| 1 | #!/usr/bin/env python |
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| 2 | |
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| 3 | |
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| 4 | """Simple water flow example using ANUGA |
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| 5 | |
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| 6 | Water driven up a linear slope and time varying boundary, |
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| 7 | similar to a beach environment |
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| 8 | |
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| 9 | This is a very simple test of the parallel algorithm using the simplified parallel API |
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| 10 | """ |
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| 11 | |
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| 12 | |
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| 13 | #------------------------------------------------------------------------------ |
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| 14 | # Import necessary modules |
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| 15 | #------------------------------------------------------------------------------ |
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| 16 | |
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| 17 | from anuga.pmesh.mesh_interface import create_mesh_from_regions |
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| 18 | from anuga.abstract_2d_finite_volumes.mesh_factory import rectangular_cross |
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| 19 | from anuga.utilities.numerical_tools import ensure_numeric |
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| 20 | from anuga.shallow_water import Domain |
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| 21 | from anuga.shallow_water import Reflective_boundary |
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| 22 | from anuga.shallow_water import Dirichlet_boundary |
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| 23 | from anuga.shallow_water import Time_boundary |
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| 24 | from anuga.shallow_water import Transmissive_boundary |
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| 25 | |
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| 26 | from parallel_api import distribute, myid |
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| 27 | |
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| 28 | |
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| 29 | #-------------------------------------------------------------------------- |
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| 30 | # Setup computational domain |
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| 31 | #-------------------------------------------------------------------------- |
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| 32 | points, vertices, boundary = rectangular_cross(10, 10) # Basic mesh |
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| 33 | domain = Domain(points, vertices, boundary) # Create domain |
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| 34 | domain.set_name('runup') # Set sww filename |
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| 35 | domain.set_datadir('.') # Set output dir |
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| 36 | |
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| 37 | |
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| 38 | #-------------------------------------------------------------------------- |
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| 39 | # Setup initial conditions |
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| 40 | #-------------------------------------------------------------------------- |
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| 41 | |
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| 42 | def topography(x,y): |
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| 43 | return -x/2 # linear bed slope |
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| 44 | |
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| 45 | domain.set_quantity('elevation', topography) # Use function for elevation |
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| 46 | domain.set_quantity('friction', 0.0) # Constant friction |
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| 47 | domain.set_quantity('stage', expression='elevation') # Dry initial stage |
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| 48 | |
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| 49 | |
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| 50 | #------------------------------------------------------------------------------ |
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| 51 | # Setup boundary conditions |
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| 52 | #------------------------------------------------------------------------------ |
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| 53 | |
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| 54 | Br = Reflective_boundary(domain) # Solid reflective wall |
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| 55 | Bd = Dirichlet_boundary([-0.2,0.,0.]) # Constant boundary values |
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| 56 | |
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| 57 | # Associate boundary tags with boundary objects |
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| 58 | domain.set_boundary({'left': Br, 'right': Bd, 'top': Br, 'bottom': Br}) |
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| 59 | |
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| 60 | |
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| 61 | #-------------------------------------------------------------------------- |
