"""

"""

import click

from app.settings import types
from app.utils import click_utils
from app.settings import app_cfg as cfg


@click.command()
@click.option('-i', '--input', 'opt_fp_in', default=None,
  help='Override enum input filename CSV')
@click.option('-o', '--output', 'opt_fp_out', default=None,
  help='Override enum output filename CSV')
@click.option('-m', '--media', 'opt_dir_media', default=None,
  help='Override enum media directory')
@click.option('--store', 'opt_data_store',
  type=cfg.DataStoreVar,
  default=click_utils.get_default(types.DataStore.HDD),
  show_default=True,
  help=click_utils.show_help(types.Dataset))
@click.option('--dataset', 'opt_dataset',
  type=cfg.DatasetVar,
  required=True,
  show_default=True,
  help=click_utils.show_help(types.Dataset))
@click.option('-f', '--force', 'opt_force', is_flag=True,
  help='Force overwrite file')
@click.pass_context
def cli(ctx, opt_fp_in, opt_fp_out, opt_dir_media, opt_data_store, opt_dataset, opt_force):
  """Converts age/gender to CSV for pie chartgs"""
  
  import sys
  import os
  from os.path import join
  from pathlib import Path
  from glob import glob
  
  from tqdm import tqdm
  import numpy as np
  import cv2 as cv
  import pandas as pd

  from app.utils import logger_utils
  from app.models.data_store import DataStore

  # -------------------------------------------------------------------------
  # init here

  log = logger_utils.Logger.getLogger()
  
  # init filepaths
  data_store = DataStore(opt_data_store, opt_dataset)
  # set file output path
  metadata_type = types.Metadata.FACE_ATTRIBUTES
  fp_in = data_store.metadata(metadata_type) if opt_fp_out is None else opt_fp_in
  dk = opt_dataset.name.lower()
  log.debug(f'dk: {dk}')
  fp_out_age = f'../site/content/pages/datasets/{dk}/assets/age.csv'
  fp_out_gender = f'../site/content/pages/datasets/{dk}/assets/gender.csv'

  if not opt_force and (Path(fp_out_age).exists() or Path(fp_out_gender).exists()):
    log.error('File exists. Use "-f / --force" to overwite')
    return

  # -------------------------------------------------------------------------
  # Age

  df = pd.read_csv(fp_in)

  results = []
  brackets = [(0, 12), (13, 18), (19,24), (25, 34), (35, 44), (45, 54), (55, 64), (64, 75), (75, 100)]
  df_age = df['age_real']

  for a1, a2 in brackets:
    n = len(df_age.loc[((df_age >= a1) & (df_age <= a2))])
    results.append({'age': f'{a1} - {a2}', 'faces': n})
    
  df_out = pd.DataFrame.from_dict(results)
  df_out = df_out[['age','faces']]
  df_out.to_csv(fp_out_age, index=False)

  # Gender
  results = []

  df_f = df['f']
  nm = len(df_f.loc[((df_f < 0.33))])
  nnb = len(df_f.loc[((df_f >= 0.33) & (df_f <= 0.66))])
  nf = len(df_f.loc[((df_f > 0.66))])

  results = []
  results.append({'gender': 'Male', 'faces':nm})
  results.append({'gender': 'Female', 'faces': nf})
  results.append({'gender': 'They', 'faces': nnb})

  df_out = pd.DataFrame.from_dict(results)
  df_out = df_out[['gender','faces']]
  df_out.to_csv(fp_out_gender, index=False)