Comments (8)
holl-
commented on August 22, 2024
1
Hi @ljbkusters, You can check out this related issue: #138
I'll post a custom extrapolation soon to make this easy.
Here is a workaround for 2.5.0. This sets the boundary values at the bottom center [30, 70] to 10 and 0 for the rest.
from phi.flow import *
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(0, {'x': ZERO_GRADIENT, 'y': (mask * 10, 0)}, x=100, y=100)
show(field.pad(t, 1))For future versions, I'll make it so you don't have to pad the mask beforehand.
from phiflow.
holl-
commented on August 22, 2024
1
Okay, here is an extrapolation class that can mix two extrapolations based on a mask tensor.
ConditionalExtrapolation
from typing import Tuple
from phi.flow import *
from phiml.math import extrapolation, Tensor, shape
from phiml.math.extrapolation import Extrapolation
class ConditionalExtrapolation(Extrapolation):
def __init__(self, mask: Tensor, true_ext, false_ext):
false_ext = extrapolation.as_extrapolation(false_ext)
true_ext = extrapolation.as_extrapolation(true_ext)
super().__init__(false_ext.pad_rank)
self.mask = mask
self.false_ext = false_ext
self.true_ext = true_ext
def to_dict(self) -> dict:
raise NotImplementedError
def spatial_gradient(self) -> 'Extrapolation':
return ConditionalExtrapolation(self.mask, self.false_ext.spatial_gradient(), self.true_ext.spatial_gradient())
def valid_outer_faces(self, dim) -> Tuple[bool, bool]:
true_lower, true_upper = self.false_ext.valid_outer_faces(dim)
false_lower, false_upper = self.true_ext.valid_outer_faces(dim)
return true_lower or false_lower, true_upper or false_upper
@property
def is_flexible(self) -> bool:
return self.false_ext.is_flexible or self.true_ext.is_flexible
def pad_values(self, value: Tensor, width: int, dim: str, upper_edge: bool, already_padded: dict = None, **kwargs) -> Tensor:
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad_values(value, width, dim, upper_edge, **kwargs)
p_true = self.true_ext.pad_values(value, width, dim, upper_edge, **kwargs)
return math.where(mask, p_true, p_false)
def pad(self, value: Tensor, widths: dict, already_padded: Optional[dict] = None, **kwargs) -> Tensor:
from phiml.math._trace import ShiftLinTracer
if isinstance(value, ShiftLinTracer):
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad(value, widths, **kwargs)
p_true = self.true_ext.pad(value, widths, **kwargs)
return p_true * mask + p_false * (1 - mask)
return Extrapolation.pad(self, value, widths, already_padded=already_padded, **kwargs)
def __abs__(self):
return ConditionalExtrapolation(self.mask, abs(self.false_ext), abs(self.true_ext))
def __neg__(self):
return ConditionalExtrapolation(self.mask, -self.false_ext, -self.true_ext)
def __add__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext + other, self.true_ext + other)
def __radd__(self, other):
return ConditionalExtrapolation(self.mask, other + self.false_ext, other + self.true_ext)
def __sub__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext - other, self.true_ext - other)
def __rsub__(self, other):
return ConditionalExtrapolation(self.mask, other - self.false_ext, other - self.true_ext)
def __mul__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext * other, self.true_ext * other)
def __rmul__(self, other):
return ConditionalExtrapolation(self.mask, other * self.false_ext, other * self.true_ext)
def __truediv__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext / other, self.true_ext / other)
def __rtruediv__(self, other):
return ConditionalExtrapolation(self.mask, other / self.false_ext, other / self.true_ext)Here is an example usage
x_pos = CenteredGrid(0, x=100, y=100).points['x'].y[0]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(Noise(), {'x': ZERO_GRADIENT, 'y': (ConditionalExtrapolation(mask, 10., ZERO_GRADIENT), ZERO_GRADIENT)}, x=100, y=100)
show(field.pad(t, 1))from phiflow.
