def test_cmap_list(self):
"""Test that colors can be a list/tuple."""
from satpy.enhancements import create_colormap
colors = [
[0, 0, 1],
[1, 0, 1],
[0, 1, 1],
[1, 1, 1],
]
values = [2, 4, 6, 8]
cmap = create_colormap({'colors': colors, 'color_scale': 1})
assert cmap.colors.shape[0] == 4
np.testing.assert_equal(cmap.colors[0], [0.0, 0.0, 1.0])
assert cmap.values.shape[0] == 4
assert cmap.values[0] == 0
assert cmap.values[-1] == 1.0
cmap = create_colormap({
'colors': colors,
'color_scale': 1,
'values': values
})
assert cmap.colors.shape[0] == 4
np.testing.assert_equal(cmap.colors[0], [0.0, 0.0, 1.0])
assert cmap.values.shape[0] == 4
assert cmap.values[0] == 2
assert cmap.values[-1] == 8
def test_cmap_from_file_vrgb(self):
"""Test that colormaps can be loaded from a binary file with values."""
from tempfile import NamedTemporaryFile
from satpy.enhancements import create_colormap
# create the colormap file on disk
with NamedTemporaryFile(suffix='.npy', delete=False) as tmp_cmap:
cmap_filename = tmp_cmap.name
np.save(
cmap_filename,
np.array([
[128, 255, 0, 0],
[130, 255, 255, 0],
[132, 255, 255, 255],
[134, 0, 0, 255],
]))
try:
# default mode of VRGB
cmap = create_colormap({'filename': cmap_filename})
self.assertEqual(cmap.colors.shape[0], 4)
np.testing.assert_equal(cmap.colors[0], [1.0, 0, 0])
self.assertEqual(cmap.values.shape[0], 4)
self.assertEqual(cmap.values[0], 128)
self.assertEqual(cmap.values[-1], 134)
cmap = create_colormap({
'filename': cmap_filename,
'colormap_mode': 'RGBA'
})
self.assertEqual(cmap.colors.shape[0], 4)
self.assertEqual(cmap.colors.shape[1], 4) # RGBA
np.testing.assert_equal(cmap.colors[0], [128 / 255., 1.0, 0, 0])
self.assertEqual(cmap.values.shape[0], 4)
self.assertEqual(cmap.values[0], 0)
self.assertEqual(cmap.values[-1], 1.0)
cmap = create_colormap({
'filename': cmap_filename,
'min_value': 50,
'max_value': 100
})
self.assertEqual(cmap.colors.shape[0], 4)
np.testing.assert_equal(cmap.colors[0], [1.0, 0, 0])
self.assertEqual(cmap.values.shape[0], 4)
self.assertEqual(cmap.values[0], 50)
self.assertEqual(cmap.values[-1], 100)
self.assertRaises(
ValueError, create_colormap, {
'filename': cmap_filename,
'colormap_mode': 'RGB',
'min_value': 50,
'max_value': 100
})
finally:
os.remove(cmap_filename)
def test_cmap_bad_mode(self, real_mode, forced_mode, filename_suffix):
"""Test that reading colormaps with the wrong mode fails."""
with closed_named_temp_file(suffix=filename_suffix) as cmap_filename:
cmap_data = _generate_cmap_test_data(None, real_mode)
_write_cmap_to_file(cmap_filename, cmap_data)
# Force colormap_mode VRGBA to RGBA and we should see an exception
with pytest.raises(ValueError):
create_colormap({
'filename': cmap_filename,
'colormap_mode': forced_mode
})
def test_cmap_from_file_bad_shape(self):
"""Test that unknown array shape causes an error."""
from satpy.enhancements import create_colormap
# create the colormap file on disk
with closed_named_temp_file(suffix='.npy') as cmap_filename:
np.save(cmap_filename, np.array([
[0],
[64],
[128],
[255],
]))
with pytest.raises(ValueError):
create_colormap({'filename': cmap_filename})
def test_cmap_from_trollimage(self):
"""Test that colormaps in trollimage can be loaded."""
from satpy.enhancements import create_colormap
cmap = create_colormap({'colors': 'pubu'})
from trollimage.colormap import pubu
np.testing.assert_equal(cmap.colors, pubu.colors)
np.testing.assert_equal(cmap.values, pubu.values)
def test_cmap_from_file(self, color_scale, colormap_mode, extra_kwargs,
filename_suffix):
"""Test that colormaps can be loaded from a binary file."""
