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Subregion modification #52

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Subregion modification #52

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2a31a56
Updated SRB landleaf data for the four hist years
evasinha Nov 18, 2019
85b4c6c
Removed rows for repeating data for all hist years
evasinha Nov 18, 2019
e3bd0ef
Updated SRB land allocation and price historical data
evasinha Dec 5, 2019
b520b35
Updated SRB land allocation
evasinha Dec 9, 2019
4717443
Resolved merge conflict in setup.R.
evasinha Dec 9, 2019
f9f35b7
Removed duplicate file for SRB prices
evasinha Dec 9, 2019
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81 changes: 8 additions & 73 deletions R/read_data.R
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Original file line number Diff line number Diff line change
Expand Up @@ -42,9 +42,9 @@ ReadData_LN0 <- function(aRegionName, aSubRegion, subregionData) {
landAllocation = allocation) ->
data

# Sum allocation and find unique logit exponent across region, root, and year
# Sum allocation and find unique logit exponent across region, and root
data %>%
group_by(region, subregion, LandAllocatorRoot, year.fillout) %>%
group_by(region, subregion, LandAllocatorRoot) %>%
summarize(landAllocation = sum(landAllocation),
logit.exponent = unique(logit.exponent)) ->
data
Expand Down Expand Up @@ -92,9 +92,9 @@ ReadData_LN1_Node <- function(aRegionName, aSubRegion, subregionData) {
logit.year.fillout = year.fillout) ->
data

# Find unique logit exponent values across region, root, LandNode1, and year
# Find unique logit exponent values across region, root, and LandNode1
data %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1, logit.year.fillout) %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1) %>%
summarize(logit.exponent = unique(logit.exponent),
unManagedLandValue = unique(unManagedLandValue)) ->
data
Expand Down Expand Up @@ -149,19 +149,6 @@ ReadData_LN1_LeafChildren <- function(aRegionName, aSubRegion, subregionData, aS
group_by(region, subregion, LandAllocatorRoot, LandNode1, UnmanagedLandLeaf, year) %>%
summarize(allocation = sum(allocation)) ->
data

# For the SubRegion if data not available for all historical years then repeat data for all historical years
if(nrow(data) != 0) {
if (! identical(data$year , TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS) ){
data %>%
select(-year) %>%
mutate(UNIQUE_JOIN_FIELD = 1) %>%
full_join(mutate(tibble::tibble(year=TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS), UNIQUE_JOIN_FIELD = 1), by = "UNIQUE_JOIN_FIELD") %>%
select(-UNIQUE_JOIN_FIELD) ->
data
}
}

}
else {
# Read in calibration data
Expand Down Expand Up @@ -205,9 +192,9 @@ ReadData_LN2_Node <- function(aRegionName, aSubRegion, subregionData) {
rename(logit.exponent = LandNode2.logit.exponent) ->
data

# Find unique logit exponent values across region, root, LandNode1, LandNode2, and year
# Find unique logit exponent values across region, root, LandNode1, and LandNode2
data %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, year.fillout) %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2) %>%
summarize(logit.exponent = unique(logit.exponent)) ->
data
}
Expand Down Expand Up @@ -262,19 +249,6 @@ ReadData_LN2_LandLeaf <- function(aRegionName, aSubRegion, subregionData, aScena
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, LandLeaf, year) %>%
summarize(allocation = sum(allocation)) ->
data

# For the SubRegion if data not available for all historical years then repeat data for all historical years
if(nrow(data) != 0) {
if (! identical(data$year , TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS) ){
data %>%
select(-year) %>%
mutate(UNIQUE_JOIN_FIELD = 1) %>%
full_join(mutate(tibble::tibble(year=TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS), UNIQUE_JOIN_FIELD = 1), by = "UNIQUE_JOIN_FIELD") %>%
select(-UNIQUE_JOIN_FIELD) ->
data
}
}

}
else {
# Read in calibration data
Expand Down Expand Up @@ -325,19 +299,6 @@ ReadData_LN2_UnmanagedLandLeaf <- function(aRegionName, aSubRegion, subregionDat
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, UnmanagedLandLeaf, year) %>%
summarize(allocation = sum(allocation)) ->
data

