# Configuration file options¶

Valve Configuration file is a simple and plain text file. It has similar structure as INI files commonly used in one of the popular operating systems and is compliant with Python module ConfigParser.

Configuration file comprises of several sections. They can be grouped into three categories. Names of sections are in bold text.

1. Global settings:
• global
2. Stages options:
1. traceable_residues
2. raw_paths
3. separate_paths
4. inlets_clusterization
5. analysis
6. visualize
3. Methods options:
• smooth
• clusterization
• reclusteriation

## Section global¶

This section allows settings of trajectory data and some other future global options.

Option Default value Description
top None Path to topology file. Aqua-Duct supports PDB, PRMTOP, PFS topology files.
trj None Path to trajectory file. Aqua-Duct supports NC and DCD trajectory files.

Note

Options top and trj are mandatory.

## Common settings of stage sections¶

Stages 1-4 which perform calculations have some common options allowing for execution control and saving/loading data.

Option Default value Description
execute runonce Option controls stage execution. It can have one of three possible values: run, runonce, and skip. If it is set to run calculations are always performed and if dump is set dump file is saved. If it is set to runonce calculations are performed if there is no dump file specified by dump option. If it is present calculations are skiped and data is loaded from the file. If it is set to skip calculations are skip and if dump is set data is loaded from the file.
dump [dump file name]

File name of dump data. It is used to save results of calculations or to load previously calculated data - this depends on execute option. Default value of this option depends on the stage and for stages 1 to 4 is one of the following (listed in order):

• 1_traceable_residues_data.dump
• 2_raw_paths_data.dump
• 3_separate_paths_data.dump
• 4_inlets_clusterization_data.dump

Stages 5-6 also uses execute option, however, since they do not perform calculations per se in stead of dump option they use save.

Option Default value Description
execute run Option controls stage execution. It can have one of three possible values: run, runonce, and skip. If it is set to run or runonce stage is executed and results is saved according to save option. If it is set to skip stage is skipped.
save [save file name]

File name for saving results. Default value of this option depends on the stage and for stages 1 to 4 is one of the following (listed in order):

• 5_analysis_results.txt
• 6_visualize_results.py

Stage 6 can save results in two file types:

1. As Python script - extension .py plus companion archive .tar.gz,
2. As PyMOL session - extension .pse.

## Stage traceable_residues¶

Option Default value Description
scope_convexhull True Flag to set if the Scope is direct or convex hull definition.

Note

Options scope and object are mandatory.

## Stage raw_paths¶

This stage also requires definition of the Scope and Object. If appropriate settings are not given, settings from the previous stage are used.

Option Default value Description
scope None Definition of Scope of interest. See also Scope definition. If None value form previous stage is used.
scope_convexhull None Flag to set if the Scope is direct or convex hull definition. If None value form previous stage is used.
object None Definition of Object of interest. See also Object definition. If None value form the previous stage is used
clear_in_object_info False If it is set to True information on occupation of Object site by traceable residues calculated in the previous stage is cleared and have to be recalculated. This is useful if definition of Object was changed.

## Stage separate_paths¶

Option Default value Description
discard_empty_paths True If set to True empty paths are discarded.
sort_by_id True If set to True separate paths are sorted by ID. Otherwise they are sorted in order of apparance.
apply_smoothing False If set to True smooth paths are precalculated according to smooth setting. This speeds up access to smooth paths in later stages but makes dump data much bigger.
apply_soft_smoothing True If set to True raw paths are replaced by smooth paths calculated according to smooth section.
discard_short_paths 1 This option allows to discard paths that are shorter than the threshold.
auto_barber None This option allows to select molecular entity used in Auto Barber procedure. See also Auto Barber and barber_with_spheres().
auto_barber_mincut None Minimal radius of spheres used in Auto Barber. If a sphere has radius smaller then this value it is not used in AutoBarber procedure. This option can be switched off by setting it to None.
auto_barber_maxcut 2.8 Maximal radius of spheres used in Auto Barber. If a sphere has radius greater then this value it is not used in AutoBarber procedure. This option can be switched off by setting it to None.
auto_barber_mincut_level True If set True spheres of radius smaller than mincut are resized to mincut value.
auto_barber_maxcut_level True If set True spheres of radius greater than maxcut are resized to maxcut value.
auto_barber_tovdw True Correct cutting sphere by decreasing its radius by VdW radius of the closest atom.

