argodata

argodata: An R interface to oceanographic data from the International Argo Program - Published in JOSS (2021)

https://github.com/argocanada/argodata

Repository

Download Argo Ocean Float Data

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  dpi = 300
)

library(argodata)
library(tidyverse)

argo_set_cache_dir("cache-dev")
options(argodata.max_global_cache_age = Inf)
options(argodata.max_data_cache_age = Inf)

argo_global_prof()
```

# argodata


[![R build status](https://github.com/ArgoCanada/argodata/workflows/R-CMD-check/badge.svg)](https://github.com/ArgoCanada/argodata/actions)
[![Codecov test coverage](https://codecov.io/gh/ArgoCanada/argodata/branch/master/graph/badge.svg)](https://codecov.io/gh/ArgoCanada/argodata?branch=master)


The goal of argodata is to provide a data frame-based interface to data generated by the [Argo floats program](https://argo.ucsd.edu) ([doi:10.17882/42182](https://doi.org/10.17882/42182)). This package provides low-level access to all variables contained within Argo NetCDF files; for a higher-level interface with built-in visualization and quality control, see the [argoFloats package](https://github.com/ArgoCanada/argoFloats).

## Installation

You can install the development version from [GitHub](https://github.com/) using:

``` r
# install.packages("remotes")
remotes::install_github("ArgoCanada/argodata")
```

The argodata package downloads files from the [FTP and HTTPS mirrors](http://www.argodatamgt.org/Access-to-data/Argo-GDAC-ftp-and-https-servers), caches them, and loads them into R. You can set the mirror using `argo_set_mirror()` and the cache directory using `argo_set_cache_dir()`:

```{r, eval = FALSE}
argo_set_mirror("https://data-argo.ifremer.fr/")
argo_set_cache_dir("my/argo/cache")
```

Optionally, you can set `options(argodata.cache_dir = "my/argo/cache")` in your .Rprofile to persist this value between R sessions (see `usethis::edit_r_profile()`). Cached files are used indefinitely by default because of the considerable time it takes to refresh them. If you do use a persistent cache, you should update the index files regularly using `argo_update_global()` (data files are also updated occasionally; update these using `argo_update_data()`).

## Example

The main workflow supported by argodata is:

- Start with `argo_global_prof()`, `argo_global_traj()`, `argo_global_meta()`, `argo_global_bio_prof()`, `argo_global_bio_prof()`, or `argo_global_synthetic_prof()`. These functions return data frames that contain meta information about each data file in Argo.
- Use `argo_filter_radius()`, other `argo_filter_*()` functions, or `dplyr::filter()` to subset the index using search criteria.
- Use extractor functions like `argo_prof_levels()`, `argo_traj_measurement()`, `argo_meta_config_param()`, and `argo_tech_tech_param()` to read information for all files in the index subset.

```{r example}
library(tidyverse)
library(argodata)

# filter profile index using search criteria
prof_lab_may_2020 <- argo_global_prof() %>%
  argo_filter_rect(50, 60, -60, -50) %>% 
  filter(
    lubridate::year(date) == 2020, 
    lubridate::month(date) == 5
  )

# download, cache, and load NetCDF files
levels_lab_may_2020 <- prof_lab_may_2020 %>% 
  argo_prof_levels()

# plot!
levels_lab_may_2020 %>% 
  filter(psal_qc == 1) %>% 
  ggplot(aes(x = psal, y = pres, col = temp)) +
  geom_point() +
  scale_y_reverse() +
  theme_bw()
```

See the reference for `argo_prof_levels()` for more ways to load Argo profiles from `argo_global_prof()`, `argo_global_bio_prof()` and `argo_global_synthetic_prof()`; see `argo_traj_measurement()` for ways to load Argo trajectories from `argo_global_traj()` or `argo_global_bio_traj()`; see `argo_meta_missions()` for ways to load float meta from `argo_global_meta()`; see `argo_tech_tech_param()` for ways to load float technical information from `argo_global_tech()`; and see `argo_info()` and `argo_vars()` for ways to load global metadata from Argo NetCDF files.

## Advanced

The argodata package also exports the low-level readers it uses to produce tables from Argo NetCDF files. You can access these using `argo_read_*()` functions.

```{r}
prof_file <- system.file(
  "cache-test/dac/csio/2900313/profiles/D2900313_000.nc",
  package = "argodata"
)

argo_read_prof_levels(prof_file)
```

## Code of Conduct
  
Please note that argodata is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

Owner

JOSS Publication

argodata: An R interface to oceanographic data from the International Argo Program

Published

December 16, 2021

DOI

10.21105/joss.03659

Volume 6, Issue 68, Page 3659

Authors

Dewey Dunnington
Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS, Canada

Jaimie Harbin
Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS, Canada

Dan E. Kelley
Department of Oceanography, Dalhousie University, Halifax, NS, Canada

Clark Richards
Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS, Canada

Editor

Kristen Thyng

Tags

oceanography measurement Argo float

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