def test_loop_exp_frq_offset_point_time_cpmg_setup(self):
"""U{Bug #21665<https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate()."""
# Load the state.
statefile = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data
ncyc_1 = [20, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28]
sfrq_1 = 499.86214*1E6
time_T2_1 = 0.04
cpmg_1 = sorted([ncyc/time_T2_1 for ncyc in ncyc_1])
ncyc_2 = [28, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 24, 14, 22]
sfrq_2 = 599.8908587*1E6
time_T2_2 = 0.06
cpmg_2 = sorted([ncyc/time_T2_2 for ncyc in ncyc_2])
# Test the loop function.
# First initialize index for the two lists.
i = -1
j = -1
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(return_indices=True):
if frq == sfrq_1:
i += 1
self.assertEqual(time, time_T2_1)
self.assertAlmostEqual(point, cpmg_1[i], 3)
if frq == sfrq_2:
j += 1
self.assertEqual(time, time_T2_2)
self.assertAlmostEqual(point, cpmg_2[j], 3)
def test_loop_exp_frq_offset_point_time_cpmg_setup(self):
"""U{Bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21665>} catch, the failure due to a a CPMG analysis recorded at two fields at two delay times, using minimise.calculate()."""
# Load the state.
statefile = status.install_path + sep + 'test_suite' + sep + 'shared_data' + sep + 'dispersion' + sep + 'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data
ncyc_1 = [
20, 16, 10, 36, 2, 12, 4, 22, 18, 40, 14, 26, 8, 32, 24, 6, 28
]
sfrq_1 = 499.86214 * 1E6
time_T2_1 = 0.04
cpmg_1 = sorted([ncyc / time_T2_1 for ncyc in ncyc_1])
ncyc_2 = [
28, 4, 32, 60, 2, 10, 16, 8, 20, 52, 18, 40, 6, 12, 24, 14, 22
]
sfrq_2 = 599.8908587 * 1E6
time_T2_2 = 0.06
cpmg_2 = sorted([ncyc / time_T2_2 for ncyc in ncyc_2])
# Test the loop function.
# First initialize index for the two lists.
i = -1
j = -1
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(
return_indices=True):
if frq == sfrq_1:
i += 1
self.assertEqual(time, time_T2_1)
self.assertAlmostEqual(point, cpmg_1[i], 3)
if frq == sfrq_2:
j += 1
self.assertEqual(time, time_T2_2)
self.assertAlmostEqual(point, cpmg_2[j], 3)
def test_loop_exp_frq_offset_point_time_cpmg(self):
"""Unit test of the loop_exp_frq_offset_point_time() function.
This uses the data of the saved state attached to U{bug #21665<https://gna.org/bugs/?21665>}.
"""
# Load the state.
statefile = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data (exp_type, frq, offset, point).
data = [
['SQ CPMG', 499862140.0, 0, [50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0, 500.0, 550.0, 600.0, 650.0, 700.0, 800.0, 900.0, 1000.0], 0.04],
['SQ CPMG', 599890858.69999993, 0, [33.3333, 66.666, 100.0, 133.333, 166.666, 200.0, 233.333, 266.666, 300.0, 333.333, 366.666, 400.0, 466.666, 533.333, 666.666, 866.666, 1000.0], 0.06]
]
# Original indices (ei, mi, oi).
indices = [
[0, 0, 0, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], 0],
[0, 1, 0, [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], 0]
]
# Check the number of iterations.
print("Checking the number of iterations of the loop.")
count = 0
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(return_indices=True):
print(exp_type, frq, offset, point, time, ei, mi, oi, di, ti)
count += 1
self.assertEqual(count, 34)
# Check the values.
print("Checking the values returned by the loop.")
frq_index = 0
disp_index = 0
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(return_indices=True):
# Check the experiment info.
self.assertEqual(exp_type, data[frq_index][0])
self.assertEqual(ei, indices[frq_index][0])
# Check the frequency info.
self.assertEqual(frq, data[frq_index][1])
self.assertEqual(mi, indices[frq_index][1])
# Check the offset info.
self.assertEqual(offset, data[frq_index][2])
self.assertEqual(oi, indices[frq_index][2])
# Check the dispersion point info.
self.assertAlmostEqual(point, data[frq_index][3][disp_index], 2)
self.assertEqual(di, indices[frq_index][3][disp_index])
# Check the time point info.
self.assertEqual(time, data[frq_index][4])
self.assertEqual(ti, indices[frq_index][4])
# Increment the data index.
if disp_index == 16:
frq_index += 1
disp_index = 0
else:
disp_index += 1
def test_loop_exp_frq_offset_point_time_cpmg(self):
"""Unit test of the loop_exp_frq_offset_point_time() function.
