5. Pre/post processing of OSMOSE model¶
In this section, the pre/post processing tools of the
osmose package are presented
5.1. Library loading¶
require("osmose")
ls("package:osmose")
Le chargement a nécessité le package : osmose
[1] "correct_ltl_file" "existOsmoseParameter"
[3] "extract_grid_mask" "extract_grid_param"
[5] "find_species_index" "getAverageMortality"
[7] "getFishingBaseRate" "getFishingMortality"
[9] "getMortality" "getMortalityDeviation"
[11] "getOsmoseParameter" "getSizeSpectrum"
[13] "getVar" "make_movement_netcdf"
[15] "osmose2R" "read_osmose"
[17] "readOsmoseConfiguration" "report"
[19] "run_osmose" "runOsmose"
[21] "writeFishingFiles" "write_osmose"
[23] "write.osmose"
5.2. Reading Osmose parameters¶
The loading of Osmose parameters is achieved by using the readOsmoseConfiguration function. The output
parameters are stored as strings in a recursive list.
The parameters are accessed by using the getOsmoseParameter function, which returns the parameter in the
proper format.
Warning
You can get access to the parameters by using the list format. However, numerical variables will be returned as strings instead of a numerics
suppressMessages(require("osmose"))
# recover the reference configuration file
filename = system.file(package="osmose", "extdata", "master", "osm_all-parameters.csv")
# load the Osmose configuration file
osmConf = readOsmoseConfiguration(filename)
# Summarize the configuration
summary(osmConf)
cat("\n")
# Recovers some parameters
ncpu = getOsmoseParameter(osmConf, "simulation", "ncpu")
# proper way to recover the season parameter (returns a vector of numeric)
map0season = getOsmoseParameter(osmConf, "movement", "season", "map0")
cat("is.vector(map0season) =", is.vector(map0season), "\n")
# Bad way to recover the map0 season parameter (returns a string)
map0season_bis = osmConf$movement$season$map0
cat("is.character(map0season_bis) =", is.character(map0season_bis), "\n")
Length Class Mode
simulation 7 -none- list
mortality 5 -none- list
osmose 2 -none- list
output 20 -none- list
movement 6 -none- list
predation 4 -none- list
reproduction 1 -none- list
species 12 -none- list
ltl 3 -none- list
plankton 6 -none- list
grid 6 -none- list
population 1 -none- list
is.vector(map0season) = TRUE
is.character(map0season_bis) = TRUE
Furthermore, some parameters can be plotted for a given species. This is done as follows:
# Plotting reproduction growth
png(filename = 'species.png')
plot(osmConf, what="species", species=0)
# Plotting reproduction seasonality
png(filename = 'reproduction.png')
plot(osmConf, what="reproduction", species=1)
# Plotting size range for predation
png(filename = 'predation.png')
plot(osmConf, what="predation", species=2)
Fig. 5.1 Growth parameters for species 0
Fig. 5.2 Reproduction seasonality for species 1
Fig. 5.3 Predation size range for species 2
5.3. Running the model¶
OSMOSE Java can be run from R by using the run_osmose function.
library("osmose")
# recover the reference configuration file
filename = system.file(package="osmose", "extdata", "master", "osm_all-parameters.csv")
# setting output directory
outdir = 'output'
# default run mode (java file in inst/java/)
runOsmose(input=fileName, output=outdir)
By default, the OSMOSE Java included in the package is used. However, the user is free to use another build of the OSMOSE Java program as follows:
# Running Osmose by using another version of the .jar file.
jarfile = "/home/nbarrier/Modeles/osmose/svn-osmose/trunk/dist/osmose-trunk.jar"
runOsmose(osmose=jarfile, input=fileName,
output=outdir, version="4")
Warning
The way the OSMOSE Java core is called has changed between versions 3 and 4. As a consequence,
the user must be sure to properly set the version argument.
