Merge pull request #296 from euroargodev/release-v0.1.14

Prepare for "v0.1.14 Frog release 🐸"

HOW_TO_RELEASE.md

@@ -1,8 +1,8 @@
 # Setup
 
 - [ ] Create a new branch for this release: ``git checkout -b releasev0.X.Y``
-- [ ] Increase release version in ``./setup.py``
 - [ ] Update release version in ``./docs/whats-new.rst``
+- [ ] Increase release version in ``./setup.py``
 - [ ] Create a PR to prepare it, name it with one of the [Nature emoji](https://www.webfx.com/tools/emoji-cheat-sheet/#tabs-3) and make sure it was [never used before](https://github.com/euroargodev/argopy/pulls?q=is%3Apr+label%3Arelease+) 
 
 # Prepare code for release
@@ -14,8 +14,7 @@
 ## Software distribution readiness
 - [ ] Manually trigger [upstream CI tests](https://github.com/euroargodev/argopy/actions/workflows/pytests-upstream.yml) for the release branch and ensure they are passed
 - [ ] Update pinned dependencies versions in ``./ci/requirements/py*-*-pinned.yml`` environment files using [upstream CI tests](https://github.com/euroargodev/argopy/actions/workflows/pytests-upstream.yml) information
-- [ ] If CI tests with the oldest dependencies versions are not passed, upgrade these versions in ``./ci/requirements/py*-*-min.yml`` files up to the point where CI tests are passed
-- [ ] Possibly update ``./requirements.txt`` and ``./docs/requirements.txt`` if the oldest dependencies versions were upgraded in the previous step
+- [ ] Possibly update ``./requirements.txt`` and ``./docs/requirements.txt`` if the oldest dependencies versions were upgraded
 - [ ] Make sure that all CI tests are passed
 - [ ] [Activate](https://readthedocs.org/projects/argopy/versions/) and make sure the documentation for the release branch is [built on RTD](https://readthedocs.org/projects/argopy/builds/)
 

argopy/data_fetchers/erddap_data.py

@@ -445,26 +445,26 @@ def _bgc_vlist_avail(self):
 
         return results
 
-    def _bgc_handle_wildcard(self, param_list):
-        """In a list, replace item with wildcard by available BGC parameter(s)"""
-        is_valid_param = lambda x: x in list(  # noqa: E731
-            argopy.ArgoNVSReferenceTables().tbl(3)["altLabel"]
-        )
-
-        results = param_list.copy()
-        for p in param_list:
-            if not is_valid_param(p):
-                if "*" not in p:
-                    raise ValueError(
-                        "Invalid BGC parameter '%s' (not listed in Argo reference table 3)"
-                        % p
-                    )
-                else:
-                    match = fnmatch.filter(self._bgc_vlist_avail, p)
-                    if len(match) > 0:
-                        [results.append(m) for m in match]
-                        results.remove(p)
-        return results
+    # def _bgc_handle_wildcard(self, param_list):
+    #     """In a list, replace item with wildcard by available BGC parameter(s)"""
+    #     is_valid_param = lambda x: x in list(  # noqa: E731
+    #         argopy.ArgoNVSReferenceTables().tbl(3)["altLabel"]
+    #     )
+
+    #     results = param_list.copy()
+    #     for p in param_list:
+    #         if not is_valid_param(p):
+    #             if "*" not in p:
+    #                 raise ValueError(
+    #                     "Invalid BGC parameter '%s' (not listed in Argo reference table 3)"
+    #                     % p
+    #                 )
+    #             else:
+    #                 match = fnmatch.filter(self._bgc_vlist_avail, p)
+    #                 if len(match) > 0:
+    #                     [results.append(m) for m in match]
+    #                     results.remove(p)
+    #     return results
 
     @property
     def _minimal_vlist(self):

argopy/plot/__init__.py

@@ -4,7 +4,7 @@
 from .plot import plot_trajectory, bar_plot, open_sat_altim_report, scatter_map, scatter_plot
 from .argo_colors import ArgoColors
 from .dashboards import open_dashboard as dashboard
-from .utils import discrete_coloring, latlongrid
+from .utils import latlongrid
 
 
 __all__ = (
@@ -21,5 +21,4 @@
 
     # Utils:
     "latlongrid",
-    "discrete_coloring",
 )

argopy/plot/utils.py

@@ -1,7 +1,6 @@
 import numpy as np
 from contextlib import contextmanager
 import importlib
-from ..utils.decorators import deprecated
 
 
 def _importorskip(modname):
@@ -64,160 +63,6 @@ def axes_style(style: str = STYLE["axes"]):
         yield
 
