def main(argv=None):
print(f"Running GaussianWrangler script plot_steps version {__version__}")
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
# Make a list of lists from the input file list
with open(args.list) as f:
row_list = [row.strip().split() for row in f.readlines()]
row_list = list(filter(None, row_list))
if args.output_fname:
plot_fname = create_out_fname(args.output_fname,
base_dir=args.out_dir,
ext='.png')
else:
plot_fname = create_out_fname(args.list,
base_dir=args.out_dir,
ext='.png')
plot_delta_g(plot_fname, args.temp, row_list, args.conv,
args.fig_width, args.fig_height, args.y_axis_label)
print("Wrote file: {}".format(plot_fname))
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("Problems reading data:", e)
return INVALID_DATA
return GOOD_RET # success
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
:param argv: is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser()
# parser.add_argument("-i", "--input_rates", help="The location of the input rates file",
# default=DEF_IRATE_FILE, type=read_input_rates)
parser.add_argument("-n", "--no_attribution", help="Whether to include attribution",
action='store_false')
args = None
try:
args = parser.parse_args(argv)
except SystemExit as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def check_input(args, cfg):
# override config entries if command-line options used
if args.file:
cfg[GAUSSLOG_FILE] = args.file
if args.list:
cfg[GAUSSLOG_FILES_FILE] = args.list
if args.tpl:
cfg[PDB_TPL_FILE] = args.tpl
if args.out_dir:
cfg[OUT_BASE_DIR] = args.out_dir
if args.only_first:
cfg[ONLY_FIRST] = True
if args.only_final:
cfg[ONLY_FINAL] = True
if args.out_fname:
cfg[OUTFILE_NAME] = args.out_fname
if args.out_dir:
cfg[OUT_BASE_DIR] = args.out_dir
# checking
if cfg[COMBINE_LOGS] and not cfg[OUTFILE_NAME]:
raise InvalidDataError("When combining outputs from multiple log files into one pdb, specify the output "
"file name")
if cfg[COMBINE_LOGS] and not cfg[ONLY_FINAL]:
warning("When combining outputs from multiple log files into one pdb, only the last coordinates of each "
"log file will be kept.")
cfg[ONLY_FINAL] = True
if cfg[OUT_BASE_DIR]:
if not os.path.exists(cfg[OUT_BASE_DIR]):
os.makedirs(cfg[OUT_BASE_DIR])
def main(argv=None):
print(
f"Running GaussianWrangler script gausslog2com version {__version__}")
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
# Make sure there are files to process
gausslog_files = check_for_files(args.file, args.list)
# and a template file to process
if not args.tpl:
raise InvalidDataError("No template file ('-t' option) specified")
if not os.path.isfile(args.tpl):
raise IOError(args.tpl)
# Read template and data files
com_tpl_content = process_gausscom_tpl(args.tpl, args.charge_from_tpl)
process_gausslog_files(gausslog_files, com_tpl_content,
args.charge_from_tpl, args.low_energy,
args.step_num, args.out_dir, args.output_fname)
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except (InvalidDataError, UnicodeDecodeError) as e:
warning("Problems reading data:", e)
return INVALID_DATA
return GOOD_RET # success
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(description='Creates pdb files from Gaussian input files, given a template pdb '
'file.')
parser.add_argument("-c", "--config", help="The location of the (optional) configuration file in ini format. The "
"default file name is {}, located in the base directory where the "
"program as run. The program will run using either the specifications "
"from the configuration file or from the command line. Command line "
"specifications will override those in the configuration "
"file.".format(DEF_CFG_FILE),
default=DEF_CFG_FILE, type=read_cfg)
parser.add_argument("-d", "--out_dir", help="The directory where the output files will be placed. This will "
"override any '{}' entry in the configuration file. The default is "
"the same directory as the log file.".format(OUT_BASE_DIR),
default=None)
parser.add_argument("-f", "--file", help="The location of a Gaussian output file. Will override any '{}' entry in "
"the configuration file.".format(GAUSSLOG_FILE), default=None)
parser.add_argument("-l", "--list", help="The location of the list of Gaussian output files. Will override any "
"'{}' entry in a configuration file.".format(GAUSSLOG_FILES_FILE),
default=None)
parser.add_argument("-o", "--out_fname", help="The name for the created pdb file. If none is provided, it will "
"take the basename from the provided Gaussian output file name, "
"with the '.pdb' extension.",
default=None)
parser.add_argument("-t", "--tpl", help="The location of the pdb template file. Will override any '{}'entry in the "
"config file.".format(PDB_TPL_FILE),
default=None)
parser.add_argument("-a", "--only_first", help="Flag to have the program output a pdb only from the first "
"set of coordinates in the log file. Will override any '{}' entry "
"in the config file. The default is False.".format(ONLY_FIRST),
action="store_true", default=False)
parser.add_argument("-z", "--only_final", help="Flag to have the program output a pdb only from the last "
"set of coordinates in the log file. Will override any '{}' entry "
"in the config file. The default is False.".format(ONLY_FINAL),
action="store_true", default=False)
args = None
try:
args = parser.parse_args(argv)
except (KeyError, InvalidDataError, MissingSectionHeaderError, SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def process_input_file(input_fname, mw_formula_dict, mw_deprot_formula_dict,
mw_prot_formula_dict, form_smi_dict, form_dbe_dict,
smi_name_dict, smi_source_dict):
"""
Read the file and uses the data to update dictionaries
:return: the number of entries that were added to the dictionaries
"""
rel_path_name = os.path.relpath(input_fname)
new_entries = 0
with open(input_fname) as f:
for line in f:
stripped_line = line.strip()
if len(stripped_line) == 0:
continue
line_list = [
entry.strip() for entry in stripped_line.split(SEP_KEY)
]
# if there is no SMILES str, there is no way to properly add any data to the library
if not line_list[0]:
warning(
f"In reading file: {rel_path_name}\n Line: '{stripped_line}'\n does not "
f"provide a SMILES string as the first '|'-separated entry. This line will be skipped."
