diff --git a/.codespellrc b/.codespellrc
index a11a40ac..439f6ea7 100644
--- a/.codespellrc
+++ b/.codespellrc
@@ -1,5 +1,5 @@
[codespell]
-skip = *.nc,*.ipynb,./local_work,./float_source,./binder,./.github,*.log,./.git,./docs/_build,./docs/_static,./argopy/tests/test_data,./build,./docs/mycache_folder,./docs/examples/cache_bgc
+skip = *.nc,*.ipynb,./local_work,./float_source,./binder,./.github,*.log,./.git,./docs/_build,./docs/_static,./argopy/tests/test_data,./build,./docs/mycache_folder,./docs/examples/cache_bgc,./argopy/static/assets/*.json
count =
quiet-level = 3
ignore-words-list = PRES, pres, idel
\ No newline at end of file
diff --git a/.flake8 b/.flake8
index c9f9129c..845125b6 100644
--- a/.flake8
+++ b/.flake8
@@ -10,7 +10,8 @@ ignore =
E501,
# line break before binary operator
W503
-
+ # whitespace before ':' (https://black.readthedocs.io/en/stable/guides/using_black_with_other_tools.html#e203)
+ E203
exclude =
# No need to traverse our git directory
.git,
diff --git a/.github/workflows/pytests-upstream.yml b/.github/workflows/pytests-upstream.yml
index d98bc65f..7cde501c 100644
--- a/.github/workflows/pytests-upstream.yml
+++ b/.github/workflows/pytests-upstream.yml
@@ -74,7 +74,7 @@ jobs:
strategy:
fail-fast: true
matrix:
- python-version: ["3.8", "3.9"]
+ python-version: ["3.9", "3.10"]
os: ["ubuntu-latest", "macos-latest", "windows-latest"]
steps:
@@ -200,7 +200,7 @@ jobs:
strategy:
fail-fast: true
matrix:
- python-version: ["3.8", "3.9"]
+ python-version: ["3.9", "3.10"]
os: ["ubuntu-latest", "macos-latest", "windows-latest"]
steps:
diff --git a/.github/workflows/pytests.yml b/.github/workflows/pytests.yml
index 43d77dec..23afc8f5 100644
--- a/.github/workflows/pytests.yml
+++ b/.github/workflows/pytests.yml
@@ -52,7 +52,7 @@ jobs:
max-parallel: 12
fail-fast: false
matrix:
- python-version: ["3.8", "3.9"]
+ python-version: ["3.9", "3.10"]
os: ["ubuntu-latest", "windows-latest", "macos-latest"]
experimental: [false]
@@ -174,7 +174,7 @@ jobs:
max-parallel: 12
fail-fast: false
matrix:
- python-version: ["3.8", "3.9"]
+ python-version: ["3.9", "3.10"]
os: ["ubuntu-latest", "macos-latest", "windows-latest"]
experimental: [false]
diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md
index b71b0dde..905f2f94 100644
--- a/CODE_OF_CONDUCT.md
+++ b/CODE_OF_CONDUCT.md
@@ -6,7 +6,7 @@ In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to making participation in our project and
our community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, sex characteristics, gender identity and expression,
-level of experience, education, socio-economic status, nationality, personal
+level of experience, education, socioeconomic status, nationality, personal
appearance, race, religion, or sexual identity and orientation.
## Our Standards
diff --git a/argopy/__init__.py b/argopy/__init__.py
index 3eef4a01..824dbf70 100644
--- a/argopy/__init__.py
+++ b/argopy/__init__.py
@@ -29,7 +29,6 @@
# Other Import
# from . import utils # noqa: E402
-from . import utilities # noqa: E402 # being deprecated until 0.1.15, then remove
from . import stores # noqa: E402
from . import errors # noqa: E402
from . import plot # noqa: E402
@@ -72,7 +71,6 @@
"ArgoDOI", # Class
# Submodules:
- "utilities", # being deprecated until 0.1.15, then remove
# "utils",
"errors",
"plot",
diff --git a/argopy/data_fetchers/argovis_data.py b/argopy/data_fetchers/argovis_data.py
index 0fc4b6b9..a8362b0e 100644
--- a/argopy/data_fetchers/argovis_data.py
+++ b/argopy/data_fetchers/argovis_data.py
@@ -1,9 +1,3 @@
-#!/bin/env python
-# -*coding: UTF-8 -*-
-#
-# Argo data fetcher for Argovis.
-#
-
import numpy as np
import pandas as pd
import xarray as xr
@@ -23,7 +17,7 @@
access_points = ["wmo", "box"]
exit_formats = ["xarray"]
dataset_ids = ["phy"] # First is default
-api_server = "https://argovis-api.colorado.edu"
+api_server = "https://argovis-api.colorado.edu"
api_server_check = "https://argovis-api.colorado.edu/ping"
log = logging.getLogger("argopy.argovis.data")
@@ -58,7 +52,7 @@ def __init__(
chunks: str = "auto",
chunks_maxsize: dict = {},
api_timeout: int = 0,
- **kwargs
+ **kwargs,
):
"""Instantiate an Argovis Argo data loader
@@ -95,7 +89,7 @@ def __init__(
"cachedir": cachedir,
"timeout": timeout,
# "size_policy": "head", # deprecated
- "client_kwargs": {"headers": {'x-argokey': OPTIONS['argovis_api_key']}},
+ "client_kwargs": {"headers": {"x-argokey": OPTIONS["argovis_api_key"]}},
}
self.fs = kwargs["fs"] if "fs" in kwargs else httpstore(**self.store_opts)
@@ -134,9 +128,12 @@ def __repr__(self):
summary = ["<datafetcher.argovis>"]
summary.append("Name: %s" % self.definition)
summary.append("API: %s" % api_server)
- api_key = self.fs.fs.client_kwargs['headers']['x-argokey']
- if api_key == DEFAULT['argovis_api_key']:
- summary.append("API KEY: '%s' (get a free key at https://argovis-keygen.colorado.edu)" % api_key)
+ api_key = self.fs.fs.client_kwargs["headers"]["x-argokey"]
+ if api_key == DEFAULT["argovis_api_key"]:
+ summary.append(
+ "API KEY: '%s' (get a free key at https://argovis-keygen.colorado.edu)"
+ % api_key
+ )
else:
summary.append("API KEY: '%s'" % api_key)
summary.append("Domain: %s" % format_oneline(self.cname()))
@@ -286,24 +283,32 @@ def json2dataframe(self, profiles):
for profile in data:
# construct metadata dictionary that will be repeated for each level
metadict = {
- 'date': profile['timestamp'],
- 'date_qc': profile['timestamp_argoqc'],
- 'lat': profile['geolocation']['coordinates'][1],
- 'lon': profile['geolocation']['coordinates'][0],
- 'cycle_number': profile['cycle_number'],
- 'DATA_MODE': profile['data_info'][2][0][1],
- 'DIRECTION': profile['profile_direction'],
- 'platform_number': profile['_id'].split('_')[0],
- 'position_qc': profile['geolocation_argoqc'],
- 'index': 0
+ "date": profile["timestamp"],
+ "date_qc": profile["timestamp_argoqc"],
+ "lat": profile["geolocation"]["coordinates"][1],
+ "lon": profile["geolocation"]["coordinates"][0],
+ "cycle_number": profile["cycle_number"],
+ "DATA_MODE": profile["data_info"][2][0][1],
+ "DIRECTION": profile["profile_direction"],
+ "platform_number": profile["_id"].split("_")[0],
+ "position_qc": profile["geolocation_argoqc"],
+ "index": 0,
}
# construct a row for each level in the profile
- for i in range(len(profile['data'][profile['data_info'][0].index('pressure')])):
+ for i in range(
+ len(profile["data"][profile["data_info"][0].index("pressure")])
+ ):
row = {
- 'temp': profile['data'][profile['data_info'][0].index('temperature')][i],
- 'pres': profile['data'][profile['data_info'][0].index('pressure')][i],
- 'psal': profile['data'][profile['data_info'][0].index('salinity')][i],
- **metadict
+ "temp": profile["data"][
+ profile["data_info"][0].index("temperature")
+ ][i],
+ "pres": profile["data"][profile["data_info"][0].index("pressure")][
+ i
+ ],
+ "psal": profile["data"][profile["data_info"][0].index("salinity")][
+ i
+ ],
+ **metadict,
}
rows.append(row)
df = pd.DataFrame(rows)
@@ -375,8 +380,8 @@ def to_xarray(self, errors: str = "ignore"):
ds.attrs["Fetched_from"] = self.server
try:
ds.attrs["Fetched_by"] = getpass.getuser()
- except:
- ds.attrs["Fetched_by"] = 'anonymous'
+ except: # noqa: E722
+ ds.attrs["Fetched_by"] = "anonymous"
ds.attrs["Fetched_date"] = pd.to_datetime("now", utc=True).strftime("%Y/%m/%d")
ds.attrs["Fetched_constraints"] = self.cname()
ds.attrs["Fetched_uri"] = self.uri
@@ -435,9 +440,9 @@ def init(self, WMO=[], CYC=None, **kwargs):
def get_url(self, wmo: int, cyc: int = None) -> str:
"""Return path toward the source file of a given wmo/cyc pair"""
if cyc is None:
- return f'{self.server}/argo?platform={str(wmo)}&data=pressure,temperature,salinity'
+ return f"{self.server}/argo?platform={str(wmo)}&data=pressure,temperature,salinity"
else:
- return f'{self.server}/argo?id={str(wmo)}_{str(cyc).zfill(3)}&data=pressure,temperature,salinity'
+ return f"{self.server}/argo?id={str(wmo)}_{str(cyc).zfill(3)}&data=pressure,temperature,salinity"
@property
def uri(self):
@@ -488,10 +493,7 @@ def init(self, box: list, **kwargs):
def get_url(self):
"""Return the URL used to download data"""
- shape = [
- [self.BOX[0], self.BOX[2]], # ll
- [self.BOX[1], self.BOX[3]] # ur
- ]
+ shape = [[self.BOX[0], self.BOX[2]], [self.BOX[1], self.BOX[3]]] # ll # ur
strShape = str(shape).replace(" ", "")
url = self.server + "/argo?data=pressure,temperature,salinity&box=" + strShape
url += "&startDate={}".format(
@@ -558,4 +560,4 @@ def uri(self):
for box in boxes:
urls.append(Fetch_box(box=box, ds=self.dataset_id).get_url())
- return self.url_encode(urls)
\ No newline at end of file
+ return self.url_encode(urls)
diff --git a/argopy/data_fetchers/erddap_data.py b/argopy/data_fetchers/erddap_data.py
index 8300c39a..c0b27980 100644
--- a/argopy/data_fetchers/erddap_data.py
+++ b/argopy/data_fetchers/erddap_data.py
@@ -27,8 +27,10 @@
from ..utils.format import format_oneline
from ..stores import httpstore
from ..errors import ErddapServerError, DataNotFound
-from ..stores import indexstore_pd as ArgoIndex # make sure we work with the Pandas index store
-from ..utils import is_list_of_strings, to_list,Chunker
+from ..stores import (
+ indexstore_pd as ArgoIndex,
+) # make sure we work with the Pandas index store
+from ..utils import is_list_of_strings, to_list, Chunker
from .proto import ArgoDataFetcherProto
@@ -159,11 +161,15 @@ def __init__( # noqa: C901
# This will be used to:
# - retrieve the list of BGC variables to ask the erddap server
# - get <param>_data_mode information because we can't get it from the server
- self.indexfs = kwargs['indexfs'] if 'indexfs' in kwargs else ArgoIndex(
- index_file='argo_synthetic-profile_index.txt', # the only available in the erddap
- cache=kwargs['cache_index'] if 'cache_index' in kwargs else cache,
- cachedir=cachedir,
- timeout=timeout,
+ self.indexfs = (
+ kwargs["indexfs"]
+ if "indexfs" in kwargs
+ else ArgoIndex(
+ index_file="argo_synthetic-profile_index.txt", # the only available in the erddap
+ cache=kwargs["cache_index"] if "cache_index" in kwargs else cache,
+ cachedir=cachedir,
+ timeout=timeout,
+ )
)
# To handle bugs in the erddap server, we need the list of parameters on the server:
@@ -615,7 +621,9 @@ def getNfromncHeader(url):
return N
- def post_process(self, this_ds, add_dm: bool = True, URI: list = None): # noqa: C901
+ def post_process(
+ self, this_ds, add_dm: bool = True, URI: list = None
+ ): # noqa: C901
"""Post-process a xarray.DataSet created from a netcdf erddap response
This method can also be applied on a regular dataset to re-enforce format compliance
@@ -667,8 +675,8 @@ def post_process(self, this_ds, add_dm: bool = True, URI: list = None): # noqa:
# In the case of a parallel download, this is a trick to preserve the chunk uri in the chunk dataset:
# (otherwise all chunks have the same list of uri)
- Fetched_url = this_ds.attrs.get('Fetched_url', False)
- Fetched_constraints = this_ds.attrs.get('Fetched_constraints', False)
+ Fetched_url = this_ds.attrs.get("Fetched_url", False)
+ Fetched_constraints = this_ds.attrs.get("Fetched_constraints", False)
# Finally overwrite erddap attributes with those from argopy:
raw_attrs = this_ds.attrs.copy()
@@ -691,12 +699,14 @@ def post_process(self, this_ds, add_dm: bool = True, URI: list = None): # noqa:
this_ds.attrs["Fetched_from"] = self.erddap.server
try:
this_ds.attrs["Fetched_by"] = getpass.getuser()
- except:
- this_ds.attrs["Fetched_by"] = 'anonymous'
+ except: # noqa: E722
+ this_ds.attrs["Fetched_by"] = "anonymous"
this_ds.attrs["Fetched_date"] = pd.to_datetime("now", utc=True).strftime(
"%Y/%m/%d"
)
- this_ds.attrs["Fetched_constraints"] = self.cname() if not Fetched_constraints else Fetched_constraints
+ this_ds.attrs["Fetched_constraints"] = (
+ self.cname() if not Fetched_constraints else Fetched_constraints
+ )
this_ds.attrs["Fetched_uri"] = URI if not Fetched_url else Fetched_url
this_ds = this_ds[np.sort(this_ds.data_vars)]
diff --git a/argopy/data_fetchers/gdacftp_data.py b/argopy/data_fetchers/gdacftp_data.py
index aae219d7..10442340 100644
--- a/argopy/data_fetchers/gdacftp_data.py
+++ b/argopy/data_fetchers/gdacftp_data.py
@@ -283,7 +283,7 @@ def _preprocess_multiprof(self, ds):
ds.attrs["Fetched_from"] = self.server
try:
ds.attrs["Fetched_by"] = getpass.getuser()
- except:
+ except: # noqa: E722
ds.attrs["Fetched_by"] = 'anonymous'
ds.attrs["Fetched_date"] = pd.to_datetime("now", utc=True).strftime("%Y/%m/%d")
ds.attrs["Fetched_constraints"] = self.cname()
@@ -352,7 +352,7 @@ def to_xarray(self, errors: str = "ignore"):
ds.attrs["Fetched_from"] = self.server
try:
ds.attrs["Fetched_by"] = getpass.getuser()
- except:
+ except: # noqa: E722
ds.attrs["Fetched_by"] = 'anonymous'
ds.attrs["Fetched_date"] = pd.to_datetime("now", utc=True).strftime("%Y/%m/%d")
ds.attrs["Fetched_constraints"] = self.cname()
diff --git a/argopy/plot/plot.py b/argopy/plot/plot.py
index 8db1b22e..fd5486ca 100644
--- a/argopy/plot/plot.py
+++ b/argopy/plot/plot.py
@@ -43,34 +43,39 @@
log = logging.getLogger("argopy.plot.plot")
-def open_sat_altim_report(WMO: Union[str, list] = None, embed: Union[str, None] = "dropdown", **kwargs):
- """ Insert the CLS Satellite Altimeter Report figure in notebook cell
+def open_sat_altim_report(
+ WMO: Union[str, list] = None, embed: Union[str, None] = "dropdown", **kwargs
+):
+ """Insert the CLS Satellite Altimeter Report figure in notebook cell
- This is the method called when using the facade fetcher methods ``plot``::
+ This is the method called when using the facade fetcher methods ``plot``::
- DataFetcher().float(6902745).plot('qc_altimetry')
+ DataFetcher().float(6902745).plot('qc_altimetry')
- Parameters
- ----------
- WMO: int or list
- The float WMO to display. By default, this is set to None and will insert the general dashboard.
- embed: str, default='dropdown'
- Set the embedding method. If set to None, simply return the list of urls to figures.
