Exemplo n.º 1
0
def sherekhan_input(spin_id=None, force=False, dir='ShereKhan'):
    """Create the ShereKhan input files.

    @keyword spin_id:           The spin ID string to restrict the file creation to.
    @type spin_id:              str
    @keyword force:             A flag which if True will cause all pre-existing files to be overwritten.
    @type force:                bool
    @keyword dir:               The optional directory to place the files into.  If None, then the files will be placed into the current directory.
    @type dir:                  str or None
    """

    # Test if the current pipe exists.
    check_pipe()

    # Test if sequence data is loaded.
    if not exists_mol_res_spin_data():
        raise RelaxNoSequenceError

    # Test if the experiment type has been set.
    if not hasattr(cdp, 'exp_type'):
        raise RelaxError("The relaxation dispersion experiment type has not been specified.")

    # Test if the model has been set.
    if not hasattr(cdp, 'model_type'):
        raise RelaxError("The relaxation dispersion model has not been specified.")

    # Directory creation.
    if dir != None:
        mkdir_nofail(dir, verbosity=0)

    # Loop over the spin blocks.
    cluster_index = 0
    for spin_ids in loop_cluster():
        # The spin containers.
        spins = spin_ids_to_containers(spin_ids)

        # Loop over the magnetic fields.
        for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
            # Loop over the time, and count it.
            time_i = 0
            for time, ti in loop_time(exp_type=exp_type, frq=frq, return_indices=True):
                time_i += 1

            # Check that not more than one time point is returned.
            if time_i > 1:
                raise RelaxError("Number of returned time poins is %i. Only 1 time point is expected."%time_i)

            # The ShereKhan input file for the spin cluster.
            file_name = 'sherekhan_frq%s.in' % (mi+1)
            if dir != None:
                dir_name = dir + sep + 'cluster%s' % (cluster_index+1)
            else:
                dir_name = 'cluster%s' % (cluster_index+1)
            file = open_write_file(file_name=file_name, dir=dir_name, force=force)

            # The B0 field for the nuclei of interest in MHz (must be positive to be accepted by the server).
            file.write("%.10f\n" % abs(frq / periodic_table.gyromagnetic_ratio('1H') * periodic_table.gyromagnetic_ratio('15N') / 1e6))

            # The constant relaxation time for the CPMG experiment in seconds.
            file.write("%s\n" % (time))

            # The comment line.
            file.write("# %-18s %-20s %-20s\n" % ("nu_cpmg (Hz)", "R2eff (rad/s)", "Error"))

            # Loop over the spins of the cluster.
            for i in range(len(spins)):
                # Get the residue container.
                res = return_residue(spin_ids[i])

                # Name the residue if needed.
                res_name = res.name
                if res_name == None:
                    res_name = 'X'

                # Initialise the lines to output (to be able to catch missing data).
                lines = []

                # The residue ID line.
                lines.append("# %s%s\n" % (res_name, res.num))

                # Loop over the dispersion points.
                for offset, point in loop_offset_point(exp_type=exp_type, frq=frq, skip_ref=True):
                    # The parameter key.
                    param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)

                    # No data.
                    if param_key not in spins[i].r2eff:
                        continue

                    # Store the data.
                    lines.append("%20.15g %20.13g %20.13g\n" % (point, spins[i].r2eff[param_key], spins[i].r2eff_err[param_key]))

                # No data.
                if len(lines) == 1:
                    continue

                # Write out the data.
                for line in lines:
                    file.write(line)

            # Close the file.
            file.close()

        # Increment the cluster index.
        cluster_index += 1
Exemplo n.º 2
0
def sherekhan_input(spin_id=None, force=False, dir='ShereKhan'):
    """Create the ShereKhan input files.

    @keyword spin_id:           The spin ID string to restrict the file creation to.
    @type spin_id:              str
    @keyword force:             A flag which if True will cause all pre-existing files to be overwritten.
    @type force:                bool
    @keyword dir:               The optional directory to place the files into.  If None, then the files will be placed into the current directory.
    @type dir:                  str or None
    """

    # Test if the current pipe exists.
    check_pipe()

    # Test if sequence data is loaded.
    if not exists_mol_res_spin_data():
        raise RelaxNoSequenceError

    # Test if the experiment type has been set.
    if not hasattr(cdp, 'exp_type'):
        raise RelaxError("The relaxation dispersion experiment type has not been specified.")

    # Test if the model has been set.
    if not hasattr(cdp, 'model_type'):
        raise RelaxError("The relaxation dispersion model has not been specified.")

    # Directory creation.
    if dir != None:
        mkdir_nofail(dir, verbosity=0)

    # Loop over the spin blocks.
    cluster_index = 0
    for spin_ids in loop_cluster():
        # The spin containers.
        spins = spin_ids_to_containers(spin_ids)

        # Loop over the magnetic fields.
        for exp_type, frq, ei, mi in loop_exp_frq(return_indices=True):
            # Loop over the time, and count it.
            time_i = 0
            for time, ti in loop_time(exp_type=exp_type, frq=frq, return_indices=True):
                time_i += 1

            # Check that not more than one time point is returned.
            if time_i > 1:
                raise RelaxError("Number of returned time poins is %i. Only 1 time point is expected."%time_i)

            # The ShereKhan input file for the spin cluster.
            file_name = 'sherekhan_frq%s.in' % (mi+1)
            if dir != None:
                dir_name = dir + sep + 'cluster%s' % (cluster_index+1)
            else:
                dir_name = 'cluster%s' % (cluster_index+1)
            file = open_write_file(file_name=file_name, dir=dir_name, force=force)

            # The B0 field for the nuclei of interest in MHz (must be positive to be accepted by the server).
            file.write("%.10f\n" % abs(frq / periodic_table.gyromagnetic_ratio('1H') * periodic_table.gyromagnetic_ratio('15N') / 1e6))

            # The constant relaxation time for the CPMG experiment in seconds.
            file.write("%s\n" % (time))

            # The comment line.
            file.write("# %-18s %-20s %-20s\n" % ("nu_cpmg (Hz)", "R2eff (rad/s)", "Error"))

            # Loop over the spins of the cluster.
            for i in range(len(spins)):
                # Get the residue container.
                res = return_residue(spin_ids[i])

                # Name the residue if needed.
                res_name = res.name
                if res_name == None:
                    res_name = 'X'

                # Initialise the lines to output (to be able to catch missing data).
                lines = []

                # The residue ID line.
                lines.append("# %s%s\n" % (res_name, res.num))

                # Loop over the dispersion points.
                for offset, point in loop_offset_point(exp_type=exp_type, frq=frq, skip_ref=True):
                    # The parameter key.
                    param_key = return_param_key_from_data(exp_type=exp_type, frq=frq, offset=offset, point=point)

                    # No data.
                    if param_key not in spins[i].r2eff:
                        continue

                    # Store the data.
                    lines.append("%20.15g %20.13g %20.13g\n" % (point, spins[i].r2eff[param_key], spins[i].r2eff_err[param_key]))

                # No data.
                if len(lines) == 1:
                    continue

                # Write out the data.
                for line in lines:
                    file.write(line)

            # Close the file.
            file.close()

        # Increment the cluster index.
        cluster_index += 1
Exemplo n.º 3
0
def copy(pipe_from=None, pipe_to=None):
    """Copy dispersion parameters from one data pipe to another, taking the median of previous values to a start value for clusters.
    Taking the median prevent averaging extreme outliers.

    @param pipe_from:   The data pipe to copy the value from.  This defaults to the current data pipe.
    @type pipe_from:    str
    @param pipe_to:     The data pipe to copy the value to.  This defaults to the current data pipe.
    @type pipe_to:      str
    """

    # The current data pipe.
    pipe_orig = pipes.cdp_name()
    if pipe_from == None:
        pipe_from = pipe_orig
    if pipe_to == None:
        pipe_to = pipe_orig

    # Test that the pipes exist.
    check_pipe(pipe_from)
    check_pipe(pipe_to)

    # Test that the pipes are not the same.
    if pipe_from == pipe_to:
        raise RelaxError("The source and destination pipes cannot be the same.")

