def get_parser():
parser = fuc.get_rna_input_parser('Calculate the RMSD in 2D space between 2 projections of '
'coarse-grained RNAs.', nargs=2, rna_type="3d",
enable_logging=True)
parser.add_argument('--directions', nargs=2, type=str,
help="The projection directions: e.g. 1.0,1.0,2.4 2.4,0,1", required=True)
parser.add_argument('--plot', action="store_true",
help="Open a window with a plot of the projections")
return parser
def get_parser():
parser = fuc.get_rna_input_parser('Visualize a 3D structure in pymol.',
'+', '3d')
parser.add_argument('--thin-cylinders', default=None,
help='Make coarse_grain RNA thinner')
parser.add_argument('--virtual-atoms', default=False, action='store_true',
help='Display the virtual atoms')
parser.add_argument('--virtual-residues', default=False,
action='store_true', help='Display the virtual residues as spheres')
parser.add_argument('--only-elements', dest='only_elements', default=None,
help='Display only these elements, separated by commas')
parser.add_argument('--no-loops', action="store_true",
help="Don't display the coarse-grain hairpin loops")
parser.add_argument('--longrange', default=False,
action='store_true', help="Display long-range interactions")
parser.add_argument('--stem-color', default='green',
help='The default stem color in coarse-grain drawings')
parser.add_argument('--multiloop-color', default='red',
help='The default multiloop color in coarse-grain drawings')
parser.add_argument('-x', '--text', default=False,
action='store_true',
help="Add labels indicating the element names to the figure.")
parser.add_argument('--labels', type=str,
help="Add labels to elements. Expects a comma seperated "
"string of element:label, like 'm0:LookHere' to"
" display 'LookHere' at the center of 'm0'.")
parser.add_argument('--encompassing-stems', default=False,
action='store_true',
help=argparse.SUPPRESS) # 'Show the big stems that encompass the colinear ones.')
parser.add_argument('--sidechain-atoms', default=False, action='store_true',
help='Include the sidechain atoms. Automatically enables --virtual-atoms')
parser.add_argument('--basis', default=False, action='store_true',
help=argparse.SUPPRESS) # Display the second basis vector of each element's coordinate system at its origin")
parser.add_argument('--rainbow', default=False, action='store_true',
help='Color virtual atoms (if displayed) depending on the nucleotide position.')
parser.add_argument('--element-colors', default="",
help='Specify a color for certain elements '
'(comma-separated element names or element_name:color)'
'Example: "m1,m2" (makes m1, m2 purple) or '
'"m0:red,m1:green,s0:AA11GG,default:black", '
'where "AA11GG" is a hex value and "default" addresses all other elements.'
' Warning: colors not understood by PYMOL will be interpreted as black.'
)
parser.add_argument('--align', default=False, action='store_true',
help='Align the RNAs (if multiple are provided)')
parser.add_argument('-o', '--output', default=None, help="Create a picture of the scene and exit",
type=str)
parser.add_argument('--batch', default=False, action='store_true',
help='Start pymol in batch mode')
parser.add_argument('--pymol-file', type=str,
help=argparse.SUPPRESS) # Store the PYMOL file under this name. WARNING: Do not use .pml as file ending!!!
return parser
def generateParser():
parser = fuc.get_rna_input_parser("Extract fragments",
nargs="+",
rna_type="pdb",
enable_logging=True)
parser.add_argument(
"--fragment-dir",
type=str,
help=
"A directory, where pdb fragments will be stored. If None is given, they will not be stored."
)
return parser
def get_parser():
parser = fuc.get_rna_input_parser("Compare two RNA 3d structures based on RMSD, ACC"
" or other measures", 2, "3d", enable_logging=True)
output_group = parser.add_argument_group("Controlling output",
description="Control, based on which measure the two "
"structures will be compared")
output_group.add_argument("--acc", help="Compare based on the Adjacency correlation coefficient"
" ACC", action="store_true")
output_group.add_argument(
"--rmsd", help="Compare based on CG-RMSD", action="store_true")
output_group.add_argument(
"--pdb-rmsd", help="Compare based on PDB-RMSD", action="store_true")
return parser
def get_parser():
parser = fuc.get_rna_input_parser("Reconstruct a pdb from a forgi *.coord file produced by ernwin.",
"+", "only_cg", enable_logging=True)
parser.add_argument("--source-pdb-dir", type=str, required=True,
help="A directory where all the pdb files, from which fragments "
"can be extracted, are located.")
