app/event_handlers/calculate_practical_tasks.py

"""
File: calculate_practical_tasks.py
Author: Elena Ryumina and Dmitry Ryumin
Description: Event handler for Gradio app to calculate practical tasks.
License: MIT License
"""

from app.oceanai_init import b5
import gradio as gr
import pandas as pd
from pathlib import Path

# Importing necessary components for the Gradio app
from app.config import config_data
from app.components import html_message, dataframe, files_create_ui, video_create_ui


def read_csv_file(file_path, drop_id=False):
    df = pd.read_csv(file_path)

    if drop_id:
        df = pd.DataFrame(df.drop(["ID"], axis=1))

    df.index.name = "ID"
    df.index += 1
    df.index = df.index.map(str)

    return df


def apply_rounding_and_rename_columns(df):
    df_rounded = df.rename(
        columns={
            "Openness": "OPE",
            "Conscientiousness": "CON",
            "Extraversion": "EXT",
            "Agreeableness": "AGR",
            "Non-Neuroticism": "NNEU",
        }
    )
    columns_to_round = df_rounded.columns[1:]
    df_rounded[columns_to_round] = df_rounded[columns_to_round].apply(
        lambda x: [round(i, 3) for i in x]
    )
    return df_rounded


def colleague_type(subtask):
    return "minor" if "junior" in subtask.lower() else "major"


def event_handler_calculate_practical_task_blocks(
    files,
    practical_subtasks,
    pt_scores,
    threshold_professional_skills,
    dropdown_professional_skills,
    target_score_ope,
    target_score_con,
    target_score_ext,
    target_score_agr,
    target_score_nneu,
    equal_coefficient,
):
    if practical_subtasks.lower() == "professional skills":
        df_professional_skills = read_csv_file(config_data.Links_PROFESSIONAL_SKILLS)

        b5._priority_skill_calculation(
            df_files=pt_scores.iloc[:, 1:],
            correlation_coefficients=df_professional_skills,
            threshold=threshold_professional_skills,
            out=True,
        )

        # Optional
        df = apply_rounding_and_rename_columns(b5.df_files_priority_skill_)

        professional_skills_list = (
            config_data.Settings_DROPDOWN_PROFESSIONAL_SKILLS.copy()
        )

        professional_skills_list.remove(dropdown_professional_skills)

        professional_skills_list = [
            "OPE",
            "CON",
            "EXT",
            "AGR",
            "NNEU",
        ] + professional_skills_list

        df_hidden = df.drop(columns=professional_skills_list)

        df_hidden.to_csv(config_data.Filenames_PT_SKILLS_SCORES)

        df_hidden.reset_index(inplace=True)

        df_hidden = df_hidden.sort_values(
            by=[dropdown_professional_skills], ascending=False
        )

        person_id = int(df_hidden.iloc[0]["Person ID"]) - 1

        return (
            gr.Row(visible=True),
            gr.Column(visible=True),
            dataframe(
                headers=df_hidden.columns.tolist(),
                values=df_hidden.values.tolist(),
                visible=True,
            ),
            files_create_ui(
                config_data.Filenames_PT_SKILLS_SCORES,
                "single",
                [".csv"],
                config_data.OtherMessages_EXPORT_PS,
                True,
                False,
                True,
                "csv-container",
            ),
            video_create_ui(
                value=files[person_id],
                file_name=Path(files[person_id]).name,
                label="Best Person ID - " + str(person_id + 1),
                visible=True,
            ),
            html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
        )
    elif (
        practical_subtasks.lower() == "finding a suitable junior colleague"
        or practical_subtasks.lower() == "finding a suitable senior colleague"
    ):
        df_correlation_coefficients = read_csv_file(config_data.Links_FINDING_COLLEAGUE)

        b5._colleague_ranking(
            df_files=pt_scores.iloc[:, 1:],
            correlation_coefficients=df_correlation_coefficients,
            target_scores=[
                target_score_ope,
                target_score_con,
                target_score_ext,
                target_score_agr,
                target_score_nneu,
            ],
            colleague=colleague_type(practical_subtasks),
            equal_coefficients=equal_coefficient,
            out=False,
        )

        # Optional
        df = df = apply_rounding_and_rename_columns(b5.df_files_colleague_)

        professional_skills_list = [
            "OPE",
            "CON",
            "EXT",
            "AGR",
            "NNEU",
        ]

        df_hidden = df.drop(columns=professional_skills_list)

        df_hidden.to_csv(
            colleague_type(practical_subtasks) + config_data.Filenames_COLLEAGUE_RANKING
        )

        df_hidden.reset_index(inplace=True)

        person_id = int(df_hidden.iloc[0]["Person ID"]) - 1

        return (
            gr.Row(visible=True),
            gr.Column(visible=True),
            dataframe(
                headers=df_hidden.columns.tolist(),
                values=df_hidden.values.tolist(),
                visible=True,
            ),
            files_create_ui(
                colleague_type(practical_subtasks)
                + config_data.Filenames_COLLEAGUE_RANKING,
                "single",
                [".csv"],
                config_data.OtherMessages_EXPORT_WT,
                True,
                False,
                True,
                "csv-container",
            ),
            video_create_ui(
                value=files[person_id],
                file_name=Path(files[person_id]).name,
                label="Best Person ID - " + str(person_id + 1),
                visible=True,
            ),
            html_message(config_data.InformationMessages_NOTI_IN_DEV, False, False),
        )
    else:
        gr.Info(config_data.InformationMessages_NOTI_IN_DEV)

        return (
            gr.Row(visible=False),
            gr.Column(visible=False),
            dataframe(visible=False),
            files_create_ui(
                None,
                "single",
                [".csv"],
                config_data.OtherMessages_EXPORT_PS,
                True,
                False,
                False,
                "csv-container",
            ),
            video_create_ui(visible=False),
            html_message(config_data.InformationMessages_NOTI_IN_DEV, False, True),
        )