#! /usr/bin/env python3
#
def graph_arc_test ( ):

#*****************************************************************************80
#
## graph_arc_test() tests graph_arc().
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    14 April 2026
#
#  Author:
#
#    John Burkardt
#
  import numpy as np
  import platform

  print ( '' )
  print ( 'graph_arc_test():' )
  print ( '  numpy version:  ' + np.version.version )
  print ( '  python version: ' + platform.python_version ( ) )
  print ( '  Test graph_arc().' )

  graph_adj_to_arc_test ( )
  graph_arc_to_adj_test ( )
#
#  Terminate.
#
  print ( '' )
  print ( 'graph_arc_test():' )
  print ( '  Normal end of execution.' )

  return

def graph_adj_to_arc ( A ):

#*****************************************************************************80
#
## graph_adj_to_arc() converts an adjacency graph to an arc list graph.
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    10 April 2026
#
#  Author:
#
#    John Burkardt
#
#  Input:
#
#    integer A(node_num,node_num), the adjacency matrix.
#
#  Output:
#
#    integer inode(edge_num), jnode(edge_num): the arc list of the graph.
#
  import numpy as np

  edge_num = np.sum ( A )
  node_num = A.shape[0]

  edge_id = 0
  inode = -1 * np.ones ( edge_num, dtype = int )
  jnode = -1 * np.ones ( edge_num, dtype = int )

  for i in range ( 0, node_num ):
    for j in range ( 0, node_num ):
      if ( A[i,j] != 0 ):
        inode[edge_id] = i
        jnode[edge_id] = j
        edge_id = edge_id + 1

  return inode, jnode

def graph_adj_to_arc_test ( ):

#*****************************************************************************80
#
## graph_adj_to_arc_test() tests graph_adj_to_arc().
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    10 April 2026
#
#  Author:
#
#    John Burkardt
#
  import numpy as np
  import pprint

  node_num = 13

  A = np.array ( [ \
    [0,1,1,1,1,1,1,1,0,0,0,0,0], \
    [1,0,0,0,1,1,0,1,0,0,0,0,0], \
    [1,0,0,1,0,0,1,0,0,0,0,0,0], \
    [1,0,1,0,0,0,0,0,0,0,0,0,0], \
    [1,1,0,0,0,0,0,0,0,0,0,0,0], \
    [1,1,0,0,0,0,0,0,0,0,0,0,0], \
    [1,0,1,0,0,0,0,0,0,0,0,0,0], \
    [1,1,0,0,0,0,0,0,1,0,0,0,0], \
    [0,0,0,0,0,0,0,1,0,1,0,0,1], \
    [0,0,0,0,0,0,0,0,1,0,1,1,1], \
    [0,0,0,0,0,0,0,0,0,1,0,1,0], \
    [0,0,0,0,0,0,0,0,0,1,1,0,0], \
    [0,0,0,0,0,0,0,0,1,1,0,0,0] ], dtype = int )

  print ( '' )
  print ( 'graph_adj_to_arc_test():' )
  print ( '  graph_adj_to_arc() converts a graph adjacency' )
  print ( '  representation of a graph to graph arc format.' )

  print ( '' )
  print ( '  The graph adjacency matrix:' )
  pprint.pprint ( A )

  edge_num = np.sum ( A )

  print ( '' )
  print ( '  Number of edges is ', edge_num )

  inode, jnode = graph_adj_to_arc ( A )

  knode = np.transpose ( np.stack ( ( inode, jnode ) ) )
  print ( '' )
  print ( '  The arc list:' )
  pprint.pprint ( knode )

  return

def graph_arc_to_adj ( inode, jnode ):

#*****************************************************************************80
#
## graph_arc_to_adj() converts an arc list graph to an adjacency graph.
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    10 April 2026
#
#  Author:
#
#    John Burkardt
#
#  Input:
#
#    integer INODE(edge_num), JNODE(edge_num), the edge array for 
#    an undirected graph.  The I-th edge connects nodes INODE(I) and JNODE(I).
#
#  Output:
#
#    integer A(node_num,node_num), the adjacency information.
#
  import numpy as np

  edge_num = len ( inode )
  node_num = max ( np.max ( inode ), np.max ( jnode ) ) + 1

  A = np.zeros ( [ node_num, node_num ] )

  for edge_id in range ( 0, edge_num ):
    i = inode[edge_id]
    j = jnode[edge_id]
    A[i,j] = 1

  return A

def graph_arc_to_adj_test ( ):

#*****************************************************************************80
#
## graph_arc_to_adj_test() tests graph_arc_to_adj().
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    10 April 2026
#
#  Author:
#
#    John Burkardt
#
  import numpy as np
  import pprint

  inode = np.array ( [ \
    1, 1, 1, 1, 1, 1, 1, 2, 2, 2, \
    2, 3, 3, 3, 4, 4, 5, 5, 6, 6, \
    7, 7, 8, 8, 8, 9, 9, 9,10,10, \
   10,10,11,11,12,12,13,13 ], dtype = int )

  jnode = np.array ( [ \
    2, 3, 4, 5, 6, 7, 8, 1, 5, 6, \
    8, 1, 4, 7, 1, 3, 1, 2, 1, 2, \
    1, 3, 1, 2, 9, 8,10,13, 9,11, \
   12,13,10,12,10,11, 9,10 ], dtype = int )
#
#  Adjust to zero-based indexing.
#
  inode = inode - 1
  jnode = jnode - 1

  print ( '' )
  print ( 'graph_arc_to_adj_test():' )
  print ( '  graph_arc_to_adj() converts a graph arc' )
  print ( '  representation of a graph to an adjacency matrix.' )

  knode = np.transpose ( np.stack ( ( inode, jnode ) ) )
  print ( '' )
  print ( '  The arc list:' )
  pprint.pprint ( knode )

  A = graph_arc_to_adj ( inode, jnode  )

  print ( '' )
  print ( '  The graph adjacency matrix:' )
  pprint.pprint ( A )

  return

def timestamp ( ):

#*****************************************************************************80
#
## timestamp() prints the date as a timestamp.
#
#  Licensing:
#
#    This code is distributed under the MIT license. 
#
#  Modified:
#
#    06 April 2013
#
#  Author:
#
#    John Burkardt
#
  import time

  t = time.time ( )
  print ( time.ctime ( t ) )

  return

if ( __name__ == "__main__" ):
  timestamp ( )
  graph_arc_test ( )
  timestamp ( )