def runInvariants(inv_list, graph_fn, save_dir, graph_format="graphml", sep_save=False):
'''
Run the selected multivariate invariants as defined
@param inv_list: the list of invariants we are to compute
@param graph_fn: the graph filename on disk
@param save_dir: the directory where to save resultant data
@param graph_format: the format of the graph
@param sep_save: boolean on whether to save invariants in separate files
'''
inv_dict = {'graph_fn':graph_fn, 'save_dir':save_dir}
for inv in inv_list:
inv_dict[inv] = True
inv_dict = cci.compute(inv_dict, sep_save=sep_save, gformat=graph_format)
if isinstance(inv_dict, str):
return inv_dict # Error message
else:
inv_dict = inv_dict[1]
return_dict = dict()
for key in inv_dict:
if key.endswith("_fn") and not key.startswith("eig"): # skip eigs
return_dict[key] = inv_dict[key]
if inv_dict.get("eigvl_fn", None): # or "eigvect_fn"
return_dict["eig"] = [inv_dict["eigvect_fn"], inv_dict["eigvl_fn"]] # Note this
return return_dict
def runInvariants(inv_list, graph_fn, save_dir, lcc_fn, graphsize):
'''
'''
inv_dict = {'graph_fn':graph_fn, 'save_dir':save_dir, \
'lcc_fn':lcc_fn,'graphsize':graphsize}
for inv in inv_list:
inv_dict[inv] = True
inv_dict = cci.compute(inv_dict)
return_dict = dict()
if inv_dict['ss1_fn']:
return_dict['ss1'] = inv_dict['ss1_fn']
if inv_dict['tri_fn']:
return_dict['tri'] = inv_dict['tri_fn']
if inv_dict['deg_fn']:
return_dict['deg'] = inv_dict['deg_fn']
if inv_dict['ss2_fn']:
return_dict['ss2'] = inv_dict['ss2_fn']
if inv_dict['apl_fn']:
return_dict['apl'] = inv_dict['apl_fn']
if inv_dict['gdia_fn']:
return_dict['gdia'] = inv_dict['gdia_fn']
if inv_dict['cc_fn']:
return_dict['cc'] = inv_dict['cc_fn']
if inv_dict['mad_fn']:
return_dict['mad'] = inv_dict['mad_fn']
if inv_dict['eigvl_fn']:
return_dict['eig'] = [inv_dict['eigvect_fn'],
inv_dict['eigvl_fn']] # Note this
return return_dict
def runInvariants(inv_list, graph_fn, save_dir, lcc_fn, graphsize):
'''
'''
inv_dict = {'graph_fn':graph_fn, 'save_dir':save_dir, \
'lcc_fn':lcc_fn,'graphsize':graphsize}
for inv in inv_list:
inv_dict[inv] = True
inv_dict = cci.compute(inv_dict)
return_dict = dict()
if inv_dict['ss1_fn']:
return_dict['ss1'] = inv_dict['ss1_fn']
if inv_dict['tri_fn']:
return_dict['tri'] = inv_dict['tri_fn']
if inv_dict['deg_fn']:
return_dict['deg'] = inv_dict['deg_fn']
if inv_dict['ss2_fn']:
return_dict['ss2'] = inv_dict['ss2_fn']
if inv_dict['apl_fn']:
return_dict['apl'] = inv_dict['apl_fn']
if inv_dict['gdia_fn']:
return_dict['gdia'] = inv_dict['gdia_fn']
if inv_dict['cc_fn']:
return_dict['cc'] = inv_dict['cc_fn']
if inv_dict['mad_fn']:
return_dict['mad'] = inv_dict['mad_fn']
if inv_dict['eigvl_fn']:
return_dict['eig'] = [inv_dict['eigvect_fn'], inv_dict['eigvl_fn']] # Note this
return return_dict
def run_invariants(inv_list, graph_fn, save_dir, graph_format="graphml", sep_save=False):
'''
Run the selected multivariate invariants as defined
@param inv_list: the list of invariants we are to compute
@param graph_fn: the graph filename on disk
@param save_dir: the directory where to save resultant data
@param graph_format: the format of the graph
@param sep_save: boolean on whether to save invariants in separate files
'''
inv_dict = {'graph_fn':graph_fn, 'save_dir':save_dir}
for inv in inv_list:
inv_dict[inv] = True
inv_dict = cci.compute(inv_dict, sep_save=sep_save, gformat=graph_format)
if isinstance(inv_dict, str):
return inv_dict # Error message
else:
inv_dict = inv_dict[1]
return_dict = dict()
for key in inv_dict:
if key.endswith("_fn") and not key.startswith("eig"): # skip eigs
return_dict[key] = inv_dict[key]
if inv_dict.get("eigvl_fn", None): # or "eigvect_fn"
return_dict["eig"] = [inv_dict["eigvect_fn"], inv_dict["eigvl_fn"]] # Note this
return return_dict
def testing(inv_dict):
print "Entering testing module ..."
