def test_count_relax_times_cpmg(self):
"""Unit test of the count_relax_times() 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).
data = [
['SQ CPMG', 499862140.0],
['SQ CPMG', 599890858.69999993]
]
# Original indices (ei, mi).
indices = [
[0, 0],
[0, 1]
]
# Check the number of time counts.
print("Checking the number of time counts.")
for id in cdp.exp_type:
exp_type = cdp.exp_type[id]
frq = cdp.spectrometer_frq[id]
point = cdp.cpmg_frqs[id]
count = count_relax_times(exp_type = exp_type, frq = frq, point = point, ei = cdp.exp_type_list.index(cdp.exp_type[id]))
print(id, exp_type, frq, point, count)
# Test the data
if id.split('A')[0] == 'Z_':
self.assertEqual(exp_type, data[0][0])
self.assertEqual(frq, data[0][1])
elif id.split('B')[0] == 'Z_':
self.assertEqual(exp_type, data[1][0])
self.assertEqual(frq, data[1][1])
# Test the time count
self.assertEqual(count, 1)
def test_count_relax_times_cpmg(self):
"""Unit test of the count_relax_times() 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).
data = [['SQ CPMG', 499862140.0], ['SQ CPMG', 599890858.69999993]]
# Original indices (ei, mi).
indices = [[0, 0], [0, 1]]
# Check the number of time counts.
print("Checking the number of time counts.")
for id in cdp.exp_type:
exp_type = cdp.exp_type[id]
frq = cdp.spectrometer_frq[id]
point = cdp.cpmg_frqs[id]
count = count_relax_times(exp_type=exp_type,
frq=frq,
point=point,
ei=cdp.exp_type_list.index(
cdp.exp_type[id]))
print(id, exp_type, frq, point, count)
# Test the data
if id.split('A')[0] == 'Z_':
self.assertEqual(exp_type, data[0][0])
self.assertEqual(frq, data[0][1])
elif id.split('B')[0] == 'Z_':
self.assertEqual(exp_type, data[1][0])
self.assertEqual(frq, data[1][1])
# Test the time count
self.assertEqual(count, 1)
def test_count_relax_times_r1rho(self):
"""Unit test of the count_relax_times() function.
This uses the data of the saved state attached to U{bug #21344<https://gna.org/bugs/?21344>}.
"""
# Load the state.
statefile = status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'dispersion'+sep+'bug_21344_trunc.bz2'
state.load_state(statefile, force=True)
# Original data (spectrum id: exp_type, frq, omega_rf_ppm, spin_lock_field_strength, time_spin_lock).
data = dict()
data['46_0_35_0'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.0]
data['48_0_35_4'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.04]
data['47_0_35_10'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.1]
data['49_0_35_20'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.2]
data['36_0_39_0'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.0]
data['39_0_39_4'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.04]
data['37_0_39_10'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.1]
data['40_0_39_20'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.2]
data['38_0_39_40'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.4]
data['41_0_41_0'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.0]
data['44_0_41_4'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.04]
data['42_0_41_10'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.1]
data['45_0_41_20'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.2]
data['43_0_41_40'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.4]
data['31_0_43_0'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.0]
data['34_0_43_4'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.04]
data['32_0_43_10'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.1]
data['35_0_43_20'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.2]
data['33_0_43_40'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.4]
data['1_0_46_0'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.0]
data['4_0_46_4'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.04]
data['2_0_46_10'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.1]
data['5_0_46_20'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.2]
data['3_0_46_40'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.4]
data['60_0_48_0'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.0]
data['63_0_48_4'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.04]
data['61_0_48_10'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.1]
data['62_0_48_14'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.14]
data['64_0_48_20'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.2]
data['11_500_46_0'] = ['R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.0]
