boosting coverage by testing main

Author: chrispycheng

nibabel/cmdline/diff.py

@@ -161,29 +161,38 @@ def display_diff(files, diff):
     return output
 
 
-def main():
+def main(args=None):
     """Getting the show on the road"""
+    try:
+        parser = get_opt_parser()
+        (opts, files) = parser.parse_args()
 
-    parser = get_opt_parser()
-    (opts, files) = parser.parse_args()
+        nibabel.cmdline.utils.verbose_level = opts.verbose
 
-    nibabel.cmdline.utils.verbose_level = opts.verbose
+        if nibabel.cmdline.utils.verbose_level < 3:
+            # suppress nibabel format-compliance warnings
+            nib.imageglobals.logger.level = 50
 
-    assert len(files) >= 2, "Please enter at least two files"
+    except SystemExit:
+        opts = None
+        files = None
+
+    if args:
+        files = args
 
-    if nibabel.cmdline.utils.verbose_level < 3:
-        # suppress nibabel format-compliance warnings
-        nib.imageglobals.logger.level = 50
+    assert len(files) >= 2, "Please enter at least two files"
 
     file_headers = [nib.load(f).header for f in files]
 
-    if opts.header_fields:  # will almost always have a header field
+    if opts:  # will almost always have a header field
         # signals "all fields"
         if opts.header_fields == 'all':
             # TODO: header fields might vary across file types, thus prior sensing would be needed
             header_fields = file_headers[0].keys()
         else:
             header_fields = opts.header_fields.split(',')
+    else:
+        header_fields = file_headers[0].keys()
 
     diff = get_headers_diff(file_headers, header_fields)
     data_diff = get_data_md5sums(files)
@@ -192,8 +201,11 @@ def main():
         diff['DATA(md5)'] = data_diff
 
     if diff:
-        sys.stdout.write(display_diff(files, diff))
-        raise SystemExit(1)
+        if opts:
+            sys.stdout.write(display_diff(files, diff))
+            raise SystemExit(1)
+        else:
+            return diff  # this functionality specifically for testing main
 
     else:
         print("These files are identical.")

nibabel/cmdline/tests/test_utils.py

@@ -6,11 +6,12 @@
 """
 
 from nose.tools import assert_equal
+from numpy.testing import assert_raises
 
 import nibabel as nib
 import numpy as np
 from nibabel.cmdline.utils import *
-from nibabel.cmdline.diff import get_headers_diff, display_diff
+from nibabel.cmdline.diff import get_headers_diff, display_diff, main
 from os.path import (join as pjoin)
 from nibabel.testing import data_path
 from collections import OrderedDict
@@ -106,3 +107,44 @@ def test_display_diff():
                                                        "\n"
 
     assert_equal(display_diff(bogus_names, dict_values), expected_output)
+
+
+def test_main():
+    test_names = [pjoin(data_path, f)
+              for f in ('standard.nii.gz', 'example4d.nii.gz')]
+    expected_difference = OrderedDict([
+        ("regular", [np.asarray("".encode("utf-8")), np.asarray("r".encode("utf-8"))]),
+        ("dim_info", [np.asarray(0).astype(dtype="uint8"), np.asarray(57).astype(dtype="uint8")]),
+        ("dim", [np.array([3, 4, 5, 7, 1, 1, 1, 1]).astype(dtype="int16"),
+                 np.array([4, 128, 96, 24, 2, 1, 1, 1]).astype(dtype="int16")]),
+        ("datatype", [np.array(2).astype(dtype="uint8"), np.array(4).astype(dtype="uint8")]),
+        ("bitpix", [np.array(8).astype(dtype="uint8"), np.array(16).astype(dtype="uint8")]),
+        ("pixdim", [np.array([1., 1., 3., 2., 1., 1., 1., 1.]).astype(dtype="float32"), np.array(
+            [-1.00000000e+00, 2.00000000e+00, 2.00000000e+00, 2.19999909e+00, 2.00000000e+03, 1.00000000e+00,
+             1.00000000e+00, 1.00000000e+00]).astype(dtype="float32")]),
+        ("slice_end", [np.array(0).astype(dtype="uint8"), np.array(23).astype(dtype="uint8")]),
+        ("xyzt_units", [np.array(0).astype(dtype="uint8"), np.array(10).astype(dtype="uint8")]),
+        ("cal_max", [np.array(0.0).astype(dtype="float32"), np.asarray(1162.0).astype(dtype="float32")]),
+        ("descrip", [np.array("".encode("utf-8")).astype(dtype="S80"),
+                     np.array("FSL3.3\x00 v2.25 NIfTI-1 Single file format".encode("utf-8")).astype(dtype="S80")]),
+        ("qform_code", [np.array(0).astype(dtype="int16"), np.array(1).astype(dtype="int16")]),
+        ("sform_code", [np.array(2).astype(dtype="int16"), np.array(1).astype(dtype="int16")]),
+        ("quatern_b", [np.array(0.0).astype(dtype="float32"),
+                       np.array(-1.9451068140294884e-26).astype(dtype="float32")]),
+        ("quatern_c", [np.array(0.0).astype(dtype="float32"), np.array(-0.9967085123062134).astype(dtype="float32")]),
+        ("quatern_d", [np.array(0.0).astype(dtype="float32"), np.array(-0.0810687392950058).astype(dtype="float32")]),
+        ("qoffset_x", [np.array(0.0).astype(dtype="float32"), np.array(117.8551025390625).astype(dtype="float32")]),
+        ("qoffset_y", [np.array(0.0).astype(dtype="float32"), np.array(-35.72294235229492).astype(dtype="float32")]),
+        ("qoffset_z", [np.array(0.0).astype(dtype="float32"), np.array(-7.248798370361328).astype(dtype="float32")]),
+        ("srow_x", [np.array([1., 0., 0., 0.]).astype(dtype="float32"),
+                    np.array([-2.00000000e+00, 6.71471565e-19, 9.08102451e-18,
+                              1.17855103e+02]).astype(dtype="float32")]),
+        ("srow_y", [np.array([0., 3., 0., 0.]).astype(dtype="float32"),
+                    np.array([-6.71471565e-19, 1.97371149e+00, -3.55528235e-01, -3.57229424e+01]).astype(
+                        dtype="float32")]),
+        ("srow_z", [np.array([0., 0., 2., 0.]).astype(dtype="float32"),
+                    np.array([8.25548089e-18, 3.23207617e-01, 2.17108178e+00,
+                              -7.24879837e+00]).astype(dtype="float32")]),
+        ('DATA(md5)', ['0a2576dd6badbb25bfb3b12076df986b', 'b0abbc492b4fd533b2c80d82570062cf'])])
+
+    np.testing.assert_equal(main(test_names), expected_difference)