ceptreee

function lorenz(h,n,a,b,c,x0,y0,z0)
    #--------------------
    # Equation
    #--------------------
    f₁(x,y,z) = -a * x + a * y
    f₂(x,y,z) = -x * z + b * x - y
    f₃(x,y,z) =  x * y - c * z
    #--------------------
    # Initialize
    #--------------------

ceptreee

function lorenz(h,N,σ,ρ,β,x0,y0,z0,a,b,c)
    # stage
    s = length(b)
    # Number of Equations
    M = 3
    #--------------------
    # Equations
    #--------------------
    f₁(x,y,z) = -σ * x + σ * y
    f₂(x,y,z) = -x * z + ρ * x - y

ceptreee

import numpy as np 
import matplotlib.pyplot as plt 
import matplotlib.animation as animation
from numba import jit

# Julia set
# https://en.wikipedia.org/wiki/Julia_set#Quadratic_polynomials

@jit
def JuliaSet(N,Nx,Ny,z,c):

ceptreee

import numpy as np 
import matplotlib.pyplot as plt 
import matplotlib.animation as animation
from numba import jit

# Julia set
# https://en.wikipedia.org/wiki/Julia_set#Quadratic_polynomials

def motion(event):  
    if (event.xdata is  None) or (event.ydata is  None):

ceptreee

using PyPlot
using PyCall
@pyimport matplotlib.animation as anim

dx  = 0.05
xlm = [0, 2π]
x   = collect(xlm[1]:dx:xlm[2])
n   = length(x)

y  = sin.(x)

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using PyPlot

function motion(event)
    x = event[:xdata]
    y = event[:ydata]

    ln[:set_data](x,y)
    draw()
end

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# x
X   = 5.0
xlm = [-X,X]
dx  = 0.1
x   = xlm[1]:dx:xlm[2]
x_n = length(x)

# t
T   = 50.0
tlm = [0,T]

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# x
Δx  = 0.1
X   = 10.0
xlm = [0, X]
x   = collect(xlm[1]:Δx:xlm[2])
I   = length(x)

# y
Δy  = 0.1
Y   = 10.0

ceptreee

import numpy as np 
import matplotlib.pyplot as plt 
import sympy as sb

x = sb.Symbol('x')

def Chebyshev1st(N):
    T = [0]*(N+1)
    T[0] = 1
    T[1] = x

ceptreee

import numpy as np 
import matplotlib.pyplot as plt 
import sympy as sb

# 森正武, "数値解析", 共立出版株式会社, 第2版, 2002.
# 4.12 ラグランジュ補間公式の標本点の分布
# 等間隔な標本点の分布(P170 - P173)

def LagrangePolynomial(X,Y):
    def l(j,N):