# coding: utf-8

# # Explore ERDDAP timeseries data using Jupyter Widgets

# Inspired by [Jason Grout's excellent ESIP Tech Dive talk on "Jupyter Widgets"](https://youtu.be/CVcrTRQkTxo?t=2596), this notebook uses the `ipyleaflet` and `bqplot` widgets

# to interactively explore the last two weeks of time series data from an ERDDAP Server. Select a `standard_name` from the list, then click a station to see the time series.

# NOTE: To access a protected ERDDAP endpoint is protected, you can add a `~/.netrc` file like this:

# ```

# machine cgoms.coas.oregonstate.edu

# login <username>

# password <password>

# ```

# In[1]:

import numpy as np

import pandas as pd

# In[2]:

import pendulum

# `ipyleaflet` and `bqplot` are both Jupyter widgets, so can interact with Python like any other widget. Since we want to click on a map in a notebook and get an interactive time series plot, they are perfect tools to use here.

# In[3]:

import ipyleaflet as ipyl

import bqplot as bq

import ipywidgets as ipyw

# To make working with ERDDAP simpler, we use `erddapy`, a high-level python interface to ERDDAP's RESTful API

# In[4]:

from erddapy import ERDDAP

from erddapy.utilities import urlopen

# This code should work with minor modifications on any ERDDAP (v1.64+) endpoint that has `cdm_data_type=timeseries` or `cdm_data_type=point` datasets. Change the values for other ERDDAP endpoints or regions of interest

# In[5]:

endpoint = 'http://erddap.sensors.ioos.us/erddap'

initial_standard_name = 'sea_surface_wave_significant_height'

nchar = 9 # number of characters for short dataset name

cdm_data_type = 'TimeSeries'

center = [35, -100]

zoom = 3

min_time = pendulum.parse('2017-11-01T00:00:00Z')

max_time = pendulum.parse('2017-11-11T00:00:00Z')

# In[6]:

endpoint = 'https://gamone.whoi.edu/erddap'

initial_standard_name = 'sea_water_temperature'

nchar = 9 # number of characters for short dataset name

cdm_data_type = 'TimeSeries'

center = [35, -100]

zoom = 3

min_time = pendulum.parse('2011-05-05T00:00:00Z')

max_time = pendulum.parse('2011-05-15T00:00:00Z')

# In[7]:

endpoint = 'https://erddap-uncabled.oceanobservatories.org/uncabled/erddap'

initial_standard_name = 'sea_water_temperature'

nchar = 8 # number of characters for short dataset name

cdm_data_type = 'Point'

center = [35, -100]

zoom = 1

min_time = pendulum.parse('2017-08-01T00:00:00Z')

max_time = pendulum.parse('2017-08-03T00:00:00Z')

# In[8]:

endpoint = 'https://cgoms.coas.oregonstate.edu/erddap'

initial_standard_name = 'air_temperature'

nchar = 8 # number of characters for short dataset name

cdm_data_type = 'TimeSeries'

center = [44, -124]

zoom = 6

now = pendulum.now(tz='utc')

max_time = now

min_time = now.subtract(days=3)

# In[9]:

endpoint = 'http://ooivm1.whoi.net/erddap'

initial_standard_name = 'solar_panel_1_voltage'

nchar = 8 # number of characters for short dataset name

cdm_data_type = 'TimeSeries'

center = [41.0, -70.]

zoom = 7

now = pendulum.now(tz='utc')

max_time = now

min_time = now.subtract(days=3)

# In[10]:

server = 'http://www.neracoos.org/erddap'

standard_name = 'significant_height_of_wind_and_swell_waves'

#standard_name = 'sea_water_temperature'

nchar = 3 # number of characters for short dataset name

cdm_data_type = 'TimeSeries'

center = [42.5, -68]

zoom = 6

now = pendulum.now(tz='utc')

search_max_time = now

search_min_time = now.subtract(weeks=2)

# In[11]:

e = ERDDAP(server=server, protocol='tabledap')

# Find all the `standard_name` attributes that exist on this ERDDAP endpoint, using [ERDDAP's "categorize" service](http://www.neracoos.org/erddap/categorize/index.html)

# In[12]:

url='{}/categorize/standard_name/index.csv'.format(server)

df = pd.read_csv(urlopen(url), skiprows=[1, 2])

standard_names = df['Category'].values

# Create a dropdown menu widget with all the `standard_name` values found

# In[13]:

widget_std_names = ipyw.Dropdown(options=standard_names, value=standard_name)

# Create a text widget to enter the search minimum time

# In[14]:

widget_search_min_time = ipyw.Text(

)

