Merge with master.

.gitlab-ci.yml

 pages:
   script:
+  - apt-get update
+  - apt-get -y upgrade
+  - apt-get -y install make
+  - conda env create -f ci/requirements_py311.yml
+  - source activate pyicon_py311
+  - pip install -e .
   - cd doc
-  - apk add --repository https://dl-cdn.alpinelinux.org/alpine/edge/community pandoc
-  - pip install nbsphinx nbsphinx_link pydata_sphinx_theme
   - make html
   - mv _build/html/* ../public/
 
   tags:
-  - sphinx
+  - conda
 
   only:
   - master
@@ -15,4 +19,4 @@ pages:
   artifacts:
     paths:
     - public
-    expire_in: 5min
+    expire_in: 10min

README.md

@@ -56,3 +56,6 @@ Once, `cartopy` is installed in your environment:
 ```bash
 pip install git+https://gitlab.dkrz.de/m300602/pyicon.git
 ```
+
+## Developing
+When adding new functions, make sure to document them with a docstring. This should detail what the function does, the arguments and what type of objects it returns. Examples are encouraged. We use so-called "numpy" style docstrings which are then automatically rendered into the sphinx documentation. A guide to numpy style docstrings is available [here](https://numpydoc.readthedocs.io/en/latest/format.html) and they even produce some nice [examples](https://numpydoc.readthedocs.io/en/latest/example.html#example).
\ No newline at end of file

ci/requirements_py311.yml

+name: pyicon_py311
+channels:
+  - conda-forge
+dependencies:
+  - python=3.11
+  - numpy
+  - dask
+  - matplotlib
+  - cartopy
+  - netcdf4
+  - xarray
+  - zarr
+  - pandas
+  - cmocean
+  - scipy
+  - ipdb
+  - ipywidgets
+  - jupytext
+  - pytest
+  - healpy
+  - pandoc
+  - sphinx  # Documentation
+  - nbsphinx  # Documentation
+  - nbsphinx-link  # Documentation
+  - sphinx-copybutton  # Documentation
+  - pydata-sphinx-theme  # Documentation

doc/api.rst

@@ -8,7 +8,32 @@ API for pyicon
 
 Some semi-automatically generate documentation about the pyicon API.
 
+
 .. automodule:: pyicon
+  :members:
+  :undoc-members:
+  :show-inheritance:
+
+pyicon.pyicon_accessor
+---------------------
+.. automodule:: pyicon.pyicon_accessor
+  :members:
+  :undoc-members:
+  :private-members:
+
+pyicon.pyicon_calc_xr
+---------------------
+.. automodule:: pyicon.pyicon_calc_xr
+  :members:
+  :undoc-members:
+  :private-members:
+
+pyicon.pyicon_calc
+---------------------
+.. automodule:: pyicon.pyicon_calc
+  :members:
+  :undoc-members:
+  :private-members:
 
 pyicon.pyicon_IconData
 ----------------------
@@ -16,8 +41,36 @@ pyicon.pyicon_IconData
 .. automodule:: pyicon.pyicon_IconData
   :members:
 
+pyicon.pyicon_params
+---------------------
+.. automodule:: pyicon.pyicon_params
+  :members:
+  :undoc-members:
+  :private-members:
+
 pyicon.pyicon_plotting
 ----------------------
 
 .. automodule:: pyicon.pyicon_plotting
   :members:
+
+pyicon.pyicon_simulation
+---------------------
+.. automodule:: pyicon.pyicon_simulation
+  :members:
+  :undoc-members:
+  :private-members:
+
+pyicon.pyicon_tb
+---------------------
+.. automodule:: pyicon.pyicon_tb
+  :members:
+  :undoc-members:
+  :private-members:
+
+pyicon.pyicon_thermo
+---------------------
+.. automodule:: pyicon.pyicon_thermo
+  :members:
+  :undoc-members:
+  :private-members:
\ No newline at end of file

doc/conf.py

@@ -18,8 +18,7 @@
 
 import os
 import sys
-# sys.path.insert(0, os.path.abspath('.'))
-sys.path.insert(0, os.path.abspath('../..'))  # Source code dir relative to this file
+sys.path.insert(0, os.path.abspath('..'))  # Source code dir relative to this file
  
