def ifu_slicer2asdf(ifuslicer, outname, ref_kw):
"""
Create an asdf reference file with the MSA description.
ifu_slicer2asdf("IFU_slicer.sgd", "ifu_slicer.asdf")
Parameters
----------
ifuslicer : str
A fits file with the IFU slicer description
outname : str
Name of output ASDF file.
"""
f = fits.open(ifuslicer)
tree = ref_kw.copy()
data = f[1].data
header = f[1].header
shiftx = models.Shift(header['XREF'], name='ifu_slicer_xref')
shifty = models.Shift(header['YREF'], name='ifu_slicer_yref')
rot = models.Rotation2D(header['ROT'], name='ifu_slicer_rot')
model = rot | shiftx & shifty
tree['model'] = model
tree['data'] = f[1].data
f.close()
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def ifupost2asdf(ifupost_files, outname, ref_kw):
"""
Create a reference file of type ``ifupost`` .
Combines all IDT ``IFU-POST`` reference files in one ASDF file.
forward direction : MSA to Collimator
backward_direction: Collimator to MSA
Parameters
----------
ifupost_files : list
Names of all ``IFU-POST`` IDT reference files
outname : str
Name of output ``ASDF`` file
"""
fa = AsdfFile()
fa.tree = ref_kw
for fifu in ifupost_files:
n = int((fifu.split('IFU-POST_')[1]).split('.pcf')[0])
fa.tree[n] = {}
with open(fifu) as f:
lines = [l.strip() for l in f.readlines()]
factors = lines[lines.index('*Factor 2') + 1].split()
rotation_angle = float(lines[lines.index('*Rotation') + 1])
input_rot_center = lines[lines.index('*InputRotationCentre 2') + 1].split()
output_rot_center = lines[lines.index('*OutputRotationCentre 2') + 1].split()
linear_sky2det = homothetic_sky2det(input_rot_center, rotation_angle, factors, output_rot_center)
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1: xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_forward = models.Polynomial2D(degree, name='x_poly_forward', **xcoeff_forward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree, name='y_poly_forward', **ycoeff_forward)
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(degree, lines[xcoeff_index + 1: xcoeff_index + 22])
x_poly_backward = models.Polynomial2D(degree, name='x_poly_backward', **xcoeff_backward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree, name='y_poly_backward', **ycoeff_backward)
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (x_poly_forward & y_poly_forward) | output2poly_mapping
model = linear_sky2det | model_poly
fa.tree[n]['model'] = model
fa.add_history_entry("Build 6")
asdffile = fa.write_to(outname)
return asdffile
def ifu_slicer2asdf(ifuslicer, outname, ref_kw):
"""
Create an asdf reference file with the MSA description.
ifu_slicer2asdf("IFU_slicer.sgd", "ifu_slicer.asdf")
Parameters
----------
ifuslicer : str
A fits file with the IFU slicer description
outname : str
Name of output ASDF file.
"""
f = fits.open(ifuslicer)
tree = ref_kw.copy()
data = f[1].data
header = f[1].header
shiftx = models.Shift(header['XREF'], name='ifu_slicer_xref')
shifty = models.Shift(header['YREF'], name='ifu_slicer_yref')
rot = models.Rotation2D(header['ROT'], name='ifu_slicer_rot')
model = rot | shiftx & shifty
tree['model'] = model
tree['data'] = f[1].data
f.close()
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def ote2asdf(otepcf, outname, ref_kw):
"""
ref_kw = common_reference_file_keywords('OTE', 'NIRSPEC OTE transform - CDP4')
ote2asdf('Model/Ref_Files/CoordTransform/OTE.pcf', 'jwst_nirspec_ote_0001.asdf', ref_kw)
"""
with open(otepcf) as f:
lines = [l.strip() for l in f.readlines()]
factors = lines[lines.index('*Factor 2 1') + 1].split()
# this corresponds to modeling Rotation direction as is
rotation_angle = float(lines[lines.index('*Rotation') + 1])
input_rot_center = lines[lines.index('*InputRotationCentre 2 1') + 1].split()
output_rot_center = lines[lines.index('*OutputRotationCentre 2 1') + 1].split()
mlinear = homothetic_det2sky(input_rot_center, rotation_angle, factors, output_rot_center)
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1].split('\t')
xcoeff_backward = coeffs_from_pcf(degree, xlines)
x_poly_forward = models.Polynomial2D(degree, name='x_poly_forward', **xcoeff_backward)
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1].split('\t')
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_backward = models.Polynomial2D(degree, name='x_poly_backward', **xcoeff_forward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ylines = lines[ycoeff_index + 1].split('\t')
ycoeff_backward = coeffs_from_pcf(degree, ylines)
y_poly_forward = models.Polynomial2D(degree, name='y_poly_forward', **ycoeff_backward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ylines = lines[ycoeff_index + 1].split('\t')
ycoeff_forward = coeffs_from_pcf(degree, ylines)
y_poly_backward = models.Polynomial2D(degree, name='y_poly_backward', **ycoeff_forward)
x_poly_forward.inverse = x_poly_backward
y_poly_forward.inverse = y_poly_backward
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (x_poly_forward & y_poly_forward) | output2poly_mapping
model = model_poly | mlinear
f = AsdfFile()
f.tree = ref_kw.copy()
f.tree['model'] = model
f.add_history_entry("Build 6")
f.write_to(outname)
return model_poly, mlinear
def create_regions_file(slices, detector, band, channel, name, author,
useafter, description):
tree = create_reffile_header("REGIONS", detector, band, channel, author,
useafter, description)
tree['filename'] = name
f = AsdfFile()
tree['regions'] = slices
f.tree = tree
f.add_history_entry(
"DOCUMENT: MIRI-TN-00001-ETH; SOFTWARE: polyd2c_CDP5.pro; DATA USED: Data set of: - FM Test Campaign relevant to MRS-OPT-01, MRS-OPT-02, MRS-OPT-04, MRS-OPT-08; - CV1 Test Campaign relevant to MRS-OPT-02; - CV2 Test Campaign relevant to MRS-OPT-02; - Laboratory measurement of SPO; ============ DIFFERENCES: - New file structure: Change of Extention names and Table Column Headers.; - Replaced V2/V3 with XAN/YAN;"
)
f.write_to(name)
def wavelength_range(spectral_conf, outname, ref_kw):
"""
Parameters
----------
spectral_conf : str
reference file: spectralconfigurations.txt
outname : str
output file name
"""
with open(spectral_conf) as f:
lines = f.readlines()
lines = [l.strip() for l in lines][13:]
lines = [l.split() for l in lines]
tree = ref_kw.copy()
filter_grating = {}
for l in lines:
f_g = l[0] + '_' + l[1]
filter_grating[f_g] = {
'order': int(l[2]),
'range': [float(l[3]), float(l[4])]
}
tree['filter_grating'] = filter_grating