# create the colormap file on disk
with closed_named_temp_file(suffix=filename_suffix) as cmap_filename:
cmap_data = _generate_cmap_test_data(color_scale, colormap_mode)
_write_cmap_to_file(cmap_filename, cmap_data)
unset_first_value = 128.0 / 255.0 if colormap_mode.startswith(
"V") else 0.0
unset_last_value = 134.0 / 255.0 if colormap_mode.startswith(
"V") else 1.0
if (color_scale is None
or color_scale == 255) and colormap_mode.startswith("V"):
unset_first_value *= 255
unset_last_value *= 255
if "min_value" in extra_kwargs:
unset_first_value = extra_kwargs["min_value"]
unset_last_value = extra_kwargs["max_value"]
first_color = [1.0, 0.0, 0.0]
if colormap_mode == "VRGBA":
first_color = [128.0 / 255.0] + first_color
kwargs1 = {"filename": cmap_filename}
kwargs1.update(extra_kwargs)
if color_scale is not None:
kwargs1["color_scale"] = color_scale
cmap = create_colormap(kwargs1)
assert cmap.colors.shape[0] == 4
np.testing.assert_equal(cmap.colors[0], first_color)
assert cmap.values.shape[0] == 4
assert cmap.values[0] == unset_first_value
assert cmap.values[-1] == unset_last_value
def test_cmap_from_file_rgb_1(self):
"""Test that colormaps can be loaded from a binary file with 0-1 colors."""
from tempfile import NamedTemporaryFile
from satpy.enhancements import create_colormap
# create the colormap file on disk
with NamedTemporaryFile(suffix='.npy', delete=False) as tmp_cmap:
cmap_filename = tmp_cmap.name
np.save(cmap_filename,
np.array([
[1, 0, 0],
[1, 1, 0],
[1, 1, 1],
[0, 0, 1],
]))
try:
cmap = create_colormap({
'filename': cmap_filename,
'color_scale': 1
})
self.assertEqual(cmap.colors.shape[0], 4)
np.testing.assert_equal(cmap.colors[0], [1.0, 0, 0])
self.assertEqual(cmap.values.shape[0], 4)
self.assertEqual(cmap.values[0], 0)
self.assertEqual(cmap.values[-1], 1.0)
cmap = create_colormap({
'filename': cmap_filename,
'color_scale': 1,
'min_value': 50,
'max_value': 100
})
self.assertEqual(cmap.colors.shape[0], 4)
np.testing.assert_equal(cmap.colors[0], [1.0, 0, 0])
self.assertEqual(cmap.values.shape[0], 4)
self.assertEqual(cmap.values[0], 50)
self.assertEqual(cmap.values[-1], 100)
finally:
os.remove(cmap_filename)
def test_cmap_vrgb_as_rgba(self):
"""Test that data created as VRGB still reads as RGBA."""
with closed_named_temp_file(suffix=".npy") as cmap_filename:
cmap_data = _generate_cmap_test_data(None, "VRGB")
np.save(cmap_filename, cmap_data)
cmap = create_colormap({
'filename': cmap_filename,
'colormap_mode': "RGBA"
})
assert cmap.colors.shape[0] == 4
assert cmap.colors.shape[1] == 4 # RGBA
np.testing.assert_equal(cmap.colors[0], [128 / 255., 1.0, 0, 0])
assert cmap.values.shape[0] == 4
assert cmap.values[0] == 0
assert cmap.values[-1] == 1.0
def load_color_table_file_to_colormap(ct_file):
"""Load a text colormap file and create a trollimage.Colormap object.
