Add plotly option to add_fig_kwargs

.github/workflows/gh-pages.yml

@@ -0,0 +1,50 @@
+name: Deploy documentation with GitHub Pages dependencies preinstalled
+
+on:
+  push:
+    branches: ["develop"]
+  workflow_dispatch: # enable manual workflow execution
+
+# Set permissions of the GITHUB_TOKEN to allow deployment to GitHub Pages
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+# Allow only one concurrent deployment, skipping runs queued between the run in-progress and latest queued.
+# However, do NOT cancel in-progress runs as we want to allow these production deployments to complete.
+concurrency:
+  group: "pages"
+  cancel-in-progress: false
+
+jobs:
+  build:
+    # prevent this action from running on forks
+    if: github.repository == 'abinit/abipy'
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Setup Pages
+        uses: actions/configure-pages@v3
+
+      - name: Build with Jekyll
+        uses: actions/jekyll-build-pages@v1
+        with:
+          source: ./docs
+          destination: ./_site
+
+      - name: Upload artifact
+        uses: actions/upload-pages-artifact@v2
+
+  deploy:
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    runs-on: ubuntu-latest
+    needs: build
+    steps:
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v2

.github/workflows/test.yml

@@ -0,0 +1,81 @@
+# Runs the complete test suite. 
+name: Tests
+
+on:
+  push:
+    branches: [develop]
+    paths-ignore: ["**/*.md", docs/**]
+  pull_request:
+    branches: [develop]
+    paths-ignore: ["**/*.md", docs/**]
+  workflow_dispatch:
+  workflow_call: # make this workflow reusable by release.yml
+
+permissions:
+  contents: read
+
+jobs:
+  test:
+    # prevent this action from running on forks
+    if: github.repository == 'abinit/abipy'
+    defaults:
+      run:
+        shell: bash -l {0} # enables conda/mamba env activation by reading bash profile
+    strategy:
+      fail-fast: false
+      matrix:
+        # maximize CI coverage of different platforms and python versions while minimizing the
+        # total number of jobs. We run all pytest splits with the oldest supported python
+        # version (currently 3.9) on windows (seems most likely to surface errors) and with
+        # newest version (currently 3.12) on ubuntu (to get complete coverage on unix).
+        config:
+          - os: windows-latest
+            python: "3.9"
+            resolution: highest
+            extras: ci,optional
+          - os: ubuntu-latest
+            python: '>3.9'
+            resolution: lowest-direct
+            extras: ci,optional
+          - os: macos-latest
+            python: '3.10'
+            resolution: lowest-direct
+            extras: ci # test with only required dependencies installed
+
+        # pytest-split automatically distributes work load so parallel jobs finish in similar time
+        # update durations file with `pytest --store-durations --durations-path tests/files/.pytest-split-durations`
+        split: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+
+    runs-on: ${{ matrix.config.os }}
+
+    #env:
+    #  PMG_MAPI_KEY: ${{ secrets.PMG_MAPI_KEY }}
+
+    steps:
+      - name: Check out repo
+        uses: actions/checkout@v4
+
+      - name: Set up micromamba
+        uses: mamba-org/setup-micromamba@main
+
+      - name: Create mamba environment
+        run: |
+          micromamba create -n abipy python=${{ matrix.config.python }} --yes
+
+      - name: Install uv
+        run: micromamba run -n abipy pip install uv
+
+      #- name: Install ubuntu-only conda dependencies
+      #  if: matrix.config.os == 'ubuntu-latest'
+      #  run: |
+      #    micromamba install -n abipy -c conda-forge enumlib packmol bader openbabel openff-toolkit --yes
+
+      - name: Install pymatgen and dependencies
+        run: |
+          micromamba activate abipy
+          uv pip install --editable '.[${{ matrix.config.extras }}]' --resolution=${{ matrix.config.resolution }}
+
+      - name: pytest split ${{ matrix.split }}
+        run: |
+          micromamba activate abipy
+          pytest --splits 10 --group ${{ matrix.split }} --durations-path tests/files/.pytest-split-durations tests

abipy/eph/varpeq.py

@@ -159,9 +159,6 @@ def to_string(self, verbose=0) -> str:
         app(self.structure.to_string(verbose=verbose, title="Structure"))
         app("")
         app(self.ebands.to_string(with_structure=False, verbose=verbose, title="Electronic Bands"))
-        #if verbose > 1:
-        #    app("")
-        #    app(self.hdr.to_string(verbose=verbose, title="Abinit Header"))
 
         app("")
         app("VARPEQ parameters:")

abipy/ppcodes/oncv_parser.py

@@ -531,7 +531,7 @@ def kin_densities(self) -> dict[str, RadialFunction]:
     @lazy_property
     def vtaus(self) -> dict[str, RadialFunction]:
         """
-        Dictionary with Vtau pototentials on the radial mesh.
+        Dictionary with Vtau ptotentials on the radial mesh.
         """
         if not self.is_metapsp:
             raise ValueEror("kin_densities are only available in pseudos generated with metapsp")

abipy/ppcodes/oncv_plotter.py

@@ -327,11 +327,12 @@ def plotly_vtau(self, *args, **kwargs):
         from plotly.tools import mpl_to_plotly
         return mpl_to_plotly(self.plot_vtau(*args, show=False, **kwargs))
 
