brapi_post_phenotypes: post /phenotypes

In mverouden/brapir: Client to Access BrAPI Compliant Plant Breeding Databases

post /phenotypes

Description

Add new Observation Unit Phenotypes

Usage

brapi_post_phenotypes(con = NULL, format = as.character(NA), data = "")

Arguments

con	list; required: TRUE; BrAPI connection object
format	character; required: FALSE; In case where JSON data is zipped for faster transfer speed (as in the case of the IRRI handheld implementation), the zipped JSON file will be listed in datafiles. The zipped file contains a JSON file with the same structure as the BrAPI call.; default: as.character(NA), other possible values: "csv", tsv" and depending on the call "flapjack" may be supported.
data	data.frame; required: TRUE, with default: ""; data.frame of observation data recorded for different observation variables across different observation units. The data argument data.frame requires to contain the following columns: observatioUnitDbId character; required: TRUE studyDbId character; required: TRUE; Identifier of the study. Usually a number, could be alphanumeric. observations data.frame; required: TRUE; the observations data.frame has required and optional columns: collector character; required: TRUE; the name or identifier of the entity which collected the observation observationDbId character; required: FALSE; the ID which uniquely identifies an observation observationTimeStamp character; required: TRUE; the date and time when this observation was made and specified in the ISO 8601 format observationVariableDbId character; required: TRUE; variable unique identifier observationVariableName character; required: TRUE; a human readable name for an observation variable season character; required: FALSE; the season when the observation data was collected value character; required: TRUE; the value of the data collected as an observation The Examples Section shows an example of how to construct the data argument as a nested data.frame.

Details

Along with the study specific phenotype saving calls (in the observationUnit and table formats), this call allows phenotypes to be saved and images to optionally be transferred as well.

Call to invoke for saving the measurements (observations) collected from field for all the observation units.

Observation timestamp should be ISO 8601 https://www.w3.org/TR/NOTE-datetime

In case where JSON data is zipped for faster transfer speed (as in the case of the IRRI handheld implementation), the zipped JSON file will be listed in datafiles. The zipped file contains a JSON file with the same structure as the BrAPI call. In this case a format parameter should be passed as well.

Images can be optionally be uploaded using this call by providing a zipfile of all images in the datafiles, along with the actual zipfile in multi-part form data.

Value

data.frame

Author(s)

