Attempting to fix #144

Corrfunc/io.py

@@ -10,6 +10,10 @@
 from os.path import dirname, abspath, splitext, exists as file_exists,\
     join as pjoin
 import numpy as np
+try:
+    import pandas as pd
+except ImportError:
+    pd = None
 
 
 __all__ = ('read_fastfood_catalog', 'read_ascii_catalog', 'read_catalog')
@@ -220,11 +224,6 @@ def read_ascii_catalog(filename, return_dtype=None):
 
     # check if pandas is available - much faster to read in the data
     # using pandas
-    try:
-        import pandas as pd
-    except ImportError:
-        pd = None
-
     if pd is not None:
         df = pd.read_csv(filename, header=None,
                          engine="c",

Corrfunc/utils.py

@@ -558,7 +558,7 @@ def compute_nbins(max_diff, binsize,
     >>> max_diff = 180
     >>> binsize = 10
     >>> compute_nbins(max_diff, binsize)
-    18
+    18L
     >>> refine_factor=2
     >>> max_nbins = 20
     >>> compute_nbins(max_diff, binsize, refine_factor=refine_factor, 
@@ -680,27 +680,27 @@ def gridlink_sphere(thetamax,
 
     >>> from Corrfunc.utils import gridlink_sphere
     >>> thetamax=30
-    >>> gridlink_sphere(thetamax)
+    >>> gridlink_sphere(thetamax) # doctest: +NORMALIZE_WHITESPACE
     array([([-1.57079633, -1.04719755], [ 0.        ,  3.14159265]),
-       ([-1.57079633, -1.04719755], [ 3.14159265,  6.28318531]),
-       ([-1.04719755, -0.52359878], [ 0.        ,  3.14159265]),
-       ([-1.04719755, -0.52359878], [ 3.14159265,  6.28318531]),
-       ([-0.52359878,  0.        ], [ 0.        ,  1.25663706]),
-       ([-0.52359878,  0.        ], [ 1.25663706,  2.51327412]),
-       ([-0.52359878,  0.        ], [ 2.51327412,  3.76991118]),
-       ([-0.52359878,  0.        ], [ 3.76991118,  5.02654825]),
-       ([-0.52359878,  0.        ], [ 5.02654825,  6.28318531]),
-       ([ 0.        ,  0.52359878], [ 0.        ,  1.25663706]),
-       ([ 0.        ,  0.52359878], [ 1.25663706,  2.51327412]),
-       ([ 0.        ,  0.52359878], [ 2.51327412,  3.76991118]),
-       ([ 0.        ,  0.52359878], [ 3.76991118,  5.02654825]),
-       ([ 0.        ,  0.52359878], [ 5.02654825,  6.28318531]),
-       ([ 0.52359878,  1.04719755], [ 0.        ,  3.14159265]),
-       ([ 0.52359878,  1.04719755], [ 3.14159265,  6.28318531]),
-       ([ 1.04719755,  1.57079633], [ 0.        ,  3.14159265]),
-       ([ 1.04719755,  1.57079633], [ 3.14159265,  6.28318531])], 
+         ([-1.57079633, -1.04719755], [ 3.14159265,  6.28318531]),
+         ([-1.04719755, -0.52359878], [ 0.        ,  3.14159265]),
+         ([-1.04719755, -0.52359878], [ 3.14159265,  6.28318531]),
+         ([-0.52359878,  0.        ], [ 0.        ,  1.25663706]),
+         ([-0.52359878,  0.        ], [ 1.25663706,  2.51327412]),
+         ([-0.52359878,  0.        ], [ 2.51327412,  3.76991118]),
+         ([-0.52359878,  0.        ], [ 3.76991118,  5.02654825]),
+         ([-0.52359878,  0.        ], [ 5.02654825,  6.28318531]),
+         ([ 0.        ,  0.52359878], [ 0.        ,  1.25663706]),
+         ([ 0.        ,  0.52359878], [ 1.25663706,  2.51327412]),
+         ([ 0.        ,  0.52359878], [ 2.51327412,  3.76991118]),
+         ([ 0.        ,  0.52359878], [ 3.76991118,  5.02654825]),
+         ([ 0.        ,  0.52359878], [ 5.02654825,  6.28318531]),
+         ([ 0.52359878,  1.04719755], [ 0.        ,  3.14159265]),
+         ([ 0.52359878,  1.04719755], [ 3.14159265,  6.28318531]),
+         ([ 1.04719755,  1.57079633], [ 0.        ,  3.14159265]),
+         ([ 1.04719755,  1.57079633], [ 3.14159265,  6.28318531])], 
       dtype=[(u'dec_limit', '<f8', (2,)), (u'ra_limit', '<f8', (2,))])
-    >>> gridlink_sphere(60, dec_refine_factor=3, ra_refine_factor=2)
+    >>> gridlink_sphere(60, dec_refine_factor=3, ra_refine_factor=2) # doctest: +NORMALIZE_WHITESPACE
     array([([-1.57079633, -1.22173048], [ 0.        ,  1.57079633]),
            ([-1.57079633, -1.22173048], [ 1.57079633,  3.14159265]),
            ([-1.57079633, -1.22173048], [ 3.14159265,  4.71238898]),

docs/source/modules/converting_3d_counts.rst

@@ -18,6 +18,7 @@ wrapper :py:mod:`Corrfunc.theory.DD`
 
           >>> # Read the supplied galaxies on a periodic box
           >>> X, Y, Z = read_catalog()
+          >>> N = len(X)
           >>> boxsize = 420.0
           >>> nthreads = 2
 

docs/source/modules/converting_ddtheta_mocks.rst

@@ -12,6 +12,7 @@ wrapper :py:mod:`Corrfunc.mocks.DDtheta_mocks`
 .. code-block:: python
 
           >>> from os.path import dirname, abspath, join as pjoin
+          >>> import numpy as np
           >>> import Corrfunc
           >>> from Corrfunc.mocks.DDtheta_mocks import DDtheta_mocks
           >>> from Corrfunc.io import read_catalog
@@ -28,11 +29,15 @@ wrapper :py:mod:`Corrfunc.mocks.DDtheta_mocks`
           >>> random_catalog=pjoin(dirname(abspath(Corrfunc.__file__)),
           ...                     "../mocks/tests/data", "Mr19_randoms_northonly.rdcz.ff")
           >>> rand_RA, rand_DEC, _ = read_catalog(random_catalog)
-          
+          >>> rand_N = len(rand_RA)
+
           # Setup the bins
           >>> nbins = 10
           >>> bins = np.linspace(0.1, 10.0, nbins + 1) # note the +1 to nbins
 
+          # Number of threads to use
+          >>> nthreads = 2
+          
           # Auto pair counts in DD
           >>> autocorr=1
           >>> DD_counts = DDtheta_mocks(autocorr, nthreads, bins,

docs/source/modules/converting_rp_pi_counts.rst

@@ -8,12 +8,14 @@ by using the helper function :py:mod:`Corrfunc.utils.convert_rp_pi_counts_to_wp`
 
 .. code-block:: python
 
+          >>> import numpy as np
           >>> from Corrfunc.theory import DDrppi
           >>> from Corrfunc.io import read_catalog
           >>> from Corrfunc.utils import convert_rp_pi_counts_to_wp
           
           # Read the supplied galaxies on a periodic box          
           >>> X, Y, Z = read_catalog()
+          >>> N = len(X)
           >>> boxsize = 420.0
 
           # Generate randoms on the box