I'm using a Kendo-UI slider to allow the user to dynamically select a specific percentage. Selecting 0% makes no sense in my particular application. The problem is that I need the slider to show the ticks on multiple of 10 values (except on the first value/tick). In order to achieve this I need to set the minimum value to 0 and have the large step from 10 to 10:
#(Html.Kendo().Slider()
.Name("sliderPercentage")
.DragHandleTitle("Select")
.Min(0)
.Max(100)
.SmallStep(1)
.LargeStep(10)
.Value(80)
.HtmlAttributes(new { style = "width:500px;" })
)
This however allows the user to select the 0% value which can be confusing. What I really need is a way of setting the minimum value to 1 and the first large step to 9, so that the ticks are shown like this: 1 10 20 30 40 50 60 70 80 90 100. How can I achieve this?
Related
Here is my problem:
Raw data 1
If there is a position 105 and 150, I need the material number of position 150. If there is only position 105, I need the material number of position 105.
On the right side of the picture you can see the correct selected material number.
Now I need to assign this data to position 100 (bc I will use a counter later on, which is depending on position 100).
Here you can see more of the raw data of the report (I can´t insert the complete report here, I use the details area only for testing).
I marked one "group" in which you can see why I can´t change the order of the positions. In this case I need to use position 105 to output the material number (number rightmost on the red border) because there is no position 150.
Raw data 2
Here is another example with position 150 used for the material number (the correct material number will be placed on position 105 every time):
Raw data 3
To use this material number in my following tables, it need to be assigned to position 100.
Thanks!
I am using data collected from two different instruments which have different resolution because of the sampling rate of each instrument. For a specific time, one of the sets have >10k entries while the other has ~2.5k. They however capture data over the same time interval, and I want to plot them on top of each other even though they have different resolution in data. The minimum and maximum x of both sets are the same however one of them have more entries.
Simplified it could look like this:
1st set from instrument with higher sampling rate:
time(s) value
0.0 10
0.2 11
0.4 12
0.6 13
0.8 14
... ..
100 50
2nd set from instrument with lower sampling rate:
time(s) value
0 100
1 120
2 125
3 128
4 130
. ...
100 430
They are measuring different things, but I would like to display them in the same plot. How can I accomplish this?
I found the mistake.. I was trying to plot both datasets using the time data from the first instrument. Of course they need to be plotted with their respective time data and I put the first time data in the second plot by mistake..
I am using VBA that gets data from an Excel 2013 spreadsheet. I have a couple years experience in computer science from a while back using VBA and java, but I'm by no means an expert.
I have a column of numbers ranging from 20 to 60 total. Each of those numbers represents 'minutes' and can range from 3 to 500 (normally 60 to 300). Each number has an assigner called a 'load number' (such as N03, N22 and etc.) and a date/time. All of these values are attributed to a 'load' that needs to be picked. 'Pickers' are the ones that have the loads or minutes assigned to them. They can only pick so many minutes per given day which ranges from 400-600 (8 hour shift = 400 minutes).
What I need to do is assign sets of loads that are equal to an approximate amount of total minutes (set number w/ threshold) to two groups of pickers (The groups are AM and PM, each have 3-5 pickers). Once one load is assigned to a picker, it can't be assigned to another UNLESS the loads for a given day have too many minutes and all the pickers can't be assigned an approximate amount of minutes.
Example: Out of 8 pickers, 6 can be assigned loads totaling between 380-420 minutes, but 2 can't be assigned between 380-420 because of the remaining loads.
In the case of the given example, for the remaining 2 pickers, a total of 760 - 840 minutes can be assigned to BOTH of them.
Loads also need to be assigned based on their date/time. If pickers are picking loads due on the same day, the earliest loads need to be assigned to the AM group of pickers and, accordingly, the latest to the PM group of pickers. If all loads to be assigned are for the next day, they can be assigned to anyone as long as the earliest loads are prioritized.
Example: AM shift starts at 5AM w/ 5 pickers. There is three loads that are 200 minutes (4 hours, actual) due at 9AM on the same day
The three loads should be assigned to three different pickers, so the loads can be done on time. They would be marked as the #1 load, so each picker knows to do it first
Example: Another load is due at 9AM on the same day. It is 400 minutes though.
2 pickers can be assigned to this load as their #1 pick and 200 minutes would be assigned to both of them.
Once the loads are assigned to the pickers, the results will be displayed in a separate spreadsheet with each row having: AM/PM, Picker's name, Load number #'s 1-10 w/ load number and minutes to pick and the total minutes.
Example: PICKER | AM | Toby | 029-N10 (268), 030-N05 (93), 030-N04 (111) | 472 TOTAL
Any help / pointers on this problem would be appreciated. I've looked at similar questions posted on here and abroad, but couldn't find any that would give me enough to go by to start working on a solution. It's not too bad assigning loads manually, but it gets complex one there's over 30 and 4,000 minutes total and especially when most of them are larger. It would just be much easier having a program assign everything and save 1-2 hours in the process everyday.
Edit:
The data, in Excel, is structured into 8 columns and up to 50 rows. Each row represents a 'load' and has only 3 useful cells. I got all the information into three arrays, which can be used to display the info for any load by using the same element (1-50) for each array.