brapir generator package

References

BrAPI SwaggerHub

See Also

Other brapi_1.3: brapi_get_allelematrices_search(), brapi_get_allelematrices(), brapi_get_attributes_categories(), brapi_get_attributes(), brapi_get_breedingmethods_breedingMethodDbId(), brapi_get_breedingmethods(), brapi_get_calls(), brapi_get_commoncropnames(), brapi_get_germplasm_germplasmDbId_attributes(), brapi_get_germplasm_germplasmDbId_markerprofiles(), brapi_get_germplasm_germplasmDbId_mcpd(), brapi_get_germplasm_germplasmDbId_pedigree(), brapi_get_germplasm_germplasmDbId_progeny(), brapi_get_germplasm_germplasmDbId(), brapi_get_germplasm(), brapi_get_images_imageDbId(), brapi_get_images(), brapi_get_lists_listDbId(), brapi_get_lists(), brapi_get_locations_locationDbId(), brapi_get_locations(), brapi_get_maps_mapDbId_positions_linkageGroupName(), brapi_get_maps_mapDbId_positions(), brapi_get_maps_mapDbId(), brapi_get_maps(), brapi_get_markerprofiles_markerProfileDbId(), brapi_get_markerprofiles(), brapi_get_markers_markerDbId(), brapi_get_markers(), brapi_get_methods_methodDbId(), brapi_get_methods(), brapi_get_observationlevels(), brapi_get_observationunits(), brapi_get_ontologies(), brapi_get_people_personDbId(), brapi_get_people(), brapi_get_programs(), brapi_get_samples_sampleDbId(), brapi_get_samples(), brapi_get_scales_scaleDbId(), brapi_get_scales(), brapi_get_search_germplasm_searchResultsDbId(), brapi_get_search_images_searchResultsDbId(), brapi_get_search_markers_searchResultsDbId(), brapi_get_search_observationtables_searchResultsDbId(), brapi_get_search_observationunits_searchResultsDbId(), brapi_get_search_programs_searchResultsDbId(), brapi_get_search_samples_searchResultsDbId(), brapi_get_search_studies_searchResultsDbId(), brapi_get_search_variables_searchResultsDbId(), brapi_get_seasons(), brapi_get_studies_studyDbId_germplasm(), brapi_get_studies_studyDbId_layouts(), brapi_get_studies_studyDbId_observations(), brapi_get_studies_studyDbId_observationunits(), brapi_get_studies_studyDbId_observationvariables(), brapi_get_studies_studyDbId_table(), brapi_get_studies_studyDbId(), brapi_get_studies(), brapi_get_studytypes(), brapi_get_traits_traitDbId(), brapi_get_traits(), brapi_get_trials_trialDbId(), brapi_get_trials(), brapi_get_variables_observationVariableDbId(), brapi_get_variables(), brapi_get_vendor_orders_orderId_plates(), brapi_get_vendor_orders_orderId_results(), brapi_get_vendor_orders_orderId_status(), brapi_get_vendor_orders(), brapi_get_vendor_plates_submissionId(), brapi_get_vendor_specifications(), brapi_post_allelematrices_search(), brapi_post_images(), brapi_post_lists_listDbId_items(), brapi_post_lists(), brapi_post_methods(), brapi_post_people(), brapi_post_scales(), brapi_post_search_germplasm(), brapi_post_search_images(), brapi_post_search_markers(), brapi_post_search_observationtables(), brapi_post_search_observationunits(), brapi_post_search_programs(), brapi_post_search_samples(), brapi_post_search_studies(), brapi_post_search_variables(), brapi_post_studies_studyDbId_table(), brapi_post_traits(), brapi_post_vendor_orders(), brapi_post_vendor_plates(), brapi_put_images_imageDbId_imagecontent(), brapi_put_images_imageDbId(), brapi_put_lists_listDbId(), brapi_put_methods_methodDbId(), brapi_put_people_personDbId(), brapi_put_samples(), brapi_put_scales_scaleDbId(), brapi_put_studies_studyDbId_layouts(), brapi_put_studies_studyDbId_observations(), brapi_put_studies_studyDbId_observationunits(), brapi_put_traits_traitDbId()

Other Observations: brapi_get_observationlevels(), brapi_get_observationunits(), brapi_get_search_observationtables_searchResultsDbId(), brapi_get_search_observationunits_searchResultsDbId(), brapi_get_studies_studyDbId_observations(), brapi_get_studies_studyDbId_observationunits(), brapi_get_studies_studyDbId_table(), brapi_post_search_observationtables(), brapi_post_search_observationunits(), brapi_post_studies_studyDbId_table(), brapi_put_studies_studyDbId_observations(), brapi_put_studies_studyDbId_observationunits()

Examples

## Not run: 

# Create a connection object
con <- brapi_db()$testserver

# Create an example data.frame data object
data <- data.frame(
  observatioUnitDbId = "7",
  studyDbId = "1002"
)
datadf <- data.frame(
  collector = c("C. Technical", "C. Technical"),
  observationDbId = c("", ""),
  observationTimeStamp = c("2020-05-15T15:30:00.760Z", "2020-05-15T15:31:16.760Z"),
  observationVariableDbId = c("MO_123:100002", "MO_123:100003"),
  observationVariableName = c("Plant height", "Carotenoid"),
  season = c("spring", "spring"),
  value = c("1.75", "1.4")
)
data[["observations"]] <- list(datadf)

# Make post /phenotypes call
brapi_post_phenotypes(con = con,
                      format = as.character(NA),
                      data = data)

## End(Not run)

mverouden/brapir documentation built on April 10, 2022, 5:36 p.m.