refactor: fixes for numpy-2.0 deprecation warnings, require numpy>=1.…

…20.3

.docs/Notebooks/zonebudget_example.py

@@ -111,7 +111,7 @@
 inyrbud = inyr.get_budget()
 
 names = ["FROM_RECHARGE"]
-rowidx = np.in1d(cmdbud["name"], names)
+rowidx = np.isin(cmdbud["name"], names)
 colidx = "ZONE_1"
 
 print(f"{cmdbud[rowidx][colidx][0]:,.1f} cubic meters/day")

README.md

@@ -35,7 +35,7 @@ Installation
 FloPy requires **Python** 3.8+ with: 
 
 ```
-numpy >=1.15.0,<2.0.0
+numpy >=1.20.3,<2.0.0
 matplotlib >=1.4.0
 pandas >=2.0.0
 ```

autotest/test_mf6.py

@@ -102,7 +102,7 @@ def write_head(
             ("kper", "i4"),
             ("pertim", "f8"),
             ("totim", "f8"),
-            ("text", "a16"),
+            ("text", "S16"),
             ("ncol", "i4"),
             ("nrow", "i4"),
             ("ilay", "i4"),

autotest/test_mp6.py

@@ -175,7 +175,7 @@ def test_get_destination_data(function_tmpdir, mp6_test_path):
         np.array(well_pthld)[["k", "i", "j"]].tolist(),
         dtype=starting_locs.dtype,
     )
-    assert np.all(np.in1d(starting_locs, pathline_locs))
+    assert np.all(np.isin(starting_locs, pathline_locs))
 
     # test writing a shapefile of endpoints
     epd.write_shapefile(

autotest/test_particledata.py

@@ -83,7 +83,7 @@ def test_particledata_structured_ctor_with_partlocs_as_list_of_tuples():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 1, 1, 0.5, 0.5, 0.5, 0.0, 0),
                 (0, 1, 2, 0.5, 0.5, 0.5, 0.0, 0),
@@ -102,7 +102,7 @@ def test_particledata_structured_ctor_with_partlocs_as_ndarray():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 1, 1, 0.5, 0.5, 0.5, 0.0, 0),
                 (0, 1, 2, 0.5, 0.5, 0.5, 0.0, 0),
@@ -121,7 +121,7 @@ def test_particledata_unstructured_ctor_with_partlocs_as_ndarray():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 0.5, 0.5, 0.5, 0.0, 0),
                 (1, 0.5, 0.5, 0.5, 0.0, 0),
@@ -141,7 +141,7 @@ def test_particledata_unstructured_ctor_with_partlocs_as_list():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 0.5, 0.5, 0.5, 0.0, 0),
                 (1, 0.5, 0.5, 0.5, 0.0, 0),
@@ -161,7 +161,7 @@ def test_particledata_unstructured_ctor_with_partlocs_as_ndarray():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 0.5, 0.5, 0.5, 0.0, 0),
                 (1, 0.5, 0.5, 0.5, 0.0, 0),
@@ -181,7 +181,7 @@ def test_particledata_structured_ctor_with_partlocs_as_list_of_lists():
     assert isinstance(data.particledata, pd.DataFrame)
     assert np.array_equal(
         data.particledata.to_records(index=False),
-        np.core.records.fromrecords(
+        np.rec.fromrecords(
             [
                 (0, 1, 1, 0.5, 0.5, 0.5, 0.0, 0),
                 (0, 1, 2, 0.5, 0.5, 0.5, 0.0, 0),
@@ -212,7 +212,7 @@ def test_particledata_to_prp_dis_1():
     )  # each coord should be a tuple (irpt, k, i, j, x, y, z)
 
     # expected
-    exp = np.core.records.fromrecords(
+    exp = np.rec.fromrecords(
         [
             (0, 1, 1, 0.5, 0.5, 0.5, 0.0, 0),
             (0, 1, 2, 0.5, 0.5, 0.5, 0.0, 0),

etc/environment.yml

@@ -6,8 +6,9 @@ dependencies:
 
   # required
   - python>=3.8
-  - numpy>=1.15.0,<2.0.0
+  - numpy>=1.20.3,<2.0.0
   - matplotlib>=1.4.0
+  - pandas>=2.0.0
 
   # lint
   - cffconvert
@@ -33,7 +34,6 @@ dependencies:
   # optional
   - affine
   - scipy
-  - pandas
   - netcdf4
   - pyshp
   - rasterio

flopy/modflow/mffhb.py

@@ -210,7 +210,7 @@ def __init__(
                 ds5 = ds5.to_records(index=False)
             # convert numpy array to a recarray
             if ds5.dtype != dtype:
-                ds5 = np.core.records.fromarrays(ds5.transpose(), dtype=dtype)
+                ds5 = np.rec.fromarrays(ds5.transpose(), dtype=dtype)
 
