class Add(object):
offset = xs.variable(description=('offset * dt added every time step '
'to profile u'))
u_diff = xs.variable(group='diff', intent='out')
def run_step(self, dt):
self.u_diff = self.offset * dt
def gen_properties(externs, modules, modulestoconsider = None, globaldependencies = {}, propertymapping = {}):
""" Generate the properties of the xs Process class that will run the lpyfile """
import numpy as np
externs = externs.difference(predefined_variables)
if not modulestoconsider is None:
mmodules = dict()
for name, pnames in modules.items():
if name in modulestoconsider:
mmodules[name] = pnames
modules = mmodules
properties = {}
properties['modules'] = modules
for m, v in modules.items():
properties[m] = xs.index(dims=m)
for p in v:
pname = m+'_'+p
properties[pname] = propertymapping.get(pname,
xs.global_ref(pname, intent='in')
if pname in globaldependencies else
xs.variable( dims=m, intent='out', encoding={'dtype': np.float}))
properties['globaldependencies'] = globaldependencies
properties['externs'] = externs
for e in externs:
properties[e] = xs.variable()
return properties
class TotalVerticalMotion:
"""Sum up all vertical motions of bedrock and topographic surface,
respectively.
Vertical motions may result from external forcing, erosion and/or
feedback of erosion on tectonics (isostasy).
"""
bedrock_upward_vars = xs.group('bedrock_upward')
surface_upward_vars = xs.group('surface_upward')
surface_downward_vars = xs.group('surface_downward')
bedrock_upward = xs.variable(
dims=('y', 'x'),
intent='out',
description='bedrock motion in upward direction'
)
surface_upward = xs.variable(
dims=('y', 'x'),
intent='out',
description='topographic surface motion in upward direction'
)
def run_step(self):
self.bedrock_upward = sum(self.bedrock_upward_vars)
self.surface_upward = (sum(self.surface_upward_vars) -
sum(self.surface_downward_vars))
class DifferentialLinearDiffusion(LinearDiffusion):
"""Hillslope differential erosion by diffusion.
Diffusivity may vary depending on whether the topographic surface
is bare rock or covered by a soil (sediment) layer.
"""
diffusivity_bedrock = xs.variable(
dims=[(), ('y', 'x')],
description='bedrock diffusivity'
)
diffusivity_soil = xs.variable(
dims=[(), ('y', 'x')],
description='soil (sediment) diffusivity'
)
diffusivity = xs.variable(
dims=('y', 'x'),
intent='out',
description='differential diffusivity'
)
soil_thickness = xs.foreign(UniformSedimentLayer, 'thickness')
def run_step(self):
self.diffusivity = np.where(self.soil_thickness <= 0.,
self.diffusivity_bedrock,
self.diffusivity_soil)
super(DifferentialLinearDiffusion, self).run_step()
class SourcePoint(object):
"""Source point for quantity `u`.
The location of the source point is adjusted to coincide with
the nearest node the grid.
"""
loc = xs.variable(description='source location')
flux = xs.variable(description='source flux')
x = xs.foreign(UniformGrid1D, 'x')
u_source = xs.variable(dims='x', intent='out', group='u_vars')
@property
def nearest_node(self):
idx = np.abs(self.x - self.loc).argmin()
return idx
@property
def source_rate(self):
src_array = np.zeros_like(self.x)
src_array[self.nearest_node] = self.flux
return src_array
def run_step(self, dt):
self.u_source = self.source_rate * dt
class SourcePoint:
"""Source point for quantity `u`.
The location of the source point is adjusted to coincide with
the nearest node the grid.
"""
loc = xs.variable(description="source location")
flux = xs.variable(description="source flux")
x = xs.foreign(UniformGrid1D, "x")
u_source = xs.variable(dims="x", intent="out", groups="u_vars")
@property
def nearest_node(self):
idx = np.abs(self.x - self.loc).argmin()
return idx
@property
def source_rate(self):
src_array = np.zeros_like(self.x)
src_array[self.nearest_node] = self.flux
return src_array
@xs.runtime(args="step_delta")
def run_step(self, dt):
self.u_source = self.source_rate * dt
class LinearDiffusion:
"""Hillslope erosion by diffusion."""
diffusivity = xs.variable(
dims=[(), ('y', 'x')],
description='diffusivity (transport coefficient)'
)
erosion = xs.variable(
dims=('y', 'x'),
intent='out',
groups='erosion'
)
shape = xs.foreign(UniformRectilinearGrid2D, 'shape')
elevation = xs.foreign(SurfaceToErode, 'elevation')
fs_context = xs.foreign(FastscapelibContext, 'context')
def run_step(self):
kd = np.broadcast_to(self.diffusivity, self.shape).flatten()
self.fs_context["kd"] = kd
# we don't use the kdsed fastscapelib-fortran feature directly
# see class DifferentialLinearDiffusion
self.fs_context["kdsed"] = -1.
