File: conftest.py

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"""``pytest`` fixtures."""

import functools
import operator
import os
import shutil
import sys
import uuid
import zipfile

import affine
import boto3
import numpy as np
import pytest
from click.testing import CliRunner

import rasterio
import rasterio.env
from rasterio.coords import BoundingBox
from rasterio.crs import CRS
from rasterio.enums import ColorInterp
from rasterio.env import GDALVersion
from affine import Affine

DEFAULT_SHAPE = (10, 10)


reduce = functools.reduce

try:
    have_credentials = boto3.Session().get_credentials()
except Exception:
    have_credentials = False

credentials = pytest.mark.skipif(
    not(have_credentials),
    reason="S3 raster access requires credentials")


test_files = [os.path.join(os.path.dirname(__file__), p) for p in [
    'data/RGB.byte.tif', 'data/float.tif', 'data/float32.tif',
    'data/float_nan.tif', 'data/shade.tif', 'data/RGBA.byte.tif']]


def pytest_cmdline_main(config):
    # Bail if the test raster data is not present. Test data is not
    # distributed with sdists since 0.12.
    if reduce(operator.and_, map(os.path.exists, test_files)):
        print("Test data present.")
    else:
        print("Test data not present. See download directions in "
              "tests/data/README.rst")
        sys.exit(1)


@pytest.fixture(scope='function')
def runner():
    return CliRunner()


@pytest.fixture(scope='function')
def data(tmpdir):
    """A temporary directory containing a copy of the files in data."""
    for filename in test_files:
        shutil.copy(filename, str(tmpdir))
    return tmpdir


@pytest.fixture(scope='function')
def red_green(tmpdir):
    """A temporary directory containing copies of red.tif, green.tif."""
    for filename in ['tests/data/red.tif', 'tests/data/red.tif.ovr', 'tests/data/green.tif', 'tests/data/green.tif.ovr']:
        shutil.copy(filename, str(tmpdir))
    return tmpdir


@pytest.fixture
def basic_geometry():
    """A Polygon with 2D coordinates.

    Returns
    -------
    dict : GeoJSON-style geometry object.
        Coordinates are in grid coordinates (Affine.identity()).

    """
    return {
        'type': 'Polygon',
        'coordinates': [[(2, 2), (2, 4.25), (4.25, 4.25), (4.25, 2), (2, 2)]]
    }


@pytest.fixture
def basic_geometry_3d():
    """A Polygon with 3D coordinates.

    Returns
    -------
    dict : GeoJSON-style geometry object.
        Coordinates are in grid coordinates (Affine.identity()).

    """
    return {
        "type": "Polygon",
        "coordinates": [
            [(2, 2, 0), (2, 4.25, 0), (4.25, 4.25, 0), (4.25, 2, 0), (2, 2, 0)]
        ],
    }


@pytest.fixture
def rotation_geometry():
    """A rotated geometry.

    Returns
    -------
    dict : GeoJSON-style geometry object.
        Coordinates are in grid coordinates (Affine.identity()).

    """
    return {
        'type': 'Polygon',
        'coordinates': [[(481070, 4481140), (481040, 4481160),
                         (481035, 4481130), (481060, 4481125),
                         (481070, 4481140)]]
    }


@pytest.fixture
def geojson_point():
    """A 2D Point.

    Returns
    -------
    dict : GeoJSON-style Point geometry object.
        Coordinates are in grid coordinates (Affine.identity()).

    """
    return {"type": "Point", "coordinates": (2, 2)}


@pytest.fixture
def geojson_multipoint():
    """
    Returns
    -------

    dict: GeoJSON-style MultiPoint geometry object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'type': 'MultiPoint',
        'coordinates': ((2, 2), (4, 4))
    }


@pytest.fixture
def geojson_line():
    """
    Returns
    -------

    dict: GeoJSON-style LineString geometry object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'type': 'LineString',
        'coordinates': ((2, 2), (4, 4))
    }


@pytest.fixture
def geojson_multiline():
    """
    Returns
    -------

    dict: GeoJSON-style MultiLineString geometry object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'type': 'MultiLineString',
        'coordinates': (((2, 2), (4, 4)), ((0, 0), (4, 0)))
    }


