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DFO_tool_fix.py
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DFO_tool_fix.py
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"""
DFO_tool.py
Download and process DFO data
Two main function:
* DFO_cron : run the daily cron job
* DFO_cron_fix: rerun cron-job for a given date
"""
import argparse
import csv
import json
import logging
import os
import shutil
import subprocess
import sys
from datetime import date, datetime
import geopandas
import numpy as np
import pandas as pd
import rasterio
import requests
from bs4 import BeautifulSoup
from rasterio.mask import mask
from DFO_MoM import update_DFO_MoM
from settings import *
from utilities import from_today, watersheds_gdb_reader
# for command line mode, no need for cron-job
# from progressbar import progress
# total number of hdf files
DFO_TOTAL_TILES = 287
DFO_MINIMUM_TILES = 280
def get_real_date(year, day_num):
"""get the real date"""
# allData/61/MCDWD_L3_NRT/2021/021
# year,day_num = foldername.split("/")[-2:]
res = datetime.strptime(str(year) + "-" + str(day_num), "%Y-%j").strftime("%Y%m%d")
return res
def check_status(adate):
"""check if a give date is processed"""
processed_list = os.listdir(DFO_SUM_DIR)
processed = any(adate in x for x in processed_list)
return processed
def get_hosturl():
"""get the host url"""
baseurl = config.get("dfo", "HOST")
cur_year = date.today().year
hosturl = os.path.join(baseurl, str(cur_year))
return hosturl
def generate_procesing_list():
"""generate list of date to process
return a dict object
{'001': '20230101', '002': '20230102'}
"""
hosturl = get_hosturl()
reqs = requests.get(hosturl, timeout = 20)
soup = BeautifulSoup(reqs.text, "html.parser")
cur_year = hosturl[-4:]
datelist = {}
# get the today in str
today_str = date.today().strftime("%Y%m%d")
for link in soup.find_all("a"):
day_num = link.string
if not day_num.isdigit():
continue
real_date = get_real_date(cur_year, day_num)
# compare date in iso str
# skip the later date, there is no data
if real_date > today_str:
continue
# check if the date is already processed
if check_status(real_date):
continue
datelist[day_num] = real_date
return datelist
def dfo_download(subfolder):
"""download a subfolder"""
# check if there is unfinished download
d_dir = os.path.join(DFO_PROC_DIR, subfolder)
if os.path.exists(d_dir):
# is file cases
if os.path.isfile(d_dir):
os.remove(d_dir)
else:
# remove the subfolder
shutil.rmtree(d_dir)
dfokey = config.get("dfo", "TOKEN")
dataurl = os.path.join(get_hosturl(), subfolder)
wgetcmd = 'wget -e robots=off -r --no-parent -R .html,.tmp -nH -l1 --cut-dirs=8 {dataurl} --header "Authorization: Bearer {key}" -P {downloadfolder}'
wgetcmd = wgetcmd.format(dataurl=dataurl, key=dfokey, downloadfolder=DFO_PROC_DIR)
# print(wgetcmd)
exitcode = subprocess.call(wgetcmd, shell=True)
if not (exitcode == 0 or exitcode ==8):
# something wrong with downloading
logging.warning("download failed: " + dataurl)
sys.exit()
return
def dfo_extract_by_mask(vrt_file, mask_json):
"""extract data for a single watershed"""
with rasterio.open(vrt_file) as src:
try:
out_image, out_transform = mask(
src, [mask_json["features"][0]["geometry"]], crop=True
)
except ValueError as e:
#'Input shapes do not overlap raster.'
