Merge pull request #176 from GeoStat-Framework/develop

Release v1.3.1

CHANGELOG.md

@@ -2,6 +2,16 @@
 
 All notable changes to **GSTools** will be documented in this file.
 
+## [1.3.1] - Pure Pink - 2021-06
+
+### Enhancements
+- Standalone use of Field class [#166](https://github.com/GeoStat-Framework/GSTools/issues/166)
+- add social badges in README [#169](https://github.com/GeoStat-Framework/GSTools/issues/169), [#170](https://github.com/GeoStat-Framework/GSTools/issues/170)
+
+### Bugfixes
+- use `oldest-supported-numpy` to build cython extensions [#165](https://github.com/GeoStat-Framework/GSTools/pull/165)
+
+
 ## [1.3.0] - Pure Pink - 2021-04
 
 ### Topics
@@ -263,7 +273,8 @@ All notable changes to **GSTools** will be documented in this file.
 First release of GSTools.
 
 
-[Unreleased]: https://github.com/GeoStat-Framework/gstools/compare/v1.3.0...HEAD
+[Unreleased]: https://github.com/GeoStat-Framework/gstools/compare/v1.3.1...HEAD
+[1.3.1]: https://github.com/GeoStat-Framework/gstools/compare/v1.3.0...v1.3.1
 [1.3.0]: https://github.com/GeoStat-Framework/gstools/compare/v1.2.1...v1.3.0
 [1.2.1]: https://github.com/GeoStat-Framework/gstools/compare/v1.2.0...v1.2.1
 [1.2.0]: https://github.com/GeoStat-Framework/gstools/compare/v1.1.1...v1.2.0

README.md

@@ -12,6 +12,13 @@
 <img src="https://raw.githubusercontent.com/GeoStat-Framework/GSTools/master/docs/source/pics/gstools.png" alt="GSTools-LOGO" width="251px"/>
 </p>
 
