def test_frac_grid(): frac_spacing = 3 nrows = 9 ncols = 9 fg = make_frac_grid(frac_spacing, nrows, ncols, seed=1) assert_array_equal(fg, [[1, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 0, 1, 0, 1], [0, 0, 0, 0, 0, 0, 1, 1, 1], [0, 0, 0, 0, 0, 1, 0, 1, 1], [1, 1, 1, 1, 1, 1, 1, 0, 1], [0, 0, 0, 1, 0, 0, 0, 1, 1], [0, 0, 0, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0, 0]])
def main(): # INITIALIZE # User-defined parameters nr = 200 # number of rows in grid nc = 200 # number of columns in grid plot_interval = 0.05 # time interval for plotting (unscaled) run_duration = 5.0 # duration of run (unscaled) report_interval = 10.0 # report interval, in real-time seconds frac_spacing = 10 # average fracture spacing, nodes outfilename = 'wx' # name for netCDF files # Remember the clock time, and calculate when we next want to report # progress. current_real_time = time.time() next_report = current_real_time + report_interval # Counter for output files time_slice = 0 # Create grid mg = RasterModelGrid(nr, nc, 1.0) # Make the boundaries be walls mg.set_closed_boundaries_at_grid_edges(True, True, True, True) # Set up the states and pair transitions. ns_dict = { 0 : 'rock', 1 : 'saprolite' } xn_list = setup_transition_list() # Create the node-state array and attach it to the grid. # (Note use of numpy's uint8 data type. This saves memory AND allows us # to write output to a netCDF3 file; netCDF3 does not handle the default # 64-bit integer type) node_state_grid = mg.add_zeros('node', 'node_state_map', dtype=np.uint8) node_state_grid[:] = make_frac_grid(frac_spacing, model_grid=mg) # Create the CA model ca = RasterCTS(mg, ns_dict, xn_list, node_state_grid) # Set up the color map rock_color = (0.8, 0.8, 0.8) sap_color = (0.4, 0.2, 0) clist = [rock_color, sap_color] my_cmap = matplotlib.colors.ListedColormap(clist) # Create a CAPlotter object for handling screen display ca_plotter = CAPlotter(ca, cmap=my_cmap) # Plot the initial grid ca_plotter.update_plot() # Output the initial grid to file write_netcdf((outfilename+str(time_slice)+'.nc'), mg, #format='NETCDF3_64BIT', names='node_state_map') # RUN current_time = 0.0 while current_time < run_duration: # Once in a while, print out simulation and real time to let the user # know that the sim is running ok current_real_time = time.time() if current_real_time >= next_report: print('Current sim time', current_time, '(', 100 * current_time/run_duration, '%)') next_report = current_real_time + report_interval # Run the model forward in time until the next output step ca.run(current_time+plot_interval, ca.node_state, plot_each_transition=False) current_time += plot_interval # Plot the current grid ca_plotter.update_plot() # Output the current grid to a netCDF file time_slice += 1 write_netcdf((outfilename+str(time_slice)+'.nc'), mg, #format='NETCDF3_64BIT', names='node_state_map') # FINALIZE # Plot ca_plotter.finalize()
def main(): # INITIALIZE # User-defined parameters nr = 128 nc = 128 fracture_spacing = 10 # fracture spacing, cell widths plot_interval = 0.25 run_duration = 4.0 report_interval = 5.0 # report interval, in real-time seconds # Remember the clock time, and calculate when we next want to report # progress. current_real_time = time.time() next_report = current_real_time + report_interval # Create grid mg = RasterModelGrid(nr, nc, 1.0) # Set up the states and pair transitions. # Transition data here represent a body of fractured rock, with rock # represented by nodes with state 0, and saprolite (weathered rock) # represented by nodes with state 1. Node pairs (links) with 0-1 or 1-0 # can undergo a transition to 1-1, representing chemical weathering of the # rock. ns_dict = { 0 : 'rock', 1 : 'saprolite' } xn_list = setup_transition_list() # Create the node-state array and attach it to the grid node_state_grid = mg.add_zeros('node', 'node_state_map', dtype=int) # Initialize the node-state array as a "fracture grid" in which randomly # oriented fractures are represented as lines of saprolite embedded in # bedrock. node_state_grid[:] = make_frac_grid(fracture_spacing, model_grid=mg) # Create the CA model ca = RasterLCA(mg, ns_dict, xn_list, node_state_grid) # Debug output if needed if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print('{0:.0f}'.format(ca.node_state[n]), end=' ') print() # Create a CAPlotter object for handling screen display ca_plotter = CAPlotter(ca) # Plot the initial grid ca_plotter.update_plot() # RUN current_time = 0.0 while current_time < run_duration: # Once in a while, print out simulation and real time to let the user # know that the sim is running ok current_real_time = time.time() if current_real_time >= next_report: print('Current sim time',current_time,'(',100*current_time/run_duration,'%)') next_report = current_real_time + report_interval # Run the model forward in time until the next output step ca.run(current_time+plot_interval, ca.node_state, plot_each_transition=False) #, plotter=ca_plotter) current_time += plot_interval # Plot the current grid ca_plotter.update_plot() # for debugging if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print('{0:.0f}'.format(ca.node_state[n]), end=' ') print() # FINALIZE # Plot ca_plotter.finalize()