# print(e)
src = None
# return empty dataframe
return 0
# extract data
no_data = src.nodata
# extract the values of the masked array
# print(out_image)
data = out_image[0]
point_count = np.count_nonzero(data == 3)
src = None
# total area
d = point_count * 0.25 * 0.25
return d
def dfo_extract_by_watershed(vtk_file):
"""extract data by all the watersheds"""
watersheds = watersheds_gdb_reader()
pfaf_id_list = watersheds.index.tolist()
headerprefix = os.path.basename(vtk_file).split("_")[1]
if "_CS_" in vtk_file:
headerprefix = "1-Day_CS"
headers_list = [
"pfaf_id",
headerprefix + "_TotalArea_km2",
headerprefix + "_perc_Area",
]
summary_file = os.path.basename(vtk_file)[:-4] + ".csv"
if not os.path.exists(summary_file):
with open(summary_file, "w") as f:
writer = csv.writer(f)
writer.writerow(headers_list)
else:
# already processed,
return
# count = 0
with open(summary_file, "a") as f:
writer = csv.writer(f)
for pfaf_id in pfaf_id_list:
# print(the_aqid, count, " out of ", len(aqid_list))
# count += 1
# progress(count, len(pfaf_id_list), status='pfaf_id')
# extract mask
test_json = json.loads(
geopandas.GeoSeries([watersheds.loc[pfaf_id, "geometry"]]).to_json()
)
# plot check
dfoarea = dfo_extract_by_mask(vtk_file, test_json)
DFO_TotalArea = dfoarea
DFO_Area_percent = DFO_TotalArea / watersheds.loc[pfaf_id]["area_km2"] * 100
results_list = [
pfaf_id,
"{:.3f}".format(DFO_TotalArea),
"{:.3f}".format(DFO_Area_percent),
]
writer.writerow(results_list)
return
def DFO_process(folder, adate):
"""processing dfo folder
folder structure
allData/61/MCDWD_L3_NRT/2021/021
|-Flood 1-Day 250m
|-Flood 1-Day CS 250m
|-Flood 2-Day 250m
|-Flood 3-Day 250m
Flood_3-Day_250m.vrt
Flood_2-Day_250m.vrt
Flood_1-Day_CS_250m.vrt
Flood_1-Day_250m.vrt
"""
hdffolder = os.path.join(DFO_PROC_DIR, folder)
if os.path.isfile(hdffolder):
logging.warning("Not downloaded properly: " + folder)
return
# switch to working directory
os.chdir(hdffolder)
floodlayer = [
"Flood 1-Day 250m",
"Flood 1-Day CS 250m",
"Flood 2-Day 250m",
"Flood 3-Day 250m",
]
# new layer name mapping
floodsubdataset = {
"Flood 1-Day 250m":"Flood_1Day_250m",
"Flood 1-Day CS 250m":"FloodCS_1Day_250m",
"Flood 2-Day 250m":"Flood_2Day_250m",
"Flood 3-Day 250m":"Flood_3Day_250m",
}
# create sub folder if necessary
for flood in floodlayer:
subfolder = flood.replace(" ", "_")
if not os.path.exists(subfolder):
os.mkdir(subfolder)
# MCDWD_L3_NRT.A2021022.h06v04.061.hdf
# HDF4_EOS:EOS_GRID:"MCDWD_L3_NRT.A2021022.h06v04.061.hdf":Grid_Water_Composite:"Flood 1-Day 250m"
# HDF4_EOS:EOS_GRID:"MCDWD_L3_NRT.A2021022.h06v04.061.hdf":Grid_Water_Composite:"Flood 1-Day CS 250m"
# HDF4_EOS:EOS_GRID:"MCDWD_L3_NRT.A2021022.h06v04.061.hdf":Grid_Water_Composite:"Flood 2-Day 250m"
# HDF4_EOS:EOS_GRID:"MCDWD_L3_NRT.A2021022.h06v04.061.hdf":Grid_Water_Composite:"Flood 3-Day 250m"
# HDF4_EOS:EOS_GRID:"{HDF}":Grid_Water_Composite:"{floodLAYER}"
# scan hdf files
hdffiles = []
for entry in os.listdir():
if entry[-4:] != ".hdf":
continue
HDF = entry
hdffiles.append(HDF)
# check the number of files
# need check the date first
ddays = from_today(adate)
# for the previous day, just process what ever it has
if ddays >= 0:
if len(hdffiles) < DFO_TOTAL_TILES:
logging.warning("Not enough files: " + folder)
return
# one step one image operation
vrt_list = []
for flood in floodlayer:
subfolder = flood.replace(" ", "_")
subdataset = floodsubdataset[flood]
# geotiff convert
for HDF in hdffiles:
nameprefix = "_".join(HDF.split(".")[1:3])
inputlayer = f'HDF4_EOS:EOS_GRID:"{HDF}":Grid_Water_Composite::{subdataset}'
tiff = nameprefix + "_" + subfolder