+<p align="center"><b>Get in Touch!</b></p>
+<p align="center">
+<a href="https://github.com/GeoStat-Framework/GSTools/discussions"><img src="https://img.shields.io/badge/GitHub-Discussions-f6f8fa?logo=github&style=flat" alt="GH-Discussions"/></a>
+<a href="https://swung.slack.com/messages/gstools"><img src="https://img.shields.io/badge/Swung-Slack-4A154B?style=flat&logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABoAAAAaCAYAAACpSkzOAAAABmJLR0QA%2FwD%2FAP%2BgvaeTAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAAB3RJTUUH5AYaFSENGSa5qgAABmZJREFUSMeFlltsVNcVhr%2B1z5m7Zzy%2BxaBwcQrGQOpgCAkKtSBQIqJepKhPBULpQ6sKBVWVKqXtSy%2BR0qYXqa2qRmlDCzjBEZGKUCK1TWqlNiGIEKDQBtf4Fki4OIxnxrex53LOXn2YwbjEtOvlHG3tvX%2Btf%2B21%2Fl%2BYJ1QVEbn1vwLYBWwCVgG1lW0ZoA%2FoAQ6LSP%2BdZ%2BeGzAMiIqK%2Bem0GpxNYVeBj3j2b4NCfM2QnfAAaa11al4fZuCZK24owQJ9v%2BbLryIVbd9wVSNUaEWNVtQPYfXHmAD0T32ZJeBM1Q8d0zzMDUpMwAFgLJU%2BxClURw9NfqedLWxMAHSKyR1WNiNhPAM0B6c%2FbdPORTLuOeUMSNkmMBHgyeo32bwwRDMh8bDM%2BZVl0j6uvPrdYknFnSESWzwUzt%2BkyVlUHx7zh5j%2BmPkXBjosjLkWdominiMQ%2BoiEZxuq8OFRXGXJ5K5%2Fde5nha8VlqjooIlZVBcBUiqeqemjGppd1ptfhSpS8pmmN7GVf4whPNY4Di9m%2BMcR03nK3sBbCQeFbv7gBsExVOyp3l6nz1VtjcM4fTK3Uok5IXtPsrHuPevcBXk8d4dWPX6I%2BsIB9wf1s%2B2Y%2FVbFynUIBIeDeplIECiXl5Iv3kbLogogRgbWukfNumT%2FnlYszBxj3hwXg0cQvqXcfYNu5tVyYPE%2B1G8dXn%2BfW72fH49U8sSlOPGr4SccoF4cKs3WzFrY%2BFCMUNmz%2Ba0aeWR1l15JwJ7DaVPpk1YnJ7xIxtQRNjDXRvTx%2F9ef0Tl0g6SYQhAlvmkH%2Fgv74qUaiTSG8ewJ0%2FGgRK5aG8Cts5ouWDa1RxoDRovK9i9MAq1S12QA7b5ROUdBxBIeQ1ACG49m%2FEXPis7Qk3ChHbx6Qw1dgXVeWB7uyDOctP%2Fx6w2zdrIVIyFCyiq8wXlJOZzyAXQbY%2FGGhC8EAilJ%2BVg7ufxU6IAHeSvewfQEadiDuCr%2B6NE1LU4hwUFAF1xFGRkvEjVDlgiPwVqoEsNkAq0ZKp3EIYrFM2xGm7Uc8u%2FzXjHkTmHIHoCiDM73E3IIsDCtRV3gn7QHQ0hTCt0ooKLw%2FWCAM1AcNISOcHSsBrDRAbc7eQMQBFFciHM18kaZIMz3r%2F0HO5mazytsiw%2FmTtCYiGGCkQlltwkEVjMDVmyUA6oIGR%2BDGjAWoM3f2giHAhH%2BFI5nPsDrWxqWNE9S4tUz5k1S7cQ5df4k9S6qY9JRipXtr4w5WQYH0eHkWrqxy8FTn3AvpmFmIqj%2B76EiQjNfHH1JNWFKc3vABj9V9npw%2FRXfmBNsaoTRnRAQDAgqqMJr1KBWUtUmHaR8WRgzAqAH6FgYexqd4R2Yuns5wcLSFK4U36bj%2FdbbUbGdoZoCi3uS%2Bqtt73TlNWygpqXGfZTGXnKesrwkA9BmgZ0noMZT5R0tQ4hzLfo4rhS46W%2F%2BCAn3T7%2BhDySiWMl2RkHArP8dAesKjPixYVbbUBwB6DHB4QWADIamuHPtkhE0t3ZP7ANhe9zgvXP2dfK0pymRJmQLiEYNW6mEVljYGuDzlkwwaHq51AQ4bERkAetvjP2XCT6H480AJeZsB4N7QYt7OnuSROtRXJV2wNNS4qIJvlbUtERJxhxcv5%2FlNWwygV0QGyzKBv%2FP%2ByFfZXf%2ButoR3UuXcS95mKNgxSjpN3qZZFHwUgFPjx5n2c9wo9ktrtcOZtMeWB2NEw4b2thivPLuIS1M%2BAzmrTy4O4ys7Zv1B5fsnVdWCr7PxYf7vej73ex2YeU1VVY9nu7ShG63vRo%2Fe%2FK1%2B518FbXkjo3OjO1XU2LFRzRZ9VdWDczFQ1VsCOHgpd1G%2FcG6jHrj2vPbn%2BjVdHNfr%2BRH92eXva2MPuvxEQpe%2BHdEnzm%2FQf4%2BrRo%2BldMUbGd393oS2dWU0cDSlw1OequrALVG9Q8rLsquqg2OlzLL2Myu1N5eShgB4CjEnSMSJYrX8Oj0t8UH7NMnX0iSDwmhBWRl3tKs9IcmgGRSRZqtqzFwpL4uWWKvWiMjyZKC24%2F1HbsrLn95Pwk3gCpS0yIw%2Fg6clPC2RLc3QmzvJupoARQsvrItxZmtSkkFz6E6Q%2F2m3PFta44jbCaw%2BO3GK7uybnJs8xfXC1fLYCdTz9NIfsCS0mYVhAHp9ZYdr5J%2F%2F127dxUA2AzuBzRUDWVfZlq4YyG6gs9ImdzWQ%2FwFNRlgCFdG5bAAAAABJRU5ErkJggg%3D%3D" alt="Slack-Swung"/></a>
+<a href="https://gitter.im/GeoStat-Framework/GSTools"><img src="https://img.shields.io/badge/Gitter-GeoStat--Framework-ed1965?logo=gitter&style=flat" alt="Gitter-GSTools"/></a>
+<a href="mailto:[email protected]"><img src="https://img.shields.io/badge/Email-GeoStat--Framework-468a88?style=flat&logo=data:image/svg+xml;base64,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" alt="Email"/></a>
+</p>
 
