# This function downloads the studies you provide in a list:

# library('skimr')
library('tidyverse')
library(ggmap)
library(move)
library(ggplot2)
loginStored <- movebankLogin(username = "Diego_Ellis", password = "")
login = loginStored
getMovebank("tag_type", loginStored)
# Show me all studies
# all_studies <- getMovebank(entity_type = "study", login=loginStored)
# Look at MPIO studies:
MPIO_studies = searchMovebankStudies(x="MPIO", login=loginStored)
# For eobs function need to find out who the PIs are
# Martin -> Can I ask Movebnak folks to run a query -> All studies with eobs tags of MPIO
# Ask for access for these to Martin:
eobs_studies = searchMovebankStudies(x="eobs", login=loginStored)
e_obs_studies = searchMovebankStudies(x="e-obs", login=loginStored)
e_Obs_studies = searchMovebankStudies(x="e-Obs", login=loginStored)
extra_studies <- c('High-altitude flights of Himalayan vultures (data from Sherub et al. 2016)',
'Corvus splendens Translocation BHUTAN', 'Livestock Movement in Bhutan', 'Steppe Eagle Bhutan',
'Takin Sangay Bhutan', 'Tragopans in Bhutan')
studies_to_check <- c(MPIO_studies, eobs_studies, e_Obs_studies, extra_studies)
# Is there a way to see what studies have e-obs temperature as a column? Or to see privacy
# studies_to_check <- studies_to_check[1:3]

ind_studies_with_eobs_temperature <- function(login, studylist, plot_this_data = NULL){
# Check which of the MPIO studies has e-obs data:
df_out <- data.frame(matrix(NA, length(studylist), 9))
names(df_out) <- c('study_name', 'has_eobs_temperature',
 'private_data', 'number_of_fixes', 'has_acc', "movebank_id",
 "license_terms", "main_location_long", "main_location_lat")
all_studies <- getMovebank(entity_type = "study", login=loginStored)

# as.data.frame(t(sapply(studylist, function(x){

  for(x in 1:length(unique(studylist))){

# x <- studylist[1]
# x <- studylist[10]
x <- studylist[x]
studyID <- x
# study_index_id <- which(studyID %in% studylist)
study_index_id <- which(studylist %in% studyID)
print(study_index_id)
df_out[study_index_id,]$study_name <- studylist[study_index_id]
## get GPS and accelerometer data within a time period
     ## create a vector with attributes for all sensors included in the study
 attrib <- unique(c(as.character(getMovebankSensorsAttributes(studyID,
                                                                  login=loginStored)$short_name),
                        'sensor_type_id', 'deployment_id', 'event_id',
                        'individual_id', 'tag_id'))
# indID <- getMovebank("individual", login=login, study_id=studyID)$id[50]
   # ## get a summary of information about the two studies
     # getMovebank("study", login=login, study_id=c(studyID,studyID2))
     # Check e-obs temp
     if(length(grep("eobs_temperature", attrib)) > 0){
df_out[study_index_id,]$has_eobs_temperature <- 1
print(paste0('study ', studyID, ' has e-obs temperature'))
     	}else{
df_out[study_index_id,]$has_eobs_temperature <- 0
     		print(paste0('study ', studyID, ' has no e-obs temperature'))
     	}
     	# Check if has ACC
     	if( any(getMovebankSensorsAttributes(study=studyID,login=loginStored)$sensor_type_id == "2365683") ){
print(paste0('study ', studyID, ' has accelerometers'))
df_out[study_index_id,]$has_acc <- 1
     	}else{
     		print(paste0('study ', studyID, ' has no accelerometers'))
df_out[study_index_id,]$has_acc <- 0
     	}
# Data privacy:
if( length(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]) > 0 ){
  df_out[study_index_id,]$private_data <- as.character(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]$there_are_data_which_i_cannot_see)
}else{df_out[study_index_id,]$private_data <- NA}
     	## return(df_out)
# Get the Movebank ID
if( length(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]) > 0 ){
df_out[study_index_id,]$movebank_id <- as.numeric(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]$id)
}else{df_out[study_index_id,]$movebank_id <- NA}
# main_location_long
if( length(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]) > 0 ){
df_out[study_index_id,]$main_location_long <- as.numeric(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]$main_location_long)
}else{df_out[study_index_id,]$main_location_long <- NA}
# main_location_lat
if( length(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]) > 0 ){
df_out[study_index_id,]$main_location_lat <- as.numeric(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]$main_location_lat)
}else{df_out[study_index_id,]$main_location_lat <- NA}
# license_terms
if( length(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]) > 0 ){
df_out[study_index_id,]$license_terms <- as.character(all_studies[all_studies$name  %in%  df_out[study_index_id,]$study_name,]$license_terms)
}else{df_out[study_index_id,]$license_terms <- NA}

 # return(df_out)
# Check permission status
     } # End of for loop
     rownames(df_out) <- NULL
if(!is.null(plot_this_data)){
# Subset all studies by the ones I found that have e-obs temperature:
all_studies_I_want <- all_studies[all_studies$name  %in%  df_out[df_out$has_eobs_temperature == 1,]$study_name,]
world <- map_data("world")
# Blue means there are private data and restricitons.
print( ggplot() +
  geom_polygon(data = world,
               fill = "grey38",
               aes(x = long, y = lat, group = group)) +
  geom_point(data = all_studies_I_want,
             aes(x = main_location_long, y = main_location_lat, color = as.factor(there_are_data_which_i_cannot_see))) +
  scale_color_discrete(guide = guide_legend(title = "Data Restrictions"))
  )
}

     print(paste0('A total of ', sum(df_out[df_out$has_eobs_temperature == 1,]$has_eobs_temperature, na.rm = TRUE), ' out of ', nrow(df_out), ' studies has e-obs temperature data'))

     return(df_out)

     # Sarah: Ask them to do a query:
     # ))) # End of sapply
} # End of function
# ind_studies_with_eobs_temperature(login = login, studylist = MPIO_studies)
study_info <- ind_studies_with_eobs_temperature(login = login, studylist = studies_to_check, plot_this_data = TRUE)


# Function:
# Things to add:  Need permision!!!
     ## get deployments reference information from the study
#getMovebank(entity_type='deployment' , login= login,studyID = studyID )
## get a summary of information about the two studies
#getMovebank(entity_type="study", login=login, study_id=studyID)
 ## get animal reference information from the study
  #   head(getMovebank("individual", login=login, study_id=studyID))

all_studies <- getMovebank(entity_type = "study", login=loginStored)
# Subset all studies by the ones I found that have e-obs temperature:
all_studies_I_want <- all_studies[all_studies$name  %in%  study_info[study_info$has_eobs_temperature == 1,]$study_name,]
write.csv(all_studies_I_want, file = '/Users/diegoellis/Dropbox/Wikelski_Temperature/all_studies_I_want.csv')

# Use recursive? -> microhabitats?

# Get temperature, extract SRTM, get elevation above ellipsoid, get wind direction

#
# Extract from this guy: 'High-altitude flights of Himalayan vultures (data from Sherub et al. 2016)'
# Elephants Java FZG MPIO DAMN
# e-Obs GPRS Himalayan Griffon, Sherub, Bhutan