From 3661e548c55cec10acbfb48eb5644ee8c03d0906 Mon Sep 17 00:00:00 2001
From: Dongdong Tian <seisman.info@gmail.com>
Date: Fri, 11 Oct 2024 21:37:25 +0800
Subject: [PATCH] Refactor vectors_to_arrays and deprecate the
 array_to_datetime function

---
 pygmt/clib/conversion.py | 12 ++++++++++++
 pygmt/clib/session.py    | 20 +++++---------------
 2 files changed, 17 insertions(+), 15 deletions(-)

diff --git a/pygmt/clib/conversion.py b/pygmt/clib/conversion.py
index 07f8756adcd..1db93768f51 100644
--- a/pygmt/clib/conversion.py
+++ b/pygmt/clib/conversion.py
@@ -224,6 +224,13 @@ def vectors_to_arrays(vectors: Sequence[Any]) -> list[np.ndarray]:
         else:
             vec_dtype = str(getattr(vector, "dtype", ""))
             array = np.ascontiguousarray(vector, dtype=dtypes.get(vec_dtype))
+        # Convert np.object_ to np.datetime64 or np.str_.
+        # If fails, then the array can't be recognized.
+        if array.dtype.type == np.object_:
+            try:
+                array = np.asarray(array, dtype=np.datetime64)
+            except ValueError:
+                array = np.asarray(array, dtype=np.str_)
         arrays.append(array)
     return arrays
 
@@ -313,6 +320,11 @@ def array_to_datetime(array: Sequence[Any]) -> np.ndarray:
 
     If the input array is not in legal datetime formats, raise a ValueError exception.
 
+    .. deprecated:: 0.14.0
+
+       The function is no longer used in the PyGMT project, but we keep this function
+       to document the supported datetime types.
+
     Parameters
     ----------
     array
diff --git a/pygmt/clib/session.py b/pygmt/clib/session.py
index 903edfc12c7..eea6e0f6efc 100644
--- a/pygmt/clib/session.py
+++ b/pygmt/clib/session.py
@@ -18,7 +18,6 @@
 import pandas as pd
 import xarray as xr
 from pygmt.clib.conversion import (
-    array_to_datetime,
     dataarray_to_matrix,
     sequence_to_ctypes_array,
     strings_to_ctypes_array,
@@ -854,22 +853,13 @@ def _check_dtype_and_dim(self, array, ndim):
         """
         # Check that the array has the given number of dimensions
         if array.ndim != ndim:
-            raise GMTInvalidInput(
-                f"Expected a numpy {ndim}-D array, got {array.ndim}-D."
-            )
+            msg = f"Expected a numpy {ndim}-D array, got {array.ndim}-D."
+            raise GMTInvalidInput(msg)
 
         # Check that the array has a valid/known data type
         if array.dtype.type not in DTYPES:
-            try:
-                if array.dtype.type is np.object_:
-                    # Try to convert unknown object type to np.datetime64
-                    array = array_to_datetime(array)
-                else:
-                    raise ValueError
-            except ValueError as e:
-                raise GMTInvalidInput(
-                    f"Unsupported numpy data type '{array.dtype.type}'."
-                ) from e
+            msg = f"Unsupported numpy data type '{array.dtype.type}'."
+            raise GMTInvalidInput(msg)
         return self[DTYPES[array.dtype.type]]
 
     def put_vector(self, dataset, column, vector):
@@ -917,7 +907,7 @@ def put_vector(self, dataset, column, vector):
         gmt_type = self._check_dtype_and_dim(vector, ndim=1)
         if gmt_type in {self["GMT_TEXT"], self["GMT_DATETIME"]}:
             if gmt_type == self["GMT_DATETIME"]:
-                vector = np.datetime_as_string(array_to_datetime(vector))
+                vector = np.datetime_as_string(vector)
             vector_pointer = strings_to_ctypes_array(vector)
         else:
             vector_pointer = vector.ctypes.data_as(ctp.c_void_p)