This uses the data of the saved state attached to U{bug #21665<https://web.archive.org/web/https://gna.org/bugs/?21665>}.
"""
# Load the state.
statefile = status.install_path + sep + 'test_suite' + sep + 'shared_data' + sep + 'dispersion' + sep + 'bug_21665.bz2'
state.load_state(statefile, force=True)
# Original data (exp_type, frq, offset, point).
data = [[
'SQ CPMG', 499862140.0, 0,
[
50.0, 100.0, 150.0, 200.0, 250.0, 300.0, 350.0, 400.0, 450.0,
500.0, 550.0, 600.0, 650.0, 700.0, 800.0, 900.0, 1000.0
], 0.04
],
[
'SQ CPMG', 599890858.69999993, 0,
[
33.3333, 66.666, 100.0, 133.333, 166.666, 200.0,
233.333, 266.666, 300.0, 333.333, 366.666, 400.0,
466.666, 533.333, 666.666, 866.666, 1000.0
], 0.06
]]
# Original indices (ei, mi, oi).
indices = [
[
0, 0, 0,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], 0
],
[
0, 1, 0,
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16], 0
]
]
# Check the number of iterations.
print("Checking the number of iterations of the loop.")
count = 0
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(
return_indices=True):
print(exp_type, frq, offset, point, time, ei, mi, oi, di, ti)
count += 1
self.assertEqual(count, 34)
# Check the values.
print("Checking the values returned by the loop.")
frq_index = 0
disp_index = 0
for exp_type, frq, offset, point, time, ei, mi, oi, di, ti in loop_exp_frq_offset_point_time(
return_indices=True):
# Check the experiment info.
self.assertEqual(exp_type, data[frq_index][0])
self.assertEqual(ei, indices[frq_index][0])
# Check the frequency info.
self.assertEqual(frq, data[frq_index][1])
self.assertEqual(mi, indices[frq_index][1])
# Check the offset info.
self.assertEqual(offset, data[frq_index][2])
self.assertEqual(oi, indices[frq_index][2])
# Check the dispersion point info.
self.assertAlmostEqual(point, data[frq_index][3][disp_index], 2)
self.assertEqual(di, indices[frq_index][3][disp_index])
# Check the time point info.
self.assertEqual(time, data[frq_index][4])
self.assertEqual(ti, indices[frq_index][4])
# Increment the data index.
if disp_index == 16:
frq_index += 1
disp_index = 0
else:
disp_index += 1
def calculate_r2eff():
"""Calculate the R2eff values for fixed relaxation time period data."""
# Data checks.
check_exp_type()
check_disp_points()
check_exp_type_fixed_time()
# Printouts.
print("Calculating the R2eff/R1rho values for fixed relaxation time period data.")
# Loop over the spins.
for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True):
# Spin ID printout.
print("Spin '%s'." % spin_id)
# Skip spins which have no data.
if not hasattr(spin, 'peak_intensity'):
continue
# Initialise the data structures.
if not hasattr(spin, 'r2eff'):
spin.r2eff = {}
if not hasattr(spin, 'r2eff_err'):
spin.r2eff_err = {}
# Loop over all the data.
for exp_type, frq, offset, point, time in loop_exp_frq_offset_point_time():
# The three keys.
ref_keys = find_intensity_keys(exp_type=exp_type, frq=frq, offset=offset, point=None, time=time)
int_keys = find_intensity_keys(exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)
param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)
# Check for missing data.
missing = False
for i in range(len(ref_keys)):
if ref_keys[i] not in spin.peak_intensity:
missing = True
for i in range(len(int_keys)):
if int_keys[i] not in spin.peak_intensity:
missing = True
if missing:
continue
# Average the reference intensity data and errors.
ref_intensity = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=None, time=time)
ref_intensity_err = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=None, time=time, error=True)
