代做comp20005、代写Information Systems、代写Python编程、代做c/c++，Java代写

日期：2019-05-19 09:31

School of Computing and Information Systems

comp20005 Engineering Computation

Semester 1, 2019

Assignment 2

Learning Outcomes

In this project you will demonstrate your understanding of structures and arrays of structures, and will

develop a computational solution for a non-trivial problem. You are expected to make extensive use of

functions; and to demonstrate that you have adopted a clear and elegant programming style. You will find

it difficult to create a working solution unless you plan your program carefully in advance, and develop

it incrementally.

The Mission

You will again be working with numeric data, this time in connection with rainfall records. All of

the data files used in this project have been sourced directly from the Bureau of Meteorology web site at

http://www.bom.gov.au/climate/data/, and remain in the format in which they were downloaded.

The program that you write will identify historical trends that may exist in the input data, and allow

visualization of the data.

Stage 1 – Reading the Data (Marks up to 9/20)

In this stage you should read all of the data into internal structures suitable for use in the later stages, and

create an output representation that provides an overview of the data that was read. Input will come from

a comma-separated-values file, with each input line (after the first header line) looking like:

IDCJAC0001,086039,2000,01,28.2,Y

IDCJAC0001,086039,2000,02,34.5,Y

IDCJAC0001,086039,2000,03,22.5,Y

IDCJAC0001,086039,2000,05,96.3,Y

IDCJAC0001,086039,2000,06,42.4,Y

IDCJAC0001,086039,2000,07,45.1,Y

recording, for example, that the rainfall measured at site 086039 (Flemington Racecourse, in Melbourne)

in January 2000 was 28.2 millimeters. The last value in each line is Y or N to indicate whether the data

has been “validated”. To read one line, you should use the format control string

"IDCJAC0001,%d,%d,%d,%lf,%c"

with suitable receiving variables, and then skip any remaining characters on that line until a newline

character has been consumed. Note that IDCJAC0001 is a fixed string that identifies the type of data, and

will appear in all data files that your program will process.

You may assume that the lines in the input are always in ascending-year then ascending-month order,

but also need to be aware that there may be missing data lines. For example, there is no data for April

2000 in the test file shown above. Missing values are completely typical of sensor-based data, and occur

because of equipment malfunction, network errors, and so on.

A sample of the required output of this stage is:

mac: ass2-soln < rainfall-086039-2000-2009.csv

S1, site number 086039, 115 datalines in input

S1, 2000: Jan Feb Mar ... May Jun Jul Aug Sep Oct Nov Dec

S1, 2001: Jan Feb Mar ... May Jun Jul Aug Sep* Oct Nov* Dec

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<plus lines for the other seven years>

S1, 2009: Jan Feb* Mar Apr May Jun* Jul Aug Sep Oct Nov Dec

where rainfall-086039-2000-2009.csv is one of the test files linked from the FAQ page; where *

indicates a value that has not been validated; and where ... indicates a completely missing value. Full

output examples are linked from the FAQ page. Note that the input might start part way through one

year and end part way through another, so be sure that you handle the first and last year correctly. There

might also be whole missing years, in which case your program should report every month for that year

as a ... entry.

You should be able to get started on the required program for this stage quite quickly, based on your

solution to the first project (or the sample solution to the first project). And an explicit permission – you

may include this declaration as a global array if you wish to (and if you can see how it would be useful):

char *months[] = {"", "Jan", "Feb", "Mar", "Apr", "May", "Jun",

"Jul", "Aug", "Sep", "Oct", "Nov", "Dec"};

Stage 2 – The Annual Rainfall Cycle (Marks up to 12/20)

Add further functionality to your program so that for each month of the year the average rainfall is

computed and reported. All months for which at least one data item is available should be listed, and

unverified items should also be counted and included in the average. A sample of output lines for the

same test file is:

S2, Jan, 10 values, 2000-2009, mean of 23.5mm

S2, Feb, 10 values, 2000-2009, mean of 45.5mm

S2, Mar, 9 values, 2000-2009, mean of 33.8mm

<plus lines for the other eight months>

S2, Dec, 10 values, 2000-2009, mean of 48.6mm

Full examples are linked from the FAQ page, including showing what should be written if there are no

rainfall records in one or more of the months. Note that the monthly averages are required again in

Stage 4, so they should be computed in this stage and then retained, rather than being computed again

later.

