Browse Source

lean+

master
Pablo Moyano 1 year ago
parent
commit
cadecba59a
  1. 3
      dataset/README.md
  2. 23
      docker-compose.yml
  3. 157
      main.py
  4. 293
      probeutils/utils.py
  5. 3
      requirements.txt
  6. BIN
      static/img/castaway.jpg
  7. BIN
      static/img/fire.jpg
  8. BIN
      static/img/gopro.png
  9. BIN
      static/img/phycoctd.jpg
  10. 1
      static/img/placeholder.svg
  11. BIN
      static/img/suna.jpg
  12. 179
      templates/upload.html

3
dataset/README.md

@ -1,2 +1 @@
This folder contains all the sensor data uploaded to the server
Barcode generator

23
docker-compose.yml

@ -2,26 +2,11 @@ version: '3.7'
services:
## TODO: Add true proxy WSGI Server instead of running the builtin
uploadtool:
ean13generator:
build: .
restart: unless-stopped
volumes:
- /mnt/storage/dataset-neo:/app/dataset
labels:
- traefik.enable=true
- traefik.http.routers.sdc-uploader.entryPoints=web-secure
- traefik.http.routers.sdc-uploader.rule=Host(`upload.med.upct.es`)
- traefik.http.routers.sdc-uploader.tls.certresolver=default
download:
image: abiosoft/caddy
restart: unless-stopped
volumes:
- /mnt/storage/dataset-neo:/srv
labels:
- traefik.enable=true
- traefik.http.routers.sdc-download.entryPoints=web-secure
- traefik.http.routers.sdc-download.rule=Host(`download.med.upct.es`)
- traefik.http.routers.sdc-download.tls.certresolver=default
- traefik.http.services.sdc-download.loadbalancer.server.port=2015
- traefik.http.routers.ean13generator.entryPoints=web-secure
- traefik.http.routers.ean13generator.rule=Host(`ean13.fosc.space`)
- traefik.http.routers.ean13generator.tls.certresolver=default