## Stage inlets_clusterization¶

Option Default value Description
recluster_outliers False If set to True reclusterization of outliers is executed according to the method defined in reclusterization section.
detect_outliers False If set detection of outliers is executed. It could be set as a floating point distance threshold or set tu Auto. See Clusterization of inlets for more details.
singletons_outliers False Maximal size of cluster to be considered as outliers. If set to number > 0 clusters of that size are removed and their objects are moved to outliers. See Clusterization of inlets for more details.
max_level 5 Maximal number of recursive clusterization levels.
create_master_paths False If set to True master paths are created (fast CPU and big RAM recommended; 50k frames long simulation may need ca 20GB of memory)

## Stage analysis¶

Option Default value Description
dump_config True If set to True configuration options, as seen by Valve, are added to the head of results.

## Stage visualize¶

Option Default value Description
simply_smooths RecursiveVector

Option indicates linear simplification method to be used in plotting smooth paths. Simplification removes points which do not (or almost do not) change the shape of smooth path. Possible choices are:

Optionally name of the method can be followed by a threshold value in parentheses, ie RecursiveVector(0.05). For sane values of thresholds see appropriate documentation of each method. Default values work well. This option is not case sensitive. It is recommended to use default method or HobbitVector method.

all_paths_raw False If True produces one object in PyMOL that holds all paths visualized by raw coordinates.
all_paths_smooth False If True produces one object in PyMOL that holds all paths visualized by smooth coordinates.
all_paths_split False If is set True objects produced by all_paths_raw and all_paths_smooth are split into Incoming, Object, and Outgoing parts and visualized as three different objects.
all_paths_raw_io False If set True arrows pointing beginning and end of paths are displayed oriented accordingly to raw paths orientation.
all_paths_smooth_io False If set True arrows pointing beginning and end of paths are displayed oriented accordingly to smooth paths orientation.
paths_raw False If set True raw paths are displayed as separate objects or as one object with states corresponding to number of path.
paths_smooth False If set True smooth paths are displayed as separate objects or as one object with states corresponding to number of path.
paths_raw_io False If set True arrows indicating beginning and end of paths, oriented accordingly to raw paths, are displayed as separate objects or as one object with states corresponding to number of paths.
paths_smooth_io False If set True arrows indicating beginning and end of paths, oriented accordingly to smooth paths, are displayed as separate objects or as one object with states corresponding to number of paths.
paths_states False If True objects displayed by paths_raw, paths_smooth, paths_raw_io, and paths_smooth_io are displayed as one object with states corresponding to number of paths. Otherwise they are displayed as separate objects.
ctypes_raw False Displays raw paths in a similar manner as non split all_paths_raw but each cluster type is displayed in separate object.
ctypes_smooth False Displays smooth paths in a similar manner as non split all_paths_smooth but each cluster type is displayed in separate object.
show_molecule False If is set to selection of some molecular object in the system, for example to protein, this object is displayed.
show_molecule_frames 0 Allows to indicate which frames of object defined by show_molecule should be displayed. It is possible to set several frames. In that case frames would be displayed as states.
show_chull False If is set to selection of some molecular object in the system, for example to protein, convex hull of this object is displayed.
show_chull_frames 0 Allows to indicate for which frames of object defined by show_chull convex hull should be displayed. It is possible to set several frames. In that case frames would be displayed as states.
show_object False If is set to selection of some molecular object in the system convex hull of this object is displayed. This works exacly the same way as show_chull but is meant to mark object shape. It can be achevied by using name * and molecular object definition plus some spatial constrains, for example those used in object definition.
show_object_frames 0 Allows to indicate for which frames of object defined by show_object convex hull should be displayed. It is possible to set several frames. In that case frames would be displayed as states.

Note

Possibly due to limitations of MDAnalysis only whole molecules can be displayed. If show_molecule is set to backbone complete protein will be displayed any way. This may change in future version of MDAnalysis and or aquaduct.

Note

If several frames are selected they are displayed as states which may interfere with other PyMOL objects displayed with several states.

Note

If several states are displayed protein tertiary structure data might be lost. This seems to be limitation of either MDAnalysis or PyMOL.

## Clusterization sections¶

Default section for definition of clusterization method is named clusterization and default section for reclusterization method definition is named reclusterization. All clusterization sections shares some common options. Other options depends on the method.

Option Default value Description
method barber or dbscan Name of clusterization method. It has to be one of the following: barber, dbscan, affprop, meanshift, birch, kmeans. Default value depends whether it is clusteriation section (barber) or reclusterization section (dbscan).
recursive_clusterization clusterization or None If it is set to name of some section that holds clusterization method settings this method will be called in the next recursion of clusteriation. Default value for reclusterization is None.
recursive_threshold None Allows to set threshold that excludes clusters of certain size from reclusterization. Value of this option comprises of operator and value. Operator can be one of the following: >, >=, <=, <. Value have to be expressed as floating number and it have to be in the range of 0 to 1. One can use several definitions separated by a space character. Only clusters of size complying with all thresholds definitions are submitted to reclusterization.

