Common Settings

Overview

The Common Settings are shared settings supported by all widgets.

Widget Settings

  • The settings apply to the [widget] section.
Name Description
type Widget visualization type: chart, gauge, bar, histogram, box, calendar, treemap, pie, console, property, text, page, graph.
Example: type = chart
title Title displayed above chart.
HTML Markup is supported.
Example: title = CPU Usage Statistics
on-title-click Action, executed on title click. Available arguments:
widget - object, corresponding to current widget
config - object, representing parsed configuration
next - callback, representing default action.
Default value: next().
Example: on-title-click = widget.reload()
tooltip Widget description displayed on title mouseover.
Example: tooltip = CPU Usage
style Widget CSS style.
Example: style = background-color: skyblue
header-style Widget header CSS style.
Example: header-style = color: red
colors Comma separated list of colors applied to series shapes: lines, rectangles, or circles, depending on the widget type.
Possible values: color names or hex codes.
Default values: steelblue, orange, forestgreen, blueviolet, maroon, yellowgreen, magenta, chocolate, deepskyblue, gray.
Additional series are assigned colors at random.
Example: colors = green, #cccccc.
Recommended color picking tools: colorhexa, material.io, web colors.

Position and Size

Name Description
width-units Number of columns the widget occupies.
Default value: 1.
Example: width-units = 0.5
height-units Number of rows the widget occupies.
Default value: 1.
Example: height-units = 2
top-units Widget offset, in units, from the top page border.
Default value is equal to the ordinal number of its [group] section.
Example: top-units = 2
left-units Widget offset, in units, from the left page border.
Default value is equal to the ordinal number of the widget within the [group].
Example: left-units = 2

See also Layout Settings that determine the total number of columns and rows in a grid placement.

Date Filter

Name Description
timespan Time interval for loading historical data, measured in time units.
Format: count unit, for example 1 day.
The end of the timespan is set to current browser time, unless start-time or end-time setting is specified.
timespan = all retrieves all data.
Default value is 1 hour except for the alert table where timespan is set to all.
Example: timespan = 6 hour
start-time Start of the time interval specified as ISO date, local date, or calendar expression.
Example: start-time = current_hour
end-time End of time interval specified as ISO date, local date, or calendar expression.
If start-time is set, the end time is calculated as start time plus the timespan.
end-time is set to now if start-time is not specified.
Example: end-time = 2018-07-05T13:00:00Z
timezone Time zone used for interpreting local dates specified in start-time and end-time settings, and for calendar aggregation where period is 1 day or longer.
Possible values: UTC or none.
If UTC is set, start-time and end-time settings specified in local format are evaluated based on the UTC time zone.
If UTC is not set, samples are displayed in the local time zone.
Example: timezone = UTC
time-offset Time series offset specified as the number of time units.
time-offset > 0: Offset into the past.
time-offset < 0: Offset into the future.
Format: count time_unit.
Example: time-offset = 3 month
  • Supported date formats for start-time and end-time settings:
    • ISO date in UTC time zone: yyyy-MM-ddTHH:mm:ss[.S]Z, for example: 2018-07-16T20:00:00Z.
    • Local date: yyyy-MM-dd[ HH:mm:ss[.S]], interpreted in the browser time zone, for example: 2017-08-16 or 2018-07-16 20:00:00.
    • Calendar expression, for example: previous_week or current_day + 4*hour.

Last Insert Filter

The filter selects entire series based on the timestamp of the most recent sample.

Name Description
min-insert-time Include series if the timestamp of the latest sample is equal or greater than min-insert-time, specified as ISO date, local date, or calendar expression.
Example: min-insert-time = current_hour
max-insert-time Include series if the timestamp of the latest sample is less than max-insert-time, specified as ISO date, local date, or calendar expression.
Example: max-insert-time = previous_hour
  • Supported date formats for min-insert-time and max-insert-time settings:
    • ISO date in UTC time zone: yyyy-MM-ddTHH:mm:ss[.S]Z, for example: 2018-07-16T20:00:00Z.
    • Local date: yyyy-MM-dd[ HH:mm:ss[.S]], interpreted in the browser time zone, for example: 2017-08-16 or 2018-07-16 20:00:00.
    • Calendar expression, for example: previous_week or current_day + 4*hour.

