add aligned lemmatized tm

tests/addAlignedLemmatizedTM.py

@@ -0,0 +1,104 @@
+#!/usr/bin/python
+# -*- coding: utf-8 -*-
+
+import unittest
+import json
+import urllib2
+import sys
+import host
+import time
+
+BUFFER_SIZE = 500
+
+address = 'http://'+host.concordia_host
+if len(host.concordia_port) > 0:
+    address += ':'+host.concordia_port
+
+
+def file_len(fname):
+    with open(fname) as f:
+        for i, l in enumerate(f):
+            pass
+    return i + 1
+
+def add_data(data):
+    req = urllib2.Request(address)
+    req.add_header('Content-Type', 'application/json')
+    json.loads(urllib2.urlopen(req, json.dumps(data)).read())
+
+name = sys.argv[1]
+sourceFile = sys.argv[2]
+sourceLangId = int(sys.argv[3])
+targetFile = sys.argv[4]
+targetLangId = int(sys.argv[5])
+alignmentsFile = sys.argv[6]
+
+if (file_len(sourceFile) != file_len(targetFile)):
+    raise Exception("source and target files are not of the same length!")
+
+if (file_len(alignmentsFile) != 3*file_len(sourceFile)):
+    raise Exception("alignments file is not exactly 3 times longer than source and target")
+
+
+totalLines = file_len(sourceFile)
+
+data = {
+    'operation': 'addTm',
+    'sourceLangId':sourceLangId,
+    'targetLangId':targetLangId,
+    'name':name
+}
+
+req = urllib2.Request(address)
+req.add_header('Content-Type', 'application/json')
+response = json.loads(urllib2.urlopen(req, json.dumps(data)).read())
+tmId = int(response['newTmId'])
+print "Added new tm: %d" % tmId
+
+data = {
+    'operation': 'addAlignedLemmatizedSentences',
+    'tmId':tmId
+}
+
+sentences = []
+start = time.time()
+with open(sourceFile) as sourceLines, open(targetFile) as targetLines, open(alignmentsFile) as alignmentsLines:
+
+    lineNumber = 0
+    for line in sourceLines:
+        line = line.strip()
+        if lineNumber % 3 == 1:
+            currSentence.append(line)
+        elif lineNumber % 3 == 2:
+            currSentence.append(line)
+            currSentence.reverse()
+            sentences.append(currSentence)
+            currSentence = []
+            if len(sentences) >= BUFFER_SIZE:
+                data['sentences'] = sentences
+                add_data(data)
+                mark = time.time()
+                print "Added %d of %d sentences. Time elapsed: %.4f s, current speed: %.4f sentences/second" % ( (lineNumber+1)/3, totalLines/3, mark-start, (lineNumber+1)/(3*(mark-start)))
+                sentences = []
+        lineNumber += 1
+
+
+if len(sentences) > 0:
+    data['sentences'] = sentences
+    add_data(data)
+
+end = time.time()
+print "Added all %d sentences. Time elapsed: %.4f s, overall speed: %.4f sentences/second" % ((lineNumber+1)/3, end-start, (lineNumber+1)/(3*(end-start)))
+
+print "Generating index..."
+start = time.time()
+data = {
+    'operation': 'refreshIndex',
+    'tmId' : tmId
+}
+req = urllib2.Request(address)
+req.add_header('Content-Type', 'application/json')
+urllib2.urlopen(req, json.dumps(data)).read()
+
+end = time.time()
+print "Index regeneration complete. The operation took %.4f s" % (end - start)