__copyright__ = "Copyright (C) 2023 Ali Mustapha"
__license__ = "GPL-3.0-or-later"

import pandas as pd
import plotly.express as px
from plotly.subplots import make_subplots
import plotly.graph_objects as go

def get_commits_per_gender(gender_counts):
    gender_counts=gender_counts[gender_counts["Predicted_Gender"]!="Unknown"]

    grouped = gender_counts.groupby('Year').agg({'Count': 'sum'})
    grouped['Male Percentage'] = gender_counts[gender_counts['Predicted_Gender'] == 'Male'].groupby('Year')['Count'].sum() / grouped['Count'] * 100
    grouped['Female Percentage'] = gender_counts[gender_counts['Predicted_Gender'] == 'Female'].groupby('Year')['Count'].sum() / grouped['Count'] * 100
    grouped=grouped.fillna(0)
    merged_gender_counts = grouped.merge(gender_counts, on=["Year"])[['Year', 'Male Percentage', 'Female Percentage',
       'Predicted_Gender', 'Count_y']].rename(columns={"Count_y":"Count"})
    
    male_count=merged_gender_counts[merged_gender_counts["Predicted_Gender"]=="Male"]
    female_count=merged_gender_counts[merged_gender_counts["Predicted_Gender"]=="Female"]
    fig = make_subplots(rows=1, cols=1, shared_xaxes=True)
    # Add bars for Male and Female counts
    fig.add_trace(
        go.Bar(x=male_count['Year'], y=male_count['Count'], name='Male',
            hovertemplate='Male Commits: %{y:.2f}<br> Male Percentage: %{customdata:.2f}',  # Use customdata for the hovertemplate
            customdata=male_count['Male Percentage']),  # Use the 'Male Percentage' column for customdata
        row=1, col=1
    )

    fig.add_trace(
        go.Bar(x=female_count['Year'], y=female_count['Count'], name='Female',
            hovertemplate='Female Commits: %{y:.2f}<br>Female Percentage: %{customdata:.2f}',  # Use customdata for the hovertemplate
            customdata=female_count['Female Percentage']),  # Use the 'Female Percentage' column for customdata
        row=1, col=1
    )

    return fig


def get_gender_percentage(df):
    
    counts = df['Predicted_Gender'].value_counts().to_dict()

    # Define the labels and their corresponding counts
    labels = ["Male", "Female", "Unknown"]
    values = [counts.get(label, 0) for label in labels]

    Gender_Percentage_plot = go.Figure(data=[go.Pie(labels=labels, values=values, marker=dict(colors=["blue","pink","gray"]))])

    return Gender_Percentage_plot

def get_commits_per_region(df,url):
    Country_to_region=pd.read_csv("utils/CodeToRegion.csv")
    Country_to_region=Country_to_region.rename(columns={"sub-region":"sub-region-prediction"})
    
    # Group by Year and sub-region-prediction, then count unique sub-regions
    sub_region_counts = df.groupby(['Year', "sub-region-prediction"])["sub-region-prediction"].count().reset_index(name='Count')
    # Calculate the sums for each region
    region_sums = sub_region_counts.groupby('sub-region-prediction')['Count'].sum().reset_index()

    # Append 'All' rows to the DataFrame
    df_all = region_sums.copy()
    df_all['Year'] = 'Overall'
    df_result = pd.concat([sub_region_counts, df_all], ignore_index=True, sort=False)

    # Merge the sub_region_counts DataFrame with the Country_to_region DataFrame
    merged_df = df_result.merge(Country_to_region, on="sub-region-prediction", how="left")
    # Create a choropleth map using plotly.express
    fig = go.Figure(data=px.choropleth(
        merged_df,
        locations="code3",
        color="Count",
        hover_name="sub-region-prediction",
        # color_continuous_scale=px.colors.qualitative.Set3,  # Choose your color scale
        color_continuous_scale="Greens",
        animation_frame="Year",
        title="Counts by Sub-Region"
    ))
    
    fig.update_layout(
        title_text='Commits Counts by Sub-Region for '+url,
        geo=dict(
            showframe=False,
            showcoastlines=False,
            projection_type='equirectangular'
        ),
        annotations = [dict(
            x=0.55,
            y=0.1,
            xref='paper',
            yref='paper',
            text='Source: <a href="https://huggingface.co/spaces/AliMustapha/Geo-GenderStudy">\
                Geo-GenderStudy</a>',
            showarrow = False
        )],
        height=600,  # Adjust the height as per your preference
        width=1000   # Adjust the width as per your preference
    )
    return fig