157
main.py

@ -1,12 +1,10 @@
from flask import Flask, render_template, request
from datetime import datetime
from probeutils import utils as probeutils
import re
import fnmatch
import os
import meinheld
app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = "./dataset/"
@ -14,41 +12,10 @@ app.config['UPLOAD_FOLDER'] = "./dataset/"
app.config['MAX_CONTENT_LENGTH'] = 10000000000 # 10GB
meinheld.set_max_content_length(100*1024*1024)
app.config['DOWNLOADS_URL'] = "https://download.med.upct.es/"
probes = [{
'sensor': 'SUNA',
'img': 'suna.jpg',
'active': ['SATSLF0037'],
'stations': ['M1', 'M2', 'M3']
}, {
'sensor': 'FIRe',
'img': 'fire.jpg',
'active': ['SATFIS0006'],
'stations': ['M1', 'M2', 'M3']
}, {
'sensor': 'PhycoCTD',
'img': 'phycoctd.jpg',
'active': ['phyco_v1', 'phyco_v2'],
'stations': ['M1', 'M2', 'M3']
}, {
'sensor': 'CastAway',
'img': 'castaway.jpg',
'active': ['CC1326008'],
'stations': ['M1', 'M2', 'M3']
}
#,{
# 'sensor': 'GoPro',
# 'img': 'gopro.png',
# 'active': ['gopro1'],
# 'stations': ['M1', 'M2', 'M3']
#}
]
# Return our beautiful Bootstrap webpage. That we totally have.
@app.route('/')
def upload():
return render_template('upload.html', probes=probes)
return render_template('upload.html')
# What happens when the files just don't fit
@app.errorhandler(413)
@ -66,131 +33,13 @@ def upload_file():
if request.method == 'POST':
f = request.files['file']
# Get which probe the user uploaded
probe = request.form.get('probe')
# Get selected probe
activeProbe = request.form.get('activeProbe')
# Check if its a valid file to upload
# TODO: Implement this method
# probeutils.check(probe, f)
# Check if folder exists
try:
if not os.path.exists(
os.path.join(app.config['UPLOAD_FOLDER'], probe)):
os.makedirs(os.path.join(app.config['UPLOAD_FOLDER'], probe))
if not os.path.exists(
os.path.join(app.config['UPLOAD_FOLDER'], probe, 'raw')):
os.makedirs(os.path.join(
app.config['UPLOAD_FOLDER'], probe, 'raw'))
except Exception:
return render_template('error.html')
# Strip station
# if forceStation is checked, override all station parsing
if (request.form.get("forceStation" + probe) != None):
station = request.form.get("stations" + probe)
else:
if (fnmatch.fnmatch((f.filename).upper(), '*M1*') or fnmatch.fnmatch((f.filename).upper(), 'M1*')):
station = 'M1'
elif (fnmatch.fnmatch((f.filename).upper(), "*M2*") or fnmatch.fnmatch((f.filename).upper(), "M2*")):
station = 'M2'
elif (fnmatch.fnmatch((f.filename).upper(), "*M3*") or fnmatch.fnmatch((f.filename).upper(), "M3*")):
station = 'M3'
# Date Parser of filename
match1 = re.search('\d{4}-\d{2}-\d{2}', f.filename)
if (match1 == None):
match1 = re.search('\d{2}-\d{2}-\d{4}', f.filename)
try:
date = datetime.strptime(match1.group(), '%d-%m-%Y').date()
except Exception:
# Error! More strange data format XD
match1 = re.search('\d{4}\d{2}\d{2}', f.filename)
if (match1 == None):
match1 = re.search('\d{2}\d{2}\d{4}', f.filename)
date = datetime.strptime(match1.group(), '%d%m%Y').date()
else:
date = datetime.strptime(match1.group(), '%Y%m%d').date()
else:
date = datetime.strptime(match1.group(), '%Y-%m-%d').date()
# Crafting the real overpowered name!!!!
filename = probe + '-' + station + '-'+ activeProbe + '-'+ date.strftime("%Y-%m-%d") + '.csv'
#print(filename)
# Setting the filePath and saving it
finalFilename = 'raw-'+filename
rawFilePath = os.path.join(app.config['UPLOAD_FOLDER'], probe, 'raw', finalFilename)
f.save(rawFilePath)
# Start with probe definition
if (probe == 'CastAway'):
''' CastAway Files '''
df_table = probeutils.process_castaway(rawFilePath)
elif (probe == 'SUNA'):
''' SUNA Files '''
df_table = probeutils.process_suna(rawFilePath)
elif (probe == 'FIRe'):
''' FIRe Files '''
df_table = probeutils.process_fire(rawFilePath)
elif (probe == 'PhycoCTD'):
''' PhycoCTD Files '''
df_table = probeutils.process_phyco(rawFilePath)
else:
''' Empty probe '''
df_table = "<div></div>"
# Save file on raw folder and create URL download
url_download = app.config['DOWNLOADS_URL'] + probe + "/" + finalFilename
# Return success webpage
return render_template('successful.html', url=url_download, tables=df_table)
return render_template('successful.html')
else:
# No POST Found
return render_template('error.html')
## Force regenerate QC
@app.route('/regenerate')
def regenerate():
error_list = []
#for each file in raw folder, execute all QC
PATH = './dataset/FIRe/raw'
for filename in os.listdir(PATH):
try:
filename_nn = probeutils.execution_NN(filename)
probeutils.execution_PAR(filename_nn)
except Exception as err:
#print(filename)
#print(repr(err))
error_list.append([filename, repr(err)])
#print('Regenerate FIRe done')
PATH = './dataset/PhycoCTD/raw'
for filename in os.listdir(PATH):
try:
probeutils.check_if_old_phyco(filename)
probeutils.execution_pb_phyco(filename)
except Exception as err:
#print(filename)
#print(repr(err))
error_list.append([filename, repr(err)])
#print('Regenerate Phyco done')
return render_template('regenerate.html', error_list=error_list)
if __name__ == '__main__':
app.run()

