本文整理汇总了Python中holoviews.Columns.dimension_values方法的典型用法代码示例。如果您正苦于以下问题：Python Columns.dimension_values方法的具体用法？Python Columns.dimension_values怎么用？Python Columns.dimension_values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.Columns的用法示例。
在下文中一共展示了Columns.dimension_values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_columns_add_dimensions_value
# 需要导入模块: from holoviews import Columns [as 别名]
# 或者: from holoviews.Columns import dimension_values [as 别名]
def test_columns_add_dimensions_value(self):
table = Columns((self.xs, self.ys),
kdims=['x'], vdims=['y'])
table = table.add_dimension('z', 1, 0)
self.assertEqual(table.kdims[1], 'z')
self.compare_arrays(table.dimension_values('z'), np.zeros(len(table)))示例2: test_columns_add_dimensions_values
# 需要导入模块: from holoviews import Columns [as 别名]
# 或者: from holoviews.Columns import dimension_values [as 别名]
def test_columns_add_dimensions_values(self):
table = Columns((self.xs, self.ys),
kdims=['x'], vdims=['y'])
table = table.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))))示例3: HeterogeneousColumnTypes
# 需要导入模块: from holoviews import Columns [as 别名]
# 或者: from holoviews.Columns import dimension_values [as 别名]
class HeterogeneousColumnTypes(HomogeneousColumnTypes):
"""
Tests for data formats that all columns to have varied types
"""
def init_data(self):
self.kdims = ['Gender', 'Age']
self.vdims = ['Weight', 'Height']
self.gender, self.age = ['M','M','F'], [10,16,12]
self.weight, self.height = [15,18,10], [0.8,0.6,0.8]
self.table = Columns({'Gender':self.gender, 'Age':self.age,
'Weight':self.weight, 'Height':self.height},
kdims=self.kdims, vdims=self.vdims)
super(HeterogeneousColumnTypes, self).init_data()
self.ys = np.linspace(0, 1, 11)
self.zs = np.sin(self.xs)
self.columns_ht = Columns({'x':self.xs, 'y':self.ys},
kdims=['x'], vdims=['y'])
# Test the constructor to be supported by all interfaces supporting
# heterogeneous column types.
def test_columns_ndelement_init_ht(self):
"Tests support for heterogeneous NdElement (backwards compatibility)"
columns = Columns(NdElement(zip(self.xs, self.ys), kdims=['x'], vdims=['y']))
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_dataframe_init_ht(self):
"Tests support for heterogeneous DataFrames"
if pd is None:
raise SkipTest("Pandas not available")
columns = Columns(pd.DataFrame({'x':self.xs, 'y':self.ys}), kdims=['x'], vdims=['y'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
# Test literal formats
def test_columns_uniq_dimvals_ht(self):
self.assertEqual(self.table.dimension_values('Gender', unique=True),
np.array(['M', 'F']))
def test_columns_implicit_indexing_init(self):
columns = Columns(self.ys, kdims=['x'], vdims=['y'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_tuple_init(self):
columns = Columns((self.xs, self.ys), kdims=['x'], vdims=['y'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_simple_zip_init(self):
columns = Columns(zip(self.xs, self.ys), kdims=['x'], vdims=['y'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_zip_init(self):
columns = Columns(zip(self.gender, self.age,
self.weight, self.height),
kdims=self.kdims, vdims=self.vdims)
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_odict_init(self):
columns = Columns(OrderedDict(zip(self.xs, self.ys)), kdims=['A'], vdims=['B'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
def test_columns_dict_init(self):
columns = Columns(dict(zip(self.xs, self.ys)), kdims=['A'], vdims=['B'])
self.assertTrue(isinstance(columns.data, self.data_instance_type))
# Operations
def test_columns_sort_vdim_ht(self):
columns = Columns({'x':self.xs, 'y':-self.ys},
kdims=['x'], vdims=['y'])
columns_sorted = Columns({'x':self.xs[::-1], 'y':-self.ys[::-1]},
kdims=['x'], vdims=['y'])
self.assertEqual(columns.sort('y'), columns_sorted)
def test_columns_sort_string_ht(self):
columns_sorted = Columns({'Gender':['F','M','M'], 'Age':[12,10,16],
'Weight':[10,15,18], 'Height':[0.8,0.8,0.6]},
kdims=self.kdims, vdims=self.vdims)
self.assertEqual(self.table.sort(), columns_sorted)
def test_columns_sample_ht(self):
samples = self.columns_ht.sample([0, 5, 10]).dimension_values('y')
self.assertEqual(samples, np.array([0, 0.5, 1]))
def test_columns_reduce_ht(self):
reduced = Columns({'Age':self.age, 'Weight':self.weight, 'Height':self.height},
kdims=self.kdims[1:], vdims=self.vdims)
self.assertEqual(self.table.reduce(['Gender'], np.mean), reduced)
def test_columns_1D_reduce_ht(self):
self.assertEqual(self.columns_ht.reduce('x', np.mean), np.float64(0.5))
def test_columns_2D_reduce_ht(self):
reduced = Columns({'Weight':[14.333333333333334], 'Height':[0.73333333333333339]},
kdims=[], vdims=self.vdims)
self.assertEqual(self.table.reduce(function=np.mean), reduced)
def test_columns_2D_partial_reduce_ht(self):
#.........这里部分代码省略.........