def GetConfigurationData(self):
''' Get configuration data from file.
@returns: ConfigData - Configuration data wrapped within a
ConfigData object. '''
with open(self._configFile, 'r') as f:
content = f.read()
broadcastData = content.split('\n')
portData = broadcastData[0]
messageData = broadcastData[1]
port = int(self._getCleanedData(portData))
message = self._getCleanedData(messageData)
return ConfigData(port, message)
def __init__(self, owner):
"""Create the SourceController
@param owner: Owner window
"""
object.__init__(self)
# Attributes
self._parent = owner
self._pid = self._parent.GetId()
self.config = ConfigData() # Singleton config data instance
self.tempdir = None
self.scThreads = {}
# Number of seconds to allow a source control command to run
# before timing out
self.scTimeout = 60
def __init__(self, config_file, workspace_folder):
self.logger = logging.getLogger(self.logger_name + '.MailBox')
self.workspace = workspace_folder
self.configs = ConfigData(config_file)
self.logger.debug('workspace "{}" configs: {}'.format(
self.workspace, self.configs.toStringFiltered()))
self.logger.debug('creating MailReceiver')
self.receiver = MailReceiver(self.configs.imap,\
self.configs.imap_port,\
self.configs.ssl_enabled,\
self.configs.username,\
self.configs.password)
self.logger.debug('creating MailSender')
self.sender = MailSender(self.configs.smtp,\
self.configs.smtp_port,\
self.configs.username,\
self.configs.password)
class GraphClusterer_WI_semisupervised(object):
CODE_DIR = '/Users/divya/work/repo/Dissertation'
#CODE_DIR = '/Users/divya/Documents/Dissertation/Dissertation'
DATA_DIR = '/Users/divya/Documents/input/Dissertation/data'
LOG_DIR = '/Users/divya/Documents/logs/Dissertation'
configdata = ConfigData(CODE_DIR, DATA_DIR, LOG_DIR)
#graphdata = GraphData_Gene(GO_SIM_TYPE)
graphdata = None
def __init__(self, K):
self.phase1data = None
self.phase2data = None
self.phase1_allKevaluationdata = None
self.phase2_allKevaluationdata = None
self.helper = MKNN_Helper()
#self.GO_SIM_TYPE = 'BP'
##############################################################
#1. Initialize MKNN
#2. As a wrapper, call MKNN_worker for different values of K
##############################################################
def MKNN_worker_wrapper(self):
#GraphClusterer.configdata.logger.info("Initialization phase of GMKNN begins")
self.MKNN_init()
GraphClusterer_WI_semisupervised.configdata.logger.info(
"Initialization phase of GMKNN ends.")
GraphClusterer_WI_semisupervised.configdata.logger.info(
"Working of G-MKNN begins")
GraphClusterer_WI_semisupervised.configdata.logger.info(
"Running G-MKNN for different values of K.")
K_range = list(
range(
(int)(GraphClusterer_WI_semisupervised.configdata.K_min),
(int)(GraphClusterer_WI_semisupervised.configdata.K_max) + 1))
for K in K_range:
GraphClusterer_WI_semisupervised.configdata.logger.info(
"Running G-MKNN for the value of K: ")
GraphClusterer_WI_semisupervised.configdata.logger.info(K)
#Call MKNN_worker for the value of K
self.MKNN_worker(K)
#(CL_List_P2, CL_List_P1, SM, SM_orig, num_clusters_P2, num_clusters_P1, num_nodes) = MKNN_worker(K, max_num_clusters, SM, SM_orig, num_nodes, node_codes, currentdate_str, dataset_name, eval_results_dir, log)
#Plot evaluation measures for all values of K for phase 1
self.phase1_allKevaluationdata.plot_evaluation_measures_for_all_K()
#Plot evaluation measures for all values of K for phase 2
self.phase2_allKevaluationdata.plot_evaluation_measures_for_all_K()
############################################
#Set up configuration
#Set up the input matrices for the algorithm
############################################
def MKNN_init(self):
#setting up configuration
GraphClusterer_WI_semisupervised.configdata.do_config()
GraphClusterer_WI_semisupervised.configdata.data_dir
logger = GraphClusterer_WI_semisupervised.configdata.logger
logger.debug("Debugging from inside MKNN_init method")
#Instantiate GraphData_Gene
GraphClusterer_WI_semisupervised.graphdata = GraphData_Gene(
GraphClusterer_WI_semisupervised.configdata.GO_TYPE,
GraphClusterer_WI_semisupervised.configdata.GO_SIZE,
GraphClusterer_WI_semisupervised.configdata.GO_SIM_TYPE,
GraphClusterer_WI_semisupervised.configdata.go_obo_file,
GraphClusterer_WI_semisupervised.configdata.gene_syn_file)
#setting up the input matrices
#Create SM and SM_orig
GraphClusterer_WI_semisupervised.graphdata.create_SM_from_relfile(
GraphClusterer_WI_semisupervised.configdata.inp_rel_file)
#Expand SM
#GraphClusterer_WI_semisupervised.graphdata.setup_expanded_SM(GraphClusterer_WI_semisupervised.configdata.nhops, GraphClusterer_WI_semisupervised.configdata.inp_rel_file)
#Setup GOsim based SM_GO
#GraphClusterer_WI_semisupervised.graphdata.setup_SM_GO(GraphClusterer_WI_semisupervised.configdata.inp_rel_file, GraphClusterer_WI_semisupervised.configdata.gene2go_file)
GraphClusterer_WI_semisupervised.graphdata.setup_SM_GO_1(
GraphClusterer_WI_semisupervised.configdata.inp_rel_file,
GraphClusterer_WI_semisupervised.configdata.gene2go_file)
#Create Edge Objects
GraphClusterer_WI_semisupervised.graphdata.create_edge_objects()
#self.helper.print_dict(GraphClusterer.graphdata.edge_dict)
#self.helper.print_set(GraphClusterer.graphdata.node_dict[1].node_edges_dict[EdgeType.secondary])
#print(GraphClusterer.graphdata.edge_dict[011].edge_id)
#Initialize all K evaluation objects for both phases
self.phase1_allKevaluationdata = AllKEvaluationData(
self.configdata, 1) #1 for phase=1
self.phase2_allKevaluationdata = AllKEvaluationData(
self.configdata, 2) #2 for phase=2
print("MKNN_Init phase complete.")
