import os
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
from .basePlotAnalysis import BasePlotAnalysis

import matplotlib
matplotlib.use('Agg')

class PlotPeakHours(BasePlotAnalysis):
    """
    Class for analyzing peak activity hours and generating a bar chart.

    Attributes:
    name (str): The name of the analysis.
    description (str): A brief description of the analysis.
    plot_filename (str): The filename for the output plot.
    note (str): Additional notes for the analysis.
    """

    name = "Peak Hours Analysis"
    description = "Identifies peak activity hours using a bar chart."
    plot_filename = "peak_hours.png"
    note = ""

    def transform_data(self, df: pd.DataFrame) -> pd.DataFrame:
        """
        Transform data to add was_active column and extract peak hours. See data_utils.py.

        Parameters:
        df (pd.DataFrame): The input DataFrame containing user activity data.

        Returns:
        pd.DataFrame: The transformed DataFrame with additional columns for analysis.
        """
        return df

    def plot_data(self, df: pd.DataFrame):
        """
        Generate bar chart for peak hours.

        Parameters:
        df (pd.DataFrame): The transformed DataFrame containing user activity data.
        """
        peak_hours = df[df["was_active"]]["hour"].value_counts().sort_index()

        plt.figure(figsize=(12, 5))
        sns.barplot(x=peak_hours.index, y=peak_hours.values, hue=peak_hours.values, palette="coolwarm")

        plt.xlabel("Hour of the Day")
        plt.ylabel("Activity Count")
        plt.title("Peak Hours of User Activity")
        plt.xticks(range(0, 24))