Update conftest.py

weaverba137 · Dec 15, 2023 · 779f94d · 779f94d
1 parent 94ccf49
commit 779f94d
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diff --git a/.github/workflows/ci_workflows.yml b/.github/workflows/ci_workflows.yml
@@ -25,7 +25,7 @@ jobs:
             python: 3.x
             toxenv: codestyle
 
-          - name: Code style checks
+          - name: Documentation build check
             os: ubuntu-latest
             python: 3.x
             toxenv: build_docs

diff --git a/conftest.py b/conftest.py
@@ -0,0 +1,22 @@
+try:
+    from pytest_astropy_header.display import PYTEST_HEADER_MODULES, TESTED_VERSIONS
+    ASTROPY_HEADER = True
+except ImportError:
+    ASTROPY_HEADER = False
+
+
+# Repeat this from specutils/conftest.py so tox picks it up.
+def pytest_configure(config):
+
+    if ASTROPY_HEADER:
+        config.option.astropy_header = True
+
+        # Customize the following lines to add/remove entries from the list of
+        # packages for which version numbers are displayed when running the tests.
+        PYTEST_HEADER_MODULES.pop('Pandas', None)
+        PYTEST_HEADER_MODULES.pop('h5py', None)
+        PYTEST_HEADER_MODULES['Astropy'] = 'astropy'
+        PYTEST_HEADER_MODULES['PyDL'] = 'pydl'
+
+        from pydl import __version__
+        TESTED_VERSIONS['pydl'] = __version__
diff --git a/pydl/conftest.py b/pydl/conftest.py
@@ -7,9 +7,9 @@
 
 """
 
-import os
+# import os
 
-from astropy.version import version as astropy_version
+# from astropy.version import version as astropy_version
 
 try:
     from pytest_astropy_header.display import PYTEST_HEADER_MODULES, TESTED_VERSIONS
@@ -38,5 +38,4 @@ def pytest_configure(config):
         PYTEST_HEADER_MODULES['PyDL'] = 'pydl'
 
         from . import __version__
-        packagename = os.path.basename(os.path.dirname(__file__))
-        TESTED_VERSIONS[packagename] = __version__
+        TESTED_VERSIONS['pydl'] = __version__
diff --git a/pydl/pydlutils/tests/test_bspline.py b/pydl/pydlutils/tests/test_bspline.py
@@ -44,11 +44,11 @@ def test_iterfit():
 
 
 def test_cholesky_band():
-    ab = np.array([[ 8.,  9., 10., 11., 12., 13., 14., 0., 0., 0.],
-                   [ 1.,  2.,  3.,  4.,  5.,  6.,  0., 0., 0., 0.],
-                   [ 1.,  2.,  3.,  4.,  5.,  0.,  0., 0., 0., 0.]])
-    l = np.array([[2.82842712, 2.97909382, 3.07877788, 3.1382224,  3.16559183, 3.16295604, 3.12782377, 0., 0., 0.],
-                  [0.35355339, 0.62938602, 0.8371714,  1.01466666, 1.17093392, 1.31223108, 0., 0., 0., 0.],
+    ab = np.array([[ 8., 9., 10., 11., 12., 13., 14., 0., 0., 0.],
+                   [ 1., 2., 3., 4., 5., 6., 0., 0., 0., 0.],
+                   [ 1., 2., 3., 4., 5., 0., 0., 0., 0., 0.]])
+    l = np.array([[2.82842712, 2.97909382, 3.07877788, 3.1382224, 3.16559183, 3.16295604, 3.12782377, 0., 0., 0.],
+                  [0.35355339, 0.62938602, 0.8371714, 1.01466666, 1.17093392, 1.31223108, 0., 0., 0., 0.],
                   [0.35355339, 0.67134509, 0.97441261, 1.27460692, 1.57948348, 0., 0., 0., 0., 0.]])
     i, ll = cholesky_band(ab)
     assert np.allclose(l, ll)
@@ -65,8 +65,8 @@ def test_cholesky_band():
 
 
 def test_cholesky_solve():
-    l = np.array([[2.82842712, 2.97909382, 3.07877788, 3.1382224,  3.16559183, 3.16295604, 3.12782377, 0., 0., 0.],
-                  [0.35355339, 0.62938602, 0.8371714,  1.01466666, 1.17093392, 1.31223108, 0., 0., 0., 0.],
+    l = np.array([[2.82842712, 2.97909382, 3.07877788, 3.1382224, 3.16559183, 3.16295604, 3.12782377, 0., 0., 0.],
+                  [0.35355339, 0.62938602, 0.8371714, 1.01466666, 1.17093392, 1.31223108, 0., 0., 0., 0.],
                   [0.35355339, 0.67134509, 0.97441261, 1.27460692, 1.57948348, 0., 0., 0., 0., 0.]])
     b = np.ones((10,), dtype=l.dtype)
     xx = np.array([0.10848432, 0.07752049, 0.05460496, 0.04231068, 0.02116434, 0.03276732, 0.04982674, 0., 0., 0.])

