[MBsysPy][Algebra] Addition and substraction

MBsysC/mbs_interface/MBsysPy/mbs_algebra.py

@@ -98,103 +98,69 @@ def scalar_product(v1, v2, size_4=True):
 
 
 def vector_sum(v1, v2, vres=None, size_4=True):
-    """Compute and return the sum of 2 vectors with first index is 1.
+    """Compute and return the sum of 2 vectors.
 
-    The vectors have unused index 0.
+    The shape of the vector differs according to size_4.
 
 
     Parameters
     ----------
-    v1 : list or numpy.ndarray
-        Vector with first element unused.
-    v2 : list or numpy.ndarray
-        Vector with first element unused.
-    vres : list or numpy.ndarray, optional
-        Vector containing the result if not None.
+    v1 : numpy.ndarray
+        First vector of the addition.
+    v2 : numpy.ndarray
+        Second vector of the addition.
+    vres : numpy.ndarray, optional
+        Vector to store the result of v1+v2. It is allocated if not provided.
         default: None
     size_4 : bool, optional
         True if vectors have a size of 4.
         default: True.
 
-    Raises
-    ------
-    ValueError
-        If v1 or v2 is not a 1-dim array of size 4 if size_4 is True.
-    TypeError
-        If v1 or v2 is not a numpy.ndarray or a list.
-
     Returns
     -------
-    v_sum : numpy.ndarray
+    vres : numpy.ndarray
         Sum of v1 and v2.
 
     """
-    v1, mat1 = __get_index_0_matrix__(v1, size_4)
-    v2, mat2 = __get_index_0_matrix__(v2, size_4)
-    if mat1 or mat2:
-        raise ValueError('Vectors must be passed as argument for addition')
-    v_sum = v1 + v2
-    if vres is not None:
-        if len(np.shape(vres)) == 1:
-            vres[1:] = v_sum
-        else:
-            if (vres.shape)[0] == 1:
-                vres[0, 1:] = v_sum
-            else:
-                vres[1:, 0] = v_sum
-    else:
-        v_sum = np.append(v_sum.shape[0], v_sum)
-        return v_sum
+    if vres is None:
+        vres = np.zeros(3 + size_4)
+
+    vres[size_4:] = v1[size_4:] + v2[size_4:]
+
+    return vres
 
 
 def vector_diff(v1, v2, vres=None, size_4=True):
-    """Compute and return the substraction of 2 vectors with first index is 1.
+    """Compute and return the substraction of 2 vectors.
+
+    The shape of the vector differs according to size_4.
 
-    The vectors have unused index 0.
 
 
     Parameters
     ----------
-    v1 : list or numpy.ndarray
-        Vector with first element unused.
+    v1 : numpy.ndarray
+        First vector of the substraction.
     v2 : list or numpy.ndarray
-        Vector with first element unused.
-    vres : list or numpy.ndarray, optional
-        Vector containing the result if not None.
+        Vector to be substracted.
+    vres : numpy.ndarray, optional
+        Vector to store the result of v1-v2. It is allocated if not provided.
         default: None
     size_4 : bool, optional
-        True if vectors have a size of 4.
+        True if vectors have a size of 4 (the first index being disregarded).
         default: True.
 
-    Raises
-    ------
-    ValueError
-        If v1 or v2 is not a 1-dim array of size 4 if size_4 is True.
-    TypeError
-        If v1 or v2 is not a numpy.ndarray or a list.
-
     Returns
     -------
-    v_diff : numpy.ndarray
+    vres : numpy.ndarray
         Substraction of v1 and v2 (v1 - v2).
-
     """
-    v1, mat1 = __get_index_0_matrix__(v1, size_4)
-    v2, mat2 = __get_index_0_matrix__(v2, size_4)
-    if mat1 or mat2:
-        raise ValueError('Vectors must be passed as argument for substraction')
-    v_diff = v1 - v2
-    if vres is not None:
-        if len(np.shape(vres)) == 1:
-            vres[1:] = v_diff
-        else:
-            if (vres.shape)[0] == 1:
-                vres[0, 1:] = v_diff
-            else:
-                vres[1:, 0] = v_diff
-    else:
-        v_diff = np.append(v_diff.shape[0], v_diff)
-        return v_diff
+    if vres is None:
+        vres = np.zeros(3 + size_4)
+
+    vres[size_4:] = v1[size_4:] - v2[size_4:]
+
+    return vres
 
 
 def cross_product(v1, v2, vres=None, size_4=True):