update flake, black and isort to set line length limit to 79

.flake8

@@ -5,7 +5,7 @@ exclude =
     build,
     dist,
     doc/source/conf.py
-max-line-length = 115
+max-line-length = 79
 # Ignore some style 'errors' produced while formatting by 'black'
 # https://black.readthedocs.io/en/stable/guides/using_black_with_other_tools.html#labels-why-pycodestyle-warnings
 extend-ignore = E203

.isort.cfg

@@ -1,4 +1,4 @@
 [settings]
-line_length = 115
+line_length = 79
 multi_line_output = 3
 include_trailing_comma = True

doc/source/conf.py

@@ -221,7 +221,13 @@
 # (source start file, target name, title,
 # author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    ("index", "diffpy.utils.tex", "diffpy.utils Documentation", ab_authors, "manual"),
+    (
+        "index",
+        "diffpy.utils.tex",
+        "diffpy.utils Documentation",
+        ab_authors,
+        "manual",
+    ),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of
@@ -249,7 +255,9 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [("index", "diffpy.utils", "diffpy.utils Documentation", ab_authors, 1)]
+man_pages = [
+    ("index", "diffpy.utils", "diffpy.utils Documentation", ab_authors, 1)
+]
 
 # If true, show URL addresses after external links.
 # man_show_urls = False

pyproject.toml

@@ -57,7 +57,7 @@ ignore-words = ".codespell/ignore_words.txt"
 skip = "*.cif,*.dat"
 
 [tool.black]
-line-length = 115
+line-length = 79
 include = '\.pyi?$'
 exclude = '''
 /(

src/diffpy/utils/parsers/custom_exceptions.py

@@ -51,5 +51,7 @@ class ImproperSizeError(Exception):
 
     def __init__(self, bad_object, message=None):
         if message is None:
-            self.message = f"The size of {bad_object} is different than expected."
+            self.message = (
+                f"The size of {bad_object} is different than expected."
+            )
         super().__init__(self.message)

src/diffpy/utils/parsers/loaddata.py

@@ -20,56 +20,67 @@
 from diffpy.utils import validators
 
 
-def loadData(filename, minrows=10, headers=False, hdel="=", hignore=None, **kwargs):
+def loadData(
+    filename, minrows=10, headers=False, hdel="=", hignore=None, **kwargs
+):
     """Find and load data from a text file.
 
-    The data block is identified as the first matrix block of at least minrows rows and constant number of columns.
-    This seems to work for most of the datafiles including those generated by diffpy programs.
+    The data block is identified as the first matrix block of at least
+    minrows rows and constant number of columns. This seems to work for most
+    of the datafiles including those generated by diffpy programs.
 
     Parameters
     ----------
     filename
         Name of the file we want to load data from.
     minrows: int
-        Minimum number of rows in the first data block. All rows must have the same number of floating
-        point values.
+        Minimum number of rows in the first data block. All rows must have
+        the same number of floating point values.
     headers: bool
-        when False (default), the function returns a numpy array of the data in the data block.
-        When True, the function instead returns a dictionary of parameters and their corresponding
-        values parsed from header (information prior the data block). See hdel and hignore for options
-        to help with parsing header information.
+        when False (default), the function returns a numpy array of the data
+        in the data block. When True, the function instead returns a
+        dictionary of parameters and their corresponding values parsed from
+        header (information prior the data block). See hdel and hignore for
+        options to help with parsing header information.
     hdel: str
-        (Only used when headers enabled.) Delimiter for parsing header information (default '='). e.g. using
-        default hdel, the line 'parameter = p_value' is put into the dictionary as {parameter: p_value}.
+        (Only used when headers enabled.) Delimiter for parsing header
+        information (default '='). e.g. using default hdel, the line '
+        parameter = p_value' is put into the dictionary as
+        {parameter: p_value}.
     hignore: list
-        (Only used when headers enabled.) Ignore header rows beginning with any elements in hignore.
-        e.g. hignore=['# ', '['] causes the following lines to be skipped: '# qmax=10', '[defaults]'.
+        (Only used when headers enabled.) Ignore header rows beginning with
+        any elements in hignore. e.g. hignore=['# ', '['] causes the
+        following lines to be skipped: '# qmax=10', '[defaults]'.
     kwargs:
-        Keyword arguments that are passed to numpy.loadtxt including the following arguments below. (See
-        numpy.loadtxt for more details.) Only pass kwargs used by numpy.loadtxt.
+        Keyword arguments that are passed to numpy.loadtxt including the
+        following arguments below. (See numpy.loadtxt for more details.) Only
+        pass kwargs used by numpy.loadtxt.
 
     Useful kwargs
     =============
     comments: str, sequence of str
-        The characters or list of characters used to indicate the start of a comment (default '#').
-        Comment lines are ignored.
+        The characters or list of characters used to indicate the start of a
+        comment (default '#'). Comment lines are ignored.
     delimiter: str
-        Delimiter for the data in the block (default use whitespace). For comma-separated data blocks,
-        set delimiter to ','.
+        Delimiter for the data in the block (default use whitespace). For
+        comma-separated data blocks, set delimiter to ','.
     unpack: bool
-        Return data as a sequence of columns that allows tuple unpacking such as x, y =
-        loadData(FILENAME, unpack=True). Note transposing the loaded array as loadData(FILENAME).T has the same
-        effect.
+        Return data as a sequence of columns that allows tuple unpacking such
+        as x, y = loadData(FILENAME, unpack=True). Note transposing the
+        loaded array as loadData(FILENAME).T has the same effect.
     usecols:
-        Zero-based index of columns to be loaded, by default use all detected columns. The reading skips
-        data blocks that do not have the usecols-specified columns.
+        Zero-based index of columns to be loaded, by default use all detected
+        columns. The reading skips data blocks that do not have the usecols-
+        specified columns.
 
     Returns
     -------
     data_block: ndarray
-        A numpy array containing the found data block. (This is not returned if headers is enabled.)
+        A numpy array containing the found data block. (This is not returned
+        if headers is enabled.)
     hdata: dict
-        If headers are enabled, return a dictionary of parameters read from the header.
+        If headers are enabled, return a dictionary of parameters read from
+        the header.
     """
     from numpy import array, loadtxt
 
@@ -105,7 +116,12 @@ def countcolumnsvalues(line):
 
     # Check if file exists before trying to open
     if not os.path.exists(filename):
-        raise IOError(f"File {filename} cannot be found. Please rerun the program specifying a valid filename.")
+        raise IOError(
+            (
+                f"File {filename} cannot be found. "
+                "Please rerun the program specifying a valid filename."
+            )
+        )
 
     # make sure fid gets cleaned up
     with open(filename, "rb") as fid:
@@ -134,7 +150,10 @@ def countcolumnsvalues(line):
                         if hignore is not None:
                             for tag in hignore:
                                 taglen = len(tag)
-                                if len(hpair[0]) >= taglen and hpair[0][:taglen] == tag:
+                                if (
+                                    len(hpair[0]) >= taglen
+                                    and hpair[0][:taglen] == tag
+                                ):
                                     flag = False
                 # add header data
                 if flag:
@@ -187,7 +206,8 @@ class TextDataLoader(object):
     minrows: int
         Minimum number of rows in the first data block. (Default 10.)
     usecols: tuple
-        Which columns in our dataset to use. Ignores all other columns. If None (default), use all columns.
+        Which columns in our dataset to use. Ignores all other columns. If
+        None (default), use all columns.
     skiprows
         Rows in dataset to skip. (Currently not functional.)
     """
@@ -235,7 +255,8 @@ def readfp(self, fp, append=False):
         File details include:
          *  File name.
          *  All data blocks findable by loadData.
-         *  Headers (if present) for each data block. (Generally the headers contain column name information).
+         *  Headers (if present) for each data block. (Generally the headers
+            contain column name information).
         """
         self._reset()
         # try to read lines from fp first
@@ -258,7 +279,13 @@ def _findDataBlocks(self):
         # nf - number of words, ok - has data
         self._linerecs = numpy.recarray(
             (nlines,),
-            dtype=[("idx", int), ("nw0", int), ("nw1", int), ("nf", int), ("ok", bool)],
+            dtype=[
+                ("idx", int),
+                ("nw0", int),
+                ("nw1", int),
+                ("nf", int),
+                ("ok", bool),
+            ],
         )
         lr = self._linerecs
         lr.idx = numpy.arange(nlines)
@@ -319,7 +346,9 @@ def _findDataBlocks(self):
             if self.usecols is None:
                 data = numpy.reshape(lw.value[bb1.nw0 : ee1.nw1], (-1, bb1.nf))
             else:
-                tdata = numpy.empty((len(self.usecols), dend - dbeg), dtype=float)
+                tdata = numpy.empty(
+                    (len(self.usecols), dend - dbeg), dtype=float
+                )
                 for j, trow in zip(self.usecols, tdata):
                     j %= bb1.nf
                     trow[:] = lw.value[bb1.nw0 + j : ee1.nw1 : bb1.nf]