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| 62 | # Create the parallel domain |
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| 63 | #-------------------------------------------------------------------------- |
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| 64 | |
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| 65 | # If this is commented out, the code works. Otherwise the interpolated |
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| 66 | # timeseries are wrong - even when run on one processor. |
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| 67 | # domain = distribute(domain, verbose=True) |
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| 68 | |
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| 69 | |
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| 70 | #------------------------------------------------------------------------------ |
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| 71 | # Evolve system through time |
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| 72 | #------------------------------------------------------------------------------ |
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| 73 | |
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| 74 | interpolation_points = [[0.4,0.5], [0.6,0.5], [0.8,0.5], [0.9,0.5]] |
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| 75 | gauge_values = [] |
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| 76 | for _ in interpolation_points: |
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| 77 | gauge_values.append([]) |
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| 78 | |
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| 79 | time = [] |
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| 80 | |
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| 81 | for t in domain.evolve(yieldstep = 0.1, finaltime = 5.0): |
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| 82 | domain.write_time() |
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| 83 | |
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| 84 | |
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| 85 | # Record time series at known points |
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| 86 | time.append(domain.get_time()) |
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| 87 | |
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| 88 | stage = domain.get_quantity('stage') |
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| 89 | w = stage.get_values(interpolation_points=interpolation_points) |
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| 90 | |
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| 91 | for i, _ in enumerate(interpolation_points): |
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| 92 | gauge_values[i].append(w[i]) |
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| 93 | |
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| 94 | |
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| 95 | for i, (x,y) in enumerate(interpolation_points): |
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| 96 | gauge_values[i] = gauge_values[i][:51] # In case an extra step was taken |
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| 97 | # print i, gauge_values[i] |
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| 98 | # print |
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| 99 | |
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| 100 | |
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| 101 | try: |
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| 102 | from pylab import * |
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| 103 | except: |
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| 104 | pass |
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| 105 | else: |
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| 106 | ion() |
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| 107 | hold(False) |
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| 108 | plot(time, gauge_values[i], 'r.-') |
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| 109 | #time, predicted_gauge_values[i], 'k-') |
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| 110 | |
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| 111 | title('Gauge %d (%f,%f)' %(i,x,y)) |
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| 112 | xlabel('time(s)') |
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| 113 | ylabel('stage (m)') |
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| 114 | #legend(('Observed', 'Modelled'), shadow=True, loc='upper left') |
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| 115 | #savefig('Gauge_%d.png' %i, dpi = 300) |
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| 116 | |
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| 117 | raw_input('Next') |
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| 118 | |
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| 119 | |
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| 120 | |
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| 121 | # Reference from sequential version (also available as a |
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| 122 | # unit test in test_shallow_water_domain) |
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| 123 | # Added Friday 13 October 2006 by Ole |
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| 124 | |
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| 125 | G0 = ensure_numeric([-0.20000000000000001, -0.19999681443389281, -0.1986192343695303, -0.19147413648863046, -0.19132688908678019, -0.17642317476621105, -0.167376262630034, -0.16192452887426961, -0.15609171725778803, -0.15127107084302249, -0.14048864340360018, -0.19296484125327093, -0.19997006390580363, -0.19999999999937063, -0.19999999999937063, -0.19999999999938772, -0.19999999999938772, -0.19999999999938772, -0.19999999999938772, -0.19974288463035494, -0.19951636867991712, -0.19966301435195755, -0.19981082259800226, -0.19978575003960128, -0.19992942471933109, -0.19999999931029933, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989, -0.19999999999906989]) |
