argiope/mesh.py
def set_nodes(self, nlabels = [], coords = [], nsets = {}, **kwargs):
    r"""
    Sets the node data.
    
    :arg nlabels: node labels. Items be strictly positive and int typed 
                  in 1D array-like with shape :math:`(N_n)`.
    :type nlabels: 1D uint typed array-like
    :arg coords: node coordinates. Must be float typed 2D array-like of shape 
                 :math:`(N_n \times 3)`.  
    :type coords: 2D float typed array-like            
    :arg nsets: node sets. Contains boolean array-like of shape :math:`(N_n)`.
    :type nsets: dict
    """ 
    # DATA PREPROCESSING
    nlabels = np.array(nlabels).astype(np.int64)
    coords = np.array(coords).astype(np.float64)
    if (nlabels < 0).sum() > 0: 
      raise ValueError("Node labels must be strictly positive.")
    if len(nlabels) != len(coords):
      raise ValueError("'nlabels' and 'coords' must have the same length")
    if coords.shape[1] != 3:
      raise ValueError("coordinates must be 3 dimensional.")    
    # ATTRIBUTES CREATION
    columns = pd.MultiIndex.from_tuples((("coords", "x"), 
                                         ("coords", "y"), 
                                         ("coords", "z")))
    self.nodes = pd.DataFrame(data = coords, 
                              columns = columns,
                              index = nlabels)
    self.nodes.index.name = "node"
    for k, v in nsets.items(): 
      v = np.array(v)
      if v.dtype != 'bool':
        raise ValueError("Sets must be boolean array-likes.")   
      self.nodes["sets", k] = v
    self.nodes["sets", "all"] = True
def set_nodes(self, nlabels = [], coords = [], nsets = {}, **kwargs):
    r"""
    Sets the node data.
    
    :arg nlabels: node labels. Items be strictly positive and int typed 
                  in 1D array-like with shape :math:`(N_n)`.
    :type nlabels: 1D uint typed array-like
    :arg coords: node coordinates. Must be float typed 2D array-like of shape 
                 :math:`(N_n \times 3)`.  
    :type coords: 2D float typed array-like            
    :arg nsets: node sets. Contains boolean array-like of shape :math:`(N_n)`.
    :type nsets: dict
    """ 
    # DATA PREPROCESSING
    nlabels = np.array(nlabels).astype(np.int64)
    coords = np.array(coords).astype(np.float64)
    if (nlabels < 0).sum() > 0: 
      raise ValueError("Node labels must be strictly positive.")
    if len(nlabels) != len(coords):
      raise ValueError("'nlabels' and 'coords' must have the same length")
    if coords.shape[1] != 3:
      raise ValueError("coordinates must be 3 dimensional.")    
    # ATTRIBUTES CREATION
    columns = pd.MultiIndex.from_tuples((("coords", "x"), 
                                         ("coords", "y"), 
                                         ("coords", "z")))
    self.nodes = pd.DataFrame(data = coords, 
                              columns = columns,
                              index = nlabels)
    self.nodes.index.name = "node"
    for k, v in nsets.items(): 
      v = np.array(v)
      if v.dtype != 'bool':
        raise ValueError("Sets must be boolean array-likes.")   
      self.nodes["sets", k] = v
    self.nodes["sets", "all"] = True
def set_nodes ( self , nlabels = [ ] , coords = [ ] , nsets = { } , * * kwargs ) : # DATA PREPROCESSING nlabels = np . array ( nlabels ) . astype ( np . int64 ) coords = np . array ( coords ) . astype ( np . float64 ) if ( nlabels < 0 ) . sum ( ) > 0 : raise ValueError ( "Node labels must be strictly positive." ) if len ( nlabels ) != len ( coords ) : raise ValueError ( "'nlabels' and 'coords' must have the same length" ) if coords . shape [ 1 ] != 3 : raise ValueError ( "coordinates must be 3 dimensional." ) # ATTRIBUTES CREATION columns = pd . MultiIndex . from_tuples ( ( ( "coords" , "x" ) , ( "coords" , "y" ) , ( "coords" , "z" ) ) ) self . nodes = pd . DataFrame ( data = coords , columns = columns , index = nlabels ) self . nodes . index . name = "node" for k , v in nsets . items ( ) : v = np . array ( v ) if v . dtype != 'bool' : raise ValueError ( "Sets must be boolean array-likes." ) self . nodes [ "sets" , k ] = v self . nodes [ "sets" , "all" ] = True
r"""
    Sets the node data.
    
    :arg nlabels: node labels. Items be strictly positive and int typed 
                  in 1D array-like with shape :math:`(N_n)`.
    :type nlabels: 1D uint typed array-like
    :arg coords: node coordinates. Must be float typed 2D array-like of shape 
                 :math:`(N_n \times 3)`.  
    :type coords: 2D float typed array-like            
    :arg nsets: node sets. Contains boolean array-like of shape :math:`(N_n)`.
    :type nsets: dict
r Sets the node data . : arg nlabels : node labels . Items be strictly positive and int typed in 1D array - like with shape : math : ( N_n ) . : type nlabels : 1D uint typed array - like : arg coords : node coordinates . Must be float typed 2D array - like of shape : math : ( N_n \ times 3 ) . : type coords : 2D float typed array - like : arg nsets : node sets . Contains boolean array - like of shape : math : ( N_n ) . : type nsets : dict