def display(sort=False, rev=False):
"""Print the details of all the data pipes."""
# Acquire the pipe lock, and make sure it is finally released.
status.pipe_lock.acquire(sys._getframe().f_code.co_name)
try:
# Loop over the data pipes.
pipe_names = []
for pipe_name_i in ds:
pipe_names.append(pipe_name_i)
if sort:
pipe_names = sort_filenames(filenames=pipe_names, rev=rev)
data = []
for pipe_name in pipe_names:
# The current data pipe.
current = ''
if pipe_name == cdp_name():
current = '*'
# Store the data for the print out.
data.append([
repr(pipe_name),
get_type(pipe_name),
repr(get_bundle(pipe_name)), current
])
# Release the lock.
finally:
status.pipe_lock.release(sys._getframe().f_code.co_name)
# Print out.
write_data(
out=sys.stdout,
headings=["Data pipe name", "Data pipe type", "Bundle", "Current"],
data=data)
# Return data
return data
def show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=None, path_to_command='showApod', outdir=None, force=False):
"""Searches 'dir' for files with extension 'file_ext'. Extract showApod 'Noise Std Dev' from showApod, and write to file with same filename and ending '.rmsd'.
@keyword file_ext: The extension for files which is NMRPipe fourier transformed file.
@type file_ext: str
@keyword dir: The directory where the files is located.
@type dir: str
@keyword path_to_command: If showApod not in PATH, then specify absolute path as: /path/to/showApod
@type path_to_command: str
@keyword outdir: The directory where to write the files. If 'None', then write in same directory.
@type outdir: str
@param force: Boolean argument which if True causes the file to be overwritten if it already exists.
@type force: bool
@return: Write the 'Noise Std Dev' from showApod to a file with same file filename, with ending '.rmsd'. This will be a list of file paths.
@rtype: list of str
"""
# First get correct dir, no matter if dir is specified with or without system folder separator.
dir_files = abspath(dir)
# Define glop pattern.
glob_pat = '*%s' % file_ext
# Get a list of files which math the file extension.
file_list = glob(dir_files + sep + glob_pat)
# Now sort into Alphanumeric order.
file_list_sorted = sort_filenames(filenames=file_list, rev=False)
# Loop over the files.
rmsd_files = []
for ft_file in file_list_sorted:
# Write rmsd to file, and get file path to file.
rmsd_file = show_apod_rmsd_to_file(file_name=ft_file, path_to_command=path_to_command, outdir=outdir, force=force)
# Collect file path.
rmsd_files.append(rmsd_file)
return rmsd_files
def show_apod_rmsd_dir_to_files(file_ext='.ft2', dir=None, path_to_command='showApod', outdir=None, force=False):
"""Searches 'dir' for files with extension 'file_ext'. Extract showApod 'Noise Std Dev' from showApod, and write to file with same filename and ending '.rmsd'.
@keyword file_ext: The extension for files which is NMRPipe fourier transformed file.
@type file_ext: str
@keyword dir: The directory where the files is located.
@type dir: str
@keyword path_to_command: If showApod not in PATH, then specify absolute path as: /path/to/showApod
@type path_to_command: str
@keyword outdir: The directory where to write the files. If 'None', then write in same directory.
@type outdir: str
@param force: Boolean argument which if True causes the file to be overwritten if it already exists.
@type force: bool
@return: Write the 'Noise Std Dev' from showApod to a file with same file filename, with ending '.rmsd'. This will be a list of file paths.
@rtype: list of str
"""
# First get correct dir, no matter if dir is specified with or without system folder separator.
dir_files = abspath(dir)
# Define glop pattern.
glob_pat = '*%s' % file_ext
# Get a list of files which math the file extension.
file_list = glob(dir_files + sep + glob_pat)
# Now sort into Alphanumeric order.
file_list_sorted = sort_filenames(filenames=file_list, rev=False)
# Loop over the files.
rmsd_files = []
for ft_file in file_list_sorted:
# Write rmsd to file, and get file path to file.
rmsd_file = show_apod_rmsd_to_file(file_name=ft_file, path_to_command=path_to_command, outdir=outdir, force=force)
# Collect file path.
rmsd_files.append(rmsd_file)
return rmsd_files
def signal_noise_ratio(verbose=True):
"""Calculate the signal to noise ratio per spin.
@keyword verbose: A flag which if True will print additional information out.
@type verbose: bool
"""
# Tests.
check_pipe()
check_mol_res_spin_data()
# Test if spectra have been loaded.
if not hasattr(cdp, 'spectrum_ids'):
raise RelaxError("No spectra have been loaded.")
# Possible print.
if verbose:
print("\nThe following signal to noise ratios has been calculated:\n")
# Set the spin specific signal to noise ratio.
for spin, spin_id in spin_loop(return_id=True):
# Skip deselected spins.
if not spin.select:
continue
# Skip spins missing intensity data.
if not hasattr(spin, 'peak_intensity'):
continue
# Test if error analysis has been performed.
if not hasattr(spin, 'peak_intensity_err'):
raise RelaxError(
"Intensity error analysis has not been performed. Please see spectrum.error_analysis()."
)
# If necessary, create the dictionary.
if not hasattr(spin, 'sn_ratio'):
spin.sn_ratio = {}
# Loop over the ID.
ids = []
for id in spin.peak_intensity:
# Append the ID to the list.
ids.append(id)
# Calculate the sn_ratio.
pint = float(spin.peak_intensity[id])
pint_err = float(spin.peak_intensity_err[id])
sn_ratio = pint / pint_err
# Assign the sn_ratio.
spin.sn_ratio[id] = sn_ratio
# Sort the ids alphanumeric.
ids = sort_filenames(filenames=ids, rev=False)
# Collect the data under sorted ids.
data_i = []
for id in ids:
# Get the values.
pint = spin.peak_intensity[id]
pint_err = spin.peak_intensity_err[id]
sn_ratio = spin.sn_ratio[id]
# Store the data.
data_i.append([id, repr(pint), repr(pint_err), repr(sn_ratio)])
if verbose:
section(file=sys.stdout,
text="Signal to noise ratio for spin ID '%s'" % spin_id,
prespace=1)
write_data(out=sys.stdout,
headings=["Spectrum ID", "Signal", "Noise", "S/N"],
data=data_i)
def sn_ratio_deselection(ratio=10.0,
operation='<',
all_sn=False,
select=False,
verbose=True):
"""Use user function deselect.spin on spins with signal to noise ratio higher or lower than ratio. The operation determines the selection operation.
@keyword ratio: The ratio to compare to.
@type ratio: float
@keyword operation: The comparison operation by which to select the spins. Of the operation(sn_ratio, ratio), where operation can either be: '<', '<=', '>', '>=', '==', '!='.
@type operation: str
@keyword all_sn: A flag specifying if all the signal to noise ratios per spin should match the comparison operator, of if just a single comparison match is enough.
@type all_sn: bool
@keyword select: A flag specifying if the user function select.spin should be used instead.
@type select: bool
@keyword verbose: A flag which if True will print additional information out.
@type verbose: bool
"""
# Tests.
check_pipe()
check_mol_res_spin_data()
# Test if spectra have been loaded.
if not hasattr(cdp, 'spectrum_ids'):
raise RelaxError("No spectra have been loaded.")
# Assign the comparison operator.
# "'<' : strictly less than"
if operation == '<':
op = operator.lt
# "'<=' : less than or equal"
elif operation == '<=':
op = operator.le
# "'>' : strictly greater than"
elif operation == '>':
op = operator.gt
# "'>=' : greater than or equal"
elif operation == '>=':
op = operator.ge
# "'==' : equal"
elif operation == '==':
op = operator.eq
# "'!=' : not equal",
elif operation == '!=':
op = operator.ne
# If not assigned, raise error.
else:
raise RelaxError(
"The compare operation does not belong to the allowed list of methods: ['<', '<=', '>', '>=', '==', '!=']"
)
# Assign text for print out.
if all_sn:
text_all_sn = "all"
else:
text_all_sn = "any"
if select:
text_sel = "selected"
sel_func = sel_spin
else:
text_sel = "deselected"
sel_func = desel_spin
# Print
section(file=sys.stdout,
text="Signal to noise ratio comparison selection",
prespace=1,
postspace=0)
print("For the comparion test: S/N %s %1.1f" % (operation, ratio))
# Loop over the spins.
spin_ids = []
for spin, spin_id in spin_loop(return_id=True):
# Skip spins missing sn_ratio.
if not hasattr(spin, 'sn_ratio'):
# Skip warning for deselected spins.
if spin.select:
warn(
RelaxWarning(
"Spin '%s' does not contain Signal to Noise calculations. Perform the user function 'spectrum.sn_ratio'. This spin is skipped."
