Add cif-reader and inital INP-generator
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rasmusvt
parent
d32b40409c
commit
51e2928472
3 changed files with 297 additions and 2 deletions
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@ -6,12 +6,266 @@ import re
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import time
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import datetime
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import warnings
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import json
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from ase import io
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import nafuma.auxillary as aux
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def make_initial_inp(data: dict, options={}):
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required_options = ['filename', 'overwrite', 'include', 'save_results', 'topas_options', 'background', 'capillary', 'start', 'finish', 'exclude']
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default_options = {
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'filename': 'start.inp',
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'overwrite': False,
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'save_results': False,
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'include': [], # Any files that should be included with #include
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'topas_options': {},
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'background': 7,
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'capillary': False,
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'interval': [None, None], # Start and finish values that TOPAS should refine on. Overrides 'start' and 'finish'
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'start': None, # Start value only. Overridden by 'interval' if this is set.
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'finish': None, # Finish value only. Overridden by 'interval' if this is set.
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'exlude': [] # Excluded regions. List of lists.
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}
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options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
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options['topas_options'] = update_topas_options(options=options)
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if not os.path.exists(options['filename']) or options['overwrite']:
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with open(options['filename'], 'w') as fout:
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write_headers(fout=fout, options=options)
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fout.write('\n\'------------------------------------------------------------------------------------------------------------------------------------------\n')
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fout.write('rw_p 0 r_exp 0 r_p 0 r_wp_dash 0 r_p_dash 0 r_exp_dash 0 weighted_Durbin_Watson 0 gof 0')
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fout.write('\n\'------------------------------------------------------------------------------------------------------------------------------------------\n')
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write_xdd(fout=fout, data=data, options=options)
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for str in data['str']:
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fout.write('\n\n')
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write_str(fout=fout, str=str, options=options)
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def write_xdd(fout, data, options):
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import nafuma.xrd as xrd
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basedir = os.path.dirname(xrd.__file__)
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with open (os.path.join(basedir, 'snippets.json'), 'r') as snip:
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snippets = json.load(snip)
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topas_options = options['topas_options']
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# Write initial parameters
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fout.write(f'xdd "{data["xdd"]}"\n')
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fout.write('\t'+snippets['calculation_step'].format(topas_options['convolution_step'])+'\n')
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# Write background
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fout.write('\tbkg @ ')
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for i in range(options['background']):
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fout.write('0 ')
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# Write wavelength and LP-factor
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fout.write('\n\n')
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fout.write('\t'+snippets['wavelength'].format(data['wavelength'])+'\n')
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fout.write('\t'+snippets['lp_factor'].format(topas_options['lp_factor'])+'\n')
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if options['capillary']:
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fout.write('\n')
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for i, line in enumerate(snippets['capillary']):
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if i == 0:
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line.format(topas_options['packing_density'])
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if i == 1:
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line.format(topas_options['capdia'])
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fout.write('\t'+line+'\n')
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fout.write('\n')
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if options['interval'][0] or options['start']:
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options['start'] = options['interval'][0] if options['interval'][0] else options['start']
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fout.write(f'\tstart_X {options["start"]}\n')
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if options['interval'][1] or options['finish']:
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options['finish'] = options['interval'][1] if options['interval'][1] else options['finish']
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fout.write(f'\tfinish_X {options["finish"]}\n')
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if options['exclude']:
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for exclude in options['exclude']:
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fout.write(f'\texclude {exclude[0]} {exclude[1]}\n')
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def write_str(fout, str, options):
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atoms = read_cif(str)
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print(atoms["atoms"]["Fe1"].keys())
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a = float(atoms['_cell_length_a'].split('(')[0])
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b = float(atoms['_cell_length_b'].split('(')[0])
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c = float(atoms['_cell_length_c'].split('(')[0])
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alpha = float(atoms['_cell_angle_alpha'].split('(')[0])
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beta = float(atoms['_cell_angle_beta'].split('(')[0])
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gamma = float(atoms['_cell_angle_gamma'].split('(')[0])
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fout.write('#ifdef start_values\n')
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fout.write(f'local lpa \t{a} \t;:\n')
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fout.write(f'local lpb \t{b} \t;:\n')
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fout.write(f'local lpc \t{c} \t;:\n')
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fout.write(f'local lpal \t{alpha} \t;:\n')
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fout.write(f'local lpbe \t{beta} \t;:\n')
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fout.write(f'local lpga \t{gamma} \t;:\n\n')
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fout.write('#else\n')
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fout.write(f'local lpa \t{a}\n')
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fout.write(f'local lpb \t{b}\n')
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fout.write(f'local lpc \t{c}\n')
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fout.write(f'local lpal \t{alpha}\n')
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fout.write(f'local lpbe \t{beta}\n')
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fout.write(f'local lpga \t{gamma}\n')
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fout.write('#endif\n\n')
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sites = list(atoms['atoms'].keys())
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attrs = {'_atom_site_fract_x': 'x', '_atom_site_fract_y': 'y', '_atom_site_fract_z': 'z', '_atom_site_B_iso_or_equiv': 'beq'}
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for attr in attrs:
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for site in sites:
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if attr in atoms["atoms"][site].keys():
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value = atoms["atoms"][site][attr].split("(")[0]
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value = value if value != '.' else 0.