Data Loading

Name Description
series-limit Maximum number of series retrieved from the database.
Default value: 1000.
Example: series-limit = 10
limit Maximum number of samples retrieved for each returned series.
Default value: 0 (not limited).
Example: limit = 100
cache Query last values from the cache table for faster response.
Possible values: false, true.
Default value: false.
Example: cache = true
add-meta Include metric and entity metadata in the response.
Possible values: false, true.
Default value: false.
Example: add-meta = true
filter Boolean expression (sampleFilter) applied to detailed samples. Samples that satisfy the condition are included in the result. Note that literal dates are evaluated in the server time zone.
Examples:
filter = value > 1
filter = date.timeOfDay > '07:00'

See also Control fields in REST API.

Data Update

Name Description
update-interval Interval for loading incremental data specified as the number of time units.
Format: count time_unit.
Default value: 1 minute.
Example: update-interval = 5 minute
refresh-interval Interval for including the series into the update request to load incremental data.
While the setting has no effect on the update frequency, set with update-interval, it controls which series are included in the request.
The interval is specified as the number of time units.
Format: count time_unit.
Example: refresh-interval = 5 minute
retry-refresh-interval Interval for including empty series into the update request to load incremental data. Empty series contain no data.
The setting has no effect on the update frequency, set with update-interval, however it controls which series are included in the request.
The interval is specified as the number of time units.
Format: count time_unit.
Example: retry-refresh-interval = 5 minute
error-refresh-interval Interval for including failed series into the update request to load incremental data. Failed series are series for which a request to load data from server produced an error.
The setting has no effect on the update frequency, set with update-interval, however it controls which series are included in the request.
The interval is specified as the number of time units.
Format: count time_unit.
Example: error-refresh-interval = 30 minute
batch-update Send data queries to the server in batches with size specified in batch-size setting.
Possible values: false, true.
If true, series for which the request has failed are requested separately from successfully updated series.
Default value: false.
Example: batch-update = true
batch-size Maximum number of series per server batch request.
If 0 is specified, the limit is not set and all series are requested in one query.
Valid when batch-update = true.
Default value: 8.
Example: batch-size = 1

See also Data API Endpoints in REST API.

Data Source

Name Description
url Server URL, if different from the origin host.
URL for data requests is built from {url}{context-path}{method-path}{url-parameters}.
Example: url = https://atsd.example.org:8443
context-path Context path for data requests.
Default value: /api/v1/.
Example: context-path = /api/v2/
path REST API method path.
Default value is specific for each data type: /series/query, /properties/query, /messages/query, /alerts/query.
Example: path = /series/query
url-parameters Optional request parameters included in data requests.
Parameter names and values must be URL-encoded and separated by &.
? at the beginning of the query is optional.
Example: url-parameters = db=1

Legend

Name Description
legend-position Legend location.
Possible values: hidden, top, right, bottom, left
Default value: hidden for a single series, top for multiple series.
Combine values to define corners.
Example: legend-position = left

