def test_fastscape_new(): input_str = os.path.join(_THIS_DIR, 'drive_sp_params.txt') inputs = ModelParameterDictionary(input_str, auto_type=True) nrows = inputs.read_int('nrows') ncols = inputs.read_int('ncols') dx = inputs.read_float('dx') dt = inputs.read_float('dt') time_to_run = inputs.read_float('run_time') uplift = inputs.read_float('uplift_rate') init_elev = inputs.read_float('init_elev') mg = RasterModelGrid(nrows, ncols, dx) mg.set_closed_boundaries_at_grid_edges(False, False, True, True) mg.add_zeros('topographic__elevation', at='node') z = mg.zeros(at='node') + init_elev numpy.random.seed(0) mg['node']['topographic__elevation'] = z + \ numpy.random.rand(len(z)) / 1000. fr = FlowAccumulator(mg, flow_director='D8') fsp = Fsc(mg, **inputs) # here's the diff from the above elapsed_time = 0. while elapsed_time < time_to_run: if elapsed_time + dt > time_to_run: dt = time_to_run - elapsed_time fr.run_one_step() fsp.run_one_step(dt) # new style mg.at_node['topographic__elevation'][mg.core_nodes] += uplift * dt elapsed_time += dt z_trg = numpy.array([5.48813504e-04, 7.15189366e-04, 6.02763376e-04, 5.44883183e-04, 4.23654799e-04, 6.45894113e-04, 1.01830760e-02, 9.58036770e-03, 6.55865452e-03, 3.83441519e-04, 7.91725038e-04, 1.00142749e-02, 8.80798884e-03, 5.78387585e-03, 7.10360582e-05, 8.71292997e-05, 9.81911417e-03, 9.52243406e-03, 7.55093226e-03, 8.70012148e-04, 9.78618342e-04, 1.00629755e-02, 8.49253798e-03, 5.33216680e-03, 1.18274426e-04, 6.39921021e-04, 9.88956320e-03, 9.47119567e-03, 6.43790696e-03, 4.14661940e-04, 2.64555612e-04, 1.00450743e-02, 8.37262908e-03, 5.21540904e-03, 1.87898004e-05, 6.17635497e-04, 9.21286940e-03, 9.34022513e-03, 7.51114450e-03, 6.81820299e-04, 3.59507901e-04, 6.19166921e-03, 7.10456176e-03, 6.62585507e-03, 6.66766715e-04, 6.70637870e-04, 2.10382561e-04, 1.28926298e-04, 3.15428351e-04, 3.63710771e-04]) assert_array_almost_equal(mg.at_node['topographic__elevation'], z_trg)
def test_fastscape(): uplift = 0.001 dt = 1.0 time_to_run = 10.0 mg = RasterModelGrid((10, 5)) mg.set_closed_boundaries_at_grid_edges(False, False, True, True) mg.add_zeros("topographic__elevation", at="node") z = mg.zeros(at="node") numpy.random.seed(0) mg["node"]["topographic__elevation"] = z + numpy.random.rand( len(z)) / 1000.0 fr = FlowAccumulator(mg, flow_director="D8") fsp = Fsc(mg, K_sp=0.1, m_sp=0.5, n_sp=1.0, threshold_sp=0.0) elapsed_time = 0.0 while elapsed_time < time_to_run: if elapsed_time + dt > time_to_run: dt = time_to_run - elapsed_time fr.run_one_step() fsp.run_one_step(dt=dt) mg.at_node["topographic__elevation"][mg.core_nodes] += uplift * dt elapsed_time += dt z_trg = numpy.array([ 5.48813504e-04, 7.15189366e-04, 6.02763376e-04, 5.44883183e-04, 4.23654799e-04, 6.45894113e-04, 1.01830760e-02, 9.58036770e-03, 6.55865452e-03, 3.83441519e-04, 7.91725038e-04, 1.00142749e-02, 8.80798884e-03, 5.78387585e-03, 7.10360582e-05, 8.71292997e-05, 9.81911417e-03, 9.52243406e-03, 7.55093226e-03, 8.70012148e-04, 9.78618342e-04, 1.00629755e-02, 8.49253798e-03, 5.33216680e-03, 1.18274426e-04, 6.39921021e-04, 9.88956320e-03, 9.47119567e-03, 6.43790696e-03, 4.14661940e-04, 2.64555612e-04, 1.00450743e-02, 8.37262908e-03, 5.21540904e-03, 1.87898004e-05, 6.17635497e-04, 9.21286940e-03, 9.34022513e-03, 7.51114450e-03, 6.81820299e-04, 3.59507901e-04, 6.19166921e-03, 7.10456176e-03, 6.62585507e-03, 6.66766715e-04, 6.70637870e-04, 2.10382561e-04, 1.28926298e-04, 3.15428351e-04, 3.63710771e-04, ]) assert_array_almost_equal(mg.at_node["topographic__elevation"], z_trg)