### barber¶

Clusterization by barber method bases on Auto Barber procedure. For each inlets a sphere is constructed according to Auto Barber separate_paths Stage settings or according to parameters given in clausterization section. Next, inlets that form coherent clouds of mutually intersecting spheres are grouped in to clusters. Method barber supports the same settings as Auto Barber settings:

Option Value type Description
auto_barber str This option allows to select molecular entity used in Auto Barber procedure. See also Auto Barber and barber_with_spheres().
auto_barber_mincut float Minimal radius of spheres used in Auto Barber. If a sphere has radius smaller then this value it is not used to cut. This option can be switched off by setting it to None.
auto_barber_maxcut float Maximal radius of spheres used in Auto Barber. If a sphere has radius greater then this value it is not used to cut. This option can be switched off by setting it to None.
auto_barber_mincut_level bool If set True spheres of radius less then mincut are resized to mincut value.
auto_barber_maxcut_level bool If set True spheres of radius greater then maxcut are resized to maxcut value.
auto_barber_tovdw bool Correct cutting sphere by decreasing its radius by VdW radius of the closest atom.

### dbscan¶

For detailed description look at sklearn.cluster.DBSCAN documentation. Following table summarized options available in Valve and is a copy of original documentation.

Option Value type Description
eps float The maximum distance between two samples for them to be considered as in the same neighborhood.
min_samples int The number of samples (or total weight) in a neighborhood for a point to be considered as a core point. This includes the point itself.
metric str

The metric to use when calculating distance between instances in a feature array. Can be one of the following:

• cityblock,
• cosine,
• euclidean,
• manhattan.
algorithm str

The algorithm to be used by the NearestNeighbors module to compute pointwise distances and find nearest neighbors. Can be one of the following:

• auto,
• ball_tree,
• kd_tree,
• brute.
leaf_size int Leaf size passed to BallTree or cKDTree.

### affprop¶

For detailed description look at AffinityPropagation documentation. Following table summarized options available in Valve and is a copy of original documentation.

Option Value type Description
damping float Damping factor between 0.5 and 1.
convergence_iter int Number of iterations with no change in the number of estimated clusters that stops the convergence.
max_iter int Maximum number of iterations.
preference float Points with larger values of preferences are more likely to be chosen as exemplars.

### meanshift¶

For detailed description look at MeanShift documentation. Following table summarized options available in Valve and is a copy of original documentation.

Option Value type Description
bandwidth Auto or float Bandwidth used in the RBF kernel. If Auto or None automatic method for bandwidth estimation is used. See estimate_bandwidth().
cluster_all bool If true, then all points are clustered, even those orphans that are not within any kernel.
bin_seeding bool If true, initial kernel locations are not locations of all points, but rather the location of the discretized version of points, where points are binned onto a grid whose coarseness corresponds to the bandwidth.
min_bin_freq int To speed up the algorithm, accept only those bins with at least min_bin_freq points as seeds. If not defined, set to 1.

### birch¶

For detailed description look at Birch documentation. Following table summarized options available in Valve and is a copy of original documentation.

Option Value type Description
threshold float The radius of the subcluster obtained by merging a new sample and the closest subcluster should be lesser than the threshold. Otherwise a new subcluster is started.
branching_factor int Maximum number of CF subclusters in each node.
n_clusters int Number of clusters after the final clustering step, which treats the subclusters from the leaves as new samples. By default, this final clustering step is not performed and the subclusters are returned as they are.

### kmeans¶

For detailed description look at KMeans documentation. Following table summarized options available in Valve and is a copy of original documentation.

Option Value type Description
n_clusters int The number of clusters to form as well as the number of centroids to generate.
max_iter int Maximum number of iterations of the k-means algorithm for a single run.
n_init int Number of time the k-means algorithm will be run with different centroid seeds. The final results will be the best output of n_init consecutive runs in terms of inertia.
init str Method for initialization, defaults to k-means++. Can be one of following: k-means++ or random.
tol float Relative tolerance with regards to inertia to declare convergence.

## Smooth section¶

Section smooth supports following options:

Option Value type Description
method str

Smoothing method. Can be one of the following:

recursive int Number of recursive runs of smoothing method.
window int or float In window based method defines window size. In plain window it has to be int number. In savgol it has to be odd integer.
step int In step based method defines size of the step.
function str In window based methods defines averaging function. Can be mean or median.
polyorder int In savgol is polynomial order.