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| 126 | |
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| 127 | |
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| 128 | G1 = ensure_numeric([-0.29999999999999993, -0.29988962537199199, -0.29293904425532025, -0.28329367722887888, -0.25999146407696289, -0.22613875068011896, -0.21190705052094994, -0.19900707995208217, -0.18876305176191882, -0.18132447501091936, -0.17395459512711151, -0.15562414200985644, -0.16212999953643359, -0.18964422820514618, -0.20871181844346975, -0.21672207791083464, -0.21774940291862779, -0.21482868050219833, -0.21057786776704043, -0.20649663432591045, -0.20294932949211578, -0.19974459897911329, -0.19733648772704043, -0.19641404599824669, -0.19654095699184146, -0.19709942852191994, -0.19780873983410741, -0.19853259125123518, -0.19916495938961168, -0.19965391267799168, -0.19993539587158982, -0.2001383705551133, -0.20029344332295113, -0.20035349748150011, -0.20029886541561631, -0.20015541958920294, -0.19997273066429103, -0.19979879448668514, -0.19966016997024041, -0.19957558009501869, -0.19955725674938532, -0.19958083002853366, -0.19961752462568647, -0.19965296611330258, -0.19968998132634594, -0.19972532942208607, -0.19975372922008239, -0.19977196116929855, -0.19977951443660594, -0.19977792107284789, -0.19976991595502003]) |
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| 129 | |
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| 130 | G2 = ensure_numeric([-0.40000000000000002, -0.39011996186687281, -0.33359026016903887, -0.29757449757405952, -0.27594124995715791, -0.25970211955309436, -0.24482929492054245, -0.23156757139219822, -0.21956485769139392, -0.20844522129026694, -0.19856327660654355, -0.18962303467030903, -0.17371085465024955, -0.16429840256208336, -0.17793711732368575, -0.19287799702389993, -0.20236271260796762, -0.20700727993623128, -0.20847704371373174, -0.20796895600687262, -0.20653398626186478, -0.20480656169870676, -0.20295863990994492, -0.20100199602968896, -0.19940642689498472, -0.19858371478015749, -0.19838672154605322, -0.19851093923669558, -0.19878191998909323, -0.19910827645394291, -0.19943514333832094, -0.19971231361970535, -0.19992429278849655, -0.20010744405928019, -0.20025927002359642, -0.20034751667523681, -0.20035504591467249, -0.20029401385620157, -0.20019492358237226, -0.20008934249434918, -0.19999808924091636, -0.19993869218976712, -0.19991589568150098, -0.19991815777945968, -0.19993012995477188, -0.19994576118144997, -0.19996497193815974, -0.19998586151236197, -0.20000487253824847, -0.20001903000364174, -0.20002698661385457]) |
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| 131 | |
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| 132 | G3 = ensure_numeric([-0.45000000000000001, -0.37713945714588398, -0.33029565026933816, -0.30598209033945367, -0.28847101155177313, -0.27211191064563195, -0.25701544058818926, -0.24298945948410997, -0.23010402733784807, -0.21820351802867713, -0.20709938367218383, -0.19719881806182216, -0.18568281604361933, -0.16828653906676322, -0.16977310768235579, -0.1832707289594605, -0.19483524345250974, -0.20233480051649216, -0.20630757214159207, -0.20763927857964531, -0.20724458160595791, -0.20599191745446047, -0.20438329669495012, -0.20256105512496606, -0.20071269486729407, -0.19934403619901719, -0.19866860191898347, -0.19849975056296071, -0.19860870923007437, -0.19885838217851401, -0.19916422433758982, -0.19946861981642039, -0.19972267778871666, -0.19993013816258154, -0.20011063428833351, -0.20024891930311628, -0.20031882555219671, -0.20031326268593497, -0.20024881068472311, -0.20015443214902759, -0.20005669097631221, -0.19997542564643309, -0.19992564006223304, -0.19990746148869892, -0.19990923999172872, -0.19991956416813192, -0.19993484556273733, -0.1999538628054662, -0.19997381636620407, -0.19999130900268777, -0.20000388227457688]) |
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| 133 | |
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| 134 | from Numeric import allclose |
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| 135 | msg = 'Computed time series and reference time series are different: %s'\ |
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| 136 | %(gauge_values[0]-G0) |
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| 137 | assert allclose(gauge_values[0], G0), msg |
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| 138 | |
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| 139 | msg = 'Computed time series and reference time series are different: %s'\ |
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| 140 | %(gauge_values[1]-G1) |
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| 141 | assert allclose(gauge_values[1], G1), msg |
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| 142 | |
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| 143 | msg = 'Computed time series and reference time series are different: %s'\ |
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| 144 | %(gauge_values[2]-G2) |
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| 145 | assert allclose(gauge_values[2], G2), msg |
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| 146 | |
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| 147 | msg = 'Computed time series and reference time series are different: %s'\ |
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| 148 | %(gauge_values[3]-G3) |
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| 149 | assert allclose(gauge_values[3], G3), msg |
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| 150 | |
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