from __future__ import absolute_import
from __future__ import print_function
import os
import sys
import shutil
import unittest
import time
import numpy
import re
from casatasks.private.casa_transition import is_CASA6
if is_CASA6:
from casatools import ctsys, quanta
from casatools import image as iatool
from casatasks import sdfixscan
_ia = iatool( )
qa = quanta( )
# default is not used in casatasks
def default(atask):
pass
else:
from __main__ import default
from tasks import *
from taskinit import iatool
from sdfixscan import sdfixscan
from taskinit import *
_ia = iatool()
# global qa tool is used here
#
# Unit test of sdfixscan task.
#
### Utility
def drop_stokes_axis(imagename, outimagename):
"""
create 3d image from 4d.
The function intends to drop Stokes axis and assumes that
the third axis is Stokes.
"""
myia = iatool( )
myia.open(imagename)
subimage = myia.subimage(outfile=outimagename, dropdeg=True,
keepaxes=[0,1,3])
subimage.close()
myia.close()
def drop_deg_axes(imagename, outimagename):
"""
create 2d image from 4d.
The function intends to drop both Stokes and Spectral axis and assumes that
the third axis is Spectral and fourth axis is Stokes.
"""
myia = iatool( )
myia.open(imagename)
subimage = myia.subimage(outfile=outimagename, dropdeg=True,
keepaxes=[0,1])
subimage.close()
myia.close()
###
# Base class for sdfixscan unit test
###
class sdfixscan_unittest_base:
"""
Base class for sdfixscan unit test
"""
taskname='sdfixscan'
if is_CASA6:
datapath=ctsys.resolve('unittest/sdfixscan/')
else:
datapath=os.path.join(os.environ.get('CASAPATH').split()[0],'casatestdata/unittest/sdfixscan/')
def _checkfile( self, name ):
isthere=os.path.exists(name)
self.assertEqual(isthere,True,
msg='output file %s was not created because of the task failure'%(name))
def _check_shape(self, infile, outfile):
self._checkfile(infile)
self._checkfile(outfile)
_ia.open(infile)
inshape = _ia.shape()
inaxistypes = _ia.coordsys().axiscoordinatetypes()
_ia.close()
_ia.open(outfile)
outshape = _ia.shape()
outaxistypes = _ia.coordsys().axiscoordinatetypes()
_ia.close()
self.assertEqual(len(inshape), len(outshape))
self.assertTrue(numpy.all(inshape == outshape))
self.assertEqual(inaxistypes, outaxistypes)
def _flux(self, csys, ref):
# see CAS-5779, images/Images/ImageStatistics.tcc
axis_ra = csys.findaxis(axis=csys.findaxisbyname('ra'))['axisincoordinate']
axis_dec = csys.findaxis(axis=csys.findaxisbyname('dec'))['axisincoordinate']
print(axis_ra, axis_dec)
units = csys.units()
increments = csys.increment()['numeric']
incr_ra = qa.quantity(abs(increments[axis_ra]), units[axis_ra])
incr_dec = qa.quantity(abs(increments[axis_dec]), units[axis_dec])
area = qa.convert(incr_ra, 'arcsec')['value'] * qa.convert(incr_dec, 'arcsec')['value']
return area * ref['sum']
def _checkstats(self,name,ref):
self._checkfile(name)
_ia.open(name)
stats=_ia.statistics(list=True, verbose=True)
# set 'flux' value to ref
if 'flux' not in ref:
ref['flux'] = self._flux(_ia.coordsys(), ref)
_ia.close()
for key in stats.keys():
#for key in self.keys:
message='statistics \'%s\' does not match: %s'%(key,str(stats[key]))
if type(stats[key])==str:
self.assertEqual(stats[key],ref[key],
msg=message)
else:
#print stats[key]-ref[key]
ret=numpy.allclose(stats[key],ref[key])
self.assertEqual(ret,True,
msg=message)
###
# Test on bad parameter settings
###
class sdfixscan_test0(unittest.TestCase,sdfixscan_unittest_base):
"""
Test on bad parameter setting
"""
# Input and output names
rawfiles=['scan_x.im','scan_y.im']
prefix=sdfixscan_unittest_base.taskname+'Test0'
outfile=prefix+'.im'
def setUp(self):
self.res=None
for name in self.rawfiles:
if (not os.path.exists(name)):
shutil.copytree(os.path.join(self.datapath,name), name)
default(sdfixscan)
def tearDown(self):
for name in self.rawfiles:
if (os.path.exists(name)):
shutil.rmtree(name)
os.system( 'rm -rf '+self.prefix+'*' )
def test000(self):
"""Test 000: Default parameters"""
# casatasks throw exception, CASA 5 tasks return False on failure
if is_CASA6:
self.assertRaises(Exception,sdfixscan)
else:
res=sdfixscan()
self.assertEqual(res,False)
def test001(self):
"""Test 001: only 1 image is given for Basket-Weaving"""
try:
res=sdfixscan(infiles=[self.rawfiles[0]],mode='fft_mask',direction=[0.])
