def test_read_sparky(self):
"""The Sparky peak height loading test."""
# Load the original state.
self.interpreter.state.load(state='basic_heights_T2_ncyc1', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states', force=True)
# Create a new data pipe for the new data.
self.interpreter.pipe.create('new', 'relax_fit')
# Load the Lupin Ap4Aase sequence.
self.interpreter.sequence.read(file="Ap4Aase.seq", dir=status.install_path + sep+'test_suite'+sep+'shared_data', res_num_col=1, res_name_col=2)
# Name the spins so they can be matched to the assignments.
self.interpreter.spin.name(name='N')
# Read the peak heights.
self.interpreter.spectrum.read_intensities(file="T2_ncyc1_ave.list", dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting', spectrum_id='0.0176')
# Test the integrity of the data.
#################################
# Get the data pipes.
dp_new = pipes.get_pipe('new')
dp_rx = pipes.get_pipe('rx')
# Loop over the spins of the original data.
for mol_index, res_index, spin_index in spin_index_loop():
# Alias the spin containers.
new_spin = dp_new.mol[mol_index].res[res_index].spin[spin_index]
orig_spin = dp_rx.mol[mol_index].res[res_index].spin[spin_index]
# Check the sequence info.
self.assertEqual(dp_new.mol[mol_index].name, dp_rx.mol[mol_index].name)
self.assertEqual(dp_new.mol[mol_index].res[res_index].num, dp_rx.mol[mol_index].res[res_index].num)
self.assertEqual(dp_new.mol[mol_index].res[res_index].name, dp_rx.mol[mol_index].res[res_index].name)
self.assertEqual(new_spin.num, orig_spin.num)
self.assertEqual(new_spin.name, orig_spin.name)
# Skip deselected spins.
if not orig_spin.select:
continue
# Check intensities (if they exist).
if hasattr(orig_spin, 'peak_intensity'):
for id in dp_new.spectrum_ids:
self.assertEqual(orig_spin.peak_intensity[id], new_spin.peak_intensity[id])
def test_read_sparky(self):
"""The Sparky peak height loading test."""
# Load the original state.
self.interpreter.state.load(state='basic_heights_T2_ncyc1', dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'saved_states', force=True)
# Create a new data pipe for the new data.
self.interpreter.pipe.create('new', 'relax_fit')
# Load the Lupin Ap4Aase sequence.
self.interpreter.sequence.read(file="Ap4Aase.seq", dir=status.install_path + sep+'test_suite'+sep+'shared_data', res_num_col=1, res_name_col=2)
# Name the spins so they can be matched to the assignments.
self.interpreter.spin.name(name='N')
# Read the peak heights.
self.interpreter.spectrum.read_intensities(file="T2_ncyc1_ave.list", dir=status.install_path + sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting', spectrum_id='0.0176')
# Test the integrity of the data.
#################################
# Get the data pipes.
dp_new = pipes.get_pipe('new')
dp_rx = pipes.get_pipe('rx')
# Loop over the spins of the original data.
for mol_index, res_index, spin_index in spin_index_loop():
# Alias the spin containers.
new_spin = dp_new.mol[mol_index].res[res_index].spin[spin_index]
orig_spin = dp_rx.mol[mol_index].res[res_index].spin[spin_index]
# Check the sequence info.
self.assertEqual(dp_new.mol[mol_index].name, dp_rx.mol[mol_index].name)
self.assertEqual(dp_new.mol[mol_index].res[res_index].num, dp_rx.mol[mol_index].res[res_index].num)
self.assertEqual(dp_new.mol[mol_index].res[res_index].name, dp_rx.mol[mol_index].res[res_index].name)
self.assertEqual(new_spin.num, orig_spin.num)
self.assertEqual(new_spin.name, orig_spin.name)
# Skip deselected spins.
if not orig_spin.select:
continue
# Check intensities (if they exist).
if hasattr(orig_spin, 'peak_intensity'):
for id in dp_new.spectrum_ids:
self.assertEqual(orig_spin.peak_intensity[id], new_spin.peak_intensity[id])
def copy(pipe_from=None, pipe_to=None, ri_id=None):
"""Copy the relaxation data from one data pipe to another.
@keyword pipe_from: The data pipe to copy the relaxation data from. This defaults to the current data pipe.
@type pipe_from: str
@keyword pipe_to: The data pipe to copy the relaxation data to. This defaults to the current data pipe.
