lpp_zpositions init

biobb_mem/lipyphilic_biobb/__init__.py

@@ -1,2 +1,2 @@
 name = "lipyphilic_biobb"
-__all__ = ["lpp_assign_leaflets"]
+__all__ = ["lpp_assign_leaflets", "lpp_zpositions"]

biobb_mem/lipyphilic_biobb/lpp_zpositions.py

@@ -0,0 +1,227 @@
+#!/usr/bin/env python3
+
+"""Module containing the Lipyphilic ZPositions class and the command line interface."""
+import argparse
+from biobb_common.generic.biobb_object import BiobbObject
+from biobb_common.configuration import settings
+from biobb_common.tools.file_utils import launchlogger
+import MDAnalysis as mda
+from MDAnalysis.transformations.boxdimensions import set_dimensions
+from lipyphilic.analysis.z_positions import ZPositions
+import pandas as pd
+import numpy as np
+
+
+class LPPZPositions(BiobbObject):
+    """
+    | biobb_mem LPPZPositions
+    | Wrapper of the LiPyphilic ZPositions module for assigning lipids to leaflets in a bilayer.
+    | LiPyphilic is a Python package for analyzing MD simulations of lipid bilayers. The parameter names and defaults are the same as the ones in the official `Lipyphilic documentation <https://lipyphilic.readthedocs.io/en/latest/reference/analysis/z_pos.html>`_.
+
+    Args:
+        input_top_path (str): Path to the input structure or topology file. File type: input. `Sample file <https://github.com/bioexcel/biobb_mem/raw/master/biobb_mem/test/data/A01JD/A01JD.pdb>`_. Accepted formats: crd (edam:3878), gro (edam:2033), mdcrd (edam:3878), mol2 (edam:3816), pdb (edam:1476), pdbqt (edam:1476), prmtop (edam:3881), psf (edam:3882), top (edam:3881), tpr (edam:2333), xml (edam:2332), xyz (edam:3887).
+        input_traj_path (str): Path to the input trajectory to be processed. File type: input. `Sample file <https://github.com/bioexcel/biobb_mem/raw/master/biobb_mem/test/data/A01JD/A01JD.xtc>`_. Accepted formats: arc (edam:2333), crd (edam:3878), dcd (edam:3878), ent (edam:1476), gro (edam:2033), inpcrd (edam:3878), mdcrd (edam:3878), mol2 (edam:3816), nc (edam:3650), pdb (edam:1476), pdbqt (edam:1476), restrt (edam:3886), tng (edam:3876), trr (edam:3910), xtc (edam:3875), xyz (edam:3887).
+        output_leaflets_path (str): Path to the output leaflet assignments. File type: output. `Sample file <https://github.com/bioexcel/biobb_mem/raw/master/biobb_mem/test/reference/lipyphilic_biobb/leaflets.csv>`_. Accepted formats: csv (edam:format_3752).
+        properties (dic - Python dictionary object containing the tool parameters, not input/output files):
+            * **start** (*int*) - (None) Starting frame for slicing.
+            * **stop** (*int*) - (None) Ending frame for slicing.
+            * **steps** (*int*) - (None) Step for slicing.
+            * **lipid_sel** (*str*) - ("all") Selection string for the lipids in a membrane. The selection should cover **all** residues in the membrane, including cholesterol.
+            * **height_sel** (*str*) - ("all") Atom selection for the molecules for which the z position will be calculated.
+            * **n_bins** (*int*) - (1) Number of bins in *x* and *y* to use to create a grid of membrane patches. Local membrane midpoints are computed for each patch, and lipids assigned a leaflet based on the distance to their local membrane midpoint. The default is `1`, which is equivalent to computing a single global midpoint.
+            * **ignore_no_box** (*bool*) - (False) Ignore the absence of box information in the trajectory. If the trajectory does not contain box information, the box will be set to the minimum and maximum positions of the atoms in the trajectory.
+            * **remove_tmp** (*bool*) - (True) [WF property] Remove temporal files.
+            * **restart** (*bool*) - (False) [WF property] Do not execute if output files exist.
+            * **sandbox_path** (*str*) - ("./") [WF property] Parent path to the sandbox directory.