)
continue
# if there aren't 3 entries, pad with blank strings, as 2nd two are optional
while len(line_list) < 3:
line_list.append("")
if len(line_list) > 3:
rel_path = os.path.relpath(input_fname)
raise InvalidDataError(
f"Error while reading: {rel_path}\n line: '{stripped_line}'\n"
f" Expected no more than 3 comma-separated values: \n SMILES "
f"string (only one per line),\n molecule name(s) (separate "
f"multiple names with semicolons),\n string description of the "
f"data source (with no commas or semicolons)")
# being explicit in separating out line_list entries; do not change global variables
new_entry_flag = add_smi_to_dicts(mw_formula_dict,
mw_deprot_formula_dict,
mw_prot_formula_dict,
form_smi_dict,
form_dbe_dict,
smi_name_dict,
smi_source_dict,
line_list[0],
mol_name=line_list[1],
mol_source=line_list[2])
if new_entry_flag:
new_entries += 1
print(
f"Completed reading file: {rel_path_name}\n Added {new_entries} entries to the dictionaries\n"
)
return new_entries
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(description="Creates Gaussian input files from Gaussian other files, given a "
"template input file. The default output name is the same as the "
"base name of the file with coordinates to use, with the '.com' "
"extension.")
parser.add_argument("-c", "--charge_read_com", help="Flag to take the charge and multiplicity from the input file "
"to be read rather than from the template file. "
"The default is {}.".format(False),
action="store_true", default=False)
parser.add_argument("-f", "--com_file", help="The location of the Gaussian input file with coordinates to be "
"input into the template file to create a new input file.",
default=None)
parser.add_argument("-l", "--list_file", help="The location of a text file with a list of Gaussian input files "
"with coordinates to be input into the template file to create new "
"input files. Each file name should be on a separate line.",
default=None)
parser.add_argument("-o", "--out_dir", help="A directory where output files should be saved. The default location "
"is the current directory.", default=None)
parser.add_argument("-t", "--tpl_file", help="The location of the Gaussian input file template (required). "
"The default file name is {}, located in the "
"base directory where the program as run.", default=None)
args = None
try:
args = parser.parse_args(argv)
if args.tpl_file is None:
raise IOError("A template file (specified with '-t') must be provided.")
if args.com_file is None and args.list_file is None:
raise IOError("No files have been specified to be read. Use '-f' to specify a single file, or '-l' to "
"specify a file with a list of input files to be read and converted using the specified "
"template file.")
except IOError as e:
warning("Problems reading file:", e)
parser.print_help()
return args, IO_ERROR
except (KeyError, InvalidDataError, MissingSectionHeaderError, SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def main(argv=None):
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
# start with copies of global variable dicts; then only the copies will be altered
if args.file_name:
mw_formula_dict = MW_FORM_DICT.copy()
mw_deprot_formula_dict = MW_DEPROT_FORM_DICT.copy()
mw_prot_formula_dict = MW_PROT_FORM_DICT.copy()
form_smi_dict = deepcopy(FORMULA_SMI_DICT)
form_dbe_dict = FORMULA_DBE_DICT.copy()
smi_name_dict = deepcopy(SMI_NAME_DICT)
smi_source_dict = deepcopy(SMI_SOURCE_DICT)
number_additions = process_input_file(
args.file_name, mw_formula_dict, mw_deprot_formula_dict,
mw_prot_formula_dict, form_smi_dict, form_dbe_dict,
smi_name_dict, smi_source_dict)
# Reading complete, now output
if number_additions:
pretty_print_dicts(mw_formula_dict, mw_deprot_formula_dict,
mw_prot_formula_dict, form_smi_dict,
form_dbe_dict, smi_name_dict,
smi_source_dict)
if args.image_library:
if args.mw_list:
mw_keys = [x.strip() for x in args.mw_list.split(",")]
else:
mw_keys = MW_FORM_DICT.keys()
if args.out_dir:
make_dir(args.out_dir)
image_grid_mult_mw(mw_keys,
MW_FORM_DICT,
FORMULA_SMI_DICT,
out_dir=args.out_dir)
except IOError as e:
warning(e)
return IO_ERROR
except InvalidDataError as e:
warning(e)
return INVALID_DATA
return GOOD_RET # success
def main(argv=None):
"""
Runs the main program.
:param argv: The command line arguments.
:return: The return code for the program's termination.
"""
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
print(canvas(args.no_attribution))
except InvalidDataError as e:
warning("Problems reading data:", e)
return INVALID_DATA
return GOOD_RET # success
def main(argv=None):
print(f"Running GaussianWrangler script check_gauss version {__version__}")
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
# Find files to process, then process them
check_sub_dirs = False
search_dir = None
if args.dir_subdirs:
search_dir = args.dir_subdirs
check_sub_dirs = True
elif args.directory:
search_dir = args.directory
check_file_list = check_for_files(args.file_name,
args.file_list,
search_pattern=args.extension,
search_dir=search_dir,
search_sub_dir=check_sub_dirs)
# now check either for convergence or termination
if args.step_converg or args.final_converg:
check_convergence(check_file_list, args.step_converg, args.to_step,
args.best, args.all)
else:
# If output directory does not exist, make it:
if not os.path.exists(args.output_directory):
os.makedirs(args.output_directory)
if args.scan:
scan_array = collect_output_scan_steps(check_file_list)
x_fit, y_fit = plot_scan(scan_array, args.scan)
find_stable_points(x_fit, y_fit)
else:
check_termination(args, check_file_list)
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("", e)
return INVALID_DATA
return GOOD_RET # success
def main(argv=None):
print(f"Running GaussianWrangler script gausslog2pdb version {__version__}")
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
cfg = args.config
# Read template and data files
try:
check_input(args, cfg)
# set up list of files to process
cfg[GAUSSLOG_FILES] = []
if os.path.isfile(cfg[GAUSSLOG_FILES_FILE]):
with open(cfg[GAUSSLOG_FILES_FILE]) as f:
for data_file in f:
cfg[GAUSSLOG_FILES].append(data_file.strip())
if cfg[GAUSSLOG_FILE] is not None:
cfg[GAUSSLOG_FILES].append(cfg[GAUSSLOG_FILE])
if len(cfg[GAUSSLOG_FILES]) == 0:
raise InvalidDataError("No files to process: no '{}' specified and "
"no list of files found for: {}".format(GAUSSLOG_FILE, cfg[GAUSSLOG_FILES_FILE]))
if cfg[ONLY_FIRST] and cfg[ONLY_FINAL]:
raise InvalidDataError("Cannot specify both '{}' and '{}'".format(ONLY_FIRST, ONLY_FINAL))
# now start the actual work
if cfg[PDB_TPL_FILE]:
pdb_tpl_content = process_pdb_file(cfg[PDB_TPL_FILE])
else:
pdb_tpl_content = {}
process_gausscom_files(cfg, pdb_tpl_content)
