/usr/lib/python3/dist-packages/pyfits/tests/test_image.py is in python3-pyfits 1:3.3-2+b1.
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import math
import os
import time
import warnings
import numpy as np
import pyfits as fits
from ..util import PyfitsDeprecationWarning, PyfitsPendingDeprecationWarning
from ..hdu.compressed import SUBTRACTIVE_DITHER_1, DITHER_SEED_CHECKSUM
from . import PyfitsTestCase
from .test_table import comparerecords
from .util import catch_warnings, ignore_warnings, CaptureStdio
from nose.tools import assert_raises
class TestImageFunctions(PyfitsTestCase):
def test_constructor_name_arg(self):
"""Like the test of the same name in test_table.py"""
hdu = fits.ImageHDU()
assert hdu.name == ''
assert 'EXTNAME' not in hdu.header
hdu.name = 'FOO'
assert hdu.name == 'FOO'
assert hdu.header['EXTNAME'] == 'FOO'
# Passing name to constructor
hdu = fits.ImageHDU(name='FOO')
assert hdu.name == 'FOO'
assert hdu.header['EXTNAME'] == 'FOO'
# And overriding a header with a different extname
hdr = fits.Header()
hdr['EXTNAME'] = 'EVENTS'
hdu = fits.ImageHDU(header=hdr, name='FOO')
assert hdu.name == 'FOO'
assert hdu.header['EXTNAME'] == 'FOO'
def test_constructor_copies_header(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/153
Ensure that a header from one HDU is copied when used to initialize new
HDU.
"""
ifd = fits.HDUList(fits.PrimaryHDU())
phdr = ifd[0].header
phdr['FILENAME'] = 'labq01i3q_rawtag.fits'
primary_hdu = fits.PrimaryHDU(header=phdr)
ofd = fits.HDUList(primary_hdu)
ofd[0].header['FILENAME'] = 'labq01i3q_flt.fits'
# Original header should be unchanged
assert phdr['FILENAME'] == 'labq01i3q_rawtag.fits'
def test_open(self):
# The function "open" reads a FITS file into an HDUList object. There
# are three modes to open: "readonly" (the default), "append", and
# "update".
# Open a file read-only (the default mode), the content of the FITS
# file are read into memory.
r = fits.open(self.data('test0.fits')) # readonly
# data parts are latent instantiation, so if we close the HDUList
# without touching data, data can not be accessed.
r.close()
assert_raises(Exception, lambda x: x[1].data[:2, :2], r)
def test_open_2(self):
r = fits.open(self.data('test0.fits'))
info = ([(0, 'PRIMARY', 'PrimaryHDU', 138, (), '', '')] +
[(x, 'SCI', 'ImageHDU', 61, (40, 40), 'int16', '')
for x in range(1, 5)])
try:
assert r.info(output=False) == info
finally:
r.close()
def test_primary_with_extname(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/151
Tests that the EXTNAME keyword works with Primary HDUs as well, and
interacts properly with the .name attribute. For convenience
hdulist['PRIMARY'] will still refer to the first HDU even if it has an
EXTNAME not equal to 'PRIMARY'.
"""
prihdr = fits.Header([('EXTNAME', 'XPRIMARY'), ('EXTVER', 1)])
hdul = fits.HDUList([fits.PrimaryHDU(header=prihdr)])
assert 'EXTNAME' in hdul[0].header
assert hdul[0].name == 'XPRIMARY'
assert hdul[0].name == hdul[0].header['EXTNAME']
info = [(0, 'XPRIMARY', 'PrimaryHDU', 5, (), '', '')]
assert hdul.info(output=False) == info
assert hdul['PRIMARY'] is hdul['XPRIMARY']
assert hdul['PRIMARY'] is hdul[('XPRIMARY', 1)]
hdul[0].name = 'XPRIMARY2'
assert hdul[0].header['EXTNAME'] == 'XPRIMARY2'
hdul.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
assert hdul[0].name == 'XPRIMARY2'
@ignore_warnings(PyfitsDeprecationWarning)
def test_io_manipulation(self):
# This legacy test also tests numerous deprecated interfaces for
# backwards compatibility
# Get a keyword value. An extension can be referred by name or by
# number. Both extension and keyword names are case insensitive.
with fits.open(self.data('test0.fits')) as r:
assert r['primary'].header['naxis'] == 0
assert r[0].header['naxis'] == 0
# If there are more than one extension with the same EXTNAME value,
# the EXTVER can be used (as the second argument) to distinguish
# the extension.
assert r['sci', 1].header['detector'] == 1
# append (using "update()") a new card
r[0].header['xxx'] = 1.234e56
assert (str(r[0].header.ascard[-3:]) ==
"EXPFLAG = 'NORMAL ' / Exposure interruption indicator \n"
"FILENAME= 'vtest3.fits' / File name \n"
"XXX = 1.234E+56 ")
# rename a keyword
r[0].header.rename_key('filename', 'fname')
assert_raises(ValueError, r[0].header.rename_key, 'fname',
'history')
assert_raises(ValueError, r[0].header.rename_key, 'fname',
'simple')
r[0].header.rename_key('fname', 'filename')
# get a subsection of data
assert (r[2].data[:3, :3] ==
np.array([[349, 349, 348],
[349, 349, 347],
[347, 350, 349]], dtype=np.int16)).all()
# We can create a new FITS file by opening a new file with "append"
# mode.
with fits.open(self.temp('test_new.fits'), mode='append') as n:
# Append the primary header and the 2nd extension to the new
# file.
n.append(r[0])
n.append(r[2])
# The flush method will write the current HDUList object back
# to the newly created file on disk. The HDUList is still open
# and can be further operated.
n.flush()
assert n[1].data[1, 1] == 349
# modify a data point
n[1].data[1, 1] = 99
# When the file is closed, the most recent additions of
# extension(s) since last flush() will be appended, but any HDU
# already existed at the last flush will not be modified
del n
# If an existing file is opened with "append" mode, like the
# readonly mode, the HDU's will be read into the HDUList which can
# be modified in memory but can not be written back to the original
# file. A file opened with append mode can only add new HDU's.
os.rename(self.temp('test_new.fits'),
self.temp('test_append.fits'))
with fits.open(self.temp('test_append.fits'),
mode='append') as a:
# The above change did not take effect since this was made
# after the flush().
assert a[1].data[1, 1] == 349
a.append(r[1])
del a
# When changes are made to an HDUList which was opened with
# "update" mode, they will be written back to the original file
# when a flush/close is called.
os.rename(self.temp('test_append.fits'),
self.temp('test_update.fits'))
with fits.open(self.temp('test_update.fits'),
mode='update') as u:
# When the changes do not alter the size structures of the
# original (or since last flush) HDUList, the changes are
# written back "in place".
assert u[0].header['rootname'] == 'U2EQ0201T'
u[0].header['rootname'] = 'abc'
assert u[1].data[1, 1] == 349
u[1].data[1, 1] = 99
u.flush()
# If the changes affect the size structure, e.g. adding or
# deleting HDU(s), header was expanded or reduced beyond
# existing number of blocks (2880 bytes in each block), or
# change the data size, the HDUList is written to a temporary
# file, the original file is deleted, and the temporary file is
# renamed to the original file name and reopened in the update
# mode. To a user, these two kinds of updating writeback seem
# to be the same, unless the optional argument in flush or
# close is set to 1.
del u[2]
u.flush()
# the write method in HDUList class writes the current HDUList,
# with all changes made up to now, to a new file. This method
# works the same disregard the mode the HDUList was opened
# with.
u.append(r[3])
u.writeto(self.temp('test_new.fits'))
del u
# Another useful new HDUList method is readall. It will "touch" the
# data parts in all HDUs, so even if the HDUList is closed, we can
# still operate on the data.
with fits.open(self.data('test0.fits')) as r:
r.readall()
assert r[1].data[1, 1] == 315
# create an HDU with data only
data = np.ones((3, 5), dtype=np.float32)
hdu = fits.ImageHDU(data=data, name='SCI')
assert (hdu.data ==
np.array([[1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1.],
[1., 1., 1., 1., 1.]],
dtype=np.float32)).all()
# create an HDU with header and data
# notice that the header has the right NAXIS's since it is constructed
# with ImageHDU
hdu2 = fits.ImageHDU(header=r[1].header, data=np.array([1, 2],
dtype='int32'))
assert (str(hdu2.header.ascard[1:5]) ==
"BITPIX = 32 / array data type \n"
"NAXIS = 1 / number of array dimensions \n"
"NAXIS1 = 2 \n"
"PCOUNT = 0 / number of parameters ")
def test_memory_mapping(self):
# memory mapping
f1 = fits.open(self.data('test0.fits'), memmap=1)
f1.close()
def test_verification_on_output(self):
# verification on output
# make a defect HDUList first
err_text = "HDUList's 0th element is not a primary HDU."
with catch_warnings(record=True) as w:
x = fits.ImageHDU()
# HDUList can take a list or one single HDU
hdu = fits.HDUList(x)
with CaptureStdio():
hdu.verify()
assert len(w) == 3
assert err_text in str(w[1].message)
fix_text = err_text + " Fixed by inserting one as 0th HDU."
with catch_warnings(record=True) as w:
with CaptureStdio():
hdu.writeto(self.temp('test_new2.fits'), 'fix')
assert len(w) == 3
assert fix_text in str(w[1].message)
def test_section(self):
# section testing
fs = fits.open(self.data('arange.fits'))
assert (fs[0].section[3, 2, 5] == np.array([357])).all()
assert (fs[0].section[3, 2, :] ==
np.array([352, 353, 354, 355, 356, 357, 358, 359, 360, 361,
362])).all()
assert (fs[0].section[3, 2, 4:] ==
np.array([356, 357, 358, 359, 360, 361, 362])).all()
assert (fs[0].section[3, 2, :8] ==
np.array([352, 353, 354, 355, 356, 357, 358, 359])).all()
assert (fs[0].section[3, 2, -8:8] ==
np.array([355, 356, 357, 358, 359])).all()
assert (fs[0].section[3, 2:5, :] ==
np.array([[352, 353, 354, 355, 356, 357, 358, 359, 360, 361,
362],
[363, 364, 365, 366, 367, 368, 369, 370, 371, 372,
373],
[374, 375, 376, 377, 378, 379, 380, 381, 382, 383,
384]])).all()
assert (fs[0].section[3, :, :][:3, :3] ==
np.array([[330, 331, 332],
[341, 342, 343],
[352, 353, 354]])).all()
dat = fs[0].data
assert (fs[0].section[3, 2:5, :8] == dat[3, 2:5, :8]).all()
assert (fs[0].section[3, 2:5, 3] == dat[3, 2:5, 3]).all()
assert (fs[0].section[3:6, :, :][:3, :3, :3] ==
np.array([[[330, 331, 332],
[341, 342, 343],
[352, 353, 354]],
[[440, 441, 442],
[451, 452, 453],
[462, 463, 464]],
[[550, 551, 552],
[561, 562, 563],
[572, 573, 574]]])).all()
assert (fs[0].section[:, :, :][:3, :2, :2] ==
np.array([[[0, 1],
[11, 12]],
[[110, 111],
[121, 122]],
[[220, 221],
[231, 232]]])).all()
assert (fs[0].section[:, 2, :] == dat[:, 2, :]).all()
assert (fs[0].section[:, 2:5, :] == dat[:, 2:5, :]).all()
assert (fs[0].section[3:6, 3, :] == dat[3:6, 3, :]).all()
assert (fs[0].section[3:6, 3:7, :] == dat[3:6, 3:7, :]).all()
def test_section_data_square(self):
a = np.arange(4).reshape((2, 2))
hdu = fits.PrimaryHDU(a)
hdu.writeto(self.temp('test_new.fits'))
hdul = fits.open(self.temp('test_new.fits'))
d = hdul[0]
dat = hdul[0].data
assert (d.section[:, :] == dat[:, :]).all()
assert (d.section[0, :] == dat[0, :]).all()
assert (d.section[1, :] == dat[1, :]).all()
assert (d.section[:, 0] == dat[:, 0]).all()
assert (d.section[:, 1] == dat[:, 1]).all()
assert (d.section[0, 0] == dat[0, 0]).all()
assert (d.section[0, 1] == dat[0, 1]).all()
assert (d.section[1, 0] == dat[1, 0]).all()
assert (d.section[1, 1] == dat[1, 1]).all()
assert (d.section[0:1, 0:1] == dat[0:1, 0:1]).all()
assert (d.section[0:2, 0:1] == dat[0:2, 0:1]).all()
assert (d.section[0:1, 0:2] == dat[0:1, 0:2]).all()