ljbkusters
commented on August 22, 2024
Thank you for your response. I have tried your code but it seems to throw an error once diffuse.explicit is called. Luckily this can easily be fixed, and the example then seems to be working.
import phi
print(f"USED PHIFLOW VERSION: {phi.__version__}")
print(10*"=")
from phi.flow import *
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(0, {'x': ZERO_GRADIENT, 'y': (mask * 10, 0)}, x=100, y=100)
diffuse.explicit(t, 0.1, 0.1)[expand] terminal output
USED PHIFLOW VERSION: 2.5.0
==========
Traceback (most recent call last):
File "/root/projects/flow-simulation/heater_patch_test.py", line 10, in <module>
diffuse.explicit(t, 0.1, 0.1)
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/physics/diffuse.py", line 36, in explicit
delta = laplace(field, weights=amount) if 'vector' in shape(amount) else amount * laplace(field)
^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field_math.py", line 84, in laplace
padded_components = [pad(field, {dim: base_widths}) for dim in axes_names]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field_math.py", line 84, in <listcomp>
padded_components = [pad(field, {dim: base_widths}) for dim in axes_names]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field_math.py", line 522, in pad
data = math.pad(grid.values, widths, grid.extrapolation, bounds=grid.bounds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 869, in pad
result_padded = mode.pad(value, widths, **kwargs) if has_positive_widths else value
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1202, in pad
value = ext.pad(value, ext_widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 267, in pad
return Extrapolation.pad(self, value, widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 88, in pad
values.append(self.pad_values(value, width[False], dim, False, already_padded=already_padded, **kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 279, in pad_values
return math.expand(self.value, shape)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_magic_ops.py", line 343, in expand
combined = merge_shapes(value, dims) # check that existing sizes match
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_shape.py", line 1634, in merge_shapes
raise IncompatibleShapes(f"Cannot merge shapes {shapes} because dimension '{dim.name}' exists with different sizes.", *shapes)
phiml.math._shape.IncompatibleShapes: Cannot merge shapes [(xˢ=102), (xˢ=100, yˢ=1)] because dimension 'x' exists with different sizes.
I can remove the error by slicing x_pos
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0][1:-1]This is the temperature profile after 100 steps
for _ in range(100):
t = diffuse.explicit(t, 1., 0.1)
show(t)
That's neat! However this is not compatible with a parital GRADIENT_ZERO BC since that is apparently not settable with a mask. I'd be interested to see some more documentation on creating custom Extrapolation classes.
from phiflow.
ljbkusters
commented on August 22, 2024
I would just like to document my findings since using advect on this hacked boundary condition was giving me trouble as well. I managed to create an even more hacky version which, however, does implement a satisfactory simulation.
When using the code in the above snippet and adding an advect call I also get a shape incompatibility exception.
[expand] new code snippet
import phi
print(f"USED PHIFLOW VERSION: {phi.__version__}")
print(10*"=")
from phi.flow import *
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0][1:-1]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(0, {'x': ZERO_GRADIENT, 'y': (mask * 10, 0)}, x=100, y=100)
# diffuse heat into the domain
t = diffuse.explicit(t, 1., 0.1)
# create a velocity field to advect the tempearture
v = CenteredGrid(values=vec(x=1, y=0),
extrapolation={"x": ZERO_GRADIENT, "y": (0)},
resolution=t.resolution)
# advect the heat on the domain
t = advect.semi_lagrangian(t, v, 1)[expand] terminal output
USED PHIFLOW VERSION: 2.5.0
==========
Traceback (most recent call last):
File "/root/projects/flow-simulation/heater_patch_test.py", line 18, in <module>
t = advect.semi_lagrangian(t, v, 1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/physics/advect.py", line 159, in semi_lagrangian
interpolated = reduce_sample(field, lookup)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field.py", line 402, in reduce_sample
return field._sample(geometry, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_grid.py", line 247, in _sample
