讲解CS112、Python编程设计辅导、辅导Python语言、讲解gmason76_210_H4 讲解留学生Processing|解析C/C+
- 首页 >> 其他 CS112 Homework 4: Memory – Groups Allowed
Due: Sun, Mar 17th, 11:59pm
As this is a Homework, you can read any and all materials, ask us questions, talk with other
students, and learn however you best learn in order to solve the task. Just create your own
solution from those experiences, and turn in your work.
Notes
The purpose of this homework is to provide additional practice with the use of memory and
aliases
We will be using function definitions for this homework. Remember, don't call input() or
print() anywhere, just use the parameters provided and return statements.
You cannot import any module. When a task has individual restrictions, note them, as we
will remove points for any task that does not follow the requirements.
A tester has been included with this assignment. Grading is based on the fraction of
passing tests. You can run it like this:
python3 testerH4.py gmason76_210_H4.py
For the tester, if you only want to test some functions, you can specify which functions:
python3 testerH4.py gmason76_210_H4.py transpose_matrix
Turning It In
Add a comment at the top of the file that indicates your name, userID, G#, lab section, a
description of your collaboration partners, as well as any other details you feel like sharing.
Please also mention what was most helpful for you. Once you are done, run the testing script
once more to make sure you didn't break things while adding these comments. If all is well, go
ahead and turn in just your .py file you've been working on, named with our usual convention
(see above), over on BlackBoard to the correct lab assignment. Please don't turn in the tester file
or any other extra files, as it will just slow us down.
Grading Rubric
Pass shared test cases 100 (zero points for hard-coding)
----------------------------------------------------------------
TOTAL: 100 Tasks
def transpose_matrix(mat)
Creates and returns a new matrix that is the transpose of mat
https://en.wikipedia.org/wiki/Transpose
mat is a nested list (e.g. [[1,2,3], [4,5,6]] and is guaranteed to have a rectangular shape
and more than one elements
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() , append()
Examples:
transpose_matrix([[1,2,3], [4,5,6]]) → [[1,4], [2,5], [3,6]]
transpose_matrix([[1,2],[3,4],[5,6]]) → [[1,3,5], [2,4,6]]
def diagonal_matrix(mat)
Converts a square matrix mat into a lower diagonal matrix
https://en.wikipedia.org/wiki/Triangular_matrix
After the conversion the values on the diagonal will be the sum of the deleted elements in
the respective row
Return value is None. Variable mat is directly modified in memory
mat is a nested list (e.g. [[1,2,3], [4,5,6], [7,8,9]] and is guaranteed to have a square
shape of size at least 2x2
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() and the del keyword
Examples:
diagonal_matrix([[1,2,3], [4,5,6], [7,8,9]]) → [[6], [4, 11], [7, 8, 9]]
diagonal_matrix([[1,2],[3,4]]) → [[3], [3,4]]
def reduce_matrix(mat)
Reduces the size of matrix mat in half, in both dimensions, by merging adjacent elements
The new values of the matrix are the average of the respective merged elements
Return value is None. Variable mat is directly modified in memory
mat is a nested list (e.g. [[1,2,3,4], [5,6,7,8]] and is guaranteed to be non-empty and have
a rectangular shape. Both dimensions are even numbers
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() and the del keyword
Examples:
reduce_matrix([[1,2],[3,4]]) → '[[2.5]]'
reduce_matrix([[1,2,3,4],[5,6,7,8],[9,8,7,6],[5,4,3,2]]) → '[[3.5,5.5],[6.5,4.5]]'
Due: Sun, Mar 17th, 11:59pm
As this is a Homework, you can read any and all materials, ask us questions, talk with other
students, and learn however you best learn in order to solve the task. Just create your own
solution from those experiences, and turn in your work.
Notes
The purpose of this homework is to provide additional practice with the use of memory and
aliases
We will be using function definitions for this homework. Remember, don't call input() or
print() anywhere, just use the parameters provided and return statements.
You cannot import any module. When a task has individual restrictions, note them, as we
will remove points for any task that does not follow the requirements.
A tester has been included with this assignment. Grading is based on the fraction of
passing tests. You can run it like this:
python3 testerH4.py gmason76_210_H4.py
For the tester, if you only want to test some functions, you can specify which functions:
python3 testerH4.py gmason76_210_H4.py transpose_matrix
Turning It In
Add a comment at the top of the file that indicates your name, userID, G#, lab section, a
description of your collaboration partners, as well as any other details you feel like sharing.
Please also mention what was most helpful for you. Once you are done, run the testing script
once more to make sure you didn't break things while adding these comments. If all is well, go
ahead and turn in just your .py file you've been working on, named with our usual convention
(see above), over on BlackBoard to the correct lab assignment. Please don't turn in the tester file
or any other extra files, as it will just slow us down.
Grading Rubric
Pass shared test cases 100 (zero points for hard-coding)
----------------------------------------------------------------
TOTAL: 100 Tasks
def transpose_matrix(mat)
Creates and returns a new matrix that is the transpose of mat
https://en.wikipedia.org/wiki/Transpose
mat is a nested list (e.g. [[1,2,3], [4,5,6]] and is guaranteed to have a rectangular shape
and more than one elements
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() , append()
Examples:
transpose_matrix([[1,2,3], [4,5,6]]) → [[1,4], [2,5], [3,6]]
transpose_matrix([[1,2],[3,4],[5,6]]) → [[1,3,5], [2,4,6]]
def diagonal_matrix(mat)
Converts a square matrix mat into a lower diagonal matrix
https://en.wikipedia.org/wiki/Triangular_matrix
After the conversion the values on the diagonal will be the sum of the deleted elements in
the respective row
Return value is None. Variable mat is directly modified in memory
mat is a nested list (e.g. [[1,2,3], [4,5,6], [7,8,9]] and is guaranteed to have a square
shape of size at least 2x2
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() and the del keyword
Examples:
diagonal_matrix([[1,2,3], [4,5,6], [7,8,9]]) → [[6], [4, 11], [7, 8, 9]]
diagonal_matrix([[1,2],[3,4]]) → [[3], [3,4]]
def reduce_matrix(mat)
Reduces the size of matrix mat in half, in both dimensions, by merging adjacent elements
The new values of the matrix are the average of the respective merged elements
Return value is None. Variable mat is directly modified in memory
mat is a nested list (e.g. [[1,2,3,4], [5,6,7,8]] and is guaranteed to be non-empty and have
a rectangular shape. Both dimensions are even numbers
You’re not allowed to use slicing, or import modules, or use the list comprehension syntax
The only functions you’re allowed to use are: len() , range() and the del keyword
Examples:
reduce_matrix([[1,2],[3,4]]) → '[[2.5]]'
reduce_matrix([[1,2,3,4],[5,6,7,8],[9,8,7,6],[5,4,3,2]]) → '[[3.5,5.5],[6.5,4.5]]'