AddData.py

# This is the code that generates databank indexing

# IMPORTING LIBRARIES

# Working with files and directories
import os
import argparse
import yaml
import logging
import shutil
import pprint
import traceback
from datetime import date
from pathlib import Path
from random import randint
from urllib.error import URLError, HTTPError
from copy import deepcopy
import pandas as pd

pd.set_option("display.max_rows", 500)
pd.set_option("display.max_columns", 500)
pd.set_option("display.width", 1000)
pd.set_option("display.max_colwidth", 1000)

from MDAnalysis import Universe
from OrderParameter import *

# import databank dictionaries
from databankLibrary import (
    calc_file_sha1_hash,
    create_databank_directories,
    lipids_dict,
    molecules_dict,
    software_dict,
)


# helpers
from databankLibrary import (
    download_resource_from_uri,
    parse_valid_config_settings,
    resolve_download_file_url,
)


# for building hydrogens to united atom simulations


# parse input yaml file
parser = argparse.ArgumentParser(
    prog="AddData.py Script", description="Add a new dataset to the NMRLipids databank"
)
parser.add_argument("-f", "--file", help="Input config file in yaml " "format.")
parser.add_argument(
    "-d", "--debug", help="enable debug logging output", action="store_true"
)
parser.add_argument(
    "-n", "--no-cache", help="always redownload repository files", action="store_true"
)
parser.add_argument(
    "-w", "--work-dir", help="set custom temporary working directory", default=""
)
parser.add_argument(
    "-o",
    "--output-dir",
    help="set custom output directory",
    default=os.path.join(
        Path(os.getcwd()).parents[1].absolute(), "Data", "Simulations"
    ),
)

args = parser.parse_args()

# configure logging
logging_level = logging.DEBUG if args.debug else logging.INFO
logging.basicConfig(
    format="%(asctime)s [%(levelname)s]: %(message)s",
    datefmt="%m/%d/%Y %I:%M:%S %p",
    level=logging_level,
)
logger = logging.getLogger()

all_molecules = []
for key in lipids_dict:
    all_molecules.append(key)
for key in molecules_dict:
    all_molecules.append(key)

input_path = os.path.join(".", args.file)

# load input yaml file into empty dictionary
info_yaml = {}

# open input file for reading and writing
with open(input_path) as yaml_file:
    info_yaml = yaml.load(
        yaml_file, Loader=yaml.FullLoader
    )  # TODO may throw yaml.YAMLError
yaml_file.close()

# Show the input read
logger.debug(f"{os.linesep} Input read from {input_path} file:")
pp = pprint.PrettyPrinter(width=41, compact=True)
if logger.isEnabledFor(logging.DEBUG):
    pp.pprint(yaml.dump(info_yaml))

# validate yaml entries and return updated sim dict
try:
    sim, files = parse_valid_config_settings(info_yaml)
except KeyError as e:
    logger.error(f"missing entry key in yaml config: {e}, aborting")
    logger.error(traceback.format_exc())
    quit()
except Exception as e:
    logger.error(
        f"an '{type(e).__name__}' occured while processing '{input_path}', script has been aborted"
    )
    logger.error(e)
    quit()
else:
    logger.info(
        f"all entries in simulation are understood and will be further processed"
    )
    logger.debug("valid sim entry keys:")
    pp = pprint.PrettyPrinter(width=41, compact=True)
    if logger.isEnabledFor(logging.DEBUG):
        pp.pprint(sim)

# Create temporary directory where to download files and analyze them

if args.work_dir:
    dir_wrk = args.work_dir
    logger.warning(
        f"--work_dir override, ignoring 'DIR_WRK' from configuration file: {sim['DIR_WRK']}"
    )
else:
    dir_wrk = sim["DIR_WRK"]

dir_tmp = (
    os.path.join(dir_wrk, "tmp_6-" + str(randint(100000, 999999)))
    if args.no_cache
    else os.path.join(dir_wrk, f"{sim['DOI'].split('/')[-1]}_download")
)

logger.info(f"The data will be processed in directory path '{dir_tmp}'")

try:
    os.makedirs(dir_tmp, exist_ok=True)
except OSError as e:
    logger.error(
        f"couldn't create temporary working directory '{dir_tmp}': {e.args[1]}"
    )
    quit()

# Check link status and download files

try:
    download_links = [
        resolve_download_file_url(sim["DOI"], fi, validate_uri=True) for fi in files
    ]

    logger.info(f"Now downloading {len(files)} files ...")

