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import numpy as np
import types
from scipy.optimize import bisect
from numba import f8, jit, njit


#---------------------------------------------------------------------#
# Thank you to Stan Seibert from the Numba team for help with this
#---------------------------------------------------------------------#
def root_func(x):

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import datetime as dt
import math
import statistics

import web3

from umapy import connect_web3, create_cryptopunks_contract, find_cryptopunk_purchases
from umapy.util import find_oldest_block_after_ts

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import numpy as np
import tensorflow as tf


nobs = 100

alpha = 1.0
beta = np.array([0.0, 0.5, 0.25])
L = np.array([[1.0, 0.0, 0.0], [0.25, 1.1, 0.0], [0.2, 0.2, 1.25]])
X = np.random.randn(nobs, 3) @ L

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# Command for clearing notifications
atom.commands.add 'atom-workspace', 'custom-commands:dismiss-notifications', ->
  atom.notifications.getNotifications().forEach (notification) ->
    notification.dismiss()
  atom.notifications.clear()

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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We begin by importing some packages called by the code that we will be using in this notebook."
   ]
  },
  {

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// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

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n = 10
srand(42)

ad = randn(n, n)
bd = randn(n, n)

ac = randn(n, n) + randn(n, n)im
bc = randn(n, n) + randn(n, n)im

# This is the "not sorted" schur

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{
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  "language": "Julia",
  "name": "",
  "signature": "sha256:48c93e55dd13e85a8b1e797778a71d47dfe8f59cbe53a02778db64f6eacaad7a"
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 "nbformat": 3,
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 "worksheets": [