--- 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` Static Badge Static Badge Static Badge 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