lh solved (#55)

pina/span.py

@@ -3,6 +3,7 @@ import torch
 
 from .location import Location
 from .label_tensor import LabelTensor
+from .utils import torch_lhs
 
 
 class Span(Location):
@@ -41,10 +42,7 @@ class Span(Location):
         elif mode == 'grid':
             pts = torch.linspace(0, 1, n).reshape(-1, 1)
         elif mode == 'lh' or mode == 'latin':
-            from scipy.stats import qmc
-            sampler = qmc.LatinHypercube(d=dim)
-            pts = sampler.random(n)
-            pts = torch.from_numpy(pts)
+            pts = torch_lhs(n, dim)
 
         pts *= bounds[:, 1] - bounds[:, 0]
         pts += bounds[:, 0]
@@ -83,7 +81,7 @@ class Span(Location):
             return result
 
         def _Nd_sampler(n, mode, variables):
-            """ Sample ll the variables together """
+            """ Sample all the variables together """
             pairs = [(k, v) for k, v in self.range_.items() if k in variables]
             keys, values = map(list, zip(*pairs))
             bounds = torch.tensor(values)
@@ -107,7 +105,7 @@ class Span(Location):
 
         if mode in ['grid', 'chebyshev']:
             return _1d_sampler(n, mode, variables)
-        elif mode in ['random', 'lhs']:
+        elif mode in ['random', 'lh', 'latin']:
             return _Nd_sampler(n, mode, variables)
         else:
             raise ValueError(f'mode={mode} is not valid.')