more pep8 fixes

pydl/pydlutils/bspline/cholesky_band.py

@@ -1,7 +1,8 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
 from __future__ import print_function
-#
+
+
 def cholesky_band(l,mininf=0.0,verbose=False):
     """Compute Cholesky decomposition of banded matrix.
 

pydl/pydlutils/bspline/cholesky_solve.py

@@ -1,5 +1,7 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
+
+
 def cholesky_solve(a,bb):
     """Solve the equation Ax=b where A is a Cholesky-banded matrix.
 

pydl/pydlutils/bspline/tests/test_iterfit.py

@@ -1,5 +1,7 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
+
+
 def test_iterfit():
     import numpy as np
     from .. import iterfit
@@ -27,11 +29,11 @@ def test_iterfit():
     assert y0.size == 100
     y = smooth(y0,10)
     assert y.size == 100
-    x = np.arange(y0.size,dtype='d')
-    sset,outmask = iterfit(x,y,nord=3,maxiter=0,bkspace=10)
+    x = np.arange(y0.size, dtype='d')
+    sset,outmask = iterfit(x, y, nord=3, maxiter=0, bkspace=10)
     assert sset.npoly == 1
     assert sset.funcname == 'legendre'
     # print(sset)
     # yfit,mask = sset.value(x)
     # print(yfit)
-    # pylab.plot(x,y,'k-',x,yfit,'r-')
+    # pylab.plot(x, y, 'k-', x, yfit, 'r-')

pydl/pydlutils/spheregroup/spheregroup.py

@@ -1,7 +1,8 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
 from __future__ import print_function
-#
+
+
 def spheregroup(ra,dec,linklength,chunksize=None):
     """Perform friends-of-friends grouping given ra/dec coordinates.
 

pydl/pydlutils/spheregroup/tests/test_spheregroup.py

@@ -1,5 +1,7 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
+
+
 def test_spheregroup(recwarn):
     import numpy as np
     from astropy.tests.helper import raises
@@ -51,10 +53,10 @@ def test_spheregroup(recwarn):
     # Exceptions
     #
     with raises(PydlutilsException):
-        group = spheregroup(np.array([137.0]),np.array([55.0]),linklength)
+        group = spheregroup(np.array([137.0]), np.array([55.0]), linklength)
     #
     # warnings
     #
-    group = spheregroup(ra,dec,linklength,chunksize=linklength)
+    group = spheregroup(ra, dec, linklength, chunksize=linklength)
     w = recwarn.pop(PydlutilsUserWarning)
     assert "chunksize changed to" in str(w.message)

pydl/pydlutils/spheregroup/tests/test_spherematch.py

@@ -1,19 +1,21 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
+
+
 def test_spherematch():
     import numpy as np
     from .. import spherematch
-    i1_should_be = np.array([17,  0,  2, 16, 12, 13,  1,  5, 15,  7,
-                             19,  8, 11, 10, 14, 18,  3,  9,  6,  4])
-    i2_should_be = np.array([ 2,  0, 17,  3, 16, 15, 14,  5,  6, 10,
-                              8, 19, 18,  4,  9,  7, 11, 12,  1, 13])
+    i1_should_be = np.array([17, 0, 2, 16, 12, 13, 1, 5, 15, 7,
+                             19, 8, 11, 10, 14, 18, 3, 9, 6, 4])
+    i2_should_be = np.array([2, 0, 17, 3, 16, 15, 14, 5, 6, 10,
+                             8, 19, 18, 4, 9, 7, 11, 12, 1, 13])
     np.random.seed(137)
     searchrad = 3.0/3600.0
     n = 20
     ra1 = 360.0*np.random.random((n,))
     dec1 = 90.0 - np.rad2deg(np.arccos(2.0*np.random.random((n,)) - 1.0))
-    ra2 = ra1 + np.random.normal(0,1.0/3600.0)
-    dec2 = dec1 + np.random.normal(0,1.0/3600.0)
+    ra2 = ra1 + np.random.normal(0, 1.0/3600.0)
+    dec2 = dec1 + np.random.normal(0, 1.0/3600.0)
     foo = np.arange(n)
     np.random.shuffle(foo)
     i1, i2, d12 = spherematch(ra1, dec1, ra2[foo], dec2[foo], searchrad,

pydl/pydlutils/tests/test_mangle.py

@@ -4,6 +4,7 @@
 from astropy.tests.helper import raises
 from ..mangle import is_cap_used
 