except (IOError, UnicodeDecodeError) as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("Problems reading data:", e)
return INVALID_DATA
return GOOD_RET # success
def check_file_termination(output_file, good_output_dir, completed_list,
likely_failed_list, perhaps_running_list):
try:
with open(output_file, 'r') as fh:
last_line = fh.readlines()[-1].strip()
except IndexError:
warning(
"Could not read the last line (may be blank) of file: {}".format(
output_file))
return
if NORM_TERM_PAT.match(last_line):
base_name = os.path.basename(output_file)
completed_list.append(output_file)
os.rename(output_file, os.path.join(good_output_dir, base_name))
return
for pattern in FAIL_PAT_LIST:
if pattern.match(last_line):
likely_failed_list.append(output_file)
return
perhaps_running_list.append(output_file)
def check_input_csv_header(fname):
"""
Checks first line of specified for expected header
:param fname: str, the location of the file to check the header
:return: num_header_lines, int: 1 by default; 0 if it appears that the header is missing
"""
num_header_lines = 1
potential_header = read_csv_header(fname)
base_fname = os.path.relpath(fname)
if potential_header is None:
raise InvalidDataError(f"Input file may be blank: {base_fname}")
while potential_header[0].startswith("#"):
with open(fname) as f:
for row in f:
if row.startswith("#"):
num_header_lines += 1
else:
potential_header = row.strip().split(",")
potential_header = [dequote(x) for x in potential_header]
break
if potential_header != TYPICAL_CSV_HEADER and potential_header != CSV_RET_HEADER:
try:
# Still move on to reading values, but first check if there may not be a header
if len(potential_header) > 1:
# if right into values (that is, no trouble converting to float), continue to reading values
float(potential_header[0])
float(potential_header[1])
num_header_lines = 0
warning(f"No header found in file: {base_fname}\n Will attempt to read data as M/Z and intensity.")
else:
raise ValueError
except ValueError:
# check that the difference is not a trivial difference in case
if (len(potential_header) in [2, 3]) and (potential_header[0].lower() == TYPICAL_CSV_HEADER[0].lower()) \
and (potential_header[1].lower() == TYPICAL_CSV_HEADER[1].lower()):
pass
else:
warning(f"While reading file: {base_fname}\n Did not find the expected headers "
f"'{TYPICAL_CSV_HEADER}', but '{potential_header}'\n Will attempt to read data as M/Z, "
f"intensity, and, if there is a third column, retention time (in min).")
return num_header_lines
def main(argv=None):
print(
f"Running GaussianWrangler script test_data.smi2gausscom version {__version__}"
)
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
try:
process_smiles(args.gau_tpl_file, args.list_file, args.max_confs,
args.out_dir)
except (IOError, UnicodeDecodeError) as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("Problems reading data template:", e)
return INVALID_DATA
return GOOD_RET # success
def initiate_state(add_rate, cfg, rep, sg_ratio):
pct_s = sg_ratio / (1 + sg_ratio)
ini_num_monos = cfg[INI_MONOS]
if cfg[RANDOM_SEED]:
# we don't want the same random seed for every iteration
np.random.seed(cfg[RANDOM_SEED] + int(add_rate / 100 + sg_ratio * 10) + rep)
monomer_draw = np.around(np.random.rand(ini_num_monos), MAX_NUM_DECIMAL)
else:
monomer_draw = np.random.rand(ini_num_monos)
initial_monomers = create_initial_monomers(pct_s, monomer_draw)
# initial event must be oxidation to create reactive species; all monomers may be oxidized
initial_events = create_initial_events(initial_monomers, cfg[RXN_RATES])
# initial_monomers and initial_events are grouped into the initial state
initial_state = create_initial_state(initial_events, initial_monomers)
if cfg[MAX_MONOS] > cfg[INI_MONOS]:
initial_events.append(Event(GROW, [], rate=add_rate))
elif cfg[MAX_MONOS] < cfg[INI_MONOS]:
warning(f"The specified maximum number of monomers ({cfg[MAX_MONOS]}) is less than the "
f"specified initial number of monomers ({cfg[INI_MONOS]}). \n The program will "
f"proceed with the with the initial number of monomers with no addition of monomers.")
return initial_events, initial_state
def main(argv=None):
print(f"Running GaussianWrangler script gausscom2com version {__version__}")
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
# Read template and data files
try:
# Make sure there are files to process
gausscom_files = check_for_files(args.com_file, args.list_file)
com_tpl_content = process_gausscom_tpl(args.tpl_file, not args.charge_read_com)
for gausscom_file in gausscom_files:
process_gausscom_file(gausscom_file, com_tpl_content, args.charge_read_com, args.out_dir)
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("", e)
return INVALID_DATA
return GOOD_RET # success
def process_smiles(gau_tpl_fname, smi_list, max_num_confs, out_dir):
"""
Creates Gaussian input files for each SMILES string provided
https://www.rdkit.org/docs/GettingStartedInPython.html
:param smi_list: list of SMILES strings
:param gau_tpl_fname: str, the location of the template file to use to create input files
:param max_num_confs: int, the maximum number of conformations to generate
:param out_dir: str, directory where files are to be saved (if None, saves to working directory)
:return: N/A, writes files and prints notes on files created
"""
gau_tpl_str = read_tpl(gau_tpl_fname)
if REQ_STR not in gau_tpl_str:
raise InvalidDataError(
f"Did not find the required string '{REQ_STR}' in the provided Gaussian input "
f"template file.")
for smi in smi_list:
mol = Chem.MolFromSmiles(smi)
if mol is None:
warning(f"Skipping SMILES input string '{smi}' due to error\n")
continue
Chem.Kekulize(mol)
mol = AddHs(mol)
confs = gen_conformers(mol, num_confs=max_num_confs)
mol_name = get_mol_name(smi)
base_fname = create_out_fname(mol_name,
ext='com',
base_dir=out_dir,
rel_path=True)
conf_id = -1 # make IDE happy
for conf_id in confs:
com_fname = create_out_fname(base_fname, suffix=f'_{conf_id}')
pdb_str = MolToPDBBlock(mol, confId=conf_id)
coord_list = get_pdb_coord_list(pdb_str)
fill_save_tpl(gau_tpl_str, {ATOMS: "\n".join(coord_list)},
gau_tpl_fname,
com_fname,
print_info=False)
print(f"Wrote {conf_id + 1} files with base name '{base_fname}'")
def main(argv=None):
print(
f"Running GaussianWrangler script pdbs2gausscoms version {__version__}"
)
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
# Read pdb files
cfg = args.config
try:
gau_tpl_content = process_gausscom_file(cfg[GAU_TPL_FILE])
process_pdb_files(cfg, gau_tpl_content)
except (IOError, UnicodeDecodeError) as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("Problems reading data template:", e)
return INVALID_DATA
return GOOD_RET # success
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(
description=
'Creates pdb files from Gaussian input files, given a template pdb '
'file.')
