Refer to .DATA file from py code

res2df/common.py

@@ -630,7 +630,7 @@ def generic_deck_table(
     renamer: Optional[Dict[str, str]] = None,
     drop_trailing_columns: bool = True,
 ) -> str:
-    """Construct string contents of a .DATA file table.
+    """Construct string contents of a :term:`.DATA file` table.
 
     This function will *not* add a final slash after all rows, as
     this is keyword dependent. Some keywords require it, some keywords

res2df/compdat.py

@@ -82,7 +82,7 @@ def deck2dfs(
 
     Args:
         deck: A deck representing the schedule
-            Does not have to be a full .DATA file, an include file is sufficient
+            Does not have to be a full :term:`.DATA file`, an include file is sufficient
         start_date: The default date to use for
             events where the DATE or START keyword is not found in advance.
             Default: None
@@ -950,7 +950,7 @@ def fill_parser(parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
     Arguments:
         parser: parser to fill with arguments
     """
-    parser.add_argument("DATAFILE", help="Name of .DATA file.")
+    parser.add_argument("DATAFILE", help="Name of :term:`.DATA file`.")
     parser.add_argument(
         "-o",
         "--output",

res2df/equil.py

@@ -1,5 +1,5 @@
 """
-Extract EQUIL from a .DATA file as Pandas DataFrame
+Extract EQUIL from a :term:`.DATA file` as Pandas DataFrame
 """
 
 import argparse
@@ -92,7 +92,7 @@ def df(
     are possibly already removed by the OPM parser in resdatafiles.str2deck().
 
     Arguments:
-        deck: .DATA file or string with deck. If
+        deck: :term:`.DATA file` or string with deck. If
            not string, EQLDIMS must be present in the deck.
         keywords: Requested keywords for which to extract data.
         ntequl: If not None, should state the NTEQUL in EQLDIMS. If

res2df/faults.py

@@ -36,7 +36,7 @@ def df(deck: Union[ResdataFiles, "opm.libopmcommon_python.Deck"]) -> pd.DataFram
     All data for the keyword FAULTS will be returned.
 
     Args:
-        deck: .DATA file
+        deck: :term:`.DATA file`
     """
     if isinstance(deck, ResdataFiles):
         deck = deck.get_deck()

res2df/fipreports.py

@@ -109,7 +109,7 @@ def df(prtfile: Union[str, ResdataFiles], fipname: str = "FIPNUM") -> pd.DataFra
         prtfile: filename (PRT) or an ResdataFiles object
         fipname: The name of the regport regions, FIPNUM, FIPZON or whatever
             Max length of the string is 8, the first three characters must be FIP,
-            and the next 3 characters must be unique for a given .DATA file.
+            and the next 3 characters must be unique for a given :term:`.DATA file`.
     """
     if isinstance(prtfile, ResdataFiles):
         prtfile = prtfile.get_prtfilename()

res2df/grid.py

@@ -626,7 +626,7 @@ def df2res(
 ) -> str:
     """
     Write an include file with grid data keyword, like PERMX, PORO,
-    FIPNUM etc, for the GRID section of the .DATA file.
+    FIPNUM etc, for the GRID section of the :term:`.DATA file`.
 
     Output (returned as string and optionally written to file) will then
     contain f.ex::

res2df/gruptree.py

@@ -1,4 +1,4 @@
-"""Extract GRUPTREE information from a .DATA file"""
+"""Extract GRUPTREE information from a :term:`.DATA file`"""
 
 import argparse
 import collections

res2df/inferdims.py

@@ -31,7 +31,7 @@ def guess_dim(deckstring: str, dimkeyword: str, dimitem: int = 0) -> int:
     stricter mode, to detect the correct table dimensionality
 
     Arguments:
-        deck: String containing a .DATA file or only a few resdata keywords
+        deck: String containing a :term:`.DATA file` or only a few resdata keywords
         dimkeyword: Either TABDIMS or EQLDIMS
         dimitem: The element number in TABDIMS/EQLDIMS to modify
     Returns:

res2df/pvt.py

@@ -1,7 +1,7 @@
 """
-Extract the PVT data from a .DATA file as Pandas Dataframes
+Extract the PVT data from a :term:`.DATA file` as Pandas Dataframes
 
-Data can be extracted from a full .DATA file or from individual files.
+Data can be extracted from a full :term:`.DATA file` or from individual files.
 """
 
 import argparse
@@ -239,7 +239,7 @@ def df(
 
 
 def fill_parser(parser: argparse.ArgumentParser) -> argparse.ArgumentParser:
-    """Set up sys.argv parsers for parsing .DATA file or
+    """Set up sys.argv parsers for parsing :term:`.DATA file` or
     include files into dataframes
 
     Arguments:

res2df/res2csv.py

@@ -24,7 +24,7 @@
 CATEGORY: str = "utility.eclipse"
 EXAMPLES: str = """
 