src/diffpy/utils/parsers/serialization.py

@@ -47,16 +47,19 @@ def serialize_data(
     data_table: list or ndarray
         Data table.
     dt_colnames: list
-        Names of each column in data_table. Every name in data_table_cols will be put into the Dictionary
-        as a key with a value of that column in data_table (stored as a List). Put None for columns
-        without names. If dt_cols has less non-None entries than columns in data_table,
-        the pair {'data table': data_table} will be put in the dictionary.
-        (Default None: only entry {'data table': data_table} will be added to dictionary.)
+        Names of each column in data_table. Every name in data_table_cols
+        will be put into the Dictionary as a key with a value of that column
+        in data_table (stored as a List). Put None for columns without names.
+        If dt_cols has less non-None entries than columns in data_table, the
+        pair {'data table': data_table} will be put in the dictionary.
+        (Default None: only entry {'data table': data_table} will be added to
+        dictionary.)
     show_path: bool
-        include a path element in the database entry (default True). If 'path' is not included in hddata,
-         extract path from filename.
+        include a path element in the database entry (default True). If
+        'path' is not included in hddata, extract path from filename.
     serial_file
-        Serial language file to dump dictionary into. If None (default), no dumping will occur.
+        Serial language file to dump dictionary into. If None (default), no
+        dumping will occur.
 
     Returns
     -------
@@ -79,32 +82,44 @@ def serialize_data(
     data.update(hdata)
 
     # second add named columns in dt_cols
-    # performed second to prioritize overwriting hdata entries with data_table column entries
+    # performed second to prioritize overwriting hdata entries with data_
+    # table column entries
     named_columns = 0  # initial value
     max_columns = 1  # higher than named_columns to trigger 'data table' entry
     if dt_colnames is not None:
         num_columns = [len(row) for row in data_table]
         max_columns = max(num_columns)
         num_col_names = len(dt_colnames)
-        if max_columns < num_col_names:  # assume numpy.loadtxt gives non-irregular array
-            raise ImproperSizeError("More entries in dt_colnames than columns in data_table.")
+        if (
+            max_columns < num_col_names
+        ):  # assume numpy.loadtxt gives non-irregular array
+            raise ImproperSizeError(
+                "More entries in dt_colnames than columns in data_table."
+            )
         named_columns = 0
         for idx in range(num_col_names):
             colname = dt_colnames[idx]
             if colname is not None:
                 if colname in hdata.keys():
                     warnings.warn(
-                        f"Entry '{colname}' in hdata has been overwritten by a data_table entry.",
+                        (
+                            f"Entry '{colname}' in hdata has been "
+                            "overwritten by a data_table entry."
+                        ),
                         RuntimeWarning,
                     )
                 data.update({colname: list(data_table[:, idx])})
                 named_columns += 1
 
-    # finally add data_table as an entry named 'data table' if not all columns were parsed
+    # finally add data_table as an entry named 'data table' if not all
+    # columns were parsed
     if named_columns < max_columns:
         if "data table" in data.keys():
             warnings.warn(
-                "Entry 'data table' in hdata has been overwritten by data_table.",
+                (
+                    "Entry 'data table' in hdata has been "
+                    "overwritten by data_table."
+                ),
                 RuntimeWarning,
             )
         data.update({"data table": data_table})

src/diffpy/utils/resampler.py

@@ -22,11 +22,11 @@
 def wsinterp(x, xp, fp, left=None, right=None):
     """One-dimensional Whittaker-Shannon interpolation.
 
-    Reconstruct a continuous signal from discrete data points by utilizing sinc functions
-    as interpolation kernels. This function interpolates the values of fp (array),
-    which are defined over xp (array), at new points x (array or float).
-    The implementation is based on E. T. Whittaker's 1915 paper
-    (https://doi.org/10.1017/S0370164600017806).
+    Reconstruct a continuous signal from discrete data points by utilizing
+    sinc functions as interpolation kernels. This function interpolates the
+    values of fp (array), which are defined over xp (array), at new points x
+    (array or float). The implementation is based on E. T. Whittaker's 1915
+    paper (https://doi.org/10.1017/S0370164600017806).
 
