def plotTresserPairs(osc, bounds, bordersEq, ps, pathToDir, imageName):
eqList = sf.findEquilibria(osc.getRestriction, osc.getRestrictionJac, bounds, bordersEq,
sf.ShgoEqFinder(300, 30, 1e-10),ps)
gfe = sf.getTresserPairs(eqList, osc, ps)
xs = ys = np.linspace(0, +2 * np.pi, 1001)
res = np.zeros([len(xs), len(xs)])
for i, y in enumerate(ys):
for j, x in enumerate(xs):
res[i][j] = np.log10(np.dot(osc.getRestriction([x, y]), osc.getRestriction([x, y])) + 1e-10)
matplotlib.rcParams['figure.figsize'] = 10, 10
plt.pcolormesh(xs, ys, res, cmap=plt.cm.get_cmap('RdBu'))
plt.xlim([0, +2 * np.pi])
plt.ylim([0, +2 * np.pi])
plt.xlabel('$\gamma_3$')
plt.ylabel('$\gamma_4$')
plt.axes().set_aspect('equal', adjustable='box')
for pair in gfe:
saddle, sadfoc = pair
p1 = plt.scatter(saddle.coordinates[0], saddle.coordinates[1], c='green', s=40)
p2 = plt.scatter(sadfoc.coordinates[0], sadfoc.coordinates[1], c='red', s=40)
plt.legend([p1, p2], ["Седло", "Седло-фокус"])
fullOutputName = os.path.join(pathToDir, imageName + '.png')
plt.savefig(fullOutputName)
def workerChectTargHet(params):
(i, a), (j, b) = params
ud = [0.5, a, b, 1]
osc = sys.FourBiharmonicPhaseOscillators(ud[0], ud[1], ud[2], ud[3])
eqf = sf.ShgoEqFinder(300, 30, 1e-10)
result = fth.checkTargetHeteroclinic(osc, bordersEq, bounds, eqf,
sf.STD_PRECISION, sf.STD_PROXIMITY,
1000.)
return i, j, a, b, result
def workerCheckTarget(params, paramR, events, pset: sf.PrecisionSettings,
proxs: sf.ProximitySettings):
(i, a), (j, b) = params
ud = [0.5, a, b, paramR]
osc = a4d.FourBiharmonicPhaseOscillators(ud[0], ud[1], ud[2], ud[3])
eqf = sf.ShgoEqFinder(300, 30, 1e-10)
result = fth.checkTargetHeteroclinic(osc, bordersEq, bounds, eqf, pset,
proxs, 1000., events)
return i, j, a, b, result
def workerStartPts(params, pset: sf.PrecisionSettings):
(i, a), (j, b) = params
ud = [0.5, a, b, 1]
osc = a4d.FourBiharmonicPhaseOscillators(ud[0], ud[1], ud[2], ud[3])
eqf = sf.ShgoEqFinder(300, 30, 1e-10)
result = fth.getStartPtsForLyapVals(osc,
bordersEq,
bounds,
eqf,
pset,
OnlySadFoci=False)
return i, j, a, b, result
def test_FindEqInSinglePoint3(self, stdPS):
ud = [-1.5, 0.5, 0, 0]
rhsCurrent = lambda X: self.rhs(X, ud)
rhsJacCurrent = lambda X: self.rhsJac(X, ud)
res = sf.findEquilibria(rhsCurrent, rhsJacCurrent,
self.bounds, self.borders,
sf.ShgoEqFinder(300, 10, 4e-14), stdPS)
data = []
for eq in res:
data.append(eq.getEqType(stdPS)[0:3])
describe = sf.describePortrType(data)
assert describe == self.analyticFind(ud)
import time
#Задаем область поиска локальных минимумов для численного метода, а также более точную область поиска.
bounds = [(-0.1, +2 * np.pi + 0.1), (-0.1, +2 * np.pi + 0.1)]
bordersEq = [(-1e-15, +2 * np.pi + 1e-15), (-1e-15, +2 * np.pi + 1e-15)]
# Разбиваем значения параметров на сетку
N = 7 # Количество разбиений параметра альфа
M = 7 # Количество разбиений параметра бета
alphas = np.linspace(0, 2 * np.pi, N)
betas = np.linspace(0, 2 * np.pi, M)
ps = sf.STD_PRECISION
start = time.time()
for i, a in enumerate(alphas):
for j, b in enumerate(betas):
# Устанавливаем значения параметров системы
ud = [0.5, a, b, 1]
osc = a4d.FourBiharmonicPhaseOscillators(ud[0], ud[1], ud[2], ud[3])
eqf = sf.ShgoEqFinder(300, 30, 1e-10)
ret = fth.checkTargetHeteroclinic(osc, bordersEq, bounds, eqf,
sf.STD_PRECISION, sf.STD_PROXIMITY,
1000.)
end = time.time()
print("Took {}s".format(end - start))