getting rid of many uses of xrange in pyx files

src/sage/calculus/interpolators.pyx

@@ -225,21 +225,21 @@ cdef class CCSpline:
         cdef int N, i, k
         N = len(pts)
         yvec = np.zeros(N, dtype=np.complex128)
-        for i in xrange(N):
+        for i in range(N):
             yvec[i] = 3 * (pts[(i - 1) % N] - 2*pts[i] + pts[(i + 1) % N])
         bmat = np.zeros([N, N], dtype=np.complex128)
-        for i in xrange(N):
+        for i in range(N):
             bmat[i, i] = 4
             bmat[(i - 1) % N, i] = 1
             bmat[(i + 1) % N, i] = 1
         bvec = (np.linalg.solve(bmat, yvec))
         cvec = np.zeros(N, dtype=np.complex128)
-        for i in xrange(N):
+        for i in range(N):
             cvec[i] = (pts[(i + 1) % N] - pts[i] - 1.0/3.0 *
                        bvec[(i + 1) % N] - 2./3. * bvec[i])
         dvec = np.array(pts, dtype=np.complex128)
         avec = np.zeros(N, dtype=np.complex128)
-        for i in xrange(N):
+        for i in range(N):
             avec[i] = 1.0/3.0 * (bvec[(i + 1) % N] - bvec[i])
         self.avec = avec
         self.bvec = bvec

src/sage/calculus/riemann.pyx

@@ -233,7 +233,7 @@ cdef class Riemann_Map:
         self.tk = np.array(np.arange(N) * TWOPI / N + 0.001 / N,
                            dtype=FLOAT)
         self.tk2 = np.zeros(N + 1, dtype=FLOAT)
-        for i in xrange(N):
+        for i in range(N):
             self.tk2[i] = self.tk[i]
         self.tk2[N] = TWOPI
         self.B = len(fs) # number of boundaries of the figure
@@ -246,14 +246,14 @@ cdef class Riemann_Map:
             dtype=COMPLEX)
         # Find the points on the boundaries and their derivatives.
         if self.exterior:
-            for k in xrange(self.B):
-                for i in xrange(N):
+            for k in range(self.B):
+                for i in range(N):
                     fk = fs[k](self.tk[N-i-1])
                     cps[k, i] = complex(1/fk)
                     dps[k, i] = complex(1/fk**2*fprimes[k](self.tk[N-i-1]))
         else:
-            for k in xrange(self.B):
-                for i in xrange(N):
+            for k in range(self.B):
+                for i in range(N):
                     cps[k, i] = complex(fs[k](self.tk[i]))
                     dps[k, i] = complex(fprimes[k](self.tk[i]))
         if self.exterior:
@@ -327,7 +327,7 @@ cdef class Riemann_Map:
              (normalized_dp[t]/(cp-cp[t])).conjugate())
               for t in np.arange(NB)], dtype=np.complex128)
         np.seterr(divide=errdivide,invalid=errinvalid) # resets the error handling
-        for i in xrange(NB):
+        for i in range(NB):
             K[i, i] = 1
         # Nystrom Method for solving 2nd kind integrals
         phi = np.linalg.solve(K, g) / NB * TWOPI
@@ -339,22 +339,22 @@ cdef class Riemann_Map:
         # regions.
         if B != 1:
             theta_array = np.zeros([1, NB])
-            for i in xrange(NB):
+            for i in range(NB):
                 theta_array[0, i] = phase(-I * np.power(phi[i], 2) * dp[i])
             self.theta_array = np.concatenate(
                 [theta_array.reshape([B, N]), np.zeros([B, 1])], axis=1)
-            for k in xrange(B):
+            for k in range(B):
                 self.theta_array[k, N] = self.theta_array[k, 0] + TWOPI
         # Finding the theta correspondence using abs. Well behaved, but
         # doesn't work on multiply connected domains.
         else:
             phi2 = phi.reshape([self.B, N])
             theta_array = np.zeros([B, N + 1], dtype=np.float64)
-            for k in xrange(B):
+            for k in range(B):
                 phik = phi2[k]
                 saa = (np.dot(abs(phi), abs(phi))) * TWOPI / NB
                 theta_array[k, 0] = 0
-                for i in xrange(1, N):
+                for i in range(1, N):
                     theta_array[k, i] = (
                         theta_array[k, i - 1] +
                         ((TWOPI / NB * TWOPI *
@@ -368,7 +368,7 @@ cdef class Riemann_Map:
                     t0 = theta_array[k, tmax] + phase(phimax)
                 else:
                     t0 = theta_array[k, tmax] - phase(phimax)
-                for i in xrange(N):
+                for i in range(N):
                     theta_array[k, i] = theta_array[k, i] - t0
                 theta_array[k, N] = TWOPI + theta_array[k, 0]
             self.theta_array = theta_array
@@ -432,7 +432,7 @@ cdef class Riemann_Map:
         cdef int k, B
         if boundary < 0:
             temptk = self.tk
-            for i in xrange(self.B - 1):
+            for i in range(self.B - 1):
                 temptk = np.concatenate([temptk, self.tk])
             if absolute_value:
                 return np.column_stack(
@@ -504,7 +504,7 @@ cdef class Riemann_Map:
         """
         if boundary < 0:
             temptk = self.tk2
-            for i in xrange(self.B - 1):
+            for i in range(self.B - 1):
                 temptk = np.concatenate([temptk, self.tk2])
             return np.column_stack(
                 [temptk, self.theta_array.flatten()]).tolist()
@@ -532,8 +532,8 @@ cdef class Riemann_Map:
             [self.B, N + 1], dtype=np.complex128)
         cdef int k, i
         # Lots of setup for Simpson's method of integration.
-        for k in xrange(self.B):
-            for i in xrange(N // 3):
+        for k in range(self.B):
+            for i in range(N // 3):
                 p_vector[k, 3*i] = (2*coeff * dps[k, 3*i] *
                                     exp(I * theta_array[k, 3*i]))
                 p_vector[k, 3*i + 1] = (3*coeff * dps[k, 3*i + 1] *
@@ -636,21 +636,21 @@ cdef class Riemann_Map:
         self.p_vector_inverse = np.zeros([B, N], dtype=np.complex128)
         # Setup for trapezoid integration because integration points are
         # not equally spaced.
-        for k in xrange(B):
-            for i in xrange(N):
+        for k in range(B):
+            for i in range(N):
                 di = theta_array[k, (i + 1) % N] - theta_array[k, (i - 1) % N]
                 if di > PI:
                     di = di - TWOPI
                 elif di < -PI:
                     di = di + TWOPI
                 self.p_vector_inverse[k, i] = di / 2
         self.sinalpha = np.zeros([B, N], dtype=np.float64)
-        for k in xrange(B):
-            for i in xrange(N):
+        for k in range(B):
+            for i in range(N):
                 self.sinalpha[k, i] = sin(-theta_array[k, i])
         self.cosalpha = np.zeros([B, N], dtype=np.float64)
-        for k in xrange(B):
-            for i in xrange(N):
+        for k in range(B):
+            for i in range(N):
                 self.cosalpha[k, i] = cos(-theta_array[k, i])
 