parser.add_argument(
"-c",
"--config",
help="The location of the configuration file in ini format. "
"The default file name is {}, located in the "
"base directory where the program as run.".format(DEF_CFG_FILE),
default=DEF_CFG_FILE,
type=read_cfg)
args = None
try:
args = parser.parse_args(argv)
except IOError as e:
warning("Problems reading file:", e)
parser.print_help()
return args, IO_ERROR
except (KeyError, InvalidDataError, MissingSectionHeaderError,
SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def main(argv=None):
print(
f"Running GaussianWrangler script gausscom2pdb version {__version__}")
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
cfg = args.config
# Read template and data files
try:
if cfg[PDB_TPL_FILE]:
pdb_tpl_content = process_pdb_file(cfg[PDB_TPL_FILE])
else:
pdb_tpl_content = {}
process_gausscom_files(cfg, pdb_tpl_content)
except (IOError, UnicodeDecodeError) as e:
warning("Problems reading file:", e)
return IO_ERROR
except InvalidDataError as e:
warning("Problems reading data:", e)
return INVALID_DATA
return GOOD_RET # success
def main(argv=None):
print(f"Running GaussianWrangler script run_gauss version {__version__}")
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
cfg = args.config
try:
# overwrite default values from reading config if they were specified in command line
args_key_map = [(args.list_of_jobs, False, LIST_OF_JOBS),
(args.old_chk_fname, None, FIRST_JOB_CHK),
(args.setup_submit, False, SETUP_SUBMIT)]
for arg_val, arg_default, cfg_key in args_key_map:
if arg_val != arg_default:
cfg[cfg_key] = arg_val
# The following do not have default config options, so overwrite
cfg[NO_SUBMIT] = args.no_submit
if cfg[FIRST_JOB_CHK]:
# remove extension (if any) from cfg[FIRST_JOB_CHK]
cfg[FIRST_JOB_CHK] = os.path.splitext(cfg[FIRST_JOB_CHK])[0]
# for the "list_of_jobs" option, "job_name" is actually the name of the name of file with the list of jobs
if args.list_of_jobs:
with open(args.job_name) as f:
for line in f:
s_line = line.strip()
if len(s_line) == 0:
continue
input_job_file = os.path.splitext(
s_line)[0] + cfg[GAUSS_IN_EXT]
base_name = get_fname_root(s_line)
tpl_dict = {
JOB_NAME: base_name,
INPUT_FILE: input_job_file
}
for thread_index, thread in enumerate(cfg[JOB_LIST]):
setup_and_submit(cfg, thread, tpl_dict, args.testing,
args.ignore_chk_warning)
return GOOD_RET
# otherwise, job_name is actually the job name. We can to ignore any extension on it
job_name_perhaps_with_dir = os.path.splitext(args.job_name)[0]
job_name = os.path.basename(job_name_perhaps_with_dir)
tpl_dict = {
JOB_NAME: job_name,
INPUT_FILE: job_name_perhaps_with_dir + cfg[GAUSS_IN_EXT]
}
if cfg[JOB_LIST][0] == '' and not os.path.isfile(tpl_dict[INPUT_FILE]):
raise IOError("Could not find input file: {}".format(
tpl_dict[INPUT_FILE]))
if args.setup_submit:
for thread_index, thread in enumerate(cfg[JOB_LIST]):
setup_and_submit(cfg, thread, tpl_dict, args.testing,
args.ignore_chk_warning)
return GOOD_RET
for job in cfg[JOB_LIST]:
run_job(job, job_name_perhaps_with_dir, tpl_dict, cfg,
args.testing)
if len(cfg[FOLLOW_JOBS_LIST]) > 1:
for thread_index, thread in enumerate(cfg[FOLLOW_JOBS_LIST]):
if thread_index == 0 and not cfg[ALL_NEW]:
continue
setup_and_submit(cfg, thread, tpl_dict, args.testing,
args.ignore_chk_warning)
if len(cfg[FOLLOW_JOBS_LIST]) > 0 and not cfg[ALL_NEW]:
for job in cfg[FOLLOW_JOBS_LIST][0]:
run_job(job, job_name_perhaps_with_dir, tpl_dict, cfg,
args.testing)
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except (subprocess.CalledProcessError, KeyError) as e:
warning("", e)
except InvalidInputError as e:
warning("Check input:", e)
return INVALID_DATA
except InvalidDataError as e:
warning("Invalid data:", e)
return INVALID_DATA
return GOOD_RET # success
def main(argv=None):
print(
f"Running GaussianWrangler script gausslog_unique version {__version__}"
)
# Read input
args, ret = parse_cmdline(argv)
if ret != GOOD_RET or args is None:
return ret
# Read template and data files
try:
gausslog_files = []
missing_files = []
log_info = {}
# check input
if args.max_diff:
args.max_diff = float(args.max_diff)
if not args.energy and not args.gibbs:
args.enthalpy = True
# check that we have files
with open(args.list) as f:
for line in f:
fname = line.strip()
if len(fname) == 0:
continue
# check that each log file can be found
if os.path.isfile(fname):
gausslog_files.append(fname)
else:
missing_files.append(fname)
if len(missing_files) > 0:
raise IOError(
"Could not find the following file(s) listed in '{}':\n "
"{}".format(args.list,
'\n '.join(sorted(set(missing_files)))))
if len(gausslog_files) < 2:
raise InvalidDataError(
"This program expects at least two files to compare to determine if they "
"have the same conformation. Check input.")
