Implementation of a dataset backed by a server, which in turn uses fi. postgreSQL Fully asynchronous, based on socketIO.
Most methods below result in a message with the methodName and a data object, containing:
dataset: dataset.toJSON()facetId: facet.get(), orfilterId: filter.getId()
Extra messages are available for synchronizing state, which can be both send and received:
syncFilterssyncFacetssyncDataset
these take the Dataset.toJSON() as content.
Data can be requested by sending getData with dataset and filter ID, on which the server
responds with a newData message containing filterId and data.
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Methods
(inner) connect()
Connect to the spot-server using a websocket on port 3080 and setup callbacks
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(inner) initDataFilter(dataset, filter)
Initialize the data filter, and construct the getData callback function on the filter.
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
filter |
Filter |
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(inner) releaseDataFilter(dataset, filter)
The opposite or initDataFilter, it should remove the filter and deallocate other configuration related to the filter.
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
filter |
Filter |
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(inner) scanData(dataset)
Autoconfigure a dataset
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset |
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(inner) setCategories(dataset, facet)
setCategories finds finds all values on an ordinal (categorial) axis Updates the categorialTransform of the facet
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
facet |
Facet |
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(inner) setExceedances(dataset, facet)
Calculate value where exceedance probability is one in 10,20,30,40,50,
Set the facet.continuousTransform to the approximate mapping.
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
facet |
Facet |
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(inner) setMinMax(dataset, facet)
setMinMax sets the range of a continuous or time facet
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
facet |
Facet |
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(inner) setPercentiles(dataset, facet)
Calculate 100 percentiles (ie. 1,2,3,4 etc.), and initialize the facet.continuousTransform
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
facet |
Facet |
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(inner) updateDataFilter(dataset, filter)
Change the filter parameters for an initialized filter
Parameters:
| Name | Type | Description |
|---|---|---|
dataset |
Dataset | |
filter |
Filter |
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