Stage 3 – Climate Change? (Marks up to 16/20)

Ok, now for some trend analysis. Suppose that a sequence of n values hr0 . . . rn?1i is given (in this case,

ri

is the rainfall amount for some specific month across a sequence of years), and we wish to know if

there is an overall upward or downward trend over the n values. One simple correlation coefficient that

can be used is Kendall’s τ (pronounced “tau”), which for data already ordered on one aspect (in our case,

ordered by time) is computed as:

where δ(ri, rj ) is +1 if ri < rj ; is ?1 if ri > rj ; and is 0 if ri = rj . A τ value of +1.0 indicates

perfect monotonic increase across the sequence of values; a τ value of ?1.0 indicates perfect monotonic

decrease across the sequence of values; and a τ value of 0.0 indicates neither consistent growth nor

consistent decrease.

In this stage you are to compute twelve τ values from the input data, one τ for each of the months.

Each τ value will be computed from the sequence hrii that represents the rainfall for one specific month

across the span of years available in the data. No τ value should be reported if there are less than two

instances of that particular month in the input file, see the FAQ for examples.

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S3, Jan, 10 values, 2000-2009, tau of -0.11

S3, Feb, 10 values, 2000-2009, tau of -0.11

S3, Mar, 9 values, 2000-2009, tau of -0.11

<plus lines for the other eight months>

S3, Dec, 10 values, 2000-2009, tau of 0.36

Stage 4 – Let It Rain! (Marks up to 20/20)

And now for the fun. Add further functionality to your program so that, for each year number specified as

an argument on the command-line, a bar chart is plotted showing the rainfall for that year broken down

by months, compared to the average for that month across the years listed in the input data file. One

complete graph is to be produced for each year that is specified as a program argument, see the examples

linked from the FAQ page. If no arguments are supplied, no graphs are to be generated. To control the

height of the graph, a vertical scaling factor should be identified by finding the smallest integer such that

the height of the maximum point plotted in the graph above the axis is at most 24 rows.

The example below shows the required output for the year 2003 when using the same sample data

file. To make this graph, the largest point to be plotted is identified as being 71.6 mm of rain, and hence

a scale factor of d71.6/24e = 3 is required. Then to get the first bar, January 2003 had a rainfall (in this

data file) of 9.8 mm and the January average (in this data file) is 23.5 mm, and so with a scale factor of

three, the January average is plotted in the 8 th cell high (d23.5/3e = 8) and the January actual is plotted

from the first to the 4 th cells high (d9.8/3e = 4). Note that the graph cells in the row to the right of

each numbered label v (for example, look at v = 24 in the example) get used for values of r (rainfall

amount) in the range v ?scale < r ≤ v. The January monthly average in this data file is 23.5, and hence

is marked in the row labeled v = 24. If the value had been exactly 24.0 it would also be plotted in that

cell, but if it was 24.1 it would appear in the row labeled 27. Finally, note that the two digits used in each

bar are the last two digits of the year number that is being plotted.