#############################
#Run MKNN for one value of K
#############################
def MKNN_worker(self, K):
self.phase1data = Phase1Data_WI_Gene(
GraphClusterer_WI_semisupervised.graphdata,
GraphClusterer_WI_semisupervised.configdata, K)
self.MKNN_Phase1()
self.phase2data = Phase2Data_WI_Gene(
GraphClusterer_WI_semisupervised.graphdata,
GraphClusterer_WI_semisupervised.configdata, K,
self.phase1data.cnodes_dict, self.phase1data.next_cluster_label,
self.phase1data.num_clusters)
self.MKNN_Phase2()
def MKNN_Phase1(self):
#Initialize Phase 1
self.phase1data.initialize_phase()
#self.helper.print_list(self.phase1data.graphdata.node_dict[10].MKNN_list)
#print('Degree')
#print((self.phase1data.graphdata.node_dict[10].degree))
#print('CI_list')
#self.helper.print_list(self.phase1data.cluster_initiator_list)
#self.helper.convert_list_ids_to_codes(self.graphdata, self.phase1data.cluster_initiator_list)
#print((self.phase1data.graphdata.CI_list[0]))
#Execute Phase 1
self.phase1data.execute_phase()
#Visualize Phase 1 results
self.phase1data.visualize_phase()
#Evaluate phase
self.phase1data.evaluate_phase()
self.phase1_allKevaluationdata.add_evaluation_for_K(
self.phase1data.phase1_evaluation_data)
print("MKNN_Phase1 complete.")
def MKNN_Phase2(self):
#Initialize phase 2
self.phase2data.initialize_phase()
#self.helper.print_list(self.phase2data.c_SM)
#self.helper.print_list(self.phase2data.c_SM_sort)
#Execute phase 2
self.phase2data.execute_phase()
#Visualize phase
self.phase2data.visualize_phase()
#Evaluate Phase
self.phase2data.evaluate_phase()
self.phase2_allKevaluationdata.add_evaluation_for_K(
self.phase2data.phase2_evaluation_data)
#self.helper.print_list(self.phase2data.phase2_evaluation_data.gold_standard_CL_list)
self.helper.print_list(
self.phase2data.phase2_evaluation_data.contingency_matrix)
print("sensitivity:")
print(self.phase2data.phase2_evaluation_data.sensitivity)
print("PPV")
print(self.phase2data.phase2_evaluation_data.PPV)
print("accuracy")
print(self.phase2data.phase2_evaluation_data.accuracy)
class MKNN_Helper(object):
CODE_DIR = '/Users/divya/work/repo/Dissertation'
#CODE_DIR = '/Users/divya/Documents/Dissertation/Dissertation'
DATA_DIR = '/Users/divya/Documents/input/Dissertation/data'
LOG_DIR = '/Users/divya/Documents/logs/Dissertation'
configdata = ConfigData(CODE_DIR, DATA_DIR, LOG_DIR)
def __init__(self):
MKNN_Helper.configdata.do_config()
###################################################
#Helper function: Calculate the union of two lists
#Used in MKNN_init
##################################################
def union(self, a, b):
""" return the union of two lists """
return list(set(a) | set(b))
def print_list(self, list_1):
for i in list_1:
print(i)
print(",")
def print_set(self, set_1):
for i in set_1:
print(i)
print(",")
def print_dict(self, dict_1):
for (key, value) in dict_1.items():
print("%s: %s" % (key, value))
def convert_list_ids_to_codes(self, graphdata, list_1):
codes_list = [graphdata.node_dict[i].node_code for i in list_1]
print(codes_list)
def print_set_codes(self, set_1, node_dict):
for i in set_1:
print(node_dict[i].node_code)
print(",")
def print_list_codes(self, list_1, node_dict):
for i in list_1:
if i != -1:
print(node_dict[i].node_code)
else:
print("-1")
print(",")
def print_clusters(self, clusters_list, cnodes_dict):
nodeset = set()
for cluster_id in clusters_list:
cnode_data = cnodes_dict[cluster_id]
nodeset = cnode_data.node_set
def edit_cluster_label_list(self, cluster_label_list, node_dict,
cnodes_dict, specific_set_to_draw,
algorithm_name):
for cluster_id in specific_set_to_draw:
set_temp = set()
set_temp.add(cluster_id)
cnode_data = cnodes_dict[cluster_id]
nodeset = cnode_data.node_set
for node_id in nodeset:
if algorithm_name == AlgorithmName.Clusterone:
if len(
set(node_dict[node_id].clusterone_clabel_dict.keys(
)).intersection(
specific_set_to_draw.difference(
set_temp))) != 0:
cluster_label_list[node_id] = -3
print("Specific 1")
else:
cluster_label_list[node_id] = cluster_id
print("Specific 2")
elif algorithm_name == AlgorithmName.GMKNN_ZhenHu:
if set(node_dict[node_id].GMKNN_clabel_dict.keys(
)).intersection(
specific_set_to_draw.difference(set_temp)) != None:
cluster_label_list[node_id] = -3
else:
cluster_label_list[node_id] = cluster_id
return cluster_label_list