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scisat.py
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scisat.py
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#
# Micro-application to visualize SCISAT data.
#
# Three main charts:
# 1. Gas concentration in parts per volume (ppv) visualized on a world map
# 2. Gas concentration in parts per volume (ppv) over the selected altitude
# 3. Evolution of the gas concentration in parts per volume (ppv) over the years
#
# @source https://github.com/asc-csa/Scisat-App
# @author Emiline Filion - Canadian Space Agency
#
# Modification History:
#
#
import dash
import cartopy.feature as cf
import configparser
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import plotly.express as px
import pandas as pd
import datetime as dt
from dash.dependencies import Input, Output, State
import flask
from io import StringIO
from flask_babel import _ ,Babel
from flask import session, redirect, url_for, make_response
import urllib.parse
import dash_table as dst
from dash_table.Format import Format, Scheme
from scipy.io import netcdf #### <--- This is the library to import data
import numpy as np
from os import path
import os.path
class CustomDash(dash.Dash):
analytics_code = ''
analytics_footer = ''
lang = ''
header = ''
footer = ''
meta_html = ''
app_header = ''
app_footer = ''
def set_analytics(self, code):
self.analytics_code = code
def set_analytics_footer(self, code):
self.analytics_footer = code
def set_lang(self, lang):
self.lang = lang
def set_header(self, header):
self.header = header
def set_footer(self, footer):
self.footer = footer
def set_meta_tags(self, meta_html):
self.meta_html = meta_html
def set_app_header(self, header):
self.app_header = header
def set_app_footer(self, footer):
self.app_footer = footer
def interpolate_index(self, **kwargs):
# Inspect the arguments by printing them
return '''
<!DOCTYPE html>
<html lang='{lang}'>
<head>
{metas}
{meta}
{analytics}
{favicon}
<title>
{title}
</title>
<style id='dash_components_css'></style>
{css}
</head>
<body id='wb-cont'>
{header}
<main property="mainContentOfPage" typeof="WebPageElement" class="container">
{app_header}
{app_entry}
{app_footer}
</main>
<div class="global-footer">
<footer id="wb-info">
{footer}
{config}
{scripts}
{renderer}
{analytics_footer}
</footer>
</div>
</body>
</html>
'''.format(
app_entry=kwargs['app_entry'],
config=kwargs['config'],
scripts=kwargs['scripts'],
renderer=kwargs['renderer'],
metas = kwargs['metas'],
favicon = kwargs['favicon'],
css = kwargs['css'],
title = kwargs['title'],
analytics = self.analytics_code,
analytics_footer = self.analytics_footer,
meta = self.meta_html,
lang = self.lang,
header = self.header,
footer = self.footer,
app_header = self.app_header,
app_footer = self.app_footer
)
#==========================================================================================
# load data and transform as needed
external_stylesheets = [
'https://canada.ca/etc/designs/canada/wet-boew/css/wet-boew.min.css',
'https://canada.ca/etc/designs/canada/wet-boew/css/theme.min.css',
'https://use.fontawesome.com/releases/v5.8.1/css/all.css'
] # Link to external CSS
external_scripts = [
'//ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js',
'https://canada.ca/etc/designs/canada/wet-boew/js/wet-boew.min.js',
'https://canada.ca/etc/designs/canada/wet-boew/js/theme.min.js',
'assets/scripts.js'
]
DATA_VERSION = 'ACEFTS_L2_v5p2'
# Loads the config file
def get_config_dict():
config = configparser.RawConfigParser()
#config.read('config.cfg')
config.read('/home/ckanportal/App-Launcher/config.cfg')
DATA_VERSION = config['SCISAT']['DATA_VERSION']
print("SCISAT Data version: " + DATA_VERSION)
if not hasattr(get_config_dict, 'config_dict'):
get_config_dict.config_dict = dict(config.items('TOKENS'))
return get_config_dict.config_dict
def generate_meta_tag(name, content):
return "<meta name=\"" + name + "\" content=\"" + content + "\">"
def generate_meta_tag_with_title(name, content, title):
return "<meta name=\"" + name + "\" title=\"" + title + "\" content=\"" + content + "\">"
