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aod_p01_plot_map_combine.py
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aod_p01_plot_map_combine.py
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2020-12-23 11:49
# @Author : NingAnMe <[email protected]>
import os
from datetime import datetime
import argparse
import numpy as np
# import cv2
# import scipy.signal as signal
from lib.aod import AodCombine
from lib.province_mask import get_province_mask
from lib.proj_aod import proj_china
from config import AOD_COMBINE_DIR, AOD_PICTURE_DIR
from aod_h01_combine import get_day_str, get_month_str, get_season_str, get_year_str
from config import get_area_range, get_areas
from aod_p02_plot_map_origin import plot_map_picture
import warnings
warnings.filterwarnings('ignore')
def plot_map(datetime_start, datetime_end, data_dir=None, out_dir=None, data_loader=AodCombine,
data_type=None, date_type=None, deploy=False):
print("plot_map")
print("datetime_start === {}".format(datetime_start))
print("datetime_end === {}".format(datetime_end))
print("data_dir === {}".format(data_dir))
print("out_dir === {}".format(out_dir))
print("data_loader === {}".format(data_loader))
print("data_type === {}".format(data_type))
print("date_type === {}".format(date_type))
filelist = list()
for root, dirs, files in os.walk(data_dir):
for name in files:
if name[-3:].lower() != 'hdf':
continue
date_ = data_loader(name).dt
if not (datetime_start <= date_ <= datetime_end):
continue
filelist.append(os.path.join(root, name))
filelist.sort()
for in_file in filelist:
print("<<< : {}".format(in_file))
for area_type in ["China", "YRD"]:
loader = data_loader(in_file)
title = get_title(data_type, date_type, loader.dt, area_type)
title_split = title.split()
if deploy:
# obs_satfy3_aod_yrd_x_YYYYMMDDHHmmss_000_x_x_l2.jpg
# obs_satfy3_aod_CHN_x_YYYYMMDDHHmmss_000_x_x_l2.jpg
# 20210112_FY3D_MERSI_AOD(550nm)_over_YRD (6)
if area_type == "China":
filename = 'obs_satfy3_aod_CHN_x_{}000000_000_x_x_l2.jpg'.format(title_split[0])
else:
filename = 'obs_satfy3_aod_yrd_x_{}000000_000_x_x_l2.jpg'.format(title_split[0])
else:
filename = "_".join(title_split) + '.png'
out_file = os.path.join(out_dir, filename)
data = loader.get_aod()
lons, lats = loader.get_lon_lat()
data, lons, lats = proj_china(data, lons, lats)
vmin = 0
vmax = 1.5
ticks = np.arange(0, 1.51, 0.3)
if area_type == 'China':
mksize = 0.1
nanhai = True
else:
mksize = 0.3
nanhai = False
areas = get_areas(area_type)
mask = get_province_mask(areas)
valid = np.logical_and.reduce((data > vmin, data < vmax, mask))
data_mask = data[valid]
lons_mask = lons[valid]
lats_mask = lats[valid]
longitude_range, latitude_range = get_area_range(area_type)
box = [latitude_range[1], latitude_range[0], longitude_range[0], longitude_range[1]]
plot_map_picture(data_mask, lons_mask, lats_mask, title=title, vmin=vmin, vmax=vmax,
areas=areas, box=box, ticks=ticks, file_out=out_file,
mksize=mksize, nanhai=nanhai)
get_dt_str = {
'Daily': get_day_str,
'Monthly': get_month_str,
'Seasonly': get_season_str,
'Yearly': get_year_str,
}
def get_title(data_type, date_type, dt, area_type):
satellite, sensor = data_type.split('_')[:2]
date_str = get_dt_str[date_type](dt)
title = "{} {} {} AOD(550nm) over {}".format(date_str, satellite, sensor, area_type)
return title
def main(data_type=None, date_start=None, date_end=None, date_type=None):
datetime_start = datetime.strptime(date_start, "%Y%m%d")
datetime_end = datetime.strptime(date_end, "%Y%m%d")
combine_dir = os.path.join(AOD_COMBINE_DIR, 'AOD_COMBINE_{}'.format(data_type))