If the provided pathname includes ``$POLAR2GRID_HOME`` it will be replaced
with the current environment variable value of ``POLAR2GRID_HOME``.
"""
from trollimage.colormap import Colormap
p2g_home = os.getenv('POLAR2GRID_HOME', '')
ct_file = ct_file.replace("$POLAR2GRID_HOME", p2g_home)
ct_file = ct_file.replace("$GEO2GRID_HOME", p2g_home)
if ct_file.endswith('.npy') or ct_file.endswith('.npz'):
# binary colormap files (RGB, RGBA, VRGB, VRGBA)
from satpy.enhancements import create_colormap
cmap = create_colormap({'filename': ct_file})
else:
# P2G style colormap text files
ct = parse_color_table_file(ct_file)
entries = ((e[0] / 255., [x / 255. for x in e[1:]]) for e in ct)
cmap = Colormap(*entries)
return cmap
def test_cmap_from_config_path(self, tmp_path):
"""Test loading a colormap relative to a config path."""
import satpy
from satpy.enhancements import create_colormap
cmap_dir = tmp_path / "colormaps"
cmap_dir.mkdir()
cmap_filename = cmap_dir / "my_colormap.npy"
cmap_data = _generate_cmap_test_data(None, "RGBA")
np.save(cmap_filename, cmap_data)
with satpy.config.set(config_path=[tmp_path]):
rel_cmap_filename = os.path.join("colormaps", "my_colormap.npy")
cmap = create_colormap({
'filename': rel_cmap_filename,
'colormap_mode': "RGBA"
})
assert cmap.colors.shape[0] == 4
assert cmap.colors.shape[1] == 4 # RGBA
np.testing.assert_equal(cmap.colors[0], [128 / 255., 1.0, 0, 0])
assert cmap.values.shape[0] == 4
assert cmap.values[0] == 0
assert cmap.values[-1] == 1.0
def test_cmap_no_colormap(self):
"""Test that being unable to create a colormap raises an error."""
from satpy.enhancements import create_colormap
with pytest.raises(ValueError):
create_colormap({})
def save_image(self,
img,
filename=None,
dtype=None,
fill_value=None,
compute=True,
keep_palette=False,
cmap=None,
tags=None,
overviews=None,
overviews_minsize=256,
overviews_resampling=None,
include_scale_offset=False,
scale_offset_tags=None,
driver=None,
tiled=True,
**kwargs):
"""Save the image to the given ``filename`` in geotiff_ format.
Note for faster output and reduced memory usage the ``rasterio``
library must be installed. This writer currently falls back to
using ``gdal`` directly, but that will be deprecated in the future.
Args:
img (xarray.DataArray): Data to save to geotiff.
filename (str): Filename to save the image to. Defaults to
``filename`` passed during writer creation. Unlike the
creation ``filename`` keyword argument, this filename does not
get formatted with data attributes.
dtype (numpy.dtype): Numpy data type to save the image as.
Defaults to 8-bit unsigned integer (``np.uint8``) or the data
type of the data to be saved if ``enhance=False``. If the
``dtype`` argument is provided during writer creation then
that will be used as the default.
fill_value (int or float): Value to use where data values are
NaN/null. If this is specified in the writer configuration
file that value will be used as the default.
compute (bool): Compute dask arrays and save the image
immediately. If ``False`` then the return value can be passed
to :func:`~satpy.writers.compute_writer_results` to do the
computation. This is useful when multiple images may share
input calculations where dask can benefit from not repeating
them multiple times. Defaults to ``True`` in the writer by
itself, but is typically passed as ``False`` by callers where
calculations can be combined.
keep_palette (bool): Save palette/color table to geotiff.
To be used with images that were palettized with the
"palettize" enhancement. Setting this to ``True`` will cause
the colormap of the image to be written as a "color table" in
the output geotiff and the image data values will represent
the index values in to that color table. By default, this will
use the colormap used in the "palettize" operation.
