Visualizing Logs

Visualizing Logs#

x4c has a Logs class to support convenient loading and visualizing log files. In this example, we show how to load and visualize the global volume mean ocean temperature and seawater d18O.

[1]:

%load_ext autoreload
%autoreload 2

import os
import matplotlib.pyplot as plt
os.chdir('/glade/u/home/fengzhu/Github/x4c/docsrc/notebooks')
import x4c
print(x4c.__version__)

2025.10.13

Load the specific variables from the log files#

[ ]:

dirpath = '/glade/campaign/univ/ubrn0018/fengzhu/CESM_output/archive/b.e13.B1850C5.ne16_g16.icesm131_d18O_fixer.Miocene.3xCO2.005/logs'
L = x4c.Logs(dirpath, comp='ocn', load_num=-10) # load the last 10 log files
L.get_vars(['TEMP', 'R18O'])

>>> Logs.dirpath: /glade/campaign/univ/ubrn0018/fengzhu/CESM_output/archive/b.e13.B1850C5.ne16_g16.icesm131_d18O_fixer.Miocene.3xCO2.005/logs
>>> 10 Logs.paths:
Start: ocn.log.4591098.desched1.240524-190730.gz
End: ocn.log.4610617.desched1.240527-034410.gz

Global Volume Mean Ocean Temperature#

[3]:

x4c.set_style('web', font_scale=1.2)
fig, ax = plt.subplots(figsize=[7, 4])
ax.plot(L.df_ann.index, L.df_ann['TEMP'], color='tab:red', lw=3)
ax.set_ylabel('TEMP [°C]')
ax.set_xlabel('Model Year')
ax.set_title('Global Volume Mean Ocean Temperature', weight='bold')

[3]:

Text(0.5, 1.0, 'Global Volume Mean Ocean Temperature')
../_images/notebooks_diags-logs_5_1.png

Global Volume Mean Seawater d18O#

[4]:

x4c.set_style('web', font_scale=1.2)
fig, ax = plt.subplots(figsize=[7, 4])
ax.plot(L.df_ann.index, (L.df_ann['R18O']-1)*1e3, color='tab:blue', lw=3)
ax.set_ylabel('d18Osw [permil]')
ax.set_xlabel('Model Year')
ax.set_title('Global Volume Mean Seawater d18O', weight='bold')

[4]:

Text(0.5, 1.0, 'Global Volume Mean Seawater d18O')
../_images/notebooks_diags-logs_7_1.png 
[ ]:
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