I'm currently reading through The Algorithm Design Manual by Steven S. Skiena. Some of the concepts in the book I haven't used in almost 7 years. Even while I was in college it was difficult for me to understand how some of my classmates came up with some of these proofs. Now, I'm completely stuck on one of the exercises. Please help.
Will you please answer this question and explain how you came up with what to use for your Base case and why each step proves why it is valid and correct. I know this might be asking a lot, but I really need help understanding how to do these.
Thank you in advance!
Proofs of Correctness
Question:
1-8. Proove the correctness of the following algorithm for evaluating a polynomial.
$$P(x) = a_nx_n+a_n−1x_n−1+⋯+a_1x+a_0$$
&function horner(A,x)
p=A_n
for i from n−1 to 0
p=p∗x+Ai
return p$
btw, off topic: Sorry guys, I'm not sure how to correctly add the mathematical formatting for the formula. I tried by addign '$' around each section. Not sure why that isn't working.
https://cs.stackexchange.com/ is probably better for this. Also I'm pretty sure that $$ formatting only works on some StackExchange sites. But anyways, think about what this algorithm is doing at each step.
We start with p = A_n.
Then we take p = p*x + A_{n-1}. So what is this doing? We now have p = x*A_n + A_{n-1}.
I'll try one more step. p = p*x + A_{n-2} so now p = (x^2)*A_n + x*A_{n-1} + A{n-2} (here x^2 means x to the power 2, of course).
You should be able to take it from here.
Related
I was trying to solve this integral x/(x-6)dx and I used substitution. u = x-6 and x = u+6.
In the end, I ended up with the answer x+6ln|x-6|-6+C, however, the answer is x+6ln|x-6|+C without the -6. Can someone help me understand why this is the case?
MY SOLUTION
You shouldn’t be asking this here, but I’ll answer you anyway. A constant term “eats” any other constants. Because think about it. +C just denotes “plus any constant” and -6 + C means “Any constant - 6” which is still…”any constant”. So the +C effectively “eats” anything that is added or subtracted to it
I have a hard time wrapping my head around the solution given by Pramp for the problem:
Award Budget Cuts
https://www.pramp.com/challenge/r1Kw0vwG6OhK9AEGAyWV
I do not seem to be able to find some other explanations of what they are doing in their solution.
I kinda understand the other ways of solving it, suggested by other users here:
https://codereview.stackexchange.com/questions/194272/award-budget-cuts-implementation-in-java
But I am trying to understand the reasoning behind the:
surplus1 = surplus0 - 1*(grantsArray[0]-grantsArray[1])
surplus2 = surplus1 - 2*(grantsArray[1]-grantsArray[2])
surplus3 = surplus2 - 3*(grantsArray[2]-grantsArray[3])
Really don't understand that part...
I found myself keep writing pretty long one-liner code(influenced by shell pipe), like this:
def parseranges(ranges, n):
"""
Translate ":2,4:6,9:" to "0 1 3 4 5 8 9...n-1"
== === == === ===== =========
"""
def torange(x, n):
if len(x)==1:
(x0, ) = x
s = 1 if x0=='' else int(x0)
e = n if x0=='' else s
elif len(x)==2:
(x0, x1) = x
s = 1 if x0=='' else int(x0)
e = n if x1=='' else int(x1)
else:
raise ValueError
return range(s-1, e)
return sorted(reduce(lambda x, y:x.union(set(y)), map(lambda x:torange(x, n), map(lambda x:x.split(':'), ranges.split(','))), set()))
I felt ok when I written it.
I thought long one-liner code is a functional-programming style.
But, several hours later, I felt bad about it.
I'm afraid I would be criticized by people who may maintain it.
Sadly, I've get used to writing these kind of one-liner.
I really want to know others' opinion.
Please give me some advice. Thanks
I would say that it is bad practice if you're sacrificing readability.
It is common wisdom that source code is written once but read many times by different people. Therefore it is wise to optimize source code for the common case: being read, trying to understand.
