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Method nodes

python/dgl/heterograph.py:1778–1825  ·  view source on GitHub ↗

Return a node view One can use it for: 1. Getting the node IDs for a single node type. 2. Setting/getting features for all nodes of a single node type. Examples -------- The following example uses PyTorch backend. >>> import dgl >>>

(self)

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1776
1777 @property
1778 def nodes(self):
1779 """Return a node view
1780
1781 One can use it for:
1782
1783 1. Getting the node IDs for a single node type.
1784 2. Setting/getting features for all nodes of a single node type.
1785
1786 Examples
1787 --------
1788 The following example uses PyTorch backend.
1789
1790 >>> import dgl
1791 >>> import torch
1792
1793 Create a homogeneous graph and a heterogeneous graph of two node types.
1794
1795 >>> g = dgl.graph((torch.tensor([0, 1]), torch.tensor([1, 2])))
1796 >>> hg = dgl.heterograph({
1797 ... ('user', 'follows', 'user'): (torch.tensor([0, 1]), torch.tensor([1, 2])),
1798 ... ('user', 'plays', 'game'): (torch.tensor([3, 4]), torch.tensor([5, 6]))
1799 ... })
1800
1801 Get the node IDs of the homogeneous graph.
1802
1803 >>> g.nodes()
1804 tensor([0, 1, 2])
1805
1806 Get the node IDs of the heterogeneous graph. With multiple node types introduced,
1807 one needs to specify the node type for query.
1808
1809 >>> hg.nodes('user')
1810 tensor([0, 1, 2, 3, 4])
1811
1812 Set and get a feature 'h' for all nodes of a single type in the heterogeneous graph.
1813
1814 >>> hg.nodes['user'].data['h'] = torch.ones(5, 1)
1815 >>> hg.nodes['user'].data['h']
1816 tensor([[1.], [1.], [1.], [1.], [1.]])
1817
1818 To set node features for a graph with a single node type, use :func:`DGLGraph.ndata`.
1819
1820 See Also
1821 --------
1822 ndata
1823 """
1824 # Todo (Mufei) Replace the syntax g.nodes[...].ndata[...] with g.nodes[...][...]
1825 return HeteroNodeView(self, self.get_ntype_id)
1826
1827 @property
1828 def srcnodes(self):

Callers 3

remove_nodesMethod · 0.95
apply_nodesMethod · 0.95
filter_nodesMethod · 0.95

Calls 1

HeteroNodeViewClass · 0.70

Tested by

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