Argo_Float/select_buoy_dates.py at main · danliba/Argo_Float · GitHub

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# -*- coding: utf-8 -*-
"""
Created on Thu Apr  1 20:22:28 2021

@author: danli
"""
#ordenando las boyas como perfiles de flotadores
from netCDF4 import Dataset
import os
import numpy as np
from datetime import date
import functools
import datetime
import pandas as pd
import matplotlib.pyplot as plt

path0='D:\\CIO\\pg_web\\flotos\\'
dir_list=os.listdir('D:\\CIO\\pg_web\\flotos\\'); check= 't'
buoy_list = [idx for idx in dir_list if idx[0].lower() == check.lower()]
today = date.today()
dirName = 'data_'+str(today)
#os.makedirs(dirName)
def main():

    # Create directory
    dirName = 'data_'+str(today)
    try:
        # Create target Directory
        os.mkdir(dirName)
        print("Directory " , dirName ,  " Created ")
    except FileExistsError:
        print("Directory " , dirName ,  " already exists")

if __name__ == '__main__':
    main()


savedir = 'D:\\CIO\\pg_web\\flotos\\'+dirName
os.chdir(savedir)

for kk in range(len(buoy_list)):
    fn=buoy_list[kk]
    print(fn)
    #fn='t0n110w_dy.cdf'
    data=Dataset(path0+fn)

    lat = data.variables['lat'][:]
    lon = data.variables['lon'][:]
    depth = data.variables['depth'][:]
    time = data.variables['time'][:]

    starting_date = data.variables['time'].units[11:21]

    temp = data.variables['T_20'][:][:,:,0,0]
    creation_day=data.variables['time'].units; yy=int(creation_day[11:15]); mm=int(creation_day[16:18]); dd=int(creation_day[19:21])
    fecha=time+np.array(date.toordinal(date(yy,mm,dd)))
    temp=np.array(temp,dtype='float32').T

    #start 5 days before today
    today = date.today()
    yesterday = today - datetime.timedelta(days=5)#5 dias atrás
    ytd=yesterday.strftime("%Y-%m-%d")

    yrst=int(ytd[0:4]); most=int(ytd[5:7]); dast=int(ytd[8:10])
    date_start=np.array(date.toordinal(date(yrst,most,dast)))
    find_stdate=np.where(fecha==date_start)
    fdt=functools.reduce(lambda sub, ele: sub * 10 + ele, find_stdate)

    if len(fdt)==0:
        print("Starting date is out of range")
        continue

    indx_date=int(fdt)
    fecha_inicio=fecha[indx_date:];

    ending_date = date.fromordinal(int(fecha_inicio[-1]))
    date_range = pd.date_range(start= starting_date, end=ending_date)

    temp[temp==1.0000000e+35] = np.nan; sst=temp[:,indx_date:]

    sst_prom=np.nanmean(sst,1)
    fig=plt.figure(figsize=(5,7))
    plt.plot(sst_prom,-depth,marker='*')
    plt.title('5 day mean '+fn)
    #boya_fn=np.concatenate((depth.reshape(-1,1),sst_prom.reshape(-1,1)),axis=1)
    #save the numpy array

    fn_save="SST-"+str(fn[:7])+".npz"
    np.savez(fn_save,depth=depth,sst=sst_prom,lon=lon,lat=lat)

    #npzfile2=np.load(fn_save,allow_pickle=True)
    #a=npzfile['arr_0']