parser.add_argument("--source-cg-dir", type=str, required=True,
help="A directory where the cg-files corresponding to the pdb files in "
"source-pdb-dir are located.")
parser.add_argument("--interactive", action="store_true")
parser.add_argument("--server", action="store_true")
parser.add_argument("--reassign-broken",action="store_true")
fbs.update_parser(parser)
return parser
def main():
parser = fuc.get_rna_input_parser(
"Train a classifier for A-Minior interactions.",
nargs="+",
rna_type="only_cg")
parser.add_argument("--fr3d-result",
type=str,
required=True,
help="A file containing the FR3D output")
parser.add_argument("--fr3d-query",
type=str,
help="Add this string describing the FR3D query "
"as a comment to the trainingsdata-out file")
parser.add_argument("--chain-id-mapping-dir",
type=str,
help="If you use PDB-bundles, this directory "
"needs to hold all chain-id-mapping.txt files.")
parser.add_argument("--trainingsdata-out",
type=str,
default="forgi/threedee/data/aminor_geometries.csv",
help="File that will be written for the geometries "
"of interactions and non-interactions.")
parser.add_argument("--model-params-out",
type=str,
default="forgi/threedee/data/aminor_params.json",
help="File that will be written for the "
"model's hyper-parameters.")
parser.add_argument("--test-set",
type=str,
help="':'-separated PDB-ids"
" for the test-set.")
parser.add_argument("--train-set",
type=str,
help="':'-separated PDB-ids for the train-set."
"Note: This is only used for cross-validation."
"The final model will be trained on all the data.")
args = parser.parse_args()
cgs, cg_filenames = fuc.cgs_from_args(args,
rna_type="only_cg",
return_filenames=True)
ftcta.create_geometry_file(args.trainingsdata_out, cgs, cg_filenames,
args.fr3d_result, args.chain_id_mapping_dir,
args.fr3d_query)
hyper_params = ftcta.tune_model(args.trainingsdata_out, args.train_set,
args.test_set)
with open(args.model_params_out, "w") as f:
json.dump(hyper_params, f)
def generateParser():
parser = fuc.get_rna_input_parser("Collect data about a list of rna files and store it as a csv.",
nargs="+", rna_type="any", enable_logging=True)
parser.add_argument(
"--csv", type=str, help="Store dataframe under this filename. (Prints to stdout if not given)")
parser.add_argument("-k", "--keys", type=str, help="Only print the following properties. "
"(A comma-seperated list of column headers, e.g. rog_vres")
parser.add_argument(
"--angles", type=str, help="Store the angles between the given pairs of elements. Comma-seperated element tuples, seperated by colons. (e.g.: 's0,s1:s1,s2')")
parser.add_argument("--distances", type=str,
help="Store the distances between the given nucleotides. Comma-seperated nucleotide tuples, seperated by colons. (e.g.: '1,20:2,19')")
parser.add_argument("--per-ml", action="store_true",
help="Describe junction segments instead of the whole cg (one entry per segment)")
parser.add_argument(
"--mode", type=str, help="For use with --csv. Either 'a' for append or 'o' for overwrite. Default: Abort if file exists.")
return parser
def get_parser():
parser = fuc.get_rna_input_parser(
'Calculate the RMSD in 2D space between 2 projections of '
'coarse-grained RNAs.',
nargs=2,
rna_type="3d",
enable_logging=True)
parser.add_argument(
'--directions',
nargs=2,
type=str,
help="The projection directions: e.g. 1.0,1.0,2.4 2.4,0,1",
required=True)
parser.add_argument('--plot',
action="store_true",
help="Open a window with a plot of the projections")
return parser
def generateParser():
parser = fuc.get_rna_input_parser(
"Collect data about a list of rna files and store it as a csv.",
nargs="+",
rna_type="any",
enable_logging=True)
parser.add_argument(
"--csv",
type=str,
help=
"Store dataframe under this filename. (Prints to stdout if not given)")
parser.add_argument(
"-k",
"--keys",
type=str,
help="Only print the following properties. "
"(A comma-seperated list of column headers, e.g. rog_vres")
parser.add_argument(
"--angles",
type=str,
help=
"Store the angles between the given pairs of elements. Comma-seperated element tuples, seperated by colons. (e.g.: 's0,s1:s1,s2')"
)
parser.add_argument(
"--distances",
type=str,
help=
"Store the distances between the given nucleotides. Comma-seperated nucleotide tuples, seperated by colons. (e.g.: '1,20:2,19')"
)
parser.add_argument(
"--per-ml",
action="store_true",
help=
"Describe junction segments instead of the whole cg (one entry per segment)"
)
parser.add_argument(
"--mode",
type=str,
help=
"For use with --csv. Either 'a' for append or 'o' for overwrite. Default: Abort if file exists."
