--- tags: - gradio-custom-component - Plot - med - medicine - bio - biology - chem - chemistry - MSA - multiple sequence alignment - seqlogo - annotation - consensus histogram - visualize title: gradio_msaplot short_description: MSAplot is customizable panels for plotting MSA. colorFrom: blue colorTo: yellow sdk: gradio pinned: false app_file: space.py --- # `gradio_msaplot`

MSAplot is customizable panels for plotting MSA, seqlogo, annotation, and consensus histograms. ## Installation ```bash pip install gradio_msaplot ``` ## Usage ```python import gradio as gr from gradio_msaplot import MSAPlot, MSAPlotData import matplotlib matplotlib.use('Agg') example = MSAPlot().example_value() with gr.Blocks() as demo: with gr.Row(): MSAPlot(label="Blank"), # blank component MSAPlot(value=example, label="Populated"), # populated component if __name__ == "__main__": demo.launch() ``` ## `MSAPlot` ### Initialization

name	type	default	description
`value`	```python typing.Any \| None ```	`None`	None
`label`	```python str \| None ```	`None`	None
`every`	```python float \| None ```	`None`	None
`show_label`	```python bool \| None ```	`None`	None
`container`	```python bool ```	`True`	None
`scale`	```python int \| None ```	`None`	None
`min_width`	```python int ```	`160`	None
`visible`	```python bool ```	`True`	None
`elem_id`	```python str \| None ```	`None`	None
`elem_classes`	```python list[str] \| str \| None ```	`None`	None
`render`	```python bool ```	`True`	None
`key`	```python int \| str \| None ```	`None`	None

### Events | name | description | |:-----|:------------| | `change` | Triggered when the value of the MSAPlot changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input. | | `clear` | Triggered when the plot is cleared. | ### User function The impact on the users predict function varies depending on whether the component is used as an input or output for an event (or both). - When used as an Input, the component only impacts the input signature of the user function. - When used as an output, the component only impacts the return signature of the user function. The code snippet below is accurate in cases where the component is used as both an input and an output. - **As output:** Is passed, the preprocessed input data sent to the user's function in the backend. - **As input:** Should return, the output data received by the component from the user's function in the backend. ```python def predict( value: MSAPlotData | None ) -> MSAPlotData: return value ``` ## `MSAPlotData` ### Initialization

name	type	default	description
`data`	```python typing.Any ```	`None`	None