Axis

Name Description
axis-title Vertical text displayed along the left axis.
Example: axis-title = CPU Utilization in %
axis-title-right Vertical text displayed along the right axis.
Example: axis-title-right = Free Memory
day-format Time axis format.
Example: day-format = %Y/%m/%d
min-range Left axis minimum range.
If loaded values exceed min-range value, axis range is adjusted to show loaded values.
Example: min-range = 0
max-range Left axis maximum range.
If loaded values exceed max-range value, axis range is adjusted to show loaded values.
Example: max-range = 100
min-range-right Right axis minimum range.
If loaded values exceed min-range-right value, right axis range is adjusted to show loaded data.
Example: min-range-right = 0
max-range-right Right axis maximum range.
If loaded values exceed max-range-right value, right axis range is adjusted to show loaded data.
Example: max-range-right = 100
max-range-force Left axis forced minimum and maximum range.
If loaded values exceed max-range-force, axis range is not adjusted to show loaded values.
max-range-force must be equal or exceed max-range.
Example: max-range-force = 100
min-range-force Left axis forced minimum and maximum range.
If loaded values exceed min-range-force, axis range is not adjusted to show loaded values.
Example: min-range-force = 0
min-range-right-force Right axis forced minimum range.
If loaded values exceed min-range-right-force, right axis range is not adjusted to show loaded values.
Example: min-range-right-force = 0
max-range-right-force Right axis forced maximum range.
If loaded values exceed max-range-right-force, right axis range is not adjusted to show loaded values.
Example: max-range-right-force = 100

Difference between range settings.

  • *-range settings specify the minimum and maximum value displayed on the axis.
  • *-range-force settings set the thresholds for hiding values outside of the range.

Series Settings

  • The settings apply to the [series] section.

Series Selection

Name Description
metric Metric name.
When requesting data from a relational database specify both table and attribute as an alternative.
Example: metric = cpu_busy
table Table in the relational database from which to retrieve numeric values.
Alternative to metric setting.
Both table and attribute must be defined.
Example: table = KLZ_CPU
attribute Column name in a relational database table. The column must be of numeric data type.
Example: attribute = Current_Average
data-type Series data type.
Possible values: history, forecast, forecast_deviation, lower_confidence, upper_confidence.
Example: data-type = forecast
forecast-name Forecast name when data-type setting is set to forecast, forecast_deviation, lower_confidence, upper_confidence.
If no forecast name is specified, the default series forecast is loaded.
Example: forecast-name = hw5

Entity Filter

Name Description
entity Entity name.
Supports ? and * wildcards.
Example: entity = nurswgvml007
entities Select multiple entities with one setting.
If both entity and entities are specified, entity takes precedence.
Supports ? and * wildcards.
Example: entities = nurswgvml007, nurswgvml008
entity-group Entity group name.
Example: entity-group = nmon-sub-group
entity-expression Server-side entity filter to select series for matching entities by name, tags, and fields.
Refer to Entity Filter REST API documentation for more information.
Example: entity-expression = tags.app LIKE '*a*'

Tag Filter

To select series with specific tags, add a [tags] section or define a condition using the tag-expression setting.

[series]
  metric = disk_used
  entity = nurswgvml007
  [tags]
    mount_point = /tmp
    fstype = tmpfs

To match multiple values for the same tag, separate the values with a comma. Escape commas if necessary using backslash.

[tags]
  tag_name = tag_value1, tag\,value

To match multiple tag values, use ? and * wildcards:

[tags]
  tag_name = *val*

If the tag name contains an equals sign =, a comma,, or reserved names such as setting names, enclose the tag name in double quotes to avoid collisions:

[tags]
  "type" = sensor
  "tag\=name" = tag\,value
Name Description
tag-expression Server-side tag filter to select series for matching tags.
Example: tag-expression = tags.make LIKE 'AU*'
exact-match Ignore series with tags other than those specified in the [tags] section.
Default value: false.
Example: exact-match = true

SQL

Name Description
sql SQL query. Can be specified as sql/endsql block or as multiple sql= settings. If specified, context-path is set to /api/sql/, path is set to series and url-parameters are set to ?q=${sql}&timeFormat=milliseconds.
Example:
sql
    SELECT time, entity, value FROM cpu_busy
    WHERE time > now - 5 * minute
endsql

Legend

Name Description
label-format Series label pattern consisting of literal text and placeholders.
Example: label-format = entity