)
return parser
def get_parser():
parser = fuc.get_rna_input_parser(
"Compare two RNA 3d structures based on RMSD, ACC"
" or other measures",
2,
"3d",
enable_logging=True)
output_group = parser.add_argument_group(
"Controlling output",
description="Control, based on which measure the two "
"structures will be compared")
output_group.add_argument(
"--acc",
help="Compare based on the Adjacency correlation coefficient"
" ACC",
action="store_true")
output_group.add_argument("--rmsd",
help="Compare based on CG-RMSD",
action="store_true")
output_group.add_argument("--pdb-rmsd",
help="Compare based on PDB-RMSD",
action="store_true")
return parser
def main():
parser = fuc.get_rna_input_parser("Train a classifier for A-Minior interactions.",
nargs="+", rna_type="only_cg")
parser.add_argument("--fr3d-result", type=str, required=True,
help="A file containing the FR3D output")
parser.add_argument("--fr3d-query", type=str,
help="Add this string describing the FR3D query "
"as a comment to the trainingsdata-out file")
parser.add_argument("--chain-id-mapping-dir", type=str,
help="If you use PDB-bundles, this directory "
"needs to hold all chain-id-mapping.txt files.")
parser.add_argument("--trainingsdata-out", type=str,
default="forgi/threedee/data/aminor_geometries.csv",
help="File that will be written for the geometries "
"of interactions and non-interactions.")
parser.add_argument("--model-params-out", type=str,
default="forgi/threedee/data/aminor_params.json",
help="File that will be written for the "
"model's hyper-parameters.")
parser.add_argument("--test-set", type=str, help="':'-separated PDB-ids"
" for the test-set.")
parser.add_argument("--train-set", type=str,
help="':'-separated PDB-ids for the train-set."
"Note: This is only used for cross-validation."
"The final model will be trained on all the data.")
args = parser.parse_args()
cgs, cg_filenames = fuc.cgs_from_args(args, rna_type="only_cg",
return_filenames=True)
ftcta.create_geometry_file(args.trainingsdata_out, cgs, cg_filenames,
args.fr3d_result, args.chain_id_mapping_dir,
args.fr3d_query)
hyper_params = ftcta.tune_model(
args.trainingsdata_out, args.train_set, args.test_set)
with open(args.model_params_out, "w") as f:
json.dump(hyper_params, f)
def main():
parser = fuc.get_rna_input_parser(
"Find pseudoknots in RNA structures, "
"classify them into shapes and analyze "
"their 3D architecturre.",
"+",
parser_kwargs={"conflict_handler": "resolve"})
parser.add_argument("--pseudoknots",
action="store_true",
help=argparse.SUPPRESS)
parser.add_argument("--outfile-mode",
choices=["w", "a"],
default='w',
help="Overwrite ('w') or append ('a') to output file")
parser.add_argument("--minlength",
type=int,
help="Minimum length of each stem. "
"Stems with fewer base-pairs are treated as unpaired.",
default=2)
args = parser.parse_args()
args.pseudoknots = True
rnas, filenames = fuc.cgs_from_args(args,
rna_type="any",
return_filenames=True,
skip_errors=True)
#variables for statistics
unfold = 0
without_pk = 0
with_pk = 0
pseudoknot_dataset = []
pseudoknot_dataset_extended = defaultdict(list)
for pos, rna in enumerate(rnas):
try:
without_pk, with_pk, unfold, pseudoknots = identification_pseudoknot\
(rna, without_pk, with_pk, unfold,args.minlength)
#count types of pseudoknots
total_pk_g1 = len(pseudoknots)
pk_sortclasses = {}
other = 0
other_pk = []
