From d81550d0cccae824cc748de48e7fd50ea8d8033a Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 16 Apr 2020 18:02:18 +0200 Subject: Make na.rm = FALSE the default for geomean() This makes more sense and is in line with mean() from base R. Adapt tests and update docs. --- docs/index.html | 2 +- docs/reference/FOCUS_Step_12_scenarios.html | 14 ++-- docs/reference/FOMC_actual_twa.html | 22 +++---- docs/reference/GUS.html | 32 ++++----- docs/reference/PEC_soil.html | 51 ++++++++------- docs/reference/PEC_sw_drainage_UK.html | 29 +++++---- docs/reference/PEC_sw_drift.html | 30 +++++---- docs/reference/PEC_sw_exposit_drainage.html | 34 +++++----- docs/reference/PEC_sw_exposit_runoff.html | 33 +++++----- docs/reference/PEC_sw_focus.html | 42 +++++++----- docs/reference/PEC_sw_sed.html | 27 ++++---- docs/reference/SFO_actual_twa.html | 18 ++---- docs/reference/TOXSWA_cwa.html | 97 +++++++++++++++++++++------- docs/reference/chent_focus_sw.html | 31 +++++---- docs/reference/endpoint.html | 62 +++++++++++------- docs/reference/geomean.html | 29 ++++----- docs/reference/one_box.html | 21 +++--- docs/reference/pfm_degradation.html | 24 ++++--- docs/reference/plot.TOXSWA_cwa.html | 29 +++++---- docs/reference/plot.one_box-3.png | Bin 37287 -> 37285 bytes docs/reference/plot.one_box.html | 28 ++++---- docs/reference/read.TOXSWA_cwa.html | 28 ++++---- docs/reference/sawtooth-2.png | Bin 37287 -> 37285 bytes docs/reference/sawtooth.html | 21 +++--- docs/reference/set_nd_nq.html | 10 ++- 25 files changed, 411 insertions(+), 303 deletions(-) (limited to 'docs') diff --git a/docs/index.html b/docs/index.html index 23000f1..2e42649 100644 --- a/docs/index.html +++ b/docs/index.html @@ -75,7 +75,7 @@ install.packages("pfm")

Alternatively you can install the package using the devtools package. Using quick = TRUE skips docs, multiple-architecture builds, demos, and vignettes.

library(devtools)
-install_github("jranke/pfm", quick = TRUE)
+install_github("jranke/pfm", quick = TRUE)

diff --git a/docs/reference/FOCUS_Step_12_scenarios.html b/docs/reference/FOCUS_Step_12_scenarios.html index 4eed02f..77045f1 100644 --- a/docs/reference/FOCUS_Step_12_scenarios.html +++ b/docs/reference/FOCUS_Step_12_scenarios.html @@ -8,11 +8,13 @@ Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios • pfm + + @@ -32,14 +34,15 @@ - + + @@ -83,7 +86,6 @@ The text file is not included in the package as its licence is not clear." /> Reference -
@@ -105,20 +107,18 @@ The text file is not included in the package as its licence is not clear." />

-

The data were extracted from the scenario.txt file using the R code shown below. The text file is not included in the package as its licence is not clear.

-
- + +

Format

A list containing the scenario names in a character vector called 'names', the drift percentiles in a matrix called 'drift', interception percentages in a matrix called 'interception' and the runoff/drainage percentages for Step 2 calculations in a matrix called 'rd'.

-

Examples


@@ -295,9 +295,7 @@ The text file is not included in the package as its licence is not clear.

   
 
     

-    
     
Actual and maximum moving window time average concentrations for FOMC kinetics

-    
     

 
-    
FOMC_actual_twa(alpha = 1.0001, beta = 10, times = c(0, 1, 2, 4, 7,
-  14, 21, 28, 42, 50, 100))

-    
+    
FOMC_actual_twa(
+  alpha = 1.0001,
+  beta = 10,
+  times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100)
+)

+
     
Arguments

     
@@ -128,13 +131,12 @@
       

     
The output times, and window sizes for time weighted average concentrations

     

     

-    
+
     
Source

 
     
FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
   Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
   18 December 2014, p. 251

-    
 
     
Examples

     
FOMC_actual_twa(alpha = 1.0001, beta = 10)
#>         actual       twa
@@ -154,9 +156,7 @@
     
Contents

     
 
diff --git a/docs/reference/GUS.html b/docs/reference/GUS.html
index b44c120..e371c1a 100644
--- a/docs/reference/GUS.html
+++ b/docs/reference/GUS.html
@@ -8,11 +8,13 @@
 
 Groundwater ubiquity score based on Gustafson (1989) — GUS • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
@@ -41,6 +43,7 @@ $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$" />
 
 
 
+
 
 
 
@@ -84,7 +87,6 @@ $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$" />
   Reference
 
       
-      
       
    
         
       

@@ -106,11 +108,9 @@ $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$" />
     

 
     

-    
     
The groundwater ubiquity score GUS is calculated according to
 the following equation
 $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$

-    
     

 
     
GUS(...)
@@ -119,14 +119,20 @@ $$GUS = \log_{10} DT50_{soil} (4 - \log_{10} K_{oc})$$

 GUS(DT50, Koc, ...)
 