# Runs the application based on what executed this file.
if __name__ == '__main__':
from header_footer import gc_header_en, gc_footer_en, gc_header_fr, gc_footer_fr, app_title_en, app_title_fr, app_footer_en, app_footer_fr
from config import Config
#print ('DEBUG: SCISAT Main Block used')
if(path.exists(os.path.dirname(os.path.abspath(__file__)) + r"/analytics.py")):
from .analytics import analytics_code, analytics_footer
else:
analytics_code = '<h1>Did not load things</h1>'
analytics_footer = '<h1>Did not load things footer</h1>'
app_config = Config()
path_data=app_config.DATA_PATH
prefixe= app_config.APP_PREFIX
tokens = get_config_dict()
app = CustomDash(
__name__,
meta_tags=[{"name": "viewport", "content": "width=device-width"}],
external_stylesheets=external_stylesheets,
external_scripts=external_scripts,
# analytics = analytics_code
)
else :
from .header_footer import gc_header_en, gc_footer_en, gc_header_fr, gc_footer_fr, app_title_en, app_title_fr, app_footer_en, app_footer_fr
from .config import Config
#print ('DEBUG: SCISAT Alternate Block used')
if(path.exists(os.path.dirname(os.path.abspath(__file__)) + r"/analytics.py")):
from .analytics import analytics_code, analytics_footer
else:
analytics_code = ''
analytics_footer = ''
app_config = Config()
path_data=app_config.DATA_PATH
prefixe= app_config.APP_PREFIX
tokens = get_config_dict()
app = CustomDash(
__name__,
requests_pathname_prefix=prefixe,
meta_tags=[{"name": "viewport", "content": "width=device-width"}],
external_stylesheets=external_stylesheets,
external_scripts=external_scripts,
# analytics = analytics_code
)
meta_html = ''
if app_config.DEFAULT_LANGUAGE == 'en':
app.set_header(gc_header_en)
app.set_footer(gc_footer_en)
meta_html += generate_meta_tag(
'description',
'Explore the composition of the Earth’s atmosphere with data from the SCISAT satellite! SCISAT has been monitoring the atmospheric concentrations of ozone and 70 other gases since 2003.'
)
meta_html += generate_meta_tag('keywords', '')
meta_html += generate_meta_tag('dcterms.title', 'SCISAT : data exploration application for atmospheric composition')
meta_html += generate_meta_tag_with_title('dcterms.language', 'eng', 'ISO639-2')
meta_html += generate_meta_tag('dcterms.creator', 'Canadian Space Agency')
meta_html += generate_meta_tag('dcterms.accessRights', '2')
meta_html += generate_meta_tag('dcterms.service', 'CSA-ASC')
app.title="SCISAT : data exploration application for atmospheric composition"
app.set_app_header(app_title_en)
app.set_app_footer(app_footer_en)
else:
app.set_header(gc_header_fr)
app.set_footer(gc_footer_fr)
meta_html += generate_meta_tag(
'description',
"Explorez la composition de l’atmosphère terrestre avec les données du satellite SCISAT! SCISAT surveille les concentrations atmosphériques d'ozone et de 70 gaz supplémentaires depuis 2003."
)
meta_html += generate_meta_tag('keywords', '')
meta_html += generate_meta_tag('dcterms.title', 'SCISAT : application d’exploration des données de composition atmosphérique ')
meta_html += generate_meta_tag_with_title('dcterms.language', 'fra', 'ISO639-2')
meta_html += generate_meta_tag('dcterms.creator', 'Agence spatiale canadienne')
meta_html += generate_meta_tag('dcterms.accessRights', '2')
meta_html += generate_meta_tag('dcterms.service', 'CSA-ASC')
app.title="SCISAT : application d’exploration des données de composition atmosphérique"
app.set_app_header(app_title_fr)
app.set_app_footer(app_footer_fr)
app.set_meta_tags(meta_html)
app.set_analytics(analytics_code)
app.set_analytics_footer(analytics_footer)
app.set_lang(app_config.DEFAULT_LANGUAGE)
server = app.server
server.config['SECRET_KEY'] = tokens['secret_key'] # Setting up secret key to access flask session
