/usr/share/pyshared/pyfits/tests/testPyfitsTable.py is in python-pyfits 1:2.4.0-1build1.
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import unittest
import pyfits
import numpy
import exceptions,os,sys
import numpy as num
from pyfits import rec
from numpy import char as chararray
import os.path
test_dir = os.path.dirname(__file__) + "/"
# Define a junk file for redirection of stdout
jfile = "junkfile.fits"
def comparefloats(a, b):
"""Compare two float scalars or arrays and see if they are consistent
Consistency is determined ensuring the difference is less than the
expected amount. Return True if consistent, False if any differences"""
aa = a
bb = b
# compute expected precision
if aa.dtype.name=="float32" or bb.dtype.name=='float32':
precision = 0.000001
else:
precision = 0.0000000000000001
precision = 0.00001 # until precision problem is fixed in pyfits
# print aa,aa.shape,type(aa)
# print bb,bb.shape,type(bb)
diff = num.absolute(aa-bb)
mask0 = aa == 0
masknz = aa != 0.
if num.any(mask0):
if diff[mask0].max() != 0.:
return False
if num.any(masknz):
if (diff[masknz]/aa[masknz]).max() > precision:
return False
return True
def comparerecords(a, b):
"""Compare two record arrays
Does this field by field, using approximation testing for float columns
(Complex not yet handled.)
Column names not compared, but column types and sizes are.
"""
nfieldsa = len(a.dtype.names)
nfieldsb = len(b.dtype.names)
if nfieldsa != nfieldsb:
print "number of fields don't match"
return False
for i in range(nfieldsa):
fielda = a.field(i)
fieldb = b.field(i)
if type(fielda) != type(fieldb):
print "type(fielda): ",type(fielda)," fielda: ",fielda
print "type(fieldb): ",type(fieldb)," fieldb: ",fieldb
print 'field %d type differs' % i
return False
if not isinstance(fielda, num.chararray) and \
isinstance(fielda[0], num.floating):
if not comparefloats(fielda, fieldb):
print "fielda: ",fielda
print "fieldb: ",fieldb
print 'field %d differs' % i
return False
else:
if num.any(fielda != fieldb):
print "fielda: ",fielda
print "fieldb: ",fieldb
print 'field %d differs' % i
return False
return True
class TestPyfitsTableFunctions(unittest.TestCase):
def setUp(self):
# Perform set up actions (if any)
pass
def tearDown(self):
# Perform clean-up actions (if any)
try:
os.remove('newtable.fits')
except:
pass
try:
os.remove('table1.fits')
except:
pass
try:
os.remove('table2.fits')
except:
pass
try:
os.remove('tableout1.fits')
except:
pass
try:
os.remove('tableout2.fits')
except:
pass
try:
os.remove('toto.fits')
except:
pass
try:
os.remove('testendian.fits')
except:
pass
def testOpen(self):
# open some existing FITS files:
tt=pyfits.open(test_dir+'tb.fits')
fd=pyfits.open(test_dir+'test0.fits')
# create some local arrays
a1=chararray.array(['abc','def','xx'])
r1=num.array([11.,12.,13.],dtype=num.float32)
# create a table from scratch, using a mixture of columns from existing
# tables and locally created arrays:
# first, create individual column definitions
c1=pyfits.Column(name='abc',format='3A', array=a1)
c2=pyfits.Column(name='def',format='E', array=r1)
a3=num.array([3,4,5],dtype='i2')
c3=pyfits.Column(name='xyz',format='I', array=a3)
a4=num.array([1,2,3],dtype='i2')
c4=pyfits.Column(name='t1', format='I', array=a4)
a5=num.array([3+3j,4+4j,5+5j],dtype='c8')
c5=pyfits.Column(name='t2', format='C', array=a5)
# Note that X format must be two-D array
a6=num.array([[0],[1],[0]],dtype=num.uint8)
c6=pyfits.Column(name='t3', format='X', array=a6)
a7=num.array([101,102,103],dtype='i4')
c7=pyfits.Column(name='t4', format='J', array=a7)
a8=num.array([[1,1,0,1,0,1,1,1,0,0,1],[0,1,1,1,1,0,0,0,0,1,0],[1,1,1,0,0,1,1,1,1,1,1]],dtype=num.uint8)
c8=pyfits.Column(name='t5', format='11X', array=a8)
# second, create a column-definitions object for all columns in a table
x = pyfits.ColDefs([c1,c2,c3,c4,c5,c6,c7,c8])
# create a new binary table HDU object by using the new_table function
tbhdu=pyfits.new_table(x)
# another way to create a table is by using existing table's information:
x2=pyfits.ColDefs(tt[1])
t2=pyfits.new_table(x2, nrows=2)
ra = rec.array([
(1, 'abc', 3.7000002861022949, 0),
(2, 'xy ', 6.6999998092651367, 1)], names='c1, c2, c3, c4')
self.assertEqual(comparerecords(t2.data, ra),True)
# the table HDU's data is a subclass of a record array, so we can access
# one row like this:
self.assertEqual(tbhdu.data[1][0], a1[1])
self.assertEqual(tbhdu.data[1][1], r1[1])
self.assertEqual(tbhdu.data[1][2], a3[1])
self.assertEqual(tbhdu.data[1][3], a4[1])
self.assertEqual(tbhdu.data[1][4], a5[1])
self.assertEqual(tbhdu.data[1][5], a6[1])
self.assertEqual(tbhdu.data[1][6], a7[1])
self.assertEqual(tbhdu.data[1][7].all(), a8[1].all())
# and a column like this:
self.assertEqual(str(tbhdu.data.field('abc')),"['abc' 'def' 'xx']")
