oceanlabpy/oceanlab

Package of Python scripts for Oceanography

OceanLab

Package of Python scripts for Oceanography (Python +3.6)

Code Example

Check examples folder in our github repository.

Installation

pip install OceanLab

Modules

• OA
  • vectoa(): Objective analysis for vectorial fields;
  • scaloa(): Objective analysis for scalar fields;
• DYN
  • dyn_amp(): Makes the projection of every dynamical mode to velocity to obtain its amplitude;
  • zeta(): Calculates the vorticity field by velocity field;
  • psi2uv(): Calculates the velocity field by stream function scalar field;
  • vmodes(): Calculates the QG pressure modes from N2 profile;
  • eqmodes(): Calculates the equatorial pressure and vertical velocity modes from N2 profile;
• EOF
  • eoft(): Calculates the Empirical Orthogonal Functions;
  • my_eof_interp(): Fillgaps on matrix based on EOFs (translated from Cesar Rocha Matlab version);
  • ceof(): Performs the Complex (or Hilbert) Empirical Orthogonal Functions decomposition;
  • reconstruct_ceof(): Reconstructs the CEOF modes individually;
• UTILS
  • argdistnear(): Searchs the position of the closest points in an array to a reference point;
  • meaneddy(): Performs an eddy-mean decomposition with a low-pass filter;

Contributors

Everyone can contribute to this code. Some of functions were based on Filipe Fernandes or Cesar Rocha functions and some of them were created with help of Dante C. Napolitano, Hélio M. R. Almeida and Wandrey Watanabe at Ocean Dynamics Lab of University of São Paulo (USP).

oceanlab's Issues

Create a requirements file (for pip and conda)

Consider creating a requirements.txt with the dependencies:

• matplotlib
• basemap
• numpy
• scipy
• pandas
• gsw
• seawater

Thinking of the return of the "utils" module

I liked the idea of simplifying and making OceanLab more direct and specific. But I missed the old utils module, where you could get e.g. argdistnear easily. Why not come up with something like "tools" or "support" and bring back some of the "utils"?

memory usage in scaloa

Hey guys,

I've used your objective mapping function scaloa and noticed there is a simple way to reduce memory usage.

The variables d2 and dc2 can occupy a huge memory space, so deleting them after defining both correlation and cross correlation matrices (A,C, respectively) and before inverting the matrix is useful. In one of my cases, it it frees up a few gbs of memory (of course, this depends on both grid and data).

(...)
    d2 = ((np.tile(x, (n, 1)).T - np.tile(x, (n, 1))) ** 2 +
    (np.tile(y, (n, 1)).T - np.tile(y, (n, 1))) ** 2)
    nv = len(xc)
    xc, yc = np.reshape(xc, (1, nv)), np.reshape(yc, (1, nv))
    # Squared distance between the observations and the grid points.
    dc2 = ((np.tile(xc, (n, 1)).T - np.tile(x, (nv, 1))) ** 2 +
    (np.tile(yc, (n, 1)).T - np.tile(y, (nv, 1))) ** 2)
    # Correlation matrix between stations (A) and cross correlation (stations
    # and grid points (C))
    A = (1 - err) * np.exp(-d2 / corrlen ** 2)
    C = (1 - err) * np.exp(-dc2 / corrlen ** 2)
    if 0: # NOTE: If the parameter zc is used (`scaloa2.m`)
        A = (1 - d2 / zc ** 2) * np.exp(-d2 / corrlen ** 2)
        C = (1 - dc2 / zc ** 2) * np.exp(-dc2 / corrlen ** 2)
        
    # here!!!!!!!!!   <----------
    del(d2, dc2)
        
(...)

Implement the error map for vectoa

Copy the example from scaloa.

Update examples for the new way to import the packages

Instead of
from OceanLab import OA
it has to be
import OceanLab.oa as OA

Raise error when err>=1 for scaloa and vectoa

We can also update the docstring to make sure users does not think the err parameter is in percentage.

LICENSE

@iuryt Choose a license for you project. I recommend MIT or BSD-like (2 or 3 Clauses) licenses.

Here is a typical MIT licenses (automatically generated by GitHub BTW).