 
 # -- General configuration ------------------------------------------------
@@ -35,12 +34,11 @@ extensions = [
     'sphinx.ext.autodoc',
     'sphinx.ext.todo',
     'sphinx.ext.imgmath',
-#    'sphinx.ext.autosummary',
     'nbsphinx',
     'nbsphinx_link',
     'sphinx_copybutton',
-#    "IPython.sphinxext.ipython_directive",
-#    "IPython.sphinxext.ipython_console_highlighting",
+    'sphinx.ext.autosummary',
+    'sphinx.ext.napoleon',
 ]
 
 # Add any paths that contain templates here, relative to this directory.
@@ -54,6 +52,8 @@ source_suffix = '.rst'
 
 # The master toctree document.
 master_doc = 'index'
+autosummary_generate = True
+napoleon_numpy_docstring = True
 
 # !by_nils
 html_sidebars = { '**': ['globaltoc.html', 'relations.html', 'sourcelink.html', 'searchbox.html'] }
@@ -165,6 +165,3 @@ texinfo_documents = [
      author, 'pyicon', 'One line description of project.',
      'Miscellaneous'),
 ]
-
-
-

doc/index.rst

@@ -27,10 +27,6 @@ Pyicon is hosted here: `<https://gitlab.dkrz.de/m300602/pyicon/>`_
    pyicon-view
    example_notebooks
    api
-
-..
-   example_notebooks
-
   
 Indices and tables
 ==================

pyicon/pyicon_plotting.py

 import sys, glob, os
 import json
+from pathlib import Path
 # --- calculations
 import numpy as np
 from scipy import interpolate
@@ -1901,6 +1902,115 @@ def plot(data,
          # --- original grid
          lonlat_for_mask=False,
          ):
+  
+  """plot map of data
+
+  Parameters
+  ----------
+  data : xr.DataArray
+      data to be
+  Plot : pyicon.Plot, optional
+      plotting canvas to draw on, by default None
+  ax : matplotlib.axes, optional
+      axis to plot on to , by default None
+  cax : matplotlib.axes, optional
+      axis to plot colorbar on, by default None
+  asp : float, optional
+      aspect ratio, by default None
+  fig_size_fac : float, optional
+      _description_, by default 2.0
+  mask_data : bool, optional
+      mask data where data = 0 (NaN value in ICON), by default True
+  logplot : bool, optional
+      logarithmic colormap, by default False
+  lon_reg : _type_, optional
+      longitude range to plot, by default None
+  lat_reg : _type_, optional
+      latitudes range to plot, by default None
+  central_longitude : str or float, optional
+      central longitude of plot, by default 'auto'
+  clim : str or (float, float), optional
+      colorbar limits, by default 'auto'
+  cmap : str or colormap, optional
+      colormap to use, by default 'auto'
+  conts : _type_, optional
+      _description_, by default None
+  contfs : _type_, optional
+      _description_, by default None
+  clevs : _type_, optional
+      _description_, by default None
+  use_pcol_or_contf : bool, optional
+      _description_, by default True
+  contcolor : str, optional
+      colour of contours, by default 'k'
+  cincr : float, optional
+      _description_, by default -1.0
+  clabel : bool, optional
+      whether to label contours, by default False
+  cbticks : str or list, optional
+      ticks for colorbar, by default 'auto'
+  xlabel : str, optional
+      label for x-axis, by default ''
+  ylabel : str, optional
+      label fo y-axis, by default ''
+  xticks : str or list, optional
+      tick labels for x-axis, by default 'auto'
+  yticks : str or list, optional
+      tick labels for y-axis, by default 'auto'
+  template : str, optional
+      _description_, by default 'none'
+  cbar_str : str, optional
+      label for colorbar, by default 'auto'
+  cbar_pos : str, optional
+      position of colorbar, by default 'bottom'
+  title_right : str, optional
+      title for rhs of plot, by default 'auto'
+  title_left : str, optional
+      title for lhs of plot, by default 'auto'
+  title_center : str, optional
+      title for centre of plot, by default 'auto'
+  projection : str, optional
+      projection for map, by default 'pc'
+  coastlines_color : str, optional
+      colour of coastlines, by default 'k'
+  land_facecolor : str, optional
+      colour of land, by default '0.7'
+  axes_facecolor : str, optional
+      colour of background axes, by default '0.7'
+  noland : bool, optional
+      whether to not plot land, by default False
+  do_plot_settings : bool, optional
+      whether to apply defauly plot settings, by default True
+  do_xyticks : bool, optional
+      _description_, by default True
+  do_gridlines : bool, optional
+      whether to plot gridlindes, by default False
+  gname : str, optional
+      name of the grid the data is on, by default 'auto'. Typically the name
+      of a subdirectory of pyicon.params["path_grid"].
+  fpath_tgrid : str, optional
+      path to the triangulation grid, by default 'auto'.
+  plot_method : "nn" or "tgrid", optional
+      whether to use perform nearest neighbour (nn) interpolation or plot on
+      the native triangular grid (tgrid), by default 'nn'
+  res : float, optional
+      resolution for healpix grids, by default 0.3
+  fpath_ckdtree : str, optional
+      path to the ckdtree, by default 'auto'
+  coordinates : str, optional
+      the coordinates of the variable to plotted, by default 'clat clon'.
+      Typically set to "xlon xlat" where x is either "c", "e" or "v" for cell,
+      edge or vertex points.
+  lonlat_for_mask : bool, optional
+      _description_, by default False
+
+  Returns
+  -------
+  ax : matplotlib.axes
+      axes that have been plotted to
+  hm : _type_
+      _description_
+  """
 