     Parameters
     ----------
@@ -37,17 +37,18 @@ def wsinterp(x, xp, fp, left=None, right=None):
     fp: ndarray
         The array of y values associated with xp.
     left: float
-        If given, set fp for x < xp[0] to left. Otherwise, if left is None (default) or not given,
-        set fp for x < xp[0] to fp evaluated at xp[-1].
+        If given, set fp for x < xp[0] to left. Otherwise, if left is None
+        (default) or not given, set fp for x < xp[0] to fp evaluated at xp[-1].
     right: float
-        If given, set fp for x > xp[-1] to right. Otherwise, if right is None (default) or not given, set fp for
-        x > xp[-1] to fp evaluated at xp[-1].
+        If given, set fp for x > xp[-1] to right. Otherwise, if right is None
+        (default) or not given, set fp for x > xp[-1] to fp evaluated at
+        xp[-1].
 
     Returns
     -------
     ndarray or float
-        The interpolated values at points x. Returns a single float if x is a scalar,
-        otherwise returns a numpy.ndarray.
+        The interpolated values at points x. Returns a single float if x is a
+        scalar, otherwise returns a numpy.ndarray.
     """
     scalar = np.isscalar(x)
     if scalar:
@@ -82,10 +83,11 @@ def nsinterp(xp, fp, qmin=0, qmax=25, left=None, right=None):
     """One-dimensional Whittaker-Shannon interpolation onto the Nyquist-Shannon
     grid.
 
-    Takes a band-limited function fp and original grid xp and resamples fp on the NS grid.
-    Uses the minimum number of points N required by the Nyquist sampling theorem.
-    N = (qmax-qmin)(rmax-rmin)/pi, where rmin and rmax are the ends of the real-space ranges.
-    fp must be finite, and the user inputs qmin and qmax of the frequency-domain.
+    Takes a band-limited function fp and original grid xp and resamples fp on
+    the NS grid. Uses the minimum number of points N required by the Nyquist
+    sampling theorem. N = (qmax-qmin)(rmax-rmin)/pi, where rmin and rmax are
+    the ends of the real-space ranges. fp must be finite, and the user inputs
+    qmin and qmax of the frequency-domain.
 
     Parameters
     ----------
@@ -103,8 +105,8 @@ def nsinterp(xp, fp, qmin=0, qmax=25, left=None, right=None):
     x: ndarray
         The Nyquist-Shannon grid computed for the given qmin and qmax.
     fp_at_x: ndarray
-        The interpolated values at points x. Returns a single float if x is a scalar,
-        otherwise returns a numpy.ndarray.
+        The interpolated values at points x. Returns a single float if x is a
+        scalar, otherwise returns a numpy.ndarray.
     """
     # Ensure numpy array
     xp = np.array(xp)
@@ -122,8 +124,9 @@ def nsinterp(xp, fp, qmin=0, qmax=25, left=None, right=None):
 def resample(r, s, dr):
     """Resample a PDF on a new grid.
 
-    This uses the Whittaker-Shannon interpolation formula to put s1 on a new grid if dr is less than the sampling
-    interval of r1, or linear interpolation if dr is greater than the sampling interval of r1.
+    This uses the Whittaker-Shannon interpolation formula to put s1 on a new
+    grid if dr is less than the sampling interval of r1, or linear
+    interpolation if dr is greater than the sampling interval of r1.
 
     Parameters
     ----------
@@ -140,8 +143,12 @@ def resample(r, s, dr):
     """
 
     warnings.warn(
-        "The 'resample' function is deprecated and will be removed in a future release (3.8.0). \n"
-        "'resample' has been renamed 'wsinterp' to better reflect functionality. Please use 'wsinterp' instead.",
+        (
+            "The 'resample' function is deprecated and will be removed "
+            "in a future release (3.8.0). \n"
+            "'resample' has been renamed 'wsinterp' to better reflect "
+            "functionality. Please use 'wsinterp' instead."
+        ),
         DeprecationWarning,
         stacklevel=2,
     )