reorganize code

app.py

@@ -9,7 +9,7 @@ from constants import *
 from mpl_data_plotter import MatplotlibDataPlotter
 
 
-
+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))
 
@@ -21,7 +21,7 @@ num_domains_in_region_df = single_df.groupby('cds_region_id', as_index=False).ag
 
 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)
 
 
@@ -29,6 +29,7 @@ def update_all_plots(frequency, split_name='stratified'):
     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="Interactive Wave Plotter") as demo:
     gr.Markdown("## Interactive Wave Plotter")
@@ -69,5 +70,7 @@ with gr.Blocks(title="Interactive Wave Plotter") as demo:
         outputs=[single_domains_plot, pair_domains_plot]#, cosine_plot]
     )
 
+
+print(f"Launching!...")
 demo.launch()
 # demo.load(filter_map, [min_price, max_price, boroughs], map)

constants.py

@@ -1,4 +1,6 @@
 
+POSTER_BLUE = '#01589C'
+
 BIOSYN_CLASS_NAMES = ['Alkaloid', 'NRP', 'Polyketide', 'RiPP', 'Saccharide', 'Terpene', "Other"]
 
 SINGLE_DOMAINS_FILE = 'data/single_domains.csv.gz'

mpl_data_plotter.py

@@ -1,5 +1,6 @@
 
 import matplotlib.pyplot as plt
+
 import plot_utils
 from constants import *
 

plot_utils.py

@@ -2,8 +2,7 @@ import numpy as np
 import matplotlib.pyplot as plt
 import seaborn as sns
 
-
-POSTER_BLUE = '#01589C'
+from constants import *
 
 
 def groupby(array_like, hue_order=None):