Merge branch 'develop' into feature/concurrentRegression

.github/workflows/mypy.yml

@@ -12,9 +12,8 @@ jobs:
     - uses: tsuyoshicho/action-mypy@v3
       with:
         github_token: ${{ secrets.github_token }}
-        # Change reviewdog reporter if you need [github-pr-check,github-check,github-pr-review].
         reporter: github-pr-review
-        # Change reporter level if you need.
-        # GitHub Status Check won't become failure with warning.
-        level: warning
+        # The action will output fail if there are mypy errors
+        level: error
+        setup_command: pip install -r requirements.txt pytest mypy
         mypy_flags: ''

.github/workflows/tests.yml

@@ -11,7 +11,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest, windows-latest]
-        python-version: ['3.8', '3.9']
+        python-version: ['3.9', '3.10']
 
     steps:
     - uses: actions/checkout@v2

binder/requirements.txt

@@ -1,4 +1,4 @@
--r ../readthedocs-requirements.txt
+scikit-fda[docs]
 jupytext
 sphinx-gallery<=0.7.0
 .

docs/_static/switcher.json

@@ -0,0 +1,13 @@
+[
+    {
+        "name": "dev",
+        "version": "dev",
+        "url": "https://fda.readthedocs.io/en/latest/"
+    },
+    {
+    	"name": "0.9 (stable)",
+        "version": "stable",
+        "url": "https://fda.readthedocs.io/en/stable/",
+        "preferred": true
+    }
+]

docs/_templates/autosummary/class.rst

@@ -10,12 +10,16 @@
 
    .. autosummary::
    {% for item in methods %}
+      {% if item != "__init__" %}
       ~{{ name }}.{{ item }}
+      {% endif %}
    {%- endfor %}
    {% endif %}
 
    {% for item in methods %}
+      {% if item != "__init__" %}
    .. automethod:: {{ item }}
+      {% endif %}
    {%- endfor %}
    {% endblock %}
 

docs/conf.py

@@ -46,8 +46,16 @@
     "Universidad Autónoma de Madrid"
 )
 github_url = "https://github.com/GAA-UAM/scikit-fda"
-rtd_version = os.environ.get("READTHEDOCS_VERSION", "latest")
-branch = "master" if rtd_version == "stable" else "develop"
+rtd_version = os.environ.get("READTHEDOCS_VERSION")
+rtd_version_type = os.environ.get("READTHEDOCS_VERSION_TYPE")
+
+switcher_version = rtd_version
+if switcher_version == "latest":
+    switcher_version = "dev"
+elif rtd_version_type not in {"branch", "tag"}:
+    switcher_version = skfda.__version__
+
+rtd_branch = os.environ.get(" READTHEDOCS_GIT_IDENTIFIER", "develop")
 language = "en"
 
 try:
@@ -72,6 +80,7 @@
 # Sphinx extensions
 extensions = [
     "jupyter_sphinx",
+    "myst_parser",
     "sphinx.ext.autodoc",
     "sphinx.ext.autodoc.typehints",
     "sphinx.ext.autosummary",
@@ -111,6 +120,14 @@
 html_theme_options = {
     "use_edit_page_button": True,
     "github_url": github_url,
+    "switcher": {
+        "json_url": (
+            "https://fda.readthedocs.io/en/latest/_static/switcher.json"
+        ),
+        "version_match": switcher_version,
+    },
+    "show_version_warning_banner": True,
+    "navbar_start": ["navbar-logo", "version-switcher"],
     "icon_links": [
         {
             "name": "PyPI",
@@ -288,7 +305,7 @@ def linkcode_resolve(domain: str, info: Mapping[str, str]) -> str | None:
     else:
         linespec = ""
 
-    return f"{github_url}/tree/{branch}/skfda/{fn}{linespec}"
+    return f"{github_url}/tree/{rtd_branch}/skfda/{fn}{linespec}"
 
