In talbertc-usgs/NABatR: R Tools for Accessing and Manipulating North American Bat Monitoring Data

Get a token for NABat Database

library(nabatr)
# Enter your NABat username here
username_ = 'NABat_Username'
token_ = get_nabat_gql_token(username = username_)
token_

# If you are not using R-Studio or are not prompted for a password use this code below
#  to manually add in your password with the password variable:
# token_ = get_nabat_gql_token(username = username_, password = 'your-password')

# Note: if you leave run token_ = get_nabat_gql_token(),
#   it will prompt you for a username and then a password

Get Project dataframe which contains all of your acoustic stationary projects in the NABat Database

# Refresh token
token_ = get_refresh_token(token_)
# Get your projects lookup table
project_df_ = get_projects(token = token_)
# Display your projects lookup table
project_df_

Get Species dataframe which contains a species lookup table for auto and manual ids

# Refresh token
token_ = get_refresh_token(token_)
# Get your species lookup table
species_df_ = get_species(token = token_)
# Display your species lookup table
species_df_

Get all Acoustic Stationary Surveys within a single Project set with project_id_

# Refresh token
token_ = get_refresh_token(token_)
# Fill in project id using the project_df_ lookup table
project_id_ = 284 # Set equal to one of your project ids

# Get survey dataframe 
survey_df_ = get_acoustic_project_summary(token = token_, 
                                          project_id = project_id_, 
                                          project_df = project_df_)

proj_dates = unique(survey_df_$year)
# Display survey dataframe
survey_df_

Get all Acoustic Stationary Survey wav file data. Format: Acoustic Stationary Bulk Upload Template

# Select Year for project (defaults to 1st available year)
year_ = proj_dates[1]

# Refresh token
token_ = get_refresh_token(token_)
# Get stationary acoustic bulk upload format dataframe
acoustic_bulk_df_ = get_acoustic_bulk_wavs(token      = token_, 
                                           survey_df  = survey_df_,
                                           project_id = project_id_,
                                           year = year_)
# Display stationary acoustic bulk upload format dataframe
acoustic_bulk_df_

Use the Acoustic Stationary acoustic bulk dataframe to build a dataframe for auto and manual species id data

# Get Acoustic stationary acoustic bulk dataframe
nightly_observed_list_ = get_observed_nights(acoustic_bulk_df_)

auto_nights_df_ = nightly_observed_list_$auto_nightly_df
manual_nights_df_  = nightly_observed_list_$manual_nightly_df

# Display the two dataframes
manual_nights_df_
auto_nights_df_

Extracting unique species found for manual and automatic nights acoustic data in long format

# Individual species totals for either Manual or Automatic
manual_species_totals_l_ = get_species_counts_long(manual_nights_df_, filter=TRUE)
auto_species_totals_l_   = get_species_counts_long(auto_nights_df_, filter=TRUE)

# Both Manual and Automatic species totals 
all_species_totals_l_l_ = get_all_species_counts_long(auto_nights_df_, manual_nights_df_, fil = TRUE)

Extracting unique species found for manual and automatic nights acoustic data in WIDE format

# Extract totals from project at GRTS cell id and GRTS site name

# MANUAL
manual_species_totals_w_   = get_species_counts_wide(manual_nights_df_)
# --- totals at sites
manual_species_sites_df_w_ = manual_species_totals_w_$species_site_id_df
# --- totals at GRTS cell id
manual_species_grts_df_w_  = manual_species_totals_w_$species_grts_df

# AUTOMATIC
auto_species_totals_w_   = get_species_counts_wide(auto_nights_df_)
# --- totals at sites
auto_species_sites_df_w_ = auto_species_totals_w_$species_site_id_df
# --- totals at GRTS cell id
auto_species_grts_df_w_  = auto_species_totals_w_$species_grts_df

Setup a leaflet map to show

grts_map = get_grts_leaflet_map(all_grts       = unique(subset(survey_df_, survey_df_$year == year_)$grts_cell_id),
                                grts_with_data = unique(auto_nights_df_$GRTS),
                                project_df = project_df_,
                                project_id = project_id_)
# Display the grts map
grts_map

Build Acoustic stationary .docx report (will take more time if range_maps = TRUE)

# Refresh token
token_ = get_refresh_token(token_)

# Edit This file path to your own output directory to store the report (No trailing '/')
out_dir_doc = '/path/to/output/directory'
# Build report and return the doc to then save out
doc_ = build_ac_doc(out_dir = out_dir_doc,
                  file_name  = paste0('doc_report_',project_id_,'_',Sys.Date(),'.docx'),
                  project_df = project_df_,
                  project_id = project_id_,
                  auto_nights_df = auto_nights_df_,
                  manual_nights_df = manual_nights_df_,
                  map = grts_map,
                  manual_species_grts_df_w = manual_species_grts_df_w_,
                  auto_species_grts_df_w = auto_species_grts_df_w_,
                  auto_species_totals_l = auto_species_totals_l_,
                  manual_species_totals_l = manual_species_totals_l_,
                  date = format(Sys.time(), "%B %d, %Y"),
                  acoustic_bulk_df = acoustic_bulk_df_,
                  range_maps = FALSE)

# Note:  Setting range_maps = FALSE will significantly decrease processing time

# Save it out to a local directory
print(doc_, target = paste0(out_dir_doc, '/', paste0(year_, '_doc_report_',project_id_,'_',format(Sys.time(), '%Y_%m_%d_%H%M%S'),'.docx')))

talbertc-usgs/NABatR documentation built on April 22, 2020, 8:23 p.m.