Commit ⋅ agrdatasci/ClimMobTools

    
    # get variables names from assessments
    assess <- dt[["assessments"]]
    assess <- do.call("rbind", assess[, "fields"])
    assess <- data.frame(assess, stringsAsFactors = FALSE)
    assess <- assess[!duplicated(assess[, "name"]), ]
    # the ids for assessments
    assess_id <- paste0("ASS", dt[["assessments"]][, "code"])
    # and the description
    assess_name <- dt[["assessments"]][, "desc"]
    
    # trial data
    trial <- dt[["data"]]
    # the names of questions
    looknames <- assess[, "name"]
    
    if(length(assess) > 0) {
    
      assess <- do.call("rbind", assess[, "fields"])
      assess <- data.frame(assess, stringsAsFactors = FALSE)
      assess <- assess[!duplicated(assess[, "name"]), ]
      # the ids for assessments
      assess_id <- paste0("ASS", dt[["assessments"]][, "code"])
      # and the description
      assess_name <- dt[["assessments"]][, "desc"]
      # the names of questions
      looknames <- assess[, "name"]
    
    } else {
      assess <- data.frame()
      assess_id <- character()
      assess_name <- character()
      looknames <- character()
    }
    
    # paste the ids of each assessments
    looknames <- c(regs_name,
                   paste(rep(assess_id, each = length(looknames)), 
                         looknames, sep = "_"))
    
    
    # trial data
    trial <- dt[["data"]]
    
    # get the values from the trial data
    trial <- lapply(looknames, function(x){
      i <- names(trial) %in% x

@@ -92,7 +105,7 @@

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    trial <- do.call("cbind", trial)
    
    # split farmgeolocation info
    # check if geografic location is available
    # check if geographic location is available
    geoTRUE <- grepl("farmgoelocation|ubicacion", names(trial))
    
    # if is available, then split the vector as lon lat

Files		•	•	•	Coverage
R	517	345	0	172	66.73%
Project Totals (7 files)	517	345	0	172	66.73%

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92	105		trial <- do.call("cbind", trial)
93	106
94	107		# split farmgeolocation info
95		-	# check if geografic location is available
	108	+	# check if geographic location is available
96	109		geoTRUE <- grepl("farmgoelocation\|ubicacion", names(trial))
97	110
98	111		# if is available, then split the vector as lon lat

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65	65
66	66		# get variables names from assessments
67	67		assess <- dt[["assessments"]]
68		-	assess <- do.call("rbind", assess[, "fields"])
69		-	assess <- data.frame(assess, stringsAsFactors = FALSE)
70		-	assess <- assess[!duplicated(assess[, "name"]), ]
71		-	# the ids for assessments
72		-	assess_id <- paste0("ASS", dt[["assessments"]][, "code"])
73		-	# and the description
74		-	assess_name <- dt[["assessments"]][, "desc"]
75	68
76		-	# trial data
77		-	trial <- dt[["data"]]
78		-	# the names of questions
79		-	looknames <- assess[, "name"]
	69	+
	70	+	if(length(assess) > 0) {
	71	+
	72	+	assess <- do.call("rbind", assess[, "fields"])
	73	+	assess <- data.frame(assess, stringsAsFactors = FALSE)
	74	+	assess <- assess[!duplicated(assess[, "name"]), ]
	75	+	# the ids for assessments
	76	+	assess_id <- paste0("ASS", dt[["assessments"]][, "code"])
	77	+	# and the description
	78	+	assess_name <- dt[["assessments"]][, "desc"]
	79	+	# the names of questions
	80	+	looknames <- assess[, "name"]
	81	+
	82	+	} else {
	83	+	assess <- data.frame()
	84	+	assess_id <- character()
	85	+	assess_name <- character()
	86	+	looknames <- character()
	87	+	}
	88	+
80	89		# paste the ids of each assessments
81	90		looknames <- c(regs_name,
82	91		paste(rep(assess_id, each = length(looknames)),
83	92		looknames, sep = "_"))
84	93
	94	+
	95	+	# trial data
	96	+	trial <- dt[["data"]]
	97	+
85	98		# get the values from the trial data
86	99		trial <- lapply(looknames, function(x){
87	100		i <- names(trial) %in% x

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