def _watermap(world, n):
def droplet(world, pos, q, _watermap):
if q < 0:
return
x, y = pos
pos_elev = world.elevation['data'][y, x] + _watermap[y, x]
lowers = []
min_higher = None
min_lower = None
# pos_min_higher = None # TODO: no longer used?
tot_lowers = 0
for p in world.tiles_around((x, y)): #TODO: switch to numpy
px, py = p
e = world.elevation['data'][py, px] + _watermap[py, px]
if e < pos_elev:
dq = int(pos_elev - e) << 2
if min_lower is None or e < min_lower:
min_lower = e
if dq == 0:
dq = 1
lowers.append((dq, p))
tot_lowers += dq
else:
if min_higher is None or e > min_higher:
min_higher = e
# pos_min_higher = p
if lowers:
f = q / tot_lowers
for l in lowers:
s, p = l
if not world.ocean[p[1], p[0]]:
px, py = p
ql = f * s
# ql = q
going = ql > 0.05
_watermap[py, px] += ql
if going:
droplet(world, p, ql, _watermap)
else:
_watermap[y, x] += q
_watermap_data = numpy.zeros((world.height, world.width), dtype=float)
for i in range(n):
x, y = world.random_land()
if True and world.precipitation['data'][y, x] > 0:
droplet(world, (x, y), world.precipitation['data'][y, x],
_watermap_data)
_watermap = dict()
_watermap['data'] = _watermap_data
_watermap['thresholds'] = dict()
_watermap['thresholds']['creek'] = find_threshold_f(_watermap_data,
0.05,
ocean=world.ocean)
_watermap['thresholds']['river'] = find_threshold_f(_watermap_data,
0.02,
ocean=world.ocean)
_watermap['thresholds']['main river'] = \
find_threshold_f(_watermap_data, 0.007, ocean=world.ocean)
return _watermap
def _watermap(world, n):
def droplet(world, pos, q, _watermap):
if q < 0:
return
x, y = pos
pos_elev = world.elevation['data'][y, x] + _watermap[y, x]
lowers = []
min_higher = None
min_lower = None
# pos_min_higher = None # TODO: no longer used?
tot_lowers = 0
for p in world.tiles_around((x, y)):#TODO: switch to numpy
px, py = p
e = world.elevation['data'][py, px] + _watermap[py, px]
if e < pos_elev:
dq = int(pos_elev - e) << 2
if min_lower is None or e < min_lower:
min_lower = e
if dq == 0:
dq = 1
lowers.append((dq, p))
tot_lowers += dq
else:
if min_higher is None or e > min_higher:
min_higher = e
# pos_min_higher = p
if lowers:
f = q / tot_lowers
for l in lowers:
s, p = l
if not world.ocean[p[1], p[0]]:
px, py = p
ql = f * s
# ql = q
going = ql > 0.05
_watermap[py, px] += ql
if going:
droplet(world, p, ql, _watermap)
else:
_watermap[y, x] += q
_watermap_data = numpy.zeros((world.height, world.width), dtype=float)
for i in range(n):
x, y = world.random_land()
if True and world.precipitation['data'][y, x] > 0:
droplet(world, (x, y), world.precipitation['data'][y, x],
_watermap_data)
_watermap = dict()
_watermap['data'] = _watermap_data
_watermap['thresholds'] = dict()
_watermap['thresholds']['creek'] = find_threshold_f(_watermap_data,
0.05,
ocean=world.ocean)
_watermap['thresholds']['river'] = find_threshold_f(_watermap_data,
0.02,
ocean=world.ocean)
_watermap['thresholds']['main river'] = \
find_threshold_f(_watermap_data, 0.007, ocean=world.ocean)
return _watermap
def execute(self, world, seed):
perm = self._calculate(seed, world.width, world.height)
perm_th = [
('low', find_threshold_f(perm, 0.75, world.ocean)),
('med', find_threshold_f(perm, 0.25, world.ocean)),
('hig', None)
]
world.set_permeability(perm, perm_th)
def execute(self, world, seed):
perm = self._calculate(seed, world.width, world.height)
ocean = world.layers['ocean'].data
perm_th = [
('low', find_threshold_f(perm, 0.75, ocean)),
('med', find_threshold_f(perm, 0.25, ocean)),
('hig', None)
]
world.permeability = (perm, perm_th)
def execute(self, world, seed):
if get_verbose():
start_time = time.time()
pre_calculated = self._calculate(seed, world.width, world.height)
ths = [('low', find_threshold_f(pre_calculated, 0.75, world.ocean)),
('med', find_threshold_f(pre_calculated, 0.3, world.ocean)),
('hig', None)]
world.set_precipitation(pre_calculated, ths)
if get_verbose():
elapsed_time = time.time() - start_time
print("...precipitations calculated. Elapsed time %f seconds." %
elapsed_time)
def _watermap(world, n):
def droplet(world, pos, q, _watermap):
if q < 0:
return
x, y = pos
pos_elev = world.layers['elevation'].data[y, x] + _watermap[y, x]
lowers = []