5.4. Reading outputs¶
The reading of outputs is achieved by using the read_osmose function:
library("osmose")
data = read_osmose(path='output')
The content of the data object can be obtained as follows:
names(data)
[1] "model" "species" "biomass"
[4] "abundance" "yield" "yieldN"
[7] "mortality" "meanTL" "meanTLCatch"
[10] "biomassByTL" "predatorPressure" "predPreyIni"
[13] "dietMatrix" "meanSize" "meanSizeCatch"
[16] "SizeSpectrum" "abundanceBySize" "biomassBySize"
[19] "yieldBySize" "yieldNBySize" "meanTLBySize"
[22] "mortalityBySize" "dietMatrixBySize" "predatorPressureBySize"
[25] "abundanceByAge" "biomassByAge" "yieldByAge"
[28] "yieldNByAge" "meanSizeByAge" "meanTLByAge"
[31] "mortalityByAge" "dietMatrixByAge" "predatorPressureByAge"
[34] "config"
Variables are accessed by using the getVar function,
which allows to apply some operations prior to extraction (average over the replicates, conversion
into a list or a matrix):
library("osmose")
data = read_osmose("output")
biom = getVar(data, "biomass")
class(biom)
dim(biom)
cat("\n")
# expected = TRUE if mean over replicate should be returned
# only works for data that inherits from array
biom = getVar(data, "biomass", expected=TRUE)
class(biom)
dim(biom)
cat("\n")
biom = getVar(data, "biomass", how="list")
class(biom)
names(biom)
cat(biom$OctopusVulgaris)
cat("\n")
biom = getVar(data, "dietMatrix")
class(biom)
cat("\n")
biom = getVar(data, "dietMatrix", how="list")
class(biom)
[1] "osmose.biomass" "array"
[1] 120 11 3
[1] "matrix"
[1] 120 11
[1] "list"
[1] "OctopusVulgaris" "MelicertusKerathurus" "MetapenaeusMonoceros"
[4] "TrachurusTrachurus" "SardinaPilchardus" "SardinellaAurita"
[7] "EngraulisEncrasicolus" "DiplodusAnnularis" "MustelusMustelus"
[10] "MerlucciusMerluccius" "PagellusErythrinus"
0 0 0 0 0 0 0 0 15781.6 48488.35 39828.78 31787.74 25370.59 20248.9 53191.6 115545.1 92327.91 77744.52 65830.65 54840.04 78690.15 145137.3 106689.6 89557.24 75448.63 63581.84 94315.63 169401.6 128161.3 111114 97743.36 85284.81 111553.3 178472.8 129631.5 112778.2 100447.8 89032.81 106923.4 139955.4 85951.02 74232.06 65498.5 57923.74 69083.21 90930.17 56089.03 46699.82 39921.29 33900.61 45667.22 79728.92 58529.65 51139.86 43699.58 37645.97 53456.19 95171.82 68095.26 58712.88 50206.31 43868.15 59624.38 97738.27 69175.62 58875.63 51371.91 44305.12 59683.55 93388.94 65217.48 56079.13 49641.77 43834.97 53074.88 72633.85 47046.89 40593.72 35075.18 29524 44159.88 76601.57 57293.17 49263.57 42465.76 35690.89 45178.8 70766.41 49709.73 43180.91 37478.74 32417.84 44701.4 80692.32 58009.92 49221.96 42412.14 36096.7 46507.37 74249.08 51200.34 43819.48 37942.7 33084.75 40183.11 71830.84 50153.7 43088.12 36432.06 30797.93 36590.15 58218.22 38542.19 32620.02 27619.44 23506.24 28160.44 50781.51 35485.84 30303.21
[1] "osmose.dietMatrix" "list"
[1] "list"
The first argument is the data object obtained by using the read_osmose function, while the second argument is
the name of the variable to extract.
5.5. Plotting outputs¶
Plotting Osmose outputs is achieved by calling the generic plot function on the osmose object, output by the read_osmose function. The function takes as argument the variable to be displayed (what argument).
The species argument allows to specify the indexes of the species to display (cf. the X in the species.name.spX parameters).
library("osmose")
data = read_osmose(path='output')
test = getVar(data, "species")
png(file="biomass.png")
plot(data, what="biomass")
png(file="abundance.png")
plot(data, what="abundance", species=c(0, 1, 2))
png(file="yield.png")
plot(data, what="yield")
png(file="yieldN.png")
plot(data, what="yieldN")
Hint
When several replicates are run, the uncertainty due to the stochastic mortality is displayed as a grey shading.
Warning
At this time, only these four variables can be plotted. However, more plot functions (diet matrix, mortality, etc.) will be released soon.
Fig. 5.4 Biomass plot
Fig. 5.5 Abundance plot
Fig. 5.6 Yield biomass plot
Fig. 5.7 Yield abundance plot