# An alternative way to create a column-definitions object is from an
# existing table.
xx=pyfits.ColDefs(tt[1])
# now we write out the newly created table HDU to a FITS file:
fout = pyfits.HDUList(pyfits.PrimaryHDU())
fout.append(tbhdu)
fout.writeto('tableout1.fits', clobber=True)
f2 = pyfits.open('tableout1.fits')
temp = f2[1].data.field(7)
self.assertEqual(str(temp[0]),"[ True True False True False True True True False False True]")
f2.close()
os.remove('tableout1.fits')
# An alternative way to create an output table FITS file:
fout2=pyfits.open('tableout2.fits','append')
fout2.append(fd[0])
fout2.append(tbhdu)
fout2.close()
tt.close()
fd.close()
os.remove("tableout2.fits")
def testBinaryTable(self):
# binary table:
t=pyfits.open(test_dir+'tb.fits')
self.assertEqual(t[1].header['tform1'],'1J')
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
t[1].columns.info()
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
tmplist = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(tmplist,['name:\n', " ['c1', 'c2', 'c3', 'c4']\n",
'format:\n', " ['1J', '3A', '1E', '1L']\n",
'unit:\n', " ['', '', '', '']\n", 'null:\n',
" [-2147483647, '', '', '']\n", 'bscale:\n',
" ['', '', 3, '']\n", 'bzero:\n',
" ['', '', 0.40000000000000002, '']\n",
'disp:\n', " ['I11', 'A3', 'G15.7', 'L6']\n",
'start:\n', " ['', '', '', '']\n", 'dim:\n',
" ['', '', '', '']\n"])
ra = rec.array([
(1, 'abc', 3.7000002861022949, 0),
(2, 'xy ', 6.6999998092651367, 1)], names='c1, c2, c3, c4')
self.assertEqual(comparerecords(t[1].data, ra[:2]),True)
# Change scaled field and scale back to the original array
t[1].data.field('c4')[0] = 1
t[1].data._scale_back()
self.assertEqual(str(rec.recarray.field(t[1].data,'c4')),"[84 84]")
# look at data column-wise
self.assertEqual(t[1].data.field(0).all(),num.array([1, 2]).all())
# When there are scaled columns, the raw data are in data._parent
t.close()
def testAsciiTable(self):
# ASCII table
a=pyfits.open(test_dir+'ascii.fits')
ra1 = rec.array([
(10.123000144958496, 37),
(5.1999998092651367, 23),
(15.609999656677246, 17),
(0.0, 0),
(345.0, 345)], names='c1, c2')
self.assertEqual(comparerecords(a[1].data, ra1),True)
# Test slicing
a2 = a[1].data[2:][2:]
ra2 = rec.array([(345.0,345)],names='c1, c2')
self.assertEqual(comparerecords(a2, ra2),True)
self.assertEqual(a2.field(1).all(),num.array([345]).all())
ra3 = rec.array([
(10.123000144958496, 37),
(15.609999656677246, 17),
(345.0, 345)
], names='c1, c2')
self.assertEqual(comparerecords(a[1].data[::2], ra3),True)
# Test Start Column
a1 = chararray.array(['abcd','def'])
r1 = numpy.array([11.,12.])
c1 = pyfits.Column(name='abc',format='A3',start=19,array=a1)
c2 = pyfits.Column(name='def',format='E',start=3,array=r1)
c3 = pyfits.Column(name='t1',format='I',array=[91,92,93])
hdu = pyfits.new_table([c2,c1,c3],tbtype='TableHDU')
self.assertEqual(hdu.data.dtype.fields,{'abc':(numpy.dtype('|S3'),18),
'def':(numpy.dtype('|S14'),2),
't1':(numpy.dtype('|S10'),21)})
hdu.writeto('toto.fits',clobber=True)
hdul = pyfits.open('toto.fits')
self.assertEqual(comparerecords(hdu.data,hdul[1].data),True)
hdul.close()
a.close()
os.remove('toto.fits')
def testVariableLengthColumns(self):
col_list = []
col_list.append(pyfits.Column(name='QUAL_SPE',format='PJ()',array=[[0]*1571]*225))
tb_hdu = pyfits.new_table(col_list)
pri_hdu = pyfits.PrimaryHDU()
hdu_list = pyfits.HDUList([pri_hdu,tb_hdu])
hdu_list.writeto('toto.fits', clobber=True)
toto = pyfits.open('toto.fits')
q = toto[1].data.field('QUAL_SPE')
self.assertEqual(q[0][4:8].all(),num.array([0,0,0,0],dtype=numpy.uint8).all())
toto.close()
os.remove('toto.fits')
def testEndianness(self):
x = num.ndarray((1,), dtype=object)
channelsIn = num.array([3], dtype='uint8')
x[0] = channelsIn
col = pyfits.Column(name="Channels", format="PB()", array=x)
cols = pyfits.ColDefs([col])
tbhdu = pyfits.new_table(cols)
tbhdu.name = "RFI"
tbhdu.writeto('testendian.fits', clobber=True)
hduL = pyfits.open('testendian.fits')
rfiHDU = hduL['RFI']
data = rfiHDU.data
channelsOut = data.field('Channels')[0]
self.assertEqual(channelsIn.all(),channelsOut.all())
hduL.close()
os.remove('testendian.fits')
def testPyfitsRecarrayToBinTableHDU(self):
bright=pyfits.rec.array([(1,'Serius',-1.45,'A1V'),\
(2,'Canopys',-0.73,'F0Ib'),\
(3,'Rigil Kent',-0.1,'G2V')],\
formats='int16,a20,float32,a10',\
names='order,name,mag,Sp')
hdu=pyfits.BinTableHDU(bright)
self.assertEqual(comparerecords(hdu.data,bright),True)
hdu.writeto('toto.fits', clobber=True)
hdul = pyfits.open('toto.fits')
self.assertEqual(comparerecords(hdu.data,hdul[1].data),True)
self.assertEqual(comparerecords(bright,hdul[1].data),True)
hdul.close()
os.remove('toto.fits')
def testNumpyNdarrayToBinTableHDU(self):
desc=numpy.dtype({'names':['order','name','mag','Sp'],\
'formats':['int','S20','float32','S10']})
a=numpy.array([(1,'Serius',-1.45,'A1V'),\
(2,'Canopys',-0.73,'F0Ib'),\
(3,'Rigil Kent',-0.1,'G2V')],dtype=desc)
hdu=pyfits.BinTableHDU(a)
self.assertEqual(comparerecords(hdu.data,a.view(pyfits.rec.recarray)),\
True)
hdu.writeto('toto.fits', clobber=True)
hdul = pyfits.open('toto.fits')
self.assertEqual(comparerecords(hdu.data,hdul[1].data),True)
hdul.close()
os.remove('toto.fits')
def testNewTableFromPyfitsRecarray(self):
bright=pyfits.rec.array([(1,'Serius',-1.45,'A1V'),\
(2,'Canopys',-0.73,'F0Ib'),\
(3,'Rigil Kent',-0.1,'G2V')],\
formats='int16,a20,float32,a10',\
names='order,name,mag,Sp')
hdu=pyfits.new_table(bright,nrows=2,tbtype='TableHDU')
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.data._coldefs._arrays[0]))
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.columns.data[0].array))
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.columns._arrays[0]))