assert (d.section[0:2, 0:2] == dat[0:2, 0:2]).all()
def test_section_data_cube(self):
a = np.arange(18).reshape((2, 3, 3))
hdu = fits.PrimaryHDU(a)
hdu.writeto(self.temp('test_new.fits'))
hdul = fits.open(self.temp('test_new.fits'))
d = hdul[0]
dat = hdul[0].data
assert (d.section[:, :, :] == dat[:, :, :]).all()
assert (d.section[:, :] == dat[:, :]).all()
assert (d.section[:] == dat[:]).all()
assert (d.section[0, :, :] == dat[0, :, :]).all()
assert (d.section[1, :, :] == dat[1, :, :]).all()
assert (d.section[0, 0, :] == dat[0, 0, :]).all()
assert (d.section[0, 1, :] == dat[0, 1, :]).all()
assert (d.section[0, 2, :] == dat[0, 2, :]).all()
assert (d.section[1, 0, :] == dat[1, 0, :]).all()
assert (d.section[1, 1, :] == dat[1, 1, :]).all()
assert (d.section[1, 2, :] == dat[1, 2, :]).all()
assert (d.section[0, 0, 0] == dat[0, 0, 0]).all()
assert (d.section[0, 0, 1] == dat[0, 0, 1]).all()
assert (d.section[0, 0, 2] == dat[0, 0, 2]).all()
assert (d.section[0, 1, 0] == dat[0, 1, 0]).all()
assert (d.section[0, 1, 1] == dat[0, 1, 1]).all()
assert (d.section[0, 1, 2] == dat[0, 1, 2]).all()
assert (d.section[0, 2, 0] == dat[0, 2, 0]).all()
assert (d.section[0, 2, 1] == dat[0, 2, 1]).all()
assert (d.section[0, 2, 2] == dat[0, 2, 2]).all()
assert (d.section[1, 0, 0] == dat[1, 0, 0]).all()
assert (d.section[1, 0, 1] == dat[1, 0, 1]).all()
assert (d.section[1, 0, 2] == dat[1, 0, 2]).all()
assert (d.section[1, 1, 0] == dat[1, 1, 0]).all()
assert (d.section[1, 1, 1] == dat[1, 1, 1]).all()
assert (d.section[1, 1, 2] == dat[1, 1, 2]).all()
assert (d.section[1, 2, 0] == dat[1, 2, 0]).all()
assert (d.section[1, 2, 1] == dat[1, 2, 1]).all()
assert (d.section[1, 2, 2] == dat[1, 2, 2]).all()
assert (d.section[:, 0, 0] == dat[:, 0, 0]).all()
assert (d.section[:, 0, 1] == dat[:, 0, 1]).all()
assert (d.section[:, 0, 2] == dat[:, 0, 2]).all()
assert (d.section[:, 1, 0] == dat[:, 1, 0]).all()
assert (d.section[:, 1, 1] == dat[:, 1, 1]).all()
assert (d.section[:, 1, 2] == dat[:, 1, 2]).all()
assert (d.section[:, 2, 0] == dat[:, 2, 0]).all()
assert (d.section[:, 2, 1] == dat[:, 2, 1]).all()
assert (d.section[:, 2, 2] == dat[:, 2, 2]).all()
assert (d.section[0, :, 0] == dat[0, :, 0]).all()
assert (d.section[0, :, 1] == dat[0, :, 1]).all()
assert (d.section[0, :, 2] == dat[0, :, 2]).all()
assert (d.section[1, :, 0] == dat[1, :, 0]).all()
assert (d.section[1, :, 1] == dat[1, :, 1]).all()
assert (d.section[1, :, 2] == dat[1, :, 2]).all()
assert (d.section[:, :, 0] == dat[:, :, 0]).all()
assert (d.section[:, :, 1] == dat[:, :, 1]).all()
assert (d.section[:, :, 2] == dat[:, :, 2]).all()
assert (d.section[:, 0, :] == dat[:, 0, :]).all()
assert (d.section[:, 1, :] == dat[:, 1, :]).all()
assert (d.section[:, 2, :] == dat[:, 2, :]).all()
assert (d.section[:, :, 0:1] == dat[:, :, 0:1]).all()
assert (d.section[:, :, 0:2] == dat[:, :, 0:2]).all()
assert (d.section[:, :, 0:3] == dat[:, :, 0:3]).all()
assert (d.section[:, :, 1:2] == dat[:, :, 1:2]).all()
assert (d.section[:, :, 1:3] == dat[:, :, 1:3]).all()
assert (d.section[:, :, 2:3] == dat[:, :, 2:3]).all()
assert (d.section[0:1, 0:1, 0:1] == dat[0:1, 0:1, 0:1]).all()
assert (d.section[0:1, 0:1, 0:2] == dat[0:1, 0:1, 0:2]).all()
assert (d.section[0:1, 0:1, 0:3] == dat[0:1, 0:1, 0:3]).all()
assert (d.section[0:1, 0:1, 1:2] == dat[0:1, 0:1, 1:2]).all()
assert (d.section[0:1, 0:1, 1:3] == dat[0:1, 0:1, 1:3]).all()
assert (d.section[0:1, 0:1, 2:3] == dat[0:1, 0:1, 2:3]).all()
assert (d.section[0:1, 0:2, 0:1] == dat[0:1, 0:2, 0:1]).all()
assert (d.section[0:1, 0:2, 0:2] == dat[0:1, 0:2, 0:2]).all()
assert (d.section[0:1, 0:2, 0:3] == dat[0:1, 0:2, 0:3]).all()
assert (d.section[0:1, 0:2, 1:2] == dat[0:1, 0:2, 1:2]).all()
assert (d.section[0:1, 0:2, 1:3] == dat[0:1, 0:2, 1:3]).all()
assert (d.section[0:1, 0:2, 2:3] == dat[0:1, 0:2, 2:3]).all()
assert (d.section[0:1, 0:3, 0:1] == dat[0:1, 0:3, 0:1]).all()
assert (d.section[0:1, 0:3, 0:2] == dat[0:1, 0:3, 0:2]).all()
assert (d.section[0:1, 0:3, 0:3] == dat[0:1, 0:3, 0:3]).all()
assert (d.section[0:1, 0:3, 1:2] == dat[0:1, 0:3, 1:2]).all()
assert (d.section[0:1, 0:3, 1:3] == dat[0:1, 0:3, 1:3]).all()
assert (d.section[0:1, 0:3, 2:3] == dat[0:1, 0:3, 2:3]).all()
assert (d.section[0:1, 1:2, 0:1] == dat[0:1, 1:2, 0:1]).all()
assert (d.section[0:1, 1:2, 0:2] == dat[0:1, 1:2, 0:2]).all()
assert (d.section[0:1, 1:2, 0:3] == dat[0:1, 1:2, 0:3]).all()
assert (d.section[0:1, 1:2, 1:2] == dat[0:1, 1:2, 1:2]).all()
assert (d.section[0:1, 1:2, 1:3] == dat[0:1, 1:2, 1:3]).all()
assert (d.section[0:1, 1:2, 2:3] == dat[0:1, 1:2, 2:3]).all()
assert (d.section[0:1, 1:3, 0:1] == dat[0:1, 1:3, 0:1]).all()
assert (d.section[0:1, 1:3, 0:2] == dat[0:1, 1:3, 0:2]).all()
assert (d.section[0:1, 1:3, 0:3] == dat[0:1, 1:3, 0:3]).all()
assert (d.section[0:1, 1:3, 1:2] == dat[0:1, 1:3, 1:2]).all()
assert (d.section[0:1, 1:3, 1:3] == dat[0:1, 1:3, 1:3]).all()
assert (d.section[0:1, 1:3, 2:3] == dat[0:1, 1:3, 2:3]).all()
assert (d.section[1:2, 0:1, 0:1] == dat[1:2, 0:1, 0:1]).all()