    for url, fi in zip(download_links, files):
        download_resource_from_uri(
            url, os.path.join(dir_tmp, fi), override_if_exists=args.no_cache
        )

    logger.info(f"Download of {len(files)} files was successful")

except HTTPError as e:
    if e.code == 404:
        logger.error(
            f"ressource not found on server '{e.url}' (404). Wrong DOI link or file name?"
        )
    else:
        logger.error(f"HTTPError {e.code} while trying to download the file '{e.url}'")
    quit()
except URLError as e:
    logger.error(
        f"couldn't resolve network adress: {e.reason}. Please check your internet connection."
    )
    quit()
except Exception as e:
    logger.error(
        f"'{type(e).__name__}' while attempting to download ressources, aborting"
    )
    logger.error(traceback.format_exc())
    quit()


# ## Calculate hash of downloaded files

sim_hashes = deepcopy(sim)

software_sim = software_dict[sim["SOFTWARE"].upper()]

# list_containing the sha1 sums for all required files
sha1_list_requied = []

# Make empty dataframe with the desired columns
df_files = pd.DataFrame(
    columns=["NAME", "TYPE", "REQUIRED", "SIZE_MB", "HASH"], dtype=object
)

for key_sim, value_sim in sim_hashes.items():
    try:
        entry_type = software_sim[key_sim]["TYPE"]
        if "file" in entry_type:
            files_list = []
            is_required = software_dict[sim_hashes["SOFTWARE"].upper()][key_sim][
                "REQUIRED"
            ]

            if not is_required and value_sim is None:
                continue  # skip not required NoneType (empty) file entries

            for file_provided in value_sim:
                file_name = os.path.join(dir_tmp, file_provided[0])
                logger.info(f"calculating sha1 hash of '{file_provided[0]}'...")
                file_hash = calc_file_sha1_hash(file_name)
                file_size_mb = f"{(os.path.getsize(file_name)/1024/1024):.2f}"

                df_files = pd.concat(
                    [
                        df_files,
                        pd.DataFrame(
                            [
                                {
                                    "NAME": file_provided[0],
                                    "TYPE": key_sim,
                                    "REQUIRED": is_required,
                                    "SIZE_MB": file_size_mb,
                                    "HASH": file_hash,
                                }
                            ]
                        ),
                    ],
                    ignore_index=True,
                )
                files_list.append([file_provided[0], file_hash])

                # Find the keys of the required files to calculate the master_hash
                if is_required:
                    sha1_list_requied.append(file_hash)

                sim_hashes[key_sim] = files_list  # TODO Problematic
    except KeyError as e:  # It is notmal that fails for "ID" and "SOFTWARE"
        continue

logger.info(f"Summary of downloaded files:{os.linesep}")
print(df_files)
print()

# Calculate the hash of a file contaning the hashes of each of the required files
# This should be always invariant as it will be used unique identifier for a simualtion
# Note order the hashes of the required files before calculating the hash (That means that the required files cannot change)

# Calculates numbers of lipid molecules in each leaflet. This is done by checking on which side of the centre
# of mass the membrane each the centre of mass of a lipid molecule is.
# If a lipid molecule is split so that headgroup and tails are their own residues, the centre of mass of the
# headgroup is used in the calculation.
################################################################################################################

logger.info(
    "Calculating the numbers of lipid molecules in each leaflet based on the center of mass of the membrane and lipids."
)
logger.info(
    "If a lipid molecule is split to multiple residues, the centre of mass of the headgroup is used."
)

top = ""
traj = ""

if sim["SOFTWARE"] == "gromacs":
    top = os.path.join(dir_tmp, sim["TPR"][0][0])
    traj = os.path.join(dir_tmp, sim["TRJ"][0][0])
elif sim["SOFTWARE"] == "openMM" or sim["SOFTWARE"] == "NAMD":
    traj = os.path.join(dir_tmp, sim["TRJ"][0][0])
    top = os.path.join(dir_tmp, sim["PDB"][0][0])
else:
    logger.error(
     "SOFTWARE '%s' is not a proper option.\n"
     "Use either 'gromacs', 'openMM', or 'NAMD'.")
    quit()

leaflet1 = 0  # total number of lipids in upper leaflet
leaflet2 = 0  # total number of lipids in lower leaflet


gro = os.path.join(dir_tmp, "frame0.gro")
NewTraj = os.path.join(dir_tmp, "NewTraj.xtc")

try:
    logger.info(f"MDAnalysis tries to use {top} and {traj}")
    u = Universe(top, traj)
    u.atoms.write(gro, frames=u.trajectory[[0]])  # write first frame into gro file
except Exception as e:
    logger.warning(e)
    logger.info(
        "Now generating frame0.gro with Gromacs because MDAnalysis cannot read tpr version ..."
    )
    if ( "WARNINGS" in sim and 
         sim["WARNINGS"] is not None and
         sim["WARNINGS"]["GROMACS_VERSION"] == "gromacs3" ):
        logger.debug(
            f"executing 'echo System | gmx trjconv -s {top} -f {traj} -dump 22000 -o {gro}'"
        )
        os.system(
            "echo System | gmx trjconv -s "
            + top
            + " -f "
            + traj
            + " -dump 22000 -o "
            + gro
        )
    else:
        logger.debug(
            f"executing 'echo System | gmx trjconv -s {top} -f {traj} -dump 0 -o {gro}'"
        )
        os.system(
            "echo System | gmx trjconv -s " + top + " -f " + traj + " -dump 0 -o " + gro
        )
    try:
        u = Universe(gro, traj)
        u.atoms.write(gro, frames=u.trajectory[[0]])  # write first frame into gro file
    except Exception as e:
        logger.warning(e)
finally:
    if not os.path.isfile(gro):
        logger.error(f"'{gro}' could not be found, aborting")
        quit()

