Cleaned up code

src/NFS.py

@@ -2,8 +2,6 @@
 
 ## import libraries
 
-ZQDFEGSRHTDR = 35279032783773322923326661023
-
 import math, os
 from datetime import datetime
 import log

src/block_lanczos.py

@@ -33,7 +33,7 @@ def block(T, N):
         else:
             for k in range(j, N):
                 if (M[k] >> N - j - 1)&1 != 0:
-                    M[k] ,M[j] = M[j], M[k]
+                    M[k], M[j] = M[j], M[k]
                     break
 
             if (M[j] >> N - j - 1)&1 == 0:
@@ -110,7 +110,7 @@ def block_lanczos(B, nb_relations, BLOCK_SIZE, LOG_PATH):
             solutions.append(Z[i])
 
     if len(solutions) == 0:
-        solutions = block_lanczos(B,nb_relations,BLOCK_SIZE<<1,LOG_PATH)
+        solutions = block_lanczos(B, nb_relations, BLOCK_SIZE<<1, LOG_PATH)
 
     return solutions
 

src/compute_solutions.py

@@ -26,7 +26,7 @@ def create_solution(pairs, null_space, n, len_primes, primes, f_x, m0, m1, inert
         f_norm += x*x*tmp
         tmp *= leading
     f_norm = int(math.sqrt(f_norm))+1
-    fd = int(pow(len(f_x)-1,1.5))+1
+    fd = int(pow(len(f_x)-1, 1.5))+1
     S = 0
 
     x = f_prime_eval
@@ -97,7 +97,7 @@ def create_solution_couveignes(pairs, null_space, n, len_primes, primes, f_x, f_
 
     #goal = 2*max([abs(c) for c in coeffs])
 
-    fd = int(pow(d,1.5))+1
+    fd = int(pow(d, 1.5))+1
     coeff_bound = [fd*pow(f_norm, d-i)*pow(2*u*f_norm, S>>1) for i in range(len(f_x)-1)]
 
     goal = max(coeff_bound)

src/polynomial_functions.py

@@ -121,7 +121,7 @@ def find_roots_poly(f, p):
     if g[-1] == 0:
         r.append(0)
         del g[-1]
-    return r+roots(g, p)
+    return r + roots(g, p)
 
 def roots(g, p):
     if len(g) == 1: return []

src/wiedemann.py

@@ -107,6 +107,7 @@ def wiedemann(A, n, BLOCK_SIZE, mini_poly_estim):
         # We will find the generator for each scalar sequence, and compute the lcm of generator and current estimate of minimal polynomial
         tmp2 = block
         sequence = [0]*BLOCK_SIZE
+
         for i in range(2*n-1):
             tmp = sparse_dot_prod(lbd, tmp2)
             for j in range(BLOCK_SIZE):