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#!/usr/bin/python
# -*- coding: utf-8 -*-

from openopt import QP

H = [[4, 1],
     [1, 2]]
f = [1, 1]
Aeq = [1, 1]
beq = 1

ki-chi

#!/usr/bin/python
# -*- coding: utf-8 -*-

import FuncDesigner as fd
from openopt import QP

x1, x2 = fd.oovars(2)
f = 2 * x1 ** 2 + x2 ** 2 + x1 * x2 + x1 + x2
startpoint = {x1: 0, x2: 0}
constraints = []

ki-chi

#!/usr/bin/python
# -*- coding: utf-8 -*-

import FuncDesigner as fd
from openopt import QP
import numpy as np

x = fd.oovars(2)
H = np.array([[4, 1],
              [1, 2]])

ki-chi

#!/usr/bin/python
# coding: utf-8
# 日経平均資料室(http://indexes.nikkei.co.jp/nkave/archives/data)の日次データの差分をクロールして追加するプログラム

import urllib2
import lxml.html
import csv
import re
import time
from datetime import datetime as dt

ki-chi

# -*- coding: utf-8 -*-
from __future__ import print_function
import numpy as np

# it's for unweighted and undirected graph.
# Adjency matrix of the graph
adjency_mat = np.array([[0, 1, 1, 1, 0, 0],
                        [1, 0, 1, 0, 0, 1],
                        [1, 1, 0, 1, 1, 0],
                        [1, 0, 1, 0, 1, 0],

ki-chi

import pandas as pd
import jsm
import datetime

def get_historical_price(stockcode, start_date=None, end_date=None):
    q = jsm.Quotes()
    if start_date is None or end_date is None:
        jsm_data = q.get_historical_prices(stockcode)
    else:
        jsm_data = q.get_historical_prices(stockcode, jsm.DAILY, start_date, end_date, jsm.DAILY)

ki-chi

ki-chi

## Convert strings of 2-digits number have the following tricky format to an integer.
## Tricky format:　the last digit is described as decimal, and the first digit is chosen from {1, ..., 9, A, ..., Z, a, ..., z}.
## The min is 0(="00") and the max is 619(="z9").
## Example: "15" -> 15, "A0" -> 100, "Z9" -> 359, "a0" -> 360, "c5" -> 385

def num2int(num):
    if num.isdigit():
        return int(num)
    elif num[0].isupper():
        return int(num[0], 36) * 10 + int(num[1])

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# julia> versioninfo()
# Julia Version 1.5.0
# Commit 96786e22cc (2020-08-01 23:44 UTC)
# Platform Info:
#   OS: macOS (x86_64-apple-darwin18.7.0)
#   CPU: Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz
#   WORD_SIZE: 64
#   LIBM: libopenlibm
#   LLVM: libLLVM-9.0.1 (ORCJIT, skylake)

ki-chi

import time
import numpy as np
import pandas as pd


def np_mode(df):
    """
    与えられたDataFrameの各列から最頻値を返す
    Original: https://twitter.com/nkay/status/1328231713919496194
    """