-Outputting the EQUIL data from a .DATA file. This is implicitly 
+Outputting the EQUIL data from a :term:`.DATA file`. This is implicitly 
 supplied in ERT configs::
 
    FORWARD_MODEL res2csv(<SUBCOMMAND>=equil, <OUTPUT>=equil.csv)
@@ -130,7 +130,7 @@ def get_parser() -> argparse.ArgumentParser:
         "pvt",
         help="Extract PVT data",
         description=(
-            "Extract data for the PVT keywords in a .DATA file "
+            "Extract data for the PVT keywords in a :term:`.DATA file` "
             "and merge all data into a single dataframe. "
             "Supported keywords are PVTO, PVDO, PVTG, PVDG, PVTW, "
             "ROCK and DENSITY. Gas phase pressure and oil phase "

res2df/satfunc.py

@@ -1,8 +1,8 @@
 """
 Extract saturation function data (SWOF, SGOF, SWFN, etc.)
-from a .DATA file as Pandas DataFrame.
+from a :term:`.DATA file` as Pandas DataFrame.
 
-Data can be extracted from a full .DATA file (`*.DATA`)
+Data can be extracted from a full :term:`.DATA file` (`*.DATA`)
 or from individual files.
 
 Note that when parsing from individual files, it is
@@ -129,7 +129,8 @@ def df(
 
 def interpolate_defaults(dframe: pd.DataFrame) -> pd.DataFrame:
     """Interpolate NaN's linearly in saturation.
-    Saturation function tables in .DATA files can have certain values defaulted.
+    Saturation function tables in :term:`.DATA files <.DATA file>`
+    can have certain values defaulted.
     When parsed by common.res2df, these values are returned as np.nan.
     The incoming dataframe must be associated to one keyword only, but
     can consist of multiple SATNUMs.

res2df/summary.py

@@ -321,8 +321,8 @@ def df(
     is always named "DATE".
 
     Arguments:
-        resdatafiles: ResdataFiles object representing a .DATA file. Alternatively
-           an Summary object.
+        resdatafiles: ResdataFiles object representing a :term:`.DATA file`.
+            Alternatively a Summary object.
         time_index: string indicating a resampling frequency,
            'yearly', 'monthly', 'daily', 'last' or 'raw', the latter will
            return the simulated report steps (also default).

res2df/vfp/_vfp.py

@@ -1,6 +1,6 @@
 """Extract the VFPPROD/VFPINJ data from an Eclipse (input) deck as Pandas Dataframes
 
-Data can be extracted from a full .DATA file or from individual files. Supports
+Data can be extracted from a full :term:`.DATA file` or from individual files. Supports
 output both in csv format as a pandas DataFrame or in pyarrow and pyarrow.table
 """
 
@@ -45,7 +45,7 @@ def basic_data(
     BASIC_DATA_KEYS in _vfpprod and _vfpinj.
 
     Args:
-        deck:           .DATA file or string with deck
+        deck:           :term:`.DATA file` or string with deck
         keyword:        VFP table type, i.e. 'VFPPROD' or 'VFPINJ'
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
@@ -250,7 +250,7 @@ def dfs(
     Data for the keyword VFPPROD or VFPINJ will be returned as separate item in list
 
     Args:
-        deck:           .DATA file or string with deck
+        deck:           :term:`.DATA file` or string with deck
         keyword:        VFP table type, i.e. 'VFPPROD' or 'VFPINJ'
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
@@ -293,7 +293,7 @@ def pyarrow_tables(
     Data for the keyword VFPPROD or VFPINJ will be returned as separate item in list
 
     Args:
-        deck:           .DATA file or string with deck
+        deck:           :term:`.DATA file` or string with deck
         keyword:        VFP table type, i.e. 'VFPPROD' or 'VFPINJ'
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
@@ -418,7 +418,7 @@ def df(
     All data for the keywords VFPPROD/VFPINJ will be returned.
 
     Args:
-        deck:           .DATA file or string wit deck
+        deck:           :term:`.DATA file` or string wit deck
         keyword:        VFP table type, i.e. 'VFPPROD' or 'VFPINJ'
         vfpnumbers_str: str with list of VFP table numbers to extract
     """

res2df/vfp/_vfpcommon.py

@@ -2,7 +2,7 @@
 deck to extract the VFPPROD/VFPINJ data from an Eclipse (input) deck as Pandas
 Dataframes
 
-Data can be extracted from a full .DATA file or from individual files. Supports
+Data can be extracted from a full :term:`.DATA file` or from individual files. Supports
 output both in csv format as a pandas DataFrame or in pyarrow and pyarrow.table
 """
 

res2df/vfp/_vfpinj.py

@@ -3,7 +3,7 @@
 basic_data (dictionary with basic data types), df (pandas DataFrame) or
 pyarrow_tables (pyarrow.Tables).
 
