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"""
Module for the creation of composite quantum objects via the tensor product.
"""
import numpy as np
import scipy.sparse as sp

from qutip.qobj import Qobj
from qutip.permute import reshuffle
import qutip.settings

def tensor(*args):
    """Calculates the tensor product of input operators.

    Parameters
    ----------
    args : array_like
        ``list`` or ``array`` of quantum objects for tensor product.

    Returns
    -------
    obj : qobj
        A composite quantum object.

    Examples
    --------
    >>> tensor([sigmax(), sigmax()])
    Quantum object: dims = [[2, 2], [2, 2]], \
shape = [4, 4], type = oper, isHerm = True
    Qobj data =
    [[ 0.+0.j  0.+0.j  0.+0.j  1.+0.j]
     [ 0.+0.j  0.+0.j  1.+0.j  0.+0.j]
     [ 0.+0.j  1.+0.j  0.+0.j  0.+0.j]
     [ 1.+0.j  0.+0.j  0.+0.j  0.+0.j]]
    """

    if not args:
        raise TypeError("Requires at least one input argument")

    if len(args) == 1 and isinstance(args[0], (list, np.ndarray)):
        # this is the case when tensor is called on the form:
        # tensor([q1, q2, q3, ...])
        qlist = list(args[0])

    elif len(args) == 1 and isinstance(args[0], Qobj):
        # tensor is called with a single Qobj as an argument, do nothing
        return args[0]

    else:
        # this is the case when tensor is called on the form:
        # tensor(q1, q2, q3, ...)
        qlist = list(args)

    # Grab constants from qlist
    i = 0
    scale = 1
    while i < len(qlist):
        if isinstance(qlist[i], (int, float, complex, np.int64)):
            scale *= qlist.pop(i)
        else:
            i += 1

    if not all([isinstance(q, Qobj) for q in qlist]):
        # raise error if one of the inputs is not a quantum object
        raise TypeError("One of inputs is not a quantum object")

    out = Qobj()

    if qlist[0].issuper:
        out.superrep = qlist[0].superrep
        if not all([q.superrep == out.superrep for q in qlist]):
            raise TypeError("In tensor products of superroperators, all must" +
                            "have the same representation")

    out.isherm = True
    for n, q in enumerate(qlist):
        if n == 0:
            out.data = q.data
            out.dims = q.dims
        else:
            out.data = sp.kron(out.data, q.data, format='csr')
            out.dims = [out.dims[0] + q.dims[0], out.dims[1] + q.dims[1]]

        out.isherm = out.isherm and q.isherm

    # Apply scaling factor due to constants
    out.data *= scale

    if not out.isherm:
        out._isherm = None

    return out.tidyup() if qutip.settings.auto_tidyup else out
    
def super_tensor(*args):
    """Calculates the tensor product of input superoperators, by tensoring
    together the underlying Hilbert spaces on which each vectorized operator
    acts.

    Parameters
    ----------
    args : array_like
        ``list`` or ``array`` of quantum objects with ``type="super"``.

    Returns
    -------
    obj : qobj
        A composite quantum object.

    """
    if isinstance(args[0], list):
        args = args[0]
        
    if not all(arg.type == "super" and arg.superrep == "super" for arg in args):
        raise TypeError(
            "super_tensor is only implemented for "
            "superrep='super'."
        )
        
    # Reshuffle the superoperators.
    shuffled_ops = list(map(reshuffle, args))
    
    # Tensor the result.
    shuffled_tensor = tensor(shuffled_ops)
    
    # Unshuffle and return.
    out = reshuffle(shuffled_tensor)
    out.superrep = args[0].superrep
    return out


@@ -2903,21 +2903,15 @@
 t = 
-list(
 args%5B0%5D
-)
 %0A%0A  
@@ -3186,234 +3186,12 @@
 t = 
-list(args)%0A%0A    # Grab constants from qlist%0A    i = 0%0A    scale = 1%0A    while i %3C len(qlist):%0A        if isinstance(qlist%5Bi%5D, (int, float, complex, np.int64)):%0A            scale *= qlist.pop(i)%0A        else:%0A            i += 1
+args
 %0A%0A  
@@ -4002,75 +4002,8 @@
 rm%0A%0A
-    # Apply scaling factor due to constants%0A    out.data *= scale%0A%0A
     

Revert "tensor: add back support for constants"