MyLiveWire1 In [1]: %matplotlib notebook In [2]: # loading standard modules import numpy as np import matplotlib.pyplot as plt # loading custom module (requires file asg1.py in the same directory as the notebook file) from asg1 import Figure, LiveWirePresenter In [3]: import heapq class Dijkstra: def __init__(self, img, useFour = True): num_rows = self.num_rows = img.shape[0] num_cols = […]
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SCHEME and functional programming Dr. Jozo Dujmović Jozo Dujmović Functional Programming 1 Programming paradigms • Paradigm = fundamental style of programming. • Main computer programming paradigms are: 1. Procedural (imperative) programming 2. Nonprocedural (declarative) programming 3. Logic programming (subset of declarative programming) 4. Functional programming (subset of declarative programming) 5. Object-oriented programming Jozo Dujmović Functional
In [1]: %matplotlib notebook In [2]: # loading standard modules import numpy as np import matplotlib.pyplot as plt # loading custom module (requires file asg1.py in the same directory as the notebook file) from asg1 import Figure, LiveWirePresenter In [3]: class BFS: white_color = 0 gray_color = 1 black_color = 2 def __init__(self, img): num_rows = self.num_rows =
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MyLiveWire In [1]: %matplotlib notebook In [2]: # loading standard modules import numpy as np import matplotlib.pyplot as plt # loading custom module (requires file asg1.py in the same directory as the notebook file) from asg1 import Figure, LiveWirePresenter In [3]: class BFS: white_color = 0 gray_color = 1 black_color = 2 def __init__(self, img): num_rows = self.num_rows
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courseScraper In [1]: import urllib2 #specify the url wiki = “http://guide.berkeley.edu/courses/compsci/” page = urllib2.urlopen(wiki) from bs4 import BeautifulSoup soup = BeautifulSoup(page, “lxml”) In [34]: res = [] for t in soup.find_all(‘h3’, class_=”courseblocktitle”): alls = t.find_all() res.append(‘ ‘.join(x.string for x in alls).replace(u’\xa0’, ‘ ‘)) # alls = soup.find_all(‘h3’, class_=”courseblocktitle”)[0].find_all() # ‘ ‘.join(x.string for x in alls).replace(u’\xa0’, ‘ ‘)
CM10227 Coursework 2 Dungeon of Doom – Part 1 November 25, 2016 1 Introduction The coursework of this unit consists of three parts: the lab sheets and two larger Java courseworks. This document provides the specification for the second large coursework: Dungeon of Doom. You can use any Integrated Development Environment (IDE) for the de-
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MyLiveWire-checkpoint In [1]: %matplotlib notebook In [2]: # loading standard modules import numpy as np import matplotlib.pyplot as plt # loading custom module (requires file asg1.py in the same directory as the notebook file) from asg1 import Figure, LiveWirePresenter In [3]: class BFS: white_color = 0 gray_color = 1 black_color = 2 def __init__(self, img): num_rows = self.num_rows
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Page |1 Realistic Urban Traffic Simulation Tool CISC 499 Project Report Muhammad R Muhaimin Student # 06127876 Page |2 Table of Contents 1. Introduction 3 2. Tools used 4 2.1 Open Street Map 4 2.1.1 Map Production Technique used in Open Street Map 4 2.2 Sumo 4 2.2.1 Features of SUMO 5 2.2.2 Included Applications
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1. Cognition 1) Proximity: When things put close with other, user will feel them as a group. Closure: Users can complete the missing part in their mind. Proximity Example Closure Example 2) First receive audio information through hearing, then processing the audio information, pay attention to it and put in memory. 3) Short-Term memory through
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Stanford typed dependencies manual Marie-Catherine de Marneffe and Christopher D. Manning September 2008 Revised for the Stanford Parser v. 3.5.2 in April 2015 Please note that this manual describes the original Stanford Dependencies representation. As of version 3.5.2 the default representation output by the Stanford Parser and Stanford CoreNLP is the new Universal Dependencies (UD)