Numerical differentiation calculator

Calculate five-point derivative estimate and estimate with half the step with your own figures.

Your numbers

Use the units shown. Results update as you change valid inputs.

Use five-point derivative estimate and estimate with half the step to compare changes to your inputs. The method and limits below explain the scope.

Examples

Examples

Try the starting example

Restricted real expression f(x)
x^3
Evaluation point x
2
Positive central-difference step
0.1
Five-point derivative estimate
12
Estimate with half the step
12
Absolute step-halving discrepancy
0

Try another scenario

Restricted real expression f(x)
sin(x)
Evaluation point x
0
Positive central-difference step
0.5
Five-point derivative estimate
0.997978
Estimate with half the step
0.999871
Absolute step-halving discrepancy
0.001893
Calculation method

Calculation method

Five-point derivative estimate

[f(x−2h)−8f(x−h)+8f(x+h)−f(x+2h)]/(12h).

Estimate with half the step

Repeat the same five-point stencil with h/2.

Absolute step-halving discrepancy

Absolute difference between the two estimates; not a certified derivative error.

Symbols and units
a
Restricted real expression f(x)
b
Evaluation point x
c
Positive central-difference step

Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.

Assumptions & limits

Assumptions & limits

  • A fourth-order central stencil for sufficiently smooth real functions. Every sampled point must be in the finite real domain; excessively small steps can amplify roundoff. Restricted expressions allow x (and y for ODEs), pi, e, + - * / ^, and sin, cos, tan, sec, csc, cot, exp, log, sqrt, abs, sinh, cosh, tanh, sech, csch, coth. Trigonometric arguments are in radians. Double-precision results are approximate. Numeric tables use 12 significant digits and display components at roundoff scale (32 machine epsilons relative to their row or relevant calculation scale) as zero; scalar diagnostics retain full precision.
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Further reading

SciPy: numerical integration and ODE method references ↗

Background reading; this does not imply endorsement or independent review of SumFizz.

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