@type pipe_to: str
@param ri_id: The relaxation data ID string.
@type ri_id: str
"""
# Defaults.
if pipe_from == None and pipe_to == None:
raise RelaxError(
"The pipe_from and pipe_to arguments cannot both be set to None.")
elif pipe_from == None:
pipe_from = pipes.cdp_name()
elif pipe_to == None:
pipe_to = pipes.cdp_name()
# Test if the pipe_from and pipe_to data pipes exist.
check_pipe(pipe_from)
check_pipe(pipe_to)
# Get the data pipes.
dp_from = pipes.get_pipe(pipe_from)
dp_to = pipes.get_pipe(pipe_to)
# Test if pipe_from contains sequence data.
if not exists_mol_res_spin_data(pipe_from):
raise RelaxNoSequenceError
# Test if pipe_to contains sequence data.
if not exists_mol_res_spin_data(pipe_to):
raise RelaxNoSequenceError
# Test if relaxation data ID string exists for pipe_from.
if ri_id and (not hasattr(dp_from, 'ri_ids')
or ri_id not in dp_from.ri_ids):
raise RelaxNoRiError(ri_id)
# The IDs.
if ri_id == None:
ri_ids = dp_from.ri_ids
else:
ri_ids = [ri_id]
# Init target pipe global structures.
if not hasattr(dp_to, 'ri_ids'):
dp_to.ri_ids = []
if not hasattr(dp_to, 'ri_type'):
dp_to.ri_type = {}
# Loop over the Rx IDs.
for ri_id in ri_ids:
# Test if relaxation data ID string exists for pipe_to.
if ri_id in dp_to.ri_ids:
raise RelaxRiError(ri_id)
# Copy the global data.
dp_to.ri_ids.append(ri_id)
dp_to.ri_type[ri_id] = dp_from.ri_type[ri_id]
# Copy the frequency information.
copy_frequencies(pipe_from=pipe_from, pipe_to=pipe_to, id=ri_id)
# Spin loop.
for mol_index, res_index, spin_index in spin_index_loop():
# Alias the spin containers.
spin_from = dp_from.mol[mol_index].res[res_index].spin[spin_index]
spin_to = dp_to.mol[mol_index].res[res_index].spin[spin_index]
# No data or errors.
if not hasattr(spin_from, 'ri_data') and not hasattr(
spin_from, 'ri_data_err'):
continue
# Initialise the spin data if necessary.
if not hasattr(spin_to, 'ri_data'):
spin_to.ri_data = {}
if not hasattr(spin_to, 'ri_data_err'):
spin_to.ri_data_err = {}
# Copy the value and error from pipe_from.
spin_to.ri_data[ri_id] = spin_from.ri_data[ri_id]
spin_to.ri_data_err[ri_id] = spin_from.ri_data_err[ri_id]
def copy(pipe_from=None, pipe_to=None, ri_id=None):
"""Copy the relaxation data from one data pipe to another.
@keyword pipe_from: The data pipe to copy the relaxation data from. This defaults to the current data pipe.
@type pipe_from: str
@keyword pipe_to: The data pipe to copy the relaxation data to. This defaults to the current data pipe.
@type pipe_to: str
@param ri_id: The relaxation data ID string.
@type ri_id: str
"""
# Defaults.
if pipe_from == None and pipe_to == None:
raise RelaxError("The pipe_from and pipe_to arguments cannot both be set to None.")
elif pipe_from == None:
pipe_from = pipes.cdp_name()
elif pipe_to == None:
pipe_to = pipes.cdp_name()
# Test if the pipe_from and pipe_to data pipes exist.
pipes.test(pipe_from)
pipes.test(pipe_to)
# Get the data pipes.
dp_from = pipes.get_pipe(pipe_from)
dp_to = pipes.get_pipe(pipe_to)
# Test if pipe_from contains sequence data.
if not exists_mol_res_spin_data(pipe_from):
raise RelaxNoSequenceError
# Test if pipe_to contains sequence data.
if not exists_mol_res_spin_data(pipe_to):
raise RelaxNoSequenceError
# Test if relaxation data ID string exists for pipe_from.
if ri_id and (not hasattr(dp_from, 'ri_ids') or ri_id not in dp_from.ri_ids):
raise RelaxNoRiError(ri_id)
