skpkg: apply black line-length 115 to all files in the project directory

.github/ISSUE_TEMPLATE/release_checklist.md

@@ -6,30 +6,41 @@ labels: "release"
 assignees: ""
 ---
 
-### PyPI/GitHub release checklist:
+### PyPI/GitHub rc-release preparation checklist:
 
 - [ ] All PRs/issues attached to the release are merged.
 - [ ] All the badges on the README are passing.
 - [ ] License information is verified as correct. If you are unsure, please comment below.
 - [ ] Locally rendered documentation contains all appropriate pages, including API references (check no modules are
-  missing), tutorials, and other human written text is up-to-date with any changes in the code.
-- [ ] Installation instructions in the README, documentation and on the website (e.g., diffpy.org) are updated.
+      missing), tutorials, and other human-written text is up-to-date with any changes in the code.
+- [ ] Installation instructions in the README, documentation, and the website are updated.
 - [ ] Successfully run any tutorial examples or do functional testing with the latest Python version.
 - [ ] Grammar and writing quality are checked (no typos).
+- [ ] Install `pip install build twine`, run `python -m build` and `twine check dist/*` to ensure that the package can be built and is correctly formatted for PyPI release.
 
-Please mention @sbillinge here when you are ready for PyPI/GitHub release. Include any additional comments necessary, such as
-version information and details about the pre-release here:
+Please tag the maintainer (e.g., @username) in the comment here when you are ready for the PyPI/GitHub release. Include any additional comments necessary, such as version information and details about the pre-release here:
 
-### conda-forge release checklist:
+### PyPI/GitHub full-release preparation checklist:
 
-<!-- After @sbillinge releases the PyPI package, please check the following when creating a PR for conda-forge release.-->
+- [ ] Create a new conda environment and install the rc from PyPI (`pip install <package-name>==??`)
+- [ ] License information on PyPI is correct.
+- [ ] Docs are deployed successfully to `https://<github-username-or-orgname>/<package-name>`.
+- [ ] Successfully run all tests, tutorial examples or do functional testing.
 
+Please let the maintainer know that all checks are done and the package is ready for full release.
+
+### conda-forge release preparation checklist:
+
+<!-- After the maintainer releases the PyPI package, please check the following when creating a PR for conda-forge release.-->
+
+- [ ] Ensure that the full release has appeared on PyPI successfully.
 - [ ] New package dependencies listed in `conda.txt` and `test.txt` are added to `meta.yaml` in the feedstock.
-- [ ] All relevant issues in the feedstock are addressed in the release PR.
+- [ ] Close any open issues on the feedstock. Reach out to the maintainer if you have questions.
+- [ ] Tag the maintainer for conda-forge release.
 
 ### Post-release checklist
 
 <!-- Before closing this issue, please complete the following: -->
 
-- [ ]  Run tutorial examples and conduct functional testing using the installation guide in the README. Attach screenshots/results as comments.
-- [ ]  Documentation (README, tutorials, API references, and websites) is deployed without broken links or missing figures.
+- [ ] Run tutorial examples and conduct functional testing using the installation guide in the README. Attach screenshots/results as comments.
+- [ ] Documentation (README, tutorials, API references, and websites) is deployed without broken links or missing figures.

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.nmf_mapping.tex", "diffpy.nmf_mapping Documentation", ab_authors, "manual"),
+    (
+        "index",
+        "diffpy.nmf_mapping.tex",
+        "diffpy.nmf_mapping Documentation",
+        ab_authors,
+        "manual",
+    ),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of
@@ -249,7 +255,15 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [("index", "diffpy.nmf_mapping", "diffpy.nmf_mapping Documentation", ab_authors, 1)]
+man_pages = [
+    (
+        "index",
+        "diffpy.nmf_mapping",
+        "diffpy.nmf_mapping Documentation",
+        ab_authors,
+        1,
+    )
+]
 
 # If true, show URL addresses after external links.
 # man_show_urls = False

src/__init__.py

@@ -13,8 +13,7 @@
 #
 ##############################################################################
 
-"""nmf_mapping - tools for performing NMF on PDF and XRD data.
-"""
+"""nmf_mapping - tools for performing NMF on PDF and XRD data."""
 
 
 __import__("pkg_resources").declare_namespace(__name__)

src/diffpy/nmf_mapping/main.py

@@ -31,7 +31,11 @@ def main(args=None):
     as well as the reconstruction error as a fxn of component
     """
 
-    parser = ArgumentParser(prog="nmf_mapping", description=_BANNER, formatter_class=RawTextHelpFormatter)
+    parser = ArgumentParser(
+        prog="nmf_mapping",
+        description=_BANNER,
+        formatter_class=RawTextHelpFormatter,
+    )
 
     def tup(s):
         if not isinstance(s, str):
@@ -45,7 +49,10 @@ def tup(s):
 
     # args
     parser.add_argument(
-        "directory", default=None, type=str, help="a directory of PDFs to calculate NMF decomposition"
+        "directory",
+        default=None,
+        type=str,
+        help="a directory of PDFs to calculate NMF decomposition",
     )
     group = parser.add_mutually_exclusive_group()
     parser.add_argument(
@@ -105,25 +112,37 @@ def tup(s):
         nargs="*",
         help="the x-range over which to calculate NMF, can be multiple ranges (e.g. --xrange 5,10 12,15)",
     )
-    parser.add_argument("--show", default=True, type=boolean_string, help="whether to show the plot")
+    parser.add_argument(
+        "--show",
+        default=True,
+        type=boolean_string,
+        help="whether to show the plot",
+    )
     args0 = Namespace()
     args1, _ = parser.parse_known_args(args, namespace=args0)
 