min_higher = None
min_lower = None
# pos_min_higher = None # TODO: no longer used?
tot_lowers = 0
for p in world.tiles_around((x, y)):#TODO: switch to numpy
px, py = p
e = world.layers['elevation'].data[py, px] + _watermap[py, px]
if e < pos_elev:
dq = int(pos_elev - e) << 2
if min_lower is None or e < min_lower:
min_lower = e
if dq == 0:
dq = 1
lowers.append((dq, p))
tot_lowers += dq
else:
if min_higher is None or e > min_higher:
min_higher = e
# pos_min_higher = p
if lowers:
f = q / tot_lowers
for l in lowers:
s, p = l
if not world.is_ocean(p):
px, py = p
ql = f * s
# ql = q
going = ql > 0.05
_watermap[py, px] += ql
if going:
droplet(world, p, ql, _watermap)
else:
_watermap[y, x] += q
_watermap_data = numpy.zeros((world.height, world.width), dtype=float)
for i in range(n):
x, y = world.random_land() # will return None for x and y if no land exists
if x is not None and world.precipitations_at((x, y)) > 0:
droplet(world, (x, y), world.precipitations_at((x, y)), _watermap_data)
ocean = world.layers['ocean'].data
thresholds = dict()
thresholds['creek'] = find_threshold_f(_watermap_data, 0.05, ocean=ocean)
thresholds['river'] = find_threshold_f(_watermap_data, 0.02, ocean=ocean)
thresholds['main river'] = find_threshold_f(_watermap_data, 0.007, ocean=ocean)
return _watermap_data, thresholds
def execute(self, world, seed):
if get_verbose():
start_time = time.time()
pre_calculated = self._calculate(seed, world)
ths = [
('low', find_threshold_f(pre_calculated, 0.75, world.ocean)),
('med', find_threshold_f(pre_calculated, 0.3, world.ocean)),
('hig', None)
]
world.set_precipitation(pre_calculated, ths)
if get_verbose():
elapsed_time = time.time() - start_time
print(
"...precipitations calculated. Elapsed time %f seconds."
% elapsed_time)
def execute(self, world, seed):
if get_verbose():
start_time = time.time()
pre_calculated = self._calculate(seed, world)
ocean = world.layers['ocean'].data
ths = [
('low', find_threshold_f(pre_calculated, 0.75, ocean)),
('med', find_threshold_f(pre_calculated, 0.3, ocean)),
('hig', None)
]
world.precipitation = (pre_calculated, ths)
if get_verbose():
elapsed_time = time.time() - start_time
print(
"...precipitations calculated. Elapsed time %f seconds."