-Data can be extracted from a full .DATA file or from individual files.
+Data can be extracted from a full :term:`.DATA file` or from individual files.
 Supports output both in csv format as a pandas DataFrame or in pyarrow
 a pyarrow.Table. Also functionality to write pandas DataFrame and
 pyarrow.Table to file as Eclipse .Ecl format
@@ -74,7 +74,7 @@ def basic_data(
     Empty string returned if vfp table number does not match any number in list
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds
     """
@@ -473,12 +473,12 @@ def df(
     keyword: "opm.libopmcommon_python.DeckKeyword",
     vfpnumbers_str: Optional[str] = None,
 ) -> Union[pd.DataFrame, None]:
-    """Return a dataframes of a single VFPINJ table from a .DATA file
+    """Return a dataframes of a single VFPINJ table from a :term:`.DATA file`
 
     Data from the VFPINJ keyword are stacked into a Pandas Dataframe
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
     """
@@ -510,11 +510,11 @@ def pyarrow(
     keyword: "opm.libopmcommon_python.DeckKeyword",
     vfpnumbers_str: Optional[str] = None,
 ) -> Union[pa.Table, None]:
-    """Return a pyarrow Table of a single VFPINJ table from a .DATA file
+    """Return a pyarrow Table of a single VFPINJ table from a :term:`.DATA file`
        If no VFPINJ table found, return None
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
     """

res2df/vfp/_vfpprod.py

@@ -3,7 +3,7 @@
 basic_data (dictionary with basic data types), df (pandas DataFrame) or
 pyarrow_tables (pyarrow.Tables).
 
-Data can be extracted from a full .DATA file or from individual files.
+Data can be extracted from a full :term:`.DATA file` or from individual files.
 Supports output both in csv format as a pandas DataFrame or in pyarrow
 as pyarrow.Table. Also functionality to write pandas DataFrame and
 pyarrow.Table to file as Eclipse .Ecl format.
@@ -86,7 +86,7 @@ def basic_data(
     Empty string returned if vfp table number does not match any number in list
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds
     """
@@ -720,10 +720,10 @@ def df(
     vfpnumbers_str: Optional[str] = None,
 ) -> Union[pd.DataFrame, None]:
     """Return a dataframe or pyarrow Table of a single VFPPROD table
-    from a .DATA file.
+    from a :term:`.DATA file`.
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
     """
@@ -764,11 +764,11 @@ def pyarrow(
     keyword: "opm.libopmcommon_python.DeckKeyword",
     vfpnumbers_str: Optional[str] = None,
 ) -> Union[pa.Table, None]:
-    """Return a pyarrow Table of a single VFPPROD table from a .DATA file.
+    """Return a pyarrow Table of a single VFPPROD table from a :term:`.DATA file`.
        If no VFPPROD curve found, return None
 
     Args:
-        keyword:        .DATA file keyword
+        keyword:        :term:`.DATA file` keyword
         vfpnumbers_str: String with list of vfp table numbers to extract.
                         Syntax "[0,1,8:11]" corresponds to [0,1,8,9,10,11].
     """

res2df/wcon.py

@@ -1,4 +1,4 @@
-"""Extract WCON* from a .DATA file"""
+"""Extract WCON* from a :term:`.DATA file`"""
 
 import argparse
 import datetime

res2df/wellcompletiondata.py

@@ -91,7 +91,7 @@ def df(
 
 
 def _get_unit_system(resdatafiles: ResdataFiles) -> UnitSystem:
-    """Returns the unit system of a .DATA file. The options are \
+    """Returns the unit system of a :term:`.DATA file`. The options are \
     METRIC, FIELD, LAB and PVT-M.
 
     If none of these are found, the function returns METRIC which is the

tests/test_gruptree.py

@@ -427,7 +427,7 @@ def test_emptytree_strdeck():
 
 
 def test_emptytree_commandlinetool(tmp_path, mocker, caplog):
-    """Test the command line tool on a .DATA file which is empty"""
+    """Test the command line tool on a :term:`.DATA file` which is empty"""
     os.chdir(tmp_path)
     Path("EMPTY.DATA").write_text("", encoding="utf8")
     mocker.patch("sys.argv", ["res2csv", "gruptree", "--prettyprint", "EMPTY.DATA"])

tests/test_satfunc.py

@@ -27,7 +27,7 @@
 
 
 def test_deck_to_satfunc_dframe():
-    """Test that dataframes can be produced from a full .DATA file (the
+    """Test that dataframes can be produced from a full :term:`.DATA file` (the
     example Reek case)"""
     resdatafiles = ResdataFiles(REEK)
     satdf = satfunc.df(resdatafiles.get_deck())

tests/test_welopen.py

@@ -1481,7 +1481,9 @@ def test_welopen_df():
     ],
 )
 def test_welopen_complump(test_input, expected):
-    """Test the welopen_complump functionality through .DATA files"""
+    """Test the welopen_complump functionality through
+       :term:`.DATA files <.DATA file>`
+    """
     deck = ResdataFiles.str2deck(test_input)
     dfs = compdat.deck2dfs(deck)
     pd.testing.assert_frame_equal(dfs["COMPDAT"][expected.columns], expected)