# values in lamp_grating come from private communication with the INS team
#lamp_grating = {}
filter_grating['FLAT1_G140M'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['LINE1_G140M'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['FLAT1_G140H'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['LINE1_G140H'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['FLAT2_G235M'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['LINE2_G235M'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['FLAT2_G235H'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['LINE2_G235H'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['FLAT3_G395M'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['LINE3_G395M'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['FLAT3_G395H'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['LINE3_G395H'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['REF_G140M'] = {'order': -1, 'range': [1.3e-6, 1.7e-6]}
filter_grating['REF_G140H'] = {'order': -1, 'range': [1.3e-6, 1.7e-6]}
filter_grating['TEST_MIRROR'] = {'order': -1, 'range': [0.6e-6, 5.3e-6]}
#for grating in ["G140H", "G140M", "G235H", "G235M", "G395H", "G395M", "MIRROR"]:
#lamp_grating['FLAT4_{0}'.format(grating)] = {'order': -1, 'range': [0.7e-6, 1.2e-6]}
#for grating in ["G140H", "G140M", "G235H", "G235M", "G395H", "G395M", "MIRROR"]:
#lamp_grating['LINE4_{0}'.format(grating)] = {'order': -1, 'range': [0.6e-6, 5.3e-6]}
#tree['lamp_grating'] = lamp_grating
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def wavelength_range(spectral_conf, outname, ref_kw):
"""
Parameters
----------
spectral_conf : str
reference file: spectralconfigurations.txt
outname : str
output file name
"""
with open(spectral_conf) as f:
lines = f.readlines()
lines = [l.strip() for l in lines][13 :]
lines = [l.split() for l in lines]
tree = ref_kw.copy()
filter_grating = {}
for l in lines:
f_g = l[0] + '_' + l[1]
filter_grating[f_g] = {'order': int(l[2]), 'range': [float(l[3]), float(l[4])]}
tree['filter_grating'] = filter_grating
# values in lamp_grating come from private communication with the INS team
#lamp_grating = {}
filter_grating['FLAT1_G140M'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['LINE1_G140M'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['FLAT1_G140H'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['LINE1_G140H'] = {'order': -1, 'range': [1e-6, 1.8e-6]}
filter_grating['FLAT2_G235M'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['LINE2_G235M'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['FLAT2_G235H'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['LINE2_G235H'] = {'order': -1, 'range': [1.7e-6, 3.1e-6]}
filter_grating['FLAT3_G395M'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['LINE3_G395M'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['FLAT3_G395H'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['LINE3_G395H'] = {'order': -1, 'range': [2.9e-6, 5.3e-6]}
filter_grating['REF_G140M'] = {'order': -1, 'range': [1.3e-6, 1.7e-6]}
filter_grating['REF_G140H'] = {'order': -1, 'range': [1.3e-6, 1.7e-6]}
filter_grating['TEST_MIRROR'] = {'order': -1, 'range': [0.6e-6, 5.3e-6]}
#for grating in ["G140H", "G140M", "G235H", "G235M", "G395H", "G395M", "MIRROR"]:
#lamp_grating['FLAT4_{0}'.format(grating)] = {'order': -1, 'range': [0.7e-6, 1.2e-6]}
#for grating in ["G140H", "G140M", "G235H", "G235M", "G395H", "G395M", "MIRROR"]:
#lamp_grating['LINE4_{0}'.format(grating)] = {'order': -1, 'range': [0.6e-6, 5.3e-6]}
#tree['lamp_grating'] = lamp_grating
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def create_wavelengthrange_file(name, detector, author, useafter, description):
f = AsdfFile()
# Relaxing the range to match the distortion. The table above
# comes from the report and is "as designed".
wavelengthrange = {
'1SHORT': (4.68, 5.97),
'1MEDIUM': (5.24, 6.87),
'1LONG': (6.2, 7.90),
'2SHORT': (7.27, 9.03),
'2MEDIUM': (8.43, 10.39),
'2LONG': (9.76, 11.97),
'3SHORT': (11.29, 13.75),
'3MEDIUM': (13.08, 15.86),
'3LONG': (15.14, 18.29),
'4SHORT': (17.40, 21.20),
'4MEDIUM': (20.31, 24.68),
'4LONG': (23.72, 28.75)
}
channels = [
'1SHORT', '1MEDIUM', '1LONG', '2SHORT', '2MEDIUM', '2LONG', '3SHORT',
'3MEDIUM', '3LONG', '4SHORT', '4MEDIUM', '4LONG'
]
tree = create_reffile_header("WAVELENGTHRANGE",
detector,
band="N/A",
channel="N/A",
author=author,
useafter=useafter,
description=description)
tree['filename'] = name
tree['author'] = 'Nadia Dencheva'
tree['detector'] = "N/A"
tree['channels'] = channels
f.tree = tree
vr = np.empty((12, 2), dtype=np.float)
for i, ch in enumerate(channels):
vr[i] = wavelengthrange[ch]
f.tree['wavelengthrange'] = vr
f.add_history_entry(
"DOCUMENT: MIRI-TN-00001-ETH; SOFTWARE: polyd2c_CDP5.pro; DATA USED: Data set of: - FM Test Campaign relevant to MRS-OPT-01, MRS-OPT-02, MRS-OPT-04, MRS-OPT-08; - CV1 Test Campaign relevant to MRS-OPT-02; - CV2 Test Campaign relevant to MRS-OPT-02; - Laboratory measurement of SPO; ============ DIFFERENCES: - New file structure: Change of Extention names and Table Column Headers.; - Replaced V2/V3 with XAN/YAN;"
)
f.write_to(name)
def create_distortion_file(reftype, detector, band, channel, data, name,
author, useafter, description):
description = 'MIRI MRS Distortion Maps'
tree = create_reffile_header(reftype, detector, band, channel, author,
useafter, description)
tree['filename'] = name
adata, bdata, xdata, ydata, bzero, bdel = data
tree['alpha_model'] = adata
tree['beta_model'] = bdata
tree['x_model'] = xdata
tree['y_model'] = ydata
tree['bzero'] = bzero
tree['bdel'] = bdel
f = AsdfFile()
f.tree = tree
f.add_history_entry(
"DOCUMENT: MIRI-TN-00001-ETH; SOFTWARE: polyd2c_CDP5.pro; DATA USED: Data set of: - FM Test Campaign relevant to MRS-OPT-01, MRS-OPT-02, MRS-OPT-04, MRS-OPT-08; - CV1 Test Campaign relevant to MRS-OPT-02; - CV2 Test Campaign relevant to MRS-OPT-02; - Laboratory measurement of SPO; ============ DIFFERENCES: - New file structure: Change of Extention names and Table Column Headers.; - Replaced V2/V3 with XAN/YAN;"
)
f.write_to(name)
def msa2asdf(msafile, outname, ref_kw):
"""
Create an asdf reference file with the MSA description.
mas2asfdf("MSA.msa", "msa.asdf")
Parameters
----------
msafile : str
A fits file with MSA description (MSA.msa)
outname : str
Name of output ASDF file.