assert (d.section[1:2, 0:1, 0:2] == dat[1:2, 0:1, 0:2]).all()
assert (d.section[1:2, 0:1, 0:3] == dat[1:2, 0:1, 0:3]).all()
assert (d.section[1:2, 0:1, 1:2] == dat[1:2, 0:1, 1:2]).all()
assert (d.section[1:2, 0:1, 1:3] == dat[1:2, 0:1, 1:3]).all()
assert (d.section[1:2, 0:1, 2:3] == dat[1:2, 0:1, 2:3]).all()
assert (d.section[1:2, 0:2, 0:1] == dat[1:2, 0:2, 0:1]).all()
assert (d.section[1:2, 0:2, 0:2] == dat[1:2, 0:2, 0:2]).all()
assert (d.section[1:2, 0:2, 0:3] == dat[1:2, 0:2, 0:3]).all()
assert (d.section[1:2, 0:2, 1:2] == dat[1:2, 0:2, 1:2]).all()
assert (d.section[1:2, 0:2, 1:3] == dat[1:2, 0:2, 1:3]).all()
assert (d.section[1:2, 0:2, 2:3] == dat[1:2, 0:2, 2:3]).all()
assert (d.section[1:2, 0:3, 0:1] == dat[1:2, 0:3, 0:1]).all()
assert (d.section[1:2, 0:3, 0:2] == dat[1:2, 0:3, 0:2]).all()
assert (d.section[1:2, 0:3, 0:3] == dat[1:2, 0:3, 0:3]).all()
assert (d.section[1:2, 0:3, 1:2] == dat[1:2, 0:3, 1:2]).all()
assert (d.section[1:2, 0:3, 1:3] == dat[1:2, 0:3, 1:3]).all()
assert (d.section[1:2, 0:3, 2:3] == dat[1:2, 0:3, 2:3]).all()
assert (d.section[1:2, 1:2, 0:1] == dat[1:2, 1:2, 0:1]).all()
assert (d.section[1:2, 1:2, 0:2] == dat[1:2, 1:2, 0:2]).all()
assert (d.section[1:2, 1:2, 0:3] == dat[1:2, 1:2, 0:3]).all()
assert (d.section[1:2, 1:2, 1:2] == dat[1:2, 1:2, 1:2]).all()
assert (d.section[1:2, 1:2, 1:3] == dat[1:2, 1:2, 1:3]).all()
assert (d.section[1:2, 1:2, 2:3] == dat[1:2, 1:2, 2:3]).all()
assert (d.section[1:2, 1:3, 0:1] == dat[1:2, 1:3, 0:1]).all()
assert (d.section[1:2, 1:3, 0:2] == dat[1:2, 1:3, 0:2]).all()
assert (d.section[1:2, 1:3, 0:3] == dat[1:2, 1:3, 0:3]).all()
assert (d.section[1:2, 1:3, 1:2] == dat[1:2, 1:3, 1:2]).all()
assert (d.section[1:2, 1:3, 1:3] == dat[1:2, 1:3, 1:3]).all()
assert (d.section[1:2, 1:3, 2:3] == dat[1:2, 1:3, 2:3]).all()
def test_section_data_four(self):
a = np.arange(256).reshape((4, 4, 4, 4))
hdu = fits.PrimaryHDU(a)
hdu.writeto(self.temp('test_new.fits'))
hdul = fits.open(self.temp('test_new.fits'))
d = hdul[0]
dat = hdul[0].data
assert (d.section[:, :, :, :] == dat[:, :, :, :]).all()
assert (d.section[:, :, :] == dat[:, :, :]).all()
assert (d.section[:, :] == dat[:, :]).all()
assert (d.section[:] == dat[:]).all()
assert (d.section[0, :, :, :] == dat[0, :, :, :]).all()
assert (d.section[0, :, 0, :] == dat[0, :, 0, :]).all()
assert (d.section[:, :, 0, :] == dat[:, :, 0, :]).all()
assert (d.section[:, 1, 0, :] == dat[:, 1, 0, :]).all()
assert (d.section[:, :, :, 1] == dat[:, :, :, 1]).all()
def test_section_data_scaled(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/143
This is like test_section_data_square but uses a file containing scaled
image data, to test that sections can work correctly with scaled data.
"""
hdul = fits.open(self.data('scale.fits'))
d = hdul[0]
dat = hdul[0].data
assert (d.section[:, :] == dat[:, :]).all()
assert (d.section[0, :] == dat[0, :]).all()
assert (d.section[1, :] == dat[1, :]).all()
assert (d.section[:, 0] == dat[:, 0]).all()
assert (d.section[:, 1] == dat[:, 1]).all()
assert (d.section[0, 0] == dat[0, 0]).all()
assert (d.section[0, 1] == dat[0, 1]).all()
assert (d.section[1, 0] == dat[1, 0]).all()
assert (d.section[1, 1] == dat[1, 1]).all()
assert (d.section[0:1, 0:1] == dat[0:1, 0:1]).all()
assert (d.section[0:2, 0:1] == dat[0:2, 0:1]).all()
assert (d.section[0:1, 0:2] == dat[0:1, 0:2]).all()
assert (d.section[0:2, 0:2] == dat[0:2, 0:2]).all()
# Test without having accessed the full data first
hdul = fits.open(self.data('scale.fits'))
d = hdul[0]
assert (d.section[:, :] == dat[:, :]).all()
assert (d.section[0, :] == dat[0, :]).all()
assert (d.section[1, :] == dat[1, :]).all()
assert (d.section[:, 0] == dat[:, 0]).all()
assert (d.section[:, 1] == dat[:, 1]).all()
assert (d.section[0, 0] == dat[0, 0]).all()
assert (d.section[0, 1] == dat[0, 1]).all()
assert (d.section[1, 0] == dat[1, 0]).all()
assert (d.section[1, 1] == dat[1, 1]).all()
assert (d.section[0:1, 0:1] == dat[0:1, 0:1]).all()
assert (d.section[0:2, 0:1] == dat[0:2, 0:1]).all()
assert (d.section[0:1, 0:2] == dat[0:1, 0:2]).all()
assert (d.section[0:2, 0:2] == dat[0:2, 0:2]).all()
assert not d._data_loaded
def test_do_not_scale_image_data(self):
hdul = fits.open(self.data('scale.fits'), do_not_scale_image_data=True)
assert hdul[0].data.dtype == np.dtype('>i2')
hdul = fits.open(self.data('scale.fits'))
assert hdul[0].data.dtype == np.dtype('float32')
def test_append_uint_data(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/56
(BZERO and BSCALE added in the wrong location when appending scaled
data)
"""
fits.writeto(self.temp('test_new.fits'), data=np.array([],
dtype='uint8'))
d = np.zeros([100, 100]).astype('uint16')
fits.append(self.temp('test_new.fits'), data=d)
f = fits.open(self.temp('test_new.fits'), uint=True)
assert f[1].data.dtype == 'uint16'
def test_uint_header_consistency(self):
"""
Regression test for https://github.com/astropy/astropy/issues/2305
This ensures that an HDU containing unsigned integer data always has
the apppriate BZERO value in its header.