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fout.write(f'local {attrs[attr]}_{site}\t\t =\t {value} \t ;= \n')
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fout.write('\n')
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fout.write('\n\'------------------------------------------------------------------------------------------------------------------------------------------\n')
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fout.write(atoms['_chemical_name_common'] + f'({atoms["_space_group_name_H-M_alt"]})')
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fout.write('\n\'------------------------------------------------------------------------------------------------------------------------------------------\n')
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fout.write('\tstr\n')
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fout.write(f'\t\tphase_name "{atoms["_chemical_name_common"]} ({atoms["_space_group_name_H-M_alt"]})"\n')
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fout.write(f'\t\tspace_group {atoms["_space_group_IT_number"]}\n')
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fout.write('\t\ta = lpa ;\n')
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fout.write('\t\tb = lpb ;\n')
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fout.write('\t\tc = lpc ;\n')
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fout.write('\t\tal = lpal ;\n')
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fout.write('\t\tbe = lpbe ;\n')
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fout.write('\t\tga = lpga ;\n')
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fout.write('\n')
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fout.write(f'\t\tcell_volume vol_XXXX {atoms["_cell_volume"]}\n')
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for atom in atoms['atoms'].keys():
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atom_label = atom if len(atom) == 3 else atom+' '
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fout.write(f'\t\tsite {atom_label}\t x = x_{atom_label} ;\t y = y_{atom_label} ;\t z = z_{atom_label} ; occ {atoms["atoms"][atom]["_atom_site_occupancy"]}\t beq = beq_{atom_label} \t ;\n')
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fout.write('\n')
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fout.write('\t\tscale @ 0.0')
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fout.write('\t\t r_bragg 1.0')
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def read_cif(path):
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data = {'atoms': {}} # Initialise dictionary
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read = True # Initialise read toggle
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# Lists attributes to get out of the .CIF-file. This will correspond to what VESTA writes out, not necessarily what you will find in ICSD
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attrs = ['_chemical_name_common', '_cell', '_space_group_name_H-M_alt', '_space_group_IT_number']
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# Open file
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with open(path, 'r') as cif:
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line = cif.readline()
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# Read until encountering #End
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while read:
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# Break loop if #End is reached
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if not line or line.startswith('#End'):
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read = False
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break
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# Handle loops
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if line.lstrip().startswith('loop_'):
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loop = []
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line = cif.readline()
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# Only handle loops with attributes that starts with _atom. Other loops are incompatible with below code due to slight differences in formatting (e.g. lineshifts)
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while line.lstrip().startswith('_atom'):
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loop.append(line) # add the attributes of the loop to a list (every keywords starting with _atom)
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line = cif.readline() # Read next line
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# If there were any attributes that started with _atom - if this is empty is just means there were other attributes in this loop
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if loop:
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# Read every line after the attribute listing has ended - until it encounters a new attribute, loop or #End tag
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# FIXME WHat a horrible condition statement - need to fix this!
