1 files changed, 92 insertions, 0 deletions
diff --git a/lib/nanoparticle.rb b/lib/nanoparticle.rb
new file mode 100644
index 0000000..02d9a89
--- /dev/null
+++ b/lib/nanoparticle.rb
@@ -0,0 +1,92 @@
+module OpenTox
+
+  class Nanoparticle < Substance
+    include OpenTox
+
+    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
+        case feature.category
+        when "P-CHEM"
+          properties[feature.id.to_s] ||= []
+          properties[feature.id.to_s] << value
+          properties[feature.id.to_s].uniq!
+        when "Proteomics"
+          properties[feature.id.to_s] ||= []
+          properties[feature.id.to_s] << value
+          properties[feature.id.to_s].uniq!
+        when "TOX"
+          dataset.add self, feature, value
+        else
+          warn "Unknown feature type '#{feature.category}'. Value '#{value}' not inserted."
+        end
+        dataset_ids << dataset.id
+        dataset_ids.uniq!
+      end
+    end
+
+    def parse_ambit_value feature, v, dataset
+      # TODO add study id to warnings
+      v.delete "unit"
+      # TODO: ppm instead of weights
+      if v.keys == ["textValue"]
+        add_feature feature, v["textValue"], dataset
+      elsif v.keys == ["loValue"]
+        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}'."
+      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."
+      elsif v.keys.size == 2 and v["loQualifier"] #== ">="
+        #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"
+      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."
+      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."
+      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."
+      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."
+      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}'."
+        add_feature feature, v["loValue"], dataset
+      elsif v == {} # do nothing
+      else
+        warn "Cannot parse Ambit eNanoMapper value '#{v}' for feature '#{feature.name}'."
+      end
+    end
+
+  end
+end