Python3 compat.

2 files changed, 11 insertions, 11 deletions

diff --git a/nonlin_ode.py b/nonlin_ode.py
index 7584882..d96c158 100644
--- a/nonlin_ode.py
+++ b/nonlin_ode.py
@@ -3,7 +3,7 @@
 import numpy as np
 import sys
 
-import series_expansion as se
+from . import series_expansion as se
 
 def _nonlin_solve_1d_iter(prev, grid, basis_vals, Fs, Fs_args):
     order = grid.shape[0]
@@ -11,7 +11,7 @@ def _nonlin_solve_1d_iter(prev, grid, basis_vals, Fs, Fs_args):
 
     # evaluate the previous iteration on the grid
     prev_vals = []
-    for diff_order in xrange(N - 1):
+    for diff_order in range(N - 1):
         prev_vals.append(prev.eval(grid, diff_order))
 
     # evaluate the RHS functions using the previous iteration
@@ -24,8 +24,8 @@ def _nonlin_solve_1d_iter(prev, grid, basis_vals, Fs, Fs_args):
 
     # TODO should be doable with fewer explicit loops
     mat = np.copy(basis_vals[-1])
-    for idx in xrange(order):
-        for diff_order in xrange(N - 1):
+    for idx in range(order):
+        for diff_order in range(N - 1):
             mat[:, idx] -= basis_vals[diff_order][:, idx] * F_vals[diff_order + 1]
 
     rhs = F_vals[0] - prev.eval(grid, N - 1)
@@ -73,14 +73,14 @@ def nonlin_solve_1d(initial_guess, Fs, args = None, maxiter = 100, atol = 1e-14,
     # at the grid
     basis = initial_guess.basis[0]
     basis_vals = []
-    for diff_order in xrange(N):
+    for diff_order in range(N):
         basis_val = np.empty((order, order))
-        for idx in xrange(order):
+        for idx in range(order):
             basis_val[:, idx] = basis.eval(idx, grid, diff_order)
         basis_vals.append(basis_val)
 
     solution = initial_guess
-    for i in xrange(maxiter):
+    for i in range(maxiter):
         delta = _nonlin_solve_1d_iter(solution, grid, basis_vals, Fs, args)
 
         err = np.max(np.abs(delta))
@@ -108,7 +108,7 @@ def nonlin_residual(solution, N, grid, F, args):
     """
     sol_vals = [solution.eval(grid)]
     dx = abs(grid[1] - grid[0])
-    for diff_order in xrange(N):
+    for diff_order in range(N):
         sol_vals.append(np.gradient(sol_vals[-1], dx))
     rhs = F(grid, sol_vals[:-1], args)
     return sol_vals[-1] - rhs
diff --git a/series_expansion.py b/series_expansion.py
index 15ee79d..ca06b40 100644
--- a/series_expansion.py
+++ b/series_expansion.py
@@ -59,7 +59,7 @@ class SeriesExpansion(object):
         basis_vals = []
         for i, (b, c, d) in enumerate(zip(self._basis, coords, diff_order)):
             val = []
-            for idx in xrange(self._coeffs.shape[i]):
+            for idx in range(self._coeffs.shape[i]):
                 val.append(b.eval(idx, c, d))
             basis_vals.append(val)
 
@@ -68,8 +68,8 @@ class SeriesExpansion(object):
                 ret += val * c
             return ret
         elif self._dim == 2:
-            for i in xrange(self._coeffs.shape[0]):
-                for j in xrange(self._coeffs.shape[1]):
+            for i in range(self._coeffs.shape[0]):
+                for j in range(self._coeffs.shape[1]):
                     ret += self._coeffs[i, j] * np.outer(basis_vals[0][i], basis_vals[1][j])
             return ret
         else: