1 files changed, 64 insertions, 0 deletions
diff --git a/lib/nlp_ruby/SparseVector.rb b/lib/nlp_ruby/SparseVector.rb
new file mode 100644
index 0000000..0033690
--- /dev/null
+++ b/lib/nlp_ruby/SparseVector.rb
@@ -0,0 +1,64 @@
+class SparseVector < Hash
+
+  def initialize
+    super
+    self.default = 0
+  end
+
+  def from_hash h
+    h.each_pair { |k,v| self[k] = v }
+  end
+
+  def sum
+    self.values.inject(:+)
+  end
+
+  def average
+    self.sum/self.size.to_f
+  end
+
+  def variance
+    avg = self.average
+    var = 0.0
+    self.values.each { |i| var += (avg - i)**2 }
+    return var
+  end
+
+  def stddev
+    Math.sqrt self.variance
+  end
+
+  def dot other
+    sum = 0.0
+    self.each_pair { |k,v| sum += v * other[k] }
+    return sum
+  end
+
+  def magnitude
+    Math.sqrt self.values.inject { |sum,i| sum+i**2 }
+  end
+
+  def cosinus_sim other
+    self.dot(other)/(self.magnitude*other.magnitude)
+  end
+
+  def euclidian_dist other
+    dims = [self.keys, other.keys].flatten.uniq
+    sum = 0.0
+    dims.each { |d| sum += (self[d] - other[d])**2 }
+    return Math.sqrt(sum)
+  end
+end
+
+def mean_sparse_vector array_of_vectors
+  mean = SparseVector.new
+  array_of_vectors.each { |i|
+    i.each_pair { |k,v|
+      mean[k] += v
+    }
+  }
+  n = array_of_vectors.size.to_f
+  mean.each_pair { |k,v| mean[k] = v/n }
+  return mean
+end
+