NEWS.md
download_wastd_turtledata(): drop logger encounters, which have been removed from the WAStD API and migrated to LoggerObservations.map_fanangles using https://github.com/dbca-wa/leaflet.circlesector/ (#46)turtle_date_awst_text
wastd_data: summarise_wastd_data_per_day_site() ## Docs ## DataEncounter class. Those Observations which only ever are recorded against AnimalEncounter, TurtleNestEncounter, or LineTransectEncounter, will show now their details in the encounter group. This simply adds more fields.
parse_encounterobservations() now includes these details.download_wastd_turtledata() now doesn’t have to merge AE/TNE/LTE details against Observation tables.TurtleTagObservation and TurtleNestDisturbanceObservation, could also happen when not associated with an animal or turtle nest, and therefore only include the Encounter details in the WAStD API.TurtleNestObservation.nest_position has been replaced and merged with the already existing TurtleNestEncounter.habitat in WAStD. This simplifies the contents of the WAStD table TurtleNestObservation, which is aptly named turtle-nest-excavation in the API to include only excavation data (egg counts, HS/ES, nest depth, ambient temperatures). “Nest habitat-only” records have been deleted from TurtleNestObservation. The calculation of HS and ES is also rectified to now exclude a false 0 for “Nest habitat-only” records (which are deleted and not coming back anyways).download_wastd_turtledata(). This should restore behaviour of analysis functions to 0.5.5. ## Docs ## Datadownload_wastd_turtledata()
wastd_data.download_wastd_turtledata() now shows correct encounter details for nested observations like nest tags, nest loggers etc. ## Minor fixesdownload_wastd_turtledata() infers verbosity from get_wastdr_verbose(). ## Docs ## Datadownload_w2_data(). (#29) ## Minor fixeswastdr_msg_* has new parameter verbose = get_wastdr_verbose() because we always want to make message verbosity conditional. ## Docs ## Datasite also the Locality (area), e.g. “Ningaloo”. This allows filtering to whole monitoring programs.is_active to indicate whether they are a closed duplicate profile or an active one. This is useful to exclude duplicate profiles from user name mapping (e.g. in etlTurtleNesting).odkc_data is not generated from wastdr::download_odkc_turtledata2020(). The first 100 records of each element are retained and sanitised of PII (names).download_wastd_turtledata() was extended to include LoggerObservations as nest_loggers in addition to the superseded LoggerEncounters. This prepares etlTurtleNesting to migrate the reports from using LoggerEnc to LoggerObs.Status Oct 2020 ## Minor fixes * download_odkc_turtledata_2020 now includes Site Visit Start (Map)
download_wastd_turtledata called parse_encounterobservations which called add_dates incorrectly. Dates are now preserved and value-added with season, calendar and turtle date and local datetime.download_w2_data to extract and parse WAMTRAM2. Early stages with improvements planned.Start work on ODKC to WAStD data ingest via ruODK, odkc_data, wastd_post_one and wastd_bulk_post. The hard bits are:
filter_dead() and filter_alive() work for WAStD and ODKC data, see examples.wastd_GET drops response, keeps url, date, and status_code. Results now always expected from WAStD in key features, not results.wastd_parse function parses any non-GeoJSON TSC API response, while wastd_parse_gj will parse amap_tracks(), map_nests(), map_dist() accept new parameters: wastd_url (default get_wastd_url()), and cluster (whether to cluster markers).parse_surveys() now includes an HTML link to the admin change_url in the data curation portal.Added datetime_as_season, datetime_as_isoweek, datetime_as_turtledate. This speeds up the parsers by re-using the costly string-to-date conversion from datetime.
Added isoweek to parsers. The parsers now provide for each record:
parse_ functions changed the column date to the more descriptive turtle_date, as in the date (ymd) of “the night before”. Using turtle_date groups turtle tagging (nightfall to sunrise) and tracks (made same night but observed the next morning) under the same date. This change requires code depending on the column date to be updated to turtle_date.parse_ functions now include season, as in the earlier year of the fiscal year. This cleanly groups the (Australian) summer nesters (nesting Oct-Mar) under the same season number. E.g., any observations made between 01/07/2017 and 30/06/2018 (AWST for the sticklers) will come up as season 2017. Note, the season for (Australian) winter nesters can be grouped by the calendar year, which can itself be derived trivially from the datetime as dplyr::mutate(year = lubridate::year(datetime)). The same goes for the calendar week, dplyr::mutate(week = lubridate::isoweek(datetime)).theme_light() to theme_classic().parse_survey, plus some data viz for Surveys, see vignette “Analysis”.map_tracks, a map of turtle tracks/nests. WIP: more data viz for tracks.