resampled_values = math.grid_sample(self.values, local_points, self.extrapolation, bounds=self.bounds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 947, in grid_sample
result = broadcast_op(functools.partial(_grid_sample, extrap=extrap, pad_kwargs=kwargs), [grid, coordinates])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 1002, in broadcast_op
return operation(*tensors)
^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 967, in _grid_sample
grid_padded = pad(grid, {dim: (1, 1) for dim in grid.shape.spatial.names}, extrap or e_.ZERO, **pad_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 869, in pad
result_padded = mode.pad(value, widths, **kwargs) if has_positive_widths else value
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1202, in pad
value = ext.pad(value, ext_widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 267, in pad
return Extrapolation.pad(self, value, widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 88, in pad
values.append(self.pad_values(value, width[False], dim, False, already_padded=already_padded, **kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 279, in pad_values
return math.expand(self.value, shape)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_magic_ops.py", line 343, in expand
combined = merge_shapes(value, dims) # check that existing sizes match
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_shape.py", line 1634, in merge_shapes
raise IncompatibleShapes(f"Cannot merge shapes {shapes} because dimension '{dim.name}' exists with different sizes.", *shapes)
phiml.math._shape.IncompatibleShapes: Cannot merge shapes [(xˢ=100), (xˢ=102, yˢ=1)] because dimension 'x' exists with different sizes.
Removing the slicing on x_pos changes the error but does not resolve the issue
[expand] new code snippet without slicing
import phi
print(f"USED PHIFLOW VERSION: {phi.__version__}")
print(10*"=")
from phi.flow import *
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(0, {'x': ZERO_GRADIENT, 'y': (mask * 10, 0)}, x=100, y=100)
# diffuse heat into the domain
# t = diffuse.explicit(t, 1., 0.1)
# create a velocity field to advect the tempearture
v = CenteredGrid(values=vec(x=1, y=0),
extrapolation={"x": ZERO_GRADIENT, "y": (0)},
resolution=t.resolution)
# advect the heat on the domain
t = advect.semi_lagrangian(t, v, 1)[expand] terminal output
USED PHIFLOW VERSION: 2.5.0
==========
Traceback (most recent call last):
File "/root/projects/flow-simulation/heater_patch_test.py", line 18, in <module>
t = advect.semi_lagrangian(t, v, 1)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/physics/advect.py", line 159, in semi_lagrangian
interpolated = reduce_sample(field, lookup)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field.py", line 402, in reduce_sample
return field._sample(geometry, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_grid.py", line 247, in _sample
resampled_values = math.grid_sample(self.values, local_points, self.extrapolation, bounds=self.bounds)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 947, in grid_sample
result = broadcast_op(functools.partial(_grid_sample, extrap=extrap, pad_kwargs=kwargs), [grid, coordinates])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 1002, in broadcast_op
return operation(*tensors)
^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 983, in _grid_sample
neighbors = _closest_grid_values(grid, coordinates, extrap or e_.ZERO, '_closest_', pad_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_ops.py", line 905, in _closest_grid_values
grid = extrap.pad(grid, non_copy_pad, **pad_kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1202, in pad
value = ext.pad(value, ext_widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 267, in pad
return Extrapolation.pad(self, value, widths, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 88, in pad
values.append(self.pad_values(value, width[False], dim, False, already_padded=already_padded, **kwargs))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 279, in pad_values
return math.expand(self.value, shape)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_magic_ops.py", line 343, in expand
combined = merge_shapes(value, dims) # check that existing sizes match
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/_shape.py", line 1634, in merge_shapes
raise IncompatibleShapes(f"Cannot merge shapes {shapes} because dimension '{dim.name}' exists with different sizes.", *shapes)
phiml.math._shape.IncompatibleShapes: Cannot merge shapes [(xˢ=102), (xˢ=100, yˢ=1)] because dimension 'x' exists with different sizes.
