NetCDF_files.Rmd

---
title: "NetCDF_files"
author: "Patricia DeRepentigny"
date: "1/18/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE)
```

```{r}
library(ncdf4)
library(dplyr)
library(tidyr)
library(ggplot2)
```

# Read in data from a file

```{r}
nc <- nc_open("data/WG2013CTD.nc")
```

```{r}
print(nc)
```

```{r}
vars <- attributes(nc$var)$names
dims <- attributes(nc$dim)$names
```

```{r}
salinity <- ncvar_get(nc, "sal")
time <- ncvar_get(nc, "time")
depth <- ncvar_get(nc, "z")
```

# Reformat the output

```{r}
time <- as.POSIXct((time + 719529)*86400, origin = "1970-01-01", tz = "UTC")
```

Coerce into a data frame

```{r}
salinity_data <- as.data.frame(salinity)
```

Assign colum names to depth values

```{r}
names(salinity_data) <- as.character(depth)
```

Reshape the data and add time

```{r}
salinity_data_long <- salinity_data %>% 
  mutate(time = time) %>% 
  gather(key = "depth", value = "salinity", -time) %>% 
  mutate(depth = as.numeric(depth)) %>% 
  arrange(time)

head(salinity_data_long)
```

# Plots

```{r}
ggplot(salinity_data_long, mapping = aes(x = time, y = depth, fill = salinity)) +
  geom_raster()
```

```{r}
ggplot(salinity_data_long, mapping = aes(x = salinity, y = depth, color = time, group = time)) +
  geom_line(size = 0.1) +
  scale_y_reverse()
```