I have the following:
for location in self.locationsWithinMapFiltered {
self.mapView.addAnnotation(location)
}
but based upon filtering, the user can remove some annotation which do not fulfill their criteria. I have a list of the location_id's to
remove but there doesn't seem to be a way to get out the location_id from the annotation.
I was thinking of using the coordinate's to determine
which is which but that seems like a cumbersome way or just removing all and adding only the ones of interest but again pretty cumbersome. Is there a way to efficiently remove a subset of annotations?
Related
Is it possible to sort returned objects from Backand based on how near the location field of type "point" is to the querying users current location?
From the Backand docs I have only seen support for querying based on a maximum distance from a point but nothing about sorting by geo points.
I was able to create a custom query in Backand which I can hit from the Backand API. Unfortunately in order to sort on the distance of nearby users I need to calculate the distance from the current user to every other user in the database and then sort based on this. Seems very complex - a lot of calculations every time the query is called! Will probably see big performance hits as the database gets larger. Guess it answers this question, but I am hopeful still of finding a better alternative.
I'm trying to make something where you search for something and it shows the locations a map. I am wondering if there is a way to get a unique id for a location (using mapkit and corelocation) so that I can store it for later. After that, when someone searches some locations and the one with the id that is saved is there, I do something else
Basically I need to get a unique id for a certain location to do something to it later. Right now I'm using the latitude and longitude, but I was wondering if there is a better way.
I think you might want to look into MKAnnotation. That way you can create an annotation for each location you want to save and then later retrieve them.
From the MKAnnotation docs:
The MKAnnotation protocol is used to provide annotation-related
information to a map view. To use this protocol, you adopt it in any
custom objects that store or represent annotation data. Each object
then serves as the source of information about a single map annotation
and provides critical information, such as the annotation’s location
on the map. Annotation objects do not provide the visual
representation of the annotation but typically coordinate (in
conjunction with the map view’s delegate) the creation of an
appropriate MKAnnotationView object to handle the display.
A position is identified by its latitude and longitude (and altitude if you consider 3 dimensions).
When you say location, however I assume you mean more than just position. For example, a restaurant and a bar may be at the same position in terms of latitude and longitude, but are different locations when you consider their name, type of business and so on.
If you create a table in Parse to store locations then you can add columns for all of these attributes, and when you save an object to this table, Parse will assign that object a unique identifier. This object is how you will identify and refer to locations in your app.
You can store a position in Parse using a PFGeoPoint, which is simply a convenient way of storing a latitude and longitude (and Parse has support for identifying nearby positions in a query).
In the VIPER design pattern, should the Interactor return all the information that might be used by multiple presenter actions or should I have a separate struct for each one?
In my case, I have a map that displays places. To display those places I need to retrieve a list of PlaceItem's from a PlacesInteractor which could have only a coordinate and a color (used to change the pin's head color) that would be transformed into a annotations by the presenter.
Now lets say that when the user selects one of the annotations in the map, a callout bubble should be displayed with more details like the place's name and a circle with the color.
Now I should create a RetrievePlaceCalloutInteractor that would return only the information for one place instead of a list of information for multiple places (Right? Or should I have only one Interactor for both scenarios?).
Should this RetrievePlaceCalloutInteractor return a PlaceCalloutItem with only the name and the color (no coordinate) of the place or should I have a single PlaceItem with coordinate, color and name, that would be returned by the RetrievePlaceCalloutInteractor and by the PlaceInteractor, and would be used by the presenter to construct either a CalloutStruct or a list of MKAnnotations?
Thank you.
VIPER is a pattern, not a very formal pattern, not a religion or a complete app architecture. For me VIPER helped to think more about a cleaner architecture but on the way I had to make decisions that were better for my specific scenario without caring to much about VIPER but about clean architecture. So, from my experience and my point of view the answer to your question is 'depends'.
In my case most of the 'Items' (I call them DO from Display Object or Data Object) have almost a one to one relationship with the 'Entities' (I call them MO from Model Object). Most of the interactors manipulate one type of Entity and they have one MO-DO mapper. I usually use the same DO for different use cases if the interactor handle more than one use case.
BUT
I also have some modules using different DOs for different uses cases, although they relate to the same entity, and also I have some DOs with combine the information of several Entities, let's say for example I needed the user name to add it to 'edited by' of a blog post I use the same DO to combine Post and User Entities.
I think VIPER 'wants' one interactor per module, that kind of forces you to have multiple use cases (related) in it, but it is up to you if you want to use different Items (my DOs) or only one.
Being a purist of clean architecture you should have different interactors, different requests and different responses for each use case.
So, as I started, it depends, the important thing is to 'draw' the boundaries properly and it doesn't matter if it's one or ten Items you use for that.
I want to implement some king of spatial indexing data structure for my MKAnnotations.
Currently it's horribly slow when I try to filter them based on distance criteria ( 3-4k of locations, currently extremely slow with a simple double for ... ).