# Ensure I can change the value of one data element and it effects
# all of the others.
hdu.data[0][0] = 213
self.assertEqual(hdu.data[0][0], 213)
self.assertEqual(hdu.data._coldefs._arrays[0][0], 213)
self.assertEqual(hdu.data._coldefs.data[0].array[0], 213)
self.assertEqual(hdu.columns._arrays[0][0], 213)
self.assertEqual(hdu.columns.data[0].array[0], 213)
hdu.data._coldefs._arrays[0][0] = 100
self.assertEqual(hdu.data[0][0], 100)
self.assertEqual(hdu.data._coldefs._arrays[0][0], 100)
self.assertEqual(hdu.data._coldefs.data[0].array[0], 100)
self.assertEqual(hdu.columns._arrays[0][0], 100)
self.assertEqual(hdu.columns.data[0].array[0], 100)
hdu.data._coldefs.data[0].array[0] = 500
self.assertEqual(hdu.data[0][0], 500)
self.assertEqual(hdu.data._coldefs._arrays[0][0], 500)
self.assertEqual(hdu.data._coldefs.data[0].array[0], 500)
self.assertEqual(hdu.columns._arrays[0][0], 500)
self.assertEqual(hdu.columns.data[0].array[0], 500)
hdu.columns._arrays[0][0] = 600
self.assertEqual(hdu.data[0][0], 600)
self.assertEqual(hdu.data._coldefs._arrays[0][0], 600)
self.assertEqual(hdu.data._coldefs.data[0].array[0], 600)
self.assertEqual(hdu.columns._arrays[0][0], 600)
self.assertEqual(hdu.columns.data[0].array[0], 600)
hdu.columns.data[0].array[0] = 800
self.assertEqual(hdu.data[0][0], 800)
self.assertEqual(hdu.data._coldefs._arrays[0][0], 800)
self.assertEqual(hdu.data._coldefs.data[0].array[0], 800)
self.assertEqual(hdu.columns._arrays[0][0], 800)
self.assertEqual(hdu.columns.data[0].array[0], 800)
self.assertEqual(hdu.data.field(0).all(),
num.array([1,2],dtype=num.int16).all())
self.assertEqual(hdu.data[0][1],'Serius')
self.assertEqual(hdu.data[1][1],'Canopys')
self.assertEqual(hdu.data.field(2).all(),
num.array([-1.45,-0.73],dtype=num.float32).all())
self.assertEqual(hdu.data[0][3],'A1V')
self.assertEqual(hdu.data[1][3],'F0Ib')
hdu.writeto('toto.fits', clobber=True)
hdul = pyfits.open('toto.fits')
self.assertEqual(hdul[1].data.field(0).all(),
num.array([1,2],dtype=num.int16).all())
self.assertEqual(hdul[1].data[0][1],'Serius')
self.assertEqual(hdul[1].data[1][1],'Canopys')
self.assertEqual(hdul[1].data.field(2).all(),
num.array([-1.45,-0.73],dtype=num.float32).all())
self.assertEqual(hdul[1].data[0][3],'A1V')
self.assertEqual(hdul[1].data[1][3],'F0Ib')
hdul.close()
os.remove('toto.fits')
hdu=pyfits.new_table(bright,nrows=2)
tmp=pyfits.rec.array([(1,'Serius',-1.45,'A1V'),\
(2,'Canopys',-0.73,'F0Ib')],\
formats='int16,a20,float32,a10',\
names='order,name,mag,Sp')
self.assertEqual(comparerecords(hdu.data,tmp),True)
hdu.writeto('toto.fits', clobber=True)
hdul = pyfits.open('toto.fits')
self.assertEqual(comparerecords(hdu.data,hdul[1].data),True)
hdul.close()
os.remove('toto.fits')
def testAppendingAColumn(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table1.fits')
counts = num.array([412,434,408,417])
names = num.array(['NGC5','NGC6','NGC7','NCG8'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[0,1,0,0])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table2.fits')
# Append the rows of table 2 after the rows of table 1
# The column definitions are assumed to be the same
# Open the two files we want to append
t1=pyfits.open('table1.fits')
t2=pyfits.open('table2.fits')
# Get the number of rows in the table from the first file
nrows1=t1[1].data.shape[0]
# Get the total number of rows in the resulting appended table
nrows=t1[1].data.shape[0]+t2[1].data.shape[0]
self.assertEqual(t1[1].columns._arrays[1] is
t1[1].columns.data[1].array, True)
# Create a new table that consists of the data from the first table
# but has enough space in the ndarray to hold the data from both tables
hdu=pyfits.new_table(t1[1].columns,nrows=nrows)
# For each column in the tables append the data from table 2 after the
# data from table 1.
for i in range(len(t1[1].columns)):
hdu.data.field(i)[nrows1:]=t2[1].data.field(i)
hdu.writeto('newtable.fits')
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
pyfits.info('newtable.fits')
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,['Filename: newtable.fits\n', 'No. Name Type Cards Dimensions Format\n', '0 PRIMARY PrimaryHDU 4 () uint8\n', '1 BinTableHDU 19 8R x 5C [10A, J, 10A, 5E, L]\n'])
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
print hdu.data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[ ('NGC1', 312, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC2', 334, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NGC3', 308, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NCG4', 317, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC5', 412, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NGC6', 434, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC7', 408, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NCG8', 417, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)]\n"])
# Verify that all of the references to the data point to the same
# numarray
hdu.data[0][1] = 300
self.assertEqual(hdu.data._coldefs._arrays[1][0], 300)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 300)
self.assertEqual(hdu.columns._arrays[1][0], 300)
self.assertEqual(hdu.columns.data[1].array[0], 300)
self.assertEqual(hdu.data[0][1], 300)
hdu.data._coldefs._arrays[1][0] = 200
self.assertEqual(hdu.data._coldefs._arrays[1][0], 200)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 200)
self.assertEqual(hdu.columns._arrays[1][0], 200)
self.assertEqual(hdu.columns.data[1].array[0], 200)
self.assertEqual(hdu.data[0][1], 200)
hdu.data._coldefs.data[1].array[0] = 100
self.assertEqual(hdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(hdu.columns._arrays[1][0], 100)
self.assertEqual(hdu.columns.data[1].array[0], 100)
self.assertEqual(hdu.data[0][1], 100)
hdu.columns._arrays[1][0] = 90
self.assertEqual(hdu.data._coldefs._arrays[1][0], 90)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 90)
self.assertEqual(hdu.columns._arrays[1][0], 90)
self.assertEqual(hdu.columns.data[1].array[0], 90)
self.assertEqual(hdu.data[0][1], 90)
hdu.columns.data[1].array[0] = 80
self.assertEqual(hdu.data._coldefs._arrays[1][0], 80)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 80)
self.assertEqual(hdu.columns._arrays[1][0], 80)
self.assertEqual(hdu.columns.data[1].array[0], 80)
self.assertEqual(hdu.data[0][1], 80)
# Same verification from the file
hdul = pyfits.open('newtable.fits')
hdu = hdul[1]
hdu.data[0][1] = 300
self.assertEqual(hdu.data._coldefs._arrays[1][0], 300)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 300)
self.assertEqual(hdu.columns._arrays[1][0], 300)
self.assertEqual(hdu.columns.data[1].array[0], 300)
self.assertEqual(hdu.data[0][1], 300)
hdu.data._coldefs._arrays[1][0] = 200
self.assertEqual(hdu.data._coldefs._arrays[1][0], 200)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 200)
self.assertEqual(hdu.columns._arrays[1][0], 200)
self.assertEqual(hdu.columns.data[1].array[0], 200)
self.assertEqual(hdu.data[0][1], 200)
hdu.data._coldefs.data[1].array[0] = 100
self.assertEqual(hdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(hdu.columns._arrays[1][0], 100)
self.assertEqual(hdu.columns.data[1].array[0], 100)
self.assertEqual(hdu.data[0][1], 100)
hdu.columns._arrays[1][0] = 90
self.assertEqual(hdu.data._coldefs._arrays[1][0], 90)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 90)
self.assertEqual(hdu.columns._arrays[1][0], 90)
self.assertEqual(hdu.columns.data[1].array[0], 90)
self.assertEqual(hdu.data[0][1], 90)
hdu.columns.data[1].array[0] = 80
self.assertEqual(hdu.data._coldefs._arrays[1][0], 80)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 80)
self.assertEqual(hdu.columns._arrays[1][0], 80)
self.assertEqual(hdu.columns.data[1].array[0], 80)
self.assertEqual(hdu.data[0][1], 80)
t1.close()
t2.close()
hdul.close()
os.remove('newtable.fits')
os.remove('table1.fits')
os.remove('table2.fits')
def testAddingAColumn(self):
