Quick and dirty list of data associated with nodes, cells, links, and faces

Jan 2016

Raster grid example



In [2]:

    
from landlab import RasterModelGrid
rg = RasterModelGrid(3, 4)

Data associated with nodes:



In [3]:

    
rg.number_of_nodes









    Out[3]:





12



In [4]:

    
rg.number_of_node_rows









    Out[4]:





3



In [5]:

    
rg.number_of_node_columns









    Out[5]:





4



In [6]:

    
rg.node_x  # x coord









    Out[6]:





array([ 0.,  1.,  2.,  3.,  0.,  1.,  2.,  3.,  0.,  1.,  2.,  3.])



In [7]:

    
rg.node_y  # y coord









    Out[7]:





array([ 0.,  0.,  0.,  0.,  1.,  1.,  1.,  1.,  2.,  2.,  2.,  2.])



In [8]:

    
rg.status_at_node  # core/boundary status (0=core, 1=FIXED_VALUE_BOUNDARY, 4=CLOSED_BOUNDARY)









    Out[8]:





array([1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1], dtype=int8)



In [9]:

    
rg.cell_at_node  # ID of cell surrounding node, or BAD_INDEX_VALUE if none









    Out[9]:





array([2147483647, 2147483647, 2147483647, 2147483647, 2147483647,
                0,          1, 2147483647, 2147483647, 2147483647,
       2147483647, 2147483647])



In [10]:

    
rg.links_at_node  # IDs of links at each node, or -1 if none (ENWS order for raster)









    Out[10]:





array([[ 0,  3, -1, -1],
       [ 1,  4,  0, -1],
       [ 2,  5,  1, -1],
       [-1,  6,  2, -1],
       [ 7, 10, -1,  3],
       [ 8, 11,  7,  4],
       [ 9, 12,  8,  5],
       [-1, 13,  9,  6],
       [14, -1, -1, 10],
       [15, -1, 14, 11],
       [16, -1, 15, 12],
       [-1, -1, 16, 13]])



In [11]:

    
rg.link_dirs_at_node









    Out[11]:





array([[-1, -1,  0,  0],
       [-1, -1,  1,  0],
       [-1, -1,  1,  0],
       [ 0, -1,  1,  0],
       [-1, -1,  0,  1],
       [-1, -1,  1,  1],
       [-1, -1,  1,  1],
       [ 0, -1,  1,  1],
       [-1,  0,  0,  1],
       [-1,  0,  1,  1],
       [-1,  0,  1,  1],
       [ 0,  0,  1,  1]], dtype=int8)

Data associated with cells:



In [12]:

    
rg.number_of_cells









    Out[12]:





2



In [13]:

    
rg.area_of_cell









    Out[13]:





array([ 1.,  1.])



In [14]:

    
rg.node_at_cell









    Out[14]:





array([5, 6])



In [15]:

    
rg.faces_at_cell()   # should be made into a property (Eric is working on this)









    Out[15]:





array([[0, 2, 5, 3],
       [1, 3, 6, 4]])

Data associated with links:



In [16]:

    
rg.number_of_links









    Out[16]:





17



In [17]:

    
rg.link_length  # naming: <element>_<attribute> vs <attribute>_of_<element> (disc. in prog)









    Out[17]:





array([ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,
        1.,  1.,  1.,  1.])



In [18]:

    
rg.node_at_link_tail









    Out[18]:





array([ 0,  1,  2,  0,  1,  2,  3,  4,  5,  6,  4,  5,  6,  7,  8,  9, 10])



In [19]:

    
rg.node_at_link_head









    Out[19]:





array([ 1,  2,  3,  4,  5,  6,  7,  5,  6,  7,  8,  9, 10, 11,  9, 10, 11])



In [20]:

    
rg.face_at_link  # ID of face at each link, or BAD_INDEX_VALUE if none









    Out[20]:





array([2147483647, 2147483647, 2147483647, 2147483647,          0,
                1, 2147483647,          2,          3,          4,
       2147483647,          5,          6, 2147483647, 2147483647,
       2147483647, 2147483647])

Data associated with faces



In [21]:

    
rg.number_of_faces









    Out[21]:





7



In [22]:

    
rg.face_width









    Out[22]:





array([ 1.,  1.,  1.,  1.,  1.,  1.,  1.])



