[Scipy-svn] r5500 - trunk/scipy/fftpack/tests
scipy-svn at scipy.org
scipy-svn at scipy.org
Mon Jan 19 03:33:26 EST 2009
Author: cdavid
Date: 2009-01-19 02:33:22 -0600 (Mon, 19 Jan 2009)
New Revision: 5500
Modified:
trunk/scipy/fftpack/tests/test_real_transforms.py
Log:
Adapt DCT tests to new API.
Modified: trunk/scipy/fftpack/tests/test_real_transforms.py
===================================================================
--- trunk/scipy/fftpack/tests/test_real_transforms.py 2009-01-19 08:33:05 UTC (rev 5499)
+++ trunk/scipy/fftpack/tests/test_real_transforms.py 2009-01-19 08:33:22 UTC (rev 5500)
@@ -5,7 +5,7 @@
from numpy.fft import fft as numfft
from numpy.testing import assert_array_almost_equal, TestCase
-from scipy.fftpack.realtransforms import dct1, dct2, dct3
+from scipy.fftpack.realtransforms import dct, idct
# Matlab reference data
MDATA = np.load(join(dirname(__file__), 'test.npz'))
@@ -21,8 +21,6 @@
FFTWDATA_SINGLE = np.load(join(dirname(__file__), 'fftw_single_ref.npz'))
FFTWDATA_SIZES = FFTWDATA_DOUBLE['sizes']
-TYPE2DCT = {1: dct1, 2: dct2, 3: dct3}
-
def fftw_ref(type, size, dt):
x = np.linspace(0, size-1, size).astype(dt)
if dt == np.double:
@@ -39,12 +37,11 @@
self.rdt = None
self.dec = 14
self.type = None
- self.func = None
def test_definition(self):
for i in FFTWDATA_SIZES:
x, yr = fftw_ref(self.type, i, self.rdt)
- y = self.func(x)
+ y = dct(x, type=self.type)
self.failUnless(y.dtype == self.rdt,
"Output dtype is %s, expected %s" % (y.dtype, self.rdt))
# XXX: we divide by np.max(y) because the tests fail otherwise. We
@@ -58,14 +55,16 @@
nt = 2
for i in [7, 8, 9, 16, 32, 64]:
x = np.random.randn(nt, i)
- y = self.func(x)
+ y = dct(x, type=self.type)
for j in range(nt):
- assert_array_almost_equal(y[j], self.func(x[j]), decimal=self.dec)
+ assert_array_almost_equal(y[j], dct(x[j], type=self.type),
+ decimal=self.dec)
x = x.T
- y = self.func(x, axis=0)
+ y = dct(x, axis=0, type=self.type)
for j in range(nt):
- assert_array_almost_equal(y[:,j], self.func(x[:,j]), decimal=self.dec)
+ assert_array_almost_equal(y[:,j], dct(x[:,j], type=self.type),
+ decimal=self.dec)
class _TestDCTIIBase(_TestDCTBase):
def test_definition_matlab(self):
@@ -73,7 +72,7 @@
for i in range(len(X)):
x = np.array(X[i], dtype=self.rdt)
yr = Y[i]
- y = dct2(x, norm="ortho")
+ y = dct(x, norm="ortho", type=2)
self.failUnless(y.dtype == self.rdt,
"Output dtype is %s, expected %s" % (y.dtype, self.rdt))
assert_array_almost_equal(y, yr, decimal=self.dec)
@@ -83,8 +82,8 @@
"""Test orthornomal mode."""
for i in range(len(X)):
x = np.array(X[i], dtype=self.rdt)
- y = dct2(x, norm='ortho')
- xi = dct3(y, norm="ortho")
+ y = dct(x, norm='ortho', type=2)
+ xi = dct(y, norm="ortho", type=3)
self.failUnless(xi.dtype == self.rdt,
"Output dtype is %s, expected %s" % (xi.dtype, self.rdt))
assert_array_almost_equal(xi, x, decimal=self.dec)
@@ -94,42 +93,96 @@
self.rdt = np.double
self.dec = 10
self.type = 1
- self.func = TYPE2DCT[self.type]
class TestDCTIFloat(_TestDCTBase):
def setUp(self):
self.rdt = np.float32
self.dec = 5
self.type = 1
- self.func = TYPE2DCT[self.type]
class TestDCTIIDouble(_TestDCTIIBase):
def setUp(self):
self.rdt = np.double
self.dec = 10
self.type = 2
- self.func = TYPE2DCT[self.type]
class TestDCTIIFloat(_TestDCTIIBase):
def setUp(self):
self.rdt = np.float32
self.dec = 5
self.type = 2
- self.func = TYPE2DCT[self.type]
class TestDCTIIIDouble(_TestDCTIIIBase):
def setUp(self):
self.rdt = np.double
self.dec = 14
self.type = 3
- self.func = TYPE2DCT[self.type]
class TestDCTIIIFloat(_TestDCTIIIBase):
def setUp(self):
self.rdt = np.float32
self.dec = 5
self.type = 3
- self.func = TYPE2DCT[self.type]
+class _TestIDCTBase(TestCase):
+ def setUp(self):
+ self.rdt = None
+ self.dec = 14
+ self.type = None
+
+ def test_definition(self):
+ for i in FFTWDATA_SIZES:
+ xr, yr = fftw_ref(self.type, i, self.rdt)
+ y = dct(xr, type=self.type)
+ x = idct(yr, type=self.type)
+ if self.type == 1:
+ x /= 2 * (i-1)
+ else:
+ x /= 2 * i
+ self.failUnless(x.dtype == self.rdt,
+ "Output dtype is %s, expected %s" % (x.dtype, self.rdt))
+ # XXX: we divide by np.max(y) because the tests fail otherwise. We
+ # should really use something like assert_array_approx_equal. The
+ # difference is due to fftw using a better algorithm w.r.t error
+ # propagation compared to the ones from fftpack.
+ assert_array_almost_equal(x / np.max(x), xr / np.max(x), decimal=self.dec,
+ err_msg="Size %d failed" % i)
+
+class TestIDCTIDouble(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.double
+ self.dec = 10
+ self.type = 1
+
+class TestIDCTIFloat(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.float32
+ self.dec = 4
+ self.type = 1
+
+class TestIDCTIIDouble(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.double
+ self.dec = 10
+ self.type = 2
+
+class TestIDCTIIFloat(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.float32
+ self.dec = 5
+ self.type = 2
+
+class TestIDCTIIIDouble(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.double
+ self.dec = 14
+ self.type = 3
+
+class TestIDCTIIIFloat(_TestIDCTBase):
+ def setUp(self):
+ self.rdt = np.float32
+ self.dec = 5
+ self.type = 3
+
if __name__ == "__main__":
np.testing.run_module_suite()
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