diff --git a/pydl/pydlutils/trace.py b/pydl/pydlutils/trace.py
@@ -205,16 +205,14 @@ def func_fit(x, y, ncoeff, invvar=None, function_name='legendre', ia=None,
         yfit += y[igood[0]]
     else:
         ncfit = min(ngood, ncoeff)
-        function_map = {
-            'legendre': flegendre,
-            'flegendre': flegendre,
-            'chebyshev': fchebyshev,
-            'fchebyshev': fchebyshev,
-            'chebyshev_split': fchebyshev_split,
-            'fchebyshev_split': fchebyshev_split,
-            'poly': fpoly,
-            'fpoly': fpoly
-            }
+        function_map = {'legendre': flegendre,
+                        'flegendre': flegendre,
+                        'chebyshev': fchebyshev,
+                        'fchebyshev': fchebyshev,
+                        'chebyshev_split': fchebyshev_split,
+                        'fchebyshev_split': fchebyshev_split,
+                        'poly': fpoly,
+                        'fpoly': fpoly}
         try:
             legarr = function_map[function_name](x, ncfit)
         except KeyError:

diff --git a/pydl/pydlutils/yanny.py b/pydl/pydlutils/yanny.py
@@ -817,7 +817,8 @@ def new_dict_from_pairs(self):
 
             >>> from os.path import dirname
             >>> from pydl.pydlutils.yanny import yanny
-            >>> new_dict = yanny(dirname(__file__)+'/tests/t/test.par').new_dict_from_pairs()
+            >>> y = yanny(dirname(__file__)+'/tests/t/test.par')
+            >>> new_dict = y.new_dict_from_pairs()
             >>> new_dict['mjd']
             '54579'
             >>> new_dict['alpha']
@@ -835,12 +836,13 @@ def write(self, newfile=None, comments=None):
 
         This assumes that the filename used to create the object was not that
         of a pre-existing file.  If a file of the same name is detected,
-        this method will *not* attempt to overwrite it, but will print a warning.
-        This also assumes that the special 'symbols' key has been properly
-        created.  This will not necessarily make the file very human-readable,
-        especially if the data lines are long.  If the name of a new file is
-        given, it will write to the new file (assuming it doesn't exist).
-        If the writing is successful, the data in the object will be updated.
+        this method will *not* attempt to overwrite it, but will print a
+        warning. This also assumes that the special 'symbols' key has been
+        properly created.  This will not necessarily make the file very
+        human-readable, especially if the data lines are long. If the name of a
+        new file is given, it will write to the new file (assuming it doesn't
+        exist). If the writing is successful, the data in the object will be
+        updated.
 
         Parameters
         ----------
@@ -865,7 +867,14 @@ def write(self, newfile=None, comments=None):
             basefile = os.path.basename(newfile)
             timestamp = datetime.datetime.utcnow().strftime(
                         '%Y-%m-%d %H:%M:%S UTC')
-            comments = "#\n# {0}\n#\n# Created by pydl.pydlutils.yanny.yanny\n#\n# {1}\n#\n".format(basefile, timestamp)
+            comments = f"""#
+# {basefile}
+#
+# Created by pydl.pydlutils.yanny.yanny
+#
+# {timestamp}
+#
+"""
         else:
             if isinstance(comments, (str,)):
                 if not comments.startswith('#'):
@@ -997,7 +1006,7 @@ def _parse(self):
 
         Parsing proceeds in this order:
 