-    def plot_vtau(self, ax=None, fontsize: int = 8, **kwargs) -> Figure:
+    def plot_vtau(self, xscale="log", ax=None, fontsize: int = 8, **kwargs) -> Figure:
         """
         Plot v_tau and v_tau(model+pseudo) potentials on axis ax.
 
         Args:
+            xscale: "log" to plot vtau in log scale or "linear". For other options see matplotlib.
             ax: |matplotlib-Axes| or None if a new figure should be created.
         """
         ax, fig, plt = get_ax_fig_plt(ax)
@@ -347,23 +348,26 @@ def plot_vtau(self, ax=None, fontsize: int = 8, **kwargs) -> Figure:
                          fontsize=fontsize,
                          )
         self._add_rc_vlines_ax(ax, with_lloc=True)
+        ax.set_xscale(xscale)
+
+        return fig
 
     def plotly_tau(self, *args, **kwargs):
         """Generate plotly figure from matplotly."""
         from plotly.tools import mpl_to_plotly
         return mpl_to_plotly(self.plot_tau(*args, show=False, **kwargs))
 
-    def plot_tau(self, ax=None, fontsize: int = 8, **kwargs) -> Figure:
+    def plot_tau(self, ax=None, yscale="log", fontsize: int = 8, **kwargs) -> Figure:
         """
         Plot kinetic energy densities tauPS and tau(M+PS) on axis ax.
 
         Args:
+            yscale: "log" to plot tau in log scale or "linear". For other options see matplotlib.
             ax: |matplotlib-Axes| or None if a new figure should be created.
         """
         ax, fig, plt = get_ax_fig_plt(ax)
 
         for key, den in self.parser.kin_densities.items():
-            #mode = "ae" if key == "tau_ps" else "ps"
             ax.plot(den.rmesh, den.values,
                     label=den.name)
                     #**self._mpl_opts_laeps(0, mode))
@@ -373,6 +377,7 @@ def plot_tau(self, ax=None, fontsize: int = 8, **kwargs) -> Figure:
                          fontsize=fontsize,
                          )
         self._add_rc_vlines_ax(ax, with_lloc=True)
+        ax.set_yscale(yscale)
 
         return fig
 

abipy/ppcodes/tests/test_oncvpsp.py

@@ -474,6 +474,10 @@ def _call_plotter_methods(self, plotter):
             assert plotter.plot_atanlogder_econv(show=False)
             assert plotter.plot_den_formfact(ecut=20, show=False)
 
+            if isinstance(plotter, OncvParser) and plotter.parser.is_metapsp:
+                assert plotter.plot_vtau(show=False)
+                assert plotter.plot_tau(show=False)
+
         #if self.has_plotly():
 
     def test_psp8_get_densities(self):

abipy/tools/plotting.py

@@ -19,12 +19,12 @@
 from collections import namedtuple, OrderedDict
 from typing import Any, Callable, Iterator
 from monty.string import list_strings
-from pymatgen.util.plotting import add_fig_kwargs
+#from pymatgen.util.plotting import add_fig_kwargs
 from abipy.tools import duck
 from abipy.tools.iotools import dataframe_from_filepath
 from abipy.tools.typing import Figure, Axes, VectorLike
 from abipy.tools.numtools import data_from_cplx_mode
-from plotly.tools import mpl_to_plotly
+
 