# Tests adding a column to a table.
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4])
tbhdu=pyfits.new_table(coldefs)
self.assertEqual(tbhdu.columns.names,['target', 'counts', 'notes',
'spectrum'])
coldefs1 = coldefs + c5
tbhdu1=pyfits.new_table(coldefs1)
self.assertEqual(tbhdu1.columns.names,['target', 'counts', 'notes',
'spectrum', 'flag'])
tmpfile = open(jfile, 'w')
sys.stdout = tmpfile
print tbhdu1.data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[ ('NGC1', 312, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC2', 334, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NGC3', 308, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NCG4', 317, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)]\n"])
def testMergeTables(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table1.fits')
counts = num.array([412,434,408,417])
names = num.array(['NGC5','NGC6','NGC7','NCG8'])
c1=pyfits.Column(name='target1',format='10A',array=names)
c2=pyfits.Column(name='counts1',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes1',format='A10')
c4=pyfits.Column(name='spectrum1',format='5E')
c5=pyfits.Column(name='flag1',format='L',array=[0,1,0,0])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table2.fits')
# Merge the columns of table 2 after the columns of table 1
# The column names are assumed to be different
# Open the two files we want to append
t1=pyfits.open('table1.fits')
t2=pyfits.open('table2.fits')
hdu =pyfits.new_table(t1[1].columns+t2[1].columns)
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
print hdu.data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[ ('NGC1', 312, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NGC5', 412, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NGC2', 334, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False, 'NGC6', 434, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC3', 308, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NGC7', 408, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NCG4', 317, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NCG8', 417, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)]\n"])
hdu.writeto('newtable.fits')
# Verify that all of the references to the data point to the same
# numarray
hdu.data[0][1] = 300
self.assertEqual(hdu.data._coldefs._arrays[1][0], 300)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 300)
self.assertEqual(hdu.columns._arrays[1][0], 300)
self.assertEqual(hdu.columns.data[1].array[0], 300)
self.assertEqual(hdu.data[0][1], 300)
hdu.data._coldefs._arrays[1][0] = 200
self.assertEqual(hdu.data._coldefs._arrays[1][0], 200)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 200)
self.assertEqual(hdu.columns._arrays[1][0], 200)
self.assertEqual(hdu.columns.data[1].array[0], 200)
self.assertEqual(hdu.data[0][1], 200)
hdu.data._coldefs.data[1].array[0] = 100
self.assertEqual(hdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(hdu.columns._arrays[1][0], 100)
self.assertEqual(hdu.columns.data[1].array[0], 100)
self.assertEqual(hdu.data[0][1], 100)
hdu.columns._arrays[1][0] = 90
self.assertEqual(hdu.data._coldefs._arrays[1][0], 90)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 90)
self.assertEqual(hdu.columns._arrays[1][0], 90)
self.assertEqual(hdu.columns.data[1].array[0], 90)
self.assertEqual(hdu.data[0][1], 90)
hdu.columns.data[1].array[0] = 80
self.assertEqual(hdu.data._coldefs._arrays[1][0], 80)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 80)
self.assertEqual(hdu.columns._arrays[1][0], 80)
self.assertEqual(hdu.columns.data[1].array[0], 80)
self.assertEqual(hdu.data[0][1], 80)
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
pyfits.info('newtable.fits')
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,['Filename: newtable.fits\n', 'No. Name Type Cards Dimensions Format\n', '0 PRIMARY PrimaryHDU 4 () uint8\n', '1 BinTableHDU 30 4R x 10C [10A, J, 10A, 5E, L, 10A, J, 10A, 5E, L]\n'])
hdul = pyfits.open('newtable.fits')
hdu = hdul[1]
self.assertEqual(hdu.columns.names,['target', 'counts', 'notes', 'spectrum', 'flag', 'target1', 'counts1', 'notes1', 'spectrum1', 'flag1'])
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
print hdu.data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[ ('NGC1', 312, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NGC5', 412, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NGC2', 334, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False, 'NGC6', 434, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True)\n", " ('NGC3', 308, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NGC7', 408, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)\n", " ('NCG4', 317, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), True, 'NCG8', 417, '0.0', array([ 0., 0., 0., 0., 0.], dtype=float32), False)]\n"])
# Same verification from the file
hdu.data[0][1] = 300
self.assertEqual(hdu.data._coldefs._arrays[1][0], 300)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 300)
self.assertEqual(hdu.columns._arrays[1][0], 300)
self.assertEqual(hdu.columns.data[1].array[0], 300)
self.assertEqual(hdu.data[0][1], 300)
hdu.data._coldefs._arrays[1][0] = 200
self.assertEqual(hdu.data._coldefs._arrays[1][0], 200)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 200)
self.assertEqual(hdu.columns._arrays[1][0], 200)
self.assertEqual(hdu.columns.data[1].array[0], 200)
self.assertEqual(hdu.data[0][1], 200)
hdu.data._coldefs.data[1].array[0] = 100
self.assertEqual(hdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(hdu.columns._arrays[1][0], 100)
self.assertEqual(hdu.columns.data[1].array[0], 100)
self.assertEqual(hdu.data[0][1], 100)
hdu.columns._arrays[1][0] = 90
self.assertEqual(hdu.data._coldefs._arrays[1][0], 90)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 90)
self.assertEqual(hdu.columns._arrays[1][0], 90)
self.assertEqual(hdu.columns.data[1].array[0], 90)
self.assertEqual(hdu.data[0][1], 90)
hdu.columns.data[1].array[0] = 80
self.assertEqual(hdu.data._coldefs._arrays[1][0], 80)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 80)
self.assertEqual(hdu.columns._arrays[1][0], 80)
self.assertEqual(hdu.columns.data[1].array[0], 80)
self.assertEqual(hdu.data[0][1], 80)
t1.close()
t2.close()
hdul.close()
os.remove('table1.fits')
os.remove('table2.fits')
os.remove('newtable.fits')
def testMaskArray(self):
t=pyfits.open(test_dir+'table.fits')
tbdata = t[1].data
mask = tbdata.field('V_mag') > 12
newtbdata = tbdata[mask]
hdu = pyfits.BinTableHDU(newtbdata)
hdu.writeto('newtable.fits')
hdul = pyfits.open('newtable.fits')
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
print hdu.data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[('NGC1002', 12.3) ('NGC1003', 15.2)]\n"])
tmpfile = open(jfile,'w')
sys.stdout = tmpfile
print hdul[1].data
sys.stdout = sys.__stdout__
tmpfile.close()
tmpfile = open(jfile,'r')
output = tmpfile.readlines()
tmpfile.close()
os.remove(jfile)
self.assertEqual(output,["[('NGC1002', 12.3) ('NGC1003', 15.2)]\n"])
t.close()
hdul.close()
os.remove('newtable.fits')
def testSliceARow(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table1.fits')
t1=pyfits.open('table1.fits')
row = t1[1].data[2]
self.assertEqual(row['counts'],308)
a,b,c = row[1:4]
self.assertEqual(a, counts[2])
self.assertEqual(b, '0.0')
self.assertEqual(c.all(), num.array([ 0., 0., 0., 0., 0.],
dtype=num.float32).all())
row['counts'] = 310
self.assertEqual(row['counts'],310)
row[1] = 315
self.assertEqual(row['counts'],315)
self.assertEqual(row[1:4]['counts'],315)
try:
flag = row[1:4]['flag']
x = "row[1:4]['flag']"
except KeyError:
x = "Failed as expected."