- Possible values are: ``dropdown``, ``slide`` and ``list``.
+ Parameters
+ ----------
+ WMO: int or list
+ The float WMO to display. By default, this is set to None and will insert the general dashboard.
+ embed: str, default='dropdown'
+ Set the embedding method. If set to None, simply return the list of urls to figures.
+ Possible values are: ``dropdown``, ``slide`` and ``list``.
- Returns
- -------
- list of Image with ``list`` embed or a dict with URLs
+ Returns
+ -------
+ list of Image with ``list`` embed or a dict with URLs
- Notes
- -----
- Requires IPython to work as expected. If IPython is not available only URLs are returned.
+ Notes
+ -----
+ Requires IPython to work as expected. If IPython is not available only URLs are returned.
"""
- warnUnless(has_ipython, "requires IPython to work as expected, only URLs are returned otherwise")
+ warnUnless(
+ has_ipython,
+ "requires IPython to work as expected, only URLs are returned otherwise",
+ )
- if 'api_server' in kwargs:
- api_server = kwargs['api_server']
+ if "api_server" in kwargs:
+ api_server = kwargs["api_server"]
else:
api_server = "https://data-argo.ifremer.fr"
@@ -79,7 +84,10 @@ def open_sat_altim_report(WMO: Union[str, list] = None, embed: Union[str, None]
urls = []
urls_dict = {}
for this_wmo in WMOs:
- url = "%s/etc/argo-ast9-item13-AltimeterComparison/figures/%i.png" % (api_server, this_wmo)
+ url = "%s/etc/argo-ast9-item13-AltimeterComparison/figures/%i.png" % (
+ api_server,
+ this_wmo,
+ )
log.debug(url)
if has_ipython and embed == "list":
urls.append(Image(url, embed=True))
@@ -90,19 +98,25 @@ def open_sat_altim_report(WMO: Union[str, list] = None, embed: Union[str, None]
# Prepare rendering:
if has_ipython and embed is not None:
if has_ipywidgets and embed == "dropdown":
+
def f(Float):
return Image(url=urls_dict[int(Float)])
+
return ipywidgets.interact(f, Float=[str(wmo) for wmo in WMOs])
elif has_ipywidgets and embed == "slide":
+
def f(Float):
return Image(url=urls[Float])
+
return ipywidgets.interact(
f, Float=ipywidgets.IntSlider(min=0, max=len(urls) - 1, step=1)
)
elif embed == "list":
return display(*urls)
else:
- raise ValueError("Invalid value for 'embed' argument. Must be: 'dropdown', 'slide', 'list' or None")
+ raise ValueError(
+ "Invalid value for 'embed' argument. Must be: 'dropdown', 'slide', 'list' or None"
+ )
else:
return urls_dict
@@ -117,7 +131,7 @@ def plot_trajectory(
with_seaborn: bool = has_seaborn,
**kwargs
):
- """ Plot trajectories for an Argo index dataframe
+ """Plot trajectories for an Argo index dataframe
This function is called by the Data and Index fetchers method 'plot' with the 'trajectory' option::
@@ -161,9 +175,18 @@ def plot_trajectory(
# Set up the figure and axis:
defaults = {"figsize": (10, 6), "dpi": 90}
if with_cartopy:
- opts = {**defaults, **{'x': 'longitude', 'y': 'latitude', 'hue': 'wmo',
- 'traj': True, 'legend': add_legend, 'set_global': set_global,
- 'cmap': palette}}
+ opts = {
+ **defaults,
+ **{
+ "x": "longitude",
+ "y": "latitude",
+ "hue": "wmo",
+ "traj": True,
+ "legend": add_legend,
+ "set_global": set_global,
+ "cmap": palette,
+ },
+ }
opts = {**opts, **kwargs}
return scatter_map(df, **opts)
else:
@@ -238,7 +261,7 @@ def bar_plot(
with_seaborn: bool = has_seaborn,
**kwargs
):
- """ Create a bar plot for an Argo index dataframe
+ """Create a bar plot for an Argo index dataframe
This is the method called when using the facade fetcher methods ``plot`` with the ``dac`` or ``profiler`` arguments::
@@ -284,24 +307,24 @@ def bar_plot(
def scatter_map( # noqa: C901
- data: Union[xr.Dataset, pd.core.frame.DataFrame],
- x: Union[str] = None,
- y: Union[str] = None,
- hue: Union[str] = None,
- markersize: int = 36,
- markeredgesize: float = 0.5,
- markeredgecolor: str = 'default',
- cmap: Union[str] = None,
- traj: bool = True,
- traj_axis: Union[str] = None,
- traj_color: str = 'default',
- legend: bool = True,
- legend_title: str = 'default',
- legend_location: Union[str, int] = 0,
- cbar: bool = False,
- cbarlabels: Union[str, list] = 'auto',
- set_global: bool = False,
- **kwargs
+ data: Union[xr.Dataset, pd.core.frame.DataFrame],
+ x: Union[str] = None,
+ y: Union[str] = None,
+ hue: Union[str] = None,
+ markersize: int = 36,
+ markeredgesize: float = 0.5,
+ markeredgecolor: str = "default",
+ cmap: Union[str] = None,
+ traj: bool = True,
+ traj_axis: Union[str] = None,
+ traj_color: str = "default",
+ legend: bool = True,
+ legend_title: str = "default",
+ legend_location: Union[str, int] = 0,
+ cbar: bool = False,
+ cbarlabels: Union[str, list] = "auto",
+ set_global: bool = False,
+ **kwargs
):
"""Try-to-be generic function to create a scatter plot on a map from **argopy** :class:`xarray.Dataset` or :class:`pandas.DataFrame` data
@@ -393,40 +416,48 @@ def scatter_map( # noqa: C901
if isinstance(data, xr.Dataset) and data.argo._type == "point":
# data = data.argo.point2profile(drop=True)
- raise InvalidDatasetStructure('Function only available to a collection of profiles')
+ raise InvalidDatasetStructure(
+ "Function only available to a collection of profiles"
+ )
# Try to guess the default hue, i.e. name for WMO:
def guess_trajvar(data):
- for v in ['WMO', 'PLATFORM_NUMBER']:
+ for v in ["WMO", "PLATFORM_NUMBER"]:
if v.lower() in data:
return v.lower()
if v.upper() in data:
return v.upper()
- raise ValueError("Can't guess the variable name for default hue/trajectory grouping (WMO)")
+ raise ValueError(
+ "Can't guess the variable name for default hue/trajectory grouping (WMO)"
+ )
+
hue = guess_trajvar(data) if hue is None else hue
if isinstance(data, xr.Dataset) and data.argo.N_LEVELS > 1:
- warnings.warn("More than one N_LEVELS found in this dataset, scatter_map will use the first level only")
+ warnings.warn(
+ "More than one N_LEVELS found in this dataset, scatter_map will use the first level only"
+ )
data = data.isel(N_LEVELS=0)
# Try to guess the colormap to use as a function of the 'hue' variable:
def guess_cmap(hue):
if hue.lower() in ArgoColors().list_valid_known_colormaps:
cmap = hue.lower()
- elif 'qc' in hue.lower():
- cmap = 'qc'
- elif 'mode' in hue.lower():
- cmap = 'data_mode'
- elif 'status_code' in hue.lower():
- cmap = 'deployment_status'
+ elif "qc" in hue.lower():
+ cmap = "qc"
+ elif "mode" in hue.lower():
+ cmap = "data_mode"
+ elif "status_code" in hue.lower():
+ cmap = "deployment_status"
else:
- cmap = STYLE['palette']
+ cmap = STYLE["palette"]
return cmap
+
cmap = guess_cmap(hue) if cmap is None else cmap
# Try to guess the x and y variables:
def guess_xvar(data):
- for v in ['lon', 'long', 'longitude', 'x']:
+ for v in ["lon", "long", "longitude", "x"]:
if v.lower() in data:
return v.lower()
if v.upper() in data:
@@ -434,15 +465,18 @@ def guess_xvar(data):
if isinstance(data, xr.Dataset):
for v in data.coords:
- if '_CoordinateAxisType' in data[v].attrs and data[v].attrs['_CoordinateAxisType'] == 'Lon':
+ if (
+ "_CoordinateAxisType" in data[v].attrs
+ and data[v].attrs["_CoordinateAxisType"] == "Lon"
+ ):
return v
- if 'axis' in data[v].attrs and data[v].attrs['axis'] == 'X':
+ if "axis" in data[v].attrs and data[v].attrs["axis"] == "X":
return v
raise ValueError("Can't guess the variable name for longitudes")
def guess_yvar(data):
- for v in ['lat', 'lati', 'latitude', 'y']:
+ for v in ["lat", "lati", "latitude", "y"]:
if v.lower() in data:
return v.lower()
if v.upper() in data:
@@ -450,28 +484,36 @@ def guess_yvar(data):
if isinstance(data, xr.Dataset):
for v in data.coords:
- if '_CoordinateAxisType' in data[v].attrs and data[v].attrs['_CoordinateAxisType'] == 'Lat':
+ if (
+ "_CoordinateAxisType" in data[v].attrs
+ and data[v].attrs["_CoordinateAxisType"] == "Lat"
+ ):
return v
- if 'axis' in data[v].attrs and data[v].attrs['axis'] == 'Y':
+ if "axis" in data[v].attrs and data[v].attrs["axis"] == "Y":
return v
raise ValueError("Can't guess the variable name for latitudes")
+
x = guess_xvar(data) if x is None else x
y = guess_yvar(data) if y is None else y
# Adjust legend title:
- if legend_title == 'default':
+ if legend_title == "default":
legend_title = str(hue)
# Load Argo colors:
- nHue = len(data.groupby(hue).first()) if isinstance(data, pd.DataFrame) else len(data.groupby(hue))
+ nHue = (
+ len(data.groupby(hue).first())
+ if isinstance(data, pd.DataFrame)
+ else len(data.groupby(hue))
+ )
mycolors = ArgoColors(cmap, nHue)
COLORS = mycolors.COLORS
- if markeredgecolor == 'default':
- markeredgecolor = COLORS['DARKBLUE']
+ if markeredgecolor == "default":
+ markeredgecolor = COLORS["DARKBLUE"]
- if traj_color == 'default':
+ if traj_color == "default":
traj_color = markeredgecolor
# Try to guess the trajectory grouping variable, i.e. name for WMO
@@ -482,7 +524,13 @@ def guess_yvar(data):
subplot_kw = {"projection": ccrs.PlateCarree()}
fig, ax = plt.subplots(**{**defaults, **kwargs}, subplot_kw=subplot_kw)
- ax.add_feature(land_feature, color=COLORS['BLUE'], edgecolor=COLORS['CYAN'], linewidth=.1, alpha=0.3)
+ ax.add_feature(
+ land_feature,
+ color=COLORS["BLUE"],
+ edgecolor=COLORS["CYAN"],
+ linewidth=0.1,
+ alpha=0.3,
+ )
# vmin = data[hue].min() if vmin == 'auto' else vmin
# vmax = data[hue].max() if vmax == 'auto' else vmax
@@ -490,48 +538,58 @@ def guess_yvar(data):
patches = []
for k, [name, group] in enumerate(data.groupby(hue)):
if mycolors.registered and name not in mycolors.lookup:
- log.info("Found '%s' values not available in the '%s' colormap" % (name, mycolors.definition['name']))
+ log.info(
+ "Found '%s' values not available in the '%s' colormap"
+ % (name, mycolors.definition["name"])
+ )
else:
scatter_opts = {
- 'color': mycolors.lookup[name] if mycolors.registered else mycolors.cmap(k),
- 'label': "%s: %s" % (name, mycolors.ticklabels[name]) if mycolors.registered else name,
- 'zorder': 10,
- 'sizes': [markersize],
- 'edgecolor': markeredgecolor,
- 'linewidths': markeredgesize,
+ "color": mycolors.lookup[name]
+ if mycolors.registered
+ else mycolors.cmap(k),
+ "label": "%s: %s" % (name, mycolors.ticklabels[name])
+ if mycolors.registered
+ else name,
+ "zorder": 10,
+ "sizes": [markersize],
+ "edgecolor": markeredgecolor,
+ "linewidths": markeredgesize,
}
if isinstance(data, pd.DataFrame) and not legend:
- scatter_opts['legend'] = False # otherwise Pandas will add a legend even if we set legend=False
- sc = group.plot.scatter(
- x=x, y=y,
- ax=ax,
- **scatter_opts
- )
+ scatter_opts[
+ "legend"
+ ] = False # otherwise Pandas will add a legend even if we set legend=False
+ sc = group.plot.scatter(x=x, y=y, ax=ax, **scatter_opts)
patches.append(sc)
if cbar:
- if cbarlabels == 'auto':
+ if cbarlabels == "auto":
cbarlabels = None
- mycolors.cbar(ticklabels=cbarlabels,
- ax=ax,
- cax=sc,
- fraction=0.03, label=legend_title)
+ mycolors.cbar(
+ ticklabels=cbarlabels, ax=ax, cax=sc, fraction=0.03, label=legend_title
+ )
if traj:
for k, [name, group] in enumerate(data.groupby(traj_axis)):
- ax.plot(group[x], group[y],
- color=traj_color,
- linewidth=0.5,
- label="_nolegend_",
- zorder=2,
- )
+ ax.plot(
+ group[x],
+ group[y],
+ color=traj_color,
+ linewidth=0.5,
+ label="_nolegend_",
+ zorder=2,
+ )
if set_global:
ax.set_global()
- latlongrid(ax, dx="auto", dy="auto",
- label_style_arg={'color': COLORS['BLUE'], 'fontsize': 10},
- **{"color": COLORS['BLUE'], "alpha": 0.7})
+ latlongrid(
+ ax,
+ dx="auto",
+ dy="auto",
+ label_style_arg={"color": COLORS["BLUE"], "fontsize": 10},
+ **{"color": COLORS["BLUE"], "alpha": 0.7}
+ )
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
@@ -546,54 +604,55 @@ def guess_yvar(data):
)
for spine in ax.spines.values():
- spine.set_edgecolor(COLORS['DARKBLUE'])
+ spine.set_edgecolor(COLORS["DARKBLUE"])
- ax.set_title('')
+ ax.set_title("")
return fig, ax
-def scatter_plot(ds: xr.Dataset,
- this_param,
- this_x='TIME',
- this_y='PRES',
- figsize=(18, 6),
- cmap=None,
- vmin=None,
- vmax=None,
- s=4,
- bgcolor='lightgrey',
- ):
+def scatter_plot(
+ ds: xr.Dataset,
+ this_param,
+ this_x="TIME",
+ this_y="PRES",
+ figsize=(18, 6),
+ cmap=None,
+ vmin=None,
+ vmax=None,
+ s=4,
+ bgcolor="lightgrey",
+):
"""A quick-and-dirty parameter scatter plot for one variable"""
warnUnless(has_mpl, "requires matplotlib installed")
if cmap is None:
- cmap = mpl.colormaps['gist_ncar']
+ cmap = mpl.colormaps["gist_ncar"]
def get_vlabel(this_ds, this_v):
attrs = this_ds[this_v].attrs
- if 'standard_name' in attrs:
- name = attrs['standard_name']
- elif 'long_name' in attrs:
- name = attrs['long_name']
+ if "standard_name" in attrs:
+ name = attrs["standard_name"]
+ elif "long_name" in attrs:
+ name = attrs["long_name"]
else:
name = this_v
- units = attrs['units'] if 'units' in attrs else None
+ units = attrs["units"] if "units" in attrs else None
return "%s\n[%s]" % (name, units) if units else name
# Read variables for the plot:
x, y = ds[this_x], ds[this_y]
if "INTERPOLATED" in this_y:
- x_bounds, y_bounds = np.meshgrid(x, y, indexing='ij')
+ x_bounds, y_bounds = np.meshgrid(x, y, indexing="ij")
c = ds[this_param]
#
fig, ax = plt.subplots(dpi=90, figsize=figsize)
- if vmin == 'attrs':
- vmin = c.attrs['valid_min'] if 'valid_min' in c.attrs else None
- if vmax == 'attrs':
- vmax = c.attrs['valid_max'] if 'valid_max' in c.attrs else None
+ if vmin == "attrs":
+ vmin = c.attrs["valid_min"] if "valid_min" in c.attrs else None
+ if vmax == "attrs":
+ vmax = c.attrs["valid_max"] if "valid_max" in c.attrs else None
if vmin is None:
vmin = np.percentile(c, 10)
if vmax is None:
@@ -605,21 +664,21 @@ def get_vlabel(this_ds, this_v):
m = ax.scatter(x, y, c=c, cmap=cmap, s=s, vmin=vmin, vmax=vmax)
ax.set_facecolor(bgcolor)
- cbar = fig.colorbar(m, shrink=0.9, extend='both', ax=ax)
+ cbar = fig.colorbar(m, shrink=0.9, extend="both", ax=ax)
cbar.ax.set_ylabel(get_vlabel(ds, this_param), rotation=90)
ylim = ax.get_ylim()
- if 'PRES' in this_y:
+ if "PRES" in this_y:
ax.invert_yaxis()
y_bottom, y_top = np.max(ylim), np.min(ylim)
else:
y_bottom, y_top = ylim
- if this_x == 'CYCLE_NUMBER':
+ if this_x == "CYCLE_NUMBER":
ax.set_xlim([np.min(ds[this_x]) - 1, np.max(ds[this_x]) + 1])
- elif this_x == 'TIME':
+ elif this_x == "TIME":
ax.set_xlim([np.min(ds[this_x]), np.max(ds[this_x])])
- if 'PRES' in this_y:
+ if "PRES" in this_y:
ax.set_ylim([y_bottom, 0])
#
diff --git a/argopy/plot/utils.py b/argopy/plot/utils.py
index ef1d2665..24561a42 100644
--- a/argopy/plot/utils.py
+++ b/argopy/plot/utils.py
@@ -22,11 +22,11 @@ def _importorskip(modname):
if has_mpl:
- import matplotlib as mpl
- import matplotlib.pyplot as plt
+ import matplotlib as mpl # noqa: F401
+ import matplotlib.pyplot as plt # noqa: F401
import matplotlib.ticker as mticker
- import matplotlib.cm as cm
- import matplotlib.colors as mcolors
+ import matplotlib.cm as cm # noqa: F401
+ import matplotlib.colors as mcolors # noqa: F401
if has_cartopy:
diff --git a/argopy/related/argo_documentation.py b/argopy/related/argo_documentation.py
index 95e8fc74..bc8a5a4f 100644
--- a/argopy/related/argo_documentation.py
+++ b/argopy/related/argo_documentation.py
@@ -49,7 +49,7 @@ def parse(self, file):
try:
with self.fs.open(file, 'r', encoding="utf-8") as f:
TXTlines = f.readlines()
- except:
+ except: # noqa: E722
with self.fs.open(file, 'r', encoding="latin-1") as f:
TXTlines = f.readlines()
diff --git a/argopy/stores/argo_index_proto.py b/argopy/stores/argo_index_proto.py
index d62c9dfa..6d7fa312 100644
--- a/argopy/stores/argo_index_proto.py
+++ b/argopy/stores/argo_index_proto.py
@@ -26,7 +26,7 @@
except ModuleNotFoundError:
pass
-from .argo_index_proto_s3 import search_s3
+# from .argo_index_proto_s3 import search_s3
log = logging.getLogger("argopy.stores.index")
@@ -457,7 +457,7 @@ def _write(self, fs, path, obj, fmt="pq"):
if isinstance(fs, memorystore):
fs.fs.touch(this_path) # Fix for https://github.com/euroargodev/argopy/issues/345
# fs.fs.touch(this_path) # Fix for https://github.com/euroargodev/argopy/issues/345
- # This is an f* mistery to me, why do we need 2 calls to trigger file creation FOR REAL ????