+
 class TestMangle(object):
     """Test the functions in pydl.pydlutils.mangle.
     """

pydl/pydlutils/tests/test_math.py

@@ -25,8 +25,8 @@ def test_computechi2(self):
             1.30800, 0.507725, 1.12840, 0.955025, 1.35925,
             1.10126, 1.45690, 0.575700, 0.949710, 1.23368,
             0.536489, 0.772543, 0.957729, 0.883976, 1.11559])
-        templates = np.vstack((np.ones((20,),dtype='d'),x)).transpose()
-        chi2 = computechi2(y,sqivar,templates)
+        templates = np.vstack((np.ones((20,), dtype='d'), x)).transpose()
+        chi2 = computechi2(y, sqivar, templates)
         #
         # 20 data points, 2 parameters = 18 degrees of freedom.
         #
@@ -47,57 +47,57 @@ def test_djs_median(self):
         data2 = 100.0*np.random.random((10, 10))
         data3 = 100.0*np.random.random((10, 10, 10))
         data_width_5 = np.array([
-            49.68311576,  74.83671757,  49.68311576,  42.12573137,
-            32.11576752,  27.22092569,  15.08905903,  15.08905903,
-            27.22092569,  20.07809411,  41.55978953,  41.55978953,
-            35.01184343,  35.01184343,  38.7967727 ,  38.7967727 ,
-            38.7967727 ,  38.7967727 ,  38.7967727 ,  28.85780425,
-            28.85780425,  30.23801035,  30.23801035,  27.0687078 ,
-            30.23801035,  64.77058052,  29.42407045,  38.51749618,
-            62.48793217,  38.51749618,  29.42407045,  38.51749618,
-            18.46919414,  18.46919414,  42.72395431,  54.11584807,
-            54.11584807,  75.67593452,  75.67593452,  72.4380356 ,
-            61.68761955,  61.68761955,  45.36796557,  45.36796557,
-            61.68761955,  76.57621138,  76.57621138,  76.57621138,
-            23.28589488,  23.28589488,  13.82755909,  12.10607597,
-            13.82755909,  27.51891089,  44.21266068,  44.21266068,
-            44.21266068,  47.18083025,  47.18083025,  47.18083025,
-            47.18083025,  47.18083025,  35.50809933,  35.50809933,
-            25.52222293,  25.52222293,  67.8568479 ,  88.54983822,
-            67.8568479 ,  93.40053148,  93.40053148,  64.12514945,
-            47.82074715,  47.82074715,  47.82074715,  34.82234113,
-            34.82234113,  52.91092248,  78.51075522,  92.16442338,
-            92.16442338,  92.16442338,  72.07989558,  72.07989558,
-            68.72579501,  72.07989558,  72.07989558,  70.43134908,
-            34.55273356,  62.09010468,  62.09010468,  70.43134908,
-            68.89705132,  68.89705132,  68.89705132,  66.30426084,
-            55.92748086,  55.92748086,  55.92748086,  65.11387444])
+            49.68311576, 74.83671757, 49.68311576, 42.12573137,
+            32.11576752, 27.22092569, 15.08905903, 15.08905903,
+            27.22092569, 20.07809411, 41.55978953, 41.55978953,
+            35.01184343, 35.01184343, 38.7967727,  38.7967727,
+            38.7967727,  38.7967727,  38.7967727,  28.85780425,
+            28.85780425, 30.23801035, 30.23801035, 27.0687078,
+            30.23801035, 64.77058052, 29.42407045, 38.51749618,
+            62.48793217, 38.51749618, 29.42407045, 38.51749618,
+            18.46919414, 18.46919414, 42.72395431, 54.11584807,
+            54.11584807, 75.67593452, 75.67593452, 72.4380356,
+            61.68761955, 61.68761955, 45.36796557, 45.36796557,
+            61.68761955, 76.57621138, 76.57621138, 76.57621138,
+            23.28589488, 23.28589488, 13.82755909, 12.10607597,
+            13.82755909, 27.51891089, 44.21266068, 44.21266068,
+            44.21266068, 47.18083025, 47.18083025, 47.18083025,
+            47.18083025, 47.18083025, 35.50809933, 35.50809933,
+            25.52222293, 25.52222293, 67.8568479,  88.54983822,
+            67.8568479,  93.40053148, 93.40053148, 64.12514945,
+            47.82074715, 47.82074715, 47.82074715, 34.82234113,
+            34.82234113, 52.91092248, 78.51075522, 92.16442338,
+            92.16442338, 92.16442338, 72.07989558, 72.07989558,
+            68.72579501, 72.07989558, 72.07989558, 70.43134908,
+            34.55273356, 62.09010468, 62.09010468, 70.43134908,
+            68.89705132, 68.89705132, 68.89705132, 66.30426084,
+            55.92748086, 55.92748086, 55.92748086, 65.11387444])
         data_width_5_reflect = np.array([
-            49.68311576,  49.68311576,  49.68311576,  42.12573137,
-            32.11576752,  27.22092569,  15.08905903,  15.08905903,
-            27.22092569,  20.07809411,  41.55978953,  41.55978953,
-            35.01184343,  35.01184343,  38.7967727 ,  38.7967727 ,
-            38.7967727 ,  38.7967727 ,  38.7967727 ,  28.85780425,
-            28.85780425,  30.23801035,  30.23801035,  27.0687078 ,
-            30.23801035,  64.77058052,  29.42407045,  38.51749618,
-            62.48793217,  38.51749618,  29.42407045,  38.51749618,
-            18.46919414,  18.46919414,  42.72395431,  54.11584807,
-            54.11584807,  75.67593452,  75.67593452,  72.4380356 ,
-            61.68761955,  61.68761955,  45.36796557,  45.36796557,
-            61.68761955,  76.57621138,  76.57621138,  76.57621138,
-            23.28589488,  23.28589488,  13.82755909,  12.10607597,
-            13.82755909,  27.51891089,  44.21266068,  44.21266068,
-            44.21266068,  47.18083025,  47.18083025,  47.18083025,
-            47.18083025,  47.18083025,  35.50809933,  35.50809933,
-            25.52222293,  25.52222293,  67.8568479 ,  88.54983822,
-            67.8568479 ,  93.40053148,  93.40053148,  64.12514945,
-            47.82074715,  47.82074715,  47.82074715,  34.82234113,
-            34.82234113,  52.91092248,  78.51075522,  92.16442338,
-            92.16442338,  92.16442338,  72.07989558,  72.07989558,
-            68.72579501,  72.07989558,  72.07989558,  70.43134908,
-            34.55273356,  62.09010468,  62.09010468,  70.43134908,
-            68.89705132,  68.89705132,  68.89705132,  55.92748086,
-            65.11387444,  55.92748086,  55.92748086,  55.92748086])
+            49.68311576, 49.68311576, 49.68311576, 42.12573137,
+            32.11576752, 27.22092569, 15.08905903, 15.08905903,
+            27.22092569, 20.07809411, 41.55978953, 41.55978953,
+            35.01184343, 35.01184343, 38.7967727,  38.7967727,
+            38.7967727,  38.7967727,  38.7967727,  28.85780425,
+            28.85780425, 30.23801035, 30.23801035, 27.0687078,
+            30.23801035, 64.77058052, 29.42407045, 38.51749618,
+            62.48793217, 38.51749618, 29.42407045, 38.51749618,
+            18.46919414, 18.46919414, 42.72395431, 54.11584807,
+            54.11584807, 75.67593452, 75.67593452, 72.4380356,
+            61.68761955, 61.68761955, 45.36796557, 45.36796557,
+            61.68761955, 76.57621138, 76.57621138, 76.57621138,
+            23.28589488, 23.28589488, 13.82755909, 12.10607597,
+            13.82755909, 27.51891089, 44.21266068, 44.21266068,
+            44.21266068, 47.18083025, 47.18083025, 47.18083025,
+            47.18083025, 47.18083025, 35.50809933, 35.50809933,
+            25.52222293, 25.52222293, 67.8568479,  88.54983822,
+            67.8568479,  93.40053148, 93.40053148, 64.12514945,
+            47.82074715, 47.82074715, 47.82074715, 34.82234113,
+            34.82234113, 52.91092248, 78.51075522, 92.16442338,
+            92.16442338, 92.16442338, 72.07989558, 72.07989558,
+            68.72579501, 72.07989558, 72.07989558, 70.43134908,
+            34.55273356, 62.09010468, 62.09010468, 70.43134908,
+            68.89705132, 68.89705132, 68.89705132, 55.92748086,
+            65.11387444, 55.92748086, 55.92748086, 55.92748086])
         #
         # Degenerate cases that fall back on numpy.median().
         #
@@ -129,6 +129,6 @@ def test_djs_median(self):
         with raises(ValueError):
             foo = djs_median(data3, width=5, boundary='reflect')
 