 
   # --- derive plot boundaries
@@ -1946,37 +2056,41 @@ def plot(data,
   
   # --- identify grid file names and paths
   path_grid = params['path_grid']
-  if gname=='auto':
+  try:
+    Dgrid = identify_grid(data, path_grid)
+  except:
+    # This doesn't always work, lets try another approach
     try:
-      Dgrid = identify_grid(data, path_grid)
-      gname = Dgrid['name']
+      Dgrid = identify_grid(
+        data, path_grid, uuidOfHGrid=data.attrs['uuidOfHGrid']
+        )
     except:
-      try:
-        Dgrid = identify_grid(data, path_grid, uuidOfHGrid=data.attrs['uuidOfHGrid'])
-        gname = Dgrid['name']
-      except:
-        gname = 'none'
-  if fpath_tgrid=='auto':
+      Dgrid = dict()
+
+  if gname == "auto":
     try:
-      Dgrid = identify_grid(data, path_grid)
-      fpath_tgrid = Dgrid['fpath_grid']
-    except:
-      fpath_tgrid = 'from_file'
-  if fpath_ckdtree=='auto':
-    fpath_ckdtree = f'{path_grid}/{gname}/ckdtree/rectgrids/{gname}_res{res:3.2f}_180W-180E_90S-90N.nc'
-  
-  if grid_type=='auto':
-    if Dgrid["name"].startswith("healpix"):
+      gname = Dgrid["name"]
+    except KeyError:
+      gname = "none"
+
+  if fpath_tgrid == "auto":
+    try:
+      fpath_tgrid = Dgrid["fpath_grid"]
+    except KeyError:
+      fpath_tgrid = "from_file"
+
+  if grid_type == 'auto':
+    if gname.startswith("healpix"):
       grid_type = 'healpix'
     else:
       grid_type = 'native'
 
+  if fpath_ckdtree == 'auto':
+    fpath_ckdtree = f'{path_grid}/{gname}/ckdtree/rectgrids/{gname}_res{res:3.2f}_180W-180E_90S-90N.nc'
+
   # --- rename dimensions
   if 'cells' in data.dims:
     data = data.rename(cells='ncells')
-  #for dim in data.dims:
-  #  if dim.startswith('layers'):
-  #    data = data.rename({dim: 'depth'})
 
