def test_find_remove_isolated_cells():
idomain = np.zeros((2, 1000, 1000), dtype=int)
idomain[:, 200:-200, 200:-200] = 1
idomain[:, 202:203, 202:203] = 0
idomain[:, 300:330, 300:301] = 0
idomain[:, 305:306, 305:306] = 0
idomain[:, 10:13, 10:13] = 1
idomain[:, 20:22, 20:22] = 1
idomain[:, -20:-18, -20:-18] = 1
result = find_remove_isolated_cells(idomain, minimum_cluster_size=10)
assert result.shape == idomain.shape
# no inactive cells should have been filled
assert result.sum() == idomain[:, 200:-200, 200:-200].sum()
result = find_remove_isolated_cells(idomain, minimum_cluster_size=9)
# cluster of 9 active cells was not removed
assert result.sum() == idomain[:, 200:-200, 200:-200].sum() + 9 * 2
idomain = np.zeros((40, 40), dtype=int)
idomain[5:-3, 2:7] = 1
idomain[3:5, 7:8] = 1 # 2 pixels
idomain[10, 8:11] = 1 # 3 pixels
idomain[20, 7] = 1 # pixel that has only one connection
result = find_remove_isolated_cells(idomain, minimum_cluster_size=10)
assert result.sum() == idomain.sum() - 6
def _set_ibound(self):
"""Remake the idomain array from the source data,
no data values in the top and bottom arrays, and
so that cells above SFR reaches are inactive."""
ibound_from_layer_elevations = make_ibound(
self.dis.top.array,
self.dis.botm.array,
nodata=self._nodata_value,
minimum_layer_thickness=self.cfg['dis'].get(
'minimum_layer_thickness', 1),
#drop_thin_cells=self._drop_thin_cells,
tol=1e-4)
# include cells that are active in the existing idomain array
# and cells inactivated on the basis of layer elevations
ibound = (self.bas6.ibound.array > 0) & (ibound_from_layer_elevations
== 1)
ibound = ibound.astype(int)
# remove cells that conincide with lakes
ibound[self.isbc == 1] = 0.
# remove cells that are above stream cells
if self.get_package('sfr') is not None:
ibound = deactivate_idomain_above(ibound, self.sfr.reach_data)
# remove cells that are above ghb cells
if self.get_package('ghb') is not None:
ibound = deactivate_idomain_above(ibound,
self.ghb.stress_period_data[0])
# inactivate any isolated cells that could cause problems with the solution
ibound = find_remove_isolated_cells(ibound, minimum_cluster_size=20)
self._ibound = ibound
# re-write the input files
self._setup_array('bas6',
'ibound',
resample_method='nearest',
data={i: arr
for i, arr in enumerate(ibound)},
datatype='array3d',
write_fmt='%d',
dtype=int)
self.bas6.ibound = self.cfg['bas6']['ibound']
def test_ibound(pleasant_nwt_with_dis):
m = pleasant_nwt_with_dis
# use pleasant lake extent as ibound
is_pleasant_lake = m.lakarr[0]
# clear out lake info, just for this test function
m.cfg['model']['packages'].remove('lak')
del m.cfg['lak']['source_data']
# specify path relative to cfg file
m.cfg['bas6']['source_data']['ibound'] = {
'filename':
'../../../examples/data/pleasant/source_data/shps/all_lakes.shp'
}
m._reset_bc_arrays()
bas6 = m.setup_bas6()
bas6.write_file()
assert np.array_equal(m.ibound, m.bas6.ibound.array)
# find_remove_isolated_cells is run on ibound array but not in Lake setup
assert np.array_equal(m.ibound[0],
find_remove_isolated_cells(is_pleasant_lake))
ibound = load_array(m.cfg['bas6']['ibound'])
assert np.array_equal(m.ibound, ibound)
def test_dis_setup(shellmound_model_with_grid):
m = shellmound_model_with_grid #deepcopy(model_with_grid)
# test intermediate array creation
m.cfg['dis']['remake_top'] = True
m.cfg['dis']['source_data']['top']['resample_method'] = 'nearest'
m.cfg['dis']['source_data']['botm']['resample_method'] = 'nearest'
dis = m.setup_dis()
botm = m.dis.botm.array.copy()
assert isinstance(dis, mf6.ModflowGwfdis)
assert 'DIS' in m.get_package_list()
# verify that units got conveted correctly
assert m.dis.top.array.mean() < 100
assert m.dis.length_units.array == 'meters'
# verify that modelgrid was reset after building DIS
mg = m.modelgrid
assert (mg.nlay, mg.nrow, mg.ncol) == m.dis.botm.array.shape
assert np.array_equal(mg.top, m.dis.top.array)
assert np.array_equal(mg.botm, m.dis.botm.array)
arrayfiles = m.cfg['intermediate_data']['top'] + \
m.cfg['intermediate_data']['botm'] + \
m.cfg['intermediate_data']['idomain']
for f in arrayfiles:
assert os.path.exists(f)
fname = os.path.splitext(os.path.split(f)[1])[0]
k = ''.join([s for s in fname if s.isdigit()])
var = fname.strip(k)
data = np.loadtxt(f)
model_array = getattr(m.dis, var).array
if len(k) > 0:
k = int(k)
model_array = model_array[k]
assert np.array_equal(model_array, data)
# test that written idomain array reflects supplied shapefile of active area
active_area = rasterize(m.cfg['dis']['source_data']['idomain']['filename'],
m.modelgrid)
isactive = active_area == 1
written_idomain = load_array(m.cfg['dis']['griddata']['idomain'])
assert np.all(written_idomain[:, ~isactive] <= 0)
# test idomain from just layer elevations
del m.cfg['dis']['griddata']['idomain']
dis = m.setup_dis()
top = dis.top.array.copy()