pk_classes, other = classify_pseudoknots(pseudoknots)
print("pk_classes:")
for key, pks in sorted(pk_classes.items()):
print("{:<17s} {}\t{}".format(key, len(pks),
", ".join(map(str, pks))))
print("other:" + "\t" + ", ".join(map(str, other)))
filename = str(filenames[pos]).split("/")[-1]
entry = {}
for key, pks in pk_classes.items():
entry[key] = len(pks)
entry["other"] = len(other)
entry["PK_other_structures"] = ",".join(map(str, other))
entry["filename"] = filename
entry["rnaname"] = rna.name
print(filename)
pseudoknot_dataset.append(entry)
pk_id = 0
for key, pks in pk_classes.items():
for pk in pks:
pk_id += 1
extend_pk_description(pseudoknot_dataset_extended,
filename, key, rna, pk, pk_id)
for pk in other:
pk_id += 1
extend_pk_description(pseudoknot_dataset_extended, filename,
"other", rna, pk, pk_id)
except GraphIntegrityError:
log.exception("Ignoring RNA %s; GraphIntegrityError", rna.name)
except GraphConstructionError:
log.exception("Ignoring RNA %s; GraphConstructionError", rna.name)
except Exception:
log.error("Error processing %s", rna.name)
raise
df1 = pandas.DataFrame(pseudoknot_dataset)
df1.to_csv("pseudoknot_identification_genus2.csv",
mode=args.outfile_mode,
header=args.outfile_mode != "a",
sep="\t")
df2 = pandas.DataFrame(pseudoknot_dataset_extended)
df2.to_csv("pseudoknot_identification_extended_genus2.csv",
mode=args.outfile_mode,
header=args.outfile_mode != "a",
sep="\t")
print("Structures with Pseudoknots: {}".format(with_pk))
print("Structures without Pseudoknots: {}".format(without_pk))
print("Structures unfold: {}".format(unfold))
import fess.builder.monitor as fbm
import fess.builder.move as fbmov
import fess.builder._other_movers
import fess.builder.replicaExchange as fbr
import fess.builder.builder as fbb
import fess.builder.models as fbmodel
import fess.builder.sampling as fbs
from fess.utils import get_version_string
import logging
log = logging.getLogger("ernwin.__main__")
parser = fuc.get_rna_input_parser(
"ERNWIN: Coarse-grained sampling of RNA 3D structures.",
nargs=1,
rna_type="cg",
parser_kwargs={"formatter_class": argparse.RawTextHelpFormatter})
parser.add_argument(
'--seed',
action='store',
help=
"Seed for the random number generator. It is taken module 2**32 to work with numpy.",
type=int)
parser.add_argument('-i',
'--iterations',
action='store',
default=10000,
help='Number of structures to generate',
type=int)
parser.add_argument('--replica-exchange', type=int, help="Experimental")
"bpseq":
OutFiletype(fgb.BulgeGraph.to_bpseq_string, lambda x: ".bpseq", "cg"),
"fasta":
OutFiletype(fgb.BulgeGraph.to_fasta_string, lambda x: ".fa", "cg"),
"dotbracket":
OutFiletype(fgb.BulgeGraph.to_dotbracket_string, lambda x: ".dotbracket",
"any"),
"neato":
OutFiletype(fgb.BulgeGraph.to_neato_string, lambda x: ".neato", "any"),
"element_string":
OutFiletype(bg_to_elem_string, lambda x: ".element_string", "any"),
"pdb":
OutFiletype(to_pdb, lambda x: ".pdb", "3d"),
}
parser = fuc.get_rna_input_parser(
"Convert RNA files between different file formats.", "+")
parser.add_argument("-T",
"--target-type",
default="forgi",
choices=FILETYPES.keys(),
type=str,
help="The target file-type to convert into.")
parser.add_argument(
"--to-file",
action="store_true",
help="Store the converted RNA in files instead of printing them to stdout. "
"The file-name will be the RNA's name (if present), otherwise 'rna001' etc."
