Support 1-D/2-D numpy arrays with longlong and ulonglong dtype

[seisman]

See #2848 (comment) for context. np.longlong and np.ulonglong are valid numpy dtypes and are almost the same as np.int64/np.uint64 (xref: https://numpy.org/devdocs/reference/arrays.scalars.html#numpy.int64), although there are technical differences (xref: numpy/numpy#12264).

As shown below, a np.longlong array is shown with the int64 dtype, but x.dtype.type is still np.longlong, which means it can't be recognized by _check_dtype_and_dim.

In [1]: import numpy as np

In [2]: x = np.array([1, 2, 3], dtype=np.longlong)

In [3]: x.dtype
Out[3]: dtype('int64')

In [4]: x.dtype.type
Out[4]: numpy.longlong

In [5]: from pygmt.clib import Session

In [6]: with Session() as lib:
   ...:     lib._check_dtype_and_dim(x, ndim=1)
   ...:
---------------------------------------------------------------------------
GMTInvalidInput                           Traceback (most recent call last)
Cell In[6], line 2
      1 with Session() as lib:
----> 2     lib._check_dtype_and_dim(x, ndim=1)

File ~/OSS/gmt/pygmt/pygmt/clib/session.py:938, in Session._check_dtype_and_dim(self, array, ndim)
    936 if (dtype := array.dtype.type) not in valid_dtypes:
    937     msg = f"Unsupported numpy data type '{dtype}'."
--> 938     raise GMTInvalidInput(msg)
    939 return self[DTYPES[dtype]]

GMTInvalidInput: Unsupported numpy data type '<class 'numpy.longlong'>'.

This PR adds support for np.longlong and np.ulonglong by mapping them to GMT_LONG and GMT_ULONG respectively.

Need to wait for #3565 first so that the newly supported dtypes are tested.

These newly supported dtypes are automatically tested after #3565.