/usr/share/pyshared/pyfits/tests/testPyfitsChecksum.py is in python-pyfits 1:2.4.0-1build1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 | from __future__ import division # confidence high
import unittest
import warnings
import pyfits
import numpy
import numpy as np
import exceptions,os,sys
import os.path
test_dir = os.path.dirname(__file__) + "/"
# Define a junk file for redirection of stdout
jfile = "junkfile.fits"
class TestPyfitsChecksumFunctions(unittest.TestCase):
def setUp(self):
# Perform set up actions (if any)
pass
def tearDown(self):
# Perform clean-up actions (if any)
try:
os.remove('tmp.fits')
except:
pass
def testSampleFile(self):
hdul=pyfits.open(test_dir+'checksum.fits',checksum=True)
hdul.close()
def testImageCreate(self):
n=np.arange(100)
hdu=pyfits.PrimaryHDU(n)
hdu.writeto('tmp.fits',clobber=True,checksum=True)
hdul=pyfits.open('tmp.fits',checksum=True)
hdul.close()
os.remove('tmp.fits')
def testNonstandardChecksum(self):
warnings.filterwarnings("error", message="Warning: Checksum verification failed")
warnings.filterwarnings("error", message="Warning: Datasum verification failed")
hdu = pyfits.PrimaryHDU(np.arange(10.**6))
hdu.writeto('tmp.fits', clobber=True, checksum="nonstandard")
del hdu
hdul = pyfits.open("tmp.fits", checksum="nonstandard") # should pass
self.assertRaises(UserWarning, pyfits.open, "tmp.fits", checksum=True)
self.assertRaises(UserWarning, pyfits.open, "tmp.fits", checksum="standard")
warnings.filterwarnings("default", message="Warning: Checksum verification failed")
warnings.filterwarnings("default", message="Warning: Datasum verification failed")
os.remove("tmp.fits")
def testScaledData(self):
hdul=pyfits.open(test_dir+'scale.fits')
hdul[0].scale('int16','old')
hdul.writeto('tmp.fits',clobber=True,checksum=True)
hdul1=pyfits.open('tmp.fits',checksum=True)
hdul.close()
hdul1.close()
os.remove('tmp.fits')
def testUint16Data(self):
hdul=pyfits.open(test_dir+'o4sp040b0_raw.fits',uint16=1)
hdul.writeto('tmp.fits',clobber=True,checksum=True)
hdul1=pyfits.open('tmp.fits',uint16=1,checksum=True)
hdul.close()
hdul1.close()
os.remove('tmp.fits')
def testGroupsHDUData(self):
imdata = np.arange(100.)
imdata.shape=(10,1,1,2,5)
pdata1 = np.arange(10)+0.1
pdata2 = 42
x = pyfits.GroupData(imdata,parnames=['abc','xyz'],
pardata=[pdata1,pdata2],bitpix=-32)
hdu=pyfits.GroupsHDU(x)
hdu.writeto('tmp.fits',clobber=True,checksum=True)
hdul1=pyfits.open('tmp.fits',checksum=True)
hdul1.close()
os.remove('tmp.fits')
def testBinaryTableData(self):
a1 = np.array(['NGC1001','NGC1002','NGC1003'])
a2 = np.array([11.1,12.3,15.2])
col1 = pyfits.Column(name='target',format='20A',array=a1)
col2=pyfits.Column(name='V_mag',format='E',array=a2)
cols=pyfits.ColDefs([col1, col2])
tbhdu=pyfits.new_table(cols)
tbhdu.writeto('tmp.fits',clobber=True,checksum=True)
hdul=pyfits.open('tmp.fits',checksum=True)
hdul.close()
os.remove('tmp.fits')
def testVariableLengthTableData(self):
c1 = pyfits.Column(name='var',format='PJ()',\
array=np.array([[45.,56],np.array([11,12,13])],'O'))
c2 = pyfits.Column(name='xyz',format='2I',array=[[11,3],[12,4]])
tbhdu=pyfits.new_table([c1,c2])
tbhdu.writeto('tmp.fits',clobber=True,checksum=True)
hdul=pyfits.open('tmp.fits',checksum=True)
hdul.close()
os.remove('tmp.fits')
def testAsciiTableData(self):
a1 = np.array(['abc','def'])
r1 = np.array([11.,12.])
