Cotton

Prototypes/Cotton/Cotton_Shaun.apsimx

@@ -2,7 +2,7 @@
   "$type": "Models.Core.Simulations, Models",
   "ExplorerWidth": 282,
   "Version": 79,
-  "ApsimVersion": "Version 0.0.0.0, built 2020-02-24",
+  "ApsimVersion": "Version 0.0.0.0, built 2020-02-27",
   "Name": "Simulations",
   "Children": [
     {
@@ -6511,20 +6511,35 @@
           "$type": "Models.PostSimulationTools.ExcelInput, Models",
           "FileName": "emerald.xlsx",
           "SheetNames": [
-            "Yield",
-            "Fruit",
-            "SoilWater"
+            "Emerald_Phenology",
+            "Emerald_Yield",
+            "Emerald_Fruit",
+            "Emerald_SoilWater"
           ],
           "Name": "Emerald",
           "Children": [],
           "IncludeInDocumentation": false,
           "Enabled": true,
           "ReadOnly": false
         },
+        {
+          "$type": "Models.PostSimulationTools.ExcelInput, Models",
+          "FileName": "narrabri.xlsx",
+          "SheetNames": [
+            "Narrabri_Yield",
+            "Narrabri_Plant",
+            "Narrabri_SoilWater"
+          ],
+          "Name": "Narrabri",
+          "Children": [],
+          "IncludeInDocumentation": false,
+          "Enabled": true,
+          "ReadOnly": false
+        },
         {
           "$type": "Models.PostSimulationTools.PredictedObserved, Models",
           "PredictedTableName": "DailyReport",
-          "ObservedTableName": "Fruit",
+          "ObservedTableName": "Emerald_Fruit",
           "FieldNameUsedForMatch": "Clock.Today",
           "FieldName2UsedForMatch": null,
           "FieldName3UsedForMatch": null,

Prototypes/Cotton/munge-experiment-data/scripts/ayr/ayr.r

@@ -57,7 +57,7 @@ bolls <- bind_rows(bolls_2009, bolls_2010, bolls_2011, bolls_2012) #nb. 2008 dat
 # WRITE TO SPREADSHEET
 # --------------------
 
-sheets <- list(Phenology = phenology, Harvest = harvest, Plant = plant, Light = light_interception, Nodes = nodes_over_time, Bolls = bolls)  
+sheets <- list(Ayr_Phenology = phenology, Ayr_Harvest = harvest, Ayr_Plant = plant, Ayr_Light = light_interception, Ayr_Nodes = nodes_over_time, Ayr_Bolls = bolls)  
 write_xlsx(x = sheets, path = "./output/ayr.xlsx")
 
 

Prototypes/Cotton/munge-experiment-data/scripts/emerald/emerald.r

@@ -48,7 +48,7 @@ soilwater <- soilwater %>% select(Clock.Today, SimulationName, everything())
 # WRITE TO SPREADSHEET
 # --------------------
 
-sheets <- list(Phenology = phenology, Yield = yield, Fruit = fruit, SoilWater = soilwater)  
+sheets <- list(Emerald_Phenology = phenology, Emerald_Yield = yield, Emerald_Fruit = fruit, Emerald_SoilWater = soilwater)  
 write_xlsx(x = sheets, path = "./output/emerald.xlsx")
 
 

Prototypes/Cotton/munge-experiment-data/scripts/narrabri/narrabri.r

@@ -0,0 +1,51 @@
+#! /bin/bash
+
+
+library(tidyverse)
+
+library(readxl)
+library(writexl)
+
+library(lubridate)
+
+
+dir_sourcedata <- file.path("C:","Users","ver078","Dropbox","CottonModel","OldData","Narrabri(Stephen)", "Soil Probe Data")
+path <- file.path(dir_sourcedata, "ProbeReading Summary.xls")
+
+
+#nb. the probes only went down to 120cm. So all the sw measurments are the cumulative sw down to 120cm
+
+
+
+
+
+# ADD SimulationName Column and Clock.Today column 
+# ------------------------------------------------
+# nb. this is needed to do predicted vs observed in ApsimX
+
+yield <- yield %>% mutate("Clock.Today" = format(date, "%d/%m/%Y"))
+yield <- yield %>% mutate(SimulationName = paste("Narrabri_", year, "Sow", Treatment, sep = ""))
+yield <- yield %>% select(Clock.Today, SimulationName, everything())
+
+plant <- plant %>% mutate("Clock.Today" = format(date, "%d/%m/%Y"))
+plant <- plant %>% mutate(SimulationName = paste("Narrabri_", year, "Sow", Treatment, sep = ""))
+plant <- plant %>% select(Clock.Today, SimulationName, everything())
+
+soilwater <- soilwater %>% mutate("Clock.Today" = format(date, "%d/%m/%Y"))
+soilwater <- soilwater %>% mutate(SimulationName = paste("Narrabri_", year, "Sow", treatment, sep = ""))
+soilwater <- soilwater %>% select(Clock.Today, SimulationName, everything())
+
+
+
+
+
+
+
+
+# WRITE TO SPREADSHEET
+# --------------------
+
+sheets <- list(Narrabri_Yield = yield, Narrabri_Plant = plant, Narrabri_SoilWater = soilwater)  
+write_xlsx(x = sheets, path = "./output/narrabri.xlsx")
+
+