   # --- infer depth name
   depth_name = identify_depth_name(data) 
@@ -1988,22 +2102,46 @@ def plot(data,
   # ---
   if data.ndim!=1:
     raise ValueError(f'::: Error: Wrong dimension of data: {data.dims}.')
-  
-  #if 'grid_mapping' in list(data.attrs):
-  #  plot_method = 'healpix'
 
   # --- interpolate and cut to region
-  if grid_type=='native' and plot_method=='nn':
-    datai = interp_to_rectgrid_xr(data.compute(), fpath_ckdtree, lon_reg=lon_reg, lat_reg=lat_reg, coordinates=coordinates, 
-                                  antialias=antialias, mask_to_zero=mask_to_zero,
-                                 )
+  if grid_type == 'native' and plot_method == 'nn':
+    # We need fpath_ckdtree so check it is there.
+    if not Path(fpath_ckdtree).exists():
+      if gname == "none":
+        raise FileNotFoundError(
+          f"Unable to find file `fpath_ckdtree={fpath_ckdtree}`. \
+          This may be because `gname='none'`. Try either setting \
+          `gname` explicitly or `fpath_ckdtree` explicitly. `gname` \
+          typically takes the name of a subdirectory of the folder \
+          {params['path_grid']}"
+        )
+      else:
+        raise FileNotFoundError(
+          f"Unable to find file `fpath_ckdtree={fpath_ckdtree}`. \
+          Try setting `fpath_ckdtree` explicitly."
+        )
+
+    datai = interp_to_rectgrid_xr(
+        data.compute(), fpath_ckdtree,
+        lon_reg=lon_reg, lat_reg=lat_reg, coordinates=coordinates,
+        antialias=antialias, mask_to_zero=mask_to_zero,
+    )
+
     lon = datai.lon
     lat = datai.lat
+
   elif grid_type=='native' and plot_method=='tgrid':
     print('Deriving triangulation object, this can take a while...')
     if fpath_tgrid != 'from_file':
       ds_tgrid = xr.open_dataset(fpath_tgrid)
     else:
+      raise NotImplementedError(
+        "Function not yet ready for calling with \
+        `fpath_tgrid='from_file'`, `grid_type='native'` and \
+        `plot_method='tgrid`"
+      )
+      # In the below code it isn't clear what ds should be?
+      
       ds_tgrid = xr.Dataset()
       ntr = ds.clon.size
       vlon = ds.clon_bnds.data.reshape(ntr*3)
@@ -2032,6 +2170,11 @@ def plot(data,
     datai = hp_to_rectgrid(data, lon_reg=lon_reg, lat_reg=lat_reg, res=res)
     lon = datai.lon
     lat = datai.lat
+  else:
+    raise ValueError(
+      "Invalid combination of `grid_type` and `plot_method` \
+      arguments."
+    )
   
   # --- title, colorbar, and x/y label  strings
   if cbar_str=='auto':
@@ -2055,7 +2198,6 @@ def plot(data,
         cbar_str = f'{data.name}'
   if (title_right=='auto') and ('time' in data.coords):
     tstr = str(data.time.data)
-    #tstr = tstr.split('T')[0].replace('-', '')+'T'+tstr.split('T')[1].split('.')[0].replace(':','')+'Z'
     tstr = tstr.split('.')[0]
     title_right = tstr
   elif (title_right=='full_time') and ('time' in data.dims):

pyicon/tests/conftest.py

-import pytest
 from pathlib import Path
+import pytest
 import xarray as xr
 import pyicon as pyic
 
+
 @pytest.fixture()
-def raw_grid():
-    cur_dir = Path(__file__).parent.resolve()
-    grid_path = cur_dir / "test_data/icon_grid_0014_R02B04_O.nc"
+def lazy_raw_grid():
+    path_data = Path(pyic.params["path_example_data"])
+    path_data.mkdir(parents=True, exist_ok=True)
+    grid_path = path_data / "icon_grid_0014_R02B04_O.nc"
 
     if not grid_path.exists():
         import requests
+
         grid_download_link = "http://icon-downloads.mpimet.mpg.de/grids/public/mpim/0014/icon_grid_0014_R02B04_O.nc"
         try:
             r = requests.get(grid_download_link, allow_redirects=True)
             with open(grid_path, "wb") as grid_file:
                 grid_file.write(r.content)
         except:
-            raise FileNotFoundError("{grid_path} does not exist and unable to \
-                download it")
+            raise FileNotFoundError(
+                "{grid_path} does not exist and unable to \
+                download it"
+            )
 