(phiflow) root@pc-luckus:~/projects/flow-simulation#
The only way I figured out how to circumvent this issue is by creating new grids and copying the t.values to this new grid on each diffuse and advect call where boundary conditions are set such that both functions are callable in conjunction.
import phi
print(f"USED PHIFLOW VERSION: {phi.__version__}")
print(10*"=")
from phi.flow import *
x_pos = field.pad(CenteredGrid(0, 0, x=100, y=100), 1).points['x'].y[0][1:-1]
mask = (30 < x_pos) & (x_pos < 70)
def diffusable_temperature_grid(values):
return CenteredGrid(values,
{'x': ZERO_GRADIENT, 'y': (mask * 10, 0)},
x=100, y=100)
def advectable_temperature_grid(values):
return CenteredGrid(values,
{'x': ZERO_GRADIENT, 'y': ZERO_GRADIENT},
x=100, y=100)
t = diffusable_temperature_grid(0)
v = CenteredGrid(values=vec(x=1, y=0),
extrapolation={"x": ZERO_GRADIENT, "y": (0)},
resolution=t.resolution)
for _ in range(100):
t = diffuse.explicit(t, 1., 0.1)
t = advectable_temperature_grid(t.values)
t = advect.semi_lagrangian(t, v, 0.1)
t = diffusable_temperature_grid(t.values)
show(t)This produces the following heat distribution:
Not very pretty to say the least, but working
from phiflow.
holl-
commented on August 22, 2024
I pushed the auto-pad of the extrapolation value to phiml/main
pip install --force-reinstall git+https://github.com/tum-pbs/PhiML.gitNow you can just write
x_pos = CenteredGrid(0, 0, x=100, y=100).points['x'].y[0]I'll add a way of mixing extrapolations on the same boundary face shortly, e.g. ZERO_GRADIENT + const
from phiflow.
ljbkusters
commented on August 22, 2024
Thank you, I will have a look at this tomorrow.
from phiflow.
ljbkusters
commented on August 22, 2024
Your custom class is throwing some errors on my side. First of all I see you forgot an import of typing.Optional. Secondly I was getting a TypeError on calling field.pad(t, 1).
TypeError: __main__.ConditionalExtrapolation.pad_values() got multiple values for keyword argument 'already_padded'
I realised that the command you provided to update phiml didn't actually use the latest version you mentioned (maybe updated to the initial 1.0.1 tag?). I had to clone the phiml repo myself and install it locally.
(for anyone else copying this code, might be good to edit the comment)
On calling diffuse.explicit(t, 1., 1.) I am now getting another error
TypeError: unsupported operand type(s) for +: '_ZeroGradient' and 'ConstantExtrapolation'
Full output
code
from typing import Tuple, Optional
from phi.flow import *
from phiml.math import extrapolation, Tensor, shape
from phiml.math.extrapolation import Extrapolation
class ConditionalExtrapolation(Extrapolation):
def __init__(self, mask: Tensor, true_ext, false_ext):
false_ext = extrapolation.as_extrapolation(false_ext)
true_ext = extrapolation.as_extrapolation(true_ext)
super().__init__(false_ext.pad_rank)
self.mask = mask
self.false_ext = false_ext
self.true_ext = true_ext
def to_dict(self) -> dict:
raise NotImplementedError
def spatial_gradient(self) -> 'Extrapolation':
return ConditionalExtrapolation(self.mask, self.false_ext.spatial_gradient(), self.true_ext.spatial_gradient())
def valid_outer_faces(self, dim) -> Tuple[bool, bool]:
true_lower, true_upper = self.false_ext.valid_outer_faces(dim)
false_lower, false_upper = self.true_ext.valid_outer_faces(dim)
return true_lower or false_lower, true_upper or false_upper
@property
def is_flexible(self) -> bool:
return self.false_ext.is_flexible or self.true_ext.is_flexible
def pad_values(self, value: Tensor, width: int, dim: str, upper_edge: bool, already_padded: dict = None, **kwargs) -> Tensor:
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad_values(value, width, dim, upper_edge, **kwargs)
p_true = self.true_ext.pad_values(value, width, dim, upper_edge, **kwargs)
return math.where(mask, p_true, p_false)
def pad(self, value: Tensor, widths: dict, already_padded: Optional[dict] = None, **kwargs) -> Tensor:
from phiml.math._trace import ShiftLinTracer
if isinstance(value, ShiftLinTracer):
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad(value, widths, **kwargs)