     cpdef inverse_riemann_map(self, COMPLEX_T pt):
@@ -748,7 +748,7 @@ cdef class Riemann_Map:
         from sage.plot.all import list_plot
 
         plots = list(range(self.B))
-        for k in xrange(self.B):
+        for k in range(self.B):
             # This conditional should be eliminated when the thickness/pointsize
             # issue is resolved later. Same for the others in plot_spiderweb().
             if plotjoined:
@@ -814,13 +814,13 @@ cdef class Riemann_Map:
         cdef np.ndarray[COMPLEX_T, ndim=2] z_values = np.empty(
             [y_points, x_points], dtype=np.complex128)
         if self.exterior:
-            for i in xrange(x_points):
-                for j in xrange(y_points):
+            for i in range(x_points):
+                for j in range(y_points):
                     pt = 1/(xmin + 0.5*xstep + i*xstep + I*(ymin + 0.5*ystep + j*ystep))
                     z_values[j, i] = 1/(-np.dot(p_vector,1/(pre_q_vector - pt)))
         else:
-            for i in xrange(x_points):
-                for j in xrange(y_points):
+            for i in range(x_points):
+                for j in range(y_points):
                     pt = xmin + 0.5*xstep + i*xstep + I*(ymin + 0.5*ystep + j*ystep)
                     z_values[j, i] = -np.dot(p_vector,1/(pre_q_vector - pt))
         return z_values, xmin, xmax, ymin, ymax
@@ -949,9 +949,9 @@ cdef class Riemann_Map:
             s = spline(np.column_stack([self.theta_array[0], self.tk2]).tolist())
             tmax = self.theta_array[0, self.N]
             tmin = self.theta_array[0, 0]
-            for k in xrange(circles):
+            for k in range(circles):
                 temp = list(range(pts*2))
-                for i in xrange(2*pts):
+                for i in range(2*pts):
                     temp[i] = self.inverse_riemann_map(
                         (k + 1) / (circles + 1.0) * exp(I*i * TWOPI / (2*pts)))
                 if plotjoined:
@@ -961,14 +961,14 @@ cdef class Riemann_Map:
                     circle_list[k] = list_plot(comp_pt(temp, 1),
                         rgbcolor=rgbcolor, pointsize=thickness)
             line_list = list(range(spokes))
-            for k in xrange(spokes):
+            for k in range(spokes):
                 temp = list(range(pts))
                 angle = (k*1.0) / spokes * TWOPI
                 if angle >= tmax:
                     angle -= TWOPI
                 elif angle <= tmin:
                     angle += TWOPI
-                for i in xrange(pts - 1):
+                for i in range(pts - 1):
                     temp[i] = self.inverse_riemann_map(
                         (i * 1.0) / (pts * 1.0) * exp(I * angle) * linescale)
                 temp[pts - 1] = complex(
@@ -1238,8 +1238,8 @@ cpdef complex_to_spiderweb(np.ndarray[COMPLEX_T, ndim = 2] z_values,
         spoke_angles = srange(-PI,PI+TWOPI/spokes,TWOPI/spokes)
     else:
         spoke_angles = []
-    for i in xrange(imax-2): # the d arrays are 1 smaller on each side
-        for j in xrange(jmax-2):
+    for i in range(imax-2): # the d arrays are 1 smaller on each side
+        for j in range(jmax-2):
             z = z_values[i+1,j+1]
             mag = abs(z)
             arg = phase(z)
@@ -1309,9 +1309,9 @@ cpdef complex_to_rgb(np.ndarray[COMPLEX_T, ndim = 2] z_values):
         dtype=FLOAT, shape=(imax, jmax, 3))
 
