From 27c26656d1d38d037b568bd182144610a4d3a4d6 Mon Sep 17 00:00:00 2001 From: BastienGrassetIRD Date: Tue, 18 Jul 2023 19:14:01 +0400 Subject: [PATCH] dimension parameters names #22 --- tunaatlas_scripts/generation/convert_units.R | 14 +++++++------- .../function_raising_georef_to_nominal.R | 14 +++++++------- 2 files changed, 14 insertions(+), 14 deletions(-) diff --git a/tunaatlas_scripts/generation/convert_units.R b/tunaatlas_scripts/generation/convert_units.R index 9e8f9a9..435d99b 100644 --- a/tunaatlas_scripts/generation/convert_units.R +++ b/tunaatlas_scripts/generation/convert_units.R @@ -4,7 +4,7 @@ convert_units = function (con, df_input, df_conversion_factor, codelist_geoident cat(paste0("\n BEGIN tunaatlas::convert_units() => converting units and measures")) columns_df_input = colnames(df_input) df_input <- data.table(df_input) - units_source <- unique(df_conversion_factor$unit) + units_source <- unique(df_conversion_factor$measurement_unit) units_target <- unique(df_conversion_factor$unit_target) df_conversion_factor$conversion_factor = as.numeric(df_conversion_factor$conversion_factor) if ("geographic_identifier" %in% colnames(df_conversion_factor)) { @@ -85,15 +85,15 @@ convert_units = function (con, df_input, df_conversion_factor, codelist_geoident df_input <- left_join(df_input, data_zone_0) df_input$conv_factor_df_geo_id[which(!is.na(df_input$zone0))] <- "0" df_input <- df_input %>% dplyr::select(-zone0, -unit_target) - class(df_input$value) <- "numeric" + class(df_input$measurement_value) <- "numeric" } if (nrow(df_input) == nrow(left_join(df_input, df_conversion_factor) %>% filter(is.na(conversion_factor)))) { - if (length(intersect(unique(df_conversion_factor$gear), - unique(df_input$gear))) == 0) { + if (length(intersect(unique(df_conversion_factor$gear_type), + unique(df_input$gear_type))) == 0) { df_conversion_factor_no_gear <- df_conversion_factor %>% group_by_at(setdiff(colnames(df_conversion_factor), - "gear")) %>% summarise(conversion_factor = mean(conversion_factor)) + "gear_type")) %>% summarise(conversion_factor = mean(conversion_factor)) df_input <- left_join(df_input, df_conversion_factor_no_gear) } } @@ -108,12 +108,12 @@ convert_units = function (con, df_input, df_conversion_factor, codelist_geoident # summarise(sum_unit_source_before_conversion = sum(value)) %>% # filter(!is.na(unit_target)) index.not_na.conv_factor <- which(!is.na(df_input$conversion_factor)) - df_input$value[index.not_na.conv_factor] <- df_input$value[index.not_na.conv_factor] * + df_input$measurement_value[index.not_na.conv_factor] <- df_input$measurement_value[index.not_na.conv_factor] * df_input$conversion_factor[index.not_na.conv_factor] # stats_after_conversion <- df_input %>% group_by(unit, unit_target) %>% # summarise(sum_unit_target_after_conversion = sum(value)) %>% # filter(!is.na(unit_target)) - df_input$unit[index.not_na.conv_factor] <- df_input$unit_target[index.not_na.conv_factor] + df_input$measurement_unit[index.not_na.conv_factor] <- df_input$unit_target[index.not_na.conv_factor] df_input <- df_input %>% dplyr::select(all_of(columns_df_input)) # sum_after_conversion <- df_input %>% group_by(unit) %>% # summarise(sum_value_after_conversion = sum(value)) diff --git a/tunaatlas_scripts/generation/function_raising_georef_to_nominal.R