CS190/295 Programming in Python for Life Sciences: Lecture 2

1. CS190/295 Programming in Python for Life Sciences: Lecture 2 Instructor: Xiaohui Xie University of California, Irvine

2. Announcements • Classroom for this course will be moved to DBH 1500 starting from Jan 17 (next Tuesday). • Enrollment max cap has been increased to 35 for CS295. However, due to limited resource, the enrollment cap cannot be further increased. • First homework assignment will be out before 5pm, Friday. Please check the course website.

3. Review of the last lecture

4. Hardware Basics • CPU (central processing unit) - the “brain” of the machine, where all the basic operations are carried out, such as adding two numbers or do logical operations • Main Memory – stores programs & data. CPU can ONLY directly access info stored in the main memory, called RAM (Random Access Memory). Main memory is fast, but volatile. • Secondary Memory – provides more permanent storage • Hard disk (magnetic) • Optical discs • Flash drives • Input Devices – keyboard, mouse, etc • Output Device – monitor, printer, etc

5. Python is an interpreted language • >>> is a Python prompt indicating that the interpreter is waiting for us to give a command. A complete command is called a statement • Start the Python interpreter in an interactive mode

6. Inside a Python program • comments: • any text from # through the end of a line • intended for humans, ignored by the Python • defining a function called main • x is variable, used to give a name to a value so that we can refer to later • The statement starting with for is an example of a loop • A loop is a device that tells Python to do the same thing over and over again • The lines indented underneath the loop heading form the body of the loop • x = 3.9 * x * (1-x) is an assignment statement: the value on the right-hand side is computed, and is then stored back (assigned) into the variable on the left-and side of =.

7. Topic 2: Writing Simple Programs

8. Software development process • Formulate Requirements Figure out exactly what the problem to be solved is • Determine Specifications Describe exactly what your program will do. Whatwill it accomplish? What the inputs and outputs of the program? • Create a Design Formulate the overall structure of the program. How will the program achieve the desired goals? • Implement the Design Translate the design into a computer language and put it into the computer. • Test/Debug the Program Try out your program and see if it works as expected. If there are any errors (often called bugs), then you should go back and fix them. The process of locating and fixing errors is called debugginga program. • Maintain the Program Continue developing the program in response to the needs of your users. Most programs are never really finished; they keep evolving over years of use.

9. An example: temperature converter • Input the temperature in degrees Celsius (call it celsius) • Calculate fahrenheit = 9/5 * celsius + 32 • Output fahrenheit

10. Elements of Programs: Names • Names (also called identifiers): we give names to • modules (e.g., convert, chaos) • functions within modules (e.g., main) • variables (e.g., celsius, fahrenheit) • Python rules on identifiers • must begin with a letter or underscore (‘_’), which may be followed by any sequence of letters, digits, or underscores. • cannot contain any spaces • the names that are part of Python, called reserved words, cannot be used as ordinary identifiers

11. Elements of Programs: Expressions • Programs manipulate data. The fragments of code that produce or calculate new data values are called expressions. • Using a variable that has not been assigned a value will result in a NameError. • More complex expressions can be constructed by combining simpler expressions with operators (e.g., +, -, *, /, **) • Spaces are irrelevant within an expression. Usually it’s a good idea to place some spaces in expressions to make them easier to read • Use parentheses to modify the order of evaluation.

12. Output statements The syntax of print: • These are templates for using print, using notations called meta-languages • Aprintstatement consists of the keyword print followed by zero or more expressions, which are separated by commas. • The angle bracket notation (<>) is used to indicate “slots” that are filled in by other fragments of Python code. The name inside the brackets indicate what is missing; expr stands for an expression. • The ellipses (“...”) indicate an indefinite series (of expressions, in this case). You don’t actually type the dots. • The fourth version shows that a print statement may be optionally ended with a comma.

13. Output statements The semantics of print: • Displays information in textual form, with expression evaluated left to right • The resulting values are displayed on a single line in a left to right fashion • A single blank space character is placed between the displayed values

14. Assignment statements: simple assignment • The template for the basic assignment statement: <variable> = <expr> where variable is an identifier and expr is an expression • A variable can be assigned many times. It always retain the value of the most recent assignment.

15. Assignment statements: assigning input • The template for the assigning input: <variable> = input(<prompt>) where prompt is an expression that serves to prompt the user for input; this is almost always a string literal (i.e., some text inside of quotation marks).

16. Assignment statements: Simultaneous Assignment • The template for simultaneous assignment: <var>, <var>, …, <var> = <expr>, <expr>, …, <expr> • Python evaluate all the expressions on the right-hand side and then assign these values to the corresponding variables named on the left-hand side.

17. Definite Loops • Programmers use loops to execute a sequence of statements several times in succession. The simplest kind of loop is called a definite loop. This is a loop that will execute a definite number of times • A Python for loop has this general form: • The body of the loop can be any sequence of Python statements. The start and end of the body is indicated by its indentation under the loop heading

18. Topic 3: Computing with Numbers

19. Numeric Data Types Example output:

20. Numeric Data Types • Whole numbers are represented using the integer data type (intfor short).Values of type int can be positive or negative whole numbers. • Numbers that can have fractional parts are represented as floating point (or float) values. • The data type of an object determines what values it can have and what operations can be performed on it. • The float type only stores approximations. There is a limit to the precision, or accuracy, of the stored values. By contrast, the int type is exact.

21. Numeric Data Types • Notice how operations on floats produce floats, and operations on ints produce ints.

22. Using the Math Library Python provides many other useful mathematical functions in a special math library. A library is just a module that contains some useful definitions. Example: find the roots of ax2+bx+c =0

23. Using the Math Library Python provides many other useful mathematical functions in a special math library. A library is just a module that contains some useful definitions.

24. Accumulating Results: Factorial • In mathematics, factorial is often denoted with an exclamation (“!”). The factorial of a whole number is defined as n!=n(n-1)(n-2)…(1). This happens to be the number of distinct arrangements for n items. Given six items, we compute 6! =720 possible arrangements. • Write a program that will compute the factorial of a number entered by the user. The basic outline of our program follows an Input-Process-Output pattern. • Basic strategy: do repeated multiplications, use an accumulator variable + a loop structure Input number to take factorial of, n Compute factorial of n, fact Output fact Initialize the accumulator variable Loop until final result is reached update the value of accumulator variable

25. Accumulating Results: Factorial Initialize the accumulator variable Loop until final result is reached update the value of accumulator variable For example, suppose we want to calculate 5!=5*4*3*2*1 We define a variable and initialize it to be 1 fact = 1 for factor in [2,3,4,5] fact = fact * factor

26. Python range() function • range(n): produce a sequence of numbers starting with 0 and continuing up to, but not including n • range(start, n): produce a sequence of numbers starting with start and continuing up to, but not including n • range(start, n, step): produce a sequence of numbers starting with start and continuing up to, but not including n, and using step as the increment between numbers Examples: >>> range(10) [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> range(5,10) [5, 6, 7, 8, 9] >>> range(5,10,3) [5, 8]

27. Accumulating Results: Factorial • n!=n(n-1)(n-2)…(1). Write a program that will compute the factorial of a number entered by the user.

28. The limits of int

29. Handling Large Numbers: Long Ints • Python provides a better solution for large, exact values in the form of a third numeric type long int. • A long int is not a fixed size, but expands to accommodate whatever value it holds. • To get a long int, you put an “L” suffix on a numeric literal.

30. Accumulating Results: Factorial • n!=n(n-1)(n-2)…(1). Write a program that will compute the factorial of a number entered by the user.

31. Type Conversions Note that the value is truncated, not rounded when using int() or long()