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import os

import numpy as np

import pandas as pd

import datetime

from utils import *

# 出口

def test1():

path = os.path.join(data_dir, '进出口'+'.csv')

df = pd.read_csv(path)

t = pd.DatetimeIndex(pd.to_datetime(df['time'], format='%Y-%m'))

start_time = '2005-01-01'

end_time = '2055-01-01'

imbalance = np.array(df['贸易顺差:当月值'], dtype=float)

datas = [[t, imbalance, '贸易顺差:当月值']]

plot_one_figure(datas, '', start_time, end_time)

export_all = np.array(df['出口金额:当月值'], dtype=float)

export_us = np.array(df['美国:出口金额:当月值'], dtype=float)

export_eu = np.array(df['欧盟:出口金额:当月值'], dtype=float)

export_de = np.array(df['德国:出口金额:当月值'], dtype=float)

export_fr = np.array(df['法国:出口金额:当月值'], dtype=float)

export_uk = np.array(df['英国:出口金额:当月值'], dtype=float)

export_jp = np.array(df['日本:出口金额:当月值'], dtype=float)

export_kr = np.array(df['韩国:出口金额:当月值'], dtype=float)

export_vn = np.array(df['越南:出口金额:当月值'], dtype=float)

export_asean = np.array(df['东南亚国家联盟:出口金额:当月值'], dtype=float)

plot_seasonality(t, export_all, start_year=2012, title='export_all')

plot_seasonality(t, export_us, start_year=2012, title='export_us')

plot_seasonality(t, export_eu, start_year=2012, title='export_eu')

plot_seasonality(t, export_de, start_year=2012, title='export_de')

plot_seasonality(t, export_fr, start_year=2012, title='export_fr')

plot_seasonality(t, export_uk, start_year=2012, title='export_uk')

plot_seasonality(t, export_jp, start_year=2012, title='export_jp')

plot_seasonality(t, export_kr, start_year=2012, title='export_kr')

plot_seasonality(t, export_vn, start_year=2012, title='export_vn')

plot_seasonality(t, export_asean, start_year=2012, title='export_asean')

