diff --git a/hypermat/_math/__init__.py b/hypermat/_math/__init__.py
deleted file mode 100644
index 9340520..0000000
--- a/hypermat/_math/__init__.py
+++ /dev/null
@@ -1 +0,0 @@
-from ._tensor import *
diff --git a/hypermat/_math/_tensor.py b/hypermat/_math/_tensor.py
deleted file mode 100644
index b878695..0000000
--- a/hypermat/_math/_tensor.py
+++ /dev/null
@@ -1,73 +0,0 @@
-"""
-    HyperMAT
-    Created August 2023
-    Copyright (C) Mohamed ZAARAOUI
-
-    This program is free software; you can redistribute it and/or
-    modify it under the terms of the GNU General Public License
-    as published by the Free Software Foundation; either version 2
-    of the License, or (at your option) any later version.
-
-    This program is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
-
-    You should have received a copy of the GNU General Public License
-    along with this program; if not, write to the Free Software
-    Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
-"""
-
-####################### - بــسم الله الرحمــان الرحيــم - #####################
-
-import numpy as np
-
-__all__ = ('trace', 'det', 'like', 'transpose', 'identity', 'dot', 'mul', 'inv',
-           'dya', 'zeros')
-
-def trace(_a):
-    """Provides tensor trace"""
-    return np.einsum('...ii', _a)
-
-def det(_a):
-    """Provides tensor determinant"""
-    return np.linalg.det(_a)
-
-def inv(_a):
-    """Provides tensor inverse"""
-    return np.linalg.pinv(_a)
-
-def like(_b, _a):
-    """Broadcasts tensor to a given shape"""
-    return np.broadcast_to(_b, _a.shape)
-
-def transpose(_a):
-    """Provides tensor transpose"""
-    return np.einsum('...ij->...ji', _a, optimize=True)
-
-def identity(_a):
-    """Provides tensor identity"""
-    return like(np.eye(3), _a)
-
-def zeros(shape):
-    """Null tensor"""
-    return np.zeros(shape)
-
-def dot(_a, _b):
-    """Calculates tensor dot product"""
-    return np.einsum('...ij,...jk->...ik', _a, _b, optimize=True)
-
-def mul(_a, _b, mode=1):
-    """Calculates tensor product"""
-    if mode:
-        _c = np.einsum('...ij,...ij->...ij', _a, _b, optimize=True)
-    else:
-        _c = np.einsum('ij...,ij...->ij...', _a, _b, optimize=True)
-    return _c
-
-def dya(_a, _b, seq):
-    """Calculates tensor dyadic product"""
-    i = seq.index(',')
-    path = f'...{seq[:i]},...{seq[i+1:]}->...ijkl'
-    _c = np.einsum(path, _a, _b, optimize=True)
-    return _c