本文整理汇总了Python中holoviews.Dataset.redim方法的典型用法代码示例。如果您正苦于以下问题：Python Dataset.redim方法的具体用法？Python Dataset.redim怎么用？Python Dataset.redim使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类holoviews.Dataset的用法示例。
在下文中一共展示了Dataset.redim方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: test_dataset_redim_with_alias_dframe
# 需要导入模块: from holoviews import Dataset [as 别名]
# 或者: from holoviews.Dataset import redim [as 别名]
def test_dataset_redim_with_alias_dframe(self):
test_df = pd.DataFrame({'x': range(10), 'y': range(0,20,2)})
dataset = Dataset(test_df, kdims=[('x', 'X-label')], vdims=['y'])
redim_df = pd.DataFrame({'X': range(10), 'y': range(0,20,2)})
dataset_redim = Dataset(redim_df, kdims=['X'], vdims=['y'])
self.assertEqual(dataset.redim(**{'X-label':'X'}), dataset_redim)
self.assertEqual(dataset.redim(**{'x':'X'}), dataset_redim)示例2: HomogeneousColumnTests
# 需要导入模块: from holoviews import Dataset [as 别名]
# 或者: from holoviews.Dataset import redim [as 别名]
#.........这里部分代码省略.........
def test_dataset_sort_reverse_hm(self):
ds = Dataset(([2, 1, 2, 1], [2, 2, 1, 1], [0.1, 0.2, 0.3, 0.4]),
kdims=['x', 'y'], vdims=['z'])
ds_sorted = Dataset(([2, 2, 1, 1], [2, 1, 2, 1], [0.1, 0.3, 0.2, 0.4]),
kdims=['x', 'y'], vdims=['z'])
self.assertEqual(ds.sort(reverse=True), ds_sorted)
def test_dataset_sort_vdim_hm(self):
xs_2 = np.array(self.xs_2)
dataset = Dataset(np.column_stack([self.xs, -xs_2]),
kdims=['x'], vdims=['y'])
dataset_sorted = Dataset(np.column_stack([self.xs[::-1], -xs_2[::-1]]),
kdims=['x'], vdims=['y'])
self.assertEqual(dataset.sort('y'), dataset_sorted)
def test_dataset_sort_reverse_vdim_hm(self):
xs_2 = np.array(self.xs_2)
dataset = Dataset(np.column_stack([self.xs, -xs_2]),
kdims=['x'], vdims=['y'])
dataset_sorted = Dataset(np.column_stack([self.xs, -xs_2]),
kdims=['x'], vdims=['y'])
self.assertEqual(dataset.sort('y', reverse=True), dataset_sorted)
def test_dataset_sort_vdim_hm_alias(self):
xs_2 = np.array(self.xs_2)
dataset = Dataset(np.column_stack([self.xs, -xs_2]),
kdims=[('x', 'X-label')], vdims=[('y', 'Y-label')])
dataset_sorted = Dataset(np.column_stack([self.xs[::-1], -xs_2[::-1]]),
kdims=[('x', 'X-label')], vdims=[('y', 'Y-label')])
self.assertEqual(dataset.sort('y'), dataset_sorted)
self.assertEqual(dataset.sort('Y-label'), dataset_sorted)
def test_dataset_redim_hm_kdim(self):
redimmed = self.dataset_hm.redim(x='Time')
self.assertEqual(redimmed.dimension_values('Time'),
self.dataset_hm.dimension_values('x'))
def test_dataset_redim_hm_kdim_range_aux(self):
redimmed = self.dataset_hm.redim.range(x=(-100,3))
self.assertEqual(redimmed.kdims[0].range, (-100,3))
def test_dataset_redim_hm_kdim_soft_range_aux(self):
redimmed = self.dataset_hm.redim.soft_range(x=(-100,30))
self.assertEqual(redimmed.kdims[0].soft_range, (-100,30))
def test_dataset_redim_hm_kdim_alias(self):
redimmed = self.dataset_hm_alias.redim(x='Time')
self.assertEqual(redimmed.dimension_values('Time'),
self.dataset_hm_alias.dimension_values('x'))
def test_dataset_redim_hm_vdim(self):
redimmed = self.dataset_hm.redim(y='Value')
self.assertEqual(redimmed.dimension_values('Value'),
self.dataset_hm.dimension_values('y'))
def test_dataset_redim_hm_vdim_alias(self):
redimmed = self.dataset_hm_alias.redim(y=Dimension(('val', 'Value')))
self.assertEqual(redimmed.dimension_values('Value'),
self.dataset_hm_alias.dimension_values('y'))
def test_dataset_sample_hm(self):
samples = self.dataset_hm.sample([0, 5, 10]).dimension_values('y')
self.assertEqual(samples, np.array([0, 10, 20]))
def test_dataset_sample_hm_alias(self):示例3: HomogeneousColumnTypes
# 需要导入模块: from holoviews import Dataset [as 别名]
# 或者: from holoviews.Dataset import redim [as 别名]
class HomogeneousColumnTypes(object):
"""
Tests for data formats that require all dataset to have the same
type (e.g numpy arrays)
"""
def setUp(self):
self.restore_datatype = Dataset.datatype
self.data_instance_type = None
def init_data(self):
self.xs = range(11)
self.xs_2 = [el**2 for el in self.xs]
self.y_ints = [i*2 for i in range(11)]
self.dataset_hm = Dataset((self.xs, self.y_ints),
kdims=['x'], vdims=['y'])
def tearDown(self):