# get the data from the files
for gausslog_file in gausslog_files:
gausslog_content = process_gausslog_file(gausslog_file,
find_dih=True,
find_converg=True)
log_info[os.path.basename(gausslog_file)] = gausslog_content
# process data from files
list_of_conf_lists = compare_gausslog_info(log_info, args.tol)
winner_str, warn_files_str = print_results(log_info,
list_of_conf_lists,
args.enthalpy, args.energy,
args.max_diff,
args.out_fname)
if len(warn_files_str) > 0:
warning("Check convergence of file(s):" + warn_files_str)
except IOError as e:
warning("Problems reading file:", e)
return IO_ERROR
except (InvalidDataError, UnicodeDecodeError) as e:
warning("Problems reading data:", e)
return INVALID_DATA
except ValueError as e:
warning(e.args[0])
return INVALID_DATA
return GOOD_RET # success
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(
description=
"This script has two modes, chosen by selected '-f' or '-i': "
"1) The '-f' option: reads a file to add entries to "
"dictionaries of lignin decomposition molecules that may be "
"observed in mass spectrometry of lignin-derived compounds. Given "
"SMILES strings, and optionally/ideally molecular names and/or source "
"of the SMILES (e.g. observed in analysis of model compounds), the "
"dictionaries are expanded to include additional potentially "
"observed molecular weights and isomers. Note: it does not change "
"the original libraries within this package, but instead outputs "
"new libraries, which could be used to update the library in this "
"package. 2) The '-i' option: creates an image library of all "
"SMILES structures currently in the compound library (further details "
"provided under the '-i' option description).")
parser.add_argument(
"-d",
"--out_dir",
help=
"A directory where output files should be saved. The default location "
"is the current working directory.",
default=None)
parser.add_argument(
"-f",
"--file_name",
help=f"File name of values separated by '{SEP_KEY}' (to avoid conflicts "
f"with IUPAC molecule names) with up to 3 values per line: SMILES "
f"string (required), molecule name(s) (optional; split multiple "
f"names with a semicolon), source (e.g. model compound analysis)",
default=None)
parser.add_argument(
"-i",
"--image_library",
help=f"Flag to request that the program create a 2D image library of "
f"the SMILES strings in the library. One file will be created "
f"per exact molecular weight (calculated only from the most "
f"abundant isotope). If there are multiple SMILES matches for a "
f"molecular formula, the name of the file is '{{molecular "
f"weight (with a '-' instead of a '.')}}_{{molecular formula}}"
f".png', and the images of each structure within the file will "
f"be labeled with its SMILES string. If there is only one "
f"structure in the library for a molecular formula, the SMILES "
f"string will be appended to the name. These files will be "
f"saved in the current directory, unless a different directory "
f"is specified with the '-o' option.",
action='store_true')
parser.add_argument(
"-m",
"--mw_list",
help="A list of molecular weight keys for making an image library.",
default=None)
args = None
try:
args = parser.parse_args(argv)
if not args.image_library and not args.file_name:
raise InvalidDataError(
"Please choose to either provide a file_name ('-f') to read new dictionary "
"entries, or the image_library flag ('-i') to request 2D image library."
)
except (KeyError, InvalidDataError, IOError, SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def add_smi_to_dicts(mw_formula_dict,
mw_deprot_formula_dict,
mw_prot_formula_dict,
form_smi_dict,
form_dbe_dict,
smi_name_dict,
smi_source_dict,
entered_smi,
mol_name=None,
mol_source=None):
"""
Given a SMILES string, and optionally a name and/or source, update the designated formulas
:param mw_formula_dict: dict of strs, eg. {'77.03913': 'C6H6', ...},
(keys=MW as str with 5 decimal places, values=molecular formulas (str))
:param mw_deprot_formula_dict: dict of strs, eg. {'78.04695': 'C6H6', ...}, (MW's have H mass subtracted)
(keys=MW as str with 5 decimal places, values=molecular formulas (str))
:param mw_prot_formula_dict: dict of strs, eg. {'78.04695': 'C6H6', ...}, (MW's have H mass added)
(keys=MW as str with 5 decimal places, values=molecular formulas (str))
:param form_smi_dict: dict of sets, e.g. {'C6H6': {'C1=CC=CC=C1'}, ...}
(keys=molecular formulas (str), values=set of corresponding SMILES strings)
:param form_dbe_dict: dict of floats, e.g. {'C6H6': 4, ...}
(keys=molecular formulas (str), values=double bond equivalents (float))
:param smi_name_dict: dict of sets, e.g. {'C1=COCCC1': {'dihydropyran', '3,4-dihydro-2h-pyran'}, ...}
(keys=molecular formulas (str), values=set names including IUPAC and common names)
:param smi_source_dict: dict of sets, e.g. {'C6H6': {'common_molecule'}, ...}
(keys=molecular formulas (str), values=set of corresponding SMILES strings)
:param entered_smi: str, the user-inputted SMILES string
:param mol_name: str, optional, a molecule name for the string
:param mol_source: str, optional, a note on the source of the molecule (e.g. if from model compound study)
:return: boolean if updated dictionary, and updates dictionaries
"""
# this will track addition to any dictionary--not going granular; can do so if later wished
addition_to_dict = False
new_smi, formula, mw, mw_deprot, mw_prot, dbe = smi_to_formula(entered_smi)
if formula in form_smi_dict and new_smi != '':
# since a set, if already there, adding would not change, but nice to track if anything changes
if new_smi not in form_smi_dict[formula]:
addition_to_dict = True
form_smi_dict[formula].add(new_smi)
else:
form_smi_dict[formula] = {new_smi}
form_dbe_dict[formula] = dbe
addition_to_dict = True
mw_dict_names = [
"molecular ion MW dictionary", "deprotonated MW dictionary",
"protonated MW dictionary"
]
mw_dicts = [mw_formula_dict, mw_deprot_formula_dict, mw_prot_formula_dict]
mw_inputs = [str(mw), str(mw_deprot), str(mw_prot)]
for dict_name, mw_dict, new_mw in zip(mw_dict_names, mw_dicts, mw_inputs):
if new_mw in mw_dict.keys():
if mw_dict[new_mw] != formula:
# hopefully never encountered
warning(
f"Unexpectedly, the MW {new_mw} was already in the {dict_name} pared with molecular "
f"formula {mw_dict[new_mw]}, while the input has formula {formula}"