    # Test if the sequence data for pipe_from is loaded.
    if not exists_mol_res_spin_data(pipe_from):
        raise RelaxNoSequenceError(pipe_from)

    # Test if the sequence data for pipe_to is loaded.
    if not exists_mol_res_spin_data(pipe_to):
        raise RelaxNoSequenceError(pipe_to)

    # Switch to the destination data pipe.
    pipes.switch(pipe_to)

    # Loop over the clusters.
    for spin_ids in loop_cluster():
        # Initialise some variables.
        model = None
        pA = []
        pB = []
        pC = []
        kex = []
        kex_AB = []
        kex_AC = []
        kex_BC = []
        k_AB = []
        kB = []
        kC = []
        tex = []
        count = 0
        spins_from = []
        spins_to = []
        selected_cluster = False

        # Loop over the spins, adding parameters to a list, which in the end will be used to find the median.
        for id in spin_ids:
            # Get the spins, then store them.
            spin_from = return_spin(spin_id=id, pipe=pipe_from)
            spin_to = return_spin(spin_id=id, pipe=pipe_to)
            spins_from.append(spin_from)
            spins_to.append(spin_to)

            # Skip deselected spins.
            if not spin_from.select or not spin_to.select:
                continue

            # The first printout.
            if not selected_cluster:
                subsection(file=sys.stdout, text="Copying parameters for the spin block %s"%spin_ids, prespace=2)

            # Change the cluster selection flag.
            selected_cluster = True

            # The model.
            if not model:
                model = spin_from.model

            # Check that the models match for all spins of the cluster.
            if spin_from.model != model:
                raise RelaxError("The model '%s' of spin '%s' from the source data pipe does not match the '%s' model of previous spins of the cluster." % (spin_from.model, id, model))
            if spin_to.model != model:
                raise RelaxError("The model '%s' of spin '%s' from the destination data pipe does not match the '%s' model of previous spins of the cluster." % (spin_from.model, id, model))

            # Sum the source parameters.
            if 'pA' in spin_from.params:
                pA.append(spin_from.pA)
            if 'pB' in spin_from.params:
                pB.append(spin_from.pB)
            if 'pC' in spin_from.params:
                pC.append(spin_from.pC)
            if 'kex' in spin_from.params:
                kex.append(spin_from.kex)
            if 'kex_AB' in spin_from.params:
                kex_AB.append(spin_from.kex_AB)
            if 'kex_AC' in spin_from.params:
                kex_AC.append(spin_from.kex_AC)
            if 'kex_BC' in spin_from.params:
                kex_BC.append(spin_from.kex_BC)
            if 'k_AB' in spin_from.params:
                k_AB.append(spin_from.k_AB)
            if 'kB' in spin_from.params:
                kB.append(spin_from.kB)
            if 'kC' in spin_from.params:
                kC.append(spin_from.kC)
            if 'tex' in spin_from.params:
                tex.append(spin_from.tex)

            # Increment the spin count.
            count += 1

        # The cluster is not selected, so move to the next.
        if not selected_cluster:
            continue

        # Take median of parameters.
        if len(pA) > 0:
            pA = median(pA)
            print("Median pA value:  %.15f" % pA)
        if len(pB) > 0:
            pB = median(pB)
            print("Median pB value:  %.15f" % pB)
        if len(pC) > 0:
            pC = median(pC)
            print("Median pC value:  %.15f" % pC)
        if len(kex) > 0:
            kex = median(kex)
            print("Median kex value: %.15f" % kex)
        if len(kex_AB) > 0:
            kex_AB = median(kex_AB)
            print("Median k_AB value: %.15f" % kex_AB)
        if len(kex_AC) > 0:
            kex_AC = median(kex_AC)
            print("Median k_AC value: %.15f" % kex_AC)
        if len(kex_BC) > 0:
            kex_BC = median(kex_BC)
            print("Median k_BC value: %.15f" % kex_BC)
        if len(k_AB) > 0:
            k_AB = median(k_AB)
            print("Median k_AB value: %.15f" % k_AB)
        if len(kB) > 0:
            kB = median(kB)
            print("Median kB value:  %.15f" % kB)
        if len(kC) > 0:
            kC = median(kC)
            print("Median kC value:  %.15f" % kC)
        if len(tex) > 0:
            tex = median(tex)
            print("Median tex value: %.15f" % tex)

        # Loop over the spins, this time copying the parameters.
        for i in range(len(spin_ids)):
            # Alias the containers.
            spin_from = spins_from[i]
            spin_to = spins_to[i]

            # Skip deselected spins.
            if not spin_from.select or not spin_to.select:
                continue

            # The R20 parameters.
            if 'r2' in spin_from.params:
                spin_to.r2 = deepcopy(spin_from.r2)
            if 'r2a' in spin_from.params:
                spin_to.r2a = deepcopy(spin_from.r2a)
            if 'r2b' in spin_from.params:
                spin_to.r2b = deepcopy(spin_from.r2b)

