added methods for generating plot input from the polynomial coeficient data directly.

solventmapcreator/polynomialanalysis/polynomialcomparison.py

@@ -15,6 +15,19 @@ logging.basicConfig()
 LOGGER = logging.getLogger(__name__)
 LOGGER.setLevel(logging.WARN)
 
+
+def generate_input_data_hausdorff(x_values, polynomial_order, poly_data_by_id):
+    """This generates the Hausdorff matrix and then returns the plot input for the Matrix.
+    """
+    haussdorff_simil_matrix = calculate_hausdorff_distance_matrix_from_poly_coeff(x_values, polynomial_order, poly_data_by_id)
+    return generate_similarity_matrix_plot_input(sorted(poly_data_by_id.keys()), haussdorff_simil_matrix)
+
+def generate_input_data_rmsd(x_values, polynomial_order, poly_data_by_id):
+    """This generates the RMSD matrix and then returns the plot input for the Matrix.
+    """
+    rmsd_simil_matrix = calculate_rmsd_matrix_from_poly_coeff(x_values, polynomial_order, poly_data_by_id)
+    return generate_similarity_matrix_plot_input(sorted(poly_data_by_id.keys()), rmsd_simil_matrix)
+
 def generate_similarity_matrix_plot_input(sorted_id_list, matrix):
     """This compiles the input information needed for the similarity matrix plot.
     """

solventmapcreator/test/polynomialanalysistest/polynomialcomparisontest.py

@@ -46,6 +46,30 @@ class PolynomialComparisonTestCase(unittest.TestCase):
         del self.poly_data_by_solvent_id
         del self.x_values
         del self.poly_values_dict
+    def test_(self):
+        """Test to see expected dict is produced.
+        """
+        expected_dict = {"labels":["poly_fit", "poly_fit2", "poly_fit3"],
+                         "value_matrix":np.array([[0.0, 1.0, 4.0],
+                                                  [1.0, 0.0, 3.0],
+                                                  [4.0, 3.0, 0.0]])}
+        actual_dict = polynomialcomparison.generate_input_data_hausdorff(self.x_values, 2, self.poly_data_by_solvent_id)
+        self.assertEqual(2, len(actual_dict.keys()))
+        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"])
+    def test_generate_input_data_rmsd(self):
+        """Test to see expected dict is returned.
+        """
+        expected_dict = {"labels":["poly_fit", "poly_fit2", "poly_fit3"],
+                         "value_matrix":np.array([[0.0, 1.0, 2.607681],
+                                                  [1.0, 0.0, 1.949359],
+                                                  [2.607681, 1.949359, 0.0]])}
+        actual_dict = polynomialcomparison.generate_input_data_rmsd(self.x_values, 2, self.poly_data_by_solvent_id)
+        self.assertEqual(2, len(actual_dict.keys()))
+        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"])
     def test_generate_similarity_matrix_plot_input(self):
         """Test to see if expected dictionary is created.
         """