vp
) or time series of vertical
profiles (vpts
)R/get_quantity.R
get_quantity.Rd
Returns values for the selected quantity from a vertical profile (vp
),
list, or time series of vertical profiles (vpts
). Values are organized per
height bin. Values for eta
are set to 0
, dbz
to -Inf
and ff
, u
,
v
, w
, dd
to NaN
when the sd_vvp
for that height bin is below the
sd_vvp_threshold()
.
get_quantity(x, quantity) # S3 method for vp get_quantity(x, quantity = "dens") # S3 method for list get_quantity(x, quantity = "dens") # S3 method for vpts get_quantity(x, quantity = "dens")
x | A |
---|---|
quantity | Character. A (case sensitive) profile quantity, one of:
|
For a vp
object: a named (height bin) vector with values for the
selected quantity.
For a list
object: a list of named (height bin) vectors with values
for the selected quantity.
For a vpts
object: a (height bin * datetime) matrix with values for
the selected quantity.
sd_vvp_threshold()<-
for setting the sd_vvp
threshold of an object.
# Load the example vertical profile vp <- example_vp # Extract the quantity animal density (dens) get_quantity(vp, "dens")#> 0 200 400 600 800 1000 #> NA 85.0995178 110.4298782 91.7822418 34.5677528 20.5497875 #> 1200 1400 1600 1800 2000 2200 #> 22.9609985 19.7929668 19.7772617 17.3985100 11.9922190 7.2263165 #> 2400 2600 2800 3000 3200 3400 #> 3.0735207 0.0000000 0.7724188 0.0000000 0.0000000 0.0000000 #> 3600 3800 4000 4200 4400 4600 #> 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 #> 4800 #> 0.0000000# Load the example time series of vertical profiles vpts <- example_vpts # Extract the quantity horizontal speed (ff) and show the first two datetimes get_quantity(vpts, "ff")[,1:2]#> 2016-09-01 00:02:00 2016-09-01 00:06:00 #> 0 NaN NaN #> 200 NaN NaN #> 400 NaN NaN #> 600 5.65 5.23 #> 800 5.07 5.64 #> 1000 5.45 5.39 #> 1200 6.02 6.20 #> 1400 5.96 5.81 #> 1600 4.82 4.63 #> 1800 4.61 4.07 #> 2000 NaN 2.74 #> 2200 NaN 2.28 #> 2400 NaN 0.73 #> 2600 NaN 0.74 #> 2800 NaN NaN #> 3000 NaN NaN #> 3200 NaN NaN #> 3400 NaN 1.11 #> 3600 NaN 1.17 #> 3800 NaN NaN #> 4000 NaN NaN #> 4200 NaN NaN #> 4400 NaN NaN #> 4600 NaN NaN #> 4800 NaN NaN