Broadcasting of Arrays and non-scalar but unit-sized numpy arrays

After 78bedd865, binary operations between a unit-sized numpy array and a PyOpenCL array ends up looping over each element of the CL array.

```python
import pyopencl as cl
import pyopencl.array
import numpy as np
ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

ary = cl.array.to_device(queue, np.random.rand(10))
np_ary = np.random.rand(1)
ary + np_ary
```

Namely, `pyopencl.Array.__add__` returns `NotImplemented` in this case and so python then asks the numpy array what to do. It appears numpy chooses to loop over each scalar element of the CL array and call its `__add__` method, and for some reason converts the unit-sized array into a scalar (which is why the single-element additions don't fail).

Could the `np.isscalar(other)` check be replaced (or augmented with) `other.size == 1`, perhaps?

Also, a few binary ops were missed in 78bedd865, like `__iadd__` and comparisons - was this intentional?

cc @kaushikcfd