def simulate_cell_year(cell, cell_count, precolumbian):
"""
Simulate a cell-type for an entire year using sample precipitation and
evapotranspiration data.
The `cell` parameter is a string with the soil type and land use
separated by a colon.
The `cell_count` parameter is the number of cells of this type.
If the `precolumbian` parameter is true, then the cell is
simulated under Pre-Columbian circumstances (anything other than
water, woody wetland, and herbaceous wetland becomes mixed
forest).
"""
(soil_type, land_use) = cell.split(':')
if precolumbian:
land_use = make_precolumbian(land_use)
cell = soil_type + ':' + land_use
retval = {}
for day in range(365):
pet = lookup_pet(day, land_use)
retval = dict_plus(retval, simulate_cell_day(pet, cell, cell_count))
return retval
def simulate_water_quality(tree, cell_res, fn,
current_cell=None, precolumbian=False):
"""
Perform a water quality simulation by doing simulations on each of
the cell types (leaves), then adding them together by summing the
values of a node's subtrees and storing them at that node.
`tree` is the (sub)tree of cell distributions that is currently
under consideration.
`cell_res` is the size of each cell (used for turning inches of
water into volumes of water).
`fn` is a function that takes a cell type and a number of cells
and returns a dictionary containing runoff, et, and inf as
volumes.
`current_cell` is the cell type for the present node.
"""
# Internal node.
if 'cell_count' in tree and 'distribution' in tree:
n = tree['cell_count']
# simulate subtrees
if n != 0:
tally = {}
for cell, subtree in tree['distribution'].items():
simulate_water_quality(subtree, cell_res, fn,
cell, precolumbian)
subtree_ex_dist = subtree.copy()
subtree_ex_dist.pop('distribution', None)
tally = dict_plus(tally, subtree_ex_dist)
tree.update(tally) # update this node
# effectively a leaf
elif n == 0:
for pol in get_pollutants():
tree[pol] = 0.0
# Leaf node.
elif 'cell_count' in tree and 'distribution' not in tree:
n = tree['cell_count']
split = current_cell.split(':')
if (len(split) == 2):
split.append('')
if precolumbian:
split[1] = make_precolumbian(split[1])
result = fn('%s:%s:%s' % tuple(split), n) # runoff, et, inf
tree.update(result)
# water quality
if n != 0:
soil_type, land_use, bmp = split
runoff = result['runoff-vol'] / n
liters = get_volume_of_runoff(runoff, n, cell_res)
for pol in get_pollutants():
tree[pol] = get_pollutant_load(land_use, pol, liters)
def simulate_water_quality(tree, cell_res, fn,
pct=1.0, current_cell=None, precolumbian=False):
"""
Perform a water quality simulation by doing simulations on each of
the cell types (leaves), then adding them together by summing the
values of a node's subtrees and storing them at that node.
`tree` is the (sub)tree of cell distributions that is currently
under consideration.
`pct` is the percentage of calculated water volume to retain.
`cell_res` is the size of each cell (used for turning inches of
water into volumes of water).
`fn` is a function that takes a cell type and a number of cells
and returns a dictionary containing runoff, et, and inf as
volumes.
`current_cell` is the cell type for the present node.
"""
# Internal node.
if 'cell_count' in tree and 'distribution' in tree:
n = tree['cell_count']
# simulate subtrees
if n != 0:
tally = {}
for cell, subtree in tree['distribution'].items():
simulate_water_quality(subtree, cell_res, fn,
pct, cell, precolumbian)
subtree_ex_dist = subtree.copy()
subtree_ex_dist.pop('distribution', None)
tally = dict_plus(tally, subtree_ex_dist)
tree.update(tally) # update this node
# effectively a leaf
elif n == 0:
for pol in get_pollutants():
tree[pol] = 0.0
# Leaf node.
elif 'cell_count' in tree and 'distribution' not in tree:
# the number of cells covered by this leaf
n = tree['cell_count']
# canonicalize the current_cell string
split = current_cell.split(':')
if (len(split) == 2):
split.append('')
if precolumbian:
split[1] = make_precolumbian(split[1])
current_cell = '%s:%s:%s' % tuple(split)
# run the runoff model on this leaf
result = fn(current_cell, n) # runoff, et, inf
runoff_adjustment = result['runoff-vol'] - (result['runoff-vol'] * pct)
result['runoff-vol'] -= runoff_adjustment
result['inf-vol'] += runoff_adjustment
tree.update(result)
# perform water quality calculation
if n != 0:
soil_type, land_use, bmp = split
runoff_per_cell = result['runoff-vol'] / n
liters = get_volume_of_runoff(runoff_per_cell, n, cell_res)
for pol in get_pollutants():
tree[pol] = get_pollutant_load(land_use, pol, liters)