     sig_on()
-    for i in xrange(imax):
+    for i in range(imax):
         row = z_values[i]
-        for j in xrange(jmax):
+        for j in range(jmax):
             z = row[j]
             mag = abs(z)
             arg = phase(z)

src/sage/coding/binary_code.pyx

@@ -202,10 +202,10 @@ def test_word_perms(t_limit=5.0):
         raise MemoryError("Error allocating memory.")
     from sage.misc.prandom import randint
     from sage.combinat.permutation import Permutations
-    S = Permutations(list(xrange(n)))
+    S = Permutations(list(range(n)))
     t = cputime()
     while cputime(t) < t_limit:
-        word = [randint(0, 1) for _ in xrange(n)]
+        word = [randint(0, 1) for _ in range(n)]
         cw1 = 0
         for j from 0 <= j < n:
             cw1 += (<codeword>word[j]) << (<codeword>j)
@@ -298,7 +298,7 @@ cdef WordPermutation *create_word_perm(object list_perm):
     word_perm.chunk_num = num_chunks
     words_per_chunk = 1 << chunk_size
     word_perm.gate = ( (<codeword>1) << chunk_size ) - 1
-    list_perm += list(xrange(len(list_perm), chunk_size*num_chunks))
+    list_perm += list(range(len(list_perm), chunk_size*num_chunks))
     word_perm.chunk_words = words_per_chunk
     for i from 0 <= i < num_chunks:
         images_i = <codeword *> sig_malloc(words_per_chunk * sizeof(codeword))
@@ -661,15 +661,15 @@ cdef codeword *expand_to_ortho_basis(BinaryCode B, int n):
     for j from i <= j < n:
         basis[j] = 0
     # now basis is length i
-    perm = list(xrange(B.nrows))
+    perm = list(range(B.nrows))
     perm_c = []
     for j from B.nrows <= j < B.ncols:
         if (<codeword>1 << j) & pivots:
             perm.append(j)
         else:
             perm_c.append(j)
     perm.extend(perm_c)
-    perm.extend(list(xrange(B.ncols, n)))
+    perm.extend(list(range(B.ncols, n)))
     perm_c = [0]*n
     for j from 0 <= j < n:
         perm_c[perm[j]] = j
@@ -4017,7 +4017,7 @@ cdef class BinaryCodeClassifier:
 
 
         for i from 0 <= i < len(aut_gp_gens):
-            parent_generators[i] = create_word_perm(aut_gp_gens[i] + list(xrange(B.ncols, n)))
+            parent_generators[i] = create_word_perm(aut_gp_gens[i] + list(range(B.ncols, n)))
 
         word = 0
         while ortho_basis[k] & (((<codeword>1) << B.ncols) - 1):
@@ -4116,7 +4116,7 @@ cdef class BinaryCodeClassifier:
                             aut_B_aug = libgap(PermutationGroup([PermutationGroupElement([a+1 for a in g]) for g in aug_aut_gp_gens]))
                         H = libgap(aut_m).Intersection2(aut_B_aug)
                         rt_transversal = [[int(a) - 1 for a in g.ListPerm(n)] for g in aut_B_aug.RightTransversal(H) if not g.IsOne()]
-                        rt_transversal.append(list(xrange(n)))
+                        rt_transversal.append(list(range(n)))
 
