def writeplaintext(wordref, stan_path, outxml, xml):
import NERTest as NER
plaintext = str.join('', [wordref[x]+' ' for x in wordref])
filename = "/home/grant/devel/TopoCluster/data/tempplain_" + xml
op = io.open(filename, 'w', encoding='utf-8')
op.write(unicode(plaintext))
op.close()
NER.calc3(stan_path, filename, outxml)
toporef2, wordref2 = NER.readnerxml2(outxml)
return wordref2, toporef2
def calc(in_domain_stat_tbl, out_domain_stat_tbl, test_xml, conn_info, gtbl, window, percentile,
main_topo_weight, other_topo_weight, other_word_weight, country_tbl, region_tbl,
state_tbl, geonames_tbl, in_corp_lamb, out_corp_lamb, results_file, stan_path):
print "In Domain Local Statistics Table Name: ", in_domain_stat_tbl
print "Out of domain Local Statistics Table Name: ", out_domain_stat_tbl
print "Directory Path containing plain text files to be parsed: ", test_xml
print "DB connection info: ", conn_info
print "Grid table used: ", gtbl
print "Window size", window
print "Percentile: ", percentile
print "Main Toponym weight: ", main_topo_weight
print "Other Toponym weight: ", other_topo_weight
print "Other Word weight: ", other_word_weight
print "Country table name: ", country_tbl
print "Region table name: ", region_tbl
print "State table name: ", state_tbl
print "Out of Domain Lambda", out_corp_lamb
print "In Domain Lambda", in_corp_lamb
#Test the connection to the database
conn = psycopg2.connect(conn_info)
print "Connection Success"
#These words and characters will not be evaluated or be used for Gi* vector summing
stopwords = set(['.',',','(',')','-', '--', u'\u2010', u'\u2011', u'\u2012', u'\u2013','=',";",':',"'",'"','$','the','a','an','that','this',
'to', 'be', 'have', 'has', 'is', 'are', 'was', 'am', "'s",
'and', 'or','but',
'by', 'of', 'from','in','after','on','for', 'to', 'TO',
'I', 'me', 'he', 'him', 'she', 'her', 'we', 'us', 'you', 'your', 'yours' 'they', 'them', 'their', 'it', 'its'])
#Initialize a cursor for DB connection
cur = conn.cursor()
#Check to see if database tables were set up properly
try:
ood_table_list = ['enwiki20130102_ner_final_atoi', 'enwiki20130102_ner_final_jtos', 'enwiki20130102_ner_final_ttoz', 'enwiki20130102_ner_final_other']
for tb in ood_table_list:
SQL_check = "select * FROM %s LIMIT 1;" % (tb)
cur.execute(SQL_check)
result = cur.fetchall()
if len(result) > 0:
print tb, "table loaded correctly"
except:
print "Out of domain tables were not loaded correctly"
print "Exiting..."
sys.exit()
try:
if in_domain_stat_tbl != "None":
SQL_check = "select * FROM %s LIMIT 1;" % (out_domain_stat_tbl)
cur.execute(SQL_check)
result = cur.fetchall()
if len(result) > 0:
print out_domain_stat_tbl, "table loaded correctly"
except:
print "In domain table provided was not loaded correctly:", in_domain_stat_tbl
print "Exiting..."
sys.exit()
#Intitialize a Ditionary that links GlobalGrid gid values to Latitude/Longitudes
lat_long_lookup = {}
SQL2 = "SELECT gid, ST_Y(geog::geometry), ST_X(geog::geometry) from %s ;" % gtbl
cur.execute(SQL2)
lat_long_lookup = dict([(int(g[0]), [g[1],g[2]]) for g in cur.fetchall()])
#print len(lat_long_lookup)
point_total_correct = 0
poly_total_correct = 0
start_time = datetime.datetime.now()
total_topo = 0
#Test xml should always be a directory name. System currently only supports directory as an argument, though may change in the future.
if os.path.isdir(test_xml) == True:
print "Reading as directory"
files = os.listdir(test_xml)
point_bigerror = []
poly_bigerror = []
point_dist_list = []
poly_dist_list = []
point_error_sum = 0.0
poly_error_sum = 0.0
error_sum2 = 0.0
poly_dist = 0.0
m = 0
#These queries are designed to pull all the alternate names from the geonames, country, state, and region tables. Alternate names are used in later steps to enhance gazetteer matching
SQL1 = "SELECT p1.gid, p1.name, p1.name_long, p1.geonames_gid, p1.altnames FROM %s as p1 ;" % country_tbl
SQl2 = "SELECT p1.gid, p1.name, p1.name_long, p1.geonames_gid, p1.altnames FROM %s as p1 ;" % region_tbl
SQL3 = "SELECT p1.gid, p1.name, p1.geonames_gid, p1.altnames FROM %s as p1 ;" % state_tbl
SQL4 = "SELECT p1.gid, p1.name, p1.asciiname, p1.alternames FROM %s as p1 where p1.featurecode = 'PPLC' or p1.featurecode = 'PPLA' or p1.featurecode = 'PPLA2' or p1.featurecode = 'PPL';" % geonames_tbl
cur.execute(SQL1)
cntry_alt = {}
for row in cur.fetchall():
alist = [row[1], row[2]]
if row[4] is not None:
alist.extend(row[4].split(','))
#print alist
for w in alist:
cntry_alt.setdefault(w, set()).add(row[0])
#cntry_alt.setdefault(row[0], list()).append(alist)
cur.execute(SQL3)
state_alt = {}
for row in cur.fetchall():
alist = [row[1], row[2]]
if row[3] is not None:
alist.extend(row[3].split(','))
#print alist
for w in alist:
state_alt.setdefault(w, set()).add(row[0])
#state_alt.setdefault(row[0], list()).append(alist)
cur.execute(SQL2)
region_alt = {}
for row in cur.fetchall():
alist = [row[1], row[2]]
#print row
if len(row) > 3 and row[4] is not None:
alist.extend(row[4].split(','))
#print alist
for w in alist:
region_alt.setdefault(w, set()).add(row[0])
#region_alt.setdefault(row[0], list()).append(alist)
cur.execute(SQL4)
pplc_alt = {}
for row in cur.fetchall():
alist = [row[1], row[2]]
#print row
if len(row) > 3 and row[3] is not None:
alist.extend(row[3].split(','))
for w in alist:
pplc_alt.setdefault(w, set()).add(row[0])
print "Done Creating Alt Names"
print "Length of PPL AltNames: ", len(pplc_alt)
#Import script that issues commands to Stanford NER
import NERTest as NER
predictions = []
#Loop through every plaintext file in directory
for plaintext in files:
m += 1
print plaintext
filename = os.path.join(test_xml, plaintext)
outxml = "ner_" + plaintext
#Catch errors from the Stanford NER. Doesn't always succeed in parsing files.