self.assertEqual(x,"Failed as expected.")
row[1:4]['counts'] = 300
self.assertEqual(row[1:4]['counts'],300)
self.assertEqual(row['counts'],300)
row[1:4][0] = 400
self.assertEqual(row[1:4]['counts'],400)
row[1:4]['counts'] = 300
self.assertEqual(row[1:4]['counts'],300)
try:
row[1:4]['flag'] = False
x = "row[1:4]['flag']"
except KeyError:
x = "Failed as expected."
self.assertEqual(x,"Failed as expected.")
self.assertEqual(row[1:4].field(0),300)
self.assertEqual(row[1:4].field('counts'),300)
try:
val = row[1:4].field('flag')
x = "row[1:4].field('flag')"
except KeyError:
x = "Failed as expected."
self.assertEqual(x,"Failed as expected.")
row[1:4].setfield('counts',500)
self.assertEqual(row[1:4].field(0),500)
try:
row[1:4].setfield('flag',False)
x = "row[1:4].setfield('flag',False)"
except KeyError:
x = "Failed as expected."
self.assertEqual(x,"Failed as expected.")
self.assertEqual(t1[1].data._coldefs._arrays[1][2], 500)
self.assertEqual(t1[1].data._coldefs.data[1].array[2], 500)
self.assertEqual(t1[1].columns._arrays[1][2], 500)
self.assertEqual(t1[1].columns.data[1].array[2], 500)
self.assertEqual(t1[1].data[2][1], 500)
t1.close()
os.remove('table1.fits')
def testFITSrecordLen(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.writeto('table1.fits')
t1=pyfits.open('table1.fits')
self.assertEqual(len(t1[1].data[0]),5)
self.assertEqual(len(t1[1].data[0][0:4]),4)
self.assertEqual(len(t1[1].data[0][0:5]),5)
self.assertEqual(len(t1[1].data[0][0:6]),5)
self.assertEqual(len(t1[1].data[0][0:7]),5)
self.assertEqual(len(t1[1].data[0][1:4]),3)
self.assertEqual(len(t1[1].data[0][1:5]),4)
self.assertEqual(len(t1[1].data[0][1:6]),4)
self.assertEqual(len(t1[1].data[0][1:7]),4)
t1.close()
os.remove('table1.fits')
def testAddDataByRows(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu1=pyfits.new_table(coldefs)
c1=pyfits.Column(name='target',format='10A')
c2=pyfits.Column(name='counts',format='J',unit='DN')
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L')
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs, nrows = 5)
# Test assigning data to a tables row using a FITS_record
tbhdu.data[0] = tbhdu1.data[0]
tbhdu.data[4] = tbhdu1.data[3]
# Test assigning data to a tables row using a tuple
tbhdu.data[2] = ('NGC1',312,'A Note',
num.array([1.1,2.2,3.3,4.4,5.5],dtype=num.float32),
True)
# Test assigning data to a tables row using a list
tbhdu.data[3] = ['JIM1','33','A Note',
num.array([1.,2.,3.,4.,5.],dtype=num.float32),True]
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.data._coldefs._arrays[0]))
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.columns.data[0].array))
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.columns._arrays[0]))
self.assertEqual(tbhdu.data[0][1], 312)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 312)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 312)
self.assertEqual(tbhdu.columns._arrays[1][0], 312)
self.assertEqual(tbhdu.columns.data[1].array[0], 312)
self.assertEqual(tbhdu.columns.data[0].array[0], 'NGC1')
self.assertEqual(tbhdu.columns.data[2].array[0], '0.0')
self.assertEqual(tbhdu.columns.data[3].array[0].all(),
num.array([0.,0.,0.,0.,0.],dtype=num.float32).all())
self.assertEqual(tbhdu.columns.data[4].array[0], True)
self.assertEqual(tbhdu.data[3][1], 33)
self.assertEqual(tbhdu.data._coldefs._arrays[1][3], 33)
self.assertEqual(tbhdu.data._coldefs.data[1].array[3], 33)
self.assertEqual(tbhdu.columns._arrays[1][3], 33)
self.assertEqual(tbhdu.columns.data[1].array[3], 33)
self.assertEqual(tbhdu.columns.data[0].array[3], 'JIM1')
self.assertEqual(tbhdu.columns.data[2].array[3], 'A Note')
self.assertEqual(tbhdu.columns.data[3].array[3].all(),
num.array([1.,2.,3.,4.,5.],dtype=num.float32).all())
self.assertEqual(tbhdu.columns.data[4].array[3], True)
def testAssignMultipleRowsToTable(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu1=pyfits.new_table(coldefs)
counts = num.array([112,134,108,117])
names = num.array(['NGC5','NGC6','NGC7','NCG8'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[0,1,0,0])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.data[0][3] = num.array([1.,2.,3.,4.,5.],dtype=num.float32)
tbhdu2=pyfits.new_table(tbhdu1.data, nrows=9)