self.assertTrue(False,
msg='The task must throw exception')
except Exception as e:
pos=str(e).find('infiles should be a list of input images for Basket-Weaving.')
self.assertNotEqual(pos,-1,
msg='Unexpected exception was thrown: %s'%(str(e)))
def test002(self):
"""Test 002: direction is not given for Basket-Weaving"""
try:
res=sdfixscan(infiles=self.rawfiles,mode='fft_mask')
self.assertTrue(False,
msg='The task must throw exception')
except Exception as e:
pos=str(e).find('direction must have at least two different direction.')
self.assertNotEqual(pos,-1,
msg='Unexpected exception was thrown: %s'%(str(e)))
def test003(self):
"""Test 003: Multiple images are given for Press"""
try:
res=sdfixscan(infiles=self.rawfiles,mode='model')
self.assertTrue(False,
msg='The task must throw exception')
except Exception as e:
pos=str(e).find('infiles allows only one input file for pressed-out method.')
self.assertNotEqual(pos,-1,
msg='Unexpected exception was thrown: %s'%(str(e)))
def test004(self):
"""Test 004: direction is not given for Press"""
try:
res=sdfixscan(infiles=[self.rawfiles[0]],mode='model')
self.assertTrue(False,
msg='The task must throw exception')
except Exception as e:
pos=str(e).find('direction allows only one direction for pressed-out method.')
self.assertNotEqual(pos,-1,
msg='Unexpected exception was thrown: %s'%(str(e)))
def test005(self):
"""Test 005: Existing output image file"""
shutil.copytree(os.path.join(self.datapath,self.rawfiles[0]), self.outfile)
self.assertRaises(Exception, sdfixscan, infiles=self.rawfiles,mode='fft_mask',direction=[0.,90.0],outfile=self.outfile,overwrite=False)
def test006(self):
"""Test 006: Zero beamsize for Press"""
self.assertRaises(Exception, sdfixscan, infiles=[self.rawfiles[0]],mode='model',beamsize=0.0,direction=[0.],outfile=self.outfile,overwrite=True)
###
# Test on Pressed method
###
class sdfixscan_test1(unittest.TestCase,sdfixscan_unittest_base):
"""
Test on Pressed method.
Test data, scan_x.im, is artificial data, which is
- 128x128 in R.A. and Dec.
