old_contents: import pickle
  import numpy as np
  import milk.supervised._svm
  from gzip import GzipFile
  from os import path
  
  def test_svm_crash():
      X,Y,kernel, C, eps ,tol, = pickle.load(GzipFile(path.dirname(__file__) + '/data/regression-2-Dec-2009.pp.gz'))
      X = X[2:-2,:].copy()
      Y = Y[2:-2].copy()
      N = len(Y)
      Y = Y.astype(np.int32)
      p = -np.ones(N,np.double)
      params = np.array([0,C,eps,tol],np.double)
      Alphas0 = np.zeros(N, np.double)
      cache_size = (1<<20)
      # The line below crashed milk:
      milk.supervised._svm.eval_LIBSVM(X,Y,Alphas0,p,params,kernel,cache_size)
      # HASN'T CRASHED!
  
new_contents: import pickle
  import numpy as np
  import milk.supervised._svm
  from gzip import GzipFile
  from os import path
  
  def test_svm_crash():
      X,Y,kernel, C, eps ,tol, = pickle.load(GzipFile(path.dirname(__file__) + '/data/regression-2-Dec-2009.pp.gz'))
      X = X[2:-2,:].copy()
      Y = Y[2:-2].copy()
      N = len(Y)
      Y = Y.astype(np.int32)
      p = -np.ones(N,np.double)
      params = np.array([0,C,eps,tol],np.double)
      Alphas0 = np.zeros(N, np.double)
      cache_size = (1<<20)
      # The line below crashed milk:
      milk.supervised._svm.eval_LIBSVM(X,Y,Alphas0,p,params,kernel,cache_size)
      # HASN'T CRASHED!
  
  
  def test_nov2010():
      # Bug submitted by Mao Ziyang
      # This was failing in 0.3.5 because SDA selected no features
      np.random.seed(222)
      features = np.random.randn(100,20)
      features[:50] *= 2
      labels = np.repeat((0,1), 50)
  
      classifier = milk.defaultclassifier()
      model = classifier.train(features, labels)
      new_label = model.apply(np.random.randn(20)*2)
      new_label2 = model.apply(np.random.randn(20))
      assert new_label == 0
      assert new_label2 == 1
  
subject: Test a simple example