)
else:
mw_dict[new_mw] = formula
addition_to_dict = True
val_dict_list = [(mol_name, smi_name_dict), (mol_source, smi_source_dict)]
for opt_val, opt_dict in val_dict_list:
if opt_val:
# user may add a list of names--unlikely multiple sources, but won't hurt it
# cannot split on comma, because that can be a part of a name. PubChem splits on ; so seems safe
opt_val_list = opt_val.split(";")
for val in opt_val_list:
stripped_val = val.strip().lower()
if stripped_val:
if new_smi in opt_dict.keys():
# as above, check is to check if we are changing any dictionaries
if stripped_val not in opt_dict[new_smi]:
addition_to_dict = True
opt_dict[new_smi].add(stripped_val)
else:
opt_dict[new_smi] = {stripped_val}
addition_to_dict = True
return addition_to_dict
def process_gausscom_file(cfg, gausscom_file, pdb_tpl_content):
with open(gausscom_file) as d:
if cfg[PDB_TPL_FILE]:
pdb_data_section = copy.deepcopy(pdb_tpl_content[SEC_ATOMS])
else:
pdb_data_section = []
section = SEC_HEAD
atom_id = 0
for line in d:
line = line.strip()
# not currently keeping anything from the header; just check num atoms
if section == SEC_HEAD:
# there may be some instructions (which start with %, and can have some blank lines) before the
# "route card lines" (which start with #)
while not GAU_HEADER_PAT.match(line):
line = next(d).strip()
# skip first line of route card
line = next(d).strip()
# for "route card" and then description, there may be more than one header line; look for blank line
for i in range(2):
while len(line) > 0:
line = next(d).strip()
# now move past the blank line, and get the content of the following line
line = next(d).strip()
# now on charge, multiplicity line, which we also skip with the "continue"
section = SEC_ATOMS
continue
elif section == SEC_ATOMS:
if len(line) == 0:
# Since the tail will come only from the template, nothing more is needed after reading atoms
break
split_line = line.split()
atom_type = split_line[0]
# if working from a template, check atom type
if cfg[PDB_TPL_FILE]:
try:
pdb_atom_type = pdb_data_section[atom_id][8].split(
' ')[-1]
except IndexError:
raise InvalidDataError(
'Gausscom file: {}\n has more atoms than the expected {} atoms in '
'the template file: {}'.format(
gausscom_file, pdb_tpl_content[NUM_ATOMS],
cfg[PDB_TPL_FILE]))
if atom_type != pdb_atom_type:
warning(
"Atom types do not match for atom number {}; pdb atom type is {} while gausscom type "
"is {}".format(atom_id, pdb_atom_type, atom_type))
else:
pdb_data_section.append(atom_id)
pdb_data_section[atom_id] = [
'HETATM', '{:5d}'.format(atom_id + 1),
' {:4} '.format(atom_type), 'UNL ', 1, 0.0, 0.0, 0.0,
' 1.00 0.00 {:>2}'.format(atom_type)
]
pdb_data_section[atom_id][5:8] = map(float, split_line[1:4])
atom_id += 1
# Now that finished reading the file, first make sure didn't exit before reaching the desired number of atoms
if cfg[PDB_TPL_FILE]:
if atom_id != pdb_tpl_content[NUM_ATOMS]:
raise InvalidDataError(
'In gausscom file: {}\n found {} atoms, while the pdb template has {} atoms'
.format(gausscom_file, atom_id, pdb_tpl_content[NUM_ATOMS]))
f_name = create_out_fname(gausscom_file,
ext='.pdb',
base_dir=cfg[OUT_BASE_DIR])
list_to_file(pdb_tpl_content[SEC_HEAD] + pdb_data_section +
pdb_tpl_content[SEC_TAIL],
f_name,
list_format=PDB_FORMAT)
def wrangler_main(args, process_file_list):
"""
Calls to other functions to perform all requested tasks
:param process_file_list:
:param args: arguments
:return: final_str: a string with all of the info that would normally be log outputs
"""
final_str = ""
write_mode = 'w'
ms2_dict = defaultdict(lambda: defaultdict(lambda: None))
dbe_dict = defaultdict(dict)
mw_dict = defaultdict(dict)
blank_data_array_dict = {}
max_mz_in_stdout = 5
if args.quit_after_mzml_to_csv:
max_unique_mz_to_collect = max_mz_in_stdout
else:
max_unique_mz_to_collect = 1e9
# blank file processing
if args.blank_file_name is not None:
fname = args.blank_file_name
fname_lower = os.path.basename(fname).lower()
blank_data_array_dict = process_blank_file(args)
for ms_level, ms_array in blank_data_array_dict.items():
array, my_str = initial_output(
fname, fname_lower, ms_array, ms_level,
max_unique_mz_to_collect, max_mz_in_stdout, args.threshold,
args.num_decimals_ms_accuracy, args.ret_time_accuracy,
args.num_decimals_ret_time_accuracy, args.out_dir,
args.quit_after_mzml_to_csv, args.direct_injection)
final_str += my_str
# all other file processing
gathered_ms2_data = False
for fname in process_file_list:
base_fname = os.path.basename(fname)
fname_lower = base_fname.lower()
data_array_dict = process_ms_run_file(args, fname,
blank_data_array_dict)
if data_array_dict is None:
continue
prot_flag = fnmatch.fnmatch(fname_lower, "*+*")
deprot_flag = fnmatch.fnmatch(fname_lower, "*-*")
for ms_level, ms_array in data_array_dict.items():
trimmed_mz_array, my_str = initial_output(
fname, fname_lower, ms_array, ms_level,
max_unique_mz_to_collect, max_mz_in_stdout, args.threshold,
args.num_decimals_ms_accuracy, args.ret_time_accuracy,
args.num_decimals_ret_time_accuracy, args.out_dir,
args.quit_after_mzml_to_csv, args.direct_injection)
final_str += my_str
if args.quit_after_mzml_to_csv or "blank" in fname_lower:
# move to next file without further analysis
continue
num_matches, matched_formulas, short_output_list, long_output_dict, high_int_peak_str_list = \
compare_mz_mw(base_fname, trimmed_mz_array, args.threshold, args.omit_mol_ion,
deprot_flag, prot_flag, args.non_dom_iso_flag, max_mz_in_stdout)
write_output(fname, ms_level, num_matches, short_output_list,
long_output_dict.values(), matched_formulas,
args.combined_output_fname, args.omit_mol_ion,
deprot_flag, prot_flag, write_mode, args.out_dir)
final_str += get_high_inten_long(ms_level, high_int_peak_str_list,
long_output_dict)
# if there is an combined_output_fname and more than one file, append the data, don't write over it
if args.combined_output_fname:
write_mode = 'a'
if "2" in ms_level and not ("blank" in fname_lower) and (
"hcd" in fname_lower):
if len(process_file_list) < 2:
warning(
f"Only one set of MS2 data has been read (from file {base_fname}).\n"
f" No chemical species matching will be attempted, since at least two MS2 data "
f"sets must be provided for\n this procedure, with one of the data sets coming "
f"from a 0 ionization energy run.")
