| 1 | """ |
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| 2 | ----------------------------------------------------------------- model_run.py |
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| 3 | ANUGA RURAL FLOOD MODELLING TEMPLATE (Domain Construction & Execution) |
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| 4 | Script for building the model domain and setting initial conditions and |
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| 5 | (temporally varying) boundary conditions appropriate to the particular |
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| 6 | scenario-event before running (evolving) the simulation. |
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| 7 | |
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| 8 | Most model data for the run is read in or otherwise referenced in |
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| 9 | model_data.py and imported into model_run.py to create the model mesh and |
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| 10 | domain before running the simulation. |
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| 11 | |
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| 12 | Code Version : 1.00 June 2008 Initial release |
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| 13 | 1.01 December 2008 Vble_n recoded to speed execution |
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| 14 | Author : E Rigby (0437 250 500) ted.rigby@rienco.com.au |
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| 15 | |
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| 16 | ------------------------------------------------------------------------------- |
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| 17 | """ |
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| 18 | |
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| 19 | #------------------------------------------------------------------------------ |
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| 20 | # Import necessary modules |
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| 21 | #------------------------------------------------------------------------------ |
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| 22 | |
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| 23 | # Standard python modules |
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| 24 | import os |
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| 25 | import time |
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| 26 | import sys |
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| 27 | from Numeric import zeros, Float |
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| 28 | |
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| 29 | # Related ANUGA modules |
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| 30 | from anuga.shallow_water import Domain |
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| 31 | from anuga.shallow_water import Reflective_boundary |
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| 32 | from anuga.shallow_water import Dirichlet_boundary |
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| 33 | from anuga.shallow_water import Time_boundary |
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| 34 | from anuga.shallow_water import Transmissive_Momentum_Set_Stage_boundary |
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| 35 | from anuga.shallow_water.shallow_water_domain import Inflow |
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| 36 | from anuga.abstract_2d_finite_volumes.util import file_function |
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| 37 | from anuga.abstract_2d_finite_volumes.quantity import Quantity |
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| 38 | from anuga.pmesh.mesh_interface import create_mesh_from_regions |
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| 39 | from anuga.utilities.polygon import read_polygon, plot_polygons, Polygon_function, inside_polygon |
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| 40 | from anuga.alpha_shape.alpha_shape import alpha_shape_via_files |
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| 41 | |
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| 42 | |
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| 43 | # Model specific imports |
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| 44 | import model_data # Defines and provides the scenario-event specific data |
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| 45 | import get_tuflow_data # Provides the routines to read in tuflow specific data |
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| 46 | |
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| 47 | ##################################################################################### |
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| 48 | # # |
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| 49 | # S I M U L A T I O N M A I N L I N E # |
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| 50 | # # |
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| 51 | ##################################################################################### |
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| 52 | |
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| 53 | t0 = time.time() # record start time of this run (secs) |
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| 54 | print model_data.basename+' >>>> Comencing model_run.py code execution at t= %.2f hours' %(float(time.time()-t0)/3600.0) |
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| 55 | |
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| 56 | ##################################################################################### |
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| 57 | # # |
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| 58 | # CREATE THE TRIANGULAR MESH # |
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| 59 | # # |
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| 60 | ##################################################################################### |
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| 61 | |
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| 62 | # Note: The mesh is created based on overall clipping polygon with a tagged |
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| 63 | # boundary and interior regions as defined in model_data.py along with |
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| 64 | # resolutions (maximal area per triangle) for each interior polygon |
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| 65 | |
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| 66 | print model_data.basename+' >>>> Creating variable mesh within bounding_poly reflecting regional resolutions' |
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| 67 | # Create the mesh reflecting the bounding (default) and internal region mesh resolutions set in model_data.py |
