Merge pull request #916 from lilleswing/singleton_csv

  valid_inds = np.array(

      [1 if elt.size > 0 else 0 for elt in features], dtype=bool)

  features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid]

  return np.squeeze(np.array(features)), valid_inds

  return np.squeeze(np.array(features), axis=1), valid_inds

def featurize_smiles_np(arr, featurizer, log_every_N=1000, verbose=True):

      [1 if elt.size > 0 else 0 for elt in features], dtype=bool)

  features = [elt for (is_valid, elt) in zip(valid_inds, features) if is_valid]

  features = np.squeeze(np.array(features))

  return features.reshape(

      -1,)

  return features.reshape(-1,)

def get_user_specified_features(df, featurizer, verbose=True):

import os

from unittest import TestCase

from io import StringIO

import tempfile

import shutil

import deepchem as dc

class TestCSVLoader(TestCase):

  def test_load_singleton_csv(self):

    fin = tempfile.NamedTemporaryFile(mode='w', delete=False)

    fin.write("smiles,endpoint\nc1ccccc1,1")

    fin.close()

    print(fin.name)

    featurizer = dc.feat.CircularFingerprint(size=1024)

    tasks = ["endpoint"]

    loader = dc.data.CSVLoader(

        tasks=tasks, smiles_field="smiles", featurizer=featurizer)

    X = loader.featurize(fin.name)

    self.assertEqual(1, len(X))

    os.remove(fin.name)