use builtin python types instead of the numpy alias (pydata#4170)

* replace np.bool with the python type

* replace np.int with the python type

* replace np.complex with the builtin python type

* replace np.float with the builtin python type

xarray/coding/times.py

@@ -158,7 +158,7 @@ def decode_cf_datetime(num_dates, units, calendar=None, use_cftime=None):
             dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)
         except (KeyError, OutOfBoundsDatetime, OverflowError):
             dates = _decode_datetime_with_cftime(
-                flat_num_dates.astype(np.float), units, calendar
+                flat_num_dates.astype(float), units, calendar
             )
 
             if (
@@ -179,7 +179,7 @@ def decode_cf_datetime(num_dates, units, calendar=None, use_cftime=None):
                     dates = cftime_to_nptime(dates)
     elif use_cftime:
         dates = _decode_datetime_with_cftime(
-            flat_num_dates.astype(np.float), units, calendar
+            flat_num_dates.astype(float), units, calendar
         )
     else:
         dates = _decode_datetime_with_pandas(flat_num_dates, units, calendar)

xarray/conventions.py

@@ -116,7 +116,7 @@ def maybe_default_fill_value(var):
 
 def maybe_encode_bools(var):
     if (
-        (var.dtype == np.bool)
+        (var.dtype == bool)
         and ("dtype" not in var.encoding)
         and ("dtype" not in var.attrs)
     ):

xarray/core/common.py

@@ -1481,7 +1481,7 @@ def zeros_like(other, dtype: DTypeLike = None):
     * lat      (lat) int64 1 2
     * lon      (lon) int64 0 1 2
 
-    >>> xr.zeros_like(x, dtype=np.float)
+    >>> xr.zeros_like(x, dtype=float)
     <xarray.DataArray (lat: 2, lon: 3)>
     array([[0., 0., 0.],
            [0., 0., 0.]])

xarray/core/formatting.py

@@ -140,7 +140,7 @@ def format_item(x, timedelta_format=None, quote_strings=True):
         return format_timedelta(x, timedelta_format=timedelta_format)
     elif isinstance(x, (str, bytes)):
         return repr(x) if quote_strings else x
-    elif isinstance(x, (float, np.float)):
+    elif isinstance(x, (float, np.float_)):
         return f"{x:.4}"
     else:
         return str(x)

xarray/tests/test_backends.py

@@ -885,7 +885,7 @@ def test_roundtrip_endian(self):
                 "x": np.arange(3, 10, dtype=">i2"),
                 "y": np.arange(3, 20, dtype="<i4"),
                 "z": np.arange(3, 30, dtype="=i8"),
-                "w": ("x", np.arange(3, 10, dtype=np.float)),
+                "w": ("x", np.arange(3, 10, dtype=float)),
             }
         )
 

xarray/tests/test_conventions.py

@@ -32,10 +32,8 @@ class TestBoolTypeArray:
     def test_booltype_array(self):
         x = np.array([1, 0, 1, 1, 0], dtype="i1")
         bx = conventions.BoolTypeArray(x)
-        assert bx.dtype == np.bool
-        assert_array_equal(
-            bx, np.array([True, False, True, True, False], dtype=np.bool)
-        )
+        assert bx.dtype == bool
+        assert_array_equal(bx, np.array([True, False, True, True, False], dtype=bool))
 
 
 class TestNativeEndiannessArray:

xarray/tests/test_dataarray.py

@@ -1503,7 +1503,7 @@ def test_reindex_regressions(self):
             da.reindex(time=time2)
 
         # regression test for #736, reindex can not change complex nums dtype
-        x = np.array([1, 2, 3], dtype=np.complex)
+        x = np.array([1, 2, 3], dtype=complex)
         x = DataArray(x, coords=[[0.1, 0.2, 0.3]])
         y = DataArray([2, 5, 6, 7, 8], coords=[[-1.1, 0.21, 0.31, 0.41, 0.51]])
         re_dtype = x.reindex_like(y, method="pad").dtype

xarray/tests/test_dataset.py

@@ -98,8 +98,8 @@ def create_append_test_data(seed=None):
     datetime_var_to_append = np.array(
         ["2019-01-04", "2019-01-05"], dtype="datetime64[s]"
     )
-    bool_var = np.array([True, False, True], dtype=np.bool)
-    bool_var_to_append = np.array([False, True], dtype=np.bool)
+    bool_var = np.array([True, False, True], dtype=bool)
+    bool_var_to_append = np.array([False, True], dtype=bool)
 
     ds = xr.Dataset(
         data_vars={
@@ -2943,12 +2943,12 @@ def test_unstack_fill_value(self):
         ds = ds.isel(x=[0, 2, 3, 4]).set_index(index=["x", "y"])
         # test fill_value
         actual = ds.unstack("index", fill_value=-1)
-        expected = ds.unstack("index").fillna(-1).astype(np.int)
-        assert actual["var"].dtype == np.int
+        expected = ds.unstack("index").fillna(-1).astype(int)
+        assert actual["var"].dtype == int
         assert_equal(actual, expected)
 
         actual = ds["var"].unstack("index", fill_value=-1)
-        expected = ds["var"].unstack("index").fillna(-1).astype(np.int)
+        expected = ds["var"].unstack("index").fillna(-1).astype(int)
         assert actual.equals(expected)
 
     @requires_sparse

xarray/tests/test_dtypes.py

@@ -7,8 +7,8 @@
 @pytest.mark.parametrize(
     "args, expected",
     [
-        ([np.bool], np.bool),
-        ([np.bool, np.string_], np.object_),
+        ([bool], bool),
+        ([bool, np.string_], np.object_),
         ([np.float32, np.float64], np.float64),
         ([np.float32, np.string_], np.object_),
         ([np.unicode_, np.int64], np.object_),

xarray/tests/test_plot.py

@@ -149,7 +149,7 @@ def test1d(self):
             (self.darray[:, 0, 0] + 1j).plot()
 
     def test_1d_bool(self):
-        xr.ones_like(self.darray[:, 0, 0], dtype=np.bool).plot()
+        xr.ones_like(self.darray[:, 0, 0], dtype=bool).plot()
 
     def test_1d_x_y_kw(self):
         z = np.arange(10)
@@ -1037,7 +1037,7 @@ def test_1d_raises_valueerror(self):
             self.plotfunc(self.darray[0, :])
 
     def test_bool(self):
-        xr.ones_like(self.darray, dtype=np.bool).plot()
+        xr.ones_like(self.darray, dtype=bool).plot()
 
     def test_complex_raises_typeerror(self):
         with raises_regex(TypeError, "complex128"):