picture_dir = os.path.join(AOD_PICTURE_DIR, 'AOD_MAP_COMBINE_{}'.format(data_type))
if data_type in {'FY3D_MERSI_1KM', 'AQUA_MODIS_3KM', 'AQUA_MODIS_10KM'}:
if date_type in {'Daily', 'Monthly', 'Seasonly', 'Yearly'}:
data_dir = os.path.join(combine_dir, date_type)
out_dir = os.path.join(picture_dir, date_type)
plot_map(datetime_start, datetime_end, data_dir=data_dir, out_dir=out_dir,
data_type=data_type, date_type=date_type)
else:
parser.print_help()
raise ValueError(date_type)
elif data_type == 'FY3D_MERSI_5KM':
if date_type in {'Monthly', 'Seasonly', 'Yearly'}:
data_dir = os.path.join(combine_dir, date_type)
out_dir = os.path.join(picture_dir, date_type)
plot_map(datetime_start, datetime_end, data_dir=data_dir, out_dir=out_dir,
data_type=data_type, date_type=date_type)
else:
parser.print_help()
raise ValueError(date_type)
else:
parser.print_help()
raise ValueError(data_type)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Schedule')
parser.add_argument('--dataType', help='数据类型：FY3D_MERSI_1KM、FY3D_MERSI_5KM、AQUA_MODIS_3KM、AQUA_MODIS_5KM',
required=True)
parser.add_argument('--dateStart', help='开始时间（8位时间）：YYYYMMDD(20190101)', required=True)
parser.add_argument('--dateEnd', help='结束时间（8位时间）：YYYYMMDD(20190102)', required=True)
parser.add_argument('--dateType', help='合成的类型日、月、季、年：Daily、Monthly、Seasonly、Yearly', required=True)
args = parser.parse_args()
dataType = args.dataType
dateStart = args.dateStart
dateEnd = args.dateEnd
dateType = args.dateType
main(data_type=dataType, date_start=dateStart, date_end=dateEnd, date_type=dateType)
"""
绘制 FY3D_MERSI_1KM 日分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_1KM --dateType Daily --dateStart 20190101 --dateEnd 20190131
绘制 FY3D_MERSI_1KM 月分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_1KM --dateType Monthly --dateStart 20190101 --dateEnd 20190131
绘制 FY3D_MERSI_1KM 季度分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_1KM --dateType Seasonly --dateStart 20190101 --dateEnd 20190228
绘制 FY3D_MERSI_1KM 年分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_1KM --dateType Yearly --dateStart 20190101 --dateEnd 20191231
绘制 FY3D_MERSI_5KM 月分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_5KM --dateType Monthly --dateStart 20190101 --dateEnd 20190131
绘制 FY3D_MERSI_5KM 季度分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_5KM --dateType Seasonly --dateStart 20190101 --dateEnd 20190228
绘制 FY3D_MERSI_5KM 年分布图
python3 aod_p01_plot_map_combine.py --dataType FY3D_MERSI_5KM --dateType Yearly --dateStart 20190101 --dateEnd 20191231
绘制 AQUA_MODIS_3KM 日分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Daily --dateStart 20190101 --dateEnd 20190131
绘制 AQUA_MODIS_3KM 月分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Monthly --dateStart 20190101 --dateEnd 20190131
绘制 AQUA_MODIS_3KM 季度分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Seasonly --dateStart 20190101 --dateEnd 20190228
绘制 AQUA_MODIS_3KM 年分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Yearly --dateStart 20190101 --dateEnd 20191231
绘制 AQUA_MODIS_3KM 日分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Daily --dateStart 20190101 --dateEnd 20190131
绘制 AQUA_MODIS_3KM 月分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Monthly --dateStart 20190101 --dateEnd 20190131
绘制 AQUA_MODIS_3KM 季度分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Seasonly --dateStart 20190101 --dateEnd 20190228
绘制 AQUA_MODIS_3KM 年分布图
python3 aod_p01_plot_map_combine.py --dataType AQUA_MODIS_3KM --dateType Yearly --dateStart 20190101 --dateEnd 20191231
"""