         # assign dataset 5
         self.ds5 = ds5
@@ -229,7 +229,7 @@ def __init__(
                 ds7 = ds7.to_records(index=False)
             # convert numpy array to a recarray
             if ds7.dtype != dtype:
-                ds7 = np.core.records.fromarrays(ds7.transpose(), dtype=dtype)
+                ds7 = np.rec.fromarrays(ds7.transpose(), dtype=dtype)
 
         # assign dataset 7
         self.ds7 = ds7

flopy/modflow/mfgage.py

@@ -131,7 +131,7 @@ def __init__(
             # convert gage_data to a recarray, if necessary
             if isinstance(gage_data, np.ndarray):
                 if not gage_data.dtype == dtype:
-                    gage_data = np.core.records.fromarrays(
+                    gage_data = np.rec.fromarrays(
                         gage_data.transpose(), dtype=dtype
                     )
             elif isinstance(gage_data, pd.DataFrame):

flopy/modflow/mfsfr2.py

@@ -1372,9 +1372,7 @@ def get_variable_by_stress_period(self, varname):
             all_data[inds, per] = self.segment_data[per][varname]
             dtype.append((f"{varname}{per}", float))
         isvar = all_data.sum(axis=1) != 0
-        ra = np.core.records.fromarrays(
-            all_data[isvar].transpose().copy(), dtype=dtype
-        )
+        ra = np.rec.fromarrays(all_data[isvar].transpose().copy(), dtype=dtype)
         segs = self.segment_data[0].nseg[isvar]
         isseg = np.array(
             [True if s in segs else False for s in self.reach_data.iseg]
@@ -1387,7 +1385,7 @@ def get_variable_by_stress_period(self, varname):
         return ra.view(np.recarray)
 
     def repair_outsegs(self):
-        isasegment = np.in1d(
+        isasegment = np.isin(
             self.segment_data[0].outseg, self.segment_data[0].nseg
         )
         isasegment = isasegment | (self.segment_data[0].outseg < 0)

flopy/modflow/mfstr.py

@@ -371,9 +371,7 @@ def __init__(
                     )
                     assert d.dtype == self.dtype, e
                 elif isinstance(d, np.ndarray):
-                    d = np.core.records.fromarrays(
-                        d.transpose(), dtype=self.dtype
-                    )
+                    d = np.rec.fromarrays(d.transpose(), dtype=self.dtype)
                 elif isinstance(d, int):
                     if model.verbose:
                         if d < 0:
@@ -404,9 +402,7 @@ def __init__(
                     )
                     assert d.dtype == self.dtype2, e
                 elif isinstance(d, np.ndarray):
-                    d = np.core.records.fromarrays(
-                        d.transpose(), dtype=self.dtype2
-                    )
+                    d = np.rec.fromarrays(d.transpose(), dtype=self.dtype2)
                 elif isinstance(d, int):
                     if model.verbose:
                         if d < 0:

flopy/plot/plotutil.py

@@ -2732,7 +2732,7 @@ def to_mp7_pathlines(
     data = data.to_records(index=False)
 
     # build mp7 format recarray
-    ret = np.core.records.fromarrays(
+    ret = np.rec.fromarrays(
         [
             data[seqn_key],
             data["iprp"],
@@ -2841,7 +2841,7 @@ def to_mp7_endpoints(
     endpts = endpts.to_records(index=False)
 
     # build mp7 format recarray
-    ret = np.core.records.fromarrays(
+    ret = np.rec.fromarrays(
         [
             endpts["sequencenumber"],
             endpts["iprp"],
@@ -2928,7 +2928,7 @@ def to_prt_pathlines(
     data = data.to_records(index=False)
 
