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Multivariable Calculus Visualizer

Visualize partial derivatives, gradient vectors, and double integrals on 3D surfaces with interactive cross-sections.

Tested tool guide Tested browser tools Checked August 16, 2026

What Multivariable Calculus Visualizer does, with a checked example

A typed two-variable function becomes a surface z = f(x,y), with movable slices that isolate change in the x or y direction. At a selected point, the visualizer relates those cross-section slopes to the partial derivatives and gradient, and it can show a double integral over chosen bounds. The common surprise is that the gradient belongs to the x-y input plane: it points toward the fastest increase of f, while the surface is drawn in three dimensions. A double integral is signed, so regions below z = 0 subtract rather than add geometric volume.

Worked example

A concrete input and expected output from the current implementation.

Input

f(x,y) = x^2 + 2y; point = (1,3)

Expected output

Surface height: 7; df/dx = 2; df/dy = 2; gradient = (2, 2).

At (1,3), the function value is 1^2 + 2(3) = 7. Since df/dx = 2x and df/dy = 2, their values at that point are 2 and 2, which form the gradient (2, 2).

How the result is produced

1

Cross-sections and local change

Fixing y and varying x traces an x-direction curve through the surface; its local slope is df/dx. Fixing x and varying y gives df/dy. The gradient combines those values as (df/dx, df/dy) at the selected input. Its direction is steepest ascent under the ordinary Euclidean coordinate scale, and its magnitude is the maximum directional derivative there.

2

Integral region

Lower and upper bounds for x and y identify the region used by the double-integral view. Surface heights over that region are accumulated with their signs: positive heights contribute positively and negative heights contribute negatively. For a continuous function on a rectangular region, changing the order of integration does not change the final value, although the nested setup and cross-sections differ.

Good uses

  • Checking how the x-slice and y-slice through a point produce two different partial-derivative slopes.
  • Seeing whether a critical point suggested by a zero gradient resembles a minimum, maximum, or saddle on the surrounding surface.
  • Connecting an iterated integral over bounded x and y intervals with the signed accumulation shown beneath a 3D graph.

Limits and checks

  • A gradient arrow is not the surface normal. For z = f(x,y), one normal to the graph is (-df/dx, -df/dy, 1).
  • Apparent steepness depends on the plotted axis scales and camera angle. Read the calculated derivatives rather than estimating slope solely from perspective.
  • A double integral represents geometric volume only when the integrand is nonnegative throughout the region; otherwise positive and negative contributions can cancel.

Common questions

Does a zero gradient prove that the point is a maximum or minimum?

No. A zero gradient identifies a critical point when the relevant partial derivatives exist, but it does not classify that point. The surface may have a local minimum, local maximum, saddle, or another inconclusive shape there. Inspect the surrounding graph and use additional analysis, such as second derivatives or directional behavior, before assigning a classification.

Why can a larger integration region produce a smaller result?

The displayed integral is signed accumulation, not necessarily unsigned volume. Enlarging the bounds may include surface values below z = 0, whose negative contributions reduce the total. Cancellation can therefore make a larger region yield a smaller value, zero, or a negative value. If actual geometric volume is needed, verify that the function stays nonnegative or integrate its absolute value where appropriate.

References and verification

The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.

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