+
+    Examples:
+        This is a use example of how to use the building block from Python::
+
+            from biobb_mem.lipyphilic_biobb.lpp_zpositions import lpp_zpositions
+            prop = {
+                'lipid_sel': 'name GL1 GL2 ROH',
+            }
+            lpp_zpositions(input_top_path='/path/to/myTopology.tpr',
+                                input_traj_path='/path/to/myTrajectory.xtc',
+                                output_leaflets_path='/path/to/leaflets.csv',
+                                properties=prop)
+
+    Info:
+        * wrapped_software:
+            * name: LiPyphilic
+            * version: 0.10.0
+            * license: GPL-2.0
+        * ontology:
+            * name: EDAM
+            * schema: http://edamontology.org/EDAM.owl
+
+    """
+
+    def __init__(self, input_top_path, input_traj_path, output_leaflets_path,
+                 properties=None, **kwargs) -> None:
+        properties = properties or {}
+
+        # Call parent class constructor
+        super().__init__(properties)
+        self.locals_var_dict = locals().copy()
+
+        # Input/Output files
+        self.io_dict = {
+            "in": {"input_top_path": input_top_path, "input_traj_path": input_traj_path},
+            "out": {"output_leaflets_path": output_leaflets_path}
+        }
+
+        # Properties specific for BB
+        self.lipid_sel = properties.get('lipid_sel', 'all')
+        self.midplane_sel = properties.get('midplane_sel', None)
+        self.midplane_cutoff = properties.get('midplane_cutoff', None)
+        self.n_bins = properties.get('n_bins', 1)
+        self.start = properties.get('start', None)
+        self.stop = properties.get('stop', None)
+        self.steps = properties.get('steps', None)
+        self.ignore_no_box = properties.get('ignore_no_box', True)
+        self.properties = properties
+
+        # Check the properties
+        self.check_properties(properties)
+        self.check_arguments()
+
+    @launchlogger
+    def launch(self) -> int:
+        """Execute the :class:`LPPZPositions <lipyphilic_biobb.lpp_zpositions.LPPZPositions>` lipyphilic_biobb.lpp_zpositions.LPPZPositions object."""
+
+        # Setup Biobb
+        if self.check_restart():
+            return 0
+        self.stage_files()
+
+        # Load the trajectory
+        u = mda.Universe(self.stage_io_dict["in"]["input_top_path"], self.stage_io_dict["in"]["input_traj_path"])
+        if u.dimensions is None:
+            if self.ignore_no_box:
+                print('Warning: trajectory probably has no box variable. Setting dimensions ussing the minimum and maximum positions of the atoms.')
+                # Initialize min and max positions with extreme values
+                min_pos = np.full(3, np.inf)
+                max_pos = np.full(3, -np.inf)
+
+                # Iterate over all frames to find the overall min and max positions
+                for ts in u.trajectory:
+                    positions = u.atoms.positions
+                    min_pos = np.minimum(min_pos, positions.min(axis=0))
+                    max_pos = np.maximum(max_pos, positions.max(axis=0))
+
+                # Calculate the dimensions of the box
+                box_dimensions = max_pos - min_pos
+                u.trajectory.add_transformations(set_dimensions([*box_dimensions, 90, 90, 90]))
+            else:
+                raise ValueError('The trajectory does not contain box information. Please set the ignore_no_box property to True to ignore this error.')