Series Style

Name Description
color Color applied to series shape.
Possible value: color name or hex code.
Default values: steelblue, orange, green, purple, maroon, yellowgreen, hotpink, chocolate, deepskyblue.
Additional series are assigned colors at random.
Example: color = blue
Recommended color picking tools: colorhexa, material.io.
label Series label displayed in the legend. Overrides label-format.
Example: label = CPU Busy - nurswgvml007
style CSS style applied to the series shape.
Example: style = stroke-width: 4
style = stroke-dasharray: 5 1 2
tooltip Tooltips displayed on mouseover.
Example: tooltip = NURSWGVML007
axis Series axis placement.
Possible values: left, right.
Default value: left.
Example: axis = right
format Format series values with a measurement unit.
Example: format = kilobytes
display Hide series based on boolean value or expression.
Supported fields: value, previous, time, value and ranking functions.
Example:
display = value > 100
display = max('1 hour') > 50
display = value >= top(3)
display = false
display = !isNaN(value)
display = time < new Date().getTime() - 60*60000*24
display = this.lastRequestTime - this.last.t < 60000
display = tags.location != 'SVL'
display = +meta().entity.tags["capacity"] > 100
enabled Toggle series visibility. Same as the display setting except that the disabled series legend remains visible.
Example:
enabled = false
alert-expression Boolean expression to apply conditional CSS style to series shapes.
The CSS style must be specified in the alert-style setting.
The value field refers to the series value.
Example: alert-expression = value < 95
alert-style CSS style applied to the series shape if alert-expression returns true.
Example: alert-style = fill: red; stroke: red
audio-alert Boolean expression to apply conditional CSS style to series shapes.
Example: audio-alert = /portal/resource/alarm.ogg

Transformation

Transformation Order

Name Description
transformation-order transformation-order controls the sequence of data modification procedures.
Default sequence: interpolate, group, rate, aggregate, smooth, downsample, forecast, none.
Example: transformation-order = downsample, aggregate.
Default value: none. If set to none, the default sequence is used.
If specified, the server-aggregate setting is set to true by default.

Aggregation

Aggregation splits the underlying series into periods of equal duration and applies statistical functions to values in each period. The derived series is regular and has fewer samples.

[series]
  statistics = avg
  period = 5 minute

Name Description
server-aggregate Forces aggregation on server side.
Default value: false.
Example: server-aggregate = true
statistics Statistical function applied to values in each period.
Example: statistics = avg
period Repeating time interval to split the timespan, specified as the number of time units.
Possible values: count time_unit or auto.
Example: period = 15 minute
align Alignment of the period start or end time.
Possible values: CALENDAR, START_TIME, END_TIME, FIRST_VALUE_TIME.
Default value: CALENDAR.
Example: align = END_TIME
interpolate Add missing aggregation periods.
Possible values: NONE, LINEAR, PREVIOUS, NEXT, VALUE(n), where n is the numerical value to be used to fill missing samples.
Default value: NONE.
Example: interpolate = LINEAR
interpolate-extend Interpolate leading and trailing periods with NEXT or PREVIOUS value.
Example: interpolate-extend = true

See also Aggregation transformation in REST API.

Interpolation

Name Description
interpolate-function Interpolation function applied to detailed samples.
Possible values: NONE, LINEAR, PREVIOUS, NEXT, VALUE(n), where n is the numerical value to be used to fill missing samples.
Default value: NONE.
Example: interpolate-function = linear
interpolate-period Interpolation period specified as the number of time units.
Format: count time_unit.
Example: interpolate-period = 1 minute
interpolate-boundary Interpolation for leading and trailing values.
Possible values: inner- Data outside of the selection interval is not loaded by the database. outer- One value before and one value after the selection interval is loaded by the database to interpolate leading and trailing values.
Default value: inner.
Example: interpolate-boundary = outer
interpolation-fill Interpolate values outside of the selection interval.
Possible values: false, true, count of values to fill.
Default value: false.
Example: interpolate-fill = true

See also Interpolation transformation in REST API.

