fixing and adding tests

from __future__ import division

from __future__ import unicode_literals

__author__ = "Bharath Ramsundar"

__author__ = "Bharath Ramsundar, Aneesh Pappu"

__copyright__ = "Copyright 2016, Stanford University"

__license__ = "GPL"

  Class for doing stratified splits -- where data is too sparse to do regular splits

  """

  def __randomizeArrays(self, array_list):

  def __randomize_arrays(self, array_list):

    generator_state = np.random.get_state()

    for array in array_list:

      np.random.shuffle(array)

   # Obtain original x, y, and w arrays

    numpyArrayList = dataset.to_numpy();

    numpyArrayList = self.__randomizeArrays(numpyArrayList)

    numpyArrayList = self.__randomize_arrays(numpyArrayList)

    X = numpyArrayList[0]

    y = numpyArrayList[1]

    w = numpyArrayList[2]

from deepchem.splits import ScaffoldSplitter

from deepchem.splits import StratifiedSplitter

from deepchem.datasets.tests import TestDatasetAPI

from deepchem.datasets import Dataset

import pandas as pd

class TestSplitters(TestDatasetAPI):

  """

          self.train_dir, self.valid_dir, self.test_dir,

          frac_train = 0.8, frac_valid = 0.1, frac_test = 0.1

      )

   train_np_list = train_data.to_numpy()

   y = train_data[1]

   #verify that each task in the train dataset has some hits

   y_df = pd.DataFrame(data = y)

   totalRows = len(y_df.index)

   for col in y_df:

       column = y_df[col]

       NaN_count = column.isnull().sum()

       numRows = len(colum)

       if NaN_count == totalRows:

           assert NaN_count != totalRows

   print("end of stratified test")

   assert 1 == 1