 # S3 method for chent
-GUS(chent, degradation_value = "DT50ref",
-  lab_field = "laboratory", redox = "aerobic",
-  sorption_value = "Kfoc", degradation_aggregator = geomean,
-  sorption_aggregator = geomean, ...)
+GUS(
+  chent,
+  degradation_value = "DT50ref",
+  lab_field = "laboratory",
+  redox = "aerobic",
+  sorption_value = "Kfoc",
+  degradation_aggregator = geomean,
+  sorption_aggregator = geomean,
+  ...
+)
 
 # S3 method for GUS_result
 print(x, ..., digits = 1)

-    
+
     
Arguments

     
@@ -198,29 +204,25 @@ be Koc values at a concentration of 1 mg/L in the water phase.

     
       
The number of digits used in the print method

     

     

-    
+
     
Value

 
     
A list with the DT50 and Koc used as well as the resulting score
   of class GUS_result

-    
     
References

 
     
Gustafson, David I. (1989) Groundwater ubiquity score: a simple
 method for assessing pesticide leachability. Environmental
 toxicology and chemistry 8(4) 339–57.

-    
 
   

   
 
     

-    
     
This is a basic calculation of a contaminant concentration in bulk soil
 based on complete, instantaneous mixing. If an interval is given, an
 attempt is made at calculating a long term maximum concentration using
 the concepts layed out in the PPR panel opinion (EFSA PPR panel 2012
 and in the EFSA guidance on PEC soil calculations (EFSA, 2015, 2017).

-    
     

 
-    
PEC_soil(rate, rate_units = "g/ha", interception = 0,
-  mixing_depth = 5, PEC_units = "mg/kg", PEC_pw_units = "mg/L",
-  interval = NA, n_periods = Inf, tillage_depth = 20,
-  leaching_depth = tillage_depth, crop = "annual",
-  cultivation = FALSE, chent = NA, DT50 = NA, FOMC = NA,
-  Koc = NA, Kom = Koc/1.724, t_avg = 0, t_act = NULL,
+    
PEC_soil(
+  rate,
+  rate_units = "g/ha",
+  interception = 0,
+  mixing_depth = 5,
+  PEC_units = "mg/kg",
+  PEC_pw_units = "mg/L",
+  interval = NA,
+  n_periods = Inf,
+  tillage_depth = 20,
+  leaching_depth = tillage_depth,
+  crop = "annual",
+  cultivation = FALSE,
+  chent = NA,
+  DT50 = NA,
+  FOMC = NA,
+  Koc = NA,
+  Kom = Koc/1.724,
+  t_avg = 0,
+  t_act = NULL,
   scenarios = c("default", "EFSA_2017", "EFSA_2015"),
-  leaching = scenarios == "EFSA_2017", porewater = FALSE)

-    
+  leaching = scenarios == "EFSA_2017",
+  porewater = FALSE
+)

+
     
Arguments

     
@@ -245,11 +261,10 @@ soil concentrations?  Based on equation (7) given in the PPR panel opinion
 p. 13).

     
     
     

-    
+
     
Value

 
     
The predicted concentration in soil

-    
     
Details

 
     
This assumes that the complete load to soil during the time specified by
@@ -258,7 +273,6 @@ opinion cited below (EFSA PPR panel 2012), only temperature correction using the
 Arrhenius equation is performed.

 
Total soil and porewater PEC values for the scenarios as defined in the EFSA
 guidance (2017, p. 14/15) can easily be calculated.

-    
     
Note

 
     
While time weighted average (TWA) concentrations given in the examples
@@ -275,7 +289,6 @@ from 2017 (p. 92).

   e.g. in the EFSA scenarios, the DT50 for groundwater modelling
   (destination 'PECgw') is taken from the chent object, otherwise the DT50
   with destination 'PECsoil'.

-    
     
References

 
     
EFSA Panel on Plant Protection Products and their Residues (2012)
@@ -293,7 +306,6 @@ from 2017 (p. 92).

   protection products and transformation products of these active substances
   in soil. EFSA Journal 13(4) 4093
   doi:10.2903/j.efsa.2015.4093

-    
 
     
Examples

     
PEC_soil(100, interception = 0.25)
#>      scenario
@@ -334,15 +346,10 @@ from 2017 (p. 92).

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_drainage_UK.html b/docs/reference/PEC_sw_drainage_UK.html
index f641773..bdcf5af 100644
--- a/docs/reference/PEC_sw_drainage_UK.html
+++ b/docs/reference/PEC_sw_drainage_UK.html
@@ -8,11 +8,13 @@
 
 Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,14 +34,15 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -83,7 +86,6 @@ published on the CRC website" />
   Reference
 
       
-      
       
    
         
       

@@ -105,16 +107,20 @@ published on the CRC website" />
     

 
     

-    
     
This implements the method specified in the UK data requirements handbook and was checked against the spreadsheet
 published on the CRC website

-    
     

 
-    
PEC_sw_drainage_UK(rate, interception = 0, Koc,
-  latest_application = NULL, soil_DT50 = NULL, model = NULL,
-  model_parms = NULL)

-    
+    
PEC_sw_drainage_UK(
+  rate,
+  interception = 0,
+  Koc,
+  latest_application = NULL,
+  soil_DT50 = NULL,
+  model = NULL,
+  model_parms = NULL
+)

+
     
Arguments

     
@@ -148,11 +154,10 @@ published on the CRC website

     
       
A named numeric vector containing the model parameters

     

     

