Use new tvt dataset with option --tvt

2 files changed, 47 insertions, 18 deletions

diff --git a/data/__init__.py b/data/__init__.py
index 2121033..9d01d2a 100644
--- a/data/__init__.py
+++ b/data/__init__.py
@@ -1,4 +1,5 @@
 import os
+import sys
 
 import h5py
 import numpy
@@ -8,23 +9,46 @@ path = os.environ.get('TAXI_PATH', '/data/lisatmp3/auvolat/taxikaggle')
 
 Polyline = h5py.special_dtype(vlen=numpy.float32)
 
-# `wc -l test.csv` - 1 # Minus 1 to ignore the header
-test_size = 320 
-
-# `wc -l train.csv` - 1
-train_size = 1710670 
-
 # `wc -l metaData_taxistandsID_name_GPSlocation.csv`
 stands_size = 64 # include 0 ("no origin_stands")
 
 # `cut -d, -f 5 train.csv test.csv | sort -u | wc -l` - 1
 taxi_id_size = 448 
 
-# `cut -d, -f 3 train.csv test.csv | sort -u | wc -l` - 2
-origin_call_size = 57125 # include 0 ("no origin_call")
-
-# As printed by csv_to_hdf5.py
-origin_call_train_size = 57106
-
 train_gps_mean = numpy.array([41.1573, -8.61612], dtype=numpy.float32)
 train_gps_std = numpy.sqrt(numpy.array([0.00549598, 0.00333233], dtype=numpy.float32))
+
+tvt = '--tvt' in sys.argv
+
+if tvt:
+    test_size = 19770
+    valid_size = 19427
+    train_size = 1671473
+
+    origin_call_size = 57106
+    origin_call_train_size = 57106
+
+    valid_set = 'valid'
+    valid_ds = 'tvt.hdf5'
+    traintest_ds = 'tvt.hdf5'
+
+else:
+    # `wc -l test.csv` - 1 # Minus 1 to ignore the header
+    test_size = 320 
+
+    # `wc -l train.csv` - 1
+    train_size = 1710670 
+
+    # `cut -d, -f 3 train.csv test.csv | sort -u | wc -l` - 2
+    origin_call_size = 57125 # include 0 ("no origin_call")
+
+    # As printed by csv_to_hdf5.py
+    origin_call_train_size = 57106
+
+    if '--largevalid' in sys.argv:
+        valid_set = 'cuts/large_valid'
+    else:
+        valid_set = 'cuts/test_times_0'
+
+    valid_ds = 'valid.hdf5'
+    traintest_ds = 'data.hdf5'
diff --git a/data/transformers.py b/data/transformers.py
index c2eb97e..b3a8486 100644
--- a/data/transformers.py
+++ b/data/transformers.py
@@ -70,7 +70,9 @@ class TaxiGenerateSplits(Transformer):
     def __init__(self, data_stream, max_splits=-1):
         super(TaxiGenerateSplits, self).__init__(data_stream)
 
-        self.sources = data_stream.sources + ('destination_latitude', 'destination_longitude', 'travel_time')
+        self.sources = data_stream.sources 
+        if not data.tvt:
+            self.sources += ('destination_latitude', 'destination_longitude', 'travel_time')
         self.max_splits = max_splits
         self.data = None
         self.splits = []
@@ -100,12 +102,15 @@ class TaxiGenerateSplits(Transformer):
         r[self.id_latitude] = numpy.array(r[self.id_latitude][:n], dtype=theano.config.floatX)
         r[self.id_longitude] = numpy.array(r[self.id_longitude][:n], dtype=theano.config.floatX)
 
-        dlat = numpy.float32(self.data[self.id_latitude][-1])
-        dlon = numpy.float32(self.data[self.id_longitude][-1])
-        ttime = numpy.int32(15 * (len(self.data[self.id_longitude]) - 1))
-
-        return tuple(r + [dlat, dlon, ttime])
+        r = tuple(r)
 
+        if data.tvt:
+            return r
+        else:
+            dlat = numpy.float32(self.data[self.id_latitude][-1])
+            dlon = numpy.float32(self.data[self.id_longitude][-1])
+            ttime = numpy.int32(15 * (len(self.data[self.id_longitude]) - 1))
+            return r + (dlat, dlon, ttime)
 
 class _taxi_add_first_last_len_helper(object):
     def __init__(self, k, id_latitude, id_longitude):