test for gaussian blur

from deepchem.molnet import load_delaney

from deepchem.trans.transformers import FeaturizationTransformer

from deepchem.trans.transformers import DataTransforms

from tensorflow.examples.tutorials.mnist import input_data

__author__ = "Bharath Ramsundar"

__copyright__ = "Copyright 2016, Stanford University"

import numpy as np

import pandas as pd

import deepchem as dc

import scipy.ndimage

class TestTransformers(unittest.TestCase):

  """

    self.assertEqual(new_train.y.shape, train.y.shape)

    self.assertEqual(new_train.X.shape[-1], fp_size)

  def test_data_transformers(self):

      mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

      # extracting validation set of MNIST for testing the DataTransforms

      valid = dc.data.NumpyDataset(mnist.validation.images, mnist.validation.labels)

      # extract only the images (no need of the labels)

      data = (valid.X)[0]

      # reshaping the vector to image

      data = np.reshape(data, (28, 28))

      dt = DataTransforms(data)

      blurred = dt.gaussian_blur(sigma=1.5)

      check = scipy.ndimage.gaussian_filter(data, 1.5)

      assert np,allclose(check, blurred)