 ## Purpose
 
@@ -22,7 +29,7 @@ GeoStatTools provides geostatistical tools for various purposes:
 - simple, ordinary, universal and external drift kriging
 - conditioned field generation
 - incompressible random vector field generation
-- (automatted) variogram estimation and fitting
+- (automated) variogram estimation and fitting
 - directional variogram estimation and modelling
 - data normalization and transformation
 - many readily provided and even user-defined covariance models

docs/source/index.rst

@@ -6,13 +6,22 @@ GSTools Quickstart
    :width: 150px
    :align: center
 
+
+**Get in Touch!**
+
+|GH-Discussions| |Slack-Swung| |Gitter-GSTools| |Email|
+
+
+Purpose
+=======
+
 GeoStatTools provides geostatistical tools for various purposes:
 
 - random field generation
 - simple, ordinary, universal and external drift kriging
 - conditioned field generation
 - incompressible random vector field generation
-- (automatted) variogram estimation and fitting
+- (automated) variogram estimation and fitting
 - directional variogram estimation and modelling
 - data normalization and transformation
 - many readily provided and even user-defined covariance models
@@ -379,7 +388,27 @@ Optional
 - `pyvista <https://docs.pyvista.org>`_
 
 
+Contact
+-------
+
+You can contact us via `[email protected] <mailto:[email protected]>`_.
+
+
 License
 =======
 