See the ``cmap`` option for other options. This option defaults
to ``False`` and palettized images will be converted to RGB/A.
cmap (trollimage.colormap.Colormap or None): Colormap to save
as a color table in the output geotiff. See ``keep_palette``
for more information. Defaults to the palette of the provided
``img`` object. The colormap's range should be set to match
the index range of the palette
(ex. `cmap.set_range(0, len(colors))`).
tags (dict): Extra metadata to store in geotiff.
overviews (list): The reduction factors of the overviews to include
in the image, eg::
scn.save_datasets(overviews=[2, 4, 8, 16])
If provided as an empty list, then levels will be
computed as powers of two until the last level has less
pixels than `overviews_minsize`.
Default is to not add overviews.
overviews_minsize (int): Minimum number of pixels for the smallest
overview size generated when `overviews` is auto-generated.
Defaults to 256.
overviews_resampling (str): Resampling method
to use when generating overviews. This must be the name of an
enum value from :class:`rasterio.enums.Resampling` and
only takes effect if the `overviews` keyword argument is
provided. Common values include `nearest` (default),
`bilinear`, `average`, and many others. See the rasterio
documentation for more information.
scale_offset_tags (Tuple[str, str]): If set, include inclusion of
scale and offset in the GeoTIFF headers in the GDALMetaData
tag. The value of this argument should be a keyword argument
``(scale_label, offset_label)``, for example, ``("scale",
"offset")``, indicating the labels to be used.
include_scale_offset (deprecated, bool): Deprecated.
Use ``scale_offset_tags=("scale", "offset")`` to include scale
and offset tags.
tiled (bool): For performance this defaults to ``True``.
Pass ``False`` to created striped TIFF files.
.. _geotiff: http://trac.osgeo.org/geotiff/
"""
filename = filename or self.get_filename(**img.data.attrs)
gdal_options = self._get_gdal_options(kwargs)
if fill_value is None:
# fall back to fill_value from configuration file
fill_value = self.info.get('fill_value')
dtype = dtype if dtype is not None else self.dtype
if dtype is None and self.enhancer is not False:
dtype = np.uint8
elif dtype is None:
dtype = img.data.dtype.type
if "alpha" in kwargs:
raise ValueError(
"Keyword 'alpha' is automatically set based on 'fill_value' "
"and should not be specified")
if np.issubdtype(dtype, np.floating):
if img.mode != "L":
raise ValueError("Image must be in 'L' mode for floating "
"point geotiff saving")
if fill_value is None:
LOG.debug("Alpha band not supported for float geotiffs, "
"setting fill value to 'NaN'")
fill_value = np.nan
if keep_palette and cmap is None and img.palette is not None:
from satpy.enhancements import create_colormap
cmap = create_colormap({'colors': img.palette})
cmap.set_range(0, len(img.palette) - 1)
if tags is None:
tags = {}
tags.update(self.tags)
return img.save(filename,
fformat='tif',
driver=driver,
fill_value=fill_value,
dtype=dtype,
compute=compute,
keep_palette=keep_palette,
cmap=cmap,
tags=tags,
include_scale_offset_tags=include_scale_offset,
scale_offset_tags=scale_offset_tags,
overviews=overviews,
overviews_resampling=overviews_resampling,
overviews_minsize=overviews_minsize,
tiled=tiled,
**gdal_options)
def save_image(self, img, filename=None, dtype=None, fill_value=None,
compute=True, keep_palette=False, cmap=None, tags=None,
include_scale_offset=False,
**kwargs):
"""Save the image to the given ``filename`` in geotiff_ format.
Note for faster output and reduced memory usage the ``rasterio``
library must be installed. This writer currently falls back to
using ``gdal`` directly, but that will be deprecated in the future.
Args:
img (xarray.DataArray): Data to save to geotiff.
filename (str): Filename to save the image to. Defaults to
``filename`` passed during writer creation. Unlike the
creation ``filename`` keyword argument, this filename does not
get formatted with data attributes.
dtype (numpy.dtype): Numpy data type to save the image as.
