def test_subset(self):
shape = (4, 3, 2)
a = [i for i in range(2*3*4)]
a = numpy.asarray(a)
a = numpy.reshape(a, shape)
ds = DataContainer(a, True, ['X', 'Y', 'Z'])
sub = ds.subset(['X'])
res = True
try:
numpy.testing.assert_array_equal(sub.as_array(),
numpy.asarray([0, 6, 12, 18]))
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
sub = ds.subset(['X'], Y=2, Z=0)
res = True
try:
numpy.testing.assert_array_equal(sub.as_array(),
numpy.asarray([4, 10, 16, 22]))
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
sub = ds.subset(['Y'])
try:
numpy.testing.assert_array_equal(
sub.as_array(), numpy.asarray([0, 2, 4]))
res = True
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
sub = ds.subset(['Z'])
try:
numpy.testing.assert_array_equal(
sub.as_array(), numpy.asarray([0, 1]))
res = True
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
sub = ds.subset(['Z'], X=1, Y=2)
try:
numpy.testing.assert_array_equal(
sub.as_array(), numpy.asarray([10, 11]))
res = True
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
print(a)
sub = ds.subset(['X', 'Y'], Z=1)
res = True
try:
numpy.testing.assert_array_equal(sub.as_array(),
numpy.asarray([[1, 3, 5],
[7, 9, 11],
[13, 15, 17],
[19, 21, 23]]))
except AssertionError as err:
res = False
print(err)
self.assertTrue(res)
def test_DataProcessorChaining(self):
shape = (2, 3, 4, 5)
size = shape[0]
for i in range(1, len(shape)):
size = size * shape[i]
#print("a refcount " , sys.getrefcount(a))
a = numpy.asarray([i for i in range(size)])
a = numpy.reshape(a, shape)
ds = DataContainer(a, False, ['X', 'Y', 'Z', 'W'])
c = ds.subset(['Z', 'W', 'X'])
arr = c.as_array()
#[ 0 60 1 61 2 62 3 63 4 64 5 65 6 66 7 67 8 68 9 69 10 70 11 71
# 12 72 13 73 14 74 15 75 16 76 17 77 18 78 19 79]
ax = AX()
ax.scalar = 2
ax.set_input(c)
#ax.apply()
print("ax in {0} out {1}".format(
c.as_array().flatten(),
ax.get_output().as_array().flatten()))
numpy.testing.assert_array_equal(ax.get_output().as_array(), arr * 2)
cast = CastDataContainer(dtype=numpy.float32)
cast.set_input(c)
out = cast.get_output()
self.assertTrue(out.as_array().dtype == numpy.float32)
out *= 0
axm = AX()
axm.scalar = 0.5
axm.set_input(c)
axm.get_output(out)
numpy.testing.assert_array_equal(out.as_array(), arr * 0.5)
# check out in DataSetProcessor
#a = numpy.asarray([i for i in range( size )])
# create a PixelByPixelDataProcessor
#define a python function which will take only one input (the pixel value)
pyfunc = lambda x: -x if x > 20 else x
clip = PixelByPixelDataProcessor()
clip.pyfunc = pyfunc
clip.set_input(c)
#clip.apply()
v = clip.get_output().as_array()
self.assertTrue(v.max() == 19)
self.assertTrue(v.min() == -79)
print("clip in {0} out {1}".format(c.as_array(),
clip.get_output().as_array()))
#dsp = DataProcessor()
#dsp.set_input(ds)
#dsp.input = a
# pipeline
chain = AX()
chain.scalar = 0.5
chain.set_input_processor(ax)
print("chain in {0} out {1}".format(ax.get_output().as_array(),
chain.get_output().as_array()))
numpy.testing.assert_array_equal(chain.get_output().as_array(), arr)