"""
f = fits.open(msafile)
tree = ref_kw.copy()
data = f[5].data # SLITS and IFU
header = f[5].header
shiftx = models.Shift(header['SLITXREF'], name='slit_xref')
shifty = models.Shift(header['SLITYREF'], name='slit_yref')
slitrot = models.Rotation2D(header['SLITROT'], name='slit_rot')
tree[5] = {}
tree[5]['model'] = slitrot | shiftx & shifty
tree[5]['data'] = f[5].data
for i in range(1, 5):
header = f[i].header
shiftx = models.Shift(header['QUADXREF'], name='msa_xref')
shifty = models.Shift(header['QUADYREF'], name='msa_yref')
slitrot = models.Rotation2D(header['QUADROT'], name='msa_rot')
tree[i] = {}
tree[i]['model'] = slitrot | shiftx & shifty
tree[i]['data'] = f[i].data
f.close()
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def msa2asdf(msafile, outname, ref_kw):
"""
Create an asdf reference file with the MSA description.
mas2asfdf("MSA.msa", "msa.asdf")
Parameters
----------
msafile : str
A fits file with MSA description (MSA.msa)
outname : str
Name of output ASDF file.
"""
f = fits.open(msafile)
tree = ref_kw.copy()
data = f[5].data # SLITS and IFU
header = f[5].header
shiftx = models.Shift(header['SLITXREF'], name='slit_xref')
shifty = models.Shift(header['SLITYREF'], name='slit_yref')
slitrot = models.Rotation2D(header['SLITROT'], name='slit_rot')
tree[5] = {}
tree[5]['model'] = slitrot | shiftx & shifty
tree[5]['data'] = f[5].data
for i in range(1, 5):
header = f[i].header
shiftx = models.Shift(header['QUADXREF'], name='msa_xref')
shifty = models.Shift(header['QUADYREF'], name='msa_yref')
slitrot = models.Rotation2D(header['QUADROT'], name='msa_rot')
tree[i] = {}
tree[i]['model'] = slitrot | shiftx & shifty
tree[i]['data'] = f[i].data
f.close()
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def create_v23(reftype, detector, band, channels, data, name, author, useafter,
description):
"""
Create the transform from MIRI Local to telescope V2/V3 system for all channels.
"""
channel = "".join([ch[0] for ch in channels])
tree = create_reffile_header(reftype, detector, band, channel, author,
useafter, description)
"""
tree = {"detector": detector,
"instrument" : "MIRI",
"band": band,
"channel": channel,
"exp_type": "MIR_MRS",
"pedigree": "GROUND",
"title": "MIRI IFU model - based on CDP-4",
"reftype": reftype,
"author": author,
"useafter": useafter,
"description": description
}
"""
tree['filename'] = name
ab_v23 = data[0]
v23_ab = data[1]
m = {}
c0_0, c0_1, c1_0, c1_1 = ab_v23[0][1:]
ch1_v2 = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="ab_v23")
c0_0, c0_1, c1_0, c1_1 = v23_ab[0][1:]
ch1_a = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="v23_ab")
c0_0, c0_1, c1_0, c1_1 = ab_v23[1][1:]
ch1_v3 = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="ab_v23")
c0_0, c0_1, c1_0, c1_1 = v23_ab[1][1:]
ch1_b = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="v23_ab")
c0_0, c0_1, c1_0, c1_1 = ab_v23[2][1:]
ch2_v2 = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="ab_v23")
c0_0, c0_1, c1_0, c1_1 = v23_ab[2][1:]
ch2_a = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="v23_ab")
c0_0, c0_1, c1_0, c1_1 = ab_v23[3][1:]
ch2_v3 = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="ab_v23")
c0_0, c0_1, c1_0, c1_1 = v23_ab[3][1:]
ch2_b = models.Polynomial2D(2,
c0_0=c0_0,
c1_0=c1_0,
c0_1=c0_1,
c1_1=c1_1,
name="v23_ab")
ch1_for = ch1_v2 & ch1_v3
ch2_for = ch2_v2 & ch2_v3
ch1_for.inverse = ch1_a & ch1_b
ch2_for.inverse = ch2_a & ch2_b
m[channels[0]] = ch1_for
m[channels[1]] = ch2_for
tree['model'] = m
f = AsdfFile()
f.tree = tree
f.add_history_entry(
"DOCUMENT: MIRI-TN-00001-ETH; SOFTWARE: polyd2c_CDP5.pro; DATA USED: Data set of: - FM Test Campaign relevant to MRS-OPT-01, MRS-OPT-02, MRS-OPT-04, MRS-OPT-08; - CV1 Test Campaign relevant to MRS-OPT-02; - CV2 Test Campaign relevant to MRS-OPT-02; - Laboratory measurement of SPO; ============ DIFFERENCES: - New file structure: Change of Extention names and Table Column Headers.; - Replaced V2/V3 with XAN/YAN;"
)
f.write_to(name)
def ote2asdf(otepcf, outname, ref_kw):
"""
ref_kw = common_reference_file_keywords('OTE', 'NIRSPEC OTE transform - CDP4')
ote2asdf('Model/Ref_Files/CoordTransform/OTE.pcf', 'jwst_nirspec_ote_0001.asdf', ref_kw)
"""
with open(otepcf) as f:
lines = [l.strip() for l in f.readlines()]
factors = lines[lines.index('*Factor 2 1') + 1].split()
# this corresponds to modeling Rotation direction as is
rotation_angle = float(lines[lines.index('*Rotation') + 1])
input_rot_center = lines[lines.index('*InputRotationCentre 2 1') +
1].split()
output_rot_center = lines[lines.index('*OutputRotationCentre 2 1') +
1].split()
mlinear = homothetic_det2sky(input_rot_center, rotation_angle, factors,
output_rot_center)
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1].split('\t')
xcoeff_backward = coeffs_from_pcf(degree, xlines)
x_poly_forward = models.Polynomial2D(degree,
name='x_poly_forward',
**xcoeff_backward)
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1].split('\t')
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_backward = models.Polynomial2D(degree,
name='x_poly_backward',
**xcoeff_forward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ylines = lines[ycoeff_index + 1].split('\t')
ycoeff_backward = coeffs_from_pcf(degree, ylines)
y_poly_forward = models.Polynomial2D(degree,
name='y_poly_forward',
**ycoeff_backward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ylines = lines[ycoeff_index + 1].split('\t')
ycoeff_forward = coeffs_from_pcf(degree, ylines)
y_poly_backward = models.Polynomial2D(degree,
name='y_poly_backward',
**ycoeff_forward)
x_poly_forward.inverse = x_poly_backward
y_poly_forward.inverse = y_poly_backward
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (x_poly_forward
& y_poly_forward) | output2poly_mapping
model = model_poly | mlinear
f = AsdfFile()
f.tree = ref_kw.copy()
f.tree['model'] = model
f.add_history_entry("Build 6")
f.write_to(outname)
return model_poly, mlinear
def fpa2asdf(fpafile, outname, ref_kw):
"""
Create an asdf reference file with the FPA description.
The CDP2 delivery includes a fits file - "FPA.fpa" which is the
input to this function. This file is converted to asdf and is a
reference file of type "FPA".
nirspec_fs_ref_tools.fpa2asdf('Ref_Files/CoordTransform/Description/FPA.fpa', 'fpa.asdf')
Parameters
----------
fpafile : str
A fits file with FPA description (FPA.fpa)
outname : str
Name of output ASDF file.
