Realtime data and Openlayers 3: Batch moving features - javascript

I have a hashtable I am trying to use in an vector layer so this is what I made:
var make = [], remove = [];
for (var key in data) {
var val = data[key];
if (featureCache[key]) {
if (val._ts > featureCache[key]._ts) {
var geom = featureCache[key].getGeometry();
The problem starts here. From what I have found out so far I have two options:
geom.setCoordinates(latlng([val.Latitude, val.Longitude]));
geom.flatCoordinates = latlng([val.Latitude, val.Longitude]);
However the first one bubbles up and makes the map render, this is a problem because I have over 1500 features and I plan on using more.
The second line gives me assertion failed, and I dont know how to debug it.
featureCache[key]._ts = val._ts;
}
} else {
make.push(featureCache[key] =
new ol.Feature({
geometry: new ol.geom.Point(latlng([val.Latitude,val.Longitude]))
})
);
featureCache[key]._ts = val._ts;
}
}
source.addFeatures(make);
This needs to be run every other second or so because I want the data to be as realtime as possible.
And if this is a really stupid way do do it, I would like to know that too.

I am not sure how you could do it with the new API, but you could try this:
clone an old geometry and update it, do this for each
add the clone to a collection that OL is not aware of (avoids the map render / updates)
once that collection is ready, remove the old collection from OL and set the new (batch)
Doing this for several thousand items should work pretty fast on 'modern' browsers as you set it only once. The key point is to avoid triggering updates while you update each entry.
Maybe there are ways to avoid the bubbling/events to allow for batch updates (no triggering of map render for each change) ?

Related

HERE Traffic incidents integration in Leaflet.js

Background:
I'm currently integrating HERE maps into our web-based application. I'm trying both - HERE provided Javascript API and Leaflet at the same time to find the best approach for our use-case.
While JavaScript API provided by HERE maps is OK, rendering wise Leaflet performs much better when using raster tiles.
Issue:
It would be fine by me to use raster tiles + leaflet, but our application also needs to display traffic incidents data.
Traffic incident data is provided by HERE in JSON and XML formats (Documentation link, Example JSON). They provide [Z]/[X]/[Y], quadkey, prox, bbox, or corridor filters which can be used to retrieve filtered data set.
I've tried using [Z]/[X]/[Y] addressing with custom L.TileLayer implementation which loads appropriate JSON, converts it to GeoJSON and displays GeoJSON on map. However that approach is very inefficient and significant performance drop is visible.
Question:
Maybe anyone has already solved this issue and could share any insights on how the HERE traffic incidents could be shown on Leaflet map without encountering performance issues?
I created the following script, which works without any performance issues:
var fg = L.featureGroup().addTo(map);
function loadTraffic(data) {
fg.clearLayers();
var d = data.TRAFFICITEMS.TRAFFICITEM.map((r) => {
var latlngs = [];
if (r.LOCATION.GEOLOC) {
if (r.LOCATION.GEOLOC.ORIGIN) {
latlngs.push(L.latLng(r.LOCATION.GEOLOC.ORIGIN.LATITUDE, r.LOCATION.GEOLOC.ORIGIN.LONGITUDE));
}
if (r.LOCATION.GEOLOC.TO) {
if (L.Util.isArray(r.LOCATION.GEOLOC.TO)) {
r.LOCATION.GEOLOC.TO.forEach((latlng) => {
latlngs.push(L.latLng(latlng.LATITUDE, latlng.LONGITUDE));
})
} else {
latlngs.push(L.latLng(r.LOCATION.GEOLOC.TO.LATITUDE, r.LOCATION.GEOLOC.TO.LONGITUDE));
}
}
}
var desc = r.TRAFFICITEMDESCRIPTION.find(x => x.TYPE === "short_desc").content;
return {
latlngs,
desc
}
})
console.log(d);
d.forEach((road)=>{
L.polyline(road.latlngs,{color: 'red'}).addTo(fg).bindPopup(road.desc);
});
map.fitBounds(fg.getBounds())
}
If this script is not working for you, please share your json file.
Ok, so I've found a solution for this task. Apparently I was on a good path, I only needed to optimize my implementation.
What I had to do to achieve appropriate performance is:
Create custom CircleMarker extension which would draw custom icon on canvas
Create JS worker which would fetch the data from a given URL, transform it to GeoJSON and return GeoJSON to it's listener
Create custom GridLayer implementation, which, in fetchTile function, creates worker instance, passes it a link with appropriate [Z]/[X]/[Y] coordinates already set, adds listener, which listens for worker's done event and returns empty tile
On worker's done event, custom GridLayer implementation creates GeoJSON layer, adds it to the dictionary with coordinates as a key and, if zoom level is still the same - adds that layer to the map
Add zoomend observer on a map, which removes any layers that does not match current zoom level from the map
Now the map is definitely usable and works way faster than original HERE JS API.
P.S. Sorry, but I can't share the implementation itself due to our company policies.

