS1") #if ss1Dir is None else ss1Dir
inv_dict['ss1_fn'] = os.path.join(ss1Dir, getBaseName(inv_dict['graph_fn']) + '_scanstat1.npy')
createSave(inv_dict['ss1_fn'], ss1_array) # save it
print 'Scan 1 statistic saved ...'
''' Clustering coefficient '''
if inv_dict['cc']:
ccDir = os.path.join(inv_dict['save_dir'], "ClustCoeff") #if ccDir is None else ccDir
inv_dict['cc_fn'] = os.path.join(ccDir, getBaseName(inv_dict['graph_fn']) + '_clustcoeff.npy')
createSave(inv_dict['cc_fn'], cc_array) # save it
print 'Clustering coefficient saved ...'
''' Global Vertices '''
if inv_dict['ver']:
vertDir = os.path.join(inv_dict['save_dir'], "Globals") #if vertDir is None else vertDir
inv_dict['ver_fn'] = os.path.join(vertDir, getBaseName(inv_dict['graph_fn']) + '_numvert.npy')
createSave(inv_dict['ver_fn'], num_nodes) # save it
print 'Global vertices number saved ...'
''' Global number of edges '''
if inv_dict['edge']:
edgeDir = os.path.join(inv_dict['save_dir'], "Globals") #if edgeDir is None else edgeDir
inv_dict['edge_fn'] = os.path.join(edgeDir, getBaseName(inv_dict['graph_fn']) + '_numedges.npy')
createSave(inv_dict['edge_fn'], edge_count) # save it
print 'Global edge number saved ...'
#if test: # bench test
# tri_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_triangles.npy')
# eigvl_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_eigvl.npy')
# eigvect_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_eigvect.npy')
# MAD_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_MAD.npy')
return inv_dict # TODO: Fix code this breaks. Originally was [tri_fn, deg_fn, MAD_fn, eigvl_fn, eigvect_fn]
eigs = None
vcount = r_igraph_vcount(g, False)
nev = k if k < (vcount - 2) else (vcount - 3)
try:
eigs = esd(g, nev, real, lcc)
except Exception, msg:
print msg
return g # *Note premature exit*
if return_eigs: return eigs # used for MAD
if save_fn:
save_fn = os.path.abspath(save_fn)
createSave(save_fn[0], eigs[0][0]) # eigenvalues
createSave(save_fn[1], eigs[0][1]) # eigenvectors
print "Eigenvalues saved as %s ..." % save_fn[0]
print "eigenvectors ssaved as %s ..." % save_fn[1]
else:
global gl_eigvects
gl_eigvects = eigs[0][1]
print "Setting eigenvalues as graph attr ..."
g = r_igraph_set_graph_attribute(
g, "eigvals", "[" + ", ".join(map(cut, (eigs[0][0]))) +
"]") # Return a comma separated string
eig_idx = eigs[1]
print "Mapping eigenvectors ..."
def compute(inv_dict, save=True):
'''
@param inv_dict: is a dict optinally containing any of these:
- inv_dict['edge']: boolean for global edge count
- inv_dict['ver']: boolean for global vertex number
- inv_dict['tri']: boolean for local triangle count
- inv_dict['tri_fn']: the path of a precomputed triangle count (.npy)
- inv_dict['eig']: boolean for eigenvalues and eigenvectors
- inv_dict['eigvl_fn']: the path of a precomputed eigenvalues (.npy)
- inv_dict['eigvect_fn']: the path of a precomputed eigenvectors (.npy)
- inv_dict['deg']: boolean for local degree count
- inv_dict['deg_fn']: the path of a precomputed triangle count (.npy)
- inv_dict['ss1']: boolean for scan 1 statistic
- inv_dict['cc']: boolean for clustering coefficient
- inv_dict['mad']: boolean for maximum average degree
- inv_dict['save_dir']: the base path where all invariants will create sub-dirs & be should be saved
@param save: boolean for auto save or not. TODO: use this
'''
# Popualate inv_dict
inv_dict = populate_inv_dict(inv_dict)