     # build prt format recarray
-    ret = np.core.records.fromarrays(
+    ret = np.rec.fromarrays(
         [
             data["stressperiod"],
             data["timestep"],

flopy/utils/binaryfile.py

@@ -299,7 +299,7 @@ def binaryread_struct(file, vartype, shape=(1,), charlen=16):
         # find the number of bytes for one value
         numbytes = vartype(1).nbytes
         # find the number of values
-        nval = np.core.fromnumeric.prod(shape)
+        nval = np.prod(shape)
         fmt = str(nval) + fmt
         s = file.read(numbytes * nval)
         result = struct.unpack(fmt, s)
@@ -1138,7 +1138,7 @@ def _set_precision(self, precision="single"):
         h1dt = [
             ("kstp", "i4"),
             ("kper", "i4"),
-            ("text", "a16"),
+            ("text", "S16"),
             ("ncol", "i4"),
             ("nrow", "i4"),
             ("nlay", "i4"),
@@ -1161,10 +1161,10 @@ def _set_precision(self, precision="single"):
             ("delt", ffmt),
             ("pertim", ffmt),
             ("totim", ffmt),
-            ("modelnam", "a16"),
-            ("paknam", "a16"),
-            ("modelnam2", "a16"),
-            ("paknam2", "a16"),
+            ("modelnam", "S16"),
+            ("paknam", "S16"),
+            ("modelnam2", "S16"),
+            ("paknam2", "S16"),
         ]
         self.header1_dtype = np.dtype(h1dt)
         self.header2_dtype0 = np.dtype(h2dt0)

flopy/utils/datafile.py

@@ -43,7 +43,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kper", "i4"),
                         ("pertim", floattype),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("ncol", "i4"),
                         ("nrow", "i4"),
                         ("ilay", "i4"),
@@ -56,7 +56,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kper", "i4"),
                         ("pertim", floattype),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("ncol", "i4"),
                         ("nrow", "i4"),
                         ("ilay", "i4"),
@@ -69,7 +69,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kstp", "i4"),
                         ("kper", "i4"),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("ncol", "i4"),
                         ("nrow", "i4"),
                         ("ilay", "i4"),
@@ -82,7 +82,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kper", "i4"),
                         ("pertim", floattype),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("m1", "i4"),
                         ("m2", "i4"),
                         ("m3", "i4"),
@@ -95,7 +95,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kper", "i4"),
                         ("pertim", floattype),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("m1", "i4"),
                         ("m2", "i4"),
                         ("m3", "i4"),
@@ -108,7 +108,7 @@ def __init__(self, filetype=None, precision="single"):
                         ("kper", "i4"),
                         ("pertim", floattype),
                         ("totim", floattype),
-                        ("text", "a16"),
+                        ("text", "S16"),
                         ("m1", "i4"),
                         ("m2", "i4"),
                         ("m3", "i4"),

flopy/utils/modpathfile.py

@@ -124,12 +124,12 @@ def intersect(
                         cells = t
 
         cells = np.array(cells, dtype=raslice.dtype)
-        inds = np.in1d(raslice, cells)
+        inds = np.isin(raslice, cells)
         epdest = self._data[inds].copy().view(np.recarray)
 
         if to_recarray:
             # use particle ids to get the rest of the paths
-            inds = np.in1d(self._data["particleid"], epdest.particleid)
+            inds = np.isin(self._data["particleid"], epdest.particleid)
             series = self._data[inds].copy()
             series.sort(order=["particleid", "time"])
             series = series.view(np.recarray)
@@ -693,7 +693,7 @@ def get_destination_endpoint_data(self, dest_cells, source=False):
         dtype = np.dtype(dtype)
         dest_cells = np.array(dest_cells, dtype=dtype)
 
-        inds = np.in1d(raslice, dest_cells)
+        inds = np.isin(raslice, dest_cells)
         return data[inds].copy().view(np.recarray)
 
     def write_shapefile(

flopy/utils/recarray_utils.py

@@ -62,7 +62,7 @@ def ra_slice(ra, cols):
     --------
     >>> import numpy as np
     >>> from flopy.utils import ra_slice
-    >>> a = np.core.records.fromrecords([("a", 1, 1.1), ("b", 2, 2.1)])
+    >>> a = np.rec.fromrecords([("a", 1, 1.1), ("b", 2, 2.1)])
     >>> ra_slice(a, ['f0', 'f1'])
     rec.array([('a', 1), ('b', 2)],
               dtype=[('f0', '<U1'), ('f1', '<i4')])
@@ -75,7 +75,7 @@ def recarray(array, dtype):
     Convert a list of lists or tuples to a recarray.
 
     .. deprecated:: 3.5
-        Use numpy.core.records.fromrecords instead
+        Use numpy.rec.fromrecords instead
 
     Parameters
     ----------

flopy/utils/util_list.py

@@ -419,7 +419,7 @@ def __cast_ndarray(self, kper, d):
                 f"dtype len: {len(self.dtype)}"
             )
         try:
-            self.__data[kper] = np.core.records.fromarrays(
+            self.__data[kper] = np.rec.fromarrays(
                 d.transpose(), dtype=self.dtype
             )
         except Exception as e: