Skip to content

Commit

Permalink
Assign growth stage
Browse files Browse the repository at this point in the history
  • Loading branch information
Sungchan Oh committed Jul 3, 2024
1 parent 007f882 commit c2b8e81
Showing 1 changed file with 167 additions and 35 deletions.
202 changes: 167 additions & 35 deletions DataExplore.r
View file
Original file line number Diff line number Diff line change
Expand Up @@ -36,30 +36,45 @@ c("/depot/smarterag/data/HSI/Master files/Hyperspectral_data_AAPF_experiment_374



# Unwanted data (incomplete scanning, demo for tour, etc.)
# See the interim results from this script (DataExplore.r)
#-------------------------------------------------------
# EXP ID TREATMENT DFP SCAN_DATETIME_BY15MIN NUM_SCANS
#-------------------------------------------------------
# List unwanted data
# (created by incomplete scanning, demo during AAPF tour visits, etc.)
#
# How to specify unwanted measurements
#
# 1. Run this script (DataExplore.r).
# 2. In the output of DataExplore.r (Overview 1 & 2),
# you'll see a list of potential unwanted measurements
# (e.g., a handful of measurements in an enough time period).
# 3. Review this list and decide which measurements you want
# to exclude from your analysis.
# 4. Look for a variable named df.unwanted below.
# This variable is a list where you can specify the unwanted
# measurements you identified in step 3.
# 5. Fill in the list under df.unwanted with the attributes of the
# measurements you want to exclude. The number of items in the list will
# depend on your specific experiment and the output from DataExplore.r.
#
# Unwanted data example:
#----------------------------------------------------------
# EXP ID TREATMENT DFP SCAN_DATETIME_BY15MIN NUM_SCANS
#----------------------------------------------------------
# 1
#374 20 -1 59 2023-10-30 11:15:00 4

# 374 20 -1 59 2023-10-30 11:15:00 4
#
# 2
#374 50-3 27 2023-09-28 09:15:00 2

# 374 50-3 27 2023-09-28 09:15:00 2
#
# 3
#374 50-3 27 2023-09-28 09:00:00 24
# or
#374 50-3 32 2023-10-03 15:00:00 24

# 374 50-3 27 2023-09-28 09:00:00 24 OR
# 374 50-3 32 2023-10-03 15:00:00 24
#
# 4
#374 50-4 27 2023-09-28 09:45:00 24
# or
#374 50-4 32 2023-10-03 15:00:00 24

# 374 50-4 27 2023-09-28 09:45:00 24 OR
# 374 50-4 32 2023-10-03 15:00:00 24
#
# 5
#396 20-1 55 2024-04-29 12:00:00 1
#-------------------------------------------------------
# 396 20-1 55 2024-04-29 12:00:00 1
#----------------------------------------------------------
df.unwanted <- data.frame(
EXP_ID=c(374, 374, 374, 374, 396),
TREATMENT=c("20 -1", "50-3", "50-3", "50-4", "20-1"),
Expand All @@ -71,14 +86,111 @@ df.unwanted <- data.frame(
stringsAsFactors=FALSE)


# Treatment name change
# List descriptive treatment info
#
# The df.convert.treatment placeholder allows you to change
# treatment attributes assigned by PPEW. It takes a list of pairs,
# where each pair contains:
#
# - Input Treatment Attribute (from): check from Overview 1 & 2.
# - New treatment attribute (to): a string (space allowed) that
# best describes the treatment itself.
#
# Treatment change info example:
df.convert.treatment <- data.frame(
from=c("20 -1", "20-2", "50-3", "50-4", "20-1", "20-2"),
to =c("20", "20", "80", "80", "20", "20"),
stringAsFactors=FALSE)



# List growth stage info
#
# The df.growth.stage variable lets you define the growth stage
# for each data point based on a combination of three factors:
# EXP ID, TREATMENT, DFP
#
# To determine the appropriate growth stage for each data point
# based on this combination, refer to Overview 5.
#
# Growth stage info Example:
df.growth.stage <- data.frame(
EXP_ID =c(374, 374, 374, 374,
375, 375, 375, 375,
378, 378, 378, 378,
380, 380, 380, 380,
390, 390, 390, 390,
391, 391, 391, 391,
396, 396, 396, 396,
401, 401, 401, 401),
TREATMENT =c("20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80",
"20", "20", "80", "80"),
DFP =c(33, 59, 32, 50,
35, 56, 28, 48,
35, 60, 28, 56,
34, 63, 28, 53,
35, 63, 28, 48,
35, 63, 28, 56,
42, 70, 42, 63,
42, 73, 43, 65),
GROWTH_STAGE=c('V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT'))

df.growth.stage <- data.frame(
EXP_ID =c(374, 374, 374, 374,
375, 375, 375, 375,
378, 378, 378, 378,
380, 380, 380, 380,
390, 390, 390, 390,
391, 391, 391, 391,
396, 396, 396, 396,
401, 401, 401, 401),
TREATMENT =c(20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80,
20, 20, 80, 80),
DFP =c(33, 59, 32, 50,
35, 56, 28, 48,
35, 60, 28, 56,
34, 63, 28, 53,
35, 63, 28, 48,
35, 63, 28, 56,
42, 70, 42, 63,
42, 73, 43, 65),
GROWTH_STAGE=c('V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT',
'V8', 'VT', 'V8', 'VT'))













Expand Down Expand Up @@ -223,7 +335,7 @@ message('Succeeded importing HSI data...')
df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]

# Show summary of rgb data
message('\nRGB Data Acquisiton Summary\n')
message('\nRGB Data Acquisiton Summary (Overview 1)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))

# Round down scan date and time down to nearest 15 minute and display
Expand All @@ -233,11 +345,11 @@ df.rgb.perscan["SCAN_DATETIME"] =
format=format)
df.rgb.perscan["SCAN_DATETIME_BY15MIN"] =
lubridate::round_date(df.rgb.perscan$SCAN_DATETIME, "15 minutes")
message('\nRGB Data Acquisiton Summary by Date and Time\n')
message('\nRGB Data Acquisiton Summary by Date and Time (Overview 2)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, SCAN_DATETIME_BY15MIN))
message('\nPlease use [`EXP ID`, TREATMENT, SCAN_DATETIME_BY15MIN]')
message('\nPlease check [`EXP ID`, TREATMENT, SCAN_DATETIME_BY15MIN]')
message('to exclude data from incomplete scan session...')
message('Check df.unwanted in DataExplore.r to check how to exclude records...\n')
message('Check df.unwanted in DataExplore.r to exclude such records...\n')



Expand All @@ -253,9 +365,8 @@ for(i in 1:nrow(df.unwanted)){
TREATMENT == row$TREATMENT &
SCAN_DATETIME_BY15MIN == row$SCAN_DATETIME_BY15MIN))
}
# Show data acquisiton summary of filtering out unwanted data
df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
message('\nRGB Data Acquisiton Summary (Unwanted Data Filtered)\n')
message('\nRGB Data Acquisiton Summary (Unwanted Data Filtered, Overview 3)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))


Expand All @@ -267,9 +378,8 @@ for(i in 1:nrow(df.convert.treatment)){
row <- df.convert.treatment[i,]
df.rgb$TREATMENT[df.rgb$TREATMENT==row$from] <- row$to
}
# Show data acquisiton summary of filtering out unwanted data
df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
message('\nRGB Data Acquisiton Summary (Treatment Info Updated)\n')
message('\nRGB Data Acquisiton Summary (Treatment Updated, Overview 4)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))


Expand All @@ -278,23 +388,45 @@ print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))

# DFP is always smaller than 365 (to prevent case with wrong year input)
df.rgb$DFP = df.rgb$DFP %% 365
# Show data acquisiton summary of filtering out unwanted data
df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
message('\nRGB Data Acquisiton Summary (DFP is always lower than 365)\n')
message('\nRGB Data Acquisiton Summary (DFP Always Less Than 365, Overview 5)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP))





# Set Growth stage
# Add growth stage attribute
df.rgb$GROWTH_STAGE <- NA
for(i in 1:nrow(df.growth.stage)){
row <- df.growth.stage[i,]
df.rgb$GROWTH_STAGE[(df.rgb$`EXP ID` == row$EXP_ID) &
(df.rgb$TREATMENT == row$TREATMENT) &
(df.rgb$DFP == row$DFP)] <- row$GROWTH_STAGE
}
df.rgb.perscan <- df.rgb[which(df.rgb$View=="Top" & df.rgb$variable=="Surface"), ]
message('\nRGB Data Acquisiton Summary (Growth Stage Added, Overview 6)\n')
print(count(df.rgb.perscan, `EXP ID`, TREATMENT, DFP, GROWTH_STAGE))







# Remove SCAN_TIME SCAN_DATE SCAN_DATETIME SCAN_DATETIME_BY15MIN

# Save data?

# Repeat for df.hsi

######### Combine rgb and hsi data using df <- rbind(df.rgb, df.hsi)



# frame_nr 0-11 (normal) , 0-23 for one scan
# For "RGB-SideAll", change column names Frame0-11 to major, major+30...
# Remove SCAN_TIME SCAN_DATE SCAN_DATETIME SCAN_DATETIME_BY15MIN

# Do the same for df.hsi
######### Combine rgb and hsi data
#########df <- rbind(df.rgb, df.hsi)



Expand Down

0 comments on commit c2b8e81

Please sign in to comment.