% spin_id))
continue
# Loop over the ID, collect and sort.
ids = []
for id in spin.peak_intensity:
# Append the ID to the list.
ids.append(id)
# Sort the ids alphanumeric.
ids = sort_filenames(filenames=ids, rev=False)
# Loop over the sorted ids.
sn_val = []
for id in ids:
# Append the Signal to Noise in the list.
sn_val.append(spin.sn_ratio[id])
# Convert the list to array.
sn_val = asarray(sn_val)
# Make the comparison for the whole array.
test_arr = op(sn_val, ratio)
# Determine how the test should evaluate.
if all_sn:
test = test_arr.all()
else:
test = test_arr.any()
# Make an numpy array for the ids, an extract id which failed the test.
ids_arr = asarray(ids)
ids_test_arr = ids_arr[test_arr]
# Make inversion of bool
test_arr_inv = test_arr == False
ids_test_arr_inv = ids_arr[test_arr_inv]
# print
if verbose:
subsection(
file=sys.stdout,
text="Signal to noise ratio comparison for spin ID '%s'" %
spin_id,
prespace=1,
postspace=0)
print("Following spectra ID evaluated to True: %s" % ids_test_arr)
print("Following spectra ID evaluated to False: %s" %
ids_test_arr_inv)
print(
"'%s' comparisons have been used for evaluation, which evaluated to: %s"
% (text_all_sn, test))
if test:
print("The spin ID '%s' is %s" % (spin_id, text_sel))
else:
print("The spin ID '%s' is skipped" % spin_id)
# If the test evaluates to True, then do selection action.
if test:
# Select/Deselect the spin.
sel_func(spin_id=spin_id)
# Assign spin_id to list, for printing.
spin_ids.append(spin_id)
# Make summary
if verbose:
if len(spin_ids) > 0:
subsection(
file=sys.stdout,
text=
"For all of the S/N comparion test, the following spin ID's was %s"
% text_sel,
prespace=1,
postspace=0)
print(spin_ids)
def sn_ratio_deselection(ratio=10.0, operation='<', all_sn=False, select=False, verbose=True):
"""Use user function deselect.spin on spins with signal to noise ratio higher or lower than ratio. The operation determines the selection operation.
@keyword ratio: The ratio to compare to.
@type ratio: float
@keyword operation: The comparison operation by which to select the spins. Of the operation(sn_ratio, ratio), where operation can either be: '<', '<=', '>', '>=', '==', '!='.
@type operation: str
@keyword all_sn: A flag specifying if all the signal to noise ratios per spin should match the comparison operator, of if just a single comparison match is enough.
@type all_sn: bool
@keyword select: A flag specifying if the user function select.spin should be used instead.
@type select: bool
@keyword verbose: A flag which if True will print additional information out.
@type verbose: bool
"""
# Tests.
check_pipe()
check_mol_res_spin_data()
# Test if spectra have been loaded.
if not hasattr(cdp, 'spectrum_ids'):
raise RelaxError("No spectra have been loaded.")
# Assign the comparison operator.
# "'<' : strictly less than"
if operation == '<':
op = operator.lt
# "'<=' : less than or equal"
elif operation == '<=':
op = operator.le
# "'>' : strictly greater than"
elif operation == '>':
op = operator.gt
# "'>=' : greater than or equal"
elif operation == '>=':
op = operator.ge
# "'==' : equal"
elif operation == '==':
op = operator.eq
# "'!=' : not equal",
elif operation == '!=':
op = operator.ne
# If not assigned, raise error.
else:
raise RelaxError("The compare operation does not belong to the allowed list of methods: ['<', '<=', '>', '>=', '==', '!=']")
# Assign text for print out.
if all_sn:
text_all_sn = "all"
else:
text_all_sn = "any"
if select:
text_sel = "selected"
sel_func = sel_spin
else:
text_sel = "deselected"
sel_func = desel_spin
# Print
section(file=sys.stdout, text="Signal to noise ratio comparison selection", prespace=1, postspace=0)
print("For the comparion test: S/N %s %1.1f"%(operation, ratio))
# Loop over the spins.
spin_ids = []
for spin, spin_id in spin_loop(return_id=True):