babel = Babel(server) # Hook flask-babel to the app
# Loads data file based on values provided into a pandas dataframe.
def data_reader(file,path_to_files,start_date=0,end_date=0,lat_min=-90,lat_max=90,lon_min=-180,lon_max=180,alt_range=[0,150]) :
"""
Parameters
----------
file : String
Name of data file.
path_to_files : String
Path to the data files.
start_date : Datetime, optional
First day in the date range selected by user. The default is the first day of data available.
end_date : Datetime, optional
Last day in the date range selected by user. The default is the last day of data available.
lat_min : float, optional
Minimum latitude selected by user. The default is -90.
lat_max : float, optional
Maximum latitude selected by user. The default is 90.
lon_min : float, optional
Minimum longitude selected by user. The default is -180.
lon_max : float, optional
Maximum longitude selected by user. The default is 180.
alt_range : List
Range of alitutudes selected. Default is [0,150]
Returns
-------
df : DATAFRAME
Dataframe of all the gaz concentrations with columns :
Altitudes (from 0.5 to 149.5), Mean on altitude (Alt_Mean), date,
Latitude (lat) and Longitude (long)
"""
if data_reader.page_df.size != 0:
return data_reader.page_df
#print('\nDEBUG: entering data_reader()')
#start_time1 = time.time()
print("SCISAT Data version: " + DATA_VERSION)
print('data_reader() -> file: ' + file)
#print('data_reader() -> datareader path: ' + path_to_files)
if type(file)==list:
file=file[0]
gaz = file.strip().split('.')[0].strip().split('_')[3:]
if len(gaz)>1:
gaz = gaz[0]+'_'+gaz[1]
else:
gaz=gaz[0]
name=path_to_files+'/'+file
nc = netcdf.netcdf_file(name,'r')
#print('DEBUG: data_reader() - Time spent so far (#1): ' + str(time.time() - start_time1))
#Trier / définir rapido les données et les variables
fillvalue1 = -999.
months=np.copy(nc.variables['month'][:])
years = np.copy(nc.variables['year'][:])
days = np.copy(nc.variables['day'][:])
lat = np.copy(nc.variables['latitude'][:])
long =np.copy( nc.variables['longitude'][:])
alt = np.copy(nc.variables['altitude'][:])
#valeurs de concentration [ppv]
data = np.copy(nc.variables[gaz][:])
#Remplacer les données vides
data[data == fillvalue1] = np.nan
#Choisir les données dans l'intervalle de l'altitude
data = data[:,alt_range[0]:alt_range[1]]
df = pd.DataFrame(data,columns=alt[alt_range[0]:alt_range[1]])
#print('DEBUG: Number of elements in the dataframe: ' + str(df.size))
#print('DEBUG: data_reader() - Time spent so far (#2): ' + str(time.time() - start_time1))
#Trie données abérrantes
# TODO: This part takes a long time. We should optmize it. numpy.nan is too slow
#slow
df[df>1e-5]=np.nan
#slow
std=df.std()
mn=df.mean()
maxV = mn+3*std
minV = mn-3*std
# slow
df[df>maxV]=np.nan
#slow
df[df<minV]=np.nan
#print('DEBUG: data_reader() - Time spent so far (#3): ' + str(time.time() - start_time1))
#Colonne de dates
date=[]
nbDays = len(days)
#print('DEBUG: Number of days to loop: ' + str(nbDays))
date = np.array([dt.datetime(int(years[i]), int(months[i]), int(days[i])) for i in range (nbDays)])
#print('DEBUG: data_reader() - Time spent so far (#4): ' + str(time.time() - start_time1))
data_meanAlt = np.nanmean(df,1)
df['Alt_Mean'] = data_meanAlt
df['date'] = date
df['lat'] = lat
df['long'] = long
if start_date!=0 and end_date!=0 :
df=df[np.where(df['date']>start_date,True,False)]
df=df[np.where(df['date']<end_date,True,False)]
#filters the data based on min/max longitude/latitude
df=df[np.where(df['lat']>lat_min,True,False)]
df=df[np.where(df['lat']<lat_max,True,False)]
df=df[np.where(df['long']>lon_min,True,False)]
df=df[np.where(df['long']<lon_max,True,False)]
#print('DEBUG: end of data_reader() - TOTAL Time spent: ' + str(time.time() - start_time1) + '\n\n')
data_reader.page_df = df
return df
data_reader.page_df = pd.DataFrame()
