Examples

Additional Examples

For more examples and benchmarks, check out the examples directory in the repository.

Basic Interpolation

Single Array Interpolation

from cudakima import AkimaInterpolant1D
import numpy as np

# Simple single array interpolation
x = np.array([1, 2, 3, 4, 5])
y = np.array([1, 4, 9, 16, 25])

interpolant = AkimaInterpolant1D()
x_new = np.linspace(1, 5, 50)
y_new = interpolant(x_new, x, y)

Batch Interpolation with Different Lengths

from cudakima import AkimaInterpolant1D
import numpy as np

# Batch interpolation with NaN padding
x = np.array([
    [1, 2, 3, 4, 5, np.nan, np.nan],
    [1, 2, 3, 4, 5, 6, np.nan],
    [1, 2, 3, 4, 5, 6, 7]
])
y = np.array([
    [1, 4, 9, 16, 25, np.nan, np.nan],
    [1, 4, 9, 16, 25, 36, np.nan],
    [1, 4, 9, 16, 25, 36, 49]
])

interpolant = AkimaInterpolant1D()
x_new = np.linspace(1, 5, 100)
y_new = interpolant(x_new, x, y)  # Shape: (3, 100)

Advanced Usage

Linear Interpolation

from cudakima import AkimaInterpolant1D

# Use linear interpolation instead of cubic
interpolant = AkimaInterpolant1D(order='linear')
y_new = interpolant(x_new, x, y)

CPU-Only Mode

from cudakima import AkimaInterpolant1D

# Force CPU execution (useful for debugging or when GPU is unavailable)
interpolant = AkimaInterpolant1D(use_gpu=False)
y_new = interpolant(x_new, x, y)

Multidimensional x_new

from cudakima import AkimaInterpolant1DMultiDim
import numpy as np

# Different interpolation points for each group
x = np.random.rand(2, 3, 10)  # 2x3 batch, 10 points each
y = np.sin(x)
x_new = np.random.rand(2, 3, 50)  # 2x3 batch, 50 interp points each

interpolant = AkimaInterpolant1DMultiDim()
y_new = interpolant(x_new, x, y)  # Shape: (2, 3, 50)

Flexible Interpolator

from cudakima import AkimaInterpolant1DFlexible

# Automatically chooses between standard and multidimensional modes
interpolant = AkimaInterpolant1DFlexible()

# Standard mode (1D x_new)
y_new_standard = interpolant(x_new_1d, x, y)

# Multidimensional mode (matching batch dims)
y_new_multidim = interpolant(x_new_multidim, x, y)

Performance Tips

Presorting: If your input data is already sorted, set sanitize=False to skip sorting:
```
interpolant = AkimaInterpolant1D(sanitize=False)
```
Batch Size: For optimal GPU performance, use larger batch sizes (more groups to interpolate).
Thread Configuration: Adjust threadsperblock for your GPU (default is 64):
```
interpolant = AkimaInterpolant1D(threadsperblock=128)
```
GPU Memory: For very large datasets, consider processing in chunks to avoid out-of-memory errors.