 `LGPLv3 <https://github.com/GeoStat-Framework/GSTools/blob/master/LICENSE>`_
+
+
+.. |GH-Discussions| image:: https://img.shields.io/badge/GitHub-Discussions-f6f8fa?logo=github&style=flat
+    :alt: GH-Discussions
+    :target: https://github.com/GeoStat-Framework/GSTools/discussions
+.. |Slack-Swung| image:: https://img.shields.io/badge/Swung-Slack-4A154B?style=flat&logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAABoAAAAaCAYAAACpSkzOAAAABmJLR0QA%2FwD%2FAP%2BgvaeTAAAACXBIWXMAAA7DAAAOwwHHb6hkAAAAB3RJTUUH5AYaFSENGSa5qgAABmZJREFUSMeFlltsVNcVhr%2B1z5m7Zzy%2BxaBwcQrGQOpgCAkKtSBQIqJepKhPBULpQ6sKBVWVKqXtSy%2BR0qYXqa2qRmlDCzjBEZGKUCK1TWqlNiGIEKDQBtf4Fki4OIxnxrex53LOXn2YwbjEtOvlHG3tvX%2Btf%2B21%2Fl%2BYJ1QVEbn1vwLYBWwCVgG1lW0ZoA%2FoAQ6LSP%2BdZ%2BeGzAMiIqK%2Bem0GpxNYVeBj3j2b4NCfM2QnfAAaa11al4fZuCZK24owQJ9v%2BbLryIVbd9wVSNUaEWNVtQPYfXHmAD0T32ZJeBM1Q8d0zzMDUpMwAFgLJU%2BxClURw9NfqedLWxMAHSKyR1WNiNhPAM0B6c%2FbdPORTLuOeUMSNkmMBHgyeo32bwwRDMh8bDM%2BZVl0j6uvPrdYknFnSESWzwUzt%2BkyVlUHx7zh5j%2BmPkXBjosjLkWdominiMQ%2BoiEZxuq8OFRXGXJ5K5%2Fde5nha8VlqjooIlZVBcBUiqeqemjGppd1ptfhSpS8pmmN7GVf4whPNY4Di9m%2BMcR03nK3sBbCQeFbv7gBsExVOyp3l6nz1VtjcM4fTK3Uok5IXtPsrHuPevcBXk8d4dWPX6I%2BsIB9wf1s%2B2Y%2FVbFynUIBIeDeplIECiXl5Iv3kbLogogRgbWukfNumT%2FnlYszBxj3hwXg0cQvqXcfYNu5tVyYPE%2B1G8dXn%2BfW72fH49U8sSlOPGr4SccoF4cKs3WzFrY%2BFCMUNmz%2Ba0aeWR1l15JwJ7DaVPpk1YnJ7xIxtQRNjDXRvTx%2F9ef0Tl0g6SYQhAlvmkH%2Fgv74qUaiTSG8ewJ0%2FGgRK5aG8Cts5ouWDa1RxoDRovK9i9MAq1S12QA7b5ROUdBxBIeQ1ACG49m%2FEXPis7Qk3ChHbx6Qw1dgXVeWB7uyDOctP%2Fx6w2zdrIVIyFCyiq8wXlJOZzyAXQbY%2FGGhC8EAilJ%2BVg7ufxU6IAHeSvewfQEadiDuCr%2B6NE1LU4hwUFAF1xFGRkvEjVDlgiPwVqoEsNkAq0ZKp3EIYrFM2xGm7Uc8u%2FzXjHkTmHIHoCiDM73E3IIsDCtRV3gn7QHQ0hTCt0ooKLw%2FWCAM1AcNISOcHSsBrDRAbc7eQMQBFFciHM18kaZIMz3r%2F0HO5mazytsiw%2FmTtCYiGGCkQlltwkEVjMDVmyUA6oIGR%2BDGjAWoM3f2giHAhH%2BFI5nPsDrWxqWNE9S4tUz5k1S7cQ5df4k9S6qY9JRipXtr4w5WQYH0eHkWrqxy8FTn3AvpmFmIqj%2B76EiQjNfHH1JNWFKc3vABj9V9npw%2FRXfmBNsaoTRnRAQDAgqqMJr1KBWUtUmHaR8WRgzAqAH6FgYexqd4R2Yuns5wcLSFK4U36bj%2FdbbUbGdoZoCi3uS%2Bqtt73TlNWygpqXGfZTGXnKesrwkA9BmgZ0noMZT5R0tQ4hzLfo4rhS46W%2F%2BCAn3T7%2BhDySiWMl2RkHArP8dAesKjPixYVbbUBwB6DHB4QWADIamuHPtkhE0t3ZP7ANhe9zgvXP2dfK0pymRJmQLiEYNW6mEVljYGuDzlkwwaHq51AQ4bERkAetvjP2XCT6H480AJeZsB4N7QYt7OnuSROtRXJV2wNNS4qIJvlbUtERJxhxcv5%2FlNWwygV0QGyzKBv%2FP%2ByFfZXf%2ButoR3UuXcS95mKNgxSjpN3qZZFHwUgFPjx5n2c9wo9ktrtcOZtMeWB2NEw4b2thivPLuIS1M%2BAzmrTy4O4ys7Zv1B5fsnVdWCr7PxYf7vej73ex2YeU1VVY9nu7ShG63vRo%2Fe%2FK1%2B518FbXkjo3OjO1XU2LFRzRZ9VdWDczFQ1VsCOHgpd1G%2FcG6jHrj2vPbn%2BjVdHNfr%2BRH92eXva2MPuvxEQpe%2BHdEnzm%2FQf4%2BrRo%2BldMUbGd393oS2dWU0cDSlw1OequrALVG9Q8rLsquqg2OlzLL2Myu1N5eShgB4CjEnSMSJYrX8Oj0t8UH7NMnX0iSDwmhBWRl3tKs9IcmgGRSRZqtqzFwpL4uWWKvWiMjyZKC24%2F1HbsrLn95Pwk3gCpS0yIw%2Fg6clPC2RLc3QmzvJupoARQsvrItxZmtSkkFz6E6Q%2F2m3PFta44jbCaw%2BO3GK7uybnJs8xfXC1fLYCdTz9NIfsCS0mYVhAHp9ZYdr5J%2F%2F127dxUA2AzuBzRUDWVfZlq4YyG6gs9ImdzWQ%2FwFNRlgCFdG5bAAAAABJRU5ErkJggg%3D%3D
+    :alt: Slack-Swung
+    :target: https://swung.slack.com/messages/gstools
+.. |Gitter-GSTools| image:: https://img.shields.io/badge/Gitter-GeoStat--Framework-ed1965?logo=gitter&style=flat
+    :alt: Gitter-GSTools
+    :target: https://gitter.im/GeoStat-Framework/GSTools
+.. |Email| image:: https://img.shields.io/badge/Email-GeoStat--Framework-468a88?style=flat&logo=data:image/svg+xml;base64,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
+    :alt: Email
+    :target: mailto:[email protected]