# Returns a binned dataframe with the provided steps.
def databin(df, step):
"""
Create data bins of specified steps in terms of longitude and latitude.
Parameters
----------
start_date : Datetime
First day in the date range selected by user. The default is the first day of data available.
end_date : Datetime
Last day in the date range selected by user. The default is the last day of data available.
lat_min : float
Minimum value of the latitude stored as a float.
lat_max : float
Maximum value of the latitude stored as a float.
lon_min : float
Minimum value of the longitude stored as a float.
lon_max : float
Maximum value of the longitude stored as a float.
gaz_list : list
Gas name strings stored in a list (e.g. ['Ozone'])
alt_range : List
Range of altitudes
step : float
Size of bins in terms of lat/long degrees
Returns
-------
Dataframe
A dataframe contained the binned data provided in steps of specified degrees.
"""
# We create a binning map
#print('\n\nDEBUG: entering databin()')
#start_time1 = time.time()
to_bin = lambda x: np.round(x / step) * step
#print('DEBUG: databin() - Time spent so far (#1): ' + str(time.time() - start_time1))
# We map the current data into the bins
# TODO: This part takes a long time, but it looks like we already use the optimized way
df["lat"] = df['lat'].map(to_bin)
df["long"] = df['long'].map(to_bin)
# We return a mean value of all overlapping data to ensure there are no overlaps
#print('DEBUG: end of databin() - TOTAL Time spent: ' + str(time.time() - start_time1) + '\n\n')
return df.groupby(["lat", "long"]).mean().reset_index()
# Dropdown options
#======================================================================================
# Controls for webapp
gaz_name_options = [
{'label': _('Acetone'), 'value': DATA_VERSION + '_C3H6O.nc'},
{'label': _('Acetonitrite'), 'value': DATA_VERSION + '_CH3CN.nc'},
{'label': _('Acetylene'), 'value': DATA_VERSION + '_C2H2.nc'},
{'label': _('Carbon dioxide'), 'value': DATA_VERSION + '_CO2.nc'},
{'label': _('Carbon dioxide 627'), 'value': DATA_VERSION + '_CO2_627.nc'},
{'label': _('Carbon dioxide 628'), 'value': DATA_VERSION + '_CO2_628.nc'},
{'label': _('Carbon dioxide 636'), 'value': DATA_VERSION + '_CO2_636.nc'},
{'label': _('Carbon dioxide 637'), 'value': DATA_VERSION + '_CO2_637.nc'},
{'label': _('Carbon dioxide 638'), 'value': DATA_VERSION + '_CO2_638.nc'}, #9
{'label': _('Carbon monoxide'), 'value': DATA_VERSION + '_CO.nc'},
{'label': _('Carbon monoxide 27'), 'value': DATA_VERSION + '_CO_27.nc'},
{'label': _('Carbon monoxide 28'), 'value': DATA_VERSION + '_CO_28.nc'},
{'label': _('Carbon monoxide 36'), 'value': DATA_VERSION + '_CO_36.nc'},
{'label': _('Carbon monoxide 38'), 'value': DATA_VERSION + '_CO_38.nc'}, #14
{'label': _('Carbon tetrachloride'), 'value': DATA_VERSION + '_CCl4.nc'},
{'label': _('Carbon tetrafluoride'), 'value': DATA_VERSION + '_CF4.nc'},
{'label': _('Carbonyl chlorofluoride'), 'value': DATA_VERSION + '_COClF.nc'},
{'label': _('Carbonyl fluoride'), 'value': DATA_VERSION + '_COF2.nc'},