)
parser.add_argument(
"--filename",
type=str,
def get_parser():
"""
Here all commandline & help-messages arguments are defined.
:returns: an instance of argparse.ArgumentParser
"""
parser = fuc.get_rna_input_parser(
"Generate target distributions for ernwin", nargs="+")
### Options ###
# Options to modify general behavior
parser.add_argument(
'--plot-only',
action="store_true",
help='Do not generate any files, only plot results from existing files'
)
parser.add_argument(
'--use-subgraphs',
type=int,
help=
'Use subgraphs for the target distribution. Default: Use enough subgraphs to generate a total of 10000 graphs.'
)
# Files that will be generated
parser.add_argument(
'--rog-target-file',
help='Filename where the ROG target distribution will be stored',
type=str)
parser.add_argument(
'--ame-target-file',
help='Filename where the AMinor target distribution will be stored',
type=str)
parser.add_argument(
'--sld-target-file',
help=
'Filename where the Shortest loop distance target distribution will be stored',
type=str)
parser.add_argument(
'--ame-orientation-outfile',
default="stats/test_aminor_orientation_1S72.txt",
help='Filename where the AMinor orientations will be stored',
type=str)
parser.add_argument(
'--chain-id-mapping-dir',
help=
'Directory name where chain-id-mappings for pdb bundles are located.',
type=str)
# Files that are required
parser.add_argument('--fr3d-result-file',
default="fess/stats/AMinor_FR3D_hits.txt",
help='Filename with the output of FR3D',
type=str)
#Additional info
parser.add_argument(
'--fr3d-query-string',
default=fr3d_query_string,
help='FR3D query information that will be added to the file generated.',
type=str)
#parser.add_argument('--ame-pdb-id-file', help='For the AMinor energy, only consider pdb ids from this file', type=str)
parser.add_argument('--precalculated-ame-orient',
default=False,
action="store_true")
return parser
def get_parser():
parser = fuc.get_rna_input_parser("Create stats",
nargs='+',
rna_type="only_cg")
return parser
continue
shortened.add(to_shorten)
# find the stems which are connected to this multiloop
# and pick a random one
db = list(bg.to_dotbracket_string())
# get the side of the stem which is connected to the
# multiloop
(s1b, s1e) = bg.get_sides(to_shorten, m)
# print to_shorten, s1b, "(", bg.defines[to_shorten], ")"
# the nucleotides that need to be changed
to_change = bg.get_side_nucleotides(to_shorten, s1b)
# print bg.defines[to_shorten], to_change
db[to_change[0] - 1] = '.'
db[to_change[1] - 1] = '.'
print("".join(db))
parser = fuc.get_rna_input_parser(
"Add (default) or remove a basepair from a random multiloop in the file and "
"print out the resulting structure.",
nargs=1,
rna_type="any",
enable_logging=True)
args = parser.parse_args()
if __name__ == '__main__':
main(args)
# The C1'->B1 and B1->B2 vectors define the plane of the base
# The O4'->C1'->B1->B2 sequence defines the torsion
# angle chi
if aname == ftup.chi_torsion_atoms[resname][-2]:
aname = 'B1'
elif aname == ftup.chi_torsion_atoms[resname][-1]:
aname = 'B2'
elif aname in scatoms:
aname = resname + "." + aname
avec = a.get_vector().get_array()
atom_pos = ftuv.change_basis(avec - origin, basis,
ftuv.standard_basis)
identifier = "%s %s %d %d %s" % (d[0], " ".join(
map(str,
cg.get_node_dimensions(d))), conn_type, i, aname)
poss[identifier] += [atom_pos]
sources[identifier] += [d]
print("{}:{}".format(identifier,
",".join(map(str, atom_pos))))
parser = fuc.get_rna_input_parser(
"Generate a list of all atom positions found in the pdb files",
nargs="+",
rna_type="pdb",
enable_logging=True)
if __name__ == '__main__':
main(parser)
def main():
parser = fuc.get_rna_input_parser("Find pseudoknots in RNA structures, "
"classify them into shapes and analyze "
"their 3D architecturre.", "+",
parser_kwargs={"conflict_handler":"resolve"})
parser.add_argument("--pseudoknots", action="store_true", help=argparse.SUPPRESS)
parser.add_argument("--outfile-mode", choices=["w","a"], default='w', help="Overwrite ('w') or append ('a') to output file")
parser.add_argument("--minlength", type= int, help= "Minimum length of each stem. "