# For the SubRegion if data not available for all historical years then repeat data for all historical years
if(nrow(data) != 0) {
if (! identical(data$year , TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS) ){
data %>%
select(-year) %>%
mutate(UNIQUE_JOIN_FIELD = 1) %>%
full_join(mutate(tibble::tibble(year=TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS), UNIQUE_JOIN_FIELD = 1), by = "UNIQUE_JOIN_FIELD") %>%
select(-UNIQUE_JOIN_FIELD) ->
data
}
}

}
else {
# Read in calibration data
Expand Down Expand Up @@ -381,9 +342,9 @@ ReadData_LN3_Node <- function(aRegionName, aSubRegion, subregionData) {
rename(logit.exponent = LandNode3.logit.exponent) ->
data

# Find unique logit exponent values across region, root, LandNode1, LandNode2, LandNode3, and year
# Find unique logit exponent values across region, root, LandNode1, LandNode2, and LandNode3
data %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, LandNode3, year.fillout) %>%
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, LandNode3) %>%
summarize(logit.exponent = unique(logit.exponent)) ->
data
}
Expand Down Expand Up @@ -465,19 +426,6 @@ ReadData_LN3_LandLeaf <- function(aRegionName, aSubRegion, subregionData, aScena
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, LandNode3, LandLeaf, year) %>%
summarize(allocation = sum(allocation)) ->
data

# For the SubRegion if data not available for all historical years then repeat data for all historical years
if(nrow(data) != 0) {
if (! identical(data$year , TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS) ){
data %>%
select(-year) %>%
mutate(UNIQUE_JOIN_FIELD = 1) %>%
full_join(mutate(tibble::tibble(year=TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS), UNIQUE_JOIN_FIELD = 1), by = "UNIQUE_JOIN_FIELD") %>%
select(-UNIQUE_JOIN_FIELD) ->
data
}
}

}
else {
# Read in calibration data
Expand Down Expand Up @@ -531,19 +479,6 @@ ReadData_LN3_UnmanagedLandLeaf <- function(aRegionName, aSubRegion, subregionDat
group_by(region, subregion, LandAllocatorRoot, LandNode1, LandNode2, LandNode3, UnmanagedLandLeaf, year) %>%
summarize(allocation = sum(allocation)) ->
data

# For the SubRegion if data not available for all historical years then repeat data for all historical years
if(nrow(data) != 0) {
if (! identical(data$year , TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS) ){
data %>%
select(-year) %>%
mutate(UNIQUE_JOIN_FIELD = 1) %>%
full_join(mutate(tibble::tibble(year=TIME.PARAMS[[aScenarioInfo$mScenarioType]]$HISTORY.YEARS), UNIQUE_JOIN_FIELD = 1), by = "UNIQUE_JOIN_FIELD") %>%
select(-UNIQUE_JOIN_FIELD) ->
data
}
}

}
else {
# Read in calibration data
Expand Down
5 changes: 3 additions & 2 deletions R/setup.R
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Original file line number Diff line number Diff line change
Expand Up @@ -271,7 +271,7 @@ Leaf_setup <- function(aLandAllocator, aRegionName, aData, aColName,
parentNames <- unique(parentNames)

# Read-in yield, cost, tech change
AgProductionTechnology_setup(newLeaf, aAgData, aScenarioInfo)
AgProductionTechnology_setup(aLandAllocator, newLeaf, aAgData, aScenarioInfo)
}

# Loop over years and add allocation
Expand Down Expand Up @@ -349,11 +349,12 @@ LandNode_addChild <- function(aLandNode, aChild, aParentNames) {
#' AgProductionTechnology_setup
#'
#' @details Setup technology (e.g., CalOutput, technical change, cost, etc.)
#' @param aLandAllocator LandAllocator that needs set up
#' @param aLandLeaf Land leaf
#' @param aAgData Agricultural technology data
#' @param aScenarioInfo Scenario info object
#' @author KVC October 2017
AgProductionTechnology_setup <- function(aLandLeaf, aAgData, aScenarioInfo) {
AgProductionTechnology_setup <- function(aLandAllocator, aLandLeaf, aAgData, aScenarioInfo) {
# Silence package checks
per <- year <- AgProductionTechnology <- GCAM_commodity <- NULL

Expand Down
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