# Average the intensity data and errors.
intensity = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)
intensity_err = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)
# Check for math domain errors or log for values less than 0.0.
if ref_intensity == 0.0:
skip_data = True
elif float(intensity) / ref_intensity <= 0.0:
skip_data = True
else:
skip_data = False
if skip_data:
spin_string = generate_spin_string(spin=spin, mol_name=mol_name, res_num=resi, res_name=resn)
msg = "Math log(I / I_ref) domain error for spin '%s' in R2eff value calculation for fixed relaxation time period data. I=%3.3f, I_ref=%3.3f. The point is skipped." % (spin_string, intensity, ref_intensity)
warn(RelaxWarning("%s" % msg))
point_info = "This happened for '%s' at %3.1f MHz, for offset=%3.1f ppm and dispersion point %3.1f Hz and time %1.2f s.\n" % (exp_type, frq/1E6, offset, point, time)
print(point_info)
else:
# Calculate the R2eff value.
spin.r2eff[param_key] = calc_two_point_r2eff(relax_time=time, I_ref=ref_intensity, I=intensity)
# Calculate the R2eff error.
spin.r2eff_err[param_key] = calc_two_point_r2eff_err(relax_time=time, I_ref=ref_intensity, I=intensity, I_ref_err=ref_intensity_err, I_err=intensity_err)
def calculate_r2eff():
"""Calculate the R2eff values for fixed relaxation time period data."""
# Data checks.
check_exp_type()
check_disp_points()
check_exp_type_fixed_time()
# Printouts.
print("Calculating the R2eff/R1rho values for fixed relaxation time period data.")
# Loop over the spins.
for spin, mol_name, resi, resn, spin_id in spin_loop(full_info=True, return_id=True, skip_desel=True):
# Spin ID printout.
print("Spin '%s'." % spin_id)
# Skip spins which have no data.
if not hasattr(spin, 'peak_intensity'):
continue
# Initialise the data structures.
if not hasattr(spin, 'r2eff'):
spin.r2eff = {}
if not hasattr(spin, 'r2eff_err'):
spin.r2eff_err = {}
# Loop over all the data.
for exp_type, frq, offset, point, time in loop_exp_frq_offset_point_time():
# The three keys.
ref_keys = find_intensity_keys(exp_type=exp_type, frq=frq, offset=offset, point=None, time=time)
int_keys = find_intensity_keys(exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)
param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)
# Check for missing data.
missing = False
for i in range(len(ref_keys)):
if ref_keys[i] not in spin.peak_intensity:
missing = True
for i in range(len(int_keys)):
if int_keys[i] not in spin.peak_intensity:
missing = True
if missing:
continue
# Average the reference intensity data and errors.
ref_intensity = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=None, time=time)
ref_intensity_err = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=None, time=time, error=True)
# Average the intensity data and errors.
intensity = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time)
intensity_err = average_intensity(spin=spin, exp_type=exp_type, frq=frq, offset=offset, point=point, time=time, error=True)
# Check for math domain errors or log for values less than 0.0.
if ref_intensity == 0.0:
skip_data = True
elif float(intensity) / ref_intensity <= 0.0:
skip_data = True
else:
skip_data = False
if skip_data:
spin_string = generate_spin_string(spin=spin, mol_name=mol_name, res_num=resi, res_name=resn)
msg = "Math log(I / I_ref) domain error for spin '%s' in R2eff value calculation for fixed relaxation time period data. I=%3.3f, I_ref=%3.3f. The point is skipped." % (spin_string, intensity, ref_intensity)
warn(RelaxWarning("%s" % msg))
point_info = "This happened for '%s' at %3.1f MHz, for offset=%3.1f ppm and dispersion point %3.1f Hz and time %1.2f s.\n" % (exp_type, frq/1E6, offset, point, time)
print(point_info)
else:
# Calculate the R2eff value.
spin.r2eff[param_key] = calc_two_point_r2eff(relax_time=time, I_ref=ref_intensity, I=intensity)
# Calculate the R2eff error.
spin.r2eff_err[param_key] = calc_two_point_r2eff_err(relax_time=time, I_ref=ref_intensity, I=intensity, I_ref_err=ref_intensity_err, I_err=intensity_err)
