#!/usr/bin/python
# Copyright (c) 2018 Satpy developers
#
# This file is part of satpy.
#
# satpy is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
#
# satpy is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE. See the GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License along with
# satpy. If not, see <http://www.gnu.org/licenses/>.
"""Unittests for generic image reader."""
import os
import unittest
import dask.array as da
import numpy as np
import pytest
import xarray as xr
from satpy.tests.utils import RANDOM_GEN, make_dataid
[docs]
class TestGenericImage(unittest.TestCase):
"""Test generic image reader."""
[docs]
def setUp(self):
"""Create temporary images to test on."""
import datetime as dt
import tempfile
from pyresample.geometry import AreaDefinition
from satpy.scene import Scene
self.date = dt.datetime(2018, 1, 1)
# Create area definition
pcs_id = "ETRS89 / LAEA Europe"
proj4_dict = "EPSG:3035"
self.x_size = 100
self.y_size = 100
area_extent = (2426378.0132, 1528101.2618, 6293974.6215, 5446513.5222)
self.area_def = AreaDefinition("geotiff_area", pcs_id, pcs_id,
proj4_dict, self.x_size, self.y_size,
area_extent)
# Create datasets for L, LA, RGB and RGBA mode images
r__ = da.random.randint(0, 256, size=(self.y_size, self.x_size),
chunks=(50, 50)).astype(np.uint8)
g__ = da.random.randint(0, 256, size=(self.y_size, self.x_size),
chunks=(50, 50)).astype(np.uint8)
b__ = da.random.randint(0, 256, size=(self.y_size, self.x_size),
chunks=(50, 50)).astype(np.uint8)
a__ = 255 * np.ones((self.y_size, self.x_size), dtype=np.uint8)
a__[:10, :10] = 0
a__ = da.from_array(a__, chunks=(50, 50))
r_nan__ = RANDOM_GEN.uniform(0., 1., size=(self.y_size, self.x_size))
r_nan__[:10, :10] = np.nan
r_nan__ = da.from_array(r_nan__, chunks=(50, 50))
ds_l = xr.DataArray(da.stack([r__]), dims=("bands", "y", "x"),
attrs={"name": "test_l",
"start_time": self.date})
ds_l["bands"] = ["L"]
ds_la = xr.DataArray(da.stack([r__, a__]), dims=("bands", "y", "x"),
attrs={"name": "test_la",
"start_time": self.date})
ds_la["bands"] = ["L", "A"]
ds_rgb = xr.DataArray(da.stack([r__, g__, b__]),
dims=("bands", "y", "x"),
attrs={"name": "test_rgb",
"start_time": self.date})
ds_rgb["bands"] = ["R", "G", "B"]
ds_rgba = xr.DataArray(da.stack([r__, g__, b__, a__]),
dims=("bands", "y", "x"),
attrs={"name": "test_rgba",
"start_time": self.date})
ds_rgba["bands"] = ["R", "G", "B", "A"]
ds_l_nan = xr.DataArray(da.stack([r_nan__]),
dims=("bands", "y", "x"),
attrs={"name": "test_l_nan",
"start_time": self.date})
ds_l_nan["bands"] = ["L"]
# Temp dir for the saved images
self.base_dir = tempfile.mkdtemp()
# Put the datasets to Scene for easy saving
scn = Scene()
scn["l"] = ds_l
scn["l"].attrs["area"] = self.area_def
scn["la"] = ds_la
scn["la"].attrs["area"] = self.area_def
scn["rgb"] = ds_rgb
scn["rgb"].attrs["area"] = self.area_def
scn["rgba"] = ds_rgba
scn["rgba"].attrs["area"] = self.area_def
scn["l_nan"] = ds_l_nan
scn["l_nan"].attrs["area"] = self.area_def
# Save the images. Two images in PNG and two in GeoTIFF
scn.save_dataset("l", os.path.join(self.base_dir, "test_l.png"), writer="simple_image")
scn.save_dataset("la", os.path.join(self.base_dir, "20180101_0000_test_la.png"), writer="simple_image")
scn.save_dataset("rgb", os.path.join(self.base_dir, "20180101_0000_test_rgb.tif"), writer="geotiff")
scn.save_dataset("rgba", os.path.join(self.base_dir, "test_rgba.tif"), writer="geotiff")
scn.save_dataset("l_nan", os.path.join(self.base_dir, "test_l_nan_fillvalue.tif"),
writer="geotiff", fill_value=0)
scn.save_dataset("l_nan", os.path.join(self.base_dir, "test_l_nan_nofillvalue.tif"),
writer="geotiff")
self.scn = scn
[docs]
def tearDown(self):
"""Remove the temporary directory created for a test."""
try:
import shutil
shutil.rmtree(self.base_dir, ignore_errors=True)
except OSError:
pass
[docs]
def test_png_scene(self):
"""Test reading PNG images via satpy.Scene()."""
from rasterio.errors import NotGeoreferencedWarning
from satpy import Scene
fname = os.path.join(self.base_dir, "test_l.png")
with pytest.warns(NotGeoreferencedWarning, match=r"Dataset has no geotransform"):
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
assert scn["image"].shape == (1, self.y_size, self.x_size)
assert scn.sensor_names == {"images"}
assert scn.start_time is None
assert scn.end_time is None
assert "area" not in scn["image"].attrs
fname = os.path.join(self.base_dir, "20180101_0000_test_la.png")
with pytest.warns(NotGeoreferencedWarning, match=r"Dataset has no geotransform"):
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
data = da.compute(scn["image"].data)
assert scn["image"].shape == (1, self.y_size, self.x_size)
assert scn.sensor_names == {"images"}
assert scn.start_time == self.date
assert scn.end_time == self.date
assert "area" not in scn["image"].attrs
assert np.sum(np.isnan(data)) == 100
[docs]
def test_geotiff_scene(self):
"""Test reading TIFF images via satpy.Scene()."""