else:
make_ms2_dict(fname_lower, ms_level, ms2_dict,
trimmed_mz_array, long_output_dict,
args.threshold, args.ms_accuracy,
args.num_decimals_ms_accuracy)
gathered_ms2_data = True
# Now that finished reading each file, exit (if only saving csv) or graph
# If '-q' option used to exit without analysis, skip the next section (which skips to the end of the
# program
if not args.quit_after_mzml_to_csv:
if gathered_ms2_data:
for fkey, fkey_dict in ms2_dict.items():
ion_energies = fkey_dict[ION_ENERGIES].keys()
num_ion_energies = len(ion_energies)
if num_ion_energies < 2:
warning(
f"No chemical species matching will be attempted for files designated {fkey}.\n "
f"For this functionality, at least two MS2 data sets must be provided, one of them "
f"from a 0 ionization energy run.\n Note that the program matches sets of MS2 "
f"output by searching for file names that differ only the number after\n 'HCD' "
f"(case insensitive), which is read as the ionization energy."
)
elif 0 not in ion_energies:
warning(
f"Did not find 0 ionization energy output for the set of files designated {fkey}.\n "
f"This output is used to identify the parent. Contact the developers for "
f"more options.")
else:
print(
f"\nNow analyzing {fkey} files.\nUsing M/Z "
f"{fkey_dict[PARENT_MZ]:.{args.num_decimals_ms_accuracy}f} as the parent peak, as "
f"it is the closest peak in the 0 ionization output to the\n specified precursor ion. "
f"The closest matching molecular formula, {fkey_dict[PARENT_FORMULA]} (with "
f"{fkey_dict[PARENT_MATCH_ERR]:.1f} ppm error),\n will be used as the parent "
f"formula.")
plot_mz_v_intensity(fkey, fkey_dict[ION_MZ_DICT],
args.num_decimals_ms_accuracy,
args.out_dir)
make_dbe_mw_graphs(fkey, fkey_dict[ION_ENERGIES],
args.out_dir)
find_substructure_sets(fkey, fkey_dict, args.threshold,
args.num_decimals_ms_accuracy,
args.out_dir)
return final_str
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(
description='Given a list of Gaussian output files, returns a list with '
'unique conformers, defined by having dihedral angles within the '
'specified tolerance.')
parser.add_argument(
"-e",
"--energy",
help="Sort output by lowest electronic energy (not ZPE corrected)."
"The default is False. This flag is superseded by the '-n'/'--enthalpy'"
"and '-g'/'--gibbs' flags.",
action='store_true')
parser.add_argument(
"-g",
"--gibbs",
help=
"Sort output by lowest Gibbs free energy. If not found, the script will "
"sort output by the lowest electronic energy. The default is False.",
action='store_true')
parser.add_argument(
"-l",
"--list",
help=
"The file location of the list of Gaussian output files. There should "
"be one output file listed per line. The default file name is '{}', "
"located in the base directory where the program as "
"run. This program assumes that all the given files have the same atom "
"order.".format(DEF_LIST_FILE),
default=DEF_LIST_FILE)
parser.add_argument(
"-m",
"--max_diff",
help=
"If a numerical value is provided with this option, the output list "
"will be split between files within or not within this maximum "
"difference, in kcal/mol), from the lowest energy or enthalpy. "
"Additionally, the program will output a file with only the file "
"names of conformations within the cutoff; see the '-o'/'--out_name' "
"option to specify the name of this file.",
default=None)
parser.add_argument(
"-n",
"--enthalpy",
help="Sort output by lowest enthalpy. If no enthalpy is found, it will "
"sort by the lowest electronic energy. The default is False.",
action='store_true')
parser.add_argument(
"-o",
"--out_fname",
help=f"When using the '-m'/'--max_diff' option, a file will be created "
f"with only the names of the files within the specified cutoff, one "
f"per line. This option allows the user to specify the output "
f"file name. By default, the name will be '{DEF_OUT_NAME}'.",
default=DEF_OUT_NAME)
parser.add_argument(
"-t",
"--tol",
help=
"The tolerance, in degrees, for concluding that dihedral angles are "
"equivalent. The default value is {}.".format(DEF_DIH_TOL),
default=DEF_DIH_TOL)
args = None
try:
args = parser.parse_args(argv)
except (KeyError, InvalidDataError, MissingSectionHeaderError,
SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def parse_cmdline(argv):
"""
Returns the parsed argument list and return code.
`argv` is a list of arguments, or `None` for ``sys.argv[1:]``.
"""
if argv is None:
argv = sys.argv[1:]
# initialize the parser object:
parser = argparse.ArgumentParser(
description=
'Creates Gaussian input files from pdb files, given a template input '
'file. The required input file provides the name/location of the '
'template file and a file with a list of pdb files to convert.')
