ENH: py3 compatibility

.gitignore

@@ -0,0 +1 @@
+*.pyc

interpolation/smolyak/grid.py

@@ -30,7 +30,8 @@
 import numpy as np
 from scipy.linalg import lu
 import pandas as pd
-from util import *
+from functools import reduce
+from .util import *
 
 ## --------------- ##
 #- Building Blocks -#
@@ -143,7 +144,7 @@ def chebyvalto(x, n, kind=1.):
     ret_matrix[:, :col] = x * kind
     ret_matrix[:, col:2*col] = 2 * x * ret_matrix[:, :col] - init
 
-    for i in xrange(3, n):
+    for i in range(3, n):
         ret_matrix[:, col*(i-1): col*(i)] = 2 * x * ret_matrix[:, col*(i-2):col*(i-1)] \
                                          - ret_matrix[:, col*(i-3): col*(i-2)]
 
@@ -255,7 +256,7 @@ def a_chain(n):
     A_chain[2] = [-1., 1.]
 
     # Need a for loop to extract remaining elements
-    for seq in xrange(n, 2, -1):
+    for seq in range(n, 2, -1):
         num = Sn.size
         # Need odd indices in python because indexing starts at 0
         A_chain[seq] = tuple(Sn[range(1, num, 2)])
@@ -293,7 +294,7 @@ def phi_chain(n):
     aphi_chain[2] = [2, 3]
 
     curr_val = 4
-    for i in xrange(3, n+1):
+    for i in range(3, n+1):
         end_val = 2**(i-1) + 1
         temp = range(curr_val, end_val+1)
         aphi_chain[i] = temp
@@ -568,7 +569,7 @@ def build_B(d, mu, pts, b_inds=None, deriv=False):
 #     # compute any more.  They are multiplications of different numbers
 #     # of elements from the pieces of easy_B.
 #     if mu==2:
-#         for i in xrange(d-1):
+#         for i in range(d-1):
 
 
 #             mult_inds = np.hstack([np.arange(i+1, d), np.arange(d + (i+1), 2*d)])
@@ -591,7 +592,7 @@ def build_B(d, mu, pts, b_inds=None, deriv=False):
 #     #-----------------------------------------------------------------#
 #     #-----------------------------------------------------------------#
 
-#     # for i in xrange(2, mu+1):
+#     # for i in range(2, mu+1):
 #     #     curr_ind = i
 
 #     #     while True:
@@ -601,15 +602,15 @@ def build_B(d, mu, pts, b_inds=None, deriv=False):
 #     #         # Find which possible polynomials can be reached (lowest is 2)
 #     #         poss_inds = np.arange(2, m_i(some function of curr_ind, d, mu)+1)
 
-#     #         for dd in xrange(d-1):
+#     #         for dd in range(d-1):
 #     #             # Create range of d to be used to build the fancy index
 #     #             mult_ind = np.arange(curr_col+1, d)
 
 #     #             # Initialize array for fancy index.  Want to add arange(d) + (d*i)
 #     #             # for every chebyshev polynomial that we need to reach with these
 #     #             # indexes
 #     #             mult_inds = np.array([])
-#     #             for tt in xrange(some condition for what is max polynomial we reach -1):
+#     #             for tt in range(some condition for what is max polynomial we reach -1):
 #     #                 mult_inds = np.hstack([mult_inds, mult_inds + (d*tt)])
 
 #     #             # this will create the column times all the stuff following it
@@ -622,7 +623,7 @@ def build_B(d, mu, pts, b_inds=None, deriv=False):
 
 #     #             while d>curr_dim and condition for continuing is met:
 #     #                 curr_dim += 1
-#     #                 for mm in xrange(curr_col + 2, d-1):
+#     #                 for mm in range(curr_col + 2, d-1):
 #     #                     for bb in mult_inds[:-1]:
 #     #                         temp2 = easy_B[:, bb*d + mm] * temp1
 #     #                         new_cols2 = temp2.shape[1]

interpolation/smolyak/interp.py

@@ -7,7 +7,7 @@
 from __future__ import division
 import numpy as np
 import numpy.linalg as la
-from grid import build_B
+from .grid import build_B
 
 __all__ = ['find_theta', 'SmolyakInterp']
 

interpolation/splines/__init__.py

@@ -1 +1 @@
-from splines import CubicSpline, MultiCubicSpline
+from .splines import CubicSpline, MultiCubicSpline

interpolation/splines/eval_cubic_splines.py

@@ -7,8 +7,8 @@
 #     from eval_cubic_splines_cython import *
 #
 # except Exception:
-from eval_cubic_multi_splines_numba import *
-from eval_cubic_splines_numba import *
+from .eval_cubic_multi_splines_numba import *
+from .eval_cubic_splines_numba import *
 
 
 ## the functions in this file work for any dimension (d<=4)

interpolation/splines/splines.py

@@ -3,7 +3,7 @@
 import numpy
 import numpy as np
 
-from misc import mlinspace
+from .misc import mlinspace
 
 
 class CubicSpline:
@@ -59,7 +59,7 @@ def set_values(self, values):
 
         values = np.array(values, dtype=float)
 
-        from filter_cubic_splines import filter_coeffs
+        from .filter_cubic_splines import filter_coeffs
 
         if not np.all( np.isfinite(values)):
             raise Exception('Trying to interpolate non-finite values')
@@ -91,7 +91,7 @@ def interpolate(self, points, values=None, with_derivatives=False):
 
         import time
 
-        from eval_cubic_splines import vec_eval_cubic_spline, eval_cubic_spline
+        from .eval_cubic_splines import vec_eval_cubic_spline, eval_cubic_spline
 
         if not np.all( np.isfinite(points)):
             raise Exception('Spline interpolator evaluated at non-finite points.')
@@ -158,7 +158,7 @@ def set_values(self, values):
 
         values = np.array(values, dtype=float)
 
-        from filter_cubic_splines import filter_coeffs
+        from .filter_cubic_splines import filter_coeffs
 
         if not np.all( np.isfinite(values)):
             raise Exception('Trying to interpolate non-finite values')
@@ -193,7 +193,7 @@ def interpolate(self, points, with_derivatives=False):
 
         import time
 
-        from eval_cubic_splines import vec_eval_cubic_multi_spline
+        from .eval_cubic_splines import vec_eval_cubic_multi_spline
 
         if points.ndim == 1:
             raise Exception('Expected 2d array. Received {}d array'.format(points.ndim))