[MRG] as_float_array doesn't copy

The function `as_float_array` doesn't copy as expected when the matrix was created with `sparse_random_matrix`. This code should fix that.

Example:
```python
import numpy as np
import scipy.sparse as sp

from sklearn.random_projection import sparse_random_matrix
from sklearn.utils import as_float_array

matrices = [
    np.matrix(np.arange(5)),
    sp.csc_matrix(np.arange(5)).todense(),
    sparse_random_matrix(10, 10, density=0.10).todense(),
]

for M in matrices:
    print type(M) # <class 'numpy.matrixlib.defmatrix.matrix'>

    N = as_float_array(M, copy=True)
    print type(N) # <type 'numpy.ndarray'>

    print np.isnan(M).any() # False
    N[0, 0] = np.nan
    print np.isnan(N).any() # True
    # False in the first and the second case
    # True in the third...
    print np.isnan(M).any()
    assert np.isnan(M).any() == False
```