     input_list, data_list = nmf.load_data(args1.directory, args1.xrd)
     if args1.pca_thresh:
-        df_components, df_component_weight_timeseries, df_reconstruction_error, df_explained_var_ratio = (
-            nmf.NMF_decomposition(
-                input_list,
-                args1.xrange,
-                args1.threshold,
-                additional_comp=False,
-                improve_thresh=args1.improve_thresh,
-                n_iter=args1.n_iter,
-                pca_thresh=args1.pca_thresh,
-            )
+        (
+            df_components,
+            df_component_weight_timeseries,
+            df_reconstruction_error,
+            df_explained_var_ratio,
+        ) = nmf.NMF_decomposition(
+            input_list,
+            args1.xrange,
+            args1.threshold,
+            additional_comp=False,
+            improve_thresh=args1.improve_thresh,
+            n_iter=args1.n_iter,
+            pca_thresh=args1.pca_thresh,
         )
     else:
-        df_components, df_component_weight_timeseries, df_reconstruction_error = nmf.NMF_decomposition(
+        (
+            df_components,
+            df_component_weight_timeseries,
+            df_reconstruction_error,
+        ) = nmf.NMF_decomposition(
             input_list,
             args1.xrange,
             args1.threshold,
@@ -149,7 +168,11 @@ def tup(s):
             os.path.join(os.getcwd(), "nmf_result", "component_index_vs_pratio_col.json")
         )
         df_component_weight_timeseries.to_csv(
-            os.path.join(os.getcwd(), "nmf_result", output_fn + "component_row_pratio_col.txt"),
+            os.path.join(
+                os.getcwd(),
+                "nmf_result",
+                output_fn + "component_row_pratio_col.txt",
+            ),
             header=None,
             index=False,
             sep=" ",
@@ -196,7 +219,11 @@ def tup(s):
 
             if args1.xrd:
                 np.savetxt(
-                    os.path.join(os.getcwd(), "nmf_result", output_fn + f"_comp{i}" + ".xy"),
+                    os.path.join(
+                        os.getcwd(),
+                        "nmf_result",
+                        output_fn + f"_comp{i}" + ".xy",
+                    ),
                     data,
                     header=f"NMF Generated XRD\nSource = nmfMapping\n"
                     f"Date = {output_fn}\n{args1.x_units} Intensity\n",
@@ -205,7 +232,11 @@ def tup(s):
                 )
             else:
                 np.savetxt(
-                    os.path.join(os.getcwd(), "nmf_result", output_fn + f"_comp{i}" + ".cgr"),
+                    os.path.join(
+                        os.getcwd(),
+                        "nmf_result",
+                        output_fn + f"_comp{i}" + ".cgr",
+                    ),
                     data,
                     header=f"NMF Generated PDF\nSource: nmfMapping\n" f"Date: {output_fn}\nr g",
                     fmt="%s",

src/diffpy/nmf_mapping/nmf_mapping_code.py

@@ -98,7 +98,13 @@ def load_data(dir, xrd=False):
 
 # TODO Add regularization on the frobenius norm in order to prevent creation of an excessive number of components
 def NMF_decomposition(
-    data_arr, x_range=None, thresh=None, additional_comp=False, improve_thresh=None, n_iter=None, pca_thresh=None
+    data_arr,
+    x_range=None,
+    thresh=None,
+    additional_comp=False,
+    improve_thresh=None,
+    n_iter=None,
+    pca_thresh=None,
 ):
     """
     Takes a 3D array of PDFs and returns the structurally significant
@@ -208,8 +214,17 @@ def NMF_decomposition(
     df_component_weight_timeseries = pd.DataFrame(nmf_weight, index=range(n_comp))
 
     if pca_thresh:
-        return df_components, df_component_weight_timeseries, df_reconstruction_error, df_explained_var_ratio
-    return df_components, df_component_weight_timeseries, df_reconstruction_error
+        return (
+            df_components,
+            df_component_weight_timeseries,
+            df_reconstruction_error,
+            df_explained_var_ratio,
+        )
+    return (
+        df_components,
+        df_component_weight_timeseries,
+        df_reconstruction_error,
+    )
 
 
 def component_plot(df_components, xrd=False, x_units=None, show=True):
@@ -244,7 +259,11 @@ def component_plot(df_components, xrd=False, x_units=None, show=True):
     shift = max_range
     # seq to align with input phase
     for i, s in enumerate(data_list):
-        ax.plot(df.index.to_numpy(dtype=np.single), df[s].to_numpy() + i * shift, label=s)
+        ax.plot(
+            df.index.to_numpy(dtype=np.single),
+            df[s].to_numpy() + i * shift,
+            label=s,
+        )
     ax.legend(loc="best")
     if xrd:
         if x_units == "twotheta" or x_units == "ttheta":

src/diffpy/version.py

@@ -13,8 +13,7 @@
 #
 ##############################################################################
 
-"""Definition of __version__ and __date__ for diffpy.nmf_mapping.
-"""
+"""Definition of __version__ and __date__ for diffpy.nmf_mapping."""
 
 __id__ = "$Id$"
 

tests/test_NMF_analysis_code.py

@@ -14,7 +14,11 @@
 test_map = [
     ([data_dir, "--xrange", "5,10"], "output_1", "Number of components: 3\n"),
     ([data_dir], "output_2", "Number of components: 3\n"),
-    ([data_dir, "--xrange", "5,10", "12,15"], "output_3", "Number of components: 3\n"),
+    (
+        [data_dir, "--xrange", "5,10", "12,15"],
+        "output_3",
+        "Number of components: 3\n",
+    ),
 ]
 
 

tests/test_version.py

@@ -1,5 +1,4 @@
-"""Unit tests for __version__.py
-"""
+"""Unit tests for __version__.py"""
 
 import diffpy.nmf_mapping