"""
with open(fpafile) as f:
lines = [l.strip() for l in f.readlines()]
# NRS1
ind = lines.index("*SCA491_PitchX")
nrs1_pitchx = float(lines[ind + 1])
ind = lines.index("*SCA491_PitchY")
nrs1_pitchy = float(lines[ind + 1])
ind = lines.index("*SCA491_RotAngle")
nrs1_angle = float(lines[ind + 1])
ind = lines.index("*SCA491_PosX")
nrs1_posx = float(lines[ind + 1])
ind = lines.index("*SCA491_PosY")
nrs1_posy = float(lines[ind + 1])
# NRS2
ind = lines.index("*SCA492_PitchX")
nrs2_pitchx = float(lines[ind + 1])
ind = lines.index("*SCA492_PitchY")
nrs2_pitchy = float(lines[ind + 1])
ind = lines.index("*SCA492_RotAngle")
nrs2_angle = float(lines[ind + 1])
ind = lines.index("*SCA492_PosX")
nrs2_posx = float(lines[ind + 1])
ind = lines.index("*SCA492_PosY")
nrs2_posy = float(lines[ind + 1])
tree = ref_kw.copy()
# NRS1 Sky to Detector
scaling = np.array([[1 / nrs1_pitchx, 0], [0, 1 / nrs1_pitchy]])
rotmat = models.Rotation2D._compute_matrix(-nrs1_angle)
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_sky2detector')
nrs1_sky2det = models.Shift(-nrs1_posx, name='fpa_shift_x') & \
models.Shift(-nrs1_posy, name='fpa_shift_y') | aff
# NRS1 Detector to Sky
rotmat = models.Rotation2D._compute_matrix(-nrs1_angle)
scaling = np.array([[nrs1_pitchx, 0], [0, nrs1_pitchy]])
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_detector2sky')
nrs1_det2sky = aff | models.Shift(nrs1_posx, name='fpa_shift_x_det2sky') & \
models.Shift(nrs1_posy, name='fpa_shift_y_det2sky')
nrs1_det2sky.inverse = nrs1_sky2det
# NRS2 Sky to Detector
scaling = np.array([[-1 / nrs2_pitchx, 0], [0, -1 / nrs2_pitchy]])
rotmat = models.Rotation2D._compute_matrix(-nrs2_angle)
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_sky2detector')
nrs2_sky2det = models.Shift(-nrs2_posx, name='fpa_shixft_x') & \
models.Shift(-nrs2_posy, name='fpa_shift_y') | aff
# NRS2 Detector to Sky
rotmat = models.Rotation2D._compute_matrix(nrs2_angle)
scaling = np.array([[-nrs2_pitchx, 0], [0, -nrs2_pitchy]])
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_detector2sky')
nrs2_det2sky = aff | models.Shift(nrs2_posx, name='fpa_shift_x_det2sky') & \
models.Shift(nrs2_posy, name='fpa_shift_y_det2sky')
nrs2_det2sky.inverse = nrs2_sky2det
tree['NRS1'] = nrs1_det2sky
tree['NRS2'] = nrs2_det2sky
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def fore2asdf(pcffore, outname, ref_kw):
"""
forward direction : msa 2 ote
backward_direction: msa 2 fpa
"""
with open(pcffore) as f:
lines = [l.strip() for l in f.readlines()]
fore_det2sky = linear_from_pcf_det2sky(pcffore)
fore_linear = fore_det2sky
fore_linear.inverse = fore_det2sky.inverse & Identity(1)
# compute the polynomial
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1: xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
# Polynomial Correction in x
x_poly_backward = models.Polynomial2D(degree, name="x_poly_backward", **xcoeff_forward)
xlines_distortion = lines[xcoeff_index + 22: xcoeff_index + 43]
xcoeff_forward_distortion = coeffs_from_pcf(degree, xlines_distortion)
x_poly_backward_distortion = models.Polynomial2D(degree, name="x_backward_distortion",
**xcoeff_forward_distortion)
# do chromatic correction
# the input is Xote, Yote, lam
model_x_backward = (Mapping((0, 1), n_inputs=3) | x_poly_backward) + \
((Mapping((0,1), n_inputs=3) | x_poly_backward_distortion) * \
(Mapping((2,)) | Identity(1)))
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree, name="y_poly_backward", **ycoeff_forward)
ylines_distortion = lines[ycoeff_index + 22: ycoeff_index + 43]
ycoeff_forward_distortion = coeffs_from_pcf(degree, ylines_distortion)
y_poly_backward_distortion = models.Polynomial2D(degree, name="y_backward_distortion",
**ycoeff_forward_distortion)
# do chromatic correction
# the input is Xote, Yote, lam
model_y_backward = (Mapping((0,1), n_inputs=3) | y_poly_backward) + \
((Mapping((0, 1), n_inputs=3) | y_poly_backward_distortion) * \
(Mapping((2,)) | Identity(1) ))
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(degree, lines[xcoeff_index + 1: xcoeff_index + 22])
x_poly_forward = models.Polynomial2D(degree,name="x_poly_forward", **xcoeff_backward)
xcoeff_backward_distortion = coeffs_from_pcf(degree, lines[xcoeff_index + 22: xcoeff_index + 43])
x_poly_forward_distortion = models.Polynomial2D(degree, name="x_forward_distortion", **xcoeff_backward_distortion)
# the chromatic correction is done here
# the input is Xmsa, Ymsa, lam
model_x_forward = (Mapping((0,1), n_inputs=3) | x_poly_forward) + \
((Mapping((0,1), n_inputs=3) | x_poly_forward_distortion) * \
(Mapping((2,)) | Identity(1)))
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree, name="y_poly_forward",**ycoeff_backward)
ycoeff_backward_distortion = coeffs_from_pcf(degree, lines[ycoeff_index + 22: ycoeff_index + 43])
y_poly_forward_distortion = models.Polynomial2D(degree, name="y_forward_distortion",
**ycoeff_backward_distortion)
# do chromatic correction
# the input is Xmsa, Ymsa, lam
model_y_forward = (Mapping((0,1), n_inputs=3) | y_poly_forward) + \
((Mapping((0,1), n_inputs=3) | y_poly_forward_distortion) * \
(Mapping((2,)) | Identity(1)))
#assign inverse transforms
model_x = model_x_forward.copy()
model_y = model_y_forward.copy()
model_x.inverse = model_x_backward
model_y.inverse = model_y_backward
output2poly_mapping = Identity(2, name="output_mapping")
output2poly_mapping.inverse = Mapping([0, 1, 2, 0, 1, 2])
input2poly_mapping = Mapping([0, 1, 2, 0, 1, 2], name="input_mapping")
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (model_x & model_y) | output2poly_mapping
model = model_poly | fore_linear
f = AsdfFile()
f.tree = ref_kw.copy()
f.tree['model'] = model
f.add_history_entry("Build 6")
asdffile = f.write_to(outname)
return asdffile
def disperser2asdf(disfile, tiltyfile, tiltxfile, outname, ref_kw):
"""
Create a NIRSPEC disperser reference file in ASDF format.