usage of querySourceFeatures and setData

I'm developping a map using mapbox gl js, my issue is the following:
I have 1 source and I apply 1 setData on this source with a geojson collection of points -> fine
I want to update one position for one feature (point) of this featurecollection
I do querySourceFeatures and I get an array of features -> fine
I detect the feature I want to modify and I modify the lat-long accordingly -> fine
I would like to apply the whole setData with the modify feature to redraw but ...
Here is the problem, how do I go from the array of features (one is modified) to a feature collection compatible with setData ... ?
I'm confused why (or what) there is not a straight path to do that ... What do I miss here?
can you help me please?
thanks,
Olivier
finally, I rebuild the featureCollection "manually" in a separate function ... I though it would not be an optimized solution but at the end, reveals quite straight ...
function build_featureCollection_from_array(parray) {
lv_fc = {};
lv_fc.type = "FeatureCollection";
lv_fc.features = parray;
return lv_fc;
}

OpenLayers: How to assign custom id's to clusters to retrieve on click

we are using OpenLayers 4.6.4 with the ol-ext extension in order to show beautiful looking clusters. That is working fine so far, but we need to link each cluster with custom informations (like putting a simple field into the cluster object) and once the cluster is clicked on the map, i want to retrieve it with the arguments delivered in the callback.
I was not able to find a simple example on putting custom fields on a cluster and retrieving them once i click them on the map.
The event i add my listener is handled by ol.interaction.SelectCluster from ol-ext
Any ideas?
You cannot change the cluster features so easily, but that's actually not necessary to get information about it.
Cluster is just a layer source which clusters (who would have guessed) an underlaying source. It creates Features, which in turn have the represented Features stored in a property features.
The ol-ext example demonstrates how to read the contained features:
var selectCluster = new ol.interaction.SelectCluster(.....);
selectCluster.getFeatures().on(['add'], function (e)
{ var c = e.element.get('features');
if (c.length==1)
{ var feature = c[0];
$(".infos").html("One feature selected...<br/>(id="+feature.get('id')+")");
}
else
{ $(".infos").text("Cluster ("+c.length+" features)");
}
})
Without any interaction, you could do this:
map.on('singleclick', function(evt) {
const feature = map.forEachFeatureAtPixel(
evt.pixel,
function(someFeature){ return someFeature; }, // stop at the very first feature
);
const containedFeatures = feature.get('features');
});

How get features from a style's layer in Mapbox GL JS?