if inv_dict['save_dir'] is None:
inv_dict['save_dir'] = os.path.dirname(inv_dict['graph_fn'])
if (inv_dict.has_key('G')):
if inv_dict['G'] is not None:
G = inv_dict['G']
elif (inv_dict['graphsize'] == 'b' or inv_dict['graphsize'] == 'big'):
G = loadAdjMat(inv_dict['graph_fn'], inv_dict['lcc_fn']) # TODO: test
# small graphs
else:
G = loadAnyMat(inv_dict['graph_fn'], inv_dict['data_elem'])
if isinstance(G, str):
print G
return G # Error message
num_nodes = G.shape[0] # number of nodes
# CC requires deg_fn and tri_fn. Load if available
if inv_dict['cc']:
# if either #tri or deg is undefined
if not inv_dict['tri_fn']:
inv_dict['tri'] = True
if not inv_dict['deg_fn']:
inv_dict['deg'] = True
cc_array = np.zeros(num_nodes)
# All invariants that require eigenvalues
if ((inv_dict['tri'] and not inv_dict['tri_fn']) or (inv_dict['mad'])):
if not inv_dict['eigvl_fn']:
inv_dict['eig'] = True
# Only create arrays if the computation will be done
if inv_dict['tri']:
if inv_dict['tri_fn']:
tri_array = np.load(inv_dict['tri_fn']) # load if precomputed
else:
tri_array = np.zeros(num_nodes) # local triangle count
if inv_dict['deg'] or inv_dict['edge']: # edge is global number of edges
inv_dict['deg'] = True
if inv_dict['deg_fn']:
deg_array = np.load(inv_dict['deg_fn'])
else:
deg_array = np.zeros(num_nodes) # Vertex degrees of all vertices
if (inv_dict['ss1']):
ss1_array = np.zeros(
num_nodes) # Induced subgraph edge number i.e scan statistic
if (not inv_dict['k'] or inv_dict['k'] > 100
or inv_dict['k'] > G.shape[0] - 2):
k = 100 if G.shape[0] - 2 > 101 else G.shape[
0] - 2 # Maximum of 100 eigenvalues
start = time()
# Calculate Eigenvalues & Eigen vectors
if inv_dict['eig']:
if not (inv_dict['eigvl_fn'] or inv_dict['eigvect_fn']):
l, u = arpack.eigs(G, k=k, which='LM') # LanczosMethod(A,0)
print 'Time taken to calc Eigenvalues: %f secs\n' % (time() -
start)
else:
try:
l = np.load(inv_dict['eigvl_fn'])
u = l = np.load(inv_dict['eigvect_fn'])
except Exception:
return "[IOERROR: ]Eigenvalues failed to load"
# All other invariants
start = time()
#### For loop ####
if (inv_dict['cc'] or inv_dict['ss1'] or (inv_dict['tri'] and not inv_dict['tri_fn'])\
or (inv_dict['deg'] and not inv_dict['deg_fn']) ): # one of the others
for j in range(num_nodes):
# tri
if not inv_dict['tri_fn'] and inv_dict[
'tri']: # if this is still None we need to compute it
tri_array[j] = abs(
round((sum(np.power(l.real, 3) * (u[j][:].real**2))) /
6.0)) # Divide by six because we count locally
# ss1 & deg
if inv_dict['ss1'] or (not inv_dict['deg_fn'] and inv_dict['deg']):
nbors = G[:, j].nonzero()[0]
# deg
if (not inv_dict['deg_fn'] and inv_dict['deg']):
deg_array[j] = nbors.shape[0]
# ss1
if inv_dict['ss1']:
if (nbors.shape[0] > 0):
nbors_mat = G[:, nbors][nbors, :]
ss1_array[j] = nbors.shape[0] + (
nbors_mat.nnz / 2.0
) # scan stat 1 # Divide by two because of symmetric matrix
else:
ss1_array[
j] = 0 # zero neighbors hence zero cardinality enduced subgraph
# cc
if inv_dict['cc']:
if (deg_array[j] > 2):
cc_array[j] = (2.0 * tri_array[j]) / (
deg_array[j] * (deg_array[j] - 1)) # Jari et al
else:
cc_array[j] = 0
print 'Time taken to compute loop dependent invariants: %f secs\n' % (
time() - start)
### End For ###
# global edge
if inv_dict['edge']:
edge_count = deg_array.sum()
# global vertices is num_nodes
''' MAD '''
if (inv_dict['mad']):
max_ave_deg = np.max(l.real)