Combine information stored in disperser_G?.dis and disperser_G?_TiltY.gtp
files delievred by the IDT.
disperser2asdf("disperser_G140H.dis", "disperser_G140H_TiltY.gtp", "disperserG140H.asdf")
Parameters
----------
disfile : list or str
A list of .dis files or a wild card string (*.dis).
tiltyfile : str
File with tilt_Y data, e.g. disperser_G395H_TiltY.gtp.
outname : str
Name of output ASDF file.
Returns
-------
fasdf : asdf.AsdfFile
"""
disperser = disfile.split('.dis')[0].split('_')[1]
with open(disfile) as f:
lines = [l.strip() for l in f.readlines()]
try:
ind = lines.index('*TYPE')
disperser_type = (lines[ind + 1]).lower()
except ValueError:
raise ValueError("Unknown disperser type in {0}".format(disfile))
if disperser_type == 'gratingdata':
d = dict.fromkeys(
['groove_density', 'theta_z', 'theta_y', 'theta_x', 'tilt_y'])
elif disperser_type == 'prismdata':
d = dict.fromkeys([
'tref', 'pref', 'angle', 'coefformula', 'thermalcoef', 'wbound'
'theta_z', 'theta_y', 'theta_x', 'tilt_y'
])
d.update(ref_kw)
try:
ind = lines.index('*GRATINGNAME')
grating_name = lines[ind + 1]
except ValueError:
grating_name = 'PRISM'
#for line in lines:
ind = lines.index('*THETAZ')
d['theta_z'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*THETAX')
d['theta_x'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*THETAY')
d['theta_y'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*TILTY')
d['tilt_y'] = float(lines[ind + 1]) # in degrees
try:
ind = lines.index('*TILTX')
d['tilt_x'] = float(lines[ind + 1]) # in degrees
except ValueError:
d['tilt_x'] = 0.0
if disperser_type == 'gratingdata':
ind = lines.index('*GROOVEDENSITY')
d['groove_density'] = float(lines[ind + 1])
elif disperser_type == 'prismdata':
ind = lines.index('*ANGLE')
d['angle'] = float(lines[ind + 1]) # in degrees
ind = lines.index('*TREF')
d['tref'] = float(lines[ind + 1]) # Temperature in K
ind = lines.index('*PREF')
d['pref'] = float(lines[ind + 1]) # Pressure in ATM
ind = lines.index('*COEFFORMULA')
coefs = np.array(lines[ind:ind + int(l[-1])], dtype=np.float)
kcoef = coefs[::2]
lcoef = coefs[1::2]
d['lcoef'] = lcoef
d['kcoef'] = kcoef
# 6 coeffs - D0, D1, D2, E0, E1, lambdak
ind = lines.index('*THERMALCOEF')
coefs = lines[ind:ind + int(l[-1])]
d['tcoef'] = [float(c) for c in coefs]
ind = lines.index('*WBOUND')
coefs = lines[ind:ind + 2]
d['wbound'] = [float(c) for c in coefs]
assert grating_name in tiltyfile
assert grating_name in tiltxfile
tiltyd = disperser_tilt(tiltyfile)
tiltxd = disperser_tilt(tiltxfile)
d['gwa_tiltx'] = tiltyd
d['gwa_tilty'] = tiltxd
fasdf = AsdfFile()
fasdf.tree = d
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def fore2asdf(pcffore, outname, ref_kw):
"""
forward direction : msa 2 ote
backward_direction: msa 2 fpa
"""
with open(pcffore) as f:
lines = [l.strip() for l in f.readlines()]
fore_det2sky = linear_from_pcf_det2sky(pcffore)
fore_linear = fore_det2sky
fore_linear.inverse = fore_det2sky.inverse & Identity(1)
# compute the polynomial
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1:xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
# Polynomial Correction in x
x_poly_backward = models.Polynomial2D(degree,
name="x_poly_backward",
**xcoeff_forward)
xlines_distortion = lines[xcoeff_index + 22:xcoeff_index + 43]
xcoeff_forward_distortion = coeffs_from_pcf(degree, xlines_distortion)
x_poly_backward_distortion = models.Polynomial2D(
degree, name="x_backward_distortion", **xcoeff_forward_distortion)
# do chromatic correction
# the input is Xote, Yote, lam
model_x_backward = (Mapping((0, 1), n_inputs=3) | x_poly_backward) + \
((Mapping((0,1), n_inputs=3) | x_poly_backward_distortion) * \
(Mapping((2,)) | Identity(1)))
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(degree,
lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree,
name="y_poly_backward",
**ycoeff_forward)
ylines_distortion = lines[ycoeff_index + 22:ycoeff_index + 43]
ycoeff_forward_distortion = coeffs_from_pcf(degree, ylines_distortion)
y_poly_backward_distortion = models.Polynomial2D(
degree, name="y_backward_distortion", **ycoeff_forward_distortion)
# do chromatic correction
# the input is Xote, Yote, lam
model_y_backward = (Mapping((0,1), n_inputs=3) | y_poly_backward) + \
((Mapping((0, 1), n_inputs=3) | y_poly_backward_distortion) * \
(Mapping((2,)) | Identity(1) ))
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(
degree, lines[xcoeff_index + 1:xcoeff_index + 22])
x_poly_forward = models.Polynomial2D(degree,
name="x_poly_forward",
**xcoeff_backward)
xcoeff_backward_distortion = coeffs_from_pcf(
degree, lines[xcoeff_index + 22:xcoeff_index + 43])
x_poly_forward_distortion = models.Polynomial2D(
degree, name="x_forward_distortion", **xcoeff_backward_distortion)
# the chromatic correction is done here
# the input is Xmsa, Ymsa, lam
model_x_forward = (Mapping((0,1), n_inputs=3) | x_poly_forward) + \
((Mapping((0,1), n_inputs=3) | x_poly_forward_distortion) * \
(Mapping((2,)) | Identity(1)))
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(
degree, lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree,
name="y_poly_forward",
**ycoeff_backward)
ycoeff_backward_distortion = coeffs_from_pcf(
degree, lines[ycoeff_index + 22:ycoeff_index + 43])
y_poly_forward_distortion = models.Polynomial2D(
degree, name="y_forward_distortion", **ycoeff_backward_distortion)
# do chromatic correction
# the input is Xmsa, Ymsa, lam
model_y_forward = (Mapping((0,1), n_inputs=3) | y_poly_forward) + \
((Mapping((0,1), n_inputs=3) | y_poly_forward_distortion) * \
(Mapping((2,)) | Identity(1)))
#assign inverse transforms
model_x = model_x_forward.copy()
model_y = model_y_forward.copy()
model_x.inverse = model_x_backward
model_y.inverse = model_y_backward
output2poly_mapping = Identity(2, name="output_mapping")
output2poly_mapping.inverse = Mapping([0, 1, 2, 0, 1, 2])
input2poly_mapping = Mapping([0, 1, 2, 0, 1, 2], name="input_mapping")
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (model_x & model_y) | output2poly_mapping
model = model_poly | fore_linear
f = AsdfFile()
f.tree = ref_kw.copy()
f.tree['model'] = model
f.add_history_entry("Build 6")
asdffile = f.write_to(outname)
return asdffile
def pcf2asdf(pcffile, outname, ref_file_kw):
"""
Create an asdf reference file with the transformation coded in a NIRSPEC
Camera.pcf or Collimator*.pcf file.
