ugo-nama-kun

val=42
for i in $(seq 1 5); do
  echo $1
  echo $(($val+$2))
done

ugo-nama-kun

import numpy as np
from IPython.core.display import HTML
import matplotlib.pyplot as plt

# if you like seaborn:
import seaborn as sns
sns.set()
sns.set_context("talk")

HTML("""

ugo-nama-kun

import numpy as np

import gym
from gym.envs.mujoco import mujoco_env
from mujoco_py.generated import const

from scipy.spatial.transform import Rotation

""" Marker types in const
GEOM_PLANE = 0

ugo-nama-kun

print('{:.3f}'.format(123.456))
# 123.456
print(f"{0.12345678:.3f}")
# 0.123

# Other Examples

print('{:.3e}'.format(123.456))
print('{:.3g}'.format(123.456))
print('{:.3}'.format(123.456))

ugo-nama-kun

import random
import functools

import numpy as np
import tensorflow as tf
import torch
import gym

import tianshou as ts

ugo-nama-kun

import seaborn as sns
import matplotlib.pyplot as plt


# load data
x_ticks = np.linspace(0, 1, 10)
y_ticks = np.linspace(0, 1, 10)

# ちなみに save は np.save("data_matrix.npy", data_matrix) みたいなかんじで
data_matrix = np.load("data_matrix.npy")

ugo-nama-kun

import os
from datetime import datetime

import logging.config
from logging import StreamHandler, FileHandler, Formatter
from logging import INFO, DEBUG, NOTSET


def get_new_logger(name, file_path="./log"):
    # ストリームハンドラの設定

ugo-nama-kun

import numpy as np
from sklearn import datasets

"""
8x8 tiny NIST image handler

NIST dataset: https://scikit-learn.org/stable/datasets/toy_dataset.html#digits-dataset

If you chose NistHandle(flat=True), you'll get 64-dim vector instead of 8x8 numpy array.

ugo-nama-kun

from datetime import datetime

s = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")

print(s)
"""
You'll get something like.... 🍺
'2021-06-08-15-35-32'
"""

ugo-nama-kun

# Reference: https://en.wikipedia.org/wiki/Conversion_between_quaternions_and_Euler_angles

# Quaternion to Euler
def qtoeuler(q):
    """ quaternion to Euler angle

    :param q: quaternion
    :return:
    """