Change StateVector and CovarianceMatrix to simpler ndarray wrap

stonesoup/types/state.py

@@ -7,38 +7,44 @@
 from .base import Type
 
 
-class StateVector(Type, np.ndarray):
+class StateVector(np.ndarray):
     """State vector wrapper for :class:`numpy.ndarray`
 
     This class returns a view to a :class:`numpy.ndarray`, but ensures that
-    its initialised at a *Nx1* vector.
+    its initialised at a *Nx1* vector. It's called same as to
+    :func:`numpy.asarray`.
     """
-    value = Property(np.ndarray, doc='Array')
 
-    def __new__(cls, value, *args, **kwargs):
-        array = np.array(value)
+    def __new__(cls, *args, **kwargs):
+        array = np.asarray(*args, **kwargs)
         if not (array.ndim == 2 and array.shape[1] == 1):
             raise ValueError(
                 "state vector shape should be Nx1 dimensions: got {}".format(
                     array.shape))
         return array.view(cls)
 
+    def __array_wrap__(self, array):
+        return np.asarray(array)
 
-class CovarianceMatrix(Type, np.ndarray):
+
+class CovarianceMatrix(np.ndarray):
     """Covariance matrix wrapper for :class:`numpy.ndarray`.
 
     This class returns a view to a :class:`numpy.ndarray`, but ensures that
-    its initialised at a *NxN* matrix.
+    its initialised at a *NxN* matrix. It's called similar to
+    :func:`numpy.asarray`.
     """
-    value = Property(np.ndarray, doc='Array')
 
-    def __new__(cls, value, *args, **kwargs):
-        array = np.array(value)
+    def __new__(cls, *args, **kwargs):
+        array = np.asarray(*args, **kwargs)
         if not array.ndim == 2:
             raise ValueError("Covariance should have ndim of 2: got {}"
                              "".format(array.ndim))
         return array.view(cls)
 
+    def __array_wrap__(self, array):
+        return np.asarray(array)
+
 
 class State(Type):
     """State type.
@@ -49,7 +55,7 @@ class State(Type):
     state_vector = Property(StateVector, doc='State vector.')
 
     def __init__(self, state_vector, *args, **kwargs):
-        state_vector.view(StateVector)
+        state_vector = state_vector.view(StateVector)
         super().__init__(state_vector, *args, **kwargs)
 
     @property
@@ -68,7 +74,7 @@ class GaussianState(State):
     covar = Property(CovarianceMatrix, doc='Covariance matrix of state.')
 
     def __init__(self, state_vector, covar, *args, **kwargs):
-        covar.view(CovarianceMatrix)
+        covar = covar.view(CovarianceMatrix)
         super().__init__(state_vector, covar, *args, **kwargs)
         if self.state_vector.shape[0] != self.covar.shape[0]:
             raise ValueError(