+ # This is an f* mystery to me, why do we need 2 calls to trigger file creation FOR REAL ????
# log.debug("memorystore touched this path before open context: '%s'" % this_path)
with fs.open(this_path, "wb") as handle:
write_this[fmt](obj, handle)
diff --git a/argopy/stores/argo_index_proto_s3.py b/argopy/stores/argo_index_proto_s3.py
index 7ce7e778..a9d04015 100644
--- a/argopy/stores/argo_index_proto_s3.py
+++ b/argopy/stores/argo_index_proto_s3.py
@@ -17,6 +17,7 @@
HAS_PYARROW = True
except ModuleNotFoundError:
HAS_PYARROW = False
+
class pa:
@property
def Table(self):
@@ -83,7 +84,7 @@ def __init__(self):
try:
access_key = self.fs._request_signer._credentials.get_frozen_credentials().access_key
log.debug("Found AWS Credentials for access_key='%s'" % access_key)
- except:
+ except: # noqa: E722
pass
else:
self.fs = boto3.client('s3', config=Config(signature_version=UNSIGNED))
@@ -160,7 +161,7 @@ def query(self, sql_expression: str) -> str:
"CompressionType": self.CompressionType},
OutputSerialization={"CSV": {}},
)
- except:
+ except: # noqa: E722
# log.debug(boto3.set_stream_logger('botocore', level='DEBUG'))
raise
diff --git a/argopy/stores/filesystems.py b/argopy/stores/filesystems.py
index 8855cec8..482fbcbd 100644
--- a/argopy/stores/filesystems.py
+++ b/argopy/stores/filesystems.py
@@ -259,7 +259,7 @@ def cachepath(self, uri: str, errors: str = "raise"):
)
def _clear_cache_item(self, uri):
- """Remove medadata and file for fsspec cache uri"""
+ """Remove metadata and file for fsspec cache uri"""
fn = os.path.join(self.fs.storage[-1], "cache")
self.fs.load_cache() # Read set of stored blocks from file and populate self.cached_files
cache = self.cached_files[-1]
diff --git a/argopy/utilities.py b/argopy/utilities.py
deleted file mode 100644
index a2f232ff..00000000
--- a/argopy/utilities.py
+++ /dev/null
@@ -1,304 +0,0 @@
-import warnings
-import importlib
-import inspect
-from functools import wraps
-
-warnings.filterwarnings("default", category=DeprecationWarning, module=__name__)
-
-
-def refactored(func1):
-
- rel = importlib.import_module('argopy.related')
- utils = importlib.import_module('argopy.utils')
- in_related = hasattr(rel, func1.__name__)
- func2 = getattr(rel, func1.__name__) if in_related else getattr(utils, func1.__name__)
-
- func1_type = 'function'
- if inspect.isclass(func1):
- func1_type = 'class'
-
- func2_loc = 'utils'
- if in_related:
- func2_loc = 'related'
-
- msg = "The 'argopy.utilities.{name}' {ftype} has moved to 'argopy.{where}.{name}'. \
-You're seeing this message because you called '{name}' imported from 'argopy.utilities'. \
-Please update your script to import '{name}' from 'argopy.{where}'. \
-After 0.1.15, importing 'utilities' will raise an error."
-
- @wraps(func1)
- def decorator(*args, **kwargs):
- # warnings.simplefilter('always', DeprecationWarning)
- warnings.warn(
- msg.format(name=func1.__name__, ftype=func1_type, where=func2_loc),
- category=DeprecationWarning,
- stacklevel=2
- )
- # warnings.simplefilter('default', DeprecationWarning)
- return func2(*args, **kwargs)
-
- return decorator
-
-# Argo related dataset and Meta-data fetchers
-
-@refactored
-class TopoFetcher:
- pass
-
-@refactored
-class ArgoDocs:
- pass
-
-@refactored
-class ArgoNVSReferenceTables:
- pass
-
-@refactored
-class OceanOPSDeployments:
- pass
-
-@refactored
-def get_coriolis_profile_id(*args, **kwargs):
- pass
-
-@refactored
-def get_ea_profile_page(*args, **kwargs):
- pass
-
-@refactored
-def load_dict(*args, **kwargs):
- pass
-
-@refactored
-def mapp_dict(*args, **kwargs):
- pass
-
-# Checkers
-@refactored
-def is_box(*args, **kwargs):
- pass
-
-@refactored
-def is_indexbox(*args, **kwargs):
- pass
-
-@refactored
-def is_list_of_strings(*args, **kwargs):
- pass
-
-@refactored
-def is_list_of_dicts(*args, **kwargs):
- pass
-
-@refactored
-def is_list_of_datasets(*args, **kwargs):
- pass
-
-@refactored
-def is_list_equal(*args, **kwargs):
- pass
-
-@refactored
-def check_wmo(*args, **kwargs):
- pass
-
-@refactored
-def is_wmo(*args, **kwargs):
- pass
-
-@refactored
-def check_cyc(*args, **kwargs):
- pass
-
-@refactored
-def is_cyc(*args, **kwargs):
- pass
-
-@refactored
-def check_index_cols(*args, **kwargs):
- pass
-
-@refactored
-def check_gdac_path(*args, **kwargs):
- pass
-
-@refactored
-def isconnected(*args, **kwargs):
- pass
-
-@refactored
-def isalive(*args, **kwargs):
- pass
-
-@refactored
-def isAPIconnected(*args, **kwargs):
- pass
-
-@refactored
-def erddap_ds_exists(*args, **kwargs):
- pass
-
-@refactored
-def urlhaskeyword(*args, **kwargs):
- pass
-
-
-# Data type casting:
-
-@refactored
-def to_list(*args, **kwargs):
- pass
-
-@refactored
-def cast_Argo_variable_type(*args, **kwargs):
- pass
-
-from .utils.casting import DATA_TYPES
-
-# Decorators
-
-@refactored
-def deprecated(*args, **kwargs):
- pass
-
-@refactored
-def doc_inherit(*args, **kwargs):
- pass
-
-# Lists:
-
-@refactored
-def list_available_data_src(*args, **kwargs):
- pass
-
-@refactored
-def list_available_index_src(*args, **kwargs):
- pass
-
-@refactored
-def list_standard_variables(*args, **kwargs):
- pass
-
-@refactored
-def list_multiprofile_file_variables(*args, **kwargs):
- pass
-
-# Cache management:
-@refactored
-def clear_cache(*args, **kwargs):
- pass
-
-@refactored
-def lscache(*args, **kwargs):
- pass
-
-# Computation and performances:
-@refactored
-class Chunker:
- pass
-
-# Accessories classes (specific objects):
-@refactored
-class float_wmo:
- pass
-
-@refactored
-class Registry:
- pass
-
-# Locals (environments, versions, systems):
-@refactored
-def get_sys_info(*args, **kwargs):
- pass
-
-@refactored
-def netcdf_and_hdf5_versions(*args, **kwargs):
- pass
-
-@refactored
-def show_versions(*args, **kwargs):
- pass
-
-@refactored
-def show_options(*args, **kwargs):
- pass
-
-@refactored
-def modified_environ(*args, **kwargs):
- pass
-
-
-# Monitors
-@refactored
-def badge(*args, **kwargs):
- pass
-
-@refactored
-class fetch_status:
- pass
-
-@refactored
-class monitor_status:
- pass
-
-# Geo (space/time data utilities)
-@refactored
-def toYearFraction(*args, **kwargs):
- pass
-
-@refactored
-def YearFraction_to_datetime(*args, **kwargs):
- pass
-
-@refactored
-def wrap_longitude(*args, **kwargs):
- pass
-
-@refactored
-def wmo2box(*args, **kwargs):
- pass
-
-# Computation with datasets:
-@refactored
-def linear_interpolation_remap(*args, **kwargs):
- pass
-
-@refactored
-def groupby_remap(*args, **kwargs):
- pass
-
-# Manipulate datasets:
-@refactored
-def drop_variables_not_in_all_datasets(*args, **kwargs):
- pass
-
-@refactored
-def fill_variables_not_in_all_datasets(*args, **kwargs):
- pass
-
-# Formatters:
-@refactored
-def format_oneline(*args, **kwargs):
- pass
-
-@refactored
-def argo_split_path(*args, **kwargs):
- pass
-
-
-# Loggers
-@refactored
-def warnUnless(*args, **kwargs):
- pass
-
-@refactored
-def log_argopy_callerstack(*args, **kwargs):
- pass
-
-if __name__ == "argopy.utilities":
- warnings.warn(
- "The 'argopy.utilities' has moved to 'argopy.utils'. After 0.1.15, importing 'utilities' "
- "will raise an error. Please update your script.",
- category=DeprecationWarning,
- stacklevel=2,
- )
diff --git a/argopy/utils/__init__.py b/argopy/utils/__init__.py
index 5c597e8f..5afa936d 100644
--- a/argopy/utils/__init__.py
+++ b/argopy/utils/__init__.py
@@ -1,4 +1,4 @@
-from .checkers import (
+from .checkers import ( # noqa: F401
is_box,
is_indexbox,
is_list_of_strings,
@@ -30,15 +30,21 @@
from .monitored_threadpool import MyThreadPoolExecutor as MonitoredThreadPoolExecutor
from .chunking import Chunker
from .accessories import Registry, float_wmo
-from .locals import (
+from .locals import ( # noqa: F401
show_versions,
show_options,
modified_environ,
- get_sys_info, # noqa: F401
+ get_sys_info, # noqa: F401
netcdf_and_hdf5_versions, # noqa: F401
)
from .monitors import monitor_status, badge, fetch_status # noqa: F401
-from .geo import wmo2box, wrap_longitude, conv_lon, toYearFraction, YearFraction_to_datetime
+from .geo import (
+ wmo2box,
+ wrap_longitude,
+ conv_lon,
+ toYearFraction,
+ YearFraction_to_datetime,
+)
from .compute import linear_interpolation_remap, groupby_remap
from .transform import (
fill_variables_not_in_all_datasets,
diff --git a/argopy/utils/casting.py b/argopy/utils/casting.py
index 00cf60e0..1119debb 100644
--- a/argopy/utils/casting.py
+++ b/argopy/utils/casting.py
@@ -20,201 +20,6 @@
DATA_TYPES = json.load(f)
-@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
-
- #todo: This is hard coded, but should be retrieved from an API somewhere.
- Should be able to handle all possible variables encountered in the Argo dataset.
-
- Parameter
- ---------
- :class:`xarray.DataSet`
-
- Returns
- -------
- :class:`xarray.DataSet`
- """
-
- list_str = [
- "PLATFORM_NUMBER",
- "DATA_MODE",
- "DIRECTION",
- "DATA_CENTRE",
- "DATA_TYPE",
- "FORMAT_VERSION",
- "HANDBOOK_VERSION",
- "PROJECT_NAME",
- "PI_NAME",
- "STATION_PARAMETERS",
- "DATA_CENTER",
- "DC_REFERENCE",
- "DATA_STATE_INDICATOR",
- "PLATFORM_TYPE",
- "FIRMWARE_VERSION",
- "POSITIONING_SYSTEM",
- "PROFILE_PRES_QC",
- "PROFILE_PSAL_QC",
- "PROFILE_TEMP_QC",
- "PARAMETER",
- "SCIENTIFIC_CALIB_EQUATION",
- "SCIENTIFIC_CALIB_COEFFICIENT",
- "SCIENTIFIC_CALIB_COMMENT",
- "HISTORY_INSTITUTION",
- "HISTORY_STEP",
- "HISTORY_SOFTWARE",
- "HISTORY_SOFTWARE_RELEASE",
- "HISTORY_REFERENCE",
- "HISTORY_QCTEST",
- "HISTORY_ACTION",
- "HISTORY_PARAMETER",
- "VERTICAL_SAMPLING_SCHEME",
- "FLOAT_SERIAL_NO",
- "SOURCE",
- "EXPOCODE",
- "QCLEVEL",
- ]
- list_int = [
- "PLATFORM_NUMBER",
- "WMO_INST_TYPE",
- "WMO_INST_TYPE",
- "CYCLE_NUMBER",
- "CONFIG_MISSION_NUMBER",
- ]
- list_datetime = [
- "REFERENCE_DATE_TIME",
- "DATE_CREATION",
- "DATE_UPDATE",
- "JULD",
- "JULD_LOCATION",
- "SCIENTIFIC_CALIB_DATE",
- "HISTORY_DATE",
- "TIME",
- ]
-
- def fix_weird_bytes(x):
- x = x.replace(b"\xb1", b"+/-")
- return x
-
- fix_weird_bytes = np.vectorize(fix_weird_bytes)
-
- def cast_this(da, type):
- """Low-level casting of DataArray values"""
- try:
- da.values = da.values.astype(type)
- da.attrs["casted"] = 1
- except Exception:
- msg = (
- "Oops! %s occurred. Fail to cast <%s> into %s for: %s. Encountered unique values: %s"
- % (sys.exc_info()[0], str(da.dtype), type, da.name, str(np.unique(da)))
- )
- log.debug(msg)
- return da
-
- def cast_this_da(da):
- """Cast any DataArray"""
- v = da.name
- da.attrs["casted"] = 0
- if v in list_str and da.dtype == "O": # Object
- if v in ["SCIENTIFIC_CALIB_COEFFICIENT"]:
- da.values = fix_weird_bytes(da.values)
- da = cast_this(da, str)
-
- if v in list_int: # and da.dtype == 'O': # Object
- da = cast_this(da, np.int32)
-
- if v in list_datetime and da.dtype == "O": # Object
- if (
- "conventions" in da.attrs
- and da.attrs["conventions"] == "YYYYMMDDHHMISS"
- ):
- if da.size != 0:
- if len(da.dims) <= 1:
- val = da.astype(str).values.astype("U14")
- # This should not happen, but still ! That's real world data
- val[val == " "] = "nan"
- da.values = pd.to_datetime(val, format="%Y%m%d%H%M%S")
- else:
- s = da.stack(dummy_index=da.dims)
- val = s.astype(str).values.astype("U14")
- # This should not happen, but still ! That's real world data
- val[val == ""] = "nan"
- val[val == " "] = "nan"
- #
- s.values = pd.to_datetime(val, format="%Y%m%d%H%M%S")
- da.values = s.unstack("dummy_index")
- da = cast_this(da, "datetime64[s]")
- else:
- da = cast_this(da, "datetime64[s]")
-
- elif v == "SCIENTIFIC_CALIB_DATE":
- da = cast_this(da, str)
- s = da.stack(dummy_index=da.dims)
- s.values = pd.to_datetime(s.values, format="%Y%m%d%H%M%S")
- da.values = (s.unstack("dummy_index")).values
- da = cast_this(da, "datetime64[s]")
-
- if "QC" in v and "PROFILE" not in v and "QCTEST" not in v:
- if da.dtype == "O": # convert object to string
- da = cast_this(da, str)
-
- # Address weird string values:
- # (replace missing or nan values by a '0' that will be cast as an integer later
-
- if da.dtype == "<U3": # string, len 3 because of a 'nan' somewhere
- ii = (
- da == " "
- ) # This should not happen, but still ! That's real world data
- da = xr.where(ii, "0", da)
-
- ii = (
- da == "nan"
- ) # This should not happen, but still ! That's real world data
- da = xr.where(ii, "0", da)
-
- # Get back to regular U1 string
- da = cast_this(da, np.dtype("U1"))
-
- if da.dtype == "<U1": # string
- ii = (
- da == ""
- ) # This should not happen, but still ! That's real world data
- da = xr.where(ii, "0", da)
-
- ii = (
- da == " "
- ) # This should not happen, but still ! That's real world data
- da = xr.where(ii, "0", da)
-
- ii = (
- da == "n"
- ) # This should not happen, but still ! That's real world data
- da = xr.where(ii, "0", da)
-
- # finally convert QC strings to integers:
- da = cast_this(da, np.int32)
-
- if da.dtype == "O":
- # By default, try to cast as float:
- da = cast_this(da, np.float32)
-
- if da.dtype != "O":
- da.attrs["casted"] = 1
-
- return da
-
- for v in ds.variables:
- try:
- ds[v] = cast_this_da(ds[v])
- except Exception:
- print("Oops!", sys.exc_info()[0], "occurred.")