try:
#NER.calc(stan_path, filename, outxml)
NER.calc2(stan_path, filename, outxml)
toporef, wordref = NER.readnerxml(outxml)
os.remove(outxml)
except:
print "Problem using the Stanford Parser for this file, skipping"
print plaintext
toporef = {}
wordref = {}
print "Files left to go: ", len(files) - m
print "Total Toponyms ", total_topo
#Vector Sum Function (Performs actual Disambiguation)
#wordref = other words dictionary with key = token index : value = word (at this point)
#toporef = toponym dictionary with key = token index : value = word (at this point)
#total_topo = total number of toponyms currently georeferenced
predictions, total_topo = VectorSum(wordref, toporef, total_topo, cur, lat_long_lookup,
percentile, window, stopwords, main_topo_weight, other_topo_weight, other_word_weight, plaintext, predictions, country_tbl, region_tbl, state_tbl,
geonames_tbl, cntry_alt, region_alt, state_alt, pplc_alt, in_domain_stat_tbl, in_corp_lamb, out_corp_lamb)
with io.open(results_file+plaintext, 'w', encoding='utf-8') as w:
w.write(u"NER_Toponym,Source_File,Token_index,GeoRefSource,Table,gid,Table_Toponym,Centroid_Lat,Centroid_Long\r\n")
for p in predictions:
#The encoding of the toponym can change based on the document being read
if isinstance(p[0], str):
toponym = p[0].decode('utf-8')
if isinstance(p[0], unicode):
toponym = p[0].encode('utf-8').decode('utf-8')
#The encoding of the toponym name from the table can change based on the table results were pulled from
if isinstance(p[6], str):
table_toponym = p[6].decode('utf-8')
if isinstance(p[6], unicode):
table_toponym = p[6].encode('utf-8').decode('utf-8')
w.write(toponym+u','+p[1]+u','+unicode(p[2])+u','+p[3]+u','+p[4]+u','+unicode(p[5])+u','+table_toponym+u','+unicode(p[7])+u','+unicode(p[8])+'\r\n')
'''print "=============Vector Sum================"
print "Total Toponyms: ", total_topo
print "Window: ", window
print "Percentile: ", percentile
print "Main Topo weight:", main_topo_weight
print "Other Topo weight:", other_topo_weight
print "Other word weight:", other_word_weight
#Write all toponym resolution results to results file
with io.open(results_file, 'w', encoding='utf-8') as w:
w.write(u"=============TopoCluster Run Settings================" + '\r\n')
w.write(u"In Domain Local Statistics Table Name: " + unicode(in_domain_stat_tbl) + '\r\n')
w.write(u"Out of domain Local Statistics Table Name: " + unicode(out_domain_stat_tbl) + '\r\n')
w.write(u"Test XML directory/file path: " + test_xml + '\r\n')
w.write(u"In Domain Corp Lambda: " + unicode(in_corp_lamb) + '\r\n')
w.write(u"Out Domain Corp Lambda: " + unicode(out_corp_lamb) + '\r\n')
w.write(u"Window: " + unicode(window) + '\r\n')
w.write(u"Total Toponyms: " + str(total_topo) + '\r\n')
w.write(u"Main Topo Weight:"+ unicode(main_topo_weight) + '\r\n')
w.write(u"Other Topo Weight:"+ unicode(other_topo_weight) + '\r\n')
w.write(u"Other Word Weight:"+ unicode(other_word_weight) + '\r\n')
w.write(u"=====================================================" + '\r\n')
w.write(u"NER_Toponym,Source_File,Token_index,GeoRefSource,Table,gid,Table_Toponym,Centroid_Lat,Centroid_Long\r\n")
for p in predictions:
#The encoding of the toponym can change based on the document being read
if isinstance(p[0], str):
toponym = p[0].decode('utf-8')
if isinstance(p[0], unicode):
toponym = p[0].encode('utf-8').decode('utf-8')
#The encoding of the toponym name from the table can change based on the table results were pulled from
if isinstance(p[6], str):
table_toponym = p[6].decode('utf-8')
if isinstance(p[6], unicode):
table_toponym = p[6].encode('utf-8').decode('utf-8')
w.write(toponym+u','+p[1]+u','+unicode(p[2])+u','+p[3]+u','+p[4]+u','+unicode(p[5])+u','+table_toponym+u','+unicode(p[7])+u','+unicode(p[8])+'\r\n')'''
conn.close()
end_time = datetime.datetime.now()
print total_topo
print "Check File @ ", results_file+plaintext
print "Total Time: ", end_time - start_time