Rate

Name Description
rate Compute the difference between consecutive samples per period of time.
If the period duration is zero, for example rate = 0, the rate function calculates the difference between consecutive samples, without adjusting it by the time difference between the samples.
Format: count time_unit.
Example: rate = 15 second
rate-counter Possible values: false, true.
Default value: true
If true, negative differences between consecutive sample values are converted to 0.
Example: rate-counter = true

See also Rate transformation in REST API.

Merging

Name Description
merge-series Merge multiple series loaded with the same [series] section into one series. Duplicate samples with the same timestamp are discarded.
Possible values: false, true.
Default value: false (keep series separate).
Example: merge-series = true
merge-fields Merge series based on the specified field(s).
Applies if merge-series is set to true.
Possible values:
entity - Combine series with the same entity into one.
tag-name - Combine series with the same value for the specified tag into one series.
Example: merge-fields = mount_point

Grouping

Name Description
group-statistic Group statistic function applied to matching series. Note that DELTA and COUNTER functions are not supported by this transformation.
Example: group-statistic = sum
group-period Group period over which to calculate group statistics specified as the number of time units.
Format: count time_unit.
Default value: auto (inherited from period or set to 15 minute if period is not set.
Example: group-period = 1 day
group-interpolate Interpolate grouped values.
Possible values: LINEAR, PREVIOUS, VALUE.
Example: group-interpolate = LINEAR
group-interpolate-extend Fill missing leading and trailing periods with NEXT or PREVIOUS values.
Example: group-interpolate-extend = true

See also Grouping transformation in REST API.

Downsampling

Name Description
downsample Enable downsampling.
Possible values: false, true.
Default value: false.
Example: downsample = true
downsample-gap Frequency of repeated values defined as downsample-gap in time units.
A larger gap value decreases the occurrence of repeated values.
Possible values: count time_unit.
Default value: 10 minute.
Example: downsample-gap = 10 minute
downsample-ratio Downsample ratio.
Example: downsample-ratio = 1.1
downsample-algorithm Downsample algorithm used in calculation.
Possible values: DETAIL, INTERPOLATE.
Default value: DETAIL.
Example: downsample-algorithm = interpolate
downsample-difference Deviation between consecutive values which ATSD considers equivalent.
Consolidate samples with minor deviations when downsampling.
Example: downsample-difference = 4

See also Downsampling transformation in REST API.

Smoothing

Name Description
smooth Averaging function applied to window samples.
Possible values: AVG, EMA, WAVG, WTAVG.
Example: smooth = AVG
smooth-count Window size.
A larger window performs greater smoothing.
Example: smooth-count = 50
smooth-interval Window duration interval, specified as the number of time units.
Format: count time_unit.
Example: smooth-interval = 15 minute
smooth-minimum-count Minimum number of samples in a window required to apply the smoothing function.
Default value: 1.
Example: smooth-minimum-count = 10
smooth-incomplete-value Sample value returned when downsampling window is not full.
Example: smooth-incomplete-value = NaN
smooth-factor EMA smoothing parameter.
EMA does not depend on the window size.
In the presence of gaps, EMA reaction is delayed due to the missing prior values.
Default value: 0.25.
Possible values: (0, 1).
Example: smooth-factor = 0.50
smooth-range EMA smoothing parameter, as an alternative to smooth-factor.
The difference with the factor parameter appears when the samples are irregular.
EMA does not depend on the window size.
Example: smooth-range = 60000

See also Smoothing transformation in REST API.

