Merge pull request #1516 from RishalAggarwal/master (bcbe3e12) · Commits · 钟慕尧 / deepchem

deepchem/trans/tests/test_transformers.py

+36 −0

Original line number	Diff line number	Diff line
		@@ -537,3 +537,39 @@ class TestTransformers(unittest.TestCase):
		scale = scipy.misc.imresize(self.d, (h, w))
		check_scale = dt.scale(h, w)
		np.allclose(scale, check_scale)

		def test_shift(self):
		# Check shift
		dt = DataTransforms(self.d)
		height = 5
		width = 5
		if len(self.d.shape) == 2:
		shift = scipy.ndimage.shift(self.d, [height, width])
		if len(self.d.shape) == 3:
		shift = scipy.ndimage.shift(self.d, [height, width, 0])
		check_shift = dt.shift(width, height)
		assert np.allclose(shift, check_shift)

		def test_gaussian_noise(self):
		# check gaussian noise
		dt = DataTransforms(self.d)
		np.random.seed(0)
		random_noise = self.d
		random_noise = random_noise + np.random.normal(
		loc=0, scale=25.5, size=self.d.shape)
		np.random.seed(0)
		check_random_noise = dt.gaussian_noise(mean=0, std=25.5)
		assert np.allclose(random_noise, check_random_noise)

		def test_salt_pepper_noise(self):
		# check salt and pepper noise
		dt = DataTransforms(self.d)
		np.random.seed(0)
		prob = 0.05
		random_noise = self.d
		noise = np.random.random(size=self.d.shape)
		random_noise[noise < (prob / 2)] = 0
		random_noise[noise > (1 - prob / 2)] = 255
		np.random.seed(0)
		check_random_noise = dt.salt_pepper_noise(prob, salt=255, pepper=0)
		assert np.allclose(random_noise, check_random_noise)

+41 −0

Original line number	Diff line number	Diff line
		@@ -1225,3 +1225,44 @@ class DataTransforms(Transformer):
		sigma - std dev. of the gaussian distribution
		"""
		return scipy.ndimage.gaussian_filter(self.Image, sigma)

		def shift(self, width, height, mode='constant', order=3):
		"""Shifts the image
		Parameters:
		width - amount of width shift(positive values shift image right )
		height - amount of height shift(positive values shift image lower)
		mode - Points outside the boundaries of the input are filled according to the given mode
		(‘constant’, ‘nearest’, ‘reflect’ or ‘wrap’). Default is ‘constant’
		order - The order of the spline interpolation, default is 3. The order has to be in the range 0-5.
		"""
		if len(self.Image.shape) == 2:
		return scipy.ndimage.shift(
		self.Image, [height, width], order=order, mode=mode)
		if len(self.Image.shape == 3):
		return scipy.ndimage.shift(
		self.Image, [height, width, 0], order=order, mode=mode)

		def gaussian_noise(self, mean=0, std=25.5):
		'''Adds gaussian noise to the image
		Parameters:
		mean - mean of gaussian.
		std - standard deviation of gaussian.
		'''

		x = self.Image
		x = x + np.random.normal(loc=mean, scale=std, size=self.Image.shape)
		return x

		def salt_pepper_noise(self, prob=0.05, salt=255, pepper=0):
		'''Adds salt and pepper noise to the image
		Parameters:
		prob - probability of the noise.
		salt - value of salt noise.
		pepper - value of pepper noise.
		'''

		noise = np.random.random(size=self.Image.shape)
		x = self.Image
		x[noise < (prob / 2)] = pepper
		x[noise > (1 - prob / 2)] = salt
		return x