% elapsed_time)
def initialize_ocean_and_thresholds(world, ocean_level=1.0):
"""
Calculate the ocean, the sea depth and the elevation thresholds
:param world: a world having elevation but not thresholds
:param ocean_level: the elevation representing the ocean level
:return: nothing, the world will be changed
"""
e = world.elevation['data']
ocean = fill_ocean(e, ocean_level)
hl = find_threshold_f(e, 0.10)
ml = find_threshold_f(e, 0.03)
e_th = [('sea', ocean_level), ('plain', hl), ('hill', ml),
('mountain', None)]
world.set_ocean(ocean)
world.set_elevation(e, e_th)
world.sea_depth = sea_depth(world, ocean_level)
def _calculate(world):
humids = world.humids
humidity = dict()
precipitationWeight = 1.0
irrigationWeight = 3
humidity['data'] = numpy.zeros((world.height, world.width), dtype=float)
humidity['data'] = (world.precipitation['data'] * precipitationWeight - world.irrigation * irrigationWeight)/(precipitationWeight + irrigationWeight)
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
humidity['quantiles'] = {}
humidity['quantiles']['12'] = find_threshold_f(humidity['data'], humids[6],
world.ocean)
humidity['quantiles']['25'] = find_threshold_f(humidity['data'], humids[5],
world.ocean)
humidity['quantiles']['37'] = find_threshold_f(humidity['data'], humids[4],
world.ocean)
humidity['quantiles']['50'] = find_threshold_f(humidity['data'], humids[3],
world.ocean)
humidity['quantiles']['62'] = find_threshold_f(humidity['data'], humids[2],
world.ocean)
humidity['quantiles']['75'] = find_threshold_f(humidity['data'], humids[1],
world.ocean)
humidity['quantiles']['87'] = find_threshold_f(humidity['data'], humids[0],
world.ocean)
return humidity
def _calculate(world):
humidity = dict()
humidity['data'] = [[0 for x in xrange(world.width)]
for y in xrange(world.height)
] # TODO: replace with numpy
for y in xrange(world.height):
for x in xrange(world.width):
humidity['data'][y][x] = world.precipitation['data'][y][x] + \
world.irrigation[y][x]
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
humidity['quantiles'] = {}
humidity['quantiles']['12'] = find_threshold_f(humidity['data'], 0.02,
world.ocean)
humidity['quantiles']['25'] = find_threshold_f(humidity['data'], 0.09,
world.ocean)
humidity['quantiles']['37'] = find_threshold_f(humidity['data'], 0.26,
world.ocean)
humidity['quantiles']['50'] = find_threshold_f(humidity['data'], 0.50,
world.ocean)
humidity['quantiles']['62'] = find_threshold_f(humidity['data'], 0.74,
world.ocean)
humidity['quantiles']['75'] = find_threshold_f(humidity['data'], 0.91,
world.ocean)
humidity['quantiles']['87'] = find_threshold_f(humidity['data'], 0.98,
world.ocean)
return humidity
def _calculate(world):
humidity = dict()
temperatureWeight = 2.3
precipitationWeight = 1.0
irrigationWeight = 3
humidity['data'] = [[0 for x in range(world.width)] for y in
range(world.height)] # TODO: replace with numpy
for y in range(world.height):
for x in range(world.width):
humidity['data'][y][x] = (((world.precipitation['data'][y][x] * precipitationWeight - world.irrigation[y][x] * irrigationWeight)+1) * ((world.temperature_at((x, y)) * temperatureWeight + 1.0)/(temperatureWeight + 1.0)))
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
humidity['quantiles'] = {}
humidity['quantiles']['12'] = find_threshold_f(humidity['data'], 0.002,
world.ocean)
humidity['quantiles']['25'] = find_threshold_f(humidity['data'], 0.014,
world.ocean)
humidity['quantiles']['37'] = find_threshold_f(humidity['data'], 0.073,
world.ocean)
humidity['quantiles']['50'] = find_threshold_f(humidity['data'], 0.236,
world.ocean)
humidity['quantiles']['62'] = find_threshold_f(humidity['data'], 0.507,
world.ocean)
humidity['quantiles']['75'] = find_threshold_f(humidity['data'], 0.778,
world.ocean)
humidity['quantiles']['87'] = find_threshold_f(humidity['data'], 0.941,
world.ocean)
return humidity
def _calculate(world):
humidity = dict()
humidity['data'] = [[0 for x in xrange(world.width)] for y in
xrange(world.height)] # TODO: replace with numpy
for y in xrange(world.height):
for x in xrange(world.width):
humidity['data'][y][x] = world.precipitation['data'][y][x] + \
world.irrigation[y][x]