 __all__ = [
     "set_axlims",
@@ -66,6 +66,115 @@
 )
 
 
+
+def add_fig_kwargs(func):
+    """Decorator that adds keyword arguments for functions returning matplotlib
+    figures.
+
+    The function should return either a matplotlib figure or None to signal
+    some sort of error/unexpected event.
+    See doc string below for the list of supported options.
+    """
+
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        # pop the kwds used by the decorator.
+        title = kwargs.pop("title", None)
+        size_kwargs = kwargs.pop("size_kwargs", None)
+        show = kwargs.pop("show", True)
+        savefig = kwargs.pop("savefig", None)
+        tight_layout = kwargs.pop("tight_layout", False)
+        ax_grid = kwargs.pop("ax_grid", None)
+        ax_annotate = kwargs.pop("ax_annotate", None)
+        fig_close = kwargs.pop("fig_close", False)
+        plotly = kwargs.pop("fig_close", False)
+
+        # Call func and return immediately if None is returned.
+        fig = func(*args, **kwargs)
+        if fig is None:
+            return fig
+
+        # Operate on matplotlib figure.
+        if title is not None:
+            fig.suptitle(title)
+
+        if size_kwargs is not None:
+            fig.set_size_inches(size_kwargs.pop("w"), size_kwargs.pop("h"), **size_kwargs)
+
+        if ax_grid is not None:
+            for ax in fig.axes:
+                ax.grid(bool(ax_grid))
+
+        if ax_annotate:
+            tags = ascii_letters
+            if len(fig.axes) > len(tags):
+                tags = (1 + len(ascii_letters) // len(fig.axes)) * ascii_letters
+            for ax, tag in zip(fig.axes, tags):
+                ax.annotate(f"({tag})", xy=(0.05, 0.95), xycoords="axes fraction")
+
+        if tight_layout:
+            try:
+                fig.tight_layout()
+            except Exception as exc:
+                # For some unknown reason, this problem shows up only on travis.
+                # https://stackoverflow.com/questions/22708888/valueerror-when-using-matplotlib-tight-layout
+                print("Ignoring Exception raised by fig.tight_layout\n", str(exc))
+
+        if savefig:
+            fig.savefig(savefig)
+
+        if plotly:
+            try:
+                plotly_fig = mpl_to_ply(fig, latex=False)
+                if show: plotly_fig.show()
+                return plotly_fig
+            except Exception as exc:
+                raise
+                #print(str(exc))
+                pass
+
+        import matplotlib.pyplot as plt
+        if show:
+            plt.show()
+
+        if fig_close:
+            plt.close(fig=fig)
+
+        return fig
+
+    # Add docstring to the decorated method.
+    doc_str = """\n\n
+        Keyword arguments controlling the display of the figure:
+
+        ================  ====================================================
+        kwargs            Meaning
+        ================  ====================================================
+        title             Title of the plot (Default: None).
+        show              True to show the figure (default: True).
+        savefig           "abc.png" or "abc.eps" to save the figure to a file.
+        size_kwargs       Dictionary with options passed to fig.set_size_inches
+                          e.g. size_kwargs=dict(w=3, h=4)
+        tight_layout      True to call fig.tight_layout (default: False)
+        ax_grid           True (False) to add (remove) grid from all axes in fig.
+                          Default: None i.e. fig is left unchanged.
+        ax_annotate       Add labels to  subplots e.g. (a), (b).
+                          Default: False
+        fig_close         Close figure. Default: False.
+        plotly            Try to convert mpl figure to plotly.
+        ================  ====================================================
+
+"""
+
+    if wrapper.__doc__ is not None:
+        # Add s at the end of the docstring.
+        wrapper.__doc__ += f"\n{doc_str}"
+    else:
+        # Use s
+        wrapper.__doc__ = doc_str
+
+    return wrapper
+
+
 class FilesPlotter:
     """
     Use matplotlib to plot multiple png files on a grid.
@@ -1743,9 +1852,7 @@ def add_plotly_fig_kwargs(func: Callable) -> Callable:
     sort of error/unexpected event.
     See doc string below for the list of supported options.
     """
-    from functools import wraps
-
-    @wraps(func)
+    @functools.wraps(func)
     def wrapper(*args, **kwargs):
         # pop the kwds used by the decorator.
         title = kwargs.pop("title", None)
@@ -2647,6 +2754,8 @@ def add_colorscale_dropwdowns(fig):
     return fig
 
 
+#TODO: Add plotly option to add_fig_kwargs
+
 def mpl_to_ply(fig: Figure, latex: bool= False):
     """
     Nasty workaround for plotly latex rendering in legend/breaking exception
@@ -2699,6 +2808,7 @@ def parse_latex(label):
                 text.set_text(new_label)
 
     # Convert to plotly figure
+    from plotly.tools import mpl_to_plotly
     plotly_fig = mpl_to_plotly(fig)
 
     plotly_fig.update_layout(template  = "plotly_white", title = {
@@ -2726,7 +2836,6 @@ def parse_latex(label):
     for trace in plotly_fig.data:
         # Retrieve the current label and remove any $ signs
         new_label = trace.name.replace("$", "")
-
         # Update the trace's name (which is used for the legend label)
         trace.name = new_label
 
@@ -2784,3 +2893,5 @@ def plot(self, deg_list: list[int],
 #
 #    def extrapolate_to_zero(self, deg: int):
 
+
+