I have created custom distribution in my model using option list.
First column is account ID. There are 3 types of account High , Low , Medium .
I want to create different scenarios in the model.
if user selects the High type of accounts then agents with High type should get generated at the source. Currently all agents with all account type are generated.
for a particular account type I want to change the custom distribution. e.g if user selects High type of account then the custom distribution for those account will be changed dynamically.
If below two accounts are High type then I want to change the distribution using percentage
before --->>
Account No of Observation
A-3929180 10
A-5414929 20
Let's increase the distribution by 50%
After--->>
Account No of Observation
A-3929180 15
A-5414929 30
I couldn't see any help around creating custom distribution using Option list in Java.
To build a customDistribution that you change during simulation runtime in any way, you can do it yourself by definining it as follows:
new CustomDistributionOfOptions(OptionList.values(),new double[] { 34.0, 4.0, 5.0, })
this is how you construct it programatically... so you have to create a variable of type CustomDistributionOfOptions and then set up a value for it as I mentionned.
The following can be an example of a function you might want to use to change your custom distribution:
double [] values=new double[OptionList.values().length];
int i=0;
for(OptionList o : OptionList.values()){
values[i++]=uniform(1,15);
}
customDist=new CustomDistributionOfOptions(OptionList.values(),values);
Related
OK... let me retry the question.
I'll just walk through the steps I (wrongly) assumed would work.
Create a data table in excel with passenger info (id, flight_time, type, class, qty...), note that the table is sorted by id... not flight_time.
Import this database into anylogic.
Create a population of agents (Passenger/Passengers) from the data table (one/row).
Create a schedule that addresses the Start Column as flight_time and Value column as qty (for this job I'm only sending one passenger at a time therefore qty = 1 for each row).
Set the pedSource to arrive according to schedule and to use the Passenger Agent as the New pedestrian.
So here is where I'm losing it. When I run this model the new Passengers do not have any parameters associated from the data table. The pedestrian id is some weird number (say 3000 or so). I can click on the Passengers icon during run time and scroll through the created agents (all of the parameter data is there and correctly assigned), but I'm not sure how to associate the new Agents in the run-time model with the population of Passengers agents.
Am I missing a step here? I was thinking that if I import a population of agents from a data table and then have each show up at a particular time in the model that I could then do some calculations with regard to each such as ped.exitTime = time() - ped.flightTime - ped.bufferTime.
I'm just not understanding why the table data is not available for use during run-time through ped? Is there another mapping step that must be performed to push the data to the ped agnets?
I'm at an impasse at this point. I hope this question is described more clearly and your feedback is appreciated.
Several things are wrong here.
You do not create agents in a pop first and then try to reuse them in a PedSource. The latter creates agents itself.
You don't seem to create pedestrians but just agents
you are not mapping the data to parameters
Quick guide to help:
create custom agent type "MyPed" . Make sure its "use in flowchart" property is set to "Pedestrian"
add 1 param into "MyPed" for each dbase table column
set your PedSource to "calls of inject()" function for its arrivals
delete your schedule, you cannot get the data you need
USe a DynamicEvent. Include 1 parameter argument for each dbase column. On Startup of main, loop across all dbase entries and create a dynamic event with the current row-data.
in the action of the DynEvent, call myPedSource.inject(1) and then manually fill that ped with the data from the arguments
This is not straightforward, especially the DynEvent stuff. So do more research in the AL help to understand these and how they work, check example models...
continuing a project I have posted a few questions for already are you able to have a more precise definition of what a dropdown is populated with?
I am using FM Starting Point and have a Projects, Estimate and Task table. A project can hold multiple estimates and tasks. Estimates contain multiple lines (stored in a separate table).
When In a Project you can add a task for that project. What I want to do is replace the field that gives the task a name with a list of lines contained within the estimates related to the project i have selected to add the task from.
I have created a dropdown and using the inspector got it to display all estimate lines but somehow I need to write a function that will only select lines from estimates that are within the project and also only estimates that have a field set to "active" for example.
what I am struggling with is where I can programme such a thing? In the inspector, you are limited to displaying a value and cant programme in a statement. I have tried a script that executes OnObjectEnter or OnObjectModify but that doesn't appear to work.
Any ideas where I can enter a more complex set of rules as to what populates a dropdown?
Create a relationship with the criteria you need. Base the value list for the dropdown on this relationship.
As for display, The value list's second field can be from a calculated field with any data or several other fields stringed together if no single field is sufficient. The first field should be the ID.
