"""Base class for sparse matrice with a .data attribute

    subclasses must provide a _with_data() method that
    creates a new matrix with the same sparsity pattern
    as self but with a different data array

"""

__all__ = []

from base import spmatrix
from sputils import isscalarlike

#TODO implement all relevant operations
#use .data.__methods__() instead of /=, *=, etc.
class _data_matrix(spmatrix):
    def __init__(self):
        spmatrix.__init__(self)

    def _get_dtype(self):
        return self.data.dtype
    def _set_dtype(self,newtype):
        self.data.dtype = newtype
    dtype = property(fget=_get_dtype,fset=_set_dtype)

    def __abs__(self):
        return self._with_data(abs(self.data))

    def _real(self):
        return self._with_data(self.data.real)

    def _imag(self):
        return self._with_data(self.data.imag)

    def __neg__(self):
        return self._with_data(-self.data)

    def __imul__(self, other): #self *= other
        if isscalarlike(other):
            self.data *= other
            return self
        else:
            raise NotImplementedError

    def __itruediv__(self, other): #self /= other
        if isscalarlike(other):
            recip = 1.0 / other
            self.data *= recip
            return self
        else:
            raise NotImplementedError

    def astype(self, t):
        return self._with_data(self.data.astype(t))

    def conj(self):
        return self._with_data(self.data.conj())

    def copy(self):
        return self._with_data(self.data.copy(), copy=True)


    ###########################
    # Multiplication handlers #
    ###########################

    def _mul_scalar(self, other):
        return self._with_data(self.data * other)