Python numpy 模块，cbrt() 实例源码
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 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 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 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 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 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 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 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
#%%