HYChou0515

from artest import autoreg, automock

@autoreg("adder")
def adder(a, b):
    return a + b

# @autoreg("summation")
# def summation(args):
#     # a complex way to implement summation
#     if len(args) == 1:

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def vec_scale(v: tuple[float, float], a: float):
    return (a * v[0], a * v[1])


def vec_mul_add(v1: tuple[float, float], v2: tuple[float, float], a: float = 1):
    """calc v1+a*v2"""
    return (v1[0] + a * v2[0], v1[1] + a * v2[1])


def inner_prod(v1: tuple[float, float], v2: tuple[float, float]):

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import itertools
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt


def get_random_dist(seed=None):
    rng = np.random.default_rng(seed)
    nsamples = int(np.exp(rng.random()*2+3))
    dists = [

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HYChou0515

Tasks involving search in a sorted list are pretty common. Sometimes using list literal would be very convenient and fast enough for small list, e.g., [v for v >= x for v in a].

However, when the list is too large, this kind of linear search can cost much time than it is actually needed. Using binary search is preffered in this situation.

Python has a built in library bisect for this kind of job. Sometimes it could be quite confusing how to use, though.

Here I tried to summary the basic usage and some useful application of bisect.

HYChou0515

# Reference: https://linuxize.com/post/how-to-install-python-3-9-on-debian-10/

PYVER=3.9.1

# Install the dependencies necessary to build Python:
sudo apt update
sudo apt install build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libsqlite3-dev libreadline-dev libffi-dev curl libbz2-dev liblzma-dev

wget https://www.python.org/ftp/python/${PYVER}/Python-{PYVER}.tgz
tar -xf Python-${PYVER}.tgz

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[alias]
lg1 = log --graph --abbrev-commit --decorate --format=format:'%C(bold blue)%h%C(reset) - %C(bold green)(%ar)%C(reset) %C(white)%s%C(reset) %C(dim white)- %an%C(reset)%C(bold yellow)%d%C(reset)' --all
lg2 = log --graph --abbrev-commit --decorate --format=format:'%C(bold blue)%h%C(reset) - %C(bold cyan)%aD%C(reset) %C(bold green)(%ar)%C(reset)%C(bold yellow)%d%C(reset)%n''          %C(white)%s%C(reset) %C(dim white)- %an%C(reset)' --all
lg = !"git lg1"

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# Given func() and cond(), assume there is a number A such that
#     cond(func(x)) == 0 if x < A
#                   == 1 if x >= A
# line search will find the number A according to func() and cond().
# Starting from point=x0 with step=s0, the searching has two phases:
# 1) expanding and 2) concentrating.
#
# 1) Expanding
# In the expanding phase, if cond(func(x0)) == 0,
# then we take larger and larger steps toward positive,

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def loan2(R, M=[55000], L=8500000, F=3000000, P=12, verbose=0):
    # R is a list of rate of each year
    # M is a list of month pay-back of each year
    # P is period per year
    R = [1.0 * r for r in R]
    M = [1.0 * m for m in M]
    L = L * 1.0
    F = F * 1.0
    P = P * 1.0
    principal = L-F