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import enum | |
import queue | |
import time | |
from collections import defaultdict | |
class Side(enum.Enum): | |
BUY = 0 | |
SELL = 1 | |
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import os | |
import time | |
import sched | |
import threading | |
import inquirer | |
class Tamagotchi: | |
age = 0 | |
bored = 0 |
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# -*- coding: utf-8 -*- | |
""" | |
Created on Mon Sep 23 23:16:44 2017 | |
@author: Marios Michailidis | |
This is an example that performs stacking to improve mean squared error | |
This examples uses 2 bases learners (a linear regression and a random forest) | |
and linear regression (again) as a meta learner to achieve the best score. | |
The initial train data are split in 2 halves to commence the stacking. |
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# -*- coding: utf-8 -*- | |
# Form implementation generated from reading ui file 'threading_design.ui' | |
# | |
# Created: Thu Aug 6 13:47:18 2015 | |
# by: PyQt4 UI code generator 4.10.4 | |
# | |
# WARNING! All changes made in this file will be lost! | |
from PyQt4 import QtCore, QtGui |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta charset="UTF-8"> | |
<!-- Replace with your own title --> | |
<title>Your Project's Title</title> | |
<script> | |
// Add your own shareable dropbox link | |
window.location.replace("https://www.dropbox.com"); | |
</script> |
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from __future__ import division | |
import os | |
import numpy | |
from PIL import Image, ImageDraw | |
class Renderer(): | |
def __init__( | |
self, size=(640, 480), sampler=None, |
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import matplotlib.pyplot as plt | |
def plotTSP(path, points, num_iters=1): | |
""" | |
path: List of lists with the different orders in which the nodes are visited | |
points: coordinates for the different nodes | |
num_iters: number of paths that are in the path list | |
""" |