timeflux_example.nodes.arithmetic
Simple example nodes
arithmetic
- class timeflux_example.nodes.arithmetic.Add(value)[source]
Bases:
timeflux.core.node.Node
Adds
value
to each cell of the input.This is one of the simplest possible nodes.
- Variables
i (Port) – Default input, expects DataFrame.
o (Port) – Default output, provides DataFrame.
Example
graphs: - nodes: - id: node_1 module: timeflux.nodes.random class: Random params: columns: 5 rows_min: 1 rows_max: 10 value_min: 0 value_max: 5 seed: 1 - id: node_2 module: timeflux_example.nodes.arithmetic class: Add params: value: 1 - id: node_3 module: timeflux.nodes.debug class: Display edges: - source: node_1 target: node_2 - source: node_2 target: node_3
- Parameters
value (int) – The value to add to each cell.
- class timeflux_example.nodes.arithmetic.MatrixAdd[source]
Bases:
timeflux.core.node.Node
Sum two input matrices together.
This node illustrates multiple named inputs. Note that it is not necessary to declare the ports. They will be created dynamically.
- Variables
i_m1 (Port) – First matrix, expects DataFrame.
i_m2 (Port) – Second matrix, expects DataFrame.
o (Port) – Default output, provides DataFrame.
Example
graphs: - id: multi nodes: - id: matrix_1 module: timeflux.nodes.random class: Random params: columns: 2 rows_min: 2 rows_max: 2 value_min: 1 value_max: 1 seed: 1 - id: matrix_2 module: timeflux.nodes.random class: Random params: columns: 2 rows_min: 2 rows_max: 2 value_min: 2 value_max: 2 seed: 1 - id: matrix_add module: timeflux_example.nodes.arithmetic class: MatrixAdd - id: display_matrix_1 module: timeflux.nodes.debug class: Display - id: display_matrix_2 module: timeflux.nodes.debug class: Display - id: display_matrix_add module: timeflux.nodes.debug class: Display edges: - source: matrix_1 target: matrix_add:m1 - source: matrix_2 target: matrix_add:m2 - source: matrix_1 target: display_matrix_1 - source: matrix_2 target: display_matrix_2 - source: matrix_add target: display_matrix_add rate: 0.1
Instantiate the node.
- class timeflux_example.nodes.arithmetic.MatrixDivide[source]
Bases:
timeflux.core.node.Node
Divide one matrix by another.
- Variables
i_m1 (Port) – First matrix, expects DataFrame.
i_m2 (Port) – Second matrix, expects DataFrame.
o (Port) – Default output, provides DataFrame.
Instantiate the node.