In [23]:

    
rg.link_at_face  # ID of link that crosses each face









    Out[23]:





array([ 4,  5,  7,  8,  9, 11, 12])

Hex grid (Voronoi subclass) example



In [24]:

    
from landlab import HexModelGrid
hg = HexModelGrid(3, 3)

Data associated with nodes



In [25]:

    
hg.number_of_nodes









    Out[25]:





10



In [26]:

    
hg.node_x









    Out[26]:





array([ 0. ,  1. ,  2. , -0.5,  0.5,  1.5,  2.5,  0. ,  1. ,  2. ])



In [27]:

    
hg.node_y









    Out[27]:





array([ 0.        ,  0.        ,  0.        ,  0.8660254 ,  0.8660254 ,
        0.8660254 ,  0.8660254 ,  1.73205081,  1.73205081,  1.73205081])



In [28]:

    
hg.status_at_node









    Out[28]:





array([1, 1, 1, 1, 0, 0, 1, 1, 1, 1], dtype=int8)



In [29]:

    
hg.cell_at_node









    Out[29]:





array([2147483647, 2147483647, 2147483647, 2147483647,          0,
                1, 2147483647, 2147483647, 2147483647, 2147483647])



In [30]:

    
hg.links_at_node  # Note that these are sorted by angle, CCW from +x









    Out[30]:





array([[ 0,  3,  2, -1, -1, -1],
       [ 1,  5,  4,  0, -1, -1],
       [ 7,  6,  1, -1, -1, -1],
       [ 8, 11,  2, -1, -1, -1],
       [ 9, 13, 12,  8,  3,  4],
       [10, 15, 14,  9,  5,  6],
       [16, 10,  7, -1, -1, -1],
       [17, 11, 12, -1, -1, -1],
       [18, 17, 13, 14, -1, -1],
       [18, 15, 16, -1, -1, -1]], dtype=int32)



In [31]:

    
hg.link_dirs_at_node  # link direction relative to node: +1 incoming, -1 outgoing, 0 none









    Out[31]:





array([[-1, -1, -1,  0,  0,  0],
       [-1, -1, -1,  1,  0,  0],
       [-1, -1,  1,  0,  0,  0],
       [-1, -1,  1,  0,  0,  0],
       [-1, -1, -1,  1,  1,  1],
       [-1, -1, -1,  1,  1,  1],
       [-1,  1,  1,  0,  0,  0],
       [-1,  1,  1,  0,  0,  0],
       [-1,  1,  1,  1,  0,  0],
       [ 1,  1,  1,  0,  0,  0]], dtype=int8)

Data associated with cells



In [32]:

    
hg.number_of_cells









    Out[32]:





2



In [33]:

    
hg.area_of_cell









    Out[33]:





array([ 0.8660254,  0.8660254])



In [34]:

    
hg.node_at_cell









    Out[34]:





array([4, 5])



In [35]:

    
hg.faces_at_cell









    Out[35]:





array([[ 5,  8,  7,  4,  0,  1],
       [ 6, 10,  9,  5,  2,  3]])

Data associated with links



In [36]:

    
hg.number_of_links









    Out[36]:





19



In [37]:

    
hg.link_length









    Out[37]:





array([ 1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,
        1.,  1.,  1.,  1.,  1.,  1.])



In [38]:

    
hg.node_at_link_tail









    Out[38]:





array([0, 1, 0, 0, 1, 1, 2, 2, 3, 4, 5, 3, 4, 4, 5, 5, 6, 7, 8])



In [39]:

    
hg.node_at_link_head









    Out[39]:





array([1, 2, 3, 4, 4, 5, 5, 6, 4, 5, 6, 7, 7, 8, 8, 9, 9, 8, 9])



In [40]:

    
hg.face_at_link









    Out[40]:





array([2147483647, 2147483647, 2147483647,          0,          1,
                2,          3, 2147483647,          4,          5,
                6, 2147483647,          7,          8,          9,
               10, 2147483647, 2147483647, 2147483647])

Data associated with faces



In [41]:

    
hg.number_of_faces









    Out[41]:





11



In [42]:

    
hg.face_width









    Out[42]:





array([ 0.57735027,  0.57735027,  0.57735027,  0.57735027,  0.57735027,
        0.57735027,  0.57735027,  0.57735027,  0.57735027,  0.57735027,
        0.57735027])



In [43]:

    
hg.link_at_face









    Out[43]:





array([ 3,  4,  5,  6,  8,  9, 10, 12, 13, 14, 15])



In [ ]:



In [ ]: