ctypes - numpy array with no shape?

Question

I am using a python wrapper to call functions of a c++ dll library. A ctype is returned by the dll library, which I convert to numpy array

score = np.ctypeslib.as_array(score,1) 

however, the array has no shape?

score
>>> array(-0.019486344729027664)

score.shape
>>> ()

score[0]
>>> IndexError: too many indices for array

How can I extract a double from the score array?

Thank you.

Svend

That is a shape; it's shape (), aka 0-dimensional. – Kiona

thanks a lot. is there any way to extract the double inside the array? I guess that is the question in the end – Svend

You can use float(score). But how are you ending up with a 0-d array, i.e. what's the initial type and value of score? – Occident

Why are you calling np.ctypeslib.as_array on this thing? 1 isn't a valid shape, and if there's only one value, why do you want to use np.ctypeslib.as_array to retrieve it? Why not go through the normal ctypes interface? – Kiona

The shape parameter is only used for a pointer, so we know score isn't initially a pointer, else passing shape=1 would be an error. If you pass as_array a scalar such as c_double(-0.19), it stores an __array_interface__ property on the c_double type with shape=(). However, in NumPy 1.8.2 this actually creates an array with shape=(1,). Maybe in older versions it creates a scalar 'array'. – Occident

Answer 1

You can access the data inside a 0-dimensional array via indexing [()].

For example, score[()] will retrieve the underlying data in your array.

The idiom is in fact consistent:

# x, y, z are 0-dim, 1-dim, 2-dim respectively
x = np.array(1)
y = np.array([1, 2, 3])
z = np.array([[1, 2, 3], [4, 5, 6]])

# use 0-dim, 1-dim, 2-dim tuple indexers respectively
res_x = x[()]      # 1
res_y = y[(1,)]    # 2
res_z = z[(1, 2)]  # 6

Tuples seem unnatural because you don't need to use them explicitly for the 1d and 2d cases, i.e. y[1] and z[1, 2] suffice. That option isn't available for the 0-dim case, so use the zero-length tuple.

Stereograph

what is this sorcery ? – Chandelle

() is a tuple with the length of 0. It's exactly the same operation as the good old array[(3, 4)]. – Wiredraw

Alternatively, for arrays with a single value, array.item() will return a scalar regardless of how dimensions it has. np.array(0).item() == np.atleast_3d(0).item(). – Logorrhea