@pytest.fixture
def geojson_polygon(basic_geometry):
    """
    Returns
    -------

    dict: GeoJSON-style Polygon geometry object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return basic_geometry


@pytest.fixture
def geojson_multipolygon():
    """
    Returns
    -------

    dict: GeoJSON-style MultiPolygon geometry object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'type': 'MultiPolygon',
        'coordinates': (
            (((2, 2), (2, 4), (4, 4), (4, 2), (2, 2)), ),
            (((0, 0), (0, 1), (1, 1), (1, 0), (0, 0)), )
        )
    }


@pytest.fixture
def geojson_geomcollection():
    """
    Returns
    -------

    dict: GeoJSON-style GeometryCollection object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'type': 'GeometryCollection',
        'geometries': (
            {
                'type': 'Polygon',
                'coordinates': (((2, 2), (2, 4), (4, 4), (4, 2), (2, 2)), )
            },
            {
                'type': 'Polygon',
                'coordinates': (((0, 0), (0, 1), (1, 1), (1, 0), (0, 0)), )
            }
        )
    }


@pytest.fixture
def basic_feature(basic_geometry):
    """
    Returns
    -------

    dict: GeoJSON object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'geometry': basic_geometry,
        'properties': {
            'val': 15
        },
        'type': 'Feature'
    }


@pytest.fixture
def basic_featurecollection(basic_feature):
    """
    Returns
    -------

    dict: GeoJSON FeatureCollection object.
        Coordinates are in grid coordinates (Affine.identity()).
    """

    return {
        'features': [basic_feature],
        'type': 'FeatureCollection'
    }


@pytest.fixture
def basic_image():
    """
    A basic 10x10 array for testing sieve and shapes functions.
    Contains a square feature 3x3 (size 9).
    Equivalent to results of rasterizing basic_geometry with all_touched=True.

    Returns
    -------

    np ndarray
    """

    image = np.zeros(DEFAULT_SHAPE, dtype=np.uint8)
    image[2:5, 2:5] = 1

    return image


@pytest.fixture
def basic_image_2x2():
    """
    A basic 10x10 array for testing sieve and shapes functions.
    Contains a square feature 2x2 (size 4).
    Equivalent to results of rasterizing basic_geometry with all_touched=False.

    Returns
    -------

    np ndarray
    """

    image = np.zeros(DEFAULT_SHAPE, dtype=np.uint8)
    image[2:4, 2:4] = 1

    return image


@pytest.fixture
def basic_image_2x2x2():
    """
    A basic 10x10 array for testing sieve and shapes functions.
    Contains a square feature 2x2 (size 4).
    Equivalent to results of rasterizing two times the basic_geometry with
    merge_alg='add'.

    Returns
    -------

    np ndarray
    """

    image = np.zeros(DEFAULT_SHAPE, dtype=np.uint8)
    image[2:4, 2:4] = 2

    return image


@pytest.fixture
def pixelated_image(basic_image):
    """
    A basic 10x10 array for testing sieve functions.  Contains a square feature
    3x3 (size 9), with 2 isolated pixels.

    Returns
    -------

    np ndarray
    """

    image = basic_image.copy()
    image[0, 0] = 1
    image[8, 8] = 1

    return image


@pytest.fixture
def diagonal_image():
    """
    A 10x10 array for testing sieve functions, with only one diagonal filled.

    Returns
    -------

    np ndarray
    """

    image = np.zeros(DEFAULT_SHAPE, dtype=np.uint8)
    np.fill_diagonal(image, 1)
    return image


@pytest.fixture()
def basic_image_file(tmpdir, basic_image):
    """
    A basic raster file with a 10x10 array for testing sieve functions.
    Contains data from pixelated_image.

    Returns
    -------

    string
        Filename of test raster file
    """
    image = basic_image

    outfilename = str(tmpdir.join('basic_image.tif'))
    kwargs = {
        "crs": CRS({'init': 'epsg:4326'}),
        "transform": Affine.identity(),
        "count": 1,
        "dtype": rasterio.uint8,
        "driver": "GTiff",
        "width": image.shape[1],
        "height": image.shape[0],
        "nodata": None
    }
    with rasterio.open(outfilename, 'w', **kwargs) as out:
        out.write(image, indexes=1)

    return outfilename


@pytest.fixture()
def pixelated_image_file(tmpdir, pixelated_image):
    """
    A basic raster file with a 10x10 array for testing sieve functions.
    Contains data from pixelated_image.