-    
+
     
Value

 
     
The predicted concentration in surface water in µg/L

-    
     
References

 
     
HSE's Chemicals Regulation Division (CRD) Active substance
@@ -162,7 +167,6 @@ published on the CRC website

 
Drainage PECs Version 1.0 (2015) Spreadsheet published at
   https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx
   accessed 2019-09-27

-    
 
     
Examples

     
PEC_sw_drainage_UK(150, Koc = 100)
#> [1] 8.076923

@@ -171,11 +175,8 @@ published on the CRC website

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_drift.html b/docs/reference/PEC_sw_drift.html
index 14ccf79..302ab0d 100644
--- a/docs/reference/PEC_sw_drift.html
+++ b/docs/reference/PEC_sw_drift.html
@@ -8,11 +8,13 @@
 
 Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
@@ -41,6 +43,7 @@ with input via spray drift." />
 
 
 
+
 
 
 
@@ -84,7 +87,6 @@ with input via spray drift." />
   Reference
 
       
-      
       
    
         
       

@@ -106,18 +108,23 @@ with input via spray drift." />
     
 
     

-    
     
This is a basic, vectorised form of a simple calculation of a contaminant
 concentration in surface water based on complete, instantaneous mixing
 with input via spray drift.

-    
     

 
-    
PEC_sw_drift(rate, applications = 1, water_depth = 30,
-  drift_percentages = NULL, drift_data = "JKI", crop = "Ackerbau",
-  distances = c(1, 5, 10, 20), rate_units = "g/ha",
-  PEC_units = "µg/L")

-    
+    
PEC_sw_drift(
+  rate,
+  applications = 1,
+  water_depth = 30,
+  drift_percentages = NULL,
+  drift_data = "JKI",
+  crop = "Ackerbau",
+  distances = c(1, 5, 10, 20),
+  rate_units = "g/ha",
+  PEC_units = "µg/L"
+)

+
     
Arguments

     
@@ -159,11 +166,10 @@ with input via spray drift.

     
       
Requested units for the calculated PEC. Only µg/L currently supported

     

     

-    
+
     
Value

 
     
The predicted concentration in surface water

-    
 
     
Examples

     
PEC_sw_drift(100)
#>        1 m        5 m       10 m       20 m 
@@ -173,9 +179,7 @@ with input via spray drift.

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_exposit_drainage.html b/docs/reference/PEC_sw_exposit_drainage.html
index 1c2deac..5bd1d80 100644
--- a/docs/reference/PEC_sw_exposit_drainage.html
+++ b/docs/reference/PEC_sw_exposit_drainage.html
@@ -8,11 +8,13 @@
 
 Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
 
 
 
+
 
 
 
@@ -88,7 +91,6 @@ details, see the discussion of the function arguments below." />
   Reference
 
       
-      
       
    
         
       

@@ -110,7 +112,6 @@ details, see the discussion of the function arguments below." />
     

 
     

-    
     
This is a reimplementation of the calculation described in the Exposit 3.02 spreadsheet file,
 in the worksheet "Konzept Drainage". Although there are four groups of
 compounds ("Gefährdungsgruppen"), only one distinction is made in the
@@ -118,14 +119,20 @@ calculations, between compounds with low mobility (group 1) and compounds
 with modest to high mobility (groups 2, 3 and 4). In this implementation,
 the group is derived only from the Koc, if not given explicitly. For
 details, see the discussion of the function arguments below.

-    
     

 
-    
PEC_sw_exposit_drainage(rate, interception = 0, Koc = NA,
-  mobility = c(NA, "low", "high"), DT50 = Inf, t_drainage = 3,
-  V_ditch = 30, V_drainage = c(spring = 10, autumn = 100),
-  dilution = 2)

-    
+    
PEC_sw_exposit_drainage(
+  rate,
+  interception = 0,
+  Koc = NA,
+  mobility = c(NA, "low", "high"),
+  DT50 = Inf,
+  t_drainage = 3,
+  V_ditch = 30,
+  V_drainage = c(spring = 10, autumn = 100),
+  dilution = 2
+)

+
     
Arguments

     
@@ -168,12 +175,11 @@ autumn/winter/early spring.

     
       
The dilution factor

     

     

-    
+
     
Source

 
     
Excel 3.02 spreadsheet available from
   https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3

-    
     
Value

 
     
A list containing the following components

@@ -184,11 +190,9 @@ autumn/winter/early spring.

   
 

 
-    
     
See also

 
     
perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

-    
 
     
Examples

     
  PEC_sw_exposit_drainage(500, Koc = 150)
#> $perc_drainage_total
@@ -208,13 +212,9 @@ autumn/winter/early spring.

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_exposit_runoff.html b/docs/reference/PEC_sw_exposit_runoff.html
index 30ef975..81549e0 100644
--- a/docs/reference/PEC_sw_exposit_runoff.html
+++ b/docs/reference/PEC_sw_exposit_runoff.html
@@ -8,11 +8,13 @@
 
 Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,14 +34,15 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -83,7 +86,6 @@ in the worksheet "Konzept Runoff"." />
   Reference
 
       
-      
       
    
         
       

@@ -105,16 +107,22 @@ in the worksheet "Konzept Runoff"." />
     

 
     

-    
     
This is a reimplementation of the calculation described in the Exposit 3.02 spreadsheet file,
 in the worksheet "Konzept Runoff".

