From f7680842ee830af78d860b3a0a09b654368df90a Mon Sep 17 00:00:00 2001
From: gebele <gebele@in-silico.ch>
Date: Thu, 14 Jan 2016 09:37:39 +0000
Subject: changed weight method for lazar v8-nestec release

---
 views/neighbors.haml  | 4 ++--
 views/prediction.haml | 8 ++++----
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/views/neighbors.haml b/views/neighbors.haml
index 4a1f3ea..a69f38b 100644
--- a/views/neighbors.haml
+++ b/views/neighbors.haml
@@ -66,10 +66,10 @@
                       %p= Compound.find(neighbor[0]).svg
                       %p= Compound.find(neighbor[0]).smiles
                     - c = Compound.find(neighbor[0])
-                    - mw = c.molecular_weight
+                    //- mw = c.molecular_weight
                     / Measured Activity
                     %td{:style =>"vertical-align:middle;padding-left:1em;width:20%;white-space:nowrap;"}
-                      = (type == "Regression") ? neighbor[2].collect{|n| weight = c.mmol_to_mg(n, mw); '%.2e' % n + " (#{@models[j].unit})"+"|#{'%.2e' % weight} (mg/kg_bw/day)"}.join("</br>") : neighbor[2].join(", ")
+                      = (type == "Regression") ? neighbor[2].collect{|n| weight = c.mmol_to_mg(n); '%.2e' % n + " (#{@models[j].unit})"+"|#{'%.2e' % weight} (mg/kg_bw/day)"}.join("</br>") : neighbor[2].join(", ")
                     / Similarity
                     %td{:style =>"vertical-align:middle;padding-left:1em;width:20%;"}
                       / TODO differentiate between no neighbors found and compound found in dataset, display neighbors for compounds in dataset?
diff --git a/views/prediction.haml b/views/prediction.haml
index a74b95a..8d7e3d0 100644
--- a/views/prediction.haml
+++ b/views/prediction.haml
@@ -18,7 +18,7 @@
           %td{:id=>"compound", :style=>"vertical-align:top;"}
             %p= @compound.svg
             %p= @compound.smiles
-          - mw = @compound.molecular_weight
+          -#- mw = @compound.molecular_weight
           - @model_types = {}
           - @dbhit = {}
           - @predictions.each_with_index do |prediction,i|
@@ -34,9 +34,9 @@
                 %b Measured activity:
                 - p prediction[:value] 
                 - if prediction[:value].is_a?(Array)
-                  = (type == "Regression") ? prediction[:value].collect{|v| weight = Compound.from_smiles(@compound.smiles).mmol_to_mg(v, mw); '%.2e' % v + " (#{@models[i].unit})"+"|#{'%.2e' % weight} (mg/kg_bw/day)"}.join("</br>") : prediction[:value].join(", ")
+                  = (type == "Regression") ? prediction[:value].collect{|v| weight = Compound.from_smiles(@compound.smiles).mmol_to_mg(v); '%.2e' % v + " (#{@models[i].unit})"+"|#{'%.2e' % weight} (mg/kg_bw/day)"}.join("</br>") : prediction[:value].join(", ")
                 - else
-                  = (type == "Regression") ? "#{"%.2e" % prediction[:value]} (#{@models[i].unit}) | #{'%.2e' % @compound.mmol_to_mg(prediction[:value], mw)} (mg/kg_bw/day)" : prediction[:value]
+                  = (type == "Regression") ? "#{"%.2e" % prediction[:value]} (#{@models[i].unit}) | #{'%.2e' % @compound.mmol_to_mg(prediction[:value])} (mg/kg_bw/day)" : prediction[:value]
                 %p 
                   %b Compound is part of the training dataset
               - elsif prediction[:neighbors].size > 0
@@ -46,7 +46,7 @@
                 = type
                 %br
                 %b Prediction:
-                = (type == "Regression") ? "#{'%.2e' % prediction[:value]} (#{@models[i].unit}) | #{'%.2e' % @compound.mmol_to_mg(prediction[:value], mw)} (mg/kg_bw/day)" : prediction[:value]
+                = (type == "Regression") ? "#{'%.2e' % prediction[:value]} (#{@models[i].unit}) | #{'%.2e' % @compound.mmol_to_mg(prediction[:value])} (mg/kg_bw/day)" : prediction[:value]
                 / TODO update description
                 / %a.btn.glyphicon.glyphicon-info-sign{:href=>"#", :title=>"Prediction", data: {toggle:"popover", placement:"left", html:"true", content:"LAZAR calculates searches the training dataset for similar compounds (neighbors) and calculates the prediction from their measured activities. LAZAR calculates predictions using <ul><li>a majority vote (weighted by compound similarity) for<br /><b>classification</b> (<a href='http://www.frontiersin.org/Journal/10.3389/fphar.2013.00038/abstract', target='_blank'>original publication</a>) </li><li>a local QSAR model based on neighbors for<br /><b>regression</b> (<a href='http://www.frontiersin.org/Journal/10.3389/fphar.2013.00038/abstract', target='_blank'</h>original publication</a>) </li></ul>Please keep in mind that predictions are based on the measured activities of neighbors."}}
                 %br
-- 
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