I'm a learner of JavaScript and have a problem with Mapbox GL JS: I have a style in Mapbox Studio, where there is one my layer — "locations". I've added it as a tileset. There are two GeoJSON-points in this layer, but I can't get them in GL JS.
I've found that I should use method querySourceFeatures(sourceID, [parameters]), but I have problems with correct filling its parameters. I wrote:
var allFeatures = map.querySourceFeatures('_id-of-my-tyleset_', {
'sourceLayer': 'locations'
});
..and it doesn't work.
More interesting, that later in the code I use this layer with method queryRenderedFeatures, and it's okay:
map.on('click', function(e) {
var features = map.queryRenderedFeatures(e.point, {
layers: ['locations']
});
if (!features.length) {
return;
}
var feature = features[0];
flyToPoint(feature);
var popup = new mapboxgl.Popup({
offset: [0, -15]
})
.setLngLat(feature.geometry.coordinates)
.setHTML('<h3>' + feature.properties.name + '</h3>' + '<p>' +
feature.properties.description + '</p>')
.addTo(map);
});
I have read a lot about adding layers on a map and know that the answer is easy, but I can't realise the solution, so help, please :)
Here is the project on GitHub.
Your problem is that your map, like all maps created in Mapbox Studio by default, uses auto-compositing. You don't actually have a source called morganvolter.cj77n1jkq1ale33jw0g9haxc0-2haga, you have a source called composite with many sub layers.
You can find the list of layers like this:
map.getSource('composite').vectorLayerIds
Which reveals you have a vector layer called akkerman. ("locations" is the name of your style layer, not your source layer). Hence your query should be:
map.querySourceFeatures('composite', {
'sourceLayer': 'akkerman'
});
Which returns 4 features.
There are lots of questions about Mapbox get features after filter or Mapbox get features before filter. And I could see there are many posts are scattering around but none of them seem to have a FULL DETAILED solution. I spend some time and put both solution together under a function, try this in jsbin.
Here it is for someone interested:
function buildRenderedFeatures(map) {
// get source from a layer, `mapLayerId` == your layer id in Mapbox Studio
var compositeSource = map.getLayer(mapLayerId.toString()).source;
//console.log(map.getSource(compositeSource).vectorLayers);
var compositeVectorLayerLength = map.getSource(compositeSource).vectorLayers.length - 1;
//console.log(compositeVectorLayerLength);
// sourceId === tileset id which is known as vector layer id
var sourceId = map.getSource(compositeSource).vectorLayers[compositeVectorLayerLength].id;
//console.log(sourceId);
// get all applied filters if any, this will return an array
var appliedFilters = map.getFilter(mapLayerId.toString());
//console.log(appliedFilters);
// if you want to get all features with/without any filters
// remember if no filters applied it will show all features
// so having `filter` does not harm at all
//resultFeatures = map.querySourceFeatures(compositeSource, {sourceLayer: sourceId, filter: appliedFilters});
var resultFeatures = null;
// this fixes issues: queryRenderedFeatures getting previous features
// a timeout helps to get the updated features after filter is applied
// Mapbox documentation doesn't talk about this!
setTimeout(function() {
resultFeatures = map.queryRenderedFeatures({layers: [mapLayerId.toString()]});
//console.log(resultFeatures);
}, 500);
}
Then you call that function like: buildRenderedFeatures(map) passing the map object which you already have when you created the Mapbox map.
You will then have resultFeatures will return an object which can be iterated using for...in. You can test the querySourceFeatures() code which I commented out but left for if anyone needs it.

Multi-dimensional input in Keras.js

I am looking to implement my Keras model into my website with the Keras.js library. One problem with this library is that when inputting data in javascript, only a Float32Array() is allowed as an input. This type of array is 1D, and in my Keras model, the input is 3D. I have asked on the Keras.js issues page and found some potential solutions such as adding an embedding layer, but that requires a specific input shape, but I would like to have any 3D input work, as it did when I trained the model. The model structure is simple, there is an input layer which takes an array of dimension mxnx3 (it is an image of unknown size with r, g, and b channels) and a Conv2D layer, which then outputs an mxnx1 array. I know the model works because it can give a good output based on an input, so the only problem I have is with the transition to Keras.js. Here is the JS code that I have at the moment.
function predictImageWithCNN(data) { //'data' is mxnx3 array
var final = [];
//instantiating model from json and buf files
var model = new KerasJS.Model({
filepaths: {
model: 'dist/model.json',
weights: 'dist/model_weights.buf',
metadata: 'dist/model_metadata.json'
},
gpu: true //MAY NEED TO CHANGE (NOT SURE REALLY)
});
//Ready the model.
model.ready()
.then(function() {
//This matches our input data with the input key (b/c Sequential Model)
var inputData = {
'input_1': new Float32Array(data)
};
// make predictions based on inputData
return model.predict(inputData);
})
.then(function(outputData) {
//Here we take the outputData and parse it to get a result.
var out = outputData['output']; //Gets output data
console.log(out);
//TODO: Put in code to assign outputData to 'final' so we can then convert it
// This should not be too hard to do.
})
.catch(function(err) {
console.log(err);
// handle error
});
return final; // should return nxmx1 array of vals 0-1.
}
If anyone had any suggestions for how to resolve this, that would be very much appreciated. Thanks! :)
I had the same problem with an LSTM. The way I got around this was by training using a flattened version of the data but using a reshape layer as the first layer to get it to the shape I needed for my LSTM. eg.
model = Sequential()
model.add(Reshape((40,59),input_shape=(1,2360)))
model.add(LSTM(128, input_shape=(maxlen, len(chars))))
model.add(Dense(len(chars)))
model.add(Activation('softmax'))
optimizer = RMSprop(lr=0.01)
model.compile(loss='categorical_crossentropy', optimizer=optimizer)
Then in Keras.JS I can feed in the flattened version from Float32Array

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