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while line and not line.lstrip().startswith('_') and not line.lstrip().startswith('loop_') and not line.lstrip().startswith('#End') and not line=='\n':
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# Initialise empty dictionary for a given atom if it has not already been created in another loop
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if line.split()[0] not in data['atoms'].keys():
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data["atoms"][line.split()[0]] = {}
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# Add all the attribute / value pairs for the current loop
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for i, attr in enumerate(loop):
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data["atoms"][line.split()[0]][attr[:-1].lstrip()] = line.split()[i]
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# Read new line
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line = cif.readline()
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# If loop list was empty, keep going to the next line
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else:
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line = cif.readline()
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# Handle free-standing attributes
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elif any([line.lstrip().startswith(i) for i in attrs]):
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#line.startswith() or line.startswith('_symmetry_space_group_name') or line.startswith('_symmetry_Int_Tables'):
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#
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#
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attr, *value = line.split()
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value = ' '.join([str(i) for i in value])
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data[attr] = value
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line = cif.readline()
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else:
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line = cif.readline()
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return data
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def update_topas_options(options):
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import nafuma.xrd as xrd
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basedir = os.path.dirname(xrd.__file__)
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with open(os.path.join(basedir, 'topas_default.json'), 'r') as default:
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topas_defaults = json.load(default)
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options['topas_options'] = aux.update_options(options=options['topas_options'], required_options=topas_defaults.keys(), default_options=topas_defaults)
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return options['topas_options']
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def make_big_inp(data: dict, options={}):
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''' Generates a big .INP-file with all filenames found in data["path"]. Uses a template .INP-file (which has to be generated manually from an initial refinement in TOPAS) and appends this to a large .INP-file
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while changing the filenames. '''
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@ -90,6 +344,18 @@ def make_big_inp(data: dict, options={}):
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def write_headers(fout, options):
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# FIXME Could modify this to make sure that certain combinations of options is not written, such as both do_errors and bootstrap_errors.
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headers = [
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"A_matrix_memory_allowed_in_Mbytes",
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"approximate_A",
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"bootstrap_errors",
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"conserve_memory",
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"continue_after_convergence",
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"do_errors",
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"chi2_convergence_criteria",
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"iters",
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"num_runs" ]
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for file in options['include']:
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fout.write(f'#include {file} \n')
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@ -101,7 +367,7 @@ def write_headers(fout, options):
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fout.write('\n')
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for option, value in options['topas_options'].items():
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if value:
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if value and option in headers:
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if isinstance(value, bool):
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fout.write(f'{option} \n')
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else:
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14
nafuma/xrd/snippets.json
Normal file
14
nafuma/xrd/snippets.json
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@ -0,0 +1,14 @@
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{
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"calculation_step": "x_calculation_step = Yobs_dx_at(Xo); convolution_step {}",
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"capillary": [
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"local !packing_density {} min 0.1 max 1.0 'typically 0.2 to 0.5",
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"local !capdia {} 'capillary diameter in mm",
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"local !linab = Get(mixture_MAC) Get(mixture_density_g_on_cm3);: 'in cm-1",
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"local muR = (capdia/20)*linab*packing_density;",
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"Cylindrical_I_Correction(muR)"
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],
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"lp_factor": "LP_Factor({}) 'change the LP correction or lh value if required",
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"wavelength": "lam ymin_on_ymax 0.0001 la 1.0 lo {} lh 0.1",
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"zero_error": "Zero_Error(zero, 0)"
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}
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15
nafuma/xrd/topas_default.json
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15
nafuma/xrd/topas_default.json
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@ -0,0 +1,15 @@
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{
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"A_matrix_memory_allowed_in_Mbytes": null,
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"approximate_A": false,
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"bootstrap_errors": null,
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"capdia": 0.5,
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"chi2_convergence_criteria": 0.001,
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"conserve_memory": false,
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"continue_after_convergence": false,
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"convolution_step": 4,
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"do_errors": false,
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"iters": 100000,
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"lp_factor": 90,
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"num_runs": null,
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"packing_density": 0.5
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}
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