我们从Python开源项目中，提取了以下18个代码示例，用于说明如何使用numpy.cbrt()。
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)))
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)))
def test_cbrt_scalar(self): assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5)
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)
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
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 #%%
