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Return all DVID body annotations

Usage

manc_dvid_annotations(
  ids = NULL,
  node = "neutu",
  rval = c("data.frame", "list"),
  columns_show = NULL,
  cache = FALSE
)

Arguments

ids

A set of body ids in any form understandable to manc_ids

node

A DVID node as returned by manc_dvid_node. The default is to return the current active (unlocked) node being used through neutu.

rval

Whether to return a fully parsed data.frame (the default) or an R list. The data.frame is easier to work with but typically includes NAs for many values that would be missing in the list.

columns_show

Whether to show all columns, or just with '_user', or '_time' suffix. Accepted options are: 'user', 'time', 'all'.

cache

Whether to cache the result of this call for 5 minutes.

Value

A tibble containing with columns including

  • bodyid as a numeric value

  • status

  • user

  • naming_user

  • instance

  • status_user

  • comment

NB only one bodyid is used regardless of whether the key-value returned has 0, 1 or 2 bodyid fields. When the ids are specified, missing ids will have a row containing the bodyid in question and then all other columns will be NA.

Details

See this Slack post from Stuart Berg for details.

Note that the original api call was <rootuuid>:master, but I have now just changed this to <neutu-uuid> as returned by manc_dvid_node. This was because the range query stopped working 16 May 2021, probably because of a bad node.

Examples

# \donttest{
mdf=manc_dvid_annotations()
head(mdf)
#> # A tibble: 6 × 53
#>   bodyid class      description entry_nerve exit_nerve group instance long_tract
#>    <dbl> <chr>      <chr>       <chr>       <chr>      <dbl> <chr>    <chr>     
#> 1  10000 descendin… Giant fiber CvC         "None"     10000 DNlt002… none      
#> 2  10001 sensory n… NA          ProLN_R      NA           NA SNxxxx_… NA        
#> 3  10002 descendin… Giant fiber CvC         "None"     10000 DNlt002… none      
#> 4  10003 sensory n… NA          ProLN_L      NA           NA SNta29_… NA        
#> 5  10004 intrinsic… 13B in T2 … None        ""         10004 IN13B07… NA        
#> 6  10007 sensory n… NA          AbN3_R       NA           NA SNpp03_… NA        
#> # ℹ 45 more variables: nt_acetylcholine_prob <dbl>, nt_gaba_prob <dbl>,
#> #   nt_glutamate_prob <dbl>, nt_unknown_prob <dbl>, origin <chr>,
#> #   position <chr>, position_type <chr>, predicted_nt <chr>,
#> #   predicted_nt_prob <dbl>, prefix <chr>, root_position <chr>,
#> #   root_side <chr>, status <chr>, subclass <chr>, synonyms <chr>,
#> #   systematic_type <chr>, target <chr>, transmission <chr>, type <chr>,
#> #   user <chr>, vfb_id <chr>, modality <chr>, tag <chr>, soma_side <chr>, …
table(mdf$status)
#> 
#>                                   0.5assign                Anchor 
#>                   497                   892                   168 
#>                Orphan            PRT Orphan Prelim Roughly traced 
#>                   287                   245                  4896 
#>        Primary Anchor             RT Orphan        Roughly traced 
#>                     1                   314                 18305 
#>        Sensory Anchor           Soma Anchor           Unimportant 
#>                    45                     3                  1617 

manc_dvid_annotations('DNp01')
#> # A tibble: 2 × 53
#>   bodyid class      description entry_nerve exit_nerve group instance long_tract
#>    <dbl> <chr>      <chr>       <chr>       <chr>      <dbl> <chr>    <chr>     
#> 1  10000 descendin… Giant fiber CvC         None       10000 DNlt002… none      
#> 2  10002 descendin… Giant fiber CvC         None       10000 DNlt002… none      
#> # ℹ 45 more variables: nt_acetylcholine_prob <dbl>, nt_gaba_prob <dbl>,
#> #   nt_glutamate_prob <dbl>, nt_unknown_prob <dbl>, origin <chr>,
#> #   position <chr>, position_type <chr>, predicted_nt <chr>,
#> #   predicted_nt_prob <dbl>, prefix <chr>, root_position <chr>,
#> #   root_side <chr>, status <chr>, subclass <chr>, synonyms <chr>,
#> #   systematic_type <chr>, target <chr>, transmission <chr>, type <chr>,
#> #   user <chr>, vfb_id <chr>, modality <chr>, tag <chr>, soma_side <chr>, …

if (FALSE) { # \dontrun{
# compare live body annotations with version in clio
mdf.clio=manc_dvid_annotations('clio')
waldo::compare(mdf.clio, mdf)
} # }
# }