    Returns
    -------

    string
        Filename of test raster file
    """
    image = pixelated_image

    outfilename = str(tmpdir.join('pixelated_image.tif'))
    kwargs = {
        "crs": CRS({'init': 'epsg:4326'}),
        "transform": Affine.identity(),
        "count": 1,
        "dtype": rasterio.uint8,
        "driver": "GTiff",
        "width": image.shape[1],
        "height": image.shape[0],
        "nodata": 255
    }
    with rasterio.open(outfilename, 'w', **kwargs) as out:
        out.write(image, indexes=1)

    return outfilename


@pytest.fixture()
def rotated_image_file(tmpdir, pixelated_image):
    """
    A basic raster file with a 1000x2000 array for testing sieve functions.
    Contains only one value: 128.

    Returns
    -------

    string
        Filename of test raster file
    """
    image = 128 * np.ones((1000, 2000), dtype=np.uint8)

    rotated_transform = Affine(-0.05, 0.07, 481060,
                               0.07, 0.05, 4481030)

    outfilename = str(tmpdir.join('rotated_image.tif'))
    kwargs = {
        "crs": CRS({'init': 'epsg:32613'}),
        "transform": rotated_transform,
        "count": 1,
        "dtype": rasterio.uint8,
        "driver": "GTiff",
        "width": image.shape[1],
        "height": image.shape[0],
        "nodata": 255,
        "compress": "lzw"
    }
    with rasterio.open(outfilename, 'w', **kwargs) as out:
        out.write(image, indexes=1)

    return outfilename


@pytest.fixture()
def image_file_with_custom_size_and_transform(tmpdir):
    """
    A basic raster file with a 10x10 array containing a
    caller supplied transform.

    Returns
    -------

    string
        Filename of test raster file
    """
    def inner(width, height, transform):
        image = np.zeros((height, width))

        outfilename = str(tmpdir.join('basic_image.tif'))
        kwargs = {
            "crs": CRS({'init': 'epsg:4326'}),
            "transform": transform,
            "count": 1,
            "dtype": rasterio.uint8,
            "driver": "GTiff",
            "width": image.shape[1],
            "height": image.shape[0],
            "nodata": None
        }
        with rasterio.open(outfilename, 'w', **kwargs) as out:
            out.write(image, indexes=1)

        return outfilename

    return inner


@pytest.fixture(scope='function')
def gdalenv(request):
    def fin():
        if rasterio.env.local._env:
            rasterio.env.delenv()
            rasterio.env.local._env = None

    request.addfinalizer(fin)


@pytest.fixture(scope='session')
def data_dir():
    """Absolute file path to the directory containing test datasets."""
    root = os.path.join(os.path.dirname(__file__), '..')
    return os.path.abspath(os.path.join(root, 'tests', 'data'))


@pytest.fixture(scope='session')
def path_rgb_byte_tif(data_dir):
    """The original RGB test fixture with no sidecar files"""
    return os.path.join(data_dir, 'RGB.byte.tif')


@pytest.fixture(scope='session')
def path_srtm_hgt(data_dir):
    """Sample SRTM HGT file"""
    return os.path.join(data_dir, 'N10W110.hgt.zip')


@pytest.fixture(scope='session')
def path_rgb_lzw_byte_tif(data_dir):
    """The original RGB test fixture with LZW compression."""
    return os.path.join(data_dir, 'rgb_lzw.tif')


@pytest.fixture(scope='session')
def path_rgb_byte_rpc_vrt(data_dir):
    return os.path.join(data_dir, 'RGB.byte.rpc.vrt')


@pytest.fixture(scope='session')
def path_rgba_byte_tif(data_dir):
    """Derived from RGB.byte.tif, this has an alpha band"""
    return os.path.join(data_dir, 'RGBA.byte.tif')


@pytest.fixture(scope='session')
def path_rgb_msk_byte_tif(data_dir):
    """Derived from RGB.byte.tif, this has an external mask"""
    return os.path.join(data_dir, 'RGB2.byte.tif')


@pytest.fixture(scope='session')
def path_cogeo_tif(data_dir):
    return os.path.join(data_dir, 'cogeo.tif')


@pytest.fixture(scope='session')
def path_white_gemini_iv_vrt(data_dir):
    return os.path.join(data_dir, 'white-gemini-iv.vrt')


@pytest.fixture(scope='function')
def _path_multiband_no_colorinterp(tmpdir):

    """Produces a function for generating an image with ``count`` bands
    and undefined color interpretation.  May trigger a PAM file depending on
    the GDAL version.