# In[15]:

widget_search_max_time = ipyw.Text(

)

# This function puts lon,lat and datasetID into a GeoJSON feature

# In[16]:

def point(dataset, lon, lat, nchar):

return geojsonFeature

# This function finds all the datasets with a given standard_name in the specified time period, and return GeoJSON

# In[17]:

def adv_search(e, standard_name, cdm_data_type, min_time, max_time):

return df

# This function returns the lon,lat vlaues from allDatasets

# In[18]:

def alllonlat(e, cdm_data_type, min_time, max_time):

return df

# In[19]:

def stdname2geojson(e, standard_name, cdm_data_type, search_min_time, search_max_time):

return geojson, datasets

# The `map_click_handler` function updates the time series plot when a station marker is clicked

# In[20]:

def map_click_handler(event=None, id=None, properties=None):

update_timeseries_plot(dataset=dataset_id, standard_name=standard_name, constraints=constraints)

# The `search_button_handler` function updates the map when the `Search` button is selected

# In[21]:

def widget_replot_button_handler(change):

update_timeseries_plot(dataset=dataset_id, standard_name=standard_name, constraints=constraints)

# In[22]:

def widget_search_button_handler(change):

update_timeseries_plot(dataset=dataset_id, standard_name=standard_name, constraints=constraints)

# In[23]:

def update_timeseries_plot(dataset=None, standard_name=None, constraints=None, title_len=18):

figure.title = '{} - {}'.format(dataset[:title_len], var)

# In[24]:

widget_search_button = ipyw.Button(

button_style='')

# In[25]:

widget_replot_button = ipyw.Button(

button_style='')

# In[26]:

widget_replot_button.on_click(widget_replot_button_handler)

# In[27]:

widget_search_button.on_click(widget_search_button_handler)

# In[28]:

widget_plot_start_time = ipyw.Text(

)

# In[29]:

widget_plot_stop_time = ipyw.Text(

)

# This function returns the specified dataset time series values as a Pandas dataframe

# In[30]:

def get_data(dataset=None, standard_name=None, constraints=None):

return df, var

# This defines the initial `ipyleaflet` map

# In[31]:

map = ipyl.Map(center=center, zoom=zoom, layout=dict(width='750px', height='350px'))

features, datasets = stdname2geojson(e, standard_name, cdm_data_type, search_min_time, search_max_time)

dataset_id = datasets[0]

feature_layer = ipyl.GeoJSON(data=features)

feature_layer.on_click(map_click_handler)

map.layers = [map.layers[0], feature_layer]

# In[32]:

widget_dsnames = ipyw.Dropdown(options=datasets, value=dataset_id)

# This defines the intitial `bqplot` time series plot

# In[33]:

dt_x = bq.DateScale()

sc_y = bq.LinearScale()

constraints = {

'time>=': search_min_time,

'time<=': search_max_time

}

df, var = get_data(dataset=dataset_id, standard_name=standard_name, constraints=constraints)

def_tt = bq.Tooltip(fields=['y'], formats=['.2f'], labels=['value'])

time_series = bq.Lines(x=df.index, y=df[var],

scales={'x': dt_x, 'y': sc_y}, tooltip=def_tt)

ax_x = bq.Axis(scale=dt_x, label='Time')

ax_y = bq.Axis(scale=sc_y, orientation='vertical')

figure = bq.Figure(marks=[time_series], axes=[ax_x, ax_y])

figure.title = '{} - {}'.format(dataset_id[:18], var)

figure.layout.height = '300px'

figure.layout.width = '800px'

# In[34]:

#Not currently using this (cell below setting "observe" to this function is commented out)

def widget_dsnames_handler(change):

update_timeseries_plot(dataset=dataset_id, standard_name=standard_name, constraints=constraints)

# In[35]:

#widget_dsnames.observe(widget_replot_button_handler)

# In[36]:

#all this widget does it take up 7 cm of vertical space

ispace = ipyw.HTML(

)

# This specifies the widget layout

# In[37]:

form_item_layout = ipyw.Layout(display='flex', flex_flow='column', justify_content='space-between')

col1 = ipyw.Box([map, figure], layout=form_item_layout)

col2 = ipyw.Box([widget_std_names, widget_search_min_time, widget_search_max_time, widget_search_button,

ispace, widget_dsnames, widget_plot_start_time, widget_plot_stop_time, widget_replot_button], layout=form_item_layout)

form_items = [col1, col2]

form = ipyw.Box(form_items, layout=ipyw.Layout(display='flex', flex_flow='row', border='solid 2px',

align_items='flex-start', width='100%'))

form