# The study of psychological questionnaire using deep search analysis

Source: Internet
Author: User

Research background of psychological questionnaire analysis using deep Search

Yesterday my girlfriend sent me a psychological questionnaire for me to do. I have always sniffed at this psychological questionnaire: how a person's character can be determined by a few simple questions. But as a technician, I decided to use technical means to analyze the questionnaire and prove to my girlfriend that it lacks scientificity.

The original of the questionnaire is as follows

Interested friends can play ~

I would like to know the following questions:
1. Does the questionnaire have a loop? If there is a loop, you can prove that the questionnaire is irregular.
2. A answer is not impossible to achieve? Because of the 4 answers, only a answer has no inclination to be the same.
3. If a answer can be reached, then how many possibilities? How much is percentage?

Analysis

This questionnaire has features: Each topic corresponds to multiple options, and each option corresponds to a question or answer. From a person's answer to the path, in fact, this is a typical diagram structure.

In combination with the questions I want to know, there are several areas to consider:
1. No loop on the proof diagram
2. Using Dfs proof A is achievable
3. Count all possible results to figure out the percentage of a

Modeling

I'm going to use list mode to build the diagram

``  @list= [    [1],    [2,3],    [3,4],    [4,5,6],    [5,6,7],    [6,7],    [7,8,9],    [8,9],    [9,Ten, One],    [Ten, One, A],    [ A, -],    [ -, -],    [ -, the],    [ the, -, -],    [ the, -],    [ -, -],    [ -, -, +, -],    [ -, +,' B '],    [ +,' C '],    [ A,' A '],    [ +,' D '],    [ A,' B '],    [' A ',' C ',' D ']  ]``

The graphs have 0 to 22 nodes, plus a, B, C, D.
1. Because I do not want to deal with subscript, so the starting position of the figure, I set to 0;
2. The node of the graph, I simply use the index of the array to express;
3. Direct output of the answer, do not need to be placed in the node collection;

DFS diagram has no loops

The code is as follows:

`` def Has_cycle? Recursion_stack = [false] * atCheck_cycle (0, Recursion_stack)End def Check_cycle (vertex, recursion_stack) Recursion_stack[vertex] =true  @list[Vertex].each Do|node|Next ifOver? (node)return true ifRecursion_stack[node] check_cycle (node, recursion_stack)EndRecursion_stack[vertex] =false  return falseEnd``

`over?`The method is used to determine whether recursion is over.

``def over?(point)  [‘A‘‘B‘‘C‘‘D‘].include?(point.to_s)end``
1. `has_cycle`To determine if there is a loop, I will be a fully iterative node whether access to the information saved in`recursion_stack`
2. It calls the deep search algorithm to implement the`check_cycle`

The result of the operation is`false`

A can you get there? A if it can be reached, then how likely is a?
``@result = []def dfs(node)  @list[node].eachdo |vertex|    if over?(vertex)      @result << vertex      next    end    dfs(vertex)  endend``

Use a limited depth search to save the final results in `@result` and print out the results.

``Def count_charactor (result, charactor)result. Count {|Item|Item= = Charactor}EndDfs0) puts"There's a total of%d possible answers."% @result. Size (' A '..' D '). To_a. each  Do|charactor| Puts"#{charactor}:%d possible, accounted for%f"% [Count_charactor (@result, charactor), Count_charactor (@result, charactor). To_f/@result.length]End``

The results are as follows:

``27860 可能的答案A:89600.321608B:33600.120603C:81200.291457D:74200.266332``
Output to the 100 path of answer a
``@i=0 def DFS (node, stack) Stack.push node@list[Node].each Do|vertex|ifOver? (vertex)@result<< VertexifVertex = =' A '        @i+=1Puts"The path to A is:"Puts Stack.join (" ,")End       Break if @i== -      Next    EndDFS (vertex, stack)EndStack.popEnd``

Use a stack `stack` to save the path, and a point to output all the results

Summarize

The application of the graph algorithm is very extensive and deserves further study. Sometimes the problem of abstracting real-time problems into graphs allows us to look at issues from a different perspective. Furthermore, the `ruby` algorithm of implementing graph is very simple. `dfs`than `bfs` simple, but received the limit of the program stack. But it is more suitable for this program.

The study of psychological questionnaire using deep search analysis

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