# Assign the 4 rows from the second table to rows 5 thru 8 of the
# new table. Note that the last row of the new table will still be
# initialized to the default values.
tbhdu2.data[4:] = tbhdu.data
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(tbhdu2.data._coldefs.data[0].array),
id(tbhdu2.data._coldefs._arrays[0]))
self.assertEqual(id(tbhdu2.data._coldefs.data[0].array),
id(tbhdu2.columns.data[0].array))
self.assertEqual(id(tbhdu2.data._coldefs.data[0].array),
id(tbhdu2.columns._arrays[0]))
self.assertEqual(tbhdu2.data[0][1], 312)
self.assertEqual(tbhdu2.data._coldefs._arrays[1][0], 312)
self.assertEqual(tbhdu2.data._coldefs.data[1].array[0], 312)
self.assertEqual(tbhdu2.columns._arrays[1][0], 312)
self.assertEqual(tbhdu2.columns.data[1].array[0], 312)
self.assertEqual(tbhdu2.columns.data[0].array[0], 'NGC1')
self.assertEqual(tbhdu2.columns.data[2].array[0], '0.0')
self.assertEqual(tbhdu2.columns.data[3].array[0].all(),
num.array([0.,0.,0.,0.,0.],dtype=num.float32).all())
self.assertEqual(tbhdu2.columns.data[4].array[0], True)
self.assertEqual(tbhdu2.data[4][1], 112)
self.assertEqual(tbhdu2.data._coldefs._arrays[1][4], 112)
self.assertEqual(tbhdu2.data._coldefs.data[1].array[4], 112)
self.assertEqual(tbhdu2.columns._arrays[1][4], 112)
self.assertEqual(tbhdu2.columns.data[1].array[4], 112)
self.assertEqual(tbhdu2.columns.data[0].array[4], 'NGC5')
self.assertEqual(tbhdu2.columns.data[2].array[4], '0.0')
self.assertEqual(tbhdu2.columns.data[3].array[4].all(),
num.array([1.,2.,3.,4.,5.],dtype=num.float32).all())
self.assertEqual(tbhdu2.columns.data[4].array[4], False)
self.assertEqual(tbhdu2.columns.data[1].array[8], 0)
self.assertEqual(tbhdu2.columns.data[0].array[8], '0.0')
self.assertEqual(tbhdu2.columns.data[2].array[8], '0.0')
self.assertEqual(tbhdu2.columns.data[3].array[8].all(),
num.array([0.,0.,0.,0.,0.],dtype=num.float32).all())
self.assertEqual(tbhdu2.columns.data[4].array[8], False)
def testVerifyDataReferences(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
# Verify that original ColDefs object has independent ndarray from
# original array object.
self.assertNotEqual(id(names), id(c1.array))
self.assertNotEqual(id(counts), id(c2.array))
tbhdu=pyfits.new_table(coldefs)
# Verify that original ColDefs object has independent Column
# objects.
self.assertNotEqual(id(coldefs.data[0]), id(c1))
# Verify that original ColDefs object has independent ndarray
# objects.
self.assertNotEqual(id(coldefs.data[0].array), id(names))
# Verify that original ColDefs object references the same data
# object as the original Column object.
self.assertEqual(id(coldefs.data[0].array), id(c1.array))
self.assertEqual(id(coldefs.data[0].array), id(coldefs._arrays[0]))
# Verify new HDU has an independent ColDefs object.
self.assertNotEqual(id(coldefs), id(tbhdu.columns))
# Verify new HDU has independent Column objects.
self.assertNotEqual(id(coldefs.data[0]), id(tbhdu.columns.data[0]))
# Verify new HDU has independent ndarray objects.
self.assertNotEqual(id(coldefs.data[0].array),
id(tbhdu.columns.data[0].array))
# Verify that both ColDefs objects in the HDU reference the same
# Coldefs object.
self.assertEqual(id(tbhdu.columns), id(tbhdu.data._coldefs))
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.data._coldefs._arrays[0]))
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.columns.data[0].array))
self.assertEqual(id(tbhdu.data._coldefs.data[0].array),
id(tbhdu.columns._arrays[0]))
tbhdu.writeto('table1.fits')
t1=pyfits.open('table1.fits')
t1[1].data[0][1] = 213
self.assertEqual(t1[1].data[0][1], 213)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 213)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 213)
self.assertEqual(t1[1].columns._arrays[1][0], 213)
self.assertEqual(t1[1].columns.data[1].array[0], 213)
t1[1].data._coldefs._arrays[1][0] = 100
self.assertEqual(t1[1].data[0][1], 100)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 100)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 100)
self.assertEqual(t1[1].columns._arrays[1][0], 100)
self.assertEqual(t1[1].columns.data[1].array[0], 100)
t1[1].data._coldefs.data[1].array[0] = 500
self.assertEqual(t1[1].data[0][1], 500)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 500)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 500)
self.assertEqual(t1[1].columns._arrays[1][0], 500)
self.assertEqual(t1[1].columns.data[1].array[0], 500)
t1[1].columns._arrays[1][0] = 600
self.assertEqual(t1[1].data[0][1], 600)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 600)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 600)
self.assertEqual(t1[1].columns._arrays[1][0], 600)
self.assertEqual(t1[1].columns.data[1].array[0], 600)
t1[1].columns.data[1].array[0] = 800
self.assertEqual(t1[1].data[0][1], 800)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 800)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 800)
self.assertEqual(t1[1].columns._arrays[1][0], 800)
self.assertEqual(t1[1].columns.data[1].array[0], 800)
t1.close()
os.remove('table1.fits')
def testNewTableWithNdarray(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu1=pyfits.new_table(tbhdu.data.view(num.ndarray))
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(tbhdu1.data._coldefs.data[0].array),
id(tbhdu1.data._coldefs._arrays[0]))
self.assertEqual(id(tbhdu1.data._coldefs.data[0].array),
id(tbhdu1.columns.data[0].array))
self.assertEqual(id(tbhdu1.data._coldefs.data[0].array),
id(tbhdu1.columns._arrays[0]))
