Fix some issues for MacOS and improve some features

streamlit/streamlit_app.py

@@ -1,32 +1,28 @@
-import mols2grid
-from rdkit import Chem
-from rdkit import DataStructs
-import prolif as plf
-import MDAnalysis as mda
-import numpy as np
-import streamlit as st
+import os
 import tempfile
-import streamlit.components.v1 as components
-from moldrug import utils
-from meeko import RDKitMolCreate, PDBQTMolecule
+import time
+import urllib.parse
 from io import StringIO
-import seaborn as sns
+
 import matplotlib.pyplot as plt
+import MDAnalysis as mda
+import mols2grid
+import numpy as np
 import pandas as pd
-from stmol import showmol
-import os
+import prolif as plf
 import pubchempy as pcp
 import requests
-import urllib.parse
+import seaborn as sns
 from bs4 import BeautifulSoup
-import time
+from meeko import PDBQTMolecule, RDKitMolCreate
+from pandas.api.types import (is_categorical_dtype, is_datetime64_any_dtype,
+                              is_numeric_dtype, is_object_dtype)
+from rdkit import Chem, DataStructs
+from stmol import showmol
 
-from pandas.api.types import (
-    is_categorical_dtype,
-    is_datetime64_any_dtype,
-    is_numeric_dtype,
-    is_object_dtype,
-)
+import streamlit as st
+import streamlit.components.v1 as components
+from moldrug import utils
 
 # TODO
 # add SyGma for metabolic prediction
@@ -146,11 +142,14 @@ def filter_dataframe(df: pd.DataFrame) -> pd.DataFrame:
 def convert(number):
     if isinstance(number, np.floating):
         return float(number)
-    if isinstance(number, np.integer):
+    elif isinstance(number, np.integer):
         return int(number)
+    # It is not possible to convert, this fix some issue on MacOS
+    else:
+        return number
 
 
-def plot_dist(individuals: list[utils.Individual], properties: list[str], every_gen: int = 1):
+def plot_dist(individuals: list[utils.Individual], properties: list[str], every_gen: int = 1, figsize=(25, 25)):
     """Create the violin plot for the MolDrug run
 
     Parameters
@@ -161,15 +160,21 @@ def plot_dist(individuals: list[utils.Individual], properties: list[str], every_
         A list of the properties to be graph (must be attributes of the provided individuals)
     every_gen : int, optional
         Frequency to plot the distribution: every how many generations, by default 1
+    fig_size : tuple(int), optional
+        The size of the graph, by default (25, 25)
 
     Returns
     -------
     tuple
         fig, axes
     """
     # Set up the matplotlib figure
+    if len(properties) <= 1:
+        extra_plot_kwargs = dict(sharex=True, gridspec_kw={'hspace': 0.05})
+    else:
+        extra_plot_kwargs = dict()
     sns.set_theme(style="whitegrid")
-    fig, axes = plt.subplots(nrows=len(properties), figsize=(25, 25))
+    fig, axes = plt.subplots(nrows=len(properties), figsize=figsize, **extra_plot_kwargs)
 
     SawIndividuals = utils.to_dataframe(individuals).drop(['pdbqt'], axis=1).replace([np.inf, -np.inf], np.nan).dropna()
     SawIndividuals = SawIndividuals[SawIndividuals['kept_gens'].map(len) != 0].reset_index(drop=True)
@@ -186,15 +191,19 @@ def plot_dist(individuals: list[utils.Individual], properties: list[str], every_
     # Draw a violinplot with a narrow bandwidth than the default
     pops = pops.loc[pops['genID'].isin([gen for gen in range(0, NumGens + every_gen, every_gen)])]
 
-    if len(properties) <= 1:
-        sns.violinplot(hue='genID', y=properties[0], data=pops, palette="Set3", bw_adjust=.2, cut=0, linewidth=1, ax=axes, legend=False)
-    else:
-        for i, prop in enumerate(properties):
+    for i, prop in enumerate(properties):
+        if len(properties) <= 1:
+            sns.violinplot(hue='genID', x='genID', y=prop, data=pops, palette="Set3", bw_adjust=.2, cut=0, linewidth=1, ax=axes, legend=False)
+        else:
             sns.violinplot(hue='genID', x='genID', y=prop, data=pops, palette="Set3", bw_adjust=.2, cut=0, linewidth=1, ax=axes[i], legend=False)
 
+            # Remove x-axis labels and ticks from all but the bottom subplot
+            if i < len(properties) - 1:
+                axes[i].xaxis.set_visible(False)
     return fig, axes
 
 
+
 @st.cache_data
 def ProtPdbBlockToProlifMol(protein_pdb_string):
     with tempfile.NamedTemporaryFile(prefix='.pro', suffix='.pdb', mode='w+') as tmp:
@@ -611,6 +620,7 @@ def get_pubchem_dataframe(df: pd.DataFrame) -> pd.DataFrame:
                 st.info('Nothing to show')
 
         with tab3:
+            st.info('🧪This feautre is still experimental. Sometimes the query just fail 🫤')
             PubChemCheck = st.checkbox("Explore PubChem")
             download_button = st.empty()
             if PubChemCheck:
@@ -688,8 +698,13 @@ def get_pubchem_dataframe(df: pd.DataFrame) -> pd.DataFrame:
         with tab2:
             try:
                 every_gen = st.number_input("Every how many generations:", min_value=1, max_value=moldrug_result.NumGens, value=10)
+                col1, col2 = st.columns(2)
+
+                # Add widgets to each column
+                fig_size_x = col1.number_input("Size of the figure in x:", value=10)
+                fig_size_y = col2.number_input("Size of the figure in y:", value=10)
                 properties_to_plot = [prop for prop in properties if prop not in ['genID']]
-                fig, axes = plot_dist(moldrug_result.SawIndividuals, properties=properties_to_plot, every_gen=every_gen)
+                fig, axes = plot_dist(moldrug_result.SawIndividuals, properties=properties_to_plot, every_gen=every_gen, figsize=(fig_size_x, fig_size_y))
                 st.pyplot(fig)
             except Exception:
                 if is_GA: