New course for Spring Quarter: OCEAN 240B
Methods of Oceanographic Data Analysis
This is a new course intended for second-year oceanography students. The goal of the
course is to learn and practice simple techniques for analyzing physical, chemical,
biological, and geological oceanographic data, including basic statistics, curve fitting,
and graphics. Students will learn these techniques through examples from ocean data
sets. The work will be done in the context of the Python programming language,
which students will learn as part of the course. Approximately half the effort in this
course will be to become familiar with data analysis techniques, with the other half
devoted to becoming proficient with Python. No previous knowledge of Python,
programming, or analysis techniques is assumed. Students should have a basic
knowledge of calculus such as from Math 125 and 126 (or equivalents).
Instructor: Prof. Stephen Riser
Course time: M-W 1:30-3:20
(SLN 20872)
#+begin_src python :results file
import matplotlib, numpy
matplotlib.use('Agg')
import matplotlib.pyplot
as plt
#+begin_src
python :results
file
fig=plt.figure(figsize=(4,2))
x=numpy.linspace(-15,15)
import
matplotlib, numpy
plt.plot(numpy.sin(x)/x)
matplotlib.use('Agg')
fig.tight_layout()
plt.savefig('images/python-matplot-fig.png')
import
matplotlib.pyplot as plt
return 'images/python-matplot-fig.png' # return
fig=plt.figure(figsize=(4,2))
filename to org-mode
#+end_src
x=numpy.linspace(-15,15)
#+RESULTS:
plt.plot(numpy.sin(x)/x)
[[file:images/python-matplot-fig.png]]
fig.tight_layout()
plt.savefig('images/python-matplot-fig.png')
return 'images/python-matplot-fig.png' # return filename
to org-mode
#+end_src
!