-    ds_grid = xr.open_dataset(grid_path)
+    ds_grid = xr.open_dataset(grid_path, chunks="auto")
     return ds_grid
 
 
 @pytest.fixture()
-def processed_tgrid(raw_grid):
-    return pyic.convert_tgrid_data(raw_grid)
+def eager_raw_grid(lazy_raw_grid):
+    ds_raw_grid = lazy_raw_grid.compute()
+    return ds_raw_grid
+
 
 @pytest.fixture()
-def examp_icon_dataset():
-    #cur_dir = Path(__file__).parent.resolve()
-    #fpath_data = cur_dir / "test_data/icon_example_data_r2b6.nc"
-    path_data = Path(pyic.params['path_example_data'])
+def lazy_processed_tgrid(lazy_raw_grid):
+    return pyic.convert_tgrid_data(lazy_raw_grid)
+
+
+@pytest.fixture()
+def eager_processed_tgrid(eager_raw_grid):
+    return pyic.convert_tgrid_data(eager_raw_grid)
+
+
+@pytest.fixture()
+def lazy_examp_icon_dataset():
+    path_data = Path(pyic.params["path_example_data"])
     path_data.mkdir(parents=True, exist_ok=True)
     fpath_data = path_data / "icon_example_data_r2b4.nc"
 
     if not fpath_data.exists():
         import requests
-        download_link = "https://swift.dkrz.de/v1/dkrz_07387162e5cd4c81b1376bd7c648bb60/pyicon_example_data/icon_example_data_r2b4.nc"
+
+        download_link = "https://swift.dkrz.de/v1/dkrz_83018ad4-3c8d-4c7d-b684-7ba0742caa1a/pyicon_test_data/icon_example_data_r2b4.nc?temp_url_sig=03fb5d20a44832c7cf736ab83c1be3936364dbf6&temp_url_expires=2026-11-24T11:53:16Z"
         try:
-            r = requests.get(download_link, allow_redirects=True)
+            r = requests.get(download_link, allow_redirects=True, stream=True)
             with open(fpath_data, "wb") as fobj:
                 fobj.write(r.content)
         except:
-            raise FileNotFoundError("{fpath_data} does not exist and unable to \
-                download it")
+            raise FileNotFoundError(
+                "{fpath_data} does not exist and unable to \
+                download it"
+            )
 
-    ds = xr.open_dataset(fpath_data)
+    ds = xr.open_dataset(fpath_data, chunks="auto")
     return ds
 
+
 @pytest.fixture()
-def examp_icon_dataarray(examp_icon_dataset):
-    return examp_icon_dataset["to"]
+def eager_examp_icon_dataset(lazy_examp_icon_dataset):
+    return lazy_examp_icon_dataset.compute()
+
 
+@pytest.fixture()
+def lazy_examp_icon_dataarray(lazy_examp_icon_dataset):
+    return lazy_examp_icon_dataset["to"]
+
+
+@pytest.fixture()
+def eager_examp_icon_dataarray(eager_examp_icon_dataset):
+    return eager_examp_icon_dataset["to"]

pyicon/tests/test_docs.py

+import subprocess
+import pytest
+import pyicon as pyic
+from pathlib import Path
+
+
+def test_docs_build(tmpdir_factory):
+    base_dir = Path(pyic.__file__).parent / ".."
+    doc_dir = base_dir.resolve() / "doc"
+    build_dir = tmpdir_factory.mktemp("_build")
+
+    # Run the sphinx-build command
+    try:
+        subprocess.check_call(["sphinx-build", "-b", "html", doc_dir, build_dir])
+    except subprocess.CalledProcessError as e:
+        pytest.fail(f"Documentation build failed with exit code {e.returncode}")

pyicon/tests/test_pyicon_calc_xr.py

@@ -2,10 +2,17 @@ from itertools import product
 import pytest
 import numpy as np
 import pyicon as pyic
-from .conftest import raw_grid, processed_tgrid
+from .conftest import (
+    eager_raw_grid,
+    eager_processed_tgrid,
+    lazy_raw_grid,
+    lazy_processed_tgrid,
+)
 