top[top == m._nodata_value] = np.nan
botm = dis.botm.array.copy()
botm[botm == m._nodata_value] = np.nan
thickness = get_layer_thicknesses(top, botm)
invalid_botms = np.ones_like(botm)
invalid_botms[np.isnan(botm)] = 0
invalid_botms[thickness < 1.0001] = 0
# these two arrays are not equal
# because isolated cells haven't been removed from the second one
# this verifies that _set_idomain is removing them
assert not np.array_equal(m.idomain[:, isactive].sum(axis=1),
invalid_botms[:, isactive].sum(axis=1))
invalid_botms = find_remove_isolated_cells(invalid_botms,
minimum_cluster_size=20)
active_cells = m.idomain[:, isactive].copy()
active_cells[active_cells <
0] = 0 # need to do this because some idomain cells are -1
assert np.array_equal(active_cells.sum(axis=1),
invalid_botms[:, isactive].sum(axis=1))
# test recreating package from external arrays
m.remove_package('dis')
assert m.cfg['dis']['griddata']['top'] is not None
assert m.cfg['dis']['griddata']['botm'] is not None
dis = m.setup_dis()
assert np.array_equal(m.dis.botm.array[m.dis.idomain.array == 1],
botm[m.dis.idomain.array == 1])
# test recreating just the top from the external array
m.remove_package('dis')
m.cfg['dis']['remake_top'] = False
m.cfg['dis']['griddata']['botm'] = None
dis = m.setup_dis()
dis.write()
assert np.array_equal(m.dis.botm.array[m.dis.idomain.array == 1],
botm[m.dis.idomain.array == 1])
arrayfiles = m.cfg['dis']['griddata']['top']
for f in arrayfiles:
assert os.path.exists(f['filename'])
assert os.path.exists(os.path.join(m.model_ws, dis.filename))
# dis package idomain should be consistent with model property
updated_idomain = m.idomain
assert np.array_equal(m.dis.idomain.array, updated_idomain)
# check that units were converted (or not)
assert np.allclose(dis.top.array[dis.idomain.array[0] == 1].mean(),
40,
atol=10)
mcaq = m.cfg['dis']['source_data']['botm']['filenames'][3]
assert 'mcaq' in mcaq
with rasterio.open(mcaq) as src:
mcaq_data = src.read(1)
mcaq_data[mcaq_data == src.meta['nodata']] = np.nan
assert np.allclose(m.dis.botm.array[3][dis.idomain.array[3] == 1].mean() /
.3048,
np.nanmean(mcaq_data),
atol=5)
def _set_idomain(self):
"""Remake the idomain array from the source data,
no data values in the top and bottom arrays, and
so that cells above SFR reaches are inactive.
Also remakes irch for the recharge package"""
# loop thru LGR models and inactivate area of parent grid for each one
lgr_idomain = np.ones(self.dis.idomain.array.shape, dtype=int)
if isinstance(self.lgr, dict):
for k, v in self.lgr.items():
lgr_idomain[v.idomain == 0] = 0
idomain_from_layer_elevations = make_idomain(self.dis.top.array,
self.dis.botm.array,
nodata=self._nodata_value,
minimum_layer_thickness=self.cfg['dis'].get('minimum_layer_thickness', 1),
drop_thin_cells=self._drop_thin_cells,
tol=1e-4)
# include cells that are active in the existing idomain array
# and cells inactivated on the basis of layer elevations
idomain = (self.dis.idomain.array == 1) & \
(idomain_from_layer_elevations == 1) & \
(lgr_idomain == 1)
idomain = idomain.astype(int)
# remove cells that conincide with lakes
idomain[self.isbc == 1] = 0.
# remove cells that are above stream cells
if self.get_package('sfr') is not None:
idomain = deactivate_idomain_above(idomain, self.sfr.packagedata)
# inactivate any isolated cells that could cause problems with the solution
idomain = find_remove_isolated_cells(idomain, minimum_cluster_size=20)
# create pass-through cells in inactive cells that have an active cell above and below
# by setting these cells to -1
idomain = create_vertical_pass_through_cells(idomain)
self._idomain = idomain
# take the updated idomain array and set cells != 1 to np.nan in layer botm array
# including lake cells
# effect is that the layer thicknesses in these cells will be set to zero
# fill_cells_vertically will be run in the setup_array routine,
# to collapse the nan cells to zero-thickness
# (assign their layer botm to the next valid layer botm above)
botm = self.dis.botm.array.copy()
botm[(idomain != 1)] = np.nan
# re-write the input files
# todo: integrate this better with setup_dis
# to reduce the number of times the arrays need to be remade
self._setup_array('dis', 'botm',
data={i: arr for i, arr in enumerate(botm)},
datatype='array3d', resample_method='linear',
write_fmt='%.2f', dtype=float)
self.dis.botm = self.cfg['dis']['griddata']['botm']
self._setup_array('dis', 'idomain',
data={i: arr for i, arr in enumerate(idomain)},
datatype='array3d', resample_method='nearest',
write_fmt='%d', dtype=int)
self.dis.idomain = self.cfg['dis']['griddata']['idomain']
self._mg_resync = False
self.setup_grid() # reset the model grid
# rebuild irch to keep it in sync with idomain changes
irch = make_irch(idomain)
self._setup_array('rch', 'irch',
data={0: irch},
datatype='array2d',
write_fmt='%d', dtype=int)