I want the salesrep to see both theirs and OVERALL TEAMS PERFORMANCE. Is it possible to create a TOGGLE SWITCH : ME/TEAM...when they click on ME - it shows them their revenue and when they click on TEAM - it show overall team revenue. But, they still shouldn't be able to see other salesman revenue...Thanks
Currently, I'm filtering their access to data by their USERNAME using the FULLNAME() function in Tableau. I'm wondering how would the salesrep be able to see the revenue of the TEAM OVERALL which helps them to compare their performance to the team overall
As far as I can tell, with your current setup, you will only be able to display the active sales reps data. This appears to be a requirement for data security. If you want reps to see the overall team data as well, I would create a second data source with aggregated team data, create a view based on this data and place both views side by side on a dashboard.
After that, you could build in the toggle functionality with parameter controls.
Create a parameter. Simple example would be a text input that accepts two values, ME or TEAM. For this example, let's call the parameter Parameter 1.
Set up a conditional calculated field to handle your data security. The condition is based on the parameter. For this example, let's call the calculated field What To Show.
Add a filter, preferably at the data source, for What To Show = True.
The code for What To Show is
if [Parameter 1] = "ME" then [USERNAME] = FULLNAME() END
[USERNAME] of course is whatever your security column is called.
What you are doing here is conditionally applying row-level security based on what parameter your user has selected.
Totaly noob to Tableau, using desktop version 10.0, no access to Tableau Public thanks to work restrictions.
I'm plotting school data by school district. Data dimensions are District, Level (Primary v. Secondary), and Ownership (Pubic v. Private). I want to know how I can make a stacked bar chart that incorporates multiple dimensions (not multiple measures).
For example, I want a bar that shows number of schools in a district, with color breakdown to indicate Public Primary, Public Secondary, Private Primary, Private Secondary.
Currently I have Rows: District; Columns: Number of Schools; Color (under marks): Level. This works fine, but I'm unable to add school ownership as another way to disaggregate.
Do I need to go back into R to make another column that joins Level and Ownership in order for Tableau to be able to figure this out?
Clare, you will need to create a calculated field. Call it "Level + Ownership" and add the calc:
[Level]+":"+[Ownership]
Place the calc on the color card...should be good to go.
What do we have as of now? - We are using Mahout's GenericItemBasedRecommender to get a list of recommended products for a user using TanimotoCoefficientSimilarity as ItemSimilarity.
Where do we want to go from here? - The above works fine when we don't care about product category but what we want to know is the Product Category specific recommendations i.e. Say if a user has been buying, browsing, liking etc. specifically more in Men's and Gadgets category, I would then want to show this user recommendation in that specific category saying Recommended for you in [X] where X would be replaced by Mens or Gadgets in this case. We are thinking about a couple of options below to achieve this and we need some leads/opinion/feedback etc. so as to make sure we are going in the right direction. Options:
Firstly we'll have to move to a non-tanimoto version for calculating item similarity so that we account for users buying, liking, etc and not only view/browsing data.
Figuring out product category for a particular user (this is where we need direction) - Our product category hierarchy is basically a tree and we need to know which top 4 nodes (with best recommendations) in tree we would show to the user. Also if we are saying that node X is a category which we are showing to the user and node Y is a parent of node X we then don't want show user products in category Y or any parent for that matter. Couple of ways achieving this:
For every user calculate SUM of similarity scores values of items for a nodes at leaf level and recursively calculate for parent node till the root. Now at each node we have A = SUM of similarity scores & B = Number of Items Recommended so we also have A/B=Value (V) at each node. Now we pick the top 4 V values from the tree and recommend that to the user. The challenge here is that if we try to calculate this online during the request it we would tough to limit this under 150 ms for the entire request. An Example:
Root Level - Category12 (A=11, B=4) (category1 + category2)
|
_____________________|_________________________
/ \
/ \
Leaf Level - category1 (A=6, B=2) category2 (A=5, B=2)
Recommended products in Category 1: Item1 (score = 2), Item2 (score = 4)
Recommended products in Category 2: Item3 (score = 1), Item4 (score = 4)
Second option: For every category create a cluster of users based on their behaviour (likes, buying, viewing etc.) and then figure out the top 4 categories to which the user belongs. Not sure if we can achieve this using clustering in Mahout but I think we can do this offline.
Please provide your feedback/suggestions/leads/thoughts.
Thanks in advance!
If you want to model more than one thing in your data, I would suggest to use the SVD recommender instead with the ALSWR factorizer set to implicit feedback. With that done you can have user,item,preference in your data and the preference value would be how strongly associated your user is to the item. You can play with the numbers, for example a purchase is a 20 and a view is just a 2. I'm just throwing numbers here, I wouldn't know what will work best for your data, because you can also model things proportionally, as in if a purchase is 30 times less likely to happen than a view, then a purchase should be 30 times stronger than a view.
Mahout provides a way to influence the recommendations through the IDRescorer. You implement your own logic here and decide how to affect the recommendations. For example, the IDRescorer would check if a recommendation candidate belongs to the same category and if it does, boost the score by X. There's an example here (link) from the Mahout in Action Book (which you should definitely read), showing a rescorer.
Hope this helps