cleaning

veerer/linear_family.py

@@ -630,6 +630,7 @@ def triangle_3_4_13_unfolding_orbit_closure():
             sage: from veerer.linear_family import VeeringTriangulationLinearFamilies
             sage: f = VeeringTriangulationLinearFamilies.triangle_3_4_13_unfolding_orbit_closure()
             sage: f
+            VeeringTriangulationLinearFamily("(0,9,~8)(1,8,2)(3,11,~10)(4,~14,15)(5,~15,12)(6,~16,13)(7,~0,22)(10,14,~9)(16,~12,~4)(17,20,~18)(18,~5,~23)(19,~22,~21)(21,~13,23)(~20,~6,~17)(~19,~7,~1)(~11,~2,~3)", "BBRBRBRRRRRRRRBRBBRRRBRR", [(1, phi, 0, 0, 0, 1, 0, 0, -phi, -phi - 1, 0, 0, -phi, -phi, phi + 1, -phi - 1, phi, 0, 0, -phi, 0, phi - 1, -1, -1), (0, 0, 1, 0, 0, 0, phi - 1, 0, 1, 1, 1, 1, 0, phi - 1, 0, 0, 0, 0, phi - 1, 0, phi - 1, 0, 0, phi - 1), (0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, -1, 0, 0, 0, 0, 0, phi - 1, 0, 0, -phi + 1, 0, 0, 0), (0, 0, 0, 0, 1, 0, 0, phi - 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, phi - 1, 0, 0, phi - 1, 0)])
         """
         from surface_dynamics import QuadraticStratum
         from sage.rings.rational_field import QQ

veerer/veering_triangulation.py

@@ -21,13 +21,6 @@
 
 from random import choice, shuffle
 
-def serialize_matrix(mat):
-    # if we have a number field!?
-    if mat.base_ring() not in [ZZ, QQ]:
-        raise NotImplementedError
-    return '_'.join(map(str, mat.list()))
-
-
 
 # TODO: better to make something topological (ie no equations)
 class VeeringTriangulation(Triangulation):
@@ -640,24 +633,6 @@ def _richcmp_(self, other, op):
         c = (self._ep > other._ep) - (self._ep < other._ep)
         return rich_to_bool(op, c)
 
-    def gl2r_plane(self, s, t):
-        r"""
-        Return the GL(2,R)-plane generated by the triangulations with vectors s and t
-        """
-        switch = self.switch_matrix()
-        switch2 = matrix(switch.base_ring(), switch.nrows() + 2, switch.ncols())
-        switch2[:switch.nrows()] = switch
-        i = switch.nrows()
-        r = switch.rank()
-        for v in matrix([s, t]).right_kernel_matrix().rows():
-            switch2[i] = v
-            if switch2.rank() == r + 1:
-                i += 1
-                r += 1
-            if i == switch2.nrows():
-                break
-        LinearFamily
-
     def to_core(self, slope=VERTICAL):
         r"""
         Change the colour of each forward (reps. backward) flippable edge in
@@ -2468,46 +2443,6 @@ def flip_back(self, e, col, Lx=None, Gx=None, check=True):
             Gx.add_multiple_of_column(e, a, +1)
             Gx.add_multiple_of_column(e, b, +1)
 
-    def switch_matrix(self, slope=VERTICAL):
-        r"""
-        Return the matrix of switch conditions.
-
-        Each row represents a linear constraints on the edge weights.
-
-        EXAMPLES::
-
-            sage: from veerer import VeeringTriangulation, HORIZONTAL
-            sage: vt = VeeringTriangulation("(0,1,2)(3,4,5)(6,7,8)(~8,~0,~7)(~6,~1,~5)(~4,~2,~3)", "RRBRRBRRB")
-            sage: vt.switch_matrix()
-            [ 1 -1  1  0  0  0  0  0  0]
-            [ 0  0  0  1 -1  1  0  0  0]
-            [ 0  0  0  0  0  0  1 -1  1]
-            [ 1  0  0  0  0  0  0 -1  1]
-            [ 0  1  0  0  0 -1 -1  0  0]
-            [ 0  0  1  1 -1  0  0  0  0]
-            sage: vt.switch_matrix(HORIZONTAL)
-            [ 1 -1 -1  0  0  0  0  0  0]
-            [ 0  0  0  1 -1 -1  0  0  0]
-            [ 0  0  0  0  0  0  1 -1 -1]
-            [ 1  0  0  0  0  0  0 -1 -1]
-            [ 0  1  0  0  0  1 -1  0  0]
-            [ 0  0  1 -1  1  0  0  0  0]
-        """
-        require_package('sage', 'switch_matrix')
-
-        from sage.matrix.constructor import matrix
-        from sage.modules.free_module_element import vector
-        from sage.rings.integer_ring import ZZ
-
-        m = self.num_edges()
-        cs = ppl.Constraint_System()
-        x = [ppl.Variable(e) for e in range(m)]
-        self._set_switch_conditions(cs.insert, x, slope)
-        switch_mat = matrix(ZZ, len(cs), m)
-        for i, g in enumerate(cs):
-            switch_mat[i] = vector(ZZ, g.coefficients())
-        return switch_mat
-
     def _set_switch_conditions(self, insert, x, slope=VERTICAL):
         r"""
         These are the linear parts of the train-track equations
@@ -2869,31 +2804,6 @@ def train_track_min_solution(self, slope=VERTICAL, allow_degenerations=False):
         self._set_train_track_constraints(M.add_constraint, x, slope, 1, allow_degenerations)
         return M.optimizing_point()
 
-    def _set_linear_subspace_constraints(self, insert, x, y, Lx):
-        Ly = self._complexify_equations(Lx)
-        for l in Lx:
-            l *= l.denominator()
-            l = sum(coeff * x[e] for e,coeff in enumerate(l))
-            insert(l == 0)
-        for l in Ly:
-            l *= l.denominator()
-            l = sum(coeff * y[e] for e,coeff in enumerate(l))
-            insert(l == 0)
-
-    def _linear_subspace_generator_system(self, x, y, Gx):
-        # construct linear equations from given generators
-        # (insert must be from a generator)
-        Gy = self._complexify_generators(Gx)
-        gs = ppl.Generator_System()
-        gs.insert(ppl.point())
-        for g in Gx:
-            g = sum(coeff * x[e] for e,coeff in enumerate(g))
-            gs.insert(ppl.line(g))
-        for g in Gy:
-            g = sum(coeff * y[e] for e,coeff in enumerate(g))
-            gs.insert(ppl.line(g))
-        return gs
-
     def geometric_polytope(self, x_low_bound=0, y_low_bound=0, hw_bound=0, backend='ppl'):
         r"""
         Return the geometric polytope of this veering triangulation.