{'label': _('Carbonyl sulfide'), 'value': DATA_VERSION + '_OCS.nc'},
{'label': _('Carbonyl sulfide 623'), 'value': DATA_VERSION + '_OCS_623.nc'},
{'label': _('Carbonyl sulfide 624'), 'value': DATA_VERSION + '_OCS_624.nc'},
{'label': _('Carbonyl sulfide 632'), 'value': DATA_VERSION + '_OCS_632.nc'},
{'label': _('Chlorine monoxide'), 'value': DATA_VERSION + '_ClO.nc'},
{'label': _('Chlorine nitrate'), 'value': DATA_VERSION + '_ClONO2.nc'},
{'label': _('Chloromethane'), 'value': DATA_VERSION + '_CH3Cl.nc'}, #25
{'label': _('Dichlorodifluoromethane'), 'value': DATA_VERSION + '_CCl2F2.nc'},
{'label': _('Difluorochloromethane'), 'value': DATA_VERSION + '_CHF2Cl.nc'},
{'label': _('Dinitrogen pentaoxide'), 'value': DATA_VERSION + '_N2O5.nc'}, #28
{'label': _('Ethane'), 'value': DATA_VERSION + '_C2H6.nc'},
{'label': _('Formaldehyde'), 'value': DATA_VERSION + '_H2CO.nc'},
{'label': _('Formic acid'), 'value': DATA_VERSION + '_HCOOH.nc'}, #31
{'label': _('GLC'), 'value': DATA_VERSION + '_GLC.nc'},
{'label': _('Hydrochlorofluorocarbon 141b'), 'value': DATA_VERSION + '_HCFC141b.nc'},
{'label': _('Hydrochlorofluorocarbon 142b'), 'value': DATA_VERSION + '_HCFC142b.nc'},
{'label': _('Hydrochloric acid'), 'value': DATA_VERSION + '_HCl.nc'},
{'label': _('Hydrofluorocarbon 134a'), 'value': DATA_VERSION + '_HFC134a.nc'},
{'label': _('Hydrogen cyanide'), 'value': DATA_VERSION + '_HCN.nc'},
{'label': _('Hydrogen fluoride'), 'value': DATA_VERSION + '_HF.nc'},
{'label': _('Hydrogen peroxide'), 'value': DATA_VERSION + '_H2O2.nc'}, #39
{'label': _('Methane'), 'value': DATA_VERSION + '_CH4.nc'},
{'label': _('Methane 212'), 'value': DATA_VERSION + '_CH4_212.nc'},
{'label': _('Methane 311'), 'value': DATA_VERSION + '_CH4_311.nc'},
{'label': _('Methanol'), 'value': DATA_VERSION + '_CH3OH.nc'}, #43
{'label': _('Nitric acid'), 'value': DATA_VERSION + '_HNO3.nc'},
{'label': _('Nitric acid 156'), 'value': DATA_VERSION + '_HNO3_156.nc'},
{'label': _('Nitrogen'), 'value': DATA_VERSION + '_N2.nc'},
{'label': _('Nitrogen dioxide'), 'value': DATA_VERSION + '_NO2.nc'},
{'label': _('Nitrogen dioxide 656'), 'value': DATA_VERSION + '_NO2_656.nc'},
{'label': _('Nitrous monoxide 447'), 'value': DATA_VERSION + '_NO.nc'},
{'label': _('Nitrous oxide'), 'value': DATA_VERSION + '_N2O.nc'},
{'label': _('Nitrous oxide 447'), 'value': DATA_VERSION + '_N2O_447.nc'},
{'label': _('Nitrous oxide 448'), 'value': DATA_VERSION + '_N2O_448.nc'},
{'label': _('Nitrous oxide 456'), 'value': DATA_VERSION + '_N2O_456.nc'},
{'label': _('Nitrous oxide 546'), 'value': DATA_VERSION + '_N2O_546.nc'}, #54
{'label': _('Oxygen'), 'value': DATA_VERSION + '_O2.nc'},
{'label': _('Ozone'), 'value': DATA_VERSION + '_O3.nc'},
{'label': _('Ozone 667'), 'value': DATA_VERSION + '_O3_667.nc'},
{'label': _('Ozone 668'), 'value': DATA_VERSION + '_O3_668.nc'},
{'label': _('Ozone 676'), 'value': DATA_VERSION + '_O3_676.nc'},
{'label': _('Ozone 686'), 'value': DATA_VERSION + '_O3_686.nc'}, #60