"Stems with fewer base-pairs are treated as unpaired.",
default = 2)
args = parser.parse_args()
args.pseudoknots=True
rnas, filenames = fuc.cgs_from_args(args, rna_type="any",return_filenames = True, skip_errors=True)
#variables for statistics
unfold = 0
without_pk = 0
with_pk = 0
pseudoknot_dataset = []
pseudoknot_dataset_extended = defaultdict(list)
for pos, rna in enumerate(rnas):
try:
without_pk, with_pk, unfold, pseudoknots = identification_pseudoknot\
(rna, without_pk, with_pk, unfold,args.minlength)
#count types of pseudoknots
total_pk_g1 = len(pseudoknots)
pk_sortclasses = {}
other = 0
other_pk = []
pk_classes, other = classify_pseudoknots(pseudoknots)
print("pk_classes:")
for key, pks in sorted(pk_classes.items()):
print("{:<17s} {}\t{}".format(key, len(pks), ", ".join(map(str, pks))))
print("other:"+"\t"+", ".join(map(str,other)))
filename = str(filenames[pos]).split("/")[-1]
entry={}
for key, pks in pk_classes.items():
entry[key] = len(pks)
entry["other"] = len(other)
entry["PK_other_structures"] = ",".join(map(str, other))
entry["filename"] = filename
entry["rnaname"] = rna.name
print(filename)
pseudoknot_dataset.append(entry)
pk_id = 0
for key, pks in pk_classes.items():
for pk in pks:
pk_id+=1
extend_pk_description(pseudoknot_dataset_extended, filename,
key, rna, pk, pk_id)
for pk in other:
pk_id+=1
extend_pk_description(pseudoknot_dataset_extended, filename,
"other", rna, pk, pk_id)
except GraphIntegrityError:
log.exception("Ignoring RNA %s; GraphIntegrityError", rna.name)
except GraphConstructionError:
log.exception("Ignoring RNA %s; GraphConstructionError", rna.name)
except Exception:
log.error("Error processing %s", rna.name)
raise
df1 = pandas.DataFrame(pseudoknot_dataset)
df1.to_csv("pseudoknot_identification_genus2.csv", mode=args.outfile_mode, header=args.outfile_mode!="a", sep="\t")
df2 = pandas.DataFrame(pseudoknot_dataset_extended)
df2.to_csv("pseudoknot_identification_extended_genus2.csv", mode=args.outfile_mode, header=args.outfile_mode!="a", sep="\t")
print("Structures with Pseudoknots: {}".format(with_pk))
print("Structures without Pseudoknots: {}".format(without_pk))
print("Structures unfold: {}".format(unfold))
def get_parser():
parser = fuc.get_rna_input_parser('Visualize a 3D structure in pymol.',
'+', '3d')
parser.add_argument('--thin-cylinders',
default=None,
help='Make coarse_grain RNA thinner')
parser.add_argument('--virtual-atoms',
default=False,
action='store_true',
help='Display the virtual atoms')
parser.add_argument('--virtual-residues',
default=False,
action='store_true',
help='Display the virtual residues as spheres')
parser.add_argument(
'--only-elements',
dest='only_elements',
default=None,
help='Display only these elements, separated by commas')
parser.add_argument('--no-loops',
action="store_true",
help="Don't display the coarse-grain hairpin loops")
parser.add_argument('--longrange',
default=False,
action='store_true',
help="Display long-range interactions")
parser.add_argument('--stem-color',
default='green',
help='The default stem color in coarse-grain drawings')
parser.add_argument(
'--multiloop-color',
default='red',
help='The default multiloop color in coarse-grain drawings')
parser.add_argument(
'-x',
'--text',
default=False,
action='store_true',
help="Add labels indicating the element names to the figure.")
parser.add_argument(
'--labels',
type=str,
help="Add labels to elements. Expects a comma seperated "
"string of element:label, like 'm0:LookHere' to"
" display 'LookHere' at the center of 'm0'.")
parser.add_argument(
'--encompassing-stems',
default=False,
action='store_true',
help=argparse.SUPPRESS
) # 'Show the big stems that encompass the colinear ones.')
parser.add_argument(
'--sidechain-atoms',
default=False,
action='store_true',
help=
'Include the sidechain atoms. Automatically enables --virtual-atoms')
parser.add_argument(
'--basis', default=False, action='store_true', help=argparse.SUPPRESS
) # Display the second basis vector of each element's coordinate system at its origin")
parser.add_argument(
'--rainbow',
default=False,
action='store_true',
help=
'Color virtual atoms (if displayed) depending on the nucleotide position.'
