fixed bug in compute_controlled_matrix

Author: stevehuang235

src/FindMonomialBasis.jl

@@ -59,16 +59,16 @@ function compute_basis_matrix(f, l, m, R, PR, termorder)
     return M
 end
 
-# Given $f, m, l$, over the ring $\texttt{PR} = R[x_0, \dots, x_n]$, and the set $S\subseteq \{0, ..., n\}$, computes
-# the matrix for the map
-# $$(\mu_0, \dots, \mu_n) \mapsto \sum_{i\in S} \mu_i \partial_i f + \sum_{i\not\in S} \mu_i x_i \partial_i f$$
-# where $\mu_i$ for $0\leq i < |S|$ are of degree $l - (d - 1)$ and $\mu_i$ for
-# $|S| \leq i \leq n$ are of degree $l - d$.
-#
+
 """
     compute_controlled_matrix(f, l, S, R, PR, params)
 
-what does this do again?
+Given f, m, l, over the ring PR = R[x_0, ..., x_n], and the set S subseteq {0, ..., n}, computes
+the matrix for the map
+(mu_0, ..., mu_n) |--> sum_{i in S} mu_i partial_i f + sum_{i notin S} mu_i x_i partial_i f
+ where mu_i for 0<= i < |S| are of degree l - (d - 1) and mu_i for
+ |S| <= i <= n are of degree l - d.
+
 """
 function compute_controlled_matrix(f, l, S, R, PR, params)
     n = nvars(parent(f)) - 1
@@ -103,7 +103,7 @@ function compute_controlled_matrix(f, l, S, R, PR, params)
         partials = reverse(partials)  # one needs to be quite careful with the ordering of partials 
         notS = reverse(notS)
     end
-
+    
     for i in 1:len_S
         var = S[i]
         for monomial in eachindex(in_set_mons)
@@ -112,14 +112,16 @@ function compute_controlled_matrix(f, l, S, R, PR, params)
         end
     end
 
+    ind_S = in_set_section * len_S
+
     for i in (len_S+1):n+1
         var = notS[i-len_S]
         for monomial in eachindex(not_in_set_mons)
-            M[:, not_in_set_section * (i-1) + monomial] = polynomial_to_vector(not_in_set_mons[monomial] * vars[var+1] * partials[i-len_S], n+1, R, PR, params.termorder)
+            M[:, ind_S + not_in_set_section * (i-len_S-1) + monomial] = polynomial_to_vector(not_in_set_mons[monomial] * vars[var+1] * partials[i-len_S], n+1, R, PR, params.termorder)
             #M[:, not_in_set_section * (i-1) + monomial] = polynomial_to_vector(not_in_set_mons[monomial] * vars[i] * partials[i], n+1, R, PR, params.termorder)
         end
     end
-    println(rank(M))
+    
     return M
 end
 

src/ZetaFunction.jl

@@ -294,20 +294,6 @@ function zeta_function(f; S=[-1], verbose=false, givefrobmat=false, algorithm=:c
     (9 < verbose) && println("Basis of cohomology is $Basis")
 
     (hodge_polygon, r_m, N_m, M) = precision_information(f,Basis,verbose)
-    #print(find_Ssmooth_model(f, M, S, params))
-    #hodge_polygon = hodgepolygon(Basis, n)
-    #hodge_numbers = hodge_polygon.slopelengths
-    #(9 < verbose) && println("Hodge numbers = $hodge_numbers")
-
-    #k = sum(hodge_numbers) # dimension of H^n
-    #(9 < verbose) && println("There are $k basis elements in H^$n")
-
-    #r_m = calculate_relative_precision(hodge_polygon, n-1, p) 
-    ##r_m = relative_precision(k, p)
-    ##N_m = series_precision(r_m, p, n) # series precision 
-    ##M = algorithm_precision(r_m, N_m, p)
-    #N_m = series_precision(p,n,d,r_m)
-    #M = algorithm_precision(p,n,d,r_m,N_m)
 
     (9 < verbose) && println("We work modulo $p^$M, and compute up to the $N_m-th term of the Frobenius power series")
     (0 < verbose) && println("algorithm precision: $M, series precision: $N_m") 
@@ -325,6 +311,14 @@ function zeta_function(f; S=[-1], verbose=false, givefrobmat=false, algorithm=:c
         S = collect(0:n)
     end
 
+    if (0 < verbose)
+        println("Starting linear algebra problem")
+        @time f, pseudo_inverse_mat_new = find_Ssmooth_model(f, M, S, params)
+    else
+        #pseudo_inverse_mat_new = pseudo_inverse_controlled_lifted(f,S,l,M,params)
+        f, pseudo_inverse_mat_new = find_Ssmooth_model(f, M, S, params)
+    end
+
     #=
     BasisTLift = []
     for i in basis
@@ -369,12 +363,6 @@ function zeta_function(f; S=[-1], verbose=false, givefrobmat=false, algorithm=:c
     #end
     l = d * n - n + d - length(S)
 
-    if (0 < verbose)
-        println("Starting linear algebra problem")
-        @time pseudo_inverse_mat_new = pseudo_inverse_controlled_lifted(f,S,l,M,params)
-    else
-        pseudo_inverse_mat_new = pseudo_inverse_controlled_lifted(f,S,l,M,params)
-    end
 
     MS = matrix_space(precisionring, nrows(pseudo_inverse_mat_new), ncols(pseudo_inverse_mat_new))
     pseudo_inverse_mat = MS()