def __init__(self, experiments, reference, reflections):
'''
Create the integration report
:param experiments: The experiment list
:param reference: The reference profiles
:param reflections: The reflection table
'''
from collections import OrderedDict
# Initialise the report class
super(ProfileModelReport, self).__init__()
# Create the table
table = Table()
# Set the title
table.name = 'profile.summary'
table.title = 'Summary of profile model'
# Add the columns
table.cols.append(('id', 'ID'))
table.cols.append(('profile', 'Profile'))
table.cols.append(('created', 'Created'))
table.cols.append(('x', 'X (px)'))
table.cols.append(('y', 'Y (px)'))
table.cols.append(('z', 'Z (im)'))
table.cols.append(('n_reflections', '# reflections'))
# Create the summary for each profile model
for i in range(len(reference)):
model = reference[i]
for j in range(len(model)):
table.rows.append([
'%d' % i,
'%d' % j,
'%s' % True,
'%.2f' % model.sampler().coord(j)[0],
'%.2f' % model.sampler().coord(j)[1],
'%.2f' % model.sampler().coord(j)[2],
'%d' % model.n_reflections(j)
])
# Add the table
self.add_table(table)
# Add the profiles
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
if model.valid(j):
array = Array()
array.name = 'profile.model.%d.%d' % (i, j)
array.title = 'Profile model (id: %d, profile: %d)' % (i,
j)
array.data = model.data(j)
self.add_array(array)
def __init__(self, experiments, reference, reflections):
"""
Create the integration report
:param experiments: The experiment list
:param reference: The reference profiles
:param reflections: The reflection table
"""
from collections import OrderedDict
# Initialise the report class
super(ProfileModelReport, self).__init__()
# Create the table
table = Table()
# Set the title
table.name = "profile.summary"
table.title = "Summary of profile model"
# Add the columns
table.cols.append(("id", "ID"))
table.cols.append(("profile", "Profile"))
table.cols.append(("created", "Created"))
table.cols.append(("x", "X (px)"))
table.cols.append(("y", "Y (px)"))
table.cols.append(("z", "Z (im)"))
table.cols.append(("n_reflections", "# reflections"))
# Create the summary for each profile model
for i in range(len(reference)):
model = reference[i]
for j in range(len(model)):
table.rows.append([
"%d" % i,
"%d" % j,
"%s" % True,
"%.2f" % model.sampler().coord(j)[0],
"%.2f" % model.sampler().coord(j)[1],
"%.2f" % model.sampler().coord(j)[2],
"%d" % model.n_reflections(j),
])
# Add the table
self.add_table(table)
# Add the profiles
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
if model.valid(j):
array = Array()
array.name = "profile.model.%d.%d" % (i, j)
array.title = "Profile model (id: %d, profile: %d)" % (i,
j)
array.data = model.data(j)
self.add_array(array)
def __init__(self, experiments, fitter, reflections):
"""
Create the integration report
:param experiments: The experiment list
:param profile_model: The profile model
:param reflections: The reflection table
"""
# Initialise the report class
super().__init__()
# Create the table
table = Table()
# Set the title
table.name = "profile.summary"
table.title = "Summary of profile model"
# Add the columns
table.cols.append(("id", "ID"))
table.cols.append(("profile", "Profile"))
table.cols.append(("created", "Created"))
table.cols.append(("x", "X (px)"))
table.cols.append(("y", "Y (px)"))
table.cols.append(("z", "Z (im)"))
table.cols.append(("n_reflections", "# reflections"))
# Create the summary for each profile model
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
table.rows.append(
[
"%d" % i,
"%d" % j,
f"{model.valid(j)}",
f"{model.coord(j)[0]:.2f}",
f"{model.coord(j)[1]:.2f}",
f"{model.coord(j)[2]:.2f}",
"%d" % model.n_reflections(j),
]
)
# Add the table
self.add_table(table)
# Add the profiles
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
if model.valid(j):
array = Array()
array.name = "profile.model.%d.%d" % (i, j)
array.title = "Profile model (id: %d, profile: %d)" % (i, j)
array.data = model.data(j)
self.add_array(array)
def __init__(self, experiments, fitter, reflections):
'''
Create the integration report
:param experiments: The experiment list
:param profile_model: The profile model
:param reflections: The reflection table
'''
from collections import OrderedDict
# Initialise the report class
super(ProfileModelReport, self).__init__()
# Create the table
table = Table()
# Set the title
table.name = 'profile.summary'
table.title = 'Summary of profile model'
# Add the columns
table.cols.append(('id', 'ID'))
table.cols.append(('profile', 'Profile'))
table.cols.append(('created', 'Created'))
table.cols.append(('x', 'X (px)'))
table.cols.append(('y', 'Y (px)'))
table.cols.append(('z', 'Z (im)'))
table.cols.append(('n_reflections', '# reflections'))
# Create the summary for each profile model
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
table.rows.append([
'%d' % i,
'%d' % j,
'%s' % model.valid(j),
'%.2f' % model.coord(j)[0],
'%.2f' % model.coord(j)[1],
'%.2f' % model.coord(j)[2],
'%d' % model.n_reflections(j)])
# Add the table
self.add_table(table)
# Add the profiles
for i in range(len(fitter)):
model = fitter[i]
for j in range(len(model)):
if model.valid(j):
array = Array()
array.name = 'profile.model.%d.%d' % (i, j)
array.title = 'Profile model (id: %d, profile: %d)' % (i, j)
array.data = model.data(j)
self.add_array(array)