Description Format Value Fields Methods Examples
The SmartProject
class implements the main class of
smartR package.
R6Class
object.
Object of R6Class
with attributes and methods to fullfill
a complete analisys with the SMART approach.
rawDataSurvey
Stores the raw survey data after being populated by loadSurveyLFD()
method.
yearInSurvey
Stores the distinct years in the rawDataSurvey
time-serie.
specieInSurvey
Stores the distinct species in the rawDataSurvey
time-serie.
surveyBySpecie
Stores a list of SurveyBySpecie
objects, one for each species in the time-series.
rawDataFishery
Stores the raw fishery data as is in the provided csv file. The attribute is populated by loadFisheryLFD()
method.
yearInFishery
Stores the distinct years in the rawDataFishery
time-serie.
specieInFishery
Stores the distinct species in the rawDataFishery
time-serie.
fisheryBySpecie
Stores a list of FisheryBySpecie
objects, one for each species in the time-series.
gooLstCoho
Stores a list of plots of species cohorts spatial distribution .
sampMap
Stores the environment
object.
fleet
Stores the FishFleet
object.
simProd
Stores the simulated pattern of production.
simEffo
Stores the simulated pattern of effort.
simBanFG
Stores a vector of fishable/banned fishing grounds.
simSpatialCost
Stores the simulated pattern of spatial costs.
simEffortCost
Stores the simulated pattern of effort costs.
simProdCost
Stores the simulated pattern of production costs.
simTotalCost
Stores the simulated pattern of total costs.
simRevenue
Stores the simulated pattern of revenue by species and fishing ground.
simTotalRevenue
Stores the simulated pattern of total revenues.
simCostRevenue
Stores the simulated pattern of costs and revenues.
simResPlot
Stores the plots with the simulation' results.
outGmat
Stores the evolution of gains during the simulation.
outOptimEffo
Stores the resulting pattern of effort.
outWeiProp
Stores the annual proportion of fish by cohort and fishing ground.
outWeiPropQ
Stores the seasonal proportion of fish by cohort and fishing ground.
setCostInput()
This method is used to setup the required data for costs computation
setInProduction()
This method is used to setup the required data for production costs computation
setDaysAtSea()
This method is used to compute the number of Days at Sea of each vessel
setEffortIndex()
This method is used to compute the value of the Effort Index
setProductionIndex()
This method is used to compute the value of the Production Index
getHarbFgDist()
This method is used to compute the weighted average distance of every fishing ground to each harbour
setFgWeigDist()
This method is used as helper function to get the weighted average distance between fishing ground and harbours
setRegHarbBox()
This method is used to compute the distance of each harbour to every fishing ground centroid
loadSurveyLFD(csv_path)
This method is used to load the raw survey LFD data from a csv file
loadFisheryLFD(csv_path)
This method is used to load the raw fishery LFD data from a csv file
setYearSurvey()
This method is used to store the distinct year in the survey time-series
setYearFishery()
TThis method is used to store the distinct year in the fishery time-series
loadMap(map_path)
This method is used to load the Environmental Grid and initialize the Environment object
createFleet()
This method is used to initialize the Fleet object
setSpecieSurvey()
This method is used to store the distinct species in the survey dataset
setSpecieFishery()
This method is used to store the distinct species in the fishery dataset
splitSpecieSurvey()
This method is used to split the survey dataset by species
splitSpecieFishery()
This method is used to split the fishery dataset by species
addSpecieSurvey(sing_spe)
This method is used to initialize a new surveyBySpecie
object
addSpecieFishery(sing_spe)
This method is used to initialize a new fisheryBySpecie
object
setSpreaFishery()
This method is used to prepare the fishery LFD data for MCMC analysis
setSpatFishery()
This method is used to setup the plot with the spatial distribution of the fishery dataset
setSpreaSurvey()
This method is used to prepare the survey LFD data for MCMC analysis
setSpatSurvey()
This method is used to setup the plot with the spatial distribution of the survey dataset
setDepthSurvey()
This method is used to assign the depth of each survey tow
setStratumSurvey()
This method is used to assign a depth stratum to each survey tow
setAbuAvgAll()
This method is used to compute the spiecies abundances at each survey stratum
setMeditsIndex()
This method is used to compute the MEDITS index
setStrataAbu()
