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You must use the zoom and pan factors in the equation to get map coordinates from screen coordinates: pan will be an x-y offset, while zoom will be a multiplication/division constant.
Note that you might introduce a conversion error if zoom is a floating point number, so you might consider using an integer. The same of course goes for pan factors.
Hope this can help.
2+2=5 for very large amounts of 2
(always loved that one hehe!)
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Hi,
u = (x-xmin)* sx + umin
v = (y-ymin)* sy + vmin
are formulas to translate and scale a coordinate system (x,y) to a new system (u,v)
The inverse operation has exactly the same structure: swap every u and x, and every y and v, and you become the inverse formulas.
x = (u-umin)* su + xmin
y = (v-vmin)* sb + ymin
All you need now is the new constants
Substituting one set into the other should lead to two identity relations, hence:
su=1/sx and sv=1/sy
Luc Pattyn [Forum Guidelines] [My Articles]
The quality and detail of your question reflects on the effectiveness of the help you are likely to get.
Show formatted code inside PRE tags, and give clear symptoms when describing a problem.
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How would I calculate the Z Scores for a list of data - for example if I run a selection on the database then tabulate the values from a particular variable (Marital Status, for example) I get the following columns:
A Description - Widowed, Married, Divorced etc.
Universe - The number of people in the database with that value
Selection - The number of people in the selection with that value
Universe % - the percentage of the total people on the database who have that value
Selection % - the percentage of the total people on the selection who have that value
I also have the number of people on the database and the number of people in the selection
Is it possible to work out a Z Score for each line in this list given the above information and how would I do it in C#?
Thanks
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If think this[^] is what you're looking for.
2+2=5 for very large amounts of 2
(always loved that one hehe!)
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Hello,
I have an app that searches for a directory that has the format "LastName FirstName". However, I want to account for misspellings in the name that is entered. For instance, the directory is named "Stein" but the user enters "Stien". Of course, more un-common misspellings are also possible. I'm looking into using NetSpell[^] and defining a custom dictionary based on the directory names. However, since new directories are always being added with different names, I was wondering what the best way is to automatically keep this dictionary up-to-date. I can certainly auto-update when the program is started, but I'd like a way to keep it updated without have to restart the program. Any ideas?
Thanks,
Dybs
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Hi,
you could have it work like this:
1.
on app start, scan the directory for names; for each name, generate all reasonable variations and add them to a list (variations could be: dropping a letter, swapping two consecutive letters, ...)
2.
whatever the user enters, compare against the list of exact and almost-exact names, and warn the user if there is either no match at all or ambiguity, i.e. he entered something that could lead to different hits.
3.
install a FileSystemWatcher to detect creation of new file objects, treat them the same way as under 1.
Luc Pattyn [Forum Guidelines] [My Articles]
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Show formatted code inside PRE tags, and give clear symptoms when describing a problem.
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Thanks for the suggestions. I completely forgot about the FileSystemWatcher class  Never used it before, but it's exactly what I need. What I was originally thinking was on app start, build a dictionary in NetSpell of all the directory names I'd be searching. If a user enters a directory that doesn't exist, it would run that name through NetSpell and search for any directories matching its suggestions (rather than generating all the variations myself - there are several hundred directories, and that could take some time). But the SoundEx algorithm Henry suggested below sounds like it might be useful as well. Thanks again!
Dybs
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you're welcome.
Luc Pattyn [Forum Guidelines] [My Articles]
The quality and detail of your question reflects on the effectiveness of the help you are likely to get.
Show formatted code inside PRE tags, and give clear symptoms when describing a problem.
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As part of 1. from Lucs' solution a Soundex algorithm might prove useful. There is A SoundEx implementation in .NET[^] on CP that might help.
Henry Minute
Do not read medical books! You could die of a misprint. - Mark Twain
Girl: (staring) "Why do you need an icy cucumber?"
“I want to report a fraud. The government is lying to us all.”
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Beyond Henry's suggestion - you might also want to look at Double Metaphone[^], which provides a richer set of results than Soundex.
"WPF has many lovers. It's a veritable porn star!" - Josh Smith As Braveheart once said, "You can take our freedom but you'll never take our Hobnobs!" - Martin Hughes.