Defaults to 8-bit unsigned integer (``np.uint8``). If the
``dtype`` argument is provided during writer creation then
that will be used as the default.
fill_value (int or float): Value to use where data values are
NaN/null. If this is specified in the writer configuration
file that value will be used as the default.
compute (bool): Compute dask arrays and save the image
immediately. If ``False`` then the return value can be passed
to :func:`~satpy.writers.compute_writer_results` to do the
computation. This is useful when multiple images may share
input calculations where dask can benefit from not repeating
them multiple times. Defaults to ``True`` in the writer by
itself, but is typically passed as ``False`` by callers where
calculations can be combined.
keep_palette (bool): Save palette/color table to geotiff.
To be used with images that were palettized with the
"palettize" enhancement. Setting this to ``True`` will cause
the colormap of the image to be written as a "color table" in
the output geotiff and the image data values will represent
the index values in to that color table. By default, this will
use the colormap used in the "palettize" operation.
See the ``cmap`` option for other options. This option defaults
to ``False`` and palettized images will be converted to RGB/A.
cmap (trollimage.colormap.Colormap or None): Colormap to save
as a color table in the output geotiff. See ``keep_palette``
for more information. Defaults to the palette of the provided
``img`` object. The colormap's range should be set to match
the index range of the palette
(ex. `cmap.set_range(0, len(colors))`).
tags (dict): Extra metadata to store in geotiff.
include_scale_offset (bool): Activate inclusion of scale and offset
factors in the geotiff to allow retrieving original values from
the pixel values. ``False`` by default.
.. _geotiff: http://trac.osgeo.org/geotiff/
"""
filename = filename or self.get_filename(**img.data.attrs)
# Update global GDAL options with these specific ones
gdal_options = self.gdal_options.copy()
for k in kwargs.keys():
if k in self.GDAL_OPTIONS:
gdal_options[k] = kwargs[k]
if fill_value is None:
# fall back to fill_value from configuration file
fill_value = self.info.get('fill_value')
dtype = dtype if dtype is not None else self.dtype
if dtype is None:
dtype = np.uint8
if "alpha" in kwargs:
raise ValueError(
"Keyword 'alpha' is automatically set based on 'fill_value' "
"and should not be specified")
if np.issubdtype(dtype, np.floating):
if img.mode != "L":
raise ValueError("Image must be in 'L' mode for floating "
"point geotiff saving")
if fill_value is None:
LOG.debug("Alpha band not supported for float geotiffs, "
"setting fill value to 'NaN'")
fill_value = np.nan
if keep_palette and cmap is None and img.palette is not None:
from satpy.enhancements import create_colormap
cmap = create_colormap({'colors': img.palette})
cmap.set_range(0, len(img.palette) - 1)
if tags is None:
tags = {}
tags.update(self.tags)
return img.save(filename, fformat='tif', fill_value=fill_value,
dtype=dtype, compute=compute,
keep_palette=keep_palette, cmap=cmap,
tags=tags, include_scale_offset_tags=include_scale_offset,
**gdal_options)
def save_image(self,
img,
filename=None,
dtype=None,
fill_value=None,
floating_point=None,
compute=True,
keep_palette=False,
cmap=None,
**kwargs):
"""Save the image to the given ``filename`` in geotiff_ format.
Note for faster output and reduced memory usage the ``rasterio``
library must be installed. This writer currently falls back to
using ``gdal`` directly, but that will be deprecated in the future.
Args:
img (xarray.DataArray): Data to save to geotiff.
filename (str): Filename to save the image to. Defaults to
``filename`` passed during writer creation. Unlike the
creation ``filename`` keyword argument, this filename does not
get formatted with data attributes.
dtype (numpy.dtype): Numpy data type to save the image as.
Defaults to 8-bit unsigned integer (``np.uint8``). If the
``dtype`` argument is provided during writer creation then
that will be used as the default.
fill_value (int or float): Value to use where data values are
NaN/null. If this is specified in the writer configuration
file that value will be used as the default.
floating_point (bool): Deprecated. Use ``dtype=np.float64``
instead.
compute (bool): Compute dask arrays and save the image
immediately. If ``False`` then the return value can be passed
to :func:`~satpy.writers.compute_writer_results` to do the
computation. This is useful when multiple images may share
input calculations where dask can benefit from not repeating
them multiple times. Defaults to ``True`` in the writer by
itself, but is typically passed as ``False`` by callers where
calculations can be combined.
keep_palette (bool): Save palette/color table to geotiff.