# datas = [[t, export_us, '美国:出口金额:当月值'],

# [t, export_eu, '欧盟:出口金额:当月值'],

# [t, export_asean, '东南亚国家联盟:出口金额:当月值']]

# plot_one_figure(datas, '', start_time, end_time)

# datas = [[t, export_de, '德国:出口金额:当月值'],

# [t, export_fr, '法国:出口金额:当月值'],

# [t, export_uk, '英国:出口金额:当月值'],

# [t, export_jp, '日本:出口金额:当月值'],

# [t, export_kr, '韩国:出口金额:当月值'],

# [t, export_vn, '越南:出口金额:当月值'],]

# plot_one_figure(datas, '', start_time, end_time)

# export_all_acc = np.array(df['出口金额:累计值'], dtype=float)

# export_us_acc = np.array(df['美国:出口金额:累计值'], dtype=float)

# export_eu_acc = np.array(df['欧盟:出口金额:累计值'], dtype=float)

# export_de_acc = np.array(df['德国:出口金额:累计值'], dtype=float)

# export_fr_acc = np.array(df['法国:出口金额:累计值'], dtype=float)

# export_uk_acc = np.array(df['英国:出口金额:累计值'], dtype=float)

# export_jp_acc = np.array(df['日本:出口金额:累计值'], dtype=float)

# export_kr_acc = np.array(df['韩国:出口金额:累计值'], dtype=float)

# export_vn_acc = np.array(df['越南:出口金额:累计值'], dtype=float)

# export_asean_acc = np.array(df['东南亚国家联盟:出口金额:累计值'], dtype=float)

# export_all_acc_yoy = np.array(df['出口金额:累计同比'], dtype=float)

# export_us_acc_yoy = np.array(df['美国:出口金额:累计同比'], dtype=float)

# export_eu_acc_yoy = np.array(df['欧盟:出口金额:累计同比'], dtype=float)

# export_de_acc_yoy = np.array(df['德国:出口金额:累计同比'], dtype=float)

# export_fr_acc_yoy = np.array(df['法国:出口金额:累计同比'], dtype=float)

# export_uk_acc_yoy = np.array(df['英国:出口金额:累计同比'], dtype=float)

# export_jp_acc_yoy = np.array(df['日本:出口金额:累计同比'], dtype=float)

# export_kr_acc_yoy = np.array(df['韩国:出口金额:累计同比'], dtype=float)

# export_vn_acc_yoy = np.array(df['越南:出口金额:累计同比'], dtype=float)

# export_asean_acc_yoy = np.array(df['东南亚国家联盟:出口金额:累计同比'], dtype=float)

# datas = [[t, export_all_acc_yoy, '出口金额:累计同比'],

# [t, export_us_acc_yoy, '美国:出口金额:累计同比'],

# [t, export_eu_acc_yoy, '欧盟:出口金额:累计同比'],

# [t, export_de_acc_yoy, '德国:出口金额:累计同比'],

# [t, export_fr_acc_yoy, '法国:出口金额:累计同比'],

# [t, export_uk_acc_yoy, '英国:出口金额:累计同比'],

# [t, export_jp_acc_yoy, '日本:出口金额:累计同比'],

# [t, export_kr_acc_yoy, '韩国:出口金额:累计同比'],

# [t, export_vn_acc_yoy, '越南:出口金额:累计同比'],

# [t, export_asean_acc_yoy, '东南亚国家联盟:出口金额:累计同比']]

# start_time = '2005-01-01'

# end_time = '2055-01-01'

# plot_one_figure(datas, '', start_time, end_time)

# t1, export_useu_acc = data_add(t, export_us_acc, t, export_eu_acc)

# t1, export_useu_acc_yoy = yoy_for_monthly_data(t1, export_useu_acc)

# t2, export_yoy_diff = data_sub(t, export_asean_acc_yoy, t1, export_useu_acc_yoy)

# datas = [[t2, export_yoy_diff, '东南亚-美欧:出口金额:累计同比差值']]

# plot_one_figure(datas, '', start_time, end_time)

# plot_seasonality(t, export_all_acc_yoy, start_year=2012, title='出口金额:累计同比')

# plot_seasonality(t, export_us_acc_yoy, start_year=2012, title='美国:出口金额:累计同比')

# plot_seasonality(t, export_eu_acc_yoy, start_year=2012, title='欧盟:出口金额:累计同比')

# plot_seasonality(t, export_de_acc_yoy, start_year=2012, title='德国:出口金额:累计同比')

# plot_seasonality(t, export_jp_acc_yoy, start_year=2012, title='日本:出口金额:累计同比')

# plot_seasonality(t, export_kr_acc_yoy, start_year=2012, title='韩国:出口金额:累计同比')

# plot_seasonality(t, export_vn_acc_yoy, start_year=2012, title='越南:出口金额:累计同比')

# plot_seasonality(t, export_asean_acc_yoy, start_year=2012, title='东南亚国家联盟:出口金额:累计同比')

# export_all_yoy = np.array(df['出口金额:当月同比'], dtype=float)

# export_us_yoy = np.array(df['美国:出口金额:当月同比'], dtype=float)

# export_eu_yoy = np.array(df['欧盟:出口金额:当月同比'], dtype=float)

# export_de_yoy = np.array(df['德国:出口金额:当月同比'], dtype=float)

# export_fr_yoy = np.array(df['法国:出口金额:当月同比'], dtype=float)

# export_uk_yoy = np.array(df['英国:出口金额:当月同比'], dtype=float)

# export_jp_yoy = np.array(df['日本:出口金额:当月同比'], dtype=float)

# export_kr_yoy = np.array(df['韩国:出口金额:当月同比'], dtype=float)

# export_vn_yoy = np.array(df['越南:出口金额:当月同比'], dtype=float)