- 1 polarization component (Stokes I)
- 1 spectral channel
- Gaussian source in the center
- 1% random noise
- scanning noise in horizontal direction
- smoothed by Gaussian kernel of FWHM of 10 pixel
"""
# Input and output names
rawfile='scan_x.im'
rawfilemod = rawfile.replace('.im', '_mod.im')
prefix=sdfixscan_unittest_base.taskname+'Test1'
outfile=prefix+'.im'
mode='model'
def setUp(self):
self.res=None
if os.path.exists(self.rawfile):
shutil.rmtree(self.rawfile)
shutil.copytree(os.path.join(self.datapath,self.rawfile), self.rawfile)
default(sdfixscan)
def tearDown(self):
if (os.path.exists(self.rawfile)):
shutil.rmtree(self.rawfile)
if (os.path.exists(self.rawfilemod)):
shutil.rmtree(self.rawfilemod)
os.system( 'rm -rf '+self.prefix+'*' )
def test100(self):
"""Test 100: Pressed method using whole pixels"""
res=sdfixscan(infiles=self.rawfile,mode=self.mode,numpoly=0,beamsize=300.0,smoothsize=2.0,direction=0.0,outfile=self.outfile,overwrite=True)
self.assertEqual(res,None,
msg='Any error occurred during imaging')
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.76603365]),
'maxpos': numpy.array([63, 63, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212, I, 1.415e+09Hz',
'mean': numpy.array([ 1.77990955e-11]),
'medabsdevmed': numpy.array([ 0.00867557]),
'median': numpy.array([-0.0022334]),
'min': numpy.array([-0.17581469]),
'minpos': numpy.array([25, 64, 0, 0], dtype=numpy.int32),
'minposf': '23:58:19.982, +01.04.00.222, I, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01854331]),
'rms': numpy.array([ 0.09749392]),
'sigma': numpy.array([ 0.09749689]),
'sum': numpy.array([ 2.91620381e-07]),
'sumsq': numpy.array([ 155.73097211]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfile, self.outfile)
self._checkstats(self.outfile,refstats)
def test101(self):
"""Test 101: Pressed method with certain threshold"""
res=sdfixscan(infiles=self.rawfile,mode=self.mode,numpoly=2,beamsize=300.0,smoothsize=2.0,direction=0.0,tmax=0.1,tmin=-0.1,outfile=self.outfile,overwrite=True)
self.assertEqual(res,None,
msg='Any error occurred during imaging')
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.91835594]),
'maxpos': numpy.array([63, 63, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212, I, 1.415e+09Hz',
'mean': numpy.array([ 0.02586879]),
'medabsdevmed': numpy.array([ 0.00599332]),
'median': numpy.array([ 0.00104136]),
'min': numpy.array([-0.03498788]),
'minpos': numpy.array([55, 0, 0, 0], dtype=numpy.int32),
'minposf': '23:56:19.991, +00.00.00.000, I, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01204253]),
'rms': numpy.array([ 0.11026896]),
'sigma': numpy.array([ 0.10719492]),
'sum': numpy.array([ 423.83432425]),
'sumsq': numpy.array([ 199.21705095]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfile, self.outfile)
self._checkstats(self.outfile,refstats)
def test102(self):
"""Test 102: Test mask in pressed method using whole pixels"""
# add spurious to image and mask the spurious.
my_ia = iatool( )
my_ia.open(self.rawfile)
try:
maxval = my_ia.statistics()['max'][0]
data = my_ia.getchunk()
data[15:25,15:25,:,:] = 100.*maxval
my_ia.putchunk(data)
del data
my_ia.calcmask("mask(%s) && '%s'<%f" % (self.rawfile, self.rawfile, 10.*maxval),
name="sprious", asdefault=True)
mask_in = my_ia.getchunk(getmask=True)
mpix = numpy.where(mask_in==False)
self.assertEqual(len(mpix[0]),100,"Failed to set mask properly at pre-processing.")
except: raise
finally: my_ia.close()
del my_ia
# Task execution
res=sdfixscan(infiles=self.rawfile,mode=self.mode,numpoly=0,beamsize=300.0,smoothsize=2.0,direction=0.0,outfile=self.outfile,overwrite=True)
# Test results
self.assertEqual(res,None,
msg='Any error occurred during imaging')
refstats = {'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.75250125]),
'maxpos': numpy.array([63, 63, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212, I, 1.415e+09Hz',
'mean': numpy.array([-0.00220275]),
'medabsdevmed': numpy.array([ 0.00883335]),
'median': numpy.array([-0.00232762]),
'min': numpy.array([-0.18934998]),
'minpos': numpy.array([25, 64, 0, 0], dtype=numpy.int32),
'minposf': '23:58:19.982, +01.04.00.222, I, 1.415e+09Hz',
'npts': numpy.array([ 16284.]),
'quartile': numpy.array([ 0.01897511]),
'rms': numpy.array([ 0.09790624]),
'sigma': numpy.array([ 0.09788447]),
'sum': numpy.array([-35.86960435]),
'sumsq': numpy.array([ 156.09243727]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfile, self.outfile)
self._checkstats(self.outfile,refstats)
_ia.open(self.outfile)
mask_out = _ia.getchunk(getmask=True)
_ia.close()
self.assertTrue((mask_out==mask_in).all(), "Unexpected mask in output image.")
