Iris works great when loading 1D coordinates cube datasets mapped
to a "regular" rectangular grid. But modern ocean models rarely falls into
that description, they usually have 2D coordinates mapped to curvilinear
staggered grids.
So how well does iris perform with modern numerical ocean models? How about the ...
xray is an interesting package that has been under my radar for a while.
According to the docs xray is:
... an open source project and Python package that aims to bring the
labeled data power of pandas to the physical sciences, by providing
N-dimensional variants of the core pandas data ...
I just handed python-gsw over to the TEOS-10 group. Even though that is probably my dearest project, I do not have the time to be a full time developer anymore. However, I will gladly review Pull Requests (PRs) ;-)
That is why I decide to post a small recipe to help ...
A Análise de Componentes Principais (em inglês PCA) é o nome comum dado ...
This is a short post on how to filter out tides from a time-series using
pandas, iris, and numpy.convolve.
Our data consists of hourly measurements of currents, temperature and salinity as follows:
from datetime import datetime
from pandas import read_table
url = 'https://raw.githubusercontent.com/ocefpaf/python4oceanographers ...
I wanted find out a minimal conda-requirements.txt file for my projects
using only the information from the
conda-recipes repository.
In order to do that I had to parse all conda recipes, to extract the dependencies
of each package, from my conda-recepis files.
A typical conda recipes file (meta.yaml ...
(This post is the second part of Gridding data.)
In the first part we implemented a function to interpolate scattered observations to a grid. Our function took a correlation length and an estimated error and, using a fixed Gaussian correlation function, interpolate the observations to a rectangular grid. Remember that ...
The CF conventions uses standard names for any variable stored using the CF-rules. I often find myself looking for possible names for a specific variable (e.g.: currents or temperature). Sadly, the answer is not that easy. Take a look at the CF Standard Names table and check confusion you ...
In the last post we filled gaps in a gridded data. However, a more common problem is quite the opposite: to grid scattered (observed) data.
There are several optimum interpolation schemes to grid observed data, two examples are Objective Analysis and LOWESS.
In this post I implemented a simple function ...