python – Binary tree pre-order crossing

What is the best way to get around _add and _preorder classroom methods Node at add_node and preorder classroom methods BinaryTree so they have the following class structure:

class Node:
class BinaryTree:

Full Code ::

class Node(object):

    def __init__(self, item, left=None, right=None):
        self.item = item
        self.left = None
        self.right = None

    def __repr__(self):
        return '{}'.format(self.item)

    def _add(self, value):
        new_node = Node(value)

        if not self.item:
            self.item = new_node
        elif not self.left:
            self.left = new_node
        elif not self.right:
            self.right = new_node
            self.left = self.left._add(value)
        return self

    def _preorder(self):
        if self.left:
        if self.right:

class BinaryTree(object):

    def __init__(self):
        self.root = None

    def add_node(self, value):
        if not self.root:
            self.root = Node(value)

    def preorder(self):
        if self.root:
            return self.root._preorder()

if __name__ == '__main__':

    binary_tree = BinaryTree()
    print( "Adding nodes 1 to 10 in the tree...")
    for i in range(1, 11):

    print( "Printing preorder...")

programming challenge – LeetCode: C # binary tree level order traversal

Please check the performance. and also naming convention

Given a binary tree, flip the level order through its nodes & # 39;
values. (i.e. from left to right, level by level).

For example:

Given binary tree (3,9,20,null,null,15,7),
  9  20
   15   7

return its level order traversal as:
using System.Collections.Generic;
using System.Linq;
using GraphsQuestions;
using Microsoft.VisualStudio.TestTools.UnitTesting;

namespace TreeQuestions
    public class BinaryTreeLevelOrderTraversalTest

        //      3
        //     / 
        //    9  20
        //   /  
        //  15   7
        public void TreeTest()
            TreeNode root = new TreeNode(3);
            root.left = new TreeNode(9);
            root.right = new TreeNode(20);
            root.left.left = new TreeNode(15);
            root.left.right = new TreeNode(7);
            IList> res = BinaryTreeLevelOrderTraversalClass.LevelOrder(root);
            CollectionAssert.AreEqual(res(0).ToList(), new List{3});
            CollectionAssert.AreEqual(res(1).ToList(), new List{9,20});
            CollectionAssert.AreEqual(res(2).ToList(), new List{15,7});

        public void OneNodeTreeTest()
            TreeNode root = new TreeNode(3);
            IList> res = BinaryTreeLevelOrderTraversalClass.LevelOrder(root);
            CollectionAssert.AreEqual(res(0).ToList(), new List { 3 });

    public class BinaryTreeLevelOrderTraversalClass
        public static IList> LevelOrder(TreeNode root)
            List> res = new List>();
            if (root == null)
                return res;
            Queue Q = new Queue();


            int counter = 0; // which level
            while (Q.Count > 0)
                int children = Q.Count;
                res.Add(new List());
                for (int i = 0; i < children; i++)
                    var temp = Q.Dequeue();
                    if (temp.left != null)
                    if (temp.right != null)
            return res;


How can I solve a recursion equation with a square root using the recursion tree method?

$ T (n) = sqrt {n} T ( frac {n} {2}) + sqrt {n} $

I am trying to solve this question by the recursion tree method, do we have a way to draw a recursion tree for this eqn.

I just don't want to use the master theorem or extended master

layout – Display of two pieces of information in the tree node

In my web application, I have a tree with each node having two statuses.

The nodes are circles linked to each other.

The status can be OK, KO or PARTIAL.

The first state is the "technical state" of the node.
The second state is "the functional state".

The functional state of the node depends on its technical state.

I need a way to display both states (OK / KO / PARTIAL) so that users can quickly identify the nodes that are in functional or technical KO or PARTIAL state.

How to synchronize a photo tree in Darktable so that it retrieves additions / deletions?

I'm new to Darktable and am trying to use it to manage a large RAW image tree.

I have already recursively imported the root of the tree. It now displays the directory names in the light table view when I select "folders" on the left under "collect images".

If I now add more images to existing directories or add new directories under the root, or delete some images, how do I tell DarkTable to scan the root directory again and do it recover additions or deletions?

Fourier analysis – Reference request: explicit construction of Kakeya sets using Perron's tree

I have found many excellent notes online that illustrate how to build a set of Kakeya needles (with measure $ < varepsilon $.) Yet none of them gives a complete argument on the construction of a set of Kakeya (with zero measure). The closest is given on page 6 of,

which unfortunately leaves the detail to argue for the existence of a unitary line segment in $ cap_ {i = 1} ^ infty U_n $. He says this is proven subtly using a compactness argument.

What is this argument?

Can we express $ EG $ with only $ US $ in CTL (Computation Tree Logic)?

According to the article on the logic of the calculation tree on Wikipedia, the following set of operators can be considered minimal (all CTL formulas can be transformed to use only these operators): $ top $, $ lor $, $ EG $, US $ $, and $ EX $.

However, I do not know if this is really a minimal example. Could we not express $ EG $ with US $ $ as follows?

EG phi equiv E ( phi U phi)

Is the equivalence given by me not true or the definition of a minimal set of operators Doesn't necessarily mean that the number of operators in this set cannot be reduced?

data structures – Proof that an almost complete binary tree with n nodes has at least $ frac {n} {2} $ leaf nodes

I'm having trouble proving what my title says. Some textbooks refer to almost complete binary trees as complete, so to be clear, when I say almost complete binary tree, I mean a binary tree whose levels are all full except the last one in which all the nodes are as far as possible on the left. .

I thought about proving it by induction but I'm not sure how to do it. Ideas?

decision tree – Entropy of data

I am new to python and entropy (using for decision trees, also new to) and am trying to figure out how to calculate specific data sets. I understand the formula in general, but I don't know how to use it in practice. For example, if I receive a file (200 entries) whose first number is x, the second number is y and the last number is the class label (0 or 1):


How could I calculate the entropy of this? And another file (8,134 entries):

PS3,2013,Racing,Deep Silver,0.02,0.01,0,0.01,0.04,"Eutechnyx, Deep Silver",M,13
PS3,2013,Adventure,Codemasters,0.06,0.03,0,0.01,0.1,Team 17,M,17
XB,2002,Misc,Infogrames,0.16,0.05,0,0.01,0.22,Data Design Interactive,E,19

How to calculate the entropy of this file?

Is it possible to access each node of a link / cut tree in $ O (n) $ time?

According to the sequential access theorem, we can access each node of a splay tree in $ O (n) $ moment when accessing the nodes in a specific order.

Given a cut link / tree, is it possible to access all of its nodes faster than the naive $ O (n log n) $ time amortized in the worst case?