Readme+test

Author: Gsaes

README.rst

@@ -23,7 +23,7 @@
 .. |Commits| image:: https://img.shields.io/github/commits-since/Quantmetry/qolmat/latest/main
 .. _Commits: https://github.com/Quantmetry/qolmat/commits/main
 
-.. image:: https://github.com/Quantmetry/qolmat/tree/main/docs/images/logo.png
+.. image:: https://raw.githubusercontent.com/Quantmetry/qolmat/main/docs/images/logo.png
     :align: center
 
 Qolmat -  The Tool for Data Imputation
@@ -95,7 +95,7 @@ For this demonstration, let us create artificial holes in our dataset.
     plt.savefig('readme1.png')
     plt.show()
 
-.. image:: https://github.com/Quantmetry/qolmat/tree/main/docs/images/readme1.png
+.. image:: https://raw.githubusercontent.com/Quantmetry/qolmat/main/docs/images/readme1.png
     :align: center
 
 To impute missing data, there are several methods that can be imported with ``from qolmat.imputations import imputers``.
@@ -191,7 +191,7 @@ We can observe the benchmark results.
     plt.savefig('readme3.png')
     plt.show()
 
-.. image:: https://github.com/Quantmetry/qolmat/tree/main/docs/images/readme2.png
+.. image:: https://raw.githubusercontent.com/Quantmetry/qolmat/main/docs/images/readme2.png
     :align: center
 
 Finally, we keep the best ``TSMLE`` imputor we represent.
@@ -206,7 +206,7 @@ Finally, we keep the best ``TSMLE`` imputor we represent.
     plt.plot(df_with_nan['y'],'.b')
     plt.show()
 
-.. image:: https://github.com/Quantmetry/qolmat/tree/main/docs/images/readme3.png
+.. image:: https://raw.githubusercontent.com/Quantmetry/qolmat/main/docs/images/readme3.png
     :align: center
 
 

qolmat/utils/utils.py

@@ -37,7 +37,15 @@ def display_bar_table(data: pd.DataFrame, ylabel: Optional[str] = "", path: Opti
     plt.show()
 
 
-def progress_bar(iteration, total, prefix="", suffix="", decimals=1, length=100, fill="█"):
+def progress_bar(
+    iteration: int,
+    total: int,
+    prefix: str = "",
+    suffix: str = "",
+    decimals: int = 1,
+    length: int = 100,
+    fill: str = "█",
+):
     """Call in a loop to create terminal progress bar
 
     Parameters
@@ -46,27 +54,40 @@ def progress_bar(iteration, total, prefix="", suffix="", decimals=1, length=100,
         current iteration
     total : int
         total iterations
-    prefix : str, optional
+    prefix : str
         prefix string, by default ""
-    suffix : str, optional
+    suffix : str
         suffix string, by default ""
-    decimals : int, optional
+    decimals : int
         positive number of decimals in percent complete, by default 1
-    length : int, optional
+    length : int
         character length of bar, by default 100
-    fill : str, optional
+    fill : str
         bar fill character, by default "█"
     """
     percent = ("{0:." + str(decimals) + "f}").format(100 * (iteration / float(total)))
     filled_length = int(length * iteration // total)
     bar = fill * filled_length + "-" * (length - filled_length)
     print(f"\r{prefix} |{bar}| {percent}% {suffix}", end="\r")
-    # Print New Line on Complete
     if iteration == total:
         print()
 
 
 def acf(values: pd.Series, lag_max: int = 30) -> pd.Series:
+    """Correlation series of dataseries
+
+    Parameters
+    ----------
+    values : pd.Series
+        dataseries
+    lag_max : int, optional
+        the maximum lag, by default 30
+
+    Returns
+    -------
+    pd.Series
+        correlation series of value
+    """
     acf = pd.Series(0, index=range(lag_max))
     for lag in range(lag_max):
         acf[lag] = values.corr(values.shift(lag))

tests/utils/test_exceptions.py

@@ -0,0 +1,13 @@
+import pytest
+from qolmat.utils import exceptions
+
+
+def test_utils_exception_init():
+    try:
+        raise exceptions.KerasExtraNotInstalled()
+    except exceptions.KerasExtraNotInstalled as e:
+        assert (
+            str(e)
+            == """Please install keras xx.xx.xx
+        pip install qolmat[keras]"""
+        )

tests/utils/test_utils.py

@@ -0,0 +1,45 @@
+import sys
+import matplotlib as mpl
+import matplotlib.pyplot as plt
+import numpy as np
+import pandas as pd
+import pytest
+from qolmat.utils import utils
+from pytest_mock.plugin import MockerFixture
+from io import StringIO
+
+df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "C": [7, 8, 9]})
+
+
+@pytest.mark.parametrize("df", [df])
+def test_utils_utils_display_bar_table(df: pd.DataFrame, mocker: MockerFixture) -> None:
+    mock_save = mocker.patch("matplotlib.pyplot.savefig")
+    mocker.patch("matplotlib.pyplot.show")
+    utils.display_bar_table(data=df, ylabel="Counts", path="output/barplot")
+    y_label_text = plt.gca().get_ylabel()
+    assert mock_save.call_count == 1
+    assert plt.gcf() is not None
+    assert plt.gca() is not None
+    assert y_label_text == "Counts"
+
+
+@pytest.mark.parametrize("iteration, total", [(1, 1)])
+def test_utils_utils_display_progress_bar(iteration: int, total: int, capsys) -> None:
+    captured_output = StringIO()
+    sys.stdout = captured_output
+    utils.progress_bar(
+        iteration, total, prefix="Progress", suffix="Complete", decimals=1, length=2, fill="█"
+    )
+    captured_output.seek(0)
+    output = captured_output.read().strip()
+    sys.stdout = sys.__stdout__
+
+    output_expected = "Progress |██| 100.0% Complete"
+    assert output == output_expected
+
+
+@pytest.mark.parametrize("values, lag_max", [(pd.Series([1, 2, 3, 4, 5]), 3)])
+def test_utils_utils_acf(values, lag_max):
+    result = utils.acf(values, lag_max)
+    result_expected = pd.Series([1.0, 1.0, 1.0])
+    pd.testing.assert_series_equal(result, result_expected, atol=0.001)