def computing_node_handler(self, communicator, data, parameter_list):
"""
12-20-05
called common's computing_node()
2006-09-21 add fuzzyDense_flag
"""
node_rank = communicator.rank
sys.stderr.write("Node no.%s working...\n"%node_rank)
data = cPickle.loads(data)
gene_no2bs_no_set, bs_no2gene_no_set, ratio_cutoff, \
top_number, p_value_cut_off, fuzzyDense_instance, degree_cut_off, fuzzyDense_flag = parameter_list
result = []
for row in data:
id, vertex_set, recurrence_array = row
vertex_set = vertex_set[1:-1].split(',')
vertex_set = map(int, vertex_set)
if fuzzyDense_flag:
recurrence_array = recurrence_array[1:-1].split(',')
recurrence_array = map(float, recurrence_array)
core_vertex_list, on_dataset_index_ls = fuzzyDense_instance.get_core_vertex_set(vertex_set, recurrence_array, degree_cut_off)
if core_vertex_list:
ls_to_return = cluster_bs_analysis(core_vertex_list, gene_no2bs_no_set, bs_no2gene_no_set, ratio_cutoff, \
top_number, p_value_cut_off)
if ls_to_return:
result.append([id, core_vertex_list, on_dataset_index_ls, ls_to_return])
else:
ls_to_return = cluster_bs_analysis(vertex_set, gene_no2bs_no_set, bs_no2gene_no_set, ratio_cutoff, \
top_number, p_value_cut_off)
if ls_to_return:
result.append([id, vertex_set, [0], ls_to_return]) #05-31-06, on_dataset_index_ls is faked by [0]
sys.stderr.write("Node no.%s done.\n"%node_rank)
return result
rows = curs.fetchall()
vertex_list, recurrence_array = rows[0]
vertex_list = vertex_list[1:-1].split(',')
vertex_list = map(int, vertex_list)
recurrence_array = recurrence_array[1:-1].split(',')
recurrence_array = map(float, recurrence_array)
fuzzyDense_instance = fuzzyDense(edge2encodedOccurrence, debug)
core_vertex_ls, recurrent_and_on_datasets_ls = fuzzyDense_instance.get_core_vertex_set(vertex_list, recurrence_array, degree_cut_off)
from MpiClusterBsStat import MpiClusterBsStat
MpiClusterBsStat_instance = MpiClusterBsStat()
gene_no2bs_no_block = MpiClusterBsStat_instance.get_gene_no2bs_no_block(curs)
gene_no2bs_no_set, bs_no2gene_no_set = MpiClusterBsStat_instance.construct_two_dicts(0, gene_no2bs_no_block)
from TF_functions import cluster_bs_analysis
ls_to_return = cluster_bs_analysis(core_vertex_ls, gene_no2bs_no_set, bs_no2gene_no_set, ratio_cutoff, \
top_number, p_value_cut_off)
gene_id2symbol = get_gene_id2gene_symbol(curs, tax_id)
dataset_no2desc = get_dataset_no2desc(curs)
dataset_no_desc_ls = []
for dataset_index in recurrent_and_on_datasets_ls:
dataset_no = dataset_index +1
dataset_no_desc_ls.append([dataset_no, dataset_no2desc[dataset_no]])
outf = open(output_file, 'w')
outf.write("out:=[\n")
for i in range(len(ls_to_return)):
row = ls_to_return[i]
score, score_type, bs_no_list, target_gene_no_list, global_ratio, local_ratio, expected_ratio, unknown_ratio = row