            # The median parameters.
            if 'pB' in spin_from.params and 'pC' not in spin_from.params:
                spin_to.pA = pA
                spin_to.pB = pB
                spin_to.pC = 1.0 - pA - pB
            elif 'pA' in spin_from.params:
                spin_to.pA = pA
                spin_to.pB = 1.0 - pA
            if 'kex' in spin_from.params:
                spin_to.kex = kex
            if 'kex_AB' in spin_from.params:
                spin_to.kex_AB = kex_AB
            if 'kex_AC' in spin_from.params:
                spin_to.kex_AC = kex_AC
            if 'kex_BC' in spin_from.params:
                spin_to.kex_BC = kex_BC
            if 'k_AB' in spin_from.params:
                spin_to.k_AB = k_AB
            if 'kB' in spin_from.params:
                spin_to.kB = kB
            if 'kC' in spin_from.params:
                spin_to.kC = kC
            if 'tex' in spin_from.params:
                spin_to.tex = tex

            # All other spin specific parameters.
            for param in spin_from.params:
                if param in ['r2', 'r2a', 'r2b', 'pA', 'pB', 'pC', 'kex', 'kex_AB', 'kex_AC', 'kex_BC', 'k_AB', 'kB', 'kC', 'tex']:
                    continue

                # Copy the value.
                setattr(spin_to, param, deepcopy(getattr(spin_from, param)))

    # Switch back to the original data pipe.
    pipes.switch(pipe_orig)
Exemplo n.º 4
0
def copy(pipe_from=None, pipe_to=None):
    """Copy dispersion parameters from one data pipe to another, taking the median of previous values to a start value for clusters.
    Taking the median prevent averaging extreme outliers.

    @param pipe_from:   The data pipe to copy the value from.  This defaults to the current data pipe.
    @type pipe_from:    str
    @param pipe_to:     The data pipe to copy the value to.  This defaults to the current data pipe.
    @type pipe_to:      str
    """

    # The current data pipe.
    pipe_orig = pipes.cdp_name()
    if pipe_from == None:
        pipe_from = pipe_orig
    if pipe_to == None:
        pipe_to = pipe_orig

    # Test that the pipes exist.
    check_pipe(pipe_from)
    check_pipe(pipe_to)

    # Test that the pipes are not the same.
    if pipe_from == pipe_to:
        raise RelaxError("The source and destination pipes cannot be the same.")

    # Test if the sequence data for pipe_from is loaded.
    if not exists_mol_res_spin_data(pipe_from):
        raise RelaxNoSequenceError(pipe_from)

    # Test if the sequence data for pipe_to is loaded.
    if not exists_mol_res_spin_data(pipe_to):
        raise RelaxNoSequenceError(pipe_to)

    # Switch to the destination data pipe.
    pipes.switch(pipe_to)

    # Loop over the clusters.
    for spin_ids in loop_cluster():
        # Initialise some variables.
        model = None
        pA = []
        pB = []
        pC = []
        kex = []
        kex_AB = []
        kex_AC = []
        kex_BC = []
        k_AB = []
        kB = []
        kC = []
        tex = []
        count = 0
        spins_from = []
        spins_to = []
        selected_cluster = False

        # Loop over the spins, adding parameters to a list, which in the end will be used to find the median.
        for id in spin_ids:
            # Get the spins, then store them.
            spin_from = return_spin(id, pipe=pipe_from)
            spin_to = return_spin(id, pipe=pipe_to)
            spins_from.append(spin_from)
            spins_to.append(spin_to)

            # Skip deselected spins.
            if not spin_from.select or not spin_to.select:
                continue

            # The first printout.
            if not selected_cluster:
                subsection(file=sys.stdout, text="Copying parameters for the spin block %s"%spin_ids, prespace=2)

            # Change the cluster selection flag.
            selected_cluster = True

            # The model.
            if not model:
                model = spin_from.model

            # Check that the models match for all spins of the cluster.
            if spin_from.model != model:
                raise RelaxError("The model '%s' of spin '%s' from the source data pipe does not match the '%s' model of previous spins of the cluster." % (spin_from.model, id, model))
            if spin_to.model != model:
                raise RelaxError("The model '%s' of spin '%s' from the destination data pipe does not match the '%s' model of previous spins of the cluster." % (spin_from.model, id, model))

