in progress of testing

test/evaluate/expected/expected-node-ensemble.csv

@@ -0,0 +1,13 @@
+Node	max_freq
+C	0.75
+E	0.75
+D	0.75
+F	0.75
+A	0.5
+B	0.5
+L	0.5
+M	0.5
+O	0.25
+P	0.25
+N	0.25
+Q	0.25

test/evaluate/input/ensemble-network.tsv

@@ -0,0 +1,10 @@
+Node1	Node2	Frequency	Direction
+A	B	0.5	U
+C	D	0.75	U
+E	F	0.75	U
+L	M	0.5	U
+M	N	0.25	U
+O	P	0.25	U
+P	Q	0.25	U
+A	B	0.25	D
+B	A	0.25	D

test/evaluate/test_evaluate.py

@@ -0,0 +1,36 @@
+import filecmp
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+from spras.evaluation import Evaluation
+
+INPUT_DIR = 'test/evaluate/input/'
+OUT_DIR = 'test/evaluate/output/'
+EXPECT_DIR = 'test/evaluate/expected/'
+
+
+class TestEvaluate:
+    @classmethod
+    def setup_class(cls):
+        """
+        Create the expected output directory
+        """
+        Path(OUT_DIR).mkdir(parents=True, exist_ok=True)
+
+    def test_node_ensemble(self):
+        ensemble_file = INPUT_DIR + 'ensemble-network.tsv'
+        edge_freq = Evaluation.edge_frequency_node_ensemble(ensemble_file)
+        edge_freq.to_csv(OUT_DIR + 'node-ensemble.csv', sep="\t", index=False)
+        assert filecmp.cmp(OUT_DIR + 'node-ensemble.csv', EXPECT_DIR + 'expected-node-ensemble.csv', shallow=False)
+
+    def test_PRC_node_ensemble(self):
+        None
+
+    def test_precision_and_recall(self):
+        None
+
+    def test_pca_chosen_pathway(self):
+        None
+