def test100_3d(self):
"""Test 100_3d: Pressed method using whole pixels for 3D image"""
drop_stokes_axis(self.rawfile, self.rawfilemod)
self.assertTrue(os.path.exists(self.rawfilemod))
res=sdfixscan(infiles=self.rawfilemod,mode=self.mode,numpoly=0,beamsize=300.0,smoothsize=2.0,direction=0.0,outfile=self.outfile,overwrite=True)
self.assertEqual(res,None,
msg='Any error occurred during imaging')
refstats={'blc': numpy.array([0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, 1.415e+09Hz',
'max': numpy.array([ 0.76603365]),
'maxpos': numpy.array([63, 63, 0], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212, 1.415e+09Hz',
'mean': numpy.array([ 1.77990955e-11]),
'medabsdevmed': numpy.array([ 0.00867557]),
'median': numpy.array([-0.0022334]),
'min': numpy.array([-0.17581469]),
'minpos': numpy.array([25, 64, 0], dtype=numpy.int32),
'minposf': '23:58:19.982, +01.04.00.222, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01854331]),
'rms': numpy.array([ 0.09749392]),
'sigma': numpy.array([ 0.09749689]),
'sum': numpy.array([ 2.91620381e-07]),
'sumsq': numpy.array([ 155.73097211]),
'trc': numpy.array([127, 127, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, 1.415e+09Hz'}
self._check_shape(self.rawfilemod, self.outfile)
self._checkstats(self.outfile,refstats)
def test100_2d(self):
"""Test 100_2d: Pressed method using whole pixels for 2D image"""
drop_deg_axes(self.rawfile, self.rawfilemod)
self.assertTrue(os.path.exists(self.rawfilemod))
res=sdfixscan(infiles=self.rawfilemod,mode=self.mode,numpoly=0,beamsize=300.0,smoothsize=2.0,direction=0.0,outfile=self.outfile,overwrite=True)
self.assertEqual(res,None,
msg='Any error occurred during imaging')
refstats={'blc': numpy.array([0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000',
'max': numpy.array([ 0.76603365]),
'maxpos': numpy.array([63, 63], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212',
'mean': numpy.array([ 1.77990955e-11]),
'medabsdevmed': numpy.array([ 0.00867557]),
'median': numpy.array([-0.0022334]),
'min': numpy.array([-0.17581469]),
'minpos': numpy.array([25, 64], dtype=numpy.int32),
'minposf': '23:58:19.982, +01.04.00.222',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01854331]),
'rms': numpy.array([ 0.09749392]),
'sigma': numpy.array([ 0.09749689]),
'sum': numpy.array([ 2.91620381e-07]),
'sumsq': numpy.array([ 155.73097211]),
'trc': numpy.array([127, 127], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734'}
self._check_shape(self.rawfilemod, self.outfile)
self._checkstats(self.outfile,refstats)
###
# Test on FFT based Basket-Weaving
###
class sdfixscan_test2(unittest.TestCase,sdfixscan_unittest_base):
"""
Test on FFT based Basket-Weaving
Test data, scan_x.im and scan_y.im, are artificial data, which is
- 128x128 in R.A. and Dec.