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| 68 | # with boundary tags as defined in model_data.py |
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| 69 | |
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| 70 | create_mesh_from_regions(model_data.bounding_polygon, |
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| 71 | boundary_tags = model_data.boundary_strings, |
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| 72 | maximum_triangle_area = model_data.default_res, |
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| 73 | minimum_triangle_angle=30.0, |
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| 74 | interior_regions = model_data.interior_resregions, |
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| 75 | filename = model_data.mesh_filename, |
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| 76 | use_cache=True, |
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| 77 | verbose=model_data.anuga_verbose) |
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| 78 | |
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| 79 | |
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| 80 | print model_data.basename+' >>>> Completed mesh creation at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 81 | |
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| 82 | ###################################################################################### |
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| 83 | # # |
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| 84 | # CREATE THE COMPUTATIONAL DOMAIN # |
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| 85 | # # |
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| 86 | ###################################################################################### |
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| 87 | |
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| 88 | print model_data.basename+' >>>> Creating domain from mesh and setting domain parameters' |
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| 89 | # create domain from mesh meshname |
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| 90 | domain = Domain(model_data.mesh_filename, use_cache=True, verbose=model_data.anuga_verbose) |
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| 91 | print domain.statistics() # confirm what has been done |
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| 92 | |
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| 93 | # set base domain parameters |
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| 94 | domain.set_name(model_data.basename) # already created in model_data.py |
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| 95 | domain.set_datadir(model_data.results_dir) # already created and/or checked in model_data.py |
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| 96 | domain.set_quantities_to_be_stored(['stage', 'xmomentum', 'ymomentum']) |
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| 97 | domain.set_minimum_storable_height(0.01) # Remove very shallow water depths from sww |
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| 98 | domain.set_maximum_allowed_speed(8.0) # Allow Maximum velocity of 8m/s.... |
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| 99 | |
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| 100 | ###################################################################################### |
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| 101 | # # |
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| 102 | # ASSIGN THE DOMAIN INITIAL CONDITIONS # |
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| 103 | # # |
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| 104 | ###################################################################################### |
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| 105 | |
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| 106 | #------------------------------------------------------------------------------------- |
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| 107 | # This section assigns the initial (t=0) conditions for the domain |
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| 108 | # Domain initial conditions can be fixed, read from a file, or from a function |
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| 109 | # Note also that anuga permits almost all initial conditions to subsequently vary |
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| 110 | # with time, so while the following conditions apply to the whole domain at t=0 |
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| 111 | # all can be modified within the evolve time loop. In this way scour, deposition, |
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| 112 | # blockage, changes in roughness etc with time can be explicitly included in a simulation |
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| 113 | #------------------------------------------------------------------------------------- |
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| 114 | |
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| 115 | print model_data.basename+' >>>> Assigning initial conditions to %s domain' %(model_data.basename) |
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| 116 | |
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| 117 | # Elevation data may be assigned to the domain from a csv or (NetCDF) pts file. |
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| 118 | |
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| 119 | # For a smaller csv that will be read in repeatedly, best to use geospatial_data to readin and |
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| 120 | # export_point_file to save the points permanently in a NetCDF *.pts file. This runs faster |
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| 121 | # than the block read of a csv - but - is limited to about 6 million points. |
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| 122 | # Alternatively - by directly assigning elevation from a csv file can take advantage of the block |
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| 123 | # read in domain.set_quantity so the elevation dataset can be virtually unlimited in size. |
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| 124 | |
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| 125 | # In this simulation the size of the elevation dataset is to large for conversion to a (NetCDF) |
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| 126 | # pts format so data is read in from the raw csv file. |
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| 127 | |
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| 128 | domain.set_quantity('elevation', |
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| 129 | filename = model_data.elev_filename, |
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| 130 | use_cache=True, |
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| 131 | verbose=model_data.anuga_verbose, |
