def gradFibonacci(xx: float, eps: float, x_min: float, x_max: float, dataPlot):
stop = False
p = plot(dataPlot.x_left, dataPlot.x_right, dataPlot.pr)
p.on(xx)
i = 0
while not stop:
#p.showPoint(xx)
def a(lmb):
return f(xx - lmb * df(xx))
x_l = xx
lmd = fibonacci(a, x_min, x_max, eps)
xx = xx - lmd * df(xx)
i += 1
#print("itter:", i, "| x:", xx)
if (abs(x_l - xx) < Decimal(eps)
and math.fabs(f(x_l) - f(xx)) < Decimal(eps)):
stop = True
p.off(xx)
return xx, i
def conjucateGrad(xx: float, N, x_min, x_max, eps: float, dataPlot, lmd=0.1):
stop = False
i, k = 0, 0
pp = -df(xx)
p = plot(dataPlot.x_left, dataPlot.x_right, dataPlot.pr)
p.on(xx)
while not stop:
print("itter:", i, "| x:", xx)
i += 1
p.showPoint(xx)
x_l = xx
def ff(lmb):
return f(xx + lmd * pp)
lmd = goldenRatio(ff, x_min, x_max, eps)
xx = x_l + lmd * pp
if abs(df(xx)) < eps:
stop = True
if k + 1 == N:
k = 0
pp = -df(xx)
continue
else:
bk = abs(df(xx))**2 / abs(df(x_l))**2
pp = -df(xx) + bk * pp
k += 1
p.off(xx)
return xx, i
def gradConst(lmd: float, xx: float, eps: float, dataPlot):
stop = False
i = 0
p = plot(dataPlot.x_left, dataPlot.x_right, dataPlot.pr)
p.on(xx)
while not stop:
#p.showPoint(xx)
x_l = xx
xx = x_l - lmd * df(x_l)
i += 1
#print("itter:", i, "| x:", xx)
if (abs(x_l - xx) < Decimal(eps)
and math.fabs(f(x_l) - f(xx)) < Decimal(eps)):
stop = True
p.off(xx)
return xx, i
def newton(xx:float, x_min, x_max, eps:float, dataPlot, lmd = 0.1):
stop = False
p = plot(dataPlot.x_left, dataPlot.x_right, dataPlot.pr)
p.on(xx)
i = 0
#arg_xx = numpy.array([x_min, x_max])
while not stop:
i += 1
p.showPoint(xx)
x_l = xx
xx = x_l - f(x_l) / df(x_l)
print("itter:", i, "| x:", xx)
if math.fabs(f(x_l) - f(xx)) < Decimal(eps):
stop = True
p.off(xx)
return xx, i