Originally posted by **bmemlh** June 29, 2024
Hello everyone,
I have an error related to number of boundary points for the problem. If the boundary number is increased until approximately 100000, no error emerges. However, when the boundary number is slightly increased from this point an error message pops out, as shown below:
_
> ValueError Traceback (most recent call last)
> Cell In[13], line 10
> 8 bc_C_n2 = dde.icbc.NeumannBC(geomtime, lambda x:0.0, boundary5)
> 9 ic_C = dde.icbc.IC(geomtime, lambda x:C0/C_scale, initial, component=0)
> ---> 10 data = dde.data.TimePDE(geomtime, pde, [bc_C_d1, bc_C_d2, bc_C_d3, bc_C_n1, bc_C_n2, ic_C], num_domain=300000, num_boundary=110000, num_test=100000, num_initial=100000)
>
> File ~\anaconda3\lib\site-packages\deepxde\data\pde.py:322, in TimePDE.__init__(self, geometryxtime, pde, ic_bcs, num_domain, num_boundary, num_initial, train_distribution, anchors, exclusions, solution, num_test, auxiliary_var_function)
> 306 def __init__(
> 307 self,
> 308 geometryxtime,
> (...)
> 319 auxiliary_var_function=None,
> 320 ):
> 321 self.num_initial = num_initial
> --> 322 super().__init__(
> 323 geometryxtime,
> 324 pde,
> 325 ic_bcs,
> 326 num_domain,
> 327 num_boundary,
> 328 train_distribution=train_distribution,
> 329 anchors=anchors,
> 330 exclusions=exclusions,
> 331 solution=solution,
> 332 num_test=num_test,
> 333 auxiliary_var_function=auxiliary_var_function,
> 334 )
>
> File ~\anaconda3\lib\site-packages\deepxde\data\pde.py:127, in PDE.__init__(self, geometry, pde, bcs, num_domain, num_boundary, train_distribution, anchors, exclusions, solution, num_test, auxiliary_var_function)
> 124 self.test_x, self.test_y = None, None
> 125 self.train_aux_vars, self.test_aux_vars = None, None
> --> 127 self.train_next_batch()
> 128 self.test()
>
> File ~\anaconda3\lib\site-packages\deepxde\utils\internal.py:38, in run_if_all_none..decorator..wrapper(self, *args, **kwargs)
> 36 x = [getattr(self, a) for a in attr]
> 37 if all(i is None for i in x):
> ---> 38 return func(self, *args, **kwargs)
> 39 return x if len(x) > 1 else x[0]
>
> File ~\anaconda3\lib\site-packages\deepxde\data\pde.py:175, in PDE.train_next_batch(self, batch_size)
> 173 @run_if_all_none("train_x", "train_y", "train_aux_vars")
> 174 def train_next_batch(self, batch_size=None):
> --> 175 self.train_x_all = self.train_points()
> 176 self.bc_points() # Generate self.num_bcs and self.train_x_bc
> 177 if self.bcs and config.hvd is not None:
>
> File ~\anaconda3\lib\site-packages\deepxde\utils\internal.py:38, in run_if_all_none..decorator..wrapper(self, *args, **kwargs)
> 36 x = [getattr(self, a) for a in attr]
> 37 if all(i is None for i in x):
> ---> 38 return func(self, *args, **kwargs)
> 39 return x if len(x) > 1 else x[0]
>
> File ~\anaconda3\lib\site-packages\deepxde\data\pde.py:338, in TimePDE.train_points(self)
> 336 @run_if_all_none("train_x_all")
> 337 def train_points(self):
> --> 338 X = super().train_points()
> 339 if self.num_initial > 0:
> 340 if self.train_distribution == "uniform":
>
> File ~\anaconda3\lib\site-packages\deepxde\utils\internal.py:38, in run_if_all_none..decorator..wrapper(self, *args, **kwargs)
> 36 x = [getattr(self, a) for a in attr]
> 37 if all(i is None for i in x):
> ---> 38 return func(self, *args, **kwargs)
> 39 return x if len(x) > 1 else x[0]
>
> File ~\anaconda3\lib\site-packages\deepxde\data\pde.py:265, in PDE.train_points(self)
> 263 tmp = self.geom.uniform_boundary_points(self.num_boundary)
> 264 else:
> --> 265 tmp = self.geom.random_boundary_points(
> 266 self.num_boundary, random=self.train_distribution
> 267 )
> 268 X = np.vstack((tmp, X))
> 269 if self.anchors is not None:
>
> File ~\anaconda3\lib\site-packages\deepxde\geometry\timedomain.py:147, in GeometryXTime.random_boundary_points(self, n, random)
> 145 t = self.timedomain.random_points(n, random=random)
> 146 t = np.random.permutation(t)
> --> 147 return np.hstack((x, t))
>
> File <__array_function__ internals>:180, in hstack(*args, **kwargs)
>
> File ~\anaconda3\lib\site-packages\numpy\core\shape_base.py:345, in hstack(tup)
> 343 return _nx.concatenate(arrs, 0)
> 344 else:
> --> 345 return _nx.concatenate(arrs, 1)
>
> File <__array_function__ internals>:180, in concatenate(*args, **kwargs)
>
> ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 0, the array at index 0 has size 109999 and the array at index 1 has size 110000
_
In addition, when I assign the number of boundary points as 300000, the inconsistency between the matrices are varied as below:
> ValueError: all the input array dimensions for the concatenation axis must match exactly, but along dimension 0, the array at index 0 has size 299997 and the array at index 1 has size 300000
I don't have any idea why is this happening, please help me
Thank you!
Discussed in https://github.com/lululxvi/deepxde/discussions/1788