"""
for int_size in (16, 32, 64):
# Just make an array of some unsigned ints that wouldn't fit in a
# signed int array of the same bit width
max_uint = (2 ** int_size) - 1
if int_size == 64:
# Otherwise may get an overflow error, at least on Python 2
max_uint = np.uint64(int_size)
dtype = 'uint%d' % int_size
arr = np.empty(100, dtype=dtype)
arr.fill(max_uint)
arr -= np.arange(100, dtype=dtype)
uint_hdu = fits.PrimaryHDU(data=arr)
assert np.all(uint_hdu.data == arr)
assert uint_hdu.data.dtype.name == 'uint%d' % int_size
assert 'BZERO' in uint_hdu.header
assert uint_hdu.header['BZERO'] == (2 ** (int_size - 1))
filename = 'uint%d.fits' % int_size
uint_hdu.writeto(self.temp(filename))
with fits.open(self.temp(filename), uint=True) as hdul:
new_uint_hdu = hdul[0]
assert np.all(new_uint_hdu.data == arr)
assert new_uint_hdu.data.dtype.name == 'uint%d' % int_size
assert 'BZERO' in new_uint_hdu.header
assert new_uint_hdu.header['BZERO'] == (2 ** (int_size - 1))
def test_blanks(self):
"""Test image data with blank spots in it (which should show up as
NaNs in the data array.
"""
arr = np.zeros((10, 10), dtype=np.int32)
# One row will be blanks
arr[1] = 999
hdu = fits.ImageHDU(data=arr)
hdu.header['BLANK'] = 999
hdu.writeto(self.temp('test_new.fits'))
hdul = fits.open(self.temp('test_new.fits'))
assert np.isnan(hdul[1].data[1]).all()
def test_bzero_with_floats(self):
"""Test use of the BZERO keyword in an image HDU containing float
data.
"""
arr = np.zeros((10, 10)) - 1
hdu = fits.ImageHDU(data=arr)
hdu.header['BZERO'] = 1.0
hdu.writeto(self.temp('test_new.fits'))
hdul = fits.open(self.temp('test_new.fits'))
arr += 1
assert (hdul[1].data == arr).all()
def test_rewriting_large_scaled_image(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/84 and
https://aeon.stsci.edu/ssb/trac/pyfits/ticket/101
"""
hdul = fits.open(self.data('fixed-1890.fits'))
orig_data = hdul[0].data
with ignore_warnings():
hdul.writeto(self.temp('test_new.fits'), clobber=True)
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[0].data == orig_data).all()
hdul.close()
# Just as before, but this time don't touch hdul[0].data before writing
# back out--this is the case that failed in
# https://aeon.stsci.edu/ssb/trac/pyfits/ticket/84
hdul = fits.open(self.data('fixed-1890.fits'))
with ignore_warnings():
hdul.writeto(self.temp('test_new.fits'), clobber=True)
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[0].data == orig_data).all()
hdul.close()
# Test opening/closing/reopening a scaled file in update mode
hdul = fits.open(self.data('fixed-1890.fits'),
do_not_scale_image_data=True)
hdul.writeto(self.temp('test_new.fits'), clobber=True,
output_verify='silentfix')
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
orig_data = hdul[0].data
hdul.close()
hdul = fits.open(self.temp('test_new.fits'), mode='update')
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[0].data == orig_data).all()
hdul = fits.open(self.temp('test_new.fits'))
hdul.close()
def test_image_update_header(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/105
Replacing the original header to an image HDU and saving should update
the NAXISn keywords appropriately and save the image data correctly.
"""
# Copy the original file before saving to it
self.copy_file('test0.fits')
with fits.open(self.temp('test0.fits'), mode='update') as hdul:
orig_data = hdul[1].data.copy()
hdr_copy = hdul[1].header.copy()
del hdr_copy['NAXIS*']
hdul[1].header = hdr_copy
with fits.open(self.temp('test0.fits')) as hdul:
assert (orig_data == hdul[1].data).all()
def test_open_scaled_in_update_mode(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/119
(Don't update scaled image data if the data is not read)
This ensures that merely opening and closing a file containing scaled
image data does not cause any change to the data (or the header).
Changes should only occur if the data is accessed.
"""
# Copy the original file before making any possible changes to it
self.copy_file('scale.fits')
mtime = os.stat(self.temp('scale.fits')).st_mtime
time.sleep(1)
fits.open(self.temp('scale.fits'), mode='update').close()
# Ensure that no changes were made to the file merely by immediately
# opening and closing it.
assert mtime == os.stat(self.temp('scale.fits')).st_mtime
# Insert a slight delay to ensure the mtime does change when the file
# is changed
time.sleep(1)
hdul = fits.open(self.temp('scale.fits'), 'update')
orig_data = hdul[0].data
hdul.close()
# Now the file should be updated with the rescaled data
assert mtime != os.stat(self.temp('scale.fits')).st_mtime
hdul = fits.open(self.temp('scale.fits'), mode='update')
assert hdul[0].data.dtype == np.dtype('>f4')
assert hdul[0].header['BITPIX'] == -32
assert 'BZERO' not in hdul[0].header
assert 'BSCALE' not in hdul[0].header
assert (orig_data == hdul[0].data).all()
# Try reshaping the data, then closing and reopening the file; let's
# see if all the changes are preseved properly
hdul[0].data.shape = (42, 10)
hdul.close()
hdul = fits.open(self.temp('scale.fits'))
assert hdul[0].shape == (42, 10)
assert hdul[0].data.dtype == np.dtype('>f4')
assert hdul[0].header['BITPIX'] == -32
assert 'BZERO' not in hdul[0].header
assert 'BSCALE' not in hdul[0].header
def test_scale_back(self):
"""A simple test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/120
The scale_back feature for image HDUs.