# bypass fastscapelib-fortran global state
self.fs_context["h"] = self.elevation.flatten()
fs.diffusion()
erosion_flat = self.elevation.ravel() - self.fs_context["h"]
self.erosion = erosion_flat.reshape(self.shape)
class TwoBlocksUplift:
"""Set two blocks separated by a clip plane, with different
uplift rates.
"""
x_position = xs.variable(
description='position of the clip plane along the x-axis')
rate_left = xs.variable(description='uplift rate of the left block')
rate_right = xs.variable(description='uplift rate of the right block')
shape = xs.foreign(UniformRectilinearGrid2D, 'shape')
x = xs.foreign(UniformRectilinearGrid2D, 'x')
# TODO: group=['bedrock_forcing_upward', 'surface_forcing_upward']
# see https://github.com/benbovy/xarray-simlab/issues/64
uplift = xs.variable(dims=[(), ('y', 'x')],
intent='out',
group='any_forcing_upward',
description='imposed vertical uplift')
def initialize(self):
# align clip plane position
self._x_idx = np.argmax(self.x > self.x_position)
@xs.runtime(args='step_delta')
def run_step(self, dt):
rate = np.full(self.shape, self.rate_left)
rate[:, self._x_idx:] = self.rate_right
self.uplift = rate * dt
class TotalVerticalMotion:
"""Sum up all vertical motions of bedrock and topographic surface,
respectively.
Vertical motions may result from external forcing, erosion and/or
feedback of erosion on tectonics (isostasy).
"""
#TODO: remove any_upward_vars
# see https://github.com/benbovy/xarray-simlab/issues/64
any_upward_vars = xs.group('any_upward')
bedrock_upward_vars = xs.group('bedrock_upward')
surface_upward_vars = xs.group('surface_upward')
surface_downward_vars = xs.group('surface_downward')
bedrock_upward = xs.variable(
dims=('y', 'x'),
intent='out',
description='bedrock motion in upward direction')
surface_upward = xs.variable(
dims=('y', 'x'),
intent='out',
description='topographic surface motion in upward direction')
def run_step(self):
sum_any = sum(self.any_upward_vars)
self.bedrock_upward = sum_any + sum(self.bedrock_upward_vars)
self.surface_upward = (sum_any + sum(self.surface_upward_vars) -
sum(self.surface_downward_vars))
class FlowAccumulator:
"""Accumulate the flow from upstream to downstream."""
runoff = xs.variable(
dims=[(), ('y', 'x')],
description='surface runoff (source term) per area unit')
shape = xs.foreign(UniformRectilinearGrid2D, 'shape')
cell_area = xs.foreign(UniformRectilinearGrid2D, 'cell_area')
stack = xs.foreign(FlowRouter, 'stack')
nb_receivers = xs.foreign(FlowRouter, 'nb_receivers')
receivers = xs.foreign(FlowRouter, 'receivers')
weights = xs.foreign(FlowRouter, 'weights')
flowacc = xs.variable(
dims=('y', 'x'),
intent='out',
description='flow accumulation from up to downstream')
def run_step(self):
field = np.broadcast_to(self.runoff * self.cell_area,
self.shape).flatten()
if self.receivers.ndim == 1:
_flow_accumulate_sd(field, self.stack, self.receivers)
else:
_flow_accumulate_mfd(field, self.stack, self.nb_receivers,
self.receivers, self.weights)
self.flowacc = field.reshape(self.shape)
class BorderBoundary:
status = xs.variable(dims=[(), 'border'],
description='node status at borders')
border = xs.variable(dims='border',
intent='out',
description='4-border boundaries coordinate')
border_status = xs.variable(
dims='border',
intent='out',
description='node status at the 4-border boundaries')
fs_context = xs.foreign(FastscapelibContext, 'context')
ibc = xs.variable(intent='out',
description='boundary code used by fastscapelib-fortran')
def initialize(self):
self.border = np.array(['left', 'right', 'top', 'bottom'])
self.border_status = np.broadcast_to(self.status, 4)
# convert to fastscapelib-fortran ibc code
arr_bc = np.array(
[1 if st == 'fixed_value' else 0 for st in self.border_status])
# different border order
self.ibc = sum(arr_bc * np.array([1, 100, 10, 1000]))
self.fs_context.ibc = self.ibc
class ExampleProcess:
"""A process with complete interface for testing."""