p_true = self.true_ext.pad(value, widths, **kwargs)
return p_true * mask + p_false * (1 - mask)
return Extrapolation.pad(self, value, widths, already_padded=already_padded, **kwargs)
def __abs__(self):
return ConditionalExtrapolation(self.mask, abs(self.false_ext), abs(self.true_ext))
def __neg__(self):
return ConditionalExtrapolation(self.mask, -self.false_ext, -self.true_ext)
def __add__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext + other, self.true_ext + other)
def __radd__(self, other):
return ConditionalExtrapolation(self.mask, other + self.false_ext, other + self.true_ext)
def __sub__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext - other, self.true_ext - other)
def __rsub__(self, other):
return ConditionalExtrapolation(self.mask, other - self.false_ext, other - self.true_ext)
def __mul__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext * other, self.true_ext * other)
def __rmul__(self, other):
return ConditionalExtrapolation(self.mask, other * self.false_ext, other * self.true_ext)
def __truediv__(self, other):
return ConditionalExtrapolation(self.mask, self.false_ext / other, self.true_ext / other)
def __rtruediv__(self, other):
return ConditionalExtrapolation(self.mask, other / self.false_ext, other / self.true_ext)
if __name__ == "__main__":
x_pos = CenteredGrid(0, x=100, y=100).points['x'].y[0]
mask = (30 < x_pos) & (x_pos < 70)
t = CenteredGrid(Noise(), {'x': ZERO_GRADIENT, 'y': (ConditionalExtrapolation(mask, 10., ZERO_GRADIENT), ZERO_GRADIENT)}, x=100, y=100)
show(field.pad(t, 1))
diffuse.explicit(t, 1., 1.)terminal output
Traceback (most recent call last):
File "/root/projects/flow-simulation/custom_extrapolation_heater_patch.py", line 87, in <module>
diffuse.explicit(t, 1., 1.)
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/physics/diffuse.py", line 36, in explicit
delta = laplace(field, weights=amount) if 'vector' in shape(amount) else amount * laplace(field)
^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field_math.py", line 86, in laplace
result_components = [sum([value * shift_ for value, shift_ in zip(values, shifted_component)]) / field.dx.vector[dim]**2 for shifted_component, dim in zip(shifted_components, axes_names)]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field_math.py", line 86, in <listcomp>
result_components = [sum([value * shift_ for value, shift_ in zip(values, shifted_component)]) / field.dx.vector[dim]**2 for shifted_component, dim in zip(shifted_components, axes_names)]
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field.py", line 262, in __add__
return self._op2(other, lambda d1, d2: d1 + d2)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field.py", line 307, in _op2
extrapolation_ = operator(self._extrapolation, other.extrapolation)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phi/field/_field.py", line 262, in <lambda>
return self._op2(other, lambda d1, d2: d1 + d2)
~~~^~~~
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1250, in __add__
return self._op2(other, lambda e1, e2: e1 + e2)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1276, in _op2
return combine_sides({k: operator(ext, other.ext[k]) for k, ext in self.ext.items()})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1276, in <dictcomp>
return combine_sides({k: operator(ext, other.ext[k]) for k, ext in self.ext.items()})
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/root/miniconda3/envs/phiflow/lib/python3.11/site-packages/phiml/math/extrapolation.py", line 1250, in <lambda>
return self._op2(other, lambda e1, e2: e1 + e2)
~~~^~~~
File "/root/projects/flow-simulation/custom_extrapolation_heater_patch.py", line 58, in __add__
return ConditionalExtrapolation(self.mask, self.false_ext + other, self.true_ext + other)
~~~~~~~~~~~~~~~^~~~~~~
File "/root/projects/flow-simulation/custom_extrapolation_heater_patch.py", line 61, in __radd__
return ConditionalExtrapolation(self.mask, other + self.false_ext, other + self.true_ext)
~~~~~~^~~~~~~~~~~~~~~
TypeError: unsupported operand type(s) for +: '_ZeroGradient' and 'ConstantExtrapolation'
Are you getting the same error?