My advice: Act according to this principle. Ask yourself: Can anybody understand any piece of my code more easily? When the answer is not a 100% "No, I can't even think of a better way to express the problem/solution." then follow your gut feeling and reformat or recode that part.
Unless performance is a major consideration, readability of the code should be given high major priority. Its really important for its maintainability.
A relevant quote from the book Structure and Interpretation of Computer Programs.
"Programs should be written for people to read, and only incidentally for machines to execute."
(Update 2022-03-25: My answer refers to a previous revision of the question.)
The first and third examples are acceptable to me. They are close enough to the application domain so that I can easily see the intention of the code.
The second example is much too clever. I don't even have an idea about its purpose. Can you rewrite it in maybe five lines, giving the variables longer names?
I am a Mechanical engineer with a computer scientist question. This is an example of what the equations I'm working with are like:
x = √((y-z)×2/r)
z = f×(L/D)×(x/2g)
f = something crazy with x in it
etc…(there are more equations with x in it)
The situation is this:
I need r to find x, but I need x to find z. I also need x to find f which is a part of finding z. So I guess a value for x, and then I use that value to find r and f. Then I go back and use the value I found for r and f to find x. I keep doing this until the guess and the calculated are the same.
My question is:
How do I get the computer to do this? I've been using mathcad, but an example in another language like C++ is fine.
The very first thing you should do faced with iterative algorithms is write down on paper the sequence that will result from your idea:
Eg.:
x_0 = ..., f_0 = ..., r_0 = ...
x_1 = ..., f_1 = ..., r_1 = ...
...
x_n = ..., f_n = ..., r_n = ...
Now, you have an idea of what you should implement (even if you don't know how). If you don't manage to find a closed form expression for one of the x_i, r_i or whatever_i, you will need to solve one dimensional equations numerically. This will imply more work.
Now, for the implementation part, if you never wrote a program, you should seriously ask someone live who can help you (or hire an intern and have him write the code). We cannot help you beginning from scratch with, eg. C programming, but we are willing to help you with specific problems which should arise when you write the program.
Please note that your algorithm is not guaranteed to converge, even if you strongly think there is a unique solution. Solving non linear equations is a difficult subject.
It appears that mathcad has many abstractions for iterative algorithms without the need to actually implement them directly using a "lower level" language. Perhaps this question is better suited for the mathcad forums at:
http://communities.ptc.com/index.jspa
If you are using Mathcad, it has the functionality built in. It is called solve block.
Start with the keyword "given"
Given
define the guess values for all unknowns
x:=2
f:=3
r:=2
...
define your constraints
x = √((y-z)×2/r)
z = f×(L/D)×(x/2g)
f = something crazy with x in it
etc…(there are more equations with x in it)
calculate the solution
find(x, y, z, r, ...)=
Check Mathcad help or Quicksheets for examples of the exact syntax.
The simple answer to your question is this pseudo-code:
X = startingX;
lastF = Infinity;
F = 0;
tolerance = 1e-10;
while ((lastF - F)^2 > tolerance)
{
lastF = F;
X = ?;
R = ?;
F = FunctionOf(X,R);
}
This may not do what you expect at all. It may give a valid but nonsense answer or it may loop endlessly between alternate wrong answers.
This is standard substitution to convergence. There are more advanced techniques like DIIS but I'm not sure you want to go there. I found this article while figuring out if I want to go there.
In general, it really pays to think about how you can transform your problem into an easier problem.
In my experience it is better to pose your problem as a univariate bounded root-finding problem and use Brent's Method if you can
Next worst option is multivariate minimization with something like BFGS.
Iterative solutions are horrible, but are more easily solved once you think of them as X2 = f(X1) where X is the input vector and you're trying to reduce the difference between X1 and X2.
As the commenters have noted, the mathematical aspects of your question are beyond the scope of the help you can expect here, and are even beyond the help you could be offered based on the detail you posted.