# export_asean_yoy = np.array(df['东南亚国家联盟:出口金额:当月同比'], dtype=float)

# datas = [[t, export_all_yoy, '出口金额:当月同比'],

# [t, export_us_yoy, '美国:出口金额:当月同比'],

# [t, export_eu_yoy, '欧盟:出口金额:当月同比'],

# [t, export_de_yoy, '德国:出口金额:当月同比'],

# [t, export_fr_yoy, '法国:出口金额:当月同比'],

# [t, export_uk_yoy, '英国:出口金额:当月同比'],

# [t, export_jp_yoy, '日本:出口金额:当月同比'],

# [t, export_kr_yoy, '韩国:出口金额:当月同比'],

# [t, export_vn_yoy, '越南:出口金额:当月同比'],

# [t, export_asean_yoy, '东南亚国家联盟:出口金额:当月同比']]

# start_time = '2005-01-01'

# end_time = '2055-01-01'

# plot_one_figure(datas, '', start_time, end_time)

# plot_seasonality(t, export_all_yoy, start_year=2012, title='出口金额:当月同比')

# plot_seasonality(t, export_us_yoy, start_year=2012, title='美国:出口金额:当月同比')

# plot_seasonality(t, export_eu_yoy, start_year=2012, title='欧盟:出口金额:当月同比')

# plot_seasonality(t, export_de_yoy, start_year=2012, title='德国:出口金额:当月同比')

# plot_seasonality(t, export_jp_yoy, start_year=2012, title='日本:出口金额:当月同比')

# plot_seasonality(t, export_kr_yoy, start_year=2012, title='韩国:出口金额:当月同比')

# plot_seasonality(t, export_vn_yoy, start_year=2012, title='越南:出口金额:当月同比')

# plot_seasonality(t, export_asean_yoy, start_year=2012, title='东南亚国家联盟:出口金额:当月同比')

# 原材料进口

def test2():

path = os.path.join(data_dir, '进出口'+'.csv')

df = pd.read_csv(path)

t = pd.DatetimeIndex(pd.to_datetime(df['time'], format='%Y-%m'))

start_time = '2005-01-01'

end_time = '2055-01-01'

import_i = np.array(df['进口数量:铁矿砂及其精矿:当月值'], dtype=float)

import_oil = np.array(df['进口数量:原油:当月值'], dtype=float)

# import_lng = np.array(df['进口数量:液化天然气:当月值'], dtype=float)

import_cu1 = np.array(df['进口数量:铜矿砂及其精矿:当月值'], dtype=float)

import_cu2 = np.array(df['进口数量:未锻造的铜及铜材:当月值'], dtype=float)

t1, import_i_yoy = yoy_for_monthly_data(t, import_i)

t2, import_oil_yoy = yoy_for_monthly_data(t, import_oil)

# t3, import_lng_yoy = yoy_for_monthly_data(t, import_lng)

t4, import_cu1_yoy = yoy_for_monthly_data(t, import_cu1)

t5, import_cu2_yoy = yoy_for_monthly_data(t, import_cu2)

datas = [[[[t,import_i,'进口数量:铁矿砂及其精矿:当月值','']],[[t1,import_i_yoy,'当月同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_oil,'进口数量:原油:当月值','']],[[t2,import_oil_yoy,'当月同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_cu1,'进口数量:铜矿砂及其精矿:当月值','']],[[t4,import_cu1_yoy,'当月同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_cu2,'进口数量:未锻造的铜及铜材:当月值','']],[[t5,import_cu2_yoy,'当月同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

import_i_acc = np.array(df['进口数量:铁矿砂及其精矿:累计值'], dtype=float)

import_oil_acc = np.array(df['进口数量:原油:累计值'], dtype=float)

import_lng_acc = np.array(df['进口数量:液化天然气:累计值'], dtype=float)

import_cu1_acc = np.array(df['进口数量:铜矿砂及其精矿:累计值'], dtype=float)

import_cu2_acc = np.array(df['进口数量:未锻造的铜及铜材:累计值'], dtype=float)

t11, import_i_acc_yoy = yoy_for_monthly_data(t, import_i_acc)

t12, import_oil_acc_yoy = yoy_for_monthly_data(t, import_oil_acc)

t13, import_lng_acc_yoy = yoy_for_monthly_data(t, import_lng_acc)

t14, import_cu1_acc_yoy = yoy_for_monthly_data(t, import_cu1_acc)

t15, import_cu2_acc_yoy = yoy_for_monthly_data(t, import_cu2_acc)

datas = [[[[t,import_i_acc,'进口数量:铁矿砂及其精矿:累计值','']],[[t11,import_i_acc_yoy,'累计同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_oil_acc,'进口数量:原油:累计值','']],[[t12,import_oil_acc_yoy,'累计同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_lng_acc,'进口数量:液化天然气:累计值','']],[[t13,import_lng_acc_yoy,'累计同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_cu1_acc,'进口数量:铜矿砂及其精矿:累计值','']],[[t14,import_cu1_acc_yoy,'累计同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

datas = [[[[t,import_cu2_acc,'进口数量:未锻造的铜及铜材:累计值','']],[[t15,import_cu2_acc_yoy,'累计同比','']],'']]

plot_many_figure(datas, start_time=start_time, end_time=end_time)

if __name__=="__main__":

# 出口

test1()

# 原材料进口

# test2()