 # -- Options for "sphinx.ext.mathjax" --
 
@@ -390,7 +407,7 @@ def __repr__(self) -> str:
     "binder": {
         "org": "GAA-UAM",
         "repo": "scikit-fda",
-        "branch": branch,
+        "branch": rtd_branch,
         "binderhub_url": "https://mybinder.org",
         "dependencies": ["../binder/requirements.txt"],
         "notebooks_dir": "../examples",

docs/contributors.md

@@ -0,0 +1,2 @@
+```{include} ../CONTRIBUTORS.md
+```

docs/index.rst

@@ -34,7 +34,8 @@ Github you can find more information related to the development of the package.
    :caption: More documentation
 
    apilist
-   glossary
+   Glossary <glossary>
+   contributors
 
 An exhaustive list of all the contents of the package can be found in the
 :ref:`genindex`.
@@ -86,8 +87,7 @@ All contributions are welcome. You can help this project grow in multiple ways,
 from creating an issue, reporting an improvement or a bug, to doing a
 repository fork and creating a pull request to the development branch.
 The people involved at some point in the development of the package can be
-found in the `contributors file
-<https://github.com/GAA-UAM/scikit-fda/blob/develop/THANKS.txt>`_.
+found in the :doc:`contributors page <contributors>`.
 
 .. Citation
    --------

docs/modules/exploratory/stats.rst

@@ -31,4 +31,5 @@ statistics can be used.
 
    skfda.exploratory.stats.cov
    skfda.exploratory.stats.var
+   skfda.exploratory.stats.std
 

docs/refs.bib

@@ -364,6 +364,21 @@ @article{pini++_2018_hotelling
   keywords = {Functional data,High-dimensional data Hotelling’s,Hilbert space,Nonparametric inference,Permutation test}
 }
 
+@incollection{pintado+romo_2005_depthbased,
+  title = {Depth-Based Classification for Functional Data},
+  shorttitle = {Data {{Depth}}},
+  booktitle = {Data {{Depth}}: {{Robust Multivariate Analysis}}, {{Computational Geometry}} and {{Applications}}},
+  author = {Pintado, Sara and Romo, Juan},
+  year = {2005},
+  month = nov,
+  series = {{{DIMACS Series}} in {{Discrete Mathematics}} and {{Theoretical Computer Science}}},
+  volume = {72},
+  pages = {103--119},
+  publisher = {{American Mathematical Society}},
+  doi = {10.1090/dimacs/072/08},
+  isbn = {978-0-8218-3596-8}
+}
+
 @inbook{ramsay+silverman_2005_functionala,
   title = {From Functional Data to Smooth Functions},
   booktitle = {Functional Data Analysis},

examples/full_examples/plot_aemet_unsupervised.py

@@ -14,11 +14,13 @@
 
 from typing import Any, Mapping, Tuple
 
+import cartopy.crs as ccrs
 import matplotlib.pyplot as plt
 import numpy as np
 import sklearn.cluster
+from cartopy.io.img_tiles import GoogleTiles
 from matplotlib.axes import Axes
-from mpl_toolkits.basemap import Basemap
+from matplotlib.figure import Figure
 
 from skfda.datasets import fetch_aemet
 from skfda.exploratory.depth import ModifiedBandDepth
@@ -68,8 +70,8 @@
 ##############################################################################
 # We want to plot the cluster of each station in the map of Spain. We need to
 # define first auxiliary variables and functions for plotting.
-coords_spain = (-10, 34.98, 5, 44.8)
-coords_canary = (-18.5, 27.5, -13, 29.5)
+coords_spain = (-10, 5, 34.98, 44.8)
+coords_canary = (-18.5, -13, 27.5, 29.5)
 
 # It is easier to obtain the longitudes and latitudes from the data in
 # a Pandas dataframe.
@@ -81,44 +83,39 @@
 
 def create_map(
     coords: Tuple[float, float, float, float],
-    ax: Axes,
-) -> Basemap:
+    figsize: Tuple[float, float],
+) -> Figure:
     """Create a map for a region of the world."""
-    basemap = Basemap(
-        *coords,
-        projection='merc',
-        resolution="h",
-        epsg=4326,
-        ax=ax,
-        fix_aspect=False,
-    )
-    basemap.arcgisimage(
-        service='World_Imagery',
-        xpixels=1000,
-        dpi=100,
-    )
+    tiler = GoogleTiles(style="satellite")
+    mercator = tiler.crs
 