My blog | My articles | MoXAML PowerToys | Onyx
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Hi can someone explain to me what a regular language is? And what is pumping lema?
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Google knows all that kind of stuff.
Luc Pattyn [Forum Guidelines] [My Articles]
The quality and detail of your question reflects on the effectiveness of the help you are likely to get.
Show formatted code inside PRE tags, and give clear symptoms when describing a problem.
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A regular language is the set of strings that can be generated by a regular expression, consisting of strings and the Kleene star (*), (which means zero or more occurrences of substrings). It's also the set of strings that can be generated by a finite-state machine, or recognized by a finite-state acceptor.
It's the simplest of four classes of languages. An example of a non-regular language is the set of strings with equal numbers of 0's and 1's. This can't be recognized by a finite-state acceptor (with n states) since a string with more than n letters would overflow the acceptor's finite capacity.
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Hello,
Pulling my hair out trying to solve this problem. I have a list of data describing maximum allowable speeds along a section of track. I need to sort the data to form a speed 'profile' for that section of track. I'll describe by example:
The generated list may look like this upon retrieval from the database:
<snip>
LOMILE, HIMILE, SPEED
0, 30, 25
2, 10, 15
4, 6, 10
10, 20, 20
<end snip="">
What this describes is a section of track 30 miles long with a normal operating speed of 30 MPH (row 1). However, the operating speed is reduced to 15 MPH from mile 2 to mile 10 (row 2), that section is further reduced to 10 MPH from mile 4 to mile 6 (row 3). The operating speed is reduced to 20 MPH from mile 10 to mile 20 (row 4).
What I've been trying to do is come up with an algorithm that would sort that list into something that looks like this:
<snip>
LOMILE, HIMILE, SPEED
0, 2, 25
2, 4, 15
4, 6, 10
6, 10, 15
10, 20, 20
20, 30, 25
<end snip="">
I'm completely stumped trying to get to the solution. Please help!
It doesn't matter what code you implement in, pseudo code would be ideal, but, however you want to present the algorithm is fine with me.
If you are curious, I'm developing this in Access with VBA, however, in the future I'll probably move it to MySQL with PHP. Therefore, whatever code you want to use to illustrate the algorithm is fine.
Thanks in advance!
Lyle.
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If I understand you correctly, the data means something like this:
|--------------------------| 25
|------------| 15
|----| 10
|-------| 20
And the lowest value on a vertical line would be the maximum allowed speed at that point.
Then you want to somehow split the ranges and drop the parts that are not the minimum.
Cut:
|--|--|----|------|-------|---| 25
|--|----|------| 15
|----| 10
|-------| 20
Drop:
|--| |---| 25
|--| |------| 15
|----| 10
|-------| 20
There is of course an efficient way to do this, but I'm having trouble defining it exactly.
What I can define exactly, is a far less elegant way..
int[] speed = new int[first.high - first.low];
for each section s
{
for (int i = s.low; i < s.high; i++)
speed[i] = min(speed[i], s.speed);
}
You can extract the result from this array in O(size-of-longest-section) time.
Being O(|sections| * size-of-longest-section), this algorithm sucks. But hey, it works.
I'm going to think about this some more, I hope I can accurately define splitting the sections.. Removing the not-minimum cuts after that, is nearly trivial.
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Hi,
here is a KISS approach that might be suboptimal but it is simple:
0. get all the different relevant points (LOMILE and HIMILE) in a list
1. sort the list (probably combine 0 and 1 in "add-and-keep-sorted")
2. start at the first listed position
3. check all the rules, apply the lowest speed, and drive to the next listed point
4. iterate 3 until done.
The advantage is we don't need to find overlaps, intersections, ... in the set of rules. A precondition is the entire trajectory needs to be described in the rules, i.e. there should not be part of the route without speed limitation at all.
PS: sorry Harold for not using your beautiful diagrams...
modified on Thursday, May 7, 2009 7:05 PM
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Hi,
a more elaborate approach:
1. assume a "run" structure holding:
- a pointer to the next run (so we can make chains, i.e. linked lists);
- a LO coordinate;
- a HI coordinate;
- a speed limit.
2. the solution will be built as a linked list of such runs.
3. note that all the rules could be stored as a linked list of runs too.
