Python tfocs示例

示例#1

def test_tfocs():
    n, p = 100, 200
    X = np.random.standard_normal((n, p))
    beta = np.zeros(p)
    beta[:4] = 3
    Y = np.random.standard_normal(n) + np.dot(X, beta)

    lscoef = np.dot(np.linalg.pinv(X), Y)
    minimum_l2 = np.linalg.norm(Y - np.dot(X, lscoef))
    maximum_l2 = np.linalg.norm(Y)

    l2bound = (minimum_l2 + maximum_l2) * 0.5

    constraint = rr.l2norm.affine(X,-Y,bound=l2bound)
    T, conjugate = constraint.dual
    l1 = rr.l1norm(p, lagrange=1)

    primal, dual = rr.tfocs(l1, T, conjugate, coef_tol=1.e-4)
    nt.assert_true(np.fabs(np.linalg.norm(Y - np.dot(X, primal)) - l2bound) <= l2bound * 1.e-3)

示例#2

文件： test_tfocs.py 项目： Xiaoying-Tian/regreg

"""
Solving basis pursuit with TFOCS
"""

import regreg.api as rr
import numpy as np
import nose.tools as nt

n, p = 100, 200
X = np.random.standard_normal((n, p))
beta = np.zeros(p)
beta[:4] = 3
Y = np.random.standard_normal(n) + np.dot(X, beta)

lscoef = np.dot(np.linalg.pinv(X), Y)
minimum_l2 = np.linalg.norm(Y - np.dot(X, lscoef))
maximum_l2 = np.linalg.norm(Y)

l2bound = (minimum_l2 + maximum_l2) * 0.5

constraint = rr.l2norm.affine(X,-Y,bound=l2bound)
T, conjugate = constraint.dual
l1 = rr.l1norm(p, lagrange=1)

primal, dual = rr.tfocs(l1, T, conjugate, coef_tol=1.e-4)
nt.assert_true(np.fabs(np.linalg.norm(Y - np.dot(X, primal)) - l2bound) <= l2bound * 1.e-3)

示例#3

"""
Solving basis pursuit with TFOCS
"""

import regreg.api as rr
import numpy as np
import nose.tools as nt

n, p = 100, 200
X = np.random.standard_normal((n, p))
beta = np.zeros(p)
beta[:4] = 3
Y = np.random.standard_normal(n) + np.dot(X, beta)

lscoef = np.dot(np.linalg.pinv(X), Y)
minimum_l2 = np.linalg.norm(Y - np.dot(X, lscoef))
maximum_l2 = np.linalg.norm(Y)

l2bound = (minimum_l2 + maximum_l2) * 0.5

l2 = rr.l2norm(n, bound=l2bound)
T = rr.affine_transform(X, -Y)
l1 = rr.l1norm(p, lagrange=1)

primal, dual = rr.tfocs(l1, T, l2, tol=1.e-10)
nt.assert_true(
    np.fabs(np.linalg.norm(Y - np.dot(X, primal)) - l2bound) <= l2bound *
    1.e-5)

示例#4

文件： test_tfocs.py 项目： amoliu/regreg

"""
Solving basis pursuit with TFOCS
"""

import regreg.api as rr
import numpy as np
import nose.tools as nt

n, p = 100, 200
X = np.random.standard_normal((n, p))
beta = np.zeros(p)
beta[:4] = 3
Y = np.random.standard_normal(n) + np.dot(X, beta)

lscoef = np.dot(np.linalg.pinv(X), Y)
minimum_l2 = np.linalg.norm(Y - np.dot(X, lscoef))
maximum_l2 = np.linalg.norm(Y)

l2bound = (minimum_l2 + maximum_l2) * 0.5

l2 = rr.l2norm(n, bound=l2bound)
T = rr.affine_transform(X, -Y)
l1 = rr.l1norm(p, lagrange=1)

primal, dual = rr.tfocs(l1, T, l2, tol=1.0e-10)
nt.assert_true(np.fabs(np.linalg.norm(Y - np.dot(X, primal)) - l2bound) <= l2bound * 1.0e-5)

示例#5

文件： test_tfocs.py 项目： matthew-brett/regreg

"""
Solving basis pursuit with TFOCS
"""

import regreg.api as rr
import numpy as np
import nose.tools as nt

n, p = 100, 200
X = np.random.standard_normal((n, p))
beta = np.zeros(p)
beta[:4] = 3
Y = np.random.standard_normal(n) + np.dot(X, beta)

lscoef = np.dot(np.linalg.pinv(X), Y)
minimum_l2 = np.linalg.norm(Y - np.dot(X, lscoef))
maximum_l2 = np.linalg.norm(Y)

l2bound = (minimum_l2 + maximum_l2) * 0.5

constraint = rr.l2norm.affine(X, -Y, bound=l2bound)
T, conjugate = constraint.dual
l1 = rr.l1norm(p, lagrange=1)

primal, dual = rr.tfocs(l1, T, conjugate, coef_tol=1.e-4)
nt.assert_true(
    np.fabs(np.linalg.norm(Y - np.dot(X, primal)) - l2bound) <= l2bound *
    1.e-3)