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Extract NetCDF data as an expanded table.

Source: R/hyper_tibble.R
hyper_tibble.Rd

Extract the raw array data as an expanded data frame. This can be the entire variable/s or after dimension-slicing using hyper_filter() expressions with dimension values expanded appropriately for each element in the arrays (one row per element).

Usage

hyper_tibble(x, ..., na.rm = TRUE, force = FALSE)

# S3 method for class 'character'
hyper_tibble(x, ..., na.rm = TRUE, force = FALSE)

# S3 method for class 'tidync'
hyper_tibble(x, ..., na.rm = TRUE, force = FALSE)

Arguments

x

NetCDF file, connection object, or tidync object

...

arguments to `hyper_filter“

na.rm

if TRUE these rows are not included in the output when all variables are NA

force

ignore caveats about large extraction and just do it

Value

a tbl_df

Details

The size of an extraction is checked and if quite large there is an a user-controlled prompt to proceed or cancel. This can be disabled with options(tidync.large.data.check = FALSE)

The function hyper_tibble() will act on an existing tidync object or a source string.

By default all variables in the active grid are returned, use select_var to limit.

See also

hyper_array() and hyper_tbl_cube() which are also delay-breaking functions that cause data to be read

Examples

l3file <- "S20080012008031.L3m_MO_CHL_chlor_a_9km.nc"
f <- system.file("extdata", "oceandata", l3file, package= "tidync")
rnc <- tidync(f)
hyper_filter(rnc)
#> 
#> Data Source (1): S20080012008031.L3m_MO_CHL_chlor_a_9km.nc ...
#> 
#> Grids (4) <dimension family> : <associated variables> 
#> 
#> [1]   D1,D0 : chlor_a    **ACTIVE GRID** ( 9331200  values per variable)
#> [2]   D3,D2 : palette
#> [3]   D0    : lat
#> [4]   D1    : lon
#> 
#> Dimensions 4 (2 active): 
#>   
#>   dim   name  length    min   max start count   dmin  dmax unlim coord_dim 
#>   <chr> <chr>  <dbl>  <dbl> <dbl> <int> <int>  <dbl> <dbl> <lgl> <lgl>     
#> 1 D0    lat     2160  -90.0  90.0     1  2160  -90.0  90.0 FALSE TRUE      
#> 2 D1    lon     4320 -180.  180.      1  4320 -180.  180.  FALSE TRUE      
#>   
#> Inactive dimensions:
#>   
#>   dim   name          length   min   max unlim coord_dim 
#>   <chr> <chr>          <dbl> <dbl> <dbl> <lgl> <lgl>     
#> 1 D2    rgb                3     1     3 FALSE FALSE     
#> 2 D3    eightbitcolor    256     1   256 FALSE FALSE     
library(dplyr)
lapply(hyper_array(f, lat = lat > 0, lon = index > 3000), dim)
#> $chlor_a
#> [1] 1320 1080
#> 

 ht <- hyper_tibble(rnc) %>%
 filter(!is.na(chlor_a))
ht
#> # A tibble: 11 × 3
#>    chlor_a   lon   lat
#>      <dbl> <dbl> <dbl>
#>  1   1.71   170. -76.0
#>  2   1.71   170. -76.0
#>  3   1.71   171. -76.0
#>  4   1.71   171. -76.0
#>  5   1.71   171. -76.0
#>  6   0.759  165. -77.4
#>  7   0.759  165. -77.4
#>  8   0.759  165. -77.4
#>  9   0.759  165. -77.4
#> 10   0.759  165. -77.4
#> 11   0.759  166. -77.4
library(ggplot2)
ggplot(ht %>% filter(!is.na(chlor_a)),
aes(x = lon, y = lat, fill = chlor_a)) + geom_tile()