Dataset.datatype = self.restore_datatype
# Test the array constructor (homogenous data) to be supported by
# all interfaces.
def test_dataset_array_init_hm(self):
"Tests support for arrays (homogeneous)"
dataset = Dataset(np.column_stack([self.xs, self.xs_2]),
kdims=['x'], vdims=['x2'])
self.assertTrue(isinstance(dataset.data, self.data_instance_type))
def test_dataset_ndelement_init_hm(self):
"Tests support for homogeneous NdElement (backwards compatibility)"
dataset = Dataset(NdElement(zip(self.xs, self.xs_2),
kdims=['x'], vdims=['x2']))
self.assertTrue(isinstance(dataset.data, self.data_instance_type))
def test_dataset_dataframe_init_hm(self):
"Tests support for homogeneous DataFrames"
if pd is None:
raise SkipTest("Pandas not available")
dataset = Dataset(pd.DataFrame({'x':self.xs, 'x2':self.xs_2}),
kdims=['x'], vdims=[ 'x2'])
self.assertTrue(isinstance(dataset.data, self.data_instance_type))
# Properties and information
def test_dataset_shape(self):
self.assertEqual(self.dataset_hm.shape, (11, 2))
def test_dataset_range(self):
self.assertEqual(self.dataset_hm.range('y'), (0, 20))
def test_dataset_closest(self):
closest = self.dataset_hm.closest([0.51, 1, 9.9])
self.assertEqual(closest, [1., 1., 10.])
# Operations
def test_dataset_sort_vdim_hm(self):
xs_2 = np.array(self.xs_2)
dataset = Dataset(np.column_stack([self.xs, -xs_2]),
kdims=['x'], vdims=['y'])
dataset_sorted = Dataset(np.column_stack([self.xs[::-1], -xs_2[::-1]]),
kdims=['x'], vdims=['y'])
self.assertEqual(dataset.sort('y'), dataset_sorted)
def test_dataset_redim_hm_kdim(self):
redimmed = self.dataset_hm.redim(x='Time')
self.assertEqual(redimmed.dimension_values('Time'),
self.dataset_hm.dimension_values('x'))
def test_dataset_redim_hm_vdim(self):
redimmed = self.dataset_hm.redim(y='Value')
self.assertEqual(redimmed.dimension_values('Value'),
self.dataset_hm.dimension_values('y'))
def test_dataset_sample_hm(self):
samples = self.dataset_hm.sample([0, 5, 10]).dimension_values('y')
self.assertEqual(samples, np.array([0, 10, 20]))
def test_dataset_array_hm(self):
self.assertEqual(self.dataset_hm.array(),
np.column_stack([self.xs, self.y_ints]))
def test_dataset_add_dimensions_value_hm(self):
table = self.dataset_hm.add_dimension('z', 1, 0)
self.assertEqual(table.kdims[1], 'z')
self.compare_arrays(table.dimension_values('z'), np.zeros(len(table)))
def test_dataset_add_dimensions_values_hm(self):
table = self.dataset_hm.add_dimension('z', 1, range(1,12))
self.assertEqual(table.kdims[1], 'z')
self.compare_arrays(table.dimension_values('z'), np.array(list(range(1,12))))
def test_dataset_slice_hm(self):
dataset_slice = Dataset({'x':range(5, 9), 'y':[2 * i for i in range(5, 9)]},
kdims=['x'], vdims=['y'])
self.assertEqual(self.dataset_hm[5:9], dataset_slice)
#.........这里部分代码省略.........