# Computation complete - handle the saving now ...
''' Top eigenvalues & eigenvectors '''
if not inv_dict['eigvl_fn'] and inv_dict['eig']:
eigvDir = os.path.join(inv_dict['save_dir'],
"Eigen") #if eigvDir is None else eigvDir
# Immediately write eigs to file
inv_dict['eigvl_fn'] = os.path.join(
eigvDir,
getBaseName(inv_dict['graph_fn']) + '_eigvl.npy')
inv_dict['eigvect_fn'] = os.path.join(
eigvDir,
getBaseName(inv_dict['graph_fn']) + '_eigvect.npy')
createSave(inv_dict['eigvl_fn'], l.real) # eigenvalues
createSave(inv_dict['eigvect_fn'], u) # eigenvectors
print 'Eigenvalues and eigenvectors saved ...'
''' Triangle count '''
if not inv_dict['tri_fn'] and inv_dict['tri']:
triDir = os.path.join(inv_dict['save_dir'],
"Triangle") #if triDir is None else triDir
inv_dict['tri_fn'] = os.path.join(triDir,
getBaseName(inv_dict['graph_fn']) +
'_triangles.npy') # TODO HERE
createSave(inv_dict['tri_fn'], tri_array)
print 'Triangle Count saved ...'
''' Degree count'''
if not inv_dict['deg_fn'] and inv_dict['deg']:
degDir = os.path.join(inv_dict['save_dir'],
"Degree") #if degDir is None else degDir
inv_dict['deg_fn'] = os.path.join(
degDir,
getBaseName(inv_dict['graph_fn']) + '_degree.npy')
createSave(inv_dict['deg_fn'], deg_array)
print 'Degree saved ...'
''' MAD '''
if inv_dict['mad']:
MADdir = os.path.join(inv_dict['save_dir'],
"MAD") #if MADdir is None else MADdir
inv_dict['mad_fn'] = os.path.join(
MADdir,
getBaseName(inv_dict['graph_fn']) + '_mad.npy')
createSave(inv_dict['mad_fn'], max_ave_deg)
print 'Maximum average Degree saved ...'
''' Scan Statistic 1'''
if inv_dict['ss1']:
ss1Dir = os.path.join(inv_dict['save_dir'],
"SS1") #if ss1Dir is None else ss1Dir
inv_dict['ss1_fn'] = os.path.join(
ss1Dir,
getBaseName(inv_dict['graph_fn']) + '_scanstat1.npy')
createSave(inv_dict['ss1_fn'], ss1_array) # save it
print 'Scan 1 statistic saved ...'
''' Clustering coefficient '''
if inv_dict['cc']:
ccDir = os.path.join(inv_dict['save_dir'],
"ClustCoeff") #if ccDir is None else ccDir
inv_dict['cc_fn'] = os.path.join(
ccDir,
getBaseName(inv_dict['graph_fn']) + '_clustcoeff.npy')
createSave(inv_dict['cc_fn'], cc_array) # save it
print 'Clustering coefficient saved ...'
''' Global Vertices '''
if inv_dict['ver']:
vertDir = os.path.join(inv_dict['save_dir'],
"Globals") #if vertDir is None else vertDir
inv_dict['ver_fn'] = os.path.join(
vertDir,
getBaseName(inv_dict['graph_fn']) + '_numvert.npy')
createSave(inv_dict['ver_fn'], num_nodes) # save it
print 'Global vertices number saved ...'
''' Global number of edges '''
if inv_dict['edge']:
edgeDir = os.path.join(inv_dict['save_dir'],
"Globals") #if edgeDir is None else edgeDir
inv_dict['edge_fn'] = os.path.join(
edgeDir,
getBaseName(inv_dict['graph_fn']) + '_numedges.npy')
createSave(inv_dict['edge_fn'], edge_count) # save it
print 'Global edge number saved ...'
#if test: # bench test
# tri_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_triangles.npy')
# eigvl_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_eigvl.npy')
# eigvect_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_eigvect.npy')
# MAD_fn = os.path.join('bench', str(G.shape[0]), getBaseName(inv_dict['graph_fn']) + '_MAD.npy')
return inv_dict # TODO: Fix code this breaks. Originally was [tri_fn, deg_fn, MAD_fn, eigvl_fn, eigvect_fn]
