"""This package provides a complete workflow to users how want to proced to NIRS analysis without particular knowledge.

This is a webapp with Streamlit.
GUI shows whatever is needed for Samples Selection based on NIRS spectra and then, to compute a model to predict
    chemical values on your samples.

Examples:
    streamlit run ./app.py
"""
#
from Packages import *
# from utils import read_dx, DxRead,  Plsr, LinearPCA, Umap, find_col_index, PinardPlsr, Nmf, AP
# from utils import LWPLSR, list_files, metrics, TpeIpls, reg_plot, resid_plot, Sk_Kmeans, DxRead, Hdbscan, read_dx, PlsProcess, PinardPlsr, Plsr
from utils.DATA_HANDLING import *
from utils.Miscellaneous import prediction, download_results, plot_spectra, local_css, desc_stats, hash_data, hist,data_split, pred_hist,background_img
from utils.Hash import create_hash, check_hash
from report import report
css_file = Path("style/")
pages_folder = Path("pages/")
from style import add_header, add_sidebar
# from style.header import add_header, add_sidebar
from config.config import pdflatex_path
local_css(css_file / "style.css")