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
humidity['quantiles'] = {}
humidity['quantiles']['12'] = find_threshold_f(humidity['data'], 0.02,
world.ocean)
humidity['quantiles']['25'] = find_threshold_f(humidity['data'], 0.09,
world.ocean)
humidity['quantiles']['37'] = find_threshold_f(humidity['data'], 0.26,
world.ocean)
humidity['quantiles']['50'] = find_threshold_f(humidity['data'], 0.50,
world.ocean)
humidity['quantiles']['62'] = find_threshold_f(humidity['data'], 0.74,
world.ocean)
humidity['quantiles']['75'] = find_threshold_f(humidity['data'], 0.91,
world.ocean)
humidity['quantiles']['87'] = find_threshold_f(humidity['data'], 0.98,
world.ocean)
return humidity
def _calculate(world):
humidity = dict()
temperatureWeight = 2.3
precipitationWeight = 1.0
irrigationWeight = 3
humidity['data'] = numpy.zeros((world.height, world.width), dtype=float)
humidity['data'] = (((world.precipitation['data'] * precipitationWeight - world.irrigation * irrigationWeight) + 1) * ((world.temperature['data'] * temperatureWeight + 1) / (temperatureWeight + 1)))
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
humidity['quantiles'] = {}
humidity['quantiles']['12'] = find_threshold_f(humidity['data'], 0.002,
world.ocean)
humidity['quantiles']['25'] = find_threshold_f(humidity['data'], 0.014,
world.ocean)
humidity['quantiles']['37'] = find_threshold_f(humidity['data'], 0.073,
world.ocean)
humidity['quantiles']['50'] = find_threshold_f(humidity['data'], 0.236,
world.ocean)
humidity['quantiles']['62'] = find_threshold_f(humidity['data'], 0.507,
world.ocean)
humidity['quantiles']['75'] = find_threshold_f(humidity['data'], 0.778,
world.ocean)
humidity['quantiles']['87'] = find_threshold_f(humidity['data'], 0.941,
world.ocean)
return humidity
def initialize_ocean_and_thresholds(world, ocean_level=1.0):
"""
Calculate the ocean, the sea depth and the elevation thresholds
:param world: a world having elevation but not thresholds
:param ocean_level: the elevation representing the ocean level
:return: nothing, the world will be changed
"""
e = world.elevation['data']
ocean = fill_ocean(e, ocean_level)
hl = find_threshold_f(e, 0.10)
ml = find_threshold_f(e, 0.03)
e_th = [('sea', ocean_level),
('plain', hl),
('hill', ml),
('mountain', None)]
world.set_ocean(ocean)
world.set_elevation(e, e_th)
world.sea_depth = sea_depth(world, ocean_level)
def initialize_ocean_and_thresholds(world, ocean_level=1.0):
"""
Calculate the ocean, the sea depth and the elevation thresholds
:param world: a world having elevation but not thresholds
:param ocean_level: the elevation representing the ocean level
:return: nothing, the world will be changed
"""
e = world.layers['elevation'].data
ocean = fill_ocean(e, ocean_level)
hl = find_threshold_f(
e, 0.10) # the highest 10% of all (!) land are declared hills
ml = find_threshold_f(e, 0.03) # the highest 3% are declared mountains
e_th = [('sea', ocean_level), ('plain', hl), ('hill', ml),
('mountain', None)]
harmonize_ocean(ocean, e, ocean_level)
world.set_ocean(ocean)
world.set_elevation(e, e_th)
world.set_sea_depth(sea_depth(world, ocean_level))
def initialize_ocean_and_thresholds(world, ocean_level=1.0):
"""
Calculate the ocean, the sea depth and the elevation thresholds
:param world: a world having elevation but not thresholds
:param ocean_level: the elevation representing the ocean level
:return: nothing, the world will be changed
"""
e = world.layers['elevation'].data
ocean = fill_ocean(e, ocean_level)
hl = find_threshold_f(e, 0.10) # the highest 10% of all (!) land are declared hills
ml = find_threshold_f(e, 0.03) # the highest 3% are declared mountains
e_th = [('sea', ocean_level),
('plain', hl),
('hill', ml),
('mountain', None)]
harmonize_ocean(ocean, e, ocean_level)
world.ocean = ocean
world.elevation = (e, e_th)
world.sea_depth = sea_depth(world, ocean_level)
def execute(self, world, seed):
e = world.elevation['data']
ml = world.start_mountain_th()
ocean = world.ocean
t = self._calculate(world, seed, e, ml)
t_th = [('polar', find_threshold_f(t, 0.90, ocean)),
('alpine', find_threshold_f(t, 0.76, ocean)),
('boreal', find_threshold_f(t, 0.59, ocean)),