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| 132 | alpha=0.01) |
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| 133 | |
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| 134 | |
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| 135 | # Set the intial water level (stage) across the domain |
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| 136 | InitialWaterLevel = model_data.InitialWaterLevel # At t=0 water surface is in this model at initial lake level (0.3m) |
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| 137 | if domain.get_quantity('elevation') < InitialWaterLevel: # This can create ponds if land is below initial tailwater level |
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| 138 | domain.set_quantity('stage', InitialWaterLevel) # set initial stage at initial tailwater level (wet) |
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| 139 | else: |
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| 140 | domain.set_quantity('stage', expression='elevation') # else set initial stage at land level (dry) |
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| 141 | |
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| 142 | |
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| 143 | # Assign uniform initial friction value to domain mesh centroids as initial condition |
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| 144 | # Note: Friction will be re-assessed based on roughness data read in from tuflow |
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| 145 | # 2d_mat files and computed depth during evolve time loop!!!! |
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| 146 | domain.set_quantity('friction', model_data.default_n, location = 'centroids') |
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| 147 | |
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| 148 | |
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| 149 | |
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| 150 | |
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| 151 | ####################################################################################### |
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| 152 | # # |
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| 153 | # ASSIGN THE (TEMPORAL) SUBAREAL INFLOWS TO THE DOMAIN # |
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| 154 | # # |
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| 155 | ####################################################################################### |
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| 156 | |
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| 157 | #-------------------------------------------------------------------------------------- |
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| 158 | # This section reads the local or total temporal inflows read in in model_data.py from |
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| 159 | # the Tuflow ts1 files and stored as NETCDF tms file in the tms_files subdirectory, |
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| 160 | # into the domain. |
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| 161 | # |
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| 162 | # Note: The current ANUGA inflow function 'pours' flow onto the domain within a circle |
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| 163 | # or polygonal area specified by the user at the specified temporal rate. |
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| 164 | # EHR -- the above inflows should eventually be augmented by inflows at the boundary |
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| 165 | # (total as distinct from local hydrographs) to better correspond with conventional |
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| 166 | # flood modelling. |
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| 167 | #-------------------------------------------------------------------------------------- |
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| 168 | |
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| 169 | print model_data.basename+" >>>> Assigning the inflow hydrographs from the (%s) tms files directory" %(model_data.tms_dir) |
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| 170 | |
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| 171 | |
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| 172 | inflow_fields=[] |
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| 173 | # read in each line of inflow_hydrographs[tms_filename,xcoord,ycoord] and assign as inflow hydrograph to domain |
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| 174 | for i in range(len(model_data.inflow_hydrographs)) : |
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| 175 | |
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| 176 | tms_filename = model_data.inflow_hydrographs[i][0] # extract the inflow hydro tms_filename |
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| 177 | xcoord = model_data.inflow_hydrographs[i][1] # extract the inflow hydro xcoord |
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| 178 | ycoord = model_data.inflow_hydrographs[i][2] # extract the inflow hydro ycoord |
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| 179 | print model_data.basename+' >>>> Reading inflow hydrograph from %s at %7.2f %7.2f and appending to forcing terms ' %(tms_filename,xcoord,ycoord) |
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| 180 | |
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| 181 | # convert time series to temporal function |
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| 182 | flowrate = file_function(tms_filename, |
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| 183 | quantities='value', |
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| 184 | boundary_polygon=None) |
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| 185 | hydrograph = Inflow(domain, |
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| 186 | center=(xcoord,ycoord), |
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| 187 | radius=10, |
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| 188 | rate=flowrate) |
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| 189 | |
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| 190 | # append hydrograph to domain |
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| 191 | domain.forcing_terms.append(hydrograph) |
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| 192 | |
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| 193 | print model_data.basename+' >>>> Completed assignment of %i inflow hydrographs at t= %.2f hours ' %(len(model_data.inflow_hydrographs),float(time.time()-t0)/3600.0) |
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| 194 | |
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| 195 | |
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| 196 | ####################################################################################### |