I'd like to create clusters of MKAnnotations, to decide if it is close to another. Also, these locations are in a somewhat (creation) order and a "previous"/"next" functionality would be needed to "jump" between (this is not a must).
I've read about kd-tree and r-tree structures and they both seem to meet the fast distance/neighbor obtaining option for filtering/clustering, but I'm not sure which is the best for me or if there are other options too.
What algorithm/data structure should I use ?
Update: I store these locations in a Core Data database, they represent a path. When the map is opened they are fetched into an array and then I just use that array for distance calculations and annotation creation.
When the user moves/zooms the map, I loop through them and decide what needs to be changed on map, so it is kinda static the whole stuff. As I understood, if I'd be using a tree, I could store the locations there and when a zoom/move happens I just search through it and obtain the ones in the new region. Is this true ?
Even in the dynamic case, when I can add new locations to this array, it would be a single insertion and it's happening rarely.
It depends a lot on what your usage patterns are (how my writes, for example, in-memory or on-disk) and how your data looks like (that is how it is distributed).
R-trees are good because they are balanced, and allow updating. The R*-tree in my experience is clearly better than the other variants because of the split strategy it has. The benefit is that it produces more square pages than the other strategies, so that for many queries you will need to scan fewer pages.
kd-trees are good if you are in-memory and static. Updating them is very bad, you will need to rebuild the index quite often.
And if your data does not change very often, bulk-loading for the R-tree works very well. You can do Sort-Tile-Recursive bulk loading, which essentially requires (partially) sorting your data on X and Y alternatingly, so it takes a low O(n log n) to build the tree; very similar to bulk-loading an kd-tree, except that you multi-split instead of binary splitting. This is very popular.
Furthermore, you can keep track of the number of objects in each page. When displaying things on a map, you may want to stop early when a page would display too small on the screen (i.e. smaller than a marker). At this point, you would not scan that page, but only take the number of objects and display that as a clustered marker until the user zooms in.
For 2D data, with a limited value domain, do not overlook the simple things. Quadtrees can work really well, too! Simplicity can make it a lot easier to optimize things. Or a classic grid approach. If your users tend to spread their annotations in an area (and not put them all into one place), you can just compute integer x,y grid coordinates, and then hash them and make a list for each grid cell.
I am no iOS developer, but I looked over the docs and found this:
MKMapView.annotationsInMapRect:
Returns the annotation objects located in the specified map rectangle.
(NSSet *)annotationsInMapRect:(MKMapRect)mapRect
Parameters
mapRect: The portion of the map that you want to search for annotations.
Return Value
The set of annotation objects located in mapRect.
Discussion
This method offers a fast way to retrieve the annotation objects in a particular portion of the map. This method is much faster than doing a linear search of the objects in the annotations property yourself.
This suggests that the NKMapView already organizes annotations in a spatial index structure. Would this method meet your needs?
If not, I would look for existing open source implementations of any 2D spatial indexing structure and pick the one with best documentation, cleanest interfaces, etc. rather than worrying about efficiency. If you need to write the code form scratch, I think a quadtree would be the easiest to implement. On the other hand, the Wikipedia article on R-tree seems more specifically targeted towards mapping than the K-D Tree or Quadtree.
I'd like to be able to order my search results by score and location. Each user in the DB has lat/lot and I am currently indexing:
location :coordinates do
Sunspot::Util::Coordinates.new latlon[0], latlon[1]
end
The model which I would performing the search against is also indexed in the same manner. Essentially what I am trying to achieve is that the results be ordered by score and then by location. So if I search for Walmart, I would like to see all Walmart's ordered by their geo proximity to my location.
I remember reading something about solr's new geo-sort but not sure if it is out of alpha and/or if sunspot has implemented a wrapper.
What would you recommend?
Because of the way that Sunspot calculates location types you'll need to do some extra leg work to have it sort by distance from your target as well. The way it works is that it creates a geo-hash for each point and then searches using regular fulltext search on that geo-hash. The result is that you probably won't be able to determine if a point 10km away is further than a point that is 5km away, but you'll be able to tell if a point 50km away is further than a point 1-2km away. The exact distances are arbitrary but the result is that you probably won't have as fine-grained of a result as you would like and the search acts more as a way to filter points that are within an acceptable proximity. After you have filtered your points using the built-in location search, there are three ways to accomplish what you want:
Upgrade to Solr 3.1 or later and upgrade your schema.xml to use the new spatial search columns. You'll then need to make custom modifications to Sunspot to create fields and orderings that work with these new data types. As far as I know these aren't available in Sunspot yet, so you'll have to make those connections on your own and you'll have to dig around in Solr to do some manual configurations.
Leverage the Spatial Solr Plugin. You'll have to install a new JAR into your Solr directory and you'll have to make some modifications to Sunspot, but they are relatively painless and the full instructions can be found here.
Leverage your DB, if your DB is also indexed on the location columns then you can use the Sunspot built-in location search to filter your results down to a reasonable sized set. You can then query the DB for those results and order them by proximity to your location using your own distance function.