API / geotoolkit / widgets / timeseries / ScaledData / ScaledData
timeseries.ScaledData.ScaledData
The ScaledData is a helper object that encapsulates the data representing a time series line and allows to associate either conversion and/or interpolation objects with this data.
↳
ScaledData
Methods
Css Properties
| Name | Type | Description |
|---|---|---|
maxwraplevel | number | Maximum wrap level |
minwraplevel | number | Minimum wrap level |
Constructors
• new ScaledData(data, conversion, interpolation?, useOutOfRangeData?)
Create ScaledData
| Name | Type | Description |
|---|---|---|
data | DataTable | DataTableView | Options | abstract log data |
conversion | DataConversion | data conversion |
Optional interpolation | DataInterpolation | algorithm to interpolate samples |
Optional useOutOfRangeData | boolean | convert values equals or less to zero to 0 instead of NaN |
AbstractScaledData.constructor
Methods
▸ convertValueFromSource(v, d?): number
Convert value from original source to current scaled data
| Name | Type | Description |
|---|---|---|
v | number | value of the original data source |
Optional d | number | depth of the original data source |
number
AbstractScaledData.convertValueFromSource
▸ convertValueFromSource(v, d?): number[]
Convert array of values from original source to current scaled data
| Name | Type | Description |
|---|---|---|
v | number[] | array of values of the original data source |
Optional d | number[] | array of depths of the original data source |
number[]
AbstractScaledData.convertValueFromSource
▸ convertValueToSource(v): number
Convert value from scaled data source to original source
| Name | Type | Description |
|---|---|---|
v | number | value of the scaled data source |
number
AbstractScaledData.convertValueToSource
▸ convertValueToSource(v): number[]
Convert array of values from scaled data source to original source
| Name | Type | Description |
|---|---|---|
v | number[] | array of values of the scaled data source |
number[]
AbstractScaledData.convertValueToSource
▸ getClassName(): string
string
AbstractScaledData.getClassName
▸ getDataOrder(): Order
Always return Order.Ascending for time series data
AbstractScaledData.getDataOrder
▸ getDataTimeStamp(): number
number
▸ getIndexRange(fromPosition, toPosition): Range
Return a wrap levels, If data doesn't have wraps than it returns null
Throws
Error if scaled data cannot be created
| Name | Type | Description |
|---|---|---|
fromPosition | number | from position |
toPosition | number | to position |
AbstractScaledData.getIndexRange
▸ getLength(): number
Gets a count of samples
number
▸ getMaxPosition(): number
Returns maximum depth
number
AbstractScaledData.getMaxPosition
▸ getMaxValue(): number
Returns maximum value
number
AbstractScaledData.getMaxValue
▸ getMaxWrapLevel(): number
Return maximum wrap level. By default it is 0
number
AbstractScaledData.getMaxWrapLevel
▸ getMinPosition(): number
Get minimum depth
number
AbstractScaledData.getMinPosition
▸ getMinValue(): number
Returns minimum value
number
AbstractScaledData.getMinValue
▸ getMinWrapLevel(): number
Return minimum wrap level. By default it is 0
number
AbstractScaledData.getMinWrapLevel
▸ getPositionArray(): number[]
Gets position array
number[]
Position array
AbstractScaledData.getPositionArray
▸ getProperties(): OptionsOut
Gets all the properties pertaining to this object
properties object
AbstractScaledData.getProperties
▸ getSample(index): DataSample
Return sample at specified index
| Name | Type | Description |
|---|---|---|
index | number | index of the sample |
sample
▸ getSamples(): DataSample[]
Gets scaled samples
▸ getSource(): DataTable | DataTableView
Gets data source
▸ getValue(position): number
Returns value at specified depth
| Name | Type | Description |
|---|---|---|
position | number | to return value |
number
return value by depth
▸ getValueArray(): number[]
Gets value array either
number[]
Value array
AbstractScaledData.getValueArray
▸ getValueAt(position): number
Gets value
| Name | Type |
|---|---|
position | number |
number
▸ Protected getValueInternal(position, samples): number
| Name | Type |
|---|---|
position | number |
samples | DataSample[] |
number
▸ isForwardOnly(): boolean
Always return true for time series data
boolean
AbstractScaledData.isForwardOnly
▸ isOutdated(): boolean
If data is outdated
boolean
▸ setConversion(conversion): ScaledData
Sets conversion
| Name | Type | Description |
|---|---|---|
conversion | DataConversion | conversion of the data |
this
AbstractScaledData.setConversion
▸ setInterpolation(interpolation): ScaledData
Sets interpolation
| Name | Type | Description |
|---|---|---|
interpolation | DataInterpolation | algorithm to interpolate samples |
this
AbstractScaledData.setInterpolation
▸ setMaxWrapLevel(level): ScaledData
Sets maximum wrap level value
| Name | Type | Description |
|---|---|---|
level | number | maximum wrap level. |
this
▸ setMinWrapLevel(level): ScaledData
Sets minimum wrap level value
| Name | Type | Description |
|---|---|---|
level | number | minimum wrap level |
this
▸ setProperties(properties?): ScaledData
Sets all the properties pertaining to this object
| Name | Type | Description |
|---|---|---|
Optional properties | Options | An object containing the properties to set |
AbstractScaledData.setProperties
▸ Static findIndex(scaledSamples, position, length): number
Find index corresponding to depth
| Name | Type | Description |
|---|---|---|
scaledSamples | DataSample[] | samples |
position | number | depth |
length | number | length of the array in the sample |
number
▸ Static getClassName(): string
string