def test_dictionary_class(self):
obj = DictionaryClass({'foo' : 'bar', 'nested' : {'myvar' : 5}})
self.assertEqual('bar', obj.foo)
self.assertEqual(5, obj.nested.myvar)
self.assertEqual({'foo' : 'bar', 'nested' : {'myvar' : 5}}, obj.get_dict())
def spectrum_redshift_calc(private_key, sender_id, msg_id, mtype, params,
extra):
"""
spectrum_redshift_calc
"""
try:
info("spectrum_redshift_calc()")
try:
payload = DictionaryClass(params)
x = decode_string(payload.x)
y = decode_string(payload.y)
yerr = decode_string(payload.yerr)
from_redshift = float(payload.from_redshift)
to_redshift = float(payload.to_redshift)
sed = Sed(x, y, yerr, from_redshift)
sed.redshift(to_redshift)
payload.x = encode_string(sed.wavelength)
payload.y = encode_string(sed.flux)
payload.yerr = encode_string(sed.err)
reply_success(msg_id, mtype, payload)
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def stack_normalize(private_key, sender_id, msg_id, mtype, params,
extra):
try:
info("stack_normalize()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
id_ = str(segment.id)
seds.append(IrisSed(x=x, y=y, yerr=yerr, id=id_))
stack = IrisStack(seds)
result = normalize(stack, payload)
for i, segment in enumerate(payload.segments):
segment.x = encode_string(result[i].x)
segment.y = encode_string(result[i].y)
segment.yerr = encode_string(result[i].yerr)
segment.norm_constant = str(result[i].norm_constant)
payload.excludeds = result.excluded
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def stack_normalize(private_key, sender_id, msg_id, mtype, params, extra):
try:
info("stack_normalize()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
id_ = str(segment.id)
seds.append(IrisSed(x=x, y=y, yerr=yerr, id=id_))
stack = IrisStack(seds)
result = normalize(stack, payload)
for i, segment in enumerate(payload.segments):
segment.x = encode_string(result[i].x)
segment.y = encode_string(result[i].y)
segment.yerr = encode_string(result[i].yerr)
segment.norm_constant = str(result[i].norm_constant)
payload.excludeds = result.excluded
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def stack_redshift(private_key, sender_id, msg_id, mtype, params,
extra):
try:
info("stack_redshift()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
z = float(segment.z)
id_ = str(segment.id)
seds.append(IrisSed(x=x, y=y, yerr=yerr, z=z, id=id_))
z0 = float(payload.z0)
correct_flux = payload.correct_flux == "true"
result = redshift(IrisStack(seds), z0, correct_flux)
for i, segment in enumerate(payload.segments):
segment.x = encode_string(result[i].x)
segment.y = encode_string(result[i].y)
segment.yerr = encode_string(result[i].yerr)
payload.excludeds = result.excluded
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def spectrum_redshift_calc(private_key, sender_id, msg_id, mtype, params,
extra):
"""
spectrum_redshift_calc
"""
try:
info("spectrum_redshift_calc()")
try:
payload = DictionaryClass(params)
x = decode_string(payload.x)
y = decode_string(payload.y)
yerr = decode_string(payload.yerr)
from_redshift = float(payload.from_redshift)
to_redshift = float(payload.to_redshift)
sed = Sed(x, y, yerr, from_redshift)
sed.redshift(to_redshift)
payload.x = encode_string(sed.wavelength)
payload.y = encode_string(sed.flux)
payload.yerr = encode_string(sed.err)
reply_success(msg_id, mtype, payload)
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def stack_redshift(private_key, sender_id, msg_id, mtype, params, extra):
try:
info("stack_redshift()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
z = float(segment.z)
id_ = str(segment.id)
seds.append(IrisSed(x=x, y=y, yerr=yerr, z=z, id=id_))
z0 = float(payload.z0)
correct_flux = payload.correct_flux == "true"
result = redshift(IrisStack(seds), z0, correct_flux)
for i, segment in enumerate(payload.segments):
segment.x = encode_string(result[i].x)
segment.y = encode_string(result[i].y)
segment.yerr = encode_string(result[i].yerr)
payload.excludeds = result.excluded
