lean+
continuous-integration/drone/push Build is passing Details

This commit is contained in:
Pablo Moyano 2020-07-13 01:31:02 +02:00
parent 6cdf4d5197
commit cadecba59a
12 changed files with 74 additions and 583 deletions

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

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

157
main.py
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@ -1,12 +1,10 @@
from flask import Flask, render_template, request from flask import Flask, render_template, request
from datetime import datetime from datetime import datetime
from probeutils import utils as probeutils
import re import re
import fnmatch import fnmatch
import os import os
import meinheld import meinheld
app = Flask(__name__) app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = "./dataset/" app.config['UPLOAD_FOLDER'] = "./dataset/"
@ -14,41 +12,10 @@ app.config['UPLOAD_FOLDER'] = "./dataset/"
app.config['MAX_CONTENT_LENGTH'] = 10000000000 # 10GB app.config['MAX_CONTENT_LENGTH'] = 10000000000 # 10GB
meinheld.set_max_content_length(100*1024*1024) 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. # Return our beautiful Bootstrap webpage. That we totally have.
@app.route('/') @app.route('/')
def upload(): def upload():
return render_template('upload.html', probes=probes) return render_template('upload.html')
# What happens when the files just don't fit # What happens when the files just don't fit
@app.errorhandler(413) @app.errorhandler(413)
@ -66,131 +33,13 @@ def upload_file():
if request.method == 'POST': if request.method == 'POST':
f = request.files['file'] 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 success webpage
return render_template('successful.html', url=url_download, tables=df_table) return render_template('successful.html')
else: else:
# No POST Found # No POST Found
return render_template('error.html') 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__': if __name__ == '__main__':
app.run() app.run()

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@ -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)

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Flask Flask
pandas pandas
meinheld meinheld
python-barcode

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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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{% extends "base.html" %} {% extends "base.html" %} {% block title %}Subida{% endblock %} {% block content %}
{% block title %}Subida{% endblock %}
{% block content %}
<!-- Row Header --> <!-- Row Header -->
<div class="px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center"> <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>
<div class="container"> <div class="container">
<div class="card-deck mb-3 text-center"></div> <form class="list-group list-group-flush" action="{{pagename}}/uploader" method="POST" enctype="multipart/form-data">
<!-- File input -->
<!-- Sensors row --> <div class="list-group-item" style="padding-left: 50px;">
<div class="row"> <input type="file" class="form-control-file" name="file" />
{% 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>
</div> </div>
{% endfor%}
<!-- 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> </div>
<!-- Setting up the modal foreach probe --> <!-- Force station -->
{% for i in probes %} <div class="form-group">
<div class="modal fade" id="upload{{i.sensor}}" role="dialog"> <input
<div class="modal-dialog modal-lg"> 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>
<!-- Modal content--> <label class="form-check-label" for="stations{{i.sensor}}" style="padding-left: 5px;">Selecciona la estación utilizada</label
<div class="modal-content"> >
<div class="modal-header"> <select name="stations{{i.sensor}}" id="stations{{i.sensor}}" disabled>
<h4 class="modal-title">Subir datos de {{ i.sensor }}</h4> {% for j in i.stations %}
<option value="{{ j }}">{{ j }}</option>
{% endfor %}
</select>
</div>
<button type="button" class="close" data-dismiss="modal"> <!-- Apply quality control -->
&times; <div class="list-group-item" style="padding-bottom: 50px;">
</button> <input
</div> 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 class="modal-body"> <!-- Submit -->
<input type="hidden" value="{{i.sensor}}" name="probe" />
<!-- Modal header --> <button type="submit" class="btn btn-primary btn-lg btn-block">
<div class="upload-header px-3 py-3 pt-md-5 pb-md-4 mx-auto text-center"> Subir CSV
<h2 class="display-5">{{ i.sensor }}</h2> </button>
</div> </form>
</div>
<div class="container"> <!-- Close container field -->
<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>
</form>
</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 -->
</div> <!-- Close container field -->
{% endblock %} {% endblock %}