{"version":"1.0","type":"rich","title":"Gist ae727f5f05cbc1b03932","description":"This example demonstrates how to construct and execute a simple Nipype workflow using the pipeline engine. It defines a Python function node that passes inputs through unchanged, connects it to an identity node with iterable parameters, and runs the workflow serially. The visualization shows the workflow's execution log, tracking how multiple parameter combinations (input1 values 1–7 and input2 values 5–9) trigger separate function node runs in distinct output directories. The code uses Nipype's `pe.Workflow`, `pe.Node`, `Function`, and `IdentityInterface` APIs to manage the dataflow.","provider_name":"VizHub AI Studio","provider_url":"https://next.vizhub.com","html":"<iframe src=\"https://next.vizhub.com/viz/gist-ae727f5f05cbc1b03932?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"1\"></iframe>","width":960,"height":500,"cache_age":3600}