"""
self.copy_file('scale.fits')
with fits.open(self.temp('scale.fits'), mode='update',
scale_back=True) as hdul:
orig_bitpix = hdul[0].header['BITPIX']
orig_bzero = hdul[0].header['BZERO']
orig_bscale = hdul[0].header['BSCALE']
orig_data = hdul[0].data.copy()
hdul[0].data[0] = 0
with fits.open(self.temp('scale.fits'),
do_not_scale_image_data=True) as hdul:
assert hdul[0].header['BITPIX'] == orig_bitpix
assert hdul[0].header['BZERO'] == orig_bzero
assert hdul[0].header['BSCALE'] == orig_bscale
zero_point = int(math.floor(-orig_bzero / orig_bscale))
assert (hdul[0].data[0] == zero_point).all()
with fits.open(self.temp('scale.fits')) as hdul:
assert (hdul[0].data[1:] == orig_data[1:]).all()
def test_image_none(self):
"""
Regression test for https://github.com/spacetelescope/PyFITS/issues/27
"""
with fits.open(self.data('test0.fits')) as h:
h[1].data
h[1].data = None
h[1].writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as h:
assert h[1].data is None
assert h[1].header['NAXIS'] == 0
assert 'NAXIS1' not in h[1].header
assert 'NAXIS2' not in h[1].header
class TestCompressedImage(PyfitsTestCase):
def test_empty(self):
"""
Regression test for https://github.com/astropy/astropy/issues/2595
"""
hdu = fits.CompImageHDU()
hdu.data is None
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits'), mode='update') as hdul:
assert len(hdul) == 2
assert isinstance(hdul[1], fits.CompImageHDU)
assert hdul[1].data is None
# Now test replacing the empty data with an array and see what
# happens
hdul[1].data = np.arange(100, dtype=np.int32)
with fits.open(self.temp('test.fits')) as hdul:
assert len(hdul) == 2
assert isinstance(hdul[1], fits.CompImageHDU)
assert np.all(hdul[1].data == np.arange(100, dtype=np.int32))
def test_comp_image(self):
argslist = [
(np.zeros((2, 10, 10), dtype=np.float32), 'RICE_1', 16),
(np.zeros((2, 10, 10), dtype=np.float32), 'GZIP_1', -0.01),
(np.zeros((100, 100)) + 1, 'HCOMPRESS_1', 16)
]
for byte_order in ('<', '>'):
for args in argslist:
yield (self._test_comp_image,) + args + (byte_order,)
@ignore_warnings(PyfitsPendingDeprecationWarning)
def _test_comp_image(self, data, compression_type, quantize_level,
byte_order):
data = data.newbyteorder(byte_order)
primary_hdu = fits.PrimaryHDU()
ofd = fits.HDUList(primary_hdu)
chdu = fits.CompImageHDU(data, name='SCI',
compressionType=compression_type,
quantizeLevel=quantize_level)
ofd.append(chdu)
ofd.writeto(self.temp('test_new.fits'), clobber=True)
ofd.close()
with fits.open(self.temp('test_new.fits')) as fd:
assert (fd[1].data == data).all()
assert fd[1].header['NAXIS'] == chdu.header['NAXIS']
assert fd[1].header['NAXIS1'] == chdu.header['NAXIS1']
assert fd[1].header['NAXIS2'] == chdu.header['NAXIS2']
assert fd[1].header['BITPIX'] == chdu.header['BITPIX']
@ignore_warnings(PyfitsPendingDeprecationWarning)
def test_comp_image_hcompression_1_invalid_data(self):
"""
Tests compression with the HCOMPRESS_1 algorithm with data that is
not 2D and has a non-2D tile size.
"""
assert_raises(ValueError, fits.CompImageHDU,
np.zeros((2, 10, 10), dtype=np.float32), name='SCI',
compressionType='HCOMPRESS_1', quantizeLevel=16,
tileSize=[2, 10, 10])
@ignore_warnings(PyfitsPendingDeprecationWarning)
def test_comp_image_hcompress_image_stack(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/171
Tests that data containing more than two dimensions can be
compressed with HCOMPRESS_1 so long as the user-supplied tile size can
be flattened to two dimensions.
"""
cube = np.arange(300, dtype=np.float32).reshape((3, 10, 10))
hdu = fits.CompImageHDU(data=cube, name='SCI',
compressionType='HCOMPRESS_1',
quantizeLevel=16, tileSize=[5, 5, 1])
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
assert (hdul['SCI'].data == cube).all()
def test_subtractive_dither_seed(self):
"""
Regression test for https://github.com/spacetelescope/PyFITS/issues/32
Ensure that when floating point data is compressed with the
SUBTRACTIVE_DITHER_1 quantization method that the correct ZDITHER0 seed
is added to the header, and that the data can be correctly
decompressed.
"""
array = np.arange(100.0).reshape(10, 10)
csum = (array[0].view('uint8').sum() % 10000) + 1
hdu = fits.CompImageHDU(data=array,
quantize_method=SUBTRACTIVE_DITHER_1,
dither_seed=DITHER_SEED_CHECKSUM)
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
assert isinstance(hdul[1], fits.CompImageHDU)
assert 'ZQUANTIZ' in hdul[1]._header
assert hdul[1]._header['ZQUANTIZ'] == 'SUBTRACTIVE_DITHER_1'
assert 'ZDITHER0' in hdul[1]._header
assert hdul[1]._header['ZDITHER0'] == csum
assert np.all(hdul[1].data == array)
def test_disable_image_compression(self):
with catch_warnings():
# No warnings should be displayed in this case
warnings.simplefilter('error')
with fits.open(self.data('comp.fits'),
disable_image_compression=True) as hdul:
# The compressed image HDU should show up as a BinTableHDU, but
# *not* a CompImageHDU
assert isinstance(hdul[1], fits.BinTableHDU)
assert not isinstance(hdul[1], fits.CompImageHDU)
with fits.open(self.data('comp.fits')) as hdul:
assert isinstance(hdul[1], fits.CompImageHDU)
def test_open_comp_image_in_update_mode(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/167
Similar to test_open_scaled_in_update_mode(), but specifically for
compressed images.
"""
# Copy the original file before making any possible changes to it
self.copy_file('comp.fits')
mtime = os.stat(self.temp('comp.fits')).st_mtime
time.sleep(1)
fits.open(self.temp('comp.fits'), mode='update').close()
# Ensure that no changes were made to the file merely by immediately
# opening and closing it.
assert mtime == os.stat(self.temp('comp.fits')).st_mtime
def test_open_scaled_in_update_mode_compressed(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/88 2
Identical to test_open_scaled_in_update_mode() but with a compressed
version of the scaled image.
