Add functional test using planetary rover sample data. (#14)

pytest.ini

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+[pytest]
+markers =
+    functional: Functional test

test/test_planetary.py

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+#!/usr/bin/env python
+# Functional tests with planetary science data.
+# Inspired by Gary's PDSC functional tests, e.g.:
+# https://github-fn.jpl.nasa.gov/COSMIC/COSMIC_PDSC/blob/master/test/test_ingest.py
+#
+# Kiri Wagstaff
+# 8/19/21
+
+import os
+import shutil
+import pytest
+from unittest import TestCase
+from dora_exp_pipeline.dora_exp import start
+from test_utils import check_results
+
+@pytest.mark.functional
+class TestPlanetary(TestCase):
+
+    def setUp(self):
+
+        self.outdir = '/tmp/dora/test/planetary'
+        if not os.path.exists(self.outdir):
+            os.makedirs(self.outdir)
+
+    def test_run(self):
+
+        config_file = 'sample_data/planetary_rover/png/exp/navcam.config'
+
+        # Run the experiment; also tests ability to parse config file
+        start(config_file, self.outdir)
+
+        # Check results for each algorithm
+        for file_base in ['demud-k=5/selections-demud.csv',
+                          'iforest/selections-iforest.csv',
+                          'negative_sampling-percent_increase=20/selections-negative_sampling.csv',
+                          'pca-k=5/selections-pca.csv'
+                          ]:
+            correct_file = 'test/ref-results/planetary_rover/%s' % file_base
+            output_file = '%s/%s' % (self.outdir, file_base)
+
+            # Check results against correct output
+            assert(check_results(output_file, correct_file))
+
+    def tearDown(self):
+        # Remove any intermediate files
+        shutil.rmtree(self.outdir)

test/test_utils.py

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+# Helper functions for pytests
+import numpy as np
+
+def read_selections(f):
+
+    sels = []
+
+    with open(f, 'r') as inf:
+        for l in inf:
+            if l[0] == '#':
+                continue
+            sels += [l.split(',')[2].split('.')[0]] # name excluding extension
+
+    return sels
+
+
+def read_selections_and_scores(f):
+
+    sels = []
+    scores = []
+
+    with open(f, 'r') as inf:
+        for l in inf:
+            if l[0] == '#':
+                continue
+            # Get the image filename and numeric score
+            vals = l.split(',')[2:4]
+            sels += [vals[0].split('.')[0]]  # exclude extension
+            scores += [float(vals[1])]  # convert score to float
+
+    return sels, scores
+
+
+def check_results(outfile, correct_file):
+
+    sels, scores = read_selections_and_scores(outfile)
+    correct_sels, correct_scores = read_selections_and_scores(correct_file)
+
+    # Check the selections by name
+    if sels != correct_sels:
+        return False
+
+    # Check the numeric scores
+    return np.isclose(scores, correct_scores, atol=1e-6).all()
+
+