mac: ass2-soln 2003 < rainfall-086039-2000-2009.csv

<output for stages 1, 2, 3>

S4, 2003 max is 71.6, scale is 3

72 | 03 03

69 | 03 03 03

66 | 03 03 03

63 | 03 03 03

60 | 03 03 03 03

57 | 03 03 03 03 **** 03

54 | 03 03 03 03 03

51 | 03 03 03 **** *03* *03*

48 | **** 03 03 *03* 03 03

45 | 03 03 03 03 03

42 | 03 *03* 03 03 03

39 | *03* **** 03 03 03 03 03 03

36 | **** 03 *03* 03 03 03 03 03

33 | 03 03 03 03 03 03 03

30 | 03 03 03 03 03 03 03

27 | 03 03 03 03 03 03 03 03 03

24 | **** 03 03 03 03 03 03 03 03 03

21 | 03 03 03 03 03 03 03 03 03 03 03

18 | 03 03 03 03 03 03 03 03 03 03 03

15 | 03 03 03 03 03 03 03 03 03 03 03

12 | 03 03 03 03 03 03 03 03 03 03 03 03

9 | 03 03 03 03 03 03 03 03 03 03 03 03

6 | 03 03 03 03 03 03 03 03 03 03 03 03

3 | 03 03 03 03 03 03 03 03 03 03 03 03

0 +-----+----+----+----+----+----+----+----+----+----+----+----+

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

If there is no record of rainfall for a particular month within the year being plotted (or if there is

no data for that whole year at all, including cases when the specified year is outside the span of years

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included in the data file), plot that month as zero (which means, no marking in the graph), but still plot

the average. If there is no average, because there were no readings at all for that month in the input file,

don’t plot the average either.

Modifications to the Specification

There are bound to be areas where this specification needs clarification or correction. Refer to the

FAQ page at http://people.eng.unimelb.edu.au/ammoffat/teaching/20005/ass2/ regularly

for updates to these instructions. There is already a range of information provided there that you need to

be aware of, with more likely to follow.

The Boring Stuff...

This project is worth 20% of your final mark. A rubric explaining the marking expectations is linked

from the FAQ page, and you should read it carefully.

You need to submit your program for assessment; detailed instructions on how to do that are linked

from the FAQ page. You can (and should) use submit both early and often – to get used to the way

it works, and also to check that your program compiles correctly on the test server, which has some

different characteristics to the lab machines. Failure to follow this simple advice is likely to result in

tears. Only the last submission that you make before the deadline will be marked.

You may discuss your work during your workshop, and with others in the class, but what gets typed

into your program must be individual work, not copied from anyone else. So, do not give hard copy

or soft copy of your work to anyone else; do not “lend” your “Uni backup” memory stick to others

for any reason at all; and do not ask others to give you their programs “just so that I can take a look

and get some ideas, I won’t copy, honest”. The best way to help your friends in this regard is to say a

very firm “no” when they ask for a copy of, or to see, your program, pointing out that your “no”, and

their acceptance of that decision, is the only thing that will preserve your friendship. A sophisticated

program that undertakes deep structural analysis of C code identifying regions of similarity will be run

over all submissions. Students whose programs are identified as containing significant overlaps will be

evaluated for mark penalties of for referral to the Student Center for possible disciplinary action without

further warning. This message is the warning. See https://academicintegrity.unimelb.edu.au

for more information. Note also that solicitation of solutions via posts to online forums, whether or not

there is payment involved, is also taken very seriously. In the past students have had their enrolment

terminated for such behavior.

Very Important: The FAQ page contains a link to a program skeleton that you must start with,

including an Authorship Declaration that you must “sign” and include at the top of your submitted

program. Marks will be deducted if you do not include the declaration, or do not sign it, or do not

comply with its expectations.

Deadline: Programs not submitted by 10:00am on Monday 27 May will lose penalty marks at the

rate of two marks per day or part day late. Students seeking extensions for medical or other “outside

my control” reasons should email ammoffat@unimelb.edu.au as soon as possible after those circumstances

arise. If you attend a GP or other health care professional as a result of illness, be sure to take

a Health Professional Report form with you (get it from the Special Consideration section of the Student

Portal), you will need this form to be filled out if your illness develops in to something that later

requires a Special Consideration application to be lodged. You should scan the HPR form and send it in

connection with any non-Special Consideration assignment extension requests.

A sample solution will be linked from the FAQ page by June 4, and it is hoped that marks will be

available on the LMS by the evening of Tuesday 11 June.

c The University of Melbourne, 2019. Prepared by Alistair Moffat,

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