Prototypes/Cotton/munge-experiment-data/scripts/narrabri/narrabri_actuals.r

@@ -14,24 +14,133 @@ path <- file.path(dir_sourcedata, "Deficit Trials - Output Summary.xls")
 
 
 
+
+# Get Input Data from Spreadsheet
+# -------------------------------
+
 lai_2006 <- read_xls(path, sheet = "Actuals 0607", range = "D4:K8")
-boll_no_2006 <- read_xls(path, sheet = "Actuals 0607", range = "D12:K16") #actually "fruit count" but I interperate this as boll no.
+bolls_2006 <- read_xls(path, sheet = "Actuals 0607", range = "D12:K16") #actually "fruit count" but I interperate this as boll no.
 yield_2006 <- read_xls(path, sheet = "Actuals 0607", range = "D27:E31")
-sites_no_2006 <- read_xls(path, sheet = "Actuals 0607", range = "P4:T8")
+sites_2006 <- read_xls(path, sheet = "Actuals 0607", range = "P4:T8")
 
 
 lai_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D4:K8")
-boll_no_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D12:K16") 
-square_no_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D20:K24") 
+bolls_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D12:K16") 
+squares_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D20:K24") 
 yield_2007 <- read_xls(path, sheet = "Actuals 0708", range = "D27:E31")
-sites_no_2007 <- read_xls(path, sheet = "Actuals 0708", range = "P4:T8")
+sites_2007 <- read_xls(path, sheet = "Actuals 0708", range = "P4:U8")
 