-        #. Lines that end with a backslash character ``\`` are reattached
+        #. Lines that end with a backslash character are reattached
            to following lines.
         #. Structure & enum definitions are identified, saved into the
            'symbols' dictionary & stripped from the contents.
@@ -1110,8 +1119,8 @@ def _parse(self):
                             if self.isarray(uckey, column):
                                 #
                                 # An array value
-                                # if it's character data, it won't be
-                                # delimited by {} unless it is a multidimensional
+                                # if it's character data, it won't be delimited
+                                # by {} unless it is a multidimensional
                                 # string array.  It may or may not be delimited
                                 # by double quotes
                                 #
@@ -1159,9 +1168,9 @@ def write_ndarray_to_yanny(filename, datatables, structnames=None,
     ----------
     filename : :class:`str`
         The name of a parameter file.
-    datatables : :class:`numpy.ndarray`, :class:`numpy.recarray` or :class:`list` of these.
+    datatables : :class:`numpy.ndarray`, :class:`numpy.recarray`, :class:`list`
         A NumPy record array containing data that can be copied into a
-        `yanny` object.
+        `yanny` object. A :class:`list` *containing* arrays can also be passed.
     structnames : :class:`str` or :class:`list` of :class:`str`, optional
         The name(s) to give the structure(s) in the yanny file.  Defaults to
         'MYSTRUCT0'.

diff --git a/pydl/tests/test_pydl.py b/pydl/tests/test_pydl.py
@@ -22,8 +22,10 @@ def test_file_lines():
     # Find the test files
     #
     line_numbers = (1, 42, 137)
-    plainfiles = [get_pkg_data_filename('t/this-file-contains-{0:d}-lines.txt'.format(l)) for l in line_numbers]
-    gzfiles = [get_pkg_data_filename('t/this-file-contains-{0:d}-lines.txt.gz'.format(l)) for l in line_numbers]
+    plainfiles = [get_pkg_data_filename('t/this-file-contains-{0:d}-lines.txt'.format(l))
+                  for l in line_numbers]
+    gzfiles = [get_pkg_data_filename('t/this-file-contains-{0:d}-lines.txt.gz'.format(l))
+               for l in line_numbers]
     for i, p in enumerate(plainfiles):
         n = file_lines(p)
         assert n == line_numbers[i]
@@ -55,7 +57,7 @@ def test_median():
     assert median(even_data, even=True) == 6.5
     assert (median(odd_data, 3) == odd_data).all()
     with pytest.raises(ValueError):
-        foo = median(np.ones((9, 9, 9)), 3)
+        _ = median(np.ones((9, 9, 9)), 3)
     odd_data2 = np.vstack((odd_data, odd_data, odd_data, odd_data, odd_data))
     assert (median(odd_data2, 3) == odd_data2).all()
     assert (median(odd_data2, axis=0) == odd_data).all()
@@ -169,36 +171,36 @@ def test_rebin_int():
         IDL> array = FIX(RANDOMN(seed, 10, 20) * 100, TYPE=1) ; UINT8
         IDL> array_rebin = REBIN(array, 5, 10)
     """
-    array = np.array([[188, 186,  25, 212,  34,  98,   3, 235, 155, 148],
-                      [107, 166,   4,  41, 101, 190,  39, 154, 153, 239],
-                      [135, 181,  92, 161, 213, 136,  35,  61,  80, 164],
-                      [123, 248,   8, 157,  96, 118,  99,   1, 109, 246],
-                      [226,  71, 183,  27,  46,  99,   8, 239,  66,  25],
-                      [ 27, 219,  37, 130,   5,  81,  65, 250,  96,  14],