from satpy import Scene
fname = os.path.join(self.base_dir, "20180101_0000_test_rgb.tif")
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
assert scn["image"].shape == (3, self.y_size, self.x_size)
assert scn.sensor_names == {"images"}
assert scn.start_time == self.date
assert scn.end_time == self.date
assert scn["image"].area == self.area_def
fname = os.path.join(self.base_dir, "test_rgba.tif")
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
assert scn["image"].shape == (3, self.y_size, self.x_size)
assert scn.sensor_names == {"images"}
assert scn.start_time is None
assert scn.end_time is None
assert scn["image"].area == self.area_def
[docs]
def test_geotiff_scene_nan(self):
"""Test reading TIFF images originally containing NaN values via satpy.Scene()."""
from satpy import Scene
fname = os.path.join(self.base_dir, "test_l_nan_fillvalue.tif")
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
assert scn["image"].shape == (1, self.y_size, self.x_size)
assert np.sum(scn["image"].data[0][:10, :10].compute()) == 0
fname = os.path.join(self.base_dir, "test_l_nan_nofillvalue.tif")
scn = Scene(reader="generic_image", filenames=[fname])
scn.load(["image"])
assert scn["image"].shape == (1, self.y_size, self.x_size)
assert np.all(np.isnan(scn["image"].data[0][:10, :10].compute()))
[docs]
def test_GenericImageFileHandler(self):
"""Test direct use of the reader."""
from satpy.readers.generic_image import GenericImageFileHandler
fname = os.path.join(self.base_dir, "test_rgba.tif")
fname_info = {"start_time": self.date}
ftype_info = {}
reader = GenericImageFileHandler(fname, fname_info, ftype_info)
foo = make_dataid(name="image")
assert reader.file_content
assert reader.finfo["filename"] == fname
assert reader.finfo["start_time"] == self.date
assert reader.finfo["end_time"] == self.date
assert reader.area == self.area_def
assert reader.get_area_def(None) == self.area_def
assert reader.start_time == self.date
assert reader.end_time == self.date
dataset = reader.get_dataset(foo, {})
assert isinstance(dataset, xr.DataArray)
assert "spatial_ref" in dataset.coords
assert np.all(np.isnan(dataset.data[:, :10, :10].compute()))
[docs]
def test_GenericImageFileHandler_masking_only_integer(self):
"""Test direct use of the reader."""
from satpy.readers.generic_image import GenericImageFileHandler
class FakeGenericImageFileHandler(GenericImageFileHandler):
def __init__(self, filename, filename_info, filetype_info, file_content, **kwargs):
"""Get fake file content from 'get_test_content'."""
super(GenericImageFileHandler, self).__init__(filename, filename_info, filetype_info)
self.file_content = file_content
self.dataset_name = None
self.file_content.update(kwargs)
data = self.scn["rgba"]
# do nothing if not integer
float_data = data / 255.
reader = FakeGenericImageFileHandler("dummy", {}, {}, {"image": float_data})
assert reader.get_dataset(make_dataid(name="image"), {}) is float_data
# masking if integer
data = data.astype(np.uint32)
assert data.bands.size == 4
reader = FakeGenericImageFileHandler("dummy", {}, {}, {"image": data})
ret_data = reader.get_dataset(make_dataid(name="image"), {})
assert ret_data.bands.size == 3
[docs]
def test_GenericImageFileHandler_datasetid(self):
"""Test direct use of the reader."""
from satpy.readers.generic_image import GenericImageFileHandler
fname = os.path.join(self.base_dir, "test_rgba.tif")
fname_info = {"start_time": self.date}
ftype_info = {}
reader = GenericImageFileHandler(fname, fname_info, ftype_info)
foo = make_dataid(name="image-custom")
assert reader.file_content
dataset = reader.get_dataset(foo, {})
assert isinstance(dataset, xr.DataArray)
[docs]
def test_GenericImageFileHandler_nodata(self):
"""Test nodata handling with direct use of the reader."""
from satpy.readers.generic_image import GenericImageFileHandler
fname = os.path.join(self.base_dir, "test_l_nan_fillvalue.tif")
fname_info = {"start_time": self.date}
ftype_info = {}
reader = GenericImageFileHandler(fname, fname_info, ftype_info)
foo = make_dataid(name="image-custom")
assert reader.file_content
info = {"nodata_handling": "nan_mask"}
dataset = reader.get_dataset(foo, info)
assert isinstance(dataset, xr.DataArray)
assert np.all(np.isnan(dataset.data[0][:10, :10].compute()))
assert np.isnan(dataset.attrs["_FillValue"])
info = {"nodata_handling": "fill_value"}
dataset = reader.get_dataset(foo, info)
assert isinstance(dataset, xr.DataArray)
assert np.sum(dataset.data[0][:10, :10].compute()) == 0
assert dataset.attrs["_FillValue"] == 0
# default same as 'nodata_handling': 'fill_value'
dataset = reader.get_dataset(foo, {})
assert isinstance(dataset, xr.DataArray)
assert np.sum(dataset.data[0][:10, :10].compute()) == 0
assert dataset.attrs["_FillValue"] == 0