-    
     

 
-    
PEC_sw_exposit_runoff(rate, interception = 0, Koc, DT50 = Inf,
-  t_runoff = 3, exposit_reduction_version = c("3.02", "3.01a",
-  "3.01a2", "2.0"), V_ditch = 30, V_event = 100, dilution = 2)

-    
+    
PEC_sw_exposit_runoff(
+  rate,
+  interception = 0,
+  Koc,
+  DT50 = Inf,
+  t_runoff = 3,
+  exposit_reduction_version = c("3.02", "3.01a", "3.01a2", "2.0"),
+  V_ditch = 30,
+  V_event = 100,
+  dilution = 2
+)

+
     
Arguments

     
@@ -159,12 +167,11 @@ and the bound fraction.

     
       
The dilution factor

     

     

-    
+
     
Source

 
     
Excel 3.02 spreadsheet available from
   https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3

-    
     
Value

 
     
A list containing the following components

@@ -175,11 +182,9 @@ and the bound fraction.

   
 

 
-    
     
See also

 
     
perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used

-    
 
     
Examples

     
  PEC_sw_exposit_runoff(500, Koc = 150)
#> $perc_runoff
@@ -226,13 +231,9 @@ and the bound fraction.

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_focus.html b/docs/reference/PEC_sw_focus.html
index 1647b19..8242f6a 100644
--- a/docs/reference/PEC_sw_focus.html
+++ b/docs/reference/PEC_sw_focus.html
@@ -8,11 +8,13 @@
 
 Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
 
 
 
+
 
 
 
@@ -88,7 +91,6 @@ to be used with the FOCUS calculator." />
   Reference
 
       
-      
       
    
         
       

@@ -110,7 +112,6 @@ to be used with the FOCUS calculator." />
     

 
     

-    
     
This is a reimplementation of the FOCUS Step 1 and 2 calculator version 3.2,
 authored by Michael Klein, in R. Note that results for multiple
 applications should be compared to the corresponding results for a
@@ -118,16 +119,28 @@ single application. At current, this is not done automatically in
 this implementation. Only Step 1 PECs are calculated. However,
 input files are generated that are suitable as input also for Step 2
 to be used with the FOCUS calculator.

-    
     

 
-    
PEC_sw_focus(parent, rate, n = 1, i = NA, comment = "", met = NULL,
-  f_drift = NA, f_rd = 0.1, scenario = FOCUS_Step_12_scenarios$names,
-  region = c("n", "s"), season = c(NA, "of", "mm", "js"),
-  interception = c("no interception", "minimal crop cover",
-  "average crop cover", "full canopy"), met_form_water = TRUE,
-  txt_file = "pesticide.txt", overwrite = FALSE, append = TRUE)

-    
+    
PEC_sw_focus(
+  parent,
+  rate,
+  n = 1,
+  i = NA,
+  comment = "",
+  met = NULL,
+  f_drift = NA,
+  f_rd = 0.1,
+  scenario = FOCUS_Step_12_scenarios$names,
+  region = c("n", "s"),
+  season = c(NA, "of", "mm", "js"),
+  interception = c("no interception", "minimal crop cover", "average crop cover",
+    "full canopy"),
+  met_form_water = TRUE,
+  txt_file = "pesticide.txt",
+  overwrite = FALSE,
+  append = TRUE
+)

+
     
Arguments

     
@@ -214,7 +227,7 @@ should be written

     
       
Should the input text file be appended?

     

     

-    
+
     
Note

 
     
The formulas for input to the waterbody via runoff/drainage of the
@@ -224,7 +237,6 @@ should be written

   multiplying the application rate with the molar weight
   correction and the formation fraction in water/sediment systems.

 
Step 2 is not implemented.

-    
     
References

 
     
FOCUS (2014) Generic guidance for Surface Water Scenarios (version 1.4).
@@ -233,7 +245,6 @@ should be written

 
Website of the Steps 1 and 2 calculator at the Joint Research
   Center of the European Union:
   http://esdac.jrc.ec.europa.eu/projects/stepsonetwo

-    
 
     
Examples

     
# Parent only
@@ -337,11 +348,8 @@ should be written

     
Contents

     
 
diff --git a/docs/reference/PEC_sw_sed.html b/docs/reference/PEC_sw_sed.html
index fe65d96..458eeb7 100644
--- a/docs/reference/PEC_sw_sed.html
+++ b/docs/reference/PEC_sw_sed.html
@@ -9,11 +9,13 @@
 Calculate predicted environmental concentrations in sediment from surface
 water concentrations — PEC_sw_sed • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -33,15 +35,16 @@ water concentrations — PEC_sw_sed • pfm
 
 
 
+
 
-
 
 
 
 
 
+
 
 
 
@@ -85,7 +88,6 @@ PEC calculator" />
   Reference
 
       
-      
       
    
         
       

@@ -108,16 +110,20 @@ water concentrations
     

 
     

-    
     
The method 'percentage' is equivalent to what is used in the CRD spreadsheet
 PEC calculator

-    
     

 
-    
PEC_sw_sed(PEC_sw, percentage = 100, method = "percentage",
-  sediment_depth = 5, water_depth = 30, sediment_density = 1.3,
-  PEC_sed_units = c("µg/kg", "mg/kg"))