    Returns
    -------
    function
    """

    def _create_path_multiband_no_colorinterp(count):
        # For GDAL 2.2.2 the first band can be 'undefined', but on older
        # versions it must be 'gray'.
        undefined_ci = [ColorInterp.gray]
        if count > 1:
            undefined_ci += [ColorInterp.undefined] * (count - 1)
        dst_path = str(tmpdir.join('4band-byte-no-ci.tif'))
        profile = {
            'height': 10,
            'width': 10,
            'count': count,
            'dtype': rasterio.ubyte,
            'transform': affine.Affine(1, 0.0, 0,
                                       0.0, -1, 1),
            'driver': 'GTiff',
            'photometric': 'minisblack'
        }

        undefined_ci = tuple(undefined_ci)
        with rasterio.open(dst_path, 'w', **profile) as src:
            src.colorinterp = undefined_ci

        # Ensure override occurred.  Setting color interpretation on an
        # existing file is surrounded by traps and forceful GDAL assumptions,
        # especially on older versions.
        with rasterio.open(dst_path) as src:
            if src.colorinterp != undefined_ci:
                raise ValueError(
                    "Didn't properly set color interpretation.  GDAL can "
                    "forcefully make assumptions.")

        return dst_path

    return _create_path_multiband_no_colorinterp


@pytest.fixture(scope='function')
def path_3band_no_colorinterp(_path_multiband_no_colorinterp):
    """A 3 band image with undefined color interpretation."""
    return _path_multiband_no_colorinterp(3)


@pytest.fixture(scope='function')
def path_4band_no_colorinterp(_path_multiband_no_colorinterp):
    """A 4 band image with undefined color interpretation."""
    return _path_multiband_no_colorinterp(4)


@pytest.fixture(scope='session')
def path_float_tif(data_dir):
    return os.path.join(data_dir, 'float.tif')


@pytest.fixture(scope='session')
def path_alpha_tif(data_dir):
    return os.path.join(data_dir, 'alpha.tif')


@pytest.fixture(scope='session')
def path_zip_file(data_dir):
    """Creates ``coutwildrnp.zip`` if it does not exist and returns
    the absolute file path."""
    path = f"{data_dir}/white-gemini-iv.zip"
    if not os.path.exists(path):
        with zipfile.ZipFile(path, 'w') as zip:
            for filename in ['white-gemini-iv.vrt',
                             '389225main_sw_1965_1024.jpg']:
                zip.write(os.path.join(data_dir, filename), filename)
    return path


@pytest.fixture(autouse=True)
def set_mem_name(request, monkeypatch):
    def youyoueyedeefour():
        return f"{request.node.name}-{uuid.uuid4()}"
    monkeypatch.setattr(rasterio._io, "uuid4", youyoueyedeefour)


class MockGeoInterface:
    """Tiny wrapper for GeoJSON to present an object with __geo_interface__ for testing"""
    def __init__(self, geojson):
        self.__geo_interface__ = geojson


# Define helpers to skip tests based on GDAL version
gdal_version = GDALVersion.runtime()

requires_gdal37 = pytest.mark.skipif(
    not gdal_version.at_least('3.7'), reason="Requires GDAL 3.7.x"
)

requires_gdal_lt_37 = pytest.mark.skipif(
    gdal_version.at_least('3.7'), reason="Requires GDAL before 3.7"
)


def assert_bounding_box_equal(expected, actual, tolerance=1e-4):
    if isinstance(expected, tuple):
        expected = BoundingBox(*expected)
    if isinstance(actual, tuple):
        actual = BoundingBox(*actual)

    left = abs(expected.left - actual.left)
    bottom = abs(expected.bottom - actual.bottom)
    right = abs(expected.right - actual.right)
    top = abs(expected.top - actual.top)

    assert all(diff < tolerance for diff in [left, bottom, right, top]), f"{expected} differs from {actual}"