# emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
#
#   See COPYING file distributed along with the NiBabel package for the
#   copyright and license terms.
#
### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ##
from __future__ import division, print_function, absolute_import

from os.path import join as pjoin

import numpy as np

from ..optpkg import optional_package

h5py, have_h5py, setup_module = optional_package('h5py')

from .. import minc2
from ..minc2 import Minc2File, Minc2Image

from nose.tools import (assert_true, assert_equal, assert_false, assert_raises)
from numpy.testing import assert_array_equal, assert_array_almost_equal

from ..testing import data_path

from . import test_minc1 as tm2

# Example images in format expected for ``test_image_api``, adding ``zooms``
# item.
EXAMPLE_IMAGES = [
    dict(
        fname = pjoin(data_path, 'small.mnc'),
        shape = (18, 28, 29),
        dtype = np.int16,
        affine = np.array([[0, 0, 7.0, -98],
                           [0, 8.0, 0, -134],
                           [9.0, 0, 0, -72],
                           [0, 0, 0, 1]]),
        zooms = (9., 8., 7.),
        # These values from mincstats
        data_summary = dict(
            min = 0.1185331417,
            max = 92.87690699,
            mean = 31.2127952),
        is_proxy = True),
    dict(
        fname = pjoin(data_path, 'minc2_1_scale.mnc'),
        shape = (10,20,20),
        dtype = np.uint8,
        affine = np.array([[0, 0, 2.0, -20],
                           [0, 2.0, 0, -20],
                           [2.0, 0, 0, -10],
                           [0, 0, 0, 1]]),
        zooms = (2., 2., 2.),
        # These values from mincstats
        data_summary = dict(
            min = 0.2082842439,
            max = 0.2094327615,
            mean = 0.2091292083),
        is_proxy = True),
    dict(
        fname = pjoin(data_path, 'minc2_4d.mnc'),
        shape = (2, 10,20,20),
        dtype = np.uint8,
        affine = np.array([[0, 0, 2.0, -20],
                           [0, 2.0, 0, -20],
                           [2.0, 0, 0, -10],
                           [0, 0, 0, 1]]),
        zooms = (1., 2., 2., 2.),
        # These values from mincstats
        data_summary = dict(
            min = 0.2078431373,
            max = 1.498039216,
            mean = 0.9090422837),
        is_proxy = True)
]

if have_h5py:
    class TestMinc2File(tm2._TestMincFile):
        module = minc2
        file_class = Minc2File
        opener = h5py.File
        test_files = EXAMPLE_IMAGES

    class TestMinc2Image(tm2.TestMinc1Image):
        image_class = Minc2Image
        eg_images = (pjoin(data_path, 'small.mnc'),)
        module = minc2