Fetching Argo data¶
To access Argo data, you need to use a data fetcher. You can import and instantiate the default argopy data fetcher like this:
In [1]: from argopy import DataFetcher as ArgoDataFetcher
In [2]: argo_loader = ArgoDataFetcher()
In [3]: argo_loader
Out[3]:
<datafetcher.erddap> 'No access point initialised'
Available access points: float, profile, region
Backend: erddap
User mode: standard
Dataset: phy
Then, you can request data for a specific space/time domain, for a given float or for a given vertical profile.
If you fetch a lot of data, you may want to look at the Performances section.
For a space/time domain¶
Use the fetcher access point argopy.DataFetcher.region() to specify a domain and chain with the argopy.DataFetcher.to_xarray() to get the data returned as xarray.Dataset.
For instance, to retrieve data from 75W to 45W, 20N to 30N, 0db to 10db and from January to May 2011:
In [4]: ds = argo_loader.region([-75, -45, 20, 30, 0, 10, '2011-01-01', '2011-06']).to_xarray()
---------------------------------------------------------------------------
ServerDisconnectedError Traceback (most recent call last)
<ipython-input-4-16f642f11712> in <module>
----> 1 ds = argo_loader.region([-75, -45, 20, 30, 0, 10, '2011-01-01', '2011-06']).to_xarray()
~/checkouts/readthedocs.org/user_builds/argopy/checkouts/v0.1.8/argopy/fetchers.py in to_xarray(self, **kwargs)
334 % ",".join(self.Fetchers.keys())
335 )
--> 336 xds = self.fetcher.to_xarray(**kwargs)
337 xds = self.postproccessor(xds)
338 return xds
~/checkouts/readthedocs.org/user_builds/argopy/checkouts/v0.1.8/argopy/data_fetchers/erddap_data.py in to_xarray(self, errors)
417 if not self.parallel:
418 if len(self.uri) == 1:
--> 419 ds = self.fs.open_dataset(self.uri[0])
420 else:
421 ds = self.fs.open_mfdataset(
~/checkouts/readthedocs.org/user_builds/argopy/checkouts/v0.1.8/argopy/stores/filesystems.py in open_dataset(self, url, *args, **kwargs)
390 # with self.fs.open(url) as of:
391 # ds = xr.open_dataset(of, *args, **kwargs)
--> 392 data = self.fs.cat_file(url)
393 ds = xr.open_dataset(data, *args, **kwargs)
394 if "source" not in ds.encoding:
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/fsspec/asyn.py in wrapper(*args, **kwargs)
116 def wrapper(*args, **kwargs):
117 self = obj or args[0]
--> 118 return maybe_sync(func, self, *args, **kwargs)
119
120 return wrapper
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/fsspec/asyn.py in maybe_sync(func, self, *args, **kwargs)
95 if inspect.iscoroutinefunction(func):
96 # run the awaitable on the loop
---> 97 return sync(loop, func, *args, **kwargs)
98 else:
99 # just call the blocking function
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/fsspec/asyn.py in sync(loop, func, callback_timeout, *args, **kwargs)
66 if error[0]:
67 typ, exc, tb = error[0]
---> 68 raise exc.with_traceback(tb)
69 else:
70 return result[0]
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/fsspec/asyn.py in f()
50 if callback_timeout is not None:
51 future = asyncio.wait_for(future, callback_timeout)
---> 52 result[0] = await future
53 except Exception:
54 error[0] = sys.exc_info()
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/fsspec/implementations/http.py in _cat_file(self, url, **kwargs)
150 kw.update(kwargs)
151 logger.debug(url)
--> 152 async with self.session.get(url, **kw) as r:
153 if r.status == 404:
154 raise FileNotFoundError(url)
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/aiohttp/client.py in __aenter__(self)
1138
1139 async def __aenter__(self) -> _RetType:
-> 1140 self._resp = await self._coro
1141 return self._resp
1142
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/aiohttp/client.py in _request(self, method, str_or_url, params, data, json, cookies, headers, skip_auto_headers, auth, allow_redirects, max_redirects, compress, chunked, expect100, raise_for_status, read_until_eof, proxy, proxy_auth, timeout, verify_ssl, fingerprint, ssl_context, ssl, proxy_headers, trace_request_ctx, read_bufsize)
557 resp = await req.send(conn)
558 try:
--> 559 await resp.start(conn)
560 except BaseException:
561 resp.close()
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/aiohttp/client_reqrep.py in start(self, connection)
896 try:
897 protocol = self._protocol
--> 898 message, payload = await protocol.read() # type: ignore[union-attr]
899 except http.HttpProcessingError as exc:
900 raise ClientResponseError(
~/checkouts/readthedocs.org/user_builds/argopy/envs/v0.1.8/lib/python3.8/site-packages/aiohttp/streams.py in read(self)
612 self._waiter = self._loop.create_future()
613 try:
--> 614 await self._waiter
615 except (asyncio.CancelledError, asyncio.TimeoutError):
616 self._waiter = None
ServerDisconnectedError: Server disconnected
In [5]: ds
Out[5]:
<xarray.Dataset>
Dimensions: (N_POINTS: 107)
Coordinates:
* N_POINTS (N_POINTS) int64 0 1 2 3 4 5 ... 102 103 104 105 106
LATITUDE (N_POINTS) float64 63.68 63.68 63.68 ... 63.68 63.68
LONGITUDE (N_POINTS) float64 -28.81 -28.81 ... -28.81 -28.81
TIME (N_POINTS) datetime64[ns] 2018-10-19T23:52:00 ... ...