# TODO refactor this
try:
    groFORu0 = os.path.join(dir_tmp, sim["GRO"][0][0])
    logger.debug(groFORu0)
except:
    groFORu0 = gro

if sim["SOFTWARE"] == "gromacs":
    u0 = Universe(groFORu0)
elif sim["SOFTWARE"] == "openMM" or sim["SOFTWARE"] == "NAMD":
    u0 = Universe(top)
    
lipids = []

# select lipids
for key_mol in lipids_dict:
    logger.info(f"Calculating number of '{key_mol}' lipids")
    selection = ""
    if key_mol in sim["COMPOSITION"].keys():
        m_file = sim["COMPOSITION"][key_mol]["MAPPING"]
        mapping_dict = {}
        with open(os.path.join(os.getcwd(), "mapping_files", m_file), "r") as yaml_file:
            mapping_dict = yaml.load(yaml_file, Loader=yaml.FullLoader)
        yaml_file.close()
        for key in mapping_dict.keys():
            if "RESIDUE" in mapping_dict[key].keys():
                selection = (
                    selection
                    + "(resname "
                    + mapping_dict[key]["RESIDUE"]
                    + " and name "
                    + mapping_dict[key]["ATOMNAME"]
                    + ") or "
                )
            else:
                selection = "resname " + sim["COMPOSITION"][key_mol]["NAME"]
                break
    selection = selection.rstrip(" or ")
    molecules = u0.select_atoms(selection)
    if molecules.n_residues > 0:
        lipids.append(u0.select_atoms(selection))

# join all the selected the lipids together to make a selection of the entire membrane and calculate the
# z component of the centre of mass of the membrane
membrane = u0.select_atoms("")
R_membrane_z = 0
if lipids != []:
    for i in range(0, len(lipids)):
        membrane = membrane + lipids[i]
    R_membrane_z = membrane.center_of_mass()[2]
logger.info(f"Center of the mass of the membrane: {str(R_membrane_z)}")

#####number of each lipid per leaflet

for key_mol in lipids_dict:
    leaflet1 = 0
    leaflet2 = 0

    selection = ""
    if key_mol in sim["COMPOSITION"].keys():
        m_file = sim["COMPOSITION"][key_mol]["MAPPING"]
        with open(os.path.join(os.getcwd(), "mapping_files", m_file), "r") as yaml_file:
            mapping_dict = yaml.load(yaml_file, Loader=yaml.FullLoader)
        yaml_file.close()
        for key in mapping_dict.keys():
            if "RESIDUE" in sim["COMPOSITION"].keys():
                selection = (
                    selection
                    + "resname "
                    + mapping_dict[key]["RESIDUE"]
                    + " and name "
                    + mapping_dict[key]["ATOMNAME"]
                    + " or "
                )
                break
                #print(selection)
            else:
                selection = "resname " + sim["COMPOSITION"][key_mol]["NAME"]
                break
    selection = selection.rstrip(" or ")
    logger.info(selection)
    molecules = u0.select_atoms(selection)
    print(molecules)
    logger.info(molecules.residues)

    # print(molecules.residues)
    if molecules.n_residues > 0:
        for mol in molecules.residues:
            R = mol.atoms.center_of_mass()

            if R[2] - R_membrane_z > 0:
                leaflet1 = leaflet1 + 1
            elif R[2] - R_membrane_z < 0:
                leaflet2 = leaflet2 + 1

    try:
        sim["COMPOSITION"][key_mol]["COUNT"] = [leaflet1, leaflet2]
    except KeyError:
        continue
    else:
        logger.info(f"Number of '{key_mol}' in upper leaflet: {str(leaflet1)}")
        logger.info(f"Number of '{key_mol}' in lower leaflet: {str(leaflet2)}")

###########################################################################################
# numbers of other molecules
for key_mol in molecules_dict:
    try:
        mol_name = sim["COMPOSITION"][key_mol]["NAME"]
    except KeyError:
        continue
    else:
        mol_number = u0.select_atoms("resname " + mol_name).n_residues
        sim["COMPOSITION"][key_mol]["COUNT"] = mol_number
        logger.info(
            f"Number of '{key_mol}': {str(sim['COMPOSITION'][key_mol]['COUNT'])}"
        )

