Make README.md simple, and point to the reference

1 files changed, 5 insertions, 75 deletions

diff --git a/docs/index.html b/docs/index.html
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@@ -69,82 +69,12 @@ this program. If not, see &lt;http:<span class="er">//</span>www.gnu.org/license
 <div id="use" class="section level2">
 <h2 class="hasAnchor">
 <a href="#use" class="anchor"> </a>Use</h2>
-<div id="analyse-toxswa-output" class="section level3">
-<h3 class="hasAnchor">
-<a href="#analyse-toxswa-output" class="anchor"> </a>Analyse TOXSWA output</h3>
-<p>Read in and analyse a cwa file:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(pfm, <span class="dt">quietly =</span> <span class="ot">TRUE</span>)</code></pre></div>
-<pre><code>## 
-## Initialize Python Version 2.7.9 (default, Jun 29 2016, 13:11:10) 
-## [GCC 4.9.2]</code></pre>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">example_cwa &lt;-<span class="st"> </span><span class="kw"><a href="reference/read.TOXSWA_cwa.html">read.TOXSWA_cwa</a></span>(<span class="st">"00003s_pa.cwa"</span>)
-<span class="kw">plot</span>(example_cwa)</code></pre></div>
-<p><img src="README_files/figure-html/unnamed-chunk-3-1.png" width="672"></p>
-<p>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:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">example_cwa$<span class="kw">get_events</span>(<span class="kw">c</span>(<span class="dv">20</span>, <span class="dv">100</span>))
-example_cwa$<span class="kw">moving_windows</span>(<span class="kw">c</span>(<span class="dv">7</span>, <span class="dv">21</span>))
-<span class="kw">print</span>(example_cwa)</code></pre></div>
-<pre><code>## &lt;TOXSWA_cwa&gt; 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</code></pre>
-<p>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.</p>
-</div>
-<div id="calculate-pec-soil" class="section level3">
-<h3 class="hasAnchor">
-<a href="#calculate-pec-soil" class="anchor"> </a>Calculate PEC soil</h3>
-<p>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:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="reference/PEC_soil.html">PEC_soil</a></span>(<span class="dv">100</span>, <span class="dt">interception =</span> <span class="fl">0.25</span>)</code></pre></div>
-<pre><code>##      scenario
-## t_avg default
-##     0     0.1</code></pre>
-</div>
-<div id="rautmann-drift-data" class="section level3">
-<h3 class="hasAnchor">
-<a href="#rautmann-drift-data" class="anchor"> </a>Rautmann drift data</h3>
-<p>Some of the drift percentage data published by the JKI are included. To see the data for one application:</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">drift_data_JKI[<span class="dv">1</span>]</code></pre></div>
-<pre><code>## [[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</code></pre>
-</div>
-<div id="pec-surface-water-due-to-drift" class="section level3">
-<h3 class="hasAnchor">
-<a href="#pec-surface-water-due-to-drift" class="anchor"> </a>PEC surface water due to drift</h3>
-<p>Initial PEC values for an application of 100 g/ha in the vicinity of a 30 cm deep water body are obtained using</p>
-<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw"><a href="reference/PEC_sw_drift.html">PEC_sw_drift</a></span>(<span class="dv">100</span>, <span class="dt">applications =</span> <span class="dv">1</span>)</code></pre></div>
-<pre><code>##        1 m        5 m       10 m       20 m 
-## 0.92333333 0.19000000 0.09666667 0.05000000</code></pre>
+<p>Please refer to the <a href="docs/index.html">reference</a>.</p>
 </div>
+<div id="examples" class="section level2">
+<h2 class="hasAnchor">
+<a href="#examples" class="anchor"> </a>Examples</h2>
+<p>One recent nice example of the usage of this package is the visualisation of a time weighted average for a sawtooth curve obtained from several overlays of mkinfit predictions as shown <a href="docs/reference/plot.one_box.html">here</a>.</p>
 </div>
 </div>
   </div>