def test_matrix_sq2norm_sqcon(): """ Relaxed Form : Minimize(square(norm(v0))) with v0 >= square(v1) """ v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(norm(v0 + v1)) con = [v0 >= square(v1)] # should become -v0 + square(v1) <= 0 p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True) sym3 = [v for vn, v in c.vars.items() if vn == 'sym3'][0] assert_A = {'row': [0, 0, 0], 'col': [0, 1, 4], 'val': [Constant(-1.0), Constant(-1.0), Constant(1.0)]} assert_b = [Constant(0.0)] #assert_G = {'row': [0, 0, 1, 2, 3, 4, 5, 6, 7, 8], # 'col': [0, 5, 3, 4, 2, 2, 3, 5, 5, 1], # 'val': [Constant(-1.0), Constant(0.0), Constant(-1.0), Constant(1.0), # Constant(-1.0), Constant(-1.0), Constant(2.0), Constant(-1.0), # Constant(-1.0), Constant(2.0)]} assert_G = {'row': [0, 0, 1, 2, 3, 4, 5, 6, 7, 8], 'col': [0, 5, 3, 4, 2, 2, 3, 5, 5, 1], 'val': [Constant(-1.0), Constant(1.0), Constant(-1.0), Constant(1.0), Constant(-1.0), Constant(-1.0), Constant(2.0), Constant(-1.0), Constant(-1.0), Constant(2.0)]} assert_h = [ (-1.0 * sym3), Constant(0.0), Constant(0.0), Constant(1.0), Constant(-1.0), Constant(0.0), Constant(1.0), Constant(-1.0), Constant(0.0)] assert_h = [Constant(0.0), Constant(0.0), Constant(0.0), Constant(1.0), Constant(-1.0), Constant(0.0), Constant(1.0), Constant(-1.0), Constant(0.0)] assert_dims = {'q': [2, 3, 3], 'l': 1} assert_A = COO_to_CS(assert_A, (len(assert_b), len(c.c)), 'col') assert_G = COO_to_CS(assert_G, (len(assert_h), len(c.c)), 'col') assert_c = [0.0, 0.0, 1.0, 0.0, 0.0, 0.0] assert(c.c == assert_c) assert(c.A == assert_A) assert(c.b == assert_b) assert(c.G == assert_G) assert(all([c.h[n].value == t.value for n, t in enumerate(assert_h)])) assert(c.dims == assert_dims) reset_symbols()
def test_elementwisesymbol_into_function(): """ Test a shaped symbol input to a scalar function and the elementwise output """ x = Variable((3, 1), name='x') expr = square(x) print(expr) constr = (expr <= 0) print(constr) expand = constr.expand() print(expand) assert (type(constr.expr) is sums.sum) assert (type(constr.expr.args[0]) is Vector) assert (len(constr.expr.args[0].args) == 3) assert (len(expand) == 3) assert (all([type(a) is le for a in expand])) reset_symbols()
def test_square_graph(): v0 = Variable(name='v0') s0 = Symbol(name='s0') expr = square(v0) constr = (expr <= s0) # effectively in relaxed smith form print('Graph form of', end='') print(constr) constr = constr.graph_form() print('-->', constr) print() n = max(v0.shape[0], v0.shape[1]) assert (constr.dims == n + 2) assert (type(constr) is SecondOrderConeConstraint) assert (all([type(c) is le for c in constr.constraints])) c = constr # keeps below names same as other tests string_equals = [ """(-1.0 + (-1.0 * s0)) <= 0""", """(1.0 + (-1.0 * s0)) <= 0""", """((2.0 * v0)) <= 0""" ] for n, string in enumerate(string_equals): print(c.constraints[n], '==', string, '?') assert (str(c.constraints[n]) == str(string)) print('SUCCESS!') reset_symbols()
def test_matrix_sq(): """ Matrix Form of Minimize(square(v0)) """ v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(v0) con = [] p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True) assert(c.c == [0, 0, 1]) assert(c.A is None) assert(c.b is None) assert_G = { 'row':[0, 1, 2], 'col':[2, 2, 0], 'val':[Constant(-1.0), Constant(-1.0), Constant(2.0)] } assert_h = [Constant(1.0), Constant(-1.0), Constant(0.0)] assert_G = COO_to_CS(assert_G, (len(assert_h), len(c.c)), 'col') assert(c.G == assert_G) assert(all([c.h[n].value == t.value for n, t in enumerate(assert_h)])) assert(c.dims == {'q': [3], 'l': 0}) reset_symbols()