in_var = xs.variable(dims=["x", ("x", "y")], description="input variable")
out_var = xs.variable(groups="example_group", intent="out")
inout_var = xs.variable(intent="inout", converter=int)
od_var = xs.on_demand()
obj_var = xs.any_object(description="arbitrary object")
in_foreign_var = xs.foreign(SomeProcess, "some_var")
in_foreign_var2 = xs.foreign(AnotherProcess, "some_var")
out_foreign_var = xs.foreign(AnotherProcess, "another_var", intent="out")
in_foreign_od_var = xs.foreign(SomeProcess, "some_od_var")
in_global_var = xs.global_ref("some_global_var")
out_global_var = xs.global_ref("another_global_var", intent="out")
group_var = xs.group("some_group")
group_dict_var = xs.group_dict("some_group")
other_attrib = attr.attrib(init=False, repr=False)
other_attr = "this is not a xsimlab variable attribute"
@od_var.compute
def compute_od_var(self):
return 0
class ProfileZ:
"""Compute the evolution of the elevation (z) profile"""
h_vars = xs.group(
"h_vars"
) #allows for multiple processes influencing; say diffusion and subsidence
z = xs.variable(dims="x",
intent="inout",
description="surface elevation z",
attrs={"units": "m"})
br = xs.variable(dims=[(), "x"],
intent="in",
description="bedrock_elevation",
attrs={"units": "m"})
h = xs.variable(dims="x",
intent="inout",
description="sed_thickness",
attrs={"units": "m"})
def run_step(self):
#self._delta_br = sum((br for br in self.br_vars))
self._delta_h = sum((h for h in self.h_vars))
def finalize_step(self):
#self.br += self._delta_br #update bedrock surface
self.h += self._delta_h #update sediment thickness
self.z = self.br + self.h #add sediment to bedrock to get topo elev.
class DifferentialStreamPowerChannel(StreamPowerChannel):
"""Stream-Power channel (differential) erosion.
Channel incision coefficient may vary depending on whether the
topographic surface is bare rock or covered by a soil (sediment)
layer.
"""
k_coef_bedrock = xs.variable(
dims=[(), ('y', 'x')],
description='bedrock channel incision coefficient')
k_coef_soil = xs.variable(
dims=[(), ('y', 'x')],
description='soil (sediment) channel incision coefficient')
k_coef = xs.variable(
dims=('y', 'x'),
intent='out',
description='differential channel incision coefficient')
active_layer_thickness = xs.foreign(UniformSedimentLayer, 'thickness')
def run_step(self):
self.k_coef = np.where(self.active_layer_thickness <= 0.,
self.k_coef_bedrock, self.k_coef_soil)
super(DifferentialStreamPowerChannel, self).run_step()
class VariableTwoBlockUplift:
"""compute diferent linear gradient uplift rate along the x or y axis
for two blocks separated by a clip plane"""
x_position = xsimlab.variable(
description='position of the clip plane along the x-axis')
uplift_rate_left = xsimlab.variable(
description='uplift rate of the left box')
uplift_rate_right = xsimlab.variable(
description='uplift rate of the right box')
gradient_left = xsimlab.variable(
description='gradient of the left box uplift')
gradient_right = xsimlab.variable(
description='gradient of the right box uplift')
grid_shape = xsimlab.foreign(RasterGrid2D, 'shape')
rate = xsimlab.foreign(BlockUplift, 'rate', intent='out')
def run_step(self):
mask = np.ones((self.grid_shape[0], self.grid_shape[1]))
mask[:, 0:self.x_position] = self.uplift_rate_left
mask[:, self.x_position:self.grid_shape[1]] = self.uplift_rate_right
gradient = np.ones((self.grid_shape[1]))
gradient[0:self.x_position] = np.linspace(self.gradient_left, 1,
self.x_position)
gradient[self.x_position:self.grid_shape[1]] = np.linspace(
self.gradient_right, 1,
np.abs(self.grid_shape[1] - self.x_position))
self.rate = mask * gradient
class Foo:
v_bool_nan = xs.variable(dims="x", intent="out")
# suppress nan values by setting an explicit fill value:
v_bool = xs.variable(dims="x", intent="out", encoding={"fill_value": None})
def initialize(self):
self.v_bool_nan = [True, False]
self.v_bool = [True, False]
class Roll(object):
shift = xs.variable(description=('shift profile by a nb. of points'),
attrs={'units': 'unitless'})
u = xs.foreign(Profile, 'u')
u_diff = xs.variable(dims='x', group='diff', intent='out')
def run_step(self, *args):
self.u_diff = np.roll(self.u, self.shift) - self.u
class Add:
offset = xs.variable(description=("offset * dt added every time step "
"to profile u"))
u_diff = xs.variable(groups="diff", intent="out")
@xs.runtime(args="step_delta")
def run_step(self, dt):
self.u_diff = self.offset * dt
class FixedGrid(UniformGrid1D):
spacing = xs.variable(description="uniform spacing", intent="out")
length = xs.variable(description="total length", intent="out")
def initialize(self):
self.spacing = 0.01
self.length = 1.0
super(FixedGrid, self).initialize()
class WithPlaceholder:
"""My process
{{attributes}}
"""
var1 = xs.variable(dims="x", description="a variable")
var2 = xs.variable()
class Foo:
v1 = xs.variable(intent="out")
v2 = xs.variable()
def initialize(self):
self.v1 = 0
def run_step(self):
self.v1 = 1
class UniformGrid1D:
"""Create a 1-dimensional, equally spaced grid."""