4. start with one run, copied from the first rule, the one that describes the entire trajectory and the overall speed limit
5. take the next rule, and locate its LO in the current chain of runs: if its LO falls halfway inside a run, replace that run by two runs with the original speed (this probably means adapt the existing run, allocate a new run, give it correct values, and insert it in the linked list)
6. now locate the rule's HI in the chain: if its HI falls halfway some run, split it in two runs.
7. now the current rule exactly covers one or more runs in the current chain, for each of those runs if the rule's speed limit is less than the run's speed, reduce the run's speed.
8. repeat 5-6-7 for all rules
9. now the chain of runs describes the trajectory with the correct speed limits.
remark: if the rules are sorted by LOMILE step 6 can take advantage of that.
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Not certain how efficient this would be, but a tree structure may work for this as well. Bear with me, this might seem more complicated than it really is, trees aren't the easiest to explain in plain text Assume your initial list is sorted the start of each speed segment as you have described, with the first entry covering the overall speed of the track:
TheConfusedGuy wrote: LOMILE, HIMILE, SPEED
0, 30, 25
2, 10, 15
4, 6, 10
*7,9,5
10, 20, 20
*Added for example clarification
I'm thinking the tree structure would be like so:
0,30,25
/ \
2,10,15 10,20,20
/ \
4,6,10 7,9,5
Insert procedure as follows:
1. Root node = (0,30,25)
2. New = (2,10,15), compare = (0,30,25)
3. 2 b/w 0 and 30, compare = child of compare (null/no children)
4. compare = null, add New as child of compare.
5. New = (4,6,10), compare = (0,30,25)
6. 4 b/w 0 and 30, compare = child of compare (2,10,15)
7. 4 b/w 2 and 10, compare = child of compare (null, no children)
8. compare = null, add New as child of compare.
9. New = (7,9,5), compare = (0,30,25)
10. 7 b/w 0 and 30, compare = child of compare (2,10,15)
11. 7 b/w 2 and 10, compare = child of compare (4, 6, 10)
12. 7 past 6, compare = sibling of compare (null, no more siblings)
13. compare = null, add New as sibling of compare
... and so on.
I know the insert procedure seems complicated (trees tend to be that way), but I think it would be relatively efficient. To find the speed limit for a given track position, simply compare the position to the LOWMILE value of each node when you traverse your tree. Your lookup wouldn't be O(1), but no worse O(log m(n)) (I think), where m is the max number of subsections to a given stretch, and n is the total number of defined subsections. So in the example here, it would be O(log 2(3)) Your 2 worst cases would be:
|----|----|----|
|----|
|----|
|----|
or
|----|----|----|
|----|----|
|----|
I hope this all makes sense. This is all totally off the top of me head, so I could be mistaken on how efficient this might be. I'm curious what ya'll's opinion is on this method
Dybs
modified on Friday, May 8, 2009 12:14 AM
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Thanks all for the input. The ideas are pretty good, but, I need to take the scenario further I think to hammer down an algorithm, so bear with me The real world application of this is to calculate train run time over a section of track. I'll use real world examples with explanation to clarify. Here we go:
1. The section of track is called a "subdivision".
2. The 'initial' speed profile for the subdivision is defined by what are called 'zone speeds'.
3. A subdivision can contain many zone speeds, but, the zone speeds do not overlap each other, instead, they run sequentially from one end to the other.
NOTE: to this point, the analysis is simple - it gets tricky with the 4th and 5th point.
4. When the condition of the rail deteriorates to a point where train operation at zone speed is not safe then mechanisms called "temporary slow orders" (TSO) are put in place to restrict the speed until repairs can be made. These mechanisms can be in place for months at a time.
5. These temporary slow orders can, and often do, overlap zone speeds, further, they can, but don't often, overlap each other.
