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import streamlit as st
import pandas as pd
from os import path
import sys
import streamlit.components.v1 as components
sys.path.append('code/')
#sys.path.append('ASCARIS/code/')
import pdb_featureVector
import alphafold_featureVector
import argparse
from st_aggrid import AgGrid, GridOptionsBuilder, JsCode,GridUpdateMode
showWarningOnDirectExecution = False
def download_button(object_to_download, download_filename):
if isinstance(object_to_download, pd.DataFrame):
object_to_download = object_to_download.to_csv(index=False)
# Try JSON encode for everything else
else:
object_to_download = json.dumps(object_to_download)
try:
# some strings <-> bytes conversions necessary here
b64 = base64.b64encode(object_to_download.encode()).decode()
except AttributeError as e:
b64 = base64.b64encode(object_to_download).decode()
dl_link = f"""<html><head><title>Start Auto Download file</title><script src="http://code.jquery.com/jquery-3.2.1.min.js"></script><script>$('<a href="data:text/csv;base64,{b64}" download="{download_filename}">')[0].click()</script></head></html>"""
return dl_link
def download_df():
components.html(
download_button(selected_df, st.session_state.filename),
height=0,
)
original_title = '<p style="font-family:Trebuchet MS; color:#FD7456; font-size: 35px; font-weight:bold; text-align:center">Welcome to ASCARIS</p>'
st.markdown(original_title, unsafe_allow_html=True)
st.write('')
st.write('')
st.write('')
st.write('')
source = st.selectbox('Select Protein Structure Database (1: PDB, SwissModel, Modbase 2: AlphaFold)',[1,2])
impute = st.selectbox('Select Imputation',[True, False])
input_data = st.text_input('Enter Input Variation')
#sys.path.append(path.abspath('../code/'))
parser = argparse.ArgumentParser(description='ASCARIS')
parser.add_argument('-s', '--source_option',
help='Selection of input structure data.\n 1: PDB Structures (default), 2: AlphaFold Structures',
default=1)
parser.add_argument('-i', '--input_datapoint',
help='Input file or query datapoint\n Option 1: Comma-separated list of idenfiers (UniProt ID-wt residue-position-mutated residue (e.g. Q9Y4W6-N-432-T or Q9Y4W6-N-432-T, Q9Y4W6-N-432-T)) \n Option 2: Enter comma-separated file path')
parser.add_argument('-impute', '--imputation_state', default='True',
help='Whether resulting feature vector should be imputed or not. Default True.')
args = parser.parse_args()
input_set = input_data
mode = source
impute = impute
print('*****************************************')
print('Feature vector generation is in progress. \nPlease check log file for updates..')
print('*****************************************')
mode = int(mode)
with st.spinner('In progress...This may take a while...'):
try:
if mode == 1:
selected_df = pdb_featureVector.pdb(input_set, mode, impute)
int_builder = GridOptionsBuilder.from_dataframe(selected_df)
int_builder.configure_default_column(editable=False, filterable=True, cellStyle={'text-align': 'center'})
int_builder.configure_pagination(enabled=True, paginationAutoPageSize=False, paginationPageSize=10)
int_builder.configure_selection(selection_mode='multiple', use_checkbox=True)
gridoptions = int_builder.build()
int_return = AgGrid(selected_df,
width='100%',
height=(len(selected_df) + 4) * 35.2 + 3,
theme='light',
enable_enterprise_modules=False,
gridOptions=gridoptions,
fit_columns_on_grid_load=False,
update_mode=GridUpdateMode.SELECTION_CHANGED, # or MODEL_CHANGED
custom_css={".ag-header-cell-label": {"justify-content": "center"}})
st.success('Feature vector successfully created.')
elif mode == 2:
selected_df = alphafold_featureVector.alphafold(input_set, mode, impute)
int_builder = GridOptionsBuilder.from_dataframe(selected_df)
int_builder.configure_default_column(editable=False, filterable=True, cellStyle={'text-align': 'center'})
int_builder.configure_pagination(enabled=True, paginationAutoPageSize=False, paginationPageSize=10)
int_builder.configure_selection(selection_mode='multiple', use_checkbox=True)
gridoptions = int_builder.build()
int_return = AgGrid(selected_df,
width='100%',
height=(len(selected_df) + 4) * 35.2 + 3,
theme='light',
enable_enterprise_modules=False,
gridOptions=gridoptions,
fit_columns_on_grid_load=False,
update_mode=GridUpdateMode.SELECTION_CHANGED, # or MODEL_CHANGED
custom_css={".ag-header-cell-label": {"justify-content": "center"}})
st.success('Feature vector successfully created.')
except:
pass
download_df = pd.DataFrame()
with st.form("my_form", clear_on_submit=False):
st.text_input("Enter filename", key="filename")
submit = st.form_submit_button("Download feature vector", on_click=download_df)
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