example_2.py

import os
import streamlit as st
import pandas as pd
import common


__author__ = 'Aleksandar Anžel'
__copyright__ = ''
__credits__ = ['Aleksandar Anžel', 'Georges Hattab']
__license__ = 'GNU General Public License v3.0'
__version__ = '1.0'
__maintainer__ = 'Aleksandar Anžel'
__email__ = 'aleksandar.anzel@uni-marburg.de'
__status__ = 'Dev'


CALCULATED_DATA_SET_NAME = 'calculated.pkl'
path_example_2_root_data = os.path.join('..', 'Data', 'cached', 'example_2')
path_example_2_transcriptomics = os.path.join(path_example_2_root_data,
                                              'transcriptomics')
path_example_2_transcriptomics_control_1 = os.path.join(
    path_example_2_transcriptomics, 'CONTROL_1.csv')
path_example_2_transcriptomics_control_2 = os.path.join(
    path_example_2_transcriptomics, 'CONTROL_2.csv')
path_example_2_transcriptomics_control_3 = os.path.join(
    path_example_2_transcriptomics, 'CONTROL_3.csv')

path_example_2_transcriptomics_benz_1 = os.path.join(
    path_example_2_transcriptomics, 'BENZ_1.csv')
path_example_2_transcriptomics_benz_2 = os.path.join(
    path_example_2_transcriptomics, 'BENZ_2.csv')
path_example_2_transcriptomics_benz_3 = os.path.join(
    path_example_2_transcriptomics, 'BENZ_3.csv')

path_example_2_transcriptomics_phe_1 = os.path.join(
    path_example_2_transcriptomics, 'PHE_1.csv')
path_example_2_transcriptomics_phe_2 = os.path.join(
    path_example_2_transcriptomics, 'PHE_1.csv')
path_example_2_transcriptomics_phe_3 = os.path.join(
    path_example_2_transcriptomics, 'PHE_3.csv')

path_example_2_transcriptomics_pov_1 = os.path.join(
    path_example_2_transcriptomics, 'POV_1.csv')
path_example_2_transcriptomics_pov_2 = os.path.join(
    path_example_2_transcriptomics, 'POV_2.csv')
path_example_2_transcriptomics_pov_3 = os.path.join(
    path_example_2_transcriptomics, 'POV_3.csv')

path_example_2_transcriptomics_final = os.path.join(
    path_example_2_transcriptomics, 'Final_compressed.csv')
path_example_2_transcriptomics_prec_1 = os.path.join(
    path_example_2_transcriptomics, CALCULATED_DATA_SET_NAME)

path_example_2_viz = os.path.join(
    path_example_2_root_data, 'visualizations')


def upload_multiple(key_suffix):
    available_data_set_types = {
        'Transcriptomics': {
            'Processed data set 1': 'CALC'}
    }

    selected_data_set_type = st.selectbox(
        'What kind of data set do you want to see?',
        list(available_data_set_types[key_suffix].keys()),
        key='Example_2_' + key_suffix)

    if key_suffix == 'Transcriptomics':
        return_path = path_example_2_transcriptomics_prec_1

    else:
        pass

    return (return_path,
            available_data_set_types[key_suffix][selected_data_set_type])


def upload_intro(folder_path, key_suffix):
    st.header(key_suffix + ' data')
    st.markdown('')

    return_path = None
    return_path, data_set_type = upload_multiple(key_suffix)

    if return_path is None:
        st.warning('Upload your data set')

    # We return DataFrame if we work with tabular data format or precalculated
    # We return folder_path if we work with archived data
    # Data_set_type is always returned
    if data_set_type == 'CALC':
        return_path_or_df = common.get_cached_dataframe(return_path)
    else:
        return_path_or_df = return_path

    return return_path_or_df, data_set_type


def example_2_transcriptomics():
    key_suffix = 'Transcriptomics'
    cache_folder_path = path_example_2_transcriptomics

    folder_path_or_df, data_set_type = upload_intro(
        cache_folder_path, key_suffix)

    return common.work_with_csv(
        folder_path_or_df, cache_folder_path, key_suffix)


def create_main_example_2():

    col_1, col_2 = st.columns([1, 2])

    col_1.info('''
            This data set comes from the following paper:
            **Merchel Piovesan Pereira, B., Wang, X., & Tagkopoulos, I. (2020).
            Short- and Long-Term Transcriptomic Responses of Escherichia coli
            to Biocides: a Systems Analysis. Applied and environmental
            microbiology, 86(14), e00708-20.
            https://doi.org/10.1128/AEM.00708-20**. Analyzed samples
            were processed in DNA Technologies Core, Genome and Biomedical
            Sciences Facility (GBSF) (38.535244, -121.764920).
            A precise location is shown on the map located on the right.

            It contains **transcriptomics** data.
            ''')

    col_2.map(pd.DataFrame({'lat': [38.53524478359195],
                            'lon': [-121.76492092285179]}),
              zoom=8, use_container_width=True)

    example_2_omics_list = ['Transcriptomics']
    choose_omics = st.multiselect(
        'What kind of omic data do you want to explore?', example_2_omics_list)

    charts = []  # An empty list to hold all pairs (visualizations, key)

    for i in choose_omics:
        if i == 'Transcriptomics':
            charts += example_2_transcriptomics()
        else:
            pass

    st.markdown('---')

    for i in charts:
        type_of_chart = type(i[0])

        with st.spinner('Visualizing...'):
            if 'altair' in str(type_of_chart):
                st.altair_chart(i[0], use_container_width=True)
                common.save_chart(i[0], path_example_2_viz, i[1])
            else:
                pass

    return None