yangyushi

import json
import base64
import numpy as np
from io import BytesIO


# save data to the binary string
a = np.random.uniform(0, 255, (1500, 1500)).astype(np.uint8)
f = BytesIO()
np.savez_compressed(f, data=a)

yangyushi

from itertools import combinations

stations = [
    "a", "b", "c", "d", "e",
    "f", "g", "h", "i", "j",
    "k", "l", "m", "n"
]

line1 = ["a", "b", "f", "d", "e"]
line2 = ["c", "e", "j", "g", "i"]

yangyushi

import numpy as np
import matplotlib.pyplot as plt

N = 5

v = np.random.random((N, 3))
v = v / np.linalg.norm(v, axis=1)[:, None]
r = np.random.randn(N, 3)
r = r / np.linalg.norm(r, axis=1)[:, None]
angle = np.arccos(np.einsum('ij,ij->i', v, r))

yangyushi

#!/usr/bin/env python3
import numpy as np
from time import time


a = np.random.random((10000, 3))
b = np.random.random((10000, 3))

t0 = time()
c = np.array([np.cross(x, y) for x, y in zip(a, b)])

yangyushi

"""
Different functions to get pairwise distance in cubic box with PBC

Args:
    positions: the positions of particles, shape (N, dim)
    box (int or float): the size of the box

Return:
    np.ndarray: the pair-wise distances, shape (N, N)
"""

yangyushi

import numpy as np

n_sample = 8
x = np.linspace(0, 10, n_sample)
par = [1e-4, 2e-3, -3e-2, -2e-1, 1]
order = len(par) - 1
# the shape of x_poly is (order + 1, n_sample)
x_poly = x[None, :] ** np.arange(order + 1)[:, None]

y = np.polyval(par, x)

yangyushi

125

H	16.658345122844334	5.438348200947194	15.278503165303777
H	11.904690376717243	5.1529666697956795	13.25948396116124
H	9.62667890619329	7.438653597799468	5.290790255780805
H	6.017600501383954	7.235017543794983	12.626298470129054
H	9.33671886855014	10.014970018631432	4.270413237226138
H	2.168893723778388	0.9019879254927321	7.552264051940874
H	10.211873888717818	10.346039720521441	13.019842912794617
H	7.797419763761877	17.778647693825153	15.882609513949191

yangyushi

yangyushi

yangyushi