spacing = xs.variable(description="uniform spacing", static=True)
length = xs.variable(description="total length", static=True)
x = xs.index(dims="x")
def initialize(self):
self.x = np.arange(0, self.length, self.spacing)
class P2:
var = xs.foreign(P1, "var")
cached_var = xs.foreign(P1, "cached_var")
view = xs.variable(dims="x", intent="out")
cached_view = xs.variable(dims="x", intent="out")
def run_step(self):
self.view = self.var
self.cached_view = self.cached_var
class UniformGrid1D(object):
"""Create a 1-dimensional, equally spaced grid."""
spacing = xs.variable(description='uniform spacing')
length = xs.variable(description='total length')
x = xs.variable(dims='x', intent='out')
def initialize(self):
self.x = np.arange(0, self.length, self.spacing)
class P:
in_var = xs.variable(dims=[(), "x"])
out_var = xs.variable(dims=[(), "x"], intent="out")
idx_var = xs.index(dims="x")
def initialize(self):
self.idx_var = [0, 1]
def run_step(self):
self.out_var = self.in_var * 2
class InitUGauss:
"""Initialize `u` profile using a Gaussian pulse."""
loc = xs.variable(description="location of initial pulse", static=True)
scale = xs.variable(description="scale of initial pulse", static=True)
x = xs.foreign(UniformGrid1D, "x")
u = xs.foreign(ProfileU, "u", intent="out")
def initialize(self):
self.u = np.exp(-1 / self.scale ** 2 * (self.x - self.loc) ** 2)
class InitUGauss(object):
"""Initialize `u` profile using a Gaussian pulse."""
loc = xs.variable(description='location of initial pulse')
scale = xs.variable(description='scale of initial pulse')
x = xs.foreign(UniformGrid1D, 'x')
u = xs.foreign(ProfileU, 'u', intent='out')
def initialize(self):
self.u = np.exp(-1 / self.scale**2 * (self.x - self.loc)**2)
class StreamPowerChannel(ChannelErosion):
"""Stream-Power channel erosion."""
k_coef = xs.variable(dims=[(), ('y', 'x')],
description='bedrock channel incision coefficient')
area_exp = xs.variable(description='drainage area exponent')
slope_exp = xs.variable(description='slope exponent')
shape = xs.foreign(UniformRectilinearGrid2D, 'shape')
elevation = xs.foreign(FlowRouter, 'elevation')
receivers = xs.foreign(FlowRouter, 'receivers')
flowacc = xs.foreign(FlowAccumulator, 'flowacc')
fs_context = xs.foreign(FastscapelibContext, 'context')
chi = xs.on_demand(dims=('y', 'x'),
description='integrated drainage area (chi)')
def _set_g_in_context(self):
# transport/deposition feature is exposed in subclasses
self.fs_context.g1 = 0.
self.fs_context.g2 = 0.
def run_step(self):
kf = np.broadcast_to(self.k_coef, self.shape).flatten()
self.fs_context.kf = kf
# we don't use kfsed fastscapelib-fortran feature directly
self.fs_context.kfsed = -1.
self._set_g_in_context()
self.fs_context.m = self.area_exp
self.fs_context.n = self.slope_exp
# bypass fastscapelib_fortran global state
self.fs_context.h = self.elevation.flatten()
# TODO: https://github.com/fastscape-lem/fastscapelib-fortran/pull/25
# this has no effect yet.
self.fs_context.a = self.flowacc.flatten()
if self.receivers.ndim == 1:
fs.streampowerlawsingleflowdirection()
else:
fs.streampowerlaw()
erosion_flat = self.elevation.ravel() - self.fs_context.h
self.erosion = erosion_flat.reshape(self.shape)
@chi.compute
def _chi(self):
chi_arr = np.empty_like(self.elevation, dtype='d')
self.fs_context.copychi(chi_arr.ravel())
return chi_arr
class P:
in_var = xs.variable()
out_var = xs.variable(intent="out")
od_var = xs.on_demand()
def run_step(self):
self.out_var = self.in_var * 2
@od_var.compute
def _dummy(self):
return None
class P:
var = xs.variable(
dims=[(), "x"],
description="a variable",
default=0,
groups=["g1", "g2"],
static=True,
attrs={"units": "m"},
encoding={"fill_value": -1},
)
var2 = xs.variable()