data['14_500_46_4'] = ['R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.04]
data['12_500_46_10'] = ['R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.1]
data['15_500_46_20'] = ['R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.2]
data['13_500_46_40'] = ['R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.4]
data['50_1000_41_0'] = ['R1rho', 799777399.1, 130.41606292412092, 800.5, 0.0]
data['53_1000_41_4'] = ['R1rho', 799777399.1, 130.41606292412092, 800.5, 0.04]
data['51_1000_41_10'] = ['R1rho', 799777399.1, 130.41606292412092, 800.5, 0.1]
data['54_1000_41_20'] = ['R1rho', 799777399.1, 130.41606292412092, 800.5, 0.2]
data['52_1000_41_40'] = ['R1rho', 799777399.1, 130.41606292412092, 800.5, 0.4]
data['21_1000_46_0'] = ['R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.0]
data['24_1000_46_4'] = ['R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.04]
data['22_1000_46_10'] = ['R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.1]
data['25_1000_46_20'] = ['R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.2]
data['23_1000_46_40'] = ['R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.4]
data['65_1000_48_0'] = ['R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.0]
data['68_1000_48_4'] = ['R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.04]
data['66_1000_48_10'] = ['R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.1]
data['67_1000_48_14'] = ['R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.14]
data['69_1000_48_20'] = ['R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.2]
data['55_2000_41_0'] = ['R1rho', 799777399.1, 142.75412584824184, 800.5, 0.0]
data['58_2000_41_4'] = ['R1rho', 799777399.1, 142.75412584824184, 800.5, 0.04]
data['56_2000_41_10'] = ['R1rho', 799777399.1, 142.75412584824184, 800.5, 0.1]
data['59_2000_41_20'] = ['R1rho', 799777399.1, 142.75412584824184, 800.5, 0.2]
data['57_2000_41_40'] = ['R1rho', 799777399.1, 142.75412584824184, 800.5, 0.4]
data['6_2000_46_0'] = ['R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.0]
data['9_2000_46_4'] = ['R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.04]
data['7_2000_46_10'] = ['R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.1]
data['10_2000_46_20'] = ['R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.2]
data['8_2000_46_40'] = ['R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.4]
data['16_5000_46_0'] = ['R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.0]
data['19_5000_46_4'] = ['R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.04]
data['17_5000_46_10'] = ['R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.1]
data['20_5000_46_20'] = ['R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.2]
data['18_5000_46_40'] = ['R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.4]
data['26_10000_46_0'] = ['R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.0]
data['29_10000_46_4'] = ['R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.04]
data['27_10000_46_10'] = ['R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.1]
data['30_10000_46_20'] = ['R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.2]
data['28_10000_46_40'] = ['R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.4]
time_comp = {
'118.078_431.00':4,
'118.078_651.20':5,
'118.078_800.50':5,
'118.078_984.00':5,
'118.078_1341.11':5,
'118.078_1648.50':5,
'124.247_1341.11':5,
'130.416_800.50':5,
'130.416_1341.11':5,
'130.416_1648.50':5,
'142.754_800.50':5,
'142.754_1341.11':5,
'179.768_1341.11':5,
'241.459_1341.11':5}
# Check the number of time counts.
print("Checking the number of time counts.")
for id in cdp.exp_type:
exp_type = cdp.exp_type[id]
frq = cdp.spectrometer_frq[id]
offset = cdp.spin_lock_offset[id]
point = cdp.spin_lock_nu1[id]
count = count_relax_times(exp_type = exp_type, frq = frq, offset=offset, point = point, ei = cdp.exp_type_list.index(cdp.exp_type[id]))
print(id, exp_type, frq, offset, point, count)
# Test the time count
print(time_comp)
self.assertEqual(count, time_comp['%.3f_%.2f'%(offset, point)])
def test_count_relax_times_r1rho(self):
"""Unit test of the count_relax_times() function.
This uses the data of the saved state attached to U{bug #21344<https://web.archive.org/web/https://gna.org/bugs/?21344>}.
"""
# Load the state.
statefile = status.install_path + sep + 'test_suite' + sep + 'shared_data' + sep + 'dispersion' + sep + 'bug_21344_trunc.bz2'
state.load_state(statefile, force=True)