- print("Fail to cast: %s " % v)
- print("Encountered unique values:", np.unique(ds[v]))
- raise
-
- return ds
-
-
def cast_Argo_variable_type(ds, overwrite=True):
"""Ensure that all dataset variables are of the appropriate types according to Argo references
diff --git a/argopy/utils/checkers.py b/argopy/utils/checkers.py
index 3775b09e..9bc5b778 100644
--- a/argopy/utils/checkers.py
+++ b/argopy/utils/checkers.py
@@ -698,4 +698,4 @@ def has_aws_credentials():
client = boto3.client('s3')
return client._request_signer._credentials is not None
else:
- raise Exception("boto3 is not available !")
\ No newline at end of file
+ raise Exception("boto3 is not available !")
diff --git a/argopy/utils/format.py b/argopy/utils/format.py
index ae72701d..c2845a7a 100644
--- a/argopy/utils/format.py
+++ b/argopy/utils/format.py
@@ -209,24 +209,33 @@ def erddapuri2fetchobj(uri: str) -> dict:
"""Given an Ifremer ERDDAP URI, return a dictionary with BOX or WMO or (WMO, CYC) fetcher arguments"""
params = parse_qs(uri)
result = {}
- if 'longitude>' in params.keys():
+ if "longitude>" in params.keys():
# Recreate the box definition:
- box = [float(params['longitude>'][0]), float(params['longitude<'][0]),
- float(params['latitude>'][0]), float(params['latitude<'][0]),
- float(params['pres>'][0]), float(params['pres<'][0])]
+ box = [
+ float(params["longitude>"][0]),
+ float(params["longitude<"][0]),
+ float(params["latitude>"][0]),
+ float(params["latitude<"][0]),
+ float(params["pres>"][0]),
+ float(params["pres<"][0]),
+ ]
if "time>" in params.keys():
- box.append(pd.to_datetime(float(params['time>'][0]), unit='s').strftime("%Y-%m-%d"))
- box.append(pd.to_datetime(float(params['time<'][0]), unit='s').strftime("%Y-%m-%d"))
- result['box'] = box
- elif 'platform_number' in params:
- wmo = params['platform_number'][0].replace("~","").replace("\"","").split("|")
+ box.append(
+ pd.to_datetime(float(params["time>"][0]), unit="s").strftime("%Y-%m-%d")
+ )
+ box.append(
+ pd.to_datetime(float(params["time<"][0]), unit="s").strftime("%Y-%m-%d")
+ )
+ result["box"] = box
+ elif "platform_number" in params:
+ wmo = params["platform_number"][0].replace("~", "").replace('"', "").split("|")
wmo = check_wmo(wmo)
- result['wmo'] = wmo
- if 'cycle_number' in params:
- cyc = params['cycle_number'][0].replace("~","").replace("\"","").split("|")
+ result["wmo"] = wmo
+ if "cycle_number" in params:
+ cyc = params["cycle_number"][0].replace("~", "").replace('"', "").split("|")
cyc = check_cyc(cyc)
- result['cyc'] = cyc
- if len(result.keys())==0:
+ result["cyc"] = cyc
+ if len(result.keys()) == 0:
raise ValueError("This is not a typical Argo Ifremer Erddap uri")
else:
return result
@@ -240,25 +249,27 @@ def _is_url(self, url):
return parsed.scheme and parsed.netloc
def __init__(self, obj):
- if hasattr(obj, 'BOX'):
+ if hasattr(obj, "BOX"):
self.BOX = obj.BOX
- elif hasattr(obj, 'WMO'):
+ elif hasattr(obj, "WMO"):
self.WMO = obj.WMO
- if hasattr(obj, 'CYC'):
+ if hasattr(obj, "CYC"):
self.CYC = obj.CYC
elif self._is_url(obj) and "/tabledap/" in obj:
obj = erddapuri2fetchobj(obj)
- if 'box' in obj.keys():
- self.BOX = obj['box']
- elif 'wmo' in obj.keys():
- self.WMO = obj['wmo']
- if 'cyc' in obj.keys():
- self.CYC = obj['cyc']
+ if "box" in obj.keys():
+ self.BOX = obj["box"]
+ elif "wmo" in obj.keys():
+ self.WMO = obj["wmo"]
+ if "cyc" in obj.keys():
+ self.CYC = obj["cyc"]
else:
- raise ValueError("This class is only available with Erddap uri string requests or an ArgoDataFetcherProto instance")
+ raise ValueError(
+ "This class is only available with Erddap uri string requests or an ArgoDataFetcherProto instance"
+ )
def _format(self, x, typ: str) -> str:
- """ string formatting helper """
+ """string formatting helper"""
if typ == "lon":
if x < 0:
x = 360.0 + x
@@ -276,7 +287,7 @@ def __repr__(self):
@property
def cname(self) -> str:
- """ Fetcher one line string definition helper """
+ """Fetcher one line string definition helper"""
cname = "?"
if hasattr(self, "BOX"):
@@ -325,4 +336,4 @@ def cname(self) -> str:
if hasattr(self, "dataset_id"):
cname = self.dataset_id + ";" + cname
- return cname
\ No newline at end of file
+ return cname
diff --git a/argopy/utils/locals.py b/argopy/utils/locals.py
index dccf3b83..737373f3 100644
--- a/argopy/utils/locals.py
+++ b/argopy/utils/locals.py
@@ -8,9 +8,21 @@
from importlib.metadata import version
import contextlib
import copy
+import shutil
+import json
from ..options import OPTIONS
+PIP_INSTALLED = {}
+try:
+ reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'list', '--format', 'json'])
+ reqs = json.loads(reqs.decode())
+ [PIP_INSTALLED.update({mod['name']: mod['version']}) for mod in reqs]
+except:
+ pass
+
+
+
def get_sys_info():
"""Returns system information as a dict"""
@@ -79,6 +91,25 @@ def netcdf_and_hdf5_versions():
return [("libhdf5", libhdf5_version), ("libnetcdf", libnetcdf_version)]
+def cli_version(cli_name):
+ try:
+ a = subprocess.run([cli_name, '--version'], capture_output=True)
+ return a.stdout.decode().strip("\n").replace(cli_name, '').strip()
+ except:
+ if shutil.which(cli_name):
+ return "- # installed"
+ else:
+ return "-"
+
+
+def pip_version(pip_name):
+ version = '-'
+ for name in [pip_name, pip_name.replace("_", "-"), pip_name.replace("-", "_")]:
+ if name in PIP_INSTALLED:
+ version = PIP_INSTALLED[name]
+ return version
+
+
def get_version(module_name):
ver = '-'
try:
@@ -87,10 +118,19 @@ def get_version(module_name):
try:
ver = version(module_name)
except importlib.metadata.PackageNotFoundError:
- pass
+ try:
+ ver = pip_version(module_name)
+ except:
+ try:
+ ver = cli_version(module_name)
+ except:
+ pass
+ if sum([int(v == '0') for v in ver.split(".")]) == len(ver.split(".")):
+ ver = '-'
return ver
+
def show_versions(file=sys.stdout, conda=False): # noqa: C901
"""Print the versions of argopy and its dependencies
@@ -112,7 +152,6 @@ def show_versions(file=sys.stdout, conda=False): # noqa: C901
"core": sorted(
[
("argopy", get_version),
-
("xarray", get_version),
("scipy", get_version),
("netCDF4", get_version),
@@ -164,9 +203,8 @@ def show_versions(file=sys.stdout, conda=False): # noqa: C901
("bottleneck", get_version),
("cftime", get_version),
("cfgrib", get_version),
- ("conda", get_version),
+ ("codespell", cli_version),
("flake8", get_version),
- ("nc_time_axis", get_version),
("numpy", get_version), # will come with xarray and pandas
("pandas", get_version), # will come with xarray
("pip", get_version),
@@ -178,9 +216,11 @@ def show_versions(file=sys.stdout, conda=False): # noqa: C901
("sphinx", get_version),
]
),
- 'pip': sorted([
- ("pytest-reportlog", get_version),
- ])
+ "pip": sorted(
+ [
+ ("pytest-reportlog", get_version),
+ ]
+ ),
}
DEPS_blob = {}
@@ -189,18 +229,10 @@ def show_versions(file=sys.stdout, conda=False): # noqa: C901
deps_blob = list()
for modname, ver_f in deps:
try:
- if modname in sys.modules:
- mod = sys.modules[modname]
- else:
- mod = importlib.import_module(modname)
+ ver = ver_f(modname)
+ deps_blob.append((modname, ver))
except Exception:
- deps_blob.append((modname, "-"))
- else:
- try:
- ver = ver_f(modname)
- deps_blob.append((modname, ver))
- except Exception:
- deps_blob.append((modname, "installed"))
+ deps_blob.append((modname, "installed"))
DEPS_blob[level] = deps_blob
print("\nSYSTEM", file=file)
diff --git a/argopy/xarray.py b/argopy/xarray.py
index ccd2e594..096e05b8 100644
--- a/argopy/xarray.py
+++ b/argopy/xarray.py
@@ -34,33 +34,33 @@
class ArgoAccessor:
"""Class registered under scope ``argo`` to access a :class:`xarray.Dataset` object.
- Examples
- --------
- - Ensure all variables are of the Argo required dtype with:
- >>> ds.argo.cast_types()
- - Convert a collection of points into a collection of profiles:
- >>> ds.argo.point2profile()
- - Convert a collection of profiles to a collection of points:
- >>> ds.argo.profile2point()
- - Filter measurements according to data mode:
- >>> ds.argo.filter_data_mode()
- - Filter measurements according to QC flag values:
- >>> ds.argo.filter_qc(QC_list=[1, 2], QC_fields='all')
- - Filter variables according OWC salinity calibration requirements:
- >>> ds.argo.filter_scalib_pres(force='default')
- - Interpolate measurements on pressure levels:
- >>> ds.argo.inter_std_levels(std_lev=[10., 500., 1000.])
- - Group and reduce measurements by pressure bins:
- >>> ds.argo.groupby_pressure_bins(bins=[0, 200., 500., 1000.])
- - Compute and add additional variables to the dataset:
- >>> ds.argo.teos10(vlist='PV')
- - Preprocess data for OWC salinity calibration:
- >>> ds.argo.create_float_source("output_folder")
-
- """
+ Examples
+ --------
+ - Ensure all variables are of the Argo required dtype with:
+ >>> ds.argo.cast_types()
+ - Convert a collection of points into a collection of profiles:
+ >>> ds.argo.point2profile()
+ - Convert a collection of profiles to a collection of points:
+ >>> ds.argo.profile2point()
+ - Filter measurements according to data mode:
+ >>> ds.argo.filter_data_mode()
+ - Filter measurements according to QC flag values:
+ >>> ds.argo.filter_qc(QC_list=[1, 2], QC_fields='all')
+ - Filter variables according OWC salinity calibration requirements:
+ >>> ds.argo.filter_scalib_pres(force='default')
+ - Interpolate measurements on pressure levels:
+ >>> ds.argo.inter_std_levels(std_lev=[10., 500., 1000.])
+ - Group and reduce measurements by pressure bins:
+ >>> ds.argo.groupby_pressure_bins(bins=[0, 200., 500., 1000.])
+ - Compute and add additional variables to the dataset:
+ >>> ds.argo.teos10(vlist='PV')
+ - Preprocess data for OWC salinity calibration:
+ >>> ds.argo.create_float_source("output_folder")
+
+ """
def __init__(self, xarray_obj):
- """ Init """
+ """Init"""
self._obj = xarray_obj
self._added = list() # Will record all new variables added by argo
# self._register = collections.OrderedDict() # Will register mutable instances of sub-modules like 'plot'
@@ -85,7 +85,9 @@ def __init__(self, xarray_obj):
elif "PRES" in self._vars:
self._mode = "standard"
else:
- raise InvalidDatasetStructure("Argo dataset structure not recognised (no PRES nor PRES_ADJUSTED")
+ raise InvalidDatasetStructure(
+ "Argo dataset structure not recognised (no PRES nor PRES_ADJUSTED"
+ )
def __repr__(self):
# import xarray.core.formatting as xrf
@@ -176,7 +178,7 @@ def _add_history(self, txt):
self._obj.attrs["history"] = txt
def _where(self, cond, other=xr.core.dtypes.NA, drop: bool = False):
- """ where that preserve dtypes of Argo fields
+ """where that preserve dtypes of Argo fields
Parameters
----------
@@ -198,7 +200,7 @@ def _where(self, cond, other=xr.core.dtypes.NA, drop: bool = False):
return this
def cast_types(self, **kwargs): # noqa: C901
- """ Make sure variables are of the appropriate types according to Argo """
+ """Make sure variables are of the appropriate types according to Argo"""
ds = self._obj
return cast_Argo_variable_type(ds, **kwargs)
@@ -206,14 +208,14 @@ def cast_types(self, **kwargs): # noqa: C901
def _dummy_argo_uid(self):
if self._type == "point":
return xr.DataArray(
- self.uid(
- self._obj["PLATFORM_NUMBER"].values,
- self._obj["CYCLE_NUMBER"].values,
- self._obj["DIRECTION"].values,
- ),
- dims="N_POINTS",
- coords={"N_POINTS": self._obj["N_POINTS"]},
- name="dummy_argo_uid",
+ self.uid(
+ self._obj["PLATFORM_NUMBER"].values,
+ self._obj["CYCLE_NUMBER"].values,
+ self._obj["DIRECTION"].values,
+ ),
+ dims="N_POINTS",
+ coords={"N_POINTS": self._obj["N_POINTS"]},
+ name="dummy_argo_uid",
)
else:
raise InvalidDatasetStructure(
@@ -221,7 +223,7 @@ def _dummy_argo_uid(self):
)
def uid(self, wmo_or_uid, cyc=None, direction=None):
- """ UID encoder/decoder
+ """UID encoder/decoder
Parameters
----------
@@ -242,21 +244,22 @@ def uid(self, wmo_or_uid, cyc=None, direction=None):
>>> wmo, cyc, drc = uid(unique_float_profile_id) # Decode
"""
+
def encode_direction(x):
- y = np.where(x == 'A', 1, x.astype(object))
- y = np.where(y == 'D', -1, y.astype(object))
+ y = np.where(x == "A", 1, x.astype(object))
+ y = np.where(y == "D", -1, y.astype(object))
try:
return y.astype(int)
except ValueError:
- raise ValueError('x has un-expected values')
+ raise ValueError("x has un-expected values")
def decode_direction(x):
x = np.array(x)
if np.any(np.unique(np.abs(x)) != 1):
- raise ValueError('x has un-expected values')
- y = np.where(x == 1, 'A', x)
- y = np.where(y == '-1', 'D', y)
- return y.astype('<U1')
+ raise ValueError("x has un-expected values")
+ y = np.where(x == 1, "A", x)
+ y = np.where(y == "-1", "D", y)
+ return y.astype("<U1")
offset = 1e5
@@ -286,18 +289,27 @@ def index(self):
this = self._obj
dummy_argo_uid = self._dummy_argo_uid
- idx = xr.DataArray(
- this["TIME"],
- dims="N_POINTS",
- coords={"N_POINTS": this["N_POINTS"]},
- ).groupby(dummy_argo_uid).max().to_dataset()
-
- for v in ["PLATFORM_NUMBER", "CYCLE_NUMBER", "LONGITUDE", "LATITUDE"]:
- idx[v] = xr.DataArray(
- this[v],
+ idx = (
+ xr.DataArray(
+ this["TIME"],
dims="N_POINTS",
coords={"N_POINTS": this["N_POINTS"]},
- ).groupby(dummy_argo_uid).max()
+ )
+ .groupby(dummy_argo_uid)
+ .max()
+ .to_dataset()
+ )
+
+ for v in ["PLATFORM_NUMBER", "CYCLE_NUMBER", "LONGITUDE", "LATITUDE"]:
+ idx[v] = (
+ xr.DataArray(
+ this[v],
+ dims="N_POINTS",
+ coords={"N_POINTS": this["N_POINTS"]},
+ )
+ .groupby(dummy_argo_uid)
+ .max()
+ )
df = idx.to_dataframe()
df = (
@@ -320,23 +332,39 @@ def index(self):
def domain(self):
"""Space/time domain of the dataset
- This is different from a usual argopy ``box`` because dates are in :class:`numpy.datetime64` format.