# Skip spins missing sn_ratio.
if not hasattr(spin, 'sn_ratio'):
# Skip warning for deselected spins.
if spin.select:
warn(RelaxWarning("Spin '%s' does not contain Signal to Noise calculations. Perform the user function 'spectrum.sn_ratio'. This spin is skipped." % spin_id))
continue
# Loop over the ID, collect and sort.
ids = []
for id in spin.peak_intensity:
# Append the ID to the list.
ids.append(id)
# Sort the ids alphanumeric.
ids = sort_filenames(filenames=ids, rev=False)
# Loop over the sorted ids.
sn_val = []
for id in ids:
# Append the Signal to Noise in the list.
sn_val.append(spin.sn_ratio[id])
# Convert the list to array.
sn_val = asarray(sn_val)
# Make the comparison for the whole array.
test_arr = op(sn_val, ratio)
# Determine how the test should evaluate.
if all_sn:
test = test_arr.all()
else:
test = test_arr.any()
# Make an numpy array for the ids, an extract id which failed the test.
ids_arr = asarray(ids)
ids_test_arr = ids_arr[test_arr]
# Make inversion of bool
test_arr_inv = test_arr == False
ids_test_arr_inv = ids_arr[test_arr_inv]
# print
if verbose:
subsection(file=sys.stdout, text="Signal to noise ratio comparison for spin ID '%s'"%spin_id, prespace=1, postspace=0)
print("Following spectra ID evaluated to True: %s"%ids_test_arr)
print("Following spectra ID evaluated to False: %s"%ids_test_arr_inv)
print("'%s' comparisons have been used for evaluation, which evaluated to: %s"%(text_all_sn, test))
if test:
print("The spin ID '%s' is %s"%(spin_id, text_sel))
else:
print("The spin ID '%s' is skipped"%spin_id)
# If the test evaluates to True, then do selection action.
if test:
# Select/Deselect the spin.
sel_func(spin_id=spin_id)
# Assign spin_id to list, for printing.
spin_ids.append(spin_id)
# Make summary
if verbose:
if len(spin_ids) > 0:
subsection(file=sys.stdout, text="For all of the S/N comparion test, the following spin ID's was %s"%text_sel, prespace=1, postspace=0)
print(spin_ids)
def signal_noise_ratio(verbose=True):
"""Calculate the signal to noise ratio per spin.
@keyword verbose: A flag which if True will print additional information out.
@type verbose: bool
"""
# Tests.
check_pipe()
check_mol_res_spin_data()
# Test if spectra have been loaded.
if not hasattr(cdp, 'spectrum_ids'):
raise RelaxError("No spectra have been loaded.")
# Possible print.
if verbose:
print("\nThe following signal to noise ratios has been calculated:\n")
# Set the spin specific signal to noise ratio.
for spin, spin_id in spin_loop(return_id=True):
# Skip deselected spins.
if not spin.select:
continue
# Skip spins missing intensity data.
if not hasattr(spin, 'peak_intensity'):
continue
# Test if error analysis has been performed.
if not hasattr(spin, 'peak_intensity_err'):
raise RelaxError("Intensity error analysis has not been performed. Please see spectrum.error_analysis().")
# If necessary, create the dictionary.
if not hasattr(spin, 'sn_ratio'):
spin.sn_ratio = {}
# Loop over the ID.
ids = []
for id in spin.peak_intensity:
# Append the ID to the list.
ids.append(id)
# Calculate the sn_ratio.
pint = float(spin.peak_intensity[id])
pint_err = float(spin.peak_intensity_err[id])
sn_ratio = pint / pint_err
# Assign the sn_ratio.
spin.sn_ratio[id] = sn_ratio
# Sort the ids alphanumeric.
ids = sort_filenames(filenames=ids, rev=False)
# Collect the data under sorted ids.
data_i = []
for id in ids:
# Get the values.
pint = spin.peak_intensity[id]
pint_err = spin.peak_intensity_err[id]
sn_ratio = spin.sn_ratio[id]
# Store the data.
data_i.append([id, repr(pint), repr(pint_err), repr(sn_ratio)])
if verbose:
section(file=sys.stdout, text="Signal to noise ratio for spin ID '%s'"%spin_id, prespace=1)
write_data(out=sys.stdout, headings=["Spectrum ID", "Signal", "Noise", "S/N"], data=data_i)
