Working on scripts_common
Former-commit-id: 830060579114debef9874748618e0dcf3f14882c
This commit is contained in:
Marek Nečada
parent
e2f9923f31
commit
4dbb8f09b0
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@ -1,4 +1,13 @@
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import argparse
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#import argparse # Do I need it when calling just parser methods?
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import warnings
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__TODOs__ = '''
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- Implement a more user-friendly way to define the lattice base vectors and positions of the particles.
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cf. https://stackoverflow.com/questions/2371436/evaluating-a-mathematical-expression-in-a-string/2371789
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- low priority: allow to perform some more custom operations on T-Matrix, using some kind of parsing from the previous point
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- Autodetect symmetries
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'''
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def make_action_sharedlist(opname, listname):
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class opAction(argparse.Action):
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@ -10,7 +19,7 @@ def make_action_sharedlist(opname, listname):
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def add_argparse_k_output_options(parser):
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parser.add_argument('--kdensity', '--k_density', action='store', type=int, default=33, help='Number of k-points per x-axis segment FIXME DESCRIPTION')
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parser.add_argument('--kdensity', '--k_density', action='store', type=int, nargs='+', default=33, help='Number of k-points per x-axis segment FIXME DESCRIPTION')
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parser.add_argument('--bz_coverage', action='store', type=float, default=1., help='Brillouin zone coverage in relative length (default 1 for whole 1. BZ)')
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parser.add_argument('--bz_edge_width', action='store', type=float, default=0., help='Width of the more densely covered belt along the 1. BZ edge in relative lengths')
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parser.add_argument('--bz_edge_factor', action='store', type=float, default=8., help='Relative density of the belt along the 1. BZ edge w.r.t. k_density (default==8)')
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@ -52,14 +61,137 @@ def add_argparse_common_options(parser):
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parser.add_argument('--frequency_multiplier', action='store', type=float, default=1., help='Multiplies the frequencies in the TMatrix file by a given factor.')
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__TODOs__ = '''
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BIG TODO: Use more efficient way to calculate the interaction sums: perhaps some customized Ewald-type summation?
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Small TODOs:
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- Implement a more user-friendly way to define the lattice base vectors and positions of the particles.
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cf. https://stackoverflow.com/questions/2371436/evaluating-a-mathematical-expression-in-a-string/2371789
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- low priority: allow to perform some more custom operations on T-Matrix, using some kind of parsing from the previous point
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- Autodetect symmetries
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def arg_preprocess_particles(parser, d=None, return_tuple=False):
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'''
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Nanoparticle position and T-matrix path parsing
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returns a dictionary d with keys 'particle_specs' and 'TMatrix_specs'
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parser: ArgumentParser on which add_argparse_unitcell_definitions() and whose
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parse_args() has been called.
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d['TMatrix_specs'] is a list of specs where a spec is a tuple of
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(lMax_override, TMatrix_path, ops).
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lMax_override: int or None
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TMatrix_path: string
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ops: iterable with operations on the T-Matrix to be processed with perform_ops()
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d['particle_specs'] is an iterable of tuples (label, (xpos, ypos), TMatrix_spec_index)
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TMatrix_spec_index is an index of the corresponding element of d['TMatrix_specs']
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If a dictionary d is provided, the result is written into it; if d is None (default),
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a new dictionary is created.
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If return_tuple is true, then a tuple (particle_specs, TMatrix_specs) is returned
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instead of the dictionary d.
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'''
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TMatrix_paths = dict()
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lMax_overrides = dict()
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default_TMatrix_path = None
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default_lMax_override = None
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if not any((arg_type == 'particle') in (arg_type, arg_content) for in pargs.particlespec):
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# no particles positions given: suppose only one per unit cell, in the cell origin
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positions = {None: (0.0)}
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else:
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positions = dict()
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for arg_type, arg_content in pargs.particlespec:
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if arg_type == 'particle' # --particle option
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if 3 <= len(arg_content) <= 4:
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try:
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positions[arg_content[0]] = (float(arg_content[1]), float(arg_content[2]))
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except ValueError as e:
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e.args += ("second and third argument of --particle must be valid floats, given: ", arg_content)
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raise
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if len(arg_content == 4):
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if arg_content[0] in TMatrix_paths:
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % arg_content[0], SyntaxWarning)
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TMatrix_paths[arg_content[0]] = arg_content[3]
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else:
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raise ValueError("--particle expects 3 or 4 arguments, %d given: " % len(arg_content), arg_content)
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elif arg_type == 'TMatrix_path': # --TMatrix option
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if len(arg_content) == 1: # --TMatrix default_path
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if default_TMatrix_path is not None:
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warnings.warn('Default T-matrix path already specified. Overriding with the last value.', SyntaxWarning)
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default_TMatrix_path = arg_content[0]
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elif len(arg_content) > 1: # --TMatrix label [label2 [...]] path
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for label in arg_content[:-1]:
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if label in TMatrix_paths.keys():
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % label, SyntaxWarning)
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TMatrix_paths[label] = arg_content[-1]
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elif arg_type == 'lMax': # --lMax option
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if len(arg_content) == 1: # --lMax default_lmax_override
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if default_lMax_override is not None:
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warnings.warn('Default lMax override value already specified. Overriding the last value.', SyntaxWarning)
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default_lMax_override = int(arg_content[-1])
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else:
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for label in arg_content[:-1]:
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if label in lMax_overrides.keys:
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warnings.warn('lMax override for particle \'%s\' already specified.'