"""
# Copy+compress the original file before making any possible changes to
# it
with fits.open(self.data('scale.fits'),
do_not_scale_image_data=True) as hdul:
chdu = fits.CompImageHDU(data=hdul[0].data,
header=hdul[0].header)
chdu.writeto(self.temp('scale.fits'))
mtime = os.stat(self.temp('scale.fits')).st_mtime
time.sleep(1)
fits.open(self.temp('scale.fits'), mode='update').close()
# Ensure that no changes were made to the file merely by immediately
# opening and closing it.
assert mtime == os.stat(self.temp('scale.fits')).st_mtime
# Insert a slight delay to ensure the mtime does change when the file
# is changed
time.sleep(1)
hdul = fits.open(self.temp('scale.fits'), 'update')
hdul[1].data
hdul.close()
# Now the file should be updated with the rescaled data
assert mtime != os.stat(self.temp('scale.fits')).st_mtime
hdul = fits.open(self.temp('scale.fits'), mode='update')
assert hdul[1].data.dtype == np.dtype('float32')
assert hdul[1].header['BITPIX'] == -32
assert 'BZERO' not in hdul[1].header
assert 'BSCALE' not in hdul[1].header
# Try reshaping the data, then closing and reopening the file; let's
# see if all the changes are preseved properly
hdul[1].data.shape = (42, 10)
hdul.close()
hdul = fits.open(self.temp('scale.fits'))
assert hdul[1].shape == (42, 10)
assert hdul[1].data.dtype == np.dtype('float32')
assert hdul[1].header['BITPIX'] == -32
assert 'BZERO' not in hdul[1].header
assert 'BSCALE' not in hdul[1].header
def test_write_comp_hdu_direct_from_existing(self):
with fits.open(self.data('comp.fits')) as hdul:
hdul[1].writeto(self.temp('test.fits'))
with fits.open(self.data('comp.fits')) as hdul1:
with fits.open(self.temp('test.fits')) as hdul2:
assert np.all(hdul1[1].data == hdul2[1].data)
assert comparerecords(hdul1[1].compressed_data,
hdul2[1].compressed_data)
def test_rewriting_large_scaled_image_compressed(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/88 1
Identical to test_rewriting_large_scaled_image() but with a compressed
image.
"""
with fits.open(self.data('fixed-1890.fits'),
do_not_scale_image_data=True) as hdul:
chdu = fits.CompImageHDU(data=hdul[0].data,
header=hdul[0].header)
chdu.writeto(self.temp('fixed-1890-z.fits'))
hdul = fits.open(self.temp('fixed-1890-z.fits'))
orig_data = hdul[1].data
with ignore_warnings():
hdul.writeto(self.temp('test_new.fits'), clobber=True)
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[1].data == orig_data).all()
hdul.close()
# Just as before, but this time don't touch hdul[0].data before writing
# back out--this is the case that failed in
# https://aeon.stsci.edu/ssb/trac/pyfits/ticket/84
hdul = fits.open(self.temp('fixed-1890-z.fits'))
with ignore_warnings():
hdul.writeto(self.temp('test_new.fits'), clobber=True)
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[1].data == orig_data).all()
hdul.close()
# Test opening/closing/reopening a scaled file in update mode
hdul = fits.open(self.temp('fixed-1890-z.fits'),
do_not_scale_image_data=True)
hdul.writeto(self.temp('test_new.fits'), clobber=True,
output_verify='silentfix')
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
orig_data = hdul[1].data
hdul.close()
hdul = fits.open(self.temp('test_new.fits'), mode='update')
hdul.close()
hdul = fits.open(self.temp('test_new.fits'))
assert (hdul[1].data == orig_data).all()
hdul = fits.open(self.temp('test_new.fits'))
hdul.close()
def test_scale_back_compressed(self):
"""
Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/88 3
Identical to test_scale_back() but uses a compressed image.
"""
# Create a compressed version of the scaled image
with fits.open(self.data('scale.fits'),
do_not_scale_image_data=True) as hdul:
chdu = fits.CompImageHDU(data=hdul[0].data,
header=hdul[0].header)
chdu.writeto(self.temp('scale.fits'))
with fits.open(self.temp('scale.fits'), mode='update',
scale_back=True) as hdul:
orig_bitpix = hdul[1].header['BITPIX']
orig_bzero = hdul[1].header['BZERO']
orig_bscale = hdul[1].header['BSCALE']
orig_data = hdul[1].data.copy()
hdul[1].data[0] = 0
with fits.open(self.temp('scale.fits'),
do_not_scale_image_data=True) as hdul:
assert hdul[1].header['BITPIX'] == orig_bitpix
assert hdul[1].header['BZERO'] == orig_bzero
assert hdul[1].header['BSCALE'] == orig_bscale
zero_point = int(math.floor(-orig_bzero / orig_bscale))
assert (hdul[1].data[0] == zero_point).all()
with fits.open(self.temp('scale.fits')) as hdul:
assert (hdul[1].data[1:] == orig_data[1:]).all()
# Extra test to ensure that after everything the data is still the
# same as in the original uncompressed version of the image
with fits.open(self.data('scale.fits')) as hdul2:
# Recall we made the same modification to the data in hdul
# above
hdul2[0].data[0] = 0
assert (hdul[1].data == hdul2[0].data).all()
def test_lossless_gzip_compression(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/198"""
noise = np.random.normal(size=(1000, 1000))
chdu1 = fits.CompImageHDU(data=noise, compressionType='GZIP_1')
# First make a test image with lossy compression and make sure it
# wasn't compressed perfectly. This shouldn't happen ever, but just to
# make sure the test non-trivial.
chdu1.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as h:
assert np.abs(noise - h[1].data).max() > 0.0
del h
chdu2 = fits.CompImageHDU(data=noise, compressionType='GZIP_1',
quantizeLevel=0.0) # No quantization
with ignore_warnings():
chdu2.writeto(self.temp('test.fits'), clobber=True)
with fits.open(self.temp('test.fits')) as h:
assert (noise == h[1].data).all()
def test_compression_column_tforms(self):
"""Regression test for https://aeon.stsci.edu/ssb/trac/pyfits/ticket/199"""
# Some interestingly tiled data so that some of it is quantized and
# some of it ends up just getting gzip-compressed
data2 = ((np.arange(1, 8, dtype=np.float32) * 10)[:, np.newaxis] +
np.arange(1, 7))
np.random.seed(1337)
data1 = np.random.uniform(size=(6 * 4, 7 * 4))
data1[:data2.shape[0], :data2.shape[1]] = data2
chdu = fits.CompImageHDU(data1, compressionType='RICE_1',
tileSize=(6, 7))
chdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits'),
disable_image_compression=True) as h:
assert h[1].header['TFORM1'] == '1PB(30)'
assert h[1].header['TFORM2'] == '1PB(359)'
def test_compression_update_header(self):
"""Regression test for
https://github.com/spacetelescope/PyFITS/issues/23
"""
self.copy_file('comp.fits')
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
assert isinstance(hdul[1], fits.CompImageHDU)
hdul[1].header['test1'] = 'test'
hdul[1]._header['test2'] = 'test2'
with fits.open(self.temp('comp.fits')) as hdul:
assert 'test1' in hdul[1].header
assert hdul[1].header['test1'] == 'test'
assert 'test2' in hdul[1].header
assert hdul[1].header['test2'] == 'test2'
# Test update via index now:
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
hdr = hdul[1].header
hdr[hdr.index('TEST1')] = 'foo'
with fits.open(self.temp('comp.fits')) as hdul:
assert hdul[1].header['TEST1'] == 'foo'
# Test slice updates
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
hdul[1].header['TEST*'] = 'qux'
with fits.open(self.temp('comp.fits')) as hdul:
assert list(hdul[1].header['TEST*'].values()) == ['qux', 'qux']
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
hdr = hdul[1].header
idx = hdr.index('TEST1')
hdr[idx:idx + 2] = 'bar'
with fits.open(self.temp('comp.fits')) as hdul:
assert list(hdul[1].header['TEST*'].values()) == ['bar', 'bar']
# Test updating a specific COMMENT card duplicate
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
hdul[1].header[('COMMENT', 1)] = 'I am fire. I am death!'
with fits.open(self.temp('comp.fits')) as hdul:
assert hdul[1].header['COMMENT'][1] == 'I am fire. I am death!'
assert hdul[1]._header['COMMENT'][1] == 'I am fire. I am death!'