{'label': _('Peroxynitric acid'), 'value': DATA_VERSION + '_HO2NO2.nc'},
{'label': _('Phosgene'), 'value': DATA_VERSION + '_COCl2.nc'},
{'label': _('Phosphorus'), 'value': DATA_VERSION + '_P.nc'},
{'label': _('Polyacrylonitrile'), 'value': DATA_VERSION + '_PAN.nc'}, #64
{'label': _('Sulfur dioxide'), 'value': DATA_VERSION + '_SO2.nc'},
{'label': _('Sulfur hexafluoride'), 'value': DATA_VERSION + '_SF6.nc'}, #66
{'label': _('Trichlorofluoromethane'), 'value': DATA_VERSION + '_CCl3F.nc'},
{'label': _('Trichlorotrifluoroethane'), 'value': DATA_VERSION + '_CFC113.nc'},
{'label': _('Trifluoromethane'), 'value': DATA_VERSION + '_CHF3.nc'}, #69
{'label': _('Water'), 'value': DATA_VERSION + '_H2O.nc'},
{'label': _('Water 162'), 'value': DATA_VERSION + '_H2O_162.nc'},
{'label': _('Water 171'), 'value': DATA_VERSION + '_H2O_171.nc'},
{'label': _('Water 181'), 'value': DATA_VERSION + '_H2O_181.nc'},
{'label': _('Water 182'), 'value': DATA_VERSION + '_H2O_182.nc'}, #74
# {'label': _('Temperature'), 'value': 'ACEFTS_L2_v5p0_T.nc'} #!!! Est ce qu'on la met?
]
#======================================================================================
# Create global chart template
mapbox_access_token = tokens['scisat_mapbox_token']
layout = dict(
autosize=True,
automargin=True,
margin=dict(l=30, r=30, b=20, t=40),
hovermode="closest",
plot_bgcolor="#F9F9F9",
paper_bgcolor="#F9F9F9",
legend=dict(font=dict(size=10), orientation="h"),
title="Gas concentration overview",
mapbox=dict(
style="light",
# center=dict(lon=-78.05, lat=42.54),
zoom=2,
),
transition={'duration': 500},
)
# Builds the layout for the header
def build_header():
return html.Div(
[
html.Div([], className="one column"),
html.Div(
[
html.H1(
"",
style={"margin-bottom": "10px", "margin-left": "15%"},
id="page-title"),
],
className="six columns",
id="title",
),
html.Div(
[
html.Img(
src=app.get_asset_url("csa-logo.png"),
id="csa-image",
style={
"height": "60px",
"width": "auto",
"margin": "25px",
},
alt="CSA Logo"
)
],
className="one column",
),
html.Div(
[
html.A(
html.Span("", id="learn-more-button"),
href="https://www.asc-csa.gc.ca/eng/satellites/scisat/about.asp",
id='learn-more-link',
className="btn btn-primary"
),
html.A(
html.Span('FR', id='language-button'),
href='/scisat/language/fr',
id='language-link',
className="btn btn-primary"
),
],
className="four columns",
id="button-div",
style={"display": "flex", "justify-content": "space-around"}
),
],
id="header",
className="row flex-display",
style={"margin-bottom": "25px"},
)
# Builds the layout and components for the inputs to filter the data
def build_filtering():
return html.Div([
html.Div(
[
html.Div(
[
html.H2(id="filtering_text"),
html.P(id="data-ratio"),
html.P(id='placeholder')
],
id="info-container",
className="mini_container three columns",
style={"text-align": "center"},
),
html.Div(
[
html.Div(
[
dcc.Markdown(id="description-1"),
dcc.Markdown(id="description-2"),
dcc.Markdown(id="description-3"),
dcc.Markdown(id="description-4"),
html.P(
html.A(
id="github-link",