def main(): # INITIALIZE # User-defined parameters nr = 128 nc = 128 fracture_spacing = 10 # fracture spacing, cell widths plot_interval = 0.25 run_duration = 4.0 report_interval = 5.0 # report interval, in real-time seconds # Remember the clock time, and calculate when we next want to report # progress. current_real_time = time.time() next_report = current_real_time + report_interval # Create grid mg = RasterModelGrid(nr, nc, 1.0) # Set up the states and pair transitions. # Transition data here represent a body of fractured rock, with rock # represented by nodes with state 0, and saprolite (weathered rock) # represented by nodes with state 1. Node pairs (links) with 0-1 or 1-0 # can undergo a transition to 1-1, representing chemical weathering of the # rock. ns_dict = {0: 'rock', 1: 'saprolite'} xn_list = setup_transition_list() # Create the node-state array and attach it to the grid node_state_grid = mg.add_zeros('node', 'node_state_map', dtype=int) # Initialize the node-state array as a "fracture grid" in which randomly # oriented fractures are represented as lines of saprolite embedded in # bedrock. node_state_grid[:] = make_frac_grid(fracture_spacing, model_grid=mg) # Create the CA model ca = LinkCellularAutomaton(mg, ns_dict, xn_list, node_state_grid) # Debug output if needed if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print '{0:.0f}'.format(ca.node_state[n]), print # Create a CAPlotter object for handling screen display ca_plotter = CAPlotter(ca) # Plot the initial grid ca_plotter.update_plot() # RUN current_time = 0.0 while current_time < run_duration: # Once in a while, print out simulation and real time to let the user # know that the sim is running ok current_real_time = time.time() if current_real_time >= next_report: print 'Current sim time', current_time, '(', 100 * current_time / run_duration, '%)' next_report = current_real_time + report_interval # Run the model forward in time until the next output step ca.run(current_time + plot_interval, ca.node_state, plot_each_transition=False) #, plotter=ca_plotter) current_time += plot_interval # Plot the current grid ca_plotter.update_plot() # for debugging if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print '{0:.0f}'.format(ca.node_state[n]), print # FINALIZE # Plot ca_plotter.finalize()
def main(): # INITIALIZE # User-defined parameters nr = 128 nc = 128 plot_interval = 0.25 run_duration = 4.0 report_interval = 5.0 # report interval, in real-time seconds # Initialize real time current_real_time = time.time() next_report = current_real_time + report_interval # Create grid and set up boundaries mg = RasterModelGrid(nr, nc, 1.0) # Transition data here represent a body of fractured rock, with rock # represented by nodes with state 0, and saprolite (weathered rock) # represented by nodes with state 1. Node pairs (links) with 0-1 or 1-0 # can undergo a transition to 1-1, representing chemical weathering of the # rock. ns_dict = { 0 : 'rock', 1 : 'saprolite' } xn_list = setup_transition_list() # The initial grid node_state_grid = mg.add_zeros('node', 'node_state_map', dtype=int) node_state_grid[:] = make_frac_grid(10, model_grid=mg) # Create the CA model ca = LinkCellularAutomaton(mg, ns_dict, xn_list, node_state_grid) # Debug output if needed if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print '{0:.0f}'.format(ca.node_state[n]), print ca_plotter = CAPlotter(ca) # RUN current_time = 0.0 while current_time < run_duration: # Once in a while, print out simulation and real time to let the user # know that the sim is running ok current_real_time = time.time() if current_real_time >= next_report: print 'Current sim time',current_time,'(',100*current_time/run_duration,'%)' next_report = current_real_time + report_interval # Run the model forward in time until the next output step ca.run(current_time+plot_interval, ca.node_state, plot_each_transition=False) #, plotter=ca_plotter) current_time += plot_interval # Plot the current grid ca_plotter.update_plot() # for debugging if _DEBUG: n = ca.grid.number_of_nodes for r in range(ca.grid.number_of_node_rows): for c in range(ca.grid.number_of_node_columns): n -= 1 print '{0:.0f}'.format(ca.node_state[n]), print # FINALIZE # Plot ca_plotter.finalize()