changed tmp dir to data/tmp instead of assuming /tmp (which is now co…

…mpatible for windows)

code/evaluate.py

@@ -88,7 +88,9 @@ def main():
 
 
     # create temporary directory for these files
-    tempdir_name = '/tmp/cliner_eval_%d' % random.randint(0,256)
+    cliner_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+    tmp_dir = os.path.join(cliner_dir, 'data', 'tmp')
+    tempdir_name = os.path.join(tmp_dir, 'cliner_eval_%d' % random.randint(0,256))
     #print tempdir_name
 
     #text_dir = os.path.join(tempdir_name, 'text/')

code/feature_extraction/genia_dir/interface_genia.py

@@ -22,7 +22,8 @@
 from subprocess import Popen, PIPE
 from .genia_cache import GeniaCache
 
-tmp_dir = '/tmp'
+cliner_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))))
+tmp_dir = os.path.join(cliner_dir, 'data', 'tmp')
 
 def genia(geniatagger, data):
 

code/format.py

@@ -16,7 +16,8 @@
 
 import tempfile
 
-tmp_dir = '/tmp'
+cliner_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+tmp_dir = os.path.join(cliner_dir, 'data', 'tmp')
 
 def create_filename(odir, bfile, extension):
     fname = os.path.basename(bfile) + extension

code/machine_learning/crf.py

@@ -16,6 +16,9 @@
 from tools import compute_performance_stats
 from feature_extraction.read_config import enabled_modules
 
+cliner_dir = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+tmp_dir = os.path.join(cliner_dir, 'data', 'tmp')
+
 def format_features(rows, labels=None):
 
     retVal = []
@@ -125,7 +128,7 @@ def train(X, Y, val_X=None, val_Y=None, test_X=None, test_Y=None):
         trainer.append(xseq, yseq)
 
     # Train the model
-    os_handle,tmp_file = tempfile.mkstemp(dir='/tmp', suffix="crf_temp")
+    os_handle,tmp_file = tempfile.mkstemp(dir=tmp_dir, suffix="crf_temp")
     trainer.train(tmp_file)
 
     # Read the trained model into a string (so it can be pickled)
@@ -173,7 +176,7 @@ def predict(clf, X):
     feats = format_features(X)
 
     # Dump the model into a temp file
-    os_handle,tmp_file = tempfile.mkstemp(dir='/tmp', suffix="crf_temp")
+    os_handle,tmp_file = tempfile.mkstemp(dir=tmp_dir, suffix="crf_temp")
     with open(tmp_file, 'wb') as f:
         f.write(clf)
 

code/model.py

@@ -21,7 +21,8 @@
 from tools           import print_str, print_vec, print_files, write
 
 
-
+cliner_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+tmp_dir = os.path.join(cliner_dir, 'data', 'tmp')
 
 class ClinerModel:
 
@@ -431,7 +432,8 @@ def generic_train(p_or_n, train_sents, train_labels, use_lstm, val_sents=None, v
 
         print ("START TRAINING")    
 
-        parameters['conll_like_result_folder']='/tmp/cliner_eval_%d' % random.randint(0,256)+os.sep
+        eval_dir = os.path.join(tmo_dir, 'cliner_eval_%d' % random.randint(0,256)+os.sep)
+        parameters['conll_like_result_folder']=eval_dir)
 
 
         test_temp = os.path.join(parameters['conll_like_result_folder'], 'test/')

data/tmp/.gitignore

@@ -0,0 +1,2 @@
+*
+!.gitignore