Forecasting

Shared Forecasting Settings
Name Description
forecast-include Include input series, forecast, or reconstructed series into response.
Possible values: RECONSTRUCTED, HISTORY, FORECAST.
Default value: FORECAST.
Example: forecast-include = HISTORY, FORECAST
forecast-horizon-interval Generate a forecast for the specified interval into the future starting with last sample of the loaded series.
The interval is specified as the number of time units.
Format: count time_unit.
Example: forecast-horizon-interval = 1 day
forecast-horizon-length Generate a forecast for the specified number of samples into the future.
Example: forecast-horizon-length = 30
forecast-horizon-end-time Generate a forecast starting with last sample of the loaded series and until the specified date in the future.
Example: forecast-horizon-end-time = 2019-02-10T00:00:00Z
forecast-horizon-start-time Generate a forecast for the specified interval into the future starting with specified date instead of the last sample of the loaded series.
Example: forecast-horizon-start-time = 2019-02-10T00:00:00Z
forecast-score-interval Interval for scoring the produced forecasts ending with the last sample of the input series.
The interval is specified as the number of time units.
Format: count time_unit.
For SSA, the default value is the minimum of forecast-horizon-interval and 1/3 of the loaded series duration.
For ARIMA and Holt-Winters the default value is 1/4 of the loaded series duration.
Example: forecast-score-interval = 1 day

The settings forecast-horizon-interval, forecast-horizon-length, and forecast-horizon-end-time are mutually exclusive. See also Forecasting transformation in REST API.

