Source code for GUI.GUI_functions

import json
import os
import pandas
import streamlit

import plotly.express as px




def import_GUI_input_values_json() -> dict:
    """
        Function to import GUI settings from an existing json file and
        save it as a dict.

        :param json_file_path: file name to the underlying json with \
            input values for all GUI pages
        :type json_file_path: str

        :return: **GUI_settings_cache_dict_reload** (dict) - exported \
            dict from json file including a (sub)dict for every GUI page
    """
    # Import json file including several (sub)dicts for every GUI page
    # Each (sub)dict includes input values as a cache from the last session
    json_file_path = os.path.dirname(os.path.abspath(__file__)) + "/cache.json"
    with open(json_file_path, "r", encoding="utf-8") as infile:
        GUI_settings_cache_dict_reload = json.load(infile)
    for row in GUI_settings_cache_dict_reload:
        if GUI_settings_cache_dict_reload[row] == "None":
            GUI_settings_cache_dict_reload[row] = None
    return GUI_settings_cache_dict_reload





def short_result_interactive_dia(result_path_results: str,
                                 session_state_name: str,
                                 title: str) -> None:
    """
        Function to create interactive results.

        :param result_path_results: path to a result results.csv file
        :type result_path_results: str
        :param session_state_name: string of the streamlit session \
            state in which the interactive results diagram whill be \
            stored
        :type session_state_name: str
        :param title: title of the diagram created within this method
        :type title: str
    """
    # Header
    streamlit.subheader(title)
    # loading result.csv as a dataframe
    result_df = pandas.read_csv(result_path_results)
    # creating column headers to select
    column_headers_result = list(result_df.columns.values)
    # column headers without date
    list_headers = column_headers_result[1:]
    # selecting headers
    select_headers = streamlit.multiselect("Select a bus:", list_headers)
    # filtered dataframe
    filtered_df = result_df[select_headers]
    # plotting
    fig = px.line(filtered_df).update_layout(
        xaxis_title="timestep (hour)",
        yaxis_title="voltage (V) / current (A)")
    streamlit.session_state[session_state_name] = fig