Partial Derivative Calculator
Calculate partial derivatives of f(x,y) = axy + bx² + cy² + d. Find df/dx, df/dy, and the gradient magnitude.
About this calculator
This calculator evaluates the partial derivatives of f(x,y) = axy + bx² + cy² + d — the coefficients labeled a, b, c, and d — at a chosen point (x, y), reporting ∂f/∂x, ∂f/∂y, f(x,y) itself, and the gradient magnitude. The two partials are cleanly separated by code, not coincidence: ∂f/∂x is computed as coeffXY * yValue + 2 * coeffX * xValue, a line that never reads Coefficient of y² (c) at all, so c is genuinely inert on ∂f/∂x for any value it holds; symmetrically, ∂f/∂y never reads Coefficient of x² (b).
Coefficient of x² (b) and x Value show an identical measured effect on ∂f/∂x under a small nudge, because only their product, 2 * coeffX * xValue, appears in the formula — scaling either factor by the same percentage moves that product by the same amount, so this calculator does not single out one of the two as dominant. What no sensitivity check here can confirm, even though it's a basic calculus fact: Constant (d) never appears in either partial-derivative formula at all (its whole contribution to f(x,y) has zero slope), but it also defaults to 0, and a nudge probe that scales a value by a fixed percentage of itself can't move an input that starts at zero — so this genuinely true relationship falls outside what the mechanical check can verify.
Inputs
Results
∂f/∂x
5
∂f/∂y
7
How to Use This Calculator
- Enter the coefficients a, b, c, and d of the fixed function f(x,y) = axy + bx² + cy² + d.
- Enter the function parameters and the point (x₀, y₀) at which to evaluate the partial derivatives.
- ∂f/∂x is computed by treating y as a constant and differentiating with respect to x only.
- ∂f/∂y is computed by treating x as a constant and differentiating with respect to y only.
- Together, (∂f/∂x, ∂f/∂y) form the gradient vector ∇f, which the Gradient Calculator can use directly.
- Mixed partial ∂²f/∂x∂y is not displayed as a separate output, but by Clairaut's theorem it equals ∂²f/∂y∂x for this smooth function.
How the result changes with Coefficient of x² (b)
| Coefficient of x² (b) | ∂f/∂x | ∂f/∂y |
|---|---|---|
| 1 | 3 | 7 |
| 1.5 | 4 | 7 |
| 3 | 7 | 7 |
| 5 | 11 | 7 |
What each input means
- Coefficient of xy (a)
- Coefficient of the xy cross-term
- Coefficient of x² (b)
- Coefficient of x²
- Coefficient of y² (c)
- Coefficient of y²
- Constant (d)
- Constant term
- x Value
- Point to evaluate at (x coordinate)
- y Value
- Point to evaluate at (y coordinate)
How this is calculated
Worked example, using the default values
- Identify Input Parameters4 parametersCoefficient of xy (a) = 1, Coefficient of x² (b) = 2, Coefficient of y² (c) = 3, Constant (d) = 0 = 6 input(s) provided
- Calculate ∂f/∂x∂f/∂x5 = 5
- Calculate ∂f/∂y∂f/∂y7 = 7
- Calculate ff6 = 6
- Calculate |∇f||∇f|8.6023 = 8.6023
Engine last updated . Checked against 3 independently-derived tests — how we verify calculators. Built by Paul Gunder, a software engineer, not a licensed financial, medical, or legal professional.
Frequently Asked Questions
Why does Coefficient of y² (c) never change ∂f/∂x?
The formula for ∂f/∂x in the engine, coeffXY * yValue + 2 * coeffX * xValue, simply never references coeffY — it isn't a coincidence of the numbers you enter, it's that the variable doesn't appear in that line of code at all. The same is true in reverse: ∂f/∂y never reads coeffX.
Why do Coefficient of x² (b) and x Value move ∂f/∂x by the same measured amount?
Both only enter the ∂f/∂x formula multiplied together, as 2 * coeffX * xValue — never separately. Scaling either one up or down by a given percentage changes that product by the same proportion, so a small nudge to either input produces an equally sized swing in ∂f/∂x at any given starting point.
Does changing the Constant (d) affect either partial derivative?
No — differentiating a constant always yields zero, and neither the ∂f/∂x nor the ∂f/∂y formula in the engine references constant at all. It only shows up in f(x,y) itself, shifting the function's value up or down without changing its slope in either direction.
What does the Gradient Magnitude, |∇f|, represent?
It's the length of the gradient vector (∂f/∂x, ∂f/∂y), computed as the square root of the sum of both partial derivatives squared. Geometrically, it tells you how steeply f(x,y) is rising at the evaluated point, combining both directions' slopes into one overall steepness value regardless of which direction it points in.
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