From 9e7b36613e98601de7b2ceb2d4442e11f1ae868a Mon Sep 17 00:00:00 2001
From: Christoph Helma <helma@in-silico.ch>
Date: Thu, 10 Nov 2016 12:23:46 +0100
Subject: intermediate commit, may be defunct

---
 lib/nanoparticle.rb | 46 ++++++++++++++++++++++++++++++++++------------
 1 file changed, 34 insertions(+), 12 deletions(-)

(limited to 'lib/nanoparticle.rb')

diff --git a/lib/nanoparticle.rb b/lib/nanoparticle.rb
index 23e155c..02d9a89 100644
--- a/lib/nanoparticle.rb
+++ b/lib/nanoparticle.rb
@@ -3,8 +3,30 @@ module OpenTox
   class Nanoparticle < Substance
     include OpenTox
 
-    field :core, type: Hash, default: {}
-    field :coating, type: Array, default: []
+    field :core_id, type: String, default: nil
+    field :coating_ids, type: Array, default: []
+
+    def core
+      Compound.find core_id
+    end
+
+    def coating
+      coating_ids.collect{|i| Compound.find i }
+    end
+
+    def fingerprint type=DEFAULT_FINGERPRINT
+      core_fp = core.fingerprint type
+      coating_fp = coating.collect{|c| c.fingerprint type}.flatten.uniq.compact
+      (core_fp.empty? or coating_fp.empty?) ? [] : (core_fp+coating_fp).uniq.compact
+    end
+
+    def calculate_properties descriptors=PhysChem::OPENBABEL
+      if core.smiles and !coating.collect{|c| c.smiles}.compact.empty?
+        core_prop = core.calculate_properties descriptors
+        coating_prop = coating.collect{|c| c.calculate_properties descriptors if c.smiles}
+        descriptors.collect_with_index{|d,i| [core_prop[i],coating_prop.collect{|c| c[i] if c}]}
+      end
+    end
 
     def add_feature feature, value, dataset
       unless feature.name == "ATOMIC COMPOSITION" or feature.name == "FUNCTIONAL GROUP" # redundand
@@ -37,28 +59,28 @@ module OpenTox
         add_feature feature, v["loValue"], dataset
       elsif v.keys.size == 2 and v["errorValue"]
         add_feature feature, v["loValue"], dataset
-        warn "Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
+        #warn "Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
       elsif v.keys.size == 2 and v["loQualifier"] == "mean"
         add_feature feature, v["loValue"], dataset
-        warn "'#{feature.name}' is a mean value. Original data is not available."
+        #warn "'#{feature.name}' is a mean value. Original data is not available."
       elsif v.keys.size == 2 and v["loQualifier"] #== ">="
-        warn "Only min value available for '#{feature.name}', entry ignored"
+        #warn "Only min value available for '#{feature.name}', entry ignored"
       elsif v.keys.size == 2 and v["upQualifier"] #== ">="
-        warn "Only max value available for '#{feature.name}', entry ignored"
+        #warn "Only max value available for '#{feature.name}', entry ignored"
       elsif v.keys.size == 3 and v["loValue"] and v["loQualifier"].nil? and v["upQualifier"].nil?
         add_feature feature, v["loValue"], dataset
-        warn "loQualifier and upQualifier are empty."
+        #warn "loQualifier and upQualifier are empty."
       elsif v.keys.size == 3 and v["loValue"] and v["loQualifier"] == "" and v["upQualifier"] == ""
         add_feature feature, v["loValue"], dataset
-        warn "loQualifier and upQualifier are empty."
+        #warn "loQualifier and upQualifier are empty."
       elsif v.keys.size == 4 and v["loValue"] and v["loQualifier"].nil? and v["upQualifier"].nil?
         add_feature feature, v["loValue"], dataset
-        warn "loQualifier and upQualifier are empty."
+        #warn "loQualifier and upQualifier are empty."
       elsif v.size == 4 and v["loQualifier"] and v["upQualifier"] and v["loValue"] and v["upValue"]
-        add_feature feature, [v["loValue"],v["upValue"]].mean, dataset
-        warn "Using mean value of range #{v["loValue"]} - #{v["upValue"]} for '#{feature.name}'. Original data is not available."
+        #add_feature feature, [v["loValue"],v["upValue"]].mean, dataset
+        #warn "Using mean value of range #{v["loValue"]} - #{v["upValue"]} for '#{feature.name}'. Original data is not available."
       elsif v.size == 4 and v["loQualifier"] == "mean" and v["errorValue"]
-        warn "'#{feature.name}' is a mean value. Original data is not available. Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
+        #warn "'#{feature.name}' is a mean value. Original data is not available. Ignoring errorValue '#{v["errorValue"]}' for '#{feature.name}'."
         add_feature feature, v["loValue"], dataset
       elsif v == {} # do nothing
       else
-- 
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