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|
import pytest
import sys
import os
import tempfile
from .checks import (
# check_header,
compare_array,
compare_array_abstol,
)
import numpy as np
from ..fitslib import (
FITS,
read,
write,
)
@pytest.mark.parametrize(
'compress',
[
'rice',
'hcompress',
'plio',
'gzip',
'gzip_2',
'gzip_lossless',
'gzip_2_lossless',
]
)
def test_compressed_write_read(compress):
"""
Test writing and reading a rice compressed image
"""
nrows = 5
ncols = 20
if compress in ['rice', 'hcompress'] or 'gzip' in compress:
dtypes = ['u1', 'i1', 'u2', 'i2', 'u4', 'i4', 'f4', 'f8']
elif compress == 'plio':
dtypes = ['i1', 'i2', 'i4', 'f4', 'f8']
else:
raise ValueError('unexpected compress %s' % compress)
if 'lossless' in compress:
qlevel = None
else:
qlevel = 16
seed = 1919
rng = np.random.RandomState(seed)
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
for ext, dtype in enumerate(dtypes):
if dtype[0] == 'f':
data = rng.normal(size=(nrows, ncols))
if compress == 'plio':
data = data.clip(min=0)
data = data.astype(dtype)
else:
data = np.arange(
nrows * ncols, dtype=dtype,
).reshape(nrows, ncols)
csend = compress.replace('_lossless', '')
write(fname, data, compress=csend, qlevel=qlevel)
rdata = read(fname, ext=ext+1)
if 'lossless' in compress or dtype[0] in ['i', 'u']:
compare_array(
data, rdata,
"%s compressed images ('%s')" % (compress, dtype)
)
else:
# lossy floating point
compare_array_abstol(
data,
rdata,
0.2,
"%s compressed images ('%s')" % (compress, dtype),
)
with FITS(fname) as fits:
for ii in range(len(dtypes)):
i = ii + 1
assert fits[i].is_compressed(), "is compressed"
@pytest.mark.parametrize(
'compress',
[
'rice',
'hcompress',
'plio',
'gzip',
'gzip_2',
'gzip_lossless',
'gzip_2_lossless',
]
)
def test_compressed_write_read_fitsobj(compress):
"""
Test writing and reading a rice compressed image
In this version, keep the fits object open
"""
nrows = 5
ncols = 20
if compress in ['rice', 'hcompress'] or 'gzip' in compress:
dtypes = ['u1', 'i1', 'u2', 'i2', 'u4', 'i4', 'f4', 'f8']
# dtypes = ['u2']
elif compress == 'plio':
dtypes = ['i1', 'i2', 'i4', 'f4', 'f8']
else:
raise ValueError('unexpected compress %s' % compress)
if 'lossless' in compress:
qlevel = None
# qlevel = 9999
else:
qlevel = 16
seed = 1919
rng = np.random.RandomState(seed)
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note i8 not supported for compressed!
for dtype in dtypes:
if dtype[0] == 'f':
data = rng.normal(size=(nrows, ncols))
if compress == 'plio':
data = data.clip(min=0)
data = data.astype(dtype)
else:
data = np.arange(
nrows * ncols, dtype=dtype,
).reshape(nrows, ncols)
csend = compress.replace('_lossless', '')
fits.write_image(data, compress=csend, qlevel=qlevel)
rdata = fits[-1].read()
if 'lossless' in compress or dtype[0] in ['i', 'u']:
# for integers we have chosen a wide range of values, so
# there will be no quantization and we expect no
# information loss
compare_array(
data, rdata,
"%s compressed images ('%s')" % (compress, dtype)
)
else:
# lossy floating point
compare_array_abstol(
data,
rdata,
0.2,
"%s compressed images ('%s')" % (compress, dtype),
)
with FITS(fname) as fits:
for ii in range(len(dtypes)):
i = ii + 1
assert fits[i].is_compressed(), "is compressed"
@pytest.mark.skipif(sys.version_info < (3, 9),
reason='importlib bug in 3.8')
def test_gzip_tile_compressed_read_lossless_astropy():
"""
Test reading an image gzip compressed by astropy (fixed by cfitsio 3.49)
"""