-
     def test_find_contiguous(self):
-        assert find_contiguous(np.array([0,1,1,1,0,1,1,0,1])) == [1,2,3]
+        assert (find_contiguous(np.array([0, 1, 1, 1, 0, 1, 1, 0, 1])) ==
+                [1, 2, 3])

pydl/pydlutils/tests/test_sdss.py

@@ -8,6 +8,7 @@
                     sdss_flagval, set_maskbits, sdss_astrombad,
                     sdss_objid)
 
+
 class TestSDSS(object):
     """Test the functions in pydl.pydlutils.sdss.
     """

pydl/pydlutils/tests/test_trace.py

@@ -1,7 +1,7 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 # -*- coding: utf-8 -*-
 import numpy as np
-from os.path import dirname,join
+from os.path import dirname, join
 from astropy.io import fits
 from astropy.tests.helper import raises
 from ..trace import (fchebyshev, fchebyshev_split, fpoly, func_fit,
@@ -235,7 +235,7 @@ def test_traceset_sdss(self):
         assert tset.xRange == tset.xmax - tset.xmin
         assert tset.nx == int(tset.xmax - tset.xmin + 1)
         assert tset.xmid == 0.5 * (tset.xmin + tset.xmax)
-        x,y = traceset2xy(tset)
+        x, y = traceset2xy(tset)
         tset2 = xy2traceset(x, y, ncoeff=tset.ncoeff)
         assert tset2.xmin == tset.xmin
         assert tset2.xmax == tset.xmax
@@ -250,7 +250,7 @@ def test_traceset_boss(self):
         assert tset.xRange == tset.xmax - tset.xmin
         assert tset.nx == int(tset.xmax - tset.xmin + 1)
         assert tset.xmid == 0.5 * (tset.xmin + tset.xmax)
-        x,y = traceset2xy(tset)
+        x, y = traceset2xy(tset)
         tset2 = xy2traceset(x, y, ncoeff=tset.ncoeff,
                             xjumplo=tset.xjumplo,
                             xjumphi=tset.xjumphi,