Data variables: (12/13)
CONFIG_MISSION_NUMBER (N_POINTS) int64 2 2 2 2 2 2 2 2 ... 2 2 2 2 2 2 2 2
CYCLE_NUMBER (N_POINTS) int64 12 12 12 12 12 12 ... 12 12 12 12 12
DATA_MODE (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'R' 'R' 'R' 'R'
DIRECTION (N_POINTS) <U1 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
PLATFORM_NUMBER (N_POINTS) int64 6902755 6902755 ... 6902755 6902755
POSITION_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
... ...
PRES_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
PSAL (N_POINTS) float64 34.87 34.87 34.87 ... 34.94 34.94
PSAL_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TEMP (N_POINTS) float64 7.598 7.599 7.602 ... 3.549 3.536
TEMP_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TIME_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
Attributes:
DATA_ID: ARGO
DOI: http://doi.org/10.17882/42182
Fetched_from: https://www.ifremer.fr/erddap
Fetched_by: docs
Fetched_date: 2021/11/02
Fetched_constraints: phy;WMO6902755_CYC12
Fetched_uri: ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...
history: Variables filtered according to DATA_MODE; Variable...
Note that:
the constraints on time is not mandatory: if not specified, the fetcher will return all data available in this region.
the last time bound is exclusive: that’s why here we specify June to retrieve data collected in May.
For one or more floats¶
If you know the Argo float unique identifier number called a WMO number you can use the fetcher access point argopy.DataFetcher.float() to specify the float WMO platform number and chain with the argopy.DataFetcher.to_xarray() to get the data returned as xarray.Dataset.
For instance, to retrieve data for float WMO 6902746:
In [6]: ds = argo_loader.float(6902746).to_xarray()
In [7]: ds
Out[7]:
<xarray.Dataset>
Dimensions: (N_POINTS: 9039)
Coordinates:
* N_POINTS (N_POINTS) int64 0 1 2 3 4 ... 9035 9036 9037 9038
LATITUDE (N_POINTS) float64 20.08 20.08 20.08 ... 16.3 16.3
LONGITUDE (N_POINTS) float64 -60.17 -60.17 ... -62.64 -62.64
TIME (N_POINTS) datetime64[ns] 2017-07-06T14:49:00 ... ...
Data variables: (12/13)
CONFIG_MISSION_NUMBER (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 3 3 3 3 3 3 3 3
CYCLE_NUMBER (N_POINTS) int64 1 1 1 1 1 1 1 ... 84 84 84 84 84 84
DATA_MODE (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'D' 'D' 'D' 'D'
DIRECTION (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'
PLATFORM_NUMBER (N_POINTS) int64 6902746 6902746 ... 6902746 6902746
POSITION_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
... ...
PRES_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
PSAL (N_POINTS) float64 36.06 36.06 36.06 ... 34.98 34.98
PSAL_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 2 2 2 2 2 2 2 2
TEMP (N_POINTS) float64 28.04 28.03 28.02 ... 4.281 4.277
TEMP_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TIME_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
Attributes:
DATA_ID: ARGO
DOI: http://doi.org/10.17882/42182
Fetched_from: https://www.ifremer.fr/erddap
Fetched_by: docs
Fetched_date: 2021/11/02
Fetched_constraints: phy;WMO6902746
Fetched_uri: ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...
history: Variables filtered according to DATA_MODE; Variable...
To fetch data for a collection of floats, input them in a list:
In [8]: ds = argo_loader.float([6902746, 6902755]).to_xarray()
In [9]: ds
Out[9]:
<xarray.Dataset>
Dimensions: (N_POINTS: 22150)
Coordinates:
* N_POINTS (N_POINTS) int64 0 1 2 3 ... 22146 22147 22148 22149
LATITUDE (N_POINTS) float64 20.08 20.08 20.08 ... 43.91 43.91
LONGITUDE (N_POINTS) float64 -60.17 -60.17 ... -36.96 -36.96
TIME (N_POINTS) datetime64[ns] 2017-07-06T14:49:00 ... ...
Data variables: (12/13)
CONFIG_MISSION_NUMBER (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 2 2 2 2 2 2 2 2
CYCLE_NUMBER (N_POINTS) int64 1 1 1 1 1 1 ... 122 122 122 122 122
DATA_MODE (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'R' 'R' 'R' 'R'
DIRECTION (N_POINTS) <U1 'D' 'D' 'D' 'D' ... 'A' 'A' 'A' 'A'
PLATFORM_NUMBER (N_POINTS) int64 6902746 6902746 ... 6902755 6902755
POSITION_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
... ...