This method is used to compute the weighted number of individuals of each size in every stratum
loadFleeEffoDbs(effort_path, met_nam, onBox = TRUE, perOnBox = 1)
This method is used to extract the vms data from one or more vmsbase DB
ggplotRawPoints(year)
This method is used to plot the raw vms points
ggplotFgWeigDists()
This method is used to plot the weighted average distance between harbours and fishing grounds
setAvailData()
This method is used to gather the required data for the spatial clustering
predictProduction(specie)
This method is used to compute the estimated production
simProdAll(selRow = numeric(0))
This method is used to compute the simulated production
genSimEffo(method = "flat", selRow = numeric(0), areaBan = numeric(0))
This method is used to create a simulated pattern of effort
getSimSpatialCost()
This method is used to compute the simulated spatial costs
getSimEffortCost()
This method is used to compute the simulated effort costs
getSimProdCost()
This method is used to compute the simulated production costs
getSimTotalCost()
This method is used to collect all the simulated costs
getSimRevenue(selRow = numeric(0), timeScale = "Year")
This method is used to compute the simulated revenues
getLWstat()
This method is used to compute the length/weight statistics for each fishing ground
simulateFishery(thr0 = 100, effoBan = numeric(0), timeStep = "Year")
This method is used to simulate one year of fishing
setSimResults()
This method is used to store the results of a simulation run
ggplotFishingPoints(year)
This method is used to plot the fishing points
setCellPoin()
This method is used assign a cell to each vms point
setTrackHarb()
This method is used to assign the harbour to each fishing trip
setFishGround(numCut)
This method is used to setup the fishing ground configuration
addFg2Fishery()
This method is used to add the fishing ground information to each fishery data point
addFg2Survey()
This method is used to add the fishing ground information to each survey data point
setWeekEffoMatrCell()
This method is used to combine the raw effort points in weekly aggregated effort by cell
setWeekEffoMatrGround()
This method is used to combine the raw effort points in weekly aggregated effort by fishing ground
ggplotGridEffort(year)
This method is used to plot the gridded fishing effort
getNnlsModel(specie, minobs, thr_r2)
This method is used to compute the coefficients of the NNLS model
cohoDisPlot(whoSpe, whoCoh, whiYea, interp)
This method is used to store the spatial distribution of the species by cohort
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | # Initialize SmartProject
yourSmartRstudy <- SmartProject$new()
# Initialize fleet object
yourSmartRstudy$createFleet()
######################
## Environment Data ##
######################
# Locate the example environment asset' file
envAssetPath <- system.file("extdata/mapAsset.RDS", package = "smartR")
# Load environment asset' data
yourSmartRstudy$importEnv(readRDS(envAssetPath))
# Setup case study' map
yourSmartRstudy$sampMap$getGooMap()
yourSmartRstudy$sampMap$setGooGrid()
yourSmartRstudy$sampMap$setGooBbox()
yourSmartRstudy$sampMap$setGgDepth()
yourSmartRstudy$sampMap$setGgBioDF()
# View case study' grid
print(yourSmartRstudy$sampMap$gooGrid)
################
## Fleet Data ##
################
# Locate the example fleet asset' file
effAssetPath <- system.file("extdata/effAsset.RDS", package = "smartR")
# Load fleet asset' data
yourSmartRstudy$fleet$rawEffort <- readRDS(effAssetPath)
# Setup fishing vessel ids
yourSmartRstudy$fleet$setEffortIds()
# View speed distribution to setup fishing point filter
yourSmartRstudy$fleet$plotSpeedDepth(
which_year = "2012",
speed_range = c(2, 8),
depth_range = c(-20, -600)
)
# Setup fishing points' filter
yourSmartRstudy$fleet$setFishPoinPara(
speed_range = c(2, 8),
depth_range = c(-20, -600)
)
# Compute fishing points
yourSmartRstudy$fleet$setFishPoin()
# Assign cell id to each fishing point
yourSmartRstudy$setCellPoin()
# Add week and month number to each point
yourSmartRstudy$fleet$setWeekMonthNum()
#####################
## Fishing Grounds ##
#####################
# Setup available data to identify fishing areas
yourSmartRstudy$setAvailData()
# Setup cluster analysis input
yourSmartRstudy$sampMap$setClusInpu()
# Run cluster analysis with the SKATER method
yourSmartRstudy$sampMap$calcFishGrou(numCuts = 3, minsize = 10,
modeska = "S", skater_method = "manhattan", nei_queen = FALSE)
# Setup cluster plot with 3 clusters
yourSmartRstudy$sampMap$setCutResult(ind_clu = 3)
# Map of the clusters' configuration
print(yourSmartRstudy$sampMap$ggCutFGmap)
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