 
-@deprecated("The 'discrete_coloring' plotting utility is deprecated since 0.1.13. It's been replaced by 'ArgoColors'. Calling it will raise an error after argopy 0.1.14")
-class discrete_coloring:
-    """ Handy class to manage discrete coloring and the associated colorbar
-
-    Warnings
-    --------
-        This plotting utility is deprecated since 0.1.13. It's been replaced by :class:`argopy.plot.ArgoColors`. Calling
-        it will raise an error after argopy 0.1.14.
-
-    Examples
-    --------
-    This class can be used like this:
-
-    ::
-
-        year_range = np.arange(2002,2010)
-        dc = discrete_coloring(name='Spectral', N=len(year_range) )
-        plt.scatter(this['LONGITUDE'], this['LATITUDE'], c=this['TIME.year'],
-                    cmap=dc.cmap, vmin=year_range[0], vmax=year_range[-1])
-        dc.cbar(ticklabels=yr_range, fraction=0.03, label='Years')
-
-    """
-
-    def __init__(self, name="Set1", N=12):
-        """
-
-        Parameters
-        ----------
-        name: str
-            Name if the colormap to use. Default: 'Set1'
-        N: int
-            Number of colors to reduce the colormap to. Default: 12
-        """
-        self.name = name
-        self.Ncolors = N
-
-    @property
-    def cmap(self):
-        """Return a discrete colormap from a quantitative or continuous colormap name
-
-        Returns
-        -------
-        :class:`matplotlib.colors.LinearSegmentedColormap`
-        """
-        name = self.name
-        K = self.Ncolors
-        if name in [
-            "Set1",
-            "Set2",
-            "Set3",
-            "Pastel1",
-            "Pastel2",
-            "Paired",
-            "Dark2",
-            "Accent",
-        ]:
-            # Segmented (or quantitative) colormap:
-            N_ref = {
-                "Set1": 9,
-                "Set2": 8,
-                "Set3": 12,
-                "Pastel1": 9,
-                "Pastel2": 8,
-                "Paired": 12,
-                "Dark2": 8,
-                "Accent": 8,
-            }
-            N = N_ref[name]
-            cmap = plt.get_cmap(name=name)
-            colors_i = np.concatenate(
-                (np.linspace(0, 1.0, N), (0.0, 0.0, 0.0, 0.0)), axis=0
-            )
-            cmap = cmap(colors_i)  # N x 4
-            n = np.arange(0, N)
-            new_n = n.copy()
-            if K > N:
-                for k in range(N, K):
-                    r = np.roll(n, -k)[0][np.newaxis]
-                    new_n = np.concatenate((new_n, r), axis=0)
-            new_cmap = cmap.copy()
-            new_cmap = cmap[new_n, :]
-            new_cmap = mcolors.LinearSegmentedColormap.from_list(
-                name + "_%d" % K, colors=new_cmap, N=K
-            )
-        elif name == "Month":
-            clist = [
-                "darkslateblue",
-                "skyblue",
-                "powderblue",
-                "honeydew",
-                "lemonchiffon",
-                "pink",
-                "salmon",
-                "deeppink",
-                "gold",
-                "chocolate",
-                "darkolivegreen",
-                "cadetblue",
-            ]
-            cmap = mcolors.LinearSegmentedColormap.from_list("my_colormap", clist)
-            N = 12
-            colors_i = np.concatenate((np.linspace(0, 1.0, N), (0.0, 0.0, 0.0, 0.0)))
-            colors_rgba = cmap(colors_i)
-            indices = np.linspace(0, 1.0, N + 1)
-            cdict = {}
-            for ki, key in enumerate(("red", "green", "blue")):
-                cdict[key] = [
-                    (indices[i], colors_rgba[i - 1, ki], colors_rgba[i, ki])
-                    for i in np.arange(N + 1)
-                ]
-            new_cmap = mcolors.LinearSegmentedColormap("month_%d" % N, cdict, N)
-        else:
-            # Continuous colormap:
-            N = K
-            cmap = plt.get_cmap(name=name)
-            colors_i = np.concatenate((np.linspace(0, 1.0, N), (0.0, 0.0, 0.0, 0.0)))
-            colors_rgba = cmap(colors_i)  # N x 4
-            indices = np.linspace(0, 1.0, N + 1)
-            cdict = {}
-            for ki, key in enumerate(("red", "green", "blue")):
-                cdict[key] = [
-                    (indices[i], colors_rgba[i - 1, ki], colors_rgba[i, ki])
-                    for i in np.arange(N + 1)
-                ]
-            # Return colormap object.
-            new_cmap = mcolors.LinearSegmentedColormap(cmap.name + "_%d" % N, cdict, N)
-        self._colormap = new_cmap
-        return new_cmap
-
-    def cbar(self, ticklabels=None, **kwargs):
-        """Return a colorbar with adjusted tick labels
-
-        Returns
-        -------
-        :class:`matplotlib.pyplot.colorbar`
-        """
-        cmap = self.cmap
-        ncolors = self.Ncolors
-        mappable = cm.ScalarMappable(cmap=cmap)
-        mappable.set_array([])
-        mappable.set_clim(-0.5, ncolors + 0.5)
-        colorbar = plt.colorbar(mappable, **kwargs)
-        colorbar.set_ticks(np.linspace(0, ncolors, ncolors))
-        colorbar.set_ticklabels(ticklabels)
-        self._colorbar = colorbar
-        return colorbar
-
-    def to_rgba(self, range, value):
-        """ Return the RGBA color for a given value of the colormap and a range """
-        norm = mpl.colors.Normalize(vmin=range[0], vmax=range[-1])
-        scalarMap = cm.ScalarMappable(norm=norm, cmap=self.cmap)
-        return scalarMap.to_rgba(value)
-
-
 def latlongrid(ax, dx="auto", dy="auto", fontsize="auto", label_style_arg={}, **kwargs):
     """ Add latitude/longitude grid line and labels to a cartopy geoaxes
 