PRES_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
PSAL (N_POINTS) float64 36.06 36.06 36.06 ... 34.93 34.93
PSAL_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TEMP (N_POINTS) float64 28.04 28.03 28.02 ... 3.625 3.616
TEMP_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TIME_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
Attributes:
DATA_ID: ARGO
DOI: http://doi.org/10.17882/42182
Fetched_from: https://www.ifremer.fr/erddap
Fetched_by: docs
Fetched_date: 2021/11/02
Fetched_constraints: phy;WMO6902746;WMO6902755
Fetched_uri: ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...
history: Variables filtered according to DATA_MODE; Variable...
For one or more profiles¶
Use the fetcher access point argopy.DataFetcher.profile() to specify the float WMO platform number and the profile cycle number to retrieve profiles for, then chain with the argopy.DataFetcher.to_xarray() to get the data returned as xarray.Dataset.
For instance, to retrieve data for the 12th profile of float WMO 6902755:
In [10]: ds = argo_loader.profile(6902755, 12).to_xarray()
In [11]: ds
Out[11]:
<xarray.Dataset>
Dimensions: (N_POINTS: 107)
Coordinates:
* N_POINTS (N_POINTS) int64 0 1 2 3 4 5 ... 102 103 104 105 106
LATITUDE (N_POINTS) float64 63.68 63.68 63.68 ... 63.68 63.68
LONGITUDE (N_POINTS) float64 -28.81 -28.81 ... -28.81 -28.81
TIME (N_POINTS) datetime64[ns] 2018-10-19T23:52:00 ... ...
Data variables: (12/13)
CONFIG_MISSION_NUMBER (N_POINTS) int64 2 2 2 2 2 2 2 2 ... 2 2 2 2 2 2 2 2
CYCLE_NUMBER (N_POINTS) int64 12 12 12 12 12 12 ... 12 12 12 12 12
DATA_MODE (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'R' 'R' 'R' 'R'
DIRECTION (N_POINTS) <U1 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
PLATFORM_NUMBER (N_POINTS) int64 6902755 6902755 ... 6902755 6902755
POSITION_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
... ...
PRES_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
PSAL (N_POINTS) float64 34.87 34.87 34.87 ... 34.94 34.94
PSAL_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TEMP (N_POINTS) float64 7.598 7.599 7.602 ... 3.549 3.536
TEMP_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TIME_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
Attributes:
DATA_ID: ARGO
DOI: http://doi.org/10.17882/42182
Fetched_from: https://www.ifremer.fr/erddap
Fetched_by: docs
Fetched_date: 2021/11/02
Fetched_constraints: phy;WMO6902755_CYC12
Fetched_uri: ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...
history: Variables filtered according to DATA_MODE; Variable...
To fetch data for more than one profile, input them in a list:
In [12]: ds = argo_loader.profile(6902755, [3, 12]).to_xarray()
In [13]: ds
Out[13]:
<xarray.Dataset>
Dimensions: (N_POINTS: 215)
Coordinates:
* N_POINTS (N_POINTS) int64 0 1 2 3 4 5 ... 210 211 212 213 214
LATITUDE (N_POINTS) float64 59.72 59.72 59.72 ... 63.68 63.68
LONGITUDE (N_POINTS) float64 -31.24 -31.24 ... -28.81 -28.81
TIME (N_POINTS) datetime64[ns] 2018-07-22T00:03:00 ... ...
Data variables: (12/13)
CONFIG_MISSION_NUMBER (N_POINTS) int64 2 2 2 2 2 2 2 2 ... 2 2 2 2 2 2 2 2
CYCLE_NUMBER (N_POINTS) int64 3 3 3 3 3 3 3 ... 12 12 12 12 12 12
DATA_MODE (N_POINTS) <U1 'R' 'R' 'R' 'R' ... 'R' 'R' 'R' 'R'
DIRECTION (N_POINTS) <U1 'A' 'A' 'A' 'A' ... 'A' 'A' 'A' 'A'
PLATFORM_NUMBER (N_POINTS) int64 6902755 6902755 ... 6902755 6902755
POSITION_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
... ...
PRES_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
PSAL (N_POINTS) float64 34.76 34.76 34.76 ... 34.94 34.94
PSAL_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TEMP (N_POINTS) float64 8.742 8.743 8.744 ... 3.549 3.536
TEMP_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
TIME_QC (N_POINTS) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1
Attributes:
DATA_ID: ARGO
DOI: http://doi.org/10.17882/42182
Fetched_from: https://www.ifremer.fr/erddap
Fetched_by: docs
Fetched_date: 2021/11/02
Fetched_constraints: phy;WMO6902755_CYC3_CYC12
Fetched_uri: ['https://www.ifremer.fr/erddap/tabledap/ArgoFloats...
history: Variables filtered according to DATA_MODE; Variable...