Heaviside hotfix (#87)

* revert to torch heaviside, as the derivative is not implemented

* force the value at x=0 in the numpy implementation

Author: ktangsali

modulus/sym/utils/sympy/numpy_printer.py

@@ -181,7 +181,9 @@ def _max_np(x, axis=None):
     return return_value
 
 
-def _heaviside_np(x, x2=0.5):
+def _heaviside_np(x, x2=0):
+    # force x2 to 0
+    x2 = 0
     return np.heaviside(x, x2)
 
 

modulus/sym/utils/sympy/torch_printer.py

@@ -72,9 +72,8 @@ def _where_torch(conditions, x, y):
     return torch.where(conditions, x, y)
 
 
-def _heaviside_torch(x, values=0.5):
-    values = torch.tensor([values]).to(x.device)
-    return torch.heaviside(x, values)
+def _heaviside_torch(x, values=0):
+    return torch.maximum(torch.sign(x), torch.zeros(1, device=x.device))
 
 
 def _sqrt_torch(x):