#!/usr/bin/env python
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"""
Module for reconstruction algorithms.
"""

from __future__ import (absolute_import, division, print_function,
                        unicode_literals)

import six
import numpy as np
import tomopy.util.mproc as mproc
import tomopy.util.extern as extern
import tomopy.util.dtype as dtype
from tomopy.sim.project import get_center
from tomopy.recon.algorithm import init_tomo
import math
import logging
import concurrent.futures as cf

logger = logging.getLogger(__name__)


__author__ = "Doga Gursoy"
__copyright__ = "Copyright (c) 2015, UChicago Argonne, LLC."
__docformat__ = 'restructuredtext en'
__all__ = ['vector', 'vector2', 'vector3']


def vector(tomo, theta, center=None, num_iter=1, axis=0):
    tomo = dtype.as_float32(tomo)
    theta = dtype.as_float32(theta)

    # Initialize tomography data.
    tomo = init_tomo(tomo, sinogram_order=False, sharedmem=False)

    recon_shape = (tomo.shape[0], tomo.shape[2], tomo.shape[2])
    recon = np.zeros(recon_shape, dtype=np.float32)

    center_arr = get_center(tomo.shape, center)

    extern.c_vector(tomo, center_arr, recon, theta, 
        num_gridx=tomo.shape[2], num_gridy=tomo.shape[2], num_iter=num_iter, axis=axis)
    return recon


def vector2(tomo1, tomo2, theta1, theta2, center1=None, center2=None, num_iter=1, axis1=1, axis2=2):
    tomo1 = dtype.as_float32(tomo1)
    tomo2 = dtype.as_float32(tomo2)
    theta1 = dtype.as_float32(theta1)
    theta2 = dtype.as_float32(theta2)

    # Initialize tomography data.
    tomo1 = init_tomo(tomo1, sinogram_order=False, sharedmem=False)
    tomo2 = init_tomo(tomo2, sinogram_order=False, sharedmem=False)

    recon_shape = (tomo1.shape[0], tomo1.shape[2], tomo1.shape[2])
    recon1 = np.zeros(recon_shape, dtype=np.float32)
    recon2 = np.zeros(recon_shape, dtype=np.float32)
    recon3 = np.zeros(recon_shape, dtype=np.float32)

    center_arr1 = get_center(tomo1.shape, center1)
    center_arr2 = get_center(tomo2.shape, center2)

    extern.c_vector2(tomo1, tomo2, center_arr1, center_arr2, recon1, recon2, recon3, theta1, theta2, 
        num_gridx=tomo1.shape[2], num_gridy=tomo1.shape[2], num_iter=num_iter, axis1=axis1, axis2=axis2)
    return recon1, recon2, recon3


def vector3(tomo1, tomo2, tomo3, theta1, theta2, theta3, center1=None, center2=None, center3=None, num_iter=1, axis1=0, axis2=1, axis3=2):
    tomo1 = dtype.as_float32(tomo1)
    tomo2 = dtype.as_float32(tomo2)
    tomo3 = dtype.as_float32(tomo3)
    theta1 = dtype.as_float32(theta1)
    theta2 = dtype.as_float32(theta2)
    theta3 = dtype.as_float32(theta3)

    # Initialize tomography data.
    tomo1 = init_tomo(tomo1, sinogram_order=False, sharedmem=False)
    tomo2 = init_tomo(tomo2, sinogram_order=False, sharedmem=False)
    tomo3 = init_tomo(tomo3, sinogram_order=False, sharedmem=False)

    recon_shape = (tomo1.shape[0], tomo1.shape[2], tomo1.shape[2])
    recon1 = np.zeros(recon_shape, dtype=np.float32)
    recon2 = np.zeros(recon_shape, dtype=np.float32)
    recon3 = np.zeros(recon_shape, dtype=np.float32)

    center_arr1 = get_center(tomo1.shape, center1)
    center_arr2 = get_center(tomo2.shape, center2)
    center_arr3 = get_center(tomo3.shape, center3)

    extern.c_vector3(tomo1, tomo2, tomo3, center_arr1, center_arr2, center_arr3, recon1, recon2, recon3, theta1, theta2, theta3,  
        num_gridx=tomo1.shape[2], num_gridy=tomo1.shape[2], num_iter=num_iter, axis1=axis1, axis2=axis2, axis3=axis3)
    return recon1, recon2, recon3