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changeset 282:b55c829695f1

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renamed test_filetensor.py to _test_filetensor.py to have it being executed by autotest
author Frederic Bastien <bastienf@iro.umontreal.ca>
date Fri, 06 Jun 2008 13:46:10 -0400
parents 29f394813c3c
children 275b92d40ea6
files _test_filetensor.py test_filetensor.py
diffstat 2 files changed, 116 insertions(+), 116 deletions(-) [+]
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/_test_filetensor.py	Fri Jun 06 13:46:10 2008 -0400
@@ -0,0 +1,116 @@
+from filetensor import *
+import filetensor
+
+import unittest
+import os
+
+class T(unittest.TestCase):
+    fname = '/tmp/some_mat'
+
+    def setUp(self):
+        #TODO: test that /tmp/some_mat does not exist
+        try:
+            os.stat(self.fname)
+        except OSError:
+            return #assume file was not found
+        raise Exception('autotest file "%s" exists!' % self.fname)
+
+    def tearDown(self):
+        os.remove(self.fname)
+
+    def test_file(self):
+        gen = numpy.random.rand(1)
+        f = file(self.fname, 'w');
+        write(f, gen)
+        f.flush()
+        f = file(self.fname, 'r');
+        mat = read(f, None, debug=False) #load from filename
+        self.failUnless(gen.shape == mat.shape)
+        self.failUnless(numpy.all(gen == mat))
+
+    def test_filename(self):
+        gen = numpy.random.rand(1)
+        write(self.fname, gen)
+        mat = read(self.fname, None, debug=False) #load from filename
+        self.failUnless(gen.shape == mat.shape)
+        self.failUnless(numpy.all(gen == mat))
+
+    def testNd(self):
+        """shape and values are stored correctly for tensors of rank 0 to 5"""
+        whole_shape = [5, 6, 7, 8, 9]
+        for i in xrange(5):
+            gen = numpy.asarray(numpy.random.rand(*whole_shape[:i]))
+            f = file(self.fname, 'w');
+            write(f, gen)
+            f.flush()
+            f = file(self.fname, 'r');
+            mat = read(f, None, debug=False) #load from filename
+            self.failUnless(gen.shape == mat.shape)
+            self.failUnless(numpy.all(gen == mat))
+
+    def test_dtypes(self):
+        """shape and values are stored correctly for all dtypes """
+        for dtype in filetensor._dtype_magic:
+            gen = numpy.asarray(
+                    numpy.random.rand(4, 5, 2, 1) * 100,
+                    dtype=dtype)
+            f = file(self.fname, 'w');
+            write(f, gen)
+            f.flush()
+            f = file(self.fname, 'r');
+            mat = read(f, None, debug=False) #load from filename
+            self.failUnless(gen.dtype == mat.dtype)
+            self.failUnless(gen.shape == mat.shape)
+            self.failUnless(numpy.all(gen == mat))
+
+    def test_dtype_invalid(self):
+        gen = numpy.zeros((3,4), dtype='uint16') #an unsupported dtype
+        f = file(self.fname, 'w')
+        passed = False
+        try:
+            write(f, gen)
+        except TypeError, e:
+            if e[0].startswith('Invalid ndarray dtype'):
+                passed = True
+        f.close()
+        self.failUnless(passed)
+        
+
+if __name__ == '__main__':
+    unittest.main()
+
+    #a small test script, starts by reading sys.argv[1]
+    #print 'rval', rval.shape, rval.size
+
+    if 0:
+        write(f, rval)
+        print ''
+        f.close()
+        f = file('/tmp/some_mat', 'r');
+        rval2 = read(f) #load from file handle
+        print 'rval2', rval2.shape, rval2.size
+
+        assert rval.dtype == rval2.dtype
+        assert rval.shape == rval2.shape
+        assert numpy.all(rval == rval2)
+        print 'ok'
+
+    def _unused():
+        f.seek(0,2) #seek to end
+        f_len =  f.tell()
+        f.seek(f_data_start,0) #seek back to where we were
+
+        if debug: print 'length:', f_len
+
+
+        f_data_bytes = (f_len - f_data_start)
+
+        if debug: print 'data bytes according to header: ', dim_size * elsize
+        if debug: print 'data bytes according to file  : ', f_data_bytes
+
+        if debug: print 'reading data...'