Therefore, consider this scenario:
1. Subdivision length is 50 miles
2. Zone speed 1 exists from mile 0 to mile 28 at 40 MPH
3. Zone speed 2 exists from mile 28 to mile 31 at 20 MPH
4. Zone speed 3 exists from 31 to mile 50 at 25 MPH
NOTE: again, analysis of train speed is simple with this scenario, it gets complicated when the following is added to the scenario:
5. TSO A exists from mile 25 to 29 at 15 MPH
6. TSA B exists from mile 30 to mile 34 at 10 MPH
The data would be presented as it is above as I sort by Zone and TSO and by low mile for both when extracting from the database. So, the question becomes, how do I take that data, as presented above, and create the following list:
1. Mile 0 to 25 @ 40 MPH
2. Mile 25 to 29 @ 15 MPH
3. Mile 29 to 30 @ 20 MPH
4. Mile 30 to 34 @ 10 MPH
5. Mile 34 to 50 @ 25 MPH
??
In terms of the ideas presented above, I have considered using a tree sort, however, does the fact that the children nodes (TSO) can overlap the parent nodes (Zones) present a problem in execution? I had not thought of using a linked list, I think that mechanism might suit the problem, however, I want to think on that a bit more. I wonder if the overlap might cause a problem?
LOL! This problem is killing me. It's been 9 years since I completed my computer science program, and, there is a lot of rust accumulated over the years. The help given thus is greatly appreciated, any other thoughts and or help would also be appreciated.
Lyle.
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TheConfusedGuy wrote:
1. Subdivision length is 50 miles (say default speed = 50 MPH
2. Zone speed 1 exists from mile 0 to mile 28 at 40 MPH
3. Zone speed 2 exists from mile 28 to mile 31 at 20 MPH
4. Zone speed 3 exists from 31 to mile 50 at 25 MPH
5. TSO A exists from mile 25 to 29 at 15 MPH
6. TSA B exists from mile 30 to mile 34 at 10 MPH
1. Mile 0 to 25 @ 40 MPH
2. Mile 25 to 29 @ 15 MPH
3. Mile 29 to 30 @ 20 MPH
4. Mile 30 to 34 @ 10 MPH
5. Mile 34 to 50 @ 25 MPH
Here's a question: what would the speed be for mile 25? 40 or 15? Or are you getting speeds for ranges only?
I hadn't thought about overlapping TSO's, such as 6 above. Such TSOs may need to have a parent node in the tree for each subsection they overlap, as below.
I think the insertion method I described above would still work, where the overlapping TSO would be a child of the subsection starting at 0. The list you described above would have a tree as follows:
0,50,50
/ | \
0,28,40 28,31,20 31,50,25
\ / \ /
25,29,15 30,34,10
Can't think of a good way to split up all the zones using the tree either, to get the speeds for a given range (say miles 26 to 33). Plus, having multiple parent nodes certainly complicates the insertion process, so a linked list like Luc's method is probably better.
Dybs
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> > > Here's a question: what would the speed be for mile 25? 40 or 15?
The speed would be 15 at mile 25. Essentially, the 40 MPH limit ends at 24.99999999999999 and so on.
The rest of your post is why I sort of gave up the idea of a tree. If the TSO did not overlap the zones then the tree approach is very elegent, but, with the overlap it becomes quite complicated.
I'm thinking linked list as well, however, need to think on it some more. The first response to my original is an interesting approach as well. I need to look at that solution more closely.
Lyle.
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do we have any formula for calculating bearing if we are given initial coordinates and great circle distance
thanks
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I'm assuming you're talking about coordinates on a sphere and navigation-type problems - something I know a little bit about.
Unfortunately there are an infinite number of great circles from any position, and therefore an infinite number of points which are at a given distance. It's possible to calculate a bearing between two positions (coordinates) or the distance between them, but not to get a bearing from only one position and a distance.
There are three kinds of people in the world - those who can count and those who can't...
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The exact problem is something like this:
I am drawing a bounding box around the circle.For calculating the right most bottom longitude,instead of making it as simply center Longitude + radius i am also trying to include bearing in it.This bearing corresponds to maxima of longitude.
I am unable to figure out this bearing.?
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Hmmm, that's an interesting problem.
I'm not even sure how to go about drawing the bounding box, or if such a thing really exists in a spherical coordinate system. A few quick sketches show up all sorts of problems in defining the shape - is it a square (with curved edges), or some distorted shape with non-parallel sides? What happens near the poles, or if a pole is inside your circle? I can even end up with a 3-sided "box" in some cases.
I'm afraid I'll have to think a bit more about this one, and get back to you later...
There are three kinds of people in the world - those who can count and those who can't...
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