#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Author : Lancelot PINCET
# GitHub : https://github.com/LancelotPincet
# %% Libraries
from arrlp import vol_correlate1d
import numpy as np
try :
import cupy as cp
except ImportError :
cp = None
# %% Function
[docs]
def vol_convolve1d(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
kernel = [xp.flip(k, axis=0) for k in kernel]
return vol_correlate1d(array, kernel=kernel, out=out, stacks=stacks, channels=channels, parallel=parallel, cuda=cuda, test=test, iterator=iterator, **kwargs)
vol_convolve1d.ndims = 3
if __name__ == '__main__' :
from arrlp import debug_array
from arrlp import kernel
func = vol_convolve1d
# Arguments
kwargs = dict(
kernel=(kernel(ndims=1, pixel=1, sigma=2), kernel(ndims=1, pixel=1, sigma=3), kernel(ndims=1, pixel=1, 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)