refined prediction

1 files changed, 36 insertions, 0 deletions

diff --git a/feature-filter.rb b/feature-filter.rb
new file mode 100644
index 0000000..3765842
--- /dev/null
+++ b/feature-filter.rb
@@ -0,0 +1,36 @@
+require 'rserve'
+require 'json'
+require 'yaml'
+require 'csv'
+
+R = Rserve::Connection.new
+ENDPOINT = "Cell.association (Net cell association [mL/ug(Mg)])"
+
+def feature_filter
+  data = JSON.parse(File.read("./data.json"))
+  features = data["G15.AC"]["physchem"].keys
+  R.assign "tox", data.collect{|id,cats| cats["tox"][ENDPOINT]}
+  filtered_features = {}
+  features.each do |feature|
+    R.assign "feature", data.collect{|id,cats| cats["physchem"][feature]}
+    begin
+      #R.eval "cor <- cor.test(-log(tox),-log(feature),use='complete')"
+      R.eval "cor <- cor.test(tox,feature,method = 'pearson',use='complete')"
+      pvalue = R.eval("cor$p.value").to_ruby
+      if pvalue <= 0.05
+        r = R.eval("cor$estimate").to_ruby
+        filtered_features[feature] = {}
+        filtered_features[feature]["pvalue"] = pvalue
+        filtered_features[feature]["r"] = r
+      end
+    rescue
+      f = data.collect{|id,cats| cats["physchem"][feature]}
+      f = R.eval("feature").to_ruby
+      p f.collect{|f| p f; Math.log f}
+      p R.eval("log(feature)").to_ruby
+    end
+  end
+  filtered_features.sort{|a,b| a[1]["pvalue"] <=> b[1]["pvalue"]}.to_h
+end
+
+puts feature_filter.to_json