293
probeutils/utils.py

@ -1,293 +0,0 @@
from datetime import datetime
from shutil import copy2
import pandas as pd
import numpy as np
import os, csv
UPLOAD_FOLDER = './dataset/'
tableClass = 'table table-striped table-sm table-responsive'
def get_date(probe, file):
''' Test utils file '''
return datetime.now().strftime("%Y-%m-%d-%H:%M:%S")
# TODO:
# - Check if is a good file
#
#def checkUploadedFile(probe, file):
# return 1
# TODO:
# - clean the head of csv, need to extract info an remove the %% (maybe new file with metadata info?) [done]
# - create the empty csv, first row with headers [done]
# - desviation and more data things
def process_castaway(file):
try:
# Copy raw file to process folder
with open(file) as CastAwayFile:
filename = os.path.basename(CastAwayFile.name).strip('raw-')
processFilePath = os.path.join(
UPLOAD_FOLDER, 'CastAway', filename)
#copy2(file, processFilePath)
# Getting some metadata info
#with open(file, newline='') as castfile:
# lines = castfile.readlines()
# device = lines[0].split(',')[1].replace('\r\n', '')
# filename = lines[1].split(',')[1].replace('\r\n', '')
# start_latitude = lines[9].split(',')[1].replace('\r\n', '')
# start_longitude = lines[10].split(',')[1].replace('\r\n', '')
# start_altitude = lines[11].split(',')[1].replace('\r\n', '')
# castfile.close()
# Opening the csv with pandas
df = pd.read_csv(file, skiprows=28)
# Extract perfil bajada, el 1 es por el header
index_max = df['Depth (Meter)'].idxmax() + 1
#df_perfilBajada = df[df['depth'].between(0, df['depth'].max())] # No funciona muy bien
# Limitamos a solo el perfil de bajada
df_perfilBajada = df[:index_max]
# Guardamos solo el perfilBajada en carpeta PB
if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'CastAway', 'PB')):
os.makedirs(os.path.join(UPLOAD_FOLDER, 'CastAway', 'PB'))
filenamePB = filename.strip('.csv') + '-PB.csv'
perfilBajadaFilePath = os.path.join(
UPLOAD_FOLDER, 'CastAway', 'PB', filenamePB)
df_perfilBajada.to_csv(perfilBajadaFilePath, index=False)
# Trying to show Dataframe on webpage
return df.to_html(classes=tableClass)
except Exception as ex:
print('Exception: '+repr(ex))
return ex
def process_suna(file):
try:
df = pd.read_csv(file, encoding="ISO-8859-1", header=None)
#df.columns = ['fechaHora', 'INSTRUMENT', 'Start-time', 'Nitrato(uMol/L)','Nitrato(MG/L)', 'ERROR', 'T_lamp', ]
#if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'SUNA', 'HEAD')):
# os.makedirs(os.path.join(UPLOAD_FOLDER, 'SUNA', 'HEAD'))
# Return webpage
return df.to_html(classes=tableClass)
except Exception as ex:
print('Exception: '+repr(ex))
return ex
# TODO:
# - Ask for FIRe examples, actually only bin files found (done)
# - Extract file to process folder (done)
# - Save a File with PAR info
# - Headers on email (ask for new headers)[done]
# - Remove negative values (this, done)
# - Arrange similar windows depth and do measure
def process_fire(file):
''' Processing FIRe '''
try:
# Copy raw file to process folder
with open(file) as FIReFile:
filename_raw = os.path.basename(FIReFile.name)
filename = os.path.basename(FIReFile.name).strip('raw-')
#raw_file_path = os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', filename_raw)
processFilePath = os.path.join(
