I have such columns in GS:
Equipments Amount . Equipment 1 Equipment 2
---------- ------- ----------- -----------
Equipment 1 2 Process 1 Process 3
Equipment 2 3 Process 2 Process 4
Process 5
I need to produce equipment 1 x2, and equipment 2 x3.
When equipments are produced, then Process 1 is executed 2 times, Process 2 - 2 times, Process 3 - 3 times, Process 4 - 3 times, Process 5 - 3 times.
So I need to generate such list:
Process 1
Process 1
Process 2
Process 2
Process 3
Process 3
Process 3
Process 4
Process 4
Process 4
Process 5
Process 5
Process 5
Of course, I want a formula which will be dynamic (e.g. can add another equipment or change processes in particular equipment)
1 list using rept:
=TRANSPOSE(SPLIT(JOIN(",",FILTER(REPT(C2:C&",",B2),C2:C<>"")),","))
Multy-list rept:
=TRANSPOSE(SPLIT(JOIN(",",FILTER(REPT(C2:C&",",VLOOKUP(D2:D,A:B,2,)),C2:C<>"")),","))
There is no easy way to solve your problem with formulas.
I would strongly suggest you write a script. It's easier than you think. You can even record an action, and then see the code you need to reproduce the action.
Related
I have a dataset where each ID has visited a website and recorded their risk level which is coded 0-3. They have then returned to the website at a future date and recorded their risk level again. I want to calculate the difference between each ID's risk level from their first recorded risk level.
For example my dataset looks like this:
ID Timestamp RiskLevel
1 20-Jan-21 2
1 04-Apr-21 2
2 05-Feb-21 1
2 12-Mar-21 2
2 07-May-21 3
3 09-Feb-21 2
3 14-Mar-21 1
3 18-Jun-21 0
And I would like it to look like this:
ID Timestamp RiskLevel DifFromFirstRiskLevel
1 20-Jan-21 2 .
1 04-Apr-21 2 0
2 05-Feb-21 1 .
2 12-Mar-21 2 1
2 07-May-21 3 2
3 09-Feb-21 2 .
3 14-Mar-21 1 -1
3 18-Jun-21 0 -2
What should I do?
One way to approach this is with the strategy in my answer here, but I will use a different approach here:
sort cases by ID timestamp.
compute firstRisk=risklevel.
if $casenum>1 and ID=lag(ID) firstRisk=lag(firstRisk).
execute.
compute DifFromFirstRiskLevel=risklevel-firstRisk.
Id' like to know if synchronised looping is supported for AKPlayer(s) that are multiples in their duration?
Seems that is not supported or if not intended, it's a bug? Found similar report here (How to use the loop if the track was not started from the beginning (with buffering type = .always in AKPlayer )), where I thought I was providing a solution but after plenty of tests found that the solution provided does not work either. See attachment (*)
I've planned to record some loops that have a duration that is the same or a multiple of the smallest loop. Firstly, found that synchronization failed when trying to start .play for several AKPlayer at the same AVAudioTime start point. After a few attempts, fixed by sticking to buffering .always, among other things such as .prepare method. So, hopefully, that's out of the way...
The problem is that I expect to listen to a bunch of loops play synchronously, even if some are 2x or 4x longer in duration...
So while expecting to have looping work for the main requirement where:
- Loop1 of duration 2.5 [looping]
- Loop2 of duration 2.5 [looping]
- Loop3 of duration 5 [looping]
Noticed that the Loop3 behaves badly, where the last half repeats a few times, let's say for a 4/4, looking at the beat numbers we'd hear the following:
- Loop1: 1 2 3 4, 1 2 3 4, 1 2 3 4, 1 2 3 4
- Loop2: 1 2 3 4, 1 2 3 4, 1 2 3 4, 1 2 3 4
- Loop3: 1 2 3 4 5 6 7 8, 5 6 7 8, 5 6 7 8
Is this expected to fail? is loop of separate players that the duration is multiples, a feature that is supported?
After a few more tests, I find that this happens after adding a third track. For example:
- Loop1: 1 2 3 4
- Loop2: 1 2 3 4 5 6 7 8
Seems to work fine this far, but now I add a new track:
Loop1: 1 2 3 4
Loop2: 1 2 3 4 5 6 7 8
Loop3: 1 2 3 4
And what I hear is:
Loop1: 1 2 3 4 1 2 3 4 1 2 3 4
Loop2: 1 2 3 4 1 2 3 4 5 6 7 8
Loop3: 1 2 3 4 1 2 3 4 1 2 3 4
I'd try AKClipRecorder but just found that I need to declare the length ahead of recording time, it breaks the main requirement :)
(*) Audio file exposing the issue, this test was done with AKWaveTable but seems to be the same problem. I'll look into rewriting some code that is easier to share to see if it's related to my implementation but, there's the link I've shared at the top, where someone else exposes the same problem.
https://drive.google.com/open?id=1zxIJgFFvTwGsve11RFpc-_Z94gEEzql7
I believe that I got the problem and that is related to scheduling the play start time for newer loops.
Before, I'd record a loop and then play it at the currentTime that is the value of a master player. The problem with that is regarding the startTime that the player holds in its state, which is immutable given that is read from memory, from my point of view. Which will always be true to more or less the end-point of the master loop, which is mid-point for the recorded loop that happens to be twice the size or another multiple of the master loop.
To solve this I've scheduled the player items differently, as follows:
player.startTime = 0
player.endTime = audioFile.duration
let offsetCurrentime = ((beatLength * 4.0) - currentTime)
player.play(at: AVAudioTime.now() + offsetCurrentime)
The .startTime defines the start of the loop start point, I've also declared the duration length as the .endTime; Finally, I've computed the length of the master bar or the master loop that I use as a reference (or looper clock), which then is passed to the play method. Meaning that I'm scheduling it to play to the startTime and not from the currentTime as that would cause issues, as I've exposed before!