outputtiff = os.path.join(subfolder, tiff + ".tiff")
if not os.path.exists(outputtiff):
# gdal cmda
gdalcmd = (
f"gdal_translate -of GTiff -co Tiled=Yes {inputlayer} {outputtiff}"
)
# convert geotiff
os.system(gdalcmd)
# build vrt
gdalcmd = f"gdalbuildvrt {subfolder}.vrt {subfolder}/*.tiff"
# print(gdalcmd)
os.system(gdalcmd)
vrt = f"{subfolder}.vrt"
vrt_list.append(vrt)
# extract flood data
dfo_extract_by_watershed(vrt)
# build geotiff
if "3-Day" in vrt:
# tiff = outputfolder + os.path.sep + "DFO_image/DFO_" + datestr + "_" + vrt.replace(".vrt",".tiff")
# DFO_20210603_Flood_3-Day_250m.tiff
tiff = "DFO_{datestr}_{layer}.tiff".format(datestr=adate, layer=subfolder)
tiff = os.path.join(DFO_IMG_DIR, tiff)
# gdal_translate -co TILED=YES -co COMPRESS=PACKBITS -of GTiff Flood_1-Day_250m.vrt Flood_1-Day_250m.tiff
# gdaladdo -r average Flood_1-Day_250m.tiff 2 4 8 16 32
gdalcmd = (
f"gdal_translate -co TILED=YES -co COMPRESS=LZW -of GTiff {vrt} {tiff}"
)
os.system(gdalcmd)
# build overview
# gdalcmd = f'gdaladdo -r average {tiff} 2 4 8 16 32'
# os.system(gdalcmd)
# delete tiff folder
if os.path.exists(subfolder):
shutil.rmtree(subfolder)
# merge flood data into one file
csv_list = []
for vrt in vrt_list:
csvfile = vrt.replace(".vrt", ".csv")
pdc = pd.read_csv(csvfile)
csv_list.append(pdc)
merged = csv_list[0].merge(csv_list[1], on="pfaf_id")
merged = merged.merge(csv_list[2], on="pfaf_id")
merged = merged.merge(csv_list[3], on="pfaf_id")
# save output
summary_csv = os.path.join(DFO_SUM_DIR, "DFO_{}.csv".format(adate))
merged.to_csv(summary_csv)
logging.info("generated: " + summary_csv)
# zip the original foldera
if config["storage"].getboolean("dfo_save"):
zipped = os.path.join(DFO_PROC_DIR, "DFO_{}.zip".format(adate))
zipcmd = f"zip -r -0 {zipped} ./*"
os.system(zipcmd)
logging.info("generated: " + zipped)
# remove all hdf file in the folder
for entry in os.listdir():
if ".hdf" in entry:
os.remove(entry)
# switch back script folder
os.chdir(BASE_DIR)
return
def DFO_cron():
"""cron job to process DFO"""
datelist = generate_procesing_list()
print(datelist)
sys.exit(0)
if len(datelist) == 0:
logging.info("no new data to process!")
sys.exit(0)
for key in datelist:
logging.info("download: " + key)
dfo_download(key)
logging.info("download finished!")
logging.info("processing: " + key)
# process data
# key: folder name
# datelist[key]: real date
DFO_process(key, datelist[key])
# run DFO_MoM
update_DFO_MoM(datelist[key])
logging.info("processing finished: " + key)
return
def DFO_fixdate(adate):
"""process a specific date"""
print(adate)
# first check if the date is fixable
datelist = generate_procesing_list()
if adate not in datelist.values():
print("date not in the available data list or already processed!")
print("list of available dates:", list(datelist.values()))
sys.exit(0)
key = [k for k, v in datelist.items() if v == adate][0]
# form a new datelist
datelist = {key: adate}
#print(datelist)
for key in datelist:
logging.info("try to fix a date: " + datelist[key])
logging.info("download: " + key)
dfo_download(key)
logging.info("download finished!")
logging.info("processing: " + key)
# process data
# key: folder name
# datelist[key]: real date
DFO_process(key, datelist[key])
# run DFO_MoM
update_DFO_MoM(datelist[key])
logging.info("processing finished: " + key)
def main():
"""main function"""
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-fd','--fixdate', dest='fixdate', type=str, help="try to process a specific date")
args = parser.parse_args()
if args.fixdate:
DFO_fixdate(args.fixdate)
else:
DFO_cron()
if __name__ == "__main__":
main()