title: ggplot legend not showing correct typelines
body: <p>I have a plot with 5 lines that are dashed, 5 that are solid. This is correctly displaying in the plot. However, using the following code, the legend shows all line to be solid. I find this strange, because the legend is showing the correct variation in the line size, which is formatted in the same way. I tried replacing <code>&quot;Factorlevel&quot; = &quot;solid&quot;</code> by <code>&quot;Factorlevel&quot; = 1</code>, but this didn't work either.</p>
  <p>Please see reproducible example below my code</p>
  <pre><code>ggplot(respplot_new, aes(x=expl.val,y=pred.val,color=model))+
  geom_line(aes(size=model,linetype=model)) +
  scale_linetype_manual(values = c(&quot;RF&quot; = &quot;solid&quot;, &quot;GBM&quot; = &quot;solid&quot;,
   &quot;MAXENT&quot; = &quot;solid&quot;, &quot;MARS&quot; = &quot;solid&quot;, &quot;GAM&quot; = &quot;solid&quot;,
   &quot;GLM&quot;=&quot;dashed&quot;, &quot;ANN&quot;=&quot;dashed&quot;, &quot;FDA&quot;=&quot;dashed&quot;,&quot;CTA&quot;=&quot;dashed&quot;,&quot;SRE&quot;=&quot;dashed&quot;))+  
  scale_size_manual(values = c(&quot;RF&quot; = 1.8, &quot;GBM&quot; = 1.8,
   &quot;MAXENT&quot; = 1.8, &quot;MARS&quot; = 1.8, &quot;GAM&quot; = 1.8,
   &quot;GLM&quot;=1.1, &quot;ANN&quot;=1.1, &quot;FDA&quot;=1.1,&quot;CTA&quot;=1.1,&quot;SRE&quot;=1.1))+  
  facet_grid(~respplot_new$expl.name,scales=&quot;free&quot;)+theme_bw() 
  </code></pre>
  <p>Sorry for the length of the reproducible example, this is the minimum I was able to obtain with the dput function. Thank you for your consideration.</p>
  <pre><code>structure(list(expl.name = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 
  3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 
  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
  1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
  4L, 4L, 4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
  2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c(&quot;Proportion of agriculture&quot;, 
  &quot;Human population density&quot;, &quot;Distance to agriculture&quot;, &quot;Proportion of development&quot;
  ), class = &quot;factor&quot;), expl.val = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
  0, 1098.78377525253, 1098.78377525253, 1098.78377525253, 1098.78377525253, 
  1098.78377525253, 1098.78377525253, 1098.78377525253, 1098.78377525253, 
  1098.78377525253, 1098.78377525253, 85.8585858585859, 85.8585858585859, 
  85.8585858585859, 85.8585858585859, 85.8585858585859, 85.8585858585859, 
  85.8585858585859, 85.8585858585859, 85.8585858585859, 85.8585858585859, 
  86.8686868686869, 86.8686868686869, 86.8686868686869, 86.8686868686869, 
  86.8686868686869, 86.8686868686869, 86.8686868686869, 86.8686868686869, 
  86.8686868686869, 86.8686868686869, 75.7575757575758, 75.7575757575758, 
  75.7575757575758, 75.7575757575758, 75.7575757575758, 75.7575757575758, 
  75.7575757575758, 75.7575757575758, 75.7575757575758, 75.7575757575758, 
  76.7676767676768, 76.7676767676768, 76.7676767676768, 76.7676767676768, 
  76.7676767676768, 76.7676767676768, 76.7676767676768, 76.7676767676768, 
  76.7676767676768, 76.7676767676768, 390.966472326806, 390.966472326806, 
  390.966472326806, 390.966472326806, 390.966472326806, 390.966472326806, 
  390.966472326806, 390.966472326806, 390.966472326806, 390.966472326806, 
  469.159766792168, 469.159766792168, 469.159766792168, 469.159766792168, 
  469.159766792168, 469.159766792168, 469.159766792168, 469.159766792168, 
  469.159766792168, 469.159766792168), model = structure(c(7L, 
  9L, 8L, 5L, 2L, 6L, 4L, 3L, 1L, 10L, 7L, 9L, 8L, 5L, 2L, 6L, 
  4L, 3L, 1L, 10L, 7L, 9L, 8L, 5L, 2L, 6L, 4L, 3L, 1L, 10L, 7L, 
  9L, 8L, 5L, 2L, 6L, 4L, 3L, 1L, 10L, 7L, 9L, 8L, 5L, 2L, 6L, 
  4L, 3L, 1L, 10L, 7L, 9L, 8L, 5L, 2L, 6L, 4L, 3L, 1L, 10L, 7L, 
  9L, 8L, 5L, 2L, 6L, 4L, 3L, 1L, 10L, 7L, 9L, 8L, 5L, 2L, 6L, 
  4L, 3L, 1L, 10L), .Label = c(&quot;RF&quot;, &quot;GBM&quot;, &quot;MAXENT&quot;, &quot;MARS&quot;, &quot;GAM&quot;, 
  &quot;GLM&quot;, &quot;ANN&quot;, &quot;FDA&quot;, &quot;CTA&quot;, &quot;SRE&quot;), class = &quot;factor&quot;), pred.val = c(0.377837081657681, 
  0.289682245014943, 0.303656725695349, 0.652763823576286, 0.551049518656044, 
  0.543664244044848, 0.600094628037518, 0.842622666666667, 0.557333333333333, 
  1, 0.497161495216137, 0.289682245014943, 0.411028449541226, 0.661018388330178, 
  0.550904016356143, 0.546817382114225, 0.634881521097495, 0.862494333333333, 
  0.594, 1, 0.0810608869754512, 0.489491284870227, 0.171208708485626, 
  0.0637801802410929, 0.307426323707738, 0.0308128470877357, 0.0743518990932153, 
  0.0817215, 0.484, 0, 0.0807936474564006, 0.489491284870227, 0.170148227471718, 
  0.0597404545728378, 0.307426323707738, 0.0295449629590053, 0.0716436251791972, 
  0.0804373, 0.483333333333333, 0, 0.654393286840172, 0.696277149376623, 
  0.73174123479955, 0.0033385823708866, 0.676035380732291, 0.978015696055508, 
  0.671377674947882, 0.883775666666667, 0.542, 0, 0.654393271023166, 
  0.696277149376623, 0.730485340340835, 0.00321040440788555, 0.676035380732291, 
  0.979003084409959, 0.670006581468528, 0.882102666666667, 0.542, 
  0, 0.0713256037593483, 0.242886821072384, 0.140090432179967, 
  0.042605020907364, 0.145155448037101, 2.42353541255428e-10, 0.0205399878748643, 
  0.0508441666666667, 0.204, 0, 0.0713256037593483, 0.242886821072384, 
  0.138548917887711, 0.00555445488463794, 0.145155448037101, 3.25156380242609e-12, 
  0.0187553675668009, 0.0508441666666667, 0.202666666666667, 0)), row.names = c(NA, 
  -80L), class = c(&quot;tbl_df&quot;, &quot;tbl&quot;, &quot;data.frame&quot;))
  </code></pre>