UPLOAD_FOLDER, 'FIRe', filename)
#copy2(file, processFilePath)
# First, need to check the csv headers
# Open the process file with pandas
df = pd.read_csv(file, header=None)
# Headers (now working fine)
df.columns = ['fechaHora', 'estacion', 'fecha', 'hora', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light', 'ETR', 'coma1', 'coma2', 'coma3', 'coma4', 'coma5', 'coma6','error_norm', 'PAR', 'V', 'cero1', 'cero2', 'cero3', 'cero4', 'raro']
df.loc[:, 'coma1'] = 0
df.loc[:, 'coma2'] = 0
df.loc[:, 'coma3'] = 0
df.loc[:, 'coma4'] = 0
df.loc[:, 'coma5'] = 0
df.loc[:, 'coma6'] = 0
# Fixing empty values
#df.to_csv(os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', 'raw-'+filename), index=False)
filename_nn = execution_NN(filename_raw)
execution_PAR(filename_nn)
return df.to_html(classes=tableClass)
except Exception as ex:
print('Exception: '+repr(ex))
return ex
# TODO:
# - Only perfil bajada (done)
def process_phyco(file):
''' Processing PhycoCTD'''
try:
# Copy raw file to process folder
with open(file, "r+") as phycoFile:
# Sustract raw- of filename
filename_raw = os.path.basename(phycoFile.name)
filename = os.path.basename(phycoFile.name).strip('raw-')
processFilePath = os.path.join(
UPLOAD_FOLDER, 'PhycoCTD', filename)
#copy2(file, processFilePath)
# Working with the process file
df = pd.read_csv(file, delimiter=';')
check_if_old_phyco(filename_raw)
execution_pb_phyco(filename_raw)
# Return webpage
return df.to_html(classes=tableClass)
except Exception as ex:
print('Exception: '+repr(ex))
return ex
def check_if_old_phyco(filename):
# Checking if old file csv
PATH = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
with open(PATH, "r+") as phycoFile:
# Check if old version
line = phycoFile.readline()
if (',' in line):
old = True
else:
old = False
if (old == True):
df_old = pd.read_csv(PATH, header=None, skiprows=1)
if (len(df_old.columns) == 16):
df_old.columns = ['station', 'latitude', 'longitude', 'time', 'depth', 'temp1', 'temp2', 'cdom[gain]',
'cdom[ppb]', 'cdom[mv]', 'pe[gain]', 'pe[ppb]', 'pe[mv]', 'chl[gain]', 'chl[ppb]', 'chl[mv]']
else:
df_old.columns = ['station', 'time', 'depth', 'temp1', 'temp2', 'cdom[gain]', 'cdom[ppb]',
'cdom[mv]', 'pe[gain]', 'pe[ppb]', 'pe[mv]', 'chl[gain]', 'chl[ppb]', 'chl[mv]']
raw_path = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
df_old.to_csv(raw_path, index=False, sep=';')
def execution_pb_phyco(filename):
# Guardamos solo el perfilBajada
if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB')):
os.makedirs(os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB'))
PATH = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'raw', filename)
df = pd.read_csv(PATH, delimiter=';')
# Checking if NaN values exists [for hack lab version csv upload]
if (df['temp2'].isnull().sum() > 0):
df.loc[:, 'temp2'] = 0
df = df.dropna()
# Extract perfil bajada, el 1 es por el header
index_max = df['depth'].idxmax() + 1
#df_perfilBajada = df[df['depth'].between(0, df['depth'].max())] # No funciona muy bien
# Limitamos a solo el perfil de bajada
df_pb= df[:index_max]
filename_pb = filename.strip('raw-').strip('.csv') + '-PB.csv'
pb_path = os.path.join(UPLOAD_FOLDER, 'PhycoCTD', 'PB', filename_pb)