However, I think that even if you understood the mathematics thoroughly there are computer science aspects to your question that should be addressed.
When you write your code, try to make organize it into functions that depend only upon the parameters you are passing in to a subroutine. So write a subroutine that takes in values for y, z, and r and returns you x. Make another that takes in f,L,D,G and returns z. Now you have testable routines that you can check to make sure they are computing correctly. Check the input values to your routines in the routines - for instance in computing x you will get a divide by 0 error if you pass in a 0 for r. Think about how you want to handle this.
If you are going to solve this problem interatively you will need a method that will decide, based on the results of one iteration, what the values for the next iteration will be. This also should be encapsulated within a subroutine. Now if you are using a language that allows only one value to be returned from a subroutine (which is most common computation languages C, C++, Java, C#) you need to package up all your variables into some kind of data structure to return them. You could use an array of reals or doubles, but it would be nicer to choose to make an object and then you can reference the variables by their name and not their position (less chance of error).
Another aspect of iteration is knowing when to stop. Certainly you'll do so when you get a solution that converges. Make this decision into another subroutine. Now when you need to change the convergence criteria there is only one place in the code to go to. But you need to consider other reasons for stopping - what do you do if your solution starts diverging instead of converging? How many iterations will you allow the run to go before giving up?
Another aspect of iteration of a computer is round-off error. Mathematically 10^40/10^38 is 100. Mathematically 10^20 + 1 > 10^20. These statements are not true in most computations. Your calculations may need to take this into account or you will end up with numbers that are garbage. This is an example of a cross-cutting concern that does not lend itself to encapsulation in a subroutine.
I would suggest that you go look at the Python language, and the pythonxy.com extensions. There are people in the associated forums that would be a good resource for helping you learn how to do iterative solving of a system of equations.
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I need to translate some python and java routines into pseudo code for my master thesis but have trouble coming up with a syntax/style that is:
consistent
easy to understand
not too verbose
not too close to natural language
not too close to some concrete programming language.
How do you write pseudo code? Are there any standard recommendations?
I recommend looking at the "Introduction to Algorithms" book (by Cormen, Leiserson and Rivest). I've always found its pseudo-code description of algorithms very clear and consistent.
An example:
DIJKSTRA(G, w, s)
1 INITIALIZE-SINGLE-SOURCE(G, s)
2 S ← Ø
3 Q ← V[G]
4 while Q ≠ Ø
5 do u ← EXTRACT-MIN(Q)
6 S ← S ∪{u}
7 for each vertex v ∈ Adj[u]
8 do RELAX(u, v, w)
Answering my own question, I just wanted to draw attention to the TeX FAQ entry Typesetting pseudocode in LaTeX. It describes a number of different styles, listing advantages and drawbacks. Incidentally, there happen to exist two stylesheets for writing pseudo code in the manner used in "Introductin to Algorithms" by Cormen, as recommended above: newalg and clrscode. The latter was written by Cormen himself.
I suggest you take a look at the Fortress Programming Language.
This is an actual programming language, and not pseudocode, but it was designed to be as close to executable pseudocode as possible. In particular, for designing the syntax, they read and analyzed hundreds of CS and math papers, courses, books and journals to find common usage patterns for pseudocode and other computational/mathematical notations.
You can leverage all that research by just looking at Fortress source code and abstracting out the things you don't need, since your target audience is human, whereas Fortress's is a compiler.
Here is an actual example of running Fortress code from the NAS (NASA Advanced Supercomputing) Conjugate Gradient Parallel Benchmark. For a fun experience, compare the specification of the benchmark with the implementation in Fortress and notice how there is almost a 1:1 correspondence. Also compare the implementation in a couple of other languages, like C or Fortran, and notice how they have absolutely nothing to do with the specification (and are also often an order of magnitude longer than the spec).
I must stress: this is not pseudocode, this is actual working Fortress code! From https://umbilicus.wordpress.com/2009/10/16/fortress-parallel-by-default/
Note that Fortress is written in ASCII characters; the special characters are rendered with a formatter.
