The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.

Example 1

def test_order(self):
        """ Test that ipipe(f, g, h, arrays) -> f(g(h(arr))) for arr in arrays """
        stream = [np.random.random((15,7,2,1)) for _ in range(10)]
        squared = [np.cbrt(np.square(arr)) for arr in stream]
        pipeline = ipipe(np.cbrt, np.square, stream)

        self.assertTrue(all(np.allclose(s, p) for s, p in zip(pipeline, squared))) 

Example 2

def test_multiprocessing(self):
        """ Test that ipipe(f, g, h, arrays) -> f(g(h(arr))) for arr in arrays """
        stream = [np.random.random((15,7,2,1)) for _ in range(10)]
        squared = [np.cbrt(np.square(arr)) for arr in stream]
        pipeline = ipipe(np.cbrt, np.square, stream, processes = 2)

        self.assertTrue(all(np.allclose(s, p) for s, p in zip(pipeline, squared))) 

Example 3

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 4

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 5

def make_data(num):
    """
    Make data allocates num samples with input dimension
    3 and output dimension of 1.
    """
    inputs = np.random.normal(size=[3, num])
    targets = np.cbrt(np.square(2.5*inputs[0:1, :]) -
                      inputs[1:2, :] * inputs[2:3, :])
    return inputs, targets 

Example 6

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 7

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 8

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 9

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 10

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 11

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 12

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 13

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 14

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 15

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 16

def test_cbrt_scalar(self):
        assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) 

Example 17

def test_cbrt(self):
        x = np.array([1., 2., -3., np.inf, -np.inf])
        assert_almost_equal(np.cbrt(x**3), x)

        assert_(np.isnan(np.cbrt(np.nan)))
        assert_equal(np.cbrt(np.inf), np.inf)
        assert_equal(np.cbrt(-np.inf), -np.inf) 

Example 18

def np_2_vExample(vid, labs, rgb, audio):
  nframes = audio.shape[0]

  if False:
      # top 5
      k = 5
      if nframes > 10:
        tk_rgb = my_utils.top_k_along_column(rgb, k)
        tk_audio = my_utils.top_k_along_column(audio, k)
      else:
        tk_rgb = np.repeat(rgb[0].reshape([1, rgb.shape[1]]), k, axis=0)
        tk_audio = np.repeat(audio[0].reshape([1, audio.shape[1]]), k, axis=0)      
              
  # std of all rgb or audio entries
  s_rgb = np.std(rgb)
  s_aud = np.std(audio)

  rgb_sq = rgb * rgb
  aud_sq = audio * audio

  vExample  = tf.train.Example(features=tf.train.Features(feature={
     'video_id':     my_utils._byteslist_feature([vid]),
     'labels':       my_utils._int64list_feature(labs),
     'mean_rgb':     my_utils._floatlist_feature(np.mean(rgb, axis=0)),
     'mean_audio':   my_utils._floatlist_feature(np.mean(audio, axis=0)),
     'std_rgb':      my_utils._floatlist_feature(np.std(rgb, axis=0)),
     'std_audio':    my_utils._floatlist_feature(np.std(audio, axis=0)),
     'x3_rgb':       my_utils._floatlist_feature(np.cbrt(np.mean(rgb_sq * rgb, axis=0))),
     'x3_audio':     my_utils._floatlist_feature(np.cbrt(np.mean(aud_sq * audio, axis=0))),
     'num_frames':   my_utils._floatlist_feature([(nframes-151.)/300.]),
     'std_all_rgb':    my_utils._floatlist_feature([s_rgb]),
     'std_all_audio':  my_utils._floatlist_feature([s_aud])
     }))      
      
     #'top_1_rgb':    my_utils._floatlist_feature(tk_rgb[-1]),
     #'top_3_rgb':    my_utils._floatlist_feature(tk_rgb[-3]),
     #'top_5_rgb':    my_utils._floatlist_feature(tk_rgb[-5]),
     #'top_1_audio':  my_utils._floatlist_feature(tk_audio[-1]),
     #'top_3_audio':  my_utils._floatlist_feature(tk_audio[-3]),
     #'top_5_audio':  my_utils._floatlist_feature(tk_audio[-5]),

  return vExample

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