- forward (team): sky to detector
- Shift inputs to input_rotation_center
- Rotate inputs
- Scale inputs
- Shift inputs to output_rot_center
- Apply polynomial distortion
- backward_team (team definition) detector to sky
- Apply polynomial distortion
- Shift inputs to output_rot_center
- Scale inputs
- Rotate inputs
- Shift inputs to input_rotation_center
WCS implementation
- forward: detector to sky
- equivalent to backward_team
- backward: sky to detector
- equivalent to forward_team
Parameters
----------
pcffile : str
one of the NIRSPEC ".pcf" reference files provided by the IDT team.
"pcf" stands for "polynomial coefficients fit"
outname : str
Name of reference file to be wriiten to disk.
Returns
-------
fasdf : AsdfFile
AsdfFile object
Examples
--------
>>> pcf2asdf("Camera.pcf", "camera.asdf")
"""
linear_det2sky = linear_from_pcf_det2sky(pcffile)
with open(pcffile) as f:
lines = [l.strip() for l in f.readlines()]
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1:xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_backward = models.Polynomial2D(degree,
name='x_poly_backward',
**xcoeff_forward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(degree,
lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree,
name='y_poly_backward',
**ycoeff_forward)
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(
degree, lines[xcoeff_index + 1:xcoeff_index + 22])
x_poly_forward = models.Polynomial2D(degree,
name='x_poly_forward',
**xcoeff_backward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(
degree, lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree,
name='y_poly_forward',
**ycoeff_backward)
x_poly_forward.inverse = x_poly_backward
y_poly_forward.inverse = y_poly_backward
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (x_poly_forward
& y_poly_forward) | output2poly_mapping
model = model_poly | linear_det2sky
f = AsdfFile()
f.tree = ref_file_kw.copy()
f.add_history_entry("Build 6")
f.tree['model'] = model
f.write_to(outname)
def disperser2asdf(disfile, tiltyfile, tiltxfile, outname, ref_kw):
"""
Create a NIRSPEC disperser reference file in ASDF format.
Combine information stored in disperser_G?.dis and disperser_G?_TiltY.gtp
files delievred by the IDT.
disperser2asdf("disperser_G140H.dis", "disperser_G140H_TiltY.gtp", "disperserG140H.asdf")
Parameters
----------
disfile : list or str
A list of .dis files or a wild card string (*.dis).
tiltyfile : str
File with tilt_Y data, e.g. disperser_G395H_TiltY.gtp.
outname : str
Name of output ASDF file.
Returns
-------
fasdf : asdf.AsdfFile
"""
disperser = disfile.split('.dis')[0].split('_')[1]
with open(disfile) as f:
lines=[l.strip() for l in f.readlines()]
try:
ind = lines.index('*TYPE')
disperser_type = (lines[ind + 1]).lower()
except ValueError:
raise ValueError("Unknown disperser type in {0}".format(disfile))
if disperser_type == 'gratingdata':
d = dict.fromkeys(['groove_density', 'theta_z', 'theta_y', 'theta_x', 'tilt_y'])
elif disperser_type == 'prismdata':
d = dict.fromkeys(['tref', 'pref', 'angle', 'coefformula', 'thermalcoef', 'wbound'
'theta_z', 'theta_y', 'theta_x', 'tilt_y'])
d.update(ref_kw)
try:
ind = lines.index('*GRATINGNAME')
grating_name = lines[ind + 1]
except ValueError:
grating_name = 'PRISM'
#for line in lines:
ind = lines.index('*THETAZ')
d['theta_z'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*THETAX')
d['theta_x'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*THETAY')
d['theta_y'] = float(lines[ind + 1]) / 3600. # in degrees
ind = lines.index('*TILTY')
d['tilt_y'] = float(lines[ind + 1]) # in degrees
try:
ind = lines.index('*TILTX')
d['tilt_x'] = float(lines[ind + 1]) # in degrees
except ValueError:
d['tilt_x'] = 0.0
if disperser_type == 'gratingdata':
ind = lines.index('*GROOVEDENSITY')
d['groove_density'] = float(lines[ind + 1])
elif disperser_type == 'prismdata':
ind = lines.index('*ANGLE')
d['angle'] = float(lines[ind + 1]) # in degrees
ind = lines.index('*TREF')
d['tref'] = float(lines[ind + 1]) # Temperature in K
ind = lines.index('*PREF')
d['pref'] = float(lines[ind + 1]) # Pressure in ATM
ind = lines.index('*COEFFORMULA')
coefs = np.array(lines[ind : ind+int(l[-1])], dtype=np.float)
kcoef = coefs[::2]
lcoef = coefs[1::2]
d['lcoef'] = lcoef
d['kcoef'] = kcoef
# 6 coeffs - D0, D1, D2, E0, E1, lambdak
ind = lines.index('*THERMALCOEF')
coefs = lines[ind : ind+int(l[-1])]
d['tcoef'] = [float(c) for c in coefs]
ind = lines.index('*WBOUND')
coefs = lines[ind : ind + 2]
d['wbound'] = [float(c) for c in coefs]
assert grating_name in tiltyfile
assert grating_name in tiltxfile
tiltyd = disperser_tilt(tiltyfile)
tiltxd = disperser_tilt(tiltxfile)
d['gwa_tiltx'] = tiltyd
d['gwa_tilty'] = tiltxd
fasdf = AsdfFile()
fasdf.tree = d
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def pcf2asdf(pcffile, outname, ref_file_kw):
"""
Create an asdf reference file with the transformation coded in a NIRSPEC
Camera.pcf or Collimator*.pcf file.
- forward (team): sky to detector
- Shift inputs to input_rotation_center
- Rotate inputs
- Scale inputs
- Shift inputs to output_rot_center
- Apply polynomial distortion
- backward_team (team definition) detector to sky
- Apply polynomial distortion
- Shift inputs to output_rot_center
- Scale inputs
- Rotate inputs
- Shift inputs to input_rotation_center
WCS implementation
- forward: detector to sky
- equivalent to backward_team
- backward: sky to detector
- equivalent to forward_team
Parameters
----------
pcffile : str
one of the NIRSPEC ".pcf" reference files provided by the IDT team.
"pcf" stands for "polynomial coefficients fit"
outname : str
Name of reference file to be wriiten to disk.
