Add the option to specify a seed for the Random sampling method

AUTHORS.md

@@ -14,6 +14,7 @@ SMT has been developed thanks to contributions from:
 * Alexandre Thouvenot
 * Andres Lopez Lopera
 * Antoine Averland
+* Enrico Stragiotti
 * Emile Roux
 * Ewout ter Hoeven
 * Florent Vergnes

smt/sampling_methods/random.py

@@ -12,6 +12,25 @@
 
 
 class Random(ScaledSamplingMethod):
+    def _initialize(self, **kwargs):
+        self.options.declare(
+            "random_state",
+            types=(type(None), int, np.random.RandomState),
+            desc="Numpy RandomState object or seed number which controls random draws",
+        )
+
+        # Update options values passed by the user here to get 'random_state' option
+        self.options.update(kwargs)
+
+        # RandomState is and has to be initialized once at constructor time,
+        # not in _compute to avoid yielding the same dataset again and again
+        if isinstance(self.options["random_state"], np.random.RandomState):
+            self.random_state = self.options["random_state"]
+        elif isinstance(self.options["random_state"], int):
+            self.random_state = np.random.RandomState(self.options["random_state"])
+        else:
+            self.random_state = np.random.RandomState()
+
     def _compute(self, nt):
         """
         Implemented by sampling methods to compute the requested number of sampling points.
@@ -30,4 +49,6 @@ def _compute(self, nt):
         """
         xlimits = self.options["xlimits"]
         nx = xlimits.shape[0]
-        return np.random.rand(nt, nx)
+        # Create a Generator object with a specified seed (np.random.rand(nt, nx) is being deprecated)
+        rng = np.random.default_rng(self.random_state)
+        return rng.random((nt, nx))