Examine the HydroTrend output

Let's use IPython Notebook to download the model output from the WMT tutorial and examine the results.

The model output is stored as a tar.gz file on the CSDMS website. Here's its name and location:



In [1]:

    
run_id = 'addbbe35-5fd7-4d1b-a37d-3629768532b4'
download_file = run_id + '.tar.gz'
download_url = 'http://csdms.colorado.edu/pub/users/wmt/' + download_file

Download the output and write it to a file on your local machine:



In [2]:

    
import requests
r = requests.get(download_url)
with open(download_file, 'w') as fp:
    fp.write(r.content)

Unpack the file:



In [3]:

    
import tarfile
tar = tarfile.open(download_file)
tar.extractall()
tar.close()

Change to the directory containing the unpacked contents and view:



In [4]:

    
import os
os.chdir(run_id)
%ls









    



README           components.yaml  hydrotrend/      model.yaml

After browsing the hydrotrend directory, as well as consulting the Model:HydroTrend and Model_help:HydroTrend pages, the files we need are

hydrotrend/HYDRO_OUTPUT/HYDROASCII.Q

for the discharge at the river mouth [m³s^-1], and

hydrotrend/_time.txt

for the model time steps [days].

Start by reading the time data from its file:



In [5]:

    
with open("hydrotrend/_time.txt", "r") as fp:
    time = fp.read().split("\n")

View basic information about the data:



In [6]:

    
print "Data type: {}".format(type(time))
print "Length: {} elements".format(len(time))
print "First five elements:\n{}".format(time[0:5])









    



Data type: <type 'list'>
Length: 367 elements
First five elements:
['0.000000', '1.000000', '2.000000', '3.000000', '4.000000']

Next, read the discharge data:



In [7]:

    
with open("hydrotrend/HYDRO_OUTPUT/HYDROASCII.Q", "r") as fp:
    discharge = fp.read().split("\n")

View basic information about the data:



In [8]:

    
print "Data type: {}".format(type(discharge))
print "Length: {} elements".format(len(discharge))
print "First five elements:\n{}".format(discharge[0:5])









    



Data type: <type 'list'>
Length: 368 elements
First five elements:
['Q(m^3/s) ', '--------- ', '1.100 ', '1.100 ', '1.100 ']

Prepare the data by removing the two header lines and the empty line at the end of the discharge series. Also remove the last two values in the time series. Both series now have 365 elements.



In [9]:

    
discharge = discharge[2:-1]
time = time[:-2]
print len(discharge), len(time)

Now we can visualize the model output as a time series:



In [10]:

    
%pylab inline
plot(time, discharge)
title("HydroTrend: discharge at river mouth versus time")
xlabel("Time [$days$]")
ylabel("Q [$m^3 s^{-1}$]")
show()









    



Populating the interactive namespace from numpy and matplotlib