update names and docstrings to match what is actually read.

solventmapcreator/clusteringanalysis/dendrogramplotting.py

@@ -16,6 +16,12 @@ logging.basicConfig()
 LOGGER = logging.getLogger(__name__)
 LOGGER.setLevel(logging.WARN)
 
+def create_dendogram(linkage_matrix, labels, figsize):
+    """Creates a 
+    """
+    dendrogram_plot, dendrogram_plot_axis = create_plot_with_axis(figsize)
+    cluster.dendrogram(linkage_matrix, labels=labels, ax=dendrogram_plot_axis)
+
 def create_plot_with_axis(figsize):
     """Function creates plot and plot axis.
     """

solventmapcreator/clusteringanalysis/matrixinput.py

@@ -16,20 +16,21 @@ logging.basicConfig()
 LOGGER = logging.getLogger(__name__)
 LOGGER.setLevel(logging.WARN)
 
-def parse_similarity_matrix_file_trig_matrix(filename):
-    """This reads a file into a dictionary, then appends the trigonal dictionary.
+def parse_similarity_matrix_file_condensed_matrix(filename):
+    """This reads a file into a dictionary, then appends the condensed matrix
+    to the dictionary.
     """
     similarity_matrix_info = parse_similarity_matrix_file(filename)
     append_condensed_matrix(similarity_matrix_info)
     return similarity_matrix_info
 
 def append_condensed_matrix(similarity_matrix_info):
-    """This appends a triagonal matrix to the input dict.
+    """This appends a condensed matrix to the input dict.
     """
     similarity_matrix_info["condensed_matrix"] = convert_to_condensed_matrix(similarity_matrix_info["value_matrix"])
 
 def convert_to_condensed_matrix(similarity_matrix):
-    """This converts the matrix to a triangular matrix.
+    """This converts the matrix to a condensed matrix.
     """
     return scidist.squareform(similarity_matrix)
 

solventmapcreator/test/clusteringanalysistest/matrixinputtest.py

@@ -31,7 +31,7 @@ class MatrixInputTestCase(unittest.TestCase):
         """
         del self.input_filename
         del self.expected_dict
-    def test_parse_similarity_matrix_file_trig_matrix(self):
+    def test_parse_similarity_matrix_file_condensed_matrix(self):
         """Test to see if expected dictionary is produced.
         """
         expected_dict = {"labels":["poly_fit", "poly_fit2", "poly_fit3"],
@@ -39,14 +39,14 @@ class MatrixInputTestCase(unittest.TestCase):
                                                   [1.0, 0.0, 3.0],
                                                   [4.0, 3.0, 0.0]]),
                          "condensed_matrix":np.array([1.0, 4.0, 3.0])}
-        actual_dict = matrixinput.parse_similarity_matrix_file_trig_matrix(self.input_filename)
+        actual_dict = matrixinput.parse_similarity_matrix_file_condensed_matrix(self.input_filename)
         self.assertListEqual(sorted(expected_dict.keys()), sorted(actual_dict.keys()))
         self.assertListEqual(expected_dict["labels"], actual_dict["labels"])
         np.testing.assert_array_almost_equal(expected_dict["value_matrix"],
                                              actual_dict["value_matrix"])
         np.testing.assert_array_almost_equal(expected_dict["condensed_matrix"],
                                              actual_dict["condensed_matrix"])
-    def test_append_trigonal_matrix(self):
+    def test_append_condensed_matrix(self):
         """Test to see if matrix is appended as expected.
         """
         expected_dict = {"labels":["poly_fit", "poly_fit2", "poly_fit3"],
@@ -61,7 +61,7 @@ class MatrixInputTestCase(unittest.TestCase):
                                              expected_dict["value_matrix"])
         np.testing.assert_array_almost_equal(self.expected_dict["condensed_matrix"],
                                              expected_dict["condensed_matrix"])
-    def test_convert_to_triangular_matrix(self):
+    def test_convert_to_condensed_matrix(self):
         """Test to see if expected matrix is returned.
         """
         expected_matrix = np.array([1.0, 4.0, 3.0])