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def test_convert_underscores_to_hyphens(self):
params = {}
segment1 = {'x': [], 'y': [], 'yerr': [], 'norm_constant': 1.0}
segment2 = {'x': [], 'y': [], 'yerr': [], 'norm_constant': 1.0}
segment3 = {'x': [], 'y': [], 'yerr': [], 'norm_constant': 1.0}
params['segments'] = [segment1, segment2, segment3]
params['norm_operator'] = '0'
params['y0'] = '1.0'
params['xmin'] = 'min'
params['xmax'] = 'max'
params['stats'] = 'avg'
params['integrate'] = 'true'
payload = DictionaryClass(params)
for keys in payload.get_dict().keys():
if set(keys) & set("_"):
self.fail("Found a '_' in '%s' key." %keys)
segments = payload.get_dict()['segments']
for seg in segments:
for key in seg.keys():
if set(key) & set("_"):
self.fail("Found a '_' in '%s' key." %key)
self.assertEqual(len(payload.__dict__.keys()), 7)
self.assertEquals(len(segments), 3)
def spectrum_interpolate(private_key, sender_id, msg_id, mtype, params,
extra):
"""
spectrum_interpolate
"""
try:
info("spectrum_interpolate()")
try:
methods = {'Neville' : neville,
'Linear' : linear_interp,
'Nearest Neighbor' : nearest_interp,
'Linear Spline' : interp1d,
}
payload = DictionaryClass(params)
x = decode_string(payload.x)
y = decode_string(payload.y)
x_min = max(float(payload.x_min), min(x))
x_max = min(float(payload.x_max), max(x))
method = methods[payload.method]
info("method " + method.__name__)
n_bins = int(payload.n_bins)
log = payload.log=='true';
sed = Sed(x, y)
newSed = sed.interpolate(method, (x_min, x_max), n_bins, log);
filtered = False
if payload.smooth == "true":
info('smoothing')
newSed = filter(newSed)
newSed.smooth(int(payload.box_size))
if payload.normalize=="true":
info('normalizing')
if not filtered:
newSed = filter(newSed)
newSed.normalise()
payload.x = encode_string(newSed.wavelength)
payload.y = encode_string(newSed.flux)
reply_success(msg_id, mtype, payload)
info("success")
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
error("error: " + repr(e))
return
except Exception:
error(str(capture_exception()))
def spectrum_interpolate(private_key, sender_id, msg_id, mtype, params, extra):
"""
spectrum_interpolate
"""
try:
info("spectrum_interpolate()")
try:
methods = {
'Neville': neville,
'Linear': linear_interp,
'Nearest Neighbor': nearest_interp,
'Linear Spline': interp1d,
}
payload = DictionaryClass(params)
x = decode_string(payload.x)
y = decode_string(payload.y)
x_min = max(float(payload.x_min), min(x))
x_max = min(float(payload.x_max), max(x))
method = methods[payload.method]
info("method " + method.__name__)
n_bins = int(payload.n_bins)
log = payload.log == 'true'
sed = Sed(x, y)
newSed = sed.interpolate(method, (x_min, x_max), n_bins, log)
filtered = False
if payload.smooth == "true":
info('smoothing')
newSed = filter(newSed)
newSed.smooth(int(payload.box_size))
if payload.normalize == "true":
info('normalizing')
if not filtered:
newSed = filter(newSed)
newSed.normalise()
payload.x = encode_string(newSed.wavelength)
payload.y = encode_string(newSed.flux)
reply_success(msg_id, mtype, payload)
info("success")
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
error("error: " + repr(e))
return
except Exception:
error(str(capture_exception()))
def test_dictionary_class(self):
obj = DictionaryClass({'foo': 'bar', 'nested': {'myvar': 5}})
self.assertEqual('bar', obj.foo)
self.assertEqual(5, obj.nested.myvar)
self.assertEqual({
'foo': 'bar',
'nested': {
'myvar': 5
}
}, obj.get_dict())
def stack_stack(private_key, sender_id, msg_id, mtype, params, extra):
try:
info("stack_stack()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
seds.append(IrisSed(x=x, y=y, yerr=yerr))
i_stack = IrisStack(seds)
binsize = float(payload.binsize)
statistic = str(payload.statistic)
smooth = payload.smooth == "true"
smooth_binsize = float(payload.smooth_binsize)
logbin = payload.log_bin == "true"
result = sedstacker.sed.stack(i_stack,
binsize,
statistic,
fill='remove',
smooth=smooth,