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| 197 | # # |
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| 198 | # ASSIGN THE (TEMPORAL) DOWNSTREAM BOUNDARY CONDITIONS TO THE DOMAIN # |
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| 199 | # # |
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| 200 | ####################################################################################### |
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| 201 | |
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| 202 | |
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| 203 | print model_data.basename+' >>>> Assigning the DSBC from the (%s) tms files directory ' %(model_data.tms_dir) |
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| 204 | print model_data.basename+' >>>> Available boundary tags are ', domain.get_boundary_tags() |
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| 205 | |
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| 206 | # convert dsbc time series to function of time |
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| 207 | tms_filename=model_data.dsbc_hydrographs[0] |
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| 208 | lake_stage = file_function(tms_filename,quantities='value',boundary_polygon=None) |
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| 209 | # Note: will need to be modified if more than one dsbc is to be applied |
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| 210 | print model_data.basename + ' >>>> Applying dsbc %s to model at the Lake_bdry ' %(tms_filename) |
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| 211 | |
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| 212 | MaMt_bdry = Reflective_boundary(domain) # all reflective except lake as using inflow() |
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| 213 | Mriv_bdry = Reflective_boundary(domain) # Really redundant untill get boundary inflows |
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| 214 | Cbck_bdry = Reflective_boundary(domain) |
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| 215 | WFra_bdry = Reflective_boundary(domain) |
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| 216 | EFra_bdry = Reflective_boundary(domain) |
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| 217 | |
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| 218 | lake_bdry = Transmissive_Momentum_Set_Stage_boundary(domain=domain,function=lake_stage) |
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| 219 | closed_bdry = Reflective_boundary(domain) |
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| 220 | |
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| 221 | # boundary conditions for current scenario |
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| 222 | domain.set_boundary({'Lake': lake_bdry, |
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| 223 | 'MaMt': MaMt_bdry, |
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| 224 | 'Mriv': Mriv_bdry, |
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| 225 | 'Cbck': Cbck_bdry, |
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| 226 | 'WFra': WFra_bdry, |
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| 227 | 'EFra': EFra_bdry, |
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| 228 | 'exterior': closed_bdry }) # this relates to the residue of the bounding poly not explicitly asigned above |
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| 229 | |
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| 230 | print model_data.basename+' >>>> Completed assignment of %i dsbc boundary conditions to domain at t= %.2f hours ' %(len(model_data.dsbc_hydrographs),float(time.time()-t0)/3600.0) |
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| 231 | |
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| 232 | |
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| 233 | ####################################################################################### |
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| 234 | # # |
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| 235 | # ASSIGN THE (TEMPORALLY DEPTH DEPENDENT) SURFACE ROUGHNESS (FRICTION) PARAMETERS # |
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| 236 | # # |
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| 237 | ####################################################################################### |
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| 238 | |
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| 239 | #--------------------------------------------------------------------------------------- |
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| 240 | # This section creates an array of surface roughness data for each element in the domain |
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| 241 | # ready for later use in the evolve loop where the roughness data is used with depth to |
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| 242 | # compute a depth dependent friction at each yieldstep (output timestep to the swww file). |
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| 243 | # |
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| 244 | # Note that because the polys read in should but may not cover the entire bounding poly area |
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| 245 | # It is prudent to initially declare a default material (as in Tuflow) applying the default |
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| 246 | # to the whole domain before applying (overwriting) with the spatial roughness data from the |
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| 247 | # polys obtained from the 2d_mat mid/mif files!!!! |
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| 248 | #-------------------------------------------------------------------------------------- |
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| 249 | |
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| 250 | print model_data.basename+' >>>> Creating and assigning surface roughness data for use in evolve' |
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| 251 | |
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| 252 | N = len(domain) |
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| 253 | # Create the new roughness array to hold the elemental roughness data |
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| 254 | # In this array of Nx5 values |
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| 255 | # n0 -- is the equivalent fixed roughness value |
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| 256 | # d1 -- is the depth below which n1 applies |
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| 257 | # n1 -- is the roughness applying below d1 |
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| 258 | # d2 -- is the depth above which n2 applies |
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| 259 | # n2 -- is the roughness applying above d2 |
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| 260 | |