def test_relax_sq2norm_constr(): """ Relaxed Form of Minimize(square(norm(v0))) with v0 >= p0""" v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(norm(v0)) con = [v0 >= p0] # should become -v0 + p0 <= 0 p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True, only='relax') assert( type(c.constraints[-1]) is le) assert( type(c.constraints[-1].expr) is sums.sum) assert( type(c.constraints[-1].expr.args[0]) is muls.smul) assert( type(c.constraints[-1].expr.args[1]) is muls.smul) assert( c.objective is not obj ) assert( 'sym0' == c.objective.name ) string_equals = [ """((-1.0 * sym1) + (1.0 * norm2(v0))) <= 0""", """((-1.0 * sym0) + (1.0 * square(sym1))) <= 0""", """((-1.0 * v0) + (p0 * 1.0)) <= 0""", ] for n, string in enumerate(string_equals): print(c.constraints[n],'==',string,'?') assert(str(c.constraints[n]) == string) print('SUCCESS!') reset_symbols()
def test_relax_sq2norm(): """ Relaxed Form of Minimize(square(norm(v0))) """ v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(norm(v0)) con = [] p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True, only='relax') assert( c.objective is not obj ) assert( 'sym0' == c.objective.name ) # Let up on the testing rigor a bit, now that we checked core fundamentals string_equals = [ """((-1.0 * sym1) + (1.0 * norm2(v0))) <= 0""", """((-1.0 * sym0) + (1.0 * square(sym1))) <= 0""", ] for n, string in enumerate(string_equals): print(c.constraints[n],'==',string,'?') assert(str(c.constraints[n]) == string) print('SUCCESS!') reset_symbols()
def test_relax_sq(): """ Relaxed Form of Minimize(square(v0)) """ v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(v0) con = [] p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True, only='relax') assert( len(c.constraints) == 1 ) assert( c.objective is not obj ) assert( 'sym0' == c.objective.name ) assert(type(c.constraints[0]) is le) assert(c.constraints[0].expr.args[0].curvature == 0) assert(c.constraints[0].expr.args[1].curvature == +1) assert(c.constraints[0].expr.args[1].symbol_groups()[0][0].value == 1.0) assert(c.constraints[0].expr.args[1].symbol_groups()[2][0].name == 'square') reset_symbols()
def test_relax_least_squares_constr(): """ Relaxed Form : Minimize(square(norm(F*x - g))) with x >= p0 """ x = Variable ((3,1),name='x') F = Parameter((3,3),name='F') g = Parameter((3,1),name='g') objective = square(norm( F*x - g )) objective = Minimize(objective) problem = Problem(objective, [x >= 0]) c = Canonicalize(problem, verbose=True, only='relax') string_equals = [ """(sym2 + (-1.0 * matmul(F, x))) == 0""", """(sym3 + (-1.0 * sym2) + (g * 1.0)) == 0""", """((-1.0 * sym1) + (1.0 * norm2(sym3))) <= 0""", """((-1.0 * sym0) + (1.0 * square(sym1))) <= 0""", """((-1.0 * x)) <= 0""", ] for n, string in enumerate(string_equals): print(c.constraints[n],' ???? ',string, end=' ') assert(str(c.constraints[n]) == string) print('... SUCCESS!') reset_symbols()