            # Sum the source parameters.
            if 'pA' in spin_from.params:
                pA.append(spin_from.pA)
            if 'pB' in spin_from.params:
                pB.append(spin_from.pB)
            if 'pC' in spin_from.params:
                pC.append(spin_from.pC)
            if 'kex' in spin_from.params:
                kex.append(spin_from.kex)
            if 'kex_AB' in spin_from.params:
                kex_AB.append(spin_from.kex_AB)
            if 'kex_AC' in spin_from.params:
                kex_AC.append(spin_from.kex_AC)
            if 'kex_BC' in spin_from.params:
                kex_BC.append(spin_from.kex_BC)
            if 'k_AB' in spin_from.params:
                k_AB.append(spin_from.k_AB)
            if 'kB' in spin_from.params:
                kB.append(spin_from.kB)
            if 'kC' in spin_from.params:
                kC.append(spin_from.kC)
            if 'tex' in spin_from.params:
                tex.append(spin_from.tex)

            # Increment the spin count.
            count += 1

        # The cluster is not selected, so move to the next.
        if not selected_cluster:
            continue

        # Take median of parameters.
        if len(pA) > 0:
            pA = median(pA)
            print("Median pA value:  %.15f" % pA)
        if len(pB) > 0:
            pB = median(pB)
            print("Median pB value:  %.15f" % pB)
        if len(pC) > 0:
            pC = median(pC)
            print("Median pC value:  %.15f" % pC)
        if len(kex) > 0:
            kex = median(kex)
            print("Median kex value: %.15f" % kex)
        if len(kex_AB) > 0:
            kex_AB = median(kex_AB)
            print("Median k_AB value: %.15f" % kex_AB)
        if len(kex_AC) > 0:
            kex_AC = median(kex_AC)
            print("Median k_AC value: %.15f" % kex_AC)
        if len(kex_BC) > 0:
            kex_BC = median(kex_BC)
            print("Median k_BC value: %.15f" % kex_BC)
        if len(k_AB) > 0:
            k_AB = median(k_AB)
            print("Median k_AB value: %.15f" % k_AB)
        if len(kB) > 0:
            kB = median(kB)
            print("Median kB value:  %.15f" % kB)
        if len(kC) > 0:
            kC = median(kC)
            print("Median kC value:  %.15f" % kC)
        if len(tex) > 0:
            tex = median(tex)
            print("Median tex value: %.15f" % tex)

        # Loop over the spins, this time copying the parameters.
        for i in range(len(spin_ids)):
            # Alias the containers.
            spin_from = spins_from[i]
            spin_to = spins_to[i]

            # Skip deselected spins.
            if not spin_from.select or not spin_to.select:
                continue

            # The R20 parameters.
            if 'r2' in spin_from.params:
                spin_to.r2 = deepcopy(spin_from.r2)
            if 'r2a' in spin_from.params:
                spin_to.r2a = deepcopy(spin_from.r2a)
            if 'r2b' in spin_from.params:
                spin_to.r2b = deepcopy(spin_from.r2b)

            # The median parameters.
            if 'pB' in spin_from.params and 'pC' not in spin_from.params:
                spin_to.pA = pA
                spin_to.pB = pB
                spin_to.pC = 1.0 - pA - pB
            elif 'pA' in spin_from.params:
                spin_to.pA = pA
                spin_to.pB = 1.0 - pA
            if 'kex' in spin_from.params:
                spin_to.kex = kex
            if 'kex_AB' in spin_from.params:
                spin_to.kex_AB = kex_AB
            if 'kex_AC' in spin_from.params:
                spin_to.kex_AC = kex_AC
            if 'kex_BC' in spin_from.params:
                spin_to.kex_BC = kex_BC
            if 'k_AB' in spin_from.params:
                spin_to.k_AB = k_AB
            if 'kB' in spin_from.params:
                spin_to.kB = kB
            if 'kC' in spin_from.params:
                spin_to.kC = kC
            if 'tex' in spin_from.params:
                spin_to.tex = tex

            # All other spin specific parameters.
            for param in spin_from.params:
                if param in ['r2', 'r2a', 'r2b', 'pA', 'pB', 'pC', 'kex', 'kex_AB', 'kex_AC', 'kex_BC', 'k_AB', 'kB', 'kC', 'tex']:
                    continue

                # Copy the value.
                setattr(spin_to, param, deepcopy(getattr(spin_from, param)))

    # Switch back to the original data pipe.
    pipes.switch(pipe_orig)