df_pb.to_csv(pb_path, sep=';', index=False)
def execution_NN(filename):
PATH = os.path.join(UPLOAD_FOLDER, 'FIRe', 'raw', filename)
df = pd.read_csv(PATH, header=None)
# Headers (now working fine)
df.columns = ['fechaHora', 'estacion', 'fecha', 'hora', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light',
'ETR', 'coma1', 'coma2', 'coma3', 'coma4', 'coma5', 'coma6', 'error_norm', 'PAR', 'V', 'cero1', 'cero2', 'cero3', 'cero4', 'raro']
df.loc[:, 'coma1'] = 0
df.loc[:, 'coma2'] = 0
df.loc[:, 'coma3'] = 0
df.loc[:, 'coma4'] = 0
df.loc[:, 'coma5'] = 0
df.loc[:, 'coma6'] = 0
# NonNegative values rutine
if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN')):
os.makedirs(os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN'))
# Remove rows with negatives values
df_nn = df[(df.iloc[:, 4:27] >= 0).all(1)]
filename_nn = filename.strip('raw-').strip('.csv') + '-NN.csv'
nonnegative_path = os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN', filename_nn)
df_nn.to_csv(nonnegative_path, index=False)
return filename_nn
def execution_PAR(filename):
# PAR rutine
if not os.path.exists(os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR')):
os.makedirs(os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR'))
PATH = os.path.join(UPLOAD_FOLDER, 'FIRe', 'NN', filename)
df = pd.read_csv(PATH)
# PAR execution
PAR_columns = ['estacion', 'fecha', 'profundidad', 'Fo', 'Fm', 'Fv', 'Fv/Fm', 'p', 'Abs_rel', 'Abs_abs', 'led_light',
'ETR', 'error_norm', 'PAR']
df_PAR = pd.DataFrame(columns=PAR_columns)
index_max = df['profundidad'].idxmax()
index_min = df['profundidad'].idxmin() + 1
depth_list = df[index_max:index_min]['profundidad'].to_list()
last_value = df['profundidad'].max()
similar_depth = []
for i in range(len(depth_list)):
#print(depth_list[i])
if (abs(last_value - depth_list[i]) <= 2000):
last_value = depth_list[i]
similar_depth.append(depth_list[i])
elif (abs(last_value - depth_list[i]) >= 6000):
## Save the actual list to DataFrame
#print(similar_depth)
index_first = pd.to_numeric(df.index[df['profundidad'] == similar_depth[0]])[0]
index_last = pd.to_numeric(df.index[df['profundidad'] == similar_depth[-1]])[0] + 1
df_range = df.iloc[index_first:index_last]
# Working with df_range
estacion = df['estacion'][0]
fecha = df['fecha'][0]
profundidad = df_range['profundidad'].mean()
Fo = df_range['Fo'].mean()
Fm = df_range['Fm'].mean()
Fv = df_range['Fv'].mean()
FvFm = df_range['Fv/Fm'].mean()
p = df_range['p'].mean()
Abs_rel = df_range['Abs_rel'].mean()
Abs_abs = df_range['Abs_abs'].mean()
led_light = df_range['led_light'].mean()
ETR = df_range['ETR'].mean()
error_norm = df_range['error_norm'].mean()
PAR = df_range['PAR'].mean()
data = [estacion, fecha, profundidad, Fo, Fm, Fv, FvFm, p, Abs_rel, Abs_abs, led_light, ETR, error_norm, PAR]
row = pd.Series(data, index=PAR_columns)
df_PAR = df_PAR.append(row, ignore_index=True)
## Empty the list
similar_depth = []
last_value = depth_list[i]
## Adding to the new list
similar_depth.append(depth_list[i])
# Saving the DataFrame
# TODO: check last values, around 400 depth
filenamePAR = filename.strip('-NN.csv') + '-PAR.csv'
PARFilePath = os.path.join(UPLOAD_FOLDER, 'FIRe', 'PAR', filenamePAR)
df_PAR.to_csv(PARFilePath, index=False)