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| 261 | # Create and assign zeros to the roughness array |
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| 262 | material_variables = zeros((N, 5), Float) |
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| 263 | |
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| 264 | # Set default material variables n0, d1, n1, d2, n2 in the roughness array |
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| 265 | default_n0 = 0.040 |
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| 266 | default_d1 = 0.3 |
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| 267 | default_n1 = 0.050 |
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| 268 | default_d2 = 1.5 |
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| 269 | default_n2 = 0.030 |
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| 270 | |
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| 271 | material_variables[:,0] = default_n0 # n0 |
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| 272 | material_variables[:,1] = default_d1 # d1 |
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| 273 | material_variables[:,2] = default_n1 # n1 |
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| 274 | material_variables[:,3] = default_d2 # d2 |
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| 275 | material_variables[:,4] = default_n2 # n2 |
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| 276 | |
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| 277 | print ' ++++ Initially - material_variables data set to default values across whole domain ' |
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| 278 | |
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| 279 | # Update material_variables from model_data.mat_poly_list |
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| 280 | |
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| 281 | # Obtain a list of real world centroid coords of model elements |
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| 282 | points = domain.get_centroid_coordinates(absolute=True) |
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| 283 | |
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| 284 | for k, poly in enumerate(model_data.mat_poly_list): |
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| 285 | |
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| 286 | # Get indices of triangles inside polygon k |
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| 287 | indices = inside_polygon(points, poly, closed=True) |
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| 288 | |
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| 289 | # Index into material data for polygon k |
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| 290 | rid = model_data.mat_RID_list[k] |
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| 291 | |
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| 292 | # Material data for polygon |
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| 293 | n0, d1, n1, d2, n2 = model_data.mat_roughness_data[rid] |
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| 294 | |
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| 295 | # Update the data for the elements inside the mat_poly |
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| 296 | for i in indices: |
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| 297 | material_variables[i, 0] = n0 |
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| 298 | material_variables[i, 1] = d1 |
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| 299 | material_variables[i, 2] = n1 |
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| 300 | material_variables[i, 3] = d2 |
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| 301 | material_variables[i, 4] = n2 |
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| 302 | |
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| 303 | |
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| 304 | |
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| 305 | print ' ++++ Finally - material_variables data updated spatially with the material values set in the mif/mid files ' |
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| 306 | |
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| 307 | |
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| 308 | print model_data.basename+' >>>> Completed assignment of material (surface roughness) data to domain at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 309 | |
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| 310 | print model_data.basename+' >>>> Completed domain construction at t= %.2f hours ' %(float(time.time()-t0)/3600.0) |
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| 311 | |
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| 312 | |
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| 313 | |
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| 314 | ######################################################################################### |
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| 315 | # # |
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| 316 | # RUN THE SIMULATION # |
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| 317 | # # |
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| 318 | ######################################################################################### |
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| 319 | |
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| 320 | #---------------------------------------------------------------------------------------- |
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| 321 | # This section starts the analysis of flow through the domain from the specified (realworld) |
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| 322 | # starttime up to the specified (realworld) finaltime |
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| 323 | # All time is in seconds. |
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| 324 | # |
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| 325 | # Note: |
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| 326 | # 1. -- The internal computational timestep is set at each timestep to meet a CFL=1 limit. |
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| 327 | # It is therefore important to examine the mesh statistics to see that there are no |
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| 328 | # unintended small triangles, particularly in areas of deeper water as they can |
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| 329 | # dramatically reduce the computational timerstep and slow the model down. |
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| 330 | # 2. -- The model runs on 'internal' time which will normally differ from realworld or |
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| 331 | # 'Design' event time as input by the user in various datafiles. This 'internal'time is |