-    
+    
PEC_sw_sed(
+  PEC_sw,
+  percentage = 100,
+  method = "percentage",
+  sediment_depth = 5,
+  water_depth = 30,
+  sediment_density = 1.3,
+  PEC_sed_units = c("µg/kg", "mg/kg")
+)

+
     
Arguments

     
@@ -152,11 +158,10 @@ g/cm3)

     
       
The units of the estimated sediment PEC value

     

     

-    
+
     
Value

 
     
The predicted concentration in sediment

-    
 
     
Examples

     
PEC_sw_sed(PEC_sw_drift(100, distances = 1), percentage = 50)
#>      1 m 
@@ -166,9 +171,7 @@ g/cm3)

     
Contents

     
 
diff --git a/docs/reference/SFO_actual_twa.html b/docs/reference/SFO_actual_twa.html
index 1f172c6..b5fa5da 100644
--- a/docs/reference/SFO_actual_twa.html
+++ b/docs/reference/SFO_actual_twa.html
@@ -8,11 +8,13 @@
 
 Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,13 +34,14 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -82,7 +85,6 @@
   Reference
 
       
-      
       
    
         
       

@@ -104,14 +106,11 @@
     

 
     

-    
     
Actual and maximum moving window time average concentrations for SFO kinetics

-    
     

 
-    
SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42,
-  50, 100))

-    
+    
SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))

+
     
Arguments

     
@@ -124,13 +123,12 @@
       

     
The output times, and window sizes for time weighted average concentrations

     

     

-    
+
     
Source

 
     
FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
   Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, 
   18 December 2014, p. 251

-    
 
     
Examples

     
SFO_actual_twa(10)
#>           actual       twa
@@ -150,9 +148,7 @@
     
Contents

     
 
diff --git a/docs/reference/TOXSWA_cwa.html b/docs/reference/TOXSWA_cwa.html
index 8939850..cedb023 100644
--- a/docs/reference/TOXSWA_cwa.html
+++ b/docs/reference/TOXSWA_cwa.html
@@ -8,11 +8,13 @@
 
 R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,14 +34,15 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -83,7 +86,6 @@ Usually, an instance of this class will be generated by read.TOXSWA_cwa." />
   Reference
 
       
-      
       
    
         
       

@@ -105,23 +107,33 @@ Usually, an instance of this class will be generated by read.TOXSWA_cwa." />
     

 
     

-    
     
An R6 class for holding TOXSWA water concentration (cwa) data and some associated statistics.
 Usually, an instance of this class will be generated by read.TOXSWA_cwa.

-    
     

 
-    
TOXSWA_cwa

-        
+
+
     
Format

 
     
An R6Class generator object.

-    
-    
Fields

+    
Methods

 
     
 
 

+  
get_events(threshold, total = FALSE)
Populate a datataframe with event information for the specified threshold value
+        in µg/L. If total = TRUE, the total concentration including the amount
+        adsorbed to suspended matter will be used. The resulting dataframe is stored in the
+        events field of the object.

+  
moving_windows(windows, total = FALSE)
Add to the windows field described above.
+        Again, if total = TRUE, the total concentration including the amount
+        adsorbed to suspended matter will be used.

+
+

+
+    
Public fields

+
+    

 
filename
Length one character vector.

 
 
basedir
Length one character vector.

@@ -136,24 +148,62 @@ Usually, an instance of this class will be generated by 
-  
get_events(threshold, total = FALSE)
Populate a datataframe with event information for the specified threshold value
-        in µg/L. If total = TRUE, the total concentration including the amount
-        adsorbed to suspended matter will be used. The resulting dataframe is stored in the
-        events field of the object.

-  
moving_windows(windows, total = FALSE)
Add to the windows field described above.
-        Again, if total = TRUE, the total concentration including the amount
-        adsorbed to suspended matter will be used.

+
+

+
Method new()

+
+
Usage

+
TOXSWA_cwa$new(
+  filename,
+  basedir,
+  zipfile = NULL,
+  segment = "last",
+  substance = "parent",
+  total = FALSE
+)

+
+

+
Method moving_windows()

+
+
Usage

+
TOXSWA_cwa$moving_windows(windows, total = FALSE)

+
+

+
Method get_events()

+
+
Usage

+
TOXSWA_cwa$get_events(thresholds, total = FALSE)

+
+

+
Method print()

+
+
Usage

+
TOXSWA_cwa$print()

+
+

+
Method clone()

+
The objects of this class are cloneable with this method.
Usage

+
TOXSWA_cwa$clone(deep = FALSE)

+
+
Arguments

+

+
deep
Whether to make a deep clone.

+
+

 
-

 
-    
 
     
Examples

     
H_sw_R1_stream  <- read.TOXSWA_cwa("00003s_pa.cwa",
@@ -192,13 +242,10 @@ for the requested moving window sizes in days.