import importlib.resources
ref = importlib.resources.files("fitsio") / 'test_images' / 'test_gzip_compressed_image.fits.fz' # noqa
with importlib.resources.as_file(ref) as gzip_file:
data = read(gzip_file)
compare_array(data, data*0.0, "astropy lossless compressed image")
def test_compress_preserve_zeros():
"""
Test writing and reading gzip compressed image
"""
zinds = [
(1, 3),
(2, 9),
]
dtypes = ['f4', 'f8']
seed = 2020
rng = np.random.RandomState(seed)
# Do not test hcompress as it doesn't support SUBTRACTIVE_DITHER_2
for compress in ['gzip', 'gzip_2', 'rice']:
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
for dtype in dtypes:
data = rng.normal(size=5*20).reshape(5, 20).astype(dtype)
for zind in zinds:
data[zind[0], zind[1]] = 0.0
fits.write_image(
data,
compress=compress,
qlevel=16,
qmethod='SUBTRACTIVE_DITHER_2',
)
rdata = fits[-1].read()
for zind in zinds:
assert rdata[zind[0], zind[1]] == 0.0
@pytest.mark.parametrize(
'compress',
[
'rice',
'hcompress',
'plio',
]
)
@pytest.mark.parametrize(
'seed_type',
['matched', 'unmatched', 'checksum', 'checksum_int'],
)
@pytest.mark.parametrize(
'use_fits_object',
[False, True],
)
@pytest.mark.parametrize(
'dtype',
['f4', 'f8'],
)
def test_compressed_seed(compress, seed_type, use_fits_object, dtype):
"""
Test writing and reading a rice compressed image
"""
nrows = 5
ncols = 20
qlevel = 16
seed = 1919
rng = np.random.RandomState(seed)
if seed_type == 'matched':
# dither_seed = 9881
dither_seed1 = 9881
dither_seed2 = 9881
elif seed_type == 'unmatched':
# dither_seed = None
dither_seed1 = 3
dither_seed2 = 4
elif seed_type == 'checksum':
dither_seed1 = 'checksum'
dither_seed2 = b'checksum'
elif seed_type == 'checksum_int':
dither_seed1 = -1
# any negative means use checksum
dither_seed2 = -3
with tempfile.TemporaryDirectory() as tmpdir:
fname1 = os.path.join(tmpdir, 'test1.fits')
fname2 = os.path.join(tmpdir, 'test2.fits')
data = rng.normal(size=(nrows, ncols))
if compress == 'plio':
data = data.clip(min=0)
data = data.astype(dtype)
if use_fits_object:
with FITS(fname1, 'rw') as fits1:
fits1.write(
data, compress=compress, qlevel=qlevel,
# dither_seed=dither_seed,
dither_seed=dither_seed1,
)
rdata1 = fits1[-1].read()
with FITS(fname2, 'rw') as fits2:
fits2.write(
data, compress=compress, qlevel=qlevel,
# dither_seed=dither_seed,
dither_seed=dither_seed2,
)
rdata2 = fits2[-1].read()
else:
write(
fname1, data, compress=compress, qlevel=qlevel,
# dither_seed=dither_seed,
dither_seed=dither_seed1,
)
rdata1 = read(fname1)
write(
fname2, data, compress=compress, qlevel=qlevel,
# dither_seed=dither_seed,
dither_seed=dither_seed2,
)
rdata2 = read(fname2)
mess = "%s compressed images ('%s')" % (compress, dtype)
if seed_type in ['checksum', 'checksum_int', 'matched']:
assert np.all(rdata1 == rdata2), mess
else:
assert np.all(rdata1 != rdata2), mess
@pytest.mark.parametrize(
'dither_seed',
['blah', 10_001],
)
def test_compressed_seed_bad(dither_seed):
"""
Test writing and reading a rice compressed image
"""
compress = 'rice'
dtype = 'f4'
nrows = 5
ncols = 20
qlevel = 16
seed = 1919
rng = np.random.RandomState(seed)
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
data = rng.normal(size=(nrows, ncols))
data = data.astype(dtype)
with pytest.raises(ValueError):
write(
fname, data, compress=compress, qlevel=qlevel,
dither_seed=dither_seed,
)
if __name__ == '__main__':
test_compressed_seed(
compress='rice',
match_seed=False,
use_fits_object=True,
dtype='f4',
)
|