inv_dict = compute(inv_dict)
num_nodes = np.load(inv_dict["ver_fn"]).item()
benchdir = "/Users/disa/m2g/MROCPdjango/computation/tests/bench" # TODO DM: Alter Dynamically
testObj = unittesting.test(
inv_dict["graph_fn"],
inv_dict["save_dir"],
num_nodes,
inv_dict["ss1_fn"],
inv_dict["deg_fn"],
inv_dict["tri_fn"],
inv_dict["cc_fn"],
inv_dict["mad_fn"],
benchdir,
) # Create unittest object
testObj.testClustCoeff()
testObj.testDegree()
testObj.testTriangles()
testObj.testMAD()
testObj.testSS1()
def main():
parser = argparse.ArgumentParser(description="Run MROCP invariants individually for timing purposes")
parser.add_argument("gfn", action="store", help="The name of the graph on disk")
result = parser.parse_args()
g = loadAnyMat(result.gfn)
begin = time()
# TODO optimize invariants
# Deg
print "Individual run ...\n Processing Degree vector ..."
b = time()
compute({"deg":True, "G":g, "graph_fn":result.gfn}, save=False)
print "Time for degree vector = %.4f"% (time()-b)
# SS
print "Processing Scan Statistic ..."
b = time()
compute({"ss1":True, "G":g, "graph_fn":result.gfn}, save=False)
print "Time for scan 1 vector = %.4f"% (time()-b)
# CC
print "Processing Clustering Coefficient (Transitivity)"
b = time()
compute({"cc":True, "G":g, "graph_fn":result.gfn}, save=False)
print "Time for Clustering Coefficient vector = %.4f"% (time()-b)
# TRI
b = time()
compute({"tri":True, "G":g, "graph_fn":result.gfn}, save=False)
print "Time for triangle vector = %.4f" % (time()-b)
print "Total time for non-daisy-chained invariant = %.4f" % (time()-begin) # minus all the populate_invariants
print "\n*** Daisy-chain run ... ***\n"
begin = time()
compute({"deg":True, "ss1":True, "cc":True, "tri":True, "G":g, "graph_fn":result.gfn}, save=False)
print "Total time for daisy-chained invariant = %.4f" % (time()-begin) # minus all the populate_invariants
def testing(inv_dict):
print "Entering testing module ..."
inv_dict = compute(inv_dict)
num_nodes = np.load(inv_dict["ver_fn"]).item()
benchdir = "/Users/disa/m2g/MROCPdjango/computation/tests/bench" # TODO DM: Alter Dynamically
testObj = unittesting.test(inv_dict["graph_fn"], inv_dict["save_dir"], num_nodes, inv_dict["ss1_fn"]\
, inv_dict["deg_fn"], inv_dict["tri_fn"], inv_dict["cc_fn"], inv_dict["mad_fn"], benchdir) # Create unittest object
testObj.testClustCoeff()
testObj.testDegree()
testObj.testTriangles()
testObj.testMAD()
testObj.testSS1()
