Mercurial > btquotients
changeset 4:50cf9efe4931
Allow basis computation with extra conditions on some edges
| author | Marc Masdeu <masdeu@math.columbia.edu> |
|---|---|
| date | Tue, 05 Jul 2011 20:32:01 +0200 |
| parents | d6fb84d5d376 |
| children | d1c2815f25e9 |
| files | pautomorphicform.py shimuracurve.py |
| diffstat | 2 files changed, 56 insertions(+), 68 deletions(-) [+] |
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--- a/pautomorphicform.py Tue Jul 05 12:31:58 2011 +0200 +++ b/pautomorphicform.py Tue Jul 05 20:32:01 2011 +0200 @@ -260,72 +260,68 @@ def iota(self,g): return self._X.iota(g,self._prec) - def get_basis_matrix(self): - if (self._basis_matrix==None): - self._compute_basis() + def get_basis_matrix(self,extra_conditions=[]): + if (self._basis_matrix==None or len(extra_conditions)>0): + self._compute_basis(extra_conditions) return self._basis_matrix - def get_basis(self): + def get_basis(self,extra_conditions=[]): nE=len(self._E) - basis_matrix=self.get_basis_matrix() + basis_matrix=self.get_basis_matrix(extra_conditions) basis=[] for ii in range(basis_matrix.nrows()): r=list(basis_matrix.row(ii)) basis.append(HarmonicCocycle(self,[OCVnElement(self._U,Matrix(self._ZZp,self._k-1,1,r[e*(self._k-1):(e+1)*(self._k-1)]),quick=True) for e in range(nE)])) return basis - def dimension(self): - if (self._basis_matrix==None): - self._compute_basis() + def dimension(self,extra_conditions=[]): + if (self._basis_matrix==None or len(extra_conditions)>0): + self._compute_basis(extra_conditions) return self._basis_matrix.nrows() - def _compute_basis(self): + def _compute_basis(self,extra_conditions): nV=len(self._V) nE=len(self._E) stab_conds=[] - tmp=self._X.get_edge_stabs() + S=self._X.get_edge_stabs() p=self._X._p - for e in self._E: - gg=tmp[e.label] - if(gg!=1): - for g in gg: - if(g[2]): - C=self._U.l_matrix_representation(self.iota(g[0])) - C-=self._U.l_matrix_representation(Matrix(RationalField(),2,2,p**g[1])) - stab_conds.append([e.label,C]) - break - self._M=Matrix(self._ZZp,(nV+len(stab_conds))*(self._k-1),nE*(self._k-1),0,sparse=True) + d=self._k-1 + for e in filter(lambda e:S[e.label]!=1,self._E): + try: + g=filter(lambda g:g[2],S[e.label])[0] + C=self._U.l_matrix_representation(self.iota(g[0])) + C-=self._U.l_matrix_representation(Matrix(RationalField(),2,2,p**g[1])) + stab_conds.append([e.label,C]) + except IndexError: pass + + n_stab_conds=len(stab_conds) + self._M=Matrix(self._ZZp,(nV+n_stab_conds+len(extra_conditions))*d,nE*d,0,sparse=True) for v in self._V: - for e in v.leaving_edges: - if e.parity!=0: - continue + for e in filter(lambda e:e.parity==0,v.leaving_edges): C=sum(self._U.l_matrix_representation([self.iota(x[0]) for x in e.links])) - for ii in range(self._k-1): - for jj in range(self._k-1): - self._M[v.label*(self._k-1)+ii,e.label*(self._k-1)+jj]+=C[ii,jj] - for e in v.entering_edges: - if e.parity!=0: - continue + self._M.set_block(v.label*d,e.label*d,C) + for e in filter(lambda e:e.parity==0,v.entering_edges): + C=sum(self._U.l_matrix_representation([self.iota(x[0]) for x in e.opposite.links])) + self._M.set_block(v.label*d,e.opposite.label*d,C) - C=sum(self._U.l_matrix_representation([self.iota(x[0]) for x in e.opposite[0].links])) - for ii in range(self._k-1): - for jj in range(self._k-1): - self._M[v.label*(self._k-1)+ii,e.opposite[0].label*(self._k-1)+jj]-=C[ii,jj] - for kk in range(len(stab_conds)): - C=stab_conds[kk] - for ii in range(self._k-1): - for jj in range(self._k-1): - self._M[(nV+kk)*(self._k-1)+ii,C[0]*(self._k-1)+jj]=C[1][ii,jj] + for kk in range(n_stab_conds): + v=stab_conds[kk] + self._M.set_block((nV+kk)*d,v[0]*d,v[1]) + + for kk in