+ This is different from a usual argopy ``box`` because dates are in :class:`numpy.datetime64` format.
"""
this_ds = self._obj
- if 'PRES_ADJUSTED' in this_ds.data_vars:
- Pmin = np.nanmin((np.min(this_ds['PRES'].values), np.min(this_ds['PRES_ADJUSTED'].values)))
- Pmax = np.nanmax((np.max(this_ds['PRES'].values), np.max(this_ds['PRES_ADJUSTED'].values)))
+ if "PRES_ADJUSTED" in this_ds.data_vars:
+ Pmin = np.nanmin(
+ (
+ np.min(this_ds["PRES"].values),
+ np.min(this_ds["PRES_ADJUSTED"].values),
+ )
+ )
+ Pmax = np.nanmax(
+ (
+ np.max(this_ds["PRES"].values),
+ np.max(this_ds["PRES_ADJUSTED"].values),
+ )
+ )
else:
- Pmin = np.min(this_ds['PRES'].values)
- Pmax = np.max(this_ds['PRES'].values)
-
- return [np.min(this_ds['LONGITUDE'].values), np.max(this_ds['LONGITUDE'].values),
- np.min(this_ds['LATITUDE'].values), np.max(this_ds['LATITUDE'].values),
- Pmin, Pmax,
- np.min(this_ds['TIME'].values), np.max(this_ds['TIME'].values)]
+ Pmin = np.min(this_ds["PRES"].values)
+ Pmax = np.max(this_ds["PRES"].values)
+
+ return [
+ np.min(this_ds["LONGITUDE"].values),
+ np.max(this_ds["LONGITUDE"].values),
+ np.min(this_ds["LATITUDE"].values),
+ np.max(this_ds["LATITUDE"].values),
+ Pmin,
+ Pmax,
+ np.min(this_ds["TIME"].values),
+ np.max(this_ds["TIME"].values),
+ ]
def point2profile(self, drop: bool = False): # noqa: C901
- """ Transform a collection of points into a collection of profiles
+ """Transform a collection of points into a collection of profiles
A "point" is a single location for measurements in space and time
A "point" is localised as unique UID based on WMO, CYCLE_NUMBER and DIRECTION variable values.
@@ -358,7 +386,7 @@ def point2profile(self, drop: bool = False): # noqa: C901
this = self._obj # Should not be modified
def fillvalue(da):
- """ Return fillvalue for a dataarray """
+ """Return fillvalue for a dataarray"""
# https://docs.scipy.org/doc/numpy/reference/generated/numpy.dtype.kind.html#numpy.dtype.kind
if da.dtype.kind in ["U"]:
fillvalue = " "
@@ -385,11 +413,16 @@ def fillvalue(da):
.max()
.values
)
- log.debug("point2profile: New dataset should be [N_PROF=%i, N_LEVELS=%i]" % (N_PROF, N_LEVELS))
+ log.debug(
+ "point2profile: New dataset should be [N_PROF=%i, N_LEVELS=%i]"
+ % (N_PROF, N_LEVELS)
+ )
assert N_PROF * N_LEVELS >= len(this["N_POINTS"])
if N_LEVELS == 1:
- log.debug("point2profile: This dataset has a single vertical level, thus final variables will only have a N_PROF "
- "dimension and no N_LEVELS")
+ log.debug(
+ "point2profile: This dataset has a single vertical level, thus final variables will only have a N_PROF "
+ "dimension and no N_LEVELS"
+ )
# Store the initial set of coordinates:
coords_list = list(this.coords)
@@ -406,7 +439,10 @@ def fillvalue(da):
try:
count[i_prof, iv] = len(np.unique(prof[vname]))
except Exception:
- log.error("point2profile: An error happened when dealing with the '%s' data variable" % vname)
+ log.error(
+ "point2profile: An error happened when dealing with the '%s' data variable"
+ % vname
+ )
raise
# Variables with a unique value for each profiles:
@@ -455,7 +491,7 @@ def fillvalue(da):
y = new_ds[vname].values
x = prof[vname].values
try:
- y[i_prof, 0: len(x)] = x
+ y[i_prof, 0 : len(x)] = x
except Exception:
print(vname, "input", x.shape, "output", y[i_prof, :].shape)
raise
@@ -468,14 +504,18 @@ def fillvalue(da):
# Restore coordinate variables:
new_ds = new_ds.set_coords([c for c in coords_list if c in new_ds])
- new_ds['N_PROF'] = np.arange(N_PROF)
- if 'N_LEVELS' in new_ds['LATITUDE'].dims:
- new_ds['LATITUDE'] = new_ds['LATITUDE'].isel(N_LEVELS=0) # Make sure LAT is (N_PROF) and not (N_PROF, N_LEVELS)
- new_ds['LONGITUDE'] = new_ds['LONGITUDE'].isel(N_LEVELS=0)
+ new_ds["N_PROF"] = np.arange(N_PROF)
+ if "N_LEVELS" in new_ds["LATITUDE"].dims:
+ new_ds["LATITUDE"] = new_ds["LATITUDE"].isel(
+ N_LEVELS=0
+ ) # Make sure LAT is (N_PROF) and not (N_PROF, N_LEVELS)
+ new_ds["LONGITUDE"] = new_ds["LONGITUDE"].isel(N_LEVELS=0)
# Misc formatting
new_ds = new_ds.sortby("TIME")
- new_ds = new_ds.argo.cast_types() if not drop else cast_Argo_variable_type(new_ds)
+ new_ds = (
+ new_ds.argo.cast_types() if not drop else cast_Argo_variable_type(new_ds)
+ )
new_ds = new_ds[np.sort(new_ds.data_vars)]
new_ds.encoding = self.encoding # Preserve low-level encoding information
new_ds.attrs = self.attrs # Preserve original attributes
@@ -485,7 +525,7 @@ def fillvalue(da):
return new_ds
def profile2point(self):
- """ Convert a collection of profiles to a collection of points
+ """Convert a collection of profiles to a collection of points
A "point" is a single location for measurements in space and time
A "point" is localised as unique UID based on WMO, CYCLE_NUMBER and DIRECTION variable values.
@@ -539,7 +579,7 @@ def profile2point(self):
def filter_data_mode( # noqa: C901
self, keep_error: bool = True, errors: str = "raise"
):
- """ Filter variables according to their data mode
+ """Filter variables according to their data mode
This filter applies to <PARAM> and <PARAM_QC>
@@ -590,7 +630,7 @@ def safe_where_eq(xds, key, value):
xds = xds.drop_vars("TIME")
xds = xds.where(xds[key] == value, drop=True)
xds["TIME"] = xr.DataArray(
- np.empty((len(xds["N_POINTS"]),), dtype='datetime64[ns]'),
+ np.empty((len(xds["N_POINTS"]),), dtype="datetime64[ns]"),
dims="N_POINTS",
attrs=TIME.attrs,
)
@@ -598,9 +638,9 @@ def safe_where_eq(xds, key, value):
return xds
def ds_split_datamode(xds):
- """ Create one dataset for each of the data_mode
+ """Create one dataset for each of the data_mode
- Split full dataset into 3 datasets
+ Split full dataset into 3 datasets
"""
# Real-time:
argo_r = safe_where_eq(xds, "DATA_MODE", "R")
@@ -631,7 +671,7 @@ def ds_split_datamode(xds):
def fill_adjusted_nan(this_ds, vname):
"""Fill in the adjusted field with the non-adjusted wherever it is NaN
- Ensure to have values even for bad QC data in delayed mode
+ Ensure to have values even for bad QC data in delayed mode
"""
ii = this_ds.where(np.isnan(this_ds[vname + "_ADJUSTED"]), drop=1)[
"N_POINTS"
@@ -642,13 +682,13 @@ def fill_adjusted_nan(this_ds, vname):
return this_ds
def merge_arrays(this_argo_r, this_argo_a, this_argo_d, this_vname):
- """ Merge one variable from 3 DataArrays
+ """Merge one variable from 3 DataArrays
- Based on xarray merge function with ’no_conflicts’: only values
- which are not null in all datasets must be equal. The returned
- dataset then contains the combination of all non-null values.
+ Based on xarray merge function with ’no_conflicts’: only values
+ which are not null in all datasets must be equal. The returned
+ dataset then contains the combination of all non-null values.
- Return a xarray.DataArray
+ Return a xarray.DataArray
"""
def merge_this(a1, a2, a3):
@@ -686,7 +726,7 @@ def merge_this(a1, a2, a3):
#########
ds = self._obj
if "DATA_MODE" not in ds:
- if errors == 'raise':
+ if errors == "raise":
raise InvalidDatasetStructure(
"Method only available for dataset with a 'DATA_MODE' variable "
)
@@ -753,7 +793,7 @@ def merge_this(a1, a2, a3):
def filter_qc( # noqa: C901
self, QC_list=[1, 2], QC_fields="all", drop=True, mode="all", mask=False
):
- """ Filter data set according to QC values
+ """Filter data set according to QC values
Filter the dataset to keep points where ``all`` or ``any`` of the QC fields has a value in the list of
integer QC flags.
@@ -815,7 +855,9 @@ def filter_qc( # noqa: C901
)
if len(QC_fields) == 0:
- this.argo._add_history("Variables selected according to QC (but found no QC variables)")
+ this.argo._add_history(
+ "Variables selected according to QC (but found no QC variables)"
+ )
return this
log.debug(
@@ -852,7 +894,7 @@ def filter_qc( # noqa: C901
return this_mask
def filter_scalib_pres(self, force: str = "default", inplace: bool = True):
- """ Filter variables according to OWC salinity calibration software requirements
+ """Filter variables according to OWC salinity calibration software requirements
By default, this filter will return a dataset with raw PRES, PSAL and TEMP; and if PRES is adjusted,
PRES variable will be replaced by PRES_ADJUSTED.
@@ -966,11 +1008,13 @@ def filter_researchmode(self) -> xr.Dataset:
# Apply filter
this = this.argo.filter_data_mode(errors="ignore")
- if 'DATA_MODE' in this.data_vars:
- this = this.where(this['DATA_MODE'] == 'D', drop=True)
+ if "DATA_MODE" in this.data_vars:
+ this = this.where(this["DATA_MODE"] == "D", drop=True)
this = this.argo.filter_qc(QC_list=1)
- if 'PRES_ERROR' in this.data_vars: # PRES_ADJUSTED_ERROR was renamed PRES_ERROR by filter_data_mode
- this = this.where(this['PRES_ERROR'] < 20, drop=True)
+ if (
+ "PRES_ERROR" in this.data_vars
+ ): # PRES_ADJUSTED_ERROR was renamed PRES_ERROR by filter_data_mode
+ this = this.where(this["PRES_ERROR"] < 20, drop=True)
# Manage output:
if to_profile:
@@ -982,10 +1026,8 @@ def filter_researchmode(self) -> xr.Dataset:
this = this.argo.cast_types()
return this
- def interp_std_levels(self,
- std_lev: list or np.array,
- axis: str = 'PRES'):
- """ Interpolate measurements to standard pressure levels
+ def interp_std_levels(self, std_lev: list or np.array, axis: str = "PRES"):
+ """Interpolate measurements to standard pressure levels
Parameters
----------
@@ -1075,13 +1117,17 @@ def interp_std_levels(self,
z_regridded_dim="Z_LEVELS",
)
ds_out[dv].attrs = this_dsp[dv].attrs # Preserve attributes
- if 'long_name' in ds_out[dv].attrs:
- ds_out[dv].attrs['long_name'] = "Interpolated %s" % ds_out[dv].attrs['long_name']
+ if "long_name" in ds_out[dv].attrs:
+ ds_out[dv].attrs["long_name"] = (
+ "Interpolated %s" % ds_out[dv].attrs["long_name"]
+ )
ds_out = ds_out.rename({"remapped": "%s_INTERPOLATED" % axis})
ds_out["%s_INTERPOLATED" % axis].attrs = this_dsp[axis].attrs
if "long_name" in ds_out["%s_INTERPOLATED" % axis].attrs:
- ds_out["%s_INTERPOLATED" % axis].attrs['long_name'] = "Standard %s levels" % axis
+ ds_out["%s_INTERPOLATED" % axis].attrs["long_name"] = (
+ "Standard %s levels" % axis
+ )
for sv in solovars:
ds_out[sv] = this_dsp[sv]
@@ -1109,7 +1155,7 @@ def groupby_pressure_bins(
squeeze: bool = True,
merge: bool = True,
):
- """ Group measurements by pressure bins
+ """Group measurements by pressure bins
This method can be used to subsample and align an irregular dataset (pressure not being similar in all profiles)
on a set of pressure bins. The output dataset could then be used to perform statistics along the ``N_PROF`` dimension
@@ -1193,7 +1239,7 @@ def groupby_pressure_bins(
bins = bins[np.where(h > 0)]
def replace_i_level_values(this_da, this_i_level, new_values_along_profiles):
- """ Convenience fct to update only one level of a ["N_PROF", "N_LEVELS"] xr.DataArray"""
+ """Convenience fct to update only one level of a ["N_PROF", "N_LEVELS"] xr.DataArray"""
if this_da.dims == ("N_PROF", "N_LEVELS"):
values = this_da.values
values[:, this_i_level] = new_values_along_profiles
@@ -1203,11 +1249,11 @@ def replace_i_level_values(this_da, this_i_level, new_values_along_profiles):
return this_da
def nanmerge(x, y):
- """ Merge two 1D array
+ """Merge two 1D array
- Given 2 arrays x, y of 1 dimension, return a new array with:
- - x values where x is not NaN
- - y values where x is NaN
+ Given 2 arrays x, y of 1 dimension, return a new array with:
+ - x values where x is not NaN
+ - y values where x is NaN
"""
z = x.copy()
for i, v in enumerate(x):
@@ -1217,12 +1263,10 @@ def nanmerge(x, y):
merged_is_nan = lambda l1, l2: len( # noqa: E731
np.unique(np.where(np.isnan(l1.values + l2.values)))
- ) == len(
- l1
- )
+ ) == len(l1)
def merge_bin_matching_levels(this_ds: xr.Dataset) -> xr.Dataset:
- """ Levels merger of type 'bins' value
+ """Levels merger of type 'bins' value
Merge pair of lines with the following pattern:
nan, VAL, VAL, nan, VAL, VAL
@@ -1264,7 +1308,7 @@ def merge_bin_matching_levels(this_ds: xr.Dataset) -> xr.Dataset:
return new_ds
def merge_all_matching_levels(this_ds: xr.Dataset) -> xr.Dataset:
- """ Levels merger
+ """Levels merger
Merge any pair of levels with a "matching" pattern like this:
VAL, VAL, VAL, nan, nan, VAL, nan, nan,
@@ -1315,7 +1359,7 @@ def merge_all_matching_levels(this_ds: xr.Dataset) -> xr.Dataset:
dv
for dv in list(this_dsp.data_vars)
if set(["N_LEVELS", "N_PROF"]) == set(this_dsp[dv].dims)
- and dv not in DATA_TYPES['data']['str']
+ and dv not in DATA_TYPES["data"]["str"]
]
else:
datavars = [
@@ -1324,7 +1368,7 @@ def merge_all_matching_levels(this_ds: xr.Dataset) -> xr.Dataset:
if set(["N_LEVELS", "N_PROF"]) == set(this_dsp[dv].dims)
and "QC" not in dv
and "ERROR" not in dv
- and dv not in DATA_TYPES['data']['str']
+ and dv not in DATA_TYPES["data"]["str"]
]
# All other variables:
@@ -1388,7 +1432,7 @@ def teos10( # noqa: C901
vlist: list = ["SA", "CT", "SIG0", "N2", "PV", "PTEMP"],
inplace: bool = True,
):
- """ Add TEOS10 variables to the dataset
+ """Add TEOS10 variables to the dataset
By default, adds: 'SA', 'CT'
Other possible variables: 'SIG0', 'N2', 'PV', 'PTEMP', 'SOUND_SPEED'
@@ -1607,7 +1651,7 @@ def create_float_source(
do_compression: bool = True,
debug_output: bool = False,
):
- """ Preprocess data for OWC software calibration
+ """Preprocess data for OWC software calibration
This method can create a FLOAT SOURCE file (i.e. the .mat file that usually goes into /float_source/) for OWC software.