examples/00_misc/05_standalone_field.py

@@ -0,0 +1,28 @@
+"""
+Standalone Field class
+----------------------
+
+The :any:`Field` class of GSTools can be used to plot arbitrary data in nD.
+
+In the following example we will produce 10000 random points in 4D with
+random values and plot them.
+"""
+import numpy as np
+import gstools as gs
+
+rng = np.random.RandomState(19970221)
+x0 = rng.rand(10000) * 100.0
+x1 = rng.rand(10000) * 100.0
+x2 = rng.rand(10000) * 100.0
+x3 = rng.rand(10000) * 100.0
+values = rng.rand(10000) * 100.0
+
+###############################################################################
+# Only thing needed to instantiate the Field is the dimension.
+#
+# Afterwards we can call the instance like all other Fields
+# (:any:`SRF`, :any:`Krige` or :any:`CondSRF`), but with an additional field.
+
+plotter = gs.field.Field(dim=4)
+plotter(pos=(x0, x1, x2, x3), field=values)
+plotter.plot()

gstools/field/base.py

@@ -41,7 +41,7 @@ class Field:
 
     Parameters
     ----------
-    model : :any:`CovModel`
+    model : :any:`CovModel`, optional
         Covariance Model related to the field.
     value_type : :class:`str`, optional
         Value type of the field. Either "scalar" or "vector".
@@ -56,15 +56,18 @@ class Field:
         Trend of the denormalized fields. If no normalizer is applied,
         this behaves equal to 'mean'.
         The default is None.
+    dim : :any:`None` or :class:`int`, optional
+        Dimension of the field if no model is given.
     """
 
     def __init__(
         self,
-        model,
+        model=None,
         value_type="scalar",
         mean=None,
         normalizer=None,
         trend=None,
+        dim=None,
     ):
         # initialize attributes
         self.pos = None
@@ -76,41 +79,69 @@ def __init__(
         self._mean = None
         self._normalizer = None
         self._trend = None
+        self._dim = dim if dim is None else int(dim)
         # set properties
         self.model = model
         self.value_type = value_type
         self.mean = mean
         self.normalizer = normalizer
         self.trend = trend
 
-    def __call__(self, *args, **kwargs):
-        """Generate the field."""
+    def __call__(
+        self, pos, field=None, mesh_type="unstructured", post_process=True
+    ):
+        """Generate the field.
+
+        Parameters
+        ----------
+        pos : :class:`list`
+            the position tuple, containing main direction and transversal
+            directions
+        field : :class:`numpy.ndarray` or :any:`None`, optional
+            the field values. Will be all zeros if :any:`None` is given.
+        mesh_type : :class:`str`, optional
+            'structured' / 'unstructured'. Default: 'unstructured'
+        post_process : :class:`bool`, optional
+            Whether to apply mean, normalizer and trend to the field.
+            Default: `True`
+
+        Returns
+        -------
+        field : :class:`numpy.ndarray`
+            the field values.
+        """
+        pos, shape = self.pre_pos(pos, mesh_type)
+        if field is None:
+            field = np.zeros(shape, dtype=np.double)
+        else:
+            field = np.array(field, dtype=np.double).reshape(shape)
+        return self.post_field(field, process=post_process)
 
     def structured(self, *args, **kwargs):
         """Generate a field on a structured mesh.
 
-        See :any:`Field.__call__`
+        See :any:`__call__`
         """
         call = partial(self.__call__, mesh_type="structured")
         return call(*args, **kwargs)
 
     def unstructured(self, *args, **kwargs):
         """Generate a field on an unstructured mesh.
 
-        See :any:`Field.__call__`
+        See :any:`__call__`
         """
         call = partial(self.__call__, mesh_type="unstructured")
         return call(*args, **kwargs)
 
     def mesh(
         self, mesh, points="centroids", direction="all", name="field", **kwargs
     ):
-        """Generate a field on a given meshio or ogs5py mesh.
+        """Generate a field on a given meshio, ogs5py or PyVista mesh.
 
         Parameters
         ----------
         mesh : meshio.Mesh or ogs5py.MSH or PyVista mesh
-            The given meshio, ogs5py, or PyVista mesh
+            The given mesh
         points : :class:`str`, optional
             The points to evaluate the field at.
             Either the "centroids" of the mesh cells
@@ -128,17 +159,17 @@ def mesh(
             cell_data. If to few names are given, digits will be appended.
             Default: "field"
         **kwargs
-            Keyword arguments forwareded to `Field.__call__`.
+            Keyword arguments forwarded to :any:`__call__`.
 
