Clean up PEGASIS submodule inclusion

1 files changed, 0 insertions, 292 deletions

diff --git a/theta_lib/isogenies_dim2/gluing_isogeny_dim2.py b/theta_lib/isogenies_dim2/gluing_isogeny_dim2.py
deleted file mode 100644
index 2dac387..0000000
--- a/theta_lib/isogenies_dim2/gluing_isogeny_dim2.py
+++ /dev/null
@@ -1,292 +0,0 @@
-"""
-This code is based on a copy of:
-https://github.com/ThetaIsogenies/two-isogenies
-
-MIT License
-
-Copyright (c) 2023 Pierrick Dartois, Luciano Maino, Giacomo Pope and Damien Robert
-
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
-
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
-
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
-"""
-
-from sage.all import *
-from ..theta_structures.Tuple_point import TuplePoint
-from ..theta_structures.Theta_dim2 import ThetaStructureDim2, ThetaPointDim2
-from ..theta_structures.theta_helpers_dim2 import batch_inversion
-from ..basis_change.base_change_dim2 import montgomery_to_theta_matrix_dim2, apply_base_change_theta_dim2
-from ..theta_structures.montgomery_theta import lift_kummer_montgomery_point
-
-class GluingThetaIsogenyDim2:
-    """
-    Compute the gluing isogeny from E1 x E2 (Elliptic Product) -> A (Theta Model)
-
-    Expected input:
-
-    - (K1_8, K2_8) The 8-torsion above the kernel generating the isogeny
-    - M (Optional) a base change matrix, if this is not including, it can
-      be derived from [2](K1_8, K2_8)
-    """
-
-    def __init__(self, K1_8, K2_8, Theta12, N):
-        # Double points to get four-torsion, we always need one of these, used
-        # for the image computations but we'll need both if we wish to derived
-        # the base change matrix as well
-        K1_4 = 2*K1_8
-
-        # Initalise self
-        # This is the base change matrix for product Theta coordinates (not used, except in the dual)
-        self._base_change_matrix_theta = N
-        # Here, base change matrix directly applied to the Montgomery coordinates. null_point_bc is the 
-        # theta null point obtained after applying the base change to the product Theta-structure.
-        self._base_change_matrix, null_point_bc = montgomery_to_theta_matrix_dim2(Theta12.zero().coords(),N, return_null_point = True)
-        self._domain_bc = ThetaStructureDim2(null_point_bc)
-        self.T_shift = K1_4
-        self._precomputation = None
-        self._zero_idx = 0
-        self._domain_product = Theta12
-        self._domain=(K1_8[0].curve(), K1_8[1].curve())
-
-        # Map points from elliptic product onto the product theta structure
-        # using the base change matrix
-        T1_8 = self.base_change(K1_8)
-        T2_8 = self.base_change(K2_8)
-
-        # Compute the codomain of the gluing isogeny
-        self._codomain = self._special_compute_codomain(T1_8, T2_8)
-
-    def apply_base_change(self, coords):
-        """
-        Apply the basis change by acting with matrix multiplication, treating
-        the coordinates as a vector
-        """
-        N = self._base_change_matrix
-        x, y, z, t = coords
-        X = N[0, 0] * x + N[0, 1] * y + N[0, 2] * z + N[0, 3] * t
-        Y = N[1, 0] * x + N[1, 1] * y + N[1, 2] * z + N[1, 3] * t
-        Z = N[2, 0] * x + N[2, 1] * y + N[2, 2] * z + N[2, 3] * t
-        T = N[3, 0] * x + N[3, 1] * y + N[3, 2] * z + N[3, 3] * t
-
-        return (X, Y, Z, T)
-
-    def base_change(self, P):
-        """
-        Compute the basis change on a TuplePoint to recover a ThetaPointDim2 of
-        compatible form
-        """
-        if not isinstance(P, TuplePoint):
-            raise TypeError("Function assumes that the input is of type `TuplePoint`")
-
-        # extract X,Z coordinates on pairs of points
-        P1, P2 = P.points()
-        X1, Z1 = P1[0], P1[2]
-        X2, Z2 = P2[0], P2[2]
-
-        # Correct in the case of (0 : 0)
-        if X1 == 0 and Z1 == 0:
-            X1 = 1
-            Z1 = 0
-        if X2 == 0 and Z2 == 0:
-            X2 = 1
-            Z2 = 0
-
-        # Apply the basis transformation on the product
-        coords = self.apply_base_change([X1 * X2, X1 * Z2, Z1 * X2, Z1 * Z2])
-        return coords
-
-    def _special_compute_codomain(self, T1, T2):
-        """
-        Given twzero_matro isotropic points of 8-torsion T1 and T2, compatible with
-        the theta null point, compute the level two theta null point A/K_2
-        """
-        xAxByCyD = ThetaPointDim2.to_squared_theta(*T1)
-        zAtBzYtD = ThetaPointDim2.to_squared_theta(*T2)
-
-        # Find the value of the non-zero index
-        zero_idx = next((i for i, x in enumerate(xAxByCyD) if x == 0), None)
-        self._zero_idx = zero_idx
-
-        # Dumb check to make sure everything is OK
-        assert xAxByCyD[self._zero_idx] == zAtBzYtD[self._zero_idx] == 0
-
-        # Initialize lists
-        # The zero index described the permutation
-        ABCD = [0 for _ in range(4)]
-        precomp = [0 for _ in range(4)]
-
-        # Compute non-trivial numerators (Others are either 1 or 0)
-        num_1 = zAtBzYtD[1 ^ self._zero_idx]
-        num_2 = xAxByCyD[2 ^ self._zero_idx]
-        num_3 = zAtBzYtD[3 ^ self._zero_idx]
-        num_4 = xAxByCyD[3 ^ self._zero_idx]
-
-        # Compute and invert non-trivial denominators
-        den_1, den_2, den_3, den_4 = batch_inversion([num_1, num_2, num_3, num_4])
-
-        # Compute A, B, C, D
-        ABCD[0 ^ self._zero_idx] = 0
-        ABCD[1 ^ self._zero_idx] = num_1 * den_3
-        ABCD[2 ^ self._zero_idx] = num_2 * den_4
-        ABCD[3 ^ self._zero_idx] = 1
-
-        # Compute precomputation for isogeny images
-        precomp[0 ^ self._zero_idx] = 0
-        precomp[1 ^ self._zero_idx] = den_1 * num_3
-        precomp[2 ^ self._zero_idx] = den_2 * num_4
-        precomp[3 ^ self._zero_idx] = 1
-        self._precomputation = precomp
-
-        # Final Hadamard of the above coordinates
-        a, b, c, d = ThetaPointDim2.to_hadamard(*ABCD)
-
-        return ThetaStructureDim2([a, b, c, d])
-
-    def special_image(self, P, translate):
-        """
-        When the domain is a non product theta structure on a product of
-        elliptic curves, we will have one of A,B,C,D=0, so the image is more
-        difficult. We need to give the coordinates of P but also of
-        P+Ti, Ti one of the point of 4-torsion used in the isogeny
-        normalisation
-        """
-        AxByCzDt = ThetaPointDim2.to_squared_theta(*P)
-
-        # We are in the case where at most one of A, B, C, D is
-        # zero, so we need to account for this
-        #
-        # To recover values, we use the translated point to get
-        AyBxCtDz = ThetaPointDim2.to_squared_theta(*translate)
-
-        # Directly compute y,z,t
-        y = AxByCzDt[1 ^ self._zero_idx] * self._precomputation[1 ^ self._zero_idx]
-        z = AxByCzDt[2 ^ self._zero_idx] * self._precomputation[2 ^ self._zero_idx]
-        t = AxByCzDt[3 ^ self._zero_idx]
-
-        # We can compute x from the translation
-        # First we need a normalisation
-        if z != 0:
-            zb = AyBxCtDz[3 ^ self._zero_idx]
-            lam = z / zb
-        else:
-            tb = AyBxCtDz[2 ^ self._zero_idx] * self._precomputation[2 ^ self._zero_idx]
-            lam = t / tb
-
-        # Finally we recover x
-        xb = AyBxCtDz[1 ^ self._zero_idx] * self._precomputation[1 ^ self._zero_idx]
-        x = xb * lam
-
-        xyzt = [0 for _ in range(4)]
-        xyzt[0 ^ self._zero_idx] = x
-        xyzt[1 ^ self._zero_idx] = y
-        xyzt[2 ^ self._zero_idx] = z
-        xyzt[3 ^ self._zero_idx] = t
-
-        image = ThetaPointDim2.to_hadamard(*xyzt)
-        return self._codomain(image)
-
-    def __call__(self, P):
-        """
-        Take into input the theta null point of A/K_2, and return the image
-        of the point by the isogeny
-        """
-        if not isinstance(P, TuplePoint):
-            raise TypeError(
-                "Isogeny image for the gluing isogeny is defined to act on TuplePoints"
-            )
-
-        # Compute sum of points on elliptic curve
-        P_sum_T = P + self.T_shift
-
-        # Push both the point and the translation through the
-        # completion
-        iso_P = self.base_change(P)
-        iso_P_sum_T = self.base_change(P_sum_T)
-
-        return self.special_image(iso_P, iso_P_sum_T)
-
-    def dual(self):
-        domain = self._codomain.hadamard()
-        codomain_bc = self._domain_bc.hadamard()
-        codomain = self._domain
-
-        precomputation = batch_inversion(codomain_bc.null_point_dual())
-
-        N_split = self._base_change_matrix.inverse()
-
-        return DualGluingThetaIsogenyDim2(domain, codomain_bc, codomain, N_split, precomputation)
-
-
-class DualGluingThetaIsogenyDim2:
-    def __init__(self, domain, codomain_bc, codomain, N_split, precomputation):
-        self._domain = domain
-        self._codomain_bc = codomain_bc # Theta structure
-        self._codomain = codomain # Elliptic curves E1 and E2
-        self._precomputation = precomputation
-        self._splitting_matrix = N_split
-
-    def __call__(self,P):
-        # Returns a TuplePoint.
-        if not isinstance(P, ThetaPointDim2):
-            raise TypeError("Isogeny evaluation expects a ThetaPointDim2 as input")
-
-        xx, yy, zz, tt = P.squared_theta()
-
-        Ai, Bi, Ci, Di = self._precomputation
-
-        xx = xx * Ai
-        yy = yy * Bi
-        zz = zz * Ci
-        tt = tt * Di
-
-        image_coords = (xx, yy, zz, tt)
-
-        X1X2, X1Z2, Z1X2, Z1Z2 = apply_base_change_theta_dim2(self._splitting_matrix, image_coords)
-
-        E1, E2 = self._codomain
-
-        if Z1Z2!=0:
-            #Z1=1, Z2=Z1Z2
-
-            Z2_inv=1/Z1Z2
-            X2=Z1X2*Z2_inv# Normalize (X2:Z2)=(X2/Z2:1)
-
-            X1=X1Z2*Z2_inv
-
-            assert X1*Z1X2==X1X2
-            P1 = lift_kummer_montgomery_point(E1, X1)
-            P2 = lift_kummer_montgomery_point(E2, X2)
-            return TuplePoint(P1,P2)
-        elif Z1X2==0 and X1Z2!=0:
-            # Case (X1:Z1)=0, X1!=0 and (X2:Z2)!=0
-
-            X2=X1X2/X1Z2
-            P2 = lift_kummer_montgomery_point(E2, X2)
-            return TuplePoint(E1(0),P2)
-        elif Z1X2!=0 and X1Z2==0:
-            # Case (X1:Z1)!=0 and (X2:Z2)=0, X2!=0
-
-            X1=X1X2/Z1X2
-            P1 = lift_kummer_montgomery_point(E1, X1)
-            return TuplePoint(P1,E2(0))
-        else:
-            return TuplePoint(E1(0),E2(0))
-
-
-
-
-