這是這里帖子的后續。
我正在嘗試將從 Scipy 的 Delaunay 三角剖分回傳的單純形轉換為 Networkx 圖。
代碼：
from scipy.spatial import Delaunay as scipy_Delaunay
# tri = scipy_Delaunay(pts[:, 0:2]) #input points
# simplices = tri.simplices
simplices = np.array([[ 9, 13, 19],
[11, 9, 4],
[ 9, 11, 13],
[ 0, 7, 2],
[ 7, 3, 18]])
G = nx.Graph(simplices)
for path in simplices:
nx.add_path(G, path)
nx.draw(G, with_labels=True, node_size=500, node_color='lightgreen')
錯誤：
raise nx.NetworkXError(f"Adjacency matrix not square: nx,ny={A.shape}")
networkx.exception.NetworkXError: Adjacency matrix not square: nx,ny=(5, 3)
networkx.exception.NetworkXError: Input is not a correct numpy matrix or array.
我不確定如何解決此錯誤。建議將非常有幫助。
uj5u.com熱心網友回復：
我認為你可以從
G = nx.Graph(simplices)
到：
G = nx.Graph()
創建一個空圖。您稍后將在回圈中添加節點，因此無需在圖形創建期間添加節點位置。最后的代碼是：
from scipy.spatial import Delaunay as scipy_Delaunay
# tri = scipy_Delaunay(pts[:, 0:2]) #input points
# simplices = tri.simplices
simplices = np.array([[ 9, 13, 19],
[11, 9, 4],
[ 9, 11, 13],
[ 0, 7, 2],
[ 7, 3, 18]])
G = nx.Graph()
for path in simplices:
nx.add_path(G, path)
nx.draw(G, with_labels=True, node_size=500, node_color='lightgreen')
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