# Ensure I can change the value of one data element and it effects
# all of the others.
tbhdu1.data[0][1] = 213
self.assertEqual(tbhdu1.data[0][1], 213)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 213)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 213)
self.assertEqual(tbhdu1.columns._arrays[1][0], 213)
self.assertEqual(tbhdu1.columns.data[1].array[0], 213)
tbhdu1.data._coldefs._arrays[1][0] = 100
self.assertEqual(tbhdu1.data[0][1], 100)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 100)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 100)
self.assertEqual(tbhdu1.columns._arrays[1][0], 100)
self.assertEqual(tbhdu1.columns.data[1].array[0], 100)
tbhdu1.data._coldefs.data[1].array[0] = 500
self.assertEqual(tbhdu1.data[0][1], 500)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 500)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 500)
self.assertEqual(tbhdu1.columns._arrays[1][0], 500)
self.assertEqual(tbhdu1.columns.data[1].array[0], 500)
tbhdu1.columns._arrays[1][0] = 600
self.assertEqual(tbhdu1.data[0][1], 600)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 600)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 600)
self.assertEqual(tbhdu1.columns._arrays[1][0], 600)
self.assertEqual(tbhdu1.columns.data[1].array[0], 600)
tbhdu1.columns.data[1].array[0] = 800
self.assertEqual(tbhdu1.data[0][1], 800)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 800)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 800)
self.assertEqual(tbhdu1.columns._arrays[1][0], 800)
self.assertEqual(tbhdu1.columns.data[1].array[0], 800)
tbhdu1.writeto('table1.fits')
t1=pyfits.open('table1.fits')
t1[1].data[0][1] = 213
self.assertEqual(t1[1].data[0][1], 213)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 213)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 213)
self.assertEqual(t1[1].columns._arrays[1][0], 213)
self.assertEqual(t1[1].columns.data[1].array[0], 213)
t1[1].data._coldefs._arrays[1][0] = 100
self.assertEqual(t1[1].data[0][1], 100)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 100)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 100)
self.assertEqual(t1[1].columns._arrays[1][0], 100)
self.assertEqual(t1[1].columns.data[1].array[0], 100)
t1[1].data._coldefs.data[1].array[0] = 500
self.assertEqual(t1[1].data[0][1], 500)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 500)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 500)
self.assertEqual(t1[1].columns._arrays[1][0], 500)
self.assertEqual(t1[1].columns.data[1].array[0], 500)
t1[1].columns._arrays[1][0] = 600
self.assertEqual(t1[1].data[0][1], 600)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 600)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 600)
self.assertEqual(t1[1].columns._arrays[1][0], 600)
self.assertEqual(t1[1].columns.data[1].array[0], 600)
t1[1].columns.data[1].array[0] = 800
self.assertEqual(t1[1].data[0][1], 800)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 800)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 800)
self.assertEqual(t1[1].columns._arrays[1][0], 800)
self.assertEqual(t1[1].columns.data[1].array[0], 800)
t1.close()
os.remove('table1.fits')
def testNewTableWithFITSrec(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu=pyfits.new_table(coldefs)
tbhdu.data[0][1] = 213
self.assertEqual(tbhdu.data[0][1], 213)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 213)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 213)
self.assertEqual(tbhdu.columns._arrays[1][0], 213)
self.assertEqual(tbhdu.columns.data[1].array[0], 213)
tbhdu.data._coldefs._arrays[1][0] = 100
self.assertEqual(tbhdu.data[0][1], 100)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(tbhdu.columns._arrays[1][0], 100)
self.assertEqual(tbhdu.columns.data[1].array[0], 100)
tbhdu.data._coldefs.data[1].array[0] = 500
self.assertEqual(tbhdu.data[0][1], 500)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 500)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 500)
self.assertEqual(tbhdu.columns._arrays[1][0], 500)
self.assertEqual(tbhdu.columns.data[1].array[0], 500)
tbhdu.columns._arrays[1][0] = 600
self.assertEqual(tbhdu.data[0][1], 600)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 600)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 600)
self.assertEqual(tbhdu.columns._arrays[1][0], 600)
self.assertEqual(tbhdu.columns.data[1].array[0], 600)
tbhdu.columns.data[1].array[0] = 800
self.assertEqual(tbhdu.data[0][1], 800)
self.assertEqual(tbhdu.data._coldefs._arrays[1][0], 800)
self.assertEqual(tbhdu.data._coldefs.data[1].array[0], 800)
self.assertEqual(tbhdu.columns._arrays[1][0], 800)
self.assertEqual(tbhdu.columns.data[1].array[0], 800)
tbhdu.columns.data[1].array[0] = 312
tbhdu.writeto('table1.fits')
t1=pyfits.open('table1.fits')
t1[1].data[0][1] = 1
fr = t1[1].data
self.assertEqual(t1[1].data[0][1], 1)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 1)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 1)
self.assertEqual(t1[1].columns._arrays[1][0], 1)
self.assertEqual(t1[1].columns.data[1].array[0], 1)
self.assertEqual(fr[0][1], 1)
self.assertEqual(fr._coldefs._arrays[1][0], 1)
self.assertEqual(fr._coldefs.data[1].array[0], 1)
fr._coldefs.data[1].array[0] = 312
tbhdu1 = pyfits.new_table(fr)
#tbhdu1 = pyfits.new_table(t1[1].data)
i = 0
for row in tbhdu1.data:
for j in range(0,len(row)):
if isinstance(row[j], num.ndarray):
self.assertEqual(row[j].all(), tbhdu.data[i][j].all())
else:
self.assertEqual(row[j], tbhdu.data[i][j])
i = i + 1
tbhdu1.data[0][1] = 213
self.assertEqual(t1[1].data[0][1], 312)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 312)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 312)
self.assertEqual(t1[1].columns._arrays[1][0], 312)
self.assertEqual(t1[1].columns.data[1].array[0], 312)
self.assertEqual(fr[0][1], 312)
self.assertEqual(fr._coldefs._arrays[1][0], 312)
self.assertEqual(fr._coldefs.data[1].array[0], 312)
self.assertEqual(tbhdu1.data[0][1], 213)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 213)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 213)
self.assertEqual(tbhdu1.columns._arrays[1][0], 213)
self.assertEqual(tbhdu1.columns.data[1].array[0], 213)
t1[1].data[0][1] = 10
self.assertEqual(t1[1].data[0][1], 10)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 10)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 10)
self.assertEqual(t1[1].columns._arrays[1][0], 10)
self.assertEqual(t1[1].columns.data[1].array[0], 10)
self.assertEqual(fr[0][1], 10)
self.assertEqual(fr._coldefs._arrays[1][0], 10)
self.assertEqual(fr._coldefs.data[1].array[0], 10)
self.assertEqual(tbhdu1.data[0][1], 213)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 213)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 213)
self.assertEqual(tbhdu1.columns._arrays[1][0], 213)
self.assertEqual(tbhdu1.columns.data[1].array[0], 213)
tbhdu1.data._coldefs._arrays[1][0] = 666
self.assertEqual(t1[1].data[0][1], 10)
self.assertEqual(t1[1].data._coldefs._arrays[1][0], 10)
self.assertEqual(t1[1].data._coldefs.data[1].array[0], 10)
self.assertEqual(t1[1].columns._arrays[1][0], 10)
self.assertEqual(t1[1].columns.data[1].array[0], 10)
self.assertEqual(fr[0][1], 10)
self.assertEqual(fr._coldefs._arrays[1][0], 10)
self.assertEqual(fr._coldefs.data[1].array[0], 10)
self.assertEqual(tbhdu1.data[0][1], 666)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 666)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 666)
self.assertEqual(tbhdu1.columns._arrays[1][0], 666)
self.assertEqual(tbhdu1.columns.data[1].array[0], 666)
t1.close()
os.remove('table1.fits')
def testBinTableHDUConstructor(self):
counts = num.array([312,334,308,317])
names = num.array(['NGC1','NGC2','NGC3','NCG4'])
c1=pyfits.Column(name='target',format='10A',array=names)
c2=pyfits.Column(name='counts',format='J',unit='DN',array=counts)
c3=pyfits.Column(name='notes',format='A10')
c4=pyfits.Column(name='spectrum',format='5E')
c5=pyfits.Column(name='flag',format='L',array=[1,0,1,1])
coldefs=pyfits.ColDefs([c1,c2,c3,c4,c5])
tbhdu1=pyfits.new_table(coldefs)
hdu = pyfits.BinTableHDU(tbhdu1.data)