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'overriding with the last value.' % label, SyntaxWarning)
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lMax_overrides[label] = int(arg_content[-1])
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else: assert False, 'unknown option type'
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# Check the info from positions and TMatrix_paths and lMax_overrides
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if not set(TMatrix_paths.keys()) <= set(positions.keys()):
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raise ValueError("T-Matrix path(s) for particle(s) labeled %s was given, but not their positions"
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% str(set(TMatrix_paths.keys()) - set(positions.keys())))
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if not set(lMax_overrides.keys()) <= set(positions.keys()):
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raise ValueError("lMax override(s) for particle(s) labeled %s was given, but not their positions"
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%str(set(lMax_overrides.keys()) - set(positions.keys())))
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if (set(TMatrix_paths.keys()) != set(positions.keys())) and default_TMatrix_path is None:
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raise ValueError("Position(s) of particles(s) labeled %s was given without their T-matrix"
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" and no default T-matrix was specified"
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% str(set(positions.keys()) - set(TMatrix_paths_keys())))
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for path in TMatrix_paths.values():
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if not os.path.exists(path):
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raise ValueError("Cannot access T-matrix file %s. Does it exist?" % path)
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# Assign (pre-parse) the T-matrix operations to individual particles
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ops = dict()
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for label in positions.keys(): ops[label] = list()
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for optype, arg_content in pargs.ops:
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# if, no label given, apply to all, otherwise on the specifield particles
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for label in (positions.keys() if len(arg_content) == 1 else arg_content[:-1]):
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try:
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ops[label].append((optype, arg_content[-1]))
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except KeyError as e:
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e.args += 'Specified operation on undefined particle labeled \'%s\'' % label
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raise
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print(sys.stderr, "ops: ", ops) #DEBUG
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#### Collect all the info about the particles / their T-matrices into one list ####
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# Enumerate and assign all the _different_ T-matrices (without any intelligent group-theory checking, though)
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TMatrix_specs = dict((spec, number)
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for (number, spec) in enumerate(set(
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(lMax_overrides[label] if label in lMax_overrides.keys() else None,
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TMatrix_paths[label],
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tuple(ops[label]))
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for label in positions.keys()
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)))
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# particles_specs contains (label, (xpos, ypos), tmspec_index per element)
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particles_specs = [(label, positions(label),
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TMatrix_specs[(lMax_overrides[label] if label in lMax_overrides.keys() else None,
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TMatrix_paths[label],
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tuple(ops[label]))]
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) for label in positions.keys()]
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# This converts the TMatrix_specs dict to a list of its ex-keys in the ex-value order
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TMatrix_specs = dict((v,k) for (k,v) in TMatrix_specs.items()) # invert dict
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TMatrix_specs = [TMatrix_specs[i] for i in range(len(TMatrix_specs))] # convert to list
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if d is None:
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d = dict()
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d['particle_specs'] = particle_specs
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d['TMatrix_specs'] = TMatrix_specs
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if return_tuple:
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return (particles_specs, TMatrix_specs)
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else:
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return d
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'''
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import argparse, re, random, string
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@ -88,100 +220,6 @@ scp_dest = pargs.scp_to if pargs.scp_to else None
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kdensity = pargs.kdensity
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chunklen = pargs.chunklen
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#### Nanoparticle position and T-matrix path parsing ####
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TMatrix_paths = dict()
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lMax_overrides = dict()
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default_TMatrix_path = None
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default_lMax_override = None
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if not any((arg_type == 'particle') in (arg_type, arg_content) for in pargs.particlespec):
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# no particles positions given: suppose only one per unit cell, in the cell origin
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positions = {None: (0.0)}
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else:
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positions = dict()
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for arg_type, arg_content in pargs.particlespec:
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if arg_type == 'particle' # --particle option
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if 3 <= len(arg_content) <= 4:
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try:
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positions[arg_content[0]] = (float(arg_content[1]), float(arg_content[2]))
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except ValueError as e:
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e.args += ("second and third argument of --particle must be valid floats, given: ", arg_content)
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raise
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if len(arg_content == 4):
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if arg_content[0] in TMatrix_paths:
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % arg_content[0], SyntaxWarning)
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TMatrix_paths[arg_content[0]] = arg_content[3]
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else:
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raise ValueError("--particle expects 3 or 4 arguments, %d given: " % len(arg_content), arg_content)
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elif arg_type == 'TMatrix_path': # --TMatrix option
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if len(arg_content) == 1: # --TMatrix default_path
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if default_TMatrix_path is not None:
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warnings.warn('Default T-matrix path already specified. Overriding with the last value.', SyntaxWarning)
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default_TMatrix_path = arg_content[0]
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elif len(arg_content) > 1: # --TMatrix label [label2 [...]] path
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for label in arg_content[:-1]:
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if label in TMatrix_paths.keys():
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warnings.warn('T-matrix path for particle \'%s\' already specified.'
