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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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{ | |
"metadata": { | |
"celltoolbar": "Slideshow", | |
"language": "Julia", | |
"name": "", | |
"signature": "sha256:48c93e55dd13e85a8b1e797778a71d47dfe8f59cbe53a02778db64f6eacaad7a" | |
}, | |
"nbformat": 3, | |
"nbformat_minor": 0, | |
"worksheets": [ |
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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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