   
 
     

-    
     
Create a chemical compound object for FOCUS Step 1 calculations

-    
     

 
-    
chent_focus_sw(name, Koc, DT50_ws = NA, DT50_soil = NA,
-  DT50_water = NA, DT50_sediment = NA, cwsat = 1000, mw = NA,
-  max_soil = 1, max_ws = 1)

-    
+    
chent_focus_sw(
+  name,
+  Koc,
+  DT50_ws = NA,
+  DT50_soil = NA,
+  DT50_water = NA,
+  DT50_sediment = NA,
+  cwsat = 1000,
+  mw = NA,
+  max_soil = 1,
+  max_ws = 1
+)

+
     
Arguments

     
@@ -159,20 +168,18 @@ in L/kg.

 systems

     
     
     

-    
+
     
Value

 
     
A list with the substance specific properties

-    
 
   

   
 

diff --git a/docs/reference/endpoint.html b/docs/reference/endpoint.html
index 99e407c..39071ee 100644
--- a/docs/reference/endpoint.html
+++ b/docs/reference/endpoint.html
@@ -8,11 +8,13 @@
 
 Retrieve endpoint information from the chyaml field of a chent object — endpoint • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
 
 
 
+
 
 
 
@@ -85,7 +88,6 @@ this function." />
   Reference
 
       
-      
       
    
         
       

@@ -107,32 +109,46 @@ this function." />
     
 
     

-    
     
R6 class objects of class chent represent chemical entities
 and can hold a list of information loaded from a chemical yaml file in their
 chyaml field. Such information is extracted and optionally aggregated by
 this function.

-    
     

 
-    
endpoint(chent, medium = "soil", type = c("degradation", "sorption"),
-  lab_field = c(NA, "laboratory", "field"), redox = c(NA, "aerobic",
-  "anaerobic"), value = c("DT50ref", "Kfoc", "N"),
-  aggregator = geomean, raw = FALSE, signif = 3)
-
-soil_DT50(chent, aggregator = geomean, signif = 3,
-  lab_field = "laboratory", value = "DT50ref", redox = "aerobic",
-  raw = FALSE)
-
-soil_Kfoc(chent, aggregator = geomean, signif = 3, value = "Kfoc",
-  raw = FALSE)
+    
endpoint(
+  chent,
+  medium = "soil",
+  type = c("degradation", "sorption"),
+  lab_field = c(NA, "laboratory", "field"),
+  redox = c(NA, "aerobic", "anaerobic"),
+  value = c("DT50ref", "Kfoc", "N"),
+  aggregator = geomean,
+  raw = FALSE,
+  signif = 3
+)
+
+soil_DT50(
+  chent,
+  aggregator = geomean,
+  signif = 3,
+  lab_field = "laboratory",
+  value = "DT50ref",
+  redox = "aerobic",
+  raw = FALSE
+)
+
+soil_Kfoc(chent, aggregator = geomean, signif = 3, value = "Kfoc", raw = FALSE)
 
 soil_N(chent, aggregator = mean, signif = 3, raw = FALSE)
 
-soil_sorption(chent, values = c("Kfoc", "N"), aggregators = c(Kfoc =
-  geomean, Koc = geomean, N = mean), signif = c(Kfoc = 3, N = 3),
-  raw = FALSE)

-    
+soil_sorption(
+  chent,
+  values = c("Kfoc", "N"),
+  aggregators = c(Kfoc = geomean, Koc = geomean, N = mean),
+  signif = c(Kfoc = 3, N = 3),
+  raw = FALSE
+)

+
     
Arguments

     
@@ -185,7 +201,7 @@ about precision?

     
       
A named vector of aggregator functions to be used

     

     

-    
+
     
Value

 
     
The result from applying the aggregator function to
@@ -193,25 +209,21 @@ about precision?

   given number of significant digits, or, if raw = TRUE,
   the values as a character value, retaining any implicit
   information on precision that may be present.

-    
     
Details

 
     
The functions soil_* are functions to extract soil specific endpoints.
 For the Freundlich exponent, the capital letter N is used in order to
 facilitate dealing with such data in R. In pesticide fate modelling, this
 exponent is often called 1/n.

-    
 
   
   
 
diff --git a/docs/reference/geomean.html b/docs/reference/geomean.html
index 469e12f..34befc3 100644
--- a/docs/reference/geomean.html
+++ b/docs/reference/geomean.html
@@ -8,11 +8,13 @@
 
 Calculate the geometric mean — geomean • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,16 +34,18 @@
 
 
 
-
 
+
 
+This function returns NA if NA values are present and na.rm = FALSE
+(default). If negative values are present, it gives an error message.
+If at least one element of the vector is 0, it returns 0." />
 
 
 
 
+
 
 
 
@@ -85,7 +89,6 @@ returns 0 if at least one element of the vector is 0." />
   Reference
 
       
-      
       
    
         
       

@@ -107,16 +110,15 @@ returns 0 if at least one element of the vector is 0." />
     
 
     

-    
     
Based on some posts in a thread on Stackoverflow
 http://stackoverflow.com/questions/2602583/geometric-mean-is-there-a-built-in
-This function checks for negative values, removes NA values per default and
-returns 0 if at least one element of the vector is 0.

-    
+This function returns NA if NA values are present and na.rm = FALSE
+(default). If negative values are present, it gives an error message.
+If at least one element of the vector is 0, it returns 0.

     

 
-    
geomean(x, na.rm = TRUE)

-    
+    
geomean(x, na.rm = FALSE)

+
     
Arguments

     
@@ -129,22 +131,19 @@ returns 0 if at least one element of the vector is 0.

     
       
Should NA values be omitted?