 
-def test_convert_tgrid_data(raw_grid):
+@pytest.mark.parametrize("raw_grid", ["lazy_raw_grid", "eager_raw_grid"])
+def test_convert_tgrid_data(raw_grid, request):
+    raw_grid = request.getfixturevalue(raw_grid)
     converted_tgrid = pyic.convert_tgrid_data(raw_grid)
 
     # Check conversion to pythonic indexing of neighbour info has worked
@@ -24,14 +31,17 @@ def test_convert_tgrid_data(raw_grid):
         assert converted_tgrid[info].min().values == 0 or -1
 
         if info.startswith("v") or info.startswith("edge_vertices"):
-            assert converted_tgrid[info].max().values == \
-                converted_tgrid.dims["vertex"] - 1
+            assert (
+                converted_tgrid[info].max().values == converted_tgrid.dims["vertex"] - 1
+            )
         elif info.startswith("e"):
-            assert converted_tgrid[info].max().values == \
-                converted_tgrid.dims["edge"] - 1
+            assert (
+                converted_tgrid[info].max().values == converted_tgrid.dims["edge"] - 1
+            )
         elif info.startswith("c") or info.startswith("a"):
-            assert converted_tgrid[info].max().values == \
-                converted_tgrid.dims["cell"] - 1
+            assert (
+                converted_tgrid[info].max().values == converted_tgrid.dims["cell"] - 1
+            )
 
     # Conversion of ecv lat and lon to degrees
     for point, dim in product("ecv", ("lat", "lon")):
@@ -50,9 +60,16 @@ def test_convert_tgrid_data(raw_grid):
     assert "cell" in converted_tgrid.dims
 
 
-@pytest.mark.parametrize("tgrid", ["raw_grid", "processed_tgrid"])
+@pytest.mark.parametrize(
+    "tgrid",
+    [
+        "lazy_raw_grid",
+        "lazy_processed_tgrid",
+        "eager_raw_grid",
+        "eager_processed_tgrid",
+    ],
+)
 def test_xr_crop_tgrid(tgrid, request):
-    # Set ireg_c and crop the grid
     tgrid = request.getfixturevalue(tgrid)
 
     for point, dim in product("cev", ["lon", "lat"]):
@@ -60,10 +77,20 @@ def test_xr_crop_tgrid(tgrid, request):
         if tgrid[coord].units == "radian":
             tgrid[coord] = np.degrees(tgrid[coord])
 
-    ireg_c = tgrid["cell"].where(
-        (tgrid["clon"] > -5) & (tgrid["clon"] < 5)
-        & (tgrid["clat"] > -5) & (tgrid["clat"] < 5),
-        drop=True).astype("int32")
+    tgrid["clon"] = tgrid["clon"].compute()
+    tgrid["clat"] = tgrid["clat"].compute()
+
+    ireg_c = (
+        tgrid["cell"]
+        .where(
+            (tgrid["clon"] > -5)
+            & (tgrid["clon"] < 5)
+            & (tgrid["clat"] > -5)
+            & (tgrid["clat"] < 5),
+            drop=True,
+        )
+        .astype("int32")
+    )
 
     # This checks ireg_c is as expected
     assert ireg_c.sum() == 301614
@@ -89,8 +116,26 @@ def test_xr_crop_tgrid(tgrid, request):
     assert cropped_tgrid["ireg_v"].sum() == 135385
     assert cropped_tgrid["ireg_v"].prod() == -1427286351937536000
 