 
 lai_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D4:K8")
-boll_no_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D12:K16") 
-square_no_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D20:K24") 
-yield_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D27:E31")
-sites_no_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P4:T8")
-greenboll_no_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P4:T8")
-openboll_no_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P4:T8")
-maturity_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P4:T8")
+bolls_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D12:K16") 
+squares_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D20:K24") 
+yield_2008 <- read_xls(path, sheet = "Actuals 0809", range = "D27:G31")
+sites_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P4:U8")
+greenbolls_2008 <- read_xls(path, sheet = "Actuals 0809", range = "O12:U16")
+openbolls_2008 <- read_xls(path, sheet = "Actuals 0809", range = "O20:U25")
+maturity_2008 <- read_xls(path, sheet = "Actuals 0809", range = "P28:Q33")
+
+
+
+# Clean up the input data
+# -----------------------
+
+lai_2006 <- lai_2006 %>% select(-2,-3)
+lai_2007 <- lai_2007 %>% select(-2,-3)
+lai_2008 <- lai_2008 %>% select(-2,-3)
+
+bolls_2006 <- bolls_2006 %>% select(-2,-3)
+bolls_2007 <- bolls_2007 %>% select(-2,-3)
+bolls_2008 <- bolls_2008 %>% select(-2,-3)
+
+squares_2007 <- squares_2007 %>% select(-2,-3)
+squares_2008 <- squares_2008 %>% select(-2,-3)
+
+greenbolls_2008 <- greenbolls_2008 %>% select(-2)
+openbolls_2008 <- openbolls_2008 %>% select(-2)
+
+
+
+
+# Munge the Data
+# --------------
+
+
+# 2006
+# ----
+
+lai_2006 <- lai_2006 %>% pivot_longer(cols = c("71","86","104","126","161"), names_to = "das", values_to = "lai")
+lai_2006 <- lai_2006 %>% pivot_longer(cols = lai, names_to = "variable", values_to = "values")
+bolls_2006 <- bolls_2006 %>% pivot_longer(cols = c("71","86","104","126","161"), names_to = "das", values_to = "bolls")
+bolls_2006 <- bolls_2006 %>% pivot_longer(cols = bolls, names_to = "variable", values_to = "values")
+sites_2006 <- sites_2006 %>% pivot_longer(cols = c("71","86","104","126"), names_to = "das", values_to = "sites")
+sites_2006 <- sites_2006 %>% pivot_longer(cols = sites, names_to = "variable", values_to = "values")
+
+plant_2006 <- bind_rows(lai_2006, sites_2006, bolls_2006)
+plant_2006 <- plant_2006 %>% pivot_wider(names_from = variable, values_from = values)
+plant_2006 <- plant_2006 %>% mutate(date = dmy("10/10/2006") + days(das))
+plant_2006 <- plant_2006 %>% mutate(year = 2006) %>% select(year, Treatment, date, das, everything())
+
+yield_2006 <- yield_2006 %>% mutate(date = dmy("10/10/2006") + days(163)) # I have no idea what the harvest date was so I used das=163 because last value in long table in "Actuals 0607" worksheet
+yield_2006 <- yield_2006 %>% mutate(year = 2006) %>% select(year, Treatment, everything())
+
+
+# 2007
+# ----
+
+lai_2007 <- lai_2007 %>% pivot_longer(cols = c("79","92","115","135","170"), names_to = "das", values_to = "lai")
+lai_2007 <- lai_2007 %>% pivot_longer(cols = lai, names_to = "variable", values_to = "values")
+bolls_2007 <- bolls_2007 %>% pivot_longer(cols  = c("79","92","115","135","170"), names_to = "das", values_to = "bolls")
+bolls_2007 <- bolls_2007 %>% pivot_longer(cols = bolls, names_to = "variable", values_to = "values")
+squares_2007 <- squares_2007 %>% pivot_longer(cols  = c("79","92","115","135","170"), names_to = "das", values_to = "squares")
+squares_2007 <- squares_2007 %>% pivot_longer(cols = squares, names_to = "variable", values_to = "values")
+sites_2007 <- sites_2007 %>% pivot_longer(cols  = c("79","92","115","135","170"), names_to = "das", values_to = "sites")
+sites_2007 <- sites_2007 %>% pivot_longer(cols = sites, names_to = "variable", values_to = "values")
+
+plant_2007 <- bind_rows(lai_2007, sites_2007, squares_2007, bolls_2007)
+plant_2007 <- plant_2007 %>% pivot_wider(names_from = variable, values_from = values)
+plant_2007 <- plant_2007 %>% mutate(date = dmy("15/10/2007") + days(das))
+plant_2007 <- plant_2007 %>% mutate(year = 2007) %>% select(year, Treatment, date, das, everything())
+
+
+yield_2007 <- yield_2007 %>% mutate(date = dmy("15/10/2007") + days(218)) # I have no idea what the harvest date was so I used das=218 because last value in long table in "Actuals 0607" worksheet
+yield_2007 <- yield_2007 %>% mutate(year = 2007) %>% select(year, Treatment, everything())
+
+
+
+# 2008
+# ----
+
+lai_2008 <- lai_2008 %>% pivot_longer(cols = c("76","90","116","137","165"), names_to = "das", values_to = "lai")
+lai_2008 <- lai_2008 %>% pivot_longer(cols = lai, names_to = "variable", values_to = "values")
+bolls_2008 <- bolls_2008 %>% pivot_longer(cols  = c("76","90","116","137","165"), names_to = "das", values_to = "bolls")
+bolls_2008 <- bolls_2008 %>% pivot_longer(cols = bolls, names_to = "variable", values_to = "values")
+squares_2008 <- squares_2008 %>% pivot_longer(cols  = c("76","90","116","137","165"), names_to = "das", values_to = "squares")
+squares_2008 <- squares_2008 %>% pivot_longer(cols = squares, names_to = "variable", values_to = "values")
+sites_2008 <- sites_2008 %>% pivot_longer(cols  = c("76","90","116","137","165"), names_to = "das", values_to = "sites")
+sites_2008 <- sites_2008 %>% pivot_longer(cols = sites, names_to = "variable", values_to = "values")
+greenbolls_2008 <- greenbolls_2008 %>% pivot_longer(cols  = c("76","90","116","137","165"), names_to = "das", values_to = "greenbolls")
+greenbolls_2008 <- greenbolls_2008 %>% pivot_longer(cols = greenbolls, names_to = "variable", values_to = "values")
+openbolls_2008 <- openbolls_2008 %>% pivot_longer(cols  = c("76","90","116","137","165"), names_to = "das", values_to = "openbolls")
+openbolls_2008 <- openbolls_2008 %>% pivot_longer(cols = openbolls, names_to = "variable", values_to = "values")
+
+plant_2008 <- bind_rows(lai_2008, sites_2008, squares_2008, bolls_2008, greenbolls_2008, openbolls_2008)
+plant_2008 <- plant_2008 %>% pivot_wider(names_from = variable, values_from = values)
+plant_2008 <- plant_2008 %>% mutate(date = dmy("15/10/2008") + days(das))
+plant_2008 <- plant_2008 %>% mutate(year = 2008) %>% select(year, Treatment, date, das, everything())
+
+yield_2008 <- yield_2008 %>% mutate(date = dmy("15/10/2008") + days(218)) # I have no idea what the harvest date was so I used das=218 because last value in long table in "Actuals 0607" worksheet
+yield_2008 <- yield_2008 %>% mutate(year = 2008) %>% select(year, Treatment, everything())
+
+
+# Combined
+# --------
+
+plant <- bind_rows(plant_2006, plant_2007, plant_2008)
+
+yield <- bind_rows(yield_2006, yield_2007, yield_2008)
+
+
+
+
+