"""This module contains simple helper functions """

from __future__ import print_function
import torch
import numpy as np
from PIL import Image
import os


def compute_psnr(img1, img2, max_pixel_value=255.):
    """ Image Peak Signal to Noise Ratio
        Reference: https://dsp.stackexchange.com/questions/38065/peak-signal-to-noise-ratio-psnr-in-python-for-an-image
    """

    mse = torch.mean( (img1 - img2) ** 2)
    if mse:
        psnr = 10. * torch.log10((max_pixel_value**2)/mse)

        return psnr.item()
    else:
        return 1000.


def tensor2im(input_image, imtype=np.uint8):
    """"Converts a Tensor array into a numpy image array.

    Parameters:
        input_image (tensor) --  the input image tensor array of shape (1, 3/1, h, w)
        imtype (type)        --  the desired type of the converted numpy array
    """
    if not isinstance(input_image, np.ndarray):
        if isinstance(input_image, torch.Tensor):  # get the data from a variable
            image_tensor = input_image.data
        else:
            return input_image
        image_numpy = image_tensor[0].cpu().float().numpy()  # convert it into a numpy array

        if image_numpy.shape[0] == 1:  # grayscale to RGB
            image_numpy = np.tile(image_numpy, (3, 1, 1))
        image_numpy = (np.transpose(image_numpy, (1, 2, 0)) * 255.0)  # post-processing: transpose and scaling
    else:  # if it is a numpy array, do nothing
        image_numpy = input_image
    return image_numpy.astype(imtype)


def save_image(image_numpy, image_path, aspect_ratio=1.0):
    """Save a numpy image to the disk

    Parameters:
        image_numpy (numpy array) -- input numpy array
        image_path (str)          -- the path of the image
    """

    image_pil = Image.fromarray(image_numpy)
    h, w, _ = image_numpy.shape

    if aspect_ratio > 1.0:
        image_pil = image_pil.resize((h, int(w * aspect_ratio)), Image.BICUBIC)
    if aspect_ratio < 1.0:
        image_pil = image_pil.resize((int(h / aspect_ratio), w), Image.BICUBIC)
    image_pil.save(image_path)



def mkdirs(paths):
    """create empty directories if they don't exist

    Parameters:
        paths (str list) -- a list of directory paths
    """
    if isinstance(paths, list) and not isinstance(paths, str):
        for path in paths:
            mkdir(path)
    else:
        mkdir(paths)


def mkdir(path):
    """create a single empty directory if it didn't exist

    Parameters:
        path (str) -- a single directory path
    """
    if not os.path.exists(path):
        os.makedirs(path)