+    # Try running the example code from the docstring
+    clon = tgrid.clon.compute().data * 180.0 / np.pi
+    clat = tgrid.clat.compute().data * 180.0 / np.pi
+    lon_reg = [6, 10]
+    lat_reg = [-32, -30]
+    ireg_c = np.where(
+        (clon > lon_reg[0])
+        & (clon <= lon_reg[1])
+        & (clat > lat_reg[0])
+        & (clat <= lat_reg[1])
+    )[0]
+    pyic.xr_crop_tgrid(tgrid, ireg_c)
+
+
+@pytest.mark.parametrize(
+    "processed_tgrid", ["lazy_processed_tgrid", "eager_processed_tgrid"]
+)
+def test_nabla_funcs(processed_tgrid, request):
+    processed_tgrid = request.getfixturevalue(processed_tgrid)
 
-def test_nabla_funcs(processed_tgrid):
     # Want to check curl of a gradient
     gradient = pyic.xr_calc_grad(processed_tgrid, processed_tgrid["clon"])
     curl_of_grad = pyic.xr_calc_curl(processed_tgrid, gradient)

pyicon/tests/test_pyicon_plotting.py

@@ -2,19 +2,23 @@ import pytest
 import pyicon as pyic
 import xarray as xr
 import matplotlib.pyplot as plt
-from .conftest import examp_icon_dataarray
+from .conftest import lazy_examp_icon_dataarray, eager_examp_icon_dataarray
 
-def test_plot(examp_icon_dataarray):
-    pyic.plot(examp_icon_dataarray.isel(time=0, depth=0))
-    return
 
-def test_plot_sec(examp_icon_dataarray):
-    pyic.plot_sec(examp_icon_dataarray.isel(time=0), section='170W')
+@pytest.mark.parametrize(
+    "examp_icon_dataarray", ["lazy_examp_icon_dataarray", "eager_examp_icon_dataarray"]
+)
+@pytest.mark.parametrize("grid_type,", ["auto", "native"])
+def test_plot(examp_icon_dataarray, grid_type, request):
+    examp_icon_dataarray = request.getfixturevalue(examp_icon_dataarray)
+    pyic.plot(examp_icon_dataarray.isel(time=0, depth=0), grid_type=grid_type)
     return
 
-#def test_shade():
-#    dai = pyic.interp_to_rectgrid_xr(da)
-#    dai = dai.compute()
-#    pyic.shade(dai.lon, dai.lat, dai)
-#    return
 
+@pytest.mark.parametrize(
+    "examp_icon_dataarray", ["lazy_examp_icon_dataarray", "eager_examp_icon_dataarray"]
+)
+def test_plot_sec(examp_icon_dataarray, request):
+    examp_icon_dataarray = request.getfixturevalue(examp_icon_dataarray)
+    pyic.plot_sec(examp_icon_dataarray.isel(time=0), section="170W")
+    return

pyicon/tests/test_pyicon_thermo.py

 import numpy as np
-from pyicon.pyicon_thermo import (
-    _calculate_mpiom_density,
-    _calculate_insitu_temperature
-)
+from pyicon.pyicon_thermo import _calculate_mpiom_density, _calculate_insitu_temperature
+
 
 def test_mpiom_density():
     """the test values come from A3.2 of Gill (1982), Atmospheric & Ocean
@@ -11,9 +9,12 @@ def test_mpiom_density():
     assert np.allclose(_calculate_mpiom_density(0, 5, 0), 999.96675, atol=1e-5)
     assert np.allclose(_calculate_mpiom_density(35, 5, 0), 1027.67547, atol=1e-5)
     assert np.allclose(_calculate_mpiom_density(35, 25, 1000), 1062.53817, atol=1e-5)
-    
+
+
 def test_insitu_temperature():
     """the test values come from A3.5 of Gill (1982), Atmospheric & Ocean
     Dynamics
     """
-    assert np.allclose(_calculate_insitu_temperature(25, 8.4678516, 1000), 10, atol=1e-7)
\ No newline at end of file
+    assert np.allclose(
+        _calculate_insitu_temperature(25, 8.4678516, 1000), 10, atol=1e-7
+    )