

In [1]:

    
%matplotlib inline

将二维网格映射到三维网格中

扩展supercell



In [2]:

    
nodes, edges = [], []

创建nodes 和 edges

top位相关



In [3]:

    
from catplot.grid_components.nodes import Node2D, Node3D
from catplot.grid_components.edges import Edge2D



In [4]:

    
top = Node2D([0.0, 0.0], size=800, color="#2A6A9C")



In [5]:

    
t1 = Node2D([0.0, 1.0])
t2 = Node2D([1.0, 0.0])



In [6]:

    
nodes.append(top)



In [7]:

    
e1 = Edge2D(top, t1, width=5)
e2 = Edge2D(top, t2, width=5)



In [8]:

    
edges.extend([e1, e2])

bridge相关



In [9]:

    
bridge1 = Node2D([0.0, 0.5], style="s", size=600, color="#5A5A5A", alpha=0.6)
bridge2 = Node2D([0.5, 0.0], style="s", size=600, color="#5A5A5A", alpha=0.6)



In [10]:

    
b1 = bridge1.clone([0.5, 0.5])
b2 = bridge2.clone([0.5, 0.5])



In [11]:

    
nodes.extend([bridge1, bridge2])



In [12]:

    
e1 = Edge2D(bridge1, b1)
e2 = Edge2D(bridge1, bridge2)
e3 = Edge2D(bridge2, b2)
e4 = Edge2D(b1, b2)



In [13]:

    
edges.extend([e1, e2, e3, e4])

hollow位



In [14]:

    
h = Node2D([0.5, 0.5], style="h", size=700, color="#5A5A5A", alpha=0.3)



In [15]:

    
nodes.append(h)

绘制



In [16]:

    
from catplot.grid_components.grid_canvas import Grid2DCanvas



In [17]:

    
from catplot.grid_components.supercell import SuperCell2D



In [18]:

    
supercell = SuperCell2D(nodes, edges)

将此supercell进行扩展



In [19]:

    
expanded_supercell = supercell.expand(4, 4)

绘制



In [20]:

    
canvas_big = Grid2DCanvas(figsize=(30, 20), dpi=60)



In [21]:

    
canvas_big.add_supercell(expanded_supercell)



In [22]:

    
canvas_big.draw()
canvas_big.figure









    Out[22]:

创建空位species node



In [23]:

    
empty = Node2D([0.0, 0.0], size=3000, 
               color="none", edgecolor="#000000", line_width="2", line_style="dashed", zorder=3, alpha=0.7)

创建O2分子



In [24]:

    
o1 = Node2D([0.0, 0.0], size=3000, color="#B95D60", zorder=4, alpha=0.7)



In [25]:

    
o2 = o1.clone([1.0, 0.0])



In [26]:

    
bond = Edge2D(o1, o2, width=15, alpha=0.7)



In [27]:

    
o2 = SuperCell2D([o1, o2], [bond])

创建CO分子



In [28]:

    
co = Node2D([0.0, 0.0], size=3000, color="#A472C8", zorder=4, alpha=0.7)

向画布中添加原子



In [29]:

    
n0 = empty.clone([1.0, 0.5])
n1 = o1.clone([3.5, 2.0])
n2 = co.clone([1.0, 1.5])
n3 = co.clone([2.0, 2.5])
n4 = co.clone([2.5, 2.0])
n5 = o1.clone([1.5, 2.0])
n6n7 = o2.clone([2.0, 1.0])
n8 = o1.clone([1.0, 2.5])
n9 = empty.clone([2.0, 1.5])
n10 = empty.clone([2.0, 3.5])



In [30]:

    
canvas_big.add_nodes([n1, n2, n3, n4, n5, n8])
canvas_big.add_supercell(n6n7)



In [31]:

    
canvas_big.redraw()
canvas_big.figure









    Out[31]:



In [32]:

    
from catplot.grid_components.grid_canvas import Grid3DCanvas
canvas3d = Grid3DCanvas(figsize=(30, 20), dpi=100)

将二维网格映射到三维空间中



In [33]:

    
canvas_big.to3d(canvas3d)









    Out[33]:





<catplot.grid_components.grid_canvas.Grid3DCanvas at 0x1084fbef0>



In [34]:

    
none = Node3D([0.0, 0.0, 1.5], color="", size=0)
canvas3d.add_node(none)



In [35]:

    
canvas3d.redraw()
canvas3d.figure









    Out[35]:

抽出快物种



In [36]:

    
f1, = canvas3d.extract_node(n2.label)



In [37]:

    
f2, = canvas3d.extract_node(n3.label)



In [37]:

    
f1









    Out[37]:





<catplot.grid_components.nodes.Node3D at 0x10cd6f4e0>



In [38]:

    
f1.move([0.0, 0.0, 1.5])
f2.move([0.0, 0.0, 1.5])









    Out[38]:





<catplot.grid_components.nodes.Node3D at 0x10804bc18>



In [39]:

    
canvas3d.redraw()
canvas3d.figure









    Out[39]: