How to use the diffcp.cones._proj function in diffcp

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github cvxgrp / diffcp / tests.py View on Github external
def test_proj_exp(self):
        np.random.seed(0)
        for _ in range(15):
            x = np.random.randn(9)
            var = cp.Variable(9)
            constr = [cp.constraints.ExpCone(var[0], var[1], var[2])]
            constr.append(cp.constraints.ExpCone(var[3], var[4], var[5]))
            constr.append(cp.constraints.ExpCone(var[6], var[7], var[8]))
            obj = cp.Minimize(cp.norm(var[0:3] - x[0:3]) +
                              cp.norm(var[3:6] - x[3:6]) +
                              cp.norm(var[6:9] - x[6:9]))
            prob = cp.Problem(obj, constr)
            prob.solve(solver="SCS", eps=1e-12)
            p = cone_lib._proj(x, cone_lib.EXP, dual=False)
            np.testing.assert_allclose(p, var.value, atol=1e-6)
            # x + Pi_{exp}(-x) = Pi_{exp_dual}(x)
            p_dual = cone_lib._proj(x, cone_lib.EXP_DUAL, dual=False)
            var = cp.Variable(9)
            constr = [cp.constraints.ExpCone(var[0], var[1], var[2])]
            constr.append(cp.constraints.ExpCone(var[3], var[4], var[5]))
            constr.append(cp.constraints.ExpCone(var[6], var[7], var[8]))
            obj = cp.Minimize(cp.norm(var[0:3] + x[0:3]) +
                              cp.norm(var[3:6] + x[3:6]) +
                              cp.norm(var[6:9] + x[6:9]))
            prob = cp.Problem(obj, constr)
            prob.solve(solver="SCS", eps=1e-12)
            np.testing.assert_allclose(
                p_dual, x + var.value, atol=1e-6)
github cvxgrp / diffcp / tests.py View on Github external
np.random.randint(1, 10))]
            psd_dim = [np.random.randint(1, 10) for _ in range(
                np.random.randint(1, 10))]
            exp_dim = np.random.randint(3, 18)
            cones = [(cone_lib.ZERO, zero_dim), (cone_lib.POS, pos_dim),
                     (cone_lib.SOC, soc_dim), (cone_lib.PSD, psd_dim),
                     (cone_lib.EXP, exp_dim), (cone_lib.EXP_DUAL, exp_dim)]
            size = zero_dim + pos_dim + sum(soc_dim) + sum(
                [cone_lib.vec_psd_dim(d) for d in psd_dim]) + 2 * 3 * exp_dim
            x = np.random.randn(size)
            for dual in [False, True]:
                proj = cone_lib.pi(x, cones, dual=dual)

                offset = 0
                np.testing.assert_allclose(proj[:zero_dim],
                                           cone_lib._proj(x[:zero_dim], cone_lib.ZERO, dual=dual))
                offset += zero_dim

                np.testing.assert_allclose(proj[offset:offset + pos_dim],
                                           cone_lib._proj(x[offset:offset + pos_dim], cone_lib.POS,
                                                          dual=dual))
                offset += pos_dim

                for dim in soc_dim:
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.SOC,
                                                              dual=dual))
                    offset += dim

                for dim in psd_dim:
                    dim = cone_lib.vec_psd_dim(dim)
                    np.testing.assert_allclose(proj[offset:offset + dim],
github cvxgrp / diffcp / tests.py View on Github external
def _test_dproj(self, cone, dual, n, x=None, tol=1e-8):
        if x is None:
            x = np.random.randn(n)
        dx = 1e-6 * np.random.randn(n)
        proj_x = cone_lib._proj(x, CPP_CONES_TO_SCS[cone.type], dual)
        z = cone_lib._proj(x + dx, CPP_CONES_TO_SCS[cone.type], dual)

        Dpi = _diffcp.dprojection(x, [cone], dual)
        np.testing.assert_allclose(Dpi.matvec(dx), z - proj_x, atol=tol)

        Dpi_dense = _diffcp.dprojection_dense(x, [cone], dual)
        np.testing.assert_allclose(Dpi_dense @ dx, z - proj_x, atol=tol)

        # assure that dense and linear operator are the same.
        for i in range(n):
            ei = np.zeros(n)
            ei[i] = 1.0
            np.testing.assert_allclose(Dpi.matvec(ei), Dpi_dense[:, i])
github cvxgrp / diffcp / tests.py View on Github external
def test_proj_pos(self):
        np.random.seed(0)
        n = 100
        for _ in range(15):
            x = np.random.randn(n)
            p = cone_lib._proj(x, cone_lib.POS, dual=False)
            np.testing.assert_allclose(p, np.maximum(x, 0))
            np.testing.assert_allclose(
                p, cone_lib._proj(x, cone_lib.POS, dual=True))
github cvxgrp / diffcp / tests.py View on Github external
for dim in soc_dim:
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.SOC,
                                                              dual=dual))
                    offset += dim

                for dim in psd_dim:
                    dim = cone_lib.vec_psd_dim(dim)
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.PSD,
                                                              dual=dual))
                    offset += dim

                dim = 3 * exp_dim
                np.testing.assert_allclose(proj[offset:offset + dim],
                                           cone_lib._proj(x[offset:offset + dim], cone_lib.EXP, dual=dual))
                offset += dim

                np.testing.assert_allclose(proj[offset:],
                                           cone_lib._proj(x[offset:], cone_lib.EXP_DUAL, dual=dual))
github cvxgrp / diffcp / tests.py View on Github external
def test_proj_pos(self):
        np.random.seed(0)
        n = 100
        for _ in range(15):
            x = np.random.randn(n)
            p = cone_lib._proj(x, cone_lib.POS, dual=False)
            np.testing.assert_allclose(p, np.maximum(x, 0))
            np.testing.assert_allclose(
                p, cone_lib._proj(x, cone_lib.POS, dual=True))
github cvxgrp / diffcp / tests.py View on Github external
cones = [(cone_lib.ZERO, zero_dim), (cone_lib.POS, pos_dim),
                     (cone_lib.SOC, soc_dim), (cone_lib.PSD, psd_dim),
                     (cone_lib.EXP, exp_dim), (cone_lib.EXP_DUAL, exp_dim)]
            size = zero_dim + pos_dim + sum(soc_dim) + sum(
                [cone_lib.vec_psd_dim(d) for d in psd_dim]) + 2 * 3 * exp_dim
            x = np.random.randn(size)
            for dual in [False, True]:
                proj = cone_lib.pi(x, cones, dual=dual)

                offset = 0
                np.testing.assert_allclose(proj[:zero_dim],
                                           cone_lib._proj(x[:zero_dim], cone_lib.ZERO, dual=dual))
                offset += zero_dim

                np.testing.assert_allclose(proj[offset:offset + pos_dim],
                                           cone_lib._proj(x[offset:offset + pos_dim], cone_lib.POS,
                                                          dual=dual))
                offset += pos_dim

                for dim in soc_dim:
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.SOC,
                                                              dual=dual))
                    offset += dim

                for dim in psd_dim:
                    dim = cone_lib.vec_psd_dim(dim)
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.PSD,
                                                              dual=dual))
                    offset += dim
github cvxgrp / diffcp / tests.py View on Github external
np.testing.assert_allclose(proj[offset:offset + pos_dim],
                                           cone_lib._proj(x[offset:offset + pos_dim], cone_lib.POS,
                                                          dual=dual))
                offset += pos_dim

                for dim in soc_dim:
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.SOC,
                                                              dual=dual))
                    offset += dim

                for dim in psd_dim:
                    dim = cone_lib.vec_psd_dim(dim)
                    np.testing.assert_allclose(proj[offset:offset + dim],
                                               cone_lib._proj(x[offset:offset + dim], cone_lib.PSD,
                                                              dual=dual))
                    offset += dim

                dim = 3 * exp_dim
                np.testing.assert_allclose(proj[offset:offset + dim],
                                           cone_lib._proj(x[offset:offset + dim], cone_lib.EXP, dual=dual))
                offset += dim

                np.testing.assert_allclose(proj[offset:],
                                           cone_lib._proj(x[offset:], cone_lib.EXP_DUAL, dual=dual))
github cvxgrp / diffcp / tests.py View on Github external
def test_proj_soc(self):
        np.random.seed(0)
        n = 100
        for _ in range(15):
            x = np.random.randn(n)
            z = cp.Variable(n)
            objective = cp.Minimize(cp.sum_squares(z - x))
            constraints = [cp.norm(z[1:], 2) <= z[0]]
            prob = cp.Problem(objective, constraints)
            prob.solve(solver="SCS", eps=1e-10)
            p = cone_lib._proj(x, cone_lib.SOC, dual=False)
            np.testing.assert_allclose(
                p, np.array(z.value))
            np.testing.assert_allclose(
                p, cone_lib._proj(x, cone_lib.SOC, dual=True))