Returns
-------
fasdf : AsdfFile
AsdfFile object
Examples
--------
>>> pcf2asdf("Camera.pcf", "camera.asdf")
"""
linear_det2sky = linear_from_pcf_det2sky(pcffile)
with open(pcffile) as f:
lines = [l.strip() for l in f.readlines()]
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1: xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_backward = models.Polynomial2D(degree, name='x_poly_backward', **xcoeff_forward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree, name='y_poly_backward', **ycoeff_forward)
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(degree, lines[xcoeff_index + 1: xcoeff_index + 22])
x_poly_forward = models.Polynomial2D(degree, name='x_poly_forward', **xcoeff_backward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(degree, lines[ycoeff_index + 1: ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree, name='y_poly_forward', **ycoeff_backward)
x_poly_forward.inverse = x_poly_backward
y_poly_forward.inverse = y_poly_backward
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (x_poly_forward & y_poly_forward) | output2poly_mapping
model = model_poly | linear_det2sky
f = AsdfFile()
f.tree = ref_file_kw.copy()
f.add_history_entry("Build 6")
f.tree['model'] = model
f.write_to(outname)
def ifupost2asdf(ifupost_files, outname, ref_kw):
"""
Create a reference file of type ``ifupost`` .
Combines all IDT ``IFU-POST`` reference files in one ASDF file.
forward direction : MSA to Collimator
backward_direction: Collimator to MSA
Parameters
----------
ifupost_files : list
Names of all ``IFU-POST`` IDT reference files
outname : str
Name of output ``ASDF`` file
"""
fa = AsdfFile()
fa.tree = ref_kw
for fifu in ifupost_files:
n = int((fifu.split('IFU-POST_')[1]).split('.pcf')[0])
fa.tree[n] = {}
with open(fifu) as f:
lines = [l.strip() for l in f.readlines()]
factors = lines[lines.index('*Factor 2') + 1].split()
rotation_angle = float(lines[lines.index('*Rotation') + 1])
input_rot_center = lines[lines.index('*InputRotationCentre 2') +
1].split()
output_rot_center = lines[lines.index('*OutputRotationCentre 2') +
1].split()
linear_sky2det = homothetic_sky2det(input_rot_center, rotation_angle,
factors, output_rot_center)
degree = int(lines[lines.index('*FitOrder') + 1])
xcoeff_index = lines.index('*xForwardCoefficients 21 2')
xlines = lines[xcoeff_index + 1:xcoeff_index + 22]
xcoeff_forward = coeffs_from_pcf(degree, xlines)
x_poly_forward = models.Polynomial2D(degree,
name='x_poly_forward',
**xcoeff_forward)
ycoeff_index = lines.index('*yForwardCoefficients 21 2')
ycoeff_forward = coeffs_from_pcf(
degree, lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_forward = models.Polynomial2D(degree,
name='y_poly_forward',
**ycoeff_forward)
xcoeff_index = lines.index('*xBackwardCoefficients 21 2')
xcoeff_backward = coeffs_from_pcf(
degree, lines[xcoeff_index + 1:xcoeff_index + 22])
x_poly_backward = models.Polynomial2D(degree,
name='x_poly_backward',
**xcoeff_backward)
ycoeff_index = lines.index('*yBackwardCoefficients 21 2')
ycoeff_backward = coeffs_from_pcf(
degree, lines[ycoeff_index + 1:ycoeff_index + 22])
y_poly_backward = models.Polynomial2D(degree,
name='y_poly_backward',
**ycoeff_backward)
output2poly_mapping = Identity(2, name='output_mapping')
output2poly_mapping.inverse = Mapping([0, 1, 0, 1])
input2poly_mapping = Mapping([0, 1, 0, 1], name='input_mapping')
input2poly_mapping.inverse = Identity(2)
model_poly = input2poly_mapping | (
x_poly_forward & y_poly_forward) | output2poly_mapping
model = linear_sky2det | model_poly
fa.tree[n]['model'] = model
fa.add_history_entry("Build 6")
asdffile = fa.write_to(outname)
return asdffile
def fpa2asdf(fpafile, outname, ref_kw):
"""
Create an asdf reference file with the FPA description.
The CDP2 delivery includes a fits file - "FPA.fpa" which is the
input to this function. This file is converted to asdf and is a
reference file of type "FPA".
nirspec_fs_ref_tools.fpa2asdf('Ref_Files/CoordTransform/Description/FPA.fpa', 'fpa.asdf')
Parameters
----------
fpafile : str
A fits file with FPA description (FPA.fpa)
outname : str
Name of output ASDF file.
"""
with open(fpafile) as f:
lines = [l.strip() for l in f.readlines()]
# NRS1
ind = lines.index("*SCA491_PitchX")
nrs1_pitchx = float(lines[ind+1])
ind = lines.index("*SCA491_PitchY")
nrs1_pitchy = float(lines[ind+1])
ind = lines.index("*SCA491_RotAngle")
nrs1_angle = float(lines[ind+1])
ind = lines.index("*SCA491_PosX")
nrs1_posx = float(lines[ind+1])
ind = lines.index("*SCA491_PosY")
nrs1_posy = float(lines[ind+1])
# NRS2
ind = lines.index("*SCA492_PitchX")
nrs2_pitchx = float(lines[ind+1])
ind = lines.index("*SCA492_PitchY")
nrs2_pitchy = float(lines[ind+1])
ind = lines.index("*SCA492_RotAngle")
nrs2_angle = float(lines[ind+1])
ind = lines.index("*SCA492_PosX")
nrs2_posx = float(lines[ind+1])
ind = lines.index("*SCA492_PosY")
nrs2_posy = float(lines[ind+1])
tree = ref_kw.copy()
# NRS1 Sky to Detector
scaling = np.array([[1/nrs1_pitchx, 0], [0, 1/nrs1_pitchy]])
rotmat = models.Rotation2D._compute_matrix(-nrs1_angle)
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_sky2detector')
nrs1_sky2det = models.Shift(-nrs1_posx, name='fpa_shift_x') & \
models.Shift(-nrs1_posy, name='fpa_shift_y') | aff
# NRS1 Detector to Sky
rotmat = models.Rotation2D._compute_matrix(-nrs1_angle)
scaling = np.array([[nrs1_pitchx, 0], [0, nrs1_pitchy]])
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_detector2sky')
nrs1_det2sky = aff | models.Shift(nrs1_posx, name='fpa_shift_x_det2sky') & \
models.Shift(nrs1_posy, name='fpa_shift_y_det2sky')
nrs1_det2sky.inverse = nrs1_sky2det
# NRS2 Sky to Detector
scaling = np.array([[-1/nrs2_pitchx, 0], [0, -1/nrs2_pitchy]])
rotmat = models.Rotation2D._compute_matrix(-nrs2_angle)
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_sky2detector')
nrs2_sky2det = models.Shift(-nrs2_posx, name='fpa_shixft_x') & \
models.Shift(-nrs2_posy, name='fpa_shift_y') | aff
# NRS2 Detector to Sky
rotmat = models.Rotation2D._compute_matrix(nrs2_angle)
scaling = np.array([[-nrs2_pitchx, 0], [0, -nrs2_pitchy]])
matrix = np.dot(rotmat, scaling)
aff = models.AffineTransformation2D(matrix, name='fpa_affine_detector2sky')
nrs2_det2sky = aff | models.Shift(nrs2_posx, name='fpa_shift_x_det2sky') & \
models.Shift(nrs2_posy, name='fpa_shift_y_det2sky')
nrs2_det2sky.inverse = nrs2_sky2det
tree['NRS1'] = nrs1_det2sky
tree['NRS2'] = nrs2_det2sky
fasdf = AsdfFile()
fasdf.tree = tree
fasdf.add_history_entry("Build 6")
fasdf.write_to(outname)
return fasdf
def create_nircam_distortion(coefffile, detector, aperture, opgsname, outname):
"""
Create an asdf reference file with all distortion components for the NIRCam imager.