# Test deleting by keyword and by slice
with fits.open(self.temp('comp.fits'), mode='update') as hdul:
hdr = hdul[1].header
del hdr['COMMENT']
idx = hdr.index('TEST1')
del hdr[idx:idx + 2]
with fits.open(self.temp('comp.fits')) as hdul:
assert 'COMMENT' not in hdul[1].header
assert 'COMMENT' not in hdul[1]._header
assert 'TEST1' not in hdul[1].header
assert 'TEST1' not in hdul[1]._header
assert 'TEST2' not in hdul[1].header
assert 'TEST2' not in hdul[1]._header
def test_compression_update_header_with_reserved(self):
"""
Ensure that setting reserved keywords related to the table data
structure on CompImageHDU image headers fails.
"""
def test_set_keyword(hdr, keyword, value):
with catch_warnings(record=True) as w:
hdr[keyword] = value
assert len(w) == 1
assert str(w[0].message).startswith(
"Keyword %r is reserved" % keyword)
assert keyword not in hdr
with fits.open(self.data('comp.fits')) as hdul:
hdr = hdul[1].header
test_set_keyword(hdr, 'TFIELDS', 8)
test_set_keyword(hdr, 'TTYPE1', 'Foo')
test_set_keyword(hdr, 'ZCMPTYPE', 'ASDF')
test_set_keyword(hdr, 'ZVAL1', 'Foo')
def test_compression_header_append(self):
with fits.open(self.data('comp.fits')) as hdul:
imghdr = hdul[1].header
tblhdr = hdul[1]._header
with catch_warnings(record=True) as w:
imghdr.append('TFIELDS')
assert len(w) == 1
assert 'TFIELDS' not in imghdr
imghdr.append(('FOO', 'bar', 'qux'), end=True)
assert 'FOO' in imghdr
assert imghdr[-1] == 'bar'
assert 'FOO' in tblhdr
assert tblhdr[-1] == 'bar'
imghdr.append(('CHECKSUM', 'abcd1234'))
assert 'CHECKSUM' in imghdr
assert imghdr['CHECKSUM'] == 'abcd1234'
assert 'CHECKSUM' not in tblhdr
assert 'ZHECKSUM' in tblhdr
assert tblhdr['ZHECKSUM'] == 'abcd1234'
def test_compression_header_insert(self):
with fits.open(self.data('comp.fits')) as hdul:
imghdr = hdul[1].header
tblhdr = hdul[1]._header
# First try inserting a restricted keyword
with catch_warnings(record=True) as w:
imghdr.insert(1000, 'TFIELDS')
assert len(w) == 1
assert 'TFIELDS' not in imghdr
assert tblhdr.count('TFIELDS') == 1
# First try keyword-relative insert
imghdr.insert('TELESCOP', ('OBSERVER', 'Phil Plait'))
assert 'OBSERVER' in imghdr
assert imghdr.index('OBSERVER') == imghdr.index('TELESCOP') - 1
assert 'OBSERVER' in tblhdr
assert tblhdr.index('OBSERVER') == tblhdr.index('TELESCOP') - 1
# Next let's see if an index-relative insert winds up being
# sensible
idx = imghdr.index('OBSERVER')
imghdr.insert('OBSERVER', ('FOO',))
assert 'FOO' in imghdr
assert imghdr.index('FOO') == idx
assert 'FOO' in tblhdr
assert tblhdr.index('FOO') == tblhdr.index('OBSERVER') - 1
def test_compression_header_set_before_after(self):
with fits.open(self.data('comp.fits')) as hdul:
imghdr = hdul[1].header
tblhdr = hdul[1]._header
with catch_warnings(record=True) as w:
imghdr.set('ZBITPIX', 77, 'asdf', after='XTENSION')
assert len(w) == 1
assert 'ZBITPIX' not in imghdr
assert tblhdr.count('ZBITPIX') == 1
assert tblhdr['ZBITPIX'] != 77
# Move GCOUNT before PCOUNT (not that there's any reason you'd
# *want* to do that, but it's just a test...)
imghdr.set('GCOUNT', 99, before='PCOUNT')
assert imghdr.index('GCOUNT') == imghdr.index('PCOUNT') - 1
assert imghdr['GCOUNT'] == 99
assert tblhdr.index('ZGCOUNT') == tblhdr.index('ZPCOUNT') - 1
assert tblhdr['ZGCOUNT'] == 99
assert tblhdr.index('PCOUNT') == 5
assert tblhdr.index('GCOUNT') == 6
assert tblhdr['GCOUNT'] == 1
imghdr.set('GCOUNT', 2, after='PCOUNT')
assert imghdr.index('GCOUNT') == imghdr.index('PCOUNT') + 1
assert imghdr['GCOUNT'] == 2
assert tblhdr.index('ZGCOUNT') == tblhdr.index('ZPCOUNT') + 1
assert tblhdr['ZGCOUNT'] == 2
assert tblhdr.index('PCOUNT') == 5
assert tblhdr.index('GCOUNT') == 6
assert tblhdr['GCOUNT'] == 1
def test_compression_header_append_commentary(self):
"""
Regression test for https://github.com/astropy/astropy/issues/2363
"""
hdu = fits.CompImageHDU(np.array([0], dtype=np.int32))
hdu.header['COMMENT'] = 'hello world'
assert hdu.header['COMMENT'] == ['hello world']
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
assert hdul[1].header['COMMENT'] == ['hello world']
def test_compression_with_gzip_column(self):
"""
Regression test for https://github.com/spacetelescope/PyFITS/issues/71
"""
arr = np.zeros((2, 7000), dtype='float32')
# The first row (which will be the first compressed tile) has a very
# wide range of values that will be difficult to quantize, and should
# result in use of a GZIP_COMPRESSED_DATA column
arr[0] = np.linspace(0, 1, 7000)
arr[1] = np.random.normal(size=7000)
hdu = fits.CompImageHDU(data=arr)
hdu.writeto(self.temp('test.fits'))
with fits.open(self.temp('test.fits')) as hdul:
comp_hdu = hdul[1]
# GZIP-compressed tile should compare exactly
assert np.all(comp_hdu.data[0] == arr[0])
# The second tile uses lossy compression and may be somewhat off,
# so we don't bother comparing it exactly
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