-    return basemap
+    fig = plt.figure(figsize=figsize)
+    ax = fig.add_axes([0, 0, 1, 1], projection=mercator)
+    ax.set_extent(coords, crs=ccrs.PlateCarree())
+
+    ax.add_image(tiler, 8)
+    ax.set_adjustable('datalim')
+
+    return fig
 
 
 def plot_cluster_points(
     longitudes: np.typing.NDArray[np.floating[Any]],
     latitudes: np.typing.NDArray[np.floating[Any]],
     clusters: np.typing.NDArray[np.integer[Any]],
     color_map: Mapping[int, str],
-    basemap: Basemap,
     ax: Axes,
 ) -> None:
     """Plot the stations in a map with their cluster color."""
-    x, y = basemap(longitudes, latitudes)
     for cluster in range(n_clusters):
         selection = (clusters == cluster)
         ax.scatter(
-            x[selection],
-            y[selection],
+            longitudes[selection],
+            latitudes[selection],
             s=64,
             color=color_map[cluster],
             edgecolors='white',
+            transform=ccrs.Geodetic(),
         )
 
 
@@ -144,29 +141,23 @@ def plot_cluster_points(
 # We now plot the obtained clustering in the maps.
 
 # Mainland
-fig_spain = plt.figure(figsize=(8, 6))
-ax_spain = fig_spain.add_axes([0, 0, 1, 1])
-map_spain = create_map(coords_spain, ax=ax_spain)
+fig_spain = create_map(coords_spain, figsize=(8, 6))
 plot_cluster_points(
     longitudes=station_longitudes,
     latitudes=station_latitudes,
     clusters=fda_clusters,
     color_map=fda_color_map,
-    basemap=map_spain,
-    ax=ax_spain,
+    ax=fig_spain.axes[0],
 )
 
 # Canary Islands
-fig_canary = plt.figure(figsize=(8, 3))
-ax_canary = fig_canary.add_axes([0, 0, 1, 1])
-map_canary = create_map(coords_canary, ax=ax_canary)
+fig_canary = create_map(coords_canary, figsize=(8, 3))
 plot_cluster_points(
     longitudes=station_longitudes,
     latitudes=station_latitudes,
     clusters=fda_clusters,
     color_map=fda_color_map,
-    basemap=map_canary,
-    ax=ax_canary,
+    ax=fig_canary.axes[0],
 )
 plt.show()
 
@@ -228,36 +219,30 @@ def plot_cluster_points(
 # color map to match cluster colors with the previously obtained ones.
 
 mv_color_map = {
-    0: "red",
-    1: "purple",
-    2: "yellow",
-    3: "green",
-    4: "orange",
+    0: "yellow",
+    1: "orange",
+    2: "red",
+    3: "purple",
+    4: "green",
 }
 
 # Mainland
-fig_spain = plt.figure(figsize=(8, 6))
-ax_spain = fig_spain.add_axes([0, 0, 1, 1])
-map_spain = create_map(coords_spain, ax=ax_spain)
+fig_spain = create_map(coords_spain, figsize=(8, 6))
 plot_cluster_points(
     longitudes=station_longitudes,
     latitudes=station_latitudes,
     clusters=mv_clusters,
     color_map=mv_color_map,
-    basemap=map_spain,
-    ax=ax_spain,
+    ax=fig_spain.axes[0],
 )
 
 # Canary Islands
-fig_canary = plt.figure(figsize=(8, 3))
-ax_canary = fig_canary.add_axes([0, 0, 1, 1])
-map_canary = create_map(coords_canary, ax=ax_canary)
+fig_canary = create_map(coords_canary, figsize=(8, 3))
 plot_cluster_points(
     longitudes=station_longitudes,
     latitudes=station_latitudes,
     clusters=mv_clusters,
     color_map=mv_color_map,
-    basemap=map_canary,
-    ax=ax_canary,
+    ax=fig_canary.axes[0],
 )
 plt.show()