)
parser.add_argument(
'--element-colors',
default="",
help='Specify a color for certain elements '
'(comma-separated element names or element_name:color)'
'Example: "m1,m2" (makes m1, m2 purple) or '
'"m0:red,m1:green,s0:AA11GG,default:black", '
'where "AA11GG" is a hex value and "default" addresses all other elements.'
' Warning: colors not understood by PYMOL will be interpreted as black.'
)
parser.add_argument('--align',
default=False,
action='store_true',
help='Align the RNAs (if multiple are provided)')
parser.add_argument('-o',
'--output',
default=None,
help="Create a picture of the scene and exit",
type=str)
parser.add_argument('--batch',
default=False,
action='store_true',
help='Start pymol in batch mode')
parser.add_argument(
'--pymol-file', type=str, help=argparse.SUPPRESS
) # Store the PYMOL file under this name. WARNING: Do not use .pml as file ending!!!
return parser
self.get_extention = extention_fun
self.rna_type = rna_type
FILETYPES = {
"forgi": OutFiletype(to_bg_or_cg_string, cg_or_bg_extention, "any"),
"bpseq": OutFiletype(fgb.BulgeGraph.to_bpseq_string, lambda x: ".bpseq", "cg"),
"fasta": OutFiletype(fgb.BulgeGraph.to_fasta_string, lambda x: ".fa", "cg"),
"dotbracket": OutFiletype(fgb.BulgeGraph.to_dotbracket_string, lambda x: ".dotbracket", "any"),
"neato": OutFiletype(fgb.BulgeGraph.to_neato_string, lambda x: ".neato", "any"),
"element_string": OutFiletype(bg_to_elem_string, lambda x: ".element_string", "any"),
"pdb": OutFiletype(to_pdb, lambda x: ".pdb", "3d"),
}
parser = fuc.get_rna_input_parser(
"Convert RNA files between different file formats.", "+")
parser.add_argument("-T", "--target-type", default="forgi", choices=FILETYPES.keys(),
type=str, help="The target file-type to convert into.")
parser.add_argument("--to-file", action="store_true",
help="Store the converted RNA in files instead of printing them to stdout. "
"The file-name will be the RNA's name (if present), otherwise 'rna001' etc.")
parser.add_argument("--filename", type=str,
help="If this is present, --to-file will automatically be true."
"A target filename (or path) without extention. "
"If it is a filename, use the given filename instead of the RNA's name. "
"If more than one input-RNA is present, appends automatically a increasing number."
"If it is a directory, create files in this directory.")
parser.add_argument("-f", "--force", action="store_true",
help="Overwrite files, if they already exist. Note: In case of race conditions, "
"files could be overwritten even if this flag is not provided.")
import fess.builder.move as fbmov
import fess.builder._other_movers
import fess.builder.replicaExchange as fbr
import fess.builder.builder as fbb
import fess.builder.models as fbmodel
import fess.builder.sampling as fbs
from fess.utils import get_version_string
import logging
log = logging.getLogger("ernwin.__main__")
parser = fuc.get_rna_input_parser(
"MULTIERNWIN: Coarse-grained sampling of RNA 3D structures from multiple secondary structures.",
nargs='+',
rna_type="cg",
parser_kwargs={
"formatter_class": argparse.RawTextHelpFormatter,
"conflict_handler": "resolve"
})
parser.add_argument(
'--seed',
action='store',
help=
"Seed for the random number generator. It is taken module 2**32 to work with numpy.",
type=int)
parser.add_argument('-i',
'--iterations',
action='store',
default=10000,
help='Number of structures to generate',
type=int)
