108 lines
4.3 KiB
R
108 lines
4.3 KiB
R
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library(tidyverse)
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site_df <- readr::read_tsv(
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snakemake@input[["station"]],
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col_types = cols(
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MonitoringLocationIdentifier = "f",
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MonitoringLocationTypeName = "f",
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MonitoringLocationName = "f",
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MonitoringLocationDescriptionText = "c",
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LatitudeMeasure = "d",
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LongitudeMeasure = "d",
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.default = "-")
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) %>%
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rename(
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location = MonitoringLocationIdentifier,
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location_type = MonitoringLocationTypeName,
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location_name = MonitoringLocationName,
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location_desc = MonitoringLocationDescriptionText,
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lat = LatitudeMeasure,
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long = LongitudeMeasure,
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)
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# This has a bunch of crap in it that has nothing to do with chemicals in
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# water (which might make amphibians gay). Additionally, there are many
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# different units that need to be standardized (eventually to be put in
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# terms of ug/ml)
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result_df <- readr::read_tsv(
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snakemake@input[["results"]],
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col_types = cols(
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ActivityTypeCode = "f",
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ActivityStartDate = "D",
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ActivityEndDate = "D",
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ActivityMediaName = "f",
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MonitoringLocationIdentifier = "f",
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CharacteristicName = "f",
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ResultMeasureValue = "c",
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"ResultMeasure/MeasureUnitCode" = "c",
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"DetectionQuantitationLimitMeasure/MeasureValue" = "c",
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"DetectionQuantitationLimitMeasure/MeasureUnitCode" = "f",
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.default = "-",
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)
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) %>%
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rename(activity = ActivityTypeCode,
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unit = "ResultMeasure/MeasureUnitCode",
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media = ActivityMediaName,
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start = ActivityStartDate,
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end = ActivityEndDate,
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location = MonitoringLocationIdentifier,
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value = ResultMeasureValue,
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limit = "DetectionQuantitationLimitMeasure/MeasureValue",
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limit_unit = "DetectionQuantitationLimitMeasure/MeasureUnitCode",
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species = CharacteristicName) %>%
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arrange(start) %>%
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filter(media == "Water") %>%
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select(-media) %>%
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# select values that are numbers (some are just descriptive strings) assuming
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# blanks are actually zeros (to be filtered out later)
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replace_na(list(value = "0")) %>%
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filter(str_detect(value, "^-?\\d+\\.?\\d*$")) %>%
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mutate(value = as.numeric(value)) %>%
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# select units that are mass concentrations or "counts per something"
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filter(str_detect(unit, "^.*g/.*(l|L|g)$") |
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unit %in% c("%", "ppb", "ppm")) %>%
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# remove a bunch of crap with "%" units
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filter(! str_detect(species, "SSC|Cloud cover|Sediment|solids|demand")) %>%
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filter(! str_detect(species, "Pha?eophytin|Chlorophyll|Alkalinity")) %>%
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filter(species != "Sodium, percent total cations" # not sure what this means
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& species != "Dissolved oxygen saturation" # whatever
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& species != "Water" # ironic...
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& species != "Barometric pressure" # not a chemical
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& species != "Relative humidity" # not a chemical either
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& species != "Extract volume" # ''
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& species != "Volume, total" # ''
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& species != "Acidity, (H+)" # will change later
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& species != "Carbon dioxide" # ditto
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& species != "Dissolved oxygen (DO)" # ditto
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& species != "Total hardness" # not specific
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) %>%
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# these seems like a typos
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mutate(species = case_when(
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species == "Diazinon0" ~ "Diazinon",
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species == "Phosphate-phosphorus***retired***use Total Phosphorus, mixed forms" ~ "Total Phosphorus, mixed forms",
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species == "Inorganic nitrogen (nitrate and nitrite) ***retired***use Nitrate + Nitrite" ~ "Nitrate + Nitrite",
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TRUE ~ species
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)) %>%
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# collapse units to (f/n/u/m)g/L
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mutate(unit = str_replace(unit, "/l", "/L"),
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unit = str_replace(unit, "kg", "L"),
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unit = case_when(unit == "ppb" ~ "ug/L",
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unit == "ppm" ~ "mg/L",
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TRUE ~ unit),
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# percent will just be in mg/L
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value = if_else(unit == "%", value * 10, value),
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unit = if_else(unit == "%", "mg/L", unit)) %>%
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# standardize all values to ug/L
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mutate(std_value = case_when(unit == "g/L" ~ value * 1e6,
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unit == "mg/L" ~ value * 1e3,
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unit == "ng/L" ~ value / 1e3,
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unit == "fg/L" ~ value / 1e6,
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TRUE ~ value)) %>%
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select(-value, -unit)
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result_df %>%
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left_join(site_df, by = "location") %>%
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select(-location) %>%
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readr::write_tsv(snakemake@output[[1]])
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