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import os
import tempfile
# import warnings
from .checks import check_header, compare_array
import numpy as np
from ..fitslib import FITS
DTYPES = ['u1', 'i1', 'u2', 'i2', '<u4', 'i4', 'i8', '>f4', 'f8']
def test_image_write_read():
"""
Test a basic image write, data and a header, then reading back in to
check the values
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note mixing up byte orders a bit
for dtype in DTYPES:
data = np.arange(5*20, dtype=dtype).reshape(5, 20)
header = {'DTYPE': dtype, 'NBYTES': data.dtype.itemsize}
fits.write_image(data, header=header)
rdata = fits[-1].read()
compare_array(data, rdata, "images")
rh = fits[-1].read_header()
check_header(header, rh)
with FITS(fname) as fits:
for i in range(len(DTYPES)):
assert not fits[i].is_compressed(), 'not compressed'
def test_image_write_empty():
"""
Test a basic image write, with no data and just a header, then reading
back in to check the values
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
data = None
header = {
'EXPTIME': 120,
'OBSERVER': 'Beatrice Tinsley',
'INSTRUME': 'DECam',
'FILTER': 'r',
}
ccds = ['CCD1', 'CCD2', 'CCD3', 'CCD4', 'CCD5', 'CCD6', 'CCD7', 'CCD8']
with FITS(fname, 'rw', ignore_empty=True) as fits:
for extname in ccds:
fits.write_image(data, header=header)
_ = fits[-1].read()
rh = fits[-1].read_header()
check_header(header, rh)
def test_image_write_read_from_dims():
"""
Test creating an image from dims and writing in place
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note mixing up byte orders a bit
for dtype in DTYPES:
data = np.arange(5*20, dtype=dtype).reshape(5, 20)
fits.create_image_hdu(dims=data.shape, dtype=data.dtype)
fits[-1].write(data)
rdata = fits[-1].read()
compare_array(data, rdata, "images")
with FITS(fname) as fits:
for i in range(len(DTYPES)):
assert not fits[i].is_compressed(), "not compressed"
def test_image_write_read_from_dims_chunks():
"""
Test creating an image and reading/writing chunks
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note mixing up byte orders a bit
for dtype in DTYPES:
data = np.arange(5*3, dtype=dtype).reshape(5, 3)
fits.create_image_hdu(dims=data.shape, dtype=data.dtype)
chunk1 = data[0:2, :]
chunk2 = data[2:, :]
#
# first using scalar pixel offset
#
fits[-1].write(chunk1)
start = chunk1.size
fits[-1].write(chunk2, start=start)
rdata = fits[-1].read()
compare_array(data, rdata, "images")
#
# now using sequence, easier to calculate
#
fits.create_image_hdu(dims=data.shape,
dtype=data.dtype)
# first using pixel offset
fits[-1].write(chunk1)
start = [2, 0]
fits[-1].write(chunk2, start=start)
rdata2 = fits[-1].read()
compare_array(data, rdata2, "images")
with FITS(fname) as fits:
for i in range(len(DTYPES)):
assert not fits[i].is_compressed(), "not compressed"
def test_image_slice():
"""
test reading an image slice
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note mixing up byte orders a bit
for dtype in DTYPES:
data = np.arange(16*20, dtype=dtype).reshape(16, 20)
header = {'DTYPE': dtype, 'NBYTES': data.dtype.itemsize}
fits.write_image(data, header=header)
rdata = fits[-1][4:12, 9:17]
compare_array(data[4:12, 9:17], rdata, "images")
rh = fits[-1].read_header()
check_header(header, rh)
def _check_shape(expected_data, rdata):
mess = (
'Data are not the same (Expected shape: %s, '
'actual shape: %s.' % (expected_data.shape, rdata.shape)
)
np.testing.assert_array_equal(expected_data, rdata, mess)
def test_read_flip_axis_slice():
"""
Test reading a slice when the slice's start is less than the slice's stop.
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
dtype = np.int16
data = np.arange(100 * 200, dtype=dtype).reshape(100, 200)
fits.write_image(data)
hdu = fits[-1]
rdata = hdu[:, 130:70]
# Expanded by two to emulate adding one to the start value, and
# adding one to the calculated dimension.
expected_data = data[:, 130:70:-1]
_check_shape(expected_data, rdata)
rdata = hdu[:, 130:70:-6]
expected_data = data[:, 130:70:-6]
_check_shape(expected_data, rdata)
# Expanded by two to emulate adding one to the start value, and
# adding one to the calculated dimension.
expected_data = data[:, 130:70:-6]
_check_shape(expected_data, rdata)
# Positive step integer with start > stop will return an empty
# array
rdata = hdu[:, 90:60:4]
expected_data = np.empty(0, dtype=dtype)
_check_shape(expected_data, rdata)
# Negative step integer with start < stop will return an empty
# array.
rdata = hdu[:, 60:90:-4]
expected_data = np.empty(0, dtype=dtype)
_check_shape(expected_data, rdata)
def test_image_slice_striding():
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
# note mixing up byte orders a bit
for dtype in DTYPES:
data = np.arange(16*20, dtype=dtype).reshape(16, 20)
header = {'DTYPE': dtype, 'NBYTES': data.dtype.itemsize}
fits.write_image(data, header=header)
rdata = fits[-1][4:16:4, 2:20:2]
expected_data = data[4:16:4, 2:20:2]
assert rdata.shape == expected_data.shape, (
"Shapes differ with dtype %s" % dtype
)
compare_array(
expected_data, rdata, "images with dtype %s" % dtype
)
def test_read_ignore_scaling():
"""
Test the flag to ignore scaling when reading an HDU.
"""
with tempfile.TemporaryDirectory() as tmpdir:
fname = os.path.join(tmpdir, 'test.fits')
with FITS(fname, 'rw') as fits:
dtype = 'i2'
data = np.arange(10 * 20, dtype=dtype).reshape(10, 20)
header = {
'DTYPE': dtype,
'BITPIX': 16,
'NBYTES': data.dtype.itemsize,
'BZERO': 9.33,
'BSCALE': 3.281
}
fits.write_image(data, header=header)
hdu = fits[-1]
rdata = hdu.read()
assert rdata.dtype == np.float32, 'Wrong dtype.'
hdu.ignore_scaling = True
rdata = hdu[:, :]
assert rdata.dtype == dtype, 'Wrong dtype when ignoring.'
np.testing.assert_array_equal(
data, rdata, err_msg='Wrong unscaled data.'
)
rh = fits[-1].read_header()
check_header(header, rh)
hdu.ignore_scaling = False
rdata = hdu[:, :]
assert rdata.dtype == np.float32, (
'Wrong dtype when not ignoring.'
)
np.testing.assert_array_equal(
data.astype(np.float32), rdata,
err_msg='Wrong scaled data returned.'
)
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