def test_smith_sq(): """ Smith Form of Minimize(square(v0)) """ v0 = Variable(name='v0') v1 = Variable(name='v1') p0 = Parameter(name='p0') p1 = Parameter(name='p1') obj = square(v0) con = [] p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True, only='smith') assert (len(c.constraints) == 1) assert (c.objective is not obj) assert ('sym0' == c.objective.name) assert (hasattr(c.constraints[0].expr.args[0], 'name')) assert (c.constraints[0].expr.args[0].name == 'sym0') assert (hasattr(c.constraints[0].expr.args[1], 'args')) assert (hasattr(c.constraints[0].expr.args[1].args[0], 'value')) assert (c.constraints[0].expr.args[1].args[0].value == -1.0) assert (hasattr(c.constraints[0].expr.args[1].args[1], 'name')) assert (c.constraints[0].expr.args[1].args[1].name == 'square') reset_symbols()
def test_smith_sq2norm_sqcon(): """ Smith Form : Minimize(square(norm(v0))) with v0 >= square(v1) """ v0 = Variable(name='v0') v1 = Variable(name='v1') p0 = Parameter(name='p0') p1 = Parameter(name='p1') obj = square(norm(v0 + v1)) con = [v0 >= square(v1)] # should become -v0 + square(v1) <= 0 p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True, only='smith') assert (type(c.constraints[-1]) is le) assert (type(c.constraints[-1].expr) is sums.sum) assert (type(c.constraints[-1].expr.args[0]) is muls.smul) assert (type(c.constraints[-1].expr.args[1]) is muls.smul) assert (c.objective is not obj) assert ('sym0' == c.objective.name) string_equals = [ """(sym2 + (-1.0 * v0) + (-1.0 * v1)) == 0""", """(sym1 + (-1.0 * norm2(sym2))) == 0""", """(sym0 + (-1.0 * square(sym1))) == 0""", """(sym3 + (-1.0 * square(v1))) == 0""", """((-1.0 * v0) + (1.0 * sym3)) <= 0""", ] for n, string in enumerate(string_equals): print(c.constraints[n], ' ???? ', string, end=' ') assert (str(c.constraints[n]) == string) print('... SUCCESS!') reset_symbols()
def test_matrix_least_squares_constr(): """ Minimize(square(norm(F*x - g))) with x >= p0 """ x = Variable ((3,1),name='x') F = Parameter((3,3),name='F') g = Parameter((3,1),name='g') objective = square(norm( F*x - g )) objective = Minimize(objective) problem = Problem(objective, [x >= 1]) c = Canonicalize(problem, verbose=True) # Test for errors, not asserts, and for solution outcome (via ecos_solution) reset_symbols()
def test_matrix_sq2norm_constr(): """ Matrix Form of Minimize(square(norm(v0))) with v0 >= p0""" v0 = Variable(name = 'v0') v1 = Variable(name = 'v1') p0 = Parameter(name = 'p0') p1 = Parameter(name = 'p1') obj = square(norm(v0)) con = [v0 >= p0] # should become -v0 + p0 <= 0 p = Problem(Minimize(obj), con) c = Canonicalize(p, verbose=True) assert_c = [0.0, 0.0, 1.0, 0.0] assert_A = COO_to_CS({'row':[],'col':[],'val':[]}, (0,4), 'col') assert_G = {'row': [0, 1, 2, 3, 4, 5], 'col': [0, 3, 0, 2, 2, 3], 'val': [Constant(-1.0), Constant(-1.0), Constant(1.0), Constant(-1.0), Constant(-1.0), Constant(2.0)]} assert_h = [(-1.0 * p0), Constant(0.0), Constant(0.0), Constant(1.0), Constant(-1.0), Constant(0.0)] assert_G = COO_to_CS(assert_G, (len(assert_h), len(c.c)), 'col') assert(c.c == assert_c) assert(c.A is None) assert(c.b is None) assert(c.G == assert_G) assert(all([c.h[n].value == t.value for n, t in enumerate(assert_h)])) assert(c.dims == {'q': [2, 3], 'l': 1}) reset_symbols()
def test_elementwiselist_into_function(): """ Test a list input to a scalar function and the elementwise output """ x = Variable(name='x') y = Variable(name='y') z = Variable(name='z') a = Variable(name='a') b = Variable(name='b') c = Variable(name='c') expr = square([x, y, z, a, b, c]) print(expr) constr = (expr <= 0) print(constr) assert (type(constr.expr) is sums.sum) assert (type(constr.expr.args[0]) is Vector) assert (len(constr.expr.args[0].args) == 6) reset_symbols()