Mathematics · Discrete Mathematics

Graph Community Modularity Excess observed within-community edge fraction Solver

Rearrange the graph community modularity excess relationship and solve for observed within-community edge fraction.

Runs locally
Your numbers

Inputs and results stay in this browser. Change one value at a time to explore the relationship.

Your inputCalculatedPassed forward in chains
observed within-community edge fraction0.46
Reconstructed modularity contribution0.15

Calculation steps

  1. Use a=c+b with modularity contribution=0.15000000000000002 and null-model expected fraction=0.31.
  2. observed within-community edge fraction=0.46.
  3. Substitution into c=a−b reconstructs 0.15000000000000002.

Understand Graph Community Modularity Excess: solve observed within-community edge fraction

One idea, three depths

Choose how deeply to explain Graph Community Modularity Excess: solve observed within-community edge fraction

Graph Community Modularity Excess: solve observed within-community edge fraction: Rearrange the graph community modularity excess relationship and solve for observed within-community edge fraction.

Age 5Explain it to a 5-year-oldStart with a picture

Imagine using Graph Community Modularity Excess: solve observed within-community edge fraction to answer this question: rearrange the graph community modularity excess relationship and solve for observed within-community edge fraction? Enter modularity contribution and null-model expected fraction; the calculator shows observed within-community edge fraction. For example: observed within-community edge fraction=0.46 and null-model expected fraction=0.31 produce modularity contribution=0.15000000000000002. The answer tells you observed within-community edge fraction.

Age 15Explain it to a 15-year-oldConnect it to the formula

A modularity contribution is observed within-community edge fraction minus its null-model expectation. This page isolates observed within-community edge fraction and verifies it in the original relationship. The rule is a=c+b. Its input values are modularity contribution, null-model expected fraction, and the main result is observed within-community edge fraction. For example: observed within-community edge fraction=0.46 and null-model expected fraction=0.31 produce modularity contribution=0.15000000000000002.

CollegeExplain it at college levelState the model precisely

This calculator evaluates the stated graph community modularity excess: solve observed within-community edge fraction relation over the valid real-number domain stated below. The implemented relation is a=c+b, evaluated from modularity contribution, null-model expected fraction to produce observed within-community edge fraction. A modularity contribution is observed within-community edge fraction minus its null-model expectation. This page isolates observed within-community edge fraction and verifies it in the original relationship. The null model and normalization must match those used for the observed fraction.

Inputs and valid domain

  • modularity contribution must be a finite real number.
  • null-model expected fraction must be a finite real number.

Important boundary: The null model and normalization must match those used for the observed fraction.

The formula

a=c+b

How the calculator works through it

It substitutes modularity contribution, null-model expected fraction into the formula and exposes every numerical step above. The main output is observed within-community edge fraction, accompanied by Reconstructed modularity contribution.

Read the result correctly

The observed within-community edge fraction is the direct answer to “rearrange the graph community modularity excess relationship and solve for observed within-community edge fraction.” Read it with the units shown beside the inputs; a sign, angle, percentage or rate changes what the number means.

A worked check

observed within-community edge fraction=0.46 and null-model expected fraction=0.31 produce modularity contribution=0.15000000000000002.

Where this model stops being reliable

The null model and normalization must match those used for the observed fraction.

Learn it by changing one value

Begin with the worked example, then change one value while keeping the others fixed. Compare the new result and calculation steps to identify which part of the formula changed.

Dictionary terms behind this calculator

Before studying the codeWhat you should know firstUse the calculator immediately, or check the foundations before reading the implementation.

These foundations help you understand why Graph Community Modularity Excess: solve observed within-community edge fraction works. They never block the calculator, and “optional” means useful context rather than a hidden requirement.

Hard requirements

  • Reading formulas and substituting values

    Graph Community Modularity Excess: solve observed within-community edge fraction uses a=c+b. You need to recognise what each side represents before substituting the stated inputs or rearranging the relationship.

    Review this foundation about 4 min

Strong support

  • Sets, membership and finite collections

    Sets provide the objects and membership rules that give Graph Community Modularity Excess: solve observed within-community edge fraction its discrete meaning.

    Review this foundation about 6 min

Optional enrichment

  • Ordered arrangements

    Permutations connect Graph Community Modularity Excess: solve observed within-community edge fraction to systematic counting and arrangement problems.

    Review this foundation about 5 min
Learn the missing foundationsI already know these — show the code

Mathematics → algorithm → program

Implement this calculation in code

These are direct reference implementations of the calculator's principal relationship and first output. They run locally and include a small known-answer check where the language supports it.

Algorithm

  1. Read modularity contribution, null-model expected fraction.
  2. Evaluate the principal relationship: a=c+b.
  3. Return observed within-community edge fraction and check the domain conditions described above.
Python
            from math import *

def graph_modularity_excess_solve_a(c, b) -> float:
    return (c + b)

assert abs(graph_modularity_excess_solve_a(0.15000000000000002, 0.31) - 0.46) < 1e-6 * max(1.0, abs(0.46))
          
Current calculator valuesUpdates when you change an input above.
              
