def __cpp_sim_matrix_l_generation_routine__(sim_matrix_path, mscmodel, msc2ix, secondary_codes_weight, docid2seccodes):
#dstmatrixpath = TMPDIR+"/mlevel_similarity_matrix_"+similarity_aggregation_method_l+"_"+base64.b16encode(aux.quick_md5(sim_matrix_path+similarity_aggregation_method_l+str(MIN_COUNT_MSCPRIM)))
dstmatrixpath = sim_matrix_path+".msc"+str(MIN_COUNT_MSCPRIM)+"_"+similarity_aggregation_method_l
if not aux.exists(dstmatrixpath):
msc2wids_list = get_msc2wids_list(msc2ix, mscmodel, secondary_codes_weight, docid2seccodes)
cpp_wrapper.aggregate_simmatrix(sim_matrix_path, dstmatrixpath, msc2wids_list, method=similarity_aggregation_method_l)
logging.info("[build_msc_tree] Loading simmatrix from: "+str(dstmatrixpath))
(rows, cols, sim_matrix_l) = matrix_io.fread_smatrix(dstmatrixpath)
____validate_cpp_output____(msc2ix, rows)
return sim_matrix_l
def __cpp_sim_matrix_l_generation_routine__(sim_matrix_path, mscmodel, msc2ix,
secondary_codes_weight,
docid2seccodes):
#dstmatrixpath = TMPDIR+"/mlevel_similarity_matrix_"+similarity_aggregation_method_l+"_"+base64.b16encode(aux.quick_md5(sim_matrix_path+similarity_aggregation_method_l+str(MIN_COUNT_MSCPRIM)))
dstmatrixpath = sim_matrix_path + ".msc" + str(
MIN_COUNT_MSCPRIM) + "_" + similarity_aggregation_method_l
if not aux.exists(dstmatrixpath):
msc2wids_list = get_msc2wids_list(msc2ix, mscmodel,
secondary_codes_weight,
docid2seccodes)
cpp_wrapper.aggregate_simmatrix(sim_matrix_path,
dstmatrixpath,
msc2wids_list,
method=similarity_aggregation_method_l)
logging.info("[build_msc_tree] Loading simmatrix from: " +
str(dstmatrixpath))
(rows, cols, sim_matrix_l) = matrix_io.fread_smatrix(dstmatrixpath)
____validate_cpp_output____(msc2ix, rows)
return sim_matrix_l
print "[build_msc_tree] MIN_COUNT_MSCPRIM =", MIN_COUNT_MSCPRIM
print "[build_msc_tree] MIN_COUNT_MSCSEC =", MIN_COUNT_MSCSEC
print "[build_msc_tree] clustering_method =", clustering_method
print "[build_msc_tree] similarity_aggregation_method_l =", similarity_aggregation_method_l
print "[build_msc_tree] secondary_weight_method =", secondary_weight_method
print "[build_msc_tree] secondary_codes_weight =", secondary_codes_weight
print "[build_msc_tree] similarity_aggregation_method_m =", similarity_aggregation_method_m
print "[build_msc_tree] similarity_aggregator_m =", similarity_aggregator_m
print "[build_msc_tree] numiterations =", numiterations
print "[build_msc_tree] l_clusters_range =", str(
l_clusters_range)[:100], "..."
print "[build_msc_tree] m_clusters_range =", str(
m_clusters_range)[:100], "..."
print "[build_msc_tree] *************************************"
if not aux.exists(
sim_matrix_path) or os.stat(sim_matrix_path).st_size <= 0:
print "[build_msc_tree] ============================================================================================================"
print "[build_msc_tree] Building similarity matrix: sim_matrix_path = ", sim_matrix_path
#print "[zbl_build_msc_tree] cpp:",zbl_path, sim_matrix_path, field_name, similarity_calculator
result = cpp_wrapper.run_exec(
"../cpp_modules/main/zbl_similarity_matrix",
args=[
field_name, similarity_calculator, zbl_path, sim_matrix_path
])
if result != 0:
print "[build_msc_tree][ERROR] Failure while calculating documents' similarity matrix!"
sys.exit(-10)
print "[build_msc_tree] ================================================================"
print "[build_msc_tree] ============================================================================================================"
print "[build_msc_tree] Loading ZBL records from zbl_path=", zbl_path
print "[build_msc_tree] sim_matrix_path=",sim_matrix_path
print "[build_msc_tree] MIN_COUNT_MSC =",MIN_COUNT_MSC
print "[build_msc_tree] MIN_COUNT_MSCPRIM =",MIN_COUNT_MSCPRIM
print "[build_msc_tree] MIN_COUNT_MSCSEC =",MIN_COUNT_MSCSEC
print "[build_msc_tree] clustering_method =", clustering_method
print "[build_msc_tree] similarity_aggregation_method_l =", similarity_aggregation_method_l
print "[build_msc_tree] secondary_weight_method =",secondary_weight_method
print "[build_msc_tree] secondary_codes_weight =",secondary_codes_weight
print "[build_msc_tree] similarity_aggregation_method_m =", similarity_aggregation_method_m
print "[build_msc_tree] similarity_aggregator_m =",similarity_aggregator_m
print "[build_msc_tree] numiterations =",numiterations
print "[build_msc_tree] l_clusters_range =",str(l_clusters_range)[:100],"..."
print "[build_msc_tree] m_clusters_range =",str(m_clusters_range)[:100],"..."
print "[build_msc_tree] *************************************"
if not aux.exists(sim_matrix_path) or os.stat(sim_matrix_path).st_size <= 0:
print "[build_msc_tree] ============================================================================================================"
print "[build_msc_tree] Building similarity matrix: sim_matrix_path = ", sim_matrix_path
#print "[zbl_build_msc_tree] cpp:",zbl_path, sim_matrix_path, field_name, similarity_calculator
result = cpp_wrapper.run_exec("../cpp_modules/main/zbl_similarity_matrix", args = [field_name, similarity_calculator, zbl_path, sim_matrix_path])
if result != 0:
print "[build_msc_tree][ERROR] Failure while calculating documents' similarity matrix!"
sys.exit(-10)
print "[build_msc_tree] ================================================================"
print "[build_msc_tree] ============================================================================================================"
print "[build_msc_tree] Loading ZBL records from zbl_path=",zbl_path
zblid2zbl = dict( (zbl[zbl_io.ZBL_ID_FIELD],zbl) for zbl in _get_zbl_generator_(zbl_path) )
print "[build_msc_tree] zblid2zbl [",len(zblid2zbl),"docs loaded] =",str(list(zblid2zbl.iteritems()))[:100]