-                      [ 71, 157, 156, 136,  47, 225, 247, 191,  49,  12],
-                      [231, 133,   9,  38, 243,   2, 235, 145,  23,  22],
-                      [146,  38,  49,  89,  42,  57, 220, 214, 135,  47],
-                      [101, 116, 122, 209, 141,  37, 158, 224, 245,  82],
-                      [ 15,  47,  51, 250, 207, 193, 209, 228, 110,   1],
-                      [ 59, 232, 216, 224,  24, 118, 190,  10, 107,  27],
-                      [ 84, 193, 112, 206, 113, 171, 138, 117, 244,  20],
-                      [  5,  31, 128, 214, 200, 119,  59,  27,  57,  10],
-                      [226,  71, 177,  85,   0,  68,  54, 207, 141, 250],
-                      [ 52, 119, 121, 177, 165,  99,  68,  29, 137, 200],
-                      [172,  91, 181, 187,  87, 250,  45, 154,  58,  83],
-                      [ 56, 175, 189,  35, 203, 223, 243, 187, 252,  97],
-                      [186, 172, 207, 128,  61, 231,  89,  57, 131, 222],
-                      [206,  96,  29,  60,   3,   8, 221,  55,  60,  17]], dtype=np.uint8)
-    array_rebin = np.array([[161,  70, 105, 107, 173],
-                            [171, 104, 140,  49, 149],
-                            [135,  94,  57, 140,  50],
-                            [148,  84, 129, 204,  26],
-                            [100, 117,  69, 204, 127],
-                            [ 88, 185, 135, 159,  61],
-                            [ 78, 165, 150,  85,  82],
-                            [116, 140,  83,  89, 181],
+    array = np.array([[188, 186, 25, 212, 34, 98, 3, 235, 155, 148],
+                      [107, 166, 4, 41, 101, 190, 39, 154, 153, 239],
+                      [135, 181, 92, 161, 213, 136, 35, 61, 80, 164],
+                      [123, 248, 8, 157, 96, 118, 99, 1, 109, 246],
+                      [226, 71, 183, 27, 46, 99, 8, 239, 66, 25],
+                      [ 27, 219, 37, 130, 5, 81, 65, 250, 96, 14],
+                      [ 71, 157, 156, 136, 47, 225, 247, 191, 49, 12],
+                      [231, 133, 9, 38, 243, 2, 235, 145, 23, 22],
+                      [146, 38, 49, 89, 42, 57, 220, 214, 135, 47],
+                      [101, 116, 122, 209, 141, 37, 158, 224, 245, 82],
+                      [ 15, 47, 51, 250, 207, 193, 209, 228, 110, 1],
+                      [ 59, 232, 216, 224, 24, 118, 190, 10, 107, 27],
+                      [ 84, 193, 112, 206, 113, 171, 138, 117, 244, 20],
+                      [  5, 31, 128, 214, 200, 119, 59, 27, 57, 10],
+                      [226, 71, 177, 85, 0, 68, 54, 207, 141, 250],
+                      [ 52, 119, 121, 177, 165, 99, 68, 29, 137, 200],
+                      [172, 91, 181, 187, 87, 250, 45, 154, 58, 83],
+                      [ 56, 175, 189, 35, 203, 223, 243, 187, 252, 97],
+                      [186, 172, 207, 128, 61, 231, 89, 57, 131, 222],
+                      [206, 96, 29, 60, 3, 8, 221, 55, 60, 17]], dtype=np.uint8)
+    array_rebin = np.array([[161, 70, 105, 107, 173],
+                            [171, 104, 140, 49, 149],
+                            [135, 94, 57, 140, 50],
+                            [148, 84, 129, 204, 26],
+                            [100, 117, 69, 204, 127],
+                            [ 88, 185, 135, 159, 61],
+                            [ 78, 165, 150, 85, 82],
+                            [116, 140, 83, 89, 181],
                             [123, 148, 190, 157, 122],
-                            [165, 105,  75, 105, 107]], dtype=np.uint8)
+                            [165, 105, 75, 105, 107]], dtype=np.uint8)
 
