InterpolatePy

InterpolatePy is a trajectory-planning and interpolation library for robotics, animation, and scientific computing. It includes scalar splines, B-spline curve tools, bounded motion profiles, quaternion interpolation, and 3D path utilities.

The package has a NumPy/SciPy implementation and an optional C++20 backend. Use the public names exported by interpolatepy; they select the available backend at import time.

Installation

python -m pip install InterpolatePy

InterpolatePy 3.3.1 requires Python 3.11 or newer, NumPy 1.26 or newer, and SciPy 1.11 or newer. Install plotting support when needed:

python -m pip install "InterpolatePy[plot]"

Quick start

import numpy as np

from interpolatepy import CubicSpline
from interpolatepy import DoubleSTrajectory
from interpolatepy import StateParams
from interpolatepy import TrajectoryBounds

# A clamped cubic spline: v0 and vn are endpoint velocities.
spline = CubicSpline(
    [0.0, 1.0, 2.0, 3.0],
    [0.0, 1.5, -0.5, 2.0],
    v0=0.0,
    vn=0.0,
)
times = np.linspace(0.0, 3.0, 100)
positions = spline.evaluate(times)
velocities = spline.evaluate_velocity(times)

# A jerk-limited Double-S motion profile.
state = StateParams(q_0=0.0, q_1=10.0, v_0=0.0, v_1=0.0)
bounds = TrajectoryBounds(v_bound=5.0, a_bound=10.0, j_bound=30.0)
motion = DoubleSTrajectory(state, bounds)
sample_times = np.linspace(0.0, motion.get_duration(), 100)
q, qd, qdd, qddd = motion.evaluate_full(sample_times)

DoubleSTrajectory.evaluate() returns position only. Use evaluate_velocity(), evaluate_acceleration(), and evaluate_jerk() for one component, or evaluate_full() for all four.

What is included

Area	Public APIs	Typical use
Scalar splines	CubicSpline, CubicSmoothingSpline, CubicSplineWithAcceleration1, CubicSplineWithAcceleration2	Smooth scalar waypoint trajectories and noisy data
B-splines	BSpline, BSplineInterpolator, CubicBSplineInterpolation, ApproximationBSpline, SmoothingCubicBSpline	Parametric curves, interpolation, approximation, and smoothing
Motion profiles	DoubleSTrajectory, TrapezoidalTrajectory, PolynomialTrajectory, ParabolicBlendTrajectory	Bounded or boundary-conditioned scalar motion
Rotations	Quaternion, QuaternionSpline, SquadC2, SpringQuaternionInterpolation, ShootingQuaternionInterpolation, LogQuaternionInterpolation, ModifiedLogQuaternionInterpolation	Orientation interpolation without Euler-angle singularities
Paths and utilities	LinearPath, CircularPath, Frenet-frame helpers, linear_traj, solve_tridiagonal	Geometric paths, moving frames, and numerical helpers

Degrees 3, 4, and 5 of BSplineInterpolator, LogQuaternionInterpolation, and ModifiedLogQuaternionInterpolation support as few as two waypoints in version 3.2.0.

See the algorithm selection guide, the full documentation, and the runnable examples.

Optional C++ backend

Platform wheels include the compiled backend. The package falls back to Python automatically when the extension is absent:

import interpolatepy

print(interpolatepy.HAS_CPP)

Set INTERPOLATEPY_NO_CPP=1 before importing the package to force the Python implementation. Installing a published wheel does not need a compiler. Building from a source distribution or source checkout requires CMake 3.21+, a C++20 compiler, and network access for CMake's fetched dependencies; see the installation guide.

Development

This project uses uv:

git clone https://github.com/GiorgioMedico/InterpolatePy.git
cd InterpolatePy
uv sync
uv run pytest
uv run pre-commit run --all-files

Documentation dependencies are in a separate group:

uv sync --group docs
uv run mkdocs serve

Every Python program in examples/ can also be run directly, for example:

uv run python examples/double_s_ex.py

For the complete workflow, see Contributing.

License and citation

InterpolatePy is distributed under the MIT License.

@misc{InterpolatePy,
  author = {Giorgio Medico},
  title  = {InterpolatePy: Trajectory Planning and Interpolation for Python},
  year   = {2026},
  url    = {https://github.com/GiorgioMedico/InterpolatePy}
}