pl = np.zeros(zvals.shape, dtype=float)
# allocate storage for hermite interpolant (evaluated using modified divided diffrence method)
phdd = np.zeros(zvals.shape, dtype=float)
# run test for varying numbers of interpolation nodes
for n in nvals:
lagrange_nodes = np.linspace(-L, L, n+1) # lagrange interpolation nodes
lagrange_f_yvals = f(lagrange_nodes) # function values
hermite_nodes = np.linspace(-L, L, int((n+1)//2))
hermite_f_yvals = f(hermite_nodes)
hermite_df_yvals = df(hermite_nodes)
# evaluate interpolant lagrange
pl = lagrange(lagrange_nodes, lagrange_f_yvals, zvals)
# evaluate interpolant hermite using modified divided diffrence method
phdd = hermite(hermite_nodes, hermite_f_yvals, hermite_df_yvals, zvals, method='modified_divided_difference')
# generate comparison plots
fig, axarr = plt.subplots(1,2)
#
# overlayed interpolant (normal) plots
#
ftitle = '$f(z)$'
ltitle = '$p_L(z)$'
htitle = '$p_H(z)$'
import lagrange as lagrange from Interpolacion import * import pylab as pl x = [2, 4, 5] y = [5, 6, 3] p = lagrange(x, y) print(p) print() r = lagrange(x, y, 4.25) print(r) print() r = lagrange(x, y, [3.15, 3.74, 4.25]) print(r)
def ployinterp_column(s, n, k=5):
y = s[list(range(n - k, n)) + list(range(n + 1, n + 1 + k))] # 取数
y = y[y.notnull()] # 剔除空值
return lagrange(y.index, list(y))(n) # 插值并返回插值结果 # #逐个元素判断是否需要插值
# Definição dos valores dos eixos de interpolação
XsIE = igualmenteEspacados(50, -180, 180)
XsCheb = chebyshev(50, -180, 180)
senoIE = list(map(seno, XsIE))
senoCheb = list(map(seno, XsCheb))
# Definição dos pontos a serem usados para os testes
testes = igualmenteEspacados(500, -180, 180)
senoTeste = list(map(seno, testes))
######################################################################################
''' Valores igualmente Espaçados '''
# Cálculos de interpolação com função Seno
lagrangeIE = lagrange(testes, XsIE, senoIE)
baricentricoIE = baricentrico(testes, XsIE, senoIE)
newtonIE = newton(testes, XsIE, senoIE)
nevilleIE = neville(testes, XsIE, senoIE)
# Gráfico 1 : Resultados da interpolação em todos os algoritmos com função seno
plt.figure(1)
plt.subplot(211)
plt.plot(testes, lagrangeIE, color='green')
plt.plot(testes, baricentricoIE, color='blue')
plt.plot(testes, newtonIE, color='red')
plt.plot(testes, nevilleIE, color='aqua')
plt.plot(testes, senoTeste, color='yellow')
plt.title('Valores igualmente espaçados')
plt.ylabel('Valores Calculados')
from turtle import *
from math import *
from lagrange import *
color("red")
# for j in range(0, len(h)):
# f = h[j]
f = "exp(x)-1.0"
w, g = lagrange(x, y, 1.0)
h = ["exp(x)-1.0", w]
x = 0.0
yo = eval(f)
def graficar(h, desde, hasta):
tracer(3)
penup()
goto(300, 0)
right(180)
pendown()
forward(600)
penup()
goto(0, -300)
right(90)
pendown()
forward(600)
espaciado = 30
penup()
goto(0, 0)
puntos = 300