Major refactor

Author: ddomingof

README.rst

@@ -43,7 +43,7 @@ The following command will run a diffusion method on a given network with the gi
 
 .. code-block:: sh
 
-    $ python3 -m diffupy diffuse --network=<path-to-network-file> --input=<path-to-data-file> --method=<method>
+    $ python3 -m diffupy diffuse --network=<path-to-network-file> --data=<path-to-data-file> --method=<method>
 
 
 2. **Generate a kernel with one of the seven methods implemented**

src/diffupy/cli.py

@@ -83,7 +83,7 @@ def kernel(
     type=click.Path(exists=True, dir_okay=False)
 )
 @click.option(
-    '-i', '--input',
+    '-i', '--data',
     help='Input data',
     required=True,
     type=click.Path(exists=True, dir_okay=False)
@@ -131,7 +131,7 @@ def kernel(
 )
 def diffuse(
         network: str,
-        input: str,
+        data: str,
         output: str,
         method: str,
         binarize: bool,
@@ -150,9 +150,9 @@ def diffuse(
         f'{EMOJI}'
     )
 
-    click.secho(f'Codifying data from {input}.')
+    click.secho(f'Codifying data from {data}.')
 
-    input_scores_dict = process_input(input, method, binarize, absolute_value, p_value, threshold)
+    input_scores_dict = process_input(data, method, binarize, absolute_value, p_value, threshold)
 
     click.secho(f'Running the diffusion algorithm.')
 

tests/test_input.py

@@ -19,95 +19,95 @@ class ValidateTest(unittest.TestCase):
     """Test validation of results."""
 
     def test_quantitative_bin_id(self):
-        """Test codify input for quantitative scoring methods- only entity IDs given (binary labels)."""
+        """Test codify label_input for quantitative scoring methods- only entity IDs given (binary labels)."""
         input = NODE_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=True, absolute_value=True, p_value=0.05, threshold=None,
         )
         self.assertEqual(input_labels_dict, {'A': 1, 'B': 1, 'C': 1, 'D': 1, 'E': 1})
 
     def test_quantitative_bin_fc_sign(self):
-        """Test codify input for quantitative scoring methods- logFC given (binary, signed labels)."""
+        """Test codify label_input for quantitative scoring methods- logFC given (binary, signed labels)."""
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=True, absolute_value=False, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 1, 'B': 1, 'C': 0, 'D': 0, 'E': -1})
 
     def test_quantitative_bin_fc_abs(self):
-        """Test codify input for quantitative scoring methods- logFC given (binary, absolute values)."""
+        """Test codify label_input for quantitative scoring methods- logFC given (binary, absolute values)."""
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=True, absolute_value=True, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 1, 'B': 1, 'C': 0, 'D': 0, 'E': 1})
 
     def test_quantitative_bin_fcp_sign(self):
-        """Test codify input for quantitative scoring methods- logFC and adj. p-value given (binary, signed labels)."""
+        """Test codify label_input for quantitative scoring methods- logFC and adj. p-value given (binary, signed labels)."""
         input = NODE_LOGFC_PVAL_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=True, absolute_value=False, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0, 'B': 1, 'C': 0, 'D': 0, 'E': -1})
 
     def test_quantitative_bin_fcp_abs(self):
-        """Test codify input for quant. scoring methods- logFC and adj. p-value given (binary, absolute values)."""
+        """Test codify label_input for quant. scoring methods- logFC and adj. p-value given (binary, absolute values)."""
         input = NODE_LOGFC_PVAL_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=True, absolute_value=True, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0, 'B': 1, 'C': 0, 'D': 0, 'E': 1})
 
     def test_quantitative_fc_sign(self):
-        """Test codify input for quantitative scoring methods- logFC given (quantitative, signed labels)."""
+        """Test codify label_input for quantitative scoring methods- logFC given (quantitative, signed labels)."""
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=False, absolute_value=False, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0.7, 'B': 1.2, 'C': 0, 'D': 0, 'E': -2.2})
 
     def test_quantitative_fc_abs(self):
-        """Test codify input for quantitative scoring methods- logFC given (quant., absolute values)."""
+        """Test codify label_input for quantitative scoring methods- logFC given (quant., absolute values)."""
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=False, absolute_value=True, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0.7, 'B': 1.2, 'C': 0, 'D': 0, 'E': 2.2})
 
     def test_quantitative_fcp_sign(self):
-        """Test codify input for quantitative scoring methods- logFC and adj. p-value given (quant., signed labels)."""
+        """Test codify label_input for quantitative scoring methods- logFC and adj. p-value given (quant., signed labels)."""
         input = NODE_LOGFC_PVAL_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=False, absolute_value=False, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0, 'B': 1.2, 'C': 0, 'D': 0, 'E': -2.2})
 
     def test_quantitative_fcp_abs(self):
-        """Test codify input for quant. scoring methods- logFC and adj. p-value given (quant., absolute values)."""
+        """Test codify label_input for quant. scoring methods- logFC and adj. p-value given (quant., absolute values)."""
         input = NODE_LOGFC_PVAL_TEST_PATH
         input_labels_dict = process_input(
             input, method=RAW, binning=False, absolute_value=True, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 0, 'B': 1.2, 'C': 0, 'D': 0, 'E': 2.2})
 
     def test_non_quantitative_bin_id(self):
-        """Test codify input for non-quantitative scoring methods- only entity IDs given (binary labels)."""
+        """Test codify label_input for non-quantitative scoring methods- only entity IDs given (binary labels)."""
         input = NODE_TEST_PATH
         input_labels_dict = process_input(
             input, method=ML, binning=True, absolute_value=True, p_value=0.05, threshold=None,
         )
         self.assertEqual(input_labels_dict, {'A': 1, 'B': 1, 'C': 1, 'D': 1, 'E': 1})
 
     def test_non_quantitative_bin_fc_abs(self):
-        """Test codify input for non-quantitative scoring methods- logFC given (binary, absolute values (sign))."""
+        """Test codify label_input for non-quantitative scoring methods- logFC given (binary, absolute values (sign))."""
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(
             input, method=ML, binning=True, absolute_value=True, p_value=0.05, threshold=0.5,
         )
         self.assertEqual(input_labels_dict, {'A': 1, 'B': 1, 'C': -1, 'D': -1, 'E': 1})
 
     def test_non_quantitative_bin_fcp_abs(self):
-        """Test codify input for non-quant. scoring methods- logFC and adj. p-value given (binary, absolute values)."""
+        """Test codify label_input for non-quant. scoring methods- logFC and adj. p-value given (binary, absolute values)."""
         input = NODE_LOGFC_PVAL_TEST_PATH
         input_labels_dict = process_input(
             input, method=ML, binning=True, absolute_value=True, p_value=0.05, threshold=0.5,
@@ -135,7 +135,7 @@ def test_network(self):
         })
 
     def test_node_mapping(self):
-        """Test mapping of nodes in input to nodes in network"""
+        """Test mapping of nodes in label_input to nodes in network"""
 
         input = NODE_LOGFC_TEST_PATH
         input_labels_dict = process_input(