         Notes
         -----
         This will store the field in the given mesh under the given name,
         if a meshio or PyVista mesh was given.
 
-        See: https://github.com/nschloe/meshio
-        See: https://github.com/pyvista/pyvista
-
-        See: :any:`Field.__call__`
+        See:
+            - meshio: https://github.com/nschloe/meshio
+            - ogs5py: https://github.com/GeoStat-Framework/ogs5py
+            - PyVista: https://github.com/pyvista/pyvista
         """
         return generate_on_mesh(self, mesh, points, direction, name, **kwargs)
 
@@ -176,9 +207,11 @@ def pre_pos(self, pos, mesh_type="unstructured"):
         # prepend dimension if we have a vector field
         if self.value_type == "vector":
             shape = (self.dim,) + shape
-            if self.model.latlon:
+            if self.latlon:
                 raise ValueError("Field: Vector fields not allowed for latlon")
         # return isometrized pos tuple and resulting field shape
+        if self.model is None:
+            return pos, shape
         return self.model.isometrize(pos), shape
 
     def post_field(self, field, name="field", process=True, save=True):
@@ -299,7 +332,7 @@ def plot(
         if self.value_type == "scalar":
             r = plot_field(self, field, fig, ax, **kwargs)
         elif self.value_type == "vector":
-            if self.model.dim == 2:
+            if self.dim == 2:
                 r = plot_vec_field(self, field, fig, ax, **kwargs)
             else:
                 raise NotImplementedError(
@@ -317,12 +350,17 @@ def model(self):
 
     @model.setter
     def model(self, model):
-        if isinstance(model, CovModel):
+        if model is not None:
+            if not isinstance(model, CovModel):
+                raise ValueError(
+                    "Field: 'model' is not an instance of 'gstools.CovModel'"
+                )
             self._model = model
+            self._dim = None
+        elif self._dim is None:
+            raise ValueError("Field: either needs 'model' or 'dim'.")
         else:
-            raise ValueError(
-                "Field: 'model' is not an instance of 'gstools.CovModel'"
-            )
+            self._model = None
 
     @property
     def mean(self):
@@ -365,7 +403,12 @@ def value_type(self, value_type):
     @property
     def dim(self):
         """:class:`int`: Dimension of the field."""
-        return self.model.field_dim
+        return self._dim if self.model is None else self.model.field_dim
+
+    @property
+    def latlon(self):
+        """:class:`bool`: Whether the field depends on geographical coords."""
+        return False if self.model is None else self.model.latlon
 
     @property
     def name(self):
@@ -378,9 +421,13 @@ def _fmt_mean_norm_trend(self):
 
     def __repr__(self):
         """Return String representation."""
-        return "{0}(model={1}, value_type='{2}'{3})".format(
+        if self.model is None:
+            dim_str = f"dim={self.dim}"
+        else:
+            dim_str = f"model={self.model.name}"
+        return "{0}({1}, value_type='{2}'{3})".format(
             self.name,
-            self.model.name,
+            dim_str,
             self.value_type,
             self._fmt_mean_norm_trend(),
         )

gstools/field/cond_srf.py

@@ -9,7 +9,7 @@
 .. autosummary::
    CondSRF
 """
-# pylint: disable=C0103, W0231, W0221, E1102
+# pylint: disable=C0103, W0231, W0221, W0222, E1102
 import numpy as np
 from gstools.field.generator import RandMeth
 from gstools.field.base import Field

gstools/field/plot.py

@@ -56,7 +56,7 @@ def plot_field(
     if fld.dim == 1:
         return plot_1d(fld.pos, plt_fld, fig, ax, **kwargs)
     return plot_nd(
-        fld.pos, plt_fld, fld.mesh_type, fig, ax, fld.model.latlon, **kwargs
+        fld.pos, plt_fld, fld.mesh_type, fig, ax, fld.latlon, **kwargs
     )
 
 

pyproject.toml

@@ -3,7 +3,7 @@ requires = [
     "setuptools>=42",
     "wheel",
     "setuptools_scm[toml]>=3.5",
-    "numpy>=1.14.5,<2.0",
+    "oldest-supported-numpy",
     "Cython>=0.28.3,<3.0",
 ]
 build-backend = "setuptools.build_meta"