#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Author : Lancelot PINCET
# GitHub : https://github.com/LancelotPincet
# %% Libraries
from arrlp import vol_correlate
import numpy as np
try :
import cupy as cp
except ImportError :
cp = None
# %% Function
[docs]
def vol_convolve(array, *, kernel, out=None, # Arrays
stacks=False, channels=False, parallel=False, cuda=False, test=False, iterator=range, # Modes
**kwargs) :
xp = cp if cuda and cp is not None else np
for dim in range(3) :
kernel = xp.flip(kernel, axis=dim)
return vol_correlate(array, kernel=kernel, out=out, stacks=stacks, channels=channels, parallel=parallel, cuda=cuda, test=test, iterator=iterator, **kwargs)
vol_convolve.ndims = 3
if __name__ == '__main__' :
from arrlp import debug_array
from arrlp import kernel
func = vol_convolve
# Arguments
kwargs = dict(
kernel=kernel(ndims=3, sigma=3),
)
# Modes
modes = { # list of dicts with kwargs
"Reference": dict(cuda=False, parallel=False),
"Parallel": dict(cuda=False, parallel=True),
"Cuda": dict(cuda=True, parallel=False),
}
debug_array(func, modes, **kwargs)