- 1 polarization component (Stokes I)
- 1 spectral channel
- Gaussian source in the center
- 1% random noise
- scanning noise in horizontal direction (scan_x.im)
or vertical direction (scan_y.im)
- smoothed by Gaussian kernel of FWHM of 10 pixel
"""
# Input and output names
rawfiles=['scan_x.im','scan_y.im']
rawfilesmod = list(map(lambda x: x.replace('.im', '_mod.im'), rawfiles))
prefix=sdfixscan_unittest_base.taskname+'Test2'
outfile=prefix+'.im'
mode='fft_mask'
def setUp(self):
self.res=None
for name in self.rawfiles:
if os.path.exists(name):
shutil.rmtree(name)
shutil.copytree(os.path.join(self.datapath,name), name)
default(sdfixscan)
def tearDown(self):
for name in self.rawfiles:
if (os.path.exists(name)):
shutil.rmtree(name)
for name in self.rawfilesmod:
if (os.path.exists(name)):
shutil.rmtree(name)
os.system( 'rm -rf '+self.prefix+'*' )
def test200(self):
"""Test 200: FFT based Basket-Weaving using whole pixels"""
res=sdfixscan(infiles=self.rawfiles,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,outfile=self.outfile,overwrite=True)
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.92863309]),
'maxpos': numpy.array([64, 64, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:43.941, +01.04.00.222, I, 1.415e+09Hz',
'mean': numpy.array([ 0.02962625]),
'medabsdevmed': numpy.array([ 0.00571492]),
'median': numpy.array([ 0.00429045]),
'min': numpy.array([-0.02551341]),
'minpos': numpy.array([ 56, 107, 0, 0], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037, I, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01154788]),
'rms': numpy.array([ 0.11279197]),
'sigma': numpy.array([ 0.1088349]),
'sum': numpy.array([ 485.39648429]),
'sumsq': numpy.array([ 208.43769809]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfiles[0], self.outfile)
self._checkstats(self.outfile,refstats)
def test201(self):
"""Test 201: FFT based Basket-Weaving with certain threshold"""
res=sdfixscan(infiles=self.rawfiles,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,tmax=0.5,tmin=-0.1,outfile=self.outfile,overwrite=True)
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.99608284]),
'maxpos': numpy.array([63, 63, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:47.944, +01.03.00.212, I, 1.415e+09Hz',
'mean': numpy.array([ 0.02962625]),
'medabsdevmed': numpy.array([ 0.00570825]),
'median': numpy.array([ 0.00428429]),
'min': numpy.array([-0.02518307]),
'minpos': numpy.array([ 56, 107, 0, 0], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037, I, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01155156]),
'rms': numpy.array([ 0.113305]),
'sigma': numpy.array([ 0.10936653]),
'sum': numpy.array([ 485.39650849]),
'sumsq': numpy.array([ 210.3381585]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfiles[0], self.outfile)
self._checkstats(self.outfile,refstats)
def test202(self):
"""Test 202: Test mask in FFT based Basket-Weaving using whole pixels"""
# add spurious to images and mask the spurious pixels.
spix = [10, 15]
epix = [20, 25]
mask_in = []
my_ia = iatool( )
for i in range(len(self.rawfiles)):
name = self.rawfiles[i]
s = spix[i % len(spix)]
e = epix[i % len(epix)]
my_ia.open(name)
try:
maxval = my_ia.statistics()['max'][0]
data = my_ia.getchunk()
data[s:e,s:e,:,:] = 100.*maxval
my_ia.putchunk(data)
del data
my_ia.calcmask("mask(%s) && '%s'<%f" % (name, name, 10.*maxval),
name="sprious", asdefault=True)
mask_in.append(my_ia.getchunk(getmask=True))
except: raise
finally: my_ia.done()
mpix = numpy.where(mask_in[i]==False)
self.assertEqual(len(mpix[0]),(e-s)**2,"Failed to set mask properly at pre-processing.")
del my_ia
mask_ref = mask_in[0]
for msk in mask_in:
mask_ref += msk
del mask_in
# Task execution
res=sdfixscan(infiles=self.rawfiles,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,outfile=self.outfile,overwrite=True)
# Test results
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.92862648]),
'maxpos': numpy.array([64, 64, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:43.941, +01.04.00.222, I, 1.415e+09Hz',
'mean': numpy.array([ 0.02969963]),
'medabsdevmed': numpy.array([ 0.00574234]),
'median': numpy.array([ 0.00439214]),
'min': numpy.array([-0.02554246]),
'minpos': numpy.array([ 56, 107, 0, 0], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037, I, 1.415e+09Hz',
'npts': numpy.array([ 16359.]),
'quartile': numpy.array([ 0.011633]),
'rms': numpy.array([ 0.11288381]),
'sigma': numpy.array([ 0.10891011]),
'sum': numpy.array([ 485.85626113]),
'sumsq': numpy.array([ 208.45871511]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
#print imstat(self.outfile)
self._check_shape(self.rawfiles[0], self.outfile)
self._checkstats(self.outfile,refstats)
_ia.open(self.outfile)
mask_out = _ia.getchunk(getmask=True)
_ia.close()
self.assertTrue((mask_out==mask_ref).all(), "Unexpected mask in output image.")