+
+        # Create ZPositions object
+        leaflets = ZPositions(
+            universe=u,
+            lipid_sel=self.lipid_sel,
+            midplane_sel=self.midplane_sel,
+            midplane_cutoff=self.midplane_cutoff,
+            n_bins=self.n_bins
+        )
+        # Run the analysis
+        leaflets.run(
+            start=self.start,
+            stop=self.stop,
+            step=self.steps
+        )
+        # Save the results
+        frames = leaflets.leaflets.shape[1]
+        resnames = np.repeat(leaflets.membrane.resnames, frames)
+        resindices = np.tile(leaflets.membrane.resindices, frames)
+        frame_numbers = np.repeat(np.arange(frames), leaflets.membrane.n_residues)
+
+        df = pd.DataFrame({
+            'resname': resnames,
+            'resindex': resindices,
+            'frame': frame_numbers,
+            'leaflet_index': leaflets.leaflets.T.flatten()
+        })
+
+        # Save the DataFrame to a CSV file
+        df.to_csv(self.stage_io_dict["out"]["output_leaflets_path"], index=False)
+
+        # Copy files to host
+        self.copy_to_host()
+        # remove temporary folder(s)
+        self.tmp_files.extend([
+            self.stage_io_dict.get("unique_dir")
+        ])
+        self.remove_tmp_files()
+
+        self.check_arguments(output_files_created=True, raise_exception=False)
+
+        return self.return_code
+
+
+def lpp_zpositions(input_top_path: str, input_traj_path: str, output_leaflets_path: str = None, properties: dict = None, **kwargs) -> int:
+    """Execute the :class:`LPPZPositions <lipyphilic_biobb.lpp_zpositions.LPPZPositions>` class and
+    execute the :meth:`launch() <lipyphilic_biobb.lpp_zpositions.LPPZPositions.launch>` method."""
+
+    return LPPZPositions(input_top_path=input_top_path,
+                         input_traj_path=input_traj_path,
+                         output_leaflets_path=output_leaflets_path,
+                         properties=properties, **kwargs).launch()
+
+
+def main():
+    """Command line execution of this building block. Please check the command line documentation."""
+    parser = argparse.ArgumentParser(description="Assign lipids to leaflets in a bilayer.", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999))
+    parser.add_argument('--config', required=False, help='Configuration file')
+
+    # Specific args of each building block
+    required_args = parser.add_argument_group('required arguments')
+    required_args.add_argument('--input_top_path', required=True, help='Path to the input structure or topology file. Accepted formats: crd, gro, mdcrd, mol2, pdb, pdbqt, prmtop, psf, top, tpr, xml, xyz.')
+    required_args.add_argument('--input_traj_path', required=True, help='Path to the input trajectory to be processed. Accepted formats: arc, crd, dcd, ent, gro, inpcrd, mdcrd, mol2, nc, pdb, pdbqt, restrt, tng, trr, xtc, xyz.')
+    required_args.add_argument('--output_leaflets_path', required=True, help='Path to the output processed analysis.')
+
+    args = parser.parse_args()
+    args.config = args.config or "{}"
+    properties = settings.ConfReader(config=args.config).get_prop_dic()
+
+    # Specific call of each building block
+    lpp_zpositions(input_top_path=args.input_top_path,
+                   input_traj_path=args.input_traj_path,
+                   output_leaflets_path=args.output_leaflets_path,
+                   properties=properties)
+
+
+def display_nglview(input_top_path: str, output_leaflets_path: str, frame: int = 0):
+    """
+    Visualize the leaflets of a membrane using NGLView.
+
+    Args:
+        input_top_path (str): Path to the input topology file.
+        output_leaflets_path (str): Path to the CSV file containing leaflet assignments.
+        frame (int, optional): Frame number to visualize. Default is 0.
+    Returns:
+        nglview.NGLWidget: An NGLView widget displaying the membrane leaflets.
+    """
+
+    try:
+        import nglview as nv
+    except ImportError:
+        raise ImportError('Please install the nglview package to visualize the leaflets.')
+    # Read the leaflets DataFrame
+    df = pd.read_csv(output_leaflets_path)
+    top_idx = df[(df['frame'] == frame) & (df['leaflet_index'] == 1)]['resindex'].values
+    bot_idx = df[(df['frame'] == frame) & (df['leaflet_index'] == -1)]['resindex'].values
+    # Load the topology and convert the resindices to resnums (nglview uses resnums)
+    u = mda.Universe(input_top_path)
+    top_resnum = u.residues[top_idx].resnums
+    bot_resnum = u.residues[bot_idx].resnums
+    # Create the view
+    view = nv.show_file(input_top_path)
+    view.update_ball_and_stick(selection='all', opacity=0.0)   # delete membrane
+    view.add_ball_and_stick(selection=", ".join(map(str, top_resnum)), color='blue')
+    view.add_ball_and_stick(selection=", ".join(map(str, bot_resnum)), color='yellow')
+    return view
+
+
+if __name__ == '__main__':
+    main()