('cool', find_threshold_f(t, 0.38, ocean)),
('warm', find_threshold_f(t, 0.26, ocean)),
('subtropical', find_threshold_f(t, 0.14, ocean)),
('tropical', None)]
world.set_temperature(t, t_th)
def execute(self, world, seed):
e = world.layers['elevation'].data
ml = world.start_mountain_th(
) # returns how many percent of the world are mountains
ocean = world.layers['ocean'].data
t = self._calculate(world, seed, e, ml)
t_th = [('polar', find_threshold_f(t, world.temps[0], ocean)),
('alpine', find_threshold_f(t, world.temps[1], ocean)),
('boreal', find_threshold_f(t, world.temps[2], ocean)),
('cool', find_threshold_f(t, world.temps[3], ocean)),
('warm', find_threshold_f(t, world.temps[4], ocean)),
('subtropical', find_threshold_f(t, world.temps[5], ocean)),
('tropical', None)]
world.temperature = (t, t_th)
def execute(self, world, seed):
e = world.layers['elevation'].data
ml = world.start_mountain_th() # returns how many percent of the world are mountains
ocean = world.layers['ocean'].data
t = self._calculate(world, seed, e, ml)
t_th = [
('polar', find_threshold_f(t, world.temps[0], ocean)),
('alpine', find_threshold_f(t, world.temps[1], ocean)),
('boreal', find_threshold_f(t, world.temps[2], ocean)),
('cool', find_threshold_f(t, world.temps[3], ocean)),
('warm', find_threshold_f(t, world.temps[4], ocean)),
('subtropical', find_threshold_f(t, world.temps[5], ocean)),
('tropical', None)
]
world.temperature = (t, t_th)
def execute(self, world, seed):
e = world.elevation['data']
ml = world.start_mountain_th()
ocean = world.ocean
t = self._calculate(world, seed, e, ml)
t_th = [
('polar', find_threshold_f(t, 0.874, ocean)),
('alpine', find_threshold_f(t, 0.765, ocean)),
('boreal', find_threshold_f(t, 0.594, ocean)),
('cool', find_threshold_f(t, 0.439, ocean)),
('warm', find_threshold_f(t, 0.366, ocean)),
('subtropical', find_threshold_f(t, 0.124, ocean)),
('tropical', None)
]
world.set_temperature(t, t_th)
def _calculate(world):
humids = world.humids
precipitationWeight = 1.0
irrigationWeight = 3
data = numpy.zeros((world.height, world.width), dtype=float)
data = (world.layers['precipitation'].data * precipitationWeight - world.layers['irrigation'].data * irrigationWeight)/(precipitationWeight + irrigationWeight)
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
ocean = world.layers['ocean'].data
quantiles = {}
quantiles['12'] = find_threshold_f(data, humids[6], ocean)
quantiles['25'] = find_threshold_f(data, humids[5], ocean)
quantiles['37'] = find_threshold_f(data, humids[4], ocean)
quantiles['50'] = find_threshold_f(data, humids[3], ocean)
quantiles['62'] = find_threshold_f(data, humids[2], ocean)
quantiles['75'] = find_threshold_f(data, humids[1], ocean)
quantiles['87'] = find_threshold_f(data, humids[0], ocean)
return data, quantiles
def _calculate(world):
humids = world.humids
precipitationWeight = 1.0
irrigationWeight = 3
data = numpy.zeros((world.height, world.width), dtype=float)
data = (world.layers['precipitation'].data * precipitationWeight -
world.layers['irrigation'].data * irrigationWeight) / (
precipitationWeight + irrigationWeight)
# These were originally evenly spaced at 12.5% each but changing them
# to a bell curve produced better results
ocean = world.layers['ocean'].data
quantiles = {}
quantiles['12'] = find_threshold_f(data, humids[6], ocean)
quantiles['25'] = find_threshold_f(data, humids[5], ocean)
quantiles['37'] = find_threshold_f(data, humids[4], ocean)
quantiles['50'] = find_threshold_f(data, humids[3], ocean)
quantiles['62'] = find_threshold_f(data, humids[2], ocean)
quantiles['75'] = find_threshold_f(data, humids[1], ocean)
quantiles['87'] = find_threshold_f(data, humids[0], ocean)
return data, quantiles
def execute(self, world, seed):
perm = self._calculate(seed, world.width, world.height)
perm_th = [('low', find_threshold_f(perm, 0.75, world.ocean)),
('med', find_threshold_f(perm, 0.25, world.ocean)),
('hig', None)]
world.set_permeability(perm, perm_th)
def _watermap(world, n):
def droplet(world, pos, q, _watermap):
if q < 0:
return
x, y = pos
pos_elev = world.layers['elevation'].data[y, x] + _watermap[y, x]
lowers = []