Dim LoadNumbers(1 To 50) As String
Dim LoadTime(1 To 50) As Double
Dim LoadMinutes(1 To 50) As Double
Dim C As Integer
C = 1
Do While C < 50
LoadNumbers(C) = Cells(C, 2)
LoadTime(C) = Cells(C, 5) * 24
LoadMinutes(C) = Cells(C, 7)
C = C + 1
Loop
For example:
LoadNumbers(5) & " # " & LoadTimes(5) & " Hours PST # " & LoadMinutes(5) & " Minutes"
Will return:
039-N06 # 9.5 Hours PST # 67.4 Minutes (9.5 hours = 9:30AM)
The LoadTimes and LoadMinutes arrays are the ones I need to assign loads. I will have another two cells that users will input the desired minutes (M) to be assigned and the threshold (T). I then need to VBA script to assign (M-T to M+T) minutes to each picker.
Here's what the values in LoadMinutes look like:
141.8
96
73.7
32.2
67.4
106.1
21.3
14.2
141.6
49.5
68.6
200.6
72
174.9
223.1
161.8
76.6
235.5
76.2
134.9
236.7
166.3
170.7
134.6
63.9
352.9
136.2
146.3
243.2
There's 29 loads # 3,818 minutes total
Lets say the minutes need to be between 430 to 470. Out of those 29 loads, I need to assign sets of different numbers adding up to 430 to 470 based on their time. The times in LoadTimes ranges from 7 to 20 (7AM to 8PM).
I can easily calculate the values for sinc(x) curve used in Lanczos, and I have read the previous explanations about Lanczos resize, but being new to this area I do not understand how to actually apply them.
To resample with lanczos imagine you
overlay the output and input over
eachother, with points signifying
where the pixel locations are. For
each output pixel location you take a
box +- 3 output pixels from that
point. For every input pixel that lies
in that box, calculate the value of
the lanczos function at that location
with the distance from the output
location in output pixel coordinates
as the parameter. You then need to
normalize the calculated values by
scaling them so that they add up to 1.
After that multiply each input pixel
value with the corresponding scaling
value and add the results together to
get the value of the output pixel.
For example, what does "overlay the input and output" actually mean in programming terms?
In the equation given
lanczos(x) = {
0 if abs(x) > 3,
1 if x == 0,
else sin(x*pi)/x
}
what is x?
As a simple example, suppose I have an input image with 14 values (i.e. in addresses In0-In13):
20 25 30 35 40 45 50 45 40 35 30 25 20 15
and I want to scale this up by 2, i.e. to an image with 28 values (i.e. in addresses Out0-Out27).
Clearly, the value in address Out13 is going to be similar to the value in address In7, but which values do I actually multiply to calculate the correct value for Out13?
What is x in the algorithm?
If the values in your input data is at t coordinates [0 1 2 3 ...], then your output (which is scaled up by 2) has t coordinates at [0 .5 1 1.5 2 2.5 3 ...]. So to get the first output value, you center your filter at 0 and multiply by all of the input values. Then to get the second output, you center your filter at 1/2 and multiply by all of the input values. Etc ...
I have to retrieve only particular records whose sum value of size field is <=150.
I have table like below ...
userid size
1 70
2 100
3 50
4 25
5 120
6 90
The output should be ...
userid size
1 70
3 50
4 25
For example, if we add 70,50,25 we get 145 which is <=150.
How would I write a query to accomplish this?
Here's a query which will produce the above results:
SELECT * FROM `users` u
WHERE (select sum(size) from `users` where size <= u.size order by size) < 150
ORDER BY userid
However, the problem you describe of wanting the selection of users which would most closely fit into a given size, is a bin packing problem. This is an NP-Hard problem, and won't be easily solved with ANSI SQL. However, the above seems to return the right result, but in fact it simply starts with the smallest item, and continues to add items until the bin is full.
A general, more effective bin packing algorithm would is to start with the largest item and continue to add smaller ones as they fit. This algorithm would select users 5 and 4.
What you're looking for is a greedy algorithm. You can't really do this with one SQL statement.
It's similar to the subset sum problem. You are definitely going to be into exponential time ...
There are several ways to solve subset
sum in time exponential in N. The most
naïve algorithm would be to cycle
through all subsets of N numbers and,
for every one of them, check if the
subset sums to the right number. The
running time is of order O(2^N*N), since
there are 2N subsets and, to check
each subset, we need to sum at most N
elements.
Unless you can constrain the problem to smaller subsets.
According to your definition as it stands you could get any of these tables:
userid size userid size
1 70 2 100
userid size userid size
3 50 4 25
userid size userid size
5 120 6 90
userid size userid size
1 70 2 100
3 50 3 50
userid size userid size
1 70 2 100
4 25 4 25
userid size userid size
1 70 4 25
3 50 6 90
4 25
userid size userid size
4 25 3 50
5 120 6 90
SQL sucks at guessing. Do you mean to say you want the most users who's total size is under a certain limit? You'll need to create a temp table of all the combinations of users, then select the ones who's total size is less then the limit, then select the one with the most users, and possibly the lowest user ID or something. Either way, it won't be fast due to the first step.
But do you want to maximize the number of results or minimize or you simply don't care? first two cases is constraints optimization for which there should be solution using SQL, the latter (as mentioned above) requires greedy strategy.