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motus/intermediate_work_scripts/data_extractor_zip.py
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data_extractor_zip.py
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# coding: utf-8
# In[7]:
#Imports
import pandas as pd
import numpy as np
from IPython.core import display as ICD
import glob
import os
from zipfile import ZipFile
pd.set_option('display.max_columns', 100)
# In[8]:
print('### --- MoTUS Data Extractor ---###')
print('')
# In[5]:
# General timestamp
# ----------------------------------- #
#List of some available timestamp, it is possible to include more
# B business day frequency
# D calendar day frequency
# W weekly frequency
# M month end frequency
# SM semi-month end frequency (15th and end of month)
# MS month start frequency
# SMS semi-month start frequency (1st and 15th)
# Q quarter end frequency
# QS quarter start frequency
# A year end frequency
# AS year start frequency
# H hourly frequency
# T minutely frequency
# S secondly frequency
# L milliseonds
# U microseconds
# N nanoseconds
time_int='5T'
#Data folder
DATA_FOLDER = r'/Users/gianlucamancini/Desktop/7zip_files/'
AVERAGE_RES_FOLDER = r'/Users/gianlucamancini/Desktop/'
name_file="guru99.txt"
print('Time interval: ',time_int)
print('Folder with zip files: ',DATA_FOLDER)
print('Folder for save results: ',AVERAGE_RES_FOLDER)
print('')
# In[6]:
### Anemometer averaging data ###
# ----------------------------------- #
print('Anemometers in progress...')
items_anem = np.arange(1,8)
columns_anem=[1,2,3,6,7]
time_stp_position_anem=-1 #Respect to columns_anem
zip_folders=os.listdir(DATA_FOLDER)
for zip_folder in zip_folders:
print("In progress: {}".format(zip_folder), end="\r")
content=open(DATA_FOLDER+zip_folder ,"rb")
zip_file = ZipFile(DATA_FOLDER+zip_folder)
for day_file in zip_file.infolist():
for i in items_anem:
if day_file.filename.endswith("anem" + str(i) +'_20Hz'+'.txt'):
df_temp=pd.read_csv(zip_file.open(day_file.filename), header=None, comment=',', error_bad_lines=False,usecols=columns_anem, index_col=time_stp_position_anem)
df_temp.index=pd.to_datetime(df_temp.index,format='%d.%m.%Y %H:%M:%S',errors='coerce')
df_temp=df_temp.resample(time_int).mean()[:-1]
df_temp.to_csv(AVERAGE_RES_FOLDER+'anem'+ str(i)+'.csv', header=None, index=True, sep=',', mode='a')
print('Anemometers OK')
print('')
# In[8]:
### Temperature averaging data ###
# ----------------------------------- #
print('Temperatures in progress...')
items_temp = [['Mat','North','East','South','West'],['Sensor Ground temperature [°C]','North temperature [°C]','East temperature [°C]','South temperature [°C]','West temperature [°C]']]
columns_temp=[0,2]
time_stp_position_temp=-1 #Respect to columns_anem
zip_folders=os.listdir(DATA_FOLDER)
for day,zip_folder in enumerate(zip_folders):
print("In progress: {}".format(zip_folder), end="\r")
zip_file = ZipFile(DATA_FOLDER+zip_folder)
k=0
for day_file in zip_file.infolist():
for i in items_temp[0]:
if day_file.filename.endswith('Temp'+i+'.txt'):
df_temp=pd.read_csv(zip_file.open(day_file.filename), header=None, comment=',', error_bad_lines=False,usecols=columns_temp, index_col=time_stp_position_temp)
df_temp.index=pd.to_datetime(df_temp.index,format='%d.%m.%Y %H:%M:%S',errors='coerce')
df_temp=df_temp.resample(time_int).mean()
df_temp.columns = [items_temp[1][k]]
if k==0:
df_tot=df_temp
else:
df_tot=df_tot.merge(df_temp,how='left', left_index=True,right_index=True)
k=k+1
if day==0:
df_tot.to_csv(AVERAGE_RES_FOLDER+'surf_temp'+'.csv', index=True, sep=',', mode='a')
else:
df_tot.to_csv(AVERAGE_RES_FOLDER+'surf_temp'+'.csv', index=True,header=None,sep=',', mode='a')
print('Temperatures OK')
print('')
# In[10]:
### Radiometer averaging data ###
# ----------------------------------- #
print('Radiometer in progress...')
columns_radio=list(range(10))+[11]
time_stp_position_temp=-1 #Respect to columns_radio
items_radio=['Pyranometer Upper Irradiance [W/m$^2$]','Pyranometer Lower Irradiance [W/m$^2$]',\
'Pyrgeometer Upper Irradiance [W/m$^2$]','Pyrgeometer Lower Irradiance [W/m$^2$]',\
'Albedo [-]','Net Solar radiation [W/m$^2$]','Net (total) radiation [W/m$^2$]',\
'Net Far Infrared radiation [W/m$^2$]','Sky temperature [°C]','Radiometer Ground temperature [°C]']
zip_folders=os.listdir(DATA_FOLDER)
for day,zip_folder in enumerate(zip_folders):
print("In progress: {}".format(zip_folder), end="\r")
zip_file = ZipFile(DATA_FOLDER+zip_folder)
for day_file in zip_file.infolist():
if day_file.filename.endswith('radiometre'+'.txt'):
df_temp=pd.read_csv(zip_file.open(day_file.filename), header=None, comment=',', error_bad_lines=False,usecols=columns_radio, index_col=time_stp_position_temp)
df_temp.index=pd.to_datetime(df_temp.index,format='%d.%m.%Y %H:%M:%S',errors='coerce')
df_temp=df_temp.resample(time_int).mean()
df_temp.columns = items_radio
if day==0:
df_temp.to_csv(AVERAGE_RES_FOLDER+'radiometer'+'.csv', index=True, sep=',', mode='a')
else:
df_temp.to_csv(AVERAGE_RES_FOLDER+'radiometer'+'.csv', index=True,header=None, sep=',', mode='a')
print('Temperatures OK')
print('JOB Finished')
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