href = "https://github.com/asc-csa",
title = "ASC-CSA Github"
)
)
],
id="description_div",
),
],
id="description-container",
className="container-display mini_container nine columns",
),
],
className="row flex-display twelve columns"
),
html.Div(
[
html.H3(
id="select-data"
),
],
style={"margin-top": "10px", "margin-left": "auto", "margin-right": "auto", "text-align": "center"},
className="twelve columns"
),
html.Div(
html.Form(
[
html.Section(
[
html.H2(
id='error_header'
),
html.Ul(
id='form_errors'
)
],
id='filter_errors',
hidden=True,
className='alert alert-danger'
),
html.Div(
[
html.Div(
[
html.Div(
className='label label-danger',
id="gas_alert",
hidden=True
)
],
className="error"
),
html.Div(
[
html.Label(
id="gas_selection",
htmlFor='gaz_list_dropdown',
className="control_label",
),
dcc.Dropdown(
id="gaz_list",
options= gaz_name_options,
placeholder=_('Select a gas'),
multi=False,
value=DATA_VERSION + '_O3.nc',
className="dcc_control",
label = 'Label test'
),
# html.Span(children=html.P(),className="wb-inv")
],
role='listbox',
**{'aria-label': 'Gas Dropdown'}
)
],
style={"textAlign":"left"}
),
html.Div(
[
html.Div(
className="error"
),
# dbc.Alert(
# color="secondary",
# id="pos_alert",
# is_open=False,
# fade=False,
# style={"margin-top":"0.5em"},
# className='dash-alert dash-alert-danger'
# )
]
),
html.Div([
html.Div( #Latitude picker
[
html.Label(
id="latitude-text",
className="control_label",
style={"textAlign":"left"}
),
html.Div(
className='label label-danger',
id="lat_alert",
hidden=True
),
html.Div([
html.Label(
id = "lat_min-text",
htmlFor = "lat_min",
hidden = True
),
dcc.Input(
id="lat_min",
type='number',
value=-90.0,
placeholder="Min Latitude",
min=-90.0,
max=90.0,
step=5,
debounce=True
),
html.Label(
id = "lat_max-text",
htmlFor = "lat_max",
hidden = True
),
dcc.Input(
id="lat_max",
type='number',
value=90.0,
placeholder="Max Latitude",
min=-90.0,
max=90.0,
step=5,
debounce=True
)
]),
html.Div(children=html.P(id="lat_selection"),className="wb-inv")
],
className="col-md-4",
),
html.Div( #longitude picker
[
html.Label(
id="longitude-text",
className="control_label",
style ={"textAlign":"left"}
),
html.Div(
className='label label-danger',
id="lon_alert",
hidden=True
),
html.Div([
html.Label(
htmlFor="lon_min",
id= "lon_min-text",
hidden = True
),
dcc.Input(
id="lon_min",
type='number',
value=-180.0,
placeholder="Min Longitude",
min=-180.0,
max=180.0,
step=5,
debounce=True
),
html.Label(
htmlFor="lon_max",
id= "lon_max-text",
hidden = True
),
dcc.Input(
id="lon_max",
type='number',
value=180.0,
placeholder="Max Longitude",
min=-180.0,
max=180.0,
step=5,
debounce=True
),
]),
html.Div(children=html.P(id="lon_selection"),className="wb-inv")
],
className="col-md-4",
style={"textAlign":"left"}
),
html.Div(
[ #Year selection + download button
html.Div([
html.Div(id="date_alert", hidden=True, style={"margin-top":"0.5em"}, className='label label-danger'),
]),
html.Label(
id="yearslider-text",
className="control_label"
),
html.Div(
[
dcc.DatePickerRange(