# Anne: Read trajectory size and length

sim["TRAJECTORY_SIZE"] = os.path.getsize(traj)

dt = 0
nsteps = 0
nstxout = 0

Nframes = len(u.trajectory)
timestep = u.trajectory.dt

logger.info(f"Number of frames: {Nframes}")
logger.info(f"Timestep: {timestep}")

trj_length = Nframes * timestep

sim["TRJLENGTH"] = trj_length

# Read temperature from tpr
if sim["SOFTWARE"] == "gromacs":
    file1 = os.path.join(dir_tmp, "tpr.txt")

    logger.info("Exporting information with gmx dump")
    if ( "WARNINGS" in sim
         and sim["WARNINGS"] is not None
         and "GROMACS_VERSION" in sim["WARNINGS"]
         and sim["WARNINGS"]["GROMACS_VERSION"] == "gromacs3" ):
        os.system("echo System | gmxdump -s " + top + " > " + file1)
        TemperatureKey = "ref_t"
    else:
        os.system("echo System | gmx dump -s " + top + " > " + file1)
        TemperatureKey = "ref-t"

    with open(file1, "rt") as tpr_info:
        for line in tpr_info:
            if TemperatureKey in line:
                sim["TEMPERATURE"] = float(line.split()[1])

logger.info("Parameters read from input files:")
logger.info(f"TEMPERATURE: {str(sim['TEMPERATURE'])}")
logger.info(f"LENGTH OF THE TRAJECTORY: {str(sim['TRJLENGTH'])}")


## Check that the number of atoms between data and README.yaml match

number_of_atomsTRJ = len(u.atoms)

number_of_atoms = 0
for key_mol in all_molecules:
    mapping_dict = {}
    try:
        mapping_file = os.path.join(
            os.getcwd(), "mapping_files", sim["COMPOSITION"][key_mol]["MAPPING"]
        )
    except:
        continue
    else:
        with open(mapping_file, "r") as yaml_file:
            mapping_dict = yaml.load(yaml_file, Loader=yaml.FullLoader)
        yaml_file.close()

    if sim.get("UNITEDATOM_DICT") and not "SOL" in key_mol:
        mapping_file_length = 0

        for key in mapping_dict.keys():
            if "H" in key:
                continue
            else:
                mapping_file_length += 1

    else:
        mapping_file_length = len(mapping_dict.keys())

    try:
        number_of_atoms += (
            np.sum(sim["COMPOSITION"][key_mol]["COUNT"]) * mapping_file_length
        )
    except:
        continue


if number_of_atoms != number_of_atomsTRJ:
    stop = input(
        f"Number of atoms in trajectory {number_of_atomsTRJ} and README.yaml {number_of_atoms} do no match. Check the mapping files and molecule names. {os.linesep} If you know what you are doing, you can still continue the running the script. Do you want to (y/n)?"
    )
    if stop == "n":
        os._exit("Interrupted because atomnumbers did not match")
    if stop == "y":
        logger.warning(
            "Progressed even thought that atom numbers did not match. CHECK RESULTS MANUALLY!"
        )

sim["NUMBER_OF_ATOMS"] = number_of_atomsTRJ
logger.info(f"Number of atoms in the system: {str(sim['NUMBER_OF_ATOMS'])}")


#####DATE OF RUNNING#####
today = date.today().strftime("%d/%m/%Y")
# print(today)
sim["DATEOFRUNNING"] = today

logger.info(f"Date of adding to the databank: {sim['DATEOFRUNNING']}")

# Type of system is currently hard coded because only lipid bilayers are currently added.
# When we go for other systems, this will be given by user.
if not "TYPEOFSYSTEM" in list(sim.keys()):
    sim["TYPEOFSYSTEM"] = "lipid bilayer"

# # Save to databank

try:
    directory_path = create_databank_directories(sim, sim_hashes, args.output_dir)
except NotImplementedError as e:
    logger.error(e)
    quit()
except OSError as e:
    logger.error(f"couldn't create output directory: {e.args[1]}")
    quit()

logger.info(f"saving results to '{directory_path}'")

# copy previously downloaded files
logger.info("copying previously downloaded files ...")
shutil.copyfile(traj, os.path.join(directory_path, os.path.basename(traj)))
shutil.copyfile(top, os.path.join(directory_path, os.path.basename(top)))

# dictionary saved in yaml format
outfileDICT = os.path.join(dir_tmp, "README.yaml")

with open(outfileDICT, "w") as f:
    yaml.dump(sim, f, sort_keys=False, allow_unicode=True)
    shutil.copyfile(
        os.path.join(dir_tmp, "README.yaml"),
        os.path.join(directory_path, "README.yaml"),
    )

logger.info("Script completed successfully!")