NOTE: The IDT has not provided any distortion information. The files are constructed
using ISIM transformations provided/(computed?) by the TEL team which they use to
create the SIAF file.
These reference files should be replaced when/if the IDT provides us with distortion.
Parameters
----------
detector : str
NRCB1, NRCB2, NRCB3, NRCB4, NRCB5, NRCA1, NRCA2, NRCA3, NRCA4, NRCA5
aperture : str
Name of the aperture/subarray. (e.g. FULL, SUB160, SUB320, SUB640, GRISM_F322W2)
outname : str
Name of output file.
Examples
--------
"""
numdet = detector[-1]
module = detector[-2]
channel = 'SHORT'
if numdet == '5':
channel = 'LONG'
full_aperture = detector + '_' + aperture
#"Forward' transformations. science --> ideal --> V2V3
sci2idlx, sci2idly, sciunit, idlunit = read_siaf_table.get_siaf_transform(coefffile,full_aperture,'science','ideal', 5)
idl2v2v3x, idl2v2v3y = read_siaf_table.get_siaf_v2v3_transform(coefffile,full_aperture,from_system='ideal')
#'Reverse' transformations. V2V3 --> ideal --> science
v2v32idlx, v2v32idly = read_siaf_table.get_siaf_v2v3_transform(coefffile,full_aperture,to_system='ideal')
idl2scix, idl2sciy, idlunit, sciunit = read_siaf_table.get_siaf_transform(coefffile,full_aperture,'ideal','science', 5)
#Map the models together to make a single transformation
model = Mapping([0, 1, 0, 1]) | sci2idlx & sci2idly | Mapping([0, 1, 0, 1]) | idl2v2v3x & idl2v2v3y
model_inv = Mapping([0, 1, 0, 1]) | v2v32idlx & v2v32idly | Mapping([0, 1, 0, 1]) | idl2scix & idl2sciy
model.inverse = model_inv
#In the reference file headers, we need to switch NRCA5 to NRCALONG, and same
#for module B.
if detector[-1] == '5':
detector = detector[0:4] + 'LONG'
tree = {"TITLE": "NIRCAM Distortion",
"TELESCOP": "JWST",
"INSTRUMENT": "NIRCAM",
"PEDIGREE": "GROUND",
"REFTYPE" : "DISTORTION",
"AUTHOR": "B. Hilbert",
"DETECTOR": detector,
"MODULE": module,
"CHANNEL": channel,
"SUBARRAY": opgsname,
"DESCRIP": "Distortion model function created from SIAF coefficients",
"EXP_TYPE": "NRC_IMAGE",
"USEAFTER": "2014-01-01T00:00:00",
"model": model
}
fasdf = AsdfFile()
fasdf.tree = tree
sdict = {'name':'nircam_reftools.py','author':'B.Hilbert','homepage':'https://github.com/spacetelescope/jwreftools','version':'0.7'}
fasdf.add_history_entry("File created from a file of distortion coefficients, NIRCam_SIAF_2016-09-29.csv, provided by Colin Cox in October 2016. Software used: https://github.com/spacetelescope/jwreftools",software=sdict)
fasdf.write_to(outname)
def create_nircam_distortion(coefffile, detector, aperture, opgsname, outname):
"""
Create an asdf reference file with all distortion components for the NIRCam imager.
NOTE: The IDT has not provided any distortion information. The files are constructed
using ISIM transformations provided/(computed?) by the TEL team which they use to
create the SIAF file.
These reference files should be replaced when/if the IDT provides us with distortion.
Parameters
----------
detector : str
NRCB1, NRCB2, NRCB3, NRCB4, NRCB5, NRCA1, NRCA2, NRCA3, NRCA4, NRCA5
aperture : str
Name of the aperture/subarray. (e.g. FULL, SUB160, SUB320, SUB640, GRISM_F322W2)
outname : str
Name of output file.
Examples
--------
"""
numdet = detector[-1]
module = detector[-2]
channel = 'SHORT'
if numdet == '5':
channel = 'LONG'
full_aperture = detector + '_' + aperture
#"Forward' transformations. science --> ideal --> V2V3
sci2idlx, sci2idly, sciunit, idlunit = read_siaf_table.get_siaf_transform(
coefffile, full_aperture, 'science', 'ideal', 5)
idl2v2v3x, idl2v2v3y = read_siaf_table.get_siaf_v2v3_transform(
coefffile, full_aperture, from_system='ideal')
#'Reverse' transformations. V2V3 --> ideal --> science
v2v32idlx, v2v32idly = read_siaf_table.get_siaf_v2v3_transform(
coefffile, full_aperture, to_system='ideal')
idl2scix, idl2sciy, idlunit, sciunit = read_siaf_table.get_siaf_transform(
coefffile, full_aperture, 'ideal', 'science', 5)
#Map the models together to make a single transformation
model = Mapping([0, 1, 0, 1]) | sci2idlx & sci2idly | Mapping(
[0, 1, 0, 1]) | idl2v2v3x & idl2v2v3y
model_inv = Mapping([0, 1, 0, 1]) | v2v32idlx & v2v32idly | Mapping(
[0, 1, 0, 1]) | idl2scix & idl2sciy
model.inverse = model_inv
#In the reference file headers, we need to switch NRCA5 to NRCALONG, and same
#for module B.
if detector[-1] == '5':
detector = detector[0:4] + 'LONG'
tree = {
"TITLE": "NIRCAM Distortion",
"TELESCOP": "JWST",
"INSTRUMENT": "NIRCAM",
"PEDIGREE": "GROUND",
"REFTYPE": "DISTORTION",
"AUTHOR": "B. Hilbert",
"DETECTOR": detector,
"MODULE": module,
"CHANNEL": channel,
"SUBARRAY": opgsname,
"DESCRIP": "Distortion model function created from SIAF coefficients",
"EXP_TYPE": "NRC_IMAGE",
"USEAFTER": "2014-01-01T00:00:00",
"model": model
}
fasdf = AsdfFile()
fasdf.tree = tree
sdict = {
'name': 'nircam_reftools.py',
'author': 'B.Hilbert',
'homepage': 'https://github.com/spacetelescope/jwreftools',
'version': '0.7'
}
fasdf.add_history_entry(
"File created from a file of distortion coefficients, NIRCam_SIAF_2016-09-29.csv, provided by Colin Cox in October 2016. Software used: https://github.com/spacetelescope/jwreftools",
software=sdict)
fasdf.write_to(outname)
