format python code using ruff (#83)

* format python code using ruff

* add test for component

doc/source/conf.py

@@ -18,7 +18,8 @@
 #
 import os
 import sys
-sys.path.insert(0, os.path.abspath('../..'))
+
+sys.path.insert(0, os.path.abspath("../.."))
 
 # -- General configuration ------------------------------------------------
 
@@ -29,54 +30,54 @@
 
 html_theme = "sphinx_rtd_theme"
 html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
-#collapse_navigation = True
+# collapse_navigation = True
 
 # Add any Sphinx extension module names here, as strings. They can be
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
-    'sphinx.ext.autodoc',
-    'sphinx.ext.mathjax',
-    'sphinx.ext.githubpages',
-    'sphinx.ext.napoleon',
+    "sphinx.ext.autodoc",
+    "sphinx.ext.mathjax",
+    "sphinx.ext.githubpages",
+    "sphinx.ext.napoleon",
 ]
 
 # Add any paths that contain templates here, relative to this directory.
-templates_path = ['_templates']
+templates_path = ["_templates"]
 
 # The suffix(es) of source filenames.
 # You can specify multiple suffix as a list of string:
 #
 # source_suffix = ['.rst', '.md']
-source_suffix = '.rst'
+source_suffix = ".rst"
 
 # The encoding of source files.
 #
 # source_encoding = 'utf-8-sig'
 
 # The master toctree document.
-master_doc = 'index'
+master_doc = "index"
 
 # General information about the project.
-project = u'PyDLM'
-copyright = u'2024, Xiangyu Wang'
-author = u'Xiangyu Wang'
+project = "PyDLM"
+copyright = "2024, Xiangyu Wang"
+author = "Xiangyu Wang"
 
 # The version info for the project you're documenting, acts as replacement for
 # |version| and |release|, also used in various other places throughout the
 # built documents.
 #
 # The short X.Y version.
-version = u'0.1.1.13'
+version = "0.1.1.13"
 # The full version, including alpha/beta/rc tags.
-release = u'0.1.1.13'
+release = "0.1.1.13"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
 #
 # This is also used if you do content translation via gettext catalogs.
 # Usually you set "language" from the command line for these cases.
-language = 'en'
+language = "en"
 
 # There are two options for replacing |today|: either, you set today to some
 # non-false value, then it is used:
@@ -112,7 +113,7 @@
 # show_authors = False
 
 # The name of the Pygments (syntax highlighting) style to use.
-pygments_style = 'sphinx'
+pygments_style = "sphinx"
 
 # A list of ignored prefixes for module index sorting.
 # modindex_common_prefix = []
@@ -163,7 +164,7 @@
 # Add any paths that contain custom static files (such as style sheets) here,
 # relative to this directory. They are copied after the builtin static files,
 # so a file named "default.css" will overwrite the builtin "default.css".
-html_static_path = ['_static']
+html_static_path = ["_static"]
 
 # Add any extra paths that contain custom files (such as robots.txt or
 # .htaccess) here, relative to this directory. These files are copied
@@ -243,34 +244,30 @@
 # html_search_scorer = 'scorer.js'
 
 # Output file base name for HTML help builder.
-htmlhelp_basename = 'PyDLMdoc'
+htmlhelp_basename = "PyDLMdoc"
 
 # -- Options for LaTeX output ---------------------------------------------
 
 latex_elements = {
-     # The paper size ('letterpaper' or 'a4paper').
-     #
-     # 'papersize': 'letterpaper',
-
-     # The font size ('10pt', '11pt' or '12pt').
-     #
-     # 'pointsize': '10pt',
-
-     # Additional stuff for the LaTeX preamble.
-     #
-     # 'preamble': '',
-
-     # Latex figure (float) alignment
-     #
-     # 'figure_align': 'htbp',
+    # The paper size ('letterpaper' or 'a4paper').
+    #
+    # 'papersize': 'letterpaper',
+    # The font size ('10pt', '11pt' or '12pt').
+    #
+    # 'pointsize': '10pt',
+    # Additional stuff for the LaTeX preamble.
+    #
+    # 'preamble': '',
+    # Latex figure (float) alignment
+    #
+    # 'figure_align': 'htbp',
 }
 
 # Grouping the document tree into LaTeX files. List of tuples
 # (source start file, target name, title,
 #  author, documentclass [howto, manual, or own class]).
 latex_documents = [
-    (master_doc, 'PyDLM.tex', u'PyDLM Documentation',
-     u'Xiangyu Wang', 'manual'),
+    (master_doc, "PyDLM.tex", "PyDLM Documentation", "Xiangyu Wang", "manual"),
 ]
 
 # The name of an image file (relative to this directory) to place at the top of
@@ -310,10 +307,7 @@
 
 # One entry per manual page. List of tuples
 # (source start file, name, description, authors, manual section).
-man_pages = [
-    (master_doc, 'pydlm', u'PyDLM Documentation',
-     [author], 1)
-]
+man_pages = [(master_doc, "pydlm", "PyDLM Documentation", [author], 1)]
 
