change file name

qutip/core/metrics.py

@@ -9,7 +9,7 @@
            'hellinger_dist', 'hilbert_dist', 'average_gate_fidelity',
            'process_fidelity', 'unitarity', 'dnorm']
 
-from ..backend import np
+from ..numpy_backend import np
 from scipy import linalg as la
 import scipy.sparse as sp
 from .superop_reps import to_choi, _to_superpauli, to_super, kraus_to_choi

qutip/entropy.py

@@ -2,15 +2,14 @@
            'concurrence', 'entropy_conditional', 'entangling_power',
            'entropy_relative']
 
-from .backend import np
-from math import e
+from .numpy_backend import np
 from .partial_transpose import partial_transpose
 from . import (ptrace, tensor, sigmay, ket2dm,
                expand_operator)
 from .core import data as _data
 
 
-def entropy_vn(rho, base=e, sparse=False):
+def entropy_vn(rho, base=np.e, sparse=False):
     """
     Von-Neumann entropy of density matrix
 
@@ -150,7 +149,7 @@ def negativity(rho, subsys, method='tracenorm', logarithmic=False):
         return N
 
 
-def entropy_mutual(rho, selA, selB, base=e, sparse=False):
+def entropy_mutual(rho, selA, selB, base=np.e, sparse=False):
     """
     Calculates the mutual information S(A:B) between selection
     components of a system density matrix.
@@ -192,7 +191,7 @@ def entropy_mutual(rho, selA, selB, base=e, sparse=False):
     return out
 
 
-def entropy_relative(rho, sigma, base=e, sparse=False, tol=1e-12):
+def entropy_relative(rho, sigma, base=np.e, sparse=False, tol=1e-12):
     """
     Calculates the relative entropy S(rho||sigma) between two density
     matrices.
@@ -288,7 +287,7 @@ def entropy_relative(rho, sigma, base=e, sparse=False, tol=1e-12):
     return np.maximum(0, S)
 
 
-def entropy_conditional(rho, selB, base=e, sparse=False):
+def entropy_conditional(rho, selB, base=np.e, sparse=False):
     """
     Calculates the conditional entropy :math:`S(A|B)=S(A,B)-S(B)`
     of a selected density matrix component.

qutip/backend.py → qutip/numpy_backend.py

@@ -10,4 +10,4 @@ def __getattr__(self, name):
         return getattr(backend, name)
 
 # Initialize the numpy backend
-np = NumpyBackend()
+np = NumpyBackend()