b/tunaatlas_scripts/generation/function_raising_georef_to_nominal.R index ddcb1ae..670cf3c 100644 --- a/tunaatlas_scripts/generation/function_raising_georef_to_nominal.R +++ b/tunaatlas_scripts/generation/function_raising_georef_to_nominal.R @@ -29,7 +29,7 @@ function_raising_georef_to_nominal<-function(con, opts,entity, cat("filter by source_authority\n") dataset_to_raise<-dataset_to_raise[which(dataset_to_raise$source_authority %in% source_authority_filter),] - config$logger.info(paste0("Total catch for dataset_to_raise before raising is ",sum(dataset_to_compute_rf$measurement_value)," \n")) + config$logger.info(paste0("Total catch for dataset_to_raise before raising is ",sum(dataset_to_raise$measurement_value)," \n")) dataset_to_compute_rf<-dataset_to_compute_rf[which(dataset_to_compute_rf$source_authority %in% source_authority_filter),] config$logger.info(paste0("Total catch for dataset_to_compute_rf before raising is ",sum(dataset_to_compute_rf$measurement_value)," \n")) @@ -49,8 +49,8 @@ function_raising_georef_to_nominal<-function(con, opts,entity, cat(paste0("raise_get_rf function has",nrow(df_rf),"rows \n")) cat(paste0(" write csv file to check \n")) - filename <- paste0("/tmp/DFPartialInfo_rf_",gsub(Sys.time(),pattern = " ", replacement = "_"),".csv") - write.csv(x = df_rf, file = filename) + # filename <- paste0("DFPartialInfo_rf_",gsub(Sys.time(),pattern = " ", replacement = "_"),".csv") + # write.csv(x = df_rf, file = filename) cat("function raise_get_rf has been executed ! \n") config$logger.info(paste0("Rows number in df_rf ",nrow(df_rf)," \n")) @@ -65,7 +65,7 @@ function_raising_georef_to_nominal<-function(con, opts,entity, # raise dataset cat("Executing raise_incomplete_dataset_to_total_dataset \n") - source("https://raw.githubusercontent.com/firms-gta/geoflow-tunaatlas/master/sardara_functions/raise_incomplete_dataset_to_total_dataset.R") + source("~/Documents/geoflow-tunaatlas/sardara_functions/raise_incomplete_dataset_to_total_dataset.R") data_raised<-raise_incomplete_dataset_to_total_dataset(df_input_incomplete = dataset_to_raise, df_input_total = nominal_dataset_df, @@ -90,11 +90,11 @@ function_raising_georef_to_nominal<-function(con, opts,entity, if (raising_raise_only_for_PS_LL==TRUE){ # @juldebar => check if gear codes are correct - gears_PS_LL<-dbGetQuery(con,"SELECT distinct(src_code) FROM gear.gear_mapping_view WHERE trg_codingsystem='geargroup_tunaatlas' AND trg_code IN ('PS','LL')")$src_code + gears_PS_LL<-dbGetQuery(con,"SELECT distinct(src_code) FROM gear_type.gear_type_mapping_view WHERE trg_codingsystem='geargroup_tunaatlas' AND trg_code IN ('PS','LL')")$src_code # config$logger.info("Now filtering gear codes with those returned by SLQ query", gears_PS_LL) - dataset_not_PS_LL<-dataset_to_raise %>% filter(!(gear_type %in% gears_PS_LL)) - dataset_to_raise<-dataset_to_raise %>% filter(gear_type %in% gears_PS_LL) + dataset_not_PS_LL<-dataset_to_raise %>% dplyr::filter(!(gear_type %in% gears_PS_LL)) + dataset_to_raise<-dataset_to_raise %>% dplyr::filter(gear_type %in% gears_PS_LL) config$logger.info(paste0("Since option raising_raise_only_for_PS_LL==TRUE, kept rows number is ",nrow(dataset_to_raise)," and number of removed rows is ",nrow(dataset_not_PS_LL),"\n"))