Esempio n. 1
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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
Esempio n. 2
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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
Esempio n. 3
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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
Esempio n. 4
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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)
Esempio n. 5
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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)
Esempio n. 6
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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)
Esempio n. 7
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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)