To be used with images that were palettized with the
"palettize" enhancement. Setting this to ``True`` will cause
the colormap of the image to be written as a "color table" in
the output geotiff and the image data values will represent
the index values in to that color table. By default, this will
use the colormap used in the "palettize" operation.
See the ``cmap`` option for other options. This option defaults
to ``False`` and palettized images will be converted to RGB/A.
cmap (trollimage.colormap.Colormap or None): Colormap to save
as a color table in the output geotiff. See ``keep_palette``
for more information. Defaults to the palette of the provided
``img`` object. The colormap's range should be set to match
the index range of the palette
(ex. `cmap.set_range(0, len(colors))`).
.. _geotiff: http://trac.osgeo.org/geotiff/
"""
filename = filename or self.get_filename(**img.data.attrs)
# Update global GDAL options with these specific ones
gdal_options = self.gdal_options.copy()
for k in kwargs.keys():
if k in self.GDAL_OPTIONS:
gdal_options[k] = kwargs[k]
if fill_value is None:
# fall back to fill_value from configuration file
fill_value = self.info.get('fill_value')
if floating_point is not None:
import warnings
warnings.warn(
"'floating_point' is deprecated, use"
"'dtype=np.float64' instead.", DeprecationWarning)
dtype = np.float64
dtype = dtype if dtype is not None else self.dtype
if dtype is None:
dtype = np.uint8
if "alpha" in kwargs:
raise ValueError(
"Keyword 'alpha' is automatically set based on 'fill_value' "
"and should not be specified")
if np.issubdtype(dtype, np.floating):
if img.mode != "L":
raise ValueError("Image must be in 'L' mode for floating "
"point geotiff saving")
if fill_value is None:
LOG.debug("Alpha band not supported for float geotiffs, "
"setting fill value to 'NaN'")
fill_value = np.nan
if keep_palette and cmap is None and img.palette is not None:
from satpy.enhancements import create_colormap
cmap = create_colormap({'colors': img.palette})
cmap.set_range(0, len(img.palette) - 1)
try:
import rasterio # noqa
# we can use the faster rasterio-based save
return img.save(filename,
fformat='tif',
fill_value=fill_value,
dtype=dtype,
compute=compute,
keep_palette=keep_palette,
cmap=cmap,
**gdal_options)
except ImportError:
LOG.warning("Using legacy/slower geotiff save method, install "
"'rasterio' for faster saving.")
import warnings
warnings.warn(
"Using legacy/slower geotiff save method with 'gdal'."
"This will be deprecated in the future. Install "
"'rasterio' for faster saving and future "
"compatibility.", PendingDeprecationWarning)
# Map numpy data types to GDAL data types
NP2GDAL = {
np.float32: gdal.GDT_Float32,
np.float64: gdal.GDT_Float64,
np.uint8: gdal.GDT_Byte,
np.uint16: gdal.GDT_UInt16,
np.uint32: gdal.GDT_UInt32,
np.int16: gdal.GDT_Int16,
np.int32: gdal.GDT_Int32,
np.complex64: gdal.GDT_CFloat32,
np.complex128: gdal.GDT_CFloat64,
}
# force to numpy dtype object
dtype = np.dtype(dtype)
gformat = NP2GDAL[dtype.type]
gdal_options['nbits'] = int(
gdal_options.get('nbits', dtype.itemsize * 8))
datasets, mode = img._finalize(fill_value=fill_value, dtype=dtype)
LOG.debug("Saving to GeoTiff: %s", filename)
g_opts = [
"{0}={1}".format(k.upper(), str(v))
for k, v in gdal_options.items()
]
ensure_dir(filename)
delayed = self._create_file(filename, img, gformat, g_opts,
datasets, mode)
if compute:
return delayed.compute()
return delayed