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'Overriding with the last value.' % label, SyntaxWarning)
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TMatrix_paths[label] = arg_content[-1]
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elif arg_type == 'lMax': # --lMax option
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if len(arg_content) == 1: # --lMax default_lmax_override
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if default_lMax_override is not None:
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warnings.warn('Default lMax override value already specified. Overriding the last value.', SyntaxWarning)
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default_lMax_override = int(arg_content[-1])
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else:
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for label in arg_content[:-1]:
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if label in lMax_overrides.keys:
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warnings.warn('lMax override for particle \'%s\' already specified.'
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'overriding with the last value.' % label, SyntaxWarning)
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lMax_overrides[label] = int(arg_content[-1])
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else: assert False, 'unknown option type'
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# Check the info from positions and TMatrix_paths and lMax_overrides
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if not set(TMatrix_paths.keys()) <= set(positions.keys()):
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raise ValueError("T-Matrix path(s) for particle(s) labeled %s was given, but not their positions"
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% str(set(TMatrix_paths.keys()) - set(positions.keys())))
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if not set(lMax_overrides.keys()) <= set(positions.keys()):
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raise ValueError("lMax override(s) for particle(s) labeled %s was given, but not their positions"
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%str(set(lMax_overrides.keys()) - set(positions.keys())))
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if (set(TMatrix_paths.keys()) != set(positions.keys())) and default_TMatrix_path is None:
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raise ValueError("Position(s) of particles(s) labeled %s was given without their T-matrix"
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" and no default T-matrix was specified"
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% str(set(positions.keys()) - set(TMatrix_paths_keys())))
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for path in TMatrix_paths.values():
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if not os.path.exists(path):
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raise ValueError("Cannot access T-matrix file %s. Does it exist?" % path)
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# Assign (pre-parse) the T-matrix operations to individual particles
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ops = dict()
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for label in positions.keys(): ops[label] = list()
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for optype, arg_content in pargs.ops:
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# if, no label given, apply to all, otherwise on the specifield particles
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for label in (positions.keys() if len(arg_content) == 1 else arg_content[:-1]):
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try:
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ops[label].append((optype, arg_content[-1]))
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except KeyError as e:
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e.args += 'Specified operation on undefined particle labeled \'%s\'' % label
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raise
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print(sys.stderr, "ops: ", ops) #DEBUG
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#### Collect all the info about the particles / their T-matrices into one list ####
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# Enumerate and assign all the _different_ T-matrices (without any intelligent group-theory checking, though)
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TMatrix_specs = dict((spec, number)
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for (number, spec) in enumerate(set(
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(lMax_overrides[label] if label in lMax_overrides.keys() else None,
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TMatrix_paths[label],
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tuple(ops[label]))
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for label in positions.keys()
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)))
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# particles_specs contains (label, (xpos, ypos), tmspec_index per element)
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particles_specs = [(label, positions(label),
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TMatrix_specs[(lMax_overrides[label] if label in lMax_overrides.keys() else None,
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TMatrix_paths[label],
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tuple(ops[label]))]
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) for label in positions.keys()]
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# -----------------finished basic CLI parsing (except for op arguments) ------------------
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from qpms.timetrack import _time_b, _time_e
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btime=_time_b(verbose)
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@ -344,3 +382,4 @@ for chunki in range(chunkn):
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_time_e(btime, verbose)
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#print(time.strftime("%H.%M:%S",time.gmtime(time.time()-begtime)))
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'''
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