 # If true, show URL addresses after external links.
 #
@@ -326,9 +320,15 @@
 # (source start file, target name, title, author,
 #  dir menu entry, description, category)
 texinfo_documents = [
-    (master_doc, 'PyDLM', u'PyDLM Documentation',
-     author, 'PyDLM', 'One line description of project.',
-     'Miscellaneous'),
+    (
+        master_doc,
+        "PyDLM",
+        "PyDLM Documentation",
+        author,
+        "PyDLM",
+        "One line description of project.",
+        "Miscellaneous",
+    ),
 ]
 
 # Documents to append as an appendix to all manuals.

examples/unemployment_insurance/main.py

@@ -1,82 +1,86 @@
-#==================================================================
+# ==================================================================
 #
 #  This example use the data from Google data science blog post
 #  http://www.unofficialgoogledatascience.com/2017/07/fitting-bayesian-structural-time-series.html
 #
 #  Make sure your working directly is pointing to the folder where
 #  `main.py` locates and `data.csv` is in the same folder.
 #
-#==================================================================
+# ==================================================================
 
 # Read data file
 import os
+
 this_dir = os.getcwd()
 DATA_PATH = os.path.join(this_dir, "data.csv")
-data_file = open(DATA_PATH, 'r')
+data_file = open(DATA_PATH, "r")
 
-variables = data_file.readline().strip().split(',')
+variables = data_file.readline().strip().split(",")
 data_map = {}
 for var in variables:
     data_map[var] = []
 
 for line in data_file:
-    for i, data_piece in enumerate(line.strip().split(',')):
+    for i, data_piece in enumerate(line.strip().split(",")):
         data_map[variables[i]].append(float(data_piece))
 
 # Extract and store the data.
 time_series = data_map[variables[0]]
-features = [[data_map[variables[j]][i] for j in range(1, len(variables)) ]
-            for i in range(len(time_series))]
+features = [
+    [data_map[variables[j]][i] for j in range(1, len(variables))]
+    for i in range(len(time_series))
+]
 
 # Plot the raw data
 import matplotlib.pyplot as plt
 import pydlm.plot.dlmPlot as dlmPlot
-dlmPlot.plotData(range(len(time_series)),
-                 time_series,
-                 showDataPoint=False,
-                 label='raw_data')
-plt.legend(loc='best', shadow=True)
+
+dlmPlot.plotData(
+    range(len(time_series)), time_series, showDataPoint=False, label="raw_data"
+)
+plt.legend(loc="best", shadow=True)
 plt.show()
 
 # Build a simple model
 from pydlm import dlm, trend, seasonality
 
 # A linear trend
-linear_trend = trend(degree=1, discount=0.95, name='linear_trend', w=10)
+linear_trend = trend(degree=1, discount=0.95, name="linear_trend", w=10)
 # A seasonality
-seasonal52 = seasonality(period=52, discount=0.99, name='seasonal52', w=10)
+seasonal52 = seasonality(period=52, discount=0.99, name="seasonal52", w=10)
 
 simple_dlm = dlm(time_series) + linear_trend + seasonal52
 simple_dlm.fit()
 
 # Plot the fitted results
-simple_dlm.turnOff('data points')
+simple_dlm.turnOff("data points")
 simple_dlm.plot()
 # Plot each component (attribution)
-simple_dlm.turnOff('predict plot')
-simple_dlm.turnOff('filtered plot')
-simple_dlm.plot('linear_trend')
-simple_dlm.plot('seasonal52')
+simple_dlm.turnOff("predict plot")
+simple_dlm.turnOff("filtered plot")
+simple_dlm.plot("linear_trend")
+simple_dlm.plot("seasonal52")
 # Plot the prediction give the first 350 weeks and forcast the next 200 weeks.
 simple_dlm.plotPredictN(N=200, date=350)
 # Plot the prediction give the first 250 weeks and forcast the next 200 weeks.
 simple_dlm.plotPredictN(N=200, date=250)
 
 # Build a dynamic regression model
 from pydlm import dynamic
-regressor10 = dynamic(features=features, discount=1.0, name='regressor10', w=10)
+
+regressor10 = dynamic(features=features, discount=1.0, name="regressor10", w=10)
 drm = dlm(time_series) + linear_trend + seasonal52 + regressor10
 drm.fit()
 
 # Plot the fitted results
-drm.turnOff('data points')
+drm.turnOff("data points")
 drm.plot()
 # Plot each component (attribution)
-drm.turnOff('predict plot')
-drm.turnOff('filtered plot')
-drm.plot('linear_trend')
-drm.plot('seasonal52')
-drm.plot('regressor10')
+drm.turnOff("predict plot")
+drm.turnOff("filtered plot")
+drm.plot("linear_trend")
+drm.plot("seasonal52")
+drm.plot("regressor10")
 # Plot the prediction give the first 300 weeks and forcast the next 150 weeks.
 drm.plotPredictN(N=150, date=300)
 # Plot the prediction give the first 250 weeks and forcast the next 200 weeks.

pydlm/__init__.py

@@ -1,6 +1,14 @@
 # This is the PyDLM package
 
-__all__ = ['dlm', 'trend', 'seasonality', 'dynamic', 'autoReg', 'longSeason', 'modelTuner']
+__all__ = [
+    "dlm",
+    "trend",
+    "seasonality",
+    "dynamic",
+    "autoReg",
+    "longSeason",
+    "modelTuner",
+]
 
 from pydlm.dlm import dlm
 from pydlm.modeler.trends import trend