To summarize, use the property at of method .play to schedule when to start from the starting point and NOT from the current time the loop is on playing.
i recently started machine learning tutorial and very first tutorial was supervised learning (spam and ham), i started by implementing it.
my implementation:
---------total spam count-------------
hi free offers for you and the ! ....
5 3 9 4 4 6 8 6
---------total ham count-------------
hi free offers for you and the ! ....
3 5 3 7 3 4 6 2
mail_1 : hi! how are you here are some free offers for you !!!
hi how are you here are some free offers for you !!!
1 1 2 1 1 2 1 1 1 1 1 4
s[T] = c_spam(T) / ( c_spam(T) + c_ham(T) )
s[T] = how spammy is the word T
c_spam(T) = how many spam messages contain the word T
c_ham(T) = how many non-spam message contain the word T
Now i have two questions:
1) Is this implementation is correct?
2) now after the result of this machine if i found the new mail is spam then would i need to update the old spam model?
I just entered into the space of data mining, machine learning and clustering. I'm having special problem, and do not know which technique to use it for solving it.
I want to perform clustering of observations (objects or whatever) on specific data format. All variables in each observation is numeric. My data input looks like this:
1 2 3 4 5 6
1 3 5 7
2 9 10 11 12 13 14
45 1 22 23 24
Let's say that n represent row (observation, or 1D vector,..) and m represents column (variable index in each vector). n could be very large number, and 0 < m < 100. Also main point is that same observation (row) cannot have identical values (in 1st row, one value could appear only once).
So, I want to somehow perform clustering where I'll put observations in one cluster based on number of identical values which contain each row/observation.
If there are two rows like:
1
1 2 3 4 5
They should be clustered in same cluster, if there are no match than for sure not. Also number of each rows in one cluster should not go above 100.
Sick problem..? If not, just for info that I didn't mention time dimension. But let's skip that for now.
So, any directions from you guys,
Thanks and best regards,
JDK
Its hard to recommend anything since your problem is totally vague, and we have no information on the data. Data mining (and in particular explorative techniques like clustering) is all about understanding the data. So we cannot provide the ultimate answer.
Two things for you to consider:
1. if the data indicates presence of species or traits, Jaccard similarity (and other set based metrics) are worth a try.
2. if absence is less informative, maybe you should be mining association rules, not clusters
Either way, without understanding your data these numbers are as good as random numbers. You can easily cluster random numbers, and spend weeks to get the best useless result!
Can your problem be treated as a Bag-of-words model, where each article (observation row) has no more than 100 terms?
Anyway, I think your have to give more information and examples about "why" and "how" you want to cluster these data. For example, we have:
1 2 3
2 3 4
2 3 4 5
1 2 3 4
3 4 6
6 7 8
9 10
9 11
10 12 13 14
What is your expected clustering? How many clusters are there in this clustering? Only two clusters?
Before you give more information, according to you current description, I think you do not need a cluster algorithm, but a structure of connected components. The first round you process the dataset to get the information of connected components, and you need a second round to check each row belong to which connected components. Take the example above, first round:
1 2 3 : 1 <- 1, 1 <- 2, 1 <- 3 (all point linked to the smallest point to
represent they are belong to the same cluster of the smallest point)
2 3 4 : 2 <- 4 (2 and 3 have already linked to 1 which is <= 2, so they do
not need to change)
2 3 4 5 : 2 <- 5
1 2 3 4 : 1 <- 4 (in fact this change are not essential because we have
1 <- 2 <- 4, but change this can speed up the second round)
3 4 6 : 3 <- 6
6 7 8 : 6 <- 7, 6 <- 8
9 10 : 9 <- 9, 9 <- 10
9 11 : 9 <- 11
10 11 12 13 14 : 10 <- 12, 10 <- 13, 10 <- 14
Now we have a forest structure to represent the connected components of points. The second round you can easily pick up one point in each row (the smallest one is the best) and trace its root in the forest. The rows which have the same root are in the same, in your words, cluster. For example:
1 2 3 : 1 <- 1, cluster root 1
2 3 4 5 : 1 <- 1 <- 2, cluster root 1
6 7 8 : 1 <- 1 <- 3 <- 6, cluster root 1
9 10 : 9 <- 9, cluster root 9
10 11 12 13 14 : 9 <- 9 <- 10, cluster root 9
This process takes O(k) space where k is the number of points, and O(nm + nh) time, where r is the height of the forest structure, where r << m.
I am not sure if this is the result you want.
I am trying to understand the differences between tasks and frames in real-time system. If my understanding is correct, tasks are mainly the combination of different threads that need to be run at a specific rat. For example, I might have task A that has 10 threads. I need to run task A every and I need to repeat the task every 30 ms (i.e. need to finish running all 10 threads by 30 ms). Also, If I cannot finish running everything with in by 30 ms, task 'A' will be "Overrunning".
In relation to this, what is a frame in real-time and how does it fit in with tasks?
I found out that "Passs" are often put out as "Frames" where each pass is actually the rate at which the scheduler runs each task.
e.g. If I have my system demading 100Hz rate:
TASKS RATE(Hz) FRAMES(PASS)
- - - - - - - - - - - - - - - - -
TASK1 100 1
TASK2 50 2
TASK3 25 4
TASK4 12.5 8
TASK5 12.5 4
100 Hz can be divided as:
2 passes (each 50 Hz)
4 passes (each 25 Hz)
8 passes (each 12.5 Hz)
16 passes (each 6.25 Hz)
Silly things!