--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/data_generation/pipeline/visualize_filtered.py	Wed Mar 16 13:43:32 2011 -0400
@@ -0,0 +1,43 @@
+import numpy
+import pylab
+from pylearn.io import filetensor as ft
+from ift6266 import datasets
+from ift6266.datasets.ftfile import FTDataSet
+
+import time
+import matplotlib.cm as cm
+
+
+dataset_str = 'P07safe_' #'PNIST07_' # NISTP
+
+base_path = '/data/lisatmp/ift6266h10/data/'+dataset_str
+base_output_path = '/data/lisatmp/ift6266h10/data/transformed_digits/'+dataset_str+'train'
+
+fileno = 15
+
+output_data_file = base_output_path+str(fileno)+'_data.ft'
+output_labels_file = base_output_path+str(fileno)+'_labels.ft'
+
+dataset_obj = lambda maxsize=None, min_file=0, max_file=100: \
+                FTDataSet(train_data = [output_data_file],
+                   train_lbl = [output_labels_file],
+                   test_data = [base_path+'_test_data.ft'],
+                   test_lbl = [base_path+'_test_labels.ft'],
+                   valid_data = [base_path+'_valid_data.ft'],
+                   valid_lbl = [base_path+'_valid_labels.ft'])
+                   # no conversion or scaling... keep data as is
+                   #indtype=theano.config.floatX, inscale=255., maxsize=maxsize)
+
+dataset = dataset_obj()
+train_ds = dataset.train(1)
+
+for i in range(2983):
+    if i < 2900:
+        continue
+    ex = train_ds.next()
+    pylab.ion()
+    pylab.clf()
+    pylab.imshow(ex[0].reshape(32,32),cmap=cm.gray)
+    pylab.draw()
+    time.sleep(0.5)
+