Ceng 111 Fall 2015 Week 7a
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1 Ceng 111 Fall 2015 Week 7a Container data Credit: Some slides are from the Invitation to Computer Science book by G. M. Schneider, J. L. Gersting and some from the Digital Design book by M. M. Mano and M. D. Ciletti.
2 Design of a solution 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 2
3 What is data? CPU can only understand two types of data: Integers, Floating points. The following are not directly understandable by a CPU: Characters ( a, A, 2, ) Strings ( apple, banana, ) Complex Numbers Matrices Vectors But, programming languages can implement these data types S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 3
4 Basic Data Types Integers Full support from the CPU Fast processing Floating Points Support from the CPU with some precision loss Slower compared to integer processing due to interpretation 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 4
5 Problems due to precision loss What has precision loss is misleading: 0.9 has precision loss whereas does not! ( ) (½ + ¼ + 1/8 + 1/16) = Imprecise representations are round-offs! If you have a lot of round-offs, you might be in trouble! 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 5
6 Problems due to precision loss Since the floating point representation is based on shifting the bits in the mantissa, the following are not equivalent in a PC: Result: Result: π = sin(π) should be zero But it is not: x S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 6
7 Problems due to precision loss Associativity in mathematics: (a+b) + c = a + (b + c) This does not hold in floating-point arithmetic: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 7
8 So what to do with precision loss, then? If you can transform the problem to the integer domain, do so. Refrain from using floating points as much as you can. Use the most precise type of floating point of the high level language you are using. Use only less precision floating points if you are short in memory S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 8
9 So what to do with precision loss, then? If you have two addends that are magnitude-wise incomparable, you are likely to lose the contribution of the smaller one. That will yield unexpected results when you repeat the addition in a computational loop where the looping is so much that the accumulation of the smaller is expected to become significant. It will not. The contrary happens too. Slight inaccuracies accumulate in loops to significant magnitudes and yield non-sense values. You better use well known, decent floating point libraries instead of coding floating point algorithms by yourself S. Kalkan & G. Ucoluk & A. Cosar - CEng 111 9
10 Integers in Python Python provides int type. For big integers, Python has the long type: int is limited by the hardware whereas long type is unlimited in Python S. Kalkan & G. Ucoluk & A. Cosar - CEng
11 Floating Points in Python Python provides float type S. Kalkan & G. Ucoluk & A. Cosar - CEng
12 Simple Operations with Numerical Values in Python abs(x): Absolute value of x. round(float): Rounded value of float. int(number), long(number), float(number): Conversion between numerical values of different types S. Kalkan & G. Ucoluk & A. Cosar - CEng
13 A portion of the ASCII table. Characters We need characters to represent textual data: Characters: A,, Z, 0,.., 9, a,, z etc. Computer uses the ASCII table for converting characters to binary numbers: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
14 Characters in Python Python does not have a separate data type for characters! However, one character strings can be treated like characters: ord(one_char_string) : returns the ASCII value of the character in One_Char_String. Ex: ord( A ) returns 65. chr(ascii_value) : returns the character in a string that has the ASCII value ASCII_value: Ex: chr(66) returns B 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
15 Boolean Values The CPU often needs to compare numbers, or data: 3 >? =? 1000/8 3? / We have the truth values for representing the answers to such comparisons: If correct: TRUE, True, true, T, 1 If not correct: FALSE, False, false, F, S. Kalkan & G. Ucoluk & A. Cosar - CEng
16 Boolean Values in Python Python provides the bool data type for boolean values. bool data type can take True or False as values. Try this: >>> True == bool(2) not operator: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
17 Today Container/structured data Approaches for storing structured data Strings Tuples Lists Reminder: Tentative midterm date: 9 December at 17: S. Kalkan & G. Ucoluk & A. Cosar - CEng
