machine learning wrapping

src/utils/ml.py

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+"""
+	This file is intended to perfom certain machine learning tasks based on numpy
+	We are trying to keep it lean that's why no sklearn involved yet
+"""
+import numpy as np
+
+class ML:
+	@staticmethod
+	def Filter (attr,value,data) :
+		#
+		# @TODO: Make sure this approach works across all transport classes
+		# We may have a potential issue of how the data is stored ... it may not scale
+		#
+		return [item[0] for item in data if item[0][attr] == value]
+	@staticmethod
+	def Extract(lattr,data):
+		return [[row[id] for id in lattr] for row in data]
+
+	def init(self,lattr,data):
+		self.lattr = attr
+		self.data = data
+		self.X = []
+		self.Xmeans = []
+		for id in lattr:
+			xvalues = [item for item in self.data[id]]
+			self.Xmeans.append(np.mean(xvalues))
+			self.X.append(xvalues)
+		slef.Xcov = np.cov(self.X)
+		#
+		# Let's get the covariance matrix here ...
+		#
+