functions.py

#! /usr/bin/env python
# -*- coding: utf-8 -*-
# @file             : functions.py
# @created          : 18-Nov-2019
#

"""

"""

# Functions to deal and handle the list of items
# import importlib
# import item

# importlib.reload(item)
from src.crops import *
from src.animal_food import *
from src.animals import *
from src.honey_extractor import *
from src.fish import *
from src.duck_salon import *
from src.sugar_mill import *
from src.dairy import *
from src.bakery import *
from src.popcorn_pot import *
from src.sauce_maker import *
from src.bbq_grill import *
from src.pie_oven import *
from src.loom import *
from src.sewing_machine import *
from src.mine import *
from src.pie_oven import *
from src.cake_oven import *
from src.smelter import *
from src.juice_press import *
from src.jam_maker import *
from src.jeweler import *
from src.candy_machine import *
from src.coffee_kiosk import *
from src.ice_cream_maker import *
from src.pasta_maker import *
from src.soup_kitchen import *
from src.candle_maker import *
from src.flower_shop import *
from src.sushi_bar import *
from src.salad_bar import *
from src.sandwich_bar import *
from src.smoothie_mixer import *
from src.smoothie_mixer import *
from src.smoothie_mixer import *
from src.smoothie_mixer import *
from src.smoothie_mixer import *
from src.smoothie_mixer import *
from src.wok_kitchen import *
from src.hat_maker import *
from src.pasta_kitchen import *
from src.hot_dog_stand import *
from src.donut_maker import *
from src.taco_kitchen import *
from src.tea_stand import *
from src.fondue_pot import *
from src.bath_kiosk import *
from src.deep_fryer import *
from src.preservation_station import *
from src.fudge_shop import *
from src.yogurt_maker import *
from src.stew_pot import *
from src.cupcake_maker import *
from src.waffle_maker import *
from src.omelet_station import *
from src.porridge_bar import *
from src.pottery_studio import *
from src.milkshake_bar import *
from src.essential_oils_lab import *
from src.perfumerie import *
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd


print('# of item in list_items {:2d}'.format(len(list_items)))


def list_places():
    places = []
    for item in list_items:
        places.append(item.production_place)

    unique_places = set(places)
    return unique_places


def list_products_at(place):
    items = []
    number = 1
    for item in list_items:
        if place == item.production_place:
            items.append(item)
    return items


def plot_time_vs_profit_at(place):
    time_and_profit_df = pd.DataFrame(
        columns=['production_time', 'profit', 'item_name', 'price_sell']
    )
    number = 1
    for item in list_items:
        if place == item.production_place:
            print(
                '{:d} ---> {:20s} {:20f} {:20f}'.format(
                    number,
                    item.name,
                    item.get_production_time(),
                    item.get_profit(),
                )
            )
            time_and_profit_df = time_and_profit_df.append(
                {
                    'production_time': item.get_production_time(),
                    'profit': item.get_profit(),
                    'item_name': item.name,
                    'price_sell': item.price_sell,
                    'profit_per_hour': item.get_profit()
                    / item.get_production_time(),
                    'prod_cost': item.get_production_price(),
                },
                ignore_index=True,
            )
            number += 1
    #    plt.plot(arr_time_and_profit[:, 0], arr_time_and_profit[:, 1], 'bo', markersize=5)
    # plt.scatter(arr_time_and_profit[:, 0], arr_time_and_profit[:, 1])
    fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(15, 10))
    axis = ax.scatter(
        time_and_profit_df['prod_cost'],
        time_and_profit_df['profit'],
        c=time_and_profit_df['production_time'],
        cmap='viridis',
    )
    cmap = fig.colorbar(axis, ax=ax)
    cmap.set_label('production time (h)')

    # Label each point in scatter plot
    for index, row in time_and_profit_df.iterrows():
        ax.annotate(
            '{:s} \n {:.2f}'.format(row['item_name'], row['profit_per_hour']),
            xy=(row['prod_cost'], row['profit']),  # Label's position
            xytext=(0, 10),
            textcoords='offset points',  # Label offset from the plotted point
            ha='center',  # alignment
            va='bottom',
        )

    ax.set_title(place, color='blue')
    ax.set_xlabel('production cost')
    ax.set_ylabel('Profit')
    return fig
    # plt.show()


def generate_df():
    df_items = pd.DataFrame(
        columns=[
            'production_time',
            'profit',
            'item_name',
            'price_sell',
            'profit_per_hour',
            'prod_cost',
            'place',
        ]
    )
    for item in list_items:
        tmp_df = pd.DataFrame.from_records(
            [
                {
                    'production_time': item.get_production_time(),
                    'profit': item.get_profit(),
                    'item_name': item.name,
                    'price_sell': item.price_sell,
                    'profit_per_hour': item.get_profit()
                    / item.get_production_time(),
                    'prod_cost': item.get_production_price(),
                    'place': item.production_place,
                }
            ]
        )

        df_items = pd.concat([df_items, tmp_df], ignore_index=True)
    return df_items


def get_object(name):
    for item in list_items:
        if item.name == name:
            return item