wip

docs/src/conf.py

@@ -173,7 +173,7 @@ def _dotv(version):
 # See https://numpydoc.readthedocs.io/en/latest/install.html#configuration
 # TREMTEST
 # numpydoc_use_plots = True  # ?
-numpydoc_show_class_members = False  # False stops lots of warnings
+numpydoc_show_class_members = False  # False stops lots of warnings: https://stackoverflow.com/questions/65198998/sphinx-warning-autosummary-stub-file-not-found-for-the-methods-of-the-class-c
 # numpydoc_show_inherited_class_members
 # numpydoc_class_members_toctree
 # numpydoc_citation_re

lib/iris/fileformats/netcdf/saver.py

@@ -2582,7 +2582,7 @@ def save(
     compute=True,
 ):
     """
-    Save cube(s) to a netCDF file, given the cube and the filename.
+    Save cube(s) to a netCDF file, given the cube and the filename. TREMTEST
 
     * Iris will write CF 1.7 compliant NetCDF files.
     * The attributes dictionaries on each cube in the saved cube list
@@ -2609,9 +2609,7 @@ def save(
             When saving to a dataset, ``compute`` **must** be ``False`` :
             See the ``compute`` parameter.
 
-    Kwargs:
-
-    * netcdf_format (string):
+    netcdf_format : string
         Underlying netCDF file format, one of 'NETCDF4', 'NETCDF4_CLASSIC',
         'NETCDF3_CLASSIC' or 'NETCDF3_64BIT'. Default is 'NETCDF4' format.
     local_keys : iterable of str
@@ -2644,7 +2642,7 @@ def save(
     chunksizes : tuple of int
         Used to manually specify the HDF5 chunksizes for each dimension of the
         variable. A detailed discussion of HDF chunking and I/O performance is
-        available here: https://www.unidata.ucar.edu/software/netcdf/documentation/NUG/netcdf_perf_chunking.html.
+        available here: TREMTEST
         Basically, you want the chunk size for each dimension to match as
         closely as possible the size of the data block that users will read
         from the file. `chunksizes` cannot be set if `contiguous=True`.
@@ -2656,15 +2654,15 @@ def save(
         computer with the opposite format as the one used to create the file,
         there may be some performance advantage to be gained by setting the
         endian-ness.
-    least_significant_digit : int)
+    least_significant_digit : int
         If `least_significant_digit` is specified, variable data will be
         truncated (quantized). In conjunction with `zlib=True` this produces
         'lossy', but significantly more efficient compression. For example, if
         `least_significant_digit=1`, data will be quantized using
         `numpy.around(scale*data)/scale`, where `scale = 2**bits`, and `bits`
         is determined so that a precision of 0.1 is retained (in this case
         `bits=4`). From
-        http://www.esrl.noaa.gov/psd/data/gridded/conventions/cdc_netcdf_standard.shtml:
+        TREMTEST:
         "least_significant_digit -- power of ten of the smallest decimal place
         in unpacked data that is a reliable value". Default is `None`, or no
         quantization, or 'lossless' compression.
@@ -2673,7 +2671,7 @@ def save(
         describes a numpy integer dtype (i.e. 'i2', 'short', 'u4') or a dict
         of packing parameters as described below or an iterable of such types,
         strings, or dicts. This provides support for netCDF data packing as
-        described in https://www.unidata.ucar.edu/software/netcdf/documentation/NUG/best_practices.html#bp_Packed-Data-Values
+        described in TREMTEST
         If this argument is a type (or type string), appropriate values of
         scale_factor and add_offset will be automatically calculated based
         on `cube.data` and possible masking. For more control, pass a dict with
@@ -2693,7 +2691,7 @@ def save(
         :class:`iris.cube.CubeList`, or a single element, and each element of
         this argument will be applied to each cube separately.
 
-    compute: bool:
+    compute: bool
         Default is ``True``, meaning complete the file immediately, and return ``None``.
 
         When ``False``, create the output file but don't write any lazy array content to
@@ -2716,11 +2714,12 @@ def save(
             must (re-)open the dataset for writing, which will fail if the file is
             still open for writing by the caller.
 
-    Returns:
-        result (None, or dask.delayed.Delayed):
-            If `compute=True`, returns `None`.
-            Otherwise returns a :class:`dask.delayed.Delayed`, which implements delayed
-            writing to fill in the variables data.
+    Returns
+    -------
+    result: None or dask.delayed.Delayed
+        If `compute=True`, returns `None`.
+        Otherwise returns a :class:`dask.delayed.Delayed`, which implements delayed
+        writing to fill in the variables data.
 
     .. note::
 
@@ -2734,9 +2733,7 @@ def save(
     `chunksizes` and `endian` keywords are silently ignored for netCDF 3
     files that do not use HDF5.
 
-    See Also
-    --------
-    NetCDF Context manager (:class:`~Saver`).
+
 
     """
     from iris.cube import Cube, CubeList