The FLOAT SOURCE file is saved as:
@@ -1763,7 +1807,7 @@ def preprocess_one_float(
select: str = "deep",
debug_output: bool = False,
):
- """ Run the entire preprocessing on a given dataset with one float data """
+ """Run the entire preprocessing on a given dataset with one float data"""
# Add potential temperature:
if "PTEMP" not in this_one:
@@ -1991,7 +2035,10 @@ def list_N_PROF_variables(self, uid=False):
try:
count[i_prof, iv] = len(np.unique(prof[vname]))
except Exception as e:
- print("An error happened when dealing with the '%s' data variable" % vname)
+ print(
+ "An error happened when dealing with the '%s' data variable"
+ % vname
+ )
raise (e)
# Variables with a single unique value for each profile:
@@ -2005,8 +2052,8 @@ def list_N_PROF_variables(self, uid=False):
def list_WMO_CYC(self):
"""Given a dataset, return a list with all possible (PLATFORM_NUMBER, CYCLE_NUMBER) tuple"""
profiles = []
- for wmo, grp in self._obj.groupby('PLATFORM_NUMBER'):
- [profiles.append((wmo, cyc)) for cyc in np.unique(grp['CYCLE_NUMBER'])]
+ for wmo, grp in self._obj.groupby("PLATFORM_NUMBER"):
+ [profiles.append((wmo, cyc)) for cyc in np.unique(grp["CYCLE_NUMBER"])]
return profiles
@@ -2017,18 +2064,19 @@ def open_Argo_dataset(filename_or_obj):
class ArgoEngine(BackendEntrypoint):
- """ Backend for Argo netCDF files based on the xarray netCDF4 engine
+ """Backend for Argo netCDF files based on the xarray netCDF4 engine
- It can open any Argo ".nc" files with 'Argo' in their global attribute 'Conventions'.
+ It can open any Argo ".nc" files with 'Argo' in their global attribute 'Conventions'.
- But it will not be detected as valid backend for netcdf files, so make
- sure to specify ``engine="argo"`` in :func:`xarray.open_dataset`.
+ But it will not be detected as valid backend for netcdf files, so make
+ sure to specify ``engine="argo"`` in :func:`xarray.open_dataset`.
- Examples
- --------
- >>> import xarray as xr
- >>> ds = xr.open_dataset("dac/aoml/1901393/1901393_prof.nc", engine='argo')
+ Examples
+ --------
+ >>> import xarray as xr
+ >>> ds = xr.open_dataset("dac/aoml/1901393/1901393_prof.nc", engine='argo')
"""
+
description = "Open Argo netCDF files (.nc)"
url = "https://argopy.readthedocs.io/en/latest/generated/argopy.xarray.ArgoEngine.html#argopy.xarray.ArgoEngine"
@@ -2050,7 +2098,7 @@ def guess_can_open(self, filename_or_obj):
except TypeError:
return False
if ext in {".nc"}:
- attrs = xr.open_dataset(filename_or_obj, engine='netcdf4').attrs
- return 'Conventions' in attrs and 'Argo' in attrs['Conventions']
+ attrs = xr.open_dataset(filename_or_obj, engine="netcdf4").attrs
+ return "Conventions" in attrs and "Argo" in attrs["Conventions"]
else:
return False
diff --git a/ci/envs_manager b/ci/envs_manager
index c1668504..de576f40 100755
--- a/ci/envs_manager
+++ b/ci/envs_manager
@@ -19,22 +19,21 @@ source ~/miniconda3/etc/profile.d/conda.sh
# LIST ALL AVAILABLE ENVIRONMENTS AND THE ASSOCIATED YAML FILE
#########################
declare -A ENV_LIST=(
-['argopy-docs']="requirements/py3.9-docs.yml"
-
-['argopy-py37-all-free']="requirements/py3.7-all-free.yml"
-['argopy-py37-core-free']="requirements/py3.7-core-free.yml"
-
-['argopy-py38-all-free']="requirements/py3.8-all-free.yml"
-['argopy-py38-all-pinned']="requirements/py3.8-all-pinned.yml"
-
-['argopy-py38-core-free']="requirements/py3.8-core-free.yml"
-['argopy-py38-core-pinned']="requirements/py3.8-core-pinned.yml"
+['argopy-docs-dev']="requirements/py3.9-docs-dev.yml"
+['argopy-docs-rtd']="requirements/py3.9-docs-rtd.yml"
['argopy-py39-all-free']="requirements/py3.9-all-free.yml"
['argopy-py39-all-pinned']="requirements/py3.9-all-pinned.yml"
['argopy-py39-core-pinned']="requirements/py3.9-core-pinned.yml"
['argopy-py39-core-free']="requirements/py3.9-core-free.yml"
+
+['argopy-py310-all-free']="requirements/py3.10-all-free.yml"
+['argopy-py310-all-pinned']="requirements/py3.10-all-pinned.yml"
+
+['argopy-py310-core-free']="requirements/py3.10-core-free.yml"
+['argopy-py310-core-pinned']="requirements/py3.10-core-pinned.yml"
+
)
diff --git a/ci/requirements/py3.8-all-free.yml b/ci/requirements/py3.10-all-free.yml
similarity index 74%
rename from ci/requirements/py3.8-all-free.yml
rename to ci/requirements/py3.10-all-free.yml
index 6b802b9c..47da7b4b 100644
--- a/ci/requirements/py3.8-all-free.yml
+++ b/ci/requirements/py3.10-all-free.yml
@@ -2,7 +2,7 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python = 3.8
+ - python = 3.10.14
# CORE:
- aiohttp
@@ -14,7 +14,7 @@ dependencies:
- requests
- scipy
- toolz
- - xarray<2024.3
+ - xarray < 2024.3 # while https://github.com/pydata/xarray/issues/8909 is not solved
# EXT.UTIL:
- boto3
@@ -26,13 +26,14 @@ dependencies:
# EXT.PERF:
- dask
- distributed
+ - h5netcdf
- pyarrow
# EXT.PLOT:
- IPython
- cartopy
- ipykernel
- - ipywidgets <= 7.8.0
+ - ipywidgets
- matplotlib
- pyproj
- seaborn
@@ -43,9 +44,8 @@ dependencies:
- bottleneck
- cfgrib
- cftime
-# - conda
+ - codespell
- flake8
-# - nc-time-axis
- numpy
- pandas
- pip
@@ -54,6 +54,8 @@ dependencies:
- pytest-env
- pytest-localftpserver
- setuptools
+# - sphinx
+# PIP:
- pip:
- - pytest-reportlog
\ No newline at end of file
+ - pytest-reportlog
diff --git a/ci/requirements/py3.10-all-pinned.yml b/ci/requirements/py3.10-all-pinned.yml
new file mode 100644
index 00000000..f20410d2
--- /dev/null
+++ b/ci/requirements/py3.10-all-pinned.yml
@@ -0,0 +1,61 @@
+name: argopy-tests
+channels:
+ - conda-forge
+dependencies:
+ - python = 3.10.14
+
+# CORE:
+ - aiohttp = 3.10.4
+ - decorator = 5.1.1
+ - erddapy = 2.2.0
+ - fsspec = 2024.6.1
+ - netCDF4 = 1.7.1
+ - packaging = 24.1
+ - requests = 2.32.3
+ - scipy = 1.14.0
+ - toolz = 0.12.1
+ - xarray = 2024.2.0
+
+# EXT.UTIL:
+ - boto3 = 1.35.0
+ - gsw = 3.6.19
+ - s3fs = 0.4.2
+ - tqdm = 4.66.5
+ - zarr = 2.18.2
+
+# EXT.PERF:
+ - dask = 2024.8.1
+ - distributed = 2024.8.1
+ - h5netcdf = 1.3.0
+ - pyarrow = 17.0.0
+
+# EXT.PLOT:
+ - IPython = 8.26.0
+ - cartopy = 0.23.0
+ - ipykernel = 6.29.5
+ - ipywidgets = 8.1.3
+ - matplotlib = 3.9.2
+ - pyproj = 3.6.1
+ - seaborn = 0.13.2
+
+# DEV:
+ - aiofiles = 24.1.0
+ - black = 24.8.0
+ - bottleneck = 1.4.0
+ - cfgrib = 0.9.14.0
+ - cftime = 1.6.4
+ - codespell = 2.3.0
+ - flake8 = 7.1.1
+ - numpy = 1.26.4
+ - pandas = 2.2.2
+ - pip = 24.2
+ - pytest = 8.3.2
+ - pytest-cov = 5.0.0
+ - pytest-env = 1.1.3
+ - pytest-localftpserver
+ - setuptools = 72.1.0
+# - sphinx = -
+
+# PIP:
+ - pip:
+ - pytest-reportlog == 0.4.0
\ No newline at end of file
diff --git a/ci/requirements/py3.8-core-free.yml b/ci/requirements/py3.10-core-free.yml
similarity index 81%
rename from ci/requirements/py3.8-core-free.yml
rename to ci/requirements/py3.10-core-free.yml
index 8a0a8740..94f62622 100644
--- a/ci/requirements/py3.8-core-free.yml
+++ b/ci/requirements/py3.10-core-free.yml
@@ -2,7 +2,7 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python = 3.8
+ - python = 3.10.14
# CORE:
- aiohttp
@@ -14,7 +14,7 @@ dependencies:
- requests
- scipy
- toolz
- - xarray<2024.3
+ - xarray < 2024.3 # while https://github.com/pydata/xarray/issues/8909 is not solved
# EXT.UTIL:
# - boto3
@@ -26,6 +26,7 @@ dependencies:
# EXT.PERF:
# - dask
# - distributed
+# - h5netcdf
# - pyarrow
# EXT.PLOT:
@@ -43,9 +44,8 @@ dependencies:
- bottleneck
- cfgrib
- cftime
-# - conda
+ - codespell
- flake8
-# - nc-time-axis
- numpy
- pandas
- pip
@@ -56,5 +56,6 @@ dependencies:
- setuptools
# - sphinx
+# PIP:
- pip:
- pytest-reportlog
\ No newline at end of file
diff --git a/ci/requirements/py3.10-core-pinned.yml b/ci/requirements/py3.10-core-pinned.yml
new file mode 100644
index 00000000..95e4e481
--- /dev/null
+++ b/ci/requirements/py3.10-core-pinned.yml
@@ -0,0 +1,61 @@
+name: argopy-tests
+channels:
+ - conda-forge
+dependencies:
+ - python = 3.10.14
+
+# CORE:
+ - aiohttp = 3.10.4
+ - decorator = 5.1.1
+ - erddapy = 2.2.0
+ - fsspec = 2024.6.1
+ - netCDF4 = 1.7.1
+ - packaging = 24.1
+ - requests = 2.32.3
+ - scipy = 1.14.0
+ - toolz = 0.12.1
+ - xarray = 2024.2.0
+
+# EXT.UTIL:
+# - boto3 = 1.35.0
+# - gsw = 3.6.19
+# - s3fs = 0.4.2
+# - tqdm = 4.66.5
+# - zarr = 2.18.2
+
+# EXT.PERF:
+# - dask = 2024.8.1
+# - distributed = 2024.8.1
+# - h5netcdf = 1.3.0
+# - pyarrow = 17.0.0
+
+# EXT.PLOT:
+# - IPython = 8.26.0
+# - cartopy = 0.23.0
+# - ipykernel = 6.29.5
+# - ipywidgets = 8.1.3
+# - matplotlib = 3.9.2
+# - pyproj = 3.6.1
+# - seaborn = 0.13.2
+
+# DEV:
+ - aiofiles = 24.1.0
+ - black = 24.8.0
+ - bottleneck = 1.4.0
+ - cfgrib = 0.9.14.0
+ - cftime = 1.6.4
+ - codespell = 2.3.0
+ - flake8 = 7.1.1
+ - numpy = 1.26.4
+ - pandas = 2.2.2
+ - pip = 24.2
+ - pytest = 8.3.2
+ - pytest-cov = 5.0.0
+ - pytest-env = 1.1.3
+ - pytest-localftpserver
+ - setuptools = 72.1.0
+# - sphinx = -
+
+# PIP:
+ - pip:
+ - pytest-reportlog == 0.4.0
\ No newline at end of file
diff --git a/ci/requirements/py3.8-all-pinned.yml b/ci/requirements/py3.8-all-pinned.yml
deleted file mode 100644
index 56ab3b01..00000000
--- a/ci/requirements/py3.8-all-pinned.yml
+++ /dev/null
@@ -1,61 +0,0 @@
-name: argopy-tests
-channels:
- - conda-forge
-dependencies:
- - python = 3.8
-
-# CORE:
- - aiohttp = 3.8.6
- - decorator = 5.1.1
- - erddapy = 2.2.0
- - fsspec = 2023.9.2
- - netCDF4 = 1.6.4
- - packaging = 23.2
- - requests = 2.31.0
- - scipy = 1.10.1
- - toolz = 0.12.0
- - xarray = 2023.1.0
-
-# EXT.UTIL:
- - boto3 = 1.28.17
- - gsw = 3.6.17
- - s3fs = 2023.9.2
- - tqdm = 4.66.1
- - zarr = 2.13.3
-
-# EXT.PERF:
- - dask = 2023.5.0
- - distributed = 2023.5.0
- - pyarrow = 13.0.0
-
-# EXT.PLOT:
- - IPython = 8.12.2
- - cartopy = 0.21.1
- - ipykernel = 6.25.2
- - ipywidgets = 7.8.0
- - matplotlib = 3.7.3
- - pyproj = 3.5.0
- - seaborn = 0.13.0
-
-# DEV:
- - aiofiles = 23.1.0
- - black = 23.9.1
- - bottleneck = 1.3.7
- - cfgrib = 0.9.10.4
- - cftime = 1.6.2
-# - conda = -
- - flake8 = 6.1.0
-# - nc-time-axis = -
- - numpy = 1.24.4
- - pandas = 1.5.3
- - pip = 23.2.1
- - pytest = 7.4.2
- - pytest-cov = 4.1.0
- - pytest-env = 1.0.1
- - pytest-localftpserver = 1.1.4
- - setuptools = 68.2.2
-# - sphinx = -
-
-# PIP:
- - pip:
- - pytest-reportlog == 0.4.0
diff --git a/ci/requirements/py3.8-core-pinned.yml b/ci/requirements/py3.8-core-pinned.yml
deleted file mode 100644
index 3eb19957..00000000
--- a/ci/requirements/py3.8-core-pinned.yml
+++ /dev/null
@@ -1,60 +0,0 @@
-name: argopy-tests
-channels:
- - conda-forge
-dependencies:
- - python = 3.8
-
-# CORE:
- - aiohttp = 3.8.6
- - decorator = 5.1.1
- - erddapy = 2.2.0
- - fsspec = 2023.9.2
- - netCDF4 = 1.6.4
- - packaging = 23.2
- - requests = 2.31.0
- - scipy = 1.10.1
- - toolz = 0.12.0
- - xarray = 2023.1.0
-
-# EXT.UTIL:
-# - boto3 = 1.28.17
-# - gsw = 3.6.17
-# - s3fs = 2023.9.2
-# - tqdm = 4.66.1
-# - zarr = 2.13.3
-
-# EXT.PERF:
-# - dask = 2023.5.0
-# - distributed = 2023.5.0
-# - pyarrow = 13.0.0
-
-# EXT.PLOT:
-# - IPython = 8.12.2
-# - cartopy = 0.21.1
-# - ipykernel = 6.25.2
-# - ipywidgets = 7.8.0
-# - matplotlib = 3.7.3
-# - pyproj = 3.5.0
-# - seaborn = 0.13.0
-
-# DEV:
- - aiofiles = 23.1.0
- - black = 23.9.1
- - bottleneck = 1.3.7
- - cfgrib = 0.9.10.4
- - cftime = 1.6.2
-# - conda = -
- - flake8 = 6.1.0
-# - nc-time-axis = -
- - numpy = 1.24.4
- - pandas = 1.5.3
- - pip = 23.2.1
- - pytest = 7.4.2
- - pytest-cov = 4.1.0
- - pytest-env = 1.0.1
- - pytest-localftpserver = 1.1.4
- - setuptools = 68.2.2
-# - sphinx = -
-
- - pip:
- - pytest-reportlog == 0.4.0
diff --git a/ci/requirements/py3.9-all-free.yml b/ci/requirements/py3.9-all-free.yml
index 35286507..8219167e 100644
--- a/ci/requirements/py3.9-all-free.yml
+++ b/ci/requirements/py3.9-all-free.yml
@@ -2,7 +2,7 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python=3.9
+ - python = 3.9.19
# CORE:
- aiohttp
@@ -14,7 +14,7 @@ dependencies:
- requests
- scipy
- toolz
- - xarray<2024.3
+ - xarray < 2024.3 # while https://github.com/pydata/xarray/issues/8909 is not solved
# EXT.UTIL:
- boto3
@@ -35,6 +35,7 @@ dependencies:
- ipykernel
- ipywidgets
- matplotlib
+ - pyproj
- seaborn
# DEV:
@@ -43,9 +44,8 @@ dependencies:
- bottleneck
- cfgrib
- cftime
-# - conda
+ - codespell
- flake8
-# - nc-time-axis
- numpy
- pandas
- pip
@@ -54,6 +54,8 @@ dependencies:
- pytest-env
- pytest-localftpserver
- setuptools
+# - sphinx
+# PIP:
- pip:
- pytest-reportlog
diff --git a/ci/requirements/py3.9-all-pinned.yml b/ci/requirements/py3.9-all-pinned.yml
index e94f6fb3..62ca9fa9 100644
--- a/ci/requirements/py3.9-all-pinned.yml
+++ b/ci/requirements/py3.9-all-pinned.yml
@@ -2,58 +2,60 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python=3.9
+ - python = 3.9.19
# CORE:
- - aiohttp = 3.8.5
+ - aiohttp = 3.10.4
- decorator = 5.1.1
- erddapy = 2.2.0
- - fsspec = 2023.9.2
- - netCDF4 = 1.6.4
- - packaging = 23.1
- - requests = 2.31.0
- - scipy = 1.11.3
- - toolz = 0.12.0
- - xarray = 2023.9.0
+ - fsspec = 2024.6.1
+ - netCDF4 = 1.7.1
+ - packaging = 24.1
+ - requests = 2.32.3
+ - scipy = 1.13.1
+ - toolz = 0.12.1
