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This repository contains the code associated with the "Working With Algorithms In Python" Safari Video. http://shop.oreilly.com/product/110000667.do

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python-algorithms's Introduction

python-algorithms

This repository contains the code associated with the "Working With Algorithms In Python" Safari Video.

The order of the videos in the final short course is listed below

Log N Behavior *. Big O SideBar
O(n log n) Behavior
Mathematical Algorithms
Brute Force Algorithms
KD Tree Data Structure
DepthFirstSearch
Seven All Pairs Shortest Path
Heap
Single-Source Shortest Path

Each module introduces a real-world problem and presents a Naive approach towards solving that problem. Invariably one can do better, with the right data structure and elegant algorithm. Each module has a corresponding problem that is either closely related, or which can be solved using a variation of the algorithms developed for that module.

The "* Big O SideBar" module introduces terminology used to analyze the algorithms whose code is contained in these modules.

All presentation slides used during the recording of the videos are found in the "Presentation Slides" folder as PDF documents.

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python-algorithms's Issues

KDNode and nearest

I'm watching your video on Safari. I read your README regarding the KDNode and nearest. Would you give an example of points where lines 99 to 118 is necessary? I tried the following as a test between your code and the revised version of nearest below. Both gave the same output.

kd = KDTree()
kd.add([2,3])
kd.add([3,4])
kd.add([5,5])
kd.add([9,6])
kd.add([4,7])
kd.add([8,1])
kd.add([7,2])
v = kd.nearest((4,4))
print(v.point)

And simplify the function to

  def nearest(self, min_distance, p):
        """Return closest node from given subtree to point."""

        d = self.distance(p)
        result = None
        if (d < min_distance):
            result = self
            min_distance = d

        pt = None
        if self.isAbove(p) and self.above:
            pt = self.above.nearest(min_distance, p)
        elif self.isBelow(p) and self.below:
            pt = self.below.nearest(min_distance, p)
        if pt:
            return pt

        return result

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