app.py

import gradio as gr
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

from constants import *


from mpl_data_plotter import MatplotlibDataPlotter

def convert_int64_to_int32(df):
    for col in df.columns:
        if df[col].dtype == 'int64':
            print(col)
            df[col] = df[col].astype('int32')
    return df

print(f"Loading domains data...")
single_df = pd.read_csv(SINGLE_DOMAINS_FILE, compression='gzip')
single_df['biosyn_class_index'] = single_df.bgc_class.apply(lambda x: BIOSYN_CLASS_NAMES.index(x))
single_df = convert_int64_to_int32(single_df)

pair_df = pd.read_csv(PAIR_DOMAINS_FILE, compression='gzip')
pair_df['biosyn_class_index'] = pair_df.bgc_class.apply(lambda x: BIOSYN_CLASS_NAMES.index(x))
pair_df = convert_int64_to_int32(pair_df)

num_domains_in_region_df = single_df.groupby('cds_region_id', as_index=False).agg({'as_domain_id': 'count'}).rename(
    columns={'as_domain_id': 'num_domains'})

unique_domain_lengths = num_domains_in_region_df.num_domains.unique()

print(f"Initializing data plotter...")
data_plotter = MatplotlibDataPlotter(single_df, pair_df, num_domains_in_region_df)


def update_all_plots(frequency, split_name):
    return data_plotter.plot_single_domains(frequency, split_name), data_plotter.plot_pair_domains(frequency, split_name)


print(f"Defining blocks...")
# Create Gradio interface
with gr.Blocks(title="BGC Keyword Plotter") as demo:
    gr.Markdown("## BGC Keyword Plotter")
    gr.Markdown("Select the model name and minimal number of domains in Antismash-db subset.")
    
    with gr.Row():
        frequency_slider = gr.Slider(
            minimum=int(unique_domain_lengths.min()), 
            maximum=int(unique_domain_lengths.max()), 
            step=1, 
            value=int(unique_domain_lengths.min()), 
            label="Min number of domains"
        )
    
    with gr.Row():
        with gr.Column():
            split_selector = gr.Dropdown(
                choices=["stratified"] + BIOSYN_CLASS_NAMES,
                value="stratified",
                label="Split name"
            )
        with gr.Column():
            single_domains_plot = gr.Plot(
                label="Single domains",
                container=True, 
                elem_id="single_domains_plot"
            )
        # gr.HTML("""
        # <style>
        #     #single_domains_plot {
        #         height: 100% !important;
        #         width: 100% !important;
        #     }
        # </style>
        # """)
        with gr.Column():
            pair_domains_plot = gr.Plot(label="Pair domains")
        # with gr.Column():
        #     combined_plot = gr.Plot(label="Combined Wave")
    
    frequency_slider.release(
        fn=update_all_plots,
        inputs=[frequency_slider, split_selector],
        outputs=[single_domains_plot, pair_domains_plot]#, cosine_plot]
    )


print(f"Launching!...")
demo.launch()
# demo.load(filter_map, [min_price, max_price, boroughs], map)