c1 = pyfits.Column(name='abc', format='A3', array=a1)
c2 = pyfits.Column(name='def', format='E', array=r1, bscale=2.3,
bzero=0.6)
c3 = pyfits.Column(name='t1', format='I', array=[91,92,93])
x = pyfits.ColDefs([c1,c2,c3], tbtype='TableHDU')
hdu = pyfits.new_table(x, tbtype='TableHDU')
hdu.writeto('tmp.fits', clobber=True, checksum=True)
hdul=pyfits.open('tmp.fits', checksum=True)
hdul.close()
os.remove('tmp.fits')
def testCompressedImageData(self):
hdul=pyfits.open(test_dir+'comp.fits')
hdul.writeto('tmp.fits',clobber=True,checksum=True)
hdul1=pyfits.open('tmp.fits',checksum=True)
hdul1.close()
os.remove('tmp.fits')
n=np.arange(100,dtype='int16')
hdu=pyfits.ImageHDU(n)
comp_hdu = pyfits.CompImageHDU(hdu.data, hdu.header)
comp_hdu.writeto('tmp.fits',checksum=True)
hdul.close()
hdul=pyfits.open('tmp.fits',checksum=True)
hdul.close()
os.remove('tmp.fits')
n=np.arange(100, dtype='float32')
comp_hdu = pyfits.CompImageHDU(n)
comp_hdu.writeto('tmp.fits',checksum=True)
hdul.close()
hdul=pyfits.open('tmp.fits',checksum=True)
hdul.close()
os.remove('tmp.fits')
def testOpenWithNoKeywords(self):
hdul=pyfits.open(test_dir+'arange.fits',checksum=True)
hdul.close()
def testAppend(self):
hdul=pyfits.open(test_dir+'tb.fits')
hdul.writeto('tmp.fits', clobber=True)
n=np.arange(100)
pyfits.append('tmp.fits',n,checksum=True)
hdul.close()
hdul=pyfits.open('tmp.fits',checksum=True)
self.assertEqual(hdul[0]._checksum, None)
hdul.close()
os.remove('tmp.fits')
def testWritetoConvenience(self):
n=np.arange(100)
pyfits.writeto('tmp.fits',n,clobber=True,checksum=True)
hdul=pyfits.open('tmp.fits',checksum=True)
if not hasattr(hdul[0], '_datasum') or not hdul[0]._datasum:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM keyword")
if not hasattr(hdul[0], '_checksum') or not hdul[0]._checksum:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM keyword")
if not hasattr(hdul[0], '_datasum_comment') or \
not hdul[0]._datasum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM Card comment")
if not hasattr(hdul[0], '_checksum_comment') or \
not hdul[0]._checksum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM Card comment")
hdul.close()
os.remove('tmp.fits')
def testHduWriteto(self):
n=np.arange(100,dtype='int16')
hdu=pyfits.ImageHDU(n)
hdu.writeto('tmp.fits',checksum=True)
hdul=pyfits.open('tmp.fits',checksum=True)
if not hasattr(hdul[0], '_datasum') or not hdul[0]._datasum:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM keyword")
if not hasattr(hdul[0], '_checksum') or not hdul[0]._checksum:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM keyword")
if not hasattr(hdul[0], '_datasum_comment') or \
not hdul[0]._datasum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM Card comment")
if not hasattr(hdul[0], '_checksum_comment') or \
not hdul[0]._checksum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM Card comment")
hdul.close()
os.remove('tmp.fits')
def testDatasumOnly(self):
n=np.arange(100,dtype='int16')
hdu=pyfits.ImageHDU(n)
hdu.writeto('tmp.fits',clobber=True,checksum='datasum')
hdul=pyfits.open('tmp.fits',checksum=True)
if not hasattr(hdul[0], '_datasum') or not hdul[0]._datasum:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM keyword")
if not hasattr(hdul[0], '_checksum') or hdul[0]._checksum:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM keyword")
if not hasattr(hdul[0], '_datasum_comment') or \
not hdul[0]._datasum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing DATASUM Card comment")
if not hasattr(hdul[0], '_checksum_comment') or \
hdul[0]._checksum_comment:
os.remove('tmp.fits')
self.fail(msg="Missing CHECKSUM Card comment")
hdul.close()
os.remove('tmp.fits')
if __name__ == '__main__':
unittest.main()
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