     

     

-    
+
     
Value

 
     
The geometric mean

-    
 
     
Examples

-    
geomean(c(1, 3, 9))
#> [1] 3
geomean(c(1, 3, NA, 9))
#> [1] 3
if (FALSE) geomean(c(1, -3, 9)) # returns an error

+    
geomean(c(1, 3, 9))
#> [1] 3
geomean(c(1, 3, NA, 9))
#> [1] NA
if (FALSE) geomean(c(1, -3, 9)) # returns an error

   
   
 
     

-    
     
Create a time series of decline data

-    
     

 
     
one_box(x, ini, ..., t_end = 100, res = 0.01)
@@ -115,13 +115,11 @@
 one_box(x, ini = 1, ..., t_end = 100, res = 0.01)
 
 # S3 method for character
-one_box(x, ini = 1, parms, ..., t_end = 100,
-  res = 0.01)
+one_box(x, ini = 1, parms, ..., t_end = 100, res = 0.01)
 
 # S3 method for mkinfit
-one_box(x, ini = "model", ..., t_end = 100,
-  res = 0.01)

-    
+one_box(x, ini = "model", ..., t_end = 100, res = 0.01)

+
     
Arguments

     
@@ -158,11 +156,10 @@ all observed variables.

     
       
A named numeric vector containing the model parameters

     

     

-    
+
     
Value

 
     
An object of class one_box, inheriting from ts.

-    
 
     
Examples

     
# Only use a half-life
@@ -181,9 +178,7 @@ all observed variables.

     
Contents

     
 
diff --git a/docs/reference/pfm_degradation.html b/docs/reference/pfm_degradation.html
index 7e4eab1..d2e62f6 100644
--- a/docs/reference/pfm_degradation.html
+++ b/docs/reference/pfm_degradation.html
@@ -8,11 +8,13 @@
 
 Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,13 +34,14 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -82,7 +85,6 @@
   Reference
 
       
-      
       
    
         
       

@@ -104,15 +106,18 @@
     

 
     

-    
     
Calculate a time course of relative concentrations based on an mkinmod model

-    
     

 
-    
pfm_degradation(model = "SFO", DT50 = 1000, parms = c(k_parent_sink =
-  log(2)/DT50), years = 1, step_days = 1, times = seq(0, years * 365,
-  by = step_days))

-    
+    
pfm_degradation(
+  model = "SFO",
+  DT50 = 1000,
+  parms = c(k_parent_sink = log(2)/DT50),
+  years = 1,
+  step_days = 1,
+  times = seq(0, years * 365, by = step_days)
+)

+
     
Arguments

     
@@ -143,7 +148,7 @@ is calculated (SFO model).

     
       
The output times

     

     

-    
+
 
     
Examples

     
head(pfm_degradation("SFO", DT50 = 10))
#>   time    parent
@@ -158,7 +163,6 @@ is calculated (SFO model).

     
Contents

     
 
diff --git a/docs/reference/plot.TOXSWA_cwa.html b/docs/reference/plot.TOXSWA_cwa.html
index 8ca5b8e..1262c71 100644
--- a/docs/reference/plot.TOXSWA_cwa.html
+++ b/docs/reference/plot.TOXSWA_cwa.html
@@ -8,11 +8,13 @@
 
 Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,14 +34,15 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -83,7 +86,6 @@ segment of a TOXSWA surface water body." />
   Reference
 
       
-      
       
    
         
       

@@ -105,18 +107,24 @@ segment of a TOXSWA surface water body." />
     

 
     

-    
     
Plot TOXSWA hourly concentrations of a chemical substance in a specific
 segment of a TOXSWA surface water body.

-    
     

 
     
# S3 method for TOXSWA_cwa
-plot(x, time_column = c("datetime", "t",
-  "t_firstjan", "t_rel_to_max"), xlab = "default", ylab = "default",
-  add = FALSE, threshold_factor = 1000, thin_low = 1,
-  total = FALSE, LC_TIME = "C", ...)

-    
+plot(
+  x,
+  time_column = c("datetime", "t", "t_firstjan", "t_rel_to_max"),
+  xlab = "default",
+  ylab = "default",
+  add = FALSE,
+  threshold_factor = 1000,
+  thin_low = 1,
+  total = FALSE,
+  LC_TIME = "C",
+  ...
+)

+
     
Arguments

     
@@ -162,7 +170,7 @@ to suspended matter?

     
       
Further arguments passed to plot if we are not adding to an existing plot

     

     

-    
+
 
     
Examples

     
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
@@ -178,7 +186,6 @@ to suspended matter?

     
Contents

     
 
diff --git a/docs/reference/plot.one_box-3.png b/docs/reference/plot.one_box-3.png
index fc8116b..ad93165 100644
Binary files a/docs/reference/plot.one_box-3.png and b/docs/reference/plot.one_box-3.png differ
diff --git a/docs/reference/plot.one_box.html b/docs/reference/plot.one_box.html
index d048d22..75b8fe9 100644
--- a/docs/reference/plot.one_box.html
+++ b/docs/reference/plot.one_box.html
@@ -8,11 +8,13 @@
 
 Plot time series of decline data — plot.one_box • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,13 +34,14 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -82,7 +85,6 @@
   Reference
 
       
-      
       
    
         
       

@@ -104,16 +106,21 @@
     

 
     

-    
     
Plot time series of decline data

-    
     

 
     
# S3 method for one_box
-plot(x, xlim = range(time(x)), ylim = c(0, max(x)),
-  xlab = "Time", ylab = "Residue", max_twa = NULL,
-  max_twa_var = dimnames(x)[[2]][1], ...)