If the code is procedural, normal pseudo-code is probably easy (Wikipedia has some examples).
Object-oriented pseudo-code might be more difficult. Consider:
using UML class diagrams to depict the classes/inheritence
using UML sequence diagrams to depict the sequence of code
I don't understand your requirement of "not too close to some concrete programming language".
Python is generally considered as a good candidate for writing pseudo-code. Perhaps a slightly simplified version of python would work for you.
Pascal has always been traditionally the most similar to pseudocode, when it comes to mathematical and technical fields. I don't know why, it was just always so.
I have some (oh, I don't know, 10 maybe books on a shelf, which concrete this theory).
Python as suggested, can be nice code, but it can be so unreadable as well, that it's a wonder by itself. Older languages are harder to make unreadable - them being "simpler" (take with caution) than today's ones. They'll maybe be harder to understand what's going on, but easier to read (less syntax/language features is needed for to understand what the program does).
This post is old, but hopefully this will help others.
"Introduction to Algorithms" book (by Cormen, Leiserson and Rivest) is a good book to read about algorithms, but the "pseudo-code" is terrible. Things like Q[1...n] is nonsense when one needs to understand what Q[1...n] is suppose to mean. Which will have to be noted outside of the "pseudo-code." Moreover, books like "Introduction to Algorithms" like to use a mathematical syntax, which is violating one purpose of pseudo-code.
Pseudo-code should do two things. Abstract away from syntax and be easy to read. If actual code is more descriptive than the pseudo-code, and actual code is more descriptive, then it is not pseudo-code.
Say you were writing a simple program.
Screen design:
Welcome to the Consumer Discount Program!
Please enter the customers subtotal: 9999.99
The customer receives a 10 percent discount
The customer receives a 20 percent discount
The customer does not receive a discount
The customer's total is: 9999.99
Variable List:
TOTAL: double
SUB_TOTAL: double
DISCOUNT: double
Pseudo-code:
DISCOUNT_PROGRAM
Print "Welcome to the Consumer Discount Program!"
Print "Please enter the customers subtotal:"
Input SUB_TOTAL
Select the case for SUB_TOTAL
SUB_TOTAL > 10000 AND SUB_TOTAL <= 50000
DISCOUNT = 0.1
Print "The customer receives a 10 percent discount"
SUB_TOTAL > 50000
DISCOUNT = 0.2
Print "The customer receives a 20 percent discount"
Otherwise
DISCOUNT = 0
Print "The customer does not a receive a discount"
TOTAL = SUB_TOTAL - (SUB_TOTAL * DISCOUNT)
Print "The customer's total is:", TOTAL
Notice that this is very easy to read and does not reference any syntax. This supports all three of Bohm and Jacopini's control structures.
Sequence:
Print "Some stuff"
VALUE = 2 + 1
SOME_FUNCTION(SOME_VARIABLE)
Selection:
if condition
Do one extra thing
if condition
do one extra thing
else
do one extra thing
if condition
do one extra thing
else if condition
do one extra thing
else
do one extra thing
Select the case for SYSTEM_NAME
condition 1
statement 1
condition 2
statement 2
condition 3
statement 3
otherwise
statement 4
Repetition:
while condition
do stuff
for SOME_VALUE TO ANOTHER_VALUE
do stuff
compare that to this N-Queens "pseudo-code" (https://en.wikipedia.org/wiki/Eight_queens_puzzle):
PlaceQueens(Q[1 .. n],r)
if r = n + 1
print Q
else
for j ← 1 to n
legal ← True
for i ← 1 to r − 1
if (Q[i] = j) or (Q[i] = j + r − i) or (Q[i] = j − r + i)
legal ← False
if legal
Q[r] ← j
PlaceQueens(Q[1 .. n],r + 1)
If you can't explain it simply, you don't understand it well enough.
- Albert Einstein