+ - xarray = 2024.2.0
# EXT.UTIL:
- - boto3 = 1.28.17
- - gsw = 3.6.17
- - s3fs = 2023.9.2
- - tqdm = 4.66.1
- - zarr = 2.16.1
+ - boto3 = 1.35.0
+ - gsw = 3.6.19
+ - s3fs = 0.4.2
+ - tqdm = 4.66.5
+ - zarr = 2.18.2
# EXT.PERF:
- - dask = 2023.9.2
- - distributed = 2023.9.2
- - h5netcdf = 1.2.0
- - pyarrow = 13.0.0
+ - dask = 2024.8.0
+ - distributed = 2024.8.0
+ - h5netcdf = 1.3.0
+ - pyarrow = 17.0.0
# EXT.PLOT:
- - IPython = 8.15.0
- - cartopy = 0.22.0
- - ipykernel = 6.25.2
- - ipywidgets = 8.1.1
- - matplotlib = 3.8.0
- - seaborn = 0.12.2
+ - IPython = 8.18.1
+ - cartopy = 0.23.0
+ - ipykernel = 6.29.5
+ - ipywidgets = 8.1.3
+ - matplotlib = 3.9.2
+ - pyproj = 3.6.1
+ - seaborn = 0.13.2
# DEV:
- - aiofiles = 23.1.0
- - black = 23.9.1
- - bottleneck = 1.3.7
- - cfgrib = 0.9.10.4
- - cftime = 1.6.2
-# - conda = -
- - flake8 = 6.1.0
-# - nc-time-axis = -
- - numpy = 1.26.0
- - pandas = 2.1.1
- - pip = 23.2.1
- - pytest = 7.4.2
- - pytest-cov = 4.1.0
- - pytest-env = 1.0.1
- - pytest-localftpserver = 1.1.4
- - setuptools = 68.2.2
+ - aiofiles = 24.1.0
+ - black = 24.8.0
+ - bottleneck = 1.4.0
+ - cfgrib = 0.9.14.0
+ - cftime = 1.6.4
+ - codespell
+ - flake8 = 7.1.1
+ - numpy = 1.26.4
+ - pandas = 2.2.2
+ - pip = 24.2
+ - pytest = 8.3.2
+ - pytest-cov = 5.0.0
+ - pytest-env = 1.1.3
+ - pytest-localftpserver
+ - setuptools = 72.1.0
+# - sphinx = -
+# PIP:
- pip:
- - pytest-reportlog==0.1.2
+ - pytest-reportlog == 0.4.0
diff --git a/ci/requirements/py3.9-core-free.yml b/ci/requirements/py3.9-core-free.yml
index 771eec21..c38813de 100644
--- a/ci/requirements/py3.9-core-free.yml
+++ b/ci/requirements/py3.9-core-free.yml
@@ -2,7 +2,7 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python=3.9
+ - python = 3.9.19
# CORE:
- aiohttp
@@ -14,7 +14,7 @@ dependencies:
- requests
- scipy
- toolz
- - xarray<2024.3
+ - xarray < 2024.3 # while https://github.com/pydata/xarray/issues/8909 is not solved
# EXT.UTIL:
# - boto3
@@ -35,6 +35,7 @@ dependencies:
# - ipykernel
# - ipywidgets
# - matplotlib
+# - pyproj
# - seaborn
# DEV:
@@ -43,9 +44,8 @@ dependencies:
- bottleneck
- cfgrib
- cftime
-# - conda
+ - codespell
- flake8
-# - nc-time-axis
- numpy
- pandas
- pip
@@ -54,6 +54,8 @@ dependencies:
- pytest-env
- pytest-localftpserver
- setuptools
+# - sphinx
+# PIP:
- pip:
- pytest-reportlog
diff --git a/ci/requirements/py3.9-core-pinned.yml b/ci/requirements/py3.9-core-pinned.yml
index cd6bd5f5..47051c8b 100644
--- a/ci/requirements/py3.9-core-pinned.yml
+++ b/ci/requirements/py3.9-core-pinned.yml
@@ -2,58 +2,60 @@ name: argopy-tests
channels:
- conda-forge
dependencies:
- - python=3.9
+ - python = 3.9.19
# CORE:
- - aiohttp = 3.8.5
+ - aiohttp = 3.10.4
- decorator = 5.1.1
- erddapy = 2.2.0
- - fsspec = 2023.9.2
- - netCDF4 = 1.6.4
- - packaging = 23.1
- - requests = 2.31.0
- - scipy = 1.11.3
- - toolz = 0.12.0
- - xarray = 2023.9.0
+ - fsspec = 2024.6.1
+ - netCDF4 = 1.7.1
+ - packaging = 24.1
+ - requests = 2.32.3
+ - scipy = 1.13.1
+ - toolz = 0.12.1
+ - xarray = 2024.2.0
-# # EXT.UTIL:
-# - boto3 = 1.28.17
-# - gsw = 3.6.17
-# - s3fs = 2023.9.2
-# - tqdm = 4.66.1
-# - zarr = 2.16.1
+# EXT.UTIL:
+# - boto3 = 1.35.0
+# - gsw = 3.6.19
+# - s3fs = 0.4.2
+# - tqdm = 4.66.5
+# - zarr = 2.18.2
-# # EXT.PERF:
-# - dask = 2023.9.2
-# - distributed = 2023.9.2
-# - h5netcdf = 1.2.0
-# - pyarrow = 13.0.0
+# EXT.PERF:
+# - dask = 2024.8.0
+# - distributed = 2024.8.0
+# - h5netcdf = 1.3.0
+# - pyarrow = 17.0.0
-# # EXT.PLOT:
-# - IPython = 8.15.0
-# - cartopy = 0.22.0
-# - ipykernel = 6.25.2
-# - ipywidgets = 8.1.1
-# - matplotlib = 3.8.0
-# - seaborn = 0.12.2
+# EXT.PLOT:
+# - IPython = 8.18.1
+# - cartopy = 0.23.0
+# - ipykernel = 6.29.5
+# - ipywidgets = 8.1.3
+# - matplotlib = 3.9.2
+# - pyproj = 3.6.1
+# - seaborn = 0.13.2
# DEV:
- - aiofiles = 23.1.0
- - black = 23.9.1
- - bottleneck = 1.3.7
- - cfgrib = 0.9.10.4
- - cftime = 1.6.2
-# - conda = -
- - flake8 = 6.1.0
-# - nc-time-axis = -
- - numpy = 1.26.0
- - pandas = 2.1.1
- - pip = 23.2.1
- - pytest = 7.4.2
- - pytest-cov = 4.1.0
- - pytest-env = 1.0.1
- - pytest-localftpserver = 1.1.4
- - setuptools = 68.2.2
+ - aiofiles = 24.1.0
+ - black = 24.8.0
+ - bottleneck = 1.4.0
+ - cfgrib = 0.9.14.0
+ - cftime = 1.6.4
+ - codespell
+ - flake8 = 7.1.1
+ - numpy = 1.26.4
+ - pandas = 2.2.2
+ - pip = 24.2
+ - pytest = 8.3.2
+ - pytest-cov = 5.0.0
+ - pytest-env = 1.1.3
+ - pytest-localftpserver
+ - setuptools = 72.1.0
+# - sphinx = -
+# PIP:
- pip:
- - pytest-reportlog==0.1.2
+ - pytest-reportlog == 0.4.0
diff --git a/ci/requirements/py3.9-docs.yml b/ci/requirements/py3.9-docs-dev.yml
similarity index 97%
rename from ci/requirements/py3.9-docs.yml
rename to ci/requirements/py3.9-docs-dev.yml
index 28f58ecb..9f883003 100644
--- a/ci/requirements/py3.9-docs.yml
+++ b/ci/requirements/py3.9-docs-dev.yml
@@ -1,4 +1,4 @@
-name: argopy-docs
+name: argopy-docs-dev
channels:
- conda-forge
dependencies:
@@ -18,6 +18,7 @@ dependencies:
- cartopy
- cmocean
- cftime
+ - cfgrib
- decorator
- distributed
- ipython
@@ -40,7 +41,6 @@ dependencies:
- sphinx-book-theme
- pydata-sphinx-theme
- codespell
- - cfgrib
- black
- flake8
- pytest-cov
diff --git a/ci/requirements/py3.9-docs-rtd.yml b/ci/requirements/py3.9-docs-rtd.yml
new file mode 100644
index 00000000..6efcae9c
--- /dev/null
+++ b/ci/requirements/py3.9-docs-rtd.yml
@@ -0,0 +1,59 @@
+name: argopy-docs-rtd
+channels:
+ - conda-forge
+dependencies:
+ - python=3.9
+ - xarray=2024.2.0
+ - scipy
+ - netcdf4
+ - dask
+# - toolz
+ - erddapy
+ - fsspec
+ - gsw
+ - aiohttp
+# - bottleneck
+ - s3fs
+ - boto3
+# - cartopy
+# - cmocean
+ - cftime
+ - cfgrib
+ - decorator
+ - distributed
+ - ipython
+ - matplotlib
+# - numpy
+ - pandas
+# - packaging
+ - pip
+# - pytest
+# - seaborn
+# - setuptools
+ - zarr
+ - tqdm
+ - ipykernel
+ - ipywidgets
+ - nbsphinx
+ - jinja2
+ - sphinx-issues
+ - sphinx_rtd_theme
+ - sphinx-book-theme
+ - pydata-sphinx-theme
+# - codespell
+# - black
+# - flake8
+# - pytest-cov
+# - pytest-env
+ - pip:
+ - Sphinx
+ - numpydoc
+ - readthedocs-sphinx-ext
+ - sphinx-autosummary-accessors
+ - pydocstyle
+ - sphinx-tabs
+ - sphinxext-rediraffe
+# - sphinxext-opengraph
+ - git+https://github.com/sphinx-contrib/googleanalytics
+ - sphinx-copybutton
+ - sphinx-design
diff --git a/cli/show_versions b/cli/show_versions
index 52e5abbe..f25b2396 100755
--- a/cli/show_versions
+++ b/cli/show_versions
@@ -9,6 +9,16 @@ import locale
import argparse
import setuptools
from importlib.metadata import version
+import shutil
+import json
+
+PIP_INSTALLED = {}
+try:
+ reqs = subprocess.check_output([sys.executable, '-m', 'pip', 'list', '--format', 'json'])
+ reqs = json.loads(reqs.decode())
+ [PIP_INSTALLED.update({mod['name']: mod['version']}) for mod in reqs]
+except:
+ pass
def get_sys_info():
@@ -79,6 +89,25 @@ def netcdf_and_hdf5_versions():
return [("libhdf5", libhdf5_version), ("libnetcdf", libnetcdf_version)]
+def cli_version(cli_name):
+ try:
+ a = subprocess.run([cli_name, '--version'], capture_output=True)
+ return a.stdout.decode().strip("\n").replace(cli_name, '').strip()
+ except:
+ if shutil.which(cli_name):
+ return "- # installed"
+ else:
+ return "-"
+
+
+def pip_version(pip_name):
+ version = '-'
+ for name in [pip_name, pip_name.replace("_", "-"), pip_name.replace("-", "_")]:
+ if name in PIP_INSTALLED:
+ version = PIP_INSTALLED[name]
+ return version
+
+
def get_version(module_name):
ver = '-'
try:
@@ -87,7 +116,15 @@ def get_version(module_name):
try:
ver = version(module_name)
except importlib.metadata.PackageNotFoundError:
- pass
+ try:
+ ver = pip_version(module_name)
+ except:
+ try:
+ ver = cli_version(module_name)
+ except:
+ pass
+ if sum([int(v == '0') for v in ver.split(".")]) == len(ver.split(".")):
+ ver = '-'
return ver
@@ -151,9 +188,8 @@ def show_versions(file=sys.stdout, conda=False, free=False, core=False): # noqa
("bottleneck", get_version),
("cftime", get_version),
("cfgrib", get_version),
- ("conda", get_version),
+ ("codespell", cli_version),
("flake8", get_version),
- ("nc_time_axis", get_version),
("numpy", get_version), # will come with xarray and pandas
("pandas", get_version), # will come with xarray
("pip", get_version),
@@ -165,7 +201,7 @@ def show_versions(file=sys.stdout, conda=False, free=False, core=False): # noqa
("sphinx", get_version),
]),
'pip': sorted([
- ("pytest_reportlog", get_version),
+ ("pytest_reportlog", pip_version),
])
}
@@ -176,19 +212,11 @@ def show_versions(file=sys.stdout, conda=False, free=False, core=False): # noqa
deps_blob = list()
for (modname, ver_f) in deps:
try:
- if modname in sys.modules:
- mod = sys.modules[modname]
- else:
- mod = importlib.import_module(modname)
+ ver = ver_f(modname)
+ deps_blob.append((modname, ver))
except Exception:
- deps_blob.append((modname, '-'))
- else:
- try:
- ver = ver_f(modname)
- deps_blob.append((modname, ver))
- except Exception:
- # raise ValueError("Can't get version for '%s'" % modname)
- deps_blob.append((modname, "installed"))
+ # raise ValueError("Can't get version for '%s'" % modname)
+ deps_blob.append((modname, "installed"))
DEPS_blob[level] = deps_blob
# Print:
diff --git a/docs/impact.rst b/docs/impact.rst
index 51202c7d..4e1c83db 100644
--- a/docs/impact.rst
+++ b/docs/impact.rst
@@ -4,24 +4,28 @@ Impact of argopy
Papers & proceedings mentioning argopy
--------------------------------------
-- Bartlett, Jenna, "An investigation of geostationary satellite imagery to compare developing and non-developing African easterly waves" (2022). Theses and Dissertations. 5600. https://scholarsjunction.msstate.edu/td/5600
+- Bartlett, Jenna, "An investigation of geostationary satellite imagery to compare developing and non-developing African easterly waves" (2022). Thesis and Dissertations. 5600. https://scholarsjunction.msstate.edu/td/5600
- Chafik, et.al, "The Faroe-Shetland Channel Jet: Structure, Variability, and Driving Mechanisms", 2023, JGR Oceans, https://doi.org/10.1029/2022JC019083
- Dan E. Kelley, Jaimie Harbin, Clark Richards, "argoFloats: An R Package for Analyzing Argo Data", 2021 Frontiers in Marine Science, https://doi.org/10.3389/fmars.2021.635922
-- de Solo, Sofia M., "What makes a hurricane fall apart? A multi-platform assessment of tropical cyclone weakening By" (2021). Theses and Dissertations. 5274. https://scholarsjunction.msstate.edu/td/5274
+- de Solo, Sofia M., "What makes a hurricane fall apart? A multi-platform assessment of tropical cyclone weakening By" (2021). Thesis and Dissertations. 5274. https://scholarsjunction.msstate.edu/td/5274
- Dunnington et al., (2021). argodata: An R interface to oceanographic data from the International Argo Program. Journal of Open Source Software, 6(68), 3659, https://doi.org/10.21105/joss.03659
+- Elipot S. , P Miron, M Curcic, K Santana, R Lumpkin (2024). Clouddrift: a Python package to accelerate the use of Lagrangian data for atmospheric, oceanic, and climate sciences. Journal of Open Source Software, 9(99), 6742, https://joss.theoj.org/papers/10.21105/joss.06742
+
- Gonzalez A., "The Argo Online School: An e-learning tool to get started with Argo" (2023), The Journal of Open Source Education (Under review)
-- Huda, Md Nurul, "Machine Learning for Improvement of Ocean Data Resolution for Weather Forecasting and Climatological Research" (2023). Theses and Dissertations, Virginia Tech, http://hdl.handle.net/10919/116504
+- Huda, Md Nurul, "Machine Learning for Improvement of Ocean Data Resolution for Weather Forecasting and Climatological Research" (2023). Thesis and Dissertations, Virginia Tech, http://hdl.handle.net/10919/116504
- Steinberg, J. M., Piecuch, C. G., Hamlington, B. D., Thompson, P. R., & Coats, S. (2024). Influence of deep-ocean warming on coastal sea-level decadal trends in the Gulf of Mexico. Journal of Geophysical Research: Oceans, 129, e2023JC019681. https://doi.org/10.1029/2023JC019681
- Zhang, Y. (2023). Python Data Analysis Techniques in Administrative Information Integration Management System. In: Atiquzzaman, M., Yen, N.Y., Xu, Z. (eds) Proceedings of the 4th International Conference on Big Data Analytics for Cyber-Physical System in Smart City - Volume 2. BDCPS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 168. Springer, Singapore. https://doi.org/10.1007/978-981-99-1157-8_35
+
+
Other interesting mentions
--------------------------
diff --git a/docs/install.rst b/docs/install.rst
index daf3b775..5669da97 100644
--- a/docs/install.rst
+++ b/docs/install.rst
@@ -32,18 +32,20 @@ Required dependencies
- aiohttp
- erddapy
-- fsspec < 2023.12.0 (more at :issue:`317`)
+- fsspec
- netCDF4
- scipy
- toolz
-- xarray
+- xarray < 2024.3.0 (because of `this issue <https://github.com/pydata/xarray/issues/8909>`_)
- requests
+- decorator
+- packaging
Note that Erddapy_ is required because `erddap <https://coastwatch.pfeg.noaa.gov/erddap/information.html>`_ is the default data fetching backend.