+        sys.stdout.flush()
+
+    def read_ndarray(f, dim, dtype):
+        return numpy.fromfile(f, dtype=dtype, count=_prod(dim)).reshape(dim)
+
--- a/test_filetensor.py	Fri Jun 06 13:44:17 2008 -0400
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,116 +0,0 @@
-from filetensor import *
-import filetensor
-
-import unittest
-import os
-
-class T(unittest.TestCase):
-    fname = '/tmp/some_mat'
-
-    def setUp(self):
-        #TODO: test that /tmp/some_mat does not exist
-        try:
-            os.stat(self.fname)
-        except OSError:
-            return #assume file was not found
-        raise Exception('autotest file "%s" exists!' % self.fname)
-
-    def tearDown(self):
-        os.remove(self.fname)
-
-    def test_file(self):
-        gen = numpy.random.rand(1)
-        f = file(self.fname, 'w');
-        write(f, gen)
-        f.flush()
-        f = file(self.fname, 'r');
-        mat = read(f, None, debug=False) #load from filename
-        self.failUnless(gen.shape == mat.shape)
-        self.failUnless(numpy.all(gen == mat))
-
-    def test_filename(self):
-        gen = numpy.random.rand(1)
-        write(self.fname, gen)
-        mat = read(self.fname, None, debug=False) #load from filename
-        self.failUnless(gen.shape == mat.shape)
-        self.failUnless(numpy.all(gen == mat))
-
-    def testNd(self):
-        """shape and values are stored correctly for tensors of rank 0 to 5"""
-        whole_shape = [5, 6, 7, 8, 9]
-        for i in xrange(5):
-            gen = numpy.asarray(numpy.random.rand(*whole_shape[:i]))
-            f = file(self.fname, 'w');
-            write(f, gen)
-            f.flush()
-            f = file(self.fname, 'r');
-            mat = read(f, None, debug=False) #load from filename
-            self.failUnless(gen.shape == mat.shape)
-            self.failUnless(numpy.all(gen == mat))
-
-    def test_dtypes(self):
-        """shape and values are stored correctly for all dtypes """
-        for dtype in filetensor._dtype_magic:
-            gen = numpy.asarray(
-                    numpy.random.rand(4, 5, 2, 1) * 100,
-                    dtype=dtype)
-            f = file(self.fname, 'w');
-            write(f, gen)
-            f.flush()
-            f = file(self.fname, 'r');
-            mat = read(f, None, debug=False) #load from filename
-            self.failUnless(gen.dtype == mat.dtype)
-            self.failUnless(gen.shape == mat.shape)
-            self.failUnless(numpy.all(gen == mat))
-
-    def test_dtype_invalid(self):
-        gen = numpy.zeros((3,4), dtype='uint16') #an unsupported dtype
-        f = file(self.fname, 'w')
-        passed = False
-        try:
-            write(f, gen)
-        except TypeError, e:
-            if e[0].startswith('Invalid ndarray dtype'):
-                passed = True
-        f.close()
-        self.failUnless(passed)
-        
-
-if __name__ == '__main__':
-    unittest.main()
-
-    #a small test script, starts by reading sys.argv[1]
-    #print 'rval', rval.shape, rval.size
-
-    if 0:
-        write(f, rval)
-        print ''
-        f.close()
-        f = file('/tmp/some_mat', 'r');
-        rval2 = read(f) #load from file handle
-        print 'rval2', rval2.shape, rval2.size
-
-        assert rval.dtype == rval2.dtype
-        assert rval.shape == rval2.shape
-        assert numpy.all(rval == rval2)
-        print 'ok'
-
-    def _unused():
-        f.seek(0,2) #seek to end
-        f_len =  f.tell()
-        f.seek(f_data_start,0) #seek back to where we were
-
-        if debug: print 'length:', f_len
-
-
-        f_data_bytes = (f_len - f_data_start)
-
-        if debug: print 'data bytes according to header: ', dim_size * elsize
-        if debug: print 'data bytes according to file  : ', f_data_bytes
-
-        if debug: print 'reading data...'
-        sys.stdout.flush()
-
-    def read_ndarray(f, dim, dtype):
-        return numpy.fromfile(f, dtype=dtype, count=_prod(dim)).reshape(dim)
-