argopy/related/euroargo_api.py

@@ -98,4 +98,3 @@ def get_ea_profile_page(WMO, CYC=None, **kwargs):
     df = get_coriolis_profile_id(WMO, CYC, **kwargs)
     url = "https://dataselection.euro-argo.eu/cycle/{}"
     return [url.format(this_id) for this_id in sorted(df["ID"])]
-

argopy/related/utils.py

@@ -39,4 +39,3 @@ def mapp_dict(Adictionnary, Avalue):
         return "Unknown"
     else:
         return Adictionnary[Avalue]
-

argopy/stores/filesystems.py

@@ -223,7 +223,7 @@ def cached_files(self):
         else:
             # See https://github.com/euroargodev/argopy/issues/294
             return self.fs._metadata.cached_files
-        
+
     def cachepath(self, uri: str, errors: str = "raise"):
         """Return path to cached file for a given URI"""
         if not self.cache:
@@ -261,7 +261,7 @@ def _clear_cache_item(self, uri):
                     cached_files = json.load(f)
         else:
             cached_files = cache
-            
+
         # Build new metadata without uri to delete, and delete corresponding cached file:
         cache = {}
         for k, v in cached_files.items():
@@ -271,7 +271,7 @@ def _clear_cache_item(self, uri):
                 # Delete file:
                 os.remove(os.path.join(self.fs.storage[-1], v["fn"]))
                 # log.debug("Removed %s -> %s" % (uri, v['fn']))
-        
+
         # Update cache metadata file:
         if version.parse(fsspec.__version__) <= version.parse("2023.6.0"):
             with tempfile.NamedTemporaryFile(mode="wb", delete=False) as f:

argopy/utils/__init__.py

@@ -12,7 +12,7 @@
     check_index_cols,
     check_gdac_path,
     isconnected,
-    urlhaskeyword,
+    urlhaskeyword,  # noqa: F401
     isalive,
     isAPIconnected,
     erddap_ds_exists,
@@ -33,10 +33,10 @@
     show_versions,
     show_options,
     modified_environ,
-    get_sys_info,
-    netcdf_and_hdf5_versions,
+    get_sys_info,   # noqa: F401
+    netcdf_and_hdf5_versions,  # noqa: F401
 )
-from .monitors import monitor_status, badge, fetch_status
+from .monitors import monitor_status, badge, fetch_status  # noqa: F401
 from .geo import wmo2box, wrap_longitude, toYearFraction, YearFraction_to_datetime
 from .compute import linear_interpolation_remap, groupby_remap
 from .transform import (

argopy/utils/casting.py

@@ -20,7 +20,7 @@
     DATA_TYPES = json.load(f)
 
 
-@deprecated
+@deprecated("The 'cast_types' utility is deprecated since 0.1.13. It's been replaced by 'cast_Argo_variable_type'. Calling it will raise an error after argopy 0.1.15")
 def cast_types(ds):  # noqa: C901
     """Make sure variables are of the appropriate types according to Argo
 

ci/requirements/py3.8-all-free.yml

@@ -10,6 +10,7 @@ dependencies:
   - fsspec
   - netCDF4
   - packaging
+  - requests
   - scipy
   - toolz
   - xarray
@@ -33,6 +34,7 @@ dependencies:
   - seaborn
 
 # DEV:
+  - aiofiles
   - black
   - bottleneck
   - cfgrib
@@ -47,11 +49,7 @@ dependencies:
   - pytest-cov
   - pytest-env
   - pytest-localftpserver
-  # - pytest-reportlog
-  - aiofiles
   - setuptools
-#  - sphinx
-  - requests
 
   - pip:
       - pytest-reportlog