-    
+plot(
+  x,
+  xlim = range(time(x)),
+  ylim = c(0, max(x)),
+  xlab = "Time",
+  ylab = "Residue",
+  max_twa = NULL,
+  max_twa_var = dimnames(x)[[2]][1],
+  ...
+)

+
     
Arguments

     
@@ -152,11 +159,10 @@ be shown if max_twa is not NULL.

     
       
Further arguments passed to methods

     

     

-    
+
     
See also

 
     
sawtooth

-    
 
     
Examples

     
dfop_pred <- one_box("DFOP", parms = c(k1 = 0.2, k2 = 0.02, g = 0.7))
@@ -170,9 +176,7 @@ be shown if max_twa is not NULL.

     
Contents

     
 
diff --git a/docs/reference/read.TOXSWA_cwa.html b/docs/reference/read.TOXSWA_cwa.html
index df84634..9c5c2a0 100644
--- a/docs/reference/read.TOXSWA_cwa.html
+++ b/docs/reference/read.TOXSWA_cwa.html
@@ -8,11 +8,13 @@
 
 Read TOXSWA surface water concentrations — read.TOXSWA_cwa • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,8 +34,8 @@
 
 
 
-
 
+
 
 
 
 
+
 
 
 
@@ -87,7 +90,6 @@ renamed to ConLiqWatLay in the out file." />
   Reference
 
       
-      
       
    
         
       

@@ -109,20 +111,25 @@ renamed to ConLiqWatLay in the out file." />
     

 
     

-    
     
Read TOXSWA hourly concentrations of a chemical substance in a specific
 segment of a TOXSWA surface water body. Per default, the data for the last
 segment are imported. As TOXSWA 4 reports the values at the end of the hour
 (ConLiqWatLayCur) in its summary file, we use this value as well instead
 of the hourly averages (ConLiqWatLay). In TOXSWA 5.5.3 this variable was
 renamed to ConLiqWatLay in the out file.

-    
     

 
-    
read.TOXSWA_cwa(filename, basedir = ".", zipfile = NULL,
-  segment = "last", substance = "parent", total = FALSE,
-  windows = NULL, thresholds = NULL)

-    
+    
read.TOXSWA_cwa(
+  filename,
+  basedir = ".",
+  zipfile = NULL,
+  segment = "last",
+  substance = "parent",
+  total = FALSE,
+  windows = NULL,
+  thresholds = NULL
+)

+
     
Arguments

     
@@ -167,12 +174,11 @@ maximum time weighted average concentrations and areas under the curve.

 generating event statistics.

     
     
     

-    
+
     
Value

 
     
An instance of an R6 object of class
 TOXSWA_cwa.

-    
 
     
Examples

     
H_sw_D4_pond  <- read.TOXSWA_cwa("00001p_pa.cwa",
@@ -184,9 +190,7 @@ generating event statistics.

     
Contents

     
 
diff --git a/docs/reference/sawtooth-2.png b/docs/reference/sawtooth-2.png
index fc8116b..ad93165 100644
Binary files a/docs/reference/sawtooth-2.png and b/docs/reference/sawtooth-2.png differ
diff --git a/docs/reference/sawtooth.html b/docs/reference/sawtooth.html
index c6756a9..7720afc 100644
--- a/docs/reference/sawtooth.html
+++ b/docs/reference/sawtooth.html
@@ -8,11 +8,13 @@
 
 Create decline time series for multiple applications — sawtooth • pfm
 
+
 
 
 
 
 
+
 
 
 
@@ -32,14 +34,15 @@
 
 
 
-
 
+
 
 
 
 
 
+
 
 
 
@@ -83,7 +86,6 @@ n and i are disregarded." />
   Reference
 
       
-      
       
    
         
       

@@ -105,15 +107,17 @@ n and i are disregarded." />
     

 
     

-    
     
If the application pattern is specified in applications, 
 n and i are disregarded.

-    
     

 
-    
sawtooth(x, n = 1, i = 365, applications = data.frame(time = seq(0,
-  (n - 1) * i, length.out = n), amount = 1))

-    
+    
sawtooth(
+  x,
+  n = 1,
+  i = 365,
+  applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1)
+)

+
     
Arguments

     
@@ -136,7 +140,7 @@ is ignored

 the corresponding amounts applied in the second column.

     
     
     

-    
+
 
     
Examples

     
applications = data.frame(time = seq(0, 14, by = 7), amount = c(1, 2, 3))
@@ -162,7 +166,6 @@ the corresponding amounts applied in the second column.

     
Contents

     
 
diff --git a/docs/reference/set_nd_nq.html b/docs/reference/set_nd_nq.html
index 9ec17ea..702b3e3 100644
--- a/docs/reference/set_nd_nq.html
+++ b/docs/reference/set_nd_nq.html
@@ -119,8 +119,14 @@ it automates the proposal of Boesten et al (2015).

 
     
set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE)
 
-set_nd_nq_focus(res_raw, lod, loq = NA, set_first_sample_nd = TRUE,
-  first_sample_nd_value = 0, ignore_below_loq_after_first_nd = TRUE)

+set_nd_nq_focus(
+  res_raw,
+  lod,
+  loq = NA,
+  set_first_sample_nd = TRUE,
+  first_sample_nd_value = 0,
+  ignore_below_loq_after_first_nd = TRUE
+)

 
     
Arguments

     
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