ARIMA Forecasting Settings
Name Description
forecast-arima-auto Generate an ARIMA forecast using optimal settings.
If true, ARIMA parameters p and d are selected automatically based on scoring.
If set to false, parameters p, d are required.
Example: forecast-arima-auto = true
forecast-arima-p Auto-regression parameter p.
Example: forecast-arima-p = 10
forecast-arima-auto-regression-interval Alternative parameter for p where p is calculated as auto-regression-interval / interval.
Specified as the number of time units.
Format: count time_unit.
Example: forecast-arima-auto-regression-interval = 1 day
forecast-arima-d Integration parameter d, a number of 0 or 1.
Example: forecast-arima-d = 0
Holt-Winters Forecasting Settings
Name Description
forecast-hw-auto Generate a Holt-Winters forecast using optimal settings.
If true Holt-Winters parameters alpha, beta, gamma are selected automatically based on scoring.
If set to false, parameters alpha, beta, gamma are required.
Example: forecast-hw-auto = true
forecast-hw-alpha Holt-Winters alpha (data) parameter.
Possible values: [0, 1].
forecast-hw-beta Holt-Winters beta (trend) parameter.
Possible values: [0, 1].
forecast-hw-gamma Holt-Winters gamma (seasonality) parameter.
Possible values: [0, 1].
forecast-hw-period Series period (seasonality) parameter.
The interval is specified as the number of time units.
Format: count time_unit.
Example: forecast-hw-period = 1 hour
SSA Forecasting Settings
Name Description
forecast-ssa Generate an SSA (singular spectrum analysis) forecast.
Example: forecast-ssa = true
forecast-ssa-decompose-eigentriple-limit Maximum number of eigenvectors extracted from the trajectory matrix during the singular value decomposition (SVD).
Possible values: between 0 and 500.
If set to 0, the count is determined automatically.
Example: forecast-decompose-eigentriple-limit = 50
forecast-ssa-decompose-method The algorithm applied in singular value decomposition (SVD) of the trajectory matrix to extract eigenvectors.
Possible values: FULL, TRUNCATED, AUTO.
Example: forecast-ssa-decompose-method = TRUNCATED
forecast-ssa-decompose-window-length Height (row count) of the trajectory matrix, specified as the % of the sample count in the input series.
Possible values: (0, 50].
Default value: 50.
Example: forecast-ssa-decompose-window-length = 50
forecast-ssa-decompose-singular-value-threshold Threshold, specified in percent, to discard small eigenvectors. Eigenvector with eigenvalue λ is discarded if √λ is less than the specified % of √ sum of all eigenvalues.
Discard if √λ ÷ √ (∑ λi) < threshold ÷ 100
If threshold is 0, no vectors are discarded.
Possible values: [0, 100).
Example: forecast-ssa-decompose-singular-value-threshold = 5
forecast-ssa-group-auto-count Maximum number of eigenvector groups. The eigenvectors are placed into groups by the clustering method in Auto mode, or using by enumerating eigenvector indexes in Manual mode. The groups are sorted by maximum eigenvalue in descending order and are named with letters A, B, C etc.
If set to 0, only one group is returned.
Example: forecast-ssa-group-auto-count = 5
forecast-ssa-group-auto-stack Build groups recursively, starting with the group A with maximum eigenvalue, to view the cumulative effect of added eigenvectors. In enabled, group A contains its own eigenvectors. Group B contains its own eigenvectors as well as eigenvectors from group A. Group C includes its own eigenvectors as well as eigenvectors from group A and B, etc.
Example: forecast-ssa-group-auto-stack = true
forecast-ssa-group-auto-clustering-method Algorithm used to place eigenvectors into groups.
Possible values: HIERARCHICAL, XMEANS, NOVOSIBIRSK.
Default value: HIERARCHICAL.
Example: forecast-ssa-group-auto-clustering-method = HIERARCHICAL
forecast-ssa-group-auto-clustering-params Dictionary (map) of parameters required by the given clustering method.
Example: forecast-ssa-group-auto-clustering-params = { "v": 0.8, "c": 0.8 }
forecast-ssa-group-auto-union Join eigenvectors from automatically created groups into custom groups. Multiple custom groups are separated using comma. Groups within the custom group are enumerated using semi-colon as a separator or hyphen for range. For example, custom group A;B;D contains eigenvectors from automatic groups A, B and D. Custom group A;C-E contains eigenvectors from automatic groups A,C,D,E.
Example: forecast-ssa-group-auto-union = A;C-E , B;F- (two groups)
forecast-ssa-group-manual-groups Join eigenvectors using their index into custom groups. Multiple custom groups are separated using comma. Eigenvectors within the same group are enumerated using semi-colon as a separator or hyphen for range. For example, custom group 1;3-6 contains eigenvectors with indexes 1, 3, 4, 5 and 6.
Example: forecast-ssa-group-manual-groups = 1;3-6 , 2;7-
forecast-ssa-reconstruct-averaging-function Averaging function to calculate anti-diagonal elements of the reconstructed matrix.
Possible values: AVG, MEDIAN.
Default value: AVG
Example: forecast-ssa-reconstruct-averaging-function = AVG
forecast-ssa-reconstruct-fourier Use Fourier transform in the reconstruction stage and in SVD (singular value decomposition).
Default value: true.
Example: forecast-ssa-reconstruct-fourier = true
forecast-ssa-forecast-method Forecast calculation method.
Possible values: RECURRENT, VECTOR.
Default value: RECURRENT.
Example: forecast-ssa-forecast-method = RECURRENT
forecast-ssa-forecast-base Input series to which the recurrent formula is applied when calculating the forecast.
Possible values: RECONSTRUCTED, ORIGINAL.
Example: forecast-ssa-forecast-base = RECONSTRUCTED

Derived Value Settings

Specify value setting to create calculated series derived from raw series using arithmetic expressions in JavaScript syntax.

The expression must return a number or null. Samples with null values are hidden.

Name Description
alias Unique series name to pass data to other series.
Example: alias = s1
value Formula to calculate derived values at each timestamp of the other series identified by alias.
The formula can include value functions.
Example: value = max('s1') - 10
replace-value Formula to replace values in the current series.
Supported fields: value, time, previousValue, previousTime.
Unlike value setting, creating and referring to another series is not required.
Example: replace-value = Math.log(value)

fill-value Interpolate a missing value for the given timestamp when merging multiple series with different timestamps using specified interpolation type.
Possible values: NONE, PREVIOUS, LINEAR.
Default value: LINEAR.Example: fill-value = PREVIOUS