def test203(self):
"""Test 203: test for len(infiles) > len(direction)"""
infiles = self.rawfiles + self.rawfiles
res=sdfixscan(infiles=infiles,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,outfile=self.outfile,overwrite=True)
refstats={'blc': numpy.array([0, 0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, I, 1.415e+09Hz',
'max': numpy.array([ 0.92863309]),
'maxpos': numpy.array([64, 64, 0, 0], dtype=numpy.int32),
'maxposf': '23:55:43.941, +01.04.00.222, I, 1.415e+09Hz',
'mean': numpy.array([ 0.02962625]),
'medabsdevmed': numpy.array([ 0.00571492]),
'median': numpy.array([ 0.00429045]),
'min': numpy.array([-0.02551341]),
'minpos': numpy.array([ 56, 107, 0, 0], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037, I, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01154788]),
'rms': numpy.array([ 0.11279196]),
'sigma': numpy.array([ 0.1088349]),
'sum': numpy.array([ 485.39648429]),
'sumsq': numpy.array([ 208.4376955]),
'trc': numpy.array([127, 127, 0, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, I, 1.415e+09Hz'}
self._check_shape(self.rawfiles[0], self.outfile)
self._checkstats(self.outfile,refstats)
def test200_3d(self):
"""Test 200_3d: FFT based Basket-Weaving using whole pixels for 3D image"""
for infile, outfile in zip(self.rawfiles, self.rawfilesmod):
drop_stokes_axis(infile, outfile)
self.assertTrue(os.path.exists(outfile))
res=sdfixscan(infiles=self.rawfilesmod,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,outfile=self.outfile,overwrite=True)
refstats={'blc': numpy.array([0, 0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000, 1.415e+09Hz',
'max': numpy.array([ 0.92863309]),
'maxpos': numpy.array([64, 64, 0], dtype=numpy.int32),
'maxposf': '23:55:43.941, +01.04.00.222, 1.415e+09Hz',
'mean': numpy.array([ 0.02962625]),
'medabsdevmed': numpy.array([ 0.00571492]),
'median': numpy.array([ 0.00429045]),
'min': numpy.array([-0.02551341]),
'minpos': numpy.array([ 56, 107, 0], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037, 1.415e+09Hz',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01154788]),
'rms': numpy.array([ 0.11279197]),
'sigma': numpy.array([ 0.1088349]),
'sum': numpy.array([ 485.39648429]),
'sumsq': numpy.array([ 208.43769809]),
'trc': numpy.array([127, 127, 0], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734, 1.415e+09Hz'}
self._check_shape(self.rawfilesmod[0], self.outfile)
self._checkstats(self.outfile,refstats)
def test200_2d(self):
"""Test 200_2d: FFT based Basket-Weaving using whole pixels for 2D image"""
for infile, outfile in zip(self.rawfiles, self.rawfilesmod):
drop_deg_axes(infile, outfile)
self.assertTrue(os.path.exists(outfile))
res=sdfixscan(infiles=self.rawfilesmod,mode=self.mode,direction=[0.0,90.0],maskwidth=20.0,outfile=self.outfile,overwrite=True)
refstats={'blc': numpy.array([0, 0], dtype=numpy.int32),
'blcf': '00:00:00.000, +00.00.00.000',
'max': numpy.array([ 0.92863309]),
'maxpos': numpy.array([64, 64], dtype=numpy.int32),
'maxposf': '23:55:43.941, +01.04.00.222',
'mean': numpy.array([ 0.02962625]),
'medabsdevmed': numpy.array([ 0.00571492]),
'median': numpy.array([ 0.00429045]),
'min': numpy.array([-0.02551341]),
'minpos': numpy.array([ 56, 107], dtype=numpy.int32),
'minposf': '23:56:15.881, +01.47.01.037',
'npts': numpy.array([ 16384.]),
'quartile': numpy.array([ 0.01154788]),
'rms': numpy.array([ 0.11279197]),
'sigma': numpy.array([ 0.1088349]),
'sum': numpy.array([ 485.39648429]),
'sumsq': numpy.array([ 208.43769809]),
'trc': numpy.array([127, 127], dtype=numpy.int32),
'trcf': '23:51:31.537, +02.07.01.734'}
self._check_shape(self.rawfilesmod[0], self.outfile)
self._checkstats(self.outfile,refstats)
def suite():
return [sdfixscan_test0,
sdfixscan_test1,
sdfixscan_test2]
if is_CASA6:
if __name__ == '__main__':
unittest.main()