3
requirements.txt

@ -1,3 +1,4 @@
Flask
pandas
meinheld
meinheld
python-barcode

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static/img/castaway.jpg

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static/img/fire.jpg

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static/img/gopro.png

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static/img/phycoctd.jpg

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static/img/placeholder.svg

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<svg width="200" height="200" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 200 200" preserveAspectRatio="none"><defs><style type="text/css">#holder_171aa8443cc text { fill:rgba(255,255,255,.75);font-weight:normal;font-family:Helvetica, monospace;font-size:10pt } </style></defs><g id="holder_171aa8443cc"><rect width="200" height="200" fill="#777"></rect><g><text x="74.41666603088379" y="104.25000009536743">200x200</text></g></g></svg>

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static/img/suna.jpg

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179
templates/upload.html

@ -1,127 +1,78 @@
{% extends "base.html" %}
{% block title %}Subida{% endblock %}
{% block content %}
{% extends "base.html" %} {% block title %}Subida{% endblock %} {% block content %}
<!-- Row Header -->
<div class="px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center">
<h1 class="display-4">Sensores</h1>
<h1 class="display-4">Upload</h1>
</div>
<div class="container">
<div class="card-deck mb-3 text-center"></div>
<!-- Sensors row -->
<div class="row">
{% for i in probes %}
<div class="col-sm">
<div class="card mb-4 shadow-sm">
<div class="card-header">
<h4 class="my-0 font-weight-normal">{{ i.sensor }}</h4>
</div>
<div class="card-body">
<div class="text-center">
<img src="{{ url_for('static',filename='img/'+i.img) }}" class="rounded" alt="..."
height="200px" width="200px" />
</div>
</div>
<button type="button" class="btn btn-primary" data-toggle="modal" data-target="#upload{{i.sensor}}">
Subir datos
</button>
</div>
<form class="list-group list-group-flush" action="{{pagename}}/uploader" method="POST" enctype="multipart/form-data">
<!-- File input -->
<div class="list-group-item" style="padding-left: 50px;">
<input type="file" class="form-control-file" name="file" />
</div>
{% endfor%}
</div>
<!-- Setting up the modal foreach probe -->
{% for i in probes %}
<div class="modal fade" id="upload{{i.sensor}}" role="dialog">
<div class="modal-dialog modal-lg">
<!-- Modal content-->
<div class="modal-content">
<div class="modal-header">
<h4 class="modal-title">Subir datos de {{ i.sensor }}</h4>
<button type="button" class="close" data-dismiss="modal">
&times;
</button>
</div>
<div class="modal-body">
<!-- Modal header -->
<div class="upload-header px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center">
<h2 class="display-5">{{ i.sensor }}</h2>
</div>
<div class="container">
<div class="text-center">
<!-- Modal form -->
<form class="list-group list-group-flush" action="{{pagename}}/uploader" method="POST"
enctype="multipart/form-data">
<!-- File input -->
<div class="list-group-item" style="padding-left: 50px;">
<input type="file" class="form-control-file" name="file" />
</div>
<!-- Sensor select -->
<div class="form-group required" style="padding-top: 10px;">
<label class="form-check-label" for="activeProbe" style="padding-left: 5px;">Escoge
el sensor utilizado</label>
<select name="activeProbe" id="activeProbe">
{% for j in i.active %}
<option value="{{ j }}">{{ j }}</option>
{% endfor %}
</select>
</div>
<!-- Force station -->
<div class="form-group">
<input class="form-check-input" type="checkbox" name="forceStation{{i.sensor}}"
id="forceStation{{i.sensor}}"
onchange="toggleSelect('forceStation{{i.sensor}}', 'stations{{i.sensor}}')">
<label class="form-check-label" for="forceStation{{i.sensor}}"
style="padding-left: 5px;">
Forzar estación
</label>
<label class="form-check-label" for="stations{{i.sensor}}"
style="padding-left: 5px;">Selecciona la estación utilizada</label>
<select name="stations{{i.sensor}}" id="stations{{i.sensor}}" disabled>
{% for j in i.stations %}
<option value="{{ j }}">{{ j }}</option>
{% endfor %}
</select>
</div>
<!-- Apply quality control -->
<div class="list-group-item" style="padding-bottom: 50px;">
<input class="form-check-input" type="checkbox" id="autoSizingCheck" checked>
<label class="form-check-label" for="autoSizingCheck" style="padding-left: 5px;">
Aplicar control de calidad
</label>
</div>
<!-- Submit -->
<input type="hidden" value="{{i.sensor}}" name="probe" />
<button type="submit" class="btn btn-primary btn-lg btn-block">Subir CSV</button>
<!-- Sensor select -->
<div class="form-group required" style="padding-top: 10px;">
<label class="form-check-label" for="activeProbe" style="padding-left: 5px;">Escoge el sensor utilizado</label
>
<select name="activeProbe" id="activeProbe">
{% for j in i.active %}
<option value="{{ j }}">{{ j }}</option>
{% endfor %}
</select>
</div>
</form>
<!-- Force station -->
<div class="form-group">
<input
class="form-check-input"
type="checkbox"
name="forceStation{{i.sensor}}"
id="forceStation{{i.sensor}}"
onchange="toggleSelect('forceStation{{i.sensor}}', 'stations{{i.sensor}}')"
/>
<label
class="form-check-label"
for="forceStation{{i.sensor}}"
style="padding-left: 5px;"
>
Forzar estación
</label>
<label class="form-check-label" for="stations{{i.sensor}}" style="padding-left: 5px;">Selecciona la estación utilizada</label
>
<select name="stations{{i.sensor}}" id="stations{{i.sensor}}" disabled>
{% for j in i.stations %}
<option value="{{ j }}">{{ j }}</option>
{% endfor %}
</select>
</div>
</div>
</div> <!-- Close Modal Container Body -->
</div> <!-- Close Modal Body -->
</div> <!-- Close Modal Content -->
</div> <!-- Close Modal dialog -->
</div> <!-- Close Modal -->
{% endfor %}
<!-- End Sensors Modals -->
<!-- Apply quality control -->
<div class="list-group-item" style="padding-bottom: 50px;">
<input
class="form-check-input"
type="checkbox"
id="autoSizingCheck"
checked
/>
<label
class="form-check-label"
for="autoSizingCheck"
style="padding-left: 5px;"
>
Aplicar control de calidad
</label>
</div>
</div> <!-- Close container field -->
<!-- Submit -->
<input type="hidden" value="{{i.sensor}}" name="probe" />
<button type="submit" class="btn btn-primary btn-lg btn-block">
Subir CSV
</button>
</form>
</div>
<!-- Close container field -->
{% endblock %}
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