range(len(extra_conditions)): + v=extra_conditions[kk] + self._M.set_block((nV+n_stab_conds+kk)*d,v*d,Matrix(self._ZZp,d,d,1)) + x1=self._M.right_kernel().matrix() K=[c for c in x1.rows()] - if(self._k==2): - assert(len(K)==self._X.genus()) + #if(self._k==2): + # assert(len(K)==self._X.genus()) for ii in range(len(K)): s=min([t.valuation() for t in K[ii]]) for jj in range(len(K[ii])): K[ii][jj]=(p**(-s))*K[ii][jj] - self._basis_matrix=Matrix(self._ZZp,len(K),nE*(self._k-1),K) + self._basis_matrix=Matrix(self._ZZp,len(K),nE*d,K) def hecke_operator(self,l): l=IntegerRing()(l) @@ -432,7 +428,7 @@ def _make_invariant(self): S=self._parent._X.get_edge_stabs() E=self._parent._E - M=[e.rep for e in E]+[e.opposite[0].rep for e in E] + M=[e.rep for e in E]+[e.opposite.rep for e in E] lS=len(S) assert(2*len(S)==self._nE) for ii in range(self._nE): @@ -500,7 +496,7 @@ tmp=self._F[u.label+len(self._parent._E)].r_act_by(r) Tf.append(tmp) for e in E: - u=EdgeDecomposition(self._parent._X,alpha*e.opposite[0].rep) + u=EdgeDecomposition(self._parent._X,alpha*e.opposite.rep) r=u.t*gg*self._parent._X._p**(-(u.power)) if(u.sign==1): tmp=self._F[u.label].r_act_by(r) @@ -733,12 +729,10 @@ def Up(self,v=None,scale=False): def T(f): HeckeData=self._X.Up_data() - #Should find a way to replace this n/2 with something more intrinsinc to U if(scale==False): factor=(self._X._p)**(self._U.weight()/2) else: factor=1 - #print 'factor=',factor Tf=[] for jj in range(2*len(self._E)): tmp=self._U(0)
--- a/shimuracurve.py Tue Jul 05 12:31:58 2011 +0200 +++ b/shimuracurve.py Tue Jul 05 20:32:01 2011 +0200 @@ -48,7 +48,7 @@ if sign==+1: gamma*edge_list[label].rep*t==x0 if sign==-1: - gamma*edge_list[label].opposite[0].rep*t==x0 + gamma*edge_list[label].opposite.rep*t==x0 It also stores a member called power, so that: p**(2*power)=gamma.reduced_norm() @@ -81,7 +81,7 @@ sign=1 t=(Y.iota(g[0])*e.rep).inverse()*x break - e3=e.opposite[0] + e3=e.opposite g=Y._are_equivalent(e3.rep,e1,-1,Xe) if(g!=0): sign=-1 @@ -574,7 +574,7 @@ for e in E: tmp[1].append(EdgeDecomposition(self,e.rep*alpha)) #edge_list for e in E: - tmp[1].append(EdgeDecomposition(self,e.opposite[0].rep*alpha)) #edge_list + tmp[1].append(EdgeDecomposition(self,e.opposite.rep*alpha)) #edge_list Up_data.append(tmp) self._Up_data=Up_data return self._Up_data @@ -657,20 +657,18 @@ mat=v[2].python().transpose() n_vecs=mat.nrows() B=self.get_eichler_order_basis() - if(n_vecs>1): - tmp=[] - for jj in range(n_vecs): - vec=Matrix(ZZ,1,4,list(mat.row(jj))) - try: nrd=ZZ((vec*A*vec.transpose())[0,0]/2) - except TypeError: continue - if(nrd.is_power_of(p**2) and nrd.valuation(p)==twom): - w=vec*E - x=self._conv(w) - tmp.append([w.transpose(),m,x!=p**m]) - return tmp - else: + if(n_vecs<=1): return 1 - return 1 + stabs=[] + for jj in range(n_vecs): + vec=Matrix(ZZ,1,4,list(mat.row(jj))) + try: nrd=ZZ((vec*A*vec.transpose())[0,0]/2) + except TypeError: continue + if(nrd.is_power_of(p**2) and nrd.valuation(p)==twom): + w=vec*E + x=self._conv(w) + stabs.append([w.transpose(),m,x!=p**m]) + return stabs def _are_equivalent(self,v1,v2,twom,X): p=self._p @@ -757,9 +755,7 @@ new_det=target.determinant() new_valuation=new_det.valuation(p) new_parity=new_valuation%2 - for v1 in V: - if(v1.parity!=new_parity): - continue + for v1 in filter(lambda v1:v1.parity==new_parity,V): g1=self._are_equivalent(target,v1.rep,v1.valuation+new_valuation,self._Xv) if(g1): target=v1.rep @@ -792,10 +788,8 @@ vertex_list[v1.parity].remove(v1) opp_det=opp.determinant() - new_e_opp=Edge(self,self._num_edges,opp,v1,v,[],[new_e],opp_det,opp_det.valuation(p)) - assert(len(new_e.opposite)==0) - new_e.opposite.append(new_e_opp) - + new_e_opp=Edge(self,self._num_edges,opp,v1,v,[],new_e,opp_det,opp_det.valuation(p)) + new_e.opposite=new_e_opp if(new_e.parity==0): edge_list.append(new_e)