# The IDs.
if ri_id == None:
ri_ids = dp_from.ri_ids
else:
ri_ids = [ri_id]
# Init target pipe global structures.
if not hasattr(dp_to, 'ri_ids'):
dp_to.ri_ids = []
if not hasattr(dp_to, 'ri_type'):
dp_to.ri_type = {}
# Loop over the Rx IDs.
for ri_id in ri_ids:
# Test if relaxation data ID string exists for pipe_to.
if ri_id in dp_to.ri_ids:
raise RelaxRiError(ri_id)
# Copy the global data.
dp_to.ri_ids.append(ri_id)
dp_to.ri_type[ri_id] = dp_from.ri_type[ri_id]
# Copy the frequency information.
copy_frequencies(pipe_from=pipe_from, pipe_to=pipe_to, id=ri_id)
# Spin loop.
for mol_index, res_index, spin_index in spin_index_loop():
# Alias the spin containers.
spin_from = dp_from.mol[mol_index].res[res_index].spin[spin_index]
spin_to = dp_to.mol[mol_index].res[res_index].spin[spin_index]
# No data or errors.
if not hasattr(spin_from, 'ri_data') and not hasattr(spin_from, 'ri_data_err'):
continue
# Initialise the spin data if necessary.
if not hasattr(spin_to, 'ri_data'):
spin_to.ri_data = {}
if not hasattr(spin_to, 'ri_data_err'):
spin_to.ri_data_err = {}
# Copy the value and error from pipe_from.
spin_to.ri_data[ri_id] = spin_from.ri_data[ri_id]
spin_to.ri_data_err[ri_id] = spin_from.ri_data_err[ri_id]
def copy(pipe_from=None, pipe_to=None, align_id=None):
"""Copy the PCS data from one data pipe to another.
@keyword pipe_from: The data pipe to copy the PCS data from. This defaults to the current data pipe.
@type pipe_from: str
@keyword pipe_to: The data pipe to copy the PCS data to. This defaults to the current data pipe.
@type pipe_to: str
@param align_id: The alignment ID string.
@type align_id: str
"""
# Defaults.
if pipe_from == None and pipe_to == None:
raise RelaxError("The pipe_from and pipe_to arguments cannot both be set to None.")
elif pipe_from == None:
pipe_from = pipes.cdp_name()
elif pipe_to == None:
pipe_to = pipes.cdp_name()
# Check the pipe setup.
check_pipe_setup(pipe=pipe_from, pcs_id=align_id, sequence=True, pcs=True)
check_pipe_setup(pipe=pipe_to, sequence=True)
# Get the data pipes.
dp_from = pipes.get_pipe(pipe_from)
dp_to = pipes.get_pipe(pipe_to)
# The IDs.
if align_id == None:
align_ids = dp_from.align_ids
else:
align_ids = [align_id]
# Init target pipe global structures.
if not hasattr(dp_to, 'align_ids'):
dp_to.align_ids = []
if not hasattr(dp_to, 'pcs_ids'):
dp_to.pcs_ids = []
# Loop over the align IDs.
for align_id in align_ids:
# Copy the global data.
if align_id not in dp_to.align_ids and align_id not in dp_to.align_ids:
dp_to.align_ids.append(align_id)
if align_id in dp_from.pcs_ids and align_id not in dp_to.pcs_ids:
dp_to.pcs_ids.append(align_id)
# Spin loop.
for mol_index, res_index, spin_index in spin_index_loop():
# Alias the spin containers.
spin_from = dp_from.mol[mol_index].res[res_index].spin[spin_index]
spin_to = dp_to.mol[mol_index].res[res_index].spin[spin_index]
# No data or errors.
if (not hasattr(spin_from, 'pcs') or not align_id in spin_from.pcs) and (not hasattr(spin_from, 'pcs_err') or not align_id in spin_from.pcs_err):
continue
# Initialise the spin data if necessary.
if hasattr(spin_from, 'pcs') and not hasattr(spin_to, 'pcs'):
spin_to.pcs = {}
if hasattr(spin_from, 'pcs_err') and not hasattr(spin_to, 'pcs_err'):
spin_to.pcs_err = {}
# Copy the value and error from pipe_from.
if hasattr(spin_from, 'pcs'):
spin_to.pcs[align_id] = spin_from.pcs[align_id]
if hasattr(spin_from, 'pcs_err'):
spin_to.pcs_err[align_id] = spin_from.pcs_err[align_id]