parser.add_argument(
"-c",
"--config",
help=
"Optional: the location of the configuration file. The default file "
"name is '{}', located in the base directory where the program as run. "
"If a config file is not provided, use the command-line options to "
"specify the '{}' (-t) and '{}' (-1) or '{}' (-f). The command lines "
"for the '{}' flag (-r) or only the first entry in the pdb ('{}', -a) "
"may also be specified.".format(DEF_CFG_FILE, GAU_TPL_FILE,
PDB_LIST_FILE, PDB_FILE, REMOVE_H,
NUM),
default=DEF_CFG_FILE,
type=read_cfg)
parser.add_argument("-t",
"--tpl_file",
help="Specifies the '{}'".format(GAU_TPL_FILE),
default=None)
parser.add_argument(
"-l",
"--pdb_list_file",
help="Option to specify a file with a list of pdbs ('{}') to convert "
"(one file per line on the list).".format(PDB_LIST_FILE),
default=None)
parser.add_argument(
"-f",
"--file",
help="Option to specify a pdb file ('{}') to convert.".format(
PDB_FILE),
default=None)
parser.add_argument(
"-n",
"--num",
help=
"Only read if a config file is not provided. This command can be used to "
"specify only using the first '-n'/'--num' set(s) of coordinates in a pdb "
"file to create gausscom file(s). The default is to use all coordinates, "
"making as many input files as there are molecules/conformations in the "
"pdb.",
default=None,
type=int)
parser.add_argument(
"-r",
"--remove_final_h",
help="Option to specify removing the last H atom from the PDB "
"file(s) when creating the gausscom files. The default is "
"False.",
action='store_true')
args = None
try:
args = parser.parse_args(argv)
if args.config[GAU_TPL_FILE] is None:
if args.tpl_file is None:
raise InvalidDataError(
"Could not read config file: {}\n and did not specify a 'tpl_file' "
"('-t' option). A tpl_file is needed to run this "
"script.".format(args.config[CONFIG_NAME]))
else:
args.config[GAU_TPL_FILE] = args.tpl_file
if args.num:
args.config[NUM] = args.num
if args.remove_final_h:
args.config[REMOVE_H] = True
if args.file:
args.config[PDB_FILE] = args.file
if args.pdb_list_file:
args.config[PDB_LIST_FILE] = args.pdb_list_file
except (IOError, KeyError, InvalidDataError, MissingSectionHeaderError,
SystemExit) as e:
if hasattr(e, 'code') and e.code == 0:
return args, GOOD_RET
warning(e)
parser.print_help()
return args, INPUT_ERROR
return args, GOOD_RET
def x_value_warning(data_max_x, default_x_max):
warning(
f"The default maximum x-axis value ({default_x_max}) is less than the maximum x-axis value in the "
f"data ({data_max_x}). Not all data will be shown.")
def plot_select_mz_intensity_v_ret_time(fname, ms_level, mz_list_to_plot,
data_array, num_decimals_ms_accuracy,
num_decimals_ret_time_accuracy,
out_dir):
"""
Plot total intensity versus retention times (combines retention times in this method; calls plotting function)
:param fname: str, name of the file where the data originated
:param ms_level: str, used to distinguish between different MS output of the same input file (no overwriting)
:param data_array: ndarray (n x 3) with M/Z, intensity, and retention times
:param mz_list_to_plot: list, with up to 5 mz values to plot vs time on the same plot
:param num_decimals_ms_accuracy: int, number of decimal points in MS accuracy, for rounding
:param num_decimals_ret_time_accuracy: number of decimal points in retention time accuracy, for rounding
:param out_dir: None or str, provides location where new file should be saved (None for current directory)
:return: ndarray, (m x 2), were m is the number of unique retention times, in first column. Second column is
total intensity for that retention time.
"""
default_x_max = 16.
data_x_max = 0.
x_index = 2
if len(mz_list_to_plot) > 5:
warning(
"Error while attempting to plot select M/Z values versus retention times.\n This "
"method expects at most 5 M/Z values to display on one plot. This plot will not be produced."
)
return
if len(mz_list_to_plot) == 0:
warning(
"Error while attempting to plot select M/Z values versus retention times.\n No "
"M/Z values provided. This plot will not be produced.")
return
if len(mz_list_to_plot) == 1:
title = f"Intensity versus Retention Time for M/Z={mz_list_to_plot[0]}"
else:
title = "Intensity versus Retention Time for Selected M/Z Values"
# At least sometimes, mz_list_to_plot and data_array are not already rounded, so doing so here
mz_list_to_plot = np.around(mz_list_to_plot, num_decimals_ms_accuracy)
data_array[:, 0] = np.around(data_array[:, 0], num_decimals_ms_accuracy)
# wait to check for max retention time (in case it does not apply to chosen mz values, but not intensity, to have
# more consistent y-axis ranges
max_intensity = np.max(data_array[:, 1])
y_max = find_pos_plot_limit(max_intensity)
inten_time_dict = {}
for mz_val in mz_list_to_plot:
sub_data_array = data_array[data_array[:, 0] == mz_val]
if len(sub_data_array) < 1:
warning(
f"No retention time data found for M/Z value {mz_val} from {os.path.relpath(fname)}.\n This "
f"M/Z will be omitted from the plot.")
else:
curve_label = f"{mz_val:.{num_decimals_ms_accuracy}f}"
# make this x, y, so ret_time, intensity
inten_time_dict[curve_label] = np.column_stack(
(sub_data_array[:, x_index], sub_data_array[:, 1]))
sub_array_max_x = np.max(sub_data_array[:, x_index])
if sub_array_max_x > data_x_max:
data_x_max = sub_array_max_x
if data_x_max > default_x_max:
warning(
f"The default maximum x-axis value ({default_x_max}) is less than the maximum x-axis value in the "
f"data ({data_x_max}). Not all data will be shown.")
x_label = "Retention time (min)"
y_label = "Intensity (unscaled)"
suffix = "_int_v_time"
if "_ms" not in fname.lower():
suffix = f"_ms{ms_level}" + suffix
plot_fname = create_out_fname(fname,
suffix=suffix,
ext='png',
base_dir=out_dir)
make_vlines_plot(title,
x_label,
y_label,
inten_time_dict,
plot_fname,
num_decimals_ret_time_accuracy,
default_x_max,
y_max,
loc="upper left")
# Maybe later... would need to re-slice data
# inten_time_dict = defaultdict(lambda: None)
# y_val_dict = defaultdict(lambda: None)
# curve_label = defaultdict(lambda: "")
# mz_counter = 0
# make_fig(plot_fname + "_make_fig",
# x_array=inten_time_dict[0], y1_array=y_val_dict[0], y1_label=curve_label[0], color1=NREL_COLORS[1],
# x2_array=inten_time_dict[1], y2_array=inten_time_dict[1], y2_label=curve_label[1], color2=NREL_COLORS[2],
# x3_array=inten_time_dict[2], y3_array=inten_time_dict[2], y3_label=curve_label[2], color3=NREL_COLORS[3],
# x4_array=inten_time_dict[3], y4_array=inten_time_dict[3], y4_label=curve_label[3], color4=NREL_COLORS[4],
# x5_array=inten_time_dict[4], y5_array=inten_time_dict[4], y5_label=curve_label[4], color5=NREL_COLORS[5],
# x_label=x_label, y_label=y_label, loc=0, title=title)
return inten_time_dict
