Workflow 5: Searching and plotting#

In this short tutorial we’ll show how to retrieve some data and create a simple plot using one of our plotting functions.

As in the previous tutorial, we will start by setting up our temporary object store for our data. If you’ve already create your own local object store you can skip the next few steps and move onto the Searching section.

import os
import tempfile

tmp_dir = tempfile.TemporaryDirectory()
os.environ["OPENGHG_PATH"] =   # temporary directory
from openghg.util import retrieve_example_data
from openghg.client import standardise_surface

tac_data = retrieve_example_data(path="timeseries/tac_example.tar.gz")
bsd_data = retrieve_example_data(path="timeseries/bsd_example.tar.gz")
standardise_surface(filepaths=tac_data, data_type="CRDS", site="TAC", network="DECC")
standardise_surface(filepaths=bsd_data, data_type="CRDS", site="BSD", network="DECC")


Let’s search for all the methane data from Tacolneston

from openghg.client import search

ch4_results = search(site="tac", species="ch4")

If we want to take a look at the data from the 185m inlet we can first retrieve the data from the object store and then create a quick timeseries plot. See the SearchResults object documentation for more information.

data_185m = ch4_results.retrieve(inlet="185m")

NOTE: the plots created below may not show up on the online documentation version of this notebook.


You can make some simple changes to the plot using arguments

data_185m.plot_timeseries(title="Methane at Tacolneston", xlabel="Time", ylabel="Conc.", units="ppm")

Plot all the data#

We can also retrieve all the data, get a list of ObsData objects.

all_ch4_tac = ch4_results.retrieve_all()

Then we can use the plot_timeseries function from the plotting submodule to compare measurements from different inlets. This creates a Plotly plot that should be interactive and and responsive, even with relatively large amounts of data.

from openghg.plotting import plot_timeseries

plot_timeseries(data=all_ch4_tac, units="ppb")

Compare different sites#

We can easily compare data from different sites by doing a quick search to see what’s available

ch4_data = search(species="ch4")

Then we refine our search to only retrieve the inlets we want

lower_inlets = search(species="ch4", inlet=["42m", "54m"])

Then we can retrieve all the data and make a plot.

lower_inlet_data = lower_inlets.retrieve_all()
plot_timeseries(data=lower_inlet_data, title="Comparing CH4 measurements at Tacolneston and Bilsdale")