smooth_binsize=smooth_binsize,
logbin=logbin)
payload.segments[0].x = encode_string(result.x)
payload.segments[0].y = encode_string(result.y)
payload.segments[0].yerr = encode_string(result.yerr)
payload.segments[0].counts = encode_string(result.counts)
payload.segments = [payload.segments[0]]
get_dict = payload.get_dict()
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def stack_stack(private_key, sender_id, msg_id, mtype, params,
extra):
try:
info("stack_stack()")
try:
payload = DictionaryClass(params)
seds = []
for segment in payload.segments:
x = decode_string(segment.x)
y = decode_string(segment.y)
yerr = decode_string(segment.yerr)
seds.append(IrisSed(x=x, y=y, yerr=yerr))
i_stack = IrisStack(seds)
binsize = float(payload.binsize)
statistic = str(payload.statistic)
smooth = payload.smooth == "true"
smooth_binsize = float(payload.smooth_binsize)
logbin = payload.log_bin == "true"
result = sedstacker.sed.stack(i_stack, binsize, statistic, fill='remove', smooth=smooth, smooth_binsize=smooth_binsize, logbin=logbin)
payload.segments[0].x = encode_string(result.x)
payload.segments[0].y = encode_string(result.y)
payload.segments[0].yerr = encode_string(result.yerr)
payload.segments[0].counts = encode_string(result.counts)
payload.segments = [payload.segments[0]]
get_dict = payload.get_dict()
reply_success(msg_id, mtype, payload.get_dict())
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def spectrum_integrate(private_key, sender_id, msg_id, mtype, params, extra):
"""
spectrum_integrate
"""
try:
info("spectrum_integrate()")
try:
payload = DictionaryClass(params)
x = decode_string(payload.x)
y = decode_string(payload.y)
sed = Sed(x, y)
response = dict()
response['points'] = list()
for curve in payload.curves:
pb = Passband(curve.file_name)
flux = sed.calcFlux(pb)
point = dict()
point['id'] = curve.id
point['wavelength'] = curve.eff_wave
point['flux'] = str(flux)
response['points'].append(point)
for window in payload.windows:
xmin = float(window.min)
xmax = float(window.max)
flux = sed.integrate(xmin, xmax)
point = dict()
point['id'] = window.id
point['wavelength'] = str((xmax + xmin) / 2)
point['flux'] = str(flux)
response['points'].append(point)
reply_success(msg_id, mtype, response)
except Exception, e:
reply_error(msg_id, sedexceptions.SEDException, e, mtype)
return
except Exception:
error(str(capture_exception()))
def test_normalize_by_int_median_mult(self):
x1 = encode_string(numpy.array([1, 5, 10, 15, 50, 100]))
y1 = encode_string(numpy.array([1, 5, 10, 15, 50, 100]) * 0.1)
yerr1 = encode_string(numpy.array([1, 5, 10, 15, 50, 100]) * 0.01)
x2 = encode_string(numpy.array([2, 4, 5, 8, 10]))
y2 = encode_string(numpy.arange(5) + 1.0)
yerr2 = encode_string(numpy.arange(5) + 1.0 * 0.1)
y3 = numpy.array([5.0, 15.0, 7.0, 4.5, 13.5, 10.5])
yerr3 = encode_string(y3 * 0.1)
y3 = encode_string(y3)
x3 = encode_string(numpy.array([0.5, 1.5, 3.0, 5.0, 10.5, 21.0]))
params = {}
segment1 = {'x': x1, 'y': y1, 'yerr': yerr1, 'id': 'sed1'}
segment2 = {'x': x2, 'y': y2, 'yerr': yerr2, 'id': 'sed2'}
segment3 = {'x': x3, 'y': y3, 'yerr': yerr3, 'id': 'sed3'}
params['segments'] = [segment1, segment2, segment3]
params['norm-operator'] = '0'
params['y0'] = '1.0'
params['xmin'] = 'min'
params['xmax'] = 'max'
params['stats'] = 'median'
params['integrate'] = 'true'
response = self.cli.callAndWait(
mtypes.cli.getPublicId(),
{'samp.mtype': MTYPE_STACK_NORMALIZE,
'samp.params': params},
"10")
assert response['samp.status'] == 'samp.ok'
results = response['samp.result']
norm_stack = DictionaryClass(results)
numpy.testing.assert_array_almost_equal(decode_string(norm_stack.segments[0].y), 0.4270427 * decode_string(y1))
numpy.testing.assert_array_almost_equal(decode_string(norm_stack.segments[1].y), 8.54 * decode_string(y2))
self.assertAlmostEqual(float(norm_stack.segments[2].norm_constant), 1.0)
def test_convert(self):
obj = DictionaryClass({"from-redshift": 5})
self.assertEqual(5, obj.from_redshift)
