update graph generating scripts

import numpy as np

import matplotlib.pyplot as plt

import time

plt.switch_backend('agg')

TODO = {

  ('tox21', 'random'): ['weave', 'graphconv', 'tf', 'tf_robust', 'irv', 'xgb', 'logreg', 'textcnn'],

  ('sampl', 'random'): ['weave_regression', 'graphconvreg', 'tf_regression', 'xgb_regression', 'krr', 'textcnn_regression', 'dag_regression', 'mpnn'],

  ('lipo', 'random'): ['weave_regression', 'graphconvreg', 'tf_regression', 'xgb_regression', 'krr', 'textcnn_regression', 'dag_regression', 'mpnn'],

  ('qm7', 'stratified'): ['dtnn', 'graphconvreg', 'tf_regression_ft', 'krr_ft'],

  ('qm7b', 'random'): ['dtnn', 'tf_regression_ft', 'krr_ft'],

  ('qm8', 'random'): ['dtnn', 'graphconvreg', 'weave_regression', 'textcnn_regression', 'mpnn', 'tf_regression', 'tf_regression_ft'],

}

    ax.set_xlabel('ROC-AUC')

    ax.set_xlim(left=0.4, right=1.)

  t = time.localtime(time.time())

  ax.set_title("Performance on %s (%s split), %i-%i-%i" % (dataset, split, t.tm_year, t.tm_mon, t.tm_mday))

  plt.tight_layout()

  for i in range(len(colors)):

    ax.get_children()[i].set_color(colors[i])

    ax.text(values[i]-0.1, y_pos[i]+0.1, str("%.3f" % values[i]), color='white')

  current_dir = os.path.dirname(os.path.realpath(__file__))

  DEEPCHEM_DIR = os.path.split(os.path.split(current_dir)[0])[0]

  FILE = os.path.join(os.path.join(DEEPCHEM_DIR, 'examples'), 'results.csv')

  run_benchmark(FILE, DEEPCHEM_DIR)

  #run_benchmark(FILE, DEEPCHEM_DIR)

  save_dir = os.path.join(DEEPCHEM_DIR, 'datasets/MolNet_pic')

  if not os.path.exists(save_dir):

    os.mkdir(save_dir)

  for pair in TODO.keys():

    plot(pair[0], pair[1], FILE, os.environ['DEEPCHEM_DATA_DIR'])

    plot(pair[0], pair[1], FILE, save_dir)

  os.system('aws s3 sync '+save_dir+' s3://deepchem.io/trained_models/MolNet_pic')