Moving Aggregator

This node calculates aggregation values for a moving window. The aggregation values are displayed in new columns appended at the end of the table.

The columns to aggregate can be either defined by selecting the columns directly, by name based on a search pattern or based on the data type. Input columns are handled in this order and only considered once e.g. columns that are added directly on the "Manual Aggregation" tab are ignored even if their name matches a search pattern on the "Pattern Based Aggregation" tab or their type matches a defined type on the "Type Based Aggregation" tab. The same holds for columns that are added based on a search pattern. They are ignored even if they match a criterion that has been defined in the "Type Based Aggregation" tab.

The "Manual Aggregation" tab allows you to change the aggregation method of more than one column. In order to do so select the columns to change, open the context menu with a right mouse click and select the aggregation method to use.

In the "Pattern Based Aggregation" tab you can assign aggregation methods to columns based on a search pattern. The pattern can be either a string with wildcards or a regular expression. Columns where the name matches the pattern but where the data type is not compatible with the selected aggregation method are ignored. Only columns that have not been selected as aggregation column on the "Manual Aggregation" tab are considered.

The "Type Based Aggregation" tab allows to select an aggregation method for all columns of a certain data type e.g. to compute the mean for all decimal columns (DoubleCell). Only columns that have not been handled by the other tabs e.g. column based and pattern based are considered. The data type list to choose from contains basic types e.g String, Double, etc. and all data types the current input table contains.

A detailed description of the available aggregation methods can be found on the 'Description' tab in the node dialog.

Options

General settings

Window type

Forward: Looks window length rows forward from the current point.
Central: Looks half the window length backward from the current point and half forward.
Backward: Looks window length rows back from the current point.

Window length

The number of samples to include in the moving window. Minimum value: 2 samples. Maximum Value: Time Series length.

Resolve missing values for incomplete windows

If selected the aggregation values of incomplete windows, are computed based on the data rows available so far.

Cumulative computation

Select this option to compute cumulative values e.g. cumulative sum over the whole table. Each result row is computed by aggregating the values from the first row to the current row.

Remove aggregation columns

If selected the columns used to aggregate are filtered from the output table.

Remove retained columns

If selected the columns that are not aggregate are filtered from the output table.

Manual Aggregation

Available columns: Select one or more column(s) for aggregation from the available columns list. Change the aggregation method in the Aggregation column of the table. You can add the same column multiple times. In order to change the aggregation method of more than one column select all columns to change, open the context menu with a right mouse click and select the aggregation method to use.
Missing: Missing values are considered during aggregation if the missing option is ticked for the corresponding row in the column aggregation table. Some aggregation methods do not support the changing of the missing option such as means.
Parameter: The parameter column shows an "Edit" button for all aggregation operators that require additional information. Clicking on the "Edit" button opens the parameter dialog which allows changing the operator specific settings.

Pattern Based Aggregation

Aggregation settings: Use the "Add" button to add a new row with a search pattern to the aggregation settings. The search pattern can either be a string with wildcards or a regular expression. Supported wildcards are * (matches any number of characters) and ? (matches one character) e.g. KNI* would match all strings that start with KNI such as KNIME whereas KNI? would match only strings that start with KNI followed by a fourth character. Double click the "Search pattern" cell to edit the pattern. The cell is colored in red if the pattern is invalid.
RegEx: Tick this option if the search pattern is a regular expression otherwise it is treated as string with wildcards ('*' and '?').
Missing: Missing values are considered during aggregation if the missing option is ticked for the corresponding row in the column aggregation table. Some aggregation methods do not support the changing of the missing option such as means.
Parameter: The parameter column shows an "Edit" button for all aggregation operators that require additional information. Clicking on the "Edit" button opens the parameter dialog which allows changing the operator specific settings.

Type Based Aggregation

Aggregation Settings

Select one or more data type from the available type list. Change the aggregation method in the Aggregation column of the table. You can add the same data type multiple times. The list contains standard types e.g. Double, String etc. and all types of the input table.

Missing

Missing values are considered during aggregation if the missing option is ticked for the corresponding row in the column aggregation table. Some aggregation methods do not support the changing of the missing option such as means.

Parameter

The parameter column shows an "Edit" button for all aggregation operators that require additional information. Clicking on the "Edit" button opens the parameter dialog which allows changing the operator specific settings.

Type matching

Strict: the type based aggregation method is only applied to columns of the selected type.
Include sub-types: the type based aggregation method is also applied to columns containing sub-types of the selected type. For example Boolean is a sub-type of Integer, Integer of Long, and Long of Double.

Aggregation settings

Maximum unique values per group

Defines the maximum number of unique values per group to avoid problems with memory overloading. All groups with more unique values are skipped during the calculation and a missing value is set in the corresponding column, and a warning is displayed.

Value delimiter

The value delimiter used by aggregation methods such as concatenate.

Column naming

The name of the resulting aggregation column(s) depends on the selected naming schema.

Keep original name(s): Keeps the original column names. Note that you can use all aggregation columns only once with this column naming option to prevent duplicate column names.
Aggregation method (column name): Uses the aggregation method first and appends the column name in brackets
Column name (aggregation method): Uses the column name first and appends the aggregation method in brackets

All aggregation methods get a * appended if the missing value option is not ticked in the aggregation settings in order to distinguish between columns that considered missing values in the aggregation process and columns that do not.

Input Ports

: Table containing time series.

Output Ports

: Table with columns holding aggregation values.

Popular Predecessors

Popular Successors

Views

This node has no views

Workflows

Developers

You want to see the source code for this node? Click the following button and we’ll use our super-powers to find it for you.

Installation

To use this node in KNIME, install the extension KNIME Timeseries nodes from the below update site following our NodePit Product and Node Installation Guide:

v5.3

A zipped version of the software site can be downloaded here.

Plugin provider: KNIME AG, Zurich, Switzerland

Plugin version: 5.3.0.v202312081535

On NodePit since: 2024-07-09

Last update: 2024-11-20

KNIME versions: Since v3.6

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!