Requirement dependencies details can be found `here <https://github.com/euroargodev/argopy/network/dependencies#requirements.txt>`_.
-The **argopy** software is `continuously tested <https://github.com/euroargodev/argopy/actions?query=workflow%3Atests>`_ under latest OS (Linux, Mac OS and Windows) and with python versions 3.8 and 3.9
+The **argopy** software is `continuously tested <https://github.com/euroargodev/argopy/actions?query=workflow%3Atests>`_ under latest OS (Linux, Mac OS and Windows) and with python versions 3.9 and 3.10
Optional dependencies
---------------------
diff --git a/docs/requirements.txt b/docs/requirements.txt
index d1a64f19..e8926d1d 100644
--- a/docs/requirements.txt
+++ b/docs/requirements.txt
@@ -1,54 +1,60 @@
+xarray==2024.2.0
+scipy>=1.5
+netcdf4>=1.5.4
+dask>=2021.9.1
+# toolz>=0.8.2
+erddapy>=0.7.2
+fsspec>=0.7.4 #, <2022.3.1
+gsw>=3.4.0
+aiohttp>=3.7.4
+# bottleneck>=1.3.2
+s3fs
+boto3
+cftime # >=1.5.1
+cfgrib # >=0.9.9.1
+decorator
+distributed>=2.30.0
+ipython<=8.26.0
+matplotlib>=3.4.0
+numpy==1.26.4
+pandas<3.0
+# packaging
pip>=23.1
-# pkgconfig
+# pytest
+# seaborn>=0.11.0
+# setuptools
+zarr>=2.4.0
+tqdm>=4.50.2
ipykernel>=6.22
-ipython<=8.26.0
ipywidgets>=8.0
-urllib3<2
-
nbsphinx>=0.9
-numpydoc>=1.1.0
jinja2>=3.0.2
sphinx_issues>=1.2.0
-gitpython>=3.1.2
-sphinx-autosummary-accessors>=0.1.2
-pydata-sphinx-theme>=0.4.3
-readthedocs-sphinx-ext
sphinx-rtd-theme
sphinx-book-theme
# sphinx-bootstrap-theme
+pydata-sphinx-theme>=0.4.3
+Sphinx
+numpydoc>=1.1.0
+readthedocs-sphinx-ext
+sphinx-autosummary-accessors>=0.1.2
+pydocstyle
sphinx-tabs
+sphinxext-rediraffe
+# sphinxext-opengraph
git+https://github.com/sphinx-contrib/googleanalytics
sphinx-copybutton
sphinx-design
-sphinxext-rediraffe
-xarray>=0.16.1,<2024.3
-pandas<3.0
-scipy>=1.5
-scikit-learn>=0.23.2
-dask>=2021.9.1
-distributed>=2.30.0
-# bottleneck>=1.3.2
-# toolz>=0.8.2
-erddapy>=0.7.2
-gsw>=3.4.0
+# pkgconfig
+# urllib3<2
-s3fs
-boto3
-decorator
+# gitpython>=3.1.2
-fsspec>=0.7.4 #, <2022.3.1
-aiohttp>=3.7.4
+# scikit-learn>=0.23.2
-matplotlib>=3.4.0
#cartopy>=0.18.0
-#seaborn>=0.11.0
#geos>=0.2
# cmocean
-zarr>=2.4.0
-netcdf4>=1.5.4
-cftime>=1.5.1
-cfgrib>=0.9.9.1
-tqdm>=4.50.2
diff --git a/docs/user-guide/working-with-argo-data/owc_workflow_eg.py b/docs/user-guide/working-with-argo-data/owc_workflow_eg.py
index 47f9dfda..e74bb0a0 100644
--- a/docs/user-guide/working-with-argo-data/owc_workflow_eg.py
+++ b/docs/user-guide/working-with-argo-data/owc_workflow_eg.py
@@ -1,4 +1,5 @@
-import os, shutil
+import os
+import shutil
from pathlib import Path
import pyowc as owc
diff --git a/docs/whats-new.rst b/docs/whats-new.rst
index 9d2665a0..4fb6404d 100644
--- a/docs/whats-new.rst
+++ b/docs/whats-new.rst
@@ -8,12 +8,12 @@ What's New
|pypi dwn| |conda dwn|
-Coming up next
---------------
+v0.1.16 (xx Aug. 2024)
+----------------------
**Features and front-end API**
-- **Support for AWS S3 index files**. This support is experimental and is primarily made available for benchmarking as part of the `ADMT working group on Argo cloud format activities <https://github.com/OneArgo/ADMT/issues/5>`_. The `ADMT working group discussion items are listed here <https://github.com/OneArgo/ADMT/discussions/categories/wg-on-best-format-to-serve-argo-data-from-the-cloud>`_. Both CORE and BGC index files are supported. The new :class:`ArgoIndex` not only support access to the AWS S3 index files but also implement improved performances for search methods on WMO and cycle numbers, using :class:`boto3.client.select_object_content` SQL queries. Indeed, the ``https`` and ``ftp`` default GDAC server index files are downloaded and loaded in memory before being searched. With ``s3``, index files can directly be queried on the server using SQL syntax; the full index is not necessarily downloaded. (:pr:`326`) by `G. Maze <http://www.github.com/gmaze>`_
+- **Support for AWS S3 index files**. This support is experimental and is primarily made available for benchmarking as part of the `ADMT working group on Argo cloud format activities <https://github.com/OneArgo/ADMT/issues/5>`_. The `ADMT working group discussion items are listed here <https://github.com/OneArgo/ADMT/discussions/categories/wg-on-best-format-to-serve-argo-data-from-the-cloud>`_. Both CORE and BGC index files are supported. The new :class:`ArgoIndex` not only support access to the AWS S3 index files but also implement improved performances for search methods on WMO and cycle numbers, using :class:`boto3.client.select_object_content` SQL queries. Indeed, the ``https`` and ``ftp`` default GDAC server index files are downloaded and loaded in memory before being searched. But with ``s3``, index files can directly be queried on the server using SQL syntax; the full index is not necessarily downloaded. (:pr:`326`) by `G. Maze <http://www.github.com/gmaze>`_
.. code-block:: python
@@ -35,10 +35,12 @@ Coming up next
**Internals**
-- Update Ifremer erddap server information. The Argo reference for DMQC (returned by the :class:`DataFetcher` fetcher with ``ds='ref'`` argument ) and Argo CTD-reference for DQMC (returned by the :class:`CTDRefDataFetcher` fetcher) now indicate the dataset version used. (:pr:`344`) by `G. Maze <http://www.github.com/gmaze>`_.
+- Drop support for Python 3.8, add support for Python 3.10. (:pr:`379`) by `G. Maze <http://www.github.com/gmaze>`_
- Update :class:`argopy.ArgoNVSReferenceTables` to handle new NVS server output format. (:pr:`378`) by `G. Maze <http://www.github.com/gmaze>`_.
+- Update Ifremer erddap server information. The Argo reference for DMQC (returned by the :class:`DataFetcher` fetcher with ``ds='ref'`` argument ) and Argo CTD-reference for DQMC (returned by the :class:`CTDRefDataFetcher` fetcher) now indicate the dataset version used. (:pr:`344`) by `G. Maze <http://www.github.com/gmaze>`_.
+
- Pin upper bound on xarray < 2024.3 to fix failing upstream tests because of ``AttributeError: 'ScipyArrayWrapper' object has no attribute 'oindex'``, `reported here <https://github.com/pydata/xarray/issues/8909>`_. (:pr:`326`) by `G. Maze <http://www.github.com/gmaze>`_
- Fix :class:`argopy.ArgoDocs` that was not working with new Archimer webpage design, :issue:`351`. (:pr:`352`) by `G. Maze <http://www.github.com/gmaze>`_.
@@ -55,7 +57,6 @@ Coming up next
- Drop support for erddapy < v0.8.0 (:pr:`344`) by `G. Maze <http://www.github.com/gmaze>`_.
-
v0.1.15 (12 Dec. 2023)
----------------------
@@ -179,7 +180,7 @@ v0.1.14 (29 Sep. 2023)
- New utility class :class:`utils.MonitoredThreadPoolExecutor` to handle parallelization with a multi-threading Pool that provide a notebook or terminal computation progress dashboard. This class is used by the httpstore open_mfdataset method for erddap requests.
-- New utilites to handle a collection of datasets: :func:`utils.drop_variables_not_in_all_datasets` will drop variables that are not in all datasets (the lowest common denominator) and :func:`utils.fill_variables_not_in_all_datasets` will add empty variables to dataset so that all the collection have the same data_vars and coords. These functions are used by stores to concat/merge a collection of datasets (chunks).
+- New utilities to handle a collection of datasets: :func:`utils.drop_variables_not_in_all_datasets` will drop variables that are not in all datasets (the lowest common denominator) and :func:`utils.fill_variables_not_in_all_datasets` will add empty variables to dataset so that all the collection have the same data_vars and coords. These functions are used by stores to concat/merge a collection of datasets (chunks).
- :func:`related.load_dict` now relies on :class:`ArgoNVSReferenceTables` instead of static pickle files.
@@ -294,7 +295,7 @@ v0.1.14rc2 (27 Jul. 2023)
- New utility class :class:`utils.MonitoredThreadPoolExecutor` to handle parallelization with a multi-threading Pool that provide a notebook or terminal computation progress dashboard. This class is used by the httpstore open_mfdataset method for erddap requests.
-- New utilites to handle a collection of datasets: :func:`utils.drop_variables_not_in_all_datasets` will drop variables that are not in all datasets (the lowest common denominator) and :func:`utils.fill_variables_not_in_all_datasets` will add empty variables to dataset so that all the collection have the same data_vars and coords. These functions are used by stores to concat/merge a collection of datasets (chunks).
+- New utilities to handle a collection of datasets: :func:`utils.drop_variables_not_in_all_datasets` will drop variables that are not in all datasets (the lowest common denominator) and :func:`utils.fill_variables_not_in_all_datasets` will add empty variables to dataset so that all the collection have the same data_vars and coords. These functions are used by stores to concat/merge a collection of datasets (chunks).
- :func:`related.load_dict` now relies on :class:`ArgoNVSReferenceTables` instead of static pickle files.
diff --git a/docs/why.rst b/docs/why.rst
index 315671bb..a24c7803 100644
--- a/docs/why.rst
+++ b/docs/why.rst
@@ -6,7 +6,7 @@ Why argopy ?
Surprisingly, the Argo community never provided its user base with a Python software to easily access and manipulate Argo measurements:
**argopy** aims to fill this gap.
-Despite, or because, its tremendous success in data management and in developping good practices and well calibrated procedures [ADMT]_, the Argo dataset is very complex: with thousands of different variables, tens of reference tables and a `user manual <http://dx.doi.org/10.13155/29825>`_ more than 100 pages long:
+Despite, or because, its tremendous success in data management and in developing good practices and well calibrated procedures [ADMT]_, the Argo dataset is very complex: with thousands of different variables, tens of reference tables and a `user manual <http://dx.doi.org/10.13155/29825>`_ more than 100 pages long:
**argopy** aims to help you navigate this complex realm.
For non-experts of the Argo dataset, it has become rather complicated to get access to Argo measurements.
diff --git a/readthedocs.yml b/readthedocs.yml
index 269de29c..dc94528c 100644
--- a/readthedocs.yml
+++ b/readthedocs.yml
@@ -12,7 +12,7 @@ build:
# image: latest
os: "ubuntu-22.04"
tools:
- python: "3.8"
+ python: "3.9"
python:
install:
diff --git a/setup.py b/setup.py
index 5187feae..4fb7aaa1 100644
--- a/setup.py
+++ b/setup.py
@@ -10,7 +10,7 @@
setuptools.setup(
name="argopy",
- version="0.1.15",
+ version="0.1.16",
author="argopy Developers",
author_email="gmaze@ifremer.fr",
description="A python library for Argo data beginners and experts",
@@ -22,7 +22,6 @@
package_data={"argopy": ["static/assets/*", "static/css/*"]},
install_requires=requirements,
classifiers=[
- "Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Topic :: Scientific/Engineering",