Skip to content

Instantly share code, notes, and snippets.

View taiga4112's full-sized avatar
💭
happy

Taiga Mitsuyuki taiga4112

💭
happy
View GitHub Profile
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@taiga4112
taiga4112 / polar_contour_graph_example.ipynb
Created August 22, 2018 09:52
Polar Contour Graph Example by matplotlib
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@taiga4112
taiga4112 / FFT_sample.ipynb
Created May 16, 2018 11:08
Fast Fourier Transformationのサンプルプログラム(Jupyter notebook解説付き)
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@taiga4112
taiga4112 / ekf_aug.py
Created December 6, 2016 09:44
Extended Kalman filter sample for estimating state and parameters at the same time
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
def main():
# 初期化
T = 30 # 観測数
r = 10.0 # 半径
w = 1.0*10/180 * np.pi # 角速度[rad/s](公称値であり、データからこの値を推定する)
@taiga4112
taiga4112 / odeint_scipy.py
Last active December 1, 2016 00:54
ODE sample by using odeint package in scipy.
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import odeint
def main():
x_ini = 0.0 # x(0) = 0
@taiga4112
taiga4112 / ode_rk_raw.py
Created November 30, 2016 11:38
Runge–Kutta method Sample by using simple problem
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
def main():
x_ini = 0.0 # x(0) = 0
@taiga4112
taiga4112 / ekf.py
Last active December 1, 2016 05:15
Extended Kalman filter sample
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
def main():
# 初期化
T = 30 # 観測数
r = 10.0 # 半径
w = 1.0*10/180 * np.pi # 角速度[rad/s]
@taiga4112
taiga4112 / lkf.py
Created November 15, 2016 07:13
Linear Kalman Filter sample
# -*- coding: utf-8 -*-
import numpy as np
import matplotlib.pyplot as plt
def lkf(T, Y, U, _X0, Sigma0, A, B, C, Q, R):
'''Linear Kalman Filter
- 状態方程式
X(t+1) = A*X(t) + B*U(t) + V(t), V(t) ~ N(0,Q)
- 観測方程式