Mercurial > pylearn
changeset 669:d17ebf9ac8c0
moved test_filetensor to tests subdir
| author | James Bergstra <bergstrj@iro.umontreal.ca> |
|---|---|
| date | Mon, 30 Mar 2009 16:00:29 -0400 |
| parents | 15a317a02f08 |
| children | 63bcc7024378 |
| files | pylearn/io/_test_filetensor.py pylearn/io/tests/__init__.py pylearn/io/tests/test_filetensor.py |
| diffstat | 3 files changed, 121 insertions(+), 120 deletions(-) [+] |
line wrap: on
line diff
--- a/pylearn/io/_test_filetensor.py Mon Mar 30 15:44:42 2009 -0400 +++ /dev/null Thu Jan 01 00:00:00 1970 +0000 @@ -1,120 +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) - f = file(self.fname, 'w') - write(f, gen) - f.close() - f = file(self.fname, 'r') - mat = read(f, None, debug=False) #load from filename - f.close() - 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) -
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pylearn/io/tests/__init__.py Mon Mar 30 16:00:29 2009 -0400 @@ -0,0 +1,2 @@ + +
--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/pylearn/io/tests/test_filetensor.py Mon Mar 30 16:00:29 2009 -0400 @@ -0,0 +1,119 @@ +from pylearn.io 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'); + filetensor.write(f, gen) + f.flush() + f = file(self.fname, 'r'); + mat = filetensor.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) + f = file(self.fname, 'w') + filetensor.write(f, gen) + f.close() + f = file(self.fname, 'r') + mat = filetensor.read(f, None, debug=False) #load from filename + f.close() + 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'); + filetensor.write(f, gen) + f.flush() + f = file(self.fname, 'r'); + mat = filetensor.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'); + filetensor.write(f, gen) + f.flush() + f = file(self.fname, 'r'); + mat = filetensor.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: + filetensor.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: + filetensor.write(f, rval) + print '' + f.close() + f = file('/tmp/some_mat', 'r'); + rval2 = filetensor.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) +