Update coffee_break_unit_test.py

tests/coffee_break_unit_test.py

@@ -1 +1,80 @@
-***
+## Test for visualization method: cappuccino
+## It relies on the n-gram frequency matrix from arabica_freq
+## n-gram frequencies are visualised with Matplotlib or Plotnine
+
+
+import unittest
+import pandas as pd
+from arabica import cappuccino
+
+class TestCappuccinoFunction(unittest.TestCase):
+
+    data = pd.DataFrame({
+        'text': ["You may find yourself trying to decide between comparable crystallized ginger offerings from Reeds",
+                 "Reed’s has a lovely raw cane sugar flavor, and is sweeter and more mellow than The Ginger People’s."],
+        'time': ["2016-08-30", "2016-08-31"]})
+
+
+def test_cappuccino_wordcloud(self):
+    # Provide test input
+    date_format = "us"
+    stopwords = []
+    skip = []
+    plot_type = "wordcloud"
+    ngram = 1
+    time_freq = "ungroup"
+    max_words = 10
+    numbers = True
+    lower_case = True
+
+    # Call the cappuccino function
+    result = cappuccino(self.data['text'], self.data['time'], date_format, stopwords, skip, plot_type,
+                        ngram, time_freq, max_words, numbers, lower_case)
+
+    # Perform assertions based on the expected behavior
+    self.assertIsNone(result)  # Assuming picture is None when using wordcloud
+
+def test_cappuccino_line(self):
+    # Provide test input
+    text = "Some example text for testing."
+    time = "date_column"
+    date_format = "us"
+    stopwords = []
+    skip = []
+    plot_type = "line"
+    ngram = 1
+    time_freq = "M"
+    max_words = 10
+    numbers = True
+    lower_case = True
+
+    # Call the cappuccino function
+    result = cappuccino(text, time, date_format, stopwords, skip, plot_type,
+                        ngram, time_freq, max_words, numbers, lower_case)
+
+
+def test_cappuccino_heatmap(self):
+    # Provide test input
+    text = "Some example text for testing."
+    time = "date_column"
+    date_format = "us"
+    stopwords = []
+    skip = []
+    plot_type = "heatmap"
+    ngram = 1
+    time_freq = "M"
+    max_words = 10
+    numbers = True
+    lower_case = True
+
+    # Call the cappuccino function
+    result = cappuccino(text, time, date_format, stopwords, skip, plot_type,
+                        ngram, time_freq, max_words, numbers, lower_case)
+
+
+
+    # Perform assertions based on the expected behavior
+    self.assertIsNone(result)  # Assuming picture is None when using line plot for monthly frequency
+
+if __name__ == '__main__':
+    unittest.main(argv=[''], exit=False)