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| 332 | # normally not seen by the user but users should be aware of its existence. |
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| 333 | # 3. -- In a similar fashion the model runs with all coordinates recomputed to a local |
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| 334 | # lower left frame origin (to impove numerical precission). The output files are in these |
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| 335 | # 'internal' coordinates but each file also stores the new origin coordintes from which |
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| 336 | # the realworld coordinates can be restored (as presently occurs in animate.exe) |
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| 337 | # 4. -- 'friction' is recomputed as a function of depth and location at each steptime for |
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| 338 | # all wet cells. Recomputation at every computational step was considered unnecessay |
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| 339 | # and greatly incresed run times. |
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| 340 | #---------------------------------------------------------------------------------------- |
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| 341 | print model_data.basename+' >>>> Starting the simulation for ',model_data.catchment,'-',model_data.simclass,'-',model_data.scenario,'-',model_data.event |
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| 342 | starttime = 40*3600 # start simulation at t=40h relative to user/data time |
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| 343 | endtime = starttime + 4*3600 # end simulation at t=44h relative to user/data time |
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| 344 | steptime = 300 # write sww file results out every 300secs = 5min |
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| 345 | |
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| 346 | print model_data.basename+' >>>> Simulation is for %.2f hours with output to the sww file at %.0f minute intervals ' %(float((endtime-starttime)/3600.0),float(steptime/60.0)) |
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| 347 | |
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| 348 | # Initiate the starttime reset |
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| 349 | domain.set_starttime(starttime) |
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| 350 | print 'Start time', domain.get_time() |
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| 351 | |
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| 352 | |
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| 353 | for t in domain.evolve(yieldstep = steptime, finaltime = endtime): # This is a steptime loop (not computaional timestep) |
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| 354 | |
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| 355 | domain.write_time() # confirm t each steptime |
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| 356 | domain.write_boundary_statistics(tags='Lake', quantities='stage') # indicate bdry stats each steptime |
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| 357 | depth = domain.create_quantity_from_expression('stage - elevation') # create depth instance for this timestep |
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| 358 | |
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| 359 | print ' ++++ Recomputing friction at t= ', t |
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| 360 | |
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| 361 | # rebuild the 'friction' values adjusted for depth |
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| 362 | for i in domain.get_wet_elements(): # loop for each wet element in domain |
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| 363 | |
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| 364 | # Get roughness variables |
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| 365 | n0 = material_variables[i,0] |
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| 366 | d1 = material_variables[i,1] |
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| 367 | n1 = material_variables[i,2] |
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| 368 | d2 = material_variables[i,3] |
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| 369 | n2 = material_variables[i,4] |
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| 370 | |
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| 371 | |
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| 372 | # Recompute friction values from depth for this element |
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| 373 | d = depth.get_values(location='centroids', indices=[i])[0] |
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| 374 | |
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| 375 | if d <= d1: |
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| 376 | depth_dependent_friction = n1 |
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| 377 | elif d >= d2: |
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| 378 | depth_dependent_friction = n2 |
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| 379 | else: |
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| 380 | depth_dependent_friction = n1+(n2-n1)/(d2-d1)*d |
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| 381 | |
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| 382 | |
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| 383 | domain.set_quantity('friction', |
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| 384 | numeric=depth_dependent_friction, |
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| 385 | location='centroids', |
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| 386 | indices=[i], |
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| 387 | verbose=model_data.anuga_verbose) |
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| 388 | |
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| 389 | |
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| 390 | if model_data.model_verbose : |
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| 391 | friction = domain.get_quantity('friction') |
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| 392 | |
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| 393 | # Print something |
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| 394 | |
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| 395 | |
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| 396 | |
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| 397 | print model_data.basename+' >>>> ',model_data.catchment,'-',model_data.simclass,'-',model_data.scenario,'-',model_data.event,' -- Simulation completed succesfully' |
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| 398 | print model_data.basename+' >>>> Completed ', endtime/3600.0, 'hours of model simulation at t= %.2f hours' %(float(time.time()-t0)/3600.0) |
|---|
| 399 | |
|---|