            
C
            #include <assert.h>
#include <math.h>

double graph_modularity_excess_solve_a(double c, double b) {
    return (c + b);
}

int main(void) {
    const double expected = 0.46;
    const double actual = graph_modularity_excess_solve_a(0.15000000000000002, 0.31);
    assert(fabs(actual - expected) < 1e-6 * fmax(1.0, fabs(expected)));
}
          
Current calculator valuesUpdates when you change an input above.
              
            
C++
            #include <cassert>
#include <cmath>
#include <numbers>

double graph_modularity_excess_solve_a(double c, double b) {
    return (c + b);
}

int main() {
    constexpr double expected = 0.46;
    const double actual = graph_modularity_excess_solve_a(0.15000000000000002, 0.31);
    assert(std::fabs(actual - expected) < 1e-6 * std::fmax(1.0, std::fabs(expected)));
}
          
Current calculator valuesUpdates when you change an input above.
              
            
Linux x86-64 assembly

x86-64 NASM · System V ABI · Linux · SSE2 with libm where required

            ; double graph_modularity_excess_solve_a(double c, double b)
; Linux x86-64 NASM · System V ABI · first eight doubles in xmm0–xmm7
global graph_modularity_excess_solve_a
section .text

graph_modularity_excess_solve_a:
    push rbp
    mov rbp, rsp
    sub rsp, 32
    movsd [rbp-8], xmm0
    movsd [rbp-16], xmm1
    movsd xmm0, [rbp-8]
    addsd xmm0, [rbp-16]
    movsd [rbp-24], xmm0
    movsd xmm0, [rbp-24]
    leave
    ret
          
Current calculator valuesUpdates when you change an input above.
              
            
MATLAB
            function result = graph_modularity_excess_solve_a(c, b)
    result = (c + b);
end
          
Current calculator valuesUpdates when you change an input above.
              
            
Wolfram Language
            ClearAll[mwCalculate];
mwCalculate[c_, b_] := (c + b);
          
Current calculator valuesUpdates when you change an input above.
              
            

Continue in mathematical software

The downloaded file includes your current inputs and first calculated result. It is created locally.

Floating-point answers can differ slightly by language, compiler and processor. Compare within a suitable tolerance rather than assuming every decimal representation will be identical.

Reuse the page responsiblyCite this pageAPA, MLA, Chicago, Harvard, BibTeX and RIS

These formats cite this calculator page itself. They are separate from the academic references above, which support the mathematical method and terminology.

APA 7

MW SysArc. (2026, July 21). Graph Community Modularity Excess observed within-community edge fraction Solver. MW SysArc Tools. https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver

MLA 9

MW SysArc. “Graph Community Modularity Excess observed within-community edge fraction Solver.” MW SysArc Tools, 21 July 2026, https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver. Accessed 31 Aug. 2026.

Chicago 17

MW SysArc. “Graph Community Modularity Excess observed within-community edge fraction Solver.” MW SysArc Tools. Published July 21, 2026. Accessed August 31, 2026. https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver.

Harvard

MW SysArc (2026) ‘Graph Community Modularity Excess observed within-community edge fraction Solver’, MW SysArc Tools. Published 21 July 2026. Available at: https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver (Accessed: 31 August 2026).

BibTeX and RIS records

BibTeX

@misc{mwsysarc_graph_modularity_excess_solve_a_2026,
  author = {{MW SysArc}},
  title = {Graph Community Modularity Excess observed within-community edge fraction Solver},
  howpublished = {MW SysArc Tools},
  year = {2026},
  url = {https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver},
  note = {Published July 21, 2026; accessed August 31, 2026}
}

RIS

TY  - ELEC
AU  - MW SysArc
TI  - Graph Community Modularity Excess observed within-community edge fraction Solver
T2  - MW SysArc Tools
PY  - 2026
DA  - 2026-07-21
Y2  - 2026-08-31
UR  - https://math.mwsysarc.com/discrete-mathematics/graph-modularity-excess-observed-within-community-edge-fraction-solver
N1  - Published July 21, 2026
ER  -

Clear answers

Frequently asked questions

What does the Graph Community Modularity Excess: solve observed within-community edge fraction do?

Rearrange the graph community modularity excess relationship and solve for observed within-community edge fraction.

How does the Graph Community Modularity Excess: solve observed within-community edge fraction work?

The calculator applies a=c+b. A modularity contribution is observed within-community edge fraction minus its null-model expectation. This page isolates observed within-community edge fraction and verifies it in the original relationship.

What can I learn from the Graph Community Modularity Excess: solve observed within-community edge fraction?

It connects the mathematical rule to your chosen numbers and shows each calculation step. Change one input at a time to see how the result responds.

Does MW SysArc receive or store what I enter?

No. The calculation runs locally in your browser. MW SysArc does not receive or store your calculation inputs.

How should I use the result?

Use the steps to understand the method, then verify important school or professional work using the notation and rounding rules required in your setting.

Last reviewed . Calculations tested .

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