min_higher = None
min_lower = None
# pos_min_higher = None # TODO: no longer used?
tot_lowers = 0
for p in world.tiles_around((x, y)): #TODO: switch to numpy
px, py = p
e = world.layers['elevation'].data[py, px] + _watermap[py, px]
if e < pos_elev:
dq = int(pos_elev - e) << 2
if min_lower is None or e < min_lower:
min_lower = e
if dq == 0:
dq = 1
lowers.append((dq, p))
tot_lowers += dq
else:
if min_higher is None or e > min_higher:
min_higher = e
# pos_min_higher = p
if lowers:
f = q / tot_lowers
for l in lowers:
s, p = l
if not world.is_ocean(p):
px, py = p
ql = f * s
# ql = q
going = ql > 0.05
_watermap[py, px] += ql
if going:
droplet(world, p, ql, _watermap)
else:
_watermap[y, x] += q
_watermap_data = numpy.zeros((world.height, world.width), dtype=float)
for i in range(n):
x, y = world.random_land(
) # will return None for x and y if no land exists
if x is not None and world.precipitations_at((x, y)) > 0:
droplet(world, (x, y), world.precipitations_at((x, y)),
_watermap_data)
ocean = world.layers['ocean'].data
thresholds = dict()
thresholds['creek'] = find_threshold_f(_watermap_data,
0.05,
ocean=ocean)
thresholds['river'] = find_threshold_f(_watermap_data,
0.02,
ocean=ocean)
thresholds['main river'] = find_threshold_f(_watermap_data,
0.007,
ocean=ocean)
return _watermap_data, thresholds
def _watermap(world, n):
def droplet(world, pos, q, _watermap):
if q < 0:
return
x, y = pos
pos_elev = world.layers['elevation'].data[y, x] + _watermap[y, x]
lowers = []
min_higher = None
min_lower = None
# pos_min_higher = None # TODO: no longer used?
tot_lowers = 0
for p in world.tiles_around((x, y)):#TODO: switch to numpy
px, py = p
e = world.layers['elevation'].data[py, px] + _watermap[py, px]
if e < pos_elev:
dq = int(pos_elev - e) << 2
if min_lower is None or e < min_lower:
min_lower = e
if dq == 0:
dq = 1
lowers.append((dq, p))
tot_lowers += dq
else:
if min_higher is None or e > min_higher:
min_higher = e
# pos_min_higher = p
if lowers:
f = q / tot_lowers
for l in lowers:
s, p = l
if not world.is_ocean(p):
px, py = p
ql = f * s
# ql = q
going = ql > 0.05
_watermap[py, px] += ql
if going:
droplet(world, p, ql, _watermap)
else:
_watermap[y, x] += q
_watermap_data = numpy.zeros((world.height, world.width), dtype=float)
# This indirectly calls the global rng.
# We want different implementations of _watermap
# and internally called functions (especially random_land)
# to show the same rng behaviour and not contamine the state of the global rng
# should anyone else happen to rely on it.
land_sample = world.random_land(n)
if land_sample[0] is not None:
for i in range(n):
x, y = land_sample[2*i], land_sample[2*i+1]
if world.precipitations_at((x, y)) > 0:
droplet(world, (x, y), world.precipitations_at((x, y)), _watermap_data)
ocean = world.layers['ocean'].data
thresholds = dict()
thresholds['creek'] = find_threshold_f(_watermap_data, 0.05, ocean=ocean)
thresholds['river'] = find_threshold_f(_watermap_data, 0.02, ocean=ocean)
thresholds['main river'] = find_threshold_f(_watermap_data, 0.007, ocean=ocean)
return _watermap_data, thresholds