                         bingo2 = 0
                         for coset_rep in rt_transversal:

src/sage/coding/codecan/autgroup_can_label.pyx

@@ -124,8 +124,8 @@ def _cyclic_shift(n, p):
         sage: p.action(t)
         [0, 2, 7, 3, 1, 5, 6, 4, 8, 9]
     """
-    x = list(xrange(1, n + 1))
-    for i in xrange(1, len(p)):
+    x = list(range(1, n + 1))
+    for i in range(1, len(p)):
         x[p[i - 1]] = p[i] + 1
     x[p[len(p) - 1]] = p[0] + 1
     return Permutation(x)
@@ -229,17 +229,17 @@ class LinearCodeAutGroupCanLabel:
         S = SemimonomialTransformationGroup(F, mat.ncols())
 
         if P is None:
-            P = [list(xrange(mat.ncols()))]
+            P = [list(range(mat.ncols()))]
 
         pos2P = [-1] * mat.ncols()
-        for i in xrange(len(P)):
+        for i in range(len(P)):
             P[i].sort(reverse=True)
             for x in P[i]:
                 pos2P[x] = i
 
         col_list = mat.columns()
-        nz = [i for i in xrange(mat.ncols()) if not col_list[i].is_zero()]
-        z = [(pos2P[i], i) for i in xrange(mat.ncols()) if col_list[i].is_zero()]
+        nz = [i for i in range(mat.ncols()) if not col_list[i].is_zero()]
+        z = [(pos2P[i], i) for i in range(mat.ncols()) if col_list[i].is_zero()]
         z.sort()
         z = [i for (p, i) in z]
 
@@ -259,7 +259,7 @@ class LinearCodeAutGroupCanLabel:
         col2pos = []
         col2P = []
         for c in col_set:
-            X = [(pos2P[y], y) for y in xrange(mat.ncols()) if col_list[y] == c ]
+            X = [(pos2P[y], y) for y in range(mat.ncols()) if col_list[y] == c ]
             X.sort()
             col2pos.append([b for (a, b) in X ])
             col2P.append([a for (a, b) in X ])
@@ -272,7 +272,7 @@ class LinearCodeAutGroupCanLabel:
         P_refined = []
         p = [0]
         act_qty = col2P[0]
-        for i in xrange(1, len(col_set)):
+        for i in range(1, len(col_set)):
             if act_qty == col2P[i]:
                 p.append(i)
             else:
@@ -357,7 +357,7 @@ class LinearCodeAutGroupCanLabel:
         perm = [-1] * mat.ncols()
         mult = [F.one()] * mat.ncols()
 
-        for i in xrange(len(can_col_set)):
+        for i in range(len(can_col_set)):
             img = can_transp.get_perm()(i + 1)
             for j in col2pos[img - 1]:
                 pos = P[ pos2P[j] ].pop()
@@ -378,7 +378,7 @@ class LinearCodeAutGroupCanLabel:
         self._full_autom_order *= a
 
 
-        for i in xrange(len(col2P)):
+        for i in range(len(col2P)):
             if len(col2P[i]) > 1:
                 A, a = self._compute_trivial_automs(normalization,
                     normalization_inverse, col2pos[i], col2P[i])
@@ -508,11 +508,11 @@ class LinearCodeAutGroupCanLabel:
         n = S.degree()
         A = []
         for g in gens:
-            perm = list(xrange(1, n + 1))
+            perm = list(range(1, n + 1))
             mult = [S.base_ring().one()] * n
             short_perm = g.get_perm()
             short_mult = g.get_v()
-            for i in xrange(len(col2pos)):
+            for i in range(len(col2pos)):
                 c = col2pos[i]
                 img_iter = iter(col2pos[short_perm(i + 1) - 1])
                 for x in c:

src/sage/crypto/boolean_function.pyx

@@ -10,7 +10,7 @@ and also algebraic immunity.
 
 EXAMPLES::
 
-    sage: R.<x>=GF(2^8,'a')[]
+    sage: R.<x> = GF(2^8,'a')[]
     sage: from sage.crypto.boolean_function import BooleanFunction
     sage: B = BooleanFunction( x^254 ) # the Boolean function Tr(x^254)
     sage: B
@@ -900,7 +900,8 @@ cdef class BooleanFunction(SageObject):
                 temp[i] = W[i]*W[i]
 
             walsh_hadamard(temp, self._nvariables)
-            self._autocorrelation = tuple([temp[i] >> self._nvariables for i in xrange(n)])
+            self._autocorrelation = tuple([temp[i] >> self._nvariables
+                                           for i in range(n)])
             sig_free(temp)
 
         return self._autocorrelation