1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
|
# pfm
The R package **pfm** provides some utilities for dealing with FOCUS pesticide fate modelling tools,
(currently only TOXSWA cwa and out files), made available under the GNU public license.
This means:
This program is free software: you can redistribute it and/or modify it under
the terms of the GNU General Public License as published by the Free Software
Foundation, either version 3 of the License, or (at your option) any later
version.
This program is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
details.
You should have received a copy of the GNU General Public License along with
this program. If not, see <http://www.gnu.org/licenses/>
## Installation
You can install the package from [github](http://github.com/jranke/pfm), e.g.
using the `devtools` package. Using `quick = TRUE` skips docs,
multiple-architecture builds, demos, and vignettes, to make installation as
fast and painless as possible.
```r
library(devtools)
install_github("jranke/pfm", subdir = "pkg", quick = TRUE)
```
## Use
### Analyse TOXSWA output
Read in and analyse a cwa file:
```r
library(pfm, quietly = TRUE)
```
```
##
## Initialize Python Version 2.7.9 (default, Jun 29 2016, 13:11:10)
## [GCC 4.9.2]
```
```r
example_cwa <- read.TOXSWA_cwa("00003s_pa.cwa")
plot(example_cwa)
```
<img src="README_files/figure-html/unnamed-chunk-3-1.png" width="672" />
Get events above thresholds of 20 and 100 µg/L,
and do a moving window analysis for windows of 7 days
and 21 days, print the results:
```r
example_cwa$get_events(c(20, 100))
example_cwa$moving_windows(c(7, 21))
print(example_cwa)
```
```
## <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20
## datetime t t_firstjan t_rel_to_max cwa_mug_per_L
## 20 1978-10-01 00:00:00 0.000 273.0000 -55.333 0
## 40 1978-10-01 01:00:00 0.042 273.0417 -55.291 0
## 60 1978-10-01 02:00:00 0.083 273.0833 -55.250 0
## 80 1978-10-01 03:00:00 0.125 273.1250 -55.208 0
## 100 1978-10-01 04:00:00 0.167 273.1667 -55.166 0
## 120 1978-10-01 05:00:00 0.208 273.2083 -55.125 0
## cwa_tot_mug_per_L
## 20 0
## 40 0
## 60 0
## 80 0
## 100 0
## 120 0
## Moving window analysis
## window max_TWAC max_AUC_h max_AUC_d
## 1 7 days 2.3926551 401.9660 16.74859
## 2 21 days 0.8369248 421.8101 17.57542
## Event statistics for threshold 20
## t_start cwa_max duration pre_interval AUC_h AUC_d
## 1 55.083 40.58401 0.417 55.083 365.7912 15.2413
## Event statistics for threshold 100
## No events found
```
This can also be done with out files, the function reads
out files from current TOXSWA versions as well as cwa files
from old TOXSWA versions.
### Calculate PEC soil
Simple PEC soil calculation for an application rate of 100 g/ha and
25% interception, assuming complete mixing into 5 cm and a soil bulk
density of 1.5 kg/L, output in mg/kg:
```r
PEC_soil(100, interception = 0.25)
```
```
## scenario
## t_avg default
## 0 0.1
```
### Rautmann drift data
Some of the drift percentage data published by the JKI are included. To
see the data for one application:
```r
drift_data_JKI[1]
```
```
## [[1]]
## crop
## distance Ackerbau Obstbau frueh Obstbau spaet
## 1 2.77 NA NA
## 3 NA 29.20 15.73
## 5 0.57 19.89 8.41
## 10 0.29 11.81 3.60
## 15 0.20 5.55 1.81
## 20 0.15 2.77 1.09
## 30 0.10 1.04 0.54
## 40 0.07 0.52 0.32
## 50 0.06 0.30 0.22
```
### PEC surface water due to drift
Initial PEC values for an application of 100 g/ha in the vicinity of a 30 cm
deep water body are obtained using
```r
PEC_sw_drift(100, applications = 1)
```
```
## 1 m 5 m 10 m 20 m
## 0.92333333 0.19000000 0.09666667 0.05000000
```
|