id='date_picker_range',
start_date=dt.datetime(2004, 2, 1),
end_date=dt.datetime(2020, 5, 5),
min_date_allowed=dt.datetime(2004, 2, 1),
max_date_allowed=dt.date.today(),
start_date_placeholder_text=_('Select start date'),
end_date_placeholder_text=_('Select end date'),
display_format="Y-MM-DD",
start_date_aria_label = _('Start Date'),
end_date_aria_label = _('End Date'),
),
html.Div(id='output-container-date-picker-range'),
html.Div(children=html.P(id="date_selection"),className="wb-inv")
]
),
],
className="col-md-12 col-lg-4",
),
],
className='row align-items-start ',
style={"textAlign":"left"}
),
html.Hr(),
html.Div([ #Choix altitude
html.Label(id="altitude-text"),
dcc.RangeSlider(
id='alt_range',
marks = {i: "{}".format(i) for i in np.append(np.arange(0.5,149.5,10),149.5)},
min=0,
max=150,
step=1,
value=[0, 150] ,
# tooltip = { 'always_visible': True }
),
html.Div(id='output-container-alt-picker-range'),
],style={"margin-top":"75px"}),
html.Div(
[
html.Div(
[
html.Div(
[
html.Div(
html.Span(
id='generate-button',
n_clicks=0,
style={
'padding': '0px 10px',
'display': 'inline-block',
'padding' : '6px 22px'
},
className="btn btn-primary",
role = 'button',
tabIndex=0
),
style={
"text-align": "center"
},
id='generate',
),
html.Div(
children=html.P(
id="generate_selection"
),
className="wb-inv"
)
],
style={'text-align': 'center'}
)
],
className="one-half column",
style={"textAlign":"right"}
),
html.Div(
[ #Download button
html.Div(
[
html.A(
html.Span(
id='download-button-1',
n_clicks=0,
style={'padding': '0px 10px'}
),
id='download-link-1',
# download='rawdata.csv',
href="",
target="_blank",
className="btn btn-primary"
),
html.Div(
children=html.P(id="download_selection"),
className="wb-inv"
)
]
),
],
id="cross-filter-options",
className="one-half column"
)
],
style={"margin-top":"30px"}
)
],
),
className="pretty_container twelve column wb-frmvld",
style={"justify-content": "space-evenly"}
)
])
def detail_table(id, id2):
#next button pagnation, for some reason the pages are 0 indexed but the dispalyed page isn't
@app.callback(
[
Output( id, 'page_current'),
Output( id+'-btn-1-a', 'data-value'),
Output( id+'-btn-2-a', 'data-value'),
Output( id+'-btn-3-a', 'data-value'),
Output( id+'-btn-1-a', "children"),
Output( id+'-btn-2-a', "children"),
Output( id+'-btn-3-a', "children"),
Output( id+'-btn-1-a', "aria-label"),
Output( id+'-btn-2-a', "aria-label"),
Output( id+'-btn-3-a', "aria-label"),
Output( id+'-btn-1-a', "aria-current"),
Output( id+'-btn-2-a', "aria-current"),
Output( id+'-btn-3-a', "aria-current"),
Output( id+'-btn-1', "className"),
Output( id+'-btn-2', "className"),
Output( id+'-btn-prev-a', 'children'),
Output( id+'-btn-next-a', 'children'),
Output( id+'-btn-prev-a', "aria-label"),
Output( id+'-btn-next-a', "aria-label"),
Output( id+'-navigation', "aria-label"),
],
[
Input( id+'-btn-prev', 'n_clicks'),
Input( id+'-btn-1', 'n_clicks'),
Input( id+'-btn-2', 'n_clicks'),
Input( id+'-btn-3', 'n_clicks'),
Input( id+'-btn-next', 'n_clicks')
],
[