     ar = rebin(array, (10, 5))
     assert (array_rebin == ar).all()
@@ -207,36 +209,36 @@ def test_rebin_int():
 def test_rebin_int_sample():
     """Similar to test_rebin_int(), but using the sample option.
     """
-    array = np.array([[188, 186,  25, 212,  34,  98,   3, 235, 155, 148],
-                      [107, 166,   4,  41, 101, 190,  39, 154, 153, 239],
-                      [135, 181,  92, 161, 213, 136,  35,  61,  80, 164],
-                      [123, 248,   8, 157,  96, 118,  99,   1, 109, 246],
-                      [226,  71, 183,  27,  46,  99,   8, 239,  66,  25],
-                      [ 27, 219,  37, 130,   5,  81,  65, 250,  96,  14],
-                      [ 71, 157, 156, 136,  47, 225, 247, 191,  49,  12],
-                      [231, 133,   9,  38, 243,   2, 235, 145,  23,  22],
-                      [146,  38,  49,  89,  42,  57, 220, 214, 135,  47],
-                      [101, 116, 122, 209, 141,  37, 158, 224, 245,  82],
-                      [ 15,  47,  51, 250, 207, 193, 209, 228, 110,   1],
-                      [ 59, 232, 216, 224,  24, 118, 190,  10, 107,  27],
-                      [ 84, 193, 112, 206, 113, 171, 138, 117, 244,  20],
-                      [  5,  31, 128, 214, 200, 119,  59,  27,  57,  10],
-                      [226,  71, 177,  85,   0,  68,  54, 207, 141, 250],
-                      [ 52, 119, 121, 177, 165,  99,  68,  29, 137, 200],
-                      [172,  91, 181, 187,  87, 250,  45, 154,  58,  83],
-                      [ 56, 175, 189,  35, 203, 223, 243, 187, 252,  97],
-                      [186, 172, 207, 128,  61, 231,  89,  57, 131, 222],
-                      [206,  96,  29,  60,   3,   8, 221,  55,  60,  17]], dtype=np.uint8)
-    array_sample = np.array([[188,  25,  34,   3, 155],
-                             [135,  92, 213,  35,  80],
-                             [226, 183,  46,   8,  66],
-                             [ 71, 156,  47, 247,  49],
-                             [146,  49,  42, 220, 135],
-                             [ 15,  51, 207, 209, 110],
+    array = np.array([[188, 186, 25, 212, 34, 98, 3, 235, 155, 148],
+                      [107, 166, 4, 41, 101, 190, 39, 154, 153, 239],
+                      [135, 181, 92, 161, 213, 136, 35, 61, 80, 164],
+                      [123, 248, 8, 157, 96, 118, 99, 1, 109, 246],
+                      [226, 71, 183, 27, 46, 99, 8, 239, 66, 25],
+                      [ 27, 219, 37, 130, 5, 81, 65, 250, 96, 14],
+                      [ 71, 157, 156, 136, 47, 225, 247, 191, 49, 12],
+                      [231, 133, 9, 38, 243, 2, 235, 145, 23, 22],
+                      [146, 38, 49, 89, 42, 57, 220, 214, 135, 47],
+                      [101, 116, 122, 209, 141, 37, 158, 224, 245, 82],
+                      [ 15, 47, 51, 250, 207, 193, 209, 228, 110, 1],
+                      [ 59, 232, 216, 224, 24, 118, 190, 10, 107, 27],
+                      [ 84, 193, 112, 206, 113, 171, 138, 117, 244, 20],
+                      [  5, 31, 128, 214, 200, 119, 59, 27, 57, 10],
+                      [226, 71, 177, 85, 0, 68, 54, 207, 141, 250],
+                      [ 52, 119, 121, 177, 165, 99, 68, 29, 137, 200],
+                      [172, 91, 181, 187, 87, 250, 45, 154, 58, 83],
+                      [ 56, 175, 189, 35, 203, 223, 243, 187, 252, 97],
+                      [186, 172, 207, 128, 61, 231, 89, 57, 131, 222],
+                      [206, 96, 29, 60, 3, 8, 221, 55, 60, 17]], dtype=np.uint8)
+    array_sample = np.array([[188, 25, 34, 3, 155],
+                             [135, 92, 213, 35, 80],
+                             [226, 183, 46, 8, 66],
+                             [ 71, 156, 47, 247, 49],
+                             [146, 49, 42, 220, 135],
+                             [ 15, 51, 207, 209, 110],
                              [ 84, 112, 113, 138, 244],
-                             [226, 177,   0,  54, 141],
-                             [172, 181,  87,  45,  58],
-                             [186, 207,  61,  89, 131]], dtype=np.uint8)
+                             [226, 177, 0, 54, 141],
+                             [172, 181, 87, 45, 58],
+                             [186, 207, 61, 89, 131]], dtype=np.uint8)
     ars = rebin(array, (10, 5), sample=True)
     assert (array_sample == ars).all()
 

diff --git a/setup.cfg b/setup.cfg
@@ -110,13 +110,11 @@ exclude_lines =
 # E227 missing whitespace around bitwise or shift operator
 # E231 missing whitespace after ','
 # E251 unexpected spaces around keyword / parameter equals
-# E501 line too long
 # E731 do not assign a lambda expression, use a def
 # E741 ambiguous variable name 'l'
 # W503 line break before binary operator
 # W504 line break after binary operator
-# W505 doc line too long
 [flake8]
 max-line-length = 100
 max-doc-length = 79
-ignore = E126,E127,E128,E201,E202,E203,E221,E225,E226,E227,E231,E251,E501,E731,E741,W503,W504,W505
+ignore = E126,E127,E128,E201,E202,E203,E221,E225,E226,E227,E231,E251,E731,E741,W503,W504
diff --git a/tox.ini b/tox.ini
@@ -104,5 +104,5 @@ changedir = .
 description = check code style, e.g. with flake8
 deps = flake8
 commands =
-    -flake8 pydl -qq --statistics --select=E501,W505
+    -flake8 pydl -qq --statistics --select=E126,E127,E128
     flake8 pydl --count