# Original data (spectrum id: exp_type, frq, omega_rf_ppm, spin_lock_field_strength, time_spin_lock).
data = dict()
data['46_0_35_0'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.0]
data['48_0_35_4'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.04]
data['47_0_35_10'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.1]
data['49_0_35_20'] = ['R1rho', 799777399.1, 118.078, 431.0, 0.2]
data['36_0_39_0'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.0]
data['39_0_39_4'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.04]
data['37_0_39_10'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.1]
data['40_0_39_20'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.2]
data['38_0_39_40'] = ['R1rho', 799777399.1, 118.078, 651.2, 0.4]
data['41_0_41_0'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.0]
data['44_0_41_4'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.04]
data['42_0_41_10'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.1]
data['45_0_41_20'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.2]
data['43_0_41_40'] = ['R1rho', 799777399.1, 118.078, 800.5, 0.4]
data['31_0_43_0'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.0]
data['34_0_43_4'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.04]
data['32_0_43_10'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.1]
data['35_0_43_20'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.2]
data['33_0_43_40'] = ['R1rho', 799777399.1, 118.078, 984.0, 0.4]
data['1_0_46_0'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.0]
data['4_0_46_4'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.04]
data['2_0_46_10'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.1]
data['5_0_46_20'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.2]
data['3_0_46_40'] = ['R1rho', 799777399.1, 118.078, 1341.11, 0.4]
data['60_0_48_0'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.0]
data['63_0_48_4'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.04]
data['61_0_48_10'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.1]
data['62_0_48_14'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.14]
data['64_0_48_20'] = ['R1rho', 799777399.1, 118.078, 1648.5, 0.2]
data['11_500_46_0'] = [
'R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.0
]
data['14_500_46_4'] = [
'R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.04
]
data['12_500_46_10'] = [
'R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.1
]
data['15_500_46_20'] = [
'R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.2
]
data['13_500_46_40'] = [
'R1rho', 799777399.1, 124.24703146206046, 1341.11, 0.4
]
data['50_1000_41_0'] = [
'R1rho', 799777399.1, 130.41606292412092, 800.5, 0.0
]
data['53_1000_41_4'] = [
'R1rho', 799777399.1, 130.41606292412092, 800.5, 0.04
]
data['51_1000_41_10'] = [
'R1rho', 799777399.1, 130.41606292412092, 800.5, 0.1
]
data['54_1000_41_20'] = [
'R1rho', 799777399.1, 130.41606292412092, 800.5, 0.2
]
data['52_1000_41_40'] = [
'R1rho', 799777399.1, 130.41606292412092, 800.5, 0.4
]
data['21_1000_46_0'] = [
'R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.0
]
data['24_1000_46_4'] = [
'R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.04
]
data['22_1000_46_10'] = [
'R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.1
]
data['25_1000_46_20'] = [
'R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.2
]
data['23_1000_46_40'] = [
'R1rho', 799777399.1, 130.41606292412092, 1341.11, 0.4
]
data['65_1000_48_0'] = [
'R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.0
]
data['68_1000_48_4'] = [
'R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.04
]
data['66_1000_48_10'] = [
'R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.1
]
data['67_1000_48_14'] = [
'R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.14
]
data['69_1000_48_20'] = [
'R1rho', 799777399.1, 130.41606292412092, 1648.5, 0.2
]
data['55_2000_41_0'] = [
'R1rho', 799777399.1, 142.75412584824184, 800.5, 0.0
]
data['58_2000_41_4'] = [
'R1rho', 799777399.1, 142.75412584824184, 800.5, 0.04
]
data['56_2000_41_10'] = [
'R1rho', 799777399.1, 142.75412584824184, 800.5, 0.1
]
data['59_2000_41_20'] = [
'R1rho', 799777399.1, 142.75412584824184, 800.5, 0.2
]
data['57_2000_41_40'] = [
'R1rho', 799777399.1, 142.75412584824184, 800.5, 0.4
]
data['6_2000_46_0'] = [
'R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.0
]
data['9_2000_46_4'] = [
'R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.04
]
data['7_2000_46_10'] = [
'R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.1
]
data['10_2000_46_20'] = [
'R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.2
]
data['8_2000_46_40'] = [
'R1rho', 799777399.1, 142.75412584824184, 1341.11, 0.4
]
data['16_5000_46_0'] = [
'R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.0
]
data['19_5000_46_4'] = [
'R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.04
]
data['17_5000_46_10'] = [
'R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.1
]
data['20_5000_46_20'] = [
'R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.2
]
data['18_5000_46_40'] = [
'R1rho', 799777399.1, 179.76831462060457, 1341.11, 0.4
]
data['26_10000_46_0'] = [
'R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.0
]
data['29_10000_46_4'] = [
'R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.04
]
data['27_10000_46_10'] = [
'R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.1
]
data['30_10000_46_20'] = [
'R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.2
]
data['28_10000_46_40'] = [
'R1rho', 799777399.1, 241.45862924120914, 1341.11, 0.4
]
time_comp = {
'118.078_431.00': 4,
'118.078_651.20': 5,
'118.078_800.50': 5,
'118.078_984.00': 5,
'118.078_1341.11': 5,
'118.078_1648.50': 5,
'124.247_1341.11': 5,
'130.416_800.50': 5,
'130.416_1341.11': 5,
'130.416_1648.50': 5,
'142.754_800.50': 5,
'142.754_1341.11': 5,
'179.768_1341.11': 5,
'241.459_1341.11': 5
}
# Check the number of time counts.
print("Checking the number of time counts.")
for id in cdp.exp_type:
exp_type = cdp.exp_type[id]
frq = cdp.spectrometer_frq[id]
offset = cdp.spin_lock_offset[id]
point = cdp.spin_lock_nu1[id]
count = count_relax_times(exp_type=exp_type,
frq=frq,
offset=offset,
point=point,
ei=cdp.exp_type_list.index(
cdp.exp_type[id]))
print(id, exp_type, frq, offset, point, count)
# Test the time count
print(time_comp)
self.assertEqual(count, time_comp['%.3f_%.2f' % (offset, point)])