from phiflow.
holl-
commented on August 22, 2024
Yes sorry, here is a fix for the extrapolation class:
ConditionalExtrapolation
from typing import Tuple, Optional, Callable
from phi.flow import *
from phiml.math import extrapolation, Tensor, shape
from phiml.math.extrapolation import Extrapolation
class ConditionalExtrapolation(Extrapolation):
def __init__(self, mask: Tensor, true_ext, false_ext):
true_ext = extrapolation.as_extrapolation(true_ext)
false_ext = extrapolation.as_extrapolation(false_ext)
super().__init__(false_ext.pad_rank)
self.mask = mask
self.false_ext = false_ext
self.true_ext = true_ext
def to_dict(self) -> dict:
raise NotImplementedError
def spatial_gradient(self) -> 'Extrapolation':
return ConditionalExtrapolation(self.mask, self.true_ext.spatial_gradient(), self.false_ext.spatial_gradient())
def valid_outer_faces(self, dim) -> Tuple[bool, bool]:
true_lower, true_upper = self.false_ext.valid_outer_faces(dim)
false_lower, false_upper = self.true_ext.valid_outer_faces(dim)
return true_lower or false_lower, true_upper or false_upper
@property
def is_flexible(self) -> bool:
return self.false_ext.is_flexible or self.true_ext.is_flexible
def pad_values(self, value: Tensor, width: int, dim: str, upper_edge: bool, already_padded: dict = None, **kwargs) -> Tensor:
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad_values(value, width, dim, upper_edge, **kwargs)
p_true = self.true_ext.pad_values(value, width, dim, upper_edge, **kwargs)
return math.where(mask, p_true, p_false)
def pad(self, value: Tensor, widths: dict, already_padded: Optional[dict] = None, **kwargs) -> Tensor:
from phiml.math._trace import ShiftLinTracer
if isinstance(value, ShiftLinTracer):
mask = self.mask
if already_padded:
mask = ZERO_GRADIENT.pad(mask, already_padded)
p_false = self.false_ext.pad(value, widths, **kwargs)
p_true = self.true_ext.pad(value, widths, **kwargs)
return p_true * mask + p_false * (1 - mask)
return Extrapolation.pad(self, value, widths, already_padded=already_padded, **kwargs)
def __abs__(self):
return ConditionalExtrapolation(self.mask, abs(self.true_ext), abs(self.false_ext))
def __neg__(self):
return ConditionalExtrapolation(self.mask, -self.true_ext, -self.false_ext)
def _op2(self, other, op: Callable):
if isinstance(other, ConditionalExtrapolation) and math.close(other.mask, self.mask):
return ConditionalExtrapolation(self.mask, op(self.true_ext, other.true_ext), op(self.false_ext, other.false_ext))
return ConditionalExtrapolation(self.mask, op(self.true_ext, other), op(self.false_ext, other))
def __add__(self, other):
return self._op2(other, lambda x, y: x + y)
def __radd__(self, other):
return self._op2(other, lambda y, x: x + y)
def __sub__(self, other):
return self._op2(other, lambda x, y: x - y)
def __rsub__(self, other):
return self._op2(other, lambda y, x: x - y)
def __mul__(self, other):
return self._op2(other, lambda x, y: x * y)
def __rmul__(self, other):
return self._op2(other, lambda y, x: x * y)
def __truediv__(self, other):
return self._op2(other, lambda x, y: x / y)
def __rtruediv__(self, other):
return self._op2(other, lambda y, x: x / y)To make it work with advection, you'll need to pull the latest phiml again.
from phiflow.
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from phiflow.