# Verify that all ndarray objects within the HDU reference the
# same ndarray.
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.data._coldefs._arrays[0]))
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.columns.data[0].array))
self.assertEqual(id(hdu.data._coldefs.data[0].array),
id(hdu.columns._arrays[0]))
# Verify that the references in the original HDU are the same as the
# references in the new HDU.
self.assertEqual(id(tbhdu1.data._coldefs.data[0].array),
id(hdu.data._coldefs._arrays[0]))
# Verify that a change in the new HDU is reflected in both the new
# and original HDU.
hdu.data[0][1] = 213
self.assertEqual(hdu.data[0][1], 213)
self.assertEqual(hdu.data._coldefs._arrays[1][0], 213)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 213)
self.assertEqual(hdu.columns._arrays[1][0], 213)
self.assertEqual(hdu.columns.data[1].array[0], 213)
self.assertEqual(tbhdu1.data[0][1], 213)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 213)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 213)
self.assertEqual(tbhdu1.columns._arrays[1][0], 213)
self.assertEqual(tbhdu1.columns.data[1].array[0], 213)
hdu.data._coldefs._arrays[1][0] = 100
self.assertEqual(hdu.data[0][1], 100)
self.assertEqual(hdu.data._coldefs._arrays[1][0], 100)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 100)
self.assertEqual(hdu.columns._arrays[1][0], 100)
self.assertEqual(hdu.columns.data[1].array[0], 100)
self.assertEqual(tbhdu1.data[0][1], 100)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 100)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 100)
self.assertEqual(tbhdu1.columns._arrays[1][0], 100)
self.assertEqual(tbhdu1.columns.data[1].array[0], 100)
hdu.data._coldefs.data[1].array[0] = 500
self.assertEqual(hdu.data[0][1], 500)
self.assertEqual(hdu.data._coldefs._arrays[1][0], 500)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 500)
self.assertEqual(hdu.columns._arrays[1][0], 500)
self.assertEqual(hdu.columns.data[1].array[0], 500)
self.assertEqual(tbhdu1.data[0][1], 500)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 500)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 500)
self.assertEqual(tbhdu1.columns._arrays[1][0], 500)
self.assertEqual(tbhdu1.columns.data[1].array[0], 500)
hdu.columns._arrays[1][0] = 600
self.assertEqual(hdu.data[0][1], 600)
self.assertEqual(hdu.data._coldefs._arrays[1][0], 600)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 600)
self.assertEqual(hdu.columns._arrays[1][0], 600)
self.assertEqual(hdu.columns.data[1].array[0], 600)
self.assertEqual(tbhdu1.data[0][1], 600)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 600)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 600)
self.assertEqual(tbhdu1.columns._arrays[1][0], 600)
self.assertEqual(tbhdu1.columns.data[1].array[0], 600)
hdu.columns.data[1].array[0] = 800
self.assertEqual(hdu.data[0][1], 800)
self.assertEqual(hdu.data._coldefs._arrays[1][0], 800)
self.assertEqual(hdu.data._coldefs.data[1].array[0], 800)
self.assertEqual(hdu.columns._arrays[1][0], 800)
self.assertEqual(hdu.columns.data[1].array[0], 800)
self.assertEqual(tbhdu1.data[0][1], 800)
self.assertEqual(tbhdu1.data._coldefs._arrays[1][0], 800)
self.assertEqual(tbhdu1.data._coldefs.data[1].array[0], 800)
self.assertEqual(tbhdu1.columns._arrays[1][0], 800)
self.assertEqual(tbhdu1.columns.data[1].array[0], 800)
def testBinTableWithLogicalArray(self):
c1=pyfits.Column(name='flag',format='2L',
array=[[True,False],[False,True]])
coldefs=pyfits.ColDefs([c1])
tbhdu1=pyfits.new_table(coldefs)
self.assertEqual(tbhdu1.data.field('flag')[0].all(),
num.array([True,False],
dtype = num.bool).all())
self.assertEqual(tbhdu1.data.field('flag')[1].all(),
num.array([False,True],
dtype = num.bool).all())
tbhdu = pyfits.new_table(tbhdu1.data)
self.assertEqual(tbhdu.data.field('flag')[0].all(),
num.array([True,False],
dtype = num.bool).all())
self.assertEqual(tbhdu.data.field('flag')[1].all(),
num.array([False,True],
dtype = num.bool).all())
def testVariableLengthTableFormatPDFromObjectArray(self):
a = num.array([num.array([7.2e-20,7.3e-20]),num.array([0.0]),
num.array([0.0])],'O')
acol = pyfits.Column(name='testa',format='PD()',array=a)
tbhdu = pyfits.new_table([acol])
tbhdu.writeto('newtable.fits')
tbhdu1 = pyfits.open('newtable.fits')
for j in range(0,3):
for i in range(0,len(a[j])):
self.assertEqual(tbhdu1[1].data.field(0)[j][i], a[j][i])
tbhdu1.close()
os.remove('newtable.fits')
def testVariableLengthTableFormatPDFromList(self):
a = [num.array([7.2e-20,7.3e-20]),num.array([0.0]),num.array([0.0])]
acol = pyfits.Column(name='testa',format='PD()',array=a)
tbhdu = pyfits.new_table([acol])
tbhdu.writeto('newtable.fits')
tbhdu1 = pyfits.open('newtable.fits')
for j in range(0,3):
for i in range(0,len(a[j])):
self.assertEqual(tbhdu1[1].data.field(0)[j][i], a[j][i])
tbhdu1.close()
os.remove('newtable.fits')
def testVariableLengthTableFormatPAFromObjectArray(self):
a = num.array([num.array(['a','b','c']), num.array(['d','e']),
num.array(['f'])],'O')
acol = pyfits.Column(name='testa',format='PA()',array=a)
tbhdu=pyfits.new_table([acol])
tbhdu.writeto('newtable.fits')
hdul=pyfits.open('newtable.fits')
for j in range(0,3):
for i in range(0,len(a[j])):
self.assertEqual(hdul[1].data.field(0)[j][i], a[j][i])
hdul.close()
os.remove('newtable.fits')
def testVariableLengthTableFormatPAFromList(self):
a = ['a','ab','abc']
acol = pyfits.Column(name='testa', format='PA()',array=a)
tbhdu=pyfits.new_table([acol])
tbhdu.writeto('newtable.fits')
hdul=pyfits.open('newtable.fits')
for j in range(0,3):
for i in range(0,len(a[j])):
self.assertEqual(hdul[1].data.field(0)[j][i], a[j][i])
hdul.close()
os.remove('newtable.fits')
def testFITS_recColumnAccess(self):
t=pyfits.open(test_dir+'table.fits')
tbdata = t[1].data
self.assertEqual(tbdata.V_mag.all(), tbdata.field('V_mag').all())
self.assertEqual(tbdata.V_mag.all(), tbdata['V_mag'].all())
t.close()
if __name__ == '__main__':
unittest.main()
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