18 Structured Data If you have lots and lots of one type of data (for example, the ages of all the people in Turkey): You can store them into memory consecutively (supported by most PLs) This is called arrays. Easy to access an element. Nth element: <Starting-address>+ (N-1)*<Word Width> Ex: 2nd element is at (2-1) * 4 = 132 Address Width = 4 bytes S. Kalkan & G. Ucoluk & A. Cosar - CEng
19 Structured Data What if you have to make a lot of deletions and insertions in the middle of an array? Then, you have to store your data in blocks/units such that each unit has the starting address of the next unit/block Blocks of Data S. Kalkan & G. Ucoluk & A. Cosar - CEng
20 Containers Containers of basic data: Strings Tuples Lists 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
21 Strings Sequence of characters: Ex: Book, Programming, Python How can they be represented? 1. Put a set of characters one after the other and end them with a non-character value. 2. At the beginning of the characters, specify how many characters follow. Both have advantages and disadvantages S. Kalkan & G. Ucoluk & A. Cosar - CEng
22 Strings in Python Simplest operation with a string: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
23 Strings in Python Accessing elements of a string Hello? [0] 1 st character (i.e., H ) Hello? [4] 5 th character Indexing starts at 0!!! What is the last element then? Hello? [len( Hello? ) - 1] Negative indexing possible: Last element: Hello? [-1]? In general: String[start:end:step] Ex: Hello? [0:4:2] Hl Ex: Hello? [2:4] ll 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
24 Creating Strings in Python 1. Enclosing a set of characters between quotes: ali, veli, deli, 2. Using the str() function: str(4.5) Using the raw_input() function: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
25 Tuples Tuple: ordered set of data: (1, 2, 3) ( a, b, c ) May be heterogeneous: ( Salary, 2000, Age, 25, Birth, Ankara ) 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
26 Tuples in Python Tuples in Python: collection of data enclosed in parentheses, separated by comma. Accessing elements of a tuple (like strings): 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
27 Creating Tuples in Python 1. Enclosing data within parentheses: Ex: (1, a, cde, 23) 2. Using the tuple() function: Ex: tuple( ABC ) ( A, B, C ) 3. Using the input() function: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
28 Lists Similar to tuples. Difference: Tuples are immutable (i.e., not changeable) whereas lists are mutable S. Kalkan & G. Ucoluk & A. Cosar - CEng
29 Lists in Python Lists in Python: collection of data enclosed in brackets, separated by comma. Accessing elements of a list (like strings & tuples): 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
![Creating Lists in Python 1. Enclosing data within brackets: Ex: [1, a, cde, 23] 2. Using the list() function: Ex: list( ABC ) [ A, B, C ] 3.](/docs-images/94/119822412/images/30-2.jpg "Using the range() function: Ex: range(1, 10, 2) [1, 3, 5, 7, 9] 4. Using the input() function: 2015 S. Kalkan & G. Ucoluk & A.")
30 Creating Lists in Python 1. Enclosing data within brackets: Ex: [1, a, cde, 23] 2. Using the list() function: Ex: list( ABC ) [ A, B, C ] 3. Using the range() function: Ex: range(1, 10, 2) [1, 3, 5, 7, 9] 4. Using the input() function: 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
![Modifying a List in Python List[range] = Data Ex: Using the append() function: List.](/docs-images/94/119822412/images/31-2.jpg "append(item) Ex: [1, 2, 3].append(5) [1, 2, 3, 5] 2015 S. Kalkan & G. Ucoluk & A.")
31 Modifying a List in Python List[range] = Data Ex: Using the append() function: List.append(item) Ex: [1, 2, 3].append(5) [1, 2, 3, 5] 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
![Modifying a List in Python Using the extend() function: List.extend(Another_list) Ex: [1, 2, 3].](/docs-images/94/119822412/images/32-2.jpg "extend([ a, b ]) [1, 2, 3, a, b ] Using the insert() function: List.insert(index, item) 2015 S. Kalkan & G.")
32 Modifying a List in Python Using the extend() function: List.extend(Another_list) Ex: [1, 2, 3].extend([ a, b ]) [1, 2, 3, a, b ] Using the insert() function: List.insert(index, item) 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
33 Removing Elements from a List in Python 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
34 Accessing Data/Containers by Names: Variables Naming: Usually: A combination of letters and numbers Ex: a123, 123a, Scope & Extent: Scope: Where a variable can be accessed. Extent: The lifetime of a variable. Typing: Statically typed: The type of a variable is fixed. Dynamically typed: The type of a variable is variable 2015 S. Kalkan & G. Ucoluk & A. Cosar - CEng
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